File: blk03531.txt
D\ terrapool.io block mined by clean energy \ <svg width="275" height="274" viewBox="0 0 275 274" fill="none" xmlns="http://www.w3.org/2000/svg"> <path d="M8 8H266V266H180V180H94V94H8V8Z" fill="white"/> <path d="M94 180V266H8V180H94Z" fill="white"/> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! FjDOUT:30E78E8BC7024111B3EA6FEE88389EF06FC3050BED6B12169A8D9E198AD9CD33 text/plain;charset=utf-8 "p":"sns","op":"reg","name":"games.unisat" text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":" text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":" text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":" text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":" text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":" EjC=:BNB.BNB:bnb103727tt3jggqluu03r9j9reqtfhjc835ydemk3:295666525:te:0 <?xml version="1.0" encoding="UTF-8"?><svg id="leo" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" viewBox="0 0 1440 1440"><defs><style>.cls-1{fill:url(#linear-gradient);}.cls-2{fill:#fff;}.cls-3{fill:url(#linear-gradient-2);}</style><linearGradient id="linear-gradient" x1="120.22" y1="-2339.79" x2="1319.78" y2="-1333.25" gradientTransform="translate(0 -1476.52) scale(1 -1)" gradientUnits="userSpaceOnUse"><stop offset="0" stop-color="#6aba71"/><stop offset=".25" stop-color="#64c195"/>M <stop offset=".5" stop-color="#8da07c"/><stop offset=".75" stop-color="#b7529a"/><stop offset="1" stop-color="#aa5457"/></linearGradient><linearGradient id="linear-gradient-2" y1="-4592.92" y2="-3586.38" gradientTransform="translate(0 5169.65)" xlink:href="#linear-gradient"/></defs><rect class="cls-1" x="0" y="0" width="1440" height="720"/><rect class="cls-3" x="0" y="720" width="1440" height="720"/><g><path class="cls-2" d="M635.15,842.18c-15.02-5.62-9.99-2.35-.08-12.22,1.48-1.34,1.07-1.67-.63-2.26-3-1.2-6.21-2.02M -9.09-3.46-.15-.1-.24-.44-.15-.57,2.93-3.25,6.15-6.25,9.19-9.4-1.44-1.25-13.05-3.76-11.98-5.3,2.05-3.41,4.76-6.56,6.35-10.19-3.83-1.44-7.74-2.69-11.51-4.24-.48-.22-.69-.69-.46-1.09,1.97-3.36,3.89-6.76,5.63-10.24-4.11-1.26-7.94-3.02-11.83-4.66-.4-.16-.61-.74-.42-1.13,1.82-3.39,2.84-7.27,5.07-10.39-4.49-1.16-8.23-3.93-12.68-5.03-2.05,3.28-3.25,6.84-5.52,10.11-4.34-1.59-8.11-4.15-12.14-6.24-.71,.07-1.06,.36-1.33,.76-1.8,2.65-3.76,5.52-5.74,7.98-.81,.25-1.21-.08-1.59-.34-3.2-2.14-6.37-4.32-9.57-6.46-.7-.47-1.25-1.12-2.M 41-1.27-2.4,2.53-5.18,4.86-7.95,7.2-.8,.91,.82,1.48,1.35,2.02,3.78,2.63,7.52,5.22,11.34,7.82-2.34,3.08-6.55,4.5-9.52,6.82,.16,.72,.78,.98,1.27,1.3,3.23,2.12,6.49,4.21,9.73,6.32,.47,.45,1.88,.89,1.53,1.66-2.94,1.97-6.39,3.17-9.54,4.81-.58,.28-1.2,.5-1.52,1.17,3.6,2.56,7.55,4.81,11.3,7.18,.44,.28,.74,.61,.66,1.18-3.76,1.77-7.94,3.16-11.95,4.53-2.27,.85,1.46,2.14,2.14,2.81,2.46,1.52,4.92,3.01,7.39,4.52,.52,.32,1.12,.58,1.34,1.13-.35,.51-.95,.73-1.6,.9-3.96,1.06-7.91,2.13-11.86,3.21-.55,.23-2.37,.39-1.57,1.28,3.41,2.29M ,6.93,4.48,10.42,6.64,.24,.16,.25,.55,.38,.88-5.73,1.55-11.48,2.56-17.3,3.48-.82,.1-.82,.76-.16,1.15,2.62,1.86,5.37,3.63,8.04,5.4,.73,.53,1.92,.79,1.91,1.82-.67,.69-1.69,.57-2.59,.7-5.83,.82-11.66,1.73-17.53,2.24-.35,.04-.62,.58-.4,.76,2.6,2.24,5.55,4.08,8.29,6.14,.53,.47,2.31,1.32,1.03,1.88-5.02,.87-10.17,.84-15.25,1.28-2.55,.17-5.1,.32-7.65,.49-.23,.02-.53,.16-.62,.31-.09,.15-.04,.45,.1,.58,2.67,2.31,5.51,4.43,8.25,6.65,2.35,1.84-.1,1.62-1.64,1.79-8.34,.5-16.69,.32-25.04,.37-.12,0-.32,.06-.34,.13-.06,.19-.17,.46-M .06,.59,2.77,2.81,5.82,5.37,8.68,8.08,.27,.35,.27,.99-.39,.95-9.13-.12-18.32-.32-27.43-1.1-1.45-.17-2.95-.12-4.42-.17-1.13,.33-.06,1.3,.34,1.82,2.12,2.23,4.26,4.44,6.38,6.67,.33,.55,1.68,1.3,.77,1.84-10.17,.22-20.35-1.58-30.46-2.57-10.54-1.31-9.25-2.16-3.04,5.93,3.64,4.8,4.9,4.96-1.92,4.22-11.27-1.71-22.63-3.16-33.79-5.45,1.97,4.39,4.2,8.66,6.68,12.78,13.36,2.25,26.78,3.86,40.31,5.03,.47,.06,1.59,.05,1.34-.67-2.41-3.54-5.54-6.56-7.91-10.12-.17-.24,.21-.68,.56-.66,12.82,1.05,25.76,2.57,38.62,2.38,.62-.36,.05-.99-.29M -1.36-2.55-2.78-5.35-5.36-7.73-8.27-.01-1.14,1.85-.57,2.61-.67,7.14,.12,14.29,.29,21.43,.34,2.95,.03,5.91-.19,8.87-.3,1.59-.41-1.87-2.59-2.28-3.21-1.97-1.9-4.27-3.52-6.03-5.63-.19-.22,.14-.7,.5-.7,9.3-.18,18.57-.53,27.8-1.55,.5-.39-.06-1.01-.48-1.32-2.38-1.91-4.78-3.8-7.16-5.71-.38-.45-1.8-1.18-1.01-1.75,2.26-.27,4.52-.55,6.8-.73,5.73-.52,11.51-.92,17.14-2.12,.13-.03,.28-.44,.19-.52-2.74-2.46-6.03-4.28-9.02-6.44-.4-.28-.81-.57-.75-1.14,6.4-1.49,13.19-1.87,19.6-3.44,.48-.12,1.45-.3,1.24-.94-2.73-2.29-6.05-3.92-9-5.9M 4-.53-.34-1.1-.64-1.25-1.34,5.84-1.57,11.86-2.67,17.66-4.39,.3-.11,.43-.66,.18-.82-3.05-1.99-6.25-3.73-9.37-5.61-.52-.32-1.13-.61-1.26-1.35,4.99-1.75,10.62-2.81,15.43-5.07,0-.68-.62-.95-1.16-1.25-3.33-2.02-6.98-3.6-10.11-5.89-.5-.86,1.57-1.12,2.12-1.49,3.54-1.53,7.36-2.55,10.73-4.44,.15-.1,.13-.37,.21-.66-4-2.33-8.22-4.43-12.15-6.94,.8-1.24,2.26-1.46,3.5-2.13,2.59-1.17,4.94-2.62,7.24-4.11,.27-.17,.34-.53,.54-.87-16.76-10.36-14.43-4.33-3.91-14.27,.14-.15,.12-.4,.18-.61h0c.78,0,1.52,.05,2.24,.43,3.74,2.09,7.71,3.85,1M 1.37,6.07-2.04,3.28-5.92,5.58-8.72,8.3,.12,.6,.53,.86,.99,1.1,2.4,1.2,4.79,2.41,7.19,3.6,.7,.61,4.5,1.43,3.21,2.61-12.11,10.15-15.26,4.39,1.29,13.36,.07,.61-.27,.9-.73,1.16-3.35,1.82-6.79,3.51-10.47,4.86-.73,.27-1.54,.46-2.03,1.24,3.61,2.34,7.84,4.04,11.7,6.3-.84,1.08-2.12,1.23-3.33,1.72-3.84,1.32-7.68,2.62-11.53,3.91-.52,.18-.91,.42-1.07,1,3.16,1.97,6.57,3.69,9.83,5.53,.43,.24,.85,.49,.95,1.05-5.84,2.31-12.13,3.41-18.16,5.22-.36,.12-.44,.57-.11,.77,3.2,1.99,6.45,3.88,9.64,5.88,.26,.16,.31,.54,.51,.91-6.94,2-14.02,M 3.04-21.07,4.53-1.45,.95,7.55,5.72,8.58,6.73,.41,.27,.85,.54,.85,1.04-.73,.52-1.69,.61-2.59,.76-7.21,1.33-14.53,2.19-21.84,3.16-1.27,.61,.47,1.44,.94,1.96,2.31,1.81,4.62,3.62,6.94,5.43,.39,.3,.74,.6,.67,1.1-2.46,.9-5.29,.79-7.89,1.18-6.91,.86-14,.94-20.88,1.67-.15,.1-.28,.46-.18,.54,2.01,1.88,4.08,3.72,6.07,5.62,.92,.88,2.33,1.49,2.61,2.76-1.19,1.02-2.77,.47-4.17,.65-9.66,.85-19.38,.55-29.07,.77-.37,.01-.72,.46-.53,.69,2.11,2.67,4.62,5.03,6.91,7.55,.4,.43,.74,.9,1.1,1.36,.29,1.2-3.73,.69-4.59,.85-11.59,.03-23.17-.4M 5-34.7-1.3-1.42,.33,.27,1.72,.59,2.38,1.98,2.57,3.98,5.13,5.96,7.69,.28,.37,.54,.75,.18,1.28-13.83-.24-27.71-1.93-41.45-3.58,3.76,4.71,7.87,9.14,12.3,13.24,12.57,1.15,25.24,2.18,37.86,2.03,1.47-.32-1.02-2.51-1.36-3.24-1.75-2.3-3.52-4.59-5.26-6.9-.19-.26-.53-.59-.18-.87,.24-.2,.69-.35,1.02-.33,4.16,.34,8.35,.29,12.52,.3,8.48-.07,16.99,.19,25.46-.35,1.1-.06,1.44-.59,.85-1.28-2.35-2.91-5.28-5.38-7.47-8.41-.17-.24,.18-.68,.54-.7,11.28-.29,22.58-.75,33.77-2.22,.02-.26,.15-.52,.04-.64-2.58-2.81-5.85-4.99-8.32-7.88-.19-.2M 2,.1-.74,.45-.77,1.73-.16,3.48-.24,5.21-.45,7.71-1,15.45-1.72,23.1-3.09,1.94-.52-1.44-2.16-1.93-2.77-2.06-1.56-4.14-3.09-6.18-4.65-.25-.2-.31-.54-.53-.93,8.34-1.8,16.97-2.44,25.09-4.91,.23-.91-.85-1.25-1.42-1.77-2.36-1.6-4.75-3.18-7.1-4.79-.28-.19-.54-.51-.56-.78-.02-.34,.45-.51,.83-.6,3.11-.72,6.23-1.39,9.31-2.15,3.35-.82,6.67-1.72,10-2.57,.54-.14,.95-.39,1.19-.94-3.04-2.29-6.73-3.8-9.78-6.1-.12-.09-.13-.47-.04-.51,6.12-2.39,12.6-3.68,18.69-6.19-2.7-2.47-6.71-3.71-9.9-5.6-.48-.24-.8-.56-.95-1.1,1.55-.72,17.17-5.67M ,15.46-7.13-3.05-1.62-6.2-3.04-9.29-4.56-.59-.28-1.15-.57-1.41-1.13,4.18-2.17,8.43-4.23,12.11-6.93,.61-.47,1.37-.84,2.15-.52,3.24,1.32,6.48,2.64,9.72,3.96,1.14,.41,.88,1.16,0,1.71-3.74,2.6-7.8,4.99-11.48,7.57,.14,.53,.52,.8,1.01,1.02,2.37,1.03,4.72,2.07,7.09,3.1q3.06,1.34,.14,3.02c-4.09,2.48-8.7,4.36-13.11,6.3,.02,.56,.39,.82,.84,1.04,3.28,1.66,6.41,3.14,9.67,4.92-5.7,3.39-12.46,4.62-18.61,7.07-.51,.19-.56,.77-.08,1.05,2.4,1.39,4.82,2.77,7.21,4.16,3.56,1.96,1.64,1.98-.97,2.96-5.99,1.96-12.18,3.49-18.28,5.15-.53,.15M -.59,.68-.11,1.01,2.65,1.84,5.42,3.55,8.11,5.34,.42,.27,.82,.56,.82,1.09-7.49,2.69-15.62,3.86-23.5,5.47-.94,.06-2.58,.57-1.46,1.49,2.25,1.87,4.62,3.61,6.92,5.43,.67,.45,1.94,1.55,.53,1.95-9.47,2.18-19.24,2.95-28.78,4.77-.08,.73,.44,1.1,.87,1.5,2.1,1.97,4.21,3.93,6.3,5.9,.43,.4,.94,.78,.94,1.39-4.35,1.45-9.25,1.37-13.8,2.02-6.82,.66-13.65,1.31-20.51,1.64-1.38,.43,.4,1.73,.78,2.37,2.39,2.58,4.8,5.15,7.21,7.72,2.39,.24,4.77-.3,7.15-.54,9.61-1.11,19.26-1.85,28.66-4.07-.1-.34-.08-.69-.29-.9-2.49-2.78-5.64-4.88-7.87-7.89M ,10.12-2.09,20.27-3.43,30.23-6.09-.04-.29,.01-.55-.12-.69-2.36-2.26-5.06-4.17-7.57-6.27-.38-.31-.7-.64-.63-1.23,8.45-2.08,17.24-4.09,25.53-6.72,.14-.54-.1-.89-.54-1.18-1.06-.98-9.15-5.24-8.2-6.18,5.59-1.88,11.31-3.43,16.84-5.42,1.82-.77,3.85-.95,5.33-2.33-3.16-2.12-6.68-3.65-9.77-5.71,.16-.55,.56-.79,1.08-.97,5.91-2.04,11.67-4.21,17.05-7.29,1.69-1.36-8.81-4.43-9.31-6,5.11-2.92,10.47-5.48,15.19-9.07-3.03-1.62-6.13-2.75-9.25-4.15-.49-.21-.86-.49-1.03-1.02,3.63-2.52,7.35-5.02,11.01-7.52,.94-.64,2.66-1.75,.74-2.35Zm-42M .47-58.69c-.68-.33-1.27-.82-2.29-.78-2.85,2.98-4.95,6.93-8.42,9.26,.27-.87-.97-1.13-1.51-1.6-3.55-2.25-7.45-4.1-10.77-6.65,2.66-2.83,5.22-5.57,7.84-8.35,4.71,1.94,8.14,5.03,12.98,6.72,2.47-2.76,4.1-6.05,6.28-9.02,.41-.46,1.32-.17,1.82,.08,3.59,1.72,7.3,3.15,10.79,5.08-1.24,3.45-3.68,6.43-5.41,9.69-.75,1.17-2.15-.06-3.08-.37-2.75-1.35-5.48-2.72-8.23-4.06Zm7.05,29.95c2.28-3.03,5.81-5.19,8.37-8.07,1.47-1.47-2.15-1.96-2.99-2.6-2.91-1.39-5.87-2.57-8.7-4.15,1.56-3.15,4.27-5.69,6.29-8.62,.77-.99,1.07-1.08,2.23-.59,3.55,1.M 63,7.4,2.9,10.81,4.78,.08,.2,.2,.33,.15,.4-1.98,3.29-4.18,6.53-6.48,9.6,.33,.58,.9,.84,1.51,1.08,2.64,1.07,5.28,2.14,7.92,3.21,.64,.44,2.95,.67,2.37,1.74-2.63,3.2-5.89,5.87-8.99,8.61-.39,0-.71,.07-.91-.01-3.81-1.87-8.04-3.12-11.58-5.38Zm12.71,19.79c-3.34-1.5-6.51-2.91-9.66-4.34-.58-.35-2.41-.9-1.53-1.73,3.44-2.41,6.8-4.88,10-7.49,.39-.32,.92-.44,1.48-.22,3.48,1.38,6.97,2.77,10.44,4.18,.31,.12,.51,.44,.75,.66-2.3,2.3-7.07,6.02-11.48,8.94Zm21.96-18.97h-.01l.15,.1-.14-.1Zm-5.61-15.56s-.02,.05-.03,.08c.04,.01,.07,.03,.M 11,.04l-.08-.12Zm-97.83,137.12s-.03-.03-.04-.05h-.05l.09,.05Zm-139.34,4.54c2.82-.11,5.59,.7,8.38,1.01-3.42-4.7-6.55-9.61-9.43-14.66-2-.36-4-.73-6-1.1-1.37,.07-.36,1.42-.12,2.11,1.77,3.84,4.05,7.48,5.48,11.45-.25,.56-1.16,.4-1.69,.33-20.82-3.76-41.42-8.38-61.82-13.82-.57-.22-1.94-.32-1.83,.48,1.21,4.88,3.87,9.38,4.95,14.29-.26,.8-1.44,.31-2.04,.24-25.47-5.88-50.32-14.04-75.2-21.51-.42,.51-.3,1.04-.17,1.57,1.09,5.08,2.89,10.07,3.57,15.2-.35,.84-2.85-.28-3.59-.38-15.65-4.97-31.18-10.14-46.54-15.65-12.78-4.58-25.44-9.3M 7-37.96-14.4-1.22-.4-2.38-1.13-3.68-1.23-.33-.03-.53,.1-.58,.34,.14,5,1.27,10.07,1.74,15.09,.15,1.17,.47,2.34,.13,3.52-36.59-12.35-72.59-28.99-107.7-44.84-.47-.22-.94-.43-1.41-.63-.76-.32-1.44-.09-1.47,.51-.11,6.57,.04,13.15,.06,19.72-.04,.86,.5,1.4,1.41,1.79,1.18,.51,2.33,1.08,3.51,1.59,35.26,15.11,70.91,29.7,107.36,42.01,.95,.27,.57-1.65,.6-2.21-.63-5.25-1.28-10.5-1.92-15.75-.03-.22,.01-.43,.01-.65,.01-.24,.6-.61,.87-.52,29.14,10.71,58.88,20.61,88.88,29.22,2.19,.49,5.65,2.56,4.23-1.57-.9-3.8-1.82-7.61-2.7-11.42-.M 22-.95-.31-1.91-.41-2.87-.01-.11,.41-.37,.56-.34,24.72,7.12,49.57,14.1,74.81,19.51,.9,.2,1.83,.31,2.76,.4,.17,.02,.57-.26,.55-.38-.06-.64-.16-1.28-.37-1.9-1.29-4.28-3.23-8.45-4.21-12.78,.37-.69,1.52-.21,2.13-.15,20.79,4.75,41.62,9.18,62.79,12.15,1.84,.22,1.11-1.48,.56-2.42-1.58-3.66-3.63-7.14-4.91-10.91-.03-.13,.26-.43,.41-.44ZM54.82,854.86c28.67,14.5,57.92,27.76,87.57,40.35,5.84,2.45,11.71,4.87,17.57,7.29,.82,.34,1.61,.8,2.68,.67-.02-5.95-1.55-11.99-2.05-17.97-.1-.86,.29-1.29,1.43-.84,27.92,11.94,56.3,22.99,85.13,M 32.79,1.11,.38,2.25,.69,3.38,1.01,.3,.08,.5-.06,.57-.33,.24-.87-.08-1.7-.3-2.54-1.12-4.32-2.26-8.64-3.39-12.96-.53-2.25,1.68-.86,2.82-.64,16.76,6.09,33.58,11.7,50.76,16.76,6.94,2.05,13.94,3.99,20.91,5.98,.52,.13,1.42,.39,1.64-.25-1.36-4.53-3.32-8.86-4.91-13.31-1-2.51,1.09-1.49,2.51-1.2,19.89,5.82,40.07,11.14,60.46,15.16,1.86,.07,.34-1.69,.06-2.52-1.56-3.1-3.13-6.19-4.68-9.29-.14-.66-1.4-2.05-.04-2.15,2.11,.37,4.21,.87,6.31,1.31-2.03-4.55-3.84-9.21-5.43-13.95-2.97-.71-5.91-1.66-8.95-2.07-.08-.02-.27,.14-.27,.21,0,.3M 1-.05,.66,.09,.93,1.91,4.13,4.61,8,6.09,12.28-.58,1.06-3.08-.1-4.01-.24-19.91-4.81-39.31-10.56-58.61-16.75-.11,.4-.35,.73-.26,.99,1.6,4.58,3.52,9.05,5.3,13.56,.12,.3,.23,.69-.18,.86-25.16-6.16-49.33-16.38-73.72-25.09-.29-.1-.86,.28-.81,.53,.05,.32,.1,.64,.18,.95,1.26,4.86,2.7,9.66,3.81,14.54,.05,.21,.04,.43,.06,.64,.02,.26-.57,.55-.9,.43-5.25-1.97-10.52-3.87-15.72-5.91-23.94-9.12-47.49-19.26-70.75-29.82-.51-.22-1.18,.08-1.14,.51,.14,1.51,.27,3.01,.47,4.51,.37,4.57,1.65,9.27,1.57,13.79-.9,.32-1.55-.2-2.2-.49-33.99-1M 4.84-67.3-30.94-100.03-48.14-1.09-.42-3.36-2.23-3.28,.09,.18,6.76-.36,13.61,.26,20.32Z"/><path class="cls-2" d="M781.53,856.25c-.79,3.03-1.55,6.08-2.25,9.14-.56-.55-1.06-1.01-1.85-1.21-4.16,5.07-7.25,10.83-11.38,15.96,1.84,2.23,3.62,4.37,5.39,6.51,1.2,1.17,3.53-3.36,4.42-4.18-.55,3.17-1.04,6.34-1.47,9.53-.94-1.26-.85-2.89-2.6-3.67-1.19,.6-1.66,1.64-2.38,2.52-3.41,4.14-6.79,8.28-10.18,12.43-.37,.45-.71,.91-1.55,1.06-1.94-2.28-3.41-4.82-5.22-6.95-.09-.72,.36-1.01,.65-1.36,4.06-4.95,8.12-9.91,12.16-14.87,.71-.87,.66-1M .2-.24-1.98-1.92-1.66-3.88-3.28-5.89-4.63-.92-.07-1.14,.37-1.4,.7-4.06,4.93-7.56,10.03-12.09,14.61-2.92-1.29-4.87-3.71-7.59-5.1-.99,0-1.29,.53-1.68,.93-4.69,4.53-8.83,9.72-13.9,13.81-2.02-1.13-6.33-4.13-7.79-5.41,4.67-4.74,9.24-9.56,13.95-14.25,.37-.34,1-.42,1.45-.15,2.52,1.53,4.88,3.06,7.48,4.5,4.37-4.36,8.24-9.07,11.9-13.93,1.04-1.31,1.39-1.37,2.78-.49,2.22,1.25,4.04,3.05,6.43,3.96,4.21-4.97,7.18-10.29,11.15-15.46,3.08,1.29,4.67,3.42,7.51,5.08,1.76-2.23,2.79-4.68,4.19-7.1Z"/><path class="cls-2" d="M987.18,901.64sM -.05,.02-.08,.03c-.01-.05-.03-.11-.04-.16l.12,.13Z"/><path class="cls-2" d="M990.88,1027.86s.02-.02,.03-.04h.02s-.03,.02-.05,.04Z"/><path class="cls-2" d="M993.11,983.16c.02,13.15-.52,26.28-1.25,39.41-.29,1.63,.15,3.97-.95,5.25-5.87,1.36-11,4.54-16.72,6.33-.84,.04-.74-.95-.73-1.53,.47-4.72,1-9.44,1.46-14.16,.46-10.12,1.71-20.22,1.66-30.33-.01-.27-.61-.5-.92-.35-4.63,2.14-9.07,4.65-13.61,6.96-.45,.23-.92,.46-1.61,.1-.02-13.16,1.68-26.44,.73-39.58-.04-.13-.5-.32-.61-.27-4.23,2.17-8.01,5.09-12.06,7.58-3.1,2.42-1.98-1.M 84-2.06-3.62,.39-9.69,.03-19.39-.33-29.08-.04-.55-.1-1.61-.88-1.51-3.92,2.5-7.37,5.68-11.09,8.47-.53,.51-1.81,1.11-1.92-.1-.26-9.78-.45-19.63-1.32-29.37-.98-.84-1.93,.67-2.67,1.21-2.55,2.37-5.08,4.75-7.63,7.12-1.11,.98-2.31,2.03-2.38-.3-.55-7.1-1.07-14.19-1.64-21.29-.1-1.17-.41-2.33-.64-3.49-.01-.07-.16-.15-.26-.17-1.53-.3-10.2,12.1-11.05,10.37-.53-1.05-.44-2.34-.59-3.49-.29-4.74-.95-9.45-1.6-14.16-.22-1.6-.44-3.2-.71-4.8-.02-.15-.34-.28-.56-.38-.45,.01-.83,.55-1.14,.84-2.26,2.8-4.46,5.65-6.69,8.47-.63,.61-1.04,1.7M 4-1.99,1.89-.17-.01-.36-.22-.5-.37-.33-1.89-.48-3.87-.77-5.78-.6-4.38-1.15-8.79-2.06-13.13-.06-.3-.33-.58-.53-.85-.51-.15-1.01,.71-1.33,.99-1.15,1.1-7.61,12.1-8.44,10.41-1.68-5.62-1.82-11.59-3.31-17.27-.44,.14-.93,.18-1.09,.39-2.6,3.75-5,7.63-7.54,11.42-.27,.41-.63,.68-1.35,.53-.8-4.67-1.87-9.34-2.89-13.98-.11-.5-.23-1.04-.91-1.32-.75,.35-.98,.99-1.33,1.56-2.17,3.59-4.34,7.17-6.53,10.75-.24,.39-.54,.75-1.31,.72-1.62-4.28-1.71-8.93-3.56-13.15-.74-.61-1.59,1.47-2.02,1.94-2.05,3.4-4.06,6.81-6.1,10.2-.28,.46-.51,.99-1.M 24,1.16-.67-.46-.76-1.11-.93-1.74-.58-2.22-1.13-4.43-1.76-6.64-.3-1.04-.73-2.06-1.16-3.08-.03-.08-.6-.15-.68-.08-3.1,3.9-5.11,8.56-7.91,12.68-.4,.48-.43,1.4-1.44,1.25-.69-.1-.67-.85-.85-1.36-.79-2.28-1.58-4.56-2.41-6.84,.78-3.03,1.62-6.05,2.51-9.05,1.38-2.45,2.75-4.9,4.13-7.35,.56-.77,.88-1.9,1.96-1.8,1.4,2.9,2.4,5.92,3.52,8.91,.26,.43,.45,1.18,1.01,1.3,.68-.22,1-1.27,1.42-1.82,2.3-3.97,4.2-8.22,6.71-12.05,.68,.18,.93,.54,1.07,.95,1.27,3.69,2.45,7.27,3.78,10.98,.42-.15,.93-.2,1.05-.39,1.02-1.76,1.97-3.54,2.96-5.31,M 1.37-2.46,2.75-4.91,4.15-7.35,.07-.11,.46-.13,.71-.15,.4,.13,.47,.76,.63,1.1,1.24,3.63,2.42,7.28,3.24,10.99,.12,.54,.27,1.06,.95,1.34,.78-.33,1-.98,1.34-1.55,1.94-3.32,3.86-6.64,5.79-9.96,.28-.48,.51-1,1.19-1.25,.77,.52,.89,1.28,1.07,2,.86,3.48,1.69,6.97,2.57,10.45,.26,1.06,.61,2.09,.94,3.14,.11,.13,.55,.13,.67,.03,2.55-3.21,4.41-6.9,6.7-10.3,.48-.61,.83-1.57,1.77-1.54,1.83,4.94,2.88,10.51,3.86,15.75,.1,.63,.41,1.24,.63,1.85,.03,.07,.18,.15,.28,.15,.77-.09,1.17-1.18,1.69-1.7,1.93-2.72,3.84-5.44,5.77-8.16,1.82-2.62,M 2.11-1.53,2.67,.93,1.16,5.95,2.29,11.91,3.45,17.97,.41-.06,.92-.02,1.07-.19,2.83-3.27,5.4-6.69,8.16-10.01,.19-.23,.73-.5,.92-.43,.3,.11,.56,.48,.62,.77,.37,1.59,.73,3.18,.97,4.78,.92,5.85,1.64,11.77,2.65,17.59,1.1,.21,1.53-.58,2.23-1.2,2.83-2.86,5.34-6.04,8.41-8.66,.24-.18,.58-.09,.65,.16,1.58,5.83,1.86,11.96,2.56,17.94,.25,2.68,.59,5.36,.91,8.04,.02,.18,.24,.35,.38,.52,1.05,.48,2.09-1.34,2.94-1.86,2.42-2.17,4.84-4.34,7.28-6.5,.54-.41,1.15-1.1,1.91-.7,1.43,7.64,1.64,15.68,2.39,23.47,.18,2.26,.34,4.52,.51,6.77,.02,.M 23,.77,.44,.99,.29,2.61-1.64,4.93-3.66,7.43-5.45,1.39-1.02,2.85-1.98,4.28-2.96,1.64-.49,1.28,2.82,1.5,3.81,.73,10.42,.7,20.9,1.24,31.32,.51,.56,1.5-.09,2.04-.36,3.45-2.07,6.88-4.16,10.33-6.23,.73-.27,2.04-1.52,2.64-.56,.93,11.49,.73,23.05,.36,34.56-.08,1.83-.03,3.66,0,5.49,.3,.5,1.27,.27,1.72,0,4.34-1.9,8.49-4.81,13.35-5.09,1.18,.06,.98,1.31,1.07,2.14Z"/><path class="cls-2" d="M1042.99,839.46c.02,.06,.04,.11,.05,.17-.04-.02-.09-.03-.13-.05l.08-.12Z"/><path class="cls-2" d="M1086.37,834.06v.03s-.01-.02-.01-.03h.01Z"M /><path class="cls-2" d="M1211.58,762.83s-.02,.02-.02,.03c0-.01-.01-.01-.01-.01l-.02-.02h.05Z"/><path class="cls-2" d="M1387.34,896.54c-21.73-23.74-44.18-46.89-67.41-69.26-2.45-2.35-1.91,.43-1.72,2.14,.6,5.15,1.21,10.29,1.79,15.43,.01,.14-.27,.31-.45,.43-.57,.08-1.06-.63-1.48-.94-7.95-8.02-16.01-15.96-24.2-23.82-11.09-10.23-21.93-21.41-33.71-30.79-.84,.37-.3,1.34-.27,2.02,.91,4.13,1.85,8.26,2.75,12.4,.09,1.3,1.01,2.98-.15,4.01-16.11-15.98-33.64-30.38-50.93-45.3-.9,.9-.09,2.05,.15,3.05,1.81,5.28,3.62,10.56,5.43,15.8M 5,.36,1.02,.8,2.01,.19,3.03-13.44-11.95-27.68-23.25-41.94-34.3-.57-.44-1.07-.99-1.96-1.07-.4,.52-.16,1.02,.05,1.53,2.45,5.93,4.89,11.86,7.32,17.79,.18,.7,.9,1.8-.4,1.59-8.26-6.29-16.49-12.71-24.92-18.9-3.54-2.65-7.16-5.22-10.76-7.82-.46-.23-1.12-.86-1.64-.64-.09,.06-.2,.2-.17,.27,2.88,6.6,5.87,13.19,8.83,19.75,.19,.41,.32,.8-.09,1.27-10.36-7.23-20.54-14.65-31.16-21.55-.51-.26-1.1-.8-1.71-.74-.31,.11-.35,.3-.23,.54,3.45,6.63,6.65,13.38,9.82,20.15,.07,.15-.11,.38-.21,.56-.69-.02-1.37-.67-1.98-.99-8.62-5.66-17.32-12.1M 1-26.47-16.81-.53,.85,.51,1.85,.78,2.7,2.76,5.49,5.54,10.98,8.3,16.47,.35,.7,.64,1.42,.93,2.13,0,.17-.39,.37-.56,.29-8.3-4.43-16.02-10.64-24.66-14.28-.09,.07-.2,.2-.17,.28,.23,.61,.45,1.23,.75,1.82,2.82,5.59,5.67,11.17,8.5,16.76,.35,1.14,1.8,2.53,.69,3.59-6.83-4.43-14.11-8.67-21.62-12.13-.44,.06-.24,.79-.15,1.07,2.98,6.09,5.98,12.18,8.97,18.27,.41,1.21,1.77,2.6,.81,3.84,.06-.07,.13-.15,.23-.26-.12,.16-.18,.24-.26,.34-5.28-3.64-11.32-6.18-17-9.2-.73-.32-2.74-1.58-2.56-.07,3.84,7.88,7.24,15.96,10.7,24,.17,.4,.27,.81-M .2,1.26-5.95-2.82-11.5-6.44-17.52-9.14-.37-.15-.67,.29-.66,.57,3.52,9.38,7.54,18.58,11,27.99,.16,.41,.34,.82,.01,1.32-5.7-2.04-10.83-5.66-16.56-7.72-.18-.07-.52,.16-.51,.34,1.43,4.73,3.44,9.27,5.03,13.94,7.26,23.26,10.37,18.24-10.94,10.03,3.39,11,7.1,21.95,9.76,33.13-.33,1.27-2.51-.39-3.33-.55-3.35-1.39-6.68-2.79-10.05-4.15-.55-.23-1.12-.56-1.96-.3,2.11,9.71,4.78,19.38,6.91,29.11,.39,1.59,.66,3.19,.96,4.79,.1,.52,.22,1.06-.2,1.56-.86,.17-1.53-.29-2.23-.56-3.29-1.24-6.55-2.52-9.82-3.79-.73-.36-2.53-.92-2.49,.25,1.75M ,11.76,4.39,23.4,5.74,35.22,.11,.84,.4,1.7-.11,2.52-.73,.19-1.31-.11-1.92-.32-3.46-1.2-6.92-2.4-10.39-3.58-.77-.26-2.34-.72-2.28,.61,1.3,13.83,3.16,27.69,3.32,41.58-.61,.18-1.1,.43-1.61,.46-5.29,.36-11.65,1.78-14.02,1.54-.44-.76-.42-1.64-.43-2.5-.41-12.91-1.31-25.85-2.58-38.71-.04-.41-.67-.76-1.17-.64-4.12,.99-8.21,2.04-12.31,3.1-1.79,.22-1.28-2.05-1.59-3.15-1.17-11.2-1.73-22.55-4.14-33.58-4.29,1.61-8.56,3.44-12.66,5.41-.75-.34-.81-.89-.89-1.42-.84-5.89-1.55-11.79-2.57-17.65-.62-3.62-1.27-7.25-1.93-10.87-.15-.62-.4M 1-1.98-1.33-1.61-3.29,2.16-6.3,4.7-9.48,7.02-.64,.4-1.88,1.73-2.49,.78-1.37-8.68-3.4-17.23-5.17-25.82-.18-.48-.5-1.74-1.22-1.35-3.63,2.59-6.47,6.13-10.03,8.81-.9,.23-1.01-1.04-1.24-1.63-.66-2.85-1.25-5.72-1.95-8.57-1.08-4.44-2.24-8.87-3.39-13.29-.13-.42-.92-.56-1.22-.29-3.06,2.95-5.52,6.43-8.61,9.34-.26,.27-.85-.05-.95-.25-1.77-6.4-3.48-12.85-5.43-19.2-.15-.51-.5-.99-.77-1.48-.41-.16-.92,.37-1.18,.61-2.47,3.2-4.7,6.56-7.28,9.67-.12,.14-.47,.16-.84,.27-2.06-6.12-3.53-12.38-6.07-18.34-.7-.15-1.05,.15-1.29,.53-1.71,2.M 69-3.39,5.39-5.1,8.07-1.32,1.78-2.03,3.98-3.14,.51-1.73-4.63-3.03-9.43-5.11-13.92-.06-.12-.43-.17-.66-.2-2.57,3.02-4.28,7.55-6.45,11.04-.23,.41-.57,.69-1.25,.62-2.04-4.76-3.21-9.6-6.22-14.01-1.87,1.04-5.88,13.81-7.5,12.28-1.71-3.4-3.21-6.85-5.2-10.14-.28-.5-.56-.98-1.15-1.3-.72,.39-.92,1.01-1.18,1.61-1.7,3.71-3.23,7.55-5.09,11.18-.71-.03-1.02-.35-1.25-.74-1.93-2.94-3.34-6.25-5.72-8.87-.08-.09-.61-.07-.65,0-.4,.68-.76,1.37-1.07,2.08-1.42,3.25-2.8,6.52-4.22,9.77-.21,.48-.41,1-1.13,1.28-1.15-.79-1.64-2.14-2.46-3.21-2.M 29,5.54-4.44,11.2-6.43,16.95,.5,.89,.65,1.62,1.77,2.05,2.64-4.69,4.65-9.47,7.14-14.19,.42,.29,.83,.45,1,.71,1.75,3.09,3.13,6.42,4.67,9.58,.72,.07,1.04-.22,1.25-.65,2.05-4.09,3.97-8.24,6.11-12.3,.09-.17,.37-.34,.6-.38,.15-.03,.46,.14,.53,.28,1.29,2.49,2.36,5.04,3.27,7.64,.68,1.47,.66,3.19,2.09,4.18,9.54-15.99,5.96-18.88,12.73,.65,1.2,.03,1.44-1.05,2.02-1.84,1.71-3.04,3.39-6.1,5.09-9.15,.27-.49,.53-.99,1.2-1.23,.17,.16,.41,.29,.48,.47,1.94,5.04,3.45,10.17,4.88,15.28,.94,.21,1.21-.47,1.66-1.07,1.87-2.98,3.72-5.98,5.6-M 8.96,2.04-3.13,2.23-.05,2.98,1.82,5.89,19.91,1.24,18.14,12.97,3.9,.09-.07,.61,.03,.63,.11,.92,3.25,1.87,6.5,2.67,9.77,.98,3.56,1.21,7.32,2.62,10.75,.01,.05,.25,.1,.31,.07,3.58-2.74,5.66-7.19,9.17-10.12,.09-.08,.63,0,.66,.08,.34,.93,.69,1.86,.89,2.81,6.62,26.27-.25,24.53,14.78,11.32,.86-.2,1.04,1.08,1.23,1.66,.92,5.55,2.27,11.05,2.84,16.64,.24,2.25,.58,4.5,.9,6.75,.11,.73,.11,1.51,.78,2.11,1.04-.1,1.67-.98,2.46-1.56,2.43-2.02,4.85-4.04,7.29-6.06,.64-.48,1.75-1.72,2.47-.81,2.32,9.98,2.57,20.39,3.99,30.5,.68,1.12,3.24M -1.38,4.13-1.78,2.78-1.88,5.54-3.77,8.34-5.64,.27-.18,.72-.29,1.08-.28,.88,.11,.61,1.39,.76,2.01,.98,10.73,2.14,21.48,2.52,32.25-.08,2.54,1.53,1.26,2.9,.64,3.4-1.89,7.3-3.51,11.27-4.19,.92,.13,.84,1.23,.97,1.92,.71,11.62,1.12,23.25,1.23,34.89,.26,1.41-.83,4.66,1.55,4.31,4.32-.79,8.6-1.85,12.96-2.44,1.95-.23,1.27,1.93,1.45,3.1,.43,14.54-.12,29.1-.29,43.62,.37,.67,1.47,.47,2.14,.48,4.42-.36,8.84-.75,13.26-1.12,.8-.11,1.73-.29,1.67-1.08,.06-1.51,.13-3.01,.13-4.52,0-7.11,.01-14.22-.06-21.33-.1-6.25-.44-12.49-.67-18.74-M .22-2.52,.43-2.63,2.61-1.84,3.19,1.16,6.37,2.33,9.55,3.5,1.01,.27,3.29,1.87,3.53,.22-.58-13.59-2.37-27.08-3.81-40.6-.46-2.24,1.26-1.44,2.54-.93,3.6,1.48,7.18,2.97,10.78,4.44,.46,.19,.97,.32,1.48,.43,.32,.07,.56-.08,.56-.32,.04-3.12-.91-6.18-1.27-9.28-1.07-7.49-2.37-14.96-3.93-22.39-.38-1.81-.7-3.62-1.02-5.43-.09-.51-.24-1.06,.23-1.53,.88-.11,1.55,.3,2.24,.61,3.74,1.71,7.46,3.45,11.2,5.17,.5,.15,1.31,.64,1.78,.36,.07-.31,.18-.63,.13-.93-1.05-5.86-2.46-11.68-3.88-17.49-1.37-5.6-2.82-11.19-4.22-16.78-.04-.24,.03-.76,.M 29-.84,5.44,1.72,10.27,5.18,15.62,7.25,1.15,.39-.24-3.2-.29-3.8-2.74-9.33-5.28-18.69-8.39-27.95-.17-.51-.18-1.06-.24-1.59-.01-.09,.08-.26,.17-.28,.23-.05,.55-.13,.72-.05,4.84,2.27,9.4,5.02,14.12,7.53,2.27,1.22,2.2,.6,1.62-1.55-3.09-9.37-6.22-18.73-9.71-28.01-.12-.62-.51-1.18-.16-1.54,1-.29,1.86,.62,2.72,.98,4.24,2.48,8.48,4.96,12.72,7.44,1,.46,2.03,1.63,3.2,1.11,.01,0,.03-.01,.04-.02,.07-.03,.15-.05,.22-.08-.75-.77-.92-1.75-1.25-2.65-2.95-8.28-6.15-16.5-9.43-24.7-1.77-4.11-.27-2.77,2.43-1.33,5.74,3.41,11.06,7.34,16M .92,10.49,.1-.17,.31-.36,.27-.49-.3-.94-.62-1.87-.99-2.79-3.05-7.81-6.22-15.58-9.64-23.29-.89-2,.02-1.77,1.51-1,6.95,3.73,13.23,8.11,19.7,12.33,.09,.06,.35,.08,.38,.04,.11-.17,.29-.39,.23-.54-2.77-6.89-6.05-13.58-9.01-20.39-.36-.81-.71-1.62-1-2.45-.06-.14,.15-.36,.29-.52,7.54,3.93,14.64,9.19,21.78,13.81,.7,.48,1.3,1.11,2.3,1.26,.5-.78-.27-1.62-.51-2.41-2.72-5.96-5.45-11.92-8.18-17.88-.32-.71-.62-1.42-.91-2.14-.02-.05,.13-.18,.24-.23,.1-.04,.29-.07,.37-.02,1.58,.98,3.22,1.93,4.73,2.98,7.2,5.03,14.36,10.09,21.54,15.1M 4,.32,.27,1.05,.7,1.26,.12-.19-.62-.36-1.25-.62-1.86-2.67-5.98-5.36-11.95-8.03-17.93-.18-.67-.89-1.46-.28-2.07,.59-.11,1.14,.57,1.64,.82,9.41,6.62,18.57,13.44,27.5,20.48,.79,.48,1.43,1.52,2.47,1.37,.07,0,.19-.18,.17-.25-2.37-6.43-5.3-12.64-7.88-18.99-.3-.87-1-1.74-.46-2.63,12.74,8.59,24.15,19.35,36.27,28.33,.14-.13,.35-.33,.31-.46-.2-.74-.44-1.47-.72-2.19-2.1-5.55-4.21-11.11-6.31-16.67-.28-.88-.98-1.87-.22-2.71,14.41,11.52,27.92,24.01,41.94,35.72,.06,.04,.29-.03,.29-.06,.04-.31,.13-.64,.04-.93-1.96-6.15-3.95-12.3-5M .91-18.45-.17-.51-.21-1.05-.28-1.58-.01-.09,.07-.23,.17-.28,.08-.05,.27-.05,.36-.01,2.64,1.65,4.76,4.1,7.18,6.07,12.98,11.53,25.65,23.27,37.94,35.27,1.02,1,2.04,2,3.1,2.97,.1,.09,.45,.04,.67,.01-.76-6.58-3.05-13.34-4.45-19.95-.06-.47-.31-1.4,.54-1.1,20.01,17.79,38.21,37.96,57.04,56.4,.19-.11,.5-.28,.49-.4-.52-5.15-1.07-10.3-1.6-15.45-.1-.96-.14-1.92-.18-2.88,0-.06,.15-.14,.25-.17,.12-.04,.32-.08,.38-.03,.65,.54,1.33,1.05,1.9,1.64,6.11,6.3,12.22,12.59,18.27,18.92,15.71,16.06,30.24,33.23,45.51,49.34,.33,0,.53-.14,.53M -.38-.02-6.88-.04-13.77-.06-20.77Zm-293.02-121.31s-.03-.02-.04-.04l.22-.12-.18,.16Zm59.12-8.88s.08-.13,.12-.13c.11,.02,.21,.07,.31,.1-.11,.15-.25,.16-.43,.03Zm29.62,6.39s-.05,.01-.08,.01c.07-.05,.13-.1,.2-.15l.03,.03c-.05,.03-.1,.07-.15,.11Zm34.32,12.1s.03,0,.05-.01c0,.02,.01,.05,.02,.08-.02-.02-.04-.05-.07-.07Zm45.17,23.4s-.04-.05-.05-.07l.13-.07-.08,.14Z"/><path class="cls-2" d="M803.51,611.25l.14,.16s.06-.07,.08-.1c-.07-.02-.15-.04-.22-.06Zm46.14,45.9l-.08,.08,.13-.06s-.03-.02-.05-.02Zm9.07-167.48c-.71,.24-2.76,M .27-2.09,1.43,1.68,1.9,3.36,3.81,5.08,5.69-.93-2.4-1.93-4.77-2.99-7.12Zm12.57,73.7c-1.21-.84-2.42-1.69-3.6-2.57-.37-1.29,4.54-1.3,5.54-1.69-.06-3.3-.19-6.57-.41-9.81-5.67,.98-11.18,1.95-16.78,3.33,.18,.37,.22,.73,.46,.91,2.93,2.05,5.95,4.04,8.88,6.1,.27,.18,.08,.67-.28,.78-6.94,1.89-13.97,3.22-20.87,5.26,.1,.32,.07,.72,.3,.87,1.36,.88,2.77,1.71,4.18,2.55,1.51,.9,3.02,1.8,4.54,2.7,.44,.26,.81,.55,.87,1.15-5.72,1.77-11.46,3.6-17.18,5.38-.63,.2-1.23,.4-1.48,1.06,16.65,9.5,12.17,3.6-5.14,12.76,.04,1.1,1.41,1.21,2.18,1.M 75,14.27,7.14,8.79,2.3-4.33,12.22-.71,.18-1.16-.04-1.64-.24-3.11-1.29-6.24-2.55-9.35-3.84-.27-.16-1.08-.56-.88-.9,3.76-3.17,8.4-5.28,12.25-8.36,.29-.81-1.21-1.11-1.75-1.48-2.47-1.1-4.96-2.18-7.44-3.26-.49-.21-.89-.48-1.05-1.02,4.52-3.1,9.89-5.27,14.98-7.47,.46-.2,.5-.82,.04-1.06-2.83-1.45-5.69-2.89-8.54-4.31-1.42-.72-1.46-1.21-.07-1.79,1.91-.79,3.83-1.58,5.8-2.28,3.69-1.3,7.46-2.47,11.16-3.76,.56-.2,.71-.73,.28-1-2.43-1.57-5.03-2.9-7.51-4.37-2.93-1.61-1.91-1.8,.61-2.65,5.24-1.71,10.6-3.15,15.98-4.54,4.71-1.14,3.94-M 1.12,.36-3.56-1.96-1.31-3.94-2.6-5.9-3.92-.64-.44-.47-.88,.39-1.15,6.11-1.75,12.33-3.09,18.62-4.28,2-.45,4.22-.5,6.06-1.42-.1-.7-.63-1.05-1.1-1.42-2.32-1.81-4.64-3.61-6.95-5.42-.4-.31-.68-.66-.42-1.22,2.77-.71,5.63-1.26,8.51-1.74-.55-3.34-1.19-6.65-1.92-9.91-4.86,.91-9.69,1.94-14.49,3.03-.88,.2-1.83,.29-2.44,.92,.09,.6,.66,.93,1.13,1.31,2.08,1.68,4.18,3.36,6.26,5.04,.38,.4,1.38,.96,.9,1.54-8.57,2.16-17.29,3.95-25.59,6.81-.06,.54,.29,.85,.71,1.12,1.87,1.23,3.75,2.46,5.61,3.7,.53,.54,3.46,1.79,2.34,2.54-6.91,2.09-13.M 83,4.2-20.57,6.68-1.32,.5-1.45,.96-.4,1.58,2.83,1.65,5.71,3.22,8.52,4.91,1.21,1.09-4.12,2.08-4.83,2.59-4.27,1.81-8.73,3.24-12.75,5.55-.87,.48-.82,.95,.17,1.45,2.81,1.47,5.77,2.72,8.48,4.38,.45,.73-.8,1-1.26,1.33-4.32,2.2-8.44,4.63-12.46,7.17-.53,.3-1.51,1.02-.61,1.45,3.11,1.43,6.4,2.63,9.44,4.2,.11,.58-.37,.82-.73,1.17-3.89,2.67-7.79,5.32-11.68,7.97-.43,.3-.95,.56-1.46,.37-3.31-1.18-6.6-2.41-9.89-3.63-.32-.11-.4-.65-.14-.86,4.03-3.35,8.41-6.35,12.73-9.33-.06-.19-.04-.32-.11-.36-3.11-1.71-6.72-2.7-9.87-4.29-.09-.53,M .2-.86,.64-1.13,2.55-1.6,5.07-3.21,7.65-4.78,2.14-1.3,4.34-2.54,6.52-3.81,.48-.29,.51-.82,.04-1.05-2.9-1.58-6.13-2.63-8.91-4.41-.13-.1-.2-.44-.1-.52,4.54-2.99,9.5-5.27,14.61-7.46,.69-.47,4.19-1.26,3.24-2.27-1.96-1.35-4.11-2.44-6.18-3.63-3.63-2.02-3.44-1.95,.44-3.45,6.34-2.43,12.76-4.61,19.2-6.92-.59-1.65-2.8-2.32-4.08-3.47-1.46-1.2-3.45-2-4.5-3.57,.66-.68,1.6-.84,2.45-1.12,7.58-2.53,15.37-4.63,23.11-6.79,.31-.08,.46-.63,.24-.83-1.99-1.78-4.09-3.42-6.14-5.13-2.31-1.91-2.56-2.19,.79-3.03,7.09-1.79,14.2-3.52,21.41-4.9M 4-1-3.42-2.1-6.8-3.33-10.12-9.56,2.54-19.28,4.56-28.7,7.59-.5,.14-1.33,.56-.87,1.16,2.43,2.28,5.23,4.27,7.42,6.78,.08,.12-.05,.48-.2,.54-1.08,.41-2.18,.83-3.31,1.15-6.97,2-13.78,4.32-20.51,6.8-.61,.36-2.02,.5-1.91,1.35,2.11,2.16,4.95,3.62,7.33,5.5,.4,.28,.79,.56,.79,1.04-.84,.76-2.06,1-3.15,1.39-6.58,2.54-13.23,4.7-19.28,8.26,2.61,2.26,6.1,3.58,8.74,5.63,0,.56-.41,.81-.88,1.03-5.56,2.64-10.86,5.6-16.05,8.69-1.5,.89-1.46,1.25,.2,2.06,2.48,1.28,5.15,2.29,7.51,3.77,.12,.1,.13,.46,0,.56-3.11,2.28-6.58,4.1-9.79,6.22-1.6M 8,1.08-3.28,2.24-4.89,3.38-.38,.26-.78,.56-.52,1.15,2.92,1.19,5.96,2.44,8.88,3.67,.29,.12,.47,.43,.76,.73-4.35,3.35-8.91,6.54-13.01,10.12,.11,.56,.51,.81,1.01,.99,2.46,.88,4.92,1.75,7.37,2.64,.51,.28,1.68,.47,1.54,1.19-3.43,3.32-7.35,6.29-10.56,9.75-.37,.38-.23,.88,.32,1.05,3.6,.92,7.05,2.63,10.74,3.04,3.87-3.26,7.56-7.07,11.78-9.88,2.45,.48,4.73,1.71,7.09,2.53,1.41,.57,3.02,.88,4.17,1.84-.47,1.48-2.23,2.06-3.36,3.08-2.64,2.17-5.56,4.29-7.74,6.85,3.98,1.13,7.74,2.64,11.47,4.06,.02,.7-.42,1.1-.85,1.52-2.72,2.74-5.69M ,5.35-8.17,8.29,.42,.59,1.01,.81,1.64,1.03,3.08,1.08,6.14,2.18,9.21,3.27,.52,.19,.87,.47,.98,1-9.63,13.87-3.17,10.09-18.66,6.56-.78,.31-1.07,.8-1.31,1.3-1.14,2.3-2.26,4.6-3.37,6.91-.63,.97-.63,2.74-2.06,2.87-3.73-.57-7.38-2.01-11.11-2.55-.83,.45-1.03,1.1-1.24,1.7-1.19,3.54-2.38,7.05-3.47,10.61,3.88,.78,7.66,1.89,11.69,2.54,2.04-3.92,2.68-7.84,4.85-11.69,3.96,.48,7.57,2.19,11.4,3.21,.2,.07,.3,.33,.52,.58-1.73,3.55-2.61,7.42-4.57,10.88-.37,.52-1.21,.13-1.83-.04-1.77-.5-3.52-1.03-5.31-1.5-1.27-.34-2.57-.61-3.86-.88-.4M 9-.11-1.15,.2-1.27,.59-1.3,3.93-1.96,8.04-3.58,11.87,3.82,.37,7.48,1.68,11.23,2.47,.3,.07,.91-.17,1-.39,5.11-14.75,.59-12.03,15.49-7.95,.92-.41,1.02-1.1,1.28-1.69,1.51-3.08,2.39-6.5,4.33-9.34-3.9-1.43-7.82-2.85-11.71-4.3-.4-.15-.49-.47-.48-.81,1.44-3.35,3.34-6.56,4.96-9.86,.09-.19,.33-.33,.6-.57,4.03,.8,7.78,2.92,11.75,3.96,.76,.07,1.39-.48,1.71-1.12,1.86-2.62,3.7-5.24,5.55-7.86,.41-.58,.29-.98-.5-1.31-3.45-1.45-6.95-2.83-10.41-4.26-.31-.13-.49-.45-.79-.74,2.77-3.24,6.02-6.08,9.39-8.84,4.15,.94,7.86,3.36,11.84,4.9,M 1.39,.87-.81,1.83-1.35,2.53-2.32,2.18-4.87,4.23-6.99,6.56,.27,.67,.88,.91,1.47,1.17,3.45,1.67,7.1,3,10.4,4.93,.22,.2,.33,.62,.08,.85-2.36,3-4.71,6.01-7.08,9.01,4.48,1.94,8.77,4.16,13.05,6.37,2.44-2.61,4.61-5.48,6.95-8.2,.39-.43,.63-1.09,0-1.42-3.76-2.12-7.62-4.04-11.44-6.07-.88-.63,.26-1.38,.69-1.89,2.08-1.84,4.17-3.67,6.25-5.5,.4-.52,1.76-1.11,1.13-1.81-3.38-2.01-7.06-3.57-10.55-5.37-.48-.23-.88-.48-.93-1.06,2.07-1.76,4.25-3.5,6.8-4.93,.7-.65,4.71-1.9,3.35-2.99-2.95-1.75-6.12-3.14-9.16-4.72-.56-.43-2.46-.83-1.73-1M .75,3.03-1.8,6.25-3.36,9.63-4.71,1.17-.47,2.54-.7,3.53-1.66-3.49-2.55-7.87-4.08-11.54-6.39,.42-.99,1.62-1.07,2.53-1.52,3.96-1.35,7.93-2.69,11.89-4.02,.61-.21,1.24-.38,1.53-.92-3.14-2.56-7.34-3.88-10.63-6.34-.28-.75,.98-.87,1.48-1.13,5.46-1.8,11.19-3.04,16.75-4.6-.1-.56-.44-.87-.89-1.13-1.74-1.02-3.48-2.03-5.21-3.06-1.45-1.08-3.52-1.58-4.39-3.23,5.75-1.63,11.58-2.82,17.51-3.81,.03-1.39,.05-2.78,.05-4.17-.66-.46-1.32-.92-1.97-1.38Zm-32.29,49.17c-3.56,2.65-7.03,5.31-10.62,7.95-3.8-1.41-7.42-3.01-11.13-4.45-.38-.19-.66M -.29-.83-.74,3.39-3.29,7.25-5.89,11.34-8.86,3.97,1.64,7.59,3.24,11.11,4.99,.45,.22,.51,.82,.13,1.11Zm96.17-133.88c-2.04-3.8-4.67-7.26-6.98-10.92-10.81,.85-21.62,1.95-32.36,3.46,1.69,3.63,3.24,7.3,4.67,11,11.46-1.25,22.95-2.21,34.44-2.96,.09-.2,.3-.43,.23-.58Zm95.68-22.56l-.1,.1c.05,.01,.1,.01,.15,.02-.02-.04-.03-.08-.05-.12Zm64.61-6.37l.12,.03v-.12l-.12,.09Zm21.78,65.12c.02,.06,.04,.11,.06,.17l.1-.13s-.11-.03-.16-.04Zm59.93-47.74s.01,.05,.02,.07c.02,0,.03,.01,.05,.01l-.07-.08Zm12.85,54.25s.03,.07,.04,.1l.14-.05c-.0M 6-.02-.12-.04-.18-.05Zm-94.56-71.63l.12,.03v-.12l-.12,.09Zm291.8,93.67c.4-2.35-1.88-2.91-3.6-3.69-35.69-15.37-71.59-30.3-108.62-42.71-.94,.1-.65,1.24-.69,1.89,.36,3.33,.78,6.65,1.15,9.97,.24,2.25,.44,4.5,.65,6.75,.02,.25-.6,.58-.88,.48-30.88-11.42-62.2-21.9-94.01-30.84-1.34-6.02-2.43-12.11-4.07-18.07-26.79-7.31-54.23-12.52-81.61-17.42,.35,4.81,2.6,9.35,3.8,14.01,.47,1.6,.25,2.24-1.61,1.87-22.15-4.02-44.44-7.28-66.87-9.42,1.77,4.14,3.56,8.27,5.32,12.4,.23,.7,.74,1.73-.33,1.95-10.58-.85-21.12-2.2-31.73-2.8-8.07-.49-1M 6.13-1.03-24.21-1.13-.55,0-.94,.48-.73,.9,1.79,3.62,3.87,7.11,5.76,10.67,.53,.98,.19,1.31-1.25,1.3-15.69-.39-31.51-1.39-47.14,.08-.24,.5,0,.89,.25,1.27,1.22,1.8,2.44,3.59,3.67,5.39,.84,1.22,1.72,2.43,2.51,3.68,.15,.23-.03,.59-.07,.96-12.91,.23-25.73,1.08-38.57,2.28,.7,2.19,1.37,4.4,1.99,6.62,.76,1.35,4.91,4.22,1.14,4.19,.91,3.5,1.72,7.02,2.44,10.55,2.61-.22,5.25-.19,7.85-.52,.31-.04,.67-.55,.53-.76-1.75-2.62-4.24-4.71-6.31-7.08-.42-.65-2.21-1.93-.8-2.33,12.32-1.4,24.74-1.17,37.11-1.39,2.97-.05,4.17,.1,1.79-2.76-1.8M 4-2.64-3.88-5.14-5.54-7.88-.16-.26,.12-.72,.44-.75,15.07-.57,30.16,.4,45.2,1.32,1.87-.02,3.08,.26,1.73-2.07-1.8-3.24-3.77-6.42-5.51-9.7-.19-.38,.27-.92,.8-.89,18.82,.58,37.5,3.62,56.16,5.35-1.35-4.81-4.45-8.98-5.8-13.73,.77-.36,1.45-.3,2.11-.21,6.65,.84,13.28,1.74,19.89,2.77,14.54,2.27,28.95,4.99,43.32,7.86,.64,.06,1.77,.45,2.15-.22-.89-4.46-2.86-8.74-4.14-13.12-.27-.84-.85-2.03,.64-1.98,26.85,4.89,53.43,11.33,79.62,18.84,1.34,5.46,2.69,10.94,3.93,16.43,.1,.43,.1,.85-.42,1.27-25.71-7.46-51.51-14.89-77.81-20.26-1.34M ,.02-.59,1.36-.46,2.12,1.38,4.26,3.09,8.45,4.3,12.77-.21,1.11-1.95,.33-2.72,.29-19.96-4.7-40.06-8.69-60.35-11.92-3.23-.4-3.81-.31-2.56,2.31,1.35,2.81,2.66,5.64,3.96,8.46,1.59,3.43,1.16,3.02-2.23,2.65-12.19-1.85-24.33-3.89-36.61-5.07-5.2-.62-10.4-1.22-15.63-1.4-.3-.02-.69,.48-.57,.71,1.99,3.81,4.64,7.25,6.62,11.06,.13,.25-.28,.68-.65,.66-1.61-.08-3.23-.11-4.83-.27-13.65-1.35-27.36-2.32-41.08-2.46-.79-.02-1.22,.55-.82,1.07,1.26,1.65,2.57,3.29,3.82,4.95,1.11,1.47,2.18,2.97,3.25,4.46,.25,.35-.23,.91-.76,.88-12.38-.55-2M 4.79-.36-37.18-.1-.65,.01-1.31,.16-1.94,.32-.76,.52,.33,1.39,.65,1.92,1.98,2.18,4,4.33,5.99,6.5,.28,.48,1.16,1.21,.41,1.66-5.16,.63-10.47,.15-15.67,.67,.54,3.41,.99,6.83,1.36,10.27,7.43-.45,14.89-.15,22.33-.31,.66-.08,2.31,.22,2.05-.85-2.41-3.14-5.63-5.71-7.89-8.92-.04-.15,.18-.48,.34-.5,.78-.12,1.58-.24,2.38-.23,12.37-.11,24.71,.51,37.02,1.35,.29-.53,.08-.92-.19-1.29-1.11-1.47-2.23-2.94-3.37-4.41-1.2-1.55-2.43-3.1-3.61-4.67-.18-.24-.11-.6-.17-1.03,15.47,.27,30.84,2.37,46.18,4.12,1.33-.29,.18-1.46-.15-2.16-1.69-2.6M 9-3.41-5.37-5.1-8.07-.41-.66-1.07-1.25-.93-2.07,1.47-.67,3.12-.05,4.65,.05,16.01,2.23,32.04,4.65,47.87,7.75,.8,.16,3.08,.82,2.72-.55-1.78-3.85-3.77-7.6-5.63-11.42-.2-.53-.79-1.41,.03-1.66,22.09,3.52,43.86,9.05,65.52,14.49-1.73-4.68-3.46-9.36-5.18-14.03-.21-.72-.51-1.29,.21-1.87,26.35,6.19,52.08,14.24,77.75,22.41-1.34-4.08-2.09-8.37-3.19-12.54-.33-1.37-.6-2.75-.86-4.13-.09-.45,.49-.87,1-.74,28.24,8.44,55.74,18.56,83.1,29.23,2.55,.97,5.03,2.09,7.62,2.95,.85,.18,1.03-.38,.99-1.01-.66-5.79-1.6-11.55-2-17.36,.31-1.62,3.M 01,.27,3.99,.42,35.81,13.53,70.89,28.91,105.59,44.71,.31,.11,.87-.17,.9-.44,.32-6.33,.01-12.7,.1-19.05Zm-291.8-93.67l.12,.03v-.12l-.12,.09Zm0,0l.12,.03v-.12l-.12,.09Z"/><path class="cls-2" d="M146.8,783.23h.02s.02-.05,.02-.08c-.01,.02-.02,.05-.04,.08Z"/><path class="cls-2" d="M154.9,843.39l-.06-.03,.07,.08s0-.03-.01-.05Z"/><path class="cls-2" d="M227.51,827.91h-.01v.02c.11,.02,.18,0,.18-.04-.06,.01-.12,.02-.17,.02Z"/><path class="cls-2" d="M481.63,853.07s-.01,.04-.02,.06l.08-.08s-.04,.01-.06,.02Z"/><path class="clsM -2" d="M488.09,758.66h-.05l.1,.06s-.04-.04-.05-.06Z"/><path class="cls-2" d="M641.75,706.89c-3.41-.65-6.41-2.08-9.68-3.05-.29-.1-.94,.12-1.01,.34-1.21,3.82-1.53,7.87-2.41,11.77-.11,.43-.73,.75-1.21,.57-1.94-.74-3.89-1.49-5.81-2.25,2.2,1.49,4.36,3.03,6.47,4.63,.06-1,.61-1.83,1.78-1.39,2.83,.97,5.66,1.97,8.51,2.87,.78,.24,1.47-.33,1.54-1.07,.58-4.14,1.67-8.24,1.87-12.41-.02,0-.03-.01-.05-.01Z"/><g><path class="cls-2" d="M594.11,745.79c-1.15,2.65-2.31,5.3-3.47,7.95-.15,.38-.7,.81-1.1,.73-3.5-1.85-6.57-4.45-9.9-6.6-1.7M 9-1.46-2.28-.75-3.25,.95-1.45,2.31-2.89,4.61-4.34,6.91-.24,.37-.99,.46-1.4,.19-4.08-2.7-7.65-6.13-11.72-8.82-2.78,2.29-4.04,5.35-6.79,7.69-.36,.33-.74,.61-1.51,.62-4.39-3.49-8.48-7.34-12.59-11.19,1.92-3.05,5.06-5.29,7.45-8.03,1.27-1.21,3.18,1.97,4.3,2.61,11.46,9.22,6.81,10.81,15.24-1.66,.74-.28,1.1,.08,1.46,.36,3.64,2.78,7.02,6.07,10.95,8.41,.7-.4,.96-.89,1.2-1.39,.9-1.87,1.81-3.75,2.7-5.62-4.58-2.14-9.33-4-14.25-5.56-.57,.92-.78,1.98-1.79,2.61-.76-.03-1.2-.46-1.64-.86-1.45-1.3-2.89-2.61-4.33-3.94-2.92-.73-5.93-1.3M 4-8.89-1.84-1.37,1.76-2.34,3.85-4.02,5.33-.14,.11-.57,.15-.69,.06-2.59-1.95-4.58-4.52-6.9-6.77-3.67-.27-7.31-.35-10.93-.28-2.32,2.01-3.13,2.52-3.5,2.3-.97-.54-1.66-1.27-2.28-2.03-4.94,.34-9.82,.99-14.62,1.94,2.03,2.36,4.15,4.65,6.11,7.07,.19,.24-.04,.67-.41,.8-3.19,1.2-6.65,1.67-9.92,2.68-.3,.09-.47,.6-.27,.83,1.01,1.15,1.98,2.31,3.04,3.43,2.6,2.74,5.22,5.48,7.89,8.19,2.4,2.43,1.72,2.22-1.31,3.01-2.91,.76-6.06,.96-8.95,1.73-.08,.91,.72,1.38,1.26,2.02,3.83,3.89,8.03,7.47,11.65,11.55,.15,.2,.04,.43-.27,.52-3.97,1.1-8M .16,1.29-12.22,2-.9,.33,.01,1.19,.4,1.58,3.65,3.45,7.32,6.9,10.97,10.35,.37,.51,2.01,1.49,1.21,2.04-17.61,3.35-18.92-2.28-3.95,11.88,.71,.93,4.42,2.89,1.89,3.58-5.07,.41-10.21,.45-15.29,.93-.8,.58,.85,1.55,1.23,2.06,2.88,2.57,5.83,5.06,8.68,7.66,.35,.33,.44,.75,.19,.86-6.34,.88-12.89-.05-19.35-.24,.1,.41,.06,.78,.26,1,2.87,2.89,6.07,5.48,9.08,8.24,.38,.42,1.36,1.12,.55,1.53-6.84,.03-13.71-.72-20.46-1.65-1.21-.11-2.83-.33-1.34,1.24,2.58,2.48,5.18,4.95,7.77,7.44,.51,.49,.97,1.01,1.43,1.53,.06,.07,.02,.23-.04,.32-2.91M ,.52-6.12-.42-9.06-.7-5.57-.78-11.1-1.73-16.65-2.6-.28-.01-.86-.07-.96,.26,.11,.3,.2,.63,.43,.87,2.56,2.64,5.15,5.26,7.71,7.89,.49,.51,.89,1.07,1.32,1.61,.06,.08,.07,.28,.01,.31-.57,.38-1.24,.15-1.85,.04-8.7-1.45-17.33-3.13-25.87-5.11-.89-.1-2.36-.64-3.11-.35-.07,.18-.17,.43-.07,.55,2.56,3.04,5.15,6.06,7.73,9.08,.45,.53,1.06,.99,1.14,1.68-.62,.38-1.25,.16-1.87,.03-9.62-2.06-19.15-4.39-28.53-7.07-2.11-.44-4.01-1.58-6.22-1.32,2.47,4.15,6.23,7.72,8.45,11.81-.18,.13-.44,.33-.6,.3-2.86-.58-5.62-1.34-8.41-2.15,.06,3.7,.2M 9,7.37,.7,11,5.98,1.38,12.41,3.57,18.42,4.23,.08-.16,.2-.39,.12-.51-2.08-2.76-4.19-5.52-6.28-8.28-.63-.83-1.23-1.67-1.79-2.53-.08-.12,.07-.36,.17-.53,.66-.3,1.6,.12,2.31,.2,7.7,1.97,15.47,3.73,23.32,5.24,3.53,.69,7.08,1.28,10.63,1.9,.09,.02,.25-.1,.32-.18,.6-1.22-10.71-11.04-8.43-11.12,9.33,1.43,18.67,3.24,28.09,4.41,1.02,.16,2.08,.36,3.13,.07,.16-.44-.11-.78-.44-1.1-2.3-2.24-4.6-4.48-6.89-6.72-.68-.67-1.32-1.35-1.97-2.04-.18-1.09,2.72-.37,3.4-.38,7.4,1.08,14.88,1.67,22.35,2.35,.86,.08,1.41-.05,1.34-.32-.07-.29-.18M -.63-.42-.84-1.68-1.54-3.41-3.04-5.1-4.56-1.33-1.21-2.65-2.42-3.93-3.67-.19-.19-.16-.53-.2-.81,7.44-.22,14.99,.96,22.45,.67,.23-.12,.68-.41,.43-.7-2.81-2.65-5.94-5-8.87-7.51-1.98-1.68-1.54-2.06,.88-1.98,5.77,.13,11.6,.17,17.35-.34,.68-.52-.37-1.15-.75-1.55-2.63-2.16-5.28-4.3-7.92-6.46-.59-.65-1.86-1.09-1.63-2.1,5.56-.71,11.27-.5,16.79-1.54,.36-.87-.7-1.29-1.21-1.85-2.93-2.39-5.87-4.75-8.79-7.14-.4-.39-1.34-1.09-.69-1.58,4.47-.73,8.97-1.47,13.42-2.27,.79-.14,.94-.7,.34-1.22-4.37-3.85-9.04-7.33-13.22-11.38,.41-.28,.6M 6-.59,1-.66,3.66-.67,7.29-1.45,10.9-2.38,.49-.12,.96-.33,1.17-.89-4.24-4.04-9.02-7.58-13.14-11.74-.21-.22-.03-.68,.32-.79,3.92-.97,7.78-2.69,11.76-3.25,4.08,3.11,11.98,9.75,13.62,11.44-.18,.43-.53,.73-1.05,.91-3.3,1.23-6.64,2.32-9.9,3.64-.64,.56,.37,1.18,.77,1.57,3.63,2.89,7.29,5.75,10.92,8.63,.55,.44,1.33,.75,1.41,1.69-3.97,1.63-8.31,2.75-12.51,4.07,.03,.82,.72,1.22,1.3,1.65,2.85,2.13,5.74,4.24,8.6,6.37,.44,.46,2.13,1.27,1.63,1.93-15.81,5.29-20.78-.96-3.72,11.99,.32,.4,.01,.89-.46,.98-4.1,.62-8.2,1.24-12.36,1.55-.M 59,.16-4.89,.26-4.16,1.09,2.77,2.54,6.03,4.6,8.99,6.94,.59,.48,2.55,1.57,1,2.09-4.3,.27-8.6,.53-12.9,.76-.94,.3-7.96-.49-6.14,1.36,3.07,2.58,6.26,5.06,9.35,7.6,.17,.14,.3,.42,.23,.58-.05,.16-.36,.35-.58,.37-1.47,.11-2.95,.27-4.42,.26-6.06-.05-12.11-.33-18.17-.3-.06,.21-.24,.48-.14,.59,.64,.69,1.3,1.37,2.02,2,2.19,1.91,4.41,3.78,6.59,5.69,.38,.43,1.34,1.07,.63,1.58-7.6,.13-15.33-.64-22.92-1.34-1.33-.14-2.65-.41-3.96-.17-.3,.5,0,.85,.34,1.19,2.83,2.87,6.02,5.44,8.61,8.52-.12,1.32-6.77-.03-8-.05-5.2-.62-10.39-1.24-15.M 58-1.88-2.66-.28-5.29-.85-7.96-1.01-.13,0-.35,.06-.36,.11-.04,.2-.1,.46,.02,.6,2.89,3.25,5.96,6.35,8.73,9.7,.11,.12-.01,.37-.04,.67-11.92-1.4-23.8-3.65-35.49-6.13-.59-.05-1.4-.36-1.94-.06-.09,.17-.24,.42-.15,.54,2.66,3.49,5.4,6.94,8.08,10.42,.1,.22-.11,.75-.46,.7-.81-.08-1.62-.14-2.4-.29-8.03-1.62-16.06-3.28-23.98-5.26,.84,4.02,1.89,7.97,3.14,11.86,11.19,2.31,22.47,5.01,33.86,6.12,.12-.63-.28-1.07-.64-1.51-2.52-3.18-5.2-6.26-7.59-9.53-.07-.21,.25-.71,.57-.66,2.37,.38,4.74,.8,7.12,1.15,6.88,1.01,13.75,2.09,20.66,2.9M 4,3.05,.38,6.1,.91,9.22,.81,.19,0,.39-.2,.54-.34,.23-.4-.38-.79-.6-1.12-2.57-2.62-5.09-5.29-7.6-7.95-.31-.34-.6-.72-.46-1.25,10.48,.79,21.03,2.37,31.61,2.39,.61-.08,1.2-.42,.54-1.12-2.8-2.77-5.88-5.29-8.55-8.16-.1-.14,.01-.39,.08-.57,8.88-.07,18.01,.91,26.98,.54,.46,0,.9-.44,.62-.87-2.84-2.98-6.97-5.1-9.47-8.24,.13-.16,.32-.41,.49-.41,1.61-.07,3.23-.13,4.84-.11,5.94,.05,11.84-.36,17.75-.73,.44-.04,.8-.57,.49-.95-2.83-2.33-5.85-4.46-8.71-6.73-1.7-1.37-.93-1.7,.83-1.78,6.03-.36,12.06-.67,18.03-1.66,1.38-.63-.88-1.61-M 1.36-2.12-2.52-1.78-5.07-3.55-7.58-5.33-1.23-.87-1.6-1.64,.22-1.86,5.31-.65,10.65-1.22,15.81-2.51,1.36-.74-1.01-1.52-1.49-2.07-2.86-1.95-5.74-3.91-8.61-5.86-.42-.29-.71-.61-.56-1.1,4.87-1.11,9.85-2.02,14.58-3.67,.52-.61-.58-1.13-.99-1.49-2.97-2.03-5.96-4.03-8.93-6.06-.42-.42-1.82-1.05-1.29-1.69,4.11-1.6,8.5-2.6,12.55-4.3,.13-.97-.89-1.26-1.5-1.81-3.41-2.44-6.98-4.68-10.3-7.25-.98-1.04,1.91-1.45,2.5-1.93,2.69-1.22,5.43-2.38,7.89-3.9,.54-.71-.89-1.25-1.31-1.71-3.36-2.49-6.73-4.97-10.09-7.46-.5-.54-2.12-1.23-1.14-2.04M ,2.73-1.36,5.42-2.82,8.08-4.27,1.66-.93,1.67-1.16,.33-2.18-3.93-2.89-7.65-6.07-11.49-9.07-.56-.44-.47-.97-.49-1.49,.45,.06,.75-.15,1.06-.37,2.78-1.82,5.24-3.99,7.81-5.95,.96,.08,1.41,.66,1.97,1.1,3.29,2.54,6.56,5.09,9.84,7.63,.48,.36,.95,.77,1.87,.77,2.75-2.74,4.39-6.01,7.05-8.95,3.84,2.7,7.36,5.1,11.18,7.7,.45,.3,1.22,.74,1.71,.33,2.47-2.87,3.25-6.78,5.84-9.52,4.34,1.94,7.65,4.32,12.1,6.05,1.37-2.49,2.19-5.01,3.13-7.45-3.64-2.91-7.47-5.62-11.48-8.11Zm-78.94-7.38c-.45-.37-.57-1.06-.03-1.4,2.74-1.91,5.48-3.81,8.22-5M .72,.79-.55,1.33-.51,2,.18,3.97,4.2,8.15,8.23,12.11,12.42-2.9,2.63-6.67,5.36-9.55,6.94-4.72-3.51-8.64-8.28-12.75-12.42Zm24.1,25.99c-2.56,1.18-5.15,2.31-7.86,3.26-.78,.27-1.36,.23-1.83-.18-4.4-4.02-9.24-7.78-12.91-12.29,.23-.44,.78-.53,1.25-.69,2.97-.98,5.96-1.93,8.94-2.9,.68-.22,1.25-.11,1.79,.37,3.43,3.02,6.84,6.05,10.28,9.07,.91,.59,1.84,2.14,3.07,1.54-.82,.68-1.68,1.33-2.73,1.82Z"/><path class="cls-2" d="M489.67,834.92s-.08,.01-.11,.02l.11-.11v.09Z"/></g><path class="cls-2" d="M475.87,744.75c4.06,4.64,8.14,9.28,M 12.22,13.91,4.17,.09,8.29-.43,12.42-.8,.56-.09,1.87-.3,1.48-1.1-3.77-4.21-7.63-8.35-11.42-12.54-1.55-1.82-1.65-2.19,.89-2.36,12.5-2.16,12.58,1.18,4.18-9.03-3.82,1.16-7.57,2.52-11.24,4.06,1.18,1.47,2.43,2.91,3.47,4.48,.45,.73-1.76,.76-2.2,.85-3.5,.08-6.97,.06-10.46,.19-.31,0-.73,.51-.59,.7,.41,.55,.79,1.12,1.25,1.64Z"/><path class="cls-2" d="M360.74,881.24c1.16-.23,2.27,.47,3.4,.69,3.27,.92,6.53,1.86,9.8,2.79-1.04-4.28-1.9-8.61-2.58-12.98-5.65-1.69-11.22-3.57-16.85-5.32-.56-.26-1.28-.39-1.86-.23-.49,.17-.28,.56-.14,M .83,2.25,4.25,4.61,8.48,6.79,12.76-.9,.62-1.77,.04-2.69-.15-17.11-5.24-33.91-11.05-50.39-17.46-2.18-.84-4.36-1.7-6.56-2.5-.44-.16-1.02-.09-1.08,.12-.06,.19-.18,.42-.11,.59,1.32,3.28,2.66,6.55,3.98,9.83,.54,1.33,1.04,2.67,1.53,4.01,.07,.17-.04,.39-.08,.59-.93,.71-2.93-.74-4.02-.95-22.25-8.27-43.85-17.32-65.22-27.11-.57-.26-1.14-.59-2-.49,.41,4.89,2.6,9.65,3.67,14.47,.2,.73,.47,1.46,.23,2.22-.24,.88-2.19-.35-2.78-.46-12.44-5.38-24.69-11.03-36.85-16.8-14.74-6.94-29.09-14.42-43.5-21.77-.47-.22-1.1,.12-1.06,.59,.14,1.39M ,.26,2.79,.45,4.18,.68,4.9,1.39,9.81,2.08,14.7,28.14,13.76,56.78,26.82,86.02,38.32,1.46,.13,.33-2.29,.26-3.11-1.17-4.42-2.52-8.81-3.62-13.25-.05-.18,.01-.46,.16-.59,1.03-.5,2.21,.59,3.23,.85,22,9.37,44.68,17.91,67.48,25.64,.7,.17,2.07,.89,2.35-.04-1.51-4.92-4.17-9.52-5.44-14.5-.02-.12,.33-.38,.52-.39,1.27-.04,2.29,.59,3.38,.98,18.89,6.3,38.27,13.82,57.87,17.63,.08-.67-.35-1.23-.66-1.82-1.56-2.97-3.15-5.95-4.72-8.92-.21-.72-1.82-2.46-.99-2.95Z"/><g><path class="cls-2" d="M150.04,803.51c26.75,14.28,53.43,29.39,81.33,M 41.37,.51-.46,.33-1,.19-1.5-1.28-5.15-3.26-10.22-4.06-15.45-.03,.01-.06,0-.1-.01,.04,0,.07,0,.11-.01,.05-.06,.09-.1,.14-.16,.03,.06,.05,.1,.03,.14,.96-.23,1.78,.4,2.61,.77,14.08,6.97,28.38,13.67,42.97,19.94,7.77,3.14,15.38,6.86,23.32,9.57,.84-.06,.48-1.05,.32-1.57-1.32-3.28-2.67-6.55-4.01-9.83-.42-1.02-.86-2.04-1.21-3.08-.08-.26,.02-.73,.25-.86,1.06-.24,2.25,.67,3.24,1,17.5,7.46,35.44,14.33,53.5,20.56,.6,.21,1.27,.29,1.92,.41,.08,.01,.3-.15,.28-.2-1.4-4.3-4.22-8.11-6.17-12.22-.17-.48-.61-1.02-.4-1.51,.12-.25,.35-.3M 3,.65-.23,2.59,.92,5.18,1.81,7.75,2.74,5.7,2.04,11.44,4,17.22,5.87-.3-3.97-.46-7.96-.46-11.98-10.44-3.58-20.8-7.44-30.93-11.6-.82-.25-1.67-.94-2.54-.51-.31,.39,.41,1.33,.56,1.79,1.88,3.57,3.78,7.14,5.67,10.71,.25,.48,.49,.96,.3,1.5-2.04,.16-3.93-1.18-5.85-1.74-17.63-6.61-34.69-14.58-51.72-21.86-.13,.17-.31,.39-.27,.55,1.34,4.08,3.17,8,4.72,12.01,.33,.82,.62,1.65,.95,2.47,.29,.55-.56,.77-.93,.65-21.89-9.47-43.41-20.05-64.25-31.13-.89-.34-1.78-1.25-2.77-.87-.09,.03-.17,.19-.15,.28,1.39,5.37,2.93,10.72,4.36,16.08,.23,M .76-.68,.91-1.18,.57-21.2-10.59-42.14-21.96-62.55-33.89-4.78-2.8-9.53-5.64-14.3-8.45-.53-.32-1.02-.7-1.76-.6-.48,1.6,.11,3.37,.21,5.02,.51,4.58,1.69,9.17,1.87,13.74-.61,.23-1.09,.06-1.52-.19-14.98-8.49-29.68-17.52-44.4-26.4-8.03-4.9-15.93-9.93-23.79-15-7.88-5.05-15.55-10.33-23.39-15.39-.36-.3-1.07-.38-1.31,.01-.64,6.7-.17,13.57-.13,20.31,.2,1.32,1.93,1.78,2.87,2.56,4.99,3.11,9.98,6.23,14.97,9.33,25.6,15.82,51.98,31.14,78.78,45.08,.11,.04,.57-.19,.57-.28-.1-5.6-1.47-11.11-2.15-16.67,.04-.61-.33-1.89,.64-1.84Z"/><patM h class="cls-2" d="M342.55,849.23c.06,.02,.14,.05,.21,.07-.22,.12-.28,.1-.21-.07Z"/></g><path class="cls-2" d="M449.27,412.22s.03-.01,.05-.02c.01-.02,.01-.03,.02-.05l-.07,.07Zm14.24-264.13s.03-.02,.05-.03t.01-.02l-.06,.05Zm25.35-1.63s-.02,.09-.04,.13c.04,0,.08-.01,.12-.01l-.08-.12Zm16.52,357c-3.19,2.47-6.3,5.04-9.53,7.46-.3,.21-.7,.46-1.06,.21-.25-.18-.41-.54-.42-.83-.14-2.8-.23-5.6-.33-8.4-.26-7.64-.25-15.29,.02-22.94-.03-.86,.37-2.9-1.11-2.49-4.35,2.48-8.34,5.51-12.67,8.01-.37,.2-1.1,.03-1.15-.44-.04-2.15-.09-4.3M 1-.05-6.46,.11-10.87,.68-21.76,.98-32.62-.54-1.03-1.88,.13-2.63,.4-3.5,1.82-6.99,3.66-10.49,5.48-.82,.23-2.46,1.66-3.05,.65,.04-15.19,2-30.32,3.17-45.46-.3-1.04-1.61-.27-2.28-.04-5.07,2.19-10.18,4.35-15.46,6.21-1.27,4.79-.68,9.84-1.2,14.75-.37,10.41-1.17,20.95-.54,31.31,2.02,1.96,12.19-4.07,14.99-5.06,.47-.22,1.09,.12,1.09,.59-.02,2.05-.01,4.1-.1,6.14-.42,11.2-.51,22.42,.32,33.59,.47,2,12.22-7.11,14.35-7.37,.86-.08,.79,.94,.81,1.53-.15,9.92,.72,19.81,1.04,29.72,.21,1.14-.26,4.6,1.5,4.13,3.91-2.56,7.54-5.55,11.34-8.M 28,.66-.5,1.27-.25,1.45,.35,.32,4.08,.63,8.17,.94,12.25,.51,5.92,.6,11.87,1.85,17.69,.01,.1,.47,.26,.61,.21,1.62-13.93,4.71-28.23,9.24-41.49-.57,.37-1.11,.79-1.63,1.2Zm18.84-48.61c-1.48-.83-14.48,11.17-14.77,8.78,.53-7.29,1.57-14.58,2.12-21.9,.41-5.57,1.75-11.26,2.03-16.75-1.42-.03-2.46,1.06-3.67,1.67-3.79,2.24-7.58,4.48-11.39,6.71-.52,.13-1.35,.3-1.26-.64,1.4-12.03,2.78-24.04,5.04-35.96,.35-2.62,1.28-5.37,1.01-7.99-.05-.12-.47-.29-.59-.24-.96,.38-1.91,.79-2.83,1.23-4.43,2.02-8.7,4.4-13.23,6.2-1.34,.06-.67-1.61-.67M -2.42,.99-6.09,1.9-12.19,3.02-18.26,1.39-7.45,2.95-14.88,4.45-22.32,.55-2.77,1.15-5.53,1.72-8.29,0-1.61-2.31-.06-3.14,.08-5.19,1.7-10.21,4.08-15.52,5.36-1.01,.17-.38-2.02-.39-2.6,2.72-14.4,6.09-28.67,9.51-42.92,.98-4.67,2.71-9.21,3.35-13.94-.41-1.05-1.94-.22-2.76-.12-5.36,1.42-10.73,2.85-16.09,4.27-.65,.06-1.71,.6-2.07-.19,3.81-18.36,9.26-36.54,14.26-54.66,1.22-4.3,2.57-8.58,3.84-12.88,.11-.8,.72-2.11-.5-2.19-6.98,1.13-13.96,2.33-20.94,3.49-.52,.08-1.07-.33-1.01-.75,6.82-27.38,16.56-54.11,25.08-81.03-7.54,.69-15.1,M 1.11-22.67,1.05-.88,.07-1.86-.13-2.59,.42-8.06,25.62-15.36,51.44-21.94,77.46-.17,1.52-1.24,3.36,1.13,3.29h17.79c1.93-.19,2.81-.02,2.29,1.51-5.98,21.92-11.34,44.02-15.83,66.29-.04,.73-.47,2.14,.47,2.34,6.44,.58,12.63-1.89,18.83-3.11,1.85-.18,.76,1.91,.71,2.91-3.46,15.23-6.54,30.53-9.29,45.91-.64,3.51-1.23,7.03-1.82,10.55-.11,.63-.28,1.29,.26,1.99,6.22-1.32,12.06-4.23,18.2-5.91,.32-.08,.87,.24,.83,.51-2.01,13.69-4.82,27.27-6.42,41.01-.57,3.63-.9,7.28-1.16,10.94,.45,1.12,1.88-.01,2.65-.23,3.88-1.74,7.75-3.48,11.62-5.2M 3,.78-.28,3.37-1.91,3.47-.34-2.1,14.75-3.84,29.54-4.72,44.41,.4,1.71,2.86-.61,3.78-.87,3.63-2.05,7.25-4.11,10.87-6.17,.47-.27,.94-.39,1.51-.2,.32,.96,.09,1.93-.05,2.88-1.37,11.89-2.09,23.85-2.38,35.81,.02,.84,.76,.85,1.27,.59,3.85-2.49,7.54-5.22,11.29-7.83,.54-.32,1.86-1.42,2.18-.42-.08,2.9-.03,5.81-.26,8.71-.63,7.92-.56,15.87-.56,23.8,4.13-11.44,9.28-22.33,15.31-32.62,.25-3.44,.59-6.87,.9-10.31,.02-.29-.15-.6-.27-.88Zm284.93,28.43s.04,.05,.06,.08c.02-.01,.04-.01,.06-.02l-.12-.06Zm22.08,23.39c-2.08-1.98-4.18-3.95-6M .25-5.93-.85-.83-1.37-.9-2.43-.55-8.44,3.01-16.86,6.28-24.9,10-.47,.22-.93,.43-1.51,.26-3.6-2.74-5.76-4.79-7.25-6.94,8.53-4.79,17.92-7.87,26.8-12.04-2.03-2.83-4.46-5.37-6.48-8.11-9.56,3.49-18.57,7.99-27.71,12.32-.68-.13-1.07-.4-1.37-.77-1.45-1.82-2.89-3.64-4.36-5.44-.45-.48-1.01-1.29-1.77-1.1-8.28,3.88-15.69,9.08-23.52,13.59-2.65-2.28-3.71-5.24-6.14-7.58-1.12,.18-1.73,.79-2.41,1.28-5.64,4.01-11.36,7.95-16.69,12.22-.7,.42-1.72,1.7-2.54,.91-1.5-2.28-2.97-4.58-4.41-6.89-.26-.4-.93-.47-1.37-.14-6.05,4.55-11.27,9.85-16.M 86,14.82-.35,.32-1.13,.16-1.29-.24-.79-2.15-1.25-4.41-1.93-6.6-.09-.28-.26-.67-.52-.76-.86-.22-1.28,.62-1.86,1.04-4.56,4.39-9.22,8.72-13.48,13.31-.47,.5-.82,1.13-1.88,1.26-1.61-2.61-1.5-5.62-2.84-8.29-.65-.05-1.03,.24-1.35,.6-1.9,2.09-3.81,4.18-5.68,6.29-2.77,3.04-5.33,6.25-8.2,9.21-.13,.12-.5,.16-.71,.11-.61-.17-.68-.84-.82-1.36-.66-2.3-1.32-4.61-2-6.91-.05-.19-.28-.41-.5-.47-.6-.08-1.07,.53-1.44,.93-4.62,4.95-8.36,10.64-12.95,15.58-1.66,.68-2.73-8.72-3.6-9.71-.93-.02-1.36,.87-1.9,1.47-2.8,3.68-5.59,7.36-8.38,11.0M 5-.65,.72-1,1.72-2.06,1.9-1.55-2.9-1.32-6.31-2.12-9.45-.12-.62-.13-1.29-.78-1.78-.75,.14-1.02,.65-1.35,1.11-2.48,3.45-4.95,6.92-7.43,10.37-.59,.64-1.26,2.08-2.04,2.32-.78-.15-.81-.96-.95-1.58-.7-3.71-.62-7.6-1.85-11.18-1.18,.05-1.57,1.31-2.29,2.07-2.33,3.28-4.63,6.57-6.95,9.84-.56,.61-.89,1.55-1.91,1.33-1.07-4.56-1.16-9.19-1.7-13.82-.05-.47-.33-.81-.59-.7-.84,.28-1.3,.94-1.77,1.62-2.7,3.6-5.3,7.25-7.98,10.86-.1,.13-.45,.16-.7,.21-.05,.01-.19-.12-.22-.21-.57-1.95-.55-4.07-.77-6.08-.33-1.27,.18-11.41-1.46-10.43-3.06,M 3.15-5.39,6.95-8.15,10.35-.63,.63-.99,1.85-2.05,1.69-.47-.08-.39-.76-.49-1.13-.38-4.95-.82-9.88-.77-14.85-.1-2.65,.37-4.99-2.39-1.71-2.46,2.96-4.9,5.93-7.38,8.89-.43,.38-1.01,1.27-1.63,1.24-.57-.14-.5-1.27-.61-1.76-.15-6.56-.27-13.13-.32-19.71,.02-1.18-1.03-.64-1.48-.26-2.86,3.13-5.69,6.28-8.55,9.41-.39,.43-.87,.81-1.33,1.2-.11,.05-.58-.09-.64-.22-.6-3.74-.15-7.62-.22-11.41-2.35,6.28-4.29,12.75-5.79,19.4,1.66-1.78,3.12-3.7,4.95-5.31,.25-.25,.81,.09,.88,.29,.41,7.1,.72,14.2,1.5,21.28,.08,.32,.2,1.04,.65,.99,.31-.17,M .69-.33,.89-.58,2.26-2.8,4.5-5.62,6.76-8.43,.58-.72,1.19-1.43,1.83-2.12,.11-.11,.47-.09,.71-.08,.51,.05,.46,.73,.56,1.11,.35,4.09,.67,8.17,1.04,12.25,.17,1.94,.44,3.86,.69,5.79,.24,.64,.74,.79,1.33,.09,2.6-3.53,5.18-7.07,7.8-10.58,1.52-1.87,1.93-.64,2.08,1.11,.23,4.95,1.06,9.88,1.96,14.76,.02,.08,.15,.22,.22,.22,1.07,.08,1.38-1.1,1.98-1.77,2.53-3.54,4.7-7.35,7.47-10.69,1.23-.47,1.26,1.85,1.38,2.55,.56,4.04,.96,8.16,1.85,12.13,.71,.16,1.1-.05,1.37-.47,2.26-3.43,4.51-6.87,6.78-10.29,1.16-1.66,2.3-3.59,2.87-.27,.38,3.M 43,1.26,6.81,1.96,10.21,.1,.29,.25,.72,.59,.79,.23,0,.58,0,.67-.1,.44-.54,.82-1.11,1.19-1.68,2.16-3.35,4.3-6.71,6.47-10.05,.62-.76,.95-1.77,2.1-1.84,.98,3.57,1.86,7.16,2.83,10.73,.07,.26,.49,.46,.74,.68,.91-.48,1.18-1.23,1.62-1.89,2.38-3.62,4.76-7.24,7.15-10.86,.41-.47,.8-1.29,1.43-1.47,.23,.06,.58,.15,.62,.28,.39,1.14,.72,2.29,1.08,3.44,.62,1.98,1.24,3.96,1.9,5.94,.03,.11,.4,.18,.63,.22,3.61-3.82,6.32-8.79,9.61-13,.66-.78,1-1.77,2.19-1.85,.74,1.16,2.72,9.73,4.04,8.62,4.15-4.85,7.71-10.15,11.9-14.98,.54-.48,1.42-2.M 07,2.17-1.17,.76,1.95,1.52,3.9,2.25,5.86,.27,.72,.5,1.45,1.22,2,.87-.2,1.19-.83,1.64-1.35,3.65-4.27,7.3-8.54,10.96-12.8,.73-.63,1.3-1.98,2.38-1.95,.22,.05,.46,.25,.54,.43,.97,2.33,1.55,4.92,3.01,6.99,.39,.2,.96-.33,1.23-.54,4.2-4.63,8.65-9.09,13.2-13.5,.58-.56,1.05-1.26,2.14-1.55,2.3,2.1,3.17,4.93,5.48,7.1,1.4-.24,2.18-1.47,3.18-2.33,4.28-4.17,8.83-8.14,13.61-11.95,.54-.43,.99-1.01,1.99-1.07,1.82,2.21,3.67,4.45,5.53,6.68,.24,.18,.47,.15,.85,.21,6.63-4.68,13-9.78,19.92-14.06,.43-.28,1.1-.18,1.42,.18,1.81,2.38,4.37,4M .35,5.68,7.03-7.05,4.39-13.58,9.46-20.38,14.12-.88-.18-1.26-.63-1.67-1.05-1.66-1.69-3.31-3.39-4.97-5.09-.24-.24-.77-.28-1.07-.06-5.57,4.28-10.98,8.91-16.05,13.65-.5,.47-.9,1.06-1.86,1.21-2.57-1.69-3.4-4.61-5.96-6.35-.38-.23-.64,0-4.05,3.38-.42,.42-.85,.84-1.26,1.26-3.17,3.22-6.32,6.45-9.49,9.66-.48,.49-.85,1.1-1.94,1.26-1.97-2.09-3.32-4.58-5.18-6.81-.84,.09-1.19,.54-1.54,.98-3.33,4.05-6.65,8.11-9.97,12.16-.9,.76-2.25,4.01-3.55,2.27-1.21-2.15-2.25-4.4-3.59-6.49-.79-.39-1.42,.74-1.91,1.2-3.94,4.76-7.24,9.84-10.98,14.M 68-.17,.22-.89,.19-1.03-.04-1.36-2.33-2.65-4.7-3.93-7.07-.14-.25-.83-.25-1.02,0-3.29,4.38-6.17,9.07-9.21,13.63-.4,.53-.69,1.3-1.5,1.22-.11,0-.27-.1-.31-.18-.9-1.92-1.78-3.83-2.67-5.74-.42-.9-.53-1.9-1.45-2.72-1.4,.59-1.88,2.22-2.74,3.37-1.88,3.1-3.73,6.21-5.6,9.31-.52,.64-.76,1.89-1.7,1.97-.23-.05-.5-.24-.57-.41-1.12-2.65-2.22-5.31-2.92-8.06-.16-.63-.3-1.27-.95-1.73-.99,.37-1.36,1.51-1.96,2.31-2.54,3.88-4.5,8.18-7.37,11.81-1.43,.62-2.85-7.88-3.4-9.16-.3-.73-.4-1.91-.98-2.41-1.07,.14-1.36,1.45-1.98,2.19-2.04,3.4-4.0M 5,6.81-6.09,10.2-.27,.46-.46,1.01-1.22,1.14-.54-.4-.68-.93-.81-1.46-.88-3.92-1.82-7.82-2.83-11.72-.02-.09-.16-.23-.22-.22-1.04,.02-1.35,1.18-1.9,1.87-1.94,3.19-3.87,6.39-5.81,9.59-.35,.57-.58,1.21-1.42,1.58-.23-.23-.62-.45-.69-.72-.99-4.23-2.1-8.45-2.69-12.74-.08-.53-.21-1.05-.35-1.58-.15-.27-.86-.15-1.01-.03-2.92,3.81-5.18,8.06-8.02,11.93-.11,.14-.48,.24-.69,.21-.18-.03-.39-.27-.43-.43-.56-2.98-1.11-5.97-1.63-8.95-.67-2.78-.42-5.76-1.75-8.32-1.19,.69-1.65,1.67-2.4,2.68-2.19,2.96-4.14,6.1-6.48,8.94-.17,.13-.86,.17-M .99-.13-1.06-4.97-1.98-9.99-2.4-15.04-.13-1.5-.46-2.98-.72-4.48-.73-.59-1.42,.69-1.9,1.12-2.56,3.16-4.99,6.42-7.6,9.53-1.92,1.66-1.52-2.44-1.81-3.44-.13,2.1-.23,4.19-.28,6.28,.23-.1,.64-.08,1-.13,1.2,6.63,2.39,13.02,3.72,19.57,.43,1.38,1.46,.46,1.98-.28,2.56-3.41,4.7-7.1,7.52-10.3,.12-.11,.57-.09,.65,.09,1.85,5.81,2.18,11.98,4.39,17.7,.97-.1,1.26-.97,1.76-1.65,1.76-2.78,3.51-5.58,5.27-8.37,.48-.64,1.43-2.81,2.33-1.53,1.2,4.63,2.28,9.3,3.5,13.93,.15,.36,.33,.96,.75,1.09,.21-.01,.56-.03,.63-.13,10.72-16.74,6.04-16.71M ,12.47,1.17,.71-.06,1.05-.35,1.27-.77,1.07-1.98,2.14-3.95,3.21-5.93,1.24-2.14,2.19-4.46,3.71-6.43,.21-.29,.84,0,.94,.17,1.32,3.62,2.51,7.26,3.86,10.86,.07,.17,.34,.35,.56,.4,.98,.02,1.16-1.31,1.66-1.95,1.83-3.35,3.65-6.71,5.47-10.07,.32-.59,.57-1.21,1.27-1.61,.1,.03,.27,.04,.3,.09,1.96,3.31,2.55,7,4.43,10.32,.85-.13,1.1-.62,1.37-1.11,2.15-3.83,4.3-7.66,6.47-11.49,1.88-3.28,2.12-1.61,3.26,.82,1.05,1.96,1.54,4.26,3.04,5.94,.94,.37,1.31-1.14,1.79-1.71,11.16-18.45,5.74-14.75,13.52-5.12,3.61-4.88,6.39-10.33,9.92-15.28,.M 54-.79,1.07-.5,1.52-.06,1.24,1.78,2.46,3.58,3.7,5.37,.3,.42,.95,1.01,1.48,.63,1.08-1.49,2.14-2.99,3.16-4.5,2.5-3.69,5.15-7.32,8-10.85,.32-.39,1.03-.39,1.34-.02,1.42,1.71,2.84,3.41,4.25,5.11,.31,.37,.68,.65,1.38,.73,4.01-4.79,7.98-9.7,11.98-14.51,.43-.53,.8-1.13,1.78-1.34,2.22,2.07,3.82,4.37,6.48,6.15,4.86-4.64,9.4-9.48,14.15-14.2,.49-.5,.93-1.08,1.92-1.19,2.15,1.86,4.35,3.75,6.52,5.65,.15,.13,.14,.38,.21,.6-4.75,4.63-9.31,9.49-13.95,14.23-.34,.35-.6,.71-.46,1.28,2.34,1.64,5.04,3.2,7.47,4.7,.98-.17,1.36-.77,1.84-1.2M 7,4.23-4.47,8.58-8.87,13.04-13.17,0-.2,.06-.48-.08-.59-2.29-1.78-4.99-3.29-7.09-5.21,.05-.27,.01-.53,.15-.68,1.84-2.11,13.87-12.2,17.29-14.52,3,1.61,4.92,4.38,8.07,5.83,6.56-4.69,13.42-9.33,20.21-13.66,2.67,1.34,5.24,4.03,7.81,5.75,.78,.54,1.8-.03,2.53-.45,6.79-3.99,13.86-7.51,20.96-10.96,.49-.25,1.1-.19,1.47,.12,2.36,2.24,5.33,3.95,7.25,6.55-7.52,3.82-15.49,7.01-22.42,11.46,2.03,2.19,5.44,3.71,7.92,5.56,.45,.29,1.01,.27,1.51,.02,5.62-2.83,11.2-5.62,17.03-8.06,1.63-.72,3.54-1.05,4.83-2.22,1.39-.02-6.76-5.26-7.96-6.M 68,.95-.97,2.2-1.18,3.39-1.7,7.03-2.74,14.06-5.46,21.35-7.72,.73-.23,1.53-.39,1.94-1.07-.19-.26-.34-.57-.59-.81Zm-44.07-2.5c-7.14,3.47-13.83,7.46-20.65,11.3-.65,.37-1.21,.88-2.29,.9-2.24-1.85-4.51-3.83-6.59-5.93-.34-.35-.27-.85,.19-1.14,2.11-1.33,4.18-2.71,6.37-3.96,5.4-2.99,10.72-6.24,16.25-9,.31-.06,.83-.02,1.07,.26,2.07,2.38,4.86,4.35,6.51,6.99-.28,.19-.54,.42-.86,.58Z"/><path class="cls-2" d="M510.8,220.17s-.02,.03-.03,.05c-.02,0-.03,.01-.05,.01l.08-.06Z"/><path class="cls-2" d="M547.46,404.29c-1.92,12.24-5.62,M 24.32-6.58,36.71-.7,.88-1.4,1.76-2.08,2.64-3.49,2.38-6.84,4.97-10.28,7.44-.82,.45-3.07,2.83-3.48,1.25,.71-5.9,1.27-11.81,2.15-17.69,.97-6.61,2.67-13.16,3.1-19.83-.51-.71-1.36,.18-1.91,.43-4.54,2.67-8.8,5.83-13.53,8.15-.11,.04-.57-.17-.56-.24,.14-1.5,.32-3,.51-4.49,.79-7.32,2.29-14.52,3.59-21.77,1.14-5.52,2.31-11.04,3.47-16.56,.05-.29,.01-.73-.18-.92-.7-.29-1.54,.31-2.18,.57-4.35,2.19-8.66,4.36-13.03,6.51-.64,.24-1.96,1.12-2.26,.08,2.09-12.17,4.71-24.27,7.66-36.29,.93-3.8,1.9-7.59,2.84-11.39,.06-.95,1.19-2.78-.32-2.M 76-6.02,2.08-11.77,4.88-17.85,6.76-.3,.07-.6-.09-.57-.34,.09-.95,.15-1.92,.38-2.86,3.78-16.12,7.81-32.15,12.54-48.04,.62-2.1,1.2-4.2,1.78-6.3,.15-.52,.28-1.06-.32-1.59-5.58,1.42-11.15,3.12-16.71,4.65-1.03,.11-3.92,1.74-3.75-.23,6.36-22.81,12.97-45.65,20.88-67.96,7.44-1.43,14.86-3,22.31-4.34,.39-.05,.84,.28,.75,.56-2.32,6.52-4.71,13.03-7.02,19.54-5.05,15.45-11.12,30.84-14.97,46.53,.51,.64,1.48,.17,2.14,.06,6.04-1.78,12.06-3.68,18.12-5.39,.81,.58,.31,1.39,.16,2.17-2.02,6.25-4.14,12.48-6.06,18.75-3.52,12.16-7.43,24.21M -10.31,36.53-.05,.24,.59,.54,.91,.42,1.1-.42,2.2-.82,3.27-1.26,4.32-1.77,8.62-3.55,12.94-5.31,.58-.18,1.66-.71,2.04-.03-2.14,9.65-5.48,19.08-7.67,28.72-1.52,6.77-3.69,13.44-4.64,20.3-.03,.28,.58,.5,.93,.33,4.73-2.25,9.28-4.78,13.94-7.16,.78-.29,1.65-1,2.48-.92,.15,.16,.25,.34,.33,.53-2.95,12.22-5.96,24.49-8.46,36.83-.39,1.8-.59,3.62-.86,5.43-.02,.1,.07,.27,.14,.29,.91,.26,1.65-.51,2.39-.9,3.49-2.2,6.97-4.41,10.46-6.62,.86-.33,2.74-2.41,3.37-.99Z"/><path class="cls-2" d="M582.64,382.65c-2.56,7.88-4.76,15.81-6.78,23.M 84-6.2,4.88-12.16,10.1-17.82,15.64,2.18-9.67,4.64-19.31,6.9-28.95-.42-1.17-1.75,.16-2.42,.46-4.03,2.53-8.04,5.08-12.06,7.61-.62,.4-1.21,.88-2.17,.87,1.2-7.82,3.7-15.62,5.66-23.39,1.72-6.08,3.45-12.17,5.16-18.26,.01-1.6-2.25,.14-2.95,.38-4.05,2.13-8.1,4.26-12.15,6.39-.73,.31-2.56,1.72-2.71,.24,1.87-7.95,4.43-15.75,6.61-23.62,2.25-7.43,4.77-14.8,7.04-22.23,.22-.71,.7-1.42,.16-2.17-6.31,1.78-12.1,5.27-18.39,7.29-.45,.18-.71-.43-.67-.58,5.67-18.91,11.84-37.65,19.07-56.06l.25-.22c7.26-2.32,14.5-4.65,21.75-6.97-7.25,17.3M 1-13.92,34.82-20,52.44-.28,.83-.5,1.67-.69,2.51-.02,.09,.42,.36,.54,.32,6.26-2.03,12.05-5.39,18.34-7.35,.14-.03,.56,.24,.54,.33-.16,.73-.34,1.47-.62,2.18-5.45,14.2-10.29,28.54-14.81,42.95-.08,.5-.5,1.51-.16,1.87,.21,.08,.52,.18,.69,.12,5.5-2.65,10.73-5.8,16.21-8.5,.24-.07,.88-.06,.89,.32-.17,.74-.31,1.49-.55,2.21-3.72,10.88-7.03,21.87-10.27,32.89-.5,1.67-.93,3.36-1.36,5.04-.05,.19,.03,.48,.2,.59,.14,.09,.55,.06,.72-.04,4.74-2.8,9.29-5.89,13.95-8.81,.52-.33,1.03-.71,1.92-.57,0,.39,.09,.82-.02,1.23Z"/><path class="clM s-2" d="M597.34,493.02h-.05s-.02-.05-.03-.07l.08,.07Z"/><path class="cls-2" d="M809.15,483.28s.04-.02,.06-.02c.02,.03,.04,.05,.06,.08l-.12-.06Z"/><path class="cls-2" d="M855.37,489.95c-.46,.61-1.12,.77-1.74,.94-2.16,.58-4.34,1.13-6.51,1.71-7.75,2.04-15.34,4.47-22.87,6.96-.34-.14-.64-.2-.79-.35-2.18-2.18-4.34-4.38-6.5-6.58-.34-.35-.54-.73-.27-1.29,9.88-3.82,20.53-7.01,30.7-10.1,.17-.45,.04-.65-.15-1.01-1.8-2.64-3.61-5.27-5.4-7.87-2.17,.15-4.78,.88-11.04,3.05-7.19,2.58-14.56,4.88-21.59,7.85-1.9-2.71-3.84-5.37-5.86-8-M .22-.3-.68-.41-1.05-.3-8.79,3.37-17.27,7.53-25.56,11.73-.65,.34-1.23,.8-2.21,.84-1.64-1.53-2.66-3.69-3.98-5.5-.7-.89-1.25-2.98-2.71-2.17-8,4.03-15.29,9.14-22.92,13.62-.72-.1-1.01-.45-1.25-.85-1.52-2.2-2.65-5.35-4.51-7.14-.87,.09-1.42,.6-2.02,1.02-5.03,3.58-10.16,7.08-14.86,10.94-1.45,1.01-2.53,2.48-4.36,2.84-1.2-2.72-1.15-5.57-1.94-8.28-.95-.2-1.61,.57-2.32,1.04-5.75,4.41-10.76,9.34-16.19,13.99-.34,.25-1.11,.08-1.25-.33-.51-2.54-.92-5.11-1.37-7.66-.03-.15-.35-.27-.57-.36-.35-.04-.73,.28-1,.48-4.64,4.33-9.28,8.67-13M .92,13.01-.78,.74-1.55,1.47-2.34,2.2-.25,.25-.87-.07-.95-.27-.54-2.75-.87-5.56-1.47-8.3-.05-.16-.35-.29-.57-.4-.78,.13-1.4,1.02-1.99,1.49-4.04,4.31-8.06,8.63-12.1,12.94-.79,.65-1.36,1.91-2.51,1.88-.06,0-.18-.14-.2-.23-.84-3.04-1.24-6.15-1.76-9.25-.03-.18-.23-.34-.39-.49-.69-.35-1.53,.9-2,1.36-3.29,3.81-6.58,7.63-9.86,11.44-1,1.15-1.91,2.36-2.96,3.47-.31,.33-.79,.46-1,.26-.17-.16-.41-.32-.44-.5-.4-2.23-.76-4.48-1.15-6.71-.19-1.07-.41-2.13-.66-3.19-.04-.15-.31-.37-.48-.38-1.04,.21-1.57,1.45-2.27,2.14-2.75,3.45-5.48,6M .92-8.23,10.37-.48,.44-.88,1.3-1.58,1.32-.41,.02-.45-.42-.56-.71-1.05-3.71-.34-8.42-1.64-11.78-1.03,.04-1.43,1.12-2.08,1.77-2.71,3.48-5.39,6.96-8.1,10.43-.35,.45-.79,.85-1.22,1.25-.05,.05-.35,.02-.37-.02-.16-.28-.36-.58-.38-.87-.23-3.88-.42-7.75-.64-11.62-.21-1.26,.09-2.86-1.54-1.41-3.33,4.03-6.29,8.35-9.74,12.26-.26,.2-.91,.18-.9-.21-2.51-16.3,3.86-23.37-10.14-5.66-.63,.6-1.17,1.72-1.96,1.97-.22-.09-.57-.21-.58-.34-.11-1.07-.21-2.15-.21-3.22,.02-4.53,.09-9.05,.12-13.57,.01-.53-.1-1.07-.18-1.6,0-.06-.17-.13-.29-.16M -.51-.17-.84,.41-1.17,.68-2.5,2.94-4.99,5.89-7.48,8.83-.61,.71-1.2,1.44-1.88,2.1-.16,.16-.68,.08-1.04,.11-.3-3.68-.2-11.64,.12-15.27,.18-2.04,.26-4.08,.38-6.13-.4-1.56-2.57,1.38-3.11,1.83-2.41,2.59-4.82,5.19-7.23,7.78-.6,.54-1.03,1.45-1.94,1.48-.33,.02-.48-.16-.48-.42,.03-7.21,.6-14.43,1.17-21.62,.07-.96,.09-1.93,.13-2.89,0-.08-.12-.23-.19-.23h-.24c.47-.77,.94-1.53,1.43-2.29,19.09-16.56,12.04-16.23,10.7,13.08,.67,1.6,2.62-1.53,3.32-2.02,2.91-2.96,5.56-6.15,8.63-8.95,.12-.1,.47-.04,.71-.02,.28,6.49-.87,13.33-1.24,19M .92-.01,.66-.04,1.71,.95,1.28,3.62-3.7,6.96-7.65,10.48-11.45,.3-.33,.62-.68,1.23-.62,.34,.6,.21,1.22,.18,1.84-.25,5.06-.49,10.12-.72,15.18,.03,.63-.17,1.43,.64,1.65,.66-.11,1.09-.95,1.57-1.38,2.83-3.28,5.64-6.58,8.48-9.85,.43-.36,1.04-1.35,1.64-1.22,.12,.03,.31,.09,.32,.15,.07,.53,.17,1.06,.16,1.59-.04,4.63-.53,9.26-.13,13.88,.01,.14,.33,.28,.53,.38,4.11-3.57,7.15-8.65,11.06-12.59,1.61-1.43,1.31,1.19,1.31,2.1,.06,3.66,.11,7.33,.19,10.99,0,.17,.22,.35,.34,.52,.55,.43,1.36-.61,1.73-1.05,3.48-4.11,6.93-8.24,10.62-12.1M 9,.11-.12,.46-.12,.7-.13,.37,.32,.29,1.05,.38,1.52,.19,2.9,.36,5.81,.55,8.71,.19,.61-.22,1.98,.66,2.02,1-.11,1.46-1.17,2.14-1.78,2.68-2.97,5.35-5.95,8.05-8.9,1.35-1.48,2.72-2.95,4.18-4.36,.62-.61,.95-1.58,2.29-1.51,.78,.61,.44,1.4,.48,2.11,.34,2.87-.19,5.9,.76,8.65,.47,.91,1.79-.88,2.27-1.19,4.35-4.4,8.67-8.81,13.01-13.2,.59-.59,1.25-1.13,1.92-1.65,.1-.08,.64,.02,.66,.11,.74,3.03,.63,6.22,1.03,9.31,.38,1.09,1.32,.52,1.94-.17,3.25-3.45,6.87-6.65,10.42-9.89,1.87-1.7,3.8-3.35,5.75-4.99,.21-.18,.68-.17,1.13-.27,.58,3.1M 1,.63,6.05,1.17,9.08,.03,.19,.88,.36,1.06,.21,6.21-5.07,11.89-10.69,18.45-15.36,.26-.2,.92,0,.96,.29,.38,2.77,.36,5.64,1.03,8.34,.73,1.06,2.85-1.34,3.66-1.77,5.58-4.34,11.47-8.59,17.49-12.45,.24-.14,.95,.1,.98,.33,.39,2.57,.53,5.14,.75,7.72,.58,1.26,2.06-.14,2.82-.58,7.01-4.31,13.83-9.13,21.35-12.73,.76-.14,1.1,.79,1.43,1.3,1.15,2.06,2.29,4.13,3.44,6.19,.22,.4,.53,.74,1.32,.86,8.83-4.6,17.82-9.35,27.23-12.99,.26-.1,.92,.1,1.06,.32,1.56,2.5,3.07,5.03,4.63,7.53,.18,.26,.56,.43,.9,.69,10.58-4.29,21.49-7.88,32.32-11.79M ,.21-.17,.34-.62,.2-.88-1.41-2.91-2.77-5.83-4.38-8.75-11.67,3.21-22.55,8.23-33.92,12.26-2.15-2.67-3.2-5.64-4.75-8.58-.19-.37-.92-.59-1.36-.39-8.26,3.52-16.18,7.66-24.1,11.82-.82,.23-2.73,1.94-3.31,.79-.15-2.79-.09-5.6-.42-8.38-.01-.11-.46-.31-.63-.27-8.2,3.78-15.59,9.2-23.4,13.73-.25,.15-.94-.07-.99-.31-.45-2.11-.21-4.3-.34-6.44,0-.65-.05-1.29-.06-1.93,0-.27-.14-.44-.47-.44-1.01,0-1.79,.84-2.62,1.31-6.4,4.3-12.6,8.78-18.73,13.31-.3,.2-.94,.05-.97-.24-.39-2.99-.11-6.01-.14-9.01,0-.25-.18-.4-.5-.42-.5-.05-.97,.34-1.3M 6,.57-5.38,4.03-10.52,8.3-15.62,12.65-.65,.55-1.27,1.12-1.95,1.64-.44,.35-.81,.96-1.62,.66-.6-.22-.41-.74-.42-1.14-.02-2.8,.13-5.6-.03-8.4-.04-.26-.37-.7-.69-.65-6.32,4.51-12.07,10.17-17.79,15.38-.3,.33-1.04,.76-1.3,.5-1.39-.75,.86-12.74-1.57-10.95-6,5.05-11.07,11.44-17.17,16.19-.33,.02-.53-.12-.53-.39-.03-2.47-.07-4.94-.08-7.42-.01-1.39,.07-2.79,.06-4.19,0-.13-.33-.27-.53-.37-5.53,4.16-10.14,9.81-15,14.71-.64,.68-1.37,1.31-2.07,1.96-.06,.05-.24,.04-.36,.02-.12-.02-.31-.07-.32-.13-.08-.42-.19-.85-.17-1.28,.18-4.09,M .47-8.17,.55-12.26,.01-.07-.12-.22-.19-.22-.96-.18-1.41,.74-2.03,1.28-3.85,3.78-7.16,8.39-11.32,11.7-.21-.09-.54-.24-.54-.36,.01-1.4,.04-2.79,.12-4.19,.03-3.7,.78-7.66,.48-11.24-.23-.03-.59-.08-.69,.02-4.12,4.07-7.98,8.36-11.78,12.69-.76-.27-.87-.66-.83-1.36,.08-5.73,1.19-11.38,1.63-17.07-.99-.2-1.5,.62-2.14,1.19-3.57,3.63-6.8,7.59-10.58,10.99-.13,.08-.58-.04-.62-.21-.01-.86-.07-1.72,.02-2.57,.66-5.25,.99-10.55,1.99-15.75-.04-.57,.66-2.31-.17-2.35-1.3,.21-2.06,1.62-3.06,2.4-2.72,2.67-5.41,5.36-8.13,8.04-.56,.37-1.3M 7,1.64-2.03,.9,.05-1.18,.02-2.36,.2-3.53,.92-6.09,1.9-12.18,2.85-18.27-.02-.61,.43-1.99-.54-1.88-3.79,2.74-6.91,6.32-10.44,9.4-.61,.57-1.29,1.09-1.96,1.62-.05,.04-.25-.03-.37-.07-.1-.04-.25-.11-.26-.18-.31-1.74,.11-3.46,.41-5.16,4.86-5.65,10.11-11,15.69-16-.47,2.2-.93,4.4-1.39,6.6-.04,.35-.16,.96,.17,1.17,.63,.17,1.38-.7,1.88-1.03,3.35-2.96,6.67-5.93,10.01-8.89,.6-.4,1.32-1.41,2.04-1.42,.17,.13,.44,.31,.42,.44-1.47,7.12-3.16,14.17-4.13,21.37-.11,.47-.29,1.82,.4,1.68,.24-.08,.54-.11,.69-.25,4-3.78,7.86-7.69,11.96-11M .37,.14-.09,.91-.17,.86,.25-1.06,6.61-2.5,13.19-3.28,19.83,.22,1.36,1.59-.26,2.08-.64,17.18-16.91,11.72-13.94,9.92,6.2,.26,1.5,1.74-.24,2.31-.8,3.76-3.65,7.28-7.55,11.23-11,.16-.1,.84-.2,.91,.15-.08,1.18-.12,2.36-.27,3.54,.07,1.38-2.54,12.74-.31,11.58,5.38-4.92,10.22-10.28,15.83-15.08,.64-.46,2.5-2.45,2.48-.58-.8,3.95-.67,7.95-1.22,11.91-.09,.41,.13,.8,.29,1.17,.83,.4,1.96-1.25,2.65-1.72,4.57-4.24,9.15-8.49,13.73-12.72,.89-.62,1.79-2.1,2.97-1.87,.33,.78-.06,1.96-.02,2.85-.24,2.79-.5,5.58-.74,8.37-.08,.42,.16,1.16,.M 58,1.04,.23-.06,.52-.1,.68-.23,3.53-2.96,7.03-5.95,10.57-8.91,2.42-2.02,4.88-4.02,7.34-6.01,.36-.29,.85-.49,1.29-.71,.09-.04,.36,.01,.38,.06,.39,3.22-.66,6.61-.79,9.9-.01,.61-.04,1.58,.82,1.43,6.34-4.8,12.2-10.03,18.85-14.6,.8-.5,1.4-1.2,2.48-1.01-.3,3.35-.8,6.63-.69,10,.36,1.44,1.85,.02,2.59-.49,5.05-3.89,10.42-7.48,15.8-11.07,1.37-.87,2.65-1.88,4.11-2.6,1.14-.37,.96,.92,.97,1.61-.13,2.26-.29,4.52-.41,6.78-.03,.49-.31,1.12,.48,1.41,.58,.22,.98-.21,1.38-.46,3.22-1.95,6.44-3.9,9.63-5.89,4.41-2.61,8.8-5.51,13.56-7.57M ,.12-.05,.56,.17,.59,.31,.29,2.87-.27,5.8-.29,8.68-.03,.61,.73,.88,1.42,.52,7.96-4.3,15.98-8.39,24.38-12.07,.9-.24,2.92-1.7,3.31-.33-.16,2.79-.35,5.59-.49,8.39,.18,1.63,3.39-.45,4.34-.63,9.34-3.84,18.82-7.57,28.51-10.75,2.85-1.4,2.47,.91,3.4,2.84,.76,1.84,1.51,3.68,2.31,5.51,.36,1.16,1.88,.72,2.86,.37,2.71,2.97,5.24,5.99,7.62,9.06-.83,.24-1.65,.5-2.48,.75-2.74,.84-2.76,.83-1.51,2.95,1.37,2.21,2.59,4.54,4.09,6.66,.27,.23,.62,.4,1.05,.3,1.81-.44,3.59-1,5.37-1.51,2.05,3.13,3.96,6.3,5.73,9.53-.95,.47-5.83,.76-4.94,2.25M ,2.16,2.66,4.41,5.36,6.58,8Z"/><path class="cls-2" d="M921.72,455.43c-.07,1.1-1.71,.89-2.51,1.13-9.56,1.29-19.21,2.34-28.68,4.07-1.85-3.44-3.83-6.83-5.93-10.18,11.2-2.02,22.49-4.21,33.86-5.3,1.1,3.42,2.42,6.78,3.26,10.28Z"/><path class="cls-2" d="M637.75,1092.25c.55,.13,1.06,.02,1.54-.19,3.79-1.63,7.59-3.24,11.37-4.9,5.67-2.48,11.16-5.2,16.67-7.9,.27-.09,1.23-.46,1.3,.02-2.6,5.81-6.35,11.13-9.39,16.75-.28,.36,.26,.65,.6,.55,9.34-3.97,18.17-9.61,27.54-13.23,.11,.17,.3,.41,.23,.55-.5,.99-1.03,1.98-1.61,2.95-2.77,4.66M -5.56,9.32-8.34,13.98-.34,.58-.61,1.18-.89,1.78-.03,.06,.1,.19,.2,.26,.33,.19,.75-.06,1.06-.17,4-1.99,8.03-3.93,11.98-5.99,4.06-2.12,8.02-4.35,12.04-6.52,.99-.52,2.52-1.12,1.5,.73-3.72,6.73-7.96,13.18-11.99,19.73-.12,.29-.33,1.01,.12,1.07,8.46-3.75,16.48-8.54,24.72-12.77,.59-.31,1.22-.43,1.86-.06l-.11-.03c-4.74,8.2-10.09,16.11-14.94,24.3-.13,.36,.58,.47,.74,.42,7.64-3.79,15.17-7.74,22.62-11.84,1.56-.74,3.57-2.02,1.88,.86-4.72,7.97-9.91,15.75-15.07,23.55-2.57,3.81-2.51,4.16,1.72,2.01,7.33-3.42,14.51-7.73,21.93-10.69M ,.49,.74-.37,1.39-.67,2.05-6.44,10.42-13.69,20.45-20.45,30.76,0,.13,.37,.39,.53,.34,.75-.23,1.51-.43,2.22-.72,5-2.1,9.99-4.22,14.99-6.33,.58-.18,3.46-1.77,3.03-.31-4.38,6.82-9.11,13.42-13.7,20.11-3.28,4.7-6.67,9.34-10,14.01-.51,1.09-2.3,2.23-1.4,3.46,0-.23-.06-.32-.29-.36l.28,.3c6.75-2.43,13.49-4.86,20.25-7.27,.16-.06,.47,.11,.68,.21,.06,.03,.06,.2,.02,.28-.67,1.56-1.82,2.88-2.74,4.31-8.85,12.94-18.58,25.41-27.86,38.19,.13,.94,2.14-.03,2.78-.07,6.35-1.76,12.62-3.81,19.02-5.38,.88,.17,.22,1.08-.06,1.56-2.84,3.91-5.6M 9,7.82-8.55,11.72-8.45,11.52-17.24,22.87-26.3,34.09-.5,.62-1.16,1.2-1.16,2.01,.64,.35,1.32,.23,1.96,.1,2.35-.47,4.69-.97,7.04-1.44,4.3-.88,8.61-1.74,12.92-2.61,.46-.15,1.14-.21,1.49,.07,.11,.14,.05,.43-.07,.6-.58,.85-1.17,1.7-1.81,2.52-6.41,8.23-12.79,16.47-19.24,24.67-7.43,9.62-15.43,18.91-23.08,28.44-.08,.28,0,.76,.43,.7,2.4-.23,4.81-.45,7.21-.71,5.21-.52,10.4-1.27,15.61-1.69,1.32-.21,2.02,.37,.95,1.47-17.51,21.6-34.69,43.52-53.74,63.85-8,.28-16.1,.05-24.12,.12-2.28-.09-3.49,.01-1.31-2.21,10.46-11.17,20.76-22.52,M 30.89-33.97,6.68-7.56,13.25-15.2,19.85-22.8,.86-1.21,2.31-2.13,2.45-3.67-7.67,.36-15.25,1.58-22.9,2.25-.49,0-2.21,.27-1.94-.48,15.33-17.94,31.61-35.31,45.79-54.05-.45-.06-.83-.19-1.15-.13-3.53,.67-7.06,1.39-10.59,2.07-3.92,.75-7.85,1.48-11.79,2.19-.11,.02-.47-.3-.43-.39,11.45-14.73,24.32-28.66,35.52-43.52,1.35-1.7,4.33-4.74-.07-3.42-6.12,1.66-12.23,3.34-18.34,5.01-.62,.17-1.26,.43-1.85,.03,10.25-13.85,22.06-26.87,31.81-41.15-.31-.82-2.12,.2-2.78,.29-5.32,1.81-10.64,3.65-15.96,5.46-.86,.29-1.76,.5-2.66,.73-.08,.02-.M 24-.1-.32-.18-.29-.35,.42-1.05,.61-1.4,7.54-9.57,14.85-19.24,22.02-28.99,1.3-1.76,2.5-3.56,3.73-5.35,.28-.33-.21-.71-.57-.58-7.77,3.17-15.41,6.63-23.13,9.91-1.74,.65-3.8,1.55-1.77-1.07,6.97-9.71,14.42-19.11,20.97-29.1,.3-1.51-3.24,.82-3.84,.9-7.39,3.31-14.64,6.93-22.12,10.05-1.46,.06-.44-.86-.05-1.55,5.68-8.07,11.36-16.14,17.04-24.21,.26-.37,.49-.77,.64-1.17,.05-.14-.17-.35-.31-.6-8.91,3.96-17.46,8.67-26.49,12.35-.14,.02-.47-.24-.4-.41,.55-.86,1.08-1.73,1.68-2.56,4.78-6.87,9.8-13.56,13.86-20.79-.34-.81-1.76,.16-2.3M 3,.34-7.45,3.89-15.25,7.31-22.94,10.86-2.39,1.1-3.42,1.29-1.52-1.42,3.84-5.81,7.69-11.61,11.52-17.42,.3-.45,.79-.88,.59-1.46-.03-.09-.22-.23-.27-.21-.73,.26-1.48,.49-2.17,.82-8.61,4.24-17.49,7.98-26.01,12.35l.12-.05c-1.22-1.12,.78-2.65,1.29-3.75,3.03-4.3,5.86-8.67,8.57-13.1,.41-.67,.77-1.36,1.09-2.06,.07-.15-.14-.38-.24-.61-10.8,4.64-21.64,9.4-32.75,13.66l.02,.08c-.94-1.12,.67-2.21,1.17-3.19,2.93-4.11,5.88-8.22,8.81-12.34,.46-.65,.9-1.32,1.29-2,.08-.14-.08-.37-.17-.55-11.55,3.8-22.96,8.96-34.66,12.88-1.55,.34-5.42,M 2.48-3.03-.79,2.88-4.26,5.77-8.51,8.65-12.78,.25-.37,.41-.79,.58-1.19,.03-.06-.09-.18-.17-.24-.52-.37-1.27,.14-1.83,.24-9.88,3.69-20.05,6.83-30.1,10.22-2.72,.92-5.44,1.88-8.34,2.41-.85-.2-.2-1.08,.08-1.57,2.88-4.25,5.92-8.42,8.59-12.8,.08-.13,0-.43-.14-.53-1.28-.41-2.85,.57-4.16,.79-12.21,3.68-24.51,7.17-36.97,10.3-.96,.17-1.83,.64-2.78,.07,2.48-4.67,5.95-8.83,8.29-13.57-.26-.78-1.81-.17-2.41-.11-14.79,3.56-29.71,7.15-44.81,9.61-1.44-.14-.25-1.4,.05-2.08,2.06-3.51,4.26-6.95,6.26-10.49,.13-.29,.25-.71,.08-.92-.74-.6M 7-2.12-.08-3.05-.03-10.74,2.07-21.61,3.58-32.48,5.08-5.45,.66-10.88,1.64-16.37,1.91-1.48-.24,.14-1.98,.37-2.75,1.68-3.05,3.4-6.09,5.08-9.15,.21-.5,.73-1.39,.03-1.69-3.72-.26-7.48,.57-11.21,.75-8.42,.87-16.9,1.28-25.34,1.87-6.44,.54-12.92,.5-19.36,.91-1.08,.12-3.39,.16-2.61-1.31,1.81-4.04,4.2-7.88,5.63-12.07,.07-.26-.33-.69-.67-.7-1.07-.04-2.14-.09-3.21-.09-21.4,.13-42.84-.14-64.19-1.77l.13,.12c1.82-4.49,3.64-8.98,5.46-13.48,.18-.48,.29-1.26-.37-1.4-6.49-.91-13.06-1.28-19.58-1.97-19.82-1.95-39.52-4.81-59.2-7.82l.09,M .1c1.68-5.4,2.84-10.98,4.89-16.25l-.13,.07c26.58,4.42,53.27,8.92,80.17,10.99l-.15-.14c.13,.66-.12,1.27-.35,1.9-1.45,4.22-3.32,8.36-4.42,12.67,6.76,1.54,14,1.03,20.93,1.74,14.11,.77,28.26,1.12,42.4,1.17,1.21,.25,5.47-.79,4.53,1.44-1.38,3.15-2.83,6.27-4.2,9.42-1.46,2.98-1.32,2.98,2.53,2.95,8.36-.07,16.69-.49,25.02-.96,9.14-.43,18.26-1.19,27.35-2.02,4.51-.66,3.94,.04,2.55,2.84-1.52,3.11-3.26,6.13-4.76,9.25-.78,1.55,1.86,1.04,2.79,.99,4-.47,8-.9,11.98-1.43,12.33-1.64,24.62-3.54,36.88-5.58,1.7-.04,.6,1.46,.23,2.25-1.88,M 3.56-4.07,6.99-5.76,10.65-.13,.29,.31,.6,.75,.52,4.32-.81,8.66-1.56,12.95-2.47,11.03-2.39,22.07-4.69,32.99-7.5,.22-.05,.5,.04,.74,.09,.66,.23-.13,1.3-.35,1.74-1.96,3.83-4.8,7.55-6.29,11.48,1.03,.62,2.27-.23,3.37-.34,10.15-2.54,20.13-5.46,30.09-8.44,3.14-.94,6.3-1.87,9.46-2.78,.18-.05,.47,.12,.69,.22,.17,.34-.17,.85-.31,1.2-2.24,3.8-4.57,7.56-6.85,11.34-.36,.6-.61,1.2-.12,1.81,.04-.22,.03-.34-.19-.43l.2,.38c13.27-4.37,26.52-8.93,39.61-13.72,.2,.23,.5,.42,.46,.54-.17,.51-.37,1.03-.67,1.5-2.26,3.67-4.55,7.33-6.82,10.9M 9-.36,.57-.66,1.17-.97,1.76-.03,.06,.05,.19,.12,.26,.46,.42,1.29-.1,1.83-.19,6.17-2.15,12.22-4.51,18.23-6.94,5.53-2.23,11.04-4.49,16.57-6.72,.46-.19,.99-.38,1.53,.11-2.81,4.89-6.01,9.6-9,14.39-.31,.48-.64,.95-.4,1.52-.4-.21-.68,.27-.28,.39,.29-.01,.39-.15,.3-.38Z"/><path class="cls-2" d="M1021.54,1215.4s-.02-.02-.02-.03c.03,.01,.06,0,.09,0h0s-.07,.03-.06,.03Z"/><path class="cls-2" d="M1386.95,984.85c-18.73-22.69-37.35-45.51-56.9-67.51-.87-.35-.67,.88-.67,1.4,.93,6.85,1.92,13.7,2.83,20.55,.02,.17-.12,.37-.22,.55-.09M ,.16-.74-.07-1.02-.39-8.93-10.24-17.75-20.57-26.73-30.79-6.66-7.58-13.44-15.09-20.18-22.63-.7-.78-1.47-1.53-2.24-2.27-.11-.1-.44-.07-.67-.05,1.27,7.93,3.6,16.11,5.05,24.15-.11,1.4-2.15-1.08-2.53-1.43-13.41-14.74-26.76-29.52-40.55-43.94-.29-.3-.51-.96-1.15-.68-.49,.22-.17,.8-.09,1.21,2.08,7.79,4.29,15.56,6.39,23.34,.61,3.54-2.15-.25-3.09-1.03-11.44-11.95-22.72-24.21-34.83-35.63-.9-.4-.42,.95-.33,1.4,2.4,7.84,4.81,15.68,7.21,23.52,.09,.7,.85,1.98-.02,2.3-.07,.04-.29,0-.36-.08-.79-.73-1.59-1.46-2.34-2.22-9.25-9.39-18.M 68-18.67-28.33-27.81-.65-.48-1.22-1.34-2.04-1.47-.08,.02-.19,.16-.18,.24,2.68,9.56,6.32,18.89,8.98,28.46-.04,.42-.73,.25-.91,.14-3.15-2.95-6.26-5.93-9.41-8.88-5.78-5.4-11.57-10.79-17.37-16.18-.53-.49-1.13-.92-1.73-1.35-.28-.2-.5-.15-.61,.27,2.84,9.21,6.11,18.41,9.09,27.59,1.23,3.74-1.43,1.08-2.7-.04-6.68-5.91-13.35-11.84-20.03-17.75-1.05-.84-1.89-1.94-3.24-2.33-.37,1.17,.54,2.33,.77,3.49,2.78,8.54,5.57,17.08,8.33,25.62,.23,.73,.34,1.48,.48,2.22,.02,.07-.11,.2-.21,.25-.11,.05-.32,.07-.39,.02-.67-.52-1.34-1.05-1.98-1M .6-6.15-5.14-12.28-10.29-18.43-15.42-.64-.54-1.41-.98-2.13-1.45-.07-.05-.27-.03-.35,.02-.1,.05-.21,.18-.2,.27,.33,2.36,1.33,4.6,2.01,6.9,2.43,8.16,4.92,16.32,7.37,24.48,.11,.44,.3,1.49-.48,1.15-6.22-4.55-12.12-9.5-18.24-14.19-.51-.27-2.52-2.09-2.72-1.14,1.19,6.47,3.6,12.8,5.19,19.22,1.19,4.31,2.34,8.63,3.46,12.95,.16,.61,.11,1.27,.13,1.9,0,.07-.14,.17-.24,.2-.83,.05-1.52-.86-2.23-1.23-4.88-3.56-9.74-7.13-14.62-10.69-.68-.36-1.49-1.23-2.26-1.22-.17,.13-.43,.32-.4,.44,.38,1.7,.8,3.39,1.2,5.08,2.33,10.37,5.12,20.67,7.M 1,31.12,.06,.44-.63,.39-.84,.32-4.48-2.8-8.72-5.95-13.12-8.85-.38,4.89-.9,9.84-1.55,14.81,1.34,7.05,2.66,14.11,3.64,21.22,.34,1.39-.74,1.6-1.7,.85-1.67-1.1-3.38-2.1-5.07-3.16-1.81,8.95-4.1,17.91-6.94,26.75,.37,3.16,.7,6.32,1.04,9.48-.06,1.99-3.12-.6-4-.88-3.23,8.79-7.07,17.43-11.62,25.76,.18,4.93,.45,9.95,.44,14.87-.62,.36-1.11,.26-1.59,.03-2.02-.96-4.05-1.91-6.07-2.86-3.08,4.68-6.42,9.21-10.04,13.55-.4,11.46-.37,22.96-1.28,34.4-.11,1.27-.49,1.42-2.06,.83-4.6-1.79-9.17-3.63-13.77-5.42-.5-.11-1.93-.78-2.12-.08-.22,1M .28-.51,2.55-.62,3.83-1.45,17.86-3.27,35.68-5.85,53.41-.38,3.73-.51,3.31-4.51,2.11-4.82-1.33-9.51-3.17-14.41-4.16-.19-.02-.58,.17-.63,.32-1.33,4.35-1.6,8.94-2.57,13.39-3.42,18.24-7.37,36.37-11.72,54.42-.15,.86-.5,1.94,.72,2.22,6.87,1.3,13.62,3.68,20.57,4.31-.48-.46-.35-.99-.24-1.5,.73-3.4,1.51-6.78,2.21-10.18,3.33-16.67,6.4-33.38,9.01-50.17,.36-2.13,.67-4.27,1.01-6.4,.07-.38,.75-.68,1.25-.56,5.67,1.58,11.24,3.57,16.81,5.47,1,.34,1.62,.08,1.71-.69,.17-1.39,.29-2.79,.48-4.18,.56-4.18,1.14-8.35,1.37-12.55,1.4-13.94,2.M 49-27.92,3.4-41.88,.76-.92,2.27,.25,3.18,.47,4.03,1.74,8.05,3.5,12.07,5.24,1.94,.67,3.33,1.98,3.45-1.08,.75-16.45,.38-32.95,.4-49.41,.02-.65,.11-1.61,1.06-1.29,5.5,2.69,10.87,5.64,16.38,8.27,.3,.12,.9-.15,.89-.42-.08-1.83-.17-3.65-.26-5.48-.39-13.68-1.87-27.31-2.62-40.95,.39-.98,1.6-.12,2.21,.21,4.08,2.47,8.15,4.95,12.22,7.43,.96,.38,3,2.59,3.79,1.3-.7-8.92-2.01-17.79-3.12-26.67-.54-5.24-2.01-10.45-2.03-15.7,.64-.66,1.65,.39,2.27,.67,4.43,2.98,8.85,5.97,13.28,8.96,4.43,3.47,2.98,.47,2.65-2.89-1.59-9.17-3.33-18.32-5M .07-27.47-.4-2.12-.82-4.25-1.21-6.38-.12-.6-.1-1.2,.29-1.74,0,.04,0,.07-.02,.1,.02-.05,.05-.12,.08-.18h-.01l-.03,.03s0-.03,.01-.05l.02,.02s.02-.03,.03-.05c-.01,.02-.02,.03-.02,.05,5.74,4.57,11.77,8.8,17.62,13.25,.49,.36,.96,.83,1.63,.58,.08-.02,.18-.19,.17-.28-.34-1.81-.65-3.62-1.05-5.42-2.28-10.28-4.57-20.57-7.07-30.8,.08-1.33,2.38,.83,2.87,1.12,5.31,4.28,10.61,8.57,15.93,12.85,.69,.54,1.44,1.55,2.5,1.45,.3-.28,.12-.86,.08-1.23-2.72-10.65-5.34-21.31-8.42-31.9-.68-2.97,1.44-.75,2.53,.02,5.88,5.04,11.74,10.1,17.61,1M 5.14,.78,.51,1.78,1.8,2.67,1.83,.41-.13,.26-.82,.23-1.14-2.79-9.75-5.6-19.5-8.39-29.26-.92-3.53,.46-2.04,2.27-.64,6.41,5.82,12.81,11.65,19.2,17.48,1.32,1.08,2.13,2.43,3.87,2.95-1.41-7.05-4.04-13.87-5.92-20.83-.87-3.47-2.56-6.79-2.84-10.35,0-.04,.26-.15,.29-.13,8.95,7.67,17.09,16.36,25.75,24.39,.83,.61,1.4,1.86,2.55,1.83,.06,0,.2-.19,.18-.27-2.46-9.28-5.56-18.4-8.25-27.62-1.14-3.99,2.8,.57,3.75,1.37,9.39,9.16,18.28,19.25,27.93,27.94,.78-.29,.38-1.08,.29-1.67-2.28-7.98-4.57-15.95-6.84-23.92-1.46-4.95,2.14-.34,3.47,.8M 8,10.19,10.69,20.26,21.49,30.39,32.25,.8,.67,1.31,1.91,2.42,2.04,.09,0,.3-.33,.27-.48-.55-2.33-1.11-4.65-1.71-6.97-1.4-5.48-2.83-10.96-4.22-16.45-.21-.81-.52-1.65-.17-2.49,.6-.06,.92,.28,1.22,.61,3.37,3.63,6.77,7.25,10.07,10.92,9.44,10.49,18.84,21.01,28.26,31.52,.75,.71,1.16,1.69,2.37,1.7-1.08-7.4-3.01-14.66-4.4-22-.09-.87-.46-1.93-.16-2.53,1.1-.06,1.67,1.25,2.42,1.89,14.78,16.59,29.12,33.34,43.36,50.28,.49,.56,2.18,2.87,2.36,1.16-.86-6.75-1.73-13.5-2.6-20.24-.75-3.7,1.71-.8,2.72,.43,17.54,20.16,33.9,41.45,51.26,61M .48,.19-.1,.51-.25,.51-.38,.05-6.57,.07-13.14,.09-19.71,.01-.54-.15-1.06-.54-1.52Zm-137.2-93.73c.16-.15,.22-.14,.2,.05-.07-.02-.14-.04-.2-.05Z"/><path class="cls-2" d="M322.27,493.7c.31-.51,.23-1.05,.13-1.58-.38-2.02-.73-4.05-1.16-6.07-1.48-7.01-2.77-14.04-3.91-21.09-.52-3.31-1.34-6.58-1.65-9.93-.13-1.33,1.01-1.06,1.61-.46,5.49,3.64,10.76,7.64,16.48,10.9,.1,.05,.58-.17,.58-.26,0-.96,.02-1.94-.15-2.89-.98-5.55-1.64-11.12-2.33-16.7-.78-7.64-2.63-15.53-2.52-23.1,1.03-.28,1.85,.66,2.72,1.07,4.29,2.61,8.58,5.22,12.87,7.M 83,.7,.32,1.61,1.21,2.36,.63-.32-14.93-2.48-30.1-2.61-45.14-.17-2.76,1.44-1.65,3.02-.8,4.81,2.32,9.41,5.17,14.36,7.18,1.04-.03,.67-1.49,.8-2.2,0-16.38-.37-32.76,.49-49.12,.02-2.38,1.9-1.08,3.25-.62,4.15,1.79,8.28,3.61,12.43,5.39,.78,.19,2.22,1.14,2.85,.41,1.15-14.49,2.08-29.04,3.58-43.52,.72-5.22,.85-10.61,2.03-15.72,.88-.77,2.31,.42,3.3,.51,5.14,1.51,10.13,3.74,15.37,4.83,.64,.04,.9-.71,.97-1.22,.76-4.7,1.49-9.4,2.27-14.1,2.17-13.81,4.75-27.53,7.51-41.23,.7-3.94,1.95-7.8,2.35-11.79,.01-.16-.27-.34-.42-.51l-.06,.02M c6.36,.36,12.47,2.63,18.71,3.81,3.38,.8,3.33,.35,2.69,3.21-4.61,19.32-8.87,38.72-12.42,58.26-.65,2.96-.75,6.04-1.69,8.93-.54,.84-1.75,.18-2.52,.06-4.17-1.23-8.33-2.48-12.5-3.71-1.19-.13-3.52-1.75-4.2-.25-1.28,7.33-1.93,14.78-2.94,22.16-1.81,12.4-2.36,24.93-3.9,37.34-.04,.24-.68,.5-.97,.4-5.42-1.84-10.61-4.26-16.01-6.15-1.04-.17-1,1.01-1.07,1.72-.24,4.74-.5,9.47-.69,14.21-.36,11.31-.77,22.62-.58,33.93,.03,3-.03,3.32-.58,3.34-1.46,.05-2.45-.78-3.58-1.29-3.75-1.7-7.43-3.49-11.15-5.24-.67-.19-1.94-1.13-2.32-.14,0,8.08,M .44,16.16,.97,24.21,.47,7.42,.94,14.85,1.41,22.27-.12,1.89-2.46-.18-3.3-.41-4.5-2.33-8.81-5.04-13.42-7.14-.12-.04-.52,.16-.58,.3-.13,.29-.17,.63-.14,.94,1.24,11.06,2.25,22.12,4.01,33.12,.38,2.86,1.06,5.74,.97,8.62-.67,.21-1.14,.02-1.58-.25-4.18-2.55-8.35-5.11-12.52-7.66-1.08-.49-2.09-1.72-3.32-1.58-.18,.07-.36,.32-.35,.49,.11,2.38,.57,4.72,.97,7.06,1.19,6.5,2.4,12.99,3.6,19.49,.75,4.05,1.49,8.09,2.2,12.14,.02,.13-.27,.31-.45,.44-5.27-2.49-10.72-7.18-15.84-10.38-.72-.33-1.78-1.66-2.4-.61,1.28,6.45,2.88,12.93,4.32,19M .39,1.3,5.61,2.69,11.21,4.02,16.81,.03,.13-.21,.32-.36,.45-1.2-.06-2.16-1.27-3.18-1.86-4.77-3.5-9.53-7-14.29-10.49-.51-.25-1.04-.94-1.63-.82-.68,.37-.35,1.13-.26,1.74,.88,3.37,1.75,6.75,2.69,10.11,1.96,7.04,3.96,14.07,5.94,21.11,.15,.52,.29,1.05-.04,1.64-1.48-.29-2.5-1.51-3.7-2.33-5.19-4.08-10.38-8.16-15.57-12.24-.57-.44-1.05-1-2.1-1.06,2.55,10.48,6.12,20.75,9.27,31.09,.99,3.74-1.7,.74-3.01-.15-6.24-5.22-12.46-10.45-18.7-15.67-.36-.3-.63-.71-1.24-.72-.1,0-.29,.09-.29,.14,.02,.53-.04,1.07,.11,1.58,1.13,3.66,2.28,7.3M 1,3.47,10.96,1.91,5.83,3.86,11.65,5.79,17.48,.14,.41,.26,.82-.08,1.26-1.2-.37-2.03-1.33-2.96-2.1-6.42-5.67-12.83-11.35-19.24-17.03-1.25-.89-2.2-2.45-3.72-2.84-.22-.03-.38,.44-.26,.81,.36,1.15,.72,2.3,1.1,3.44,2.66,8.01,5.32,16.02,7.99,24.03,.17,.52,.44,1.02,.17,1.56-.59,.01-.99-.26-1.35-.58-1.79-1.61-3.61-3.2-5.36-4.84-6.02-5.66-12.01-11.35-18.03-17.02-1.31-1.23-2.65-2.44-4-3.64-.12-.11-.45-.08-.69-.07-.36,.28,0,1.13,.08,1.55,2.74,8.44,5.49,16.88,8.24,25.31,.11,.58,.62,1.31-.09,1.67-.68-.07-1.21-.86-1.75-1.25-10.61M -9.87-20.55-20.32-30.99-30.22-.9-.4-.42,.99-.34,1.43,2.43,7.95,4.88,15.89,7.31,23.84,.09,.53,.42,1.42,.14,1.85-1.15,0-1.77-1.2-2.59-1.84-10.78-10.76-21.33-21.68-31.71-32.69-1.4-1.28-2.24-2.97-4.13-3.65,1.84,8.77,4.81,17.28,6.92,26-.15,1.42-2.38-1.36-2.82-1.68-13.86-14.44-27.13-29.27-40.6-43.92-.12-.12-.47-.11-.72-.12-.04,0-.14,.19-.14,.28,.97,8.11,3.92,15.88,4.84,24.01-1.91-.53-2.73-2.34-4.08-3.6-9.9-11.16-19.82-22.3-29.68-33.49-5.04-5.72-9.95-11.53-14.92-17.29-.55-.51-1.03-1.56-1.91-1.44-.34,.19-.32,.8-.26,1.16,.6M 6,4.71,1.33,9.42,1.99,14.13,.31,2.25,.62,4.5,.89,6.75,.02,.14-.2,.42-.34,.43-.23,.03-.59-.05-.72-.18-.73-.77-1.43-1.56-2.12-2.36-6.54-7.64-13.16-15.25-19.61-22.95-11.25-13.42-22.4-26.9-33.59-40.35-.93-1.23-2.36-2.39-2.31-4.03,0-6.36,0-12.71,0-19.07,0-.44,.37-.82,.62-.66,3.21,2.78,5.49,6.67,8.36,9.85,14.33,17.6,28.83,35.12,43.62,52.48,.6,.71,1.29,1.36,1.96,2.03,.12,.09,.59-.03,.62-.21-.43-5.7-1.28-11.36-2.01-17.02,0-1.12-1.77-7.48,.89-4.71,14.36,17.01,28.74,33.88,43.59,50.55,.96,.99,1.57,2.17,2.97,2.66-.8-7.27-2.99-M 14.46-4.28-21.71-.13-1.03-.61-2.15-.07-3.12,.14-.26,.4-.15,.91,.42,4.62,5.17,9.2,10.36,13.86,15.51,8.76,9.53,17.26,19.34,26.23,28.69,.28,.27,.72-.08,.76-.28-.58-2.43-1.17-4.86-1.79-7.29-1.45-5.7-2.92-11.39-4.37-17.09-.12-.45-.48-1.66,.31-1.64,11.76,11.72,22.88,24.26,34.54,36.17,.47,.49,.83,1.13,1.88,1.19-2.28-9.55-5.5-18.83-7.85-28.42,1.45,.23,1.86,1.2,2.84,2.05,8.34,8.46,16.67,16.93,25.02,25.38,1.33,1.35,2.78,2.63,4.19,3.93,.06,.06,.27,.05,.38,.02,.1-.03,.25-.15,.24-.21-.18-.84-.33-1.69-.58-2.52-2.5-8.27-5.02-16.5M 3-7.52-24.79-.16-.52-.21-1.06-.29-1.6-.01-.09,.07-.26,.16-.28,1.03-.31,1.77,1.13,2.54,1.66,7.68,7.37,15.35,14.74,23.03,22.1,.92,.67,1.64,2.01,2.88,2.02,.05,0,.18-.19,.16-.28-.81-2.72-1.64-5.44-2.44-8.16-2.18-7.33-4.35-14.66-6.5-22-.06-.19,.06-.41,.1-.61,.92,.09,1.5,.65,2.09,1.27,3.88,3.58,7.74,7.18,11.66,10.74,3.47,3.16,7,6.27,10.51,9.39,.36,.25,.84,.73,1.32,.58,.1-.05,.2-.19,.18-.28-.51-1.89-1.04-3.78-1.58-5.66-2.37-8.93-5.41-17.8-7.44-26.77,.31-.9,2.1,1.11,2.59,1.38,5.88,5.05,11.74,10.1,17.62,15.15,1,.85,3.63,3.2M 3,2.82,.14-3.07-10.7-5.82-21.45-8.5-32.23-.31-1.03,.76-.89,1.32-.41,2.65,2.15,5.25,4.34,7.91,6.48,3.52,2.83,7.07,5.62,10.62,8.42,.37,.2,1.36,.95,1.54,.26-1.4-7.36-3.45-14.59-5.07-21.9-.93-4.02-1.77-8.06-2.62-12.09-.07-.76-.37-1.96-.08-2.53,.25-.03,.59-.09,.74,0,.93,.62,1.82,1.28,2.7,1.94,4.34,3.23,8.67,6.47,13.02,9.69,.93,.54,1.76,1.6,2.93,1.5,0,.22,.05,.23,.14,.04l-.22,.04Z"/><path class="cls-2" d="M811.58,722.43s.07,.03,.1,.04c0,.02-.01,.03-.01,.05l-.09-.09Z"/><path class="cls-2" d="M832.37,731.85c-1.73,4.19-3.48M ,8.35-5.24,12.48-1.99-.99-3.94-2.05-6-2.91-.29-.12-.73,0-1.12,0-1.32,4.17-1.66,8.61-3.05,12.73-.09,.13-.47,.24-.67,.2-2.61-.75-5-2.11-7.53-3.08-2.1-1.01-2.48,.07-2.74,1.83-.62,3.19-1.23,6.39-1.86,9.57-.13,.63-.22,1.3-1.03,1.8-2.98-.79-5.84-2.14-8.84-2.95-.36-.1-.91,.1-.98,.36-.98,4-1.7,8.06-2.59,12.09-.15,1.05-.48,1.82-1.9,1.31-2.76-.75-5.46-1.95-8.29-2.35-.2,.25-.41,.42-.47,.61-1.08,3.88-1.74,7.84-2.65,11.76-.23,.64-.39,1.77-1.29,1.77-1.94,.12-8.92-3.41-9.61-1.23-1.03,4.54-2.69,9.04-3.36,13.6-3.57-.78-7.14-1.58-10M .63-2.6,.01-.01,.01-.03,.02-.04,1.59-4.4,2.34-9.02,3.59-13.53,.49-1.66,7.41,.96,9.05,1.07,1.03,.23,1.63-.02,1.79-.77,.35-1.59,.67-3.18,1.01-4.77,.57-2.66,1.13-5.31,1.7-7.96,.53-.97,2-.3,2.86-.22,2.19,.52,4.37,1.08,6.55,1.62,.31,.08,.95-.16,1.01-.38,1.38-4.33,1.5-9.06,2.87-13.33,.16-.15,.49-.34,.66-.29,2.93,.78,5.81,1.69,8.75,2.43,.85,.13,1.19-.66,1.33-1.32,.67-3.85,1.28-7.68,2.03-11.51,.1-.55,.87-.92,1.51-.72,2.89,.85,5.66,2.07,8.56,2.87,.32,.09,.8-.17,.86-.49,.84-4.15,1.37-8.35,2.55-12.42,.07-.24,.67-.45,.99-.35,2M .58,.87,5.03,2.06,7.54,3.09,.82,.37,2.25,1.02,2.54-.24,.86-3.81,1.45-7.69,2.61-11.43,.08-.27,.68-.51,.97-.38,2.86,1.3,5.69,2.67,8.5,4.09Z"/><path class="cls-2" d="M846.04,696.41c-1.39,3.91-2.82,7.81-4.28,11.68-.01,0-.01-.01-.02-.01-.17-.09-.48,.02-.74,.04-1.85,3.68-1.87,7.54-3.87,11.24-3.6-1.17-6.61-3.43-10.17-4.67-.44-.16-1.15,.15-1.25,.55-.4,1.58-.78,3.17-1.16,4.75-.72,2.15-.73,4.89-1.99,6.72-3.72-1.03-7.23-2.9-10.88-4.24,.87-4.01,1.72-8.03,2.57-12.04,.12-.58,.8-.81,1.55-.52,2.76,1.09,5.51,2.26,8.26,3.4,1.4,.55,1M .9,.55,2.24-.74,.76-2.95,1.59-5.89,2.38-8.83,.17-.64,.32-1.27,1.11-1.8,3.7,1.32,7.02,3.67,10.72,4.94,.82,.05,.96-.89,1.21-1.46,.99-2.68,1.97-5.36,2.97-8.05,.15-.57,.67-1.38,1.35-.96Z"/><path class="cls-2" d="M964.37,753.62c.01-.05,.01-.11,.01-.15h.14l-.15,.15Z"/><path class="cls-2" d="M1387.34,675.7c-.03-1.77-2.28-2.36-3.48-3.32-6.16-3.85-12.29-7.72-18.49-11.52-21.26-13.11-42.81-25.53-64.79-37.55-2.89-1.58-5.81-3.12-8.72-4.68-.55-.3-1.1-.63-1.84-.49-.29,2.49,.65,5.14,.81,7.67,.29,3.62,1.45,7.29,1.18,10.91-.59,.74-2M .61-.89-3.35-1.16-10.69-6-21.5-11.88-32.42-17.62-15.02-7.79-30.24-15.54-45.74-22.55-.21-.05-.85,.06-.82,.41,1.07,4.78,2.5,9.47,3.78,14.2,.17,.86,.93,2.94-.74,2.4-22.5-10.82-44.93-21.61-68.3-30.64-.65,.72-.17,1.42,.06,2.21,1.32,3.28,2.68,6.55,4.01,9.82,.35,.97,2.1,4.18,.14,3.63-18.64-7.93-37.44-15.41-56.7-21.94-3.18-1.04-1.23,1.26-.59,2.72,1.76,3.39,3.62,6.72,5.34,10.12,.12,.25,.32,.67,.11,.89-.23,.08-.53,.22-.71,.16-4.56-1.59-9.12-3.18-13.67-4.8-11.08-3.93-22.41-7.37-33.8-10.67-.62-.17-1.28-.26-1.93-.36-.08-.01-.3,M .13-.3,.19,.03,.31,.01,.65,.18,.91,2.34,3.93,5.62,7.65,7.46,11.73-.22,.11-.51,.28-.69,.23-2.54-.7-5.07-1.43-7.59-2.18-10.22-3.03-20.55-5.83-31.03-8.26-1.15-.26-2.34-.42-3.52-.61-.1-.02-.27,.07-.34,.15-.29,.53,.63,1.22,.83,1.71,2.24,2.95,4.49,5.89,6.73,8.83,.27,.36,.44,.73,.25,1.14-.96,.2-1.83-.08-2.72-.3-11.04-2.77-22.26-5.36-33.55-7.09-.18,0-.74,.36-.53,.64,2.92,3.36,5.97,6.62,8.78,10.06,.06,.07,.08,.26,0,.3-.62,.49-1.51,.21-2.22,.11-8.45-1.85-17.11-2.93-25.7-4.23-1.12-.08-2.48-.34-3.55-.08-.29,.93,.92,1.49,1.41,2M .17,2.38,2.34,4.82,4.63,7.16,7.01,.17,.24,.62,.54,.39,.85-.15,.13-.37,.34-.53,.33-3.07-.32-6.14-.62-9.2-1.02-5.7-.59-11.48-1.41-17.2-1.46-.25,.5,.04,.84,.41,1.17,2.78,2.49,5.55,4.98,8.32,7.48,.29,.37,1.1,.83,.99,1.3-.64,.72-1.72,.24-2.57,.28-6.18-.46-12.36-.78-18.56-.89-.64,0-1.46-.2-1.85,.32-.45,.59,.35,.94,.76,1.31,.62,.57,1.31,1.09,1.96,1.63,2.15,1.79,4.3,3.57,6.44,5.36,.37,.41,1.34,1.1,.61,1.55-6.4,.22-12.93-.37-19.3,.53-.4,.26,.22,.85,.42,1.08,3.09,2.55,6.21,5.08,9.32,7.63,.36,.29,.88,.56,.75,1.05-.15,.58-.83,M .44-1.31,.47-5.15,.41-10.49,.46-15.56,1.34-.24,.57,.08,.9,.47,1.22,3.43,2.87,7.1,5.52,10.37,8.59,.21,.19-.04,.74-.37,.79-1.98,.31-3.96,.59-5.94,.93-2.5,.42-4.99,.87-7.49,1.32-.61,.11-.84,.62-.45,.96,3.92,3.42,7.96,6.73,11.9,10.12,.55,.46,1.23,.86,1.38,1.61-1.06,1.29-14.02,2.1-12.7,4.04,4.24,3.75,8.57,7.42,12.7,11.28,.22,.21,.23,.55,.37,.89-3.98,1.15-8.02,1.98-11.69,3.63,3.7,4.24,8.28,7.69,12.28,11.69,.42,.4,.89,.8,.74,1.41-3.74,1.01-7.58,2.96-11.36,3.44-3.99-3.59-8.11-7.14-12.16-10.7-.43-.38-.82-.85-1.69-.81-.94,.6M 6-1.9,1.31-2.85,1.97-.84,2.78-1.7,5.56-2.58,8.32,3.19,2.81,6.28,5.61,9.5,8.41,3.76-1.73,6.17-4.81,9.84-6.59,1.17,.38,1.68,1.18,2.36,1.83,6.85,6.57,9.23,9.06,11.06,11.54-3.01,2.13-6.03,4.26-9.06,6.39-.43,.3-1.05,.27-1.41-.09-3.63-3.77-7.3-7.47-11-11.17-.48-.48-.89-1.07-1.96-1.23-2.85,2.33-5.24,5.06-7.83,7.72-2.24-.63-3.7-3.01-5.58-4.37-1.41,4.15-2.85,8.29-4.33,12.4,1,.76,1.43,1.8,2.89,1.97,1.96-2.89,4.09-5.79,6.17-8.63,.28-.39,.97-.4,1.37-.05,3.74,3.64,7.28,7.49,10.93,11.21,.79,.82,.72,1.06-.03,2.01-2.22,2.49-4.17,5M .92-6.59,8.05-.79-.05-1.13-.54-1.53-.96-3.61-3.48-6.53-7.75-10.6-10.66-2.46,2.98-3.83,6.67-6.21,9.7-.39-.07-.69-.2-.94-.36-1.44,3.78-2.89,7.53-4.36,11.25,1.83-3.09,3.02-6.46,5.03-9.6,.42,.12,.9,.14,1.11,.35,3.25,3.12,6.09,6.57,9.14,9.86,.44,.41,1.05,1.31,1.74,.86,2.02-2.48,3.53-5.33,5.33-7.96,.31-.48,.61-.96,1.31-1.17,.8,.26,1.17,.85,1.61,1.38,3.24,3.9,6.44,7.91,9.72,11.77,.78-.06,1.09-.4,1.4-.76,1.53-1.77,3.05-3.55,4.6-5.31,.84-.81,2.28-2.97,3.42-1.54,3.62,4.63,6.93,9.48,10.41,14.22,.28,.39,.59,.7,1.37,.73,1.54-1.M 22,3.09-2.57,4.8-3.78,1.48-1.04,2.47-2.58,4.59-2.98,1.37,1.08,2.05,2.5,2.9,3.82,2.66,4.12,5.26,8.26,7.88,12.38,.36,.57,.59,1.22,1.34,1.54,1.05-.11,1.67-.72,2.42-1.14,2.93-1.41,5.5-3.64,8.6-4.55,.01-.63-.47-1.13-.79-1.65-3.62-5.66-7.02-11.48-11.14-16.81-.19-.24-.76-.32-1.07-.14-2.83,1.66-5.63,3.32-8.47,4.96-.51,.3-.94,.78-1.67,.65-.69-.29-.94-.8-1.27-1.26-3.32-4.72-6.81-9.29-10.36-13.85-.59-.77-1.18-.84-1.9-.27-2.71,2.08-5.22,4.41-8.03,6.35-.16,.09-.61,.07-.73-.04-4.17-4.42-7.9-9.24-11.89-13.82-.07-.07-.03-.2-.05-.4M ,2.38-2.66,5.15-5.13,8.23-7.37,.17-.12,.48-.1,.73-.15,.72,.17,1.01,.68,1.38,1.11,3.91,4.23,7.24,8.91,11.34,12.91,1.53-.06,2.18-1.15,3.23-1.76,2.32-1.29,4.44-2.87,6.82-4.01,1.15-.33,1.76,1.15,2.44,1.82,3.34,4.42,6.67,8.85,10,13.27,.34,.45,.57,.99,1.46,1.2,3.36-.24,6.87-.78,10.28-.84,.5,.02,1.52-.2,1.37-.82-3.45-5.66-7.84-10.76-11.65-16.2-.3-.42-.02-.89,.55-.97,3.72-.56,7.49-.51,11.24-.8,.17-.03,.43-.37,.37-.48-3.57-5.37-8.12-10.13-12.06-15.26-.52-.66-.1-1.22,.95-1.29,3.9-.24,7.8,.04,11.7-.24,.32,0,.6-.5,.42-.74-4.22M -5.31-8.95-10.22-13.35-15.37l-.24-.15c-4.44,.02-8.84,.57-13.25,1.01-.56,.05-.82,.63-.5,1.01,3.45,3.86,7.01,7.64,10.5,11.47,.73,.99,2.05,1.74,1.88,3.11-4.01,.62-8.09,.66-11.88,1.65-.29,.69,.22,1.09,.58,1.52,3.46,4.11,6.95,8.2,10.41,12.31,.51,.62,1.19,1.19,1.23,2.06-2.43,.87-5.22,.92-7.77,1.41-1.33,.14-2.53,.77-4.09,.64-3.66-4.04-7.2-8.27-10.79-12.38-.7-.92-1.81-1.55-1.88-2.79,3.09-.98,6.17-1.6,9.28-2.37,.62-.15,1.29-.27,1.65-.95-3.79-4.45-8.02-8.6-12.06-12.85-.33-.34-.64-.69-.45-1.3,3.62-1.27,7.67-1.57,11.52-2.39,.3M 4-.85-.57-1.37-1.04-1.97-3.87-3.87-7.92-7.58-11.7-11.53-.38-.78,.99-.97,1.53-1.09,3.71-.54,7.42-1.06,11.07-1.58,.42-.45,.25-.83-.11-1.18-3.64-3.47-7.29-6.92-10.94-10.38-.6-.58-1.22-1.15-1.78-1.75-.11-.12,.02-.39,.05-.66,4.67-1.03,9.53-1.16,14.25-1.48,.46-.49,.31-.88-.07-1.23-4.08-3.72-8.12-7.51-12.27-11.16-.46-.44-1.24-1.2-.18-1.51,4.57-.27,9.13-.53,13.7-.79,2.74-.06,2.92-.31,.84-2.21-2.61-2.32-5.26-4.62-7.88-6.94-.45-.39-.83-.84-1.17-1.29-.06-.08,.18-.39,.37-.49,6.27-.41,12.64,.06,18.92,.4,.09-.27,.27-.52,.19-.63-M .43-.54-.88-1.08-1.41-1.56-2.83-2.6-5.82-5.06-8.58-7.74-.13-.14-.17-.42-.09-.58,.08-.15,.38-.32,.59-.32,7,.08,13.95,.89,20.86,1.83,.35,.02,.9,.07,1.17-.11,.03-.19,.11-.47-.02-.59-2.8-2.75-5.63-5.49-8.44-8.24-.49-.48-1.54-.94-1.16-1.56,.52-.83,1.68-.29,2.53-.21,8.12,.66,16.08,2.67,24.17,3.39,.05-.81-.59-1.27-1.08-1.77-2.31-2.38-4.66-4.74-6.99-7.11-.33-.34-.66-.68-.97-1.03-.29-.34-.72-.72-.4-1.11,.13-.16,.77-.13,1.14-.07,8.01,1.42,16.04,2.82,23.91,4.7,1.81,.44,3.64,.78,5.48,1.13,.15,.03,.39-.18,.55-.31,.06-.06,.06-.2M 3,0-.31-1.72-2.05-3.46-4.1-5.19-6.16-1.21-1.42-2.42-2.84-3.6-4.28-.1-.21,.13-.73,.49-.64,10.66,2.14,21.21,4.88,31.6,7.85,1.34,.21,3,1.26,4.23,.6-2.37-4.09-6.15-7.68-8.34-11.71,.18-.12,.46-.29,.64-.25,1.3,.26,2.6,.52,3.87,.87,12.09,3.35,24,7.05,35.78,11.06,.71,.19,1.48,.72,2.18,.23-1.43-3.62-4.43-6.89-6.46-10.33-.45-.66-.85-1.34-1.22-2.04-.08-.15-.03-.44,.1-.54,.16-.11,.52-.16,.72-.09,15.37,4.99,30.74,10.32,45.63,16.47,.83,.35,1.72,.62,2.58,.9,.15,.04,.5-.23,.46-.38-1.84-4.63-4.7-8.89-6.75-13.46-.39-1.41,3.45,.5,4.0M 1,.58,18.39,6.76,36.09,15.37,53.86,22.65,.29-.09,.33-.31,.24-.55-1.1-2.77-2.18-5.54-3.27-8.32-.8-2.05-1.61-4.1-2.39-6.16-.06-.16,.13-.39,.24-.56,.03-.05,.26-.06,.36-.03,23.13,9.44,44.83,21.32,67.05,32.32,.82,.27,.53-.81,.49-1.24-1.42-5.13-2.93-10.28-4.19-15.46,0-.2,.53-.63,.81-.5,5.48,2.44,10.69,5.42,16.03,8.14,21.39,10.99,42.09,23.26,62.83,35.24,.14,.06,.59-.11,.61-.21,.08-.42,.12-.86,.06-1.27-.65-4.5-1.34-8.98-1.99-13.48,.07-.94-1.09-4.35,.81-3.73,30.73,17.42,60.75,36.14,90.03,55.83,1.02,.49,1.79,1.66,2.97,1.37,.M 19-.08,.38-.31,.38-.48,.11-6.57,.04-13.14,.04-19.71Zm-368.62-88.28s.08-.03,.12-.05c0,.19-.04,.21-.12,.05Z"/><path class="cls-2" d="M660.75,307.25s.01,0,.01-.01t.01,.02h-.05s.02,0,.03,0Z"/><path class="cls-2" d="M734.91,352.19c-.71,2.12-2.06,3.99-3.09,5.97-2.72-.22-5.45-.38-8.17-.48,3.23-1.8,6.47-3.58,9.68-5.4,.41-.17,1.41-.8,1.58-.09Z"/><path class="cls-2" d="M751.5,358.19c-.42,.76-.85,1.53-1.28,2.29-1.15-.2-2.31-.39-3.47-.57,1.29-.72,2.67-1.33,4.02-1.97,.12-.05,.44,.15,.73,.25Z"/><path class="cls-2" d="M770.19,363M .17c-.28,.54-.57,1.07-.86,1.61-1.06-.3-2.13-.59-3.2-.86,.82-.18,4.76-3.04,4.06-.75Z"/><path class="cls-2" d="M774.45,53.99c-17.37,22.14-35.49,43.82-51.64,66.74-.13,.21,.32,.68,.65,.67,.94-.04,1.88-.04,2.81-.14,6.81-.7,13.6-1.58,20.42-2.17,.21-.02,.55,.11,.65,.25,.1,.15,.08,.44-.03,.59-1.52,2.04-3.02,4.08-4.6,6.09-13.12,17.17-26.49,34.07-38.17,52.07-.03,.11,.33,.42,.44,.4,2.11-.37,4.21-.75,6.29-1.18,5.09-1.05,10.16-2.13,15.24-3.19,.36-.07,.77-.04,1.15-.03,.08,.01,.19,.13,.22,.22-11.51,17-24.72,33.46-35.56,51.01-.17,M 1.22,4.49-.77,5.31-.86,4.92-1.47,9.83-2.95,14.75-4.41,.64-.12,1.63-.69,2.06,.02-9.53,14.66-20.2,28.88-29.16,43.88-.2,.67,.21,.95,1.1,.63,5.72-2.17,11.43-4.32,17.17-6.48,.72-.27,1.49-.48,2.25-.7,.07-.02,.22,.09,.29,.16,.34,.39-.29,1.04-.47,1.45-4.47,6.76-9.01,13.49-13.4,20.28-3.34,5.16-6.5,10.39-9.73,15.6-1.78,3.01,.3,1.86,2.16,1,5.17-2.31,10.34-4.63,15.52-6.93,.45-.19,.99-.25,1.5-.35,.07-.01,.28,.16,.27,.21-.67,1.9-2.07,3.49-3.08,5.25-5.4,8.31-10.38,16.79-15.42,25.24-1.86,3.29-2.98,4.71,1.78,2.25,5.32-2.45,10.37-5.M 61,15.85-7.65,.07-.02,.3,.15,.28,.2-.12,.4-.22,.82-.44,1.19-2.05,3.4-4.19,6.76-6.18,10.17-3.34,5.76-6.59,11.56-9.86,17.35-.15,.26-.05,.61-.03,.92,0,.05,.2,.17,.25,.15,.37-.12,.75-.23,1.08-.42,6.57-3.75,13.14-7.52,19.73-11.27,.96-.42,2.42-1.48,3.41-1.52,.09,.18,.27,.42,.19,.57-.46,.89-.99,1.76-1.49,2.64-3.98,7.07-7.97,14.13-11.92,21.21-.26,.46-.7,.92-.51,1.49,.03,.08,.22,.2,.26,.18,8.45-4.23,16.25-9.65,24.61-14.09,.16,.26,.4,.47,.35,.59-.32,.7-.68,1.4-1.09,2.07-2.37,4.01-4.53,8.09-6.66,12.18-12.71,.12-25.43,1.44-37.M 89,3.79,2.55-5.02,5.36-9.95,7.7-15.08,.02-.18-.3-.4-.49-.33-5.12,2.46-9.86,5.63-14.82,8.39-1.93,1.09-4.14,2.79-2.33-.91,4.1-8.55,8.53-16.99,13.24-25.33,.42-1.07,1.59-2.09,1.41-3.26-.05-.22-.51-.2-1.04,.07-5.77,2.95-11.46,6.06-17.2,9.06-1.37,.12-.61-.83-.29-1.59,5.93-11.27,12.18-22.3,18.65-33.3,.37-.78-.9-.63-1.31-.41-5.93,2.94-12.21,5.31-17.92,8.62-1.02-1.04,.3-2.25,.69-3.28,6.82-12.72,14.57-25.08,22.03-37.51-.43-.1-.85-.32-1.09-.23-2.58,.93-5.13,1.89-7.67,2.88-3.64,1.42-7.25,2.86-10.87,4.29-.36,.14-.8,.35-1.03,0-.M 15-.23-.1-.63,.05-.89,3.57-6.03,7.09-12.09,10.8-18.06,5.55-9.21,11.74-18.1,17.11-27.4-1.34-.47-2.56,.36-3.87,.64-5.4,1.66-10.8,3.34-16.2,4.99-.5,.16-1.02,.27-1.54,.32-.12,.01-.45-.32-.41-.42,10.23-17.65,22.05-34.6,33.5-51.58,.19-.4,1.19-1.6,.22-1.61-7.36,1.11-14.57,3.04-21.88,4.47-.42,.08-1.04-.13-.88-.67,12.73-20.86,27.51-40.51,41.36-60.66,.13-.24-.06-.45-.37-.47-5.08,.1-10.13,1.12-15.19,1.57-2.4,.28-4.8,.57-7.2,.82-1.65,.35-2.63-.23-1.26-1.71,15.8-22.79,31.93-45.35,48.87-67.33,.21-.28,.47-.53,.63-.83,.6-1.21,2.02M -1.31,3.37-1.26,7.41-.02,14.82-.03,22.24-.03,.66,0,1.33,.09,1.97,.21,.15,.02,.38,.39,.31,.5Z"/><path class="cls-2" d="M792.02,365.6c-.86,1.99-1.92,3.91-2.9,5.85-2.17-.87-4.35-1.7-6.54-2.47,2.86-1.38,5.74-2.68,8.69-3.88,.41-.2,.75,.15,.75,.5Z"/><path class="cls-2" d="M892.54,367.68c-.05,.01-.11,.03-.16,.04,.03-.05,.06-.11,.09-.16l.07,.12Z"/><path class="cls-2" d="M933.79,370.86s-.09,.03-.13,.04c.01-.04,.03-.08,.05-.12l.08,.08Z"/><path class="cls-2" d="M1024.28,414.75h.13l-.03,.09-.1-.09Z"/><path class="cls-2" d="M10M 93.82,419.36s.04-.07,.06-.1c.02,.01,.05,.01,.07,.01l-.13,.09Z"/><path class="cls-2" d="M1098.65,405.13c-1.65,4.68-2.87,9.56-4.77,14.13-23.1-2.38-46.25-4.11-69.47-4.51,3.11-7.77,4.4-11.43,4.56-12.92,.01-.1-.08-.2-.16-.39-18.81-.35-37.67,.55-56.45,1.73-.72-.1-2.66,.42-2.63-.69,1.3-3.64,2.89-7.17,4.32-10.75,.57-1.85-4.51-.62-5.52-.71-12.26,1.33-24.52,2.7-36.69,4.69-3.04,.46-6.08,.91-9.13,1.36-.52,.08-1.08-.38-.94-.77,1.24-3.32,2.86-6.49,4.27-9.75,.22-.65,.82-1.79-.34-1.84-14.42,2.49-28.73,5.63-42.93,9.06-4.36,1.09-3.1M 2-.02-1.9-3.21,1.14-2.53,2.43-5.03,3.56-7.55,.24-1.01-.07-1.36-1.47-1.01-12.96,3.47-26,7.07-38.67,11.32-.6,.21-1.28,.25-1.92,.35-.07,.01-.27-.16-.26-.23,.91-3.73,3.08-7.1,4.52-10.66,1.42-2.5-.85-1.58-2.26-1.13-7.12,2.42-14.25,4.82-21.28,7.45-3.33-2.18-6.72-4.25-10.14-6.19,.18-.42,.31-.84,.41-1.28-.51-.79-1.68-.06-2.36,.18-4.43-2.46-8.92-4.72-13.46-6.78,7.08-2.93,14.25-5.71,21.36-8.6,.92-.24,2-.99,2.92-.48,.07,.04,.1,.2,.06,.28-2.02,4-4.33,7.88-6.46,11.82-.3,.57-.92,1.97,.29,1.74,11.97-4.13,23.71-8.74,35.88-12.54,1.M 14-.21,2.29-1.1,3.4-.46-1.97,4.34-4.65,8.45-6.58,12.8,.9,.6,1.74,.03,2.66-.18,13.6-4.26,27.38-8.4,41.31-11.69-2.09,3.75-4.02,7.59-5.99,11.4-.2,.58-.96,1.75,.02,1.9,15.66-3.64,31.35-7.16,47.25-10.12-1.61,3.63-3.51,7.13-5.3,10.67-.33,.85-1.66,2.58,.1,2.6,14.11-2.35,28.3-4.29,42.51-6.03,2.79-.34,5.6-.55,8.41-.78,.3-.02,.64,.19,1.05,.33-1.21,3.07-2.69,5.89-4.06,8.87-2.01,4.21-2.07,3.85,3.5,3.56,10.84-1.03,21.73-1.49,32.61-1.9,6.72-.31,13.44-.58,20.18-.52,.64,.09,1.8-.16,1.96,.64-1.19,4.1-3.37,7.9-4.64,11.99-.17,1.6,3.7M 3,.79,4.83,1.05,21.3,.64,42.68,1.17,63.84,3.75Z"/><path class="cls-2" d="M1098.8,405.15c-.05-.01-.1-.01-.15-.02,.01-.02,.01-.04,.02-.06l.13,.08Z"/><path class="cls-2" d="M657.28,1058.23c8.98-4.12,17.66-8.8,26.41-13.35,.55-.29,1.07-.66,1.81-.44l-.09-.07c.34,.65,.03,1.26-.23,1.86-1.38,3.13-2.77,6.25-4.17,9.38-.51,1.2-1.31,2.32-1.2,3.67-.3,.04-.32,.08-.07,.14v-.2c.55,.16,1.02-.01,1.47-.27,2.09-1.17,4.18-2.34,6.29-3.48,5.67-3.07,11.33-6.15,16.68-9.57,.82-.53,1.89-1.2,2.8-.49l.06-.08c-.78,.64-.99,1.51-1.34,2.31-1.38,3.1M 5-2.71,6.31-4.07,9.46-1.96,4.49-3.11,5.98,2.25,2.59,6.12-3.7,12.24-7.4,18.36-11.11,.98-.43,2.24-1.86,3.3-1.51,.26,.31,.13,.61,0,.91-2.35,5.16-4.87,10.26-7.28,15.4-.2,.67-.94,1.46-.29,2.05,.04,.05,.29,.04,.38-.01,8.21-4.6,15.88-9.97,23.89-14.88,.17,.26,.39,.45,.35,.58-.3,.82-.63,1.64-.99,2.45-2.48,5.57-5,11.14-7.85,16.6-.2,.38-.53,.75-.32,1.2,.04,.08,.22,.2,.26,.18,.47-.19,.98-.35,1.39-.61,6.65-4.21,13.29-8.43,19.93-12.65,.84-.43,1.72-1.25,2.64-1.39,.62,.75-.46,1.87-.7,2.68-2.95,6.01-5.9,12.01-8.85,18.02-.39,.8-.73,M 1.61-1.07,2.43-.03,.08,.06,.2,.11,.29,.11,.21,.37,.3,.64,.13,3.11-1.88,6.24-3.75,9.3-5.68,4.33-2.73,8.61-5.52,12.93-8.27,.13-.08,.47,.01,.7,.06,.3,.3-.16,.83-.25,1.18-3.63,7.92-7.74,15.62-11.8,23.33-.36,.69-.66,1.4-.97,2.11-.03,.08,.04,.25,.11,.27,1.1,.31,2.06-.77,3.03-1.16,4.25-2.47,8.48-4.95,12.73-7.42,.75-.44,1.39-1.04,2.39-1.13l-.06-.09c.41,.88-.12,1.62-.5,2.42-4.09,8.61-8.57,17.09-13.29,25.49-.52,1.08-1.51,2.04-1.41,3.29l-.12-.07c1.58,.05,2.83-1.06,4.2-1.69,4.13-2.21,8.25-4.43,12.38-6.63,.75-.28,1.6-.99,2.41-.M 88,.09,.07,.21,.2,.18,.27-.31,.71-.61,1.42-.97,2.11-5.43,10.28-11.03,20.5-17.09,30.56-.41,.67-.76,1.37-1.07,2.08-.07,.15,.1,.38,.22,.56,5.95-1.94,11.63-5.35,17.46-7.83,.58-.27,1.14-.58,1.86-.35l-.09-.06c.2,.56-.05,1.05-.33,1.55-4.01,7.06-7.95,14.14-12.05,21.16-3.19,5.46-6.6,10.84-9.9,16.26-.23,.38-.37,.8-.52,1.21-.02,.06,.11,.19,.21,.25,.83,.19,1.75-.44,2.57-.64,4.96-1.94,9.91-3.89,14.86-5.84,.95-.24,1.91-1.11,2.9-.64,.08,.03,.15,.19,.12,.26-.23,.5-.45,1.01-.73,1.5-8.29,15.12-18.76,29.66-27.1,44.62,.07,.08,.23,.2,.M 3,.18,.9-.21,1.81-.42,2.68-.69,5.4-1.66,10.8-3.34,16.2-5,.93-.2,1.79-.74,2.68-.11-10.61,18.11-22.71,35.48-34.36,52.94,.81,.47,1.46,.34,2.11,.2,6.37-1.37,12.73-2.77,19.1-4.14,.67-.1,2.3-.56,2.11,.48-9.1,14.78-19.09,28.96-29.05,43.24-3.64,5.16-7.38,10.27-11.06,15.41-.46,.65-.83,1.34-1.2,2.02-.25,.58,.8,.51,1.14,.53,6.94-.77,13.86-1.62,20.8-2.36,1.94,0,3.71-.53,1.91,1.96-16.21,23.36-32.68,46.57-50.21,69-8.32,.47-16.69,.07-25.03,.19-.68,0-1.83,.05-1.97-.65,16.6-21.39,34.08-42.35,49.78-64.21,.68-.92,1.31-1.88,1.94-2.82,M .17-.25-.21-.74-.53-.72-1.87,.12-3.74,.37-5.61,.56-4.8,.55-9.59,1.12-14.39,1.65-.86-.07-4.46,.89-3.99-.61,12.06-15.94,24.37-31.75,35.83-47.98,2.07-2.9,4.1-5.82,6.12-8.74,.32-.46,.55-.97,.75-1.48,.03-.08-.3-.37-.47-.37-6.8,1.15-13.54,2.84-20.32,4.17-.71,.03-1.67,.45-2.33,.12-.09-.18-.21-.43-.13-.56,.49-.76,1.03-1.51,1.58-2.25,11.62-16.01,23.47-31.86,33.9-48.46-.75-.5-1.48-.12-2.26,.08-6.55,1.74-13.08,4.4-19.66,5.61-.64-.61,.38-1.38,.67-1.96,7.31-10.06,14.05-20.36,20.87-30.63,2.59-3.9,5.02-7.86,7.51-11.79,.15-.23,.05M -.44-.23-.54-1.92-.01-3.67,1.27-5.5,1.8-4.89,1.77-9.71,3.79-14.66,5.39-.24,.04-.94-.12-.73-.46,8.27-12.7,16.96-25.14,24.33-38.27,.06-.13-.14-.37-.27-.53-.04-.05-.27-.04-.37,0-5.94,2.49-11.76,5.23-17.67,7.8-.45,.2-.99,.29-1.49,.4-.07,.01-.29-.15-.28-.21,.57-1.92,2.04-3.49,3.02-5.24,5.95-9.42,11.84-18.78,17.15-28.5,.01-.33-.37-.64-.76-.39-5.88,2.8-11.66,5.81-17.5,8.68-.32,.08-1.15,.42-1.35-.01,4.39-8.02,9.55-15.66,13.85-23.68,.93-1.67,1.82-3.36,2.69-5.05,.27-.52,.16-1.06-.26-1.52,.07,.05,.13,.09,.2,.13-.22,.06-.24,0-M .06-.17-7.03,4.98-15.08,8.67-22.5,13.12-2.84,1.46-2.09,.13-.96-1.71,4.14-7.37,8.27-14.73,12.4-22.1,.15-.4,.75-1.16,.41-1.48-.75-.31-1.36,.34-2,.64-6.4,3.76-12.8,7.53-19.21,11.29-.98,.57-1.96,1.14-2.98,1.67-.16,.08-.55,.05-.69-.05-.41-.72,.74-1.9,1.02-2.63,3.59-6.03,6.64-12.24,9.87-18.4,1.31-2.54-.57-1.62-1.93-.69-6.85,4.37-14.19,8.2-21.34,12.24-2.41,1.22-2.06,.19-1.09-1.64,3.13-5.71,6.48-11.33,9.32-17.18,.12-.25-.06-.59-.12-1.06-7.5,4.15-14.74,8.42-22.18,12.63-1.09,.62-2.26,1.17-3.4,1.75-.29,.14-.53,.09-.65-.11-.24M -.49,.33-1.02,.48-1.5,2.62-5.07,5.25-10.14,7.87-15.22,.21-.4,.41-.8-.04-1.3-6.91,3.43-13.62,7.26-20.48,10.82-1.91,1.01-3.88,1.94-5.83,2.9-.46,.23-.91,.21-1.08,.03-.3-.32-.09-.61,.06-.89,1.58-2.97,3.2-5.93,4.76-8.91,.94-1.79,1.82-3.59,2.67-5.4,.12-.25-.08-.59-.13-.9-8.32,3.41-16.12,7.89-24.31,11.65-1.48,.6-3.08,1.57-4.63,1.82-.12-.17-.3-.39-.24-.54,2.08-4.45,4.44-8.78,6.63-13.18,.2-.4,.27-.83-.21-1.3-11.87,4.75-23.78,10.46-35.92,14.33-.1-.18-.27-.42-.2-.56,2-3.89,4.25-7.67,6.31-11.53,.31-.58,.46-1.22,.66-1.84,.02-.0M 6-.16-.22-.26-.22-13.02,4.02-25.62,9.68-38.89,13.29-.19,.04-.47-.12-.67-.22-.18-.56,.55-1.52,.76-2.11,1.76-3.49,3.9-6.82,5.39-10.43,.06-.15-.14-.38-.27-.55-13.58,3.73-27.11,8.33-40.96,11.68-.76,.19-.75,.21-2-.14,2.11-3.83,4.02-7.75,5.98-11.64,.38-.75-.53-.87-1.06-.89-11.63,2.69-23.23,5.53-35,7.78-3.53,.62-7.03,1.67-10.62,1.88-1.19-.25-.03-1.55,.18-2.21,1.63-3.3,3.51-6.49,4.88-9.91,.18-.75-.86-.73-1.35-.66-9.64,1.55-19.27,3.17-28.96,4.38-4.52,.59-9.04,1.16-13.57,1.7-2.86,.15-5.86,1.04-8.68,.57-.17-.87,.38-1.53,.69-2M .22,1.1-2.43,2.28-4.84,3.41-7.25,.41-1.15,2.2-3.35-.28-3.28-12.35,.86-24.7,1.8-37.08,2.13-6.06,.2-12.11,.6-18.18,.52-.8-.01-1.61-.06-2.4-.15-.16-.02-.41-.32-.38-.46,1.09-4.23,3.71-8.04,4.58-12.32,.05-.26-.11-.44-.42-.48-3.86-.47-7.79-.31-11.68-.44-18.92-.58-38-1.17-56.75-3.58l.15,.14c1.91-4.66,3.2-9.56,4.88-14.31l-.12,.09c23.14,2.58,46.4,3.98,69.68,4.52l-.11-.09c-1.54,4.12-3.08,8.25-4.61,12.37-.21,.56,.26,1.04,1.01,1.08,10.64,.2,21.29-.28,31.92-.56,8.47-.36,16.92-1.04,25.4-1.35,.37-.02,.81,.36,.75,.62-.98,3.81-2.92M ,7.37-4.23,11.09-.11,.28,.27,.69,.61,.7,16.96-1.07,33.81-3.92,50.62-6.36,.63-.09,1.06,.28,.89,.74-1.15,3.12-2.65,6.1-3.96,9.15-.29,.77-1.34,2.34,.16,2.4,14.94-2.45,29.74-5.92,44.47-9.4,.45-.03,1.17-.2,1.41,.19-1.22,3.98-3.51,7.65-5,11.56-.12,.28,.36,.61,.76,.52,8.74-2.04,17.32-4.73,25.93-7.18,5.06-1.45,9.98-3.28,15.04-4.69,1.16-.03,.58,1.14,.31,1.8-1.42,3.14-2.85,6.27-4.26,9.41-.08,.34-.53,1.34,.02,1.42,4.33-.91,8.5-2.71,12.7-4.07,8.61-2.93,17.04-6.73,25.69-9.29,.62,.51,.15,1.2-.07,1.79-1.62,3.42-3.25,6.84-4.89,10.M 26-.2,.41-.33,.82,.12,1.22,11.7-4.03,22.99-9.58,34.27-14.16,.11,.05,.24,.18,.23,.25-.15,.63-.26,1.28-.51,1.88-1.41,3.37-2.87,6.72-4.3,10.08-.26,.61-.52,1.23-.09,1.85-.07-.09-.14-.17-.2-.25l.2,.19Z"/><path class="cls-2" d="M555.62,1219.39c-.99-1.21,.96-2.1,1.6-2.98,7.4-7.4,14.81-14.8,22.21-22.2,.42-.58,1.48-1.05,1.14-1.84-.02-.06-.25-.13-.34-.1-11.26,3.15-22.38,6.82-33.6,10.15-.88,.27-1.78,.5-2.68,.71-.15,.03-.41-.17-.56-.29,6.26-7.42,13.83-14.29,20.52-21.53,.3-.45,2.03-1.94,.98-2.07-4.34,1.04-8.56,2.56-12.81,3.88-7M .85,2.57-15.83,4.85-23.83,7.1-.63,.18-1.25,.4-1.91,.04,.05-.81,.8-1.33,1.36-1.91,5.72-6.37,12.2-12.27,17.55-18.9-.56-.28-1.09-.24-1.6-.09-3.04,.88-6.08,1.75-9.1,2.65-9.46,2.82-19.07,5.29-28.63,7.88-.57,.2-1.39,.33-1.91,.1-.7-.45,1.48-2.09,1.78-2.63,4.26-4.71,8.52-9.42,12.76-14.15,.61-.68,1.42-1.29,1.55-2.2-.78-.32-1.55,0-2.31,.18-11.2,3.09-22.59,5.7-33.9,8.5-2.3,.57-4.6,1.22-7.02,1.43-.2,.02-.45-.15-.63-.27,0-.97,1.21-1.69,1.73-2.47,4.1-4.81,8.44-9.42,12.37-14.36,.2-1.29-3-.06-3.73-.03-14.45,2.97-28.85,6.51-43.43,8M .67-1.12-.1,.51-1.67,.75-2.14,3.29-4.07,6.61-8.12,9.9-12.19,1.78-2.11,1.78-2.79-1.19-2.26-12.44,2.39-25.04,4.15-37.6,6.06-3.57,.54-7.17,.93-10.76,1.38-.25,.03-.72-.05-.74-.12-.22-.8,.4-1.41,.85-2.01,3.25-4.47,6.69-8.81,9.8-13.37,.16-.24-.21-.71-.56-.68-5.9,.35-11.73,1.31-17.6,1.93-13.24,1.27-26.49,2.51-39.77,3.36l.06,.11c2.63-4.5,5.53-8.83,8.38-13.21,2.08-3.14,1.69-3.19-2.22-3.03-20.4,.87-40.81,1.6-61.24,1.27l.09,.1c2.32-5.29,5.41-10.25,7.79-15.52,.2-.4-.19-.92-.72-.95-2.01-.11-4.01-.28-6.02-.29-22.53-.46-45.03-2.0M 7-67.48-4.03l.14,.11c2.14-5.86,4.22-11.74,6.44-17.58l-.11,.09c25.19,3.46,50.75,4.12,76.13,5.85l-.15-.09c-1.9,4.75-4.43,9.24-6.62,13.86-.29,.65-.91,1.68,.16,1.94,18.02,.81,36.11,.21,54.14-.29,3.23-.1,6.46-.23,9.69-.34,.71-.02,1.16,.58,.86,1.13-2.46,4.2-5.06,8.33-7.59,12.49-.52,.8-1.08,1.9,.57,1.86,13.42-.78,26.85-1.79,40.2-3.24,5.34-.53,10.67-1.33,16.03-1.56,.35,0,.79,.43,.65,.65-3.02,4.86-6.62,9.35-9.71,14.16-.17,.26,.18,.7,.54,.66,2.27-.24,4.55-.42,6.79-.75,14.85-2,29.6-4.63,44.39-6.94,.35-.04,.76,.42,.59,.66-3.19M ,4.67-6.86,9-10.25,13.53-.41,.53-.92,1.04-.92,1.79,7.26-.63,14.43-2.7,21.62-3.97,8.07-1.69,16.18-3.3,24.13-5.34,.59-.07,1.4-.36,1.94-.09,.1,.16,.25,.4,.17,.53-.43,.67-.9,1.32-1.41,1.96-3.61,4.54-7.43,8.94-10.92,13.58-.06,.08-.09,.27-.03,.31,.73,.62,1.74,.04,2.57-.05,12.66-2.98,25.22-6.2,37.68-9.67,1.43-.22,2.9-1.18,4.31-.58-4.22,5.45-8.91,10.5-13.32,15.79-.45,.53-.84,1.08-1.24,1.64-.05,.07,0,.22,.06,.29,.75,.34,1.87-.2,2.68-.3,13.02-3.22,25.81-7.97,38.65-11.08,.09,.16,.23,.41,.14,.52-.55,.74-1.13,1.46-1.75,2.16-4.3M 5,4.93-8.71,9.85-13.06,14.78-.54,.61-1,1.27-1.47,1.91-.04,.06,0,.2,.05,.25,.63,.35,1.61-.13,2.28-.23,12.24-3.68,24.43-8.35,36.67-11.62,.29,.12,.2,.51-.35,1.12-5.98,6.96-12.51,13.47-18.56,20.36-.07,1.12,1.45,.3,2.06,.2,11.82-3.89,23.84-7.26,35.29-11.96l-.12,.07c.34,.37,.53,.77,.18,1.18-.76,.89-1.53,1.77-2.33,2.63-6.31,7.15-13.68,13.84-19.43,21.26,.07,.08,.25,.19,.33,.17,.89-.24,1.78-.48,2.64-.77,9.65-3.28,19.29-6.57,28.93-9.85,1.09-.23,2.23-1.08,3.34-.65,.09,.52-.76,1.19-1.05,1.66-7.85,8.81-15.99,17.7-24.73,25.86,.3M ,0,.33,.04,.11,.12l-.03-.22c1.44,.79,3.09-.36,4.54-.67,8.33-2.76,16.65-5.54,24.97-8.31,.62-.21,1.2-.5,1.9-.17-7.52,9.73-16.62,18.51-25.08,27.66-.9,.93-1.73,1.9-2.58,2.87-.05,.06,0,.21,.07,.29,.07,.08,.23,.18,.31,.17,.78-.17,1.56-.33,2.31-.56,7.03-2.16,14.06-4.34,21.09-6.5,1.38-.42,2.77-.83,4.17-1.21,.15-.04,.41,.14,.58,.26,.05,.04,0,.23-.06,.3-10.07,11.44-20.92,22.19-31.46,33.21-1.87,2.01-1.86,2.37,.99,1.71,7.29-1.9,14.58-3.82,21.87-5.73,1.34-.21,2.57-1.03,3.93-.57-7.36,8.35-15.49,16.02-23.29,23.98-5.46,5.71-11.72,M 10.95-16.8,16.89-.01,.63,1.63,.15,2.11,.09,8.22-1.68,16.46-3.28,24.73-4.75,1.07,.32,.42,.82-.13,1.42-2.86,2.86-5.7,5.73-8.59,8.57-9.11,8.96-18.39,17.76-27.68,26.55-3.57,3.37-7.21,6.69-10.81,10.03-.25,.33-.83,.67-.63,1.11,.52,.42,1.58,.11,2.25,.16,7.47-.45,15-1.72,22.46-1.67,.83,.58-.81,1.53-1.16,2.07-17.91,17.01-35.86,33.97-54.34,50.41-2.48,2.24-2.01,2.08-5.87,2.09-6.74,.01-13.47,.02-20.21,.02-2.4-.1-4.33,.1-1.28-2.38,16.8-14.2,33.43-28.68,49.65-43.37,2.15-1.93,4.15-3.96,6.2-5.95,.21-.33-.3-.52-.54-.66-8.51,.91-17.M 07,1.93-25.6,2.78-.22,.02-.59-.07-.68-.2-.19-.79,.95-1.27,1.4-1.82,8.86-7.97,17.79-15.88,26.57-23.91,6.29-5.76,12.38-11.66,18.54-17.5,.46-.58,1.41-1.12,.99-1.92,0,.23,.08,.27,.28,.14l-.26-.05c-9.22,1.37-18.33,3.41-27.51,5.03-.88-.17-.68-.54-.11-1.1,13.42-12.44,27.78-24.76,39.62-38.08-.07-.08-.24-.18-.33-.16-.91,.17-1.83,.34-2.73,.56-8.88,2.13-17.71,4.48-26.61,6.49-.18,.04-.44-.12-.64-.22,0-.6,1.11-1.32,1.51-1.83,11.31-10.7,22.99-20.99,33.63-32.35-1.62-.39-2.8,.4-4.31,.74-8.86,2.54-17.72,5.07-26.59,7.6-1.1,.28-2.38,M .81-3.43,.12l.04,.03c10.14-8.99,19.5-18.92,29.36-28.24,.38-.46,1.23-.96,1.07-1.59-.11-.13-.49-.22-.69-.16-1.02,.27-2.02,.58-3.02,.88-7.02,2.16-14.03,4.33-21.06,6.47-3.41,1.21-7.22,1.72-10.44,3.32h.05Z"/><path class="cls-2" d="M376.96,212.56c-.59,.32-1.22,.43-1.91,.24-3.81-1.08-7.62-2.14-11.42-3.23-2.81-.68-5.53-1.9-8.39-2.25-.22,0-.57,.16-.63,.31-3.76,20.55-5.39,41.55-7.33,62.36-.06,2.49-1.66,1.24-3.14,.79-5.27-2.16-10.54-4.34-15.81-6.5-.59-.23-1.68-.78-2.04-.01-1.63,18.12-1.7,36.38-2.24,54.57,.04,1.96-1.48,1.06-2.M 57,.51-4.35-2.35-8.7-4.72-13.04-7.08-1.1-.32-4.24-3.26-4.77-1.41-.21,16.36,.99,32.75,1.46,49.06-.97,.38-1.69-.33-2.48-.75-4.69-3.07-9.36-6.16-14.04-9.24-1.15-.57-2.24-1.94-3.56-1.9-.19,.06-.44,.3-.43,.45,.25,4.09,.48,8.17,.82,12.26,.77,9.13,1.75,18.26,2.64,27.38-.09,.94,.94,5-.21,4.93-.36-.1-.76-.18-1.03-.38-6-4.28-11.73-8.88-17.56-13.38-.48-.33-.91-1.01-1.64-.64-.62,.31-.3,.97-.28,1.48,.03,.65,.1,1.29,.19,1.93,1.43,12.55,3.63,25.04,5.16,37.56-1.12,.12-1.8-.79-2.63-1.36-5.58-4.68-11.14-9.37-16.72-14.05-.7-.42-2.6-2M .8-2.99-1.15,1.64,12.44,4.59,24.77,6.22,37.19-2.11-.55-3.3-2.49-4.97-3.76-5.49-5.04-10.96-10.08-16.45-15.12-.78-.58-1.35-1.58-2.45-1.46,1.44,10.54,4.19,21.04,6.07,31.57,.19,.96,.34,1.92,.46,2.88,.02,.13-.28,.3-.47,.41-.94-.28-1.91-1.63-2.73-2.27-6.71-6.61-13.41-13.22-20.11-19.83-.88-.7-1.44-1.84-2.69-1.85,.85,7.37,3.03,14.65,4.38,21.98,.61,2.87,1.25,5.73,1.86,8.59,.11,.52,.24,1.06-.09,1.56-.03,.05-.29,.07-.38,.03-1.95-1.11-3.27-3.11-4.91-4.63-6.84-7.21-13.68-14.42-20.52-21.63-.79-.64-1.37-1.91-2.48-1.96-.13,.01-.33M ,.31-.3,.46,.22,1.28,.47,2.56,.74,3.83,1.23,5.73,2.47,11.46,3.7,17.19,.55,2.55,1.1,5.09,1.62,7.64,.06,.28-.11,.6-.21,.89-.55,.19-1.34-.8-1.74-1.13-9.82-10.66-19.46-21.48-29.37-32.06-.12-.12-.48-.1-.74-.12-.03,0-.13,.19-.12,.28,1.36,9.1,3.48,18.08,5.22,27.11-.3,1.4-1.77-.61-2.18-1.04-11.39-12.38-21.85-25.95-33.44-37.95-1.08-.23-.21,2.39-.31,2.95,1.04,7.47,3.02,15.02,3.51,22.46-1.46-.35-2.11-1.82-3.09-2.82-10.26-12.26-20.52-24.53-30.79-36.79-1.95-2.32-3.91-4.64-5.9-6.94-.1-.12-.48-.1-.73-.11-.45,.42-.18,1.27-.17,1.83M ,.68,6.22,1.37,12.44,2.04,18.67,.07,.64,.03,1.28,.02,1.93-.09,.36-.77,.17-.92,.07-14.72-17.71-28.96-35.82-43.51-53.67-.76-.96-1.73-1.94-1.56-3.24-.02-6.25-.05-12.5-.06-18.74,0-.3,.16-.61,.29-.9,.02-.05,.32-.11,.37-.07,13.69,15.93,26.51,32.72,39.95,48.91,.89,.84,1.61,2.54,2.94,2.5-.15-5.27-1.03-10.5-1.46-15.76-.23-2.25-.46-4.51-.67-6.76,.27-1.08,1-.43,1.51,.1,11.32,13.51,22.64,27.02,33.98,40.53,.6,.55,2.9,3.82,3.2,2.29-1.06-8.42-2.96-16.94-3.56-25.32,1.02-.11,1.51,1,2.17,1.6,9.73,11.12,19.46,22.24,29.2,33.36,.48,.5,M 3.01,3.83,2.99,1.58-1.57-8.74-3.24-17.46-4.72-26.21-.07-.41,.07-.84,.13-1.25,0-.02,.3-.06,.38,0,9.92,9.99,19.11,20.86,28.81,31.13,.3,.32,.51,.76,1.13,.81,.09,0,.28-.1,.28-.16-.18-3.99-1.36-7.87-1.99-11.81-1.15-6.07-2.29-12.14-3.43-18.2-.24-1.15,.95-.8,1.33-.31,3.2,3.33,6.41,6.66,9.62,9.98,4.78,4.94,9.58,9.88,14.38,14.8,.58,.59,1.23,1.13,1.87,1.68,.12,.08,.58-.02,.63-.18-1.01-9.08-3.56-18.05-4.78-27.15-.31-1.81-.59-3.63-.84-5.45,.37-1.46,1.7,.35,2.36,.82,6.43,6.23,12.85,12.47,19.28,18.7,.85,.83,1.78,1.61,2.71,2.38,.M 11,.09,.49-.01,.87-.03-.91-8.79-3-17.47-4.18-26.24-.42-3.2-1.25-6.38-1.34-9.61,.44-.82,2.11,.99,2.64,1.33,5.49,4.89,10.95,9.8,16.43,14.7,2.8,2.21,5.28,5.88,4.09-.63-1.12-7.59-2.28-15.18-3.2-22.79-.34-4.38-1.59-8.8-1.39-13.16,.7-.63,1.83,.69,2.46,1.05,4.85,3.9,9.67,7.81,14.52,11.7,1.33,1.07,2.71,2.09,4.1,3.11,.13,.1,.49,.03,.73-.02,.08-.01,.18-.18,.17-.28-.22-2.47-.43-4.93-.68-7.4-.96-8.9-1.86-17.81-2.61-26.73-.24-2.79-.41-5.59-.62-8.39-.03-.44,.21-.76,.49-.79,.45-.05,.75,.15,1.04,.35,3.85,2.69,7.69,5.41,11.56,8.09,M 2.34,1.62,4.72,3.21,7.1,4.79,.16,.11,.53,.13,.74,.06,.76-.35,.39-1.39,.46-2.06-.29-5.06-.79-10.1-.85-15.17-.38-9.58-.95-19.16-.99-28.75,.13-.88-.28-2.49,1.04-2.35,5.78,3.08,11.33,6.59,17.03,9.83,.86,.23,2.3,1.78,2.98,.68,.17-18.2,.43-36.4,1.1-54.59l-.14,.05c6.28,2.66,12.5,5.46,18.76,8.17,1.13,.35,3.11,1.59,3.06-.53,1.41-20.5,3.06-41,5.82-61.38l-.13,.12c6.79,2.07,13.6,4.07,20.4,6.1,.63,.19,1.27,.36,2.08,.01,2.87-19.84,6.37-39.63,10.07-59.34,.7-3.72,1.53-7.43,2.31-11.14,.2-.95,.71-1.2,2.01-1.04,5.96,.81,11.9,1.78,17.M 84,2.66,1.32,.2,2.63,.46,3.93,.73,.79,.33,.4,1.43,.35,2.09-3.26,14.48-6.46,28.99-9.21,43.56-1.82,9.13-3.38,18.29-4.97,27.45-.08,.43-.11,.85,.18,1.25h0Z"/><path class="cls-2" d="M1063.89,1226.8c5.16,.76,10.15,2.88,15.25,4.12,1.61,.13,7.1,3.06,7.29,.51,2.55-17.85,4.63-35.76,6.39-53.71,.46-2.96-.04-6.11,.96-8.96,.66-.62,1.77,.13,2.5,.31,5.28,2.16,10.54,4.33,15.82,6.49,1.08,.44,2.25,.95,2.43-.71,1.31-18.26,1.25-36.6,2.11-54.87,1.07-.4,1.97,.4,2.92,.8,4.79,2.61,9.57,5.23,14.35,7.84,.75,.42,2.41,1.67,2.89,.52,.37-16.35-.M 91-32.78-1.37-49.07,.67-.64,1.68,.31,2.33,.6,5.63,3.69,11.22,7.41,16.85,11.1,.35,.22,1.04,.29,1.12,.12-.02-14.7-2.56-29.65-3.59-44.41,.42-1.61,2.45,.59,3.19,.97,4.97,3.8,9.92,7.61,14.88,11.41,.81,.46,1.54,1.42,2.48,1.5,.31-.02,.48-.16,.47-.43-.05-3.13-.54-6.23-.95-9.33-1.22-10.39-3.07-20.78-4.33-31.12,.99-.32,1.73,.71,2.49,1.19,5.67,4.76,11.33,9.53,17,14.29,.65,.54,1.35,1.05,2.04,1.55,.06,.05,.26,0,.38-.04,.1-.03,.25-.11,.25-.17,0-.64,.08-1.29-.03-1.92-.93-5.55-1.89-11.09-2.85-16.64-.96-6.29-2.46-12.59-3.21-18.85,1M .25-.11,2.08,1.23,3.03,1.9,5.85,5.36,11.68,10.72,17.53,16.08,.99,.69,1.92,2.27,3.19,2.22,.3-.37,.11-1.07,.09-1.54-2.04-10.21-4.09-20.41-6.13-30.61-.02-.76-.64-1.92,.22-2.35,.07-.05,.3-.03,.36,.03,8.43,7.58,16.02,16.05,24.43,23.66,.11,.06,.59-.08,.63-.23,0-.64,.06-1.29-.07-1.92-2.01-9.77-4.12-19.54-6.23-29.29-.04-.2,.03-.42,.08-.63,.08-.18,.49-.22,.63-.13,5.32,4.89,10.02,10.42,15.09,15.57,3.91,4.12,7.82,8.24,11.75,12.34,.22,.23,.63,.36,.96,.52,.34,.02,.39-.49,.36-.74-2.05-9.66-4.18-19.3-6.19-28.97,.23-1.47,1.79,.5,2M .22,.94,9.13,10.01,18.25,20.02,27.39,30.03,1.43,1.42,3.06,3.8,2.51-.16-1.47-7.88-3.03-15.75-4.67-23.61-.1-.52-.04-1.06-.03-1.59,0-.07,.13-.16,.23-.19,.12-.03,.33-.05,.39,0,.67,.67,1.36,1.33,1.97,2.04,9.39,10.79,18.76,21.58,28.14,32.37,1.38,1.59,2.76,3.19,4.18,4.76,.19,.21,.67,.26,1.21,.46-1.02-7.64-2.43-14.98-3.68-22.55-.14-.85-.13-1.71-.18-2.57,0-.1,.1-.28,.14-.28,.24,0,.59,0,.71,.11,.75,.76,1.47,1.54,2.14,2.34,11.45,13.7,22.9,27.41,34.35,41.11,.75,.89,1.53,1.77,2.34,2.63,.1,.11,.46,.09,.7,.08,.06,0,.17-.17,.17-.2M 6-.32-6.89-1.18-13.74-1.83-20.61-.11-3,1.45-.75,2.41,.31,6.99,8.57,13.99,17.14,20.93,25.73,6.72,8.32,13.38,16.68,20.07,25.02,.75,1.09,2.01,2.05,2.06,3.44-.07,6.66,.32,13.39-.16,20.02-.09,.1-.54,.19-.67,.08-.71-.78-1.43-1.56-2.09-2.37-7.38-9.14-14.73-18.29-22.12-27.43-5.75-6.87-11.1-14.13-17.17-20.73-.12-.06-.58,.08-.62,.23-.03,.64-.1,1.29-.04,1.92,.68,6.76,1.41,13.51,1.92,20.28,0,.09-.1,.26-.17,.26-.7,.15-1.09-.32-1.49-.79-11.5-13.82-23.08-27.56-34.63-41.35-.52-.62-1.13-1.19-1.72-1.78-.13-.1-.57-.04-.65,.12,.72,8.3M 1,2.67,16.64,3.45,25-.05,.56-.68,.54-1,.22-10.44-11.75-20.71-23.65-31.09-35.45-.59-.62-1.13-1.75-2.2-1.72,.2,5.34,1.93,11.06,2.72,16.51,.64,3.73,1.46,7.43,1.76,11.2,.03,.27-.17,.41-.48,.39-9.47-9.07-18-19.65-27.14-29.23-.91-.76-1.75-2.36-2.99-2.39-.32,.47-.03,1.32-.01,1.89,1.77,9.47,3.67,18.93,5.35,28.42,.01,.58-.73,.54-1.03,.26-8.07-8.2-15.99-16.53-24.01-24.78-4.75-5.23-2.48,.34-2.11,3.51,1.49,7.99,2.99,15.97,4.47,23.96,.45,3,1.26,5.75-1.91,2.49-6.68-6.49-13.35-12.98-20.04-19.46-.68-.66-1.45-1.27-2.19-1.89-.14-.08M -.58,.03-.66,.15,0,4.41,1.4,8.74,1.96,13.12,1.12,6.72,2.23,13.45,3.28,20.18,.15,.95,.48,1.91,.11,2.87-1.26-.02-2.03-1.28-2.99-1.97-5.57-4.98-11.13-9.97-16.71-14.94-.9-.8-1.87-1.54-2.82-2.3-.06-.05-.26-.02-.37,0-.11,.03-.27,.1-.28,.16-.06,.42-.16,.85-.1,1.27,.34,2.68,.72,5.35,1.1,8.03,1.34,9.84,2.98,19.66,3.81,29.56-.04,.46-.63,.86-1.05,.47-.87-.67-1.77-1.32-2.62-2.01-5.85-4.61-11.46-9.51-17.5-13.88-.29-.06-.93-.03-.85,.4,.76,10.86,2.24,21.67,3.05,32.53,.29,3.33,.54,6.66,.79,10-.37,1.41-1.95-.09-2.63-.5-5.78-4.05-11M .54-8.14-17.41-12.06-2.42-1.51-1.06,3.73-1.22,4.86,.82,14.29,1.64,28.63,1.67,42.94-.51,1.14-1.81-.11-2.54-.42-5.11-2.99-10.21-5.99-15.33-8.97-1.06-.59-1.92-1.35-3.24-.94-.21,18.23-.12,36.44-1.09,54.65l.14-.04c-6.28-2.65-12.49-5.45-18.74-8.17-1.79-.73-3.14-1.45-3.06,1.24-1.45,20.22-2.77,40.64-5.85,60.67l.11-.12c-6.81-2.02-13.6-4.07-20.4-6.1-1.43-.45-1.98-.03-2.15,1.43-1.8,14.03-4.47,27.96-6.71,41.93-1.56,9.58-4.1,19.14-5.44,28.69l.13-.1c-7.97-1.35-16.78-2.68-24.44-3.65,.22-4.7,1.97-9.3,2.78-13.96,1.19-5.39,2.4-10.78M ,3.5-16.19,2.92-14.95,5.86-29.89,8.28-44.93l-.14,.13Z"/><path class="cls-2" d="M1191.44,947.12c.49-.58,.5-1.22,.36-1.86-.33-1.48-.67-2.97-1.06-4.44-2.25-8.42-4.52-16.84-6.78-25.25-.09-.42-.28-1.51,.46-1.16,8.23,7.23,15.71,15.33,23.67,22.88,1.25,1.09,2.03,2.47,3.68,3.05-1.83-9.69-5.14-19.21-7.47-28.84-.14-.52-.18-1.05-.24-1.58,0-.08,.07-.22,.15-.24,.81,.05,1.66,1.18,2.3,1.67,5.88,6.03,11.76,12.06,17.61,18.11,3.38,3.49,6.71,7.01,10.08,10.51,.1,.1,.45,.07,.68,.05,.28-.19,.07-.62,.01-.91-1.96-8.48-4.28-16.88-6.51-25.3-M .21-.95-.54-1.94,0-2.83l-.05,.09c11.02,10.93,21.27,22.57,31.72,33.94,.91,.77,1.68,2.36,2.93,2.4-.04,.29,.03,.34,.22,.14l-.31-.07c.4-.86,.1-1.71-.09-2.55-1.69-7.19-3.42-14.38-5.13-21.57-.17-.73-.26-1.48-.37-2.22-.01-.1,.08-.29,.12-.29,.25,0,.6-.02,.72,.1,.93,.92,1.86,1.84,2.71,2.8,8.67,9.74,17.33,19.48,25.97,29.23,2.88,3.25,5.69,6.54,8.55,9.8,.47,.4,.98,1.28,1.63,1.31,.24-.2,.48-.44,.34-.75-1.43-7.34-2.87-14.67-4.28-22.01-.77-4.35,1.5-1.14,2.89,.33,13.21,15.21,26.25,30.52,39.03,45.97,.74,.9,1.5,1.79,2.26,2.67,.4,.47M ,.8,.62,.95,.38,.11-.18,.29-.37,.27-.55-.46-5.81-1.26-11.58-1.96-17.37-.17-1.39-.38-2.78-.53-4.17-.02-.15,.19-.42,.34-.44,.23-.03,.59,.04,.72,.18,.72,.78,1.4,1.58,2.07,2.39,4.92,5.92,9.88,11.82,14.73,17.77,10.73,13.17,21.44,26.35,32.12,39.55,1.38,1.32,1.66,2.84,1.64,4.52-.18,6.02,.19,12.07-.16,18.08-.03,.14-.33,.27-.54,.36-.05,.02-.22-.08-.31-.14-15.99-18.66-30.47-39.54-47.3-57.22-.32,.22-.2,.84-.21,1.19,.74,7.06,1.88,14.13,2.27,21.21-.34,.03-.71,.14-.8,.06-.6-.57-1.19-1.16-1.71-1.78-6.13-7.34-12.21-14.71-18.37-22.M 04-6.38-7.6-12.83-15.16-19.26-22.73-.68-.8-1.38-1.59-2.11-2.36-.11-.12-.47-.11-.71-.12,.64,7.93,2.81,16.22,4.03,24.25,.05,.29-.1,.6-.19,.89-.27,.1-.82-.16-1.01-.37-11.2-12.79-22.38-25.59-33.58-38.38-.77-.88-1.6-1.73-2.44-2.57-.12-.12-.47-.09-.72-.14l-.03-.18,.13,.12c-.37,.97-.05,1.92,.16,2.86,1.78,8.15,3.67,16.22,5.3,24.42-1.14,.22-1.6-.85-2.34-1.47-6.47-7.11-12.9-14.25-19.4-21.35-3.49-3.81-7.08-7.55-10.64-11.32-.39-.41-.71-.93-1.52-.88l.09-.06c.99,7.93,3.68,15.64,5.33,23.49,.41,1.69,.75,3.39,1.11,5.09,.1,.45-.11,.M 81-.39,.75-9.36-8.41-17.72-18.48-26.75-27.44-.79-.62-1.41-1.88-2.54-1.78-.05,0-.16,.19-.14,.29,2.17,10.09,4.73,20.09,7.07,30.14,.13,2.17-2.65-1.09-3.15-1.57-7.48-7.35-14.83-14.83-22.39-22.1-.43-.6-1.61-.68-1.28,.35,2.37,10.84,5.39,21.92,7.25,32.7-.91,.17-1.44-.74-2.08-1.21-4.02-3.77-8.02-7.56-12.05-11.32-2.8-2.62-5.63-5.22-8.46-7.83-.44-.39-.94-.91-1.59-.87-.12,.01-.3,.32-.27,.47,.27,1.38,.59,2.76,.88,4.14,2.08,9.87,4.29,19.72,6.16,29.63,.06,.62,.41,1.38-.34,1.72-.06,.04-.28,.02-.34-.03-.75-.62-1.5-1.24-2.23-1.87-6M .29-5.29-12.22-11.05-18.74-16.05-.74-.16-.64,.69-.55,1.22,2.28,12.45,4.79,24.88,6.52,37.41-1.19,.32-2.23-1.09-3.2-1.67-4.78-3.8-9.53-7.61-14.31-11.42-.86-.68-1.76-1.33-2.67-1.97-.15-.1-.49-.06-.74-.03-.08,0-.2,.17-.19,.26,.74,7.52,2.34,14.94,3.16,22.46,.67,5.25,1.34,10.5,1.99,15.75,.12,.96,.09,1.93,.12,2.9,.03,.41-.68,.39-.87,.34-5.6-3.65-10.93-7.68-16.43-11.48-.83-.45-1.63-1.37-2.66-1.11,.46,8.07,1.7,16.31,2.11,24.47,.55,6.98,1.31,13.96,1.49,20.97,0,.17-.18,.41-.37,.49-1.22,.17-2.25-1.08-3.31-1.56-4.36-2.71-8.72-5M .43-13.09-8.13-1.01-.53-2.86-2.01-2.88,.17,.44,16.47,1.27,32.95,.91,49.43-.01,.28-.58,.58-.86,.45-5.59-2.52-10.97-5.47-16.47-8.17-3.22-1.88-2.47,.74-2.61,2.92-.47,17.87-1.29,35.78-2.88,53.58-.44,.82-1.74,.27-2.44,.03-3.87-1.52-7.73-3.06-11.6-4.57-2.1-.63-4.09-2.01-6.31-1.92-2.91,22.13-5.02,44.49-9.27,66.46l.14-.13c-7.2-2.18-14.57-4.29-21.94-5.82l.06,.09c4.81-21.94,7.7-44.32,10.76-66.58,.24-2.43,2.95-.66,4.31-.3,4.29,1.55,8.58,3.11,12.87,4.66,.81,.23,2.24,1.13,2.83,.23,1.18-6.69,1.37-13.51,2.08-20.26,.67-12.04,1.77-M 24.08,2.04-36.14,.1-.77-.16-2.23,1.06-2.04,5.87,2.27,11.38,5.37,17.19,7.78,1.14,.28,1.11-.81,1.18-1.58,.05-8.07,.45-16.15,.2-24.23-.26-8.29-.3-16.58-.42-24.87-.09-2.16,1.85-.76,2.89-.25,5.1,2.78,10.01,5.92,15.22,8.49,.56,.12,.9-.75,.83-1.21-.22-3.76-.47-7.53-.71-11.29-.48-6.12-.76-12.26-1.27-18.38-.25-5.25-1.5-10.51-1.35-15.75,1.21-.27,2.11,.75,3.11,1.26,4.26,2.81,8.51,5.63,12.77,8.44,.78,.36,2.9,2.45,3.25,.88-.62-6.98-1.51-13.95-2.48-20.89-.87-6.95-2.34-13.88-2.89-20.84,0-.09,.08-.25,.15-.25,.92-.23,1.63,.55,2.35,M .98,5.46,4,10.89,8,16.27,12.1,.8,.35,1.36,.19,1.15-.92-2.06-12.84-4.87-25.6-6.91-38.41,1.54,.24,2.36,1.31,3.53,2.15,5.21,4.21,10.42,8.42,15.64,12.62,.54,.44,.98,1.07,1.95,1,.23-1.39-.44-3-.61-4.44-2.11-10.62-4.97-21.14-6.88-31.78,.37-.88,1.89,.76,2.37,1.03,5.67,4.9,11.32,9.82,16.99,14.72,1.07,.71,1.9,2.16,3.25,2.18v.14l-.1-.08c.34-.86,.06-1.72-.14-2.55-2.57-10.44-5.21-20.87-7.77-31.32,.03-.66,1.16-.22,1.4,.11,7.89,7.2,15.93,14.26,23.34,21.83-.11-.24-.07-.29,.14-.13l-.28,.08Z"/><path class="cls-2" d="M171.16,461.61cM 10.66,11.81,21.24,23.67,32.27,35.16,.51,.38,1.44,1.01,1.21-.24-1.88-7.82-3.77-15.64-5.65-23.46-.38-1.58-.72-3.18-1.04-4.77-.03-.14,.19-.44,.31-.44,.79,0,1.21,.76,1.71,1.24,9.1,9.62,18.46,19.02,27.4,28.78,.01-.25,.07-.28,.17-.1l-.28,.03c1.05-1.03,.12-2.51-.01-3.74-1.99-9.4-4.99-18.84-6.47-28.22,.59,0,.97,.29,1.31,.63,2.27,2.28,4.52,4.56,6.81,6.82,5.68,5.61,11.39,11.2,17.08,16.81,.41,.4,.79,.84,1.53,.88-1.66-11.04-5.5-22.18-7.25-33.37,.35-1.04,2.77,1.77,3.34,2.12,6.24,5.8,12.46,11.61,18.69,17.42,.64,.46,1.26,1.34,2.0M 4,1.47,.25-.17,.57-.38,.43-.72-1.16-5.3-2.35-10.6-3.48-15.91-1.22-5.73-2.39-11.47-3.55-17.21-.58-3.85,1.1-1.65,2.81-.37,5.66,4.91,11.31,9.84,16.97,14.75,.64,.42,1.38,1.32,2.14,1.36,.16-.13,.38-.31,.36-.45-.53-2.98-1.11-5.96-1.65-8.95-1.66-9.83-3.88-19.62-5.02-29.51,1.6,.14,2.51,1.46,3.74,2.31,4.87,3.87,9.74,7.75,14.62,11.62,.8,.5,1.53,1.47,2.58,1.31,.06,0,.16-.18,.15-.28-.9-8.05-2.54-16.01-3.45-24.06-.6-5.36-1.51-10.7-1.9-16.08,0-.48-.41-1.13,.48-1.37,.58-.16,.96,.29,1.33,.55,4.54,3.21,9.06,6.45,13.6,9.66,1.54,.91,M 2.75,2.37,4.64,2.51-.83-10.12-1.9-20.21-2.73-30.34-.37-4.62-.65-9.25-.96-13.88,0-.57-.24-1.43,.32-1.8,.99-.29,1.85,.73,2.69,1.11,4.37,2.71,8.72,5.43,13.09,8.13,.82,.32,3.03,2.34,3.53,1.12,.13-5.69-.27-11.42-.45-17.11-.44-11.09-.63-22.19-.41-33.28,.01-.27,.62-.5,.94-.35,5.66,2.67,11.2,5.58,16.82,8.34,2.47,1.26,2.05-.33,2.18-2.18,.16-10.34,.77-20.67,1.33-31.01,.54-7.84,.69-15.74,1.73-23.54,.75-.93,2.28,.16,3.21,.38,4.35,1.71,8.69,3.44,13.04,5.15,1.08,.42,2.14,.92,3.36,1.02,.19,.02,.54-.15,.6-.29,.16-.4,.25-.83,.3-1.2M 6,2.58-21.86,4.79-43.93,9.24-65.47-.02,.32-.03,.69,.38,.82,1.23,.4,2.47,.77,3.73,1.11,5.17,1.39,10.35,2.75,15.52,4.14,.53,.14,1.03,.17,1.53-.04,0,.01-.07-.09-.07-.09-.75,7.59-2.86,15.1-3.82,22.7-.56,3.63-1.23,7.25-1.84,10.88-1.86,11.08-3.15,22.25-4.76,33.37-.23,2.58-3.25,.42-4.67,.16-4.79-1.71-9.58-3.44-14.37-5.16-1.6-.34-1.28,2.85-1.56,3.88-1.49,18.3-3.07,36.56-3.7,54.92-1.46,.21-2.48-.57-3.73-1.11-4.31-2.01-8.61-4.02-12.91-6.02-.64-.29-1.95-1.04-2.41-.26-.77,16.67-.05,33.39,.06,50.07,.13,2.56-1.45,1.28-2.84,.66-4M .52-2.54-9.01-5.11-13.52-7.66-1.31-.71-2.66-1.57-2.55,.74,.72,14.96,2.19,29.88,3.24,44.81-.57,.75-1.65-.29-2.26-.55-4.28-2.8-8.54-5.61-12.8-8.41-1.32-.74-2.34-2.02-3.96-2.02,.93,13.64,3.5,27.25,5.23,40.85,.01,.61,.35,1.86-.57,1.86-5.85-3.61-11.1-8.17-16.74-12.13-.71-.43-2.7-2.18-2.55-.28,1.37,8.11,2.72,16.23,4.31,24.3,.87,4.58,1.75,9.15,2.62,13.72-.33,1.49-3.12-1.43-3.79-1.8-5.54-4.4-10.95-8.94-16.55-13.26-.2-.09-.9-.18-.91,.23,1.7,9.39,3.97,18.67,6.01,28,.51,2.54,1.39,5.04,1.63,7.63-.02,.21-.5,.61-.77,.42-.6-.43-1M .21-.86-1.76-1.33-5.49-4.74-10.97-9.5-16.46-14.24-.91-.79-1.84-1.57-2.8-2.33-.13-.11-.48-.04-.88-.05,1.9,10.87,5.33,21.53,7.78,32.31,.98,3.38-1.76,.64-2.81-.27-6.44-5.95-12.85-11.9-19.29-17.85-.58-.36-1.99-2.28-2.54-1.47,1.55,9.25,4.85,18.3,6.95,27.49,.15,.8,1.86,4.59,.31,4.3-9.13-8.04-17.41-17.01-26.27-25.35-.14-.09-.88-.14-.84,.26,2.23,9.43,4.95,18.75,7.48,28.11,.06,.52,.45,1.54,.07,1.87-.24-.01-.57-.01-.7-.13-9.27-9.03-18.16-18.47-27.01-27.82-.89-.72-1.53-2.11-2.78-2.12-.3,.55,.13,1.84,.21,2.51,2.06,8.74,4.93,17M .41,6.59,26.18-.73-.07-1.06-.41-1.39-.76-2.62-2.74-5.28-5.45-7.84-8.22-7.37-7.97-14.7-15.96-22.05-23.94-1.16-1-2.15-2.92-3.6-3.35-1.01,.07,.47,3.77,.49,4.58,1.59,7.39,3.96,14.81,5.13,22.2-.22,0-.56,.08-.65-.01-.71-.64-1.42-1.29-2.04-1.99-11.84-13.36-23.76-26.64-35.51-40.08-.42-.33-.85-1.09-1.46-.93-.43,.15-.22,1.1-.22,1.47,1.49,7.85,3.14,15.54,4.5,23.43-1.63-.18-2.18-1.68-3.23-2.69-8.83-10.31-17.69-20.6-26.49-30.92-4.47-5.25-8.83-10.56-13.26-15.84-.86-.78-1.4-2.19-2.7-2.21,.19,6.13,1.46,12.21,2.06,18.32,.59,4.84,.3M 4,5.63-3.03,1.32-15.81-19.27-31.72-38.44-47.34-57.86-.85-1.04-1.23-2.09-1.22-3.33,.04-6.14,0-12.28-.01-18.42-.02-1.26,.95-.6,1.39-.2,14.57,18.15,29.33,36.13,43.99,54.2,1.14,1.14,1.84,2.94,3.52,3.33-.3-7.25-1.6-14.64-2.2-21.94-.04-.41-.04-.87,.79-.93,12.95,15.46,25.77,31.02,39,46.34,.76,.88,1.57,1.74,2.4,2.59,.11,.11,.45,.09,.68,.08,.05,0,.15-.19,.13-.29-1-6.09-2.12-12.15-3.19-18.22-.11-1.88-2.64-9.9,1.21-5.06,8.31,9.55,16.61,19.1,24.94,28.64,3.16,3.62,6.39,7.2,9.62,10.79,.21,.24,.62,.37,.95,.53,.33,0,.35-.5,.32-.75M -1.77-7.95-3.6-15.88-5.26-23.85-.24-1.15-.68-2.33,.06-3.49l-.16-.05Z"/><path class="cls-2" d="M671.72,960.33s0,.01,.01,.01c-.02,.01-.03,.02-.05,.03l.02-.03h.02Z"/><path class="cls-2" d="M772.48,941.81c-1.45,1.43-2.81,2.94-4.34,4.28-.21,.2-.47,.27-.71,.11-.18-.13-.38-.33-.39-.5-.26-2.69-.49-5.37-.74-8.06-.07-.58-.09-1.62-.93-1.45-5.26,4.46-10,9.59-15.37,14.09-.77,.47-2.36,2.72-3.1,1.29-.4-2.9-.49-5.82-1.06-8.68-.02-.07-.17-.17-.27-.18-.25-.03-.6-.1-.73,0-.87,.67-1.7,1.37-2.52,2.08-4.65,4.04-9.12,8.22-14.06,12.04-.78M ,.42-2,1.99-2.78,.92-.27-2.67-.53-5.36-.89-8.03-.07-.47-.77-.71-1.17-.42-6.21,4.81-12.57,9.43-19.14,13.91-.56,.41-1.05,.71-1.83,.63-.74-2.69-.5-5.56-1.02-8.31-.04-.28-.68-.47-.98-.3-7.44,4.42-14.54,9.36-22.17,13.49-.42,.23-.86,.5-1.5,.35-1.67-2.9-3.36-5.81-5.05-8.73h0c8.32-4.35,15.88-9.57,23.88-14.17,.62-.23,1.13,.41,1.42,.87,1.29,2.13,2.55,4.28,3.81,6.42,.72,1.02,1.87-.02,2.61-.48,4.86-3.41,9.74-6.8,14.28-10.49,1.04-.85,2.09-1.68,3.17-2.5,.45-.35,.9-.94,1.63-.66,.63,.25,.68,.89,.78,1.42,.42,2.23,.83,4.46,1.25,6.77M ,.41-.05,.91,.01,1.13-.16,1.84-1.42,3.7-2.83,5.43-4.33,3.46-3.02,6.84-6.09,10.26-9.14,.76-.56,1.32-1.57,2.36-1.6,.32-.02,.5,.14,.55,.38,.34,1.92,.69,3.84,1.03,5.75,.15,.77-.04,1.98,.87,2.3,1.06-.06,1.84-1.2,2.63-1.82,5.03-4.46,9.8-9.25,14.63-13.77,.28-.26,.86,.07,.96,.26,2.13,9.07-.37,12.21,7.58,3.37,.04,4.35,.19,8.7,.49,13.05Z"/><path class="cls-2" d="M906.2,1224.04c.05-.01,.11-.02,.16-.03-.02,.05-.04,.1-.06,.15l-.1-.12Z"/><path class="cls-2" d="M945.14,1096.22c-.05,.02-.1,.04-.15,.05,.01-.06,.03-.12,.04-.18l.11,.M 13Z"/><path class="cls-2" d="M951.59,1293.34h-.17s.01-.05,.02-.07l.15,.07Z"/><path class="cls-2" d="M926.27,1016.9c-1.84,14.1-4.61,28.1-7.55,42.02-5.04-1.19-10.04-2.65-14.98-4.35,1.91-8.65,3.93-17.3,5.56-26.01,.51-3.07-.82-1.72-2.51-.87-3.71,2.33-7.39,4.68-11.09,7.02-.66,.29-1.65,1.27-2.34,1.02-.4-.21-.2-1.11-.18-1.51,.98-4.99,1.97-9.99,2.98-14.98,1.4-6.88,3.04-13.79,3.4-20.79-.84-1.7-14.62,11.58-15,9.47,1.34-9.92,3.57-19.79,4.59-29.78,.09-.74,.03-1.49,.01-2.24-.05-.14-.52-.27-.64-.2-17.61,13.75-13.95,16.16-11.19-6M .39,.38-3.74,1.03-7.5,1.15-11.25-.01-.1-.08-.27-.13-.27-1.05-.16-1.67,.9-2.42,1.46-3.43,3.17-6.62,6.61-10.21,9.58-.14,.07-.59-.02-.67-.14-.26-3.69,.72-7.52,1.1-11.23,.65-4.18,.67-8.38,1.06-12.57,.02-.2-.08-.41-.19-.6-.59-.28-1.26,.32-1.58,.71-2.76,2.92-5.51,5.85-8.27,8.77-.65,.48-2.17,2.96-2.85,1.49,.13-2.47,.29-4.94,.47-7.42,.31-3.97,.65-7.95,.95-11.92-.05-.54,0-1.3-.47-1.46-.63-.2-1.19,.85-1.65,1.18-3,3.31-5.98,6.64-8.99,9.95-.78,.76-1.53,1.58-1.7-.1,.23-5.06,.5-10.11,.73-15.17,.03-.75-.06-1.5-.12-2.25-.06-.12-.5M 4-.25-.67-.18-3.67,3.43-6.61,7.59-10.01,11.3-.37,.43-.87,.78-1.33,1.15-.05,.04-.35-.02-.37-.07-.84-5.12,.51-10.52-.18-15.73-.1-.32-.71-.47-.91-.15-3.83,4.1-6.99,8.79-10.99,12.74-.07,.07-.27,.15-.34,.12-.9-.28-.53-1.26-.64-1.97-.04-3.45-.07-6.9-.12-10.34,0-.54-.09-1.07-.17-1.61-.01-.07-.16-.18-.25-.19-.25,0-.63-.04-.73,.07-1.2,1.26-2.27,2.59-3.41,3.9-.01-5.73,.23-11.51,.71-17.32,.45-.6,1-1.13,1.53-1.67,.06-.06,.25-.06,.37-.05,.11,.01,.28,.07,.3,.13,.6,2.1,.85,4.24,1,6.39,.13,1.83,.31,3.65,.5,5.47,0,.19,.23,.38,.39,.M 54,.53,.09,1.26-.89,1.62-1.24,3-3.84,5.96-7.69,8.96-11.53,.22-.23,.91-.73,1.25-.48,.12,.42,.27,.84,.29,1.26,.21,3.55,.39,7.1,.59,10.65,.05,.75,.16,1.49,.26,2.24,.07,.12,.54,.23,.67,.16,3.78-3.92,6.71-8.61,10.28-12.72,.19-.22,.45-.31,.69-.16,.67,.46,.38,1.4,.51,2.1,.26,4.41,.64,8.82,.48,13.24,.03,.32,.22,1.06,.67,.97,.39-.27,.83-.53,1.1-.86,2.37-2.88,4.71-5.78,7.05-8.67,.73-.9,1.42-1.83,2.18-2.71,.1-.11,.49-.08,.74-.07,.09,.01,.24,.12,.25,.19,.09,1.08,.22,2.15,.22,3.22,.08,5.06-.35,10.13,.03,15.17,.18,.25,.71,.48,.9M 4,.12,.7-.78,1.45-1.54,2.13-2.34,2.5-2.94,4.97-5.89,7.47-8.83,.27-.22,.92-.71,1.28-.41,.54,5.4,.32,10.98-.18,16.43-.04,2.36-1.39,8.18,2.33,3.74,2.83-3.02,5.64-6.04,8.47-9.06,.37-.27,1.06-1.09,1.51-.76,.63,2.44-.09,5.14,0,7.67-.25,5.81-.66,11.6-1.15,17.4,1.18,.29,1.74-.7,2.55-1.33,2.85-2.73,5.68-5.48,8.52-8.21,.65-.66,2.46-2.22,2.34-.25-.85,9.13-1.42,18.27-2.26,27.39,.36,1.26,2.03-.57,2.59-.94,2.86-2.44,5.71-4.88,8.57-7.32,.77-.5,1.43-1.54,2.46-1.35,.08,.01,.19,.15,.19,.23-.08,3.45-.45,6.87-.84,10.3-.57,7.41-1.72,14M .78-2.7,22.16-.01,.4,.69,.37,.88,.29,4.52-3.02,8.81-6.32,13.26-9.46,.21-.1,.82-.16,.93,.22-.4,7.38-1.68,14.8-2.77,22.15-.76,5.11-2.16,10.17-2.31,15.35,.54,.72,1.66-.24,2.27-.48,3.74-2.3,7.45-4.62,11.18-6.93,.77-.4,1.5-1.08,2.44-.87,.05,.21,.15,.42,.12,.63Z"/><path class="cls-2" d="M936.27,1052.95c-.23,3-1.14,5.9-1.64,8.86-4.47-.56-8.94-1.34-13.4-2.32,3.92-1.96,7.83-3.92,11.75-5.88,.83-.22,2.84-1.9,3.29-.66Z"/><path class="cls-2" d="M926.83,1293c-.17,.72-.9,2.03,.26,2.23,8.13-.26,16.19-1.68,24.33-1.89-10.75,31.31-22M .93,62.14-35.81,92.63-.37,.13-.61,.29-.86,.29-8.77-.02-17.51,.21-26.29,0-.35-1.37,.61-2.52,1.05-3.77,4.96-11.27,10.05-22.49,14.87-33.8,4.55-10.69,8.97-21.42,13.28-32.18,2.58-6.45,5-12.95,7.53-19.42,.6-1.33-.3-1.54-1.44-1.42-7.36,.68-14.71,1.39-22.07,2.05-1.9,.06-.56-1.97-.24-2.89,2.38-5.83,4.79-11.65,7.12-17.49,7.48-18.65,14.38-37.42,20.91-56.31,.3-.93,.18-1.62-1.72-1.24-7.12,1.41-14.25,2.83-21.39,4.22,7.94-22.07,16.26-44.28,22.4-66.85-.34-.89-2.09,0-2.79,.07-5.95,1.57-11.74,3.98-17.76,5.11-.51-.62-.17-1.24,.03-1.8M 5,5.38-16.3,10.34-32.74,14.92-49.26,.54-1.89,.98-3.79,1.42-5.7,.13-.95-.69-1.04-1.45-.77-5.58,2.12-11.02,4.57-16.58,6.71-.22,.08-.69,.11-.75,.03-.53-.64-.27-1.43-.05-2.14,.99-3.41,1.98-6.82,2.94-10.23,5.55,1.33,11.16,2.43,16.81,3.25-.54,1.86,1.78,.63,2.61,.37,5,.67,10.02,1.13,15.04,1.38-3.84,16.92-8.53,33.67-13.33,50.38-.12,.42-.17,.85,.36,1.3,6.09-1.46,12.14-3.35,18.2-4.98,.7-.14,2.09-.74,2.3,.26-4.53,17.52-9.83,34.85-15.31,52.12-1.42,5.14-3.81,10.09-4.79,15.31,.36,.85,1.78,.31,2.49,.31,6.51-1.2,13.11-2.43,19.59-3M .57,.23,.27,.51,.43,.51,.6-.02,.53-.06,1.07-.22,1.59-1.96,5.8-3.61,11.7-5.57,17.5-6.58,19.46-13.35,38.8-20.55,58.05Z"/><path class="cls-2" d="M589.21,1154.29c-.11-.59,.35-1.01,.73-1.45,3.14-3.62,6.3-7.23,9.44-10.86,2.09-2.5,4.32-4.89,6.21-7.53,.18-.24,.14-.42-.13-.52-12.94,3.6-25.52,9.24-38.66,12.68-1.12-.09,.19-1.29,.45-1.76,3.98-4.86,7.98-9.7,11.95-14.56,.51-.62,.92-1.3,1.36-1.96,.03-.05-.06-.18-.13-.23-.45-.28-1.02,.06-1.49,.15-2.24,.72-4.49,1.44-6.72,2.18-10.17,3.41-20.57,6.33-30.86,9.49-.73,.22-1.53,.32-2.3,.4M 5-.07,.01-.27-.13-.27-.18,3.54-5.42,8.13-10.36,12-15.64,.36-.46,.64-.95,.29-1.49,0,.01,.14,.25,.14,.25l-.13-.16c-14.65,3.47-29.25,8.91-44.08,11.12-.07-.07-.13-.22-.08-.29,.35-.57,.68-1.15,1.09-1.69,2.95-3.86,5.91-7.71,8.86-11.56,.32-.57,1.24-1.43,1.12-2.02-.17-.13-.43-.33-.58-.3-1.95,.41-3.9,.84-5.83,1.3-13.14,3.19-26.45,5.84-39.78,8.48-.51,.1-1.05,.14-1.59,.15-.33,0-.56-.19-.45-.38,2.6-4.43,5.96-8.41,8.86-12.65,.46-.64,1.08-1.25,1.08-2.04-.46-.31-.98-.27-1.5-.18-3.95,.67-7.9,1.33-11.85,2.01-8.15,1.42-16.33,2.74-24M .57,3.79-4.89,.38-9.8,1.95-14.68,1.72-.32-.62,.12-1.07,.41-1.52,2.21-3.45,4.44-6.89,6.65-10.33,.39-.84,2.26-2.66,.47-2.9-15.77,1.47-31.53,3.24-47.38,4-3.22,.12-6.43,.59-9.66,.5-1.25-.31-.13-1.5,.14-2.19,2.13-4.06,4.78-7.9,6.57-12.12-.12-.79-1.34-.54-1.94-.62-21.68,.64-43.35,.59-65.04,.04l.15,.09c2.43-5.2,4.86-10.4,7.29-15.59l-.11,.07c22.41,.6,44.88,.7,67.3,.63,.45,.66,.11,1.16-.14,1.64-1.55,2.98-3.12,5.95-4.68,8.93-.28,.98-2.77,3.75-.78,3.88,14.79-.46,29.54-1.62,44.27-2.88,4.41-.39,8.8-.97,13.22-1.27,.34-.03,.75,.4M 2,.63,.67-2.23,4.42-5.14,8.49-7.47,12.86-.2,1.29,2.16,.57,2.91,.63,16.49-1.97,32.81-4.69,49.17-7.45,.2-.03,.47,.14,.67,.25,.13,.61-.68,1.48-.93,2.07-2.53,4.02-5.38,7.88-7.7,12.02,.89,.46,1.68,.26,2.46,.1,4.57-.91,9.13-1.86,13.7-2.76,9.67-1.91,19.19-4.23,28.76-6.42,.9-.21,1.82-.39,2.74-.53,.16-.02,.4,.19,.55,.33,.12,.62-.75,1.45-1.05,2.04-2.33,3.27-4.68,6.54-7,9.81-1.53,2.28-2.71,3.44,1.12,2.55,6.52-1.71,13.02-3.45,19.55-5.14,6.02-1.56,11.91-3.39,17.85-5.12,1.3-.2,2.9-1.24,4.14-.72,.06,.03,.09,.2,.05,.28-.33,.58-.62M ,1.19-1.02,1.74-2.85,3.9-5.73,7.79-8.59,11.69-1.71,2.35-1.2,2.35,1.32,1.69,9.5-2.72,18.85-5.77,28.15-8.9,3.35-1.13,6.72-2.21,10.08-3.31,.3-.1,.57-.09,.69,.15,.27,.55-.23,1.01-.53,1.44-4.01,5.06-7.57,10.55-11.88,15.35,.16,.14,.21,.3,.43,.29l-.52-.31c2.13,.97,4.62-.91,6.74-1.36,10.97-3.62,21.79-8.17,32.65-11.65,.9,.25-1.32,2.53-1.57,3.08-4.25,5.18-8.03,10.81-12.6,15.71,0,0,.17,.08,.17,.08l-.09-.15c1.01,.81,2.28,0,3.32-.34,10.58-4.02,21.25-7.9,31.6-12.3,.26-.09,1.22-.37,1.29,.06-3.97,6.79-9.14,12.97-13.93,19.27-2.39,3M .06,5.41-1.06,6.25-1.19,6.49-2.63,12.89-5.39,19.21-8.27,1.23-.37,2.68-1.61,3.94-1.22,.21,.38-.45,1.05-.64,1.42-3.54,4.83-7.08,9.66-10.63,14.49-1.5,2.04-3.04,4.07-4.54,6.11-.53,.97-.25,1.33,1.21,.76,8.71-3.62,17.32-7.45,26.01-11.11,.39-.13,1.04,.11,.77,.64-4.35,6.1-9.11,11.95-13.62,17.95-1.76,2.29-3.56,4.57-5.31,6.87-.29,.48,.29,.82,.73,.67,8.07-3.16,16.14-6.46,24.01-9.99,.84-.26,2.08-1.04,2.89-.9,.09,.17,.23,.41,.15,.54-.5,.76-1.05,1.5-1.61,2.24-6.15,8.69-15.4,18.96-20.87,27.13,.07,.08,.23,.19,.3,.17,.75-.23,1.52-.M 44,2.24-.72,7.24-2.87,14.47-5.76,21.7-8.63,1.11-.27,2.19-1.31,3.3-.68-8.62,11.65-18.25,22.65-27.31,33.93,1.13,.67,2.59-.36,3.79-.63,7.13-2.54,14.25-5.11,21.38-7.65,.59-.13,1.3-.53,1.88-.26,.08,.05,.17,.19,.13,.24-.37,.57-.72,1.15-1.15,1.68-10.08,12.51-20.66,24.79-31.3,36.9-1.05,1.56,.56,.96,1.5,.84,5.9-1.51,11.79-3.04,17.68-4.55,1.05-.14,2.49-.88,3.45-.6,.07,.05,.13,.18,.09,.24-.21,.39-.4,.8-.7,1.15-4.1,4.81-8.13,9.65-12.33,14.39-8.09,9.15-16.26,18.24-24.4,27.36-2.6,2.66-1.52,2.71,1.57,2.2,6.7-1.13,13.34-2.76,20.07M -3.62,1.39,.17-.76,2.02-1.11,2.57-13.97,16.12-28.65,31.83-43.51,47.41-.51,.71-1.66,1.16-1.43,2.18,.9,.42,1.85,.18,2.75,.09,5.62-.55,11.22-1.14,16.84-1.69,1.46-.14,2.95-.19,4.42-.26,.33-.02,.51,.14,.51,.39-16.91,20.3-36.55,39.27-55.21,58.47-.61,.67-1.54,.86-2.48,.85-7.82,.04-15.63,.08-23.45,.11-.77,.01-1.87-.08-1.72-.85,18.36-18.02,37.14-35.65,54.89-54.27,.44-.6,1.39-1.12,1.1-1.94-1.34-.29-2.95,.05-4.36,.07-5.22,.46-10.43,1.03-15.64,1.53-1.34,.11-2.68,.17-4.02,.23-.33,.02-.51-.15-.5-.4,11.19-12.17,23.76-23.66,35.02-M 35.85,3.76-3.94,7.49-7.9,11.23-11.85,.56-.56,1.14-1.1,1.16-1.92-7.9,.6-15.72,2.92-23.66,3.76-1.2-.12,.96-1.88,1.21-2.31,13.04-13.6,26.3-26.93,38.41-41.16,.38-1.08-2.86,.26-3.4,.28-7.9,2.11-15.68,4.69-23.65,6.49-1.14-.12,.6-1.58,.86-2.03,4.58-4.93,9.26-9.8,13.75-14.78,5.83-6.46,11.52-13.01,17.26-19.53,2.21-2.66-1.48-.92-2.72-.63-7.11,2.32-14.21,4.64-21.31,6.96-.87,.28-1.7,.67-2.7,.52l-.17-.14c.11-.3,.12-.66,.33-.9,3.73-4.23,7.51-8.42,11.21-12.66,5.01-5.74,9.97-11.51,14.95-17.27,.24-.39,.92-.98,.75-1.4-1.31-.4-2.75,.M 69-4.05,.98-6.99,2.53-13.98,5.06-20.97,7.59-1.15,.28-2.21,1.13-3.41,.69,2.48-3.51,5.58-6.57,8.27-9.92,4.9-6.17,10.52-11.91,14.98-18.35,.02-.04-.21-.22-.27-.21-.63,.14-1.28,.26-1.86,.49-8.61,3.35-17.15,6.82-25.88,9.87-.58,.11-1.35,.07-.67-.82,6.49-7.78,13.05-15.51,19.2-23.54,.26-.42-.04-1.02-.63-.71-9.19,3.6-18.38,7.19-27.72,10.54-1.22,.44-2.49,.82-3.74,1.21-.14,.02-.5-.23-.44-.41,1.84-2.82,4.46-5.1,6.58-7.72,3.77-4.33,7.5-8.68,11.24-13.03,.38-.44,.68-.92,1.01-1.39,.04-.06,.01-.23-.04-.25-.23-.07-.49-.16-.73-.15-7.3M 8,2.53-14.66,5.44-22.03,8.05-4.29,1.56-8.63,3.02-12.95,4.53-.62,.22-1.26,.38-1.94,.15l.09,.06Z"/><path class="cls-2" d="M609.5,986.84v.05s-.07,.03-.1,.04l.1-.09Z"/><path class="cls-2" d="M613.62,997.25s.04-.03,.06-.05c.02,.05,.05,.09,.07,.14h-.01s-.12-.09-.12-.09Z"/><path class="cls-2" d="M643.47,973.96s-.06,.03-.09,.04c-.01-.03-.02-.06-.04-.09l.13,.05Z"/><path class="cls-2" d="M775.49,966.2c-11.55,10.13-10.13,12.56-8.81-3.68,.02-.18-.17-.37-.28-.55-.33-.44-1.2,.35-1.58,.67-6.11,4.98-11.97,10.32-18.24,15.1-.2,.07-.M 91,.1-.87-.32,.32-3.53,.87-7.06,.94-10.61,0-.24-.19-.38-.52-.39-2.07,.66-3.98,3.06-5.81,4.35-4.8,3.87-9.65,7.99-14.96,11.29-.94,.14-.68-.87-.65-1.46,.42-2.89,.58-5.79,.4-8.69-.06-.36-.67-.36-.91-.31-7.26,4.86-14.12,10.51-21.84,14.81-.92-.04-.63-1.27-.67-1.91,.17-2.37,.38-4.73,.54-7.1,.02-.3-.12-.61-.23-.91-.02-.06-.24-.09-.37-.09-.72,.02-1.2,.42-1.73,.74-4.82,2.94-9.59,5.93-14.46,8.82-2.59,1.54-5.33,2.92-8,4.36-.3,.17-.9-.08-.91-.35-.34-2.98,.8-6.08,.09-8.99-.05-.13-.5-.31-.63-.25-.83,.34-1.64,.73-2.43,1.13-7.8,4.1M 2-15.63,8.15-23.74,11.67-.45,.2-.91,.54-1.48,.29-.76-.33-.45-.92-.44-1.43,.03-.64,.13-1.28,.16-1.93-.18-1.18,.95-6.14-.61-6.09-2.4,.52-4.63,1.71-6.93,2.56-8.67,3.87-18.04,6.66-26.84,10.27-1.15-2.37-3.2-7.64-4.18-10.31,11.36-4.1,22.9-8.08,33.88-12.89,1.47,2.85,2.94,5.7,4.43,8.54,.19,.37,.39,.8,1.19,.9,9.18-3.85,17.96-8.57,26.69-13.15,.27-.14,.91,.11,.93,.36,.31,2.67,.37,5.36,.48,8.05,.02,.45,.72,.75,1.17,.51,7.36-3.86,14.25-8.49,21.34-12.78,1.88-1.15,2.75-1.76,2.73,1.03,.04,2.15,.05,4.31,.08,6.46,.01,.3-.02,.66,.5,.M 77,1.17,.08,1.97-1.03,2.93-1.52,5.64-3.86,11.26-7.72,16.6-11.84,1.18-.73,3.01-2.66,3.16,.03-.03,2.48-.12,4.95-.15,7.43-.01,.28,.17,.63,.41,.83,.37,.29,.76,0,1.03-.2,2.34-1.79,4.72-3.54,6.98-5.39,3.57-2.93,7.05-5.93,10.59-8.9,.71-.48,1.31-1.33,2.29-.88,.14,2.89,0,5.81,.03,8.7,.06,.58,.01,1.6,.88,1.44,5.81-4.47,11.06-9.74,16.68-14.49,.65-.44,1.24-1.33,2.02-1.46,.21,.11,.52,.25,.54,.4,.28,3.33,.08,6.67,.16,10.01-.02,2.91,5.74-4.01,6.59-4.55,.49,3.98,1.1,7.94,1.83,11.9Z"/><path class="cls-2" d="M835.47,996.84s.01-.02,.M 02-.03l.03,.03-.12,.08s.04-.05,.07-.08Z"/><path class="cls-2" d="M906.3,1224.16c-.05,.01-.11,.02-.16,.03l.06-.15,.1,.12Z"/><path class="cls-2" d="M890.71,1208.77c5.72-14.9,11.54-29.76,16.21-44.97-.38-.8-1.78-.14-2.45-.04-5.41,1.66-10.8,3.34-16.2,5.01-.66,.14-2.17,.82-2.23-.26,6.5-18.06,12.87-36.18,18.39-54.54,.57-2.29-2.26-.42-3.25-.18-5.03,2.04-9.97,4.33-15.06,6.22-.31,.11-.92-.21-.88-.45,.04-.32,.04-.65,.14-.96,2.57-7.98,5.17-15.94,7.54-23.98-4.96-1.63-9.86-3.46-14.68-5.47-4.04,12.5-8.22,24.9-12.98,37.21-1.29,3.2M 9-.21,2.6,2.2,1.65,4.77-2.01,9.52-4.03,14.3-6.03,.58-.24,1.22-.4,1.86-.54,.13-.03,.54,.26,.51,.35-5.49,17.74-12.66,34.97-19.5,52.25-.9,2.31-.37,2.42,1.79,1.72,5.25-1.68,10.49-3.37,15.74-5.05,.75-.23,1.53-.41,2.31-.56,.13-.02,.52,.27,.5,.37-7.29,20.82-16.34,41.07-25.25,61.29-.64,1.57-.5,2.17,1.5,1.69,6.11-1.3,12.22-2.6,18.33-3.9,.75-.2,2.64-.59,2.4,.6-6.85,16.75-14.16,33.22-21.85,49.64-3.26,6.95-6.65,13.86-9.98,20.8-.34,.7-.8,1.37-.63,2.16,1.21,.53,2.64,.09,3.94,.07,4.93-.54,9.86-1.13,14.8-1.65,1.72-.18,3.47-.21,5.2M 1-.28,.14,0,.45,.31,.43,.45-11.1,26.33-24.52,51.76-37.7,77.24-1.11,2.08-2.15,4.19-3.22,6.28-.22,.41-.25,.82,.03,1.31,8.95,.22,18.03,.37,26.97-.09,14.03-28.55,27.49-57.37,39.63-86.76,.3-.68-.02-1.41-1-1.31-7.21,.74-14.41,1.54-21.63,2.28-.64,.06-1.32,.15-2-.34,10.81-25.08,21.9-50.11,31.19-75.81-7.13,1.42-14.26,2.8-21.37,4.33-2.01,.3-1.87-.34-1.22-1.92,2.38-5.94,4.81-11.88,7.16-17.83Zm-.39-170.64c-3.29,2.08-6.57,4.16-9.87,6.23,3.02,1.63,6.1,3.16,9.24,4.58,.78-3.8,2.11-7.55,2.56-11.4-.89-.11-1.41,.26-1.93,.59Zm-6.76-27M .73c-1.1-.24-1.82,.69-2.68,1.21-2.86,2.13-5.7,4.27-8.56,6.41-1.24,.77-2.26,2.11-3.81,2.16-.36-.46-.1-1.28-.02-1.84,1.81-9.93,4.86-20.03,5.79-29.94-1.02-.24-1.69,.83-2.47,1.32-3.14,2.66-6.28,5.34-9.42,8-.79,.5-1.44,1.56-2.49,1.36-.07,0-.18-.18-.16-.27,.52-3.1,1.03-6.19,1.59-9.27,.85-4.69,1.78-9.37,2.6-14.06,.22-1.27,.14-2.57,.19-3.86,0-.06-.14-.15-.24-.19-.65-.2-1.29,.76-1.81,1.09-2.97,2.78-5.93,5.58-8.91,8.36-1.7,1.38-3.03,3-2.57-.54,.95-6.2,1.94-12.39,2.88-18.59,.15-.96,.16-1.93,.22-2.9,.06-.41-.56-.48-.84-.33-3.7M 2,3.35-7.13,7.02-10.75,10.5-.51,.35-1.12,1.26-1.79,1.13-.1-.03-.24-.12-.24-.18,.01-.64-.04-1.29,.08-1.92,1.08-6.17,1.87-12.4,2.1-18.63-1.01-.33-1.47,.57-2.12,1.13-3.17,3.35-6.32,6.71-9.48,10.07-.44,.34-1.16,1.33-1.74,.8-.52-1.5,3.87-22.16-.2-17.45-3.63,4.12-7.61,8.02-11.03,12.28-.53-.52-.61-1.14-.57-1.79,.26-4.84,.78-9.67,.69-14.52-1-.79-2.88,2.21-3.69,2.85,.45,5.29,1.15,10.51,2.09,15.65,.03,.02,.06,.03,.06,.05,.07,.3,.15,.61,.11,.9,.81,4.28,1.8,8.51,2.96,12.68,2.58-2.55,5.17-5.12,7.74-7.69,.32-.31,.96-.51,1.05-.34M ,.16,6.4-2.16,13.28-3,19.75-.04,.28-.14,.75,.15,.89,.25-.01,.59,0,.72-.12,3.38-3.22,6.73-6.45,10.11-9.67,.89-.64,1.73-2.1,2.92-1.91,.31,2.17-.51,4.29-.76,6.43-.67,3.62-1.12,7.27-2.11,10.85-.47,1.68-.77,3.39-1.13,5.08-.12,.54-.01,1.05,.47,1.47,4.21-4.01,8.63-7.93,13.08-11.69,.49-.25,1.03-.22,.94,.44-.46,2.34-.94,4.68-1.44,7.01-1.14,6.5-2.98,12.9-4.23,19.38,.03,.43,.69,.26,.9,.17,4.23-3.28,8.31-6.77,12.5-10.11,.36-.29,.71-.77,1.31-.58,.67,.2,.34,.71,.25,1.09-1.75,7.7-3.56,15.38-5.58,23.02,1.34,1.18,2.7,2.33,4.1,3.46,M 13.26-9.64,10.65-9.2,6.98,5.31,3.92,2.81,8.02,5.44,12.27,7.88,2.53-9.38,4.45-18.85,6.66-28.28,.27-1.16,.61-2.32,.33-3.51Zm-65.91-54.1s-.04-.07-.04-.09c.02,.01,.04,.04,.06,.05-.01,.01-.01,.03-.02,.04Zm46.85,126.48c-.71,2.24-1.56,4.45-2.06,6.75-.02,.09,.07,.26,.15,.28,.22,.06,.52,.14,.69,.07,2.59-1.23,5.05-2.68,7.59-3.99-2.14-1-4.27-2.03-6.37-3.11Z"/><path class="cls-2" d="M718.94,54c-10.18,15.18-21.13,30.02-30.99,45.35-5.49,8.4-10.98,16.8-16.45,25.2-.49,.76-.89,1.55-1.27,2.35-.05,.11,.2,.38,.39,.47,7.83-.25,15.71-2.M 02,23.59-2.25,.33-.02,.72,.45,.58,.68-.6,.97-1.2,1.93-1.83,2.88-13.06,19.81-26.32,39.61-38.02,60.2,.61,.31,1.14,.33,1.67,.22,2.34-.51,4.67-1.04,7.01-1.55,4.29-.93,8.57-1.86,12.87-2.77,.37-.08,.79-.04,1.18-.02,.34,.02,.5,.22,.38,.46-10.76,17.73-21.9,35.16-31.88,53.3-.27,.48-.37,1.02-.52,1.54-.01,.05,.2,.21,.28,.2,.53-.04,1.08-.05,1.56-.2,6.02-1.87,12-3.84,18.03-5.7,.48-.12,1.04-.49,1.48-.16,.64,.49-.07,.98-.27,1.44-.27,.6-.68,1.17-1.02,1.75-8.42,14.83-18.29,29.83-24.95,45.04,.69,.23,1.5-.35,2.19-.51,5.89-2.37,11.73-M 4.85,17.65-7.15,.17,.29,.41,.51,.36,.65-.3,.71-.64,1.41-1.02,2.09-4.47,7.84-8.79,15.73-12.94,23.68-2.49,4.77-4.91,9.56-7.36,14.34-.25,.49-.54,1,.15,1.56,5.58-2.47,11.04-5.32,16.56-7.93,.57-.28,1.2-.49,1.81-.71,.05-.02,.2,.07,.26,.14,.08,.08,.17,.21,.14,.28-.31,.71-.61,1.42-.98,2.11-5.35,10.11-10.56,20.28-15.5,30.52-.67,1.98-2.97,5.15,.93,2.87,4.64-2.6,9.27-5.2,13.91-7.79,.62-.23,1.42-.89,2.09-.68,.09,.06,.2,.19,.17,.26-.24,.61-.47,1.23-.78,1.83-4.76,9.15-8.83,18.5-13.13,27.79-1.75,3.61,.91,1.65,2.57,.6,4.06-2.5,8.1M 2-4.99,12.18-7.49,.57-.36,3.24-2.02,2.47-.13-.99,2.03-2.01,4.04-2.98,6.07-5.61,1.47-11.16,3.16-16.63,5.07-.03-.05-.06-.1-.09-.15-5.17,2.23-10.57,3.94-15.71,6.28,3.88-9.24,7.88-18.44,11.81-27.65,.1-.38,.49-.93,.08-1.21-.72-.14-1.68,.66-2.37,.93-4.58,2.66-9.14,5.34-13.72,7.99-.42,.25-.94,.38-1.42,.55-.06,.02-.28-.12-.27-.17,1.63-5.33,4.33-10.37,6.48-15.56,2.95-6.47,6.04-12.9,9.04-19.36,.38-.8,.65-1.63,.94-2.46,.03-.07-.09-.2-.18-.27-.64-.21-1.48,.44-2.09,.64-5.26,2.61-10.42,5.4-15.73,7.91-.3,.16-.77-.27-.77-.48,5.88-M 14.27,13.09-28.09,20.04-41.92,.21-.41,.35-.8-.21-1.24-6.37,2.43-12.58,5.43-19.01,7.73-.38,.15-.61-.34-.6-.6,7.39-15.82,15.45-31.27,23.91-46.6,1.21-2.16,1.29-2.5,.78-2.64-1.17-.32-2.07,.29-3.03,.59-5.91,1.72-11.65,4.07-17.66,5.43-.56-.14-.02-1.07,.08-1.44,9.5-19.03,20.14-37.48,30.69-55.98-1.67-.54-3.1,.23-4.74,.48-5.72,1.22-11.4,2.62-17.14,3.73-.39,.06-.82,.17-1.14-.1-.6-.64,.37-1.43,.58-2.07,5.94-10.73,12.02-21.41,18.3-32.02,6.25-10.63,12.84-21.09,19.14-31.71,.22-.9-1.19-.66-1.74-.64-5.74,.63-11.48,1.27-17.21,1.92-M 1.92,.04-3.78,1.01-5.66,.22,14.01-26.03,30.84-50.78,46.95-75.69,1.06-1.56,3.53-.77,5.18-.97,6.87,0,13.75-.02,20.62-.02,.64,.07,1.82-.15,1.93,.65Z"/><path class="cls-2" d="M786.03,415.49c-20.55,8.64-18.03,13.22-13.94-3.79,.03-.15-.19-.34-.35-.48-.33-.16-.77,.16-1.08,.3-8.79,4.35-17.11,9.48-25.68,13.97-.35-.48-.24-.88-.12-1.29,1.06-3.78,2.26-7.52,3.18-11.34,.02-.09-.1-.26-.18-.28-.24-.04-.56-.1-.72-.01-7.1,4.04-13.95,8.39-20.73,12.9-.7,.31-3.48,2.71-3.75,1.51,.52-4.21,2.47-8.15,3.62-12.22,.87-2.17-1.01-.95-1.96-.41-6M .9,4.48-13.95,8.82-20.5,13.65-.48,.43-1.09,.6-1.71,.78-.06-.29-.25-.61-.17-.87,1.42-4.71,2.94-9.4,4.35-14.11-.24-1.09-2.15,.61-2.66,.9-5.88,4.28-11.74,8.58-17.62,12.86-.76,.43-1.68,1.46-2.53,1.49-.71-.37-.25-1.12-.16-1.71,1.36-4.83,3.05-9.59,4.82-14.34,.48-1.86-1.22-.71-1.92-.16-4.53,3.22-9.12,6.39-13.41,9.83-1.8,1.45-3.64,2.87-5.48,4.29-.48,.37-.91,.82-1.68,.84-.33-.38-.13-.78,.01-1.19,1.9-5.61,3.8-11.22,5.7-16.83,.16-.51,.43-1.05-.09-1.45-.91,.14-1.74,1.03-2.53,1.51-5.54,4.26-11.06,8.52-16.6,12.78-.7,.41-1.36,1.2M 7-2.17,1.34-.17-.11-.44-.3-.41-.41,1.19-4.65,2.88-9.13,4.53-13.65,6.35-2.31,12.82-4.26,19.36-5.84-.19,.66-.97,1.3-.28,2.05,.92-.02,1.38-.61,1.97-1.02,1.01-.7,2.03-1.41,3.04-2.11,4.84-1.06,9.71-1.9,14.6-2.54-1.01,3.13-2.67,6.18-3.19,9.41,.73,.06,1.14-.2,1.54-.48,4.86-3.35,9.69-6.76,14.53-10.13,2.12-.13,4.24-.21,6.35-.25-1.4,3.57-2.81,7.13-4.21,10.7-.1,.45-.56,1.17-.24,1.54,1.01,.25,1.79-.71,2.65-1.11,5.65-3.59,11.25-7.25,16.97-10.73,1.5,.1,2.99,.22,4.48,.37-1.52,3.52-2.65,7.14-3.92,10.72-.15,.41-.25,.83,.21,1.3,5.76M -3.08,10.93-7.06,16.73-10.18,2.36,.42,4.72,.91,7.06,1.46-.15,.98-3.7,8.11-1.76,7.61,3.47-1.64,6.71-3.68,10.14-5.42,8.84,2.57,17.51,5.97,25.91,10.24Z"/><path class="cls-2" d="M840.78,395.42c-.53,1.69-1.24,3.32-1.88,4.97-1.59-1.24-3.21-2.47-4.86-3.68,.97-.16,6.92-2.97,6.74-1.29Z"/><path class="cls-2" d="M912.65,421.86c.06-.01,.11-.02,.17-.03-.02,.04-.03,.08-.04,.12l-.13-.09Z"/><path class="cls-2" d="M964.38,416.15l.09-.12h.06l-.15,.12Z"/><path class="cls-2" d="M968.57,404.73c-.97,3.6-2.42,7.05-3.6,10.59-.08,.26-.31,.M 48-.5,.71-17.28,1.24-34.56,2.98-51.65,5.8,1.01-3.3,2.03-6.6,3.03-9.91,.14-.58,.42-1.54-.38-1.7-11.79,1.39-23.38,4.23-34.92,6.69-2.98,.68-5.95,1.36-8.93,2.04-2,.38,.1-3.52,.16-4.5,.61-1.99,1.25-3.96,1.87-5.95,.13-.41-.44-.86-.95-.75-6.44,1.55-12.81,3.37-19.14,5.19-3-2.82-6.12-5.57-9.36-8.27,11.17-3.54,22.48-6.78,33.83-9.72,.68,.46,.56,.84,.32,1.48-1.09,2.77-2.21,5.53-3.29,8.31-.2,.7-.87,2.15,.37,2.14,12.98-2.92,25.91-5.92,39.02-8.26,.65-.12,1.31-.25,1.96-.38,3.29-.62,4.08-.68,4.21-.29,.41,1.14-.45,2.08-.78,3.1-.86,2M .59-1.88,5.16-2.82,7.74-.15,.43,.35,.83,.95,.74,1.99-.27,3.97-.57,5.95-.85,11.95-1.72,23.9-3.36,35.94-4.32,2.67-.26,5.32-.71,8.03-.63,.28,.01,.73,.45,.68,.68-.02,.11,.03,.22,0,.32Z"/><path class="cls-2" d="M638.3,415.08s-.05,.04-.07,.07l-.03,.03-.04-.04,.14-.06Z"/><path class="cls-2" d="M663.18,54.75c-15.45,25.12-30.31,50.57-44.27,76.5-.93,1.31-.67,2.28,1.12,1.98,6.01-.68,12-1.37,18.01-2.05,1.56-.09,3.21-.48,4.74-.11,.22,.62-.09,1.11-.36,1.59-1.53,2.64-3.11,5.26-4.6,7.91-10.93,19.38-21.62,38.84-31.36,58.8-.12,.29,.M 34,.63,.76,.54,7.15-1.53,14.29-3.09,21.44-4.63,1.58,0-.13,1.97-.32,2.68-9.85,18.69-19.81,37.44-28.26,56.69,.38,.66,1.45,.17,2.05,.04,6.13-1.92,12.21-4.03,18.38-5.85,1.39-.26,.59,1.38,.22,1.98-8.09,16.31-16.17,32.57-22.9,49.33,.36,.69,1.42,.1,1.98-.07,5.83-2.37,11.56-5.09,17.45-7.31,.52,.48,.36,.91,.18,1.3-1.18,2.64-2.39,5.26-3.6,7.89-5.1,11.12-9.95,22.3-14.41,33.6-.18,.7-.81,1.49-.22,2.13,4.94-1.71,9.52-4.87,14.32-7.12,1.01-.52,2.06-1.02,3.11-1.49,.15-.06,.45,.05,.64,.13,.09,.04,.16,.2,.13,.29-.24,.72-.46,1.45-.78,M 2.16-4.51,10.03-8.54,20.19-12.44,30.38-.71,1.85-1.27,3.73-1.89,5.6-.02,.09,.06,.27,.14,.29,1.11,.32,1.99-.85,2.96-1.26,4.53-2.71,9.05-5.42,13.59-8.12,.13-.08,.45,0,.66,.06,.26,.18,.08,.65,.02,.91-3.16,8.2-6.35,16.38-9.43,24.6-5.85,3.1-11.56,6.45-17.12,10.05,2.32-8.04,5.55-15.88,8.04-23.88,.09-.39-.55-.43-.74-.37-3.03,1.8-6.04,3.6-9.05,5.43-2.03,1.23-4.04,2.51-6.07,3.75-.39,.23-.81,.52-1.4,.34-.26-.55,.08-1.05,.24-1.56,2.68-8.56,5.63-17.07,8.77-25.53,1.34-3.61,2.75-7.2,4.1-10.81,.23-.61,.57-1.22,.35-1.88-.02-.08-.17M -.22-.22-.21-.37,.08-.79,.13-1.1,.3-4.4,2.29-8.78,4.61-13.18,6.91-.9,.47-1.82,.91-2.74,1.36-.32,.13-.72-.27-.74-.53,1.87-6.64,4.69-13.03,7.06-19.52,3.09-7.91,6.34-15.78,9.51-23.67,.18-.78,.98-1.7,.36-2.42-5.7,1.68-11.19,4.75-16.8,6.91-.64,.15-1.92,.99-2.36,.21,4.46-13.74,10.75-27.07,16.46-40.49,1.68-3.74,3.36-7.49,5.04-11.24,.18-.41,.31-.83-.18-1.25-6.33,1.58-12.41,4.04-18.65,5.96-.6,.2-1.22,.38-1.89,.23-.34-.66-.01-1.27,.25-1.87,1.93-4.48,3.82-8.97,5.81-13.43,6.58-15.41,14.29-30.43,21.21-45.69,.04-.13-.27-.46-.4-.M 45-.79,.05-1.6,.1-2.37,.26-5.97,1.31-11.94,2.63-17.91,3.95-.68,.16-2.28,.61-1.98-.57,10.41-23.34,21.91-46.19,34.02-68.75,.29-.56,.86-1.11,.48-1.8-.78-.32-1.58-.13-2.37-.04-6.54,.74-13.07,1.49-19.61,2.22-.73-.03-2.67,.47-2.6-.64,8.94-18.71,18.78-36.9,28.74-55.14,4.45-7.96,8.88-15.93,13.36-23.88,.54-.97,.9-2.04,2.02-2.87,8.16-.28,16.39-.03,24.55-.1,.96,0,2.93-.11,2.05,1.34Z"/><path class="cls-2" d="M816.76,435.77c-7.5,2.63-14.74,5.69-22.1,8.62-.68,.27-1.35-.15-1.25-.77,.4-2.99,1.11-5.95,1.13-8.97,0-.27-.22-.4-.55-.35M -3.1,.79-5.97,2.46-8.93,3.67-6.73,2.95-13.02,6.54-19.56,9.68-1.78,.27,.27-8.12,.24-9.57,.03-.91-.67-.83-1.24-.63-8.4,4.23-16.07,9.45-24.3,13.88-1.77,.12,.73-8.92,.72-10.52,.01-.1-.06-.27-.15-.29-.87-.35-1.66,.45-2.37,.82-6.48,4.37-12.95,8.76-19.43,13.14-.63,.3-1.24,1.09-1.96,.96-.46-.13-.3-.76-.31-1.13,.37-3.41,1.34-6.82,1.37-10.23-.59-.57-1.4,.22-1.94,.52-7.1,4.6-13.29,10.13-20.07,14.97-.76,.19-.71-.65-.67-1.16,.47-3.74,1.08-7.46,1.72-11.2,0-.09-.09-.27-.15-.27-1.04-.14-1.74,.85-2.54,1.35-5.52,4.42-11.04,8.85-16.5M 6,13.27-.56,.46-1.17,.88-1.78,1.31-.14,.07-.56-.05-.65-.2,.12-4.35,1.64-8.72,2.02-13.1-.38-1.63-2.35,.73-3.01,1.15-4.81,4.22-9.61,8.45-14.42,12.67-.84,.55-1.56,1.84-2.66,1.72-.68-.58-.06-1.98-.07-2.78,.67-3.83,1.37-7.67,2.05-11.51,.05-.51,.14-1.37-.63-1.12-6.31,4.84-12.09,10.42-17.86,15.8-.29,.22-.59,.51-.98,.47-.32,.02-.5-.12-.47-.39,.48-5.69,1.98-11.28,3-16.91,.07-.26-.4-.36-.55-.24-4.42,3.31-8.21,7.42-12.38,11.03-.62,.42-1.08,1.21-1.79,1.19-.23-.2-.49-.45-.38-.77,1.22-5.62,2.45-11.24,3.66-16.86,.16-.73,.49-1.46,M .23-2.22-.08-.21-.46-.29-.63-.2-4.21,3.25-7.95,7.02-11.99,10.48-.73,.57-2.81,2.6-2.29,.24,1.09-4.43,2.18-8.86,3.3-13.29,0-1.12,3.88-10.84,.57-8.23-3.5,2.98-6.99,5.98-10.49,8.96-.74,.63-1.5,1.23-2.27,1.83-.07,.06-.3,.09-.37,.04-.17-.12-.43-.3-.4-.42,.48-2,.91-4.01,1.35-6.02,4.94-3.59,10.09-6.89,15.37-9.97-.23,.8-.45,1.6-.67,2.4-.03,.09,.04,.27,.11,.28,.65,.25,1.14-.21,1.62-.56,4.57-3.75,9.36-7.27,13.8-11.16,.02,.02,.05,.05,.06,.08,.26,.31,.4,.66,.33,1.03,0,.02,0,.03,0,.05-1.99,7.15-4.19,14.24-6.23,21.37-.04,.15,.15,M .35,.27,.5,.32,.04,.77-.26,1.03-.44,4.13-3.39,8.18-6.86,12.29-10.28,.66-.41,1.3-1.35,2.17-1,.09,.02,.18,.19,.16,.28-.13,.63-.24,1.27-.45,1.89-1.7,5.21-2.98,10.5-4.29,15.78-.09,.81-.19,1.67,.61,1.46,6.13-4.78,12-9.9,18.05-14.8,1.49-1.13,2.52-1.94,2,.74-1.18,4.53-2.4,9.06-3.58,13.59-.13,.51-.11,1.06-.14,1.59-.01,.08,.08,.21,.17,.25,.82,.03,1.52-.86,2.19-1.26,3.85-3.18,7.65-6.38,11.52-9.53,1.97-1.62,4.04-3.17,6.08-4.74,.39-.3,.82-.56,1.48-.5,.02,2.63-1.39,5.21-1.88,7.82-.62,2.42-1.14,4.86-1.69,7.3-.03,.09,.03,.28,.1,.M 29,1.1,.26,1.91-.97,2.8-1.46,6.28-4.71,12.32-9.75,18.74-14.24,.28-.19,.78,.18,.8,.39-.89,4.36-1.89,8.69-2.81,13.04-.05,.4,.65,.41,.84,.33,6.8-5.07,13.67-10.07,20.87-14.77,.53-.26,1.12-.77,1.74-.68,.41,.26,.06,1.1,.05,1.5-.79,3.79-2.13,7.52-2.6,11.36,1.06,.02,1.6-.5,2.21-.91,4.35-2.89,8.68-5.81,13.05-8.68,2.39-1.58,4.84-3.1,7.27-4.63,.64-.34,1.33-.89,2.12-.64,.08,.02,.15,.19,.14,.29-.22,2.91-1.25,5.7-1.75,8.57-.17,.89-.93,1.79-.12,2.71,1.31-.08,2.13-.86,3.08-1.43,6.59-3.91,13.2-7.82,20.08-11.42,1.01-.38,2.02-1.39,3.M 14-1.23,.17,.08,.33,.36,.3,.52-.47,3.51-1.8,6.97-1.91,10.49,.84,.19,1.38-.16,1.93-.44,3.53-1.79,7.03-3.61,10.57-5.38,5.6-2.76,11.41-5.36,17.31-7.66,.54-.31,1.37-.14,1.25,.6-.09,1.29-3.48,10.54-1.5,10.12,3.93-1.02,7.55-3.05,11.39-4.4,3.26,2.34,6.37,4.73,9.33,7.17Z"/><path class="cls-2" d="M869.74,421.17c-.54,2.31-1.1,4.62-1.65,6.93-1.91-2.22-3.88-4.41-5.92-6.57,2.37-.52,4.69-1.51,7.1-1.71,.65,.11,.6,.85,.47,1.35Z"/><path class="cls-2" d="M516.24,1302.89c.91,.4,1.85,.16,2.75,0,2.63-.45,5.25-.94,7.87-1.44,6.02-1.16,12M .03-2.33,18.05-3.49,.72-.07,1.59-.41,2.19,.14-13.96,13.66-29.89,26.26-44.77,39.36-2.86,2.42-4.31,3.58,.74,2.92,8.13-.87,16.23-2.1,24.39-2.69,.11,0,.33,.07,.34,.13,.04,.19,.11,.46-.01,.58-.77,.75-1.57,1.47-2.39,2.19-17.73,15.34-35.78,30.51-53.98,45.45-.98,.87-2.51,.75-3.78,.76-7.79-.14-15.62,.34-23.38-.2-1.05-.77,1.6-2.12,2.07-2.7,16.3-13.47,32.59-26.93,48.88-40.41,.35-.44,2.51-1.8,1.59-2.23-9.35,.38-18.63,2.28-28,2.66-.18,0-.41-.35-.32-.49,.68-.66,1.34-1.34,2.08-1.96,14.11-11.83,28.18-23.72,42.09-35.76,3.53-2.91-1.M 41-1.23-3.03-1.14-8.81,1.53-17.62,3.07-26.43,4.59-1.69-.37,1.47-2.2,1.94-2.8,12.08-10.67,24.92-20.89,36.24-32.07-.56-.41-1.19-.12-1.79,0-8.83,1.93-17.65,3.86-26.48,5.77-1.55,.34-3.14,.59-4.71,.86-.11,.02-.34-.04-.36-.1-.06-.17-.14-.42-.04-.53,10.65-10.26,22.91-19.55,32.99-30.2-12.26,2.45-23.65,5.87-35.97,8.23,.68-1.65,2.04-2.31,3.21-3.54,7.43-6.82,14.86-13.64,22.28-20.47,.92-1.01,2.37-1.74,2.66-3.12,.17-.03,.39-.05,.28-.25-.26-.02-.33,.09-.19,.31-.8-.29-1.58-.08-2.34,.11-3.7,.91-7.38,1.86-11.08,2.78-7.94,1.73-15.76M ,4.36-23.8,5.5l.06,.09c-.03-.2-.18-.47-.07-.59,.71-.78,1.44-1.55,2.22-2.29,6.64-6.38,13.29-12.74,19.93-19.12,.52-.5,1.03-1,1.49-1.53,.1-.11,0-.37-.08-.54-.76-.25-1.88,.25-2.69,.37-11.52,3.01-23.15,5.71-34.8,8.37-3.14,.77-2.07-.49-.53-1.95,6.26-6.35,12.8-12.45,18.91-18.94,.3-1.15-1.4-.44-1.99-.38-12.5,3.03-25.14,5.66-37.74,8.39-.82,.07-1.87,.59-2.55-.05-.07-.06-.07-.24-.01-.31,.53-.62,1.06-1.24,1.63-1.84,4.99-5.22,9.99-10.43,14.98-15.66,.32-.45,1.63-1.65,.61-1.79-14.38,2.75-28.71,5.79-43.21,8.19-.73,.06-1.6,.35-2.21M -.17-.07-.05-.09-.23-.03-.31,4.78-5.92,10.3-11.25,15.08-17.17,.1-.22-.12-.75-.47-.69-10.72,1.63-21.34,3.61-32.11,5-5.58,.7-11.12,1.73-16.71,2.31-.26-.03-.74-.29-.57-.62,3.73-4.9,7.77-9.57,11.62-14.38,.32-.57,2.33-2.43,.96-2.64-4,.44-8,.91-11.99,1.35-14.11,1.4-28.3,3.38-42.44,3.86-.16-.75,.37-1.28,.76-1.83,2.44-3.47,4.89-6.94,7.34-10.41,.6-.84,1.23-1.67,1.76-2.54,.39-.65,1.38-1.31,.74-2.04-.46-.53-1.5-.24-2.28-.18-19.51,1.31-39.04,2.04-58.59,2.32-.46-1.31,.66-2.23,1.15-3.36,2.2-3.93,4.42-7.86,6.61-11.79,1.49-2.58-.2M 3-1.98-2.17-2.14-22.51,.08-44.98-.98-67.45-2.01l.09,.1c2.43-6.07,4.86-12.13,7.29-18.2l-.12,.07c24.25,2,48.57,2.9,72.9,3.25l-.09-.1c-2.84,5.22-5.68,10.44-8.51,15.66-.42,.78-.06,1.18,1.12,1.17,20.85,.12,41.66-1.01,62.47-1.86l-.06-.11c-3.46,5.11-6.92,10.22-10.38,15.33-.3,.47-.49,1.2,.3,1.32,10.47-.6,20.89-1.64,31.32-2.68,7.89-.75,15.75-1.68,23.6-2.61,.34-.04,.78,.42,.65,.66-.17,.29-.31,.6-.51,.87-3.28,4.34-6.69,8.59-10.01,12.9-.49,.64-.93,1.31-1.37,1.97-.21,.4,.34,.46,.62,.56,16.87-1.79,33.57-5.37,50.34-7.41,.2,.64-.2M 6,1.06-.62,1.48-4.36,5.18-8.88,10.25-13.17,15.49-.08,.22,.14,.72,.51,.66,1.85-.22,3.69-.62,5.52-.94,13.5-2.45,26.89-5.38,40.34-8.03,1.06,.2-.31,1.36-.59,1.82-4.28,4.7-8.58,9.39-12.86,14.09-.71,.78-1.39,1.58-2.07,2.38-.29,.35,.32,.55,.54,.55,13.44-2.62,26.67-6.03,39.94-9.2,1.02-.15,2.07-.69,3.08-.3,.05,.6-.49,.97-.89,1.38-5.86,6.33-12.18,12.28-17.84,18.78,1.27,.34,2.26-.14,3.25-.37,4.9-1.18,9.77-2.42,14.63-3.68,7.59-2.16,15.44-3.72,22.88-6.28l-.02-.05c.86,1.14-.68,1.96-1.33,2.77-5.57,5.54-11.14,11.08-16.71,16.62-1.0M 3,1.24-5.53,4.61-.98,3.38,11.98-3.24,24.05-6.18,35.93-9.73,1.38,.06-.89,1.99-1.25,2.43-6.86,6.8-13.74,13.6-20.81,20.2-1.24,1.26-4.29,3.67-.25,2.61,10.83-2.94,21.66-5.87,32.45-8.93,3.55-.99,1.25,.81,.04,2.15-6.14,5.86-12.3,11.71-18.47,17.55-.59,.93-10.64,8.92-8.22,8.72,11.07-2.62,22.01-5.69,33.01-8.59,3.22-.52-.59,2.19-1.3,3.01-10.02,9.16-20.04,18.32-30.06,27.48-.53,.49-1.05,.98-1.52,1.51-.1,.11,0,.36,.07,.53,.03,.06,.25,.13,.36,.1,3.11-.68,6.24-1.33,9.33-2.06,7.23-1.69,14.45-3.42,21.68-5.13,.4,0,1.2-.32,1.28,.14-12M .14,12.22-25.76,23.14-38.51,34.8-.7,.62-1.67,1.12-1.84,2.06-.18,.23-.16,.26,.08,.09l-.19-.14Z"/><path class="cls-2" d="M1030.77,1025.7c-1.66,2.19-3.4,4.29-5.21,6.31,.08-1.94,.14-3.88,.23-5.81-.27-3.38,3.05-1.01,4.98-.5Z"/><path class="cls-2" d="M1041.09,1074.32c-.25,3.29-.25,6.6-.89,9.83-.39,0-.83,.1-1.15-.01-2.56-.86-5.07-1.81-7.63-2.68,3.33-2.22,6.58-4.6,9.67-7.14Z"/><path class="cls-2" d="M1051.31,985.74c-2.51,7.48-5.61,14.91-9.11,21.7,0-8.35-.8-16.69-.91-25.03,.01-.25,.59-.57,.86-.47,3.13,1.1,6.12,2.48,9.16,3.8M Z"/><path class="cls-2" d="M1060.19,947.67c-1.06,7.47-2.48,14.94-4.28,22.26-.9-8.19-1.94-16.37-2.88-24.55,.3-1.86,5.91,1.97,7.16,2.29Z"/><path class="cls-2" d="M1074.71,918.05l-11.17-.27c-.2-1.07-.45-2.14-.63-3.22-.14-.8-.75-1.61-.06-2.42,1.19-.03,1.98,.63,2.86,1.09,3.01,1.59,6,3.21,9,4.82Z"/><path class="cls-2" d="M1240.27,858.9s.01-.05,.02-.07c.03,0,.07,0,.1,.01l-.12,.06Z"/><path class="cls-2" d="M1387.52,942.79c-.05,6.14-.02,12.28-.04,18.42-.21,.88-.39,1.52-1.49,.23-18.66-22.27-37.17-44.49-56.72-66.07-2.82-3.09-M 3.52-3.86-2.92,1.04,.65,4.82,1.35,9.63,2,14.45,.23,2.71,.65,4.97-2.17,1.73-16.55-18.23-32.41-37.8-50.5-54.32-.1,.03-.22,.16-.2,.24,1.26,6.71,2.85,13.36,4.31,20.03,.18,.81,.41,1.65,.04,2.47h-.02c-9.3-9.31-17.97-19.34-27.57-28.59-5.3-5.28-10.7-10.51-16.06-15.76-.53-.45-.99-1.15-1.8-1.02-.07,0-.2,.19-.17,.27,.74,2.73,1.47,5.47,2.25,8.19,1.19,4.19,2.41,8.38,3.61,12.57,.2,.71,.42,1.42,.22,2.16-1.23-.18-2-1.63-2.93-2.38-11.53-11.58-23.34-24-36.24-34.17-.14,.13-.36,.32-.32,.46,.29,1.05,.61,2.09,.95,3.13,2.02,6.14,4.06,12.M 28,6.08,18.42,.23,.72,.36,1.47,.52,2.2,0,.06-.12,.2-.2,.21-.91-.15-1.56-1.18-2.29-1.71-5.69-5.47-11.28-11-17.08-16.39-4.4-4.08-9.06-7.98-13.62-11.94-.42-.37-.82-.83-1.62-.72-.24,.89,.33,1.69,.61,2.49,1.92,5.49,3.94,10.97,5.88,16.46,.88,2.48,1.67,4.97,2.49,7.47-.02,.23-.4,.35-.6,.19-9.03-7.92-17.69-16.25-26.88-24.12-.91-.79-1.87-1.55-2.83-2.29-.11-.09-.42-.03-.62,.01-.06,.01-.13,.2-.1,.29,.31,.94,.61,1.87,.95,2.8,2.79,7.65,5.6,15.29,8.35,22.95,.33,.9,.9,1.81,.66,2.87-1.38-.33-2.18-1.5-3.24-2.31-6.83-5.81-13.66-11.63M -20.5-17.43-.83-.7-1.74-1.34-2.63-1.99-.08-.06-.33-.09-.38-.04-.71,.53,.02,1.38,.14,2.05,3.15,8.8,6.3,17.6,9.44,26.4,.18,.5,.53,.99,.15,1.53-1.13-.24-1.72-1.01-2.47-1.61-7-5.52-13.76-11.32-20.89-16.66-.19-.1-.89-.17-.88,.23,.76,2.29,1.54,4.57,2.33,6.85,2.47,7.16,4.96,14.32,7.42,21.48,.25,.73,.39,1.47,.56,2.21,.02,.09-.08,.27-.16,.28-.23,.03-.56,.09-.69-.01-.91-.64-1.77-1.32-2.65-1.99-5.19-3.92-10.37-7.86-15.56-11.77-2.98-2.17-3.36-2.08-2.1,1.54,3,8.72,5.79,17.48,8.45,26.27,.32,1.05,.62,2.1,.89,3.15,.04,.15-.14,.34-M .22,.52-1.03-.15-1.6-.79-2.29-1.29-4.44-3.14-8.85-6.31-13.28-9.46-1.18-.64-2.52-2.11-3.85-2.19-.39,.15-.41,.49-.34,.8,.15,.64,.31,1.27,.5,1.89,2.97,9.62,5.61,19.3,8.25,28.97,.09,.77,1.03,3.12-.11,2.85-5.9-3.5-11.33-7.74-17.33-11.1-.2-.06-.86-.07-.78,.34,1.91,8,4.08,15.96,5.82,23.98l-15.94-.39c-2.2-10.72-5.01-21.31-7.66-31.93-.07-.82-.84-2.17-.04-2.72,.67-.16,1.46,.56,2.08,.81,4.35,2.54,8.69,5.09,13.03,7.64,.52,.3,1,.68,1.72,.53,.3-.85,0-1.69-.24-2.5-1.93-6.81-3.89-13.62-5.86-20.43-1.06-3.67-2.18-7.32-3.25-10.99-.03M -.08,.06-.25,.14-.27,.76-.31,1.42,.27,2.05,.6,5.21,3.23,10.4,6.48,15.59,9.73,.19,.07,.87,.03,.83-.35-2.8-10.12-6.68-19.94-9.9-29.93-1.79-4.39,2.59-.57,4.07,.25,5.2,3.4,10.18,7.1,15.5,10.3,.35-.5,.22-.91,.07-1.32-3.38-9.65-6.91-19.23-10.51-28.8-.46-1.04,.27-1.31,1.37-.56,6.33,4.29,12.47,8.86,18.65,13.36,.59,.3,1.25,1,1.93,.95,.39-.4-.16-1.33-.25-1.84-3.16-8.23-6.32-16.45-9.48-24.67-.88-2.46-2.07-4.39,1.42-1.97,7.44,5.58,14.85,11.2,22.19,16.9l-.03,.09s.03-.05,.04-.08h.01s0-.02,0-.03c0,.01,0,.02-.02,.03h0l.05-.15s-.02M ,.08-.02,.11c.35-.71,.08-1.4-.18-2.08-1.08-2.77-2.15-5.55-3.27-8.32-1.96-4.81-3.97-9.6-5.92-14.42-.27-.67-.92-1.33-.43-2.12,.74,.04,1.22,.44,1.72,.79,1.91,1.37,3.82,2.73,5.71,4.11,6.17,4.5,12.36,8.99,18.13,13.83,.35,.3,.83,.49,1.27,.72,.05,.02,.3-.1,.29-.14-2.18-7.56-5.86-14.75-8.68-22.12-.17-.4-.34-.79,.02-1.18,1.21,.33,1.95,1.13,2.82,1.79,9.53,6.88,18.32,14.9,27.7,21.63,.15-.12,.37-.31,.33-.43-.28-.94-.6-1.88-.96-2.8-1.39-3.6-2.8-7.2-4.2-10.79-1.01-2.57-2.04-5.13-3.03-7.7-.1-.27-.01-.59-.01-.89,.81,.09,1.26,.52,1M .72,.9,4.64,3.76,9.33,7.48,13.87,11.31,5.75,4.84,11.38,9.78,17.07,14.67,.86,.54,1.52,1.84,2.64,1.63,.07-.01,.16-.19,.14-.27-.24-.84-.46-1.68-.75-2.51-2.1-5.9-4.21-11.8-6.31-17.7-.08-.48-.54-1.13-.25-1.55,.98-.09,1.69,.9,2.43,1.4,3.55,3.1,7.14,6.17,10.63,9.31,8.6,7.73,17.22,15.44,25.53,23.37,.5,.49,1.12,.9,1.71,1.33,.21,.13,.54,.04,.55-.22-1.51-7.11-4.17-14.01-6.09-21.04-.04-.14,.15-.34,.28-.48,1.17,.22,1.97,1.45,2.88,2.16,6.02,5.66,12.12,11.27,18.03,17.01,8.68,8.37,17.06,16.98,25.73,25.34,.06,.06,.29,.1,.34,.06,.17M -.12,.43-.3,.42-.44-.07-.75-.18-1.5-.35-2.24-1.16-4.97-2.36-9.94-3.52-14.92-.27-1.15-.41-2.33-.6-3.5-.01-.07,.11-.19,.21-.23,.11-.05,.33-.1,.38-.05,.48,.38,.96,.75,1.38,1.16,7.7,7.77,15.46,15.5,23.07,23.32,9.51,9.78,18.75,19.73,27.88,29.74,2.42,2.62,2.63,1.79,2.23-1.43-.7-5.57-1.51-11.13-2.23-16.7-.02-1.98,1.47-.33,2.23,.5,16.22,17.2,32.01,34.93,47.37,52.77,4.58,5.33,9.1,10.68,13.71,15.99,.89,1.03,1.3,2.06,1.29,3.3Z"/><path class="cls-2" d="M257.76,597.97c1.93-.77,3.29,1.94,4.75,2.88,7.59,6.85,15.18,13.69,22.78,20.M 53,1.13,.89,2.08,2.16,3.53,2.54,.68-.66-.5-2.46-.7-3.34-2.79-7.64-5.59-15.27-8.37-22.92-1.44-4.03,.26-2.29,2.26-.64,7.01,5.96,14.02,11.92,21.04,17.87,.83,.7,1.71,1.37,2.61,2.02,.12,.08,.46,0,.68-.05,.07-.01,.14-.19,.11-.27-.41-1.25-.83-2.49-1.27-3.73-2.95-8.39-6.17-16.69-8.98-25.12-.09-.29-.26-.64,.2-.8,1.29,.14,2.42,1.79,3.55,2.49,5.98,4.81,11.96,9.62,17.96,14.41,.65,.52,1.2,1.18,2.33,1.33,.12-1.9-1.14-3.68-1.6-5.53-2.68-7.77-5.35-15.55-8.03-23.33-.29-.83-.67-1.64-.39-2.52l-.11,.07c1.37,.01,2.29,1.39,3.42,2.05,5.9M 6,4.33,11.57,9.16,17.77,13.15,.9,.32,.45-1.04,.36-1.49-3.43-10.28-6.83-20.57-9.82-30.98,.17-.73,1.16-.02,1.53,.18,5.92,4.39,12.33,8.28,17.96,12.98,.05-.05,.11-.11,.16-.16l-.22,.14c.98-.84,.34-2.05,.12-3.08-2.99-9.61-5.66-19.28-8.26-28.96-.23-.84-.37-1.7-.5-2.55-.02-.14,.23-.33,.39-.46,.74-.08,1.57,.88,2.26,1.2,4.58,3.01,9.15,6.02,13.74,9.02,.6,.39,1.17,.91,2.21,.78-1.03-6.07-3.07-12-4.35-18.03-1.3-6.2-3.13-12.58-4-18.73,.64-.25,1.2,.14,1.73,.45,4.46,2.81,9.01,5.48,13.55,8.17,.61,.36,1.28,1.13,2.05,.7,.67-.38,.2-1.2M 2,.09-1.84-.28-1.6-.65-3.19-.95-4.78-1.07-5.75-2.14-11.5-3.2-17.25-.67-5.1-2.44-10.2-2.28-15.35,.67-.74,1.92,.48,2.65,.72,4.22,2.31,8.43,4.64,12.66,6.94,.33,.11,1.12,.41,1.4,.11-.26-7.39-2-14.77-2.74-22.15-.65-6.95-1.67-13.92-1.84-20.89,1.29-.32,2.2,.63,3.34,1.04,3.8,1.84,7.6,3.68,11.41,5.52,.57,.27,1.15,.59,1.89,.33-.48-15.29-1.83-30.75-1.87-46.13,.02-.58,0-1.59,.81-1.56,4.8,1.56,9.32,3.87,14.02,5.71,3.36,1.54,2.28-2.04,2.52-4.06,.26-16.24,.48-32.58,2.15-48.73,.74-.72,2.04,.26,2.89,.39,3.82,1.34,7.62,2.72,11.46,4.M 03,.83,.28,1.66,.77,2.68,.52,.01,0-.04-.05-.04-.05,.33,.36,.53,.76,.5,1.2-.23,3.55-.55,7.09-.81,10.64-1.09,13.43-1.83,26.87-2.22,40.34-.15,.83,.19,2.46-1.06,2.45-4.52-1.28-8.83-3.18-13.26-4.74-.61-.15-1.63-.63-2.1,0-.63,2.6-.23,5.38-.33,8.04,.03,12.93,.81,25.83,1.18,38.74,0,.25-.59,.56-.87,.45-1.21-.47-2.44-.91-3.63-1.41-3.33-1.42-6.64-2.86-9.96-4.29-.48-.21-.97-.35-1.54-.14,.34,14.16,2.83,28.33,4.25,42.45,.05,.4-.68,.73-1.17,.5-3.6-1.68-7.2-3.37-10.79-5.06-1.45-.6-2.64-1.66-4.26-1.72,1.25,13.08,4.5,26.06,6.72,39.0M 4-.04,.24-.47,.61-.78,.47-.94-.42-1.89-.82-2.79-1.3-3.59-1.91-7.16-3.84-10.73-5.76-.66-.36-1.29-.78-2.29-.81,1.41,10.01,4.36,19.92,6.74,29.83,.56,2.1,1.04,4.22,1.52,6.34,.03,.13-.23,.33-.4,.46-.59,.13-1.23-.42-1.76-.64-4.82-2.75-9.56-5.62-14.42-8.31-.29-.14-.76,.26-.78,.48,2.37,11.27,6.39,22.21,9.43,33.36-.16,1.16-2.49-.64-3.07-.89-4.77-2.99-9.54-5.97-14.29-8.99-.32-.2-.69-.39-1.07-.19-.15,.08-.21,.39-.17,.57,.2,.84,.42,1.69,.7,2.52,3,8.94,6.01,17.87,9,26.81,.24,.72,.39,1.46,.55,2.19,.02,.07-.12,.2-.22,.24-.99,.02-M 2.38-1.23-3.31-1.69-4.86-3.25-9.68-6.52-14.53-9.78-.52-.2-1.88-1.48-2.17-.61,.54,1.67,1.05,3.34,1.65,4.99,2.83,7.75,5.69,15.49,8.54,23.23,.13,.77,1.03,1.73,.29,2.35-.05,.04-.29,.02-.38-.04-6.59-4.14-12.68-9.02-19.07-13.46-.68-.49-1.23-1.16-2.25-1.26-.36,.41-.19,.82-.04,1.23,1.92,5.04,3.83,10.09,5.77,15.13,1.67,4.32,3.38,8.62,5.04,12.94,.05,.13-.16,.35-.3,.5-1.16-.24-2.15-1.3-3.14-1.94-6.32-4.85-12.63-9.7-18.96-14.54-.67-.51-1.21-1.17-2.21-1.32-.34,.56-.12,1.06,.08,1.58,3.2,8.23,6.48,16.43,9.86,24.59,.03,.08-.03,.26M -.1,.29-.74,.34-1.33-.32-1.93-.68-7.74-5.52-15.44-11.08-22.73-16.99-.67-.44-1.31-1.34-2.17-1.3-.56,.41-.04,1.26,.11,1.79,2.62,6.45,5.24,12.89,7.86,19.34,.21,.51,.38,1.03,.54,1.55,.03,.09-.06,.27-.14,.29-.77,.27-1.35-.4-1.93-.77-9.55-7.43-19.34-14.56-28.2-22.63-.06,.07-.11,.13-.15,.18l.21-.23c-1.02,1.01-.13,2.27,.21,3.38,2.32,5.95,4.65,11.89,6.96,17.84,.19,.68,.92,1.86-.4,1.54-11.76-8.88-22.65-18.71-33.81-28.11-.17-.09-.86-.14-.81,.27,1.98,6.6,4.61,13.01,6.84,19.54,.26,.72,.59,1.43,.33,2.2l.11-.07c-1.34-.06-2.25-1.4M 3-3.3-2.15-6.83-6.05-13.69-12.08-20.45-18.19-5.25-4.74-10.36-9.57-15.54-14.36-.34-.31-.63-.71-1.23-.75-.4-.03-.4,.44-.36,.71,1.88,6.25,3.76,12.51,5.66,18.75,.25,.84,.57,1.66,.38,2.53l.08-.06c-.61,.03-.98-.29-1.33-.61-14.43-13.12-28.47-26.75-42.07-40.53-.54-.36-3.92-4.45-4.2-3.04,1.42,6.47,3,12.91,4.52,19.36,.57,2.59-.79,1.75-2.07,.45-17.33-17.34-34.57-34.89-50.98-53.03-.6-.53-1.03-1.49-1.98-1.32-.06,0-.17,.18-.16,.28,.17,1.72,.3,3.43,.53,5.14,.65,4.82,1.35,9.63,2.02,14.45,0,.28,.05,.72-.32,.79-.61,.09-1.09-.58-1.52M -.9-4.52-4.83-9.06-9.65-13.52-14.51-16.16-17.61-31.73-35.51-47.18-53.66-1.28-1.43-2.72-2.98-2.35-4.99-.05-6.23-.16-12.48-.17-18.71,.36-.06,.73-.2,.82-.12,.46,.37,.9,.78,1.27,1.21,6.24,7.42,12.42,14.87,18.7,22.26,12.7,14.97,25.48,29.91,38.81,44.53,.74,.62,1.2,1.73,2.34,1.49-.46-7.1-1.89-14.13-2.72-21.21,.46-1.57,2.15,1.12,2.67,1.56,5.13,5.81,10.26,11.61,15.39,17.42,11.26,12.09,22.32,25.48,34.65,36.36,.09-.04,.2-.15,.2-.23-.03-.64,0-1.29-.13-1.91-1.33-6.83-3.44-13.57-4.36-20.43,1.88,.81,2.81,2.61,4.24,3.96,13.23,13.9M 1,26.63,28.81,41.3,41.25,.06-.2,.23-.42,.18-.61-.59-2.21-1.18-4.42-1.81-6.62-1.31-5.4-3.55-10.69-4.35-16.15,1.89,.81,2.89,2.56,4.37,3.9,11.15,11.16,22.61,22.97,34.98,32.9,.1-.03,.26-.15,.25-.21-.16-.74-.29-1.48-.53-2.2-2.23-6.76-4.48-13.52-6.72-20.29-.07-.45-.44-1.22-.1-1.55,.22-.04,.56-.1,.66,0,.74,.62,1.45,1.27,2.14,1.93,9.82,9.53,19.64,19.04,30.22,27.8,.89,.69,1.89,1.1,1.34-.63-2.68-7.56-5.36-15.12-8.09-22.67-.29-.81-.34-1.72-1.16-2.37l-.02,.03Z"/><path class="cls-2" d="M138.15,1155.19c1.49-6.81,2.57-13.68,4.7-2M 0.35l-.15,.11c15.17,2,30.38,3.66,45.61,5.06,10.96,1.06,22.02,1.32,32.95,2.72l-.09-.1c-2.03,4.9-4.08,9.8-6.1,14.7-.38,.91-.67,1.85-.95,2.78-.04,.13,.19,.43,.36,.47,22.24,1.54,44.62,1.24,66.91,1.56,.32,.52,.16,.92-.08,1.32-1.49,2.53-2.96,5.07-4.45,7.61-1.32,2.24-2.66,4.47-3.97,6.71-.26,.51-.88,1.32-.18,1.7,16.08,.32,32.28-1.03,48.37-1.86,3.22-.2,6.44-.43,9.67-.6,1.03-.04,1.34,.44,.79,1.24-3.39,4.79-6.97,9.46-10.42,14.21-.83,1.21-1.96,2.48,.47,2.3,17.22-1.24,34.55-3.64,51.62-5.11,.51,.85-.71,1.53-1.09,2.23-4,4.73-8.01M ,9.45-12,14.18-.43,.51-1.08,.97-.82,1.74,12.23-.95,24.38-3.38,36.56-4.99,3.7-.57,7.38-1.21,11.07-1.81,.24-.04,.74,.05,.74,.1,.14,.83-.53,1.37-1.05,1.93-5.05,5.76-11.06,11.23-15.59,17.19,.57,.62,1.43,.15,2.15,.1,4.47-.76,8.94-1.56,13.42-2.3,9.83-1.56,19.44-3.75,29.23-5.39-.34,1.49-1.65,2.18-2.6,3.29-5.23,5.21-10.47,10.41-15.7,15.61-.45,.64-1.72,1.25-1.42,2.09,13.3-1.75,26.66-5.19,39.89-7.81,.51-.11,1.02-.32,1.64-.06-.64,1.57-2.34,2.52-3.47,3.78-6.01,5.67-12.02,11.33-18.03,17.01-.52,.49-1,1.01-1.48,1.52-.07,.07-.08,.M 26-.02,.31,.6,.56,1.46,.17,2.17,.09,12.02-2.23,24.27-5.88,36.28-7.4-.38,1.57-2.12,2.4-3.16,3.57-7.22,6.54-14.45,13.07-21.67,19.61-.62,.56-1.2,1.16-1.78,1.75-.07,.07-.12,.26-.06,.3,.15,.12,.39,.29,.55,.26,11.4-2.07,22.67-4.7,33.95-7.19,.6-.12,1.25-.37,1.8,.02,.04,.02,0,.22-.08,.3-9.5,8.88-19.45,17.28-29.11,25.98-.73,.72-1.8,1.21-1.93,2.3,.93,.22,1.83,.05,2.74-.18,10.4-1.94,20.68-4.31,31.12-6.01-.59,1.55-2.06,2.25-3.2,3.39-10.74,9.7-23.56,19.18-33.45,29.2,.46,.37,1.66,.09,2.25,.08,9.65-1.36,19.22-3.58,28.92-4.38l-.05M -.09c.03,.2,.18,.48,.07,.59-.76,.75-1.53,1.5-2.37,2.2-7.55,6.3-15.12,12.58-22.68,18.88-5.5,4.59-10.98,9.19-16.47,13.79-.29,.4-1.68,1.01-1.17,1.53,.17,.13,.46,.23,.69,.22,1.88-.13,3.76-.27,5.63-.46,5.88-.58,11.76-1.18,17.64-1.76,1.46-.15,2.93-.26,4.4-.37,.07,0,.18,.11,.21,.18,.04,.1,.09,.25,.03,.31-.68,.66-1.34,1.34-2.09,1.95-15.58,12.86-31.26,25.62-47.03,38.27-2.14,1.71-2.06,1.63-4.96,1.63-6.87,.01-13.75,.02-20.62,.02-3.63,.05-3.89-.42-.84-2.71,14.76-11.96,29.77-23.64,44.32-35.85,.13-.13,.07-.4,.05-.6-.65-.29-1.6-.M 09-2.33-.1-8.3,.73-16.59,1.56-24.88,2.32-1.18,.09-2.28-.05-.9-1.29,12.46-10.29,24.91-20.6,37.36-30.91,.48-.56,2.91-2.17,1.79-2.43-10.46,.94-20.88,3.59-31.36,4.24,.03-.24-.05-.51,.08-.64,.87-.82,1.78-1.61,2.7-2.39,9.61-8.15,19.23-16.3,28.84-24.45,1.04-1.01,2.38-1.71,2.94-3.08-9,1-17.91,3.11-26.88,4.5-1.01,0-9.91,2.41-6.69-.38,8.99-7.86,17.97-15.76,26.9-23.68,1.4-1.38,2.67-2.31-.39-1.89-10.21,1.95-20.42,3.92-30.62,5.9-.75,.08-4.38,1.11-4.28-.05,8.18-7.91,16.91-15.29,25.03-23.26,.22-.87-.62-.64-1.19-.51-11.72,2.46-23.M 6,4.37-35.4,6.56-.91,.01-2.29,.66-2.99-.05-.08-.16,.01-.44,.16-.59,.74-.77,1.51-1.52,2.28-2.26,5.77-5.55,11.55-11.1,17.32-16.65,.51-.49,.99-1.02,1.46-1.54,.07-.07,.09-.25,.03-.31-.34-.39-.86-.4-1.34-.29-10.25,1.8-20.5,3.63-30.76,5.4-3.42,.59-6.88,1.03-10.32,1.52-.17,.02-.42-.16-.58-.29-.07-.05-.06-.24,0-.31,.78-.88,1.55-1.76,2.37-2.61,4.86-5.03,9.74-10.05,14.59-15.08,.56-.58,1.32-1.1,1.33-2.06-10.47,1.08-20.83,3.25-31.33,4.4-5.17,.46-10.31,1.8-15.5,1.77,0-.28-.1-.54,.02-.69,.56-.73,1.17-1.45,1.78-2.15,3.78-4.32,7.5M 8-8.64,11.36-12.97,.69-.79,1.34-1.61,1.99-2.43,.06-.07,.06-.24,0-.3-.15-.15-.37-.38-.54-.37-1.48,.1-2.96,.2-4.42,.39-10.64,1.39-21.35,2.34-32.02,3.49-4.55,.43-9.11,.75-13.67,1.09-1.95-.09,.22-2.02,.64-2.76,3.62-5.04,7.81-9.73,11.08-14.99,.05-.1-.22-.45-.35-.45-5.24-.11-10.45,.72-15.68,.96-12.63,.77-25.28,1.26-37.93,1.8-.83-.13-3.49,.54-3.41-.68,3.08-5.66,6.84-10.94,9.95-16.59,.19-1.16-1.78-.72-2.5-.85-4.45,.05-8.89,.14-13.34,.19-14.96,.21-29.91-.27-44.87-.55-1.21-.03-2.41-.14-3.62-.21-.3-.02-.72-.49-.63-.71,.31-.82M ,.61-1.65,.96-2.46,1.93-4.92,4.5-9.65,6.06-14.69,.03-.15-.18-.38-.36-.48-2.05-.5-4.28-.39-6.39-.61-16.53-.77-33.02-2.06-49.49-3.62-5.21-.52-10.42-1.08-15.63-1.6-1.05-.1-2.13-.33-3.19,.01l.12,.1Z"/><path class="cls-2" d="M1009.12,190.08c12.91-2.58,25.93-4.91,38.93-7.08,1.98,.1-1.1,2.24-1.51,2.82-5.68,5.46-11.36,10.92-17.04,16.38-.85,.95-2.06,1.61-2.38,2.89,11.93-1.59,23.69-4.1,35.59-5.98,2.23-.38,4.5-.62,6.76-.89,.19-.02,.53,.13,.6,.27,.08,.97-1.46,1.87-2.02,2.67-5.29,5.57-10.8,10.95-15.95,16.65-.3,1.52,7.01-.38,8.1M 6-.35,11.63-1.79,23.27-3.53,34.96-4.92,1.17-.14,2.38-.44,3.58-.07l-.09-.07c.12,1.41-1.41,2.22-2.14,3.3-3.78,4.32-7.56,8.64-11.33,12.97-.54,.62-1.02,1.26-1.51,1.91-.15,.31,.38,.6,.61,.62,8.55-.65,17.06-1.9,25.6-2.69,8.41-.67,16.89-2.21,25.29-2.13,0,1.26-1.16,2.11-1.81,3.13-3.27,4.33-6.54,8.66-9.81,12.99-.41,.69-1.18,1.24-.8,2.1,19.13-1.24,38.05-2.36,57.27-2.98,.22,1.55-.92,2.46-1.57,3.73-2.72,4.56-5.65,9.02-8.23,13.66-.31,1.25,3.35,.66,4.16,.83,11.04,0,22.08-.1,33.12-.02,9.01,.14,18.04,.24,27.04,.69,1.42,.37,.08,1.9M 5-.1,2.84-2.04,5.01-4.36,9.92-6.25,14.98-.09,.26,.28,.67,.63,.69,2.95,.21,5.9,.47,8.85,.59,13.56,.66,27.08,1.8,40.6,3.04,7.22,.65,14.43,1.41,21.64,2.1,1.01-.02,2.21,.4,3.03-.31l-.02-.05c.15,.74,.3,1.46,.13,2.22-1.25,6.1-2.99,12.13-3.81,18.31l.11-.08c-17.4-1.82-34.76-4.14-52.22-5.53-9.05-.94-18.19-.99-27.2-2.25l.14,.09c2.26-5.41,4.57-10.81,6.84-16.21,.73-1.81-.08-1.85-1.67-1.94-21.78-1.09-43.6-1.27-65.4-1.33-.57-.91,.32-1.65,.67-2.48,2.75-4.79,5.74-9.47,8.34-14.34-.1-1.1-1.84-.69-2.63-.79-9.83,.32-19.66,.59-29.48,.9M 9-8.87,.43-17.72,1.17-26.6,1.62-2.08-.15,.58-2.57,.94-3.41,2.8-3.81,5.62-7.6,8.42-11.4,.55-.74,1.05-1.5,1.52-2.27,.09-.15-.07-.39-.15-.69-14.44,.91-28.86,2.69-43.26,4.2-3.07,.33-6.14,.63-9.21,.93-.32,.03-.73-.48-.59-.7,.19-.29,.35-.58,.57-.85,4.02-4.86,8.16-9.63,12.22-14.46,1.76-2.25,1.58-2.29-1.23-2.09-11.94,1.6-23.88,3.25-35.79,5.1-3.3,.51-6.6,1.07-9.9,1.6-.1,.02-.3-.07-.33-.14-.08-.18-.19-.42-.1-.57,1.15-1.61,2.66-2.98,3.98-4.47,3.7-3.97,7.42-7.94,11.11-11.92,.56-.6,1.06-1.24,1.57-1.87,.06-.08,.07-.26,0-.31-.41-M .33-.92-.3-1.4-.18-13.28,2.32-26.6,4.5-39.77,7.22-1.03,.21-2.11,.27-3.16,.38-.21,.02-.48-.27-.36-.46,5.48-5.92,11.42-11.43,17.07-17.2,.76-.76,1.52-1.51,2.24-2.29,.14-.15,.23-.54,.17-.57-.94-.52-2-.08-2.99,.06-11.94,2.2-23.81,4.6-35.61,7.23-3.07,.45-3.67,.45-.98-2,6.35-6.01,12.71-12.01,19.06-18.01,.7-.66,1.39-1.32,2.04-2,.11-.11,0-.37-.06-.55-.78-.29-1.87,.2-2.72,.27-11.96,2.3-23.91,5.61-35.88,7.4,.13-1.29,1.54-1.9,2.35-2.79,8.06-7.39,16.31-14.59,24.28-22.08,.49-1.17-1.3-.53-1.9-.5-10.32,2.05-20.59,4.24-30.81,6.6-2.M 75,.58-5.11,1.24-1.56-1.73,9.77-8.77,19.76-17.32,29.43-26.2,.29-1.01-2.9-.03-3.51-.03-9.01,1.79-18.02,3.59-27.04,5.38-4.72,1-3.52-.02-.68-2.46,10.39-8.9,20.78-17.79,31.17-26.69,.92-.79,1.83-1.58,2.7-2.4,.12-.11,.04-.38,0-.57-9.83,.66-19.82,3.04-29.68,4.41-2.76,.3-1.06-.91,0-1.95,12.99-10.95,26.1-21.78,39.16-32.67,.74-.62,1.38-1.31,2.04-1.97,.06-.06,.01-.22-.05-.31-9.47,.1-19.17,1.9-28.75,2.52-.28-.96,1.26-1.71,1.85-2.37,15.37-12.55,30.67-25.19,46.18-37.58,1.57-1.32,3.13-2.75,5.36-2.39,7.55,0,15.09-.01,22.64-.01,3.4M 8-.02,.72,1.55-.48,2.67-9.22,7.41-18.45,14.8-27.67,22.21-5.03,4.05-10.04,8.13-15.04,12.2-.57,.6-1.89,1.25-1.53,2.12,6.16-.21,12.3-1.16,18.45-1.62,3.21-.29,6.43-.51,9.64-.76,.34-.03,.52,.13,.5,.38-11.87,10.8-25.06,20.73-37.36,31.24-.93,.77-1.78,1.61-2.65,2.42-.24,.31,.34,.58,.55,.58,10.32-1.37,20.61-3.54,30.98-4.25-.03,.28,.05,.55-.09,.68-.78,.74-1.6,1.46-2.43,2.16-10.71,9.1-21.43,18.2-32.11,27.3,.29,.28,.38,.28,.23,.05-.04-.06-.22-.05-.34-.08,2.52,.76,5.3-.53,7.87-.72,8.82-1.41,17.56-3.38,26.44-4.4,.11-.01,.35,.07,M .35,.12,.01,.2,.05,.46-.08,.59-9.24,8.29-18.63,16.41-27.92,24.64-.39,.46-1.29,1-1.32,1.56,.42,.32,.92,.28,1.41,.15,10.07-1.94,20.13-3.88,30.2-5.81,1.69-.32,3.41-.55,5.12-.81,.1-.02,.28,.07,.34,.15,.06,.08,.06,.24,0,.31-.46,.52-.91,1.05-1.43,1.53-7.24,6.66-14.49,13.31-21.74,19.97-.8,.88-2.15,1.56-1.64,2.67,.04-.32-.06-.4-.3-.26l.3,.19Z"/><path class="cls-2" d="M892.55,367.68c2.59-4.6,5.15-9.23,7.76-13.82-.68-.63-1.44-.2-2.21-.07-13.91,3.39-27.43,7.57-41.1,11.6-.2,.02-.87-.17-.68-.53,2.24-4.3,4.98-8.34,7.41-12.54,1.1M 5-2.14-1.44-.91-2.47-.66-5.23,1.71-10.48,3.38-15.67,5.18-7.3,2.27-14.42,5.71-21.79,7.46-.28-.11-.36-.31-.22-.55,1.85-3.11,3.69-6.22,5.57-9.32,.88-1.45,1.85-2.87,2.77-4.31,.17-.27,.4-.61,.01-.85-.35-.23-.74-.04-1.1,.09-4.4,1.63-8.83,3.19-13.18,4.89-7.86,2.86-15.56,6.72-23.46,9.16-.59-.67,.26-1.39,.54-2.04,2.55-4.03,5.11-8.06,7.66-12.1,.24-.58,1.11-1.48,.88-2.04-.15-.24-.39-.3-.69-.18-4.17,1.75-8.37,3.45-12.49,5.26-5.19,2.29-10.3,4.68-15.3,7.23-.67,.34-1.43,.56-2.16,.82-.06,.02-.21-.08-.29-.15-.08-.07-.2-.2-.17-.26,.M 25-.61,.48-1.23,.82-1.81,2.56-4.39,5.14-8.77,7.7-13.16,1.96-3.3-.09-1.97-2.08-1.11-7.09,3.53-14.16,7.07-21.25,10.6-2.46,1.05-5.9,3.67-2.92-1.2,2.83-4.76,5.68-9.52,8.52-14.28,.52-.93,1.51-1.99,.55-2.98,.15,.13,.29,.26,.43,.39h.01l-.42-.39c-.31,.54-.87,.81-1.43,1.07-8.55,3.88-16.42,8.67-24.73,12.8-.09,.04-.33,.03-.35-.01-.1-.18-.27-.42-.19-.56,3.38-6.52,7.53-12.63,11.38-18.9,.33-.79,1.5-1.82,.98-2.64-.76-.09-1.71,.65-2.44,.92-7.44,3.88-14.86,7.77-22.26,11.73-.42,.22-.96,.65-1.39,.37-.71-.46,0-.97,.24-1.43,4.59-7.81,9M .75-15.31,14.28-23.16-.2-.8-1.43,.03-1.91,.17-6.89,3.56-13.81,7.06-20.59,10.82-2.67,1.44-3.33,1.67-3.4,1.27-.16-1.02,.65-1.79,1.16-2.63,4.47-7.48,9.35-14.79,14.2-22.11,3.14-4.35,2.79-4.62-1.93-2.18-6.99,3.44-13.89,7.06-20.92,10.4-1.78,.19,.02-1.75,.35-2.4,6.16-10.35,13.96-20.21,20.1-30.47-.17-.22-.42-.26-.71-.15-.97,.37-1.95,.72-2.9,1.11-4.53,1.9-9.05,3.82-13.57,5.72-1.21,.43-2.35,1.26-3.68,.89l.12,.03c6.15-10.43,13.75-20.24,20.75-30.29,1.68-2.33,3.27-4.7,4.88-7.05,.04-.06-.03-.19-.09-.26-.08-.08-.24-.19-.31-.17-.7M 6,.21-1.53,.4-2.27,.66-5.9,2.12-11.78,4.25-17.67,6.38-.83,.37-1.36,.13-.92-.92,.4-.67,.89-1.33,1.33-1.99,3.85-5.44,7.64-10.9,11.57-16.3,5.08-6.98,10.19-13.95,15.6-20.78,.71-.9,1.28-1.87,1.9-2.82,.04-.07-.01-.21-.08-.28-.08-.08-.24-.19-.32-.18-1.03,.22-2.07,.43-3.07,.72-5.07,1.45-10.13,2.92-15.2,4.38-1.01,.29-2.04,.56-3.06,.82-.32,.1-.64-.42-.58-.62,9.24-13.34,19.18-26.19,29.29-39.05,2.46-3.09,4.9-6.19,7.33-9.29,.1-.13,0-.39-.08-.57-.27-.24-.8-.13-1.15-.08-6.16,1.1-12.27,2.48-18.41,3.69-1.04,.21-2.1,.36-3.17,.5-.18,M .02-.43-.17-.6-.3,12.55-17.88,27.1-34.95,41.11-52.14,.9-1.07,1.82-2.14,2.72-3.21,.3-.36,.54-.74,.4-1.21-.92-.3-1.85-.11-2.78,0-6.81,.75-13.61,1.52-20.41,2.27-.44,0-1.79,.18-1.55-.49,17.01-22.29,35.32-43.79,54.04-64.72,7.84-.29,15.65-.1,23.5-.19,.8,.13,3.66-.3,3.23,.89-9.18,10.29-18.82,20.21-27.84,30.56-8.48,9.59-17.02,19.14-25.18,28.9-.45,.54-.88,1.09-1.25,1.66-.06,.1,.17,.44,.34,.48,8.16-.2,16.27-2.08,24.44-2.09,.21,.99-.83,1.58-1.34,2.31-9.44,10.5-18.79,21.04-27.8,31.78-5.03,5.99-10.01,12.01-14.99,18.03-.51,.62-1M .21,1.18-1.28,1.97-.01,.15,.3,.48,.4,.46,6.97-1.17,13.87-2.65,20.81-3.99,.56-.08,2.72-.46,2.32,.33-12.28,15.46-25.68,30.19-37.5,45.99-1.06,1.33,.18,1.2,.97,1.1,6.37-1.74,12.73-3.5,19.1-5.25,.58-.07,1.36-.47,1.9-.19,.09,.17,.23,.41,.14,.53-.82,1.11-1.65,2.22-2.54,3.3-9.76,12.39-20.67,24.57-28.96,37.54,.07,.08,.22,.18,.3,.16,.76-.21,1.53-.41,2.27-.66,5.46-1.85,10.91-3.7,16.36-5.55,1.09-.33,2.33-.96,3.41-.29v-.04c-9.71,11.25-18.38,23.51-27.13,35.53-.09,.15,.05,.4,.13,.59,.02,.04,.23,.09,.31,.06,8.02-3.25,15.9-6.81,23.M 87-10.18,1.96-.8,3.05-1.05,1.31,1.25-5.79,7.89-11.61,15.78-17.38,23.68-1.29,1.76-2.44,3.59-3.63,5.4-.09,.13,.08,.38,.18,.56,1.18-.11,2.37-.98,3.52-1.39,7.01-3.21,14.01-6.43,21.03-9.63,.56-.25,1.21-.38,1.82-.55,.04,0,.23,.18,.21,.24-5.31,8.5-11.6,16.49-17.26,24.8-.52,.74-.88,1.58-1.77,2.13,0,0,.2,.09,.2,.09l-.12-.17c1.03,.8,2.21-.15,3.2-.57,6.66-3.18,13.31-6.35,19.97-9.53,1.53-.62,2.95-1.67,4.64-1.74l-.08-.06c.08,1.39-1.22,2.33-1.89,3.46-4.77,6.74-9.65,13.35-13.69,20.48,.31,.86,2.36-.6,2.99-.78,8.12-3.89,16.29-8.25,M 24.79-11.34,.63,.11-.33,1.33-.47,1.69-3.77,5.71-7.55,11.41-11.33,17.12-.39,.77-1.25,1.47-1.02,2.37-.18,.01-.43,.01-.35,.24,.26,.05,.35-.05,.27-.3,1.59,.13,2.88-.97,4.3-1.53,7.94-3.65,15.67-7.72,23.83-10.89,.35-.09,.84,.2,.55,.57-3.78,5.69-7.77,11.33-11.17,17.19-.15,.26-.14,.59-.17,.88,0,.07,.19,.22,.25,.21,2.86-.75,5.47-2.3,8.21-3.41,7.62-3.45,15.48-6.52,23.38-9.55,.45-.09,1.05-.52,1.45-.15,.07,.07,.16,.2,.12,.26-.33,.58-.65,1.17-1.04,1.73-3.2,4.49-6.42,8.97-9.62,13.46-.4,.56-.7,1.16-1.02,1.74,.11,.53,.85,.42,1.25,M .27,12.33-4.58,24.64-10.16,37.28-13.73,.62,.26-.33,1.3-.58,1.7-2.83,4.16-5.66,8.32-8.48,12.49-.17,.51-1.45,1.65-.7,1.98,12.37-3.76,24.7-8.51,37.25-12.24,1.24-.24,2.55-1.08,3.79-.63-11.29,18.87-15.91,16.75,7.36,10.31,8.97-2.43,18.07-5.34,27.17-7.06,.11,.04,.28,.16,.27,.2-.14,.41-.25,.83-.49,1.21-2.64,4.23-5.51,8.33-7.96,12.67,1.07,.6,2.07-.05,3.16-.21,14.81-3.39,29.8-7.26,44.81-9.4,.72,.23-.11,1.28-.35,1.71-1.93,3.2-3.87,6.4-5.78,9.6-.46,.76-1.09,1.48-1.04,2.39,.79,.37,1.58,.16,2.36,.03,3.55-.62,7.08-1.31,10.65-1.86M ,12.59-1.85,25.13-3.94,37.81-5.19,.9,0,2.53-.4,1.93,1.08-2.37,4.22-4.76,8.43-7.15,12.65l.08-.06c-8.06,1.62-16.8,1.91-25.01,3.31-9.84,1.14-19.46,3.23-29.28,4.45l.09,.08c2.17-3.92,4.28-7.88,6.53-11.76,.21-.41,.72-1.07,.52-1.49-.28-.17-.71-.36-1.02-.3-4.05,.73-8.12,1.43-12.14,2.26-11.81,2.46-23.59,5.02-35.21,7.99l.07,.12Z"/><path class="cls-2" d="M342.27,130.02c-3.54,23.39-7.76,46.69-10.31,70.21-6.34-1.78-14.07-4.47-20.88-6.58-.61-.19-1.74-.64-2.08,.1-2.35,19.96-3.22,40.05-4.55,60.1l.14-.05c-6.97-3.26-13.86-6.7-20.88-M 9.84-.5-.21-1.06,.08-1.1,.58-.49,16.47-.85,32.96-.31,49.44,.13,3.28-.82,2.45-3.07,1.21-5.91-3.58-11.72-7.28-17.71-10.73-.23-.13-.72,.03-1.19,.06,.13,12.64,1.06,25.23,1.81,37.84,.16,2.69,.26,5.38,.36,8.07,0,.18-.17,.37-.27,.56-.59,.5-1.73-.62-2.32-.95-5.8-4.17-11.45-8.51-17.18-12.76-.58-.33-1.22-1.05-1.91-1.03-.25,.2-.6,.41-.52,.77,1.12,13.44,2.31,26.87,3.78,40.27-.02,2.7-2.85-.79-3.77-1.31-5.87-4.9-11.73-9.81-17.61-14.71-.51-.37-1.72-1.46-1.98-.33,.58,5.37,1.32,10.72,2.03,16.07,.93,7.07,1.82,14.14,2.81,21.2,.02,.41M -.7,.36-.87,.28-7.77-6.8-15.16-14.02-22.8-20.97-2.46-2.08-.46,4.72-.56,5.73,1.3,9.53,3.15,18.99,4.4,28.52-.37,0-.73,.09-.85-.01-.83-.7-1.66-1.41-2.41-2.16-7.8-7.67-15.25-15.72-23.24-23.18-.15-.1-.57-.06-.59,.17,.24,1.92,.44,3.85,.75,5.77,1.33,8.22,2.77,16.43,4.08,24.66,.07,.47,.64,1.15-.2,1.36-.71,.18-1.05-.56-1.43-.97-6.44-6.91-12.86-13.83-19.29-20.75-2.49-2.68-4.97-5.36-7.48-8.04-.13-.14-.43-.18-.67-.24-.49,0-.35,1.07-.37,1.41,.79,6.33,2.08,12.6,2.94,18.91,1.9,10.74,1.83,10.3-5.12,2.33-8-9.06-16-18.13-24-27.19-.6M 7-.59-1.12-1.73-2.1-1.79-.16,.02-.41,.29-.39,.43,.49,3.97,.99,7.93,1.52,11.89,.45,4.58,1.56,9.28,1.71,13.79-1.17,.02-1.85-1.45-2.65-2.17-11.3-12.87-21.8-26.74-33.48-39.12-1.06-.13-.3,2.83-.38,3.58,.42,6.43,1.46,12.91,1.56,19.32-.61,.63-1.21-.48-1.62-.86-12.59-15.42-25.18-30.85-37.76-46.28-.72-.86-1.56-1.78-1.46-2.93-.13-6.03-.08-12.06-.08-18.1,0-.53,.14-1.06,.25-1.58,.07-.12,.54-.21,.66-.12,12.13,14.03,23.68,28.57,35.68,42.71,.69,.63,1.13,1.77,2.24,1.53-.26-7.3-1.14-14.6-1.6-21.9-.03-.41,.11-.83,.21-1.24,.01-.05,.2M 8-.13,.36-.09,11.01,11.86,21.25,24.65,32.01,36.82,.52,.64,1.02,1.33,1.89,1.53,.3,.08,.48-.22,.41-.73-.34-2.79-.68-5.57-1.03-8.36-.72-5.57-1.45-11.13-1.98-16.72-.02-.17,.15-.37,.28-.53,.05-.05,.32-.07,.37-.03,.62,.56,1.28,1.1,1.83,1.71,4.57,5.07,9.1,10.16,13.68,15.22,4.42,4.89,8.89,9.75,13.34,14.62,.39,.44,1.01,1.29,1.75,1.02,.29-2.87-.72-5.77-.96-8.65-.9-6.2-1.73-12.41-2.55-18.62-.08-.77-.61-2.74,.82-2,8.54,8.71,16.88,17.62,25.4,26.36,.62,.54,1.14,1.4,2.08,1.32,.04,0,.15-.16,.14-.25-.14-1.18-.29-2.35-.45-3.53-1.21-M 9.61-3.12-19.2-3.83-28.85,1.21-.21,1.88,1.01,2.74,1.65,6.96,6.72,13.9,13.46,20.86,20.18,.73,.54,1.38,1.53,2.3,1.68,.29,0,.47-.14,.44-.41-.54-5.05-1.33-10.06-1.99-15.09-.81-6.75-1.58-13.51-2.34-20.27-.02-.15,.23-.4,.41-.45,1-.06,1.62,1.04,2.37,1.55,6.36,5.57,12.72,11.14,19.08,16.71,.77,.52,1.43,1.56,2.47,1.37,.08,0,.2-.14,.19-.22-.04-.97-.05-1.93-.15-2.9-1.16-12.21-2.94-24.49-3.41-36.71,.93-.27,1.59,.53,2.3,.98,6.04,4.61,12.08,9.23,18.12,13.85,1.25,.87,3.03,2.66,2.83-.23-.94-14.28-2.08-28.59-2.43-42.88,1.16-.36,1.94M ,.46,2.88,.96,4.75,3.02,9.48,6.05,14.22,9.07,1.63,.84,3.1,2.36,4.92,2.66,.94-.15,.49-1.65,.59-2.35-.1-15.51-.57-31.02-.23-46.53,.03-2.72,3.03-.23,4.32,.25,5.25,2.63,10.5,5.26,15.76,7.88,.7,.25,1.8,1.05,2.45,.41,.98-17.71,1.59-35.52,2.83-53.25,.28-1.09-.26-3.83,1.47-3.51,6.48,2.13,12.95,4.26,19.43,6.38,1.43,.49,2.88,.94,2.99-1.09,1.69-16.65,3.83-33.25,6.03-49.84,.78-4.9,1.05-9.93,2.49-14.7l-.13,.09c5.91,.99,11.83,1.98,17.74,2.97,2.36,.26,4.73,1.12,7.1,.69l-.1-.1Z"/><path class="cls-2" d="M1256.91,1041.89c1.6-.11,2.3M 3,1.51,3.38,2.42,8.52,9.16,16.93,18.41,25.51,27.51,.35,.28,1.03,.21,.98-.38-.55-3.63-1.12-7.27-1.68-10.9-.86-5.66-1.79-11.32-2.6-16.99-.02-.13,.23-.4,.39-.41,1.2,.1,1.96,1.81,2.84,2.56,9.02,10.2,18.03,20.41,27.06,30.61,.75,.64,1.41,2.02,2.52,1.76-3.48-34.04-8.49-32.03,14.6-5.95,5.99,7.02,11.79,14.21,17.88,21.14,.22,.32,.75,.26,.91-.09,.06-.32,.13-.64,.11-.95-.5-6.88-1.14-13.75-1.68-20.63,.03-.33,.22-1.02,.68-.92,.38,.3,.78,.59,1.08,.94,2.38,2.87,4.74,5.76,7.1,8.64,9.86,12.09,19.73,24.17,29.57,36.27,2.29,2.82,2.05,2M .02,2.07,5.71,.01,2.26,0,4.52,0,6.79-.01,3.55,.1,7.11-.06,10.66-.49,1.64-2.67-1.77-3.18-2.23-7.07-8.53-14.12-17.06-21.19-25.59-3.8-4.58-7.61-9.14-11.44-13.71-.48-.42-1.18-1.58-1.84-1.53-.42,0-.47,.43-.49,.75,.36,7,1.04,13.98,1.59,20.96,.03,.32-.04,.64-.1,.96-.06,.14-.52,.24-.65,.17-8.12-8.56-15.45-17.92-23.29-26.75-3.43-3.84-6.59-7.95-10.23-11.61-.13-.07-.57,.03-.64,.18,.18,7.15,1.75,14.36,2.41,21.52,.17,1.38,.15,2.78,.2,4.18,0,.06-.14,.15-.24,.19-.11,.04-.33,.09-.37,.05-.54-.47-1.11-.94-1.58-1.46-4.41-4.89-8.8-9.8M -13.21-14.69-4.26-4.71-8.56-9.41-12.84-14.11-4.63-5.33-2.67-.04-2.35,3.29,1.15,7.8,2.32,15.59,3.07,23.44-.13,.93-1.38-.06-1.69-.44-8.34-8.74-16.72-17.44-25.09-26.15-.32-.33-.73-.61-1.12-.9-.51-.11-.53,.66-.54,1.01,.42,3.21,.87,6.42,1.32,9.63,.85,6.21,1.76,12.41,2.61,18.62,.14,1.07,.17,2.14,.23,3.21,0,.09-.1,.26-.15,.26-1.33,.05-2.1-1.55-3.12-2.26-6.96-6.72-13.9-13.45-20.86-20.17-.67-.57-1.18-1.37-2.21-1.21,.49,6.22,1.63,12.41,2.32,18.62,.71,5.57,1.38,11.14,2.05,16.72,.03,.29-.1,.6-.2,.89-.01,.04-.3,.09-.37,.05-.53-M .31-1.09-.61-1.53-.99-5.01-4.37-9.98-8.76-14.99-13.12-2.18-1.9-4.41-3.77-6.65-5.63-.12-.1-.5-.04-.75,0-.25,.29-.13,.85-.14,1.24,.9,8.8,2.03,17.58,2.79,26.4,.32,3.54,.62,7.09,.91,10.64-.08,.56,.33,1.65-.53,1.68-.73-.03-1.31-.7-1.91-1.06-6.23-4.76-12.46-9.54-18.69-14.3-.47-.36-.88-.81-1.62-.85-1.24,.09-.11,5.37-.25,6.53,.84,12.47,1.73,24.94,2.05,37.43-.36,1.37-2.43-.44-3.12-.77-5.39-3.4-10.72-6.89-16.12-10.27-.98-.47-1.62-1.48-3.04-1.27-.68,.78-.32,1.65-.31,2.48-.03,15.71,1.01,31.48,.09,47.15-.03,.22-.7,.54-.93,.44-.M 94-.42-1.88-.83-2.79-1.28-5.99-2.87-11.79-6.14-17.89-8.78-.29-.12-.87,.17-.89,.44-.87,18.71-1.35,37.49-3.06,56.14-.05,.27-.61,.52-.94,.42-6.49-2.08-12.95-4.25-19.43-6.36-.85-.13-2.26-.99-2.85-.05-2.31,16.79-3.74,33.69-6.3,50.46-.61,4.39-1.21,8.78-1.83,13.16-.11,.75-.25,1.5-.95,2.08,0,0,.14-.08,.14-.08-7.67-1.61-15.52-2.62-23.25-4.05-1.54-.33-.71-2.1-.72-3.17,3.53-22.15,7.72-44.3,9.64-66.64l-.11,.12c7.14,1.57,14.01,4.43,21.06,6.46,.63,.14,1.66,.67,2.13,.02,2.3-19.99,3.22-40.13,4.45-60.22l-.14,.04c6.59,3.14,13.17,6.2M 9,19.76,9.43,.61,.23,1.5,.89,2.09,.33,1.33-16.42,.68-33.17,.6-49.7-.11-3.15,.69-2.68,3.01-1.35,3.75,2.28,7.48,4.59,11.22,6.88,2.14,1.31,4.28,2.61,6.46,3.88,.25,.14,.73,.02,1.24,.02-.16-15.42-1.62-30.78-2.21-46.18-.07-.59,.84-.51,1.16-.34,6.12,4.16,11.89,8.74,17.85,13.11,.78,.58,1.65,1.09,2.52,1.6,.09,.05,.57-.14,.6-.26,.11-5.56-.89-11.17-1.23-16.74-.77-7.83-1.66-15.66-2.41-23.5-.21-2.8,1.76-.73,2.85,.08,5.96,4.98,11.91,9.96,17.88,14.94,.78,.51,1.47,1.52,2.51,1.27-.45-7.57-1.94-15.21-2.77-22.8-.52-3.74-1.08-7.48-1.5M 7-11.23-.15-1.17-.14-2.35-.19-3.53,0-.06,.14-.15,.24-.19,.6-.27,1.34,.74,1.83,1.05,6.95,6.44,13.89,12.89,20.84,19.33,.55,.47,1.04,1.11,1.86,.91-.66-8.49-2.56-17.09-3.7-25.61-.46-2.88-.94-5.76-1.39-8.65-.03-.18,.12-.38,.18-.57,1.05,.15,1.67,.89,2.35,1.6,7.28,7.34,14.56,14.68,21.85,22.01,.84,.66,1.43,1.88,2.63,1.78-1.04-10.57-3.4-21.13-4.91-31.69h-.09Z"/><path class="cls-2" d="M1074.53,313.27c-19.6,1.34-38.67,3.19-58.19,5.13-.36,0-.76-.41-.6-.65,.55-.86,1.08-1.73,1.67-2.58,2.63-3.88,5.53-7.6,7.99-11.59,.2-1.25-3.05-.M 39-3.83-.44-6.36,.9-12.72,1.84-19.08,2.73-9.42,1.32-18.75,2.96-28.07,4.64-.53,.1-1.05,.12-1.53-.13,.04-.79,.66-1.39,1.15-2.02,2.81-3.67,5.64-7.34,8.45-11.01,.39-.72,2.66-2.67,.83-2.8-15.35,2.52-30.58,5.93-45.7,9.48-.51,.13-1.04,.24-1.53-.08,0-.81,.69-1.38,1.18-2,3.35-4.16,6.76-8.3,10.12-12.46,.3-.55,2.09-2.27,.94-2.37-13.6,2.96-27.04,6.58-40.41,10.19-.75,.1-3.98,1.42-3.69,.2,4.68-5.97,9.95-11.46,14.66-17.41-1.21-.59-2.55,.3-3.81,.47-8.43,2.24-16.74,4.75-25.06,7.25-4.16,1.25-8.31,2.5-12.48,3.73-.18,.05-.46-.09-.68-.M 18,.26-1.16,1.52-2.04,2.24-3.01,4.74-5.5,9.8-10.74,14.33-16.4,.26-1.06-3.22,.45-3.79,.5-10.01,3.18-20.07,6.25-29.93,9.71-1.6,.56-3.25,1.02-4.9,1.49-.17,.05-.46-.11-.66-.21,4.96-6.6,11.32-12.6,16.93-18.84,1.59-1.82,3.99-3.87-.38-2.46-10.63,3.37-21.3,6.68-31.73,10.46-2.35,.72-5.09,2.14-1.9-1.33,6.71-7.52,14.17-14.59,20.54-22.33-.56-.31-1.06-.21-1.57-.04-5.21,1.75-10.44,3.48-15.64,5.25-5.57,1.9-11.13,3.84-16.69,5.74-.36,.07-1.16,.29-1.36-.08,2.81-4.11,6.63-7.56,9.95-11.34,4.48-4.71,9.09-9.35,13.64-14.03,.65-.67,1.49-1M .25,1.72-2.15-1.52-.29-3.05,.68-4.53,1-8.2,2.73-16.4,5.47-24.6,8.2-1.23,.27-3.11,1.16-1.48-.88,7.95-9.16,16.4-17.91,24.69-26.79,.8-.86,1.55-1.75,2.31-2.63,.06-.07,.07-.27,.03-.29-.23-.08-.52-.22-.71-.16-8.56,2.56-17.15,5.06-25.64,7.85-.61,.2-1.3,.32-1.69,.81h.04c-.35-.49-.52-1-.07-1.5,3.09-3.38,6.13-6.8,9.31-10.12,7.35-7.68,14.77-15.31,22.16-22.96,.36-.49,1.27-.89,.83-1.58-.78-.27-2.18,.38-3.06,.49-7.15,1.86-14.29,3.73-21.44,5.6-1.24,.25-2.64,.94-3.84,.24l.06,.03c13.14-13.08,26.01-26.48,39.39-39.35,2.97-2.8-1.61-1.M 14-3.03-1.02-7.06,1.4-14.11,2.81-21.17,4.21-3.73,.63-1.9-.81-.31-2.5,15.15-15.12,30.65-29.78,46.31-44.44,.34-1.2-1.82-.52-2.49-.62-6.3,.49-12.58,1.12-18.88,1.68-4.14,.35-4.43,.14-1.26-2.82,5.72-5.44,11.43-10.89,17.18-16.32,12.01-11.35,24.3-22.51,36.7-33.59,.94-.82,1.79-1.82,3.18-1.8,7.95-.03,15.9,.02,23.86,.03,1.57,.19,2.03,.37,.55,1.79-19,16.29-38.19,32.32-56.18,49.56-.12,.12-.02,.4,.03,.6,.01,.06,.21,.11,.33,.12,6.68-.19,13.35-1.41,20.02-2.01,1.47-.17,2.93-.39,4.4-.52,.59-.05,1.4-.37,1.74,.3,.24,.46-.34,.77-.69,1M .08-15.87,13.72-31.07,27.96-46.21,42.4-2.78,2.74,4.16,.44,5.15,.42,7.2-1.36,14.41-2.72,21.62-4.07,2.1-.05-.68,1.87-1.17,2.44-12.68,11.35-24.88,23.19-37.04,35.06-.49,.48-1.15,.9-1.14,1.62,.67,.26,1.3,.08,1.95-.08,5.4-1.35,10.79-2.69,16.19-4.03,3.47-.86,6.95-1.72,10.42-2.57,.62-.14,1.29-.32,1.87,.03-10.89,11.54-23.73,21.86-34.68,33.57-.91,1.72,2.55,0,3.22-.02,10.01-2.62,20.03-6.22,30.05-8.32,.08,.16,.2,.41,.11,.51-.72,.78-1.47,1.54-2.24,2.29-9.15,9.06-18.63,17.81-27.6,27.04-.1,.12-.02,.35,.03,.52,.02,.05,.25,.11,.35,M .09,10.62-3.07,21.16-6.4,31.75-9.56,.98-.13,2.4-1.06,3.26-.42,0,.59-.93,1.1-1.28,1.59-7.58,7.57-15.16,15.14-22.73,22.71-.37,.53-2.02,1.89-.93,2.02,6.76-1.65,13.3-4.11,19.98-6.04,5.15-1.58,10.34-3.1,15.51-4.63,.34-.1,.77-.05,1.15-.01,.72,.16-.74,1.47-1.08,1.83-6.82,7.18-14.25,13.99-20.53,21.57,.67,.39,1.23,.21,1.9,0,3.51-1.1,7.03-2.17,10.52-3.31,7.73-2.52,15.58-4.79,23.46-6.99,.89-.25,1.75-.58,2.73-.4l.1,.08c-.37,1.67-2.16,2.67-3.19,4-5.05,5.7-10.94,10.85-15.51,16.88-.01,.03,.23,.2,.3,.18,1.02-.23,2.06-.45,3.06-.74,M 12.39-3.61,24.86-7.15,37.42-10.29,.63-.09,.95,.22,.55,.74-5.24,6.26-11.4,11.93-16.21,18.47-.02,.03,.2,.21,.28,.2,.64-.1,1.3-.2,1.92-.37,11.85-3.24,23.89-6.02,35.85-8.96,4.83-1.09,6.24-1.26,6.15-.93-.41,1.65-2.03,2.74-3.14,4.06-3.5,4.22-7.35,8.21-10.76,12.51-.81,1.45,1.45,.96,2.21,.75,14.16-3.16,28.37-6.08,42.66-8.7,.73-.07,1.59-.39,2.22,.13,.08,.05,.11,.23,.06,.3-.4,.56-.81,1.12-1.25,1.66-2.93,3.62-5.88,7.22-8.81,10.84-.77,1.19-2.2,2.17-2.27,3.61,10.78-1.17,21.58-3.68,32.44-5,6.23-.83,12.45-1.94,18.72-2.5,.38-.02,.M 79,.39,.62,.63-3.36,4.81-6.93,9.48-10.37,14.24-.29,.3-.52,.86-.09,1.13,2.94,.25,5.87-.42,8.79-.69,16.27-1.9,32.63-3.37,48.99-4.3l-.08-.12c-3.55,5.37-6.81,10.99-10.53,16.23l.1-.05Z"/><path class="cls-2" d="M1005,333.95c-7.9,1.23-15.88,2.1-23.78,3.26-8.96,1.36-17.93,2.67-26.81,4.34-1.02,.11-2.12,.52-3.11,.09-.11-.69,.39-1.22,.76-1.79,2.36-3.61,4.72-7.22,7.09-10.83,.31-.48,.65-.94,.48-1.51,.05-.04,.11-.08,.16-.12-.25-.02-.27,.03-.05,.17-.93-.37-1.86-.1-2.76,.07-2.49,.46-4.96,1-7.45,1.48-12.69,2.13-25.23,6.02-37.76,7.9M 6-.09-.17-.22-.4-.14-.53,.46-.78,.94-1.55,1.48-2.29,2.47-3.46,4.96-6.91,7.43-10.38,.27-.53,1.34-1.71,.35-1.89-1.94,.43-3.91,.82-5.82,1.33-7.16,1.88-14.33,3.76-21.46,5.72-5.49,1.45-10.82,3.36-16.34,4.68-.17,.02-.5-.2-.44-.39,3.16-5.42,7.67-10.04,10.84-15.45,.05-.17-.29-.43-.45-.4-.9,.23-1.79,.47-2.67,.72-12.18,3.47-24.04,7.6-36.01,11.49-.69,.25-1.54,.63-2.24,.38-.39-.19-.14-.56,.05-.82,3.88-5.44,8.1-10.65,12.04-16.05-1.02-.71-2.29,.23-3.38,.45-10.87,3.77-21.74,7.55-32.4,11.69-1.91,.56-4.98,2.24-2.4-1.14,4.24-5.5,8.5M 6-10.94,12.76-16.48,.18-.24,.14-.42-.13-.52-8.97,2.61-17.75,6.74-26.64,9.89-2.67,1.03-5.28,2.14-7.93,3.21-.52,.21-1.04,.12-1.49-.17l-.1,.08c4.81-6.28,9.19-12.84,14.29-19.01,.36-.45,.8-.87,.61-1.46l.22-.1-.13,.18c-2.56,.01-4.88,1.76-7.32,2.49-7.6,2.84-14.88,6.74-22.39,9.41-.09-.18-.27-.44-.18-.57,2.31-3.28,4.6-6.57,6.99-9.81,2.8-3.8,5.68-7.56,8.52-11.34,.27-.36,.45-.77,.65-1.16,.03-.07-.06-.2-.14-.26-.07-.06-.24-.12-.31-.1-.98,.35-1.97,.69-2.91,1.09-8.19,3.48-16.35,7.04-24.56,10.49-.35,.19-.85-.02-.73-.4,5.81-8.32,1M 2.34-16.14,18.45-24.25,1.59-2.23,.44-1.63-1.34-1.1-7.22,2.89-14.44,5.77-21.49,8.92-1.8,.67-6.28,3.37-3.18-.67,7.1-9.14,14.34-18.18,21.37-27.36,.06-.07,.06-.26,0-.28-1.08-.51-2.2,.48-3.26,.73-8.01,2.95-15.81,6.75-23.92,9.26l.07,.09c-.36-1.18,.84-1.92,1.41-2.83,7.48-9.53,15.02-19.03,23.02-28.29,.73-1.08,2.21-1.92,2.07-3.32,.22,.04,.47,.08,.41-.21-.27-.11-.38-.01-.33,.28-.69-.19-1.32,0-1.94,.21-5.76,2.05-11.55,4.06-17.28,6.2-6.89,2.49-7.87,2.72-7.72,2.29,9.18-12.92,20.39-24.68,30.78-36.89,1.77-1.97,3.61-3.75-.67-2.54-M 6,1.55-12.01,3.11-18.01,4.66-.76,.2-1.53,.43-2.33,.09l.11,.05c-.06-.59,.37-1.01,.75-1.45,12.31-14.91,25.71-28.93,38.29-43.62,.27-.38-.4-.53-.63-.52-7.62,1.35-15.22,2.76-22.83,4.14-.12,.02-.33-.02-.37-.08-.4-.52,.14-.94,.45-1.35,11.46-13.07,23.07-26,35.2-38.66,3.28-3.42,6.52-6.86,9.76-10.31,.33-.51,1.56-1.38,.69-1.83-7.88,.17-15.77,1.45-23.65,1.98-1.53-.36,.28-1.69,.71-2.29,17.14-19.2,35.38-37.84,53.65-56.27,.71-.74,1.53-1.15,2.72-1.15,7.54-.2,15.09-.14,22.64-.13,2.29,.24,3.97-.28,1.25,2.28-14.76,13.92-29.16,28.21-4M 3.53,42.5-3.55,3.52-6.95,7.14-10.41,10.72-.48,.62-1.54,1.35-.25,1.72,7.36-.41,14.72-1.37,22.07-1.99,3.09-.21,1.75,.84,.36,2.35-6.14,6.14-12.39,12.22-18.43,18.42-8.94,9.18-17.74,18.44-26.59,27.67-.36,.41-.92,.8-.57,1.37,7.42-.52,15.01-2.51,22.45-3.65,.51-.09,1.02-.18,1.49,.1,.01,.72-.63,1.16-1.11,1.66-4.7,4.86-9.44,9.69-14.09,14.57-8.66,8.93-16.9,18.18-25.39,27.17,.1,.03,.19,.06,.27,.08l-.29-.13c1.85,.87,3.87-.52,5.73-.84,6.72-1.89,13.45-3.78,20.18-5.66,.5-.07,1.99-.6,1.99,.15-10.35,11.92-21.63,23.27-31.74,35.38-.45M ,.52-1.08,.98-1.09,1.68,0,.07,.18,.22,.24,.21,8.82-2.32,17.37-5.76,26.16-8.31,.52-.17,1-.29,1.62,.07-8.66,10.16-17.76,19.96-26.28,30.16-.53,.62-.94,1.29-1.4,1.95-.04,.17,.32,.39,.47,.35,8.21-2.56,16.19-5.82,24.31-8.65,1.3-.32,2.81-1.43,4.11-.62l.09-.09c-3.59,3.53-6.7,7.5-9.97,11.3-4.41,5.26-8.79,10.54-13.18,15.82-.18,.31-.69,.81-.35,1.11,.08,.07,.25,.15,.33,.13,.99-.32,2-.62,2.96-1,7.84-3.07,15.64-6.2,23.62-9.02,2.6-.93,2.23-.19,.81,1.58-6.11,7.3-12.26,14.59-18.1,22.1-.3,.38-.44,.77-.15,1.19-.19-.16-.28-.15-.29,.03M l.23-.11c9.71-3.14,19.11-7.48,28.9-10.71,.98-.35,1.98-.67,2.98-.96,.17-.05,.46,.12,.66,.22,.05,.03,.02,.23-.05,.3-.75,.89-1.51,1.78-2.28,2.66-5,5.74-10.01,11.48-15.01,17.23-.54,.62-1.04,1.25-1.51,1.91-.09,.13,.06,.38,.15,.56,.45,.16,1.01-.19,1.47-.3,7.09-2.61,14.2-5.19,21.28-7.83,4.64-1.73,9.33-3.34,14.11-4.81,.19-.06,.48,.09,.71,.18,.04,.01,.01,.2-.04,.29-3.6,4.73-7.85,9-11.64,13.58-1.68,1.95-3.27,3.95-4.89,5.93-.31,1.45,3.28-.48,3.98-.54,7.42-2.56,14.82-5.14,22.25-7.67,4.09-1.39,8.22-2.69,12.34-4.01,.2-.06,.56-.0M 4,.7,.07,.14,.11,.19,.42,.09,.56-.46,.65-.98,1.29-1.49,1.92-3.62,4.41-7.25,8.82-10.87,13.23-.59,.72-1.18,1.44-1.71,2.19-.09,.12,.05,.37,.14,.54,12.47-3.2,25.02-7.91,37.64-11.35,1.24-.21,2.55-1.11,3.78-.64-3.51,5.85-8.83,10.95-12.61,16.77,1.38,.49,2.58-.42,3.93-.64,12.97-3.58,25.93-7.21,39.12-10.27,.72-.17,1.23-.35,1.93,.13-3.44,4.77-7.12,9.37-10.65,14.07-.29,.47-1,1.33-.18,1.6,13.6-2.78,27.19-6.15,40.93-8.71,2.09-.19,4.65-1.41,6.65-.77,.08,.7-.44,1.21-.84,1.77-2.96,4.23-6.2,8.28-8.95,12.64-.06,.21,.27,.72,.59,.67,2M .64-.42,5.28-.84,7.92-1.27,14.51-2.38,29.05-4.83,43.67-6.4,.34,0,.72,.44,.57,.69-3.01,4.83-6.13,9.59-9.24,14.35l.1-.06Z"/><path class="cls-2" d="M475.58,1023.99s.02,.02,.02,.03c-.03,0-.06,.01-.09,.01,0,0,.01,0,.01-.01,.02,0,.03-.03,.05-.02h.01Z"/><polygon class="cls-2" points="708.53 1043.43 708.53 1043.42 708.54 1043.43 708.53 1043.43"/><path class="cls-2" d="M771.18,1312.07s.02-.03,.03-.05c.02,0,.05-.01,.07-.01l-.1,.06Z"/><path class="cls-2" d="M800.44,1026.36h-.12s0-.03,0-.04l.13,.04Z"/><path class="cls-2" d="M8M 21.24,1148.14c-6.13,1.7-11.93,4.93-17.95,7.18-.46,.19-1.01,.26-1.52,.36-.07,.02-.29-.15-.28-.21,6.48-14.47,14.61-28.31,20.22-43.11,0-.07-.18-.21-.24-.21-6.41,2.35-12.05,6.23-18.38,8.9-.51-1.32,.52-2.26,.96-3.43,5.2-11.44,11.4-22.94,15.25-34.62-1-.25-1.82,.68-2.68,1.04-4.24,2.48-8.46,4.97-12.71,7.44-.74,.43-1.4,.99-2.39,1.05-.36-.43-.11-.82,.06-1.23,2.66-6.21,5.32-12.42,7.97-18.63,1.65-3.87,3.27-7.75,4.91-11.63,.22-.51,.46-1.01,.12-1.53-.75-.03-1.24,.37-1.75,.71-4.87,3.27-9.79,6.46-14.82,9.47-.1,.06-.36,.1-.38,.07-.M 54-.54,.02-1.18,.22-1.76,3.72-8.87,7.57-17.69,10.51-26.77,.04-.43-.62-.35-.83-.27-5.22,3.34-10.02,7.26-15.25,10.58-.1,.06-.34,.11-.38,.07-.64-.48-.05-1.14,.12-1.72,2.91-7.05,5.25-14.24,7.9-21.36,.26-.7,.55-1.42,.4-2.17-1.28,.08-2.24,1.37-3.33,2.01-1.48,.73-13.45,10.89-13.36,8.82,2.22-6.21,4.73-12.35,6.61-18.63,.06-.66,1.52-3.48,.22-3.08-6.71,4.69-12.96,10.08-19.61,14.89-.49,.37-.98,.75-1.69,.82-.27-.41-.14-.81,0-1.22,1.38-4.05,2.77-8.1,4.13-12.16,.62-1.87,1.21-3.74,1.78-5.63-.04-.24-.41-.59-.73-.36-6.72,4.96-13.13,M 10.21-20.14,14.94-.49,.21-1.51,1.26-1.87,.44,.47-1.46,.9-2.93,1.47-4.36,1.44-3.59,2.4-7.29,3.54-10.94,.22-.54,.18-1.63-.64-1.42-6.6,4.55-12.95,9.43-19.47,14.11-.81,.44-1.64,1.4-2.58,1.41-.09-.03-.22-.16-.2-.22,.14-.74,.24-1.48,.47-2.2,1.16-3.76,2.36-7.52,3.54-11.28,.09-.45,.39-1.22,.05-1.54-.6-.07-1.19,.47-1.7,.74-2.33,1.62-4.61,3.31-6.99,4.89-4.9,3.18-9.75,6.52-14.78,9.53-2.07,.65,2.01-8.07,2.1-9.27,.99-3.86,2.58-6.52-2.47-2.92-6.93,4.5-13.77,9.13-21.05,13.08-.13,.08-.47-.03-.69-.11-.32-.26-.07-.87-.03-1.24,.92-3.M 14,1.86-6.28,2.76-9.43,.68-3.01-.86-1.62-2.49-.8-7.17,4.4-14.74,8.33-22.28,12.3-.55,.29-1.16,.52-1.76,.74-.28,.1-.56-.03-.56-.3,.52-3.42,1.92-6.7,2.77-10.07,.91-2.86-1.38-1.21-2.72-.6-9.32,4.53-18.88,9.68-28.88,12.77-.12-.18-.31-.4-.26-.57,.93-3.47,2.21-6.86,2.97-10.37,.05-.28-.46-.64-.76-.54-.87,.28-1.77,.52-2.59,.88-9.86,4.23-20.14,7.74-30.31,11.44-2.29,.52-4.75,2.6-3.01-1.89,.82-2.62,1.8-5.17,2.52-7.82,.11-.38-.53-.83-1.02-.69-13.05,4.02-26.08,8.16-39.43,11.42-.21-.24-.49-.41-.47-.57,.4-3.02,1.7-5.86,2.51-8.79,.M 25-.83,.8-2.07-.7-1.92-13.86,3.28-27.71,6.31-41.81,8.69-.88,.05-1.9,.44-2.6-.25,.81-2.94,1.81-5.84,2.68-8.76,.29-.91,.7-2.41-.84-2.25-16.91,2.8-34.02,4.02-51.02,5.94,.37,.34,.43,.75,.28,1.17-1.03,3.54-2.85,6.95-3.43,10.59,1.17,.52,2.4,.22,3.57,.12,15.37-1.22,30.61-3.45,45.86-5.66,.78-.14,2.33-.21,1.98,.8-1.08,3.34-2.36,6.62-3.54,9.93-.22,.62,.29,1.03,1.12,.9,7.87-1.35,15.75-2.82,23.53-4.53,7.01-1.47,13.92-3.48,20.99-4.61,.63,.15,.43,.94,.25,1.39-1.13,3.31-2.89,6.48-3.63,9.88,.25,.58,1.2,.4,1.72,.29,13.14-3.48,26.06M -7.42,39-11.44,.32-.08,.9,.27,.84,.5-.11,.42-.18,.85-.34,1.26-1.24,3.29-2.79,6.49-3.81,9.85-.02,.09,.41,.38,.52,.35,12.76-3.71,25.04-9.13,37.5-13.43,.45,.18,.25,.8,.2,1.16-1.1,2.88-2.25,5.75-3.35,8.63-.27,.71-.45,1.45-.61,2.18-.02,.08,.39,.32,.58,.31,9.24-3.2,18.28-7.34,27-11.53,1.62-.77,3.2-1.63,4.88-2.28,.18-.06,.47,.01,.68,.08,.42,.32-.07,1.12-.11,1.54-1.22,3.63-2.78,7.17-3.78,10.87-.03,.18,.35,.41,.52,.36,.94-.4,1.92-.76,2.81-1.23,7.63-4.04,15.4-7.9,22.8-12.22,.42-.24,.94-.39,1.42-.56,.08-.03,.25,.01,.32,.07,.1M ,.07,.2,.2,.18,.28-1.63,4.43-3.26,8.87-4.89,13.3h-.09c.15,.05,.3,.1,.45,.12h0c1.01,.23,1.88-.6,2.74-.99,6.54-3.56,12.81-7.41,18.94-11.4,1.14-.74,2.33-1.44,3.51-2.14,.08-.06,.31-.06,.38-.01,.67,.36,.32,1.13,.18,1.71-1.18,3.29-2.15,6.63-3.61,9.86-.32,1.23-1.74,2.8-.63,3.93,7.64-5.3,15.71-10.02,23.51-15.1,.29-.25,.68-.22,1.04-.19,.07,0,.17,.19,.15,.28-.11,.53-.2,1.07-.4,1.58-1.4,3.59-2.83,7.17-4.25,10.76-2.92,6.62-.86,4.16,3.32,1.63,5.19-3.6,10.34-7.23,15.51-10.85,.99-.56,2.07-1.73,3.21-1.78,.4,.58,.29,1.19,0,1.78-1.8M 3,4.95-3.58,9.92-5.76,14.79-.19,.67-.82,1.48-.61,2.14,.52,.51,1.25-.16,1.63-.43,6.6-4.59,13.19-9.2,19.79-13.79,.5-.22,1.94-1.55,2.09-.66-2.18,6.24-4.97,12.26-7.37,18.42-.33,.82-.63,1.64-.92,2.47-.02,.06,.12,.2,.23,.25,.72,.09,1.37-.64,1.98-.94,5.96-4.19,11.91-8.4,17.88-12.6,.79-.55,1.41-1.31,2.7-1.52-2.25,8.44-6.73,16.3-9.93,24.5,.09,.46,1.08,.04,1.32-.09,5.21-3.41,10.32-6.94,15.61-10.24,.16-.07,.86,.04,.78,.4-.19,.62-.36,1.26-.62,1.86-3.29,7.63-6.61,15.25-10.39,22.74-1.18,2.33-2,4.04,1.31,1.98,4.92-3,9.79-6.06,14.M 74-9.03,.08-.05,.33-.05,.38,0,.65,.47,.08,1.16-.11,1.74-4.42,9.7-8.77,19.45-13.65,28.99-.48,1.34-.01,1.34,1.12,.88,4.43-2.45,8.84-4.92,13.26-7.39,.99-.55,1.99-1.1,3.01-1.61,.13-.07,.46,.08,.67,.17,.08,.03,.14,.19,.11,.27-.23,.62-.44,1.24-.73,1.84-3,6.11-5.97,12.23-9.05,18.31-2.62,5.19-5.35,10.34-8.04,15.5-.13,.25-.07,.43,.25,.53,5.84-1.93,11.31-5.43,16.99-7.93,.56-.27,1.08-.59,1.79-.43,.23,.9-.31,1.61-.69,2.39-6.59,13.19-13.64,26.25-20.92,39.19,.87,.64,1.72,.06,2.59-.21,4.57-1.86,9.12-3.73,13.68-5.59,.96-.35,4.58-2M .26,4.2-.71-8.05,15.69-17.06,31-26.07,46.22-.22,.38-.31,.81-.42,1.23-.02,.05,.17,.21,.26,.21,.52-.03,1.07-.01,1.54-.16,6.41-1.96,12.74-4.14,19.18-5.98,.33-.02,.81,.25,.56,.63-9.79,18.12-20.66,35.59-31.66,53.04-.96,1.54-1.53,2.46,.98,1.9,6.91-1.41,13.74-3.2,20.7-4.33,.3-.04,.67,.46,.53,.73-12.37,21.4-26.33,42.02-39.73,62.82-.14,.25,.29,.66,.67,.64,1.07-.06,2.15-.08,3.22-.2,7.18-.81,14.34-1.63,21.51-2.45,13.33-21.72,26.41-43.53,38.56-65.72,.23-.53,.28-1.25-.57-1.2-7.15,1.52-14.29,3.08-21.46,4.54-.2,.04-.48-.12-.69-.2M 2,10.05-19.04,21.68-37.6,30.9-57.11-.96-.75-2.29,.16-3.37,.36-5.38,1.71-10.75,3.43-16.13,5.14-.59,.12-1.7,.68-1.98-.09,7.81-15.32,16.4-30.4,23.66-45.96,.43-.9,.85-1.82,1.26-2.73,.17-.39,.08-.88-.15-.89Zm-19.87-25.55c-.07,.02-.15,.02-.23,.01-.1-.31,.44-.27,.23-.01Z"/><path class="cls-2" d="M613.74,997.34c-.05,0-.1,0-.15-.01,.01-.03,.02-.05,.03-.08,0,0,.13,.09,.12,.09Z"/><path class="cls-2" d="M810.45,1039.03l-.05,.02,.03-.03s.01,.01,.02,.01Z"/><path class="cls-2" d="M822.93,1306.26s.02-.03,.03-.05c.02-.01,.04-.01,.0M 6-.01l-.09,.06Z"/><path class="cls-2" d="M785.88,1002.17c-2.96,2.37-5.76,4.94-8.83,7.17-.18,.11-.59,.18-.72,.09-.29-.27-.2-.86-.09-1.22,1.24-5.38,3.23-10.64,3.89-16.11-1.18-.05-2,1.23-2.94,1.82-4.23,3.48-8.42,6.98-12.66,10.45-1.79,1.29-3.53,3.28-5.76,3.9-.09-.04-.2-.19-.18-.26,1.15-4.96,2.85-9.85,3.63-14.87,0-.12-.28-.29-.46-.4-2.2,.81-3.92,2.96-5.93,4.27-4.36,3.36-8.73,6.72-13.12,10.07-.68,.52-1.43,.98-2.17,1.45-.08,.05-.32,.06-.38,.01-.15-.12-.37-.31-.34-.44,.96-4.35,1.94-8.69,2.89-13.03,.03-.14-.2-.33-.36-.45-1.M 18,.07-2.11,1.32-3.09,1.94-5.71,4.59-11.97,8.68-18.14,12.86-.52,.25-1.08,.88-1.7,.69-.1-.04-.25-.15-.24-.21,.16-1.06,.28-2.13,.53-3.18,.51-3.06,2.04-6.09,1.93-9.18-.82-.26-1.47,.36-2.04,.73-4.14,2.76-8.25,5.55-12.42,8.28-2.91,1.91-5.9,3.76-8.88,5.61-.29,.18-.72,.21-1.1,.29-.06,.01-.24-.1-.25-.15-.02-.43-.09-.86,.01-1.27,.66-3.29,1.87-6.51,2.16-9.85-.04-.23-.47-.62-.77-.48-.79,.41-1.59,.81-2.35,1.26-6.49,3.84-12.94,7.74-19.72,11.28-3.81,2.13-4.39,2.3-3.36-2.23,.39-2.13,1.07-4.22,1.24-6.38,.02-.31,0-.66-.43-.78-1.15-M .12-2.14,.85-3.16,1.25-8.35,4.36-16.95,8.57-25.82,12.03-.78,.28-1.53,0-1.35-.91,.69-2.95,1.51-5.9,2.12-8.87,.13-.93-.73-1.05-1.44-.74-4.11,1.62-8.2,3.27-12.29,4.91-6.86,2.77-13.93,5.15-20.93,7.66-.51,.17-1.4,.44-1.72-.1,.25-3.34,1.88-6.49,1.84-9.84-.38-.67-1.48-.17-2.08-.07-11.83,3.71-23.59,7.36-35.67,10.37-3.11,1.04-1.8-1.28-1.44-3.07,.47-2.12,.95-4.24,1.39-6.36,.18-.92-.3-1.28-1.28-1.03-13.8,3.45-27.84,6.12-41.9,8.41-.7,.2-1.71,.14-1.96-.6-.12-.53-.2-1.07-.31-1.6-.49-2.3-1.02-4.58-1.48-6.88,15.69,.49,31.1-1.32,45M .82-5.19,.41,1.48,.8,2.97,1.23,4.44,.12,.38,.77,.73,1.23,.64,13.34-2.71,26.06-7.53,39.06-10.97-.94,3.08-1.16,6.31-1.7,9.48-.04,.29,.15,.6,.23,.88,1.51,.09,2.64-.59,3.85-1.01,10.42-3.53,20.45-7.7,30.6-11.64,.31-.12,.84,.22,.8,.51-.3,3.11-.86,6.2-1.32,9.29-.05,.3,.44,.62,.78,.5,8.99-3.61,17.83-7.92,26.3-12.57,.73-.32,2.48-1.64,2.78-.24-.08,2.37-.53,4.71-.76,7.07-.02,.75-.47,1.88,.02,2.48,1.33,.16,2.35-.84,3.48-1.35,6.62-3.52,12.92-7.38,19.24-11.23,.98-.46,1.9-1.5,3.03-1.39,.19,.06,.41,.32,.39,.47-.46,3.21-1.02,6.4-1.M 41,9.61,.07,1.91,2.72-.41,3.47-.8,6.17-4.16,12.5-8.17,18.46-12.53,.61-.32,1.29-1.02,2.01-.89,.39,.22,.21,.81,.23,1.17-.5,3.31-1.31,6.58-1.43,9.92,.5,1.13,1.71-.19,2.39-.53,4.67-3.24,9.28-6.55,13.59-10.11,1.77-1.47,3.6-2.9,5.43-4.34,.16-.12,.51-.19,.73-.14,.56,.19,.46,.92,.38,1.39-.52,2.76-.56,5.57-1.3,8.32-.15,1.12-.75,2.5,.25,3.39-.04-.02-.09-.04-.12-.05l.04,.13c6.3-5.67,13.25-10.7,19.78-16.14,.39-.31,.78-.56,1.51-.35-.39,4.05-1.47,8.06-2.1,12.09-.09,.52-.03,1.06-.01,1.59,0,.06,.17,.12,.27,.15,.12,.03,.32,.07,.38,M .02,.69-.51,1.4-1.01,2.03-1.56,4.08-3.57,8.14-7.15,12.21-10.73,.92,3.69,1.96,7.37,3.11,11.02-.02,.14-.04,.27-.06,.41,.07,.01,.14,.02,.21,.04,1.35,4.21,2.82,8.42,4.52,12.51Z"/><path class="cls-2" d="M822.48,1053.62c-8.45,6.01-6.6,4.39-3.84-3.68,1.26,1.24,2.54,2.47,3.84,3.68Z"/><path class="cls-2" d="M833.75,999.26c-.2,1.2-.41,2.41-.67,3.61-.57-.85-1.13-1.7-1.66-2.56,.51-.29,1.94-1.98,2.33-1.05Z"/><path class="cls-2" d="M842.68,1014.97c-.01,.06-.01,.11-.03,.17-.14-.16-.28-.31-.42-.47,.21,0,.45,.04,.45,.3Z"/><path claM ss="cls-2" d="M842.75,1180.57c-.36,.81-.71,1.62-1,2.45-.04,.15,.22,.72,.63,.58,5.93-1.66,11.73-3.79,17.61-5.62,2.12-.58,3.57-1.44,2.27,1.6-8.54,19.9-17.55,39.51-27.03,59.01,.58,.4,1.1,.4,1.63,.28,3.25-.71,6.49-1.42,9.73-2.14,3.24-.72,6.48-1.45,9.72-2.16,.63-.14,1.31-.25,1.94,.36-10.76,24.15-22.83,47.87-35.29,71.28-7.59,.74-15.15,1.67-22.73,2.52-1.89-.04-3.23,.67-1.79-1.94,12.17-21.37,24.11-42.88,35.06-64.88,.26-.65,1.22-1.36,.35-2.02-.65-.48-1.52,.04-2.27,.21-6.37,1.35-12.7,2.86-19.09,4.14-.59,.15-1.46-.02-1.1-.79,M 4.67-9.17,9.61-18.24,14.22-27.42,5.08-10.31,10.52-20.47,14.85-31.03-.4-.64-1.49-.14-2.08-.03-5.37,1.73-10.72,3.48-16.09,5.21-1.74,.41-4.13,1.73-2.48-1.28,8.15-16.29,15.99-32.58,22.92-49.3,.06-.14-.13-.37-.26-.54-.04-.05-.27-.06-.37-.02-5.67,2.16-11.19,4.71-16.8,7.02-1.05,.39-3,1.41-2.14-.66,6.52-14.21,13.03-28.42,18.5-43.01,.02-.19-.08-.47-.24-.55-.18-.08-.54-.03-.75,.07-5.82,2.82-11.37,6.2-17.29,8.78-.42-.51-.27-.92-.1-1.33,1.67-3.87,3.38-7.72,5-11.59,3.41-8.17,6.69-16.36,9.63-24.64,.08-.44,.52-1.22,.16-1.54-1.01-M .27-1.79,.71-2.64,1.09-4.18,2.54-8.36,5.08-12.54,7.62-.63,.31-1.27,.95-2.01,.6-.09-.02-.17-.19-.14-.28,.3-.93,.6-1.87,.95-2.79,2.38-6.2,4.8-12.39,7.14-18.59,3.54,2.98,7.2,5.82,10.98,8.53-.1,.66-.8,1.38-.18,1.95,.61,0,1.2-.58,1.78-.82,3.36,2.37,6.81,4.62,10.33,6.76-2.55,7.4-5.29,14.77-8.09,22.12-.14,.71-.99,1.85-.18,2.33,.07,.05,.28,.04,.39,0,5.15-2.5,10.13-5.31,15.22-7.92,.66-.28,1.82-1.19,2.19-.2-.43,1.46-.85,2.93-1.39,4.37-5,13.75-10.65,27.33-15.84,40.98,.5,.74,1.7-.13,2.37-.28,5.65-2.19,11.04-5.15,16.8-6.95,.42,M .37,.32,.8,.17,1.21-6.26,16.64-13.29,32.96-20.63,49.26Z"/><path class="cls-2" d="M378.87,529.22c.56-.16,1.04-.01,1.51,.21,4.55,1.9,8.89,4.8,13.7,5.88,.39-.7,.2-1.34,.08-1.97-.92-4.78-1.9-9.56-2.78-14.35-1.1-7.44-2.95-14.9-3.32-22.39,.02-.11,.43-.3,.59-.26,4.19,1.34,8.14,3.32,12.24,4.9,.71,.17,1.84,.99,2.41,.26-.03-4.81-1.07-9.64-1.45-14.45-.95-8.89-1.83-17.8-2.27-26.73-.02-.42,.12-.84,.23-1.25,.01-.06,.25-.14,.35-.11,5.13,1.3,9.86,4.34,15.18,4.98l-.09-.08c.77,8.78,.97,17.64,1.92,26.42,.46,4.72,.97,9.43,1.48,14.15,.M 1,.96,.11,1.94,.66,2.84l.16-.13c-3.92,.15-7.86-2.3-11.67-3.25-.99-.34-1.97-.69-2.96-1.03-.29-.1-.84,.24-.83,.5,.75,8.47,2.28,16.88,3.78,25.28,.75,3.71,1.33,7.45,1.96,11.18,.24,1.53-.35,1.87-1.77,1.33-2.92-1.09-5.83-2.2-8.75-3.31-.92-.15-3.78-2.06-4.15-.87,.86,7.18,3.12,14.17,4.61,21.26,.95,4.64,2.68,9.19,3.27,13.87-1,.17-1.67-.22-2.36-.5-3.35-1.37-6.68-2.78-10.02-4.17-.96-.29-1.91-1.06-2.93-.7,0,0,.15-.17,.15-.17-.31,.91,0,1.8,.26,2.68,2.75,10.09,6.04,20.06,9,30.12-.46,.62-1.51,.05-2.09-.14-4.35-1.93-8.67-3.92-13.0M 1-5.86-.17-.07-.48,.05-.7,.13-.1,.03-.2,.19-.18,.27,.21,.84,.41,1.69,.67,2.52,2.66,8.34,5.76,16.58,8.79,24.83,2.12,4.92,.69,3.72-2.98,2.03-3.78-1.87-7.54-3.75-11.32-5.62-.53-.16-1.21-.68-1.76-.44-.09,.07-.2,.19-.18,.27,.29,.94,.56,1.88,.92,2.8,3.22,8.1,6.46,16.19,9.68,24.28,1.22,3.02,.17,2.37-2.08,1.36-3.82-2.02-7.63-4.04-11.42-6.09-3.74-2.02-4.3-2.25-4.35-1.89-.19,1.33,.67,2.46,1.16,3.67,2.84,7.07,6.06,14.03,9.39,20.96,.14,.29,.32,.59,.08,.9-.34,.42-1-.02-1.39-.1-6.1-3.07-12.42-5.87-18.09-9.65-.01,.25-.07,.28-.18,M .09l.28-.03c-1.16,1.03,.25,2.48,.6,3.62,2.8,5.71,5.62,11.42,8.44,17.12,2.05,3.75-.24,2.24-2.42,1.11-5.53-2.88-10.9-5.96-16.2-9.1-.54-.19-2.75-1.83-2.89-.91,2.58,6.49,6.28,12.57,9.26,18.9,.4,.79,.72,1.61,1.06,2.42,.03,.08-.07,.2-.15,.28-.06,.06-.22,.13-.27,.11-.81-.38-1.64-.73-2.41-1.16-7.55-4.02-14.6-9.16-21.99-13.05-.68,.56,.06,1.38,.26,2.03,2.91,5.79,5.84,11.58,8.76,17.37,.3,.6,.59,1.2,.87,1.81,.03,.07-.05,.23-.11,.25-1.13,.3-2.05-.81-3.02-1.25-8.28-5.11-16.33-10.55-24.41-15.94-.31-.23-.99-.69-1.28-.18,.1,.52,.15M ,1.06,.38,1.54,2.92,6.15,5.92,12.27,9.05,18.32,.2,.4,.41,.8-.03,1.3-11.14-6.7-21.54-14.54-32.13-22.04-1.57-.39-.35,1.42-.12,2.13,2.74,6.19,5.75,12.27,8.33,18.52,.05,.39-.6,.37-.79,.3-4.74-3.1-9.22-6.63-13.8-9.95-7.18-5.37-14.43-10.69-21.36-16.27-.69-.45-1.31-1.27-2.22-1.13-.06,0-.18,.2-.15,.28,.28,.83,.55,1.66,.89,2.48,2.19,5.32,4.4,10.63,6.59,15.94,.16,.75,1.07,1.71,.4,2.35-9.6-6.29-18.46-14.22-27.44-21.37-5.13-4.27-10.21-8.59-15.31-12.89-.37-.31-.72-.66-1.3-.7-.08,0-.26,.08-.26,.13,1.62,6.52,4.39,12.84,6.41,19.29M ,.06,.47,.57,1.14,.25,1.55-.22,.04-.55,.11-.67,.02-.9-.65-1.79-1.31-2.63-2-9.96-8.19-19.65-16.58-29.14-25.11-6-5.39-11.91-10.85-17.87-16.27-.42-.39-.78-.88-1.72-.76,.93,6.06,2.89,12,3.68,18.07-.75,.11-1.14-.16-1.5-.49-13.66-12.25-27.17-24.79-40.26-37.53-5.81-5.66-11.51-11.39-17.25-17.11-.7-.61-1.19-.54-1.27,.2,.64,5.79,1.38,11.58,2.07,17.36,.04,.31-.04,.64-.1,.95-.07,.15-.5,.24-.64,.15-17.87-16.53-34.81-34.26-51.59-51.8-5.37-5.66-10.64-11.39-16.01-17.06-.95-1-1.39-2.02-1.38-3.27,.04-6.14,0-12.28,0-18.42,.27-1.41,1.M 56-.24,2.01,.4,18.57,20.64,37,41.16,56.55,60.99,2.49,2.54,4.99,5.08,7.52,7.6,.2,.2,.67,.22,1.08,.35-.08-6.31-1.34-12.47-1.83-18.75,0-.14,.29-.3,.48-.41,16.11,15.82,31.85,32.87,48.62,48.61,2.58,2.49,5.24,4.92,7.86,7.38,1.32,.93,.95-1.3,.75-1.97-1.3-6.26-3.66-12.72-4.3-18.93,.71-.05,1.3,.74,1.84,1.11,4.15,3.97,8.25,7.96,12.41,11.92,10.83,10.32,22,20.39,33.32,30.36,.55,.42,1.07,1.07,1.86,.94-1.35-6.29-4.03-12.73-5.87-19.06-.26-.82-.66-1.66-.17-2.52l-.06,.1c.73,.1,1.11,.57,1.56,.96,12.63,11.29,25.31,22.36,38.6,33.06,.6M 1,.47,1.25,1.3,2.18,1.18,.32-.68-.17-1.27-.39-1.86-1.19-3.2-2.47-6.37-3.68-9.56-1.17-3.09-2.29-6.19-3.41-9.29-.07-.18,.06-.41,.1-.62,.93,.02,1.54,.54,2.18,1.13,2.81,2.32,5.61,4.65,8.45,6.95,8.55,6.62,16.69,14.05,25.84,19.92,.37-.45,.17-.84,0-1.24-2.15-4.99-4.3-9.97-6.41-14.96-.73-1.73-1.35-3.49-1.98-5.24-.04-.12,.19-.33,.34-.47,9.91,6.89,19.42,14.94,29.66,21.81,.49,.32,1.29,1.18,1.94,.69-1.67-5.12-4.42-9.89-6.48-14.87-.95-2.12-1.83-4.27-2.71-6.41-.07-.17,.12-.4,.18-.6,.52,.05,.96,.23,1.36,.56,6.99,4.9,13.96,9.81,20M .96,14.7,1.68,1.04,3.36,2.75,5.36,3.13,.08-.07,.18-.21,.15-.28-.32-.82-.63-1.64-1-2.44-2.72-5.96-5.46-11.92-8.18-17.89-.19-.65-.91-1.47-.29-2.05,7.41,4.18,14.64,9.52,22.02,14.04,.61,.32,1.24,.97,1.99,.64,.33-.33-.2-1.09-.31-1.51-3.11-7.22-6.75-14.25-9.45-21.63,0-.2,.5-.61,.78-.41,6.41,4.4,12.81,8.6,19.7,12.36,1.94,.97,1.7,.06,1.08-1.47-3.21-7.76-6.43-15.52-9.64-23.29-.2-.81-1.11-1.99-.69-2.75,.35-.21,.75-.03,1.04,.15,5.84,3.86,11.85,7.46,17.8,11.16,.33,.15,1.15,.55,1.35,.17-.02-.31-.03-.62-.14-.91-1.51-3.91-3.07-7.M 8-4.56-11.71-2-5.25-3.95-10.51-5.91-15.77-.08-.45-.49-1.22-.13-1.55,.21-.08,.53-.19,.67-.12,5.08,2.79,10,5.85,15.04,8.72,.75,.32,1.6,.97,2.43,.94,.43-.39-.12-1.33-.2-1.84-3.42-9.83-7.38-19.55-9.94-29.57,.11-.87,1.5,.12,1.95,.23,4.83,2.55,9.47,5.43,14.48,7.62,.27,.12,.61-.06,.59-.29-2.72-10.97-6.71-21.67-9.38-32.67-.07-1.64,2.6,.29,3.26,.55,3.66,1.81,7.33,3.62,11.01,5.41,.52,.07,1.85,1.04,2.02,.2-1.21-6.98-3.5-13.92-5.02-20.89-.98-4.01-1.86-8.04-2.71-12.07-.2-.93-.57-1.9-.07-2.86l-.08,.08Z"/><path class="cls-2" d="MM 187.62,673.04c-.45,.45-.59,.97-.47,1.51,.42,1.91,.85,3.81,1.3,5.72,.84,3.6,1.69,7.19,2.52,10.79,.02,.09-.08,.27-.15,.28-1,.25-1.74-.81-2.51-1.28-13.39-10.92-26.78-21.85-39.64-33.18-6.43-5.66-12.82-11.35-19.23-17.03-.86-.56-1.54-1.82-2.67-1.64-.07,0-.18,.16-.18,.24,.14,5.82,1.35,11.57,2.03,17.35,.1,.77-.07,1.17-.45,1.06-26.11-21.17-50.35-45.1-74.35-68.36-.31-6.61-.11-13.18-.2-19.78,0-.41,.17-.83,.3-1.23,.02-.05,.29-.12,.37-.08,22.96,22.16,44.92,45.4,68.86,66.73,3.38,3.31,2.75,.61,2.5-2.27-.66-4.81-1.37-9.61-1.61-14.M 46-.02-.27,.18-.41,.51-.39,13.53,11.45,26,24.58,39.68,36.08,6.54,5.73,13.15,11.41,19.73,17.1,.7,.46,1.82,1.83,2.18,.65-1.12-4.98-2.27-9.95-3.39-14.93-.17-.73-.23-1.48-.32-2.23-.01-.09,.1-.28,.15-.28,1.36,.06,2.2,1.48,3.27,2.19,8.9,7.8,17.91,15.52,27.14,23.06,7.06,5.77,14.27,11.44,21.42,17.14,.49,.29,1.04,.84,1.64,.76,.1-.05,.23-.19,.21-.26-.83-2.71-1.66-5.43-2.51-8.14-.82-2.61-1.66-5.22-2.45-7.83-.08-.25,.1-.55,.16-.83,.35,.14,.78,.22,1.04,.43,4.69,3.71,9.35,7.45,14.05,11.16,10.11,7.65,20.03,15.99,30.84,22.75,.35-.M 4,.22-.79,.04-1.2-2.18-4.98-4.35-9.96-6.51-14.94-.57-1.32-1.09-2.66-1.59-4-.04-.11,.18-.32,.33-.44,.05-.04,.28,0,.37,.06,12.51,8.98,24.98,18.22,38.03,26.57,.25,.16,.66,.49,.93,.17,.18-.2,.1-.63-.03-.9-2.65-5.41-5.33-10.82-8-16.22-.44-1.1-1.42-2.11-1.12-3.34,1.08,.15,1.68,.76,2.38,1.25,10.3,6.92,20.66,14.09,31.56,20.15,.09-.31,.26-.54,.19-.7-.54-1.1-1.12-2.19-1.69-3.28-2.7-5.16-5.41-10.32-8.11-15.49-.21-.39-.36-.8,.1-1.18,8.58,4.84,16.69,10.55,25.53,15.25,.99,.56,2.01,1.07,3.03,1.59,.29,.15,.53,.07,.65-.16,.05-.09,.M 13-.21,.09-.28-.34-.7-.67-1.4-1.05-2.09-2.91-5.33-5.83-10.65-8.75-15.97-1.93-3.34,.65-1.69,2.3-.7,6.67,4.02,13.71,7.62,20.65,11.34,.55,.3,1.96,1.01,2.09,.54,.32-.75-.54-1.4-.78-2.07-2.88-5.1-5.77-10.2-8.64-15.3-.28-.72-2.53-3.86-.5-3.18,6.57,3.39,13.15,6.74,19.74,10.1,.65,.22,1.42,.81,2.11,.66,.09-.06,.22-.2,.19-.26-.27-.6-.55-1.21-.87-1.8-2.83-5.12-5.67-10.23-8.5-15.36-.47-1.38-2.47-3.15-1.15-4.49l-.12-.05c5.79,3.78,12.55,6.23,18.9,9.22,1.62,.27,.51-1.42,.15-2.12-2.96-5.66-5.93-11.31-8.87-16.98-1.31-2.84-2.13-3.88M ,1.53-2.23,4.89,2.03,9.67,4.31,14.63,6.18,2.11,.43-.1-2.48-.34-3.3-3.14-6.18-6.16-12.4-8.92-18.69-1.12-2.99,.71-1.62,2.37-1.03,3.81,1.59,7.5,3.46,11.38,4.89,.82,.25,1.69,1.01,2.52,.35,.64-.51-.11-1.2-.35-1.78-3.43-8.72-7.41-17.27-10.56-26.08,.05-.35,.38-.62,.8-.44,4.77,1.7,9.33,3.93,14.17,5.45,.45,.13,.98-.22,.82-.71-1.63-4.44-3.32-8.86-4.94-13.3-1.75-5.4-4.26-10.63-5.4-16.17-.03-.24,.28-.4,.57-.33,3.87,1.14,7.59,2.73,11.41,4.04,.76,.1,2.35,1.11,2.72,.05-2.62-9.68-6.11-19.17-8.57-28.87-.23-.84-.36-1.69-.52-2.54-.05M -.24,.59-.57,.9-.47,4.21,1.44,8.46,2.78,12.69,4.15,.32,.1,.89-.22,.85-.47-2.04-8.66-4.24-17.3-6.14-26-.53-2.33-1.05-4.66-1.55-6.99-.11-.51-.21-1.04,.24-1.5,4.03,.86,7.78,2.38,11.77,3.41,.68,.2,2.18,.43,2.21-.57-1.4-8.86-2.95-17.7-4.34-26.56-.47-2.99-.76-6-1.11-9-.1-.86-.2-1.72,.13-2.56l-.16,.13c.53,0,1.07,.05,1.58-.03,4.41-.7,8.8-1.46,13.08-2.57l-.14-.08c1.22,3.8,1.11,7.86,1.69,11.78,1.07,8.84,2.15,17.74,4.04,26.45l.07-.08c-4.44,1.22-8.83,2.56-13.4,3.45-.69,.13-1.05,.64-.92,1.24,2.27,11.22,4.63,22.48,7.76,33.53l.14M -.13c-1.07,.32-2.14,.17-3.17-.09-2.95-.74-5.89-1.52-8.84-2.26-.61-.09-1.78-.42-2.11,.26,2.18,10.41,5.97,20.48,8.95,30.71-.41,.47-.9,.54-1.45,.4-3.32-.88-6.63-1.76-9.95-2.65-.74-.1-2.48-1.05-2.72,0,2.94,9.2,6.66,18.14,9.91,27.24,.28,.79,.85,2.13-.64,1.91-3.69-.98-7.31-2.16-10.96-3.26-.71-.21-2.55-.99-2.52,.23,3.09,8.27,6.55,16.37,10.28,24.44,.36,.78,1.31,2.37-.31,2.19-4.23-.96-8.28-2.54-12.44-3.76-2.8-.87-2.05,.29-1.21,2.18,3.12,6.69,7.18,13.3,9.83,20.04-.81,.5-1.77-.07-2.59-.25-4.56-1.55-9.12-3.13-13.67-4.7-.18,.26M -.44,.47-.39,.61,.25,.72,.52,1.44,.9,2.12,3.33,6.23,7.07,12.27,10.18,18.6-.29,.78-1.4,.17-1.97,.04-4.86-1.84-9.72-3.69-14.56-5.56-.74-.29-1.45-.57-2.28-.33,.02,0,.33-.04,.33-.04h-.3c3.42,5.86,6.85,11.71,10.27,17.56,2.32,3.62,2.06,3.95-1.92,2.26-5.11-2.18-10.21-4.37-15.32-6.55-1.33-.42-2.29-.92-1.4,1,1.95,3.31,3.91,6.62,5.9,9.91,1.64,2.71,3.33,5.41,4.97,8.12,.22,.49-.38,.81-.81,.65-7.65-2.82-14.61-6.95-22.03-10.07-.58,.81,.33,1.62,.63,2.39,2.91,5.09,5.98,10.12,9.19,15.1,.43,.66,.78,1.36,1.11,2.06,.05,.12-.2,.32-.37,M .58-7.5-3.3-14.77-7.1-21.93-10.92-1.36-.61-2.57-1.72-4.12-1.81-.24-.02-.28,.5-.05,.89,3.49,5.83,7,11.64,10.49,17.47,.23,.41,.73,1.21-.03,1.28-10.42-4.42-19.87-10.93-29.84-15.88-.62,.78,.51,1.87,.8,2.67,2.74,4.8,5.5,9.59,8.25,14.39,.3,.81,1.49,1.84,.92,2.64-.02,.03-.25,.04-.33,0-10.02-5.26-19.69-11.33-29.27-17.23-1.58-1-3.18-1.99-4.79-2.96-.15-.09-.57-.08-.66,0-.14,.14-.19,.42-.12,.59,.36,.81,.76,1.61,1.18,2.4,2.66,5.06,5.32,10.12,7.99,15.18,.26,.5,.6,.97,.18,1.55-14.24-7.67-27.14-17.67-40.79-26.34,0-.03,.03-.06,.04M -.1-.47,.62-.24,1.25,.02,1.86,1.76,4.76,4.42,9.6,5.74,14.33-.23,.06-.57,.16-.69,.08-1.89-1.21-3.77-2.42-5.62-3.67-13.05-8.82-25.67-18.03-38.05-27.45-1.1-.7-4.44-3.88-3.27-.43,1.37,4.16,2.78,8.3,4.14,12.46,.27,.82,.39,1.67,.57,2.51-.01,.2-.45,.32-.61,.23-18.72-13.63-36.95-27.69-54.36-42.71,.06,.25,0,.29-.16,.11l.29-.05Z"/><path class="cls-2" d="M924.94,209.92c-.66-.26-1.33-.14-1.96,.01-2.05,.51-4.11,1.04-6.14,1.6-9.42,2.42-18.74,5.64-28.21,7.65-.51-.12,.43-1.1,.61-1.31,8.89-8.54,17.9-16.98,26.9-25.41,.4-.54,1.58-1.0M 8,1.1-1.81-.55-.27-1.33,.14-1.92,.21-8.96,2.34-17.91,4.69-26.87,7.03-1.66,.43-3.33,.86-5.01,1.26-.18,.04-.44-.11-.64-.21,9.93-10.37,21.57-19.8,32.08-29.83,.71-.65,1.37-1.32,2.04-1.99,.28-.36-.36-.54-.6-.56-9.99,2.04-19.98,4.44-29.85,6.9-.64,.07-1.76,.46-2.3,.1,11.4-11.84,24.9-22.62,37.33-33.86,1.02-1.07,2.6-1.8,3.05-3.24-9.74,1.06-19.46,3.63-29.18,5.24-.59,.09-1.27,.34-1.75-.15-.07-.05-.06-.24,0-.31,15.26-14.51,32.61-27.58,47.65-42.05-.05-.13-.39-.29-.58-.27-3.87,.43-7.73,.88-11.6,1.33-5.33,.48-10.64,1.57-15.99,1.5M 8-.02-.24-.15-.52-.03-.64,.75-.76,1.52-1.51,2.34-2.22,17.08-14.73,34.38-29.2,51.75-43.62,3.35-2.79,2.47-2.38,6.96-2.4,6.6-.04,13.21-.07,19.81-.09,.95,.13,2.26-.32,2.91,.52,.05,.07,0,.23-.07,.3-.61,.57-1.22,1.14-1.87,1.68-16.54,13.57-33.11,27.11-49.47,40.88-.67,.61-1.63,1.09-1.6,2.09,7.88-.2,15.99-1.69,23.93-2.33,1.54-.03,3.25-.58,4.72-.28,.06,.08,.08,.25,.01,.31-.57,.59-1.11,1.2-1.75,1.74-8.44,7.12-16.91,14.2-25.32,21.33-5.73,4.86-11.4,9.77-17.09,14.66-.45,.48-1.26,.84-1.06,1.58,.52,.26,1.35,.07,1.95,.02,9.2-1.62,1M 8.4-3.25,27.6-4.88,.51-.09,1.03-.17,1.52,.1-.03,.73-.75,1.12-1.28,1.58-5.21,4.51-10.47,8.99-15.65,13.52-6.82,5.96-13.59,11.96-20.38,17.95-.35,.44-1.38,1.02-1.24,1.57,.05,.08,.2,.18,.29,.17,1.05-.15,2.11-.28,3.13-.5,7.93-1.71,15.85-3.45,23.77-5.16,1.69-.36,3.4-.65,5.11-.94,.2-.03,.59,.08,.65,.2,.08,.16-.02,.44-.17,.59-.86,.83-1.76,1.63-2.66,2.43-8.44,7.55-16.89,15.1-25.32,22.65-1.52,1.36-2.98,2.78-4.45,4.18-.29,1.16,2.69-.04,3.3-.08,10.2-2.41,20.4-4.82,30.6-7.23,.41-.16,1.67-.11,1.38,.5-8.15,7.95-16.76,15.45-25.07,2M 3.24-.84,.9-2.61,1.9-2.66,3.07,11.2-1.79,22.39-5.46,33.58-7.9,1.23-.14,2.59-.99,3.78-.49,.05,.02,.03,.23-.04,.3-.63,.69-1.25,1.39-1.94,2.05-6.47,6.21-12.95,12.41-19.42,18.61-.91,.96-2.05,1.66-2.51,2.94,1.41,.24,2.63-.29,3.96-.61,10.98-2.95,22.15-5.39,33.25-8.02,.84-.11,1.84-.58,2.62-.07,.07,.04,.07,.23,0,.3-.39,.44-.79,.87-1.21,1.29-5.92,5.87-11.84,11.74-17.75,17.62-3.15,3.09-1.31,2.42,1.7,1.76,12.9-2.97,25.87-6.17,38.95-8.36,.22-.02,.48,.26,.37,.46-5.3,5.88-10.93,11.47-16.35,17.23-.49,.51-.91,1.06-1.34,1.6-.06,.08M -.06,.27,0,.31,.19,.11,.46,.26,.64,.23,3.14-.6,6.27-1.24,9.41-1.84,7.85-1.52,15.7-3.05,23.56-4.52,3.8-.71,7.64-1.3,11.46-1.93,.24-.04,.63,0,.74,.12,.25,.28,.07,.59-.17,.86-4.97,5.64-10.15,11.11-14.99,16.85-.22,.31,.36,.62,.55,.63,11.79-1.64,23.47-3.88,35.31-5.34,4.52-.54,8.99-1.51,13.53-1.78,.12,0,.34,.04,.36,.1,.07,.19,.17,.43,.07,.58-4.07,5.5-8.77,10.54-12.8,16.07-.11,1.21,2.21,.48,2.97,.56,17.07-2.01,34.17-3.83,51.32-5.02,.34-.03,.7,.42,.56,.68-.16,.3-.29,.61-.48,.89-3.7,5.25-7.36,10.52-11.04,15.78l-.04,.03c-18.M 78,1-37.44,3.36-56.14,5.23-.35,.02-.79-.44-.64-.67,.45-.66,.87-1.33,1.36-1.97,2.97-3.85,5.96-7.68,8.94-11.53,.34-.67,2.33-2.38,.92-2.65-11.3,1.15-22.55,3-33.76,4.83-5.4,.88-10.81,1.77-16.22,2.64-.18,.03-.44-.14-.63-.26-.07-.04-.06-.23,0-.31,.47-.65,.92-1.31,1.44-1.93,4.02-5.04,8.95-9.74,12.49-15-.19-.11-.45-.26-.64-.23-2.11,.35-4.21,.7-6.3,1.1-7.85,1.5-15.71,2.98-23.54,4.55-4.7,.94-9.35,2.02-14.02,3.03-.77,.17-1.55,.4-2.35,.05-.08-.72,.54-1.19,1.01-1.7,4.28-4.7,8.57-9.39,12.86-14.09,.7-.97,2.14-1.69,1.94-3.02,0,.01M ,.02,.25,.02,.25l-.02-.18c-13.95,2.71-27.73,6.19-41.51,9.52-.59,.07-1.37,.37-1.92,.09-.06-.07-.07-.22-.01-.29,.49-.63,.94-1.29,1.5-1.88,5.52-5.97,11.56-11.53,16.8-17.74,.06-.78-1.53-.16-1.98-.15-9.43,2.2-18.74,4.7-28.07,7.16-3.44,.91-6.9,1.79-10.35,2.67-1.24-.02,.9-1.81,1.16-2.23,5.82-5.79,11.65-11.57,17.48-17.36,.84-.84,1.66-1.69,2.47-2.55,.06-.07,.05-.27-.01-.3-.19-.11-.45-.26-.63-.23-1.56,.34-3.11,.69-4.64,1.1-7.53,2.01-15.06,4.02-22.58,6.06-3.06,.83-6.08,1.74-9.12,2.61-.5,.14-1.02,.2-1.5-.16,.41-1.04,1.41-1.8,2M .25-2.62,5.36-5.26,10.76-10.49,16.16-15.73,1.89-1.83,3.81-3.63,5.72-5.44,.35-.33,.68-.67,.61-1.14,.16-.05,.38-.07,.25-.27-.26,0-.31,.12-.16,.32Z"/><path class="cls-2" d="M1007.3,858.26c4.1,1.05,8.2,2.1,12.31,3.13,.5,.12,1.5,.22,1.72-.32-2.14-10.42-5.98-20.5-8.95-30.74,.44-.47,.94-.53,1.49-.39,3.96,1.04,7.9,2.15,11.86,3.15,.38,.09,.88-.24,.79-.52-.32-1.04-.61-2.09-.99-3.12-2.98-8.05-5.98-16.09-8.96-24.14-.19-.6-.73-1.91,.36-1.87,4.54,.86,8.77,2.88,13.3,3.7,.16,.01,.51-.26,.5-.4-2.75-8.23-6.51-16.18-10.02-24.19-1.59-M 3.17-1.07-3.04,2.06-2.23,4.04,1.14,7.95,2.79,12.06,3.64,.16,.02,.54-.26,.52-.34-1.99-5.3-5-10.21-7.41-15.34-.95-2.31-2.76-4.42-3.21-6.86,0-.23,.79-.26,1.51-.04,4.89,1.47,9.59,3.47,14.48,4.91,.33,.09,.63-.39,.59-.62-2.92-6.3-6.7-12.21-9.96-18.35-.23-.72-1.76-2.2-.9-2.6,1.05-.1,2.01,.37,2.97,.71,4,1.54,8,3.09,12,4.63,1.19,.39,2.47,1.3,3.72,.67-.12,.06-.23,.11-.33,.16l.33-.13c-4.09-6.01-7.45-12.52-11.26-18.72-.34-.57-.83-1.11-.59-1.8l-.09,.06c.53-.2,1.05-.12,1.54,.09,3.71,1.53,7.43,3.04,11.12,4.6,2.26,.96,4.47,2,6.71,M 2.99,.77,.41,1.67,0,1-.86-3.71-6.22-7.43-12.43-11.15-18.64-.14-.24-.03-.43,.29-.52,6.31,1.95,12.32,5.34,18.25,8.17,2.2,.97,6.68,4.13,3.58-.76-3.29-5.43-6.57-10.86-9.9-16.26-.26-.43-.23-.86,.05-.86,1.2-.06,2.15,.68,3.2,1.12,7.9,3.41,15.19,8,22.89,11.47,.67-.66-.36-1.62-.63-2.32-3.24-5.78-7.21-11.23-10.03-17.2,.29-.38,1.06,.03,1.41,.14,2.51,1.26,5.03,2.51,7.49,3.83,6.83,3.66,13.55,7.41,20.15,11.36,3.04,1.6,.56-1.97,.04-2.95-2.69-4.7-5.39-9.4-8.07-14.1-2.46-3.92,1.37-1.38,3.03-.46,10.09,5.94,20.24,11.82,29.98,18.13,.5M 1,.33,1.03,.75,1.69,.52,.07-.01,.16-.19,.12-.25-.57-1.21-1.13-2.42-1.75-3.61-2.68-5.17-5.37-10.34-8.05-15.51-.04-.07,0-.25,.06-.27,.22-.07,.54-.19,.69-.12,12.77,7.52,25.08,15.93,37.23,24.34,1.01,.69,1.87,1.56,3.22,1.88,.37-.41,.21-.8,.04-1.21-1.83-4.39-3.65-8.78-5.47-13.18-.18-.59-.74-1.23-.14-1.74,15.24,9.27,29.59,20.45,43.8,31.03,1.07,.82,2.2,1.58,3.32,2.35,.09,.06,.34,.1,.38,.06,.14-.13,.34-.33,.3-.46-5.63-19.72-10.68-21.18,8.32-7.06,13.1,9.94,25.91,20.11,38.42,30.53,.62,.36,3.56,3.37,3.7,1.83-1.08-5.65-2.52-11.M 23-3.79-16.83-.04-.16,.11-.48,.25-.51,14.37,10.18,27.8,22.63,41.28,33.99,6.96,6.15,13.89,12.33,20.84,18.49,.45,.4,.95,.76,1.45,1.11,.13,.06,.58-.08,.62-.26-.11-6.09-1.53-12.18-1.86-18.3,.34-.67,1.16,.02,1.53,.31,25.1,21.79,49.42,44.45,73.02,67.82,.19,6.6,.03,13.16,.07,19.76,0,.4-.17,.81-.3,1.2-.26,.32-.78-.04-1-.22-21.88-22.52-44.47-44.62-67.63-65.99-1.38-1.07-3.28-3.54-2.99-.11,.7,5.57,1.46,11.13,1.88,16.72,.03,.43-.68,.35-.87,.27-17.28-16.47-35.08-32.57-53.18-48.24-2.36-2.07-4.79-4.08-7.21-6.11-.16-.13-.48-.15-.7M 3-.19-.46-.1-.41,.67-.31,1.07,1.18,5.08,2.37,10.16,3.54,15.24,.06,.47,.25,1.18-.04,1.55-.26-.02-.6,0-.75-.13-17.34-14.51-34.19-30.2-52.66-43.21-.17,.12-.42,.31-.39,.43,.34,1.26,.7,2.52,1.1,3.77,1.13,3.55,2.29,7.09,3.4,10.64,.19,.61,.21,1.26,.29,1.9,0,.21-.45,.32-.6,.25-14.29-11.39-28.67-22.79-43.78-33.53-.48-.35-.87-.84-1.62-.87-.1,0-.3,.11-.29,.15,2.14,6.78,5.75,13.14,8.14,19.87,.06,.41-.56,.37-.8,.33-12.76-8.91-25.25-18.97-38.74-26.8-.3,.07-.43,.24-.33,.46,.42,.91,.83,1.82,1.27,2.72,2.47,5.01,4.95,10.01,7.41,15.0M 2,.3,.6,.55,1.21,.82,1.82,.11,.23,.03,.41-.27,.5-.12,.04-.31,.05-.39,0-1.97-1.3-3.94-2.61-5.89-3.93-9.05-5.87-17.94-12.38-27.57-17.39-.65-.41-.32,.42,.07-.09-.56,1.09,.41,2.02,.82,3,2.83,5.89,6.58,11.47,8.88,17.56-.32,.35-.97-.13-1.32-.27-4.99-3.1-9.92-6.26-14.96-9.32-3.75-2.28-7.61-4.43-11.43-6.63-.52-.3-1-.71-1.75-.63-.58,.69,.18,1.2,.4,1.76,.24,.61,.66,1.18,.98,1.77,2.7,4.92,5.4,9.84,8.09,14.76,.36,.87,1.23,1.69,.56,2.45-7.78-4.45-15.59-8.81-23.61-12.97-.57-.17-1.58-1.1-2.05-.48,2.26,5.51,6.91,12.31,9.8,17.94,.3M ,.82,1.35,1.86,.8,2.68-.81,0-1.63-.7-2.4-.99-6.64-3.21-13.01-7.05-19.81-9.89-1.02,.1,.09,1.35,.25,1.88,2.88,5.21,5.77,10.41,8.65,15.63,.5,1.42,2.36,3.06,1.16,4.51v-.03c-5.7-3.83-12.48-6.22-18.79-9.23-.2-.09-.48-.05-.73-.06-.23,0-.32,.54-.14,.89,2.4,4.55,4.84,9.08,7.2,13.64,1.23,2.38,2.35,4.79,3.5,7.19,.08,.35-.57,.47-.77,.45-5.33-2.23-10.54-4.76-15.96-6.82-.61-.25-1.27-.33-1.88,0,.22,.02,.37,.04,.46-.18l-.37,.18c3.57,7.3,7.29,14.54,10.54,21.99,.18,.4,.24,.83,.32,1.26,.02,.08-.09,.23-.18,.27-.98,.41-1.89-.5-2.81-.78M -4.26-1.86-8.43-3.92-12.87-5.36-.4-.12-1.04,.2-.91,.68,3.51,9.24,8.05,18.22,11.04,27.61-.16,.88-2.16-.37-2.75-.45-3.74-1.48-7.46-2.99-11.2-4.45-.46-.18-1.03-.2-1.55-.26-.07,0-.25,.16-.24,.23,3.42,10.36,7.5,20.6,10.92,30.99l.08-.12c-4.44-1.82-8.96-3.44-13.51-5.01-.58-.15-1.8-.58-1.98,.25,2.68,9.84,6.22,19.56,8.77,29.44,.2,.71,.54,1.45,.09,2.19-1.16,.48-1.97-.31-2.93-.54-.77-.18-1.47-.53-2.21-.77-2.61-.85-5.23-1.69-7.84-2.54-.71-.23-1.41-.02-1.24,.69,2.91,10.81,5.29,21.71,7.7,32.6,.12,.52,.22,1.06-.16,1.56-.7,.14-1.2M 9-.15-1.88-.35-4.03-1.5-8.32-2.38-12.39-3.82-2.52-11.71-5.06-23.4-8-35.01l-.1,.1Z"/><path class="cls-2" d="M870.71,600.19c-.53,4.07-1.15,8.16-1.85,12.27-.06,.1-.08,.22-.06,.33-.73,4.28-1.54,8.58-2.43,12.89-4.15-1.97-8.07-4.5-12.14-6.68-1.21-1.01,1.04-1.52,1.72-1.9,2.89-1.15,5.8-2.27,8.71-3.4,.82-.48,2.13-.47,2.39-1.51-3.65-2.48-7.82-4.46-11.85-6.87,5.1-2.54,10.14-3.51,15.51-5.13Z"/><path class="cls-2" d="M871.97,589.33c-.32,3.29-.7,6.59-1.13,9.91-3.23-2.2-6.75-4.07-10.07-6.13-.23-.15-.2-.55-.31-.9,3.82-1.09,7.67-2.M 01,11.51-2.88Z"/><path class="cls-2" d="M872.79,578.89c-.09,1.52-.2,3.05-.32,4.59-4.84-3.22-6.85-3.38,.32-4.59Z"/><path class="cls-2" d="M915.35,574.42c-.29,.02-.58,.04-.87,.05,.03-.46,.05-.92,.06-1.38,.52,.34,.71,.65,.81,1.33Z"/><path class="cls-2" d="M1117.4,514.89c.02,.06,.04,.11,.06,.17-.05-.01-.11-.03-.16-.04l.1-.13Z"/><path class="cls-2" d="M1190.2,521.41v.1c-.05-.02-.09-.03-.14-.05l.14-.05Z"/><path class="cls-2" d="M1387.31,603.78c0,1.07-.03,2.15-.05,3.29-1.29,.43-2.17-.36-3.25-.87-26.06-13.81-52.7-26.87-79.M 85-39.26-6.67-3.04-13.39-6-20.09-9-.69-.3-1.37-.67-2.22-.5-.39,.89-.1,1.75,.02,2.59,.65,4.71,1.32,9.42,1.97,14.13,.14,.9,.31,2.57-1.14,2.06-13.21-5.81-26.24-11.91-39.64-17.46-15.01-6.33-30.28-12.24-45.64-18-.72-.21-2.02-.95-2.37-.02,.78,4.93,2.52,9.68,3.68,14.54,.1,.71,.54,1.55-.11,2.1-24.4-8.84-48.61-18.33-73.71-25.47-1.83,.04-.07,2.33,.11,3.25,1.36,3.49,2.73,6.98,4.08,10.48,.18,.55,.59,1.52-.28,1.62-20.47-6.06-40.69-12.72-61.64-17.36-2.03-.1-.06,2.18,.22,3.07,1.73,3.39,3.48,6.77,5.2,10.17,.19,.48-.43,.81-.85,.72-M 16.56-4.29-33.28-8.09-50.14-11.27-.76-.15-1.57-.34-2.35,.03-.16,.58,.21,1.03,.51,1.5,2.23,3.44,4.46,6.88,6.66,10.34,.09,.13-.06,.37-.15,.55-.04,.07-.22,.12-.35,.14-1.32-.11-2.64-.46-3.93-.69-10.55-2.27-21.3-3.74-32-5.42-1.25,0-9.19-1.71-9.1-.31,2.13,3.68,5.42,6.61,7.7,10.2,.16,.29-.41,.65-.59,.66-3.32-.4-6.64-.85-9.97-1.25-8.79-1.16-17.62-1.93-26.49-2.41-.52-.03-1.53-.04-1.51,.63,2.32,3.09,5.31,5.69,7.86,8.59,.18,.26,.59,.89,.25,1.13-10.56-.11-21.2-1.52-31.83-1.25-2.37,.05-.09,1.65,.6,2.43,2.36,2.21,4.76,4.39,7.12,M 6.61,.11,.11,.02,.38-.03,.57-1.29,.55-2.93,.09-4.33,.19-5-.07-9.99-.06-14.99,.08,.03-3.27-.01-6.54-.13-9.8,2.75-.17,5.5,.04,8.24-.21,1.08-.44-.25-1.34-.66-1.79-2.58-2.34-5.24-4.6-7.72-7.04-.21-.2,.12-.7,.47-.72,3.49-.25,6.98-.42,10.49-.34,6.87,.17,13.74,.31,20.61,.47,.55-.06,1.51,.21,1.76-.39-.09-1.12-1.58-2.02-2.24-2.94-1.95-2.19-4.26-4.13-6.01-6.47-.1-.5,.58-.72,1.02-.66,12.79,.06,25.49,1.7,38.22,2.45,.12-.01,.36-.37,.3-.48-2.14-3.42-5.05-6.35-7.49-9.56-.3-.38-.51-.75-.23-1.2,15.34,.63,30.61,3.48,45.83,5.51,1.54-M .14-.99-2.69-1.36-3.57-1.67-2.58-3.34-5.16-4.99-7.75-.28-.41-.51-1.19,.1-1.36,18.12,2.04,35.97,6.88,53.74,9.87,.52-.53-.15-1.23-.35-1.76-1.66-3.3-3.33-6.59-4.99-9.88-.33-.8-1.5-2.31,.24-2.23,21.25,4.27,42.23,9.94,62.99,15.97,.53-.44,.52-.86,.36-1.28-1.84-4.88-3.68-9.78-5.43-14.69,26.05,6.72,51.09,15.76,76.46,24.08,.47-.63,.26-1.27,.09-1.89-1.17-5.25-3.17-10.41-3.81-15.74,30.4,10.41,60.22,21.97,89.71,34.57,.77,.3,1.54,.1,1.37-.87-.59-4.6-1.21-9.2-1.82-13.81-.18-1.37-.52-2.75-.16-4.15,35.66,13.34,70.11,30.06,104.3,46M .66,4.32,2.16,3.66,1.4,3.69,5.33,.05,4.85,.02,9.69,.02,14.54Z"/><path class="cls-2" d="M907.7,654.84c-.22,.55-.64,.78-1.14,.95-1.7,.57-3.39,1.14-5.07,1.72,.55-2.15,1.1-4.29,1.62-6.44,1.51,1.23,3.2,2.44,4.59,3.77Z"/><path class="cls-2" d="M906.79,639.41c-.35,.11-.69,.22-1.04,.33,.11-.5,.22-1,.33-1.5,.42,.27,.65,.69,.71,1.17Z"/><path class="cls-2" d="M909.36,671.73c-3.22,1.4-6.41,2.79-9.6,4.17-1.18,.59-2.16-.53-3.03-1.19,1.12-3.83,2.21-7.67,3.25-11.53,2.97,2.49,5.93,4.96,8.9,7.45,.38,.32,.62,.68,.48,1.1Z"/><path clasM s="cls-2" d="M909.86,626.13c-.31,.33-.96,.54-1.46,.59,.13-.66,.26-1.33,.37-2,.37,.37,1.47,.8,1.09,1.41Z"/><path class="cls-2" d="M916.06,614.42c-1.83,.42-3.74,.54-5.64,.7,.26-1.68,.52-3.36,.76-5.04,1.4,1.06,2.81,2.11,4.22,3.17,.39,.3,.78,.6,.66,1.17Z"/><path class="cls-2" d="M1387.33,649.99c.01,2.54-1.05,1.63-2.75,.74-30.9-18.54-62.65-35.92-94.92-52.14-.66-.2-1.79-1.08-2.35-.36-.3,1.29,.04,2.57,.22,3.85,.64,4.39,1.29,8.77,1.92,13.16,.08,.57,.17,1.57-.63,1.53-26.85-13.65-54.07-27.43-82.07-39.4-.54-.17-1.66-.74-2.01-M .04,.77,4.83,2.54,9.47,3.69,14.21,.89,3.27-.17,2.61-2.58,1.58-22.19-10.11-44.86-19.89-68.18-28.08-.12-.04-.54,.26-.52,.35,.23,.84,.49,1.68,.81,2.49,1.6,4.11,3.5,8.13,4.89,12.31,.02,.34-.62,.47-.84,.41-18.75-7.22-37.51-14.13-56.91-20.04-.88-.27-1.77-.5-2.68-.7-.1-.02-.47,.29-.44,.42,1.49,3.82,3.87,7.32,5.69,11.01,1.45,2.61,1.58,3.22-1.46,2.22-9.07-3.03-18.24-5.87-27.51-8.48-7.01-1.79-14-4.12-21.11-5.42-.18,.02-.48,.29-.45,.4,1.94,4.27,5.3,7.9,7.44,12.08-.57,.4-1.07,.37-1.6,.23-4.22-1.1-8.45-2.19-12.67-3.3-8.83-2.33-M 17.84-4.16-26.83-6-.94-.06-2.17-.62-2.97,.03,1.67,3.05,5.34,6.78,7.51,9.88,.32,.42,1.01,.91,.46,1.39-.47,.42-1.28,.15-1.93,.02-1.3-.25-2.6-.55-3.9-.82-10.37-1.94-21-4.35-31.51-5.2-.19,.71,.28,1.21,.77,1.67,2.16,2.34,4.33,4.67,6.49,7.02,.41,.65,1.68,1.32,1.25,2.17-5.7-.3-11.67-1.6-17.46-2.16-4.73-.45-9.64-1.49-14.32-1.1-.04,.2-.12,.46-.01,.6,2.7,2.85,5.64,5.5,8.42,8.26,.34,.34,.64,.69,.35,1.22-8.82-.53-17.65-1.48-26.52-1.69-.21-.01-.53,.11-.64,.25-.1,.15-.11,.44,.01,.58,2.25,2.34,4.9,4.29,7.31,6.47,.72,.63,1.41,1.3,M 2.06,1.98,.12,.12,0,.39-.04,.58-7.49,.49-15.32-.66-22.89,.03-.28,.02-.52,.64-.31,.81,13.99,11.58,12.69,8.21-3.66,9.42,.87-6.71,1.55-13.42,2.01-20.13,4.26-.15,8.52-.09,12.79-.19,.44,.03,.61-.41,.39-.71-2.66-2.49-5.64-4.63-8.42-6.97-.97-.89-2.18-1.96,.25-1.92,6.07,.05,12.13-.08,18.18,.42,2.54,.21,5.11,.19,7.66,.26,.48,.05,.59-.39,.48-.7-2.81-2.91-5.79-5.69-8.71-8.49-.3-1.08,1.43-.65,2.07-.76,9.95,.28,19.84,1.48,29.73,2.49,.53,.03,.87-.43,.53-.85-2.53-2.81-5.1-5.58-7.75-8.28-1.66-1.35-.4-1.94,1.23-1.59,12,1.19,23.92,2M .96,35.8,4.98,2.47,.18-7.61-9.83-7.74-11.33-.05-.12,.3-.47,.4-.46,3.96,.61,7.93,1.21,11.88,1.9,9.73,1.72,19.35,3.77,28.92,6.01,1.25,.14,2.63,.94,3.83,.39-1.69-3.8-4.66-7.28-6.8-10.94-.24-.51-.94-1.36-.09-1.61,11.51,1.97,22.82,5.11,34.04,8.06,5.35,1.48,10.66,3.02,15.99,4.53,2.08,.57,2.42,.27,1.17-1.97-1.88-3.8-4.26-7.41-5.83-11.34,.27-.75,1.44-.24,2.01-.16,20.28,5.26,39.98,12.36,59.77,18.82,.56-1.36-.62-2.67-.97-3.99-1.33-3.71-3.25-7.3-4.27-11.09,.3-.85,1.76-.07,2.38,.02,9.38,3.27,18.76,6.54,28.04,10,13.8,5.14,27.36M ,10.66,40.83,16.33,.46,.19,.98,.32,1.48,.45,.32,.08,.56-.05,.54-.33-.64-4.93-2.54-9.67-3.66-14.52-.2-.72-.53-1.46-.01-2.19,25.83,9.55,51.26,21.49,76.06,33.36,3.11,1.51,6.25,2.97,9.39,4.44,.26,.13,.9-.17,.93-.39-.05-5.68-1.42-11.36-2.03-17.02-.08-.72-.13-1.56,.95-1.31,34.6,16.21,68.75,33.49,101.77,52.6,.37,6.56,.05,13.16,.16,19.74Z"/><path class="cls-2" d="M236.98,168.26c.96-.1,1.86,.03,2.74,.37,3.64,1.38,7.29,2.75,10.95,4.1,3.63,1.16,7.03,2.97,10.81,3.57,1.72-10.71,1.56-21.72,2.69-32.54,.72-8.14,1.57-16.28,2.28-24.M 43,.05-.53,.11-1.07-.37-1.53l-.05,.02c.89-.36,1.8-.32,2.74-.14,7.88,1.32,15.65,3.34,23.59,4.2l-.09-.08c-2.76,20.32-4.83,40.72-6.47,61.16-.11,2.65-1.77,1.48-3.49,1.05-4.68-1.65-9.35-3.33-14.03-4.98-2.13-.58-4.15-1.81-6.39-1.74-1.48,17.84-1.41,35.8-2.17,53.68-.9,1.26-6.12-2.42-7.55-2.88-4.19-2.16-8.37-4.33-12.56-6.49-.99-.39-1.86-1.17-2.99-.76-.16,14.83,.1,29.71,.65,44.54,.02,1.22,.42,3.95-1.73,2.47-6.88-4.49-13.66-9.13-20.58-13.57-.44-.37-.97,.03-1.11,.45,.18,13.76,1.73,27.52,2.44,41.27-1.1,.48-1.82-.56-2.68-1.08-6.M 27-4.89-12.53-9.79-18.8-14.68-4.06-3.61-2.66,.59-2.64,3.36,.74,7.84,1.49,15.68,2.26,23.52,.27,2.9,.73,5.78,.78,8.69-.44,1.25-2.27-.94-2.87-1.3-6.58-5.85-13.15-11.7-19.73-17.55-.72-.64-1.48-1.24-2.27-1.82-.12-.09-.47,.03-.78,.06,.34,8.68,1.89,17.38,2.78,26.04,.28,2.36,.57,4.72,.82,7.08-.06,.19-.53,.58-.82,.36-.65-.54-1.32-1.07-1.9-1.65-7.21-7.11-14.4-14.24-21.62-21.35-.84-.83-1.77-1.6-2.68-2.39-.06-.05-.25-.02-.38,0-.11,.02-.29,.08-.3,.12-.03,.43-.08,.86-.03,1.28,.76,6.43,1.52,12.87,2.3,19.3,.34,2.79,.73,5.57,1.1,8.M 35,.11,.82,.02,1.09-.36,1.08-.63-.02-.92-.39-1.23-.72-8.69-9.2-17.38-18.4-26.07-27.59-.56-.59-1.22-1.13-1.86-1.68-.12-.07-.59,.04-.63,.19,.08,5.59,1.09,11.16,1.56,16.74,.33,3,.69,6.01,1.04,9.01,.14,1.11-1.01,.85-1.36,.29-4.3-4.83-8.6-9.65-12.89-14.48-5.46-6.15-10.9-12.31-16.36-18.45-.94-.88-2.98-3.72-2.81-.62,.39,5.16,.82,10.32,1.21,15.48-.09,1.17,1.08,7.69-.76,6.2-11.76-13.33-23.09-27.05-34.67-40.53-1.25-1.21-.94-2.82-1.05-4.35-.02-5.39-.03-10.77-.04-16.16,.04-.64-.08-1.41,.62-1.75,.05-.04,.29,.03,.36,.1,11.51,12.M 07,21.88,25.22,33.44,37.23,.12,.08,.57-.03,.61-.2,.01-4.2-.42-8.39-.68-12.58-.2-3.44-.64-6.88-.63-10.33,.18-.6,.73-.85,1.35-.21,10.02,10.51,19.59,21.45,29.79,31.79,.55,.21,.8-.25,.76-.76-.47-5.05-.96-10.09-1.43-15.14-.29-3.11-.57-6.23-.84-9.35-.04-.43-.08-.86-.04-1.29,.07-.42,.7-.87,1.07-.43,8.37,8.12,16.5,16.49,24.79,24.7,1.06,.82,1.8,2.34,3.26,2.32-.76-10.3-2.17-20.6-2.96-30.88,1.15-.37,1.79,.65,2.61,1.24,3.89,3.58,7.76,7.17,11.64,10.75,3.62,3.34,7.23,6.68,10.86,10.01,.39,.26,1.1,1.07,1.57,.76,.15-.16,.34-.35,.32M -.53-.12-1.72-.27-3.44-.44-5.16-.85-9.56-2.1-19.1-2.38-28.68,.17-.92,1.36-.17,1.78,.19,7.59,5.94,14.82,12.31,22.54,18.08,1.01,.21,.87-.69,.89-1.39-.33-6.89-.99-13.76-1.44-20.65-.31-5.27-.6-10.54-.9-15.82-.02-.43,0-.86,.11-1.28,.24-.3,1.04-.25,1.37,.04,6.82,4.55,13.54,9.22,20.33,13.81,1.72,1.14,2.79,1.9,2.63-.93-.42-13.89-1.16-27.78-1.14-41.68,0-.3,0-.71,.49-.76,.36-.04,.81,.02,1.11,.18,3.39,1.76,6.75,3.56,10.12,5.34,3.6,1.9,7.19,3.8,10.79,5.7,.5,.26,.98,.27,1.54-.08,.25-15.69,.18-31.42,.94-47.11-.05-1.27,.36-2.67-.M 37-3.79h0Z"/><path class="cls-2" d="M1148.11,1317.93c.52-.78,.61-1.64,.71-2.5,.76-6.65,1.58-13.29,2.29-19.95,1.29-12.66,2.62-25.32,3.6-38.01,.2-.88,.04-2.44,1.36-2.31,5.52,1.61,10.85,3.8,16.29,5.65,1.48,.52,2.97,1.02,4.46,1.51,1.61,.52,1.97,.36,2.05-.89,.34-5.06,.63-10.11,.75-15.18,.6-11.19,.77-22.39,1-33.59,.03-1.18,.13-2.36,.2-3.54,.28-.8,1.44-.39,2-.15,6.17,3.06,12.24,6.28,18.36,9.42,.75,.24,2.15,1.41,2.7,.46,.42-13.11,0-26.28-.43-39.4-.11-2.37-.15-4.74-.19-7.11,0-.18,.17-.37,.27-.56,.11-.2,.71-.16,1.11,.08,6.64M ,4.18,13.08,8.66,19.63,12.97,.68,.28,1.59,1.36,2.3,.7,.4-6.31-.61-12.69-.77-19.02-.34-7.53-1.1-15.05-1.41-22.57,.91-.31,1.59,.5,2.29,.95,7.08,5.44,14.01,11.09,21.17,16.42,.19,.08,.91,.15,.92-.26-.23-3.11-.42-6.23-.71-9.34-.84-8.91-1.81-17.82-2.7-26.73,.01-.38-.14-.96,.26-1.15,.12-.04,.32-.08,.39-.03,.61,.42,1.24,.81,1.78,1.29,7.42,6.54,14.72,13.2,22.21,19.67,1.5,.86,.97-1.93,.94-2.7-.33-3.22-.68-6.44-1.04-9.66-.71-6.33-1.48-12.65-2.23-18.98,0-.71-.42-1.66,.42-2.04,.05-.04,.26,0,.32,.06,8.16,7.68,15.95,15.74,23.98,2M 3.56,.82,.62,1.42,1.89,2.57,1.79,.06,0,.18-.15,.18-.23-.05-1.07-.06-2.15-.18-3.21-.79-7.08-1.74-14.15-2.62-21.22,.05-2.09-1.68-7.79,1.79-3.9,9.11,9.46,17.86,19.27,27.18,28.52,.11,.07,.59-.08,.61-.25-.05-1.5-.04-3.01-.19-4.5-.7-7.08-1.54-14.16-2.24-21.24,0-.24,.43-.68,.71-.57,10.15,10.59,19.51,21.96,29.39,32.83,.7,.79,1.46,1.54,2.23,2.28,.1,.1,.46,.05,.7,.02,.07,0,.17-.16,.18-.25,.01-6.56-.89-13.11-1.23-19.67,.04-.95-.33-2.37,0-3.17,.25,0,.62-.04,.74,.07,11.57,13.02,22.62,26.52,34.02,39.7,.69,.81,1.37,1.6,1.37,2.63-M .03,6.57-.06,13.14-.09,19.7-.16,2.41-7.18-6.95-7.99-7.51-7.77-8.8-15.54-17.6-23.32-26.39-.7-.79-1.47-1.54-2.22-2.29-.12-.07-.59,.06-.64,.19-.12,6.86,.78,13.76,1.02,20.63,.28,4.19-.83,2.61-2.9,.5-8.6-9.25-17.19-18.5-25.79-27.75-.64-.69-1.33-1.35-1.99-2.03-.2-.21-.45-.3-.7-.12-.55,.44-.29,1.21-.29,1.82,.77,8.37,1.55,16.74,2.28,25.11-1,.34-1.53-.51-2.19-1.06-8.72-8.62-17.23-17.45-26.05-25.96-.39-.26-1.02-.13-1.03,.41,.89,9.77,2,19.53,2.79,29.31,0,.3-.25,1.04-.68,.96-1.31-.63-2.26-1.85-3.37-2.75-6.35-5.86-12.69-11.74-1M 9.04-17.6-.88-.81-1.84-1.57-2.77-2.34-.24-.23-.82,.15-.86,.31,.21,7.11,1.12,14.18,1.72,21.26,.33,3.98,.71,7.95,.92,11.93,0,2.45-2.15,.15-2.95-.45-6.14-4.99-12.28-9.99-18.43-14.97-.94-.76-1.93-1.49-2.94-2.2-.18-.08-.88-.09-.89,.3,.23,9.59,1.42,19.13,1.75,28.71,.01,3.32,.73,6.69,.41,9.99-.39,.48-1.28,.1-1.7-.2-6.78-4.61-13.54-9.22-20.33-13.81-.53-.26-1.04-.85-1.67-.74-.32,.03-.47,.17-.49,.43-.16,3.86,.13,7.75,.25,11.62,.42,10.65,.92,21.32,.63,31.97-.27,.74-1.5,.16-2.01-.12-6.51-3.45-13.02-6.9-19.54-10.35-2.6-1.45-2.3M 9-.26-2.45,2.03-.25,16.26,.01,32.54-1.08,48.78l.14-.06c-7.8-2.53-15.31-5.85-23.15-8.31-.49-.17-1.14,.17-1.17,.59-1.36,19.43-2.9,38.84-4.92,58.22l.12-.11c-8.74-.93-17.25-3.52-26-4.44l.08,.07Z"/><path class="cls-2" d="M773.42,900.08c-.53,4.97-.92,9.97-1.15,14.98-2.44,2.63-4.62,5.49-7.27,7.93-.15,.13-.49,.11-.81,.16-1.25-2.7-1.37-5.66-2.71-8.3-.81,.05-1.15,.36-1.46,.71-4.01,4.47-8.52,8.63-12.89,12.86-.85,.76-2.93,3.36-3.46,1.24-.6-2.21-1.22-4.42-1.93-6.59-1.02-1.35-2.54,1.19-3.43,1.75-4.9,4.39-9.52,9.26-15.04,13.05-.2M 1,.08-.81-.06-.97-.32-1.55-2.5-3.1-5-4.66-7.52,5.34-4.76,11-9.18,15.93-14.2,.77-.62,1.38-1.52,2.47-1.55,2.12,2.13,3.38,4.85,5.26,7.11,1.08-.25,1.48-.84,1.97-1.32,4.55-4.41,9-8.87,13.18-13.5,.39-.43,.73-.9,1.61-.88,1.26,1.89,1.82,4,2.6,6.06,.23,.52,.54,1.52,1.29,1.28,4.23-3.9,7.58-8.7,11.47-12.95Z"/><path class="cls-2" d="M977.4,1211.24s.01-.05,.02-.08h.06l-.08,.08Z"/><path class="cls-2" d="M973.01,1036.03c-.72,8.54-2.15,17.04-3.39,25.52-5.9,.91-11.81,1.34-17.92,1.34,1.02-5.81,1.94-11.63,2.9-17.45,.09-.63,.37-1.98-.M 7-1.81-4.67,1.81-9.05,4.27-13.6,6.34-.82,.22-2.92,1.87-3.29,.6,.36-4.19,1.43-8.32,2.05-12.48,1.2-7.25,2.02-14.55,2.98-21.84,.41-3.21,.78-6.43,1.15-9.65,.02-.15-.16-.41-.33-.47-.9-.17-1.68,.59-2.44,.94-3.79,2.25-7.56,4.51-11.35,6.75-.47,.21-2.16,1.36-2.28,.48,1.89-12.7,3.07-25.48,4.21-38.26-.19-1.07-1.64,0-2.14,.32-3.93,2.79-7.84,5.61-11.85,8.29-.14,.1-.49,.02-.74-.02-.17-.06-.25-.37-.27-.54,.34-5.16,.87-10.31,1.28-15.48,.38-5.8,1.13-11.59,.86-17.42-.68-.62-1.63,.37-2.21,.74-3.57,2.92-6.82,6.21-10.59,8.87-.12,.07-.6M 7-.07-.68-.15-.1-.63-.2-1.28-.17-1.92,.26-5.92,.57-11.84,.79-17.76,.11-2.9,.08-5.81,.09-8.72,0-.18-.21-.36-.33-.53-.14-.21-.69-.1-1.03,.21-2.2,2.02-4.24,4.19-6.39,6.26-1.51,1.28-2.83,3.08-4.49,4.06-.21-.09-.52-.22-.54-.36-.08-.75-.13-1.5-.12-2.25,.02-7.22,.36-14.44,.12-21.65-.02-.48,.31-1.22-.58-1.34-.72-.1-1.02,.58-1.4,.99-2.68,2.97-5.35,5.95-8.03,8.92-.65,.58-1.11,1.43-2.14,1.15-.15-6.34-.21-12.7-.35-19.05-.02-.96,.09-1.94-.43-2.85-.52-.74-1.51,.73-1.92,1.08-2.48,2.95-4.92,5.92-7.39,8.88-.54,.42-1.13,1.76-1.91,1.M 35-.1-.06-.21-.15-.22-.23-.06-1.07-.17-2.14-.16-3.21,.07-5.07-.65-10.11-.85-15.17,.04-.4-.67-.9-1.01-.6-2.93,3.42-5.48,7.15-8.26,10.71-.54,.55-.89,1.54-1.81,1.46-.1,0-.28-.12-.3-.2-.12-.52-.27-1.05-.3-1.58-.15-4.86-.45-9.69-1.04-14.52-.02-.18-.22-.35-.34-.52-.13-.18-.7,.06-.97,.42-2.79,3.81-5.53,7.64-8.34,11.45-.28,.28-.98,1.12-1.43,.84-2.93-17.89,.86-19.75-10.9-3.32-.68,.69-1.06,2.07-2.18,2.02-.09-.01-.23-.15-.25-.24-.19-.74-.41-1.47-.51-2.22-.49-1.34-.68-11.45-2.46-10.17-3.15,4.1-6.04,8.4-9.08,12.58-.33,.46-.63,.M 96-1.34,1.14-.57-.37-.69-.9-.78-1.44-.25-1.47-.5-2.94-.76-4.42,.45-3.66,1-7.31,1.63-10.96,2.04-3.08,4.06-6.15,6.07-9.24,.37-.57,.65-1.18,1.34-1.57,.59,.14,.81,.52,.91,.93,.95,3.47,1.55,7.02,2.85,10.39,.02,.05,.2,.09,.3,.09,.78-.17,1.33-1.41,1.85-2.01,2.17-3.34,4.31-6.7,6.47-10.05,.42-.59,1.15-2.11,1.98-1.31,1.24,3.69,1.52,7.65,2.37,11.46,.13,.36,.2,1.02,.65,1.1,.23-.01,.58-.02,.68-.13,2.95-3.94,5.43-8.18,8.2-12.24,.24-.26,.79-.83,1.19-.58,1.53,4.65,1.21,9.88,2.59,14.63,.12,.31,.81,.23,.95,.1,.65-.82,1.26-1.65,1.84-M 2.5,2.13-3.12,4.25-6.25,6.37-9.37,.3-.43,.7-.6,1.39-.35,.86,5.41,1.81,10.86,2.06,16.33,.01,.31,.52,.74,.72,.64,.22-.11,.47-.21,.63-.36,2-2.38,3.72-5,5.61-7.48,.96-1.3,1.88-2.61,2.89-3.89,.15-.19,.67-.19,1.12-.31,1.03,6.52,1.26,12.89,2.02,19.41,0,.14,.35,.27,.56,.37,.56-.06,.98-.73,1.37-1.1,2.64-3.25,5.22-6.54,7.85-9.79,.77-.87,1.2-.43,1.42,.35,3.34,24.39-3.22,28.17,11.55,11.78,.41-.41,1.19-1.22,1.8-.72,.93,7.91,1,15.92,1.03,23.88,.11,.72-.28,2.38,.95,1.97,3.66-3.07,6.89-6.62,10.37-9.89,.37-.36,.8-.55,1.48-.23,.41,8M .68,.4,17.41,.17,26.1-.03,1.08,.03,2.15,.1,3.22,.06,.2,.6,.55,.87,.31,3.27-2.35,6.23-5.06,9.37-7.58,.83-.42,2.53-2.68,3.29-1.59,.78,11.28-.68,22.61-.66,33.88,.99,.53,2.14-.7,3.03-1.18,3.36-2.33,6.7-4.68,10.05-7.02,.32-.3,1.02-.45,1.42-.19,.12,.31,.25,.62,.24,.94-.28,6.13-.37,12.28-.92,18.4-.33,4.62-.65,9.25-.99,13.87-.1,2.01-.92,4.07-.51,6.08,.59,.21,1.07,.03,1.51-.22,2.31-1.31,4.6-2.64,6.92-3.93,2.21-1.24,4.44-2.44,6.66-3.65,.27-.15,.92,.1,.95,.34-.23,10.83-1.66,21.73-2.97,32.52-.53,4.06-1.05,8.13-1.56,12.21-.05,.M 41,.65,.75,1.13,.55,4.72-2.06,9.41-4.19,14.11-6.3,.73-.28,2.37-1.19,2.59,.02Z"/><path class="cls-2" d="M993.69,1141.18c-4.01,23.57-10.58,46.75-16.27,69.98-7.64,.76-15.24,2.51-22.81,3.7-.7-.54-.5-1.16-.32-1.88,1.47-4.92,3.03-9.81,4.43-14.74,2.11-7.45,4.19-14.9,6.14-22.37,2.56-9.79,4.99-19.6,7.46-29.4,.12-.75,.43-1.79-.73-1.79-5.29,1.14-10.48,2.75-15.72,4.07-1.34,.17-4.94,2.15-4.32-.54,3.63-14.69,7.4-29.39,10.42-44.21,6.56-.4,13.13-1.21,19.59-2.45-2.45,14-5.57,27.89-8.39,41.82-.04,.24,.54,.6,.84,.54,6.24-1.23,12.4-3.M 58,18.85-3.11,.23,0,.46,.2,.83,.38Z"/><path class="cls-2" d="M1072.64,698.95c-1.4,.77-2.71-.42-3.97-.94-6.16-2.88-12.31-5.78-18.49-8.64-1.21-.37-7.37-3.77-4.72-.23,3.3,4.94,6.61,9.87,9.9,14.81,.98,1.61,2.13,3.21-.79,1.96-5-2.12-9.97-4.27-14.99-6.36-1.91-.8-3.88-1.49-5.86-2.18-.28-.1-.72,.08-1.25,.16,3.95,5.97,7.9,11.8,11.85,17.75,.24,.37,.46,.78-.14,1.21-6.68-2.44-13.15-5.34-20.08-7.4-.19,.19-.5,.39-.46,.49,.19,.51,.42,1.01,.73,1.48,3.18,4.87,6.38,9.72,9.57,14.59,.51,.94,1.42,1.8,1.35,2.92-.01,.25-.44,.27-1.07,.06-M 4.83-1.64-9.66-3.28-14.5-4.91-.99-.22-2.02-.9-3.01-.42,.09,1,.87,1.79,1.4,2.64,3.06,4.91,6.17,9.81,9.25,14.72,.42,.67,.79,1.37,1.12,2.07,.07,.14-.12,.38-.23,.55-.7,.18-1.55-.31-2.25-.45-4.23-1.41-8.55-2.6-12.9-3.74-.38-.1-.79-.26-1.12-.01-.53,.39-.06,.78,.13,1.14,.2,.4,.46,.78,.69,1.17,2.97,5.07,5.94,10.14,8.89,15.22,.56,.97,1.03,1.98,1.52,2.98,.04,.09,.03,.27-.04,.3-.97,.49-2.03-.21-3.03-.35-3.46-.88-6.92-1.78-10.38-2.65-.63-.16-1.32-.25-1.94,.11,0,.89,.6,1.61,1.01,2.4,3.12,6.4,6.99,12.56,9.69,19.11,.02,.15-.31,.4M 7-.43,.45-4.34-.67-8.62-1.7-12.93-2.53-1.85,0-.07,2.08,.18,2.92,3.63,7.51,6.89,15.12,9.87,22.83-.42,.46-.93,.5-1.47,.39-4.28-.97-8.58-1.88-12.93-2.5l.1,.06c-3.16-8.39-7.06-16.48-10.79-24.64-.1-.26,.29-.75,.59-.73,3.88,.22,7.75,.63,11.6,1.12,.54,.06,1.03-.42,.83-.84-3.1-6.46-6.77-12.65-10.13-18.98-.27-.59-1.16-1.69-.05-1.91,4.43,.03,8.67,1.5,13.04,1.81,.34-.02,.52-.2,.42-.43-3.01-6.16-7.05-11.82-10.46-17.77-.4-.66-1.03-1.27-.88-2.08,.62-.35,1.3-.24,1.94-.12,3.78,.74,7.63,1.31,11.33,2.3,.64,.17,1.3,.29,1.95-.09-2.91-M 5.93-7.36-11.22-10.83-16.89-.37-.76-1.31-1.46-.94-2.35l-.06,.09c4.6,.09,9.04,2.09,13.57,2.93,.67,.03,3.15,1.09,3.13,.09-3.75-6.23-8.35-11.99-12.33-18.08,.5-.45,1.02-.41,1.52-.28,5.6,1.52,11.19,3.06,16.75,4.72,1.52-.05-.2-1.69-.5-2.31-3.17-4.38-6.36-8.75-9.52-13.14-.6-.83-1.13-1.71-1.67-2.57-.03-.05,.05-.18,.12-.23,.53-.33,1.32,.06,1.9,.15,5.41,1.64,10.81,3.31,16.09,5.22,.85,.31,1.75,.53,2.64,.77,.12,.03,.52-.24,.49-.39-3.71-6.04-8.44-11.46-12.35-17.39-.06-.08-.07-.28-.03-.3,.21-.09,.49-.23,.68-.19,7.23,2.24,14.35,4M .95,21.37,7.65,.74,.41,3.36,1.32,1.95-.63-3.87-5.42-7.75-10.84-11.62-16.26-.31-.37,.2-.65,.54-.58,5.19,1.67,10.18,3.94,15.25,5.91,3.84,1.57,7.61,3.22,11.43,4.82,.15,.05,.94-.03,.79-.39-.62-1.34-1.63-2.47-2.44-3.71-2.88-4.14-5.76-8.28-8.65-12.42-.31-.39-.8-1.17-.15-1.39,3.36,.81,6.49,2.58,9.68,3.86,7.48,3.14,14.67,6.98,22.1,10,.46-.19-.04-1.12-.18-1.46-2.14-3.48-4.32-6.94-6.47-10.41-.36-.57-.66-1.17-.97-1.76-.03-.06,.06-.19,.14-.25,.55-.29,1.26,.24,1.8,.39,5.18,2.52,10.4,4.98,15.51,7.59,6.13,3.13,12.15,6.4,18.22,9.6M ,.64,.21,1.4,.92,2.06,.69,.09-.07,.21-.2,.18-.27-.24-.61-.47-1.23-.79-1.82-1.75-3.27-3.52-6.52-5.28-9.78-2.43-3.91-.46-2.77,2.21-1.38,13.71,7.07,26.68,14.97,39.84,22.63,.1,.05,.36,.07,.38,.03,.11-.17,.29-.4,.22-.55-2.16-4.86-4.37-9.72-6.45-14.61,.33-.77,1.4,.09,1.92,.29,16.78,9.5,32.47,20.24,48.68,30.43,.17,.07,.53-.14,.48-.34-.29-.94-.58-1.88-.92-2.81-1.43-3.93-2.87-7.85-4.3-11.78-.18-.51-.38-1.03,.13-1.63,17.57,10.46,34.16,22.77,50.72,34.5,2.39,1.74,4.76,3.49,7.16,5.22,.12,.09,.47,.01,.7-.04,.5-.67-.13-1.73-.22-2M .51-1.18-4.64-2.37-9.28-3.55-13.92-.34-1.55,1.11-.89,1.84-.32,2.12,1.5,4.25,2.99,6.34,4.51,18.33,13.32,36.62,27.01,54.1,41.27,1.89,1.53,3.82,3.04,5.75,4.54,.15,.12,.54,.15,.74,.07,.23-.14,.38-.55,.31-.83-.63-4.49-1.29-8.99-1.89-13.48-.17-1.58-1.29-6.16,1.65-3.68,26.66,20.93,52.78,42.49,78,65.1,.43,6.66,.06,13.37,.17,20.06-.18,1.21-.21,1.83-1.57,.74-3.28-3-6.54-6.02-9.8-9.03-20.71-19.14-42.18-37.93-64.17-55.99-.5-.3-1.35-1.24-1.85-.56,.28,5.6,1.44,11.12,2.08,16.69,.05,.54,.42,1.98-.48,1.97-18.61-14.89-36.6-30.74-55.M 95-45.19-2.82-2.17-5.64-4.32-8.47-6.48-.48-.37-.97-.76-1.86-.66,.82,5.76,3.1,11.32,3.86,17.1-.04,.22-.48,.62-.77,.45-13.33-10.15-26.6-20.47-40.4-30.27-4.6-3.32-9.31-6.55-13.97-9.81-.61-.36-1.22-.97-2-.77-.07,.01-.16,.19-.14,.29,.09,.42,.19,.84,.33,1.25,1.64,4.77,3.3,9.54,4.93,14.32,.06,.19-.03,.41-.08,.62-.32,.36-1.25-.22-1.64-.54-9.02-6.34-18.04-12.63-27.19-18.83-6.18-4.17-12.57-8.12-18.88-12.16-.49-.21-1.17-.76-1.71-.55-.09,.06-.2,.19-.18,.26,.32,.82,.65,1.64,1.01,2.45,1.7,3.86,3.42,7.71,5.1,11.57,.17,.38,.11,.83M ,.12,1.25,0,.05-.21,.16-.27,.14-3.49-1.6-6.51-4.16-9.84-6.11-9.67-6.2-19.54-12.2-29.65-17.93-.76-.43-1.6-.78-2.41-1.15-.05-.02-.22,.05-.28,.11-.08,.08-.17,.21-.14,.28,.31,.71,.63,1.42,.99,2.11,1.96,3.78,3.93,7.55,5.89,11.33,.21,.44,.58,1.33-.23,1.27-11.09-6.25-22.07-12.7-33.53-18.56-.78-.41-1.64-.71-2.48-1.04-.03-.01-.27,.16-.25,.21,1.67,4.12,4.65,7.73,6.8,11.65,1.49,2.28,2.6,4.81,4.36,6.9l-.07-.07c-1.42,.87-2.86-.8-4.16-1.28-8.84-4.71-17.86-9.19-27.06-13.43-1.27-.33-.49,1.16-.08,1.64,3.82,5.64,7.15,11.68,11.27,17.M 09l.04-.04Z"/><path class="cls-2" d="M412.1,696.62h0s-.07,.04-.1,.05l.1-.05Z"/><path class="cls-2" d="M439.68,639.76s-.07,0-.1-.02c0-.01-.01-.03-.01-.04l.11,.06Z"/><path class="cls-2" d="M450.29,664.37c.09,.24-.33,.69-.65,.67-3.36-.09-6.69-.54-10.02-.94-.76-.09-1.7-.54-2.23,.11-.48,.58,.18,1.23,.49,1.81,3.35,6.34,6.84,12.62,10.12,19,.13,.26-.26,.68-.62,.65-4.27-.26-8.46-1.18-12.67-1.86-.35-.06-.8,.33-.69,.58,3.34,6.65,7.64,12.8,11.36,19.24,.23,.42-.24,.8-.87,.73-4.2-.6-8.44-1.41-12.54-2.43-.48-.1-1.45-.28-1.65,.29,M 2.26,4.53,5.48,8.54,8.18,12.83-2,1.38-3.96,2.82-5.89,4.29-2.34-.45-4.6-1.48-7-1.41-.07,0-.22,.16-.2,.21,.6,1.72,1.93,3.08,2.89,4.62-11.03,9.02-20.91,19.56-29.28,31.37-.76-.18-1.62-.12-.74,1.07-2.27,3.25-4.42,6.59-6.45,10.03-3.16-1.16-6.25-3.01-9.46-3.8-.12,.17-.31,.41-.24,.54,1.89,3.22,4.23,6.18,6.31,9.28-.91,1.69-1.78,3.4-2.62,5.13-8.12-3.48-16.12-7.26-24.12-10.98-.71,.55-.31,.87,.11,1.71,2.41,3.98,4.96,7.88,7.32,11.88,.08,.15-.09,.39-.18,.58-9.43-3.54-18.46-8.87-27.45-13.41-3.13-1.67-6.31-3.28-9.47-4.92-.1-.05-.3M 4-.06-.36-.03-.12,.18-.31,.41-.24,.56,2.07,4.23,4.49,8.3,6.68,12.46,.15,.42,.67,1.14,.31,1.5-.08,.06-.25,.12-.32,.09-.93-.42-1.87-.83-2.76-1.29-13.88-6.97-26.81-15.32-40.23-22.64-.39,.58-.11,1.07,.12,1.58,1.95,4.35,4.05,8.66,5.91,13.05,.1,.27-.05,.6-.12,1.05-16.33-9.07-31.94-19.21-47.28-29.41-.82-.55-1.68-1.07-2.55-1.58-.13-.07-.44,.01-.64,.07-.08,.03-.13,.2-.11,.29,1.58,5.25,3.87,10.29,5.44,15.53,.02,.16-.16,.36-.3,.52-.03,.04-.28,.01-.38-.04-19.28-12.08-38.13-25.26-56.34-38.75-2.11-1.52-2.06-.61-1.73,1.41,1.17,4.M 64,2.39,9.28,3.58,13.91,.12,.53,.35,1.09-.26,1.39-18.6-12.23-36.55-26.45-54.17-40.12-4.3-3.41-8.55-6.87-12.83-10.3-.29-.3-.92-.64-1.3-.25,.12,6.08,1.61,12.19,2.08,18.29-.16,1.06-1.64-.11-2.08-.45-12.62-9.87-25.14-19.81-37.38-29.98-13.28-11.02-26.19-22.28-39.1-33.59-1.97-1.78-1.84-1.49-1.86-3.71,0-5.92-.06-11.86-.07-17.77,0-.41-.09-.86,.36-1.18,.43-.36,.96,.25,1.3,.45,8.26,7.55,16.45,15.11,24.77,22.61,15.73,14.18,31.77,27.91,48.16,41.41,.75,.61,1.56,1.18,2.36,1.75,.12,.05,.59-.07,.65-.22-.09-6.12-1.6-12.19-2.17-18.2M 9-.07-.43,.54-.49,.83-.37,20.51,17.04,41.15,34.34,62.66,50.39,.78,.6,1.64,1.12,2.47,1.66,.31,.18,.73-.21,.74-.45-1.33-5.6-2.77-11.18-4-16.81-.03-.13,.23-.33,.39-.46,13.8,9.95,27.41,21.03,41.63,30.95,4.2,3.03,8.51,5.96,12.79,8.92,.59,.42,1.3,.73,1.97,1.08,.08,.04,.27,.02,.35-.03,.09-.06,.18-.2,.16-.29-.23-.83-.46-1.67-.75-2.5-1.44-4.14-2.91-8.28-4.36-12.43-.72-2.08,1.1-1.15,1.99-.42,4.86,3.41,9.68,6.86,14.57,10.24,10.41,7.15,20.98,14.31,31.93,20.83,.33,.19,.71-.23,.69-.48-1.74-4.78-4.08-9.34-6.04-14.03-.04-.36-.53-.M 95-.06-1.19,13.9,8.17,27.75,17.35,42.04,25.5,0-.01,.14-.11,.14-.11l-.22,.06c1.19-1.05-.45-2.44-.8-3.57-1.86-3.58-3.72-7.15-5.58-10.73-.21-.41-.34-.8,.08-1.27,10.95,6.25,21.86,12.56,33.18,18.39,.83,.31,2.35,1.56,3.12,1.07,.31-.79-.75-1.61-1.04-2.33-2.83-4.65-5.65-9.3-8.46-13.95-.34-.76-1.22-1.48-.97-2.35,.64-.54,2.27,.89,3.04,1.15,8.72,4.69,17.69,9.06,26.73,13.34,.44,.21,.87,.51,1.45,.37,.71-.05-.49-1.58-.65-1.98-3.56-5.42-7.18-10.8-10.48-16.38-.48-1.48,2.45,.17,2.99,.41,7.99,3.55,15.64,7.79,23.87,10.81,.65-.72-.24-M 1.37-.58-2.06-3.37-5.03-6.75-10.05-10.1-15.09-.6-1.22-1.68-2.49,.58-1.71,6.61,3,13.32,5.65,20.09,8.3,.7,.22,1.48,.68,2.2,.24,.05-.03,.08-.2,.03-.27-.61-.95-1.23-1.9-1.86-2.85-3.33-5.04-6.66-10.08-9.97-15.13-.09-.13,.11-.39,.21-.57,6.87,1.94,13.51,5.66,20.52,7.2,.91-.32-.86-1.97-1.05-2.55-3.44-5.6-7.54-10.86-10.58-16.68,.45-.8,1.71,.12,2.41,.21,5.11,1.65,10.14,3.55,15.29,5.06,1.86,.22,.27-1.65-.14-2.37-3.47-5.47-7.02-10.89-10.27-16.47-.22-.36-.18-.81-.25-1.23,.63-.2,1.24-.01,1.83,.17,3.27,.99,6.52,2.02,9.8,2.97,1.51M ,.44,3.07,.77,4.62,1.11,.09,0,.45-.33,.41-.44-3.3-6.27-7.31-12.19-10.56-18.44-.2-.62-1.36-1.96-.37-2.19,4.17,.69,8.18,2.08,12.29,3.03,.92,.13,1.86,.51,2.68-.16-3.48-6.86-7.19-13.62-10.66-20.5-.19-.39-.42-.8,0-1.19,.33-.29,.75-.13,1.12-.06,4.02,.87,8.07,1.63,12.11,2.43,.87,.04,.82-.64,.54-1.18-3.9-8.07-7.54-16.26-10.69-24.58,.5-.42,1.01-.45,1.55-.34,4.25,.95,8.5,1.78,12.81,2.48,2.88,8.47,7.06,16.41,10.71,24.63Z"/><polygon class="cls-2" points="431.53 461.92 431.53 462 431.44 462 431.53 461.92"/><polygon class="cls-2M " points="433.83 504.59 433.98 504.59 433.98 504.67 433.83 504.59"/><path class="cls-2" d="M439.62,542.74v.06s-.05,.01-.07,.02l.07-.08Z"/><path class="cls-2" d="M496.61,578.52c-1.24,.83-5.12,5.64-6.29,4.65-2.36-7.39-3.28-15.26-4.92-22.86-.26-1.38-.51-2.77-.81-4.14-.02-.11-.5-.28-.65-.22-3.97,2.21-7.18,5.6-11.06,7.98-1.87,.59-1.62-3.25-1.96-4.31-1.95-8.8-2.72-17.75-4.26-26.58-.28-.62-1.17-.44-1.65-.15-3.14,1.91-6.78,3.08-10.25,4.51-.38,.18-1.15,.23-1.42-.08-2.85-11.37-2.84-23.37-4.37-34.98-.31-1.73-2.42-.74-3.56-.49M -3.82,.83-7.55,2.31-11.43,2.74-.67-14.19-2.42-28.37-2.45-42.59,4.51-.36,8.85-1.58,13.29-2.41,.69-.18,2.21-.41,2.4,.45,.54,13.33,.34,26.74,1.62,40.02,.43,1.53,7.55-1.57,8.7-2.06,1.5-.71,2.92-1.53,4.39-2.3,.64-.34,1.34-.44,1.47-.19,.15,.28,.32,.57,.34,.87,.55,11.41,1.47,22.81,2.68,34.17,.67,1.76,3.01-.77,4.01-1.22,2.36-1.61,4.7-3.22,7.06-4.83,.83-.41,2.4-2.19,3.13-.93,.7,5.34,1.06,10.73,1.71,16.09,.58,4.72,1.29,9.43,2.11,14.11,.07,.42,.88,.62,1.26,.32,3.46-2.73,6.8-5.51,10.2-8.3,.32-.3,1.05-.23,1.21,.21,.1,.41,.2,.81M ,.29,1.22-1.06,10.52-1.31,20.97-.79,31.3Z"/><path class="cls-2" d="M506.42,632.39c-.09,.02-.18,.03-.28,.03-2.32-4.72-3.85-9.86-5.82-14.74-.72-1.1-1.71-7.8-3.35-6.65-2.93,2.67-5.75,5.47-8.81,8-.79,.48-1.29-.36-1.54-.98-2.33-6.85-4.7-13.7-6.68-20.63-.27-.94-.62-1.87-.98-2.79-.04-.1-.48-.2-.67-.15-3.59,1.79-6.66,4.5-10.31,6.19-.67,.17-.95-.54-1.09-1.04-1.54-5.46-3.13-10.91-4.61-16.38-.98-3.58-1.73-7.2-2.65-10.78-.13-.43-.77-.71-1.24-.51-2.26,.96-4.5,1.94-6.77,2.89-1.31,.55-2.65,1.04-3.99,1.54-.44,.17-1.16-.14-1.26-.54M -2.69-10.07-4.46-20.35-6.61-30.55-.16-.82-.09-1.67-.14-2.5,4.48-1.29,8.88-3.56,13.46-4.2,1.82,10.65,3.78,21.3,6.14,31.85,.11,.41,.76,.63,1.27,.41,3.21-1.38,6.22-3.01,9.22-4.65,.57-.27,1.44-.99,2.03-.49,2.57,8.75,4.09,17.8,6.73,26.56,.06,.21,.18,.41,.26,.61,.08,.18,.86,.3,1.08,.15,3.42-2.32,6.34-5.3,9.62-7.81,.44-.36,1.02-.21,1.18,.32,.52,1.78,1.03,3.56,1.52,5.35,1.81,6.02,2.91,12.39,5.53,18.15,.94,.55,1.82-.78,2.45-1.33,1.61,8.38,3.72,16.62,6.31,24.67Z"/><path class="cls-2" d="M670,602.28s.04-.07,.07-.1c.03,.01,.05M ,.03,.08,.04l-.15,.06Z"/><path class="cls-2" d="M697.61,575.53c-.09,.33-.08,.68-.26,.94-3.24,4.59-6.45,9.22-9.75,13.77-.27,.34-.96,.49-1.43,.26-2.56-1.24-4.97-2.57-7.63-3.66-3.49,4.93-5.34,10.32-8.47,15.34-2.56-1.32-4.99-2.95-7.64-4.07-.2-.05-.57,.05-.69,.19-2.18,3.61-3.57,7.66-5.44,11.44-.65,1.19-.83,2.64-2.02,3.44-3.11-1.15-4.94-3.28-8.14-4.37-2.01,4.12-3.44,8.4-5.18,12.61-.31,.81-.49,1.66-1.34,2.43-3.06-1.15-4.93-3.56-7.94-4.85-1.87,.89-4.98,15.73-6.65,14.48-2.13-1.55-3.8-3.62-5.72-5.41-.42-.42-.8-.88-1.66-1.01-M 2.38,4.32-2.92,9.48-5.36,13.74-.63,.01-1-.31-1.31-.66-1.74-1.92-3.46-3.85-5.2-5.77-.57-.57-.9-1.18-1.87-.98-1.74,4.21-2.71,8.9-4.8,12.91-.1,.11-.59,.14-.67,.06-.75-.76-1.49-1.52-2.15-2.32-1.63-1.98-3.22-3.98-4.82-5.97-.17-.21-.94-.16-1.03,.07-1.73,3.92-3.18,7.99-4.64,11.98-.83,.14-1.19-.16-1.63-.72-1.86-2.63-3.7-5.26-5.56-7.88-.47-.48-.96-1.72-1.8-1.2-2.15,3.59-3.15,7.83-5.22,11.49-.19,.31-.78,.15-.96,0-2.87-3.56-4.71-8.31-7.75-11.64-.63,.3-.89,.78-1.13,1.29-1.18,2.45-2.35,4.89-3.56,7.32-2.9-5.37-5.51-10.9-7.82-16.M 56,1.15-2.08,2.28-4.15,3.43-6.22,.26-.46,.45-1,1.27-1.23,2.52,4.31,4.55,8.96,7.04,13.34,.21,.36,.91,.52,1.17,.09,1.84-3.44,3.39-7.02,5.09-10.54,.19-.39,.47-.75,1.14-.9,2.63,3.69,4.21,7.98,7.14,11.47,.68-.05,.98-.35,1.16-.79,1.73-3.83,3.07-7.86,5.12-11.53,.8,.28,1.08,.77,1.38,1.24,1.69,2.57,3.37,5.15,5.07,7.72,1.01,1.41,1.61,1.42,2.28-.24,6.71-15.27,2.31-14.32,12.06-3.1,.93,.41,1.27-1.52,1.65-2.12,1.46-3.58,2.69-7.24,4.28-10.77,.08-.17,.34-.35,.56-.4,.92-.12,1.3,.94,1.85,1.47,1.41,1.69,2.77,3.45,4.24,5.11,.51,.56,.9M 2,.72,1.27,.59,.42-.16,.56-.44,.68-.74,1.39-3.49,2.77-6.98,4.17-10.46,.52-.8,.83-3.2,2.11-2.64,2.02,2.01,4.04,4.01,6.1,5.99,.2,.19,.93,.09,1.05-.14,2.28-4.68,3.82-9.72,6.39-14.26,.08-.11,.55-.19,.7-.11,2.14,1.24,3.94,2.92,5.94,4.36,.39,.29,.84,.55,1.59,.44,2.55-4.76,4.61-9.85,7.23-14.58,.26-.47,.86-.62,1.29-.33,1.43,.98,2.85,1.97,4.3,2.94,.85,.39,2.04,1.81,2.96,.95,2.71-5,5.6-10.03,8.09-15.11-.58-1.17-2.02-1.68-3.05-2.5-1.23-.98-2.41-2.01-3.89-2.85-1.18,.55-1.52,1.67-2.14,2.69-1.95,3.55-3.88,7.1-5.83,10.65-.49,.62-M .8,1.98-1.79,1.86-2.15-1.14-3.85-3.01-5.8-4.46-.39-.32-.79-.58-1.52-.52-3.01,4.8-5.02,10.15-7.76,15.08-.74,0-1.11-.29-1.43-.63-1.85-1.83-3.39-3.99-5.46-5.58-.12-.08-.62,.01-.68,.12-.61,1.07-1.23,2.15-1.73,3.26-1.5,3.34-2.96,6.7-4.43,10.05-.18,.42-.47,.76-1.07,1-2.6-2.07-4.09-4.99-6.33-7.33-.73,.12-1,.47-1.18,.87-1.95,4.21-3.48,8.66-5.71,12.74-1.28,1.05-4.74-5.72-5.8-6.78-1-1.41-1.56-2.06-2.44-.07-1.85,3.9-3.2,8.07-5.33,11.81-.4,.2-.99-.36-1.21-.62-1.62-2.6-3.21-5.21-4.81-7.82-.29-.49-.56-.98-1.32-1.31-2.53,4.02-3.8M 8,8.7-6.14,12.87-.72-.1-1.04-.45-1.26-.84-1.51-2.76-3.15-5.48-4.3-8.36-.32-.8-.83-1.57-1.27-2.34-.11-.11-.57-.13-.69,.01-2.59,3.86-3.78,8.43-6.46,12.21-1.23-.53-1.44-1.93-1.99-3.01-1.49-3.58-2.95-7.15-4.46-10.83-1.22,.04-1.47,1.19-2,2.04-1.58,2.85-3.15,5.71-4.74,8.56-1.52,2.69-1.82,.18-2.58-1.31-1.62-4.46-3.01-8.96-4.79-13.35-.05-.12-.36-.18-.54-.27-.64,.3-.88,.81-1.18,1.29-1.06,1.69-2.12,3.39-3.19,5.08-2.03-7.33-3.57-14.82-4.59-22.43,.83-1.16,1.66-2.33,2.49-3.49,.25-.35,.52-.73,1.18-.68,.63,.73,.74,1.59,.96,2.43,1M .12,4.32,2.24,8.64,3.39,12.96,.23,.84,.55,1.66,.89,2.48,.12,.15,.76,.33,.96,.07,2.72-3.53,4.61-7.59,7.28-11.14,.1-.13,.47-.14,.72-.17,.42,.12,.41,.76,.57,1.1,1.36,4.39,2.7,8.78,4.07,13.16,.22,.44,.42,1.21,.91,1.38,.22-.04,.52-.11,.6-.24,.55-.86,1.07-1.74,1.56-2.62,1.61-2.85,3.2-5.7,4.82-8.54,.15-.27,.48-.47,.76-.68,.45-.09,.76,.56,.92,.89,1.49,4.22,2.78,8.55,4.42,12.71,1.19,.1,1.36-.96,1.95-1.84,1.67-3.18,3.32-6.36,4.97-9.54,.31-.6,.6-1.2,1.29-1.61,.73,.59,.91,1.33,1.16,2.06,1.15,3.31,2.29,6.7,4.05,9.8,.08,.13,.35,M .2,.56,.25,2.93-3.94,4.2-9.19,7.07-13.29,.66-.36,1.01,.34,1.26,.84,1,1.48,3.63,9.64,5.27,8.96,2.65-4.28,4.34-9.08,6.88-13.43,.31-.43,.91-.26,1.13,.14,1.63,2.67,2.87,5.76,5.01,8.05,.15,.1,.65,.09,.7,0,.44-.67,.84-1.35,1.19-2.04,1.93-3.79,3.84-7.58,5.75-11.38,.21-.41,.52-.74,1.24-.9,.9,.98,5.11,9.17,6.42,7.08,2.23-4.28,4.53-8.52,6.81-12.77,1.28-2.49,1.74-2.06,3.19,.03,1.34,1.48,2.7,2.95,4.07,4.41,.23,.25,.82,.18,1-.1,3.22-4.99,5.75-10.27,9.11-15.18,.47,.16,.93,.19,1.15,.4,1.8,1.6,3.3,3.48,5.29,4.86,1.29,.49,1.74-1.39M ,2.46-2.11,2.83-4.04,5.64-8.09,8.47-12.13,.32-.45,.62-.94,1.14-.99,2.42,1.88,4.73,3.68,7.07,5.51,.2,.43-.2,.76-.46,1.13-3.34,4.8-6.72,9.57-10.05,14.38-.24,.38-.13,.88,.3,1.16,1.78,1.15,3.57,2.3,5.37,3.42,2.01,1.24,2.21,.46,3.4-1.13,2.89-4.02,5.76-8.04,8.64-12.06,.33-.45,.65-.94,1.38-1.07,2.65,1.15,5.01,2.9,7.59,4.3Z"/><path class="cls-2" d="M196.48,1198.45c19.59-.23,39.32,.32,58.96-.25,5.19-.09,5.05-.3,2.78,3.32-2.94,4.84-6.18,9.53-8.95,14.47-.23,1.29,2.14,.59,2.9,.74,3.1-.11,6.19-.21,9.29-.38,12.89-.76,25.82-1.27,M 38.67-2.42,1.31-.11,2.65-.35,4.06,.02-.14,1.37-1.38,2.28-2.11,3.4-3.34,4.3-6.69,8.59-10.03,12.89-.42,.55-.79,1.12-1.17,1.69-.13,.19,.34,.69,.64,.68,13.4-.68,26.76-2.38,40.1-3.8,2.66-.3,5.34-.52,8.01-.77,.43-.04,.48,.41,.42,.72-4.93,5.94-10.39,11.53-15.5,17.34-.46,.51-1.05,.99-.92,1.74,14.79-1.07,29.49-4.03,44.24-5.65,1.48,.34-.13,1.37-.78,2.2-5.29,5.31-10.6,10.6-15.89,15.91-.94,1.21-4.53,3.63-.68,3.11,12.98-1.81,25.91-3.96,38.84-6.08,.2,0,.74,.33,.49,.62-6.83,6.86-14.09,13.31-21.08,20.02-.45,.54-3.06,2.49-1.6,2.72,M 12.29-1.88,24.54-3.99,36.81-5.96,.55-.08,1.04,.21,.55,.75-8.17,7.49-16.6,14.71-24.86,22.1-.81,.72-1.61,1.44-2.38,2.19-.12,.12-.06,.39-.02,.58,.83,.33,2.22-.08,3.15-.11,4.9-.73,9.79-1.47,14.68-2.24,5.62-.66,11.42-2.33,16.98-2.51,.13,.91-1.07,1.46-1.69,2.04-9.37,8.04-18.75,16.07-28.13,24.1-.73,.63-1.44,1.28-2.11,1.95-.12,.12,.01,.39,.04,.67,10.55-.81,20.9-3.02,31.46-3.85,0,.32,.11,.6-.02,.71-.87,.82-1.76,1.63-2.7,2.4-10.58,8.76-21.16,17.51-31.74,26.26-.84,.7-1.67,1.4-2.47,2.13-.14,.12-.17,.43-.08,.57,.7,.5,1.83,.14,2M .66,.16,4.15-.36,8.3-.73,12.45-1.09,4.28-.38,8.57-.76,12.85-1.14,.36-.03,.81-.13,.97,.25,.15,.35-.15,.62-.42,.85-.83,.7-1.68,1.4-2.53,2.09-13.61,10.89-27.14,21.9-40.81,32.73-.9,.78-2.27,.63-3.42,.66-7.14,0-14.28,.02-21.43,.02-5.03,.24-1.35-1.89,.44-3.41,5.6-4.51,11.21-9.02,16.8-13.53,5.78-4.67,11.54-9.36,17.31-14.04,1.75-1.48,4.74-3.28,.22-2.82-8.92,.76-17.73,1.29-26.68,1.94,.07-1.5,1.76-2.09,2.7-3.08,9.7-8.08,19.41-16.16,29.11-24.25,1.65-1.54,4.67-3.33,.11-2.83-9.2,1.06-18.39,2.14-27.59,3.15-.57,0-1.39,.16-1.87-.1M 8-.06-.09-.13-.25-.08-.31,.57-.59,1.13-1.19,1.76-1.74,8.47-7.39,16.94-14.76,25.41-22.15,.65-.71,3.52-2.74,.98-2.52-11.17,1.4-22.23,3.61-33.46,4.36-1.1-.07-.21-1.11,.21-1.46,7.18-6.57,14.39-13.12,21.56-19.7,.64-.78,4.21-3.36,1.45-3.03-7.96,1.09-15.92,2.19-23.89,3.27-4.39,.5-8.76,1.36-13.18,1.52-1.51-.16,.44-1.72,.86-2.23,5.77-5.69,11.56-11.37,17.33-17.05,2.45-2.42,2.89-3-1.09-2.57-12.89,1.79-25.77,3.51-38.74,4.64-.2-.01-.75-.35-.58-.65,.77-.88,1.54-1.77,2.34-2.63,4.73-5.11,9.48-10.2,14.21-15.31,.32-.5,1.21-1.1,1.07-M 1.65-.16-.14-.38-.37-.55-.36-3.88,.38-7.75,.8-11.62,1.19-9.09,.92-18.17,1.87-27.27,2.68-2.14,.19-4.29,.34-6.43,.5-.41,.03-.8-.02-1.01-.34-.22-.34,.04-.62,.25-.88,4.59-5.95,9.7-11.56,13.94-17.76,.06-.1-.21-.47-.34-.47-4.17-.15-8.31,.42-12.47,.65-12.99,.88-26.06,2.03-39.07,2.11-.97-.52,.36-1.59,.55-2.26,3-4.7,6.03-9.39,9.03-14.08,.43-.67,.79-1.36,1.11-2.07,.06-.13-.18-.47-.35-.51-3.46-.36-7,.09-10.48,.05-15.88,.33-31.8,.8-47.67,.27-.79-.37-.06-1.41,.09-2.01,2.25-5.07,4.52-10.14,6.76-15.21,.26-.59,.77-1.16,.44-1.85l-.M 13,.07Z"/><path class="cls-2" d="M1007.42,688.18c-.81,.29-1.58,.05-2.35-.13-4.13-.94-8.26-1.91-12.39-2.84-1.44-.16-2.91-.94-4.32-.41,3.83,6.01,9.39,11.13,12.99,17.3-.65,.29-1.16,.17-1.68,.05-4.52-1.04-9.1-1.9-13.73-2.55-.42-.05-1.77-.37-1.6,.32,3.41,5.29,7.47,10.17,11.13,15.3,.33,.67,1.48,1.54,1.03,2.29-.15,.13-.5,.19-.73,.16-4.35-.69-8.72-1.3-13.09-1.85-.77-.05-1.58,.4-.86,1.18,3.26,4.7,6.54,9.39,9.8,14.08,.55,1.04,3.37,3.9,.58,3.65-4.39-.49-8.78-1.02-13.2-1.28l.09,.07c-4.07-5.7-8.14-11.4-12.21-17.1-.33-.46-.77-.9M -.32-1.56,4.23-.22,8.54,.29,12.78,.43,.34,.02,.7-.45,.54-.69-3.37-4.96-7.33-9.53-10.94-14.33-.36-.69-1.64-1.46-1.13-2.27,.16-.2,.73-.29,1.1-.26,2.15,.13,4.3,.28,6.43,.49,2.27,.22,4.53,.52,6.8,.76,.22-.01,.77-.28,.58-.61-3.78-5.15-8.08-9.92-12.08-14.91-.37-.45-.8-.87-.61-1.56,5.44,.13,10.84,1.44,16.27,1.94,.45,.07,.51-.5,.39-.69-4.24-5.12-8.52-10.23-12.87-15.27-.09-.11,.05-.38,.14-.55,.04-.07,.23-.11,.36-.13,6.08,.47,12.18,2.35,18.14,2.77,.45-.52-.05-.96-.38-1.39-1.73-2.05-3.46-4.11-5.23-6.14-.53-1-8.37-8.49-6.35-8.M 45,7.17,.5,14.03,2.93,21.02,4.22,1.3-.32-4.26-5.81-4.8-6.75-2.21-2.58-4.47-5.12-6.7-7.69-.45-.52-1.03-1.01-1.09-1.7,.59-.38,1.21-.18,1.84-.02,6.7,1.61,13.42,3.18,19.94,5.24,.99,.31,2.04,.51,3.07,.75,.1,.02,.26-.07,.35-.14,.06-.05,.1-.18,.06-.24-.3-.48-.59-.97-.95-1.41-2.12-2.62-4.27-5.23-6.41-7.84-.56-.87-1.89-1.67-1.83-2.75,.19-.4,.68-.18,1.05-.08,5.89,1.54,11.66,3.34,17.37,5.26,3.35,1.12,6.68,2.28,10.04,3.4,.21,.07,.56,.03,.74-.07,.13-.07,.2-.39,.11-.52-2.76-4.12-6.14-7.81-8.94-11.9,.74-.38,1.25-.18,1.95,.07,6.58M ,2.21,13.14,4.46,19.54,6.98,3.99,1.57,7.98,3.11,11.99,4.65,.18,.07,.55,0,.7-.11,.14-.11,.21-.41,.12-.55-.79-1.25-1.6-2.49-2.45-3.71-1.65-2.79-4.45-5.6-5.53-8.54,.13-.25,.37-.32,.67-.21,4.83,1.91,9.72,3.72,14.46,5.74,8.13,3.34,16.1,7.05,24.08,10.55,.16-.19,.44-.39,.4-.5-.24-.61-.51-1.22-.85-1.8-1.95-3.31-3.93-6.61-5.89-9.92-.29-.48-.51-.99-.73-1.5-.03-.07,.02-.24,.09-.26,.23-.07,.54-.19,.7-.12,2.27,.94,4.54,1.88,6.76,2.89,13.07,5.7,25.6,12.59,38.31,18.53,.14-.15,.36-.39,.3-.51-1.69-3.51-3.43-7.01-5.13-10.53-.58-1.2-M 1.09-2.42-1.62-3.63-.02-.16,.32-.4,.5-.34,6.57,2.78,12.76,6.44,19.13,9.63,10.46,5.52,20.7,11.28,30.85,17.16,.87,.5,1.76,.99,2.67,1.45,.14,.07,.44-.03,.64-.1,.37-.41-.26-1.35-.32-1.85-1.65-4.32-3.31-8.64-4.95-12.97-.15-.39-.26-.81,.22-1.15,21.22,11,41.16,24.15,61.3,36.87,.58,.13,1.33,.43,1.23-.44-.36-1.48-.77-2.95-1.15-4.42-1.01-3.9-2.03-7.8-3.02-11.7-.03-.27,.19-.78,.58-.65,24.73,14.98,48.65,31.67,72.16,48.28,.13,.04,.56-.12,.62-.29,.06-.21,.12-.42,.09-.63-.58-4.17-1.19-8.34-1.76-12.52,.06-1.17-1.63-6.89,.75-5.24,2M 8.99,19.99,57.33,40.95,84.58,63.1,.27,6.42,.04,12.89,.11,19.32-.08,.63,.22,1.35-.38,1.82-.74,.39-2.05-1.14-2.76-1.63-17.1-14.28-34.28-28.34-52.11-41.97-8.36-6.41-16.88-12.69-25.34-19.03-.71-.44-1.39-1.22-2.32-1.03-.3,.24-.2,.84-.2,1.2,.58,5.78,2.1,11.53,2.17,17.33,0,.09-.44,.23-.64,.21-1.13-.44-2.05-1.41-3.05-2.08-21.46-16.46-43.8-32.64-66.66-47.47-1.02-.26-.52,1.3-.5,1.83,1.14,4.43,2.32,8.85,3.49,13.27,.24,.73,.41,1.45,.11,2.19-.95-.03-1.64-.49-2.35-1.05-18.89-12.67-38.08-26.52-58.21-37.2-.16,.1-.24,.39-.19,.57,1.M 5,4.48,3.27,8.88,4.86,13.33,.23,.62,.35,1.26,.51,1.89,.02,.41-.57,.37-.83,.33-16.62-10.2-33.45-20.74-50.96-29.6-.2-.09-.57,.09-.55,.29,2.01,4.82,4.44,9.47,6.6,14.22,.07,.22-.02,.76-.36,.73-13.81-7.06-27.12-14.94-41.22-21.56-1.16-.5-2.26-1.37-3.6-1.11,0,0,.18-.14,.18-.14l-.06,.1c.06,.31,.04,.66,.2,.94,2.5,4.36,5.03,8.71,7.55,13.07l.08-.02c-1.63,.7-3.16-.9-4.64-1.42-11.24-5.28-22.43-11.55-34.26-15.55-.37,0-.35,.41,.12,1.14,1.85,2.87,3.72,5.74,5.61,8.59,1.9,2.95,2.26,3.8,1.78,3.78-1.68-.07-2.88-1.01-4.26-1.6-8.52-3.69M -17.06-7.36-25.85-10.63-4.52-1.83-2.81-.03-1.06,2.58,2.17,3.22,4.81,6.18,6.69,9.57,0,.15-.38,.37-.53,.33-.74-.24-1.5-.46-2.21-.75-7.95-3.16-16.08-6.09-24.32-8.69-.48-.11-1.06-.46-1.48-.1-.45,.38,.03,.78,.3,1.12,.94,1.18,1.9,2.35,2.82,3.54,2.76,3.57,5.5,7.15,8.26,10.73,.35,.46,.76,.9,.51,1.48l.08-.06c-.69,.19-1.31,0-1.94-.2-4.23-1.36-8.45-2.75-12.69-4.07-3-.93-6.04-1.78-9.08-2.63-.3-.08-.71,.08-1.09,.14,3.75,5.79,8.86,10.71,12.66,16.49,.19,.39-.51,.47-.72,.45-5.58-1.54-11.15-3.09-16.74-4.59-1.14-.31-2.31-.55-3.48-.7M 9-.19-.04-.46,.13-.66,.24,.09,.79,1.42,1.99,1.9,2.77,3.39,4.25,6.79,8.5,10.18,12.75,.36,.45,.76,.89,.56,1.48l.09-.06Z"/><path class="cls-2" d="M1112.89,621.47c1.23-1.22-.36-2.66-.81-3.9-1.66-3.18-3.32-6.36-4.97-9.54-.2-.39-.28-.82-.38-1.24-.02-.08,.1-.2,.19-.27,17.96,6.57,35.43,15.51,52.52,23.84,1.26,.5,5.02,3.09,3.58-.21-1.59-4-3.2-8-4.79-12-.17-.68-.79-1.54-.08-2.06,21.77,9.52,42.49,21.43,63.27,32.88,.54,.17,2.51,1.56,2.64,.65-.6-4.94-2.56-9.67-3.69-14.51-.17-.62-.19-1.27-.26-1.91-.01-.09,.07-.26,.16-.28,.24-.05,M .56-.14,.73-.05,17.32,9.19,34.26,19.12,50.86,29.22,7.48,4.59,14.86,9.28,22.3,13.92,.95,.59,1.93,1.17,2.93,1.71,.11,.06,.62-.1,.65-.21,.01-5.97-1.55-11.99-2.12-17.97,.32-1.34,2.03,.13,2.73,.46,30.37,18.65,60.17,38.16,88.9,59.04,.34,6.57,.07,13.15,.17,19.73,0,.43-.06,.86-.12,1.28-.01,.08-.16,.18-.26,.2-.24,.03-.53,.09-.73,.01-8.98-6.24-17.53-13.1-26.47-19.45-18.59-13.43-37.46-26.38-56.69-38.98-1.24-.82-2.57-1.54-3.89-2.28-.09-.05-.58,.17-.58,.26,.17,5.71,1.5,11.34,2.16,17.01,.29,2.31-1.01,1.47-2.3,.65-23.15-15.76-46.M 6-30.69-70.96-44.92-.75-.3-2.03-1.55-2.44-.43,.59,2.43,1.21,4.85,1.85,7.27,.81,3.05,1.65,6.1,2.44,9.16-.41,1.4-2.57-.67-3.38-.98-19.39-11.69-38.88-22.91-59.05-33.39-.67-.3-1.33-.88-2.11-.55-.1,.03-.22,.19-.2,.26,.27,.83,.54,1.67,.86,2.49,1.62,4.22,3.25,8.43,4.87,12.65,.03,.08-.03,.24-.11,.27-.22,.08-.52,.2-.69,.14-2.36-.98-4.5-2.35-6.76-3.52-15.43-8.25-31.18-16.28-47.37-23.46-.18,.25-.44,.44-.39,.58,.24,.72,.51,1.44,.86,2.14,1.65,3.3,3.34,6.58,5,9.88,.3,.6,.54,1.21,.79,1.83,.03,.08-.02,.25-.1,.27-.97,.42-1.9-.52-2.M 8-.81-14.24-6.71-28.65-13.46-43.58-19.03-.16-.05-.45,.12-.65,.23-.14,.53,.63,1.51,.87,2.07,1.95,3.19,3.93,6.37,5.88,9.57,.29,.48,.45,1,.64,1.51,.02,.05-.19,.23-.26,.22-4-.99-7.65-3.11-11.53-4.52-8.28-3.37-16.7-6.51-25.22-9.48-1.07-.23-2.22-1.14-3.32-.8-.15,.1-.27,.4-.19,.53,2.25,3.59,4.92,6.92,7.37,10.39,.21,.49,1.44,1.71,.39,1.84-10.84-3.45-21.42-7.6-32.48-10.63-.61-.09-1.31-.53-1.89-.22-.2,.11-.27,.36-.14,.54,3.18,3.66,6.02,7.84,9.4,11.23l-.06-.06c-1.37,.95-3.09-.17-4.53-.45-7.92-2.41-15.92-4.65-24.03-6.62-.61-.0M 6-1.35-.44-1.92-.12-.07,.06-.15,.18-.12,.24,.22,.38,.43,.79,.73,1.13,2.92,3.48,6.16,6.72,8.84,10.38-.63,.26-1.14,.18-1.67,.04-6.38-1.71-12.89-3.07-19.38-4.49-1.68-.28-3.35-.97-5.06-.76-.03,.64,.42,1.05,.82,1.47,3,3.31,6.27,6.41,9.08,9.88,.24,.36-.39,.56-.61,.56-6.98-1.07-13.89-2.9-20.96-3.14-1.18,.14,.93,1.87,1.2,2.32,3.55,3.79,7.11,7.57,10.67,11.36,.27,.41,1,.91,.86,1.4-.16,.13-.39,.32-.56,.3-1.73-.2-3.46-.4-5.17-.69-4.09-.69-8.24-1.07-12.38-1.47-.89-.16-1.47,.53-.69,1.19,3.38,3.62,6.76,7.25,10.13,10.88,.87,1.15,2M .38,2.04,2.59,3.51-5.18-.03-10.46-.99-15.71-1.04-.88-.15-1.43,.58-.66,1.23,3.92,4.23,7.81,8.5,11.66,12.78,1.06,1.21,1.56,2.07-.6,1.88-4.7-.43-9.4-.44-14.12-.25l-.24-.15c-3.7-4.24-7.74-8.28-11.82-12.29-.49-.67-3.01-2.24-1.32-2.79,4.01-.47,8.06-.35,12.09-.51,.61-.05,2.38,.16,2.03-.87-3.94-4.42-8.39-8.4-12.52-12.65-.21-.22-.64-.91-.32-1.12,.38-.1,.77-.23,1.16-.24,4.58-.07,9.16-.1,13.73,.15,1.61,.24,2.22-.6,.81-1.62-3.93-3.98-7.92-7.93-12.01-11.76-2.43-2.23,3.65-1.05,4.64-1.14,4.16,.3,8.34,.36,12.47,.89,2.79,.22,.69-1.M 45-.21-2.43-2.8-2.75-5.63-5.49-8.42-8.25-.55-1.12,1.25-.73,1.88-.71,5.73,.66,11.47,1.27,17.13,2.25,.51,0,3.54,.57,3.15-.29-2.69-3.56-6.25-6.44-9.28-9.72-.91-1.24,1.16-.93,1.94-.82,7.79,1.14,15.49,2.74,23.19,4.31,.24,.05,.62,.04,.76-.08,.31-.26,.04-.57-.15-.81-2.6-3.04-5.43-5.9-8.11-8.86-2.32-2.37,.4-1.65,1.99-1.39,7.44,1.49,14.78,3.28,22.05,5.24,.99,.07,6.22,2.16,5.24,.35-2.47-3.23-5.18-6.29-7.74-9.46-.36-.44-.88-.83-.83-1.41,.48-.33,1.02-.24,1.51-.12,1.93,.48,3.84,.99,5.76,1.5,8.29,2.23,16.49,4.67,24.59,7.31,1.36,M .38,2.45,1.06,3.93,.65-2.36-3.64-5.07-6.88-7.6-10.37-.26-.48-1.03-1.25-.81-1.72,.48-.42,1.65,.16,2.25,.24,12.56,3.89,24.94,8.11,37.06,12.79,4.41,1.91,1.02-2.11,.12-3.75-1.83-2.87-3.81-5.66-5.41-8.66-.19-.38,.51-.48,.71-.48,16.01,5.67,31.95,11.67,47.06,19.1,.06-.07,.11-.13,.17-.19l-.22,.18Z"/><path class="cls-2" d="M372.08,814.2c.25,.1,.49,.2,.74,.3-.73,3.5-1.33,6.99-1.82,10.48-.79-.15-1.86-1.05-2.58-.68-.66,.47,0,.98,.23,1.43,.54,1.02,1.26,1.98,1.88,2.96-.28,2.38-.5,4.76-.66,7.13-12.94-4.72-25.82-9.87-38.35-15.42-1M .06-.47-2.14-.91-3.23-1.33-.17-.06-.47,.08-.68,.17-.08,.03-.14,.19-.11,.26,.32,.71,.64,1.42,1,2.11,1.92,3.79,3.87,7.57,5.78,11.36,.07,.14-.14,.38-.26,.55-19.02-6.89-37.22-16.51-55.38-25.11-.16-.06-.46,.06-.67,.15-.31,.32,.08,1.13,.19,1.53,1.64,4.1,3.31,8.2,4.96,12.29,.1,.44,.52,1.22,.18,1.54-.21,.08-.47,.18-.67,.14-1.48-.45-2.82-1.24-4.23-1.88-19.69-9.52-38.77-19.66-57.71-30.38-1.36-.6-4.25-2.87-3.32,.43,1.16,4.2,2.35,8.4,3.52,12.61,.08,.83,.84,2.11,.09,2.72-17.63-8.61-34.76-19.33-51.62-29.32-7.48-4.59-14.88-9.27-2M 2.33-13.9-1.11-.51-2.09-1.76-3.39-1.44-.31,2.06,.39,4.06,.64,6.09,.38,4.14,1.54,8.32,1.57,12.45-.69,.21-1.16-.01-1.59-.27-16.39-9.89-32.57-20.24-48.43-30.75-13.25-8.83-26.36-17.8-39.19-27.02-.94-.79-2.52-1.38-2.6-2.74-.11-6.25-.02-12.49-.05-18.74-.11-2.93,2.11-.85,3.32,.01,27.45,20.61,55.51,40.46,84.63,59.1,.95,.58,1.24-.78,1-1.46-.74-5.57-1.53-11.13-2.3-16.7-.02-.19,.14-.56,.2-.56,20.31,12.22,40.11,26.47,61.08,38.54,3.98,2.4,8.01,4.75,12.02,7.11,.64,.38,1.23,.86,2.12,.79,.29-.53,.12-1.05-.02-1.58-1.17-4.2-2.34-8.4M 1-3.48-12.61-.26-.94-.43-1.9-.62-2.85-.02-.09,.09-.22,.18-.28,.81-.11,1.67,.65,2.41,.95,7.15,4.23,14.24,8.52,21.44,12.7,12.44,7.2,25.11,14.15,37.99,20.84,.78,.3,1.56,1.1,2.42,.66,.31-.49-.38-1.56-.49-2.15-1.61-4.11-3.23-8.21-4.85-12.32-.16-.4-.45-.8-.14-1.27,1.29-.11,2.79,1.18,4.01,1.67,16.55,8.72,33.46,17.95,50.84,25.01,.78-.12-.24-1.58-.41-2.05-1.74-3.39-3.48-6.78-5.2-10.17-.35-.69-.59-1.42-.86-2.14-.03-.06,.11-.19,.21-.26,.82-.15,1.69,.56,2.47,.81,14.4,6.7,28.98,13.67,44,19.07,1.04-.09-.04-1.35-.24-1.86-9.86-15.M 96-9.39-12.75,6.36-6.72Z"/><path class="cls-2" d="M375.64,837.54s.05-.01,.08-.02l-.08,.06v-.04Z"/><path class="cls-2" d="M428.06,823.4c.06-.03,.12-.05,.18-.06,0,.06-.07,.09-.2,.1,.01-.01,.01-.03,.02-.04Z"/><path class="cls-2" d="M488.14,758.72h-.04l-.06-.06,.1,.06Z"/><path class="cls-2" d="M501.09,773.81c-4.41,.45-8.87,.39-13.3,.57-1.49,.37,.74,1.95,1.14,2.56,3.78,3.78,7.57,7.56,11.36,11.34,.45,.7-.56,.9-1.07,.91-3.9,.03-7.81,.19-11.7-.05-3.37-.12-3.87-.08-3.78,.34,.22,1.01,1.18,1.63,1.92,2.36,3.47,3.43,6.99,6.83,1M 0.48,10.25,1.55,1.47,.8,1.78-.97,1.66-4.82-.42-9.69-.35-14.49-.98-.77-.06-3.76-.51-2.48,.99,3.19,3.2,6.5,6.32,9.71,9.5,.15,.14,.2,.43,.12,.6-.14,.19-.69,.35-.99,.28-5.74-.59-11.47-1.25-17.15-2.15-1.18-.19-2.39-.24-3.59-.34-.5-.06-.52,.53-.42,.68,2.81,3.54,6.8,6.5,9.37,10.02-.14,.15-.32,.38-.5,.39-2.53-.03-5.06-.6-7.55-.98-5.5-1.04-10.99-2.12-16.47-3.2-.51-.1-1.01-.34-1.5,.02,1.94,3.38,5.29,5.91,7.78,8.96,.55,.6,1.04,1.24,1.53,1.87,.06,.07,.02,.23-.05,.31-.93,.31-2.13-.15-3.11-.23-7.45-1.48-14.79-3.25-22.05-5.21-1.6M 7-.3-3.39-1.23-5.09-.94,0-.03-.02-.07-.07-.12-.03,.06-.07,.12-.11,.18-.04,.01-.08,.03-.12,.05,.04,0,.07,0,.1,0,2.64,3.86,6,7.38,8.85,11.13,.06,.08,.03,.24-.04,.32-.71,.33-1.9-.12-2.68-.22-7.33-1.91-14.61-3.94-21.8-6.14,.52-3.25,1.18-6.53,1.96-9.74,3.13,1,6.28,1.95,9.44,2.89,.71,.11,1.62,.59,2.29,.33,.08-.17,.21-.42,.12-.54-2.87-3.88-6.37-7.37-8.97-11.42,.58-.36,1.1-.27,1.61-.12,4.56,1.33,9.09,2.71,13.67,3.98,4.32,1.2,8.69,2.3,13.04,3.43,.47,.05,1.11,.25,1.55-.03,.06-.06,.1-.19,.06-.26-.39-.56-.75-1.13-1.21-1.66-2.4M 6-2.83-4.94-5.65-7.41-8.47-.37-.42-.83-.82-.75-1.44,.39,0,.81-.08,1.16,.01,8.05,1.88,16.32,4.25,24.47,5.27,.09-.17,.23-.41,.14-.53-3.08-3.72-6.71-6.97-9.76-10.7-.11-.13-.04-.38,.01-.56,.01-.05,.24-.11,.36-.1,7.09,.9,14.17,3.12,21.37,3.11,.28-.99-.86-1.51-1.37-2.23-3.56-3.79-7.13-7.57-10.69-11.36-1.71-1.84-.91-1.93,1.11-1.62,5.54,.71,11.13,1.9,16.75,1.82,.84-.43-.17-1.11-.5-1.57-4-4.47-8.41-8.62-12.17-13.28-.11-.27-.01-.76,.41-.7,5.36,.32,10.69,1.41,16.06,1.07,.89-.52-.66-1.57-.99-2.13-3.81-4.44-8.23-8.44-11.69-13.1M 4,0-.16,.46-.63,.76-.53,4.95,.51,9.93,.34,14.9,.41,4.37,4.75,8.93,9.38,13.6,13.94,.52,.5,.22,1.04-.61,1.15Z"/><path class="cls-2" d="M376.29,794.07c.64,.27,1.33,.48,1.87,.86h0c-1.08,3.14-2.05,6.31-2.93,9.53-7.65-3.25-15.22-6.66-22.81-10.01-.8-.35-1.7-.61-2.19-1.3-.02-.01-.02-.02-.03-.03-.07,.07-.13,.14-.19,.2,.08-.06,.14-.11,.22-.17-1.26,1.34,.7,2.84,1.21,4.13,1.83,3.23,3.9,6.37,5.62,9.66,.06,.17-.02,.46-.17,.57-15.65-5.67-30.38-14.18-45.4-21.42-.72,.57-.22,1.11,.03,1.78,1.82,3.71,3.67,7.41,5.48,11.12,.29,.59,.48,1M .22,.68,1.84,.03,.06-.11,.2-.22,.25-10.62-4.16-20.74-10.46-30.86-15.73-7.34-3.99-14.45-8.35-21.85-12.2-.37-.19-.68,.23-.69,.52,1.43,4.85,3.6,9.47,5.3,14.22,.08,.39,.38,.94,0,1.21-14.18-6.81-27.62-15.78-41.09-23.82-6.49-4.04-12.89-8.16-19.33-12.25-.63-.33-1.23-.97-2.01-.71-.08,.02-.18,.2-.16,.28,.62,2.43,1.26,4.85,1.88,7.27,.81,3.16,1.89,6.27,2.34,9.48,.01,.08-.11,.2-.22,.25-.1,.05-.3,.1-.38,.06-.89-.48-1.79-.95-2.63-1.48-18.02-11.23-35.53-22.97-52.89-35.08-5.44-3.68-10.6-7.72-16.08-11.31-.19-.09-.51-.03-.75,.01-.08M ,.01-.16,.18-.16,.27,.23,5.18,1.26,10.29,1.91,15.42,.44,2.67,.43,3.05-.03,3-1.31-.12-2.05-.96-2.94-1.57-27.55-19.04-54.59-39.14-80.52-59.86-2.72-2.16-2.35-1.7-2.37-4.48,.06-6.13-.27-12.3,.05-18.41,.99-.43,1.79,.66,2.55,1.14,22.34,18.63,44.81,36.77,68.33,54.15,3.16,2.35,6.31,4.71,9.48,7.05,.57,.31,2.43,2.02,2.77,.86-.3-5.93-1.5-11.77-2.26-17.65-.06-1.94,2.33,.24,2.95,.68,21.82,16.44,44.36,33.52,67.7,47.88,.61-.34,.26-1.22,.17-1.77-.9-3.37-1.82-6.73-2.72-10.1-.36-1.78-1.29-3.55-.93-5.37,.77-.14,1.25,.27,1.75,.62,3.89M ,2.66,7.77,5.33,11.68,7.98,15.32,10,30.66,20.88,46.92,29.51,.1-.05,.23-.18,.21-.26-.12-.63-.19-1.27-.42-1.88-1.32-3.62-2.69-7.22-4.04-10.83-.34-.93-.68-1.86-.98-2.8,.02-.23,.36-.66,.72-.47,16.6,10.08,33.31,20.49,50.68,29.41,.15,.06,.45-.05,.65-.12,.4-.32-.18-1.09-.27-1.51-1.81-3.83-3.64-7.65-5.44-11.48-.23-.49-.37-1.02-.52-1.54-.03-.08,.08-.21,.18-.28,.06-.05,.24-.09,.3-.06,.93,.43,1.87,.84,2.75,1.33,13.51,7.51,27.25,14.99,41.35,21.45,.14-.28,.38-.51,.31-.64-.44-.9-.92-1.79-1.42-2.67-1.98-3.53-3.98-7.06-5.95-10.6-.M 07-.14,.11-.38,.23-.55,11.84,5.04,23.42,11.49,35.59,16.42Z"/><path class="cls-2" d="M372.97,781.77c2.91,1.24,5.82,2.5,8.73,3.75-1.1,2.66-2.13,5.35-3.08,8.09-2.35-4.04-5.29-7.75-7.53-11.87-.03-.07,.02-.25,.09-.27,.64-.3,1.22,.05,1.79,.3Z"/><path class="cls-2" d="M459.8,724.44s0-.01-.01-.02l.04,.02h-.03Z"/><path class="cls-2" d="M470.48,757.97c-5.48-.15-10.85-1.52-16.28-1.95-.24-.02-.52,.22-.41,.45,3.97,5.43,8.84,10.2,12.96,15.54,.08,.18-.17,.48-.38,.47-5.57-.46-11.13-1.48-16.57-2.64-.39-.04-2.28-.39-1.95,.37,3.06,4.M 5,7.11,8.32,10.55,12.56,.69,.79,1.34,1.61,1.99,2.42,.19,.3-.35,.64-.56,.66-6.61-.73-13.09-2.47-19.49-4.06-1.72-.53-1.96-.09-.88,1.34,2.41,2.85,4.85,5.69,7.27,8.53,1.59,1.87,3.19,3.74,4.75,5.62,.32,.49-.3,.81-.75,.68-7.91-1.76-15.66-3.78-23.37-6.13-.63-.18-1.37,.25-.7,.87,2.03,2.54,4.08,5.06,6.13,7.59,.95,1.17,1.92,2.33,2.87,3.51,.19,.23,.13,.42-.13,.51-5.04-.85-10.07-2.74-15-4.24h0c3.14-7.34,6.95-14.24,11.39-20.65,1.79,.32,3.3,1.41,5.15,.9-1.1-1.4-2.01-2.57-3.05-3.86,2.19-3,4.53-5.87,6.99-8.63,4.66,1.02,6.53,2.29,2M .43-2.65,5.99-6.33,12.65-12.02,19.87-16.88,2.39,3.01,4.99,5.89,7.27,8.98,.1,.14-.04,.38-.1,.69Z"/><path class="cls-2" d="M266.44,990.81v-.15s.09,.02,.13,.03l-.13,.12Z"/><path class="cls-2" d="M410.43,983.7s-.03-.07-.05-.11c.05,0,.09,.01,.14,.01l-.09,.1Z"/><path class="cls-2" d="M404.64,969.96c1.52,4.65,3.91,9.07,5.74,13.63-22.77-1.96-45.35-5.54-67.85-9.39-.9-.04-.8,.95-.64,1.54,1.32,4.28,2.8,8.51,3.81,12.88,.11,.43,.03,.85-.5,1.25-26.4-4-52.51-9.83-78.38-16.23-.63-.1-1.72-.5-2.11,.16,.15,1.28,.31,2.56,.55,3.83,.95,M 4.31,1.34,8.64,1.18,13.03-32.14-7.51-63.69-16.32-94.88-26.23-1.31-.38-1.37,.87-1.3,1.75-.03,5.46,.62,11.06-.15,16.45-1.09,.8-2.92-.3-4.06-.55-37.24-11.24-73.9-24.11-110.08-38.08-.74-.32-1.24-.77-1.23-1.53,.03-1.72-.01-3.45-.02-5.17,.07-5.05-.18-10.11,.11-15.15,.94-.44,1.81,.16,2.68,.44,35.81,14.47,71.63,28.14,108.55,40.05,1.04,.13,3.77,1.85,3.97,.1-.61-5.91-1.28-11.81-1.9-17.7-.05-.42,.61-.82,1.07-.68,30.47,10.4,61.22,19.93,92.54,27.96,.66,.21,2.21,.6,2.23-.41-.33-1.7-.66-3.4-1.03-5.09-.06-1.53-3.45-11.74-1.51-11.4M 6,25.09,6.65,50.32,12.95,75.9,17.83,.91,.18,1.85,.29,2.78,.42,1.07,.01,.62-1.23,.47-1.87-1.43-4.26-2.88-8.52-4.32-12.78-.21-.61,.34-1.09,1.06-.97,21.34,4.26,42.8,8.17,64.43,10.75,1.67,.16,2.04-.14,1.52-1.34-1.73-4.21-4-8.19-5.48-12.5,.51-.08,.91-.24,1.27-.19,4.4,.55,8.8,1.15,13.21,1.71,4.93,5.35,10.2,10.35,15.84,15.01-7.35-.52-14.64-1.47-21.97-2.11-.52-.07-1.51-.04-1.5,.64Z"/><path class="cls-2" d="M497.08,948.76h-.05s-.03-.04-.04-.06l.09,.06Z"/><path class="cls-2" d="M503.6,958.13c.49,.71,.89,1.47,1.32,2.2-3.98,.1M 5-7.97,.39-11.95,.47-9.38-3.11-18.14-7.3-26.19-12.41,10.07,.48,20.18,.46,30.25,.37,2.19,3.12,4.39,6.24,6.57,9.37Z"/><path class="cls-2" d="M505.13,960.32l-.16,.1s-.04-.06-.05-.09c.07,0,.14-.01,.21-.01Z"/><path class="cls-2" d="M1192.65,222.76c-18.63,.68-37.07,1.81-55.69,3.23-.13-1.59,1.21-2.37,1.98-3.58,3.41-4.39,6.83-8.78,10.23-13.18,.42-.55,.79-1.12,1.17-1.69,.14-.2-.35-.68-.67-.66-14.87,1.1-29.68,2.83-44.52,4.35-.67,.07-1.33,.2-1.99,.26-.74,.06-1.74,.54-2.16-.1-.39-.6,.49-1.16,.95-1.67,4.63-5.16,9.29-10.31,13.93M -15.48,.34-.56,2.1-1.97,1.18-2.36-14.92,1.03-29.73,4.04-44.61,5.64-.21-1.1,1.07-1.74,1.67-2.54,5.29-5.31,10.6-10.61,15.89-15.91,.64-.85,2.18-1.67,1.95-2.79-12.6,1.28-25.18,3.51-37.65,5.66-5.12,.95-3.25-.36-.68-2.87,6.27-5.92,12.56-11.82,18.83-17.74,.61-.57,1.16-1.18,1.72-1.79,.07-.07,.07-.25,0-.31-.15-.13-.39-.32-.55-.3-2.91,.43-5.82,.87-8.72,1.34-8.44,1.39-16.87,2.8-25.31,4.18-1.04,.17-2.1,.44-3.18,.13l.08,.08c0-.2-.12-.47,0-.6,.65-.68,1.34-1.35,2.06-1.99,7.95-7.04,15.9-14.07,23.85-21.1,.63-.52,1.28-.97,1.34-1.83-M 11.34,1.1-22.76,3.34-34.07,5.03-1.55,.09-.59-.77,0-1.42,10.19-8.92,20.68-17.54,30.83-26.5,.76-1.36-2.35-.63-3.02-.65-6.91,.92-13.81,1.87-20.71,2.8-2.39,.32-4.78,.62-7.18,.9-.2,.02-.55-.11-.61-.24-.06-.92,1.47-1.59,2.04-2.25,10.58-8.76,21.16-17.51,31.74-26.27,3.65-2.97,5.33-3.99-.91-3.36-8.03,.68-16.07,1.37-24.11,1.98-.47,.03-.49-.52-.37-.7,4.02-3.52,8.29-6.77,12.42-10.17,9.79-7.86,19.6-15.72,29.4-23.58,2.63-2.11,2.11-1.87,5.62-1.87,7.75-.01,15.42,0,23.19,0,0,.4,.15,.79-.03,.96-.77,.74-1.63,1.43-2.48,2.12-11.37,9.19M -22.75,18.38-34.12,27.58-.94,.76-1.82,1.58-2.69,2.4-.07,.06,.13,.4,.3,.5,9.45-.07,19.03-1.5,28.52-1.75,.02,.22,.15,.49,.03,.62-.57,.6-1.17,1.18-1.82,1.72-9.14,7.62-18.3,15.23-27.44,22.85-1.68,1.4-3.32,2.82-4.95,4.26-.13,.12-.08,.4-.06,.59,.54,.26,1.35,.07,1.96,.07,6.26-.74,12.51-1.53,18.78-2.24,3.47-.39,6.95-.67,10.43-.98,.2-.02,.54,.11,.63,.25,.22,.84-1.13,1.46-1.61,2.06-3.83,3.33-7.67,6.66-11.49,9.99-5.01,4.37-10.01,8.74-15.01,13.11-.81,.56-1.27,1.54,.16,1.4,11.4-1.24,22.82-3.79,34.23-4.22,.5,.5-.93,1.43-1.29,1.8M 5-5.96,5.42-11.93,10.84-17.87,16.27-1.86,1.7-3.66,3.45-5.46,5.19-.12,.12-.04,.39,.01,.58,.01,.06,.23,.1,.36,.11,10.38-.97,20.72-2.75,31.09-4.01,2.29-.17,4.84-1.05,7.06-.5,.07,.09,.14,.25,.09,.31-.46,.53-.92,1.06-1.43,1.56-5.77,5.69-11.56,11.37-17.33,17.06-.76,.75-1.5,1.52-2.2,2.31-.12,.13-.02,.4-.02,.64,9.74-.57,19.38-2.67,29.12-3.53,4.27-.46,8.54-.91,12.82-1.34,.17-.02,.4,.18,.55,.31,.06,.06,.05,.23-.01,.31-.51,.63-1,1.27-1.56,1.88-4.65,5.02-9.31,10.03-13.96,15.06-.72,.77-1.36,1.59-1.99,2.41-.06,.08,.2,.47,.31,.47M ,8.31-.17,16.53-1.84,24.83-2.38,6.96-.63,13.92-1.24,20.89-1.86,.56-.05,1,.13,.95,.37-.19,1.24-1.38,2.07-2.06,3.08-3.71,4.62-7.42,9.25-11.12,13.88-.72,1.03-2.31,2.58,.14,2.4,16.89-1.22,33.83-2.68,50.76-2.94,.54,.25,.21,1-.08,1.39-3.81,5.94-7.63,11.88-11.44,17.81l.1-.06Z"/><path class="cls-2" d="M1093.82,419.36c26.96,2.92,53.78,7.54,80.34,12.8,1.05,.06,1.15-.95,1.41-1.68,1.1-4.1,2.18-8.21,3.28-12.32,.41-1.51,.84-1.71,2.84-1.35,1.31,.23,2.62,.48,3.93,.74,29.5,5.66,58.59,12.67,87.56,20.46,.34,.08,.92-.15,.98-.39,.25-1.M 05,.55-2.1,.72-3.17,.66-4.17,1.27-8.34,1.92-12.5,.21-.66,.22-1.8,1.11-1.89,36.82,9.24,73.52,19.99,109.19,32.58,.42,6.58,.04,13.19,.15,19.79-.04,.73-.02,1.88-1.09,1.71-12.02-4.01-23.89-8.44-35.95-12.42-24.57-8.24-49.42-16.1-74.6-22.96-1.93-.46-1.55,2.12-1.96,3.28-.66,4.92-1.72,9.8-1.86,14.76l.13-.06c-30.73-8.71-61.71-17.02-93.09-23.57-2.6-.34-3.85-1.34-3.79,2.11-.07,4.41,.28,8.83-.09,13.23-.41,.82-1.75,.42-2.49,.33-3.12-.68-6.22-1.39-9.33-2.07-22.24-4.85-44.77-8.94-67.37-11.93-.87-.06-1.31,.62-1.22,1.33,.21,4.52,.13M ,9.05,.93,13.54l.12-.09c-20-2.58-40.03-5.45-60.18-6.86-2.27-.17-4.55-.22-6.83-.31-.49-.02-.98,.42-.97,.84-.03,4.46,1.57,8.74,3.16,12.89l.1-.09c-19.69-1.39-39.43-2.95-59.18-2.46-.27-4.03-2.12-7.93-2.34-11.96,.78-.57,1.62-.49,2.41-.52,18.16-.71,36.3,.11,54.44,.82,.52,.02,.99-.41,.93-.85-.25-4.28-1.65-8.55-1.07-12.83l-.13,.1c20.82,1.31,41.68,2.71,62.36,5.5,1.34-.1,6.07,1.47,6-.48-.11-4.72-.22-9.44-.33-14.15l-.13,.09Z"/><path class="cls-2" d="M138.69,233.83c.3-.5,.32-1.03,.29-1.58-.25-3.87-.51-7.74-.75-11.61-.36-5.91-.M 71-11.82-1.05-17.74-.24-3.14,1.52-1.37,3.05-.48,7.52,5.08,14.75,11.03,22.51,15.56,.26-.19,.61-.39,.55-.75-.37-12.24-1.26-24.55-1.11-36.77,.11-.44,.97-.37,1.34-.12,7.72,4.07,15.13,8.76,22.97,12.57,1.12,.11,.73-1.74,.87-2.47-.04-5.27-.14-10.55-.15-15.82,.07-8.38-.17-16.78,.16-25.15,1.09-.4,2.07,.23,3.1,.52,4.37,1.67,8.73,3.36,13.08,5.05,.85,.33,1.67,.71,2.52,1.03,5.07,1.93,6.02,2.2,6.25,1.78,.89-1.63,.48-3.38,.56-5.07,.44-14.84,.97-29.72,2.1-44.51,.05-.25,.55-.59,.87-.55,1.06,.13,2.13,.22,3.17,.42,7.14,1.47,14.38,2.6M ,21.46,4.31,.45,1.12,.19,2.14,.15,3.29-.45,6.34-.95,12.68-1.36,19.02-.99,11.01-.68,22.67-2.28,33.5h0c-.18-.27-.28-.67-.56-.78-2.29-.92-4.59-1.8-6.92-2.66-5.42-1.95-10.74-4.03-16.21-5.85-.94,.94-.66,2.25-.74,3.47-.21,14.53-.15,29.08-.38,43.61-.01,.25-.62,.56-.88,.44-.82-.37-1.66-.71-2.43-1.13-6.13-3.33-12.24-6.68-18.36-10.01-.77-.24-2.41-1.72-2.98-.63,.34,11.51,.46,23.04,1.16,34.54,.14,2.03,.06,4.08,.05,6.12,0,.1-.46,.33-.58,.29-8.07-4.81-15.41-10.88-23.39-15.85-1.33-.42-1.01,1.02-1.08,1.84,.23,3.98,.4,7.96,.71,11.9M 4,.47,7.1,.93,14.19,1.37,21.29,.02,.29-.18,.59-.32,.87-.03,.07-.3,.14-.36,.11-.53-.33-1.07-.65-1.53-1.03-5.65-4.62-11.27-9.26-16.93-13.88-2.07-1.69-3.96-3.52-6.32-4.98-.12-.07-.56,.03-.69,.15-.39,.95-.04,2.17-.07,3.2,.67,9.14,1.36,18.27,2.19,27.4-.11,2.2-2.12-.11-2.96-.83-7.97-7.3-15.89-14.65-23.84-21.96-.44-.61-1.61-.58-1.48,.35,.41,7.75,1.2,15.47,1.75,23.21,.08,1.07,.07,2.15,.1,3.22,0,.28-.16,.42-.49,.4-9.66-8.58-18.42-18.56-27.77-27.62-.63-.52-1.12-1.44-2.07-1.25-.07,0-.19,.14-.19,.22,0,.86-.01,1.72,.04,2.57,.33M ,6.88,.96,13.76,1.15,20.65-.28,1.05-1.56-.24-1.95-.65-9.92-10.61-19.83-21.22-29.74-31.84-.88-.88-1.84-1.88-1.74-3.17,0-2.48-.06-4.95-.08-7.43-.02-3.45-.02-6.89,0-10.34-.11-3.62,1.65-1.62,3.14-.14,9.35,9.17,18.37,18.67,27.9,27.65,.83,.57,1.09-.56,1.04-1.18-.1-2.48-.22-4.95-.33-7.43-.2-4.52-.4-9.04-.59-13.56,.03-.63-.15-1.41,.58-1.7,.07-.04,.27-.03,.34,.03,9.46,7.98,18.09,16.87,27.44,24.99,.11,.1,.47,.04,.7,.01,.32-.23,.25-.84,.28-1.2-.36-8.92-1.46-17.85-1.56-26.76,.96-.44,1.57,.42,2.29,.88,7.63,6.24,15.24,12.49,22.8M 6,18.73,.69,.48,1.3,1.28,2.24,1.14l.04,.13-.13-.06Z"/><path class="cls-2" d="M1203.01,1271.97c5.12,1.91,10.24,3.83,15.37,5.73,2.69,1,5.39,1.97,8.08,2.95,.92,.34,1.49,.02,1.51-.87,.38-14.54,.29-29.08,.32-43.63-.14-3.81,.66-2.85,3.38-1.57,6.35,3.45,12.69,6.91,19.03,10.38,.65,.31,1.27,1.04,2.1,.6,.74-.39,.38-1.18,.38-1.79-.05-6.14-.45-12.28-.63-18.41-.01-6.89-.7-13.78-.74-20.66,.05-.33,.74-.35,.93-.28,7.61,4.89,14.89,10.28,22.39,15.35,.39,.27,.75,.62,1.34,.58,.38,0,.53-.46,.54-.75-.25-4.63-.5-9.25-.79-13.88-.41-6.56-.M 85-13.12-1.27-19.69,.08-.57-.29-1.63,.54-1.7,.92,.14,1.67,1.05,2.44,1.54,5.18,4.24,10.34,8.49,15.51,12.74,2.26,1.85,4.52,3.69,6.81,5.52,.12,.1,.48,.03,.71,0,.15-.08,.25-.4,.25-.58-.22-3.55-.43-7.1-.67-10.65-.58-6.44-1.05-12.9-1.56-19.35-.08-1.84,1.07-1.02,1.94-.22,8.51,7.79,16.9,15.68,25.5,23.37,.13,.11,.5,.07,.76,.06,.1-.06,.22-.43,.19-.59-.61-7.96-1.32-15.91-1.94-23.86-.14-2.75-.61-4.83,2.37-1.76,9.28,8.95,17.93,18.94,27.55,27.35,.2-.11,.5-.27,.5-.4-.09-3.12-.21-6.24-.35-9.36-.2-4.52-.42-9.04-.6-13.56,0-.14,.31-.M 3,.5-.41,10.57,10.18,20.34,21.73,30.61,32.4,1.16,1.01,1.81,2.3,1.6,3.85,0,5.82,0,11.64,0,17.45,0,.52,.11,1.07-.33,1.53-.07,.07-.31,.15-.36,.11-.5-.34-1.04-.66-1.44-1.06-3.57-3.51-7.14-7.02-10.68-10.55-5.47-5.47-10.91-10.95-16.38-16.43-.69-.54-1.17-1.4-2.19-1.07,.11,7.85,.73,15.7,.98,23.55,.01,.25-.16,.4-.49,.43-1.71-.43-2.84-2.26-4.23-3.3-7.49-6.93-14.97-13.87-22.45-20.8-.6-.43-1.62-1.97-2.31-1.02,.09,9.14,1.32,18.27,1.5,27.42-.32,1.27-1.67,.03-2.22-.44-7.43-6.1-14.86-12.19-22.29-18.29-2.48-2.03-3.41-2.72-3.04,1.24M ,.44,9.81,1.89,19.93,1.42,29.61-.93,.26-1.61-.55-2.34-.96-7.27-5.15-14.51-10.32-21.82-15.4-.27-.19-.69-.25-1.05-.35-.1-.02-.33,.06-.34,.11-.1,.42-.22,.84-.21,1.27,.3,10.23,.74,20.46,1.09,30.69,.06,1.72,.03,3.44,.03,5.15,0,.24-.67,.53-.92,.42-.24-.1-.49-.18-.71-.3-7.01-3.81-13.94-7.74-20.91-11.62-3.25-1.94-2.59-.21-2.72,2.46,.07,13.38,.42,26.75-.04,40.12-2.37,.15-4.46-1.37-6.7-2.01-5.1-1.95-10.2-3.91-15.3-5.86-.9-.17-2.55-1.37-3.11-.22-1.19,16.54-.63,33.3-2.63,49.75-8.64-.64-17.03-3.36-25.61-4.56l.08,.08c.79-18.57,2M .79-37.09,3.24-55.69l-.14,.06Z"/><path class="cls-2" d="M670.91,824.59s-.03,.05-.04,.08l.09-.07s-.03-.01-.05-.01Zm21.26,37.4l-.03,.03s.07-.02,.09-.03h.01s-.05-.01-.07,0Zm104-67s.07,.01,.1,.02c.02-.05,.03-.1,.05-.15l-.15,.13Zm3.57,1.46c-1.11-.55-2.15-1.21-3.47-1.44-1.44,4.64-2.88,9.28-4.33,13.91-.26,.81-.95,1.05-1.79,.67-1.99-.9-3.96-1.82-5.95-2.71-.52-.23-1.34-.53-1.81-.09-2.28,4.51-3.23,9.6-5.49,14.12-.14,.27-.63,.39-1.01,.24-2.15-.91-4.29-1.78-6.47-2.63-1.61-.62-1.88-.51-2.52,.98-1.98,4.49-3.46,9.13-5.83,13.44-3.M 12-.91-5.84-2.33-8.99-3.12-2.88,4.29-4.71,9.19-7.18,13.73-.15,.31-.15,.6,.26,.81-3.67,.09-6.83-2.4-10.42-2.95-.01,.01-.02,.03-.02,.04-2.99,5.02-6.88,9.6-10.66,14.32-3.27-1.27-6.38-2.23-9.27-3.52,0-.88,.73-1.4,1.2-2.01,3-4.05,6.41-7.84,9.13-12.08-.02,0-.04-.01-.06-.02-3.27-.81-6.47-1.77-9.78-2.73,.33-1.85,1.53-3.28,2.28-4.83,1.52-3.05,3-6.12,4.37-9.24-2.6-.53-5.2-1.06-7.8-1.59-1.13-.21-2.99-.87-3.5,.43-2.03,4.04-3.94,8.24-6.26,12.12-.43,.06-.72,.17-.95,.13-3.25-.65-6.48-1.36-9.56-2.3-.05-.2-.13-.32-.09-.4,1.86-4.37,M 4.24-8.59,6.3-12.9-3.22-.69-6.46-1.39-9.68-2.1-1.77-.44-.51-2.01-.19-3.05,1.44-3.45,2.51-7.06,4.23-10.37-3.16-.55-6.33-1.1-9.49-1.65,3.04,9.7,5.17,19.74,6.32,30,.44,.11,.88,.22,1.31,.33,.48,1.1-.53,1.72-1.02,2.52,.4,4.22,.64,8.48,.69,12.77,2.02,.42,.85,1.39,.02,2.31,0,4.78-.22,9.6-.67,14.43,.17,.02,.39-.02,.58-.03,3.94-4.08,7.98-8.08,11.58-12.37,.19-.23,.61-.35,.95-.54,3.04,.97,6.1,1.8,8.89,2.94,.28,.53,.13,.92-.19,1.29-3.64,4.19-7.2,8.35-11.04,12.39,.26,.29,.42,.64,.73,.77,2.76,1.23,5.51,2.16,8.18,3.65-4.27,5.02-9M .62,9-14.2,13.67,1.74,1.42,5.26,3.34,8.63,4.74,.72-.12,1.08-.61,1.52-.99,4.6-4.09,8.91-8.35,12.84-12.8-.14-.53-.52-.81-1-1.04-2.25-1.15-4.68-2.09-6.81-3.44-.62-.69,.74-1.6,1.1-2.22,3.33-3.78,6.71-7.53,10-11.35,.48-.54,1.06-.7,1.73-.47,2.74,1.12,5.8,1.83,8.06,3.68-3.79,4.74-7.97,9.2-11.96,13.77-.32,.36-.21,.89,.24,1.14,2.34,1.27,4.68,2.54,7.01,3.81,.86,.56,1.61-.39,2.14-.95,3.98-4.54,7.87-9.04,11.86-13.58,2.97,1.17,5.26,3.05,8.15,4.41,4.1-4.8,7.36-10.26,11.2-15.27,2.19,.5,3.49,1.96,5.37,2.93,.86,.48,1.47,1.29,2.68,1M .32,.8-.49,1.06-1.23,1.43-1.9,2.12-3.96,4.24-7.92,6.34-11.88,.27-.5,.45-1.02,1.09-1.32,2.23,.56,3.79,2.38,5.75,3.48,1.74-5.84,3.63-11.61,5.66-17.29-1.17-.47-3.81-3.01-4.82-1.57-2.25,4.58-4.05,9.39-6.42,13.92-.24,.41-.91,.61-1.34,.37-2.01-1.08-4.01-2.17-6.01-3.27-.46-.25-.93-.41-1.64-.29-2.62,4.86-4.71,9.99-7.9,14.68-.39,0-.72,.08-.91-.01-2.41-1.18-4.8-2.38-7.19-3.58-.45-.23-.51-.62-.22-1.16,2.36-4.46,4.72-8.92,7.08-13.38,.22-.56,.93-.86,1.58-.61,2.58,.91,4.97,2.63,7.65,3.12,2.76-4.44,4.17-9.73,6.61-14.38,.13-.25,.7M 4-.47,1.01-.35,2.61,1.14,5.14,2.26,7.68,3.58,.72-.5,1-1.08,1.23-1.69,1.69-4.38,3.14-8.91,5.02-13.19,1.87-.13,3.07,1.34,4.68,2,2.06-5.02,4.23-9.95,6.48-14.78-.97-.52-1.94-1.04-2.93-1.53Zm-85.45,39.61c-3.01,4.09-6.27,8.02-9.38,12.04-.42,.53-1,.68-1.74,.45-2.87-.89-5.83-1.64-8.93-2.84,2.84-3.89,5.77-7.4,8.7-11.21,.6-.71,1.12-1.79,2.26-1.51,2.99,.62,5.96,1.29,8.83,2.23,.32,.11,.45,.53,.26,.84Zm38.34,13.2c-2.98,4.68-6.25,9.24-9.65,13.74-.38,.51-1.07,.64-1.72,.34-2.3-1.1-4.6-2.21-6.9-3.31-.42-.21-.52-.76-.22-1.15,1.53-2.M 01,3.11-4.01,4.58-6.05,2.3-2.75,3.57-6.27,6.44-8.46-.8,1.44,8.62,3.13,7.47,4.89Zm240.89,13.47l.13,.05v-.09s-.09,.03-.13,.04Zm7.28-62.69s.02,.03,.03,.05c.02,0,.05,0,.07,.01l-.1-.06Zm6.49,58.18s.01,.03,.01,.04l.1-.1s-.07,.04-.11,.06Zm3.83-31.36c-3.33-8.9-6.11-18.19-10.29-26.77-1.35-.23-13.39-2.43-12.91-.58,2.79,7.78,5.97,15.41,8.61,23.21,.4,1.13,.75,2.29,1.11,3.43,.12,.41-.18,.86-.69,1.05-3.86,1.23-7.44,3.16-11.18,4.45-.82,0-.95-.88-1.2-1.47-1.87-5.28-3.7-10.58-5.61-15.85-1.05-2.89-2.24-5.75-3.37-8.63-.49-.89-1.7-.33M -2.36,.08-2.88,1.78-5.73,3.57-8.6,5.36-.3,.19-.82,.06-.97-.25-3.16-6.97-5.76-14.16-9.09-21.05-.22-.48-.39-1.02-1.22-1.32-2.48,1.44-4.5,3.64-6.75,5.41-.84,.46-2.27,2.73-3.19,1.83-3.43-6.25-6.23-12.86-9.8-19.02-.76-.03-1.13,.25-1.44,.6-2.28,2.53-4.54,5.07-6.85,7.59-1.26,.75-1.65-1.33-2.27-2.06-2.77-4.65-5.19-9.53-8.2-14.03-1.03-.7-1.72,1.08-2.32,1.69-1.59,2.25-3.16,4.51-4.73,6.77-.27,.38-.6,.68-1.34,.7-2.72-4.14-5.42-8.39-8.12-12.56-.48-.57-1.07-2.14-2.01-1.44-1.89,2.65-3.22,5.69-4.91,8.48-.4,.54-.78,1.83-1.67,1.36-2M .89-3.28-5-7.16-7.73-10.58-.38-.56-.89-1.15-1.58-1.32-.49-.11-.69,.27-.82,.55-1.63,3.3-2.93,6.75-4.74,9.95-.98,.79-1.69-1.07-2.32-1.63-2.13-2.61-4.18-5.29-6.35-7.87-.53-.6-.95-.82-1.21-.61-.27,.22-.57,.46-.68,.74-1.15,2.98-2.26,5.98-3.39,8.96-.38,.62-.47,1.95-1.44,1.75-1.94,4.39-3.89,8.71-5.84,12.98,.45,.48,.67,.78,1.45,.71,6.55-16.33,2.73-14.54,13.45-1.69,.71-.18,1.01-.5,1.19-.93,1.16-2.75,2.32-5.5,3.5-8.25,.31-.71,.7-1.39,1.11-2.07,.05-.08,.6-.11,.7-.02,2.89,3.1,4.84,6.96,7.36,10.36,1.46,2.19,1.78,1.5,2.83-.44,1.M 24-2.38,2.45-4.78,3.7-7.16,.38-.55,.78-1.75,1.62-1.48,3.34,4.23,5.64,9.29,8.64,13.76,.75-.02,1.07-.32,1.32-.72,1.62-2.6,3.25-5.2,4.9-7.79,.43-.48,.92-1.72,1.73-1.24,3.55,5.17,5.88,10.92,9.19,16.26,3.03-2.74,4.89-6.3,7.72-9.22,.2-.24,.82-.18,.99,.1,3.28,6.02,5.75,12.51,8.85,18.64,.72,.06,1.08-.22,1.41-.56,1.38-1.01,7.61-8.92,8.71-7.34,3.25,6.67,5.73,13.67,8.51,20.53,.17,.42,.43,.76,1.15,.94,2.8-2.09,5.72-4.21,8.56-6.26,.41-.31,1.3-.72,1.75-.35,3.24,7.33,5.28,15.13,8.05,22.65,.28,.83,.62,1.64,.99,2.45,.05,.12,.5,.24,M .68,.18,3.38-1.48,6.61-3.33,9.93-4.94,.46-.23,.95-.39,1.62-.26,3.16,9.87,6.47,19.93,8.39,30.07,4.53-1.53,9.18-2.78,13.64-4.47-2.47-9.84-5.72-19.45-8.63-29.18-.22-.7-.48-1.82,.65-1.81,3.86,.22,7.61,1.38,11.45,1.84,1.17-.1,.51-1.5,.36-2.21Z"/><path class="cls-2" d="M169.9,1258.03c.04-.86,0-1.73,.46-2.5,3.02-5.89,5.45-12.19,8.82-17.86l-.09,.06c17-.83,34.21-.58,51.28-1.29,.9,.2,5.82-.82,4.89,.97-3.54,5.45-7.16,10.86-10.72,16.3-.34,.7-1.44,1.78-.22,2.19,12.9-.1,25.8-1.36,38.69-2.1,3.21-.1,6.44-.78,9.63-.49,.94,.41-.76,1M .87-1.06,2.44-4.48,5.64-9.16,11.14-13.54,16.85-.18,.24,.14,.73,.47,.72,13.96-.55,27.84-2.36,41.73-3.78,3.62-.41,.91,1.49-.15,2.89-5.18,5.51-10.39,11.01-15.57,16.52-.27,.45-2,2-.84,2.1,13.28-.94,26.49-3,39.7-4.09-.25,1.41-1.68,2.15-2.58,3.19-6.58,6.42-13.26,12.74-19.78,19.22-.54,.65,.15,1,.81,.88,11.63-.97,23.17-2.82,34.79-3.91,1.38,.21-1.43,2.26-1.8,2.7-7.61,6.84-15.23,13.68-22.84,20.52-.62,.56-1.18,1.17-1.75,1.76-.07,.07-.08,.25-.01,.3,.16,.13,.38,.32,.56,.31,1.74-.15,3.48-.33,5.21-.5,7.09-.69,14.18-1.37,21.26-2.0M 6,3.26-.26,8.77-2.01,3.16,2.39-9.18,7.88-18.44,15.71-27.6,23.62-.51,.44-1.5,.84-1.04,1.57,.32,.5,1.21,.26,1.84,.22,8.99-.41,17.98-1.6,26.97-1.65,.49,.38-.15,1-.53,1.29-12.28,10.02-24.38,20.24-36.77,30.14-8.15,.4-16.39,.05-24.56,.17-.57-.03-2.05,.11-2.13-.5,.21-1.12,1.58-1.68,2.33-2.51,6.37-5.41,12.76-10.82,19.13-16.23,3.6-3.06,7.2-6.12,10.8-9.18,.38-.32,.7-.65,.51-1.14-9.47,0-19.05,1.28-28.56,1.52-.68-.05-1.18-.25-.5-1.06,8.36-7.64,16.89-15.1,25.3-22.67,.47-.62,3.8-2.76,1.98-3.08-10.72,.88-21.39,2.15-32.14,2.66-.12M ,0-.33-.05-.35-.11-.06-.19-.16-.46-.05-.59,.54-.62,1.11-1.21,1.72-1.79,6.49-6.19,12.99-12.38,19.49-18.57,.69-.87,4.11-3.08,1.2-3.09-7.37,.49-14.72,1.37-22.08,2.01-4.42,.19-9.37,1.43-13.69,.97,.42-1.65,2.16-2.66,3.2-4,4.95-5.24,9.92-10.48,14.86-15.73,.56-.81,1.76-1.43,1.61-2.49-13.51,.92-27.03,2.62-40.6,3.21-1.14-.24-.4-.97,0-1.5,5.07-6.23,10.44-12.25,15.35-18.61,.19-.26-.12-.74-.47-.73-5.65,.04-11.26,.76-16.9,1.09-9.27,.53-18.54,1.17-27.83,1.48-.73,.02-1.09-.55-.72-1.14,.85-1.34,1.71-2.69,2.6-4.02,2.48-3.7,4.97-7.4M ,7.45-11.1,1.02-1.9,3.85-4.25-.37-3.88-12.26,.38-24.51,.86-36.77,1.01-3.77,.04-7.55,.15-11.32,.24-.67,.01-1.35,.02-1.89,.42l.03,.02Z"/><path class="cls-2" d="M1262.17,202.07c-11.54,.6-23.17,.35-34.74,.71-6.06,.12-12.12,.37-18.18,.55-1.07,.03-2.15-.02-3.22-.09-.14,0-.4-.37-.34-.49,3.56-6.33,8.13-12.09,11.78-18.37,.14-.25-.22-.72-.54-.72-13.44,.4-26.87,1.48-40.3,2.34-2.68,.18-5.35,.55-8.05,.54-1.51-.28,.52-1.96,.86-2.62,4.23-5.25,8.47-10.5,12.7-15.75,.36-.44,.64-.93,.88-1.42,.05-.1-.24-.32-.42-.46-14.42,.88-28.9,2.52M -43.31,3.87-1.14-.09,.65-1.68,.89-2.09,5.17-5.52,10.36-11.02,15.53-16.54,.72-.77,1.37-1.59,2.01-2.4,.06-.08-.14-.39-.31-.47-12.9,.93-25.93,2.54-38.79,4.18-2.48,.32-.45-1.45,.35-2.24,6.97-6.86,14.14-13.52,20.99-20.5,.21-.28-.31-.66-.5-.68-11.08,1.15-22.14,2.48-33.2,3.8-.86,.1-1.74,.64-2.6-.02,.03-.87,.93-1.28,1.53-1.82,7.87-7.09,15.76-14.17,23.63-21.26,.62-.56,1.15-1.18,1.7-1.78,.06-.06,0-.22-.06-.31-.61-.38-1.56-.12-2.27-.15-8.29,.82-16.57,1.64-24.86,2.48-2.89,.08-8.69,2.08-3.27-2.17,9.61-8.29,19.4-16.41,28.87-24.8M 7,.11-.1,.01-.38-.04-.57-.26-.21-.77-.17-1.11-.19-8.6,.37-17.19,1.18-25.78,1.71-.64,.04-1.3-.05-1.95-.1-.05,0-.12-.21-.09-.3,11.83-10.78,24.86-20.68,37.25-30.96,8.2-.26,16.42-.04,24.63-.11,.73,.06,1.64-.18,2.12,.49,.05,.06,.02,.22-.04,.28-.59,.58-1.15,1.18-1.79,1.73-4.05,3.46-8.12,6.91-12.19,10.36-5.64,4.78-11.28,9.57-16.9,14.36-.85,.74-2.92,2.37-.41,2.23,6.59-.37,13.17-.75,19.76-1.13,2.67-.05,5.38-.61,8.04-.38,1,.42-.97,1.78-1.35,2.28-8.73,7.93-17.69,15.62-26.28,23.69-.22,.3,.36,.64,.54,.66,10.88-.68,21.73-2.31,32M .61-2.61-.12,.35-.11,.71-.33,.94-1.16,1.19-2.37,2.34-3.58,3.5-5.97,5.7-11.96,11.39-17.92,17.09-.69,.66-1.33,1.35-1.95,2.05-.1,.12,.05,.38,.11,.65,11.24-.67,22.45-2.23,33.69-3.05,5.43-.64,2.21,1.41,.31,3.69-5.52,5.98-11.34,11.72-16.68,17.86-.07,.31,.06,.74,.54,.68,11.79-.91,23.55-2.23,35.36-2.98,3.9-.09,7.65-1.77,3.09,3.19-4.02,4.85-8.05,9.69-12.07,14.54-.59,.72-1.16,1.45-1.68,2.2-.11,.15,.02,.41,.04,.66,14.86-.42,29.77-2.23,44.69-2.53,1.38-.04,1.73,.37,1.13,1.33-.9,1.44-1.82,2.88-2.77,4.31-2.98,4.59-6.21,9.03-9.03,M 13.72-.22,1.06,1.45,.71,2.09,.79,4.04-.14,8.08-.3,12.12-.43,12.93-.35,25.86-.66,38.8-.82l-.12-.12c-3.15,6.75-6.32,13.48-9.72,20.12l.09-.06Z"/><path class="cls-2" d="M169.87,1258.01c-.57,.12-.87,.44-1.07,.86-1.78,3.72-3.56,7.44-5.34,11.16-1.06,2.21-2.12,4.42-3.17,6.64-.24,.45-.45,1.2,.21,1.37,15.47,.24,30.95-.88,46.42-1.35,2.19-.04,1.81,.42,.93,2.01-2.94,4.36-5.91,8.71-8.85,13.06-1.09,1.61-2.13,3.24-3.18,4.87-.25,.39,.2,.86,.8,.84,13.73-.31,27.41-1.57,41.12-2.25,.33-.01,.77,.47,.62,.67-.47,.65-.93,1.31-1.45,1.93-4.7M 4,5.76-9.5,11.51-14.24,17.26-.41,.62-1.42,1.48-.14,1.81,2.82-.16,5.65-.29,8.47-.48,9.39-.62,18.78-1.31,28.17-2.03,.23,0,.73,.34,.6,.63-6.54,7.57-14.04,14.37-20.5,22.01-.04,.67,1,.61,1.48,.59,8.32-.59,16.64-1.18,24.96-1.78,1.28,.12,7.2-1.26,7.05,.15-5.52,5.92-11.73,11.23-17.5,16.92-9.71,9.4-9.82,7.73,3.25,7.36,6.05-.29,12.1-.62,18.15-.93,1.57-.09,1.12,.86,.19,1.63-8.82,7.85-17.63,15.72-26.43,23.59-1.14,.87-2.09,2.19-3.56,2.51-8.07,.19-16.17,.02-24.25,.07-.58-.04-1.89,.08-1.9-.69,8.02-8.61,17.05-16.34,25.27-24.77,.11M -.11,.01-.39-.04-.58-.26-.23-.78-.18-1.12-.22-9.28,.45-18.57,.85-27.86,1-.2,0-.49-.18-.58-.33-.09-.16-.08-.45,.04-.59,2.39-2.61,4.77-5.21,7.21-7.79,4.14-4.38,8.32-8.74,12.48-13.11,.56-.59,2.23-2.01,.46-2.14-11.03,.28-22.03,1.46-33.05,1.7-.77-.33,0-1.15,.29-1.61,1.82-2.26,3.66-4.52,5.51-6.77,3.41-4.14,6.82-8.27,10.23-12.41,.36-.44,.83-.87,.43-1.54-11.63,.14-23.33,1.38-34.98,1.77-.87-.11-4.49,.68-3.72-.93,4.24-6.63,8.93-12.99,13.09-19.66,.02-.8-1.28-.71-1.86-.71-3.23,.11-6.46,.22-9.69,.34-11.17,.49-22.34,.94-33.52,.9M 8l.14,.11c2.93-6.11,5.86-12.22,8.79-18.33,.32-.76,1.36-2.24-.03-2.48-11.14-.25-22.28,0-33.43-.09-5.36-.12-10.75,.1-16.08-.39-1.05-.29-.43-1.57-.34-2.32,1.42-5.46,2.85-10.92,4.27-16.38,.16-.61,.46-1.26-.21-1.82l-.06,.02c1.12-.49,2.34-.42,3.55-.4,4.98,.08,9.96,.11,14.93,.25,13.01,.71,26.16-.26,39.1,.77,0,0-.03-.02-.03-.02Z"/><path class="cls-2" d="M555.12,270.11c-7,1.83-13.79,4.34-20.78,6.2-.32,.09-.82-.29-.75-.56,6.68-20.92,14.95-41.42,23.13-61.84,.13-.81,1.53-2.6,.09-2.8-7.13,.88-14.05,3.09-21.18,4-1.41-.19-.12-2,0M -2.82,8.89-23.82,18.88-47.2,29.24-70.46,.19-.82,1.38-2.28-.05-2.46-7.65,.34-15.2,1.79-22.85,2.16-2,0-.21-2.24,0-3.22,12.04-28.51,24.92-56.77,38.73-84.5,.33-.12,.57-.28,.82-.29,8.7,.03,17.46-.23,26.14,.01,.34,.53,.27,.95,.06,1.35-.86,1.7-1.71,3.4-2.6,5.08-13.61,25.67-26.43,51.46-38.34,77.78-.48,1.68,2.4,.9,3.36,.93,5.07-.55,10.14-1.12,15.21-1.66,1.73-.18,3.48-.32,5.22-.46,.59-.05,.96,.39,.73,.87-11.5,23.85-22.85,47.72-32.65,72.24-.09,1.45,3.69-.15,4.58-.11,5.33-1.13,10.66-2.29,15.99-3.41,.61-.02,1.77-.44,2.09,.27-6.M 31,15.65-13.81,30.95-19.66,46.79-1.97,5.56-4.9,10.94-6.23,16.68l-.25,.21Z"/><path class="cls-2" d="M433.2,580.83c.01,.05,.01,.1,.02,.15-.05,0-.11-.01-.16-.02l.14-.13Z"/><path class="cls-2" d="M439.57,639.7s.05,.01,.07,.01c.02,.02,.03,.03,.04,.05l-.11-.06Z"/><path class="cls-2" d="M514.96,654.63c-2.54,2.68-4.76,5.89-7.66,8.26-.69-.19-.94-.56-1.15-.94-.91-1.68-1.84-3.36-2.68-5.06-2.44-4.42-4.01-9.31-6.87-13.46-1.43,.61-2.13,1.7-3.14,2.54-2.21,1.74-4.01,3.88-6.58,5.18-.84-.53-1.06-1.27-1.37-1.98-2.95-6.89-5.95-13.82-8M .88-20.7-.89-.05-1.39,.31-1.91,.64-2.53,1.61-5.06,3.22-7.61,4.81-2.23,1.36-2.27,.03-3.09-1.76-2.23-6.1-4.45-12.2-6.65-18.3-.64-1.75-1.23-3.52-1.86-5.28-.45-.88-1.69-.43-2.39-.07-3.21,1.59-6.71,2.7-10.02,4.17-.64,.55-.07,1.47,.05,2.15,2.87,8.52,6.2,16.93,9.39,25.38,.52,1.9-11.44-.31-12.9-.5-.25-.35-.57-.69-.72-1.06-3.49-9.13-7.4-18.15-9.98-27.51,.56-1.72,13.08,2.99,13.04,.75-2.75-10.35-6.83-20.41-8.76-30.91,3.58-.3,6.93-2.14,10.41-3.03,.86-.28,1.65-.76,2.95-.61,2.72,9.82,5.26,19.95,8.57,29.63,.86,.17,1.45-.1,2.01-.3M 9,3.2-1.54,6.28-3.41,9.57-4.78,.64-.08,.96,.63,1.11,1.13,1.66,4.99,3.28,9.99,4.99,14.98,1.03,3,2.2,5.98,3.31,8.97,.16,.42,.9,.61,1.31,.33,3.05-2.1,6.1-4.19,8.98-6.5,.29-.21,.88-.13,1.02,.14,3.28,6.98,5.67,14.4,8.99,21.37,1.05,.08,1.59-.64,2.28-1.25,2.1-2.1,4.18-4.22,6.26-6.34,.35-.35,.74-.61,1.44-.59,3.31,6.64,5.28,13.91,8.54,20.59Z"/><path class="cls-2" d="M630.4,655.28c.01-.07,.01-.13,.01-.2,.06,.02,.11,.05,.17,.08l-.18,.12Z"/><path class="cls-2" d="M670.15,602.22s-.01,.08-.02,.12c-.04-.02-.09-.04-.13-.06l.15-.06M Z"/><path class="cls-2" d="M725.85,587.44s.05-.06,.08-.09c.01,0,.02,.01,.03,.01l-.11,.08Z"/><path class="cls-2" d="M737.94,573.78c-3.62,4.76-8.11,8.99-12.01,13.57-2.68-.99-5.35-1.97-8.03-2.96-1.27-.46-1.72-.39-2.38,.42-3.43,4.39-7.29,8.51-9.81,13.37,2.77,1.41,6,1.93,8.86,3.13,.12,1.3-.78,2.25-1.25,3.39-1.74,3.7-3.69,7.33-5.14,11.11,0,.02-.01,.04-.02,.06-.04-.01-.08-.02-.12-.04-3.2-1.1-6.63-1.51-9.64-3.09,1.83-4.6,4.24-9.02,6.42-13.47,.29-.59,.08-1.15-.54-1.37-2.44-.9-4.88-1.78-7.32-2.66-.68-.2-1.22,.25-1.5,.77-2.26M ,4.47-4.52,8.95-6.76,13.43-.08,.15,.01,.36,.05,.55,.01,.02,.01,.05,.01,.07-2.91-1.1-5.85-2.16-8.78-3.26-.31-.12-.91,.05-1.04,.28-2.48,4.69-3.84,9.94-6.43,14.58-2.65-1.05-5.29-2.11-7.94-3.17-.48-.19-1.14,.03-1.33,.43-1.68,3.94-2.95,8.05-4.49,12.06-.32,.88-.5,1.68-1.37,2.24-2.73-1.03-5.14-2.42-7.85-3.45-.29-.12-.89,.1-.98,.37-1.55,4.7-3.08,9.35-4.62,14.06-.51-.04-.97,.04-1.28-.1-2.45-1.12-4.79-2.37-7.19-3.59-.27-.14-.87,.07-.98,.33-1.63,4.62-3.18,9.44-4.07,14.24-3.22-1.3-5.98-3.49-9.11-4.9-.95,.57-1,1.36-1.2,2.07-.93M ,3.25-1.8,6.51-2.72,9.77-.3,.8-.54,2.63-1.8,1.69-11.12-9.27-6.44-8.95-11.97,6.46-.72,.12-1.14-.1-1.49-.45-2.38-2.34-4.63-4.79-7.11-7.03-.14-.12-.48-.09-.84-.14-1.44,3.31-2.3,6.84-3.47,10.25-.24,.71-.35,1.47-1.03,2.03-.62-.03-.97-.36-1.29-.72-1.88-2.1-3.75-4.2-5.63-6.3-.75-.57-1.65-2.62-2.7-1.69-1.47,3.13-2.47,6.47-3.76,9.68-3.33-4.05-6.45-8.27-9.38-12.61,1.12-2.6,2.25-5.22,3.37-7.82,.29-.64,.65-1.91,1.57-1.41,2.47,2.75,4.46,5.89,6.75,8.79,.48,.46,1.09,1.64,1.89,1.17,2.06-3.72,2.9-8.07,4.8-11.88,.76,0,1.09,.33,1.37,M .68,2.21,2.73,4.33,5.51,6.84,7.98,.19,.21,.94,.11,1.02-.13,1.39-3.71,2.52-7.47,3.79-11.22,.2-.56,.71-1.58,1.43-1.01,2.43,2.45,4.55,5.17,7.25,7.33,.11,.08,.62,.03,.67-.07,2.01-4.11,2.61-8.79,4.42-12.97,.66-.28,1.1-.1,1.48,.25,2.27,1.94,4.2,4.38,6.72,5.98,.8,.16,1.02-.81,1.24-1.36,1.13-3.65,2.23-7.31,3.36-10.97,.19-.61,.36-1.25,1.25-1.78,2.6,1.6,5.1,3.4,7.88,4.75,.85-.32,1.02-.83,1.19-1.35,1.16-3.54,2.31-7.08,3.5-10.61,.28-.83,.67-1.63,1.08-2.43,.06-.13,.5-.26,.68-.21,2.37,.91,4.48,2.38,6.73,3.53,.46,.26,.96,.36,1.66M ,.24,7.87-18.7,2.26-15.61,14.51-10.9,2.46-4.84,4.99-10.34,6.77-15.43,2.79,1.21,5.41,2.77,8.31,3.68,.19,.06,.58-.06,.7-.19,2.58-4.32,4.74-8.89,7.17-13.3,.26-.5,.56-.97,1.35-1.24,2.53,1.06,5.1,2.42,7.79,3.21,.2,.06,.59-.03,.72-.16,3.04-3.6,5.35-7.73,8.29-11.41,2.89-3.45,1.82-3.23,6.34-1.33,1.89,.68,3.55,1.72,5.59,1.94,4.18-4.43,7.88-9.32,12.27-13.53,.26-.14,.8-.18,1.13-.05,2.74,1.14,5.47,2.29,8.15,3.41,0,.21,.01,.31,0,.41Z"/><path class="cls-2" d="M97.05,1321.32c-.26-.52-.21-1.05-.07-1.58,1.66-6.31,3.3-12.62,4.86-18.M 95,.52-1.7-1.99-1.36-3.12-1.45-3.63-.05-7.27-.14-10.9-.15-11.29-.13-22.61-.41-33.87-.95-.68-.21-1.05-.89-.98-1.57,.02-6.35,.05-12.69,.09-19.04-.09-1.45,1.46-1.34,2.53-1.34,15.32,.78,30.65,1.17,45.97,1.63,1.39,.32,6.08-.65,5.63,1.55-.67,2.74-1.36,5.48-2.06,8.22-.88,3.48-1.77,6.95-2.64,10.43-.16,.42,.06,.99,.51,1.09,15.45,.66,30.94-.26,46.4-.02l-.14-.11c-2.89,6.51-6.08,12.89-9.19,19.3-.35,.78-1.04,1.9,.35,2.09,13.1,.2,26.13-.94,39.23-1.16,.35,1.33-.84,2.19-1.42,3.28-3.73,5.61-7.46,11.21-11.18,16.82-.27,.48-.94,1.33-.M 2,1.66,11.28,.18,22.59-.94,33.88-1.16,.63-.01,.99,.44,.69,.85-5.6,7.39-12.02,14.21-17.45,21.72-.02,.67,.99,.64,1.49,.64,9.29-.3,18.57-.61,27.86-.9,.39-.06,.7,.18,.98,.4,.21,.3-.21,.6-.38,.84-7.42,7.81-14.59,15.85-22.15,23.53-8.3,.48-16.68,.05-25,.2-3.79,.1-1.15-1.94-.07-3.45,4.78-5.99,9.57-11.98,14.35-17.96,.58-.71,2.19-2.35,.33-2.51-9.69,.12-19.39,.69-29.07,.55-.28-.02-.69-.51-.6-.71,.09-.2,.15-.42,.27-.61,4.22-6.62,8.53-13.2,12.83-19.78,.59-.91,.18-1.35-1.2-1.3-11.17,.34-22.34,.83-33.52,.93-1.39-.07-.7-1.34-.38-2M .08,1.94-4.13,3.9-8.25,5.84-12.38,1-2.11,1.99-4.23,2.97-6.34,.2-.43-.18-.88-.75-.89-13.58,.28-27.26,.19-40.79,.64-.01,0,.09,.05,.09,.05Z"/><path class="cls-2" d="M1344.66,118.75c-.19,.28-.49,.54-.56,.84-1.66,6.53-3.31,13.06-4.95,19.6-.14,.56,.34,1.01,1.12,1.08,14.93,.46,29.87,.5,44.79,1.11,1.75,.03,2.56,.05,2.49,2.09,0,6.13,0,12.27-.01,18.4-.05,.63,0,1.47-.79,1.63-5.76,.01-11.56-.5-17.32-.7-9.28-.29-18.56-.57-27.84-.85-2.8-.15-5.66,.12-8.38-.66l.14,.13c2.14-6.26,3.27-12.84,4.97-19.23,.11-.57,.38-1.51-.39-1.69-8.17-M .55-16.37-.06-24.55-.1-6.05,.06-12.1,.15-18.14,.22-1.04-.07-3.73,.42-2.99-1.35,2.93-6.23,5.96-12.43,8.93-18.64,.47-.98,.12-1.37-1.23-1.38-13.16,.09-26.33,.53-39.46,1.37l.16,.11c3.68-7.1,8.9-13.53,13.09-20.38,.84-1.37,.42-1.84-1.13-1.81-11.08,.26-22.09,.76-33.16,1.31-.28-1.4,1.05-2.13,1.74-3.18,4.79-5.86,9.58-11.72,14.36-17.59,1.49-1.89,1.95-2.52-.96-2.43-9.02,.3-18.04,.59-27.07,.8-1.51-.21-.63-1.23,.09-1.92,7.15-7.46,13.99-15.13,21.15-22.58,8.93-.32,17.97-.22,26.9-.05,.31,.51,.12,.88-.18,1.27-3.03,3.82-6.04,7.65-9.M 08,11.47-2.39,3-4.81,5.98-7.2,8.97-.38,.52-1.36,1.6-.24,1.84,9.83-.09,19.66-.56,29.49-.58,.99,.29,.56,1.02,.21,1.62-4.13,6.41-8.31,12.81-12.43,19.22-.88,1.5,.64,1.51,1.74,1.5,10.51-.31,21.01-.63,31.52-.8,1.94,0,2.36,.21,1.6,2.19-1.98,4.23-4,8.46-5.99,12.69-.9,1.91-1.75,3.84-2.62,5.76-.18,.4,.23,.94,.72,.97,13.86,.15,27.75-.63,41.61-.15l-.14-.12Z"/><path class="cls-2" d="M488.94,146.58c11-30.71,22.64-61.24,35.4-91.29,.17-.41,.31-.84,.59-1.19,.58-.69,1.66-.66,2.52-.66,7.68,0,15.37,0,23.05,0,.61-.04,1.9-.04,1.89,.72-4M .98,11.98-10.58,23.72-15.59,35.66-7.46,17.5-14.67,35.07-21.37,52.85-.36,1.09-.04,1.49,1.22,1.4,1.88-.13,3.75-.29,5.63-.47,5.22-.5,10.43-1.02,15.64-1.53,.95-.14,2.42-.03,1.91,1.22-10.59,25.37-20.38,50.95-29.09,76.95l.08-.06c-6.93,1.29-13.86,2.59-20.79,3.86-.79,.03-2.51,.66-2.67-.47,2.7-8.99,5.59-17.91,8.62-26.82,5.62-16.84,11.55-33.58,17.88-50.18,.14-.64,.7-1.72-.15-2-1.34,.01-2.68,.01-4.01,.13-6.95,.53-13.87,1.5-20.84,1.76l.08,.11Z"/><path class="cls-2" d="M1271.78,456.81c37.9,11.66,75.35,24.51,112.26,38.83,1.08,.4M 1,2.29,.69,3.1,1.66,.24,6.39,.05,12.86,.11,19.26-.06,.79,.14,2.22-1.1,1.97-22.58-8.99-45.03-18.03-68.01-26.24-14.84-5.35-29.77-10.66-44.91-15.38-.52-.15-1.19,.19-1.19,.57,.41,5.8,1.28,11.58,1.86,17.37,.02,.21,0,.43,0,.65,0,.25-.58,.64-.84,.55-31.46-10.83-63.55-20.68-95.91-28.95l.07,.08c-.82-5.6-2.66-11.29-1.74-16.95,.43-.66,1.47-.25,2.12-.18,29.7,6.83,59.04,15.19,88.03,24.3,1.85,.58,3.59,1.47,5.65,1.54,.49,.02,.51-.16,.36-4.97,.05-4.65-.68-9.62,.26-14.16l-.13,.06Z"/><path class="cls-2" d="M1001.34,1295.62c-.43-.72-M .33-1.44-.11-2.2,.79-2.71,1.54-5.44,2.32-8.16,2.81-9.72,5.37-19.48,7.83-29.26,1.74-6.94,3.48-13.88,5.14-20.83,1.36-5.69,2.61-11.39,3.91-17.09,.22-.95,.39-1.91,1.17-2.71,0,0-.06,.03-.05,.02,.48,.59,1.3,.7,2.05,.87,6.14,1.65,12.62,2.46,18.56,4.68l-.06-.09c-.45,6.23-2.27,12.34-3.38,18.5-4.09,18.79-8.3,37.52-13.13,56.15-.13,.99-1.07,2.52,.47,2.83,7.81,1.11,15.63,2.2,23.43,3.41l-.07-.09c-3.31,10.9-5.35,22.19-8.4,33.21-4.7,17.08-8.75,34.48-14.43,51.26-2.82,.26-16.49,.72-27.26,.03,8.33-28.47,17.65-56.76,24.94-85.56,.14-.5M 3,.18-1.07,.25-1.6,.02-.46-.81-1-1.35-1-6.78-.89-13.55-1.78-20.33-2.67-.54-.07-1.07-.05-1.5,.28v.02Z"/><path class="cls-2" d="M418.87,224.39c-.33-.54-.99-.67-1.62-.82-3.96-.92-7.93-1.82-11.89-2.74-2.23-.73-5.77-.93-7.25-2.24,5.17-24.77,10.5-49.52,16.86-74.03,.08-1.05,1.16-2.81-.47-3.14-6.5-.93-13-1.81-19.5-2.75-.92-.13-1.83-.36-2.72-.59-.2-.05-.43-.33-.43-.5,.84-6.32,2.86-12.49,4.25-18.73,5.56-21.74,11.27-43.51,17.86-64.96,.61-.64,1.79-.4,2.62-.49,7.41,0,14.83,0,22.24,.02,.84,0,2.46-.19,2.41,1-4.75,15.91-10.12,31.6M 9-14.58,47.68-3.49,12.83-7.62,25.53-10.57,38.48-.16,1.04,1.47,1.23,2.31,1.33,4.38,.59,8.76,1.2,13.15,1.77,2.26,.29,4.53,.54,6.8,.78,.23,.02,.49-.14,.73-.21h0c.53,.56,.56,1.19,.37,1.83-3.91,13.36-7.53,26.81-10.92,40.28-2.12,8.42-4.31,16.82-6.03,25.3-.75,3.71-1.71,7.39-2.59,11.08-.15,.65-.51,1.22-1.1,1.7,0,0,.06-.01,.06-.01Z"/><path class="cls-2" d="M1287.14,363.02c-.97,5.98-2.15,11.93-3.26,17.89-.34,1.49-2.25,.69-3.29,.61-28.6-6-57.55-10.64-86.51-14.64l.15,.12c2.27-5.06,3.61-10.59,5.53-15.82,.47-1.77-3.38-1.3-4.48-1M .66-3.07-.33-6.13-.64-9.2-.95-20.7-2.28-41.53-2.93-62.3-4.3l.15,.1c1.99-4.1,3.97-8.21,5.99-12.31,1.84-3.73,2.09-3.71-3.31-3.78-9.68-.15-19.36-.1-29.04-.05-10.35,.12-20.69,.64-31.04,.76-1.66-.34-.29-1.81,.11-2.67,2.63-4.35,5.3-8.68,7.91-13.05l-.1,.05c21.86-.81,43.72-1.72,65.6-1.27l-.09-.1c-1.75,4.63-4.6,8.95-6.72,13.47-.53,1.34-2.21,3.09,.67,3.08,24.21,.52,48.35,2.2,72.47,4.24l-.1-.11c-1.51,5.86-4.27,11.3-5.73,17.19,28.95,3.92,58.02,7.7,86.72,13.3l-.11-.1Z"/><path class="cls-2" d="M1096.34,280.31c19.3-1.43,38.66-2.0M 2,58.01-2.49,.83,.14,4.47-.48,4.09,.81-2.39,4.7-5.14,9.22-7.66,13.85-.25,.73-1.55,2.15-.37,2.54,23.27,.07,46.5,1.04,69.74,2.13l-.14-.09c-1.39,5.36-4.11,10.45-5.99,15.7-.29,.71-.65,1.41-.4,2.23,10.15,1.5,20.53,1.84,30.74,3.05,17.05,1.67,33.95,4.62,50.98,6.27l-.07-.09c-.22,.5-.53,.99-.64,1.5-1.09,5.99-2.75,11.92-3.43,17.95l.13-.05c-9.65-.58-19.25-3-28.9-4.16-18.66-2.73-37.43-4.72-56.18-6.83l.1,.11c2.04-5.7,4.9-11.45,6.2-17.22-23.96-2.93-48.44-2.85-72.62-3.56l.09,.1c2.85-5.22,5.7-10.44,8.55-15.66,.54-1.07-.6-1.27-1.49M -1.22-20.73-.09-41.43,.84-62.13,1.92l.08,.12c3.76-5.62,7.51-11.24,11.27-16.87l.04-.03Z"/><path class="cls-2" d="M1189.33,383.81c30.14,4.3,59.95,10.21,89.61,16.81,.72,.14,1.41-.21,1.51-.76,1.04-5.32,1.92-10.65,2.88-15.98,.34-1.99,1.77-1.33,3.25-1.1,33.63,7.05,66.61,15.51,99.38,24.94,1.16,.3,1.37,1.15,1.32,2.11,0,5.92,0,11.85,0,17.77,0,2.07-.27,2.56-3.01,1.74-10.45-3.15-20.89-6.34-31.4-9.39-23.4-6.81-47.12-13.01-70.99-18.59-1.14-.26-1.71,.07-1.88,1.1-.88,5.34-1.72,10.68-2.65,16.01-.13,.76-.76,1.08-1.75,.86-30.36-7.78M -61.27-13.66-92.08-19.49l.17,.12c2.07-4.64,3.15-9.69,4.81-14.5,.19-.63,.37-1.24,.91-1.75l-.09,.09Z"/><path class="cls-2" d="M52.33,141.44c0-6.17-.02-12.66,0-18.89,.13-.85-.31-2.56,1.11-2.25,4.43,1.92,8.61,4.43,12.93,6.6,4.55,2.27,8.84,5.07,13.53,7.02,.14,.05,.59-.16,.61-.28,.13-.74,.24-1.49,.23-2.23-.09-7.22-.25-14.43-.3-21.65,0-.43,.05-.86,.08-1.29,.37-1.4,3.53,.54,4.51,.71,5.84,2.22,11.67,4.45,17.5,6.67,1.39,.27,5.46,2.94,5.36,.29,0-.65-.02-1.29-.02-1.94,0-9.05-.24-18.1-.04-27.15,.03-1.04,.52-1.36,1.76-1.11,4.44,M .88,8.88,1.78,13.32,2.66,2.61,.52,5.23,1.02,7.83,1.56,4.25,.89,4.21,1.44,4.28-2.74,.26-11.09,.33-22.19,.79-33.28,.03-1.31,1.65-1.34,2.69-1.3,8.07,.13,16.2-.23,24.24,.17,1.12,.36,.83,1.67,.86,2.58-.36,7.43-.78,14.85-1.1,22.28-.2,4.63-.26,9.26-.4,13.89-.31,1.36,.72,4.71-1.6,4.33-8.3-1.13-16.41-3.87-24.72-4.55-1.54,.09-.71,7.51-.95,9.06,0,7.97,0,15.94,0,23.91-.22,1.1,.65,3.9-1.29,3.38-8.01-3.04-15.9-6.4-23.94-9.37-2.04-.92-1.64,1.32-1.66,2.56-.19,9.25,.8,18.55,.4,27.76-.54,.52-1.51-.08-2.08-.35-5.77-3.18-11.51-6.38-17M .29-9.55-2.33-1.28-4.73-2.47-7.11-3.69-.3-.16-.88,.09-.9,.39-.24,7.2,.27,14.43,.36,21.63,.06,3,0,3.4-.53,3.33-1.41-.2-2.19-1.15-3.19-1.82-7.65-5.12-15.27-10.25-22.91-15.38-.82-.55-1.75-1.01-2.37-1.99Z"/><path class="cls-2" d="M1305.47,1311.84c.95-.16,1.82,.09,2.67,.47,7.71,3.09,15.42,6.18,23.2,9.12,1.27,.47,1.41-.79,1.35-1.68-.1-8.83-.27-17.66-.45-26.49-.01-.64,.07-1.28,.12-1.93,.02-.24,.65-.54,.89-.42,1.03,.51,2.07,1.01,3.07,1.56,7.44,4.09,14.79,8.34,22.37,12.17,.45,.23,1.12-.1,1.12-.55,.09-8.17-.53-16.35-.52-24.5M 1,.75-.37,1.24-.12,1.85,.28,8.73,6,17.72,11.65,26.3,17.84,.53,6.78,.06,13.73,.21,20.56,.02,.52-.21,1.28-.86,1.19-8.17-3.82-15.97-8.43-24.01-12.53-3.09-1.65-2.73-.79-2.8,2.1,.08,6.68,.18,13.36,.25,20.03,0,.85-.11,1.71-.24,2.56-.47,.62-1.48,.05-2.08-.11-8.07-2.95-15.99-6.3-24.16-8.96-.27-.09-.85,.27-.85,.52-.02,2.37-.05,4.73-.05,7.1,.03,7.32,.07,14.65,.1,21.97-.06,.72-.01,1.81-1,1.84-8.72-1.21-17.3-4.11-26.01-4.85-.75,11.35-.6,22.79-.98,34.17-.08,3.89,.08,3.71-4.66,3.71-6.6-.01-13.21-.02-19.81-.03-1.33,0-3.67,.26-3.4M 2-1.69,.64-12.05,1.15-24.1,1.44-36.17,.05-1.61,.23-3.22,.35-4.82,.02-.22,.59-.62,.84-.6,7.37,1.01,14.63,2.92,21.96,4.26,3.07,.37,4.24,1.31,4.09-2.57-.19-11.18,.47-22.44-.23-33.58l-.03,.06Z"/><path class="cls-2" d="M161.33,138.68c-.15,13.24,.38,26.5,.36,39.72-.26,.31-1.03,.27-1.41,.02-5.86-3.01-11.47-6.43-17.24-9.59-1.99-1.11-4.02-2.17-6.05-3.23-2.19-.71-1.01,2.76-1.2,3.91,.33,9.15,.72,18.3,1.18,27.45,.15,1.97-.1,3.27-2.21,1.65-6.19-4.32-12.38-8.64-18.58-12.96-1.72-1.2-3.43-2.42-5.19-3.59-.23-.16-.72-.07-1.17-.11-.0M 7,8.66,.87,17.24,1.22,25.89,.05,.86,0,1.72-.01,2.58-.02,.36-.73,.36-.9,.29-6.21-4.51-11.91-9.67-17.94-14.42-2.83-2.3-5.7-4.58-8.57-6.85-1.85-1.02-1.21,1.73-1.24,2.77,.26,6.46,.53,12.92,.78,19.38-.06,.53,.11,1.52-.31,1.83-.23,.04-.58,.1-.71,0-9.05-7.73-17.63-16.03-26.56-23.91-1.34-1.32-3.42-2.54-3.19-4.63,.15-6.49-.22-12.99,.15-19.46,1.59-.29,2.55,1.25,3.75,2.01,7.8,6.26,15.59,12.52,23.39,18.77,.69,.44,1.3,1.32,2.22,1.07,.08-.01,.18-.16,.19-.24,.04-.86,.11-1.72,.09-2.57-.2-6.68-.42-13.35-.62-20.03,.06-.74-.31-2.31,.M 92-2.01,2.42,1.26,4.57,3.01,6.85,4.5,6.11,4.24,12.2,8.48,18.3,12.72,.43,.33,1.17,.8,1.73,.44,.1-.42,.22-.84,.21-1.26-.24-9.35-.92-18.72-.77-28.06,1.21-.42,2.17,.62,3.23,1.04,7.11,3.89,14.22,7.8,21.33,11.69,2.09,1.22,2.16,.48,2.17-1.58-.2-9.26-.42-18.52-.61-27.78-.09-4.58-.04-4.93,.6-4.95,2.15-.07,3.72,1.1,5.5,1.77,6.83,2.56,13.6,5.21,20.39,7.83l-.08-.08Z"/><path class="cls-2" d="M1305.5,1311.78c-.18-.92-1.32-.9-2.03-1.29-8.13-3.17-16.24-6.39-24.41-9.46l.08,.07c.38-13.13-.51-26.28-.18-39.4,.01-.25,.65-.53,.92-.39,2.M 24,1.2,4.49,2.38,6.7,3.6,5.2,2.88,10.38,5.79,15.58,8.67,.74,.28,2.13,1.36,2.66,.37,.03-11.07-1.11-22.14-1.16-33.21,.99-.39,1.64,.38,2.43,.83,5.9,4.1,11.79,8.2,17.67,12.31,2.21,1.32,4.06,3.4,6.52,4.19,.1,.02,.32-.06,.35-.13,.58-9.47-1.03-19.13-1.04-28.65,1.25-.21,2.01,.92,2.95,1.51,5.57,4.54,11.1,9.1,16.69,13.62,2.65,2.14,5.37,4.23,8.06,6.34,.23,.18,.5,.15,.73-.03,.4-.36,.25-1.03,.31-1.52-.11-2.8-.25-5.6-.35-8.39-.17-4.52-.33-9.04-.47-13.56,.39-1.82,2.22,.47,2.95,1.02,8.72,7.92,17.45,15.84,26.17,23.77,1.33,1.03,.96,M 2.55,1.02,3.98,0,5.17,0,10.34,0,15.51,.34,4.94-1.76,2.26-4.11,.55-8.05-6.34-15.87-12.97-24.04-19.15-1.18-.56-1.03,1.16-1.03,1.87,.18,5.06,.38,10.12,.55,15.18,.08,2.37,.09,4.74,.12,7.11-.14,.64-.61,.9-1.39,.39-7.81-5.27-15.52-10.67-23.25-16.05-.92-.56-1.77-1.51-2.93-1.51-.5,.03-.54,.44-.53,.74,.31,9.04,.65,18.08,.94,27.13,.01,2.23-1.25,1.49-2.64,.79-7.22-3.96-14.43-7.93-21.65-11.89-.85-.4-1.56-1.07-2.57-.68-.16,11.93,1.07,23.91,.37,35.83,0,.02,.02-.04,.02-.04Z"/><path class="cls-2" d="M987.06,901.51s.07-.02,.1-.03c.M 01,.05,.01,.11,.02,.16l-.12-.13Z"/><path class="cls-2" d="M993.65,862.78s-.06,.03-.09,.04c-.01-.03-.03-.06-.04-.09l.13,.05Z"/><path class="cls-2" d="M1000.92,896.97s-.01,.09-.02,.13c-.01,0-.02,0-.03,.01-4.74,1.01-9.12,2.91-13.71,4.37-1.29-10.69-3.59-21.25-5.81-31.78-.25-1.19-1.07-1.06-2.02-.62-3.43,1.59-6.72,3.52-10.14,5.15-.3-.19-.61-.28-.65-.43-.55-2.21-1.11-4.43-1.6-6.65-1.7-6.8-2.94-13.95-5.4-20.5-.68-.46-1.46,.2-2,.56-2.7,2.26-5.38,4.53-8.06,6.81-.37,.31-.74,.59-1.35,.54-.62-.73-.75-1.6-.98-2.44-1.82-6.73-3.48M -13.49-5.72-20.14-.21-.63-.36-1.27-1-1.72-.6,.02-.95,.33-1.28,.67-2.48,2.55-4.96,5.11-7.43,7.66-.34,.35-.71,.64-1.33,.63-3-6.77-4-14.4-7.38-21.07-.67-.44-1.28,.46-1.69,.87-2.29,2.79-4.35,5.74-6.78,8.41-.16,.13-.84,.23-1.01-.03-.42-1.02-.84-2.04-1.21-3.07-1.64-4.44-3.25-8.88-4.88-13.32-.26-.71-.43-1.46-1.12-2.01-.62,.09-.91,.45-1.16,.84-2.18,3.21-4.1,6.59-6.49,9.66-.24,.27-.74,.04-.88-.15-1.83-4.39-3.63-8.78-5.49-13.17-.35-.81-.81-1.59-1.27-2.36-.08-.13-.44-.16-.67-.19-.67,.29-.97,1.31-1.41,1.87-1.42,2.56-2.81,5.13-M 4.23,7.69-.4,.5-.85,1.77-1.67,1.28-2.22-3.88-4.09-7.95-6.19-11.9-.3-.6-.59-1.21-1.46-1.61-2.42,3.75-3.72,8.11-6.11,11.88-.84-.23-1.06-.74-1.34-1.21-1.99-3.31-3.72-6.73-5.92-9.91-.16-.22-.62-.32-1.08-.54-1.92,3.97-3.31,8.02-5.26,11.95-.08,.14-.38,.3-.55,.28-.23-.02-.53-.17-.65-.33-2.02-2.92-3.92-5.89-5.93-8.81-.25-.25-.8-.8-1.22-.58-2.2,3.94-3.29,8.45-5.32,12.49-1.03,1.24-2.25-1.86-2.94-2.48,2.14-4.53,4.3-9.07,6.48-13.75,.59,.61,1.53,2.62,2.39,1.32,1.81-3.89,2.87-8.09,4.71-11.96,.71,.02,1.08,.29,1.36,.67,1.61,2.24,3M .22,4.48,4.83,6.73,.6,.84,1.17,1.69,1.77,2.53,.23,.3,.77,.08,.95-.1,1.88-3.51,3.14-7.33,4.78-10.96,.19-.43,.59-.72,.83-.59,1.17,.58,1.63,1.88,2.35,2.88,1.62,2.6,3.23,5.21,4.84,7.81,.29,.48,.57,.95,1.22,1.19,2.27-2.89,3.43-6.87,5.25-10.12,.24-.51,.51-1,1.28-1.3,2.96,4.26,5.18,8.99,7.93,13.38,.15,.15,.78,.39,.98,.08,1.93-2.79,3.44-5.83,5.21-8.73,1.44-2.59,1.88-1.12,3.01,.64,2.41,4.44,4.48,9,6.62,13.53,.27,.44,.9,.32,1.17-.05,2.11-2.86,4.11-5.81,6.19-8.69,.27-.38,.56-.75,1.15-.87,.66,.41,.85,1.04,1.12,1.63,2.16,4.76,4M .1,9.57,5.94,14.41,.38,.85,.56,3.01,1.94,2.76,2.71-2.6,4.97-5.62,7.5-8.4,.32-.37,.71-.61,1.39-.57,12.39,27.31,3,24.78,18.54,13.12,.75,.53,.93,1.17,1.14,1.79,2.76,7.6,4.98,15.39,7.52,23,.94,.12,1.41-.3,1.93-.63,2.53-1.6,5.05-3.22,7.6-4.81,.54-.29,1.47-.96,2.07-.51,3.38,9.36,5.29,19.16,7.97,28.72,1.79-.09,3.01-1.01,4.42-1.57,2.72-1.12,5.4-2.32,8.1-3.46,1.66,3.81,2.13,8.1,3.17,12.12,1.33,7.33,3.43,14.66,4.19,22.03Z"/><path class="cls-2" d="M1246.01,141.96c-9.51,.74-19.07,1-28.58,1.69-4.83,.21-9.66,.86-14.49,.82-1.22-.M 41,.59-1.79,.91-2.4,3.34-4.04,6.7-8.08,10.03-12.12,1.63-1.98,3.23-3.97,4.81-5.97,.19-.25,.35-.64,.24-.89-.22-.52-.88-.35-1.36-.31-7.38,.52-14.75,1.06-22.13,1.59-4.56,.27-9.11,.81-13.68,.87-.38,.04-.57-.46-.47-.71,5.94-6.71,12.34-13.04,18.45-19.61,.75-.9,1.84-1.54,1.92-2.79-10.51,.23-20.94,1.48-31.43,2.17-.65-.06-2.23,.38-2.32-.46,7.46-7.86,15.72-14.99,23.39-22.65,1.04-1.01,1.95-2.1-.3-2.04-9.28,.28-18.54,1.04-27.81,1.21-.4-.6,.03-.98,.46-1.4,9.82-8.63,19.35-17.59,29.34-26.03,8.24-.33,16.6-.05,24.86-.14,.66,.05,2.3-M .2,1.91,.89-7.86,7.98-16.15,15.57-24.16,23.42-.56,.65-1.6,1.25-.2,1.7,9.42-.33,18.83-.67,28.25-.92,1.43,.18,.32,1.39-.23,1.95-6.25,6.77-12.66,13.41-19,20.1-.34,.51-1.54,1.42-.65,1.82,1.34,0,2.69-.01,4.02-.09,9-.5,18-1.03,27-1.58,.89,.06,3.57-.54,2.62,1.09-4.99,6.29-10.18,12.43-15.24,18.66-.5,.84-1.65,1.52-1.43,2.57,1.33,.33,2.66,.08,3.99-.01,11.93-.76,23.91-1.64,35.88-1.66l-.16-.11c-5.04,7.01-9.71,14.27-14.58,21.4l.12-.05Z"/><path class="cls-2" d="M796.17,794.99c.02-.06,.04-.12,.05-.18,.03,.02,.07,.03,.1,.05l-.15,.M 13Z"/><path class="cls-2" d="M821.51,757.2c-1.97,4.46-3.96,8.88-5.95,13.23-.59-.26-1.57-.87-1.97-.04-1.05,4.01-2.05,8-3.03,12.02-.14,.51-.28,1.05-.91,1.4-13.22-4.84-7.17-7.74-13.43,11-4.99-2.35-6.59-2.97-9.38-3.66-1.55,3.94-2.35,8.12-3.62,12.15-.23,.82-.39,1.68-1.25,2.43-3.07-.94-5.99-2.59-9.22-3.02,1.44-4.8,2.54-9.71,4.1-14.47,.09-.26,.66-.51,.96-.42,2.25,.72,4.49,1.45,6.74,2.16,1.52,.53,2.26,.67,2.7-1.12,.96-3.91,1.89-7.82,2.84-11.73,.19-.79,.89-1.13,1.73-.83,2.62,.94,5.36,1.96,7.92,2.98,.94-.45,1-1.13,1.14-1.74,M .93-3.92,1.71-7.85,2.69-11.75,.12-.44,.7-.63,1.26-.4,2.63,1.08,5.18,2.28,7.78,3.42,.3,.12,.74,0,1.13,0,1.38-4.25,1.81-8.76,3.17-13.02,.07-.21,.78-.42,1.04-.31,1.25,.44,2.4,1.11,3.56,1.71Z"/><path class="cls-2" d="M964.52,753.47s.04,.05,.05,.07c-.07,.02-.13,.05-.2,.08l.15-.15Z"/><path class="cls-2" d="M977.5,752.9h-.04s-.04-.05-.05-.07l.09,.07Z"/><path class="cls-2" d="M988.27,774.2c-2.29,.1-4.57-.04-6.86-.02-5.54,0-5.43-.47-3.31,3.78,3.26,6.68,6.46,13.39,9.03,20.29-.22,.24-.32,.47-.53,.58-3.7,1.68-7.24,3.94-11.06,5M .27-.8-.35-.91-1.03-1.16-1.61-1.18-2.74-2.26-5.52-3.48-8.25-1.8-4.06-3.7-8.08-5.55-12.12-.24-.52-.48-1.01-1.26-1.31-3.49,1.7-6.38,4.15-9.48,6.4-1.53,.84-1.76-1.38-2.4-2.26-2.38-4.57-4.75-9.14-7.16-13.7-.57-1.09-1.26-2.13-1.95-3.18-.08-.12-.52-.22-.7-.16-2.28,1.33-4,3.5-6.03,5.17-1,.85-1.72,2.09-3.07,2.38-3.9-5.34-6.55-11.42-10.42-16.8-.2-.28-.83-.37-1.03-.14-2.34,2.75-4.61,5.53-6.82,8.37-1.47,.92-2.39-2.19-3.22-3.04-2.31-3.41-4.62-6.81-6.94-10.22-.32-.47-.64-.95-1.52-1.12-9.85,14-3.29,12.47-16.86-2.81-.68,.21-.99,.M 54-1.2,.96-1.33,2.7-2.67,5.4-4.01,8.1-.33,.61-.55,1.3-1.33,1.44-3.12-3.01-5.55-6.6-8.47-9.82-.43-.36-.9-1.14-1.57-.85,1.61-3.89,3.21-7.81,4.78-11.76,.01-.01,.02-.03,.02-.05,.09-.15,.17-.3,.24-.45,.71-.02,1.12,.22,1.45,.58,1.58,1.75,3.19,3.47,4.75,5.23,1.08,.81,4.31,6.25,5.46,4.85,1.76-3.16,3.43-6.33,5.37-9.38,.16-.26,.82-.26,1.05-.01,3.66,4.02,6.74,8.55,10.24,12.7,.69-.1,1.03-.4,1.3-.78,1.95-2.77,3.83-5.73,5.99-8.33,.73-.01,1.1,.25,1.38,.65,3.46,4.59,6.64,9.36,9.98,14.02,.2,.26,.82,.3,1.05,.07,2.73-2.53,4.88-5.57,8M .01-7.66,.97,.23,1.37,1.24,1.92,1.96,2.95,4.72,5.89,9.44,8.82,14.17,.35,.57,.57,1.2,1.44,1.58,1.88-.84,8.96-7.81,10.3-6.53,3.54,5.61,6.39,11.63,9.67,17.39,.51,.66,.96,2.32,1.97,2.13,3.48-1.84,6.94-3.69,10.39-5.56,.32-.17,.43-.53,.28-.87-3.61-6.7-7.25-13.44-11.2-19.94,4.12-1.14,8.63-.34,12.89-.64,3.82,5.95,6.95,12.3,10.42,18.46,.24,.79,1.71,2.48,.39,2.84Z"/><path class="cls-2" d="M596.88,946.12c1.09-.29,2.17-.6,3.24-.91-3.91,2.75-7.99,5.26-12.19,7.52-.83-.96-1.67-1.9-2.49-2.84,.16-.64,.59-.86,1.11-1,3.44-.93,6.89-1.M 84,10.33-2.77Z"/><path class="cls-2" d="M613.19,930.27c2.16-.69,4.29-1.42,6.4-2.18-2.37,2.6-4.87,5.09-7.46,7.46-4.03-3.95-4.66-3.46,1.06-5.28Z"/><path class="cls-2" d="M628.86,914.09c.79-.3,1.58-.61,2.36-.92-.76,1.15-1.53,2.29-2.33,3.41-1.54-1.12-2.34-1.7-.03-2.49Z"/><path class="cls-2" d="M637.62,964.9l.15-.06-.12,.1s-.02-.03-.03-.04Z"/><path class="cls-2" d="M659.1,943.98s.03-.01,.05-.02h0s-.03,.07-.04,.07c0-.02,0-.03,0-.05Z"/><path class="cls-2" d="M675.62,922.88c-.75,.92-2.11,1.48-3.22,2.15,.67-1.21,1.32-2.43,1M .96-3.66,.51,.4,1.05,.79,1.26,1.51Z"/><path class="cls-2" d="M683.51,899.87c1.6,.96,3.19,1.93,4.53,3.18-2.7,1.99-4.96,3.48-7.67,5.23,1.13-2.76,2.18-5.57,3.14-8.41Z"/><path class="cls-2" d="M695.81,884.63c-3.18,2.78-6.65,5.24-9.96,7.86,1.05-3.61,1.98-7.28,2.78-11.01h-.01c.1-.44,.19-.88,.28-1.33,2.23,1.11,4.46,2.23,6.66,3.36,.48,.24,.6,.81,.25,1.12Z"/><path class="cls-2" d="M1271.91,182.14c2.73-7.07,6.55-13.84,9.65-20.8l-.07,.07c17.28-.01,34.6,.47,51.86,.01l-.14-.13c-.71,6.33-3.05,12.44-4.39,18.68-.19,.73-.25,1.49-.3M ,2.23-.01,.15,.25,.39,.46,.45,14.71,1.24,29.56,1.19,44.29,2.39,4.03,.25,8.05,.53,12.07,.8,.79,.08,2.01,.02,2.11,1.04,.16,6.45,0,12.91,.04,19.37-.04,.58-.05,1.52-.78,1.63-21.32-1.03-42.62-3.68-63.97-3.86l.1,.09c1.53-6.1,3.07-12.2,4.59-18.31,.05-.88,.86-2.66-.43-2.9-18.39-.7-36.79-.69-55.19-.89l.12,.12Z"/><path class="cls-2" d="M976.39,1292.07c5.18,.62,10.37,1.25,15.55,1.87,3.1,.54,6.5,.36,9.39,1.68v-.02c-.6,.1-.88,.44-1.01,.88-.52,1.78-1.04,3.56-1.55,5.35-8.27,28.13-17.38,56.08-27.38,83.69-.39,.99-1.88,.78-2.79,.83-M 8.26-.1-16.48,.2-24.74-.15,6.32-19.51,14.76-38.71,21.08-58.29,3.91-11.31,7.57-22.66,11.35-34,.21-.63,.39-1.25,.2-1.91,0,0-.1,.06-.1,.06Z"/><path class="cls-2" d="M439.08,144.22c.41-.01,.86-.08,.97-.43,.53-1.67,1.03-3.34,1.52-5.01,8.58-28.57,17.51-57.17,28.03-85.12,8.76-.53,17.57-.01,26.36-.15,.25,0,.49,.14,.73,.21,.27,.55,.05,1.05-.15,1.57-2.01,5.24-4.07,10.48-6.01,15.74-9.6,25.48-18.63,51.2-27.02,77.06-.01,0,.08-.07,.06-.06-.38-.5-1.01-.65-1.68-.73-7.58-1.05-15.4-1.25-22.81-3.09Z"/><path class="cls-2" d="M164.64,1M 020.42c-36.95-9.62-73.85-19.97-109.74-32.76-.65-7.42-.2-18.46,.08-21.23,1.8-.34,3.52,.83,5.23,1.28,35.47,12.52,71.18,24.54,107.68,34.07l-.1-.08c-1.18,6.27-1.91,12.61-3.27,18.85l.12-.12Z"/><path class="cls-2" d="M266.55,1007.6c.02-5.64-.13-11.27,.02-16.91,25.63,5.47,53.01,11.43,79.68,14.23,.77-.13,.64-1.09,.66-1.67-.17-3.44-.35-6.88-.53-10.32-.04-1-.42-2.74,1.15-2.58,17.2,2.68,34.51,4.64,51.85,6.2,4.02,.3,8.04,.56,12.06,.84,.8,.06,1.62,.1,2.29,.53l-.08-.07c1.03,3.27,1.1,6.77,1.62,10.15,.14,1.16,.36,2.34-.04,3.51l.13M -.1c-20.12-1.34-40.24-2.48-60.24-5.14-2.39-.18-4.8-.8-7.2-.65-.22,.04-.51,.25-.54,.41-.42,4.81,.01,9.68-.07,14.51l.12-.09c-27.2-2.72-54.25-7.39-80.99-12.93l.1,.08Z"/><path class="cls-2" d="M158.18,1057.92c-34.73-7.53-69.69-15.4-103.48-26.1-.46-6.71,.02-13.55-.1-20.29,0-.32,.13-.63,.2-.91,.56-.27,1.06-.15,1.57,0,2.77,.84,5.54,1.67,8.31,2.51,31.76,9.85,64.28,18.18,96.7,26.17l-.07-.09c-.51,6.33-2.25,12.55-3.25,18.83l.13-.11Z"/><path class="cls-2" d="M822.93,1306.26c8.25-.92,16.47-2.37,24.78-2.59,.89,.29-.05,1.69-.22,2M .29-13.05,26.32-27.1,52.19-41.6,77.79-.49,.87-.8,1.84-1.92,2.55-8.15,.24-16.37,.04-24.53,.1-.68-.06-2.24,.2-2.25-.74,15.76-26.21,31.38-52.55,45.84-79.46l-.09,.07Z"/><path class="cls-2" d="M342.37,130.12c4.44-25.31,10.01-50.4,15.64-75.48,.24-1.53,1.96-1.22,3.17-1.27,7.27,0,14.55,0,21.83,0,.93,0,1.9-.11,2.81,.36-6.21,26.36-13.25,52.65-18.43,79.28-.23,1.29-1.75,1.25-2.77,1.01-5.68-.9-11.35-1.81-17.03-2.71-1.6-.29-4.36-.39-5.22-1.2Z"/><path class="cls-2" d="M1073.79,1305.5c7.27,1.12,14.55,2.22,21.81,3.37,2.58,.33,2.62,M .81,2.24,3.24-4.58,24.75-9.6,49.41-15.48,73.9-1.17,.52-2.35,.39-3.58,.41-6.87,0-13.75,0-20.62-.01-2.95-.1-3.58,.41-2.78-2.97,6.94-25.84,12.51-52,18.53-78.03,0,0-.12,.1-.12,.1Z"/><path class="cls-2" d="M154.84,843.36c.94,6.3,1.77,12.61,2.5,18.94-.23,.71-1.01,.55-1.59,.28-29.78-13.91-58.92-28.75-87.62-44.53-3.55-1.95-7.09-3.92-10.63-5.89-1.36-.84-3.39-1.47-3.05-3.42-.02-6.03-.03-12.06-.03-18.09,.06-.73,.02-1.96,1.15-1.55,6.71,3.74,13.21,7.82,19.92,11.6,26.03,15.01,52.55,29.21,79.42,42.75l-.08-.08Z"/><path class="cls-M 2" d="M1291.21,343.66c19.67,4.02,39.62,7.12,59.15,11.6,11.43,2.47,22.85,4.99,34.18,7.73,.9,.22,1.85,.33,2.64,1.05,.41,6.56,.03,13.26,.14,19.86,.09,2.43-1.57,1.37-3.13,1.14-32.05-8.44-64.42-15.72-97.05-22.03l.11,.1c1.5-6.46,1.94-13.24,4.09-19.5l-.13,.05Z"/><path class="cls-2" d="M151.08,1095.92c-32.28-4.74-64.34-11.96-96.08-19.4-.71-.64-.71-1.29-.71-1.94-.01-5.92,.02-11.85,.15-17.77-.03-2.97,1.3-1.99,3.43-1.59,31.24,8.07,62.66,15.29,94.41,21.35,.76,.17,2.07,.21,1.94,1.25-.36,2.13-.74,4.26-1.14,6.39-.47,2.56-1.03,5.1M -1.43,7.67-.22,1.38-.92,2.72-.7,4.14l.12-.1Z"/><path class="cls-2" d="M476.1,686.23s.01,.02,.01,.03c-.05,.03-.11,.05-.16,.08l.15-.11Z"/><path class="cls-2" d="M493.77,690.47c-4.41,1.02-8.76,2.24-13.04,3.63-1.49-2.64-3.55-5.02-4.62-7.84,3.73-1.64,7.09-4.05,10.73-5.83,.93,.38,1.17,1.02,1.53,1.59,1.8,2.82,3.6,5.64,5.4,8.45Z"/><path class="cls-2" d="M646.68,678.52s0,.05-.01,.07c-.68,4.69-1.19,9.52-2.68,14.02-3.26-.7-6.18-2.13-9.37-3.01-1.78-.62-2.05,6.98-2.57,8.37-.28,1.49-.6,2.97-.9,4.46-.09,.43-.7,.64-1.25,.43-3.07-1M .02-5.91-2.71-9.02-3.55-.21-.02-.6,.14-.64,.26-1.13,3.95-1.66,7.95-2.84,11.91-3.44-2.36-7.34-4.08-10.68-6.62,1.09-3.6,1.68-7.32,2.89-10.87,.18-.05,.32-.14,.4-.12,3.58,1.02,6.15,3.43,9.79,4.5,.24-.23,.63-.45,.7-.71,.4-1.69,.72-3.39,1.1-5.09,.52-2.32,1.08-4.64,1.65-6.96,.04-.16,.33-.27,.61-.47,1.93,.61,3.74,1.62,5.63,2.38,4.69,2.07,4.08,1.69,4.97-2.35,2.86-12.95-.33-10.85,12.12-6.68h0l.09,.03Z"/><path class="cls-2" d="M771.18,1312.07c7.2-.82,14.39-1.64,21.59-2.46,1.93-.16,4.6-.76,2.99,1.71-14.74,25.38-30.53,50.37-46.M 9,74.83-.47,.08-.98,.23-1.5,.23-8.5-.11-17.03,.29-25.5-.14-.21-1.48,1.28-2.53,1.95-3.75,7.65-10.64,15.03-21.4,22.32-32.2,8.69-12.63,16.74-25.56,25.17-38.28l-.11,.06Z"/><path class="cls-2" d="M977.4,1211.23c6.65-.94,13.42-.27,20.13-.41,.64,.03,1.76,.09,1.85,.88-.13,.85-.2,1.72-.42,2.56-4.72,18.35-9.63,36.64-15.03,54.81-2.09,7.12-4.34,14.2-6.52,21.3-.19,.63-.31,1.27-1.03,1.7,0,0,.1-.06,.1-.06-8.36,.13-16.79-.02-25.06,1.26l.15,.07c9.39-27.15,17.98-54.61,25.89-82.18l-.08,.08Z"/><path class="cls-2" d="M1299.31,304.92c29M .38,3.86,58.63,8.6,87.69,14.3,.15,.39,.36,.69,.36,.99,0,6.56,0,13.12-.03,19.68-.02,1.89-2.19,.93-3.35,.82-24.8-5.07-49.53-10.16-74.6-13.97-4.68-.91-9.59-1.09-14.11-2.53l.07,.09c-.22-3.21,1.32-6.56,1.75-9.78,.54-2.63,1.04-5.27,1.54-7.9,.12-.64,.29-1.26,.79-1.79l-.11,.08Z"/><path class="cls-2" d="M142.84,1134.84c-28.64-3.11-57.14-8.26-85.46-13.49-1.55-.34-3.73-.32-3.4-2.39,.04-6.35-.03-12.7,.08-19.05,.05-.83,.61-1.2,1.55-1,3.13,.64,6.26,1.28,9.37,1.95,26.83,5.74,55.12,10.7,81.75,14.61-1.41,6.48-3.03,12.93-4.05,19.48lM .15-.11Z"/><path class="cls-2" d="M476,659.09v.04s-.03,.02-.05,.03l.05-.07Z"/><path class="cls-2" d="M532.54,686.24c-3.85-.05-7.67,.04-11.48,.27-1.17-1.38-1.68-3.23-3.38-4.08-1.66,1.57-3.14,3.16-4.74,4.76-1.95,.21-3.9,.45-5.83,.75-2.55-4.08-5.11-8.16-7.65-12.24-.75-1.07-1.05-2.3-2.27-2.97-3.09,2.15-5.8,4.59-8.99,6.6-.59,.39-1.21,.22-1.6-.4-3.67-6.52-7.66-13.07-10.6-19.8,3.66-2,6.72-4.61,10.11-6.85,1.07-.29,1.4,1.45,1.92,2.11,3.1,5.8,5.73,11.9,9.32,17.41,.75,.03,1.17-.24,1.53-.56,2.47-2.12,4.81-4.32,7.12-6.6,.24-.23M ,.66-.32,.98-.47,4,5.22,6.54,11.44,10.46,16.76,.17,.22,.87,.28,1.06,.07,2.24-2.33,4.12-4.95,6.11-7.48,2.49,4.33,5.14,8.58,7.93,12.72Z"/><path class="cls-2" d="M626.4,670.72c-.92,4.02-1.83,8.05-2.72,12.07-.13,.5-.22,1.06-.89,1.35-2.97-.76-5.45-2.75-8.21-4.02-.48-.26-.97-.35-1.57-.15-1.36,3.97-2.01,8.21-3.23,12.25-.06,.24-.79,.42-1.01,.27-11.63-8.41-8.03-10.33-12.45,3.99-3.54-3.08-6.95-6.31-10.22-9.67,1.13-3.35,2.24-6.69,3.36-10.04,.74-.96,1.74,.48,2.36,.94,2.31,2.09,4.39,4.44,6.86,6.35,.17,.12,.49,.12,.76,.17,.72-.6M 9,.84-1.55,1.07-2.38,.87-3.15,1.75-6.3,2.63-9.45,.73-1.28,1.95,.23,2.66,.78,2.07,1.67,3.96,3.61,6.17,5.1,.28,.15,.74,.07,1.17,.1,1.4-4.41,2.08-8.89,3.61-13.33,3.72,1.47,6.24,3.35,9.63,5.05,.01,.2,.07,.43,.02,.62Z"/><path class="cls-2" d="M626.45,670.14s-.05-.03-.07-.04v-.02l.07,.06Z"/><path class="cls-2" d="M1048.73,359.22c1.68-4.25,4.15-8.16,6.19-12.25,.43-.99,1.53-2.48-.38-2.43-13.97,.67-27.93,1.46-41.85,2.75-4.68,.41-9.36,.84-14.02,1.4-.66,.07-1.33,.18-2.09-.18,2.27-5.09,5.7-9.69,8.44-14.56l-.1,.06c19.53-1.86,39M .06-4.02,58.68-4.63,1.25,.33,.18,1.5-.12,2.2-2.13,4.06-4.76,7.92-6.57,12.13-.05,.13,.19,.46,.35,.48,5.36,.31,10.77-.14,16.14-.18,16.84-.57,33.68,.04,50.52,.34l-.15-.1c-2.25,5.23-4.49,10.64-7.28,15.59l.1-.05c-22.66-.5-45.33-1.05-68.02-.67l.16,.08Z"/><path class="cls-2" d="M1148.03,1317.86c.33,.5,.27,1.04,.2,1.58-.41,3.1-.79,6.21-1.23,9.31-1.89,13.7-3.97,27.37-6.23,41.02-.85,5.12-1.71,10.24-2.57,15.36-.09,1.05-1.31,1.44-2.25,1.38-7.95,0-15.89-.01-23.84-.02-.64,0-1.89-.13-1.75-.9,3.65-19.35,7.57-38.66,10.66-58.12,.62-M 3.62,1.27-7.25,1.84-10.88,.16-1.04,.56-2.12-.04-3.17,0,0-.14,.08-.14,.09,7.9,.73,15.73,2.63,23.59,3.82,.64,.11,1.23,.4,1.84,.61l-.08-.07Z"/><path class="cls-2" d="M317.66,126.38c-8.46-1.47-17.07-2.43-25.38-4.58l.09,.07c1.97-18.53,5.13-37,8.11-55.42,.62-3.73,1.22-7.46,1.85-11.19,.17-1.63,1.31-2.11,2.85-1.98,7.67,0,15.34,.02,23.01,.05,1.14,.06,2.4,.08,2.01,1.62-4.58,23.75-9.58,47.55-12.67,71.5l.13-.09Z"/><path class="cls-2" d="M410.52,983.6s.02,.07,.03,.11c-.04-.01-.08-.01-.12-.01l.09-.1Z"/><polygon class="cls-2" poiM nts="413.65 997.84 413.73 997.84 413.73 997.91 413.65 997.84"/><path class="cls-2" d="M471.89,998.46c-19.4,.86-38.78-.05-58.16-.62,.1-4.88-1.47-9.53-3.18-14.13,12.76,.98,25.52,1.83,38.32,2.3,7.29,4.31,14.98,8.07,23.03,11.23,.07,.4,.09,.81-.01,1.22Z"/><path class="cls-2" d="M471.89,998.46h.08l-.1,.1s.02-.07,.02-.1Z"/><path class="cls-2" d="M505.13,960.32l.06,.09c-.07,.01-.15,.01-.22,.01l.16-.1Z"/><path class="cls-2" d="M548.1,956.57h-.05s-.03-.04-.05-.06l.1,.06Z"/><path class="cls-2" d="M554.29,964.81c-14.84,2.93-30M .47,3.07-46.24-.03-.95-1.46-1.9-2.91-2.86-4.37,14.36-.5,28.61-2.24,42.86-3.84,2.08,2.74,4.17,5.49,6.24,8.24Z"/><path class="cls-2" d="M548,956.51s.03,0,.05,0c.02,.02,.03,.05,.05,.07l-.1-.06Z"/><path class="cls-2" d="M650.81,847.86c0,3.44-.17,6.9-.49,10.37-1.31,1.21-3.23,2.04-4.19,3.52,.87,.96,2.45,1.16,3.6,1.74-.37,2.73-.83,5.46-1.4,8.21h0c-2.53,1.66-5.27,3.1-7.73,4.87-.6,1.08,4.77,2.81,5.69,3.49-.48,1.71-.99,3.41-1.55,5.08-4.23,2.52-8.77,4.69-13.13,7.08-1.02,1.02,7.16,4.67,8.09,5.71,.72,1.03-2.26,1.82-2.94,2.29-5.M 94,2.58-11.91,5.11-18.04,7.24-.49,.19-.91,.42-.98,1.01,2.67,2.21,6.05,3.83,8.5,6.44-8.37,3.67-17.25,6.09-26,8.89-.3,.1-.43,.62-.19,.84,1.89,1.68,3.79,3.35,5.67,5.04,.7,.63,1.62,1.14,1.93,2.01-.41,.48-1.02,.67-1.66,.88-9.14,2.92-18.62,5.1-27.98,7.35-1.37,.36-.47,1.48,.15,2.07,2.12,2.43,4.48,4.52,6.32,7.18-11.82,3.53-24.24,5.13-36.43,7.33-2.46-3.3-5.18-6.46-7.55-9.81-.06-.08-.01-.21-.01-.43,11.73-2.08,23.76-3.15,35.32-6.1,.34-1.49-9.08-8.2-7.3-8.92,10.03-2.45,20.29-4.01,30.06-7.19-.22-1.02-1.19-1.5-1.87-2.14-1.42-1.3M 1-3.04-2.46-4.49-3.72-.68-.62-1.78-1.03-1.81-2.07,8.27-2.54,16.75-4.55,24.88-7.46,1.03-.37,1.2-.89,.43-1.43-2.12-1.5-4.26-2.98-6.38-4.47-.5-.36-.97-.74-1.45-1.12-.88-.92,2.95-1.56,3.55-1.96,5.3-1.87,10.67-3.59,15.79-5.77,.83-.35,1.63-.74,2.4-1.16,.14-.08,.2-.46,.09-.56-2.46-1.9-5.42-3.18-8.08-4.8-.46-.27-.76-.58-.72-1.16,5.71-2.42,11.5-5.11,16.83-8.16,.46-.33,1.58-.77,1.16-1.43-2.87-1.62-5.94-2.96-8.9-4.42-.31-.15-.31-.66-.02-.85,4.02-2.54,8.15-4.93,12.2-7.43,1.03-.7,2.17-1.16,2.84-2.25-3.29-1.76-6.96-2.73-10.24-4.M 42,.5-1.12,1.67-1.54,2.54-2.19,.89-.65,1.86-1.24,2.77-1.88,2.93-1.91,5.4-4.18,8.3-6.16,.81,.28,1.62,.55,2.42,.82Z"/><path class="cls-2" d="M1303,284.44c.53-.22,.72-.63,.81-1.05,1.34-5.71,2.7-11.41,3.93-17.14,.57-1.73,3.63-.6,5.04-.71,21.34,2.2,42.64,4.73,63.88,7.7,3.18,.44,6.36,.92,9.53,1.39,.69,.1,1.15,.55,1.19,1.13,.13,6.35,0,12.7,.03,19.06,0,.63,.16,1.3-.48,1.88-18.24-2.25-36.39-6-54.72-8.01-5.44-.72-10.89-1.43-16.34-2.11-3.32-.42-6.66-.79-9.99-1.18-1.08-.12-2.12-.31-2.9-1l.02,.05Z"/><path class="cls-2" d="M138.M 02,1155.09c-1.53,5.89-2.87,11.82-4.13,17.75-.28,1.74-1.05,1.73-2.61,1.63-25.75-2.29-51.37-5.63-76.94-9.36-.67-.87-.54-1.84-.57-2.86,.02-5.59,.06-11.18,.1-16.78-.11-2.93,1.14-2.14,3.37-2,16.62,2.67,33.22,5.43,49.93,7.54,8.89,1.19,17.79,2.26,26.7,3.32,1.46,.17,2.95,.26,4.28,.85,0,0-.12-.1-.12-.1Z"/><path class="cls-2" d="M167.88,1001.77c.78-5.56,1.6-11.11,2.41-16.66,.11-.67,.3-1.48,1.22-1.33,31.21,9.08,62.97,17.28,95.03,23.81l-.1-.08c-.99,5.47-2.79,10.82-4.05,16.25l.13-.07c-31.84-6.17-63.67-12.94-94.74-22.01l.1,.08Z"M /><path class="cls-2" d="M161.38,1039.29c1.58-6.15,2.49-12.57,3.26-18.87l-.12,.12c30.82,7.29,61.77,14.05,93.13,19.4l-.09-.1c-1.25,5.46-3.33,10.81-4.86,16.24l.14-.08c-30.8-3.61-61.25-10.51-91.53-16.8l.07,.09Z"/><path class="cls-2" d="M1199.82,1327.52c-1.65,14.47-2.68,28.99-4.52,43.44-.4,3.54-.76,7.08-1.17,10.62-.16,1.39-.41,2.77-.64,4.16-.07,.42-.58,.74-1.12,.78-7.81,.18-15.62,0-23.43,.03-.84-.13-2.46,.17-2.89-.65-.06-.53-.08-1.08,0-1.61,3.09-20.61,5.63-41.29,7.99-61.99l-.12,.11c8.64,1.81,17.46,3.08,26,5.19l-.08-.08M Z"/><path class="cls-2" d="M266.08,117.79c-.16-.46-.58-.7-1.13-.8-7.33-1.37-14.66-2.79-21.98-4.21-.8-.15-1.89-.5-1.78-1.45,.73-11.08,1.85-22.13,3.11-33.17,.88-7.83,1.81-15.65,2.73-23.47,0-1.36,1.33-1.51,2.48-1.48,7.41,0,14.82,.02,22.23,.03,3.76-.19,2.85,1.04,2.64,3.95-1.78,13.16-3.8,26.29-5.36,39.48-.5,4.18-.99,8.36-1.47,12.54-.46,2.89-.06,5.92-1.51,8.6,0,0,.04-.01,.04-.01Z"/><path class="cls-2" d="M241.47,1089.6c-27.16-2.22-54.14-7.06-81-11.59-1.58-.27-3.14-.59-4.71-.9-.43-.08-.92-.63-.87-.98,.97-6.09,2.21-12.14,3M .29-18.21l-.13,.11c29.52,5.69,59.17,11.1,89.08,14.87l-.1-.1c-1.53,5.69-3.86,11.25-5.67,16.89l.11-.09Z"/><path class="cls-2" d="M747.01,609.29c-3.24-.4-6.47-1.46-9.69-2.12-.32-.08-.55-.42-.85-.67,2.81-4.45,6.53-8.13,9.48-12.5-2.57-1.39-5.45-1.84-8.19-2.8-.53-.16-.93-.42-1.21-.92,3.11-4.13,7.04-7.92,10.71-11.65,.34-.34,.61-.71,.5-1.3-2.73-1.39-5.94-2.27-8.89-3.75,3.93-4.84,9.3-8.67,13.78-12.96-.08-.55-.43-.83-.92-1.07-2.52-1.24-5.03-2.51-7.54-3.76-.6-.03-.97,.28-1.31,.61-4.83,4.24-9.15,9-14.2,12.93-2.93-1.13-5.64-2.7M 3-8.63-4.01-5.01,4.46-8.44,9.77-13.25,14.43-3.04-1.2-5.88-2.58-8.69-4.16,3.69-4.98,8.01-9.27,12.01-14,.86-.98,1.26-.97,2.65-.21,2.01,1.09,4.02,2.16,6.05,3.22,.72,.38,1.28,.31,1.76-.19,4.21-4.55,8.76-8.77,13.35-12.96,.48-.45,1.16-.49,1.82-.14,2.37,1.23,4.69,2.54,7.09,3.73,1.24,.6,2.07-.55,2.97-1.16,4.89-3.87,10.01-7.48,14.76-11.49-.06-.2-.03-.49-.19-.59-2.73-1.6-5.2-3.67-8.11-4.93-6.27,3.92-11.66,9.16-17.54,13.58-2.31-1.15-6.22-3.48-7.78-4.65-.28-.21-.36-.66-.16-.88,5.36-4.86,10.88-9.69,16.93-13.89,3.15,1.36,5.54,3.M 72,8.55,5.47,6.73-4.4,13.18-8.97,20.08-13.05,2.12,1,5.38,3.33,8.5,6.07-6.31,4.15-12.98,7.88-19.16,12.31,.24,.37,.34,.72,.62,.89,2.43,1.53,5.09,2.76,7.4,4.47,.14,.11,.22,.46,.12,.54-4.79,3.65-9.88,6.99-14.44,10.81-.48,.55-2.13,1.28-1.16,2.05,2.66,1.25,5.35,2.45,7.95,3.81,.26,.13,.31,.67,.08,.87-4.46,4.09-9.36,7.67-13.49,12.1,3.07,1.55,6.48,2.3,9.4,3.67,.09,.73-.43,1.1-.83,1.51-3.52,3.74-7.35,7.1-10.6,11.08,13.98,5.64,12.31-.8,.26,15.65Z"/><path class="cls-2" d="M817.23,696.61l.09,.03s0,.02,0,.03l-.08-.06Z"/><path clM ass="cls-2" d="M849.7,657.17s-.02,.07-.03,.11c-.03-.01-.07-.03-.1-.05l.13-.06Z"/><path class="cls-2" d="M856.28,660.81c-2.2-1.18-4.4-2.35-6.61-3.53-1.84,3.03-3.98,6-5.87,9.04-.36,.56-.97,.7-1.67,.38-3.67-1.48-7.59-3.94-11.33-4.9-.78,.32-.95,1-1.22,1.57-1.19,2.51-2.32,5.05-3.46,7.58-.24,.51-.47,1.01-1.36,1.23-15.24-5.06-10.26-7.44-15.61,7.65,.03,.01,.06,.02,.09,.04h.01c4.03,1.52,8.12,2.88,12.12,4.51-2.04,3.78-2.37,8.29-4.05,12.26,3.89,1.2,7.38,2.94,11.1,4.44,.31,.12,.89-.07,.99-.34,1.21-3.18,2.15-6.44,3.27-9.65,.4-1M .14,1.03-1.31,2.39-.66,3.1,1.48,6.16,3.06,9.2,4.67,.54,.28,1.11,.15,1.3-.29,1.44-3.61,3.5-6.98,4.73-10.67-.01,.02-.02,.03-.03,.05-.39-.05-.68-.01-.88-.11-3.61-1.88-7.21-3.78-10.81-5.67-.43-.23-.61-.71-.4-1.16,1.42-3.13,2.91-6.25,4.78-9.23,.11-.17,.4-.27,.68-.44,3.55,1.58,6.83,3.55,10.3,5.38,1.2-3.82,2.37-7.67,3.49-11.51-.38-.22-.76-.43-1.15-.64Zm-18.85,17.83c-1.45,3.45-2.64,6.97-4.19,10.48-1.67-.05-2.76-.92-4.03-1.44-2.58-1.09-5.13-2.27-7.73-3.31-.06-.29-.21-.61-.12-.86,1.2-3.3,2.43-6.59,3.69-9.88,.11-.28,.45-.5,.7M 4-.82,4.03,1.53,7.87,3.27,11.53,5.09,.06,.33,.18,.56,.11,.74Z"/><path class="cls-2" d="M862.21,643.86c-.49,1.97-1,3.94-1.53,5.92-1.01-.58-1.98-1.24-2.92-1.89,1.31-1.54,2.83-2.83,4.45-4.03Z"/><path class="cls-2" d="M866.29,626.06c-.81,3.95-1.69,7.91-2.63,11.88-2.92-1.9-6.41-3.2-9.08-5.41,2.71-2.15,3.82-2.76,11.63-6.47,.03,0,.06-.01,.08,0Z"/><path class="cls-2" d="M150.95,1096.03c27.85,4.91,55.97,8.17,84.08,11.15-1.99,5.23-4.43,11.77-6.61,17.43l.12-.07c-27.37-1.76-54.62-5.35-81.8-9.06l.12,.11c1.46-6.53,2.32-13.23,4.2M 1-19.65,0,0-.12,.1-.12,.1Z"/><path class="cls-2" d="M1313.16,244.77c-.19-1.62,.51-3.15,.85-4.71,1.23-5.09,2.27-10.28,3.87-15.27l-.08,.07c6.25-.6,12.58,.63,18.85,.92,16.06,1.15,32.08,2.61,48.09,4.27,1.21,.16,2.92,.16,2.72,1.72,.02,3.44,.02,6.88,.01,10.32,0,2.9-.02,5.8-.03,8.71,0,.53,.02,1.07-.52,1.54-12.5-.96-24.96-2.98-37.46-4.15-12.1-1.39-24.34-1.89-36.4-3.52l.1,.09Z"/><path class="cls-2" d="M123.43,1214.96c-21.71-.31-43.77-3.21-65.45-5.06-1.66-.26-4.7,.18-4.42-2.17,0-1.94,.05-3.88,.06-5.81,.02-4.2,.03-8.4,.06-12.M 6,0-.63-.08-1.3,.69-1.86,22.35,2.55,44.74,5.25,67.19,6.94,1.74,.15,3.48,.28,5.22,.46,1.26,.13,1.59,.52,1.39,1.53-1.51,6.22-2.75,12.57-4.79,18.64l.08-.07Z"/><path class="cls-2" d="M1332.76,1370.74c.15-5.16-.05-10.35,.34-15.5,.63-1.09,2.6-.26,3.63-.24,7.2,1.38,14.35,2.96,21.56,4.26,2.69,.67,2.13-1.76,2.19-3.46,.02-7.43-.27-14.87-.04-22.29,.02-.42,.69-.74,1.18-.56,3.43,1.25,6.85,2.52,10.28,3.77,4.78,1.74,9.57,3.47,14.35,5.2,.96,.35,1.42,.92,1.41,1.77-.01,1.94,.01,3.88,.01,5.82,0,4.2,0,8.4,0,12.6-.13,.88,.34,2.42-1,2.4M 3-8.19-1.1-16.26-3.02-24.39-4.48-1.15-.22-1.67,.15-1.72,1.19-.07,8.08-.01,16.16-.12,24.24,.11,1.74-1.71,1.68-3.1,1.65-7.28,0-14.56-.02-21.84-.03-1-.04-2.74,.14-2.83-1.18-.15-5.06,.07-10.12,.09-15.19h0Z"/><path class="cls-2" d="M1349.41,96.78c-12.27-.05-24.53,.75-36.79,.43,0-.35-.11-.7,.02-.97,2.92-6.36,5.9-12.7,8.77-19.08,1.32-2.41-1.29-1.85-2.81-1.94-8.35,.12-16.7,.25-25.05,.36-.82-.15-3,.37-2.92-.84,4.59-7.32,9.1-14.75,14.04-21.85,8.48-.33,16.97-.04,25.46-.13,2.83-.12,1.62,1.18,.99,2.91-2.56,5.78-5.13,11.56-7.7,1M 7.34-1.1,1.99-.17,2.04,1.68,2.03,9.96-.16,19.95-.04,29.9-.35l-.13-.09c-.65,6.06-2.84,11.98-4.07,17.98-.42,1.47-.38,3.1-1.48,4.27l.1-.07Z"/><path class="cls-2" d="M740.58,623.02c-.18-.55,.07-1.04,.32-1.54,2.04-4.06,4.07-8.12,6.11-12.19l-.09,.06c3.48,1.08,7.19,1.81,10.65,2.68,.35-.18,.64-.26,.78-.42,3.09-3.53,6.17-7.06,9.24-10.6,.86-1.02-.91-1.4-1.68-1.61-2.57-.78-5.31-1.43-7.8-2.38-.33-.58,.07-.91,.37-1.22,3.26-3.62,7.02-7.08,10.58-10.46-.14-.62-.64-.81-1.1-.97-2.85-1.03-5.68-1.92-8.51-3.06,.27-1.23,1.4-1.79,2.26-2.M 62,3.35-2.8,6.71-5.6,10.07-8.39,.46-.38,1-.73,.93-1.47-2.81-1.27-5.95-2.34-8.69-3.9-.16-.09-.25-.42-.17-.56,4.74-4.32,10.57-7.58,15.69-11.46-.01-.6-.34-.89-.82-1.14-1.92-1-3.84-2-5.74-3.01-.52-.41-1.94-.73-1.67-1.53,5.7-4.53,12.57-7.78,18.74-11.59,.37,.07,.68,.07,.87,.18,2.74,1.86,5.98,3.25,8.42,5.43-.34,.65-1.13,.9-1.78,1.27-5.42,3.2-11.02,6.14-16.34,9.49-.4,.28-.34,.83,.16,1.1,2.7,1.4,5.42,2.8,8.08,4.27,.59,.74-1.24,1.41-1.72,1.86-4.41,2.67-8.49,5.65-12.61,8.59-.49,.35-.99,.69-1.22,1.3,3.01,1.66,6.53,2.58,9.44,4.M 25-.13,.79-.83,1.16-1.41,1.59-3.66,2.71-7.23,5.49-10.55,8.46-1.85,1.58-.72,1.75,.94,2.38,2.34,.82,4.7,1.61,7.05,2.42,.66,.23,.79,.84,.29,1.32-3.62,3.57-7.52,6.69-10.89,10.52,3.34,1.22,6.51,2.09,9.86,3.16,.55,.17,.78,.71,.46,1.06-3.18,3.54-6.57,6.79-9.4,10.62,3.61,1.43,7.56,1.81,11,3.19,.22,.48,.04,.86-.18,1.26-1.37,2.46-2.73,4.92-4.08,7.38-.49,1.24-2.5,3.36-.16,3.84,3.47,.83,6.9,1.81,10.33,2.76l-.1-.11c-1.71,3.74-3.5,7.45-5.16,11.21-.33,.69-1.43,.63-2.11,.47-3.23-.84-6.57-1.19-9.7-2.38,.99-4.07,3.01-7.81,4.77-11.64M ,.28-1.16-1.93-1.09-2.68-1.45-2.85-.66-5.7-1.29-8.55-1.94,1.31-4.09,3.86-7.76,5.73-11.64,.19-.36-.13-.94-.59-1.06-3.06-.78-6.13-1.56-9.2-2.32-.72-.18-1.29,.07-1.6,.66-1.57,2.96-3.11,5.93-4.66,8.9-.67,.97-.75,2.7-2.2,2.79-3.4-.4-6.76-1.34-10.14-1.95l.16,.13Z"/><path class="cls-2" d="M189.3,102.26c-.68-.5-.54-1.39-.57-2.14,.18-4.31,.37-8.61,.57-12.92,.47-7.42,.87-14.85,1.33-22.27,.27-3.65,.41-7.33,.84-10.96,.27-1.06,1.77-.92,2.65-.97,7.68,.01,15.37,.04,23.05,.07,.75-.05,1.6,.15,1.89,.87-.77,11.35-2.08,22.78-2.79,34.1M 7-.43,5.7-.83,11.4-1.26,17.1-.05,.63,.02,1.31-.71,1.8-8.4-1.24-16.63-3.52-25.07-4.79-.02-.01,.06,.06,.06,.06Z"/><path class="cls-2" d="M1252.55,1337.94c-.5,.55-.56,1.2-.6,1.85-.11,1.94-.22,3.87-.28,5.81-.24,7.97-.81,15.92-1.4,23.88-.28,5.27-.65,10.54-1.05,15.81-.05,.53-.24,1.21-.85,1.33-8.04,.51-16.15,.02-24.22,.16-1.04,0-2.66,0-2.57-1.36,.53-9.04,1.67-18.04,2.34-27.07,.83-8.46,.78-17.07,2.06-25.45,8.95,1.16,17.78,3.61,26.7,5.16,0,0-.13-.1-.13-.1Z"/><path class="cls-2" d="M1244.37,241.5c22.97,.28,45.86,2.13,68.79,3M .27l-.1-.09c-1.62,6.43-3.24,12.86-4.89,19.28-.46,1.77-4,.56-5.41,.72-2.68-.2-5.36-.43-8.03-.66-17.81-1.69-35.67-2.55-53.54-3.27-1.18-.29-5.49,.37-4.85-1.49,2.72-5.91,4.91-12.22,8.14-17.84l-.11,.07Z"/><path class="cls-2" d="M196.62,1198.39c-12.23-.58-24.49-.83-36.72-1.49-5.51-.27-11.02-.66-16.52-1.01-4.43-.29-8.86-.61-13.29-.92-1.35-.07-1.27-1.1-1.05-2.01,1.39-5.59,2.78-11.19,4.18-16.78,.14-.55,.47-1.15,1.15-1.18,9.41,.32,18.76,1.47,28.15,2.04,13.95,1.17,27.95,1.44,41.91,2.35,.8,.21,.66,1.1,.36,1.67-2.38,5.38-4.77,1M 0.75-7.16,16.13-.23,.51-.49,1-1.15,1.28-.01,0,.12-.06,.12-.06Z"/><path class="cls-2" d="M112.37,1257.38c-.33-.16-.66-.43-1-.45-2.82-.17-5.65-.29-8.47-.43-13.58-.64-27.17-1.23-40.75-2.07-1.88-.11-3.75-.32-5.63-.42-3.38-.19-3.39-.21-3.37-2.8,.05-5.6,.09-11.2,.14-16.8,.06-1.09-.2-2.62,1.45-2.54,3.36,.12,6.71,.44,10.06,.71,17.16,1.54,34.36,2.54,51.57,3.33,1.3,.08,1.76,.47,1.58,1.39-.57,2.88-1.37,5.71-2.09,8.56-.78,3.06-1.57,6.12-2.32,9.18-.21,.86-.48,1.68-1.23,2.35,0,0,.06-.02,.06-.02Z"/><path class="cls-2" d="M1194.07M ,366.88c.24,.66-.03,1.27-.23,1.9-1.44,5.02-3.57,9.91-4.51,15.03l.09-.09c-26.35-3.7-52.84-6.69-79.4-8.33,2.15-5.21,4.59-10.31,6.56-15.59l-.1,.05c25.96,1.79,51.91,3.86,77.73,7.14l-.15-.12Z"/><path class="cls-2" d="M331.12,1064.38c-1.6,5.36-4.4,10.4-6.45,15.63l.11-.07c-25.97-1.78-51.94-3.66-77.75-7.14l.1,.1c1.94-5.62,3.42-11.42,5.7-16.91l-.14,.08c26,4.26,52.29,6.46,78.55,8.42l-.13-.12Z"/><path class="cls-2" d="M1183.54,399.84c.03,.42,.18,.87,.07,1.26-1.31,4.73-2.66,9.45-4.01,14.16-.54,1.84-4.35,.12-5.77,.09-24.88-4.32M -49.97-8.24-75.16-10.29l.13,.08c1.87-4.99,3.43-10.1,5.55-15,26.57,2.32,53.03,5.89,79.36,9.81l-.17-.12Z"/><path class="cls-2" d="M1322.73,204.02c-1.51,6.97-3.58,13.84-4.93,20.84l.08-.07c-7.5-1.31-15.32-.86-22.92-1.44-13.06-.52-26.12-1.09-39.19-1.2-2.45-.09-2.84-.03-1.7-2.5,2.69-5.86,5.53-11.66,8.09-17.58l-.09,.06c20.21,.86,40.65,.1,60.75,1.98l-.1-.09Z"/><path class="cls-2" d="M179.17,1237.68c-19.76-.78-39.58-.45-59.33-1.69-1.3-.07-1.29-1.1-.94-2.02,1.47-6.34,3.54-12.57,4.51-19.01l-.08,.06c21.14,2.05,42.62,1.92,63.88M ,2.69,.31,.02,.73,.45,.63,.68-2.74,6.52-6.2,12.76-8.77,19.34l.09-.06Z"/><path class="cls-2" d="M436.03,360.73c-1.33-.36-2.67-.14-3.98,0-4,.41-8.03,.37-12.05,.48-.95,.03-1.88-.02-2.73-.44-.01,0,.04,.05,.03,.04,.2-.26,.56-.5,.61-.78,.79-4.79,1.03-9.65,1.62-14.47,1.77-15.12,3.79-30.24,6.47-45.22,.1-.54,.94-.84,1.53-.83,5.52-.12,11.04-.24,16.56-.35,.78-.05,2.22,.08,2.08,.98-1.95,12.39-4.57,24.68-6.42,37.09-1.11,7.15-1.99,14.33-2.9,21.51-.1,.74-.16,1.51-.91,2.07l.09-.07Z"/><path class="cls-2" d="M1021.66,1087.36c-1.58,1M 7.38-4.25,34.64-7.09,51.85-.19,1.29-1.97,.93-2.96,1-5.38,.09-10.77,.25-16.16,.31-1.44-.08-1-1.5-.9-2.43,2.7-13.91,5.15-27.88,7.14-41.91,6.84-2.38,13.53-5.3,19.97-8.82Z"/><path class="cls-2" d="M161.4,138.76c-.07-13.73-.08-27.52,.64-41.24,.02-.41,.65-.78,1.12-.68,8.71,1.79,17.47,3.37,26.13,5.41,.01,0-.07-.06-.05-.05-.47,.28-.62,.67-.65,1.11-.14,2.25-.34,4.51-.41,6.76-.42,12.57-.57,25.15-1.02,37.72-.13,.76-1.37,.54-1.94,.24-7.93-3.17-16.06-5.96-23.89-9.35l.08,.08Z"/><path class="cls-2" d="M1192.55,222.83c19.87-.69,39M .77-1,59.65-.56,.27,1.77-1.07,3.31-1.61,4.97-2.03,4.77-4.39,9.42-6.22,14.27l.11-.08c-20.85-.39-41.72-.07-62.58,.02-.77-.28-.14-1.15,.11-1.64,3.54-5.68,7.09-11.36,10.64-17.03l-.09,.06Z"/><path class="cls-2" d="M1279.05,1301.04c.32,13.68,.05,27.54-.41,41.24-.05,.45-.62,.79-1.11,.69-8.37-1.5-16.65-3.43-24.99-5.03,0,0,.13,.1,.13,.11-.58-.67-.42-1.44-.4-2.19,.13-4.74,.31-9.48,.43-14.21,.32-9.9,.3-19.82,.8-29.71,.19-.59,1.22-.41,1.7-.19,8.05,2.97,15.97,6.21,23.94,9.37l-.08-.07Z"/><path class="cls-2" d="M646.67,818.15l-.0M 3,.03s-.05,.01-.07,.01l.1-.04Z"/><path class="cls-2" d="M649.88,832.75c.52,4.02,.82,8.09,.9,12.19-.7,.62-1.55,1.26-2.26,1.78-3.64-.59-6.97-2.44-10.51-3.52-.46-.17-.61-.82-.27-1.11,1.39-1.18,2.8-2.33,4.18-3.52,2.08-1.93,4.48-3.64,6.3-5.79-.36-.61-.98-.8-1.6-1.01-3.19-1.23-6.64-1.74-9.56-3.53,3.45-3.28,6.55-6.48,9.58-10.06,.17-.03,.33-.02,.49,.03h0c1.13,4.39,2,8.86,2.61,13.39-.42,.3-.37,.92,.14,1.14h0Z"/><path class="cls-2" d="M670.96,824.6s-.04,.05-.06,.08c-.01-.01-.02-.01-.03-.01l.09-.07Z"/><path class="cls-2" d="MM 1281.56,161.34c-16.21,.57-32.48,1.16-48.7,1.52-1.01-.35,.28-1.6,.53-2.19,4.2-6.24,8.45-12.45,12.62-18.7l-.12,.05c9-.16,17.99-.57,26.98-.93,5.36-.36,10.74-.37,16.11-.42,.65,0,1.33-.06,1.91,.28,.28,.56-.05,1.05-.28,1.54-3.04,6.31-5.89,12.71-9.13,18.92l.07-.07Z"/><path class="cls-2" d="M449.34,412.15c-5.31,.65-10.6,1.53-15.94,1.98-1.4,.13-1.22-1.36-1.2-2.3,.73-12.79,1.43-25.6,2.94-38.33,.41-3.75,.83-7.5,1.23-11.25,.06-.53,.13-1.07-.34-1.53-.01,0-.1,.08-.1,.08,5.64-1.28,11.84-.51,17.38-2.42,.61-.2,1.75-.62,1.96,.25-2.2M 5,17.81-5.32,35.63-6.02,53.58l.07-.06Z"/><path class="cls-2" d="M990.94,1027.81s.03,.03,.04,.05c-.04,.01-.09,.03-.13,.03,.02-.03,.07-.06,.09-.08Z"/><path class="cls-2" d="M1008.28,1027.59c-.19,6.79-.83,13.56-1.3,20.34-5.75,3.67-11.92,6.65-18.45,8.94,.86-6.36,1.39-12.76,2-19.14,.26-2.79,.5-5.58,.75-8.37,.04-.52,.04-1.03-.3-1.5,5.39-1.14,10.97-1.86,16.46-2.19,.96,.14,.82,1.21,.84,1.92Z"/><path class="cls-2" d="M90.76,1343.29c-1.36-.59-2.89-.33-4.34-.4-9.57-.04-19.14-.05-28.71-.09-5.56-.19-4.99,.35-4.98-4.06,.13-5.81-M .14-11.65,.29-17.44,.45-1.14,2.21-.59,3.2-.73,6.06,.11,12.12,.25,18.19,.33,7.54,.26,15.13-.22,22.63,.41,0,0-.09-.05-.08-.04-.58,.35-.73,.89-.86,1.4-1.97,6.85-3.06,14.01-5.45,20.7l.11-.08Z"/><path class="cls-2" d="M1349.31,96.84c12.37,.12,24.75-.14,37.12,.23,1.2,.1,1.16,1.22,1.18,2.1,0,6.02-.03,12.04-.05,18.07,.03,.73-.1,1.72-.95,1.89-13.97,.01-27.97-.55-41.95-.38l.15,.12c-.27-.51-.22-1.05-.09-1.58,1.42-6.85,4.06-13.57,4.7-20.52l-.1,.07Z"/><path class="cls-2" d="M987.92,363.09c20.25-1.6,40.49-3.31,60.81-3.87l-.16-.0M 8c-2.41,4.77-4.65,9.63-7.23,14.32-19.56,1.02-39.21,1.52-58.74,3.44-.78,.06-1.32-.44-1.05-1,2.07-4.32,4.27-8.59,6.44-12.87l-.08,.06Z"/><path class="cls-2" d="M80.48,79.91c-.47-8.03-.07-16.12-.19-24.17-.16-3.09,.55-2.98,3.42-2.95,6.99,0,13.99,0,20.98,.02,1.67,.05,3.55-.3,3.31,2.05-.16,9.88,.07,19.79-.32,29.66-.28,1-1.97,.6-2.78,.5-8.11-1.85-16.56-2.83-24.48-5.18l.08,.07Z"/><path class="cls-2" d="M415.36,463.94c-.89-14.74-.8-29.49-.79-44.25,0-1.17-.1-2.36,.31-3.58,5-1,10.15-.93,15.23-1.47,.55-.02,1.47-.03,1.71,.54-.3,M 15.59-.66,31.22-.38,46.82l.09-.07c-4,1.13-8.26,1.29-12.37,1.93-1.28,.15-2.6,.43-3.9,0l.09,.08Z"/><path class="cls-2" d="M474.26,1010.7c1.27,3.76,1.53,7.95,1.91,11.91,.02,.55-.14,1.04-.67,1.43,0,0,.09-.06,.08-.05-6.1-.28-12.31,.67-18.45,.72-13.4,.48-26.84,.64-40.24,.26l.11,.09c-.7-4.54-.54-9.19-1.63-13.65l-.13,.1c19.71-.05,39.52,1,59.18-.67l-.15-.13Z"/><path class="cls-2" d="M964.38,416.15c19.92-1.71,40.02-1.89,60-1.32l-.11-.09c.98,4.49,.33,9.24,1.64,13.65l.13-.1c-19.05-.16-38.11-.66-57.16,.22-.79-.06-2.08,.16-2.43-M .71-.91-3.86-.85-7.94-1.92-11.78l-.14,.12Z"/><path class="cls-2" d="M90.65,1343.37c2.41-1.01,5.32-.26,7.9-.52,7.51-.12,15.01-.26,22.52-.38,1.88-.03,3.75-.05,5.63-.04,1.15,0,1.87,.24,1.36,1.33-3.01,6.85-6.74,13.52-9.3,20.51l.13-.07c-.55,.39-1.23,.37-1.9,.39-9.55,.16-19.1,.44-28.65,.39-.72-.09-2.16,.16-2.27-.82,.91-7.06,3.83-13.87,4.7-20.88,0,0-.12,.09-.12,.09Z"/><path class="cls-2" d="M80.4,79.84c-.27,8.28-.07,16.56-.05,24.85-.05,2.06,0,2.7-2.28,1.9-8.51-3.24-17.18-6.07-25.61-9.51-.35-6.57-.05-13.15-.14-19.73,0-.82-M .1-2.05,1.01-2.14,9.12,1.01,18.04,3.85,27.15,4.7l-.08-.07Z"/><path class="cls-2" d="M118.76,1364.27c9.72,.64,19.64-.28,29.42-.17,2.04,.03,2.46,.28,1.21,2.14-4.29,6.7-8.59,13.4-12.9,20.09-.52,.91-1.85,.84-2.82,.86-8.18-.15-16.42,.43-24.57-.15-.54-.22-.43-.99-.25-1.43,3.08-6.88,6.18-13.76,9.29-20.63,.13-.28,.47-.51,.72-.77,.01,0-.12,.07-.12,.07Z"/><path class="cls-2" d="M85.23,1365.49c-.62,4.99-2.25,9.88-3.29,14.81-.59,2.07-.83,4.3-1.68,6.28-.56,.68-1.67,.66-2.5,.68-7.52,0-15.05,0-22.57,0-1.45-.01-2.97,0-2.84-1.87,.0M 3-6.23,.07-12.46,.11-18.68-.14-1.92,1.65-1.58,3.01-1.66,9-.02,18-.03,27-.02,.91,0,1.89-.19,2.75,.47Z"/><path class="cls-2" d="M1354.98,74.68c1.94-5.74,2.98-11.81,4.33-17.71,1.22-4.75,0-4.2,6.17-4.22,6.33-.02,12.66,0,19,0,1.26,.12,3.32-.4,3.15,1.51,0,6.25,0,12.49-.02,18.74-.05,.64-.04,1.52-.86,1.64-10.61,.2-21.29,.31-31.91-.04,0,0,.12,.09,.12,.09Z"/><path class="cls-2" d="M463.06,686.97c-4-6.21-7.22-12.95-10.93-19.35-.32-.59-.7-1.17-.44-1.84,3.12-.66,7.11-.02,10.4-.21,.52-.02,1.48,0,1.57-.64-1.64-4.45-4.1-8.6-5.97-1M 2.96-1.47-3.22-2.81-6.49-4.2-9.74-.76-1.56,1.44-1.86,2.41-2.46,3.03-1.35,5.83-3.25,8.96-4.29,.73,.23,.76,.82,.96,1.28,3.23,7.55,6.23,15.1,10.12,22.39l.05-.07c-3.37,2.1-6.8,4.13-10.51,5.85-1.16,.4-.94,1.3-.45,2.17,3.68,6.38,7,13,10.91,19.24l.15-.11c-4.29,.92-8.76,.58-13.13,.67l.08,.06Z"/><path class="cls-2" d="M729.03,620.39c3.85,.86,7.73,1.61,11.55,2.63l-.16-.13c-2.15,3.91-3.58,8.27-5.44,12.35-.12,.28-.01,.61-.01,1.01,3.67,.93,7.5,1.43,11.22,2.17-2.06,4.08-2.68,8.77-4.59,12.9-3.76,.15-7.18-.87-10.88-1.18,.7-4.36,2.M 44-8.54,3.39-12.86,.14-.55-.29-1.07-.98-1.2-3.15-.36-6.27-1.61-9.43-1.31-1.65,4.45-3.02,8.91-4.24,13.4-3.34,.1-6.6-.95-9.92-1.3-.47-.07-1.11,.29-1.21,.67-1.33,4.51-2.05,9.11-3.46,13.59-3.45-1.02-7.07-1.3-10.6-1.96,1.54-4.68,2.1-9.64,3.86-14.23,3.29,.03,6.3,1.26,9.58,1.34,.32,.01,.79-.22,.96-.45,1.29-3.46,2.26-7.1,3.46-10.62,.47-.9,.47-2.66,1.84-2.58,2.9,.44,5.79,.98,8.69,1.44,.71,.11,1.24-.21,1.48-.83,1.68-4.31,3.36-8.63,5.03-12.94l-.15,.08Z"/><path class="cls-2" d="M471.97,998.46s.04,.06,.05,.09c-.05,.01-.1,.01-.1M 5,.01l.1-.1Z"/><path class="cls-2" d="M474.26,1010.7s.11,.01,.16,.01v.12l-.16-.13Z"/><path class="cls-2" d="M496.93,1004.8c5.68,1.23,11.35,2.14,17.01,2.75-13.12,1.38-26.33,3.17-39.52,3.16,.02-2.66-.73-5.25-1.29-7.85-.31-1.44-.31-2.94-1.11-4.31,1-.05,2.01-.09,3.01-.14,7.06,2.61,14.35,4.75,21.9,6.39Z"/><path class="cls-2" d="M659.17,943.95s.04,0,.06,.01c-.04,.02-.07,.04-.11,.06,0-.02,.04-.06,.05-.07Z"/><path class="cls-2" d="M716.82,930.39c-5.9,4.99-12.37,9.26-18.62,13.82-.58,.42-1.13,.88-2.01,1.05-2.3-2.55-3.44-5.38M -6.15-7.61-7.82,4.52-15.33,9.52-23.37,13.64-.77-.03-1.12-.32-1.42-.7-1.59-1.99-3.2-3.97-4.8-5.96-.31-.4-.67-.63-1.22-.67,.58-.34,1.16-.7,1.74-1.03h0c7.54-4.16,15.04-8.4,22.26-12.87,.66-.01,1,.34,1.29,.67,1.7,1.94,3.37,3.89,5.07,5.83,.51,.51,1.13,.48,1.7,.06,6.63-4.3,12.86-9.13,19.26-13.74,.4-.28,1.16-.25,1.43,.08,1.72,2.19,3.44,4.37,5.1,6.58,.14,.18-.03,.67-.26,.85Z"/><path class="cls-2" d="M912.78,421.95h-.11s-.01-.06-.02-.09l.13,.09Z"/><path class="cls-2" d="M915.2,433.56c-12.55,1.95-25.04,4-37.42,6.81-2.48-3.43-M 5.09-6.79-7.85-10.1,14.12-3.24,28.38-6.35,42.74-8.32,.91,3.84,1.64,7.68,2.52,11.53,0,.03,0,.05,.01,.08Z"/><path class="cls-2" d="M530.87,935.77c2.56,3.01,5.12,6.02,7.68,9.02,.31,.37,.5,.74,.32,1.26-6.06,1.23-12.47,1.17-18.63,1.88-7.74,.24-15.52,1.11-23.25,.77l.09,.06c-2.48-3.43-4.97-6.85-7.45-10.28-.38-.53,.03-1.08,.8-1.12,13.52-.13,27.06-.18,40.53-1.54l-.09-.05Z"/><path class="cls-2" d="M787.33,729.68c2.76,.25,5.37,1.32,8.06,1.96,1.13,.39,3.06,1,3.14-.53,.59-3.74,1.18-7.47,1.92-11.18,.56-1.44,2.73-.19,3.8,.06,2.48M ,.84,4.94,1.69,7.41,2.53l-.09-.09c0,3.19-1.15,6.36-1.59,9.54-.37,1.28-.29,2.86-1.23,3.87-3.19-.73-5.93-2.02-9.06-2.89-.88-.28-1.51,.09-1.66,.9-.67,3.93-1.26,7.87-1.96,11.8-.09,.41-.7,.73-1.19,.59-2.52-.72-5.04-1.46-7.56-2.19-.64-.18-1.29-.3-1.99,0-1.09,3.9-1.34,8.06-2.13,12.05-.12,.65-.44,1.44-1.25,1.4-3.41-.37-6.65-2.07-10.09-1.96,.71-.96,.75-2.05,.9-3.11,.53-3.74,1.08-7.47,1.62-11.21,15.3,2.35,9.2,5.41,13.04-11.64l-.1,.1Z"/><path class="cls-2" d="M704.24,914.84c-.27,.37-.41,.69-.68,.9-6.28,4.67-12.58,9.52-19.46,1M 3.54-.34,.05-.81,.07-1.09-.19-2.06-2.09-4.75-3.8-6.44-6.14-.05-.52,.48-.74,.88-1,6.24-4.03,12.44-8.13,18.34-12.62,.41-.3,.4-.86-.01-1.15-2.28-1.66-4.69-3.19-6.88-4.97-.13-.11-.15-.45-.03-.58,2.68-2.45,5.8-4.48,8.59-6.81,2.57-2.05,5.02-4.2,7.57-6.26,.83-.66,1.72-.06,2.45,.39,5.21,3.1,6.52,3.99,6.27,4.35-4.78,5.15-10.75,9.34-16.24,13.85-.37,.32-.38,.84,.02,1.16,2.26,1.82,4.58,3.55,6.71,5.53Z"/><path class="cls-2" d="M729.44,905.99c1.09-.32,1.6-.98,2.18-1.57,3.76-3.8,7.51-7.6,11.26-11.4,.75-.76,1.5-1.51,2.3-2.24,.12-.M 11,.47-.08,.72-.07,2.09,1.68,3.87,3.88,5.83,5.75,.34,.34,.3,.8-.08,1.18-4.84,4.9-9.68,9.8-14.53,14.69-.38,.37-1.03,.92-1.59,.61-1.68-1.46-2.84-3.39-4.33-5.03-1.28-1.5-1.66-1.45-2.95-.25-5.03,4.78-10.48,9.32-15.97,13.7-.43,.33-1.11,.34-1.42,.02-1.98-2.03-3.94-4.07-5.89-6.08,.08-.25,.07-.51,.22-.63,5.85-4.58,11.31-9.62,16.96-14.27,.22-.07,.61-.1,.74,0,2.32,1.69,4.56,3.57,6.55,5.59Z"/><path class="cls-2" d="M609.5,986.84l-.1,.09s-.02-.03-.03-.05c.04-.01,.09-.03,.13-.04Z"/><path class="cls-2" d="M725.85,587.43c3.15,.89M ,6.23,1.92,9.27,3.02,.28,.16,.32,.29,.56,.59-3.14,4.17-6.85,8.44-9.85,12.69,.34,.57,.75,.82,1.28,.96,2.68,.69,5.38,1.3,8.03,2.1,.32,.09,.56,.54,.43,.8-2.17,4.27-4.35,8.54-6.53,12.8l.15-.08c-3.59-.2-7.01-1.88-10.59-1.84,1.26-4.57,3.81-8.68,6.05-12.9,.21-.37,.55-.74,.22-1.21-2.83-1.67-6.59-1.57-9.45-3.24,3.18-4.84,7.08-9.12,10.55-13.75l-.11,.08Z"/><path class="cls-2" d="M786.61,633.33c1.25-2.95,3.12-5.68,4.81-8.48,2.2-3.64,2.64-3.13-2.17-4.53-2.41-.87-5.27-1.04-7.44-2.36,1.82-3.18,7.12-8.03,9.75-10.6,4.07,.95,8.29,2.M 3,12.08,4.05l-.14-.16c-8.54,8.26-8.64,8.37-9.43,10.36,13.94,5.46,13.28,.42,5.36,14.02-.43,.92-1.47,.84-2.29,.53-3.55-.98-7.1-1.96-10.64-2.94l.1,.11Z"/><path class="cls-2" d="M628.79,798.7s.08,.03,.12,.05c-.01,.02-.03,.05-.04,.07l-.08-.12Z"/><path class="cls-2" d="M634.4,814.26c.07,.01,.13,.01,.2,.01l-.06,.09-.14-.1Z"/><path class="cls-2" d="M646.61,818.13s.04,0,.06,.02l-.1,.04s.03-.04,.04-.06Z"/><path class="cls-2" d="M646.98,817.61c-.12,.18-.24,.35-.37,.52-4.02-1.22-7.95-2.87-12.01-3.86q5.9-9.45,6.34-11.4c-3.95-1.M 42-8.18-2.48-12.03-4.12,1.89-3.15,3.44-6.44,5.08-9.72,.2-.39,.36-.85,.85-1.07,2.65,4.6,4.99,9.38,7.01,14.3-.04,.31,.07,.61,.33,.79,1.9,4.73,3.51,9.59,4.8,14.56Z"/><path class="cls-2" d="M643.34,973.91s.05-.01,.08-.02c.02,.02,.03,.05,.05,.07l-.13-.05Z"/><path class="cls-2" d="M666.55,952.42c1.49,1.77,3.93,5.61,5.07,7.97-9.08,4.87-18.41,9.92-28.2,13.5-1.67-2.14-2.89-4.55-4.33-6.84,1.74-1.55,3.46-3.16,5.13-4.82,6.7-2.89,13.2-6.04,19.59-9.36,.84-.35,1.92-1.32,2.74-.45Z"/><path class="cls-2" d="M671.71,960.34l-.03,.03s-M .05,.04-.05,.04c0-.01-.01-.01-.01-.02,.02,0,.05-.02,.07-.04,.01,0,.01-.01,.02-.01Z"/><path class="cls-2" d="M626.45,670.14c1.5-4.94,2-10.29,4.14-14.98l-.18,.12c2.79,1.49,5.58,2.98,8.62,4.12,.21,.08,.52,.01,.92,.01,1.2-4.6,2.45-9.22,3.74-13.8,.07-.26,.68-.52,.95-.42,2.9,1.1,5.74,2.3,8.48,3.55,.24,1.07-.13,2-.35,2.94-.95,4-1.9,8-2.85,12-3-.78-5.85-2.09-8.75-3.17-.62-.23-1.43,.07-1.56,.6-.37,1.47-.73,2.93-1.06,4.41-.59,2.63-1.15,5.26-1.72,7.9-.17,.78-.79,1.01-1.74,.64-2.94-1.24-5.79-2.66-8.7-3.98l.07,.06Z"/><path clasM s="cls-2" d="M817.23,696.61c-.34,3.9-1.81,7.8-2.56,11.69-.1,.41-.76,.71-1.24,.56-3.23-1.06-6.44-2.13-9.71-3.04-.64-.07-.89,.67-.97,1.17-.59,3.18-1.15,6.37-1.74,9.55-.22,.71-.27,1.69-1.16,1.87-3.67-.87-7.32-2.11-10.98-3.1l.15,.11c1.5-4.26,1.01-8.8,2.8-13.01,3.59,.48,6.83,1.96,10.36,2.64,.26,.05,.83-.27,.92-.51,1-3.29,1.41-6.76,2.21-10.12,.2-.72,.45-1.77,1.45-1.6,3.65,1.05,7.25,2.21,10.57,3.84l-.08-.06Z"/><path class="cls-2" d="M979,733.46c4.12,6.46,8.61,12.71,11.97,19.54,.1,.24-.1,.46-.39,.45-4.41,.06-8.76-.65-13.17M -.62l.09,.06c-3.68-6.6-8.2-12.74-12-19.24,1.54-.72,3.15-.53,4.79-.59,2.94,.09,5.88,.13,8.8,.46l-.09-.07Z"/><path class="cls-2" d="M449.49,705.17c1.39,.22,2.78,.39,4.17,.54-1.66,.9-3.31,1.83-4.93,2.79-1.23-2.14-3.43-3.91,.76-3.33Z"/><path class="cls-2" d="M459.82,724.42s.01,.01,.01,.02l-.04-.02h.03Z"/><path class="cls-2" d="M461.47,706.35h-.04s-.03-.04-.04-.06l.08,.06Z"/><path class="cls-2" d="M461.43,706.29s.03,.04,.04,.06l-.08-.06h.04Z"/><path class="cls-2" d="M463.06,686.97h-.06l-.03-.06,.09,.06Z"/><path class="cM ls-2" d="M469.8,698.08c-3.61,1.47-7.16,3.07-10.65,4.79-3.23-4.9-6.3-9.86-9.22-14.89-.55-.97-.74-1.81,.72-1.75,4.14,.11,8.21,.73,12.35,.74,2.11,3.77,4.42,7.45,6.8,11.11Z"/><path class="cls-2" d="M702.58,555.4c-4.47,4.82-8.53,9.93-12.65,14.92-.12,.11-.55,.13-.72,.05-2.45-1.31-4.8-3.13-7.02-4.59,0-.37-.1-.63,.01-.79,3.94-5.05,7.71-10.47,12.38-15.01,.43-.21,1.04-.03,1.4,.26,2.16,1.76,4.79,3.06,6.59,5.16Z"/><path class="cls-2" d="M692.21,862s-.04,.03-.06,.04c-.01,0-.01-.01-.02-.01,0,0,.01,0,.01-.01,.02,0,.05-.02,.07-.02M Z"/><path class="cls-2" d="M701.25,866.08c-.03,.19,.02,.44-.11,.56-3.74,3.71-7.57,7.35-11.7,10.78,.95-4.98,1.65-9.96,2.11-14.92,.17-.18,.39-.32,.6-.46,2.12,1.14,4.55,1.84,6.77,2.83,.8,.36,1.82,.48,2.33,1.21Z"/><path class="cls-2" d="M788.86,715.32c.45,1.39,.03,2.77-.16,4.14-.38,3.41-1.2,6.79-1.37,10.22l.1-.1c-3.72-1.07-7.6-2.11-11.48-2.49,3.73-15.49-2.76-15.13,13.06-11.66l-.15-.11Z"/><path class="cls-2" d="M1228.38,910.98c-.05,.07-.09,.19-.14,.19-.31,0-.28-.04,.09-.09,0-.01,.05-.1,.05-.1Z"/><path class="cls-2" d="MM 1279.81,881.08v-.2s.02,.17,0,.2Z"/><path class="cls-2" d="M1240.27,858.9s.12-.06,.12-.06c0,0-.12,.06-.12,.06Z"/><path class="cls-2" d="M481.61,853.12l.15,.02c-.08-.1-.05-.11-.15-.02Z"/><path class="cls-2" d="M248.66,642.99l.11,.06c0-.15,.02-.14-.11-.06Z"/><path class="cls-2" d="M375.72,837.52v.07s-.05-.01-.08-.01l.08-.06Z"/><path class="cls-2" d="M1037.31,730.23l-.31-.14c.26-.16,.33-.1,.22,.19l.09-.06Z"/><path class="cls-2" d="M1086.38,834.09l-.3,.07c.09-.03,.19-.07,.29-.11,0,0,0,.04,0,.04Z"/><path class="cls-2" d=M "M1028.34,666.28c.29-.06,.4,.01,.33,.2-.21,.03-.27-.04-.25-.26l-.08,.06Z"/><path class="cls-2" d="M215.67,631.85l-.23,.11c.12,0,.17,.02,.23-.11Z"/><path class="cls-2" d="M835.41,996.91l-.03-.19c-.19,.08-.15,.11,.14,.11,0,0-.11,.08-.11,.08Z"/><path class="cls-2" d="M1024.12,629.75l-.19,.07c.1-.08,.1-.19,.19-.07Z"/><path class="cls-2" d="M213.94,629.46s.07-.07,.08-.06-.08,.06-.08,.06Z"/><path class="cls-2" d="M998.52,718.5l-.17,.09c.11,.02,.11,0,.17-.09Z"/><path class="cls-2" d="M1070.09,761.82c.09-.16,.18-.45,.28-.4M 5,.35-.01,.34,.09-.02,.19-.09,.03-.15,.12-.24,.21l-.02,.05Z"/><path class="cls-2" d="M146.85,783.14l-.17,.11c.11,0,.12-.01,.17-.11Z"/><path class="cls-2" d="M1257,1041.9c.08-.04,.16-.08,.24-.13-.1,.04-.2,.08-.31,.12-.02,0,.08,0,.08,0Z"/><path class="cls-2" d="M686.57,1042.33c.13,0,.34-.03,.37,.02,.19,.24,.09,.25-.26-.02-.03,0-.12,0-.12,0Z"/><path class="cls-2" d="M708.45,1043.49l-.06-.12c.08,.05,.24,.03,.06,.12Z"/><path class="cls-2" d="M685.5,1044.44l.05-.26c.3,.13,.25,.19-.14,.19l.09,.07Z"/><path class="cls-2" d=M "M706.98,1045.42l-.11-.14c.13,.07,.22,.03,.11,.14Z"/><path class="cls-2" d="M1211.59,762.83l-.21,.18c.04-.06,.09-.11,.14-.18,.01,0,.07,0,.07,0Z"/><path class="cls-2" d="M1072.6,698.98l-.42,.2c.1-.04,.47-.27,.42-.2Z"/><path class="cls-2" d="M412.1,696.62l-.23-.12c.26-.09,.3-.03,.14,.18l.1-.05Z"/><path class="cls-2" d="M1092.71,695.04l-.14,.07c.06-.08,.04-.19,.14-.07Z"/><path class="cls-2" d="M775.96,1083.78l.27-.12c0,.2-.11,.22-.33,.04,0,0,.06,.08,.06,.08Z"/><path class="cls-2" d="M257.78,597.94l.51-.18c-.14,.03-.43M ,.2-.51,.18Z"/><path class="cls-2" d="M718.23,1098.91l-.37-.32c.24-.03,.18,.12,.24,.29,.02,0,.13,.04,.13,.04Z"/><path class="cls-2" d="M1100.78,662.2c-.08,.07-.21,.21-.24,.2-.19-.08-.09-.16,.3-.22,.03,0-.06,.02-.06,.02Z"/><path class="cls-2" d="M624.22,1111.98c-.12-.1-.23-.2-.35-.3,.25,.02,.32,.12,.36,.35,0,.02-.01-.06-.01-.06Z"/><path class="cls-2" d="M646.13,1117.89v-.18c.1,.11,.19,.12,0,.18Z"/><path class="cls-2" d="M310.21,573.78l-.1-.06c0,.15-.03,.14,.1,.06Z"/><path class="cls-2" d="M780.14,1133.02v-.27c.35,.0M 6,.31,.13-.09,.22l.09,.06Z"/><path class="cls-2" d="M589.12,1154.23l.04,.21c-.26,0-.25-.05,.05-.15l-.1-.06Z"/><path class="cls-2" d="M605.07,1165.57v.14c-.15-.07-.15-.06,0-.14Z"/><path class="cls-2" d="M378.95,529.15l-.21,.04,.11-.13c0,.06,.01,.11,.02,.16l.08-.08Z"/><path class="cls-2" d="M1007.33,688.24l.31,.13c-.25,.17-.32,.11-.22-.18l-.09,.06Z"/><path class="cls-2" d="M523.46,1191.36l.23,.39c-.08-.13-.16-.26-.24-.42,0-.02,.01,.03,.01,.03Z"/><path class="cls-2" d="M597.35,493.02v-.16c.18,.12,.15,.15-.08,.09l.08,.M 07Z"/><path class="cls-2" d="M171.32,461.66l-.27,.08c.21,.14,.25,.09,.11-.13,0,0,.16,.05,.16,.05Z"/><path class="cls-2" d="M555.57,1219.39l-.19-.22c.07,.07,.15,.14,.23,.21,0,0-.04,0-.04,0Z"/><path class="cls-2" d="M628.12,1219.02c.06,.7-1.41,.28-.17-.14l.17,.14Z"/><path class="cls-2" d="M638.3,415.08s-.01,.05-.02,.08c-.03,0-.07-.02-.12-.02l.14-.06Z"/><path class="cls-2" d="M638.26,415.26s.01-.07,.02-.1c.19,.03,.18,.07-.02,.1Z"/><path class="cls-2" d="M560.31,1238.68l.46,.32c-.12-.09-.24-.18-.39-.27-.03,0-.07-.04-.0M 7-.04Z"/><path class="cls-2" d="M476.02,1239.66l-.19,.13c-.01-.2,.07-.21,.25-.05,0,0-.06-.08-.06-.08Z"/><path class="cls-2" d="M796.77,320.09v.21c.21-.02,.19-.07-.09-.13,0,0,.09-.08,.09-.08Z"/><path class="cls-2" d="M660.72,307.27l-.19-.21c.07,.07,.15,.14,.23,.2,0,0-.04,0-.04,0Z"/><path class="cls-2" d="M767.07,301.73l-.08-.06,.08,.06Z"/><path class="cls-2" d="M703.81,286.66c.07,.03,.21,.08,.21,.09-.09,.23-.11,.21-.08-.05-.01,0-.13-.04-.13-.04Z"/><path class="cls-2" d="M479.99,1310.06l.2-.09-.1,.15c-.05-.05-.1-.09-M .15-.14,0,0,.05,.09,.05,.09Z"/><path class="cls-2" d="M755.9,264.86l-.26,.15c-.04-.2,.07-.23,.32-.07,0,0-.07-.08-.07-.08Z"/><path class="cls-2" d="M577.14,262.92c.65,.28,.66-.3,.79-.71l-.05-.02c-.4,.12-.77,.2-.74,.68v.04Z"/><path class="cls-2" d="M914.3,249.26c-.17-.36,.47-.5,.58-.18,0,.24-.19,.32-.48,.26l-.1-.08Z"/><path class="cls-2" d="M814.39,243.8l-.02-.22c-.23,.06-.2,.11,.1,.14,0,0-.09,.09-.09,.09Z"/><path class="cls-2" d="M753.96,241.18l-.35-.14c.09,.05,.29,.04,.35,.14Z"/><path class="cls-2" d="M816,219.41l-M .32-.47c.16,.22,.25,.35,.35,.47,0,0-.03,0-.03,0Z"/><path class="cls-2" d="M1098.81,212.47v-.19c.22,.14,.19,.18-.09,.11l.09,.07Z"/><path class="cls-2" d="M765.37,204.6l.16,.16c-.25,.12-.27,.08-.05-.11,0,0-.11-.05-.11-.05Z"/><path class="cls-2" d="M819.94,189.58l.51,.23c-.19,.04-.25-.1-.42-.2-.03,0-.09-.03-.09-.03Z"/><path class="cls-2" d="M1036.44,164.59l-.08,.21c-.19-.18-.14-.23,.16-.13l-.08-.08Z"/><path class="cls-2" d="M370.46,678.14l-.14,.14c.04-.16-.04-.23,.14-.14Z"/><path class="cls-2" d="M616.24,763.49c2,2.03M ,3.93,4.13,5.78,6.3-2.33-.86-4.66-1.77-6.99-2.67,.21-1.26,.76-2.44,1.21-3.63Z"/><path class="cls-2" d="M649.17,737.27s-.06,.09-.09,.14c-.03-.01-.05-.02-.08-.03l.17-.11Z"/><path class="cls-2" d="M662.05,726.32s.01,.07,.02,.11c-.05-.01-.09-.03-.14-.04l.12-.07Z"/><path class="cls-2" d="M671.64,742.58s.01-.07,.02-.11c.04,.01,.07,.02,.11,.03l-.13,.08Z"/><path class="cls-2" d="M699.27,703.72s-.01,.03-.02,.05c-1.08,4.11-.97,8.46-1.62,12.67-.08,.66-.55,1.02-1.28,.96-3.29-.14-6.29-.92-9.65-.72-1.27,4.37-.87,9.15-2.01,13.61-M 2.9-.44-5.8-.87-8.7-1.3-.88-.1-2.44-.33-2.57,.81-.59,4.22-1.18,8.45-1.76,12.67-2.81-.93-5.87-1.11-8.76-1.81-.74-.13-1.57-.28-2.28,.05-.13,.18-.33,.35-.36,.55-.52,2.67-1.03,5.33-1.54,8-3.08-4-6.36-7.87-9.81-11.58,.05-.09,.11-.18,.17-.27,3.29,1.2,6.81,1.8,10.29,2.47,.49,.09,.93-.24,1.03-.77,.71-4.21,1.48-8.44,1.67-12.68,3,.86,6.17,1.18,9.24,1.8,1.72,.34,2.14,.06,2.41-1.35,.43-4.01,1.44-8.1,1.16-12.12-.01-.02-.01-.05-.02-.07,3.17,.46,6.33,.94,9.51,1.35,1.6,.2,1.98-.05,2.16-1.23,.2-1.38,.34-2.77,.5-4.16,.27-2.35,.52-4.M 71,.8-7.06,.1-.84,.59-1.19,1.51-1.13,3.32,.34,6.63,.85,9.93,1.26Z"/><path class="cls-2" d="M671.77,742.5s-.01,.05-.01,.08h-.12l.13-.08Z"/><path class="cls-2" d="M683.05,743.76s0,.07-.01,.1c-.01,4.56-1.49,9-1.57,13.54-.04,0-.07,.01-.11,0-3.57,.03-7.04-1-10.6-1.33-.45-.07-1.13,.32-1.23,.65-.51,2.05-.91,4.13-1.38,6.19-1.82-2.93-3.71-5.8-5.71-8.6,2.01,.38,4.01,.77,6.02,1.15,.68,.12,1.33-.26,1.42-.84,.64-4.01,1.25-8.03,1.88-12.04,3.81-.08,7.47,1.25,11.29,1.18Z"/><path class="cls-2" d="M629.1,778.93c1.86,2.67,3.62,5.41,5M .26,8.21-4.09-.57-8-2.65-11.99-3.84-.02,0-.05-.01-.07-.02,1.25-2.85,2.56-5.67,3.74-8.52,1.05,1.37,2.07,2.76,3.06,4.17Z"/><path class="cls-2" d="M679.14,770.91c-.46,.37-.71,.89-.84,1.42-.54,2.09-1.08,4.19-1.6,6.28-1.41-2.96-2.9-5.88-4.49-8.74,2.32,.3,4.55,1.05,6.93,1.04Z"/><path class="cls-2" d="M1000.81,897c4.77-1.63,9.81-2.57,14.69-3.93,1.73,12.7,4.63,25.33,5.65,38.14,.02,.54-.47,1-1.18,1.13-4.2,.71-8.38,1.69-12.6,2.24-1.29,.02-1.19-1.45-1.43-2.34-.38-3.32-.68-6.65-1.07-9.97-.84-7.3-2.08-14.55-3.18-21.81-.18-1.17-M .21-2.37-.88-3.46Z"/><path class="cls-2" d="M928.04,467.85c-1.5-3.82-4.9-7.1-5.51-11.26,16-2.45,33-2.77,49.28-3.07,2.01,3.99,4.02,7.98,6.03,11.98,.3,.59-.08,.98-.95,1-16.29,0-32.62-.24-48.85,1.35Z"/><path class="cls-2" d="M918.34,445.23c-1.11-3.91-1.88-7.92-3.26-11.74,15.45-1.65,30.87-3.67,46.41-4.46,5.28-.17,4.95-.84,5.61,3.62,.29,1.92,.82,3.81,1.18,5.72,.22,2.11,.76,2.84-1.86,2.88-6.72,.23-13.41,.75-20.12,1.13-9.36,.73-18.73,1.39-27.97,2.86Z"/><path class="cls-2" d="M727.47,663.7c2.82,.71,5.76,.87,8.65,1.25,1.99,M .26,2.45,.28,2.87-1.68,.7-3.26,1.52-6.5,2.31-9.75,.19-.57,.38-1.46,1.12-1.53,3.73-.06,7.3,1.29,11.02,1.27-1.46,4.49-2.87,9.02-3.34,13.67l.11-.08c-3.55-.45-7.09-1.07-10.66-1.3-.44-.03-1.08,.37-1.16,.74-.27,1.26-.58,2.52-.8,3.78-.45,2.53-.85,5.07-1.26,7.61-.09,.53-.12,1.06,.2,1.56-3.55-.53-7.12-.98-10.68-1.42-1.03-.13-.92-1.14-.82-1.88,.83-4.12,1.18-8.33,2.54-12.33l-.11,.1Z"/><path class="cls-2" d="M757.47,640.44c-3.8-.58-7.59-1.7-11.4-1.95,1.8-4.2,2.96-8.73,5.18-12.72,.11-.15,.45-.28,.67-.26,3.83,.15,7.46,1.72,11.27M ,1.92-2.5,4.02-3.57,8.8-5.72,13.02Z"/><path class="cls-2" d="M776.91,657.8c-1.04,4.34-2.68,8.6-3.34,13.01l.12-.08c-4.08-.67-8.13-1.62-12.26-1.94l.1,.13q2.58-10.93,3.8-13.08c3.89,.29,7.74,1.29,11.58,1.95Z"/><path class="cls-2" d="M753.33,653.34c1.26-4.35,3.27-8.57,4.05-13,3.52,.71,7.04,1.41,10.56,2.13,1.54,.34,.59,1.87,.31,2.82-.95,2.91-1.89,5.83-2.85,8.74-.18,.53-.45,1.11-1.09,1.22-3.68-.21-7.4-1.12-10.98-1.91Z"/><path class="cls-2" d="M750.12,666.94c3.76,.76,7.83,.69,11.41,1.99l-.1-.13c-.74,4.33-1.83,8.61-2.31,12.M 97-3.83-.04-7.6-.94-11.43-1.25,.36-4.06,1.34-8.08,1.97-12.12,.09-.52,.37-1.03,.57-1.54l-.11,.08Z"/><path class="cls-2" d="M793.88,688.83c-.22,3.66-1.26,7.23-1.88,10.85-.27,.93-.35,2.37-1.75,2.09-3.11-.68-6.19-1.5-9.35-1.98-1.24-.03-1.27,1.46-1.46,2.35-.37,2.78-.71,5.57-1.09,8.35-.23,.77-.13,2.03-1.13,2.22-3.68-.32-7.35-1.34-11.02-1.92l.16,.11c1.6-4.16,.83-9.35,2.37-13.67,3.36,.65,6.73,1.3,10.09,1.95,.84,.12,1.26-.6,1.3-1.29,.93-3.86,1.01-7.94,2.46-11.64l-.1,.1c3.8,.81,7.56,1.84,11.39,2.48Z"/><path class="cls-2" d="M M818.05,656.59c-.08-.56,.29-1.02,.56-1.5,1.5-2.72,3-5.45,4.52-8.16,.26-.47,.55-.96,1.34-1.26,4.1,1.51,8.15,3.5,12.3,5.04-2.17,3.37-3.95,7.18-6.34,10.32-.73,.11-1.29-.22-1.88-.46-3.53-1.26-6.81-3.2-10.5-3.97Z"/><path class="cls-2" d="M773.58,670.81c3.81,.84,7.61,1.68,11.42,2.52-.75,4.35-2.16,8.63-2.5,13.02l.1-.1c-4.1-.84-8.19-1.69-12.29-2.53,1.66-4.21,1.52-8.83,3.39-12.99l-.12,.08Z"/><path class="cls-2" d="M809.28,679.77c-5.82,14.87,1.42,13.79-15.52,9.11,1.77-3.73,1.67-8.06,3.23-11.86,.09-.24,.66-.49,.97-.41,3.86,.8M 6,7.43,2.37,11.33,3.16Z"/><path class="cls-2" d="M646.55,678.57c1.6-4.82,2.36-9.99,3.28-14.97,3.38,1.43,6.94,2.47,10.61,3.3l-.08-.06c-1.72,4.84-1.64,10.08-3.29,14.96l.12-.12c-3.56-.98-7.01-2.46-10.64-3.12Z"/><path class="cls-2" d="M653.2,710.13c-3.92-.84-7.71-1.98-11.5-3.13,1.57-4.3,1.35-9.09,2.73-13.44,.79-.29,1.41-.11,2.03,.07,2.76,.79,5.51,1.6,8.26,2.39l-.07-.08c.14,4.77-1.22,9.54-1.62,14.31l.16-.12Z"/><path class="cls-2" d="M654.73,696.02c1.29-4.63,1.84-9.55,2.46-14.32l-.12,.11c3.59,.6,7.16,1.47,10.62,2.59l-.08M -.09c0,4.81-1.48,9.5-1.51,14.29-3.81-.89-7.63-1.78-11.44-2.67l.07,.08Z"/><path class="cls-2" d="M649,737.38s0-.08-.01-.12c.06,0,.12,0,.18,.01l-.17,.11Z"/><path class="cls-2" d="M653.2,710.13l-.03,.15s-.09-.02-.13-.03l.16-.12Z"/><path class="cls-2" d="M661.93,726.39s.02-.05,.03-.08c.03,0,.06,0,.09,0l-.12,.07Z"/><path class="cls-2" d="M663.76,714.26c-.65,4-.59,8.18-1.8,12.05-3.39-.2-6.58-1.46-9.94-1.92-.46-.07-1.1,.31-1.16,.68-.55,4.07-1.64,8.11-1.87,12.19-.17-.02-.34-.03-.51-.04-3.19-3.4-6.53-6.66-10.02-9.78,.43-1.9M 4,.56-3.97,1.19-5.85,.07-.23,.64-.46,.98-.38,3.06,.72,6.06,1.65,9.1,2.46,1.06,.24,1.41-.69,1.54-1.47,.55-3.98,1-7.99,1.9-11.92,2.94,.65,5.86,1.29,8.79,1.95,1.1,.11,2.14,.84,1.8,2.03Z"/><path class="cls-2" d="M725.01,838.22c2.57-3.99,4.24-8.51,6.4-12.73,.2-.56,.57-1.38-.1-1.75-3.05-1.1-6.37-1.49-9.52-2.31,1.54-4.63,3.83-9.17,4.96-13.85-.51-.6-1.35-.7-2.1-.85-1.82-.36-3.66-.64-5.48-1-.91-.25-2.65-.39-2.16-1.74,1.37-4.36,2.75-8.72,4.13-13.08l-.15,.12c3.48,.92,7.08,1.31,10.62,1.96l-.1-.1c-.72,4.15-2.48,8.1-3.63,12.16-.M 21,.78-.82,1.95,.35,2.27,2.94,.73,5.9,1.39,8.94,1.77,.88,0,1.1-1.12,1.4-1.74,1.11-4.17,3-8.25,3.57-12.51l-.18,.11c3.57,.51,7.1,1.66,10.69,1.82-1.31,4.8-2.95,9.56-4.09,14.39,0,.25,.31,.66,.59,.75,2.86,.75,5.79,2.2,8.79,2.19,2.29-4.67,3.36-9.86,5.14-14.75,3.18,1.31,6.54,2.16,9.8,3.26-1.92,4.95-3.19,10.01-5.37,14.87-14.08-3.65-6.86-5.63-15.29,11.21-.17,.37-.89,.63-1.33,.49-2.5-.77-5-1.55-7.51-2.27-.68-.22-1.31,0-1.95,.05,2.98-4.11,4.11-9.29,6.24-13.87,.15-.38,.35-.83-.27-1.42-2.01-.87-4.58-1.1-6.97-1.75-.8-.11-1.94-.5M 1-2.63,.06-2.12,4.18-3.46,8.79-5.28,13.13-.06,.17,.08,.39,.13,.58,2.56,1.2,5.55,1.56,8.23,2.5,.28,.08,.4,.49,.6,.75,.26,.29,.19,.6,.05,.9-2.08,4.62-4.32,9.17-6.71,13.64-3.07-1.53-6.56-2.14-9.81-3.28Z"/><path class="cls-2" d="M758.98,767.7c-.1,4.56-1.79,9.1-2.5,13.64-.09,.4-.7,.77-1.18,.7-2.63-.43-5.24-.89-7.86-1.36-1.17-.18-1.76,.16-1.99,1.09-1.29,4.36-1.67,9.04-3.51,13.19l.18-.11c-3.54-.65-7.09-1.3-10.63-1.95l.1,.1c1.32-4.7,2.99-9.48,3.11-14.31,3.28,.36,6.54,.92,9.81,1.37,.78,.11,1.34-.2,1.46-.77,.97-4.49,1.93-8.9M 9,2.5-13.55,3.49,.87,7.16,1.07,10.61,2.04l-.11-.09Z"/><path class="cls-2" d="M761.43,753.6c3.55-.02,7.2,.98,10.63,1.82-.11,4.27-1.28,8.44-1.91,12.65-.16,.98-.67,1.82-1.89,1.53-3.09-.62-6.15-1.43-9.27-1.9l.11,.09c1.29-4.67,1.63-9.53,2.46-14.29l-.12,.11Z"/><path class="cls-2" d="M1041.28,373.35c22.91,.41,45.94,.34,68.85,1.97-1.87,4.66-3.75,9.33-5.6,14-.12,.29-.04,.63-.06,.95-22.75-1.75-45.54-2.5-68.35-2.76-.8-.3-.22-1.4-.06-1.99,1.73-4.05,3.81-7.98,5.22-12.16Z"/><path class="cls-2" d="M699.95,816.9c1.84-4.57,4.07-9.0M 1,5.67-13.66,2.61,.47,5.22,.94,7.82,1.42,.83,.28,2.83,.25,2.69,1.43-1.16,3.64-2.68,7.16-4.01,10.75-.4,.7-.66,1.96-1.65,2-3.56-.34-6.94-1.53-10.52-1.93Z"/><path class="cls-2" d="M721.13,790.92c-3.86,.11-7.58-1.13-11.44-1.24l.09,.1c.58-4.33,2.03-8.58,2.93-12.87,.16-.6,.7-.93,1.41-.87,3.44,.29,6.88,.62,10.22,1.39-1.61,4.4-2.11,9.1-3.36,13.61l.15-.12Z"/><path class="cls-2" d="M705.72,803.34c-3.81-.65-7.62-1.3-11.42-1.95,1.32-4.57,3.22-9.02,4.14-13.67l-.12,.09c3.78,.85,7.72,1.01,11.45,1.98l-.09-.1c-1.32,4.55-2.63,9.11-3M .97,13.66Z"/><path class="cls-2" d="M698.33,787.8l.03-.09h.08l-.11,.09Z"/><path class="cls-2" d="M701.68,774.15s-.02,.07-.02,.1c-1.04,4.5-1.97,9.03-3.3,13.46-3.48-.1-6.81-1.01-10.26-1.34-.68-.09-1.28,.26-1.48,.84-.96,2.9-1.91,5.82-2.9,8.71-1.28-3.78-2.7-7.5-4.26-11.16,2.26,.32,4.52,1.06,6.82,1.07,.24-.03,.57-.18,.63-.33,1.7-4.02,2.4-8.35,3.33-12.57,0-.01,.01-.03,.01-.04,3.85,.21,7.58,1.12,11.43,1.26Z"/><path class="cls-2" d="M702.5,630c-1.34,4.25-2.68,8.5-4.02,12.76-.15,.77-.49,1.71-1.49,1.61-2.75-.46-5.48-.97-8.22M -1.48-.65-.11-1.3,.26-1.45,.84-1.19,4.5-2.22,9.04-3.55,13.51l.13-.08c-2.6-.56-5.2-1.11-7.79-1.67-.77-.16-1.54-.4-2.41-.11-1.86,4.25-1.77,9.15-3.22,13.55-.08,.24-.66,.5-.98,.42-3.02-.83-6.3-1.2-9.13-2.51l.08,.06c.01-.63-.08-1.27,.05-1.88,1.07-4.33,1.54-8.87,3.1-13.05,2.52,1.29,5.53,1.68,8.27,2.49,1.12,.28,1.71-.03,1.98-1.03,.95-3.8,1.89-7.59,2.92-11.37,.17-.62,.3-1.28,1.17-1.73,12.24,2.2,8.48,4.81,12.45-7.3,.45-1.46,.98-2.9,1.5-4.35,.17-.47,.69-.69,1.26-.56,3.12,.61,6.17,1.65,9.35,1.87Z"/><path class="cls-2" d="M672M .46,621.58c3.15,1.33,6.35,2.54,9.81,3.25-1.55,4.66-3.06,9.32-4.61,13.98-.29,.84-.84,1.09-1.76,.82-2.77-.81-5.51-1.69-8.29-2.44,.97-5.34,3.93-10.31,4.85-15.62Z"/><path class="cls-2" d="M667.74,637.13c-1.91,4.09-2.59,8.71-3.94,13.03-.16,.61-.1,1.26-.14,1.9-3.28-.64-6.24-1.89-9.26-3.04-.49-.18-.71-.59-.58-1.08,.6-2.3,1.2-4.61,1.84-6.91,.52-1.88,1.08-3.76,1.64-5.63,.24-.74,.67-1.75,1.66-1.41,2.93,1.05,5.86,2.1,8.79,3.15Z"/><path class="cls-2" d="M682.15,624.89c2.47-4.82,3.63-10.25,6.53-14.93,2.72,.91,5.44,1.81,8.16,2.7M 2,.9,.28,1,.9,.72,1.59-1.71,4.18-3.41,8.36-5.13,12.53-.22,.53-.93,.83-1.61,.64-2.9-.84-5.78-1.69-8.68-2.54Z"/><path class="cls-2" d="M718.68,618.4c-2.46,4.14-3.29,9.1-5.58,13.32-.31,.35-.97,.4-1.44,.31-3.12-.57-6.27-1.08-9.29-1.96,2.17-4.64,3.75-9.55,5.69-14.29,3.53,.9,7.16,1.47,10.62,2.62Z"/><path class="cls-2" d="M774.48,741.3c-3-1.14-6.44-1.27-9.61-2-.97-.17-1.55,.2-1.65,.95-.64,4.44-1.2,8.9-1.79,13.35l.12-.11c-3.42-1.05-7.05-1.22-10.57-1.86-.04-.53-.16-1.06-.11-1.59,.61-4.24,.57-8.62,1.8-12.74l-.1,.1c2.64,.38,5M .27,.77,7.91,1.14,.86,.01,2.42,.58,2.83-.46,.75-4.02,1.1-8.09,1.61-12.13,.06-.75,1.07-.95,1.81-.8,3.12,.61,6.24,1.22,9.37,1.83-.42,4.78-1.56,9.55-1.62,14.33Z"/><path class="cls-2" d="M754.18,723.08c-.19,.62-.49,1.23-.56,1.86-.35,4.15-1.07,8.3-1.05,12.47l.1-.1c-3.85-.25-7.59-1.07-11.46-1.19,.54-4.78,.63-9.62,1.65-14.33,3.74,.74,7.56,1.12,11.39,1.37l-.07-.09Z"/><path class="cls-2" d="M766.2,710.79c.54,1.64,.02,3.38-.07,5.06-.34,2.64-.52,5.32-1.05,7.93-.31,.9-1.54,.79-2.32,.67-2.86-.47-5.82-.53-8.59-1.38l.07,.09c-.35-M 4.13,.73-8.37,.95-12.53,.03-.42,.4-.91,.83-.97,3.48-.05,6.89,.82,10.33,1.23l-.16-.11Z"/><path class="cls-2" d="M694.41,659.09c-1.12,4.68-1.49,9.62-2.94,14.18-3.35,.3-6.35-.82-9.62-1.16-.86-.04-1.1,.75-1.21,1.41-.61,4.24-1.62,8.49-1.68,12.79l.12-.08c-3.85-.45-7.64-1.29-11.46-1.93l.08,.09c1.08-4.16,1.61-8.45,2.38-12.68,.3-1.77,.69-1.96,2.88-1.53,1.66,.06,7.56,2.47,8.13,.57,.9-4.54,1.86-9.07,2.81-13.6l-.13,.08c3.55,.61,7.05,1.5,10.64,1.86Z"/><path class="cls-2" d="M719.38,648.07c3.63,1.3,7.64,1.27,11.44,1.98-1.77,4.35M -2.13,9.12-3.34,13.65l.11-.1c-3.85,.07-7.63-.83-11.44-1.29l.12,.09c.53-4.84,2.15-9.56,3.12-14.34Z"/><path class="cls-2" d="M678.95,686.32c3.3,.4,6.59,1.31,9.92,1.32,.22-.02,.56-.22,.6-.38,.29-1.27,.57-2.54,.77-3.82,.39-2.56,.71-5.13,1.08-7.7,.18-.92,.47-1.99,1.66-1.82,3.2,.34,6.41,.61,9.49,1.42l-.08-.09c.17,4.81-1.95,9.54-1.46,14.32-3.12-.7-6.35-.85-9.52-1.34-.68-.08-1.72-.06-1.85,.78-.56,3.73-.98,7.48-1.51,11.21-.12,.58-.16,1.53-.9,1.62-3.61-.13-7.16-.77-10.72-1.28,.61-.62,.67-1.36,.76-2.1,.75-4.05,.44-8.35,1.88-1M 2.22l-.12,.08Z"/><path class="cls-2" d="M704.82,661.04c3.87,.13,7.6,.99,11.45,1.37l-.12-.09c-.69,4.78-2.1,9.53-2.3,14.34-3.78-.66-7.6-1.12-11.46-1.4l.08,.09c.8-4.76,2.22-9.47,2.35-14.31Z"/><path class="cls-2" d="M742.94,721.87c-3.58-.32-7.15-.59-10.74-.77-.2-.01-.52,.19-.62,.35-1,4.32-1.01,8.92-1.7,13.33l.12-.07c-2.93-.12-5.86-.34-8.78-.63-.89-.07-2.4-.23-2.51,.92-.33,2.98-.63,5.97-.97,8.95-.14,1.27-.02,2.58-.81,3.76l.11-.07c-15.69-.52-9.23-3.89-13.05,13.02l.11-.09c-3.81-.42-7.59-1.1-11.42-1.2,.6-4.26,1.15-8.53,1.8M 3-12.78,.51-1.64,3.29-.52,4.61-.61,.8,.08,1.58,.25,2.38,.31,4.76,.36,4.61,.74,4.96-3.24,.38-3.41,.81-6.82,.87-10.26l-.12,.08c3.45,.22,6.9,.48,10.35,.72,.53,.04,1.08-.3,1.13-.7,.6-4.34,1.09-8.69,1.6-13.04l-.1,.09c2.79,.11,5.56,.35,8.34,.6,2.65,.17,2.89,.21,3.07-2.13,.18-3.82,.98-7.64,.8-11.46l-.14,.06c3.86-.34,7.59,.94,11.46,.63l-.14-.16c.67,4.79-1.14,9.59-.66,14.38Z"/><path class="cls-2" d="M747.8,680.43c-1.51,4.42-.89,9.34-2.58,13.65l.13-.08c-3.82-.37-7.66-.66-11.44-1.31l.11,.09c1.05-4.5,.85-9.31,2.35-13.65l11.43,M 1.3Z"/><path class="cls-2" d="M696.01,731.49c-.09,4.39-.48,8.88-1.44,13.15-.16,.45-.81,.64-1.28,.59-3.49-.26-6.94-.68-10.34-1.39,1.15-4.4,1.62-9.1,1.62-13.64,3.81,.45,7.59,1.16,11.43,1.3Z"/><path class="cls-2" d="M700.78,689.47c3.54,.43,7.13,.59,10.61,1.3-.06,3.98-.52,7.93-.98,11.88-.05,1-.38,1.92-1.64,1.79-3.23-.08-6.39-.83-9.61-.66,.26-4.75,.62-9.65,1.62-14.31Z"/><path class="cls-2" d="M707.33,732.8c-3.81-.41-7.63-.82-11.44-1.23,.74-1.31,.65-2.72,.8-4.11,.31-2.89,.59-5.77,.9-8.66,.1-1.12,1.68-.93,2.56-.86,2.93,.3M 1,5.87,.53,8.81,.7l-.1-.09c-.56,4.77-.49,9.65-1.65,14.33l.12-.08Z"/><path class="cls-2" d="M708.96,718.64c.29-4.29,.61-8.59,1.23-12.85,.09-.54,.69-.9,1.46-.85,2.01,.15,4.01,.3,6.01,.49,3.92,.38,3.72,.1,3.46,3.27-.34,3.75-.78,7.49-.92,11.25l.1-.09c-3.82-.36-7.66-.6-11.44-1.31l.1,.09Z"/><path class="cls-2" d="M732.41,706.96c-3.17-.86-6.6-.7-9.85-1.27-.51-.06-.9-.48-.88-.91,.1-1.7,.18-3.41,.34-5.11,.26-2.33,.44-4.69,.86-7,.06-.29,.78-.73,1.2-.7,3.32,.23,6.64,.5,9.95,.81l-.11-.09c-.1,4.78-.36,9.72-1.64,14.33l.14-.06Z"/M ><path class="cls-2" d="M711.24,690.87c.68-.97,.68-2.06,.83-3.13,.54-3.73,1.09-7.46,1.64-11.2,14.16,1.76,10.7-1.22,9.54,12.77-.15,.97-.27,2.32-1.62,2.2-3.48-.11-6.91-.89-10.4-.65Z"/><path class="cls-2" d="M666.01,698.53c3.48,.83,7.03,1.43,10.6,1.94-.14,4.8-.63,9.61-1.63,14.31-3.42-.78-7.08-1.09-10.39-2.21-.36-2.3-.27-3.17,1.42-14.04Z"/><path class="cls-2" d="M692.8,759.3c-.88,4.54-1.81,9.08-2.44,13.67-3.72-.97-7.64-1.26-11.43-1.96,.36-4.6,1.5-9.15,2.45-13.67,3.56,1.33,7.68,1.19,11.42,1.96Z"/><path class="cls-2" d="M M770.43,683.66c-.4,4.44-1.97,9.28-1.61,13.66-3.55-.52-7.08-1.16-10.66-1.45-.68-.06-1.25,.35-1.33,.95-.51,3.82-.83,7.67-1.51,11.47-.08,.42-.63,.75-1.15,.73-3.53-.33-7.22-.35-10.58-1.51l.14,.16c1.02-4.47,1.4-9.09,1.62-13.66l-.13,.08c3.59,.41,7.17,1.04,10.78,1.24,.36,0,.79-.15,.92-.51,1.02-4.27,1.32-8.77,2.08-13.11,3.52,1.13,7.72,1.55,11.42,1.96Z"/><path class="cls-2" d="M724.23,777.48c.88-4.77,1.16-9.63,2.54-14.29l-.12,.07c3.58,.2,7.12,.54,10.59,1.3l-.11-.08c.41,1.07,.08,2.14-.09,3.19-.73,3.7-.99,7.54-2.23,11.11-3.48M -.69-6.98-1.29-10.59-1.3Z"/><path class="cls-2" d="M739.6,750.34c3.88,.05,7.61,1.02,11.47,1.19-.23,.5-.59,.98-.66,1.5-.63,4.27-1.21,8.54-1.81,12.81-3.81-.47-7.62-1-11.45-1.36l.11,.08c1.5-4.51,1.52-9.61,2.46-14.31l-.11,.1Z"/><path class="cls-2" d="M701.57,774.24c1.17-4.51,1.83-9.09,2.54-13.66l-.11,.09c3.83,.3,7.67,.61,11.43,1.3l-.11-.08c-.11,4.36-1.58,8.64-2.36,12.94-.4,1.16-2.18,.57-3.12,.57-2.76-.37-5.51-.77-8.26-1.16Z"/><path class="cls-2" d="M726.77,763.18c-3.82-.43-7.64-.86-11.46-1.3l.11,.08c.62-4.77,1.61-9.5,1L .61-14.31l-.11,.07c3.8,.52,7.62,.91,11.43,1.31l-.1-.09c.12,4.78-1.21,9.54-1.61,14.31l.12-.07Z"/><path class="cls-2" d="M729.87,734.79l11.45,1.23c-.58,4.77-1.15,9.55-1.73,14.32l.11-.1-11.45-1.3,.1,.09c.86-4.75,1.2-9.54,1.63-14.32l-.12,.07Z"/></g></svg>h! ulJgvyfuxriH_mp_mo^lo]V;F]bBKM)IP x=FH)HO(HO(HN(GN&CJ$AG99;/78 ulJgvyfuxriH_mp_mo^lo]V;F]bBKM)IP x=FH)HO(HO(HN(GN&CJ$AG99;/78 ulJgvyfuxriH_mp_mo^lo]V;F]bBKM)IP x=FH)HO(HO(HN(GN&CJ$AG99;/78 +gvyfuxriH_mp_mo^lo]V;F]bBKM)IP x=FH)HO(HO(HN(GN&CJ$AG99;/78 ulJgvyfuxriH_mp_mo^lo]V;F]bBKM)IP x=FH)HO(HO(HN(GN&CJ$AG99;y ulJgvyfuxriH_mp_mo^lo]V;F]bBKM)IP x=FH)HO(HO(HN(GN&CJ$AG99;/78 ulJgvyfuxriH_mp_mo^lo]V;F]bBKM)IP x=FH)HO(HO(HN(GN&CJ$AG99;/78 ulJgvyfuxriH_mp_mo^lo]V;F]bBKM)IP x=FH)HO(HO(HN(GN&CJ$AG99;/78 ulJgvyfuxriH_mp_mo^lo]V;F]bBKM)IP x=FH)HO(HO(HN(GN&CJ$AG99;/78 text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 Adaptati0n Ordinalsh! text/html;charset=utf-8 <meta charset="utf-8" /> position: relative; width: var(--width); height: var(--height); border: 1px solid blue; position: relative; <div id="upload"> <input id="inputUpload" type="file"> function e(e){"use strict";return new function e(t){let n="global"==t?window:this;n.canvas=document.createElement("canvas");let r=n.canvas.getContext("2d");n.width=100,n.height=100,n.canvas.width=n.width,n.canvas.height=n.height,"offscreen"!=t&&(document.body?document.body.appendChild(n.canvas):window.addEventListener("load",(function(){document.body.appendChild(n.canvas)}))),g(),n.MAGIC=161533525,n.RGB=0,n.HSV=1,n.HM SB=1,n.CHORD=0,n.PIE=1,n.OPEN=2,n.RADIUS=1,n.CORNER=2,n.CORNERS=3,n.ROUND="round",n.SQUARE="butt",n.PROJECT="square",n.MITER="miter",n.BEVEL="bevel",n.CLOSE=1,n.BLEND="source-over",n.REMOVE="destination-out",n.ADD="lighter",n.DARKEST="darken",n.LIGHTEST="lighten",n.DIFFERENCE="difference",n.SUBTRACT="subtract",n.EXCLUSION="exclusion",n.MULTIPLY="multiply",n.SCREEN="screen",n.REPLACE="copy",n.OVERLAY="overlay",n.HARD_LIGHT="hard-light",n.SOFT_LIGHT="soft-light",n.DODGE="color-dodge",n.BURN="color-burn",n.NORMAL="norM mal",n.ITALIC="italic",n.BOLD="bold",n.BOLDITALIC="italic bold",n.CENTER="center",n.LEFT="left",n.RIGHT="right",n.TOP="top",n.BOTTOM="bottom",n.BASELINE="alphabetic",n.LANDSCAPE="landscape",n.PORTRAIT="portrait",n.ALT=18,n.BACKSPACE=8,n.CONTROL=17,n.DELETE=46,n.DOWN_ARROW=40,n.ENTER=13,n.ESCAPE=27,n.LEFT_ARROW=37,n.OPTION=18,n.RETURN=13,n.RIGHT_ARROW=39,n.SHIFT=16,n.TAB=9,n.UP_ARROW=38,n.HALF_PI=Math.PI/2,n.PI=Math.PI,n.QUARTER_PI=Math.PI/4,n.TAU=2*Math.PI,n.TWO_PI=2*Math.PI,n.THRESHOLD=1,n.GRAY=2,n.OPAQUE=3,n.INVEM RT=4,n.POSTERIZE=5,n.DILATE=6,n.ERODE=7,n.BLUR=8,n.ARROW="default",n.CROSS="crosshair",n.HAND="pointer",n.MOVE="move",n.TEXT="text",n.VIDEO={video:!0,audio:!1},n.AUDIO={video:!1,audio:!0},n.SHR3=1,n.LCG=2,n.HARDWARE_FILTERS=!0,n.hint=function(e,t){n[e]=t},n.frameCount=0,n.mouseX=0,n.mouseY=0,n.pmouseX=0,n.pmouseY=0,n.mouseButton=null,n.keyIsPressed=!1,n.mouseIsPressed=!1,n.key=null,n.keyCode=null,n.pixels=null,n.accelerationX=0,n.accelerationY=0,n.accelerationZ=0,n.rotationX=0,n.rotationY=0,n.rotationZ=0,n.relRotatM ionX=0,n.relRotationY=0,n.relRotationZ=0,n.pAccelerationX=0,n.pAccelerationY=0,n.pAccelerationZ=0,n.pRotationX=0,n.pRotationY=0,n.pRotationZ=0,n.pRelRotationX=0,n.pRelRotationY=0,n.pRelRotationZ=0,n.touches=[],n._styleCache=[{colorMode:n.RGB,noStroke:!1,noFill:!1,ellipseMode:n.CENTER,rectMode:n.CORNER,curveDetail:20,curveAlpha:0,textFont:"sans-serif",textSize:12,textLeading:12,textStyle:"normal"}],n._style=n._styleCache[n._styleCache.length-1],n._noLoop=!1,n._pixelDensity=1,n._frameRate=null,n._tint=null;let i=nullM ,o=!0,a=[],l=null,s=0,h={},c=0,u=null,f=null,d=null;Object.defineProperty(n,"deviceOrientation",{get:function(){return 90==Math.abs(window.orientation)?n.LANDSCAPE:n.PORTRAIT}}),Object.defineProperty(n,"windowWidth",{get:function(){return window.innerWidth}}),Object.defineProperty(n,"windowHeight",{get:function(){return window.innerHeight}}),Object.defineProperty(n,"drawingContext",{get:function(){return r}}),n.createCanvas=function(e,t){return n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t,g(),n.canvas},nM .resizeCanvas=function(e,t){n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t},n.createGraphics=n.createImage=function(t,n){let r=new e("offscreen");return r.createCanvas(t,n),r.noLoop(),r},n.pixelDensity=function(e){return null==e||(n._pixelDensity=e,n.canvas.width=Math.ceil(n.width*e),n.canvas.height=Math.ceil(n.height*e),n.canvas.style.width=n.width+"px",n.canvas.style.height=n.height+"px",r.scale(n._pixelDensity,n._pixelDensity),g()),n._pixelDensity},n.map=function(e,t,n,r,i,o){let a=r+1*(e-t)/(n-t)*(i-r)M ;return o?r<i?Math.min(Math.max(a,r),i):Math.min(Math.max(a,i),r):a},n.lerp=function(e,t,n){return e*(1-n)+t*n},n.constrain=function(e,t,n){return Math.min(Math.max(e,t),n)},n.dist=function(){return 4==arguments.length?Math.hypot(arguments[0]-arguments[2],arguments[1]-arguments[3]):Math.hypot(arguments[0]-arguments[3],arguments[1]-arguments[4],arguments[2]-arguments[5])},n.norm=function(e,t,r){return n.map(e,t,r,0,1)},n.sq=function(e){return e*e},n.fract=function(e){return e-Math.floor(e)},n.degrees=function(e){retM urn 180*e/Math.PI},n.radians=function(e){return e*Math.PI/180},n.abs=Math.abs,n.ceil=Math.ceil,n.exp=Math.exp,n.floor=Math.floor,n.log=Math.log,n.mag=Math.hypot,n.max=Math.max,n.min=Math.min,n.round=Math.round,n.sqrt=Math.sqrt,n.sin=Math.sin,n.cos=Math.cos,n.tan=Math.tan,n.asin=Math.asin,n.acos=Math.acos,n.atan=Math.atan,n.atan2=Math.atan2,n.Vector=function(e,t,r){let i=this;i.x=e||0,i.y=t||0,i.z=r||0;let o=null,a=null;function l(e,t,n){return null!=e.x?e:null!=t?{x:e,y:t,z:n||0}:{x:e,y:e,z:e}}function s(){null==a&M &(a=i.x*i.x+i.y*i.y+i.z*i.z,o=Math.sqrt(a))}function h(){a=null,o=null}i.set=function(e,t,n){i.x=e||0,i.y=t||0,i.z=n||0},i.copy=function(){return new n.Vector(i.x,i.y,i.z)},i.add=function(){let e=l.apply(null,arguments);return i.x+=e.x,i.y+=e.y,i.z+=e.z,h(),i},i.rem=function(){let e=l.apply(null,arguments);return i.x%=e.x,i.y%=e.y,i.z%=e.z,h(),i},i.sub=function(){let e=l.apply(null,arguments);return i.x-=e.x,i.y-=e.y,i.z-=e.z,h(),i},i.mult=function(){let e=l.apply(null,arguments);return i.x*=e.x,i.y*=e.y,i.z*=e.z,hM (),i},i.div=function(){let e=l.apply(null,arguments);return i.x/=e.x,i.y/=e.y,i.z/=e.z,h(),i},i.mag=function(){return s(),o},i.magSq=function(){return s(),a},i.dot=function(){let e=l.apply(null,arguments);return i.x*e.x+i.y*e.y+i.z*e.z},i.dist=function(){let e=l.apply(null,arguments),t=i.x-e.x,n=i.y-e.y,r=i.z-e.z;return Math.sqrt(t*t+n*n+r*r)},i.cross=function(){let e=l.apply(null,arguments),t=i.y*e.z-i.z*e.y,n=i.z*e.x-i.x*e.z,r=i.x*e.y-i.y*e.x;return i.x=t,i.y=n,i.z=r,h(),i},i.normalize=function(){s();let e=o;retuM rn i.x/=e,i.y/=e,i.z/=e,o=1,a=1,i},i.limit=function(e){s();if(o>e){let t=e/o;i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e}return i},i.setMag=function(e){s();let t=e/o;return i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e,i},i.heading=function(){return Math.atan2(i.y,i.x)},i.rotate=function(e){let t=Math.cos(e),n=Math.sin(e),r=i.x*t-i.y*n,o=i.x*n+i.y*t;return i.x=r,i.y=o,i},i.angleBetween=function(){let e=l.apply(null,arguments);const t=i.dot(e)/(i.mag()*e.mag());let n;return n=Math.acos(Math.min(1,Math.max(-1,t))),n*Math.sign(i.cross(e).z||1)},M i.lerp=function(e,t){return i.x=i.x*(1-t)+e.x*t,i.y=i.y*(1-t)+e.y*t,i.z=i.z*(1-t)+e.z*t,h(),i},i.reflect=function(e){return e.normalize(),i.sub(e.mult(2*i.dot(e)))},i.array=function(){return[i.x,i.y,i.z]},i.equals=function(e,t){return null==t&&null==(t=Number.EPSILON)&&(t=0),Math.abs(e.x-i.x)<t&&Math.abs(e.y-i.y)<t&&Math.abs(e.z-i.z)<t},i.fromAngle=function(e,t){return null==t&&(t=1),o=t,a=t*t,i.x=t*Math.cos(e),i.y=t*Math.sin(e),i.z=0,i},i.fromAngles=function(e,t,n){null==n&&(n=1),o=n,a=n*n;const r=Math.cos(t),l=MaM th.sin(t),s=Math.cos(e),h=Math.sin(e);return i.x=n*h*l,i.y=-n*s,i.z=n*h*r,i},i.random2D=function(){return o=1,a=1,i.fromAngle(Math.random()*Math.PI*2)},i.random3D=function(){return o=1,a=1,i.fromAngles(Math.random()*Math.PI*2,Math.random()*Math.PI*2)},i.toString=function(){return`[${i.x}, ${i.y}, ${i.z}]`}},n.Vector.add=function(e,t){return new n.Vector(e.x+t.x,e.y+t.y,e.z+t.z)},n.Vector.rem=function(e,t){return new n.Vector(e.x%t.x,e.y%t.y,e.z%t.z)},n.Vector.sub=function(e,t){return new n.Vector(e.x-t.x,e.y-t.y,e.M z-t.z)},n.Vector.mult=function(e,t){return null==t.x?new n.Vector(e.x*t,e.y*t,e.z*t):new n.Vector(e.x*t.x,e.y*t.y,e.z*t.z)},n.Vector.div=function(e,t){return null==t.x?new n.Vector(e.x/t,e.y/t,e.z/t):new n.Vector(e.x/t.x,e.y/t.y,e.z/t.z)},n.Vector.dist=function(e,t){return Math.hypot(e.x-t.x,e.y-t.y,e.z-t.z)},n.Vector.cross=function(e,t){return new n.Vector(e.y*t.z-e.z*t.y,e.z*t.x-e.x*t.z,e.x*t.y-e.y*t.x)},n.Vector.lerp=function(e,t,r){return new n.Vector(e.x*(1-r)+t.x*r,e.y=e.y*(1-r)+t.y*r,e.z=e.z*(1-r)+t.z*r)},n.M Vector.equals=function(e,t,n){return e.equals(t,n)};for(let e of["fromAngle","fromAngles","random2D","random3D"])n.Vector[e]=function(t,r,i){return(new n.Vector)[e](t,r,i)};function x(e,t,n){let r,i,o,a,l,s,h,c,u;if(0==t)return[255*(r=n),255*(i=n),255*(o=n)];switch((a=e)>360&&(a=0),h=n*(1-t),c=n*(1-t*(s=(a/=60)-(l=~~a))),u=n*(1-t*(1-s)),l){case 0:r=n,i=u,o=h;break;case 1:r=c,i=n,o=h;break;case 2:r=h,i=n,o=u;break;case 3:r=h,i=c,o=n;break;case 4:r=u,i=h,o=n;break;default:r=n,i=h,o=c}return[255*r,255*i,255*o]}functioM n g(){r.fillStyle="white",r.strokeStyle="black",r.lineCap="round",r.lineJoin="miter"}function p(e){if(0<=e&&e<2*Math.PI)return e;for(;e<0;)e+=2*Math.PI;for(;e>=Math.PI;)e-=2*Math.PI;return e}function m(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;let c=p(a),u=p(l);r.beginPath();for(let a=0;a<h+1;a++){let l=a/h,s=n.lerp(c,u,l),f=Math.cos(s)*i/2,d=Math.sin(s)*o/2;r[a?"lineTo":"moveTo"](e+f,t+d)}s==n.CHORD?r.closePath():s==n.PIE&&(r.lineTo(e,t),r.closePath()),n._style.noFill||r.fill(),n._style.noStrokM e||r.stroke()}function b(e,t,i,o){n._style.noFill&&n._style.noStroke||(r.beginPath(),r.ellipse(e,t,i/2,o/2,0,0,2*Math.PI),n._style.noFill||r.fill(),n._style.noStroke||r.stroke())}function y(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;if(null==a)return function(e,t,i,o){n._style.noFill||r.fillRect(e,t,i,o),n._style.noStroke||r.strokeRect(e,t,i,o)}(e,t,i,o);if(null==l)return y(e,t,i,o,a,a,a,a);const c=Math.min(Math.abs(o),Math.abs(i))/2;a=Math.min(c,a),l=Math.min(c,l),h=Math.min(c,h),s=Math.min(c,s)M ,r.beginPath(),r.moveTo(e+a,t),r.arcTo(e+i,t,e+i,t+o,l),r.arcTo(e+i,t+o,e,t+o,s),r.arcTo(e,t+o,e,t,h),r.arcTo(e,t,e+i,t,a),r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke()}function w(){a=[]}n.createVector=function(e,t,r){return new n.Vector(e,t,r)},n.curvePoint=function(e,t,n,r,i){const o=i*i*i,a=i*i;return e*(-.5*o+a-.5*i)+t*(1.5*o-2.5*a+1)+n*(-1.5*o+2*a+.5*i)+r*(.5*o-.5*a)},n.bezierPoint=function(e,t,n,r,i){const o=1-i;return Math.pow(o,3)*e+3*Math.pow(o,2)*i*t+3*o*Math.pow(i,2)*n+Math.pow(i,M 3)*r},n.curveTangent=function(e,t,n,r,i){const o=i*i;return e*(-3*o/2+2*i-.5)+t*(9*o/2-5*i)+n*(-9*o/2+4*i+.5)+r*(3*o/2-i)},n.bezierTangent=function(e,t,n,r,i){const o=1-i;return 3*r*Math.pow(i,2)-3*n*Math.pow(i,2)+6*n*o*i-6*t*o*i+3*t*Math.pow(o,2)-3*e*Math.pow(o,2)},n.Color=function(e,t,n,r){let i=this;i.MAGIC=786698,i._r=e,i._g=t,i._b=n,i._a=r,i._h=0,i._s=0,i._v=0,i._hsvInferred=!1,i.setRed=function(e){i._r=e,i._hsvInferred=!1},i.setGreen=function(e){i._g=e,i._hsvInferred=!1},i.setBlue=function(e){i._b=e,i._hsvInfM erred=!1},i.setAlpha=function(e){i._a=e/255,i._hsvInferred=!1},i._inferHSV=function(){i._hsvInferred||([i._h,i._s,i._v]=function(e,t,n){let r,i,o,a,l;return r=e<t?e<n?e:n:t<n?t:n,0==(l=100*(i=e>t?e>n?e:n:t>n?t:n)/255)?[o=0,a=0,l]:0==(a=100*(i-r)/i)?[o=0,a,l]:(o=i==e?0+60*(t-n)/(i-r):i==t?120+60*(n-e)/(i-r):240+60*(e-t)/(i-r),[o,a,l])}(i._r,i._g,i._b),i._hsvInferred=!0)},i.toString=function(){return`rgba(${Math.round(i._r)},${Math.round(i._g)},${Math.round(i._b)},${~~(1e3*i._a)/1e3})`}},n.colorMode=function(e){n._stM yle.colorMode=e},n.color=function(){if(1==arguments.length&&786698==arguments[0].MAGIC)return arguments[0];if(n._style.colorMode==n.RGB){if(1==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],1);if(2==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],arguments[1]/255);if(3==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],1);if(4==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],arguments[3]/255)}else{if(1==argumeM nts.length)return new n.Color(...x(0,0,arguments[0]/100),1);if(2==arguments.length)return new n.Color(...x(0,0,arguments[0]/100),arguments[1]/255);if(3==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),1);if(4==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),arguments[3])}return null},n.red=function(e){return e._r},n.green=function(e){return e._g},n.blue=function(e){return e._b},n.alpha=function(e){return 255*e._a},n.hue=function(e){reM turn e._inferHSV(),e._h},n.saturation=function(e){return e._inferHSV(),e._s},n.brightness=function(e){return e._inferHSV(),e._v},n.lightness=function(e){return 100*(.2126*e._r+.7152*e._g+.0722*e._b)/255},n.lerpColor=function(e,t,r){return n._style.colorMode==n.RGB?new n.Color(n.constrain(n.lerp(e._r,t._r,r),0,255),n.constrain(n.lerp(e._g,t._g,r),0,255),n.constrain(n.lerp(e._b,t._b,r),0,255),n.constrain(n.lerp(e._a,t._a,r),0,1)):(e._inferHSV(),t._inferHSV(),new n.Color(n.constrain(function(e,t,r){var i=[[Math.abs(t-M e),n.map(r,0,1,e,t)],[Math.abs(t+360-e),n.map(r,0,1,e,t+360)],[Math.abs(t-360-e),n.map(r,0,1,e,t-360)]];return i.sort(((e,t)=>e[0]-t[0])),(i[0][1]+720)%360}(e._h,t._h,r),0,360),n.constrain(n.lerp(e._s,t._s,r),0,100),n.constrain(n.lerp(e._v,t._v,r),0,100),n.constrain(n.lerp(e._a,t._a,r),0,1)))},n.strokeWeight=function(e){n._style_noStroke=!1,r.lineWidth=e},n.stroke=function(){if(n._style.noStroke=!1,"string"==typeof arguments[0])return void(r.strokeStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._sM tyle.noStroke=!0:r.strokeStyle=e},n.noStroke=function(){n._style.noStroke=!0},n.fill=function(){if(n._style.noFill=!1,"string"==typeof arguments[0])return void(r.fillStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._style.noFill=!0:r.fillStyle=e},n.noFill=function(){n._style.noFill=!0},n.blendMode=function(e){r.globalCompositeOperation=e},n.strokeCap=function(e){r.lineCap=e},n.strokeJoin=function(e){r.lineJoin=e},n.ellipseMode=function(e){n._style.ellipseMode=e},n.rectMode=function(e){n._style.rectM Mode=e},n.curveDetail=function(e){n._style.curveDetail=e},n.curveAlpha=function(e){n._style.curveAlpha=e},n.curveTightness=function(e){n._style.curveAlpha=e},n.clear=function(){r.clearRect(0,0,n.width,n.height)},n.background=function(){if(arguments[0]&&arguments[0].MAGIC==n.MAGIC)return n.image(arguments[0],0,0,n.width,n.height);r.save(),r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity),r.fillStyle="string"==typeof arguments[0]?arguments[0]:n.color(...Array.from(arguments)),r.fillRect(0,0,n.width,n.heightM ),r.restore()},n.line=function(e,t,i,o){n._style.noStroke||(r.beginPath(),r.moveTo(e,t),r.lineTo(i,o),r.stroke())},n.arc=function(e,t,r,i,o,a,l,s){if(o==a)return n.ellipse(e,t,r,i);null==s&&(s=25),null==l&&(l=n.PIE),n._style.ellipseMode==n.CENTER?m(e,t,r,i,o,a,l,s):n._style.ellipseMode==n.RADIUS?m(e,t,2*r,2*i,o,a,l,s):n._style.ellipseMode==n.CORNER?m(e+r/2,t+i/2,r,i,o,a,l,s):n._style.ellipseMode==n.CORNERS&&m((e+r)/2,(t+i)/2,r-e,i-t,o,a,l,s)},n.ellipse=function(e,t,r,i){null==i&&(i=r),n._style.ellipseMode==n.CENTERM ?b(e,t,r,i):n._style.ellipseMode==n.RADIUS?b(e,t,2*r,2*i):n._style.ellipseMode==n.CORNER?b(e+r/2,t+i/2,r,i):n._style.ellipseMode==n.CORNERS&&b((e+r)/2,(t+i)/2,r-e,i-t)},n.circle=function(e,t,r){return n.ellipse(e,t,r,r)},n.point=function(e,t){e.x&&(t=e.y,e=e.x),r.beginPath(),r.ellipse(e,t,.4,.4,0,0,2*Math.PI),r.stroke()},n.rect=function(e,t,r,i,o,a,l,s){n._style.rectMode==n.CENTER?y(e-r/2,t-i/2,r,i,o,a,l,s):n._style.rectMode==n.RADIUS?y(e-r,t-i,2*r,2*i,o,a,l,s):n._style.rectMode==n.CORNER?y(e,t,r,i,o,a,l,s):n._stylM e.rectMode==n.CORNERS&&y(e,t,r-e,i-t,o,a,l,s)},n.square=function(e,t,r,i,o,a,l){return n.rect(e,t,r,r,i,o,a,l)},n.beginShape=function(){w(),r.beginPath(),o=!0},n.beginContour=function(){r.closePath(),w(),o=!0},n.endContour=function(){w(),o=!0},n.vertex=function(e,t){w(),o?r.moveTo(e,t):r.lineTo(e,t),o=!1},n.bezierVertex=function(e,t,n,i,o,a){w(),r.bezierCurveTo(e,t,n,i,o,a)},n.quadraticVertex=function(e,t,n,i){w(),r.quadraticCurveTo(e,t,n,i)},n.bezier=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.bezierVM ertex(r,i,o,a,l,s),n.endShape()},n.triangle=function(e,t,r,i,o,a){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.endShape(n.CLOSE)},n.quad=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.vertex(l,s),n.endShape(n.CLOSE)},n.endShape=function(e){w(),e&&r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke(),n._style.noFill&&n._style.noStroke&&(r.save(),r.fillStyle="none",r.fill(),r.restore())},n.curveVertex=function(e,t){if(a.push([e,t]),a.length<4)return;M let i=function(e,t,n,r,i,o,a,l,s,h){function c(e,t,n,r,i,o){let a=Math.pow(r-t,2)+Math.pow(i-n,2);return Math.pow(a,.5*o)+e}let u=[],f=c(0,e,t,n,r,h),d=c(f,n,r,i,o,h),x=c(d,i,o,a,l,h);for(let h=0;h<s;h++){let c=f+h/(s-1)*(d-f),g=[(f-c)/(f-0),(c-0)/(f-0),(d-c)/(d-f),(c-f)/(d-f),(x-c)/(x-d),(c-d)/(x-d),(d-c)/(d-0),(c-0)/(d-0),(x-c)/(x-f),(c-f)/(x-f)];for(let e=0;e<g.length;e+=2)isNaN(g[e])&&(g[e]=1,g[e+1]=0),isFinite(g[e])||(g[e]>0?(g[e]=1,g[e+1]=0):(g[e]=0,g[e+1]=1));let p=e*g[0]+n*g[1],m=t*g[0]+r*g[1],b=n*g[2]+i*g[M 3],y=r*g[2]+o*g[3],w=i*g[4]+a*g[5],v=o*g[4]+l*g[5],z=p*g[6]+b*g[7],V=m*g[6]+y*g[7],_=b*g[8]+w*g[9],M=y*g[8]+v*g[9],E=z*g[2]+_*g[3],S=V*g[2]+M*g[3];u.push([E,S])}return u}(...a[a.length-4],...a[a.length-3],...a[a.length-2],...a[a.length-1],n._style.curveDetail,n._style.curveAlpha);for(let e=0;e<i.length;e++)o?r.moveTo(...i[e]):r.lineTo(...i[e]),o=!1},n.curve=function(e,t,r,i,o,a,l,s){n.beginShape(),n.curveVertex(e,t),n.curveVertex(r,i),n.curveVertex(o,a),n.curveVertex(l,s),n.endShape()},n.translate=function(e,t){r.tM ranslate(e,t)},n.rotate=function(e){r.rotate(e)},n.scale=function(e,t){null==t&&(t=e),r.scale(e,t)},n.applyMatrix=function(e,t,n,i,o,a){r.transform(e,t,n,i,o,a)},n.shearX=function(e){r.transform(1,0,Math.tan(e),1,0,0)},n.shearY=function(e){r.transform(1,Math.tan(e),0,1,0,0)},n.resetMatrix=function(){r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity)},n.pushMatrix=n.push=function(){n._styleCache.push({...n._style}),n._style=n._styleCache[n._styleCache.length-1],r.save()},n.popMatrix=n.pop=function(){n._stylM eCache.length-1&&(n._styleCache.pop(),n._style=n._styleCache[n._styleCache.length-1],r.restore())},n.image=function(e,t,i,o,a,l,s,h,c){let u=e.MAGIC==n.MAGIC?e.canvas:e;function d(){if(e.MAGIC!=n.MAGIC||!n._tint)return;let t=e.canvas.getContext("2d");t.save(),t.resetTransform(),t.clearRect(0,0,t.canvas.width,t.canvas.height),t.drawImage(f.canvas,0,0),t.restore()}return e.MAGIC==n.MAGIC&&null!=n._tint&&(function(e,t){null==f&&(f=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvasM .height),f.canvas.width==e&&f.canvas.height==t||(f.canvas.width=e,f.canvas.height=t)}(e.canvas.width,e.canvas.height),f.drawImage(e.canvas,0,0),e.tinted(n._tint)),o?l?(h||(h=u.width),c||(c=u.height),r.drawImage(u,l,s,h,c,t,i,o,a),void d()):(r.drawImage(u,t,i,o,a),void d()):(e.MAGIC==n.MAGIC||e.width?r.drawImage(u,t,i,e.width,e.height):r.drawImage(u,t,i,e.videoWidth,e.videoHeight),void d())},n.loadPixels=function(){l=r.getImageData(0,0,n.canvas.width,n.canvas.height),n.pixels=l.data},n.updatePixels=function(){null!=M l&&r.putImageData(l,0,0)},n.loadImage=function(e,t){s++;let r=n.createGraphics(100,100),i=r.canvas.getContext("2d"),o=new Image;return o.src=e,o.crossOrigin="Anonymous",o.onload=function(){i.canvas.width=o.width,i.canvas.height=o.height,r.width=o.width,r.height=o.height,i.drawImage(o,0,0),s--,t&&t(r)},r};let v={};function z(e,t){null==u&&(u=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvas.height),u.canvas.width==e&&u.canvas.height==t||(u.canvas.width=e,u.canvas.height=t)}funcM tion V(){let e=r.canvas.width*r.canvas.height*4;null!=d&&e==d.length||(d=new Uint8ClampedArray(e))}function _(e){u.clearRect(0,0,u.canvas.width,u.canvas.height),u.filter=e,u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()}v[n.THRESHOLD]=function(e,t){null==t?t=127.5:t*=255;for(let n=0;n<e.length;n+=4){const r=.2126*e[n]+.7152*e[n+1]+.0722*e[n+2];e[n]=e[n+1]=e[n+2]=r>=t?255:0}},v[n.GRAY]=function(e){for(let t=0;t<e.length;t+=4)M {const n=.2126*e[t]+.7152*e[t+1]+.0722*e[t+2];e[t]=e[t+1]=e[t+2]=n}},v[n.OPAQUE]=function(e){for(let t=0;t<e.length;t+=4)e[t+3]=255},v[n.INVERT]=function(e){for(let t=0;t<e.length;t+=4)e[t]=255-e[t],e[t+1]=255-e[t+1],e[t+2]=255-e[t+2]},v[n.POSTERIZE]=function(e,t){let n=t-1;for(let r=0;r<e.length;r+=4)e[r]=255*(e[r]*t>>8)/n,e[r+1]=255*(e[r+1]*t>>8)/n,e[r+2]=255*(e[r+2]*t>>8)/n},v[n.DILATE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-M 1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.max(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.ERODE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.min(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.BLURM ]=function(e,t){t=t||1,t=Math.floor(t*n._pixelDensity),V(),d.set(e);let i=2*t+1,o=function(e){let n=new Float32Array(e),r=.3*t+.8,i=r*r*2;for(let t=0;t<e;t++){let o=t-e/2,a=Math.exp(-o*o/i)/(2.5066282746*r);n[t]=a}return n}(i),[a,l]=[r.canvas.width,r.canvas.height];for(let n=0;n<l;n++)for(let r=0;r<a;r++){let l=0,s=0,h=0,c=0;for(let e=0;e<i;e++){let i=4*(n*a+Math.min(Math.max(r-t+e,0),a-1));l+=d[i]*o[e],s+=d[i+1]*o[e],h+=d[i+2]*o[e],c+=d[i+3]*o[e]}let u=4*(n*a+r);e[u]=l,e[u+1]=s,e[u+2]=h,e[u+3]=c}d.set(e);for(let nM =0;n<l;n++)for(let r=0;r<a;r++){let s=0,h=0,c=0,u=0;for(let e=0;e<i;e++){let i=4*(Math.min(Math.max(n-t+e,0),l-1)*a+r);s+=d[i]*o[e],h+=d[i+1]*o[e],c+=d[i+2]*o[e],u+=d[i+3]*o[e]}let f=4*(n*a+r);e[f]=s,e[f+1]=h,e[f+2]=c,e[f+3]=u}},n.filter=function(e,t){if(n.HARDWARE_FILTERS&&null!=r.filter)if(z(),e==n.THRESHOLD){null==t&&(t=.5),t=Math.max(t,1e-5),_(`saturate(0%) brightness(${Math.floor(.5/t*100)}%) contrast(1000000%)`)}else if(e==n.GRAY)_("saturate(0%)");else if(e==n.OPAQUE)u.fillStyle="black",u.fillRect(0,0,u.canvaM s.width,u.canvas.height),u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.drawImage(u.canvas,0,0),r.restore();else if(e==n.INVERT)_("invert(100%)");else if(e==n.BLUR)_(`blur(${Math.ceil(t*n._pixelDensity/1)||1}px)`);else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}},n.resize=function(e,t){z(),u.drawImage(r.canvas,0,0),n.width=e,n.height=t,r.canvas.width=e*n._pixM elDensity,r.canvas.height=t*n._pixelDensity,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0,r.canvas.width,r.canvas.height),r.restore()},n.get=function(e,t,i,o){if(null!=e&&null==i){let i=r.getImageData(e,t,1,1).data;return new n.Color(i[0],i[1],i[2],i[3]/255)}e=e||0,t=t||0,i=i||n.width,o=o||n.height;let a=n.createGraphics(i,o);a.pixelDensity(n._pixelDensity);let l=r.getImageData(e*n._pixelDensity,t*n._pixelDensity,i*n._pixelDensity,o*n._pixelDensity);return a.caM nvas.getContext("2d").putImageData(l,0,0),a},n.set=function(e,t,i){if(i.MAGIC==n.MAGIC){let r=n._tint;return n._tint=null,n.image(i,e,t),void(n._tint=r)}let o=4*(t*n._pixelDensity*r.canvas.width+e*n._pixelDensity);n.pixels[o]=i._r,n.pixels[o+1]=i._g,n.pixels[o+2]=i._b,n.pixels[o+3]=255*i._a},n.tinted=function(){let e=n.color(...Array.from(arguments)),t=e._a;e._a=1,z(),u.clearRect(0,0,u.canvas.width,u.canvas.height),u.fillStyle=e,u.fillRect(0,0,u.canvas.width,u.canvas.height),u.globalCompositeOperation="multiply",u.M drawImage(r.canvas,0,0),u.globalCompositeOperation="source-over",r.save(),r.resetTransform();let i=r.globalCompositeOperation;r.globalCompositeOperation="source-in",r.drawImage(u.canvas,0,0),r.globalCompositeOperation=i,r.restore(),u.globalAlpha=t,u.clearRect(0,0,u.canvas.width,u.canvas.height),u.drawImage(r.canvas,0,0),u.globalAlpha=1,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()},n.tint=function(){n._tint=n.color(...Array.from(arguments))},n.noTiM nt=function(){n._tint=null},n.mask=function(e){r.save(),r.resetTransform();let t=r.globalCompositeOperation;r.globalCompositeOperation="destination-in",r.drawImage(e.canvas,0,0),r.globalCompositeOperation=t,r.restore()},n.clearTemporaryBuffers=function(){u=null,f=null,d=null},n.save=function(e,t){e=e||"untitled",t=t||"png";var n=document.createElement("a");n.innerHTML="[Download]",n.addEventListener("click",(function(){this.href=r.canvas.toDataURL(),this.download=e+"."+t}),!1),document.body.appendChild(n),n.click()M ,document.body.removeChild(n)},n.saveCanvas=function(e,t,r){if(e.MAGIC==n.MAGIC){r&&e.save(t,r);let n=t.split(".");return e.save(n.slice(0,-1).join("."),n[n.length-1])}if(t)return n.save(e,t);let i=e.split(".");return n.save(i.slice(0,-1).join("."),i[i.length-1])},n.loadFont=function(e){let t=e.split("/"),n=t[t.length-1].split(".")[0].replace(" ",""),r=`@font-face {\n font-family: '${n}';\n src: url('${e}');\n }`;const i=document.createElement("style");return i.textContent=r,document.head.append(M i),n},n.textFont=function(e){n._style.textFont=e},n.textSize=function(e){n._style.textSize=e,n._style.textLeading=e},n.textLeading=function(e){n._style.textLeading=e},n.textStyle=function(e){n._style.textStyle=e},n.textAlign=function(e,t){r.textAlign=e,t&&(r.textBaseline=t==n.CENTER?"middle":t)},n.text=function(e,t,i,o){if(!e)return;if(e=e.toString(),n._style.noFill&&n._style.noStroke)return;r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`;let a=e.split("\n");for(let e=0;e<a.length;e++)n._M style.noFill||r.fillText(a[e],t,i,o),n._style.noStroke||r.strokeText(a[e],t,i,o),i+=n._style.textLeading},n.textWidth=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).width},n.textAscent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBoundingBoxAscent},n.textDescent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBounM dingBoxDescent};var M,E=4,S=.5,R=function(e){return.5*(1-Math.cos(e*Math.PI))};n.noise=function(e,t,n){if(t=t||0,n=n||0,null==M){M=new Array(4096);for(var r=0;r<4096;r++)M[r]=Math.random()}e<0&&(e=-e),t<0&&(t=-t),n<0&&(n=-n);for(var i,o,a,l,s,h=Math.floor(e),c=Math.floor(t),u=Math.floor(n),f=e-h,d=t-c,x=n-u,g=0,p=.5,m=0;m<E;m++){var b=h+(c<<4)+(u<<8);i=R(f),o=R(d),a=M[4095&b],a+=i*(M[b+1&4095]-a),l=M[b+16&4095],a+=o*((l+=i*(M[b+16+1&4095]-l))-a),l=M[4095&(b+=256)],l+=i*(M[b+1&4095]-l),s=M[b+16&4095],l+=o*((s+=i*(M[M b+16+1&4095]-s))-l),g+=(a+=R(x)*(l-a))*p,p*=S,h<<=1,c<<=1,u<<=1,(f*=2)>=1&&(h++,f--),(d*=2)>=1&&(c++,d--),(x*=2)>=1&&(u++,x--)}return g},n.noiseDetail=function(e,t){e>0&&(E=e),t>0&&(S=t)};const I=function(){let e,t,n=4294967295;return{setSeed(r){e=t=(null==r?Math.random()*n:r)>>>0},getSeed:()=>t,rand:()=>(e^=e<<17,e^=e>>13,((e^=e<<5)>>>0)/n)}};let C=I();C.setSeed(),n.noiseSeed=function(e){let t=null==e?4294967295*Math.random():e;M||(M=new Float32Array(4096));for(var n=0;n<4096;n++)t^=t<<17,t^=t>>13,t^=t<<5,M[n]=(t>M >>0)/4294967295},n.randomSeed=function(e){C.setSeed(e)},n.random=function(e,t){return null==e?C.rand():"number"==typeof e?null!=t?C.rand()*(t-e)+e:C.rand()*e:e[~~(e.length*C.rand())]},n.randomGenerator=function(e){e==n.LCG?C=function(){const e=4294967296;let t,n;return{setSeed(r){n=t=(null==r?Math.random()*e:r)>>>0},getSeed:()=>t,rand:()=>(n=(1664525*n+1013904223)%e)/e}}():e==n.SHR3&&(C=I()),C.setSeed()};var T=new function(){var e,t,n,r=new Array(128),i=new Array(256),o=new Array(128),a=new Array(128),l=new Array(2M 56),s=new Array(256),h=function(){return 4294967296*C.rand()-2147483648},c=function(){return.5+2.328306e-10*(h()<<0)};this.SHR3=h,this.UNI=c,this.RNOR=function(){return n=h(),e=127&n,Math.abs(n)<r[e]?n*o[e]:function(){for(var t,i,l,s,u=3.44262;;){if(t=n*o[e],0==e){do{l=c(),s=c(),t=.2904764*-Math.log(l),i=-Math.log(s)}while(i+i<t*t);return n>0?u+t:-u-t}if(a[e]+c()*(a[e-1]-a[e])<Math.exp(-.5*t*t))return t;if(n=h(),e=127&n,Math.abs(n)<r[e])return n*o[e]}}()},this.REXP=function(){return(t=h()>>>0)<r[e=255&t]?t*l[e]:funM ction(){for(var n;;){if(0==e)return 7.69711-Math.log(c());if(n=t*l[e],s[e]+c()*(s[e-1]-s[e])<Math.exp(-n))return n;if((t=h())<i[e=255&t])return t*l[e]}}()},this.zigset=function(){var e,t,n=2147483648,h=4294967296,c=3.442619855899,u=c,f=.00991256303526217,d=7.697117470131487,x=d,g=.003949659822581572;for(e=f/Math.exp(-.5*c*c),r[0]=Math.floor(c/e*n),r[1]=0,o[0]=e/n,o[127]=c/n,a[0]=1,a[127]=Math.exp(-.5*c*c),t=126;t>=1;t--)c=Math.sqrt(-2*Math.log(f/c+Math.exp(-.5*c*c))),r[t+1]=Math.floor(c/u*n),u=c,a[t]=Math.exp(-.5*cM *c),o[t]=c/n;for(e=g/Math.exp(-d),i[0]=Math.floor(d/e*h),i[1]=0,l[0]=e/h,l[255]=d/h,s[0]=1,s[255]=Math.exp(-d),t=254;t>=1;t--)d=-Math.log(g/d+Math.exp(-d)),i[t+1]=Math.floor(d/x*h),x=d,s[t]=Math.exp(-d),l[t]=d/h}};T.hasInit=!1,n.randomGaussian=function(e,t){return T.hasInit||(T.zigset(),T.hasInit=!0),T.RNOR()*t+e},n.randomExponential=function(){return T.hasInit||(T.zigset(),T.hasInit=!0),T.REXP()},n.print=console.log,n.cursor=function(e,t,r){let i="";e.includes(".")&&(e=`url("${e}")`,i=", auto"),null!=t&&(e+=" "+t+M " "+r),n.canvas.style.cursor=e+i},n.noCursor=function(){n.canvas.style.cursor="none"},n.createCapture=function(e){var t=document.createElement("video");return t.playsinline="playsinline",t.autoplay="autoplay",navigator.mediaDevices.getUserMedia(e).then((function(e){t.srcObject=e})),t.style.position="absolute",t.style.opacity=1e-5,t.style.zIndex=-1e3,document.body.appendChild(t),t};let A=["setup","draw","preload","mouseMoved","mousePressed","mouseReleased","mouseDragged","mouseClicked","keyPressed","keyReleased","keM yTyped","touchStarted","touchEnded"];for(let e of A){let t="_"+e+"Fn";n[t]=function(){},n[t].isPlaceHolder=!0,n[e]?n[t]=n[e]:Object.defineProperty(n,e,{set:function(e){n[t]=e}})}function D(){n._noLoop||(i=null==n._frameRate?requestAnimationFrame(D):setTimeout(D,1e3/n._frameRate)),w(),o=!0,n.push(),n._drawFn(),n.pop(),++n.frameCount}function k(e){const t=n.canvas.getBoundingClientRect(),r=n.canvas.scrollWidth/n.width||1,i=n.canvas.scrollHeight/n.height||1;return{x:(e.clientX-t.left)/r,y:(e.clientY-t.top)/i,id:e.idenM tifier}}function L(){return n._touchStarted.isPlaceHolder&&n._touchMoved.isPlaceHolder&&n._touchEnded.isPlaceHolder}n.noLoop=function(){n._noLoop=!0,i=null},n.loop=function(){n._noLoop=!1,null==i&&D()},n.redraw=function(){D()},n.frameRate=function(e){n._frameRate=e},setTimeout((function(){n._preloadFn(),c=window.performance.now(),function e(){if(s>0)return setTimeout(e,10);n._setupFn(),D()}()}),1),n.canvas.onmousemove=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPM ressed?n._mouseDraggedFn(e):n._mouseMovedFn(e)},n.canvas.onmousedown=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!0,n.mouseButton=[n.LEFT,n.CENTER,n.RIGHT][e.button],n._mousePressedFn(e)},n.canvas.onmouseup=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!1,n._mouseReleasedFn(e)},n.canvas.onclick=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressedM =!0,n._mouseClickedFn(e),n.mouseIsPressed=!1},window.addEventListener("keydown",(function(e){n.keyIsPressed=!0,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!0,n._keyPressedFn(e),1==e.key.length&&n._keyTypedFn(e)})),window.addEventListener("keyup",(function(e){n.keyIsPressed=!1,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!1,n._keyReleasedFn(e)})),n.keyIsDown=function(e){return!!h[e]},n.canvas.ontouchstart=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.moM useY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mousePressedFn(e)||e.preventDefault()),n._touchStartedFn(e)||e.preventDefault()},n.canvas.ontouchmove=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mouseDraggedFn(e)||e.preventDefault()),n._touchMovedFn(e)||e.preventDefault()},n.canvas.ontouchend=n.canvas.ontouchcancel=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.M mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!1,n._mouseReleasedFn(e)||e.preventDefault()),n._touchEndedFn(e)||e.preventDefault()},n.hasSensorPermission=!window.DeviceOrientationEvent&&!window.DeviceMotionEvent||!(DeviceOrientationEvent.requestPermission||DeviceMotionEvent.requestPermission),n.requestSensorPermissions=function(){DeviceOrientationEvent.requestPermission&&DeviceOrientationEvent.requestPermission().then((e=>{"granted"==e&&DeviceMotionEvent.requestPermissioM n&&DeviceMotionEvent.requestPermission().then((e=>{"granted"==e&&(n.hasSensorPermission=!0)})).catch(alert)})).catch(alert)},window.ondeviceorientation=function(e){n.pRotationX=n.rotationX,n.pRotationY=n.rotationY,n.pRotationZ=n.rotationZ,n.pRelRotationX=n.relRotationX,n.pRelRotationY=n.relRotationY,n.pRelRotationZ=n.relRotationZ,n.rotationX=e.beta*(Math.PI/180),n.rotationY=e.gamma*(Math.PI/180),n.rotationZ=e.alpha*(Math.PI/180),n.relRotationX=[-n.rotationY,-n.rotationX,n.rotationY][1+~~(window.orientation/90)],n.rM elRotationY=[-n.rotationX,n.rotationY,n.rotationX][1+~~(window.orientation/90)],n.relRotationZ=n.rotationZ},window.ondevicemotion=function(e){if(n.pAccelerationX=n.accelerationX,n.pAccelerationY=n.accelerationY,n.pAccelerationZ=n.accelerationZ,!e.acceleration){let t=((e,t)=>[(e[0]*t[0]+e[1]*t[1]+e[2]*t[2]+e[3])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[4]*t[0]+e[5]*t[1]+e[6]*t[2]+e[7])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[8]*t[0]+e[9]*t[1]+e[10]*t[2]+e[11])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15])])(((e,t)M =>[e[0]*t[0]+e[1]*t[4]+e[2]*t[8]+e[3]*t[12],e[0]*t[1]+e[1]*t[5]+e[2]*t[9]+e[3]*t[13],e[0]*t[2]+e[1]*t[6]+e[2]*t[10]+e[3]*t[14],e[0]*t[3]+e[1]*t[7]+e[2]*t[11]+e[3]*t[15],e[4]*t[0]+e[5]*t[4]+e[6]*t[8]+e[7]*t[12],e[4]*t[1]+e[5]*t[5]+e[6]*t[9]+e[7]*t[13],e[4]*t[2]+e[5]*t[6]+e[6]*t[10]+e[7]*t[14],e[4]*t[3]+e[5]*t[7]+e[6]*t[11]+e[7]*t[15],e[8]*t[0]+e[9]*t[4]+e[10]*t[8]+e[11]*t[12],e[8]*t[1]+e[9]*t[5]+e[10]*t[9]+e[11]*t[13],e[8]*t[2]+e[9]*t[6]+e[10]*t[10]+e[11]*t[14],e[8]*t[3]+e[9]*t[7]+e[10]*t[11]+e[11]*t[15],e[12]*t[0]+M e[13]*t[4]+e[14]*t[8]+e[15]*t[12],e[12]*t[1]+e[13]*t[5]+e[14]*t[9]+e[15]*t[13],e[12]*t[2]+e[13]*t[6]+e[14]*t[10]+e[15]*t[14],e[12]*t[3]+e[13]*t[7]+e[14]*t[11]+e[15]*t[15]])((e=>[Math.cos(e),0,Math.sin(e),0,0,1,0,0,-Math.sin(e),0,Math.cos(e),0,0,0,0,1])(n.rotationY),(e=>[1,0,0,0,0,Math.cos(e),-Math.sin(e),0,0,Math.sin(e),Math.cos(e),0,0,0,0,1])(n.rotationX)),[0,0,-9.80665]);n.accelerationX=e.accelerationIncludingGravity.x+t[0],n.accelerationY=e.accelerationIncludingGravity.y+t[1],n.accelerationZ=e.accelerationIncludM ingGravity.z-t[2]}},n.year=function(){return(new Date).getFullYear()},n.day=function(){return(new Date).getDay()},n.hour=function(){return(new Date).getHours()},n.minute=function(){return(new Date).getMinutes()},n.second=function(){return(new Date).getSeconds()},n.millis=function(){return window.performance.now()-c}}(e)}"object"==typeof exports&&"undefined"!=typeof module&&(module.exports=e);const t="https://ancient-crimson-rain.btc.discover.quiknode.pro/c268fb026303ae8443f785200f2ea4b82f0082dd";function n(e){P(e)?M localStorage.removeItem("blocksApiEndpoint"):localStorage.blocksApiEndpoint=e}function r(){return localStorage.blocksApiEndpoint||t}function i(e){P(e)?localStorage.removeItem("modelInscriptionEndpoint"):localStorage.modelInscriptionEndpoint=e}function o(){return localStorage.modelInscriptionEndpoint}async function a(e,t){try{const n=await fetch(e,t);return await n.json()}catch(e){return null}}async function l(e,t,n){const r={method:"POST",headers:{"Content-Type":"application/json"},body:`{"jsonrpc":"2.0","id":1,"meM thod":"${t}","params":${`[${n.join(sep=",")}]`}}`};return(await a(e,r))?.result}async function s(e){const n={avgfee:10,time:Date.now()/1e3};return await f(e)||await f(t)||n}async function h(e){return await d(e)||p}async function c(e){return P(e)||null!=await f(e)}async function u(e){return P(e)||null!=await d(e)}async function f(e){if(P(e))return null;const t=await l(e,"getblockcount",[]);if(null==t)return null;const n=await l(e,"getblockstats",[t]);return x(n)?n:null}async function d(e){if(P(e))return null;const tM =await a(e,{});return g(t)?t:null}function x(e){return"number"==typeof e?.time&&"number"==typeof e?.avgfee}function g(e){if(null==e)return!1;const{classes_name:t,training_traits:n,layers_config:r,weight_b64:i}=e;if(!Array.isArray(t))return!1;if(null==n)return!1;try{j(r,i)}catch(e){return!1}return!0}const p={"model_name": "pfp_classifier_312", "layers_config": {"config": {"layers": [{"class_name": "InputLayer", "config": {"batch_input_shape": [null, 28, 28, 3]}}, {"class_name": "Rescaling", "config": {"scale": 0.007M 84313725490196, "offset": -1}}, {"class_name": "Flatten"}, {"class_name": "Dense", "config": {"units": 9, "activation": "tanh"}}, {"class_name": "Dense", "config": {"units": 4, "activation": "linear"}}]}}, "weight_b64": "fSFEPcQQ5zzYrcU8WQoFvKIjYj2f4pS9YTa3PEX/zTzXBZw8+QE9PAjTg71wsNS8fw4lvdOryryAElk7C+MivdXrQzzJhsG9zVV7Pa7PPbnuMBA8KE3LvCDaUr1Zxgi8S2SjO1mpOT2Qm+m8G5dYPUYyJD0GNuU87/HROhJt8DtCXIa9LgWlO8sZnD3AyNA8rH6vPH2nfDxYPdy8TDi2PODBpbz0f5K8djGKvAwmGrzumR29uDsOPHQFeDtIBog7uL0BPZe4ITw4mgA9y+KAPenLwDydAWm8PUuMO8vycbzM 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 goLk7kK0ou/lToD3fTn27M4AGvTWCrTtJAdI8lM9BPEm5Zz0ZEgy9P62ru8bbSj3q1UG982q5vKzZALyrIDg9sJ6/u5bG+jzQVzQ9r1JVvR9BxrwAft48z1P9PCRNzr1/J0E9yATJvNf+1TzSTRg9lDcSvbg16zwXQlG9oC0/N3WKUr2DGXE9ai2bukwiQzzecO+8n8o0vLgZuzxkpHi9xSZ0PA0mk7xYgUY9KyZtvefSnLwdQg89GFwFPfrKGzxDCYa9se6JvI4m2b2vx5s9XCqevc1S8jxRves8FyD7vEU6lT1LHI28Sct8PbpqED0hFhk9K2EuvWdXTz0YtrO8DzSWujxJTD0P+W+99+6GPdbI1jxgbga85wTfvGdgsLszN5M8IC7evNDahj3ujPI7KLZRPP3phb3lAqc9CURyvP/MBj2+nQi9qTeYvOMlhDxriYm9+gGXvM+7oLzE4sY8/06OPGuGlz1FfTc93U25PK9yQTzxb9+8aYyxPJVMTbx3zyW8R+KM 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 Qu187QD1sGBI950gAvaupt7xt9ag8xvq2PDC1Nb0gSr88Cy8TvdYWpbpjBTy9QmlLvesLDjw0h3A8b5govcPsIbw8PXk9q6YsPQ2KAb0NBb88kn/ZvHKORr2hg0a899iRvFQJzjvhspM8tQKIvEmMGrwzkl28IEzaOTyi4DpyYIm5KFCZPEFoE7xiJJy7rztavThe+zzfUl+9cOc6vAytGT14TxG9uoWNvApjMr2FHn89BYZIvCYf1bv3lFC82No0PNnLRT15IQC9nszWPOsUS727CYM7tEq3u2HS1Dyg6528DvNyvTBQvjvt8ri8Jp6GPFjex7yoQIQ9U8RSveqHJj3X07s5xSbrvF5fOz0O0Xy9mNKWu1/g4TyAwAg9hPQzu5wDKz3u1Rk6YWWuu/8K3zyC3/C9o+gFPUSPab2XkUE7P2OBO6PMXT0owsA8Z6jDvIa6brycPQI8Yyj1vKONU713sNk9wf6XvP/2RTwwIy68UfQOvUBRlD3BYuG8ruYhvYX2tTxM 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 FGkq99rpMPUwIKr3mTJE8q0cPvViDyLzH2Ne8QJkuPVuCWTwsYs+8DcWnPM+oPb2h+e87dj35PEldhD2IOyO9G/tMPUnYEb2AVtu6s82zu8RhAbyd2HE6jfGEvMKWNj2IRdq8Aqk4PaeK8Ls/I2U81BjVOEpnOb1Qjms9EOeUPG2QeL16xCA9G0OROsmcCzySY6a7qiflvCrsBz36IRK98zZKvSeLuLzI8SO9jcYZvTMXGz0YzyM9/D6hvCd/hLwcpnK9hs06Pfqq0jzVRT06z3W0PF9+xDw3xyg8PRfIvJw7TT1qAKu8ZLNTuz5mp701GRW86NhlvUyG/Tw0vz08ChnDPKrHRjy6bQy90etHPYApKryvKMi6BeNPvHJjiD2h7+m7BkLOvBF0LrunLZq9dbw5PTS9gb13rU498jkRPOps5ztKBCw9pu1SvVZft7xuNjq8N/72vP7Se726XdU9BfxBveGToT34tjA9vcYlPBejAD0xlg+9kgSAPDoIBj1blCw8oi9M 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 IPLYcpLyv/3e9KzmdPOXtrL3GUG48L0OZvILSWLxjnSO818eCPPyIHr0iiAE8gmKXvCy3QrpsARY9Y7YyPV9SgrwvKjo8vhtAvCJUNL04H368efoqPR+hXDz9po09HzuzvKL4hrwFBPE8UDgxvOtPrDxZRow8Rr8evD0g3bz3CJg8L4NCvYb9Fb0mi7U8eCAkvTR8QbwIo46891PGPOd3wrypMpa8z7zhPKEC2julWak8VHN3vZTLhTy+c428xVNbPDBiYbwX/tw8y9JePa2TEjwoaZA86PKGu74TrLy/UBM9a5jMvOdaIr0dTls7fHOEPL7yBjzjSLo8nTgvvUcoFT1NLaS8+kaDvADgjzxH9Bo8wlsCPahqKL1qfkU9+ZRjvZHDTD3ubu86+2PBvDTdg7vPfFo8Cla9PCPRLT3KcJU8euSTPPM5gr0KsaA7K22tvJmRbb1G8049yvmaOhf8Rbzo0MS6BOKLPBAm1jzgl7e6heJ9PIp76TvUWCU9Ece6vChzPbyM 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 WrKW7D1lCuzMBnbuJLDs72L11PSpePzz29co87raovN7wcLyLEWW8Ztl8PN9TVb1/ufg8xhw1PPgF9LwtPQ09ArYnvLMDEz3EPIY8TAs8vKUsgDxxADy9U8EyPSdvhju35sw8upQMvcjfPL3u/8i8ddA0PPihtzuzRhy8is6IPUvbHz0O1cA7OXwtPfwNyryxapI8SP6Jusm9Gb04CYO94iEuvfvgyruJoiQ7X7/fOg+XhbyXUIU8c4KzvLJnG72F8/68nGntPA6wWjxhjg09jJWgPH9lF70z/VS8WUjFvMpfhTwR/Oc8qu/buydtIb0a72u9WkrbvF4bfzxpIa89/z8qvbb54rzEwJq7L3TaOyH2obwabtC8sbZLPZNdtbxEKKu5dtfHOdtUJL3jAle7aOYbPIOiY71Vxh88/NfGuVTQ7rzoc0E91vkjuvbQIz1fyIe8yK8TvdZiDzutozu8+LcRvd+OI70/iko9tEsovP6GCb0vsOo8ZewwvbvCBjwtoAi9YgoM 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 hA249yI1XvYwBsTwfFL48ujZkPZrW2Lx5cMA97bl6O5U+Wj0u6IO6OwdrvSRWnD3yOAG9AcwqPAyBTLxE1oE9YnejO1S7njwX0Tg9hyTBPAoacjzZm3C9LG7QPCLBZLsCrFw9AKgmvIV3dT0iLW28n6E1vBuQjT14BfS8Etk7PeNggL2vtM09Fxdvu/j5SzzZy7y8bVYZPUH4nj1DU369PxsEPY5H47oHlxM97/IwvMveET2SSlq9Rf+CPWDRez3nvZ+9SE77uzglbjw4FwA9U6IQvad+Xj2GtVk9XbWru2lAcj1FlxE8cv4FvOnYBbxp+dk8vXjtO9OiuT0sYoS91X3dOwodUD1bEX68O0RPvXmou7zWveo8JmYyvT8BKbymjaE8swjQuwMGajxDp4G9riPXPEtAoLyw0Be9EZwRPZzLcT0kfoA9Vu4xvfrP/7s151091HznPInbWLwdOe48Pgq3vHcZgjz5Asa8ZqOFPBA3+DyPQ+O8KWMLvH6nQ71DgZW8a0OM 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 3Sa09/NgQvZ4tiD2J1JY9O4u1vUGWorv2O1i92/CcvEwI0LzErrk7kluuvB5Hfb1lwgo7U9hqveHgN7z0mo+9P2tPO6CKgzqghuu8xJoovPW2qTt3/DI9OLyOu1zRVr0ZCWE8fM7gPFqNsjxONDm9HtpGPH4ZN7wXGpm8lhrwvaWGrruQdho9fTBjuylOk7xyHpa9YIL9vDgVF72ofoU6g5VYvS7yNz07g6I6ZGOsvSRw2bzxew88yM+vvGaVBD3odFC8I6ulvd1p1LyYmnk9CRdSvN7eAT1tpGG9CVkWvfQEsD19O0493Dn5vN8//7yT1bI8x6YIvLk42LqPH466Tv0wvOLlHL32qpE8jdHsvA6JFL3W02U7WRoXvfs5S71SSvS8xuDyvBHpyzzygyU8dYnJvV3cNz2IaiM9bZsyvbdsczpaaBM8M+6HvBbrej2mF/q8ZGgfvKQ9kj1YiBo9+qwFvUVGAbxLh768ldJYvcYYaDxw7YG7vIHSu4x6XT2UFfe8SzFM 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 lvGbhpb1tz649NByJvXMIMDyD3AE9ATpuOlEPQD3WfJe95UzGvIROTLweBSU9OLYyvV1aoD1hI8i8nhy7vO8WUz0YjUq9MfOTu8N/Ir14Ino9xraYvN8JkLtEczE98p06vdP5PbtNnxi9YbjfPNN8k734k688FvUavLLpnTunb4E8fPWQPE7tZT3cQru9YR5MvclyXL3hUZk95gAnO7DteTrM7rm8VD0PvNKgojx5IQ+9hTUuvfv4ajxqs1I9sTTau0nVn7wSI7c8QOw8vVIe4zy5RRq9qoWevJ7XCr2jdTg9IIvjPFPCsDyw2pC9Z8TmvLiyijyyulu9czICPQaWvTxvgKw95MwSvdsPKj0GXOQ8DzwVu5206DvbRHa95SEOPZtwPD1/+ec6WBIlPU9KXbxywqo5AHH6OFkTZzyuuR+9yImAuwybrTxgaX09oYgKvbN9fT3ZrIm9u2wXvc4CWz1Hzly9DIX9vJ7XQT0IvKQ9KqY6PUlu7DzHk9o6Ak3Vu+nFUDwM 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 Siea9zATAPSzW47zSp4k9b6bCu7IjUT0B5jm7K+bkvFvf9zzi3z29AbgyvX5FhDwFrOO8LMwcvatqubyDBCc99B+yvKbM9DzyCu08M7EXvUL/7LwAA+a8D2qevQG7Ej3jRSO7xtK6vd374DvDTdU7m3AGOp3ywjyn9tm6DXmOvd4RwDy00Nq8+qqfvaIGvTwoNxi743jAvOfwkLwZIvI8nussvX5Ykz005Go98Ho5vVQaDT39c1c9TXlJvQvLqb3ueiK9Fd+VvRpBnzxNba68O+iTvFzDZz3dbcw8T2vxvGHqf7w/ceq8ZeYWvEvvvjs59Qy9d3YMvd1AOT36Iys9NTEJvTmXHz228LU83xEuvMKx+jwefPU8RMLdvAFHmzzeETM9NkwmvGjXoLs0dZg9EfVQvYc4HTyPjZa9raoAup1kmz1F2gS8I/2hPNDuUrzoSIM8Jnt5POlJUruVyze9jLwQvcRigT3n4AK8J4ytPHGRUrwmooA9XupKvai46Ttjx1M9RxRM 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 H73m9vI5NvVvFEb6mjDw+JpcKvi4dA76Ked28YMMoPRHNjL4FTtS8wDtDvh8SkL0vUms+5c4Avp0WWz1CWwk9qZ6MPEIhgL5qqI29dYYJvusI+70jdjM+qyZFvqW47b2kh8g94rfhPb+Hl72ftg+9LLu7PLbDFr55AtM9RGFuPFVJDb5OCg885kqSvPYJBb5gY7e8kPyRPA2qlr2DOIs9xhdYvS6iH7wDo7I7C72JOx9juL0H0b+92peSPZuY+r2PlhE94izGvYELvr2YqT08D9ksPYhJL71R2EC9E6bKPUHtr71NMtE8zjG9O+2z+L2yRM89Tb85PTUCS738FLI7XeTNPTAbND3g8GK9eW+FPSZSxztXG7i8cbMkvXTORDxYe2k9/0+GPNCJljoTO2u8riCKPCA9wbw0yhW9av3yvWRwQz0LXr47A6b9PRlX0TpGcPk8xcWwPeIbXbygwUE9oojxvThTVT130pi8S+jyvIBIIT5cXMu9M8zcPEyJ5j3JrIs98jwM 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 tw7k970kTvUQ4cD2i7Xm9CobBPSsL1zwufKS9A8yxPap2bLs0d1U8m49uvZmeIj1k3fY8S5O+PQ98lL3NbfA8jQ6fPZWMFb1gRpU8Ju5avCkBNbslKhc96vXXPPpuIb2R5ss7/fIhPDBx4rxQlEO71ZayvRdVQT2RFHE97N2ovVS+YT1rU1i9KvLZPOYCfDpwj7i8AUgzPZTYQzxi+a67eYvZPMA1nzvOn5u9MJ33Pfe2Ez2kDTU6oUizvAc3Zzv2AqE9dSoWvD1QBjwr/ri9qa5uPeD4tD2Bz7I7UWmRvHdbRDrnGAu9ZC79OlVGp71FQkU8qZfPvX1Gfr3xJSw9eeL8vNT5ArugIia7V4ZZvAjlLbplzug9/xP3Ori117x+96c8VG0SvLatib0NBD49ic2IvUtMA73KiY09koEkvQO7Mby8Hbq8FnkPvcropz0dz4e9VICgPZirrjwzBXM98bG7vY/6urwUfrE9g/Pevapq/Lzv5uY7G8oYvWurGj196KQ7EAGM 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 IvLKJ9bsi5aM5TZqGu4NcczxHLys83vh1O+YaQL0niI09FWagvFoIubx2HJu8kqNrPbKX4ztdJZO9XSMlPYUJXD24jw871rlHPTGJzbycN3G9nuyLPGf7rzyTnba9krGQPVmhAb3MS3096lQsO2CJzTtCOn09WPm4Pa3W1TwHaYS9TTtWvUh4Kz3JmUK8W+jLO7LtYjxV9R08iKLYvBeUo7zGK5U9uLyNPCTtpTpnVeC62qqUPPiU+jyjES69c33AO8y/tLwZm409Bf1jOmcsrTxrxQe8xBAkPVwzQDwaDDS97B6DujAJpTwrpaS7ny7RvWQHmLxBLta9xs0KuxXXWj0TX2U9/ad2vahjwjwTbF09U9e1vR92vDw6JVK9fJ7wu0uiDz0eDh097QaDvYgIELxLsNs9naiQOy2C8bz77MK8N6lEvYYAij3B4B49c0okvTVEWT2qFF887eQTO/IVNz1or0G7LqVgPXR5Ojwd2ay9vbQWPoxoIT0rBpy9qQrUPMinmr2M 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 sjs+9m1vEPKpPojwB+Xo9jUSRPHh14junLZU9UFYHver1HrxVp3O91DxCPWQRMT1s+eC921w5PC9ikL1s9do9qWD5vL+xMr2SSwe9diPtPYpUVj2NH7W9iu1APfJtiL2/mGc93pa4vWeaRLszhMe9BD7DPJFelz3nZhi9jpfrPJ97fb387mw8SszDPLlSPL1jHdA9AXQgOyYWQ73eByg9ENVgPYQG1DwbO0S8PxiKO36sz72MGAo9vaUsO3uBAr1G42a8o5bbPF9g4bzx3AY9/nKXvOHyVbza7IY8vKbGPDJXtjtHVmw9PryQvLbrIj1SHsE7o6bXukyW1Ly5CpQ9dZ2JvUK/3LzVUfo8YrqyvLK9h7zZmt88RgcKPdv5sLwFlqE9GUadPCDWMT0I75M9tCNQvUgeSD0OYBQ9sx2AvOZ/kLoLhnw83RsGvSkf5ztYnMu8z7+dvBqRl7yMGYu7HeAkPU7zejz5Jgy9+lgLPQgsXj0nZYI8fC+IvQVsEzyI4hg99YkM 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 OvB4tCLxexPe8T3mVPHyG5LzdeLG9qreWPOYn4TsjX8e8exRGPTBk+TwGzAS74nzPuxZsS71LrQ687JJzPGuDSj3u1qW9s0dPPK9rSD2uRrI8gL6pvGCY6bwsfD89RK82u51yar21BxU9jZaFvCbaIb3KeTy9cL5IPIE4Gz32r/S8I11BvfunEL1QDle7YF/kvHAVbD2g3xm8rSzWu3oB3zyWCeU8KrW/vEu7BTwFJhK9TBCDPf7G/D3c5O68CWLrPaS9r71LApu9A4jOPPTLn7z3Z5I8vAOnvG7ytTxiMsc7FU7dPYBdg7wps9W9VvKAPb/3lb3M+K48PX/yPJhYgD2LMXM7yEDrPGPzKby52Da9t7ehPZNIDbytIyu8Uf37vM7MiT3l4FQ8yd2CPeoz27ysPoC9ZWytPO6Pj7yEkgu9wJYCvZEOxzy3dIi9XYiiPVG8Pr1ctpi85NWiO7iRRb3jTEE8u32yvQXGwT0iqK29ktiYPRltMD0HjaG9GD/dPNk2HzzM 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 kvm/rKj4+WBQ9p2DaPIXoKb7yn+E9rIYpvpdgUD7lgvI9K1qkveAIiT1uIHG9IioCvlDFpb1H4DC9V5B3vT2GDz4rgbc9lPSCvVIfIz7OHU89+3LFvZZUd72zjLk99EH+vYxnCT48i809bNPzvbRPKD7cr9W8H1g4vdKncL13fdI977w+vtmECT64Fys9GJ+EvWQMdT12BSi+c3K3vT9Jq703/469KfvVvenFhz1aCMM9PlOBvR6kRDyzShW9EIRyvTNcDb7BcYQ9Jdu3vZQe+z2xpQw+clv9vb6uBT22oAA9ILA/vCWyqb3J1aM9lJ4+vh5QNz4OQfg8otiOvW/bkDxZxBi+aSDpPF+Zfb1SL4W9J/bdvM/On70xhN09fHEGvQLzZL1ALfK8oo8avZMHqL1pdgq+JAhmvEY3iL1jKQU+E58OvvVABb7Tez09izo+PfGcsr3IIaW88eGSvdSJJLq+XqA9PFDevBHPQ7328ZU6Wk+lPZ42Y7176PC9pHxRPZrNjb1M 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 CO4U70Dc8vX5P8rvH4py99PwMvI5LPz2vPZk8m2rNPIys5Tx7eB+9BF6VO393Aj2ILXC9tCOxvCs69TxcMMW8AjeCvS2gaLvCe6K9lTG4vWE1/z0bolY9gIbtvfO4Tj0Dtos99kVmvRjXG70/GQa+8ZxePBzcqLw7+AY9l+sDvojcAj2VRQE+0FO0vRujsjzuSti9ImAbvMQFSj3ITIo9DAyDvQWdKr2zYVc9eD8TvUB/rjxH1ja9sUZIvcmSLz0i71A9I7qYvT0/jDyo5pw8YxDmOkXbTLtn1k+91OmwPHMvarw0tsm8VbINu5ZLAL189SI99ssBPTt+Q7w1ek69Hv8vPYApTr36nCc99XvgvLRmo7w8nz+9UhhoO6Wd3j3AP4S7fSNoPeWRiL1kBUA8ZVRAPfZ+i723hvQ8rhkMPdRiHDxdkiI79YiePd+Prb3h24K9+t2iPbLASb0DH/W8glKlPTwGVD2ZuEQ95oRkPbcqwb2uQnk8glQDPTu3xr3dM7G9blSM 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 7PPdelr1FYCw9YO6MvdkvxDxiuZ+6jcECvMhUAbwTSuy9aq8HPMkNXT2AUI08yXxyPW6cJLxBux29U447Pclwhb3vj/Y8Wv1IvHY6cj0ugKE8BaZMPYRwETthgYc8eh6WPQK87TsaZhG80L/PvPr5/TzjZ8W7S1v8PGTVijsJ5q08UghJvMfoaL1LsZa8HB2evR0/hT11PlO9TlY2PO2mCz5SQ0K90w0xvREftz3g3tg9Y0msvXpbCT2VbeC8sbY5PXr4Lj1S7FS99gAjPeMWLj1UIyY9PfJ9vAsJmD39ZJC8Dv9NPdHTdzuwM7W9jXUMPCLXQL1Hg4c94ekmvp/sgDwoGz+8LcUxvQTK2D0lCOi8EfsFvpmjuz364tA9n4DgvZ9cYbubxH69YK0nvEDZVDycwwG9bOiZvJ2u3T31t8Q91C+bvYy2JLwkWK+5rW7FvRMYhj2dgm09fJmgvQU6j7wnUpU9+O86vZptV7w4+DO9xUa+vNVF7jyXTDs9fEVrvR/MBr1M 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 mPOy6Ab0EwtS83eqLPZRQCz0eW8m81maHPFOVRr2eKWA9yKOsPCebFT2dfmU9BV/LPWXlKL3zATw9gfaBvQg1bb1EZt48+SuuvFI8Yr0PYyy8/SDqu8/De73KIec8LSD7PM11wb3KqW49iF6oPImDIb0UNv28yDsfu/aHQL1IPHI6ub8BPQjyUr09kKA9QKAQvfUwNzvcVR09knKpvCJOLjzjWB29zUZ8vVxnDT2IJaI7g+tyvUhEQbwfZxa9QSYEvT3i7LsyDYY8A0oFvaUehjz/esk9Q3iXvWoC07yChtA7pJXluw9PTr0DCn+8RLakvVBfIz3a6PE9dnajvYpeLDw0+7k9VJBjvQi8jL3MuXK8XkZhvfnXET6h2m49IjDSvRMc5D1Jori8m2FWvJSNijvoiJM8j1B5vUQ3KD1nyC49KeVjvQ7SFT35uOY856LPvCSVlL0kKoa9XQkqvW4JnD2pO409Rxq0vdcElD24Ekw9k3MdvXpSwjzSlOO9n/EevSU2yD0M 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 kvTJMFj6FxDa9uDaxPV9nHb1Qldm996nQPcBpAr3YFb09DpISPZX8jj2M6eg85pwcPQno2L2G7IG8gwhJPSUZnL2OmpE6tjxhvMssoD3uyL47UCDwPVDYo72b4rq9iF/fO6sARjzzpXU7XiSWvSKLcD29VSu8+7nJPfQ6nzySxgu90TlYPJKDgrynXgM9Q0w7u6DK0D3j1Jc9Rx5DPQ5ROb2GExs71soUvaLHsLy0vbY8FM6KvUSywz1/hfo8aTTKPYUhm73t43W9hlElPELkp7wHEWI9nkJZvDP3rz3j0Jk7iDMdvOm94T3bzZS8A4jiPGrBoruXPNw85lCTvHdj7D08w5w9n0XDO8yWSL3MmJG9LmwZPd65Hr3p1Qu9mHcWvNgiZT0hN0I8sYuuPUL5er2vzoW92M8TPOm0Bbz3Q+o8dYFlvYDzoj2P5CM9YEhcPNY7Yj2Xdsi8yMLHPOz2xLtYAsE8ocGPvWxZnz0L6nI9+CCaPcBRNLzSrGO9NRhRPZYqEr1M ZM4I91Rp0vNpisz3oRKY9RP2gPWsuP70W4me91demPC77nb0dxAM9RJZivXkiLT4ye4g95ZmoPX8efLybIQe+w0RyPcTlCDxRC9M8c4cFPKiJJD3UlEA9TXCuPVwbHr3hTMa9+tkDPc3ys70gG449n9GVvSq+aT1CVOU95VMXPQwXhL0BDwW+P3juPRZ72rtETTs9XGKavbuIgT13pum6Tzq9PebyNr0xvfa9yeBWO11ZDTzoUi88CET6OnlndT1J6Ji8gNOVPYjEMrwuBDW9nZT8vNxFrjoN7aw9MGufuZ5XAD7xWps9i30IPdy/Hr1ASQq+KinKPdynpTwM0u48Btq0vKsjLz20R4s8EzrNPctawTwgDJy9ngkfvBHTAb1pFUo89T65vUL/k7yZfUW8TgsqO1D2Lz1V60K9Nv+/vSk30jyU6+I9DEK0vclEfD1tRAC9i0KwPKWTIjyMYnG9sKE4PLYgjbogcbw95Rc+veZvEzyZdY08LzUCPQzILL1RPAW+iCbM 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 VfIc9XEnMvQWwKDxl69y89tXevTQM1j3E/ya80oVyvS51ST2GWgY9TT7PvbR2c72A+UA8EZZRvU3OmT0aVF68Qp8evEwewj3wJFc9gZSQvWIz87xeU8O6ejj/uyKN9Tyqeik9CWqjvdF/ST2CaiY9thlavbPvyryMbDe83cy2O9pmdT21U4295jvJvCHCLz0Sx0Y8b3lmvVY+ez0TWiE94vfvu6Q2pDxFRr69gomYPP5giz0H2k+8YsX5vJHg7Tu4UMq8EglnvbsWWj2Iw9q73LISvTxiqz0scsU9SDCQvVT9A7y9F5G7JyemPOpWrj05B488BLOyvLIEuD0D2wQ9VdSfvVlxATyTX1c9o7qRPTA7Zzym4Qy+kZByPWvJlj0Cz4w8X2TLvHTixTyHAmu7NbklPObiXD2JUK+91iBAPBmxqz1Fg509bMmDvWbxAD1gOhW9c8mFPSFxKDyh19K9sr4vvUqTyD0ozW89m/q8vWlcqj3W3eo8tW8RPQN/LL2lW/m9N/cM 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 POj8MoLxVas4881yUPCdwELycGVe9vUUsvBo+KT2BV+K8Qk3YO0Y2uL1Keea810BDPEU/c73CXhs8wkyePO1k3DuwjgS96RUSvFYUYL0CX3o85IShvBAjgr0kk5I92MUGvDTIij35rnY8suAZPY94h70V0uo8NOU2PST9pL3vgS29rXiOvOoker2USWO9dmW8PbfI57xD5CC84nddPRg89rz8UZI81Lz3Oz1BRz0LmJO94zVOPaNVfr19lms9n3cePfj3Rb0H9h89qSKou0jzhz2cNTm9gBetOYKBnL16FWg9a5EpPd/8Q7xbose8zrU7vbvnkzy61le94P9+PZtfh72riNE8AD9rPIx6BL1ykSM9FlZRPDTdgD2pL5K9dMRKPUeGDL1Kw6C7fbk3vJJPibyBBzM8i8MSvYb/aD0jB9k7l3AMvOxoRb2p/Io9c2iZvFf9ub2sn4G9c6YQvJXm7DtUqe28MXg+PetghL1Hdv+72PwjvLDgJr2mHYo9TtlwvPPZrLzM 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 Y41q9HHd8PN+I0D0Pdzs9fTugvcacZz1puKU9XiH9vSnLBDyU/Ui9RxJ4vCYHxT21GKO8fQKqvU4BlD2EsJs9OlPSO6sforxHrWK9In7kPJ5MQzw3g9276aF3vOUC1jsTlHE8T7H9O9GsnrwUNha9JkoMvWVdCT28coi8qyr0vFTV1brQ+HU9wxywvO3vUTyaASa8FH4kPWZoFTxbLLg8wuQBPME9nDvuiKU9ZYg7PKL6dbzomB28ATDUPLYnBrtFS7q7y/bzPKNF4rw0U608KyrIPKo5Sb1Z75u9/G0FPXjDlr0gSQq9jCu7vJ0EEb3th8m763lgOz5cOD00RH08hicBPVwdSby2jl09N2h2vKNSLb1RiG89cit3PDkYYDwBs0y9lPiBPbmTiL08T/Q8haggPY3RG71glKk7qSOZPBULI73+L769nIYoO97Ljr0rbLi8D6ADPdgMJ72c+ZI9M6vXPEiUfDwhNqS8CVlvPYk2hryiIRU9ZGFmvIonN7xHZZ49hgyM 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 eRNo8GvwdPRSNjb3AF9Q88A66Oz9PRj1tYc+8WCIhvMv1u7wTeDg9PnZkPZ+YZL1L8xK805SrPVt9aL0QoRe8/5S/PVBKG7yE40c7PS5MPM9Etr3u+8E9lRJRPZeNJLsjpsc8maGhvGo+jL2Vywk93QpaPRbgob3a/AY9NnobvXhifD1FN+I7YcHkPIWJXr3b3+y8q7DgPEhzIr3BBS08kzsuPZBeCrxhOg27fNmJPZ9uaL06zJM8LtaRvBTapb3GCWI9KzAqPXkzoTqpTho97l0pPSp8NL2JxhU80lGQPL42fL0ya+A8J8y0PA5q8TwPars8hsxePW5IZL341E08lGaEPUZ2fryVdgC8QnrivHkpAD0okLY4aK+RPdbXhL2DyAQ87MwevFDXA72Qeog9Ei0UvQQgjrsFhrS84olUPZKo7bwuxRQ9WSITvStCab1hvbG8IoRwvb4Qej1yEgm9KFPhvB1iGr1cIxO98GITvYgZRL3TFi89GKGeutaLlT2aQly83XSM 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 ePiAH2j09JC6+RHTPvg==", "training_traits": {"structure_gen": "Random", "n_layers": 1, "max_nodes": 9, "activation_func": "Tanh", "epoch_num": 5}, "classes_name": ["Cryptoadz", "Cryptopunks", "Moonbirds", "Nouns"]},m=25,b=50,y=59+11/12,w=59+11.5/12,v=60;function z(e,t){const n=Math.log(1-t)/Math.log(1-e);return e=>1-Math.pow(1-e,n)}class V{constructor(e,t,n){const{model:r,inputDim:i}=j(t,n);this.model=r,this.inputDim=i,this.iteration=0,this.stage=0;const o=new Date(parseInt(e.birthYear),0,1).getTime(),a=new Date(parM seInt(e.birthYear)+1,0,1).getTime();this.birthDate=new Date(Math.floor((o+a)/2));const l=zr.filter((t=>t[0]==e.lifeCycle))[0][2];this.growSpeed=365/l,this.cycleLength=60*l*24*3600*1e3,this.growthFunc=z(.4,.8)}updateAge(e){const t=(e.getTime()-this.birthDate.getTime())/31536e6*this.growSpeed;this.iteration=Math.floor(t/60);const n=t-60*this.iteration;let r;this.age=n;let i,o=0;if(n<25){let e=map(n,0,25,0,1);o=this.growthFunc(e),r=(25-n)/60,this.stage=1,this.stageRatio=map(n,0,25,0,1)}else n<50?(o=1,r=(50-n)/60,this.M stage=2,this.stageRatio=map(n,25,50,0,1)):n<y?(o=map(n,50,y,1,0),r=(y-n)/60,this.stage=3,this.stageRatio=map(n,50,y,0,1)):n<w?(o=0,r=(w-n)/60,this.stage=4,this.stageRatio=map(n,y,w,0,1)):n<60&&(o=0,r=(60-n)/60,this.stage=5,this.stageRatio=map(n,w,60,0,1));n<50?i=map(n,0,50,0,780/880):n<w?i=map(n,50,w,780/880,800/880):n<60&&(i=map(n,w,60,800/880,1)),this.nextStateTimestamp=Math.round(e.getTime()+this.cycleLength*r),this.statePercentage=round(100*i);let a=(25-n)/60;a<0&&(a+=1),this.nextStableTimestamp=Math.round(e.geM tTime()+this.cycleLength*a),this.growth=o,this.model.updateNeurons(o,this.iteration)}getBrainStatus(){return{totalNeurons:this.model.getTotalNeurons(),neuronsLife:this.model.getNeuronsLife(),stage:this.stage,inputDim:this.inputDim,stageRatio:this.stageRatio,age:this.age,growth:this.growth,nextStateTimestamp:this.nextStateTimestamp,nextStableTimestamp:this.nextStableTimestamp,rebirthCount:max(this.iteration,0),statePercentage:this.statePercentage}}classifyImage(e){const t=new G(e,1,e.length);return this.model.forwarM d(t).mat[0]}}class M{constructor(e,t,n,r,i){this.p=e,this.v=t,this.size=n,this.shape=i,this.col=r}getRadius(){return 1==Oe?1*this.size/2:2==Oe?7*this.size/16:3==Oe||4==Oe?4*this.size/7:0}update(){this.p.add(this.v)}draw(e,t,n,r){const i=this.p.x*r,o=this.p.y*r,a=this.size*r,{col:l,shape:s}=this;let h,c;1==n?h=c=l:2==n?(h=dr(t,1),c=l):(h=dr(t,0),c=dr(l,1));e.stroke(dr(c,map(1,0,1,.25,1))),e.fill(dr(h,map(1,0,1,.15,1))),3==n&&e.fill(dr(h,0)),1==s?e.ellipse(i,o,a,a):2==s?e.rect(i,o,7*a/8,7*a/8):3==s&&(e.beginShape(),eM .vertex(i-4*a/7,o),e.vertex(i,o-4*a/7),e.vertex(i+4*a/7,o),e.vertex(i,o+4*a/7),e.endShape(CLOSE))}}class E{constructor(e,t,n,r,i,o,a){this.center=e,this.len=t,this.angle=n,this.v=r,this.angV=i,this.c1=o,this.c2=a}getEndpoints(){const e=createVector(this.len/2*cos(this.angle),this.len/2*sin(this.angle));return[Vector.add(this.center,e),Vector.sub(this.center,e)]}update(){this.center.add(this.v),this.angle+=this.angV}draw(e,t){const[n,r]=this.getEndpoints(),i=n.x*t,o=n.y*t,a=r.x*t,l=r.y*t,s=this.c1,h=this.c2;var c=e.M drawingContext.createLinearGradient(i,o,a,l);c.addColorStop(0,s),c.addColorStop(1,h),e.drawingContext.strokeStyle=c,e.drawingContext.globalAlpha=1,e.line(i,o,a,l),e.drawingContext.globalAlpha=1}}function S(e,t){const n=random(TAU),r=random(e,t);return createVector(r*cos(n),r*sin(n))}class R{constructor(e,t,n,r,i){this.wall=n,this.maxR=i;const o=t.length;this.nodes=[];for(let a=0;a<o;++a){const o=[],l=.25*t[a];for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),l=S(.02*i,.05*M i),s=random(10,25)*i;o.push(new M(t,l,s,e[a],r))}this.nodes.push(o)}const a=A(e);a.unshift(e[0]),a.push(e[e.length-1]),this.lines=[];for(let e=0;e<=o;++e){const r=[],l=(0==e?1:t[e-1])*(e==o?1:t[e])*1.5;for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),o=random(5*i,10*i),l=random(TAU),s=S(.02*i,.05*i),h=random(2e-4,.001);r.push(new E(t,o,l,s,h,a[e],a[e+1]))}this.lines.push(r)}}reflectNode(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,{p:o,v:a}=e,l=e.getRadius();(o.xM -l<t&&a.x<0||o.x+l>r&&a.x>0)&&(a.x=-a.x),(o.y-l<n&&a.y<0||o.y+l>i&&a.y>0)&&(a.y=-a.y)}reflectLine(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,[o,a]=e.getEndpoints(),l=e.v;(min(o.x,a.x)<t&&l.x<0||max(o.x,a.x)>r&&l.x>0)&&(l.x=-l.x),(min(o.y,a.y)<n&&l.y<0||max(o.y,a.y)>i&&l.y>0)&&(l.y=-l.y)}update(){for(const e of this.lines)for(const t of e)t.update(),this.reflectLine(t);for(const e of this.nodes)for(const t of e)t.update(),this.reflectNode(t)}draw(e,t,n,r,i){const o=i/this.maxR;for(const t of this.lines){cM onst n=t.length*r;for(let r=0;r<n;++r)t[r].draw(e,o)}for(const i of this.nodes){const a=i.length*r;for(let r=0;r<a;++r)i[r].draw(e,t,n,o)}}}function I(e,t){re(e),e.fill(0),e.rect(0,0,500,500),ie(e),e.noStroke(),e.fill(dr(cr("#000000"),.5)),e.push(),e.translate(250,250),e.scale(t),e.translate(-250,-250),e.beginShape(),e.vertex(235.2,24.9),e.bezierVertex(215,24.6,185,11.4,164.8,11),e.bezierVertex(147.2,10.7,129.3,10.4,112.2,14.7),e.bezierVertex(95.1,19,78.5,28.5,69.6,43.8),e.bezierVertex(57.699,64.199,61.599,90.199,7M 0.199,112.2),e.bezierVertex(78.799,134.2,91.6,154.6,97.199,177.5),e.bezierVertex(102.499,199.2,100.899,222.5,92.799,243.2),e.bezierVertex(83,268,64.6,288.3,48.9,310),e.bezierVertex(33.2,331.7,24.5,337.5,26.599,364.1),e.bezierVertex(28.2,384.1,61.399,404.2,75.7,418.3),e.bezierVertex(90,432.4,73.7,488.2,91.9,496.7),e.bezierVertex(124.2,511.6,159,472.5,194.3,468.1),e.bezierVertex(211.6,465.9,267.4,501.5,283.9,495.9),e.bezierVertex(340.7,476.7,298.599,428.9,355.4,409.7),e.bezierVertex(370.799,404.5,454.5,407.6,464.4,39M 4.8),e.bezierVertex(478.599,376.3,474.7,349.3,464.299,328.4),e.bezierVertex(453.9,307.5,438.099,289.5,428.699,268.2),e.bezierVertex(412,230,419,182.6,446.1,150.9),e.bezierVertex(449.7,146.7,453.6,142.7,455.8,137.6),e.bezierVertex(459.4,129.299,457.5,119.6,454.8,111),e.bezierVertex(443.2,73.4,417.3,40.4,383.6,20.299),e.bezierVertex(358.1,5,343.2,-.4,313.5,0),e.bezierVertex(287.5,.4,261.6,25.4,235.2,24.9),e.endShape(),e.pop()}function C(e,t,n,r,i,o){let a,l,s;re(t),t.fill(0),t.rect(0,0,500,500),ie(t),t.noStroke(),t.fM ill(dr(n,.5)),1==i?(l=0,s=25,a=map(o,0,25,500,0)):a=0,t.rect(0,a,500,500),e.noStroke(),e.fill(r),e.rect(0,0,500,500),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierM Vertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99M .4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3M ,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),e.fill(n),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,3M 86.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVeM rtex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4)M ,e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456M .5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),re(e),e.fill(r),e.beginShape(),e.vertex(184.3,473.2),e.bezierVertex(164,473.2,144.7,462.099,134,444.3),e.bezierVertex(131.7,440.5,129.1,438.5,125,437.1),e.bezierVertex(97.3,428.1,80.5,400.6,85.2,371.8),e.bezierVertex(86.3,365.1,85.8,364.1,79.9,361.2),e.bezierVertex(57.2,349.8,46.2,323.3,54.3,299.7),e.bezierVertex(54.7,298.599,55.1,297.7,55.5,296.9),e.bezierVertex(55.6,296.599,55.8,2M 96.4,55.9,296.099),e.vertex(57.9,291.499),e.vertex(62.5,293.599),e.bezierVertex(64.9,294.7,67.3,295.799,69.5,296.9),e.bezierVertex(74.5,299.299,79.1,301.599,83.9,303.099),e.bezierVertex(89.8,304.9,96.5,305.499,102.7,305.9),e.bezierVertex(102.8,305.9,102.9,305.9,103,305.9),e.bezierVertex(106.6,305.9,108.9,302.799,109,299.799),e.bezierVertex(109.1,296.199,106.6,293.4,102.7,292.799),e.bezierVertex(101.3,292.599,99.9,292.4,98.4,292.299),e.bezierVertex(94.3,291.799,90.1,291.299,86,289.9),e.bezierVertex(68.9,284,56.5,270M .2,52.7,252.799),e.bezierVertex(48.9,235.499,54.5,217.7,67.6,205.299),e.bezierVertex(71.9,201.299,72.7,198.1,70.8,192.399),e.bezierVertex(64.2,172.2,68.8,153.99,84.2,139.599),e.bezierVertex(94.2,130.199,105.5,125.399,117.8,125.399),e.bezierVertex(124.3,125.399,131.1,126.799,137.8,129.599),e.bezierVertex(157,137.399,167.9,152.799,169.4,173.99),e.vertex(169.4,174.399),e.bezierVertex(169.5,175.899,169.6,177.2,169.9,178.299),e.bezierVertex(170.7,181.2,173.2,183.2,176.1,183.2),e.bezierVertex(176.299,183.2,176.5,183.2,17M 6.7,183.2),e.bezierVertex(180.1,182.899,182.6,180.299,182.7,177),e.bezierVertex(183.1,162,178.299,148.2,168.399,136.1),e.bezierVertex(158.2,123.5,144.899,115.8,128.799,113.199),e.bezierVertex(123.499,112.299,120.399,109.799,118.899,104.99),e.bezierVertex(113.899,89.699,120.699,72.299,134.899,64.499),e.bezierVertex(139.99,61.699,145.799,60.199,151.7,60.199),e.bezierVertex(162.2,60.199,171.899,64.799,178.1,72.699),e.bezierVertex(179.6,74.6,180.799,76.6,181.9,78.499),e.vertex(182.2,79.099),e.bezierVertex(183.2,80.699,M 185.2,83.299,188.4,83.299),e.bezierVertex(189.5,83.299,190.6,82.99,191.7,82.399),e.bezierVertex(195.1,80.599,196,76.99,194,72.799),e.bezierVertex(190.1,64.799,184.1,58.499,175.6,53.299),e.bezierVertex(174.6,52.699,173.7,52.099,172.5,51.499),e.vertex(170.5,50.299),e.vertex(163,45.899),e.vertex(170.5,41.599),e.bezierVertex(182,34.99,193.1,30.799,204.4,28.599),e.bezierVertex(208.6,27.799,212.9,27.399,217.2,27.399),e.bezierVertex(217.6,27.399,217.9,27.399,218.3,27.399),e.bezierVertex(231.4,27.599,242.7,38.199,243,50.59M 9),e.bezierVertex(243.4,64.899,243.3,78.99,243.2,93.799),e.bezierVertex(243.2,99.799,243.1,105.899,243.1,112.099),e.vertex(243.1,119.199),e.vertex(236.4,116.799),e.bezierVertex(235.7,116.499,235,116.299,234.4,115.99),e.bezierVertex(233.4,115.599,232.6,115.299,232,115.199),e.bezierVertex(230.6,114.899,229.2,114.599,227.8,114.299),e.bezierVertex(223.8,113.499,220.1,112.699,216.4,112.499),e.vertex(216.2,112.499),e.bezierVertex(212.5,112.499,210.7,115.599,210.6,118.599),e.bezierVertex(210.4,122.399,212.7,125.099,216.4,M 125.399),e.bezierVertex(230.1,126.399,238.9,133.099,242.3,145.199),e.bezierVertex(243.2,148.399,243.2,151.599,243.2,154.499),e.vertex(243.2,155.099),e.bezierVertex(243.2,254.199,243.2,330,243.2,400.599),e.bezierVertex(243.2,401.99,243.2,403.4,243.2,404.9),e.bezierVertex(243.3,411.099,243.3,417.599,242.3,423.9),e.bezierVertex(238.1,449.2,219.6,467.799,194,472.5),e.bezierVertex(190.9,472.9,187.6,473.2,184.3,473.2),e.endShape(),e.beginShape(),e.vertex(315.8,473.1),e.bezierVertex(309.3,473.1,302.8,472,296.5,469.9),e.beM zierVertex(270.4,461,253.8,434.9,257.1,407.9),e.bezierVertex(260,384,273.8,366.8,297,358.3),e.bezierVertex(297.7,358.1,298.3,357.8,299,357.6),e.bezierVertex(299.8,357.3,300.6,357.1,301.2,356.8),e.bezierVertex(304.3,355.4,306,351.8,304.9,348.7),e.bezierVertex(304,345.9,301.7,344.2,299,344.2),e.bezierVertex(298.6,344.2,298.1,344.2,297.6,344.3),e.bezierVertex(288.1,346.3,279,350.9,269.7,358.3),e.bezierVertex(268.9,358.9,268.1,359.6,267.2,360.4),e.vertex(265.5,361.8),e.vertex(258.5,367.6),e.vertex(257.4,358.6),e.bezierM Vertex(257.3,358,257.3,357.5,257.2,357.1),e.bezierVertex(257,356,256.9,354.9,256.9,353.7),e.bezierVertex(256.9,334.8,256.9,316,256.9,297.1),e.bezierVertex(256.9,260.3,256.9,222.3,256.8,185),e.bezierVertex(256.8,170.7,268.3,158.8,282.5,158.4),e.bezierVertex(284.8,158.3,286.7,157.6,287.9,156.2),e.bezierVertex(289.099,154.9,289.599,153.2,289.5,151.3),e.bezierVertex(289.3,147.5,286.7,145.1,282.7,145.1),e.bezierVertex(282.5,145.1,282.2,145.1,282,145.1),e.bezierVertex(278.8,145.3,275.5,146.1,272,146.9),e.bezierVertex(270M .9,147.2,269.8,147.4,268.6,147.7),e.bezierVertex(267.9,147.9,267,148.2,265.8,148.7),e.bezierVertex(265.1,149,264.4,149.3,263.5,149.6),e.vertex(256.8,152),e.vertex(256.8,114.6),e.bezierVertex(256.8,95,256.8,75.4,256.8,55.9),e.bezierVertex(256.8,38,267.2,27.3,284.6,27.3),e.bezierVertex(285.3,27.3,285.9,27.3,286.6,27.3),e.bezierVertex(299,27.9,318.7,34.5,329.6,41.9),e.vertex(336.1,46.3),e.vertex(324.4,53.3),e.bezierVertex(316.2,58.2,310.2,64.6,306,72.9),e.bezierVertex(304.2,76.4,305.1,78.5,306.1,80),e.bezierVertex(307M .4,81.9,309.4,83,311.6,83),e.bezierVertex(313.7,83,315.7,81.9,317.1,80.1),e.bezierVertex(317.4,79.7,317.8,79,318.1,78.4),e.bezierVertex(318.4,77.9,318.7,77.3,319,76.8),e.bezierVertex(325.3,66.2,336.3,59.9,348.5,59.9),e.bezierVertex(353.2,59.9,357.8,60.8,362.1,62.7),e.bezierVertex(377.6,69.3,386,86.7,381.7,103.2),e.bezierVertex(380.7,107.1,378.5,111.8,371.1,113.1),e.bezierVertex(342.7,118.1,322.2,139.1,317.8,167.8),e.bezierVertex(317.4,170.3,317.3,173.2,317.4,176.5),e.bezierVertex(317.5,180,320.1,182.8,323.5,183),e.M bezierVertex(323.6,183,323.8,183,323.9,183),e.bezierVertex(327.1,183,329.8,180.6,330.3,177.2),e.bezierVertex(330.6,175.7,330.7,174,330.9,172.3),e.bezierVertex(331.1,169.8,331.4,167.3,332,164.7),e.bezierVertex(337.3,141.9,357.7,125.4,380.7,125.4),e.bezierVertex(382.5,125.4,384.3,125.5,386.1,125.7),e.bezierVertex(412.8,128.9,432.6,150.9,432,176.9),e.bezierVertex(431.9,182.3,430.9,187.7,429.1,192.7),e.bezierVertex(427.2,197.9,428,201,432.3,205),e.bezierVertex(446.8,218.7,451.8,236,446.6,255),e.bezierVertex(441.4,274,4M 28.3,286.5,408.7,291.3),e.bezierVertex(406.1,291.9,403.6,292.1,401.1,292.3),e.bezierVertex(400,292.4,398.9,292.5,397.9,292.6),e.bezierVertex(393.6,293.1,390.9,295.7,391,299.5),e.bezierVertex(391.1,303.4,394,305.8,398.5,305.8),e.bezierVertex(409.9,305.8,420.8,302.6,431.1,296.4),e.bezierVertex(431.8,296,432.5,295.5,433.2,295.1),e.bezierVertex(433.8,294.7,434.5,294.3,435.2,293.9),e.bezierVertex(436,293.4,436.6,293.2,437.2,293.1),e.bezierVertex(437.4,293,437.7,292.9,438.1,292.8),e.vertex(442.5,291.4),e.vertex(444.2,295M .7),e.bezierVertex(450.9,312.4,449.5,328.4,440,343.4),e.bezierVertex(435.3,350.8,428.7,356.7,420.2,361.1),e.bezierVertex(414.3,364.1,413.7,365.2,414.8,371.7),e.bezierVertex(419.5,400.2,403,427.6,375.6,436.9),e.bezierVertex(371,438.5,368.3,440.7,365.8,444.7),e.bezierVertex(355.2,462.5,336.4,473.1,315.8,473.1),e.bezierVertex(315.8,473.1,315.8,473.1,315.8,473.1),e.endShape(),ie(e),e.fill(n),e.beginShape(),e.vertex(120.2,279.9),e.bezierVertex(117.9,279.9,112.4,279.299,112.2,273.599),e.bezierVertex(112,267.7,117.4,266.7M ,119.7,266.599),e.bezierVertex(133.1,265.799,143.1,259.499,149.3,247.899),e.bezierVertex(149.6,247.299,150.1,246.399,150.3,245.399),e.bezierVertex(150.6,244.299,150.5,243.299,150.5,242.7),e.bezierVertex(150.5,242.6,150.5,242.5,150.5,242.299),e.vertex(150.3,238.799),e.vertex(141.1,235.99),e.bezierVertex(114.6,227.799,95.6,202.499,95.9,175.799),e.bezierVertex(95.9,173.99,96.4,168.199,102.2,168.199),e.bezierVertex(102.6,168.199,103,168.199,103.4,168.299),e.bezierVertex(104.8,168.499,108.2,168.899,109.2,175.599),e.beziM erVertex(109.3,176.599,109.5,177.599,109.6,178.499),e.bezierVertex(110.4,184.199,111.3,189.99,113.7,195.499),e.bezierVertex(121.9,213.99,139.5,225.499,159.7,225.499),e.bezierVertex(172.1,225.499,184.1,220.899,193.5,212.599),e.bezierVertex(194,212.199,194.4,211.799,194.8,211.399),e.bezierVertex(195.1,211.099,195.5,210.799,195.8,210.399),e.bezierVertex(197.4,208.99,199.2,208.2,200.9,208.2),e.bezierVertex(202.5,208.2,204,208.899,205.3,210.1),e.bezierVertex(208,212.9,207.9,216.9,205,219.9),e.bezierVertex(196.5,228.6,18M 6.3,234.3,174.7,236.8),e.bezierVertex(168.799,238.1,165.6,241,163.899,246.7),e.bezierVertex(158.3,265.9,139.9,279.7,120.2,279.9),e.vertex(120.2,279.9),e.endShape(),e.beginShape(),e.vertex(187.2,427.5),e.bezierVertex(183.799,427.5,181.299,425.3,180.799,422),e.bezierVertex(180.6,420.8,180.499,419.5,180.399,418.1),e.bezierVertex(180.299,417,180.2,415.8,180.099,414.7),e.bezierVertex(177.199,390.5,156.699,371.3,132.399,370.2),e.bezierVertex(131.99,370.2,131.499,370.2,131.099,370.2),e.bezierVertex(130.699,370.2,130.299,3M 70.2,129.799,370.2),e.bezierVertex(125.99,369.9,123.199,367.2,123.099,363.6),e.bezierVertex(122.99,360.2,125.799,357.3,129.599,356.9),e.bezierVertex(130.499,356.8,131.499,356.8,132.599,356.7),e.bezierVertex(133.199,356.7,133.799,356.7,134.399,356.6),e.vertex(138.299,356.4),e.vertex(139.1,352.6),e.bezierVertex(139.5,350.7,139.799,348.9,140.2,347),e.bezierVertex(140.899,343.4,141.5,340,142.399,336.8),e.bezierVertex(150.099,310.7,174.399,292,201.399,291.3),e.vertex(201.599,291.3),e.bezierVertex(203.699,291.3,206.299,2M 92,208.299,293.2),e.bezierVertex(210.499,294.5,210.699,297.5,209.99,299.8),e.bezierVertex(209.499,301.5,208.199,303.9,203.299,304.7),e.bezierVertex(202.199,304.9,200.99,305,199.799,305.2),e.bezierVertex(194.499,305.9,188.99,306.599,183.799,308.9),e.bezierVertex(165.499,316.799,155.199,331.299,152.99,352),e.bezierVertex(152.399,357.8,154.499,361.7,159.699,364.5),e.bezierVertex(178.199,374.4,189.399,390,193.099,410.9),e.bezierVertex(193.699,414.299,193.899,418,193.599,422),e.bezierVertex(193.399,425.2,190.899,427.5,1M 87.399,427.5),e.vertex(187.2,427.5),e.endShape(),e.beginShape(),e.vertex(364.3,281.1),e.bezierVertex(346.3,280.6,332.9,272.8,323.5,257),e.bezierVertex(321.6,253.9,320.4,250.2,319.2,246.7),e.bezierVertex(317.7,242.2,315,239.799,310.5,238.799),e.bezierVertex(298.5,236.299,288,230.7,279.4,222.1),e.bezierVertex(276.7,219.4,274.9,215.299,278,211.9),e.bezierVertex(279.4,210.3,281,209.6,282.6,209.6),e.bezierVertex(284.4,209.6,286.4,210.6,288.3,212.5),e.bezierVertex(297.8,221.8,310.4,226.9,323.9,226.9),e.bezierVertex(340.2M ,226.9,355.1,219.3,364.8,206.2),e.bezierVertex(371,197.8,374.2,188.5,374.5,178.5),e.vertex(374.5,177.9),e.bezierVertex(374.5,177,374.5,176.1,374.7,175.4),e.bezierVertex(375.3,171.8,377.9,169.5,381.3,169.5),e.bezierVertex(381.4,169.5,381.5,169.5,381.7,169.5),e.bezierVertex(385.4,169.7,388,172.4,388,176.1),e.bezierVertex(388.1,190.7,383.4,204,374.2,215.8),e.bezierVertex(365.8,226.5,354.7,233.9,341.2,237.9),e.bezierVertex(340,238.3,338.7,238.6,337.3,239.1),e.bezierVertex(335.9,239.6,335.1,240.4,334.7,240.9),e.bezierVeM rtex(334.599,241,334.5,241.1,334.4,241.2),e.vertex(331.799,243.6),e.vertex(333.199,246.8),e.bezierVertex(338.199,258,346.799,264.9,358.699,267.3),e.bezierVertex(360.199,267.6,361.599,267.7,362.99,267.9),e.bezierVertex(363.599,268,364.299,268,364.899,268.1),e.bezierVertex(369.099,268.6,371.799,271.4,371.499,275),e.bezierVertex(371.199,278.6,368.299,281.2,364.399,281.2),e.vertex(364.3,281.1),e.endShape(),e.beginShape(),e.vertex(323.9,437),e.bezierVertex(323.7,437,323.5,437,323.299,437),e.bezierVertex(319.599,436.7,31M 7.299,434.1,317.4,430.2),e.bezierVertex(317.9,406.099,328.299,388,349.5,375),e.bezierVertex(350.7,374.2,352,373.5,353.4,372.8),e.bezierVertex(354.099,372.4,354.7,372.1,355.299,371.7),e.vertex(357.499,370.5),e.vertex(357.799,368),e.bezierVertex(360.4,346.6,345.199,323.7,323.9,317),e.bezierVertex(319.099,315.5,314.099,314.9,309.299,314.4),e.vertex(308.199,314.299),e.bezierVertex(305.99,314.099,300.799,312.9,300.899,307.299),e.bezierVertex(300.99,303.499,303.899,300.9,308.099,300.9),e.vertex(308.299,300.9),e.bezierVerM tex(327.099,301.299,343.099,308.7,355.699,322.9),e.bezierVertex(364.299,332.5,369.399,344.099,370.99,357.299),e.bezierVertex(371.099,358.4,371.299,359.4,371.499,360.499),e.bezierVertex(371.599,360.99,371.699,361.499,371.799,361.99),e.vertex(372.499,365.899),e.vertex(377.899,366.199),e.bezierVertex(378.799,366.299,379.699,366.299,380.599,366.399),e.bezierVertex(385.099,366.699,387.899,369.399,387.799,373.299),e.bezierVertex(387.699,377.099,384.99,379.599,380.799,379.799),e.bezierVertex(369.799,380.199,359.99,383.299M ,351.899,389.299),e.bezierVertex(338.799,398.799,331.699,411.699,330.699,427.499),e.vertex(330.699,428.299),e.bezierVertex(330.599,429.199,330.599,430.099,330.499,430.799),e.bezierVertex(330,434.7,327.5,437,323.9,437),e.endShape()}function T(e){return e[0].map(((t,n)=>e.map((e=>e[n]))))}function A(e){return e.map((e=>Array.isArray(e)?A(e):e))}function D(e,t){return floor(random(e,t))}function k(e){let t=0;for(const n of e)t+=n[1];let n=random(t),r=0;for(const t of e)if(r+=t[1],n<r)return t[0];return null}function LM (e){for(let t=1;t<e.length;++t){let n=D(0,t),r=e[t];e[t]=e[n],e[n]=r}}function P(e){return null==e||""===e}function O(e){return new Promise((t=>setTimeout(t,e)))}function F(e,t,n){let r=0;for(let i=1;i<=1e3;++i)for(let o=1;o<=1e3;++o)if(e*o%(t*i)==0){let e=1*i/o;abs(e-n)<abs(r-n)&&(r=e)}return r}function N(){let e=60*(new Date).getTimezoneOffset()*1e3;return new Date(Date.now()-e).toISOString().slice(0,-1)}function B(e,t,n){let r;if(push(),textSize(e),textWidth(t)<=n)r=t;else for(let e=0;e<t.length;++e){const i=t.sM lice(0,e+1)+"...";if(textWidth(i)>n){r=i;break}}return pop(),r}function Y(e){var t=e%10,n=e%100;return 1==t&&11!=n?e+"st":2==t&&12!=n?e+"nd":3==t&&13!=n?e+"rd":e+"th"}class G{constructor(e,t,n){this.n=t,this.m=n,this.mat=[];let r=0;for(let t=0;t<this.n;++t){this.mat.push([]);for(let n=0;n<this.m;++n)this.mat[t].push(r<e.length?e[r]:0),r+=1}return this}copy(){return new G(this.mat.flat(),this.n,this.m)}}class H{static __linear=e=>e;static __relu=e=>Math.max(e,0);static __leaky_relu=e=>e>0?e:.2*e;static __sigmoid=e=>M 1/(1+Math.exp(-e));static __tanh=e=>Math.tanh(e);static __apply_unary_op(e,t){const n=e.copy();for(let e=0;e<n.n;++e)for(let r=0;r<n.m;++r)n.mat[e][r]=t(n.mat[e][r]);return n}static linear=e=>H.__apply_unary_op(e,H.__linear);static relu=e=>H.__apply_unary_op(e,H.__relu);static leaky_relu=e=>H.__apply_unary_op(e,H.__leaky_relu);static sigmoid=e=>H.__apply_unary_op(e,H.__sigmoid);static tanh=e=>H.__apply_unary_op(e,H.__tanh);static __add=(e,t)=>e+t;static __mul=(e,t)=>e*t;static __apply_binary_op=(e,t,n)=>{"object"!=M typeof t&&(t=new G([t],1,1));const r=e.copy();for(let e=0;e<r.n;++e)for(let i=0;i<r.m;++i)r.mat[e][i]=n(r.mat[e][i],t.mat[e%t.n][i%t.m]);return r};static mul=(e,t)=>H.__apply_binary_op(e,t,H.__mul);static add=(e,t)=>H.__apply_binary_op(e,t,H.__add);static matMul(e,t){const n=new G([],e.n,t.m);for(let r=0;r<n.n;++r)for(let i=0;i<n.m;++i)for(let o=0;o<e.m;++o)n.mat[r][i]+=e.mat[r][o]*t.mat[o][i];return n}static softmax(e){const t=H.__apply_unary_op(e,(e=>Math.exp(e))),n=t.mat.flat().reduce(((e,t)=>e+t));for(let r=0;rM <e.n;++r)for(let i=0;i<e.m;++i)t.mat[r][i]/=n;return t}}class ${constructor(e,t){this.scale=e,this.offset=t}forward(e){return H.add(H.mul(e,this.scale),this.offset)}}class X{constructor(){}forward(e){return e.map((e=>e.flat()))}}class W{constructor(e,t,n,r){this.out_dim=e,this.activation=t,this.w=n,this.b=r}forward(e){const t=H.add(H.matMul(e,this.w),this.b);return null==this.activation?t:this.activation(t)}}class U{constructor(e,t,n){this.preprocessLayers=e,this.hiddenLayers=t,this.outputLayer=n,this.totalNeurons=M this.hiddenLayers.map((e=>e.out_dim)),this.currentOrders=[],this.currentIteration=null}updateNeurons(e,t){if(t!=this.currentIteration){this.currentOrders=[];for(let e=0;e<this.totalNeurons.length;++e){randomSeed(100*(t+1)+e);const n=[];for(let t=0;t<this.totalNeurons[e];++t)n.push(t);L(n),this.currentOrders.push(n)}this.currentIteration=t}const n=A(this.totalNeurons),r=n.reduce(((e,t)=>e+t))*(1-e);for(let e=0;e<r;++e){const t=n.map(((e,t)=>(e-1)/this.totalNeurons[t]));n[t.map(((e,t)=>[e,t])).reduce(((e,t)=>t[0]>e[0M ]?t:e))[1]]-=Math.min(r-e,1)}this.neuronsLife=[];for(let e=0;e<n.length;++e){const t=this.currentOrders[e],r=Array(this.totalNeurons[e]).fill(0);for(let i=0;i<n[e];++i)r[t[i]]=Math.min(n[e]-i,1);this.neuronsLife.push(r)}}getTotalNeurons(){return A(this.totalNeurons)}getNeuronsLife(){return A(this.neuronsLife)}forward(e){for(const t of this.preprocessLayers)e=t.forward(e);for(const[t,n]of this.hiddenLayers.entries()){e=n.forward(e);const r=new G(this.neuronsLife[t],1,e.m);e=H.mul(e,r)}return e=this.outputLayer.forwaM rd(e),H.softmax(e)}}function q(e){switch(e){case"relu":return H.relu;case"sigmoid":return H.sigmoid;case"tanh":return H.tanh;case"leaky_relu":return H.leaky_relu;default:return H.linear}}function j(e,t){const n=[],r=[],i=Z(t);let o=null,a=0,l=[];for(const t of e.config.layers)if("InputLayer"==t.class_name)o=t.config.batch_input_shape.slice(1),l=o;else if("Rescaling"==t.class_name)n.push(new $(t.config.scale,t.config.offset));else if("Flatten"==t.class_name)o=[o.reduce(((e,t)=>e*t))];else if("Dense"==t.class_name){cM onst e=[t.config.units],n=o[0]*e[0],l=e[0],s=i.subarray(a,a+n);a+=n;const h=i.subarray(a,a+l);a+=l;const c=new G(s,o[0],e[0]),u=new G(h,1,e[0]),f=q(t.config.activation);r.push(new W(e[0],f,c,u)),o=e}const s=r.pop();return{model:new U(n,r,s),inputDim:l}}function Z(e){const t=window.atob(e),n=t.length/Float32Array.BYTES_PER_ELEMENT,r=new DataView(new ArrayBuffer(Float32Array.BYTES_PER_ELEMENT)),i=new Float32Array(n);let o=0;for(let e=0;e<n;e++){o=4*e;for(let e=0;e<4;++e)r.setUint8(e,t.charCodeAt(o+e));i[e]=r.getFloatM 32(0,!0)}return i}class K{constructor(e){this.elt=e,this._events={},this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight}position(){if(0===arguments.length)return{x:this.elt.offsetLeft,y:this.elt.offsetTop};var e="absolute";return"static"!==arguments[2]&&"fixed"!==arguments[2]&&"relative"!==arguments[2]&&"sticky"!==arguments[2]&&"initial"!==arguments[2]&&"inherit"!==arguments[2]||(e=arguments[2]),this.elt.style.position=e,this.elt.style.left=arguments[0]+"px",this.elt.style.top=arguments[1]+"px",this.xM =arguments[0],this.y=arguments[1],this}show(){return this.elt.style.display="block",this}hide(){return this.elt.style.display="none",this}size(e,t){if(0===arguments.length)return{width:this.elt.offsetWidth,height:this.elt.offsetHeight};var n=e,r=t;if(n!==te||r!==te){if(n===te?n=t*this.width/this.height:r===te&&(r=e*this.height/this.width),this.elt instanceof HTMLCanvasElement){var i,o={},a=this.elt.getContext("2d");for(i in a)o[i]=a[i];for(i in this.elt.setAttribute("width",n*this._pInst._pixelDensity),this.elt.setM Attribute("height",r*this._pInst._pixelDensity),this.elt.style.width=n+"px",this.elt.style.height=r+"px",this._pInst.scale(this._pInst._pixelDensity,this._pInst._pixelDensity),o)this.elt.getContext("2d")[i]=o[i]}else this.elt.style.width=n+"px",this.elt.style.height=r+"px",this.elt.width=n,this.elt.height=r;this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight,this._pInst&&this._pInst._curElement&&this._pInst._curElement.elt===this.elt&&(this._pInst._setProperty("width",this.elt.offsetWidth),this._pInstM ._setProperty("height",this.elt.offsetHeight))}return this}style(e,t){if(t instanceof Color&&(t="rgba("+t.levels[0]+","+t.levels[1]+","+t.levels[2]+","+t.levels[3]/255+")"),void 0===t){if(-1===e.indexOf(":"))return window.getComputedStyle(this.elt).getPropertyValue(e);for(var n=e.split(";"),r=0;r<n.length;r++){var i=n[r].split(":");i[0]&&i[1]&&(this.elt.style[i[0].trim()]=i[1].trim())}}else if(this.elt.style[e]=t,"width"===e||"height"===e||"left"===e||"top"===e){var o=window.getComputedStyle(this.elt).getPropertyVaM lue(e).replace(/[^\d.]/g,"");this[e]=Math.round(parseFloat(o,10))}return this}value(){return arguments.length>0?(this.elt.value=arguments[0],this):"range"===this.elt.type?parseFloat(this.elt.value):this.elt.value}mouseClicked(e){return this._adjustListener("click",e,this),this}isFocused(){return document.activeElement===this.elt}_adjustListener(e,t,n){return!1===t?this._detachListener(e,n):this._attachListener(e,t,n),this}_attachListener(e,t,n){n._events[e]&&this._detachListener(e,n);var r=t.bind(n);n.elt.addEventLM istener(e,r,!1),n._events[e]=r}_detachListener(e,t){var n=t._events[e];t.elt.removeEventListener(e,n,!1),t._events[e]=null}}function J(e,t){var n=document.createElement("button");return n.innerHTML=e,t&&(n.value=t),ee(n)}function Q(e){var t=arguments.length>1&&void 0!==arguments[1]&&arguments[1],n=function(t){var n=!0,r=!1,i=void 0;try{for(var o,a=t.target.files[Symbol.iterator]();!(n=(o=a.next()).done);n=!0){var l=o.value;File._load(l,e)}}catch(e){r=!0,i=e}finally{try{n||null==a.return||a.return()}finally{if(r)thrM ow i}}};if(window.File&&window.FileReader&&window.FileList&&window.Blob){var r=document.createElement("input");return r.setAttribute("type","file"),t&&r.setAttribute("multiple",!0),r.addEventListener("change",n,!1),ee(r)}}function ee(e){return document.body.appendChild(e),new K(e)}createImg=function(){var e,t=document.createElement("img"),n=arguments;return n.length>1&&"string"==typeof n[1]&&(t.alt=n[1]),n.length>2&&"string"==typeof n[2]&&(t.crossOrigin=n[2]),t.src=n[0],e=ee(t,this),t.addEventListener("load",(functM ion(){e.width=t.offsetWidth||t.width,e.height=t.offsetHeight||t.height;var r=n[n.length-1];"function"==typeof r&&r(e)})),e},createInput=function(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:"",t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:"text",n=document.createElement("input");return n.setAttribute("value",e),n.setAttribute("type",t),ee(n,this)};const te="auto";function ne(e){re(e);const t=e._rectMode;e.rectMode(CORNER),e.rect(0,0,e.width,e.height),e.rectMode(t),ie(e)}function re(e){eM .push(),e.fill(255,255,255,255),e.blendMode(REMOVE)}function ie(e){e.blendMode(BLEND),e.pop()}File=function(e,t){this.file=e,this._pInst=t;var n=e.type.split("/");this.type=n[0],this.subtype=n[1],this.name=e.name,this.size=e.size,this.data=void 0},File._createLoader=function(e,t){var n=new FileReader;return n.onload=function(n){var r=new File(e);if("application/json"===r.file.type)r.data=JSON.parse(n.target.result);else if("text/xml"===r.file.type){var i=(new DOMParser).parseFromString(n.target.result,"text/xml");rM .data=new XML(i.documentElement)}else r.data=n.target.result;t(r)},n},File._load=function(e,t){if(/^text\//.test(e.type)||"application/json"===e.type)File._createLoader(e,t).readAsText(e);else if(/^(video|audio)\//.test(e.type)){var n=new File(e);n.data=URL.createObjectURL(e),t(n)}else File._createLoader(e,t).readAsDataURL(e)},XML=function(e){if(e)this.DOM=e;else{var t=document.implementation.createDocument(null,"doc");this.DOM=t.createElement("root")}},document.addEventListener("DOMContentLoaded",(function(){addEvM entListener("mousemove",(e=>{window.mouseX=e.pageX,window.mouseY=e.pageY}))})),new e("global");const oe="313";let ae,le,se,he,ce,ue,fe,de,xe,ge,pe,me,be,ye,we,ve,ze,Ve,_e,Me,Ee,Se,Re,Ie,Ce,Te,Ae,De,ke,Le,Pe,Oe,Fe,Ne,Be,Ye,Ge,He,$e,Xe,We,Ue,qe,je,Ze,Ke,Je,Qe,et,tt,nt,rt,it,ot,at,lt,st,ht,ct,ut,ft,dt,xt,gt,pt,mt,bt,yt,wt,vt,zt,Vt,_t,Mt,Et,St,Rt,It,Ct,Tt,At=!1,Dt=!1,kt=!0,Lt=!1,Pt=!1;const Ot=[" ","Growing","Stable","Decaying","Dead","Rebirth"];let Ft,Nt,Bt,Yt,Gt,Ht,$t,Xt,Wt,Ut,qt,jt,Zt,Kt,Jt,Qt,en,tn,nn,rn,on,an,ln,sM n,hn=0,cn=0,un=0,fn=!1,dn=!0,xn=!0,gn=null,pn=null,mn=null,bn=!1,yn=!1,wn=null,vn=null,zn=!1;async function setup(){let e=windowWidth,t=windowHeight;createCanvas(e,t),et=createGraphics(e,t),Xe=createGraphics(e,t),$e=createGraphics(e,t),We=createGraphics(e,t),Ue=createGraphics(e,t),qe=createGraphics(e,t),Qe=createGraphics(e,t),je=createGraphics(e,t),Ze=createGraphics(e,t),Ke=createGraphics(e,t),Je=createGraphics(e,t),tt=createGraphics(500,500),nt=createGraphics(500,500),rt=createGraphics(500,500),_n(),Mn(),Sn(),awaiM t En(),Gn(),Rn(),bn=!0}function _n(){Et=parseInt(oe),randomSeed(Et),noiseSeed(Et)}function Mn(){Wt=Ir(p.training_traits),Cr(Wt)}async function En(){let e;Jt=r(),Qt=o(),[Xt,e]=await Promise.all([s(Jt),h(Qt)]),Ut=new V(Wt.visual,e.layers_config,e.weight_b64),Ut.updateAge(new Date),_n(),Wt.training=e.training_traits,Ht=e.model_name,$t=e.classes_name}function Sn(){le=min(width,height)/1024,ut=Rr.findIndex((e=>e[0]===Wt.visual.colorPalette)),ft=[["#ffffff","#231f20","#231f20"],["#231f20","#ffffff","#ffffff"],["#104da8",M "#ffffff","#ffffff"],["#722F1F","#FCE1B2","#FCE1B2"],["#e88120","#f9f2e5","#f9f2e5"],["#f6b941","#2E2E2E","#2E2E2E"],["#45daaa","#012221","#012221"],["#F1F1F1","#328DFE","#328DFE"],["#111822","#D3EB8D","#D3EB8D"],["#713FF9","#D6D5E6","#D6D5E6"],["#FBDA9D","#795106","#795106"],["#8f5b62","#ead0d0","#ead0d0"],["#eae4cb","#508cac","#508cac"],["#ffc6cc","#cc313d","#cc313d"],["#60A900","#E0FE00","#E0FE00"],["#507DBE","#D0D1D3","#D0D1D3"],["#305848","#E8F2EE","#E8F2EE"],["#2a2634","#5b6988","#cb78a2","#5b6988"],["#590e29M ","#fd5e53","#fd5e53","#ffe373"],["#0a141d","#57d4e4","#328195","#2A9ECF","#0ab6a8","#57d4e4"],["#3a2d28","#d5c2ac","#df6338","#3d9895","#d5c2ac"],["#030706","#77c4d9","#77c4d9","#77c4d9","#ffffff","#ffffff","#e72020","#e72020"],["#3a4664","#92f5ff","#f9ff94","#eaa0a2","#55dde0"],["#fbfaff","#f04bb1","#f04bb1","#fac373","#82cef0","#8b31ce"],["#000000","#ffffff","#ff0002","#f26522","#fdff00","#00ff03","#01fffe","#0000ff","#ff00ff"]];for(let e=0;e<ft.length;++e)for(let t=0;t<ft[e].length;++t)ft[e][t]=cr(ft[e][t]);pt=M [],ct=ft[ut][0],st=ft[ut][1]}function Rn(){gn=document.querySelector("#upload"),pn=document.querySelector("#inputUpload"),gn.addEventListener("dblclick",(()=>{if(!Lt&&!yn)if(In(Ie)&&cn==Ve-1)pn.click();else{if(4!=Pe&&5!=Pe&&(In(Ie)||cn!=Ve-1))return;fn=!0,dn=!0,Bt=0,un=0}})),pn.addEventListener("click",(()=>{pn.value=null,gn.style.display="block"})),pn.addEventListener("change",(()=>{const[e]=pn.files;e?(se=null,gn.style.display="none",Tn(URL.createObjectURL(e)),mn=e):gn.style.display="block"}))}function In(e){for(M let t=0;t<e.length;++t){let n=0;for(let r=0;r<e[t].length;++r)e[t][r]>0&&++n;if(0==n)return!1}return!0}function Cn(){null!=se&&(un=0,Pt=!0,he=0,ue=0,drewLineAnim=!0,ce=(ae/2+we/2)/le,loadImage(se.elt.src,(e=>{const[t,n,r]=Gt,i=createGraphics(t,n);i.image(e,0,0,t,n),i.loadPixels();const o=i.pixels.filter(((e,t)=>t%4!=3)),a=Ut.classifyImage(o);Zt=T([a,$t.map((e=>e.toUpperCase()))]).sort(((e,t)=>e[0]>t[0]?-1:1))})))}function Tn(e){se=createImg(e,""),se.hide(),Cn()}function An(){zn||(ce+=(width-ae-we)/tn/le),re(Xe),Xe.M rect(ce*le,0,width,height),ie(Xe),un>=ge&&1==kt&&(kt=!1,un-=ge),kt&&(re($e),$e.strokeWeight(2*Fe),Jn(he,ze,ct,ct,$e),ie($e)),un>=ge&&0==kt&&(kt=!0,un-=ge,he+=1,he==en&&(++ue,he=0,ce=(ae/2+we/2)/le,1==ue&&(Pt=!1,Dn(),ye=millis())))}function Dn(){At=!0,pe=!1,me=!1,tryButton=br("Try Again",width/2-225*le,height/2+265*le,290*le,40*le,kn),closeResultButton=br("Close",width/2+75*le,height/2+265*le,150*le,40*le,Ln)}function kn(){At=!1,tryButton.hide(),closeResultButton.hide(),pn.click()}function Ln(){Yt=!0,At=!1,Gn(),tryBM utton.hide(),closeResultButton.hide(),gn.style.display="block",se=null}function keyTyped(){bn&&!1===yn&&!1===yr()&&("i"!==key&&"I"!==key||(Dt=!Dt),"b"!==key&&"B"!==key||(xn=!xn),"s"!==key&&"S"!==key||!1!==Lt||saveCanvasAtCurrentTime(),"k"!==key&&"K"!==key||!1!==Lt||save4KCanvasAtCurrentTime(),"u"!==key&&"U"!==key||!1!==Lt||!1!==At||!1!==fn||!1!==Pt||On())}function On(){Lt=!0,wn=null,vn=null,submitButton=br("Submit",width/2-155*le,height/2+115*le,150*le,40*le,Fn),closeSettingButton=br("Close",width/2+5*le,height/2+1M 15*le,150*le,40*le,Yn),vt=createInput(),vt.position(width/2-252.5*le,height/2-40*le),vt.size(500*le,25*le),vt.style("font-size","15px"),vt.value(Jt||""),zt=createInput(),zt.position(width/2-252.2*le,height/2+35*le),zt.size(500*le,25*le),zt.style("font-size","15px"),zt.value(Qt||"")}function Fn(){Vt=vt.value(),_t=zt.value(),submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide(),Lt=!1,yn=!0,Nn()}async function Nn(){[wn,vn,_]=await Promise.all([c(Vt),u(_t),O(1e3)]),yn=!1,wn&&vn?(n(Vt),i(_t),window.location.M reload()):(Lt=!0,submitButton.show(),closeSettingButton.show(),vt.show(),zt.show())}function Bn(){Je.textFont("Trebuchet MS"),Je.noStroke(),pr(Je,600*le,200*le),Je.strokeWeight(1*le),Je.stroke(xt),Je.fill(xt),Je.textSize(50*le),Je.text("update()",width/2,height/2+2.5*le)}function Yn(){wn=null,vn=null,Lt=!1,submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide()}function Gn(){_n(),nn=Date.now(),pe=!1,me=!1,St=Wt.training.structure_gen,Rt=Wt.visual.birthYear,It=Wt.visual.lifeCycle,Ct=Wt.training.epoch_num,TM t=Wt.training.activation_func,Ft=Mr.findIndex((e=>e[0]==Wt.visual.hardwareAcceleration))+1,1==Ft?(Nt=30,fe=40):2==Ft?(Nt=15,fe=20):(Nt=2,fe=10);const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,wM indow.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),ae=100*le,ht=50*le,Oe=Sr.findIndex((e=>e[0]==Wt.visual.nodeShape))+1,dt=Er.findIndex((e=>e[0]==Wt.visual.nodeFill))+1,lt=_r.findIndex((e=>e[0]==Wt.visual.pattern))+1,de=Math.tanh(Math.log10(Xt.avgfeerate)),de=map(de,0,1,.2,.8),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?M Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.lenM gth;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(M Be,1/30,1,1,10)*le,at=.7,pt=[],xt=ft[ut][2],gt=ft[ut][ft[ut].length-1];for(let e=3;e<ft[ut].length-1;e++)pt.push(ft[ut][e]);mt=sr(xt,gt,pt,width),bt=[],wt=[],yt=width/(Ve-1);for(let e=0;e<Ve;e++)bt.push(hr(mt,yt*e/width)),wt.push(hr(mt,yt*e/width));wt.unshift(bt[0]),wt.push(bt[bt.length-1]),hn=0,cn=0,un=0,Yt=!0;const n={xLeft:ae/8,xRight:width-ae/8,yTop:ae/8,yBottom:height-ae/8},r=Ce.map((e=>e.length));jt=new R(bt,r,n,Oe,le)}function Hn(e,t){let n=Ce[e].length;return[e*we+we/2+ae/2,height/2-(n-1)/2*ve+t*ve]}functioM n $n(e,t){le=min(e,t)/1024,ae=100*le,ht=50*le,we=(e-ae)/Ve,ve=(t-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}xe=floor(De.length*de),Le=[],ke=[],ge=floor(map(de,.2,.8,15,2));for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,mt=sr(xt,gt,pt,e),bt=[],wt=[],yt=e/(Ve-1);for(letM t=0;t<Ve;t++)bt.push(hr(mt,yt*t/e)),wt.push(hr(mt,yt*t/e));wt.unshift(bt[0]),wt.push(bt[bt.length-1])}function Xn(){const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,MathM .ceil(Mt),`Perceptron #${Et}`,$t),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;iM ++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;consM t t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le}function Wn(){jt.update();const e=4==Pe?0:Kt;jt.draw(Qe,ct,dt,e,le)}function Un(){if(!bn)return ar(),void et.image(je,0,0);if(4==Pe||5==Pe)return Wn(),void et.image(Qe,0,0);un>=Nt&&hn<Ve&&(hn++,un=0);for(let e=0;e<hn;e++)1==dt?it=ot=btM [e]:(it=ct,ot=bt[e]),Kn(e,it,ot,$e);un>=Nt&&cn<Ve-1&&(cn++,un=0);for(let e=0;e<cn;e++)Zn(e)}function qn(){et.background(ct),Ue.background(255),Ue.rectMode(CENTER),ne(Ue),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),Ue.stroke(st),Ue.strokeWeight(8*le),Ue.fill(ct),Qe.background(255),Qe.rectMode(CENTER),ne(Qe),Qe.strokeWeight(le),qe.background(255),qe.rectMode(CENTER),ne(qe),qe.textAlign(LEFT),$e.background(255),$e.rectMode(CENTER),ne($e),Xe.background(255),ne(Xe),Xe.strokeWeight(Ne),We.background(255),We.rectMode(CM ENTER),ne(We),We.fill(st),We.stroke(st),We.strokeWeight(.1*le),er(lt),We.noStroke(),xn&&(We.rect(ae/16,height/2,ae/8,height),We.rect(width-ae/16,height/2,ae/8,height),We.rect(width/2,ae/16,width,ae/8),We.rect(width/2,height-ae/16,width,ae/8)),Ze.background(255),Ze.rectMode(CENTER),ne(Ze),Ze.textAlign(CENTER,CENTER),Ze.textStyle(BOLD),Ze.stroke(st),Ze.strokeWeight(8*le),Ze.fill(ct),je.background(255),je.rectMode(CENTER),ne(je),je.textAlign(CENTER,CENTER),je.textStyle(BOLD),Ke.background(255),Ke.rectMode(CENTER),ne(KM e),Ke.textAlign(CENTER,CENTER),Ke.textStyle(BOLD),Ke.stroke(st),Ke.strokeWeight(8*le),Ke.fill(ct),Je.background(255),Je.rectMode(CENTER),ne(Je),Je.textAlign(CENTER,CENTER),Je.textStyle(BOLD),Je.stroke(st),Je.strokeWeight(8*le),Je.fill(ct),Un(),et.image(We,0,0),Pt&&An(),et.image(Xe,0,0),et.image($e,0,0),At&&(tr(),et.image(Ue,0,0)),fn&&(lr(),et.image(Ze,0,0)),Lt&&(or(),et.image(Ke,0,0)),Dt&&(ir(),et.image(qe,0,0)),yn&&(Bn(),et.image(Je,0,0))}function draw(){const e=Date.now();bn&&(Ut.updateAge(new Date(e)),Xn()),qn()M ,image(et,0,0),zn||un++}function Zn(e){let t,n=Ce[e].length,r=Ce[e+1].length;for(let i=0;i<n;i++){const[n,o]=Hn(e,i);for(let a=0;a<r;a++){const[r,l]=Hn(e+1,a);t=map(min(Ce[e][i],Ce[e+1][a]),0,1,0,.5),ur(n,o,r,l,bt[e],bt[e+1],Xe,t)}}}function Kn(e,t,n,r){let i,o,a,l=Ce[e].length;for(let s=0;s<l;s++){const[l,h]=Hn(e,s);i=Ce[e][s],a=map(Be,1/30,1,3,10),o=map(Ce[e][s],0,1,2*a,0)*le,o<1.5*le&&(o=0),Qn(l,h,ze,Oe,t,n,o,i,r)}}function Jn(e,t,n,r,i){for(let o=0;o<Le[e].length;o++)Qn(Le[e][o][0],Le[e][o][1],t,Oe,n,r,0,1,i)}fM unction Qn(e,t,n,r,i,o,a,l,s){s.stroke(dr(o,map(l,0,1,.25,1))),s.fill(dr(i,map(l,0,1,.15,1))),s.strokeWeight(Fe),fr([a],s),3==dt&&s.fill(dr(i,0)),1==r?s.ellipse(e,t,n):2==r?s.rect(e,t,7*n/8,7*n/8):3==r&&(s.beginShape(),s.vertex(e-4*n/7,t),s.vertex(e,t-4*n/7),s.vertex(e+4*n/7,t),s.vertex(e,t+4*n/7),s.endShape(CLOSE))}function er(e){if(1==e);else if(2==e){We.strokeWeight(1*le);for(let e=ht/4;e<width+ht/4;e+=ht)for(let t=ht/4;t<height+ht/4;t+=ht)We.point(e,t)}else if(3==e){ht=25*le;for(let e=ht/2;e<height+ht/2;e+=ht)WM e.line(0,e,width,e);for(let e=ht/2;e<width+ht/2;e+=ht)We.line(e,0,e,height)}}function tr(){Ue.textFont("Trebuchet MS"),Ue.textAlign(LEFT,CENTER),Ue.noStroke(),pr(Ue,800*le,500*le),Ue.noStroke(),Ue.fill(dr(st,.75)),Ue.rect(width/2,height/2-100*le,800*le,300*le,25*le,25*le,0,0),Ue.fill(st),Ue.rect(width/2-250*le,height/2-100*le,225*le,225*le),Ue.image(se.elt,width/2-357.5*le,height/2-207.5*le,215*le,215*le);let e=100*Zt[0][0];Ue.fill(ct),Ue.textSize(25*le),Ue.textStyle(NORMAL),1==me&&(e>=0&&e<20?Ue.text("I have a feeM ling this image belongs to",width/2-100*le,height/2-170*le):e>=20&&e<40?Ue.text("I have a hunch this image belongs to",width/2-100*le,height/2-170*le):e>=40&&e<60?Ue.text("I think this image belongs to",width/2-100*le,height/2-170*le):e>=60&&e<80?Ue.text("I'm almost certain this image belongs to",width/2-100*le,height/2-170*le):Ue.text("I'm positive this image belongs to",width/2-100*le,height/2-170*le));let t=e.toFixed(2);"100.00"==t&&(t="100"),1==me&&Ue.text("I'm "+t+"% confident that I'm right!",width/2-100*le,hM eight/2-25*le),example=Zt.map((e=>e[1])),be=Ue.textWidth('"FIDENZAAAA"'),defaultPhrase=Ue.textWidth('"PERPENDICULAR INHABITATION"'),Ue.textStyle(BOLD);const n=me?example[0]:random(example);if(1===n.split(" ").length){let e=75*be/Ue.textWidth('"'+n+'"');e>75&&(e=75),Ue.textSize(e*le),Ue.text('"'+n+'"',width/2-100*le,height/2-90*le)}else nr(width/2-100*le,height/2-90*le,460*le,110*le,n,Ue);if(millis()-ye>1500&&(me=!0),C(tt,nt,st,ct,Pe,Mt),Ue.image(nt,width/2-370*le,height/2+70*le,80*le,80*le),3==Pe){let e;e=map(Mt,50M ,60,.25,1.3),I(rt,e),Ue.image(rt,width/2-370*le,height/2+70*le,80*le,80*le)}let r,i;Ue.image(tt,width/2-370*le,height/2+70*le,80*le,80*le),Ue.fill(xt),Ue.textSize(40*le),Ue.text("INTELLIGENCE INFO",width/2-275*le,height/2+115*le),Ue.textSize(18*le),Ue.textStyle(NORMAL),Ue.circle(width/2-360*le,height/2+180*le,7.5*le),1==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s growing and getting smarter by the day.`:2==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s stable and it has reached peak perM formance.`:3==Pe&&(r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s decaying and losing its luster.`),i=2==Pe?"The Perceptron remains stable for some time before entering the decay phase.":`Wait until ${new Date(an).toLocaleString("en-US")} for your Perceptron to reach its peak performance.`,Ue.text(r,width/2-350*le,height/2+180*le),Ue.circle(width/2-360*le,height/2+210*le,7.5*le),Ue.text(i,width/2-350*le,height/2+210*le),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),gr(Ue,width/2-225*le,width/2+65*le,heigM ht/2+265*le,height/2+305*le,"SELECT ANOTHER IMAGE"),gr(Ue,width/2+75*le,width/2+225*le,height/2+265*le,height/2+305*le,"CLOSE")}function nr(e,t,n,r,i,o){let a=i.split(" "),l=75*be/o.textWidth('"'+i+'"'),s=0,h=[],c=[],u=[],f="",d="";if(l>=50)l>75&&(l=75),o.textSize(l*le),o.text('"'+i+'"',e,t);else if(l<50){if(l=50*defaultPhrase/o.textWidth('"'+i+'"'),l>30){if(l>50&&(l=50),[f,d]=rr(l,n,s,h,c,a,f,d,Ue),0==c.length)return o.textSize(l*le),void o.text('"'+i+'"',e,t);for(s=0,h=[],c=[];o.textWidth(d)>n/le;)l=l*n/le/o.textM Width(d),f="",d="",[f,d]=rr(l,n,s,h,c,a,f,d,Ue)}else{l=30,o.textSize(l);for(let e=0;e<a.length;e++)s+=o.textWidth(" "+a[e]),s<=n/le?h.push(a[e]):s>n/le&&s<=n/le*2?c.push(a[e]):u.push(a[e]);for(let e=1;e<h.length;e++)f=f+" "+h[e];if(f='"'+h[0]+f,0==u.length){for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+c[c.length-1]+'"'}else if(1==c.length)d="... "+u[u.length-1]+'"';else{for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+"... "+u[u.length-1]+'"'}}o.textSize(l*le);let r=1.25*(o.textDescent()+o.textAscent());o.text(f,e,t-M r/2),o.text(d,e,t+r/2)}}function rr(e,t,n,r,i,o,a,l,s){s.textSize(e);for(let e=0;e<o.length;e++)(n+=s.textWidth(" "+o[e]))<=t/le?r.push(o[e]):i.push(o[e]);for(let e=1;e<r.length;e++)a=a+" "+r[e];if(a='"'+r[0]+a,0==i.length&&(a+='"',l=""),1==i.length)l=i[i.length-1]+'"';else{for(let e=0;e<i.length-1;e++)l=l+i[e]+" ";l=l+i[i.length-1]+'"'}return[a,l]}function ir(){const e=45*le;qe.textFont("Tahoma"),qe.stroke(st),qe.strokeWeight(2*le),qe.fill(ct),qe.rect(width/2,e/2+height-87.5*le,600*le,90*le),qe.fill(st),qe.rect(wiM dth/2-150*le,e+height-170*le,300*le,30*le),qe.fill(ct),qe.rect(width/2+150*le,e+height-170*le,300*le,30*le),qe.noStroke(),qe.fill(ct),qe.textSize(15*le),qe.textStyle(BOLD),qe.text("PERCEPTRON INFORMATION",width/2-285*le,e+height-165*le),qe.fill(xt),qe.text("ARTWORK NAME:",width/2+10*le,e+height-165*le),qe.textAlign(RIGHT),qe.textStyle(ITALIC),qe.text("Perceptron #"+Et,width/2+285*le,e+height-165*le);const[t,n]=It.split(" ");let r;"60 Years"===It?r="1 Year":"60 Months"===It?r="1 Month":"60 Weeks"===It?r="1 Week":"60M Days"===It?r="1 Day":"12 Hours"===It&&(r="12 Minutes"),data=[["AI MODEL NAME:",B(12*le,Ht,140*le)],["SCALE:","1:"+Te],["NUMBER OF CLASSES:",$t.length],["BIRTH YEAR:",Rt],["NUMBER OF REBIRTHS:",sn.toString()],["AGE:",`${Math.ceil(Mt)} Perceptron Years`],["ONE PERCEPTRON YEAR:",`${r}`],["STATE:",Ot[Pe]],["ACTIVE NEURONS:",`${round(ln*rn)} / ${ln}`],["NEXT STATE TIME:",vr(new Date(on))]],qe.fill(xt);const i=data.length/2;for(let t=0;t<data.length;++t){const n=t<i,r=n?width/2-285*le:width/2+10*le,o=n?width/2-10*le:widM th/2+285*le,a=e+height-(135-t%i*15)*le;qe.textStyle(BOLD),qe.textAlign(LEFT),qe.textSize(12*le),qe.text(data[t][0],r,a),qe.textStyle(ITALIC),qe.textAlign(RIGHT),qe.textSize(12*le),qe.text(data[t][1],o,a)}}function or(){Ke.textFont("Trebuchet MS"),Ke.noStroke(),pr(Ke,600*le,200*le),gr(Ke,width/2-155*le,width/2-5*le,height/2+115*le,height/2+155*le,"UPDATE"),gr(Ke,width/2+5*le,width/2+155*le,height/2+115*le,height/2+155*le,"CLOSE"),Ke.textAlign(LEFT),Ke.fill(xt),Ke.text("UPDATE BITCOIN FULL NODE ADDRESS",width/2-252.5M *le,height/2-55*le),Ke.text("UPDATE MODEL ADDRESS",width/2-252.5*le,height/2+20*le),Ke.textAlign(RIGHT),Ke.textStyle(ITALIC),Ke.textSize(15*le),0==wn&&Ke.text("(*) Invalid Address",width/2+252.5*le,height/2-53*le),0==vn&&Ke.text("(*) Invalid Model",width/2+252.5*le,height/2+23*le)}function ar(){je.textFont("Trebuchet MS"),je.fill(st),je.textSize(50*le),je.stroke(st),je.strokeWeight(1*le),je.text("main()",width/2,height/2)}function lr(){un>=20&&1==dn&&(dn=!1,un=0),dn&&(Ze.textFont("Trebuchet MS"),Ze.stroke(st),Ze.fiM ll(ct),Ze.rect(width/2,height/2,600*le,150*le,25*le),Ze.fill(xt),Ze.textSize(75*le),Ze.noStroke(),1==Pe?Ze.text("GROWING",width/2,height/2+5*le):3==Pe?Ze.text("AGING",width/2,height/2+5*le):4==Pe?Ze.text("DEAD",width/2,height/2+5*le):5==Pe&&Ze.text("BIRTH",width/2,height/2+5*le)),un>=20&&0==dn&&(dn=!0,un=0,Bt++,3==Bt&&(fn=!1))}function sr(e,t,n,r){let i=[],o=r/(n.length+1),a=color(e),l=color(t);i.push(a);for(let e=0;e<n.length;e++){let t=color(n[e]);for(let e=1;e<=o;e++){let n=lerpColor(a,t,e/o);i.push(n)}a=t}for(lM et e=1;e<o;e++){let t=lerpColor(a,l,e/o);i.push(t)}if(i.push(l),i.length>r)i.splice(r);else if(i.length<r){let e=i[i.length-1];for(;i.length<r;)i.push(e)}return i}function hr(e,t){let n=e.length,r=Math.floor(t*n);return r>=n&&(r=n-1),e[r]}function cr(e){e=e.replace("#","");var t=parseInt(e,16);return color(t>>16&255,t>>8&255,255&t)}function ur(e,t,n,r,i,o,a,l){var s=a.drawingContext.createLinearGradient(e,t,n,r);s.addColorStop(0,i),s.addColorStop(1,o),a.drawingContext.strokeStyle=s,a.drawingContext.globalAlpha=l,a.M line(e,t,n,r),a.drawingContext.globalAlpha=1}function fr(e,t){t.drawingContext.setLineDash(e)}function dr(e,t){let n=color(e),r=red(n),i=green(n),o=blue(n);return color(r,i,o,255*t)}function xr(e,t,n,r){return mouseX>e&&mouseX<t&&mouseY>n&&mouseY<r}function gr(e,t,n,r,i,o){e.strokeWeight(1*le),e.stroke(st);const[a,l]=xr(t,n,r,i)?[xt,ct]:[ct,xt];e.fill(a),e.push(),e.rectMode(CORNERS),e.rect(t,r,n,i,5*le),e.pop(),e.noStroke(),e.textSize(20*le),e.fill(l),e.text(o,(t+n)/2,(46*r+54*i)/100)}function pr(e,t,n){e.fill(0,0,M 0,75),e.rect(width/2,height/2,width,height),e.stroke(st),e.fill(ct),e.rect(width/2,height/2,t,n,25*le)}function mr(e,t){resizeCanvas(e,t,!0),Xe.resizeCanvas(e,t,!0),$e.resizeCanvas(e,t,!0),We.resizeCanvas(e,t,!0),Ue.resizeCanvas(e,t,!0),qe.resizeCanvas(e,t,!0),Qe.resizeCanvas(e,t,!0),je.resizeCanvas(e,t,!0),Ze.resizeCanvas(e,t,!0),Ke.resizeCanvas(e,t,!0),Je.resizeCanvas(e,t,!0),et.resizeCanvas(e,t,!0)}function br(e,t,n,r,i,o){const a=J(e);return a.position(t,n),a.size(r,i),a.style("opacity","0"),a.mouseClicked(o),aM }function yr(){return null!=vt&&vt?.isFocused()||null!=zt&&zt?.isFocused()}function wr(e,t,n,r){let i;if(e<=3){i=`Hey ${String.fromCodePoint(128075)}, I'm ${n}, ${t} years old. I can detect ${r.length} NFT collections: `;let e=0;for(let t=0;t<r.length;++t){const n=r[t];if(e+n.length>500){i+=", etc";break}t==r.length-1?i+=", and ":t>0&&(i+=", "),i+=n,e+=n.length}i+=". ",t<=5?i+="However, I am only a baby, so my recognition ability is not accurate. I'm in the state of Growing both looks and intelligence.":t<=13?i+="IM am now a child. My recognition ability is becoming better, but still not very accurate. I'm in the state of Growing both looks and intelligence.":t<=25?i+="I have grown up to be a teen. My recognition ability almost reaches the peak, but I will still mess up sometimes. I'm in the state of Growing both looks and intelligence.":t<=50?i+="I finally reach adulthood. My recognition is fully functional now. I'm in the Stable state, where I am the most intelligent with all neurons activated.":t<=60&&(i+="I am now an old M Perceptron, so my recognition ability is no longer the best. I'm in the Decaying state, meaning that my neurons are dying, and my intelligence is decreasing over time.")}else 4==e?i=`${n} is Dead. However, this is not the end to its story...`:5==e&&(i=`${n} is now in the Rebirth state, and is preparing to start a new life.`);return i}function vr(e){const t=e.getDate(),n=e.toLocaleString("en-US",{month:"long"}),r=e.getFullYear();let i=e.getHours().toString();1==i.length&&(i="0"+i);let o=e.getMinutes().toString();retM urn 1==o.length&&(o="0"+o),`${Y(t)} ${n} ${r} | ${i}:${o}`}saveCanvasAtCurrentTime=()=>{save(N())},save4KCanvasAtCurrentTime=()=>{const e=width,t=height,n=min(4096/min(e,t),1e4/max(e,t)),r=e*n,i=t*n;mr(r,i),zn=!0,$n(r,i),qn();let o="4K_"+N()+".png";saveCanvas(et,o),mr(e,t),$n(e,t),zn=!1};const zr=[["60 Years",3,365],["60 Months",40,30],["60 Weeks",37,7],["60 Days",20,1]],Vr=[["1943",1],["1951",1.5],["1957",2],["1969",2.5],["1970",3],["1980",3.5],["1982",4],["1986",4.5],["1988",5],["1997",5.5],["1998",6],["2002",6.5M ],["2009",7],["2012",7.5],["2014",8],["2015",8.5],["2016",9],["2023",15]],_r=[["Plain",20],["Dotted",40],["Squared",40]],Mr=[["Basic",30],["Standard",60],["Advanced",10]],Er=[["MNIST",70],["CIFAR",25],["IMAGENET",5]],Sr=[["Theano",60],["Torch",30],["TensorFlow",10]],Rr=[["Whitepaper",2],["Blackboard",2],["Blueprint",2],["Nak",74/14],["Jims",74/14],["Level 10",74/14],["Flips",74/14],["Level 14",74/14],["III",74/14],["XMB",74/14],["Info",74/14],["Adventure",74/14],["Marigold",74/14],["Phoenix",74/14],["Love",74/14],[M "Cachet",74/14],["Human",74/14],["Twilight",3],["Sunset",3],["Aurora",3],["Liminal Space",3],["D Vu",3],["Lucid Dream",3],["Parallel",1],["Multiverse",1]];function Ir(e){for(let e=0;e<100;++e)random(1);return{visual:{pattern:k(_r),hardwareAcceleration:k(Mr),nodeFill:k(Er),nodeShape:k(Sr),colorPalette:k(Rr),lifeCycle:k(zr),birthYear:k(Vr)},training:e}}function Cr(e){window.$generativeTraits={"Network Architecture":e.training.structure_gen,"Hidden Layers":e.training.n_layers,"Max Neurons Per Hidden Layer":e.traiM ning.max_nodes,"Activation Function":e.training.activation_func,"Training Epochs":e.training.epoch_num,Dataset:e.visual.nodeFill,"Deep Learning Framework":e.visual.nodeShape,"Hardware Acceleration":e.visual.hardwareAcceleration,"Paper Pattern":e.visual.pattern,"Life Cycle":e.visual.lifeCycle,"Birth Year":e.visual.birthYear,"Color Palette":e.visual.colorPalette}} <script defer src="https://static.cloudflareinsights.com/beacon.min.js/v2b4487d741ca48dcbadcaf954e159fc61680799950996" integrity="sha512-D/M jdE0CypeVxFadTejKGTzmwyV10c1pxZk/AqjJuZbaJwGMyNHY3q/mTPWqMUnFACfCTunhZUVcd4cV78dK1pQ==" data-cf-beacon='{"rayId":"7b4da14148d6a21c","version":"2023.3.0","b":1,"token":"6c07c178c94442f695e7a0a2aaee641a","si":100}' crossorigin="anonymous"></script> text/plain;charset=utf-8 "to": "bc1pdrh3du0e2rj7up3k8trsrzz6eyyq05gs0tqdwz59g3yweeguvuqsnvlctm" text/plain;charset=utf-8 6{"p":"brc-20","op":"mint","tick":"BRUH","amt":"10000"}h! text/plain;charset=utf-8 6{"p":"brc-20","op":"mint","tick":"BRUH","amt":"10000"}h! text/plain;charset=utf-8 6{"p":"brc-20","op":"mint","tick":"BRUH","amt":"10000"}h! text/plain;charset=utf-8 6{"p":"brc-20","op":"mint","tick":"BRUH","amt":"10000"}h! text/plain;charset=utf-8 6{"p":"brc-20","op":"mint","tick":"BRUH","amt":"10000"}h! text/plain;charset=utf-8 6{"p":"brc-20","op":"mint","tick":"BRUH","amt":"10000"}h! text/plain;charset=utf-8 6{"p":"brc-20","op":"mint","tick":"BRUH","amt":"10000"}h! text/plain;charset=utf-8 6{"p":"brc-20","op":"mint","tick":"BRUH","amt":"10000"}h! text/plain;charset=utf-8 6{"p":"brc-20","op":"mint","tick":"BRUH","amt":"10000"}h! text/plain;charset=utf-8 6{"p":"brc-20","op":"mint","tick":"BRUH","amt":"10000"}h! text/plain;charset=utf-8 6{"p":"brc-20","op":"mint","tick":"BRUH","amt":"10000"}h! text/plain;charset=utf-8 6{"p":"brc-20","op":"mint","tick":"BRUH","amt":"10000"}h! text/plain;charset=utf-8 6{"p":"brc-20","op":"mint","tick":"BRUH","amt":"10000"}h! text/plain;charset=utf-8 6{"p":"brc-20","op":"mint","tick":"BRUH","amt":"10000"}h! text/plain;charset=utf-8 6{"p":"brc-20","op":"mint","tick":"BRUH","amt":"10000"}h! text/plain;charset=utf-8 6{"p":"brc-20","op":"mint","tick":"BRUH","amt":"10000"}h! text/plain;charset=utf-8 6{"p":"brc-20","op":"mint","tick":"BRUH","amt":"10000"}h! text/plain;charset=utf-8 6{"p":"brc-20","op":"mint","tick":"BRUH","amt":"10000"}h! text/plain;charset=utf-8 6{"p":"brc-20","op":"mint","tick":"BRUH","amt":"10000"}h! text/plain;charset=utf-8 6{"p":"brc-20","op":"mint","tick":"BRUH","amt":"10000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"rssc","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"rssc","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"rssc","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"rssc","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"rssc","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"rssc","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"rssc","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"rssc","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"rssc","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"rssc","amt":"1000"}h! text/plain;charset=utf-8 3{"p":"brc-20","op":"mint","tick":"WASS","amt":"20"}h! text/plain;charset=utf-8 "p":"sns","op":"reg","name":"metawallet.unisat" text/plain;charset=utf-8 +{"p":"sns","op":"reg","name":"auburn.sats"}h! text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 ){"p":"sns","op":"reg","name":"esso.sats"}h! text/plain;charset=utf-8 +{"p":"sns","op":"reg","name":"texaco.sats"}h! text/plain;charset=utf-8 1{"p":"sns","op":"reg","name":" text/plain;charset=utf-8 +{"p":"sns","op":"reg","name":"1chain.sats"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 8{"p":"sns","op":"reg","name":"vestiairecollective.sats"}h! text/plain;charset=utf-8 +{"p":"sns","op":"reg","name":"luxify.sats"}h! text/plain;charset=utf-8 /{"p":"sns","op":"reg","name":"MonAfrique.sats"}h! text/plain;charset=utf-8 /{"p":"sns","op":"reg","name":"netaporter.sats"}h! "3 % % 3-7,),7-Q@88@Q^OJO^qeeq "3 % % 3-7,),7-Q@88@Q^OJO^qeeq text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 OiCCPPhotoshop ICC profile text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 -{"p":"sns","op":"reg","name":"jacob&co.sats"}h! FjDOUT:FE724489CEECCEFA630827CDD39601A70A0D186304A9DDF1D29A2448AEAD0E8A FjDOUT:30C38B0F52E4D0D458C0FC4D430DD608BA54EA5B2D51718BAA26C51F413173FB text/plain;charset=utf-8 ,{"p":"sns","op":"reg","name":"Daimond.sats"}h! Bj@=:BNB.BNB:bnb195g9wjaep23yv9hf4944evh44up5fhu6pfdplu:14947110::0 text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":" DjB=:ETH.ETH:0xBa1ca9c92099CD5c8792D4f7afe0Af8b9FfD8989:20725963:te:0 text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 Lm{"p":"orditalk.org","op":"post","content":"Third unique post on orditalk!","attached_inscription_id":"68040"}h! DjB=:ETH.ETH:0x06c5aDBA450a602b370A61DE0eCe41A949550E93:12019881:te:0 text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 La{"p":"orditalk.org","op":"create_user","name":"Carbonz","profile_picture_inscription_id":"26158"}h! text/plain;charset=utf-8 "p":"sns","op":"reg","name":"0008.unisat" text/plain;charset=utf-8 "p":"sns","op":"reg","name":"nike.unisat" text/plain;charset=utf-8 "p":"sns","op":"reg","name":"hermes.unisat" text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 "p":"sns","op":"reg","name":"bit.unisat" text/plain;charset=utf-8 "p":"sns","op":"reg","name":".unisat" text/plain;charset=utf-8 "p":"sns","op":"reg","name":"samsung.unisat" text/plain;charset=utf-8 "p":"sns","op":"reg","name":"starbucks.unisat" 45f2eb92485a8bcd90ad3c0765be2d4ee <?xml version="1.0" encoding="UTF-8"?><svg id="cancer" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" viewBox="0 0 1440 1440"><defs><style>.cls-1{fill:url(#linear-gradient);}.cls-2{fill:#fff;}.cls-3{fill:url(#linear-gradient-2);}</style><linearGradient id="linear-gradient" x1="120.22" y1="-2339.79" x2="1319.78" y2="-1333.25" gradientTransform="translate(0 -1476.52) scale(1 -1)" gradientUnits="userSpaceOnUse"><stop offset="0" stop-color="#6aba71"/><stop offset=".25" stop-color="#64c195M "/><stop offset=".5" stop-color="#8da07c"/><stop offset=".75" stop-color="#b7529a"/><stop offset="1" stop-color="#aa5457"/></linearGradient><linearGradient id="linear-gradient-2" y1="-4592.92" y2="-3586.38" gradientTransform="translate(0 5169.65)" xlink:href="#linear-gradient"/></defs><rect class="cls-1" width="1440" height="720"/><rect class="cls-3" y="720" width="1440" height="720"/><g><path class="cls-2" d="M628.79,798.7s-.02,.05-.03,.08c.04,.01,.07,.03,.11,.04l-.08-.12Zm6.36,43.48c-15.02-5.63-10-2.34-.08-12.22,M 1.47-1.33,1.07-1.68-.63-2.26-3-1.2-6.2-2.02-9.09-3.46-.15-.1-.24-.44-.15-.57,2.93-3.25,6.16-6.25,9.19-9.4-1.43-1.25-13.05-3.77-11.98-5.3,2.05-3.41,4.76-6.56,6.35-10.19-3.82-1.44-7.73-2.69-11.51-4.24-.48-.22-.69-.69-.46-1.09,1.98-3.36,3.89-6.76,5.63-10.24-4.11-1.27-7.94-3.02-11.83-4.66-.39-.16-.6-.74-.42-1.13,1.78-3.35,2.83-7.14,4.96-10.26,.05-.04,.08-.09,.12-.13-4.5-1.15-8.23-3.93-12.69-5.03-2.05,3.28-3.25,6.84-5.52,10.11-4.35-1.6-8.1-4.15-12.14-6.24-.71,.07-1.06,.36-1.33,.76-1.8,2.65-3.76,5.52-5.74,7.98-.81,.25-1.M 21-.08-1.59-.34-3.2-2.14-6.37-4.32-9.57-6.46-.69-.47-1.25-1.12-2.41-1.27-2.4,2.53-5.18,4.86-7.95,7.2-.8,.91,.82,1.48,1.35,2.02,3.78,2.63,7.53,5.22,11.34,7.82-2.34,3.09-6.55,4.5-9.52,6.82,.17,.72,.78,.98,1.27,1.3,3.24,2.12,6.49,4.21,9.73,6.32,.48,.45,1.87,.89,1.53,1.66-2.94,1.97-6.39,3.17-9.54,4.81-.58,.28-1.2,.5-1.52,1.17,3.6,2.56,7.55,4.81,11.3,7.18,.45,.28,.74,.61,.66,1.18-3.75,1.76-7.94,3.16-11.95,4.53-2.25,.85,1.45,2.14,2.14,2.81,2.46,1.52,4.93,3.01,7.39,4.52,.52,.32,1.12,.58,1.34,1.13-.34,.51-.95,.73-1.6,.9-3.M 95,1.06-7.91,2.13-11.85,3.21-.56,.23-2.38,.39-1.58,1.28,3.42,2.29,6.93,4.48,10.42,6.64,.24,.16,.25,.55,.38,.88-5.74,1.55-11.47,2.56-17.3,3.48-.82,.1-.82,.76-.16,1.15,2.62,1.86,5.37,3.63,8.04,5.4,.73,.53,1.92,.79,1.91,1.82-.67,.69-1.69,.57-2.59,.7-5.83,.82-11.66,1.73-17.53,2.24-.35,.04-.62,.58-.4,.76,2.6,2.24,5.55,4.08,8.29,6.14,.54,.48,2.32,1.33,1.03,1.88-5.03,.87-10.16,.84-15.25,1.28-2.55,.17-5.1,.32-7.65,.49-.22,.02-.53,.16-.62,.31-.09,.15-.04,.45,.11,.58,2.65,2.31,5.51,4.43,8.24,6.65,2.35,1.84-.09,1.62-1.64,1.79M -7.67,.36-15.35,.51-23.03,.3-.75,.05-1.69-.1-2.35,.2-.06,.19-.17,.46-.05,.59,2.76,2.82,5.82,5.37,8.68,8.08,.25,.36,.26,.99-.4,.95-9.14-.12-18.31-.32-27.43-1.1-1.45-.17-2.95-.12-4.42-.17-1.13,.34-.06,1.3,.35,1.82,2.11,2.23,4.25,4.44,6.37,6.67,.33,.55,1.67,1.29,.78,1.84-10.18,.22-20.35-1.57-30.47-2.57-2.4-.28-4.78-.62-7.18-.91-.21-.02-.56,.1-.66,.24-.1,.15-.07,.44,.06,.59,2.56,3.29,5.19,6.53,7.71,9.86,.2,.26-.12,.75-.47,.72-1.47-.11-2.96-.14-4.41-.35-13.83-1.91-27.59-4.18-41.27-6.83,2.62,3.94,5.17,7.95,7.7,11.94,.32,M .52-.08,.76-.54,.86,.76,.39,1.52,.78,2.28,1.16,.19-.55,1.06-.35,1.55-.31,14.66,2.44,29.42,4.47,44.27,5.55,.35,0,.71-.43,.54-.68-2.4-3.54-5.54-6.56-7.91-10.12-.23-1.16,2.29-.44,2.97-.51,3.2,.32,6.4,.75,9.62,.98,8.84,.42,17.75,1.54,26.59,1.25,.61-.36,.06-.99-.29-1.36-2.55-2.78-5.34-5.36-7.73-8.27,0-1.15,1.85-.56,2.62-.67,7.14,.12,14.28,.29,21.42,.34,2.95,.03,5.91-.19,8.87-.3,1.59-.41-1.86-2.59-2.28-3.21-1.97-1.9-4.27-3.53-6.03-5.63-.18-.22,.14-.7,.5-.7,9.3-.18,18.57-.53,27.8-1.55,.5-.39-.05-1.01-.48-1.32-2.38-1.91-4.M 78-3.8-7.15-5.71-.39-.44-1.81-1.18-1.02-1.75,2.26-.27,4.52-.55,6.8-.73,5.73-.52,11.51-.92,17.14-2.12,.13-.03,.28-.44,.2-.52-2.76-2.45-6.04-4.28-9.02-6.44-.41-.28-.82-.57-.76-1.14,6.4-1.49,13.19-1.87,19.6-3.44,.48-.12,1.45-.3,1.24-.94-2.73-2.3-6.04-3.92-9-5.94-.52-.34-1.1-.64-1.25-1.34,5.85-1.57,11.86-2.67,17.66-4.39,.3-.11,.43-.66,.18-.82-3.05-1.99-6.25-3.73-9.37-5.61-.52-.32-1.13-.61-1.26-1.35,5.01-1.75,10.61-2.81,15.44-5.07,0-.68-.63-.95-1.17-1.25-3.32-2.02-6.98-3.6-10.1-5.89-.53-.86,1.57-1.13,2.11-1.49,3.55-1.53M ,7.37-2.55,10.73-4.44,.15-.1,.13-.37,.21-.66-4-2.33-8.22-4.43-12.15-6.94,.8-1.24,2.27-1.46,3.5-2.13,2.59-1.17,4.94-2.62,7.24-4.11,.27-.17,.35-.53,.54-.87-16.76-10.36-14.43-4.33-3.91-14.27,.14-.15,.13-.4,.18-.61h0c.77,0,1.52,.05,2.24,.43,3.74,2.09,7.71,3.85,11.37,6.07-2.04,3.28-5.92,5.58-8.72,8.3,.12,.6,.53,.86,.99,1.1,2.4,1.2,4.79,2.41,7.19,3.6,.7,.61,4.52,1.44,3.21,2.61-12.11,10.14-15.25,4.39,1.29,13.36,.07,.61-.26,.9-.73,1.16-3.35,1.82-6.79,3.51-10.47,4.86-.73,.27-1.54,.46-2.03,1.24,3.61,2.34,7.84,4.04,11.7,6.3-.M 84,1.08-2.12,1.23-3.33,1.72-3.83,1.32-7.68,2.62-11.52,3.91-.53,.18-.92,.42-1.08,1,3.16,1.97,6.57,3.69,9.83,5.53,.43,.24,.85,.49,.95,1.05-5.84,2.31-12.12,3.41-18.16,5.22-1.55,.61,3.53,2.75,4.07,3.32,1.82,1.1,3.66,2.19,5.46,3.33,.26,.16,.32,.54,.51,.91-6.94,2-14.02,3.04-21.07,4.53-1.45,.95,7.55,5.72,8.58,6.73,.41,.27,.85,.54,.85,1.04-.73,.52-1.69,.61-2.58,.76-7.22,1.33-14.54,2.19-21.85,3.16-1.29,.6,.48,1.44,.95,1.96,2.3,1.81,4.61,3.62,6.93,5.43,.39,.3,.74,.6,.68,1.1-2.47,.9-5.29,.79-7.89,1.18-6.93,.86-14,.94-20.89,1.M 67-.15,.1-.27,.46-.18,.54,2.01,1.88,4.08,3.72,6.07,5.62,.92,.88,2.33,1.49,2.61,2.76-1.19,1.02-2.77,.47-4.17,.65-9.66,.85-19.38,.55-29.07,.77-.37,.01-.72,.46-.53,.69,2.12,2.67,4.62,5.03,6.91,7.55,.41,.43,.74,.9,1.1,1.36,.31,1.2-3.74,.7-4.58,.85-11.6,.03-23.17-.45-34.71-1.3-1.41,.33,.27,1.72,.59,2.38,1.98,2.57,3.98,5.13,5.96,7.69,.29,.37,.54,.75,.18,1.28-7.36,.11-14.81-.93-22.17-1.42,10.27,4.44,20.74,8.64,31.4,12.58-2.1-3.34-4.81-6.38-7.13-9.61-.2-.26-.54-.59-.19-.87,.24-.2,.69-.35,1.02-.33,10.63,.61,21.29,.21,31.93,M .23,1.14-.22,8.83,.42,6.91-1.56-2.16-2.49-4.46-4.87-6.69-7.3-.4-.52-1.44-1.53-.25-1.81,11.28-.29,22.58-.75,33.77-2.22,.03-.26,.15-.52,.04-.64-2.58-2.81-5.85-4.99-8.32-7.88-.19-.22,.1-.74,.45-.77,1.73-.16,3.48-.24,5.21-.45,7.7-1,15.46-1.72,23.1-3.09,1.94-.52-1.43-2.16-1.93-2.77-2.05-1.56-4.14-3.09-6.18-4.65-.25-.2-.31-.54-.53-.93,8.34-1.8,16.98-2.44,25.09-4.91,.23-.91-.85-1.25-1.41-1.77-2.37-1.6-4.76-3.18-7.11-4.79-.27-.19-.54-.51-.56-.78-.02-.34,.45-.51,.83-.6,3.11-.72,6.23-1.39,9.32-2.15,3.34-.82,6.66-1.72,9.99-2.M 57,.54-.14,.95-.39,1.2-.94-3.05-2.3-6.73-3.8-9.79-6.1-.12-.09-.13-.47-.03-.51,6.11-2.39,12.6-3.68,18.68-6.19-2.65-2.45-6.74-3.72-9.9-5.6-.48-.24-.8-.56-.95-1.1,1.54-.72,17.19-5.68,15.46-7.13-3.04-1.62-6.19-3.04-9.29-4.56-.59-.28-1.15-.57-1.41-1.13,4.18-2.17,8.42-4.23,12.12-6.93,.6-.48,1.36-.84,2.14-.52l9.72,3.96c.42,.14,.93,.51,.75,.97-3.66,3.19-8.36,5.42-12.23,8.31,.14,.53,.52,.8,1.01,1.02,2.37,1.03,4.72,2.07,7.09,3.1q3.06,1.34,.14,3.02c-4.07,2.48-8.71,4.36-13.11,6.3,.02,.56,.4,.82,.84,1.04,3.28,1.66,6.42,3.14,9.6M 7,4.92-5.71,3.39-12.46,4.62-18.61,7.07-.51,.19-.56,.77-.08,1.05,2.4,1.39,4.82,2.77,7.21,4.16,3.56,1.97,1.65,1.97-.97,2.96-5.98,1.96-12.17,3.49-18.28,5.15-.53,.15-.59,.68-.11,1.01,2.66,1.84,5.43,3.55,8.12,5.34,.41,.27,.82,.56,.81,1.09-7.49,2.69-15.62,3.86-23.5,5.47-.94,.06-2.58,.57-1.46,1.49,2.26,1.87,4.61,3.61,6.92,5.43,.67,.45,1.94,1.55,.53,1.95-9.47,2.18-19.24,2.95-28.78,4.77-.08,.73,.45,1.1,.87,1.5,2.1,1.97,4.21,3.93,6.3,5.9,.43,.4,.94,.78,.94,1.39-4.35,1.45-9.25,1.37-13.8,2.02-6.82,.66-13.63,1.31-20.5,1.64-1.39M ,.43,.39,1.73,.78,2.37,2.38,2.58,4.79,5.15,7.2,7.72,2.41,.24,4.77-.3,7.15-.54,9.62-1.11,19.26-1.86,28.67-4.07-.11-.34-.09-.69-.3-.9-2.49-2.78-5.64-4.88-7.87-7.89,10.12-2.09,20.27-3.43,30.23-6.09-.04-.29,.01-.55-.12-.69-2.36-2.26-5.06-4.17-7.57-6.27-.38-.31-.7-.64-.62-1.23,8.45-2.08,17.24-4.09,25.52-6.72,.14-.54-.09-.89-.54-1.18-1.06-.98-9.15-5.24-8.2-6.18,5.59-1.88,11.31-3.43,16.84-5.42,1.83-.77,3.85-.95,5.33-2.33-3.15-2.12-6.67-3.65-9.76-5.71,.15-.55,.55-.79,1.07-.97,5.9-2.04,11.67-4.21,17.05-7.29,1.7-1.35-8.81-4.M 44-9.31-6,5.11-2.92,10.48-5.48,15.19-9.07-3.03-1.62-6.13-2.75-9.25-4.15-.49-.21-.86-.49-1.03-1.02,3.63-2.52,7.35-5.02,11.01-7.52,.94-.64,2.65-1.75,.74-2.35Zm-42.47-58.69c-.68-.33-1.27-.82-2.29-.78-2.84,2.98-4.96,6.94-8.42,9.26,.27-.87-.97-1.13-1.51-1.6-3.55-2.25-7.45-4.1-10.77-6.65,2.66-2.83,5.23-5.57,7.84-8.35,4.71,1.93,8.14,5.04,12.98,6.72,2.47-2.76,4.11-6.05,6.28-9.02,.4-.46,1.32-.18,1.82,.08,3.6,1.72,7.3,3.15,10.79,5.08-1.23,3.44-3.68,6.43-5.41,9.69-.75,1.17-2.16-.06-3.08-.37-2.75-1.35-5.48-2.72-8.23-4.06Zm7.06M ,29.95c1.34-2.11,3.77-3.51,5.52-5.34,.6-.87,4.54-3.28,2.67-4.07-3.86-1.79-7.77-3.38-11.52-5.41,1.56-3.15,4.28-5.69,6.29-8.62,.78-.99,1.08-1.08,2.23-.59,3.56,1.63,7.4,2.91,10.82,4.78,.07,.2,.19,.33,.15,.4-1.98,3.29-4.19,6.53-6.49,9.6,.33,.58,.9,.84,1.51,1.08l7.92,3.21c.64,.44,2.96,.67,2.37,1.74-2.63,3.2-5.89,5.87-8.99,8.61-.39,0-.7,.07-.91-.01-3.81-1.87-8.04-3.11-11.57-5.38Zm12.7,19.79c-3.34-1.5-6.51-2.91-9.66-4.34-.57-.35-2.42-.92-1.52-1.73,3.43-2.41,6.8-4.88,9.99-7.49,.39-.32,.92-.44,1.48-.22,3.48,1.38,6.97,2.77,1M 0.44,4.18,.32,.12,.51,.44,.75,.66-2.3,2.3-7.07,6.02-11.48,8.94Zm16.35-34.53s-.02,.05-.03,.08c.04,.01,.07,.03,.11,.04l-.08-.12Zm5.61,15.56h-.01l.15,.1-.14-.1Zm-5.61-15.56s-.02,.05-.03,.08c.04,.01,.07,.03,.11,.04l-.08-.12Zm-97.87,137.07h-.05l.09,.05s-.03-.03-.04-.05Zm-117.1-41.36l-.16,.07c.08,.01,.15,.03,.23,.04-.02-.04-.05-.07-.07-.11Zm-17.15,58.51c-1.71-4.08-4.03-7.94-5.45-12.12-.03-.13,.25-.43,.41-.44,1.24-.13,2.48,.11,3.71,.3-2.03-1.06-4.04-2.14-6.05-3.23,.59,1.43,1.29,2.46-1.04,2.07-20.82-3.76-41.43-8.38-61.82-1M 3.82-2.51-.69-1.82,.79-1.3,2.37,1.34,3.61,2.72,7.21,4.07,10.82,.13,.63,.75,1.74-.12,2.02-18.43-3.93-36.65-9.46-54.63-14.85-6.41-1.98-12.74-4.11-19.12-6.14-.97-.31-1.89-.84-3.03-.72-.42,.51-.3,1.04-.17,1.57,1.09,5.08,2.89,10.07,3.57,15.2-.34,.84-2.86-.29-3.59-.38-15.64-4.97-31.18-10.14-46.54-15.65-12.78-4.58-25.44-9.37-37.96-14.4-1.22-.4-2.38-1.13-3.68-1.23-.33-.03-.53,.1-.58,.34,.14,5,1.27,10.07,1.74,15.09,.15,1.17,.47,2.34,.13,3.52-37.09-12.51-73.51-29.42-109.11-45.47-.76-.32-1.44-.09-1.47,.51-.03,.43-.05,.87-.04,M 1.3,.02,5.71,.05,11.42,.09,17.13,.02,1.31-.17,2.54,1.42,3.08,35.35,15.56,71.35,29.78,107.86,42.7,.98,.35,2,.62,3.01,.9,.31,.08,.57-.06,.58-.29,.04-.64,.09-1.28,.02-1.92-.57-5.47-1.51-10.93-1.9-16.4,.45-1.25,2.91,.34,3.83,.5,29.07,10.84,58.99,20.46,88.95,29.08,1.99,.6,1.52-1.28,1.19-2.45-.9-3.8-1.82-7.61-2.7-11.42-.22-.95-.31-1.91-.4-2.87-.01-.11,.4-.37,.55-.34,25.62,7.2,51.33,14.93,77.57,19.91,.18,.02,.57-.26,.55-.38-.9-4.71-3.04-9.15-4.44-13.73-.2-.51-.32-1.25,.42-1.31,20.32,4.32,40.55,8.86,61.16,11.96,1.06,.17,2.M 13,.28,3.2,.4,1.01,.11,1.44-.36,1.11-1.21Zm-77.86-43.74c13.27,3.42,26.45,7.52,39.88,10.57-12.23-7.53-24.09-15.44-35.55-23.7-3.71-1.13-7.23-2.35-10.97-3.46-.12,.4-.36,.73-.27,.99,1.6,4.58,3.53,9.05,5.3,13.56,.12,.3,.23,.69-.18,.86-25.17-6.17-49.33-16.39-73.72-25.09-.29-.1-.85,.28-.81,.53,.06,.32,.1,.64,.18,.95,1.26,4.86,2.71,9.66,3.81,14.54,.05,.21,.04,.43,.06,.64,.02,.26-.57,.55-.9,.43-5.25-1.97-10.52-3.87-15.72-5.91-23.94-9.12-47.48-19.26-70.75-29.82-.51-.22-1.18,.08-1.14,.51,.14,1.51,.27,3.01,.47,4.51,.37,4.57,1.M 65,9.27,1.57,13.79-.9,.32-1.55-.2-2.2-.49-33.99-14.84-67.29-30.94-100.03-48.14-1.09-.42-3.36-2.23-3.28,.09,.18,6.76-.36,13.61,.26,20.32,28.67,14.5,57.92,27.76,87.57,40.35,5.84,2.45,11.71,4.87,17.57,7.29,.83,.34,1.62,.8,2.68,.67-.02-5.95-1.55-11.99-2.05-17.97-.09-.86,.29-1.29,1.43-.84,27.92,11.94,56.3,22.99,85.13,32.79,2.7,.67,5,2.56,3.66-1.86-1.04-4.64-2.78-9.22-3.42-13.9,.25-.85,2.2,.22,2.84,.3,23.51,8.62,47.48,16.06,71.68,22.74,2.64,.78,1.25-1.29,.84-2.75-1.37-3.6-2.76-7.2-4.12-10.81-.12-.53-.59-1.49,.18-1.69Z"/>M <path class="cls-2" d="M935.24,851.14c-2.12-2.39-4.14-4.89-6.04-7.5,.83-.64,2.54-3.69,3.55-2.16,.84,3.22,1.68,6.44,2.49,9.66Z"/><path class="cls-2" d="M952.52,866.65c-2.76-1.95-5.42-4.05-7.99-6.3,.95-.6,4.71-5.12,5.5-4.03,1.4,3.22,1.58,6.92,2.49,10.33Z"/><path class="cls-2" d="M960.79,930.65c-4.76,2-9.58,3.95-14.44,5.83-.08-2.2-.16-4.41-.24-6.61-.03-.55-.1-1.61-.88-1.51-3.92,2.5-7.37,5.68-11.09,8.47-2.92,2.41-1.66-2.81-1.98-4.3-.28-7.64-.61-15.29-.98-22.92-.04-.75-.17-1.5-.28-2.25-.02-.08-.18-.18-.29-.2-.24-.03-.59M -.09-.72,0-3.24,2.69-6.16,5.71-9.29,8.53-1.11,.98-2.3,2.03-2.38-.3-.85-8.25-.78-16.63-2.28-24.78-.06-.18-.52-.24-.65-.16-3.61,3.23-6.4,7.27-10.01,10.51-1.3,.43-1.05-2.83-1.24-3.64-.41-6.35-1.36-12.66-2.31-18.96-.02-.15-.34-.28-.56-.38-.45,0-.83,.55-1.13,.84-2.28,2.8-4.45,5.65-6.7,8.47-.57,.63-2.01,3.05-2.56,1.21-.81-6.21-1.49-12.45-2.76-18.6-.06-.3-.33-.58-.53-.85-.02-.04-.27-.03-.33,.03-2.95,3.03-4.98,6.89-7.58,10.23-1.31,1.71-1.89,1.96-2.36-.39-1-5.25-1.59-10.54-2.81-15.74-.44,.14-.93,.18-1.09,.39-2.6,3.75-5,7.63M -7.54,11.42-.27,.41-.63,.68-1.35,.53-.8-4.67-1.87-9.34-2.89-13.98-.11-.5-.23-1.04-.91-1.32-.75,.35-.98,.99-1.32,1.56-2.18,3.59-4.35,7.17-6.54,10.75-.23,.39-.54,.75-1.31,.72-1.62-4.28-1.71-8.93-3.56-13.15-.74-.61-1.59,1.47-2.02,1.94-2.05,3.4-4.06,6.81-6.1,10.2-.28,.46-.51,.99-1.24,1.16-.67-.46-.76-1.11-.93-1.74-.58-1.44-2.07-10.39-3.59-9.8-2.78,3.44-4.62,7.53-7.01,11.24-.29,.48-.54,.99-.91,1.44-.4,.48-.43,1.4-1.44,1.25-.69-.1-.67-.85-.85-1.36-1.22-2.82-1.68-6.41-3.55-8.81-.79,.48-1.07,1.1-1.41,1.68-2.15,3.59-4.3,7.1M 8-6.48,10.77-.47,.77-1.04,1.5-1.58,2.24-.06,.08-.26,.18-.34,.15-.2-.07-.48-.17-.55-.32-1.61-2.78-2.2-6.15-4.22-8.65-1.04,.6-1.35,1.46-1.85,2.21-2.6,3.89-5.16,7.81-7.75,11.7-.54,.67-.9,1.52-1.94,1.47-1.19-2.26-2.39-4.54-3.59-6.82-.22-.42-.55-.72-1.28-.85-3.6,4.9-6.96,9.93-10.85,14.69-.57,.5-1.24,1.89-2.12,1.49-1.04-1.21-1.44-2.78-2.32-4.1-.65-1.02-.68-2.35-2.19-2.95-1.19,.6-1.65,1.64-2.38,2.52-3.4,4.14-6.79,8.28-10.18,12.43-.36,.45-.71,.91-1.55,1.06-1.94-2.28-3.4-4.82-5.22-6.95-.09-.72,.36-1.01,.65-1.36,4.06-4.95,8.M 12-9.91,12.17-14.87,.7-.87,.65-1.2-.25-1.98-1.92-1.66-3.88-3.28-5.89-4.63-.91-.07-1.14,.37-1.4,.7-4.06,4.93-7.56,10.03-12.09,14.61-2.92-1.29-4.87-3.71-7.59-5.1-.99,0-1.29,.53-1.68,.93-4.69,4.53-8.83,9.72-13.9,13.81-2.02-1.13-6.33-4.13-7.78-5.41,4.66-4.74,9.24-9.56,13.94-14.25,.38-.34,1-.42,1.45-.15,2.53,1.53,4.88,3.06,7.48,4.5,4.37-4.36,8.24-9.07,11.9-13.93,1.04-1.31,1.39-1.37,2.78-.49,2.22,1.25,4.04,3.05,6.43,3.96,4.21-4.97,7.18-10.29,11.15-15.46,3.08,1.28,4.66,3.42,7.51,5.08,3.03-4.28,5.09-9.05,7.74-13.57,.79-1.3M 2,1.2-2.59,2.83-1.23,1.53,1.21,3.03,2.44,4.55,3.67,1.29,1.05,1.67,.97,2.48-.49,1.87-3.56,3.59-7.2,5.39-10.8,.6-1.07,.84-2.38,1.89-3.12,.86,.26,1.27,.84,1.76,1.34,1.55,1.63,3.09,3.26,4.63,4.89,.89,.54,1.36-.7,1.69-1.32,1.02-2.23,2.02-4.45,3.03-6.68,.87-1.92,1.72-3.85,2.59-5.77,.19-.43,.98-.56,1.3-.23,1.87,1.93,3.4,4.14,5.12,6.19,.28,.35,.55,.73,1.17,.74,.6-.47,.83-1.08,1.09-1.7,1.53-3.56,3.07-7.12,4.61-10.68,.31-.66,.68-1.89,1.62-1.24,2.23,2.63,3.82,5.81,6.19,8.25,.72-.28,.92-.8,1.13-1.28,1.42-3.25,2.8-6.52,4.22-9.7M 7,.31-.71,.67-1.4,1.07-2.08,.04-.07,.57-.09,.65,0,2.38,2.62,3.79,5.93,5.72,8.87,.23,.39,.54,.71,1.26,.74,1.85-3.64,3.39-7.47,5.08-11.18,.27-.6,.46-1.22,1.18-1.61,.59,.32,.87,.8,1.15,1.3,2,3.29,3.49,6.74,5.2,10.14,1.63,1.52,5.62-11.24,7.5-12.28,.08,.1,.17,.21,.24,.32,1.3,5.74,2.97,11.44,5.02,17.08-1.72,3.07-3.41,6.16-5.13,9.22-.57,.79-.83,1.87-2.02,1.84-6.78-19.62-3.21-16.56-12.73-.65-1.43-.99-1.41-2.71-2.09-4.18-.91-2.6-1.98-5.15-3.26-7.64-.08-.14-.39-.31-.54-.28-.23,.04-.5,.21-.6,.38-2.14,4.06-4.06,8.21-6.1,12.3-.M 22,.43-.54,.72-1.26,.65-1.54-3.16-2.92-6.49-4.67-9.58-.16-.26-.58-.42-1-.71-2.48,4.72-4.5,9.5-7.13,14.19-1.81-.82-2.1-3.25-3.24-4.79-.79-1.36-1.48-2.77-2.78-3.9-.11-.1-.6-.09-.65-.02-2.4,4.3-4.44,8.78-6.72,13.14-1.21,2.34-1.58,1-2.61-.47-1.11-1.85-2.44-3.6-3.89-5.28-.43-.55-1.27-.32-1.49,.25-2.54,4.74-4.69,9.7-7.69,14.19-.32-.04-.66,0-.8-.12-1.98-2.05-3.57-4.35-5.7-6.29-1.69,.78-1.97,2.73-3,4.14-2.37,3.72-4.16,7.86-6.92,11.29-.09,.1-.59,.09-.71-.01-2.09-1.74-3.78-4.2-6.27-5.34-4.18,5.06-7.26,10.83-11.39,15.96,1.84,M 2.23,3.62,4.37,5.4,6.51,.2,.26,.85,.28,1.06,.04,4.19-4.82,7.48-10.23,11.14-15.35,.18-.24,.87-.29,1.05-.06,1,1.27,2.02,2.53,2.98,3.82,.76,.68,1.31,3.11,2.56,2.28,3.08-4.09,5.54-8.62,8.36-12.89,.64-.74,1.35-3.18,2.57-1.95,1.45,2.3,2.81,4.61,4.04,7.04,.08,.14,.38,.31,.55,.29,.24-.01,.55-.16,.66-.32,.64-.94,1.27-1.9,1.84-2.87,1.96-3.43,3.9-6.86,5.84-10.29,.33-.58,.56-1.21,1.34-1.69,1.77,1.72,2.26,4.33,3.42,6.47,.37,.8,.74,1.61,1.12,2.42,.03,.07,.2,.16,.27,.15,1.12-.13,1.39-1.47,1.99-2.24,1.94-3.43,3.86-6.87,5.81-10.31,M .56-.74,.8-1.88,1.95-1.8,1.4,2.9,2.4,5.92,3.53,8.91,.25,.43,.44,1.18,1,1.3,.66-.21,1.02-1.29,1.43-1.82,2.29-3.97,4.19-8.22,6.7-12.05,.68,.18,.93,.54,1.07,.95,1.29,3.69,2.45,7.27,3.78,10.98,.42-.15,.93-.2,1.05-.39,1.03-1.76,1.97-3.54,2.96-5.31,1.37-2.46,2.75-4.91,4.15-7.35,.07-.11,.46-.13,.71-.15,.41,.13,.46,.76,.63,1.1,1.24,3.63,2.42,7.28,3.24,10.99,.12,.54,.27,1.06,.96,1.34,.77-.33,1-.98,1.33-1.55,1.94-3.32,3.86-6.64,5.79-9.96,.28-.48,.52-1,1.19-1.25,.77,.52,.89,1.28,1.07,2,1.18,4.53,2.07,9.13,3.51,13.59,.69,.44,1M .18-.6,1.55-1.03,1.95-3.08,3.87-6.16,5.82-9.24,.48-.61,.83-1.57,1.77-1.54,.06,0,.19,.12,.21,.2,.34,1.16,.68,2.31,.97,3.47,1.39,4.59,1.9,9.41,3.32,13.93,.85,.93,3.21-3.64,3.91-4.31,3.07,4.68,6.39,9.13,9.92,13.35l.03,.15s.06,0,.09,0c8.43,10.04,18.03,18.71,28.73,26.08,.29,2.58,.17,4.9,2.96,1.98,3.74,2.44,7.6,4.71,11.54,6.78,.43,5.21,.86,10.45,1.23,15.66,.02,.23,.77,.44,1,.29,4-2.66,7.63-5.82,11.7-8.41,.88-.32,1.13,.58,1.24,1.23,.45,3.77,.47,7.57,.7,11.35Z"/><path class="cls-2" d="M968.72,876.08c-.36-.16-.71-.32-1.06-.M 51,.02,0,.05-.02,.07-.04,.37-.21,.92,.13,.99,.55Z"/><path class="cls-2" d="M978.01,923.08c-.85,.39-1.71,.78-2.56,1.17-.05-.61-.11-1.23-.17-1.84,.91,.24,1.81,.46,2.73,.67Z"/><path class="cls-2" d="M990.88,1027.86s.02-.02,.03-.04h.02s-.03,.02-.05,.04Z"/><path class="cls-2" d="M993.11,983.16c.03,13.15-.52,26.28-1.25,39.41-.29,1.63,.15,3.97-.95,5.25-5.87,1.35-11.01,4.55-16.72,6.33-.83,.04-.74-.95-.72-1.53,.45-4.72,.99-9.44,1.45-14.16,.46-10.12,1.72-20.21,1.66-30.33-.01-.27-.6-.5-.92-.35-4.63,2.14-9.07,4.65-13.61,6.96-.M 45,.23-.92,.46-1.6,.1-.26-6.54,.64-13.13,.75-19.67,5.4-2.09,10.74-4.25,16.04-6.49,.36,22.79-4.45,19.13,10.92,13.12,1.17-.35,3.9-1.5,4.77-.24,.07,.53,.18,1.06,.18,1.6Z"/><path class="cls-2" d="M1040.89,980.13c.02,.64-.58,.93-1.35,.63-3.89-1.52-7.81-2.91-11.73-4.35-.77-.24-2.36-.97-2.6,.23,.06,6.79,.6,13.56,.66,20.35,.07,7.11,.06,14.22,.06,21.33,0,1.51-.06,3.01-.13,4.52,.05,.76-.86,1.01-1.67,1.08-4.42,.37-8.84,.76-13.26,1.12-.68,0-1.76,.19-2.14-.48,.17-14.52,.72-29.08,.29-43.62-.18-1.18,.5-3.33-1.45-3.1-4.35,.59-8.64M ,1.65-12.96,2.44-2.41,.31-1.26-2.9-1.55-4.31-.09-4.7-.13-9.4-.26-14.1,5.06-2.3,10.07-4.67,15.03-7.1,.51,6.62,.91,13.25,1.06,19.88,0,.85-.01,1.74,.43,2.5,2.37,.24,8.73-1.18,14.03-1.54,.5-.03,.99-.28,1.6-.46,0-9.39-1.15-18.76-1.92-28.12,4.73-2.49,9.42-5.04,14.04-7.66,1.42,13.57,3.25,27.11,3.82,40.76Z"/><path class="cls-2" d="M1042.99,839.46c.02,.06,.04,.11,.05,.17-.04-.02-.09-.03-.13-.05l.08-.12Z"/><path class="cls-2" d="M1052.44,943.15c-.22,.77-1.53,0-2.04-.11-3.85-1.55-7.64-3.2-11.5-4.71,4.01-2.28,7.97-4.6,11.9-6.9M 7,.43,3.94,1.57,7.83,1.64,11.79Z"/><path class="cls-2" d="M1086.37,834.06v.03s-.01-.02-.01-.03h.01Z"/><path class="cls-2" d="M1211.59,762.83l-.03,.03-.03-.03h.06Z"/><path class="cls-2" d="M1097.14,776.83c6.2,3.59,12.15,7.62,18.11,11.54,.18-3.31,.19-6.64,.03-9.98-1.34-2.99-2.79-5.95-4.04-8.98,0-.16,.44-.35,.61-.25,.92,.57,1.87,1.13,2.79,1.71-.78-6.39-2.17-12.77-4.22-19.08-3.42-2.17-6.79-4.39-10.34-6.37-.09-.05-.35-.04-.37,0-.53,.89,.51,1.83,.78,2.7,2.76,5.49,5.54,10.98,8.3,16.47,.35,.7,.64,1.42,.93,2.13,.03,.06-.11,M .19-.21,.24-.69,.16-1.39-.57-2.01-.82-6.69-4.18-13.37-8.36-20.31-12.27-1.92-.93-3.87-2.47-2.11,.96,2.82,5.59,5.67,11.17,8.5,16.76,.35,1.14,1.79,2.52,.7,3.59-6.84-4.44-14.12-8.67-21.63-12.13-.43,.04-.24,.8-.14,1.07,2.97,6.09,5.97,12.18,8.96,18.27,.41,1.21,1.76,2.6,.82,3.84,.05-.07,.12-.14,.21-.25-.11,.15-.17,.23-.24,.33-.01,0-.01-.01-.02-.02-5.31-3.62-11.31-6.18-16.99-9.18-.73-.32-2.73-1.58-2.56-.07,3.84,7.88,7.24,15.96,10.7,24,.18,.4,.27,.81-.2,1.26-5.96-2.82-11.49-6.44-17.52-9.14-.36-.15-.67,.29-.65,.57,3.5,9.39,7M .53,18.58,11,27.99,.15,.41,.33,.82,0,1.32-5.69-2.04-10.83-5.66-16.56-7.72-.19-.07-.52,.17-.51,.34,1.43,4.73,3.44,9.27,5.03,13.94,7.26,23.26,10.37,18.24-10.94,10.03,3.39,11,7.11,21.95,9.76,33.13-.32,1.27-2.51-.39-3.33-.55-3.35-1.39-6.68-2.79-10.04-4.15-.55-.23-1.13-.56-1.97-.3,.73,4.75,2.47,9.39,3.4,14.12,4.46-1.27,8.89-2.87,13.26-4.8-1.25-3.71,.63-2.38,2.86-1.32,3.5-1.66,6.86-3.51,10.07-5.53-1.93-6.72-3.88-13.44-6.12-20.11-.17-.51-.18-1.06-.24-1.59-.01-.09,.09-.26,.17-.28,.23-.05,.55-.13,.72-.05,5.34,2.4,10.19,5.71M ,15.51,8.13,1.15,.31,.3-1.6,.23-2.15-3.08-9.37-6.22-18.73-9.7-28.01-.09-.45-.52-1.22-.17-1.54,1-.28,1.86,.62,2.72,.98,4.24,2.48,8.48,4.96,12.72,7.44,1,.47,2.03,1.63,3.2,1.11,0,0,.03-.01,.04-.02,.07-.03,.15-.05,.22-.08-.75-.77-.92-1.75-1.25-2.65-2.95-8.28-6.14-16.5-9.43-24.7-1.77-4.11-.27-2.76,2.44-1.33,5.73,3.41,11.05,7.34,16.91,10.49,.1-.17,.31-.36,.27-.49-.3-.94-.62-1.87-.98-2.79-3.06-7.81-6.23-15.58-9.65-23.29-.88-2,.02-1.77,1.51-1,6.94,3.74,13.23,8.1,19.7,12.33,.09,.06,.35,.08,.38,.04,.11-.17,.29-.39,.23-.54-2.M 78-6.89-6.04-13.58-9.01-20.39-.36-.81-.71-1.62-1-2.45-.06-.14,.16-.36,.29-.52,.03-.04,.27,0,.38,.06Zm-2.82-1.6s-.03-.02-.04-.04l.22-.12-.18,.16Zm67.13,10.56c-1.63-3.88-3.28-7.76-4.91-11.64,.23,3.51,.32,7.02,.28,10.52,1.63,1.01,7.29,6.8,4.63,1.12Zm225.89,110.75c-21.73-23.76-44.18-46.88-67.41-69.26-2.43-2.35-1.91,.44-1.72,2.14,.6,5.15,1.21,10.29,1.79,15.43,.01,.14-.27,.31-.44,.43-.57,.08-1.06-.63-1.49-.94-7.95-8.02-16.01-15.96-24.2-23.82-11.09-10.23-21.93-21.41-33.71-30.79-.83,.37-.3,1.34-.27,2.02,.91,4.13,1.85,8.26,M 2.75,12.4,.09,1.3,1.01,2.98-.15,4.01-16.1-15.98-33.64-30.38-50.93-45.3-.9,.9-.09,2.05,.15,3.05,1.81,5.28,3.63,10.56,5.43,15.85,.36,1.02,.79,2.01,.2,3.03-13.46-11.94-27.67-23.25-41.95-34.3-.57-.44-1.07-.99-1.95-1.07-.41,.52-.17,1.02,.04,1.53,2.45,5.93,4.89,11.86,7.32,17.79,.1,.44,.58,1.19,.25,1.53-.88,.32-1.49-.62-2.16-1-8.47-6.8-17.34-13.3-26.1-19.83,1.47,6.05,2.53,12.15,3.19,18.24,11.8,8.57,22.76,18.41,34.18,26.99,.14-.13,.35-.33,.31-.46-.2-.74-.44-1.47-.72-2.19-2.1-5.55-4.21-11.11-6.31-16.67-.27-.88-.98-1.87-.22-M 2.71,11.28,9.37,22.63,18.71,33.41,28.46,2.51,2.26,5.03,4.5,7.56,6.73,.32,.21,.9,.67,1.27,.47,.03-.31,.13-.64,.03-.93-1.96-6.15-3.95-12.3-5.91-18.45-.17-.51-.21-1.05-.28-1.58-.01-.09,.07-.23,.17-.28,.45-.14,.97,.33,1.31,.55,15.08,13.24,29.93,26.87,44.17,40.78,1.02,1,2.05,2,3.1,2.97,.16,.08,.85,.13,.81-.27-1.27-6.93-3.45-13.7-4.66-20.62,.05-.18,.47-.27,.61-.15,2.32,2.09,4.7,4.14,6.93,6.29,16.5,15.92,32.69,32.03,48.19,48.59,.59,.47,1.18,1.44,1.92,1.52,.19-.11,.51-.28,.49-.4-.54-6.11-1.42-12.2-1.78-18.33,.04-.15,.51-.2M 7,.63-.2,.65,.54,1.34,1.05,1.91,1.64,21.78,22.1,42.8,45.14,63.44,68.13,.26,.23,.91,.12,.86-.25-.02-6.88-.04-13.77-.06-20.77Zm-204.28-123.8s-.05,.01-.07,.01c.06-.05,.12-.1,.19-.15l.03,.03c-.05,.03-.1,.07-.15,.11Zm34.33,12.1s.03,0,.04-.01c.01,.02,.02,.05,.03,.08l-.07-.07Zm45.16,23.4s-.04-.05-.05-.07l.13-.07-.08,.14Z"/><path class="cls-2" d="M1095.46,449.73l.12,.03v-.12l-.12,.09Z"/><path class="cls-2" d="M1387.26,543.4c.4-2.35-1.87-2.91-3.6-3.69-35.69-15.38-71.58-30.29-108.61-42.71-.96,.1-.66,1.23-.7,1.89,.36,3.33,.78M ,6.65,1.15,9.97,.25,2.25,.44,4.5,.65,6.75,.03,.25-.6,.58-.88,.48-30.88-11.42-62.21-21.91-94.01-30.84-1.33-6.02-2.44-12.11-4.07-18.07-26.79-7.31-54.23-12.52-81.61-17.42,.35,4.81,2.6,9.35,3.8,14.01,.47,1.6,.26,2.24-1.61,1.87-22.16-4.02-44.45-7.28-66.87-9.42,1.77,4.14,3.56,8.27,5.32,12.4,.23,.7,.74,1.73-.33,1.95-6.17-.42-12.3-1.25-18.46-1.76-9.9-.93-19.86-1.47-29.8-1.97-2.55-.13-5.12-.14-7.67-.2-1.85,.24,.19,2.35,.47,3.24,9.06,3.58,17.99,7.34,26.79,11.27h.01c12.11,.83,24.13,3.01,36.17,3.92-1.35-4.81-4.45-8.98-5.8-13.7M 3,.77-.36,1.45-.3,2.11-.21,6.65,.84,13.29,1.74,19.9,2.77,14.54,2.27,28.95,4.99,43.31,7.86,.64,.06,1.77,.45,2.15-.22-.88-4.46-2.86-8.73-4.14-13.12-.26-.84-.86-2.03,.64-1.98,26.85,4.89,53.42,11.33,79.62,18.84,1.34,5.46,2.69,10.94,3.93,16.43,.1,.43,.1,.85-.41,1.27-25.71-7.45-51.52-14.89-77.82-20.26-1.32,.02-.61,1.36-.45,2.12,1.37,4.26,3.09,8.45,4.29,12.77-.2,1.11-1.96,.33-2.72,.29-19.69-4.64-39.55-8.58-59.56-11.8-2.84-.37-5.1-.97-3.34,2.19,1.35,2.81,2.65,5.64,3.96,8.46,.15,.69,1.54,2.63,.54,2.89-1.92-.05-3.78-.4-5.67-M .68,2.85,1.49,5.68,3.01,8.49,4.54-.57-1.28-2.38-3.74,.47-3.06,21.67,3.86,43.07,8.94,64.34,14.41-1.73-4.68-3.46-9.36-5.18-14.03-.21-.72-.51-1.29,.21-1.87,26.34,6.19,52.08,14.24,77.75,22.41-1.34-4.08-2.09-8.37-3.19-12.54-.33-1.37-.59-2.75-.86-4.13-.09-.45,.49-.87,1-.74,28.25,8.44,55.73,18.56,83.1,29.23,2.56,.97,5.04,2.1,7.63,2.95,.84,.18,1.02-.38,.98-1.01-.65-5.79-1.61-11.55-2-17.36,.31-1.62,3,.27,4,.42,35.8,13.53,70.89,28.91,105.58,44.71,.31,.11,.87-.17,.9-.44,.32-6.33,.01-12.7,.1-19.05Z"/><path class="cls-2" d="M10M 95.46,449.73l.12,.03v-.12l-.12,.09Z"/><path class="cls-2" d="M1190.02,521.36s.03,.07,.04,.1l.14-.05c-.06-.02-.12-.04-.18-.05Z"/><path class="cls-2" d="M1177.17,467.11s.01,.05,.02,.07c.02,0,.03,.01,.05,.01l-.07-.08Z"/><path class="cls-2" d="M1117.24,514.85c.02,.06,.04,.11,.06,.17l.1-.13c-.05,0-.11-.03-.16-.04Z"/><path class="cls-2" d="M1095.46,449.73l.12,.03v-.12l-.12,.09Z"/><path class="cls-2" d="M1030.85,456.1l-.1,.1c.05,.01,.1,.01,.15,.02-.02-.04-.03-.08-.05-.12Z"/><path class="cls-2" d="M964.56,514.34c6.08,.33,1M 2.16,.77,18.23,1.34-9.62-4.15-19.41-8.08-29.37-11.78,2.36,3.02,4.7,6.08,6.91,9.21,.25,.35-.23,.91-.76,.88-7.8-.43-15.62-.3-23.44-.32-5.2,.17-10.53-.24-15.67,.54-.77,.48,.31,1.41,.64,1.92,2.14,2.59,4.91,4.8,6.7,7.63,.04,.69-.95,.69-1.46,.72-7.27,.13-14.55,.39-21.79,.95-3.66,.43-7.6,.19-11.09,1.37-.02,.86,.84,1.3,1.39,1.88,1.34,1.3,7.57,6.2,6.84,6.94-1.44,.78-3.12,.51-4.69,.68-2.27,.25-4.55,.43-6.81,.71-5.19,.65-10.37,1.32-15.56,2.01-.6,.2-2.84,.26-2.18,1.25,2.97,2.32,6.04,4.57,8.92,7.01,.09,.08-.02,.5-.13,.53-8.42,1M .69-16.87,2.7-25.2,4.82,.18,.37,.22,.73,.46,.91,2.94,2.05,5.94,4.04,8.89,6.1,.55,.9-1.26,.98-1.81,1.19-6.45,1.67-12.95,2.96-19.34,4.85,.09,.32,.06,.72,.29,.87,1.36,.88,2.78,1.71,4.18,2.55,1.51,.9,3.03,1.8,4.54,2.7,.44,.26,.82,.55,.88,1.15-5.73,1.77-11.47,3.6-17.19,5.38-.62,.2-1.23,.4-1.48,1.06,16.64,9.5,12.19,3.6-5.14,12.76,.04,1.1,1.41,1.21,2.18,1.75,14.26,7.13,8.82,2.3-4.33,12.22-.71,.18-1.16-.04-1.64-.24-3.11-1.29-6.24-2.55-9.34-3.84-.35-.14-.61-.41-.89-.63-.06-.05-.06-.21,0-.27,3.77-3.17,8.4-5.28,12.25-8.36,.29M -.82-1.22-1.11-1.75-1.48-2.47-1.1-4.96-2.18-7.44-3.26-.49-.21-.89-.48-1.05-1.02,4.52-3.1,9.89-5.27,14.98-7.47,.47-.2,.5-.82,.04-1.06-2.84-1.45-5.69-2.9-8.54-4.31-1.42-.72-1.46-1.21-.06-1.79,1.9-.79,3.82-1.58,5.79-2.28,3.69-1.3,7.46-2.47,11.16-3.76,.56-.2,.71-.73,.29-1-2.44-1.56-5.03-2.9-7.52-4.37-2.94-1.62-1.91-1.8,.61-2.65,5.24-1.71,10.6-3.15,15.98-4.54,4.71-1.14,3.94-1.12,.36-3.56-1.96-1.31-3.94-2.6-5.9-3.92-.64-.44-.47-.88,.4-1.15,6.11-1.75,12.33-3.09,18.61-4.28,2-.45,4.22-.5,6.06-1.42-.1-.7-.63-1.05-1.1-1.42-2.M 31-1.81-4.64-3.61-6.95-5.42-.4-.31-.68-.66-.42-1.22,9.49-2.31,19.69-3.38,29.35-4.82,.18-.68-.14-1.02-.49-1.35-2.4-2.45-5.31-4.52-7.4-7.22-.06-.61,.86-.8,1.36-.89,7.05-.87,14.15-1.6,21.22-2.25,3.87-.5,7.79-.43,11.66-.86,1.23-.45-.04-1.53-.45-2.15-2.2-2.45-4.61-4.72-6.65-7.3-.18-.23,.13-.68,.52-.72,12.68-1.45,25.46-1.14,38.19-1.42-10.17-3.7-20.5-7.17-31-10.4-5.39,.52-10.84,.61-16.18,1.51-.34,.06-.57,.54-.37,.79,2.34,2.9,4.75,5.75,7.15,8.61,.32,.39,0,.89-.56,.95-11.45,1.44-23.29,1.85-34.43,4.75-.16,1.72,9.05,7.77,7.62M ,8.79-9.15,1.82-18.41,3.14-27.44,5.36-.88,.2-1.83,.29-2.44,.92,.09,.6,.67,.93,1.13,1.31,2.08,1.68,4.18,3.36,6.26,5.04,.38,.4,1.38,.97,.9,1.54-8.56,2.16-17.29,3.94-25.58,6.81-.07,.54,.28,.85,.7,1.12,1.87,1.23,3.75,2.46,5.61,3.7,.53,.55,3.45,1.77,2.34,2.54-6.91,2.09-13.83,4.2-20.57,6.68-1.32,.5-1.45,.96-.4,1.58,2.84,1.65,5.71,3.23,8.53,4.91,.3,.17,.24,.65-.09,.8-4.83,1.88-9.71,3.7-14.46,5.75-.88,.6-5.36,1.94-2.87,3.04,2.81,1.47,5.77,2.72,8.48,4.38,.47,.72-.8,1-1.26,1.33-4.32,2.2-8.44,4.63-12.46,7.17-.53,.3-1.51,1.02-M .61,1.45,3.11,1.43,6.41,2.63,9.44,4.2,.12,.58-.37,.82-.73,1.17-3.88,2.67-7.79,5.32-11.68,7.97-.43,.3-.95,.56-1.46,.37-3.31-1.18-6.6-2.41-9.89-3.63-.32-.11-.4-.65-.14-.86,4.04-3.35,8.41-6.35,12.73-9.33-.06-.19-.04-.32-.11-.36-3.11-1.71-6.72-2.7-9.87-4.29-.09-.53,.2-.86,.64-1.13,2.55-1.6,5.07-3.21,7.65-4.78,2.14-1.3,4.35-2.54,6.52-3.81,.49-.29,.51-.82,.04-1.05-2.9-1.58-6.12-2.63-8.91-4.41-.13-.1-.2-.44-.1-.52,4.55-2.98,9.5-5.27,14.61-7.46,.68-.46,4.21-1.27,3.24-2.27-1.96-1.35-4.11-2.44-6.18-3.63-3.63-2.02-3.44-1.95,.M 44-3.45,6.36-2.43,12.77-4.61,19.2-6.92-.6-1.66-2.79-2.31-4.08-3.47-1.46-1.2-3.45-2-4.5-3.57,.66-.68,1.6-.84,2.45-1.12,6.47-2.14,13.06-4.03,19.69-5.83,.75-.4,4.41-.63,3.66-1.79-1.99-1.78-4.09-3.42-6.14-5.13-2.31-1.91-2.56-2.19,.79-3.03,9.12-2.57,18.68-4.05,27.85-6.44,.21-1.5-9.07-8.14-7.27-8.85,11.37-3,23.33-4.05,34.98-5.94,.21-.57-.03-.94-.33-1.31-1.87-2.35-3.75-4.7-5.6-7.06h0c-1.68-.45-3.37-.89-5.05-1.33h0c-10.86,1.64-21.56,3.73-32.19,6.27-.53,.12-.78,.68-.46,1.04,1.24,1.41,2.49,2.81,3.74,4.21,1.02,1.14,2.06,2.26,M 3.08,3.4,.24,.27,.09,.69-.25,.81-9.88,2.81-20.12,4.6-29.8,8.04-.28,.13-.4,.64-.17,.85,.86,1.09,8.53,6.59,7.22,7.32-8.51,2.96-17.35,5.12-25.55,8.74-1.59,1.1,8.04,5.65,7.94,7.1-.83,.76-2.06,1-3.15,1.39-6.58,2.54-13.23,4.7-19.28,8.26,2.61,2.26,6.1,3.58,8.74,5.63,0,.56-.41,.81-.87,1.03-5.57,2.64-10.87,5.6-16.06,8.69-1.5,.89-1.46,1.25,.2,2.06,2.48,1.28,5.15,2.29,7.51,3.77,.13,.1,.13,.46,.02,.56-3.12,2.27-6.58,4.1-9.8,6.22-1.68,1.08-3.27,2.24-4.89,3.38-.38,.26-.78,.56-.52,1.15,2.92,1.19,5.96,2.44,8.88,3.67,.29,.12,.47,.4M 3,.77,.73-4.37,3.36-8.91,6.54-13.02,10.12,.12,.56,.51,.81,1.01,.99,2.46,.88,4.92,1.75,7.37,2.64,.51,.28,1.68,.47,1.54,1.19-3.43,3.32-7.35,6.29-10.56,9.75-.36,.38-.23,.88,.32,1.05,3.61,.92,7.06,2.63,10.74,3.04,3.87-3.26,7.56-7.07,11.78-9.88,2.45,.48,4.73,1.71,7.09,2.53,1.42,.57,3.02,.88,4.17,1.84-.46,1.48-2.23,2.06-3.35,3.08-2.64,2.16-5.57,4.29-7.74,6.86,3.98,1.12,7.73,2.63,11.46,4.05,.02,.7-.42,1.1-.85,1.52-2.72,2.74-5.69,5.35-8.17,8.29,.42,.59,1.01,.81,1.64,1.03,3.08,1.08,6.14,2.18,9.21,3.27,.53,.19,.87,.47,.98,1-M 9.66,13.9-3.13,10.08-18.66,6.56-.78,.31-1.07,.8-1.31,1.3-1.14,2.3-2.26,4.6-3.37,6.91-.63,.97-.63,2.74-2.06,2.87-3.72-.57-7.38-2.01-11.11-2.55-.83,.45-1.02,1.1-1.23,1.7-1.21,3.54-2.38,7.05-3.48,10.61,3.89,.78,7.66,1.89,11.69,2.54,2.03-3.92,2.69-7.84,4.85-11.69,3.96,.48,7.57,2.19,11.4,3.21,.2,.07,.3,.33,.52,.58-1.72,3.55-2.61,7.43-4.57,10.88-.36,.52-1.21,.13-1.82-.04-1.78-.5-3.53-1.03-5.32-1.5-1.27-.34-2.57-.61-3.86-.88-.49-.11-1.15,.2-1.27,.59-1.31,3.93-1.96,8.05-3.58,11.87,3.82,.37,7.48,1.68,11.23,2.47,.31,.07,.92-M .17,1-.39,5.12-14.77,.59-12.02,15.5-7.95,.91-.41,1.01-1.1,1.27-1.69,1.51-3.08,2.39-6.5,4.33-9.34-3.9-1.43-7.81-2.85-11.71-4.3-.4-.15-.49-.47-.48-.81,1.44-3.35,3.34-6.56,4.96-9.86,.09-.19,.33-.33,.6-.57,4.03,.79,7.79,2.93,11.76,3.96,.75,.07,1.38-.49,1.71-1.12,1.85-2.62,3.69-5.24,5.54-7.86,.41-.58,.29-.98-.5-1.31-3.44-1.45-6.95-2.83-10.41-4.26-.31-.13-.49-.45-.79-.74,2.77-3.24,6.02-6.08,9.4-8.84,4.15,.95,7.86,3.36,11.83,4.9,1.41,.88-.81,1.83-1.35,2.53-2.31,2.18-4.87,4.23-6.99,6.56,.28,.67,.88,.91,1.47,1.17,2.93,1.33,M 5.85,2.66,8.76,4,.62,.41,2.33,.83,1.72,1.78-2.36,3-4.71,6.01-7.08,9.01,4.48,1.94,8.77,4.16,13.06,6.36,2.44-2.61,4.61-5.47,6.94-8.19,.4-.42,.63-1.09,0-1.42-3.76-2.12-7.62-4.04-11.44-6.07-.88-.63,.26-1.38,.7-1.89,2.07-1.84,4.16-3.67,6.24-5.5,.4-.52,1.76-1.11,1.13-1.81-3.38-2.01-7.05-3.57-10.55-5.37-.48-.23-.88-.48-.93-1.06,2.07-1.76,4.26-3.5,6.8-4.93,.7-.65,4.71-1.9,3.35-2.99-2.95-1.75-6.11-3.14-9.16-4.72-.56-.43-2.46-.83-1.73-1.75,3.03-1.8,6.25-3.36,9.63-4.71,1.18-.47,2.54-.7,3.53-1.66-3.49-2.55-7.87-4.08-11.54-6.39M ,.43-.99,1.62-1.07,2.53-1.52,3.96-1.35,7.93-2.69,11.9-4.02,.6-.21,1.23-.38,1.53-.92-3.15-2.55-7.35-3.89-10.64-6.34-.28-.75,.98-.87,1.48-1.13,5.46-1.8,11.19-3.04,16.75-4.6-.1-.56-.44-.87-.89-1.13-1.73-1.02-3.48-2.03-5.21-3.06-1.43-1.07-3.56-1.59-4.38-3.23,6.65-1.91,13.5-3.18,20.35-4.28,.47-.07,1.48-.48,1.01-1.05-3.11-2.19-6.31-4.34-9.38-6.6-.24-.59,.7-.85,1.17-.95,7.6-1.42,15.31-2.41,23.03-3.36,.63-.1,.81-.59,.36-.95-2.59-2.05-5.18-4.09-7.76-6.14-2.17-1.64-.72-1.56,1.06-1.98,5.75-.53,11.47-1.3,17.26-1.55,3.08-.19,6.M 18-.28,9.25-.62,.28-.04,.45-.6,.25-.81-1.82-1.91-3.9-3.55-5.86-5.33-.81-.72-1.62-1.44-2.42-2.17-.27-.25-.48-.55-.21-.87,10.85-1.7,22.26-.75,33.31-1.23,.3-.02,.62-.56,.44-.77-2.4-3.14-5.62-5.71-7.88-8.92-.05-.15,.18-.48,.33-.5,.78-.12,1.58-.24,2.38-.23,12.37-.11,24.72,.51,37.03,1.35,.28-.53,.08-.92-.2-1.29-1.11-1.47-2.23-2.94-3.36-4.41-1.21-1.55-2.44-3.1-3.61-4.67-.18-.24-.12-.6-.18-1.03,.89-.01,1.69-.07,2.48-.03Zm-125.56,98.2c-3.56,2.65-7.03,5.31-10.62,7.95-3.79-1.41-7.41-3.01-11.13-4.45-.38-.19-.66-.29-.83-.74,3.3M 9-3.29,7.25-5.89,11.34-8.86,3.97,1.64,7.59,3.24,11.11,4.99,.45,.22,.51,.82,.13,1.11Z"/><path class="cls-2" d="M885.35,472.92l-.15,.1c.06-.01,.12-.03,.18-.04l-.03-.06Z"/><path class="cls-2" d="M849.66,657.14l-.09,.09,.14-.06s-.03-.02-.05-.03Z"/><path class="cls-2" d="M803.51,611.25l.15,.16s.05-.06,.08-.09c-.08-.03-.15-.05-.23-.07Z"/><path class="cls-2" d="M478.42,742.32c-1.07,.02-2.14,.06-3.21,.09-.31,.01-.73,.51-.59,.7,.92,1.33,2.01,2.51,3.09,3.73,2.61-1.43,5.14-2.97,7.58-4.61-2.29,.05-4.58,.05-6.87,.09Zm33.56-26.2M c-.18-.2-.84-.23-1.1-.06-2.43,1.54-4.83,3.09-7.27,4.61-.97,.67-2.75,1.94-3.54,.38-4-5.31-8.21-10.48-11.96-15.96-3.76,1.21-7.88,.89-11.86,1.49-.38,1.35,1.01,2.35,1.63,3.46,2.92,3.98,5.88,7.95,8.81,11.92,.41,.75,1.49,1.44,.99,2.34-3.83,.46-7.73,.55-11.58,.84-.35,.03-.63,.47-.46,.73,3.67,5.15,8.04,9.79,11.8,14.88,3.12-2.19,6.1-4.55,8.91-7.06-2.02-2.41-4.04-4.83-6.06-7.25-.44-.53-.97-1.03-1.06-1.71,.35-.55,1.06-.64,1.68-.7,2.95-.28,5.83-.82,8.68-1.47,2.27-.64,3.12,2.21,4.54,3.43,2.84-3.13,5.47-6.42,7.87-9.85l-.02-.02ZmM 129.78-9.23c-14.15-3.53-9.51-6.94-13.04,8.74-.01,.6-.64,1.11-1.28,.89-3.02-1.16-6.05-2.3-9.02-3.59-1.14-.38-1.45,.96-1.63,1.77-.63,2.75-1.22,5.51-1.86,8.26-.16,.72-.23,1.5-1.01,2.03-.89,.07-1.54-.37-2.21-.7-2.65-1.28-5.27-2.6-7.9-3.91-.32-.16-.87-.01-1,.27-1.41,3.32-1.98,6.93-3.27,10.31-.19,.54-1,.71-1.6,.31-2.9-1.89-5.6-4.02-8.37-6.08-.49-.36-.92-.8-1.64-.88-.65,.28-.84,.78-1.04,1.3-1.19,2.97-2.12,6.05-3.64,8.88-.82,.74-1.87-.48-2.57-.92-3.08-2.39-5.9-5.09-9.13-7.28-.14-.08-.6-.02-.67,.09-1.65,2.55-2.85,5.33-4.33,M 7.98-.31,.58-.57,1.2-1.25,1.59-.76-.03-1.2-.46-1.64-.86-3.15-2.83-6.27-5.68-9.35-8.58-1.99,3.61-4.13,7.14-6.42,10.57,3.3,3.01,6.69,5.92,10.06,8.87,1.37,1.02,1.98-1.23,2.71-2.01,1.46-2.24,2.9-4.6,4.37-6.8,.74-.28,1.11,.08,1.46,.36,3.65,2.77,7.02,6.07,10.95,8.41,.7-.4,.96-.89,1.2-1.39,1.55-2.81,2.48-6.03,4.41-8.58,.37,.07,.57,.07,.84,.23,3.65,2.52,7.3,5.06,10.94,7.59-.99,3.34-2.88,6.65-4.19,9.98-.09,.19-.24,.4-.44,.53-.69,.52-1.4-.18-2-.5-2.86-1.96-5.71-3.93-8.56-5.9-1.78-1.46-2.29-.73-3.25,.95-1.45,2.31-2.89,4.61-4.M 34,6.91-.24,.37-.99,.46-1.4,.19-4.07-2.71-7.65-6.12-11.71-8.82-2.78,2.29-4.04,5.35-6.79,7.69-.37,.33-.75,.61-1.51,.62-3.41-2.71-6.64-5.63-9.84-8.61-2.47,3.1-5.07,6.1-7.81,9,1.98,1.75,3.96,3.49,5.94,5.24,.91,.59,1.84,2.14,3.07,1.54-3.02,2.47-6.96,3.63-10.59,5.08-.78,.27-1.36,.23-1.83-.18-1.51-1.29-2.99-2.6-4.45-3.94-2.81,2.55-5.73,5.01-8.76,7.36,.99,.9-1.04,1.01-1.61,1.23-2.53,1.9-5.13,3.72-7.8,5.46,3.29,3.22,6.84,6.2,9.96,9.57,.08,.09-.09,.46-.24,.5-3.63,.92-7.41,1.03-11.16,1.35-2.14,.28-4.78-.32-1.88,2.3,15.59,14.M 81,17.16,10.92-4.31,12.74-.78,.57,.84,1.55,1.23,2.06,2.87,2.57,5.83,5.06,8.68,7.66,.36,.33,.44,.75,.19,.86-6.34,.88-12.89-.05-19.35-.24,.1,.41,.06,.78,.26,1,2.87,2.89,6.08,5.48,9.08,8.24,.38,.42,1.37,1.11,.55,1.53-6.84,.03-13.71-.72-20.46-1.65-1.21-.11-2.83-.33-1.34,1.24,2.58,2.48,5.18,4.95,7.77,7.44,.51,.49,.97,1.01,1.44,1.53,.05,.07,.01,.23-.04,.32-2.92,.52-6.13-.42-9.07-.7-5.57-.78-11.1-1.73-16.65-2.6-.28-.01-.86-.07-.96,.26,.12,.3,.2,.63,.43,.87,2.56,2.64,5.15,5.26,7.71,7.89,.49,.51,.89,1.07,1.32,1.61,.06,.08,.M 07,.28,.01,.31-.57,.38-1.24,.15-1.85,.04-8.7-1.45-17.33-3.13-25.87-5.11-.9-.1-2.35-.64-3.11-.35-.07,.18-.17,.43-.07,.55,2.56,3.04,5.16,6.06,7.74,9.08,.45,.53,1.05,.99,1.13,1.68-.62,.38-1.24,.16-1.87,.03-9.62-2.06-19.14-4.39-28.53-7.07-2.12-.44-4.01-1.59-6.22-1.32,2.47,4.15,6.23,7.72,8.45,11.81-.17,.13-.44,.33-.6,.3-1.55-.34-3.12-.67-4.64-1.09-11.45-3.19-22.77-6.63-33.91-10.45-1.01-.2-2.49-1.19-3.34-.41,2.3,3.9,5.01,7.59,7.44,11.43,.17,.35,.53,.85,.35,1.19-.2,.1-.51,.27-.67,.21-15.54-4.9-31.03-10.36-46.03-16.53-.82-M .26-1.67-.94-2.54-.51-.32,.41,.42,1.32,.56,1.79,1.88,3.57,3.78,7.14,5.67,10.71,.25,.48,.49,.96,.3,1.5-2.05,.16-3.92-1.18-5.85-1.74-6.1-2.37-12.16-4.8-18.18-7.29,10.28,8.53,21.01,16.76,32.15,24.66,.1-.03,.25-.15,.23-.19-1.39-4.31-4.22-8.11-6.17-12.22-.19-.48-.6-1.02-.4-1.51,.13-.25,.35-.33,.65-.23,2.59,.92,5.18,1.81,7.75,2.74,12.66,4.54,25.54,8.64,38.61,12.36,1.72,.28,4.88,1.99,2.71-1.15-2.3-3.53-4.83-6.94-6.99-10.55-.07-.15,.08-.4,.18-.58,13.87,3.43,27.82,8.13,42.06,11,.23,.06,.61,.06,.77-.06,.09-.16,.2-.39,.12-.51M -2.66-3.61-5.55-7.1-8.07-10.81-.08-.12,.07-.36,.17-.53,.67-.29,1.6,.12,2.32,.2,7.69,1.97,15.46,3.73,23.31,5.24,3.53,.69,7.09,1.28,10.63,1.9,1.03-.26-.35-1.38-.61-1.85-2.27-2.54-4.57-5.07-6.84-7.61-.22-.44-1.7-1.64-.66-1.84,9.34,1.43,18.67,3.24,28.09,4.41,1.02,.16,2.08,.36,3.13,.07,.16-.44-.11-.78-.44-1.1-2.29-2.24-4.6-4.48-6.89-6.72-.68-.67-1.32-1.35-1.97-2.04-.18-1.09,2.71-.37,3.4-.38,7.4,1.08,14.88,1.67,22.35,2.35,.87,.08,1.41-.05,1.34-.32-.07-.29-.18-.63-.42-.84-1.68-1.54-3.41-3.04-5.1-4.56-1.33-1.21-2.65-2.42-3M .93-3.67-.19-.19-.16-.53-.2-.81,7.44-.22,14.99,.96,22.45,.67,.23-.12,.68-.41,.43-.7-2.82-2.65-5.93-5-8.87-7.51-1.99-1.68-1.53-2.06,.89-1.98,5.76,.13,11.59,.17,17.34-.34,.68-.52-.37-1.15-.75-1.55-2.63-2.16-5.28-4.3-7.92-6.46-.59-.65-1.86-1.09-1.63-2.1,5.56-.71,11.27-.5,16.79-1.54,.36-.87-.69-1.29-1.21-1.85-2.92-2.39-5.87-4.75-8.79-7.14-.4-.39-1.34-1.09-.69-1.58,4.48-.73,8.97-1.47,13.43-2.27,.78-.14,.93-.7,.33-1.22-4.37-3.85-9.04-7.33-13.22-11.38,.41-.28,.66-.59,1-.66,3.66-.67,7.29-1.45,10.9-2.38,.49-.12,.96-.33,1.17M -.89-2.82-2.78-10.5-8.91-13.14-11.74-.2-.22-.03-.68,.32-.79,3.93-.97,7.78-2.69,11.76-3.25,4.08,3.11,11.98,9.75,13.62,11.44-.17,.43-.53,.73-1.05,.91-3.3,1.23-6.64,2.32-9.9,3.64-.63,.55,.37,1.18,.77,1.57,3.63,2.89,7.29,5.75,10.93,8.63,.54,.44,1.32,.75,1.41,1.69-3.98,1.63-8.32,2.75-12.51,4.07,.02,.82,.71,1.22,1.29,1.65,2.86,2.13,5.74,4.24,8.6,6.37,.44,.47,2.14,1.26,1.63,1.93-15.8,5.29-20.78-.97-3.72,11.99,.32,.4,.02,.89-.45,.98-4.11,.62-8.21,1.24-12.37,1.55-.59,.16-4.89,.26-4.16,1.09,2.77,2.54,6.03,4.6,8.99,6.94,.59,.M 48,2.55,1.57,1,2.09-4.3,.27-8.6,.53-12.9,.76-.94,.3-7.95-.49-6.14,1.36,3.08,2.58,6.25,5.06,9.36,7.6,.16,.14,.29,.42,.23,.58s-.37,.35-.59,.37c-1.47,.11-2.95,.27-4.42,.26-6.05-.05-12.12-.33-18.17-.3-.06,.21-.24,.48-.14,.59,.64,.69,1.3,1.37,2.02,2,2.19,1.91,4.41,3.78,6.6,5.69,.37,.43,1.32,1.06,.63,1.58-7.61,.13-15.34-.64-22.93-1.34-1.33-.14-2.65-.41-3.96-.17-.3,.5,0,.85,.35,1.19,2.82,2.87,6.01,5.44,8.6,8.52-.12,1.32-6.77-.04-8-.05-5.2-.62-10.39-1.24-15.58-1.88-2.66-.28-5.29-.85-7.96-1.01-.12,0-.35,.06-.36,.11-.03,.2-.M 1,.46,.03,.6,2.87,3.25,5.96,6.35,8.72,9.7,.11,.12-.01,.37-.04,.67-11.92-1.4-23.79-3.65-35.49-6.13-.58-.05-1.4-.36-1.94-.06-.09,.17-.24,.42-.15,.54,2.66,3.49,5.4,6.94,8.08,10.42,.1,.13-.04,.39-.13,.57-.74,.32-1.91-.11-2.73-.16-8.22-1.66-16.43-3.36-24.53-5.39-5.01-1.25-9.99-2.57-14.98-3.87-.52-.13-1.03-.27-1.66,.07,2.23,4.17,5.26,7.91,7.57,12.03,.16,.36-.43,.57-.67,.59-16.52-3.66-32.62-8.78-48.65-13.88-.56-.26-1.27-.39-1.86-.23,10.83,7.61,22.04,14.89,33.62,21.84,9.02,2.33,18.12,4.44,27.31,6.33-2.57-3.97-5.15-7.94-7.7M 1-11.92-.14-.29-.47-1.01-.04-1.14,14.87,2.57,29.55,6.89,44.62,8.29,.12-.63-.28-1.07-.64-1.51-2.51-3.18-5.2-6.25-7.58-9.53-.07-.21,.24-.72,.56-.66,2.38,.38,4.74,.8,7.12,1.15,6.88,1.01,13.75,2.09,20.66,2.94,3.05,.38,6.1,.91,9.22,.81,.19,0,.39-.2,.55-.34,.2-.41-.39-.79-.61-1.12-2.56-2.61-5.09-5.28-7.59-7.95-.32-.34-.61-.72-.47-1.25,10.48,.79,21.03,2.37,31.62,2.39,.61-.08,1.19-.43,.53-1.12-2.8-2.77-5.87-5.29-8.55-8.16-.1-.14,.01-.39,.08-.57,8.88-.07,18.01,.91,26.98,.54,.45,0,.91-.44,.62-.87-2.84-2.98-6.97-5.1-9.47-8.24M ,.13-.16,.32-.41,.5-.41,1.61-.07,3.22-.13,4.83-.11,5.94,.05,11.84-.36,17.75-.73,.43-.04,.81-.57,.49-.95-2.83-2.33-5.85-4.46-8.71-6.73-1.7-1.37-.93-1.7,.83-1.78,6.03-.36,12.06-.67,18.03-1.66,1.38-.63-.88-1.61-1.36-2.12-2.52-1.78-5.06-3.55-7.58-5.33-1.22-.85-1.59-1.66,.23-1.86,5.31-.65,10.64-1.22,15.8-2.51,1.36-.74-1.01-1.52-1.49-2.07-2.86-1.95-5.73-3.91-8.61-5.86-.42-.29-.71-.61-.56-1.1,4.87-1.11,9.86-2.02,14.58-3.67,.52-.61-.58-1.13-.99-1.49-2.97-2.03-5.96-4.03-8.93-6.06-.43-.44-1.79-1.02-1.29-1.69,4.11-1.59,8.5-2.M 6,12.55-4.3,.13-.97-.88-1.26-1.5-1.81-3.41-2.44-6.98-4.68-10.3-7.25-.98-1.04,1.91-1.45,2.5-1.93,2.69-1.22,5.43-2.38,7.89-3.9,.55-.7-.89-1.25-1.31-1.71-3.36-2.49-6.73-4.97-10.08-7.46-.51-.54-2.14-1.24-1.14-2.04,2.72-1.36,5.41-2.82,8.07-4.27,1.66-.93,1.67-1.16,.33-2.18-3.93-2.89-7.65-6.07-11.49-9.07-.56-.44-.47-.97-.49-1.49,.46,.06,.75-.15,1.06-.37,2.79-1.82,5.24-4,7.82-5.95,.96,.08,1.4,.66,1.97,1.1,3.28,2.54,6.55,5.09,9.83,7.63,.48,.36,.95,.77,1.88,.77,2.74-2.74,4.39-6.01,7.04-8.95,3.84,2.7,7.36,5.1,11.18,7.7,.45,.3M ,1.22,.74,1.71,.33,2.47-2.87,3.25-6.78,5.84-9.52,4.34,1.94,7.65,4.32,12.1,6.05,2-3.63,2.83-7.35,4.57-10.75,.39-.03,.69-.13,.87-.05,3.77,1.64,7.54,3.29,11.3,4.95,0-.02,.01-.03,.01-.05,1.04-3.85,2.26-7.68,3.31-11.53,.55-1.43,4.42,1.01,5.67,1.16,2.11,.69,4.24,1.33,6.36,1.99v-.02c.69-4.33,2.31-8.64,2.39-13t-.02-.01c-3.74-1.23-7.49-2.47-11.23-3.72,.78-3.67,1.55-7.35,2.33-11.02,.12-1.06,.45-2.32,1.86-1.79,2.83,.97,5.66,1.97,8.51,2.87,.79,.24,1.47-.34,1.54-1.07,.58-4.14,1.67-8.24,1.87-12.41-.01,0-.03-.01-.04-.01Zm-299.21,M 142.34c.07,.02,.14,.05,.21,.07-.21,.12-.28,.1-.21-.07Zm147.12-14.31s-.08,.01-.11,.02c.04-.04,.08-.07,.12-.11-.01,.03-.01,.06-.01,.09Zm118.08-86.87c-.26,.68-.61,1.76-1.56,1.52-3.95-1.64-7.72-3.69-11.32-5.82,1.39-3.61,2.86-7.32,4.18-10.93,.72-.22,1.2-.04,1.65,.18,3.38,1.74,6.78,3.4,10.28,4.92-1.08,3.38-2.14,6.75-3.23,10.13Zm17.01-13.36c-.55,2.41-1.17,4.8-1.77,7.19-.13,.53-.94,.84-1.56,.6-3.52-1.41-7.17-2.67-10.37-4.56,1.21-4.01,1.73-8.24,3.45-12.07,2.37,.72,8.05,3.03,11.08,4.48-.26,1.46-.5,2.91-.83,4.36Zm-136.71-29.6M 9l.06,.09s.05-.02,.07-.03l-.13-.06Zm.04,53.66h-.05l.1,.06s-.04-.04-.05-.06Zm-6.46,94.41s-.01,.04-.02,.06l.08-.08s-.04,.01-.06,.02Zm-68.05,41.29s.05,.08,.08,.12l.16-.07c-.08-.02-.16-.03-.24-.05Zm-120.55-51.44c3.16,1.32,6.28,2.66,9.46,3.96l8.48-9.91c-8.8-3.52-17.3-8.03-26.02-11.41-.63,.75,.28,1.88,.48,2.73,1.64,4.1,3.35,8.17,4.92,12.3,.29,.55-.56,.77-.93,.65-21.89-9.47-43.4-20.05-64.25-31.13-.89-.34-1.78-1.25-2.77-.87-.09,.03-.17,.19-.15,.28,1.39,5.37,2.93,10.72,4.37,16.08,.2,.75-.68,.91-1.19,.57-21.19-10.59-42.15-21M .96-62.55-33.89-4.78-2.8-9.53-5.64-14.29-8.45-.54-.32-1.03-.7-1.77-.6-.48,1.6,.11,3.37,.21,5.02,.53,4.58,1.69,9.17,1.87,13.74-.61,.23-1.09,.06-1.52-.19-3.29-1.87-6.61-3.71-9.85-5.65-27.05-15.97-53.84-32.34-79.84-49.93-1.38-.78-3.51-3.03-3.47,.38,0,5.82,.03,11.63,.06,17.44,.05,.87-.09,1.85,.77,2.41,.73,.48,1.44,.97,2.18,1.44,29.7,18.87,60.26,36.56,91.32,53.3,.77,.42,1.6,.77,2.43,1.11,.12,.04,.58-.19,.57-.28-.1-5.6-1.47-11.11-2.14-16.67-.39-2.9,1.11-1.62,2.7-.86,25.91,14.26,52.12,28.6,79.26,40.39,.52-.46,.33-1,.19-1.M 5-1.28-5.15-3.26-10.22-4.06-15.45-.03,.01-.06,0-.1-.01,.04,0,.07,0,.11-.01,.05-.06,.09-.1,.14-.16,.03,.06,.05,.1,.03,.14,.98-.22,1.78,.4,2.61,.77,20.62,10.29,41.96,19.72,63.38,28.53l2.35-2.75c-1.4-3.59-3-7.13-4.33-10.75-.21-.95,.57-1.08,1.34-.77Zm17.36,47.05c-.64-1.61-1.28-3.22-1.92-4.83-6.46-4.96-12.78-10.04-18.96-15.23-18.66-7.14-36.81-14.92-54.85-23.16-.57-.26-1.14-.59-1.99-.49-.19,1.81,.7,3.57,1.1,5.33,.85,3.05,1.72,6.09,2.56,9.14,.2,.73,.47,1.46,.23,2.22-.22,.88-2.2-.35-2.78-.46-12.44-5.38-24.69-11.03-36.85-16M .8-14.74-6.94-29.08-14.42-43.5-21.77-.47-.22-1.1,.12-1.05,.59,.13,1.39,.25,2.79,.44,4.18,.68,4.9,1.39,9.81,2.08,14.7,28.14,13.76,56.78,26.82,86.02,38.32,.32,.11,.83-.25,.77-.56-.69-3.97-2.03-7.79-3.05-11.69-.04-1.12-2.42-5.72,.15-4.73,22.75,9.64,46.07,18.57,69.64,26.52,1.18,.35,3.1,1.19,1.96-1.28Zm-82.88-62.06h-.01v.02c.11,.02,.18,0,.18-.04-.06,.01-.11,.02-.17,.02Zm-72.61,15.48l-.06-.03,.07,.08s0-.03,0-.05Zm-8.1-60.16h.02l.03-.09-.05,.09Z"/><path class="cls-2" d="M449.27,412.22s.03-.01,.05-.02c.01-.02,.01-.03,.02-.M 05l-.07,.07Zm14.24-264.13s.03-.02,.05-.03t.01-.02l-.06,.05Zm16.55,296.87c-.54-1.04-1.88,.14-2.63,.4-3.5,1.82-6.99,3.66-10.49,5.48-.79,.25-2.51,1.64-3.04,.65-.2-6.24,.54-12.48,.86-18.71,.63-8.62,1.43-17.19,2.27-25.79,.31-2.03-.9-1.56-2.25-1-5.07,2.19-10.18,4.35-15.46,6.21-1.26,4.79-.69,9.84-1.19,14.75-.56,9.69-.71,19.38-.79,29.08,.07,.98-.27,2.69,1.19,2.69,3.98-.4,7.3-2.57,10.91-4.06,1.03-.22,3.82-2.58,4.22-.87,.01,5.78-.39,11.54-.39,17.31,5.32-2.24,10.69-4.41,16.11-6.49,.03-6.55,.66-13.11,.68-19.65Zm8.8-298.5s-.02,M .09-.04,.13c.04,0,.08-.01,.12-.01l-.08-.12Zm24.74,278.52c-1.42-.03-2.46,1.06-3.67,1.67-3.79,2.24-7.58,4.48-11.39,6.71-.18,.11-.5,.08-.76,.11-.31,.03-.55-.33-.5-.75,1.4-12.04,2.78-24.04,5.05-35.96,.33-2.62,1.27-5.37,1-7.99-.05-.12-.46-.29-.59-.24-.96,.38-1.9,.79-2.82,1.23-4.43,2.02-8.71,4.41-13.24,6.2-1.34,.06-.67-1.61-.67-2.42,.99-6.09,1.9-12.19,3.03-18.26,1.38-7.45,2.94-14.88,4.44-22.32,.56-2.77,1.15-5.53,1.72-8.29,0-1.61-2.31-.06-3.13,.08-5.2,1.7-10.22,4.08-15.53,5.36-1.02,.17-.37-2.02-.39-2.6,2.72-14.4,6.1-28.67M ,9.51-42.92,.98-4.67,2.71-9.21,3.35-13.94-.41-1.05-1.94-.23-2.75-.12-5.37,1.42-10.73,2.85-16.1,4.27-.65,.06-1.7,.6-2.07-.19,3.81-18.36,9.25-36.54,14.27-54.66,1.22-4.3,2.56-8.58,3.83-12.88,.16-.52,.19-1.06,.26-1.59,.04-.29-.41-.65-.75-.6-6.99,1.13-13.96,2.33-20.95,3.49-.52,.08-1.07-.33-1.01-.75,6.84-27.38,16.57-54.11,25.08-81.03-7.54,.69-15.09,1.11-22.67,1.05-.88,.07-1.86-.13-2.59,.42-8.06,25.62-15.36,51.44-21.94,77.46-.17,1.52-1.24,3.36,1.13,3.29h17.79c1.94-.19,2.82-.02,2.29,1.51-5.98,21.92-11.34,44.02-15.83,66.29-M .04,.73-.47,2.14,.47,2.34,6.44,.58,12.62-1.89,18.83-3.11,1.85-.18,.77,1.91,.71,2.91-3.45,15.24-6.54,30.53-9.29,45.91-.64,3.51-1.23,7.03-1.82,10.55-.1,.63-.27,1.29,.26,1.99,6.21-1.32,12.06-4.24,18.2-5.91,.32-.08,.88,.24,.84,.51-2.03,13.69-4.83,27.27-6.43,41.01-.56,3.63-.89,7.28-1.16,10.94,.46,1.12,1.87-.01,2.65-.23,3.88-1.74,7.75-3.48,11.62-5.23,.78-.28,3.39-1.91,3.47-.34-2.09,14.75-3.84,29.54-4.72,44.41,.42,1.71,2.86-.61,3.78-.87,3.63-2.05,7.25-4.11,10.88-6.17,.46-.27,.94-.39,1.5-.2,.32,.96,.1,1.93-.05,2.88-.91,6.9M 3-1.22,13.88-1.8,20.83,5.14-1.83,10.31-3.6,15.53-5.29,.63-9.52,2.19-19.17,3.13-28.56Zm-5.32,73.1c-.02,.61,.03,1.35,.12,1.92,.66,.3,1.08,.09,1.48-.24,1.57-1.29,3.13-2.59,4.7-3.88-2.11,.72-4.21,1.45-6.3,2.2Zm300.87-14.8s.04,.05,.06,.08c.02-.01,.04-.01,.06-.02l-.12-.06Zm22.08,23.39c-2.08-1.98-4.18-3.95-6.25-5.93-.85-.83-1.37-.9-2.43-.55-8.44,3.01-16.86,6.28-24.9,10-.47,.22-.93,.43-1.51,.26-3.6-2.74-5.76-4.79-7.25-6.94,8.53-4.79,17.92-7.86,26.8-12.04-2.03-2.83-4.45-5.37-6.48-8.11-9.56,3.49-18.57,7.99-27.71,12.32-.68-.1M 3-1.07-.4-1.37-.77-1.44-1.82-2.89-3.64-4.36-5.44-.45-.48-1.01-1.29-1.77-1.1-8.29,3.88-15.68,9.08-23.52,13.59-2.65-2.28-3.71-5.24-6.14-7.58-1.12,.18-1.73,.79-2.41,1.28-5.64,4.01-11.36,7.95-16.69,12.22-.69,.42-1.73,1.7-2.54,.91-1.5-2.28-2.97-4.58-4.41-6.89-.26-.4-.92-.47-1.37-.14-6.04,4.55-11.28,9.84-16.85,14.82-.36,.32-1.14,.16-1.3-.24-.79-2.15-1.25-4.41-1.93-6.6-.08-.28-.26-.67-.52-.76-.85-.22-1.29,.61-1.85,1.04-4.57,4.39-9.22,8.72-13.49,13.31-.47,.5-.82,1.13-1.88,1.26-1.61-2.61-1.5-5.62-2.83-8.29-.66-.05-1.04,.24-M 1.36,.6-1.89,2.09-3.81,4.18-5.68,6.29-2.78,3.04-5.33,6.26-8.2,9.21-.12,.12-.5,.16-.71,.11-.61-.18-.68-.84-.82-1.36-.66-2.3-1.31-4.61-2-6.91-.05-.19-.28-.41-.5-.47-.6-.08-1.07,.53-1.44,.93-4.62,4.95-8.37,10.64-12.95,15.58-1.66,.69-2.73-8.72-3.6-9.71-.93-.02-1.36,.87-1.9,1.47-2.8,3.68-5.59,7.36-8.38,11.05-.65,.72-1,1.72-2.06,1.9-1.55-2.9-1.32-6.31-2.12-9.45-.12-.62-.13-1.29-.78-1.78-.75,.14-1.02,.65-1.35,1.11-2.48,3.45-4.94,6.92-7.43,10.37-.59,.64-1.26,2.08-2.04,2.32-.77-.15-.81-.96-.95-1.58-.69-3.71-.62-7.59-1.84-11M .18-1.19,.05-1.58,1.3-2.3,2.07-2.32,3.28-4.63,6.57-6.95,9.84-.56,.62-.9,1.56-1.91,1.33-3.28-18.91,1.24-19.22-12.04-2.04-.1,.12-.84,.37-.91,0-.59-1.95-.56-4.07-.78-6.08-.35-3.42,.06-6.95-.83-10.28-.44-.81-1.49,.76-1.85,1.09-2.79,3.55-5.36,7.26-8.26,10.72-.11,.11-.48,.09-.72,.08-.47-.08-.4-.76-.48-1.13-.4-4.95-.82-9.88-.78-14.85-.22-.79,.51-3.85-.91-3.24-3.19,3.26-5.86,6.97-8.85,10.42-.46,.38-1,1.26-1.64,1.24-.57-.15-.5-1.27-.61-1.76-.1-4.3-.18-8.61-.25-12.92-.03-2.26-.04-4.52-.06-6.79,0-1.18-1.03-.65-1.49-.26-2.86,3M .13-5.69,6.28-8.54,9.41-.4,.43-.88,.81-1.33,1.2-.05,.04-.25-.01-.36-.05-.11-.03-.27-.1-.29-.17-.49-2.19-.19-4.52-.28-6.76,.06-5.28,.15-10.56,.22-15.83-.13-.87,.33-2.26-.62-2.66-.07-.03-.27,.02-.35,.09-3.55,3.01-6.63,6.52-10.02,9.7-.43,.35-.7,1.04-1.54,.76-.58-.19-.38-.73-.41-1.13,.05-5.9,.43-11.8,.56-17.7-4.54,1.36-9.04,2.78-13.51,4.25-.19,8.05-.27,16.09,.02,24.14,.03,.86,.07,1.72,.17,2.58,.02,.15,.32,.29,.52,.4,.68-.03,1.24-.8,1.77-1.18,2.74-2.66,5.46-5.34,8.21-7.99,2.42-2.29,2.17-.51,2.26,1.71-.05,7.32,.23,14.64,M .8,21.96,.03,.57,.02,1.14,.7,1.31,3.92-3.01,6.66-7.66,10.44-10.97,.26-.25,.81,.09,.88,.29,.41,7.1,.72,14.2,1.5,21.28,.09,.32,.21,1.05,.65,.99,.31-.17,.69-.33,.89-.58,2.26-2.8,4.5-5.62,6.76-8.43,.58-.72,1.19-1.43,1.84-2.12,.1-.11,.46-.09,.71-.08,.5,.06,.45,.73,.55,1.11,.35,4.09,.67,8.17,1.04,12.25,.18,1.94,.44,3.86,.69,5.79,.03,.18,.23,.35,.37,.51,.14,.18,.69-.06,.96-.42,3.03-3.75,5.42-8.15,8.85-11.51,.09-.07,.59,.07,.62,.16,.19,.62,.4,1.25,.41,1.88,.03,3.46,.78,6.86,1.17,10.29,.16,1.5,.51,2.98,.79,4.47,.02,.08,.15,M .22,.22,.22,1.07,.08,1.38-1.1,1.98-1.77,11.63-17.53,7.14-11.58,10.7,3.99,.71,.16,1.1-.05,1.38-.47,2.25-3.43,4.5-6.87,6.77-10.29,1.17-1.66,2.29-3.58,2.88-.27,.37,3.43,1.26,6.81,1.96,10.21,.08,.29,.24,.72,.58,.79,.23,0,.58,0,.67-.1,.44-.54,.82-1.11,1.19-1.68,2.16-3.35,4.31-6.71,6.48-10.05,.62-.76,.95-1.78,2.09-1.84,.98,3.57,1.86,7.16,2.83,10.73,.08,.26,.49,.46,.74,.68,.92-.48,1.19-1.23,1.62-1.89,2.39-3.62,4.76-7.24,7.15-10.86,.41-.47,.8-1.3,1.43-1.47,.23,.06,.58,.15,.62,.28,1.01,3.12,1.93,6.26,2.98,9.38,.99,.78,1.52-M .78,2.23-1.56,2.67-3.74,5.33-7.49,8.01-11.22,.67-.78,1-1.77,2.19-1.85,.74,1.16,2.72,9.74,4.04,8.62,4.14-4.85,7.72-10.15,11.9-14.98,.54-.48,1.42-2.07,2.17-1.17,.76,1.95,1.52,3.9,2.25,5.86,.27,.72,.5,1.45,1.22,2,.87-.2,1.19-.83,1.64-1.35,3.65-4.27,7.3-8.54,10.96-12.8,.73-.63,1.3-1.99,2.38-1.95,.22,.05,.46,.25,.54,.43,.97,2.33,1.55,4.92,3.01,6.99,.41,.19,.94-.32,1.24-.54,4.19-4.63,8.64-9.09,13.19-13.5,.58-.56,1.05-1.26,2.14-1.55,2.31,2.1,3.17,4.93,5.48,7.1,1.41-.24,2.17-1.47,3.19-2.33,4.27-4.17,8.82-8.14,13.6-11.95,.5M 4-.43,.99-1.01,1.99-1.07,1.82,2.21,3.67,4.45,5.53,6.68,.24,.18,.47,.15,.85,.21,6.63-4.68,13-9.78,19.92-14.06,.43-.28,1.1-.18,1.42,.18,1.81,2.38,4.37,4.35,5.68,7.03-7.04,4.39-13.58,9.45-20.37,14.12-.88-.18-1.27-.63-1.68-1.05-1.66-1.69-3.31-3.39-4.97-5.09-.24-.24-.77-.28-1.07-.06-5.56,4.3-10.98,8.91-16.05,13.65-.5,.47-.9,1.06-1.86,1.21-2.57-1.69-3.4-4.61-5.96-6.35-.38-.23-.64,0-4.05,3.38-.42,.42-.85,.84-1.26,1.26-3.16,3.22-6.32,6.45-9.49,9.66-.48,.49-.85,1.1-1.94,1.26-1.97-2.09-3.32-4.58-5.18-6.81-.83,.09-1.19,.54-1.M 54,.98-3.33,4.05-6.65,8.11-9.97,12.16-.9,.76-2.25,4.01-3.55,2.27-1.21-2.15-2.25-4.4-3.59-6.49-.79-.39-1.42,.74-1.91,1.2-3.94,4.76-7.25,9.83-10.97,14.68-.17,.22-.9,.19-1.04-.04-1.36-2.33-2.65-4.7-3.93-7.07-.13-.25-.83-.25-1.02,0-3.29,4.38-6.16,9.07-9.21,13.63-.41,.53-.69,1.31-1.5,1.22-.11,0-.27-.1-.31-.18-.9-1.92-1.78-3.83-2.67-5.74-.42-.9-.53-1.9-1.45-2.72-1.4,.58-1.88,2.22-2.74,3.37-1.88,3.1-3.73,6.21-5.6,9.31-.52,.64-.76,1.9-1.7,1.97-.22-.05-.5-.24-.57-.41-1.12-2.65-2.21-5.31-2.92-8.06-.16-.63-.29-1.27-.95-1.73-.M 99,.37-1.36,1.51-1.96,2.31-2.54,3.88-4.5,8.18-7.37,11.81-1.43,.6-2.85-7.88-3.4-9.16-.3-.7-.4-1.96-.98-2.41-1.06,.14-1.37,1.45-1.98,2.19-2.04,3.4-4.05,6.81-6.09,10.2-.27,.46-.46,1.01-1.22,1.14-.54-.4-.68-.93-.81-1.46-.88-3.92-1.82-7.82-2.83-11.72-.02-.09-.16-.23-.22-.22-1.05,.02-1.34,1.18-1.9,1.87-1.94,3.19-3.87,6.39-5.81,9.59-.35,.57-.58,1.21-1.42,1.58-.23-.23-.62-.45-.69-.72-.99-4.23-2.09-8.45-2.69-12.74-.17-.49-.07-1.62-.64-1.74-.97-.11-1.25,.89-1.76,1.5-2.36,3.51-4.52,7.12-6.98,10.56-.11,.14-.48,.24-.69,.21-.17-M .03-.39-.27-.42-.43-.57-2.98-1.12-5.97-1.64-8.95-.67-2.78-.42-5.76-1.75-8.32-1.19,.69-1.64,1.67-2.4,2.68-2.19,2.96-4.13,6.1-6.48,8.94-.15,.13-.87,.17-.98-.13-1.08-4.97-1.97-9.99-2.41-15.04-.13-1.5-.46-2.98-.72-4.48-.73-.59-1.42,.69-1.9,1.12-2.56,3.15-4.98,6.43-7.6,9.53-.29,.34-.77,.51-.98,.34-.17-.15-.41-.31-.43-.48-.19-1.39-.32-2.79-.51-4.18-1.06-6.06-1.15-12.25-2.2-18.27-.73-.16-1.09,.15-1.41,.5-3.1,3.24-5.86,6.81-9.19,9.81-.09,.08-.61,0-.65-.09-1.03-2.72-.69-5.77-1.08-8.63-.42-5.38-.82-10.75-1.24-16.13-.07-.57-.M 04-1.59-.87-1.46-3.18,2.37-5.84,5.36-8.8,7.99-.79,.52-2.24,2.75-3.11,1.43-.55-9.34-1.26-18.73-1.19-28.09-.09-.52,.11-1.57-.36-1.82-.24-.03-.58-.1-.73,0-3.39,2.4-6.55,5.12-9.85,7.65-.75,.42-1.6,1.69-2.52,1.32-.26-.18-.42-.54-.43-.83-.11-2.32-.19-4.63-.28-6.95-4.84,1.87-9.63,3.8-14.37,5.79,.25,3.72,.21,7.45,.59,11.16,.11,.69,.37,1.52,1.27,1.23,3.91-2.56,7.55-5.54,11.34-8.28,.67-.49,1.26-.26,1.45,.35,.43,5.38,.83,10.77,1.23,16.15,3.74,1.99,7.4,4.15,10.95,6.46,3.58-3.44,3.09-.93,3.52,2.37,10.29,7.13,19.73,15.65,27.99,2M 5.44,.22-.03,.51-.03,.77-.07,.08,.43,.16,.85,.23,1.27,3.31,4,6.42,8.2,9.3,12.61,.69-.72,3.49-5.8,4.34-4.8,1.85,5.81,2.19,11.97,4.39,17.7,.97-.1,1.26-.97,1.76-1.65,1.77-2.78,3.51-5.58,5.27-8.37,.48-.64,1.44-2.81,2.33-1.53,1.2,4.63,2.28,9.3,3.5,13.93,.15,.36,.33,.96,.75,1.09,.22-.01,.57-.03,.63-.13,10.73-16.73,6.03-16.73,12.47,1.17,.71-.06,1.05-.35,1.28-.77,1.06-1.98,2.13-3.95,3.2-5.93,1.24-2.14,2.19-4.46,3.71-6.43,.21-.28,.83,0,.94,.17,1.33,3.62,2.5,7.26,3.86,10.86,.07,.17,.34,.35,.56,.4,.98,.02,1.16-1.31,1.66-1.95,M 1.83-3.35,3.65-6.71,5.48-10.07,.32-.59,.56-1.21,1.26-1.61,.11,.03,.27,.04,.3,.09,1.96,3.31,2.55,7,4.43,10.32,.85-.13,1.1-.62,1.37-1.11,2.15-3.83,4.3-7.66,6.47-11.49,1.87-3.28,2.13-1.61,3.26,.82,1.04,1.96,1.54,4.26,3.04,5.94,.97,.36,1.29-1.12,1.79-1.71,11.15-18.43,5.74-14.77,13.52-5.12,3.61-4.88,6.38-10.33,9.92-15.28,.54-.79,1.07-.5,1.52-.06,1.24,1.78,2.46,3.58,3.7,5.37,.29,.42,.96,1.01,1.48,.63,1.08-1.49,2.14-2.99,3.16-4.5,2.51-3.69,5.15-7.32,8-10.85,.32-.39,1.04-.39,1.35-.02,1.41,1.71,2.83,3.41,4.24,5.11,.31,.37,.M 68,.65,1.38,.73,4.01-4.79,7.98-9.7,11.98-14.51,.43-.53,.8-1.13,1.78-1.34,2.22,2.07,3.83,4.37,6.48,6.15,4.87-4.63,9.39-9.48,14.15-14.2,.49-.5,.93-1.08,1.92-1.19,2.16,1.86,4.35,3.75,6.52,5.65,.15,.13,.14,.38,.21,.6-4.75,4.63-9.31,9.49-13.95,14.23-.34,.35-.6,.71-.46,1.28,2.34,1.64,5.05,3.2,7.47,4.7,.98-.17,1.36-.77,1.84-1.27,4.22-4.47,8.59-8.85,13.04-13.17,0-.2,.06-.48-.07-.59-2.3-1.78-5-3.29-7.1-5.21,.06-.27,.01-.53,.15-.68,1.84-2.11,13.87-12.2,17.29-14.52,3,1.61,4.92,4.38,8.07,5.83,6.56-4.69,13.42-9.33,20.21-13.66,2M .67,1.34,5.24,4.03,7.81,5.75,.78,.54,1.81-.03,2.53-.45,6.8-3.99,13.86-7.51,20.96-10.96,.49-.25,1.1-.19,1.47,.12,2.36,2.24,5.33,3.95,7.25,6.55-7.51,3.82-15.49,7.01-22.42,11.46,2.01,2.17,5.46,3.72,7.92,5.56,.45,.29,1.01,.27,1.51,.02,5.62-2.83,11.19-5.62,17.03-8.06,1.63-.72,3.54-1.05,4.83-2.22,1.34-.12-6.72-5.19-7.96-6.68,.95-.97,2.19-1.18,3.4-1.7,7.02-2.74,14.05-5.46,21.34-7.72,.74-.23,1.53-.39,1.94-1.07-.19-.26-.34-.57-.59-.81Zm-44.07-2.5c-7.14,3.47-13.83,7.46-20.65,11.3-.64,.37-1.2,.88-2.29,.9-2.24-1.85-4.51-3.83-6M .59-5.93-.34-.35-.27-.85,.19-1.14,2.12-1.33,4.19-2.71,6.37-3.96,5.41-2.99,10.72-6.25,16.26-9,.3-.06,.83-.01,1.06,.26,2.07,2.38,4.86,4.35,6.51,6.99-.27,.19-.54,.42-.86,.58Z"/><path class="cls-2" d="M510.81,220.17s-.02,.03-.03,.05c-.02,0-.04,.01-.06,.01l.09-.06Z"/><path class="cls-2" d="M555.97,432.23c-.44,2.9-1.03,5.79-1.54,8.69-4.8,1.19-9.57,2.44-14.31,3.74,.91-3.59-3.42,.65-4.5,1.24-3.41,.96-6.8,1.94-10.18,2.95,.97-10.15,2.74-20.17,4.51-30.2,.22-1.27,.27-2.56,.34-3.84,.01-.1-.47-.34-.58-.29-4.38,2.44-8.51,5.29-12.M 82,7.86-.63,.39-1.34,.7-2.04,1.01-.11,.04-.57-.17-.56-.24,1.42-14.45,4.6-28.63,7.57-42.82,.28-1.74-1.54-.74-2.36-.35-4.82,2.35-9.52,4.97-14.45,7.09-.3,.12-.88-.22-.84-.5,.26-1.49,.56-2.97,.8-4.47,1.91-10.66,4.3-21.28,6.86-31.82,.94-3.8,1.9-7.59,2.85-11.39,.04-.91,1.18-2.78-.33-2.76-6.01,2.09-11.77,4.87-17.84,6.76-.31,.07-.61-.09-.58-.34,.09-.95,.15-1.92,.38-2.86,3.78-16.12,7.81-32.15,12.54-48.04,.62-2.1,1.2-4.2,1.78-6.3,.15-.52,.28-1.06-.32-1.59-5.59,1.42-11.15,3.12-16.71,4.65-1.03,.11-3.92,1.74-3.75-.23,6.37-22.8,M 12.96-45.66,20.89-67.96,7.44-1.43,14.85-2.99,22.3-4.34,.39-.05,.85,.28,.75,.56-2.32,6.51-4.71,13.03-7.01,19.54-5.07,15.45-11.12,30.84-14.98,46.53,.51,.64,1.48,.17,2.14,.06,6.04-1.78,12.06-3.68,18.12-5.39,.81,.57,.31,1.4,.16,2.17-2.02,6.25-4.14,12.48-6.06,18.75-3.51,12.16-7.43,24.21-10.31,36.53-.05,.24,.59,.54,.91,.42,5.46-2.06,10.8-4.4,16.21-6.57,2.25-.84,2.28-.2,1.75,1.89-4.46,15.59-9.03,31.2-12.02,47.1-.03,.28,.58,.5,.94,.33,4.72-2.25,9.27-4.78,13.93-7.16,.78-.29,1.65-1,2.48-.92,.2,.25,.43,.52,.32,.85-.38,1.48-.7M 6,2.95-1.12,4.43-2.69,10.64-5.08,21.34-7.33,32.08-.38,1.8-.59,3.62-.86,5.43-.02,.1,.07,.27,.14,.29,.92,.26,1.64-.51,2.4-.9,3.49-2.2,6.97-4.41,10.45-6.62,.97-.46,1.86-1.54,2.98-1.46,.45,.16,.46,.72,.31,1.11-2.01,12.13-5.64,24.09-6.49,36.37,.67,.15,1.1-.07,1.51-.38,2.75-2.06,5.5-4.13,8.25-6.19,.87-.39,5.47-5.01,5.32-2.5Z"/><path class="cls-2" d="M577.14,262.92s-.01,0-.02,.01c.01-.02,.01-.03,.02-.05v.04Z"/><path class="cls-2" d="M588.97,408.1c-2.62,8.76-4.72,17.66-6.77,26.56-4.56,.92-9.11,1.89-13.62,2.91,1.34-5.92,2.4M 3-11.9,3.58-17.85-.02-.2-.53-.58-.81-.4-4.22,2.77-8.12,5.98-12.21,8.94-.62,.31-1.56,1.46-2.21,.79-.02-3.37,1.14-6.59,1.8-9.87,1.95-8.03,3.62-16.14,5.87-24.09,.1-.76,.88-2.51-.43-2.38-4.68,2.67-9.11,5.73-13.71,8.54-.62,.4-1.21,.88-2.16,.87,2.48-14,7.11-27.84,10.81-41.65,.01-1.6-2.24,.14-2.95,.38l-12.15,6.39c-.73,.31-2.56,1.71-2.71,.24,1.88-7.95,4.43-15.75,6.61-23.62,2.25-7.43,4.77-14.8,7.04-22.23,.22-.71,.7-1.42,.16-2.17-6.31,1.78-12.1,5.27-18.39,7.29-.45,.18-.71-.43-.67-.58,5.67-18.91,11.84-37.65,19.07-56.06l.25-.2M 2c7.25-2.32,14.5-4.65,21.75-6.96-7.24,17.31-13.92,34.82-20,52.43-.28,.83-.5,1.67-.69,2.51-.02,.09,.42,.36,.54,.32,6.27-2.03,12.05-5.39,18.34-7.35,.14-.03,.56,.24,.54,.33-.16,.73-.34,1.47-.62,2.18-5.45,14.2-10.29,28.54-14.8,42.95-.09,.52-.51,1.48-.17,1.87,.22,.08,.52,.18,.69,.12,5.51-2.65,10.73-5.81,16.22-8.5,.22-.07,.88-.06,.88,.32-.17,.74-.31,1.49-.55,2.21-3.72,10.88-7.02,21.87-10.27,32.89-.49,1.67-.93,3.36-1.36,5.04-.05,.19,.04,.48,.2,.59,.14,.09,.55,.06,.73-.04,4.74-2.8,9.28-5.89,13.94-8.81,.52-.33,1.03-.71,1.92M -.57-.41,4.68-2.89,9.15-3.86,13.77-1.5,5.9-3.02,11.81-4.71,17.68-.36,1.26-.64,2.53-.91,3.8-.03,.14,.19,.33,.34,.46,.79,.08,1.85-1.04,2.58-1.42,3.59-2.61,7.16-5.23,10.75-7.84,.92-.55,2.6-1.98,2.12,.23Z"/><path class="cls-2" d="M594.31,474.5c-2.29,2.15-4.34,4.57-6.83,6.52-.06,.04-.26-.02-.38-.07-.1-.04-.25-.12-.25-.18,.03-1.62,.1-3.24,.4-4.84,2.35-.49,4.7-.97,7.06-1.43Z"/><path class="cls-2" d="M596.7,427.88c-.34,1.4-.71,2.79-1.06,4.19-2.49,.44-4.97,.91-7.44,1.4,2.67-2.1,5.15-4.42,7.99-6.27,.37-.11,.56,.4,.51,.68Z"/>M <path class="cls-2" d="M597.35,493.02s-.04-.01-.06,0c0-.02-.02-.05-.03-.07l.09,.07Z"/><path class="cls-2" d="M809.15,483.28s.04-.02,.06-.02c.02,.03,.04,.05,.06,.08l-.12-.06Z"/><path class="cls-2" d="M870.74,441.97s-.07,.01-.1,.02l-.03-.09,.13,.07Z"/><path class="cls-2" d="M756.79,463.43c-5.83,3.41-11.52,7.01-17.28,10.52-1.12,.29-1.12-.82-1.21-1.58-.07-2.36-.08-4.74-.18-7.1-.3-1.32-2.47,.52-3.09,.87-6.4,4.3-12.59,8.78-18.73,13.31-.3,.2-.94,.05-.97-.24-.39-2.99-.11-6.01-.14-9.01,0-.25-.18-.4-.5-.42-.5-.05-.96,.34-1.3M 6,.57-2.43,1.87-4.88,3.72-7.24,5.64-3.5,2.83-6.87,5.78-10.32,8.65-.45,.35-.81,.96-1.63,.66-.6-.22-.41-.74-.41-1.14-.03-2.8,.11-5.6-.03-8.4-.05-.26-.38-.69-.7-.65-.24,.07-.5,.16-.68,.3-5.83,4.87-11.67,9.87-17.1,15.08-.31,.32-1.03,.76-1.31,.5-.16-.15-.36-.33-.37-.5-.15-2.8-.03-5.61-.06-8.4-.08-.71,.22-1.63-.44-2.12-.23-.19-.48-.13-.7,.07-.89,.81-1.83,1.58-2.68,2.42-4.91,4.45-9.31,9.8-14.49,13.77-.33,.02-.52-.12-.53-.39-.03-2.47-.07-4.94-.08-7.42,0-1.39,.07-2.79,.06-4.19,0-.13-.33-.27-.53-.37-6.34,4.73-11.25,11.34-17.M 07,16.67-.15,.09-.6,0-.68-.11-.08-.42-.18-.85-.17-1.28,.18-4.09,.46-8.17,.56-12.26,0-.07-.13-.22-.2-.22-.96-.18-1.41,.74-2.03,1.28-3.15,3.37-6.28,6.74-9.42,10.11-.61,.5-1.13,1.38-1.9,1.59-.21-.09-.54-.24-.54-.36,.01-1.4,.04-2.79,.12-4.19,.03-3.7,.78-7.66,.48-11.24-.23-.03-.59-.08-.69,.02-4.11,4.07-7.98,8.36-11.78,12.69-.76-.27-.86-.68-.83-1.36,.08-5.73,1.21-11.38,1.63-17.07-.99-.21-1.49,.62-2.13,1.19-3.58,3.63-6.8,7.59-10.59,10.99-.12,.08-.58-.04-.61-.21,.02-5.58,1.04-11.14,1.68-16.68,4.21-.79,8.43-1.54,12.68-2.24-M .12,1.4-.58,2.85-.46,4.22,.04,.07,.13,.16,.22,.18,.12,.04,.32,.06,.39,0,2.07-1.57,3.76-3.55,5.64-5.34,2.4-.37,4.81-.74,7.22-1.08-.5,3.83-1.2,7.63-1.54,11.48-.02,.18,.14,.37,.25,.55,.11,.18,.66,0,1.03-.35,3.3-3.25,6.56-6.56,9.85-9.83,3.52-3.38,3.57-3.15,3.04,1.52,.06,1.36-2.54,12.75-.31,11.58,5.38-4.92,10.22-10.28,15.83-15.08,.66-.42,1.28-1.35,2.11-1.35,.37,.04,.4,.5,.38,.77-.81,3.95-.68,7.95-1.23,11.91,.01,2.72,1.97,.25,2.94-.55,5.36-4.83,10.43-9.96,15.96-14.58,.13-.1,.49-.04,.74,0,.06,.01,.14,.18,.13,.27-.16,3.66-M .6,7.3-.89,10.95-.08,.42,.15,1.16,.58,1.04,.23-.06,.53-.1,.68-.23,3.53-2.96,7.03-5.95,10.57-8.91,2.89-2.2,5.46-4.94,8.63-6.72,.65-.15,.57,.86,.54,1.26-.3,2.9-.65,5.79-.95,8.7-.02,.58-.02,1.59,.82,1.43,4.56-3.34,8.69-7.12,13.26-10.49,2.51-.05,5.02-.08,7.54-.1-.14,1.66-.15,3.32-.16,4.98,0,.18,.19,.36,.31,.54,.13,.19,.66,.11,1.07-.17,2.46-1.75,4.81-3.62,7.32-5.35,4.77,.03,9.56,.12,14.37,.25,.31,.61,1.24,.47,1.65,.05,5.54,.16,11.09,.4,16.66,.71Z"/><path class="cls-2" d="M773.99,464.58c-3.04,1.57-6.03,3.21-9.13,4.68-.29M ,.14-.89-.12-.9-.39-.07-1.67-.12-3.35-.19-5.03,3.4,.22,6.81,.47,10.22,.74Z"/><path class="cls-2" d="M838.85,472.87c-8.79,2.6-20.66,6.79-29.64,10.39-1.89-2.71-3.85-5.37-5.85-8-.23-.3-.68-.41-1.06-.3-8.8,3.38-17.27,7.53-25.55,11.73-.66,.34-1.24,.8-2.22,.84-1.64-1.54-2.67-3.69-3.98-5.5-.7-.89-1.24-2.98-2.71-2.17-8.01,4.04-15.29,9.14-22.92,13.62-.72-.1-1.01-.45-1.25-.85-1.51-2.2-2.64-5.33-4.51-7.14-.87,.09-1.42,.6-2.02,1.02-5.03,3.58-10.15,7.08-14.86,10.94-1.46,1.02-2.53,2.49-4.36,2.84-1.2-2.72-1.15-5.57-1.94-8.28-.95-M .2-1.61,.57-2.32,1.04-5.75,4.41-10.76,9.35-16.19,13.99-.34,.25-1.11,.08-1.25-.33-.5-2.54-.93-5.11-1.36-7.66-.04-.15-.36-.27-.58-.36-.35-.04-.73,.28-1,.48-4.64,4.33-9.28,8.67-13.91,13.01-.79,.74-1.56,1.47-2.35,2.2-.24,.25-.87-.07-.95-.27-.54-2.75-.87-5.56-1.47-8.3-.05-.16-.35-.29-.57-.4-.78,.13-1.4,1.02-1.99,1.49-4.04,4.31-8.06,8.63-12.1,12.94-.79,.65-1.36,1.91-2.51,1.88-.06,0-.18-.14-.2-.23-.84-3.04-1.23-6.14-1.75-9.25-.03-.18-.24-.34-.4-.49-.69-.35-1.52,.9-2,1.36-3.29,3.81-6.58,7.63-9.86,11.44-1,1.15-1.91,2.36-2.9M 6,3.47-.31,.33-.79,.46-1,.26-.17-.16-.4-.32-.44-.5-.4-2.23-.76-4.48-1.15-6.71-.19-1.07-.41-2.13-.66-3.19-.04-.15-.31-.37-.48-.38-1.05,.21-1.56,1.45-2.27,2.14-2.75,3.45-5.48,6.92-8.23,10.37-.46,.43-.9,1.31-1.58,1.32-.41,.02-.45-.42-.56-.71-1.04-3.67-.34-8.52-1.64-11.78-1.02,.05-1.44,1.13-2.08,1.77-2.7,3.48-5.39,6.96-8.1,10.43-.35,.45-.79,.85-1.21,1.25-.05,.05-.35,.02-.38-.02-.16-.28-.36-.58-.38-.87-.22-3.88-.42-7.75-.64-11.62-.2-1.26,.09-2.86-1.54-1.41-3.33,4.03-6.29,8.35-9.74,12.26-.25,.2-.92,.18-.9-.21-2.51-16.34,M 3.85-23.35-10.14-5.66-.64,.6-1.16,1.73-1.96,1.97-.22-.09-.56-.21-.58-.34-.11-1.07-.21-2.15-.21-3.22,.03-4.53,.09-9.05,.13-13.57,0-.53-.1-1.07-.18-1.6-.01-.06-.18-.13-.29-.16-.52-.17-.84,.41-1.18,.68-2.5,2.94-4.99,5.89-7.48,8.83-.6,.71-1.2,1.44-1.88,2.1-.16,.16-.68,.08-1.04,.11-1.71-22.73,6.41-29.37-9.84-11.79-.6,.54-1.03,1.45-1.94,1.48-.33,.02-.48-.16-.48-.42,0-.97-.04-1.94,0-2.91,.28-6.23,.6-12.49,1.16-18.71,.07-.96,.1-1.93,.13-2.89-.06-.38-.74-.23-.93-.15-3.51,3.07-6.71,6.46-10.13,9.65-.67,.51-1.21,1.36-2.19,1.06M -.03-3.22,.43-6.43,.61-9.64,4.34-1.2,8.7-2.36,13.09-3.47,.56,.05,.79,.06,1.13-.28,3.85-.98,7.73-1.91,11.62-2.8-.78,5.36-1.07,10.79-1.5,16.19,.67,1.6,2.62-1.52,3.32-2.02,2.36-2.49,4.7-4.99,7.06-7.48,.71-.55,1.24-1.71,2.28-1.49,.07,.01,.17,.17,.16,.26-.11,2.37-.2,4.73-.37,7.09-.32,4.19-.69,8.38-1.03,12.57-.1,2.9,1.78,.45,2.67-.49,2.92-3.22,5.83-6.46,8.76-9.68,.3-.33,.62-.68,1.23-.62,.34,.6,.21,1.22,.18,1.84-.24,5.06-.49,10.12-.71,15.18,.03,.63-.18,1.43,.63,1.65,.66-.11,1.09-.95,1.57-1.38,2.83-3.28,5.64-6.58,8.48-9.85M ,.43-.36,1.04-1.35,1.64-1.22,.12,.03,.31,.09,.32,.15,.07,.53,.17,1.06,.16,1.59,.25,1.58-1.33,15.47,.72,14.18,3.78-4.01,6.99-8.48,10.74-12.51,1.64-1.45,1.29,1.2,1.31,2.1,.06,3.66,.11,7.33,.19,10.99,.01,.17,.22,.35,.34,.52,.54,.43,1.37-.61,1.73-1.05,3.48-4.11,6.94-8.24,10.62-12.19,.11-.12,.46-.12,.7-.13,.37,.32,.29,1.05,.39,1.52,.18,2.9,.36,5.81,.54,8.71,.19,.6-.2,1.97,.66,2.02,1-.11,1.46-1.17,2.14-1.78,2.68-2.97,5.35-5.95,8.05-8.9,1.35-1.48,2.72-2.95,4.18-4.36,.62-.61,.95-1.58,2.29-1.51,.78,.61,.44,1.4,.48,2.11,.34,M 2.87-.17,5.89,.76,8.65,.47,.91,1.79-.88,2.27-1.19,4.35-4.4,8.67-8.81,13.02-13.2,.58-.59,1.24-1.13,1.91-1.65,.1-.08,.64,.02,.67,.11,.72,3.04,.63,6.22,1.02,9.31,.39,1.1,1.31,.51,1.95-.17,3.24-3.45,6.86-6.65,10.41-9.89,1.87-1.7,3.8-3.35,5.75-4.99,.21-.18,.68-.17,1.13-.27,.57,3.11,.63,6.05,1.17,9.08,.03,.19,.88,.36,1.06,.21,6.21-5.06,11.9-10.68,18.45-15.36,.26-.2,.92,0,.96,.29,.38,2.77,.36,5.64,1.03,8.34,.73,1.06,2.85-1.34,3.66-1.77,5.58-4.34,11.47-8.59,17.49-12.45,.24-.14,.95,.1,.98,.33,.39,2.57,.53,5.14,.75,7.72,.59,M 1.26,2.07-.14,2.82-.58,7.01-4.31,13.83-9.13,21.35-12.73,.76-.14,1.1,.79,1.43,1.3,1.15,2.06,2.29,4.13,3.44,6.19,.22,.4,.54,.74,1.32,.86,8.83-4.6,17.83-9.35,27.23-12.99,.77-.19,1.24,.51,1.54,1.1,1.42,2.24,2.74,4.51,4.15,6.75,.18,.26,.56,.43,.91,.69,4.46-1.61,8.77-3.51,13.27-5.08,7.49,1.07,14.93,2.25,22.31,3.56Z"/><path class="cls-2" d="M848.79,481.95c2.16,2.66,4.41,5.36,6.58,8-.46,.61-1.12,.77-1.74,.94-2.16,.58-4.34,1.13-6.51,1.71-7.74,2.04-15.34,4.47-22.87,6.96-.34-.14-.64-.2-.79-.35-2.18-2.18-4.33-4.38-6.5-6.58-.34M -.35-.54-.73-.27-1.29,9.89-3.82,20.52-7.01,30.71-10.1,.16-.44,.03-.65-.16-1.01-1.52-2.24-3.06-4.46-4.57-6.67,6.7,1.22,13.36,2.54,19.96,3.95-4.1,.96-8.17,2-12.24,3.03-.67,.17-2.16,.48-1.6,1.41Z"/><path class="cls-2" d="M919.81,449.19c-3.43-1-6.88-1.97-10.34-2.91,3.02-.31,5.92-1.17,8.99-1.13,.45,1.34,.9,2.69,1.35,4.04Z"/><path class="cls-2" d="M637.75,1092.25c.55,.13,1.06,.02,1.54-.19,3.79-1.63,7.59-3.24,11.37-4.9,5.67-2.48,11.16-5.2,16.67-7.9,.27-.09,1.23-.46,1.3,.02-2.6,5.81-6.35,11.13-9.39,16.75-.28,.36,.26,.65,.6M ,.55,9.34-3.97,18.17-9.61,27.54-13.23,.11,.17,.3,.41,.23,.55-.5,.99-1.03,1.98-1.61,2.95-2.77,4.66-5.56,9.32-8.34,13.98-.34,.58-.61,1.18-.89,1.78-.03,.06,.1,.19,.2,.26,.33,.19,.75-.06,1.06-.17,4-1.99,8.03-3.93,11.98-5.99,4.06-2.12,8.02-4.35,12.04-6.52,.99-.52,2.52-1.12,1.5,.73-3.72,6.73-7.96,13.18-11.99,19.73-.12,.29-.33,1.01,.12,1.07,8.46-3.75,16.48-8.54,24.72-12.77,.59-.31,1.22-.43,1.86-.06l-.11-.03c-4.74,8.2-10.09,16.11-14.94,24.3-.13,.36,.58,.47,.74,.42,7.64-3.79,15.17-7.74,22.62-11.84,1.56-.74,3.57-2.02,1.88,.8M 6-4.72,7.97-9.91,15.75-15.07,23.55-2.57,3.81-2.51,4.16,1.72,2.01,7.33-3.42,14.51-7.73,21.93-10.69,.49,.74-.37,1.39-.67,2.05-6.44,10.42-13.69,20.45-20.45,30.76,0,.13,.37,.39,.53,.34,.75-.23,1.51-.43,2.22-.72,5-2.1,9.99-4.22,14.99-6.33,.58-.18,3.46-1.77,3.03-.31-4.38,6.82-9.11,13.42-13.7,20.11-3.28,4.7-6.67,9.34-10,14.01-.51,1.09-2.3,2.23-1.4,3.46,0-.23-.06-.32-.29-.36l.28,.3c6.75-2.43,13.49-4.86,20.25-7.27,.16-.06,.47,.11,.68,.21,.06,.03,.06,.2,.02,.28-.67,1.56-1.82,2.88-2.74,4.31-8.85,12.94-18.58,25.41-27.86,38.19,M .13,.94,2.14-.03,2.78-.07,6.35-1.76,12.62-3.81,19.02-5.38,.88,.17,.22,1.08-.06,1.56-2.84,3.91-5.69,7.82-8.55,11.72-8.45,11.52-17.24,22.87-26.3,34.09-.5,.62-1.16,1.2-1.16,2.01,.64,.35,1.32,.23,1.96,.1,2.35-.47,4.69-.97,7.04-1.44,4.3-.88,8.61-1.74,12.92-2.61,.46-.15,1.14-.21,1.49,.07,.11,.14,.05,.43-.07,.6-.58,.85-1.17,1.7-1.81,2.52-6.41,8.23-12.79,16.47-19.24,24.67-7.43,9.62-15.43,18.91-23.08,28.44-.08,.28,0,.76,.43,.7,2.4-.23,4.81-.45,7.21-.71,5.21-.52,10.4-1.27,15.61-1.69,1.32-.21,2.02,.37,.95,1.47-17.51,21.6-34.6M 9,43.52-53.74,63.85-8,.28-16.1,.05-24.12,.12-2.28-.09-3.49,.01-1.31-2.21,10.46-11.17,20.76-22.52,30.89-33.97,6.68-7.56,13.25-15.2,19.85-22.8,.86-1.21,2.31-2.13,2.45-3.67-7.67,.36-15.25,1.58-22.9,2.25-.49,0-2.21,.27-1.94-.48,15.33-17.94,31.61-35.31,45.79-54.05-.45-.06-.83-.19-1.15-.13-3.53,.67-7.06,1.39-10.59,2.07-3.92,.75-7.85,1.48-11.79,2.19-.11,.02-.47-.3-.43-.39,11.45-14.73,24.32-28.66,35.52-43.52,1.35-1.7,4.33-4.74-.07-3.42-6.12,1.66-12.23,3.34-18.34,5.01-.62,.17-1.26,.43-1.85,.03,10.25-13.85,22.06-26.87,31.81-M 41.15-.31-.82-2.12,.2-2.78,.29-5.32,1.81-10.64,3.65-15.96,5.46-.86,.29-1.76,.5-2.66,.73-.08,.02-.24-.1-.32-.18-.29-.35,.42-1.05,.61-1.4,7.54-9.57,14.85-19.24,22.02-28.99,1.3-1.76,2.5-3.56,3.73-5.35,.28-.33-.21-.71-.57-.58-7.77,3.17-15.41,6.63-23.13,9.91-1.74,.65-3.8,1.55-1.77-1.07,6.97-9.71,14.42-19.11,20.97-29.1,.3-1.51-3.24,.82-3.84,.9-7.39,3.31-14.64,6.93-22.12,10.05-1.46,.06-.44-.86-.05-1.55,5.68-8.07,11.36-16.14,17.04-24.21,.26-.37,.49-.77,.64-1.17,.05-.14-.17-.35-.31-.6-8.91,3.96-17.46,8.67-26.49,12.35-.14,.0M 2-.47-.24-.4-.41,.55-.86,1.08-1.73,1.68-2.56,4.78-6.87,9.8-13.56,13.86-20.79-.34-.81-1.76,.16-2.33,.34-7.45,3.89-15.25,7.31-22.94,10.86-2.39,1.1-3.42,1.29-1.52-1.42,3.84-5.81,7.69-11.61,11.52-17.42,.3-.45,.79-.88,.59-1.46-.03-.09-.22-.23-.27-.21-.73,.26-1.48,.49-2.17,.82-8.61,4.24-17.49,7.98-26.01,12.35l.12-.05c-1.22-1.12,.78-2.65,1.29-3.75,3.03-4.3,5.86-8.67,8.57-13.1,.41-.67,.77-1.36,1.09-2.06,.07-.15-.14-.38-.24-.61-10.8,4.64-21.64,9.4-32.75,13.66l.02,.08c-.94-1.12,.67-2.21,1.17-3.19,2.93-4.11,5.88-8.22,8.81-12.M 34,.46-.65,.9-1.32,1.29-2,.08-.14-.08-.37-.17-.55-11.55,3.8-22.96,8.96-34.66,12.88-1.55,.34-5.42,2.48-3.03-.79,2.88-4.26,5.77-8.51,8.65-12.78,.25-.37,.41-.79,.58-1.19,.03-.06-.09-.18-.17-.24-.52-.37-1.27,.14-1.83,.24-9.88,3.69-20.05,6.83-30.1,10.22-2.72,.92-5.44,1.88-8.34,2.41-.85-.2-.2-1.08,.08-1.57,2.88-4.25,5.92-8.42,8.59-12.8,.08-.13,0-.43-.14-.53-1.28-.41-2.85,.57-4.16,.79-12.21,3.68-24.51,7.17-36.97,10.3-.96,.17-1.83,.64-2.78,.07,2.48-4.67,5.95-8.83,8.29-13.57-.26-.78-1.81-.17-2.41-.11-14.79,3.56-29.71,7.15-4M 4.81,9.61-1.44-.14-.25-1.4,.05-2.08,2.06-3.51,4.26-6.95,6.26-10.49,.13-.29,.25-.71,.08-.92-.74-.67-2.12-.08-3.05-.03-10.74,2.07-21.61,3.58-32.48,5.08-5.45,.66-10.88,1.64-16.37,1.91-1.48-.24,.14-1.98,.37-2.75,1.68-3.05,3.4-6.09,5.08-9.15,.21-.5,.73-1.39,.03-1.69-3.72-.26-7.48,.57-11.21,.75-8.42,.87-16.9,1.28-25.34,1.87-6.44,.54-12.92,.5-19.36,.91-1.08,.12-3.39,.16-2.61-1.31,1.81-4.04,4.2-7.88,5.63-12.07,.07-.26-.33-.69-.67-.7-1.07-.04-2.14-.09-3.21-.09-21.4,.13-42.84-.14-64.19-1.77l.13,.12c1.82-4.49,3.64-8.98,5.46-1M 3.48,.18-.48,.29-1.26-.37-1.4-6.49-.91-13.06-1.28-19.58-1.97-19.82-1.95-39.52-4.81-59.2-7.82l.09,.1c1.68-5.4,2.84-10.98,4.89-16.25l-.13,.07c26.58,4.42,53.27,8.92,80.17,10.99l-.15-.14c.13,.66-.12,1.27-.35,1.9-1.45,4.22-3.32,8.36-4.42,12.67,6.76,1.54,14,1.03,20.93,1.74,14.11,.77,28.26,1.12,42.4,1.17,1.21,.25,5.47-.79,4.53,1.44-1.38,3.15-2.83,6.27-4.2,9.42-1.46,2.98-1.32,2.98,2.53,2.95,8.36-.07,16.69-.49,25.02-.96,9.14-.43,18.26-1.19,27.35-2.02,4.51-.66,3.94,.04,2.55,2.84-1.52,3.11-3.26,6.13-4.76,9.25-.78,1.55,1.86,1.M 04,2.79,.99,4-.47,8-.9,11.98-1.43,12.33-1.64,24.62-3.54,36.88-5.58,1.7-.04,.6,1.46,.23,2.25-1.88,3.56-4.07,6.99-5.76,10.65-.13,.29,.31,.6,.75,.52,4.32-.81,8.66-1.56,12.95-2.47,11.03-2.39,22.07-4.69,32.99-7.5,.22-.05,.5,.04,.74,.09,.66,.23-.13,1.3-.35,1.74-1.96,3.83-4.8,7.55-6.29,11.48,1.03,.62,2.27-.23,3.37-.34,10.15-2.54,20.13-5.46,30.09-8.44,3.14-.94,6.3-1.87,9.46-2.78,.18-.05,.47,.12,.69,.22,.17,.34-.17,.85-.31,1.2-2.24,3.8-4.57,7.56-6.85,11.34-.36,.6-.61,1.2-.12,1.81,.04-.22,.03-.34-.19-.43l.2,.38c13.27-4.37,26M .52-8.93,39.61-13.72,.2,.23,.5,.42,.46,.54-.17,.51-.37,1.03-.67,1.5-2.26,3.67-4.55,7.33-6.82,10.99-.36,.57-.66,1.17-.97,1.76-.03,.06,.05,.19,.12,.26,.46,.42,1.29-.1,1.83-.19,6.17-2.15,12.22-4.51,18.23-6.94,5.53-2.23,11.04-4.49,16.57-6.72,.46-.19,.99-.38,1.53,.11-2.81,4.89-6.01,9.6-9,14.39-.31,.48-.64,.95-.4,1.52-.4-.21-.68,.27-.28,.39,.29-.01,.39-.15,.3-.38Z"/><path class="cls-2" d="M1250.03,891.19c-.37,.86-.06,1.71,.15,2.55,1.39,5.48,2.82,10.96,4.22,16.44,.59,2.32,1.16,4.64,1.7,6.97,.04,.15-.18,.48-.27,.48-1.1-.12M -1.63-1.38-2.42-2.04-10.13-10.76-20.2-21.56-30.39-32.25-1.33-1.22-4.93-5.82-3.48-.87,2.27,7.97,4.57,15.94,6.84,23.92,.09,.59,.48,1.38-.28,1.67-9.65-8.67-18.54-18.78-27.93-27.93-.97-.83-4.88-5.34-3.75-1.38,2.7,9.22,5.78,18.34,8.25,27.63,.02,.08-.12,.27-.18,.27-1.15,.03-1.72-1.22-2.55-1.83-8.66-8.03-16.8-16.72-25.74-24.39-.04-.02-.3,.09-.29,.13,.27,3.56,1.97,6.89,2.84,10.35,1.89,6.97,4.5,13.78,5.93,20.84-1.73-.53-2.55-1.87-3.87-2.95-6.4-5.83-12.79-11.66-19.21-17.48-1.73-1.32-3.21-2.97-2.27,.64,2.79,9.76,5.6,19.51,8.3M 9,29.26,.04,.32,.16,.99-.22,1.14-.89-.03-1.9-1.33-2.67-1.83-5.87-5.05-11.73-10.1-17.61-15.15-1.07-.73-3.22-3.01-2.53-.02,3.08,10.59,5.7,21.25,8.43,31.9,.04,.38,.21,.94-.09,1.23-1.07,.1-1.8-.92-2.5-1.45-5.32-4.28-10.61-8.57-15.93-12.85-.55-.32-2.77-2.44-2.87-1.12,2.5,10.23,4.79,20.52,7.07,30.8,.4,1.8,.71,3.61,1.05,5.42,.02,.09-.08,.26-.17,.28-.67,.24-1.14-.21-1.63-.58-5.86-4.45-11.9-8.69-17.66-13.27-.02,.08-.03,.14-.05,.21l.1-.23c-.47,.58-.49,1.22-.37,1.87,.4,2.13,.81,4.25,1.22,6.38,1.73,9.15,3.49,18.29,5.07,27.47,.M 38,3.6,1.69,6.25-2.65,2.89-4.42-2.99-8.84-5.98-13.28-8.96-.61-.35-1.67-1.28-2.27-.67,.02,5.26,1.48,10.47,2.03,15.7,1.11,8.88,2.41,17.75,3.12,26.67,.01,.13-.3,.29-.49,.41-.35,.11-.78-.17-1.08-.31-4.77-3.01-9.62-5.89-14.44-8.83-.61-.35-1.81-1.19-2.21-.22,.75,13.65,2.23,27.27,2.62,40.95,.09,1.83,.18,3.65,.26,5.48,.01,.27-.58,.55-.89,.42-5.5-2.65-10.89-5.57-16.37-8.27-.95-.31-1.04,.62-1.06,1.29-.04,16.47,.35,32.96-.4,49.41-.13,2.99-1.45,1.8-3.45,1.07-4.03-1.74-8.04-3.5-12.07-5.24-.93-.2-2.42-1.41-3.18-.47-.92,13.97-2.0M 1,27.94-3.4,41.88-.23,4.2-.81,8.37-1.38,12.54-.53,1.6,.43,5.9-2.18,4.87-5.57-1.9-11.14-3.89-16.81-5.48-.5-.12-1.18,.18-1.25,.56-.34,2.13-.66,4.27-1.02,6.4-2.6,16.78-5.67,33.51-9.01,50.17-.69,3.4-1.48,6.78-2.21,10.18-.11,.52-.25,1.07,.26,1.53,0,0,.06-.02,.06-.02-6.98-.58-13.76-3.02-20.65-4.31-1.22-.31-.87-1.35-.73-2.23,1.43-6.14,2.92-12.27,4.3-18.41,3.87-16.36,6.59-32.97,9.99-49.4,.61-.69,1.81-.04,2.57,.07,4.16,1.24,8.31,2.51,12.47,3.77,4,1.21,4.13,1.62,4.51-2.1,2.58-17.73,4.4-35.56,5.85-53.42,.12-1.28,.4-2.55,.62-3M .82,.05-.26,.29-.38,.61-.31,5.23,1.51,10.16,3.96,15.28,5.8,1.57,.59,1.95,.44,2.06-.83,1.23-17.19,1.18-34.46,1.43-51.67,.76-1.23,2.76,.68,3.77,.83,4.07,1.91,8.12,3.83,12.18,5.75,.48,.23,.97,.34,1.59-.03-.06-15.7-1.64-31.37-2.37-47.04-.02-.3,.56-.55,.88-.39,5.23,2.59,10.26,5.56,15.41,8.3,.52,.2,1.32,.28,1.25-.62-1.3-11.15-2.28-22.35-4.01-33.44,.04-1.39-2.15-9.13-.49-8.92,5.38,2.68,10.32,6.21,15.47,9.29,.42,.28,.93,.62,1.42,.35,.46-.25,.33-.77,.28-1.19-.11-.86-.19-1.72-.33-2.57-1.49-9.19-3.2-18.35-5-27.48-.35-1.81-.82M -3.61-1.07-5.42-.14-1-.86-2.04,.01-3.06,1.27,.16,2.03,.96,2.92,1.56,4.23,2.84,8.41,5.73,12.61,8.6,.83,.43,1.59,1.43,2.61,1.17-1.43-10.43-4.8-20.97-6.97-31.42-.4-1.69-.83-3.38-1.2-5.08-.03-.13,.23-.32,.4-.44,.76-.03,1.6,.85,2.27,1.21,4.88,3.56,9.74,7.13,14.61,10.69,.72,.38,1.4,1.28,2.24,1.23,.1-.03,.24-.13,.24-.2-.02-.64,.03-1.29-.13-1.9-1.13-4.32-2.27-8.64-3.46-12.95-1.58-6.42-4.01-12.75-5.18-19.22,.16-.99,2.27,.92,2.72,1.14,6.11,4.69,12.02,9.64,18.23,14.19,.75,.34,.61-.71,.48-1.14-2.46-8.16-4.94-16.32-7.37-24.49-.M 68-2.3-1.67-4.54-2.01-6.9-.01-.09,.1-.22,.19-.27,.09-.05,.28-.06,.36-.02,.72,.47,1.48,.91,2.12,1.45,6.15,5.13,12.29,10.28,18.43,15.42,.65,.54,1.31,1.08,1.99,1.6,.06,.05,.28,.02,.39-.02,.1-.05,.23-.17,.21-.25-.14-.74-.25-1.49-.48-2.22-2.76-8.54-5.55-17.09-8.33-25.63-.24-1.17-1.14-2.31-.77-3.48,1.34,.38,2.19,1.48,3.23,2.32,6.68,5.92,13.36,11.84,20.04,17.76,1.25,1.09,3.92,3.8,2.7,.04-2.99-9.18-6.24-18.38-9.09-27.59-.03-1.21,2.07,.9,2.34,1.07,5.8,5.39,11.6,10.78,17.38,16.18,3.15,2.95,6.26,5.92,9.4,8.87,.17,.12,.88,.28,M .91-.14-2.67-9.25-5.9-18.34-8.8-27.52-.72-2.43,1.26-.38,2.05,.3,10.5,9.83,20.47,20.04,30.67,30.04,.26,.24,.77-.12,.79-.32-2.17-8.56-5.17-16.93-7.63-25.42-.13-.41-.16-.84-.22-1.26,0-.07,.1-.2,.17-.21,12.48,10.89,23.59,23.86,35.21,35.69,.51,.34,2.73,3.34,3.14,2.3-1.32-7.75-4.16-15.34-6.02-23.03-.14-.53-.31-1.05-.42-1.58-.08-.41-.4-.99,.1-1.21,.64-.29,.86,.38,1.14,.68,14.45,14.93,28.08,30.59,42.33,45.68,.24,.14,.88,.16,.76-.31-1.63-7.97-3.37-15.92-5.17-23.86-.02-.09,.06-.28,.12-.29,.22-.02,.56-.05,.67,.05,.77,.74,1.54M ,1.49,2.24,2.27,6.74,7.54,13.52,15.04,20.18,22.63,8.97,10.23,17.81,20.53,26.73,30.79,.28,.32,.93,.55,1.03,.38,.1-.17,.24-.37,.22-.55-.91-6.85-1.9-13.7-2.82-20.55-.3-2.98,1.51-.55,2.4,.37,18.22,21.16,36.13,42.55,53.85,64.1,.7,1,1.88,1.88,1.85,3.16-.02,6.57-.04,13.14-.09,19.71,0,.13-.32,.28-.51,.38-.64-.17-1.05-.95-1.52-1.4-16.37-20.18-32.83-40.23-49.74-60.09-.76-.66-1.52-2.3-2.63-2.22-.53,.37-.09,1.25-.09,1.79,.87,6.75,1.75,13.5,2.61,20.24,.02,.19-.11,.39-.2,.58-.08,.16-.73-.1-1.01-.41-2.83-3.27-5.57-6.61-8.38-9.9-1M 1.87-14-23.85-27.93-36.13-41.7-.77-.65-1.29-1.94-2.42-1.89-.31,.57,.11,1.82,.16,2.53,1.38,7.35,3.32,14.61,4.39,22-1.2,0-1.61-.99-2.37-1.7-9.42-10.51-18.81-21.02-28.25-31.52-3.3-3.67-6.71-7.29-10.07-10.92-.31-.33-.64-.7-1.29-.6,.05-.26-.01-.3-.19-.13l.27,.07Z"/><path class="cls-2" d="M322.27,493.7c.31-.51,.23-1.05,.13-1.58-.38-2.02-.73-4.05-1.16-6.07-1.48-7.01-2.77-14.04-3.91-21.09-.52-3.31-1.34-6.58-1.65-9.93-.13-1.33,1.01-1.06,1.61-.46,5.49,3.64,10.76,7.64,16.48,10.9,.1,.05,.58-.17,.58-.26,0-.96,.02-1.94-.15-2.89-M .98-5.55-1.64-11.12-2.33-16.7-.78-7.64-2.63-15.53-2.52-23.1,1.03-.28,1.85,.66,2.72,1.07,4.29,2.61,8.58,5.22,12.87,7.83,.7,.32,1.61,1.21,2.36,.63-.32-14.93-2.48-30.1-2.61-45.14-.17-2.76,1.44-1.65,3.02-.8,4.81,2.32,9.41,5.17,14.36,7.18,1.04-.03,.67-1.49,.8-2.2,0-16.38-.37-32.76,.49-49.12,.02-2.38,1.9-1.08,3.25-.62,4.15,1.79,8.28,3.61,12.43,5.39,.78,.19,2.22,1.14,2.85,.41,1.15-14.49,2.08-29.04,3.58-43.52,.72-5.22,.85-10.61,2.03-15.72,.88-.77,2.31,.42,3.3,.51,5.14,1.51,10.13,3.74,15.37,4.83,.64,.04,.9-.71,.97-1.22,.76-M 4.7,1.49-9.4,2.27-14.1,2.17-13.81,4.75-27.53,7.51-41.23,.7-3.94,1.95-7.8,2.35-11.79,.01-.16-.27-.34-.42-.51l-.06,.02c6.36,.36,12.47,2.63,18.71,3.81,3.38,.8,3.33,.35,2.69,3.21-4.61,19.32-8.87,38.72-12.42,58.26-.65,2.96-.75,6.04-1.69,8.93-.54,.84-1.75,.18-2.52,.06-4.17-1.23-8.33-2.48-12.5-3.71-1.19-.13-3.52-1.75-4.2-.25-1.28,7.33-1.93,14.78-2.94,22.16-1.81,12.4-2.36,24.93-3.9,37.34-.04,.24-.68,.5-.97,.4-5.42-1.84-10.61-4.26-16.01-6.15-1.04-.17-1,1.01-1.07,1.72-.24,4.74-.5,9.47-.69,14.21-.36,11.31-.77,22.62-.58,33.93,M .03,3-.03,3.32-.58,3.34-1.46,.05-2.45-.78-3.58-1.29-3.75-1.7-7.43-3.49-11.15-5.24-.67-.19-1.94-1.13-2.32-.14,0,8.08,.44,16.16,.97,24.21,.47,7.42,.94,14.85,1.41,22.27-.12,1.89-2.46-.18-3.3-.41-4.5-2.33-8.81-5.04-13.42-7.14-.12-.04-.52,.16-.58,.3-.13,.29-.17,.63-.14,.94,1.24,11.06,2.25,22.12,4.01,33.12,.38,2.86,1.06,5.74,.97,8.62-.67,.21-1.14,.02-1.58-.25-4.18-2.55-8.35-5.11-12.52-7.66-1.08-.49-2.09-1.72-3.32-1.58-.18,.07-.36,.32-.35,.49,.11,2.38,.57,4.72,.97,7.06,1.19,6.5,2.4,12.99,3.6,19.49,.75,4.05,1.49,8.09,2.2,1M 2.14,.02,.13-.27,.31-.45,.44-5.27-2.49-10.72-7.18-15.84-10.38-.72-.33-1.78-1.66-2.4-.61,1.28,6.45,2.88,12.93,4.32,19.39,1.3,5.61,2.69,11.21,4.02,16.81,.03,.13-.21,.32-.36,.45-1.2-.06-2.16-1.27-3.18-1.86-4.77-3.5-9.53-7-14.29-10.49-.51-.25-1.04-.94-1.63-.82-.68,.37-.35,1.13-.26,1.74,.88,3.37,1.75,6.75,2.69,10.11,1.96,7.04,3.96,14.07,5.94,21.11,.15,.52,.29,1.05-.04,1.64-1.48-.29-2.5-1.51-3.7-2.33-5.19-4.08-10.38-8.16-15.57-12.24-.57-.44-1.05-1-2.1-1.06,2.55,10.48,6.12,20.75,9.27,31.09,.99,3.74-1.7,.74-3.01-.15-6.24-5M .22-12.46-10.45-18.7-15.67-.36-.3-.63-.71-1.24-.72-.1,0-.29,.09-.29,.14,.02,.53-.04,1.07,.11,1.58,1.13,3.66,2.28,7.31,3.47,10.96,1.91,5.83,3.86,11.65,5.79,17.48,.14,.41,.26,.82-.08,1.26-1.2-.37-2.03-1.33-2.96-2.1-6.42-5.67-12.83-11.35-19.24-17.03-1.25-.89-2.2-2.45-3.72-2.84-.22-.03-.38,.44-.26,.81,.36,1.15,.72,2.3,1.1,3.44,2.66,8.01,5.32,16.02,7.99,24.03,.17,.52,.44,1.02,.17,1.56-.59,.01-.99-.26-1.35-.58-1.79-1.61-3.61-3.2-5.36-4.84-6.02-5.66-12.01-11.35-18.03-17.02-1.31-1.23-2.65-2.44-4-3.64-.12-.11-.45-.08-.69-.0M 7-.36,.28,0,1.13,.08,1.55,2.74,8.44,5.49,16.88,8.24,25.31,.11,.58,.62,1.31-.09,1.67-.68-.07-1.21-.86-1.75-1.25-10.61-9.87-20.55-20.32-30.99-30.22-.9-.4-.42,.99-.34,1.43,2.43,7.95,4.88,15.89,7.31,23.84,.09,.53,.42,1.42,.14,1.85-1.15,0-1.77-1.2-2.59-1.84-10.78-10.76-21.33-21.68-31.71-32.69-1.4-1.28-2.24-2.97-4.13-3.65,1.84,8.77,4.81,17.28,6.92,26-.15,1.42-2.38-1.36-2.82-1.68-13.86-14.44-27.13-29.27-40.6-43.92-.12-.12-.47-.11-.72-.12-.04,0-.14,.19-.14,.28,.97,8.11,3.92,15.88,4.84,24.01-1.91-.53-2.73-2.34-4.08-3.6-9.9-M 11.16-19.82-22.3-29.68-33.49-5.04-5.72-9.95-11.53-14.92-17.29-.55-.51-1.03-1.56-1.91-1.44-.34,.19-.32,.8-.26,1.16,.66,4.71,1.33,9.42,1.99,14.13,.31,2.25,.62,4.5,.89,6.75,.02,.14-.2,.42-.34,.43-.23,.03-.59-.05-.72-.18-.73-.77-1.43-1.56-2.12-2.36-6.54-7.64-13.16-15.25-19.61-22.95-11.25-13.42-22.4-26.9-33.59-40.35-.93-1.23-2.36-2.39-2.31-4.03,0-6.36,0-12.71,0-19.07,0-.44,.37-.82,.62-.66,3.21,2.78,5.49,6.67,8.36,9.85,14.33,17.6,28.83,35.12,43.62,52.48,.6,.71,1.29,1.36,1.96,2.03,.12,.09,.59-.03,.62-.21-.43-5.7-1.28-11.3M 6-2.01-17.02,0-1.12-1.77-7.48,.89-4.71,14.36,17.01,28.74,33.88,43.59,50.55,.96,.99,1.57,2.17,2.97,2.66-.8-7.27-2.99-14.46-4.28-21.71-.13-1.03-.61-2.15-.07-3.12,.14-.26,.4-.15,.91,.42,4.62,5.17,9.2,10.36,13.86,15.51,8.76,9.53,17.26,19.34,26.23,28.69,.28,.27,.72-.08,.76-.28-.58-2.43-1.17-4.86-1.79-7.29-1.45-5.7-2.92-11.39-4.37-17.09-.12-.45-.48-1.66,.31-1.64,11.76,11.72,22.88,24.26,34.54,36.17,.47,.49,.83,1.13,1.88,1.19-2.28-9.55-5.5-18.83-7.85-28.42,1.45,.23,1.86,1.2,2.84,2.05,8.34,8.46,16.67,16.93,25.02,25.38,1.33,M 1.35,2.78,2.63,4.19,3.93,.06,.06,.27,.05,.38,.02,.1-.03,.25-.15,.24-.21-.18-.84-.33-1.69-.58-2.52-2.5-8.27-5.02-16.53-7.52-24.79-.16-.52-.21-1.06-.29-1.6-.01-.09,.07-.26,.16-.28,1.03-.31,1.77,1.13,2.54,1.66,7.68,7.37,15.35,14.74,23.03,22.1,.92,.67,1.64,2.01,2.88,2.02,.05,0,.18-.19,.16-.28-.81-2.72-1.64-5.44-2.44-8.16-2.18-7.33-4.35-14.66-6.5-22-.06-.19,.06-.41,.1-.61,.92,.09,1.5,.65,2.09,1.27,3.88,3.58,7.74,7.18,11.66,10.74,3.47,3.16,7,6.27,10.51,9.39,.36,.25,.84,.73,1.32,.58,.1-.05,.2-.19,.18-.28-.51-1.89-1.04-3.7M 8-1.58-5.66-2.37-8.93-5.41-17.8-7.44-26.77,.31-.9,2.1,1.11,2.59,1.38,5.88,5.05,11.74,10.1,17.62,15.15,1,.85,3.63,3.23,2.82,.14-3.07-10.7-5.82-21.45-8.5-32.23-.31-1.03,.76-.89,1.32-.41,2.65,2.15,5.25,4.34,7.91,6.48,3.52,2.83,7.07,5.62,10.62,8.42,.37,.2,1.36,.95,1.54,.26-1.4-7.36-3.45-14.59-5.07-21.9-.93-4.02-1.77-8.06-2.62-12.09-.07-.76-.37-1.96-.08-2.53,.25-.03,.59-.09,.74,0,.93,.62,1.82,1.28,2.7,1.94,4.34,3.23,8.67,6.47,13.02,9.69,.93,.54,1.76,1.6,2.93,1.5,0,.22,.05,.23,.14,.04l-.22,.04Z"/><path class="cls-2" d="MM 811.58,722.43s.07,.03,.1,.04c0,.02-.01,.03-.01,.05l-.09-.09Z"/><path class="cls-2" d="M880.35,724.27c-1.89,3.77-2.87,7.95-4.99,11.58-.9,0-1.26-.48-1.67-.88-2.65-2.59-5.28-5.18-7.94-7.75-.47-.39-1.3-1.14-1.94-.7-1.56,2.93-2.46,6.15-3.73,9.21-.2,.52-.42,1.02-1.1,1.42-3.35-2.32-6.14-5.42-9.38-7.92-.64-.53-1.33-.45-1.53,.17-1.14,3.61-2.29,7.31-3.41,10.9-.75,.08-1.19-.13-1.58-.45-1.9-1.53-3.79-3.06-5.71-4.57-.99-.51-2.72-2.76-3.69-1.32-.97,3.45-1.73,6.98-2.63,10.45-.16,.65-.43,1.54-1.33,1.24-2.86-1.42-5.64-2.97-8.58-4.2M 3-.3-.12-.74,0-1.12,0-1.35,4.16-1.66,8.61-3.06,12.73-.09,.13-.47,.24-.67,.2-2.61-.75-5-2.11-7.53-3.08-2.09-1-2.49,.07-2.73,1.83-.62,3.19-1.24,6.39-1.87,9.57-.13,.63-.22,1.3-1.03,1.8-2.98-.79-5.84-2.14-8.84-2.95-.36-.1-.9,.1-.98,.36-.98,4-1.7,8.06-2.59,12.09-.14,1.05-.48,1.82-1.9,1.31-2.76-.75-5.45-1.95-8.29-2.35-.2,.25-.41,.42-.47,.61-1.08,3.88-1.74,7.84-2.65,11.76-.23,.64-.39,1.77-1.29,1.77-1.94,.12-8.92-3.41-9.61-1.23-1.04,4.54-2.67,9.04-3.36,13.6-3.57-.78-7.14-1.58-10.63-2.6,.01-.01,.01-.03,.02-.04,1.59-4.4,2.34M -9.02,3.59-13.53,.48-1.66,7.44,.96,9.05,1.07,1.03,.23,1.63-.02,1.79-.77,.91-4.24,1.8-8.5,2.71-12.73,.6-1.51,7.76,1.23,9.42,1.4,.31,.08,.94-.16,1-.38,1.39-4.33,1.5-9.06,2.87-13.33,.16-.15,.49-.34,.66-.29,2.93,.78,5.81,1.69,8.75,2.43,.86,.12,1.19-.65,1.33-1.32,.36-2.03,.68-4.06,1.04-6.08,.31-1.81,.65-3.62,.99-5.43,.1-.55,.87-.92,1.51-.72,2.9,.85,5.65,2.06,8.56,2.87,.32,.09,.8-.17,.86-.49,.84-4.15,1.37-8.34,2.55-12.42,.07-.24,.68-.45,.99-.35,2.57,.86,5.02,2.06,7.54,3.09,.81,.37,2.25,1.02,2.54-.24,.63-2.97,1.25-5.95,1.M 9-8.91,.39-.92,.28-3.16,1.68-2.9,3.03,1.37,6,2.84,8.99,4.33,.46,.22,1.16-.01,1.27-.42,.96-3.58,1.96-7.15,2.96-10.71,.4-.95,1.66-.26,2.22,.24,2.16,1.63,4.3,3.26,6.45,4.89,.84,.37,1.95,2.01,2.84,1.15,1.24-3.3,2.36-6.63,3.55-9.93,.28-.76,1.04-.86,1.82-.27,2.98,2.31,5.76,4.85,8.65,7.25,.36,.31,.72,.61,1.48,.59,1.56-2.89,2.8-6.01,4.18-9,.23-.51,.5-1,1.09-1.31,.71,.14,1.13,.57,1.56,.98,3.2,2.85,6.07,6.08,9.42,8.72Z"/><path class="cls-2" d="M892.36,702.54c-2.29,3.42-4.44,6.93-6.43,10.53-2.9-2.66-5.75-5.34-8.67-7.98-.61-.5M 6-1.13-1.22-2.24-1.5-2.14,2.36-3.32,5.59-4.83,8.38-.82,1.81-1.47,1.59-2.69,.56-2.77-2.39-5.64-4.63-8.47-6.94-.47-.38-.93-.8-1.84-.82-2.02,3.27-2.61,7.16-4.55,10.47-.9,.03-1.35-.39-1.84-.75-2.48-1.83-4.94-3.66-7.43-5.48-.72-.43-1.45-1.14-2.37-.89-1.83,3.69-1.87,7.55-3.87,11.24-3.59-1.17-6.61-3.43-10.17-4.67-.43-.16-1.15,.15-1.25,.55-.4,1.58-.78,3.17-1.16,4.75-.72,2.15-.73,4.89-1.99,6.72-3.72-1.03-7.23-2.9-10.88-4.24,.87-4.01,1.72-8.03,2.57-12.04,.12-.58,.8-.81,1.55-.52,2.77,1.09,5.51,2.26,8.26,3.4,1.4,.55,1.91,.55,2M .24-.74,.76-2.95,1.59-5.89,2.38-8.83,.17-.64,.32-1.27,1.11-1.8,3.7,1.32,7.02,3.67,10.72,4.94,.82,.05,.96-.89,1.21-1.46,1-2.68,1.98-5.36,2.97-8.05,.5-1.84,1.74-.8,2.8-.14,2.65,1.83,5.27,3.69,7.9,5.53,.5,.35,.91,.81,1.82,.84,1.9-2.49,2.88-5.71,4.43-8.46,.35-.61,.83-1.79,1.74-1.26,3.69,2.84,7.25,5.79,11.03,8.52,.75,.33,1.26-.58,1.64-1.08,1.75-2.6,3.28-5.47,5.26-7.89,.92,.02,1.34,.45,1.78,.84,3.1,2.76,6.22,5.47,9.27,8.27Z"/><path class="cls-2" d="M907.33,683.85c-2.73,2.88-5.33,5.87-7.8,8.95-2.73-2.42-5.45-4.84-8.18-7.2M 6-.7-.5-1.63-1.67-2.56-1.13-2.34,2.03-4.19,4.4-6.06,6.83-.35,.43-.61,.94-1.28,1.15-4.28-2.66-8.23-6.23-12.28-9.12-.27-.59,.12-.93,.38-1.29,2.12-2.58,3.74-5.64,6.2-7.91,.82-.32,1.66,.56,2.31,.95,3.63,2.71,7.06,5.69,10.79,8.25,.57,.24,1.25-.31,1.65-.66,2.4-2.21,5.21-4.05,7.9-5.92,.87-.04,1.26,.43,1.69,.81,2.42,2.11,4.83,4.23,7.24,6.35Z"/><path class="cls-2" d="M964.38,753.47c-3.1,.91-5.68,3.14-8.6,4.55-.75,.42-1.37,1.03-2.42,1.14-.75-.32-.98-.97-1.34-1.54-2.62-4.12-5.22-8.26-7.88-12.38-.85-1.32-1.53-2.74-2.89-3.82-2.M 13,.4-3.12,1.94-4.59,2.98-1.71,1.21-3.27,2.56-4.81,3.78-.78-.03-1.09-.34-1.37-.73-3.07-4.21-6.06-8.48-9.19-12.65,1.57-2.98,3.3-5.89,5.18-8.7,.93-.71,2.13-2.21,3.14-.73,3.55,4.56,7.04,9.13,10.36,13.85,.33,.46,.58,.97,1.27,1.26,.73,.13,1.16-.35,1.67-.65,2.84-1.64,5.65-3.3,8.47-4.96,.31-.18,.88-.1,1.07,.14,4.11,5.33,7.53,11.15,11.14,16.81,.32,.52,.81,1.02,.79,1.65Z"/><path class="cls-2" d="M964.38,753.47h.14l-.15,.15c.01-.05,.01-.1,.01-.15Z"/><path class="cls-2" d="M964.8,714.1c.06,.11-.2,.45-.37,.48-3.74,.29-7.52,.24M -11.24,.8-1.74,.44,.52,2.11,.89,2.91,3.35,4.78,7.21,9.27,10.22,14.26,.13,.63-.88,.83-1.38,.82-3.41,.06-6.92,.6-10.27,.84-.9-.21-1.13-.75-1.47-1.2-3.33-4.42-6.66-8.85-10-13.27-.68-.67-1.29-2.15-2.43-1.82-2.39,1.13-4.51,2.72-6.83,4.01-1.05,.61-1.7,1.7-3.23,1.76-.14-.08-.26-.16-.38-.26,2.4-3.4,5.03-6.66,7.86-9.75,1.02,1.19,2.14,2.43,3.16,3.56,1.56,.13,2.76-.5,4.09-.64,2.56-.49,5.34-.54,7.77-1.41-.04-.87-.72-1.44-1.23-2.06-1.99-2.37-3.99-4.73-6-7.09,2.82-2.5,5.8-4.84,8.93-7.02,3.89,5.07,8.39,9.77,11.91,15.08Z"/><path cM lass="cls-2" d="M965.39,697.31c-3.41,.22-6.82,.09-10.24,.17,2.45-1.63,4.99-3.16,7.61-4.57,.44,.77,4.29,3.99,2.63,4.4Z"/><path class="cls-2" d="M1387.34,675.7c-.03-1.77-2.29-2.36-3.48-3.32-6.16-3.85-12.29-7.72-18.49-11.52-21.26-13.11-42.81-25.53-64.79-37.55-2.89-1.58-5.81-3.12-8.72-4.68-.55-.3-1.1-.63-1.84-.49-.29,2.49,.64,5.14,.81,7.67,.3,3.62,1.43,7.29,1.19,10.91-.65,.73-2.59-.88-3.36-1.16-10.69-6-21.5-11.88-32.42-17.62-15.02-7.79-30.24-15.54-45.74-22.55-.21-.05-.85,.06-.82,.41,1.07,4.78,2.5,9.47,3.78,14.2,.17,.86M ,.93,2.94-.74,2.4-22.5-10.82-44.93-21.61-68.3-30.64-.68,.72-.15,1.43,.06,2.21,1.67,4.21,3.52,8.36,5.07,12.6,.09,.27-.07,.61-.21,.9-.02,.05-.48,.02-.71-.05-3.66-1.45-7.25-3.1-10.9-4.56l-8.48,9.91c8.24,3.51,16.39,7.15,24.45,10.94,.79,.29,1.63,1,2.53,.79,.29-.09,.33-.31,.24-.55-1.89-4.82-3.8-9.64-5.66-14.48-.06-.16,.13-.39,.24-.56,.83-.07,1.74,.52,2.55,.77,21.59,9.5,42.37,19.85,63.09,30.81,.45,.12,2.22,1.28,2.33,.42-.45-3.41-1.83-6.72-2.62-10.09-.58-2.1-1.12-4.21-1.64-6.32-.03-.13,.25-.32,.43-.46,.99-.07,2.55,1.03,3.5M 3,1.41,25.78,12.99,50.85,27.42,75.71,41.93,.84,.11,.73-.92,.67-1.48-.71-5.57-1.89-11.09-2.26-16.7-.03-.49,.72-.71,1.08-.51,13.88,7.67,27.32,16.1,40.93,24.21,17.52,10.49,34.26,21.92,51.32,33.01,.43,.14,1.08,0,1.13-.5,.11-6.57,.04-13.14,.04-19.71Zm-286.57-79.64c-.83-1.59-1.61-3.19-2.41-4.79-.22-.35,.38-.62,.68-.54,7.35,2.44,14.47,5.58,21.62,8.45-9.79-8.1-19.98-15.92-30.55-23.43,2.08,4.25,4.44,8.35,6.57,12.57,.14,.26,.31,.67,.11,.89-.22,.08-.53,.22-.71,.16-15.69-5.6-31.36-10.94-47.47-15.47-.62-.17-1.28-.26-1.93-.36-.0M 8-.01-.3,.13-.29,.19,.02,.31,0,.65,.17,.91,2.07,3.15,4.18,6.27,6.26,9.41,.32,.67,1.25,1.66,1.2,2.32-.21,.11-.51,.28-.69,.23-14.04-3.7-28.13-8.91-42.48-10.9-.29,.49,.63,1.24,.83,1.71,2.24,2.95,4.49,5.89,6.73,8.83,.27,.36,.44,.73,.25,1.14-.95,.2-1.83-.08-2.72-.3-11.04-2.77-22.26-5.36-33.54-7.09-.19,0-.76,.35-.53,.64,2.9,3.36,5.96,6.62,8.77,10.06,.06,.07,.08,.26,0,.3-.62,.49-1.51,.21-2.22,.11-8.45-1.85-17.1-2.93-25.7-4.23-1.12-.08-2.48-.34-3.55-.08-.29,.93,.92,1.49,1.41,2.17,2.38,2.34,4.82,4.63,7.16,7.01,.17,.23,.63,.M 54,.39,.85-.15,.13-.37,.34-.53,.33-3.07-.32-6.14-.62-9.19-1.02-5.71-.59-11.49-1.41-17.21-1.46-.25,.5,.04,.84,.41,1.17,2.78,2.49,5.55,4.98,8.32,7.48,.3,.37,1.1,.84,.99,1.3-.64,.72-1.72,.24-2.57,.28-6.18-.46-12.36-.78-18.56-.89-.64,0-1.45-.2-1.85,.32-.45,.59,.35,.94,.76,1.31,2.78,2.35,5.63,4.65,8.4,6.99,1.66,1.47,.71,1.73-.99,1.66-5.39-.31-10.77-.02-16.15,.16-1.03,.17-2.47,0-1.13,1.34,3.1,2.55,6.22,5.08,9.32,7.63,.36,.29,.88,.56,.75,1.05-.15,.58-.83,.44-1.31,.47-5.15,.41-10.48,.46-15.56,1.34-.24,.57,.08,.9,.47,1.22,3M .45,2.87,7.11,5.52,10.37,8.59,.21,.19-.04,.74-.37,.79-1.98,.31-3.96,.59-5.94,.93-2.5,.42-4.99,.87-7.49,1.32-.61,.11-.84,.62-.45,.96,3.93,3.41,7.96,6.73,11.91,10.12,.54,.46,1.22,.86,1.37,1.61-1.03,1.28-14.06,2.12-12.7,4.04,4.23,3.75,8.58,7.41,12.7,11.28,.22,.21,.23,.55,.37,.89-3.98,1.15-8.02,1.98-11.69,3.63,1.18,1.85,3.11,2.94,4.58,4.53,2.82-2.56,5.76-5.01,8.81-7.36-.79-.85,1.07-1.17,1.65-1.24,2.54-1.9,5.15-3.72,7.84-5.46-3.26-3.15-6.63-6.21-9.84-9.4-.11-.12,.02-.39,.05-.66,4.67-1.03,9.53-1.16,14.25-1.48,.46-.49,.31M -.88-.07-1.23-4.08-3.72-8.12-7.51-12.27-11.16-.44-.44-1.24-1.2-.18-1.51,4.57-.27,9.14-.53,13.7-.79,2.75-.05,2.91-.31,.84-2.21-2.61-2.32-5.26-4.62-7.88-6.94-.44-.39-.83-.84-1.17-1.29-.06-.08,.18-.39,.37-.49,6.27-.41,12.64,.06,18.92,.4,.09-.27,.27-.52,.19-.63-.43-.54-.88-1.08-1.41-1.56-2.83-2.6-5.82-5.06-8.58-7.74-.13-.14-.17-.42-.08-.58,.07-.15,.38-.32,.58-.32,7.01,.08,13.94,.89,20.86,1.83,.35,.02,.91,.07,1.17-.11,.03-.19,.11-.47-.02-.59-2.8-2.75-5.63-5.49-8.44-8.24-.49-.48-1.54-.94-1.16-1.56,.52-.83,1.68-.29,2.53-.M 21,8.12,.66,16.09,2.67,24.17,3.39,.05-.81-.59-1.27-1.08-1.77-2.31-2.38-4.66-4.74-6.99-7.11-.33-.34-.66-.68-.97-1.03-.29-.34-.72-.72-.4-1.11,.13-.16,.77-.13,1.14-.07,8.02,1.42,16.04,2.82,23.91,4.7,1.81,.44,3.65,.78,5.48,1.13,.15,.03,.4-.18,.55-.31,.07-.06,.06-.23,0-.31-1.72-2.05-3.46-4.1-5.19-6.16-1.21-1.42-2.42-2.84-3.6-4.28-.1-.21,.13-.73,.49-.64,10.66,2.14,21.21,4.88,31.6,7.85,1.32,.2,3.01,1.26,4.23,.6-2.37-4.1-6.14-7.68-8.34-11.71,.19-.12,.46-.29,.64-.25,1.3,.26,2.61,.52,3.87,.87,12.09,3.35,24.01,7.05,35.78,11.0M 6,.72,.19,1.47,.72,2.18,.23-1.44-3.63-4.42-6.88-6.46-10.33-.44-.66-.84-1.34-1.21-2.04-.09-.15-.04-.44,.1-.54,.15-.11,.51-.16,.71-.09,6.34,2.11,12.71,4.16,19,6.37,9.92,3.35,19.48,7.39,29.22,11,1.81,.16-3.62-7.92-3.89-9.05Zm-82.05-8.64s.08-.03,.12-.05c0,.19-.04,.21-.12,.05Z"/><path class="cls-2" d="M660.77,307.26c-1.02-1.05,.27-2.26,.68-3.31,6.82-12.72,14.57-25.08,22.03-37.51-.42-.1-.84-.32-1.09-.23-2.57,.93-5.13,1.9-7.67,2.89-3.63,1.41-7.25,2.85-10.87,4.29-.35,.14-.8,.35-1.03,0-.15-.23-.1-.64,.05-.89,3.58-6.03,7.09-M 12.09,10.8-18.07,5.55-9.2,11.74-18.09,17.11-27.4-1.33-.5-2.56,.39-3.87,.64-5.4,1.66-10.8,3.34-16.2,5-.61,.1-1.68,.69-1.95-.11,10.34-18.1,22.78-35.2,34.13-52.74,.23-1.07-2.94,.09-3.55,.04-6.25,1.32-12.48,2.67-18.73,3.99-.43,.11-1.04-.16-.88-.67,12.49-20.08,26.27-39.43,40.16-58.63,.46-.64,.83-1.34,1.2-2.02,.13-.24-.05-.45-.37-.47-.53-.03-1.07-.07-1.59-.01-6.94,.78-13.86,1.65-20.8,2.39-1.68,.37-2.61-.24-1.26-1.71,11.54-16.6,23.19-33.11,35.28-49.36,4.45-6.03,9.06-11.98,13.6-17.97,.21-.28,.47-.53,.63-.83,.6-1.22,2.02-1.M 31,3.37-1.27,7.41-.01,14.82-.03,22.24-.03,.66,0,1.33,.09,1.97,.21,.15,.03,.38,.39,.31,.51-17.37,22.13-35.49,43.81-51.64,66.73-.13,.21,.32,.69,.64,.67,.94-.04,1.89-.04,2.81-.14,6.81-.71,13.6-1.58,20.42-2.18,.21-.02,.54,.11,.64,.26,.1,.15,.08,.43-.03,.59-1.51,2.04-3.02,4.08-4.59,6.08-13.05,16.73-25.6,33.56-37.62,50.89-.27,.46-.95,1.38-.11,1.58,7.22-1.25,14.35-2.9,21.53-4.36,2.54-.38,.93,1.06,.2,2.2-3.46,4.74-6.94,9.48-10.4,14.22-8.13,11.59-16.97,23.01-23.97,35.06,.23,.08,.52,.21,.73,.16,1.53-.41,3.05-.85,4.56-1.3,4.9M 2-1.47,9.83-2.94,14.75-4.41,.63-.09,1.63-.7,2.06,.03-9.05,13.86-19.07,27.47-27.77,41.55-.45,.96-1.49,1.83-1.38,2.9,.03,.21,.6,.25,1.1,.06,5.72-2.18,11.44-4.33,17.17-6.48,.73-.27,1.5-.48,2.25-.7,.15-.02,.46,.27,.42,.43-7.76,12.42-16.29,24.43-23.73,37.06-1.75,2.93,.23,1.91,2.16,1,5.17-2.31,10.34-4.63,15.52-6.93,.45-.2,.99-.26,1.5-.35,.07-.01,.28,.15,.27,.21-.67,1.9-2.06,3.5-3.07,5.25-5.4,8.31-10.38,16.79-15.43,25.25-1.7,3.06-3.15,4.82,1.78,2.25,4.8-2.39,9.58-4.81,14.39-7.2,.44-.22,.97-.33,1.47-.46,.06-.02,.3,.15,.28,M .2-1.7,4-4.58,7.51-6.62,11.36-3.34,5.76-6.6,11.55-9.86,17.34-.15,.26-.05,.61-.03,.92,0,.06,.2,.17,.25,.15,7.11-3.51,13.83-7.88,20.81-11.68,1-.44,2.36-1.44,3.41-1.52,.1,.18,.27,.42,.2,.57-.46,.89-1,1.76-1.49,2.64-3.98,7.07-7.97,14.13-11.93,21.21-.26,.47-.7,.93-.51,1.5,.03,.08,.22,.19,.26,.18,8.45-4.23,16.26-9.65,24.61-14.09,.16,.26,.41,.47,.35,.59-.32,.7-.68,1.4-1.08,2.07-3.75,6.33-6.96,12.84-10.37,19.28-.21,.39-.44,.79,.04,1.3,7.88-4.63,15.87-9.21,23.95-13.65,1.96-1.01,1.74-.05,.98,1.43-3.26,5.9-6.67,11.72-9.63,17.M 78-.13,.25-.12,.47,.19,.54,1.37,.03,2.48-1.22,3.71-1.74,5.91-3.39,11.82-6.79,17.75-10.15,1.42-.8,2.94-1.49,4.45-2.19,.12-.06,.44,.14,.73,.25-3.23,5.64-6,11.51-8.95,17.29-.11,.22,0,.4,.31,.49,8.94-4.02,17.43-9.5,26.45-13.59,.65-.22,1.22-.17,.88,.79-2.56,4.85-5.33,9.61-7.56,14.62-.09,1.73,3.25-.76,4.01-.95,6.73-3.37,13.45-6.77,20.36-9.91,1.4-.64,2.84-1.22,4.27-1.81,.3-.13,.54-.04,.66,.21-1.47,4.79-4.91,9.27-6.76,14.07-.06,.15,.14,.38,.27,.54,.83,.02,1.75-.56,2.54-.82,10.12-4.51,20.59-8.48,30.91-12.67,.93-.24,1.99-1,2M .93-.48,.07,.03,.1,.2,.06,.27-.35,.7-.69,1.4-1.07,2.08-1.79,3.25-3.6,6.49-5.39,9.75-.16,.47-.61,1.03-.38,1.51,.13,.24,.37,.33,.66,.23,1.36-.46,2.74-.89,4.08-1.39,10.51-3.89,21.05-7.71,31.81-11.15,1.13-.21,2.29-1.1,3.4-.46-1.97,4.34-4.65,8.45-6.58,12.8,.89,.61,1.74,.02,2.66-.17,13.66-4.28,27.49-8.43,41.48-11.74l-.07-.12c-2.13,3.8-4.09,7.69-6.08,11.56-.2,.58-.96,1.75,.02,1.9,15.7-3.68,31.45-7.15,47.38-10.16l-.09-.08c-1.61,3.68-3.54,7.21-5.35,10.79-.33,.84-1.66,2.59,.1,2.6,14.11-2.36,28.3-4.29,42.51-6.03,2.79-.34,5.61M -.55,8.42-.78,.3-.02,.64,.19,1.05,.33-1.21,3.07-2.69,5.89-4.07,8.87-2,4.21-2.07,3.85,3.5,3.56,10.85-1.02,21.73-1.5,32.61-1.9,6.73-.31,13.45-.59,20.18-.52,.62,.08,1.8-.16,1.96,.63-1.2,4.1-3.38,7.9-4.64,11.99-.17,1.6,3.73,.79,4.83,1.05,21.34,.64,42.78,1.17,63.98,3.77l-.13-.08c-1.69,4.73-2.86,9.71-4.85,14.29l.13-.09c-23.16-2.39-46.38-4.12-69.67-4.52l.11,.09c3.13-7.83,4.43-11.51,4.58-13.01,.01-.1-.08-.2-.16-.4-18.81-.34-37.67,.56-56.45,1.73-.66-.08-2.7,.41-2.64-.69,1.31-3.63,2.89-7.17,4.32-10.75,.56-1.86-4.5-.61-5.51-.M 71-15.34,1.55-30.6,3.66-45.82,6.05-.52,.08-1.08-.38-.94-.77,1.24-3.32,2.86-6.5,4.26-9.75,1.37-2.83-1.53-1.57-3.12-1.44-13.43,2.7-26.87,5.32-40.15,8.66-.77,.03-3.02,1.03-3.09-.14,1.26-3.67,3.19-7.08,4.75-10.62,.37-1.32-.54-1.29-1.85-.9-12.84,3.44-25.75,7.01-38.29,11.22-.59,.2-1.28,.25-1.92,.35-.07,.01-.27-.16-.25-.23,.92-3.73,3.08-7.1,4.51-10.67,1.42-2.49-.84-1.58-2.25-1.13-5.44,1.87-10.92,3.68-16.31,5.63-6.13,2.22-12.2,4.55-18.3,6.84-.63,.29-2.07,.8-1.9-.36,1.56-3.56,3.34-7.04,4.97-10.58,.13-.63,1.06-1.67,0-1.9-11.M 54,3.97-22.74,9.28-33.92,14.08-.45-.46-.42-.87-.24-1.29,1.68-4.09,3.51-8.12,5.09-12.25,.02-.07-.1-.19-.2-.26-.69-.23-1.76,.56-2.46,.77-7.89,3.73-15.53,7.76-23.19,11.78-1.28,.68-3.7,2.18-2.43-.63,1.85-4.38,4.05-8.63,5.66-13.09-.32-.76-1.46,.15-1.97,.31-5.11,2.8-10.24,5.59-15.3,8.44-3.26,1.61-6.06,4.15-9.45,5.34-.36-.47-.11-.87,.06-1.27,2.09-4.77,4.19-9.54,6.27-14.32,.85-2.51-2.72,.34-3.53,.68-6.56,3.96-13.12,7.92-19.67,11.88-.72,.37-1.53,1.16-2.36,1.05-.15-.07-.26-.4-.19-.56,2.34-5.53,5.11-10.88,7.64-16.33,.76-1.51,M .53-1.99-1.08-1.17-7.47,4.2-14.43,8.95-21.6,13.58-.48,.31-1.02,.95-1.65,.54-.6-.39-.02-1.02,.19-1.49,2.44-5.36,4.75-10.76,7.51-16.02,.83-1.92,2.49-4.34-.93-2.22-6.13,3.87-12.25,7.76-18.37,11.64-1.05,.67-2.11,1.34-3.19,1.98-.14,.08-.47,0-.69-.05-.07-.01-.15-.19-.12-.27,.25-.61,.49-1.23,.79-1.83,3.19-6.52,6.39-13.03,9.58-19.54,.92-1.96,.68-2.39-1.27-1.24-5.18,3.27-10.35,6.56-15.52,9.84-1.9,1.2-3.79,2.41-5.71,3.6-.18,.07-.86,.03-.79-.34,3.65-9.07,9-17.47,13.08-26.39,.04-.15-.31-.41-.49-.33-.7,.32-1.42,.61-2.07,.99-5.0M 4,2.88-10.01,5.86-15.06,8.71-1.47,.46-.23-1.64-.02-2.22,4.49-9.46,9.56-18.75,14.69-27.99,.16-.63-.18-1.03-1.08-.53-5.77,2.96-11.45,6.06-17.2,9.07-.15,.08-.48-.04-.71-.11-.29-.43,.28-1.04,.42-1.48,5.62-10.54,11.28-20.98,17.5-31.24,.49-1.01,2.46-3.34-.17-2.48-5.94,2.95-12.25,5.31-17.96,8.65h.05Z"/><path class="cls-2" d="M657.28,1058.23c8.98-4.12,17.66-8.8,26.41-13.35,.55-.29,1.07-.66,1.81-.44l-.09-.07c.34,.65,.03,1.26-.23,1.86-1.38,3.13-2.77,6.25-4.17,9.38-.51,1.2-1.31,2.32-1.2,3.67-.3,.04-.32,.08-.07,.14v-.2c.55,.16M ,1.02-.01,1.47-.27,2.09-1.17,4.18-2.34,6.29-3.48,5.67-3.07,11.33-6.15,16.68-9.57,.82-.53,1.89-1.2,2.8-.49l.06-.08c-.78,.64-.99,1.51-1.34,2.31-1.38,3.15-2.71,6.31-4.07,9.46-1.96,4.49-3.11,5.98,2.25,2.59,6.12-3.7,12.24-7.4,18.36-11.11,.98-.43,2.24-1.86,3.3-1.51,.26,.31,.13,.61,0,.91-2.35,5.16-4.87,10.26-7.28,15.4-.2,.67-.94,1.46-.29,2.05,.04,.05,.29,.04,.38-.01,8.21-4.6,15.88-9.97,23.89-14.88,.17,.26,.39,.45,.35,.58-.3,.82-.63,1.64-.99,2.45-2.48,5.57-5,11.14-7.85,16.6-.2,.38-.53,.75-.32,1.2,.04,.08,.22,.2,.26,.18,.47M -.19,.98-.35,1.39-.61,6.65-4.21,13.29-8.43,19.93-12.65,.84-.43,1.72-1.25,2.64-1.39,.62,.75-.46,1.87-.7,2.68-2.95,6.01-5.9,12.01-8.85,18.02-.39,.8-.73,1.61-1.07,2.43-.03,.08,.06,.2,.11,.29,.11,.21,.37,.3,.64,.13,3.11-1.88,6.24-3.75,9.3-5.68,4.33-2.73,8.61-5.52,12.93-8.27,.13-.08,.47,.01,.7,.06,.3,.3-.16,.83-.25,1.18-3.63,7.92-7.74,15.62-11.8,23.33-.36,.69-.66,1.4-.97,2.11-.03,.08,.04,.25,.11,.27,1.1,.31,2.06-.77,3.03-1.16,4.25-2.47,8.48-4.95,12.73-7.42,.75-.44,1.39-1.04,2.39-1.13l-.06-.09c.41,.88-.12,1.62-.5,2.42-4.M 09,8.61-8.57,17.09-13.29,25.49-.52,1.08-1.51,2.04-1.41,3.29l-.12-.07c1.58,.05,2.83-1.06,4.2-1.69,4.13-2.21,8.25-4.43,12.38-6.63,.75-.28,1.6-.99,2.41-.88,.09,.07,.21,.2,.18,.27-.31,.71-.61,1.42-.97,2.11-5.43,10.28-11.03,20.5-17.09,30.56-.41,.67-.76,1.37-1.07,2.08-.07,.15,.1,.38,.22,.56,5.95-1.94,11.63-5.35,17.46-7.83,.58-.27,1.14-.58,1.86-.35l-.09-.06c.2,.56-.05,1.05-.33,1.55-4.01,7.06-7.95,14.14-12.05,21.16-3.19,5.46-6.6,10.84-9.9,16.26-.23,.38-.37,.8-.52,1.21-.02,.06,.11,.19,.21,.25,.83,.19,1.75-.44,2.57-.64,4.96-M 1.94,9.91-3.89,14.86-5.84,.95-.24,1.91-1.11,2.9-.64,.08,.03,.15,.19,.12,.26-.23,.5-.45,1.01-.73,1.5-8.29,15.12-18.76,29.66-27.1,44.62,.07,.08,.23,.2,.3,.18,.9-.21,1.81-.42,2.68-.69,5.4-1.66,10.8-3.34,16.2-5,.93-.2,1.79-.74,2.68-.11-10.61,18.11-22.71,35.48-34.36,52.94,.81,.47,1.46,.34,2.11,.2,6.37-1.37,12.73-2.77,19.1-4.14,.67-.1,2.3-.56,2.11,.48-9.1,14.78-19.09,28.96-29.05,43.24-3.64,5.16-7.38,10.27-11.06,15.41-.46,.65-.83,1.34-1.2,2.02-.25,.58,.8,.51,1.14,.53,6.94-.77,13.86-1.62,20.8-2.36,1.94,0,3.71-.53,1.91,1.96M -16.21,23.36-32.68,46.57-50.21,69-8.32,.47-16.69,.07-25.03,.19-.68,0-1.83,.05-1.97-.65,16.6-21.39,34.08-42.35,49.78-64.21,.68-.92,1.31-1.88,1.94-2.82,.17-.25-.21-.74-.53-.72-1.87,.12-3.74,.37-5.61,.56-4.8,.55-9.59,1.12-14.39,1.65-.86-.07-4.46,.89-3.99-.61,12.06-15.94,24.37-31.75,35.83-47.98,2.07-2.9,4.1-5.82,6.12-8.74,.32-.46,.55-.97,.75-1.48,.03-.08-.3-.37-.47-.37-6.8,1.15-13.54,2.84-20.32,4.17-.71,.03-1.67,.45-2.33,.12-.09-.18-.21-.43-.13-.56,.49-.76,1.03-1.51,1.58-2.25,11.62-16.01,23.47-31.86,33.9-48.46-.75-.5-1M .48-.12-2.26,.08-6.55,1.74-13.08,4.4-19.66,5.61-.64-.61,.38-1.38,.67-1.96,7.31-10.06,14.05-20.36,20.87-30.63,2.59-3.9,5.02-7.86,7.51-11.79,.15-.23,.05-.44-.23-.54-1.92-.01-3.67,1.27-5.5,1.8-4.89,1.77-9.71,3.79-14.66,5.39-.24,.04-.94-.12-.73-.46,8.27-12.7,16.96-25.14,24.33-38.27,.06-.13-.14-.37-.27-.53-.04-.05-.27-.04-.37,0-5.94,2.49-11.76,5.23-17.67,7.8-.45,.2-.99,.29-1.49,.4-.07,.01-.29-.15-.28-.21,.57-1.92,2.04-3.49,3.02-5.24,5.95-9.42,11.84-18.78,17.15-28.5,.01-.33-.37-.64-.76-.39-5.88,2.8-11.66,5.81-17.5,8.68-.M 32,.08-1.15,.42-1.35-.01,4.39-8.02,9.55-15.66,13.85-23.68,.93-1.67,1.82-3.36,2.69-5.05,.27-.52,.16-1.06-.26-1.52,.07,.05,.13,.09,.2,.13-.22,.06-.24,0-.06-.17-7.03,4.98-15.08,8.67-22.5,13.12-2.84,1.46-2.09,.13-.96-1.71,4.14-7.37,8.27-14.73,12.4-22.1,.15-.4,.75-1.16,.41-1.48-.75-.31-1.36,.34-2,.64-6.4,3.76-12.8,7.53-19.21,11.29-.98,.57-1.96,1.14-2.98,1.67-.16,.08-.55,.05-.69-.05-.41-.72,.74-1.9,1.02-2.63,3.59-6.03,6.64-12.24,9.87-18.4,1.31-2.54-.57-1.62-1.93-.69-6.85,4.37-14.19,8.2-21.34,12.24-2.41,1.22-2.06,.19-1.09M -1.64,3.13-5.71,6.48-11.33,9.32-17.18,.12-.25-.06-.59-.12-1.06-7.5,4.15-14.74,8.42-22.18,12.63-1.09,.62-2.26,1.17-3.4,1.75-.29,.14-.53,.09-.65-.11-.24-.49,.33-1.02,.48-1.5,2.62-5.07,5.25-10.14,7.87-15.22,.21-.4,.41-.8-.04-1.3-6.91,3.43-13.62,7.26-20.48,10.82-1.91,1.01-3.88,1.94-5.83,2.9-.46,.23-.91,.21-1.08,.03-.3-.32-.09-.61,.06-.89,1.58-2.97,3.2-5.93,4.76-8.91,.94-1.79,1.82-3.59,2.67-5.4,.12-.25-.08-.59-.13-.9-8.32,3.41-16.12,7.89-24.31,11.65-1.48,.6-3.08,1.57-4.63,1.82-.12-.17-.3-.39-.24-.54,2.08-4.45,4.44-8.78,M 6.63-13.18,.2-.4,.27-.83-.21-1.3-11.87,4.75-23.78,10.46-35.92,14.33-.1-.18-.27-.42-.2-.56,2-3.89,4.25-7.67,6.31-11.53,.31-.58,.46-1.22,.66-1.84,.02-.06-.16-.22-.26-.22-13.02,4.02-25.62,9.68-38.89,13.29-.19,.04-.47-.12-.67-.22-.18-.56,.55-1.52,.76-2.11,1.76-3.49,3.9-6.82,5.39-10.43,.06-.15-.14-.38-.27-.55-13.58,3.73-27.11,8.33-40.96,11.68-.76,.19-.75,.21-2-.14,2.11-3.83,4.02-7.75,5.98-11.64,.38-.75-.53-.87-1.06-.89-11.63,2.69-23.23,5.53-35,7.78-3.53,.62-7.03,1.67-10.62,1.88-1.19-.25-.03-1.55,.18-2.21,1.63-3.3,3.51-6M .49,4.88-9.91,.18-.75-.86-.73-1.35-.66-9.64,1.55-19.27,3.17-28.96,4.38-4.52,.59-9.04,1.16-13.57,1.7-2.86,.15-5.86,1.04-8.68,.57-.17-.87,.38-1.53,.69-2.22,1.1-2.43,2.28-4.84,3.41-7.25,.41-1.15,2.2-3.35-.28-3.28-12.35,.86-24.7,1.8-37.08,2.13-6.06,.2-12.11,.6-18.18,.52-.8-.01-1.61-.06-2.4-.15-.16-.02-.41-.32-.38-.46,1.09-4.23,3.71-8.04,4.58-12.32,.05-.26-.11-.44-.42-.48-3.86-.47-7.79-.31-11.68-.44-18.92-.58-38-1.17-56.75-3.58l.15,.14c1.91-4.66,3.2-9.56,4.88-14.31l-.12,.09c23.14,2.58,46.4,3.98,69.68,4.52l-.11-.09c-1.54M ,4.12-3.08,8.25-4.61,12.37-.21,.56,.26,1.04,1.01,1.08,10.64,.2,21.29-.28,31.92-.56,8.47-.36,16.92-1.04,25.4-1.35,.37-.02,.81,.36,.75,.62-.98,3.81-2.92,7.37-4.23,11.09-.11,.28,.27,.69,.61,.7,16.96-1.07,33.81-3.92,50.62-6.36,.63-.09,1.06,.28,.89,.74-1.15,3.12-2.65,6.1-3.96,9.15-.29,.77-1.34,2.34,.16,2.4,14.94-2.45,29.74-5.92,44.47-9.4,.45-.03,1.17-.2,1.41,.19-1.22,3.98-3.51,7.65-5,11.56-.12,.28,.36,.61,.76,.52,8.74-2.04,17.32-4.73,25.93-7.18,5.06-1.45,9.98-3.28,15.04-4.69,1.16-.03,.58,1.14,.31,1.8-1.42,3.14-2.85,6.27M -4.26,9.41-.08,.34-.53,1.34,.02,1.42,4.33-.91,8.5-2.71,12.7-4.07,8.61-2.93,17.04-6.73,25.69-9.29,.62,.51,.15,1.2-.07,1.79-1.62,3.42-3.25,6.84-4.89,10.26-.2,.41-.33,.82,.12,1.22,11.7-4.03,22.99-9.58,34.27-14.16,.11,.05,.24,.18,.23,.25-.15,.63-.26,1.28-.51,1.88-1.41,3.37-2.87,6.72-4.3,10.08-.26,.61-.52,1.23-.09,1.85-.07-.09-.14-.17-.2-.25l.2,.19Z"/><path class="cls-2" d="M555.62,1219.39c-.99-1.21,.96-2.1,1.6-2.98,7.4-7.4,14.81-14.8,22.21-22.2,.42-.58,1.48-1.05,1.14-1.84-.02-.06-.25-.13-.34-.1-11.26,3.15-22.38,6.82-33M .6,10.15-.88,.27-1.78,.5-2.68,.71-.15,.03-.41-.17-.56-.29,6.26-7.42,13.83-14.29,20.52-21.53,.3-.45,2.03-1.94,.98-2.07-4.34,1.04-8.56,2.56-12.81,3.88-7.85,2.57-15.83,4.85-23.83,7.1-.63,.18-1.25,.4-1.91,.04,.05-.81,.8-1.33,1.36-1.91,5.72-6.37,12.2-12.27,17.55-18.9-.56-.28-1.09-.24-1.6-.09-3.04,.88-6.08,1.75-9.1,2.65-9.46,2.82-19.07,5.29-28.63,7.88-.57,.2-1.39,.33-1.91,.1-.7-.45,1.48-2.09,1.78-2.63,4.26-4.71,8.52-9.42,12.76-14.15,.61-.68,1.42-1.29,1.55-2.2-.78-.32-1.55,0-2.31,.18-11.2,3.09-22.59,5.7-33.9,8.5-2.3,.57-4M .6,1.22-7.02,1.43-.2,.02-.45-.15-.63-.27,0-.97,1.21-1.69,1.73-2.47,4.1-4.81,8.44-9.42,12.37-14.36,.2-1.29-3-.06-3.73-.03-14.45,2.97-28.85,6.51-43.43,8.67-1.12-.1,.51-1.67,.75-2.14,3.29-4.07,6.61-8.12,9.9-12.19,1.78-2.11,1.78-2.79-1.19-2.26-12.44,2.39-25.04,4.15-37.6,6.06-3.57,.54-7.17,.93-10.76,1.38-.25,.03-.72-.05-.74-.12-.22-.8,.4-1.41,.85-2.01,3.25-4.47,6.69-8.81,9.8-13.37,.16-.24-.21-.71-.56-.68-5.9,.35-11.73,1.31-17.6,1.93-13.24,1.27-26.49,2.51-39.77,3.36l.06,.11c2.63-4.5,5.53-8.83,8.38-13.21,2.08-3.14,1.69-3.M 19-2.22-3.03-20.4,.87-40.81,1.6-61.24,1.27l.09,.1c2.32-5.29,5.41-10.25,7.79-15.52,.2-.4-.19-.92-.72-.95-2.01-.11-4.01-.28-6.02-.29-22.53-.46-45.03-2.07-67.48-4.03l.14,.11c2.14-5.86,4.22-11.74,6.44-17.58l-.11,.09c25.19,3.46,50.75,4.12,76.13,5.85l-.15-.09c-1.9,4.75-4.43,9.24-6.62,13.86-.29,.65-.91,1.68,.16,1.94,18.02,.81,36.11,.21,54.14-.29,3.23-.1,6.46-.23,9.69-.34,.71-.02,1.16,.58,.86,1.13-2.46,4.2-5.06,8.33-7.59,12.49-.52,.8-1.08,1.9,.57,1.86,13.42-.78,26.85-1.79,40.2-3.24,5.34-.53,10.67-1.33,16.03-1.56,.35,0,.79,M .43,.65,.65-3.02,4.86-6.62,9.35-9.71,14.16-.17,.26,.18,.7,.54,.66,2.27-.24,4.55-.42,6.79-.75,14.85-2,29.6-4.63,44.39-6.94,.35-.04,.76,.42,.59,.66-3.19,4.67-6.86,9-10.25,13.53-.41,.53-.92,1.04-.92,1.79,7.26-.63,14.43-2.7,21.62-3.97,8.07-1.69,16.18-3.3,24.13-5.34,.59-.07,1.4-.36,1.94-.09,.1,.16,.25,.4,.17,.53-.43,.67-.9,1.32-1.41,1.96-3.61,4.54-7.43,8.94-10.92,13.58-.06,.08-.09,.27-.03,.31,.73,.62,1.74,.04,2.57-.05,12.66-2.98,25.22-6.2,37.68-9.67,1.43-.22,2.9-1.18,4.31-.58-4.22,5.45-8.91,10.5-13.32,15.79-.45,.53-.84,M 1.08-1.24,1.64-.05,.07,0,.22,.06,.29,.75,.34,1.87-.2,2.68-.3,13.02-3.22,25.81-7.97,38.65-11.08,.09,.16,.23,.41,.14,.52-.55,.74-1.13,1.46-1.75,2.16-4.35,4.93-8.71,9.85-13.06,14.78-.54,.61-1,1.27-1.47,1.91-.04,.06,0,.2,.05,.25,.63,.35,1.61-.13,2.28-.23,12.24-3.68,24.43-8.35,36.67-11.62,.29,.12,.2,.51-.35,1.12-5.98,6.96-12.51,13.47-18.56,20.36-.07,1.12,1.45,.3,2.06,.2,11.82-3.89,23.84-7.26,35.29-11.96l-.12,.07c.34,.37,.53,.77,.18,1.18-.76,.89-1.53,1.77-2.33,2.63-6.31,7.15-13.68,13.84-19.43,21.26,.07,.08,.25,.19,.33,.1M 7,.89-.24,1.78-.48,2.64-.77,9.65-3.28,19.29-6.57,28.93-9.85,1.09-.23,2.23-1.08,3.34-.65,.09,.52-.76,1.19-1.05,1.66-7.85,8.81-15.99,17.7-24.73,25.86,.3,0,.33,.04,.11,.12l-.03-.22c1.44,.79,3.09-.36,4.54-.67,8.33-2.76,16.65-5.54,24.97-8.31,.62-.21,1.2-.5,1.9-.17-7.52,9.73-16.62,18.51-25.08,27.66-.9,.93-1.73,1.9-2.58,2.87-.05,.06,0,.21,.07,.29,.07,.08,.23,.18,.31,.17,.78-.17,1.56-.33,2.31-.56,7.03-2.16,14.06-4.34,21.09-6.5,1.38-.42,2.77-.83,4.17-1.21,.15-.04,.41,.14,.58,.26,.05,.04,0,.23-.06,.3-10.07,11.44-20.92,22.19-M 31.46,33.21-1.87,2.01-1.86,2.37,.99,1.71,7.29-1.9,14.58-3.82,21.87-5.73,1.34-.21,2.57-1.03,3.93-.57-7.36,8.35-15.49,16.02-23.29,23.98-5.46,5.71-11.72,10.95-16.8,16.89-.01,.63,1.63,.15,2.11,.09,8.22-1.68,16.46-3.28,24.73-4.75,1.07,.32,.42,.82-.13,1.42-2.86,2.86-5.7,5.73-8.59,8.57-9.11,8.96-18.39,17.76-27.68,26.55-3.57,3.37-7.21,6.69-10.81,10.03-.25,.33-.83,.67-.63,1.11,.52,.42,1.58,.11,2.25,.16,7.47-.45,15-1.72,22.46-1.67,.83,.58-.81,1.53-1.16,2.07-17.91,17.01-35.86,33.97-54.34,50.41-2.48,2.24-2.01,2.08-5.87,2.09-6.M 74,.01-13.47,.02-20.21,.02-2.4-.1-4.33,.1-1.28-2.38,16.8-14.2,33.43-28.68,49.65-43.37,2.15-1.93,4.15-3.96,6.2-5.95,.21-.33-.3-.52-.54-.66-8.51,.91-17.07,1.93-25.6,2.78-.22,.02-.59-.07-.68-.2-.19-.79,.95-1.27,1.4-1.82,8.86-7.97,17.79-15.88,26.57-23.91,6.29-5.76,12.38-11.66,18.54-17.5,.46-.58,1.41-1.12,.99-1.92,0,.23,.08,.27,.28,.14l-.26-.05c-9.22,1.37-18.33,3.41-27.51,5.03-.88-.17-.68-.54-.11-1.1,13.42-12.44,27.78-24.76,39.62-38.08-.07-.08-.24-.18-.33-.16-.91,.17-1.83,.34-2.73,.56-8.88,2.13-17.71,4.48-26.61,6.49-.18M ,.04-.44-.12-.64-.22,0-.6,1.11-1.32,1.51-1.83,11.31-10.7,22.99-20.99,33.63-32.35-1.62-.39-2.8,.4-4.31,.74-8.86,2.54-17.72,5.07-26.59,7.6-1.1,.28-2.38,.81-3.43,.12l.04,.03c10.14-8.99,19.5-18.92,29.36-28.24,.38-.46,1.23-.96,1.07-1.59-.11-.13-.49-.22-.69-.16-1.02,.27-2.02,.58-3.02,.88-7.02,2.16-14.03,4.33-21.06,6.47-3.41,1.21-7.22,1.72-10.44,3.32h.05Z"/><path class="cls-2" d="M376.96,212.56c-.59,.32-1.22,.43-1.91,.24-3.81-1.08-7.62-2.14-11.42-3.23-2.81-.68-5.53-1.9-8.39-2.25-.22,0-.57,.16-.63,.31-3.76,20.55-5.39,41.55M -7.33,62.36-.06,2.49-1.66,1.24-3.14,.79-5.27-2.16-10.54-4.34-15.81-6.5-.59-.23-1.68-.78-2.04-.01-1.63,18.12-1.7,36.38-2.24,54.57,.04,1.96-1.48,1.06-2.57,.51-4.35-2.35-8.7-4.72-13.04-7.08-1.1-.32-4.24-3.26-4.77-1.41-.21,16.36,.99,32.75,1.46,49.06-.97,.38-1.69-.33-2.48-.75-4.69-3.07-9.36-6.16-14.04-9.24-1.15-.57-2.24-1.94-3.56-1.9-.19,.06-.44,.3-.43,.45,.25,4.09,.48,8.17,.82,12.26,.77,9.13,1.75,18.26,2.64,27.38-.09,.94,.94,5-.21,4.93-.36-.1-.76-.18-1.03-.38-6-4.28-11.73-8.88-17.56-13.38-.48-.33-.91-1.01-1.64-.64-.62,M .31-.3,.97-.28,1.48,.03,.65,.1,1.29,.19,1.93,1.43,12.55,3.63,25.04,5.16,37.56-1.12,.12-1.8-.79-2.63-1.36-5.58-4.68-11.14-9.37-16.72-14.05-.7-.42-2.6-2.8-2.99-1.15,1.64,12.44,4.59,24.77,6.22,37.19-2.11-.55-3.3-2.49-4.97-3.76-5.49-5.04-10.96-10.08-16.45-15.12-.78-.58-1.35-1.58-2.45-1.46,1.44,10.54,4.19,21.04,6.07,31.57,.19,.96,.34,1.92,.46,2.88,.02,.13-.28,.3-.47,.41-.94-.28-1.91-1.63-2.73-2.27-6.71-6.61-13.41-13.22-20.11-19.83-.88-.7-1.44-1.84-2.69-1.85,.85,7.37,3.03,14.65,4.38,21.98,.61,2.87,1.25,5.73,1.86,8.59,.11M ,.52,.24,1.06-.09,1.56-.03,.05-.29,.07-.38,.03-1.95-1.11-3.27-3.11-4.91-4.63-6.84-7.21-13.68-14.42-20.52-21.63-.79-.64-1.37-1.91-2.48-1.96-.13,.01-.33,.31-.3,.46,.22,1.28,.47,2.56,.74,3.83,1.23,5.73,2.47,11.46,3.7,17.19,.55,2.55,1.1,5.09,1.62,7.64,.06,.28-.11,.6-.21,.89-.55,.19-1.34-.8-1.74-1.13-9.82-10.66-19.46-21.48-29.37-32.06-.12-.12-.48-.1-.74-.12-.03,0-.13,.19-.12,.28,1.36,9.1,3.48,18.08,5.22,27.11-.3,1.4-1.77-.61-2.18-1.04-11.39-12.38-21.85-25.95-33.44-37.95-1.08-.23-.21,2.39-.31,2.95,1.04,7.47,3.02,15.02,3.M 51,22.46-1.46-.35-2.11-1.82-3.09-2.82-10.26-12.26-20.52-24.53-30.79-36.79-1.95-2.32-3.91-4.64-5.9-6.94-.1-.12-.48-.1-.73-.11-.45,.42-.18,1.27-.17,1.83,.68,6.22,1.37,12.44,2.04,18.67,.07,.64,.03,1.28,.02,1.93-.09,.36-.77,.17-.92,.07-14.72-17.71-28.96-35.82-43.51-53.67-.76-.96-1.73-1.94-1.56-3.24-.02-6.25-.05-12.5-.06-18.74,0-.3,.16-.61,.29-.9,.02-.05,.32-.11,.37-.07,13.69,15.93,26.51,32.72,39.95,48.91,.89,.84,1.61,2.54,2.94,2.5-.15-5.27-1.03-10.5-1.46-15.76-.23-2.25-.46-4.51-.67-6.76,.27-1.08,1-.43,1.51,.1,11.32,13.M 51,22.64,27.02,33.98,40.53,.6,.55,2.9,3.82,3.2,2.29-1.06-8.42-2.96-16.94-3.56-25.32,1.02-.11,1.51,1,2.17,1.6,9.73,11.12,19.46,22.24,29.2,33.36,.48,.5,3.01,3.83,2.99,1.58-1.57-8.74-3.24-17.46-4.72-26.21-.07-.41,.07-.84,.13-1.25,0-.02,.3-.06,.38,0,9.92,9.99,19.11,20.86,28.81,31.13,.3,.32,.51,.76,1.13,.81,.09,0,.28-.1,.28-.16-.18-3.99-1.36-7.87-1.99-11.81-1.15-6.07-2.29-12.14-3.43-18.2-.24-1.15,.95-.8,1.33-.31,3.2,3.33,6.41,6.66,9.62,9.98,4.78,4.94,9.58,9.88,14.38,14.8,.58,.59,1.23,1.13,1.87,1.68,.12,.08,.58-.02,.63-.M 18-1.01-9.08-3.56-18.05-4.78-27.15-.31-1.81-.59-3.63-.84-5.45,.37-1.46,1.7,.35,2.36,.82,6.43,6.23,12.85,12.47,19.28,18.7,.85,.83,1.78,1.61,2.71,2.38,.11,.09,.49-.01,.87-.03-.91-8.79-3-17.47-4.18-26.24-.42-3.2-1.25-6.38-1.34-9.61,.44-.82,2.11,.99,2.64,1.33,5.49,4.89,10.95,9.8,16.43,14.7,2.8,2.21,5.28,5.88,4.09-.63-1.12-7.59-2.28-15.18-3.2-22.79-.34-4.38-1.59-8.8-1.39-13.16,.7-.63,1.83,.69,2.46,1.05,4.85,3.9,9.67,7.81,14.52,11.7,1.33,1.07,2.71,2.09,4.1,3.11,.13,.1,.49,.03,.73-.02,.08-.01,.18-.18,.17-.28-.22-2.47-.43-M 4.93-.68-7.4-.96-8.9-1.86-17.81-2.61-26.73-.24-2.79-.41-5.59-.62-8.39-.03-.44,.21-.76,.49-.79,.45-.05,.75,.15,1.04,.35,3.85,2.69,7.69,5.41,11.56,8.09,2.34,1.62,4.72,3.21,7.1,4.79,.16,.11,.53,.13,.74,.06,.76-.35,.39-1.39,.46-2.06-.29-5.06-.79-10.1-.85-15.17-.38-9.58-.95-19.16-.99-28.75,.13-.88-.28-2.49,1.04-2.35,5.78,3.08,11.33,6.59,17.03,9.83,.86,.23,2.3,1.78,2.98,.68,.17-18.2,.43-36.4,1.1-54.59l-.14,.05c6.28,2.66,12.5,5.46,18.76,8.17,1.13,.35,3.11,1.59,3.06-.53,1.41-20.5,3.06-41,5.82-61.38l-.13,.12c6.79,2.07,13.6,M 4.07,20.4,6.1,.63,.19,1.27,.36,2.08,.01,2.87-19.84,6.37-39.63,10.07-59.34,.7-3.72,1.53-7.43,2.31-11.14,.2-.95,.71-1.2,2.01-1.04,5.96,.81,11.9,1.78,17.84,2.66,1.32,.2,2.63,.46,3.93,.73,.79,.33,.4,1.43,.35,2.09-3.26,14.48-6.46,28.99-9.21,43.56-1.82,9.13-3.38,18.29-4.97,27.45-.08,.43-.11,.85,.18,1.25h0Z"/><path class="cls-2" d="M1063.89,1226.8c5.16,.76,10.15,2.88,15.25,4.12,1.61,.13,7.1,3.06,7.29,.51,2.55-17.85,4.63-35.76,6.39-53.71,.46-2.96-.04-6.11,.96-8.96,.66-.62,1.77,.13,2.5,.31,5.28,2.16,10.54,4.33,15.82,6.49,1.M 08,.44,2.25,.95,2.43-.71,1.31-18.26,1.25-36.6,2.11-54.87,1.07-.4,1.97,.4,2.92,.8,4.79,2.61,9.57,5.23,14.35,7.84,.75,.42,2.41,1.67,2.89,.52,.37-16.35-.91-32.78-1.37-49.07,.67-.64,1.68,.31,2.33,.6,5.63,3.69,11.22,7.41,16.85,11.1,.35,.22,1.04,.29,1.12,.12-.02-14.7-2.56-29.65-3.59-44.41,.42-1.61,2.45,.59,3.19,.97,4.97,3.8,9.92,7.61,14.88,11.41,.81,.46,1.54,1.42,2.48,1.5,.31-.02,.48-.16,.47-.43-.05-3.13-.54-6.23-.95-9.33-1.22-10.39-3.07-20.78-4.33-31.12,.99-.32,1.73,.71,2.49,1.19,5.67,4.76,11.33,9.53,17,14.29,.65,.54,1.M 35,1.05,2.04,1.55,.06,.05,.26,0,.38-.04,.1-.03,.25-.11,.25-.17,0-.64,.08-1.29-.03-1.92-.93-5.55-1.89-11.09-2.85-16.64-.96-6.29-2.46-12.59-3.21-18.85,1.25-.11,2.08,1.23,3.03,1.9,5.85,5.36,11.68,10.72,17.53,16.08,.99,.69,1.92,2.27,3.19,2.22,.3-.37,.11-1.07,.09-1.54-2.04-10.21-4.09-20.41-6.13-30.61-.02-.76-.64-1.92,.22-2.35,.07-.05,.3-.03,.36,.03,8.43,7.58,16.02,16.05,24.43,23.66,.11,.06,.59-.08,.63-.23,0-.64,.06-1.29-.07-1.92-2.01-9.77-4.12-19.54-6.23-29.29-.04-.2,.03-.42,.08-.63,.08-.18,.49-.22,.63-.13,5.32,4.89,10.M 02,10.42,15.09,15.57,3.91,4.12,7.82,8.24,11.75,12.34,.22,.23,.63,.36,.96,.52,.34,.02,.39-.49,.36-.74-2.05-9.66-4.18-19.3-6.19-28.97,.23-1.47,1.79,.5,2.22,.94,9.13,10.01,18.25,20.02,27.39,30.03,1.43,1.42,3.06,3.8,2.51-.16-1.47-7.88-3.03-15.75-4.67-23.61-.1-.52-.04-1.06-.03-1.59,0-.07,.13-.16,.23-.19,.12-.03,.33-.05,.39,0,.67,.67,1.36,1.33,1.97,2.04,9.39,10.79,18.76,21.58,28.14,32.37,1.38,1.59,2.76,3.19,4.18,4.76,.19,.21,.67,.26,1.21,.46-1.02-7.64-2.43-14.98-3.68-22.55-.14-.85-.13-1.71-.18-2.57,0-.1,.1-.28,.14-.28,.2M 4,0,.59,0,.71,.11,.75,.76,1.47,1.54,2.14,2.34,11.45,13.7,22.9,27.41,34.35,41.11,.75,.89,1.53,1.77,2.34,2.63,.1,.11,.46,.09,.7,.08,.06,0,.17-.17,.17-.26-.32-6.89-1.18-13.74-1.83-20.61-.11-3,1.45-.75,2.41,.31,6.99,8.57,13.99,17.14,20.93,25.73,6.72,8.32,13.38,16.68,20.07,25.02,.75,1.09,2.01,2.05,2.06,3.44-.07,6.66,.32,13.39-.16,20.02-.09,.1-.54,.19-.67,.08-.71-.78-1.43-1.56-2.09-2.37-7.38-9.14-14.73-18.29-22.12-27.43-5.75-6.87-11.1-14.13-17.17-20.73-.12-.06-.58,.08-.62,.23-.03,.64-.1,1.29-.04,1.92,.68,6.76,1.41,13.51,M 1.92,20.28,0,.09-.1,.26-.17,.26-.7,.15-1.09-.32-1.49-.79-11.5-13.82-23.08-27.56-34.63-41.35-.52-.62-1.13-1.19-1.72-1.78-.13-.1-.57-.04-.65,.12,.72,8.31,2.67,16.64,3.45,25-.05,.56-.68,.54-1,.22-10.44-11.75-20.71-23.65-31.09-35.45-.59-.62-1.13-1.75-2.2-1.72,.2,5.34,1.93,11.06,2.72,16.51,.64,3.73,1.46,7.43,1.76,11.2,.03,.27-.17,.41-.48,.39-9.47-9.07-18-19.65-27.14-29.23-.91-.76-1.75-2.36-2.99-2.39-.32,.47-.03,1.32-.01,1.89,1.77,9.47,3.67,18.93,5.35,28.42,.01,.58-.73,.54-1.03,.26-8.07-8.2-15.99-16.53-24.01-24.78-4.75-5M .23-2.48,.34-2.11,3.51,1.49,7.99,2.99,15.97,4.47,23.96,.45,3,1.26,5.75-1.91,2.49-6.68-6.49-13.35-12.98-20.04-19.46-.68-.66-1.45-1.27-2.19-1.89-.14-.08-.58,.03-.66,.15,0,4.41,1.4,8.74,1.96,13.12,1.12,6.72,2.23,13.45,3.28,20.18,.15,.95,.48,1.91,.11,2.87-1.26-.02-2.03-1.28-2.99-1.97-5.57-4.98-11.13-9.97-16.71-14.94-.9-.8-1.87-1.54-2.82-2.3-.06-.05-.26-.02-.37,0-.11,.03-.27,.1-.28,.16-.06,.42-.16,.85-.1,1.27,.34,2.68,.72,5.35,1.1,8.03,1.34,9.84,2.98,19.66,3.81,29.56-.04,.46-.63,.86-1.05,.47-.87-.67-1.77-1.32-2.62-2.01-M 5.85-4.61-11.46-9.51-17.5-13.88-.29-.06-.93-.03-.85,.4,.76,10.86,2.24,21.67,3.05,32.53,.29,3.33,.54,6.66,.79,10-.37,1.41-1.95-.09-2.63-.5-5.78-4.05-11.54-8.14-17.41-12.06-2.42-1.51-1.06,3.73-1.22,4.86,.82,14.29,1.64,28.63,1.67,42.94-.51,1.14-1.81-.11-2.54-.42-5.11-2.99-10.21-5.99-15.33-8.97-1.06-.59-1.92-1.35-3.24-.94-.21,18.23-.12,36.44-1.09,54.65l.14-.04c-6.28-2.65-12.49-5.45-18.74-8.17-1.79-.73-3.14-1.45-3.06,1.24-1.45,20.22-2.77,40.64-5.85,60.67l.11-.12c-6.81-2.02-13.6-4.07-20.4-6.1-1.43-.45-1.98-.03-2.15,1.43-M 1.8,14.03-4.47,27.96-6.71,41.93-1.56,9.58-4.1,19.14-5.44,28.69l.13-.1c-7.97-1.35-16.78-2.68-24.44-3.65,.22-4.7,1.97-9.3,2.78-13.96,1.19-5.39,2.4-10.78,3.5-16.19,2.92-14.95,5.86-29.89,8.28-44.93l-.14,.13Z"/><path class="cls-2" d="M1191.44,947.12c.49-.58,.5-1.22,.36-1.86-.33-1.48-.67-2.97-1.06-4.44-2.25-8.42-4.52-16.84-6.78-25.25-.09-.42-.28-1.51,.46-1.16,8.23,7.23,15.71,15.33,23.67,22.88,1.25,1.09,2.03,2.47,3.68,3.05-1.83-9.69-5.14-19.21-7.47-28.84-.14-.52-.18-1.05-.24-1.58,0-.08,.07-.22,.15-.24,.81,.05,1.66,1.18,2.M 3,1.67,5.88,6.03,11.76,12.06,17.61,18.11,3.38,3.49,6.71,7.01,10.08,10.51,.1,.1,.45,.07,.68,.05,.28-.19,.07-.62,.01-.91-1.96-8.48-4.28-16.88-6.51-25.3-.21-.95-.54-1.94,0-2.83l-.05,.09c11.02,10.93,21.27,22.57,31.72,33.94,.91,.77,1.68,2.36,2.93,2.4-.04,.29,.03,.34,.22,.14l-.31-.07c.4-.86,.1-1.71-.09-2.55-1.69-7.19-3.42-14.38-5.13-21.57-.17-.73-.26-1.48-.37-2.22-.01-.1,.08-.29,.12-.29,.25,0,.6-.02,.72,.1,.93,.92,1.86,1.84,2.71,2.8,8.67,9.74,17.33,19.48,25.97,29.23,2.88,3.25,5.69,6.54,8.55,9.8,.47,.4,.98,1.28,1.63,1.31,M .24-.2,.48-.44,.34-.75-1.43-7.34-2.87-14.67-4.28-22.01-.77-4.35,1.5-1.14,2.89,.33,13.21,15.21,26.25,30.52,39.03,45.97,.74,.9,1.5,1.79,2.26,2.67,.4,.47,.8,.62,.95,.38,.11-.18,.29-.37,.27-.55-.46-5.81-1.26-11.58-1.96-17.37-.17-1.39-.38-2.78-.53-4.17-.02-.15,.19-.42,.34-.44,.23-.03,.59,.04,.72,.18,.72,.78,1.4,1.58,2.07,2.39,4.92,5.92,9.88,11.82,14.73,17.77,10.73,13.17,21.44,26.35,32.12,39.55,1.38,1.32,1.66,2.84,1.64,4.52-.18,6.02,.19,12.07-.16,18.08-.03,.14-.33,.27-.54,.36-.05,.02-.22-.08-.31-.14-15.99-18.66-30.47-39.M 54-47.3-57.22-.32,.22-.2,.84-.21,1.19,.74,7.06,1.88,14.13,2.27,21.21-.34,.03-.71,.14-.8,.06-.6-.57-1.19-1.16-1.71-1.78-6.13-7.34-12.21-14.71-18.37-22.04-6.38-7.6-12.83-15.16-19.26-22.73-.68-.8-1.38-1.59-2.11-2.36-.11-.12-.47-.11-.71-.12,.64,7.93,2.81,16.22,4.03,24.25,.05,.29-.1,.6-.19,.89-.27,.1-.82-.16-1.01-.37-11.2-12.79-22.38-25.59-33.58-38.38-.77-.88-1.6-1.73-2.44-2.57-.12-.12-.47-.09-.72-.14l-.03-.18,.13,.12c-.37,.97-.05,1.92,.16,2.86,1.78,8.15,3.67,16.22,5.3,24.42-1.14,.22-1.6-.85-2.34-1.47-6.47-7.11-12.9-14.M 25-19.4-21.35-3.49-3.81-7.08-7.55-10.64-11.32-.39-.41-.71-.93-1.52-.88l.09-.06c.99,7.93,3.68,15.64,5.33,23.49,.41,1.69,.75,3.39,1.11,5.09,.1,.45-.11,.81-.39,.75-9.36-8.41-17.72-18.48-26.75-27.44-.79-.62-1.41-1.88-2.54-1.78-.05,0-.16,.19-.14,.29,2.17,10.09,4.73,20.09,7.07,30.14,.13,2.17-2.65-1.09-3.15-1.57-7.48-7.35-14.83-14.83-22.39-22.1-.43-.6-1.61-.68-1.28,.35,2.37,10.84,5.39,21.92,7.25,32.7-.91,.17-1.44-.74-2.08-1.21-4.02-3.77-8.02-7.56-12.05-11.32-2.8-2.62-5.63-5.22-8.46-7.83-.44-.39-.94-.91-1.59-.87-.12,.01-.3M ,.32-.27,.47,.27,1.38,.59,2.76,.88,4.14,2.08,9.87,4.29,19.72,6.16,29.63,.06,.62,.41,1.38-.34,1.72-.06,.04-.28,.02-.34-.03-.75-.62-1.5-1.24-2.23-1.87-6.29-5.29-12.22-11.05-18.74-16.05-.74-.16-.64,.69-.55,1.22,2.28,12.45,4.79,24.88,6.52,37.41-1.19,.32-2.23-1.09-3.2-1.67-4.78-3.8-9.53-7.61-14.31-11.42-.86-.68-1.76-1.33-2.67-1.97-.15-.1-.49-.06-.74-.03-.08,0-.2,.17-.19,.26,.74,7.52,2.34,14.94,3.16,22.46,.67,5.25,1.34,10.5,1.99,15.75,.12,.96,.09,1.93,.12,2.9,.03,.41-.68,.39-.87,.34-5.6-3.65-10.93-7.68-16.43-11.48-.83-.4M 5-1.63-1.37-2.66-1.11,.46,8.07,1.7,16.31,2.11,24.47,.55,6.98,1.31,13.96,1.49,20.97,0,.17-.18,.41-.37,.49-1.22,.17-2.25-1.08-3.31-1.56-4.36-2.71-8.72-5.43-13.09-8.13-1.01-.53-2.86-2.01-2.88,.17,.44,16.47,1.27,32.95,.91,49.43-.01,.28-.58,.58-.86,.45-5.59-2.52-10.97-5.47-16.47-8.17-3.22-1.88-2.47,.74-2.61,2.92-.47,17.87-1.29,35.78-2.88,53.58-.44,.82-1.74,.27-2.44,.03-3.87-1.52-7.73-3.06-11.6-4.57-2.1-.63-4.09-2.01-6.31-1.92-2.91,22.13-5.02,44.49-9.27,66.46l.14-.13c-7.2-2.18-14.57-4.29-21.94-5.82l.06,.09c4.81-21.94,7.7M -44.32,10.76-66.58,.24-2.43,2.95-.66,4.31-.3,4.29,1.55,8.58,3.11,12.87,4.66,.81,.23,2.24,1.13,2.83,.23,1.18-6.69,1.37-13.51,2.08-20.26,.67-12.04,1.77-24.08,2.04-36.14,.1-.77-.16-2.23,1.06-2.04,5.87,2.27,11.38,5.37,17.19,7.78,1.14,.28,1.11-.81,1.18-1.58,.05-8.07,.45-16.15,.2-24.23-.26-8.29-.3-16.58-.42-24.87-.09-2.16,1.85-.76,2.89-.25,5.1,2.78,10.01,5.92,15.22,8.49,.56,.12,.9-.75,.83-1.21-.22-3.76-.47-7.53-.71-11.29-.48-6.12-.76-12.26-1.27-18.38-.25-5.25-1.5-10.51-1.35-15.75,1.21-.27,2.11,.75,3.11,1.26,4.26,2.81,8.5M 1,5.63,12.77,8.44,.78,.36,2.9,2.45,3.25,.88-.62-6.98-1.51-13.95-2.48-20.89-.87-6.95-2.34-13.88-2.89-20.84,0-.09,.08-.25,.15-.25,.92-.23,1.63,.55,2.35,.98,5.46,4,10.89,8,16.27,12.1,.8,.35,1.36,.19,1.15-.92-2.06-12.84-4.87-25.6-6.91-38.41,1.54,.24,2.36,1.31,3.53,2.15,5.21,4.21,10.42,8.42,15.64,12.62,.54,.44,.98,1.07,1.95,1,.23-1.39-.44-3-.61-4.44-2.11-10.62-4.97-21.14-6.88-31.78,.37-.88,1.89,.76,2.37,1.03,5.67,4.9,11.32,9.82,16.99,14.72,1.07,.71,1.9,2.16,3.25,2.18v.14l-.1-.08c.34-.86,.06-1.72-.14-2.55-2.57-10.44-5.21M -20.87-7.77-31.32,.03-.66,1.16-.22,1.4,.11,7.89,7.2,15.93,14.26,23.34,21.83-.11-.24-.07-.29,.14-.13l-.28,.08Z"/><path class="cls-2" d="M171.16,461.61c10.66,11.81,21.24,23.67,32.27,35.16,.51,.38,1.44,1.01,1.21-.24-1.88-7.82-3.77-15.64-5.65-23.46-.38-1.58-.72-3.18-1.04-4.77-.03-.14,.19-.44,.31-.44,.79,0,1.21,.76,1.71,1.24,9.1,9.62,18.46,19.02,27.4,28.78,.01-.25,.07-.28,.17-.1l-.28,.03c1.05-1.03,.12-2.51-.01-3.74-1.99-9.4-4.99-18.84-6.47-28.22,.59,0,.97,.29,1.31,.63,2.27,2.28,4.52,4.56,6.81,6.82,5.68,5.61,11.39,11.2,1M 7.08,16.81,.41,.4,.79,.84,1.53,.88-1.66-11.04-5.5-22.18-7.25-33.37,.35-1.04,2.77,1.77,3.34,2.12,6.24,5.8,12.46,11.61,18.69,17.42,.64,.46,1.26,1.34,2.04,1.47,.25-.17,.57-.38,.43-.72-1.16-5.3-2.35-10.6-3.48-15.91-1.22-5.73-2.39-11.47-3.55-17.21-.58-3.85,1.1-1.65,2.81-.37,5.66,4.91,11.31,9.84,16.97,14.75,.64,.42,1.38,1.32,2.14,1.36,.16-.13,.38-.31,.36-.45-.53-2.98-1.11-5.96-1.65-8.95-1.66-9.83-3.88-19.62-5.02-29.51,1.6,.14,2.51,1.46,3.74,2.31,4.87,3.87,9.74,7.75,14.62,11.62,.8,.5,1.53,1.47,2.58,1.31,.06,0,.16-.18,.15-M .28-.9-8.05-2.54-16.01-3.45-24.06-.6-5.36-1.51-10.7-1.9-16.08,0-.48-.41-1.13,.48-1.37,.58-.16,.96,.29,1.33,.55,4.54,3.21,9.06,6.45,13.6,9.66,1.54,.91,2.75,2.37,4.64,2.51-.83-10.12-1.9-20.21-2.73-30.34-.37-4.62-.65-9.25-.96-13.88,0-.57-.24-1.43,.32-1.8,.99-.29,1.85,.73,2.69,1.11,4.37,2.71,8.72,5.43,13.09,8.13,.82,.32,3.03,2.34,3.53,1.12,.13-5.69-.27-11.42-.45-17.11-.44-11.09-.63-22.19-.41-33.28,.01-.27,.62-.5,.94-.35,5.66,2.67,11.2,5.58,16.82,8.34,2.47,1.26,2.05-.33,2.18-2.18,.16-10.34,.77-20.67,1.33-31.01,.54-7.84,M .69-15.74,1.73-23.54,.75-.93,2.28,.16,3.21,.38,4.35,1.71,8.69,3.44,13.04,5.15,1.08,.42,2.14,.92,3.36,1.02,.19,.02,.54-.15,.6-.29,.16-.4,.25-.83,.3-1.26,2.58-21.86,4.79-43.93,9.24-65.47-.02,.32-.03,.69,.38,.82,1.23,.4,2.47,.77,3.73,1.11,5.17,1.39,10.35,2.75,15.52,4.14,.53,.14,1.03,.17,1.53-.04,0,.01-.07-.09-.07-.09-.75,7.59-2.86,15.1-3.82,22.7-.56,3.63-1.23,7.25-1.84,10.88-1.86,11.08-3.15,22.25-4.76,33.37-.23,2.58-3.25,.42-4.67,.16-4.79-1.71-9.58-3.44-14.37-5.16-1.6-.34-1.28,2.85-1.56,3.88-1.49,18.3-3.07,36.56-3.7,5M 4.92-1.46,.21-2.48-.57-3.73-1.11-4.31-2.01-8.61-4.02-12.91-6.02-.64-.29-1.95-1.04-2.41-.26-.77,16.67-.05,33.39,.06,50.07,.13,2.56-1.45,1.28-2.84,.66-4.52-2.54-9.01-5.11-13.52-7.66-1.31-.71-2.66-1.57-2.55,.74,.72,14.96,2.19,29.88,3.24,44.81-.57,.75-1.65-.29-2.26-.55-4.28-2.8-8.54-5.61-12.8-8.41-1.32-.74-2.34-2.02-3.96-2.02,.93,13.64,3.5,27.25,5.23,40.85,.01,.61,.35,1.86-.57,1.86-5.85-3.61-11.1-8.17-16.74-12.13-.71-.43-2.7-2.18-2.55-.28,1.37,8.11,2.72,16.23,4.31,24.3,.87,4.58,1.75,9.15,2.62,13.72-.33,1.49-3.12-1.43-3M .79-1.8-5.54-4.4-10.95-8.94-16.55-13.26-.2-.09-.9-.18-.91,.23,1.7,9.39,3.97,18.67,6.01,28,.51,2.54,1.39,5.04,1.63,7.63-.02,.21-.5,.61-.77,.42-.6-.43-1.21-.86-1.76-1.33-5.49-4.74-10.97-9.5-16.46-14.24-.91-.79-1.84-1.57-2.8-2.33-.13-.11-.48-.04-.88-.05,1.9,10.87,5.33,21.53,7.78,32.31,.98,3.38-1.76,.64-2.81-.27-6.44-5.95-12.85-11.9-19.29-17.85-.58-.36-1.99-2.28-2.54-1.47,1.55,9.25,4.85,18.3,6.95,27.49,.15,.8,1.86,4.59,.31,4.3-9.13-8.04-17.41-17.01-26.27-25.35-.14-.09-.88-.14-.84,.26,2.23,9.43,4.95,18.75,7.48,28.11,.06M ,.52,.45,1.54,.07,1.87-.24-.01-.57-.01-.7-.13-9.27-9.03-18.16-18.47-27.01-27.82-.89-.72-1.53-2.11-2.78-2.12-.3,.55,.13,1.84,.21,2.51,2.06,8.74,4.93,17.41,6.59,26.18-.73-.07-1.06-.41-1.39-.76-2.62-2.74-5.28-5.45-7.84-8.22-7.37-7.97-14.7-15.96-22.05-23.94-1.16-1-2.15-2.92-3.6-3.35-1.01,.07,.47,3.77,.49,4.58,1.59,7.39,3.96,14.81,5.13,22.2-.22,0-.56,.08-.65-.01-.71-.64-1.42-1.29-2.04-1.99-11.84-13.36-23.76-26.64-35.51-40.08-.42-.33-.85-1.09-1.46-.93-.43,.15-.22,1.1-.22,1.47,1.49,7.85,3.14,15.54,4.5,23.43-1.63-.18-2.18-M 1.68-3.23-2.69-8.83-10.31-17.69-20.6-26.49-30.92-4.47-5.25-8.83-10.56-13.26-15.84-.86-.78-1.4-2.19-2.7-2.21,.19,6.13,1.46,12.21,2.06,18.32,.59,4.84,.34,5.63-3.03,1.32-15.81-19.27-31.72-38.44-47.34-57.86-.85-1.04-1.23-2.09-1.22-3.33,.04-6.14,0-12.28-.01-18.42-.02-1.26,.95-.6,1.39-.2,14.57,18.15,29.33,36.13,43.99,54.2,1.14,1.14,1.84,2.94,3.52,3.33-.3-7.25-1.6-14.64-2.2-21.94-.04-.41-.04-.87,.79-.93,12.95,15.46,25.77,31.02,39,46.34,.76,.88,1.57,1.74,2.4,2.59,.11,.11,.45,.09,.68,.08,.05,0,.15-.19,.13-.29-1-6.09-2.12-12M .15-3.19-18.22-.11-1.88-2.64-9.9,1.21-5.06,8.31,9.55,16.61,19.1,24.94,28.64,3.16,3.62,6.39,7.2,9.62,10.79,.21,.24,.62,.37,.95,.53,.33,0,.35-.5,.32-.75-1.77-7.95-3.6-15.88-5.26-23.85-.24-1.15-.68-2.33,.06-3.49l-.16-.05Z"/><path class="cls-2" d="M892.26,945.53c-.26,3.04-.53,6.09-.79,9.13-4.3,1.2-8.63,2.35-12.98,3.46-.01-.1-.07-.32-.14-.33-.75-.15-1.14,.38-1.66,.78-3.67,.92-7.36,1.81-11.06,2.66,.69-5.59,1.66-11.39,1.39-16.94-.62-.31-1.24,.34-1.58,.71-2.76,2.92-5.51,5.85-8.27,8.77-.64,.51-2.19,2.95-2.85,1.49,.13-2.47,.M 29-4.94,.48-7.42,.3-3.97,.64-7.95,.94-11.92-.03-.42,0-1.32-.47-1.46-.58-.19-1.22,.84-1.65,1.18-3,3.31-5.98,6.64-8.99,9.95-.79,.74-1.5,1.6-1.7-.1,.23-5.06,.5-10.11,.73-15.17,.04-.75-.06-1.5-.12-2.25-.07-.13-.54-.24-.67-.18-3.67,3.43-6.61,7.59-10.01,11.3-.37,.43-.87,.78-1.33,1.15-.05,.04-.35-.02-.37-.07-.13-.39-.32-.8-.31-1.2-.11-4.86,.89-10.08-.07-14.76-.9-.39-1.49,1.18-2.12,1.65-3.21,3.69-6.09,7.72-9.58,11.17-.07,.07-.27,.15-.33,.12-.91-.27-.54-1.26-.65-1.97-.04-3.45-.07-6.9-.12-10.34,0-.54-.09-1.07-.17-1.61-.01-.0M 7-.16-.18-.25-.19-1.18-.17-1.79,1.49-2.6,2.17-2.82,3.29-5.62,6.59-8.44,9.87-.58,.54-1.05,1.46-1.98,1.35-.88-3.81-.59-8.18-1.12-12.14-1.01-.31-1.48,.59-2.11,1.16-4.6,5.08-9.06,10.24-13.91,15.08-.27,.28-.6,.42-1.02,.31-.49-.13-.45-.5-.47-.8-.05-.86-.08-1.72-.11-2.59-.22-2.45,.11-5-.59-7.39-.05-.14-.37-.24-.59-.32-5.33,4.45-10.03,10.16-15.15,15.03-.65,.51-1.85,2.29-2.43,.83-.26-2.69-.49-5.37-.74-8.06-.08-.58-.09-1.62-.93-1.45-5.25,4.46-10,9.59-15.37,14.09-.77,.48-2.38,2.72-3.1,1.29-.41-2.9-.48-5.82-1.06-8.68-.15-.26-.M 82-.27-1-.18-5.67,4.57-10.73,9.65-16.58,14.12-.8,.43-1.99,1.99-2.78,.92-.26-2.67-.53-5.36-.89-8.03-.06-.47-.77-.71-1.17-.42-6.21,4.81-12.57,9.43-19.14,13.91-.55,.41-1.05,.71-1.83,.63-.74-2.69-.48-5.56-1.02-8.31-.04-.28-.68-.47-.98-.3-7.44,4.42-14.54,9.36-22.17,13.49-.42,.23-.86,.5-1.49,.35-1.68-2.9-3.37-5.82-5.06-8.74,8.32-4.34,15.88-9.56,23.88-14.16,.62-.23,1.13,.41,1.42,.87,1.3,2.13,2.55,4.28,3.82,6.42,.71,1.02,1.87-.03,2.6-.48,4.86-3.41,9.75-6.8,14.28-10.49,1.04-.85,2.09-1.68,3.17-2.5,.46-.35,.9-.94,1.63-.66,.64M ,.25,.68,.89,.78,1.42,.42,2.23,.83,4.46,1.25,6.77,.41-.05,.91,.01,1.13-.16,1.85-1.42,3.71-2.83,5.43-4.33,3.46-3.02,6.84-6.09,10.26-9.14,.77-.56,1.33-1.57,2.36-1.6,.32-.02,.5,.14,.55,.38,.34,1.92,.7,3.84,1.03,5.75,.11,.78-.01,1.98,.87,2.3,1.08-.06,1.83-1.19,2.63-1.82,4.66-4.32,9.46-8.55,13.77-13.11,.3-.29,.79-.75,1.23-.76,.22,.09,.57,.22,.59,.36,.4,2.12,.76,4.26,1.13,6.39,.17,.72,.14,2.71,1.29,2.23,5.46-5.07,10.13-10.92,15.43-16.15,.18-.12,.84-.33,.96,.04,.31,1.37,.64,2.74,.91,4.12,.35,1.81,.65,3.62,.99,5.43,.21,.28M ,.72,.42,.98,.13,5.17-5.13,9.42-11.06,14.38-16.37,.17-.11,.85-.11,.98,.19,1.02,3.29,.92,6.88,1.99,10.18,.05,.15,.33,.26,.53,.34,.65,0,1.35-1.17,1.82-1.61,3.33-4.03,6.32-8.35,9.86-12.19,1.98-1.08,1.37,11.79,2.57,12.48,.55,.07,1.24-.88,1.61-1.24,3-3.84,5.96-7.69,8.96-11.53,.26-.25,.87-.72,1.25-.48,.77,3.89,.51,7.96,.88,11.91,.05,.75,.16,1.49,.26,2.24,.01,.06,.2,.12,.31,.15,.59,.13,1.01-.64,1.38-.96,2.51-3.19,5-6.4,7.5-9.59,.57-.73,1.18-1.44,1.77-2.16,.18-.22,.44-.31,.68-.16,.67,.46,.38,1.4,.51,2.1,.26,4.41,.64,8.82,.M 48,13.24,.06,.32,.2,1.07,.68,.97,.38-.27,.82-.53,1.1-.86,3.11-3.77,6.14-7.6,9.23-11.38,.09-.11,.48-.08,.73-.07,.09,.01,.24,.12,.25,.19,.09,1.08,.22,2.15,.22,3.22-.02,4.31-.1,8.62-.13,12.93-.07,4.58,1.46,1.9,3.23,.02,2.5-2.94,4.97-5.89,7.48-8.83,.19-.23,.59-.37,.92-.51,.07-.04,.33,.04,.35,.1,.54,5.4,.32,10.98-.18,16.43-.2,1.6-.19,3.23-.23,4.84,0,.17,.18,.42,.36,.49,.99,.17,1.53-1.05,2.21-1.59,2.82-3.02,5.63-6.04,8.46-9.06,.32-.33,.75-.59,1.15-.85,.06-.04,.34,.03,.36,.09,.63,2.44-.09,5.14,0,7.67-.25,5.81-.66,11.6-1.1M 5,17.4,1.2,.31,1.73-.72,2.56-1.33,2.84-2.73,5.67-5.48,8.51-8.21,.65-.66,2.46-2.23,2.34-.25Z"/><path class="cls-2" d="M906.2,1224.04s.11-.02,.16-.03l-.06,.15-.1-.12Z"/><path class="cls-2" d="M945.14,1096.22s-.1,.04-.15,.05c.01-.06,.03-.12,.04-.18l.11,.13Z"/><path class="cls-2" d="M951.59,1293.34h-.17s.01-.05,.02-.07l.15,.07Z"/><path class="cls-2" d="M926.83,1293c-.17,.73-.9,2.03,.27,2.23,8.13-.26,16.19-1.68,24.32-1.89-10.74,31.31-22.94,62.14-35.81,92.63-.37,.13-.61,.29-.86,.29-8.77-.02-17.5,.21-26.28,0-.37-1.37,.61-M 2.52,1.04-3.77,4.96-11.27,10.06-22.49,14.87-33.8,4.55-10.69,8.97-21.42,13.28-32.18,2.58-6.45,5-12.95,7.53-19.42,.61-1.32-.3-1.54-1.44-1.42-7.35,.68-14.71,1.39-22.06,2.05-1.91,.06-.57-1.97-.25-2.89,2.38-5.83,4.79-11.65,7.13-17.49,7.47-18.65,14.37-37.42,20.9-56.31,.3-.93,.18-1.62-1.72-1.24-7.12,1.41-14.25,2.83-21.39,4.22,7.96-22.06,16.25-44.28,22.41-66.85-.36-.89-2.08,0-2.8,.07-5.95,1.57-11.74,3.98-17.76,5.11-.51-.62-.17-1.24,.03-1.85,2.11-6.57,4.26-13.13,6.31-19.71,3.07-9.81,5.8-19.69,8.62-29.55,.54-1.89,.98-3.79,1.M 41-5.7,.06-.27-.07-.73-.31-.84-.82-.26-1.82,.35-2.6,.62-5.04,2.04-10.06,4.18-15.12,6.16-1.39,.46-1.1-1.33-.8-2.11,4.41-14.75,8.13-29.61,11.68-44.56,.73-3.07,.78-3.93-2.41-2.17-4.79,2.36-9.38,5.18-14.31,7.24-1.68,.7,2.14-10.16,2.16-11.4,1.63-7.2,3.21-14.41,4.78-21.62,.59-3.29,1.62-6.56,1.72-9.89-.23-.95-2.07,.55-2.58,.73-4.38,2.67-8.58,5.62-13.06,8.13-.15,.04-.56-.13-.58-.32,1.03-8.55,3.4-17.01,4.91-25.5,.59-3.41,1.03-6.84,1.52-10.27,.06-.42,.01-.85-.02-1.28-.01-.05-.16-.13-.27-.15-.72-.15-1.36,.64-1.97,.95-3.54,2.6M 5-7.06,5.32-10.59,7.97-.52,.22-1.76,1.53-2.17,.7,.05-3.02,1.06-5.97,1.47-8.96,4.81-1.19,9.59-2.44,14.33-3.75-.65,2.89,3.06-.62,3.93-1.08,3.61-1.02,7.2-2.06,10.77-3.13-.93,11.27-3.74,22.32-4.8,33.55,.54,.71,1.67-.23,2.27-.48,3.74-2.3,7.45-4.62,11.18-6.93,.77-.41,1.51-1.09,2.45-.87-.48,7.44-2.13,14.97-3.36,22.41-1.13,5.96-2.41,11.9-3.55,17.86-.16,1.25-.85,2.51-.51,3.77,.94,.08,1.58-.37,2.25-.7,4.82-2.36,9.55-4.9,14.44-7.13,1.36-.16,.67,1.63,.64,2.4-1.29,5.94-2.4,11.9-3.64,17.85-2.08,9.09-4.03,18.26-6.4,27.28-.05,.9-1M .39,3.59,.15,3.41,6.33-2.23,12.46-4.98,18.81-7.15-3.79,16.49-7.8,32.84-12.59,49.12-.89,3.03-1.73,6.08-2.58,9.12-.12,.42-.17,.85,.36,1.3,6.09-1.46,12.14-3.35,18.2-4.98,.7-.14,2.1-.74,2.3,.26-4.52,17.52-9.82,34.85-15.31,52.12-1.42,5.14-3.8,10.09-4.79,15.31,.37,.85,1.77,.31,2.49,.31,6.5-1.2,13.1-2.43,19.59-3.57,.23,.27,.51,.43,.51,.6-.02,.53-.06,1.07-.22,1.59-1.96,5.8-3.61,11.7-5.57,17.5-6.58,19.47-13.35,38.8-20.55,58.05Z"/><path class="cls-2" d="M589.21,1154.29c-.11-.59,.35-1.01,.73-1.45,3.14-3.62,6.3-7.23,9.44-10.86M ,2.09-2.5,4.32-4.89,6.21-7.53,.18-.24,.14-.42-.13-.52-12.94,3.6-25.52,9.24-38.66,12.68-1.12-.09,.19-1.29,.45-1.76,3.98-4.86,7.98-9.7,11.95-14.56,.51-.62,.92-1.3,1.36-1.96,.03-.05-.06-.18-.13-.23-.45-.28-1.02,.06-1.49,.15-2.24,.72-4.49,1.44-6.72,2.18-10.17,3.41-20.57,6.33-30.86,9.49-.73,.22-1.53,.32-2.3,.45-.07,.01-.27-.13-.27-.18,3.54-5.42,8.13-10.36,12-15.64,.36-.46,.64-.95,.29-1.49,0,.01,.14,.25,.14,.25l-.13-.16c-14.65,3.47-29.25,8.91-44.08,11.12-.07-.07-.13-.22-.08-.29,.35-.57,.68-1.15,1.09-1.69,2.95-3.86,5.91-7M .71,8.86-11.56,.32-.57,1.24-1.43,1.12-2.02-.17-.13-.43-.33-.58-.3-1.95,.41-3.9,.84-5.83,1.3-13.14,3.19-26.45,5.84-39.78,8.48-.51,.1-1.05,.14-1.59,.15-.33,0-.56-.19-.45-.38,2.6-4.43,5.96-8.41,8.86-12.65,.46-.64,1.08-1.25,1.08-2.04-.46-.31-.98-.27-1.5-.18-3.95,.67-7.9,1.33-11.85,2.01-8.15,1.42-16.33,2.74-24.57,3.79-4.89,.38-9.8,1.95-14.68,1.72-.32-.62,.12-1.07,.41-1.52,2.21-3.45,4.44-6.89,6.65-10.33,.39-.84,2.26-2.66,.47-2.9-15.77,1.47-31.53,3.24-47.38,4-3.22,.12-6.43,.59-9.66,.5-1.25-.31-.13-1.5,.14-2.19,2.13-4.06,4M .78-7.9,6.57-12.12-.12-.79-1.34-.54-1.94-.62-21.68,.64-43.35,.59-65.04,.04l.15,.09c2.43-5.2,4.86-10.4,7.29-15.59l-.11,.07c22.41,.6,44.88,.7,67.3,.63,.45,.66,.11,1.16-.14,1.64-1.55,2.98-3.12,5.95-4.68,8.93-.28,.98-2.77,3.75-.78,3.88,14.79-.46,29.54-1.62,44.27-2.88,4.41-.39,8.8-.97,13.22-1.27,.34-.03,.75,.42,.63,.67-2.23,4.42-5.14,8.49-7.47,12.86-.2,1.29,2.16,.57,2.91,.63,16.49-1.97,32.81-4.69,49.17-7.45,.2-.03,.47,.14,.67,.25,.13,.61-.68,1.48-.93,2.07-2.53,4.02-5.38,7.88-7.7,12.02,.89,.46,1.68,.26,2.46,.1,4.57-.91,9M .13-1.86,13.7-2.76,9.67-1.91,19.19-4.23,28.76-6.42,.9-.21,1.82-.39,2.74-.53,.16-.02,.4,.19,.55,.33,.12,.62-.75,1.45-1.05,2.04-2.33,3.27-4.68,6.54-7,9.81-1.53,2.28-2.71,3.44,1.12,2.55,6.52-1.71,13.02-3.45,19.55-5.14,6.02-1.56,11.91-3.39,17.85-5.12,1.3-.2,2.9-1.24,4.14-.72,.06,.03,.09,.2,.05,.28-.33,.58-.62,1.19-1.02,1.74-2.85,3.9-5.73,7.79-8.59,11.69-1.71,2.35-1.2,2.35,1.32,1.69,9.5-2.72,18.85-5.77,28.15-8.9,3.35-1.13,6.72-2.21,10.08-3.31,.3-.1,.57-.09,.69,.15,.27,.55-.23,1.01-.53,1.44-4.01,5.06-7.57,10.55-11.88,15.M 35,.16,.14,.21,.3,.43,.29l-.52-.31c2.13,.97,4.62-.91,6.74-1.36,10.97-3.62,21.79-8.17,32.65-11.65,.9,.25-1.32,2.53-1.57,3.08-4.25,5.18-8.03,10.81-12.6,15.71,0,0,.17,.08,.17,.08l-.09-.15c1.01,.81,2.28,0,3.32-.34,10.58-4.02,21.25-7.9,31.6-12.3,.26-.09,1.22-.37,1.29,.06-3.97,6.79-9.14,12.97-13.93,19.27-2.39,3.06,5.41-1.06,6.25-1.19,6.49-2.63,12.89-5.39,19.21-8.27,1.23-.37,2.68-1.61,3.94-1.22,.21,.38-.45,1.05-.64,1.42-3.54,4.83-7.08,9.66-10.63,14.49-1.5,2.04-3.04,4.07-4.54,6.11-.53,.97-.25,1.33,1.21,.76,8.71-3.62,17.32-M 7.45,26.01-11.11,.39-.13,1.04,.11,.77,.64-4.35,6.1-9.11,11.95-13.62,17.95-1.76,2.29-3.56,4.57-5.31,6.87-.29,.48,.29,.82,.73,.67,8.07-3.16,16.14-6.46,24.01-9.99,.84-.26,2.08-1.04,2.89-.9,.09,.17,.23,.41,.15,.54-.5,.76-1.05,1.5-1.61,2.24-6.15,8.69-15.4,18.96-20.87,27.13,.07,.08,.23,.19,.3,.17,.75-.23,1.52-.44,2.24-.72,7.24-2.87,14.47-5.76,21.7-8.63,1.11-.27,2.19-1.31,3.3-.68-8.62,11.65-18.25,22.65-27.31,33.93,1.13,.67,2.59-.36,3.79-.63,7.13-2.54,14.25-5.11,21.38-7.65,.59-.13,1.3-.53,1.88-.26,.08,.05,.17,.19,.13,.24-.M 37,.57-.72,1.15-1.15,1.68-10.08,12.51-20.66,24.79-31.3,36.9-1.05,1.56,.56,.96,1.5,.84,5.9-1.51,11.79-3.04,17.68-4.55,1.05-.14,2.49-.88,3.45-.6,.07,.05,.13,.18,.09,.24-.21,.39-.4,.8-.7,1.15-4.1,4.81-8.13,9.65-12.33,14.39-8.09,9.15-16.26,18.24-24.4,27.36-2.6,2.66-1.52,2.71,1.57,2.2,6.7-1.13,13.34-2.76,20.07-3.62,1.39,.17-.76,2.02-1.11,2.57-13.97,16.12-28.65,31.83-43.51,47.41-.51,.71-1.66,1.16-1.43,2.18,.9,.42,1.85,.18,2.75,.09,5.62-.55,11.22-1.14,16.84-1.69,1.46-.14,2.95-.19,4.42-.26,.33-.02,.51,.14,.51,.39-16.91,20.M 3-36.55,39.27-55.21,58.47-.61,.67-1.54,.86-2.48,.85-7.82,.04-15.63,.08-23.45,.11-.77,.01-1.87-.08-1.72-.85,18.36-18.02,37.14-35.65,54.89-54.27,.44-.6,1.39-1.12,1.1-1.94-1.34-.29-2.95,.05-4.36,.07-5.22,.46-10.43,1.03-15.64,1.53-1.34,.11-2.68,.17-4.02,.23-.33,.02-.51-.15-.5-.4,11.19-12.17,23.76-23.66,35.02-35.85,3.76-3.94,7.49-7.9,11.23-11.85,.56-.56,1.14-1.1,1.16-1.92-7.9,.6-15.72,2.92-23.66,3.76-1.2-.12,.96-1.88,1.21-2.31,13.04-13.6,26.3-26.93,38.41-41.16,.38-1.08-2.86,.26-3.4,.28-7.9,2.11-15.68,4.69-23.65,6.49-1.1M 4-.12,.6-1.58,.86-2.03,4.58-4.93,9.26-9.8,13.75-14.78,5.83-6.46,11.52-13.01,17.26-19.53,2.21-2.66-1.48-.92-2.72-.63-7.11,2.32-14.21,4.64-21.31,6.96-.87,.28-1.7,.67-2.7,.52l-.17-.14c.11-.3,.12-.66,.33-.9,3.73-4.23,7.51-8.42,11.21-12.66,5.01-5.74,9.97-11.51,14.95-17.27,.24-.39,.92-.98,.75-1.4-1.31-.4-2.75,.69-4.05,.98-6.99,2.53-13.98,5.06-20.97,7.59-1.15,.28-2.21,1.13-3.41,.69,2.48-3.51,5.58-6.57,8.27-9.92,4.9-6.17,10.52-11.91,14.98-18.35,.02-.04-.21-.22-.27-.21-.63,.14-1.28,.26-1.86,.49-8.61,3.35-17.15,6.82-25.88,9.M 87-.58,.11-1.35,.07-.67-.82,6.49-7.78,13.05-15.51,19.2-23.54,.26-.42-.04-1.02-.63-.71-9.19,3.6-18.38,7.19-27.72,10.54-1.22,.44-2.49,.82-3.74,1.21-.14,.02-.5-.23-.44-.41,1.84-2.82,4.46-5.1,6.58-7.72,3.77-4.33,7.5-8.68,11.24-13.03,.38-.44,.68-.92,1.01-1.39,.04-.06,.01-.23-.04-.25-.23-.07-.49-.16-.73-.15-7.38,2.53-14.66,5.44-22.03,8.05-4.29,1.56-8.63,3.02-12.95,4.53-.62,.22-1.26,.38-1.94,.15l.09,.06Z"/><path class="cls-2" d="M643.48,973.96s-.06,.03-.09,.04c-.02-.03-.03-.06-.05-.09l.14,.05Z"/><path class="cls-2" d="M67M 7.01,976.21c-3.68-.24-7.37-.5-11.07-.8,3.29-1.65,6.46-3.49,9.75-5.12,.27-.14,.91,.11,.93,.36,.21,1.85,.33,3.7,.39,5.56Z"/><path class="cls-2" d="M842.26,949.42c-1.02-.33-1.48,.56-2.13,1.13-3.17,3.35-6.32,6.71-9.48,10.07-1.47,1.42-1.98,1.37-1.7-.8,.51-5.44,1.87-10.94,1.29-16.4-.62-.44-1.08,.15-1.52,.55-3.64,4.12-7.6,8.02-11.05,12.28-.01-.01-.03-.03-.05-.04,.02,.01,.04,.03,.05,.05,0,.01-.01,.03-.02,.04-.04-.07-.05-.1-.05-.12-.46-.5-.53-1.1-.48-1.72,.25-4.84,.76-9.67,.69-14.52,0-.05-.19-.12-.31-.14-.58-.12-1.05,.6-1.4M 6,.91-3.87,3.99-7.36,8.34-11.48,12.07-1.37,.48-.74-1.53-.83-2.27,.35-3.66,.51-7.31,.5-10.98,0-.16-.22-.35-.37-.49-.2-.19-.69-.03-1.02,.3-3.05,3.14-5.97,6.39-9.06,9.5-2.26,2.28-4.66,4.47-6.99,6.69-.24,.3-.81,.19-.92-.17,0-3.87,.53-7.74,.02-11.61-.02-.16-.27-.38-.47-.43-.97-.03-1.55,1.1-2.25,1.62-4.88,4.74-9.61,9.63-14.63,14.22-.48,.49-1.62,.71-1.46-.31-.09-3.34,.12-6.68-.17-10.01-.02-.15-.33-.29-.54-.4-.77,.13-1.38,1.02-2.02,1.46-5.62,4.75-10.87,10.02-16.68,14.49-.86,.15-.83-.86-.87-1.44-.04-2.89,.1-5.81-.04-8.7-.98M -.45-1.56,.4-2.29,.88-3.53,2.97-7.02,5.97-10.59,8.9-2.26,1.85-4.64,3.6-6.98,5.39-.27,.2-.66,.49-1.03,.2-.24-.2-.42-.55-.41-.83-.18-2.86,.63-5.9-.19-8.65-.05-.12-.53-.26-.64-.2-.75,.44-1.51,.88-2.18,1.39-5.34,4.12-10.96,7.98-16.59,11.84-.98,.5-1.77,1.59-2.94,1.52-.51-.11-.49-.47-.5-.77-.1-2.69,.1-5.4-.23-8.07-.03-.29-.63-.52-.94-.35-6.13,3.55-12.02,7.48-18.14,11.07,5.54,.3,11.07,.54,16.57,.7,.82-.5,2.53-1.73,2.55,.08,4.55,.12,9.08,.2,13.6,.23,2.53-1.76,4.91-3.62,7.39-5.42,.5-.37,1.05-.75,1.71-.5,.58,1.66,.14,4.09,.1M 2,5.92,2.28-.02,4.55-.05,6.82-.1,2.89-2.18,5.72-4.41,8.45-6.71,1.87-1.31,3.69-3.66,5.81-4.35,.33,.01,.53,.15,.52,.39-.07,3.55-.63,7.08-.94,10.61-.01,.1,.07,.27,.15,.29,.73,.27,1.25-.3,1.77-.69,5.75-4.77,11.46-9.59,17.19-14.38,.35-.32,1.29-1.11,1.58-.67,.11,.18,.3,.37,.29,.55-.26,3.12-.55,6.23-.81,9.35-.07,.75-.08,1.5-.09,2.25,0,.04,.19,.11,.3,.13,.71,.14,1.54-.93,2.11-1.3,4.94-4.56,9.86-9.13,14.8-13.69,.82-.6,1.37-1.63,2.56-1.34-.36,4.5-.53,9.02-1.28,13.5-.03,.13,.21,.32,.38,.44,.68,.01,1.25-.8,1.81-1.15,5.01-4.37,M 9.62-9.01,14.2-13.67,.55-.42,2.29-2.7,2.73-1.4,.09,3.67-.67,7.29-1.08,10.93-.16,1.28-.29,2.57-.42,3.85-.02,.27,.16,.42,.46,.42,.71,0,1.22-.81,1.74-1.2,3.38-3.36,6.73-6.73,10.11-10.09,.53-.38,1.04-1.19,1.75-1.18,.5,0,.4,.73,.42,1.07-.5,3.79-1.01,7.57-1.58,11.35,2.3-.34,4.59-.68,6.88-1.04,1.8-1.79,3.6-3.58,5.39-5.37,.32-.31,.96-.51,1.05-.34,.52,1.27-.29,3.28-.33,4.72,4.24-.71,8.46-1.46,12.66-2.26,.84-5.67,1.62-11.38,1.81-17.08Z"/><path class="cls-2" d="M851.64,1006.57c-2.31,1.84-4.54,3.78-6.9,5.55-.17,.11-.48,.09-.73M ,.09-.06,0-.18-.17-.17-.26,.07-1.39,.48-2.73,.85-4.08,2.33-.42,4.64-.85,6.95-1.3Z"/><path class="cls-2" d="M853.69,958.85c-.04,1.73-.26,3.44-.56,5.14-2.48,.52-4.98,1.03-7.48,1.52,.96-.59,7.93-8.9,8.04-6.66Z"/><path class="cls-2" d="M906.3,1224.16s-.11,.02-.16,.03l.06-.15,.1,.12Z"/><path class="cls-2" d="M883.55,1226.6c-.64,1.57-.8,2.22,1.22,1.92,7.11-1.53,14.24-2.91,21.37-4.33-9.28,25.7-20.38,50.73-31.19,75.81,.68,.49,1.36,.4,2,.34,7.22-.74,14.42-1.54,21.63-2.28,.98-.08,1.32,.61,1,1.31-12.13,29.39-25.6,58.22-39.63,M 86.76-8.94,.46-18.02,.31-26.97,.09-.28-.49-.24-.9-.03-1.31,1.07-2.09,2.11-4.2,3.22-6.28,13.18-25.47,26.61-50.91,37.7-77.24,.02-.14-.29-.45-.43-.45-1.74,.07-3.48,.1-5.21,.28-4.94,.52-9.86,1.11-14.8,1.65-1.3,.01-2.73,.46-3.94-.07-.17-.79,.29-1.46,.63-2.16,3.33-6.94,6.72-13.85,9.98-20.8,7.56-16,14.54-32.13,21.4-48.4,1.12-2.18-.01-2.36-1.94-1.84-6.12,1.3-12.23,2.6-18.34,3.9-1.7,.33-2.31,.22-1.49-1.69,2.94-6.7,5.99-13.37,8.83-20.1,5.7-13.66,11.65-27.21,16.41-41.19,.02-.1-.37-.39-.5-.37-.78,.15-1.56,.33-2.31,.56-5.77,1.7M 9-11.46,3.8-17.26,5.46-1.28,0-.45-1.43-.26-2.13,3.08-7.8,6.26-15.57,9.25-23.39,3.64-9.57,7.29-19.1,10.24-28.86-.44-.76-1.73,.04-2.37,.19-5.51,2.24-10.9,4.75-16.47,6.84-1.25,.13-.18-1.85-.02-2.46,4.01-10.39,7.62-20.86,11.07-31.38,1.27-3.85,2.5-7.7,3.73-11.56,.12-.72,.47-1.49,.13-1.88-.98-.45-1.87,.53-2.76,.85-4.15,2.21-8.29,4.42-12.44,6.63-.78,.32-1.52,1.11-2.41,.79-.08-.02-.17-.19-.15-.28,3.94-13.08,8.45-25.99,11.97-39.19,.74-2.56-.81-1.59-2.28-.67-4.57,2.83-8.98,5.92-13.67,8.56-1.83,.24,.65-4.79,.81-5.84,1.96-5.71M ,3.26-11.54,4.82-17.33,1-3.68,2.03-7.35,3.03-11.03,.12-.42,.17-.85,.23-1.28,.01-.09-.07-.26-.15-.28-1-.3-1.75,.78-2.55,1.19-3.59,2.61-7.17,5.23-10.75,7.84-.69,.59-1.4,1.02-2.34,1.08-.31-1.13,.41-2.33,.64-3.47,2.33-7.88,4.07-15.86,5.98-23.84,4.59-.93,9.15-1.91,13.69-2.94-1.12,5.34-2.26,10.67-3.38,16.01-.21,1.21-.52,2.34,1.12,1.61,3.85-2.66,7.5-5.58,11.27-8.34,.86-.51,1.57-1.46,2.68-1.21,.29,1.19-.06,2.35-.33,3.51-2.25,10.91-5.28,21.78-7.56,32.67,.38,.81,2.02-.64,2.59-.84,4.03-2.53,8.04-5.07,12.06-7.61,.53-.33,1.04-.M 7,1.93-.59-1.73,9.57-4.62,18.98-7.06,28.43-1.14,4.21-2.42,8.39-3.62,12.59-.06,.36-.26,.95,.05,1.23,.72,.09,1.5-.45,2.16-.7,3.73-1.94,7.43-3.9,11.15-5.86,1.36-.57,2.59-1.82,4.15-1.67,.47,.64-.09,1.73-.2,2.48-3.12,10.8-6.15,21.64-9.57,32.36-1.29,4.07-2.62,8.13-3.93,12.2-.09,.31-.1,.64-.14,.96-.04,.24,.57,.56,.88,.45,5.09-1.89,10.03-4.18,15.06-6.22,.84-.35,1.71-.64,2.56-.95,.31-.11,.54-.04,.65,.19,.18,.29,.11,.62,.04,.94-2.94,9.51-5.9,19.01-9.19,28.45-2.67,7.67-5.13,15.39-8.21,22.97-.41,1.02-.67,2.08-.98,3.12-.1,.31,.M 34,.69,.68,.61,5.98-1.53,11.81-3.63,17.74-5.36,1.46-.36,3.07-.93,2.2,1.3-6.99,20.76-14.8,41.25-23.12,61.54Z"/><path class="cls-2" d="M912.65,421.86l.18-.03s-.03,.08-.04,.12l-.14-.09Z"/><path class="cls-2" d="M964.38,416.15s.06-.08,.1-.12h.05l-.15,.12Z"/><path class="cls-2" d="M968.57,404.41c-.1-1.63-7.32,.01-8.71-.05-14.05,1.11-27.96,3.18-41.89,5.17-.6,.09-1.1-.31-.95-.74,.95-2.58,1.96-5.15,2.82-7.74,.33-1.02,1.19-1.96,.79-3.1-.14-.39-.93-.33-4.22,.29-.65,.13-1.31,.26-1.96,.38-13.09,2.34-26.04,5.33-39.01,8.26-1.27,M .01-.55-1.44-.37-2.14,1.07-2.78,2.19-5.54,3.28-8.31,.25-.64,.35-1.03-.32-1.48-13.72,3.51-27.37,7.64-40.84,11.91-.47-.44-.52-.86-.35-1.28,1.09-2.77,2.2-5.54,3.29-8.31,.17-.73,1.35-2.43-.04-2.45-11.25,3.34-22.22,7.72-33.11,11.9-1.2,.48-2.41,.96-3.63,1.41-.16,.05-.47-.1-.68-.19-.09-.04-.16-.2-.14-.28,.17-.63,.31-1.27,.55-1.88,1.15-2.98,2.32-5.96,3.48-8.94,.16-.4,.21-.82-.31-1.2-11.21,3.95-21.88,9.44-32.61,14.02-1.59,.05,2.4-8.38,2.68-9.69,.33-.92,.64-1.86,.94-2.79,0-.18-.38-.39-.57-.34-8.22,3.65-16.13,8.21-24,12.47-.6M 2,.2-3.13,2.05-3.29,1.11,.45-3.66,2.46-7.02,3.54-10.54,.3-.83,.55-1.67,.8-2.5,.03-.08-.08-.25-.16-.27-.65-.28-1.2,.13-1.73,.43-8.31,4.35-15.87,9.62-23.9,14.24-.46-.47-.35-.89-.21-1.3,1.36-3.83,2.55-7.7,4.24-11.45,.21-.82,1.2-1.97,.54-2.69-.03-.04-.29-.02-.38,.04-7.41,4.41-14.66,9.09-21.93,13.74-.84,.4-1.63,1.36-2.64,1.11-.08-.01-.16-.2-.13-.29,1.75-5.43,4.25-10.63,6.12-16.03,.04-.15-.16-.35-.28-.57-5.95,3.12-11.03,7.56-16.66,11.22-1.83,1.28-3.66,2.54-5.49,3.81-.4,.28-.81,.54-1.53,.48,1.31-5.59,3.84-10.96,6.03-16.34M ,.37-.8,.63-1.64,.91-2.46,.02-.07-.11-.21-.21-.26-.58-.07-1.19,.48-1.67,.73-6.51,4.52-13.01,9.05-19.52,13.57-.59,.41-1.05,1-1.97,1.02-.7-.76,.11-1.41,.29-2.08,.25-.94,.73-1.85,1.1-2.77,2.06-5.01,4.12-10.02,6.17-15.03,.2-.49,.62-.98,.25-1.54-1.04,.05-1.62,.69-2.3,1.17-6.63,4.53-13.01,9.45-19.77,13.77-.21,.11-.58,0-.55-.27,2.52-8.08,6.37-15.79,9.77-23.57,.14-.7-.21-.94-1.04-.46-4.91,3.19-9.76,6.45-14.64,9.67-.51,.34-.99,.73-1.73,.7-.36-.61-.06-1.21,.19-1.78,3.77-8.43,7.41-16.91,11.58-25.16,.78-1.86-1.9-.25-2.47,.13-4M .06,2.5-8.12,4.99-12.18,7.49-.95,.46-1.87,1.51-2.96,1.49-.56-.55,.21-1.46,.39-2.09,4.3-9.29,8.37-18.64,13.13-27.79,.31-.6,.54-1.22,.78-1.83,.03-.07-.08-.2-.17-.26-.64-.21-1.5,.46-2.09,.68-4.64,2.59-9.27,5.19-13.9,7.79-.61,.18-1.88,1.32-2.29,.51,4.87-11.61,11.08-22.64,16.86-33.9,.36-.69,.66-1.4,.97-2.11,.03-.07-.06-.2-.14-.28-.06-.07-.21-.16-.26-.14-.61,.22-1.23,.43-1.8,.71-5.53,2.61-10.99,5.46-16.57,7.93-.69-.56-.4-1.07-.15-1.56,2.45-4.78,4.87-9.57,7.36-14.34,4.15-7.95,8.47-15.84,12.94-23.68,.39-.68,.72-1.38,1.02-2M .09,.06-.14-.19-.36-.36-.65-5.92,2.3-11.76,4.78-17.65,7.15-.69,.18-1.49,.72-2.19,.51,6.66-15.21,16.53-30.21,24.95-45.04,.35-.58,.75-1.15,1.02-1.75,.2-.46,.91-.95,.27-1.44-.44-.33-1,.04-1.48,.16-6.03,1.86-12.01,3.83-18.03,5.7-.48,.15-1.03,.16-1.55,.2-.09,.01-.3-.15-.29-.2,.15-.52,.25-1.06,.52-1.54,9.98-18.14,21.13-35.57,31.88-53.3,.22-.73-1.17-.45-1.56-.44-4.3,.91-8.58,1.84-12.87,2.77-2.34,.51-4.67,1.04-7.01,1.55-.53,.11-1.06,.09-1.67-.22,12.22-21.61,26.32-42.22,39.85-63.08,.23-1.22-3.01-.46-3.8-.52-6.78,.57-13.61,1M .85-20.37,2.09-.19-.09-.44-.36-.38-.47,.38-.8,.77-1.59,1.26-2.35,14.06-21.69,28.18-43.19,43.23-64.31,1.35-2.1,3.12-4,4.21-6.24-.1-.81-1.32-.57-1.93-.65-6.87,0-13.75,.01-20.62,.02-1.64,.18-4.13-.58-5.18,.97-16.11,24.91-32.93,49.66-46.95,75.69,1.88,.78,3.74-.18,5.66-.22,5.74-.65,11.47-1.29,17.21-1.92,.56-.06,1.96-.24,1.74,.64-6.3,10.62-12.89,21.08-19.14,31.71-6.28,10.61-12.36,21.29-18.3,32.02-.23,.66-1.16,1.41-.58,2.07,.93,.46,2.11-.19,3.1-.27,5.06-1.12,10.12-2.24,15.18-3.36,1.64-.25,3.08-1.03,4.74-.48-10.55,18.5-21.M 19,36.95-30.69,55.98-.11,.35-.63,1.33-.08,1.44,6.01-1.36,11.75-3.71,17.67-5.43,.95-.3,1.85-.91,3.02-.59,.51,.14,.43,.48-.78,2.64-8.46,15.33-16.52,30.78-23.91,46.6,0,.25,.22,.76,.61,.6,6.43-2.31,12.63-5.3,19.01-7.73,.55,.44,.41,.83,.2,1.24-6.94,13.83-14.17,27.65-20.04,41.92,0,.22,.47,.64,.77,.48,5.31-2.51,10.47-5.3,15.73-7.91,.6-.21,1.49-.85,2.09-.64,.09,.07,.21,.2,.18,.27-.29,.83-.56,1.66-.93,2.46-3.01,6.46-6.1,12.89-9.05,19.36-2.15,5.19-4.85,10.23-6.48,15.56,0,.05,.21,.19,.27,.17,.48-.17,1-.3,1.42-.55,4.58-2.65,9.M 14-5.33,13.72-7.99,.65-.37,1.36-.67,2.06-.99,.18-.07,.52,.15,.5,.34-2.78,7.32-6.18,14.44-9.17,21.7-1.39,3.26-2.76,6.53-4.13,9.79-.18,.42-.24,.84,.15,1.44,5.77-3.44,10.86-7.42,16.78-10.63,.6,.64,.08,1.17-.14,1.82-3.7,8.44-6.93,16.99-10.25,25.52-.1,.46-.51,1.19-.11,1.54,.62,.15,1.43-.58,1.97-.85,4.83-3.15,9.33-7.19,14.38-9.83,.51,.39,.23,.94,.04,1.42-3.09,7.68-5.98,15.4-8.46,23.24,.02,.23,.46,.6,.75,.38,4.62-3.28,9.12-6.7,13.7-10.04,3.44-2.51,2,.13,1.22,2.24-2.06,5.24-3.98,10.51-5.64,15.84-.26,.83-.5,1.67-.69,2.52,.0M 1,.18,.51,.59,.78,.36,6.24-4.55,12.24-9.41,18.4-14.07,.8-.48,1.62-1.37,2.53-1.51,.52,.4,.27,.94,.09,1.45-1.49,4.4-2.98,8.79-4.47,13.19,2.03-.16,4.07-.3,6.11-.44,4.23-3.39,8.75-6.51,13.23-9.69,.49-.35,.93-.79,1.66-.85,.1-.01,.29,.05,.29,.08,.01,.31,.06,.64-.04,.93-1.1,2.94-2.16,5.89-3.13,8.85,3.12-.16,6.24-.3,9.38-.4,3.08-2.26,6.16-4.51,9.24-6.75,.79-.43,1.55-1.42,2.54-1.19,.07,.02,.14,.2,.12,.29-.73,2.46-1.5,4.92-2.27,7.37,3.31-.08,6.63-.13,9.96-.15,3.43-2.24,6.9-4.44,10.34-6.67,.59-.27,1.35-.94,2.02-.81,.09,.06,.1M 9,.19,.18,.28-.62,2.43-1.57,4.78-2.3,7.18,2.95,.02,5.9,.06,8.86,.12,4.58-3.03,9.3-5.77,14.06-8.55,.16-.09,.48-.03,.72,0,.08,.02,.2,.19,.18,.28-.68,2.89-1.58,5.73-2.39,8.59,2.05,.08,4.13,.16,6.19,.25,6.12-3.58,12.52-6.82,18.82-10.18,.32-.13,.74-.47,1.08-.3,.16,.14,.38,.33,.35,.48-.75,3.71-2.01,7.31-2.95,10.98-.01,.02-.01,.04-.02,.06,.05,.22,.47,.62,.8,.48,.7-.32,1.4-.63,2.08-.98,8.84-4.55,18-8.67,27.4-12.44,.4-.17,1.66-.64,1.81-.24,.07,.2,.18,.42,.12,.6-.76,2.52-1.56,5.02-2.31,7.53-.28,.94-.46,1.9-.67,2.85-.06,.26,.M 55,.59,.86,.48,10.7-4.43,21.57-8.41,32.51-12.27,.91-.14,3.89-1.91,4.03-.36-.03,1.65-4.42,10.57-2.55,10.69,12.63-3.68,25.09-7.8,37.96-10.97,.77-.17,2.5-.86,2.49,.39-.62,1.99-1.26,3.96-1.86,5.95-.39,1.25-.73,2.51-1.07,3.77-.12,.48,.35,.86,.9,.73,14.54-3.2,29.02-6.89,43.85-8.73,.78,.17,.53,1.12,.38,1.7-1,3.31-2.02,6.61-3.02,9.91,17.09-2.82,34.37-4.56,51.65-5.8,.19-.23,.41-.45,.5-.71,1.13-3.64,2.86-7.2,3.59-10.91Zm-318.22-18.56s.09-.15,.14-.16c.06,0,.12,.02,.19,.05-.09,.2-.2,.24-.33,.11Z"/><path class="cls-2" d="M638.2M 3,415.15l-.03,.03-.04-.04,.14-.06s-.05,.04-.07,.07Z"/><path class="cls-2" d="M663.18,54.75c-15.45,25.12-30.3,50.57-44.27,76.5-.94,1.32-.67,2.28,1.13,1.98,6-.68,12-1.37,18-2.05,1.56-.09,3.21-.48,4.74-.11,.23,.62-.08,1.11-.36,1.59-1.53,2.64-3.11,5.26-4.6,7.91-10.94,19.38-21.61,38.84-31.36,58.8-.12,.29,.35,.63,.76,.54,7.15-1.53,14.29-3.09,21.44-4.63,1.6,0-.13,1.97-.32,2.68-9.84,18.69-19.83,37.43-28.25,56.69,.36,.67,1.46,.17,2.04,.04,6.14-1.92,12.21-4.03,18.39-5.85,1.38-.26,.58,1.39,.21,1.98-8.1,16.31-16.15,32.58-22.9,M 49.33,.36,.69,1.43,.1,1.98-.07,5.83-2.37,11.56-5.1,17.45-7.31,.52,.48,.36,.91,.19,1.3-1.19,2.64-2.4,5.26-3.61,7.89-5.1,11.12-9.95,22.3-14.41,33.6-.19,.7-.81,1.49-.22,2.13,4.95-1.71,9.52-4.87,14.32-7.12,1.01-.52,2.06-1.02,3.12-1.49,.14-.06,.44,.05,.63,.13,.09,.04,.16,.2,.13,.29-.24,.72-.46,1.45-.78,2.16-4.51,10.03-8.54,20.19-12.44,30.38-.7,1.85-1.27,3.73-1.89,5.6-.02,.09,.06,.27,.14,.29,1.11,.32,1.99-.85,2.97-1.26,4.52-2.71,9.04-5.42,13.58-8.12,.13-.08,.45,0,.67,.06,.07,.02,.13,.18,.13,.28-.15,1.09-.73,2.07-1.08,3.1M -2.69,7-5.4,13.99-8.05,20.99-1.01,2.68-1.9,5.39-2.8,8.09-.13,.4-.03,.84-.01,1.26,.4,.29,1.23-.37,1.63-.56,4.89-3.07,9.48-7.11,14.59-9.59,.13,.16,.31,.37,.27,.52-.43,1.35-.9,2.7-1.38,4.05-1.93,5.38-3.9,10.75-5.79,16.14-.94,2.69-1.74,5.42-2.58,8.14-.08,.27,.03,.59,.05,.9,.97-.07,1.45-.64,2.03-1.07,4.13-3.09,8.26-6.19,12.39-9.28,.4-.23,.86-.72,1.36-.54,.1,.04,.22,.17,.2,.24-.17,.84-.31,1.69-.58,2.52-2.11,6.46-4.25,12.91-6.36,19.36-.38,1.15-.69,2.3-1.01,3.46-.03,.09,.04,.27,.11,.28,.65,.24,1.16-.21,1.62-.56,4.57-3.75,9M .36-7.26,13.8-11.16,.02,.03,.05,.05,.06,.08,.28,.32,.41,.69,.33,1.08-.87,3.24-1.89,6.44-2.81,9.67-8.99,1.08-17.91,2.33-26.76,3.77,5.7-20.52,8.1-18.78-8.9-6-.7,.44-1.26,1.33-2.19,1.11-.07,0-.19-.18-.17-.26,1.36-5.05,2.67-10.11,4.13-15.14,1.2-4.09,2.61-8.13,3.89-12.2,.26-.83,.4-1.68,.57-2.52,.02-.08-.09-.21-.19-.26-.1-.05-.31-.08-.39-.03-.94,.6-1.9,1.19-2.8,1.83-4.07,2.81-7.89,5.96-12.12,8.52-.65,.23-.83-.67-.61-1.13,2.35-7.85,4.66-15.7,7.52-23.45,1.06-2.89,2.04-5.8,3.05-8.7,.08-.49,.52-1.12,.25-1.55-.2-.06-.51-.15-.M 64-.08-3.02,1.8-6.04,3.6-9.04,5.43-2.04,1.23-4.05,2.51-6.08,3.75-.39,.23-.81,.52-1.4,.34-.26-.55,.09-1.05,.25-1.56,2.67-8.56,5.62-17.07,8.76-25.53,1.34-3.61,2.75-7.2,4.1-10.81,.23-.61,.57-1.22,.36-1.88-.03-.08-.18-.22-.23-.21-.37,.08-.78,.13-1.1,.3-4.4,2.29-8.78,4.61-13.18,6.91-.9,.47-1.82,.91-2.74,1.36-.32,.13-.73-.27-.74-.53,1.87-6.64,4.7-13.03,7.06-19.52,3.09-7.91,6.34-15.78,9.51-23.67,.17-.78,.98-1.7,.36-2.42-5.7,1.68-11.19,4.75-16.8,6.91-.64,.15-1.92,.99-2.36,.21,4.46-13.75,10.75-27.07,16.46-40.49,1.68-3.74,3.M 36-7.49,5.04-11.24,.18-.41,.31-.83-.18-1.25-6.31,1.58-12.41,4.04-18.64,5.96-.61,.2-1.23,.38-1.9,.23-.33-.66-.01-1.27,.25-1.87,1.93-4.48,3.83-8.97,5.81-13.43,6.58-15.41,14.29-30.42,21.21-45.69,.04-.13-.27-.46-.4-.45-.79,.05-1.6,.1-2.37,.26-5.97,1.31-11.94,2.63-17.91,3.95-.67,.16-2.27,.61-1.98-.57,10.41-23.34,21.91-46.19,34.02-68.75,.29-.56,.86-1.11,.48-1.8-.78-.32-1.58-.13-2.37-.04-6.54,.74-13.07,1.49-19.61,2.22-.72-.03-2.67,.47-2.6-.64,8.94-18.71,18.77-36.9,28.75-55.14,4.44-7.96,8.88-15.93,13.35-23.88,.54-.97,.9-2.M 04,2.02-2.87,8.15-.28,16.38-.03,24.56-.1,.95,0,2.93-.11,2.04,1.34Z"/><path class="cls-2" d="M797.54,422.88c-.18,.75-.39,1.49-.59,2.24-2.02-.23-4.05-.43-6.08-.62,1.79-.77,3.59-1.55,5.42-2.22,.54-.31,1.37-.13,1.25,.6Z"/><path class="cls-2" d="M831.75,420.82c-.51,2.88-1.38,5.7-2.01,8.55-5.9-.9-11.83-1.74-17.8-2.49,5.5-2.08,11.06-4.06,16.62-6.04,.86-.15,3.1-1.6,3.19-.02Z"/><path class="cls-2" d="M867.39,431s.01-.05,.02-.07c.02-.01,.04-.01,.06-.02l-.08,.09Z"/><path class="cls-2" d="M869.74,421.17c-.76,3.26-1.55,6.5-2.33M ,9.76-3.86,.99-7.76,1.92-11.61,2.94-7.41-1.43-14.88-2.74-22.41-3.92,11.46-3.68,23.02-7,34.7-10,1.1-.31,2.04-.19,1.65,1.22Z"/><path class="cls-2" d="M516.24,1302.89c.91,.4,1.85,.16,2.75,0,2.63-.45,5.25-.94,7.87-1.44,6.02-1.16,12.03-2.33,18.05-3.49,.72-.07,1.59-.41,2.19,.14-13.96,13.66-29.89,26.26-44.77,39.36-2.86,2.42-4.31,3.58,.74,2.92,8.13-.87,16.23-2.1,24.39-2.69,.11,0,.33,.07,.34,.13,.04,.19,.11,.46-.01,.58-.77,.75-1.57,1.47-2.39,2.19-17.73,15.34-35.78,30.51-53.98,45.45-.98,.87-2.51,.75-3.78,.76-7.79-.14-15.62,.M 34-23.38-.2-1.05-.77,1.6-2.12,2.07-2.7,16.3-13.47,32.59-26.93,48.88-40.41,.35-.44,2.51-1.8,1.59-2.23-9.35,.38-18.63,2.28-28,2.66-.18,0-.41-.35-.32-.49,.68-.66,1.34-1.34,2.08-1.96,14.11-11.83,28.18-23.72,42.09-35.76,3.53-2.91-1.41-1.23-3.03-1.14-8.81,1.53-17.62,3.07-26.43,4.59-1.69-.37,1.47-2.2,1.94-2.8,12.08-10.67,24.92-20.89,36.24-32.07-.56-.41-1.19-.12-1.79,0-8.83,1.93-17.65,3.86-26.48,5.77-1.55,.34-3.14,.59-4.71,.86-.11,.02-.34-.04-.36-.1-.06-.17-.14-.42-.04-.53,10.65-10.26,22.91-19.55,32.99-30.2-12.26,2.45-23.6M 5,5.87-35.97,8.23,.68-1.65,2.04-2.31,3.21-3.54,7.43-6.82,14.86-13.64,22.28-20.47,.92-1.01,2.37-1.74,2.66-3.12,.17-.03,.39-.05,.28-.25-.26-.02-.33,.09-.19,.31-.8-.29-1.58-.08-2.34,.11-3.7,.91-7.38,1.86-11.08,2.78-7.94,1.73-15.76,4.36-23.8,5.5l.06,.09c-.03-.2-.18-.47-.07-.59,.71-.78,1.44-1.55,2.22-2.29,6.64-6.38,13.29-12.74,19.93-19.12,.52-.5,1.03-1,1.49-1.53,.1-.11,0-.37-.08-.54-.76-.25-1.88,.25-2.69,.37-11.52,3.01-23.15,5.71-34.8,8.37-3.14,.77-2.07-.49-.53-1.95,6.26-6.35,12.8-12.45,18.91-18.94,.3-1.15-1.4-.44-1.99-M .38-12.5,3.03-25.14,5.66-37.74,8.39-.82,.07-1.87,.59-2.55-.05-.07-.06-.07-.24-.01-.31,.53-.62,1.06-1.24,1.63-1.84,4.99-5.22,9.99-10.43,14.98-15.66,.32-.45,1.63-1.65,.61-1.79-14.38,2.75-28.71,5.79-43.21,8.19-.73,.06-1.6,.35-2.21-.17-.07-.05-.09-.23-.03-.31,4.78-5.92,10.3-11.25,15.08-17.17,.1-.22-.12-.75-.47-.69-10.72,1.63-21.34,3.61-32.11,5-5.58,.7-11.12,1.73-16.71,2.31-.26-.03-.74-.29-.57-.62,3.73-4.9,7.77-9.57,11.62-14.38,.32-.57,2.33-2.43,.96-2.64-4,.44-8,.91-11.99,1.35-14.11,1.4-28.3,3.38-42.44,3.86-.16-.75,.37-M 1.28,.76-1.83,2.44-3.47,4.89-6.94,7.34-10.41,.6-.84,1.23-1.67,1.76-2.54,.39-.65,1.38-1.31,.74-2.04-.46-.53-1.5-.24-2.28-.18-19.51,1.31-39.04,2.04-58.59,2.32-.46-1.31,.66-2.23,1.15-3.36,2.2-3.93,4.42-7.86,6.61-11.79,1.49-2.58-.23-1.98-2.17-2.14-22.51,.08-44.98-.98-67.45-2.01l.09,.1c2.43-6.07,4.86-12.13,7.29-18.2l-.12,.07c24.25,2,48.57,2.9,72.9,3.25l-.09-.1c-2.84,5.22-5.68,10.44-8.51,15.66-.42,.78-.06,1.18,1.12,1.17,20.85,.12,41.66-1.01,62.47-1.86l-.06-.11c-3.46,5.11-6.92,10.22-10.38,15.33-.3,.47-.49,1.2,.3,1.32,10.4M 7-.6,20.89-1.64,31.32-2.68,7.89-.75,15.75-1.68,23.6-2.61,.34-.04,.78,.42,.65,.66-.17,.29-.31,.6-.51,.87-3.28,4.34-6.69,8.59-10.01,12.9-.49,.64-.93,1.31-1.37,1.97-.21,.4,.34,.46,.62,.56,16.87-1.79,33.57-5.37,50.34-7.41,.2,.64-.26,1.06-.62,1.48-4.36,5.18-8.88,10.25-13.17,15.49-.08,.22,.14,.72,.51,.66,1.85-.22,3.69-.62,5.52-.94,13.5-2.45,26.89-5.38,40.34-8.03,1.06,.2-.31,1.36-.59,1.82-4.28,4.7-8.58,9.39-12.86,14.09-.71,.78-1.39,1.58-2.07,2.38-.29,.35,.32,.55,.54,.55,13.44-2.62,26.67-6.03,39.94-9.2,1.02-.15,2.07-.69,3.M 08-.3,.05,.6-.49,.97-.89,1.38-5.86,6.33-12.18,12.28-17.84,18.78,1.27,.34,2.26-.14,3.25-.37,4.9-1.18,9.77-2.42,14.63-3.68,7.59-2.16,15.44-3.72,22.88-6.28l-.02-.05c.86,1.14-.68,1.96-1.33,2.77-5.57,5.54-11.14,11.08-16.71,16.62-1.03,1.24-5.53,4.61-.98,3.38,11.98-3.24,24.05-6.18,35.93-9.73,1.38,.06-.89,1.99-1.25,2.43-6.86,6.8-13.74,13.6-20.81,20.2-1.24,1.26-4.29,3.67-.25,2.61,10.83-2.94,21.66-5.87,32.45-8.93,3.55-.99,1.25,.81,.04,2.15-6.14,5.86-12.3,11.71-18.47,17.55-.59,.93-10.64,8.92-8.22,8.72,11.07-2.62,22.01-5.69,33M .01-8.59,3.22-.52-.59,2.19-1.3,3.01-10.02,9.16-20.04,18.32-30.06,27.48-.53,.49-1.05,.98-1.52,1.51-.1,.11,0,.36,.07,.53,.03,.06,.25,.13,.36,.1,3.11-.68,6.24-1.33,9.33-2.06,7.23-1.69,14.45-3.42,21.68-5.13,.4,0,1.2-.32,1.28,.14-12.14,12.22-25.76,23.14-38.51,34.8-.7,.62-1.67,1.12-1.84,2.06-.18,.23-.16,.26,.08,.09l-.19-.14Z"/><path class="cls-2" d="M1023.11,1078.99h.02s.01,.03,.02,.05l-.04-.05Z"/><path class="cls-2" d="M1240.27,858.9s.01-.05,.02-.07c.04,0,.07,0,.1,.01l-.12,.06Z"/><path class="cls-2" d="M1081.64,859.25c-M .66,.6-1.33,1.19-2.02,1.78-.24-.82-.49-1.64-.73-2.46-.03-.08,.06-.25,.14-.27,.98-.34,1.8,.53,2.61,.95Z"/><path class="cls-2" d="M1096.81,842.07c-1.72,2.46-3.56,4.85-5.51,7.16-1.35-4.05-2.81-8.06-4.08-12.13-.08-.31-.2-.66,.23-.82,.19-.07,.56,0,.74,.11,2.96,1.78,5.75,3.76,8.62,5.68Z"/><path class="cls-2" d="M1097.61,931.04c-.8,.13-1.31-.24-1.84-.57-4.61-2.8-9.17-5.69-13.88-8.36-1.67-.89-1.85-.12-1.64,1.48,2.13,10.62,4.16,21.26,5.93,31.95-.05,1.26,2.02,7.54-1,5.37-4.38-2.56-8.84-4.94-13.29-7.37-.55-.25-1.53-.89-2.01-.M 29,.63,9.55,2.75,19.02,3.46,28.59,.42,4.19,.81,8.38,1.19,12.57-.03,.65,.2,1.89-.75,1.85-5.21-2.19-10.07-5.11-15.34-7.17-.15-.05-.6,.11-.63,.22,.7,15.67,1.96,31.4,1.8,47.13-.32,1.68-7.07-2.39-8.41-2.63-2.4-.99-4.75-2.07-7.19-2.96-.67-.24-1.45,.07-1.49,.61-.59,17.55-.36,35.25-2.32,52.69-2.21,.09-4.21-1.27-6.33-1.83-3.2-1.13-6.41-2.26-9.63-3.36-.3-.1-.74,.02-1.11,.03-.74-1.36-.21-2.92-.18-4.4,.21-2.79,.43-5.58,.64-8.38,1.1-13.21,1.81-26.44,2.18-39.69,.05-1.75,.14-2.74,2.56-1.73,3.9,1.45,7.81,2.92,11.71,4.38,.62,.15,1.M 62,.62,2.11,.02,.68-2.69,.21-5.58,.34-8.36-.16-12.82-.73-25.62-1.19-38.42,.51-1.28,3.17,.62,4.13,.78,3.44,1.48,6.87,2.97,10.3,4.46,.48,.21,.96,.4,1.58,.12-.25-14.21-3.14-28.58-4.17-42.69,.64-.6,1.42-.03,2.08,.2,3.93,1.88,7.85,3.78,11.77,5.66,.68,.33,1.29,.81,2.24,.67,.06-3.9-1.26-7.89-1.72-11.8-.95-5.68-1.91-11.35-3.01-17,2.88-1.86,5.73-3.73,8.56-5.65,6.91,3.61,6.99,4.87,5.09-3.46,4.55-3.13,9.04-6.33,13.46-9.59,2.05,8.95,4.67,17.94,6,26.93Z"/><path class="cls-2" d="M1106.77,824.31c-1.37,3.13-2.89,6.2-4.57,9.18-1.8-M 4.91-3.64-9.8-5.47-14.71-.11-.3-.26-.61,0-.92,.15-.19,.77-.03,1.37,.36,2.93,1.97,5.8,4.04,8.67,6.09Z"/><path class="cls-2" d="M1107.94,905.02c-.42,.89-1.64-.42-2.2-.65-2.58-1.69-5.15-3.39-7.72-5.08,2.37-1.78,4.72-3.6,7.07-5.42,.94,3.71,2.23,7.37,2.85,11.15Z"/><path class="cls-2" d="M1112.83,805.9c-.45,2.05-.98,4.08-1.58,6.09-1.11-2.91-2.29-5.8-3.3-8.75-.02-.08,.07-.22,.17-.29,1.78,.29,3.2,1.97,4.71,2.95Z"/><path class="cls-2" d="M1118.68,883.24c.04,.15-.14,.34-.22,.52-.75-.11-1.26-.48-1.75-.87,.49-.51,.97-1.02,1.45M -1.53,.19,.63,.36,1.25,.52,1.88Z"/><path class="cls-2" d="M1144.43,853.27c-1.8-.56-2.72-2.01-4.19-3,.71-1.35,1.4-2.7,2.06-4.07,.66,1.85,1.32,3.69,1.98,5.54,.18,.5,.53,.99,.15,1.53Z"/><path class="cls-2" d="M1161.45,845.06c-1.38-.34-2.18-1.5-3.24-2.31-3.52-2.99-7.04-5.99-10.56-8.99,1.84-4.86,3.39-9.82,4.68-14.85,2.8,7.77,5.69,15.51,8.47,23.28,.32,.9,.9,1.81,.65,2.87Z"/><path class="cls-2" d="M1387.52,942.79c-.05,6.14-.02,12.28-.03,18.42-.23,.88-.38,1.52-1.5,.23-18.66-22.27-37.17-44.49-56.72-66.07-2.83-3.1-3.51-3.86-M 2.92,1.04,.65,4.82,1.35,9.63,2,14.45,.25,2.71,.64,4.95-2.17,1.73-16.54-18.23-32.41-37.8-50.5-54.32-.1,.03-.22,.16-.2,.24,1.27,6.71,2.85,13.36,4.31,20.03,.19,.82,.4,1.64,.04,2.47-.01,0-.01,0-.02,0-9.3-9.3-17.97-19.33-27.57-28.58-5.3-5.28-10.7-10.51-16.06-15.76-.53-.46-.99-1.16-1.8-1.02-.07,0-.19,.19-.17,.27,.74,2.73,1.47,5.47,2.25,8.19,1.19,4.19,2.41,8.38,3.61,12.57,.2,.71,.42,1.42,.22,2.16-1.23-.18-2-1.63-2.93-2.38-11.53-11.58-23.35-24-36.24-34.17-.14,.13-.36,.32-.32,.46,.29,1.05,.61,2.09,.95,3.13,2.03,6.14,4.06,12M .28,6.08,18.42,.23,.72,.36,1.47,.52,2.2,.01,.06-.11,.2-.2,.21-.91-.15-1.56-1.18-2.29-1.71-5.69-5.47-11.28-11-17.08-16.39-4.4-4.08-9.06-7.98-13.62-11.94-.42-.37-.82-.83-1.61-.72-.24,.89,.33,1.69,.61,2.49,1.91,5.49,3.93,10.97,5.87,16.46,.88,2.48,1.67,4.97,2.49,7.47,.02,.07-.11,.22-.22,.25-10.1-7.98-19.19-17.8-29.42-25.95,1.25-5.21,2.21-10.51,2.87-15.85,5.3,4.1,10.34,8.47,15.65,12.53,.33,.25,.7-.16,.71-.36-1.51-4.6-3.46-9.06-5.17-13.59-1.01-2.57-2.04-5.13-3.02-7.7-.11-.27-.02-.59-.02-.89,.81,.09,1.26,.52,1.73,.9,4.63,M 3.76,9.32,7.48,13.86,11.31,5.76,4.84,11.39,9.78,17.07,14.67,.86,.54,1.52,1.84,2.64,1.63,.07-.01,.16-.19,.14-.27-.23-.84-.46-1.68-.75-2.51-2.09-5.9-4.21-11.8-6.31-17.7-.08-.48-.54-1.13-.25-1.55,.98-.09,1.69,.9,2.43,1.4,3.55,3.1,7.14,6.17,10.63,9.31,8.6,7.73,17.22,15.44,25.53,23.37,.51,.49,1.13,.9,1.71,1.33,.21,.13,.54,.04,.55-.22-1.5-7.12-4.18-14.01-6.09-21.04-.04-.14,.15-.34,.28-.48,1.17,.22,1.97,1.45,2.88,2.16,6.02,5.66,12.12,11.27,18.03,17.01,8.68,8.37,17.06,16.98,25.73,25.34,.06,.06,.29,.1,.34,.06,.17-.12,.44-.3M ,.42-.44-.07-.75-.17-1.5-.35-2.24-1.16-4.97-2.36-9.94-3.52-14.92-.26-1.15-.41-2.33-.59-3.5-.02-.07,.1-.19,.2-.23,.6-.26,1.29,.8,1.76,1.11,7.7,7.77,15.46,15.5,23.07,23.32,9.51,9.78,18.75,19.73,27.88,29.74,2.42,2.62,2.61,1.79,2.24-1.43-.71-5.57-1.52-11.13-2.24-16.7-.01-1.97,1.47-.33,2.23,.5,16.22,17.2,32.01,34.93,47.37,52.77,4.58,5.33,9.1,10.68,13.71,15.99,.89,1.03,1.3,2.06,1.29,3.3Z"/><path class="cls-2" d="M213.94,629.46s.01-.04,.01-.06h.06s0,.01-.01,.01l-.02,.02s-.04,.03-.04,.03Z"/><path class="cls-2" d="M248.66,6M 42.99s.02-.05,.02-.08c.03,0,.06,.01,.09,.01h0s-.11,.07-.11,.07Z"/><path class="cls-2" d="M257.79,597.95s.01,.01,.01,.01h-.02s-.01,.01-.02,.01h.01s.01-.03,.01-.03h0Z"/><path class="cls-2" d="M269.29,626.4c-.95,.99-.07,2.25,.26,3.31,2.32,5.95,4.65,11.89,6.96,17.84,.2,.69,.91,1.85-.4,1.55-11.76-8.88-22.65-18.7-33.81-28.12-.17-.08-.85-.14-.81,.27,1.98,6.6,4.61,13.01,6.84,19.54,.25,.69,.57,1.38,.35,2.12-1.28-.1-2.18-1.45-3.2-2.14-6.84-6.05-13.7-12.08-20.46-18.19-5.25-4.73-10.36-9.57-15.54-14.36-.34-.31-.62-.71-1.22-.75-M .4-.04-.41,.44-.36,.71,1.87,6.25,3.76,12.5,5.65,18.75,.25,.82,.56,1.62,.4,2.47-.58,.01-.92-.3-1.27-.61-14.43-13.12-28.47-26.75-42.07-40.53-.54-.37-3.9-4.45-4.2-3.04,1.42,6.46,3,12.92,4.53,19.35,.56,2.59-.78,1.76-2.07,.45-17.34-17.32-34.57-34.89-50.99-53.02-.59-.54-1.03-1.5-1.98-1.33-.06,.01-.17,.19-.16,.28,.16,1.72,.3,3.44,.53,5.15,.65,4.81,1.35,9.63,2.02,14.44-.01,.28,.05,.73-.33,.79-.6,.1-1.09-.58-1.51-.9-4.52-4.83-9.06-9.65-13.53-14.51-16.16-17.61-31.72-35.52-47.18-53.66-1.28-1.43-2.73-2.99-2.35-4.99-.05-6.23-.1M 5-12.48-.17-18.71,.36-.06,.73-.19,.82-.12,.47,.38,.9,.78,1.27,1.22,6.23,7.42,12.42,14.86,18.69,22.26,12.71,14.98,25.48,29.91,38.82,44.54,.73,.61,1.19,1.73,2.34,1.49-.46-7.09-1.88-14.14-2.72-21.2,.46-1.58,2.15,1.11,2.67,1.56,5.13,5.8,10.26,11.61,15.39,17.41,11.27,12.1,22.33,25.49,34.66,36.37,.09-.04,.2-.15,.2-.23-.03-.64,.01-1.29-.13-1.92-1.32-6.82-3.45-13.56-4.36-20.43,1.88,.82,2.8,2.61,4.24,3.96,13.23,13.9,26.62,28.82,41.3,41.25,.06-.2,.22-.42,.18-.61-.59-2.21-1.19-4.41-1.82-6.62-1.31-5.4-3.56-10.69-4.35-16.15,1.9M ,.81,2.9,2.56,4.37,3.9,11.15,11.16,22.61,22.95,34.98,32.9,.11-.03,.26-.15,.25-.21-.16-.74-.29-1.48-.53-2.2-2.23-6.76-4.48-13.52-6.72-20.29-.06-.44-.44-1.24-.09-1.55,.21-.04,.55-.1,.66,0,.74,.62,1.44,1.27,2.13,1.93,9.83,9.54,19.64,19.04,30.22,27.8,.9,.69,1.89,1.1,1.34-.63-2.68-7.56-5.36-15.12-8.09-22.67-.29-.79-.34-1.69-1.14-2.35,1.88-.75,3.28,1.97,4.71,2.89,8.25,7.36,16.35,14.9,24.69,22.16-1.27,5.2-2.23,10.48-2.91,15.81-5.02-4.16-10.37-7.93-15.01-12.43-.03,.03-.06,.07-.08,.1l.09-.09Z"/><path class="cls-2" d="M292.4M 7,605.91c-1.76,4.64-3.27,9.37-4.53,14.18-2.73-7.47-5.47-14.95-8.19-22.42-.26-.72-.42-1.46-.6-2.19-.02-.08,.11-.22,.21-.26,.11-.05,.32-.06,.39-.01,.77,.6,1.53,1.2,2.26,1.82,3.49,2.96,6.98,5.92,10.46,8.88Z"/><path class="cls-2" d="M299.93,589.42c-.66,1.22-1.29,2.45-1.89,3.69-1.21-3.94-4.46-9.42,1.89-3.69Z"/><path class="cls-2" d="M310.21,573.78s-.02,.05-.02,.08c-.03-.01-.06-.01-.09-.01l.11-.07Z"/><path class="cls-2" d="M323.53,556.87c-.41,.42-.82,.85-1.23,1.28-.62-1.74-.76-2.54,1.23-1.28Z"/><path class="cls-2" d="M33M 2.63,636.65c.06,.13-.16,.35-.29,.5-.03,.03-.27-.02-.38-.07-1.7-.93-3.16-2.22-4.71-3.36,.5-2.18,1.08-4.32,1.72-6.46,1.22,3.13,2.46,6.26,3.66,9.39Z"/><path class="cls-2" d="M342.29,540.47c-2.33,1.75-4.63,3.55-6.94,5.32-3.53-13.9-5.48-13.43,6.94-5.32Z"/><path class="cls-2" d="M343.89,621.63c.02,.18-.3,.67-.71,.44-3.43-2.01-6.51-4.52-9.77-6.79,1.42-3.21,3.01-6.36,4.76-9.41,1.87,5.26,3.98,10.46,5.72,15.76Z"/><path class="cls-2" d="M353.32,603.38c-.37,1.39-8.61-5.12-9.92-5.75,1.78-2.52,3.68-4.97,5.71-7.34,1.37,4.37,3.13,M 8.64,4.21,13.09Z"/><path class="cls-2" d="M361.66,581.36c-.21,1.15-2.41-.61-3.01-.87,.73-.65,1.47-1.3,2.23-1.93,.29,.93,.53,1.86,.78,2.8Z"/><path class="cls-2" d="M417.3,360.8s-.01-.02-.02-.02c0-.01,.02,.02,.02,.02Z"/><path class="cls-2" d="M417.76,361.95c-1.33,16.98-2.61,33.95-3.03,50.98-.14,.83,.19,2.46-1.05,2.45-4.53-1.29-8.82-3.19-13.26-4.74-.61-.16-1.63-.62-2.1-.01-.63,2.6-.23,5.38-.33,8.04,.02,12.92,.81,25.83,1.18,38.74,0,.25-.6,.56-.87,.46-1.21-.47-2.44-.91-3.62-1.42-3.33-1.41-6.64-2.85-9.96-4.29-.48-.21-.97M -.35-1.54-.13,.33,14.16,2.83,28.33,4.24,42.45,.05,.4-.68,.72-1.17,.5-3.6-1.68-7.2-3.37-10.79-5.07-1.44-.59-2.63-1.66-4.26-1.71,.87,9.59,3.03,19.18,4.75,28.71-2.92,1.87-5.81,3.77-8.68,5.7-2.08-.9-3.61-2.42-5.95-2.77-.14,2.09,.73,4.05,1.06,6.1-4.58,3.13-9.09,6.34-13.53,9.62-2.11-8.8-4.53-17.84-5.96-26.65,.63-.26,1.21,.14,1.72,.44,4.46,2.82,9.01,5.48,13.56,8.17,.61,.36,1.28,1.14,2.04,.7,.67-.38,.2-1.21,.1-1.83-.28-1.6-.65-3.19-.95-4.79-1.07-5.75-2.14-11.49-3.2-17.25-.67-5.09-2.44-10.2-2.28-15.34,.68-.74,1.91,.47,2.65,M .72,4.23,2.31,8.44,4.63,12.67,6.94,.33,.11,1.11,.4,1.4,.11-.27-7.39-2-14.76-2.74-22.15-.65-6.95-1.68-13.92-1.85-20.89,1.29-.32,2.21,.62,3.34,1.04,3.81,1.84,7.6,3.69,11.41,5.52,.57,.27,1.14,.59,1.89,.33-.49-15.28-1.83-30.75-1.87-46.12,.02-.59,0-1.59,.81-1.57,4.8,1.57,9.32,3.87,14.02,5.71,3.37,1.53,2.27-2.05,2.51-4.06,.26-16.24,.48-32.58,2.15-48.73,.74-.72,2.04,.25,2.9,.39,3.82,1.34,7.62,2.72,11.45,4.03,.83,.28,1.66,.77,2.69,.53,.3,.34,.48,.72,.45,1.14Z"/><path class="cls-2" d="M138.15,1155.19c1.49-6.81,2.57-13.68,4.M 7-20.35l-.15,.11c15.17,2,30.38,3.66,45.61,5.06,10.96,1.06,22.02,1.32,32.95,2.72l-.09-.1c-2.03,4.9-4.08,9.8-6.1,14.7-.38,.91-.67,1.85-.95,2.78-.04,.13,.19,.43,.36,.47,22.24,1.54,44.62,1.24,66.91,1.56,.32,.52,.16,.92-.08,1.32-1.49,2.53-2.96,5.07-4.45,7.61-1.32,2.24-2.66,4.47-3.97,6.71-.26,.51-.88,1.32-.18,1.7,16.08,.32,32.28-1.03,48.37-1.86,3.22-.2,6.44-.43,9.67-.6,1.03-.04,1.34,.44,.79,1.24-3.39,4.79-6.97,9.46-10.42,14.21-.83,1.21-1.96,2.48,.47,2.3,17.22-1.24,34.55-3.64,51.62-5.11,.51,.85-.71,1.53-1.09,2.23-4,4.73-8M .01,9.45-12,14.18-.43,.51-1.08,.97-.82,1.74,12.23-.95,24.38-3.38,36.56-4.99,3.7-.57,7.38-1.21,11.07-1.81,.24-.04,.74,.05,.74,.1,.14,.83-.53,1.37-1.05,1.93-5.05,5.76-11.06,11.23-15.59,17.19,.57,.62,1.43,.15,2.15,.1,4.47-.76,8.94-1.56,13.42-2.3,9.83-1.56,19.44-3.75,29.23-5.39-.34,1.49-1.65,2.18-2.6,3.29-5.23,5.21-10.47,10.41-15.7,15.61-.45,.64-1.72,1.25-1.42,2.09,13.3-1.75,26.66-5.19,39.89-7.81,.51-.11,1.02-.32,1.64-.06-.64,1.57-2.34,2.52-3.47,3.78-6.01,5.67-12.02,11.33-18.03,17.01-.52,.49-1,1.01-1.48,1.52-.07,.07-.0M 8,.26-.02,.31,.6,.56,1.46,.17,2.17,.09,12.02-2.23,24.27-5.88,36.28-7.4-.38,1.57-2.12,2.4-3.16,3.57-7.22,6.54-14.45,13.07-21.67,19.61-.62,.56-1.2,1.16-1.78,1.75-.07,.07-.12,.26-.06,.3,.15,.12,.39,.29,.55,.26,11.4-2.07,22.67-4.7,33.95-7.19,.6-.12,1.25-.37,1.8,.02,.04,.02,0,.22-.08,.3-9.5,8.88-19.45,17.28-29.11,25.98-.73,.72-1.8,1.21-1.93,2.3,.93,.22,1.83,.05,2.74-.18,10.4-1.94,20.68-4.31,31.12-6.01-.59,1.55-2.06,2.25-3.2,3.39-10.74,9.7-23.56,19.18-33.45,29.2,.46,.37,1.66,.09,2.25,.08,9.65-1.36,19.22-3.58,28.92-4.38l-M .05-.09c.03,.2,.18,.48,.07,.59-.76,.75-1.53,1.5-2.37,2.2-7.55,6.3-15.12,12.58-22.68,18.88-5.5,4.59-10.98,9.19-16.47,13.79-.29,.4-1.68,1.01-1.17,1.53,.17,.13,.46,.23,.69,.22,1.88-.13,3.76-.27,5.63-.46,5.88-.58,11.76-1.18,17.64-1.76,1.46-.15,2.93-.26,4.4-.37,.07,0,.18,.11,.21,.18,.04,.1,.09,.25,.03,.31-.68,.66-1.34,1.34-2.09,1.95-15.58,12.86-31.26,25.62-47.03,38.27-2.14,1.71-2.06,1.63-4.96,1.63-6.87,.01-13.75,.02-20.62,.02-3.63,.05-3.89-.42-.84-2.71,14.76-11.96,29.77-23.64,44.32-35.85,.13-.13,.07-.4,.05-.6-.65-.29-1.M 6-.09-2.33-.1-8.3,.73-16.59,1.56-24.88,2.32-1.18,.09-2.28-.05-.9-1.29,12.46-10.29,24.91-20.6,37.36-30.91,.48-.56,2.91-2.17,1.79-2.43-10.46,.94-20.88,3.59-31.36,4.24,.03-.24-.05-.51,.08-.64,.87-.82,1.78-1.61,2.7-2.39,9.61-8.15,19.23-16.3,28.84-24.45,1.04-1.01,2.38-1.71,2.94-3.08-9,1-17.91,3.11-26.88,4.5-1.01,0-9.91,2.41-6.69-.38,8.99-7.86,17.97-15.76,26.9-23.68,1.4-1.38,2.67-2.31-.39-1.89-10.21,1.95-20.42,3.92-30.62,5.9-.75,.08-4.38,1.11-4.28-.05,8.18-7.91,16.91-15.29,25.03-23.26,.22-.87-.62-.64-1.19-.51-11.72,2.46-M 23.6,4.37-35.4,6.56-.91,.01-2.29,.66-2.99-.05-.08-.16,.01-.44,.16-.59,.74-.77,1.51-1.52,2.28-2.26,5.77-5.55,11.55-11.1,17.32-16.65,.51-.49,.99-1.02,1.46-1.54,.07-.07,.09-.25,.03-.31-.34-.39-.86-.4-1.34-.29-10.25,1.8-20.5,3.63-30.76,5.4-3.42,.59-6.88,1.03-10.32,1.52-.17,.02-.42-.16-.58-.29-.07-.05-.06-.24,0-.31,.78-.88,1.55-1.76,2.37-2.61,4.86-5.03,9.74-10.05,14.59-15.08,.56-.58,1.32-1.1,1.33-2.06-10.47,1.08-20.83,3.25-31.33,4.4-5.17,.46-10.31,1.8-15.5,1.77,0-.28-.1-.54,.02-.69,.56-.73,1.17-1.45,1.78-2.15,3.78-4.32,M 7.58-8.64,11.36-12.97,.69-.79,1.34-1.61,1.99-2.43,.06-.07,.06-.24,0-.3-.15-.15-.37-.38-.54-.37-1.48,.1-2.96,.2-4.42,.39-10.64,1.39-21.35,2.34-32.02,3.49-4.55,.43-9.11,.75-13.67,1.09-1.95-.09,.22-2.02,.64-2.76,3.62-5.04,7.81-9.73,11.08-14.99,.05-.1-.22-.45-.35-.45-5.24-.11-10.45,.72-15.68,.96-12.63,.77-25.28,1.26-37.93,1.8-.83-.13-3.49,.54-3.41-.68,3.08-5.66,6.84-10.94,9.95-16.59,.19-1.16-1.78-.72-2.5-.85-4.45,.05-8.89,.14-13.34,.19-14.96,.21-29.91-.27-44.87-.55-1.21-.03-2.41-.14-3.62-.21-.3-.02-.72-.49-.63-.71,.31-M .82,.61-1.65,.96-2.46,1.93-4.92,4.5-9.65,6.06-14.69,.03-.15-.18-.38-.36-.48-2.05-.5-4.28-.39-6.39-.61-16.53-.77-33.02-2.06-49.49-3.62-5.21-.52-10.42-1.08-15.63-1.6-1.05-.1-2.13-.33-3.19,.01l.12,.1Z"/><path class="cls-2" d="M1009.12,190.08c12.91-2.58,25.93-4.91,38.93-7.08,1.98,.1-1.1,2.24-1.51,2.82-5.68,5.46-11.36,10.92-17.04,16.38-.85,.95-2.06,1.61-2.38,2.89,11.93-1.59,23.69-4.1,35.59-5.98,2.23-.38,4.5-.62,6.76-.89,.19-.02,.53,.13,.6,.27,.08,.97-1.46,1.87-2.02,2.67-5.29,5.57-10.8,10.95-15.95,16.65-.3,1.52,7.01-.38,M 8.16-.35,11.63-1.79,23.27-3.53,34.96-4.92,1.17-.14,2.38-.44,3.58-.07l-.09-.07c.12,1.41-1.41,2.22-2.14,3.3-3.78,4.32-7.56,8.64-11.33,12.97-.54,.62-1.02,1.26-1.51,1.91-.15,.31,.38,.6,.61,.62,8.55-.65,17.06-1.9,25.6-2.69,8.41-.67,16.89-2.21,25.29-2.13,0,1.26-1.16,2.11-1.81,3.13-3.27,4.33-6.54,8.66-9.81,12.99-.41,.69-1.18,1.24-.8,2.1,19.13-1.24,38.05-2.36,57.27-2.98,.22,1.55-.92,2.46-1.57,3.73-2.72,4.56-5.65,9.02-8.23,13.66-.31,1.25,3.35,.66,4.16,.83,11.04,0,22.08-.1,33.12-.02,9.01,.14,18.04,.24,27.04,.69,1.42,.37,.08,M 1.95-.1,2.84-2.04,5.01-4.36,9.92-6.25,14.98-.09,.26,.28,.67,.63,.69,2.95,.21,5.9,.47,8.85,.59,13.56,.66,27.08,1.8,40.6,3.04,7.22,.65,14.43,1.41,21.64,2.1,1.01-.02,2.21,.4,3.03-.31l-.02-.05c.15,.74,.3,1.46,.13,2.22-1.25,6.1-2.99,12.13-3.81,18.31l.11-.08c-17.4-1.82-34.76-4.14-52.22-5.53-9.05-.94-18.19-.99-27.2-2.25l.14,.09c2.26-5.41,4.57-10.81,6.84-16.21,.73-1.81-.08-1.85-1.67-1.94-21.78-1.09-43.6-1.27-65.4-1.33-.57-.91,.32-1.65,.67-2.48,2.75-4.79,5.74-9.47,8.34-14.34-.1-1.1-1.84-.69-2.63-.79-9.83,.32-19.66,.59-29.48M ,.99-8.87,.43-17.72,1.17-26.6,1.62-2.08-.15,.58-2.57,.94-3.41,2.8-3.81,5.62-7.6,8.42-11.4,.55-.74,1.05-1.5,1.52-2.27,.09-.15-.07-.39-.15-.69-14.44,.91-28.86,2.69-43.26,4.2-3.07,.33-6.14,.63-9.21,.93-.32,.03-.73-.48-.59-.7,.19-.29,.35-.58,.57-.85,4.02-4.86,8.16-9.63,12.22-14.46,1.76-2.25,1.58-2.29-1.23-2.09-11.94,1.6-23.88,3.25-35.79,5.1-3.3,.51-6.6,1.07-9.9,1.6-.1,.02-.3-.07-.33-.14-.08-.18-.19-.42-.1-.57,1.15-1.61,2.66-2.98,3.98-4.47,3.7-3.97,7.42-7.94,11.11-11.92,.56-.6,1.06-1.24,1.57-1.87,.06-.08,.07-.26,0-.31-.M 41-.33-.92-.3-1.4-.18-13.28,2.32-26.6,4.5-39.77,7.22-1.03,.21-2.11,.27-3.16,.38-.21,.02-.48-.27-.36-.46,5.48-5.92,11.42-11.43,17.07-17.2,.76-.76,1.52-1.51,2.24-2.29,.14-.15,.23-.54,.17-.57-.94-.52-2-.08-2.99,.06-11.94,2.2-23.81,4.6-35.61,7.23-3.07,.45-3.67,.45-.98-2,6.35-6.01,12.71-12.01,19.06-18.01,.7-.66,1.39-1.32,2.04-2,.11-.11,0-.37-.06-.55-.78-.29-1.87,.2-2.72,.27-11.96,2.3-23.91,5.61-35.88,7.4,.13-1.29,1.54-1.9,2.35-2.79,8.06-7.39,16.31-14.59,24.28-22.08,.49-1.17-1.3-.53-1.9-.5-10.32,2.05-20.59,4.24-30.81,6.6M -2.75,.58-5.11,1.24-1.56-1.73,9.77-8.77,19.76-17.32,29.43-26.2,.29-1.01-2.9-.03-3.51-.03-9.01,1.79-18.02,3.59-27.04,5.38-4.72,1-3.52-.02-.68-2.46,10.39-8.9,20.78-17.79,31.17-26.69,.92-.79,1.83-1.58,2.7-2.4,.12-.11,.04-.38,0-.57-9.83,.66-19.82,3.04-29.68,4.41-2.76,.3-1.06-.91,0-1.95,12.99-10.95,26.1-21.78,39.16-32.67,.74-.62,1.38-1.31,2.04-1.97,.06-.06,.01-.22-.05-.31-9.47,.1-19.17,1.9-28.75,2.52-.28-.96,1.26-1.71,1.85-2.37,15.37-12.55,30.67-25.19,46.18-37.58,1.57-1.32,3.13-2.75,5.36-2.39,7.55,0,15.09-.01,22.64-.01,M 3.48-.02,.72,1.55-.48,2.67-9.22,7.41-18.45,14.8-27.67,22.21-5.03,4.05-10.04,8.13-15.04,12.2-.57,.6-1.89,1.25-1.53,2.12,6.16-.21,12.3-1.16,18.45-1.62,3.21-.29,6.43-.51,9.64-.76,.34-.03,.52,.13,.5,.38-11.87,10.8-25.06,20.73-37.36,31.24-.93,.77-1.78,1.61-2.65,2.42-.24,.31,.34,.58,.55,.58,10.32-1.37,20.61-3.54,30.98-4.25-.03,.28,.05,.55-.09,.68-.78,.74-1.6,1.46-2.43,2.16-10.71,9.1-21.43,18.2-32.11,27.3,.29,.28,.38,.28,.23,.05-.04-.06-.22-.05-.34-.08,2.52,.76,5.3-.53,7.87-.72,8.82-1.41,17.56-3.38,26.44-4.4,.11-.01,.35,.M 07,.35,.12,.01,.2,.05,.46-.08,.59-9.24,8.29-18.63,16.41-27.92,24.64-.39,.46-1.29,1-1.32,1.56,.42,.32,.92,.28,1.41,.15,10.07-1.94,20.13-3.88,30.2-5.81,1.69-.32,3.41-.55,5.12-.81,.1-.02,.28,.07,.34,.15,.06,.08,.06,.24,0,.31-.46,.52-.91,1.05-1.43,1.53-7.24,6.66-14.49,13.31-21.74,19.97-.8,.88-2.15,1.56-1.64,2.67,.04-.32-.06-.4-.3-.26l.3,.19Z"/><path class="cls-2" d="M892.55,367.68c2.59-4.6,5.15-9.23,7.76-13.82-.68-.63-1.44-.2-2.21-.07-13.91,3.39-27.43,7.57-41.1,11.6-.2,.02-.87-.17-.68-.53,2.24-4.3,4.98-8.34,7.41-12.54,M 1.15-2.14-1.44-.91-2.47-.66-5.23,1.71-10.48,3.38-15.67,5.18-7.3,2.27-14.42,5.71-21.79,7.46-.28-.11-.36-.31-.22-.55,1.85-3.11,3.69-6.22,5.57-9.32,.88-1.45,1.85-2.87,2.77-4.31,.17-.27,.4-.61,.01-.85-.35-.23-.74-.04-1.1,.09-4.4,1.63-8.83,3.19-13.18,4.89-7.86,2.86-15.56,6.72-23.46,9.16-.59-.67,.26-1.39,.54-2.04,2.55-4.03,5.11-8.06,7.66-12.1,.24-.58,1.11-1.48,.88-2.04-.15-.24-.39-.3-.69-.18-4.17,1.75-8.37,3.45-12.49,5.26-5.19,2.29-10.3,4.68-15.3,7.23-.67,.34-1.43,.56-2.16,.82-.06,.02-.21-.08-.29-.15-.08-.07-.2-.2-.17-.2M 6,.25-.61,.48-1.23,.82-1.81,2.56-4.39,5.14-8.77,7.7-13.16,1.96-3.3-.09-1.97-2.08-1.11-7.09,3.53-14.16,7.07-21.25,10.6-2.46,1.05-5.9,3.67-2.92-1.2,2.83-4.76,5.68-9.52,8.52-14.28,.52-.93,1.51-1.99,.55-2.98,.15,.13,.29,.26,.43,.39h.01l-.42-.39c-.31,.54-.87,.81-1.43,1.07-8.55,3.88-16.42,8.67-24.73,12.8-.09,.04-.33,.03-.35-.01-.1-.18-.27-.42-.19-.56,3.38-6.52,7.53-12.63,11.38-18.9,.33-.79,1.5-1.82,.98-2.64-.76-.09-1.71,.65-2.44,.92-7.44,3.88-14.86,7.77-22.26,11.73-.42,.22-.96,.65-1.39,.37-.71-.46,0-.97,.24-1.43,4.59-7.8M 1,9.75-15.31,14.28-23.16-.2-.8-1.43,.03-1.91,.17-6.89,3.56-13.81,7.06-20.59,10.82-2.67,1.44-3.33,1.67-3.4,1.27-.16-1.02,.65-1.79,1.16-2.63,4.47-7.48,9.35-14.79,14.2-22.11,3.14-4.35,2.79-4.62-1.93-2.18-6.99,3.44-13.89,7.06-20.92,10.4-1.78,.19,.02-1.75,.35-2.4,6.16-10.35,13.96-20.21,20.1-30.47-.17-.22-.42-.26-.71-.15-.97,.37-1.95,.72-2.9,1.11-4.53,1.9-9.05,3.82-13.57,5.72-1.21,.43-2.35,1.26-3.68,.89l.12,.03c6.15-10.43,13.75-20.24,20.75-30.29,1.68-2.33,3.27-4.7,4.88-7.05,.04-.06-.03-.19-.09-.26-.08-.08-.24-.19-.31-.17M -.76,.21-1.53,.4-2.27,.66-5.9,2.12-11.78,4.25-17.67,6.38-.83,.37-1.36,.13-.92-.92,.4-.67,.89-1.33,1.33-1.99,3.85-5.44,7.64-10.9,11.57-16.3,5.08-6.98,10.19-13.95,15.6-20.78,.71-.9,1.28-1.87,1.9-2.82,.04-.07-.01-.21-.08-.28-.08-.08-.24-.19-.32-.18-1.03,.22-2.07,.43-3.07,.72-5.07,1.45-10.13,2.92-15.2,4.38-1.01,.29-2.04,.56-3.06,.82-.32,.1-.64-.42-.58-.62,9.24-13.34,19.18-26.19,29.29-39.05,2.46-3.09,4.9-6.19,7.33-9.29,.1-.13,0-.39-.08-.57-.27-.24-.8-.13-1.15-.08-6.16,1.1-12.27,2.48-18.41,3.69-1.04,.21-2.1,.36-3.17,.5-.M 18,.02-.43-.17-.6-.3,12.55-17.88,27.1-34.95,41.11-52.14,.9-1.07,1.82-2.14,2.72-3.21,.3-.36,.54-.74,.4-1.21-.92-.3-1.85-.11-2.78,0-6.81,.75-13.61,1.52-20.41,2.27-.44,0-1.79,.18-1.55-.49,17.01-22.29,35.32-43.79,54.04-64.72,7.84-.29,15.65-.1,23.5-.19,.8,.13,3.66-.3,3.23,.89-9.18,10.29-18.82,20.21-27.84,30.56-8.48,9.59-17.02,19.14-25.18,28.9-.45,.54-.88,1.09-1.25,1.66-.06,.1,.17,.44,.34,.48,8.16-.2,16.27-2.08,24.44-2.09,.21,.99-.83,1.58-1.34,2.31-9.44,10.5-18.79,21.04-27.8,31.78-5.03,5.99-10.01,12.01-14.99,18.03-.51,.6M 2-1.21,1.18-1.28,1.97-.01,.15,.3,.48,.4,.46,6.97-1.17,13.87-2.65,20.81-3.99,.56-.08,2.72-.46,2.32,.33-12.28,15.46-25.68,30.19-37.5,45.99-1.06,1.33,.18,1.2,.97,1.1,6.37-1.74,12.73-3.5,19.1-5.25,.58-.07,1.36-.47,1.9-.19,.09,.17,.23,.41,.14,.53-.82,1.11-1.65,2.22-2.54,3.3-9.76,12.39-20.67,24.57-28.96,37.54,.07,.08,.22,.18,.3,.16,.76-.21,1.53-.41,2.27-.66,5.46-1.85,10.91-3.7,16.36-5.55,1.09-.33,2.33-.96,3.41-.29v-.04c-9.71,11.25-18.38,23.51-27.13,35.53-.09,.15,.05,.4,.13,.59,.02,.04,.23,.09,.31,.06,8.02-3.25,15.9-6.81,M 23.87-10.18,1.96-.8,3.05-1.05,1.31,1.25-5.79,7.89-11.61,15.78-17.38,23.68-1.29,1.76-2.44,3.59-3.63,5.4-.09,.13,.08,.38,.18,.56,1.18-.11,2.37-.98,3.52-1.39,7.01-3.21,14.01-6.43,21.03-9.63,.56-.25,1.21-.38,1.82-.55,.04,0,.23,.18,.21,.24-5.31,8.5-11.6,16.49-17.26,24.8-.52,.74-.88,1.58-1.77,2.13,0,0,.2,.09,.2,.09l-.12-.17c1.03,.8,2.21-.15,3.2-.57,6.66-3.18,13.31-6.35,19.97-9.53,1.53-.62,2.95-1.67,4.64-1.74l-.08-.06c.08,1.39-1.22,2.33-1.89,3.46-4.77,6.74-9.65,13.35-13.69,20.48,.31,.86,2.36-.6,2.99-.78,8.12-3.89,16.29-8.M 25,24.79-11.34,.63,.11-.33,1.33-.47,1.69-3.77,5.71-7.55,11.41-11.33,17.12-.39,.77-1.25,1.47-1.02,2.37-.18,.01-.43,.01-.35,.24,.26,.05,.35-.05,.27-.3,1.59,.13,2.88-.97,4.3-1.53,7.94-3.65,15.67-7.72,23.83-10.89,.35-.09,.84,.2,.55,.57-3.78,5.69-7.77,11.33-11.17,17.19-.15,.26-.14,.59-.17,.88,0,.07,.19,.22,.25,.21,2.86-.75,5.47-2.3,8.21-3.41,7.62-3.45,15.48-6.52,23.38-9.55,.45-.09,1.05-.52,1.45-.15,.07,.07,.16,.2,.12,.26-.33,.58-.65,1.17-1.04,1.73-3.2,4.49-6.42,8.97-9.62,13.46-.4,.56-.7,1.16-1.02,1.74,.11,.53,.85,.42,1.M 25,.27,12.33-4.58,24.64-10.16,37.28-13.73,.62,.26-.33,1.3-.58,1.7-2.83,4.16-5.66,8.32-8.48,12.49-.17,.51-1.45,1.65-.7,1.98,12.37-3.76,24.7-8.51,37.25-12.24,1.24-.24,2.55-1.08,3.79-.63-11.29,18.87-15.91,16.75,7.36,10.31,8.97-2.43,18.07-5.34,27.17-7.06,.11,.04,.28,.16,.27,.2-.14,.41-.25,.83-.49,1.21-2.64,4.23-5.51,8.33-7.96,12.67,1.07,.6,2.07-.05,3.16-.21,14.81-3.39,29.8-7.26,44.81-9.4,.72,.23-.11,1.28-.35,1.71-1.93,3.2-3.87,6.4-5.78,9.6-.46,.76-1.09,1.48-1.04,2.39,.79,.37,1.58,.16,2.36,.03,3.55-.62,7.08-1.31,10.65-1M .86,12.59-1.85,25.13-3.94,37.81-5.19,.9,0,2.53-.4,1.93,1.08-2.37,4.22-4.76,8.43-7.15,12.65l.08-.06c-8.06,1.62-16.8,1.91-25.01,3.31-9.84,1.14-19.46,3.23-29.28,4.45l.09,.08c2.17-3.92,4.28-7.88,6.53-11.76,.21-.41,.72-1.07,.52-1.49-.28-.17-.71-.36-1.02-.3-4.05,.73-8.12,1.43-12.14,2.26-11.81,2.46-23.59,5.02-35.21,7.99l.07,.12Z"/><path class="cls-2" d="M342.27,130.02c-3.54,23.39-7.76,46.69-10.31,70.21-6.34-1.78-14.07-4.47-20.88-6.58-.61-.19-1.74-.64-2.08,.1-2.35,19.96-3.22,40.05-4.55,60.1l.14-.05c-6.97-3.26-13.86-6.7-20.M 88-9.84-.5-.21-1.06,.08-1.1,.58-.49,16.47-.85,32.96-.31,49.44,.13,3.28-.82,2.45-3.07,1.21-5.91-3.58-11.72-7.28-17.71-10.73-.23-.13-.72,.03-1.19,.06,.13,12.64,1.06,25.23,1.81,37.84,.16,2.69,.26,5.38,.36,8.07,0,.18-.17,.37-.27,.56-.59,.5-1.73-.62-2.32-.95-5.8-4.17-11.45-8.51-17.18-12.76-.58-.33-1.22-1.05-1.91-1.03-.25,.2-.6,.41-.52,.77,1.12,13.44,2.31,26.87,3.78,40.27-.02,2.7-2.85-.79-3.77-1.31-5.87-4.9-11.73-9.81-17.61-14.71-.51-.37-1.72-1.46-1.98-.33,.58,5.37,1.32,10.72,2.03,16.07,.93,7.07,1.82,14.14,2.81,21.2,.02,M .41-.7,.36-.87,.28-7.77-6.8-15.16-14.02-22.8-20.97-2.46-2.08-.46,4.72-.56,5.73,1.3,9.53,3.15,18.99,4.4,28.52-.37,0-.73,.09-.85-.01-.83-.7-1.66-1.41-2.41-2.16-7.8-7.67-15.25-15.72-23.24-23.18-.15-.1-.57-.06-.59,.17,.24,1.92,.44,3.85,.75,5.77,1.33,8.22,2.77,16.43,4.08,24.66,.07,.47,.64,1.15-.2,1.36-.71,.18-1.05-.56-1.43-.97-6.44-6.91-12.86-13.83-19.29-20.75-2.49-2.68-4.97-5.36-7.48-8.04-.13-.14-.43-.18-.67-.24-.49,0-.35,1.07-.37,1.41,.79,6.33,2.08,12.6,2.94,18.91,1.9,10.74,1.83,10.3-5.12,2.33-8-9.06-16-18.13-24-27.19M -.67-.59-1.12-1.73-2.1-1.79-.16,.02-.41,.29-.39,.43,.49,3.97,.99,7.93,1.52,11.89,.45,4.58,1.56,9.28,1.71,13.79-1.17,.02-1.85-1.45-2.65-2.17-11.3-12.87-21.8-26.74-33.48-39.12-1.06-.13-.3,2.83-.38,3.58,.42,6.43,1.46,12.91,1.56,19.32-.61,.63-1.21-.48-1.62-.86-12.59-15.42-25.18-30.85-37.76-46.28-.72-.86-1.56-1.78-1.46-2.93-.13-6.03-.08-12.06-.08-18.1,0-.53,.14-1.06,.25-1.58,.07-.12,.54-.21,.66-.12,12.13,14.03,23.68,28.57,35.68,42.71,.69,.63,1.13,1.77,2.24,1.53-.26-7.3-1.14-14.6-1.6-21.9-.03-.41,.11-.83,.21-1.24,.01-.05M ,.28-.13,.36-.09,11.01,11.86,21.25,24.65,32.01,36.82,.52,.64,1.02,1.33,1.89,1.53,.3,.08,.48-.22,.41-.73-.34-2.79-.68-5.57-1.03-8.36-.72-5.57-1.45-11.13-1.98-16.72-.02-.17,.15-.37,.28-.53,.05-.05,.32-.07,.37-.03,.62,.56,1.28,1.1,1.83,1.71,4.57,5.07,9.1,10.16,13.68,15.22,4.42,4.89,8.89,9.75,13.34,14.62,.39,.44,1.01,1.29,1.75,1.02,.29-2.87-.72-5.77-.96-8.65-.9-6.2-1.73-12.41-2.55-18.62-.08-.77-.61-2.74,.82-2,8.54,8.71,16.88,17.62,25.4,26.36,.62,.54,1.14,1.4,2.08,1.32,.04,0,.15-.16,.14-.25-.14-1.18-.29-2.35-.45-3.53-1.M 21-9.61-3.12-19.2-3.83-28.85,1.21-.21,1.88,1.01,2.74,1.65,6.96,6.72,13.9,13.46,20.86,20.18,.73,.54,1.38,1.53,2.3,1.68,.29,0,.47-.14,.44-.41-.54-5.05-1.33-10.06-1.99-15.09-.81-6.75-1.58-13.51-2.34-20.27-.02-.15,.23-.4,.41-.45,1-.06,1.62,1.04,2.37,1.55,6.36,5.57,12.72,11.14,19.08,16.71,.77,.52,1.43,1.56,2.47,1.37,.08,0,.2-.14,.19-.22-.04-.97-.05-1.93-.15-2.9-1.16-12.21-2.94-24.49-3.41-36.71,.93-.27,1.59,.53,2.3,.98,6.04,4.61,12.08,9.23,18.12,13.85,1.25,.87,3.03,2.66,2.83-.23-.94-14.28-2.08-28.59-2.43-42.88,1.16-.36,1M .94,.46,2.88,.96,4.75,3.02,9.48,6.05,14.22,9.07,1.63,.84,3.1,2.36,4.92,2.66,.94-.15,.49-1.65,.59-2.35-.1-15.51-.57-31.02-.23-46.53,.03-2.72,3.03-.23,4.32,.25,5.25,2.63,10.5,5.26,15.76,7.88,.7,.25,1.8,1.05,2.45,.41,.98-17.71,1.59-35.52,2.83-53.25,.28-1.09-.26-3.83,1.47-3.51,6.48,2.13,12.95,4.26,19.43,6.38,1.43,.49,2.88,.94,2.99-1.09,1.69-16.65,3.83-33.25,6.03-49.84,.78-4.9,1.05-9.93,2.49-14.7l-.13,.09c5.91,.99,11.83,1.98,17.74,2.97,2.36,.26,4.73,1.12,7.1,.69l-.1-.1Z"/><path class="cls-2" d="M1256.91,1041.89c1.6-.11,M 2.33,1.51,3.38,2.42,8.52,9.16,16.93,18.41,25.51,27.51,.35,.28,1.03,.21,.98-.38-.55-3.63-1.12-7.27-1.68-10.9-.86-5.66-1.79-11.32-2.6-16.99-.02-.13,.23-.4,.39-.41,1.2,.1,1.96,1.81,2.84,2.56,9.02,10.2,18.03,20.41,27.06,30.61,.75,.64,1.41,2.02,2.52,1.76-3.48-34.04-8.49-32.03,14.6-5.95,5.99,7.02,11.79,14.21,17.88,21.14,.22,.32,.75,.26,.91-.09,.06-.32,.13-.64,.11-.95-.5-6.88-1.14-13.75-1.68-20.63,.03-.33,.22-1.02,.68-.92,.38,.3,.78,.59,1.08,.94,2.38,2.87,4.74,5.76,7.1,8.64,9.86,12.09,19.73,24.17,29.57,36.27,2.29,2.82,2.0M 5,2.02,2.07,5.71,.01,2.26,0,4.52,0,6.79-.01,3.55,.1,7.11-.06,10.66-.49,1.64-2.67-1.77-3.18-2.23-7.07-8.53-14.12-17.06-21.19-25.59-3.8-4.58-7.61-9.14-11.44-13.71-.48-.42-1.18-1.58-1.84-1.53-.42,0-.47,.43-.49,.75,.36,7,1.04,13.98,1.59,20.96,.03,.32-.04,.64-.1,.96-.06,.14-.52,.24-.65,.17-8.12-8.56-15.45-17.92-23.29-26.75-3.43-3.84-6.59-7.95-10.23-11.61-.13-.07-.57,.03-.64,.18,.18,7.15,1.75,14.36,2.41,21.52,.17,1.38,.15,2.78,.2,4.18,0,.06-.14,.15-.24,.19-.11,.04-.33,.09-.37,.05-.54-.47-1.11-.94-1.58-1.46-4.41-4.89-8.8-M 9.8-13.21-14.69-4.26-4.71-8.56-9.41-12.84-14.11-4.63-5.33-2.67-.04-2.35,3.29,1.15,7.8,2.32,15.59,3.07,23.44-.13,.93-1.38-.06-1.69-.44-8.34-8.74-16.72-17.44-25.09-26.15-.32-.33-.73-.61-1.12-.9-.51-.11-.53,.66-.54,1.01,.42,3.21,.87,6.42,1.32,9.63,.85,6.21,1.76,12.41,2.61,18.62,.14,1.07,.17,2.14,.23,3.21,0,.09-.1,.26-.15,.26-1.33,.05-2.1-1.55-3.12-2.26-6.96-6.72-13.9-13.45-20.86-20.17-.67-.57-1.18-1.37-2.21-1.21,.49,6.22,1.63,12.41,2.32,18.62,.71,5.57,1.38,11.14,2.05,16.72,.03,.29-.1,.6-.2,.89-.01,.04-.3,.09-.37,.05-.M 53-.31-1.09-.61-1.53-.99-5.01-4.37-9.98-8.76-14.99-13.12-2.18-1.9-4.41-3.77-6.65-5.63-.12-.1-.5-.04-.75,0-.25,.29-.13,.85-.14,1.24,.9,8.8,2.03,17.58,2.79,26.4,.32,3.54,.62,7.09,.91,10.64-.08,.56,.33,1.65-.53,1.68-.73-.03-1.31-.7-1.91-1.06-6.23-4.76-12.46-9.54-18.69-14.3-.47-.36-.88-.81-1.62-.85-1.24,.09-.11,5.37-.25,6.53,.84,12.47,1.73,24.94,2.05,37.43-.36,1.37-2.43-.44-3.12-.77-5.39-3.4-10.72-6.89-16.12-10.27-.98-.47-1.62-1.48-3.04-1.27-.68,.78-.32,1.65-.31,2.48-.03,15.71,1.01,31.48,.09,47.15-.03,.22-.7,.54-.93,.4M 4-.94-.42-1.88-.83-2.79-1.28-5.99-2.87-11.79-6.14-17.89-8.78-.29-.12-.87,.17-.89,.44-.87,18.71-1.35,37.49-3.06,56.14-.05,.27-.61,.52-.94,.42-6.49-2.08-12.95-4.25-19.43-6.36-.85-.13-2.26-.99-2.85-.05-2.31,16.79-3.74,33.69-6.3,50.46-.61,4.39-1.21,8.78-1.83,13.16-.11,.75-.25,1.5-.95,2.08,0,0,.14-.08,.14-.08-7.67-1.61-15.52-2.62-23.25-4.05-1.54-.33-.71-2.1-.72-3.17,3.53-22.15,7.72-44.3,9.64-66.64l-.11,.12c7.14,1.57,14.01,4.43,21.06,6.46,.63,.14,1.66,.67,2.13,.02,2.3-19.99,3.22-40.13,4.45-60.22l-.14,.04c6.59,3.14,13.17,M 6.29,19.76,9.43,.61,.23,1.5,.89,2.09,.33,1.33-16.42,.68-33.17,.6-49.7-.11-3.15,.69-2.68,3.01-1.35,3.75,2.28,7.48,4.59,11.22,6.88,2.14,1.31,4.28,2.61,6.46,3.88,.25,.14,.73,.02,1.24,.02-.16-15.42-1.62-30.78-2.21-46.18-.07-.59,.84-.51,1.16-.34,6.12,4.16,11.89,8.74,17.85,13.11,.78,.58,1.65,1.09,2.52,1.6,.09,.05,.57-.14,.6-.26,.11-5.56-.89-11.17-1.23-16.74-.77-7.83-1.66-15.66-2.41-23.5-.21-2.8,1.76-.73,2.85,.08,5.96,4.98,11.91,9.96,17.88,14.94,.78,.51,1.47,1.52,2.51,1.27-.45-7.57-1.94-15.21-2.77-22.8-.52-3.74-1.08-7.48-M 1.57-11.23-.15-1.17-.14-2.35-.19-3.53,0-.06,.14-.15,.24-.19,.6-.27,1.34,.74,1.83,1.05,6.95,6.44,13.89,12.89,20.84,19.33,.55,.47,1.04,1.11,1.86,.91-.66-8.49-2.56-17.09-3.7-25.61-.46-2.88-.94-5.76-1.39-8.65-.03-.18,.12-.38,.18-.57,1.05,.15,1.67,.89,2.35,1.6,7.28,7.34,14.56,14.68,21.85,22.01,.84,.66,1.43,1.88,2.63,1.78-1.04-10.57-3.4-21.13-4.91-31.69h-.09Z"/><path class="cls-2" d="M1074.53,313.27c-19.6,1.34-38.67,3.19-58.19,5.13-.36,0-.76-.41-.6-.65,.55-.86,1.08-1.73,1.67-2.58,2.63-3.88,5.53-7.6,7.99-11.59,.2-1.25-3.0M 5-.39-3.83-.44-6.36,.9-12.72,1.84-19.08,2.73-9.42,1.32-18.75,2.96-28.07,4.64-.53,.1-1.05,.12-1.53-.13,.04-.79,.66-1.39,1.15-2.02,2.81-3.67,5.64-7.34,8.45-11.01,.39-.72,2.66-2.67,.83-2.8-15.35,2.52-30.58,5.93-45.7,9.48-.51,.13-1.04,.24-1.53-.08,0-.81,.69-1.38,1.18-2,3.35-4.16,6.76-8.3,10.12-12.46,.3-.55,2.09-2.27,.94-2.37-13.6,2.96-27.04,6.58-40.41,10.19-.75,.1-3.98,1.42-3.69,.2,4.68-5.97,9.95-11.46,14.66-17.41-1.21-.59-2.55,.3-3.81,.47-8.43,2.24-16.74,4.75-25.06,7.25-4.16,1.25-8.31,2.5-12.48,3.73-.18,.05-.46-.09-.6M 8-.18,.26-1.16,1.52-2.04,2.24-3.01,4.74-5.5,9.8-10.74,14.33-16.4,.26-1.06-3.22,.45-3.79,.5-10.01,3.18-20.07,6.25-29.93,9.71-1.6,.56-3.25,1.02-4.9,1.49-.17,.05-.46-.11-.66-.21,4.96-6.6,11.32-12.6,16.93-18.84,1.59-1.82,3.99-3.87-.38-2.46-10.63,3.37-21.3,6.68-31.73,10.46-2.35,.72-5.09,2.14-1.9-1.33,6.71-7.52,14.17-14.59,20.54-22.33-.56-.31-1.06-.21-1.57-.04-5.21,1.75-10.44,3.48-15.64,5.25-5.57,1.9-11.13,3.84-16.69,5.74-.36,.07-1.16,.29-1.36-.08,2.81-4.11,6.63-7.56,9.95-11.34,4.48-4.71,9.09-9.35,13.64-14.03,.65-.67,1.4M 9-1.25,1.72-2.15-1.52-.29-3.05,.68-4.53,1-8.2,2.73-16.4,5.47-24.6,8.2-1.23,.27-3.11,1.16-1.48-.88,7.95-9.16,16.4-17.91,24.69-26.79,.8-.86,1.55-1.75,2.31-2.63,.06-.07,.07-.27,.03-.29-.23-.08-.52-.22-.71-.16-8.56,2.56-17.15,5.06-25.64,7.85-.61,.2-1.3,.32-1.69,.81h.04c-.35-.49-.52-1-.07-1.5,3.09-3.38,6.13-6.8,9.31-10.12,7.35-7.68,14.77-15.31,22.16-22.96,.36-.49,1.27-.89,.83-1.58-.78-.27-2.18,.38-3.06,.49-7.15,1.86-14.29,3.73-21.44,5.6-1.24,.25-2.64,.94-3.84,.24l.06,.03c13.14-13.08,26.01-26.48,39.39-39.35,2.97-2.8-1.61M -1.14-3.03-1.02-7.06,1.4-14.11,2.81-21.17,4.21-3.73,.63-1.9-.81-.31-2.5,15.15-15.12,30.65-29.78,46.31-44.44,.34-1.2-1.82-.52-2.49-.62-6.3,.49-12.58,1.12-18.88,1.68-4.14,.35-4.43,.14-1.26-2.82,5.72-5.44,11.43-10.89,17.18-16.32,12.01-11.35,24.3-22.51,36.7-33.59,.94-.82,1.79-1.82,3.18-1.8,7.95-.03,15.9,.02,23.86,.03,1.57,.19,2.03,.37,.55,1.79-19,16.29-38.19,32.32-56.18,49.56-.12,.12-.02,.4,.03,.6,.01,.06,.21,.11,.33,.12,6.68-.19,13.35-1.41,20.02-2.01,1.47-.17,2.93-.39,4.4-.52,.59-.05,1.4-.37,1.74,.3,.24,.46-.34,.77-.6M 9,1.08-15.87,13.72-31.07,27.96-46.21,42.4-2.78,2.74,4.16,.44,5.15,.42,7.2-1.36,14.41-2.72,21.62-4.07,2.1-.05-.68,1.87-1.17,2.44-12.68,11.35-24.88,23.19-37.04,35.06-.49,.48-1.15,.9-1.14,1.62,.67,.26,1.3,.08,1.95-.08,5.4-1.35,10.79-2.69,16.19-4.03,3.47-.86,6.95-1.72,10.42-2.57,.62-.14,1.29-.32,1.87,.03-10.89,11.54-23.73,21.86-34.68,33.57-.91,1.72,2.55,0,3.22-.02,10.01-2.62,20.03-6.22,30.05-8.32,.08,.16,.2,.41,.11,.51-.72,.78-1.47,1.54-2.24,2.29-9.15,9.06-18.63,17.81-27.6,27.04-.1,.12-.02,.35,.03,.52,.02,.05,.25,.11,.M 35,.09,10.62-3.07,21.16-6.4,31.75-9.56,.98-.13,2.4-1.06,3.26-.42,0,.59-.93,1.1-1.28,1.59-7.58,7.57-15.16,15.14-22.73,22.71-.37,.53-2.02,1.89-.93,2.02,6.76-1.65,13.3-4.11,19.98-6.04,5.15-1.58,10.34-3.1,15.51-4.63,.34-.1,.77-.05,1.15-.01,.72,.16-.74,1.47-1.08,1.83-6.82,7.18-14.25,13.99-20.53,21.57,.67,.39,1.23,.21,1.9,0,3.51-1.1,7.03-2.17,10.52-3.31,7.73-2.52,15.58-4.79,23.46-6.99,.89-.25,1.75-.58,2.73-.4l.1,.08c-.37,1.67-2.16,2.67-3.19,4-5.05,5.7-10.94,10.85-15.51,16.88-.01,.03,.23,.2,.3,.18,1.02-.23,2.06-.45,3.06-.M 74,12.39-3.61,24.86-7.15,37.42-10.29,.63-.09,.95,.22,.55,.74-5.24,6.26-11.4,11.93-16.21,18.47-.02,.03,.2,.21,.28,.2,.64-.1,1.3-.2,1.92-.37,11.85-3.24,23.89-6.02,35.85-8.96,4.83-1.09,6.24-1.26,6.15-.93-.41,1.65-2.03,2.74-3.14,4.06-3.5,4.22-7.35,8.21-10.76,12.51-.81,1.45,1.45,.96,2.21,.75,14.16-3.16,28.37-6.08,42.66-8.7,.73-.07,1.59-.39,2.22,.13,.08,.05,.11,.23,.06,.3-.4,.56-.81,1.12-1.25,1.66-2.93,3.62-5.88,7.22-8.81,10.84-.77,1.19-2.2,2.17-2.27,3.61,10.78-1.17,21.58-3.68,32.44-5,6.23-.83,12.45-1.94,18.72-2.5,.38-.0M 2,.79,.39,.62,.63-3.36,4.81-6.93,9.48-10.37,14.24-.29,.3-.52,.86-.09,1.13,2.94,.25,5.87-.42,8.79-.69,16.27-1.9,32.63-3.37,48.99-4.3l-.08-.12c-3.55,5.37-6.81,10.99-10.53,16.23l.1-.05Z"/><path class="cls-2" d="M1005,333.95c-7.9,1.23-15.88,2.1-23.78,3.26-8.96,1.36-17.93,2.67-26.81,4.34-1.02,.11-2.12,.52-3.11,.09-.11-.69,.39-1.22,.76-1.79,2.36-3.61,4.72-7.22,7.09-10.83,.31-.48,.65-.94,.48-1.51,.05-.04,.11-.08,.16-.12-.25-.02-.27,.03-.05,.17-.93-.37-1.86-.1-2.76,.07-2.49,.46-4.96,1-7.45,1.48-12.69,2.13-25.23,6.02-37.76,M 7.96-.09-.17-.22-.4-.14-.53,.46-.78,.94-1.55,1.48-2.29,2.47-3.46,4.96-6.91,7.43-10.38,.27-.53,1.34-1.71,.35-1.89-1.94,.43-3.91,.82-5.82,1.33-7.16,1.88-14.33,3.76-21.46,5.72-5.49,1.45-10.82,3.36-16.34,4.68-.17,.02-.5-.2-.44-.39,3.16-5.42,7.67-10.04,10.84-15.45,.05-.17-.29-.43-.45-.4-.9,.23-1.79,.47-2.67,.72-12.18,3.47-24.04,7.6-36.01,11.49-.69,.25-1.54,.63-2.24,.38-.39-.19-.14-.56,.05-.82,3.88-5.44,8.1-10.65,12.04-16.05-1.02-.71-2.29,.23-3.38,.45-10.87,3.77-21.74,7.55-32.4,11.69-1.91,.56-4.98,2.24-2.4-1.14,4.24-5.5,M 8.56-10.94,12.76-16.48,.18-.24,.14-.42-.13-.52-8.97,2.61-17.75,6.74-26.64,9.89-2.67,1.03-5.28,2.14-7.93,3.21-.52,.21-1.04,.12-1.49-.17l-.1,.08c4.81-6.28,9.19-12.84,14.29-19.01,.36-.45,.8-.87,.61-1.46l.22-.1-.13,.18c-2.56,.01-4.88,1.76-7.32,2.49-7.6,2.84-14.88,6.74-22.39,9.41-.09-.18-.27-.44-.18-.57,2.31-3.28,4.6-6.57,6.99-9.81,2.8-3.8,5.68-7.56,8.52-11.34,.27-.36,.45-.77,.65-1.16,.03-.07-.06-.2-.14-.26-.07-.06-.24-.12-.31-.1-.98,.35-1.97,.69-2.91,1.09-8.19,3.48-16.35,7.04-24.56,10.49-.35,.19-.85-.02-.73-.4,5.81-8.3M 2,12.34-16.14,18.45-24.25,1.59-2.23,.44-1.63-1.34-1.1-7.22,2.89-14.44,5.77-21.49,8.92-1.8,.67-6.28,3.37-3.18-.67,7.1-9.14,14.34-18.18,21.37-27.36,.06-.07,.06-.26,0-.28-1.08-.51-2.2,.48-3.26,.73-8.01,2.95-15.81,6.75-23.92,9.26l.07,.09c-.36-1.18,.84-1.92,1.41-2.83,7.48-9.53,15.02-19.03,23.02-28.29,.73-1.08,2.21-1.92,2.07-3.32,.22,.04,.47,.08,.41-.21-.27-.11-.38-.01-.33,.28-.69-.19-1.32,0-1.94,.21-5.76,2.05-11.55,4.06-17.28,6.2-6.89,2.49-7.87,2.72-7.72,2.29,9.18-12.92,20.39-24.68,30.78-36.89,1.77-1.97,3.61-3.75-.67-2.M 54-6,1.55-12.01,3.11-18.01,4.66-.76,.2-1.53,.43-2.33,.09l.11,.05c-.06-.59,.37-1.01,.75-1.45,12.31-14.91,25.71-28.93,38.29-43.62,.27-.38-.4-.53-.63-.52-7.62,1.35-15.22,2.76-22.83,4.14-.12,.02-.33-.02-.37-.08-.4-.52,.14-.94,.45-1.35,11.46-13.07,23.07-26,35.2-38.66,3.28-3.42,6.52-6.86,9.76-10.31,.33-.51,1.56-1.38,.69-1.83-7.88,.17-15.77,1.45-23.65,1.98-1.53-.36,.28-1.69,.71-2.29,17.14-19.2,35.38-37.84,53.65-56.27,.71-.74,1.53-1.15,2.72-1.15,7.54-.2,15.09-.14,22.64-.13,2.29,.24,3.97-.28,1.25,2.28-14.76,13.92-29.16,28.2M 1-43.53,42.5-3.55,3.52-6.95,7.14-10.41,10.72-.48,.62-1.54,1.35-.25,1.72,7.36-.41,14.72-1.37,22.07-1.99,3.09-.21,1.75,.84,.36,2.35-6.14,6.14-12.39,12.22-18.43,18.42-8.94,9.18-17.74,18.44-26.59,27.67-.36,.41-.92,.8-.57,1.37,7.42-.52,15.01-2.51,22.45-3.65,.51-.09,1.02-.18,1.49,.1,.01,.72-.63,1.16-1.11,1.66-4.7,4.86-9.44,9.69-14.09,14.57-8.66,8.93-16.9,18.18-25.39,27.17,.1,.03,.19,.06,.27,.08l-.29-.13c1.85,.87,3.87-.52,5.73-.84,6.72-1.89,13.45-3.78,20.18-5.66,.5-.07,1.99-.6,1.99,.15-10.35,11.92-21.63,23.27-31.74,35.38-M .45,.52-1.08,.98-1.09,1.68,0,.07,.18,.22,.24,.21,8.82-2.32,17.37-5.76,26.16-8.31,.52-.17,1-.29,1.62,.07-8.66,10.16-17.76,19.96-26.28,30.16-.53,.62-.94,1.29-1.4,1.95-.04,.17,.32,.39,.47,.35,8.21-2.56,16.19-5.82,24.31-8.65,1.3-.32,2.81-1.43,4.11-.62l.09-.09c-3.59,3.53-6.7,7.5-9.97,11.3-4.41,5.26-8.79,10.54-13.18,15.82-.18,.31-.69,.81-.35,1.11,.08,.07,.25,.15,.33,.13,.99-.32,2-.62,2.96-1,7.84-3.07,15.64-6.2,23.62-9.02,2.6-.93,2.23-.19,.81,1.58-6.11,7.3-12.26,14.59-18.1,22.1-.3,.38-.44,.77-.15,1.19-.19-.16-.28-.15-.29,M .03l.23-.11c9.71-3.14,19.11-7.48,28.9-10.71,.98-.35,1.98-.67,2.98-.96,.17-.05,.46,.12,.66,.22,.05,.03,.02,.23-.05,.3-.75,.89-1.51,1.78-2.28,2.66-5,5.74-10.01,11.48-15.01,17.23-.54,.62-1.04,1.25-1.51,1.91-.09,.13,.06,.38,.15,.56,.45,.16,1.01-.19,1.47-.3,7.09-2.61,14.2-5.19,21.28-7.83,4.64-1.73,9.33-3.34,14.11-4.81,.19-.06,.48,.09,.71,.18,.04,.01,.01,.2-.04,.29-3.6,4.73-7.85,9-11.64,13.58-1.68,1.95-3.27,3.95-4.89,5.93-.31,1.45,3.28-.48,3.98-.54,7.42-2.56,14.82-5.14,22.25-7.67,4.09-1.39,8.22-2.69,12.34-4.01,.2-.06,.56M -.04,.7,.07,.14,.11,.19,.42,.09,.56-.46,.65-.98,1.29-1.49,1.92-3.62,4.41-7.25,8.82-10.87,13.23-.59,.72-1.18,1.44-1.71,2.19-.09,.12,.05,.37,.14,.54,12.47-3.2,25.02-7.91,37.64-11.35,1.24-.21,2.55-1.11,3.78-.64-3.51,5.85-8.83,10.95-12.61,16.77,1.38,.49,2.58-.42,3.93-.64,12.97-3.58,25.93-7.21,39.12-10.27,.72-.17,1.23-.35,1.93,.13-3.44,4.77-7.12,9.37-10.65,14.07-.29,.47-1,1.33-.18,1.6,13.6-2.78,27.19-6.15,40.93-8.71,2.09-.19,4.65-1.41,6.65-.77,.08,.7-.44,1.21-.84,1.77-2.96,4.23-6.2,8.28-8.95,12.64-.06,.21,.27,.72,.59,.6M 7,2.64-.42,5.28-.84,7.92-1.27,14.51-2.38,29.05-4.83,43.67-6.4,.34,0,.72,.44,.57,.69-3.01,4.83-6.13,9.59-9.24,14.35l.1-.06Z"/><path class="cls-2" d="M475.58,1023.99s.02,.02,.02,.03c-.03,0-.06,.01-.09,.01,0,0,.01,0,.01-.01,.02,0,.03-.03,.05-.02h.01Z"/><path class="cls-2" d="M708.53,1043.43h0s-.04,.03-.07,.05c.02-.02,.04-.04,.06-.05Z"/><path class="cls-2" d="M771.18,1312.07s.02-.03,.03-.05c.02,0,.05-.01,.07-.01l-.1,.06Z"/><path class="cls-2" d="M800.44,1026.36h-.12s-.01-.03-.01-.04l.13,.04Z"/><path class="cls-2" d="M8M 21.24,1148.14c-6.13,1.7-11.93,4.93-17.95,7.18-.46,.19-1,.26-1.52,.36-.07,.02-.29-.15-.27-.21,6.46-14.48,14.61-28.31,20.21-43.11,0-.07-.18-.21-.24-.21-6.41,2.35-12.05,6.23-18.38,8.9-.51-1.32,.52-2.26,.96-3.43,5.19-11.44,11.4-22.95,15.25-34.62-1-.25-1.81,.68-2.67,1.04-4.25,2.48-8.47,4.97-12.72,7.44-.74,.43-1.4,.99-2.39,1.05-.36-.43-.11-.82,.07-1.23,2.65-6.21,5.32-12.42,7.96-18.63,1.65-3.87,3.27-7.75,4.91-11.63,.22-.51,.46-1.01,.12-1.53-.75-.03-1.24,.37-1.75,.71-5.01,3.21-9.96,6.86-15.2,9.54-.54-.54,.03-1.18,.22-1.76,M 3.72-8.87,7.57-17.69,10.51-26.77-.24-1-1.92,.45-2.4,.74-4.72,3.1-9.15,6.99-14.05,9.64-.65-.47-.05-1.14,.11-1.72,2.91-7.05,5.25-14.24,7.9-21.36,.27-.71,.55-1.42,.4-2.17-1.32,.08-2.22,1.37-3.33,2.01-3.56,2.63-7.12,5.27-10.69,7.89-.81,.45-1.56,1.37-2.56,1.22-.06-.01-.14-.2-.11-.29,.27-.83,.53-1.66,.86-2.48,2.15-5.33,4.04-10.72,5.76-16.15,.29-.93,.55-1.88,.81-2.82,.02-.07-.12-.21-.23-.26-.01,0-.02-.01-.03-.01-.7-.03-1.32,.67-1.89,1.01-3.19,2.47-6.35,4.97-9.56,7.44-2.81,2.17-5.66,4.3-8.5,6.45-.49,.37-.98,.75-1.69,.82-.2M 7-.41-.14-.81,0-1.22,1.47-4.32,2.97-8.63,4.39-12.97-2.21,.17-4.42,.33-6.64,.47-4.14,3.19-8.36,6.29-12.71,9.29-.51,.24-1.05,.9-1.65,.7-.11-.06-.24-.19-.22-.26,.88-3.07,2.2-6.02,3.12-9.07-3.31,.17-6.63,.31-9.96,.43-2.75,2.01-5.5,4.02-8.25,6.03-.83,.43-1.64,1.4-2.59,1.41-.09-.03-.21-.16-.2-.22,.37-2.39,1.28-4.64,1.96-6.96-3.5,.09-7.01,.14-10.53,.17-3.06,2-6.14,3.99-9.22,5.98-.63,.29-1.3,1.05-2.01,.94-.14-.15-.34-.35-.31-.51,.46-2.18,1.35-4.28,2.03-6.4-3.2-.02-6.41-.06-9.62-.12-4.26,2.83-8.64,5.45-13.13,7.93-.13,.08-.4M 7-.03-.69-.11-.32-.26-.07-.87-.03-1.24,.67-2.3,1.36-4.59,2.02-6.89-2.31-.08-4.62-.18-6.93-.28-5.59,3.21-11.35,6.21-17.09,9.24-.49,.14-2.14,1.3-2.33,.44,.53-3.86,2.4-7.48,2.98-11.34-.26-1.03-2.32,.46-2.93,.67-9.31,4.53-18.89,9.67-28.87,12.77-.13-.18-.32-.4-.27-.57,.93-3.47,2.21-6.86,2.97-10.37-.23-1.26-2.57,.17-3.34,.34-9.86,4.23-20.15,7.74-30.32,11.44-.86,.13-3.76,1.75-3.63,.31,.86-3.4,2.22-6.63,3.15-10.02,.1-.38-.54-.83-1.03-.69-13.05,4.02-26.09,8.17-39.43,11.42-.21-.24-.49-.41-.47-.57,.41-3.01,1.7-5.86,2.51-8.79,M .25-.83,.8-2.07-.7-1.92-13.85,3.28-27.71,6.31-41.81,8.69-.87,.05-1.9,.44-2.6-.25,.81-2.94,1.81-5.84,2.68-8.76,.29-.91,.7-2.41-.84-2.25-16.9,2.8-34.02,4.02-51.02,5.94,.37,.34,.43,.75,.28,1.17-1.03,3.54-2.85,6.95-3.43,10.59,1.17,.52,2.4,.22,3.57,.12,15.37-1.22,30.61-3.45,45.86-5.66,.78-.14,2.33-.21,1.98,.8-1.08,3.34-2.36,6.62-3.53,9.93-.22,.62,.29,1.03,1.11,.9,7.87-1.35,15.75-2.82,23.53-4.53,7.01-1.47,13.92-3.48,20.99-4.61,.64,.15,.42,.94,.25,1.39-1.13,3.31-2.89,6.48-3.63,9.88,.25,.58,1.2,.4,1.72,.29,13.14-3.48,26.06M -7.42,39-11.44,.32-.08,.9,.27,.84,.5-.11,.42-.18,.85-.34,1.26-1.24,3.29-2.79,6.49-3.81,9.85-.02,.09,.41,.38,.53,.35,12.75-3.71,25.05-9.13,37.49-13.43,.45,.18,.26,.8,.2,1.16-1.1,2.88-2.25,5.75-3.34,8.63-.28,.71-.46,1.45-.62,2.18-.02,.08,.39,.32,.58,.31,9.25-3.2,18.28-7.34,27-11.53,1.62-.77,3.2-1.63,4.88-2.28,.19-.06,.47,.01,.68,.08,.43,.32-.08,1.11-.11,1.54-1.21,3.63-2.8,7.17-3.77,10.87-.04,.18,.35,.41,.51,.36,.95-.4,1.92-.76,2.81-1.23,7.63-4.04,15.4-7.9,22.8-12.22,.54-.19,1.17-.69,1.75-.49,.09,.07,.2,.2,.17,.28-1.6M 2,4.43-3.26,8.87-4.89,13.3h-.09c.15,.05,.3,.1,.45,.12h0c1.01,.23,1.88-.6,2.74-.99,6.54-3.56,12.81-7.41,18.94-11.4,1.12-.57,2.75-2.02,3.89-2.15,.67,.36,.32,1.13,.18,1.71-1.18,3.29-2.15,6.63-3.61,9.86-.32,1.23-1.75,2.81-.62,3.93,7.63-5.31,15.7-10.02,23.5-15.1,.22-.23,1.21-.41,1.19,.09-1.56,5.48-4.18,10.66-6.09,16.04-.2,.37,.33,.66,.66,.52,6.77-4.15,13.07-8.97,19.61-13.44,.98-.56,2.09-1.74,3.21-1.78,.41,.58,.29,1.18,0,1.78-1.84,4.95-3.59,9.92-5.77,14.79-.19,.67-.82,1.48-.61,2.14,.52,.5,1.24-.15,1.63-.43,6.6-4.59,13.19M -9.2,19.79-13.79,.5-.22,1.94-1.55,2.09-.66-2.18,6.23-4.98,12.26-7.36,18.42-.34,.82-.64,1.64-.93,2.47-.02,.06,.12,.2,.23,.25,.72,.1,1.36-.63,1.98-.94,5.96-4.19,11.91-8.4,17.88-12.6,.79-.55,1.41-1.31,2.7-1.52-2.25,8.44-6.73,16.3-9.93,24.5,.09,.46,1.08,.04,1.32-.09,3.33-2.18,6.62-4.4,9.95-6.6,1.86-1.23,3.76-2.44,5.66-3.64,.16-.07,.86,.04,.78,.4-.19,.62-.36,1.26-.62,1.86-3.29,7.63-6.6,15.25-10.39,22.74-1.18,2.32-1.99,4.04,1.31,1.98,4.92-3,9.79-6.06,14.74-9.03,.09-.05,.33-.05,.38,0,.65,.47,.08,1.16-.11,1.74-4.41,9.7-8.7M 6,19.45-13.65,28.99-.48,1.34-.01,1.34,1.12,.88,4.43-2.45,8.84-4.92,13.26-7.39,.99-.55,1.99-1.1,3.01-1.61,.13-.07,.46,.08,.67,.17,.08,.03,.14,.19,.11,.27-.23,.62-.43,1.24-.73,1.84-3,6.11-5.97,12.23-9.05,18.31-2.61,5.19-5.35,10.34-8.04,15.5-.13,.25-.07,.43,.25,.53,5.85-1.93,11.31-5.43,17-7.93,.55-.27,1.07-.59,1.78-.43,.24,.9-.31,1.61-.69,2.39-6.58,13.19-13.64,26.25-20.92,39.19,.87,.64,1.71,.05,2.6-.21,4.56-1.86,9.11-3.73,13.67-5.59,.97-.34,4.56-2.27,4.21-.71-8.07,15.68-17.06,31-26.08,46.22-.22,.38-.31,.81-.42,1.23-.0M 2,.05,.17,.21,.26,.21,.52-.03,1.07-.01,1.55-.16,6.4-1.96,12.74-4.14,19.18-5.98,.32-.02,.8,.25,.55,.63-9.79,18.12-20.65,35.59-31.66,53.04-.97,1.54-1.52,2.46,.98,1.9,6.91-1.41,13.74-3.2,20.7-4.33,.3-.04,.67,.46,.53,.73-12.37,21.4-26.33,42.02-39.73,62.82-.14,.25,.29,.66,.67,.64,1.07-.06,2.16-.08,3.22-.2,7.18-.81,14.34-1.63,21.51-2.45,13.34-21.72,26.4-43.54,38.57-65.72,.21-.54,.28-1.25-.58-1.2-7.15,1.52-14.29,3.08-21.46,4.54-.2,.04-.48-.12-.69-.22,10.05-19.03,21.69-37.6,30.9-57.11-.95-.75-2.29,.17-3.37,.36-5.38,1.71-10M .75,3.43-16.13,5.14-.59,.12-1.7,.68-1.98-.09,7.82-15.32,16.39-30.4,23.66-45.96,.44-.9,.85-1.82,1.26-2.73,.17-.39,.08-.88-.15-.89Zm-19.87-25.55c-.07,.02-.15,.02-.23,.01-.03-.2,.06-.26,.28-.19,.01,.01-.01,.17-.05,.18Z"/><path class="cls-2" d="M606.21,1010c-11.16,3.55-22.33,6.87-33.74,9.74-.82,.2-1.44-.15-1.3-.74,.74-2.94,1.39-5.93,2.01-8.89,.19-.92-.29-1.28-1.28-1.03-8.85,2.28-17.88,4.03-26.9,5.81-5.22,1.02-10.51,1.86-15.79,2.71-1.33,.05-1.28-1.38-1.48-2.31-.55-2.66-1.19-5.29-1.68-7.96-.14-.9,.3-1.35,1.52-1.55,10.02-M 1.5,20.03-3.17,29.89-5.28,4.89,1.14,9.81,2.22,14.76,3.25,.36,1.31,.7,2.61,1.08,3.91,.12,.38,.77,.73,1.24,.64,3.11-.55,6.15-1.45,9.19-2.24,7.44,1.43,14.93,2.74,22.48,3.94Z"/><path class="cls-2" d="M627.78,1013.08c-5.99,2.13-11.96,4.62-18.07,6.33-.2,0-.57-.22-.57-.33,.31-2.83,1.26-5.56,1.81-8.34,5.58,.85,11.19,1.63,16.83,2.34Z"/><path class="cls-2" d="M648.82,1015.47c-1.84,.51-6.72,3.92-5.11-.52,1.7,.19,3.4,.36,5.11,.52Z"/><path class="cls-2" d="M783.55,974.56c-.47,.05-.95,.1-1.42,.14,.31-.19,.62-.71,1.01-.58,.16,.13M ,.4,.3,.41,.44Z"/><path class="cls-2" d="M810.4,1039.05s.02-.03,.03-.04c.01,.01,.01,.02,.02,.02l-.05,.02Z"/><path class="cls-2" d="M822.93,1306.26s.02-.03,.03-.05c.02-.01,.04-.01,.06-.01l-.09,.06Z"/><path class="cls-2" d="M834.45,1045.34c-.03-.08-.06-.15-.1-.23,.05,.02,.09,.1,.12,.24,0,0,0-.01-.02-.01Z"/><path class="cls-2" d="M842.75,1180.57c-.36,.81-.7,1.62-1,2.45-.04,.15,.22,.72,.63,.58,5.93-1.66,11.73-3.79,17.61-5.62,2.11-.57,3.57-1.45,2.27,1.6-8.54,19.89-17.54,39.52-27.03,59.01,.58,.4,1.1,.4,1.63,.28,3.25-.71,M 6.49-1.42,9.73-2.14,3.24-.72,6.48-1.45,9.73-2.16,.63-.14,1.3-.25,1.93,.36-10.76,24.14-22.82,47.88-35.29,71.28-7.59,.74-15.15,1.67-22.73,2.52-1.89-.03-3.23,.65-1.78-1.94,12.14-21.37,24.12-42.88,35.05-64.88,.26-.65,1.23-1.36,.35-2.02-.65-.48-1.52,.04-2.27,.21-6.36,1.36-12.7,2.86-19.08,4.14-.6,.15-1.47-.01-1.11-.79,4.67-9.17,9.61-18.24,14.23-27.42,5.07-10.31,10.51-20.48,14.84-31.03-.4-.64-1.49-.14-2.08-.03-5.37,1.73-10.72,3.48-16.09,5.21-1.74,.41-4.13,1.73-2.48-1.28,8.17-16.29,15.97-32.59,22.93-49.3-.08-1.36-2.1,.15-2M .81,.26-4.88,2.06-9.75,4.14-14.62,6.2-1.06,.38-3,1.42-2.15-.66,6.52-14.21,13.02-28.42,18.51-43.01,0-.19-.08-.47-.25-.55-.18-.08-.54-.03-.75,.07-5.82,2.82-11.36,6.2-17.29,8.78-.42-.51-.27-.92-.1-1.33,1.67-3.87,3.38-7.72,5-11.59,3.47-8.6,7.22-17.1,9.94-25.9,.04-.39-.63-.39-.83-.32-5.37,3-10.44,6.53-15.85,9.45-.21,.06-.85-.02-.8-.38,.31-.93,.6-1.87,.96-2.79,2.44-6.38,4.93-12.75,7.35-19.13,1.2-3.19,2.29-6.41,3.41-9.62,.22-.78,.55-1.68-.12-2.33v-.18c-4.38,3.72-9.53,6.62-14.21,10.03-.51,.24-1.09,.86-1.68,.65-.1-.06-.23-.M 19-.21-.27,.2-.73,.4-1.47,.66-2.19,2.14-6,4.35-11.99,6.44-18.01,1.01-2.9,1.81-5.84,2.69-8.77,.04-.43-.51-.32-.79-.32-4.84,3.31-9.44,7.09-14.18,10.57-.27,.2-.42,.5-.63,.75-.97-.85-.28-2.03-.04-3.05,2.4-7.72,5.35-15.28,7.33-23.11-.27-.92-2.18,1.02-2.68,1.27-3.62,2.88-7.23,5.78-10.86,8.66-.68,.44-1.27,1.31-2.18,1.12-.07-.01-.16-.19-.15-.28,.69-3.27,1.85-6.44,2.74-9.67,8.98-1.08,17.89-2.34,26.73-3.78-1.22,4.59-2.62,9.15-4.01,13.7-.05,.39-.32,1.26,.03,1.5,.94-.08,1.75-1,2.54-1.46,3.98-3.06,7.94-6.14,11.92-9.19,.18-.09,.M 89-.15,.88,.25-.34,1.92-.95,3.8-1.42,5.7-1.94,7.26-4.16,14.46-6.54,21.64-.2,.9-.8,1.91-.37,2.8-.05-.02-.11,0-.18,.06,.09,.06,.19,.11,.28,.17,.01,.02,.02,.05,.03,.07,0-.02-.01-.04-.01-.06,4.92-3.52,9.83-7.05,14.8-10.51,.18-.12,.49-.13,.75-.17,.65,.18,.2,1.26,.07,1.76-2.82,9.86-6.12,19.62-9.6,29.34-1.61,4.53-1.88,4.88,2.48,2.23,4.31-2.57,8.47-5.37,12.85-7.82,.22-.09,.88-.07,.85,.31-3.73,12.61-8.35,24.93-13.02,37.29-.13,.73-1,1.85-.17,2.33,5.33-2.08,10.39-5.42,15.6-7.93,.64-.26,1.82-1.2,2.19-.2-.43,1.46-.85,2.93-1.39,M 4.37-5,13.75-10.64,27.33-15.84,40.98,.5,.75,1.7-.14,2.37-.28,5.65-2.19,11.05-5.15,16.8-6.95,.42,.37,.32,.8,.17,1.21-6.25,16.65-13.3,32.96-20.63,49.26Z"/><polygon class="cls-2" points="215.62 631.94 215.62 631.95 215.61 631.95 215.62 631.94"/><path class="cls-2" d="M283.35,664.05c-1.64-3.86-3.36-7.71-4.72-11.68-.04-.12,.33-.66,.71-.42,1.37,.86,2.54,1.99,3.85,2.93-.05,3.05,.01,6.11,.16,9.17Z"/><path class="cls-2" d="M259.61,670.12c2.25,6.22,5.02,12.27,7.48,18.41,.16,.75,1.06,1.71,.39,2.35-9.61-6.3-18.45-14.22-27.43-2M 1.37-5.14-4.27-10.21-8.59-15.31-12.88-.67-.63-1.97-1.35-1.47,.35,2.19,6.54,4.6,13.03,6.68,19.62,.07,.41-.61,.39-.78,.31-17.34-13.65-33.38-28.58-49.64-43.38-.42-.38-.78-.88-1.73-.76,.93,6.05,2.9,12,3.68,18.07-.75,.11-1.14-.16-1.5-.49-13.67-12.25-27.16-24.79-40.26-37.53-5.81-5.66-11.5-11.39-17.25-17.1-.69-.61-1.19-.54-1.27,.19,.65,5.8,1.38,11.57,2.08,17.37,.04,.31-.04,.63-.1,.95-.08,.15-.5,.24-.64,.15-17.87-16.53-34.82-34.27-51.59-51.8-5.37-5.67-10.64-11.39-16.01-17.06-.94-1-1.38-2.02-1.37-3.27,.03-6.14,0-12.28-.01-1M 8.42,.28-1.41,1.56-.23,2.02,.4,18.55,20.64,37.01,41.16,56.54,60.99,2.5,2.55,4.99,5.09,7.52,7.61,.2,.2,.67,.22,1.08,.35-.07-6.31-1.34-12.47-1.83-18.75-.01-.14,.29-.3,.48-.41,16.11,15.81,31.85,32.88,48.62,48.6,2.57,2.49,5.24,4.92,7.86,7.38,1.31,.94,.95-1.29,.75-1.97-1.31-6.26-3.65-12.73-4.3-18.93,.71-.06,1.3,.75,1.84,1.11,4.14,3.97,8.25,7.96,12.41,11.92,10.82,10.32,22,20.39,33.32,30.36,.54,.42,1.07,1.07,1.85,.94-1.35-6.31-4.04-12.72-5.87-19.06-.26-.78-.64-1.58-.24-2.41h.01c.72,.1,1.1,.56,1.55,.95,12.62,11.3,25.32,22.M 36,38.59,33.06,.62,.48,1.26,1.3,2.19,1.18,.31-.67-.18-1.26-.4-1.86-1.19-3.19-2.47-6.37-3.68-9.56-1.17-3.09-2.29-6.19-3.41-9.29-.07-.18,.06-.41,.1-.62,.93,.02,1.55,.54,2.18,1.13,2.82,2.32,5.61,4.65,8.45,6.95,7.48,6.07,15.02,12.1,22.77,17.95,.64,6.06,1.67,12.12,3.11,18.14-8.42-6.26-16.95-12.5-25.09-19.03-.7-.45-1.31-1.27-2.23-1.13-.06,.01-.17,.2-.14,.29Z"/><path class="cls-2" d="M378.95,529.15l-.03,.06s-.03,.01-.05,.01l.08-.07Z"/><path class="cls-2" d="M401.49,501.45c-4,2.27-7.97,4.59-11.89,6.95-.53-3.4-1.08-6.81-1.5M 8-10.21,0-.62-.32-1.87,.64-1.85,4.39,1.39,8.5,3.53,12.83,5.11Z"/><path class="cls-2" d="M402.89,570.87c-1.07-4.29-2.21-8.59-3.24-12.89-4.46,1.25-8.89,2.82-13.26,4.73,1.3,3.94-.67,2.47-3.04,1.38-3.44,1.62-6.74,3.41-9.9,5.37,1.96,6.73,3.87,13.46,6.12,20.13,.1,.49,.77,2.5-.31,2.18-5.01-2.19-9.64-5.08-14.48-7.62-1.91-.92-2.26-.86-1.7,1.34,3.1,9.37,6.24,18.72,9.7,28,1.07,3-.57,1.66-2.23,.9-21.29-12.06-17.36-13.42-9.67,8.72,1.49,3.91,3.04,7.8,4.56,11.71,.08,.33,.33,1.01-.12,1.09-5.2-2.33-9.85-6.02-14.83-8.85-1.38-.86-2.7M -1.78-4.07-2.66-2.15-1.11-.66,1.73-.34,2.6,3.31,8.3,7.05,16.45,10.14,24.84-.21,.68-1.16,.09-1.58-.08-6.89-3.76-13.29-7.95-19.7-12.36-.27-.19-.78,.22-.77,.41,.43,1.24,.85,2.49,1.39,3.7,2.67,5.98,5.38,11.95,8.06,17.92,.1,.51,.66,1.13,.31,1.51-.21,.07-.5,.16-.66,.09-6.3-3.72-12.32-7.92-18.5-11.83-.17,2.93-.21,5.87-.11,8.83,1.57,3.53,3.33,7,4.73,10.61-.14,1.16-3.51-1.55-4.07-1.84,.75,6.32,2.1,12.64,4.09,18.89,1.36,.59,11.86,8.36,11.86,6.53-3.24-6.97-7.22-13.64-10.2-20.71,.27-1.27,1.66,.21,2.3,.49,6.58,4.11,13.18,8.2,20M ,12.06,.77,.43,1.6,.79,2.41,1.16,.15,.04,.45-.25,.41-.39-2.99-6.72-6.59-13.18-9.81-19.79-1.48-3.21,.84-1.36,2.37-.63,6.07,3.58,12.23,7.14,18.6,10.31,.49,.25,.96,.04,.85-.5-2.96-6.37-6.21-12.61-9.26-18.94-.34-1.15-1.76-2.58-.6-3.62,5.66,3.75,11.93,6.53,17.99,9.58,.37,.12,1.1,.48,1.39,.11,.24-.31,.06-.61-.08-.9-3.34-6.93-6.55-13.89-9.39-20.96-.49-1.2-1.35-2.34-1.16-3.66,.05-.37,.62-.14,4.35,1.88,4.52,2.3,8.83,5.08,13.55,6.96,1.08,.03,.05-1.66-.05-2.23-3.46-9.04-7.45-17.92-10.6-27.08-.03-.17,.32-.41,.48-.36,4.4,1.71,8M .48,4.16,12.77,6.15,3.66,1.68,5.1,2.93,2.98-2.03-3.03-8.25-6.13-16.49-8.79-24.83-.27-.83-.47-1.68-.68-2.52-.02-.08,.09-.24,.18-.28,1-.41,1.89,.54,2.81,.83,3.63,1.64,7.26,3.28,10.9,4.91,.59,.18,1.63,.75,2.09,.14-2.96-10.06-6.24-20.03-9-30.12-.24-.83-.54-1.66-.29-2.54,.99-.29,1.9,.45,2.82,.73,3.34,1.39,6.66,2.8,10.01,4.17,.69,.28,1.36,.67,2.36,.5-.02-.4,.02-.83-.09-1.24Zm-44.66,82.8s.01-.05,.01-.08c.03,.02,.06,.04,.09,.07-.03,0-.07,.01-.1,.01Z"/><path class="cls-2" d="M415.36,463.94s-.05,0-.08,0c-.01-.03-.01-.05-.02-M .08l.1,.08Z"/><path class="cls-2" d="M417.43,492.72c-4.74,2.49-9.43,5.05-14.06,7.66-1.29-13.69-3.72-27.6-3.55-41.31,.54-.3,1.62,.27,2.21,.41,4.33,1.53,8.65,3.82,13.25,4.46,.79,9.58,1.04,19.22,2.15,28.78Z"/><path class="cls-2" d="M419.48,507.14l-.16,.13s-.04-.07-.06-.11c.07,0,.15-.01,.22-.02Z"/><path class="cls-2" d="M283.37,718.28c7.14,4.84,14.22,9.78,21.49,14.45-4.4-7.09-8.32-14.85-11.44-22.69-7.94-5.43-15.56-11.18-23.35-16.72-.39-.26-.73,.25-.7,.38,.5,1.34,1.02,2.68,1.59,4,2.16,4.98,4.33,9.96,6.51,14.94,.18,.41,.M 31,.8-.04,1.2-10.81-6.76-20.73-15.11-30.85-22.75-4.7-3.71-9.36-7.45-14.05-11.16-.26-.21-.69-.29-1.04-.43-.07,.28-.25,.58-.17,.84,.79,2.61,1.63,5.22,2.45,7.83,.85,2.71,1.68,5.42,2.51,8.13,.02,.08-.11,.22-.21,.26-.57,.12-1.2-.5-1.65-.76-7.15-5.7-14.36-11.37-21.42-17.14-9.23-7.55-18.24-15.26-27.14-23.06-1.05-.7-1.95-2.15-3.27-2.19-.05,0-.17,.19-.15,.28,.09,.74,.15,1.49,.32,2.23,1.12,4.97,2.27,9.95,3.39,14.93,.03,.14-.19,.33-.33,.47-.68,.02-1.29-.76-1.85-1.12-6.59-5.69-13.2-11.37-19.74-17.1-13.67-11.5-26.14-24.65-39.67M -36.08-.34-.02-.54,.12-.52,.39,.25,4.86,.95,9.64,1.61,14.46,.27,2.97,.85,5.53-2.49,2.27-23.94-21.33-45.91-44.58-68.87-66.74-.07-.04-.34,.03-.36,.08-.13,.41-.3,.82-.3,1.23,.08,6.62-.1,13.18,.19,19.79,24.01,23.26,48.25,47.21,74.36,68.36,.38,.12,.55-.29,.45-1.05-.69-5.79-1.89-11.52-2.04-17.35,0-.08,.11-.23,.18-.24,1.13-.19,1.83,1.08,2.68,1.64,6.41,5.68,12.8,11.37,19.22,17.03,12.86,11.33,26.25,22.25,39.65,33.18,.78,.47,1.48,1.52,2.5,1.27,.08-.01,.17-.19,.15-.28-.83-3.6-1.68-7.19-2.52-10.79-.44-1.9-.88-3.81-1.3-5.72-.11M -.49-.01-.94,.33-1.35,.01,0,.02,0,.03-.02h0s.04-.07,.08-.1c17.4,14.96,35.57,29.01,54.26,42.61,.16,.09,.6-.02,.61-.23-.17-.84-.3-1.69-.56-2.51-1.36-4.15-2.76-8.3-4.14-12.46-1.17-3.47,2.17-.27,3.27,.43,12.38,9.42,25,18.63,38.05,27.45,1.85,1.24,3.73,2.46,5.62,3.67,.13,.08,.47-.03,.7-.08-1.34-4.74-3.97-9.58-5.74-14.34-.26-.61-.49-1.24-.02-1.86-.02,.04-.04,.08-.04,.1,1.26,.79,2.54,1.58,3.77,2.42Zm-95.86-45.22s-.01-.05-.01-.08c.02,.02,.04,.05,.06,.07-.01,0-.03,.01-.05,.01Z"/><path class="cls-2" d="M370.46,678.14l-.03,.03M s-.07-.08-.07-.06l-.02-.02s.11,.05,.12,.05Z"/><path class="cls-2" d="M391.54,688.94c.07-.03,.21-.02,.28-.03,0,0-.18,.02-.28,.03Z"/><path class="cls-2" d="M419.48,507.14s-.03,.09-.04,.13h-.12l.16-.13Z"/><path class="cls-2" d="M433.04,580.87c-3.93,.39-7.96-1.72-11.84-2.38-.61-.1-1.78-.42-2.11,.25,2.17,10.41,5.98,20.48,8.95,30.71-.41,.47-.9,.54-1.45,.4-3.32-.88-6.64-1.77-9.95-2.65-.74-.11-2.49-1.04-2.73,0,2.95,9.19,6.66,18.15,9.91,27.23,.27,.79,.85,2.13-.64,1.92-3.68-.98-7.32-2.16-10.96-3.26-.71-.21-2.54-.98-2.52,.23,M 3.08,8.27,6.55,16.37,10.28,24.44,.35,.78,1.3,2.39-.31,2.19-4.23-.95-8.28-2.54-12.44-3.75-2.79-.88-2.05,.29-1.21,2.18,3.13,6.68,7.17,13.29,9.84,20.04-.82,.49-1.76-.07-2.6-.25-4.56-1.54-9.12-3.12-13.66-4.7-.18,.26-.44,.47-.39,.61,.25,.72,.52,1.44,.89,2.12,3.34,6.23,7.06,12.27,10.19,18.6-.3,.78-1.39,.17-1.97,.04-4.86-1.84-9.72-3.69-14.56-5.56-.69-.26-1.36-.53-2.12-.36h-.13s.01,.01,.01,.02c3.43,5.84,6.84,11.69,10.26,17.53,2.32,3.62,2.07,3.95-1.91,2.26-5.11-2.18-10.21-4.37-15.32-6.55-1.35-.42-2.28-.92-1.4,1,3.54,6.06,7.M 2,12.06,10.87,18.04,.09,.14,.03,.44-.11,.55-.81,.39-1.73-.38-2.52-.6-6.98-2.79-13.37-6.5-20.22-9.37-.58,.81,.33,1.62,.63,2.39,2.91,5.09,5.98,10.13,9.19,15.1,.43,.67,.78,1.37,1.11,2.07,.05,.11-.2,.32-.37,.58-7.51-3.3-14.76-7.11-21.93-10.92-1.37-.62-2.57-1.73-4.12-1.82-.24,0-.28,.5-.05,.89,3.48,5.84,7,11.64,10.49,17.47,.86,1.47,.14,1.45-1.08,.87-10.18-7.76-19.01-17.51-25.86-29.03,4.51,2.66,9.01,5.4,13.7,7.79,.29,.14,.54,.06,.65-.17,.05-.09,.13-.21,.09-.28-.33-.71-.67-1.41-1.05-2.1-3.11-5.83-6.5-11.55-9.45-17.47-.11-1M .42,2.46,.58,3.01,.8,6.67,4.03,13.71,7.63,20.65,11.34,.99,.62,2.78,1.29,1.97-.35-3.11-5.49-6.21-10.99-9.31-16.48-1.61-2.94-2.41-4.44,1.53-2.13,6.52,3.2,12.84,6.87,19.5,9.76,.18,.07,.53-.16,.51-.32-2.9-5.83-6.29-11.41-9.37-17.16-.46-1.36-2.42-3.13-1.18-4.46,5.8,3.71,12.49,6.18,18.81,9.14,1.62,.28,.51-1.42,.15-2.12-2.96-5.65-5.93-11.31-8.87-16.97-1.31-2.82-2.14-3.89,1.52-2.24,4.9,2.03,9.67,4.33,14.63,6.19,2.11,.43-.1-2.48-.34-3.3-3.14-6.18-6.16-12.4-8.93-18.7-.14-.47-.8-2.09,.22-1.85,3.99,1.48,7.79,3.37,11.71,5.03,.5M 9,.25,1.2,.5,1.82,.69,.82,.25,1.69,1,2.52,.35,.64-.51-.11-1.2-.35-1.78-3.39-8.28-6.81-16.56-10.21-24.83-.12-.49-.51-1.09-.21-1.54,.51-.55,1.52,.27,2.13,.38,4.24,1.63,8.37,3.55,12.71,4.92,.45,.14,.99-.22,.82-.7-3.41-9.82-7.75-19.44-10.34-29.48,.22-.79,1.51,.02,2.06,.1,3.31,1.2,6.61,2.42,9.92,3.61,.77,.1,2.35,1.11,2.73,.05-2.79-10.53-6.87-20.76-9.09-31.41-.05-.24,.59-.57,.9-.47,4.21,1.44,8.46,2.78,12.69,4.15,.32,.1,.89-.23,.85-.48-.04-.32-.07-.64-.15-.95-1.81-6.9-3.44-13.85-5.02-20.81,4.53-.65,9.06-.98,13.57-1,1.83,8M .96,3.88,17.9,6.36,26.72Z"/><path class="cls-2" d="M433.04,580.87c.05-.01,.11-.02,.16-.04l-.14,.13s-.02-.06-.02-.09Z"/><path class="cls-2" d="M433.98,504.67l-.12,.03s-.02-.07-.03-.11l.15,.08Z"/><path class="cls-2" d="M439.63,542.74l-.07,.08s-.01-.04-.01-.06c.03,0,.05,0,.08-.02Z"/><path class="cls-2" d="M924.94,209.92c-.66-.26-1.33-.14-1.96,.01-2.05,.51-4.11,1.04-6.14,1.6-9.42,2.42-18.74,5.64-28.21,7.65-.51-.12,.43-1.1,.61-1.31,8.89-8.54,17.9-16.98,26.9-25.41,.4-.54,1.58-1.08,1.1-1.81-.55-.27-1.33,.14-1.92,.21-8.96,M 2.34-17.91,4.69-26.87,7.03-1.66,.43-3.33,.86-5.01,1.26-.18,.04-.44-.11-.64-.21,9.93-10.37,21.57-19.8,32.08-29.83,.71-.65,1.37-1.32,2.04-1.99,.28-.36-.36-.54-.6-.56-9.99,2.04-19.98,4.44-29.85,6.9-.64,.07-1.76,.46-2.3,.1,11.4-11.84,24.9-22.62,37.33-33.86,1.02-1.07,2.6-1.8,3.05-3.24-9.74,1.06-19.46,3.63-29.18,5.24-.59,.09-1.27,.34-1.75-.15-.07-.05-.06-.24,0-.31,15.26-14.51,32.61-27.58,47.65-42.05-.05-.13-.39-.29-.58-.27-3.87,.43-7.73,.88-11.6,1.33-5.33,.48-10.64,1.57-15.99,1.58-.02-.24-.15-.52-.03-.64,.75-.76,1.52-1.5M 1,2.34-2.22,17.08-14.73,34.38-29.2,51.75-43.62,3.35-2.79,2.47-2.38,6.96-2.4,6.6-.04,13.21-.07,19.81-.09,.95,.13,2.26-.32,2.91,.52,.05,.07,0,.23-.07,.3-.61,.57-1.22,1.14-1.87,1.68-16.54,13.57-33.11,27.11-49.47,40.88-.67,.61-1.63,1.09-1.6,2.09,7.88-.2,15.99-1.69,23.93-2.33,1.54-.03,3.25-.58,4.72-.28,.06,.08,.08,.25,.01,.31-.57,.59-1.11,1.2-1.75,1.74-8.44,7.12-16.91,14.2-25.32,21.33-5.73,4.86-11.4,9.77-17.09,14.66-.45,.48-1.26,.84-1.06,1.58,.52,.26,1.35,.07,1.95,.02,9.2-1.62,18.4-3.25,27.6-4.88,.51-.09,1.03-.17,1.52,.M 1-.03,.73-.75,1.12-1.28,1.58-5.21,4.51-10.47,8.99-15.65,13.52-6.82,5.96-13.59,11.96-20.38,17.95-.35,.44-1.38,1.02-1.24,1.57,.05,.08,.2,.18,.29,.17,1.05-.15,2.11-.28,3.13-.5,7.93-1.71,15.85-3.45,23.77-5.16,1.69-.36,3.4-.65,5.11-.94,.2-.03,.59,.08,.65,.2,.08,.16-.02,.44-.17,.59-.86,.83-1.76,1.63-2.66,2.43-8.44,7.55-16.89,15.1-25.32,22.65-1.52,1.36-2.98,2.78-4.45,4.18-.29,1.16,2.69-.04,3.3-.08,10.2-2.41,20.4-4.82,30.6-7.23,.41-.16,1.67-.11,1.38,.5-8.15,7.95-16.76,15.45-25.07,23.24-.84,.9-2.61,1.9-2.66,3.07,11.2-1.79,2M 2.39-5.46,33.58-7.9,1.23-.14,2.59-.99,3.78-.49,.05,.02,.03,.23-.04,.3-.63,.69-1.25,1.39-1.94,2.05-6.47,6.21-12.95,12.41-19.42,18.61-.91,.96-2.05,1.66-2.51,2.94,1.41,.24,2.63-.29,3.96-.61,10.98-2.95,22.15-5.39,33.25-8.02,.84-.11,1.84-.58,2.62-.07,.07,.04,.07,.23,0,.3-.39,.44-.79,.87-1.21,1.29-5.92,5.87-11.84,11.74-17.75,17.62-3.15,3.09-1.31,2.42,1.7,1.76,12.9-2.97,25.87-6.17,38.95-8.36,.22-.02,.48,.26,.37,.46-5.3,5.88-10.93,11.47-16.35,17.23-.49,.51-.91,1.06-1.34,1.6-.06,.08-.06,.27,0,.31,.19,.11,.46,.26,.64,.23,3.1M 4-.6,6.27-1.24,9.41-1.84,7.85-1.52,15.7-3.05,23.56-4.52,3.8-.71,7.64-1.3,11.46-1.93,.24-.04,.63,0,.74,.12,.25,.28,.07,.59-.17,.86-4.97,5.64-10.15,11.11-14.99,16.85-.22,.31,.36,.62,.55,.63,11.79-1.64,23.47-3.88,35.31-5.34,4.52-.54,8.99-1.51,13.53-1.78,.12,0,.34,.04,.36,.1,.07,.19,.17,.43,.07,.58-4.07,5.5-8.77,10.54-12.8,16.07-.11,1.21,2.21,.48,2.97,.56,17.07-2.01,34.17-3.83,51.32-5.02,.34-.03,.7,.42,.56,.68-.16,.3-.29,.61-.48,.89-3.7,5.25-7.36,10.52-11.04,15.78l-.04,.03c-18.78,1-37.44,3.36-56.14,5.23-.35,.02-.79-.44M -.64-.67,.45-.66,.87-1.33,1.36-1.97,2.97-3.85,5.96-7.68,8.94-11.53,.34-.67,2.33-2.38,.92-2.65-11.3,1.15-22.55,3-33.76,4.83-5.4,.88-10.81,1.77-16.22,2.64-.18,.03-.44-.14-.63-.26-.07-.04-.06-.23,0-.31,.47-.65,.92-1.31,1.44-1.93,4.02-5.04,8.95-9.74,12.49-15-.19-.11-.45-.26-.64-.23-2.11,.35-4.21,.7-6.3,1.1-7.85,1.5-15.71,2.98-23.54,4.55-4.7,.94-9.35,2.02-14.02,3.03-.77,.17-1.55,.4-2.35,.05-.08-.72,.54-1.19,1.01-1.7,4.28-4.7,8.57-9.39,12.86-14.09,.7-.97,2.14-1.69,1.94-3.02,0,.01,.02,.25,.02,.25l-.02-.18c-13.95,2.71-27.7M 3,6.19-41.51,9.52-.59,.07-1.37,.37-1.92,.09-.06-.07-.07-.22-.01-.29,.49-.63,.94-1.29,1.5-1.88,5.52-5.97,11.56-11.53,16.8-17.74,.06-.78-1.53-.16-1.98-.15-9.43,2.2-18.74,4.7-28.07,7.16-3.44,.91-6.9,1.79-10.35,2.67-1.24-.02,.9-1.81,1.16-2.23,5.82-5.79,11.65-11.57,17.48-17.36,.84-.84,1.66-1.69,2.47-2.55,.06-.07,.05-.27-.01-.3-.19-.11-.45-.26-.63-.23-1.56,.34-3.11,.69-4.64,1.1-7.53,2.01-15.06,4.02-22.58,6.06-3.06,.83-6.08,1.74-9.12,2.61-.5,.14-1.02,.2-1.5-.16,.41-1.04,1.41-1.8,2.25-2.62,5.36-5.26,10.76-10.49,16.16-15.73M ,1.89-1.83,3.81-3.63,5.72-5.44,.35-.33,.68-.67,.61-1.14,.16-.05,.38-.07,.25-.27-.26,0-.31,.12-.16,.32Z"/><path class="cls-2" d="M1007.4,858.16s.02,.09,.03,.13c-.04-.01-.09-.02-.13-.03l.1-.1Z"/><path class="cls-2" d="M1037.31,730.23s-.01,.02-.01,.03l-.09,.03,.1-.06Z"/><path class="cls-2" d="M1042.96,767.69h.02c-.07,.16-.19,.2-.37,.17,.11-.06,.24-.11,.35-.17Z"/><path class="cls-2" d="M1042.91,839.58l-.06-.18c.05,.02,.09,.04,.14,.06l-.08,.12Z"/><path class="cls-2" d="M1089.01,723.41c3.84,2.21,7.73,4.39,11.5,6.67-6.94-M 11.51-15.87-21.24-26.14-28.95-.09,.03-.23,.13-.23,.16,2.81,5.97,6.8,11.42,10.03,17.2,.27,.71,1.28,1.65,.63,2.33-1.42-.34-2.77-1.36-4.12-1.96-6.17-3.28-12.33-6.58-18.78-9.51-4.48-2.21-3.92-1.13-1.64,2.35,2.77,4.55,5.54,9.1,8.29,13.66,3.11,4.91-1.39,1.72-3.58,.75-5.81-2.91-11.74-5.84-17.87-8.17-.31-.12-.94,.15-.67,.52,.87,1.46,1.74,2.91,2.62,4.37,2.84,4.76,5.69,9.51,8.53,14.27,.17,.28,.4,.61,.09,.88-.31,.27-.75,.13-1.09-.02-2.24-.99-4.45-2.03-6.71-2.98-3.69-1.56-7.41-3.08-11.12-4.61-.46-.19-.94-.28-1.45-.11-.23,.68,.M 26,1.21,.59,1.77,3.8,6.2,7.18,12.67,11.24,18.7h.01s.01,.01,.01,.02c-.11,.04-.21,.09-.32,.13,.09-.05,.19-.09,.3-.15-1.24,.61-2.52-.3-3.69-.68-4.01-1.54-8.01-3.09-12.01-4.63-.96-.34-1.92-.82-2.97-.71-.31,.01-.36,.4-.11,.84,3.65,6.7,7.7,13.23,10.97,20.11,.03,.23-.26,.72-.6,.62-4.89-1.43-9.6-3.44-14.48-4.91-.72-.22-1.5-.19-1.51,.04,.46,2.44,2.25,4.56,3.21,6.87,2.4,5.12,5.42,10.03,7.41,15.33,.03,.09-.35,.36-.51,.34-4.9-.96-9.47-3.24-14.39-4.14-1.52,.02,.11,2.01,.27,2.73,3.52,8.01,7.25,15.97,10.02,24.19-.35,.75-1.45,.23-M 2.06,.12-2.89-.88-5.77-1.79-8.67-2.66-.82-.07-3.77-1.51-3.76-.14,2.79,8.55,6.27,16.91,9.28,25.4,.39,1.03,.68,2.08,1,3.12,.08,.29-.41,.61-.79,.52-3.97-1-7.91-2.11-11.87-3.15-.54-.14-1.05-.08-1.48,.39,2.95,10.24,6.8,20.31,8.94,30.73-.22,.56-1.22,.44-1.72,.33-4.07-1.02-8.12-2.07-12.18-3.1,2.3,9.15,4.43,18.33,6.38,27.56,4.51-.04,9.05-.39,13.57-1.06-1.51-7.24-3.4-14.43-5.25-21.61-.17-.71,.53-.92,1.24-.69,3.36,1.08,6.73,2.17,10.06,3.31,.95,.23,1.77,1.01,2.93,.54,.45-.74,.11-1.48-.09-2.19-2.55-9.88-6.09-19.6-8.77-29.44,.1M 9-.83,1.39-.41,1.98-.25,4.5,1.54,8.97,3.16,13.37,4.94-3.4-10.33-7.46-20.51-10.86-30.81,0-.08,.17-.24,.24-.23,.52,.06,1.09,.07,1.55,.25,3.74,1.47,7.47,2.98,11.2,4.46,.6,.1,2.6,1.31,2.75,.45-2.99-9.39-7.53-18.36-11.04-27.61-.13-.46,.51-.81,.91-.67,4.45,1.43,8.61,3.49,12.88,5.35,.91,.27,1.82,1.19,2.8,.78,.43-.29-.03-1.12-.13-1.52-3.25-7.45-6.97-14.69-10.54-21.99h-.09c.14-.08,.29-.14,.44-.17,.01,0,.01-.01,.02-.01h0c.48-.11,.97-.01,1.43,.17,4.9,1.97,9.75,4.02,14.52,6.27,.69,.25,1.39,.83,2.12,.37,.07-.03,.12-.19,.09-.26-M 3.09-6.69-6.63-13.14-10.08-19.65-.23-.55-1.16-1.69-.49-2.08,.25,.01,.54-.03,.73,.06,6.31,3.01,13.09,5.4,18.81,9.23,0-.01,.01-.01,.01-.02t.01-.02s.07-.08,.1-.11c.91-1.37-.82-3.01-1.29-4.33-2.88-5.21-5.77-10.42-8.65-15.62-1.4-2.41-.37-2.05,1.55-1.21,6.83,3.28,13.48,7.32,20.4,10.21,.56-.81-.51-1.87-.8-2.69-2.98-5.29-5.97-10.58-8.95-15.87-1.21-2.01-1.44-3.02,1.19-1.58,8.02,4.16,15.83,8.52,23.61,12.97,.68-.73-.17-1.53-.55-2.44-2.69-4.93-5.39-9.85-8.09-14.77-.33-.59-.74-1.15-.98-1.76-.23-.57-.98-1.08-.4-1.77,.74-.08,1.22M ,.33,1.74,.63Zm298.37,128.8c-23.6-23.37-47.92-46.03-73.02-67.82-.39-.3-1.16-.98-1.53-.32,.31,6.13,1.75,12.21,1.85,18.31-.55,.79-1.55-.54-2.07-.86-6.95-6.16-13.87-12.34-20.84-18.49-13.46-11.36-26.9-23.81-41.27-33.99-.14,.03-.29,.35-.26,.51,1.28,5.61,2.72,11.18,3.8,16.83-.16,1.55-3.08-1.47-3.7-1.82-12.51-10.42-25.32-20.59-38.42-30.53-18.74-13.87-14.13-12.96-8.32,7.06,.04,.12-.16,.32-.3,.45-.04,.04-.28,0-.37-.06-1.12-.78-2.25-1.54-3.32-2.35-14.22-10.58-28.57-21.78-43.81-31.03-.6,.5-.03,1.15,.14,1.74,1.82,4.39,3.64,8.7M 8,5.47,13.18,.17,.4,.33,.79-.04,1.2-1.35-.32-2.21-1.19-3.22-1.88-7.74-5.33-15.46-10.73-23.46-15.79,4.46,7.12,8.46,14.92,11.64,22.81h.01c7.4,5.13,14.68,10.38,21.86,15.71,1,.54,1.86,1.94,3.1,1.65,.08-.01,.16-.2,.13-.28-1.07-2.66-2.12-5.33-3.25-7.98-1.51-3.99-3.85-7.76-4.89-11.89,.67-.52,1.45,.4,1.91,.71,14.76,10.58,29.01,21.57,42.88,32.89,.34,.25,1.17,1.09,1.51,.39-.63-4.29-2.54-8.35-3.69-12.53-.44-1.88-2.63-6.21,1.18-3.09,16.61,12.75,32.53,26.3,48.25,40.02,1.06,.72,1.92,2.13,3.27,2.21,.31-.37,.07-1.09,.04-1.55-1.17-M 5.19-2.45-10.36-3.59-15.56-.21-.96,.62-.82,1.09-.56,2.42,2.03,4.85,4.04,7.21,6.11,18.11,15.66,35.91,31.77,53.19,48.24,.2,.08,.88,.14,.86-.28-.25-6.13-1.75-12.21-1.8-18.31,.07-.12,.54-.22,.67-.15,.76,.61,1.55,1.2,2.24,1.85,7.09,6.64,14.19,13.27,21.24,19.93,16.23,15.05,31.23,31.23,47.04,46.41,.08,.03,.33-.06,.35-.13,.13-.39,.3-.8,.3-1.2-.02-6.59,.12-13.17-.06-19.76Z"/><path class="cls-2" d="M1026.28,545.01c-.04,.07-.22,.12-.34,.14-1.32-.1-2.63-.46-3.94-.69-13.43-2.49-27.12-5.36-40.77-6.2-1.62,.55,6.76,8.98,7.37,10.67M ,.16,.29-.41,.65-.59,.66-8.92-1.07-17.81-2.37-26.79-3.03-3.6-.09-7.27-.79-10.85-.51-.86,.53,.38,1.34,.72,1.88,2.27,2.41,4.56,4.8,6.81,7.22,.18,.24,.58,.91,.26,1.13-.25,.08-.52,.16-.78,.15-10.35-.67-20.67-1.48-31.06-1.4-2.35,.04-.09,1.66,.6,2.43,2.36,2.21,4.76,4.39,7.12,6.61,.12,.17,.04,.72-.33,.72-8.2,.15-16.43-.18-24.64,.32-1.02,.12-2.21,.04-3.14,.39-.02,.2-.08,.48,.05,.6,2.9,2.58,6.06,4.92,9.05,7.38,.22,.19,.2,.56,.32,.94-8.03,.63-15.9,.66-23.81,1.84-1.26,.69,1.35,1.81,1.82,2.34,2.3,1.67,4.6,3.33,6.89,4.99,.4,.29M ,.81,.59,.81,1.09-.58,.51-1.41,.52-2.2,.6-2.41,.26-4.82,.45-7.21,.75-3.46,.44-6.9,.96-10.35,1.46-.39,.05-.85,.2-.84,.55,0,.28,.22,.62,.48,.8,1.75,1.19,3.55,2.32,5.3,3.5,1.44,.97,2.85,1.97,4.22,3.01,.21,.15,.12,.56,.17,.9-6.02,.99-11.97,1.9-17.64,3.54-.06,.57,.3,.86,.72,1.13,3.17,2.18,7.56,4.2,10.29,6.69,.1,.45-.34,.55-.67,.64-4.74,1.19-9.41,2.57-14.1,3.92-.52,.15-.59,.77-.12,1.06,2.77,1.72,5.55,3.41,8.31,5.14,.95,.59,1.85,1.24,2.74,1.89,.11,.09,.07,.42-.05,.55-4.06,1.65-8.38,2.9-12.39,4.67-.65,.27-1.3,.35-1.91,0-3.M 86-2.15-7.72-4.32-11.58-6.49-1.21-1.01,1.05-1.52,1.72-1.9,3.58-1.48,7.29-2.72,10.82-4.32,.17-.08,.18-.35,.29-.59-3.66-2.48-7.83-4.46-11.86-6.87,5.26-2.6,10.44-3.59,15.99-5.26-.16-.34-.19-.73-.44-.9-1.24-.83-2.53-1.61-3.82-2.38-2.05-1.23-4.13-2.43-6.16-3.67-.22-.15-.2-.55-.31-.9,5.93-1.69,11.91-2.97,17.82-4.28,.12-.56-.2-.87-.63-1.14-2.11-1.35-4.22-2.69-6.32-4.04-.95-.6-1.89-1.22-2.82-1.83-.39-.26-.58-.71-.37-.85,6.56-2.11,13.85-2.51,20.7-3.71,.4-.87-.57-1.2-1.3-1.83-2.55-1.76-5.11-3.51-7.67-5.26-.41-.29-.76-.61-.69M -1.17,7.92-1.98,16.62-1.44,24.5-3.04,.08-.17,.03-.46-.11-.59-.81-.72-1.66-1.41-2.52-2.09-2.09-1.68-4.19-3.35-6.26-5.05-.22-.18-.19-.55-.32-.95,9.48-1.05,18.83-1.18,28.33-1.48,1.08-.44-.25-1.34-.66-1.79-10.45-9.55-10.97-7.65,3.24-8.1,6.87,.17,13.74,.31,20.61,.47,.55-.06,1.51,.21,1.76-.39-.09-1.12-1.57-2.02-2.24-2.94-1.94-2.19-4.27-4.12-6-6.47-.12-.5,.58-.72,1.02-.66,2.82,.08,5.66,.11,8.48,.27,9.94,.33,19.82,1.69,29.73,2.18,.12-.01,.36-.37,.3-.48-2.14-3.42-5.04-6.35-7.49-9.56-.3-.38-.51-.75-.23-1.2,15.32,.63,30.56,3.M 48,45.76,5.5,0,.01,.01,.01,.01,.01,.72,.36,1.43,.72,2.15,1.09-.05,.48,.27,.88,.54,1.29,2.22,3.44,4.45,6.88,6.65,10.34,.09,.13-.06,.37-.15,.55Z"/><path class="cls-2" d="M1117.4,514.89c.02,.06,.04,.11,.06,.17-.05-.01-.11-.03-.16-.04l.1-.13Z"/><path class="cls-2" d="M1190.2,521.41v.1s-.09-.03-.14-.05l.14-.05Z"/><path class="cls-2" d="M1387.31,603.78c0,1.07-.03,2.15-.04,3.29-1.29,.43-2.18-.35-3.26-.87-26.06-13.81-52.7-26.87-79.85-39.26-6.66-3.04-13.39-6-20.09-9-.69-.3-1.37-.67-2.22-.5-.39,.89-.09,1.75,.02,2.59,.65,4.71M ,1.32,9.42,1.97,14.13,.14,.9,.31,2.57-1.14,2.06-13.21-5.82-26.24-11.91-39.63-17.46-15.01-6.33-30.29-12.24-45.65-18-.71-.21-2.02-.95-2.37-.02,.78,4.93,2.52,9.68,3.68,14.54,.1,.71,.54,1.55-.11,2.1-9.38-3-18.43-7.11-27.82-10.3-14.36-5.19-28.9-10.02-43.6-14.57-.94-.15-2.08-.93-2.97-.39-.14,.13-.22,.4-.16,.57,.29,.83,.63,1.65,.95,2.47,1.36,3.92,3.37,7.71,4.34,11.74,0,.12-.38,.38-.53,.36-4.32-.93-8.45-2.6-12.69-3.83h-.01c-11.5-8.26-23.39-16.17-35.67-23.71,14.15,3.33,28.16,7.29,42.07,11.31,.53-.44,.52-.86,.37-1.28-1.86-4.M 88-3.68-9.77-5.44-14.69,26.05,6.72,51.09,15.76,76.46,24.08,.47-.63,.26-1.27,.1-1.89-1.19-5.25-3.18-10.41-3.82-15.74,30.4,10.41,60.23,21.97,89.71,34.57,.79,.3,1.53,.1,1.38-.87-.6-4.6-1.22-9.2-1.83-13.81-.18-1.37-.52-2.75-.16-4.15,35.67,13.34,70.11,30.06,104.3,46.66,4.32,2.16,3.66,1.4,3.7,5.33,.04,4.85,.02,9.69,.01,14.54Z"/><path class="cls-2" d="M1087.4,573.83c-16.4-5.16-32.98-10.58-49.81-14.22-.85,.24-.2,1.1,.05,1.61,2.27,3.63,4.88,7.13,6.94,10.87-.57,.4-1.07,.37-1.6,.23-4.22-1.1-8.45-2.19-12.67-3.3-8.83-2.33-17.84M -4.16-26.83-6-.94-.06-2.16-.63-2.97,.03,1.95,3.4,5.17,6.56,7.51,9.88,.32,.42,1.01,.91,.46,1.39-.47,.42-1.28,.15-1.92,.02-1.31-.25-2.6-.55-3.91-.82-10.37-1.94-21-4.35-31.51-5.2-.18,.71,.28,1.21,.77,1.67,2.16,2.34,4.33,4.67,6.49,7.02,.42,.64,1.7,1.36,1.25,2.17-5.7-.3-11.67-1.6-17.46-2.16-4.72-.45-9.65-1.5-14.31-1.1-.05,.2-.13,.46-.01,.6,2.68,2.86,5.63,5.5,8.41,8.26,.34,.34,.64,.69,.35,1.22-8.83-.53-17.64-1.48-26.52-1.69-.21-.01-.53,.11-.64,.25-.1,.15-.11,.44,.01,.58,2.24,2.34,4.92,4.29,7.31,6.47,.72,.63,1.41,1.3,2.06M ,1.98,.12,.12,.02,.39-.04,.58-7.48,.5-15.32-.66-22.89,.03-.28,.02-.52,.64-.31,.81,.84,.7,1.68,1.4,2.52,2.09,2.36,1.92,4.73,3.84,7.07,5.78,.15,.13,.24,.42,.17,.58-.07,.16-.35,.33-.58,.38-1.85,.3-3.78,.22-5.64,.29-4.56,.16-9.19,.2-13.67,.93-.21,.88,.85,1.23,1.38,1.77,2.84,2.14,5.69,4.28,8.54,6.42,.39,.3,.78,.6,.66,1.17-5.54,.87-11.43,1.21-16.97,2.17-.27,.58-.04,.92,.39,1.23,2.87,2.12,5.74,4.25,8.6,6.37,2.19,1.53,2.86,2.19-.37,2.63-4.01,.87-8.17,1.3-12.09,2.53-1.16,.67,.67,1.42,1.13,1.92,3.23,2.45,6.62,4.71,9.72,7.31,M .23,.2,.23,.57,.32,.83-3.97,1.27-7.84,2.35-11.71,3.72-2.04,.93,.91,2.06,1.58,2.83,3.65,2.96,7.52,5.77,11.04,8.88-.22,.55-.63,.78-1.14,.95-3.08,1.07-6.22,2.01-9.23,3.28-.95,.39-1.13,.95-.46,1.51,1.1,.94,2.24,1.87,3.36,2.8,2.88,2.42,5.76,4.83,8.65,7.25,.38,.32,.62,.68,.48,1.1-3.22,1.4-6.41,2.79-9.6,4.17-.65,.28-1.25,.2-1.83-.25-3.85-3.02-7.69-6.04-11.54-9.05-.48-.37-1.05-.7-1.05-1.39,2.91-1.98,6.46-3.4,9.56-5.26,.6-.61-.45-1.14-.86-1.55-3.55-2.63-7.13-5.26-10.69-7.89-.49-.36-1.09-.65-1.34-1.31,2.49-1.97,6.12-3.01,9.0M 1-4.53,2.34-1.05,2.38-1.1,.27-2.62-3.53-2.71-7.58-4.77-10.82-7.82,4.21-1.96,8.79-2.94,12.98-4.49,.16-.56-.17-.89-.59-1.17-3.18-2.17-6.37-4.33-9.54-6.5-.61-.47-1.32-.7-1.4-1.55,4.83-1.62,9.91-2.63,14.96-3.64-.02-.29,.07-.56-.06-.68-2.91-2.46-6.31-4.37-9.41-6.59-.85-.52-2.32-1.54-.58-2.01,3.02-.52,6.06-1.02,9.1-1.48,2.25-.34,4.51-.6,6.76-.92,1.71-.53-.09-1.5-.83-2.08-2.32-1.64-4.65-3.27-6.98-4.91-.78-.67-2.1-.96-1.94-2.2,5.4-.8,10.74-1.34,16.14-1.55,1.95-.26,6.23,.37,2.68-2.23-2.71-2.33-6.16-4.22-8.46-6.84,.11-.17,.2M 8-.44,.45-.45,4.83-.38,9.66-.72,14.52-.73,2.82-.01,5.65-.06,8.48-.1,.31,0,.48-.16,.48-.42-.42-1.6-11.18-8.15-9.44-9.04,6.42-.33,12.93-.12,19.36,.28,2.54,.21,5.11,.19,7.66,.26,.34,0,.51-.14,.51-.41-2.34-3.18-5.92-5.85-8.74-8.78-.11-.31,.01-.72,.47-.7,10.48-.07,20.92,1.44,31.33,2.43,.5,.04,.89-.43,.53-.85-2.53-2.81-5.09-5.59-7.75-8.28-1.68-1.36-.35-1.94,1.23-1.59,12.01,1.19,23.92,2.97,35.81,4.98,1.3-.12-.49-1.8-.78-2.3-2.11-2.63-4.23-5.25-6.33-7.88-.31-.47-1.04-1.29-.24-1.61,13.71,1.99,27.36,4.75,40.8,7.91,1.25,.14,2M .63,.94,3.83,.39,.06-.66-.75-1.42-1.03-2.05-1.92-2.97-3.86-5.92-5.77-8.89-.21-.51-.94-1.36-.09-1.61,8.16,1.28,16.17,3.54,24.18,5.45h.01c11.93,7.13,23.48,14.61,34.62,22.43Z"/><path class="cls-2" d="M1387.33,649.99c.06,2.55-1.13,1.6-2.75,.74-25.67-15.4-51.89-30-78.57-43.8-6.05-2.95-11.91-6.47-18.15-9.01-1.31,.18-.38,3.22-.33,4.16,.64,4.39,1.29,8.77,1.92,13.16,.04,.56,.2,1.58-.63,1.53-26.84-13.65-54.07-27.43-82.07-39.4-2-.76-2.34-.46-1.71,1.87,1.19,4.76,2.84,9.41,3.74,14.22-.31,1.24-2.16-.15-2.93-.34-18.33-8.48-37.06-M 16.35-56.14-23.69-5.36-4.49-10.85-8.89-16.43-13.23-.85-2.47-2.25-4.84-2.77-7.39,.27-.85,1.76-.07,2.37,.02,23.27,7.94,46.32,16.73,68.87,26.33,2.31,.89,2.22,.54,1.79-1.78-1.13-4.21-2.3-8.41-3.43-12.62-.2-.72-.53-1.46-.01-2.19,25.84,9.55,51.26,21.49,76.06,33.36,3.11,1.51,6.26,2.97,9.39,4.44,.26,.13,.9-.17,.93-.39-.05-5.67-1.43-11.36-2.03-17.02-.06-.72-.14-1.56,.95-1.31,34.61,16.21,68.74,33.49,101.77,52.6,.38,6.57,.05,13.16,.16,19.74Z"/><path class="cls-2" d="M236.98,168.26c.96-.1,1.86,.03,2.74,.37,3.64,1.38,7.29,2.75,M 10.95,4.1,3.63,1.16,7.03,2.97,10.81,3.57,1.72-10.71,1.56-21.72,2.69-32.54,.72-8.14,1.57-16.28,2.28-24.43,.05-.53,.11-1.07-.37-1.53l-.05,.02c.89-.36,1.8-.32,2.74-.14,7.88,1.32,15.65,3.34,23.59,4.2l-.09-.08c-2.76,20.32-4.83,40.72-6.47,61.16-.11,2.65-1.77,1.48-3.49,1.05-4.68-1.65-9.35-3.33-14.03-4.98-2.13-.58-4.15-1.81-6.39-1.74-1.48,17.84-1.41,35.8-2.17,53.68-.9,1.26-6.12-2.42-7.55-2.88-4.19-2.16-8.37-4.33-12.56-6.49-.99-.39-1.86-1.17-2.99-.76-.16,14.83,.1,29.71,.65,44.54,.02,1.22,.42,3.95-1.73,2.47-6.88-4.49-13.66-9M .13-20.58-13.57-.44-.37-.97,.03-1.11,.45,.18,13.76,1.73,27.52,2.44,41.27-1.1,.48-1.82-.56-2.68-1.08-6.27-4.89-12.53-9.79-18.8-14.68-4.06-3.61-2.66,.59-2.64,3.36,.74,7.84,1.49,15.68,2.26,23.52,.27,2.9,.73,5.78,.78,8.69-.44,1.25-2.27-.94-2.87-1.3-6.58-5.85-13.15-11.7-19.73-17.55-.72-.64-1.48-1.24-2.27-1.82-.12-.09-.47,.03-.78,.06,.34,8.68,1.89,17.38,2.78,26.04,.28,2.36,.57,4.72,.82,7.08-.06,.19-.53,.58-.82,.36-.65-.54-1.32-1.07-1.9-1.65-7.21-7.11-14.4-14.24-21.62-21.35-.84-.83-1.77-1.6-2.68-2.39-.06-.05-.25-.02-.38,0M -.11,.02-.29,.08-.3,.12-.03,.43-.08,.86-.03,1.28,.76,6.43,1.52,12.87,2.3,19.3,.34,2.79,.73,5.57,1.1,8.35,.11,.82,.02,1.09-.36,1.08-.63-.02-.92-.39-1.23-.72-8.69-9.2-17.38-18.4-26.07-27.59-.56-.59-1.22-1.13-1.86-1.68-.12-.07-.59,.04-.63,.19,.08,5.59,1.09,11.16,1.56,16.74,.33,3,.69,6.01,1.04,9.01,.14,1.11-1.01,.85-1.36,.29-4.3-4.83-8.6-9.65-12.89-14.48-5.46-6.15-10.9-12.31-16.36-18.45-.94-.88-2.98-3.72-2.81-.62,.39,5.16,.82,10.32,1.21,15.48-.09,1.17,1.08,7.69-.76,6.2-11.76-13.33-23.09-27.05-34.67-40.53-1.25-1.21-.94-M 2.82-1.05-4.35-.02-5.39-.03-10.77-.04-16.16,.04-.64-.08-1.41,.62-1.75,.05-.04,.29,.03,.36,.1,11.51,12.07,21.88,25.22,33.44,37.23,.12,.08,.57-.03,.61-.2,.01-4.2-.42-8.39-.68-12.58-.2-3.44-.64-6.88-.63-10.33,.18-.6,.73-.85,1.35-.21,10.02,10.51,19.59,21.45,29.79,31.79,.55,.21,.8-.25,.76-.76-.47-5.05-.96-10.09-1.43-15.14-.29-3.11-.57-6.23-.84-9.35-.04-.43-.08-.86-.04-1.29,.07-.42,.7-.87,1.07-.43,8.37,8.12,16.5,16.49,24.79,24.7,1.06,.82,1.8,2.34,3.26,2.32-.76-10.3-2.17-20.6-2.96-30.88,1.15-.37,1.79,.65,2.61,1.24,3.89,3.M 58,7.76,7.17,11.64,10.75,3.62,3.34,7.23,6.68,10.86,10.01,.39,.26,1.1,1.07,1.57,.76,.15-.16,.34-.35,.32-.53-.12-1.72-.27-3.44-.44-5.16-.85-9.56-2.1-19.1-2.38-28.68,.17-.92,1.36-.17,1.78,.19,7.59,5.94,14.82,12.31,22.54,18.08,1.01,.21,.87-.69,.89-1.39-.33-6.89-.99-13.76-1.44-20.65-.31-5.27-.6-10.54-.9-15.82-.02-.43,0-.86,.11-1.28,.24-.3,1.04-.25,1.37,.04,6.82,4.55,13.54,9.22,20.33,13.81,1.72,1.14,2.79,1.9,2.63-.93-.42-13.89-1.16-27.78-1.14-41.68,0-.3,0-.71,.49-.76,.36-.04,.81,.02,1.11,.18,3.39,1.76,6.75,3.56,10.12,5.3M 4,3.6,1.9,7.19,3.8,10.79,5.7,.5,.26,.98,.27,1.54-.08,.25-15.69,.18-31.42,.94-47.11-.05-1.27,.36-2.67-.37-3.79h0Z"/><path class="cls-2" d="M1148.11,1317.93c.52-.78,.61-1.64,.71-2.5,.76-6.65,1.58-13.29,2.29-19.95,1.29-12.66,2.62-25.32,3.6-38.01,.2-.88,.04-2.44,1.36-2.31,5.52,1.61,10.85,3.8,16.29,5.65,1.48,.52,2.97,1.02,4.46,1.51,1.61,.52,1.97,.36,2.05-.89,.34-5.06,.63-10.11,.75-15.18,.6-11.19,.77-22.39,1-33.59,.03-1.18,.13-2.36,.2-3.54,.28-.8,1.44-.39,2-.15,6.17,3.06,12.24,6.28,18.36,9.42,.75,.24,2.15,1.41,2.7,.46,.4M 2-13.11,0-26.28-.43-39.4-.11-2.37-.15-4.74-.19-7.11,0-.18,.17-.37,.27-.56,.11-.2,.71-.16,1.11,.08,6.64,4.18,13.08,8.66,19.63,12.97,.68,.28,1.59,1.36,2.3,.7,.4-6.31-.61-12.69-.77-19.02-.34-7.53-1.1-15.05-1.41-22.57,.91-.31,1.59,.5,2.29,.95,7.08,5.44,14.01,11.09,21.17,16.42,.19,.08,.91,.15,.92-.26-.23-3.11-.42-6.23-.71-9.34-.84-8.91-1.81-17.82-2.7-26.73,.01-.38-.14-.96,.26-1.15,.12-.04,.32-.08,.39-.03,.61,.42,1.24,.81,1.78,1.29,7.42,6.54,14.72,13.2,22.21,19.67,1.5,.86,.97-1.93,.94-2.7-.33-3.22-.68-6.44-1.04-9.66-.71-M 6.33-1.48-12.65-2.23-18.98,0-.71-.42-1.66,.42-2.04,.05-.04,.26,0,.32,.06,8.16,7.68,15.95,15.74,23.98,23.56,.82,.62,1.42,1.89,2.57,1.79,.06,0,.18-.15,.18-.23-.05-1.07-.06-2.15-.18-3.21-.79-7.08-1.74-14.15-2.62-21.22,.05-2.09-1.68-7.79,1.79-3.9,9.11,9.46,17.86,19.27,27.18,28.52,.11,.07,.59-.08,.61-.25-.05-1.5-.04-3.01-.19-4.5-.7-7.08-1.54-14.16-2.24-21.24,0-.24,.43-.68,.71-.57,10.15,10.59,19.51,21.96,29.39,32.83,.7,.79,1.46,1.54,2.23,2.28,.1,.1,.46,.05,.7,.02,.07,0,.17-.16,.18-.25,.01-6.56-.89-13.11-1.23-19.67,.04-.9M 5-.33-2.37,0-3.17,.25,0,.62-.04,.74,.07,11.57,13.02,22.62,26.52,34.02,39.7,.69,.81,1.37,1.6,1.37,2.63-.03,6.57-.06,13.14-.09,19.7-.16,2.41-7.18-6.95-7.99-7.51-7.77-8.8-15.54-17.6-23.32-26.39-.7-.79-1.47-1.54-2.22-2.29-.12-.07-.59,.06-.64,.19-.12,6.86,.78,13.76,1.02,20.63,.28,4.19-.83,2.61-2.9,.5-8.6-9.25-17.19-18.5-25.79-27.75-.64-.69-1.33-1.35-1.99-2.03-.2-.21-.45-.3-.7-.12-.55,.44-.29,1.21-.29,1.82,.77,8.37,1.55,16.74,2.28,25.11-1,.34-1.53-.51-2.19-1.06-8.72-8.62-17.23-17.45-26.05-25.96-.39-.26-1.02-.13-1.03,.41,M .89,9.77,2,19.53,2.79,29.31,0,.3-.25,1.04-.68,.96-1.31-.63-2.26-1.85-3.37-2.75-6.35-5.86-12.69-11.74-19.04-17.6-.88-.81-1.84-1.57-2.77-2.34-.24-.23-.82,.15-.86,.31,.21,7.11,1.12,14.18,1.72,21.26,.33,3.98,.71,7.95,.92,11.93,0,2.45-2.15,.15-2.95-.45-6.14-4.99-12.28-9.99-18.43-14.97-.94-.76-1.93-1.49-2.94-2.2-.18-.08-.88-.09-.89,.3,.23,9.59,1.42,19.13,1.75,28.71,.01,3.32,.73,6.69,.41,9.99-.39,.48-1.28,.1-1.7-.2-6.78-4.61-13.54-9.22-20.33-13.81-.53-.26-1.04-.85-1.67-.74-.32,.03-.47,.17-.49,.43-.16,3.86,.13,7.75,.25,11.M 62,.42,10.65,.92,21.32,.63,31.97-.27,.74-1.5,.16-2.01-.12-6.51-3.45-13.02-6.9-19.54-10.35-2.6-1.45-2.39-.26-2.45,2.03-.25,16.26,.01,32.54-1.08,48.78l.14-.06c-7.8-2.53-15.31-5.85-23.15-8.31-.49-.17-1.14,.17-1.17,.59-1.36,19.43-2.9,38.84-4.92,58.22l.12-.11c-8.74-.93-17.25-3.52-26-4.44l.08,.07Z"/><path class="cls-2" d="M918.38,945.35c-.01,.38-.01,.76,0,1.14-4.47,1.48-8.98,2.91-13.52,4.29,.3-6.18,.58-12.34,.51-18.53-.4-1.32-1.52-.24-2.16,.41-3.22,3.19-6.42,6.4-9.74,9.48-.07,.07-.27,.14-.34,.11-.97-.24-.53-1.82-.66-2.61M ,.01-7.22,.36-14.44,.12-21.65-.02-.48,.31-1.22-.58-1.34-.72-.1-1.02,.58-1.4,.99-2.68,2.97-5.34,5.95-8.03,8.92-.65,.58-1.11,1.44-2.14,1.15-.15-6.34-.21-12.7-.35-19.05-.02-.96,.09-1.94-.43-2.85-.52-.74-1.51,.73-1.92,1.08-2.48,2.95-4.92,5.92-7.39,8.88-.54,.42-1.13,1.76-1.91,1.35-.09-.06-.21-.15-.21-.23-.07-1.07-.18-2.14-.17-3.21,.08-5.07-.65-10.11-.84-15.17,0-.4-.67-.9-1.02-.6-2.93,3.43-5.49,7.15-8.26,10.71-.54,.56-.88,1.54-1.81,1.46-.1,0-.28-.12-.3-.2-.12-.52-.27-1.05-.29-1.58-.16-4.85-.46-9.69-1.05-14.52-.02-.18-.22M -.35-.34-.52-.13-.18-.7,.06-.97,.42-2.79,3.81-5.53,7.64-8.34,11.45-.28,.28-.98,1.12-1.43,.84-2.9-17.89,.84-19.73-10.9-3.32-1.8,2.47-2.39,3.16-2.94-.44-.48-1.33-.69-11.44-2.45-10.17-3.16,4.1-6.05,8.4-9.09,12.58-.33,.46-.63,.96-1.34,1.14-.57-.37-.69-.9-.78-1.44-.64-3.35-.9-6.71-2.05-9.96-1.62,.56-2.07,2.16-3.12,3.34-2.66,3.49-5.33,6.99-8.01,10.47-.31,.3-.71,.83-1.21,.72-1.45-2.8-1.46-6.6-3.08-9.56-.87-.47-1.58,.96-2.14,1.44-4,5.02-7.77,10.18-12.29,14.78-.95,.46-1.2-.82-1.4-1.49-.65-2.2-1.27-4.4-1.93-6.6-.05-.18-.31-.M 32-.49-.46-.22-.19-.68-.06-1.01,.28-.83,.84-1.55,1.75-2.35,2.63-3.43,3.87-6.85,7.74-10.3,11.6-.7,.65-1.24,1.65-2.33,1.64-1.26-2.7-1.38-5.66-2.72-8.3-.8,.05-1.15,.36-1.46,.71-4.01,4.47-8.51,8.63-12.89,12.86-.84,.76-2.93,3.36-3.46,1.24-.58-2.21-1.23-4.42-1.93-6.59-1.02-1.35-2.53,1.19-3.43,1.75-4.9,4.39-9.52,9.26-15.04,13.05-.21,.08-.81-.06-.97-.32-1.55-2.5-3.1-5-4.66-7.52,5.34-4.77,10.99-9.18,15.94-14.2,.75-.62,1.37-1.52,2.46-1.55,2.12,2.13,3.38,4.84,5.26,7.11,1.08-.25,1.48-.84,1.97-1.32,4.55-4.41,9-8.87,13.18-13.5,.M 39-.43,.73-.9,1.61-.88,1.59,2.23,1.86,4.94,3.22,7.22,.77,.52,1.51-.62,2.02-1.05,4.22-4.85,8.35-9.79,12.61-14.62,1.64-1.4,3.18,6.92,4.33,7.94,.84-.16,1.18-.62,1.56-1.07,3.75-4.34,7.11-8.89,10.53-13.4,.7-.68,1.08-2.03,2.19-2.04,.09,0,.25,.11,.29,.2,1.32,2.66,2.15,5.53,3.3,8.28,.02,.06,.55,.11,.64,.02,4-4.46,6.92-9.76,10.67-14.44,.14-.17,.66-.15,1.12-.24,1.01,3.32,2,6.55,2.98,9.76,1.16,.16,1.53-.89,2.19-1.68,2.4-3.62,4.77-7.24,7.14-10.87,.37-.57,.65-1.18,1.35-1.57,.58,.14,.8,.52,.9,.93,.95,3.47,1.55,7.02,2.85,10.39,.0M 2,.05,.2,.09,.3,.09,.78-.17,1.33-1.41,1.85-2.01,2.17-3.34,4.31-6.7,6.47-10.05,.49-.59,.75-1.61,1.69-1.51,.1,0,.26,.12,.29,.2,1.24,3.69,1.52,7.65,2.38,11.46,.13,.36,.19,1.01,.64,1.1,.24-.01,.58-.02,.68-.13,2.95-3.94,5.43-8.18,8.2-12.24,.24-.26,.79-.83,1.19-.58,1.53,4.65,1.21,9.88,2.59,14.63,.12,.31,.81,.23,.96,.1,.64-.82,1.25-1.65,1.83-2.5,2.13-3.12,4.25-6.25,6.37-9.37,.3-.43,.71-.6,1.39-.35,.86,5.41,1.81,10.86,2.06,16.33,0,.31,.52,.74,.72,.64,.22-.11,.47-.21,.63-.36,2-2.39,3.73-5,5.62-7.48,.95-1.3,1.88-2.61,2.88-3.M 89,.15-.19,.67-.19,1.12-.31,1.03,6.52,1.26,12.89,2.02,19.41,0,.14,.35,.27,.56,.37,.56-.06,.98-.73,1.37-1.1,2.64-3.25,5.22-6.54,7.85-9.79,.77-.87,1.2-.43,1.42,.35,3.37,24.36-3.23,28.18,11.55,11.78,.43-.41,1.2-1.22,1.8-.72,.95,7.9,.99,15.92,1.03,23.88,.11,.72-.28,2.38,.95,1.97,3.66-3.07,6.89-6.62,10.37-9.89,.37-.36,.8-.55,1.48-.23,.41,8.67,.4,17.41,.17,26.1Z"/><path class="cls-2" d="M932.16,941.31v.45c-2.31,.83-4.62,1.64-6.95,2.44,1.93-1.59,3.82-3.2,5.84-4.69,1.15-.64,1.08,1.08,1.11,1.8Z"/><path class="cls-2" d="M945M .03,1096.09s.1-.04,.15-.05c-.02,.06-.03,.12-.04,.18l-.11-.13Z"/><path class="cls-2" d="M977.4,1211.24s0-.05,.02-.08h.06l-.08,.08Z"/><path class="cls-2" d="M993.69,1141.18c-4.01,23.57-10.58,46.75-16.27,69.98-7.64,.76-15.24,2.51-22.81,3.7-.69-.54-.49-1.17-.32-1.88,1.47-4.92,3.03-9.81,4.43-14.74,4.95-17.16,9.26-34.46,13.61-51.77,.11-.75,.42-1.79-.74-1.79-5.28,1.14-10.47,2.75-15.72,4.07-1.33,.19-4.94,2.14-4.32-.54,1.42-6.02,3-12.01,4.49-18.03,3.18-13.39,6.4-26.81,8.64-40.37,.03-.27-.54-.56-.88-.45-6.24,2.14-12.41,4.45-M 18.62,6.68,3.39-17.25,7.21-34.46,9.52-51.89-.35-1.16-1.88-.03-2.61,.17-3.94,1.88-7.86,3.77-11.79,5.65-.82,.2-2.9,1.88-3.29,.6,2.36-14.6,4.63-29.24,6.18-43.97-.37-1.28-2.07,.17-2.77,.47-4.39,2.46-8.51,5.4-13.06,7.54-.3,.12-.6-.06-.57-.31,1.4-9.31,2.38-18.65,3.26-28.01,5.18-1.68,10.31-3.44,15.41-5.26-.49,5.79-.83,11.59-1.28,17.38-.1,2.01-.92,4.07-.51,6.08,.59,.21,1.07,.03,1.51-.22,2.31-1.31,4.6-2.64,6.92-3.93,2.21-1.24,4.44-2.44,6.66-3.65,.28-.15,.92,.1,.96,.34,.13,6.85-1.14,13.76-1.56,20.62-.74,8.06-2.04,16.05-2.98,M 24.11-.05,.41,.65,.75,1.13,.55,4.73-2.06,9.41-4.19,14.11-6.3,.71-.33,2.37-1.16,2.59,.02-.19,2.04-.34,4.08-.61,6.12-1.4,10.61-3.02,21.19-4.69,31.76,.04,1.68-3.64,15.13-1.66,14.38,5.68-1.53,11.11-3.85,16.72-5.61,1.68-.52,2.08-.23,1.9,1.33-3.24,19.89-7.4,39.63-11.5,59.36-.04,.24,.54,.6,.85,.54,6.23-1.23,12.4-3.58,18.84-3.11,.24,0,.46,.2,.83,.38Z"/><path class="cls-2" d="M998.52,718.5s-.01,.06-.02,.09c-.02,0-.03,.01-.05,.01l.07-.1Z"/><path class="cls-2" d="M1000.8,800.04s.05,.01,.08,.01c.01,.02,.01,.03,.02,.05l-.1-.06ZM "/><path class="cls-2" d="M1071.72,699.2c-7.31-2.71-14.31-6.72-21.54-9.83-.75-.21-5.65-2.81-5.39-1.39,3.35,5.43,7.09,10.63,10.57,15.98,.96,1.61,2.13,3.22-.79,1.95-5-2.11-9.98-4.26-14.99-6.36-1.91-.79-3.88-1.49-5.85-2.18-.29-.09-.72,.09-1.25,.16,3.94,5.97,7.9,11.81,11.85,17.75,.24,.37,.46,.79-.14,1.22-6.68-2.44-13.15-5.34-20.08-7.41-.19,.2-.5,.39-.46,.5,.19,.5,.42,1.01,.73,1.47,3.18,4.87,6.38,9.73,9.57,14.59,.5,.94,1.42,1.81,1.35,2.92-.01,.25-.43,.27-1.06,.05-4.84-1.63-9.67-3.27-14.51-4.9-.99-.22-2.02-.91-3.01-.42,.M 1,1,.87,1.78,1.4,2.64,3.06,4.91,6.17,9.81,9.25,14.71,.42,.68,.78,1.37,1.11,2.08,.07,.14-.11,.38-.23,.55-4.59-.83-10.2-3.15-15.15-4.2-.38-.09-.79-.26-1.13-.01-.52,.39-.05,.78,.13,1.14,.2,.4,.46,.78,.69,1.17,2.97,5.07,5.94,10.13,8.89,15.21,.56,.97,1.02,1.98,1.52,2.98,.04,.09,.03,.27-.04,.3-.97,.48-2.03-.21-3.02-.35-3.47-.89-6.92-1.79-10.39-2.65-.63-.16-1.31-.26-1.94,.11,0,.89,.6,1.61,1.01,2.4,3.12,6.41,6.99,12.56,9.69,19.11,.02,.14-.31,.47-.43,.45-4.35-.67-8.62-1.7-12.93-2.53-1.86,0-.06,2.07,.18,2.91,3.64,7.51,6.89,1M 5.12,9.87,22.83-.42,.46-.93,.51-1.47,.39-4.26-.97-8.53-1.85-12.85-2.49-3.15-8.37-7.06-16.44-10.76-24.59-.11-.25,.29-.74,.58-.72,3.89,.21,7.74,.63,11.61,1.11,.54,.07,1.02-.42,.82-.84-3.1-6.46-6.77-12.65-10.13-18.98-.26-.59-1.16-1.69-.05-1.91,4.42,.04,8.66,1.5,13.04,1.82,.33-.02,.52-.21,.42-.43-3-6.17-7.05-11.82-10.46-17.78-.4-.66-1.03-1.27-.88-2.08,.62-.35,1.3-.25,1.94-.12,3.78,.75,7.62,1.31,11.33,2.3,.64,.18,1.3,.3,1.95-.09-2.91-5.93-7.36-11.22-10.83-16.89-.34-.72-1.29-1.44-.96-2.26,5.52,.26,10.77,2.69,16.25,3.49,1M -.21-.36-1.67-.6-2.21-3.75-5.44-7.62-10.86-11.33-16.33,.5-.45,1.02-.42,1.52-.28,5.6,1.51,11.19,3.04,16.75,4.72,1.54-.06-.21-1.68-.5-2.32-3.17-4.38-6.36-8.75-9.52-13.13-.61-.84-1.13-1.71-1.68-2.57-.03-.05,.05-.18,.12-.23,.55-.34,1.31,.06,1.9,.15,5.41,1.64,10.81,3.31,16.09,5.22,.85,.3,1.75,.52,2.64,.76,.15,.04,.5-.23,.49-.38-3.62-6.15-8.88-11.56-12.38-17.69,.84-.45,1.74,.18,2.58,.37,3.98,1.39,7.96,2.78,11.91,4.23h.03c2.76,1.02,5.53,2.06,8.25,3.17,.59,.27,2.3,.69,1.39-.7,10.44,3.2,20.34,8.02,29.31,14.34Z"/><path classM ="cls-2" d="M1072.62,698.96l-.02,.02h0s.02-.01,.03-.02Z"/><path class="cls-2" d="M1387.43,827.74c-.19,1.19-.18,1.84-1.57,.74-23.99-22.29-48.46-44.13-73.97-65.02-2.5-2.01-1.79,.16-1.71,2,.63,4.71,1.3,9.42,1.94,14.13,.09,.63,.26,1.27-.11,1.88-.04,.07-.28,.13-.37,.09-2.37-1.18-4.17-3.34-6.27-4.93-18.71-16.11-38.31-31.69-58.15-46.74-.48-.37-.97-.76-1.85-.66,.82,5.77,3.09,11.32,3.86,17.1-.04,.21-.48,.61-.78,.45-17.75-13.64-35.78-27.37-54.37-40.08-.6-.37-1.22-.98-2-.77-.35,.35,.12,1.1,.19,1.54,1.64,4.77,3.3,9.54,4.93,14.M 31,.07,.19-.03,.42-.07,.62-1,.44-2.25-1.17-3.15-1.62-14.65-10.26-29.32-20.48-44.57-29.92-.41-.26-.91-.43-1.38-.62-.18-.05-.53,.14-.51,.33,1.92,4.72,4.12,9.34,6.11,14.02,.17,.38,.11,.83,.13,1.25,0,.04-.21,.15-.27,.13-.36-.12-.75-.23-1.05-.42-2.94-1.89-5.85-3.81-8.79-5.69-8.8-5.65-17.77-11.12-26.94-16.39-2.9-3.03-5.93-5.93-9.06-8.66-1.77-3.31-3.58-6.6-5.34-9.91-.35-.59,.56-.69,.93-.51,14.56,7.3,28.31,15.76,42.23,23.84,.1,.05,.36,.06,.38,.03,.11-.18,.29-.41,.23-.55-2.17-4.87-4.37-9.72-6.46-14.61,.35-.77,1.4,.08,1.92,.M 28,16.78,9.5,32.47,20.24,48.68,30.43,1.22,.16-.43-2.56-.43-3.14-1.43-3.93-2.88-7.85-4.31-11.78-.18-.51-.38-1.03,.13-1.63,17.58,10.46,34.16,22.77,50.72,34.5,2.39,1.74,4.76,3.49,7.16,5.22,.13,.09,.48,.01,.71-.04,.49-.68-.13-1.73-.22-2.51-1.18-4.64-2.37-9.28-3.55-13.92-.33-1.56,1.12-.88,1.84-.32,2.12,1.5,4.25,2.99,6.34,4.51,18.32,13.34,36.62,27.01,54.1,41.27,1.89,1.54,3.81,3.04,5.75,4.54,.15,.11,.54,.14,.74,.07,.23-.14,.38-.55,.3-.84-.63-4.49-1.29-8.98-1.89-13.48-.17-1.59-1.28-6.16,1.66-3.68,26.66,20.93,52.77,42.49,78M ,65.1,.41,6.67,.06,13.37,.16,20.06Z"/><path class="cls-2" d="M338.57,775.45c-.06,1.04-2.64-.77-3.23-.92-13.88-6.97-26.81-15.32-40.23-22.64-.39,.58-.11,1.07,.12,1.58,1.96,4.35,4.04,8.67,5.92,13.05,.1,.27-.06,.6-.12,1.05-16.34-9.06-31.94-19.21-47.29-29.41-.82-.55-1.68-1.07-2.55-1.58-.19-.06-.83-.02-.75,.36,1.58,5.25,3.87,10.29,5.44,15.53,.02,.16-.16,.36-.3,.52-.03,.04-.28,.01-.38-.04-19.28-12.08-38.13-25.26-56.34-38.75-2.12-1.52-2.04-.6-1.73,1.41,1.18,4.64,2.39,9.28,3.58,13.91,.12,.53,.35,1.09-.26,1.39-18.6-12.23-36.M 55-26.45-54.17-40.12-4.3-3.41-8.54-6.87-12.83-10.3-.29-.3-.91-.63-1.3-.25,.13,6.08,1.6,12.19,2.09,18.29-.21,1.05-1.62-.11-2.09-.45-12.61-9.87-25.14-19.81-37.38-29.98-13.28-11.02-26.18-22.29-39.1-33.59-1.97-1.78-1.84-1.49-1.86-3.71,0-5.92-.04-11.86-.07-17.77,0-.41-.09-.86,.36-1.18,.44-.36,.95,.24,1.3,.45,8.26,7.55,16.45,15.11,24.77,22.61,15.73,14.18,31.77,27.91,48.16,41.41,.75,.61,1.57,1.18,2.36,1.75,.12,.04,.6-.07,.65-.22-.08-6.12-1.61-12.19-2.16-18.29-.08-.43,.53-.49,.82-.37,20.51,17.02,41.15,34.35,62.66,50.39,.78M ,.6,1.64,1.12,2.47,1.66,.31,.18,.73-.21,.74-.45-1.33-5.6-2.78-11.18-3.99-16.81-.03-.13,.22-.33,.39-.46,13.79,9.96,27.4,21.03,41.62,30.95,4.2,3.03,8.51,5.96,12.79,8.92,.6,.42,1.3,.73,1.97,1.08,.08,.04,.27,.02,.35-.03,.09-.06,.19-.2,.16-.29-.23-.83-.46-1.67-.74-2.5-1.45-4.14-2.92-8.28-4.37-12.43-.71-2.09,1.1-1.14,2-.42,4.85,3.41,9.67,6.86,14.56,10.24,10.42,7.15,20.97,14.32,31.94,20.83,.09,.05,.33,.06,.38,0,.14-.14,.34-.35,.3-.49-1.73-4.78-4.08-9.34-6.04-14.03-.04-.36-.53-.95-.06-1.19,11.82,6.64,23.18,14.84,35.34,21.4M 9,3.64,3.87,7.48,7.52,11.5,10.93,1.48,2.97,3.43,5.76,4.6,8.86Z"/><path class="cls-2" d="M412.1,696.62h0s-.07,.04-.1,.05l.1-.05Z"/><path class="cls-2" d="M439.68,639.76s-.07,0-.1-.02c0-.01-.01-.03-.01-.04l.11,.06Z"/><path class="cls-2" d="M450.29,664.37c.09,.24-.33,.69-.65,.67-3.36-.09-6.69-.54-10.02-.94-.76-.09-1.7-.54-2.23,.11-.48,.58,.18,1.23,.49,1.81,2.9,5.44,5.83,10.88,8.74,16.32,.48,.88,.93,1.78,1.38,2.68,.3,1.26-3.8,.24-4.61,.25-2.9-.45-5.78-.97-8.68-1.46-1.23,.06-.43,1.17-.14,1.78,3.44,6.1,7.22,12.02,10.82,1M 8.04,.35,1.01-1.47,.7-2.08,.61-3.78-.78-7.63-1.3-11.34-2.31-.48-.12-1.45-.27-1.65,.29,3.12,5.92,7.33,11.25,10.9,16.91,.37,.57,.71,1.15,1.02,1.74,.31,1.03-2.95,0-3.52,0-4.38-.86-8.67-2.63-13.11-2.93-.07,0-.22,.16-.2,.21,.16,.41,.28,.83,.54,1.2,3.75,5.47,7.51,10.96,11.39,16.35,.18,.25,.47,.6,.05,.8-.3,.14-.79,.15-1.14,.07-4.14-.97-8.2-2.12-12.22-3.35-.82-.09-5.45-2.15-5.23-.84,3.04,4.85,6.69,9.32,9.97,14.02,1.98,2.85,4.34,4.91-1.13,3.14-5.36-1.76-10.72-3.44-16.05-5.27-.48-.16-.92-.44-1.49-.18-.33,.14-.32,.4,.21,1.12,M 3.44,4.76,6.91,9.51,10.37,14.26-5.32-.42-10.69-.88-15.63-3.02-1.03-.09-9.16-4.48-6.64-1.04-10.61-3.17-20.67-7.99-29.78-14.34,.76-.88,2.19,.5,3.07,.73,8,3.55,15.65,7.8,23.88,10.81,.63-.72-.24-1.36-.59-2.06-3.37-5.03-6.75-10.05-10.1-15.09-.6-1.21-1.67-2.49,.58-1.71,6.6,3,13.33,5.65,20.09,8.3,.7,.22,1.48,.68,2.2,.24,.06-.03,.08-.2,.03-.27-.61-.95-1.23-1.9-1.86-2.85-3.33-5.04-6.66-10.08-9.97-15.13-.08-.13,.11-.39,.21-.57,6.87,1.94,13.51,5.66,20.52,7.2,.91-.32-.85-1.97-1.04-2.55-3.45-5.6-7.55-10.86-10.59-16.68,.45-.8,1.M 71,.12,2.41,.21,5.12,1.65,10.14,3.55,15.29,5.06,1.87,.22,.27-1.65-.14-2.37-3.47-5.47-7.01-10.89-10.27-16.47-.22-.36-.18-.81-.25-1.23,.64-.2,1.24-.01,1.83,.17,3.27,.99,6.52,2.02,9.8,2.97,1.51,.44,3.07,.77,4.62,1.11,.09,0,.45-.33,.41-.44-3.29-6.27-7.31-12.19-10.56-18.44-.19-.61-1.36-1.96-.37-2.19,4.17,.68,8.17,2.08,12.29,3.03,.92,.13,1.87,.51,2.68-.16-3.47-6.86-7.19-13.62-10.65-20.5-.2-.39-.43-.8,0-1.19,.33-.29,.75-.13,1.12-.06,4.02,.87,8.07,1.63,12.11,2.43,.87,.04,.82-.64,.54-1.18-3.9-8.07-7.54-16.26-10.69-24.58,.5-M .42,1.01-.45,1.55-.34,4.25,.95,8.5,1.78,12.81,2.48,2.89,8.47,7.07,16.41,10.71,24.63Z"/><polygon class="cls-2" points="431.54 461.92 431.54 462 431.44 462 431.54 461.92"/><polygon class="cls-2" points="433.98 504.59 433.98 504.67 433.83 504.59 433.98 504.59"/><path class="cls-2" d="M439.63,542.74v.06s-.05,.01-.07,.02l.07-.08Z"/><path class="cls-2" d="M447.66,477.92c-5.07,2.3-10.08,4.66-15.04,7.09-.57-7.67-1.03-15.33-1.08-23.01,4.51-.37,8.85-1.58,13.28-2.41,.71-.14,2.19-.44,2.4,.45,.4,5.95,.18,11.92,.44,17.88Z"/><patM h class="cls-2" d="M465.16,517.71c-1.05-.28-2.1-.55-3.16-.79,.99-.46,1.98-.91,2.97-1.36,.06,.72,.12,1.43,.19,2.15Z"/><path class="cls-2" d="M495.43,579.61c-1.1,.73-3.9,4.44-5.1,3.56-1.3-2.94-1.48-6.31-2.29-9.42,2.54,1.83,5.01,3.78,7.39,5.86Z"/><path class="cls-2" d="M510.78,596.33c-.78,.63-1.66,2.49-2.77,2.22-.15-.15-.37-.3-.42-.48-.78-2.78-1.45-5.59-2.12-8.4,1.86,2.13,3.63,4.35,5.31,6.66Z"/><path class="cls-2" d="M528.6,636.4c-1,1.43-2.01,2.86-3.03,4.29-.39,.55-.68,1.18-1.47,1.48-.69-.23-.91-.74-1.12-1.24-1.35-3.1M 5-2.73-6.3-4.03-9.47-.93-2.25-1.75-4.53-2.61-6.8-.19-.52-.41-1.02-.97-1.37-.22,.09-.52,.14-.66,.28-2.43,2.71-4.79,5.47-7.19,8.2-.32,.37-.72,.62-1.38,.65-2.32-4.72-3.85-9.86-5.82-14.74-.72-1.11-1.71-7.8-3.35-6.65-2.92,2.67-5.75,5.47-8.8,8-.8,.48-1.3-.35-1.55-.98-2.33-6.85-4.7-13.7-6.68-20.63-.27-.94-.61-1.87-.98-2.79-.04-.1-.48-.2-.67-.15-3.58,1.79-6.65,4.5-10.31,6.19-.66,.18-.95-.54-1.09-1.04-1.54-5.46-3.12-10.91-4.6-16.38-4.32-15.87,.18-11.86-14.66-6.86-.44,.17-1.16-.14-1.26-.54-1.87-6.82-3.17-13.77-4.6-20.7,5.06,M .72,10.06,1.78,14.95,3.25,.74,3.7,1.5,7.4,2.26,11.1,.11,.8,.42,1.77,1.51,1.36,3.72-1.53,7.04-3.6,10.59-5.31,1.01-.25,1.19,1.95,1.49,2.65,1.72,8.09,3.7,16.1,5.9,24.08,.06,.21,.18,.41,.26,.61,.09,.18,.86,.3,1.08,.15,2.83-1.89,5.27-4.31,7.93-6.43,.77-.46,2.16-2.49,2.87-1.06,2.24,7.43,3.88,14.96,6.44,22.33,.24,.54,.5,1.5,1.27,1.31,3.14-2.31,5.52-5.57,8.35-8.25,.34-.36,.7-.65,1.41-.6,2.68,6.89,4.15,14.37,7.25,21.06,.71,.37,1.33-.48,1.76-.92,1.5-1.88,2.98-3.78,4.47-5.67,3.2,7.08,5.53,14.31,7.04,21.59Z"/><path class="cls-M 2" d="M557.81,594.52c-.22-.46-.44-.92-.66-1.37,.47,.19,.46,.95,.66,1.37Z"/><path class="cls-2" d="M670,602.28s.04-.07,.07-.1c.03,.01,.05,.03,.08,.04l-.15,.06Z"/><path class="cls-2" d="M697.61,575.53c-.09,.33-.07,.68-.26,.94-3.24,4.59-6.45,9.22-9.75,13.77-.27,.34-.96,.49-1.42,.26-2.57-1.24-4.98-2.56-7.64-3.66-3.49,4.93-5.34,10.32-8.47,15.34-2.56-1.32-4.99-2.95-7.64-4.07-.2-.05-.57,.05-.69,.19-2.17,3.61-3.57,7.66-5.44,11.44-.65,1.19-.84,2.63-2.01,3.44-3.13-1.14-4.94-3.28-8.15-4.37-2.02,4.12-3.43,8.4-5.18,12.61-.31,.8M 1-.49,1.66-1.34,2.43-3.06-1.15-4.93-3.56-7.94-4.85-1.9,.94-4.94,15.69-6.65,14.48-2.12-1.55-3.8-3.62-5.72-5.41-.42-.42-.8-.88-1.66-1.01-2.36,4.32-2.93,9.47-5.35,13.74-.64,.01-1.01-.31-1.32-.66-1.74-1.92-3.46-3.85-5.2-5.77-.57-.57-.9-1.18-1.87-.98-1.74,4.21-2.71,8.89-4.79,12.91-.11,.11-.6,.14-.68,.06-.75-.76-1.48-1.52-2.15-2.32-1.63-1.98-3.22-3.98-4.82-5.97-.17-.21-.93-.16-1.03,.07-1.72,3.92-3.18,7.99-4.64,11.98-.81,.14-1.2-.16-1.62-.72-9.35-12.93-5.77-11.82-12.15,1.64-.33-8.02-1.35-16.07-3.07-24.07,.15-.1,.33-.17,.5M 5-.22,2.64,3.68,4.21,7.99,7.15,11.47,.67-.05,.97-.35,1.15-.79,1.73-3.83,3.07-7.86,5.12-11.53,.8,.28,1.08,.77,1.39,1.24,1.68,2.57,3.36,5.15,5.07,7.72,.34,.45,.94,1.37,1.61,.92,2.24-3.92,3.12-8.57,5.35-12.48,.17-.26,.78-.26,.99,.02,2.15,2.72,3.91,5.75,6.38,8.2,.93,.41,1.27-1.52,1.65-2.12,1.46-3.58,2.7-7.24,4.28-10.77,.08-.17,.34-.35,.56-.4,.92-.12,1.3,.94,1.85,1.47,1.43,1.69,2.78,3.45,4.24,5.11,.51,.56,.92,.72,1.28,.59,.41-.16,.55-.44,.67-.74,1.39-3.49,2.77-6.98,4.17-10.46,.52-.8,.83-3.2,2.11-2.64,2.02,2.01,4.05,4.01M ,6.1,5.99,.2,.19,.94,.09,1.05-.14,2.29-4.67,3.81-9.73,6.39-14.26,.08-.11,.56-.19,.7-.11,2.14,1.24,3.94,2.92,5.94,4.36,.39,.29,.84,.55,1.6,.44,2.54-4.77,4.6-9.85,7.22-14.58,.26-.47,.87-.62,1.29-.33,1.43,.98,2.85,1.97,4.3,2.94,.86,.39,2.04,1.81,2.97,.95,2.69-5.01,5.6-10.03,8.08-15.11-.58-1.17-2.02-1.68-3.05-2.5-1.22-.98-2.41-2.01-3.88-2.85-1.2,.54-1.53,1.67-2.15,2.69-1.94,3.55-3.88,7.1-5.83,10.65-.49,.62-.8,1.97-1.79,1.86-2.15-1.14-3.85-3.01-5.8-4.46-.38-.32-.79-.58-1.52-.52-3.01,4.8-5.02,10.15-7.76,15.08-.74,0-1.11-M .29-1.43-.63-1.84-1.83-3.4-3.98-5.45-5.58-.13-.08-.63,.01-.69,.12-.61,1.07-1.23,2.15-1.73,3.26-1.5,3.34-2.96,6.7-4.43,10.05-.18,.42-.47,.76-1.07,1-2.6-2.07-4.08-4.99-6.33-7.33-.73,.12-1,.47-1.17,.87-1.96,4.21-3.49,8.66-5.72,12.74-1.31,1.03-4.72-5.71-5.8-6.78-1.02-1.42-1.52-2.08-2.44-.07-1.85,3.9-3.2,8.07-5.32,11.81-.42,.2-.98-.35-1.22-.62-1.62-2.6-3.21-5.21-4.8-7.82-.3-.49-.57-.98-1.33-1.31-2.53,4.02-3.88,8.7-6.14,12.87-.72-.1-1.04-.45-1.25-.84-1.52-2.76-3.15-5.48-4.31-8.36-.32-.8-.83-1.57-1.27-2.34-.11-.11-.57-.13M -.69,.01-2.59,3.86-3.78,8.43-6.46,12.21-.5-.27-.89-.5-1.08-1.02-1.25-5.29-2.81-10.55-4.7-15.76,9.83-17.01,5.65-13.8,12.22,2.17,1.19,.1,1.36-.96,1.95-1.84,1.67-3.18,3.33-6.36,4.97-9.54,.31-.6,.61-1.2,1.29-1.61,.73,.59,.91,1.33,1.16,2.06,1.15,3.31,2.29,6.7,4.05,9.8,.08,.13,.35,.2,.56,.25,2.94-3.93,4.19-9.2,7.08-13.29,.66-.36,.99,.35,1.25,.84,.99,1.48,3.63,9.63,5.27,8.96,2.65-4.28,4.34-9.08,6.88-13.43,.32-.44,.91-.25,1.14,.14,1.61,2.67,2.86,5.76,5,8.05,1.03,.46,1.4-1.4,1.89-2.03,1.93-3.79,3.84-7.58,5.75-11.38,.21-.41,M .52-.74,1.24-.9,.9,.98,5.11,9.17,6.42,7.08,2.23-4.28,4.54-8.52,6.81-12.77,1.28-2.49,1.74-2.06,3.19,.03,1.34,1.48,2.7,2.95,4.07,4.41,.23,.25,.82,.18,1.01-.1,3.2-4.99,5.74-10.28,9.11-15.18,.46,.16,.92,.19,1.14,.4,1.81,1.6,3.31,3.48,5.29,4.86,1.29,.49,1.75-1.39,2.46-2.11,2.83-4.04,5.65-8.09,8.47-12.13,.32-.45,.62-.94,1.14-.99,2.42,1.88,4.73,3.68,7.07,5.51,.2,.43-.2,.76-.45,1.13-3.34,4.8-6.74,9.56-10.05,14.38-.25,.38-.14,.88,.29,1.16,1.78,1.15,3.57,2.3,5.37,3.42,2.01,1.25,2.21,.45,3.41-1.13,2.88-4.02,5.75-8.04,8.64-12.M 06,.32-.45,.64-.94,1.37-1.07,2.65,1.15,5.01,2.9,7.59,4.3Z"/><path class="cls-2" d="M196.48,1198.45c19.59-.23,39.32,.32,58.96-.25,5.19-.09,5.05-.3,2.78,3.32-2.94,4.84-6.18,9.53-8.95,14.47-.23,1.29,2.14,.59,2.9,.74,3.1-.11,6.19-.21,9.29-.38,12.89-.76,25.82-1.27,38.67-2.42,1.31-.11,2.65-.35,4.06,.02-.14,1.37-1.38,2.28-2.11,3.4-3.34,4.3-6.69,8.59-10.03,12.89-.42,.55-.79,1.12-1.17,1.69-.13,.19,.34,.69,.64,.68,13.4-.68,26.76-2.38,40.1-3.8,2.66-.3,5.34-.52,8.01-.77,.43-.04,.48,.41,.42,.72-4.93,5.94-10.39,11.53-15.5,17.34-M .46,.51-1.05,.99-.92,1.74,14.79-1.07,29.49-4.03,44.24-5.65,1.48,.34-.13,1.37-.78,2.2-5.29,5.31-10.6,10.6-15.89,15.91-.94,1.21-4.53,3.63-.68,3.11,12.98-1.81,25.91-3.96,38.84-6.08,.2,0,.74,.33,.49,.62-6.83,6.86-14.09,13.31-21.08,20.02-.45,.54-3.06,2.49-1.6,2.72,12.29-1.88,24.54-3.99,36.81-5.96,.55-.08,1.04,.21,.55,.75-8.17,7.49-16.6,14.71-24.86,22.1-.81,.72-1.61,1.44-2.38,2.19-.12,.12-.06,.39-.02,.58,.83,.33,2.22-.08,3.15-.11,4.9-.73,9.79-1.47,14.68-2.24,5.62-.66,11.42-2.33,16.98-2.51,.13,.91-1.07,1.46-1.69,2.04-9.37M ,8.04-18.75,16.07-28.13,24.1-.73,.63-1.44,1.28-2.11,1.95-.12,.12,.01,.39,.04,.67,10.55-.81,20.9-3.02,31.46-3.85,0,.32,.11,.6-.02,.71-.87,.82-1.76,1.63-2.7,2.4-10.58,8.76-21.16,17.51-31.74,26.26-.84,.7-1.67,1.4-2.47,2.13-.14,.12-.17,.43-.08,.57,.7,.5,1.83,.14,2.66,.16,4.15-.36,8.3-.73,12.45-1.09,4.28-.38,8.57-.76,12.85-1.14,.36-.03,.81-.13,.97,.25,.15,.35-.15,.62-.42,.85-.83,.7-1.68,1.4-2.53,2.09-13.61,10.89-27.14,21.9-40.81,32.73-.9,.78-2.27,.63-3.42,.66-7.14,0-14.28,.02-21.43,.02-5.03,.24-1.35-1.89,.44-3.41,5.6-4.M 51,11.21-9.02,16.8-13.53,5.78-4.67,11.54-9.36,17.31-14.04,1.75-1.48,4.74-3.28,.22-2.82-8.92,.76-17.73,1.29-26.68,1.94,.07-1.5,1.76-2.09,2.7-3.08,9.7-8.08,19.41-16.16,29.11-24.25,1.65-1.54,4.67-3.33,.11-2.83-9.2,1.06-18.39,2.14-27.59,3.15-.57,0-1.39,.16-1.87-.18-.06-.09-.13-.25-.08-.31,.57-.59,1.13-1.19,1.76-1.74,8.47-7.39,16.94-14.76,25.41-22.15,.65-.71,3.52-2.74,.98-2.52-11.17,1.4-22.23,3.61-33.46,4.36-1.1-.07-.21-1.11,.21-1.46,7.18-6.57,14.39-13.12,21.56-19.7,.64-.78,4.21-3.36,1.45-3.03-7.96,1.09-15.92,2.19-23.89M ,3.27-4.39,.5-8.76,1.36-13.18,1.52-1.51-.16,.44-1.72,.86-2.23,5.77-5.69,11.56-11.37,17.33-17.05,2.45-2.42,2.89-3-1.09-2.57-12.89,1.79-25.77,3.51-38.74,4.64-.2-.01-.75-.35-.58-.65,.77-.88,1.54-1.77,2.34-2.63,4.73-5.11,9.48-10.2,14.21-15.31,.32-.5,1.21-1.1,1.07-1.65-.16-.14-.38-.37-.55-.36-3.88,.38-7.75,.8-11.62,1.19-9.09,.92-18.17,1.87-27.27,2.68-2.14,.19-4.29,.34-6.43,.5-.41,.03-.8-.02-1.01-.34-.22-.34,.04-.62,.25-.88,4.59-5.95,9.7-11.56,13.94-17.76,.06-.1-.21-.47-.34-.47-4.17-.15-8.31,.42-12.47,.65-12.99,.88-26.06M ,2.03-39.07,2.11-.97-.52,.36-1.59,.55-2.26,3-4.7,6.03-9.39,9.03-14.08,.43-.67,.79-1.36,1.11-2.07,.06-.13-.18-.47-.35-.51-3.46-.36-7,.09-10.48,.05-15.88,.33-31.8,.8-47.67,.27-.79-.37-.06-1.41,.09-2.01,2.25-5.07,4.52-10.14,6.76-15.21,.26-.59,.77-1.16,.44-1.85l-.13,.07Z"/><path class="cls-2" d="M979,733.46h.04s.03,.05,.05,.07l-.09-.07Z"/><path class="cls-2" d="M1007.34,688.2c-.78,.26-1.53,.02-2.27-.14-4.13-.95-8.25-1.91-12.39-2.84-1.44-.16-2.91-.94-4.32-.41,3.84,6.01,9.39,11.14,13,17.3-.65,.28-1.17,.17-1.69,.05-4.9-1.M 08-9.87-2.15-14.91-2.65-1.2-.02,.64,1.92,.85,2.41,3.61,5.03,7.55,9.87,10.99,15.02,.51,1.61-4.27-.04-5.18,.06-2.91-.41-5.82-.81-8.74-1.18-.77-.04-1.58,.4-.86,1.18,3.26,4.7,6.53,9.39,9.8,14.09,.54,1.03,3.37,3.9,.58,3.64-4.38-.48-8.75-1.02-13.16-1.27-4.05-5.68-8.11-11.36-12.17-17.04-.32-.45-.77-.89-.32-1.55,4.23-.23,8.55,.29,12.79,.43,.33,.02,.69-.45,.54-.69-3.38-4.96-7.33-9.53-10.94-14.33-.36-.69-1.64-1.46-1.13-2.28,.16-.2,.72-.28,1.09-.26,2.15,.13,4.3,.28,6.44,.49,2.27,.22,4.53,.52,6.8,.76,.17,.02,.4-.17,.56-.3,.07-M .06,.08-.23,.02-.31-.53-.75-1.05-1.5-1.64-2.22-2.34-2.86-4.68-5.71-7.03-8.56,3.82-1.52,7.68-2.8,11.56-3.84,.38,.03,1.11,.3,1.11-.28,5.07-1.31,10.17-2.2,15.27-2.7,1.59,2,3.19,3.99,4.78,5.99,.35,.44,.74,.87,.57,1.43Z"/><path class="cls-2" d="M1007.34,688.2s.05,0,.08-.02l-.09,.06s.01-.03,.01-.04Z"/><path class="cls-2" d="M1017.66,638.95c-3.46-.13-6.93-.14-10.4-.03-.49-.7-4.05-4.09-1.21-3.35,3.92,1.02,7.78,2.16,11.61,3.38Z"/><path class="cls-2" d="M1028.42,666.21l-.08,.07s.02-.04,.02-.06c.02,0,.04,0,.06-.01Z"/><path clM ass="cls-2" d="M1387.43,765.33c.01,5.81,0,11.63,0,17.45-.07,.62,.22,1.34-.37,1.82-.73,.37-2.06-1.14-2.76-1.63-17.11-14.28-34.28-28.34-52.12-41.97-8.36-6.41-16.88-12.69-25.34-19.03-.7-.43-1.39-1.21-2.31-1.03-.31,.25-.2,.84-.21,1.21,.59,5.78,2.1,11.53,2.17,17.33-.01,.08-.44,.23-.64,.2-1.14-.44-2.04-1.4-3.06-2.08-21.46-16.45-43.8-32.64-66.66-47.48-1.01-.24-.52,1.3-.5,1.83,1.14,4.43,2.32,8.85,3.49,13.27,.24,.74,.39,1.45,.11,2.19-.95-.03-1.65-.49-2.35-1.05-18.89-12.67-38.08-26.53-58.21-37.2-.16,.1-.24,.39-.19,.56,1.5,4.M 48,3.27,8.87,4.86,13.33,.22,.62,.35,1.26,.5,1.89,.03,.41-.58,.36-.83,.33-16.61-10.2-33.45-20.74-50.96-29.6-.2-.09-.57,.09-.56,.29,2.02,4.81,4.45,9.46,6.61,14.21,.07,.23-.03,.76-.36,.74-13.82-7.06-27.12-14.94-41.23-21.57-1.12-.46-2.18-1.33-3.47-1.12,.06,.3,.03,.64,.19,.91,2.5,4.36,5.03,8.7,7.55,13.06h.08s-.07,.02-.1,.03h-.01c-1.59,.58-3.08-.96-4.53-1.47-9.94-4.95-19.99-9.76-30.3-14.21-3.01-1.23-6.07-2.99-2.63,1.67-10.17-3.84-20.7-6.52-31.48-8.01-2.13-2.84-4.45-5.52-6.45-8.45,.74-.39,1.26-.18,1.95,.07,6.58,2.21,13.13M ,4.46,19.54,6.98,3.99,1.56,7.98,3.11,11.99,4.65,.18,.07,.55,0,.7-.11,.13-.11,.21-.41,.12-.55-.79-1.24-1.61-2.48-2.45-3.71-1.63-2.78-4.48-5.63-5.52-8.54,.12-.25,.37-.32,.67-.2,4.82,1.9,9.71,3.71,14.46,5.74,8.13,3.35,16.1,7.04,24.07,10.55,.16-.19,.45-.39,.4-.5-.23-.61-.5-1.22-.84-1.8-1.96-3.31-3.94-6.61-5.9-9.92-.28-.48-.5-.99-.73-1.49-.03-.08,.03-.25,.09-.27,.23-.07,.54-.19,.71-.12,2.26,.95,4.54,1.88,6.76,2.89,13.07,5.7,25.59,12.59,38.31,18.53,.14-.15,.36-.39,.3-.51-1.7-3.52-3.43-7.02-5.13-10.53-.58-1.2-1.1-2.42-1.6M 2-3.63-.03-.17,.33-.39,.49-.35,6.56,2.79,12.76,6.44,19.13,9.63,10.46,5.52,20.7,11.28,30.85,17.16,.87,.51,1.76,.99,2.67,1.46,.13,.06,.43-.03,.63-.1,.38-.41-.26-1.36-.32-1.86-1.65-4.32-3.31-8.64-4.96-12.96-.15-.39-.25-.81,.23-1.15,21.21,10.99,41.16,24.17,61.3,36.86,.55,.14,1.34,.43,1.23-.44-.36-1.48-.76-2.95-1.15-4.42-1.01-3.9-2.03-7.8-3.02-11.7-.02-.28,.19-.79,.58-.65,24.74,14.97,48.65,31.67,72.16,48.28,.13,.04,.55-.12,.61-.29,.06-.21,.12-.43,.09-.63-.58-4.17-1.19-8.35-1.76-12.52,.08-1.07-1.64-6.91,.74-5.24,28.99,19M .99,57.34,40.94,84.58,63.1,.04,.59,.11,1.23,.11,1.87Z"/><path class="cls-2" d="M954.83,650.71c-3.52,1.52-7.03,3.2-10.39,4.98-1.33-1.56-3.28-2.76-4.21-4.59-.03-.08,.05-.26,.13-.29,4.75-.63,9.67-.19,14.47-.1Z"/><path class="cls-2" d="M1024.05,629.69s.07,.06,.07,.06c-.03-.01-.06-.02-.1-.03l.03-.03Z"/><path class="cls-2" d="M1387.37,720.66c0-.54-.09-1.07-.13-1.64-28.73-20.88-58.54-40.39-88.91-59.04-.69-.3-2.4-1.8-2.72-.46,.56,5.98,2.12,12,2.12,17.97-.55,.78-2.87-1.2-3.59-1.49-7.43-4.64-14.82-9.34-22.3-13.93-16.6-10.09-M 33.54-20.03-50.86-29.21-.21-.08-.9-.06-.88,.33,.07,.64,.09,1.29,.26,1.91,1.12,4.86,3.09,9.58,3.69,14.52-.14,.93-2.12-.5-2.64-.65-20.77-11.46-41.49-23.36-63.26-32.88-.74,.51-.06,1.39,.08,2.06,1.59,4,3.2,8,4.79,12,1.44,3.3-2.31,.7-3.58,.21-17.09-8.33-34.56-17.27-52.52-23.84-.09,.06-.21,.18-.19,.26,.1,.42,.18,.86,.38,1.25,1.64,3.18,3.31,6.36,4.96,9.54,.41,1.21,2.09,2.67,.83,3.88-15.12-7.39-31.03-13.42-47.03-19.07-.2-.03-.9,.12-.71,.47,1.6,3,3.58,5.8,5.41,8.66,.89,1.64,4.31,5.66-.12,3.76-12.13-4.68-24.51-8.9-37.06-12.7M 9-.68-.09-1.69-.65-2.26-.24-.23,.51,.59,1.23,.82,1.72,2.53,3.49,5.24,6.74,7.6,10.37-1.48,.41-2.57-.27-3.93-.65-8.11-2.63-16.3-5.07-24.6-7.31-1.91-.51-3.83-1.01-5.75-1.5-.49-.12-1.04-.21-1.51,.12-.05,.59,.47,.98,.83,1.42,2.14,2.61,4.31,5.2,6.46,7.81,.44,.69,1.47,1.39,1.36,2.23-.1,.13-.49,.23-.69,.18-1.55-.34-3.1-.7-4.63-1.11-8.06-2.08-16.16-4.32-24.43-5.58-.11,0-.32,.04-.35,.11-.47,.66,.39,1.13,.74,1.62,2.69,2.96,5.5,5.83,8.11,8.86,.18,.25,.46,.55,.15,.82-.14,.11-.52,.12-.76,.07-7.71-1.55-15.4-3.17-23.19-4.3-.54-.06M -2.09-.33-2.18,.24,.1,1.39,11.44,10.52,9.16,10.75-6.66-.46-13.24-1.85-19.93-2.4-.61-.03-1.4-.2-1.94,.09-.02,.21-.07,.48,.06,.62,2.8,2.76,5.63,5.5,8.43,8.25,.9,.98,2.99,2.65,.21,2.43-4.14-.53-8.32-.59-12.48-.89-.97,.1-6.56-1.02-4.89,.89,4.4,4.18,8.81,8.45,13.01,12.78,4.65-1.94,9.35-3.61,14.09-5.02-.49-.83-7.47-7.08-5.65-7.06,7.07,.24,13.98,2.07,20.95,3.14,.19,.03,.45-.13,.63-.25,.06-.04,.05-.23-.01-.3-.43-.55-.84-1.1-1.32-1.62-2.58-2.76-5.18-5.51-7.76-8.26-.4-.42-.85-.83-.82-1.47,1.72-.2,3.39,.48,5.07,.76,6.48,1.42,M 12.99,2.78,19.37,4.49,.53,.14,1.04,.22,1.67-.04-2.69-3.66-5.92-6.9-8.84-10.38-.3-.34-.5-.75-.73-1.13-.03-.06,.05-.18,.12-.24,.55-.31,1.32,.06,1.91,.13,8.12,1.96,16.11,4.2,24.04,6.61,1.43,.28,3.1,1.37,4.48,.48-3.26-3.52-6.16-7.52-9.29-11.2-.11-.18-.06-.43,.14-.54,.56-.31,1.3,.13,1.89,.22,11.06,3.02,21.64,7.18,32.48,10.63,1.03-.1-.15-1.36-.39-1.84-2.44-3.46-5.12-6.8-7.37-10.39-.08-.13,.04-.43,.19-.53,1.09-.33,2.25,.57,3.31,.81,8.52,2.97,16.94,6.11,25.22,9.48,15.87,6.51,13.39,7.02,5.27-6.78-.24-.57-1.01-1.53-.87-2.07,M .2-.11,.49-.28,.65-.23,14.94,5.56,29.33,12.33,43.58,19.03,.92,.29,1.81,1.24,2.8,.81,.07-.02,.12-.19,.09-.27-.25-.61-.49-1.23-.79-1.82-1.66-3.3-3.34-6.59-4.99-9.88-.35-.7-.62-1.42-.87-2.14-.04-.13,.22-.33,.4-.58,16.19,7.17,31.94,15.21,47.37,23.46,2.26,1.17,4.41,2.53,6.76,3.52,.17,.06,.48-.06,.7-.14-1.27-5.07-4.07-10.23-5.62-15.41,.39-.87,1.72,.02,2.3,.29,12.84,6.74,25.53,13.66,37.95,20.89,7.08,4.12,14.07,8.33,21.1,12.51,.98,.45,1.94,1.49,3.05,1.45,.15-.14,.37-.34,.33-.48-1.43-5.47-2.96-10.93-4.29-16.43,.03-.21,.43-.M 62,.75-.45,25.06,14.28,48.95,29.76,72.66,45.81,1.08,.66,2.66,1.79,2.3-.65-.65-5.68-1.99-11.31-2.15-17.01,0-.09,.49-.31,.57-.26,1.32,.74,2.66,1.46,3.9,2.28,19.23,12.61,38.1,25.54,56.69,38.98,8.08,5.86,16.03,11.85,24.03,17.78,1.02,.6,1.88,1.89,3.17,1.66,.58-.17,.24-1.05,.38-1.48-.01-6.03-.02-12.06-.04-18.09Zm-274.43-99.18s-.02-.01-.03-.02c.06-.06,.13-.12,.2-.17-.06,.06-.11,.13-.17,.19Z"/><path class="cls-2" d="M375.64,837.58v-.04s.06-.01,.09-.02l-.09,.06Z"/><path class="cls-2" d="M428.06,823.4c.06-.03,.12-.05,.18-.06M ,0,.06-.07,.09-.2,.1,.01-.01,.02-.03,.02-.04Z"/><path class="cls-2" d="M488.14,758.72h-.04l-.06-.06,.1,.06Z"/><path class="cls-2" d="M496.76,803.67c-5.34,0-10.76-.38-16.08-.9-.76-.07-3.78-.5-2.47,.99,3.18,3.21,6.5,6.32,9.7,9.5,.15,.14,.2,.43,.13,.6-.16,.2-.68,.35-1,.28-7.05-.45-14.13-2.15-21.1-2.39-.06,.19-.17,.45-.06,.58,.68,.81,1.39,1.59,2.13,2.36,1.97,2.29,5.84,5.41,7.24,7.66-.14,.15-.32,.38-.5,.39-2.54-.03-5.06-.6-7.55-.98-5.5-1.04-10.98-2.12-16.47-3.2-.51-.1-1.01-.34-1.5,.02,1.95,3.38,5.3,5.91,7.78,8.96,.55,.6M ,1.04,1.24,1.53,1.87,.06,.07,.02,.23-.04,.31-.94,.31-2.13-.15-3.12-.23-7.45-1.48-14.78-3.25-22.05-5.21-1.67-.3-3.39-1.23-5.09-.94,0-.03-.02-.07-.07-.12-.03,.06-.07,.12-.11,.18-.04,.01-.08,.03-.12,.05,.04,0,.07,0,.1,0,2.64,3.86,6,7.38,8.85,11.13,.06,.08,.03,.24-.03,.32-.79,.32-1.86-.11-2.69-.22-9.85-2.56-19.59-5.35-29.18-8.48-1.07-.28-2.26-1.01-3.37-.7-.45,.19-.16,.56,.02,.81,2.69,3.8,5.85,7.52,8.21,11.43-.59,.42-1.21,.11-1.82-.07-8.63-2.73-17.29-5.38-25.71-8.51-4.14-1.54-8.3-3.07-12.45-4.59-.46-.17-1.01-.57-1.45-.2M 6-.66,.47,.01,.98,.23,1.43,.35,.7,.83,1.35,1.27,2.02,1.9,2.96,3.94,5.85,5.69,8.9,.13,.25,.04,.59,.03,.89-.66,.16-1.26-.04-1.84-.26-4.64-1.73-9.3-3.42-13.91-5.19-9.6-3.68-19.06-7.57-28.37-11.69-1.06-.47-2.14-.91-3.23-1.33-.16-.06-.47,.08-.68,.17-.07,.03-.14,.19-.11,.26,.32,.71,.64,1.42,1,2.11,1.93,3.79,3.87,7.57,5.78,11.36,.07,.14-.14,.38-.26,.55-19.02-6.89-37.22-16.51-55.38-25.11-.16-.06-.46,.06-.67,.15-.32,.34,.1,1.11,.19,1.53,1.64,4.1,3.31,8.2,4.96,12.29,.09,.44,.52,1.22,.18,1.54-.21,.08-.47,.18-.67,.14-1.48-.46-M 2.83-1.24-4.23-1.88-19.69-9.52-38.77-19.67-57.71-30.38-1.36-.6-4.25-2.88-3.32,.43,1.17,4.2,2.35,8.4,3.52,12.61,.07,.82,.85,2.12,.09,2.72-17.63-8.61-34.76-19.33-51.62-29.32-7.48-4.59-14.88-9.27-22.32-13.9-1.12-.5-2.1-1.76-3.4-1.44-.3,2.06,.39,4.06,.64,6.09,.38,4.14,1.54,8.32,1.57,12.45-.69,.21-1.16-.01-1.59-.27-16.39-9.9-32.57-20.24-48.43-30.75-13.25-8.83-26.36-17.8-39.19-27.02-.94-.79-2.52-1.38-2.6-2.74-.11-6.25-.02-12.49-.05-18.74-.11-2.94,2.11-.85,3.33,.01,27.36,20.57,55.61,40.53,84.62,59.1,.95,.58,1.24-.78,1-1.4M 6-.74-5.57-1.52-11.13-2.3-16.7-.02-.19,.14-.56,.2-.56,20.31,12.22,40.11,26.47,61.08,38.54,3.98,2.4,8.01,4.75,12.03,7.11,.63,.38,1.22,.86,2.11,.79,.29-.53,.12-1.05-.02-1.58-1.17-4.2-2.34-8.41-3.48-12.61-.26-.94-.43-1.9-.62-2.85-.01-.09,.09-.22,.18-.28,.78-.13,1.69,.66,2.41,.95,7.15,4.23,14.24,8.52,21.44,12.7,12.44,7.2,25.11,14.15,37.99,20.84,.78,.3,1.56,1.1,2.42,.66,.08-.03,.13-.19,.11-.28-.19-.62-.36-1.26-.6-1.87-1.61-4.11-3.23-8.21-4.85-12.32-.16-.4-.45-.8-.14-1.27,1.28-.12,2.8,1.18,4.01,1.67,16.28,8.83,33.08,17.2M 5,50.07,24.93,.58,.14,1.42,.27,.93-.77-2.09-4.56-4.82-8.84-6.63-13.51,.28-.86,2.08,.39,2.68,.55,10.19,4.84,20.48,9.54,30.98,13.95,3.82,1.6,7.66,3.15,11.51,4.71,.53,.11,1.76,.81,1.99,.04-1.88-3.85-4.48-7.34-6.63-11.05-.35-.57-.61-1.19-.88-1.79-.01-.14,.36-.4,.51-.38,12.74,4.88,25.27,10.18,38.26,14.56,.46,.17,1.02,.16,1.53,.2,.08,.01,.26-.16,.24-.2-.17-.41-.31-.83-.57-1.19-2.45-3.7-5.59-7.11-7.71-10.96-.01-.18,.29-.42,.46-.42,2.04,.39,3.98,1.31,5.96,1.95,9.04,3.03,19.17,7.1,28.45,8.88,.08-.17,.22-.42,.13-.54-2.87-3.8M 8-6.39-7.37-8.98-11.42,.58-.36,1.1-.27,1.62-.12,4.55,1.33,9.08,2.71,13.66,3.98,4.32,1.2,8.69,2.3,13.04,3.43,.48,.05,1.11,.25,1.55-.03,.06-.06,.1-.19,.06-.26-.39-.56-.75-1.13-1.21-1.66-2.45-2.83-4.94-5.65-7.41-8.47-.37-.42-.82-.82-.75-1.44,.39,0,.81-.08,1.16,.01,8.04,1.88,16.32,4.25,24.47,5.27,.09-.17,.23-.41,.14-.53-3.07-3.72-6.71-6.97-9.76-10.7-.11-.23-.1-.72,.38-.66,7.08,.9,14.17,3.12,21.36,3.11,.02-.25,.14-.51,.03-.65-1.85-2.2-3.95-4.23-5.88-6.35,4.77-1.45,9.51-3.15,14.19-5.13,3.72,4.33,8.28,8.11,12.29,12.24,.34M ,.43,1.28,1.11,.61,1.58Z"/><path class="cls-2" d="M500.01,789.06c-4.7,.41-9.67,.16-14.36,.03,3.52-1.55,7.03-3.24,10.4-5.04,1.42,1.41,2.83,2.82,4.24,4.23,.24,.23,.05,.73-.28,.78Z"/><path class="cls-2" d="M415.11,808.13c-.72,.46-1.49-.02-2.21-.21-10.08-3.32-19.94-7.03-29.69-10.93-.71-.24-1.41-.76-2.17-.4-.06,.02-.1,.19-.06,.26,2.32,3.93,5.09,7.58,7.65,11.36,.24,.36,.36,.78,.5,1.18,.02,.05-.19,.21-.28,.2-4.97-1.25-9.72-3.67-14.5-5.5-7.35-3.15-14.63-6.41-21.93-9.64-.8-.35-1.7-.61-2.19-1.3-.02-.01-.02-.02-.03-.03-.07,.0M 7-.13,.14-.19,.2,.08-.06,.15-.11,.22-.17-1.26,1.34,.7,2.84,1.21,4.13,1.83,3.23,3.9,6.37,5.62,9.66,.06,.17-.02,.46-.17,.57-15.64-5.67-30.38-14.18-45.4-21.42-.7,.57-.22,1.12,.03,1.78,1.82,3.71,3.67,7.41,5.48,11.12,.29,.59,.48,1.22,.68,1.84,.03,.06-.11,.2-.21,.25-10.63-4.15-20.73-10.46-30.87-15.73-7.34-3.99-14.45-8.35-21.85-12.2-.37-.19-.69,.24-.69,.52,1.43,4.85,3.6,9.47,5.3,14.22,.09,.39,.38,.94,0,1.21-14.18-6.81-27.62-15.78-41.09-23.82-6.49-4.04-12.89-8.16-19.33-12.25-.64-.33-1.22-.97-2.01-.71-.08,.02-.18,.2-.16,.28M ,.62,2.43,1.26,4.85,1.88,7.27,.81,3.16,1.89,6.27,2.34,9.48,.02,.08-.11,.2-.21,.25-.11,.05-.31,.1-.39,.06-.89-.48-1.78-.95-2.63-1.48-18.02-11.23-35.53-22.97-52.89-35.08-5.44-3.68-10.6-7.72-16.08-11.31-.19-.09-.5-.03-.75,.01-.07,.01-.16,.18-.15,.27,.21,5.18,1.26,10.29,1.9,15.42,.44,2.67,.43,3.05-.03,3-1.31-.12-2.05-.96-2.94-1.57-27.54-19.04-54.59-39.14-80.52-59.86-2.72-2.16-2.35-1.7-2.37-4.48,.06-6.13-.26-12.3,.05-18.41,.99-.43,1.79,.66,2.55,1.14,22.34,18.62,44.82,36.77,68.33,54.15,3.16,2.35,6.31,4.71,9.48,7.05,.58,.M 31,2.41,2.02,2.78,.86-.32-5.93-1.5-11.77-2.26-17.65-.09-1.94,2.33,.25,2.94,.68,21.84,16.44,44.35,33.52,67.7,47.88,.61-.34,.26-1.22,.17-1.77-.9-3.37-1.82-6.73-2.72-10.1-.35-1.78-1.29-3.55-.93-5.37,.77-.14,1.25,.27,1.75,.62,3.9,2.66,7.77,5.33,11.68,7.98,15.32,10,30.66,20.88,46.92,29.51,.1-.05,.23-.18,.21-.26-.12-.63-.19-1.27-.42-1.88-1.32-3.62-2.69-7.22-4.04-10.83-.34-.93-.68-1.86-.98-2.8,.02-.23,.36-.66,.72-.47,16.6,10.08,33.31,20.49,50.68,29.41,.21,.05,.84-.05,.8-.4-.12-.41-.23-.83-.42-1.23-1.81-3.83-3.64-7.65-5.44M -11.48-.23-.49-.37-1.02-.52-1.54-.03-.08,.08-.21,.18-.28,.07-.05,.24-.09,.31-.06,.92,.43,1.86,.84,2.74,1.33,13.51,7.51,27.25,14.99,41.35,21.45,.14-.28,.38-.51,.31-.64-.43-.9-.92-1.79-1.41-2.67-1.99-3.53-3.99-7.06-5.96-10.6-.07-.14,.12-.38,.23-.55,.97-.06,1.93,.72,2.82,1.08,11.34,5.92,23.38,10.94,34.99,16.51,.03,.02,.06,.05,.08,.08l.03-.17-.11,.09c1.07-.97-.3-2.12-.75-3.06,10.12,3.75,20.6,6.32,31.31,7.74,1.95,2.73,4.48,5.35,6.04,8.21Z"/><path class="cls-2" d="M435.53,804.31c-3.94-.61-7.94-2.07-11.8-3.21,3.22,.09,6.4M 5,.08,9.69-.04,.27,.59,3.01,2.98,2.11,3.25Z"/><path class="cls-2" d="M472.16,741.92c-4.82,.44-9.61-1.16-14.36-1-.07,.71,.46,1.22,.9,1.75,2.59,3.17,5.2,6.34,7.79,9.5-3.79,1.55-7.61,2.84-11.45,3.89-.4,.04-1.21-.27-1.27,.33-5.03,1.33-10.09,2.24-15.15,2.77-1.55-1.94-3.11-3.88-4.66-5.82-.42-.53-1.01-1.03-.87-1.74,.76-.27,1.5-.02,2.23,.14,4.14,.93,8.27,1.89,12.41,2.81,1.38,.17,2.88,.91,4.24,.47,0-.7-.55-1.19-.98-1.73-3.87-5.24-8.52-10.04-11.86-15.6,.64-.28,1.16-.17,1.68-.05,4.78,1.11,9.62,2,14.53,2.65,.25,0,.92-.02,.85-.M 41-.33-.57-.64-1.16-1.04-1.71-3.65-5.01-7.52-9.9-11.05-15-.47-.6,0-1.14,.7-.99,5.01,.73,10,1.52,15,2.25,4.11,5.3,8.21,10.6,12.32,15.9,.38,.53,1,1.23,.04,1.59Z"/><path class="cls-2" d="M266.44,990.81v-.15s.09,.02,.13,.03l-.13,.12Z"/><path class="cls-2" d="M410.43,983.7s-.03-.07-.05-.11c.05,0,.09,.01,.14,.01l-.09,.1Z"/><path class="cls-2" d="M461.99,972.56c.05,.13-.2,.46-.36,.48-4.28,.27-8.61-.21-12.89-.32-14.26-.52-28.43-1.96-42.6-3.4-1.3-.15-1.81,.28-1.28,1.58,1.83,4.23,3.68,8.46,5.52,12.69-22.77-1.96-45.35-5.54-67M .85-9.39-.9-.04-.8,.95-.64,1.54,1.32,4.28,2.81,8.51,3.81,12.88,.11,.43,.03,.85-.5,1.25-26.4-4-52.52-9.83-78.38-16.23-.63-.1-1.72-.5-2.11,.16,.15,1.28,.31,2.56,.55,3.83,.95,4.31,1.34,8.64,1.18,13.03-32.14-7.51-63.69-16.32-94.88-26.23-1.3-.38-1.37,.87-1.3,1.75-.03,5.46,.62,11.06-.15,16.45-1.09,.8-2.91-.3-4.06-.55-37.24-11.24-73.91-24.11-110.08-38.08-.74-.32-1.24-.77-1.23-1.53,.03-1.72-.01-3.45-.01-5.17,.06-5.05-.19-10.11,.1-15.15,.94-.44,1.8,.16,2.68,.44,35.81,14.46,71.62,28.14,108.55,40.05,1.04,.13,3.77,1.85,3.98,.1M -.63-5.9-1.29-11.8-1.91-17.7-.04-.42,.61-.82,1.07-.68,30.46,10.39,61.22,19.94,92.54,27.96,.66,.21,2.21,.6,2.23-.41-.33-1.7-.66-3.4-1.03-5.09-.06-1.53-3.45-11.74-1.51-11.46,25.1,6.65,50.32,12.95,75.9,17.83,.91,.18,1.85,.29,2.78,.42,1.07,.01,.62-1.23,.47-1.87-1.43-4.26-2.88-8.52-4.32-12.78-.2-.61,.34-1.09,1.06-.97,21.34,4.26,42.8,8.17,64.43,10.75,1.67,.16,2.04-.14,1.52-1.34-1.72-4.21-4-8.19-5.48-12.5,.51-.08,.91-.24,1.27-.19,5.85,.73,11.69,1.55,17.55,2.23,5.1,.6,10.22,1.04,15.32,1.53,9.61,4.31,19.38,8.42,29.31,12.31,M .31,.57,.55,1.17,.75,1.78Z"/><path class="cls-2" d="M1192.65,222.76c-18.63,.68-37.07,1.81-55.69,3.23-.13-1.59,1.21-2.37,1.98-3.58,3.41-4.39,6.83-8.78,10.23-13.18,.42-.55,.79-1.12,1.17-1.69,.14-.2-.35-.68-.67-.66-14.87,1.1-29.68,2.83-44.52,4.35-.67,.07-1.33,.2-1.99,.26-.74,.06-1.74,.54-2.16-.1-.39-.6,.49-1.16,.95-1.67,4.63-5.16,9.29-10.31,13.93-15.48,.34-.56,2.1-1.97,1.18-2.36-14.92,1.03-29.73,4.04-44.61,5.64-.21-1.1,1.07-1.74,1.67-2.54,5.29-5.31,10.6-10.61,15.89-15.91,.64-.85,2.18-1.67,1.95-2.79-12.6,1.28-25.18,3.5M 1-37.65,5.66-5.12,.95-3.25-.36-.68-2.87,6.27-5.92,12.56-11.82,18.83-17.74,.61-.57,1.16-1.18,1.72-1.79,.07-.07,.07-.25,0-.31-.15-.13-.39-.32-.55-.3-2.91,.43-5.82,.87-8.72,1.34-8.44,1.39-16.87,2.8-25.31,4.18-1.04,.17-2.1,.44-3.18,.13l.08,.08c0-.2-.12-.47,0-.6,.65-.68,1.34-1.35,2.06-1.99,7.95-7.04,15.9-14.07,23.85-21.1,.63-.52,1.28-.97,1.34-1.83-11.34,1.1-22.76,3.34-34.07,5.03-1.55,.09-.59-.77,0-1.42,10.19-8.92,20.68-17.54,30.83-26.5,.76-1.36-2.35-.63-3.02-.65-6.91,.92-13.81,1.87-20.71,2.8-2.39,.32-4.78,.62-7.18,.9-.2M ,.02-.55-.11-.61-.24-.06-.92,1.47-1.59,2.04-2.25,10.58-8.76,21.16-17.51,31.74-26.27,3.65-2.97,5.33-3.99-.91-3.36-8.03,.68-16.07,1.37-24.11,1.98-.47,.03-.49-.52-.37-.7,4.02-3.52,8.29-6.77,12.42-10.17,9.79-7.86,19.6-15.72,29.4-23.58,2.63-2.11,2.11-1.87,5.62-1.87,7.75-.01,15.42,0,23.19,0,0,.4,.15,.79-.03,.96-.77,.74-1.63,1.43-2.48,2.12-11.37,9.19-22.75,18.38-34.12,27.58-.94,.76-1.82,1.58-2.69,2.4-.07,.06,.13,.4,.3,.5,9.45-.07,19.03-1.5,28.52-1.75,.02,.22,.15,.49,.03,.62-.57,.6-1.17,1.18-1.82,1.72-9.14,7.62-18.3,15.23-M 27.44,22.85-1.68,1.4-3.32,2.82-4.95,4.26-.13,.12-.08,.4-.06,.59,.54,.26,1.35,.07,1.96,.07,6.26-.74,12.51-1.53,18.78-2.24,3.47-.39,6.95-.67,10.43-.98,.2-.02,.54,.11,.63,.25,.22,.84-1.13,1.46-1.61,2.06-3.83,3.33-7.67,6.66-11.49,9.99-5.01,4.37-10.01,8.74-15.01,13.11-.81,.56-1.27,1.54,.16,1.4,11.4-1.24,22.82-3.79,34.23-4.22,.5,.5-.93,1.43-1.29,1.85-5.96,5.42-11.93,10.84-17.87,16.27-1.86,1.7-3.66,3.45-5.46,5.19-.12,.12-.04,.39,.01,.58,.01,.06,.23,.1,.36,.11,10.38-.97,20.72-2.75,31.09-4.01,2.29-.17,4.84-1.05,7.06-.5,.07,M .09,.14,.25,.09,.31-.46,.53-.92,1.06-1.43,1.56-5.77,5.69-11.56,11.37-17.33,17.06-.76,.75-1.5,1.52-2.2,2.31-.12,.13-.02,.4-.02,.64,9.74-.57,19.38-2.67,29.12-3.53,4.27-.46,8.54-.91,12.82-1.34,.17-.02,.4,.18,.55,.31,.06,.06,.05,.23-.01,.31-.51,.63-1,1.27-1.56,1.88-4.65,5.02-9.31,10.03-13.96,15.06-.72,.77-1.36,1.59-1.99,2.41-.06,.08,.2,.47,.31,.47,8.31-.17,16.53-1.84,24.83-2.38,6.96-.63,13.92-1.24,20.89-1.86,.56-.05,1,.13,.95,.37-.19,1.24-1.38,2.07-2.06,3.08-3.71,4.62-7.42,9.25-11.12,13.88-.72,1.03-2.31,2.58,.14,2.4,16M .89-1.22,33.83-2.68,50.76-2.94,.54,.25,.21,1-.08,1.39-3.81,5.94-7.63,11.88-11.44,17.81l.1-.06Z"/><path class="cls-2" d="M1093.82,419.36c26.96,2.92,53.78,7.54,80.34,12.8,1.05,.06,1.15-.95,1.41-1.68,1.1-4.1,2.18-8.21,3.28-12.32,.41-1.51,.84-1.71,2.84-1.35,1.31,.23,2.62,.48,3.93,.74,29.5,5.66,58.59,12.67,87.56,20.46,.34,.08,.92-.15,.98-.39,.25-1.05,.55-2.1,.72-3.17,.66-4.17,1.27-8.34,1.92-12.5,.21-.66,.22-1.8,1.11-1.89,36.82,9.24,73.52,19.99,109.19,32.58,.42,6.58,.04,13.19,.15,19.79-.04,.73-.02,1.88-1.09,1.71-12.02-4.M 01-23.89-8.44-35.95-12.42-24.57-8.24-49.42-16.1-74.6-22.96-1.93-.46-1.55,2.12-1.96,3.28-.66,4.92-1.72,9.8-1.86,14.76l.13-.06c-30.73-8.71-61.71-17.02-93.09-23.57-2.6-.34-3.85-1.34-3.79,2.11-.07,4.41,.28,8.83-.09,13.23-.41,.82-1.75,.42-2.49,.33-3.12-.68-6.22-1.39-9.33-2.07-22.24-4.85-44.77-8.94-67.37-11.93-.87-.06-1.31,.62-1.22,1.33,.21,4.52,.13,9.05,.93,13.54l.12-.09c-20-2.58-40.03-5.45-60.18-6.86-2.27-.17-4.55-.22-6.83-.31-.49-.02-.98,.42-.97,.84-.03,4.46,1.57,8.74,3.16,12.89l.1-.09c-19.69-1.39-39.43-2.95-59.18-2.4M 6-.27-4.03-2.12-7.93-2.34-11.96,.78-.57,1.62-.49,2.41-.52,18.16-.71,36.3,.11,54.44,.82,.52,.02,.99-.41,.93-.85-.25-4.28-1.65-8.55-1.07-12.83l-.13,.1c20.82,1.31,41.68,2.71,62.36,5.5,1.34-.1,6.07,1.47,6-.48-.11-4.72-.22-9.44-.33-14.15l-.13,.09Z"/><path class="cls-2" d="M138.69,233.83c.3-.5,.32-1.03,.29-1.58-.25-3.87-.51-7.74-.75-11.61-.36-5.91-.71-11.82-1.05-17.74-.24-3.14,1.52-1.37,3.05-.48,7.52,5.08,14.75,11.03,22.51,15.56,.26-.19,.61-.39,.55-.75-.37-12.24-1.26-24.55-1.11-36.77,.11-.44,.97-.37,1.34-.12,7.72,4.07,15M .13,8.76,22.97,12.57,1.12,.11,.73-1.74,.87-2.47-.04-5.27-.14-10.55-.15-15.82,.07-8.38-.17-16.78,.16-25.15,1.09-.4,2.07,.23,3.1,.52,4.37,1.67,8.73,3.36,13.08,5.05,.85,.33,1.67,.71,2.52,1.03,5.07,1.93,6.02,2.2,6.25,1.78,.89-1.63,.48-3.38,.56-5.07,.44-14.84,.97-29.72,2.1-44.51,.05-.25,.55-.59,.87-.55,1.06,.13,2.13,.22,3.17,.42,7.14,1.47,14.38,2.6,21.46,4.31,.45,1.12,.19,2.14,.15,3.29-.45,6.34-.95,12.68-1.36,19.02-.99,11.01-.68,22.67-2.28,33.5h0c-.18-.27-.28-.67-.56-.78-2.29-.92-4.59-1.8-6.92-2.66-5.42-1.95-10.74-4.03-M 16.21-5.85-.94,.94-.66,2.25-.74,3.47-.21,14.53-.15,29.08-.38,43.61-.01,.25-.62,.56-.88,.44-.82-.37-1.66-.71-2.43-1.13-6.13-3.33-12.24-6.68-18.36-10.01-.77-.24-2.41-1.72-2.98-.63,.34,11.51,.46,23.04,1.16,34.54,.14,2.03,.06,4.08,.05,6.12,0,.1-.46,.33-.58,.29-8.07-4.81-15.41-10.88-23.39-15.85-1.33-.42-1.01,1.02-1.08,1.84,.23,3.98,.4,7.96,.71,11.94,.47,7.1,.93,14.19,1.37,21.29,.02,.29-.18,.59-.32,.87-.03,.07-.3,.14-.36,.11-.53-.33-1.07-.65-1.53-1.03-5.65-4.62-11.27-9.26-16.93-13.88-2.07-1.69-3.96-3.52-6.32-4.98-.12-.07M -.56,.03-.69,.15-.39,.95-.04,2.17-.07,3.2,.67,9.14,1.36,18.27,2.19,27.4-.11,2.2-2.12-.11-2.96-.83-7.97-7.3-15.89-14.65-23.84-21.96-.44-.61-1.61-.58-1.48,.35,.41,7.75,1.2,15.47,1.75,23.21,.08,1.07,.07,2.15,.1,3.22,0,.28-.16,.42-.49,.4-9.66-8.58-18.42-18.56-27.77-27.62-.63-.52-1.12-1.44-2.07-1.25-.07,0-.19,.14-.19,.22,0,.86-.01,1.72,.04,2.57,.33,6.88,.96,13.76,1.15,20.65-.28,1.05-1.56-.24-1.95-.65-9.92-10.61-19.83-21.22-29.74-31.84-.88-.88-1.84-1.88-1.74-3.17,0-2.48-.06-4.95-.08-7.43-.02-3.45-.02-6.89,0-10.34-.11-3.6M 2,1.65-1.62,3.14-.14,9.35,9.17,18.37,18.67,27.9,27.65,.83,.57,1.09-.56,1.04-1.18-.1-2.48-.22-4.95-.33-7.43-.2-4.52-.4-9.04-.59-13.56,.03-.63-.15-1.41,.58-1.7,.07-.04,.27-.03,.34,.03,9.46,7.98,18.09,16.87,27.44,24.99,.11,.1,.47,.04,.7,.01,.32-.23,.25-.84,.28-1.2-.36-8.92-1.46-17.85-1.56-26.76,.96-.44,1.57,.42,2.29,.88,7.63,6.24,15.24,12.49,22.86,18.73,.69,.48,1.3,1.28,2.24,1.14l.04,.13-.13-.06Z"/><path class="cls-2" d="M1203.01,1271.97c5.12,1.91,10.24,3.83,15.37,5.73,2.69,1,5.39,1.97,8.08,2.95,.92,.34,1.49,.02,1.51-M .87,.38-14.54,.29-29.08,.32-43.63-.14-3.81,.66-2.85,3.38-1.57,6.35,3.45,12.69,6.91,19.03,10.38,.65,.31,1.27,1.04,2.1,.6,.74-.39,.38-1.18,.38-1.79-.05-6.14-.45-12.28-.63-18.41-.01-6.89-.7-13.78-.74-20.66,.05-.33,.74-.35,.93-.28,7.61,4.89,14.89,10.28,22.39,15.35,.39,.27,.75,.62,1.34,.58,.38,0,.53-.46,.54-.75-.25-4.63-.5-9.25-.79-13.88-.41-6.56-.85-13.12-1.27-19.69,.08-.57-.29-1.63,.54-1.7,.92,.14,1.67,1.05,2.44,1.54,5.18,4.24,10.34,8.49,15.51,12.74,2.26,1.85,4.52,3.69,6.81,5.52,.12,.1,.48,.03,.71,0,.15-.08,.25-.4,.25M -.58-.22-3.55-.43-7.1-.67-10.65-.58-6.44-1.05-12.9-1.56-19.35-.08-1.84,1.07-1.02,1.94-.22,8.51,7.79,16.9,15.68,25.5,23.37,.13,.11,.5,.07,.76,.06,.1-.06,.22-.43,.19-.59-.61-7.96-1.32-15.91-1.94-23.86-.14-2.75-.61-4.83,2.37-1.76,9.28,8.95,17.93,18.94,27.55,27.35,.2-.11,.5-.27,.5-.4-.09-3.12-.21-6.24-.35-9.36-.2-4.52-.42-9.04-.6-13.56,0-.14,.31-.3,.5-.41,10.57,10.18,20.34,21.73,30.61,32.4,1.16,1.01,1.81,2.3,1.6,3.85,0,5.82,0,11.64,0,17.45,0,.52,.11,1.07-.33,1.53-.07,.07-.31,.15-.36,.11-.5-.34-1.04-.66-1.44-1.06-3.57-3M .51-7.14-7.02-10.68-10.55-5.47-5.47-10.91-10.95-16.38-16.43-.69-.54-1.17-1.4-2.19-1.07,.11,7.85,.73,15.7,.98,23.55,.01,.25-.16,.4-.49,.43-1.71-.43-2.84-2.26-4.23-3.3-7.49-6.93-14.97-13.87-22.45-20.8-.6-.43-1.62-1.97-2.31-1.02,.09,9.14,1.32,18.27,1.5,27.42-.32,1.27-1.67,.03-2.22-.44-7.43-6.1-14.86-12.19-22.29-18.29-2.48-2.03-3.41-2.72-3.04,1.24,.44,9.81,1.89,19.93,1.42,29.61-.93,.26-1.61-.55-2.34-.96-7.27-5.15-14.51-10.32-21.82-15.4-.27-.19-.69-.25-1.05-.35-.1-.02-.33,.06-.34,.11-.1,.42-.22,.84-.21,1.27,.3,10.23,.74M ,20.46,1.09,30.69,.06,1.72,.03,3.44,.03,5.15,0,.24-.67,.53-.92,.42-.24-.1-.49-.18-.71-.3-7.01-3.81-13.94-7.74-20.91-11.62-3.25-1.94-2.59-.21-2.72,2.46,.07,13.38,.42,26.75-.04,40.12-2.37,.15-4.46-1.37-6.7-2.01-5.1-1.95-10.2-3.91-15.3-5.86-.9-.17-2.55-1.37-3.11-.22-1.19,16.54-.63,33.3-2.63,49.75-8.64-.64-17.03-3.36-25.61-4.56l.08,.08c.79-18.57,2.79-37.09,3.24-55.69l-.14,.06Z"/><path class="cls-2" d="M1011.12,826.86c-3.33-8.9-6.1-18.19-10.29-26.77-1.32-.23-13.43-2.43-12.91-.58,2.81,7.77,5.96,15.41,8.61,23.21,.4,1.13,.M 75,2.29,1.11,3.43,.12,.41-.18,.86-.69,1.05-3.86,1.23-7.44,3.16-11.18,4.45-.82,0-.95-.88-1.2-1.47-1.87-5.28-3.69-10.58-5.61-15.85-1.05-2.89-2.23-5.75-3.37-8.63-.49-.89-1.7-.33-2.36,.08-2.88,1.78-5.73,3.57-8.6,5.36-.3,.19-.82,.06-.97-.25-3.16-6.97-5.75-14.16-9.09-21.05-.22-.48-.39-1.02-1.21-1.32-2.48,1.43-4.5,3.64-6.76,5.41-.84,.46-2.27,2.73-3.19,1.83-3.42-6.25-6.23-12.86-9.8-19.02-.76-.03-1.12,.25-1.44,.6-1.65,1.84-3.3,3.67-4.96,5.51-.8,.59-1.81,2.9-2.93,2.05-3.29-5.27-5.99-10.89-9.43-16.06-1.17-1.2-4.3,4.94-5.23,5.M 86-.24,2.83-.35,5.67-.34,8.52,2.4,4.32,4.53,8.57,7.06,12.84,3.03-2.74,4.89-6.3,7.72-9.22,.2-.24,.82-.18,.99,.1,3.28,6.02,5.75,12.51,8.85,18.64,.72,.06,1.08-.22,1.41-.56,1.36-1,7.65-8.93,8.71-7.34,3.25,6.67,5.73,13.67,8.51,20.53,.17,.42,.43,.76,1.15,.94,2.8-2.09,5.71-4.21,8.57-6.26,.41-.31,1.29-.72,1.74-.35,3.24,7.33,5.29,15.13,8.05,22.65,.29,.83,.62,1.64,.99,2.45,.06,.12,.5,.24,.68,.18,3.38-1.48,6.61-3.33,9.93-4.94,.47-.23,.95-.39,1.62-.26,3.17,9.87,6.47,19.93,8.39,30.07,4.53-1.53,9.18-2.78,13.64-4.47-2.46-9.85-5.7M 2-19.45-8.63-29.18-.22-.7-.47-1.82,.65-1.81,3.86,.22,7.61,1.38,11.45,1.84,1.18-.1,.51-1.5,.36-2.21Zm-3.83,31.36s.01,.03,.01,.04l.1-.1s-.08,.04-.11,.06Zm-6.49-58.18s.02,.03,.03,.05c.02,0,.05,0,.07,.01l-.1-.06Zm-7.28,62.69l.13,.05v-.09s-.09,.03-.13,.04Zm-126.63-98.99c-.89-1.08-1.71-2.26-2.57-.67-1.41,3.47-2.5,7.08-4.09,10.47-.77,.88-1.62-.69-2.18-1.16-1.96-2.19-3.9-4.39-5.85-6.59-.39-.43-.77-.89-1.6-1.07-1.08,1.26-1.24,3-1.81,4.52-.85,2.6-1.72,5.19-2.56,7.73-.77,.08-1.17-.17-1.51-.53-2.33-2.39-4.56-4.86-7.11-7.03-1.1M 8-.54-1.3,1.32-1.66,2.05-.89,3.04-1.74,6.08-2.64,9.12-.17,.6-.26,1.27-1.01,1.65-.74-.11-1.1-.6-1.54-1-1.69-1.53-3.38-3.07-5.07-4.6-.58-.6-2.01-1.53-2.42-.42-1.15,4.22-2.38,8.39-3.61,12.59-.14,.48-.73,.66-1.23,.37-2.82-1.41-5.01-3.44-8.12-4.34-.51,.46-.68,1.08-.86,1.69-1.15,4.14-2.33,8.42-3.66,12.47-.73,.2-1.21,0-1.66-.23-2.63-1.27-4.97-3-7.86-3.75-1.44,4.64-2.88,9.28-4.33,13.91-.26,.81-.95,1.05-1.79,.67-1.99-.9-3.96-1.82-5.95-2.71-.52-.23-1.34-.53-1.81-.09-2.27,4.51-3.25,9.59-5.48,14.12-.15,.27-.64,.39-1.02,.24-2.1M 5-.92-4.29-1.78-6.47-2.63-1.61-.62-1.88-.51-2.52,.98-1.98,4.49-3.45,9.13-5.83,13.44-3.12-.91-5.84-2.33-8.99-3.12-2.88,4.3-4.71,9.18-7.18,13.73-.15,.31-.15,.6,.26,.81-3.67,.09-6.84-2.41-10.42-2.95-.01,.01-.02,.03-.02,.04-2.98,5.02-6.88,9.6-10.66,14.32-3.27-1.27-6.38-2.23-9.27-3.52,0-.88,.73-1.4,1.2-2.01,3-4.05,6.41-7.84,9.13-12.08-.02,0-.04-.01-.06-.02-3.27-.81-6.47-1.77-9.78-2.73,.33-1.85,1.53-3.28,2.28-4.83,1.53-3.05,3-6.12,4.37-9.24-2.6-.53-5.2-1.06-7.8-1.59-1.13-.21-2.98-.87-3.5,.43-2.03,4.04-3.93,8.24-6.26,12.1M 2-.43,.06-.71,.17-.95,.13-3.25-.65-6.48-1.36-9.56-2.3-.05-.2-.13-.32-.09-.4,1.86-4.37,4.24-8.59,6.3-12.9-3.22-.69-6.46-1.39-9.68-2.1-1.78-.45-.49-2.01-.19-3.05,1.44-3.41,2.48-6.99,4.19-10.27,.01-.03,.03-.07,.05-.1-3.54-.61-7.07-1.23-10.6-1.84-.79-.14-1.32,.1-1.56,.69-1.1,2.76-2.19,5.52-3.3,8.27-.69,1.14-.77,3.37-2.48,3.34-3.55-.62-7.09-1.32-10.51-2.47,1.36-4.24,3.87-8.1,4.92-12.42,0-.03,.01-.07,.02-.1-.02,0-.04-.01-.06-.01-3.46-.75-6.92-1.48-10.37-2.24-.73-.16-1.05-.69-.87-1.24,1.15-3.51,2.29-7.03,3.47-10.53,.1-.3,M .4-.55,.6-.82-2.47-.85-5.11-1.28-7.67-1.87-4.63-1.08-4.25-1.52-5.62,2.42-.87,2.48-1.86,4.94-2.84,7.38-.37,1.01-.13,1.44,1.02,1.74,2.68,.69,5.38,1.34,8.06,2.03,.7,.3,1.99,.31,2.15,1.17-1.1,3.95-3.35,7.46-4.86,11.31,3.4,1.76,7.62,1.94,11.14,3.31,.23,.65-.03,1.14-.3,1.64-1.38,2.56-2.76,5.11-4.14,7.67-.26,.87-1.81,2.2-.7,2.9,3.57,1.23,7.33,1.93,10.97,2.95,2.02-3.71,4.25-7.35,5.93-11.18,.47-1.06,1.01-1.23,2.51-.93,3.2,.64,6.23,1.15,9.39,2.09-1.58,4.2-3.96,7.99-5.81,12.08-.19,.38,.11,.94,.57,1.06,2.98,.76,6.17,1.54,9.07,M 2.28,.34,.71-.02,1.17-.36,1.64-2.53,3.88-6.13,7.07-8.77,10.91,2.94,1.37,6.22,1.91,9.32,2.89,1.81,.63-1.14,2.57-1.63,3.38-2.81,2.88-5.64,5.74-8.46,8.62-.69,.7-.58,1.16,.36,1.5,3.05,.92,6.02,2.61,9.14,3.06,3.94-4.08,7.98-8.08,11.58-12.37,.2-.23,.61-.35,.95-.54,3.04,.97,6.1,1.8,8.9,2.94,.27,.53,.12,.92-.2,1.29-3.63,4.19-7.21,8.34-11.03,12.39,.26,.29,.41,.64,.72,.77,2.76,1.23,5.51,2.16,8.18,3.65-4.26,5.02-9.62,9-14.2,13.67,1.75,1.42,5.26,3.34,8.63,4.74,.72-.12,1.08-.61,1.52-.99,4.6-4.09,8.92-8.35,12.84-12.8-.14-.53-.52M -.81-1-1.04-2.25-1.15-4.67-2.09-6.81-3.44-.62-.69,.74-1.6,1.1-2.22,3.33-3.78,6.71-7.53,10-11.35,.48-.54,1.06-.7,1.73-.47,2.75,1.12,5.81,1.83,8.06,3.68-3.79,4.74-7.96,9.2-11.96,13.77-.32,.36-.21,.89,.24,1.14,2.34,1.27,4.68,2.54,7.01,3.81,.86,.56,1.61-.39,2.14-.95,3.98-4.54,7.87-9.04,11.86-13.58,2.97,1.17,5.26,3.05,8.16,4.41,4.09-4.81,7.36-10.26,11.19-15.27,2.2,.5,3.49,1.96,5.38,2.93,.85,.48,1.47,1.29,2.67,1.32,.8-.49,1.07-1.23,1.43-1.9,2.12-3.96,4.24-7.92,6.35-11.88,.26-.5,.44-1.02,1.08-1.32,.87,.04,1.41,.55,2.01,.9M 5,1.66,1.1,3.28,2.23,4.92,3.34,.31,.21,.82,.12,1.02-.16,2.67-4.73,4.77-9.84,7.21-14.72,.09-.18,.02-.42,.02-.83-2.26-1.47-4.65-3.02-7.25-4.36-.42-.21-1.14,0-1.34,.4-2.24,4.58-4.05,9.4-6.42,13.92-.24,.41-.91,.61-1.34,.37-2.01-1.08-4.01-2.17-6.01-3.27-.46-.25-.93-.41-1.64-.29-2.62,4.86-4.71,9.99-7.9,14.68-.39,0-.72,.08-.91-.01-2.41-1.18-4.8-2.38-7.19-3.58-.45-.23-.5-.62-.22-1.16,2.36-4.46,4.72-8.92,7.08-13.38,.23-.55,.92-.86,1.58-.61,2.57,.9,5,2.64,7.65,3.12,2.76-4.44,4.17-9.73,6.61-14.38,.13-.25,.74-.47,1.01-.35,2.61M ,1.14,5.14,2.26,7.68,3.58,.72-.5,1.01-1.08,1.23-1.69,1.69-4.38,3.15-8.9,5.02-13.19,.72-.15,1.18,.08,1.61,.32,2.26,1.15,4.37,2.59,6.71,3.57,.16,.05,.59-.08,.65-.21,2.08-4.37,3.21-9.1,4.82-13.65,.2-.6,.92-.81,1.56-.43,2.39,1.37,4.71,2.89,7.11,4.23,.15,.08,.62-.01,.68-.11,2.03-4.4,2.96-9.14,4.55-13.78,.42,.04,.93-.04,1.12,.12,1.9,1.68,3.74,3.39,5.61,5.08,.9,.79,2,2.06,2.6,.22,1.44-4,2.19-8.31,4.01-12.14,.65-.48,1.35,.36,1.8,.75,1.8,1.88,3.58,3.78,5.36,5.67,.4,.42,.73,.92,1.65,.99,1.85-4.11,2.83-8.45,4.44-12.6,.66-.21,M 1.08-.01,1.4,.37,2.38,2.72,4.53,5.66,7.1,8.22,.12,.11,.48,.06,.82,.09,6.21-14.36,2.26-16.11,12.74-2.51-.09-6.32,.24-12.6,.98-18.81-.65-.8-1.3-1.61-1.94-2.41Zm-152.59,72.32c-3.02,4.09-6.28,8.02-9.39,12.04-.42,.53-1,.68-1.74,.45-2.87-.89-5.82-1.64-8.93-2.84,2.84-3.89,5.78-7.4,8.7-11.21,.62-.7,1.11-1.79,2.26-1.51,2.99,.62,5.97,1.29,8.83,2.23,.32,.11,.45,.53,.27,.84Zm38.33,13.2c-2.98,4.68-6.25,9.24-9.65,13.74-.38,.51-1.07,.64-1.72,.34-2.3-1.1-4.6-2.21-6.9-3.31-.42-.21-.52-.76-.22-1.15,1.53-2.01,3.11-4.01,4.59-6.05,2.29M -2.75,3.56-6.27,6.43-8.46-.8,1.44,8.62,3.12,7.47,4.89Zm43.55-54.27s.06,.01,.09,.02c.02-.05,.03-.1,.05-.15l-.14,.13Zm-104.01,67l-.03,.03s.07-.02,.09-.03h.01s-.05-.01-.07,0Zm-21.26-37.4s-.03,.05-.04,.08l.09-.07s-.03-.01-.05-.01Z"/><path class="cls-2" d="M169.9,1258.03c.04-.86,0-1.73,.46-2.5,3.02-5.89,5.45-12.19,8.82-17.86l-.09,.06c17-.83,34.21-.58,51.28-1.29,.9,.2,5.82-.82,4.89,.97-3.54,5.45-7.16,10.86-10.72,16.3-.34,.7-1.44,1.78-.22,2.19,12.9-.1,25.8-1.36,38.69-2.1,3.21-.1,6.44-.78,9.63-.49,.94,.41-.76,1.87-1.06,2.4M 4-4.48,5.64-9.16,11.14-13.54,16.85-.18,.24,.14,.73,.47,.72,13.96-.55,27.84-2.36,41.73-3.78,3.62-.41,.91,1.49-.15,2.89-5.18,5.51-10.39,11.01-15.57,16.52-.27,.45-2,2-.84,2.1,13.28-.94,26.49-3,39.7-4.09-.25,1.41-1.68,2.15-2.58,3.19-6.58,6.42-13.26,12.74-19.78,19.22-.54,.65,.15,1,.81,.88,11.63-.97,23.17-2.82,34.79-3.91,1.38,.21-1.43,2.26-1.8,2.7-7.61,6.84-15.23,13.68-22.84,20.52-.62,.56-1.18,1.17-1.75,1.76-.07,.07-.08,.25-.01,.3,.16,.13,.38,.32,.56,.31,1.74-.15,3.48-.33,5.21-.5,7.09-.69,14.18-1.37,21.26-2.06,3.26-.26,8M .77-2.01,3.16,2.39-9.18,7.88-18.44,15.71-27.6,23.62-.51,.44-1.5,.84-1.04,1.57,.32,.5,1.21,.26,1.84,.22,8.99-.41,17.98-1.6,26.97-1.65,.49,.38-.15,1-.53,1.29-12.28,10.02-24.38,20.24-36.77,30.14-8.15,.4-16.39,.05-24.56,.17-.57-.03-2.05,.11-2.13-.5,.21-1.12,1.58-1.68,2.33-2.51,6.37-5.41,12.76-10.82,19.13-16.23,3.6-3.06,7.2-6.12,10.8-9.18,.38-.32,.7-.65,.51-1.14-9.47,0-19.05,1.28-28.56,1.52-.68-.05-1.18-.25-.5-1.06,8.36-7.64,16.89-15.1,25.3-22.67,.47-.62,3.8-2.76,1.98-3.08-10.72,.88-21.39,2.15-32.14,2.66-.12,0-.33-.05-.M 35-.11-.06-.19-.16-.46-.05-.59,.54-.62,1.11-1.21,1.72-1.79,6.49-6.19,12.99-12.38,19.49-18.57,.69-.87,4.11-3.08,1.2-3.09-7.37,.49-14.72,1.37-22.08,2.01-4.42,.19-9.37,1.43-13.69,.97,.42-1.65,2.16-2.66,3.2-4,4.95-5.24,9.92-10.48,14.86-15.73,.56-.81,1.76-1.43,1.61-2.49-13.51,.92-27.03,2.62-40.6,3.21-1.14-.24-.4-.97,0-1.5,5.07-6.23,10.44-12.25,15.35-18.61,.19-.26-.12-.74-.47-.73-5.65,.04-11.26,.76-16.9,1.09-9.27,.53-18.54,1.17-27.83,1.48-.73,.02-1.09-.55-.72-1.14,.85-1.34,1.71-2.69,2.6-4.02,2.48-3.7,4.97-7.4,7.45-11.1,1M .02-1.9,3.85-4.25-.37-3.88-12.26,.38-24.51,.86-36.77,1.01-3.77,.04-7.55,.15-11.32,.24-.67,.01-1.35,.02-1.89,.42l.03,.02Z"/><path class="cls-2" d="M1262.17,202.07c-11.54,.6-23.17,.35-34.74,.71-6.06,.12-12.12,.37-18.18,.55-1.07,.03-2.15-.02-3.22-.09-.14,0-.4-.37-.34-.49,3.56-6.33,8.13-12.09,11.78-18.37,.14-.25-.22-.72-.54-.72-13.44,.4-26.87,1.48-40.3,2.34-2.68,.18-5.35,.55-8.05,.54-1.51-.28,.52-1.96,.86-2.62,4.23-5.25,8.47-10.5,12.7-15.75,.36-.44,.64-.93,.88-1.42,.05-.1-.24-.32-.42-.46-14.42,.88-28.9,2.52-43.31,3.87-M 1.14-.09,.65-1.68,.89-2.09,5.17-5.52,10.36-11.02,15.53-16.54,.72-.77,1.37-1.59,2.01-2.4,.06-.08-.14-.39-.31-.47-12.9,.93-25.93,2.54-38.79,4.18-2.48,.32-.45-1.45,.35-2.24,6.97-6.86,14.14-13.52,20.99-20.5,.21-.28-.31-.66-.5-.68-11.08,1.15-22.14,2.48-33.2,3.8-.86,.1-1.74,.64-2.6-.02,.03-.87,.93-1.28,1.53-1.82,7.87-7.09,15.76-14.17,23.63-21.26,.62-.56,1.15-1.18,1.7-1.78,.06-.06,0-.22-.06-.31-.61-.38-1.56-.12-2.27-.15-8.29,.82-16.57,1.64-24.86,2.48-2.89,.08-8.69,2.08-3.27-2.17,9.61-8.29,19.4-16.41,28.87-24.87,.11-.1,.01M -.38-.04-.57-.26-.21-.77-.17-1.11-.19-8.6,.37-17.19,1.18-25.78,1.71-.64,.04-1.3-.05-1.95-.1-.05,0-.12-.21-.09-.3,11.83-10.78,24.86-20.68,37.25-30.96,8.2-.26,16.42-.04,24.63-.11,.73,.06,1.64-.18,2.12,.49,.05,.06,.02,.22-.04,.28-.59,.58-1.15,1.18-1.79,1.73-4.05,3.46-8.12,6.91-12.19,10.36-5.64,4.78-11.28,9.57-16.9,14.36-.85,.74-2.92,2.37-.41,2.23,6.59-.37,13.17-.75,19.76-1.13,2.67-.05,5.38-.61,8.04-.38,1,.42-.97,1.78-1.35,2.28-8.73,7.93-17.69,15.62-26.28,23.69-.22,.3,.36,.64,.54,.66,10.88-.68,21.73-2.31,32.61-2.61-.12M ,.35-.11,.71-.33,.94-1.16,1.19-2.37,2.34-3.58,3.5-5.97,5.7-11.96,11.39-17.92,17.09-.69,.66-1.33,1.35-1.95,2.05-.1,.12,.05,.38,.11,.65,11.24-.67,22.45-2.23,33.69-3.05,5.43-.64,2.21,1.41,.31,3.69-5.52,5.98-11.34,11.72-16.68,17.86-.07,.31,.06,.74,.54,.68,11.79-.91,23.55-2.23,35.36-2.98,3.9-.09,7.65-1.77,3.09,3.19-4.02,4.85-8.05,9.69-12.07,14.54-.59,.72-1.16,1.45-1.68,2.2-.11,.15,.02,.41,.04,.66,14.86-.42,29.77-2.23,44.69-2.53,1.38-.04,1.73,.37,1.13,1.33-.9,1.44-1.82,2.88-2.77,4.31-2.98,4.59-6.21,9.03-9.03,13.72-.22,1.M 06,1.45,.71,2.09,.79,4.04-.14,8.08-.3,12.12-.43,12.93-.35,25.86-.66,38.8-.82l-.12-.12c-3.15,6.75-6.32,13.48-9.72,20.12l.09-.06Z"/><path class="cls-2" d="M169.87,1258.01c-.57,.12-.87,.44-1.07,.86-1.78,3.72-3.56,7.44-5.34,11.16-1.06,2.21-2.12,4.42-3.17,6.64-.24,.45-.45,1.2,.21,1.37,15.47,.24,30.95-.88,46.42-1.35,2.19-.04,1.81,.42,.93,2.01-2.94,4.36-5.91,8.71-8.85,13.06-1.09,1.61-2.13,3.24-3.18,4.87-.25,.39,.2,.86,.8,.84,13.73-.31,27.41-1.57,41.12-2.25,.33-.01,.77,.47,.62,.67-.47,.65-.93,1.31-1.45,1.93-4.74,5.76-9.5,1M 1.51-14.24,17.26-.41,.62-1.42,1.48-.14,1.81,2.82-.16,5.65-.29,8.47-.48,9.39-.62,18.78-1.31,28.17-2.03,.23,0,.73,.34,.6,.63-6.54,7.57-14.04,14.37-20.5,22.01-.04,.67,1,.61,1.48,.59,8.32-.59,16.64-1.18,24.96-1.78,1.28,.12,7.2-1.26,7.05,.15-5.52,5.92-11.73,11.23-17.5,16.92-9.71,9.4-9.82,7.73,3.25,7.36,6.05-.29,12.1-.62,18.15-.93,1.57-.09,1.12,.86,.19,1.63-8.82,7.85-17.63,15.72-26.43,23.59-1.14,.87-2.09,2.19-3.56,2.51-8.07,.19-16.17,.02-24.25,.07-.58-.04-1.89,.08-1.9-.69,8.02-8.61,17.05-16.34,25.27-24.77,.11-.11,.01-.39M -.04-.58-.26-.23-.78-.18-1.12-.22-9.28,.45-18.57,.85-27.86,1-.2,0-.49-.18-.58-.33-.09-.16-.08-.45,.04-.59,2.39-2.61,4.77-5.21,7.21-7.79,4.14-4.38,8.32-8.74,12.48-13.11,.56-.59,2.23-2.01,.46-2.14-11.03,.28-22.03,1.46-33.05,1.7-.77-.33,0-1.15,.29-1.61,1.82-2.26,3.66-4.52,5.51-6.77,3.41-4.14,6.82-8.27,10.23-12.41,.36-.44,.83-.87,.43-1.54-11.63,.14-23.33,1.38-34.98,1.77-.87-.11-4.49,.68-3.72-.93,4.24-6.63,8.93-12.99,13.09-19.66,.02-.8-1.28-.71-1.86-.71-3.23,.11-6.46,.22-9.69,.34-11.17,.49-22.34,.94-33.52,.98l.14,.11c2.M 93-6.11,5.86-12.22,8.79-18.33,.32-.76,1.36-2.24-.03-2.48-11.14-.25-22.28,0-33.43-.09-5.36-.12-10.75,.1-16.08-.39-1.05-.29-.43-1.57-.34-2.32,1.42-5.46,2.85-10.92,4.27-16.38,.16-.61,.46-1.26-.21-1.82l-.06,.02c1.12-.49,2.34-.42,3.55-.4,4.98,.08,9.96,.11,14.93,.25,13.01,.71,26.16-.26,39.1,.77,0,0-.03-.02-.03-.02Z"/><path class="cls-2" d="M555.12,270.11c-7,1.83-13.79,4.34-20.78,6.2-.32,.09-.82-.29-.75-.56,6.68-20.92,14.95-41.42,23.13-61.84,.13-.81,1.53-2.6,.09-2.8-7.13,.88-14.05,3.09-21.18,4-1.41-.19-.12-2,0-2.82,8.89-2M 3.82,18.88-47.2,29.24-70.46,.19-.82,1.38-2.28-.05-2.46-7.65,.34-15.2,1.79-22.85,2.16-2,0-.21-2.24,0-3.22,12.04-28.51,24.92-56.77,38.73-84.5,.33-.12,.57-.28,.82-.29,8.7,.03,17.46-.23,26.14,.01,.34,.53,.27,.95,.06,1.35-.86,1.7-1.71,3.4-2.6,5.08-13.61,25.67-26.43,51.46-38.34,77.78-.48,1.68,2.4,.9,3.36,.93,5.07-.55,10.14-1.12,15.21-1.66,1.73-.18,3.48-.32,5.22-.46,.59-.05,.96,.39,.73,.87-11.5,23.85-22.85,47.72-32.65,72.24-.09,1.45,3.69-.15,4.58-.11,5.33-1.13,10.66-2.29,15.99-3.41,.61-.02,1.77-.44,2.09,.27-6.31,15.65-13.M 81,30.95-19.66,46.79-1.97,5.56-4.9,10.94-6.23,16.68l-.25,.21Z"/><path class="cls-2" d="M433.2,580.83c.01,.05,.01,.1,.02,.15-.05,0-.11-.01-.16-.02l.14-.13Z"/><path class="cls-2" d="M439.57,639.7s.05,.01,.07,.01c.02,.02,.03,.03,.04,.05l-.11-.06Z"/><path class="cls-2" d="M530.38,665.31c-1.16,1.67-2.32,3.34-3.49,5-.27,.39-.64,.65-1.36,.65-13.72-21.42-5.89-19.44-18.23-8.07-.69-.19-.94-.56-1.15-.94-.91-1.68-1.84-3.36-2.68-5.06-2.44-4.42-4.01-9.31-6.87-13.46-1.43,.61-2.13,1.7-3.14,2.54-2.21,1.74-4.01,3.88-6.58,5.18-.84-.5M 3-1.06-1.27-1.37-1.98-2.95-6.89-5.96-13.81-8.87-20.7-.9-.05-1.4,.31-1.92,.64-2.53,1.61-5.06,3.22-7.61,4.81-2.23,1.36-2.28,.02-3.09-1.76-2.23-6.1-4.44-12.2-6.65-18.3-.64-1.75-1.23-3.52-1.86-5.28-.45-.88-1.68-.42-2.39-.07-3.2,1.59-6.71,2.7-10.02,4.17-.63,.55-.08,1.47,.06,2.15,2.86,8.52,6.19,16.93,9.38,25.38,.52,1.9-11.45-.31-12.9-.5-.25-.35-.57-.69-.72-1.06-3.49-9.13-7.4-18.15-9.98-27.51,.56-1.72,13.08,2.99,13.04,.75-2.75-10.35-6.83-20.41-8.76-30.91,3.58-.3,6.93-2.14,10.41-3.03,.86-.28,1.65-.76,2.95-.61,2.72,9.82,5.2M 6,19.95,8.57,29.63,.86,.17,1.45-.1,2.01-.39,3.21-1.54,6.29-3.41,9.57-4.78,.64-.08,.96,.63,1.11,1.13,1.66,4.99,3.28,9.99,4.99,14.98,1.03,3,2.2,5.98,3.31,8.97,.16,.42,.9,.61,1.31,.33,3.05-2.1,6.1-4.19,8.98-6.5,.29-.21,.88-.13,1.03,.14,3.26,6.99,5.67,14.4,8.98,21.37,1.05,.08,1.59-.64,2.28-1.25,2.11-2.1,4.19-4.22,6.26-6.34,.35-.35,.74-.61,1.44-.59,2.94,5.95,5.4,12.16,8.44,18.08,.2,.42,.51,.73,1.25,.83,2.57-2.78,4.68-6.03,7.2-8.86,.14-.14,.47-.17,.71-.25,.75,.51,.93,1.26,1.29,1.94,1.81,3.34,3.6,6.68,5.4,10.02,.05,3.18-.M 07,6.36-.33,9.51Z"/><path class="cls-2" d="M630.4,655.28c0-.07,0-.13,.02-.2,.06,.03,.11,.05,.17,.08l-.19,.12Z"/><path class="cls-2" d="M670.15,602.22s-.01,.08-.02,.12c-.04-.02-.09-.04-.13-.06l.15-.06Z"/><path class="cls-2" d="M725.85,587.44s.05-.06,.08-.09c.01,0,.02,.01,.03,.01l-.11,.08Z"/><path class="cls-2" d="M737.94,573.78c-3.61,4.76-8.11,8.99-12.01,13.57-2.68-.99-5.35-1.97-8.03-2.96-1.27-.46-1.72-.39-2.38,.42-3.43,4.39-7.28,8.51-9.81,13.37,2.77,1.41,6,1.93,8.86,3.13,.12,1.3-.78,2.25-1.25,3.39-1.74,3.7-3.69,7.3M 3-5.14,11.11,0,.02-.01,.04-.02,.06-.04-.01-.08-.02-.12-.04-3.2-1.1-6.63-1.51-9.64-3.09,1.83-4.6,4.24-9.02,6.42-13.47,.3-.59,.08-1.15-.54-1.37-2.43-.9-4.88-1.78-7.32-2.66-.67-.2-1.22,.26-1.5,.77-2.26,4.47-4.52,8.95-6.76,13.43-.08,.15,.01,.36,.05,.55,.01,.02,.01,.05,.01,.07-2.91-1.1-5.85-2.16-8.77-3.26-.32-.12-.92,.05-1.05,.28-2.48,4.69-3.84,9.94-6.43,14.58-2.64-1.05-5.29-2.11-7.94-3.17-.48-.19-1.14,.03-1.33,.43-1.68,3.94-2.95,8.05-4.49,12.06-.31,.88-.51,1.68-1.36,2.24-2.74-1.04-5.14-2.42-7.86-3.45-.29-.12-.89,.1-.98M ,.37-1.55,4.7-3.09,9.34-4.61,14.06-.52-.04-.98,.04-1.28-.1-2.44-1.12-4.81-2.37-7.19-3.59-.28-.14-.88,.07-.99,.33-1.63,4.62-3.19,9.44-4.06,14.24-3.24-1.3-5.98-3.49-9.12-4.9-.95,.57-1,1.36-1.2,2.07-.93,3.25-1.8,6.51-2.71,9.77-.32,.8-.53,2.64-1.81,1.69-11.15-9.31-6.43-8.89-11.97,6.46-.72,.12-1.14-.1-1.49-.45-2.38-2.34-4.63-4.79-7.11-7.03-.13-.12-.47-.09-.84-.14-1.45,3.31-2.29,6.84-3.47,10.25-.23,.71-.35,1.47-1.03,2.03-.62-.03-.97-.36-1.28-.72-1.89-2.1-3.76-4.2-5.64-6.3-.74-.57-1.65-2.62-2.69-1.69-1.77,3.56-2.62,7.52-4M .46,11.04-1.01,1.15-3.52-3.27-4.35-3.98,.71-6.26,1.01-12.58,.88-18.93,10.86,13.65,6.56,12.8,13.16-2.21,.76,0,1.09,.33,1.38,.68,2.2,2.73,4.32,5.51,6.83,7.98,.19,.21,.94,.11,1.03-.13,1.37-3.71,2.52-7.47,3.78-11.22,.21-.57,.71-1.58,1.44-1.01,2.41,2.45,4.54,5.17,7.24,7.33,.11,.08,.62,.03,.67-.07,2.01-4.11,2.61-8.79,4.42-12.97,.66-.28,1.1-.1,1.48,.25,2.27,1.94,4.2,4.38,6.72,5.98,.8,.16,1.02-.81,1.24-1.36,1.13-3.65,2.24-7.31,3.37-10.97,.18-.61,.35-1.25,1.24-1.78,2.6,1.6,5.1,3.4,7.88,4.75,.85-.32,1.02-.83,1.19-1.35,1.55-4M .34,2.59-8.87,4.58-13.04,.59-.54,1.5,.13,2.09,.39,1.78,.97,3.55,1.95,5.32,2.93,.46,.26,.96,.36,1.66,.24,7.87-18.7,2.26-15.6,14.51-10.9,2.46-4.84,4.99-10.34,6.77-15.43,2.78,1.21,5.4,2.76,8.31,3.68,.19,.06,.58-.06,.7-.19,2.59-4.31,4.74-8.9,7.17-13.3,.26-.5,.56-.97,1.35-1.24,2.53,1.06,5.09,2.41,7.79,3.21,.2,.06,.59-.03,.73-.16,3.02-3.61,5.34-7.74,8.29-11.41,2.88-3.45,1.81-3.23,6.33-1.33,1.89,.68,3.55,1.71,5.6,1.94,4.17-4.43,7.87-9.33,12.27-13.53,.25-.14,.8-.18,1.12-.05,2.74,1.14,5.47,2.29,8.15,3.41,0,.21,.01,.31,0,.41M Z"/><path class="cls-2" d="M97.05,1321.32c-.26-.52-.21-1.05-.07-1.58,1.66-6.31,3.3-12.62,4.86-18.95,.52-1.7-1.99-1.36-3.12-1.45-3.63-.05-7.27-.14-10.9-.15-11.29-.13-22.61-.41-33.87-.95-.68-.21-1.05-.89-.98-1.57,.02-6.35,.05-12.69,.09-19.04-.09-1.45,1.46-1.34,2.53-1.34,15.32,.78,30.65,1.17,45.97,1.63,1.39,.32,6.08-.65,5.63,1.55-.67,2.74-1.36,5.48-2.06,8.22-.88,3.48-1.77,6.95-2.64,10.43-.16,.42,.06,.99,.51,1.09,15.45,.66,30.94-.26,46.4-.02l-.14-.11c-2.89,6.51-6.08,12.89-9.19,19.3-.35,.78-1.04,1.9,.35,2.09,13.1,.2,26.M 13-.94,39.23-1.16,.35,1.33-.84,2.19-1.42,3.28-3.73,5.61-7.46,11.21-11.18,16.82-.27,.48-.94,1.33-.2,1.66,11.28,.18,22.59-.94,33.88-1.16,.63-.01,.99,.44,.69,.85-5.6,7.39-12.02,14.21-17.45,21.72-.02,.67,.99,.64,1.49,.64,9.29-.3,18.57-.61,27.86-.9,.39-.06,.7,.18,.98,.4,.21,.3-.21,.6-.38,.84-7.42,7.81-14.59,15.85-22.15,23.53-8.3,.48-16.68,.05-25,.2-3.79,.1-1.15-1.94-.07-3.45,4.78-5.99,9.57-11.98,14.35-17.96,.58-.71,2.19-2.35,.33-2.51-9.69,.12-19.39,.69-29.07,.55-.28-.02-.69-.51-.6-.71,.09-.2,.15-.42,.27-.61,4.22-6.62,8.M 53-13.2,12.83-19.78,.59-.91,.18-1.35-1.2-1.3-11.17,.34-22.34,.83-33.52,.93-1.39-.07-.7-1.34-.38-2.08,1.94-4.13,3.9-8.25,5.84-12.38,1-2.11,1.99-4.23,2.97-6.34,.2-.43-.18-.88-.75-.89-13.58,.28-27.26,.19-40.79,.64-.01,0,.09,.05,.09,.05Z"/><path class="cls-2" d="M1344.66,118.75c-.19,.28-.49,.54-.56,.84-1.66,6.53-3.31,13.06-4.95,19.6-.14,.56,.34,1.01,1.12,1.08,14.93,.46,29.87,.5,44.79,1.11,1.75,.03,2.56,.05,2.49,2.09,0,6.13,0,12.27-.01,18.4-.05,.63,0,1.47-.79,1.63-5.76,.01-11.56-.5-17.32-.7-9.28-.29-18.56-.57-27.84-.85-M 2.8-.15-5.66,.12-8.38-.66l.14,.13c2.14-6.26,3.27-12.84,4.97-19.23,.11-.57,.38-1.51-.39-1.69-8.17-.55-16.37-.06-24.55-.1-6.05,.06-12.1,.15-18.14,.22-1.04-.07-3.73,.42-2.99-1.35,2.93-6.23,5.96-12.43,8.93-18.64,.47-.98,.12-1.37-1.23-1.38-13.16,.09-26.33,.53-39.46,1.37l.16,.11c3.68-7.1,8.9-13.53,13.09-20.38,.84-1.37,.42-1.84-1.13-1.81-11.08,.26-22.09,.76-33.16,1.31-.28-1.4,1.05-2.13,1.74-3.18,4.79-5.86,9.58-11.72,14.36-17.59,1.49-1.89,1.95-2.52-.96-2.43-9.02,.3-18.04,.59-27.07,.8-1.51-.21-.63-1.23,.09-1.92,7.15-7.46,13M .99-15.13,21.15-22.58,8.93-.32,17.97-.22,26.9-.05,.31,.51,.12,.88-.18,1.27-3.03,3.82-6.04,7.65-9.08,11.47-2.39,3-4.81,5.98-7.2,8.97-.38,.52-1.36,1.6-.24,1.84,9.83-.09,19.66-.56,29.49-.58,.99,.29,.56,1.02,.21,1.62-4.13,6.41-8.31,12.81-12.43,19.22-.88,1.5,.64,1.51,1.74,1.5,10.51-.31,21.01-.63,31.52-.8,1.94,0,2.36,.21,1.6,2.19-1.98,4.23-4,8.46-5.99,12.69-.9,1.91-1.75,3.84-2.62,5.76-.18,.4,.23,.94,.72,.97,13.86,.15,27.75-.63,41.61-.15l-.14-.12Z"/><path class="cls-2" d="M488.94,146.58c11-30.71,22.64-61.24,35.4-91.29,.17M -.41,.31-.84,.59-1.19,.58-.69,1.66-.66,2.52-.66,7.68,0,15.37,0,23.05,0,.61-.04,1.9-.04,1.89,.72-4.98,11.98-10.58,23.72-15.59,35.66-7.46,17.5-14.67,35.07-21.37,52.85-.36,1.09-.04,1.49,1.22,1.4,1.88-.13,3.75-.29,5.63-.47,5.22-.5,10.43-1.02,15.64-1.53,.95-.14,2.42-.03,1.91,1.22-10.59,25.37-20.38,50.95-29.09,76.95l.08-.06c-6.93,1.29-13.86,2.59-20.79,3.86-.79,.03-2.51,.66-2.67-.47,2.7-8.99,5.59-17.91,8.62-26.82,5.62-16.84,11.55-33.58,17.88-50.18,.14-.64,.7-1.72-.15-2-1.34,.01-2.68,.01-4.01,.13-6.95,.53-13.87,1.5-20.84,1M .76l.08,.11Z"/><path class="cls-2" d="M1271.78,456.81c37.9,11.66,75.35,24.51,112.26,38.83,1.08,.41,2.29,.69,3.1,1.66,.24,6.39,.05,12.86,.11,19.26-.06,.79,.14,2.22-1.1,1.97-22.58-8.99-45.03-18.03-68.01-26.24-14.84-5.35-29.77-10.66-44.91-15.38-.52-.15-1.19,.19-1.19,.57,.41,5.8,1.28,11.58,1.86,17.37,.02,.21,0,.43,0,.65,0,.25-.58,.64-.84,.55-31.46-10.83-63.55-20.68-95.91-28.95l.07,.08c-.82-5.6-2.66-11.29-1.74-16.95,.43-.66,1.47-.25,2.12-.18,29.7,6.83,59.04,15.19,88.03,24.3,1.85,.58,3.59,1.47,5.65,1.54,.49,.02,.51-.16,.M 36-4.97,.05-4.65-.68-9.62,.26-14.16l-.13,.06Z"/><path class="cls-2" d="M1001.34,1295.62c-.43-.72-.33-1.44-.11-2.2,.79-2.71,1.54-5.44,2.32-8.16,2.81-9.72,5.37-19.48,7.83-29.26,1.74-6.94,3.48-13.88,5.14-20.83,1.36-5.69,2.61-11.39,3.91-17.09,.22-.95,.39-1.91,1.17-2.71,0,0-.06,.03-.05,.02,.48,.59,1.3,.7,2.05,.87,6.14,1.65,12.62,2.46,18.56,4.68l-.06-.09c-.45,6.23-2.27,12.34-3.38,18.5-4.09,18.79-8.3,37.52-13.13,56.15-.13,.99-1.07,2.52,.47,2.83,7.81,1.11,15.63,2.2,23.43,3.41l-.07-.09c-3.31,10.9-5.35,22.19-8.4,33.21-4.7,17M .08-8.75,34.48-14.43,51.26-2.82,.26-16.49,.72-27.26,.03,8.33-28.47,17.65-56.76,24.94-85.56,.14-.53,.18-1.07,.25-1.6,.02-.46-.81-1-1.35-1-6.78-.89-13.55-1.78-20.33-2.67-.54-.07-1.07-.05-1.5,.28v.02Z"/><path class="cls-2" d="M418.87,224.39c-.33-.54-.99-.67-1.62-.82-3.96-.92-7.93-1.82-11.89-2.74-2.23-.73-5.77-.93-7.25-2.24,5.17-24.77,10.5-49.52,16.86-74.03,.08-1.05,1.16-2.81-.47-3.14-6.5-.93-13-1.81-19.5-2.75-.92-.13-1.83-.36-2.72-.59-.2-.05-.43-.33-.43-.5,.84-6.32,2.86-12.49,4.25-18.73,5.56-21.74,11.27-43.51,17.86-64M .96,.61-.64,1.79-.4,2.62-.49,7.41,0,14.83,0,22.24,.02,.84,0,2.46-.19,2.41,1-4.75,15.91-10.12,31.69-14.58,47.68-3.49,12.83-7.62,25.53-10.57,38.48-.16,1.04,1.47,1.23,2.31,1.33,4.38,.59,8.76,1.2,13.15,1.77,2.26,.29,4.53,.54,6.8,.78,.23,.02,.49-.14,.73-.21h0c.53,.56,.56,1.19,.37,1.83-3.91,13.36-7.53,26.81-10.92,40.28-2.12,8.42-4.31,16.82-6.03,25.3-.75,3.71-1.71,7.39-2.59,11.08-.15,.65-.51,1.22-1.1,1.7,0,0,.06-.01,.06-.01Z"/><path class="cls-2" d="M1287.14,363.02c-.97,5.98-2.15,11.93-3.26,17.89-.34,1.49-2.25,.69-3.29,.6M 1-28.6-6-57.55-10.64-86.51-14.64l.15,.12c2.27-5.06,3.61-10.59,5.53-15.82,.47-1.77-3.38-1.3-4.48-1.66-3.07-.33-6.13-.64-9.2-.95-20.7-2.28-41.53-2.93-62.3-4.3l.15,.1c1.99-4.1,3.97-8.21,5.99-12.31,1.84-3.73,2.09-3.71-3.31-3.78-9.68-.15-19.36-.1-29.04-.05-10.35,.12-20.69,.64-31.04,.76-1.66-.34-.29-1.81,.11-2.67,2.63-4.35,5.3-8.68,7.91-13.05l-.1,.05c21.86-.81,43.72-1.72,65.6-1.27l-.09-.1c-1.75,4.63-4.6,8.95-6.72,13.47-.53,1.34-2.21,3.09,.67,3.08,24.21,.52,48.35,2.2,72.47,4.24l-.1-.11c-1.51,5.86-4.27,11.3-5.73,17.19,28.9M 5,3.92,58.02,7.7,86.72,13.3l-.11-.1Z"/><path class="cls-2" d="M1096.34,280.31c19.3-1.43,38.66-2.02,58.01-2.49,.83,.14,4.47-.48,4.09,.81-2.39,4.7-5.14,9.22-7.66,13.85-.25,.73-1.55,2.15-.37,2.54,23.27,.07,46.5,1.04,69.74,2.13l-.14-.09c-1.39,5.36-4.11,10.45-5.99,15.7-.29,.71-.65,1.41-.4,2.23,10.15,1.5,20.53,1.84,30.74,3.05,17.05,1.67,33.95,4.62,50.98,6.27l-.07-.09c-.22,.5-.53,.99-.64,1.5-1.09,5.99-2.75,11.92-3.43,17.95l.13-.05c-9.65-.58-19.25-3-28.9-4.16-18.66-2.73-37.43-4.72-56.18-6.83l.1,.11c2.04-5.7,4.9-11.45,6.2-1M 7.22-23.96-2.93-48.44-2.85-72.62-3.56l.09,.1c2.85-5.22,5.7-10.44,8.55-15.66,.54-1.07-.6-1.27-1.49-1.22-20.73-.09-41.43,.84-62.13,1.92l.08,.12c3.76-5.62,7.51-11.24,11.27-16.87l.04-.03Z"/><path class="cls-2" d="M1189.33,383.81c30.14,4.3,59.95,10.21,89.61,16.81,.72,.14,1.41-.21,1.51-.76,1.04-5.32,1.92-10.65,2.88-15.98,.34-1.99,1.77-1.33,3.25-1.1,33.63,7.05,66.61,15.51,99.38,24.94,1.16,.3,1.37,1.15,1.32,2.11,0,5.92,0,11.85,0,17.77,0,2.07-.27,2.56-3.01,1.74-10.45-3.15-20.89-6.34-31.4-9.39-23.4-6.81-47.12-13.01-70.99-18.M 59-1.14-.26-1.71,.07-1.88,1.1-.88,5.34-1.72,10.68-2.65,16.01-.13,.76-.76,1.08-1.75,.86-30.36-7.78-61.27-13.66-92.08-19.49l.17,.12c2.07-4.64,3.15-9.69,4.81-14.5,.19-.63,.37-1.24,.91-1.75l-.09,.09Z"/><path class="cls-2" d="M52.33,141.44c0-6.17-.02-12.66,0-18.89,.13-.85-.31-2.56,1.11-2.25,4.43,1.92,8.61,4.43,12.93,6.6,4.55,2.27,8.84,5.07,13.53,7.02,.14,.05,.59-.16,.61-.28,.13-.74,.24-1.49,.23-2.23-.09-7.22-.25-14.43-.3-21.65,0-.43,.05-.86,.08-1.29,.37-1.4,3.53,.54,4.51,.71,5.84,2.22,11.67,4.45,17.5,6.67,1.39,.27,5.46,M 2.94,5.36,.29,0-.65-.02-1.29-.02-1.94,0-9.05-.24-18.1-.04-27.15,.03-1.04,.52-1.36,1.76-1.11,4.44,.88,8.88,1.78,13.32,2.66,2.61,.52,5.23,1.02,7.83,1.56,4.25,.89,4.21,1.44,4.28-2.74,.26-11.09,.33-22.19,.79-33.28,.03-1.31,1.65-1.34,2.69-1.3,8.07,.13,16.2-.23,24.24,.17,1.12,.36,.83,1.67,.86,2.58-.36,7.43-.78,14.85-1.1,22.28-.2,4.63-.26,9.26-.4,13.89-.31,1.36,.72,4.71-1.6,4.33-8.3-1.13-16.41-3.87-24.72-4.55-1.54,.09-.71,7.51-.95,9.06,0,7.97,0,15.94,0,23.91-.22,1.1,.65,3.9-1.29,3.38-8.01-3.04-15.9-6.4-23.94-9.37-2.04-.92M -1.64,1.32-1.66,2.56-.19,9.25,.8,18.55,.4,27.76-.54,.52-1.51-.08-2.08-.35-5.77-3.18-11.51-6.38-17.29-9.55-2.33-1.28-4.73-2.47-7.11-3.69-.3-.16-.88,.09-.9,.39-.24,7.2,.27,14.43,.36,21.63,.06,3,0,3.4-.53,3.33-1.41-.2-2.19-1.15-3.19-1.82-7.65-5.12-15.27-10.25-22.91-15.38-.82-.55-1.75-1.01-2.37-1.99Z"/><path class="cls-2" d="M1305.47,1311.84c.95-.16,1.82,.09,2.67,.47,7.71,3.09,15.42,6.18,23.2,9.12,1.27,.47,1.41-.79,1.35-1.68-.1-8.83-.27-17.66-.45-26.49-.01-.64,.07-1.28,.12-1.93,.02-.24,.65-.54,.89-.42,1.03,.51,2.07,1.0M 1,3.07,1.56,7.44,4.09,14.79,8.34,22.37,12.17,.45,.23,1.12-.1,1.12-.55,.09-8.17-.53-16.35-.52-24.51,.75-.37,1.24-.12,1.85,.28,8.73,6,17.72,11.65,26.3,17.84,.53,6.78,.06,13.73,.21,20.56,.02,.52-.21,1.28-.86,1.19-8.17-3.82-15.97-8.43-24.01-12.53-3.09-1.65-2.73-.79-2.8,2.1,.08,6.68,.18,13.36,.25,20.03,0,.85-.11,1.71-.24,2.56-.47,.62-1.48,.05-2.08-.11-8.07-2.95-15.99-6.3-24.16-8.96-.27-.09-.85,.27-.85,.52-.02,2.37-.05,4.73-.05,7.1,.03,7.32,.07,14.65,.1,21.97-.06,.72-.01,1.81-1,1.84-8.72-1.21-17.3-4.11-26.01-4.85-.75,11.M 35-.6,22.79-.98,34.17-.08,3.89,.08,3.71-4.66,3.71-6.6-.01-13.21-.02-19.81-.03-1.33,0-3.67,.26-3.42-1.69,.64-12.05,1.15-24.1,1.44-36.17,.05-1.61,.23-3.22,.35-4.82,.02-.22,.59-.62,.84-.6,7.37,1.01,14.63,2.92,21.96,4.26,3.07,.37,4.24,1.31,4.09-2.57-.19-11.18,.47-22.44-.23-33.58l-.03,.06Z"/><path class="cls-2" d="M161.33,138.68c-.15,13.24,.38,26.5,.36,39.72-.26,.31-1.03,.27-1.41,.02-5.86-3.01-11.47-6.43-17.24-9.59-1.99-1.11-4.02-2.17-6.05-3.23-2.19-.71-1.01,2.76-1.2,3.91,.33,9.15,.72,18.3,1.18,27.45,.15,1.97-.1,3.27-2.M 21,1.65-6.19-4.32-12.38-8.64-18.58-12.96-1.72-1.2-3.43-2.42-5.19-3.59-.23-.16-.72-.07-1.17-.11-.07,8.66,.87,17.24,1.22,25.89,.05,.86,0,1.72-.01,2.58-.02,.36-.73,.36-.9,.29-6.21-4.51-11.91-9.67-17.94-14.42-2.83-2.3-5.7-4.58-8.57-6.85-1.85-1.02-1.21,1.73-1.24,2.77,.26,6.46,.53,12.92,.78,19.38-.06,.53,.11,1.52-.31,1.83-.23,.04-.58,.1-.71,0-9.05-7.73-17.63-16.03-26.56-23.91-1.34-1.32-3.42-2.54-3.19-4.63,.15-6.49-.22-12.99,.15-19.46,1.59-.29,2.55,1.25,3.75,2.01,7.8,6.26,15.59,12.52,23.39,18.77,.69,.44,1.3,1.32,2.22,1.07M ,.08-.01,.18-.16,.19-.24,.04-.86,.11-1.72,.09-2.57-.2-6.68-.42-13.35-.62-20.03,.06-.74-.31-2.31,.92-2.01,2.42,1.26,4.57,3.01,6.85,4.5,6.11,4.24,12.2,8.48,18.3,12.72,.43,.33,1.17,.8,1.73,.44,.1-.42,.22-.84,.21-1.26-.24-9.35-.92-18.72-.77-28.06,1.21-.42,2.17,.62,3.23,1.04,7.11,3.89,14.22,7.8,21.33,11.69,2.09,1.22,2.16,.48,2.17-1.58-.2-9.26-.42-18.52-.61-27.78-.09-4.58-.04-4.93,.6-4.95,2.15-.07,3.72,1.1,5.5,1.77,6.83,2.56,13.6,5.21,20.39,7.83l-.08-.08Z"/><path class="cls-2" d="M1305.5,1311.78c-.18-.92-1.32-.9-2.03-1.2M 9-8.13-3.17-16.24-6.39-24.41-9.46l.08,.07c.38-13.13-.51-26.28-.18-39.4,.01-.25,.65-.53,.92-.39,2.24,1.2,4.49,2.38,6.7,3.6,5.2,2.88,10.38,5.79,15.58,8.67,.74,.28,2.13,1.36,2.66,.37,.03-11.07-1.11-22.14-1.16-33.21,.99-.39,1.64,.38,2.43,.83,5.9,4.1,11.79,8.2,17.67,12.31,2.21,1.32,4.06,3.4,6.52,4.19,.1,.02,.32-.06,.35-.13,.58-9.47-1.03-19.13-1.04-28.65,1.25-.21,2.01,.92,2.95,1.51,5.57,4.54,11.1,9.1,16.69,13.62,2.65,2.14,5.37,4.23,8.06,6.34,.23,.18,.5,.15,.73-.03,.4-.36,.25-1.03,.31-1.52-.11-2.8-.25-5.6-.35-8.39-.17-4.5M 2-.33-9.04-.47-13.56,.39-1.82,2.22,.47,2.95,1.02,8.72,7.92,17.45,15.84,26.17,23.77,1.33,1.03,.96,2.55,1.02,3.98,0,5.17,0,10.34,0,15.51,.34,4.94-1.76,2.26-4.11,.55-8.05-6.34-15.87-12.97-24.04-19.15-1.18-.56-1.03,1.16-1.03,1.87,.18,5.06,.38,10.12,.55,15.18,.08,2.37,.09,4.74,.12,7.11-.14,.64-.61,.9-1.39,.39-7.81-5.27-15.52-10.67-23.25-16.05-.92-.56-1.77-1.51-2.93-1.51-.5,.03-.54,.44-.53,.74,.31,9.04,.65,18.08,.94,27.13,.01,2.23-1.25,1.49-2.64,.79-7.22-3.96-14.43-7.93-21.65-11.89-.85-.4-1.56-1.07-2.57-.68-.16,11.93,1.0M 7,23.91,.37,35.83,0,.02,.02-.04,.02-.04Z"/><path class="cls-2" d="M870.97,812.72c-.59-.26-.78-.69-1.02-1.09-1.41-2.44-2.82-4.89-4.25-7.32-.84-1.19-1.18-2.67-2.74-3.13-1.94,3.96-3.31,8.02-5.27,11.95-1.19,1.15-2.22-1.91-2.92-2.6-1.69-2.15-2.93-5.22-5.04-6.88-.5-.15-.73,.54-.93,.87-1.63,3.88-2.99,7.86-4.78,11.66-.07,.15-.36,.33-.52,.32-.23-.03-.51-.19-.64-.35-1.3-1.76-2.55-3.54-3.87-5.3-.68-.61-2.23-3.69-3.17-2.62-1.94,3.96-3.24,8.21-4.97,12.28-.16,.4-.4,.78-.98,.92-.77-.3-1.09-.91-1.53-1.44-1.49-1.8-2.98-3.59-4.47-5.M 38-.31-.37-.71-.64-1.47-.57-1.73,4.25-3.45,8.56-5.16,12.83-.21,.52-.43,1.02-1.11,1.31-2.41-1.79-4.11-4.23-6.36-6.21-1.33-.88-1.6,1.21-2.05,2.02-1.72,3.96-3.25,8.01-5.1,11.92-.38,.77-1.02,.85-1.84,.22-2.12-1.64-4.23-3.3-6.36-4.96,1.46-5.04,3.88-9.85,5.7-14.8,.08-.2,.29-.36,.45-.54,1.18,.04,1.85,.78,2.67,1.29,1.99,1.08,3.19,2.72,5.49,3.39,2.18-3.73,3.54-9.21,5.26-13.37,.26-1.57,1.61-1.23,2.33-.26,1.95,1.76,3.6,3.84,5.69,5.43,.15,.1,.46,.04,.83,.05,1.68-4.16,3.02-8.47,4.51-12.7,.28-1,1.06-1.23,1.82-.39,2.09,2.24,4.09,M 4.53,6.21,6.76,.21,.23,.91,.14,1.01-.12,1.66-4.24,3.04-8.45,4.59-12.79,.46,.1,.98,.08,1.14,.26,2.33,2.63,4.45,5.37,6.66,8.09,.11,.14,.46,.28,.63,.24,.22-.05,.46-.26,.54-.44,1.82-3.89,2.86-8.09,4.71-11.96,.71,.02,1.08,.29,1.36,.67,1.61,2.24,3.22,4.48,4.83,6.73,.6,.84,1.17,1.69,1.78,2.53,.23,.3,.77,.08,.94-.1,1.75-3.2,2.88-6.72,4.4-10.05,.34,7.87,1.33,15.78,3,23.63Z"/><path class="cls-2" d="M993.65,862.78s-.06,.03-.09,.04c-.01-.03-.03-.06-.04-.09l.13,.05Z"/><path class="cls-2" d="M998.79,884.93c-5.06-.7-10.05-1.74-14M .94-3.16-.77-4.03-1.62-8.06-2.5-12.07-.25-1.19-1.07-1.06-2.01-.62-3.44,1.59-6.73,3.53-10.15,5.15-.3-.19-.61-.28-.65-.43-.55-2.21-1.11-4.43-1.6-6.65-1.69-6.8-2.94-13.95-5.4-20.5-.68-.46-1.46,.2-2,.56-2.7,2.26-5.38,4.53-8.06,6.81-.37,.31-.74,.59-1.35,.54-.62-.73-.75-1.6-.98-2.44-1.82-6.73-3.48-13.49-5.72-20.14-.21-.63-.36-1.27-1-1.72-.59,.02-.95,.33-1.28,.67-2.48,2.55-4.96,5.11-7.43,7.66-.34,.35-.71,.64-1.33,.63-3-6.77-3.99-14.4-7.38-21.07-.68-.44-1.27,.46-1.69,.87-1.64,2.05-3.24,4.13-4.88,6.18-3.2-7.08-5.53-14.31-7.M 04-21.59,1.28-1.8,2.56-3.61,3.84-5.4,.26-.38,.55-.75,1.14-.87,.66,.41,.85,1.04,1.12,1.63,2.17,4.76,4.1,9.57,5.94,14.41,.38,.85,.56,3.01,1.94,2.76,2.71-2.6,4.97-5.62,7.5-8.4,.32-.37,.72-.61,1.4-.57,12.37,27.36,3.02,24.74,18.53,13.12,.75,.53,.93,1.17,1.15,1.79,2.75,7.6,4.97,15.39,7.51,23,.94,.12,1.41-.3,1.93-.63,2.53-1.6,5.05-3.22,7.6-4.81,.55-.29,1.47-.96,2.07-.51,3.4,9.35,5.26,19.17,7.98,28.72,1.78-.09,3.01-1.01,4.41-1.57,2.73-1.12,5.4-2.32,8.1-3.46,2.62,7.06,3.54,14.76,5.23,22.11Z"/><path class="cls-2" d="M1246.01M ,141.96c-9.51,.74-19.07,1-28.58,1.69-4.83,.21-9.66,.86-14.49,.82-1.22-.41,.59-1.79,.91-2.4,3.34-4.04,6.7-8.08,10.03-12.12,1.63-1.98,3.23-3.97,4.81-5.97,.19-.25,.35-.64,.24-.89-.22-.52-.88-.35-1.36-.31-7.38,.52-14.75,1.06-22.13,1.59-4.56,.27-9.11,.81-13.68,.87-.38,.04-.57-.46-.47-.71,5.94-6.71,12.34-13.04,18.45-19.61,.75-.9,1.84-1.54,1.92-2.79-10.51,.23-20.94,1.48-31.43,2.17-.65-.06-2.23,.38-2.32-.46,7.46-7.86,15.72-14.99,23.39-22.65,1.04-1.01,1.95-2.1-.3-2.04-9.28,.28-18.54,1.04-27.81,1.21-.4-.6,.03-.98,.46-1.4,9.8M 2-8.63,19.35-17.59,29.34-26.03,8.24-.33,16.6-.05,24.86-.14,.66,.05,2.3-.2,1.91,.89-7.86,7.98-16.15,15.57-24.16,23.42-.56,.65-1.6,1.25-.2,1.7,9.42-.33,18.83-.67,28.25-.92,1.43,.18,.32,1.39-.23,1.95-6.25,6.77-12.66,13.41-19,20.1-.34,.51-1.54,1.42-.65,1.82,1.34,0,2.69-.01,4.02-.09,9-.5,18-1.03,27-1.58,.89,.06,3.57-.54,2.62,1.09-4.99,6.29-10.18,12.43-15.24,18.66-.5,.84-1.65,1.52-1.43,2.57,1.33,.33,2.66,.08,3.99-.01,11.93-.76,23.91-1.64,35.88-1.66l-.16-.11c-5.04,7.01-9.71,14.27-14.58,21.4l.12-.05Z"/><path class="cls-2" M d="M796.18,794.99c.02-.06,.03-.11,.05-.17,.03,.01,.06,.03,.09,.04l-.14,.13Z"/><path class="cls-2" d="M875.27,737.28c-1.44,4.33-2.69,8.73-3.71,13.18-1.15-1.3-1.77-1.43-2.47,.32-1.12,2.76-2.2,5.53-3.32,8.3-.3,.64-.73,1.87-1.65,1.2-2.99-2.85-5.45-6.3-8.7-8.86-.97-.42-1.25,1.54-1.59,2.17-.89,2.71-1.74,5.42-2.62,8.13-.23,.51-.51,1.51-1.27,1.3-3.18-2.16-5.41-5.46-8.6-7.63-1.61-1.03-3.28,10.49-4.38,11.99-1.09,.98-2.35-1.16-3.3-1.67-1.77-1.48-3.53-2.97-5.33-4.41-.23-.19-.71-.16-1.14-.25-1.53,4.41-2.08,8.92-3.63,13.2-1.91,.M 58-9.05-5.78-9.97-3.86-1.04,4.01-2.06,8-3.03,12.02-.14,.51-.28,1.05-.91,1.4-13.17-4.8-7.17-7.83-13.42,11.01-5-2.36-6.59-2.98-9.39-3.67-1.55,3.94-2.35,8.12-3.62,12.15-.23,.82-.39,1.68-1.25,2.43-3.07-.94-5.98-2.58-9.21-3.02,1.42-4.8,2.54-9.71,4.09-14.47,.09-.26,.66-.51,.96-.42,2.25,.72,4.49,1.45,6.74,2.16,1.53,.54,2.24,.67,2.71-1.12,.95-3.91,1.88-7.82,2.83-11.73,.19-.79,.89-1.13,1.73-.83,2.62,.94,5.36,1.96,7.92,2.98,.94-.45,1-1.13,1.14-1.74,.93-3.92,1.71-7.85,2.7-11.75,.11-.44,.69-.63,1.25-.4,2.63,1.08,5.18,2.28,7.79M ,3.42,.29,.12,.74,0,1.12,0,1.38-4.25,1.81-8.76,3.17-13.02,.07-.21,.78-.42,1.04-.31,2.72,1.08,5.21,2.66,7.82,3.97,.92,.48,1.59,.3,1.79-.49,.37-1.48,.72-2.96,1.07-4.44,.56-2.32,1.11-4.65,1.68-6.97,.16-.63,.85-.77,1.51-.31,2.46,1.8,4.71,3.85,7.09,5.75,.46,.39,.86,.84,1.76,.87,1.69-3.64,2.22-7.74,3.57-11.51,.13-.38,.96-.55,1.31-.25,1.38,1.18,2.76,2.35,4.1,3.56,1.43,1.29,2.79,2.63,4.23,3.91,.22,.19,.7,.18,1.14,.29,1.26-3.47,2.4-6.86,3.62-10.32,.56-1.55,1.49-.98,2.37-.09,2.1,2.1,4.15,4.23,6.27,6.33,.74,.73,1.24,1.66,2.4,M 2.09,1.43-.58,1.27-1.82,1.73-2.77,1.27-2.57,2.17-5.33,3.54-7.84,.11,0,.22,0,.32,.01Z"/><path class="cls-2" d="M964.52,753.47s.04,.05,.05,.07c-.07,.02-.13,.05-.2,.08l.15-.15Z"/><path class="cls-2" d="M977.5,752.9h-.04s-.04-.05-.05-.07l.09,.07Z"/><path class="cls-2" d="M988.27,774.2c-2.29,.1-4.57-.04-6.86-.02-5.54,0-5.43-.47-3.31,3.78,3.26,6.68,6.47,13.39,9.03,20.29-.22,.24-.32,.47-.53,.58-3.7,1.68-7.24,3.95-11.06,5.27-.79-.35-.9-1.03-1.15-1.61-1.19-2.74-2.27-5.52-3.49-8.25-1.8-4.06-3.7-8.08-5.55-12.12-.24-.52-.48-1.M 01-1.26-1.31-3.49,1.7-6.38,4.15-9.48,6.4-1.53,.84-1.76-1.38-2.4-2.26-2.38-4.57-4.75-9.14-7.16-13.7-.57-1.09-1.26-2.13-1.95-3.18-.08-.12-.52-.22-.7-.16-2.27,1.33-4,3.5-6.02,5.17-1.02,.85-1.72,2.09-3.08,2.38-3.89-5.35-6.56-11.42-10.42-16.8-.2-.28-.83-.37-1.03-.14-2.34,2.75-4.61,5.53-6.82,8.37-1.41,1.07-2.88-2.98-3.78-3.87,1.02-5.2,2.46-10.32,4.29-15.29,9.93,13.33,3.66,10.77,15.44,1.48,.97,.23,1.37,1.24,1.92,1.96,2.95,4.72,5.89,9.44,8.82,14.17,.35,.57,.57,1.2,1.44,1.58,1.88-.84,8.95-7.8,10.3-6.53,3.54,5.61,6.39,11.63,M 9.67,17.39,.51,.66,.96,2.32,1.97,2.13,3.48-1.84,6.94-3.69,10.39-5.56,.32-.17,.43-.53,.28-.87-3.61-6.7-7.25-13.44-11.2-19.94,4.12-1.14,8.63-.34,12.89-.64,3.82,5.95,6.95,12.3,10.42,18.46,.24,.79,1.71,2.48,.39,2.84Z"/><path class="cls-2" d="M599.08,967.55s-.05,.01-.07,.02c-.02-.03-.04-.07-.06-.1h.08s.03,.05,.05,.08Z"/><path class="cls-2" d="M637.65,964.94s-.02-.03-.03-.04l.15-.06-.12,.1Z"/><path class="cls-2" d="M659.11,944.03s-.01-.03-.01-.05c.02-.01,.03-.01,.05-.02h0s-.03,.07-.04,.07Z"/><path class="cls-2" d="M695.5M 7,883.51c-2.81-1.22-5.44-3.2-8.41-3.93-5.36,3.76-10.3,8.15-15.95,11.73-.4,.28-.75,.62-1.44,.57-3.15-1.43-6.2-3.61-9.53-4.63-6.31,3.37-12.52,7.1-18.71,10.69-.28,.19-.32,.67-.03,.85,2.6,1.69,5.43,3.11,7.84,5.05,.38,.71-.75,1.09-1.23,1.42-6.61,3.53-13.6,6.51-20.61,9.51-.37,.51,.36,1.01,.74,1.32,2.29,1.81,4.86,3.34,6.94,5.38,.27,.63-.64,.87-1.1,1.08-8.07,3.21-16.27,6.29-24.6,8.97-.51,.18-.71,.74-.38,1.07,2.19,2.19,4.48,4.3,6.67,6.49,.21,.22,.17,.59,.26,.94-6.25,2.39-12.66,4.26-19.15,6.1-3.44,.93-6.89,1.84-10.33,2.77-.5M 2,.14-.95,.36-1.11,1,2.29,2.63,4.77,5.32,6.83,8.16-.45,.73-1.25,.86-2.01,1.07-4.38,1.18-8.8,2.28-13.24,3.3,7.11,1.52,14.27,2.94,21.49,4.23-1.74-2.64-3.73-5.19-5.35-7.9,.92-.87,2.04-1.02,3.22-1.36,9.67-2.64,18.96-6.01,28.28-9.32,2.38,2.56,4.48,5.26,6.7,8.01-9.69,4.75-20.32,7.52-30.56,10.99,7.39,1.31,14.84,2.5,22.34,3.58,4.9-1.78,9.74-3.62,14.48-5.75-1.82-2.73-4.02-5.26-5.61-8.12-.07-.17,.02-.48,.18-.58,9.07-3.98,18.05-8.02,26.91-12.22-.08-.4-.03-.87-.29-1.17-2.03-2.27-4.3-4.43-6.43-6.61,3.13-2.24,6.83-3.45,10.06-5.5M 4,4.3-2.61,9.25-4.73,13.18-7.78-.22-.8-.88-1.2-1.43-1.65-1.52-1.22-3.08-2.4-4.62-3.61-.44-.46-1.39-.86-.96-1.58,6.42-4.53,13.06-8.3,19.44-12.99-2.46-2.28-5.73-3.65-8.38-5.67,4.63-3.86,9.49-7.36,14.21-11.11,.62-.72,3.09-1.78,1.69-2.76Zm-17.48,14.7c-4.84,3.26-9.65,6.55-14.79,9.52-1.28,.84-2.75,1.3-3.68,2.56,2.6,1.92,5.17,3.81,7.78,5.73-.48,1.1-1.58,1.41-2.54,2.01-6.38,3.81-13.16,7.06-19.83,10.54-.64,.67,.7,1.3,1.07,1.82,1.74,1.64,3.49,3.27,5.22,4.92,.39,.37,.3,.88-.16,1.12-8.52,4.43-17.58,7.98-26.53,11.55-2.49-2.62-4M .98-5.26-7.56-7.98,8.55-3.79,17.52-6.5,25.9-10.66,.66-.3,.76-.9,.24-1.36-2.25-1.94-4.59-3.93-6.82-5.87,.18-.69,.82-.88,1.36-1.14,6.94-3.25,13.85-6.53,20.47-10.36,.51-.28,.52-.75,.03-1.07-2.42-1.71-5.05-3.18-7.34-5.04-.13-.12-.14-.45-.02-.59,6.18-3.91,12.66-7.57,18.83-11.53,.37,.03,.69-.01,.89,.09,2.81,1.48,5.54,3.05,8.13,4.63,.23,.62-.28,.86-.65,1.11Z"/><path class="cls-2" d="M1271.91,182.14c2.73-7.07,6.55-13.84,9.65-20.8l-.07,.07c17.28-.01,34.6,.47,51.86,.01l-.14-.13c-.71,6.33-3.05,12.44-4.39,18.68-.19,.73-.25,1.4M 9-.3,2.23-.01,.15,.25,.39,.46,.45,14.71,1.24,29.56,1.19,44.29,2.39,4.03,.25,8.05,.53,12.07,.8,.79,.08,2.01,.02,2.11,1.04,.16,6.45,0,12.91,.04,19.37-.04,.58-.05,1.52-.78,1.63-21.32-1.03-42.62-3.68-63.97-3.86l.1,.09c1.53-6.1,3.07-12.2,4.59-18.31,.05-.88,.86-2.66-.43-2.9-18.39-.7-36.79-.69-55.19-.89l.12,.12Z"/><path class="cls-2" d="M976.39,1292.07c5.18,.62,10.37,1.25,15.55,1.87,3.1,.54,6.5,.36,9.39,1.68v-.02c-.6,.1-.88,.44-1.01,.88-.52,1.78-1.04,3.56-1.55,5.35-8.27,28.13-17.38,56.08-27.38,83.69-.39,.99-1.88,.78-2.79,M .83-8.26-.1-16.48,.2-24.74-.15,6.32-19.51,14.76-38.71,21.08-58.29,3.91-11.31,7.57-22.66,11.35-34,.21-.63,.39-1.25,.2-1.91,0,0-.1,.06-.1,.06Z"/><path class="cls-2" d="M439.08,144.22c.41-.01,.86-.08,.97-.43,.53-1.67,1.03-3.34,1.52-5.01,8.58-28.57,17.51-57.17,28.03-85.12,8.76-.53,17.57-.01,26.36-.15,.25,0,.49,.14,.73,.21,.27,.55,.05,1.05-.15,1.57-2.01,5.24-4.07,10.48-6.01,15.74-9.6,25.48-18.63,51.2-27.02,77.06-.01,0,.08-.07,.06-.06-.38-.5-1.01-.65-1.68-.73-7.58-1.05-15.4-1.25-22.81-3.09Z"/><path class="cls-2" d="M164.M 64,1020.42c-36.95-9.62-73.85-19.97-109.74-32.76-.65-7.42-.2-18.46,.08-21.23,1.8-.34,3.52,.83,5.23,1.28,35.47,12.52,71.18,24.54,107.68,34.07l-.1-.08c-1.18,6.27-1.91,12.61-3.27,18.85l.12-.12Z"/><path class="cls-2" d="M266.55,1007.6c.02-5.64-.13-11.27,.02-16.91,25.63,5.47,53.01,11.43,79.68,14.23,.77-.13,.64-1.09,.66-1.67-.17-3.44-.35-6.88-.53-10.32-.04-1-.42-2.74,1.15-2.58,17.2,2.68,34.51,4.64,51.85,6.2,4.02,.3,8.04,.56,12.06,.84,.8,.06,1.62,.1,2.29,.53l-.08-.07c1.03,3.27,1.1,6.77,1.62,10.15,.14,1.16,.36,2.34-.04,3.51M l.13-.1c-20.12-1.34-40.24-2.48-60.24-5.14-2.39-.18-4.8-.8-7.2-.65-.22,.04-.51,.25-.54,.41-.42,4.81,.01,9.68-.07,14.51l.12-.09c-27.2-2.72-54.25-7.39-80.99-12.93l.1,.08Z"/><path class="cls-2" d="M158.18,1057.92c-34.73-7.53-69.69-15.4-103.48-26.1-.46-6.71,.02-13.55-.1-20.29,0-.32,.13-.63,.2-.91,.56-.27,1.06-.15,1.57,0,2.77,.84,5.54,1.67,8.31,2.51,31.76,9.85,64.28,18.18,96.7,26.17l-.07-.09c-.51,6.33-2.25,12.55-3.25,18.83l.13-.11Z"/><path class="cls-2" d="M822.93,1306.26c8.25-.92,16.47-2.37,24.78-2.59,.89,.29-.05,1.69-.M 22,2.29-13.05,26.32-27.1,52.19-41.6,77.79-.49,.87-.8,1.84-1.92,2.55-8.15,.24-16.37,.04-24.53,.1-.68-.06-2.24,.2-2.25-.74,15.76-26.21,31.38-52.55,45.84-79.46l-.09,.07Z"/><path class="cls-2" d="M342.37,130.12c4.44-25.31,10.01-50.4,15.64-75.48,.24-1.53,1.96-1.22,3.17-1.27,7.27,0,14.55,0,21.83,0,.93,0,1.9-.11,2.81,.36-6.21,26.36-13.25,52.65-18.43,79.28-.23,1.29-1.75,1.25-2.77,1.01-5.68-.9-11.35-1.81-17.03-2.71-1.6-.29-4.36-.39-5.22-1.2Z"/><path class="cls-2" d="M1073.79,1305.5c7.27,1.12,14.55,2.22,21.81,3.37,2.58,.33,2M .62,.81,2.24,3.24-4.58,24.75-9.6,49.41-15.48,73.9-1.17,.52-2.35,.39-3.58,.41-6.87,0-13.75,0-20.62-.01-2.95-.1-3.58,.41-2.78-2.97,6.94-25.84,12.51-52,18.53-78.03,0,0-.12,.1-.12,.1Z"/><path class="cls-2" d="M154.84,843.36c.94,6.3,1.77,12.61,2.5,18.94-.23,.71-1.01,.55-1.59,.28-29.78-13.91-58.92-28.75-87.62-44.53-3.55-1.95-7.09-3.92-10.63-5.89-1.36-.84-3.39-1.47-3.05-3.42-.02-6.03-.03-12.06-.03-18.09,.06-.73,.02-1.96,1.15-1.55,6.71,3.74,13.21,7.82,19.92,11.6,26.03,15.01,52.55,29.21,79.42,42.75l-.08-.08Z"/><path class="M cls-2" d="M1291.21,343.66c19.67,4.02,39.62,7.12,59.15,11.6,11.43,2.47,22.85,4.99,34.18,7.73,.9,.22,1.85,.33,2.64,1.05,.41,6.56,.03,13.26,.14,19.86,.09,2.43-1.57,1.37-3.13,1.14-32.05-8.44-64.42-15.72-97.05-22.03l.11,.1c1.5-6.46,1.94-13.24,4.09-19.5l-.13,.05Z"/><path class="cls-2" d="M151.08,1095.92c-32.28-4.74-64.34-11.96-96.08-19.4-.71-.64-.71-1.29-.71-1.94-.01-5.92,.02-11.85,.15-17.77-.03-2.97,1.3-1.99,3.43-1.59,31.24,8.07,62.66,15.29,94.41,21.35,.76,.17,2.07,.21,1.94,1.25-.36,2.13-.74,4.26-1.14,6.39-.47,2.56-1.03M ,5.1-1.43,7.67-.22,1.38-.92,2.72-.7,4.14l.12-.1Z"/><path class="cls-2" d="M476.1,686.23s.01,.02,.01,.03c-.05,.03-.11,.05-.16,.08l.15-.11Z"/><path class="cls-2" d="M488.05,705s.06,0,.09,0c.02,.02,.03,.03,.04,.05l-.13-.06Z"/><path class="cls-2" d="M518.95,704.74c-1.63,3.14-3.44,6.2-5.41,9.16-.48,.36-.97,.72-1.47,1.06-.75-.09-1.12-.38-1.42-.76-4.1-4.92-7.41-10.37-11.59-15.2-3.34,1.72-6.34,3.68-9.57,5.54-.41,.24-.8,.49-1.35,.47-4.23-6.08-8.73-12.17-12.03-18.75,3.73-1.64,7.09-4.05,10.73-5.83,.93,.38,1.17,1.02,1.53,1.59,M 3.68,5.32,6.59,11.21,10.71,16.18,.65,.02,1.08-.23,1.47-.53,2.65-2.05,5.36-4.23,8.03-6.22,.92,.13,1.19,.63,1.53,1.09,2.94,4.06,5.87,8.15,8.84,12.2Z"/><path class="cls-2" d="M646.68,678.52s0,.05-.01,.07c-.68,4.69-1.19,9.52-2.68,14.02-3.25-.7-6.18-2.13-9.37-3.01-.33-.11-.87,.13-.95,.41-.85,2.58-1.07,5.31-1.62,7.96-.28,1.49-.59,2.97-.9,4.46-.09,.43-.7,.64-1.25,.43-3.07-1.02-5.91-2.71-9.02-3.55-.21-.02-.6,.14-.64,.26-1.17,4.1-1.67,8.25-2.98,12.35-1.55-.01-2.54-.83-3.68-1.34-2.39-.97-4.36-2.61-6.88-3.26-.71,.44-.81,1.63-M 1.12,2.37-.91,3.08-1.43,6.38-2.67,9.33-.75,.18-1.18-.06-1.57-.36-2.45-1.84-4.89-3.69-7.35-5.54-.62-.34-1.46-1.39-2.2-.87-1.44,3.09-2.31,6.4-3.5,9.59-.22,.61-.73,1.47-1.51,1.06-13.86-10.12-7.85-12.21-15.59,2.06-.93,0-1.36-.44-1.79-.85-3.2-2.99-6.23-5.97-9.5-8.91,1.75-3.67,2.79-7.63,4.84-11.14,1.02-.96,2.27,1.3,3.09,1.85,2.23,2.15,4.45,4.32,6.69,6.47,.47,.38,1.22,1.17,1.86,.71,1.99-3.17,2.56-7.1,4.42-10.33,.67-.45,1.42,.33,1.93,.7,2.66,2.3,5.19,4.68,7.92,6.9,.55,.45,1.38,.32,1.56-.25,1.15-3.53,2.03-7.15,3.39-10.62,.6M 1-.83,1.59,.26,2.17,.66,1.81,1.44,3.6,2.9,5.42,4.34,.9,.47,2.51,2.58,3.33,1.12,1.17-3.85,1.82-7.82,3.09-11.62,.18-.05,.32-.14,.4-.12,3.58,1.02,6.16,3.43,9.79,4.5,.24-.23,.63-.45,.7-.71,.4-1.69,.72-3.39,1.1-5.09,.53-2.32,1.08-4.64,1.65-6.96,.04-.16,.33-.27,.61-.47,1.93,.61,3.74,1.62,5.63,2.38,4.69,2.07,4.08,1.69,4.97-2.35,2.87-12.94-.35-10.86,12.12-6.68h.01l.09,.03Z"/><path class="cls-2" d="M771.18,1312.07c7.2-.82,14.39-1.64,21.59-2.46,1.93-.16,4.6-.76,2.99,1.71-14.74,25.38-30.53,50.37-46.9,74.83-.47,.08-.98,.23-1.5M ,.23-8.5-.11-17.03,.29-25.5-.14-.21-1.48,1.28-2.53,1.95-3.75,7.65-10.64,15.03-21.4,22.32-32.2,8.69-12.63,16.74-25.56,25.17-38.28l-.11,.06Z"/><path class="cls-2" d="M977.4,1211.23c6.65-.94,13.42-.27,20.13-.41,.64,.03,1.76,.09,1.85,.88-.13,.85-.2,1.72-.42,2.56-4.72,18.35-9.63,36.64-15.03,54.81-2.09,7.12-4.34,14.2-6.52,21.3-.19,.63-.31,1.27-1.03,1.7,0,0,.1-.06,.1-.06-8.36,.13-16.79-.02-25.06,1.26l.15,.07c9.39-27.15,17.98-54.61,25.89-82.18l-.08,.08Z"/><path class="cls-2" d="M1299.31,304.92c29.38,3.86,58.63,8.6,87.69,14M .3,.15,.39,.36,.69,.36,.99,0,6.56,0,13.12-.03,19.68-.02,1.89-2.19,.93-3.35,.82-24.8-5.07-49.53-10.16-74.6-13.97-4.68-.91-9.59-1.09-14.11-2.53l.07,.09c-.22-3.21,1.32-6.56,1.75-9.78,.54-2.63,1.04-5.27,1.54-7.9,.12-.64,.29-1.26,.79-1.79l-.11,.08Z"/><path class="cls-2" d="M142.84,1134.84c-28.64-3.11-57.14-8.26-85.46-13.49-1.55-.34-3.73-.32-3.4-2.39,.04-6.35-.03-12.7,.08-19.05,.05-.83,.61-1.2,1.55-1,3.13,.64,6.26,1.28,9.37,1.95,26.83,5.74,55.12,10.7,81.75,14.61-1.41,6.48-3.03,12.93-4.05,19.48l.15-.11Z"/><path class="clsM -2" d="M476.01,659.09s0,.03-.01,.04c-.02,0-.03,.02-.05,.03l.06-.07Z"/><path class="cls-2" d="M528.89,676.29c-1,5.22-2.39,10.35-4.2,15.35-2.02-2.85-4.02-5.7-6.01-8.57-.19-.25-.59-.39-1-.64-2.26,2.16-4.33,4.4-6.55,6.59-.66,.51-1.62,1.75-2.5,1.04-3.34-4.59-6.08-9.61-9.17-14.36-.74-1.06-1.05-2.3-2.27-2.97-3.09,2.15-5.8,4.59-8.99,6.6-.59,.39-1.21,.22-1.6-.4-3.66-6.53-7.67-13.07-10.6-19.8,3.66-2,6.72-4.61,10.11-6.85,1.07-.29,1.41,1.45,1.92,2.11,3.1,5.8,5.73,11.89,9.32,17.41,.75,.03,1.17-.24,1.53-.56,2.46-2.12,4.82-4.32,7M .12-6.6,.24-.23,.66-.32,.98-.47,4,5.22,6.54,11.44,10.47,16.76,.16,.22,.86,.28,1.05,.07,2.5-2.61,4.57-5.56,6.81-8.38,1.26-1.11,2.77,2.9,3.58,3.67Z"/><path class="cls-2" d="M626.41,670.72c-.93,4.02-1.83,8.05-2.73,12.07-.13,.5-.21,1.06-.89,1.35-2.97-.76-5.44-2.75-8.21-4.02-.48-.26-.97-.35-1.57-.15-1.35,3.98-2,8.21-3.23,12.25-.06,.24-.79,.42-1.01,.27-2.46-1.59-4.58-3.64-6.88-5.44-.51-.41-1.72-1.6-2.17-1.15-.25,.23-.54,.49-.62,.78-4.56,15.93-1.55,12.26-13.09,3.13-.95-.31-1.18,1.27-1.52,1.87-.91,2.59-1.76,5.2-2.67,7.78-.M 87,2.18-1.4,1.78-2.89,.36-2.74-2.64-5.18-5.59-8.1-8.03-.14-.1-.48-.02-.81-.02-1.38,3.15-2.72,6.31-4.13,9.44-.16,.42-.33,1.01-1,1.02,1.44-4.37,2.67-8.8,3.69-13.29,.56,.5,.92,1.24,1.76,1.23,.62-.59,.84-1.33,1.12-2.04,1.13-2.88,2.28-5.75,3.44-8.61,.07-.17,.35-.35,.57-.4,.21-.05,.58,0,.7,.13,2.53,2.64,4.98,5.36,7.54,7.99,.88,.85,1.91,1.46,2.31-.18,1.15-3.43,2.29-6.86,3.44-10.29,.73-.96,1.74,.48,2.36,.94,2.31,2.09,4.39,4.44,6.86,6.35,.17,.12,.49,.12,.76,.17,.72-.69,.84-1.55,1.07-2.38,.87-3.15,1.75-6.3,2.63-9.45,.73-1.28M ,1.95,.23,2.66,.78,2.09,1.67,3.96,3.62,6.18,5.1,.27,.15,.73,.07,1.16,.1,1.4-4.41,2.09-8.89,3.61-13.33,3.72,1.47,6.24,3.35,9.63,5.05,.01,.2,.07,.43,.03,.62Z"/><path class="cls-2" d="M626.45,670.14s-.05-.03-.07-.04v-.02l.07,.06Z"/><path class="cls-2" d="M1048.73,359.22c1.68-4.25,4.15-8.16,6.19-12.25,.43-.99,1.53-2.48-.38-2.43-13.97,.67-27.93,1.46-41.85,2.75-4.68,.41-9.36,.84-14.02,1.4-.66,.07-1.33,.18-2.09-.18,2.27-5.09,5.7-9.69,8.44-14.56l-.1,.06c19.53-1.86,39.06-4.02,58.68-4.63,1.25,.33,.18,1.5-.12,2.2-2.13,4.06-4.M 76,7.92-6.57,12.13-.05,.13,.19,.46,.35,.48,5.36,.31,10.77-.14,16.14-.18,16.84-.57,33.68,.04,50.52,.34l-.15-.1c-2.25,5.23-4.49,10.64-7.28,15.59l.1-.05c-22.66-.5-45.33-1.05-68.02-.67l.16,.08Z"/><path class="cls-2" d="M1148.03,1317.86c.33,.5,.27,1.04,.2,1.58-.41,3.1-.79,6.21-1.23,9.31-1.89,13.7-3.97,27.37-6.23,41.02-.85,5.12-1.71,10.24-2.57,15.36-.09,1.05-1.31,1.44-2.25,1.38-7.95,0-15.89-.01-23.84-.02-.64,0-1.89-.13-1.75-.9,3.65-19.35,7.57-38.66,10.66-58.12,.62-3.62,1.27-7.25,1.84-10.88,.16-1.04,.56-2.12-.04-3.17,0,0-M .14,.08-.14,.09,7.9,.73,15.73,2.63,23.59,3.82,.64,.11,1.23,.4,1.84,.61l-.08-.07Z"/><path class="cls-2" d="M317.66,126.38c-8.46-1.47-17.07-2.43-25.38-4.58l.09,.07c1.97-18.53,5.13-37,8.11-55.42,.62-3.73,1.22-7.46,1.85-11.19,.17-1.63,1.31-2.11,2.85-1.98,7.67,0,15.34,.02,23.01,.05,1.14,.06,2.4,.08,2.01,1.62-4.58,23.75-9.58,47.55-12.67,71.5l.13-.09Z"/><path class="cls-2" d="M410.52,983.6s.02,.07,.03,.11c-.04-.01-.08-.01-.12-.01l.09-.1Z"/><polygon class="cls-2" points="413.65 997.84 413.73 997.84 413.73 997.91 413.65 997M .84"/><path class="cls-2" d="M471.87,998.56s.02-.07,.02-.1h.08l-.1,.1Z"/><path class="cls-2" d="M469.67,986.42c-.02,3.27,1.37,6.37,1.95,9.58,.2,.82,.46,1.62,.27,2.46-19.39,.86-38.78-.05-58.16-.62,.1-4.88-1.47-9.53-3.18-14.13,18.83,1.42,37.71,2.7,56.62,2.53,3.37,.2-.1-3.8-.51-5.27-1.07-2.09-2.14-4.17-3.23-6.25-.21-.42-.31-.82-.07-1.24,1.41-.4,2.95-.12,4.41-.19,10.95,4.17,22.08,8.07,33.38,11.7-10.49,.78-20.96,1.03-31.48,1.43Z"/><path class="cls-2" d="M548.1,956.57h-.05s-.03-.04-.05-.06l.1,.06Z"/><path class="cls-2" dM ="M548.1,956.57l-.1-.06s.03,0,.05,0c.02,.02,.03,.05,.05,.07Z"/><path class="cls-2" d="M658.64,851.69c-3.52,3.02-7.33,5.71-10.97,8.58-.58,.45-1.3,.8-1.54,1.48,2.33,1.69,6.05,2.5,8.75,3.81,1.17,.47,1.19,.86,.13,1.64-4,2.94-8.27,5.51-12.56,8.12-.5,.46-2.3,1.02-1.83,1.8,2.71,1.98,6.35,2.74,8.96,4.78-.26,.69-1.02,1-1.65,1.38-4.76,2.82-9.62,5.53-14.67,8.02-.52,.39-2.04,.67-1.72,1.49,2.47,1.88,5.33,3.28,7.95,4.95,.46,.28,.45,.85,0,1.09-6.68,3.4-13.71,6.06-20.76,8.63-.49,.19-.91,.42-.98,1.01,2.68,2.21,6.04,3.83,8.5,6.44-8.M 37,3.67-17.25,6.09-26,8.89-.3,.1-.43,.62-.19,.84,1.89,1.68,3.8,3.35,5.67,5.04,.7,.63,1.63,1.14,1.93,2.01-.41,.48-1.02,.67-1.66,.88-9.14,2.92-18.62,5.1-27.98,7.35-1.36,.36-.47,1.48,.15,2.07,2.12,2.43,4.48,4.52,6.32,7.18-11.83,3.53-24.24,5.13-36.43,7.33-2.47-3.31-5.18-6.47-7.55-9.81-.06-.08-.01-.21-.01-.43,11.74-2.08,23.76-3.15,35.32-6.1,.34-1.49-9.08-8.2-7.3-8.92,10.02-2.45,20.29-4.01,30.06-7.19-.21-1.02-1.19-1.5-1.87-2.14-1.42-1.31-3.03-2.46-4.49-3.72-.68-.62-1.78-1.03-1.81-2.07,8.27-2.54,16.75-4.55,24.88-7.46,1.04M -.37,1.2-.89,.43-1.43-2.12-1.5-4.26-2.98-6.38-4.47-.5-.36-.97-.74-1.45-1.12-.88-.92,2.95-1.56,3.55-1.96,5.3-1.87,10.68-3.59,15.79-5.77,.83-.35,1.63-.74,2.4-1.16,.14-.08,.2-.46,.1-.56-2.47-1.9-5.43-3.18-8.08-4.8-.47-.27-.77-.58-.73-1.16,5.71-2.42,11.5-5.11,16.83-8.16,.46-.33,1.58-.77,1.16-1.43-2.88-1.62-5.93-2.96-8.9-4.42-.3-.15-.31-.66-.02-.85,4.03-2.54,8.15-4.93,12.21-7.43,1.03-.7,2.16-1.16,2.83-2.25-3.3-1.76-6.94-2.73-10.24-4.42,.5-1.12,1.67-1.54,2.54-2.19,.89-.65,1.86-1.24,2.77-1.88,2.94-1.91,5.4-4.18,8.3-6.16,3M .43,1.16,6.75,2.31,10.01,3.56,.47,.18,.61,.77,.24,1.09Z"/><path class="cls-2" d="M1303,284.44c.53-.22,.72-.63,.81-1.05,1.34-5.71,2.7-11.41,3.93-17.14,.57-1.73,3.63-.6,5.04-.71,21.34,2.2,42.64,4.73,63.88,7.7,3.18,.44,6.36,.92,9.53,1.39,.69,.1,1.15,.55,1.19,1.13,.13,6.35,0,12.7,.03,19.06,0,.63,.16,1.3-.48,1.88-18.24-2.25-36.39-6-54.72-8.01-5.44-.72-10.89-1.43-16.34-2.11-3.32-.42-6.66-.79-9.99-1.18-1.08-.12-2.12-.31-2.9-1l.02,.05Z"/><path class="cls-2" d="M138.02,1155.09c-1.53,5.89-2.87,11.82-4.13,17.75-.28,1.74-1.05,M 1.73-2.61,1.63-25.75-2.29-51.37-5.63-76.94-9.36-.67-.87-.54-1.84-.57-2.86,.02-5.59,.06-11.18,.1-16.78-.11-2.93,1.14-2.14,3.37-2,16.62,2.67,33.22,5.43,49.93,7.54,8.89,1.19,17.79,2.26,26.7,3.32,1.46,.17,2.95,.26,4.28,.85,0,0-.12-.1-.12-.1Z"/><path class="cls-2" d="M167.88,1001.77c.78-5.56,1.6-11.11,2.41-16.66,.11-.67,.3-1.48,1.22-1.33,31.21,9.08,62.97,17.28,95.03,23.81l-.1-.08c-.99,5.47-2.79,10.82-4.05,16.25l.13-.07c-31.84-6.17-63.67-12.94-94.74-22.01l.1,.08Z"/><path class="cls-2" d="M161.38,1039.29c1.58-6.15,2.49-12M .57,3.26-18.87l-.12,.12c30.82,7.29,61.77,14.05,93.13,19.4l-.09-.1c-1.25,5.46-3.33,10.81-4.86,16.24l.14-.08c-30.8-3.61-61.25-10.51-91.53-16.8l.07,.09Z"/><path class="cls-2" d="M1199.82,1327.52c-1.65,14.47-2.68,28.99-4.52,43.44-.4,3.54-.76,7.08-1.17,10.62-.16,1.39-.41,2.77-.64,4.16-.07,.42-.58,.74-1.12,.78-7.81,.18-15.62,0-23.43,.03-.84-.13-2.46,.17-2.89-.65-.06-.53-.08-1.08,0-1.61,3.09-20.61,5.63-41.29,7.99-61.99l-.12,.11c8.64,1.81,17.46,3.08,26,5.19l-.08-.08Z"/><path class="cls-2" d="M266.08,117.79c-.16-.46-.58-.7-M 1.13-.8-7.33-1.37-14.66-2.79-21.98-4.21-.8-.15-1.89-.5-1.78-1.45,.73-11.08,1.85-22.13,3.11-33.17,.88-7.83,1.81-15.65,2.73-23.47,0-1.36,1.33-1.51,2.48-1.48,7.41,0,14.82,.02,22.23,.03,3.76-.19,2.85,1.04,2.64,3.95-1.78,13.16-3.8,26.29-5.36,39.48-.5,4.18-.99,8.36-1.47,12.54-.46,2.89-.06,5.92-1.51,8.6,0,0,.04-.01,.04-.01Z"/><path class="cls-2" d="M241.47,1089.6c-27.16-2.22-54.14-7.06-81-11.59-1.58-.27-3.14-.59-4.71-.9-.43-.08-.92-.63-.87-.98,.97-6.09,2.21-12.14,3.29-18.21l-.13,.11c29.52,5.69,59.17,11.1,89.08,14.87l-.1-.M 1c-1.53,5.69-3.86,11.25-5.67,16.89l.11-.09Z"/><path class="cls-2" d="M747.01,609.29c-3.24-.4-6.47-1.46-9.69-2.12-.32-.08-.55-.42-.85-.67,2.81-4.45,6.53-8.13,9.48-12.5-2.57-1.39-5.45-1.84-8.19-2.8-.53-.16-.93-.42-1.21-.92,3.11-4.13,7.04-7.92,10.71-11.65,.34-.34,.61-.71,.5-1.3-2.73-1.39-5.94-2.27-8.89-3.75,3.93-4.84,9.3-8.67,13.78-12.96-.08-.55-.43-.83-.92-1.07-2.52-1.24-5.03-2.51-7.54-3.76-.6-.03-.97,.28-1.31,.61-4.83,4.24-9.15,9-14.2,12.93-2.93-1.13-5.64-2.73-8.63-4.01-5.01,4.46-8.44,9.77-13.25,14.43-3.04-1.2-5.88-M 2.58-8.69-4.16,3.69-4.98,8.01-9.27,12.01-14,.86-.98,1.26-.97,2.65-.21,2.01,1.09,4.02,2.16,6.05,3.22,.72,.38,1.28,.31,1.76-.19,4.21-4.55,8.76-8.77,13.35-12.96,.48-.45,1.16-.49,1.82-.14,2.37,1.23,4.69,2.54,7.09,3.73,1.24,.6,2.07-.55,2.97-1.16,4.89-3.87,10.01-7.48,14.76-11.49-.06-.2-.03-.49-.19-.59-2.73-1.6-5.2-3.67-8.11-4.93-6.27,3.92-11.66,9.16-17.54,13.58-2.31-1.15-6.22-3.48-7.78-4.65-.28-.21-.36-.66-.16-.88,5.36-4.86,10.88-9.69,16.93-13.89,3.15,1.36,5.54,3.72,8.55,5.47,6.73-4.4,13.18-8.97,20.08-13.05,2.12,1,5.38,3M .33,8.5,6.07-6.31,4.15-12.98,7.88-19.16,12.31,.24,.37,.34,.72,.62,.89,2.43,1.53,5.09,2.76,7.4,4.47,.14,.11,.22,.46,.12,.54-4.79,3.65-9.88,6.99-14.44,10.81-.48,.55-2.13,1.28-1.16,2.05,2.66,1.25,5.35,2.45,7.95,3.81,.26,.13,.31,.67,.08,.87-4.46,4.09-9.36,7.67-13.49,12.1,3.07,1.55,6.48,2.3,9.4,3.67,.09,.73-.43,1.1-.83,1.51-3.52,3.74-7.35,7.1-10.6,11.08,13.98,5.64,12.31-.8,.26,15.65Z"/><path class="cls-2" d="M849.57,657.23c4.32,2.23,8.66,4.7,12.87,7.05,1.24-.49,1.59-1.36,2.24-2.01,1.95-2.11,3.77-4.21,5.93-6.15-.26-.31-.M 41-.63-.71-.81-4.02-2.49-8.22-4.76-12.14-7.41,1.92-2.26,4.3-3.99,6.77-5.67,.9-.61,2.06-1.07,2.48-2.2-3.91-2.76-8.65-4.61-12.44-7.49,2.71-2.15,3.82-2.77,11.63-6.47,.6-.07,.99,.21,1.42,.48,3.29,2.06,6.59,4.1,9.88,6.16,.73,.45,1.55,.85,1.97,1.66-3.7,1.97-7.74,3.49-11.23,5.59-.02,.57,.29,.89,.72,1.17,3.36,2.16,6.72,4.32,10.06,6.5,.7,.46,1.54,.83,1.92,1.68-2.69,1.7-5.66,3.26-8.13,5.23-1.75,1.37-1.75,1.43,.09,2.7,3.87,2.71,7.84,5.2,11.57,8.09-2.72,2.85-5.86,4.98-8.61,7.86-3.81-2.28-7.25-4.85-10.94-7.29-.6-.41-1.16-.9-2.2M -.99-2.78,2.68-4.25,6.11-6.92,9.05-4.2-2.09-8-4.5-12.19-6.36-.28,.18-.57,.27-.68,.44-1.87,2.99-3.36,6.1-4.78,9.23-.2,.44-.02,.93,.4,1.16,3.6,1.9,7.2,3.79,10.81,5.67,.19,.1,.49,.07,.87,.11,1.68-2.64,2.94-5.54,4.58-8.21,.97-1.58,1.33-1.66,2.93-.65,3.32,2.16,6.5,4.53,9.74,6.8,1.06,.75,1.13,1.06,.59,1.94-1.6,2.61-3.21,5.22-4.81,7.82-.57,.92-1.09,.97-2.15,.23-2.9-2.11-5.9-4.1-8.87-6.13-.63-.35-1.72-1.31-2.34-.54-6.83,13.19-1.4,10.97-14.86,4.99-1.36-.65-1.99-.48-2.38,.66-1.12,3.21-2.07,6.47-3.27,9.65-.1,.26-.69,.46-.99,.M 33-3.74-1.5-7.27-3.28-11.19-4.46l.08,.06c1.69-4,2.02-8.53,4.09-12.34,2.63,1.05,5.21,2.22,7.81,3.34,1.27,.52,2.36,1.38,4.03,1.44,1.55-3.51,2.74-7.03,4.19-10.48,.07-.17-.05-.4-.11-.73-3.67-1.83-7.5-3.57-11.53-5.09-.29,.32-.63,.54-.74,.82-1.26,3.28-2.49,6.57-3.7,9.87-.1,.27,.08,.61,.13,.92-4.06-1.66-8.23-3.05-12.34-4.6,5.33-15.11,.42-12.68,15.61-7.66,.88-.22,1.12-.72,1.35-1.23,1.15-2.53,2.27-5.06,3.46-7.58,.27-.57,.44-1.25,1.22-1.57,3.7,.95,7.69,3.42,11.33,4.91,.7,.31,1.31,.18,1.68-.38,1.88-3.09,4.14-6.05,5.9-9.15l-.1M 4,.06Z"/><path class="cls-2" d="M150.95,1096.03c27.85,4.91,55.97,8.17,84.08,11.15-1.99,5.23-4.43,11.77-6.61,17.43l.12-.07c-27.37-1.76-54.62-5.35-81.8-9.06l.12,.11c1.46-6.53,2.32-13.23,4.21-19.65,0,0-.12,.1-.12,.1Z"/><path class="cls-2" d="M1313.16,244.77c-.19-1.62,.51-3.15,.85-4.71,1.23-5.09,2.27-10.28,3.87-15.27l-.08,.07c6.25-.6,12.58,.63,18.85,.92,16.06,1.15,32.08,2.61,48.09,4.27,1.21,.16,2.92,.16,2.72,1.72,.02,3.44,.02,6.88,.01,10.32,0,2.9-.02,5.8-.03,8.71,0,.53,.02,1.07-.52,1.54-12.5-.96-24.96-2.98-37.46-4.15-1M 2.1-1.39-24.34-1.89-36.4-3.52l.1,.09Z"/><path class="cls-2" d="M123.43,1214.96c-21.71-.31-43.77-3.21-65.45-5.06-1.66-.26-4.7,.18-4.42-2.17,0-1.94,.05-3.88,.06-5.81,.02-4.2,.03-8.4,.06-12.6,0-.63-.08-1.3,.69-1.86,22.35,2.55,44.74,5.25,67.19,6.94,1.74,.15,3.48,.28,5.22,.46,1.26,.13,1.59,.52,1.39,1.53-1.51,6.22-2.75,12.57-4.79,18.64l.08-.07Z"/><path class="cls-2" d="M1332.76,1370.74c.15-5.16-.05-10.35,.34-15.5,.63-1.09,2.6-.26,3.63-.24,7.2,1.38,14.35,2.96,21.56,4.26,2.69,.67,2.13-1.76,2.19-3.46,.02-7.43-.27-14.87-.04-M 22.29,.02-.42,.69-.74,1.18-.56,3.43,1.25,6.85,2.52,10.28,3.77,4.78,1.74,9.57,3.47,14.35,5.2,.96,.35,1.42,.92,1.41,1.77-.01,1.94,.01,3.88,.01,5.82,0,4.2,0,8.4,0,12.6-.13,.88,.34,2.42-1,2.43-8.19-1.1-16.26-3.02-24.39-4.48-1.15-.22-1.67,.15-1.72,1.19-.07,8.08-.01,16.16-.12,24.24,.11,1.74-1.71,1.68-3.1,1.65-7.28,0-14.56-.02-21.84-.03-1-.04-2.74,.14-2.83-1.18-.15-5.06,.07-10.12,.09-15.19h0Z"/><path class="cls-2" d="M1349.41,96.78c-12.27-.05-24.53,.75-36.79,.43,0-.35-.11-.7,.02-.97,2.92-6.36,5.9-12.7,8.77-19.08,1.32-2.41M -1.29-1.85-2.81-1.94-8.35,.12-16.7,.25-25.05,.36-.82-.15-3,.37-2.92-.84,4.59-7.32,9.1-14.75,14.04-21.85,8.48-.33,16.97-.04,25.46-.13,2.83-.12,1.62,1.18,.99,2.91-2.56,5.78-5.13,11.56-7.7,17.34-1.1,1.99-.17,2.04,1.68,2.03,9.96-.16,19.95-.04,29.9-.35l-.13-.09c-.65,6.06-2.84,11.98-4.07,17.98-.42,1.47-.38,3.1-1.48,4.27l.1-.07Z"/><path class="cls-2" d="M740.58,623.02c-.18-.55,.07-1.04,.32-1.54,2.04-4.06,4.07-8.12,6.11-12.19l-.09,.06c3.48,1.08,7.19,1.81,10.65,2.68,.35-.18,.64-.26,.78-.42,3.09-3.53,6.17-7.06,9.24-10.6,.86-M 1.02-.91-1.4-1.68-1.61-2.57-.78-5.31-1.43-7.8-2.38-.33-.58,.07-.91,.37-1.22,3.26-3.62,7.02-7.08,10.58-10.46-.14-.62-.64-.81-1.1-.97-2.85-1.03-5.68-1.92-8.51-3.06,.27-1.23,1.4-1.79,2.26-2.62,3.35-2.8,6.71-5.6,10.07-8.39,.46-.38,1-.73,.93-1.47-2.81-1.27-5.95-2.34-8.69-3.9-.16-.09-.25-.42-.17-.56,4.74-4.32,10.57-7.58,15.69-11.46-.01-.6-.34-.89-.82-1.14-1.92-1-3.84-2-5.74-3.01-.52-.41-1.94-.73-1.67-1.53,5.7-4.53,12.57-7.78,18.74-11.59,.37,.07,.68,.07,.87,.18,2.74,1.86,5.98,3.25,8.42,5.43-.34,.65-1.13,.9-1.78,1.27-5.42,M 3.2-11.02,6.14-16.34,9.49-.4,.28-.34,.83,.16,1.1,2.7,1.4,5.42,2.8,8.08,4.27,.59,.74-1.24,1.41-1.72,1.86-4.41,2.67-8.49,5.65-12.61,8.59-.49,.35-.99,.69-1.22,1.3,3.01,1.66,6.53,2.58,9.44,4.25-.13,.79-.83,1.16-1.41,1.59-3.66,2.71-7.23,5.49-10.55,8.46-1.85,1.58-.72,1.75,.94,2.38,2.34,.82,4.7,1.61,7.05,2.42,.66,.23,.79,.84,.29,1.32-3.62,3.57-7.52,6.69-10.89,10.52,3.34,1.22,6.51,2.09,9.86,3.16,.55,.17,.78,.71,.46,1.06-3.18,3.54-6.57,6.79-9.4,10.62,3.61,1.43,7.56,1.81,11,3.19,.22,.48,.04,.86-.18,1.26-1.37,2.46-2.73,4.92-4M .08,7.38-.49,1.24-2.5,3.36-.16,3.84,3.47,.83,6.9,1.81,10.33,2.76l-.1-.11c-1.71,3.74-3.5,7.45-5.16,11.21-.33,.69-1.43,.63-2.11,.47-3.23-.84-6.57-1.19-9.7-2.38,.99-4.07,3.01-7.81,4.77-11.64,.28-1.16-1.93-1.09-2.68-1.45-2.85-.66-5.7-1.29-8.55-1.94,1.31-4.09,3.86-7.76,5.73-11.64,.19-.36-.13-.94-.59-1.06-3.06-.78-6.13-1.56-9.2-2.32-.72-.18-1.29,.07-1.6,.66-1.57,2.96-3.11,5.93-4.66,8.9-.67,.97-.75,2.7-2.2,2.79-3.4-.4-6.76-1.34-10.14-1.95l.16,.13Z"/><path class="cls-2" d="M189.3,102.26c-.68-.5-.54-1.39-.57-2.14,.18-4.31,.M 37-8.61,.57-12.92,.47-7.42,.87-14.85,1.33-22.27,.27-3.65,.41-7.33,.84-10.96,.27-1.06,1.77-.92,2.65-.97,7.68,.01,15.37,.04,23.05,.07,.75-.05,1.6,.15,1.89,.87-.77,11.35-2.08,22.78-2.79,34.17-.43,5.7-.83,11.4-1.26,17.1-.05,.63,.02,1.31-.71,1.8-8.4-1.24-16.63-3.52-25.07-4.79-.02-.01,.06,.06,.06,.06Z"/><path class="cls-2" d="M1252.55,1337.94c-.5,.55-.56,1.2-.6,1.85-.11,1.94-.22,3.87-.28,5.81-.24,7.97-.81,15.92-1.4,23.88-.28,5.27-.65,10.54-1.05,15.81-.05,.53-.24,1.21-.85,1.33-8.04,.51-16.15,.02-24.22,.16-1.04,0-2.66,0-2.M 57-1.36,.53-9.04,1.67-18.04,2.34-27.07,.83-8.46,.78-17.07,2.06-25.45,8.95,1.16,17.78,3.61,26.7,5.16,0,0-.13-.1-.13-.1Z"/><path class="cls-2" d="M1244.37,241.5c22.97,.28,45.86,2.13,68.79,3.27l-.1-.09c-1.62,6.43-3.24,12.86-4.89,19.28-.46,1.77-4,.56-5.41,.72-2.68-.2-5.36-.43-8.03-.66-17.81-1.69-35.67-2.55-53.54-3.27-1.18-.29-5.49,.37-4.85-1.49,2.72-5.91,4.91-12.22,8.14-17.84l-.11,.07Z"/><path class="cls-2" d="M196.62,1198.39c-12.23-.58-24.49-.83-36.72-1.49-5.51-.27-11.02-.66-16.52-1.01-4.43-.29-8.86-.61-13.29-.92-1.35M -.07-1.27-1.1-1.05-2.01,1.39-5.59,2.78-11.19,4.18-16.78,.14-.55,.47-1.15,1.15-1.18,9.41,.32,18.76,1.47,28.15,2.04,13.95,1.17,27.95,1.44,41.91,2.35,.8,.21,.66,1.1,.36,1.67-2.38,5.38-4.77,10.75-7.16,16.13-.23,.51-.49,1-1.15,1.28-.01,0,.12-.06,.12-.06Z"/><path class="cls-2" d="M112.37,1257.38c-.33-.16-.66-.43-1-.45-2.82-.17-5.65-.29-8.47-.43-13.58-.64-27.17-1.23-40.75-2.07-1.88-.11-3.75-.32-5.63-.42-3.38-.19-3.39-.21-3.37-2.8,.05-5.6,.09-11.2,.14-16.8,.06-1.09-.2-2.62,1.45-2.54,3.36,.12,6.71,.44,10.06,.71,17.16,1.54,3M 4.36,2.54,51.57,3.33,1.3,.08,1.76,.47,1.58,1.39-.57,2.88-1.37,5.71-2.09,8.56-.78,3.06-1.57,6.12-2.32,9.18-.21,.86-.48,1.68-1.23,2.35,0,0,.06-.02,.06-.02Z"/><path class="cls-2" d="M1194.07,366.88c.24,.66-.03,1.27-.23,1.9-1.44,5.02-3.57,9.91-4.51,15.03l.09-.09c-26.35-3.7-52.84-6.69-79.4-8.33,2.15-5.21,4.59-10.31,6.56-15.59l-.1,.05c25.96,1.79,51.91,3.86,77.73,7.14l-.15-.12Z"/><path class="cls-2" d="M331.12,1064.38c-1.6,5.36-4.4,10.4-6.45,15.63l.11-.07c-25.97-1.78-51.94-3.66-77.75-7.14l.1,.1c1.94-5.62,3.42-11.42,5.7-16M .91l-.14,.08c26,4.26,52.29,6.46,78.55,8.42l-.13-.12Z"/><path class="cls-2" d="M1183.54,399.84c.03,.42,.18,.87,.07,1.26-1.31,4.73-2.66,9.45-4.01,14.16-.54,1.84-4.35,.12-5.77,.09-24.88-4.32-49.97-8.24-75.16-10.29l.13,.08c1.87-4.99,3.43-10.1,5.55-15,26.57,2.32,53.03,5.89,79.36,9.81l-.17-.12Z"/><path class="cls-2" d="M1322.73,204.02c-1.51,6.97-3.58,13.84-4.93,20.84l.08-.07c-7.5-1.31-15.32-.86-22.92-1.44-13.06-.52-26.12-1.09-39.19-1.2-2.45-.09-2.84-.03-1.7-2.5,2.69-5.86,5.53-11.66,8.09-17.58l-.09,.06c20.21,.86,40.65,.1,M 60.75,1.98l-.1-.09Z"/><path class="cls-2" d="M179.17,1237.68c-19.76-.78-39.58-.45-59.33-1.69-1.3-.07-1.29-1.1-.94-2.02,1.47-6.34,3.54-12.57,4.51-19.01l-.08,.06c21.14,2.05,42.62,1.92,63.88,2.69,.31,.02,.73,.45,.63,.68-2.74,6.52-6.2,12.76-8.77,19.34l.09-.06Z"/><path class="cls-2" d="M436.03,360.73c-1.33-.36-2.67-.14-3.98,0-4,.41-8.03,.37-12.05,.48-.95,.03-1.88-.02-2.73-.44-.01,0,.04,.05,.03,.04,.2-.26,.56-.5,.61-.78,.79-4.79,1.03-9.65,1.62-14.47,1.77-15.12,3.79-30.24,6.47-45.22,.1-.54,.94-.84,1.53-.83,5.52-.12,11.04-M .24,16.56-.35,.78-.05,2.22,.08,2.08,.98-1.95,12.39-4.57,24.68-6.42,37.09-1.11,7.15-1.99,14.33-2.9,21.51-.1,.74-.16,1.51-.91,2.07l.09-.07Z"/><path class="cls-2" d="M1023.11,1078.99c-.96,1.08-.73,2.68-.99,4.03-.67,6.33-1.26,12.67-1.99,18.99-1.59,12.43-3.51,24.83-5.55,37.2-.18,1.29-1.97,.93-2.96,1-4.17,.09-8.35,.18-12.52,.26-1.19-.19-4.4,.72-4.67-.77,1.58-11.01,4.23-21.89,5.66-32.94,.74-4.81,1.49-9.61,2.18-14.43,.82-4.35,.65-8.88,2.01-13.11l-.11,.08c5.28-.63,10.61-.65,15.92-.79,1.07-.03,2.14-.04,3.06,.52,0,0-.04-.05-.M 04-.05Z"/><path class="cls-2" d="M161.4,138.76c-.07-13.73-.08-27.52,.64-41.24,.02-.41,.65-.78,1.12-.68,8.71,1.79,17.47,3.37,26.13,5.41,.01,0-.07-.06-.05-.05-.47,.28-.62,.67-.65,1.11-.14,2.25-.34,4.51-.41,6.76-.42,12.57-.57,25.15-1.02,37.72-.13,.76-1.37,.54-1.94,.24-7.93-3.17-16.06-5.96-23.89-9.35l.08,.08Z"/><path class="cls-2" d="M1192.55,222.83c19.87-.69,39.77-1,59.65-.56,.27,1.77-1.07,3.31-1.61,4.97-2.03,4.77-4.39,9.42-6.22,14.27l.11-.08c-20.85-.39-41.72-.07-62.58,.02-.77-.28-.14-1.15,.11-1.64,3.54-5.68,7.09-11.3M 6,10.64-17.03l-.09,.06Z"/><path class="cls-2" d="M1279.05,1301.04c.32,13.68,.05,27.54-.41,41.24-.05,.45-.62,.79-1.11,.69-8.37-1.5-16.65-3.43-24.99-5.03,0,0,.13,.1,.13,.11-.58-.67-.42-1.44-.4-2.19,.13-4.74,.31-9.48,.43-14.21,.32-9.9,.3-19.82,.8-29.71,.19-.59,1.22-.41,1.7-.19,8.05,2.97,15.97,6.21,23.94,9.37l-.08-.07Z"/><path class="cls-2" d="M670.87,824.67c3.54,.66,6.93,1.71,10.38,2.59,.54,.14,.68,.58,.3,1.03-2.89,3.52-5.86,6.99-8.88,10.41-.31,.35-.1,.91,.41,1.07,2.52,.76,5.04,1.5,7.55,2.27,1.65,.51,2.16,.82,.79,2.24M -2.72,2.95-5.59,5.8-8.63,8.55-.61,.56-1.37,1.06-1.49,1.96,3.18,1.29,6.63,2.21,9.94,3.7-4.27,4.13-8.86,7.6-13.33,11.48-.23,.19-.19,.74,.06,.86,2.69,1.47,5.78,2.24,8.4,3.83,.35,.34,.08,.85-.28,1.11-4.87,3.78-10.07,7.14-15.07,10.76-.43,.3-1,.32-1.49,.07-2.87-1.67-6.19-2.71-8.76-4.76,5.05-3.7,10.84-6.92,15.65-10.95-.1-.55-.47-.82-.97-1.03-2.71-1.13-5.5-2.24-8.15-3.46,0-.29-.11-.56,.02-.68,.61-.57,1.24-1.13,1.92-1.64,3.44-2.58,6.79-5.24,9.95-8.04,.45-.4,.92-.79,.83-1.47-3.14-1.34-6.71-2.07-9.75-3.54-.03-.73,.53-1.08,.95M -1.47,3.27-3.15,6.72-6.14,9.89-9.39,.47-.6-.41-.99-.87-1.16-3.15-.94-6.3-1.87-9.37-2.78-.7,.03-.99,.42-1.32,.75-3.44,3.38-7.11,6.79-11.03,9.74-3.63-.6-6.98-2.44-10.51-3.52-.46-.17-.61-.82-.27-1.11,3.5-3.06,7.33-5.9,10.48-9.31-.36-.62-.98-.81-1.6-1.01-3.19-1.23-6.63-1.75-9.56-3.53,3.46-3.29,6.57-6.52,9.61-10.1l-.1,.04c3.7,.66,7.36,2.05,11.03,2.99,.34,.1,.61,.35,.98,.56-2.63,3.61-5.96,6.68-8.97,9.99-.32,.34-.12,.92,.38,1.07,3.14,.97,6.28,1.93,9.42,2.89,.46,.16,1.13,0,1.5-.19,3.7-3.33,6.89-7.18,10.06-10.9l-.09,.07Z"/>M <path class="cls-2" d="M1281.56,161.34c-16.21,.57-32.48,1.16-48.7,1.52-1.01-.35,.28-1.6,.53-2.19,4.2-6.24,8.45-12.45,12.62-18.7l-.12,.05c9-.16,17.99-.57,26.98-.93,5.36-.36,10.74-.37,16.11-.42,.65,0,1.33-.06,1.91,.28,.28,.56-.05,1.05-.28,1.54-3.04,6.31-5.89,12.71-9.13,18.92l.07-.07Z"/><path class="cls-2" d="M449.34,412.15c-5.31,.65-10.6,1.53-15.94,1.98-1.4,.13-1.22-1.36-1.2-2.3,.73-12.79,1.43-25.6,2.94-38.33,.41-3.75,.83-7.5,1.23-11.25,.06-.53,.13-1.07-.34-1.53-.01,0-.1,.08-.1,.08,5.64-1.28,11.84-.51,17.38-2.42,.61-M .2,1.75-.62,1.96,.25-2.25,17.81-5.32,35.63-6.02,53.58l.07-.06Z"/><path class="cls-2" d="M990.83,1027.9c5.44-1.18,11.06-1.89,16.61-2.23,.96,.13,.82,1.2,.84,1.92-.54,17.3-2.84,34.49-4.12,51.72l.11-.08c-5.3,.55-10.79,.31-15.94,1.75-1.13,.14-3.35,1.2-2.99-.86,1.98-14.1,4.04-28.19,5.19-42.38,.26-2.79,.5-5.58,.75-8.37,.05-.54,.05-1.08-.33-1.55l-.12,.09Z"/><path class="cls-2" d="M90.76,1343.29c-1.36-.59-2.89-.33-4.34-.4-9.57-.04-19.14-.05-28.71-.09-5.56-.19-4.99,.35-4.98-4.06,.13-5.81-.14-11.65,.29-17.44,.45-1.14,2.21-.59M ,3.2-.73,6.06,.11,12.12,.25,18.19,.33,7.54,.26,15.13-.22,22.63,.41,0,0-.09-.05-.08-.04-.58,.35-.73,.89-.86,1.4-1.97,6.85-3.06,14.01-5.45,20.7l.11-.08Z"/><path class="cls-2" d="M1349.31,96.84c12.37,.12,24.75-.14,37.12,.23,1.2,.1,1.16,1.22,1.18,2.1,0,6.02-.03,12.04-.05,18.07,.03,.73-.1,1.72-.95,1.89-13.97,.01-27.97-.55-41.95-.38l.15,.12c-.27-.51-.22-1.05-.09-1.58,1.42-6.85,4.06-13.57,4.7-20.52l-.1,.07Z"/><path class="cls-2" d="M987.92,363.09c20.25-1.6,40.49-3.31,60.81-3.87l-.16-.08c-2.41,4.77-4.65,9.63-7.23,14.32-19.M 56,1.02-39.21,1.52-58.74,3.44-.78,.06-1.32-.44-1.05-1,2.07-4.32,4.27-8.59,6.44-12.87l-.08,.06Z"/><path class="cls-2" d="M80.48,79.91c-.47-8.03-.07-16.12-.19-24.17-.16-3.09,.55-2.98,3.42-2.95,6.99,0,13.99,0,20.98,.02,1.67,.05,3.55-.3,3.31,2.05-.16,9.88,.07,19.79-.32,29.66-.28,1-1.97,.6-2.78,.5-8.11-1.85-16.56-2.83-24.48-5.18l.08,.07Z"/><path class="cls-2" d="M415.36,463.94c-.89-14.74-.8-29.49-.79-44.25,0-1.17-.1-2.36,.31-3.58,5-1,10.15-.93,15.23-1.47,.55-.02,1.47-.03,1.71,.54-.3,15.59-.66,31.22-.38,46.82l.09-.07c-4,M 1.13-8.26,1.29-12.37,1.93-1.28,.15-2.6,.43-3.9,0l.09,.08Z"/><path class="cls-2" d="M474.26,1010.7c1.27,3.76,1.53,7.95,1.91,11.91,.02,.55-.14,1.04-.67,1.43,0,0,.09-.06,.08-.05-6.1-.28-12.31,.67-18.45,.72-13.4,.48-26.84,.64-40.24,.26l.11,.09c-.7-4.54-.54-9.19-1.63-13.65l-.13,.1c19.71-.05,39.52,1,59.18-.67l-.15-.13Z"/><path class="cls-2" d="M964.38,416.15c19.92-1.71,40.02-1.89,60-1.32l-.11-.09c.98,4.49,.33,9.24,1.64,13.65l.13-.1c-19.05-.16-38.11-.66-57.16,.22-.79-.06-2.08,.16-2.43-.71-.91-3.86-.85-7.94-1.92-11.78l-.14M ,.12Z"/><path class="cls-2" d="M90.65,1343.37c2.41-1.01,5.32-.26,7.9-.52,7.51-.12,15.01-.26,22.52-.38,1.88-.03,3.75-.05,5.63-.04,1.15,0,1.87,.24,1.36,1.33-3.01,6.85-6.74,13.52-9.3,20.51l.13-.07c-.55,.39-1.23,.37-1.9,.39-9.55,.16-19.1,.44-28.65,.39-.72-.09-2.16,.16-2.27-.82,.91-7.06,3.83-13.87,4.7-20.88,0,0-.12,.09-.12,.09Z"/><path class="cls-2" d="M80.4,79.84c-.27,8.28-.07,16.56-.05,24.85-.05,2.06,0,2.7-2.28,1.9-8.51-3.24-17.18-6.07-25.61-9.51-.35-6.57-.05-13.15-.14-19.73,0-.82-.1-2.05,1.01-2.14,9.12,1.01,18.04,3.8M 5,27.15,4.7l-.08-.07Z"/><path class="cls-2" d="M118.76,1364.27c9.72,.64,19.64-.28,29.42-.17,2.04,.03,2.46,.28,1.21,2.14-4.29,6.7-8.59,13.4-12.9,20.09-.52,.91-1.85,.84-2.82,.86-8.18-.15-16.42,.43-24.57-.15-.54-.22-.43-.99-.25-1.43,3.08-6.88,6.18-13.76,9.29-20.63,.13-.28,.47-.51,.72-.77,.01,0-.12,.07-.12,.07Z"/><path class="cls-2" d="M85.23,1365.49c-.62,4.99-2.25,9.88-3.29,14.81-.59,2.07-.83,4.3-1.68,6.28-.56,.68-1.67,.66-2.5,.68-7.52,0-15.05,0-22.57,0-1.45-.01-2.97,0-2.84-1.87,.03-6.23,.07-12.46,.11-18.68-.14-1.92,1M .65-1.58,3.01-1.66,9-.02,18-.03,27-.02,.91,0,1.89-.19,2.75,.47Z"/><path class="cls-2" d="M1354.98,74.68c1.94-5.74,2.98-11.81,4.33-17.71,1.22-4.75,0-4.2,6.17-4.22,6.33-.02,12.66,0,19,0,1.26,.12,3.32-.4,3.15,1.51,0,6.25,0,12.49-.02,18.74-.05,.64-.04,1.52-.86,1.64-10.61,.2-21.29,.31-31.91-.04,0,0,.12,.09,.12,.09Z"/><path class="cls-2" d="M463.06,686.97c-4-6.21-7.22-12.95-10.93-19.35-.32-.59-.7-1.17-.44-1.84,3.12-.66,7.11-.02,10.4-.21,.52-.02,1.48,0,1.57-.64-1.64-4.45-4.1-8.6-5.97-12.96-1.47-3.22-2.81-6.49-4.2-9.74-.76M -1.56,1.44-1.86,2.41-2.46,3.03-1.35,5.83-3.25,8.96-4.29,.73,.23,.76,.82,.96,1.28,3.23,7.55,6.23,15.1,10.12,22.39l.05-.07c-3.37,2.1-6.8,4.13-10.51,5.85-1.16,.4-.94,1.3-.45,2.17,3.68,6.38,7,13,10.91,19.24l.15-.11c-4.29,.92-8.76,.58-13.13,.67l.08,.06Z"/><path class="cls-2" d="M729.03,620.39c3.85,.86,7.73,1.61,11.55,2.63l-.16-.13c-2.15,3.91-3.58,8.27-5.44,12.35-.12,.28-.01,.61-.01,1.01,3.67,.93,7.5,1.43,11.22,2.17-2.06,4.08-2.68,8.77-4.59,12.9-3.76,.15-7.18-.87-10.88-1.18,.7-4.36,2.44-8.54,3.39-12.86,.14-.55-.29-1.07-.M 98-1.2-3.15-.36-6.27-1.61-9.43-1.31-1.65,4.45-3.02,8.91-4.24,13.4-3.34,.1-6.6-.95-9.92-1.3-.47-.07-1.11,.29-1.21,.67-1.33,4.51-2.05,9.11-3.46,13.59-3.45-1.02-7.07-1.3-10.6-1.96,1.54-4.68,2.1-9.64,3.86-14.23,3.29,.03,6.3,1.26,9.58,1.34,.32,.01,.79-.22,.96-.45,1.29-3.46,2.26-7.1,3.46-10.62,.47-.9,.47-2.66,1.84-2.58,2.9,.44,5.79,.98,8.69,1.44,.71,.11,1.24-.21,1.48-.83,1.68-4.31,3.36-8.63,5.03-12.94l-.15,.08Z"/><path class="cls-2" d="M522.87,994.6c.38,3.67,2.1,7.11,2.48,10.77,.06,1.23-3.57,1.13-4.55,1.42-15.46,1.59-30.M 99,3.92-46.54,3.91l.15,.13c.05-2.71-.72-5.33-1.29-7.97-.32-1.47-.31-3.01-1.16-4.4l-.1,.09c17.09-.57,34.11-2.07,51.11-3.89l-.11-.07Z"/><path class="cls-2" d="M659.11,944.03c8.06-4.65,16.33-9.07,24.12-13.97,.66,0,1,.34,1.29,.68,1.7,1.94,3.37,3.89,5.06,5.82,.23,.21,.67,.48,1.01,.39,2.09-1.08,4-2.56,5.94-3.86,4.4-3.17,8.75-6.37,13.12-9.56,.61-.51,1.64-1.27,2.32-.57,1.72,2.18,3.44,4.36,5.1,6.57,.14,.19-.03,.67-.26,.86-5.9,4.98-12.37,9.27-18.62,13.82-.58,.41-1.13,.88-2,1.04-2.3-2.54-3.44-5.38-6.15-7.61-7.82,4.51-15.33,9.M 53-23.37,13.64-.77-.03-1.12-.31-1.42-.69-1.59-1.99-3.2-3.98-4.79-5.97-.31-.38-.69-.65-1.28-.68-.02,.02-.07,.08-.07,.08Z"/><path class="cls-2" d="M867.47,430.91s.01,.04,.01,.06l-.09,.03,.08-.09Z"/><path class="cls-2" d="M912.79,421.95h-.12s-.01-.06-.02-.09l.14,.09Z"/><path class="cls-2" d="M915.2,433.56c-11.03,1.78-22.08,3.4-32.96,5.87-4.46-1.04-8.95-2.02-13.46-2.97-.52-1.81-.95-3.64-1.3-5.49,14.84-3.79,30.03-6.83,45.19-9.02,.92,3.83,1.64,7.69,2.52,11.53,0,.03,.01,.05,.01,.08Z"/><path class="cls-2" d="M522.87,994.6sM .03,0,.04-.01c.02,.03,.04,.05,.06,.08l-.1-.07Z"/><path class="cls-2" d="M530,993.57c-2.36,.34-4.72,.69-7.09,1.02-.89-.92-.97-2.27-1.46-3.41,2.84,.81,5.69,1.62,8.55,2.39Z"/><path class="cls-2" d="M530.96,935.82h-.04s-.04-.03-.05-.05l.09,.05Z"/><path class="cls-2" d="M538.87,946.05c-5.76,1.2-11.87,1.12-17.72,1.8-10.51-3.24-20.85-6.73-31.03-10.44,13.6-.29,27.24-.16,40.8-1.59,2.54,2.99,5.07,5.99,7.63,8.97,.31,.37,.5,.74,.32,1.26Z"/><path class="cls-2" d="M787.33,729.68c2.76,.25,5.37,1.32,8.06,1.96,1.13,.39,3.06,1,3.14-M .53,.59-3.74,1.18-7.47,1.92-11.18,.56-1.44,2.73-.19,3.8,.06,2.48,.84,4.94,1.69,7.41,2.53l-.09-.09c0,3.19-1.15,6.36-1.59,9.54-.37,1.28-.29,2.86-1.23,3.87-3.19-.73-5.93-2.02-9.06-2.89-.88-.28-1.51,.09-1.66,.9-.67,3.93-1.26,7.87-1.96,11.8-.09,.41-.7,.73-1.19,.59-2.52-.72-5.04-1.46-7.56-2.19-.64-.18-1.29-.3-1.99,0-1.09,3.9-1.34,8.06-2.13,12.05-.12,.65-.44,1.44-1.25,1.4-3.41-.37-6.65-2.07-10.09-1.96,.71-.96,.75-2.05,.9-3.11,.53-3.74,1.08-7.47,1.62-11.21,15.3,2.35,9.2,5.41,13.04-11.64l-.1,.1Z"/><path class="cls-2" d="M70M 4.24,914.84c-.27,.37-.41,.69-.68,.9-6.28,4.67-12.58,9.52-19.46,13.54-.34,.05-.81,.07-1.09-.19-2.06-2.09-4.75-3.8-6.44-6.14-.05-.52,.48-.74,.88-1,6.24-4.03,12.44-8.13,18.34-12.62,.41-.3,.4-.86-.01-1.15-2.28-1.66-4.69-3.19-6.88-4.97-.13-.11-.15-.45-.03-.58,2.68-2.45,5.8-4.48,8.59-6.81,2.57-2.05,5.02-4.2,7.57-6.26,.83-.66,1.72-.06,2.45,.39,5.21,3.1,6.52,3.99,6.27,4.35-4.78,5.15-10.75,9.34-16.24,13.85-.37,.32-.38,.84,.02,1.16,2.26,1.82,4.58,3.55,6.71,5.53Z"/><path class="cls-2" d="M729.44,905.99c1.09-.32,1.6-.98,2.18-1M .57,3.76-3.8,7.51-7.6,11.26-11.4,.75-.76,1.5-1.51,2.3-2.24,.12-.11,.47-.08,.72-.07,2.09,1.68,3.87,3.88,5.83,5.75,.34,.34,.3,.8-.08,1.18-4.84,4.9-9.68,9.8-14.53,14.69-.38,.37-1.03,.92-1.59,.61-1.68-1.46-2.84-3.39-4.33-5.03-1.28-1.5-1.66-1.45-2.95-.25-5.03,4.78-10.48,9.32-15.97,13.7-.43,.33-1.11,.34-1.42,.02-1.98-2.03-3.94-4.07-5.89-6.08,.08-.25,.07-.51,.22-.63,5.85-4.58,11.31-9.62,16.96-14.27,.22-.07,.61-.1,.74,0,2.32,1.69,4.56,3.57,6.55,5.59Z"/><path class="cls-2" d="M725.85,587.43c3.15,.89,6.23,1.92,9.27,3.02,.28,M .16,.32,.29,.56,.59-3.14,4.17-6.85,8.44-9.85,12.69,.34,.57,.75,.82,1.28,.96,2.68,.69,5.38,1.3,8.03,2.1,.32,.09,.56,.54,.43,.8-2.17,4.27-4.35,8.54-6.53,12.8l.15-.08c-3.59-.2-7.01-1.88-10.59-1.84,1.26-4.57,3.81-8.68,6.05-12.9,.21-.37,.55-.74,.22-1.21-2.83-1.67-6.59-1.57-9.45-3.24,3.18-4.84,7.08-9.12,10.55-13.75l-.11,.08Z"/><path class="cls-2" d="M786.61,633.33c1.25-2.95,3.12-5.68,4.81-8.48,2.2-3.64,2.64-3.13-2.17-4.53-2.41-.87-5.27-1.04-7.44-2.36,1.82-3.18,7.12-8.03,9.75-10.6,4.07,.95,8.29,2.3,12.08,4.05l-.14-.16c-8.M 54,8.26-8.64,8.37-9.43,10.36,13.94,5.46,13.28,.42,5.36,14.02-.43,.92-1.47,.84-2.29,.53-3.55-.98-7.1-1.96-10.64-2.94l.1,.11Z"/><path class="cls-2" d="M646.67,818.15c-4.1-1.21-8.11-3.01-12.27-3.89l.14,.1q5.96-9.54,6.4-11.49c-4-1.43-8.28-2.49-12.16-4.17l.08,.12c1.91-3.17,3.47-6.49,5.13-9.79,.24-.47,.42-1.03,1.18-1.19,3.03,.85,6.06,1.7,9.09,2.57,.88,.31,1.8,.39,2.44,1.13-.88,2.92-2.54,5.62-3.75,8.43-.25,.95-1.93,2.51-.56,3.18,3.39,1.03,6.8,1.98,10.2,2.98,.81,.27,.7,1.11,.39,1.68-2,3.51-3.98,7.03-6.41,10.38l.1-.04Z"/><pM ath class="cls-2" d="M637.77,964.84s.02,.03,.03,.04l-.15,.06,.12-.1Z"/><path class="cls-2" d="M643.48,973.96l-.14-.05s.06-.01,.09-.02c.01,.02,.03,.05,.05,.07Z"/><path class="cls-2" d="M671.62,960.39c-9.05,4.86-18.41,9.92-28.19,13.5-2.15-2.82-3.73-6.02-5.63-9.01,9.65-3.74,18.66-8.3,27.74-12.82,.27-.06,.81,.1,1.01,.36,1.49,1.77,3.93,5.61,5.07,7.97Z"/><path class="cls-2" d="M671.73,960.33l-.1,.08s-.01-.01-.01-.02c.04-.02,.07-.04,.11-.06Z"/><path class="cls-2" d="M626.45,670.14c1.5-4.94,2-10.29,4.14-14.98l-.18,.12c2.79M ,1.49,5.58,2.98,8.62,4.12,.21,.08,.52,.01,.92,.01,1.2-4.6,2.45-9.22,3.74-13.8,.07-.26,.68-.52,.95-.42,2.9,1.1,5.74,2.3,8.48,3.55,.24,1.07-.13,2-.35,2.94-.95,4-1.9,8-2.85,12-3-.78-5.85-2.09-8.75-3.17-.62-.23-1.43,.07-1.56,.6-.37,1.47-.73,2.93-1.06,4.41-.59,2.63-1.15,5.26-1.72,7.9-.17,.78-.79,1.01-1.74,.64-2.94-1.24-5.79-2.66-8.7-3.98l.07,.06Z"/><path class="cls-2" d="M817.23,696.61c-.34,3.9-1.81,7.8-2.56,11.69-.1,.41-.76,.71-1.24,.56-3.23-1.06-6.44-2.13-9.71-3.04-.64-.07-.89,.67-.97,1.17-.59,3.18-1.15,6.37-1.74,9.55M -.22,.71-.27,1.69-1.16,1.87-3.67-.87-7.32-2.11-10.98-3.1l.15,.11c1.5-4.26,1.01-8.8,2.8-13.01,3.59,.48,6.83,1.96,10.36,2.64,.26,.05,.83-.27,.92-.51,1-3.29,1.41-6.76,2.21-10.12,.2-.72,.45-1.77,1.45-1.6,3.65,1.05,7.25,2.21,10.57,3.84l-.08-.06Z"/><path class="cls-2" d="M979,733.46c4.12,6.46,8.61,12.71,11.97,19.54,.1,.24-.1,.46-.39,.45-4.41,.06-8.76-.65-13.17-.62l.09,.06c-3.68-6.6-8.2-12.74-12-19.24,1.54-.72,3.15-.53,4.79-.59,2.94,.09,5.88,.13,8.8,.46l-.09-.07Z"/><path class="cls-2" d="M461.39,706.29c3.86,5.43,7.72,10.8M 6,11.58,16.29,.39,.76,1.46,1.48,.92,2.35-4.69,.22-9.4-.38-14.09-.51l.04,.02c-3.66-5.25-7.33-10.49-10.97-15.75-.31-.73-2.81-3.38-1.36-3.6,4.66,.24,9.28,1.08,13.97,1.25l-.09-.06Z"/><path class="cls-2" d="M461.47,706.35c-4.16-6.45-8.72-12.73-11.99-19.56,.05-.44,.75-.6,1.17-.56,4.15,.12,8.25,.74,12.41,.74l-.09-.06c3.5,6.29,7.62,12.37,11.6,18.45,1.91,2.43-11.82,.76-13.19,.94l.09,.06Z"/><path class="cls-2" d="M702.58,555.4c-4.47,4.82-8.53,9.93-12.65,14.92-.12,.11-.55,.13-.72,.05-2.45-1.31-4.8-3.13-7.02-4.59,0-.37-.1-.63,M .01-.79,3.94-5.05,7.71-10.47,12.38-15.01,.43-.21,1.04-.03,1.4,.26,2.16,1.76,4.79,3.06,6.59,5.16Z"/><path class="cls-2" d="M692.13,862.03c2.13,1.15,4.56,1.84,6.79,2.84,.8,.36,1.82,.48,2.33,1.21-.03,.19,.02,.44-.11,.56-4.06,4.03-8.23,7.98-12.77,11.67-1.06,.86-1.38,.89-2.81,.25-2.24-.99-4.46-2-6.69-3.01-.46-.21-.88-.45-1.05-1,4.9-4.11,9.8-8.3,14.41-12.57,0,0-.1,.05-.1,.05Z"/><path class="cls-2" d="M788.86,715.32c.45,1.39,.03,2.77-.16,4.14-.38,3.41-1.2,6.79-1.37,10.22l.1-.1c-3.72-1.07-7.6-2.11-11.48-2.49,3.73-15.49-2.7M 6-15.13,13.06-11.66l-.15-.11Z"/><path class="cls-2" d="M1228.38,910.98c-.05,.07-.09,.19-.14,.19-.31,0-.28-.04,.09-.09,0-.01,.05-.1,.05-.1Z"/><path class="cls-2" d="M1279.81,881.08v-.2s.02,.17,0,.2Z"/><path class="cls-2" d="M433.09,751.59c-.28-.18-.27-.23,.03-.15-.04,.06-.09,.13-.13,.19l.1-.05Z"/><path class="cls-2" d="M1240.27,858.9s.12-.06,.12-.06c0,0-.12,.06-.12,.06Z"/><path class="cls-2" d="M481.61,853.12l.15,.02c-.08-.1-.05-.11-.15-.02Z"/><path class="cls-2" d="M248.66,642.99l.11,.06c0-.15,.02-.14-.11-.06Z"/><pM ath class="cls-2" d="M375.64,837.58l.27,.03c-.13,.19-.19,.16-.18-.09l-.08,.07Z"/><path class="cls-2" d="M1037.31,730.23l-.31-.14c.26-.16,.33-.1,.22,.19l.09-.06Z"/><path class="cls-2" d="M1086.38,834.09l-.3,.07c.09-.03,.19-.07,.29-.11,0,0,0,.04,0,.04Z"/><path class="cls-2" d="M1028.42,666.21v.06s-.05,.01-.08,.01l.08-.07Z"/><path class="cls-2" d="M215.67,631.85l-.23,.11c.12,0,.17,.02,.23-.11Z"/><path class="cls-2" d="M1024.12,629.75l-.19,.07c.1-.08,.1-.19,.19-.07Z"/><path class="cls-2" d="M213.94,629.46s.07-.07,.08-.M 06-.08,.06-.08,.06Z"/><path class="cls-2" d="M998.52,718.5l-.17,.09c.11,.02,.11,0,.17-.09Z"/><path class="cls-2" d="M800.44,1026.36l-.16-.05s.14,.05,.16,.05Z"/><path class="cls-2" d="M1070.09,761.82c.09-.16,.18-.45,.28-.45,.35-.01,.34,.09-.02,.19-.09,.03-.15,.12-.24,.21l-.02,.05Z"/><path class="cls-2" d="M810.4,1039.05l-.17-.18c.07,.05,.14,.11,.21,.16,0,0-.05,.02-.05,.02Z"/><path class="cls-2" d="M146.85,783.14l-.17,.11c.11,0,.12-.01,.17-.11Z"/><path class="cls-2" d="M1257,1041.9c.08-.04,.16-.08,.24-.13-.1,.04-.2,.M 08-.31,.12-.02,0,.08,0,.08,0Z"/><path class="cls-2" d="M686.57,1042.33c.13,0,.34-.03,.37,.02,.19,.24,.09,.25-.26-.02-.03,0-.12,0-.12,0Z"/><path class="cls-2" d="M708.45,1043.49l-.06-.12c.08,.05,.24,.03,.06,.12Z"/><path class="cls-2" d="M685.5,1044.44l.05-.26c.3,.13,.25,.19-.14,.19l.09,.07Z"/><path class="cls-2" d="M706.98,1045.42l-.11-.14c.13,.07,.22,.03,.11,.14Z"/><path class="cls-2" d="M1211.59,762.83l-.21,.18c.04-.06,.09-.11,.14-.18,.01,0,.07,0,.07,0Z"/><path class="cls-2" d="M1072.62,698.96l-.02,.02c-.07,.04-.1M 4,.07-.21,.1,.07-.04,.13-.07,.2-.11,0,0,.02,0,.03-.01Z"/><path class="cls-2" d="M412.1,696.62l-.23-.12c.26-.09,.3-.03,.14,.18l.1-.05Z"/><path class="cls-2" d="M1092.71,695.04l-.14,.07s.07-.13,.07-.14l.07,.07Z"/><path class="cls-2" d="M775.96,1083.78l.27-.12c0,.2-.11,.22-.33,.04,0,0,.06,.08,.06,.08Z"/><path class="cls-2" d="M257.78,597.94l.51-.18c-.14,.03-.43,.2-.51,.18Z"/><path class="cls-2" d="M718.23,1098.91l-.37-.32c.24-.03,.18,.12,.24,.29,.02,0,.13,.04,.13,.04Z"/><path class="cls-2" d="M1100.78,662.2c-.08,.07-.M 21,.21-.24,.2-.19-.08-.09-.16,.3-.22,.03,0-.06,.02-.06,.02Z"/><path class="cls-2" d="M624.22,1111.98c-.12-.1-.23-.2-.35-.3,.25,.02,.32,.12,.36,.35,0,.02-.01-.06-.01-.06Z"/><path class="cls-2" d="M646.13,1117.89v-.18c.1,.11,.19,.12,0,.18Z"/><polygon class="cls-2" points="310.21 573.78 310.1 573.85 310.1 573.72 310.21 573.78"/><path class="cls-2" d="M780.14,1133.02v-.27c.35,.06,.31,.13-.09,.22l.09,.06Z"/><path class="cls-2" d="M589.12,1154.23l.04,.21c-.26,0-.25-.05,.05-.15l-.1-.06Z"/><path class="cls-2" d="M605.07,11M 65.57v.14c-.15-.07-.15-.06,0-.14Z"/><path class="cls-2" d="M378.86,529.17s-.08,.01-.11,.02c.03-.04,.07-.09,.1-.13,.01,.03,.01,.07,.01,.11Z"/><path class="cls-2" d="M378.95,529.15l-.08,.07s0-.03-.01-.05c.03-.01,.06-.02,.09-.02Z"/><path class="cls-2" d="M1007.33,688.24l.31,.13c-.25,.17-.32,.11-.22-.18l-.09,.06Z"/><path class="cls-2" d="M523.46,1191.36l.23,.39c-.08-.13-.16-.26-.24-.42,0-.02,.01,.03,.01,.03Z"/><path class="cls-2" d="M597.35,493.02v-.16c.18,.12,.15,.15-.08,.09l.08,.07Z"/><path class="cls-2" d="M171.32,4M 61.66l-.27,.08c.21,.14,.25,.09,.11-.13,0,0,.16,.05,.16,.05Z"/><path class="cls-2" d="M555.57,1219.39l-.19-.22c.07,.07,.15,.14,.23,.21,0,0-.04,0-.04,0Z"/><path class="cls-2" d="M628.12,1219.02c.06,.7-1.41,.28-.17-.14l.17,.14Z"/><path class="cls-2" d="M638.3,415.07l-.04,.19c.24-.05,.2-.09-.1-.12,0,0,.14-.07,.14-.07Z"/><path class="cls-2" d="M560.31,1238.68l.46,.32c-.12-.09-.24-.18-.39-.27-.03,0-.07-.04-.07-.04Z"/><path class="cls-2" d="M476.02,1239.66l-.19,.13c-.01-.2,.07-.21,.25-.05,0,0-.06-.08-.06-.08Z"/><path clasM s="cls-2" d="M796.77,320.09v.21c.21-.02,.19-.07-.09-.13,0,0,.09-.08,.09-.08Z"/><path class="cls-2" d="M660.72,307.27l-.19-.21c.07,.07,.15,.14,.23,.2,0,0-.04,0-.04,0Z"/><path class="cls-2" d="M767.07,301.73l-.08-.06,.08,.06Z"/><path class="cls-2" d="M703.81,286.66c.07,.03,.21,.08,.21,.09-.09,.23-.11,.21-.08-.05-.01,0-.13-.04-.13-.04Z"/><path class="cls-2" d="M479.99,1310.06l.2-.09-.1,.15c-.05-.05-.1-.09-.15-.14,0,0,.05,.09,.05,.09Z"/><path class="cls-2" d="M755.9,264.86l-.26,.15c-.04-.2,.07-.23,.32-.07,0,0-.07-.08-.M 07-.08Z"/><path class="cls-2" d="M577.14,262.92c.65,.28,.66-.3,.79-.71l-.05-.02c-.4,.12-.77,.2-.74,.68v.04Z"/><path class="cls-2" d="M914.3,249.26c-.17-.36,.47-.5,.58-.18,0,.24-.19,.32-.48,.26l-.1-.08Z"/><path class="cls-2" d="M814.39,243.8l-.02-.22c-.23,.06-.2,.11,.1,.14,0,0-.09,.09-.09,.09Z"/><path class="cls-2" d="M753.96,241.18l-.35-.14c.09,.05,.29,.04,.35,.14Z"/><path class="cls-2" d="M816,219.41l-.32-.47c.16,.22,.25,.35,.35,.47,0,0-.03,0-.03,0Z"/><path class="cls-2" d="M1098.81,212.47v-.19c.22,.14,.19,.18-.09M ,.11l.09,.07Z"/><path class="cls-2" d="M765.37,204.6l.16,.16c-.25,.12-.27,.08-.05-.11,0,0-.11-.05-.11-.05Z"/><path class="cls-2" d="M819.94,189.58l.51,.23c-.19,.04-.25-.1-.42-.2-.03,0-.09-.03-.09-.03Z"/><path class="cls-2" d="M1036.44,164.59l-.08,.21c-.19-.18-.14-.23,.16-.13l-.08-.08Z"/><path class="cls-2" d="M370.46,678.14l-.14,.14c.04-.16-.04-.23,.14-.14Z"/><path class="cls-2" d="M634.46,747c3.26,1.49,6.97,2.11,10.41,3.2,.65,.18,1.35-.18,1.5-.72,1.13-4.01,1.04-8.42,2.8-12.2l-.16,.11c3.31,1.22,6.85,1.81,10.37,2.49M ,.49,.09,.93-.24,1.03-.76,.69-4.24,1.54-8.52,1.65-12.79l-.12,.07c3.04,.89,6.26,1.21,9.38,1.84,1.72,.35,2.14,.06,2.41-1.34,.42-4.01,1.48-8.19,1.14-12.19,3.17,.45,6.33,.93,9.51,1.34,1.59,.21,1.98-.04,2.16-1.22,.2-1.38,.34-2.78,.5-4.17,.27-2.35,.52-4.7,.8-7.05,.1-.85,.59-1.19,1.51-1.13,3.32,.34,6.62,.86,9.93,1.26-1.11,4.12-.98,8.5-1.64,12.72-.07,.66-.55,1.02-1.27,.96-3.29-.15-6.3-.93-9.65-.73-1.28,4.37-.86,9.15-2.02,13.61-2.9-.44-5.8-.87-8.7-1.29-.88-.11-2.43-.32-2.56,.8-.6,4.26-1.19,8.52-1.78,12.79l.13-.08c-2.84-.97-M 5.94-1.13-8.86-1.84-.74-.14-1.57-.28-2.29,.05-.12,.18-.32,.35-.36,.54-.8,4.1-1.58,8.2-2.36,12.31l.12-.07c-3.46-.84-6.92-1.67-10.39-2.51-.55-.15-1.5,.01-1.64,.56-.89,3.9-1.77,7.8-2.66,11.7l.14-.08c-3.94-.48-7.8-2.29-11.65-3.15-.7,.24-.94,.62-1.08,1.05-1.15,3.56-2.06,7.14-3.6,10.58l.12-.12c-4.24-.99-8.13-2.97-12.23-4.4,1.03-3.99,3.05-7.73,4.07-11.71,3.92,1.31,7.7,2.99,11.72,4.01,2.09-3.77,2.62-8.29,3.65-12.42Z"/><path class="cls-2" d="M666.93,768.98c-4.1-.79-8.16-2.04-12.28-2.55l.09,.06c1.79-4.05,2.08-8.72,3.29-13l-.M 12,.07c15.95,2.19,10.53,5.53,13.87-11.06l-.13,.08c3.85-.11,7.55,1.25,11.4,1.17-.02,4.6-1.47,9.06-1.57,13.65-3.61,.05-7.12-.99-10.71-1.33-.46-.06-1.13,.32-1.23,.65-.97,4.1-1.81,8.24-2.74,12.35l.14-.09Z"/><path class="cls-2" d="M622.3,783.28c1.58-3.93,3.79-7.74,4.97-11.76l-.12,.12c3.97,1.52,8.01,2.9,12.24,3.91l-.13-.15c.03,.21,.15,.44,.07,.63-1.31,3.36-2.65,6.72-3.98,10.08-.2,.68-.84,1.27-1.64,1.07-3.86-1.14-7.62-2.57-11.42-3.89Z"/><path class="cls-2" d="M654.65,766.43c.28,.64,.12,1.28-.05,1.9-1.05,3.3-1.58,6.83-3,9.M 98-.11,.21-.73,.42-1.04,.34-3.82-.96-7.7-1.8-11.3-3.26l.13,.15c1.75-4.05,2.56-8.3,4.09-12.38l-.14,.08c3.68,1.45,7.74,1.76,11.4,3.25l-.09-.06Z"/><path class="cls-2" d="M675.9,783.82c-4.19-.08-8.15-1.72-12.33-1.83,.65-4.39,2.07-8.75,3.35-13.01l-.14,.09c4.17,.16,8.15,1.7,12.34,1.84-.48,.4-.71,.88-.84,1.42-.79,3.13-1.61,6.26-2.39,9.39-.18,.72-.45,1.45-.21,2.21l.21-.11Z"/><path class="cls-2" d="M976.88,466.5c-1.72,.02-3.47,0-5.19,0-10.91-4.14-21.99-8.02-33.25-11.63,11.11-.81,22.23-1.32,33.37-1.35,2.02,3.98,4.02,7.99,6.0M 3,11.98,.29,.59-.08,.98-.96,1Z"/><path class="cls-2" d="M918.34,445.23c-1.11-3.91-1.88-7.92-3.26-11.74,15.45-1.65,30.87-3.67,46.41-4.46,5.28-.17,4.95-.84,5.61,3.62,.29,1.92,.82,3.81,1.18,5.72,.22,2.11,.76,2.84-1.86,2.88-6.72,.23-13.41,.75-20.12,1.13-9.36,.73-18.73,1.39-27.97,2.86Z"/><path class="cls-2" d="M727.47,663.7c2.82,.71,5.76,.87,8.65,1.25,1.99,.26,2.45,.28,2.87-1.68,.7-3.26,1.52-6.5,2.31-9.75,.19-.57,.38-1.46,1.12-1.53,3.73-.06,7.3,1.29,11.02,1.27-1.46,4.49-2.87,9.02-3.34,13.67l.11-.08c-3.55-.45-7.09-1.07-1M 0.66-1.3-.44-.03-1.08,.37-1.16,.74-.27,1.26-.58,2.52-.8,3.78-.45,2.53-.85,5.07-1.26,7.61-.09,.53-.12,1.06,.2,1.56-3.55-.53-7.12-.98-10.68-1.42-1.03-.13-.92-1.14-.82-1.88,.83-4.12,1.18-8.33,2.54-12.33l-.11,.1Z"/><path class="cls-2" d="M757.47,640.44c-3.8-.58-7.59-1.7-11.4-1.95,1.8-4.2,2.96-8.73,5.18-12.72,.11-.15,.45-.28,.67-.26,3.83,.15,7.46,1.72,11.27,1.92-2.5,4.02-3.57,8.8-5.72,13.02Z"/><path class="cls-2" d="M776.91,657.8c-1.04,4.34-2.68,8.6-3.34,13.01l.12-.08c-4.08-.67-8.13-1.62-12.26-1.94l.1,.13q2.58-10.93,3.8M -13.08c3.89,.29,7.74,1.29,11.58,1.95Z"/><path class="cls-2" d="M753.33,653.34c1.26-4.35,3.27-8.57,4.05-13,3.52,.71,7.04,1.41,10.56,2.13,1.54,.34,.59,1.87,.31,2.82-.95,2.91-1.89,5.83-2.85,8.74-.18,.53-.45,1.11-1.09,1.22-3.68-.21-7.4-1.12-10.98-1.91Z"/><path class="cls-2" d="M750.12,666.94c3.76,.76,7.83,.69,11.41,1.99l-.1-.13c-.74,4.33-1.83,8.61-2.31,12.97-3.83-.04-7.6-.94-11.43-1.25,.36-4.06,1.34-8.08,1.97-12.12,.09-.52,.37-1.03,.57-1.54l-.11,.08Z"/><path class="cls-2" d="M793.88,688.83c-.22,3.66-1.26,7.23-1.88,10.8M 5-.27,.93-.35,2.37-1.75,2.09-3.11-.68-6.19-1.5-9.35-1.98-1.24-.03-1.27,1.46-1.46,2.35-.37,2.78-.71,5.57-1.09,8.35-.23,.77-.13,2.03-1.13,2.22-3.68-.32-7.35-1.34-11.02-1.92l.16,.11c1.6-4.16,.83-9.35,2.37-13.67,3.36,.65,6.73,1.3,10.09,1.95,.84,.12,1.26-.6,1.3-1.29,.93-3.86,1.01-7.94,2.46-11.64l-.1,.1c3.8,.81,7.56,1.84,11.39,2.48Z"/><path class="cls-2" d="M818.05,656.59c-.08-.56,.29-1.02,.56-1.5,1.5-2.72,3-5.45,4.52-8.16,.26-.47,.55-.96,1.34-1.26,4.1,1.51,8.15,3.5,12.3,5.04-2.17,3.37-3.95,7.18-6.34,10.32-.73,.11-1.29-.M 22-1.88-.46-3.53-1.26-6.81-3.2-10.5-3.97Z"/><path class="cls-2" d="M773.58,670.81c3.81,.84,7.61,1.68,11.42,2.52-.75,4.35-2.16,8.63-2.5,13.02l.1-.1c-4.1-.84-8.19-1.69-12.29-2.53,1.66-4.21,1.52-8.83,3.39-12.99l-.12,.08Z"/><path class="cls-2" d="M809.28,679.77c-5.82,14.87,1.42,13.79-15.52,9.11,1.77-3.73,1.67-8.06,3.23-11.86,.09-.24,.66-.49,.97-.41,3.86,.86,7.43,2.37,11.33,3.16Z"/><path class="cls-2" d="M646.55,678.57c1.6-4.82,2.36-9.99,3.28-14.97,3.38,1.43,6.94,2.47,10.61,3.3l-.08-.06c-1.72,4.84-1.64,10.08-3.29,14.96lM .12-.12c-3.56-.98-7.01-2.46-10.64-3.12Z"/><path class="cls-2" d="M653.2,710.13c-3.92-.84-7.71-1.98-11.5-3.13,1.57-4.3,1.35-9.09,2.73-13.44,.79-.29,1.41-.11,2.03,.07,2.76,.79,5.51,1.6,8.26,2.39l-.07-.08c.14,4.77-1.22,9.54-1.62,14.31l.16-.12Z"/><path class="cls-2" d="M654.73,696.02c1.29-4.63,1.84-9.55,2.46-14.32l-.12,.11c3.59,.6,7.16,1.47,10.62,2.59l-.08-.09c0,4.81-1.48,9.5-1.51,14.29-3.81-.89-7.63-1.78-11.44-2.67l.07,.08Z"/><path class="cls-2" d="M649.17,737.27c-4.22-.41-8.19-2.19-12.33-3.11,1.66-3.72,1.59-8.02,2.59M -11.96,.11-.57,.48-1.11,1.21-.99,14.82,3.75,8.7,4.93,12.57-11.08l-.16,.12c2.97,.66,5.95,1.32,8.92,1.98,1.09,.11,2.14,.85,1.8,2.04-.65,4.02-.57,8.24-1.83,12.12l.12-.07c-2.89-.15-5.65-1.11-8.47-1.66-.84-.15-2.34-.65-2.72,.41-.54,4.1-1.7,8.2-1.85,12.31l.16-.11Z"/><path class="cls-2" d="M725.01,838.22c2.57-3.99,4.24-8.51,6.4-12.73,.2-.56,.57-1.38-.1-1.75-3.05-1.1-6.37-1.49-9.52-2.31,1.54-4.63,3.83-9.17,4.96-13.85-.51-.6-1.35-.7-2.1-.85-1.82-.36-3.66-.64-5.48-1-.91-.25-2.65-.39-2.16-1.74,1.37-4.36,2.75-8.72,4.13-13.08l-M .15,.12c3.48,.92,7.08,1.31,10.62,1.96l-.1-.1c-.72,4.15-2.48,8.1-3.63,12.16-.21,.78-.82,1.95,.35,2.27,2.94,.73,5.9,1.39,8.94,1.77,.88,0,1.1-1.12,1.4-1.74,1.11-4.17,3-8.25,3.57-12.51l-.18,.11c3.57,.51,7.1,1.66,10.69,1.82-1.31,4.8-2.95,9.56-4.09,14.39,0,.25,.31,.66,.59,.75,2.86,.75,5.79,2.2,8.79,2.19,2.29-4.67,3.36-9.86,5.14-14.75,3.18,1.31,6.54,2.16,9.8,3.26-1.92,4.95-3.19,10.01-5.37,14.87-14.08-3.65-6.86-5.63-15.29,11.21-.17,.37-.89,.63-1.33,.49-2.5-.77-5-1.55-7.51-2.27-.68-.22-1.31,0-1.95,.05,2.98-4.11,4.11-9.29,6.M 24-13.87,.15-.38,.35-.83-.27-1.42-2.01-.87-4.58-1.1-6.97-1.75-.8-.11-1.94-.51-2.63,.06-2.12,4.18-3.46,8.79-5.28,13.13-.06,.17,.08,.39,.13,.58,2.56,1.2,5.55,1.56,8.23,2.5,.28,.08,.4,.49,.6,.75,.26,.29,.19,.6,.05,.9-2.08,4.62-4.32,9.17-6.71,13.64-3.07-1.53-6.56-2.14-9.81-3.28Z"/><path class="cls-2" d="M758.98,767.7c-.1,4.56-1.79,9.1-2.5,13.64-.09,.4-.7,.77-1.18,.7-2.63-.43-5.24-.89-7.86-1.36-1.17-.18-1.76,.16-1.99,1.09-1.29,4.36-1.67,9.04-3.51,13.19l.18-.11c-3.54-.65-7.09-1.3-10.63-1.95l.1,.1c1.32-4.7,2.99-9.48,3.11-M 14.31,3.28,.36,6.54,.92,9.81,1.37,.78,.11,1.34-.2,1.46-.77,.97-4.49,1.93-8.99,2.5-13.55,3.49,.87,7.16,1.07,10.61,2.04l-.11-.09Z"/><path class="cls-2" d="M761.43,753.6c3.55-.02,7.2,.98,10.63,1.82-.11,4.27-1.28,8.44-1.91,12.65-.16,.98-.67,1.82-1.89,1.53-3.09-.62-6.15-1.43-9.27-1.9l.11,.09c1.29-4.67,1.63-9.53,2.46-14.29l-.12,.11Z"/><path class="cls-2" d="M1041.28,373.35c22.91,.41,45.94,.34,68.85,1.97-1.87,4.66-3.75,9.33-5.6,14-.12,.29-.04,.63-.06,.95-22.75-1.75-45.54-2.5-68.35-2.76-.8-.3-.22-1.4-.06-1.99,1.73-4.05,3.8M 1-7.98,5.22-12.16Z"/><path class="cls-2" d="M699.95,816.9c1.84-4.57,4.07-9.01,5.67-13.66,2.61,.47,5.22,.94,7.82,1.42,.83,.28,2.83,.25,2.69,1.43-1.16,3.64-2.68,7.16-4.01,10.75-.4,.7-.66,1.96-1.65,2-3.56-.34-6.94-1.53-10.52-1.93Z"/><path class="cls-2" d="M721.13,790.92c-3.86,.11-7.58-1.13-11.44-1.24l.09,.1c.58-4.33,2.03-8.58,2.93-12.87,.16-.6,.7-.93,1.41-.87,3.44,.29,6.88,.62,10.22,1.39-1.61,4.4-2.11,9.1-3.36,13.61l.15-.12Z"/><path class="cls-2" d="M705.72,803.34c-3.81-.65-7.62-1.3-11.42-1.95,1.32-4.57,3.22-9.02,4.14M -13.67l-.12,.09c3.78,.85,7.72,1.01,11.45,1.98l-.09-.1c-1.32,4.55-2.63,9.11-3.97,13.66Z"/><path class="cls-2" d="M670.82,796.85c2.37-4.04,2.56-9.13,5.08-13.03l-.21,.11c3.04,.91,6.27,1.2,9.39,1.86,.56,.07,1.46,.2,1.83-.29,1.69-4.04,2.4-8.39,3.34-12.61,3.85,.23,7.57,1.12,11.43,1.26-1.06,4.57-1.99,9.16-3.36,13.66l.12-.09c-3.51-.08-6.86-1.01-10.34-1.35-.69-.08-1.28,.26-1.48,.84-.91,2.7-1.77,5.41-2.7,8.11-1.43,4.14-.68,4.06-6.05,2.94-2.34-.49-4.7-.94-7.04-1.41Z"/><path class="cls-2" d="M702.5,630c-1.34,4.25-2.68,8.5-4.02M ,12.76-.15,.77-.49,1.71-1.49,1.61-2.75-.46-5.48-.97-8.22-1.48-.65-.11-1.3,.26-1.45,.84-1.19,4.5-2.22,9.04-3.55,13.51l.13-.08c-2.6-.56-5.2-1.11-7.79-1.67-.77-.16-1.54-.4-2.41-.11-1.86,4.25-1.77,9.15-3.22,13.55-.08,.24-.66,.5-.98,.42-3.02-.83-6.3-1.2-9.13-2.51l.08,.06c.01-.63-.08-1.27,.05-1.88,1.07-4.33,1.54-8.87,3.1-13.05,2.52,1.29,5.53,1.68,8.27,2.49,1.12,.28,1.71-.03,1.98-1.03,.95-3.8,1.89-7.59,2.92-11.37,.17-.62,.3-1.28,1.17-1.73,12.24,2.2,8.48,4.81,12.45-7.3,.45-1.46,.98-2.9,1.5-4.35,.17-.47,.69-.69,1.26-.56,3.1M 2,.61,6.17,1.65,9.35,1.87Z"/><path class="cls-2" d="M672.46,621.58c3.15,1.33,6.35,2.54,9.81,3.25-1.55,4.66-3.06,9.32-4.61,13.98-.29,.84-.84,1.09-1.76,.82-2.77-.81-5.51-1.69-8.29-2.44,.97-5.34,3.93-10.31,4.85-15.62Z"/><path class="cls-2" d="M667.74,637.13c-1.91,4.09-2.59,8.71-3.94,13.03-.16,.61-.1,1.26-.14,1.9-3.28-.64-6.24-1.89-9.26-3.04-.49-.18-.71-.59-.58-1.08,.6-2.3,1.2-4.61,1.84-6.91,.52-1.88,1.08-3.76,1.64-5.63,.24-.74,.67-1.75,1.66-1.41,2.93,1.05,5.86,2.1,8.79,3.15Z"/><path class="cls-2" d="M682.15,624.89c2.4M 7-4.82,3.63-10.25,6.53-14.93,2.72,.91,5.44,1.81,8.16,2.72,.9,.28,1,.9,.72,1.59-1.71,4.18-3.41,8.36-5.13,12.53-.22,.53-.93,.83-1.61,.64-2.9-.84-5.78-1.69-8.68-2.54Z"/><path class="cls-2" d="M718.68,618.4c-2.46,4.14-3.29,9.1-5.58,13.32-.31,.35-.97,.4-1.44,.31-3.12-.57-6.27-1.08-9.29-1.96,2.17-4.64,3.75-9.55,5.69-14.29,3.53,.9,7.16,1.47,10.62,2.62Z"/><path class="cls-2" d="M774.48,741.3c-3-1.14-6.44-1.27-9.61-2-.97-.17-1.55,.2-1.65,.95-.64,4.44-1.2,8.9-1.79,13.35l.12-.11c-3.42-1.05-7.05-1.22-10.57-1.86-.04-.53-.16-1.0M 6-.11-1.59,.61-4.24,.57-8.62,1.8-12.74l-.1,.1c2.64,.38,5.27,.77,7.91,1.14,.86,.01,2.42,.58,2.83-.46,.75-4.02,1.1-8.09,1.61-12.13,.06-.75,1.07-.95,1.81-.8,3.12,.61,6.24,1.22,9.37,1.83-.42,4.78-1.56,9.55-1.62,14.33Z"/><path class="cls-2" d="M754.18,723.08c-.19,.62-.49,1.23-.56,1.86-.35,4.15-1.07,8.3-1.05,12.47l.1-.1c-3.85-.25-7.59-1.07-11.46-1.19,.54-4.78,.63-9.62,1.65-14.33,3.74,.74,7.56,1.12,11.39,1.37l-.07-.09Z"/><path class="cls-2" d="M766.2,710.79c.54,1.64,.02,3.38-.07,5.06-.34,2.64-.52,5.32-1.05,7.93-.31,.9-1.5M 4,.79-2.32,.67-2.86-.47-5.82-.53-8.59-1.38l.07,.09c-.35-4.13,.73-8.37,.95-12.53,.03-.42,.4-.91,.83-.97,3.48-.05,6.89,.82,10.33,1.23l-.16-.11Z"/><path class="cls-2" d="M694.41,659.09c-1.12,4.68-1.49,9.62-2.94,14.18-3.35,.3-6.35-.82-9.62-1.16-.86-.04-1.1,.75-1.21,1.41-.61,4.24-1.62,8.49-1.68,12.79l.12-.08c-3.85-.45-7.64-1.29-11.46-1.93l.08,.09c1.08-4.16,1.61-8.45,2.38-12.68,.3-1.77,.69-1.96,2.88-1.53,1.66,.06,7.56,2.47,8.13,.57,.9-4.54,1.86-9.07,2.81-13.6l-.13,.08c3.55,.61,7.05,1.5,10.64,1.86Z"/><path class="cls-2" dM ="M719.38,648.07c3.63,1.3,7.64,1.27,11.44,1.98-1.77,4.35-2.13,9.12-3.34,13.65l.11-.1c-3.85,.07-7.63-.83-11.44-1.29l.12,.09c.53-4.84,2.15-9.56,3.12-14.34Z"/><path class="cls-2" d="M678.95,686.32c3.3,.4,6.59,1.31,9.92,1.32,.22-.02,.56-.22,.6-.38,.29-1.27,.57-2.54,.77-3.82,.39-2.56,.71-5.13,1.08-7.7,.18-.92,.47-1.99,1.66-1.82,3.2,.34,6.41,.61,9.49,1.42l-.08-.09c.17,4.81-1.95,9.54-1.46,14.32-3.12-.7-6.35-.85-9.52-1.34-.68-.08-1.72-.06-1.85,.78-.56,3.73-.98,7.48-1.51,11.21-.12,.58-.16,1.53-.9,1.62-3.61-.13-7.16-.77-10.7M 2-1.28,.61-.62,.67-1.36,.76-2.1,.75-4.05,.44-8.35,1.88-12.22l-.12,.08Z"/><path class="cls-2" d="M704.82,661.04c3.87,.13,7.6,.99,11.45,1.37l-.12-.09c-.69,4.78-2.1,9.53-2.3,14.34-3.78-.66-7.6-1.12-11.46-1.4l.08,.09c.8-4.76,2.22-9.47,2.35-14.31Z"/><path class="cls-2" d="M742.94,721.87c-3.58-.32-7.15-.59-10.74-.77-.2-.01-.52,.19-.62,.35-1,4.32-1.01,8.92-1.7,13.33l.12-.07c-2.93-.12-5.86-.34-8.78-.63-.89-.07-2.4-.23-2.51,.92-.33,2.98-.63,5.97-.97,8.95-.14,1.27-.02,2.58-.81,3.76l.11-.07c-15.69-.52-9.23-3.89-13.05,13.02l.1M 1-.09c-3.81-.42-7.59-1.1-11.42-1.2,.6-4.26,1.15-8.53,1.83-12.78,.51-1.64,3.29-.52,4.61-.61,.8,.08,1.58,.25,2.38,.31,4.76,.36,4.61,.74,4.96-3.24,.38-3.41,.81-6.82,.87-10.26l-.12,.08c3.45,.22,6.9,.48,10.35,.72,.53,.04,1.08-.3,1.13-.7,.6-4.34,1.09-8.69,1.6-13.04l-.1,.09c2.79,.11,5.56,.35,8.34,.6,2.65,.17,2.89,.21,3.07-2.13,.18-3.82,.98-7.64,.8-11.46l-.14,.06c3.86-.34,7.59,.94,11.46,.63l-.14-.16c.67,4.79-1.14,9.59-.66,14.38Z"/><path class="cls-2" d="M747.8,680.43c-1.51,4.42-.89,9.34-2.58,13.65l.13-.08c-3.82-.37-7.66-.6M 6-11.44-1.31l.11,.09c1.05-4.5,.85-9.31,2.35-13.65l11.43,1.3Z"/><path class="cls-2" d="M696.01,731.49c-.09,4.39-.48,8.88-1.44,13.15-.16,.45-.81,.64-1.28,.59-3.49-.26-6.94-.68-10.34-1.39,1.15-4.4,1.62-9.1,1.62-13.64,3.81,.45,7.59,1.16,11.43,1.3Z"/><path class="cls-2" d="M700.78,689.47c3.54,.43,7.13,.59,10.61,1.3-.06,3.98-.52,7.93-.98,11.88-.05,1-.38,1.92-1.64,1.79-3.23-.08-6.39-.83-9.61-.66,.26-4.75,.62-9.65,1.62-14.31Z"/><path class="cls-2" d="M707.33,732.8c-3.81-.41-7.63-.82-11.44-1.23,.74-1.31,.65-2.72,.8-4.11,.31M -2.89,.59-5.77,.9-8.66,.1-1.12,1.68-.93,2.56-.86,2.93,.31,5.87,.53,8.81,.7l-.1-.09c-.56,4.77-.49,9.65-1.65,14.33l.12-.08Z"/><path class="cls-2" d="M708.96,718.64c.29-4.29,.61-8.59,1.23-12.85,.09-.54,.69-.9,1.46-.85,2.01,.15,4.01,.3,6.01,.49,3.92,.38,3.72,.1,3.46,3.27-.34,3.75-.78,7.49-.92,11.25l.1-.09c-3.82-.36-7.66-.6-11.44-1.31l.1,.09Z"/><path class="cls-2" d="M732.41,706.96c-3.17-.86-6.6-.7-9.85-1.27-.51-.06-.9-.48-.88-.91,.1-1.7,.18-3.41,.34-5.11,.26-2.33,.44-4.69,.86-7,.06-.29,.78-.73,1.2-.7,3.32,.23,6.64,.5,9M .95,.81l-.11-.09c-.1,4.78-.36,9.72-1.64,14.33l.14-.06Z"/><path class="cls-2" d="M711.24,690.87c.68-.97,.68-2.06,.83-3.13,.54-3.73,1.09-7.46,1.64-11.2,14.16,1.76,10.7-1.22,9.54,12.77-.15,.97-.27,2.32-1.62,2.2-3.48-.11-6.91-.89-10.4-.65Z"/><path class="cls-2" d="M666.01,698.53c3.48,.83,7.03,1.43,10.6,1.94-.14,4.8-.63,9.61-1.63,14.31-3.42-.78-7.08-1.09-10.39-2.21-.36-2.3-.27-3.17,1.42-14.04Z"/><path class="cls-2" d="M692.8,759.3c-.88,4.54-1.81,9.08-2.44,13.67-3.72-.97-7.64-1.26-11.43-1.96,.36-4.6,1.5-9.15,2.45-13.67,3M .56,1.33,7.68,1.19,11.42,1.96Z"/><path class="cls-2" d="M770.43,683.66c-.4,4.44-1.97,9.28-1.61,13.66-3.55-.52-7.08-1.16-10.66-1.45-.68-.06-1.25,.35-1.33,.95-.51,3.82-.83,7.67-1.51,11.47-.08,.42-.63,.75-1.15,.73-3.53-.33-7.22-.35-10.58-1.51l.14,.16c1.02-4.47,1.4-9.09,1.62-13.66l-.13,.08c3.59,.41,7.17,1.04,10.78,1.24,.36,0,.79-.15,.92-.51,1.02-4.27,1.32-8.77,2.08-13.11,3.52,1.13,7.72,1.55,11.42,1.96Z"/><path class="cls-2" d="M724.23,777.48c.88-4.77,1.16-9.63,2.54-14.29l-.12,.07c3.58,.2,7.12,.54,10.59,1.3l-.11-.08c.41M ,1.07,.08,2.14-.09,3.19-.73,3.7-.99,7.54-2.23,11.11-3.48-.69-6.98-1.29-10.59-1.3Z"/><path class="cls-2" d="M739.6,750.34c3.88,.05,7.61,1.02,11.47,1.19-.23,.5-.59,.98-.66,1.5-.63,4.27-1.21,8.54-1.81,12.81-3.81-.47-7.62-1-11.45-1.36l.11,.08c1.5-4.51,1.52-9.61,2.46-14.31l-.11,.1Z"/><path class="cls-2" d="M701.57,774.24c1.17-4.51,1.83-9.09,2.54-13.66l-.11,.09c3.83,.3,7.67,.61,11.43,1.3l-.11-.08c-.11,4.36-1.58,8.64-2.36,12.94-.4,1.16-2.18,.57-3.12,.57-2.76-.37-5.51-.77-8.26-1.16Z"/><path class="cls-2" d="M726.77,763.18cM3 -3.82-.43-7.64-.86-11.46-1.3l.11,.08c.62-4.77,1.61-9.5,1.61-14.31l-.11,.07c3.8,.52,7.62,.91,11.43,1.31l-.1-.09c.12,4.78-1.21,9.54-1.61,14.31l.12-.07Z"/><path class="cls-2" d="M729.87,734.79l11.45,1.23c-.58,4.77-1.15,9.55-1.73,14.32l.11-.1-11.45-1.3,.1,.09c.86-4.75,1.2-9.54,1.63-14.32l-.12,.07Z"/></g></svg>h! iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 7.0-c000 79.217bca6, 2021/06/14-18:28:11 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmpMM="http://ns.adobe.com/xap/1.0/mm/" xmlns:stRef="http://ns.adobe.com/xap/1.0/sType/ResourceRef#" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmlnsM :xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmpMM:OriginalDocumentID="xmp.did:6834ea4d-fb58-c244-ad09-a97d464ba723" xmpMM:DocumentID="xmp.did:5794AF0D336D11ECB4AECBAAFB618A4D" xmpMM:InstanceID="xmp.iid:455213ee-c7a4-b849-8615-0a3088a2385c" xmp:CreatorTool="Adobe Photoshop 22.4 (Windows)" xmp:CreateDate="2021-10-22T22:22:05+03:00" xmp:ModifyDate="2021-10-23T06:03:29+03:00" xmp:MetadataDate="2021-10-23T06:03:29+03:00" dc:format="M image/png" photoshop:ColorMode="3" photoshop:ICCProfile="sRGB IEC61966-2.1"> <xmpMM:DerivedFrom stRef:instanceID="xmp.iid:451c8736-57fa-2140-9123-dad371786109" stRef:documentID="adobe:docid:photoshop:8c5ac5b7-d7e3-b44b-ba11-70a36c9b2a83"/> <xmpMM:History> <rdf:Seq> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:455213ee-c7a4-b849-8615-0a3088a2385c" stEvt:when="2021-10-23T06:03:29+03:00" stEvt:softwareAgent="Adobe Photoshop 22.4 (Windows)" stEvt:changed="/"/> </rdf:Seq> </xmpMM:History> </rdf:Description> </M rdf:RDF> </x:xmpmeta> <?xpacket end="r"?>M text/plain;charset=utf-8 6{"p":"brc-20","op":"mint","tick":"ponz","amt":"10000"}h! text/plain;charset=utf-8 6{"p":"brc-20","op":"mint","tick":"ponz","amt":"10000"}h! text/plain;charset=utf-8 6{"p":"brc-20","op":"mint","tick":"ponz","amt":"10000"}h! text/plain;charset=utf-8 6{"p":"brc-20","op":"mint","tick":"ponz","amt":"10000"}h! text/plain;charset=utf-8 6{"p":"brc-20","op":"mint","tick":"ponz","amt":"10000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! %&'()*456789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz &'()*56789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":" text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":" text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 A{"p":"brc-20","op":"deploy","tick":"modo","max":"6174","lim":"1"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"bits","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"bits","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"bits","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"bits","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"bits","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"bits","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"bits","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"bits","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"bits","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"bits","amt":"1000"}h! FjDOUT:F9B5555E080D24A285EB8F4354F8DF217B0633A103CA1D65095BE088A0F904FC text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/html;charset=utf-8 <!DOCTYPE html><html lang="en"><head><meta charset="UTF-8"><meta http-equiv="X-UA-Compatible"content="IE=edge"><meta name="viewport"content="width=device-width,initial-scale=1.0"><title>SnakeGame</title></head><body style="display:flex;justify-content:center;align-items:center;min-height:100vh;margin:0;background-color:#333;"><canvas id="gameBoard" width="400" height="400" style="border: 1px solid #000000;"></canvas><script>const canvas=document.getElementById("gameBoard");const ctx=canvas.getContext("2d");const grM idSize=20;const tileSize=canvas.width/gridSize;let snake=[{x:10,y:10}];let velocity={x:0,y:0};let food=createFood();document.addEventListener("keydown",moveSnake);function gameLoop(){updateSnake();if(gameOver()){alert("GameOver!");snake=[{x:10,y:10}];velocity={x:0,y:0};food=createFood();}draw();setTimeout(gameLoop,100)}gameLoop();function draw(){ctx.clearRect(0,0,canvas.width,canvas.height);ctx.fillStyle="lime";snake.forEach((segment)=>{ctx.fillRect(segment.x*tileSize,segment.y*tileSize,tileSize,tileSize)});ctx.filM lStyle="red";ctx.fillRect(food.x*tileSize,food.y*tileSize,tileSize,tileSize);}function updateSnake(){const oldSnake=JSON.parse(JSON.stringify(snake));snake[0].x+=velocity.x;snake[0].y+=velocity.y;for(let i=1;i<snake.length;i++){snake[i]=oldSnake[i-1]}if(snake[0].x===food.x&&snake[0].y===food.y){food=createFood();snake.push(oldSnake[oldSnake.length-1])}}function moveSnake(event){if(event.key==="ArrowUp"&&velocity.y===0){velocity={x:0,y:-1}}if(event.key==="ArrowDown"&&velocity.y===0){velocity={x:0,y:1}}if(event.key==M ="ArrowLeft"&&velocity.x===0){velocity={x:-1,y:0}}if(event.key==="ArrowRight"&&velocity.x===0){velocity={x:1,y:0}}}function createFood(){const newFood={x:Math.floor(Math.random()*gridSize),y:Math.floor(Math.random()*gridSize)};for(const segment of snake){if(segment.x===newFood.x&&segment.y===newFood.y){return createFood()}}return newFood}function growSnake(){const lastSegment=snake[snake.length-1];snake.push({x:lastSegment.x,y:lastSegment.y})};function gameOver(){if(snake[0].x<0||snake[0].x>=gridSize||snake[0].y<0|L |snake[0].y>=gridSize){return true}for(let i=1;i<snake.length;i++){if(snake[i].x===snake[0].x&&snake[i].y===snake[0].y){return true}}return false}</script></body></html>h! text/plain;charset=utf-8 text/plain;charset=utf-8 +{"p":"sns","op":"reg","name":"Roshan.sats"}h! text/plain;charset=utf-8 :{"p":"brc-20","op":"transfer","tick":"pepe","amt":"10000"}h! text/plain;charset=utf-8 :{"p":"brc-20","op":"transfer","tick":"pepe","amt":"10000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 "p":"sns","op":"reg","name":"discord.unisat" text/plain;charset=utf-8 "p":"sns","op":"reg","name":"adidas.unisatt" text/plain;charset=utf-8 "p":"sns","op":"reg","name":"0009.unisatt" text/plain;charset=utf-8 "p":"sns","op":"reg","name":"0006.unisatt" text/plain;charset=utf-8 "p":"sns","op":"reg","name":"66666.unisatt" text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 LW{"p":"orditalk.org","op":"post","content":"GM<br />","attached_inscription_id":"26158"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 @{"p":"brc-20","op":"deploy","tick":" ","max":"300","lim":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":" text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":" text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! gvyfuxulJ_mp_mo^loriH]V;F]bBKM6J gvyulJriHfux_mp_mo^loF]b]V;BKM6J gvyfuxulJ_mp_mo^loriH]V;F]bBKM6J gvyfuxulJ_mp_mo^loriH]V;F]bBKM6J gvyfuxulJ_mp_mo^loriH]V;F]bBKM6J gvyfuxulJ_mp_mo^loriH]V;F]bBKM6J =FH/7873#51")IP)HO)3 gvyfuxulJ_mp_mo^loriH]V;F]bBKM6J ulJ_mp_mo^loriH]V;F]bBKM _mp_mo^loF]b]V;BKM=FH:x gvyfuxulJriH_mp_mo^loF]b Yl]V;BKM)IP)HO(HO(HN(GN=FH&CJ$AG/7873#51" gvyfuxulJriH_mp_mo^loF]b Yl]V;BKM)IP)HO(HO(HN(GN=FH&CJ$AG/7873#51" gvyfuxulJriH_mp_mo^loF]b Yl]V;BKM)IP)HO(HO(HN(GN=FH&CJ$AG/7873#51" gvyfuxulJriH_mp_mo^loF]b Yl]V;BKM)IP)HO(HO(HN(GN=FH&CJ$AG/7873#51" gvyfuxulJ_mp_mo^loriH]V;F]bBKM)IP Yl]V;BKM)IP)HO(HO(HN(GN=FH&CJ$AG/7873#51" gvyfuxulJriH_mp_mo^loF]b Yl]V;BKM)IP)HO(HO(HN(GN=FH&CJ$AG/7873#51" gvyfuxulJriH_mp_mo^loF]b )HO(HO(HN=FH(GN&CJ$AG/7873#51" gvyfuxulJ_mp_mo^loriH]V;F]bBKM=FH<' )IP)HO(HO(HN(GN&CJ$AG o^loriH]V;F]bBKM=FH<' )IP)HO(HO(HN(GN&CJ$AG gvyfuxulJ_mp_mo^loriH]V;F]bBKM=FH<' )IP)HO(HO(HN(GN&CJ$AG gvyfuxulJ_mp_mo^loriH]V;F]bBKM=FH<' )IP)HO(HO(HN(GN&CJ$AG (yulJriH_mp_mo^loF]b]V;BKM=FH/7873#51"] (yulJriH_mp_mo^loF]b]V;BKM=FH/7873#51"] (yulJriH_mp_mo^loF]b]V;BKM=FH/7873#51"] (yulJriH_mp_mo^loF]b]V;BKM=FH/7873#51"] (yulJriH_mp_mo^loF]b]V;BKM=FH/7873#51"] (y_mp_mo^loF]b]V;BKM=FH/7873#51"] (y_mp_mo^loF]b]V;BKM=FH/7873#51"] (y_mp_mo^loF]b]V;BKM=FH/7873#51"] $iulJriH_mp_mo^lo]V;F]b DBKM)IP)HO(HO(HN=FH(GN&CJ$AG73#/7851">+ D^loF]b]V;BKM)IP)HO(HO(HN=FH(GN&CJ$AG73#/7851">+ DriH_mp_mo^lo]V;F]bBKM)IP)HO(HO(HN=FH(GN&CJ$AG73#/7851">+ DriH_mp_mo^lo]V;F]bBKM)IP)HO(HO(HN=FH(GN&CJ$AG73#/7851">+ DriH_mp_mo^lo]V;F]bBKM)IP)HO(HO(HN=FH(GN&CJ$AG73#/7851">+ DriH_mp_mo^lo]V;F]bBKM)IP)HO(HO(HN=FH(GN&CJ$AG73#/7851">+ DulJ_mp_mo^loriH]V;F]bBKM)IP)HO(HO(HN(GN=FH&CJ$AG/7873#51">+ DulJ_mp_mo^loriH]V;M F]bBKM)IP)HO(HO(HN(GN=FH&CJ$AG/7873#51">+ text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! %&'()*456789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz &'()*56789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":" text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 ){"p":"sns","op":"reg","name":"GPT8.sats"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 ){"p":"sns","op":"reg","name":"DOGE.sats"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xap/1.0/mm/" xmlns:stEvtM ="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMM:History> <rdf:Seq> <M rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </rdf:Seq> </xmpMM:HistM ory> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> sMuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuu text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 1{"p":"sns","op":"reg","name":" text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":" text/plain;charset=utf-8 9{"p":"brc-20","op":"mint","tick":"Gua~","amt":"21000000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! <svg xmlns='http://www.w3.org/2000/svg' xmlns:xlink='http://www.w3.org/1999/xlink' image-rendering='pixelated' viewBox='0 0 800 800'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoCAMAAAC7IEhfAAAARVBMVEXinc3flMjhmMrkoc/y0OnlptLz1OruxOLruNzpsdjmqtTdjMPsvN7nrdbtwODbhsHxy+bwyOTej8bqtNrxzefZgr7ZgL0cO9EEAAABH0lEQVQ4y8TPSQ7CMBBE0Q4zCRCIY9//qNRgt8QJqA0Inn7L0Vqt67ouy7JtE3bo4/dtw8/4s9bWwo5MKnKwpM pYxXFfHXLdDRgWzozpjM8ZPWknSGuA4ixyY0FMjBkWU54FCd5kDI7r3EYMi6uuRDjWoUm5aKbCopox0ZFQPjZY0ZegddoXq1UdbJPUiwnRi1z7SlIQ/juyjkf7IAeGQI3troIhSDjhNDrJntmOiaipJpaAO2+0nbbfUcSYFHeRd1IA0VHndSUJfdtC9C+amk74d4ykO2lk6OZ4jiMsOyqVE0rcHnAfc7TwlDef/w29jdUAAAACCAOj/ay4woVKqYXo9u/A+4YeiY9bB7Spsub6uDcCS8kg1ew1p09zY9/sAJFQ4OREZSsoAAAAASUVORK5CYII='/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAM AAAoBAMAAAB+0KVeAAAAIVBMVEUAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABt0UjBAAAAC3RSTlMAYEJYVDQnGBNOTJeVFx8AAAAzSURBVCjPYxgFo2BIAvZULRdDYZdFYQUIsSZBONCACxoiBIVxqESYqeksKGgyCWgmiQAAX5gI535S03cAAAAASUVORK5CYII='/></foreignObject><g class='effect2'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAG1BMVEUAAAAAAAAAAAAAPMMAJnEqbfFjm/8STL8cCyxw0u+6AAAAAnRSTlMACQ9PdZwAAACgSURBVCjPM 3Y87DsMgEESBE0Q5gTM4n9oWpo0iCpdRHHMAiHyCIFpXOXfkDsPWLjzl08w+Lds8AjnBgYmpylgHxs9NRqXFSQSXHVSdQ7DrKpdhaOLoUgQgBnsJr6SK1jsYHf0n3UM9BZZUK/tAvXO9lxC6gBz+XUAxjd+5WEvdE56W8LB6JuQ1L9eKOPkzlAc36suekhPwaB5EEyAgZzvKH/JfGIEt4FetAAAAAElFTkSuQmCC'/></foreignObject></g><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAG1BMVEUAAAAnDQislnWTg2q9qIhZVlLLtaE7NzLezLzZuBaIAAAAAXRSTlMAQObYZgAAAHtM JREFUKM9jGAWDEYhiEWMsDcAiGGyOKShurKReXi6AZqSRSpqTKqogY7GSi1uasiCqYJGyiluGk6gAqqCwiktak6giFkFBVMFikKCSgCCKoGAwUFAZ3UnGRm5JphiCQBCIHh6mgYLBAujeDBdgLEUXFBQUYBQECtIZAADsZxPbfZk9RAAAAABJRU5ErkJggg=='/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoAgMAAADxkFD+AAAADFBMVEUAAADfcSauSwjBXRkAUmJRAAAAAXRSTlMAQObYZgAAAB5JREFUGNNjGAWUAu7QOBhTG8HUrdsBY6o3TKC6pQCYogQ329qTgAAAAABJRU5ErkM Jggg=='/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAFVBMVEUAAAD92gD/8AY0Ly78qwAnDQjy2BZpdjU7AAAAAXRSTlMAQObYZgAAAFFJREFUKM9jGAWDEYRgEWN1ccAiKOiipGSAJhgopOjs7BKALihobKyCKsjqKCRoqGQSii6YCFQZGIAi6KQEUhkigCoYhDATARgVhYVFGEYWAAAMRAsG3NsXsgAAAABJRU5ErkJggg=='/></foreignObject><g class='effect'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='M http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAJ1BMVEUAAAAnDQich2aslnW9qIiTg2o7NzLezLxZVlIAAADsmJnNd3jDXV6RqQwDAAAAAXRSTlMAQObYZgAAAFNJREFUKM9jGAWMgggKIbhaEASkF6IolelQcS931hFA1Z9kbOJipIYuaBrsYhqGKeiOKaga7FKkiOamDGVjo5mNaC4VbFLSnAnTjRAFAoZRMLAAAEOoDnwejNL6AAAAAElFTkSuQmCC'/></foreignObject></g><g class='effect'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='dM ata:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAIVBMVEUAAAAhFC1OK2B8WdaPcd1oRMOjKZi+QrLsXt/9oT793T7D1pfbAAAAAXRSTlMAQObYZgAAAFdJREFUKM9joDtgFBTEFBRSMhbAUKgopKyIoVCAUcUIXakgUL+JIob+tPQZywXQVAqmVcxcUSiIok5JKdTY2NglSABFpZBqsLGJoyC644FAgGEUjAJUAAAXLgqYkKe3hgAAAABJRU5ErkJggg=='/></foreignObject></g><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoAgMAAADxkFD+AAAADFBMVEUAAAM AAAADL2/xJWv9uTtKqAAAAAXRSTlMAQObYZgAAABhJREFUGNNjGAUDBPIcd8KY1Y7vHEjUDQC19gNT1hAW0QAAAABJRU5ErkJggg=='/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoAQMAAAC2MCouAAAAA1BMVEUAAACnej3aAAAAAXRSTlMAQObYZgAAAAtJREFUCNdjGGEAAADwAAFOldjfAAAAAElFTkSuQmCC'/></foreignObject><g class='effect2'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/M xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoAgMAAADxkFD+AAAACVBMVEUAAAAAAAD///+D3c/SAAAAAXRSTlMAQObYZgAAABVJREFUGNNjGIqAsUECznQQYRiJAADtwwDvRmwtWAAAAABJRU5ErkJggg=='/></foreignObject></g><style> .effect { animation: 0.75s effect infinite alternate ease-in-out; } @keyframes effect { from { transform: translateY(0px); } to { transform: translateY(2.5%); } }.effect2 { animation: 0.75s effect2 infinite alternate ease-in-out; } @keyframes effect2 { from { transform: translaAteY(0px); } to { transform: translateY(1.5%); } } </style> </svg>h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 -{"p":"sns","op":"reg","name":"rolltide.sats"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! %&'()*456789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz &'()*56789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 ({"p":"sns","op":"reg","name":"sex.sats"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! riTXtXML:com.adobe.xmp ' id='W5M0MpCehiHzreSzNTczkc9d'?> <x:xmpmeta xmlns:x='adobe:ns:meta/'> <rdf:RDF xmlns:rdf='http://www.w3.org/1999/02/22-rdf-syntax-ns#'> <rdf:Description rdf:about='' xmlns:Attrib='http://ns.attribution.com/ads/1.0/'> <rdf:li rdf:parseType='Resource'> <Attrib:Created>2023-04-08</Attrib:Created> <Attrib:ExtId>0cb840c1-6826-4fb4-M a925-3bea33deed1c</Attrib:ExtId> <Attrib:FbId>525265914179580</Attrib:FbId> <Attrib:TouchType>2</Attrib:TouchType> <rdf:Description rdf:about='' xmlns:dc='http://purl.org/dc/elements/1.1/'> <rdf:li xml:lang='x-default'>Jesus - 11</rdf:li> <rdf:Description rdf:about='' xmlns:pdf='http://ns.adobe.com/pdf/1.3/'> <pdf:Author>Lion's Logistics</pdf:Author> <rdf:Description rdf:about='' xmlns:xmp='http://ns.adobe.com/xap/1.0/'> <xmp:CreatorTool>Canva</xmp:CreatorTool> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/html;charset=utf-8 <meta charset="UTF-8"> <title>Minimal Indicator</title> <script sandbox="allow-scripts" type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/p5.js/1.5.0/p5.min.js"></script> <!-- svgjs@3.1.2 <script sandbox="allow-scripts" type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/svg.js/3.1.2/svg.min.js"></script> <script id="snippet-random-code" type="text/javascript"> // DO NOT EDIT M let seed = window.location.href.split('/').find(t => t.includes('i0')); if (seed == null) { const alphabet = "0123456789abcdefghijklmnopqrstuvwsyz"; seed = new URLSearchParams(window.location.search).get("seed") || Array(64).fill(0).map(_ => alphabet[(Math.random() * alphabet.length) | 0]).join('') + "i0"; let pattern = "seed="; for (let i = 0; i < seed.length - pattern.length; ++i) { if (seed.sM ubstring(i, i + pattern.length) == pattern) { seed = seed.substring(i + pattern.length); break; function cyrb128($) { let _ = 1779033703, u = 3144134277, i = 1013904242, l = 2773480762; for (let n = 0, r; n < $.length; n++) _ = u ^ Math.imul(_ ^ (r = $.charCodeAt(n)), 597399067), u = i ^ Math.imul(u ^ r, 2869860233), i = l ^ Math.imul(i ^ r, 951274213), l = _ ^ Math.imul(l ^ r, 2716044179); return _ = Math.imul(i ^ _ >>> 18, 597399067), u = Math.imul(l ^ u >>> 22, 2869860233), i = Math.imul(_ ^ i >>> 17, 951274213), l = Math.imul(u ^ l >>> 19, 2716044179), [(_ ^ u ^ i ^ l) >>> 0, (u ^ _) >>> 0, (i ^ _) >>> 0, (l ^ _) >>> 0] function sfc32($, _, u, i) { return function () { u >>>= 0, i >>>= 0; var l = ($ >>>= 0) + (_ >>>= 0) | 0; return $ = _ ^ _ >>> 9, _ = u + (u << 3) | 0, u = (u = u << 21 | u >>> 11) + (M l = l + (i = i + 1 | 0) | 0) | 0, (l >>> 0) / 4294967296 // IMPORTANT: Instead of Math.random(), use this function mathRand() for random number generation. // This function generates a random number between 0 and 1 with on-chain seed. let mathRand = sfc32(...cyrb128(seed)); #fullScreen, display: flex; right: 0; bottom: 0; justify-content: center; position: fixed color: #000000; background-color: #ffffff; align-items: center; margin: 0; padding: 0; font-size: .8em #fullScreen .p5Canvas, #fullScreen canvas, object-fit: contain; max-height: 100%; max-width: 100% align-items: center color: #f9f9f9; opacity: .85; background-color: #000000; border-radius: 5px; padding-top: 0; width: auto; height: auto; position: fixed; text-align: center; justify-content: center; align-items: center; top: 50%; left: 50%; -webkit-transform: translate(-50%, -50%)M transform: translate(-50%, -50%) #progress h2 { display: block; font-size: .9rem; color: #efefef; margin: 5% #progress p { font-size: .75rem; display: block; margin: 5% #progress hr { width: 75%; margin-bottom: 10% <script type="text/javascript"> const rand = mathM let bg, main, maxI; ////////////////INFO & FEATURES let title = "Minimal Indicator"; function clr(rand) { if (rand > 0.5) { bg = 0; main = 255 return ("Black") } else { bg = 255; main = 0 return ("White") function layers(rand) { if (rand < 0.33) { return ('1'M else if (rand < 0.66) { return ('2'); } else { return ('3') function rot(rand) { if (rand < 0.1) { return (-1) else if (rand < 0.2) { return (1) else if (rand < 0.3) { return (-1.5) else if (rand < 0.4) { return (1.5) else if (rand < 0.5) { return (-0.75) else if (rand < 0.6) { return (0.75) else if (rand < 0.7) { return (-0.5) else if (rand < 0.8) { return (0.5) else if (rand < 0.9) { return (-0.25) } else { return (0.25) let ratio = 1.414142 let format M n: mathRand(), name: '' if (format.n < 0.33) { format.ww = ratio format.hh = 1 format.name = "Landscape" } else if (format.n < 0.66) { format.ww = 1 format.hh = ratio format.name = "Portrait" format.ww = 1 format.hh = 1 format.name = "Square" let cSize = choM oseRandom([2.5, 5, 7.5, 10]); window.$generativeTraits = { "Format": format.name, "Bg Color": clr(rand), "Layers": layers(rand), console.log(title + " | smldms 2023.02") console.log(window.$generativeTraits) //////////////////////////////////////// let globalSize = 1920 * 2; let xoff = 0.5; let yoff = 0.5; let globalData; let url = 'https://api.coingecko.com/api/v3/simple/price?ids=bitcoin&vs_currencies=usd&include_market_cap=true&include_24hr_vol=true&include_24hr_change=true&include_last_updated_at=true'; let priceClr; function setup() { randomSeed(seed); noiseSeed(seed); cnv = createCanvas(globalSize * format.ww, globalSize * format.hh); cnv.parent('fullScreen'); background(bg); setInterval(askData, 1000); angleMode(DEGRM rectMode(CENTER) function draw() { progress('--- PLEASE WAIT ---<br/><br/>LOADING DATA') if (globalData) { noLoop() progressClear() btcChange = globalData.bitcoin.usd_24h_change; gridPoint(10000) pX = mathRandBetween(width * 0.1, width * 0.9) pY = mathRandBetween(height * 0.1, height * 0.9) if (btcChange < 0) { priceClr = color(250, 4, 4) priceClr = color(4, 250, 4) theSquare(pX, pY, globalSize / 16.18) for (let i = 0; i < 5; i++) { theShape(width / 2, height / 2, 0, 0, globalSize / mathRandBetween(10,15), mathRandBetween(-360,360), pX, pY) blendMode(DIFFERENCE) rect(width / 2, height / 2, width / mathRandBetween(1.618, 3.14), height / mathRandM Between(1.618, 3.14)) theSquare(pX, pY, globalSize / 31.414) grainy(23) progressShow() function theShape(x, y, anchorX, anchorY, maxtheShape, s, x1, y1) { down = maxtheShape / (globalSize / 15) for (let j = 0; j < 5; j++) { for (let i = 0; i < maxtheShape; i++) { noFill() stM roke(map(i, 0, maxtheShape, main, bg)) strokeWeight(map(i, 0, maxtheShape, 4, 0)) let noisetheShape = map(noise(xoff * 0.25, yoff * 0.25), 0, 1, s * 1.25, s) let factor = map(noise(xoff, yoff), 0, 1, -globalSize / 3, globalSize / 3) push() translate(x, y) print(x1, y1) let distance = dist(anchorX + j + factor, anchorY + j + factor + noisetheShape, 0, 0) if (distance < globalSize * 0.75) { beginShape(); vertex(anchorX + j + factor, anchorY + j - factor + noisetheShape); if (mathRand() < 0.05) { vertex(x1 - x, y1 - y) } vertex(anchorX - j + factor, anchorY - j + factor - noisetheShape); endShape(CLOSE); } pop() xoff += 0.002M yoff += 0.005; s -= down; function askData() { loadJSON(url, gotData); function gotData(data) { globalData = data; setTimeout(askData, 120000); function gridPoint(nbrPoint) { for (let pt = 0; pt < nbrPoint; pt++) { push() strokeWeight(mathRand() * 1.5) point(mathRand() * width, mathRand() * height) pop() let scl = mathRandBetween(10, 25); for (let x = width * 0.15; x < width * 0.85; x += scl) { for (let y = height * 0.1; y < height * 0.9; y += scl) { push() noStroke() fill(main, mathRandBetween(2, 150)) ellipse(x, y, mathRand() * cSize) pop() stroke(main, mathRandBetween(0, 5)) if (mathRand() < 0.25) { line(x, y, x, height * 0.9) } else if (mathRand() < 0.5) { line(x, y, width * 0.15, y) } else { // line(x, y, x, height * 0.1) } function theSquare(posX, posY, s) { fill(priceClr) rect(posX, posY, s) function grainy(force) { loadPixels(); let d = pixelDensity(); let halfImage = 4 * (width * d) * (height * d); for (let i = 0; i < halfImage; i += 4) { grainAmount = random(-force, force); pixels[i] = pixels[i] + grainAmount; pixels[i + 1] = pixels[i + 1] + grainAmount; pixels[i + M 2] = pixels[i + 2] + grainAmount; pixels[i + 3] = pixels[i + 3] + grainAmount updatePixels(); function chooseRandom(arr) { const randomIndex = Math.floor(mathRand() * arr.length); return arr[randomIndex]; function keyTyped() { if (keyCode === 83) { // if "s" is pressed save(title + '.png'); function mathRandBetween(a, b) { return mathRand() * a return mathRand() * (b - a) + a /////////////PROGRESS async function progress(message) { document.body.style.cursor = 'wait'; document.getElementById("progress").innerHTML = message; await new Promise((fn => setTimeout(fn, 1))); async function progressClear() { document.body.style.cursor = 'default'; document.getElementByM Id("progress").style.display = 'none'; await new Promise((fn => setTimeout(fn, 1))); async function progressShow() { document.body.style.cursor = 'default'; document.getElementById("progress").style.display = 'block'; await new Promise((fn => setTimeout(fn, 1))); <div id="fullScreen"> <div id="progress"> <script defer src="https://static.cloudflareinsights.com/beacon.minM\ .js/v2b4487d741ca48dcbadcaf954e159fc61680799950996" integrity="sha512-D/jdE0CypeVxFadTejKGTzmwyV10c1pxZk/AqjJuZbaJwGMyNHY3q/mTPWqMUnFACfCTunhZUVcd4cV78dK1pQ==" data-cf-beacon='{"rayId":"7b4cebbf1fb7a22e","version":"2023.3.0","b":1,"token":"6c07c178c94442f695e7a0a2aaee641a","si":100}' crossorigin="anonymous"></script> text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 .{"p":"sns","op":"reg","name":"richemont.sats"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"nako","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"nako","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! sMuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuu text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/html;charset=utf-8 <meta charset="utf-8" /> position: relative; width: var(--width); height: var(--height); border: 1px solid blue; position: relative; <div id="upload"> <input id="inputUpload" type="file"> function e(e){"use strict";return new function e(t){let n="global"==t?window:this;n.canvas=document.createElement("canvas");let r=n.canvas.getContext("2d");n.width=100,n.height=100,n.canvas.width=n.width,n.canvas.height=n.height,"offscreen"!=t&&(document.body?document.body.appendChild(n.canvas):window.addEventListener("load",(function(){document.body.appendChild(n.canvas)}))),g(),n.MAGIC=161533525,n.RGB=0,n.HSV=1,n.HM SB=1,n.CHORD=0,n.PIE=1,n.OPEN=2,n.RADIUS=1,n.CORNER=2,n.CORNERS=3,n.ROUND="round",n.SQUARE="butt",n.PROJECT="square",n.MITER="miter",n.BEVEL="bevel",n.CLOSE=1,n.BLEND="source-over",n.REMOVE="destination-out",n.ADD="lighter",n.DARKEST="darken",n.LIGHTEST="lighten",n.DIFFERENCE="difference",n.SUBTRACT="subtract",n.EXCLUSION="exclusion",n.MULTIPLY="multiply",n.SCREEN="screen",n.REPLACE="copy",n.OVERLAY="overlay",n.HARD_LIGHT="hard-light",n.SOFT_LIGHT="soft-light",n.DODGE="color-dodge",n.BURN="color-burn",n.NORMAL="norM mal",n.ITALIC="italic",n.BOLD="bold",n.BOLDITALIC="italic bold",n.CENTER="center",n.LEFT="left",n.RIGHT="right",n.TOP="top",n.BOTTOM="bottom",n.BASELINE="alphabetic",n.LANDSCAPE="landscape",n.PORTRAIT="portrait",n.ALT=18,n.BACKSPACE=8,n.CONTROL=17,n.DELETE=46,n.DOWN_ARROW=40,n.ENTER=13,n.ESCAPE=27,n.LEFT_ARROW=37,n.OPTION=18,n.RETURN=13,n.RIGHT_ARROW=39,n.SHIFT=16,n.TAB=9,n.UP_ARROW=38,n.HALF_PI=Math.PI/2,n.PI=Math.PI,n.QUARTER_PI=Math.PI/4,n.TAU=2*Math.PI,n.TWO_PI=2*Math.PI,n.THRESHOLD=1,n.GRAY=2,n.OPAQUE=3,n.INVEM RT=4,n.POSTERIZE=5,n.DILATE=6,n.ERODE=7,n.BLUR=8,n.ARROW="default",n.CROSS="crosshair",n.HAND="pointer",n.MOVE="move",n.TEXT="text",n.VIDEO={video:!0,audio:!1},n.AUDIO={video:!1,audio:!0},n.SHR3=1,n.LCG=2,n.HARDWARE_FILTERS=!0,n.hint=function(e,t){n[e]=t},n.frameCount=0,n.mouseX=0,n.mouseY=0,n.pmouseX=0,n.pmouseY=0,n.mouseButton=null,n.keyIsPressed=!1,n.mouseIsPressed=!1,n.key=null,n.keyCode=null,n.pixels=null,n.accelerationX=0,n.accelerationY=0,n.accelerationZ=0,n.rotationX=0,n.rotationY=0,n.rotationZ=0,n.relRotatM ionX=0,n.relRotationY=0,n.relRotationZ=0,n.pAccelerationX=0,n.pAccelerationY=0,n.pAccelerationZ=0,n.pRotationX=0,n.pRotationY=0,n.pRotationZ=0,n.pRelRotationX=0,n.pRelRotationY=0,n.pRelRotationZ=0,n.touches=[],n._styleCache=[{colorMode:n.RGB,noStroke:!1,noFill:!1,ellipseMode:n.CENTER,rectMode:n.CORNER,curveDetail:20,curveAlpha:0,textFont:"sans-serif",textSize:12,textLeading:12,textStyle:"normal"}],n._style=n._styleCache[n._styleCache.length-1],n._noLoop=!1,n._pixelDensity=1,n._frameRate=null,n._tint=null;let i=nullM ,o=!0,a=[],l=null,s=0,h={},c=0,u=null,f=null,d=null;Object.defineProperty(n,"deviceOrientation",{get:function(){return 90==Math.abs(window.orientation)?n.LANDSCAPE:n.PORTRAIT}}),Object.defineProperty(n,"windowWidth",{get:function(){return window.innerWidth}}),Object.defineProperty(n,"windowHeight",{get:function(){return window.innerHeight}}),Object.defineProperty(n,"drawingContext",{get:function(){return r}}),n.createCanvas=function(e,t){return n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t,g(),n.canvas},nM .resizeCanvas=function(e,t){n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t},n.createGraphics=n.createImage=function(t,n){let r=new e("offscreen");return r.createCanvas(t,n),r.noLoop(),r},n.pixelDensity=function(e){return null==e||(n._pixelDensity=e,n.canvas.width=Math.ceil(n.width*e),n.canvas.height=Math.ceil(n.height*e),n.canvas.style.width=n.width+"px",n.canvas.style.height=n.height+"px",r.scale(n._pixelDensity,n._pixelDensity),g()),n._pixelDensity},n.map=function(e,t,n,r,i,o){let a=r+1*(e-t)/(n-t)*(i-r)M ;return o?r<i?Math.min(Math.max(a,r),i):Math.min(Math.max(a,i),r):a},n.lerp=function(e,t,n){return e*(1-n)+t*n},n.constrain=function(e,t,n){return Math.min(Math.max(e,t),n)},n.dist=function(){return 4==arguments.length?Math.hypot(arguments[0]-arguments[2],arguments[1]-arguments[3]):Math.hypot(arguments[0]-arguments[3],arguments[1]-arguments[4],arguments[2]-arguments[5])},n.norm=function(e,t,r){return n.map(e,t,r,0,1)},n.sq=function(e){return e*e},n.fract=function(e){return e-Math.floor(e)},n.degrees=function(e){retM urn 180*e/Math.PI},n.radians=function(e){return e*Math.PI/180},n.abs=Math.abs,n.ceil=Math.ceil,n.exp=Math.exp,n.floor=Math.floor,n.log=Math.log,n.mag=Math.hypot,n.max=Math.max,n.min=Math.min,n.round=Math.round,n.sqrt=Math.sqrt,n.sin=Math.sin,n.cos=Math.cos,n.tan=Math.tan,n.asin=Math.asin,n.acos=Math.acos,n.atan=Math.atan,n.atan2=Math.atan2,n.Vector=function(e,t,r){let i=this;i.x=e||0,i.y=t||0,i.z=r||0;let o=null,a=null;function l(e,t,n){return null!=e.x?e:null!=t?{x:e,y:t,z:n||0}:{x:e,y:e,z:e}}function s(){null==a&M &(a=i.x*i.x+i.y*i.y+i.z*i.z,o=Math.sqrt(a))}function h(){a=null,o=null}i.set=function(e,t,n){i.x=e||0,i.y=t||0,i.z=n||0},i.copy=function(){return new n.Vector(i.x,i.y,i.z)},i.add=function(){let e=l.apply(null,arguments);return i.x+=e.x,i.y+=e.y,i.z+=e.z,h(),i},i.rem=function(){let e=l.apply(null,arguments);return i.x%=e.x,i.y%=e.y,i.z%=e.z,h(),i},i.sub=function(){let e=l.apply(null,arguments);return i.x-=e.x,i.y-=e.y,i.z-=e.z,h(),i},i.mult=function(){let e=l.apply(null,arguments);return i.x*=e.x,i.y*=e.y,i.z*=e.z,hM (),i},i.div=function(){let e=l.apply(null,arguments);return i.x/=e.x,i.y/=e.y,i.z/=e.z,h(),i},i.mag=function(){return s(),o},i.magSq=function(){return s(),a},i.dot=function(){let e=l.apply(null,arguments);return i.x*e.x+i.y*e.y+i.z*e.z},i.dist=function(){let e=l.apply(null,arguments),t=i.x-e.x,n=i.y-e.y,r=i.z-e.z;return Math.sqrt(t*t+n*n+r*r)},i.cross=function(){let e=l.apply(null,arguments),t=i.y*e.z-i.z*e.y,n=i.z*e.x-i.x*e.z,r=i.x*e.y-i.y*e.x;return i.x=t,i.y=n,i.z=r,h(),i},i.normalize=function(){s();let e=o;retuM rn i.x/=e,i.y/=e,i.z/=e,o=1,a=1,i},i.limit=function(e){s();if(o>e){let t=e/o;i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e}return i},i.setMag=function(e){s();let t=e/o;return i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e,i},i.heading=function(){return Math.atan2(i.y,i.x)},i.rotate=function(e){let t=Math.cos(e),n=Math.sin(e),r=i.x*t-i.y*n,o=i.x*n+i.y*t;return i.x=r,i.y=o,i},i.angleBetween=function(){let e=l.apply(null,arguments);const t=i.dot(e)/(i.mag()*e.mag());let n;return n=Math.acos(Math.min(1,Math.max(-1,t))),n*Math.sign(i.cross(e).z||1)},M i.lerp=function(e,t){return i.x=i.x*(1-t)+e.x*t,i.y=i.y*(1-t)+e.y*t,i.z=i.z*(1-t)+e.z*t,h(),i},i.reflect=function(e){return e.normalize(),i.sub(e.mult(2*i.dot(e)))},i.array=function(){return[i.x,i.y,i.z]},i.equals=function(e,t){return null==t&&null==(t=Number.EPSILON)&&(t=0),Math.abs(e.x-i.x)<t&&Math.abs(e.y-i.y)<t&&Math.abs(e.z-i.z)<t},i.fromAngle=function(e,t){return null==t&&(t=1),o=t,a=t*t,i.x=t*Math.cos(e),i.y=t*Math.sin(e),i.z=0,i},i.fromAngles=function(e,t,n){null==n&&(n=1),o=n,a=n*n;const r=Math.cos(t),l=MaM th.sin(t),s=Math.cos(e),h=Math.sin(e);return i.x=n*h*l,i.y=-n*s,i.z=n*h*r,i},i.random2D=function(){return o=1,a=1,i.fromAngle(Math.random()*Math.PI*2)},i.random3D=function(){return o=1,a=1,i.fromAngles(Math.random()*Math.PI*2,Math.random()*Math.PI*2)},i.toString=function(){return`[${i.x}, ${i.y}, ${i.z}]`}},n.Vector.add=function(e,t){return new n.Vector(e.x+t.x,e.y+t.y,e.z+t.z)},n.Vector.rem=function(e,t){return new n.Vector(e.x%t.x,e.y%t.y,e.z%t.z)},n.Vector.sub=function(e,t){return new n.Vector(e.x-t.x,e.y-t.y,e.M z-t.z)},n.Vector.mult=function(e,t){return null==t.x?new n.Vector(e.x*t,e.y*t,e.z*t):new n.Vector(e.x*t.x,e.y*t.y,e.z*t.z)},n.Vector.div=function(e,t){return null==t.x?new n.Vector(e.x/t,e.y/t,e.z/t):new n.Vector(e.x/t.x,e.y/t.y,e.z/t.z)},n.Vector.dist=function(e,t){return Math.hypot(e.x-t.x,e.y-t.y,e.z-t.z)},n.Vector.cross=function(e,t){return new n.Vector(e.y*t.z-e.z*t.y,e.z*t.x-e.x*t.z,e.x*t.y-e.y*t.x)},n.Vector.lerp=function(e,t,r){return new n.Vector(e.x*(1-r)+t.x*r,e.y=e.y*(1-r)+t.y*r,e.z=e.z*(1-r)+t.z*r)},n.M Vector.equals=function(e,t,n){return e.equals(t,n)};for(let e of["fromAngle","fromAngles","random2D","random3D"])n.Vector[e]=function(t,r,i){return(new n.Vector)[e](t,r,i)};function x(e,t,n){let r,i,o,a,l,s,h,c,u;if(0==t)return[255*(r=n),255*(i=n),255*(o=n)];switch((a=e)>360&&(a=0),h=n*(1-t),c=n*(1-t*(s=(a/=60)-(l=~~a))),u=n*(1-t*(1-s)),l){case 0:r=n,i=u,o=h;break;case 1:r=c,i=n,o=h;break;case 2:r=h,i=n,o=u;break;case 3:r=h,i=c,o=n;break;case 4:r=u,i=h,o=n;break;default:r=n,i=h,o=c}return[255*r,255*i,255*o]}functioM n g(){r.fillStyle="white",r.strokeStyle="black",r.lineCap="round",r.lineJoin="miter"}function p(e){if(0<=e&&e<2*Math.PI)return e;for(;e<0;)e+=2*Math.PI;for(;e>=Math.PI;)e-=2*Math.PI;return e}function m(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;let c=p(a),u=p(l);r.beginPath();for(let a=0;a<h+1;a++){let l=a/h,s=n.lerp(c,u,l),f=Math.cos(s)*i/2,d=Math.sin(s)*o/2;r[a?"lineTo":"moveTo"](e+f,t+d)}s==n.CHORD?r.closePath():s==n.PIE&&(r.lineTo(e,t),r.closePath()),n._style.noFill||r.fill(),n._style.noStrokM e||r.stroke()}function b(e,t,i,o){n._style.noFill&&n._style.noStroke||(r.beginPath(),r.ellipse(e,t,i/2,o/2,0,0,2*Math.PI),n._style.noFill||r.fill(),n._style.noStroke||r.stroke())}function y(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;if(null==a)return function(e,t,i,o){n._style.noFill||r.fillRect(e,t,i,o),n._style.noStroke||r.strokeRect(e,t,i,o)}(e,t,i,o);if(null==l)return y(e,t,i,o,a,a,a,a);const c=Math.min(Math.abs(o),Math.abs(i))/2;a=Math.min(c,a),l=Math.min(c,l),h=Math.min(c,h),s=Math.min(c,s)M ,r.beginPath(),r.moveTo(e+a,t),r.arcTo(e+i,t,e+i,t+o,l),r.arcTo(e+i,t+o,e,t+o,s),r.arcTo(e,t+o,e,t,h),r.arcTo(e,t,e+i,t,a),r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke()}function w(){a=[]}n.createVector=function(e,t,r){return new n.Vector(e,t,r)},n.curvePoint=function(e,t,n,r,i){const o=i*i*i,a=i*i;return e*(-.5*o+a-.5*i)+t*(1.5*o-2.5*a+1)+n*(-1.5*o+2*a+.5*i)+r*(.5*o-.5*a)},n.bezierPoint=function(e,t,n,r,i){const o=1-i;return Math.pow(o,3)*e+3*Math.pow(o,2)*i*t+3*o*Math.pow(i,2)*n+Math.pow(i,M 3)*r},n.curveTangent=function(e,t,n,r,i){const o=i*i;return e*(-3*o/2+2*i-.5)+t*(9*o/2-5*i)+n*(-9*o/2+4*i+.5)+r*(3*o/2-i)},n.bezierTangent=function(e,t,n,r,i){const o=1-i;return 3*r*Math.pow(i,2)-3*n*Math.pow(i,2)+6*n*o*i-6*t*o*i+3*t*Math.pow(o,2)-3*e*Math.pow(o,2)},n.Color=function(e,t,n,r){let i=this;i.MAGIC=786698,i._r=e,i._g=t,i._b=n,i._a=r,i._h=0,i._s=0,i._v=0,i._hsvInferred=!1,i.setRed=function(e){i._r=e,i._hsvInferred=!1},i.setGreen=function(e){i._g=e,i._hsvInferred=!1},i.setBlue=function(e){i._b=e,i._hsvInfM erred=!1},i.setAlpha=function(e){i._a=e/255,i._hsvInferred=!1},i._inferHSV=function(){i._hsvInferred||([i._h,i._s,i._v]=function(e,t,n){let r,i,o,a,l;return r=e<t?e<n?e:n:t<n?t:n,0==(l=100*(i=e>t?e>n?e:n:t>n?t:n)/255)?[o=0,a=0,l]:0==(a=100*(i-r)/i)?[o=0,a,l]:(o=i==e?0+60*(t-n)/(i-r):i==t?120+60*(n-e)/(i-r):240+60*(e-t)/(i-r),[o,a,l])}(i._r,i._g,i._b),i._hsvInferred=!0)},i.toString=function(){return`rgba(${Math.round(i._r)},${Math.round(i._g)},${Math.round(i._b)},${~~(1e3*i._a)/1e3})`}},n.colorMode=function(e){n._stM yle.colorMode=e},n.color=function(){if(1==arguments.length&&786698==arguments[0].MAGIC)return arguments[0];if(n._style.colorMode==n.RGB){if(1==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],1);if(2==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],arguments[1]/255);if(3==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],1);if(4==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],arguments[3]/255)}else{if(1==argumeM nts.length)return new n.Color(...x(0,0,arguments[0]/100),1);if(2==arguments.length)return new n.Color(...x(0,0,arguments[0]/100),arguments[1]/255);if(3==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),1);if(4==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),arguments[3])}return null},n.red=function(e){return e._r},n.green=function(e){return e._g},n.blue=function(e){return e._b},n.alpha=function(e){return 255*e._a},n.hue=function(e){reM turn e._inferHSV(),e._h},n.saturation=function(e){return e._inferHSV(),e._s},n.brightness=function(e){return e._inferHSV(),e._v},n.lightness=function(e){return 100*(.2126*e._r+.7152*e._g+.0722*e._b)/255},n.lerpColor=function(e,t,r){return n._style.colorMode==n.RGB?new n.Color(n.constrain(n.lerp(e._r,t._r,r),0,255),n.constrain(n.lerp(e._g,t._g,r),0,255),n.constrain(n.lerp(e._b,t._b,r),0,255),n.constrain(n.lerp(e._a,t._a,r),0,1)):(e._inferHSV(),t._inferHSV(),new n.Color(n.constrain(function(e,t,r){var i=[[Math.abs(t-M e),n.map(r,0,1,e,t)],[Math.abs(t+360-e),n.map(r,0,1,e,t+360)],[Math.abs(t-360-e),n.map(r,0,1,e,t-360)]];return i.sort(((e,t)=>e[0]-t[0])),(i[0][1]+720)%360}(e._h,t._h,r),0,360),n.constrain(n.lerp(e._s,t._s,r),0,100),n.constrain(n.lerp(e._v,t._v,r),0,100),n.constrain(n.lerp(e._a,t._a,r),0,1)))},n.strokeWeight=function(e){n._style_noStroke=!1,r.lineWidth=e},n.stroke=function(){if(n._style.noStroke=!1,"string"==typeof arguments[0])return void(r.strokeStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._sM tyle.noStroke=!0:r.strokeStyle=e},n.noStroke=function(){n._style.noStroke=!0},n.fill=function(){if(n._style.noFill=!1,"string"==typeof arguments[0])return void(r.fillStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._style.noFill=!0:r.fillStyle=e},n.noFill=function(){n._style.noFill=!0},n.blendMode=function(e){r.globalCompositeOperation=e},n.strokeCap=function(e){r.lineCap=e},n.strokeJoin=function(e){r.lineJoin=e},n.ellipseMode=function(e){n._style.ellipseMode=e},n.rectMode=function(e){n._style.rectM Mode=e},n.curveDetail=function(e){n._style.curveDetail=e},n.curveAlpha=function(e){n._style.curveAlpha=e},n.curveTightness=function(e){n._style.curveAlpha=e},n.clear=function(){r.clearRect(0,0,n.width,n.height)},n.background=function(){if(arguments[0]&&arguments[0].MAGIC==n.MAGIC)return n.image(arguments[0],0,0,n.width,n.height);r.save(),r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity),r.fillStyle="string"==typeof arguments[0]?arguments[0]:n.color(...Array.from(arguments)),r.fillRect(0,0,n.width,n.heightM ),r.restore()},n.line=function(e,t,i,o){n._style.noStroke||(r.beginPath(),r.moveTo(e,t),r.lineTo(i,o),r.stroke())},n.arc=function(e,t,r,i,o,a,l,s){if(o==a)return n.ellipse(e,t,r,i);null==s&&(s=25),null==l&&(l=n.PIE),n._style.ellipseMode==n.CENTER?m(e,t,r,i,o,a,l,s):n._style.ellipseMode==n.RADIUS?m(e,t,2*r,2*i,o,a,l,s):n._style.ellipseMode==n.CORNER?m(e+r/2,t+i/2,r,i,o,a,l,s):n._style.ellipseMode==n.CORNERS&&m((e+r)/2,(t+i)/2,r-e,i-t,o,a,l,s)},n.ellipse=function(e,t,r,i){null==i&&(i=r),n._style.ellipseMode==n.CENTERM ?b(e,t,r,i):n._style.ellipseMode==n.RADIUS?b(e,t,2*r,2*i):n._style.ellipseMode==n.CORNER?b(e+r/2,t+i/2,r,i):n._style.ellipseMode==n.CORNERS&&b((e+r)/2,(t+i)/2,r-e,i-t)},n.circle=function(e,t,r){return n.ellipse(e,t,r,r)},n.point=function(e,t){e.x&&(t=e.y,e=e.x),r.beginPath(),r.ellipse(e,t,.4,.4,0,0,2*Math.PI),r.stroke()},n.rect=function(e,t,r,i,o,a,l,s){n._style.rectMode==n.CENTER?y(e-r/2,t-i/2,r,i,o,a,l,s):n._style.rectMode==n.RADIUS?y(e-r,t-i,2*r,2*i,o,a,l,s):n._style.rectMode==n.CORNER?y(e,t,r,i,o,a,l,s):n._stylM e.rectMode==n.CORNERS&&y(e,t,r-e,i-t,o,a,l,s)},n.square=function(e,t,r,i,o,a,l){return n.rect(e,t,r,r,i,o,a,l)},n.beginShape=function(){w(),r.beginPath(),o=!0},n.beginContour=function(){r.closePath(),w(),o=!0},n.endContour=function(){w(),o=!0},n.vertex=function(e,t){w(),o?r.moveTo(e,t):r.lineTo(e,t),o=!1},n.bezierVertex=function(e,t,n,i,o,a){w(),r.bezierCurveTo(e,t,n,i,o,a)},n.quadraticVertex=function(e,t,n,i){w(),r.quadraticCurveTo(e,t,n,i)},n.bezier=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.bezierVM ertex(r,i,o,a,l,s),n.endShape()},n.triangle=function(e,t,r,i,o,a){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.endShape(n.CLOSE)},n.quad=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.vertex(l,s),n.endShape(n.CLOSE)},n.endShape=function(e){w(),e&&r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke(),n._style.noFill&&n._style.noStroke&&(r.save(),r.fillStyle="none",r.fill(),r.restore())},n.curveVertex=function(e,t){if(a.push([e,t]),a.length<4)return;M let i=function(e,t,n,r,i,o,a,l,s,h){function c(e,t,n,r,i,o){let a=Math.pow(r-t,2)+Math.pow(i-n,2);return Math.pow(a,.5*o)+e}let u=[],f=c(0,e,t,n,r,h),d=c(f,n,r,i,o,h),x=c(d,i,o,a,l,h);for(let h=0;h<s;h++){let c=f+h/(s-1)*(d-f),g=[(f-c)/(f-0),(c-0)/(f-0),(d-c)/(d-f),(c-f)/(d-f),(x-c)/(x-d),(c-d)/(x-d),(d-c)/(d-0),(c-0)/(d-0),(x-c)/(x-f),(c-f)/(x-f)];for(let e=0;e<g.length;e+=2)isNaN(g[e])&&(g[e]=1,g[e+1]=0),isFinite(g[e])||(g[e]>0?(g[e]=1,g[e+1]=0):(g[e]=0,g[e+1]=1));let p=e*g[0]+n*g[1],m=t*g[0]+r*g[1],b=n*g[2]+i*g[M 3],y=r*g[2]+o*g[3],w=i*g[4]+a*g[5],v=o*g[4]+l*g[5],z=p*g[6]+b*g[7],V=m*g[6]+y*g[7],_=b*g[8]+w*g[9],M=y*g[8]+v*g[9],E=z*g[2]+_*g[3],S=V*g[2]+M*g[3];u.push([E,S])}return u}(...a[a.length-4],...a[a.length-3],...a[a.length-2],...a[a.length-1],n._style.curveDetail,n._style.curveAlpha);for(let e=0;e<i.length;e++)o?r.moveTo(...i[e]):r.lineTo(...i[e]),o=!1},n.curve=function(e,t,r,i,o,a,l,s){n.beginShape(),n.curveVertex(e,t),n.curveVertex(r,i),n.curveVertex(o,a),n.curveVertex(l,s),n.endShape()},n.translate=function(e,t){r.tM ranslate(e,t)},n.rotate=function(e){r.rotate(e)},n.scale=function(e,t){null==t&&(t=e),r.scale(e,t)},n.applyMatrix=function(e,t,n,i,o,a){r.transform(e,t,n,i,o,a)},n.shearX=function(e){r.transform(1,0,Math.tan(e),1,0,0)},n.shearY=function(e){r.transform(1,Math.tan(e),0,1,0,0)},n.resetMatrix=function(){r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity)},n.pushMatrix=n.push=function(){n._styleCache.push({...n._style}),n._style=n._styleCache[n._styleCache.length-1],r.save()},n.popMatrix=n.pop=function(){n._stylM eCache.length-1&&(n._styleCache.pop(),n._style=n._styleCache[n._styleCache.length-1],r.restore())},n.image=function(e,t,i,o,a,l,s,h,c){let u=e.MAGIC==n.MAGIC?e.canvas:e;function d(){if(e.MAGIC!=n.MAGIC||!n._tint)return;let t=e.canvas.getContext("2d");t.save(),t.resetTransform(),t.clearRect(0,0,t.canvas.width,t.canvas.height),t.drawImage(f.canvas,0,0),t.restore()}return e.MAGIC==n.MAGIC&&null!=n._tint&&(function(e,t){null==f&&(f=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvasM .height),f.canvas.width==e&&f.canvas.height==t||(f.canvas.width=e,f.canvas.height=t)}(e.canvas.width,e.canvas.height),f.drawImage(e.canvas,0,0),e.tinted(n._tint)),o?l?(h||(h=u.width),c||(c=u.height),r.drawImage(u,l,s,h,c,t,i,o,a),void d()):(r.drawImage(u,t,i,o,a),void d()):(e.MAGIC==n.MAGIC||e.width?r.drawImage(u,t,i,e.width,e.height):r.drawImage(u,t,i,e.videoWidth,e.videoHeight),void d())},n.loadPixels=function(){l=r.getImageData(0,0,n.canvas.width,n.canvas.height),n.pixels=l.data},n.updatePixels=function(){null!=M l&&r.putImageData(l,0,0)},n.loadImage=function(e,t){s++;let r=n.createGraphics(100,100),i=r.canvas.getContext("2d"),o=new Image;return o.src=e,o.crossOrigin="Anonymous",o.onload=function(){i.canvas.width=o.width,i.canvas.height=o.height,r.width=o.width,r.height=o.height,i.drawImage(o,0,0),s--,t&&t(r)},r};let v={};function z(e,t){null==u&&(u=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvas.height),u.canvas.width==e&&u.canvas.height==t||(u.canvas.width=e,u.canvas.height=t)}funcM tion V(){let e=r.canvas.width*r.canvas.height*4;null!=d&&e==d.length||(d=new Uint8ClampedArray(e))}function _(e){u.clearRect(0,0,u.canvas.width,u.canvas.height),u.filter=e,u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()}v[n.THRESHOLD]=function(e,t){null==t?t=127.5:t*=255;for(let n=0;n<e.length;n+=4){const r=.2126*e[n]+.7152*e[n+1]+.0722*e[n+2];e[n]=e[n+1]=e[n+2]=r>=t?255:0}},v[n.GRAY]=function(e){for(let t=0;t<e.length;t+=4)M {const n=.2126*e[t]+.7152*e[t+1]+.0722*e[t+2];e[t]=e[t+1]=e[t+2]=n}},v[n.OPAQUE]=function(e){for(let t=0;t<e.length;t+=4)e[t+3]=255},v[n.INVERT]=function(e){for(let t=0;t<e.length;t+=4)e[t]=255-e[t],e[t+1]=255-e[t+1],e[t+2]=255-e[t+2]},v[n.POSTERIZE]=function(e,t){let n=t-1;for(let r=0;r<e.length;r+=4)e[r]=255*(e[r]*t>>8)/n,e[r+1]=255*(e[r+1]*t>>8)/n,e[r+2]=255*(e[r+2]*t>>8)/n},v[n.DILATE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-M 1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.max(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.ERODE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.min(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.BLURM ]=function(e,t){t=t||1,t=Math.floor(t*n._pixelDensity),V(),d.set(e);let i=2*t+1,o=function(e){let n=new Float32Array(e),r=.3*t+.8,i=r*r*2;for(let t=0;t<e;t++){let o=t-e/2,a=Math.exp(-o*o/i)/(2.5066282746*r);n[t]=a}return n}(i),[a,l]=[r.canvas.width,r.canvas.height];for(let n=0;n<l;n++)for(let r=0;r<a;r++){let l=0,s=0,h=0,c=0;for(let e=0;e<i;e++){let i=4*(n*a+Math.min(Math.max(r-t+e,0),a-1));l+=d[i]*o[e],s+=d[i+1]*o[e],h+=d[i+2]*o[e],c+=d[i+3]*o[e]}let u=4*(n*a+r);e[u]=l,e[u+1]=s,e[u+2]=h,e[u+3]=c}d.set(e);for(let nM =0;n<l;n++)for(let r=0;r<a;r++){let s=0,h=0,c=0,u=0;for(let e=0;e<i;e++){let i=4*(Math.min(Math.max(n-t+e,0),l-1)*a+r);s+=d[i]*o[e],h+=d[i+1]*o[e],c+=d[i+2]*o[e],u+=d[i+3]*o[e]}let f=4*(n*a+r);e[f]=s,e[f+1]=h,e[f+2]=c,e[f+3]=u}},n.filter=function(e,t){if(n.HARDWARE_FILTERS&&null!=r.filter)if(z(),e==n.THRESHOLD){null==t&&(t=.5),t=Math.max(t,1e-5),_(`saturate(0%) brightness(${Math.floor(.5/t*100)}%) contrast(1000000%)`)}else if(e==n.GRAY)_("saturate(0%)");else if(e==n.OPAQUE)u.fillStyle="black",u.fillRect(0,0,u.canvaM s.width,u.canvas.height),u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.drawImage(u.canvas,0,0),r.restore();else if(e==n.INVERT)_("invert(100%)");else if(e==n.BLUR)_(`blur(${Math.ceil(t*n._pixelDensity/1)||1}px)`);else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}},n.resize=function(e,t){z(),u.drawImage(r.canvas,0,0),n.width=e,n.height=t,r.canvas.width=e*n._pixM elDensity,r.canvas.height=t*n._pixelDensity,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0,r.canvas.width,r.canvas.height),r.restore()},n.get=function(e,t,i,o){if(null!=e&&null==i){let i=r.getImageData(e,t,1,1).data;return new n.Color(i[0],i[1],i[2],i[3]/255)}e=e||0,t=t||0,i=i||n.width,o=o||n.height;let a=n.createGraphics(i,o);a.pixelDensity(n._pixelDensity);let l=r.getImageData(e*n._pixelDensity,t*n._pixelDensity,i*n._pixelDensity,o*n._pixelDensity);return a.caM nvas.getContext("2d").putImageData(l,0,0),a},n.set=function(e,t,i){if(i.MAGIC==n.MAGIC){let r=n._tint;return n._tint=null,n.image(i,e,t),void(n._tint=r)}let o=4*(t*n._pixelDensity*r.canvas.width+e*n._pixelDensity);n.pixels[o]=i._r,n.pixels[o+1]=i._g,n.pixels[o+2]=i._b,n.pixels[o+3]=255*i._a},n.tinted=function(){let e=n.color(...Array.from(arguments)),t=e._a;e._a=1,z(),u.clearRect(0,0,u.canvas.width,u.canvas.height),u.fillStyle=e,u.fillRect(0,0,u.canvas.width,u.canvas.height),u.globalCompositeOperation="multiply",u.M drawImage(r.canvas,0,0),u.globalCompositeOperation="source-over",r.save(),r.resetTransform();let i=r.globalCompositeOperation;r.globalCompositeOperation="source-in",r.drawImage(u.canvas,0,0),r.globalCompositeOperation=i,r.restore(),u.globalAlpha=t,u.clearRect(0,0,u.canvas.width,u.canvas.height),u.drawImage(r.canvas,0,0),u.globalAlpha=1,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()},n.tint=function(){n._tint=n.color(...Array.from(arguments))},n.noTiM nt=function(){n._tint=null},n.mask=function(e){r.save(),r.resetTransform();let t=r.globalCompositeOperation;r.globalCompositeOperation="destination-in",r.drawImage(e.canvas,0,0),r.globalCompositeOperation=t,r.restore()},n.clearTemporaryBuffers=function(){u=null,f=null,d=null},n.save=function(e,t){e=e||"untitled",t=t||"png";var n=document.createElement("a");n.innerHTML="[Download]",n.addEventListener("click",(function(){this.href=r.canvas.toDataURL(),this.download=e+"."+t}),!1),document.body.appendChild(n),n.click()M ,document.body.removeChild(n)},n.saveCanvas=function(e,t,r){if(e.MAGIC==n.MAGIC){r&&e.save(t,r);let n=t.split(".");return e.save(n.slice(0,-1).join("."),n[n.length-1])}if(t)return n.save(e,t);let i=e.split(".");return n.save(i.slice(0,-1).join("."),i[i.length-1])},n.loadFont=function(e){let t=e.split("/"),n=t[t.length-1].split(".")[0].replace(" ",""),r=`@font-face {\n font-family: '${n}';\n src: url('${e}');\n }`;const i=document.createElement("style");return i.textContent=r,document.head.append(M i),n},n.textFont=function(e){n._style.textFont=e},n.textSize=function(e){n._style.textSize=e,n._style.textLeading=e},n.textLeading=function(e){n._style.textLeading=e},n.textStyle=function(e){n._style.textStyle=e},n.textAlign=function(e,t){r.textAlign=e,t&&(r.textBaseline=t==n.CENTER?"middle":t)},n.text=function(e,t,i,o){if(!e)return;if(e=e.toString(),n._style.noFill&&n._style.noStroke)return;r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`;let a=e.split("\n");for(let e=0;e<a.length;e++)n._M style.noFill||r.fillText(a[e],t,i,o),n._style.noStroke||r.strokeText(a[e],t,i,o),i+=n._style.textLeading},n.textWidth=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).width},n.textAscent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBoundingBoxAscent},n.textDescent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBounM dingBoxDescent};var M,E=4,S=.5,R=function(e){return.5*(1-Math.cos(e*Math.PI))};n.noise=function(e,t,n){if(t=t||0,n=n||0,null==M){M=new Array(4096);for(var r=0;r<4096;r++)M[r]=Math.random()}e<0&&(e=-e),t<0&&(t=-t),n<0&&(n=-n);for(var i,o,a,l,s,h=Math.floor(e),c=Math.floor(t),u=Math.floor(n),f=e-h,d=t-c,x=n-u,g=0,p=.5,m=0;m<E;m++){var b=h+(c<<4)+(u<<8);i=R(f),o=R(d),a=M[4095&b],a+=i*(M[b+1&4095]-a),l=M[b+16&4095],a+=o*((l+=i*(M[b+16+1&4095]-l))-a),l=M[4095&(b+=256)],l+=i*(M[b+1&4095]-l),s=M[b+16&4095],l+=o*((s+=i*(M[M b+16+1&4095]-s))-l),g+=(a+=R(x)*(l-a))*p,p*=S,h<<=1,c<<=1,u<<=1,(f*=2)>=1&&(h++,f--),(d*=2)>=1&&(c++,d--),(x*=2)>=1&&(u++,x--)}return g},n.noiseDetail=function(e,t){e>0&&(E=e),t>0&&(S=t)};const I=function(){let e,t,n=4294967295;return{setSeed(r){e=t=(null==r?Math.random()*n:r)>>>0},getSeed:()=>t,rand:()=>(e^=e<<17,e^=e>>13,((e^=e<<5)>>>0)/n)}};let C=I();C.setSeed(),n.noiseSeed=function(e){let t=null==e?4294967295*Math.random():e;M||(M=new Float32Array(4096));for(var n=0;n<4096;n++)t^=t<<17,t^=t>>13,t^=t<<5,M[n]=(t>M >>0)/4294967295},n.randomSeed=function(e){C.setSeed(e)},n.random=function(e,t){return null==e?C.rand():"number"==typeof e?null!=t?C.rand()*(t-e)+e:C.rand()*e:e[~~(e.length*C.rand())]},n.randomGenerator=function(e){e==n.LCG?C=function(){const e=4294967296;let t,n;return{setSeed(r){n=t=(null==r?Math.random()*e:r)>>>0},getSeed:()=>t,rand:()=>(n=(1664525*n+1013904223)%e)/e}}():e==n.SHR3&&(C=I()),C.setSeed()};var T=new function(){var e,t,n,r=new Array(128),i=new Array(256),o=new Array(128),a=new Array(128),l=new Array(2M 56),s=new Array(256),h=function(){return 4294967296*C.rand()-2147483648},c=function(){return.5+2.328306e-10*(h()<<0)};this.SHR3=h,this.UNI=c,this.RNOR=function(){return n=h(),e=127&n,Math.abs(n)<r[e]?n*o[e]:function(){for(var t,i,l,s,u=3.44262;;){if(t=n*o[e],0==e){do{l=c(),s=c(),t=.2904764*-Math.log(l),i=-Math.log(s)}while(i+i<t*t);return n>0?u+t:-u-t}if(a[e]+c()*(a[e-1]-a[e])<Math.exp(-.5*t*t))return t;if(n=h(),e=127&n,Math.abs(n)<r[e])return n*o[e]}}()},this.REXP=function(){return(t=h()>>>0)<r[e=255&t]?t*l[e]:funM ction(){for(var n;;){if(0==e)return 7.69711-Math.log(c());if(n=t*l[e],s[e]+c()*(s[e-1]-s[e])<Math.exp(-n))return n;if((t=h())<i[e=255&t])return t*l[e]}}()},this.zigset=function(){var e,t,n=2147483648,h=4294967296,c=3.442619855899,u=c,f=.00991256303526217,d=7.697117470131487,x=d,g=.003949659822581572;for(e=f/Math.exp(-.5*c*c),r[0]=Math.floor(c/e*n),r[1]=0,o[0]=e/n,o[127]=c/n,a[0]=1,a[127]=Math.exp(-.5*c*c),t=126;t>=1;t--)c=Math.sqrt(-2*Math.log(f/c+Math.exp(-.5*c*c))),r[t+1]=Math.floor(c/u*n),u=c,a[t]=Math.exp(-.5*cM *c),o[t]=c/n;for(e=g/Math.exp(-d),i[0]=Math.floor(d/e*h),i[1]=0,l[0]=e/h,l[255]=d/h,s[0]=1,s[255]=Math.exp(-d),t=254;t>=1;t--)d=-Math.log(g/d+Math.exp(-d)),i[t+1]=Math.floor(d/x*h),x=d,s[t]=Math.exp(-d),l[t]=d/h}};T.hasInit=!1,n.randomGaussian=function(e,t){return T.hasInit||(T.zigset(),T.hasInit=!0),T.RNOR()*t+e},n.randomExponential=function(){return T.hasInit||(T.zigset(),T.hasInit=!0),T.REXP()},n.print=console.log,n.cursor=function(e,t,r){let i="";e.includes(".")&&(e=`url("${e}")`,i=", auto"),null!=t&&(e+=" "+t+M " "+r),n.canvas.style.cursor=e+i},n.noCursor=function(){n.canvas.style.cursor="none"},n.createCapture=function(e){var t=document.createElement("video");return t.playsinline="playsinline",t.autoplay="autoplay",navigator.mediaDevices.getUserMedia(e).then((function(e){t.srcObject=e})),t.style.position="absolute",t.style.opacity=1e-5,t.style.zIndex=-1e3,document.body.appendChild(t),t};let A=["setup","draw","preload","mouseMoved","mousePressed","mouseReleased","mouseDragged","mouseClicked","keyPressed","keyReleased","keM yTyped","touchStarted","touchEnded"];for(let e of A){let t="_"+e+"Fn";n[t]=function(){},n[t].isPlaceHolder=!0,n[e]?n[t]=n[e]:Object.defineProperty(n,e,{set:function(e){n[t]=e}})}function D(){n._noLoop||(i=null==n._frameRate?requestAnimationFrame(D):setTimeout(D,1e3/n._frameRate)),w(),o=!0,n.push(),n._drawFn(),n.pop(),++n.frameCount}function k(e){const t=n.canvas.getBoundingClientRect(),r=n.canvas.scrollWidth/n.width||1,i=n.canvas.scrollHeight/n.height||1;return{x:(e.clientX-t.left)/r,y:(e.clientY-t.top)/i,id:e.idenM tifier}}function L(){return n._touchStarted.isPlaceHolder&&n._touchMoved.isPlaceHolder&&n._touchEnded.isPlaceHolder}n.noLoop=function(){n._noLoop=!0,i=null},n.loop=function(){n._noLoop=!1,null==i&&D()},n.redraw=function(){D()},n.frameRate=function(e){n._frameRate=e},setTimeout((function(){n._preloadFn(),c=window.performance.now(),function e(){if(s>0)return setTimeout(e,10);n._setupFn(),D()}()}),1),n.canvas.onmousemove=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPM ressed?n._mouseDraggedFn(e):n._mouseMovedFn(e)},n.canvas.onmousedown=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!0,n.mouseButton=[n.LEFT,n.CENTER,n.RIGHT][e.button],n._mousePressedFn(e)},n.canvas.onmouseup=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!1,n._mouseReleasedFn(e)},n.canvas.onclick=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressedM =!0,n._mouseClickedFn(e),n.mouseIsPressed=!1},window.addEventListener("keydown",(function(e){n.keyIsPressed=!0,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!0,n._keyPressedFn(e),1==e.key.length&&n._keyTypedFn(e)})),window.addEventListener("keyup",(function(e){n.keyIsPressed=!1,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!1,n._keyReleasedFn(e)})),n.keyIsDown=function(e){return!!h[e]},n.canvas.ontouchstart=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.moM useY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mousePressedFn(e)||e.preventDefault()),n._touchStartedFn(e)||e.preventDefault()},n.canvas.ontouchmove=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mouseDraggedFn(e)||e.preventDefault()),n._touchMovedFn(e)||e.preventDefault()},n.canvas.ontouchend=n.canvas.ontouchcancel=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.M mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!1,n._mouseReleasedFn(e)||e.preventDefault()),n._touchEndedFn(e)||e.preventDefault()},n.hasSensorPermission=!window.DeviceOrientationEvent&&!window.DeviceMotionEvent||!(DeviceOrientationEvent.requestPermission||DeviceMotionEvent.requestPermission),n.requestSensorPermissions=function(){DeviceOrientationEvent.requestPermission&&DeviceOrientationEvent.requestPermission().then((e=>{"granted"==e&&DeviceMotionEvent.requestPermissioM n&&DeviceMotionEvent.requestPermission().then((e=>{"granted"==e&&(n.hasSensorPermission=!0)})).catch(alert)})).catch(alert)},window.ondeviceorientation=function(e){n.pRotationX=n.rotationX,n.pRotationY=n.rotationY,n.pRotationZ=n.rotationZ,n.pRelRotationX=n.relRotationX,n.pRelRotationY=n.relRotationY,n.pRelRotationZ=n.relRotationZ,n.rotationX=e.beta*(Math.PI/180),n.rotationY=e.gamma*(Math.PI/180),n.rotationZ=e.alpha*(Math.PI/180),n.relRotationX=[-n.rotationY,-n.rotationX,n.rotationY][1+~~(window.orientation/90)],n.rM elRotationY=[-n.rotationX,n.rotationY,n.rotationX][1+~~(window.orientation/90)],n.relRotationZ=n.rotationZ},window.ondevicemotion=function(e){if(n.pAccelerationX=n.accelerationX,n.pAccelerationY=n.accelerationY,n.pAccelerationZ=n.accelerationZ,!e.acceleration){let t=((e,t)=>[(e[0]*t[0]+e[1]*t[1]+e[2]*t[2]+e[3])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[4]*t[0]+e[5]*t[1]+e[6]*t[2]+e[7])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[8]*t[0]+e[9]*t[1]+e[10]*t[2]+e[11])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15])])(((e,t)M =>[e[0]*t[0]+e[1]*t[4]+e[2]*t[8]+e[3]*t[12],e[0]*t[1]+e[1]*t[5]+e[2]*t[9]+e[3]*t[13],e[0]*t[2]+e[1]*t[6]+e[2]*t[10]+e[3]*t[14],e[0]*t[3]+e[1]*t[7]+e[2]*t[11]+e[3]*t[15],e[4]*t[0]+e[5]*t[4]+e[6]*t[8]+e[7]*t[12],e[4]*t[1]+e[5]*t[5]+e[6]*t[9]+e[7]*t[13],e[4]*t[2]+e[5]*t[6]+e[6]*t[10]+e[7]*t[14],e[4]*t[3]+e[5]*t[7]+e[6]*t[11]+e[7]*t[15],e[8]*t[0]+e[9]*t[4]+e[10]*t[8]+e[11]*t[12],e[8]*t[1]+e[9]*t[5]+e[10]*t[9]+e[11]*t[13],e[8]*t[2]+e[9]*t[6]+e[10]*t[10]+e[11]*t[14],e[8]*t[3]+e[9]*t[7]+e[10]*t[11]+e[11]*t[15],e[12]*t[0]+M e[13]*t[4]+e[14]*t[8]+e[15]*t[12],e[12]*t[1]+e[13]*t[5]+e[14]*t[9]+e[15]*t[13],e[12]*t[2]+e[13]*t[6]+e[14]*t[10]+e[15]*t[14],e[12]*t[3]+e[13]*t[7]+e[14]*t[11]+e[15]*t[15]])((e=>[Math.cos(e),0,Math.sin(e),0,0,1,0,0,-Math.sin(e),0,Math.cos(e),0,0,0,0,1])(n.rotationY),(e=>[1,0,0,0,0,Math.cos(e),-Math.sin(e),0,0,Math.sin(e),Math.cos(e),0,0,0,0,1])(n.rotationX)),[0,0,-9.80665]);n.accelerationX=e.accelerationIncludingGravity.x+t[0],n.accelerationY=e.accelerationIncludingGravity.y+t[1],n.accelerationZ=e.accelerationIncludM ingGravity.z-t[2]}},n.year=function(){return(new Date).getFullYear()},n.day=function(){return(new Date).getDay()},n.hour=function(){return(new Date).getHours()},n.minute=function(){return(new Date).getMinutes()},n.second=function(){return(new Date).getSeconds()},n.millis=function(){return window.performance.now()-c}}(e)}"object"==typeof exports&&"undefined"!=typeof module&&(module.exports=e);const t="https://ancient-crimson-rain.btc.discover.quiknode.pro/c268fb026303ae8443f785200f2ea4b82f0082dd";function n(e){P(e)?M localStorage.removeItem("blocksApiEndpoint"):localStorage.blocksApiEndpoint=e}function r(){return localStorage.blocksApiEndpoint||t}function i(e){P(e)?localStorage.removeItem("modelInscriptionEndpoint"):localStorage.modelInscriptionEndpoint=e}function o(){return localStorage.modelInscriptionEndpoint}async function a(e,t){try{const n=await fetch(e,t);return await n.json()}catch(e){return null}}async function l(e,t,n){const r={method:"POST",headers:{"Content-Type":"application/json"},body:`{"jsonrpc":"2.0","id":1,"meM thod":"${t}","params":${`[${n.join(sep=",")}]`}}`};return(await a(e,r))?.result}async function s(e){const n={avgfee:10,time:Date.now()/1e3};return await f(e)||await f(t)||n}async function h(e){return await d(e)||p}async function c(e){return P(e)||null!=await f(e)}async function u(e){return P(e)||null!=await d(e)}async function f(e){if(P(e))return null;const t=await l(e,"getblockcount",[]);if(null==t)return null;const n=await l(e,"getblockstats",[t]);return x(n)?n:null}async function d(e){if(P(e))return null;const tM =await a(e,{});return g(t)?t:null}function x(e){return"number"==typeof e?.time&&"number"==typeof e?.avgfee}function g(e){if(null==e)return!1;const{classes_name:t,training_traits:n,layers_config:r,weight_b64:i}=e;if(!Array.isArray(t))return!1;if(null==n)return!1;try{j(r,i)}catch(e){return!1}return!0}const p={"model_name": "pfp_classifier_342", "layers_config": {"config": {"layers": [{"class_name": "InputLayer", "config": {"batch_input_shape": [null, 28, 28, 3]}}, {"class_name": "Rescaling", "config": {"scale": 0.007M 84313725490196, "offset": -1}}, {"class_name": "Flatten"}, {"class_name": "Dense", "config": {"units": 3, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 7, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 4, "activation": "linear"}}]}}, "weight_b64": "pNkmPWWmqbtHtUY8nbuTPcChVz1yTq082vocPXcRPD3gQEW9Lp85PcqwBj1aomq9faezPMvjVbzBNRe9x1TRPILVjzyJaK+8dMQHvbb2gzyQ1Z+8qjdLPBpILz1okMy8UMPXO9z8yjxA2K45y7y8PBEHirxbzxa9q5aWPbcXPz3W4SM5WXMCvI3htT1aWVI88sAZvGdiIj32zx294YkyPfjDHz3/WLi88MCsM 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 PZJWNj07sUo9ufrXO3sYcz10FRy9JI8CPXGRjz1kZFg8Ici0PFzUhj1uOyi8L2h1vK5P5jw0v/28ZpUSvWT/Az3I/CK9gOFeO3AmpT0aaVs8zJ+lPN+IVD1/zlG9Zr8iPXeCozyuml45egWhvNPVQz2FvDi8C2MKOwy4ZDuNIBY7u71ovcmhWbs857I8KGsuPbDBQD0KSnw8Ju/0vJU2T7wMVFu93PuLPGqDhbwbVzE9pI54PKYvCL0LD2E88m+DvKU+Pj1GVxy9cHkBvd45zLs69OU8ryOEvDK/x7trF7g7VJ8mvefpCb10LlA8VtBCPRbHRD30xmc5LuELPWDguLxAo3E8HggivfUyN71k++e8rJS0PH8eubz/cpY8fcEEPM05iTjmc9m7qQWBunX0EL3Gruk8RYOUPIe/nDxGe5W8nx8KvFYdA70Wb9c7uC/VvJ/vfL01+GM8LRylvDijHbxSxiC9sxuqPHymDj3E29I8ZovDvKCSRz2pB368ciQmPGj/hjqkM 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 4lC8exobPaau1Ly9rgw9OjF7PaA9cbxAm3+8UAcDvCvgtDxrxsM8FGW2PHJsvDzVCuW8ehq7PW7WpbtDWqm8sTLgPNcSNz3lC++81pCoPSxIAj0Pfx+9XbC7PeRW1TxM1LW96b80PbPCxbzIi+6879PpPaCVhryRu/Y8MtiWPRIAbD0XHHK9KoRjPc3KkLxyPck8dzc6PC0P47uCblc9ITePPWVZVj2uW9y7TQaVvHE1WztFCEY9qMSZPeOitLy8I4U9MQbvu0uf0DxxZ4I9PD8pvdNQmj2RnmW8ZislPS0LiD0rpf08LOsEPcs5XD1YDIa8w/mgO1mQrz0Fdjy8QSKpPe4dwbxQstw7KJHvOmjDGz2OZWG9MvM/vbEAyDx9DHk8hAWHPFqCZjx3lGg956NsveIo/rxsx0U9owqWPGWHorufwlM9qLapPF4VML3Sybk8JLP6uqJ11Duyh9A8GyY8PNmopTvybdE9A0UMPEMydL25yCK9Dg8EvUruZL1ruF28I+EeM 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 Pb5B6rpXvpg81ucUvC1ouz23A4e8Hu1VPRkHYT0xUA88x4NqvHa1pLz4MS67GZkBvbCNtjwSCsC9jSJLPeiVILxbGqi8q9whvSdnQ7xlA968PNHXPCp4pTuuwkU9njcevcJUcr3Sv4k8IwkXu5vYMr1WhzW97MAgPcfBsr2OL5M9ulnvuxyWEL1ptU891HYyvbKfa70MZZk9Ex0DPK2vUb3ZXMg9xYRvvEx6yL1o+W07lOzHPEug+Lz0PQu9otruPCLhB7wD4bq8u4f5vEwwk72fga28nAKBvbsuRL2Ozyq95j+/uXx2fjtxDY29/RWXvYEJhL2B0Bw8TWqkvXwE47yDOR28UsZJPGS4Nb0XP869miyTPBt8yL3DCaq8RFEYvRrfDzxYBTS9SdHJvHQck73ZG5085V8ZPW7/vL1TrgS8ITCgO1ivDLyRHSk9UBnJPEegLb2foIc9pce5PJ1T8r26MMM8SmqAvcjLLL0GsKc9aYLmuhYNiT2A80k95G7fPJbOK711M 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 vAyLmjyCKqO94C7AOv8zazxhMay9xEuTPE/qzTz002G9c2DJOnPdhr2lGew8zr//PDMa1r27r6K88y+5PJzNIb3If409rHKUuko3gr3Dx0m9wZnoO64gLjvaP4E8DaXnPJAMnb3s5tk7RXXHvFQ9rDyhPZy9HEsxvQn7sbxOEvm9xE6rvATQSjwlMwe+Fk5MvS/fyLyvAGY8FQsYvTBMOjtM1Ci9G7ZrvVlX2LwthZ29Wt5OPLi2BL733zM95ekAvGCrer2E3/M9Bv4QPUbduLxkMlM9AQRqvPQzBr1imfC9A2Q+vWXuBz0LMd+9Mob/uh/SMT1r+dW9AmZvPE0En70rqUk84385vUiib71jeu09gc8wvT0HoDtHh1094uftu1tFdL3unKo88BB1vYZ+VDzkv7u8yza1vEDPJ72SFME9YdG0PPFFsTwyDWa6L5mCPZPNxz3OpEK9UjeIuzprVL2bx289KryjPYvrxjzmbSU8DfIHPq1ptD3jmNW9JuALPoy9iD0jM 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 sga9JOKKvAlRXL2f7Fe97rIqPVm+wb2NoZE9TWFbPdrStb3focU9SbQbPY7Sk73VTVQ9DG0OvVsRIz1xIhG+bxllvScZhj1O7NK9pf2qve6Sgz3nU9+9AUSLPQTrwb3r6bI9JuhvPch0Vr0badw9rfc8PSL9uL3T8ro90grVvPPAaL3ppNm8WkI2vRjr4rtTx/i5IRbnvcyOgzsmn9881vlYvA2LfT2siWy8RWOAPatQCj2s52Q7+9kWPQXy3TwVJlc8+1uVPZLJCz4tFba9bBetPQUraj4v6Cu+NUa3PdJtBT7QKQ6+wXGYveZbHr6YnaE9ZMEPvkzftTzdzwo9uc2bvZJNjb2jqcs6qMMXvld0PL7HuV0+UYWJvh0HRr4I740+u85RvhaSA75jrFU+nRJsvbleHL6cZ7I+2BNNvkEeG76LMMI+vV+bvq6qcjypPUA+a8nxOwpHIj0eMvQ9MXn3vYEmYb1G3XA+q1x5vgOHzTwU9vk9TcRLPXBVQj1XWCQ8pJLHM vJTlEDz9boQ9NGAovAJtJj1baNE8AYZfPj4ewD0EO+W97HB0Pv5y0z2pzv+96OF1PmLtwTuDQMu9ZPgavdO8ET2sC8O9SA8rPMeKoD3QtI69aDx1PUgijj2sjcW9IPpMvvouTrzyUv49tIU7vlWt0LxaQUo+7DBMvqRih70sxSQ+4aLhPSoAGr7Pf509qcS0PLuQI76NOkw9Kg6evERCDL488RA90DnnvFJc5z0HIBK+ww6tu7XtGT07UBa9nJpRPYg/9DyyuQ+9wxrovGUUWj2gUJu8jS4Evcfamj24zHS9YVNYPd9ypT2uSHG93DQ2vWWbijznS309Pf0WvWLExTrI5c09WFX0u7Pvkjt6eH89ctV5PIHknL2KIuw9rJSsvHJUnL0cfsY8ZTqgvIJ2oL0e0BI97W8FPMndUTy/4xu7ZY3/vO6Wqz1mZRM5xaqovL5CsTwKr7S8RnIDvRNlgjv9JQm9jx0mPTz5fjxhE4k9H6e7u+JwGL2qQYA8DGwNPSKojDwCM 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 PD7CVz1OYcy8DK93vNWvWDxa8iY9hNkROnIzzjxW8yu9jkNwvDYotzyIIfs8F4aDPAQK0zyEvFw8pZ+uvCMTkLymOFY9wP+Xuxg8LL1oHL895qxUvb2gV722DIs92N7pvYnkOD1RFGg9VrQPvncCFj5AbI09WFLPvR9M2zwQMz+8uNNDvRl0rLy2Vde8QW9TvSnKijxdEmi9rbJYPeTpxLy5OKc8xoQmPAMnPjwNhHa9OjuAvXGaqb3hMA49E4lzPei0HL34mvA8zia7vNcdNLy3p8K9tWnqu5zfFbsjm3u9UY+evamb9by4Ycc8KT/7vDdEhjvVY/i9v40qPLEuCz0ijVK9rI2NvX78Aj074rW9m0Mzvdgyk70PxIg8N/MRvHatBD0NfL671PwovazMwjwYA029tijeuxH7hTrAIKq8KkHzPDEckbyu8Hc9a0WuPbZdqLt1zU+9/5yyPMVZnz1Lx4G9jjXpvJvpiT2WO7C88s70uxsvtD0aP5q9iKWuPK4klr2MM 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 PaQ9WbOkvUf/ub0tu4s96GyVvdXA9bxxndA9aPCCvd7wCD2mEws9hh1rvVbsC7sVsFM9tSvIvQjygj0adak8S8YkvbZDCryb0Ok8rs70vD+/MbzUqJU8HEG9vQRi4jvgq1s9dXW2vKd7FL3BZ3C6DYeKvU6tx7zP7dq8Q7rYOW/tWb2drZs7wGyLvA9bZL2HVUm97LCEvczW3rwjpoq91xZ/vVy9MjqMxhu9r780vYh8BL0ioJ+9zRh6vacAcb3a7aC9hyBwvXPdrr0aFNy9mKuzvDQfer1iBoS9d8A4PLm3jb0U0ey8jTdNvRhfPr0L2ym9D7gMPhjUpb1m+eq8sQaQPerFsb26CYm84h7kPa+D671Z/UI9qdA9PZHah73FvGQ9azm3PdlmdDyCoWe9IP+XPVqlGL1UMpi9deOtvaiRkz3YNTc96dRVvUg4mT2Uyqm9dOX6uhHESD2jb668ZEIxu2y18D1iF9C9CvksPSG4Lj7/QBy963YQPuuzpD0NkZs8TiFEM 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 PHhUq7xSzWc8RO+HvOmQor1gxTk9mzSfOxU5O71Ye9E9RcdUvDT0Dr13jzw95duBPeLHPjy2Qrc9Ll3JvLTJjr1tFCc+4jTIPDxVe73JTOA8cAxFPP7Xw7r4VRA6dKaLvUhjjL0FK9M75uAYPdu8tr3mYgO8vRktujgkF76E0ZA8Ya7PO9nf173r38w8opG0PVtzZL1W7NM8HdWePEiaRL1S8lC8iVPovKcZtL2vMAE9bgAnvV0YM73/04e9ujGtvRuIjTzQcGO9tX+ZvTT7Fr3GJNO97U7bOzJOdLs8gTm9aSa+vatJQ7u2WMe9jxAQvaROQL1Z0nC9jzJ1vPy+lTxz2oa93YUgvrNuPbzr+aS9vfPjvTrSer2Gsb68DLS+vU/VCD0lmaC9ES4AvjYOOr1Cdza9q0dnvWVcA72mKkC9NxVPvaVg5LgcpPS8vG4EvsYCYTzroMa9LrPKvbO7hL1fHTI73F1zvdhwgboqXCI9avpCvYtGGL2ZRdE8j7dzvSRUtL32M 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 PerjNj9NbsM+sxyCPyyNPb8S4WA/yBmFvuILRT/CEdi9GG1OPc9J8z0kIYw/3fsAPqA+4b0qzra+9nIGPqWVDD8+Qtc9ydsaP4SDQb4AAAAAz/6ZPo0x4L5e85I7jWgQv5GmEz/gPNq9bO5pPtOUJr/QYsE98RAaP4aeeD7QcKS+MMdzvQC1qLsA1Vs7EiX0PvkZrL7Q90A/k0WJv8GwAz96Q2q/DH0jv+rIXT+X4s890EQoP2hYaT4HHe0+EZnnPkwR0L6mLc2+a8KBPgFd6j6t8lQ/oH46Pz26Nr9Jfki/", "training_traits": {"structure_gen": "Random", "n_layers": 2, "max_nodes": 7, "activation_func": "ReLU", "epoch_num": 5}, "classes_name": ["Cryptoadz", "Cryptopunks", "Moonbirds", "Nouns"]},m=25,b=50,y=59+11/12,w=59+1M 1.5/12,v=60;function z(e,t){const n=Math.log(1-t)/Math.log(1-e);return e=>1-Math.pow(1-e,n)}class V{constructor(e,t,n){const{model:r,inputDim:i}=j(t,n);this.model=r,this.inputDim=i,this.iteration=0,this.stage=0;const o=new Date(parseInt(e.birthYear),0,1).getTime(),a=new Date(parseInt(e.birthYear)+1,0,1).getTime();this.birthDate=new Date(Math.floor((o+a)/2));const l=zr.filter((t=>t[0]==e.lifeCycle))[0][2];this.growSpeed=365/l,this.cycleLength=60*l*24*3600*1e3,this.growthFunc=z(.4,.8)}updateAge(e){const t=(e.getTime(M )-this.birthDate.getTime())/31536e6*this.growSpeed;this.iteration=Math.floor(t/60);const n=t-60*this.iteration;let r;this.age=n;let i,o=0;if(n<25){let e=map(n,0,25,0,1);o=this.growthFunc(e),r=(25-n)/60,this.stage=1,this.stageRatio=map(n,0,25,0,1)}else n<50?(o=1,r=(50-n)/60,this.stage=2,this.stageRatio=map(n,25,50,0,1)):n<y?(o=map(n,50,y,1,0),r=(y-n)/60,this.stage=3,this.stageRatio=map(n,50,y,0,1)):n<w?(o=0,r=(w-n)/60,this.stage=4,this.stageRatio=map(n,y,w,0,1)):n<60&&(o=0,r=(60-n)/60,this.stage=5,this.stageRatio=maM p(n,w,60,0,1));n<50?i=map(n,0,50,0,780/880):n<w?i=map(n,50,w,780/880,800/880):n<60&&(i=map(n,w,60,800/880,1)),this.nextStateTimestamp=Math.round(e.getTime()+this.cycleLength*r),this.statePercentage=round(100*i);let a=(25-n)/60;a<0&&(a+=1),this.nextStableTimestamp=Math.round(e.getTime()+this.cycleLength*a),this.growth=o,this.model.updateNeurons(o,this.iteration)}getBrainStatus(){return{totalNeurons:this.model.getTotalNeurons(),neuronsLife:this.model.getNeuronsLife(),stage:this.stage,inputDim:this.inputDim,stageRatioM :this.stageRatio,age:this.age,growth:this.growth,nextStateTimestamp:this.nextStateTimestamp,nextStableTimestamp:this.nextStableTimestamp,rebirthCount:max(this.iteration,0),statePercentage:this.statePercentage}}classifyImage(e){const t=new G(e,1,e.length);return this.model.forward(t).mat[0]}}class M{constructor(e,t,n,r,i){this.p=e,this.v=t,this.size=n,this.shape=i,this.col=r}getRadius(){return 1==Oe?1*this.size/2:2==Oe?7*this.size/16:3==Oe||4==Oe?4*this.size/7:0}update(){this.p.add(this.v)}draw(e,t,n,r){const i=thisM .p.x*r,o=this.p.y*r,a=this.size*r,{col:l,shape:s}=this;let h,c;1==n?h=c=l:2==n?(h=dr(t,1),c=l):(h=dr(t,0),c=dr(l,1));e.stroke(dr(c,map(1,0,1,.25,1))),e.fill(dr(h,map(1,0,1,.15,1))),3==n&&e.fill(dr(h,0)),1==s?e.ellipse(i,o,a,a):2==s?e.rect(i,o,7*a/8,7*a/8):3==s&&(e.beginShape(),e.vertex(i-4*a/7,o),e.vertex(i,o-4*a/7),e.vertex(i+4*a/7,o),e.vertex(i,o+4*a/7),e.endShape(CLOSE))}}class E{constructor(e,t,n,r,i,o,a){this.center=e,this.len=t,this.angle=n,this.v=r,this.angV=i,this.c1=o,this.c2=a}getEndpoints(){const e=creatM eVector(this.len/2*cos(this.angle),this.len/2*sin(this.angle));return[Vector.add(this.center,e),Vector.sub(this.center,e)]}update(){this.center.add(this.v),this.angle+=this.angV}draw(e,t){const[n,r]=this.getEndpoints(),i=n.x*t,o=n.y*t,a=r.x*t,l=r.y*t,s=this.c1,h=this.c2;var c=e.drawingContext.createLinearGradient(i,o,a,l);c.addColorStop(0,s),c.addColorStop(1,h),e.drawingContext.strokeStyle=c,e.drawingContext.globalAlpha=1,e.line(i,o,a,l),e.drawingContext.globalAlpha=1}}function S(e,t){const n=random(TAU),r=random(eM ,t);return createVector(r*cos(n),r*sin(n))}class R{constructor(e,t,n,r,i){this.wall=n,this.maxR=i;const o=t.length;this.nodes=[];for(let a=0;a<o;++a){const o=[],l=.25*t[a];for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),l=S(.02*i,.05*i),s=random(10,25)*i;o.push(new M(t,l,s,e[a],r))}this.nodes.push(o)}const a=A(e);a.unshift(e[0]),a.push(e[e.length-1]),this.lines=[];for(let e=0;e<=o;++e){const r=[],l=(0==e?1:t[e-1])*(e==o?1:t[e])*1.5;for(let t=0;t<l;++t){const t=createVectM or(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),o=random(5*i,10*i),l=random(TAU),s=S(.02*i,.05*i),h=random(2e-4,.001);r.push(new E(t,o,l,s,h,a[e],a[e+1]))}this.lines.push(r)}}reflectNode(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,{p:o,v:a}=e,l=e.getRadius();(o.x-l<t&&a.x<0||o.x+l>r&&a.x>0)&&(a.x=-a.x),(o.y-l<n&&a.y<0||o.y+l>i&&a.y>0)&&(a.y=-a.y)}reflectLine(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,[o,a]=e.getEndpoints(),l=e.v;(min(o.x,a.x)<t&&l.x<0||max(o.x,a.x)>r&&l.x>0)&&(l.x=-l.x),(M min(o.y,a.y)<n&&l.y<0||max(o.y,a.y)>i&&l.y>0)&&(l.y=-l.y)}update(){for(const e of this.lines)for(const t of e)t.update(),this.reflectLine(t);for(const e of this.nodes)for(const t of e)t.update(),this.reflectNode(t)}draw(e,t,n,r,i){const o=i/this.maxR;for(const t of this.lines){const n=t.length*r;for(let r=0;r<n;++r)t[r].draw(e,o)}for(const i of this.nodes){const a=i.length*r;for(let r=0;r<a;++r)i[r].draw(e,t,n,o)}}}function I(e,t){re(e),e.fill(0),e.rect(0,0,500,500),ie(e),e.noStroke(),e.fill(dr(cr("#000000"),.5)),eM .push(),e.translate(250,250),e.scale(t),e.translate(-250,-250),e.beginShape(),e.vertex(235.2,24.9),e.bezierVertex(215,24.6,185,11.4,164.8,11),e.bezierVertex(147.2,10.7,129.3,10.4,112.2,14.7),e.bezierVertex(95.1,19,78.5,28.5,69.6,43.8),e.bezierVertex(57.699,64.199,61.599,90.199,70.199,112.2),e.bezierVertex(78.799,134.2,91.6,154.6,97.199,177.5),e.bezierVertex(102.499,199.2,100.899,222.5,92.799,243.2),e.bezierVertex(83,268,64.6,288.3,48.9,310),e.bezierVertex(33.2,331.7,24.5,337.5,26.599,364.1),e.bezierVertex(28.2,384.M 1,61.399,404.2,75.7,418.3),e.bezierVertex(90,432.4,73.7,488.2,91.9,496.7),e.bezierVertex(124.2,511.6,159,472.5,194.3,468.1),e.bezierVertex(211.6,465.9,267.4,501.5,283.9,495.9),e.bezierVertex(340.7,476.7,298.599,428.9,355.4,409.7),e.bezierVertex(370.799,404.5,454.5,407.6,464.4,394.8),e.bezierVertex(478.599,376.3,474.7,349.3,464.299,328.4),e.bezierVertex(453.9,307.5,438.099,289.5,428.699,268.2),e.bezierVertex(412,230,419,182.6,446.1,150.9),e.bezierVertex(449.7,146.7,453.6,142.7,455.8,137.6),e.bezierVertex(459.4,129.2M 99,457.5,119.6,454.8,111),e.bezierVertex(443.2,73.4,417.3,40.4,383.6,20.299),e.bezierVertex(358.1,5,343.2,-.4,313.5,0),e.bezierVertex(287.5,.4,261.6,25.4,235.2,24.9),e.endShape(),e.pop()}function C(e,t,n,r,i,o){let a,l,s;re(t),t.fill(0),t.rect(0,0,500,500),ie(t),t.noStroke(),t.fill(dr(n,.5)),1==i?(l=0,s=25,a=map(o,0,25,500,0)):a=0,t.rect(0,a,500,500),e.noStroke(),e.fill(r),e.rect(0,0,500,500),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,44M 2.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezM ierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,M 22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.M 5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),e.fill(n),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,M 148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezM ierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezM ierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),re(e),e.fill(r),e.beginShape(),e.vertex(184.3,473.2),e.bezierVertex(164,473.2,144.7,462.099,134,444.3),e.bM ezierVertex(131.7,440.5,129.1,438.5,125,437.1),e.bezierVertex(97.3,428.1,80.5,400.6,85.2,371.8),e.bezierVertex(86.3,365.1,85.8,364.1,79.9,361.2),e.bezierVertex(57.2,349.8,46.2,323.3,54.3,299.7),e.bezierVertex(54.7,298.599,55.1,297.7,55.5,296.9),e.bezierVertex(55.6,296.599,55.8,296.4,55.9,296.099),e.vertex(57.9,291.499),e.vertex(62.5,293.599),e.bezierVertex(64.9,294.7,67.3,295.799,69.5,296.9),e.bezierVertex(74.5,299.299,79.1,301.599,83.9,303.099),e.bezierVertex(89.8,304.9,96.5,305.499,102.7,305.9),e.bezierVertex(102M .8,305.9,102.9,305.9,103,305.9),e.bezierVertex(106.6,305.9,108.9,302.799,109,299.799),e.bezierVertex(109.1,296.199,106.6,293.4,102.7,292.799),e.bezierVertex(101.3,292.599,99.9,292.4,98.4,292.299),e.bezierVertex(94.3,291.799,90.1,291.299,86,289.9),e.bezierVertex(68.9,284,56.5,270.2,52.7,252.799),e.bezierVertex(48.9,235.499,54.5,217.7,67.6,205.299),e.bezierVertex(71.9,201.299,72.7,198.1,70.8,192.399),e.bezierVertex(64.2,172.2,68.8,153.99,84.2,139.599),e.bezierVertex(94.2,130.199,105.5,125.399,117.8,125.399),e.bezierVM ertex(124.3,125.399,131.1,126.799,137.8,129.599),e.bezierVertex(157,137.399,167.9,152.799,169.4,173.99),e.vertex(169.4,174.399),e.bezierVertex(169.5,175.899,169.6,177.2,169.9,178.299),e.bezierVertex(170.7,181.2,173.2,183.2,176.1,183.2),e.bezierVertex(176.299,183.2,176.5,183.2,176.7,183.2),e.bezierVertex(180.1,182.899,182.6,180.299,182.7,177),e.bezierVertex(183.1,162,178.299,148.2,168.399,136.1),e.bezierVertex(158.2,123.5,144.899,115.8,128.799,113.199),e.bezierVertex(123.499,112.299,120.399,109.799,118.899,104.99),eM .bezierVertex(113.899,89.699,120.699,72.299,134.899,64.499),e.bezierVertex(139.99,61.699,145.799,60.199,151.7,60.199),e.bezierVertex(162.2,60.199,171.899,64.799,178.1,72.699),e.bezierVertex(179.6,74.6,180.799,76.6,181.9,78.499),e.vertex(182.2,79.099),e.bezierVertex(183.2,80.699,185.2,83.299,188.4,83.299),e.bezierVertex(189.5,83.299,190.6,82.99,191.7,82.399),e.bezierVertex(195.1,80.599,196,76.99,194,72.799),e.bezierVertex(190.1,64.799,184.1,58.499,175.6,53.299),e.bezierVertex(174.6,52.699,173.7,52.099,172.5,51.499),M e.vertex(170.5,50.299),e.vertex(163,45.899),e.vertex(170.5,41.599),e.bezierVertex(182,34.99,193.1,30.799,204.4,28.599),e.bezierVertex(208.6,27.799,212.9,27.399,217.2,27.399),e.bezierVertex(217.6,27.399,217.9,27.399,218.3,27.399),e.bezierVertex(231.4,27.599,242.7,38.199,243,50.599),e.bezierVertex(243.4,64.899,243.3,78.99,243.2,93.799),e.bezierVertex(243.2,99.799,243.1,105.899,243.1,112.099),e.vertex(243.1,119.199),e.vertex(236.4,116.799),e.bezierVertex(235.7,116.499,235,116.299,234.4,115.99),e.bezierVertex(233.4,115M .599,232.6,115.299,232,115.199),e.bezierVertex(230.6,114.899,229.2,114.599,227.8,114.299),e.bezierVertex(223.8,113.499,220.1,112.699,216.4,112.499),e.vertex(216.2,112.499),e.bezierVertex(212.5,112.499,210.7,115.599,210.6,118.599),e.bezierVertex(210.4,122.399,212.7,125.099,216.4,125.399),e.bezierVertex(230.1,126.399,238.9,133.099,242.3,145.199),e.bezierVertex(243.2,148.399,243.2,151.599,243.2,154.499),e.vertex(243.2,155.099),e.bezierVertex(243.2,254.199,243.2,330,243.2,400.599),e.bezierVertex(243.2,401.99,243.2,403.M 4,243.2,404.9),e.bezierVertex(243.3,411.099,243.3,417.599,242.3,423.9),e.bezierVertex(238.1,449.2,219.6,467.799,194,472.5),e.bezierVertex(190.9,472.9,187.6,473.2,184.3,473.2),e.endShape(),e.beginShape(),e.vertex(315.8,473.1),e.bezierVertex(309.3,473.1,302.8,472,296.5,469.9),e.bezierVertex(270.4,461,253.8,434.9,257.1,407.9),e.bezierVertex(260,384,273.8,366.8,297,358.3),e.bezierVertex(297.7,358.1,298.3,357.8,299,357.6),e.bezierVertex(299.8,357.3,300.6,357.1,301.2,356.8),e.bezierVertex(304.3,355.4,306,351.8,304.9,348.M 7),e.bezierVertex(304,345.9,301.7,344.2,299,344.2),e.bezierVertex(298.6,344.2,298.1,344.2,297.6,344.3),e.bezierVertex(288.1,346.3,279,350.9,269.7,358.3),e.bezierVertex(268.9,358.9,268.1,359.6,267.2,360.4),e.vertex(265.5,361.8),e.vertex(258.5,367.6),e.vertex(257.4,358.6),e.bezierVertex(257.3,358,257.3,357.5,257.2,357.1),e.bezierVertex(257,356,256.9,354.9,256.9,353.7),e.bezierVertex(256.9,334.8,256.9,316,256.9,297.1),e.bezierVertex(256.9,260.3,256.9,222.3,256.8,185),e.bezierVertex(256.8,170.7,268.3,158.8,282.5,158.4)M ,e.bezierVertex(284.8,158.3,286.7,157.6,287.9,156.2),e.bezierVertex(289.099,154.9,289.599,153.2,289.5,151.3),e.bezierVertex(289.3,147.5,286.7,145.1,282.7,145.1),e.bezierVertex(282.5,145.1,282.2,145.1,282,145.1),e.bezierVertex(278.8,145.3,275.5,146.1,272,146.9),e.bezierVertex(270.9,147.2,269.8,147.4,268.6,147.7),e.bezierVertex(267.9,147.9,267,148.2,265.8,148.7),e.bezierVertex(265.1,149,264.4,149.3,263.5,149.6),e.vertex(256.8,152),e.vertex(256.8,114.6),e.bezierVertex(256.8,95,256.8,75.4,256.8,55.9),e.bezierVertex(256M .8,38,267.2,27.3,284.6,27.3),e.bezierVertex(285.3,27.3,285.9,27.3,286.6,27.3),e.bezierVertex(299,27.9,318.7,34.5,329.6,41.9),e.vertex(336.1,46.3),e.vertex(324.4,53.3),e.bezierVertex(316.2,58.2,310.2,64.6,306,72.9),e.bezierVertex(304.2,76.4,305.1,78.5,306.1,80),e.bezierVertex(307.4,81.9,309.4,83,311.6,83),e.bezierVertex(313.7,83,315.7,81.9,317.1,80.1),e.bezierVertex(317.4,79.7,317.8,79,318.1,78.4),e.bezierVertex(318.4,77.9,318.7,77.3,319,76.8),e.bezierVertex(325.3,66.2,336.3,59.9,348.5,59.9),e.bezierVertex(353.2,59.M 9,357.8,60.8,362.1,62.7),e.bezierVertex(377.6,69.3,386,86.7,381.7,103.2),e.bezierVertex(380.7,107.1,378.5,111.8,371.1,113.1),e.bezierVertex(342.7,118.1,322.2,139.1,317.8,167.8),e.bezierVertex(317.4,170.3,317.3,173.2,317.4,176.5),e.bezierVertex(317.5,180,320.1,182.8,323.5,183),e.bezierVertex(323.6,183,323.8,183,323.9,183),e.bezierVertex(327.1,183,329.8,180.6,330.3,177.2),e.bezierVertex(330.6,175.7,330.7,174,330.9,172.3),e.bezierVertex(331.1,169.8,331.4,167.3,332,164.7),e.bezierVertex(337.3,141.9,357.7,125.4,380.7,12M 5.4),e.bezierVertex(382.5,125.4,384.3,125.5,386.1,125.7),e.bezierVertex(412.8,128.9,432.6,150.9,432,176.9),e.bezierVertex(431.9,182.3,430.9,187.7,429.1,192.7),e.bezierVertex(427.2,197.9,428,201,432.3,205),e.bezierVertex(446.8,218.7,451.8,236,446.6,255),e.bezierVertex(441.4,274,428.3,286.5,408.7,291.3),e.bezierVertex(406.1,291.9,403.6,292.1,401.1,292.3),e.bezierVertex(400,292.4,398.9,292.5,397.9,292.6),e.bezierVertex(393.6,293.1,390.9,295.7,391,299.5),e.bezierVertex(391.1,303.4,394,305.8,398.5,305.8),e.bezierVertex(M 409.9,305.8,420.8,302.6,431.1,296.4),e.bezierVertex(431.8,296,432.5,295.5,433.2,295.1),e.bezierVertex(433.8,294.7,434.5,294.3,435.2,293.9),e.bezierVertex(436,293.4,436.6,293.2,437.2,293.1),e.bezierVertex(437.4,293,437.7,292.9,438.1,292.8),e.vertex(442.5,291.4),e.vertex(444.2,295.7),e.bezierVertex(450.9,312.4,449.5,328.4,440,343.4),e.bezierVertex(435.3,350.8,428.7,356.7,420.2,361.1),e.bezierVertex(414.3,364.1,413.7,365.2,414.8,371.7),e.bezierVertex(419.5,400.2,403,427.6,375.6,436.9),e.bezierVertex(371,438.5,368.3,44M 0.7,365.8,444.7),e.bezierVertex(355.2,462.5,336.4,473.1,315.8,473.1),e.bezierVertex(315.8,473.1,315.8,473.1,315.8,473.1),e.endShape(),ie(e),e.fill(n),e.beginShape(),e.vertex(120.2,279.9),e.bezierVertex(117.9,279.9,112.4,279.299,112.2,273.599),e.bezierVertex(112,267.7,117.4,266.7,119.7,266.599),e.bezierVertex(133.1,265.799,143.1,259.499,149.3,247.899),e.bezierVertex(149.6,247.299,150.1,246.399,150.3,245.399),e.bezierVertex(150.6,244.299,150.5,243.299,150.5,242.7),e.bezierVertex(150.5,242.6,150.5,242.5,150.5,242.299)M ,e.vertex(150.3,238.799),e.vertex(141.1,235.99),e.bezierVertex(114.6,227.799,95.6,202.499,95.9,175.799),e.bezierVertex(95.9,173.99,96.4,168.199,102.2,168.199),e.bezierVertex(102.6,168.199,103,168.199,103.4,168.299),e.bezierVertex(104.8,168.499,108.2,168.899,109.2,175.599),e.bezierVertex(109.3,176.599,109.5,177.599,109.6,178.499),e.bezierVertex(110.4,184.199,111.3,189.99,113.7,195.499),e.bezierVertex(121.9,213.99,139.5,225.499,159.7,225.499),e.bezierVertex(172.1,225.499,184.1,220.899,193.5,212.599),e.bezierVertex(19M 4,212.199,194.4,211.799,194.8,211.399),e.bezierVertex(195.1,211.099,195.5,210.799,195.8,210.399),e.bezierVertex(197.4,208.99,199.2,208.2,200.9,208.2),e.bezierVertex(202.5,208.2,204,208.899,205.3,210.1),e.bezierVertex(208,212.9,207.9,216.9,205,219.9),e.bezierVertex(196.5,228.6,186.3,234.3,174.7,236.8),e.bezierVertex(168.799,238.1,165.6,241,163.899,246.7),e.bezierVertex(158.3,265.9,139.9,279.7,120.2,279.9),e.vertex(120.2,279.9),e.endShape(),e.beginShape(),e.vertex(187.2,427.5),e.bezierVertex(183.799,427.5,181.299,425M .3,180.799,422),e.bezierVertex(180.6,420.8,180.499,419.5,180.399,418.1),e.bezierVertex(180.299,417,180.2,415.8,180.099,414.7),e.bezierVertex(177.199,390.5,156.699,371.3,132.399,370.2),e.bezierVertex(131.99,370.2,131.499,370.2,131.099,370.2),e.bezierVertex(130.699,370.2,130.299,370.2,129.799,370.2),e.bezierVertex(125.99,369.9,123.199,367.2,123.099,363.6),e.bezierVertex(122.99,360.2,125.799,357.3,129.599,356.9),e.bezierVertex(130.499,356.8,131.499,356.8,132.599,356.7),e.bezierVertex(133.199,356.7,133.799,356.7,134.39M 9,356.6),e.vertex(138.299,356.4),e.vertex(139.1,352.6),e.bezierVertex(139.5,350.7,139.799,348.9,140.2,347),e.bezierVertex(140.899,343.4,141.5,340,142.399,336.8),e.bezierVertex(150.099,310.7,174.399,292,201.399,291.3),e.vertex(201.599,291.3),e.bezierVertex(203.699,291.3,206.299,292,208.299,293.2),e.bezierVertex(210.499,294.5,210.699,297.5,209.99,299.8),e.bezierVertex(209.499,301.5,208.199,303.9,203.299,304.7),e.bezierVertex(202.199,304.9,200.99,305,199.799,305.2),e.bezierVertex(194.499,305.9,188.99,306.599,183.799,3M 08.9),e.bezierVertex(165.499,316.799,155.199,331.299,152.99,352),e.bezierVertex(152.399,357.8,154.499,361.7,159.699,364.5),e.bezierVertex(178.199,374.4,189.399,390,193.099,410.9),e.bezierVertex(193.699,414.299,193.899,418,193.599,422),e.bezierVertex(193.399,425.2,190.899,427.5,187.399,427.5),e.vertex(187.2,427.5),e.endShape(),e.beginShape(),e.vertex(364.3,281.1),e.bezierVertex(346.3,280.6,332.9,272.8,323.5,257),e.bezierVertex(321.6,253.9,320.4,250.2,319.2,246.7),e.bezierVertex(317.7,242.2,315,239.799,310.5,238.799)M ,e.bezierVertex(298.5,236.299,288,230.7,279.4,222.1),e.bezierVertex(276.7,219.4,274.9,215.299,278,211.9),e.bezierVertex(279.4,210.3,281,209.6,282.6,209.6),e.bezierVertex(284.4,209.6,286.4,210.6,288.3,212.5),e.bezierVertex(297.8,221.8,310.4,226.9,323.9,226.9),e.bezierVertex(340.2,226.9,355.1,219.3,364.8,206.2),e.bezierVertex(371,197.8,374.2,188.5,374.5,178.5),e.vertex(374.5,177.9),e.bezierVertex(374.5,177,374.5,176.1,374.7,175.4),e.bezierVertex(375.3,171.8,377.9,169.5,381.3,169.5),e.bezierVertex(381.4,169.5,381.5,16M 9.5,381.7,169.5),e.bezierVertex(385.4,169.7,388,172.4,388,176.1),e.bezierVertex(388.1,190.7,383.4,204,374.2,215.8),e.bezierVertex(365.8,226.5,354.7,233.9,341.2,237.9),e.bezierVertex(340,238.3,338.7,238.6,337.3,239.1),e.bezierVertex(335.9,239.6,335.1,240.4,334.7,240.9),e.bezierVertex(334.599,241,334.5,241.1,334.4,241.2),e.vertex(331.799,243.6),e.vertex(333.199,246.8),e.bezierVertex(338.199,258,346.799,264.9,358.699,267.3),e.bezierVertex(360.199,267.6,361.599,267.7,362.99,267.9),e.bezierVertex(363.599,268,364.299,268M ,364.899,268.1),e.bezierVertex(369.099,268.6,371.799,271.4,371.499,275),e.bezierVertex(371.199,278.6,368.299,281.2,364.399,281.2),e.vertex(364.3,281.1),e.endShape(),e.beginShape(),e.vertex(323.9,437),e.bezierVertex(323.7,437,323.5,437,323.299,437),e.bezierVertex(319.599,436.7,317.299,434.1,317.4,430.2),e.bezierVertex(317.9,406.099,328.299,388,349.5,375),e.bezierVertex(350.7,374.2,352,373.5,353.4,372.8),e.bezierVertex(354.099,372.4,354.7,372.1,355.299,371.7),e.vertex(357.499,370.5),e.vertex(357.799,368),e.bezierVertM ex(360.4,346.6,345.199,323.7,323.9,317),e.bezierVertex(319.099,315.5,314.099,314.9,309.299,314.4),e.vertex(308.199,314.299),e.bezierVertex(305.99,314.099,300.799,312.9,300.899,307.299),e.bezierVertex(300.99,303.499,303.899,300.9,308.099,300.9),e.vertex(308.299,300.9),e.bezierVertex(327.099,301.299,343.099,308.7,355.699,322.9),e.bezierVertex(364.299,332.5,369.399,344.099,370.99,357.299),e.bezierVertex(371.099,358.4,371.299,359.4,371.499,360.499),e.bezierVertex(371.599,360.99,371.699,361.499,371.799,361.99),e.vertex(M 372.499,365.899),e.vertex(377.899,366.199),e.bezierVertex(378.799,366.299,379.699,366.299,380.599,366.399),e.bezierVertex(385.099,366.699,387.899,369.399,387.799,373.299),e.bezierVertex(387.699,377.099,384.99,379.599,380.799,379.799),e.bezierVertex(369.799,380.199,359.99,383.299,351.899,389.299),e.bezierVertex(338.799,398.799,331.699,411.699,330.699,427.499),e.vertex(330.699,428.299),e.bezierVertex(330.599,429.199,330.599,430.099,330.499,430.799),e.bezierVertex(330,434.7,327.5,437,323.9,437),e.endShape()}function TM (e){return e[0].map(((t,n)=>e.map((e=>e[n]))))}function A(e){return e.map((e=>Array.isArray(e)?A(e):e))}function D(e,t){return floor(random(e,t))}function k(e){let t=0;for(const n of e)t+=n[1];let n=random(t),r=0;for(const t of e)if(r+=t[1],n<r)return t[0];return null}function L(e){for(let t=1;t<e.length;++t){let n=D(0,t),r=e[t];e[t]=e[n],e[n]=r}}function P(e){return null==e||""===e}function O(e){return new Promise((t=>setTimeout(t,e)))}function F(e,t,n){let r=0;for(let i=1;i<=1e3;++i)for(let o=1;o<=1e3;++o)if(e*o%M (t*i)==0){let e=1*i/o;abs(e-n)<abs(r-n)&&(r=e)}return r}function N(){let e=60*(new Date).getTimezoneOffset()*1e3;return new Date(Date.now()-e).toISOString().slice(0,-1)}function B(e,t,n){let r;if(push(),textSize(e),textWidth(t)<=n)r=t;else for(let e=0;e<t.length;++e){const i=t.slice(0,e+1)+"...";if(textWidth(i)>n){r=i;break}}return pop(),r}function Y(e){var t=e%10,n=e%100;return 1==t&&11!=n?e+"st":2==t&&12!=n?e+"nd":3==t&&13!=n?e+"rd":e+"th"}class G{constructor(e,t,n){this.n=t,this.m=n,this.mat=[];let r=0;for(let tM =0;t<this.n;++t){this.mat.push([]);for(let n=0;n<this.m;++n)this.mat[t].push(r<e.length?e[r]:0),r+=1}return this}copy(){return new G(this.mat.flat(),this.n,this.m)}}class H{static __linear=e=>e;static __relu=e=>Math.max(e,0);static __leaky_relu=e=>e>0?e:.2*e;static __sigmoid=e=>1/(1+Math.exp(-e));static __tanh=e=>Math.tanh(e);static __apply_unary_op(e,t){const n=e.copy();for(let e=0;e<n.n;++e)for(let r=0;r<n.m;++r)n.mat[e][r]=t(n.mat[e][r]);return n}static linear=e=>H.__apply_unary_op(e,H.__linear);static relu=e=>HM .__apply_unary_op(e,H.__relu);static leaky_relu=e=>H.__apply_unary_op(e,H.__leaky_relu);static sigmoid=e=>H.__apply_unary_op(e,H.__sigmoid);static tanh=e=>H.__apply_unary_op(e,H.__tanh);static __add=(e,t)=>e+t;static __mul=(e,t)=>e*t;static __apply_binary_op=(e,t,n)=>{"object"!=typeof t&&(t=new G([t],1,1));const r=e.copy();for(let e=0;e<r.n;++e)for(let i=0;i<r.m;++i)r.mat[e][i]=n(r.mat[e][i],t.mat[e%t.n][i%t.m]);return r};static mul=(e,t)=>H.__apply_binary_op(e,t,H.__mul);static add=(e,t)=>H.__apply_binary_op(e,t,HM .__add);static matMul(e,t){const n=new G([],e.n,t.m);for(let r=0;r<n.n;++r)for(let i=0;i<n.m;++i)for(let o=0;o<e.m;++o)n.mat[r][i]+=e.mat[r][o]*t.mat[o][i];return n}static softmax(e){const t=H.__apply_unary_op(e,(e=>Math.exp(e))),n=t.mat.flat().reduce(((e,t)=>e+t));for(let r=0;r<e.n;++r)for(let i=0;i<e.m;++i)t.mat[r][i]/=n;return t}}class ${constructor(e,t){this.scale=e,this.offset=t}forward(e){return H.add(H.mul(e,this.scale),this.offset)}}class X{constructor(){}forward(e){return e.map((e=>e.flat()))}}class W{consM tructor(e,t,n,r){this.out_dim=e,this.activation=t,this.w=n,this.b=r}forward(e){const t=H.add(H.matMul(e,this.w),this.b);return null==this.activation?t:this.activation(t)}}class U{constructor(e,t,n){this.preprocessLayers=e,this.hiddenLayers=t,this.outputLayer=n,this.totalNeurons=this.hiddenLayers.map((e=>e.out_dim)),this.currentOrders=[],this.currentIteration=null}updateNeurons(e,t){if(t!=this.currentIteration){this.currentOrders=[];for(let e=0;e<this.totalNeurons.length;++e){randomSeed(100*(t+1)+e);const n=[];for(lM et t=0;t<this.totalNeurons[e];++t)n.push(t);L(n),this.currentOrders.push(n)}this.currentIteration=t}const n=A(this.totalNeurons),r=n.reduce(((e,t)=>e+t))*(1-e);for(let e=0;e<r;++e){const t=n.map(((e,t)=>(e-1)/this.totalNeurons[t]));n[t.map(((e,t)=>[e,t])).reduce(((e,t)=>t[0]>e[0]?t:e))[1]]-=Math.min(r-e,1)}this.neuronsLife=[];for(let e=0;e<n.length;++e){const t=this.currentOrders[e],r=Array(this.totalNeurons[e]).fill(0);for(let i=0;i<n[e];++i)r[t[i]]=Math.min(n[e]-i,1);this.neuronsLife.push(r)}}getTotalNeurons(){reM turn A(this.totalNeurons)}getNeuronsLife(){return A(this.neuronsLife)}forward(e){for(const t of this.preprocessLayers)e=t.forward(e);for(const[t,n]of this.hiddenLayers.entries()){e=n.forward(e);const r=new G(this.neuronsLife[t],1,e.m);e=H.mul(e,r)}return e=this.outputLayer.forward(e),H.softmax(e)}}function q(e){switch(e){case"relu":return H.relu;case"sigmoid":return H.sigmoid;case"tanh":return H.tanh;case"leaky_relu":return H.leaky_relu;default:return H.linear}}function j(e,t){const n=[],r=[],i=Z(t);let o=null,a=0,M l=[];for(const t of e.config.layers)if("InputLayer"==t.class_name)o=t.config.batch_input_shape.slice(1),l=o;else if("Rescaling"==t.class_name)n.push(new $(t.config.scale,t.config.offset));else if("Flatten"==t.class_name)o=[o.reduce(((e,t)=>e*t))];else if("Dense"==t.class_name){const e=[t.config.units],n=o[0]*e[0],l=e[0],s=i.subarray(a,a+n);a+=n;const h=i.subarray(a,a+l);a+=l;const c=new G(s,o[0],e[0]),u=new G(h,1,e[0]),f=q(t.config.activation);r.push(new W(e[0],f,c,u)),o=e}const s=r.pop();return{model:new U(n,r,s),M inputDim:l}}function Z(e){const t=window.atob(e),n=t.length/Float32Array.BYTES_PER_ELEMENT,r=new DataView(new ArrayBuffer(Float32Array.BYTES_PER_ELEMENT)),i=new Float32Array(n);let o=0;for(let e=0;e<n;e++){o=4*e;for(let e=0;e<4;++e)r.setUint8(e,t.charCodeAt(o+e));i[e]=r.getFloat32(0,!0)}return i}class K{constructor(e){this.elt=e,this._events={},this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight}position(){if(0===arguments.length)return{x:this.elt.offsetLeft,y:this.elt.offsetTop};var e="absolute";retuM rn"static"!==arguments[2]&&"fixed"!==arguments[2]&&"relative"!==arguments[2]&&"sticky"!==arguments[2]&&"initial"!==arguments[2]&&"inherit"!==arguments[2]||(e=arguments[2]),this.elt.style.position=e,this.elt.style.left=arguments[0]+"px",this.elt.style.top=arguments[1]+"px",this.x=arguments[0],this.y=arguments[1],this}show(){return this.elt.style.display="block",this}hide(){return this.elt.style.display="none",this}size(e,t){if(0===arguments.length)return{width:this.elt.offsetWidth,height:this.elt.offsetHeight};var nM =e,r=t;if(n!==te||r!==te){if(n===te?n=t*this.width/this.height:r===te&&(r=e*this.height/this.width),this.elt instanceof HTMLCanvasElement){var i,o={},a=this.elt.getContext("2d");for(i in a)o[i]=a[i];for(i in this.elt.setAttribute("width",n*this._pInst._pixelDensity),this.elt.setAttribute("height",r*this._pInst._pixelDensity),this.elt.style.width=n+"px",this.elt.style.height=r+"px",this._pInst.scale(this._pInst._pixelDensity,this._pInst._pixelDensity),o)this.elt.getContext("2d")[i]=o[i]}else this.elt.style.width=n+"M px",this.elt.style.height=r+"px",this.elt.width=n,this.elt.height=r;this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight,this._pInst&&this._pInst._curElement&&this._pInst._curElement.elt===this.elt&&(this._pInst._setProperty("width",this.elt.offsetWidth),this._pInst._setProperty("height",this.elt.offsetHeight))}return this}style(e,t){if(t instanceof Color&&(t="rgba("+t.levels[0]+","+t.levels[1]+","+t.levels[2]+","+t.levels[3]/255+")"),void 0===t){if(-1===e.indexOf(":"))return window.getComputedStyle(thM is.elt).getPropertyValue(e);for(var n=e.split(";"),r=0;r<n.length;r++){var i=n[r].split(":");i[0]&&i[1]&&(this.elt.style[i[0].trim()]=i[1].trim())}}else if(this.elt.style[e]=t,"width"===e||"height"===e||"left"===e||"top"===e){var o=window.getComputedStyle(this.elt).getPropertyValue(e).replace(/[^\d.]/g,"");this[e]=Math.round(parseFloat(o,10))}return this}value(){return arguments.length>0?(this.elt.value=arguments[0],this):"range"===this.elt.type?parseFloat(this.elt.value):this.elt.value}mouseClicked(e){return this.M _adjustListener("click",e,this),this}isFocused(){return document.activeElement===this.elt}_adjustListener(e,t,n){return!1===t?this._detachListener(e,n):this._attachListener(e,t,n),this}_attachListener(e,t,n){n._events[e]&&this._detachListener(e,n);var r=t.bind(n);n.elt.addEventListener(e,r,!1),n._events[e]=r}_detachListener(e,t){var n=t._events[e];t.elt.removeEventListener(e,n,!1),t._events[e]=null}}function J(e,t){var n=document.createElement("button");return n.innerHTML=e,t&&(n.value=t),ee(n)}function Q(e){var t=M arguments.length>1&&void 0!==arguments[1]&&arguments[1],n=function(t){var n=!0,r=!1,i=void 0;try{for(var o,a=t.target.files[Symbol.iterator]();!(n=(o=a.next()).done);n=!0){var l=o.value;File._load(l,e)}}catch(e){r=!0,i=e}finally{try{n||null==a.return||a.return()}finally{if(r)throw i}}};if(window.File&&window.FileReader&&window.FileList&&window.Blob){var r=document.createElement("input");return r.setAttribute("type","file"),t&&r.setAttribute("multiple",!0),r.addEventListener("change",n,!1),ee(r)}}function ee(e){retuM rn document.body.appendChild(e),new K(e)}createImg=function(){var e,t=document.createElement("img"),n=arguments;return n.length>1&&"string"==typeof n[1]&&(t.alt=n[1]),n.length>2&&"string"==typeof n[2]&&(t.crossOrigin=n[2]),t.src=n[0],e=ee(t,this),t.addEventListener("load",(function(){e.width=t.offsetWidth||t.width,e.height=t.offsetHeight||t.height;var r=n[n.length-1];"function"==typeof r&&r(e)})),e},createInput=function(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:"",t=arguments.length>1&&void 0!=M =arguments[1]?arguments[1]:"text",n=document.createElement("input");return n.setAttribute("value",e),n.setAttribute("type",t),ee(n,this)};const te="auto";function ne(e){re(e);const t=e._rectMode;e.rectMode(CORNER),e.rect(0,0,e.width,e.height),e.rectMode(t),ie(e)}function re(e){e.push(),e.fill(255,255,255,255),e.blendMode(REMOVE)}function ie(e){e.blendMode(BLEND),e.pop()}File=function(e,t){this.file=e,this._pInst=t;var n=e.type.split("/");this.type=n[0],this.subtype=n[1],this.name=e.name,this.size=e.size,this.data=vM oid 0},File._createLoader=function(e,t){var n=new FileReader;return n.onload=function(n){var r=new File(e);if("application/json"===r.file.type)r.data=JSON.parse(n.target.result);else if("text/xml"===r.file.type){var i=(new DOMParser).parseFromString(n.target.result,"text/xml");r.data=new XML(i.documentElement)}else r.data=n.target.result;t(r)},n},File._load=function(e,t){if(/^text\//.test(e.type)||"application/json"===e.type)File._createLoader(e,t).readAsText(e);else if(/^(video|audio)\//.test(e.type)){var n=new FiM le(e);n.data=URL.createObjectURL(e),t(n)}else File._createLoader(e,t).readAsDataURL(e)},XML=function(e){if(e)this.DOM=e;else{var t=document.implementation.createDocument(null,"doc");this.DOM=t.createElement("root")}},document.addEventListener("DOMContentLoaded",(function(){addEventListener("mousemove",(e=>{window.mouseX=e.pageX,window.mouseY=e.pageY}))})),new e("global");const oe="343";let ae,le,se,he,ce,ue,fe,de,xe,ge,pe,me,be,ye,we,ve,ze,Ve,_e,Me,Ee,Se,Re,Ie,Ce,Te,Ae,De,ke,Le,Pe,Oe,Fe,Ne,Be,Ye,Ge,He,$e,Xe,We,Ue,qM e,je,Ze,Ke,Je,Qe,et,tt,nt,rt,it,ot,at,lt,st,ht,ct,ut,ft,dt,xt,gt,pt,mt,bt,yt,wt,vt,zt,Vt,_t,Mt,Et,St,Rt,It,Ct,Tt,At=!1,Dt=!1,kt=!0,Lt=!1,Pt=!1;const Ot=[" ","Growing","Stable","Decaying","Dead","Rebirth"];let Ft,Nt,Bt,Yt,Gt,Ht,$t,Xt,Wt,Ut,qt,jt,Zt,Kt,Jt,Qt,en,tn,nn,rn,on,an,ln,sn,hn=0,cn=0,un=0,fn=!1,dn=!0,xn=!0,gn=null,pn=null,mn=null,bn=!1,yn=!1,wn=null,vn=null,zn=!1;async function setup(){let e=windowWidth,t=windowHeight;createCanvas(e,t),et=createGraphics(e,t),Xe=createGraphics(e,t),$e=createGraphics(e,t),We=crM eateGraphics(e,t),Ue=createGraphics(e,t),qe=createGraphics(e,t),Qe=createGraphics(e,t),je=createGraphics(e,t),Ze=createGraphics(e,t),Ke=createGraphics(e,t),Je=createGraphics(e,t),tt=createGraphics(500,500),nt=createGraphics(500,500),rt=createGraphics(500,500),_n(),Mn(),Sn(),await En(),Gn(),Rn(),bn=!0}function _n(){Et=parseInt(oe),randomSeed(Et),noiseSeed(Et)}function Mn(){Wt=Ir(p.training_traits),Cr(Wt)}async function En(){let e;Jt=r(),Qt=o(),[Xt,e]=await Promise.all([s(Jt),h(Qt)]),Ut=new V(Wt.visual,e.layers_confiM g,e.weight_b64),Ut.updateAge(new Date),_n(),Wt.training=e.training_traits,Ht=e.model_name,$t=e.classes_name}function Sn(){le=min(width,height)/1024,ut=Rr.findIndex((e=>e[0]===Wt.visual.colorPalette)),ft=[["#ffffff","#231f20","#231f20"],["#231f20","#ffffff","#ffffff"],["#104da8","#ffffff","#ffffff"],["#722F1F","#FCE1B2","#FCE1B2"],["#e88120","#f9f2e5","#f9f2e5"],["#f6b941","#2E2E2E","#2E2E2E"],["#45daaa","#012221","#012221"],["#F1F1F1","#328DFE","#328DFE"],["#111822","#D3EB8D","#D3EB8D"],["#713FF9","#D6D5E6","#D6D5EM 6"],["#FBDA9D","#795106","#795106"],["#8f5b62","#ead0d0","#ead0d0"],["#eae4cb","#508cac","#508cac"],["#ffc6cc","#cc313d","#cc313d"],["#60A900","#E0FE00","#E0FE00"],["#507DBE","#D0D1D3","#D0D1D3"],["#305848","#E8F2EE","#E8F2EE"],["#2a2634","#5b6988","#cb78a2","#5b6988"],["#590e29","#fd5e53","#fd5e53","#ffe373"],["#0a141d","#57d4e4","#328195","#2A9ECF","#0ab6a8","#57d4e4"],["#3a2d28","#d5c2ac","#df6338","#3d9895","#d5c2ac"],["#030706","#77c4d9","#77c4d9","#77c4d9","#ffffff","#ffffff","#e72020","#e72020"],["#3a4664","M #92f5ff","#f9ff94","#eaa0a2","#55dde0"],["#fbfaff","#f04bb1","#f04bb1","#fac373","#82cef0","#8b31ce"],["#000000","#ffffff","#ff0002","#f26522","#fdff00","#00ff03","#01fffe","#0000ff","#ff00ff"]];for(let e=0;e<ft.length;++e)for(let t=0;t<ft[e].length;++t)ft[e][t]=cr(ft[e][t]);pt=[],ct=ft[ut][0],st=ft[ut][1]}function Rn(){gn=document.querySelector("#upload"),pn=document.querySelector("#inputUpload"),gn.addEventListener("dblclick",(()=>{if(!Lt&&!yn)if(In(Ie)&&cn==Ve-1)pn.click();else{if(4!=Pe&&5!=Pe&&(In(Ie)||cn!=Ve-1M ))return;fn=!0,dn=!0,Bt=0,un=0}})),pn.addEventListener("click",(()=>{pn.value=null,gn.style.display="block"})),pn.addEventListener("change",(()=>{const[e]=pn.files;e?(se=null,gn.style.display="none",Tn(URL.createObjectURL(e)),mn=e):gn.style.display="block"}))}function In(e){for(let t=0;t<e.length;++t){let n=0;for(let r=0;r<e[t].length;++r)e[t][r]>0&&++n;if(0==n)return!1}return!0}function Cn(){null!=se&&(un=0,Pt=!0,he=0,ue=0,drewLineAnim=!0,ce=(ae/2+we/2)/le,loadImage(se.elt.src,(e=>{const[t,n,r]=Gt,i=createGraphicsM (t,n);i.image(e,0,0,t,n),i.loadPixels();const o=i.pixels.filter(((e,t)=>t%4!=3)),a=Ut.classifyImage(o);Zt=T([a,$t.map((e=>e.toUpperCase()))]).sort(((e,t)=>e[0]>t[0]?-1:1))})))}function Tn(e){se=createImg(e,""),se.hide(),Cn()}function An(){zn||(ce+=(width-ae-we)/tn/le),re(Xe),Xe.rect(ce*le,0,width,height),ie(Xe),un>=ge&&1==kt&&(kt=!1,un-=ge),kt&&(re($e),$e.strokeWeight(2*Fe),Jn(he,ze,ct,ct,$e),ie($e)),un>=ge&&0==kt&&(kt=!0,un-=ge,he+=1,he==en&&(++ue,he=0,ce=(ae/2+we/2)/le,1==ue&&(Pt=!1,Dn(),ye=millis())))}function DM n(){At=!0,pe=!1,me=!1,tryButton=br("Try Again",width/2-225*le,height/2+265*le,290*le,40*le,kn),closeResultButton=br("Close",width/2+75*le,height/2+265*le,150*le,40*le,Ln)}function kn(){At=!1,tryButton.hide(),closeResultButton.hide(),pn.click()}function Ln(){Yt=!0,At=!1,Gn(),tryButton.hide(),closeResultButton.hide(),gn.style.display="block",se=null}function keyTyped(){bn&&!1===yn&&!1===yr()&&("i"!==key&&"I"!==key||(Dt=!Dt),"b"!==key&&"B"!==key||(xn=!xn),"s"!==key&&"S"!==key||!1!==Lt||saveCanvasAtCurrentTime(),"k"!==M key&&"K"!==key||!1!==Lt||save4KCanvasAtCurrentTime(),"u"!==key&&"U"!==key||!1!==Lt||!1!==At||!1!==fn||!1!==Pt||On())}function On(){Lt=!0,wn=null,vn=null,submitButton=br("Submit",width/2-155*le,height/2+115*le,150*le,40*le,Fn),closeSettingButton=br("Close",width/2+5*le,height/2+115*le,150*le,40*le,Yn),vt=createInput(),vt.position(width/2-252.5*le,height/2-40*le),vt.size(500*le,25*le),vt.style("font-size","15px"),vt.value(Jt||""),zt=createInput(),zt.position(width/2-252.2*le,height/2+35*le),zt.size(500*le,25*le),zt.sM tyle("font-size","15px"),zt.value(Qt||"")}function Fn(){Vt=vt.value(),_t=zt.value(),submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide(),Lt=!1,yn=!0,Nn()}async function Nn(){[wn,vn,_]=await Promise.all([c(Vt),u(_t),O(1e3)]),yn=!1,wn&&vn?(n(Vt),i(_t),window.location.reload()):(Lt=!0,submitButton.show(),closeSettingButton.show(),vt.show(),zt.show())}function Bn(){Je.textFont("Trebuchet MS"),Je.noStroke(),pr(Je,600*le,200*le),Je.strokeWeight(1*le),Je.stroke(xt),Je.fill(xt),Je.textSize(50*le),Je.text("updaM te()",width/2,height/2+2.5*le)}function Yn(){wn=null,vn=null,Lt=!1,submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide()}function Gn(){_n(),nn=Date.now(),pe=!1,me=!1,St=Wt.training.structure_gen,Rt=Wt.visual.birthYear,It=Wt.visual.lifeCycle,Ct=Wt.training.epoch_num,Tt=Wt.training.activation_func,Ft=Mr.findIndex((e=>e[0]==Wt.visual.hardwareAcceleration))+1,1==Ft?(Nt=30,fe=40):2==Ft?(Nt=15,fe=20):(Nt=2,fe=10);const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCounM t,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),ae=100*le,ht=50*le,Oe=Sr.findIndex((e=>e[0]==Wt.visual.nodeShape))+1,dt=Er.findIndex((e=>e[0]==Wt.visual.nodeFill))+1,lt=_r.findIndex((e=>e[0]==Wt.visual.pattern))+1,de=Math.tanh(MM ath.log10(Xt.avgfeerate)),de=map(de,0,1,.2,.8),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(M let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(M Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,at=.7,pt=[],xt=ft[ut][2],gt=ft[ut][ft[ut].length-1];for(let e=3;e<ft[ut].length-1;e++)pt.push(ft[ut][e]);mt=sr(xt,gt,pt,width),bt=[],wt=[],yt=width/(Ve-1);for(let e=0;e<Ve;e++)bt.push(hr(mt,yt*e/width)),wt.push(hr(mt,yt*e/M width));wt.unshift(bt[0]),wt.push(bt[bt.length-1]),hn=0,cn=0,un=0,Yt=!0;const n={xLeft:ae/8,xRight:width-ae/8,yTop:ae/8,yBottom:height-ae/8},r=Ce.map((e=>e.length));jt=new R(bt,r,n,Oe,le)}function Hn(e,t){let n=Ce[e].length;return[e*we+we/2+ae/2,height/2-(n-1)/2*ve+t*ve]}function $n(e,t){le=min(e,t)/1024,ae=100*le,ht=50*le,we=(e-ae)/Ve,ve=(t-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}xe=floor(De.length*de),Le=M [],ke=[],ge=floor(map(de,.2,.8,15,2));for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,mt=sr(xt,gt,pt,e),bt=[],wt=[],yt=e/(Ve-1);for(let t=0;t<Ve;t++)bt.push(hr(mt,yt*t/e)),wt.push(hr(mt,yt*t/e));wt.unshift(bt[0]),wt.push(bt[bt.length-1])}function Xn(){const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,aM n=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.leM ngth;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}MM e=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(M Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le}function Wn(){jt.update();const e=4==Pe?0:Kt;jt.draw(Qe,ct,dt,e,le)}function Un(){if(!bn)return ar(),void et.image(je,0,0);if(4==Pe||5==Pe)return Wn(),void et.image(Qe,0,0);un>=Nt&&hn<Ve&&(hn++,un=0);for(let e=0;e<hn;e++)1==dt?it=ot=bt[e]:(it=ct,ot=bt[e]),Kn(e,it,ot,$e);un>=Nt&&cn<Ve-1&&(cn++,un=0);for(let e=0;e<cn;e++)Zn(e)}function qn(){et.background(ct),Ue.background(255),Ue.rectMode(CENTER),ne(Ue),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),Ue.stroke(st),Ue.strokeWM eight(8*le),Ue.fill(ct),Qe.background(255),Qe.rectMode(CENTER),ne(Qe),Qe.strokeWeight(le),qe.background(255),qe.rectMode(CENTER),ne(qe),qe.textAlign(LEFT),$e.background(255),$e.rectMode(CENTER),ne($e),Xe.background(255),ne(Xe),Xe.strokeWeight(Ne),We.background(255),We.rectMode(CENTER),ne(We),We.fill(st),We.stroke(st),We.strokeWeight(.1*le),er(lt),We.noStroke(),xn&&(We.rect(ae/16,height/2,ae/8,height),We.rect(width-ae/16,height/2,ae/8,height),We.rect(width/2,ae/16,width,ae/8),We.rect(width/2,height-ae/16,width,ae/8)M ),Ze.background(255),Ze.rectMode(CENTER),ne(Ze),Ze.textAlign(CENTER,CENTER),Ze.textStyle(BOLD),Ze.stroke(st),Ze.strokeWeight(8*le),Ze.fill(ct),je.background(255),je.rectMode(CENTER),ne(je),je.textAlign(CENTER,CENTER),je.textStyle(BOLD),Ke.background(255),Ke.rectMode(CENTER),ne(Ke),Ke.textAlign(CENTER,CENTER),Ke.textStyle(BOLD),Ke.stroke(st),Ke.strokeWeight(8*le),Ke.fill(ct),Je.background(255),Je.rectMode(CENTER),ne(Je),Je.textAlign(CENTER,CENTER),Je.textStyle(BOLD),Je.stroke(st),Je.strokeWeight(8*le),Je.fill(ct),UnM (),et.image(We,0,0),Pt&&An(),et.image(Xe,0,0),et.image($e,0,0),At&&(tr(),et.image(Ue,0,0)),fn&&(lr(),et.image(Ze,0,0)),Lt&&(or(),et.image(Ke,0,0)),Dt&&(ir(),et.image(qe,0,0)),yn&&(Bn(),et.image(Je,0,0))}function draw(){const e=Date.now();bn&&(Ut.updateAge(new Date(e)),Xn()),qn(),image(et,0,0),zn||un++}function Zn(e){let t,n=Ce[e].length,r=Ce[e+1].length;for(let i=0;i<n;i++){const[n,o]=Hn(e,i);for(let a=0;a<r;a++){const[r,l]=Hn(e+1,a);t=map(min(Ce[e][i],Ce[e+1][a]),0,1,0,.5),ur(n,o,r,l,bt[e],bt[e+1],Xe,t)}}}functionM Kn(e,t,n,r){let i,o,a,l=Ce[e].length;for(let s=0;s<l;s++){const[l,h]=Hn(e,s);i=Ce[e][s],a=map(Be,1/30,1,3,10),o=map(Ce[e][s],0,1,2*a,0)*le,o<1.5*le&&(o=0),Qn(l,h,ze,Oe,t,n,o,i,r)}}function Jn(e,t,n,r,i){for(let o=0;o<Le[e].length;o++)Qn(Le[e][o][0],Le[e][o][1],t,Oe,n,r,0,1,i)}function Qn(e,t,n,r,i,o,a,l,s){s.stroke(dr(o,map(l,0,1,.25,1))),s.fill(dr(i,map(l,0,1,.15,1))),s.strokeWeight(Fe),fr([a],s),3==dt&&s.fill(dr(i,0)),1==r?s.ellipse(e,t,n):2==r?s.rect(e,t,7*n/8,7*n/8):3==r&&(s.beginShape(),s.vertex(e-4*n/7,t),s.M vertex(e,t-4*n/7),s.vertex(e+4*n/7,t),s.vertex(e,t+4*n/7),s.endShape(CLOSE))}function er(e){if(1==e);else if(2==e){We.strokeWeight(1*le);for(let e=ht/4;e<width+ht/4;e+=ht)for(let t=ht/4;t<height+ht/4;t+=ht)We.point(e,t)}else if(3==e){ht=25*le;for(let e=ht/2;e<height+ht/2;e+=ht)We.line(0,e,width,e);for(let e=ht/2;e<width+ht/2;e+=ht)We.line(e,0,e,height)}}function tr(){Ue.textFont("Trebuchet MS"),Ue.textAlign(LEFT,CENTER),Ue.noStroke(),pr(Ue,800*le,500*le),Ue.noStroke(),Ue.fill(dr(st,.75)),Ue.rect(width/2,height/2-10M 0*le,800*le,300*le,25*le,25*le,0,0),Ue.fill(st),Ue.rect(width/2-250*le,height/2-100*le,225*le,225*le),Ue.image(se.elt,width/2-357.5*le,height/2-207.5*le,215*le,215*le);let e=100*Zt[0][0];Ue.fill(ct),Ue.textSize(25*le),Ue.textStyle(NORMAL),1==me&&(e>=0&&e<20?Ue.text("I have a feeling this image belongs to",width/2-100*le,height/2-170*le):e>=20&&e<40?Ue.text("I have a hunch this image belongs to",width/2-100*le,height/2-170*le):e>=40&&e<60?Ue.text("I think this image belongs to",width/2-100*le,height/2-170*le):e>=60&M &e<80?Ue.text("I'm almost certain this image belongs to",width/2-100*le,height/2-170*le):Ue.text("I'm positive this image belongs to",width/2-100*le,height/2-170*le));let t=e.toFixed(2);"100.00"==t&&(t="100"),1==me&&Ue.text("I'm "+t+"% confident that I'm right!",width/2-100*le,height/2-25*le),example=Zt.map((e=>e[1])),be=Ue.textWidth('"FIDENZAAAA"'),defaultPhrase=Ue.textWidth('"PERPENDICULAR INHABITATION"'),Ue.textStyle(BOLD);const n=me?example[0]:random(example);if(1===n.split(" ").length){let e=75*be/Ue.textWidthM ('"'+n+'"');e>75&&(e=75),Ue.textSize(e*le),Ue.text('"'+n+'"',width/2-100*le,height/2-90*le)}else nr(width/2-100*le,height/2-90*le,460*le,110*le,n,Ue);if(millis()-ye>1500&&(me=!0),C(tt,nt,st,ct,Pe,Mt),Ue.image(nt,width/2-370*le,height/2+70*le,80*le,80*le),3==Pe){let e;e=map(Mt,50,60,.25,1.3),I(rt,e),Ue.image(rt,width/2-370*le,height/2+70*le,80*le,80*le)}let r,i;Ue.image(tt,width/2-370*le,height/2+70*le,80*le,80*le),Ue.fill(xt),Ue.textSize(40*le),Ue.text("INTELLIGENCE INFO",width/2-275*le,height/2+115*le),Ue.textSizeM (18*le),Ue.textStyle(NORMAL),Ue.circle(width/2-360*le,height/2+180*le,7.5*le),1==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s growing and getting smarter by the day.`:2==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s stable and it has reached peak performance.`:3==Pe&&(r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s decaying and losing its luster.`),i=2==Pe?"The Perceptron remains stable for some time before entering the decay phase.":`Wait until ${new Date(an).toLocaleString("eM n-US")} for your Perceptron to reach its peak performance.`,Ue.text(r,width/2-350*le,height/2+180*le),Ue.circle(width/2-360*le,height/2+210*le,7.5*le),Ue.text(i,width/2-350*le,height/2+210*le),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),gr(Ue,width/2-225*le,width/2+65*le,height/2+265*le,height/2+305*le,"SELECT ANOTHER IMAGE"),gr(Ue,width/2+75*le,width/2+225*le,height/2+265*le,height/2+305*le,"CLOSE")}function nr(e,t,n,r,i,o){let a=i.split(" "),l=75*be/o.textWidth('"'+i+'"'),s=0,h=[],c=[],u=[],f="",d="";if(l>=50)M l>75&&(l=75),o.textSize(l*le),o.text('"'+i+'"',e,t);else if(l<50){if(l=50*defaultPhrase/o.textWidth('"'+i+'"'),l>30){if(l>50&&(l=50),[f,d]=rr(l,n,s,h,c,a,f,d,Ue),0==c.length)return o.textSize(l*le),void o.text('"'+i+'"',e,t);for(s=0,h=[],c=[];o.textWidth(d)>n/le;)l=l*n/le/o.textWidth(d),f="",d="",[f,d]=rr(l,n,s,h,c,a,f,d,Ue)}else{l=30,o.textSize(l);for(let e=0;e<a.length;e++)s+=o.textWidth(" "+a[e]),s<=n/le?h.push(a[e]):s>n/le&&s<=n/le*2?c.push(a[e]):u.push(a[e]);for(let e=1;e<h.length;e++)f=f+" "+h[e];if(f='"'+h[0M ]+f,0==u.length){for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+c[c.length-1]+'"'}else if(1==c.length)d="... "+u[u.length-1]+'"';else{for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+"... "+u[u.length-1]+'"'}}o.textSize(l*le);let r=1.25*(o.textDescent()+o.textAscent());o.text(f,e,t-r/2),o.text(d,e,t+r/2)}}function rr(e,t,n,r,i,o,a,l,s){s.textSize(e);for(let e=0;e<o.length;e++)(n+=s.textWidth(" "+o[e]))<=t/le?r.push(o[e]):i.push(o[e]);for(let e=1;e<r.length;e++)a=a+" "+r[e];if(a='"'+r[0]+a,0==i.length&&(a+='"',l=""),1==M i.length)l=i[i.length-1]+'"';else{for(let e=0;e<i.length-1;e++)l=l+i[e]+" ";l=l+i[i.length-1]+'"'}return[a,l]}function ir(){const e=45*le;qe.textFont("Tahoma"),qe.stroke(st),qe.strokeWeight(2*le),qe.fill(ct),qe.rect(width/2,e/2+height-87.5*le,600*le,90*le),qe.fill(st),qe.rect(width/2-150*le,e+height-170*le,300*le,30*le),qe.fill(ct),qe.rect(width/2+150*le,e+height-170*le,300*le,30*le),qe.noStroke(),qe.fill(ct),qe.textSize(15*le),qe.textStyle(BOLD),qe.text("PERCEPTRON INFORMATION",width/2-285*le,e+height-165*le),qe.fM ill(xt),qe.text("ARTWORK NAME:",width/2+10*le,e+height-165*le),qe.textAlign(RIGHT),qe.textStyle(ITALIC),qe.text("Perceptron #"+Et,width/2+285*le,e+height-165*le);const[t,n]=It.split(" ");let r;"60 Years"===It?r="1 Year":"60 Months"===It?r="1 Month":"60 Weeks"===It?r="1 Week":"60 Days"===It?r="1 Day":"12 Hours"===It&&(r="12 Minutes"),data=[["AI MODEL NAME:",B(12*le,Ht,140*le)],["SCALE:","1:"+Te],["NUMBER OF CLASSES:",$t.length],["BIRTH YEAR:",Rt],["NUMBER OF REBIRTHS:",sn.toString()],["AGE:",`${Math.ceil(Mt)} PercepM tron Years`],["ONE PERCEPTRON YEAR:",`${r}`],["STATE:",Ot[Pe]],["ACTIVE NEURONS:",`${round(ln*rn)} / ${ln}`],["NEXT STATE TIME:",vr(new Date(on))]],qe.fill(xt);const i=data.length/2;for(let t=0;t<data.length;++t){const n=t<i,r=n?width/2-285*le:width/2+10*le,o=n?width/2-10*le:width/2+285*le,a=e+height-(135-t%i*15)*le;qe.textStyle(BOLD),qe.textAlign(LEFT),qe.textSize(12*le),qe.text(data[t][0],r,a),qe.textStyle(ITALIC),qe.textAlign(RIGHT),qe.textSize(12*le),qe.text(data[t][1],o,a)}}function or(){Ke.textFont("TrebuchetM MS"),Ke.noStroke(),pr(Ke,600*le,200*le),gr(Ke,width/2-155*le,width/2-5*le,height/2+115*le,height/2+155*le,"UPDATE"),gr(Ke,width/2+5*le,width/2+155*le,height/2+115*le,height/2+155*le,"CLOSE"),Ke.textAlign(LEFT),Ke.fill(xt),Ke.text("UPDATE BITCOIN FULL NODE ADDRESS",width/2-252.5*le,height/2-55*le),Ke.text("UPDATE MODEL ADDRESS",width/2-252.5*le,height/2+20*le),Ke.textAlign(RIGHT),Ke.textStyle(ITALIC),Ke.textSize(15*le),0==wn&&Ke.text("(*) Invalid Address",width/2+252.5*le,height/2-53*le),0==vn&&Ke.text("(*) InvalidM Model",width/2+252.5*le,height/2+23*le)}function ar(){je.textFont("Trebuchet MS"),je.fill(st),je.textSize(50*le),je.stroke(st),je.strokeWeight(1*le),je.text("main()",width/2,height/2)}function lr(){un>=20&&1==dn&&(dn=!1,un=0),dn&&(Ze.textFont("Trebuchet MS"),Ze.stroke(st),Ze.fill(ct),Ze.rect(width/2,height/2,600*le,150*le,25*le),Ze.fill(xt),Ze.textSize(75*le),Ze.noStroke(),1==Pe?Ze.text("GROWING",width/2,height/2+5*le):3==Pe?Ze.text("AGING",width/2,height/2+5*le):4==Pe?Ze.text("DEAD",width/2,height/2+5*le):5==Pe&&M Ze.text("BIRTH",width/2,height/2+5*le)),un>=20&&0==dn&&(dn=!0,un=0,Bt++,3==Bt&&(fn=!1))}function sr(e,t,n,r){let i=[],o=r/(n.length+1),a=color(e),l=color(t);i.push(a);for(let e=0;e<n.length;e++){let t=color(n[e]);for(let e=1;e<=o;e++){let n=lerpColor(a,t,e/o);i.push(n)}a=t}for(let e=1;e<o;e++){let t=lerpColor(a,l,e/o);i.push(t)}if(i.push(l),i.length>r)i.splice(r);else if(i.length<r){let e=i[i.length-1];for(;i.length<r;)i.push(e)}return i}function hr(e,t){let n=e.length,r=Math.floor(t*n);return r>=n&&(r=n-1),e[r]}fuM nction cr(e){e=e.replace("#","");var t=parseInt(e,16);return color(t>>16&255,t>>8&255,255&t)}function ur(e,t,n,r,i,o,a,l){var s=a.drawingContext.createLinearGradient(e,t,n,r);s.addColorStop(0,i),s.addColorStop(1,o),a.drawingContext.strokeStyle=s,a.drawingContext.globalAlpha=l,a.line(e,t,n,r),a.drawingContext.globalAlpha=1}function fr(e,t){t.drawingContext.setLineDash(e)}function dr(e,t){let n=color(e),r=red(n),i=green(n),o=blue(n);return color(r,i,o,255*t)}function xr(e,t,n,r){return mouseX>e&&mouseX<t&&mouseY>n&&mM ouseY<r}function gr(e,t,n,r,i,o){e.strokeWeight(1*le),e.stroke(st);const[a,l]=xr(t,n,r,i)?[xt,ct]:[ct,xt];e.fill(a),e.push(),e.rectMode(CORNERS),e.rect(t,r,n,i,5*le),e.pop(),e.noStroke(),e.textSize(20*le),e.fill(l),e.text(o,(t+n)/2,(46*r+54*i)/100)}function pr(e,t,n){e.fill(0,0,0,75),e.rect(width/2,height/2,width,height),e.stroke(st),e.fill(ct),e.rect(width/2,height/2,t,n,25*le)}function mr(e,t){resizeCanvas(e,t,!0),Xe.resizeCanvas(e,t,!0),$e.resizeCanvas(e,t,!0),We.resizeCanvas(e,t,!0),Ue.resizeCanvas(e,t,!0),qe.rM esizeCanvas(e,t,!0),Qe.resizeCanvas(e,t,!0),je.resizeCanvas(e,t,!0),Ze.resizeCanvas(e,t,!0),Ke.resizeCanvas(e,t,!0),Je.resizeCanvas(e,t,!0),et.resizeCanvas(e,t,!0)}function br(e,t,n,r,i,o){const a=J(e);return a.position(t,n),a.size(r,i),a.style("opacity","0"),a.mouseClicked(o),a}function yr(){return null!=vt&&vt?.isFocused()||null!=zt&&zt?.isFocused()}function wr(e,t,n,r){let i;if(e<=3){i=`Hey ${String.fromCodePoint(128075)}, I'm ${n}, ${t} years old. I can detect ${r.length} NFT collections: `;let e=0;for(let t=0;M t<r.length;++t){const n=r[t];if(e+n.length>500){i+=", etc";break}t==r.length-1?i+=", and ":t>0&&(i+=", "),i+=n,e+=n.length}i+=". ",t<=5?i+="However, I am only a baby, so my recognition ability is not accurate. I'm in the state of Growing both looks and intelligence.":t<=13?i+="I am now a child. My recognition ability is becoming better, but still not very accurate. I'm in the state of Growing both looks and intelligence.":t<=25?i+="I have grown up to be a teen. My recognition ability almost reaches the peak, but I M will still mess up sometimes. I'm in the state of Growing both looks and intelligence.":t<=50?i+="I finally reach adulthood. My recognition is fully functional now. I'm in the Stable state, where I am the most intelligent with all neurons activated.":t<=60&&(i+="I am now an old Perceptron, so my recognition ability is no longer the best. I'm in the Decaying state, meaning that my neurons are dying, and my intelligence is decreasing over time.")}else 4==e?i=`${n} is Dead. However, this is not the end to its story...M `:5==e&&(i=`${n} is now in the Rebirth state, and is preparing to start a new life.`);return i}function vr(e){const t=e.getDate(),n=e.toLocaleString("en-US",{month:"long"}),r=e.getFullYear();let i=e.getHours().toString();1==i.length&&(i="0"+i);let o=e.getMinutes().toString();return 1==o.length&&(o="0"+o),`${Y(t)} ${n} ${r} | ${i}:${o}`}saveCanvasAtCurrentTime=()=>{save(N())},save4KCanvasAtCurrentTime=()=>{const e=width,t=height,n=min(4096/min(e,t),1e4/max(e,t)),r=e*n,i=t*n;mr(r,i),zn=!0,$n(r,i),qn();let o="4K_"+N()M +".png";saveCanvas(et,o),mr(e,t),$n(e,t),zn=!1};const zr=[["60 Years",3,365],["60 Months",40,30],["60 Weeks",37,7],["60 Days",20,1]],Vr=[["1943",1],["1951",1.5],["1957",2],["1969",2.5],["1970",3],["1980",3.5],["1982",4],["1986",4.5],["1988",5],["1997",5.5],["1998",6],["2002",6.5],["2009",7],["2012",7.5],["2014",8],["2015",8.5],["2016",9],["2023",15]],_r=[["Plain",20],["Dotted",40],["Squared",40]],Mr=[["Basic",30],["Standard",60],["Advanced",10]],Er=[["MNIST",70],["CIFAR",25],["IMAGENET",5]],Sr=[["Theano",60],["TorcM h",30],["TensorFlow",10]],Rr=[["Whitepaper",2],["Blackboard",2],["Blueprint",2],["Nak",74/14],["Jims",74/14],["Level 10",74/14],["Flips",74/14],["Level 14",74/14],["III",74/14],["XMB",74/14],["Info",74/14],["Adventure",74/14],["Marigold",74/14],["Phoenix",74/14],["Love",74/14],["Cachet",74/14],["Human",74/14],["Twilight",3],["Sunset",3],["Aurora",3],["Liminal Space",3],["D Vu",3],["Lucid Dream",3],["Parallel",1],["Multiverse",1]];function Ir(e){for(let e=0;e<100;++e)random(1);return{visual:{pattern:k(_r),hardwM areAcceleration:k(Mr),nodeFill:k(Er),nodeShape:k(Sr),colorPalette:k(Rr),lifeCycle:k(zr),birthYear:k(Vr)},training:e}}function Cr(e){window.$generativeTraits={"Network Architecture":e.training.structure_gen,"Hidden Layers":e.training.n_layers,"Max Neurons Per Hidden Layer":e.training.max_nodes,"Activation Function":e.training.activation_func,"Training Epochs":e.training.epoch_num,Dataset:e.visual.nodeFill,"Deep Learning Framework":e.visual.nodeShape,"Hardware Acceleration":e.visual.hardwareAcceleration,"Paper PatterM n":e.visual.pattern,"Life Cycle":e.visual.lifeCycle,"Birth Year":e.visual.birthYear,"Color Palette":e.visual.colorPalette}} <script defer src="https://static.cloudflareinsights.com/beacon.min.js/v2b4487d741ca48dcbadcaf954e159fc61680799950996" integrity="sha512-D/jdE0CypeVxFadTejKGTzmwyV10c1pxZk/AqjJuZbaJwGMyNHY3q/mTPWqMUnFACfCTunhZUVcd4cV78dK1pQ==" data-cf-beacon='{"rayId":"7b4cce5018e4a1ea","version":"2023.3.0","b":1,"token":"6c07c178c94442f695e7a0a2aaee641a","si":100}' crossorigin="anonymous"></sc text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"nako","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! riTXtXML:com.adobe.xmp ' id='W5M0MpCehiHzreSzNTczkc9d'?> <x:xmpmeta xmlns:x='adobe:ns:meta/'> <rdf:RDF xmlns:rdf='http://www.w3.org/1999/02/22-rdf-syntax-ns#'> <rdf:Description rdf:about='' xmlns:Attrib='http://ns.attribution.com/ads/1.0/'> <rdf:li rdf:parseType='Resource'> <Attrib:Created>2023-04-08</Attrib:Created> <Attrib:ExtId>700e54e0-0c08-45M 6b-9953-c6ac4d4e64d9</Attrib:ExtId> <Attrib:FbId>525265914179580</Attrib:FbId> <Attrib:TouchType>2</Attrib:TouchType> <rdf:Description rdf:about='' xmlns:dc='http://purl.org/dc/elements/1.1/'> <rdf:li xml:lang='x-default'>Jesus - 14</rdf:li> <rdf:Description rdf:about='' xmlns:pdf='http://ns.adobe.com/pdf/1.3/'> <pdf:Author>Lion's Logistics</pdf:AuthorM <rdf:Description rdf:about='' xmlns:xmp='http://ns.adobe.com/xap/1.0/'> <xmp:CreatorTool>Canva</xmp:CreatorTool> <?xpacket end='r'?>. text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 0{"p":"sns","op":"reg","name":"bittyboners.sats"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! &1233333333333333333333333333 text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! <svg xmlns='http://www.w3.org/2000/svg' xmlns:xlink='http://www.w3.org/1999/xlink' image-rendering='pixelated' viewBox='0 0 800 800'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoCAMAAAC7IEhfAAAAY1BMVEWDPdGeUtuLQtR/Oc+rX+GSR9aHP9J7Ns12M8xyL8mkWN68dei5cOa2bOVtLMfGg+vCfem/eemaTtrIh+yvZOKnW9+YTNmVStiORdWzaeTMje7Kie3EgOqhVdzJie2xZuOuY+EssbyLAAABbUlEQVQ4y5XV7W6CQBCF4bUKSL9ABBaKCPd/lX3nuAHT9M Md4TEw0T84sK6zh21KW5/O5KI7HY9jCh6Lg67IUCWKlGCrP31LyHAtFiobkYFLDkCnDIAuVBJqjTgwUY6/ECBalFCIoZyz2TXNIaZo+QpMEPrkeNb+nzNj+SQbWJ5dFsa47KV0nGjOk1hl2B0OtrbJiobsMuzPWLuP4RcZxaY1uUpD1Pdy6oD4V7LI+JOs0aIVDJteOqI8U7NhKZoNVAhncH2Y52OVyqWveoJLzoWc4kEINPq3mTN2IWZPrScOp5JUKF5yxSoGaXFIlzCZTyGC5qroqVSXJcCptdtDkrdDcnZjcKjU7BPaGS2aFuFt1vU/K/VrdkKySC2eHgCxxm0zfNP2QaaJzm80id2iTVQgjqrTZ/8H6L6xfhv7R/ovxb497w70/of+mcN9m7hvX/Sh4Hy7/4+o+ANxHivuQ8h577oPUfTT7D3v338cvxaJNBVvwCP0AAAAASUVORK5CYII='/></foreignObject><foreignObject x='0' y='0' widM th='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAIVBMVEUAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABt0UjBAAAAC3RSTlMAYEJYVDQnGBNOTJeVFx8AAAAzSURBVCjPYxgFo2BIAvZULRdDYZdFYQUIsSZBONCACxoiBIVxqESYqeksKGgyCWgmiQAAX5gI535S03cAAAAASUVORK5CYII='/></foreignObject><g class='effect2'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:iM mage/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAHlBMVEUAAAAAAAAAAAAAAAAAAAAAtwAAawAA5wAG+BIAIyNIYzJ+AAAABHRSTlMABgkMb2rtSgAAAJlJREFUKM/dj70NwjAUhE3kERiEEYJ0DgyQx0tJZYmeJB7AhpQpGRfROfbVFLny0/3ozN9lURKcjF3agg0wzaUvqAs4W41FoQ4RGrbWg9OxlznmCIBouOozs0LS23uR9Mrz0GnyP21K3XgndxyBkAo2SFMF7TLf1irt5EF2hOyYbiXjHUkrqfx49getIZSOE3j0zAkQ2Jgd6Qvy6ySQbX+PrgAAAABJRU5ErkJggg=='/></foreignObject></g><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' srM c='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAG1BMVEUAAAAnDQislnWTg2q9qIhZVlLLtaE7NzLezLzZuBaIAAAAAXRSTlMAQObYZgAAAHtJREFUKM9jGAWDEYhiEWMsDcAiGGyOKShurKReXi6AZqSRSpqTKqogY7GSi1uasiCqYJGyiluGk6gAqqCwiktak6giFkFBVMFikKCSgCCKoGAwUFAZ3UnGRm5JphiCQBCIHh6mgYLBAujeDBdgLEUXFBQUYBQECtIZAADsZxPbfZk9RAAAAABJRU5ErkJggg=='/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUM hEUgAAACgAAAAoBAMAAAB+0KVeAAAAD1BMVEUAAACZ5VA3lG5qvjAnDQgb2TL3AAAAAXRSTlMAQObYZgAAAClJREFUKM9jGAWjgB5AWVDQ0QhNjAkoKIIhaChs5KyALiiswKDIMIgBAN5GAncQdEsNAAAAAElFTkSuQmCC'/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAG1BMVEUAAAAAAAAyPDlZVlIiIDT///+brbf5DwSsMjIRdaP7AAAAAXRSTlMAQObYZgAAAFdJREFUKM9jGAWDEQhgEWMUwSbo6IKpXMRRKLExCV1QSUxRUAlVkNFFWTGwMVAQVdDJ2DCwMM FBIAFVQ2FiwUEjIEF1QsVBZkBFFkAEoKKgsgGqoIMPwBgCeRAo+7AxeoAAAAABJRU5ErkJggg=='/></foreignObject><g class='effect'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAJ1BMVEUAAAAnDQich2aslnW9qIiTg2o7NzLezLxZVlIAAADsmJnNd3jDXV6RqQwDAAAAAXRSTlMAQObYZgAAAFNJREFUKM9jGAWMgggKIbhaEASkF6IolelQcS931hFA1Z9kbOJipIYuaBrsYhqGKeiOKaga7FKkiOamDGVjo5mNaC4VbFLSnAnTjRAFAoZRMLAAAEOoDnwejNL6AAAAAEM lFTkSuQmCC'/></foreignObject></g><g class='effect'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAJ1BMVEUAAAAPIgMpUg6yrHVBZCFefjZukz24yW1dgDDZ04jMyIGAq0RTXSwrzFg1AAAAAXRSTlMAQObYZgAAAEVJREFUKM9jGMxAUFBQAF2McbKZy0Z0QSnT0JBgATSFGkeMXY0V0QSbnYxcnNEEhZTU0spdQgXQ7RZUEhISYBgFo4AwAAAXZwkxfwJvhQAAAABJRU5ErkJggg=='/></foreignObject></g><foreignObject x='0' y='0' width='800' heighM t='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoAgMAAADxkFD+AAAADFBMVEUAAAAnDQhZVlI7NzL2q9zyAAAAAXRSTlMAQObYZgAAABdJREFUGNNjGAUDBKocX8KYoY6hpOoGAJNDApChKFBbAAAAAElFTkSuQmCC'/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoAgMAAADxkFD+AAAADFBMVEUAAAAAAADPIwA8kgA9MDpPAAAAAXRSTlMAQObYZgAAAM DVJREFUGNNjGAUoQADOYkyBM9lTHODM1AlwZiycySgLZzKwIPQxYGemIphiDnAmG4LJSNidAJcXBfFZ89COAAAAAElFTkSuQmCC'/></foreignObject><g class='effect2'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAJFBMVEUAAAD39/fi8N/M2ckCrvUAmvD7aVzrPTLx9fTt9Ozp7ez0UUBMLYYDAAAAAXRSTlMAQObYZgAAADFJREFUKM9jGAUUA2NjJSVBQUEUMWYGUxcnwbJENKWmIU6M1eiCxkpaHIKSDKNgCAMAKvoE3fxR7N0AAAAASUVORK5CYII='/></foreignOMi bject></g><style> .effect { animation: 0.75s effect infinite alternate ease-in-out; } @keyframes effect { from { transform: translateY(0px); } to { transform: translateY(2.5%); } }.effect2 { animation: 0.75s effect2 infinite alternate ease-in-out; } @keyframes effect2 { from { transform: translateY(0px); } to { transform: translateY(1.5%); } } </style> </svg>h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 ,{"p":"sns","op":"reg","name":"BITCOIN.sats"}h! text/plain;charset=utf-8 ){"p":"sns","op":"reg","name":"DOGE.sats"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! <svg xmlns='http://www.w3.org/2000/svg' xmlns:xlink='http://www.w3.org/1999/xlink' image-rendering='pixelated' viewBox='0 0 800 800'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoCAMAAAC7IEhfAAAAV1BMVEW17XO47niw62zW9bHQ9KSy7G+77n3e97/b97vZ9rfT9KrJ8pa+74Gt62io6WLB8Ifg+MLF8Y7M85ur6mWm6V6i51nN9KDH8ZKe51bD8YvY9rXA8ISk6FvHn0/rAAABS0lEQVQ4y5XVwVKEMBCE4RFlNWpQCIiBff/n9M/MVKja09gXPXzVDbuQlV+ybM fd1naZSch56ci5lmtb1vm3NiDmYqnEUzziqhZqUy6l66lF7ScEx29ntdvsk/OmUeaTQZw7W0PmlORuGmqRTuqMNVeusqRVLa5fSnbJ53z80+z4r7VK4D3cw1LL8kGXBQl1yR8DiDoZ68WChLguQ4cvB3j3QSzIuNuwO9uyBurRxscKz4qhDHEdKx8E/lCLraZVSKGzD2gdLHqh2tnEqi+TBCs2l9OZJyaRVDlnashZ290q61Mq2LcPILXOFFLJrzCjrVHKV3Pg4iC9roblvolIrfdugLXshjFilbxvUS/Rldy59m4t8gOkRpn/D+HT8ZuIfT/gDD3+F4Yci/JiFH9zwqxB+ucKva/gACB8p4UMqfOxFD9Lw0Rw/7MM/H39y5Ub9cztS7AAAAABJRU5ErkJggg=='/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtM ml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAIVBMVEUAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABt0UjBAAAAC3RSTlMAYEJYVDQnGBNOTJeVFx8AAAAzSURBVCjPYxgFo2BIAvZULRdDYZdFYQUIsSZBONCACxoiBIVxqESYqeksKGgyCWgmiQAAX5gI535S03cAAAAASUVORK5CYII='/></foreignObject><g class='effect2'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoCAMAAAC7IEhfM 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 aEc+WgosKMcwDAAAAABJRU5ErkJggg=='/></foreignObject></g><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAG1BMVEUAAAAnDQislnWTg2q9qIhZVlLLtaE7NzLezLzZuBaIAAAAAXRSTlMAQObYZgAAAHtJREFUKM9jGAWDEYhiEWMsDcAiGGyOKShurKReXi6AZqSRSpqTKqogY7GSi1uasiCqYJGyiluGk6gAqqCwiktak6giFkFBVMFikKCSgCCKoGAwUFAZ3UnGRm5JphiCQBCIHh6mgYLBAujeDBdgLEUXFBQUYBQECtIZAADsZxPbfZk9RAAAAABJRU5ErkJggg=='/></foM reignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAD1BMVEUAAACZ5VA3lG5qvjAnDQgb2TL3AAAAAXRSTlMAQObYZgAAAClJREFUKM9jGAWjgB5AWVDQ0QhNjAkoKIIhaChs5KyALiiswKDIMIgBAN5GAncQdEsNAAAAAElFTkSuQmCC'/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAM AANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAElBMVEUAAABXKySPVjtmOTH/2037rx60EnRrAAAAAXRSTlMAQObYZgAAAC1JREFUKM9jGAVDBihiEzQSxCLIrCQoKCiALmqs6qKMqdZUxQBTkDWEYRSQAgBOTwJu6N9rJAAAAABJRU5ErkJggg=='/></foreignObject><g class='effect'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAJ1BMVEUAAAAnDQich2aslnW9qIiTg2o7NzLezLxZVlIAAADsmJnNd3jDXV6RqQwDAAAAAXRSTlMAQObYZgAAAFNJREFUKM9jGAWMgggKIbM haEASkF6IolelQcS931hFA1Z9kbOJipIYuaBrsYhqGKeiOKaga7FKkiOamDGVjo5mNaC4VbFLSnAnTjRAFAoZRMLAAAEOoDnwejNL6AAAAAElFTkSuQmCC'/></foreignObject></g><g class='effect'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoAQMAAAC2MCouAAAAA1BMVEUAAACnej3aAAAAAXRSTlMAQObYZgAAAAtJREFUCNdjGGEAAADwAAFOldjfAAAAAElFTkSuQmCC'/></foreignObject></g><foreignObject x='0' y='0' width='800' height='800'><img xmlns='M http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoAgMAAADxkFD+AAAADFBMVEUAAAABJT4AFiUHQ23+DLtgAAAAAXRSTlMAQObYZgAAABtJREFUGNNjGAUDAwK+NtWIQJiqYU1TE0jUDgDx8wRKlG8mXgAAAABJRU5ErkJggg=='/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoAgMAAADxkFD+AAAADFBMVEUAAAAAAAA8kgDPIwDJzSIsAAAAAXRSTlMAQObYZgAAADNJREFUGNNjIM BowIphsDjRnSjKQxUyBs1gQTEkk5gVszBQHBBObWYwIJnsAgumAFDb0BgDJwgiAQQ0KcAAAAABJRU5ErkJggg=='/></foreignObject><g class='effect2'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoAgMAAADxkFD+AAAACVBMVEUAAAAAAAD///+D3c/SAAAAAXRSTlMAQObYZgAAABVJREFUGNNjGIqAsUECznQQYRiJAADtwwDvRmwtWAAAAABJRU5ErkJggg=='/></foreignObject></g><style> .effect { animation: 0.75s effect infinite alternate ease-in-out; M } @keyframes effect { from { transform: translateY(0px); } to { transform: translateY(2.5%); } }.effect2 { animation: 0.75s effect2 infinite alternate ease-in-out; } @keyframes effect2 { from { transform: translateY(0px); } to { transform: translateY(1.5%); } } </style> </svg>h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"nako","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"nako","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! *{"p":"sns","op":"reg","name":"idr0p.sats"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 @{"p":"brc-20","op":"deploy","tick":" ","max":"300","lim":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"nako","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":" text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":" text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/html;charset=utf-8 <meta charset=UTF-8> <script id=snippet-random-code type=text/javascript>let seed=window.location.href.split('/').find(t=>t.includes('i0'));if(seed==null){const alphabet="0123456789abcdefghijklmnopqrstuvwsyz";seed=new URLSearchParams(window.location.search).get("seed")||Array(64).fill(0).map(_=>alphabet[(Math.random()*alphabet.length)|0]).join('')+"i0";}else{let pattern="seed=";for(let i=0;i<seed.length-pattern.lengM th;++i){if(seed.substring(i,i+pattern.length)==pattern){seed=seed.substring(i+pattern.length);break;}}} function cyrb128($){let _=1779033703,u=3144134277,i=1013904242,l=2773480762;for(let n=0,r;n<$.length;n++)_=u^Math.imul(_^(r=$.charCodeAt(n)),597399067),u=i^Math.imul(u^r,2869860233),i=l^Math.imul(i^r,951274213),l=_^Math.imul(l^r,2716044179);return _=Math.imul(i^_>>>18,597399067),u=Math.imul(l^u>>>22,2869860233),i=Math.imul(_^i>>>17,951274213),l=Math.imul(u^l>>>19,2716044179),[(_^u^i^l)>>>0,(u^_)>>>0,(i^_)>>>0,(l^M function sfc32($,_,u,i){return function(){u>>>=0,i>>>=0;var l=($>>>=0)+(_>>>=0)|0;return $=_^_>>>9,_=u+(u<<3)|0,u=(u=u<<21|u>>>11)+(l=l+(i=i+1|0)|0)|0,(l>>>0)/4294967296}} let mathRand=sfc32(...cyrb128(seed));</script> <style>html,body{position:fixed;top:0;right:0;bottom:0;left:0;color:#fff;background-color:#fff;display:flex;justify-content:center;align-items:center;margin:0;padding:0;font-size:.8em}canvas{object-fit:contain;max-height:100%;max-width:100%}</style> <canvas id=cnv></canvas> cript defer src="https://static.cloudflareinsights.com/beacon.min.js/v2b4487d741ca48dcbadcaf954e159fc61680799950996" integrity="sha512-D/jdE0CypeVxFadTejKGTzmwyV10c1pxZk/AqjJuZbaJwGMyNHY3q/mTPWqMUnFACfCTunhZUVcd4cV78dK1pQ==" data-cf-beacon='{"rayId":"7b4cf1b46885a232","version":"2023.3.0","b":1,"token":"6c07c178c94442f695e7a0a2aaee641a","si":100}' crossorigin="anonymous"></script> <script type=text/javascript>let myTitle=" console.log(myTitle+" | smldms 2023.03") ocument.getElementById('cnv');const ctx=cnv.getContext('2d');cnv.width=1280;cnv.height=1280*1.4142;const url='https://api.blockchain.info/stats';let hash_rate,btcPrice,totalBTC,tradeVol,mapBlock,mapVol,mapPrice;const plt={n:mathRand(),clr:[],name:""} plt.clr=chooseRdm([["#172E73","#244BBF","#D9CC1A","#D92B2B","#73620D"],["#593B02","#A67314","#0D0D0D","#F2E96D","#F2C438"],["#0D0D0D","#8C8C8C","#404040","#F2F2F2","#BFBFBF"],["#00040D","#0B1226","#2A2D40","#F2F2F2","#8F94A6"],["#958976","#DDDCC5","#1D2326","#611427","M #6A6A61"],["#C2ACF2","#EBEEF2","#483473","#9E82D9","#7756BF"],["#BFBFBF","#F2F2F2","#262626","#8C8C8C","#595959"],["#193441","#91AA9D","#3E606F","#D1DBBD","#FCFFF5"],["#0D1621","#03718A","#F272AE","#82D9D0","#F0F2A0"],["#555259","#8C837B","#BF3F57","#0D0D0D","#F2DAC4"],["#52591E","#818C30","#0D0D0D","#DFF250","#F2E96B"],["#0D0000","#26081C","#F24BD6","#400E2E","#8C1F66"],["#000000","#424242","#000000","#BF0000","#E0E5E4"],["#251726","#F2DCC9","#592E1E","#BF5F0B","#F2B66D"],["#383040","#D9C8B4","#BF4163","#383040","M #D9C8B4"],["#001715","#012E26","#034159","#038C3E","#0CF25D"],["#131617","#30302F","#6C733D","#013B35","#05E8D1"],["#1A1E26","#283040","#405173","#5D75A6","#B9B4D9"],["#01132B","#023373","#0367A6","#F2E205","#D9B504"],["#13181A","#1D2426","#B6E1F2","#F25E5E","#404040"],["#211D1A","#383430","#A69E97","#F2EAE4","#736258"],["#000000","#424242","#898A8A","#E0E5E4","#0D0D0D"],]) const area={n:mathRand(),val:12,};if(area.n<0.25){area.val=6} else if(area.n<0.5){area.val=8} else if(area.n<0.75){area.val=12} let margin=cnv.height/6.18;window.$generativeTraits={"Palette":plt.clr,'Base Area':area.val,} console.log(window.$generativeTraits) const IsoX=cnv.width/2;const IsoY=cnv.height/2;let IsoW=4;let IsoH=IsoW/2;function rdmColor(palette,a){const couleurs=palette;const couleurHex=couleurs[Math.floor(mathRand()*couleurs.length)];const alpha=a;const r=parseInt(couleurHex.slice(1,3),16);const g=parseInt(couleurHex.slice(3,5),16);const b=parseInt(couleurHex.slice(5,7),16);const couleurRGBA=`rgba(${r},${g},${b},${alpha})`;M return couleurRGBA;} function isoToScreenX(localX,localY){return IsoX+(localX-localY)*IsoW;} function isoToScreenY(localX,localY){return IsoY+(localX+localY)*IsoH;} function drawCube(isoX,isoY){ctx.lineWidth=0.5;ctx.strokeStyle=rdmColor(plt.clr,mathRand()*200);if(mathRand()<0.25){ctx.shadowColor=rdmColor(plt.clr,mathRand()*25);ctx.shadowBlur=mathRand()*100;} else{ctx.shadowColor=rdmColor(plt.clr,0);ctx.shadowBlur=0;} ctx.fillStyle=plt.clr[2];ctx.beginPath();ctx.moveTo(isoToScreenX(isoX,isoY),isoToScreenY(isoX,isoY)M );ctx.lineTo(isoToScreenX(isoX,isoY-1),isoToScreenY(isoX,isoY-1));ctx.lineTo(isoToScreenX(isoX-1,isoY-1),isoToScreenY(isoX-1,isoY-1));ctx.lineTo(isoToScreenX(isoX-1,isoY),isoToScreenY(isoX-1,isoY));ctx.closePath();ctx.fill();ctx.stroke();ctx.fillStyle=plt.clr[3];ctx.beginPath();ctx.moveTo(isoToScreenX(isoX+1,isoY+1),isoToScreenY(isoX+1,isoY+1));ctx.lineTo(isoToScreenX(isoX,isoY),isoToScreenY(isoX,isoY));ctx.lineTo(isoToScreenX(isoX-1,isoY),isoToScreenY(isoX-1,isoY));ctx.lineTo(isoToScreenX(isoX,isoY+1),isoToScreenYM (isoX,isoY+1));ctx.closePath();ctx.fill();ctx.stroke();ctx.strokeStyle=plt.clr[3];ctx.fillStyle=plt.clr[2];ctx.beginPath();ctx.moveTo(isoToScreenX(isoX+1,isoY+1),isoToScreenY(isoX+1,isoY+1));ctx.lineTo(isoToScreenX(isoX+1,isoY),isoToScreenY(isoX+1,isoY));ctx.lineTo(isoToScreenX(isoX,isoY-1),isoToScreenY(isoX,isoY-1));ctx.lineTo(isoToScreenX(isoX,isoY),isoToScreenY(isoX,isoY));ctx.closePath();ctx.fill();ctx.stroke();} function drawCubes(x,y,zone,h){ctx.save() for(let x=0;x<zone;x++){for(let y=0;y<M zone;y++){let nbr=Math.floor(mathRand()*mapPrice);for(let z=0;z<nbr*h;z++){drawCube(x-z,y-z);}}} function drawScene(time){fetch(url).then(response=>response.json()).then(data=>{console.log(data) const maxBtcPrice=500000;btcPrice=Math.floor(data.market_price_usd);const constrainedBtcPrice=Math.min(btcPrice,maxBtcPrice);mapPrice=mapRange(constrainedBtcPrice,0,maxBtcPrice,8,25) const maxTradeVol=50000;tradeVol=Math.floor(data.trade_volume_btc);const constrainedTradeVol=Math.min(tradeVol,maxTradeVol);mapM Vol=mapRange(constrainedTradeVol,0,maxTradeVol,1,50) mapTotalMinted=mapRange(totalBTC,1900000,21000000,1,10) totalBTC=Math.floor(data.totalbc/100000000);let mint=21000000-totalBTC;let mapBTC=mapRange(totalBTC,19000000,21000000,cnv.height/10,cnv.height/25) hash_rate=data.hash_rate;let minValue=500000000;let maxValue=800000000000;let mappedHashRate=mapRange(hash_rate,minValue,maxValue,cnv.height*0.01314,cnv.height*0.01618);console.log('HRATE: '+hash_rate+'|||||||'+mappedHashRate+' PRIX: '+btcPrice) ber=btcPrice.toLocaleString('us-US',{style:'currency',currency:'USD',minimumFractionDigits:0});const totalNumber=totalBTC.toLocaleString('us-US',{maximumFractionDigits:0});const restMint=mint.toLocaleString('us-US',{maximumFractionDigits:0});const tradeNumber=tradeVol.toLocaleString('us-US',{maximumFractionDigits:0});const centerX=cnv.width/2;const centerY=cnv.height/2;const radius=Math.sqrt(Math.pow(centerX,2)+Math.pow(centerY,2));const gradient=ctx.createRadialGradient(centerX,centerY,0,centerX,centerY,radius);grM adient.addColorStop(0,plt.clr[1]);gradient.addColorStop(1,plt.clr[0]);ctx.fillStyle=gradient;ctx.fillRect(0,0,cnv.width,cnv.height);if(mathRand()<0.5){IsoW=mappedHashRate;} else{IsoW=-mappedHashRate;} let scl=mapBTC;for(let x=-cnv.width/2+margin*1.5;x<cnv.width/2-margin;x+=scl){for(let y=-cnv.height/2+margin*1.5;y<cnv.height/2-margin;y+=scl){funkyBezier(x,y) drawCubes(x,y,Math.floor(mathRand()*area.val+2),mathRand());}} addGrain(cnv,31.4)}).catch(error=>{console.error(error);});} al(drawScene,3600000);function funkyBezier(x,y){ctx.save() ctx.translate(cnv.width/2,cnv.height/2) for(let i=0;i<mapVol;i++){const dirX=mathRand()*2-1;const dirY=mathRand()*2-1;const len=mathRand()*cnv.height/3+5;const x1=x+len*(mathRand()*0.5+0.2)*dirX;const y1=y+len*(mathRand()*0.5+0.2)*dirY;const x2=x+len*(mathRand()*0.5+0.5)*dirX;const y2=y+len*(mathRand()*0.5+0.5)*dirY;const x3=x+len*(mathRand()*0.5+0.8)*dirX;const y3=y+len*(mathRand()*0.5+0.8)*dirY;for(let halo=mathRand()*25;halo>0;halo--){ctx.beginPath();ctxM .moveTo(x,y);ctx.bezierCurveTo(x1,y1,x2,y2,x3,y3);ctx.filter='blur('+halo+'px)' ctx.strokeStyle=chooseRdm(plt.clr);ctx.lineWidth=mathRand()*2;ctx.lineCap="round";ctx.stroke();}} function mapRange(value,in_min,in_max,out_min,out_max){return(value-in_min)*(out_max-out_min)/(in_max-in_min)+out_min;} function addGrain(canvas,graininess){const ctx=cnv.getContext('2d');const width=cnv.width;const height=cnv.height;const pixels=ctx.getImageData(0,0,width,height);for(let i=0;i<pixels.data.length;i+=4){const M r=pixels.data[i];const g=pixels.data[i+1];const b=pixels.data[i+2];const alpha=pixels.data[i+3];const random=mathRand();const offset=(random-0.5)*graininess;pixels.data[i]=Math.max(0,Math.min(255,r+offset));pixels.data[i+1]=Math.max(0,Math.min(255,g+offset));pixels.data[i+2]=Math.max(0,Math.min(255,b+offset));pixels.data[i+3]=alpha;} ctx.putImageData(pixels,0,0);} function mathRandBetween(a,b){if(!b){return mathRand()*a} return mathRand()*(b-a)+a} function chooseRdm(arr){const randomIndex=Math.floor(mathRand()*arr.2length);return arr[randomIndex];}</script> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 ){"p":"sns","op":"reg","name":"ELON.sats"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":" text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/html;charset=utf-8 <meta charset="UTF-8"> <title>Bitcoin Flux by SMLDMS</title> <script id="snippet-random-code" type="text/javascript"> // DO NOT EDIT THIS SECTION let seed = window.location.href.split('/').find(t => t.includes('i0')); if (seed == null) { const alphabet = "0123456789abcdefghijklmnopqrstuvwsyz"; seed = new URLSearchParams(window.location.search).get("seed") || Array(64).fill(0).map(_ => alphabet[(MathM .random() * alphabet.length) | 0]).join('') + "i0"; let pattern = "seed="; for (let i = 0; i < seed.length - pattern.length; ++i) { if (seed.substring(i, i + pattern.length) == pattern) { seed = seed.substring(i + pattern.length); break; function cyrb128($) { let _ = 1779033703, u = 3144134277, i = 1013904242, l = 2773480762; for (leM t n = 0, r; n < $.length; n++) _ = u ^ Math.imul(_ ^ (r = $.charCodeAt(n)), 597399067), u = i ^ Math.imul(u ^ r, 2869860233), i = l ^ Math.imul(i ^ r, 951274213), l = _ ^ Math.imul(l ^ r, 2716044179); return _ = Math.imul(i ^ _ >>> 18, 597399067), u = Math.imul(l ^ u >>> 22, 2869860233), i = Math.imul(_ ^ i >>> 17, 951274213), l = Math.imul(u ^ l >>> 19, 2716044179), [(_ ^ u ^ i ^ l) >>> 0, (u ^ _) >>> 0, (i ^ _) >>> 0, (l ^ _) >>> 0] function sfc32($, _, u, i) { u >>>= 0, i >>>= 0; var l = ($ >>>= 0) + (_ >>>= 0) | 0; return $ = _ ^ _ >>> 9, _ = u + (u << 3) | 0, u = (u = u << 21 | u >>> 11) + (l = l + (i = i + 1 | 0) | 0) | 0, (l >>> 0) / 4294967296 let mathRand = sfc32(...cyrb128(seed)); position: fixed; right: 0; bottom: 0; left: 0; color: rgb(255, 255, 255); background-color: rgb(255, 255, 255); display: flex; justify-content: center; align-items: center; margin: 0; padding: 0; font-size: 0.8em; object-fit: contain; background-color: rgb(255, 255, 255); max-height: 100%; max-width: 100%; display: inline-block; opacity: 0.75; padding: 1.5vh; background-color: black; color: rgb(255, 255, 255); position: absolute; font-family: Impact, Haettenschweiler, 'Arial Narrow Bold', sans-serif; text-align: CENTER; #progress h1 { font-size: 10vh; margin-top: -0.618em; #progress h2 { font-size: 5vh; <canvas id="cnv"> <div id="progress"></div> <script defer src="https://static.cloudflareinsights.com/beacon.min.js/v2b4487d741ca48dcbadcaf954e159fc61680799950996" integrity="sha512-D/jdE0CypeVxFadTejKGTzmwyV10c1pxZk/AqjJuZbaJwGMyNHY3q/mTPWqMUnFACfCTunhZUVcd4cV78dK1pQ==" data-cf-beacon='{"rayId":"7b4cf1d05e12a22f","version":"2023.3.0","b":1,"token":"6c07c178c94442f695e7a0a2aaee641a","si":100}' crossorigin="anonymous"></script> <script type="text/javascript"> n: mathRand(), palette.clr = chooseRandom([ ["#D9C49C", "#BFB39B", "#D9CCB4", "#594A3C", "#260906"], ["#171F26", "#3B4B59", "#96B9D9", "#728EA6", "#D5E7F2"], ["#283959", "#364A73", "#6D8BA6", "#99B4BF", "#F0F2EB"], ["#5C5751", "#9C9389", "#DBCFC1", "#C2B7AB", "#E8DBCD"], ["#23282B", "#2D353B", "#778899", "#DFE5F2", "#EBF0F5"], ["#F2B807", "#F2C84B", "#F2D57E", "#F2A007", "#BF5B04"], ["#D9D9D9", "#BFBFBF", "#A6A6A6", "#7373M ["#D9B0B3", "#A65858", "#F28585", "#D98282", "#F2CECE"], ["#BFBFBF", "#8C8C8C", "#404040", "#262626", "#0D0D0D"], ["#A6A6A6", "#737373", "#404040", "#262626", "#0D0D0D"], ["#68736A", "#818C83", "#3A403A", "#D2D9D2", "#0D0D0D"], ["#F2F2F2", "#BFBFBF", "#8C8C8C", "#262626", "#0D0D0D"], ["#585459", "#3B3340", "#D9CBA0", "#A6977B", "#F2E2CE"], ["#D9A404", "#D98E04", "#8C4E03", "#592202", "#260B01"], ["#232226", "#D9C7B8", "#F2E3D5"M , "#A69992", "#595959"], ["#A60311", "#73020C", "#400101", "#260101", "#0D0D0D"], ["#ffffff", "#8C8C8C", "#000000", "#262626", "#0D0D0D"], n: mathRand(), if (mode.n < 0.333333) { mode.val = 1; mode.name = 'VERTICAL' else if (mode.n < 0.666666) { mode.val = 0.5; mode.name = 'RANDOM' mode.val = 0; mode.name = 'HORIZONTAL' const url = 'https://api.blockchain.info/stats'; let btcPrice, totalBTC, tradeVol, blockS, mapBlock, mapVol, mapPrice; const maxBtcPrice = 1000000; const maxTradeVol = 50000; const ctx = document.getElementById("cnv").getContext("2d"); ////////////////////// let myTitle = "Bitcoin Flux" console.log(myTitle + " | smldms 2023.03") // let complexity = Math.floor(mathRand() * 4 + 1) let complexity = chooseRandom([1, 1, 1, 1, 1, 2, 3, 4, 5, M window.$generativeTraits = { "Palette": palette.clr, "Mode": mode.name, "Complexity": complexity console.log(window.$generativeTraits) let s = 1080 * 2; cnv.height = s * 1.4142 let padding; let longSide, shortSide; .then(response => response.json()) .then(data => { console.log(data) btcPrice = Math.floor(data.market_price_usd); totalBTC = MathM .floor(data.totalbc / 100000000); tradeVol = Math.floor(data.trade_volume_btc); blockS = data.blocks_size; mapBlock = mapRange(blockS, 0, 1000000000, 1, 500) mapTotalMinted = mapRange(totalBTC, 1900000, 21000000, 1, 10) const constrainedVolume = Math.min(tradeVol, maxTradeVol); mapVol = mapRange(tradeVol, 0, maxTradeVol, 6.18, 50) const constrainedBtcPrice = Math.min(btcPrice, maxBtcPrice); mapPrice = mapRange(coM nstrainedBtcPrice, 10000, maxBtcPrice, 2, 8) let mint = 21000000 - totalBTC; longSide = cnv.width shortSide = cnv.height padding = shortSide / mapVol; ctx.save() ctx.fillStyle = chooseRandom(palette.clr); ctx.fillRect(0, 0, cnv.width, cnv.height) ctx.fill() ctx.restore() createCell(padding, padding, longSide - padding * 2, shortSide - padding * 2, mapPrice) addGrain(cnv, 23)M const btcNumber = btcPrice.toLocaleString('us-US', { style: 'currency', currency: 'USD', minimumFractionDigits: 0 }); const totalNumber = totalBTC.toLocaleString('us-US', { maximumFractionDigits: 0 }); const restMint = mint.toLocaleString('us-US', { maximumFractionDigits: 0 }); const tradeNumber = tradeVol.toLocaleString('us-US', { maximumFractionDigits: 0 }); progress('<h2>TOTAL OF BITCOINS</h2><h1>' + totalNumber + '</h1><h2><h2>REST TO MINT</hM 2><h1>' + restMint + '</h1><h2>PRICE</h2><h1>' + btcNumber + '</h1><h2>TRADE VOLUME IN BTC</h2><h1>' + tradeNumber + '</h1>'); progressClear() .catch(error => { console.error(error); progress('<h1>LOADING IS LONGER THAN USUAL</h1> <h2> PLEASE RESTART</h2>'); progressShow() function createCell(posX, posY, w, h, depth) { if (depth > 0) { if (mathRand() > mode.val) { createCell(posX, poM sY, w, h / 2, depth - 1); createCell(posX, posY + h / 2, w, h / 2, depth - 1); } else { createCell(posX, posY, w / 2, h, depth - 1); createCell(posX + w / 2, posY, w / 2, h, depth - 1); for (let i = 1; i <= complexity; i += 0.1) { linearGradientFill(posX + w / randBetween(1, 5), posY, posX + w / randBetween(1, 5), posY + h); const rectX = posX + (w / 2) - (w / i / 2); const rectY = posY + (h / 2) - (h / i / 2); ctx.fillRect(rectX, rectY, w / i, h / i); ctx.fill(); ctx.textAlign = "center"; function linearGradientFill(x1, y1, x2, y2) { const gradient = ctx.createLinearGradient(x1, y1, x2, y2); let maxStep = mathRand() * mapBlock for (let step = 0; step <= maxStep; step++) { let mapper = mapRange(step, 0, maxStep, 0, 1) gradienM t.addColorStop(mathRand() * mapper, chooseRandom(palette.clr)); ctx.fillStyle = gradient; function mapRange(value, inputMin, inputMax, outputMin, outputMax) { return ((value - inputMin) * (outputMax - outputMin)) / (inputMax - inputMin) + outputMin; function randBetween(a, b) { return mathRand() * a return mathRand() * (b - a) + a function chooseRandom(arr) { const randomIndex = MaM th.floor(mathRand() * arr.length); return arr[randomIndex]; function addGrain(canvas, graininess) { const ctx = canvas.getContext('2d'); const width = canvas.width; const height = canvas.height; const pixels = ctx.getImageData(0, 0, width, height); for (let i = 0; i < pixels.data.length; i += 4) { const r = pixels.data[i]; const g = pixels.data[i + 1]; const b = pixels.data[i + 2]; const alpha =M pixels.data[i + 3]; const random = mathRand(); const offset = (random - 0.5) * graininess; pixels.data[i] = Math.max(0, Math.min(255, r + offset)); pixels.data[i + 1] = Math.max(0, Math.min(255, g + offset)); pixels.data[i + 2] = Math.max(0, Math.min(255, b + offset)); pixels.data[i + 3] = alpha; ctx.putImageData(pixels, 0, 0); ///////////////SAVE function saveCanvasAsPNG(canvas) { ment.addEventListener('keydown', function (event) { if (event.key === 's' || event.key === 'S' || event.key === 'd' || event.key === 'D') { const ctx = canvas.getContext('2d'); const width = canvas.width; const height = canvas.height; const pixelRatio = (event.key === 'd' || event.key === 'D') ? window.devicePixelRatio * 8 : window.devicePixelRatio; const canvasCopy = document.createElement('canvas'); canvasCopy.width = width * pixelRatio; canvasCopy.height = height * pixelRatio; const ctxCopy = canvasCopy.getContext('2d'); ctxCopy.imageSmoothingEnabled = false; ctxCopy.drawImage(canvas, 0, 0, width, height, 0, 0, width * pixelRatio, height * pixelRatio); const url = canvasCopy.toDataURL('image/png'); const link = document.createElement('a'); link.download = 'canvas.png'; link.hM link.click(); saveCanvasAsPNG(cnv); let spacePressed = false; document.addEventListener('keydown', function (event) { if (event.code === 'Space' && !spacePressed) { progressShow() spacePressed = true; document.addEventListener('keyup', function (event) { progressClear() if (event.code === 'Space') { spacePressed = false; /////////////PROGRESS async function progress(message) { document.body.style.cursor = 'crosshair'; document.getElementById("progress").innerHTML = message; progressColor = document.getElementById("progress"); // progressColor.style.backgroundColor = chooseRandom(palette.clr); await new Promise((fn => setTimeout(fn, 1))); async function progressClear() { document.body.style.cursor = 'default'; document.getElementById("progress")MJ .style.display = 'none'; await new Promise((fn => setTimeout(fn, 1))); async function progressShow() { document.body.style.cursor = 'default'; document.getElementById("progress").style.display = 'block'; await new Promise((fn => setTimeout(fn, 1))); text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":" text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 .{"p":"sns","op":"reg","name":"mytheresa.sats"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! <svg xmlns='http://www.w3.org/2000/svg' xmlns:xlink='http://www.w3.org/1999/xlink' image-rendering='pixelated' viewBox='0 0 800 800'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoCAMAAAC7IEhfAAAAY1BMVEWDPdGeUtuLQtR/Oc+rX+GSR9aHP9J7Ns12M8xyL8mkWN68dei5cOa2bOVtLMfGg+vCfem/eemaTtrIh+yvZOKnW9+YTNmVStiORdWzaeTMje7Kie3EgOqhVdzJie2xZuOuY+EssbyLAAABbUlEQVQ4y5XV7W6CQBCF4bUKSL9ABBaKCPd/lX3nuAHT9M Md4TEw0T84sK6zh21KW5/O5KI7HY9jCh6Lg67IUCWKlGCrP31LyHAtFiobkYFLDkCnDIAuVBJqjTgwUY6/ECBalFCIoZyz2TXNIaZo+QpMEPrkeNb+nzNj+SQbWJ5dFsa47KV0nGjOk1hl2B0OtrbJiobsMuzPWLuP4RcZxaY1uUpD1Pdy6oD4V7LI+JOs0aIVDJteOqI8U7NhKZoNVAhncH2Y52OVyqWveoJLzoWc4kEINPq3mTN2IWZPrScOp5JUKF5yxSoGaXFIlzCZTyGC5qroqVSXJcCptdtDkrdDcnZjcKjU7BPaGS2aFuFt1vU/K/VrdkKySC2eHgCxxm0zfNP2QaaJzm80id2iTVQgjqrTZ/8H6L6xfhv7R/ovxb497w70/of+mcN9m7hvX/Sh4Hy7/4+o+ANxHivuQ8h577oPUfTT7D3v338cvxaJNBVvwCP0AAAAASUVORK5CYII='/></foreignObject><foreignObject x='0' y='0' widM th='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAIVBMVEUAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABt0UjBAAAAC3RSTlMAYEJYVDQnGBNOTJeVFx8AAAAzSURBVCjPYxgFo2BIAvZULRdDYZdFYQUIsSZBONCACxoiBIVxqESYqeksKGgyCWgmiQAAX5gI535S03cAAAAASUVORK5CYII='/></foreignObject><g class='effect2'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:iM mage/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAJ1BMVEUAAAA7DSGAGkbWeoWrKU6RPmmwVnbUMS7RQlr/ztD1VUT3mp7yXmDWFxMcAAAAAXRSTlMAQObYZgAAALhJREFUKM9joCdgFAASAoICKILChgIMjIbTC1EUmgYnCkqLFxuiCaYJLyw3FBBE0W6alphYJcBoLICsVDA0LapKUNgyEEWpaNhuU2fjtGkCKPqVlFRDQlxDkAQZLY0KGJRAAElQ2NKoCsNHwlOUqhTQBUVmOKtjCvZgCjK69FgaYQh6uExqYsBQaayhgGm7RhOmoFATUDemoBKmoISSAxaV2AQZlRQYsCglKIjQz4BNKdGCjAyDHQAAC+UeIW7W7F8AAAAASUVORK5CYII='/></foreignObject></g><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://wwM w.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAG1BMVEUAAAAnDQislnWTg2q9qIhZVlLLtaE7NzLezLzZuBaIAAAAAXRSTlMAQObYZgAAAHtJREFUKM9jGAWDEYhiEWMsDcAiGGyOKShurKReXi6AZqSRSpqTKqogY7GSi1uasiCqYJGyiluGk6gAqqCwiktak6giFkFBVMFikKCSgCCKoGAwUFAZ3UnGRm5JphiCQBCIHh6mgYLBAujeDBdgLEUXFBQUYBQECtIZAADsZxPbfZk9RAAAAABJRU5ErkJggg=='/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='80M 0' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAD1BMVEUAAAD3AABhAACuAAAnDQiRYqN1AAAAAXRSTlMAQObYZgAAAClJREFUKM9jGAWjgB5AWVDQ0QhNjAkoKIIhaChs5KyALiiswKDIMIgBAN5GAncQdEsNAAAAAElFTkSuQmCC'/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAG1BMVEUAAAAAAAAyPDlZVlIiIDT///+brbf5DwSsMjIRdaP7AAAAAXRSTlMAQObYZgAAAFdJREFUKM9jGAWDEQhgEWMUwM Sbo6IKpXMRRKLExCV1QSUxRUAlVkNFFWTGwMVAQVdDJ2DCwMFBIAFVQ2FiwUEjIEF1QsVBZkBFFkAEoKKgsgGqoIMPwBgCeRAo+7AxeoAAAAABJRU5ErkJggg=='/></foreignObject><g class='effect'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAJ1BMVEUAAAAnDQich2aslnW9qIiTg2o7NzLezLxZVlIAAADsmJnNd3jDXV6RqQwDAAAAAXRSTlMAQObYZgAAAFNJREFUKM9jGAWMgggKIbhaEASkF6IolelQcS931hFA1Z9kbOJipIYuaBrsYhqGKeiOKaga7FKkiOamDGM Vjo5mNaC4VbFLSnAnTjRAFAoZRMLAAAEOoDnwejNL6AAAAAElFTkSuQmCC'/></foreignObject></g><g class='effect'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAJ1BMVEUAAAAPIgMpUg6yrHVBZCFefjZukz24yW1dgDDZ04jMyIGAq0RTXSwrzFg1AAAAAXRSTlMAQObYZgAAAEVJREFUKM9jGMxAUFBQAF2McbKZy0Z0QSnT0JBgATSFGkeMXY0V0QSbnYxcnNEEhZTU0spdQgXQ7RZUEhISYBgFo4AwAAAXZwkxfwJvhQAAAABJRU5ErkJggg=='/></foreignObject>M </g><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoAgMAAADxkFD+AAAADFBMVEUAAAAnDQhZVlI7NzL2q9zyAAAAAXRSTlMAQObYZgAAABdJREFUGNNjGAUDBKocX8KYoY6hpOoGAJNDApChKFBbAAAAAElFTkSuQmCC'/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoAgMAAADxkFD+AAAADM FBMVEUAAAAAAAA8kgDPIwDJzSIsAAAAAXRSTlMAQObYZgAAADNJREFUGNNjIBowIphsDjRnSjKQxUyBs1gQTEkk5gVszBQHBBObWYwIJnsAgumAFDb0BgDJwgiAQQ0KcAAAAABJRU5ErkJggg=='/></foreignObject><g class='effect2'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoAgMAAADxkFD+AAAACVBMVEUAAAAAAAD///+D3c/SAAAAAXRSTlMAQObYZgAAABVJREFUGNNjGIqAsUECznQQYRiJAADtwwDvRmwtWAAAAABJRU5ErkJggg=='/></foreignObject></g><style> .effecMQ t { animation: 0.75s effect infinite alternate ease-in-out; } @keyframes effect { from { transform: translateY(0px); } to { transform: translateY(2.5%); } }.effect2 { animation: 0.75s effect2 infinite alternate ease-in-out; } @keyframes effect2 { from { transform: translateY(0px); } to { transform: translateY(1.5%); } } </style> </svg>h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! riTXtXML:com.adobe.xmp ' id='W5M0MpCehiHzreSzNTczkc9d'?> <x:xmpmeta xmlns:x='adobe:ns:meta/'> <rdf:RDF xmlns:rdf='http://www.w3.org/1999/02/22-rdf-syntax-ns#'> <rdf:Description rdf:about='' xmlns:Attrib='http://ns.attribution.com/ads/1.0/'> <rdf:li rdf:parseType='Resource'> <Attrib:Created>2023-04-08</Attrib:Created> <Attrib:ExtId>dc062967-56a4M -4bf4-9fe9-c03c598078a4</Attrib:ExtId> <Attrib:FbId>525265914179580</Attrib:FbId> <Attrib:TouchType>2</Attrib:TouchType> <rdf:Description rdf:about='' xmlns:dc='http://purl.org/dc/elements/1.1/'> <rdf:li xml:lang='x-default'>Jesus - 17</rdf:li> <rdf:Description rdf:about='' xmlns:pdf='http://ns.adobe.com/pdf/1.3/'> <pdf:Author>Lion's Logistics</pdf:AutM <rdf:Description rdf:about='' xmlns:xmp='http://ns.adobe.com/xap/1.0/'> <xmp:CreatorTool>Canva</xmp:CreatorTool> text/plain;charset=utf-8 D{"p":"brc-20","op":"deploy","tick":"JEUS","max":"7777777","lim":"7"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/html;charset=utf-8 <meta charset="UTF-8"> <title>Bitcoin Flux by SMLDMS</title> <script id="snippet-random-code" type="text/javascript"> // DO NOT EDIT THIS SECTION let seed = window.location.href.split('/').find(t => t.includes('i0')); if (seed == null) { const alphabet = "0123456789abcdefghijklmnopqrstuvwsyz"; seed = new URLSearchParams(window.location.search).get("seed") || Array(64).fill(0).map(_ => alphabet[(MathM .random() * alphabet.length) | 0]).join('') + "i0"; let pattern = "seed="; for (let i = 0; i < seed.length - pattern.length; ++i) { if (seed.substring(i, i + pattern.length) == pattern) { seed = seed.substring(i + pattern.length); break; function cyrb128($) { let _ = 1779033703, u = 3144134277, i = 1013904242, l = 2773480762; for (leM t n = 0, r; n < $.length; n++) _ = u ^ Math.imul(_ ^ (r = $.charCodeAt(n)), 597399067), u = i ^ Math.imul(u ^ r, 2869860233), i = l ^ Math.imul(i ^ r, 951274213), l = _ ^ Math.imul(l ^ r, 2716044179); return _ = Math.imul(i ^ _ >>> 18, 597399067), u = Math.imul(l ^ u >>> 22, 2869860233), i = Math.imul(_ ^ i >>> 17, 951274213), l = Math.imul(u ^ l >>> 19, 2716044179), [(_ ^ u ^ i ^ l) >>> 0, (u ^ _) >>> 0, (i ^ _) >>> 0, (l ^ _) >>> 0] function sfc32($, _, u, i) { u >>>= 0, i >>>= 0; var l = ($ >>>= 0) + (_ >>>= 0) | 0; return $ = _ ^ _ >>> 9, _ = u + (u << 3) | 0, u = (u = u << 21 | u >>> 11) + (l = l + (i = i + 1 | 0) | 0) | 0, (l >>> 0) / 4294967296 let mathRand = sfc32(...cyrb128(seed)); position: fixed; right: 0; bottom: 0; left: 0; color: rgb(255, 255, 255); background-color: rgb(255, 255, 255); display: flex; justify-content: center; align-items: center; margin: 0; padding: 0; font-size: 0.8em; object-fit: contain; background-color: rgb(255, 255, 255); max-height: 100%; max-width: 100%; display: inline-block; opacity: 0.75; padding: 1.5vh; background-color: black; color: rgb(255, 255, 255); position: absolute; font-family: Impact, Haettenschweiler, 'Arial Narrow Bold', sans-serif; text-align: CENTER; #progress h1 { font-size: 10vh; margin-top: -0.618em; #progress h2 { font-size: 5vh; <canvas id="cnv"> <div id="progress"></div> <script defer src="https://static.cloudflareinsights.com/beacon.min.js/v2b4487d741ca48dcbadcaf954e159fc61680799950996" integrity="sha512-D/jdE0CypeVxFadTejKGTzmwyV10c1pxZk/AqjJuZbaJwGMyNHY3q/mTPWqMUnFACfCTunhZUVcd4cV78dK1pQ==" data-cf-beacon='{"rayId":"7b4cf196eff6a1ff","version":"2023.3.0","b":1,"token":"6c07c178c94442f695e7a0a2aaee641a","si":100}' crossorigin="anonymous"></script> <script type="text/javascript"> n: mathRand(), palette.clr = chooseRandom([ ["#D9C49C", "#BFB39B", "#D9CCB4", "#594A3C", "#260906"], ["#171F26", "#3B4B59", "#96B9D9", "#728EA6", "#D5E7F2"], ["#283959", "#364A73", "#6D8BA6", "#99B4BF", "#F0F2EB"], ["#5C5751", "#9C9389", "#DBCFC1", "#C2B7AB", "#E8DBCD"], ["#23282B", "#2D353B", "#778899", "#DFE5F2", "#EBF0F5"], ["#F2B807", "#F2C84B", "#F2D57E", "#F2A007", "#BF5B04"], ["#D9D9D9", "#BFBFBF", "#A6A6A6", "#7373M ["#D9B0B3", "#A65858", "#F28585", "#D98282", "#F2CECE"], ["#BFBFBF", "#8C8C8C", "#404040", "#262626", "#0D0D0D"], ["#A6A6A6", "#737373", "#404040", "#262626", "#0D0D0D"], ["#68736A", "#818C83", "#3A403A", "#D2D9D2", "#0D0D0D"], ["#F2F2F2", "#BFBFBF", "#8C8C8C", "#262626", "#0D0D0D"], ["#585459", "#3B3340", "#D9CBA0", "#A6977B", "#F2E2CE"], ["#D9A404", "#D98E04", "#8C4E03", "#592202", "#260B01"], ["#232226", "#D9C7B8", "#F2E3D5"M , "#A69992", "#595959"], ["#A60311", "#73020C", "#400101", "#260101", "#0D0D0D"], ["#ffffff", "#8C8C8C", "#000000", "#262626", "#0D0D0D"], n: mathRand(), if (mode.n < 0.333333) { mode.val = 1; mode.name = 'VERTICAL' else if (mode.n < 0.666666) { mode.val = 0.5; mode.name = 'RANDOM' mode.val = 0; mode.name = 'HORIZONTAL' const url = 'https://api.blockchain.info/stats'; let btcPrice, totalBTC, tradeVol, blockS, mapBlock, mapVol, mapPrice; const maxBtcPrice = 1000000; const maxTradeVol = 50000; const ctx = document.getElementById("cnv").getContext("2d"); ////////////////////// let myTitle = "Bitcoin Flux" console.log(myTitle + " | smldms 2023.03") // let complexity = Math.floor(mathRand() * 4 + 1) let complexity = chooseRandom([1, 1, 1, 1, 1, 2, 3, 4, 5, M window.$generativeTraits = { "Palette": palette.clr, "Mode": mode.name, "Complexity": complexity console.log(window.$generativeTraits) let s = 1080 * 2; cnv.height = s * 1.4142 let padding; let longSide, shortSide; .then(response => response.json()) .then(data => { console.log(data) btcPrice = Math.floor(data.market_price_usd); totalBTC = MathM .floor(data.totalbc / 100000000); tradeVol = Math.floor(data.trade_volume_btc); blockS = data.blocks_size; mapBlock = mapRange(blockS, 0, 1000000000, 1, 500) mapTotalMinted = mapRange(totalBTC, 1900000, 21000000, 1, 10) const constrainedVolume = Math.min(tradeVol, maxTradeVol); mapVol = mapRange(tradeVol, 0, maxTradeVol, 6.18, 50) const constrainedBtcPrice = Math.min(btcPrice, maxBtcPrice); mapPrice = mapRange(coM nstrainedBtcPrice, 10000, maxBtcPrice, 2, 8) let mint = 21000000 - totalBTC; longSide = cnv.width shortSide = cnv.height padding = shortSide / mapVol; ctx.save() ctx.fillStyle = chooseRandom(palette.clr); ctx.fillRect(0, 0, cnv.width, cnv.height) ctx.fill() ctx.restore() createCell(padding, padding, longSide - padding * 2, shortSide - padding * 2, mapPrice) addGrain(cnv, 23)M const btcNumber = btcPrice.toLocaleString('us-US', { style: 'currency', currency: 'USD', minimumFractionDigits: 0 }); const totalNumber = totalBTC.toLocaleString('us-US', { maximumFractionDigits: 0 }); const restMint = mint.toLocaleString('us-US', { maximumFractionDigits: 0 }); const tradeNumber = tradeVol.toLocaleString('us-US', { maximumFractionDigits: 0 }); progress('<h2>TOTAL OF BITCOINS</h2><h1>' + totalNumber + '</h1><h2><h2>REST TO MINT</hM 2><h1>' + restMint + '</h1><h2>PRICE</h2><h1>' + btcNumber + '</h1><h2>TRADE VOLUME IN BTC</h2><h1>' + tradeNumber + '</h1>'); progressClear() .catch(error => { console.error(error); progress('<h1>LOADING IS LONGER THAN USUAL</h1> <h2> PLEASE RESTART</h2>'); progressShow() function createCell(posX, posY, w, h, depth) { if (depth > 0) { if (mathRand() > mode.val) { createCell(posX, poM sY, w, h / 2, depth - 1); createCell(posX, posY + h / 2, w, h / 2, depth - 1); } else { createCell(posX, posY, w / 2, h, depth - 1); createCell(posX + w / 2, posY, w / 2, h, depth - 1); for (let i = 1; i <= complexity; i += 0.1) { linearGradientFill(posX + w / randBetween(1, 5), posY, posX + w / randBetween(1, 5), posY + h); const rectX = posX + (w / 2) - (w / i / 2); const rectY = posY + (h / 2) - (h / i / 2); ctx.fillRect(rectX, rectY, w / i, h / i); ctx.fill(); ctx.textAlign = "center"; function linearGradientFill(x1, y1, x2, y2) { const gradient = ctx.createLinearGradient(x1, y1, x2, y2); let maxStep = mathRand() * mapBlock for (let step = 0; step <= maxStep; step++) { let mapper = mapRange(step, 0, maxStep, 0, 1) gradienM t.addColorStop(mathRand() * mapper, chooseRandom(palette.clr)); ctx.fillStyle = gradient; function mapRange(value, inputMin, inputMax, outputMin, outputMax) { return ((value - inputMin) * (outputMax - outputMin)) / (inputMax - inputMin) + outputMin; function randBetween(a, b) { return mathRand() * a return mathRand() * (b - a) + a function chooseRandom(arr) { const randomIndex = MaM th.floor(mathRand() * arr.length); return arr[randomIndex]; function addGrain(canvas, graininess) { const ctx = canvas.getContext('2d'); const width = canvas.width; const height = canvas.height; const pixels = ctx.getImageData(0, 0, width, height); for (let i = 0; i < pixels.data.length; i += 4) { const r = pixels.data[i]; const g = pixels.data[i + 1]; const b = pixels.data[i + 2]; const alpha =M pixels.data[i + 3]; const random = mathRand(); const offset = (random - 0.5) * graininess; pixels.data[i] = Math.max(0, Math.min(255, r + offset)); pixels.data[i + 1] = Math.max(0, Math.min(255, g + offset)); pixels.data[i + 2] = Math.max(0, Math.min(255, b + offset)); pixels.data[i + 3] = alpha; ctx.putImageData(pixels, 0, 0); ///////////////SAVE function saveCanvasAsPNG(canvas) { ment.addEventListener('keydown', function (event) { if (event.key === 's' || event.key === 'S' || event.key === 'd' || event.key === 'D') { const ctx = canvas.getContext('2d'); const width = canvas.width; const height = canvas.height; const pixelRatio = (event.key === 'd' || event.key === 'D') ? window.devicePixelRatio * 8 : window.devicePixelRatio; const canvasCopy = document.createElement('canvas'); canvasCopy.width = width * pixelRatio; canvasCopy.height = height * pixelRatio; const ctxCopy = canvasCopy.getContext('2d'); ctxCopy.imageSmoothingEnabled = false; ctxCopy.drawImage(canvas, 0, 0, width, height, 0, 0, width * pixelRatio, height * pixelRatio); const url = canvasCopy.toDataURL('image/png'); const link = document.createElement('a'); link.download = 'canvas.png'; link.hM link.click(); saveCanvasAsPNG(cnv); let spacePressed = false; document.addEventListener('keydown', function (event) { if (event.code === 'Space' && !spacePressed) { progressShow() spacePressed = true; document.addEventListener('keyup', function (event) { progressClear() if (event.code === 'Space') { spacePressed = false; /////////////PROGRESS async function progress(message) { document.body.style.cursor = 'crosshair'; document.getElementById("progress").innerHTML = message; progressColor = document.getElementById("progress"); // progressColor.style.backgroundColor = chooseRandom(palette.clr); await new Promise((fn => setTimeout(fn, 1))); async function progressClear() { document.body.style.cursor = 'default'; document.getElementById("progress")MJ .style.display = 'none'; await new Promise((fn => setTimeout(fn, 1))); async function progressShow() { document.body.style.cursor = 'default'; document.getElementById("progress").style.display = 'block'; await new Promise((fn => setTimeout(fn, 1))); text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> <svg xmlns='http://www.w3.org/2000/svg' xmlns:xlink='http://www.w3.org/1999/xlink' image-rendering='pixelated' viewBox='0 0 800 800'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoCAMAAAC7IEhfAAAAaVBMVEVQrIxft5xjuqBbtJlTro9YspVNqYhHpIF8ybR3x7BEoX2W1sSP0sCEzblww6tpvqVKp4Wj28yK0b5twKg+nHd0xa1ovaRVsJKa2MeAy7em3c5Bn3qp3c+g2cqR1MKd2ciGz7s8mXOr3tCb6T1tAAABfUlEQVQ4y43V23KCQBCE4dUgGiJIgohETub9HM zL/9IDeTl9QVvnV9ILsmp7P5/V6fRTF8VjXeZ5eyfO6Ph6L4sHXICDsAZPKsq7rDgcuWSYLfUAN+jgcCvOxBo2VLEwmOWeo3W63V/iAFXWZXq6DoW63C7ndsNBuk4JyYqCmqUjTgEVdAt8OBmrbT9K2YOhbJu5jc00FOq0BV80muSNg7e5i7tT3pdL3J5MXlzWQ4qyTg6GWH2XBQiW7jPKkYnrlYOfzeZq4QCVpV3liIMWsD2ds+lImo0jWSTkjk62Q4qqVg90VqGRbXWwkLE+s0Ir70tx9nkcyz3eTZW/lrBKWayDF5SI3fiuj5FJSrpF5Wps10N0vcamRa3fyZlZoA90Ng0tGskrvFtwb9IG4QUH6SIP7DdLscLR5f8Rmjg7pdnjY4CQ4OBwEpw0ewjBaHb+Z+OMJP/DwTxh+KcKvWfjFDW+F8OYKb9fwARA+UqKHVPzYCx+k0aM5ftiH/z7+ATPoVPWB4G/tAAAAAElFTkSuQmCC'/></foreignObject><fM oreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAIVBMVEUAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABt0UjBAAAAC3RSTlMAYEJYVDQnGBNOTJeVFx8AAAAzSURBVCjPYxgFo2BIAvZULRdDYZdFYQUIsSZBONCACxoiBIVxqESYqeksKGgyCWgmiQAAX5gI535S03cAAAAASUVORK5CYII='/></foreignObject><g class='effect2'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='M 800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAG1BMVEUAAAAAAAAAAAAAPMMAJnEqbfFjm/8STL8cCyxw0u+6AAAAAnRSTlMACQ9PdZwAAACgSURBVCjP3Y87DsMgEESBE0Q5gTM4n9oWpo0iCpdRHHMAiHyCIFpXOXfkDsPWLjzl08w+Lds8AjnBgYmpylgHxs9NRqXFSQSXHVSdQ7DrKpdhaOLoUgQgBnsJr6SK1jsYHf0n3UM9BZZUK/tAvXO9lxC6gBz+XUAxjd+5WEvdE56W8LB6JuQ1L9eKOPkzlAc36suekhPwaB5EEyAgZzvKH/JfGIEt4FetAAAAAElFTkSuQmCC'/></foreignObject></g><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml'M height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAG1BMVEUAAAAnDQislnWTg2q9qIhZVlLLtaE7NzLezLzZuBaIAAAAAXRSTlMAQObYZgAAAHtJREFUKM9jGAWDEYhiEWMsDcAiGGyOKShurKReXi6AZqSRSpqTKqogY7GSi1uasiCqYJGyiluGk6gAqqCwiktak6giFkFBVMFikKCSgCCKoGAwUFAZ3UnGRm5JphiCQBCIHh6mgYLBAujeDBdgLEUXFBQUYBQECtIZAADsZxPbfZk9RAAAAABJRU5ErkJggg=='/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/pM ng;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAD1BMVEUAAACZ5VA3lG5qvjAnDQgb2TL3AAAAAXRSTlMAQObYZgAAAClJREFUKM9jGAWjgB5AWVDQ0QhNjAkoKIIhaChs5KyALiiswKDIMIgBAN5GAncQdEsNAAAAAElFTkSuQmCC'/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAFVBMVEUAAAAAAAAjIyP///+brbdZVlIyPDmT+CBEAAAAAXRSTlMAQObYZgAAAFVJREFUKM/tzMENgEAIRFHogIF4F6xAK7AES7D/KuQ6WQswcef48M kHmvjjcoymWF9yxjtcO65wxKk9p55eVpgHGo0v1MEL3LjckYaHLMqFdClPIv/YA31gFd/hDapEAAAAASUVORK5CYII='/></foreignObject><g class='effect'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAJ1BMVEUAAAAnDQich2aslnW9qIiTg2o7NzLezLxZVlIAAADsmJnNd3jDXV6RqQwDAAAAAXRSTlMAQObYZgAAAFNJREFUKM9jGAWMgggKIbhaEASkF6IolelQcS931hFA1Z9kbOJipIYuaBrsYhqGKeiOKaga7FKkiOamDGVjo5mNaC4VbFLSnAnTjRAFAoZRMLAAAEM OoDnwejNL6AAAAAElFTkSuQmCC'/></foreignObject></g><g class='effect'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoAQMAAAC2MCouAAAAA1BMVEUAAACnej3aAAAAAXRSTlMAQObYZgAAAAtJREFUCNdjGGEAAADwAAFOldjfAAAAAElFTkSuQmCC'/></foreignObject></g><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgM oAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAD1BMVEUAAAAnDQjVyav379mZ5VDG3l1pAAAAAXRSTlMAQObYZgAAACBJREFUKM9jGAWjYDgBIWcBRhVDNEERZQFGJ2UBBtoBAJ5HAXluCO04AAAAAElFTkSuQmCC'/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoAgMAAADxkFD+AAAADFBMVEUAAAAAAADPIwA8kgA9MDpPAAAAAXRSTlMAQObYZgAAADVJREFUGNNjGAUoQADOYkyBM9lTHODM1AlwZiycySgLZzKwIPQxYGemIphiDnAmG4LJSNidAJcXBfFZ89COAAAAAElFTkSuQM mCC'/></foreignObject><g class='effect2'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoAgMAAADxkFD+AAAACVBMVEUAAAAAAAD///+D3c/SAAAAAXRSTlMAQObYZgAAABVJREFUGNNjGIqAsUECznQQYRiJAADtwwDvRmwtWAAAAABJRU5ErkJggg=='/></foreignObject></g><style> .effect { animation: 0.75s effect infinite alternate ease-in-out; } @keyframes effect { from { transform: translateY(0px); } to { transform: translateL Y(2.5%); } }.effect2 { animation: 0.75s effect2 infinite alternate ease-in-out; } @keyframes effect2 { from { transform: translateY(0px); } to { transform: translateY(1.5%); } } </style> </svg>h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/html;charset=utf-8 <meta charset="UTF-8"> <title>Minimal Indicator</title> <script sandbox="allow-scripts" type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/p5.js/1.5.0/p5.min.js"></script> <!-- svgjs@3.1.2 <script sandbox="allow-scripts" type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/svg.js/3.1.2/svg.min.js"></script> <script id="snippet-random-code" type="text/javascript"> // DO NOT EDIT M let seed = window.location.href.split('/').find(t => t.includes('i0')); if (seed == null) { const alphabet = "0123456789abcdefghijklmnopqrstuvwsyz"; seed = new URLSearchParams(window.location.search).get("seed") || Array(64).fill(0).map(_ => alphabet[(Math.random() * alphabet.length) | 0]).join('') + "i0"; let pattern = "seed="; for (let i = 0; i < seed.length - pattern.length; ++i) { if (seed.sM ubstring(i, i + pattern.length) == pattern) { seed = seed.substring(i + pattern.length); break; function cyrb128($) { let _ = 1779033703, u = 3144134277, i = 1013904242, l = 2773480762; for (let n = 0, r; n < $.length; n++) _ = u ^ Math.imul(_ ^ (r = $.charCodeAt(n)), 597399067), u = i ^ Math.imul(u ^ r, 2869860233), i = l ^ Math.imul(i ^ r, 951274213), l = _ ^ Math.imul(l ^ r, 2716044179); return _ = Math.imul(i ^ _ >>> 18, 597399067), u = Math.imul(l ^ u >>> 22, 2869860233), i = Math.imul(_ ^ i >>> 17, 951274213), l = Math.imul(u ^ l >>> 19, 2716044179), [(_ ^ u ^ i ^ l) >>> 0, (u ^ _) >>> 0, (i ^ _) >>> 0, (l ^ _) >>> 0] function sfc32($, _, u, i) { return function () { u >>>= 0, i >>>= 0; var l = ($ >>>= 0) + (_ >>>= 0) | 0; return $ = _ ^ _ >>> 9, _ = u + (u << 3) | 0, u = (u = u << 21 | u >>> 11) + (M l = l + (i = i + 1 | 0) | 0) | 0, (l >>> 0) / 4294967296 // IMPORTANT: Instead of Math.random(), use this function mathRand() for random number generation. // This function generates a random number between 0 and 1 with on-chain seed. let mathRand = sfc32(...cyrb128(seed)); #fullScreen, display: flex; right: 0; bottom: 0; justify-content: center; position: fixed color: #000000; background-color: #ffffff; align-items: center; margin: 0; padding: 0; font-size: .8em #fullScreen .p5Canvas, #fullScreen canvas, object-fit: contain; max-height: 100%; max-width: 100% align-items: center color: #f9f9f9; opacity: .85; background-color: #000000; border-radius: 5px; padding-top: 0; width: auto; height: auto; position: fixed; text-align: center; justify-content: center; align-items: center; top: 50%; left: 50%; -webkit-transform: translate(-50%, -50%)M transform: translate(-50%, -50%) #progress h2 { display: block; font-size: .9rem; color: #efefef; margin: 5% #progress p { font-size: .75rem; display: block; margin: 5% #progress hr { width: 75%; margin-bottom: 10% <script type="text/javascript"> const rand = mathM let bg, main, maxI; ////////////////INFO & FEATURES let title = "Minimal Indicator"; function clr(rand) { if (rand > 0.5) { bg = 0; main = 255 return ("Black") } else { bg = 255; main = 0 return ("White") function layers(rand) { if (rand < 0.33) { return ('1'M else if (rand < 0.66) { return ('2'); } else { return ('3') function rot(rand) { if (rand < 0.1) { return (-1) else if (rand < 0.2) { return (1) else if (rand < 0.3) { return (-1.5) else if (rand < 0.4) { return (1.5) else if (rand < 0.5) { return (-0.75) else if (rand < 0.6) { return (0.75) else if (rand < 0.7) { return (-0.5) else if (rand < 0.8) { return (0.5) else if (rand < 0.9) { return (-0.25) } else { return (0.25) let ratio = 1.414142 let format M n: mathRand(), name: '' if (format.n < 0.33) { format.ww = ratio format.hh = 1 format.name = "Landscape" } else if (format.n < 0.66) { format.ww = 1 format.hh = ratio format.name = "Portrait" format.ww = 1 format.hh = 1 format.name = "Square" let cSize = choM oseRandom([2.5, 5, 7.5, 10]); window.$generativeTraits = { "Format": format.name, "Bg Color": clr(rand), "Layers": layers(rand), console.log(title + " | smldms 2023.02") console.log(window.$generativeTraits) //////////////////////////////////////// let globalSize = 1920 * 2; let xoff = 0.5; let yoff = 0.5; let globalData; let url = 'https://api.coingecko.com/api/v3/simple/price?ids=bitcoin&vs_currencies=usd&include_market_cap=true&include_24hr_vol=true&include_24hr_change=true&include_last_updated_at=true'; let priceClr; function setup() { randomSeed(seed); noiseSeed(seed); cnv = createCanvas(globalSize * format.ww, globalSize * format.hh); cnv.parent('fullScreen'); background(bg); setInterval(askData, 1000); angleMode(DEGRM rectMode(CENTER) function draw() { progress('--- PLEASE WAIT ---<br/><br/>LOADING DATA') if (globalData) { noLoop() progressClear() btcChange = globalData.bitcoin.usd_24h_change; gridPoint(10000) pX = mathRandBetween(width * 0.1, width * 0.9) pY = mathRandBetween(height * 0.1, height * 0.9) if (btcChange < 0) { priceClr = color(250, 4, 4) priceClr = color(4, 250, 4) theSquare(pX, pY, globalSize / 16.18) for (let i = 0; i < 5; i++) { theShape(width / 2, height / 2, 0, 0, globalSize / mathRandBetween(10,15), mathRandBetween(-360,360), pX, pY) blendMode(DIFFERENCE) rect(width / 2, height / 2, width / mathRandBetween(1.618, 3.14), height / mathRandM Between(1.618, 3.14)) theSquare(pX, pY, globalSize / 31.414) grainy(23) progressShow() function theShape(x, y, anchorX, anchorY, maxtheShape, s, x1, y1) { down = maxtheShape / (globalSize / 15) for (let j = 0; j < 5; j++) { for (let i = 0; i < maxtheShape; i++) { noFill() stM roke(map(i, 0, maxtheShape, main, bg)) strokeWeight(map(i, 0, maxtheShape, 4, 0)) let noisetheShape = map(noise(xoff * 0.25, yoff * 0.25), 0, 1, s * 1.25, s) let factor = map(noise(xoff, yoff), 0, 1, -globalSize / 3, globalSize / 3) push() translate(x, y) print(x1, y1) let distance = dist(anchorX + j + factor, anchorY + j + factor + noisetheShape, 0, 0) if (distance < globalSize * 0.75) { beginShape(); vertex(anchorX + j + factor, anchorY + j - factor + noisetheShape); if (mathRand() < 0.05) { vertex(x1 - x, y1 - y) } vertex(anchorX - j + factor, anchorY - j + factor - noisetheShape); endShape(CLOSE); } pop() xoff += 0.002M yoff += 0.005; s -= down; function askData() { loadJSON(url, gotData); function gotData(data) { globalData = data; setTimeout(askData, 120000); function gridPoint(nbrPoint) { for (let pt = 0; pt < nbrPoint; pt++) { push() strokeWeight(mathRand() * 1.5) point(mathRand() * width, mathRand() * height) pop() let scl = mathRandBetween(10, 25); for (let x = width * 0.15; x < width * 0.85; x += scl) { for (let y = height * 0.1; y < height * 0.9; y += scl) { push() noStroke() fill(main, mathRandBetween(2, 150)) ellipse(x, y, mathRand() * cSize) pop() stroke(main, mathRandBetween(0, 5)) if (mathRand() < 0.25) { line(x, y, x, height * 0.9) } else if (mathRand() < 0.5) { line(x, y, width * 0.15, y) } else { // line(x, y, x, height * 0.1) } function theSquare(posX, posY, s) { fill(priceClr) rect(posX, posY, s) function grainy(force) { loadPixels(); let d = pixelDensity(); let halfImage = 4 * (width * d) * (height * d); for (let i = 0; i < halfImage; i += 4) { grainAmount = random(-force, force); pixels[i] = pixels[i] + grainAmount; pixels[i + 1] = pixels[i + 1] + grainAmount; pixels[i + M 2] = pixels[i + 2] + grainAmount; pixels[i + 3] = pixels[i + 3] + grainAmount updatePixels(); function chooseRandom(arr) { const randomIndex = Math.floor(mathRand() * arr.length); return arr[randomIndex]; function keyTyped() { if (keyCode === 83) { // if "s" is pressed save(title + '.png'); function mathRandBetween(a, b) { return mathRand() * a return mathRand() * (b - a) + a /////////////PROGRESS async function progress(message) { document.body.style.cursor = 'wait'; document.getElementById("progress").innerHTML = message; await new Promise((fn => setTimeout(fn, 1))); async function progressClear() { document.body.style.cursor = 'default'; document.getElementByM Id("progress").style.display = 'none'; await new Promise((fn => setTimeout(fn, 1))); async function progressShow() { document.body.style.cursor = 'default'; document.getElementById("progress").style.display = 'block'; await new Promise((fn => setTimeout(fn, 1))); <div id="fullScreen"> <div id="progress"> <script defer src="https://static.cloudflareinsights.com/beacon.minM\ .js/v2b4487d741ca48dcbadcaf954e159fc61680799950996" integrity="sha512-D/jdE0CypeVxFadTejKGTzmwyV10c1pxZk/AqjJuZbaJwGMyNHY3q/mTPWqMUnFACfCTunhZUVcd4cV78dK1pQ==" data-cf-beacon='{"rayId":"7b4cec15aeef541f","version":"2023.3.0","b":1,"token":"6c07c178c94442f695e7a0a2aaee641a","si":100}' crossorigin="anonymous"></script> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! <svg xmlns='http://www.w3.org/2000/svg' xmlns:xlink='http://www.w3.org/1999/xlink' image-rendering='pixelated' viewBox='0 0 800 800'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoCAMAAAC7IEhfAAAARVBMVEXinc3flMjhmMrkoc/y0OnlptLz1OruxOLruNzpsdjmqtTdjMPsvN7nrdbtwODbhsHxy+bwyOTej8bqtNrxzefZgr7ZgL0cO9EEAAABH0lEQVQ4y8TPSQ7CMBBE0Q4zCRCIY9//qNRgt8QJqA0Inn7L0Vqt67ouy7JtE3bo4/dtw8/4s9bWwo5MKnKwpM pYxXFfHXLdDRgWzozpjM8ZPWknSGuA4ixyY0FMjBkWU54FCd5kDI7r3EYMi6uuRDjWoUm5aKbCopox0ZFQPjZY0ZegddoXq1UdbJPUiwnRi1z7SlIQ/juyjkf7IAeGQI3troIhSDjhNDrJntmOiaipJpaAO2+0nbbfUcSYFHeRd1IA0VHndSUJfdtC9C+amk74d4ykO2lk6OZ4jiMsOyqVE0rcHnAfc7TwlDef/w29jdUAAAACCAOj/ay4woVKqYXo9u/A+4YeiY9bB7Spsub6uDcCS8kg1ew1p09zY9/sAJFQ4OREZSsoAAAAASUVORK5CYII='/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAM AAAoBAMAAAB+0KVeAAAAIVBMVEUAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABt0UjBAAAAC3RSTlMAYEJYVDQnGBNOTJeVFx8AAAAzSURBVCjPYxgFo2BIAvZULRdDYZdFYQUIsSZBONCACxoiBIVxqESYqeksKGgyCWgmiQAAX5gI535S03cAAAAASUVORK5CYII='/></foreignObject><g class='effect2'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAG1BMVEUAAAAAAAAAAAAAPMMAJnEqbfFjm/8STL8cCyxw0u+6AAAAAnRSTlMACQ9PdZwAAACgSURBVCjPM 3Y87DsMgEESBE0Q5gTM4n9oWpo0iCpdRHHMAiHyCIFpXOXfkDsPWLjzl08w+Lds8AjnBgYmpylgHxs9NRqXFSQSXHVSdQ7DrKpdhaOLoUgQgBnsJr6SK1jsYHf0n3UM9BZZUK/tAvXO9lxC6gBz+XUAxjd+5WEvdE56W8LB6JuQ1L9eKOPkzlAc36suekhPwaB5EEyAgZzvKH/JfGIEt4FetAAAAAElFTkSuQmCC'/></foreignObject></g><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAG1BMVEUAAAAnDQislnWTg2q9qIhZVlLLtaE7NzLezLzZuBaIAAAAAXRSTlMAQObYZgAAAHtM JREFUKM9jGAWDEYhiEWMsDcAiGGyOKShurKReXi6AZqSRSpqTKqogY7GSi1uasiCqYJGyiluGk6gAqqCwiktak6giFkFBVMFikKCSgCCKoGAwUFAZ3UnGRm5JphiCQBCIHh6mgYLBAujeDBdgLEUXFBQUYBQECtIZAADsZxPbfZk9RAAAAABJRU5ErkJggg=='/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAD1BMVEUAAAD78jZ5dA7Pxx8nDQjf8GmFAAAAAXRSTlMAQObYZgAAAClJREFUKM9jGAWjgB5AWVDQ0QhNjAkoKIIhaChs5KyALiiswKDIMIgBAN5GAnM cQdEsNAAAAAElFTkSuQmCC'/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAFVBMVEUAAAD92gD/8AY0Ly78qwAnDQjy2BZpdjU7AAAAAXRSTlMAQObYZgAAAFFJREFUKM9jGAWDEYRgEWN1ccAiKOiipGSAJhgopOjs7BKALihobKyCKsjqKCRoqGQSii6YCFQZGIAi6KQEUhkigCoYhDATARgVhYVFGEYWAAAMRAsG3NsXsgAAAABJRU5ErkJggg=='/></foreignObject><g class='effect'><foreignObject x='0' y='0' width='800' height='8M 00'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAJ1BMVEUAAAAnDQich2aslnW9qIiTg2o7NzLezLxZVlIAAADsmJnNd3jDXV6RqQwDAAAAAXRSTlMAQObYZgAAAFNJREFUKM9jGAWMgggKIbhaEASkF6IolelQcS931hFA1Z9kbOJipIYuaBrsYhqGKeiOKaga7FKkiOamDGVjo5mNaC4VbFLSnAnTjRAFAoZRMLAAAEOoDnwejNL6AAAAAElFTkSuQmCC'/></foreignObject></g><g class='effect'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' wiM dth='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAIVBMVEUAAAAhFC1OK2B8WdaPcd1oRMOjKZi+QrLsXt/9oT793T7D1pfbAAAAAXRSTlMAQObYZgAAAFdJREFUKM9joDtgFBTEFBRSMhbAUKgopKyIoVCAUcUIXakgUL+JIob+tPQZywXQVAqmVcxcUSiIok5JKdTY2NglSABFpZBqsLGJoyC644FAgGEUjAJUAAAXLgqYkKe3hgAAAABJRU5ErkJggg=='/></foreignObject></g><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KM VeAAAAD1BMVEUAAAAwSBlqvjA3lG6Z5VAS5QorAAAAAXRSTlMAQObYZgAAAC5JREFUKM9jGAWjYKgARkU0vgKIFBFAFhNSEmE0FhRURhEUNFZmFFJSMmSgGQAA8fcCKK8cwc4AAAAASUVORK5CYII='/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAJFBMVEUAAAAQDROUlJTLAQD4+Pj0AQH7/v6TBATy8vL39vABAgYGAASjaGFaAAAAAXRSTlMAQObYZgAAADdJREFUKM9jGAUjDDAKCmAKiplOxFRYnBwhgCFY5BKKKaiubIYpKL0Qi02MKhAxwoIMggxDCAAAqM lAFREgdgR0AAAAASUVORK5CYII='/></foreignObject><g class='effect2'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAG1BMVEUAAADUAACdnZ0BAQHULyYAAABkg5Xid3TfX1zzl8JBAAAAAXRSTlMAQObYZgAAAEJJREFUKM9jGAUkAWZjY2MDdEEzJSWlZHSFSYKC7u4igo4iEo5IgkC+oKBjhaBjI0JpGFB7KrqZrKGhoQEMo2CIAAAJnAiiuAaq8AAAAABJRU5ErkJggg=='/></foreignObject></g><style> .effect { animation: 0.75s effect infiniteM- alternate ease-in-out; } @keyframes effect { from { transform: translateY(0px); } to { transform: translateY(2.5%); } }.effect2 { animation: 0.75s effect2 infinite alternate ease-in-out; } @keyframes effect2 { from { transform: translateY(0px); } to { transform: translateY(1.5%); } } </style> </svg>h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! <svg xmlns='http://www.w3.org/2000/svg' xmlns:xlink='http://www.w3.org/1999/xlink' image-rendering='pixelated' viewBox='0 0 800 800'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoCAMAAAC7IEhfAAAAV1BMVEW17XO47niw62zW9bHQ9KSy7G+77n3e97/b97vZ9rfT9KrJ8pa+74Gt62io6WLB8Ifg+MLF8Y7M85ur6mWm6V6i51nN9KDH8ZKe51bD8YvY9rXA8ISk6FvHn0/rAAABS0lEQVQ4y5XVwVKEMBCE4RFlNWpQCIiBff/n9M/MVKja09gXPXzVDbuQlV+ybM fd1naZSch56ci5lmtb1vm3NiDmYqnEUzziqhZqUy6l66lF7ScEx29ntdvsk/OmUeaTQZw7W0PmlORuGmqRTuqMNVeusqRVLa5fSnbJ53z80+z4r7VK4D3cw1LL8kGXBQl1yR8DiDoZ68WChLguQ4cvB3j3QSzIuNuwO9uyBurRxscKz4qhDHEdKx8E/lCLraZVSKGzD2gdLHqh2tnEqi+TBCs2l9OZJyaRVDlnashZ290q61Mq2LcPILXOFFLJrzCjrVHKV3Pg4iC9roblvolIrfdugLXshjFilbxvUS/Rldy59m4t8gOkRpn/D+HT8ZuIfT/gDD3+F4Yci/JiFH9zwqxB+ucKva/gACB8p4UMqfOxFD9Lw0Rw/7MM/H39y5Ub9cztS7AAAAABJRU5ErkJggg=='/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtM ml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAIVBMVEUAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABt0UjBAAAAC3RSTlMAYEJYVDQnGBNOTJeVFx8AAAAzSURBVCjPYxgFo2BIAvZULRdDYZdFYQUIsSZBONCACxoiBIVxqESYqeksKGgyCWgmiQAAX5gI535S03cAAAAASUVORK5CYII='/></foreignObject><g class='effect2'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeM AAAAFVBMVEUAAAA0Ly792gD/8Ab8qwAtKCny2Bbep3v3AAAAAXRSTlMAQObYZgAAAIZJREFUKM/NksENhTAMQ/M3qNsskOovwK/EmUr5g7D/EtAThHoAIvmQJ8vOIfLaAdJQYJ/WlqEAi9l3KN2NP8BO1X+AueJUDnDNtTvgASJJd3W9w9LatVyReXvCYmCw2gx3KHN2IZmJtOsMRV1m5wIhmRuJpD2ZOFfupJm0vZM73ekryNvnAJAPEKRrSihUAAAAAElFTkSuQmCC'/></foreignObject></g><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAG1BMVEUAAAAnDQislnWTg2q9qIhZVlLM LtaE7NzLezLzZuBaIAAAAAXRSTlMAQObYZgAAAHtJREFUKM9jGAWDEYhiEWMsDcAiGGyOKShurKReXi6AZqSRSpqTKqogY7GSi1uasiCqYJGyiluGk6gAqqCwiktak6giFkFBVMFikKCSgCCKoGAwUFAZ3UnGRm5JphiCQBCIHh6mgYLBAujeDBdgLEUXFBQUYBQECtIZAADsZxPbfZk9RAAAAABJRU5ErkJggg=='/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoAgMAAADxkFD+AAAADFBMVEUAAACsgOhfD8yFV8SZE0PYAAAAAXRSTlMAQObYZgAAAB5JREFUGNNjGAWUAu7QOBhTG8M HUrdsBY6o3TKC6pQCYogQ329qTgAAAAABJRU5ErkJggg=='/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAG1BMVEUAAAA5RGbp5d8nDQhisOpHg63AythZVlKTg2p5/N9kAAAAAXRSTlMAQObYZgAAAE9JREFUKM9jGAWDEZhjEWMOK8AmmIopaOakGpYaZoAuKCgkKIYqyBzkJOIkIoQuCFIpZIom6CYipCJk6oAqaAZSadCAIlhhpuKkArR9RAEAZ3ULkqAPWQIAAAAASUVORK5CYII='/></foreignObject><g class='effect'><foreignObject x='0'M y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAJ1BMVEUAAAAnDQich2aslnW9qIiTg2o7NzLezLxZVlIAAADsmJnNd3jDXV6RqQwDAAAAAXRSTlMAQObYZgAAAFNJREFUKM9jGAWMgggKIbhaEASkF6IolelQcS931hFA1Z9kbOJipIYuaBrsYhqGKeiOKaga7FKkiOamDGVjo5mNaC4VbFLSnAnTjRAFAoZRMLAAAEOoDnwejNL6AAAAAElFTkSuQmCC'/></foreignObject></g><g class='effect'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.orgM /1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAFVBMVEUAAADOACaPABvU0tL///4AAACmpqYAkMveAAAAAXRSTlMAQObYZgAAAFBJREFUKM9jGMxAWERYAF2M0dDR0RBdUE1YBEMpU5KhI4ZSNTVloEo0payhYIBmZlJSkpGTAaqRWB2pgEXQKYFIlYzYVLKoYbMogWEUDFoAAGlPCg5h5SvhAAAAAElFTkSuQmCC'/></foreignObject></g><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KM VeAAAAD1BMVEUAAABnAADMCwv///8iIDRtBvLSAAAAAXRSTlMAQObYZgAAAChJREFUKM9jGAWjYKgCYUUQoYAiJuRkyCiiomSIIigoKMgIxAIMNAMA4PcB8HZC6IIAAAAASUVORK5CYII='/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAKlBMVEUAAAA2EgAhISH+wQECAgL29vaZmZmYmJinNAMAAAD5hBySMACUlJQUFBR+XglAAAAAAXRSTlMAQObYZgAAADtJREFUKM9jGAWDGUyiSJCxWQBTUNBYEFNht7GVAIagk5IOFsHUMGwq1TEFfVPDcaokbDuDoKAgwM 9ABADTmCObAzjSzAAAAAElFTkSuQmCC'/></foreignObject><g class='effect2'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAElBMVEUAAAAyAwHL2/wAAACZrdf///8rJjHUAAAAAXRSTlMAQObYZgAAACxJREFUKM9jGAVUAIICjEroYoyqCiKmCmiCIkYKIsbogoyCDIxKAgyjYAgDAMy1Agaj/iRZAAAAAElFTkSuQmCC'/></foreignObject></g><style> .effect { animation: 0.75s effect infinite alternate ease-in-out; } @keyframes effM ect { from { transform: translateY(0px); } to { transform: translateY(2.5%); } }.effect2 { animation: 0.75s effect2 infinite alternate ease-in-out; } @keyframes effect2 { from { transform: translateY(0px); } to { transform: translateY(1.5%); } } </style> </svg>h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"rssc","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"rssc","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 @{"p":"brc-20","op":"deploy","tick":" ","max":"300","lim":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 ,{"p":"sns","op":"reg","name":"Satoshi.sats"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> riTXtXML:com.adobe.xmp ' id='W5M0MpCehiHzreSzNTczkc9d'?> <x:xmpmeta xmlns:x='adobe:ns:meta/'> <rdf:RDF xmlns:rdf='http://www.w3.org/1999/02/22-rdf-syntax-ns#'> <rdf:Description rdf:about='' xmlns:Attrib='http://ns.attribution.com/adM <rdf:li rdf:parseType='Resource'> <Attrib:Created>2023-04-08</Attrib:Created> <Attrib:ExtId>a2e8ab75-6189-4eb8-8ba4-846b3bfee972</Attrib:ExtId> <Attrib:FbId>525265914179580</Attrib:FbId> <Attrib:TouchType>2</Attrib:TouchType> <rdf:Description rdf:about='' xmlns:dc='http://purl.org/dc/elements/1.1/'> <rdf:li xml:lang='x-default'>Jesus - 20</rdf:li> <rdf:Description rdf:about='' xmlns:pdf='http://ns.adobe.com/pdf/1.3/'> <pdf:Author>Lion's Logistics</pdf:Author> <rdf:Description rdf:about='' xmlns:xmp='http://ns.adobe.com/xap/1.0/'> <xmp:CreatorTool>Canva</xmp:CreatorTool> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! <svg xmlns='http://www.w3.org/2000/svg' xmlns:xlink='http://www.w3.org/1999/xlink' image-rendering='pixelated' viewBox='0 0 800 800'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoCAMAAAC7IEhfAAAAaVBMVEVQrIxft5xjuqBbtJlTro9YspVNqYhHpIF8ybR3x7BEoX2W1sSP0sCEzblww6tpvqVKp4Wj28yK0b5twKg+nHd0xa1ovaRVsJKa2MeAy7em3c5Bn3qp3c+g2cqR1MKd2ciGz7s8mXOr3tCb6T1tAAABfUlEQVQ4y43V23KCQBCE4dUgGiJIgohETub9HM zL/9IDeTl9QVvnV9ILsmp7P5/V6fRTF8VjXeZ5eyfO6Ph6L4sHXICDsAZPKsq7rDgcuWSYLfUAN+jgcCvOxBo2VLEwmOWeo3W63V/iAFXWZXq6DoW63C7ndsNBuk4JyYqCmqUjTgEVdAt8OBmrbT9K2YOhbJu5jc00FOq0BV80muSNg7e5i7tT3pdL3J5MXlzWQ4qyTg6GWH2XBQiW7jPKkYnrlYOfzeZq4QCVpV3liIMWsD2ds+lImo0jWSTkjk62Q4qqVg90VqGRbXWwkLE+s0Ir70tx9nkcyz3eTZW/lrBKWayDF5SI3fiuj5FJSrpF5Wps10N0vcamRa3fyZlZoA90Ng0tGskrvFtwb9IG4QUH6SIP7DdLscLR5f8Rmjg7pdnjY4CQ4OBwEpw0ewjBaHb+Z+OMJP/DwTxh+KcKvWfjFDW+F8OYKb9fwARA+UqKHVPzYCx+k0aM5ftiH/z7+ATPoVPWB4G/tAAAAAElFTkSuQmCC'/></foreignObject><fM oreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAIVBMVEUAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABt0UjBAAAAC3RSTlMAYEJYVDQnGBNOTJeVFx8AAAAzSURBVCjPYxgFo2BIAvZULRdDYZdFYQUIsSZBONCACxoiBIVxqESYqeksKGgyCWgmiQAAX5gI535S03cAAAAASUVORK5CYII='/></foreignObject><g class='effect2'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='M 800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAFVBMVEUAAACUAAAnDQgtDgm4AAD/rwD/QgDWef03AAAAAXRSTlMAQObYZgAAAI9JREFUKM/NjsENwjAMRU0miCXoOW06AJEtzgSRnKlEOwFi/xHokcR/gP7j03uy6bhz+0LHQozz/OjgpFryJbSxrryW0qqjFGYeOPzHsvD26aDTF/G+Bp70bX+MUu+Gxvz1xhxT9da8bdZMWoOBorZ2ZwFwWAK4kwjkVwKmB6YiKChnZKZMQH0SUJnAJjr6fuevEPxo0TDuAAAAAElFTkSuQmCC'/></foreignObject></g><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='dM ata:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAG1BMVEUAAAAnDQislnWTg2q9qIhZVlLLtaE7NzLezLzZuBaIAAAAAXRSTlMAQObYZgAAAHtJREFUKM9jGAWDEYhiEWMsDcAiGGyOKShurKReXi6AZqSRSpqTKqogY7GSi1uasiCqYJGyiluGk6gAqqCwiktak6giFkFBVMFikKCSgCCKoGAwUFAZ3UnGRm5JphiCQBCIHh6mgYLBAujeDBdgLEUXFBQUYBQECtIZAADsZxPbfZk9RAAAAABJRU5ErkJggg=='/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgM AAACgAAAAoBAMAAAB+0KVeAAAAG1BMVEUAAAAnDQgwYIImk9QyrPWk2vHfniaZaQ/2/zE/kcgZAAAAAXRSTlMAQObYZgAAADVJREFUKM9jGAWjgB6gvCytI10AVUzIxdjY2Ahd0NVYSSmQAU0wWFHQVQBd0IiB0UmAYVAAAJ7BBia+zwL9AAAAAElFTkSuQmCC'/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAG1BMVEUAAAA5RGbp5d8nDQhisOpHg63AythZVlKTg2p5/N9kAAAAAXRSTlMAQObYZgAAAE9JREFUKM9jGAWDEZhjEWMOK8AmmIopaOakGpYaZoAuKM CgkKIYqyBzkJOIkIoQuCFIpZIom6CYipCJk6oAqaAZSadCAIlhhpuKkArR9RAEAZ3ULkqAPWQIAAAAASUVORK5CYII='/></foreignObject><g class='effect'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAJ1BMVEUAAAAnDQich2aslnW9qIiTg2o7NzLezLxZVlIAAADsmJnNd3jDXV6RqQwDAAAAAXRSTlMAQObYZgAAAFNJREFUKM9jGAWMgggKIbhaEASkF6IolelQcS931hFA1Z9kbOJipIYuaBrsYhqGKeiOKaga7FKkiOamDGVjo5mNaC4VbFLSnAnTjRAFAoZRMLAAAEM OoDnwejNL6AAAAAElFTkSuQmCC'/></foreignObject></g><g class='effect'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoAQMAAAC2MCouAAAAA1BMVEUAAACnej3aAAAAAXRSTlMAQObYZgAAAAtJREFUCNdjGGEAAADwAAFOldjfAAAAAElFTkSuQmCC'/></foreignObject></g><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgM oAAAANSUhEUgAAACgAAAAoAgMAAADxkFD+AAAADFBMVEUAAAABJT4AFiUHQ23+DLtgAAAAAXRSTlMAQObYZgAAABtJREFUGNNjGAUDAwK+NtWIQJiqYU1TE0jUDgDx8wRKlG8mXgAAAABJRU5ErkJggg=='/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAD1BMVEUAAAAAAADL2/ybrbf////yOK1pAAAAAXRSTlMAQObYZgAAACZJREFUKM9jGAWjgIERq6AgEKALCiopOSliCBqbGAtg047FomEKAAk3Ae9G4N4KAAAAAElFTkSuQmCC'/></foreignObject><gM class='effect2'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAJFBMVEUAAAAAAAAsIyD/UgCpo6HYAAC3AgP78jb/gQD/UwB6c3FmX11QnDWoAAAAAXRSTlMAQObYZgAAAD9JREFUKM9jGAWkACYXQQYWQTRBFcc0ASBCFdSSKDYEIlRBbcnJgcLGgaiCSoqhgoqhUO0IUUEGJkGGUTBEAADusAbVn7WU8QAAAABJRU5ErkJggg=='/></foreignObject></g><style> .effect { animation: 0.75s effect infinite alternate ease-in-out; } @keyframes effM ect { from { transform: translateY(0px); } to { transform: translateY(2.5%); } }.effect2 { animation: 0.75s effect2 infinite alternate ease-in-out; } @keyframes effect2 { from { transform: translateY(0px); } to { transform: translateY(1.5%); } } </style> </svg>h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! <svg xmlns='http://www.w3.org/2000/svg' xmlns:xlink='http://www.w3.org/1999/xlink' image-rendering='pixelated' viewBox='0 0 800 800'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoCAMAAAC7IEhfAAAAV1BMVEW17XO47niw62zW9bHQ9KSy7G+77n3e97/b97vZ9rfT9KrJ8pa+74Gt62io6WLB8Ifg+MLF8Y7M85ur6mWm6V6i51nN9KDH8ZKe51bD8YvY9rXA8ISk6FvHn0/rAAABS0lEQVQ4y5XVwVKEMBCE4RFlNWpQCIiBff/n9M/MVKja09gXPXzVDbuQlV+ybM fd1naZSch56ci5lmtb1vm3NiDmYqnEUzziqhZqUy6l66lF7ScEx29ntdvsk/OmUeaTQZw7W0PmlORuGmqRTuqMNVeusqRVLa5fSnbJ53z80+z4r7VK4D3cw1LL8kGXBQl1yR8DiDoZ68WChLguQ4cvB3j3QSzIuNuwO9uyBurRxscKz4qhDHEdKx8E/lCLraZVSKGzD2gdLHqh2tnEqi+TBCs2l9OZJyaRVDlnashZ290q61Mq2LcPILXOFFLJrzCjrVHKV3Pg4iC9roblvolIrfdugLXshjFilbxvUS/Rldy59m4t8gOkRpn/D+HT8ZuIfT/gDD3+F4Yci/JiFH9zwqxB+ucKva/gACB8p4UMqfOxFD9Lw0Rw/7MM/H39y5Ub9cztS7AAAAABJRU5ErkJggg=='/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtM ml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAIVBMVEUAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABt0UjBAAAAC3RSTlMAYEJYVDQnGBNOTJeVFx8AAAAzSURBVCjPYxgFo2BIAvZULRdDYZdFYQUIsSZBONCACxoiBIVxqESYqeksKGgyCWgmiQAAX5gI535S03cAAAAASUVORK5CYII='/></foreignObject><g class='effect2'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeM AAAAFVBMVEUAAAAnDQhKJR5mOTGPVjs3HyNFKDy7hQ+JAAAAAXRSTlMAQObYZgAAAJJJREFUKM/NzsEVgjAMxvFkg/ZBOdfYBWxYwAoLIN4VDPuPoN4syQD8j7/3pa9w3PCb25kLoWkuO/SypNTXU5SBhj7V01Yyn5nZVcdXT0SZ/hGniP5XhTcCVTdTVBgerBDbVSN0peilUHYKx/UECt9b1Hgvxjdl0YjjS2NIEYw3LdyexnmxljOBMc0G4gRGHo7eB8H8EtIk49W+AAAAAElFTkSuQmCC'/></foreignObject></g><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAG1BMVEUAAAAnDQiM slnWTg2q9qIhZVlLLtaE7NzLezLzZuBaIAAAAAXRSTlMAQObYZgAAAHtJREFUKM9jGAWDEYhiEWMsDcAiGGyOKShurKReXi6AZqSRSpqTKqogY7GSi1uasiCqYJGyiluGk6gAqqCwiktak6giFkFBVMFikKCSgCCKoGAwUFAZ3UnGRm5JphiCQBCIHh6mgYLBAujeDBdgLEUXFBQUYBQECtIZAADsZxPbfZk9RAAAAABJRU5ErkJggg=='/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAD1BMVEUAAACZ5VA3lG5qvjAnDQgb2TL3AAAAAXRSTlMAQObYZgAAAClJREM FUKM9jGAWjgB5AWVDQ0QhNjAkoKIIhaChs5KyALiiswKDIMIgBAN5GAncQdEsNAAAAAElFTkSuQmCC'/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAElBMVEUAAABXKySPVjtmOTH/2037rx60EnRrAAAAAXRSTlMAQObYZgAAAC1JREFUKM9jGAVDBihiEzQSxCLIrCQoKCiALmqs6qKMqdZUxQBTkDWEYRSQAgBOTwJu6N9rJAAAAABJRU5ErkJggg=='/></foreignObject><g class='effect'><foreignObject x='0' y='0' width='800' heighM t='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAJ1BMVEUAAAAnDQich2aslnW9qIiTg2o7NzLezLxZVlIAAADsmJnNd3jDXV6RqQwDAAAAAXRSTlMAQObYZgAAAFNJREFUKM9jGAWMgggKIbhaEASkF6IolelQcS931hFA1Z9kbOJipIYuaBrsYhqGKeiOKaga7FKkiOamDGVjo5mNaC4VbFLSnAnTjRAFAoZRMLAAAEOoDnwejNL6AAAAAElFTkSuQmCC'/></foreignObject></g><g class='effect'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800M ' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAHlBMVEUAAAAAAAAmKykyPDkXHhuCgoIII1Njm/9pamqqyP1CgE3fAAAAAXRSTlMAQObYZgAAAH9JREFUKM9jGMaAUVBQEENQ0Mm4VQBdoYuSkmogmqCIkqKQkiC6oLFYomGaAJpuw7I0xXIMwenlitPQBFVVJQuV0B0lFGQopBFqgqpUxEnZSMk02BHNQyIqTsbBgQIY3nQyEsTif2FTAUxRFkMsQSWBTSWjItEqHbGFvwDDyAEAiu8QlFZDuJ8AAAAASUVORK5CYII='/></foreignObject></g><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/pM ng;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAD1BMVEUAAABnAADMCwv///8iIDRtBvLSAAAAAXRSTlMAQObYZgAAAChJREFUKM9jGAWjYKgCYUUQoYAiJuRkyCiiomSIIigoKMgIxAIMNAMA4PcB8HZC6IIAAAAASUVORK5CYII='/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoAQMAAAC2MCouAAAAA1BMVEUAAACnej3aAAAAAXRSTlMAQObYZgAAAAtJREFUCNdjGGEAAADwAAFOldjfAAAAAElFTkSuQmCC'/></foreignObject><g class='effeM ct2'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoAQMAAAC2MCouAAAAA1BMVEUAAACnej3aAAAAAXRSTlMAQObYZgAAAAtJREFUCNdjGGEAAADwAAFOldjfAAAAAElFTkSuQmCC'/></foreignObject></g><style> .effect { animation: 0.75s effect infinite alternate ease-in-out; } @keyframes effect { from { transform: translateY(0px); } to { transform: translateY(2.5%); } }.effect2 { animation: 0.75s effect2 infinite altL ernate ease-in-out; } @keyframes effect2 { from { transform: translateY(0px); } to { transform: translateY(1.5%); } } </style> </svg>h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"nako","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 @{"p":"brc-20","op":"deploy","tick":" ","max":"300","lim":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/html;charset=utf-8 <meta charset="UTF-8"> <title>GENERATIVE BTC LOGO</title> <script type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/p5.js/1.5.0/p5.min.js"></script> <script id="snippet-contract-code" type="text/javascript"> const tokenIdRand = (Math.floor(Math.random() * 1000000) + 1) * 1000000 + (Math.floor(Math.random() * 100) + 1); let tokenData = { "tokenId": tokenIdRand, "seed": tokenIdRand.toString(), <script id="snippet-random-code" type="text/javascript"> const urlSeed = new URLSearchParams(window.location.search).get('seed'); if (urlSeed && urlSeed.length > 0) { tokenData.seed = urlSeed; const seed = tokenData.seed function cyrb128($) { let _ = 1779033703, u = 3144134277, i = 1013904242, l = 2773480762; for (let n = 0, r; n < $.length; n++) _ = u ^ Math.imul(_ ^ (r = $.charCodeAt(n)), 597399067), u = i ^ Math.iM mul(u ^ r, 2869860233), i = l ^ Math.imul(i ^ r, 951274213), l = _ ^ Math.imul(l ^ r, 2716044179); return _ = Math.imul(i ^ _ >>> 18, 597399067), u = Math.imul(l ^ u >>> 22, 2869860233), i = Math.imul(_ ^ i >>> 17, 951274213), l = Math.imul(u ^ l >>> 19, 2716044179), [(_ ^ u ^ i ^ l) >>> 0, (u ^ _) >>> 0, (i ^ _) >>> 0, (l ^ _) >>> 0] function sfc32($, _, u, i) { return function () { u >>>= 0, i >>>= 0; var l = ($ >>>= 0) + (_ >>>= 0) | 0; return $ = _ ^ _ >>> 9, _ = u + (u << 3) | 0, u = (u = u << 21 | u >>> 11) + (l = l + (i = i + 1 | 0) | 0) | 0, (l >>> 0) / 4294967296 // IMPORTANT: Instead of Math.random(), use this function mathRand() for random number generation. // This function generates a random number between 0 and 1 with on-chain seed. let mathRand = sfc32(...cyrb128(seed)); position: fixed; right: 0; bottom: 0; left: 0; color: rgb(255, 255, 255); background-color: rgb(0, 0, 0); display: flex; justify-content: center; align-items: center; margin: 0; padding: 0; font-size: 0.8em; /* overflow: hidden; */ object-fit: contain; max-height: 100%; max-width: 100%; #fullScreen { display: flex; position: fixed; right: 0; bottom: 0; left: 0; justify-content: center; align-items: center; #fullScreen canvas { object-fit: contain; max-height: 100%; max-width: 100%; color: rgb(249, 249, 249); opacity: 0.75; background-color: rgb(23, 23, 23); border-radius: 10px; padding-top: 0%; width: auto; height: auto; position: fixed; text-align: center; justify-content: center; align-items: center; top: 50%; left: 50%; -webkit-transform: translate(-50%, -50%); transform: translate(-50%, -50%); #progress h2 { display: block; font-size: 0.9rem; color: rgb(239, 239, 239); margin: 5% font-size: 0.75rem; display: block; margin: 5% #progress hr { width: 75%; margin-bottom: 10% <div id="fullScreen"> <div id="progress"> <script type="text/javascript"> ////////////////INFO & FEATURES let title = "Generative BTC Logo"; let st; const rand = mathRand(); let cnv; let maxBrush = Math.floor(randBetween(500, 1500)) function clr(rand) { if (rand > 0.75) { return 240 } else { return 10 } window.$generativeTraits = { "BG Color": clr(rand), "Force": Math.floor(randBetween(1, 5)), "Brush Size": maxBrush, console.loM g(title + " | smldms 2023.02") console.log(window.$generativeTraits) let img; let balls = []; let maxFrame = 1500; let maxForce = 1; function preload() { img = loadImage('https://gateway.pinata.cloud/ipfs/QmQVs9Xpa5e1JDooNiTPWct2kEorxwqk92A1HkHrn8jx1V'); function setup() { randomSeed(seed); noiseSeed(seed); cnv = createCanvas(1920, 1920, WEBGL); cnv.parent(fullScreen) img.resize(width, height) background(clr(rand)); function draw() { rotateY(sin(frameCount * 0.05) / 25) translate(-width / 2, -height / 2, frameCount * 0.25) let x = mathRand() * width let y = mathRand() * height for (let i = 0; i < balls.length; i++) { balls[i].draw(); balls[i].update(); balls[i].changeColour(); } for (let i = 0; i < balls.length; i++) { if (balls[i].radius < 0) { balls.splice(i, mathRand() * 2); } } if (frameCount < maxFrame) { for (let i = 0; i < 5; i++) { balls.push(neM w Ball(x, y, color(img.get(x + mathRand() * 2, y + mathRand() * 2)))); } } else { noLoop() print('stop') // saver() // timer(2000) } class Ball { constructor(mX, mY, c) { this.location = createVector(mX, mY); this.radius = randBetween(0M this.r = red(c); this.g = green(c); this.b = blue(c); this.a = alpha(c); this.xOff = 0.0; this.yOff = 0.0; } update() { this.radius -= mathRand() * 0.00025; let force = randBetween(0.5, maxForce) this.xOff = this.xOff + randBetween(-force, force); this.nX = noise(this.location.x) * this.xOff; this.yOff = this.yOff + randBetween(-force, force); this.nY = noise(this.location.y) * this.yOff; this.location.x += this.nX; this.location.y += this.nY; } changeColour() { this.c = color(img.get(this.location.x, this.location.y)); this.r = red(this.c); this.g = green(this.c); this.b = blue(this.c); this.a = alpha(this.c); } draw() { noStroke(); fill(this.r, this.g, this.b); let brushSize = round(randBetween(1, maxBrush)); if (this.a > 10) { strokeWeight(randBetween(0.25,0.5)) if (clr(rand) == 240) { stroke(10) } else { stroke(250) } ellipse(this.location.x, this.location.y, this.radius * brushSize, this.radius * brushSize); } else { fill(this.r, this.g, this.b, 100) noStroke() rect(this.location.x, this.location.y, thisM .radius * brushSize / randBetween(2.5, 5)); } } function randBetween(a, b) { if (!b) { return mathRand() * a } return mathRand() * (b - a) + a function keyTyped() { if (keyCode === 83) { // if "s" is pressed save(title + '.png'); } function timer(t) { setTimeout(function () { location.reload(true); }, t); function saver() { save(title + '.png'); </script> <script defer src="https://static.cloudflareinsights.com/beacon.min.js/v2b4487d741ca48dcbadcaf954e159fc61680799950996" integrity="sha512-D/jdE0CypeVxFadTejKGTzmwyV10c1pxZk/AqjJuZbaJwGMyNHY3q/mTPWqMUnFACfCTL unhZUVcd4cV78dK1pQ==" data-cf-beacon='{"rayId":"7b4cebf948125491","version":"2023.3.0","b":1,"token":"6c07c178c94442f695e7a0a2aaee641a","si":100}' crossorigin="anonymous"></script> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":" text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"nako","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"nako","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 @{"p":"brc-20","op":"deploy","tick":" ","max":"300","lim":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 4This is the REAL 1 millionth inscription on Bitcoin.h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"rssc","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":" text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":" text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 J{"p":"brc-20","op":"deploy","tick":"Mili","max":"1000000","lim":"1000000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 0{"p":"sns","op":"reg","name":"sub1million.sats"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! qiTXtXML:com.adobe.xmp ' id='W5M0MpCehiHzreSzNTczkc9d'?> <x:xmpmeta xmlns:x='adobe:ns:meta/'> <rdf:RDF xmlns:rdf='http://www.w3.org/1999/02/22-rdf-syntax-ns#'> <rdf:Description rdf:about='' xmlns:Attrib='http://ns.attribution.com/ads/1.0/'> <rdf:li rdf:parseType='Resource'> <Attrib:Created>2023-04-08</Attrib:Created> <Attrib:ExtId>f73b56e9-7bab-42ae-M bd0c-4f4cf47245ef</Attrib:ExtId> <Attrib:FbId>525265914179580</Attrib:FbId> <Attrib:TouchType>2</Attrib:TouchType> <rdf:Description rdf:about='' xmlns:dc='http://purl.org/dc/elements/1.1/'> <rdf:li xml:lang='x-default'>Jesus - 9</rdf:li> <rdf:Description rdf:about='' xmlns:pdf='http://ns.adobe.com/pdf/1.3/'> <pdf:Author>Lion's Logistics</pdf:Author> <rdf:Description rdf:about='' xmlns:xmp='http://ns.adobe.com/xap/1.0/'> <xmp:CreatorTool>Canva</xmp:CreatorTool> <?xpacket end='r'?>T text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":" text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! sMuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuu text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! riTXtXML:com.adobe.xmp ' id='W5M0MpCehiHzreSzNTczkc9d'?> <x:xmpmeta xmlns:x='adobe:ns:meta/'> <rdf:RDF xmlns:rdf='http://www.w3.org/1999/02/22-rdf-syntax-ns#'> <rdf:Description rdf:about='' xmlns:Attrib='http://ns.attribution.com/ads/1.0/'> <rdf:li rdf:parseType='Resource'> <Attrib:Created>2023-04-08</Attrib:Created> <Attrib:ExtId>8d0e72e8-1ae1-44M 50-af34-8a1be64d8ade</Attrib:ExtId> <Attrib:FbId>525265914179580</Attrib:FbId> <Attrib:TouchType>2</Attrib:TouchType> <rdf:Description rdf:about='' xmlns:dc='http://purl.org/dc/elements/1.1/'> <rdf:li xml:lang='x-default'>Jesus - 15</rdf:li> <rdf:Description rdf:about='' xmlns:pdf='http://ns.adobe.com/pdf/1.3/'> <pdf:Author>Lion's Logistics</pdf:AuthorM <rdf:Description rdf:about='' xmlns:xmp='http://ns.adobe.com/xap/1.0/'> <xmp:CreatorTool>Canva</xmp:CreatorTool> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"rssc","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 *{"p":"sns","op":"reg","name":"ODOGE.sats"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! 1{"p":"sns","op":"reg","name":"vettedcrypto.sats"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"nako","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! .{"p":"sns","op":"reg","name":"bankingon.sats"}h! text/plain;charset=utf-8 @{"p":"brc-20","op":"deploy","tick":" ","max":"300","lim":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":" text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> riTXtXML:com.adobe.xmp ' id='W5M0MpCehiHzreSzNTczkc9d'?> <x:xmpmeta xmlns:x='adobe:ns:meta/'> <rdf:RDF xmlns:rdf='http://www.w3.org/1999/02/22-rdf-syntax-ns#'> <rdf:Description rdf:about='' xmlns:Attrib='http://ns.attribution.com/ads/1.0/'> <rdf:li rdf:parseType='Resource'> <Attrib:Created>2023-04-08</Attrib:Created> <Attrib:ExtId>20ba24f6-e28bM -48c1-ac0d-29f9d9f3ac4c</Attrib:ExtId> <Attrib:FbId>525265914179580</Attrib:FbId> <Attrib:TouchType>2</Attrib:TouchType> <rdf:Description rdf:about='' xmlns:dc='http://purl.org/dc/elements/1.1/'> <rdf:li xml:lang='x-default'>Jesus - 10</rdf:li> <rdf:Description rdf:about='' xmlns:pdf='http://ns.adobe.com/pdf/1.3/'> <pdf:Author>Lion's Logistics</pdf:AutM <rdf:Description rdf:about='' xmlns:xmp='http://ns.adobe.com/xap/1.0/'> <xmp:CreatorTool>Canva</xmp:CreatorTool> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! qiTXtXML:com.adobe.xmp ' id='W5M0MpCehiHzreSzNTczkc9d'?> <x:xmpmeta xmlns:x='adobe:ns:meta/'> <rdf:RDF xmlns:rdf='http://www.w3.org/1999/02/22-rdf-syntax-ns#'> <rdf:Description rdf:about='' xmlns:Attrib='http://ns.attribution.com/ads/1.0/'> <rdf:li rdf:parseType='Resource'> <Attrib:Created>2023-04-08</Attrib:Created> <Attrib:ExtId>5863c6b0-bd21-46M a9-ac86-bc1b2da13135</Attrib:ExtId> <Attrib:FbId>525265914179580</Attrib:FbId> <Attrib:TouchType>2</Attrib:TouchType> <rdf:Description rdf:about='' xmlns:dc='http://purl.org/dc/elements/1.1/'> <rdf:li xml:lang='x-default'>Jesus - 6</rdf:li> <rdf:Description rdf:about='' xmlns:pdf='http://ns.adobe.com/pdf/1.3/'> <pdf:Author>Lion's Logistics</pdf:Author>M <rdf:Description rdf:about='' xmlns:xmp='http://ns.adobe.com/xap/1.0/'> <xmp:CreatorTool>Canva</xmp:CreatorTool> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 thinkingabout.satsh! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! riTXtXML:com.adobe.xmp ' id='W5M0MpCehiHzreSzNTczkc9d'?> <x:xmpmeta xmlns:x='adobe:ns:meta/'> <rdf:RDF xmlns:rdf='http://www.w3.org/1999/02/22-rdf-syntax-ns#'> <rdf:Description rdf:about='' xmlns:Attrib='http://ns.attribution.com/ads/1.0/'> <rdf:li rdf:parseType='Resource'> <Attrib:Created>2023-04-08</Attrib:Created> <Attrib:ExtId>9e9bM 2c9f-c571-4112-8401-04f0e14a1efd</Attrib:ExtId> <Attrib:FbId>525265914179580</Attrib:FbId> <Attrib:TouchType>2</Attrib:TouchType> <rdf:Description rdf:about='' xmlns:dc='http://purl.org/dc/elements/1.1/'> <rdf:li xml:lang='x-default'>Jesus - 18</rdf:li> <rdf:Description rdf:about='' xmlns:pdf='http://ns.adobe.com/pdf/1.3/'> <pdf:Author>Lion's LogisticsM <rdf:Description rdf:about='' xmlns:xmp='http://ns.adobe.com/xap/1.0/'> <xmp:CreatorTool>Canva</xmp:CreatorTool> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"nako","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! riTXtXML:com.adobe.xmp ' id='W5M0MpCehiHzreSzNTczkc9d'?> <x:xmpmeta xmlns:x='adobe:ns:meta/'> <rdf:RDF xmlns:rdf='http://www.w3.org/1999/02/22-rdf-syntax-ns#'> <rdf:Description rdf:about='' xmlns:Attrib='http://ns.attribution.com/ads/1.0/'> <rdf:li rdf:parseType='Resource'> <Attrib:Created>2023-04-08</Attrib:Created> <Attrib:ExtId>43b7852f-2335-42M 3d-9afd-8fc65decbd5d</Attrib:ExtId> <Attrib:FbId>525265914179580</Attrib:FbId> <Attrib:TouchType>2</Attrib:TouchType> <rdf:Description rdf:about='' xmlns:dc='http://purl.org/dc/elements/1.1/'> <rdf:li xml:lang='x-default'>Jesus - 19</rdf:li> <rdf:Description rdf:about='' xmlns:pdf='http://ns.adobe.com/pdf/1.3/'> <pdf:Author>Lion's Logistics</pdf:AuthorM <rdf:Description rdf:about='' xmlns:xmp='http://ns.adobe.com/xap/1.0/'> <xmp:CreatorTool>Canva</xmp:CreatorTool> <?xpacket end='r'?>$ text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":" text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/html;charset=utf-8 <meta charset="utf-8" /> position: relative; width: var(--width); height: var(--height); border: 1px solid blue; position: relative; <div id="upload"> <input id="inputUpload" type="file"> function e(e){"use strict";return new function e(t){let n="global"==t?window:this;n.canvas=document.createElement("canvas");let r=n.canvas.getContext("2d");n.width=100,n.height=100,n.canvas.width=n.width,n.canvas.height=n.height,"offscreen"!=t&&(document.body?document.body.appendChild(n.canvas):window.addEventListener("load",(function(){document.body.appendChild(n.canvas)}))),g(),n.MAGIC=161533525,n.RGB=0,n.HSV=1,n.HM SB=1,n.CHORD=0,n.PIE=1,n.OPEN=2,n.RADIUS=1,n.CORNER=2,n.CORNERS=3,n.ROUND="round",n.SQUARE="butt",n.PROJECT="square",n.MITER="miter",n.BEVEL="bevel",n.CLOSE=1,n.BLEND="source-over",n.REMOVE="destination-out",n.ADD="lighter",n.DARKEST="darken",n.LIGHTEST="lighten",n.DIFFERENCE="difference",n.SUBTRACT="subtract",n.EXCLUSION="exclusion",n.MULTIPLY="multiply",n.SCREEN="screen",n.REPLACE="copy",n.OVERLAY="overlay",n.HARD_LIGHT="hard-light",n.SOFT_LIGHT="soft-light",n.DODGE="color-dodge",n.BURN="color-burn",n.NORMAL="norM mal",n.ITALIC="italic",n.BOLD="bold",n.BOLDITALIC="italic bold",n.CENTER="center",n.LEFT="left",n.RIGHT="right",n.TOP="top",n.BOTTOM="bottom",n.BASELINE="alphabetic",n.LANDSCAPE="landscape",n.PORTRAIT="portrait",n.ALT=18,n.BACKSPACE=8,n.CONTROL=17,n.DELETE=46,n.DOWN_ARROW=40,n.ENTER=13,n.ESCAPE=27,n.LEFT_ARROW=37,n.OPTION=18,n.RETURN=13,n.RIGHT_ARROW=39,n.SHIFT=16,n.TAB=9,n.UP_ARROW=38,n.HALF_PI=Math.PI/2,n.PI=Math.PI,n.QUARTER_PI=Math.PI/4,n.TAU=2*Math.PI,n.TWO_PI=2*Math.PI,n.THRESHOLD=1,n.GRAY=2,n.OPAQUE=3,n.INVEM RT=4,n.POSTERIZE=5,n.DILATE=6,n.ERODE=7,n.BLUR=8,n.ARROW="default",n.CROSS="crosshair",n.HAND="pointer",n.MOVE="move",n.TEXT="text",n.VIDEO={video:!0,audio:!1},n.AUDIO={video:!1,audio:!0},n.SHR3=1,n.LCG=2,n.HARDWARE_FILTERS=!0,n.hint=function(e,t){n[e]=t},n.frameCount=0,n.mouseX=0,n.mouseY=0,n.pmouseX=0,n.pmouseY=0,n.mouseButton=null,n.keyIsPressed=!1,n.mouseIsPressed=!1,n.key=null,n.keyCode=null,n.pixels=null,n.accelerationX=0,n.accelerationY=0,n.accelerationZ=0,n.rotationX=0,n.rotationY=0,n.rotationZ=0,n.relRotatM ionX=0,n.relRotationY=0,n.relRotationZ=0,n.pAccelerationX=0,n.pAccelerationY=0,n.pAccelerationZ=0,n.pRotationX=0,n.pRotationY=0,n.pRotationZ=0,n.pRelRotationX=0,n.pRelRotationY=0,n.pRelRotationZ=0,n.touches=[],n._styleCache=[{colorMode:n.RGB,noStroke:!1,noFill:!1,ellipseMode:n.CENTER,rectMode:n.CORNER,curveDetail:20,curveAlpha:0,textFont:"sans-serif",textSize:12,textLeading:12,textStyle:"normal"}],n._style=n._styleCache[n._styleCache.length-1],n._noLoop=!1,n._pixelDensity=1,n._frameRate=null,n._tint=null;let i=nullM ,o=!0,a=[],l=null,s=0,h={},c=0,u=null,f=null,d=null;Object.defineProperty(n,"deviceOrientation",{get:function(){return 90==Math.abs(window.orientation)?n.LANDSCAPE:n.PORTRAIT}}),Object.defineProperty(n,"windowWidth",{get:function(){return window.innerWidth}}),Object.defineProperty(n,"windowHeight",{get:function(){return window.innerHeight}}),Object.defineProperty(n,"drawingContext",{get:function(){return r}}),n.createCanvas=function(e,t){return n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t,g(),n.canvas},nM .resizeCanvas=function(e,t){n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t},n.createGraphics=n.createImage=function(t,n){let r=new e("offscreen");return r.createCanvas(t,n),r.noLoop(),r},n.pixelDensity=function(e){return null==e||(n._pixelDensity=e,n.canvas.width=Math.ceil(n.width*e),n.canvas.height=Math.ceil(n.height*e),n.canvas.style.width=n.width+"px",n.canvas.style.height=n.height+"px",r.scale(n._pixelDensity,n._pixelDensity),g()),n._pixelDensity},n.map=function(e,t,n,r,i,o){let a=r+1*(e-t)/(n-t)*(i-r)M ;return o?r<i?Math.min(Math.max(a,r),i):Math.min(Math.max(a,i),r):a},n.lerp=function(e,t,n){return e*(1-n)+t*n},n.constrain=function(e,t,n){return Math.min(Math.max(e,t),n)},n.dist=function(){return 4==arguments.length?Math.hypot(arguments[0]-arguments[2],arguments[1]-arguments[3]):Math.hypot(arguments[0]-arguments[3],arguments[1]-arguments[4],arguments[2]-arguments[5])},n.norm=function(e,t,r){return n.map(e,t,r,0,1)},n.sq=function(e){return e*e},n.fract=function(e){return e-Math.floor(e)},n.degrees=function(e){retM urn 180*e/Math.PI},n.radians=function(e){return e*Math.PI/180},n.abs=Math.abs,n.ceil=Math.ceil,n.exp=Math.exp,n.floor=Math.floor,n.log=Math.log,n.mag=Math.hypot,n.max=Math.max,n.min=Math.min,n.round=Math.round,n.sqrt=Math.sqrt,n.sin=Math.sin,n.cos=Math.cos,n.tan=Math.tan,n.asin=Math.asin,n.acos=Math.acos,n.atan=Math.atan,n.atan2=Math.atan2,n.Vector=function(e,t,r){let i=this;i.x=e||0,i.y=t||0,i.z=r||0;let o=null,a=null;function l(e,t,n){return null!=e.x?e:null!=t?{x:e,y:t,z:n||0}:{x:e,y:e,z:e}}function s(){null==a&M &(a=i.x*i.x+i.y*i.y+i.z*i.z,o=Math.sqrt(a))}function h(){a=null,o=null}i.set=function(e,t,n){i.x=e||0,i.y=t||0,i.z=n||0},i.copy=function(){return new n.Vector(i.x,i.y,i.z)},i.add=function(){let e=l.apply(null,arguments);return i.x+=e.x,i.y+=e.y,i.z+=e.z,h(),i},i.rem=function(){let e=l.apply(null,arguments);return i.x%=e.x,i.y%=e.y,i.z%=e.z,h(),i},i.sub=function(){let e=l.apply(null,arguments);return i.x-=e.x,i.y-=e.y,i.z-=e.z,h(),i},i.mult=function(){let e=l.apply(null,arguments);return i.x*=e.x,i.y*=e.y,i.z*=e.z,hM (),i},i.div=function(){let e=l.apply(null,arguments);return i.x/=e.x,i.y/=e.y,i.z/=e.z,h(),i},i.mag=function(){return s(),o},i.magSq=function(){return s(),a},i.dot=function(){let e=l.apply(null,arguments);return i.x*e.x+i.y*e.y+i.z*e.z},i.dist=function(){let e=l.apply(null,arguments),t=i.x-e.x,n=i.y-e.y,r=i.z-e.z;return Math.sqrt(t*t+n*n+r*r)},i.cross=function(){let e=l.apply(null,arguments),t=i.y*e.z-i.z*e.y,n=i.z*e.x-i.x*e.z,r=i.x*e.y-i.y*e.x;return i.x=t,i.y=n,i.z=r,h(),i},i.normalize=function(){s();let e=o;retuM rn i.x/=e,i.y/=e,i.z/=e,o=1,a=1,i},i.limit=function(e){s();if(o>e){let t=e/o;i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e}return i},i.setMag=function(e){s();let t=e/o;return i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e,i},i.heading=function(){return Math.atan2(i.y,i.x)},i.rotate=function(e){let t=Math.cos(e),n=Math.sin(e),r=i.x*t-i.y*n,o=i.x*n+i.y*t;return i.x=r,i.y=o,i},i.angleBetween=function(){let e=l.apply(null,arguments);const t=i.dot(e)/(i.mag()*e.mag());let n;return n=Math.acos(Math.min(1,Math.max(-1,t))),n*Math.sign(i.cross(e).z||1)},M i.lerp=function(e,t){return i.x=i.x*(1-t)+e.x*t,i.y=i.y*(1-t)+e.y*t,i.z=i.z*(1-t)+e.z*t,h(),i},i.reflect=function(e){return e.normalize(),i.sub(e.mult(2*i.dot(e)))},i.array=function(){return[i.x,i.y,i.z]},i.equals=function(e,t){return null==t&&null==(t=Number.EPSILON)&&(t=0),Math.abs(e.x-i.x)<t&&Math.abs(e.y-i.y)<t&&Math.abs(e.z-i.z)<t},i.fromAngle=function(e,t){return null==t&&(t=1),o=t,a=t*t,i.x=t*Math.cos(e),i.y=t*Math.sin(e),i.z=0,i},i.fromAngles=function(e,t,n){null==n&&(n=1),o=n,a=n*n;const r=Math.cos(t),l=MaM th.sin(t),s=Math.cos(e),h=Math.sin(e);return i.x=n*h*l,i.y=-n*s,i.z=n*h*r,i},i.random2D=function(){return o=1,a=1,i.fromAngle(Math.random()*Math.PI*2)},i.random3D=function(){return o=1,a=1,i.fromAngles(Math.random()*Math.PI*2,Math.random()*Math.PI*2)},i.toString=function(){return`[${i.x}, ${i.y}, ${i.z}]`}},n.Vector.add=function(e,t){return new n.Vector(e.x+t.x,e.y+t.y,e.z+t.z)},n.Vector.rem=function(e,t){return new n.Vector(e.x%t.x,e.y%t.y,e.z%t.z)},n.Vector.sub=function(e,t){return new n.Vector(e.x-t.x,e.y-t.y,e.M z-t.z)},n.Vector.mult=function(e,t){return null==t.x?new n.Vector(e.x*t,e.y*t,e.z*t):new n.Vector(e.x*t.x,e.y*t.y,e.z*t.z)},n.Vector.div=function(e,t){return null==t.x?new n.Vector(e.x/t,e.y/t,e.z/t):new n.Vector(e.x/t.x,e.y/t.y,e.z/t.z)},n.Vector.dist=function(e,t){return Math.hypot(e.x-t.x,e.y-t.y,e.z-t.z)},n.Vector.cross=function(e,t){return new n.Vector(e.y*t.z-e.z*t.y,e.z*t.x-e.x*t.z,e.x*t.y-e.y*t.x)},n.Vector.lerp=function(e,t,r){return new n.Vector(e.x*(1-r)+t.x*r,e.y=e.y*(1-r)+t.y*r,e.z=e.z*(1-r)+t.z*r)},n.M Vector.equals=function(e,t,n){return e.equals(t,n)};for(let e of["fromAngle","fromAngles","random2D","random3D"])n.Vector[e]=function(t,r,i){return(new n.Vector)[e](t,r,i)};function x(e,t,n){let r,i,o,a,l,s,h,c,u;if(0==t)return[255*(r=n),255*(i=n),255*(o=n)];switch((a=e)>360&&(a=0),h=n*(1-t),c=n*(1-t*(s=(a/=60)-(l=~~a))),u=n*(1-t*(1-s)),l){case 0:r=n,i=u,o=h;break;case 1:r=c,i=n,o=h;break;case 2:r=h,i=n,o=u;break;case 3:r=h,i=c,o=n;break;case 4:r=u,i=h,o=n;break;default:r=n,i=h,o=c}return[255*r,255*i,255*o]}functioM n g(){r.fillStyle="white",r.strokeStyle="black",r.lineCap="round",r.lineJoin="miter"}function p(e){if(0<=e&&e<2*Math.PI)return e;for(;e<0;)e+=2*Math.PI;for(;e>=Math.PI;)e-=2*Math.PI;return e}function m(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;let c=p(a),u=p(l);r.beginPath();for(let a=0;a<h+1;a++){let l=a/h,s=n.lerp(c,u,l),f=Math.cos(s)*i/2,d=Math.sin(s)*o/2;r[a?"lineTo":"moveTo"](e+f,t+d)}s==n.CHORD?r.closePath():s==n.PIE&&(r.lineTo(e,t),r.closePath()),n._style.noFill||r.fill(),n._style.noStrokM e||r.stroke()}function b(e,t,i,o){n._style.noFill&&n._style.noStroke||(r.beginPath(),r.ellipse(e,t,i/2,o/2,0,0,2*Math.PI),n._style.noFill||r.fill(),n._style.noStroke||r.stroke())}function y(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;if(null==a)return function(e,t,i,o){n._style.noFill||r.fillRect(e,t,i,o),n._style.noStroke||r.strokeRect(e,t,i,o)}(e,t,i,o);if(null==l)return y(e,t,i,o,a,a,a,a);const c=Math.min(Math.abs(o),Math.abs(i))/2;a=Math.min(c,a),l=Math.min(c,l),h=Math.min(c,h),s=Math.min(c,s)M ,r.beginPath(),r.moveTo(e+a,t),r.arcTo(e+i,t,e+i,t+o,l),r.arcTo(e+i,t+o,e,t+o,s),r.arcTo(e,t+o,e,t,h),r.arcTo(e,t,e+i,t,a),r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke()}function w(){a=[]}n.createVector=function(e,t,r){return new n.Vector(e,t,r)},n.curvePoint=function(e,t,n,r,i){const o=i*i*i,a=i*i;return e*(-.5*o+a-.5*i)+t*(1.5*o-2.5*a+1)+n*(-1.5*o+2*a+.5*i)+r*(.5*o-.5*a)},n.bezierPoint=function(e,t,n,r,i){const o=1-i;return Math.pow(o,3)*e+3*Math.pow(o,2)*i*t+3*o*Math.pow(i,2)*n+Math.pow(i,M 3)*r},n.curveTangent=function(e,t,n,r,i){const o=i*i;return e*(-3*o/2+2*i-.5)+t*(9*o/2-5*i)+n*(-9*o/2+4*i+.5)+r*(3*o/2-i)},n.bezierTangent=function(e,t,n,r,i){const o=1-i;return 3*r*Math.pow(i,2)-3*n*Math.pow(i,2)+6*n*o*i-6*t*o*i+3*t*Math.pow(o,2)-3*e*Math.pow(o,2)},n.Color=function(e,t,n,r){let i=this;i.MAGIC=786698,i._r=e,i._g=t,i._b=n,i._a=r,i._h=0,i._s=0,i._v=0,i._hsvInferred=!1,i.setRed=function(e){i._r=e,i._hsvInferred=!1},i.setGreen=function(e){i._g=e,i._hsvInferred=!1},i.setBlue=function(e){i._b=e,i._hsvInfM erred=!1},i.setAlpha=function(e){i._a=e/255,i._hsvInferred=!1},i._inferHSV=function(){i._hsvInferred||([i._h,i._s,i._v]=function(e,t,n){let r,i,o,a,l;return r=e<t?e<n?e:n:t<n?t:n,0==(l=100*(i=e>t?e>n?e:n:t>n?t:n)/255)?[o=0,a=0,l]:0==(a=100*(i-r)/i)?[o=0,a,l]:(o=i==e?0+60*(t-n)/(i-r):i==t?120+60*(n-e)/(i-r):240+60*(e-t)/(i-r),[o,a,l])}(i._r,i._g,i._b),i._hsvInferred=!0)},i.toString=function(){return`rgba(${Math.round(i._r)},${Math.round(i._g)},${Math.round(i._b)},${~~(1e3*i._a)/1e3})`}},n.colorMode=function(e){n._stM yle.colorMode=e},n.color=function(){if(1==arguments.length&&786698==arguments[0].MAGIC)return arguments[0];if(n._style.colorMode==n.RGB){if(1==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],1);if(2==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],arguments[1]/255);if(3==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],1);if(4==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],arguments[3]/255)}else{if(1==argumeM nts.length)return new n.Color(...x(0,0,arguments[0]/100),1);if(2==arguments.length)return new n.Color(...x(0,0,arguments[0]/100),arguments[1]/255);if(3==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),1);if(4==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),arguments[3])}return null},n.red=function(e){return e._r},n.green=function(e){return e._g},n.blue=function(e){return e._b},n.alpha=function(e){return 255*e._a},n.hue=function(e){reM turn e._inferHSV(),e._h},n.saturation=function(e){return e._inferHSV(),e._s},n.brightness=function(e){return e._inferHSV(),e._v},n.lightness=function(e){return 100*(.2126*e._r+.7152*e._g+.0722*e._b)/255},n.lerpColor=function(e,t,r){return n._style.colorMode==n.RGB?new n.Color(n.constrain(n.lerp(e._r,t._r,r),0,255),n.constrain(n.lerp(e._g,t._g,r),0,255),n.constrain(n.lerp(e._b,t._b,r),0,255),n.constrain(n.lerp(e._a,t._a,r),0,1)):(e._inferHSV(),t._inferHSV(),new n.Color(n.constrain(function(e,t,r){var i=[[Math.abs(t-M e),n.map(r,0,1,e,t)],[Math.abs(t+360-e),n.map(r,0,1,e,t+360)],[Math.abs(t-360-e),n.map(r,0,1,e,t-360)]];return i.sort(((e,t)=>e[0]-t[0])),(i[0][1]+720)%360}(e._h,t._h,r),0,360),n.constrain(n.lerp(e._s,t._s,r),0,100),n.constrain(n.lerp(e._v,t._v,r),0,100),n.constrain(n.lerp(e._a,t._a,r),0,1)))},n.strokeWeight=function(e){n._style_noStroke=!1,r.lineWidth=e},n.stroke=function(){if(n._style.noStroke=!1,"string"==typeof arguments[0])return void(r.strokeStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._sM tyle.noStroke=!0:r.strokeStyle=e},n.noStroke=function(){n._style.noStroke=!0},n.fill=function(){if(n._style.noFill=!1,"string"==typeof arguments[0])return void(r.fillStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._style.noFill=!0:r.fillStyle=e},n.noFill=function(){n._style.noFill=!0},n.blendMode=function(e){r.globalCompositeOperation=e},n.strokeCap=function(e){r.lineCap=e},n.strokeJoin=function(e){r.lineJoin=e},n.ellipseMode=function(e){n._style.ellipseMode=e},n.rectMode=function(e){n._style.rectM Mode=e},n.curveDetail=function(e){n._style.curveDetail=e},n.curveAlpha=function(e){n._style.curveAlpha=e},n.curveTightness=function(e){n._style.curveAlpha=e},n.clear=function(){r.clearRect(0,0,n.width,n.height)},n.background=function(){if(arguments[0]&&arguments[0].MAGIC==n.MAGIC)return n.image(arguments[0],0,0,n.width,n.height);r.save(),r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity),r.fillStyle="string"==typeof arguments[0]?arguments[0]:n.color(...Array.from(arguments)),r.fillRect(0,0,n.width,n.heightM ),r.restore()},n.line=function(e,t,i,o){n._style.noStroke||(r.beginPath(),r.moveTo(e,t),r.lineTo(i,o),r.stroke())},n.arc=function(e,t,r,i,o,a,l,s){if(o==a)return n.ellipse(e,t,r,i);null==s&&(s=25),null==l&&(l=n.PIE),n._style.ellipseMode==n.CENTER?m(e,t,r,i,o,a,l,s):n._style.ellipseMode==n.RADIUS?m(e,t,2*r,2*i,o,a,l,s):n._style.ellipseMode==n.CORNER?m(e+r/2,t+i/2,r,i,o,a,l,s):n._style.ellipseMode==n.CORNERS&&m((e+r)/2,(t+i)/2,r-e,i-t,o,a,l,s)},n.ellipse=function(e,t,r,i){null==i&&(i=r),n._style.ellipseMode==n.CENTERM ?b(e,t,r,i):n._style.ellipseMode==n.RADIUS?b(e,t,2*r,2*i):n._style.ellipseMode==n.CORNER?b(e+r/2,t+i/2,r,i):n._style.ellipseMode==n.CORNERS&&b((e+r)/2,(t+i)/2,r-e,i-t)},n.circle=function(e,t,r){return n.ellipse(e,t,r,r)},n.point=function(e,t){e.x&&(t=e.y,e=e.x),r.beginPath(),r.ellipse(e,t,.4,.4,0,0,2*Math.PI),r.stroke()},n.rect=function(e,t,r,i,o,a,l,s){n._style.rectMode==n.CENTER?y(e-r/2,t-i/2,r,i,o,a,l,s):n._style.rectMode==n.RADIUS?y(e-r,t-i,2*r,2*i,o,a,l,s):n._style.rectMode==n.CORNER?y(e,t,r,i,o,a,l,s):n._stylM e.rectMode==n.CORNERS&&y(e,t,r-e,i-t,o,a,l,s)},n.square=function(e,t,r,i,o,a,l){return n.rect(e,t,r,r,i,o,a,l)},n.beginShape=function(){w(),r.beginPath(),o=!0},n.beginContour=function(){r.closePath(),w(),o=!0},n.endContour=function(){w(),o=!0},n.vertex=function(e,t){w(),o?r.moveTo(e,t):r.lineTo(e,t),o=!1},n.bezierVertex=function(e,t,n,i,o,a){w(),r.bezierCurveTo(e,t,n,i,o,a)},n.quadraticVertex=function(e,t,n,i){w(),r.quadraticCurveTo(e,t,n,i)},n.bezier=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.bezierVM ertex(r,i,o,a,l,s),n.endShape()},n.triangle=function(e,t,r,i,o,a){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.endShape(n.CLOSE)},n.quad=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.vertex(l,s),n.endShape(n.CLOSE)},n.endShape=function(e){w(),e&&r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke(),n._style.noFill&&n._style.noStroke&&(r.save(),r.fillStyle="none",r.fill(),r.restore())},n.curveVertex=function(e,t){if(a.push([e,t]),a.length<4)return;M let i=function(e,t,n,r,i,o,a,l,s,h){function c(e,t,n,r,i,o){let a=Math.pow(r-t,2)+Math.pow(i-n,2);return Math.pow(a,.5*o)+e}let u=[],f=c(0,e,t,n,r,h),d=c(f,n,r,i,o,h),x=c(d,i,o,a,l,h);for(let h=0;h<s;h++){let c=f+h/(s-1)*(d-f),g=[(f-c)/(f-0),(c-0)/(f-0),(d-c)/(d-f),(c-f)/(d-f),(x-c)/(x-d),(c-d)/(x-d),(d-c)/(d-0),(c-0)/(d-0),(x-c)/(x-f),(c-f)/(x-f)];for(let e=0;e<g.length;e+=2)isNaN(g[e])&&(g[e]=1,g[e+1]=0),isFinite(g[e])||(g[e]>0?(g[e]=1,g[e+1]=0):(g[e]=0,g[e+1]=1));let p=e*g[0]+n*g[1],m=t*g[0]+r*g[1],b=n*g[2]+i*g[M 3],y=r*g[2]+o*g[3],w=i*g[4]+a*g[5],v=o*g[4]+l*g[5],z=p*g[6]+b*g[7],V=m*g[6]+y*g[7],_=b*g[8]+w*g[9],M=y*g[8]+v*g[9],E=z*g[2]+_*g[3],S=V*g[2]+M*g[3];u.push([E,S])}return u}(...a[a.length-4],...a[a.length-3],...a[a.length-2],...a[a.length-1],n._style.curveDetail,n._style.curveAlpha);for(let e=0;e<i.length;e++)o?r.moveTo(...i[e]):r.lineTo(...i[e]),o=!1},n.curve=function(e,t,r,i,o,a,l,s){n.beginShape(),n.curveVertex(e,t),n.curveVertex(r,i),n.curveVertex(o,a),n.curveVertex(l,s),n.endShape()},n.translate=function(e,t){r.tM ranslate(e,t)},n.rotate=function(e){r.rotate(e)},n.scale=function(e,t){null==t&&(t=e),r.scale(e,t)},n.applyMatrix=function(e,t,n,i,o,a){r.transform(e,t,n,i,o,a)},n.shearX=function(e){r.transform(1,0,Math.tan(e),1,0,0)},n.shearY=function(e){r.transform(1,Math.tan(e),0,1,0,0)},n.resetMatrix=function(){r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity)},n.pushMatrix=n.push=function(){n._styleCache.push({...n._style}),n._style=n._styleCache[n._styleCache.length-1],r.save()},n.popMatrix=n.pop=function(){n._stylM eCache.length-1&&(n._styleCache.pop(),n._style=n._styleCache[n._styleCache.length-1],r.restore())},n.image=function(e,t,i,o,a,l,s,h,c){let u=e.MAGIC==n.MAGIC?e.canvas:e;function d(){if(e.MAGIC!=n.MAGIC||!n._tint)return;let t=e.canvas.getContext("2d");t.save(),t.resetTransform(),t.clearRect(0,0,t.canvas.width,t.canvas.height),t.drawImage(f.canvas,0,0),t.restore()}return e.MAGIC==n.MAGIC&&null!=n._tint&&(function(e,t){null==f&&(f=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvasM .height),f.canvas.width==e&&f.canvas.height==t||(f.canvas.width=e,f.canvas.height=t)}(e.canvas.width,e.canvas.height),f.drawImage(e.canvas,0,0),e.tinted(n._tint)),o?l?(h||(h=u.width),c||(c=u.height),r.drawImage(u,l,s,h,c,t,i,o,a),void d()):(r.drawImage(u,t,i,o,a),void d()):(e.MAGIC==n.MAGIC||e.width?r.drawImage(u,t,i,e.width,e.height):r.drawImage(u,t,i,e.videoWidth,e.videoHeight),void d())},n.loadPixels=function(){l=r.getImageData(0,0,n.canvas.width,n.canvas.height),n.pixels=l.data},n.updatePixels=function(){null!=M l&&r.putImageData(l,0,0)},n.loadImage=function(e,t){s++;let r=n.createGraphics(100,100),i=r.canvas.getContext("2d"),o=new Image;return o.src=e,o.crossOrigin="Anonymous",o.onload=function(){i.canvas.width=o.width,i.canvas.height=o.height,r.width=o.width,r.height=o.height,i.drawImage(o,0,0),s--,t&&t(r)},r};let v={};function z(e,t){null==u&&(u=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvas.height),u.canvas.width==e&&u.canvas.height==t||(u.canvas.width=e,u.canvas.height=t)}funcM tion V(){let e=r.canvas.width*r.canvas.height*4;null!=d&&e==d.length||(d=new Uint8ClampedArray(e))}function _(e){u.clearRect(0,0,u.canvas.width,u.canvas.height),u.filter=e,u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()}v[n.THRESHOLD]=function(e,t){null==t?t=127.5:t*=255;for(let n=0;n<e.length;n+=4){const r=.2126*e[n]+.7152*e[n+1]+.0722*e[n+2];e[n]=e[n+1]=e[n+2]=r>=t?255:0}},v[n.GRAY]=function(e){for(let t=0;t<e.length;t+=4)M {const n=.2126*e[t]+.7152*e[t+1]+.0722*e[t+2];e[t]=e[t+1]=e[t+2]=n}},v[n.OPAQUE]=function(e){for(let t=0;t<e.length;t+=4)e[t+3]=255},v[n.INVERT]=function(e){for(let t=0;t<e.length;t+=4)e[t]=255-e[t],e[t+1]=255-e[t+1],e[t+2]=255-e[t+2]},v[n.POSTERIZE]=function(e,t){let n=t-1;for(let r=0;r<e.length;r+=4)e[r]=255*(e[r]*t>>8)/n,e[r+1]=255*(e[r+1]*t>>8)/n,e[r+2]=255*(e[r+2]*t>>8)/n},v[n.DILATE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-M 1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.max(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.ERODE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.min(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.BLURM ]=function(e,t){t=t||1,t=Math.floor(t*n._pixelDensity),V(),d.set(e);let i=2*t+1,o=function(e){let n=new Float32Array(e),r=.3*t+.8,i=r*r*2;for(let t=0;t<e;t++){let o=t-e/2,a=Math.exp(-o*o/i)/(2.5066282746*r);n[t]=a}return n}(i),[a,l]=[r.canvas.width,r.canvas.height];for(let n=0;n<l;n++)for(let r=0;r<a;r++){let l=0,s=0,h=0,c=0;for(let e=0;e<i;e++){let i=4*(n*a+Math.min(Math.max(r-t+e,0),a-1));l+=d[i]*o[e],s+=d[i+1]*o[e],h+=d[i+2]*o[e],c+=d[i+3]*o[e]}let u=4*(n*a+r);e[u]=l,e[u+1]=s,e[u+2]=h,e[u+3]=c}d.set(e);for(let nM =0;n<l;n++)for(let r=0;r<a;r++){let s=0,h=0,c=0,u=0;for(let e=0;e<i;e++){let i=4*(Math.min(Math.max(n-t+e,0),l-1)*a+r);s+=d[i]*o[e],h+=d[i+1]*o[e],c+=d[i+2]*o[e],u+=d[i+3]*o[e]}let f=4*(n*a+r);e[f]=s,e[f+1]=h,e[f+2]=c,e[f+3]=u}},n.filter=function(e,t){if(n.HARDWARE_FILTERS&&null!=r.filter)if(z(),e==n.THRESHOLD){null==t&&(t=.5),t=Math.max(t,1e-5),_(`saturate(0%) brightness(${Math.floor(.5/t*100)}%) contrast(1000000%)`)}else if(e==n.GRAY)_("saturate(0%)");else if(e==n.OPAQUE)u.fillStyle="black",u.fillRect(0,0,u.canvaM s.width,u.canvas.height),u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.drawImage(u.canvas,0,0),r.restore();else if(e==n.INVERT)_("invert(100%)");else if(e==n.BLUR)_(`blur(${Math.ceil(t*n._pixelDensity/1)||1}px)`);else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}},n.resize=function(e,t){z(),u.drawImage(r.canvas,0,0),n.width=e,n.height=t,r.canvas.width=e*n._pixM elDensity,r.canvas.height=t*n._pixelDensity,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0,r.canvas.width,r.canvas.height),r.restore()},n.get=function(e,t,i,o){if(null!=e&&null==i){let i=r.getImageData(e,t,1,1).data;return new n.Color(i[0],i[1],i[2],i[3]/255)}e=e||0,t=t||0,i=i||n.width,o=o||n.height;let a=n.createGraphics(i,o);a.pixelDensity(n._pixelDensity);let l=r.getImageData(e*n._pixelDensity,t*n._pixelDensity,i*n._pixelDensity,o*n._pixelDensity);return a.caM nvas.getContext("2d").putImageData(l,0,0),a},n.set=function(e,t,i){if(i.MAGIC==n.MAGIC){let r=n._tint;return n._tint=null,n.image(i,e,t),void(n._tint=r)}let o=4*(t*n._pixelDensity*r.canvas.width+e*n._pixelDensity);n.pixels[o]=i._r,n.pixels[o+1]=i._g,n.pixels[o+2]=i._b,n.pixels[o+3]=255*i._a},n.tinted=function(){let e=n.color(...Array.from(arguments)),t=e._a;e._a=1,z(),u.clearRect(0,0,u.canvas.width,u.canvas.height),u.fillStyle=e,u.fillRect(0,0,u.canvas.width,u.canvas.height),u.globalCompositeOperation="multiply",u.M drawImage(r.canvas,0,0),u.globalCompositeOperation="source-over",r.save(),r.resetTransform();let i=r.globalCompositeOperation;r.globalCompositeOperation="source-in",r.drawImage(u.canvas,0,0),r.globalCompositeOperation=i,r.restore(),u.globalAlpha=t,u.clearRect(0,0,u.canvas.width,u.canvas.height),u.drawImage(r.canvas,0,0),u.globalAlpha=1,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()},n.tint=function(){n._tint=n.color(...Array.from(arguments))},n.noTiM nt=function(){n._tint=null},n.mask=function(e){r.save(),r.resetTransform();let t=r.globalCompositeOperation;r.globalCompositeOperation="destination-in",r.drawImage(e.canvas,0,0),r.globalCompositeOperation=t,r.restore()},n.clearTemporaryBuffers=function(){u=null,f=null,d=null},n.save=function(e,t){e=e||"untitled",t=t||"png";var n=document.createElement("a");n.innerHTML="[Download]",n.addEventListener("click",(function(){this.href=r.canvas.toDataURL(),this.download=e+"."+t}),!1),document.body.appendChild(n),n.click()M ,document.body.removeChild(n)},n.saveCanvas=function(e,t,r){if(e.MAGIC==n.MAGIC){r&&e.save(t,r);let n=t.split(".");return e.save(n.slice(0,-1).join("."),n[n.length-1])}if(t)return n.save(e,t);let i=e.split(".");return n.save(i.slice(0,-1).join("."),i[i.length-1])},n.loadFont=function(e){let t=e.split("/"),n=t[t.length-1].split(".")[0].replace(" ",""),r=`@font-face {\n font-family: '${n}';\n src: url('${e}');\n }`;const i=document.createElement("style");return i.textContent=r,document.head.append(M i),n},n.textFont=function(e){n._style.textFont=e},n.textSize=function(e){n._style.textSize=e,n._style.textLeading=e},n.textLeading=function(e){n._style.textLeading=e},n.textStyle=function(e){n._style.textStyle=e},n.textAlign=function(e,t){r.textAlign=e,t&&(r.textBaseline=t==n.CENTER?"middle":t)},n.text=function(e,t,i,o){if(!e)return;if(e=e.toString(),n._style.noFill&&n._style.noStroke)return;r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`;let a=e.split("\n");for(let e=0;e<a.length;e++)n._M style.noFill||r.fillText(a[e],t,i,o),n._style.noStroke||r.strokeText(a[e],t,i,o),i+=n._style.textLeading},n.textWidth=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).width},n.textAscent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBoundingBoxAscent},n.textDescent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBounM dingBoxDescent};var M,E=4,S=.5,R=function(e){return.5*(1-Math.cos(e*Math.PI))};n.noise=function(e,t,n){if(t=t||0,n=n||0,null==M){M=new Array(4096);for(var r=0;r<4096;r++)M[r]=Math.random()}e<0&&(e=-e),t<0&&(t=-t),n<0&&(n=-n);for(var i,o,a,l,s,h=Math.floor(e),c=Math.floor(t),u=Math.floor(n),f=e-h,d=t-c,x=n-u,g=0,p=.5,m=0;m<E;m++){var b=h+(c<<4)+(u<<8);i=R(f),o=R(d),a=M[4095&b],a+=i*(M[b+1&4095]-a),l=M[b+16&4095],a+=o*((l+=i*(M[b+16+1&4095]-l))-a),l=M[4095&(b+=256)],l+=i*(M[b+1&4095]-l),s=M[b+16&4095],l+=o*((s+=i*(M[M b+16+1&4095]-s))-l),g+=(a+=R(x)*(l-a))*p,p*=S,h<<=1,c<<=1,u<<=1,(f*=2)>=1&&(h++,f--),(d*=2)>=1&&(c++,d--),(x*=2)>=1&&(u++,x--)}return g},n.noiseDetail=function(e,t){e>0&&(E=e),t>0&&(S=t)};const I=function(){let e,t,n=4294967295;return{setSeed(r){e=t=(null==r?Math.random()*n:r)>>>0},getSeed:()=>t,rand:()=>(e^=e<<17,e^=e>>13,((e^=e<<5)>>>0)/n)}};let C=I();C.setSeed(),n.noiseSeed=function(e){let t=null==e?4294967295*Math.random():e;M||(M=new Float32Array(4096));for(var n=0;n<4096;n++)t^=t<<17,t^=t>>13,t^=t<<5,M[n]=(t>M >>0)/4294967295},n.randomSeed=function(e){C.setSeed(e)},n.random=function(e,t){return null==e?C.rand():"number"==typeof e?null!=t?C.rand()*(t-e)+e:C.rand()*e:e[~~(e.length*C.rand())]},n.randomGenerator=function(e){e==n.LCG?C=function(){const e=4294967296;let t,n;return{setSeed(r){n=t=(null==r?Math.random()*e:r)>>>0},getSeed:()=>t,rand:()=>(n=(1664525*n+1013904223)%e)/e}}():e==n.SHR3&&(C=I()),C.setSeed()};var T=new function(){var e,t,n,r=new Array(128),i=new Array(256),o=new Array(128),a=new Array(128),l=new Array(2M 56),s=new Array(256),h=function(){return 4294967296*C.rand()-2147483648},c=function(){return.5+2.328306e-10*(h()<<0)};this.SHR3=h,this.UNI=c,this.RNOR=function(){return n=h(),e=127&n,Math.abs(n)<r[e]?n*o[e]:function(){for(var t,i,l,s,u=3.44262;;){if(t=n*o[e],0==e){do{l=c(),s=c(),t=.2904764*-Math.log(l),i=-Math.log(s)}while(i+i<t*t);return n>0?u+t:-u-t}if(a[e]+c()*(a[e-1]-a[e])<Math.exp(-.5*t*t))return t;if(n=h(),e=127&n,Math.abs(n)<r[e])return n*o[e]}}()},this.REXP=function(){return(t=h()>>>0)<r[e=255&t]?t*l[e]:funM ction(){for(var n;;){if(0==e)return 7.69711-Math.log(c());if(n=t*l[e],s[e]+c()*(s[e-1]-s[e])<Math.exp(-n))return n;if((t=h())<i[e=255&t])return t*l[e]}}()},this.zigset=function(){var e,t,n=2147483648,h=4294967296,c=3.442619855899,u=c,f=.00991256303526217,d=7.697117470131487,x=d,g=.003949659822581572;for(e=f/Math.exp(-.5*c*c),r[0]=Math.floor(c/e*n),r[1]=0,o[0]=e/n,o[127]=c/n,a[0]=1,a[127]=Math.exp(-.5*c*c),t=126;t>=1;t--)c=Math.sqrt(-2*Math.log(f/c+Math.exp(-.5*c*c))),r[t+1]=Math.floor(c/u*n),u=c,a[t]=Math.exp(-.5*cM *c),o[t]=c/n;for(e=g/Math.exp(-d),i[0]=Math.floor(d/e*h),i[1]=0,l[0]=e/h,l[255]=d/h,s[0]=1,s[255]=Math.exp(-d),t=254;t>=1;t--)d=-Math.log(g/d+Math.exp(-d)),i[t+1]=Math.floor(d/x*h),x=d,s[t]=Math.exp(-d),l[t]=d/h}};T.hasInit=!1,n.randomGaussian=function(e,t){return T.hasInit||(T.zigset(),T.hasInit=!0),T.RNOR()*t+e},n.randomExponential=function(){return T.hasInit||(T.zigset(),T.hasInit=!0),T.REXP()},n.print=console.log,n.cursor=function(e,t,r){let i="";e.includes(".")&&(e=`url("${e}")`,i=", auto"),null!=t&&(e+=" "+t+M " "+r),n.canvas.style.cursor=e+i},n.noCursor=function(){n.canvas.style.cursor="none"},n.createCapture=function(e){var t=document.createElement("video");return t.playsinline="playsinline",t.autoplay="autoplay",navigator.mediaDevices.getUserMedia(e).then((function(e){t.srcObject=e})),t.style.position="absolute",t.style.opacity=1e-5,t.style.zIndex=-1e3,document.body.appendChild(t),t};let A=["setup","draw","preload","mouseMoved","mousePressed","mouseReleased","mouseDragged","mouseClicked","keyPressed","keyReleased","keM yTyped","touchStarted","touchEnded"];for(let e of A){let t="_"+e+"Fn";n[t]=function(){},n[t].isPlaceHolder=!0,n[e]?n[t]=n[e]:Object.defineProperty(n,e,{set:function(e){n[t]=e}})}function D(){n._noLoop||(i=null==n._frameRate?requestAnimationFrame(D):setTimeout(D,1e3/n._frameRate)),w(),o=!0,n.push(),n._drawFn(),n.pop(),++n.frameCount}function k(e){const t=n.canvas.getBoundingClientRect(),r=n.canvas.scrollWidth/n.width||1,i=n.canvas.scrollHeight/n.height||1;return{x:(e.clientX-t.left)/r,y:(e.clientY-t.top)/i,id:e.idenM tifier}}function L(){return n._touchStarted.isPlaceHolder&&n._touchMoved.isPlaceHolder&&n._touchEnded.isPlaceHolder}n.noLoop=function(){n._noLoop=!0,i=null},n.loop=function(){n._noLoop=!1,null==i&&D()},n.redraw=function(){D()},n.frameRate=function(e){n._frameRate=e},setTimeout((function(){n._preloadFn(),c=window.performance.now(),function e(){if(s>0)return setTimeout(e,10);n._setupFn(),D()}()}),1),n.canvas.onmousemove=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPM ressed?n._mouseDraggedFn(e):n._mouseMovedFn(e)},n.canvas.onmousedown=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!0,n.mouseButton=[n.LEFT,n.CENTER,n.RIGHT][e.button],n._mousePressedFn(e)},n.canvas.onmouseup=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!1,n._mouseReleasedFn(e)},n.canvas.onclick=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressedM =!0,n._mouseClickedFn(e),n.mouseIsPressed=!1},window.addEventListener("keydown",(function(e){n.keyIsPressed=!0,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!0,n._keyPressedFn(e),1==e.key.length&&n._keyTypedFn(e)})),window.addEventListener("keyup",(function(e){n.keyIsPressed=!1,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!1,n._keyReleasedFn(e)})),n.keyIsDown=function(e){return!!h[e]},n.canvas.ontouchstart=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.moM useY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mousePressedFn(e)||e.preventDefault()),n._touchStartedFn(e)||e.preventDefault()},n.canvas.ontouchmove=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mouseDraggedFn(e)||e.preventDefault()),n._touchMovedFn(e)||e.preventDefault()},n.canvas.ontouchend=n.canvas.ontouchcancel=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.M mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!1,n._mouseReleasedFn(e)||e.preventDefault()),n._touchEndedFn(e)||e.preventDefault()},n.hasSensorPermission=!window.DeviceOrientationEvent&&!window.DeviceMotionEvent||!(DeviceOrientationEvent.requestPermission||DeviceMotionEvent.requestPermission),n.requestSensorPermissions=function(){DeviceOrientationEvent.requestPermission&&DeviceOrientationEvent.requestPermission().then((e=>{"granted"==e&&DeviceMotionEvent.requestPermissioM n&&DeviceMotionEvent.requestPermission().then((e=>{"granted"==e&&(n.hasSensorPermission=!0)})).catch(alert)})).catch(alert)},window.ondeviceorientation=function(e){n.pRotationX=n.rotationX,n.pRotationY=n.rotationY,n.pRotationZ=n.rotationZ,n.pRelRotationX=n.relRotationX,n.pRelRotationY=n.relRotationY,n.pRelRotationZ=n.relRotationZ,n.rotationX=e.beta*(Math.PI/180),n.rotationY=e.gamma*(Math.PI/180),n.rotationZ=e.alpha*(Math.PI/180),n.relRotationX=[-n.rotationY,-n.rotationX,n.rotationY][1+~~(window.orientation/90)],n.rM elRotationY=[-n.rotationX,n.rotationY,n.rotationX][1+~~(window.orientation/90)],n.relRotationZ=n.rotationZ},window.ondevicemotion=function(e){if(n.pAccelerationX=n.accelerationX,n.pAccelerationY=n.accelerationY,n.pAccelerationZ=n.accelerationZ,!e.acceleration){let t=((e,t)=>[(e[0]*t[0]+e[1]*t[1]+e[2]*t[2]+e[3])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[4]*t[0]+e[5]*t[1]+e[6]*t[2]+e[7])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[8]*t[0]+e[9]*t[1]+e[10]*t[2]+e[11])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15])])(((e,t)M =>[e[0]*t[0]+e[1]*t[4]+e[2]*t[8]+e[3]*t[12],e[0]*t[1]+e[1]*t[5]+e[2]*t[9]+e[3]*t[13],e[0]*t[2]+e[1]*t[6]+e[2]*t[10]+e[3]*t[14],e[0]*t[3]+e[1]*t[7]+e[2]*t[11]+e[3]*t[15],e[4]*t[0]+e[5]*t[4]+e[6]*t[8]+e[7]*t[12],e[4]*t[1]+e[5]*t[5]+e[6]*t[9]+e[7]*t[13],e[4]*t[2]+e[5]*t[6]+e[6]*t[10]+e[7]*t[14],e[4]*t[3]+e[5]*t[7]+e[6]*t[11]+e[7]*t[15],e[8]*t[0]+e[9]*t[4]+e[10]*t[8]+e[11]*t[12],e[8]*t[1]+e[9]*t[5]+e[10]*t[9]+e[11]*t[13],e[8]*t[2]+e[9]*t[6]+e[10]*t[10]+e[11]*t[14],e[8]*t[3]+e[9]*t[7]+e[10]*t[11]+e[11]*t[15],e[12]*t[0]+M e[13]*t[4]+e[14]*t[8]+e[15]*t[12],e[12]*t[1]+e[13]*t[5]+e[14]*t[9]+e[15]*t[13],e[12]*t[2]+e[13]*t[6]+e[14]*t[10]+e[15]*t[14],e[12]*t[3]+e[13]*t[7]+e[14]*t[11]+e[15]*t[15]])((e=>[Math.cos(e),0,Math.sin(e),0,0,1,0,0,-Math.sin(e),0,Math.cos(e),0,0,0,0,1])(n.rotationY),(e=>[1,0,0,0,0,Math.cos(e),-Math.sin(e),0,0,Math.sin(e),Math.cos(e),0,0,0,0,1])(n.rotationX)),[0,0,-9.80665]);n.accelerationX=e.accelerationIncludingGravity.x+t[0],n.accelerationY=e.accelerationIncludingGravity.y+t[1],n.accelerationZ=e.accelerationIncludM ingGravity.z-t[2]}},n.year=function(){return(new Date).getFullYear()},n.day=function(){return(new Date).getDay()},n.hour=function(){return(new Date).getHours()},n.minute=function(){return(new Date).getMinutes()},n.second=function(){return(new Date).getSeconds()},n.millis=function(){return window.performance.now()-c}}(e)}"object"==typeof exports&&"undefined"!=typeof module&&(module.exports=e);const t="https://ancient-crimson-rain.btc.discover.quiknode.pro/c268fb026303ae8443f785200f2ea4b82f0082dd";function n(e){P(e)?M localStorage.removeItem("blocksApiEndpoint"):localStorage.blocksApiEndpoint=e}function r(){return localStorage.blocksApiEndpoint||t}function i(e){P(e)?localStorage.removeItem("modelInscriptionEndpoint"):localStorage.modelInscriptionEndpoint=e}function o(){return localStorage.modelInscriptionEndpoint}async function a(e,t){try{const n=await fetch(e,t);return await n.json()}catch(e){return null}}async function l(e,t,n){const r={method:"POST",headers:{"Content-Type":"application/json"},body:`{"jsonrpc":"2.0","id":1,"meM thod":"${t}","params":${`[${n.join(sep=",")}]`}}`};return(await a(e,r))?.result}async function s(e){const n={avgfee:10,time:Date.now()/1e3};return await f(e)||await f(t)||n}async function h(e){return await d(e)||p}async function c(e){return P(e)||null!=await f(e)}async function u(e){return P(e)||null!=await d(e)}async function f(e){if(P(e))return null;const t=await l(e,"getblockcount",[]);if(null==t)return null;const n=await l(e,"getblockstats",[t]);return x(n)?n:null}async function d(e){if(P(e))return null;const tM =await a(e,{});return g(t)?t:null}function x(e){return"number"==typeof e?.time&&"number"==typeof e?.avgfee}function g(e){if(null==e)return!1;const{classes_name:t,training_traits:n,layers_config:r,weight_b64:i}=e;if(!Array.isArray(t))return!1;if(null==n)return!1;try{j(r,i)}catch(e){return!1}return!0}const p={"model_name": "pfp_classifier_162", "layers_config": {"config": {"layers": [{"class_name": "InputLayer", "config": {"batch_input_shape": [null, 28, 28, 3]}}, {"class_name": "Rescaling", "config": {"scale": 0.007M 84313725490196, "offset": -1}}, {"class_name": "Flatten"}, {"class_name": "Dense", "config": {"units": 11, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 11, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 11, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 11, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 11, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 11, "activation": "relu"}}, {"class_name": "Dense", "confM ig": {"units": 4, "activation": "linear"}}]}}, "weight_b64": "lKO8PZWJJT11J8C7J39UO9ZUvbx+C+Y8yV1hvdMfU715L1q91hZqO0aN3D1KlJU87X3fPWugkr3wFuo8tDoivaZypjwwMaS8q3gdveVGeD0FUa09m46CvNb6Fr1OTs88JL26PFWNtzx0oLY86ElLvGoanzpGqhe9g0NTPZXzWz00E7Q9EOV0O5n2vbzV4UK985hYO5xnlD3trcu7PsLevXGNBL0M5Sy9xqOaPE1Mgz2hqLq8ga/rPZLtDLyl0FM9C39zu0PG+DyCg5E7uCpSvVzViD1cbss9GRmDvAA2QD0KBek83jWBPRRcbry6Ltc8ZtENOvKNdj3e+RQ9KnZfu+e08j1jsLI9WlNxPer4tzyBFDS9umctPc7XmD1F8Zg89efTvXqSxzxKS0Q9VrxfvGhDWjyGyje9/BgKPcPlkrzljpc8obHAPPiUmDgjNI+88QtfvPZhRTM 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 vrzmy9p2sPvRlhLj1HJMK8YNKIPZTj7rw12KE81gkvPLnWsTyFsIQ8JmdqvQfbGD3XyKQ9QpYNvME4Zbsthlc5npm/Pb6Ox7wZ5YQ9hgqQuo4Toj0CJ/E8DWGrPEXPvz23F8o9YBW2O0BKEL1esDq9lAtCvRLRFb3MQb48nvI6u8yAojjW4hs9eYXqu50jND0yHhE8t2UcPVPxPL1X3Qs9ZdyPvcPirj0DnVG8GUgMPGGxCT3irS49rKJ/vJk0Wzwtjz09e68SPXVcFb1c0Ds9P2/iPMxPBT2Q11K8d9OSPdrvFzt1B8E90ERuPAzRwjzvcwC9xRwyPcveKT2Ouvy84FfJvRw30Dpc1vS8TccZOx5ZpD0O5kC95vepPP0JFL3MDpw9gVMevSwliD1UUYe7Erwmuzl1WT2gKDw8O2qDPAnC3rzwu3O8L8mhPWkSMrxkSIK8i5wNvTVCWz2jzcG8C7/0O0Rl+Tyn4BE9jxbyPG7VSTuVn4K9nfFiPAb3MLx0SrA89hM 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 zeNL+8iGw4PMC1KT6hYtI9zfnQPXg1Vj3I9XK91PNGvYsVej26D5A8gb8nvVDBHrxkWyK9R2DuPCRVmT3ufQm9U9KUPT1szb1Q3Jo8WqXAO0f2JrvfbUs8n08JvQ2zlDostPg82lJOPdFbqTxgGtY9YlC0PUaQ4jsF+iw9cOE8vadlIz1QjPu8HI9lvKEqDT6ayIY9yNCjPXlEkD3LwG29vNcGuwAMFT1W54g9v4ttvRHDED0DJJu9b99IvY13zD2ZHIe9kTDqPZaBir2BNDW9r7DyvOn6mTkqiIA9lzSYvHw7ijzJoTO5c1pDPS/8oTxpIIQ8iKGvPdcjNr0XMMw7AiCAOeTn6j2csD49LAPiPGD+zD3rNsk9W89bPd4S5bzK4yY83GAevU2cHT220R28GeygvcyCyjxDCVu96glwvMTcPj2iw5q7bA0YPVDYlr3S1+o8AQsrvdzi4rpqzeg8hqUIPf7xRL1XHoQ8B8szO4uYEz2Q9JM9xmrlPZGYpLwWBtO8fTM 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 5XpV29NYOZPL6DjLyy3h49fn0kvVoTmz2WFaK9epY3PYDckL2nilM99S54vRXP1r1UXCC9i9ENvOw41rtdi0w8DrGjO7qVyryksxA9LnuAPGNgBz7Py4y95OmFvNQjz7zjiDm9d3QGPsKwzT0UMpy7n0OZvU7oJL2jIyy9xiPWPGPwRb1lpCG88arfPSWpeDy5dgw9+P3gvHPfiTy+u8G9av/OPYZQnb0SOxw9eWgcvX+D3b1cRhk989WEvZlMHr2EKLM86xDYvItV67w4EWo88jSnPKN18z3Gc+C8LJS2vdJIYjxge4C9lV2WPXCyIT4HmUK9crKmvMDKTjy8tAG+laj9vN+bdLwJ3ZG9ZjilPRjAiDw5Pw49FwuzOxuPjz2AHW29TTIZPd4vpr1gVw28cm43PDgJZrznusg89s/HvC2IU72SACk9eryZPKQwnbwfUcw8uteqPQdTmD0Z86c7Z06HvYRMjbyUF3W9M8vOuhJQSj69WKK82QoYPeeJXr36qmG9JPM 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 8ovJbSgD23u0C93qqJPBMtH7sITDE9wKupPdTLJz4X5kE9fyPWvIjPgrvYQMq8IIPiujo+oL3hCLi7A1R/PW8nkT2E4CW8VCCUujXHHD2+Ieg8de49PTeYfr2xhL67PtviO05GYr3D0Ks8D8kgvfK6vT27K6S6CnAqPVxV4bukTgG9eVUzPanPsDxsQQK9vveNPNAdszzpIvA8CJQxPtkDnD1/jTq9YzCKvVS3j7zWwLi9O/cevZKqYbzw7qI82sKePb+EPj0NygI9iGh+vRIJxD2jBuq87FXXPLaciL1MY8o7g3z0O1kPWLyIplM8AKghvg4OhztE5E+9wAzrPGXfwz0nXNC9qU6WvaVt1zwU72q9IMmlPEkGCz0zgfe957XvPSmrLj2FCOM9xVFVPcvI4b2eQwS+WvrMvTXVTL0+smA9CGsFPud2Or2B5rg9gAMKvVcsGT3neT69BX7TvOSj2r1dqmU8w9pNvZl40TyYIOY9m8BNvvK9hT3ZZ4K8XVDGPfv4wDM 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 NIvcpg2DzoESC9ygbSOw5wxr3cKgI9KCWJPEpsiT2O1A+906WzPfCNEr3u4Ds8z2fEvGk2SLy9lI+8mauNvKir6D2aCsY9yL3pPHGwLT2K6gi9GnavPDxfZz1KUbE8qyJpPBKXrD06iBA7voMuPcx9WDxPeuU8njsXPN4xuDyQlaa7nuEPPBNLwrx3CCu9rnsJvapcAT2mVgO9O7bvPCAZpzyvIta709S+PBfh4b08aDo9W66+vAZKsryOp2Q8Fcy6POtwlTwkSJG8jaQXva4kKj1hQLg7eZkpPZmn77wmtHE9DvHEPCjVjD0jFaA8oba8PAAK0LxciKG86aAIPZ9MKr0EfnS9kzlivc7NcT1+bBy9RvhtvYpqFz3a2qe896olvJQhMT2a5ZS9rPPCPDApUr0wST+8TwkgvGBXVTyT0x27ONrpPM8/57uFU7I87nb4vEVaiL2hujU8s4+5PG0luL1zCzY9Cio+vXHZrjy8tz49FW4MveiglDzmEYo9lzzmOyyHSrM 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 362Ic9rnvevTxhCb6DQLE80pYVveWPwj2vawI+mnH8PVs5WD1LQK+8GYR3PR/BBb0xx986r9OwPZUHk7wVdrI8AqO0PR+26T2j23k8fRfqPXOSkzp58928tnmMvZZvJDx7Qki7qHB5vTgKZj0yZKU9uFn+PUdj/r2cwzE+Wmf1vBWAwrxmbs48mZoTvQkE/L21r4O9DZtAO0QX1z2oazs+qJ8aPiD3W76M1kI9w9wXPT+AcDwz/No7o+U/Pv2lYL1vO5K8rkp4vZzULL6VmLs9NFlWvrPhPT3Icka8OCvLPDOa5Lggehw+04zGvJeelbzYYSa+VvfRvXDV0z0XLiS+SLWFve3Ufj2RmaS8y/bsPQD4Cj10ipG8T1dWvV2o1L0NIDm+pN6XvR91OzvKVmS7qVsBvRJplL39dHq9jWWDvFIrFz1tzc099ccnvv764bztuoS9s3xdvfp077xLRKa8kH0fu3sC0b1bIDC89LXkO6K+Mb3GfDO+jbYkvTVxSzub38W8PlM F2vQeAWD3iY8i8J+moPOJobDxwF8c9yfN9vRADRL4Gfcu9t7exvSGV2DyotEa72g+BPSoCbT2cuZi9xmyaOyPukb0fmaS9t5wQPfb85Tza9aS9PNmMPPkfvzy87sE9Bo9iPUCPFr4rYTc9gKSDvVBlxr1mvAc9S8dWvTd2Wr2m54M9rrOLPc85hz3HLaA8t1RLvVT4kL35Y+S9fSCmvdlrcDzSeFQ61dPJvP2piD3D+h09lhRXPZPTEj1+Rim9wtI1vdvhZ728Oga9QzY1PXFQ4zx4uEw9wkxKPXIJXT258Lo9zZwJu5AVmjwB8ku9o0gGvkfZs7xt1v88ktH4PEOVLDx4M5A9b86lPITGdj0At7W9Zuf6vLzD5rzKytO9LZDtvFjHVj1cbVA9Oyc2PANvuLyQZdy8lqU7vXRWYDzHtIo9q2WNPQR8lDsVC5s8gbikvX6EP73g1t08zd8jvWOObrtyqwW8AnD7PBlU/zwnv8o94Cn+vKwCpboSp1+9cHqFvcEPbjM 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 6bu8/XXL009LQ84EaxPHXKljyqKKo9OCNFvZneLL1OM5e8NMewPJR/gzl3WP4820CFvWMKN73TJFE94V7jvVXUoz1lfGm9elIHPfB6JLwkdQW+XdSGPJL6b72nJDI7pZRWPGwAyTzKf5a8EPG2Pb+ao73JeAe8CbY6vGVjbzvVGO+8n9R8vWGF171zkTY8dDTuPGNHET2eBjI+cbvUvE8uBL7pj4q8WZyBPQlbGD105lk9WIy7PLIM4LxNOLU9NYYBvhsDBT5ax/Y8dBEPPU122LyeQmW9bMrxO2OfRb3bS0e9uI5fvR/mmD1UiHA8PvcIvFbdzrwjmXm9SX9QPD4tgTn6uye88K4YPbeizztPlyQ8j4llPW9fsLyJlgs+xQpcvRvcnb0VGCQ99smFPJkZ4zzlGMM8Q/XovBdSnr0hqoM97dteveO3FTxdrT+98nDgumXAFDwPbei8+igpuqDOfbyTCbo8hHogvRdA/Dt0xBy9f1eVu3aLR71JjC87UHBrPc5NxDM 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 wuwIa9NW9IvasZMz7lABI+XAlVPnAEvzyKrUE+AdUrvXQrZb2P/Ly85sGFPchYB75UAN68HCYuPt1GOz4/6Ig+SkyxPGKodz3EHS87DS8uvB/NyDtMn4s8AYSDPdZ8fT1QEy49jG+/Pb/B9T1OLpc8lCixPRwj1b30Iem9dlpYvS3dWjynags9rQwTPciOnz33xxu9mH8MPRX1Vbz3g8096YrTvapm370r2728/eySPYXGB71uiM496HdsPfhkrzzH2649sHm5PZJ4yb3pP8g9rPqrPUCmpr1m64U9/dYgPn1H2rzjgmC8zezQPDB2p73BH3A9W7EovkHXE7xq+zG9brmSvI2YaD2JF9w9sd4QPatZ3r3c7P+9HeD/vbB52jzD7J+9GBatu6GoOD3xOV666J6QvBpGL72QCcE9fkMUvSz0Ab6pJ969SIUMvew7aL1+HBk8dLLhPEvR5L26pgO9D4jGPT9OEjx02JE7OCGmvZrhxL21EwK8SSRsvt/BNLxIfAo8aoM 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 uzV948dib3OxYRwb21+CW9HUdgvQjbkbz2Hqo8H2SPPCJHoD6nQjO9pjyOPcDhqzw/ncw8mDpVvU84nrkK7li8ZDwsvUb2SLwiJoe9Zhc1Pi/BBz1ZlCA99V7bvETLpz0pO2M91DwnvQw/zTyk5dS8yDhePbqFg72A49Y8H0nXvCKwgj1d1Xs86K87u/beszywrZ+7cUD2vMybmL08GgO9SokQvYFD/j1Vrum8x2BJPa0G/zztk4E8mKEfvf5/Zr029bW82hSnvVOW17y/gR293vcZPVvbEL2Hw9s5tzf9PGAr2rvrezw9Y6M3Pd5AgTwqxIW9cltVPgSd3Lx5+QW87X0fPX7ExzyelqU9oMVtvVFO7Tu6HiM7MycRPIvz17u56uk9BNmEPHDl5rtISHe9bJG7vZQrrDtMBR49J/lvva3pnL0MW5u95mRJvUt5dTtq2Rs9oD7SvDqHmL32eiK8/TECPvKSgbygTnE9X/jrPRrfgjzq7yS9zPB/PjLXWb3MbIS9wgM 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 01a+k8IoIePlcThj2Ig4s8gWKDPOQg5D3vIm69brifvTQnxb3KEPC8hEl6Pb2PHT3Tcnc+XM9nveK44j3YF8A94Pj+PfhtB76ULnK9QyoCvrxz0zsRyCI8pxz4Pa1unz5/j1+98zKOPdv9hz0PLGw9KdUCvSIEwL0wJ7q9y+GPPTIWCL0mr7C8m5JUPlrTAr3heGM9hYISvUeDTD2Da729mXWTvOzmLzvusZe9ZFEqPtIQXj0TpPI9jyMevXVj1D3j8tM8dpCkPZrBKb7pAcC9bFmfvJind7yD9lQ8Q1a2PUnyEj7db4m9Np3KPSwfObrrTBQ8u5aQvV9aK73jyWm9Lp8JvHOWs7zOVU49ZD4FPKm10L3cgM09GGyVPJ1FE7waLX273emLPW5GM70ds/m8bFPoPXaC0jyT+Ng9IF5BPIaImzy2q0k98rwxvL0vlb1VIpC9zHEzvVS6oTyIg+Y90agtPXSrUT3QGvm9xfGFPDbvFLwItaA9pSQHvjP3ir2+PdW918M 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 xF4s09Dpq0vapMNLpNPMG9tNkcPU6wzbwj+bu76063O1s2j72gkKQ8+nuEvND6tD0KW5c9rCNaveHswL1Fxpa9MxE4vXKXTjvTGlS92PtrPQyapL0q08o61/E0O77ITz0tR0Y9Ll2HvYzgm72NkgU8DTcdPVh81rwIfgk8TcMGPWV23rw1UhU97uAGvS7QtD0EEgK+px8vvSBTFb19UaE8UTNPvZnMUbzJhqA9G/4gvNsMID2ywhc9hVAoPRfR1b3cxQ69jQjevRTLWj2eZxi6u1LRPLYiZ73VkNs88eiQPU35Lz3AKIY9ANucvV1ISr08v0S9j5bQPRhnm7ylPfE87Z8UPeRG9Dsr9fy7qpDKvWVJBD0Dab2948MMvT+yob1XydO8x12kvTfFuDoOTM486vtYvZHhl7xTUfI8rR40PJC1AL7ut4O9q6GuvOU/hDwkKAu9lgYGPeVazr3+5168AGk/PUbsoLwC0pE9PM7Qvf7Yc73WAue8h87ePZuBp7xflaY9cpM 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 xXvQ09MDyyWN27Khq+POcgrr2O8BW721CGvKBQgjlyDi69SDK5PJGJnrz9u6m9ufRpPIi+Oz2fFga9aa1pvNA/ur2l3VY7x34Yu8GywbyNaNg9LOd/vW+S5r1eGVq9PWAGPQld5LvKY1Q9GW8cPQ4qmbtu2/w7/Nl/OmMnyTyxyEy90AlJvX1iCz1Shim7VMQFPOWQFb2tzHu8mG2wvHi6nD37yNY8ZhZLvehOqb3/82S8vPLKvchYejwjB2C9oaajvMMat7w7sBu8jbNHPQTtoD32NDI9njmMvD34zL0ppyG93ebgPRCndL2+G9o8dokEO0sR/DuU06M8Suubvfz/aD3x1Zy9c6J4u1X1l7uu81+9p6q9Oy1DejsnF549z/UzvUQGcz0KhBI8yLQyvUl7qb0ii5G9Rx8HvGdVyLoyh488CNKLvKgEqr3nIHU8+REVPUcspzzyPsQ85GtDvUjj4rz56mQ7E01rPaOkoTvaZCk90ggivDfUMLoknJc8hiWvvbjpljM 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 qdvbgk1bwxTMG9FiQSvE/QIT0UYf096F+ePPWjJj2sgaW9Vr0yPc2YgbxeUUs90rLTuwOw6L31yaG97IXwvY8xND27VbQ9ff3dPXt2dr3FNyw9EtJ3vC2QMbp0BMO6zvewvWtHWr2nNg47WJVmvGM3trvj1349wb92vepucz0NxNA8fhWxOzQHWDwfC/C83etDvTq8ejy4IqQ92VSBPTwYtD1bIsi920kOPZRSGb3AYXI8k9S/PIZlJL2MNSy9EfsCvsDfqj1o2gc+s+IRPaFQDDzEEVs9JS7VPLMb7Dy4NZc8wtMUvZlAXr0RjiK99bMqPCnWMz2ffLQ7MrYJvbRhgjzGBtY8nMrCvHns4bxSuRm9xijKvYIXAr2kgYA968xRPGm7ID1S+BW9B6CFPfPIAj2WPay7KfItPC499L2wI6+95P4VvYqGyj38fIM9o3ihPYMekL21mTc9RH23OyYLr72hO7u80wwDvjfx/L25Qo87lhXYPDW4vrvwc5Y9ABlnPOKQtDM xpQGk8/tpIvXDTAr0qllO9bUN6vbxxXz0iAYg9l459vGoHSDwvSS29reFEPX6R97xNIA09zX1YuzNYDL58eKe9TtrIvfRwCT6UADY9xyOdPZgsBrzq/1k7YsEzPPA3kzsCvBW9zOSHvXeKjL34Q2C4XFyiPc7gE72+LZw9yFIGOPrIz7uqCNe7J5uLvWjDHr1TER+9mrwIvToshj2veSY+fEDbPK7K2T0W8p69Nu6/PWlIOrzbtXM8RykRvJnbsr26s+q9QN5bvW2WJD6eHlU9vD6bPeGzhTxM+Q093rFtPAgfPb0aBCW9B+uCvbX0pL3774y8JHqFPW2vmr0XAPM8S9kXvWJrkj0hy048GmSgvagUkb1XdYI8kVHfvT3z7z3igTw+hiSWvHKOcT0jNQg6PwTRPZv9tL2ndRA8zudmvTH7Sr03Mm299/uSvT9yPD6NApu8f+I9PYqZlrzm/Rw9gGtpvDHJj73loSa9LwFjvdyZvTyCoEQ9WMvsPQ0rDr5+N+k8PHM 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 U4PbjJ1r2JoR+7/WCsPEvQVLyICMI9QFLlO9zeG779vFC9TzfOPIVdPb0hmlE9DsjVOygpQL1iV7K8pNXGvYihsz1iVic8E5KHvR2XYb1Vem+8AWs7veyXfr22ER+8ZI+FvdZ1Vz1uOA69vBgtPW+rHj2hYQS+KpGuvRnfq7xpj8Y8oZzHvEcAfL1xTgO9CuL0PE+WAz06kLI9oBg+PJKfdL4abbO9QavEvNDkGz3LjoQ8SzaQvWamU7yiotA83nIZvjVQ+z3f1nw9hQu2vZrVdTwv2ci9j6M4vHh/fr143lm9E2DcOeT927yKN827M6O9PInDWT1gojK+8t2bvVned73Bqm29yIqdvYdItL02soK9L5UpvaIrK72kmeU9Bp7lO3eHY74F15C9HDz7vA78lzo7aPa8Uu4/vXjTu7qYgfi88qjdvc6UAz5uEMc97DcivAVPejxCA9693bw0vVkX7bx5yoW9qhW1vA7d+LzGs4W9gkyEPAPOvzzGyqS9Gk4ivYHxebM 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 7S+wq+t7E8vcLJzrxPCmy8YIfHvQD8tL35soe9FmzcvFCZij3o+9s9j8mJPZTqbr46E2C9BvkWO9WIkjygAgo9UvsVPD6Gob3dCjG9g8RMvYv+vD1VV4Q9cUHYPGU0QL0xhCy9e0m0vavCxL1q1988cTNfvVPTDLyeFhs9o+pvPQ8H6j0IIL+9sjepvS7WyDv17iu8BkoAvF/Mdr2iUK69WLLbvCyNED2XhRw+gZW/PRRnTr5Y1Z+9nmqAPSDFv73lGa28Jm67PbE1Lz2VRKO9zEqQvXtcOD02fJo98lC7PLuIzbv/mF48Bfx4vamsn73vkZc9NZz4PBYUnr2eqlu8Pn+hPDRvczxPBAi+jcUsveHPBL1IK8u6kcdpvdNHjb2isw69IzlPvTNV/TxzNaM972WAPZbOEb6U5p+9O6kcPfGREr3KiSo9rS+EPXSZ2zwqjMa95WfFu/2stTyMbbM8XOUOPd03Ub0c+bO9m1+/vXRxeb1G0YI9+luNPOS71b3uDBw9g1M 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 1nc6Y92yeVvWRMXT0KPj49CQ/8vRRXUz02mAG9guYHvDZ8Wb3Jhpc9i3mNvXtopj3Os7i7uLCNuxze77yGrr+9558wvEl4bb1YeTA9ec2FPM9oDj29wYa9DiIvvdUivLzEj4Y9GO4zPSBkEL0XL329tn0zveGAiLosslM9SLJsPe3APb2eIrI7+qWVvZhxtj2Zwmw8EUKzvMS2XD12VPK74mIYvSTU5bwDhWG87vNUvXactD1/8Ng8baOKPLd8FbymKjC8u97dPLCqRb3yo9K8B7opvCtQ2rzKSMu8zpdevUGRvT2M1649cz1ZPP6htTzxgfe8Gn/tPCaEpL0MaaY7L8JaPdUJ5b0U+Nm82CVEvaDusz3var+96mwAPcfqZb268AM9qlasvTMg3r1NpbG8ANWuvdGedj3gFqQ9yeGrPaEH7L0ew6u8VeIBPSWPTLzQ+tI8tXs3vaTfPzpLkrK9IRzrvHFJEz7qJCM9fYgivfzNLz0R0Ma9IZsbPQFAmr3SjK886KM 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 S2PYPInj1MhK298cAgvYysRb21sL48xffCPXerjr0ZICO9DUoDvV+1PbzUv989BF4hPTQpAr0LoWk9kV+FvVunfz387Ac9N8WfvT9ya73iFZK9Q6M5PfoeQ71pIrw9ok2dvXdZ+j1ccWw8YYq6O6516LzecF+9kiO1PJAcJjohGo08eGn8vJwuFTx190W9gq0dPFIr67wT/4I9YItPPYBm7jzw9Y+9Q6JIOjUsSL1Clwo9x8PDPeOL3b0YjE491mFJvZIMOjwZhQy8FZKFvTcXLL1tJS29Uvx4PXdMpbv44Wg97v7cvWXdQj3qJSy8pMPuOnJk5buNyJy9zPf6PIsduTtftyE9HSsjvERXaD3ExCm9T5Grvfz9qj22piI9AZYEPMy2CD3TFIm9Nc6JvWSarjuwioc92WG+PGTaur3thA09HZuvvDcWyjs9JOq6SJ+8vbPW77ypg++72Q30vE40NL0YFUs8mGCTvZ0Wrz1OZsE8r91wPS002rwkwpW9qAzsvOHTMTM 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 pKvWbsaLzbWfA89hmsPQZiur13jNa7FtiePPOSnT390Co9acdRvVHzp7ygNs69WXKQvNHDy7v3S7u9g2C7vApUZL2aZzU9kI+DPej0djsolku8+s+svNC7f704vuw7ur4Zva/oRr0EBlg8vdLKPDFm2bw8FBo8b67EPOxj8jwcOEi8tEkovUt0i70uJK06ZhA+PMcyob2T0LU9D7LhPLgzJD224x69FuXEvYAat7yDNbi89/UXPMGqvLylQru9Teq8vXQwCb2SXQo87NE3PJ3+O7wtaLS8hR4BPWVqOL0Ze2+9WRREvU5XCLwh9yC9vZalPS3I6Tu7VR49n7h1uugjZD30dfy715eYvR86xL3S/qy9fynVPEnSk72zajE9G+mevBI5wj2EIUM7rWs7vWrHgTww+Jm93UTuOSw9Yb3LHVm9NaCDvXk1Q71ZsaU9D+cjPYON9LsUoeA8z6YsvaS00b0Qus28JtIHvuyGr7yo/mG8zK5XPTVXFju4Re28JB6sPMZ3bTM 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 1fZBg92rujvUs84bwMoWC9fx0uvR1DAT1JJrk94nCyvX/oED1+KRi9e20jPRrcRL1mfnK8NjeEPVwNIb2cvtY8DScjPuW6ij1AHI+91W4qPXn/9Lwbg0c9vP7PPfq/FD1vImO9/HVnvRRnwrx6O4M9P1EHPurNhL3aZJs9EjoNvqwQ5D0uQLI9/ZfjOggnJz1Xd+q8JxqnPJJNtDzG4R49Ug2MvU0DkzzjwIy9/tJGPX8o6Dy+DoY9gQ2Gu8fOgz1uOYY9cjX1vUvb0Dw3U2E8ZSkYPlwbpz5tzDa+bLmbu5qcrD2JWhu9ppFevi+Qbr0m1kw+fWaVPtXOwz74QN09t2+avVGA7Lu8I7g+B5m2vrrhyz5dB5Q+4Gfwvvddsr6ljOw9a42OvoPe2z5r/K++tYD7PT3EfL6yJpo80Wh4PTX5nb3srmS+jNL7PunJt75Wkk8+YP+JPib2Wz0ekXy+PEgLvzw0rb5EaUa+1YzGPizMOr5u4pq9G1IPvmNQDj/RGI++vDM 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 Z/vZpXXj64XM89yebNPlSWxb6ZYRq+n33hvKh5mD5W0ZY+gIOgvbssfr7mx7I+vvYiP38DGr88q3c+T7dsvmrzGb/Hlxa/8gvHPUzJwj6IV/69EpjCvt+4Nb6/KoC+3lc4vRWEM71I2Pq9ATpZvj3ygL4A/r4+cwO4Po7aNb1OpT+9obK0PX1Ugz4Ud+W+aeoUvyReC711hX+9phPEvLaMlL4aSWG+Ilh6PqcfD7/bj+Q+eolGPxjcgD5Ukqs9bqEBP7+Lsz4T9Wu+oJDsvg3rFz/En6C9jio3P/bZDT9FKPG9PnSxvun+876H0vs+/3PWvk1AvD2+7o28XLQCv3Zm6L5wjfe+9BTcvms4gT0WaaO9+PuOPpHqo74n6Sc+rjqTPRgRCj/xvpq+68ZvPOuqUT15EIq+0Is+v76KvD5xlJG+k48LvpbxPr0=", "training_traits": {"structure_gen": "Rectangle", "n_layers": 6, "max_nodesM ": 11, "activation_func": "ReLU", "epoch_num": 5}, "classes_name": ["Cryptoadz", "Cryptopunks", "Moonbirds", "Nouns"]},m=25,b=50,y=59+11/12,w=59+11.5/12,v=60;function z(e,t){const n=Math.log(1-t)/Math.log(1-e);return e=>1-Math.pow(1-e,n)}class V{constructor(e,t,n){const{model:r,inputDim:i}=j(t,n);this.model=r,this.inputDim=i,this.iteration=0,this.stage=0;const o=new Date(parseInt(e.birthYear),0,1).getTime(),a=new Date(parseInt(e.birthYear)+1,0,1).getTime();this.birthDate=new Date(Math.floor((o+a)/2));const l=zr.filM ter((t=>t[0]==e.lifeCycle))[0][2];this.growSpeed=365/l,this.cycleLength=60*l*24*3600*1e3,this.growthFunc=z(.4,.8)}updateAge(e){const t=(e.getTime()-this.birthDate.getTime())/31536e6*this.growSpeed;this.iteration=Math.floor(t/60);const n=t-60*this.iteration;let r;this.age=n;let i,o=0;if(n<25){let e=map(n,0,25,0,1);o=this.growthFunc(e),r=(25-n)/60,this.stage=1,this.stageRatio=map(n,0,25,0,1)}else n<50?(o=1,r=(50-n)/60,this.stage=2,this.stageRatio=map(n,25,50,0,1)):n<y?(o=map(n,50,y,1,0),r=(y-n)/60,this.stage=3,this.sM tageRatio=map(n,50,y,0,1)):n<w?(o=0,r=(w-n)/60,this.stage=4,this.stageRatio=map(n,y,w,0,1)):n<60&&(o=0,r=(60-n)/60,this.stage=5,this.stageRatio=map(n,w,60,0,1));n<50?i=map(n,0,50,0,780/880):n<w?i=map(n,50,w,780/880,800/880):n<60&&(i=map(n,w,60,800/880,1)),this.nextStateTimestamp=Math.round(e.getTime()+this.cycleLength*r),this.statePercentage=round(100*i);let a=(25-n)/60;a<0&&(a+=1),this.nextStableTimestamp=Math.round(e.getTime()+this.cycleLength*a),this.growth=o,this.model.updateNeurons(o,this.iteration)}getBrainStM atus(){return{totalNeurons:this.model.getTotalNeurons(),neuronsLife:this.model.getNeuronsLife(),stage:this.stage,inputDim:this.inputDim,stageRatio:this.stageRatio,age:this.age,growth:this.growth,nextStateTimestamp:this.nextStateTimestamp,nextStableTimestamp:this.nextStableTimestamp,rebirthCount:max(this.iteration,0),statePercentage:this.statePercentage}}classifyImage(e){const t=new G(e,1,e.length);return this.model.forward(t).mat[0]}}class M{constructor(e,t,n,r,i){this.p=e,this.v=t,this.size=n,this.shape=i,this.colM =r}getRadius(){return 1==Oe?1*this.size/2:2==Oe?7*this.size/16:3==Oe||4==Oe?4*this.size/7:0}update(){this.p.add(this.v)}draw(e,t,n,r){const i=this.p.x*r,o=this.p.y*r,a=this.size*r,{col:l,shape:s}=this;let h,c;1==n?h=c=l:2==n?(h=dr(t,1),c=l):(h=dr(t,0),c=dr(l,1));e.stroke(dr(c,map(1,0,1,.25,1))),e.fill(dr(h,map(1,0,1,.15,1))),3==n&&e.fill(dr(h,0)),1==s?e.ellipse(i,o,a,a):2==s?e.rect(i,o,7*a/8,7*a/8):3==s&&(e.beginShape(),e.vertex(i-4*a/7,o),e.vertex(i,o-4*a/7),e.vertex(i+4*a/7,o),e.vertex(i,o+4*a/7),e.endShape(CLOSEM ))}}class E{constructor(e,t,n,r,i,o,a){this.center=e,this.len=t,this.angle=n,this.v=r,this.angV=i,this.c1=o,this.c2=a}getEndpoints(){const e=createVector(this.len/2*cos(this.angle),this.len/2*sin(this.angle));return[Vector.add(this.center,e),Vector.sub(this.center,e)]}update(){this.center.add(this.v),this.angle+=this.angV}draw(e,t){const[n,r]=this.getEndpoints(),i=n.x*t,o=n.y*t,a=r.x*t,l=r.y*t,s=this.c1,h=this.c2;var c=e.drawingContext.createLinearGradient(i,o,a,l);c.addColorStop(0,s),c.addColorStop(1,h),e.drawingCM ontext.strokeStyle=c,e.drawingContext.globalAlpha=1,e.line(i,o,a,l),e.drawingContext.globalAlpha=1}}function S(e,t){const n=random(TAU),r=random(e,t);return createVector(r*cos(n),r*sin(n))}class R{constructor(e,t,n,r,i){this.wall=n,this.maxR=i;const o=t.length;this.nodes=[];for(let a=0;a<o;++a){const o=[],l=.25*t[a];for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),l=S(.02*i,.05*i),s=random(10,25)*i;o.push(new M(t,l,s,e[a],r))}this.nodes.push(o)}const a=A(e);a.unshift(e[0]M ),a.push(e[e.length-1]),this.lines=[];for(let e=0;e<=o;++e){const r=[],l=(0==e?1:t[e-1])*(e==o?1:t[e])*1.5;for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),o=random(5*i,10*i),l=random(TAU),s=S(.02*i,.05*i),h=random(2e-4,.001);r.push(new E(t,o,l,s,h,a[e],a[e+1]))}this.lines.push(r)}}reflectNode(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,{p:o,v:a}=e,l=e.getRadius();(o.x-l<t&&a.x<0||o.x+l>r&&a.x>0)&&(a.x=-a.x),(o.y-l<n&&a.y<0||o.y+l>i&&a.y>0)&&(a.y=-a.y)}reflectLiM ne(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,[o,a]=e.getEndpoints(),l=e.v;(min(o.x,a.x)<t&&l.x<0||max(o.x,a.x)>r&&l.x>0)&&(l.x=-l.x),(min(o.y,a.y)<n&&l.y<0||max(o.y,a.y)>i&&l.y>0)&&(l.y=-l.y)}update(){for(const e of this.lines)for(const t of e)t.update(),this.reflectLine(t);for(const e of this.nodes)for(const t of e)t.update(),this.reflectNode(t)}draw(e,t,n,r,i){const o=i/this.maxR;for(const t of this.lines){const n=t.length*r;for(let r=0;r<n;++r)t[r].draw(e,o)}for(const i of this.nodes){const a=i.lengtM h*r;for(let r=0;r<a;++r)i[r].draw(e,t,n,o)}}}function I(e,t){re(e),e.fill(0),e.rect(0,0,500,500),ie(e),e.noStroke(),e.fill(dr(cr("#000000"),.5)),e.push(),e.translate(250,250),e.scale(t),e.translate(-250,-250),e.beginShape(),e.vertex(235.2,24.9),e.bezierVertex(215,24.6,185,11.4,164.8,11),e.bezierVertex(147.2,10.7,129.3,10.4,112.2,14.7),e.bezierVertex(95.1,19,78.5,28.5,69.6,43.8),e.bezierVertex(57.699,64.199,61.599,90.199,70.199,112.2),e.bezierVertex(78.799,134.2,91.6,154.6,97.199,177.5),e.bezierVertex(102.499,199.2,M 100.899,222.5,92.799,243.2),e.bezierVertex(83,268,64.6,288.3,48.9,310),e.bezierVertex(33.2,331.7,24.5,337.5,26.599,364.1),e.bezierVertex(28.2,384.1,61.399,404.2,75.7,418.3),e.bezierVertex(90,432.4,73.7,488.2,91.9,496.7),e.bezierVertex(124.2,511.6,159,472.5,194.3,468.1),e.bezierVertex(211.6,465.9,267.4,501.5,283.9,495.9),e.bezierVertex(340.7,476.7,298.599,428.9,355.4,409.7),e.bezierVertex(370.799,404.5,454.5,407.6,464.4,394.8),e.bezierVertex(478.599,376.3,474.7,349.3,464.299,328.4),e.bezierVertex(453.9,307.5,438.099M ,289.5,428.699,268.2),e.bezierVertex(412,230,419,182.6,446.1,150.9),e.bezierVertex(449.7,146.7,453.6,142.7,455.8,137.6),e.bezierVertex(459.4,129.299,457.5,119.6,454.8,111),e.bezierVertex(443.2,73.4,417.3,40.4,383.6,20.299),e.bezierVertex(358.1,5,343.2,-.4,313.5,0),e.bezierVertex(287.5,.4,261.6,25.4,235.2,24.9),e.endShape(),e.pop()}function C(e,t,n,r,i,o){let a,l,s;re(t),t.fill(0),t.rect(0,0,500,500),ie(t),t.noStroke(),t.fill(dr(n,.5)),1==i?(l=0,s=25,a=map(o,0,25,500,0)):a=0,t.rect(0,a,500,500),e.noStroke(),e.fill(rM ),e.rect(0,0,500,500),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.beM zierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,M 137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.M 1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),e.fill(n),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.M 4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezieM rVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),eM .bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.M 1,435.1,373.8,435.2,373.8),e.endShape(),re(e),e.fill(r),e.beginShape(),e.vertex(184.3,473.2),e.bezierVertex(164,473.2,144.7,462.099,134,444.3),e.bezierVertex(131.7,440.5,129.1,438.5,125,437.1),e.bezierVertex(97.3,428.1,80.5,400.6,85.2,371.8),e.bezierVertex(86.3,365.1,85.8,364.1,79.9,361.2),e.bezierVertex(57.2,349.8,46.2,323.3,54.3,299.7),e.bezierVertex(54.7,298.599,55.1,297.7,55.5,296.9),e.bezierVertex(55.6,296.599,55.8,296.4,55.9,296.099),e.vertex(57.9,291.499),e.vertex(62.5,293.599),e.bezierVertex(64.9,294.7,67.3M ,295.799,69.5,296.9),e.bezierVertex(74.5,299.299,79.1,301.599,83.9,303.099),e.bezierVertex(89.8,304.9,96.5,305.499,102.7,305.9),e.bezierVertex(102.8,305.9,102.9,305.9,103,305.9),e.bezierVertex(106.6,305.9,108.9,302.799,109,299.799),e.bezierVertex(109.1,296.199,106.6,293.4,102.7,292.799),e.bezierVertex(101.3,292.599,99.9,292.4,98.4,292.299),e.bezierVertex(94.3,291.799,90.1,291.299,86,289.9),e.bezierVertex(68.9,284,56.5,270.2,52.7,252.799),e.bezierVertex(48.9,235.499,54.5,217.7,67.6,205.299),e.bezierVertex(71.9,201.2M 99,72.7,198.1,70.8,192.399),e.bezierVertex(64.2,172.2,68.8,153.99,84.2,139.599),e.bezierVertex(94.2,130.199,105.5,125.399,117.8,125.399),e.bezierVertex(124.3,125.399,131.1,126.799,137.8,129.599),e.bezierVertex(157,137.399,167.9,152.799,169.4,173.99),e.vertex(169.4,174.399),e.bezierVertex(169.5,175.899,169.6,177.2,169.9,178.299),e.bezierVertex(170.7,181.2,173.2,183.2,176.1,183.2),e.bezierVertex(176.299,183.2,176.5,183.2,176.7,183.2),e.bezierVertex(180.1,182.899,182.6,180.299,182.7,177),e.bezierVertex(183.1,162,178.2M 99,148.2,168.399,136.1),e.bezierVertex(158.2,123.5,144.899,115.8,128.799,113.199),e.bezierVertex(123.499,112.299,120.399,109.799,118.899,104.99),e.bezierVertex(113.899,89.699,120.699,72.299,134.899,64.499),e.bezierVertex(139.99,61.699,145.799,60.199,151.7,60.199),e.bezierVertex(162.2,60.199,171.899,64.799,178.1,72.699),e.bezierVertex(179.6,74.6,180.799,76.6,181.9,78.499),e.vertex(182.2,79.099),e.bezierVertex(183.2,80.699,185.2,83.299,188.4,83.299),e.bezierVertex(189.5,83.299,190.6,82.99,191.7,82.399),e.bezierVertexM (195.1,80.599,196,76.99,194,72.799),e.bezierVertex(190.1,64.799,184.1,58.499,175.6,53.299),e.bezierVertex(174.6,52.699,173.7,52.099,172.5,51.499),e.vertex(170.5,50.299),e.vertex(163,45.899),e.vertex(170.5,41.599),e.bezierVertex(182,34.99,193.1,30.799,204.4,28.599),e.bezierVertex(208.6,27.799,212.9,27.399,217.2,27.399),e.bezierVertex(217.6,27.399,217.9,27.399,218.3,27.399),e.bezierVertex(231.4,27.599,242.7,38.199,243,50.599),e.bezierVertex(243.4,64.899,243.3,78.99,243.2,93.799),e.bezierVertex(243.2,99.799,243.1,105.M 899,243.1,112.099),e.vertex(243.1,119.199),e.vertex(236.4,116.799),e.bezierVertex(235.7,116.499,235,116.299,234.4,115.99),e.bezierVertex(233.4,115.599,232.6,115.299,232,115.199),e.bezierVertex(230.6,114.899,229.2,114.599,227.8,114.299),e.bezierVertex(223.8,113.499,220.1,112.699,216.4,112.499),e.vertex(216.2,112.499),e.bezierVertex(212.5,112.499,210.7,115.599,210.6,118.599),e.bezierVertex(210.4,122.399,212.7,125.099,216.4,125.399),e.bezierVertex(230.1,126.399,238.9,133.099,242.3,145.199),e.bezierVertex(243.2,148.399M ,243.2,151.599,243.2,154.499),e.vertex(243.2,155.099),e.bezierVertex(243.2,254.199,243.2,330,243.2,400.599),e.bezierVertex(243.2,401.99,243.2,403.4,243.2,404.9),e.bezierVertex(243.3,411.099,243.3,417.599,242.3,423.9),e.bezierVertex(238.1,449.2,219.6,467.799,194,472.5),e.bezierVertex(190.9,472.9,187.6,473.2,184.3,473.2),e.endShape(),e.beginShape(),e.vertex(315.8,473.1),e.bezierVertex(309.3,473.1,302.8,472,296.5,469.9),e.bezierVertex(270.4,461,253.8,434.9,257.1,407.9),e.bezierVertex(260,384,273.8,366.8,297,358.3),e.bM ezierVertex(297.7,358.1,298.3,357.8,299,357.6),e.bezierVertex(299.8,357.3,300.6,357.1,301.2,356.8),e.bezierVertex(304.3,355.4,306,351.8,304.9,348.7),e.bezierVertex(304,345.9,301.7,344.2,299,344.2),e.bezierVertex(298.6,344.2,298.1,344.2,297.6,344.3),e.bezierVertex(288.1,346.3,279,350.9,269.7,358.3),e.bezierVertex(268.9,358.9,268.1,359.6,267.2,360.4),e.vertex(265.5,361.8),e.vertex(258.5,367.6),e.vertex(257.4,358.6),e.bezierVertex(257.3,358,257.3,357.5,257.2,357.1),e.bezierVertex(257,356,256.9,354.9,256.9,353.7),e.bezM ierVertex(256.9,334.8,256.9,316,256.9,297.1),e.bezierVertex(256.9,260.3,256.9,222.3,256.8,185),e.bezierVertex(256.8,170.7,268.3,158.8,282.5,158.4),e.bezierVertex(284.8,158.3,286.7,157.6,287.9,156.2),e.bezierVertex(289.099,154.9,289.599,153.2,289.5,151.3),e.bezierVertex(289.3,147.5,286.7,145.1,282.7,145.1),e.bezierVertex(282.5,145.1,282.2,145.1,282,145.1),e.bezierVertex(278.8,145.3,275.5,146.1,272,146.9),e.bezierVertex(270.9,147.2,269.8,147.4,268.6,147.7),e.bezierVertex(267.9,147.9,267,148.2,265.8,148.7),e.bezierVerM tex(265.1,149,264.4,149.3,263.5,149.6),e.vertex(256.8,152),e.vertex(256.8,114.6),e.bezierVertex(256.8,95,256.8,75.4,256.8,55.9),e.bezierVertex(256.8,38,267.2,27.3,284.6,27.3),e.bezierVertex(285.3,27.3,285.9,27.3,286.6,27.3),e.bezierVertex(299,27.9,318.7,34.5,329.6,41.9),e.vertex(336.1,46.3),e.vertex(324.4,53.3),e.bezierVertex(316.2,58.2,310.2,64.6,306,72.9),e.bezierVertex(304.2,76.4,305.1,78.5,306.1,80),e.bezierVertex(307.4,81.9,309.4,83,311.6,83),e.bezierVertex(313.7,83,315.7,81.9,317.1,80.1),e.bezierVertex(317.4,M 79.7,317.8,79,318.1,78.4),e.bezierVertex(318.4,77.9,318.7,77.3,319,76.8),e.bezierVertex(325.3,66.2,336.3,59.9,348.5,59.9),e.bezierVertex(353.2,59.9,357.8,60.8,362.1,62.7),e.bezierVertex(377.6,69.3,386,86.7,381.7,103.2),e.bezierVertex(380.7,107.1,378.5,111.8,371.1,113.1),e.bezierVertex(342.7,118.1,322.2,139.1,317.8,167.8),e.bezierVertex(317.4,170.3,317.3,173.2,317.4,176.5),e.bezierVertex(317.5,180,320.1,182.8,323.5,183),e.bezierVertex(323.6,183,323.8,183,323.9,183),e.bezierVertex(327.1,183,329.8,180.6,330.3,177.2),eM .bezierVertex(330.6,175.7,330.7,174,330.9,172.3),e.bezierVertex(331.1,169.8,331.4,167.3,332,164.7),e.bezierVertex(337.3,141.9,357.7,125.4,380.7,125.4),e.bezierVertex(382.5,125.4,384.3,125.5,386.1,125.7),e.bezierVertex(412.8,128.9,432.6,150.9,432,176.9),e.bezierVertex(431.9,182.3,430.9,187.7,429.1,192.7),e.bezierVertex(427.2,197.9,428,201,432.3,205),e.bezierVertex(446.8,218.7,451.8,236,446.6,255),e.bezierVertex(441.4,274,428.3,286.5,408.7,291.3),e.bezierVertex(406.1,291.9,403.6,292.1,401.1,292.3),e.bezierVertex(400,M 292.4,398.9,292.5,397.9,292.6),e.bezierVertex(393.6,293.1,390.9,295.7,391,299.5),e.bezierVertex(391.1,303.4,394,305.8,398.5,305.8),e.bezierVertex(409.9,305.8,420.8,302.6,431.1,296.4),e.bezierVertex(431.8,296,432.5,295.5,433.2,295.1),e.bezierVertex(433.8,294.7,434.5,294.3,435.2,293.9),e.bezierVertex(436,293.4,436.6,293.2,437.2,293.1),e.bezierVertex(437.4,293,437.7,292.9,438.1,292.8),e.vertex(442.5,291.4),e.vertex(444.2,295.7),e.bezierVertex(450.9,312.4,449.5,328.4,440,343.4),e.bezierVertex(435.3,350.8,428.7,356.7,42M 0.2,361.1),e.bezierVertex(414.3,364.1,413.7,365.2,414.8,371.7),e.bezierVertex(419.5,400.2,403,427.6,375.6,436.9),e.bezierVertex(371,438.5,368.3,440.7,365.8,444.7),e.bezierVertex(355.2,462.5,336.4,473.1,315.8,473.1),e.bezierVertex(315.8,473.1,315.8,473.1,315.8,473.1),e.endShape(),ie(e),e.fill(n),e.beginShape(),e.vertex(120.2,279.9),e.bezierVertex(117.9,279.9,112.4,279.299,112.2,273.599),e.bezierVertex(112,267.7,117.4,266.7,119.7,266.599),e.bezierVertex(133.1,265.799,143.1,259.499,149.3,247.899),e.bezierVertex(149.6,M 247.299,150.1,246.399,150.3,245.399),e.bezierVertex(150.6,244.299,150.5,243.299,150.5,242.7),e.bezierVertex(150.5,242.6,150.5,242.5,150.5,242.299),e.vertex(150.3,238.799),e.vertex(141.1,235.99),e.bezierVertex(114.6,227.799,95.6,202.499,95.9,175.799),e.bezierVertex(95.9,173.99,96.4,168.199,102.2,168.199),e.bezierVertex(102.6,168.199,103,168.199,103.4,168.299),e.bezierVertex(104.8,168.499,108.2,168.899,109.2,175.599),e.bezierVertex(109.3,176.599,109.5,177.599,109.6,178.499),e.bezierVertex(110.4,184.199,111.3,189.99,1M 13.7,195.499),e.bezierVertex(121.9,213.99,139.5,225.499,159.7,225.499),e.bezierVertex(172.1,225.499,184.1,220.899,193.5,212.599),e.bezierVertex(194,212.199,194.4,211.799,194.8,211.399),e.bezierVertex(195.1,211.099,195.5,210.799,195.8,210.399),e.bezierVertex(197.4,208.99,199.2,208.2,200.9,208.2),e.bezierVertex(202.5,208.2,204,208.899,205.3,210.1),e.bezierVertex(208,212.9,207.9,216.9,205,219.9),e.bezierVertex(196.5,228.6,186.3,234.3,174.7,236.8),e.bezierVertex(168.799,238.1,165.6,241,163.899,246.7),e.bezierVertex(158M .3,265.9,139.9,279.7,120.2,279.9),e.vertex(120.2,279.9),e.endShape(),e.beginShape(),e.vertex(187.2,427.5),e.bezierVertex(183.799,427.5,181.299,425.3,180.799,422),e.bezierVertex(180.6,420.8,180.499,419.5,180.399,418.1),e.bezierVertex(180.299,417,180.2,415.8,180.099,414.7),e.bezierVertex(177.199,390.5,156.699,371.3,132.399,370.2),e.bezierVertex(131.99,370.2,131.499,370.2,131.099,370.2),e.bezierVertex(130.699,370.2,130.299,370.2,129.799,370.2),e.bezierVertex(125.99,369.9,123.199,367.2,123.099,363.6),e.bezierVertex(122M .99,360.2,125.799,357.3,129.599,356.9),e.bezierVertex(130.499,356.8,131.499,356.8,132.599,356.7),e.bezierVertex(133.199,356.7,133.799,356.7,134.399,356.6),e.vertex(138.299,356.4),e.vertex(139.1,352.6),e.bezierVertex(139.5,350.7,139.799,348.9,140.2,347),e.bezierVertex(140.899,343.4,141.5,340,142.399,336.8),e.bezierVertex(150.099,310.7,174.399,292,201.399,291.3),e.vertex(201.599,291.3),e.bezierVertex(203.699,291.3,206.299,292,208.299,293.2),e.bezierVertex(210.499,294.5,210.699,297.5,209.99,299.8),e.bezierVertex(209.4M 99,301.5,208.199,303.9,203.299,304.7),e.bezierVertex(202.199,304.9,200.99,305,199.799,305.2),e.bezierVertex(194.499,305.9,188.99,306.599,183.799,308.9),e.bezierVertex(165.499,316.799,155.199,331.299,152.99,352),e.bezierVertex(152.399,357.8,154.499,361.7,159.699,364.5),e.bezierVertex(178.199,374.4,189.399,390,193.099,410.9),e.bezierVertex(193.699,414.299,193.899,418,193.599,422),e.bezierVertex(193.399,425.2,190.899,427.5,187.399,427.5),e.vertex(187.2,427.5),e.endShape(),e.beginShape(),e.vertex(364.3,281.1),e.bezierVM ertex(346.3,280.6,332.9,272.8,323.5,257),e.bezierVertex(321.6,253.9,320.4,250.2,319.2,246.7),e.bezierVertex(317.7,242.2,315,239.799,310.5,238.799),e.bezierVertex(298.5,236.299,288,230.7,279.4,222.1),e.bezierVertex(276.7,219.4,274.9,215.299,278,211.9),e.bezierVertex(279.4,210.3,281,209.6,282.6,209.6),e.bezierVertex(284.4,209.6,286.4,210.6,288.3,212.5),e.bezierVertex(297.8,221.8,310.4,226.9,323.9,226.9),e.bezierVertex(340.2,226.9,355.1,219.3,364.8,206.2),e.bezierVertex(371,197.8,374.2,188.5,374.5,178.5),e.vertex(374.M 5,177.9),e.bezierVertex(374.5,177,374.5,176.1,374.7,175.4),e.bezierVertex(375.3,171.8,377.9,169.5,381.3,169.5),e.bezierVertex(381.4,169.5,381.5,169.5,381.7,169.5),e.bezierVertex(385.4,169.7,388,172.4,388,176.1),e.bezierVertex(388.1,190.7,383.4,204,374.2,215.8),e.bezierVertex(365.8,226.5,354.7,233.9,341.2,237.9),e.bezierVertex(340,238.3,338.7,238.6,337.3,239.1),e.bezierVertex(335.9,239.6,335.1,240.4,334.7,240.9),e.bezierVertex(334.599,241,334.5,241.1,334.4,241.2),e.vertex(331.799,243.6),e.vertex(333.199,246.8),e.bezM ierVertex(338.199,258,346.799,264.9,358.699,267.3),e.bezierVertex(360.199,267.6,361.599,267.7,362.99,267.9),e.bezierVertex(363.599,268,364.299,268,364.899,268.1),e.bezierVertex(369.099,268.6,371.799,271.4,371.499,275),e.bezierVertex(371.199,278.6,368.299,281.2,364.399,281.2),e.vertex(364.3,281.1),e.endShape(),e.beginShape(),e.vertex(323.9,437),e.bezierVertex(323.7,437,323.5,437,323.299,437),e.bezierVertex(319.599,436.7,317.299,434.1,317.4,430.2),e.bezierVertex(317.9,406.099,328.299,388,349.5,375),e.bezierVertex(350M .7,374.2,352,373.5,353.4,372.8),e.bezierVertex(354.099,372.4,354.7,372.1,355.299,371.7),e.vertex(357.499,370.5),e.vertex(357.799,368),e.bezierVertex(360.4,346.6,345.199,323.7,323.9,317),e.bezierVertex(319.099,315.5,314.099,314.9,309.299,314.4),e.vertex(308.199,314.299),e.bezierVertex(305.99,314.099,300.799,312.9,300.899,307.299),e.bezierVertex(300.99,303.499,303.899,300.9,308.099,300.9),e.vertex(308.299,300.9),e.bezierVertex(327.099,301.299,343.099,308.7,355.699,322.9),e.bezierVertex(364.299,332.5,369.399,344.099,3M 70.99,357.299),e.bezierVertex(371.099,358.4,371.299,359.4,371.499,360.499),e.bezierVertex(371.599,360.99,371.699,361.499,371.799,361.99),e.vertex(372.499,365.899),e.vertex(377.899,366.199),e.bezierVertex(378.799,366.299,379.699,366.299,380.599,366.399),e.bezierVertex(385.099,366.699,387.899,369.399,387.799,373.299),e.bezierVertex(387.699,377.099,384.99,379.599,380.799,379.799),e.bezierVertex(369.799,380.199,359.99,383.299,351.899,389.299),e.bezierVertex(338.799,398.799,331.699,411.699,330.699,427.499),e.vertex(330.M 699,428.299),e.bezierVertex(330.599,429.199,330.599,430.099,330.499,430.799),e.bezierVertex(330,434.7,327.5,437,323.9,437),e.endShape()}function T(e){return e[0].map(((t,n)=>e.map((e=>e[n]))))}function A(e){return e.map((e=>Array.isArray(e)?A(e):e))}function D(e,t){return floor(random(e,t))}function k(e){let t=0;for(const n of e)t+=n[1];let n=random(t),r=0;for(const t of e)if(r+=t[1],n<r)return t[0];return null}function L(e){for(let t=1;t<e.length;++t){let n=D(0,t),r=e[t];e[t]=e[n],e[n]=r}}function P(e){return nullM ==e||""===e}function O(e){return new Promise((t=>setTimeout(t,e)))}function F(e,t,n){let r=0;for(let i=1;i<=1e3;++i)for(let o=1;o<=1e3;++o)if(e*o%(t*i)==0){let e=1*i/o;abs(e-n)<abs(r-n)&&(r=e)}return r}function N(){let e=60*(new Date).getTimezoneOffset()*1e3;return new Date(Date.now()-e).toISOString().slice(0,-1)}function B(e,t,n){let r;if(push(),textSize(e),textWidth(t)<=n)r=t;else for(let e=0;e<t.length;++e){const i=t.slice(0,e+1)+"...";if(textWidth(i)>n){r=i;break}}return pop(),r}function Y(e){var t=e%10,n=e%100M ;return 1==t&&11!=n?e+"st":2==t&&12!=n?e+"nd":3==t&&13!=n?e+"rd":e+"th"}class G{constructor(e,t,n){this.n=t,this.m=n,this.mat=[];let r=0;for(let t=0;t<this.n;++t){this.mat.push([]);for(let n=0;n<this.m;++n)this.mat[t].push(r<e.length?e[r]:0),r+=1}return this}copy(){return new G(this.mat.flat(),this.n,this.m)}}class H{static __linear=e=>e;static __relu=e=>Math.max(e,0);static __leaky_relu=e=>e>0?e:.2*e;static __sigmoid=e=>1/(1+Math.exp(-e));static __tanh=e=>Math.tanh(e);static __apply_unary_op(e,t){const n=e.copy();M for(let e=0;e<n.n;++e)for(let r=0;r<n.m;++r)n.mat[e][r]=t(n.mat[e][r]);return n}static linear=e=>H.__apply_unary_op(e,H.__linear);static relu=e=>H.__apply_unary_op(e,H.__relu);static leaky_relu=e=>H.__apply_unary_op(e,H.__leaky_relu);static sigmoid=e=>H.__apply_unary_op(e,H.__sigmoid);static tanh=e=>H.__apply_unary_op(e,H.__tanh);static __add=(e,t)=>e+t;static __mul=(e,t)=>e*t;static __apply_binary_op=(e,t,n)=>{"object"!=typeof t&&(t=new G([t],1,1));const r=e.copy();for(let e=0;e<r.n;++e)for(let i=0;i<r.m;++i)r.matM [e][i]=n(r.mat[e][i],t.mat[e%t.n][i%t.m]);return r};static mul=(e,t)=>H.__apply_binary_op(e,t,H.__mul);static add=(e,t)=>H.__apply_binary_op(e,t,H.__add);static matMul(e,t){const n=new G([],e.n,t.m);for(let r=0;r<n.n;++r)for(let i=0;i<n.m;++i)for(let o=0;o<e.m;++o)n.mat[r][i]+=e.mat[r][o]*t.mat[o][i];return n}static softmax(e){const t=H.__apply_unary_op(e,(e=>Math.exp(e))),n=t.mat.flat().reduce(((e,t)=>e+t));for(let r=0;r<e.n;++r)for(let i=0;i<e.m;++i)t.mat[r][i]/=n;return t}}class ${constructor(e,t){this.scale=e,tM his.offset=t}forward(e){return H.add(H.mul(e,this.scale),this.offset)}}class X{constructor(){}forward(e){return e.map((e=>e.flat()))}}class W{constructor(e,t,n,r){this.out_dim=e,this.activation=t,this.w=n,this.b=r}forward(e){const t=H.add(H.matMul(e,this.w),this.b);return null==this.activation?t:this.activation(t)}}class U{constructor(e,t,n){this.preprocessLayers=e,this.hiddenLayers=t,this.outputLayer=n,this.totalNeurons=this.hiddenLayers.map((e=>e.out_dim)),this.currentOrders=[],this.currentIteration=null}updateNeM urons(e,t){if(t!=this.currentIteration){this.currentOrders=[];for(let e=0;e<this.totalNeurons.length;++e){randomSeed(100*(t+1)+e);const n=[];for(let t=0;t<this.totalNeurons[e];++t)n.push(t);L(n),this.currentOrders.push(n)}this.currentIteration=t}const n=A(this.totalNeurons),r=n.reduce(((e,t)=>e+t))*(1-e);for(let e=0;e<r;++e){const t=n.map(((e,t)=>(e-1)/this.totalNeurons[t]));n[t.map(((e,t)=>[e,t])).reduce(((e,t)=>t[0]>e[0]?t:e))[1]]-=Math.min(r-e,1)}this.neuronsLife=[];for(let e=0;e<n.length;++e){const t=this.curreM ntOrders[e],r=Array(this.totalNeurons[e]).fill(0);for(let i=0;i<n[e];++i)r[t[i]]=Math.min(n[e]-i,1);this.neuronsLife.push(r)}}getTotalNeurons(){return A(this.totalNeurons)}getNeuronsLife(){return A(this.neuronsLife)}forward(e){for(const t of this.preprocessLayers)e=t.forward(e);for(const[t,n]of this.hiddenLayers.entries()){e=n.forward(e);const r=new G(this.neuronsLife[t],1,e.m);e=H.mul(e,r)}return e=this.outputLayer.forward(e),H.softmax(e)}}function q(e){switch(e){case"relu":return H.relu;case"sigmoid":return H.sigM moid;case"tanh":return H.tanh;case"leaky_relu":return H.leaky_relu;default:return H.linear}}function j(e,t){const n=[],r=[],i=Z(t);let o=null,a=0,l=[];for(const t of e.config.layers)if("InputLayer"==t.class_name)o=t.config.batch_input_shape.slice(1),l=o;else if("Rescaling"==t.class_name)n.push(new $(t.config.scale,t.config.offset));else if("Flatten"==t.class_name)o=[o.reduce(((e,t)=>e*t))];else if("Dense"==t.class_name){const e=[t.config.units],n=o[0]*e[0],l=e[0],s=i.subarray(a,a+n);a+=n;const h=i.subarray(a,a+l);aM +=l;const c=new G(s,o[0],e[0]),u=new G(h,1,e[0]),f=q(t.config.activation);r.push(new W(e[0],f,c,u)),o=e}const s=r.pop();return{model:new U(n,r,s),inputDim:l}}function Z(e){const t=window.atob(e),n=t.length/Float32Array.BYTES_PER_ELEMENT,r=new DataView(new ArrayBuffer(Float32Array.BYTES_PER_ELEMENT)),i=new Float32Array(n);let o=0;for(let e=0;e<n;e++){o=4*e;for(let e=0;e<4;++e)r.setUint8(e,t.charCodeAt(o+e));i[e]=r.getFloat32(0,!0)}return i}class K{constructor(e){this.elt=e,this._events={},this.width=this.elt.offsetWM idth,this.height=this.elt.offsetHeight}position(){if(0===arguments.length)return{x:this.elt.offsetLeft,y:this.elt.offsetTop};var e="absolute";return"static"!==arguments[2]&&"fixed"!==arguments[2]&&"relative"!==arguments[2]&&"sticky"!==arguments[2]&&"initial"!==arguments[2]&&"inherit"!==arguments[2]||(e=arguments[2]),this.elt.style.position=e,this.elt.style.left=arguments[0]+"px",this.elt.style.top=arguments[1]+"px",this.x=arguments[0],this.y=arguments[1],this}show(){return this.elt.style.display="block",this}hide()M {return this.elt.style.display="none",this}size(e,t){if(0===arguments.length)return{width:this.elt.offsetWidth,height:this.elt.offsetHeight};var n=e,r=t;if(n!==te||r!==te){if(n===te?n=t*this.width/this.height:r===te&&(r=e*this.height/this.width),this.elt instanceof HTMLCanvasElement){var i,o={},a=this.elt.getContext("2d");for(i in a)o[i]=a[i];for(i in this.elt.setAttribute("width",n*this._pInst._pixelDensity),this.elt.setAttribute("height",r*this._pInst._pixelDensity),this.elt.style.width=n+"px",this.elt.style.heigM ht=r+"px",this._pInst.scale(this._pInst._pixelDensity,this._pInst._pixelDensity),o)this.elt.getContext("2d")[i]=o[i]}else this.elt.style.width=n+"px",this.elt.style.height=r+"px",this.elt.width=n,this.elt.height=r;this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight,this._pInst&&this._pInst._curElement&&this._pInst._curElement.elt===this.elt&&(this._pInst._setProperty("width",this.elt.offsetWidth),this._pInst._setProperty("height",this.elt.offsetHeight))}return this}style(e,t){if(t instanceof Color&&(tM ="rgba("+t.levels[0]+","+t.levels[1]+","+t.levels[2]+","+t.levels[3]/255+")"),void 0===t){if(-1===e.indexOf(":"))return window.getComputedStyle(this.elt).getPropertyValue(e);for(var n=e.split(";"),r=0;r<n.length;r++){var i=n[r].split(":");i[0]&&i[1]&&(this.elt.style[i[0].trim()]=i[1].trim())}}else if(this.elt.style[e]=t,"width"===e||"height"===e||"left"===e||"top"===e){var o=window.getComputedStyle(this.elt).getPropertyValue(e).replace(/[^\d.]/g,"");this[e]=Math.round(parseFloat(o,10))}return this}value(){return arM guments.length>0?(this.elt.value=arguments[0],this):"range"===this.elt.type?parseFloat(this.elt.value):this.elt.value}mouseClicked(e){return this._adjustListener("click",e,this),this}isFocused(){return document.activeElement===this.elt}_adjustListener(e,t,n){return!1===t?this._detachListener(e,n):this._attachListener(e,t,n),this}_attachListener(e,t,n){n._events[e]&&this._detachListener(e,n);var r=t.bind(n);n.elt.addEventListener(e,r,!1),n._events[e]=r}_detachListener(e,t){var n=t._events[e];t.elt.removeEventListeneM r(e,n,!1),t._events[e]=null}}function J(e,t){var n=document.createElement("button");return n.innerHTML=e,t&&(n.value=t),ee(n)}function Q(e){var t=arguments.length>1&&void 0!==arguments[1]&&arguments[1],n=function(t){var n=!0,r=!1,i=void 0;try{for(var o,a=t.target.files[Symbol.iterator]();!(n=(o=a.next()).done);n=!0){var l=o.value;File._load(l,e)}}catch(e){r=!0,i=e}finally{try{n||null==a.return||a.return()}finally{if(r)throw i}}};if(window.File&&window.FileReader&&window.FileList&&window.Blob){var r=document.createEM lement("input");return r.setAttribute("type","file"),t&&r.setAttribute("multiple",!0),r.addEventListener("change",n,!1),ee(r)}}function ee(e){return document.body.appendChild(e),new K(e)}createImg=function(){var e,t=document.createElement("img"),n=arguments;return n.length>1&&"string"==typeof n[1]&&(t.alt=n[1]),n.length>2&&"string"==typeof n[2]&&(t.crossOrigin=n[2]),t.src=n[0],e=ee(t,this),t.addEventListener("load",(function(){e.width=t.offsetWidth||t.width,e.height=t.offsetHeight||t.height;var r=n[n.length-1];"funM ction"==typeof r&&r(e)})),e},createInput=function(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:"",t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:"text",n=document.createElement("input");return n.setAttribute("value",e),n.setAttribute("type",t),ee(n,this)};const te="auto";function ne(e){re(e);const t=e._rectMode;e.rectMode(CORNER),e.rect(0,0,e.width,e.height),e.rectMode(t),ie(e)}function re(e){e.push(),e.fill(255,255,255,255),e.blendMode(REMOVE)}function ie(e){e.blendMode(BLEND),e.pop()}FM ile=function(e,t){this.file=e,this._pInst=t;var n=e.type.split("/");this.type=n[0],this.subtype=n[1],this.name=e.name,this.size=e.size,this.data=void 0},File._createLoader=function(e,t){var n=new FileReader;return n.onload=function(n){var r=new File(e);if("application/json"===r.file.type)r.data=JSON.parse(n.target.result);else if("text/xml"===r.file.type){var i=(new DOMParser).parseFromString(n.target.result,"text/xml");r.data=new XML(i.documentElement)}else r.data=n.target.result;t(r)},n},File._load=function(e,t){M if(/^text\//.test(e.type)||"application/json"===e.type)File._createLoader(e,t).readAsText(e);else if(/^(video|audio)\//.test(e.type)){var n=new File(e);n.data=URL.createObjectURL(e),t(n)}else File._createLoader(e,t).readAsDataURL(e)},XML=function(e){if(e)this.DOM=e;else{var t=document.implementation.createDocument(null,"doc");this.DOM=t.createElement("root")}},document.addEventListener("DOMContentLoaded",(function(){addEventListener("mousemove",(e=>{window.mouseX=e.pageX,window.mouseY=e.pageY}))})),new e("global");M const oe="163";let ae,le,se,he,ce,ue,fe,de,xe,ge,pe,me,be,ye,we,ve,ze,Ve,_e,Me,Ee,Se,Re,Ie,Ce,Te,Ae,De,ke,Le,Pe,Oe,Fe,Ne,Be,Ye,Ge,He,$e,Xe,We,Ue,qe,je,Ze,Ke,Je,Qe,et,tt,nt,rt,it,ot,at,lt,st,ht,ct,ut,ft,dt,xt,gt,pt,mt,bt,yt,wt,vt,zt,Vt,_t,Mt,Et,St,Rt,It,Ct,Tt,At=!1,Dt=!1,kt=!0,Lt=!1,Pt=!1;const Ot=[" ","Growing","Stable","Decaying","Dead","Rebirth"];let Ft,Nt,Bt,Yt,Gt,Ht,$t,Xt,Wt,Ut,qt,jt,Zt,Kt,Jt,Qt,en,tn,nn,rn,on,an,ln,sn,hn=0,cn=0,un=0,fn=!1,dn=!0,xn=!0,gn=null,pn=null,mn=null,bn=!1,yn=!1,wn=null,vn=null,zn=!1;asM ync function setup(){let e=windowWidth,t=windowHeight;createCanvas(e,t),et=createGraphics(e,t),Xe=createGraphics(e,t),$e=createGraphics(e,t),We=createGraphics(e,t),Ue=createGraphics(e,t),qe=createGraphics(e,t),Qe=createGraphics(e,t),je=createGraphics(e,t),Ze=createGraphics(e,t),Ke=createGraphics(e,t),Je=createGraphics(e,t),tt=createGraphics(500,500),nt=createGraphics(500,500),rt=createGraphics(500,500),_n(),Mn(),Sn(),await En(),Gn(),Rn(),bn=!0}function _n(){Et=parseInt(oe),randomSeed(Et),noiseSeed(Et)}function Mn()M {Wt=Ir(p.training_traits),Cr(Wt)}async function En(){let e;Jt=r(),Qt=o(),[Xt,e]=await Promise.all([s(Jt),h(Qt)]),Ut=new V(Wt.visual,e.layers_config,e.weight_b64),Ut.updateAge(new Date),_n(),Wt.training=e.training_traits,Ht=e.model_name,$t=e.classes_name}function Sn(){le=min(width,height)/1024,ut=Rr.findIndex((e=>e[0]===Wt.visual.colorPalette)),ft=[["#ffffff","#231f20","#231f20"],["#231f20","#ffffff","#ffffff"],["#104da8","#ffffff","#ffffff"],["#722F1F","#FCE1B2","#FCE1B2"],["#e88120","#f9f2e5","#f9f2e5"],["#f6b941"M ,"#2E2E2E","#2E2E2E"],["#45daaa","#012221","#012221"],["#F1F1F1","#328DFE","#328DFE"],["#111822","#D3EB8D","#D3EB8D"],["#713FF9","#D6D5E6","#D6D5E6"],["#FBDA9D","#795106","#795106"],["#8f5b62","#ead0d0","#ead0d0"],["#eae4cb","#508cac","#508cac"],["#ffc6cc","#cc313d","#cc313d"],["#60A900","#E0FE00","#E0FE00"],["#507DBE","#D0D1D3","#D0D1D3"],["#305848","#E8F2EE","#E8F2EE"],["#2a2634","#5b6988","#cb78a2","#5b6988"],["#590e29","#fd5e53","#fd5e53","#ffe373"],["#0a141d","#57d4e4","#328195","#2A9ECF","#0ab6a8","#57d4e4"],M ["#3a2d28","#d5c2ac","#df6338","#3d9895","#d5c2ac"],["#030706","#77c4d9","#77c4d9","#77c4d9","#ffffff","#ffffff","#e72020","#e72020"],["#3a4664","#92f5ff","#f9ff94","#eaa0a2","#55dde0"],["#fbfaff","#f04bb1","#f04bb1","#fac373","#82cef0","#8b31ce"],["#000000","#ffffff","#ff0002","#f26522","#fdff00","#00ff03","#01fffe","#0000ff","#ff00ff"]];for(let e=0;e<ft.length;++e)for(let t=0;t<ft[e].length;++t)ft[e][t]=cr(ft[e][t]);pt=[],ct=ft[ut][0],st=ft[ut][1]}function Rn(){gn=document.querySelector("#upload"),pn=document.queM rySelector("#inputUpload"),gn.addEventListener("dblclick",(()=>{if(!Lt&&!yn)if(In(Ie)&&cn==Ve-1)pn.click();else{if(4!=Pe&&5!=Pe&&(In(Ie)||cn!=Ve-1))return;fn=!0,dn=!0,Bt=0,un=0}})),pn.addEventListener("click",(()=>{pn.value=null,gn.style.display="block"})),pn.addEventListener("change",(()=>{const[e]=pn.files;e?(se=null,gn.style.display="none",Tn(URL.createObjectURL(e)),mn=e):gn.style.display="block"}))}function In(e){for(let t=0;t<e.length;++t){let n=0;for(let r=0;r<e[t].length;++r)e[t][r]>0&&++n;if(0==n)return!1}rM eturn!0}function Cn(){null!=se&&(un=0,Pt=!0,he=0,ue=0,drewLineAnim=!0,ce=(ae/2+we/2)/le,loadImage(se.elt.src,(e=>{const[t,n,r]=Gt,i=createGraphics(t,n);i.image(e,0,0,t,n),i.loadPixels();const o=i.pixels.filter(((e,t)=>t%4!=3)),a=Ut.classifyImage(o);Zt=T([a,$t.map((e=>e.toUpperCase()))]).sort(((e,t)=>e[0]>t[0]?-1:1))})))}function Tn(e){se=createImg(e,""),se.hide(),Cn()}function An(){zn||(ce+=(width-ae-we)/tn/le),re(Xe),Xe.rect(ce*le,0,width,height),ie(Xe),un>=ge&&1==kt&&(kt=!1,un-=ge),kt&&(re($e),$e.strokeWeight(2*FM e),Jn(he,ze,ct,ct,$e),ie($e)),un>=ge&&0==kt&&(kt=!0,un-=ge,he+=1,he==en&&(++ue,he=0,ce=(ae/2+we/2)/le,1==ue&&(Pt=!1,Dn(),ye=millis())))}function Dn(){At=!0,pe=!1,me=!1,tryButton=br("Try Again",width/2-225*le,height/2+265*le,290*le,40*le,kn),closeResultButton=br("Close",width/2+75*le,height/2+265*le,150*le,40*le,Ln)}function kn(){At=!1,tryButton.hide(),closeResultButton.hide(),pn.click()}function Ln(){Yt=!0,At=!1,Gn(),tryButton.hide(),closeResultButton.hide(),gn.style.display="block",se=null}function keyTyped(){bn&&M !1===yn&&!1===yr()&&("i"!==key&&"I"!==key||(Dt=!Dt),"b"!==key&&"B"!==key||(xn=!xn),"s"!==key&&"S"!==key||!1!==Lt||saveCanvasAtCurrentTime(),"k"!==key&&"K"!==key||!1!==Lt||save4KCanvasAtCurrentTime(),"u"!==key&&"U"!==key||!1!==Lt||!1!==At||!1!==fn||!1!==Pt||On())}function On(){Lt=!0,wn=null,vn=null,submitButton=br("Submit",width/2-155*le,height/2+115*le,150*le,40*le,Fn),closeSettingButton=br("Close",width/2+5*le,height/2+115*le,150*le,40*le,Yn),vt=createInput(),vt.position(width/2-252.5*le,height/2-40*le),vt.size(50M 0*le,25*le),vt.style("font-size","15px"),vt.value(Jt||""),zt=createInput(),zt.position(width/2-252.2*le,height/2+35*le),zt.size(500*le,25*le),zt.style("font-size","15px"),zt.value(Qt||"")}function Fn(){Vt=vt.value(),_t=zt.value(),submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide(),Lt=!1,yn=!0,Nn()}async function Nn(){[wn,vn,_]=await Promise.all([c(Vt),u(_t),O(1e3)]),yn=!1,wn&&vn?(n(Vt),i(_t),window.location.reload()):(Lt=!0,submitButton.show(),closeSettingButton.show(),vt.show(),zt.show())}function BnM (){Je.textFont("Trebuchet MS"),Je.noStroke(),pr(Je,600*le,200*le),Je.strokeWeight(1*le),Je.stroke(xt),Je.fill(xt),Je.textSize(50*le),Je.text("update()",width/2,height/2+2.5*le)}function Yn(){wn=null,vn=null,Lt=!1,submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide()}function Gn(){_n(),nn=Date.now(),pe=!1,me=!1,St=Wt.training.structure_gen,Rt=Wt.visual.birthYear,It=Wt.visual.lifeCycle,Ct=Wt.training.epoch_num,Tt=Wt.training.activation_func,Ft=Mr.findIndex((e=>e[0]==Wt.visual.hardwareAcceleration))+1,1==FM t?(Nt=30,fe=40):2==Ft?(Nt=15,fe=20):(Nt=2,fe=10);const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),ae=100*le,ht=50*le,Oe=Sr.findIndexM ((e=>e[0]==Wt.visual.nodeShape))+1,dt=Er.findIndex((e=>e[0]==Wt.visual.nodeFill))+1,lt=_r.findIndex((e=>e[0]==Wt.visual.pattern))+1,de=Math.tanh(Math.log10(Xt.avgfeerate)),de=map(de,0,1,.2,.8),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(EeM /30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,zM e=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,at=.7,pt=[],xt=ft[ut][2],gt=ft[ut][ft[ut].length-1];for(let e=3;e<ft[ut].lenM gth-1;e++)pt.push(ft[ut][e]);mt=sr(xt,gt,pt,width),bt=[],wt=[],yt=width/(Ve-1);for(let e=0;e<Ve;e++)bt.push(hr(mt,yt*e/width)),wt.push(hr(mt,yt*e/width));wt.unshift(bt[0]),wt.push(bt[bt.length-1]),hn=0,cn=0,un=0,Yt=!0;const n={xLeft:ae/8,xRight:width-ae/8,yTop:ae/8,yBottom:height-ae/8},r=Ce.map((e=>e.length));jt=new R(bt,r,n,Oe,le)}function Hn(e,t){let n=Ce[e].length;return[e*we+we/2+ae/2,height/2-(n-1)/2*ve+t*ve]}function $n(e,t){le=min(e,t)/1024,ae=100*le,ht=50*le,we=(e-ae)/Ve,ve=(t-2*ae)/_e,ze=min(we,ve)/2,De=[]M ;for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}xe=floor(De.length*de),Le=[],ke=[],ge=floor(map(de,.2,.8,15,2));for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,mt=sr(xt,gt,pt,e),bt=[],wt=[],yt=e/(Ve-1);for(let t=0;t<Ve;t++)bt.push(hr(mt,yt*t/e)),wt.push(hr(mt,yt*t/e));wt.unshift(bt[0]),wt.push(bt[bt.lenM gth-1])}function Xn(){const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=M Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.lengM th;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];foM r(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le}function Wn(){jt.update();const e=4==Pe?0:Kt;jt.draw(Qe,ct,dt,e,le)}function Un(){if(!bn)return ar(),void et.image(je,0,0);if(4==Pe||5==Pe)return Wn(),void et.image(Qe,0,0);un>=Nt&&hn<Ve&&(hn++,un=0);for(let e=0;e<hn;e++)1==dt?it=ot=bt[e]:(it=ct,ot=bt[e]),Kn(e,it,ot,$e);un>=Nt&&cn<Ve-1&&(cn++,un=0);for(let e=0;e<cn;e++)Zn(e)}funM ction qn(){et.background(ct),Ue.background(255),Ue.rectMode(CENTER),ne(Ue),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),Ue.stroke(st),Ue.strokeWeight(8*le),Ue.fill(ct),Qe.background(255),Qe.rectMode(CENTER),ne(Qe),Qe.strokeWeight(le),qe.background(255),qe.rectMode(CENTER),ne(qe),qe.textAlign(LEFT),$e.background(255),$e.rectMode(CENTER),ne($e),Xe.background(255),ne(Xe),Xe.strokeWeight(Ne),We.background(255),We.rectMode(CENTER),ne(We),We.fill(st),We.stroke(st),We.strokeWeight(.1*le),er(lt),We.noStroke(),xn&&(We.recM t(ae/16,height/2,ae/8,height),We.rect(width-ae/16,height/2,ae/8,height),We.rect(width/2,ae/16,width,ae/8),We.rect(width/2,height-ae/16,width,ae/8)),Ze.background(255),Ze.rectMode(CENTER),ne(Ze),Ze.textAlign(CENTER,CENTER),Ze.textStyle(BOLD),Ze.stroke(st),Ze.strokeWeight(8*le),Ze.fill(ct),je.background(255),je.rectMode(CENTER),ne(je),je.textAlign(CENTER,CENTER),je.textStyle(BOLD),Ke.background(255),Ke.rectMode(CENTER),ne(Ke),Ke.textAlign(CENTER,CENTER),Ke.textStyle(BOLD),Ke.stroke(st),Ke.strokeWeight(8*le),Ke.fill(cM t),Je.background(255),Je.rectMode(CENTER),ne(Je),Je.textAlign(CENTER,CENTER),Je.textStyle(BOLD),Je.stroke(st),Je.strokeWeight(8*le),Je.fill(ct),Un(),et.image(We,0,0),Pt&&An(),et.image(Xe,0,0),et.image($e,0,0),At&&(tr(),et.image(Ue,0,0)),fn&&(lr(),et.image(Ze,0,0)),Lt&&(or(),et.image(Ke,0,0)),Dt&&(ir(),et.image(qe,0,0)),yn&&(Bn(),et.image(Je,0,0))}function draw(){const e=Date.now();bn&&(Ut.updateAge(new Date(e)),Xn()),qn(),image(et,0,0),zn||un++}function Zn(e){let t,n=Ce[e].length,r=Ce[e+1].length;for(let i=0;i<n;i+M +){const[n,o]=Hn(e,i);for(let a=0;a<r;a++){const[r,l]=Hn(e+1,a);t=map(min(Ce[e][i],Ce[e+1][a]),0,1,0,.5),ur(n,o,r,l,bt[e],bt[e+1],Xe,t)}}}function Kn(e,t,n,r){let i,o,a,l=Ce[e].length;for(let s=0;s<l;s++){const[l,h]=Hn(e,s);i=Ce[e][s],a=map(Be,1/30,1,3,10),o=map(Ce[e][s],0,1,2*a,0)*le,o<1.5*le&&(o=0),Qn(l,h,ze,Oe,t,n,o,i,r)}}function Jn(e,t,n,r,i){for(let o=0;o<Le[e].length;o++)Qn(Le[e][o][0],Le[e][o][1],t,Oe,n,r,0,1,i)}function Qn(e,t,n,r,i,o,a,l,s){s.stroke(dr(o,map(l,0,1,.25,1))),s.fill(dr(i,map(l,0,1,.15,1))),sM .strokeWeight(Fe),fr([a],s),3==dt&&s.fill(dr(i,0)),1==r?s.ellipse(e,t,n):2==r?s.rect(e,t,7*n/8,7*n/8):3==r&&(s.beginShape(),s.vertex(e-4*n/7,t),s.vertex(e,t-4*n/7),s.vertex(e+4*n/7,t),s.vertex(e,t+4*n/7),s.endShape(CLOSE))}function er(e){if(1==e);else if(2==e){We.strokeWeight(1*le);for(let e=ht/4;e<width+ht/4;e+=ht)for(let t=ht/4;t<height+ht/4;t+=ht)We.point(e,t)}else if(3==e){ht=25*le;for(let e=ht/2;e<height+ht/2;e+=ht)We.line(0,e,width,e);for(let e=ht/2;e<width+ht/2;e+=ht)We.line(e,0,e,height)}}function tr(){Ue.tM extFont("Trebuchet MS"),Ue.textAlign(LEFT,CENTER),Ue.noStroke(),pr(Ue,800*le,500*le),Ue.noStroke(),Ue.fill(dr(st,.75)),Ue.rect(width/2,height/2-100*le,800*le,300*le,25*le,25*le,0,0),Ue.fill(st),Ue.rect(width/2-250*le,height/2-100*le,225*le,225*le),Ue.image(se.elt,width/2-357.5*le,height/2-207.5*le,215*le,215*le);let e=100*Zt[0][0];Ue.fill(ct),Ue.textSize(25*le),Ue.textStyle(NORMAL),1==me&&(e>=0&&e<20?Ue.text("I have a feeling this image belongs to",width/2-100*le,height/2-170*le):e>=20&&e<40?Ue.text("I have a hunchM this image belongs to",width/2-100*le,height/2-170*le):e>=40&&e<60?Ue.text("I think this image belongs to",width/2-100*le,height/2-170*le):e>=60&&e<80?Ue.text("I'm almost certain this image belongs to",width/2-100*le,height/2-170*le):Ue.text("I'm positive this image belongs to",width/2-100*le,height/2-170*le));let t=e.toFixed(2);"100.00"==t&&(t="100"),1==me&&Ue.text("I'm "+t+"% confident that I'm right!",width/2-100*le,height/2-25*le),example=Zt.map((e=>e[1])),be=Ue.textWidth('"FIDENZAAAA"'),defaultPhrase=Ue.textWM idth('"PERPENDICULAR INHABITATION"'),Ue.textStyle(BOLD);const n=me?example[0]:random(example);if(1===n.split(" ").length){let e=75*be/Ue.textWidth('"'+n+'"');e>75&&(e=75),Ue.textSize(e*le),Ue.text('"'+n+'"',width/2-100*le,height/2-90*le)}else nr(width/2-100*le,height/2-90*le,460*le,110*le,n,Ue);if(millis()-ye>1500&&(me=!0),C(tt,nt,st,ct,Pe,Mt),Ue.image(nt,width/2-370*le,height/2+70*le,80*le,80*le),3==Pe){let e;e=map(Mt,50,60,.25,1.3),I(rt,e),Ue.image(rt,width/2-370*le,height/2+70*le,80*le,80*le)}let r,i;Ue.image(ttM ,width/2-370*le,height/2+70*le,80*le,80*le),Ue.fill(xt),Ue.textSize(40*le),Ue.text("INTELLIGENCE INFO",width/2-275*le,height/2+115*le),Ue.textSize(18*le),Ue.textStyle(NORMAL),Ue.circle(width/2-360*le,height/2+180*le,7.5*le),1==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s growing and getting smarter by the day.`:2==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s stable and it has reached peak performance.`:3==Pe&&(r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s decaying and losingM its luster.`),i=2==Pe?"The Perceptron remains stable for some time before entering the decay phase.":`Wait until ${new Date(an).toLocaleString("en-US")} for your Perceptron to reach its peak performance.`,Ue.text(r,width/2-350*le,height/2+180*le),Ue.circle(width/2-360*le,height/2+210*le,7.5*le),Ue.text(i,width/2-350*le,height/2+210*le),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),gr(Ue,width/2-225*le,width/2+65*le,height/2+265*le,height/2+305*le,"SELECT ANOTHER IMAGE"),gr(Ue,width/2+75*le,width/2+225*le,height/2M +265*le,height/2+305*le,"CLOSE")}function nr(e,t,n,r,i,o){let a=i.split(" "),l=75*be/o.textWidth('"'+i+'"'),s=0,h=[],c=[],u=[],f="",d="";if(l>=50)l>75&&(l=75),o.textSize(l*le),o.text('"'+i+'"',e,t);else if(l<50){if(l=50*defaultPhrase/o.textWidth('"'+i+'"'),l>30){if(l>50&&(l=50),[f,d]=rr(l,n,s,h,c,a,f,d,Ue),0==c.length)return o.textSize(l*le),void o.text('"'+i+'"',e,t);for(s=0,h=[],c=[];o.textWidth(d)>n/le;)l=l*n/le/o.textWidth(d),f="",d="",[f,d]=rr(l,n,s,h,c,a,f,d,Ue)}else{l=30,o.textSize(l);for(let e=0;e<a.length;M e++)s+=o.textWidth(" "+a[e]),s<=n/le?h.push(a[e]):s>n/le&&s<=n/le*2?c.push(a[e]):u.push(a[e]);for(let e=1;e<h.length;e++)f=f+" "+h[e];if(f='"'+h[0]+f,0==u.length){for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+c[c.length-1]+'"'}else if(1==c.length)d="... "+u[u.length-1]+'"';else{for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+"... "+u[u.length-1]+'"'}}o.textSize(l*le);let r=1.25*(o.textDescent()+o.textAscent());o.text(f,e,t-r/2),o.text(d,e,t+r/2)}}function rr(e,t,n,r,i,o,a,l,s){s.textSize(e);for(let e=0;e<o.length;e++M )(n+=s.textWidth(" "+o[e]))<=t/le?r.push(o[e]):i.push(o[e]);for(let e=1;e<r.length;e++)a=a+" "+r[e];if(a='"'+r[0]+a,0==i.length&&(a+='"',l=""),1==i.length)l=i[i.length-1]+'"';else{for(let e=0;e<i.length-1;e++)l=l+i[e]+" ";l=l+i[i.length-1]+'"'}return[a,l]}function ir(){const e=45*le;qe.textFont("Tahoma"),qe.stroke(st),qe.strokeWeight(2*le),qe.fill(ct),qe.rect(width/2,e/2+height-87.5*le,600*le,90*le),qe.fill(st),qe.rect(width/2-150*le,e+height-170*le,300*le,30*le),qe.fill(ct),qe.rect(width/2+150*le,e+height-170*le,3M 00*le,30*le),qe.noStroke(),qe.fill(ct),qe.textSize(15*le),qe.textStyle(BOLD),qe.text("PERCEPTRON INFORMATION",width/2-285*le,e+height-165*le),qe.fill(xt),qe.text("ARTWORK NAME:",width/2+10*le,e+height-165*le),qe.textAlign(RIGHT),qe.textStyle(ITALIC),qe.text("Perceptron #"+Et,width/2+285*le,e+height-165*le);const[t,n]=It.split(" ");let r;"60 Years"===It?r="1 Year":"60 Months"===It?r="1 Month":"60 Weeks"===It?r="1 Week":"60 Days"===It?r="1 Day":"12 Hours"===It&&(r="12 Minutes"),data=[["AI MODEL NAME:",B(12*le,Ht,140*M le)],["SCALE:","1:"+Te],["NUMBER OF CLASSES:",$t.length],["BIRTH YEAR:",Rt],["NUMBER OF REBIRTHS:",sn.toString()],["AGE:",`${Math.ceil(Mt)} Perceptron Years`],["ONE PERCEPTRON YEAR:",`${r}`],["STATE:",Ot[Pe]],["ACTIVE NEURONS:",`${round(ln*rn)} / ${ln}`],["NEXT STATE TIME:",vr(new Date(on))]],qe.fill(xt);const i=data.length/2;for(let t=0;t<data.length;++t){const n=t<i,r=n?width/2-285*le:width/2+10*le,o=n?width/2-10*le:width/2+285*le,a=e+height-(135-t%i*15)*le;qe.textStyle(BOLD),qe.textAlign(LEFT),qe.textSize(12*le)M ,qe.text(data[t][0],r,a),qe.textStyle(ITALIC),qe.textAlign(RIGHT),qe.textSize(12*le),qe.text(data[t][1],o,a)}}function or(){Ke.textFont("Trebuchet MS"),Ke.noStroke(),pr(Ke,600*le,200*le),gr(Ke,width/2-155*le,width/2-5*le,height/2+115*le,height/2+155*le,"UPDATE"),gr(Ke,width/2+5*le,width/2+155*le,height/2+115*le,height/2+155*le,"CLOSE"),Ke.textAlign(LEFT),Ke.fill(xt),Ke.text("UPDATE BITCOIN FULL NODE ADDRESS",width/2-252.5*le,height/2-55*le),Ke.text("UPDATE MODEL ADDRESS",width/2-252.5*le,height/2+20*le),Ke.textAligM n(RIGHT),Ke.textStyle(ITALIC),Ke.textSize(15*le),0==wn&&Ke.text("(*) Invalid Address",width/2+252.5*le,height/2-53*le),0==vn&&Ke.text("(*) Invalid Model",width/2+252.5*le,height/2+23*le)}function ar(){je.textFont("Trebuchet MS"),je.fill(st),je.textSize(50*le),je.stroke(st),je.strokeWeight(1*le),je.text("main()",width/2,height/2)}function lr(){un>=20&&1==dn&&(dn=!1,un=0),dn&&(Ze.textFont("Trebuchet MS"),Ze.stroke(st),Ze.fill(ct),Ze.rect(width/2,height/2,600*le,150*le,25*le),Ze.fill(xt),Ze.textSize(75*le),Ze.noStrokeM (),1==Pe?Ze.text("GROWING",width/2,height/2+5*le):3==Pe?Ze.text("AGING",width/2,height/2+5*le):4==Pe?Ze.text("DEAD",width/2,height/2+5*le):5==Pe&&Ze.text("BIRTH",width/2,height/2+5*le)),un>=20&&0==dn&&(dn=!0,un=0,Bt++,3==Bt&&(fn=!1))}function sr(e,t,n,r){let i=[],o=r/(n.length+1),a=color(e),l=color(t);i.push(a);for(let e=0;e<n.length;e++){let t=color(n[e]);for(let e=1;e<=o;e++){let n=lerpColor(a,t,e/o);i.push(n)}a=t}for(let e=1;e<o;e++){let t=lerpColor(a,l,e/o);i.push(t)}if(i.push(l),i.length>r)i.splice(r);else if(M i.length<r){let e=i[i.length-1];for(;i.length<r;)i.push(e)}return i}function hr(e,t){let n=e.length,r=Math.floor(t*n);return r>=n&&(r=n-1),e[r]}function cr(e){e=e.replace("#","");var t=parseInt(e,16);return color(t>>16&255,t>>8&255,255&t)}function ur(e,t,n,r,i,o,a,l){var s=a.drawingContext.createLinearGradient(e,t,n,r);s.addColorStop(0,i),s.addColorStop(1,o),a.drawingContext.strokeStyle=s,a.drawingContext.globalAlpha=l,a.line(e,t,n,r),a.drawingContext.globalAlpha=1}function fr(e,t){t.drawingContext.setLineDash(e)}fM unction dr(e,t){let n=color(e),r=red(n),i=green(n),o=blue(n);return color(r,i,o,255*t)}function xr(e,t,n,r){return mouseX>e&&mouseX<t&&mouseY>n&&mouseY<r}function gr(e,t,n,r,i,o){e.strokeWeight(1*le),e.stroke(st);const[a,l]=xr(t,n,r,i)?[xt,ct]:[ct,xt];e.fill(a),e.push(),e.rectMode(CORNERS),e.rect(t,r,n,i,5*le),e.pop(),e.noStroke(),e.textSize(20*le),e.fill(l),e.text(o,(t+n)/2,(46*r+54*i)/100)}function pr(e,t,n){e.fill(0,0,0,75),e.rect(width/2,height/2,width,height),e.stroke(st),e.fill(ct),e.rect(width/2,height/2,t,nM ,25*le)}function mr(e,t){resizeCanvas(e,t,!0),Xe.resizeCanvas(e,t,!0),$e.resizeCanvas(e,t,!0),We.resizeCanvas(e,t,!0),Ue.resizeCanvas(e,t,!0),qe.resizeCanvas(e,t,!0),Qe.resizeCanvas(e,t,!0),je.resizeCanvas(e,t,!0),Ze.resizeCanvas(e,t,!0),Ke.resizeCanvas(e,t,!0),Je.resizeCanvas(e,t,!0),et.resizeCanvas(e,t,!0)}function br(e,t,n,r,i,o){const a=J(e);return a.position(t,n),a.size(r,i),a.style("opacity","0"),a.mouseClicked(o),a}function yr(){return null!=vt&&vt?.isFocused()||null!=zt&&zt?.isFocused()}function wr(e,t,n,r)M {let i;if(e<=3){i=`Hey ${String.fromCodePoint(128075)}, I'm ${n}, ${t} years old. I can detect ${r.length} NFT collections: `;let e=0;for(let t=0;t<r.length;++t){const n=r[t];if(e+n.length>500){i+=", etc";break}t==r.length-1?i+=", and ":t>0&&(i+=", "),i+=n,e+=n.length}i+=". ",t<=5?i+="However, I am only a baby, so my recognition ability is not accurate. I'm in the state of Growing both looks and intelligence.":t<=13?i+="I am now a child. My recognition ability is becoming better, but still not very accurate. I'm inM the state of Growing both looks and intelligence.":t<=25?i+="I have grown up to be a teen. My recognition ability almost reaches the peak, but I will still mess up sometimes. I'm in the state of Growing both looks and intelligence.":t<=50?i+="I finally reach adulthood. My recognition is fully functional now. I'm in the Stable state, where I am the most intelligent with all neurons activated.":t<=60&&(i+="I am now an old Perceptron, so my recognition ability is no longer the best. I'm in the Decaying state, meaningM that my neurons are dying, and my intelligence is decreasing over time.")}else 4==e?i=`${n} is Dead. However, this is not the end to its story...`:5==e&&(i=`${n} is now in the Rebirth state, and is preparing to start a new life.`);return i}function vr(e){const t=e.getDate(),n=e.toLocaleString("en-US",{month:"long"}),r=e.getFullYear();let i=e.getHours().toString();1==i.length&&(i="0"+i);let o=e.getMinutes().toString();return 1==o.length&&(o="0"+o),`${Y(t)} ${n} ${r} | ${i}:${o}`}saveCanvasAtCurrentTime=()=>{save(N(M ))},save4KCanvasAtCurrentTime=()=>{const e=width,t=height,n=min(4096/min(e,t),1e4/max(e,t)),r=e*n,i=t*n;mr(r,i),zn=!0,$n(r,i),qn();let o="4K_"+N()+".png";saveCanvas(et,o),mr(e,t),$n(e,t),zn=!1};const zr=[["60 Years",3,365],["60 Months",40,30],["60 Weeks",37,7],["60 Days",20,1]],Vr=[["1943",1],["1951",1.5],["1957",2],["1969",2.5],["1970",3],["1980",3.5],["1982",4],["1986",4.5],["1988",5],["1997",5.5],["1998",6],["2002",6.5],["2009",7],["2012",7.5],["2014",8],["2015",8.5],["2016",9],["2023",15]],_r=[["Plain",20],["DoM tted",40],["Squared",40]],Mr=[["Basic",30],["Standard",60],["Advanced",10]],Er=[["MNIST",70],["CIFAR",25],["IMAGENET",5]],Sr=[["Theano",60],["Torch",30],["TensorFlow",10]],Rr=[["Whitepaper",2],["Blackboard",2],["Blueprint",2],["Nak",74/14],["Jims",74/14],["Level 10",74/14],["Flips",74/14],["Level 14",74/14],["III",74/14],["XMB",74/14],["Info",74/14],["Adventure",74/14],["Marigold",74/14],["Phoenix",74/14],["Love",74/14],["Cachet",74/14],["Human",74/14],["Twilight",3],["Sunset",3],["Aurora",3],["Liminal Space",3],["M Vu",3],["Lucid Dream",3],["Parallel",1],["Multiverse",1]];function Ir(e){for(let e=0;e<100;++e)random(1);return{visual:{pattern:k(_r),hardwareAcceleration:k(Mr),nodeFill:k(Er),nodeShape:k(Sr),colorPalette:k(Rr),lifeCycle:k(zr),birthYear:k(Vr)},training:e}}function Cr(e){window.$generativeTraits={"Network Architecture":e.training.structure_gen,"Hidden Layers":e.training.n_layers,"Max Neurons Per Hidden Layer":e.training.max_nodes,"Activation Function":e.training.activation_func,"Training Epochs":e.training.epM och_num,Dataset:e.visual.nodeFill,"Deep Learning Framework":e.visual.nodeShape,"Hardware Acceleration":e.visual.hardwareAcceleration,"Paper Pattern":e.visual.pattern,"Life Cycle":e.visual.lifeCycle,"Birth Year":e.visual.birthYear,"Color Palette":e.visual.colorPalette}} <script defer src="https://static.cloudflareinsights.com/beacon.min.js/v2b4487d741ca48dcbadcaf954e159fc61680799950996" integrity="sha512-D/jdE0CypeVxFadTejKGTzmwyV10c1pxZk/AqjJuZbaJwGMyNHY3q/mTPWqMUnFACfCTunhZUVcd4cV78dK1pQ==" data-cfL -beacon='{"rayId":"7b4c1ea038b8a205","version":"2023.3.0","b":1,"token":"6c07c178c94442f695e7a0a2aaee641a","si":100}' crossorigin="anonymous"></script> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":" text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 &{"p":"sns","op":"reg","name":"8.sats"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":" text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 1{"p":"sns","op":"reg","name":"jamesedition.sats"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! <svg xmlns='http://www.w3.org/2000/svg' xmlns:xlink='http://www.w3.org/1999/xlink' image-rendering='pixelated' viewBox='0 0 800 800'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoCAMAAAC7IEhfAAAARVBMVEXinc3flMjhmMrkoc/y0OnlptLz1OruxOLruNzpsdjmqtTdjMPsvN7nrdbtwODbhsHxy+bwyOTej8bqtNrxzefZgr7ZgL0cO9EEAAABH0lEQVQ4y8TPSQ7CMBBE0Q4zCRCIY9//qNRgt8QJqA0Inn7L0Vqt67ouy7JtE3bo4/dtw8/4s9bWwo5MKnKwpM pYxXFfHXLdDRgWzozpjM8ZPWknSGuA4ixyY0FMjBkWU54FCd5kDI7r3EYMi6uuRDjWoUm5aKbCopox0ZFQPjZY0ZegddoXq1UdbJPUiwnRi1z7SlIQ/juyjkf7IAeGQI3troIhSDjhNDrJntmOiaipJpaAO2+0nbbfUcSYFHeRd1IA0VHndSUJfdtC9C+amk74d4ykO2lk6OZ4jiMsOyqVE0rcHnAfc7TwlDef/w29jdUAAAACCAOj/ay4woVKqYXo9u/A+4YeiY9bB7Spsub6uDcCS8kg1ew1p09zY9/sAJFQ4OREZSsoAAAAASUVORK5CYII='/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAM AAAoBAMAAAB+0KVeAAAAIVBMVEUAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABt0UjBAAAAC3RSTlMAYEJYVDQnGBNOTJeVFx8AAAAzSURBVCjPYxgFo2BIAvZULRdDYZdFYQUIsSZBONCACxoiBIVxqESYqeksKGgyCWgmiQAAX5gI535S03cAAAAASUVORK5CYII='/></foreignObject><g class='effect2'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAMFBMVEUAAADbzKgANQb18/YGihUOlg8aqxv3r1ktxC7+rVjwsnACmwH6+/3s+Oz6qkscsBb8aFQ8AAAAM AXRSTlMAQObYZgAAAMZJREFUKM9joD9QQBdgUlBSMlJiUEIRVDZy8RR2UTJGUa0ubDpT2NT5OqpguVjkxIyQuiRkI1PK810i0lpDkpGUqqW1hhqntWWkGiIEmZQtEgVBwFgQIahsbJbGABYVQDJS8GgyA4bTy0OdYWoQ2sOTMQSZzMMMMVUqmZZj0S4abrgBXbuhqIs0hu3qpZi6GVRKnTHDXDnEENPthiGYuhXFsQgylQMFMW13wSKo4oxFu7CxIBZBQylM7YpSkzAFmZQUGAY7AACPDiGgkx0AYAAAAABJRU5ErkJggg=='/></foreignObject></g><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAABM +0KVeAAAAG1BMVEUAAAAnDQislnWTg2q9qIhZVlLLtaE7NzLezLzZuBaIAAAAAXRSTlMAQObYZgAAAHtJREFUKM9jGAWDEYhiEWMsDcAiGGyOKShurKReXi6AZqSRSpqTKqogY7GSi1uasiCqYJGyiluGk6gAqqCwiktak6giFkFBVMFikKCSgCCKoGAwUFAZ3UnGRm5JphiCQBCIHh6mgYLBAujeDBdgLEUXFBQUYBQECtIZAADsZxPbfZk9RAAAAABJRU5ErkJggg=='/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAD1BMVEUAAACZ5VA3lG5qvjAnDQgb2TL3AAM AAAXRSTlMAQObYZgAAAClJREFUKM9jGAWjgB5AWVDQ0QhNjAkoKIIhaChs5KyALiiswKDIMIgBAN5GAncQdEsNAAAAAElFTkSuQmCC'/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAFVBMVEUAAAD92gD/8AY0Ly78qwAnDQjy2BZpdjU7AAAAAXRSTlMAQObYZgAAAFFJREFUKM9jGAWDEYRgEWN1ccAiKOiipGSAJhgopOjs7BKALihobKyCKsjqKCRoqGQSii6YCFQZGIAi6KQEUhkigCoYhDATARgVhYVFGEYWAAAMRAsG3NsXsgAAAABJRU5ErkJggg=='/></M foreignObject><g class='effect'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAJ1BMVEUAAAAnDQich2aslnW9qIiTg2o7NzLezLxZVlIAAADsmJnNd3jDXV6RqQwDAAAAAXRSTlMAQObYZgAAAFNJREFUKM9jGAWMgggKIbhaEASkF6IolelQcS931hFA1Z9kbOJipIYuaBrsYhqGKeiOKaga7FKkiOamDGVjo5mNaC4VbFLSnAnTjRAFAoZRMLAAAEOoDnwejNL6AAAAAElFTkSuQmCC'/></foreignObject></g><g class='effect'><foreignObject x='0' y='0' wiM dth='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAG1BMVEUAAABIFgZrJxJ8NSHZhW6rY0/L2/yDPionDQgZZCTBAAAAAXRSTlMAQObYZgAAAEhJREFUKM9jwA/Y2LCJNuBQnZCARZADU0gBizJGJyyCQqoKmApVQoIwFSoZG2EoVHZ1cUXXL6hkbFxeiK5SEAgEGEbBKCAXAABfPQZbyiJedQAAAABJRU5ErkJggg=='/></foreignObject></g><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/pM ng;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoAgMAAADxkFD+AAAACVBMVEUAAAAAAADT09O5Y3cbAAAAAXRSTlMAQObYZgAAABhJREFUGNNjGAUDBCIdU2HMMMdIBxJ1AwB5TAIwT//nMwAAAABJRU5ErkJggg=='/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoAQMAAAC2MCouAAAAA1BMVEUAAACnej3aAAAAAXRSTlMAQObYZgAAAAtJREFUCNdjGGEAAADwAAFOldjfAAAAAElFTkSuQmCC'/></foreignObject><g class='effect2'><foreignObject x='0' y=M '0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAJFBMVEUAAAD39/fi8N/M2ckCrvUAmvD7aVzrPTLx9fTt9Ozp7ez0UUBMLYYDAAAAAXRSTlMAQObYZgAAADFJREFUKM9jGAUUA2NjJSVBQUEUMWYGUxcnwbJENKWmIU6M1eiCxkpaHIKSDKNgCAMAKvoE3fxR7N0AAAAASUVORK5CYII='/></foreignObject></g><style> .effect { animation: 0.75s effect infinite alternate ease-in-out; } @keyframes effect { from { transform: translateY(0px); } to { transform: tL ranslateY(2.5%); } }.effect2 { animation: 0.75s effect2 infinite alternate ease-in-out; } @keyframes effect2 { from { transform: translateY(0px); } to { transform: translateY(1.5%); } } </style> </svg>h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! riTXtXML:com.adobe.xmp ' id='W5M0MpCehiHzreSzNTczkc9d'?> <x:xmpmeta xmlns:x='adobe:ns:meta/'> <rdf:RDF xmlns:rdf='http://www.w3.org/1999/02/22-rdf-syntax-ns#'> <rdf:Description rdf:about='' xmlns:Attrib='http://ns.attribution.com/ads/1.0/'> <rdf:li rdf:parseType='Resource'> <Attrib:Created>2023-04-08</Attrib:Created> <Attrib:ExtId>cb2b9f3e-a624-4cf8-977M 8-70f82ebc8300</Attrib:ExtId> <Attrib:FbId>525265914179580</Attrib:FbId> <Attrib:TouchType>2</Attrib:TouchType> <rdf:Description rdf:about='' xmlns:dc='http://purl.org/dc/elements/1.1/'> <rdf:li xml:lang='x-default'>Jesus - 13</rdf:li> <rdf:Description rdf:about='' xmlns:pdf='http://ns.adobe.com/pdf/1.3/'> <pdf:Author>Lion's Logistics</pdf:Author> <rdf:Description rdf:about='' xmlns:xmp='http://ns.adobe.com/xap/1.0/'> <xmp:CreatorTool>Canva</xmp:CreatorTool> <?xpacket end='r'?>L text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":" text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"nako","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":" text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/html;charset=utf-8 <meta charset="UTF-8"> <title>Ordinals Sprout</title> <script sandbox="allow-scripts" type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/p5.js/1.5.0/p5.min.js"></script> <script id="snippet-random-code" type="text/javascript"> // DO NOT EDIT THIS SECTION let seed = window.location.href.split('/').find(t => t.includes('i0')); if (seed == null) { const alphabet = "0123456789abcdeM fghijklmnopqrstuvwsyz"; seed = new URLSearchParams(window.location.search).get("seed") || Array(64).fill(0).map(_ => alphabet[(Math.random() * alphabet.length) | 0]).join('') + "i0"; let pattern = "seed="; for (let i = 0; i < seed.length - pattern.length; ++i) { if (seed.substring(i, i + pattern.length) == pattern) { seed = seed.substring(i + pattern.length); break; function cyrb128($) { let _ = 1779033703, u = 3144134277, i = 1013904242, l = 2773480762; for (let n = 0, r; n < $.length; n++) _ = u ^ Math.imul(_ ^ (r = $.charCodeAt(n)), 597399067), u = i ^ Math.imul(u ^ r, 2869860233), i = l ^ Math.imul(i ^ r, 951274213), l = _ ^ Math.imul(l ^ r, 2716044179); return _ = Math.imul(i ^ _ >>> 18, 597399067), u = Math.imul(l ^ u >>> 22, 2869860233), i = Math.imul(_ ^ i >>> 17, 951274213), l = Math.imul(u ^ l >>> 19, 271604M 4179), [(_ ^ u ^ i ^ l) >>> 0, (u ^ _) >>> 0, (i ^ _) >>> 0, (l ^ _) >>> 0] function sfc32($, _, u, i) { return function () { u >>>= 0, i >>>= 0; var l = ($ >>>= 0) + (_ >>>= 0) | 0; return $ = _ ^ _ >>> 9, _ = u + (u << 3) | 0, u = (u = u << 21 | u >>> 11) + (l = l + (i = i + 1 | 0) | 0) | 0, (l >>> 0) / 4294967296 let mathRand = sfc32(...cyrb128(seed)); display: flex; position: fixed; right: 0; bottom: 0; color: #fff; background-color: #000; justify-content: center; align-items: center; margin: 0; padding: 0; font-size: .8em #fullScreen canvas, object-fit: contain; max-height: 100%; max-width: 100% #fullScreen { justify-content: center; align-items: center <script type="text/javascript"> const rand = mathRand(); //////////////// FEATURES let myTitle = "ORDINALS SPROUT"; console.log(myTitle + " | SMLDMS 2023.02") let globalSize = 1000; let myString = "ORDINALS" let textAlpha = 160; let strokeAlpha = 127; let strokeColor = 0; let strokeSize = 1; let fontSize; let fontSampleFactor = mathRandBetween(0.15, 0.33); //How many points there are: the higher the number, the closer together they are (more detail) let simplifyFactor = 0.0; // 0 is normal let noiseZoom = mathRandBetween(0.033, 0.01) //how zoomed in the perlin noise is (0.05 to 0.01) let noiseOctaves = mathRandBetween(1, M 50); //The number of octaves for the noise let noiseFalloff = mathRandBetween(0.4, 0.6); //The falloff for the noise layers let zOffsetChange = 0.1; //How much the noise field changes in the z direction each frame let individualZOffset = 0.01; //how far away the points/lines are from each other in the z noise axies (the bigger the number, the more chaotic) let speedFactor = mathRandBetween(10, 100); let lineSpeed = speedFactor; //the maximum amount each point can move M let points = []; let startingPoints; let maxFrame = 100; function preload() { font = loadFont("https://gateway.pinata.cloud/ipfs/QmYhhjHt9J8N1CXQnHdNRAt7c1BmzyUsdw8s1stfeDJrP5"); function setup() { randomSeed(seed); noiseSeed(seed); cnv = createCanvas(globalSize * 1.77, globalSize); cnv.parent('fullScreen'); rectMode(CENTER) angleMode(DEGREES) pixelDensity(2) fontSize = width * 0.1618 textFont(font); textSize(fontSize); textAlign(CENTER, BASELINE) noFill() stroke(strokeColor); strokeWeight(strokeSize) background(0) for (let i = 0; i < 25; i++) { push() fill(255) noStroke() rect(mathRand() * width, mathRand() * height, mathRandBetweenM pop() fill(255) noStroke() rect(width / 2, height / 2, width, height * 0.45) for (let i = 0; i < 50; i++) { push() fill(0) noStroke() rect(mathRand() * width, mathRand() * height, mathRandBetween(5, 150)) pop() grainy(15) noiseDetail(noiseOctaves, noiseFalloffM translate(0, 50) makeTxt(myString, width / 2, height * 0.55); grainy(5) function makeTxt(string, x, y) { startingPoints = font.textToPoints(string, x - textWidth(string) / 2, y, fontSize, { sampleFactor: fontSampleFactor, simplifyThreshold: simplifyFactor for (let p = 0; p < startingPoints.length; p++) { points[p] = startingPoints[p]; pointsM [p].zOffset = random(); if (showText) { stroke(strokeColor, strokeAlpha); fill(255, 255); text(myString, x, y); for (let i = 0; i <= maxFrame; i++) { for (let pt = 0; pt < points.length; pt++) { let p = points[pt]; let noiseX = p.x * noiseZoom; let noiseY = p.y * noiseZoom; let noiseZ = frameCount * zOffsetM Change + p.zOffset * individualZOffset; lineSpeed = map(pt, 0, startingPoints.length, -speedFactor, speedFactor) let newPX = p.x + map(noise(noiseX, noiseY, noiseZ), 0, 1, -lineSpeed, lineSpeed); let newPY = p.y + map(noise(noiseX, noiseY, noiseZ + 23), 0, 1, -lineSpeed, lineSpeed); if (i < maxFrame) { rect(p.x, p.y, globalSize / 125) } else { } p.x = newPX; p.y = newPY; function grainy(force) { _seed = floor(mathRand() * 999999) randomSeed(_seed) noiseSeed(_seed) loadPixels(); let d = pixelDensity(); let halfImage = 4 * (width * d) * (height * d); for (let i = 0; i < halfImage; i += 4) { grainAmount = random(-force, force); pixels[i] = M pixels[i] + grainAmount; pixels[i + 1] = pixels[i + 1] + grainAmount; pixels[i + 2] = pixels[i + 2] + grainAmount; pixels[i + 3] = pixels[i + 3] + grainAmount updatePixels(); function keyTyped() { if (keyCode === 83) { // if "s" is pressed save(myTitle + '.png'); function mathRandBetween(a, b) { if (!b) { return mathRandM return mathRand() * (b - a) + a <div id="fullScreen"> </div> <script defer src="https://static.cloudflareinsights.com/beacon.min.js/v2b4487d741ca48dcbadcaf954e159fc61680799950996" integrity="sha512-D/jdE0CypeVxFadTejKGTzmwyV10c1pxZk/AqjJuZbaJwGMyNHY3q/mTPWqMUnFACfCTunhZUVcd4cV78dK1pQ==" data-cf-beacon='{"rayId":"7b4cec30febb3fde","version":"2023.3.0","b":1,"token":"6c07c178c94442f695e7a0a2aaee641a","si":100}' crossorigin="anonymous"></script> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"nako","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/html;charset=utf-8 <meta charset="utf-8" /> position: relative; width: var(--width); height: var(--height); border: 1px solid blue; position: relative; <div id="upload"> <input id="inputUpload" type="file"> function e(e){"use strict";return new function e(t){let n="global"==t?window:this;n.canvas=document.createElement("canvas");let r=n.canvas.getContext("2d");n.width=100,n.height=100,n.canvas.width=n.width,n.canvas.height=n.height,"offscreen"!=t&&(document.body?document.body.appendChild(n.canvas):window.addEventListener("load",(function(){document.body.appendChild(n.canvas)}))),g(),n.MAGIC=161533525,n.RGB=0,n.HSV=1,n.HM SB=1,n.CHORD=0,n.PIE=1,n.OPEN=2,n.RADIUS=1,n.CORNER=2,n.CORNERS=3,n.ROUND="round",n.SQUARE="butt",n.PROJECT="square",n.MITER="miter",n.BEVEL="bevel",n.CLOSE=1,n.BLEND="source-over",n.REMOVE="destination-out",n.ADD="lighter",n.DARKEST="darken",n.LIGHTEST="lighten",n.DIFFERENCE="difference",n.SUBTRACT="subtract",n.EXCLUSION="exclusion",n.MULTIPLY="multiply",n.SCREEN="screen",n.REPLACE="copy",n.OVERLAY="overlay",n.HARD_LIGHT="hard-light",n.SOFT_LIGHT="soft-light",n.DODGE="color-dodge",n.BURN="color-burn",n.NORMAL="norM mal",n.ITALIC="italic",n.BOLD="bold",n.BOLDITALIC="italic bold",n.CENTER="center",n.LEFT="left",n.RIGHT="right",n.TOP="top",n.BOTTOM="bottom",n.BASELINE="alphabetic",n.LANDSCAPE="landscape",n.PORTRAIT="portrait",n.ALT=18,n.BACKSPACE=8,n.CONTROL=17,n.DELETE=46,n.DOWN_ARROW=40,n.ENTER=13,n.ESCAPE=27,n.LEFT_ARROW=37,n.OPTION=18,n.RETURN=13,n.RIGHT_ARROW=39,n.SHIFT=16,n.TAB=9,n.UP_ARROW=38,n.HALF_PI=Math.PI/2,n.PI=Math.PI,n.QUARTER_PI=Math.PI/4,n.TAU=2*Math.PI,n.TWO_PI=2*Math.PI,n.THRESHOLD=1,n.GRAY=2,n.OPAQUE=3,n.INVEM RT=4,n.POSTERIZE=5,n.DILATE=6,n.ERODE=7,n.BLUR=8,n.ARROW="default",n.CROSS="crosshair",n.HAND="pointer",n.MOVE="move",n.TEXT="text",n.VIDEO={video:!0,audio:!1},n.AUDIO={video:!1,audio:!0},n.SHR3=1,n.LCG=2,n.HARDWARE_FILTERS=!0,n.hint=function(e,t){n[e]=t},n.frameCount=0,n.mouseX=0,n.mouseY=0,n.pmouseX=0,n.pmouseY=0,n.mouseButton=null,n.keyIsPressed=!1,n.mouseIsPressed=!1,n.key=null,n.keyCode=null,n.pixels=null,n.accelerationX=0,n.accelerationY=0,n.accelerationZ=0,n.rotationX=0,n.rotationY=0,n.rotationZ=0,n.relRotatM ionX=0,n.relRotationY=0,n.relRotationZ=0,n.pAccelerationX=0,n.pAccelerationY=0,n.pAccelerationZ=0,n.pRotationX=0,n.pRotationY=0,n.pRotationZ=0,n.pRelRotationX=0,n.pRelRotationY=0,n.pRelRotationZ=0,n.touches=[],n._styleCache=[{colorMode:n.RGB,noStroke:!1,noFill:!1,ellipseMode:n.CENTER,rectMode:n.CORNER,curveDetail:20,curveAlpha:0,textFont:"sans-serif",textSize:12,textLeading:12,textStyle:"normal"}],n._style=n._styleCache[n._styleCache.length-1],n._noLoop=!1,n._pixelDensity=1,n._frameRate=null,n._tint=null;let i=nullM ,o=!0,a=[],l=null,s=0,h={},c=0,u=null,f=null,d=null;Object.defineProperty(n,"deviceOrientation",{get:function(){return 90==Math.abs(window.orientation)?n.LANDSCAPE:n.PORTRAIT}}),Object.defineProperty(n,"windowWidth",{get:function(){return window.innerWidth}}),Object.defineProperty(n,"windowHeight",{get:function(){return window.innerHeight}}),Object.defineProperty(n,"drawingContext",{get:function(){return r}}),n.createCanvas=function(e,t){return n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t,g(),n.canvas},nM .resizeCanvas=function(e,t){n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t},n.createGraphics=n.createImage=function(t,n){let r=new e("offscreen");return r.createCanvas(t,n),r.noLoop(),r},n.pixelDensity=function(e){return null==e||(n._pixelDensity=e,n.canvas.width=Math.ceil(n.width*e),n.canvas.height=Math.ceil(n.height*e),n.canvas.style.width=n.width+"px",n.canvas.style.height=n.height+"px",r.scale(n._pixelDensity,n._pixelDensity),g()),n._pixelDensity},n.map=function(e,t,n,r,i,o){let a=r+1*(e-t)/(n-t)*(i-r)M ;return o?r<i?Math.min(Math.max(a,r),i):Math.min(Math.max(a,i),r):a},n.lerp=function(e,t,n){return e*(1-n)+t*n},n.constrain=function(e,t,n){return Math.min(Math.max(e,t),n)},n.dist=function(){return 4==arguments.length?Math.hypot(arguments[0]-arguments[2],arguments[1]-arguments[3]):Math.hypot(arguments[0]-arguments[3],arguments[1]-arguments[4],arguments[2]-arguments[5])},n.norm=function(e,t,r){return n.map(e,t,r,0,1)},n.sq=function(e){return e*e},n.fract=function(e){return e-Math.floor(e)},n.degrees=function(e){retM urn 180*e/Math.PI},n.radians=function(e){return e*Math.PI/180},n.abs=Math.abs,n.ceil=Math.ceil,n.exp=Math.exp,n.floor=Math.floor,n.log=Math.log,n.mag=Math.hypot,n.max=Math.max,n.min=Math.min,n.round=Math.round,n.sqrt=Math.sqrt,n.sin=Math.sin,n.cos=Math.cos,n.tan=Math.tan,n.asin=Math.asin,n.acos=Math.acos,n.atan=Math.atan,n.atan2=Math.atan2,n.Vector=function(e,t,r){let i=this;i.x=e||0,i.y=t||0,i.z=r||0;let o=null,a=null;function l(e,t,n){return null!=e.x?e:null!=t?{x:e,y:t,z:n||0}:{x:e,y:e,z:e}}function s(){null==a&M &(a=i.x*i.x+i.y*i.y+i.z*i.z,o=Math.sqrt(a))}function h(){a=null,o=null}i.set=function(e,t,n){i.x=e||0,i.y=t||0,i.z=n||0},i.copy=function(){return new n.Vector(i.x,i.y,i.z)},i.add=function(){let e=l.apply(null,arguments);return i.x+=e.x,i.y+=e.y,i.z+=e.z,h(),i},i.rem=function(){let e=l.apply(null,arguments);return i.x%=e.x,i.y%=e.y,i.z%=e.z,h(),i},i.sub=function(){let e=l.apply(null,arguments);return i.x-=e.x,i.y-=e.y,i.z-=e.z,h(),i},i.mult=function(){let e=l.apply(null,arguments);return i.x*=e.x,i.y*=e.y,i.z*=e.z,hM (),i},i.div=function(){let e=l.apply(null,arguments);return i.x/=e.x,i.y/=e.y,i.z/=e.z,h(),i},i.mag=function(){return s(),o},i.magSq=function(){return s(),a},i.dot=function(){let e=l.apply(null,arguments);return i.x*e.x+i.y*e.y+i.z*e.z},i.dist=function(){let e=l.apply(null,arguments),t=i.x-e.x,n=i.y-e.y,r=i.z-e.z;return Math.sqrt(t*t+n*n+r*r)},i.cross=function(){let e=l.apply(null,arguments),t=i.y*e.z-i.z*e.y,n=i.z*e.x-i.x*e.z,r=i.x*e.y-i.y*e.x;return i.x=t,i.y=n,i.z=r,h(),i},i.normalize=function(){s();let e=o;retuM rn i.x/=e,i.y/=e,i.z/=e,o=1,a=1,i},i.limit=function(e){s();if(o>e){let t=e/o;i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e}return i},i.setMag=function(e){s();let t=e/o;return i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e,i},i.heading=function(){return Math.atan2(i.y,i.x)},i.rotate=function(e){let t=Math.cos(e),n=Math.sin(e),r=i.x*t-i.y*n,o=i.x*n+i.y*t;return i.x=r,i.y=o,i},i.angleBetween=function(){let e=l.apply(null,arguments);const t=i.dot(e)/(i.mag()*e.mag());let n;return n=Math.acos(Math.min(1,Math.max(-1,t))),n*Math.sign(i.cross(e).z||1)},M i.lerp=function(e,t){return i.x=i.x*(1-t)+e.x*t,i.y=i.y*(1-t)+e.y*t,i.z=i.z*(1-t)+e.z*t,h(),i},i.reflect=function(e){return e.normalize(),i.sub(e.mult(2*i.dot(e)))},i.array=function(){return[i.x,i.y,i.z]},i.equals=function(e,t){return null==t&&null==(t=Number.EPSILON)&&(t=0),Math.abs(e.x-i.x)<t&&Math.abs(e.y-i.y)<t&&Math.abs(e.z-i.z)<t},i.fromAngle=function(e,t){return null==t&&(t=1),o=t,a=t*t,i.x=t*Math.cos(e),i.y=t*Math.sin(e),i.z=0,i},i.fromAngles=function(e,t,n){null==n&&(n=1),o=n,a=n*n;const r=Math.cos(t),l=MaM th.sin(t),s=Math.cos(e),h=Math.sin(e);return i.x=n*h*l,i.y=-n*s,i.z=n*h*r,i},i.random2D=function(){return o=1,a=1,i.fromAngle(Math.random()*Math.PI*2)},i.random3D=function(){return o=1,a=1,i.fromAngles(Math.random()*Math.PI*2,Math.random()*Math.PI*2)},i.toString=function(){return`[${i.x}, ${i.y}, ${i.z}]`}},n.Vector.add=function(e,t){return new n.Vector(e.x+t.x,e.y+t.y,e.z+t.z)},n.Vector.rem=function(e,t){return new n.Vector(e.x%t.x,e.y%t.y,e.z%t.z)},n.Vector.sub=function(e,t){return new n.Vector(e.x-t.x,e.y-t.y,e.M z-t.z)},n.Vector.mult=function(e,t){return null==t.x?new n.Vector(e.x*t,e.y*t,e.z*t):new n.Vector(e.x*t.x,e.y*t.y,e.z*t.z)},n.Vector.div=function(e,t){return null==t.x?new n.Vector(e.x/t,e.y/t,e.z/t):new n.Vector(e.x/t.x,e.y/t.y,e.z/t.z)},n.Vector.dist=function(e,t){return Math.hypot(e.x-t.x,e.y-t.y,e.z-t.z)},n.Vector.cross=function(e,t){return new n.Vector(e.y*t.z-e.z*t.y,e.z*t.x-e.x*t.z,e.x*t.y-e.y*t.x)},n.Vector.lerp=function(e,t,r){return new n.Vector(e.x*(1-r)+t.x*r,e.y=e.y*(1-r)+t.y*r,e.z=e.z*(1-r)+t.z*r)},n.M Vector.equals=function(e,t,n){return e.equals(t,n)};for(let e of["fromAngle","fromAngles","random2D","random3D"])n.Vector[e]=function(t,r,i){return(new n.Vector)[e](t,r,i)};function x(e,t,n){let r,i,o,a,l,s,h,c,u;if(0==t)return[255*(r=n),255*(i=n),255*(o=n)];switch((a=e)>360&&(a=0),h=n*(1-t),c=n*(1-t*(s=(a/=60)-(l=~~a))),u=n*(1-t*(1-s)),l){case 0:r=n,i=u,o=h;break;case 1:r=c,i=n,o=h;break;case 2:r=h,i=n,o=u;break;case 3:r=h,i=c,o=n;break;case 4:r=u,i=h,o=n;break;default:r=n,i=h,o=c}return[255*r,255*i,255*o]}functioM n g(){r.fillStyle="white",r.strokeStyle="black",r.lineCap="round",r.lineJoin="miter"}function p(e){if(0<=e&&e<2*Math.PI)return e;for(;e<0;)e+=2*Math.PI;for(;e>=Math.PI;)e-=2*Math.PI;return e}function m(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;let c=p(a),u=p(l);r.beginPath();for(let a=0;a<h+1;a++){let l=a/h,s=n.lerp(c,u,l),f=Math.cos(s)*i/2,d=Math.sin(s)*o/2;r[a?"lineTo":"moveTo"](e+f,t+d)}s==n.CHORD?r.closePath():s==n.PIE&&(r.lineTo(e,t),r.closePath()),n._style.noFill||r.fill(),n._style.noStrokM e||r.stroke()}function b(e,t,i,o){n._style.noFill&&n._style.noStroke||(r.beginPath(),r.ellipse(e,t,i/2,o/2,0,0,2*Math.PI),n._style.noFill||r.fill(),n._style.noStroke||r.stroke())}function y(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;if(null==a)return function(e,t,i,o){n._style.noFill||r.fillRect(e,t,i,o),n._style.noStroke||r.strokeRect(e,t,i,o)}(e,t,i,o);if(null==l)return y(e,t,i,o,a,a,a,a);const c=Math.min(Math.abs(o),Math.abs(i))/2;a=Math.min(c,a),l=Math.min(c,l),h=Math.min(c,h),s=Math.min(c,s)M ,r.beginPath(),r.moveTo(e+a,t),r.arcTo(e+i,t,e+i,t+o,l),r.arcTo(e+i,t+o,e,t+o,s),r.arcTo(e,t+o,e,t,h),r.arcTo(e,t,e+i,t,a),r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke()}function w(){a=[]}n.createVector=function(e,t,r){return new n.Vector(e,t,r)},n.curvePoint=function(e,t,n,r,i){const o=i*i*i,a=i*i;return e*(-.5*o+a-.5*i)+t*(1.5*o-2.5*a+1)+n*(-1.5*o+2*a+.5*i)+r*(.5*o-.5*a)},n.bezierPoint=function(e,t,n,r,i){const o=1-i;return Math.pow(o,3)*e+3*Math.pow(o,2)*i*t+3*o*Math.pow(i,2)*n+Math.pow(i,M 3)*r},n.curveTangent=function(e,t,n,r,i){const o=i*i;return e*(-3*o/2+2*i-.5)+t*(9*o/2-5*i)+n*(-9*o/2+4*i+.5)+r*(3*o/2-i)},n.bezierTangent=function(e,t,n,r,i){const o=1-i;return 3*r*Math.pow(i,2)-3*n*Math.pow(i,2)+6*n*o*i-6*t*o*i+3*t*Math.pow(o,2)-3*e*Math.pow(o,2)},n.Color=function(e,t,n,r){let i=this;i.MAGIC=786698,i._r=e,i._g=t,i._b=n,i._a=r,i._h=0,i._s=0,i._v=0,i._hsvInferred=!1,i.setRed=function(e){i._r=e,i._hsvInferred=!1},i.setGreen=function(e){i._g=e,i._hsvInferred=!1},i.setBlue=function(e){i._b=e,i._hsvInfM erred=!1},i.setAlpha=function(e){i._a=e/255,i._hsvInferred=!1},i._inferHSV=function(){i._hsvInferred||([i._h,i._s,i._v]=function(e,t,n){let r,i,o,a,l;return r=e<t?e<n?e:n:t<n?t:n,0==(l=100*(i=e>t?e>n?e:n:t>n?t:n)/255)?[o=0,a=0,l]:0==(a=100*(i-r)/i)?[o=0,a,l]:(o=i==e?0+60*(t-n)/(i-r):i==t?120+60*(n-e)/(i-r):240+60*(e-t)/(i-r),[o,a,l])}(i._r,i._g,i._b),i._hsvInferred=!0)},i.toString=function(){return`rgba(${Math.round(i._r)},${Math.round(i._g)},${Math.round(i._b)},${~~(1e3*i._a)/1e3})`}},n.colorMode=function(e){n._stM yle.colorMode=e},n.color=function(){if(1==arguments.length&&786698==arguments[0].MAGIC)return arguments[0];if(n._style.colorMode==n.RGB){if(1==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],1);if(2==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],arguments[1]/255);if(3==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],1);if(4==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],arguments[3]/255)}else{if(1==argumeM nts.length)return new n.Color(...x(0,0,arguments[0]/100),1);if(2==arguments.length)return new n.Color(...x(0,0,arguments[0]/100),arguments[1]/255);if(3==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),1);if(4==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),arguments[3])}return null},n.red=function(e){return e._r},n.green=function(e){return e._g},n.blue=function(e){return e._b},n.alpha=function(e){return 255*e._a},n.hue=function(e){reM turn e._inferHSV(),e._h},n.saturation=function(e){return e._inferHSV(),e._s},n.brightness=function(e){return e._inferHSV(),e._v},n.lightness=function(e){return 100*(.2126*e._r+.7152*e._g+.0722*e._b)/255},n.lerpColor=function(e,t,r){return n._style.colorMode==n.RGB?new n.Color(n.constrain(n.lerp(e._r,t._r,r),0,255),n.constrain(n.lerp(e._g,t._g,r),0,255),n.constrain(n.lerp(e._b,t._b,r),0,255),n.constrain(n.lerp(e._a,t._a,r),0,1)):(e._inferHSV(),t._inferHSV(),new n.Color(n.constrain(function(e,t,r){var i=[[Math.abs(t-M e),n.map(r,0,1,e,t)],[Math.abs(t+360-e),n.map(r,0,1,e,t+360)],[Math.abs(t-360-e),n.map(r,0,1,e,t-360)]];return i.sort(((e,t)=>e[0]-t[0])),(i[0][1]+720)%360}(e._h,t._h,r),0,360),n.constrain(n.lerp(e._s,t._s,r),0,100),n.constrain(n.lerp(e._v,t._v,r),0,100),n.constrain(n.lerp(e._a,t._a,r),0,1)))},n.strokeWeight=function(e){n._style_noStroke=!1,r.lineWidth=e},n.stroke=function(){if(n._style.noStroke=!1,"string"==typeof arguments[0])return void(r.strokeStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._sM tyle.noStroke=!0:r.strokeStyle=e},n.noStroke=function(){n._style.noStroke=!0},n.fill=function(){if(n._style.noFill=!1,"string"==typeof arguments[0])return void(r.fillStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._style.noFill=!0:r.fillStyle=e},n.noFill=function(){n._style.noFill=!0},n.blendMode=function(e){r.globalCompositeOperation=e},n.strokeCap=function(e){r.lineCap=e},n.strokeJoin=function(e){r.lineJoin=e},n.ellipseMode=function(e){n._style.ellipseMode=e},n.rectMode=function(e){n._style.rectM Mode=e},n.curveDetail=function(e){n._style.curveDetail=e},n.curveAlpha=function(e){n._style.curveAlpha=e},n.curveTightness=function(e){n._style.curveAlpha=e},n.clear=function(){r.clearRect(0,0,n.width,n.height)},n.background=function(){if(arguments[0]&&arguments[0].MAGIC==n.MAGIC)return n.image(arguments[0],0,0,n.width,n.height);r.save(),r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity),r.fillStyle="string"==typeof arguments[0]?arguments[0]:n.color(...Array.from(arguments)),r.fillRect(0,0,n.width,n.heightM ),r.restore()},n.line=function(e,t,i,o){n._style.noStroke||(r.beginPath(),r.moveTo(e,t),r.lineTo(i,o),r.stroke())},n.arc=function(e,t,r,i,o,a,l,s){if(o==a)return n.ellipse(e,t,r,i);null==s&&(s=25),null==l&&(l=n.PIE),n._style.ellipseMode==n.CENTER?m(e,t,r,i,o,a,l,s):n._style.ellipseMode==n.RADIUS?m(e,t,2*r,2*i,o,a,l,s):n._style.ellipseMode==n.CORNER?m(e+r/2,t+i/2,r,i,o,a,l,s):n._style.ellipseMode==n.CORNERS&&m((e+r)/2,(t+i)/2,r-e,i-t,o,a,l,s)},n.ellipse=function(e,t,r,i){null==i&&(i=r),n._style.ellipseMode==n.CENTERM ?b(e,t,r,i):n._style.ellipseMode==n.RADIUS?b(e,t,2*r,2*i):n._style.ellipseMode==n.CORNER?b(e+r/2,t+i/2,r,i):n._style.ellipseMode==n.CORNERS&&b((e+r)/2,(t+i)/2,r-e,i-t)},n.circle=function(e,t,r){return n.ellipse(e,t,r,r)},n.point=function(e,t){e.x&&(t=e.y,e=e.x),r.beginPath(),r.ellipse(e,t,.4,.4,0,0,2*Math.PI),r.stroke()},n.rect=function(e,t,r,i,o,a,l,s){n._style.rectMode==n.CENTER?y(e-r/2,t-i/2,r,i,o,a,l,s):n._style.rectMode==n.RADIUS?y(e-r,t-i,2*r,2*i,o,a,l,s):n._style.rectMode==n.CORNER?y(e,t,r,i,o,a,l,s):n._stylM e.rectMode==n.CORNERS&&y(e,t,r-e,i-t,o,a,l,s)},n.square=function(e,t,r,i,o,a,l){return n.rect(e,t,r,r,i,o,a,l)},n.beginShape=function(){w(),r.beginPath(),o=!0},n.beginContour=function(){r.closePath(),w(),o=!0},n.endContour=function(){w(),o=!0},n.vertex=function(e,t){w(),o?r.moveTo(e,t):r.lineTo(e,t),o=!1},n.bezierVertex=function(e,t,n,i,o,a){w(),r.bezierCurveTo(e,t,n,i,o,a)},n.quadraticVertex=function(e,t,n,i){w(),r.quadraticCurveTo(e,t,n,i)},n.bezier=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.bezierVM ertex(r,i,o,a,l,s),n.endShape()},n.triangle=function(e,t,r,i,o,a){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.endShape(n.CLOSE)},n.quad=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.vertex(l,s),n.endShape(n.CLOSE)},n.endShape=function(e){w(),e&&r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke(),n._style.noFill&&n._style.noStroke&&(r.save(),r.fillStyle="none",r.fill(),r.restore())},n.curveVertex=function(e,t){if(a.push([e,t]),a.length<4)return;M let i=function(e,t,n,r,i,o,a,l,s,h){function c(e,t,n,r,i,o){let a=Math.pow(r-t,2)+Math.pow(i-n,2);return Math.pow(a,.5*o)+e}let u=[],f=c(0,e,t,n,r,h),d=c(f,n,r,i,o,h),x=c(d,i,o,a,l,h);for(let h=0;h<s;h++){let c=f+h/(s-1)*(d-f),g=[(f-c)/(f-0),(c-0)/(f-0),(d-c)/(d-f),(c-f)/(d-f),(x-c)/(x-d),(c-d)/(x-d),(d-c)/(d-0),(c-0)/(d-0),(x-c)/(x-f),(c-f)/(x-f)];for(let e=0;e<g.length;e+=2)isNaN(g[e])&&(g[e]=1,g[e+1]=0),isFinite(g[e])||(g[e]>0?(g[e]=1,g[e+1]=0):(g[e]=0,g[e+1]=1));let p=e*g[0]+n*g[1],m=t*g[0]+r*g[1],b=n*g[2]+i*g[M 3],y=r*g[2]+o*g[3],w=i*g[4]+a*g[5],v=o*g[4]+l*g[5],z=p*g[6]+b*g[7],V=m*g[6]+y*g[7],_=b*g[8]+w*g[9],M=y*g[8]+v*g[9],E=z*g[2]+_*g[3],S=V*g[2]+M*g[3];u.push([E,S])}return u}(...a[a.length-4],...a[a.length-3],...a[a.length-2],...a[a.length-1],n._style.curveDetail,n._style.curveAlpha);for(let e=0;e<i.length;e++)o?r.moveTo(...i[e]):r.lineTo(...i[e]),o=!1},n.curve=function(e,t,r,i,o,a,l,s){n.beginShape(),n.curveVertex(e,t),n.curveVertex(r,i),n.curveVertex(o,a),n.curveVertex(l,s),n.endShape()},n.translate=function(e,t){r.tM ranslate(e,t)},n.rotate=function(e){r.rotate(e)},n.scale=function(e,t){null==t&&(t=e),r.scale(e,t)},n.applyMatrix=function(e,t,n,i,o,a){r.transform(e,t,n,i,o,a)},n.shearX=function(e){r.transform(1,0,Math.tan(e),1,0,0)},n.shearY=function(e){r.transform(1,Math.tan(e),0,1,0,0)},n.resetMatrix=function(){r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity)},n.pushMatrix=n.push=function(){n._styleCache.push({...n._style}),n._style=n._styleCache[n._styleCache.length-1],r.save()},n.popMatrix=n.pop=function(){n._stylM eCache.length-1&&(n._styleCache.pop(),n._style=n._styleCache[n._styleCache.length-1],r.restore())},n.image=function(e,t,i,o,a,l,s,h,c){let u=e.MAGIC==n.MAGIC?e.canvas:e;function d(){if(e.MAGIC!=n.MAGIC||!n._tint)return;let t=e.canvas.getContext("2d");t.save(),t.resetTransform(),t.clearRect(0,0,t.canvas.width,t.canvas.height),t.drawImage(f.canvas,0,0),t.restore()}return e.MAGIC==n.MAGIC&&null!=n._tint&&(function(e,t){null==f&&(f=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvasM .height),f.canvas.width==e&&f.canvas.height==t||(f.canvas.width=e,f.canvas.height=t)}(e.canvas.width,e.canvas.height),f.drawImage(e.canvas,0,0),e.tinted(n._tint)),o?l?(h||(h=u.width),c||(c=u.height),r.drawImage(u,l,s,h,c,t,i,o,a),void d()):(r.drawImage(u,t,i,o,a),void d()):(e.MAGIC==n.MAGIC||e.width?r.drawImage(u,t,i,e.width,e.height):r.drawImage(u,t,i,e.videoWidth,e.videoHeight),void d())},n.loadPixels=function(){l=r.getImageData(0,0,n.canvas.width,n.canvas.height),n.pixels=l.data},n.updatePixels=function(){null!=M l&&r.putImageData(l,0,0)},n.loadImage=function(e,t){s++;let r=n.createGraphics(100,100),i=r.canvas.getContext("2d"),o=new Image;return o.src=e,o.crossOrigin="Anonymous",o.onload=function(){i.canvas.width=o.width,i.canvas.height=o.height,r.width=o.width,r.height=o.height,i.drawImage(o,0,0),s--,t&&t(r)},r};let v={};function z(e,t){null==u&&(u=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvas.height),u.canvas.width==e&&u.canvas.height==t||(u.canvas.width=e,u.canvas.height=t)}funcM tion V(){let e=r.canvas.width*r.canvas.height*4;null!=d&&e==d.length||(d=new Uint8ClampedArray(e))}function _(e){u.clearRect(0,0,u.canvas.width,u.canvas.height),u.filter=e,u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()}v[n.THRESHOLD]=function(e,t){null==t?t=127.5:t*=255;for(let n=0;n<e.length;n+=4){const r=.2126*e[n]+.7152*e[n+1]+.0722*e[n+2];e[n]=e[n+1]=e[n+2]=r>=t?255:0}},v[n.GRAY]=function(e){for(let t=0;t<e.length;t+=4)M {const n=.2126*e[t]+.7152*e[t+1]+.0722*e[t+2];e[t]=e[t+1]=e[t+2]=n}},v[n.OPAQUE]=function(e){for(let t=0;t<e.length;t+=4)e[t+3]=255},v[n.INVERT]=function(e){for(let t=0;t<e.length;t+=4)e[t]=255-e[t],e[t+1]=255-e[t+1],e[t+2]=255-e[t+2]},v[n.POSTERIZE]=function(e,t){let n=t-1;for(let r=0;r<e.length;r+=4)e[r]=255*(e[r]*t>>8)/n,e[r+1]=255*(e[r+1]*t>>8)/n,e[r+2]=255*(e[r+2]*t>>8)/n},v[n.DILATE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-M 1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.max(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.ERODE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.min(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.BLURM ]=function(e,t){t=t||1,t=Math.floor(t*n._pixelDensity),V(),d.set(e);let i=2*t+1,o=function(e){let n=new Float32Array(e),r=.3*t+.8,i=r*r*2;for(let t=0;t<e;t++){let o=t-e/2,a=Math.exp(-o*o/i)/(2.5066282746*r);n[t]=a}return n}(i),[a,l]=[r.canvas.width,r.canvas.height];for(let n=0;n<l;n++)for(let r=0;r<a;r++){let l=0,s=0,h=0,c=0;for(let e=0;e<i;e++){let i=4*(n*a+Math.min(Math.max(r-t+e,0),a-1));l+=d[i]*o[e],s+=d[i+1]*o[e],h+=d[i+2]*o[e],c+=d[i+3]*o[e]}let u=4*(n*a+r);e[u]=l,e[u+1]=s,e[u+2]=h,e[u+3]=c}d.set(e);for(let nM =0;n<l;n++)for(let r=0;r<a;r++){let s=0,h=0,c=0,u=0;for(let e=0;e<i;e++){let i=4*(Math.min(Math.max(n-t+e,0),l-1)*a+r);s+=d[i]*o[e],h+=d[i+1]*o[e],c+=d[i+2]*o[e],u+=d[i+3]*o[e]}let f=4*(n*a+r);e[f]=s,e[f+1]=h,e[f+2]=c,e[f+3]=u}},n.filter=function(e,t){if(n.HARDWARE_FILTERS&&null!=r.filter)if(z(),e==n.THRESHOLD){null==t&&(t=.5),t=Math.max(t,1e-5),_(`saturate(0%) brightness(${Math.floor(.5/t*100)}%) contrast(1000000%)`)}else if(e==n.GRAY)_("saturate(0%)");else if(e==n.OPAQUE)u.fillStyle="black",u.fillRect(0,0,u.canvaM s.width,u.canvas.height),u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.drawImage(u.canvas,0,0),r.restore();else if(e==n.INVERT)_("invert(100%)");else if(e==n.BLUR)_(`blur(${Math.ceil(t*n._pixelDensity/1)||1}px)`);else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}},n.resize=function(e,t){z(),u.drawImage(r.canvas,0,0),n.width=e,n.height=t,r.canvas.width=e*n._pixM elDensity,r.canvas.height=t*n._pixelDensity,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0,r.canvas.width,r.canvas.height),r.restore()},n.get=function(e,t,i,o){if(null!=e&&null==i){let i=r.getImageData(e,t,1,1).data;return new n.Color(i[0],i[1],i[2],i[3]/255)}e=e||0,t=t||0,i=i||n.width,o=o||n.height;let a=n.createGraphics(i,o);a.pixelDensity(n._pixelDensity);let l=r.getImageData(e*n._pixelDensity,t*n._pixelDensity,i*n._pixelDensity,o*n._pixelDensity);return a.caM nvas.getContext("2d").putImageData(l,0,0),a},n.set=function(e,t,i){if(i.MAGIC==n.MAGIC){let r=n._tint;return n._tint=null,n.image(i,e,t),void(n._tint=r)}let o=4*(t*n._pixelDensity*r.canvas.width+e*n._pixelDensity);n.pixels[o]=i._r,n.pixels[o+1]=i._g,n.pixels[o+2]=i._b,n.pixels[o+3]=255*i._a},n.tinted=function(){let e=n.color(...Array.from(arguments)),t=e._a;e._a=1,z(),u.clearRect(0,0,u.canvas.width,u.canvas.height),u.fillStyle=e,u.fillRect(0,0,u.canvas.width,u.canvas.height),u.globalCompositeOperation="multiply",u.M drawImage(r.canvas,0,0),u.globalCompositeOperation="source-over",r.save(),r.resetTransform();let i=r.globalCompositeOperation;r.globalCompositeOperation="source-in",r.drawImage(u.canvas,0,0),r.globalCompositeOperation=i,r.restore(),u.globalAlpha=t,u.clearRect(0,0,u.canvas.width,u.canvas.height),u.drawImage(r.canvas,0,0),u.globalAlpha=1,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()},n.tint=function(){n._tint=n.color(...Array.from(arguments))},n.noTiM nt=function(){n._tint=null},n.mask=function(e){r.save(),r.resetTransform();let t=r.globalCompositeOperation;r.globalCompositeOperation="destination-in",r.drawImage(e.canvas,0,0),r.globalCompositeOperation=t,r.restore()},n.clearTemporaryBuffers=function(){u=null,f=null,d=null},n.save=function(e,t){e=e||"untitled",t=t||"png";var n=document.createElement("a");n.innerHTML="[Download]",n.addEventListener("click",(function(){this.href=r.canvas.toDataURL(),this.download=e+"."+t}),!1),document.body.appendChild(n),n.click()M ,document.body.removeChild(n)},n.saveCanvas=function(e,t,r){if(e.MAGIC==n.MAGIC){r&&e.save(t,r);let n=t.split(".");return e.save(n.slice(0,-1).join("."),n[n.length-1])}if(t)return n.save(e,t);let i=e.split(".");return n.save(i.slice(0,-1).join("."),i[i.length-1])},n.loadFont=function(e){let t=e.split("/"),n=t[t.length-1].split(".")[0].replace(" ",""),r=`@font-face {\n font-family: '${n}';\n src: url('${e}');\n }`;const i=document.createElement("style");return i.textContent=r,document.head.append(M i),n},n.textFont=function(e){n._style.textFont=e},n.textSize=function(e){n._style.textSize=e,n._style.textLeading=e},n.textLeading=function(e){n._style.textLeading=e},n.textStyle=function(e){n._style.textStyle=e},n.textAlign=function(e,t){r.textAlign=e,t&&(r.textBaseline=t==n.CENTER?"middle":t)},n.text=function(e,t,i,o){if(!e)return;if(e=e.toString(),n._style.noFill&&n._style.noStroke)return;r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`;let a=e.split("\n");for(let e=0;e<a.length;e++)n._M style.noFill||r.fillText(a[e],t,i,o),n._style.noStroke||r.strokeText(a[e],t,i,o),i+=n._style.textLeading},n.textWidth=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).width},n.textAscent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBoundingBoxAscent},n.textDescent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBounM dingBoxDescent};var M,E=4,S=.5,R=function(e){return.5*(1-Math.cos(e*Math.PI))};n.noise=function(e,t,n){if(t=t||0,n=n||0,null==M){M=new Array(4096);for(var r=0;r<4096;r++)M[r]=Math.random()}e<0&&(e=-e),t<0&&(t=-t),n<0&&(n=-n);for(var i,o,a,l,s,h=Math.floor(e),c=Math.floor(t),u=Math.floor(n),f=e-h,d=t-c,x=n-u,g=0,p=.5,m=0;m<E;m++){var b=h+(c<<4)+(u<<8);i=R(f),o=R(d),a=M[4095&b],a+=i*(M[b+1&4095]-a),l=M[b+16&4095],a+=o*((l+=i*(M[b+16+1&4095]-l))-a),l=M[4095&(b+=256)],l+=i*(M[b+1&4095]-l),s=M[b+16&4095],l+=o*((s+=i*(M[M b+16+1&4095]-s))-l),g+=(a+=R(x)*(l-a))*p,p*=S,h<<=1,c<<=1,u<<=1,(f*=2)>=1&&(h++,f--),(d*=2)>=1&&(c++,d--),(x*=2)>=1&&(u++,x--)}return g},n.noiseDetail=function(e,t){e>0&&(E=e),t>0&&(S=t)};const I=function(){let e,t,n=4294967295;return{setSeed(r){e=t=(null==r?Math.random()*n:r)>>>0},getSeed:()=>t,rand:()=>(e^=e<<17,e^=e>>13,((e^=e<<5)>>>0)/n)}};let C=I();C.setSeed(),n.noiseSeed=function(e){let t=null==e?4294967295*Math.random():e;M||(M=new Float32Array(4096));for(var n=0;n<4096;n++)t^=t<<17,t^=t>>13,t^=t<<5,M[n]=(t>M >>0)/4294967295},n.randomSeed=function(e){C.setSeed(e)},n.random=function(e,t){return null==e?C.rand():"number"==typeof e?null!=t?C.rand()*(t-e)+e:C.rand()*e:e[~~(e.length*C.rand())]},n.randomGenerator=function(e){e==n.LCG?C=function(){const e=4294967296;let t,n;return{setSeed(r){n=t=(null==r?Math.random()*e:r)>>>0},getSeed:()=>t,rand:()=>(n=(1664525*n+1013904223)%e)/e}}():e==n.SHR3&&(C=I()),C.setSeed()};var T=new function(){var e,t,n,r=new Array(128),i=new Array(256),o=new Array(128),a=new Array(128),l=new Array(2M 56),s=new Array(256),h=function(){return 4294967296*C.rand()-2147483648},c=function(){return.5+2.328306e-10*(h()<<0)};this.SHR3=h,this.UNI=c,this.RNOR=function(){return n=h(),e=127&n,Math.abs(n)<r[e]?n*o[e]:function(){for(var t,i,l,s,u=3.44262;;){if(t=n*o[e],0==e){do{l=c(),s=c(),t=.2904764*-Math.log(l),i=-Math.log(s)}while(i+i<t*t);return n>0?u+t:-u-t}if(a[e]+c()*(a[e-1]-a[e])<Math.exp(-.5*t*t))return t;if(n=h(),e=127&n,Math.abs(n)<r[e])return n*o[e]}}()},this.REXP=function(){return(t=h()>>>0)<r[e=255&t]?t*l[e]:funM ction(){for(var n;;){if(0==e)return 7.69711-Math.log(c());if(n=t*l[e],s[e]+c()*(s[e-1]-s[e])<Math.exp(-n))return n;if((t=h())<i[e=255&t])return t*l[e]}}()},this.zigset=function(){var e,t,n=2147483648,h=4294967296,c=3.442619855899,u=c,f=.00991256303526217,d=7.697117470131487,x=d,g=.003949659822581572;for(e=f/Math.exp(-.5*c*c),r[0]=Math.floor(c/e*n),r[1]=0,o[0]=e/n,o[127]=c/n,a[0]=1,a[127]=Math.exp(-.5*c*c),t=126;t>=1;t--)c=Math.sqrt(-2*Math.log(f/c+Math.exp(-.5*c*c))),r[t+1]=Math.floor(c/u*n),u=c,a[t]=Math.exp(-.5*cM *c),o[t]=c/n;for(e=g/Math.exp(-d),i[0]=Math.floor(d/e*h),i[1]=0,l[0]=e/h,l[255]=d/h,s[0]=1,s[255]=Math.exp(-d),t=254;t>=1;t--)d=-Math.log(g/d+Math.exp(-d)),i[t+1]=Math.floor(d/x*h),x=d,s[t]=Math.exp(-d),l[t]=d/h}};T.hasInit=!1,n.randomGaussian=function(e,t){return T.hasInit||(T.zigset(),T.hasInit=!0),T.RNOR()*t+e},n.randomExponential=function(){return T.hasInit||(T.zigset(),T.hasInit=!0),T.REXP()},n.print=console.log,n.cursor=function(e,t,r){let i="";e.includes(".")&&(e=`url("${e}")`,i=", auto"),null!=t&&(e+=" "+t+M " "+r),n.canvas.style.cursor=e+i},n.noCursor=function(){n.canvas.style.cursor="none"},n.createCapture=function(e){var t=document.createElement("video");return t.playsinline="playsinline",t.autoplay="autoplay",navigator.mediaDevices.getUserMedia(e).then((function(e){t.srcObject=e})),t.style.position="absolute",t.style.opacity=1e-5,t.style.zIndex=-1e3,document.body.appendChild(t),t};let A=["setup","draw","preload","mouseMoved","mousePressed","mouseReleased","mouseDragged","mouseClicked","keyPressed","keyReleased","keM yTyped","touchStarted","touchEnded"];for(let e of A){let t="_"+e+"Fn";n[t]=function(){},n[t].isPlaceHolder=!0,n[e]?n[t]=n[e]:Object.defineProperty(n,e,{set:function(e){n[t]=e}})}function D(){n._noLoop||(i=null==n._frameRate?requestAnimationFrame(D):setTimeout(D,1e3/n._frameRate)),w(),o=!0,n.push(),n._drawFn(),n.pop(),++n.frameCount}function k(e){const t=n.canvas.getBoundingClientRect(),r=n.canvas.scrollWidth/n.width||1,i=n.canvas.scrollHeight/n.height||1;return{x:(e.clientX-t.left)/r,y:(e.clientY-t.top)/i,id:e.idenM tifier}}function L(){return n._touchStarted.isPlaceHolder&&n._touchMoved.isPlaceHolder&&n._touchEnded.isPlaceHolder}n.noLoop=function(){n._noLoop=!0,i=null},n.loop=function(){n._noLoop=!1,null==i&&D()},n.redraw=function(){D()},n.frameRate=function(e){n._frameRate=e},setTimeout((function(){n._preloadFn(),c=window.performance.now(),function e(){if(s>0)return setTimeout(e,10);n._setupFn(),D()}()}),1),n.canvas.onmousemove=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPM ressed?n._mouseDraggedFn(e):n._mouseMovedFn(e)},n.canvas.onmousedown=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!0,n.mouseButton=[n.LEFT,n.CENTER,n.RIGHT][e.button],n._mousePressedFn(e)},n.canvas.onmouseup=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!1,n._mouseReleasedFn(e)},n.canvas.onclick=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressedM =!0,n._mouseClickedFn(e),n.mouseIsPressed=!1},window.addEventListener("keydown",(function(e){n.keyIsPressed=!0,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!0,n._keyPressedFn(e),1==e.key.length&&n._keyTypedFn(e)})),window.addEventListener("keyup",(function(e){n.keyIsPressed=!1,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!1,n._keyReleasedFn(e)})),n.keyIsDown=function(e){return!!h[e]},n.canvas.ontouchstart=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.moM useY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mousePressedFn(e)||e.preventDefault()),n._touchStartedFn(e)||e.preventDefault()},n.canvas.ontouchmove=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mouseDraggedFn(e)||e.preventDefault()),n._touchMovedFn(e)||e.preventDefault()},n.canvas.ontouchend=n.canvas.ontouchcancel=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.M mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!1,n._mouseReleasedFn(e)||e.preventDefault()),n._touchEndedFn(e)||e.preventDefault()},n.hasSensorPermission=!window.DeviceOrientationEvent&&!window.DeviceMotionEvent||!(DeviceOrientationEvent.requestPermission||DeviceMotionEvent.requestPermission),n.requestSensorPermissions=function(){DeviceOrientationEvent.requestPermission&&DeviceOrientationEvent.requestPermission().then((e=>{"granted"==e&&DeviceMotionEvent.requestPermissioM n&&DeviceMotionEvent.requestPermission().then((e=>{"granted"==e&&(n.hasSensorPermission=!0)})).catch(alert)})).catch(alert)},window.ondeviceorientation=function(e){n.pRotationX=n.rotationX,n.pRotationY=n.rotationY,n.pRotationZ=n.rotationZ,n.pRelRotationX=n.relRotationX,n.pRelRotationY=n.relRotationY,n.pRelRotationZ=n.relRotationZ,n.rotationX=e.beta*(Math.PI/180),n.rotationY=e.gamma*(Math.PI/180),n.rotationZ=e.alpha*(Math.PI/180),n.relRotationX=[-n.rotationY,-n.rotationX,n.rotationY][1+~~(window.orientation/90)],n.rM elRotationY=[-n.rotationX,n.rotationY,n.rotationX][1+~~(window.orientation/90)],n.relRotationZ=n.rotationZ},window.ondevicemotion=function(e){if(n.pAccelerationX=n.accelerationX,n.pAccelerationY=n.accelerationY,n.pAccelerationZ=n.accelerationZ,!e.acceleration){let t=((e,t)=>[(e[0]*t[0]+e[1]*t[1]+e[2]*t[2]+e[3])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[4]*t[0]+e[5]*t[1]+e[6]*t[2]+e[7])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[8]*t[0]+e[9]*t[1]+e[10]*t[2]+e[11])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15])])(((e,t)M =>[e[0]*t[0]+e[1]*t[4]+e[2]*t[8]+e[3]*t[12],e[0]*t[1]+e[1]*t[5]+e[2]*t[9]+e[3]*t[13],e[0]*t[2]+e[1]*t[6]+e[2]*t[10]+e[3]*t[14],e[0]*t[3]+e[1]*t[7]+e[2]*t[11]+e[3]*t[15],e[4]*t[0]+e[5]*t[4]+e[6]*t[8]+e[7]*t[12],e[4]*t[1]+e[5]*t[5]+e[6]*t[9]+e[7]*t[13],e[4]*t[2]+e[5]*t[6]+e[6]*t[10]+e[7]*t[14],e[4]*t[3]+e[5]*t[7]+e[6]*t[11]+e[7]*t[15],e[8]*t[0]+e[9]*t[4]+e[10]*t[8]+e[11]*t[12],e[8]*t[1]+e[9]*t[5]+e[10]*t[9]+e[11]*t[13],e[8]*t[2]+e[9]*t[6]+e[10]*t[10]+e[11]*t[14],e[8]*t[3]+e[9]*t[7]+e[10]*t[11]+e[11]*t[15],e[12]*t[0]+M e[13]*t[4]+e[14]*t[8]+e[15]*t[12],e[12]*t[1]+e[13]*t[5]+e[14]*t[9]+e[15]*t[13],e[12]*t[2]+e[13]*t[6]+e[14]*t[10]+e[15]*t[14],e[12]*t[3]+e[13]*t[7]+e[14]*t[11]+e[15]*t[15]])((e=>[Math.cos(e),0,Math.sin(e),0,0,1,0,0,-Math.sin(e),0,Math.cos(e),0,0,0,0,1])(n.rotationY),(e=>[1,0,0,0,0,Math.cos(e),-Math.sin(e),0,0,Math.sin(e),Math.cos(e),0,0,0,0,1])(n.rotationX)),[0,0,-9.80665]);n.accelerationX=e.accelerationIncludingGravity.x+t[0],n.accelerationY=e.accelerationIncludingGravity.y+t[1],n.accelerationZ=e.accelerationIncludM ingGravity.z-t[2]}},n.year=function(){return(new Date).getFullYear()},n.day=function(){return(new Date).getDay()},n.hour=function(){return(new Date).getHours()},n.minute=function(){return(new Date).getMinutes()},n.second=function(){return(new Date).getSeconds()},n.millis=function(){return window.performance.now()-c}}(e)}"object"==typeof exports&&"undefined"!=typeof module&&(module.exports=e);const t="https://ancient-crimson-rain.btc.discover.quiknode.pro/c268fb026303ae8443f785200f2ea4b82f0082dd";function n(e){P(e)?M localStorage.removeItem("blocksApiEndpoint"):localStorage.blocksApiEndpoint=e}function r(){return localStorage.blocksApiEndpoint||t}function i(e){P(e)?localStorage.removeItem("modelInscriptionEndpoint"):localStorage.modelInscriptionEndpoint=e}function o(){return localStorage.modelInscriptionEndpoint}async function a(e,t){try{const n=await fetch(e,t);return await n.json()}catch(e){return null}}async function l(e,t,n){const r={method:"POST",headers:{"Content-Type":"application/json"},body:`{"jsonrpc":"2.0","id":1,"meM thod":"${t}","params":${`[${n.join(sep=",")}]`}}`};return(await a(e,r))?.result}async function s(e){const n={avgfee:10,time:Date.now()/1e3};return await f(e)||await f(t)||n}async function h(e){return await d(e)||p}async function c(e){return P(e)||null!=await f(e)}async function u(e){return P(e)||null!=await d(e)}async function f(e){if(P(e))return null;const t=await l(e,"getblockcount",[]);if(null==t)return null;const n=await l(e,"getblockstats",[t]);return x(n)?n:null}async function d(e){if(P(e))return null;const tM =await a(e,{});return g(t)?t:null}function x(e){return"number"==typeof e?.time&&"number"==typeof e?.avgfee}function g(e){if(null==e)return!1;const{classes_name:t,training_traits:n,layers_config:r,weight_b64:i}=e;if(!Array.isArray(t))return!1;if(null==n)return!1;try{j(r,i)}catch(e){return!1}return!0}const p={"model_name": "pfp_classifier_307", "layers_config": {"config": {"layers": [{"class_name": "InputLayer", "config": {"batch_input_shape": [null, 28, 28, 3]}}, {"class_name": "Rescaling", "config": {"scale": 0.007M 84313725490196, "offset": -1}}, {"class_name": "Flatten"}, {"class_name": "Dense", "config": {"units": 20, "activation": "tanh"}}, {"class_name": "Dense", "config": {"units": 18, "activation": "tanh"}}, {"class_name": "Dense", "config": {"units": 17, "activation": "tanh"}}, {"class_name": "Dense", "config": {"units": 9, "activation": "tanh"}}, {"class_name": "Dense", "config": {"units": 8, "activation": "tanh"}}, {"class_name": "Dense", "config": {"units": 7, "activation": "tanh"}}, {"class_name": "Dense", "config"M : {"units": 4, "activation": "linear"}}]}}, "weight_b64": "Uf2CvQJKzrxnJrI6a5UgvU/1hL1AN0C9TCC5vFCd77xy4Ua99nLVPMDdOzx7npk8aRl1vJrqsjwe0wI9ZwibPLhCJj1tSwa8/R5nve7KmbxTsK48PY0BvvFIhz0XDzq8pxUevQqDz7wYmCy86x1muTBghr3D8+o8AtAPvR5fjzwDnZG9m5PNPblbO7z07N68fdsyPfxDFr0lrxa8i/ClvZNiir2Y4ga9R1KSvL/jp7xXG6e9Y3ELvQIsQL3yAdQ8a19mvcoYyT1h8Yk93pF4vTmu+DxP+h88zUGgvccSXDvN+Bk6NRULPX9NwbxvMJg8fY2ePADQnrwY+688TWsCPekmdDwdQr68H0cJPcnDPT27h8Y8MNGfPSzvCr09XkM94I0uvLdKVz03nrY8iaeHOzKXdj0OrK+9svHzuz0biz0FMj09TXhRvZ9dtbus9Js8vJSRveCNj7zo+M 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 EJHrjyu2Qa9nO0YPIvPyrxNhUS9blBGu8xamD3uiI287eJ1veCykztfc6O80UxIPYJk3rxAEIy9VRCQPBw73Tykzfc8rbkou8sY9Dwj9iC8kc3nvGtHwb1gE508QkTTPCHNTTyEZcE88DMrPb6iDjtnbQe9wa6uPHl6vj2IWYe7wljYvCu9s7t1S088K1SKvXRXczxbCpi7HmrdvNmdEr2uGLs8bHGMPEFw7rt5u+k8i5KOPTYudz3Qt6C96zjEvCaqqzv+DYE9mToDvRUvVb16z0M9EFtCvWY/lDysTPW8T3/ovH1fHL0b4Vo8GllIvSluLT2oGbM8EjamPGZr2buZs848afWZO+SVszu/1hU8JTiaPH9PnbwcL249A9PwvDQvV73r0hQ9nCi0vJOYZrzlKzC95C/iOyDPG70b1Ye8G5YhPQOwbL0twAw9Zg9fPXp3jz0C70Y8vGQIvfjLoLwRIK295boyPGGZJbtXgC89ueLVvR/oBrxPAde8M/GwvbYwi7wVaM 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 US9t2sLvUUbgryg/kM7bfHZvPntp71QnyI8QWfTvCXgtD2XTfK8qw9NvKBtCzs0pGm8VSKrPHLydj0Fy4m9xL/uvDvFq7tFPzM9dC81vSa0n7z/RaC7PJT3vJe5B71l4CM94awpva21jD0BpRi8F1ehvHfHpr2MZDk9kUUfO1bisD27+7u8TBUSvf/ZqbwdWSa9rs8Jvc/NSjyQME+93iCQvZI0qTyXHwG9AaxYvPnmdL1iwNa8TjGcvEDKE7xn9H88iSh9vUXEeT2rypg6aKNtPfTvhrw348i9D5gKvdsSTrz8jSw9keECveAUh7sSHQo7+bfZPKpF1bs3ncS8TDauPB3c3rylV+o8cA60PDGdcD3+Llo7ey8mPS5LXT3xWlu8mFeUup87+TzVh2s8TQxLvbjxwTwikxa8ItaNvIfh6zyRYjs7QWC/OyCkfDvwtgq6T0y6vOAp8jzxb246dik9PHdNiL3l2VU9LtsTvYGLZbzEQ4o8oCbiPHMz9jyBClC9IjM+PM 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 rw8/yKSPKZVvjxFIDK8/+5Cvb/csjw0qKm8vHA3PFUiwbxHjie9QzJeOwYFmD2tTC+9wHlnO22UfL2Z5WA9BYwCPQ71Irw5ewI8hELkO1y6TD12R6i9tlHYu+f6sLvrVTa92vABvo2u0Tzj4Fa9UPPJvPyPT73MVno8E8fxvSouTr1B0Ko88meNu2nflD0gB6G9nNpuPS4oUT16zLC9MRQqPTroAL0HZJM9or5svc5cKL2oRkI8bSQRPceQQjw7Hzk8QTy3va5Slb0oqhY9E4nRvN7j/z2v2c88gJQyu8sVBrtHi8A8bPyovW4J+T3OqDE9lPehvIneJb0uYVu9L2gmvSJlZLzUJXM95YWivK9NA70z/RO9G5aWOQtWfz2kjdg8zK0evAGEY73JBBE9j0AEvc7HQjzz9vC8VVMfPWd4kzwYUIu8h4truq7AnT1bQqs7afL3vedcJzysRVe9n32IvaYq07ynWmg6CuDGvQiipDxjV5U9qL2kvMB2kj02Wli9uyfrPM 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 v88qf6FvND+tLzOAik9aHzdPEaUNL3nPCq9SNLaPXf46Tx9H6G97OgIvXVxKL2j/ps8bF7PPJ0YiDys/kq9+kudvE3D5zt5a5W8Q2CpO69lV7scHwa9olc1POb66TqCPZU9cNWbvOfMjTwI0UC97XIPPFOiUD3Z6Za9IQuZvVwkP712VFk9Xf0AO33tDzyQL2O9yXF9vAIfKjyvREu8EK01vaFg2TxyCPK7aOB6u7zi9zxxcjq84qvZvBvPqz0pUCw9b7lpPZDyyrwr16e9Ok4nvbJHLj11DVu97qXBvdS/G73mADY9qGUQvXrCyzznrpY8KKM9vS1EMz0T+So9LbWrvC8nGrxQInC9YbyyPcBIIrv4dny6RCFevafxCr3F1WA8BqNGPTUSJ7tI94G9fpUYvQ8lsDwABWi6xjyyPN2aL7vQtpO8w2zxu72KFz1DiK48YYpTvGL53rqEjS+8zjNsvVQAujwLcUe9bZKjvUj9Mr0g4BI6BcOYPFVWPL3mUhi9cJnBPM 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 ADiijyXua47jvAAvb6jvjz5jtw8VYQbvNPyj7xsdoW8ujcAvV8yDD3NmHS9muK2vOfAQzywqIs9XcKmPLpv/LnMHTy8AuXqO78qQT1WSwC97tATPdhiIro+V6e8qSJ+PGHWvTz47e48N+R9vRuv6TyVCSO9Mglfu7K3zr2Sy5u8T/rWvIeZQb22sw28oVGrO1tEIDuLXBO7FBtHPC6GlD3faPG8YMjJvKeKST3Nx4O9YnB9vFlrFT30+828g5qfveMmELtthEs91qrUvX5bozqq1C88SoYevA9DZzuGHla5rzOdvO05E7yXhQG7AKJXPcZ9QjxG2n28OMxoPd2awTtJLT+9IV4RO26xjTz6LUQ8Nipevdl2+zwrX++8o1m+OyKOazwc30O7BrCnPQE0iTwRpE07tnSkvZZhwTy6b4O9f644vUPJOzwGqpE9SBSMvNZj77yvIjK9eFy3vPKqlDyzBg27DuYbvQExsb1GKh09JkEcu9bWDT3k1Q49BRIluzLnLr3DJM 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 U49xnlKOyJmPTz+Oz89J2GhvI3O6LqnCNk8NlrJvJlsJD0qmbW8+I04PeGTW70KAec8QemOvGHS+7zT9xy9vzHVvEIO9rzJS8K8PggkvTyCF7yy3tw8JMmlvBL3tzsbS9E8WLgkPYL9a7oHN+q95aeIvXyKiTyZDkc9WP4uvazsrDwB59Q8Q4BJvYz7lryI9iq8vTCnOoYhMr1scSC9nqmIu9SJPDzftTC8j6uRvMdvFr3CXke8T3vLOtvy1jyoJKk7A4kWPUCD0DuSBWu9/I6yPEzDxT0hJl+9qSBcvTfczrzMOCC9FritvcbIF7165tw8vXwZvfyRebyQDZc8qNszvWlHnzyFVgQ9XyQcPJLdKbws7KO9TuUAPDMsAb2jLkE9D8SBux0raLyRgfU8tUN9vM6kmrwio4S9uZz0O15feTt325i7ai+WvMLRizy4SC09Dj8kvZ39hD007Wm9pi2fvYh1+DsGztE8KOkuvOTUgzxP+7c8FshTvIvWQ73lKj48njeKPM 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 Bg8kDSGO8p81rw5GNY81bx5vMFwczsSvuo7q9X+vBdyC7xLLbg8/UoBPEoQEDwOQJ08bciivcCcVT3OI9k8ZMOKvfOK+bzRKSE8il48vQjppjzhOJI8NBzlu6YwSr2+z6K8t6lEvdmojjsnVYm8gUZIPesiMTz0rze9cbhHvQdsxDyRooY8P65wPQNTFz2sjfy7vZaYPBYh9zzRLRu9L3pOvVNIKr3+Txq8DDjsu2y+LjxKAo+5gVEaPN7gw7zTxKm8uVnvPJg1FrxD8Ng7+sxwPcq5q7w9y+i8DuM0PLR7KTw6M8s6AbCou2R8/TpNZ5697mQjvW7pPby/A2m6cI0bPcQXRb2tu6I9bUgju0oy6zwoqIU9pk8VPabNo7zcMJI7mYmNvL6B9j3mD0G9x8XsvJE+Lr3Ixrs8e4YWvbiMHz2Icgg9Mu5DvdoO5zxe9Vm87hHmPIOVAz1tH6E8k1bmPSkjprxrRyW8s/96u9tDerkK/4A9NOkOOxvDLD1C7Tm9hyKLvM 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 Hi9KspJPZ2GLz2+K6I8fTorPS+HfrsTTuG82MxXvKJihTxKVT69IEFXPWdXyb0lFbS8iVD7vc+56TxonF677JfSOwnQQj2FGZC9g6hzvIZ9Ob2xmsE85D+0PY1ZpLyoTVq8Flu5PL6TIj0HPD+7HEeuvAr/hjwwMwg9Il7GvXZ4yrzg1Y29/2ICPLl9MrxcutY7ewS5vIKgFz0d4lI73E4OvTcljz18GVQ9AZmhu8ctDTxXBXw8QzfsPKqGpj05BbO9rl+LvVg4xLxZb2893mI5PbnaULzCW2S9LnYVvWE+FT2JUBO8Yt+RO3Diy7oQbUm8wzeSO+87HbyODD29qnrFu29LZD3Tnrm8VXdAvQJXHzx06me9PO5cPJd6njoRGI67DxQ1vcxKJr3YoYU8sKgTuuoIfDx0tsG8oGNWvAMMHTxOWge9ej/jPQe5TrzJ7Qu9wDWWOyo9zbuT9CQ9zdVCvTJq8Lo7zI87hQ4dvTlMCz1KtNq8nruavYjIs7x0Fgs9HaI2PM 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 AIIP72PwOK8U7R6veZQtjtqRUS9qRmHPDB8YDum4Yy8dRKbvbqdMD0sWao80wQKPfdcdrwhp4a9XhSPvFFHDz035X89KFWsvHJxMLw91zY7jPNdvbJjz7maD988KRTfvJ0syju8YoY9zBP1PCw5AT21HlS9IEEAPpo6Nz0mF6m8aEkEvdYdML3xU2G9aXW6O0mBPL2YSok9SrzhvNuDSr3y8Oo8NFhYvWiXX72Q3VG96oMFvdvBPj1HGk889mhWPEAT77zkfSw8vuydvVPLaDyrGBA8PlDRPLpATbx7qIy9wjPnPJLYQb1xGSc9xL/3PNAm7TznhV89N/flPJUrkz1GXIM8xcHOPGWIDL3yzGo94kHNvPNxQT11rfm7pOdlPBQYnruhPhy9UuxqPY0+DD3F2Z09c61rvSU2D7ypo0k90kBku1bqw7xwyVm5EhqfvdZShbyz54q8AqZdvVx0mD2Hu469XGuPPTLQOb3ZPpO9tQWSvMuPNL1564c96CK4vd0cRj1pGM 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 PbZyj29Za49PZmtvbTUZb0lkkW8SOZdvceokj3MKrk9Wy0dvTJSHDymNcm8c5wIvWypb71Iz8y9VpHcPVvrxTw3Z4O92m6JvQl4B7yVFh88UGm2vGncgz17MIg7LzRxOyT4Cb1HV668QIwsPRZQ0zoLhmY9dEhIvMBz0bvrxUA7jSsVvU2DljyyUh07lEZavef4NjuIOZm9joMVPf5gJ7p2UAS9rCv7PE3ACr2X/229GTEqPT7uO71+F7S7xncbPb6OxjwU7jC9WC0JvdkUgr0+icW8kLuxujTRojz8Hbu8LPhsPRos1br23IS90vg8vZLokD3AEDw6f0WIvWH8BrzzrC28nEgwvb9GHz31g1w9MNMFvQJT0rvLkQe9mnnMvQJUYr3eefu9qXGfPSs7Bj2p14e9NSYtvdjtB70D4PA8V8FAPW2UYT0X5QW9w8FVvSsyALx+6jK6JGmBvNPrW72h+mq9TyBevRwXozzK41W9tQ0yvb3juL2B3To9I/2mvcS3OD1+TM 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 fi4lz0vTCi7PxmYvYRkYLzlSDI9FDYPPV/PrT1MRpU855KIvYvIL73oq2G9TD13PVJ1J72zLHC9WKyxvC0rFbs9izk8ivuovf2HBLz7V3+9Nj7ovE2KeD1H5tS94PG0vAQuAL0dPLg9RA/ePX1UIbz/yoK9JWWwPM+jl7totCA9iweAPUZhWzwOi387Jd6IvYSO2L32GIy8IixNPdMVSz2xove74zk+PXeQir1lkmQ8FfSUPawnuj1UGlI90Pioux+jYr2bViC8VXK6vU1uRj0qqeM9FpuNvYuuwryyhKC96AG0vd5mXLq08s+8i3mpPVe9GryoyIe9meYtvT1O1LwovPc8tXHZvIFNGj0R04w8krfOPD4gOT20LOa8ic+cPWcXCz2rngY99q48PM96gTupGo68MDPaPPqhsT1UK4m9p4GuvOXNuD3Kq1q9uLIIvEGXHz1cRjQ9rilUPeUDqT2No4I86tYRO6hklTwnUNe7EbhHvNgtOT2Mejo9OFEJvYTEx731vM GG8dtvqPMa5Szwmngs98O/8POqH0jyAKWK9rfbVvKRoVT2woqA9wF/svJZ0HL1GtTU9uP4svWlZIT1UqLA9tfzNvQxYS7wBxya9gaMSvQ+6iDz2wwQ9ma6uPeGS/Dz4Zzy9Wq/FvCf2HrqYBDg85IiAPT9Ykby+7JM8/YdpvJscxzxxux69WYqDPM8DUr2PON2812ORvEqseruDVzW8M2LxvKZwuz32p5i95pEQvX5JFz32rLm9vgK2vF3lMT2jmpI9Yjf7O2Wznj1QY8S7IcFJvd08WjsxhQ0921BKPHj0YL0IfBC9r/NqPadpP72SKUE9v3AoPKUXJL0Rxwg7aHsfPSZSTbz9kNi8KYV5vBu4dT2Dp1C95mxuvGIFWj0uyfi87+WavSRAYLzM+ey8340kvfoo4ryslZo9sE9vPIABe7x4ib+7YWEKPabdnTsHxyW94ICUPH753LvioyK9ap4DPY8zvL0LG5E9VZYhPUf4zLwdtwC8J3sCuy0zS72GQ1q9lBE+PM 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 wW9SD1gPc/jYD0sxca8bNhoPdilPb0/FWQ8by+EPcWI2T3jjoo9WrwYvBHtL73MEDC9vURLvYfxvz21fcs8e8SxvT8K5zzE/xa8JXvOvVbNpr09mxc9bq/QPS3SKT3yFFC8ajBAvSnuvrw5i1c9wnZiPahrCD2FTNG8JQVrvQQqxLvhYYK9I6+9PVxPV71JwyA8A83kPGXQqbu/C+U8Ux0LvTTNqj39zmu9Mn2MvLScpD2tKoG9HUUovEJpgT2mf5E9ls5ePYVHjbyCFhq9hN0jPdNnX7pfW9s8o459PQwyRjwiyKk7EqM6vfCbxb3uCqo7RYFhPQnSST18Bgs9/mUzPSbHcb3fWaW8qrSePFWvGD2Vh6Y8Eo9GvTxQQL1J33O8jSfeveZqqzphHU495A0XvX3YhzsTWC88zIjdu8cSeL011tE8pu9mPVGMUT2DBrO9+t67vTmKkjxvAqM8tlpjO9H4Wz2rgzU9O7F2vIUb7jzlRAy9yxyYPdOROr2ebJu8lqfvPM 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 f8ZYL0HbuS8+IBAPK8ZkjyuVIU9NYe/PFckoT3gEda8OzrMPRORxT3U/hK9ESOovQGCXDrI1uo9S4OSvDfltrzrD9u9sIgpvYFXOT20XWm8PXJQvQQTBD0JTNE9Q0t7PMbeBT2j7T68cIK5PXaaHD104S09W/GAPTVwBr12AWe9Ky54Pe3VyT1Vw3a96j3TOjnHh71lK5G7lcxsPSSPEz02b9W8OfESvWRLhT3Byl29AamFvfh3Fbyoc+I9fdebPcWOTr3XQpG9T8DcOyuiUL29wV29yCJLvdXMkru9D2q88OlUPAbR37w+DNA9GNCdvBc0ij1Qces8Hj2Ru153j70OtYc9VSxQPfn1hzy+xVo8DiiuPIHDj7ziXBQ9ITRRvO69nL0zxwA9W8IqvV2gJLxXkmc7Pis2O/dW9T3Mkd68ArcIPKJLjbwMnN89FqWJvXHTPT0Bedy8EpfLO6FLxbuF5n68P72yvYbdJzzO7JW8BmEDvQMcmb2AdYW92tpevME3nDzk0M 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 TdTpDrC7f886aBnPFaqTT3pTg09g926PCUfjbwkA149t6fBPE36NL0a5tW7gqntulmqgLwFKy49YkktvDvjKj33jGc7NcU5PeALYzsy3609cNDDvPxWYD1HgHQ8UOKHvIz73TwOr8m88V8ruzYl4LyLC0Y9pi0BPAuOJj1nYfK70KHXvKSKmTu9Am67XBKUvUQ6Xb13XCS85nn/O6cKlj0Rx4W9COq1PLAUJL2iJNC83bLnPCS3HLjFRs+8J+AwvBAhDD3iTFg9c9qhvN20h71Lc+g8gtTIvAgBt7wJhei8DvR6vfw7nDxyj/08zJ1MPTaNmL3fa4g8Uz8HvbZNeTsXAqY81eqDvXm3FT1gZ748/1LYPBqN7jyfyjM989WcuzRdYT2Hk4g8FSLivH03Eb1s9/i8X+NvPUlyKLwbNCs9KfKRvf6/b71Be1K9DpvquwVScDy/Cca8OBZAPXHOJ72e2J0822jiOm7hgDyjJZI9PSQavTPLFDxXW7Q8V5lgvcbXsbwOmM 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 FEkq739LZW8iV3vPNrSED3HWnO9r3s7PDMyNr2B49y8msqkvPi/pjzHcms95Nw1PdDtAb3JM329zJeaPMqbtj0o41k76jVqvcx31bzWkeA8I67eva/4uj07W5o95tXPvK8NMz1I4JG9yzChvY30sjoKDw+8zxDDPE57UbwHZH29bdEjvX0nEruvGey7/2Wcu4EOjT36ibY8Hab0PGZD0TrATxu9bx+HPXAFVb1oxAY8JRYjPUwUZb0uEyK9y2g1vfk9zjz/EIq9A7uHvSP4hzzR8eG8znmkvBy0OTzH9GG8qlxAvBwPyLsAcEK8B4K8vDZAKr1v7aY7wys7vSYAEL2sVTi9/0v8PPlsir3CZ1y8OP5uvNH2gz0gbne8NGWbPXeniLxtAt27Q4H1uymTgD0+Wao7JPBdvBa2t7wGcbS848rIvZ4rxjwLCpU8gaAkvPKxyrv8mC85hQQwvZ6B/rwYnPi8bqelPEC2Vz0ikfc7XZB2O5JYjDybtRO9GwCMPcAxFj1PPM og9HI34PPeSM719+bs7R0SpPLr9N73tJJG8aZERPKFn27yPpE49hQ+VPUvm1jxeIRu8U7qFvTI9rzwMCq27kktOPJ0wLr2elQe958BNvRNvhD16ts08ItCMPN1r+jvkele8IwB2vDNE3bwXGpm9W/6pPfO4JT3043O9qWBHPf0nebydCwm96xAsPVeTFzyAaRU9sMOWvWCskDvidXi9TEXuPExqVLxYDmq9Tjq1vW7Mgb1qTaE9w5lkvaUo87xXQbY9qcUpvRTvwTp0iIY8T1FePdTt1ruv2T+9UPkpPAkvfTuS3pK9nkFYPPs3N70HZW49U9VVPXP+R709VpO96MPdvAbpuLzrrRk8lh5nveKohD0L9WA9mqDXO8Vjqzzl2gm87bUkPe0WhjydrjE8XgdrvZ7LFb366wM9TW2GPOyVfDztsLm8ec9vu0RLEL34nI89wAHFPFXLyjzyXNG8myjYvPp7wbxg+n+809w6PZBWNr2BQOo7+4t7PMpHjL2VEgI9TaYoPM 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 fu9p591uzQllD1060E9yNPSPJvQnb0yH8Y9e0D8vH3mtDypDLU8tZtLPVk9b72Ou928yRNvvVhhiL0KGwQ9L8E8PQr8BDzI7z89oJrPvTz/2b23Ux89WOlVPalK+DwdC2w9b64dvk/vIL1oimW8AIK1PaPzdD00Ss+7n3t5PcYoirvbC6i87tECvdK5WrvDRzy9gx67PHtW8zzFPlK9Uh+cOjwTWj0/scw9odA9vQdxKT3Luxm+cHWCPQSlfLwlnC87taK6PaJ9bDyNUyA8In39vRvU3ryOl4G9vkksPYZgSLwhSZ+7ZKBIPcSD773Xjo47imkkPBiFqT1TQG47ih9RPaVUkb22zIO5Z5tIvQQkdz1lePU9SERdPW6xCj2Jh6w8YiR4vb9tiL03iFM9upy5vfFjeL1yGKI995Z7vfSStLz1OwG9EP7kPbjiwz3Ccdg9R6r+vVK53ru/TFC84JGRPd26Lz4ncbQ86MF8PZ0sALy++pG9oEggvT/jFz3Cxeq9zyG1vM 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 QMtmzyOuVk8Wa9bvP5I+zxN7Ra9HE/lu5zfODuvEvU8ngJhPQxw9zw/DDq7YbxlvTW0/jzNtD65XNAHvZPdEj0770E9nzlPPO+B5jzbeja9S7ajvJcvpLyatuk7CFQqPU8Lqr3ByyM8Rv0evVEQlbzZVIc9vOpGvaGLeD3RQj+9n0vnPL3H9L0WSmG9gwRqPd7Jnj1DqCc8kcCNvEyyLTzOZhU9Pv+VPe+oqrwa4Qo+FJWfvcR/5Lv1Kpi9iHZEPDxOVD311B09AjFxvLh/jb3rIIm9+fqhuxssh7zhMXk9rPGTPdZ0xDy8ylW964kLPQAtHT1LJIw8JRwvPauqdj32FFa9b83xvOW6gTqzvco9JPk0vfYHBDwsOyy92ZkcPFLvjL2nn848ZvNku8otpD2vAvY9JnyUPeKvV72qzgw9c0rHPD6OgT3+ojA9wulTPYehwb2jddY8209vOyMcBb0EOXA9NW48vU2J6Dy8bAA+ZzGGPdm7I7zZaMM8gEDWvU3uajz/dM rq9gSUgvLfcETtZsJ69b1EcvcswuL2r55M9XAqcPXUeEz2nZju9ZaoPPFbwwzxfvpA9XGWlPDNx+T1wQ4O8hLiWPU4uYr1ErcO94FmCva/NvjudIYo70gEMO/Ktorzqqgq9VFquvM8nsTtoe2U72q86PZd5Hz30S6q6H9msvZcGLz2rVc27mB7TPfgIHb3FdTc97olLuz8yZ714EzK9pnY7u35nP70K1Nc8dTjxvN/5dr2OY8O89Ge8PDhKALtcULw79PTRvRU9k7xnpha9RilBvrlmVbx31fm80w8/PVa+dr2xgOC8o1DqPYLt6rwSF4K9TiHovBeilbz4ph+8CUx9PDzamTyYsDg9EGTcvVNle70eRu29x5oUvZ5Gmzz0Uv68LPNyvZFCR73ABse7L70QveyBlL1OhWA9VTaKPNB1w7xLwgK7BZHoPWZPez1WIEE9B9aoPTYZMLzBLSa+tSNVPDcG1r3wtty8oSSqvBjtU71ZeXC91MunvHycrL2E1Ea642VcvM 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 H73dTziAKK7LOt6OxASYr2XiH29tzvCOwiF0jtVMD+9zf1DukQCnrxs/zs9B//PveViLzpJr3I8diL+vDpybjzlwpU8ld7BPPTBkj0AVCG87YTUPNfsHL1auGo8QM7DvNGrYb2950C703GHPEyTWj1Zhiy8SIryPE/ENrzdj1a9uXOWvVumDDy+sik9s7+YvdqUC71KOhE9RmYwPP7oBj18w4088QJrPLwDJL1fh1y82dIbvGyA+7zbVIq8NpgWPdiOOj25Gn668YgEvTR3V72wXH28ZWvDvJuUlrt9kcK7UlsUOm+8rT09j289rzi4u6UuTT0Q+BM9r/DyvONWDzxu3GA8AgHOORHvLTzpYak9zkGFu+DqyryMs1m9ZHHbPNgylr3X+E+9CYkmvfnfmrxxptW8XhdaO1l9QT3wOQU96RQeva5WtL3Fjse9787EvIINij1UstA8Y4GBvHARLTse+AG883KwPFtg3byl7Cu7MsY5vZ647rzBZgE8hAjTvblMiDtzRM 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 cQiiTxFSF49jRxrvOUbvjwqNpE8j/gCvpBKQD3ThLs9TmeBvVswkDyKl+G7kC8zvDn2fjwbCzo93+snPUAkzbwUUPK8Jq08vQcNtDzEmN68PxcYPUga3Dz8CQE9/1YMvfnPmDxzASI81pQ6PT3rqTzGqVs85yygPV2o6LwB40693kAuvEFjKTyRcW29KPtzvJYAGj3RgoG8yN23PGFrij3k7BQ9hcIkPeyUJT3pMH69MnpwvG+err15QQu80TbVPIlZ2zzbPBg9K54oPaqUMb24pIS8tw+iuzKwXTxMv+S8DdJqvZXrKz3lLLO9GVf6vCM/aDuZYa28owSvvb+6QL3w3iO8k/WxvPT0djxZfVG8yGv8PLKgkbt1RZe9khsqvd+KMTwT0E89LBGTvHvonTx8YLK9ddKPvBdCi71pj8872VjEPDNp5DwIbhw8wK5bPLwSiz00qJY84TKoPRPmajwsrne8nuJrPSTsb72dCyM9+FxzPSi/gz1Hjvm8wFpOvfvm7rwXvM 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 foLqj3gSBA8onUTvfMDob0eVj6926lLPDUn3zwcoiA8wEbgPEnqZD1qrqy98HM6vb1QIjyBdDm9RCVWPT9YZT0nrE49C2vuvOGxLL0jMym9FxNpPTuPAz0rBwm824ejPGjWMLzsSRo9CH9Ru7EuIT1Fvay9g00cPaFuar0nCK49KEGNPXgKOz08mgg9VUaUvXkjbr0sxBu8dyhUPXUn8bum3Qa9I3DDPCvDOb3ubP28AtPSPLnt4j3dQ1C9UGUbO1rtYr2Er+M745SdvXspqbtgKh8+GrPyvLF9Rb1c7aC9ULKuvRdcSb1ZSJg8sCWxvB7VbT1UR8E7QmzyvYJ22zu356U8TcMBPpepAr3GOKo9gbFwvYlhkbx72aW9BiAfu2O5aj3bMPM8wlK1PIwm97vJh1U9oOQePC/gnzyqIQW9FuoVPb9KTz1h+qm98Yf6PNzYcb1NoZ89lfoavWjULj1JoME6sy1HvQmYMT0EYTO9BcxFPaJlCz2gkzM9vC9svUEzlDxcMM 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 jo9uIYbPH87Gj0yj2y9KczqvBSpzLyyVnw8pmahPMQpfTwRLQW80jscPbO/2DwUyjI9+N03vIzLdL0pOxq9LffxPNg3oD2+EoW8s//EvM6D8DpZO8K99o26vI/6RjwUYBo9l1UBvZbd6TzUl625jCuZvT/iJD02Ds082DDCPH8OyzxqhfS8wAGXPHzTN70L/SM9VfiyPX7BEz1QR9278QMKvehywzwWcwq8AFVSvZC4tbyawpm9thb6vPvpmD3sZDE9qscnvOI+b7sIn5A9hVIavHbMbL3rlrC8caEivRhVij0lKDM9UKG3vFMPqTv3NGG7h6SLvQrnzTyEEgK4juoNvCuJsD3Au5+9SYMxPfE3bL1ozli8F4yAu4ZvXT2gnm29MpIOPEzAj73C4BC9HzhfPQhexj06zau8/xglO418ZzxrIFa80NY+vSBn7DwY55s5q1VWvHxWRL0OrQy5flX0vXQ+Vj1JXPU9FQDZu1mYMr3Eg4e9WcFgvRjI2r2CGMa80pfXPM 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 tY8lPA6PopU4b1iCIW8gfmtvWXblTteoiu+W8mYvvkDur3juTO8/PAiPj2ZM7yJrz++77WcPQa/Lr5ENg++zlJXvMH9/7oCOV49AeTlPSYUiL1fFaA9cXqvvcaIwT0NIye+XrjmPZ/ViL434Fc9RJRWvWU5HT72aRk+yZLSu6CI3r3VvrC8XI8UvrsGjb64igc+X8ZVOawKJT2UdcI9N12uvbahVD0IWra9nZU6Pb6ZLL38qQc+m+1nvsZC1rrQKLq9JWgIPtwC4z3DUFS8a9djveH1qTziCjC+0tguvkHxkDyG/fI8Y6mrPTucnbx5zO295YMIPhNvlrzwgiQ9m/cQvYFnfT3F2RC+xPBDvhcc972hNJE9p14APi3TerzouQi+YX+KO0Hjx70yWRC+o3/BPey4rL0VP4E8dQa7PQkj1L2Y1fI9m08WvVwvij2f0qK9IcwKParZeL484BI9dNvDvU+Qiz0JSCs+6wrSPLCUeb2lxmi8leEgvh60cr5riS0+IoJFuM 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 gy+csu8vY/mPL2yjFy8cIBePdGzSj1JzH49iQFrvTyu1zx1oEC+QsKLPa9mTL5c/5M9UBwJPEFfoLxRJuc91iSoPZNO1DpWN6S8ewuuvTcf+72vyp89cPd3vTIaFD2Z5j09EeoPvRjKlzx3VOu8jQhbvdiTh7323aA9m/7nvV8QvTxGQPG7V7S4PTVxJz03x0q9blWRvIEDCb2SNfe8ELpjPS0iNjy5weA7bFQePfotNb1YpBO9CpGrPfUpiL30X2k8smj3vSAwlT1T78W9L1JovhBHwL2SUkI81+GcPcFuGr2GZ/m9TNkrPThNy7w8tLy9mjCivBZAZL17dcw9H3+HPUgxob3apYc9Az0XvcJgqrvRQh++eMayPfllDb5kztg9SscbOqC4uj3xJBQ9OXLUPE2pMb0ojqy7yEqPvUVzF753vRM9b8HAPLkKCj1pLl67UKdyveEcMz38S9A8gOG2PK25MDxYXOA9XB+QvXLOH706f6m9hCoTPhwdSz3fX2i9AQRQvM 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 bY9Hg0svfkkiLxsjxw81jtzvb1rA75lWSy+Ca0evUTfuT2Rbrw8ab5zPafuEb1FviK9vKTzPVTsUj3Pqcs9wsqIPfg0Br7vDC09eA6ovSaDuTxX0YA8gprMvRrwpDqZ/5O8eHt2vOK4070hLTm8HYkRvPYZZbykxSa8ts87PbBZw72iwAW9jR/SvKBt2TyAdxE9D3WmvKHaZrz2TvK8NIbwvD0J+z1oG8A7DMVlvNm5vrywN2m9t3/yvbPMpT0Ao149fBjdPBuPAj3+nqQ71XodvluRk7ydmHY9tO3GuVS9S7sUkS09W+jGvPUrkzyw66M9rjBIvf8TMLxnsNm73GmMOtFIH70AFhO+X3x7Pbiylj2vIaE9mp0fPQpBH72tDvO9j1+JPO3jM7tEkkM9LRsaPcd2sb1o/T090Sjwvc9Itz0mfkg9bGDyvW/yXLx6fTC9qWUGuzafGrwwX6m7bHSuPS08dj09ZZu8C0c8vRGvd73Cy8M8S9ChPcW2zT3H8ry899GevM 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 7s8TK0NOk0+/bxu8bE4b90rPSCjfb2OJM66IktcvO4xfD0Agme8cjzzPLFjRj1KHO487ZtSvcfyfb1TEI080Uc8Oo6IsbxRdGg7lsIlPe0dI73gvxW8lpJbPSafeT2Bbkc93Z96PApnLTz6c608mFGnvJ3virtncCY9uI6XPB8bn7x1hLY8/SKiul2hLr03nxO9hUNHPQj11LzAQCu9JFUSu4iaab2km787i2VdPYLjZzsYAWg9+cmBvZ3oiTum7Z48zTENvRFA2jvgrfw64SvcPD4zxzsArAK9j229PGYi2Lyfpv48dvRjvf/jpLwyZcG7jPcmPaHXH71z47k8D0gaPdKOpbzQ+GQ9/LA1PVAlwTyI8i49eimAvTZBMDrvjjK9sYiIveFtz7sRHKw8GkaUvdVOYz2ofU48zpumvEH/DDyqfNa8fKYPPZDEhDzEWGU9l5mnvX15qjuSUBI97WshvDak4TyyMI69gGKHvQUDHjx+/KY82CQ6vKpVKT1lE7u9GiZUPM 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 cU9TjYYveE/Jz14oNq9qeeRvYmdcL0Q1QG8vpMzPXWITr0mGbQ9EIfnPAezdT5zgjk+Ow+tPQmj3LxsmB6+J+uJPT252DzjLGC9hjRPvLe3Fj6zxGe920VgPQESvr11JuA8YfTsvCelTT29PcQ9r4EjvYTkDT7VKI49A2n4PKeUkz0jO7o9p4oZOzeQ3r1SMio7pOGcO1s/oLsCiaQ7rwERPo9wwb2Uzc49fIqqO0M9Nb2TVGA8LMtLPW2877z+JUO9CkcAvQFx7rwzQr09e/U4vS7nXLx9f069ckc4Pb1b7bz1b4c7LzsNveGOpLzY6d27qlKRvWLxMj1vMB69m+kUPWUbFzyIkek71QYpPUrwoL3yka+8ob93vclU9j0WITY+NKDWPVm6XT3ldK69IR70vDC8Iz1tIYe9P/IrPX71rj2I33I7v3wcvSb32L0XwvO825o8ve+0HD38LH89ONSLvJ6OnDzXFds9Ju0nPQW7bz1Rcyw8npFsPTJ7HL1HIgS9qAvFPM 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 DQjNbxXtWm9fyIpvd/0J73b66O7mnAfPZmiKzsCnxm91HtRvWQXmTwEUny9gT/muwBhHr0+zYA8h500veV2SL3XcSm9asCsPIuu3jwfHQo96akNPRn+nLw7sSa9gYr6O/I/g72KIGg987MUPaiRX73v/IQ87M9tu3VnWjvP0RM9YGMiPcacBz3Spe+8mZA8vbhpVLxoazK8OfaSvBdIhj3sPHK8CjrIvOsY77yegFu9tehXPZRO1TzZznU9OkiovdjDVT2+Pns9NLi4O4AxGL1ojdy8xQ89vRAyNb301ym8Im5Nvco5oby5WM28KYy8PSAoD72qRZu7Zb1yvT0cqL06aMo7SHJ5PQAydD1tqju9w8zLvNbpOzy1LCW9OCX2POcpKL0sFIY9Qah3PLwTHDx4Phy9KSaovDIBoLzDRYg9E/OHuyLAEjxm0mS8SMhbPaSaET36gxQ9TWDXuwh0zrzIOi09Fc8UPQiTgjxGiT886B2yvWkQH7vkCqM7hLK3uhHUPj03wM 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 G7JjTwsRsy7oKdqPb/yLj2Qpks9IdmQPL1HX7wMIB26cyjSO6JLBT1UI9m8wFsevQ4147wDnzy8tYsHvPnU4Ly7AKC7+BkmPTmJwLyecPu89RjEvRfRhDw+GSs8q+H4Oz7uEjxOMSa8YiUgPRt0PLxu3S67271/PZ19X7wCf5q9SBRKPZqv7zvcEBw9ykf4vCtmGb23jm+8hBofvVQAErwa7ki9SRCQPFFOEzw44W08b+NivM63orzVc3o8Z+BNvYk1IT0XzaK71cZmPDZGfzsATSa9lM+UO/mHJb2bAhm96DmUu9Aqoj1wFAG9GRqGO5NXGb0C5Z88pE1HPXlPqrtVcxA9NPKQPJlWSboDRT48GGNXPYkQlbwZ9wQ9l5QNuwpZED18mRS9f8+QvfKF4ztTVHa82xRrPWyJzrxovGq9AkHmvdnwHr0bZ3c9bZATve7ymDz3Vc698B/fPOqgHb03ARc9qXxrO2Phgj3KzUy8BEBJPQikVD22etc8jS/6Ozc3K705xM zW8Xc3/vB1ZSb3Cxo291lfuPLXQY7vkPD691HgsvGmBpb0gzcc69rBDvSTdMj3TtZm8h4YlPYYoCT1sGqk7hccsPeWB+LwolQw8gV1AvVbHdT0dHXC9SLI3vRKwQj08Gq48s81VPZxdtzygjMu8pvJfvDfhHD2kWo69fVRiPF9iKLxYCMe7/Sw6vRrSGz1GZau9b3rZvP6w5zww4yq97XvAvEA5zb15d2W9Q7xyvSEO0Lzm3+w8M6RSPai91DzdCiO9kSEvOySE+Lzy8BW9D8WDO0E51rupsIG8p46FvMM1yDzNYSw96sHPO0pu3Lvaov68i7c9uqKzmjx4INe8TWDSu249wjz819q8ql8zPUdIXb2emBg9PyUqvW+/4DyW1cC9M2YVPfWQKz2NReW8rBWZPbklIj0dRS48HBbrvA/K7bv0GC+90LxevW5sMjsebC28Yc2PO/JLizw/FyW94bFCPATa+bwktPs50NXhO2KKXLx7P8U8nk3RuzvHE7w+GY+9xOF0OM 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 ZMGEjv9E0095Y2OvYwbGjwyyas9KKvuuof5qT16IAQ9HvsAPOoiUDwLkN88G+kWO8pBub130YM8LEtPPT8afb2/xoc8yRiJPTTBH7x5H5e8bLULvfzytbxIpZI8Kzn6vIyorzwNrps8Z4eqPPzB6TyrvFK9fRBcvaa/Rb2Sc3Q8RtgrPFWYQb2W2iG9+r+bvU7NDTzMDye9TZWvPL2jmT3jEwi9aahlPUb2Qb0xgA+9cd0YvbJr5bpwarA7R4NSPMBD57koFic8/WSUvSbsGj0en3Q9QME3Pe96wr3F7oO9y1n6O7Cvbb2RIn29UqN9PBw+Vb16H4k9HIGLvQgloTpwBQW9bqJ5Pam66jzVpig9HrSUvbSqzDxwb3G9kxjaPLckML0P7OW8JIniu4BEY71jKUM95AOdvP4TkrxrToy7OQBBPa6KrDxkgGm89XyRPcnhSTzYQjE9sPaLvbrztTx8e4w9gCSovW8Ggr3BW968XYAkvTWozTwIfI68HCE1PQ11kjsZoM 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 dpOY7sRjce8dit6vPzpxTp4D+m8slhRPXY6PjzDUj69zobOvPxFIT2Bb+M8IQFgOwy9Zj1mNhU9UdmUvGbNIrxyJom92qfuOzzP1D1z1Fc8lWvFPIeB8L38ox697cWDvNQZaDsPVWs909DmPDE79byIw4u9oYerPUTsUT04BLY8JkutPUTDJbyMp9y8x0akvcrfTD1Xz4Q9AL+TPWlfAL1Ak209MgDrvRvWlL2iFgK96nWgvM0GTT07tDM9uvVAvO5B+r0dpWA9GWUOPd5pCbvMbQM9T/idPUpls71VoIe9bte2vRGTWjznu5U8SgLwvYKvDD0pd+G9TG1QvRzkJD2mvQG97jDsvHuD+zw2soC8uPe2vPmgMT3T7Me8+kSJPOgPqD0A3rQ8cBLqu9vG07xF2s+9DfMRPY3PhDtHhrI8UmWxPLbtXr2ZOIC92nUqPX766Dt2KLY9WIqQPXy817x0fOG8IO/2OyHCfzt1zoq80/WQPdhVAL1P4bq8l5oqvFSVDL1Z8M 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 WsSQb2Ry1c9xk36PM5xsD1TXuK9wU+cvHmMqrzbUgk8lFiOOz2S67xy+gK9DITfPDVaTL3ss589Z+c0OiGKZz1BGxA84kc8vUEkETyhZ6Y8+2QhuzOgcD2+Et87Qa4EvRZvQjzCt5m92s0xvFrEEL1lR+m9tdfpuqkAazvlI9+8k9AJvOfCsrt0k5o6QxIRvSsPLr3Ngw494X6vPUy9prohZKm8uT8EPbTMmzy2Mws9MZGsPI+Dcr2l6o29nF/iPJo1JL2yd0896bo5PEsbHz18M6q9zA+TPepchLwQ72g8yVpavGTAmLytn7I9cJqtPVyeC72yEbc977zJPPY+iTxr/lC9m0bAu/6ahrtIW0Q9KZzePPukGT3eicy8aeYBPgW+Oz03u789FoioPbNso7pduck7bVvhvKHibT0cLky8tK8RvVTEeT3EQpg9MfqpvP/xj7owjUu9HDBHvDW5k71nDI69l6RTPXhdBj1FnhI9VojQvMzZ0zusWUw9ZR3RPOuZgT39hM 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 oK8IHqcvL031ztOeIw7WGifPfMQIDzhSR49+exIPX3jQ7xVZjK7vrhfPefk5jxBUEQ846uDO0GzU71+Q+08B7GEu+VoQz3cjQg8/lEQvcSHojrBxKW9cqlrvIzDXzwr4qY93pGqvSYgmLzFZDE8av+SvTBx+DyZVZw76223PKvMPj2HWtO9e0SBvccCej2SWjE7NzRoPem2kb1oWS29j2JkvbxX2Dp4Q5s92JKAvId5/z0p8rW7jRD1vAAd4j2CwNc8ZaXcPaBiQDzoTiO8rARZPXOrpL3me229vFRWPLgQ1rwscXE9y438vN3lejzHASu9WxcOPQ97pz3CQFW9XNU9POeCdbxz/am69dG2urcHwzuLw0I9gYZzvLM5wzwXeb473JPRvDdV8TzdHq49t3gBvIUWLT2vEsC8pIKEO/GNaD00INa8h2BGPUTKybwhEK47g/c8vd1AVrxG4SI7Gus4vV4C2joa1Ii8IcRFPXMt5DwdCQu9TSIbvSHJjz0bbfg8yjR3PM 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 Or9jTy6wiG71RC2O/zvjT2Pr4K8vu9aPCIEMD1WWlU9O87PvC+2HDzR7j+9OG7YPKhzczw8y7C90lIGu0Hk3LwcNAC9bkAIvZriIj2mg1C8i1QnvTWZqzyieB+90c6SPfv6YTxbS569ZldhPeUkb7wJqVQ94iTyPL5HKL2OKPS8fV86Pf8OdjxK76a8baybPApxXrwYdVC98GGAvFtS+jwtNyc9KodRPQY9ELxwyKc8DJkHPefObr3gb8s7DgcOPHAO0z3iyLy94tulvYdNDTywXR+9EEJ5ud+lfT2pUFW9Yk3kPVMm97xpVgs9MEtovNJ/jDyZ6E+8POz5vIndkzzE9aA9cDpcvdOoKjwV5pc9rbJ1vOoZMz0qc1Y8enoDPCwZDL2KDza9DWxiPecKLL0bdRg9ki2xu7ZESD3tfF07efldvSx1lzso9Rm8OFiuvJeT37s9sO29OJCZPTq5QD1a1ew8GsMQvd4Tm73uBG28h6F/vcmW5zzL/a09f/IxPcOYez38IM 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 cbuLDyvt449L7c/Pf0TaD3iNXA8ldKSPOhTeTyT2Yi9ZOR2vR/Y0rzhTuE8q60nvTjhrz34KI+8dE3VPXFhbT0vmK68ED+7vXbRgTztH+S8pcaeOSLZuz2YkvY8k/s4PBBmGz3epkO8GQi0PFISE72cWOW8hRqhvFVStrzLTog9SbAmvXq1Ez2NBzy8zDiSOzL9OT1xuBu9tVv1O5IrUbyTQsO7vgD9PagbDT1u+Dc9E7s3PTRx3LxKXDQ9JO4ovXIvETqgBYW8ad/kvLWNa73ldM27Q/eWPM0O7TzOQx69XItAPAiP5L0Jj8u7bEJHPbhCRz3/fqU8KvNsPdzETb09S1Q8PgeYveO7ED3xKee7slyIvVsqtL2YOny9s+I4PPe1+DxuaBK99mrAPR2vlj1IRJA7GhaGvROyPb0zPEg8IkCsPQL5kT0PjVM8AjBwPRo727wc3vu8236CPU+0VL3VRBu9Bz7wvLfytrwAKFq8OxAEPFq7hry96IQ73NmfOxNynjyxlM 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 d8zo70DMBE9yNImvGPhiL0jg1Q9ldqePcW6dT1p+Ki9qBsTPQC2v73l5Lg9RCHqPRI6hT2YIpc9jndzPXtl67xBPPE7QTyOvWZgIz2mXgI9bKSDvch0gLw/3ms9x2zHvBnn9D2BFh094++AvJQy17x73mi9e1RoPHxmhzy8wtc9zPfRvGAilD0QwWi87EnuvOs8hD3I/Hq9wrGXvR2TM70smtk8aBw6va3iRjy2xiS+DUF0PQaVzTuLxEi90BWdvcFIib0lqoe8aFSwPet/+z3vNC67IHUzPRPN9DtpOXS9tdZ2PWalir1jbIi8IJbCNr4dZ7ypNiu9fWQbPf84/b1EpjY9hhavPTMpQr2ajlO834ASu98et70lROK79JbBPeUfWr3yN6c9Yy6aPQhhYj0G+Qc9M16VvXGbpjy9eLe8awF5vZqOv7yJd4g9I3cgvBTk1jyXPsc85bhRPbreeruAvzQ8fRMFPeZ7CTxJepM9md61vV1puj25Sgc9FtPJvcJY77umrM 9K7xPN9vfLfZryzRRW9W/7qvE7HL7t/ZMy98cAoPUR7fj1/Gpe7hBq8vVqALr18C7K7O8qQPBIu5T1zGxa9X980PBxF9TohAdA8j5MqPPPQdb0hsBc8XKPAvDuw2rwSqNg8lj5TPYgPrrrYo9i8O9i/PLXSjbwjtWm9sDdLPXbhj7tDaW686uwIPlAEwbvKSWE92FiOPbufr7wApaA8vYWcvTRdFT1X+pc7ZSdxvStIALw5wp08ufV6ve8tIT3Cvb88h0ZgvTi5Dj0Ihg29HaL4PEGeI733am49oNeqvaGYtz3mjGE9Qtr4On34WD1PLIy97xh5u9OXo7u2U8i9fCS4O+98ZD2sYeM8JOpAvTJdM71a5669J3mMOyT7ID11VOy86ShTvbTFJj04Q6C9UH8NPUh5iT0josC8Xkk+PaHmn7sc9YI9aqGlPC3z8b0gcx489HyXPHitHT2wV8y7ek4HveIudr2cYGU8ViQkPFWuvjx5g9c8ro9pPAitAT1HZWI8tO4uvM 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 ci8nK3nvMgObb0GVrS8hGsJO757njv0ZQI9N7nIPKxOnr0DlGY8N1WevJFjyj0I4cu82wkbvPKZdj0Jgh+9qYjePANwMT0g7nw9T2QlvcQMAj04zV68xLRQvWbMx7zVKnM8C7xkvFSuxzzVVtU8qRuyvC4LM72GruS8gzesPHPUprxxlyA91tg3O9Pp3bx1Zfa9lJyMvRmZDTwu7Oo7bEQXvTa2yL0YFB69W7iCvXsrbz2BjEc9ZRRZPYxss7xWOba8nKISPVqF67xPHAM9Lt99u6y/Nj2W56C9qtTMuzEjbL3MVte6vviBPFjTpTzt/P078o1ZvVcjUb2Zdq67b5JjO9H0yzyYZNi8kBe+Ov8Or71kqgs8vsxvvbLqtz2e6Wi8G12yPI5pbj06mZE8ElGzO0WQj7ykAIo9y77BPL6reD1rjou9aOIMPM1ART2HGPM8lrRFPY+UVDwrpxm9vvGfugTSVr0uune99T6HPRBvfLxZB8i8T0yVPACWuDwhr2y9sQICvM 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 2499pIfvVi6tz398To8ziIbvRKogb0MpKG9FdNavVDFGT2KiKk9MkvGvbPyC72QaR09C6vNvT8M0j2xRPY8yUdLvK3B2rxZ6Ka8vq3UvL6iBbw/d269vCoXPUI7Krv2LGI8GCfxvZcixztVqFY9jnEoOonntz1R3b48kS+zvBobEjnUYF282ZC3PcHhpDw7rfa71xkhPNw4k72aOkO9nDXavKDKLrwcpCk98ja6vN2KxLzjMaK9L+VxvCw0aD3y2qu8cPqFPPkyLr2VT4G8RC+7PIaY0bxi8E689FFAPflqYj2QQ+07GpucvS1RuLztc5O84llivYiX3j2uF0U8JfCYvCQOuDvS4LK9pGRfO/g8YT3c9yI9XOnpvcAkUzoHZN88vMIUvdK0FT0s9I09+BkdPb94mr33D++9aEdfvbj/pb06DSS8+HxJPcB7Aj1NGny9QcOTvTkqgDzSHCU95kRUPb1JxT0Wiju9lOIQvcYEwDwa6fk8UUeWPQbRqrt0XSc9CPs/vM 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 rE85myDvW6ns7xFnCM9Bt++vZ2gF73vrmG9FBn8POwCX7x55zu9FxsnvVBQmL0IRe+8Y2bFvHmmoz1WTfU6XzdDPG55yjy8U9a8A+/PPGmTTrzomAS7Eqv/OUZZ0LteX9K9RP6NvWO57byG92k9ngPAPGydibzGivm851omvJL3EjxbVSk9qdcWvZKAlD2ZEa681FF5vYuAVr1drqa8qHkTPTEDMr0HEI+7EhvfPc8turuigqy9l3izvDu1gD3iZEk9Bw73u35o8zqGBci8zKWZOgP3yD2WEWe9ljNWvcJ6E71QXTi9u6A8vSNHlL39sKI83kyWvb2Kir1LeRM+3awmvaNdwL12Gqq9DzlaPa1Uzz12N3U8qi8+vEV+xzvuWpK8VxQ/PIs1dr1SsHk9/BUUvWA2oL2jPqO96EQvvDK09buaaHK9AMyDvR1rtTzrtPW7CwqJvfoIjzxLWzi9yhqXPZ32WT0yhqS6BOB4vKOrC72jlM47S1ASvcDiq7xA2Z697keZvM 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 LS9G25nvxwcbL8PwCS7nwImPmzEGjw+yrw9G6G6PZVxLb0rPhQ9/AbePgCohL87eOQ94XeHvyYkOD+1pK6+8Gl8P5IVm78LW3+/chyEP4lAoj/Q+46/5GqEv1IGIj8bUY6/UhJOPnUhdD8ahyU/cl+av/2b9r5fllM/J+RXP5WHgb9ysf6+N5xSvt6GgD9nsxW83F9Rv9nwE7z7B7Y9Y5mzvf1aLTo=", "training_traits": {"structure_gen": "Triangle", "n_layers": 6, "max_nodes": 20, "activation_func": "Tanh", "epoch_num": 5}, "classes_name": ["Cryptoadz", "Cryptopunks", "Moonbirds", "Nouns"]},m=25,b=50,y=59+11/12,w=59+11.5/12,v=60;function z(e,t){const n=Math.log(1-t)/Math.log(1-e);return e=>M 1-Math.pow(1-e,n)}class V{constructor(e,t,n){const{model:r,inputDim:i}=j(t,n);this.model=r,this.inputDim=i,this.iteration=0,this.stage=0;const o=new Date(parseInt(e.birthYear),0,1).getTime(),a=new Date(parseInt(e.birthYear)+1,0,1).getTime();this.birthDate=new Date(Math.floor((o+a)/2));const l=zr.filter((t=>t[0]==e.lifeCycle))[0][2];this.growSpeed=365/l,this.cycleLength=60*l*24*3600*1e3,this.growthFunc=z(.4,.8)}updateAge(e){const t=(e.getTime()-this.birthDate.getTime())/31536e6*this.growSpeed;this.iteration=Math.floM or(t/60);const n=t-60*this.iteration;let r;this.age=n;let i,o=0;if(n<25){let e=map(n,0,25,0,1);o=this.growthFunc(e),r=(25-n)/60,this.stage=1,this.stageRatio=map(n,0,25,0,1)}else n<50?(o=1,r=(50-n)/60,this.stage=2,this.stageRatio=map(n,25,50,0,1)):n<y?(o=map(n,50,y,1,0),r=(y-n)/60,this.stage=3,this.stageRatio=map(n,50,y,0,1)):n<w?(o=0,r=(w-n)/60,this.stage=4,this.stageRatio=map(n,y,w,0,1)):n<60&&(o=0,r=(60-n)/60,this.stage=5,this.stageRatio=map(n,w,60,0,1));n<50?i=map(n,0,50,0,780/880):n<w?i=map(n,50,w,780/880,800/8M 80):n<60&&(i=map(n,w,60,800/880,1)),this.nextStateTimestamp=Math.round(e.getTime()+this.cycleLength*r),this.statePercentage=round(100*i);let a=(25-n)/60;a<0&&(a+=1),this.nextStableTimestamp=Math.round(e.getTime()+this.cycleLength*a),this.growth=o,this.model.updateNeurons(o,this.iteration)}getBrainStatus(){return{totalNeurons:this.model.getTotalNeurons(),neuronsLife:this.model.getNeuronsLife(),stage:this.stage,inputDim:this.inputDim,stageRatio:this.stageRatio,age:this.age,growth:this.growth,nextStateTimestamp:this.nM extStateTimestamp,nextStableTimestamp:this.nextStableTimestamp,rebirthCount:max(this.iteration,0),statePercentage:this.statePercentage}}classifyImage(e){const t=new G(e,1,e.length);return this.model.forward(t).mat[0]}}class M{constructor(e,t,n,r,i){this.p=e,this.v=t,this.size=n,this.shape=i,this.col=r}getRadius(){return 1==Oe?1*this.size/2:2==Oe?7*this.size/16:3==Oe||4==Oe?4*this.size/7:0}update(){this.p.add(this.v)}draw(e,t,n,r){const i=this.p.x*r,o=this.p.y*r,a=this.size*r,{col:l,shape:s}=this;let h,c;1==n?h=c=l:M 2==n?(h=dr(t,1),c=l):(h=dr(t,0),c=dr(l,1));e.stroke(dr(c,map(1,0,1,.25,1))),e.fill(dr(h,map(1,0,1,.15,1))),3==n&&e.fill(dr(h,0)),1==s?e.ellipse(i,o,a,a):2==s?e.rect(i,o,7*a/8,7*a/8):3==s&&(e.beginShape(),e.vertex(i-4*a/7,o),e.vertex(i,o-4*a/7),e.vertex(i+4*a/7,o),e.vertex(i,o+4*a/7),e.endShape(CLOSE))}}class E{constructor(e,t,n,r,i,o,a){this.center=e,this.len=t,this.angle=n,this.v=r,this.angV=i,this.c1=o,this.c2=a}getEndpoints(){const e=createVector(this.len/2*cos(this.angle),this.len/2*sin(this.angle));return[VectM or.add(this.center,e),Vector.sub(this.center,e)]}update(){this.center.add(this.v),this.angle+=this.angV}draw(e,t){const[n,r]=this.getEndpoints(),i=n.x*t,o=n.y*t,a=r.x*t,l=r.y*t,s=this.c1,h=this.c2;var c=e.drawingContext.createLinearGradient(i,o,a,l);c.addColorStop(0,s),c.addColorStop(1,h),e.drawingContext.strokeStyle=c,e.drawingContext.globalAlpha=1,e.line(i,o,a,l),e.drawingContext.globalAlpha=1}}function S(e,t){const n=random(TAU),r=random(e,t);return createVector(r*cos(n),r*sin(n))}class R{constructor(e,t,n,r,i){M this.wall=n,this.maxR=i;const o=t.length;this.nodes=[];for(let a=0;a<o;++a){const o=[],l=.25*t[a];for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),l=S(.02*i,.05*i),s=random(10,25)*i;o.push(new M(t,l,s,e[a],r))}this.nodes.push(o)}const a=A(e);a.unshift(e[0]),a.push(e[e.length-1]),this.lines=[];for(let e=0;e<=o;++e){const r=[],l=(0==e?1:t[e-1])*(e==o?1:t[e])*1.5;for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),o=random(5*i,10*i),lM =random(TAU),s=S(.02*i,.05*i),h=random(2e-4,.001);r.push(new E(t,o,l,s,h,a[e],a[e+1]))}this.lines.push(r)}}reflectNode(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,{p:o,v:a}=e,l=e.getRadius();(o.x-l<t&&a.x<0||o.x+l>r&&a.x>0)&&(a.x=-a.x),(o.y-l<n&&a.y<0||o.y+l>i&&a.y>0)&&(a.y=-a.y)}reflectLine(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,[o,a]=e.getEndpoints(),l=e.v;(min(o.x,a.x)<t&&l.x<0||max(o.x,a.x)>r&&l.x>0)&&(l.x=-l.x),(min(o.y,a.y)<n&&l.y<0||max(o.y,a.y)>i&&l.y>0)&&(l.y=-l.y)}update(){for(conM st e of this.lines)for(const t of e)t.update(),this.reflectLine(t);for(const e of this.nodes)for(const t of e)t.update(),this.reflectNode(t)}draw(e,t,n,r,i){const o=i/this.maxR;for(const t of this.lines){const n=t.length*r;for(let r=0;r<n;++r)t[r].draw(e,o)}for(const i of this.nodes){const a=i.length*r;for(let r=0;r<a;++r)i[r].draw(e,t,n,o)}}}function I(e,t){re(e),e.fill(0),e.rect(0,0,500,500),ie(e),e.noStroke(),e.fill(dr(cr("#000000"),.5)),e.push(),e.translate(250,250),e.scale(t),e.translate(-250,-250),e.beginShapM e(),e.vertex(235.2,24.9),e.bezierVertex(215,24.6,185,11.4,164.8,11),e.bezierVertex(147.2,10.7,129.3,10.4,112.2,14.7),e.bezierVertex(95.1,19,78.5,28.5,69.6,43.8),e.bezierVertex(57.699,64.199,61.599,90.199,70.199,112.2),e.bezierVertex(78.799,134.2,91.6,154.6,97.199,177.5),e.bezierVertex(102.499,199.2,100.899,222.5,92.799,243.2),e.bezierVertex(83,268,64.6,288.3,48.9,310),e.bezierVertex(33.2,331.7,24.5,337.5,26.599,364.1),e.bezierVertex(28.2,384.1,61.399,404.2,75.7,418.3),e.bezierVertex(90,432.4,73.7,488.2,91.9,496.7),M e.bezierVertex(124.2,511.6,159,472.5,194.3,468.1),e.bezierVertex(211.6,465.9,267.4,501.5,283.9,495.9),e.bezierVertex(340.7,476.7,298.599,428.9,355.4,409.7),e.bezierVertex(370.799,404.5,454.5,407.6,464.4,394.8),e.bezierVertex(478.599,376.3,474.7,349.3,464.299,328.4),e.bezierVertex(453.9,307.5,438.099,289.5,428.699,268.2),e.bezierVertex(412,230,419,182.6,446.1,150.9),e.bezierVertex(449.7,146.7,453.6,142.7,455.8,137.6),e.bezierVertex(459.4,129.299,457.5,119.6,454.8,111),e.bezierVertex(443.2,73.4,417.3,40.4,383.6,20.29M 9),e.bezierVertex(358.1,5,343.2,-.4,313.5,0),e.bezierVertex(287.5,.4,261.6,25.4,235.2,24.9),e.endShape(),e.pop()}function C(e,t,n,r,i,o){let a,l,s;re(t),t.fill(0),t.rect(0,0,500,500),ie(t),t.noStroke(),t.fill(dr(n,.5)),1==i?(l=0,s=25,a=map(o,0,25,500,0)):a=0,t.rect(0,a,500,500),e.noStroke(),e.fill(r),e.rect(0,0,500,500),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVM ertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7M ,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.M 8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3)M ,e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),e.fill(n),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9)M ,e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,M 58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,M 406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),re(e),e.fill(r),e.beginShape(),e.vertex(184.3,473.2),e.bezierVertex(164,473.2,144.7,462.099,134,444.3),e.bezierVertex(131.7,440.5,129.1,438.5,125,437.1),e.bezierVertex(97.3,428.1,8M 0.5,400.6,85.2,371.8),e.bezierVertex(86.3,365.1,85.8,364.1,79.9,361.2),e.bezierVertex(57.2,349.8,46.2,323.3,54.3,299.7),e.bezierVertex(54.7,298.599,55.1,297.7,55.5,296.9),e.bezierVertex(55.6,296.599,55.8,296.4,55.9,296.099),e.vertex(57.9,291.499),e.vertex(62.5,293.599),e.bezierVertex(64.9,294.7,67.3,295.799,69.5,296.9),e.bezierVertex(74.5,299.299,79.1,301.599,83.9,303.099),e.bezierVertex(89.8,304.9,96.5,305.499,102.7,305.9),e.bezierVertex(102.8,305.9,102.9,305.9,103,305.9),e.bezierVertex(106.6,305.9,108.9,302.799,1M 09,299.799),e.bezierVertex(109.1,296.199,106.6,293.4,102.7,292.799),e.bezierVertex(101.3,292.599,99.9,292.4,98.4,292.299),e.bezierVertex(94.3,291.799,90.1,291.299,86,289.9),e.bezierVertex(68.9,284,56.5,270.2,52.7,252.799),e.bezierVertex(48.9,235.499,54.5,217.7,67.6,205.299),e.bezierVertex(71.9,201.299,72.7,198.1,70.8,192.399),e.bezierVertex(64.2,172.2,68.8,153.99,84.2,139.599),e.bezierVertex(94.2,130.199,105.5,125.399,117.8,125.399),e.bezierVertex(124.3,125.399,131.1,126.799,137.8,129.599),e.bezierVertex(157,137.39M 9,167.9,152.799,169.4,173.99),e.vertex(169.4,174.399),e.bezierVertex(169.5,175.899,169.6,177.2,169.9,178.299),e.bezierVertex(170.7,181.2,173.2,183.2,176.1,183.2),e.bezierVertex(176.299,183.2,176.5,183.2,176.7,183.2),e.bezierVertex(180.1,182.899,182.6,180.299,182.7,177),e.bezierVertex(183.1,162,178.299,148.2,168.399,136.1),e.bezierVertex(158.2,123.5,144.899,115.8,128.799,113.199),e.bezierVertex(123.499,112.299,120.399,109.799,118.899,104.99),e.bezierVertex(113.899,89.699,120.699,72.299,134.899,64.499),e.bezierVertexM (139.99,61.699,145.799,60.199,151.7,60.199),e.bezierVertex(162.2,60.199,171.899,64.799,178.1,72.699),e.bezierVertex(179.6,74.6,180.799,76.6,181.9,78.499),e.vertex(182.2,79.099),e.bezierVertex(183.2,80.699,185.2,83.299,188.4,83.299),e.bezierVertex(189.5,83.299,190.6,82.99,191.7,82.399),e.bezierVertex(195.1,80.599,196,76.99,194,72.799),e.bezierVertex(190.1,64.799,184.1,58.499,175.6,53.299),e.bezierVertex(174.6,52.699,173.7,52.099,172.5,51.499),e.vertex(170.5,50.299),e.vertex(163,45.899),e.vertex(170.5,41.599),e.bezieM rVertex(182,34.99,193.1,30.799,204.4,28.599),e.bezierVertex(208.6,27.799,212.9,27.399,217.2,27.399),e.bezierVertex(217.6,27.399,217.9,27.399,218.3,27.399),e.bezierVertex(231.4,27.599,242.7,38.199,243,50.599),e.bezierVertex(243.4,64.899,243.3,78.99,243.2,93.799),e.bezierVertex(243.2,99.799,243.1,105.899,243.1,112.099),e.vertex(243.1,119.199),e.vertex(236.4,116.799),e.bezierVertex(235.7,116.499,235,116.299,234.4,115.99),e.bezierVertex(233.4,115.599,232.6,115.299,232,115.199),e.bezierVertex(230.6,114.899,229.2,114.599M ,227.8,114.299),e.bezierVertex(223.8,113.499,220.1,112.699,216.4,112.499),e.vertex(216.2,112.499),e.bezierVertex(212.5,112.499,210.7,115.599,210.6,118.599),e.bezierVertex(210.4,122.399,212.7,125.099,216.4,125.399),e.bezierVertex(230.1,126.399,238.9,133.099,242.3,145.199),e.bezierVertex(243.2,148.399,243.2,151.599,243.2,154.499),e.vertex(243.2,155.099),e.bezierVertex(243.2,254.199,243.2,330,243.2,400.599),e.bezierVertex(243.2,401.99,243.2,403.4,243.2,404.9),e.bezierVertex(243.3,411.099,243.3,417.599,242.3,423.9),e.bM ezierVertex(238.1,449.2,219.6,467.799,194,472.5),e.bezierVertex(190.9,472.9,187.6,473.2,184.3,473.2),e.endShape(),e.beginShape(),e.vertex(315.8,473.1),e.bezierVertex(309.3,473.1,302.8,472,296.5,469.9),e.bezierVertex(270.4,461,253.8,434.9,257.1,407.9),e.bezierVertex(260,384,273.8,366.8,297,358.3),e.bezierVertex(297.7,358.1,298.3,357.8,299,357.6),e.bezierVertex(299.8,357.3,300.6,357.1,301.2,356.8),e.bezierVertex(304.3,355.4,306,351.8,304.9,348.7),e.bezierVertex(304,345.9,301.7,344.2,299,344.2),e.bezierVertex(298.6,34M 4.2,298.1,344.2,297.6,344.3),e.bezierVertex(288.1,346.3,279,350.9,269.7,358.3),e.bezierVertex(268.9,358.9,268.1,359.6,267.2,360.4),e.vertex(265.5,361.8),e.vertex(258.5,367.6),e.vertex(257.4,358.6),e.bezierVertex(257.3,358,257.3,357.5,257.2,357.1),e.bezierVertex(257,356,256.9,354.9,256.9,353.7),e.bezierVertex(256.9,334.8,256.9,316,256.9,297.1),e.bezierVertex(256.9,260.3,256.9,222.3,256.8,185),e.bezierVertex(256.8,170.7,268.3,158.8,282.5,158.4),e.bezierVertex(284.8,158.3,286.7,157.6,287.9,156.2),e.bezierVertex(289.09M 9,154.9,289.599,153.2,289.5,151.3),e.bezierVertex(289.3,147.5,286.7,145.1,282.7,145.1),e.bezierVertex(282.5,145.1,282.2,145.1,282,145.1),e.bezierVertex(278.8,145.3,275.5,146.1,272,146.9),e.bezierVertex(270.9,147.2,269.8,147.4,268.6,147.7),e.bezierVertex(267.9,147.9,267,148.2,265.8,148.7),e.bezierVertex(265.1,149,264.4,149.3,263.5,149.6),e.vertex(256.8,152),e.vertex(256.8,114.6),e.bezierVertex(256.8,95,256.8,75.4,256.8,55.9),e.bezierVertex(256.8,38,267.2,27.3,284.6,27.3),e.bezierVertex(285.3,27.3,285.9,27.3,286.6,27M .3),e.bezierVertex(299,27.9,318.7,34.5,329.6,41.9),e.vertex(336.1,46.3),e.vertex(324.4,53.3),e.bezierVertex(316.2,58.2,310.2,64.6,306,72.9),e.bezierVertex(304.2,76.4,305.1,78.5,306.1,80),e.bezierVertex(307.4,81.9,309.4,83,311.6,83),e.bezierVertex(313.7,83,315.7,81.9,317.1,80.1),e.bezierVertex(317.4,79.7,317.8,79,318.1,78.4),e.bezierVertex(318.4,77.9,318.7,77.3,319,76.8),e.bezierVertex(325.3,66.2,336.3,59.9,348.5,59.9),e.bezierVertex(353.2,59.9,357.8,60.8,362.1,62.7),e.bezierVertex(377.6,69.3,386,86.7,381.7,103.2),eM .bezierVertex(380.7,107.1,378.5,111.8,371.1,113.1),e.bezierVertex(342.7,118.1,322.2,139.1,317.8,167.8),e.bezierVertex(317.4,170.3,317.3,173.2,317.4,176.5),e.bezierVertex(317.5,180,320.1,182.8,323.5,183),e.bezierVertex(323.6,183,323.8,183,323.9,183),e.bezierVertex(327.1,183,329.8,180.6,330.3,177.2),e.bezierVertex(330.6,175.7,330.7,174,330.9,172.3),e.bezierVertex(331.1,169.8,331.4,167.3,332,164.7),e.bezierVertex(337.3,141.9,357.7,125.4,380.7,125.4),e.bezierVertex(382.5,125.4,384.3,125.5,386.1,125.7),e.bezierVertex(41M 2.8,128.9,432.6,150.9,432,176.9),e.bezierVertex(431.9,182.3,430.9,187.7,429.1,192.7),e.bezierVertex(427.2,197.9,428,201,432.3,205),e.bezierVertex(446.8,218.7,451.8,236,446.6,255),e.bezierVertex(441.4,274,428.3,286.5,408.7,291.3),e.bezierVertex(406.1,291.9,403.6,292.1,401.1,292.3),e.bezierVertex(400,292.4,398.9,292.5,397.9,292.6),e.bezierVertex(393.6,293.1,390.9,295.7,391,299.5),e.bezierVertex(391.1,303.4,394,305.8,398.5,305.8),e.bezierVertex(409.9,305.8,420.8,302.6,431.1,296.4),e.bezierVertex(431.8,296,432.5,295.5,M 433.2,295.1),e.bezierVertex(433.8,294.7,434.5,294.3,435.2,293.9),e.bezierVertex(436,293.4,436.6,293.2,437.2,293.1),e.bezierVertex(437.4,293,437.7,292.9,438.1,292.8),e.vertex(442.5,291.4),e.vertex(444.2,295.7),e.bezierVertex(450.9,312.4,449.5,328.4,440,343.4),e.bezierVertex(435.3,350.8,428.7,356.7,420.2,361.1),e.bezierVertex(414.3,364.1,413.7,365.2,414.8,371.7),e.bezierVertex(419.5,400.2,403,427.6,375.6,436.9),e.bezierVertex(371,438.5,368.3,440.7,365.8,444.7),e.bezierVertex(355.2,462.5,336.4,473.1,315.8,473.1),e.bezM ierVertex(315.8,473.1,315.8,473.1,315.8,473.1),e.endShape(),ie(e),e.fill(n),e.beginShape(),e.vertex(120.2,279.9),e.bezierVertex(117.9,279.9,112.4,279.299,112.2,273.599),e.bezierVertex(112,267.7,117.4,266.7,119.7,266.599),e.bezierVertex(133.1,265.799,143.1,259.499,149.3,247.899),e.bezierVertex(149.6,247.299,150.1,246.399,150.3,245.399),e.bezierVertex(150.6,244.299,150.5,243.299,150.5,242.7),e.bezierVertex(150.5,242.6,150.5,242.5,150.5,242.299),e.vertex(150.3,238.799),e.vertex(141.1,235.99),e.bezierVertex(114.6,227.7M 99,95.6,202.499,95.9,175.799),e.bezierVertex(95.9,173.99,96.4,168.199,102.2,168.199),e.bezierVertex(102.6,168.199,103,168.199,103.4,168.299),e.bezierVertex(104.8,168.499,108.2,168.899,109.2,175.599),e.bezierVertex(109.3,176.599,109.5,177.599,109.6,178.499),e.bezierVertex(110.4,184.199,111.3,189.99,113.7,195.499),e.bezierVertex(121.9,213.99,139.5,225.499,159.7,225.499),e.bezierVertex(172.1,225.499,184.1,220.899,193.5,212.599),e.bezierVertex(194,212.199,194.4,211.799,194.8,211.399),e.bezierVertex(195.1,211.099,195.5,M 210.799,195.8,210.399),e.bezierVertex(197.4,208.99,199.2,208.2,200.9,208.2),e.bezierVertex(202.5,208.2,204,208.899,205.3,210.1),e.bezierVertex(208,212.9,207.9,216.9,205,219.9),e.bezierVertex(196.5,228.6,186.3,234.3,174.7,236.8),e.bezierVertex(168.799,238.1,165.6,241,163.899,246.7),e.bezierVertex(158.3,265.9,139.9,279.7,120.2,279.9),e.vertex(120.2,279.9),e.endShape(),e.beginShape(),e.vertex(187.2,427.5),e.bezierVertex(183.799,427.5,181.299,425.3,180.799,422),e.bezierVertex(180.6,420.8,180.499,419.5,180.399,418.1),e.M bezierVertex(180.299,417,180.2,415.8,180.099,414.7),e.bezierVertex(177.199,390.5,156.699,371.3,132.399,370.2),e.bezierVertex(131.99,370.2,131.499,370.2,131.099,370.2),e.bezierVertex(130.699,370.2,130.299,370.2,129.799,370.2),e.bezierVertex(125.99,369.9,123.199,367.2,123.099,363.6),e.bezierVertex(122.99,360.2,125.799,357.3,129.599,356.9),e.bezierVertex(130.499,356.8,131.499,356.8,132.599,356.7),e.bezierVertex(133.199,356.7,133.799,356.7,134.399,356.6),e.vertex(138.299,356.4),e.vertex(139.1,352.6),e.bezierVertex(139.M 5,350.7,139.799,348.9,140.2,347),e.bezierVertex(140.899,343.4,141.5,340,142.399,336.8),e.bezierVertex(150.099,310.7,174.399,292,201.399,291.3),e.vertex(201.599,291.3),e.bezierVertex(203.699,291.3,206.299,292,208.299,293.2),e.bezierVertex(210.499,294.5,210.699,297.5,209.99,299.8),e.bezierVertex(209.499,301.5,208.199,303.9,203.299,304.7),e.bezierVertex(202.199,304.9,200.99,305,199.799,305.2),e.bezierVertex(194.499,305.9,188.99,306.599,183.799,308.9),e.bezierVertex(165.499,316.799,155.199,331.299,152.99,352),e.bezierVM ertex(152.399,357.8,154.499,361.7,159.699,364.5),e.bezierVertex(178.199,374.4,189.399,390,193.099,410.9),e.bezierVertex(193.699,414.299,193.899,418,193.599,422),e.bezierVertex(193.399,425.2,190.899,427.5,187.399,427.5),e.vertex(187.2,427.5),e.endShape(),e.beginShape(),e.vertex(364.3,281.1),e.bezierVertex(346.3,280.6,332.9,272.8,323.5,257),e.bezierVertex(321.6,253.9,320.4,250.2,319.2,246.7),e.bezierVertex(317.7,242.2,315,239.799,310.5,238.799),e.bezierVertex(298.5,236.299,288,230.7,279.4,222.1),e.bezierVertex(276.7,M 219.4,274.9,215.299,278,211.9),e.bezierVertex(279.4,210.3,281,209.6,282.6,209.6),e.bezierVertex(284.4,209.6,286.4,210.6,288.3,212.5),e.bezierVertex(297.8,221.8,310.4,226.9,323.9,226.9),e.bezierVertex(340.2,226.9,355.1,219.3,364.8,206.2),e.bezierVertex(371,197.8,374.2,188.5,374.5,178.5),e.vertex(374.5,177.9),e.bezierVertex(374.5,177,374.5,176.1,374.7,175.4),e.bezierVertex(375.3,171.8,377.9,169.5,381.3,169.5),e.bezierVertex(381.4,169.5,381.5,169.5,381.7,169.5),e.bezierVertex(385.4,169.7,388,172.4,388,176.1),e.bezierVM ertex(388.1,190.7,383.4,204,374.2,215.8),e.bezierVertex(365.8,226.5,354.7,233.9,341.2,237.9),e.bezierVertex(340,238.3,338.7,238.6,337.3,239.1),e.bezierVertex(335.9,239.6,335.1,240.4,334.7,240.9),e.bezierVertex(334.599,241,334.5,241.1,334.4,241.2),e.vertex(331.799,243.6),e.vertex(333.199,246.8),e.bezierVertex(338.199,258,346.799,264.9,358.699,267.3),e.bezierVertex(360.199,267.6,361.599,267.7,362.99,267.9),e.bezierVertex(363.599,268,364.299,268,364.899,268.1),e.bezierVertex(369.099,268.6,371.799,271.4,371.499,275),e.M bezierVertex(371.199,278.6,368.299,281.2,364.399,281.2),e.vertex(364.3,281.1),e.endShape(),e.beginShape(),e.vertex(323.9,437),e.bezierVertex(323.7,437,323.5,437,323.299,437),e.bezierVertex(319.599,436.7,317.299,434.1,317.4,430.2),e.bezierVertex(317.9,406.099,328.299,388,349.5,375),e.bezierVertex(350.7,374.2,352,373.5,353.4,372.8),e.bezierVertex(354.099,372.4,354.7,372.1,355.299,371.7),e.vertex(357.499,370.5),e.vertex(357.799,368),e.bezierVertex(360.4,346.6,345.199,323.7,323.9,317),e.bezierVertex(319.099,315.5,314.0M 99,314.9,309.299,314.4),e.vertex(308.199,314.299),e.bezierVertex(305.99,314.099,300.799,312.9,300.899,307.299),e.bezierVertex(300.99,303.499,303.899,300.9,308.099,300.9),e.vertex(308.299,300.9),e.bezierVertex(327.099,301.299,343.099,308.7,355.699,322.9),e.bezierVertex(364.299,332.5,369.399,344.099,370.99,357.299),e.bezierVertex(371.099,358.4,371.299,359.4,371.499,360.499),e.bezierVertex(371.599,360.99,371.699,361.499,371.799,361.99),e.vertex(372.499,365.899),e.vertex(377.899,366.199),e.bezierVertex(378.799,366.299,M 379.699,366.299,380.599,366.399),e.bezierVertex(385.099,366.699,387.899,369.399,387.799,373.299),e.bezierVertex(387.699,377.099,384.99,379.599,380.799,379.799),e.bezierVertex(369.799,380.199,359.99,383.299,351.899,389.299),e.bezierVertex(338.799,398.799,331.699,411.699,330.699,427.499),e.vertex(330.699,428.299),e.bezierVertex(330.599,429.199,330.599,430.099,330.499,430.799),e.bezierVertex(330,434.7,327.5,437,323.9,437),e.endShape()}function T(e){return e[0].map(((t,n)=>e.map((e=>e[n]))))}function A(e){return e.map(M (e=>Array.isArray(e)?A(e):e))}function D(e,t){return floor(random(e,t))}function k(e){let t=0;for(const n of e)t+=n[1];let n=random(t),r=0;for(const t of e)if(r+=t[1],n<r)return t[0];return null}function L(e){for(let t=1;t<e.length;++t){let n=D(0,t),r=e[t];e[t]=e[n],e[n]=r}}function P(e){return null==e||""===e}function O(e){return new Promise((t=>setTimeout(t,e)))}function F(e,t,n){let r=0;for(let i=1;i<=1e3;++i)for(let o=1;o<=1e3;++o)if(e*o%(t*i)==0){let e=1*i/o;abs(e-n)<abs(r-n)&&(r=e)}return r}function N(){let eM =60*(new Date).getTimezoneOffset()*1e3;return new Date(Date.now()-e).toISOString().slice(0,-1)}function B(e,t,n){let r;if(push(),textSize(e),textWidth(t)<=n)r=t;else for(let e=0;e<t.length;++e){const i=t.slice(0,e+1)+"...";if(textWidth(i)>n){r=i;break}}return pop(),r}function Y(e){var t=e%10,n=e%100;return 1==t&&11!=n?e+"st":2==t&&12!=n?e+"nd":3==t&&13!=n?e+"rd":e+"th"}class G{constructor(e,t,n){this.n=t,this.m=n,this.mat=[];let r=0;for(let t=0;t<this.n;++t){this.mat.push([]);for(let n=0;n<this.m;++n)this.mat[t].puM sh(r<e.length?e[r]:0),r+=1}return this}copy(){return new G(this.mat.flat(),this.n,this.m)}}class H{static __linear=e=>e;static __relu=e=>Math.max(e,0);static __leaky_relu=e=>e>0?e:.2*e;static __sigmoid=e=>1/(1+Math.exp(-e));static __tanh=e=>Math.tanh(e);static __apply_unary_op(e,t){const n=e.copy();for(let e=0;e<n.n;++e)for(let r=0;r<n.m;++r)n.mat[e][r]=t(n.mat[e][r]);return n}static linear=e=>H.__apply_unary_op(e,H.__linear);static relu=e=>H.__apply_unary_op(e,H.__relu);static leaky_relu=e=>H.__apply_unary_op(e,H.M __leaky_relu);static sigmoid=e=>H.__apply_unary_op(e,H.__sigmoid);static tanh=e=>H.__apply_unary_op(e,H.__tanh);static __add=(e,t)=>e+t;static __mul=(e,t)=>e*t;static __apply_binary_op=(e,t,n)=>{"object"!=typeof t&&(t=new G([t],1,1));const r=e.copy();for(let e=0;e<r.n;++e)for(let i=0;i<r.m;++i)r.mat[e][i]=n(r.mat[e][i],t.mat[e%t.n][i%t.m]);return r};static mul=(e,t)=>H.__apply_binary_op(e,t,H.__mul);static add=(e,t)=>H.__apply_binary_op(e,t,H.__add);static matMul(e,t){const n=new G([],e.n,t.m);for(let r=0;r<n.n;++rM )for(let i=0;i<n.m;++i)for(let o=0;o<e.m;++o)n.mat[r][i]+=e.mat[r][o]*t.mat[o][i];return n}static softmax(e){const t=H.__apply_unary_op(e,(e=>Math.exp(e))),n=t.mat.flat().reduce(((e,t)=>e+t));for(let r=0;r<e.n;++r)for(let i=0;i<e.m;++i)t.mat[r][i]/=n;return t}}class ${constructor(e,t){this.scale=e,this.offset=t}forward(e){return H.add(H.mul(e,this.scale),this.offset)}}class X{constructor(){}forward(e){return e.map((e=>e.flat()))}}class W{constructor(e,t,n,r){this.out_dim=e,this.activation=t,this.w=n,this.b=r}forwarM d(e){const t=H.add(H.matMul(e,this.w),this.b);return null==this.activation?t:this.activation(t)}}class U{constructor(e,t,n){this.preprocessLayers=e,this.hiddenLayers=t,this.outputLayer=n,this.totalNeurons=this.hiddenLayers.map((e=>e.out_dim)),this.currentOrders=[],this.currentIteration=null}updateNeurons(e,t){if(t!=this.currentIteration){this.currentOrders=[];for(let e=0;e<this.totalNeurons.length;++e){randomSeed(100*(t+1)+e);const n=[];for(let t=0;t<this.totalNeurons[e];++t)n.push(t);L(n),this.currentOrders.push(nM )}this.currentIteration=t}const n=A(this.totalNeurons),r=n.reduce(((e,t)=>e+t))*(1-e);for(let e=0;e<r;++e){const t=n.map(((e,t)=>(e-1)/this.totalNeurons[t]));n[t.map(((e,t)=>[e,t])).reduce(((e,t)=>t[0]>e[0]?t:e))[1]]-=Math.min(r-e,1)}this.neuronsLife=[];for(let e=0;e<n.length;++e){const t=this.currentOrders[e],r=Array(this.totalNeurons[e]).fill(0);for(let i=0;i<n[e];++i)r[t[i]]=Math.min(n[e]-i,1);this.neuronsLife.push(r)}}getTotalNeurons(){return A(this.totalNeurons)}getNeuronsLife(){return A(this.neuronsLife)}forwM ard(e){for(const t of this.preprocessLayers)e=t.forward(e);for(const[t,n]of this.hiddenLayers.entries()){e=n.forward(e);const r=new G(this.neuronsLife[t],1,e.m);e=H.mul(e,r)}return e=this.outputLayer.forward(e),H.softmax(e)}}function q(e){switch(e){case"relu":return H.relu;case"sigmoid":return H.sigmoid;case"tanh":return H.tanh;case"leaky_relu":return H.leaky_relu;default:return H.linear}}function j(e,t){const n=[],r=[],i=Z(t);let o=null,a=0,l=[];for(const t of e.config.layers)if("InputLayer"==t.class_name)o=t.confM ig.batch_input_shape.slice(1),l=o;else if("Rescaling"==t.class_name)n.push(new $(t.config.scale,t.config.offset));else if("Flatten"==t.class_name)o=[o.reduce(((e,t)=>e*t))];else if("Dense"==t.class_name){const e=[t.config.units],n=o[0]*e[0],l=e[0],s=i.subarray(a,a+n);a+=n;const h=i.subarray(a,a+l);a+=l;const c=new G(s,o[0],e[0]),u=new G(h,1,e[0]),f=q(t.config.activation);r.push(new W(e[0],f,c,u)),o=e}const s=r.pop();return{model:new U(n,r,s),inputDim:l}}function Z(e){const t=window.atob(e),n=t.length/Float32Array.BM YTES_PER_ELEMENT,r=new DataView(new ArrayBuffer(Float32Array.BYTES_PER_ELEMENT)),i=new Float32Array(n);let o=0;for(let e=0;e<n;e++){o=4*e;for(let e=0;e<4;++e)r.setUint8(e,t.charCodeAt(o+e));i[e]=r.getFloat32(0,!0)}return i}class K{constructor(e){this.elt=e,this._events={},this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight}position(){if(0===arguments.length)return{x:this.elt.offsetLeft,y:this.elt.offsetTop};var e="absolute";return"static"!==arguments[2]&&"fixed"!==arguments[2]&&"relative"!==arguments[M 2]&&"sticky"!==arguments[2]&&"initial"!==arguments[2]&&"inherit"!==arguments[2]||(e=arguments[2]),this.elt.style.position=e,this.elt.style.left=arguments[0]+"px",this.elt.style.top=arguments[1]+"px",this.x=arguments[0],this.y=arguments[1],this}show(){return this.elt.style.display="block",this}hide(){return this.elt.style.display="none",this}size(e,t){if(0===arguments.length)return{width:this.elt.offsetWidth,height:this.elt.offsetHeight};var n=e,r=t;if(n!==te||r!==te){if(n===te?n=t*this.width/this.height:r===te&&(r=M e*this.height/this.width),this.elt instanceof HTMLCanvasElement){var i,o={},a=this.elt.getContext("2d");for(i in a)o[i]=a[i];for(i in this.elt.setAttribute("width",n*this._pInst._pixelDensity),this.elt.setAttribute("height",r*this._pInst._pixelDensity),this.elt.style.width=n+"px",this.elt.style.height=r+"px",this._pInst.scale(this._pInst._pixelDensity,this._pInst._pixelDensity),o)this.elt.getContext("2d")[i]=o[i]}else this.elt.style.width=n+"px",this.elt.style.height=r+"px",this.elt.width=n,this.elt.height=r;this.wM idth=this.elt.offsetWidth,this.height=this.elt.offsetHeight,this._pInst&&this._pInst._curElement&&this._pInst._curElement.elt===this.elt&&(this._pInst._setProperty("width",this.elt.offsetWidth),this._pInst._setProperty("height",this.elt.offsetHeight))}return this}style(e,t){if(t instanceof Color&&(t="rgba("+t.levels[0]+","+t.levels[1]+","+t.levels[2]+","+t.levels[3]/255+")"),void 0===t){if(-1===e.indexOf(":"))return window.getComputedStyle(this.elt).getPropertyValue(e);for(var n=e.split(";"),r=0;r<n.length;r++){varM i=n[r].split(":");i[0]&&i[1]&&(this.elt.style[i[0].trim()]=i[1].trim())}}else if(this.elt.style[e]=t,"width"===e||"height"===e||"left"===e||"top"===e){var o=window.getComputedStyle(this.elt).getPropertyValue(e).replace(/[^\d.]/g,"");this[e]=Math.round(parseFloat(o,10))}return this}value(){return arguments.length>0?(this.elt.value=arguments[0],this):"range"===this.elt.type?parseFloat(this.elt.value):this.elt.value}mouseClicked(e){return this._adjustListener("click",e,this),this}isFocused(){return document.activeEleM ment===this.elt}_adjustListener(e,t,n){return!1===t?this._detachListener(e,n):this._attachListener(e,t,n),this}_attachListener(e,t,n){n._events[e]&&this._detachListener(e,n);var r=t.bind(n);n.elt.addEventListener(e,r,!1),n._events[e]=r}_detachListener(e,t){var n=t._events[e];t.elt.removeEventListener(e,n,!1),t._events[e]=null}}function J(e,t){var n=document.createElement("button");return n.innerHTML=e,t&&(n.value=t),ee(n)}function Q(e){var t=arguments.length>1&&void 0!==arguments[1]&&arguments[1],n=function(t){var M n=!0,r=!1,i=void 0;try{for(var o,a=t.target.files[Symbol.iterator]();!(n=(o=a.next()).done);n=!0){var l=o.value;File._load(l,e)}}catch(e){r=!0,i=e}finally{try{n||null==a.return||a.return()}finally{if(r)throw i}}};if(window.File&&window.FileReader&&window.FileList&&window.Blob){var r=document.createElement("input");return r.setAttribute("type","file"),t&&r.setAttribute("multiple",!0),r.addEventListener("change",n,!1),ee(r)}}function ee(e){return document.body.appendChild(e),new K(e)}createImg=function(){var e,t=docuM ment.createElement("img"),n=arguments;return n.length>1&&"string"==typeof n[1]&&(t.alt=n[1]),n.length>2&&"string"==typeof n[2]&&(t.crossOrigin=n[2]),t.src=n[0],e=ee(t,this),t.addEventListener("load",(function(){e.width=t.offsetWidth||t.width,e.height=t.offsetHeight||t.height;var r=n[n.length-1];"function"==typeof r&&r(e)})),e},createInput=function(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:"",t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:"text",n=document.createElement("input");returnM n.setAttribute("value",e),n.setAttribute("type",t),ee(n,this)};const te="auto";function ne(e){re(e);const t=e._rectMode;e.rectMode(CORNER),e.rect(0,0,e.width,e.height),e.rectMode(t),ie(e)}function re(e){e.push(),e.fill(255,255,255,255),e.blendMode(REMOVE)}function ie(e){e.blendMode(BLEND),e.pop()}File=function(e,t){this.file=e,this._pInst=t;var n=e.type.split("/");this.type=n[0],this.subtype=n[1],this.name=e.name,this.size=e.size,this.data=void 0},File._createLoader=function(e,t){var n=new FileReader;return n.onloM ad=function(n){var r=new File(e);if("application/json"===r.file.type)r.data=JSON.parse(n.target.result);else if("text/xml"===r.file.type){var i=(new DOMParser).parseFromString(n.target.result,"text/xml");r.data=new XML(i.documentElement)}else r.data=n.target.result;t(r)},n},File._load=function(e,t){if(/^text\//.test(e.type)||"application/json"===e.type)File._createLoader(e,t).readAsText(e);else if(/^(video|audio)\//.test(e.type)){var n=new File(e);n.data=URL.createObjectURL(e),t(n)}else File._createLoader(e,t).readM AsDataURL(e)},XML=function(e){if(e)this.DOM=e;else{var t=document.implementation.createDocument(null,"doc");this.DOM=t.createElement("root")}},document.addEventListener("DOMContentLoaded",(function(){addEventListener("mousemove",(e=>{window.mouseX=e.pageX,window.mouseY=e.pageY}))})),new e("global");const oe="308";let ae,le,se,he,ce,ue,fe,de,xe,ge,pe,me,be,ye,we,ve,ze,Ve,_e,Me,Ee,Se,Re,Ie,Ce,Te,Ae,De,ke,Le,Pe,Oe,Fe,Ne,Be,Ye,Ge,He,$e,Xe,We,Ue,qe,je,Ze,Ke,Je,Qe,et,tt,nt,rt,it,ot,at,lt,st,ht,ct,ut,ft,dt,xt,gt,pt,mt,bt,M yt,wt,vt,zt,Vt,_t,Mt,Et,St,Rt,It,Ct,Tt,At=!1,Dt=!1,kt=!0,Lt=!1,Pt=!1;const Ot=[" ","Growing","Stable","Decaying","Dead","Rebirth"];let Ft,Nt,Bt,Yt,Gt,Ht,$t,Xt,Wt,Ut,qt,jt,Zt,Kt,Jt,Qt,en,tn,nn,rn,on,an,ln,sn,hn=0,cn=0,un=0,fn=!1,dn=!0,xn=!0,gn=null,pn=null,mn=null,bn=!1,yn=!1,wn=null,vn=null,zn=!1;async function setup(){let e=windowWidth,t=windowHeight;createCanvas(e,t),et=createGraphics(e,t),Xe=createGraphics(e,t),$e=createGraphics(e,t),We=createGraphics(e,t),Ue=createGraphics(e,t),qe=createGraphics(e,t),Qe=createGM raphics(e,t),je=createGraphics(e,t),Ze=createGraphics(e,t),Ke=createGraphics(e,t),Je=createGraphics(e,t),tt=createGraphics(500,500),nt=createGraphics(500,500),rt=createGraphics(500,500),_n(),Mn(),Sn(),await En(),Gn(),Rn(),bn=!0}function _n(){Et=parseInt(oe),randomSeed(Et),noiseSeed(Et)}function Mn(){Wt=Ir(p.training_traits),Cr(Wt)}async function En(){let e;Jt=r(),Qt=o(),[Xt,e]=await Promise.all([s(Jt),h(Qt)]),Ut=new V(Wt.visual,e.layers_config,e.weight_b64),Ut.updateAge(new Date),_n(),Wt.training=e.training_traits,M Ht=e.model_name,$t=e.classes_name}function Sn(){le=min(width,height)/1024,ut=Rr.findIndex((e=>e[0]===Wt.visual.colorPalette)),ft=[["#ffffff","#231f20","#231f20"],["#231f20","#ffffff","#ffffff"],["#104da8","#ffffff","#ffffff"],["#722F1F","#FCE1B2","#FCE1B2"],["#e88120","#f9f2e5","#f9f2e5"],["#f6b941","#2E2E2E","#2E2E2E"],["#45daaa","#012221","#012221"],["#F1F1F1","#328DFE","#328DFE"],["#111822","#D3EB8D","#D3EB8D"],["#713FF9","#D6D5E6","#D6D5E6"],["#FBDA9D","#795106","#795106"],["#8f5b62","#ead0d0","#ead0d0"],["#eaeM 4cb","#508cac","#508cac"],["#ffc6cc","#cc313d","#cc313d"],["#60A900","#E0FE00","#E0FE00"],["#507DBE","#D0D1D3","#D0D1D3"],["#305848","#E8F2EE","#E8F2EE"],["#2a2634","#5b6988","#cb78a2","#5b6988"],["#590e29","#fd5e53","#fd5e53","#ffe373"],["#0a141d","#57d4e4","#328195","#2A9ECF","#0ab6a8","#57d4e4"],["#3a2d28","#d5c2ac","#df6338","#3d9895","#d5c2ac"],["#030706","#77c4d9","#77c4d9","#77c4d9","#ffffff","#ffffff","#e72020","#e72020"],["#3a4664","#92f5ff","#f9ff94","#eaa0a2","#55dde0"],["#fbfaff","#f04bb1","#f04bb1","#fM ac373","#82cef0","#8b31ce"],["#000000","#ffffff","#ff0002","#f26522","#fdff00","#00ff03","#01fffe","#0000ff","#ff00ff"]];for(let e=0;e<ft.length;++e)for(let t=0;t<ft[e].length;++t)ft[e][t]=cr(ft[e][t]);pt=[],ct=ft[ut][0],st=ft[ut][1]}function Rn(){gn=document.querySelector("#upload"),pn=document.querySelector("#inputUpload"),gn.addEventListener("dblclick",(()=>{if(!Lt&&!yn)if(In(Ie)&&cn==Ve-1)pn.click();else{if(4!=Pe&&5!=Pe&&(In(Ie)||cn!=Ve-1))return;fn=!0,dn=!0,Bt=0,un=0}})),pn.addEventListener("click",(()=>{pn.vaM lue=null,gn.style.display="block"})),pn.addEventListener("change",(()=>{const[e]=pn.files;e?(se=null,gn.style.display="none",Tn(URL.createObjectURL(e)),mn=e):gn.style.display="block"}))}function In(e){for(let t=0;t<e.length;++t){let n=0;for(let r=0;r<e[t].length;++r)e[t][r]>0&&++n;if(0==n)return!1}return!0}function Cn(){null!=se&&(un=0,Pt=!0,he=0,ue=0,drewLineAnim=!0,ce=(ae/2+we/2)/le,loadImage(se.elt.src,(e=>{const[t,n,r]=Gt,i=createGraphics(t,n);i.image(e,0,0,t,n),i.loadPixels();const o=i.pixels.filter(((e,t)=>t%M 4!=3)),a=Ut.classifyImage(o);Zt=T([a,$t.map((e=>e.toUpperCase()))]).sort(((e,t)=>e[0]>t[0]?-1:1))})))}function Tn(e){se=createImg(e,""),se.hide(),Cn()}function An(){zn||(ce+=(width-ae-we)/tn/le),re(Xe),Xe.rect(ce*le,0,width,height),ie(Xe),un>=ge&&1==kt&&(kt=!1,un-=ge),kt&&(re($e),$e.strokeWeight(2*Fe),Jn(he,ze,ct,ct,$e),ie($e)),un>=ge&&0==kt&&(kt=!0,un-=ge,he+=1,he==en&&(++ue,he=0,ce=(ae/2+we/2)/le,1==ue&&(Pt=!1,Dn(),ye=millis())))}function Dn(){At=!0,pe=!1,me=!1,tryButton=br("Try Again",width/2-225*le,height/2+265M *le,290*le,40*le,kn),closeResultButton=br("Close",width/2+75*le,height/2+265*le,150*le,40*le,Ln)}function kn(){At=!1,tryButton.hide(),closeResultButton.hide(),pn.click()}function Ln(){Yt=!0,At=!1,Gn(),tryButton.hide(),closeResultButton.hide(),gn.style.display="block",se=null}function keyTyped(){bn&&!1===yn&&!1===yr()&&("i"!==key&&"I"!==key||(Dt=!Dt),"b"!==key&&"B"!==key||(xn=!xn),"s"!==key&&"S"!==key||!1!==Lt||saveCanvasAtCurrentTime(),"k"!==key&&"K"!==key||!1!==Lt||save4KCanvasAtCurrentTime(),"u"!==key&&"U"!==key|M |!1!==Lt||!1!==At||!1!==fn||!1!==Pt||On())}function On(){Lt=!0,wn=null,vn=null,submitButton=br("Submit",width/2-155*le,height/2+115*le,150*le,40*le,Fn),closeSettingButton=br("Close",width/2+5*le,height/2+115*le,150*le,40*le,Yn),vt=createInput(),vt.position(width/2-252.5*le,height/2-40*le),vt.size(500*le,25*le),vt.style("font-size","15px"),vt.value(Jt||""),zt=createInput(),zt.position(width/2-252.2*le,height/2+35*le),zt.size(500*le,25*le),zt.style("font-size","15px"),zt.value(Qt||"")}function Fn(){Vt=vt.value(),_t=zM t.value(),submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide(),Lt=!1,yn=!0,Nn()}async function Nn(){[wn,vn,_]=await Promise.all([c(Vt),u(_t),O(1e3)]),yn=!1,wn&&vn?(n(Vt),i(_t),window.location.reload()):(Lt=!0,submitButton.show(),closeSettingButton.show(),vt.show(),zt.show())}function Bn(){Je.textFont("Trebuchet MS"),Je.noStroke(),pr(Je,600*le,200*le),Je.strokeWeight(1*le),Je.stroke(xt),Je.fill(xt),Je.textSize(50*le),Je.text("update()",width/2,height/2+2.5*le)}function Yn(){wn=null,vn=null,Lt=!1,submitBM utton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide()}function Gn(){_n(),nn=Date.now(),pe=!1,me=!1,St=Wt.training.structure_gen,Rt=Wt.visual.birthYear,It=Wt.visual.lifeCycle,Ct=Wt.training.epoch_num,Tt=Wt.training.activation_func,Ft=Mr.findIndex((e=>e[0]==Wt.visual.hardwareAcceleration))+1,1==Ft?(Nt=30,fe=40):2==Ft?(Nt=15,fe=20):(Nt=2,fe=10);const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=M Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),ae=100*le,ht=50*le,Oe=Sr.findIndex((e=>e[0]==Wt.visual.nodeShape))+1,dt=Er.findIndex((e=>e[0]==Wt.visual.nodeFill))+1,lt=_r.findIndex((e=>e[0]==Wt.visual.pattern))+1,de=Math.tanh(Math.log10(Xt.avgfeerate)),de=map(de,0,1,.2,.8),inputNodes=1,Ye=1,Ge=[],He=M [],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshifM t(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=M floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,at=.7,pt=[],xt=ft[ut][2],gt=ft[ut][ft[ut].length-1];for(let e=3;e<ft[ut].length-1;e++)pt.push(ft[ut][e]);mt=sr(xt,gt,pt,width),bt=[],wt=[],yt=width/(Ve-1);for(let e=0;e<Ve;e++)bt.push(hr(mt,yt*e/width)),wt.push(hr(mt,yt*e/width));wt.unshift(bt[0]),wt.push(bt[bt.length-1]),hn=0,cn=0,un=0,Yt=!0;coM nst n={xLeft:ae/8,xRight:width-ae/8,yTop:ae/8,yBottom:height-ae/8},r=Ce.map((e=>e.length));jt=new R(bt,r,n,Oe,le)}function Hn(e,t){let n=Ce[e].length;return[e*we+we/2+ae/2,height/2-(n-1)/2*ve+t*ve]}function $n(e,t){le=min(e,t)/1024,ae=100*le,ht=50*le,we=(e-ae)/Ve,ve=(t-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}xe=floor(De.length*de),Le=[],ke=[],ge=floor(map(de,.2,.8,15,2));for(let e=0;e<en;e++){for(let e=0;e<M xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,mt=sr(xt,gt,pt,e),bt=[],wt=[],yt=e/(Ve-1);for(let t=0;t<Ve;t++)bt.push(hr(mt,yt*t/e)),wt.push(hr(mt,yt*t/e));wt.unshift(bt[0]),wt.push(bt[bt.length-1])}function Xn(){const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(MtM ),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.M push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=CeM .length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le}function Wn(){jt.update();consM t e=4==Pe?0:Kt;jt.draw(Qe,ct,dt,e,le)}function Un(){if(!bn)return ar(),void et.image(je,0,0);if(4==Pe||5==Pe)return Wn(),void et.image(Qe,0,0);un>=Nt&&hn<Ve&&(hn++,un=0);for(let e=0;e<hn;e++)1==dt?it=ot=bt[e]:(it=ct,ot=bt[e]),Kn(e,it,ot,$e);un>=Nt&&cn<Ve-1&&(cn++,un=0);for(let e=0;e<cn;e++)Zn(e)}function qn(){et.background(ct),Ue.background(255),Ue.rectMode(CENTER),ne(Ue),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),Ue.stroke(st),Ue.strokeWeight(8*le),Ue.fill(ct),Qe.background(255),Qe.rectMode(CENTER),ne(Qe),Qe.sM trokeWeight(le),qe.background(255),qe.rectMode(CENTER),ne(qe),qe.textAlign(LEFT),$e.background(255),$e.rectMode(CENTER),ne($e),Xe.background(255),ne(Xe),Xe.strokeWeight(Ne),We.background(255),We.rectMode(CENTER),ne(We),We.fill(st),We.stroke(st),We.strokeWeight(.1*le),er(lt),We.noStroke(),xn&&(We.rect(ae/16,height/2,ae/8,height),We.rect(width-ae/16,height/2,ae/8,height),We.rect(width/2,ae/16,width,ae/8),We.rect(width/2,height-ae/16,width,ae/8)),Ze.background(255),Ze.rectMode(CENTER),ne(Ze),Ze.textAlign(CENTER,CENTERM ),Ze.textStyle(BOLD),Ze.stroke(st),Ze.strokeWeight(8*le),Ze.fill(ct),je.background(255),je.rectMode(CENTER),ne(je),je.textAlign(CENTER,CENTER),je.textStyle(BOLD),Ke.background(255),Ke.rectMode(CENTER),ne(Ke),Ke.textAlign(CENTER,CENTER),Ke.textStyle(BOLD),Ke.stroke(st),Ke.strokeWeight(8*le),Ke.fill(ct),Je.background(255),Je.rectMode(CENTER),ne(Je),Je.textAlign(CENTER,CENTER),Je.textStyle(BOLD),Je.stroke(st),Je.strokeWeight(8*le),Je.fill(ct),Un(),et.image(We,0,0),Pt&&An(),et.image(Xe,0,0),et.image($e,0,0),At&&(tr(),eM t.image(Ue,0,0)),fn&&(lr(),et.image(Ze,0,0)),Lt&&(or(),et.image(Ke,0,0)),Dt&&(ir(),et.image(qe,0,0)),yn&&(Bn(),et.image(Je,0,0))}function draw(){const e=Date.now();bn&&(Ut.updateAge(new Date(e)),Xn()),qn(),image(et,0,0),zn||un++}function Zn(e){let t,n=Ce[e].length,r=Ce[e+1].length;for(let i=0;i<n;i++){const[n,o]=Hn(e,i);for(let a=0;a<r;a++){const[r,l]=Hn(e+1,a);t=map(min(Ce[e][i],Ce[e+1][a]),0,1,0,.5),ur(n,o,r,l,bt[e],bt[e+1],Xe,t)}}}function Kn(e,t,n,r){let i,o,a,l=Ce[e].length;for(let s=0;s<l;s++){const[l,h]=Hn(eM ,s);i=Ce[e][s],a=map(Be,1/30,1,3,10),o=map(Ce[e][s],0,1,2*a,0)*le,o<1.5*le&&(o=0),Qn(l,h,ze,Oe,t,n,o,i,r)}}function Jn(e,t,n,r,i){for(let o=0;o<Le[e].length;o++)Qn(Le[e][o][0],Le[e][o][1],t,Oe,n,r,0,1,i)}function Qn(e,t,n,r,i,o,a,l,s){s.stroke(dr(o,map(l,0,1,.25,1))),s.fill(dr(i,map(l,0,1,.15,1))),s.strokeWeight(Fe),fr([a],s),3==dt&&s.fill(dr(i,0)),1==r?s.ellipse(e,t,n):2==r?s.rect(e,t,7*n/8,7*n/8):3==r&&(s.beginShape(),s.vertex(e-4*n/7,t),s.vertex(e,t-4*n/7),s.vertex(e+4*n/7,t),s.vertex(e,t+4*n/7),s.endShape(CLOSEM ))}function er(e){if(1==e);else if(2==e){We.strokeWeight(1*le);for(let e=ht/4;e<width+ht/4;e+=ht)for(let t=ht/4;t<height+ht/4;t+=ht)We.point(e,t)}else if(3==e){ht=25*le;for(let e=ht/2;e<height+ht/2;e+=ht)We.line(0,e,width,e);for(let e=ht/2;e<width+ht/2;e+=ht)We.line(e,0,e,height)}}function tr(){Ue.textFont("Trebuchet MS"),Ue.textAlign(LEFT,CENTER),Ue.noStroke(),pr(Ue,800*le,500*le),Ue.noStroke(),Ue.fill(dr(st,.75)),Ue.rect(width/2,height/2-100*le,800*le,300*le,25*le,25*le,0,0),Ue.fill(st),Ue.rect(width/2-250*le,heiM ght/2-100*le,225*le,225*le),Ue.image(se.elt,width/2-357.5*le,height/2-207.5*le,215*le,215*le);let e=100*Zt[0][0];Ue.fill(ct),Ue.textSize(25*le),Ue.textStyle(NORMAL),1==me&&(e>=0&&e<20?Ue.text("I have a feeling this image belongs to",width/2-100*le,height/2-170*le):e>=20&&e<40?Ue.text("I have a hunch this image belongs to",width/2-100*le,height/2-170*le):e>=40&&e<60?Ue.text("I think this image belongs to",width/2-100*le,height/2-170*le):e>=60&&e<80?Ue.text("I'm almost certain this image belongs to",width/2-100*le,heM ight/2-170*le):Ue.text("I'm positive this image belongs to",width/2-100*le,height/2-170*le));let t=e.toFixed(2);"100.00"==t&&(t="100"),1==me&&Ue.text("I'm "+t+"% confident that I'm right!",width/2-100*le,height/2-25*le),example=Zt.map((e=>e[1])),be=Ue.textWidth('"FIDENZAAAA"'),defaultPhrase=Ue.textWidth('"PERPENDICULAR INHABITATION"'),Ue.textStyle(BOLD);const n=me?example[0]:random(example);if(1===n.split(" ").length){let e=75*be/Ue.textWidth('"'+n+'"');e>75&&(e=75),Ue.textSize(e*le),Ue.text('"'+n+'"',width/2-100*lM e,height/2-90*le)}else nr(width/2-100*le,height/2-90*le,460*le,110*le,n,Ue);if(millis()-ye>1500&&(me=!0),C(tt,nt,st,ct,Pe,Mt),Ue.image(nt,width/2-370*le,height/2+70*le,80*le,80*le),3==Pe){let e;e=map(Mt,50,60,.25,1.3),I(rt,e),Ue.image(rt,width/2-370*le,height/2+70*le,80*le,80*le)}let r,i;Ue.image(tt,width/2-370*le,height/2+70*le,80*le,80*le),Ue.fill(xt),Ue.textSize(40*le),Ue.text("INTELLIGENCE INFO",width/2-275*le,height/2+115*le),Ue.textSize(18*le),Ue.textStyle(NORMAL),Ue.circle(width/2-360*le,height/2+180*le,7.5*M le),1==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s growing and getting smarter by the day.`:2==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s stable and it has reached peak performance.`:3==Pe&&(r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s decaying and losing its luster.`),i=2==Pe?"The Perceptron remains stable for some time before entering the decay phase.":`Wait until ${new Date(an).toLocaleString("en-US")} for your Perceptron to reach its peak performance.`,Ue.text(r,widtM h/2-350*le,height/2+180*le),Ue.circle(width/2-360*le,height/2+210*le,7.5*le),Ue.text(i,width/2-350*le,height/2+210*le),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),gr(Ue,width/2-225*le,width/2+65*le,height/2+265*le,height/2+305*le,"SELECT ANOTHER IMAGE"),gr(Ue,width/2+75*le,width/2+225*le,height/2+265*le,height/2+305*le,"CLOSE")}function nr(e,t,n,r,i,o){let a=i.split(" "),l=75*be/o.textWidth('"'+i+'"'),s=0,h=[],c=[],u=[],f="",d="";if(l>=50)l>75&&(l=75),o.textSize(l*le),o.text('"'+i+'"',e,t);else if(l<50){if(l=50*M defaultPhrase/o.textWidth('"'+i+'"'),l>30){if(l>50&&(l=50),[f,d]=rr(l,n,s,h,c,a,f,d,Ue),0==c.length)return o.textSize(l*le),void o.text('"'+i+'"',e,t);for(s=0,h=[],c=[];o.textWidth(d)>n/le;)l=l*n/le/o.textWidth(d),f="",d="",[f,d]=rr(l,n,s,h,c,a,f,d,Ue)}else{l=30,o.textSize(l);for(let e=0;e<a.length;e++)s+=o.textWidth(" "+a[e]),s<=n/le?h.push(a[e]):s>n/le&&s<=n/le*2?c.push(a[e]):u.push(a[e]);for(let e=1;e<h.length;e++)f=f+" "+h[e];if(f='"'+h[0]+f,0==u.length){for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+c[c.length-M 1]+'"'}else if(1==c.length)d="... "+u[u.length-1]+'"';else{for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+"... "+u[u.length-1]+'"'}}o.textSize(l*le);let r=1.25*(o.textDescent()+o.textAscent());o.text(f,e,t-r/2),o.text(d,e,t+r/2)}}function rr(e,t,n,r,i,o,a,l,s){s.textSize(e);for(let e=0;e<o.length;e++)(n+=s.textWidth(" "+o[e]))<=t/le?r.push(o[e]):i.push(o[e]);for(let e=1;e<r.length;e++)a=a+" "+r[e];if(a='"'+r[0]+a,0==i.length&&(a+='"',l=""),1==i.length)l=i[i.length-1]+'"';else{for(let e=0;e<i.length-1;e++)l=l+i[e]+" M ";l=l+i[i.length-1]+'"'}return[a,l]}function ir(){const e=45*le;qe.textFont("Tahoma"),qe.stroke(st),qe.strokeWeight(2*le),qe.fill(ct),qe.rect(width/2,e/2+height-87.5*le,600*le,90*le),qe.fill(st),qe.rect(width/2-150*le,e+height-170*le,300*le,30*le),qe.fill(ct),qe.rect(width/2+150*le,e+height-170*le,300*le,30*le),qe.noStroke(),qe.fill(ct),qe.textSize(15*le),qe.textStyle(BOLD),qe.text("PERCEPTRON INFORMATION",width/2-285*le,e+height-165*le),qe.fill(xt),qe.text("ARTWORK NAME:",width/2+10*le,e+height-165*le),qe.textAligM n(RIGHT),qe.textStyle(ITALIC),qe.text("Perceptron #"+Et,width/2+285*le,e+height-165*le);const[t,n]=It.split(" ");let r;"60 Years"===It?r="1 Year":"60 Months"===It?r="1 Month":"60 Weeks"===It?r="1 Week":"60 Days"===It?r="1 Day":"12 Hours"===It&&(r="12 Minutes"),data=[["AI MODEL NAME:",B(12*le,Ht,140*le)],["SCALE:","1:"+Te],["NUMBER OF CLASSES:",$t.length],["BIRTH YEAR:",Rt],["NUMBER OF REBIRTHS:",sn.toString()],["AGE:",`${Math.ceil(Mt)} Perceptron Years`],["ONE PERCEPTRON YEAR:",`${r}`],["STATE:",Ot[Pe]],["ACTIVE NEM URONS:",`${round(ln*rn)} / ${ln}`],["NEXT STATE TIME:",vr(new Date(on))]],qe.fill(xt);const i=data.length/2;for(let t=0;t<data.length;++t){const n=t<i,r=n?width/2-285*le:width/2+10*le,o=n?width/2-10*le:width/2+285*le,a=e+height-(135-t%i*15)*le;qe.textStyle(BOLD),qe.textAlign(LEFT),qe.textSize(12*le),qe.text(data[t][0],r,a),qe.textStyle(ITALIC),qe.textAlign(RIGHT),qe.textSize(12*le),qe.text(data[t][1],o,a)}}function or(){Ke.textFont("Trebuchet MS"),Ke.noStroke(),pr(Ke,600*le,200*le),gr(Ke,width/2-155*le,width/2-5*leM ,height/2+115*le,height/2+155*le,"UPDATE"),gr(Ke,width/2+5*le,width/2+155*le,height/2+115*le,height/2+155*le,"CLOSE"),Ke.textAlign(LEFT),Ke.fill(xt),Ke.text("UPDATE BITCOIN FULL NODE ADDRESS",width/2-252.5*le,height/2-55*le),Ke.text("UPDATE MODEL ADDRESS",width/2-252.5*le,height/2+20*le),Ke.textAlign(RIGHT),Ke.textStyle(ITALIC),Ke.textSize(15*le),0==wn&&Ke.text("(*) Invalid Address",width/2+252.5*le,height/2-53*le),0==vn&&Ke.text("(*) Invalid Model",width/2+252.5*le,height/2+23*le)}function ar(){je.textFont("TrebucM het MS"),je.fill(st),je.textSize(50*le),je.stroke(st),je.strokeWeight(1*le),je.text("main()",width/2,height/2)}function lr(){un>=20&&1==dn&&(dn=!1,un=0),dn&&(Ze.textFont("Trebuchet MS"),Ze.stroke(st),Ze.fill(ct),Ze.rect(width/2,height/2,600*le,150*le,25*le),Ze.fill(xt),Ze.textSize(75*le),Ze.noStroke(),1==Pe?Ze.text("GROWING",width/2,height/2+5*le):3==Pe?Ze.text("AGING",width/2,height/2+5*le):4==Pe?Ze.text("DEAD",width/2,height/2+5*le):5==Pe&&Ze.text("BIRTH",width/2,height/2+5*le)),un>=20&&0==dn&&(dn=!0,un=0,Bt++,3=M =Bt&&(fn=!1))}function sr(e,t,n,r){let i=[],o=r/(n.length+1),a=color(e),l=color(t);i.push(a);for(let e=0;e<n.length;e++){let t=color(n[e]);for(let e=1;e<=o;e++){let n=lerpColor(a,t,e/o);i.push(n)}a=t}for(let e=1;e<o;e++){let t=lerpColor(a,l,e/o);i.push(t)}if(i.push(l),i.length>r)i.splice(r);else if(i.length<r){let e=i[i.length-1];for(;i.length<r;)i.push(e)}return i}function hr(e,t){let n=e.length,r=Math.floor(t*n);return r>=n&&(r=n-1),e[r]}function cr(e){e=e.replace("#","");var t=parseInt(e,16);return color(t>>16&2M 55,t>>8&255,255&t)}function ur(e,t,n,r,i,o,a,l){var s=a.drawingContext.createLinearGradient(e,t,n,r);s.addColorStop(0,i),s.addColorStop(1,o),a.drawingContext.strokeStyle=s,a.drawingContext.globalAlpha=l,a.line(e,t,n,r),a.drawingContext.globalAlpha=1}function fr(e,t){t.drawingContext.setLineDash(e)}function dr(e,t){let n=color(e),r=red(n),i=green(n),o=blue(n);return color(r,i,o,255*t)}function xr(e,t,n,r){return mouseX>e&&mouseX<t&&mouseY>n&&mouseY<r}function gr(e,t,n,r,i,o){e.strokeWeight(1*le),e.stroke(st);const[aM ,l]=xr(t,n,r,i)?[xt,ct]:[ct,xt];e.fill(a),e.push(),e.rectMode(CORNERS),e.rect(t,r,n,i,5*le),e.pop(),e.noStroke(),e.textSize(20*le),e.fill(l),e.text(o,(t+n)/2,(46*r+54*i)/100)}function pr(e,t,n){e.fill(0,0,0,75),e.rect(width/2,height/2,width,height),e.stroke(st),e.fill(ct),e.rect(width/2,height/2,t,n,25*le)}function mr(e,t){resizeCanvas(e,t,!0),Xe.resizeCanvas(e,t,!0),$e.resizeCanvas(e,t,!0),We.resizeCanvas(e,t,!0),Ue.resizeCanvas(e,t,!0),qe.resizeCanvas(e,t,!0),Qe.resizeCanvas(e,t,!0),je.resizeCanvas(e,t,!0),Ze.resM izeCanvas(e,t,!0),Ke.resizeCanvas(e,t,!0),Je.resizeCanvas(e,t,!0),et.resizeCanvas(e,t,!0)}function br(e,t,n,r,i,o){const a=J(e);return a.position(t,n),a.size(r,i),a.style("opacity","0"),a.mouseClicked(o),a}function yr(){return null!=vt&&vt?.isFocused()||null!=zt&&zt?.isFocused()}function wr(e,t,n,r){let i;if(e<=3){i=`Hey ${String.fromCodePoint(128075)}, I'm ${n}, ${t} years old. I can detect ${r.length} NFT collections: `;let e=0;for(let t=0;t<r.length;++t){const n=r[t];if(e+n.length>500){i+=", etc";break}t==r.lengM th-1?i+=", and ":t>0&&(i+=", "),i+=n,e+=n.length}i+=". ",t<=5?i+="However, I am only a baby, so my recognition ability is not accurate. I'm in the state of Growing both looks and intelligence.":t<=13?i+="I am now a child. My recognition ability is becoming better, but still not very accurate. I'm in the state of Growing both looks and intelligence.":t<=25?i+="I have grown up to be a teen. My recognition ability almost reaches the peak, but I will still mess up sometimes. I'm in the state of Growing both looks and iM ntelligence.":t<=50?i+="I finally reach adulthood. My recognition is fully functional now. I'm in the Stable state, where I am the most intelligent with all neurons activated.":t<=60&&(i+="I am now an old Perceptron, so my recognition ability is no longer the best. I'm in the Decaying state, meaning that my neurons are dying, and my intelligence is decreasing over time.")}else 4==e?i=`${n} is Dead. However, this is not the end to its story...`:5==e&&(i=`${n} is now in the Rebirth state, and is preparing to start a M new life.`);return i}function vr(e){const t=e.getDate(),n=e.toLocaleString("en-US",{month:"long"}),r=e.getFullYear();let i=e.getHours().toString();1==i.length&&(i="0"+i);let o=e.getMinutes().toString();return 1==o.length&&(o="0"+o),`${Y(t)} ${n} ${r} | ${i}:${o}`}saveCanvasAtCurrentTime=()=>{save(N())},save4KCanvasAtCurrentTime=()=>{const e=width,t=height,n=min(4096/min(e,t),1e4/max(e,t)),r=e*n,i=t*n;mr(r,i),zn=!0,$n(r,i),qn();let o="4K_"+N()+".png";saveCanvas(et,o),mr(e,t),$n(e,t),zn=!1};const zr=[["60 Years",3,36M 5],["60 Months",40,30],["60 Weeks",37,7],["60 Days",20,1]],Vr=[["1943",1],["1951",1.5],["1957",2],["1969",2.5],["1970",3],["1980",3.5],["1982",4],["1986",4.5],["1988",5],["1997",5.5],["1998",6],["2002",6.5],["2009",7],["2012",7.5],["2014",8],["2015",8.5],["2016",9],["2023",15]],_r=[["Plain",20],["Dotted",40],["Squared",40]],Mr=[["Basic",30],["Standard",60],["Advanced",10]],Er=[["MNIST",70],["CIFAR",25],["IMAGENET",5]],Sr=[["Theano",60],["Torch",30],["TensorFlow",10]],Rr=[["Whitepaper",2],["Blackboard",2],["BlueprinM t",2],["Nak",74/14],["Jims",74/14],["Level 10",74/14],["Flips",74/14],["Level 14",74/14],["III",74/14],["XMB",74/14],["Info",74/14],["Adventure",74/14],["Marigold",74/14],["Phoenix",74/14],["Love",74/14],["Cachet",74/14],["Human",74/14],["Twilight",3],["Sunset",3],["Aurora",3],["Liminal Space",3],["D Vu",3],["Lucid Dream",3],["Parallel",1],["Multiverse",1]];function Ir(e){for(let e=0;e<100;++e)random(1);return{visual:{pattern:k(_r),hardwareAcceleration:k(Mr),nodeFill:k(Er),nodeShape:k(Sr),colorPalette:k(Rr),liM feCycle:k(zr),birthYear:k(Vr)},training:e}}function Cr(e){window.$generativeTraits={"Network Architecture":e.training.structure_gen,"Hidden Layers":e.training.n_layers,"Max Neurons Per Hidden Layer":e.training.max_nodes,"Activation Function":e.training.activation_func,"Training Epochs":e.training.epoch_num,Dataset:e.visual.nodeFill,"Deep Learning Framework":e.visual.nodeShape,"Hardware Acceleration":e.visual.hardwareAcceleration,"Paper Pattern":e.visual.pattern,"Life Cycle":e.visual.lifeCycle,"Birth Year":e.visual.M birthYear,"Color Palette":e.visual.colorPalette}} <script defer src="https://static.cloudflareinsights.com/beacon.min.js/v2b4487d741ca48dcbadcaf954e159fc61680799950996" integrity="sha512-D/jdE0CypeVxFadTejKGTzmwyV10c1pxZk/AqjJuZbaJwGMyNHY3q/mTPWqMUnFACfCTunhZUVcd4cV78dK1pQ==" data-cf-beacon='{"rayId":"7b4c96c3ab6fa244","version":"2023.3.0","b":1,"token":"6c07c178c94442f695e7a0a2aaee641a","si":100}' crossorigin="anonymous"></script> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":" text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! riTXtXML:com.adobe.xmp ' id='W5M0MpCehiHzreSzNTczkc9d'?> <x:xmpmeta xmlns:x='adobe:ns:meta/'> <rdf:RDF xmlns:rdf='http://www.w3.org/1999/02/22-rdf-syntax-ns#'> <rdf:Description rdf:about='' xmlns:Attrib='http://ns.attribution.com/ads/1.0/'> <rdf:li rdf:parseType='Resource'> <Attrib:Created>2023-04-08</Attrib:Created> <Attrib:ExtId>114b65fc-64e2-42ad-M 86de-38382fc6dec3</Attrib:ExtId> <Attrib:FbId>525265914179580</Attrib:FbId> <Attrib:TouchType>2</Attrib:TouchType> <rdf:Description rdf:about='' xmlns:dc='http://purl.org/dc/elements/1.1/'> <rdf:li xml:lang='x-default'>Jesus - 12</rdf:li> <rdf:Description rdf:about='' xmlns:pdf='http://ns.adobe.com/pdf/1.3/'> <pdf:Author>Lion's Logistics</pdf:Author> <rdf:Description rdf:about='' xmlns:xmp='http://ns.adobe.com/xap/1.0/'> <xmp:CreatorTool>Canva</xmp:CreatorTool> <?xpacket end='r'?># text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":" text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! 0{"p":"sns","op":"reg","name":"undervalued.sats"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"nako","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xM mpMM="http://ns.adobe.com/xap/1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-01M 4c-baeb-d7f687c78db6"> <xmpMM:History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (WinM dows)" stEvt:changed="/"/> </rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/html;charset=utf-8 <meta charset=UTF-8> <script id=snippet-random-code type=text/javascript>let seed=window.location.href.split('/').find(t=>t.includes('i0'));if(seed==null){const alphabet="0123456789abcdefghijklmnopqrstuvwsyz";seed=new URLSearchParams(window.location.search).get("seed")||Array(64).fill(0).map(_=>alphabet[(Math.random()*alphabet.length)|0]).join('')+"i0";}else{let pattern="seed=";for(let i=0;i<seed.length-pattern.lengM th;++i){if(seed.substring(i,i+pattern.length)==pattern){seed=seed.substring(i+pattern.length);break;}}} function cyrb128($){let _=1779033703,u=3144134277,i=1013904242,l=2773480762;for(let n=0,r;n<$.length;n++)_=u^Math.imul(_^(r=$.charCodeAt(n)),597399067),u=i^Math.imul(u^r,2869860233),i=l^Math.imul(i^r,951274213),l=_^Math.imul(l^r,2716044179);return _=Math.imul(i^_>>>18,597399067),u=Math.imul(l^u>>>22,2869860233),i=Math.imul(_^i>>>17,951274213),l=Math.imul(u^l>>>19,2716044179),[(_^u^i^l)>>>0,(u^_)>>>0,(i^_)>>>0,(l^M function sfc32($,_,u,i){return function(){u>>>=0,i>>>=0;var l=($>>>=0)+(_>>>=0)|0;return $=_^_>>>9,_=u+(u<<3)|0,u=(u=u<<21|u>>>11)+(l=l+(i=i+1|0)|0)|0,(l>>>0)/4294967296}} let mathRand=sfc32(...cyrb128(seed));</script> <style>html,body{position:fixed;top:0;right:0;bottom:0;left:0;color:#fff;background-color:#fff;display:flex;justify-content:center;align-items:center;margin:0;padding:0;font-size:.8em}canvas{object-fit:contain;max-height:100%;max-width:100%}</style> <canvas id=cnv></canvas> cript defer src="https://static.cloudflareinsights.com/beacon.min.js/v2b4487d741ca48dcbadcaf954e159fc61680799950996" integrity="sha512-D/jdE0CypeVxFadTejKGTzmwyV10c1pxZk/AqjJuZbaJwGMyNHY3q/mTPWqMUnFACfCTunhZUVcd4cV78dK1pQ==" data-cf-beacon='{"rayId":"7b4cf17a9edaf98d","version":"2023.3.0","b":1,"token":"6c07c178c94442f695e7a0a2aaee641a","si":100}' crossorigin="anonymous"></script> <script type=text/javascript>let myTitle=" console.log(myTitle+" | smldms 2023.03") ocument.getElementById('cnv');const ctx=cnv.getContext('2d');cnv.width=1280;cnv.height=1280*1.4142;const url='https://api.blockchain.info/stats';let hash_rate,btcPrice,totalBTC,tradeVol,mapBlock,mapVol,mapPrice;const plt={n:mathRand(),clr:[],name:""} plt.clr=chooseRdm([["#172E73","#244BBF","#D9CC1A","#D92B2B","#73620D"],["#593B02","#A67314","#0D0D0D","#F2E96D","#F2C438"],["#0D0D0D","#8C8C8C","#404040","#F2F2F2","#BFBFBF"],["#00040D","#0B1226","#2A2D40","#F2F2F2","#8F94A6"],["#958976","#DDDCC5","#1D2326","#611427","M #6A6A61"],["#C2ACF2","#EBEEF2","#483473","#9E82D9","#7756BF"],["#BFBFBF","#F2F2F2","#262626","#8C8C8C","#595959"],["#193441","#91AA9D","#3E606F","#D1DBBD","#FCFFF5"],["#0D1621","#03718A","#F272AE","#82D9D0","#F0F2A0"],["#555259","#8C837B","#BF3F57","#0D0D0D","#F2DAC4"],["#52591E","#818C30","#0D0D0D","#DFF250","#F2E96B"],["#0D0000","#26081C","#F24BD6","#400E2E","#8C1F66"],["#000000","#424242","#000000","#BF0000","#E0E5E4"],["#251726","#F2DCC9","#592E1E","#BF5F0B","#F2B66D"],["#383040","#D9C8B4","#BF4163","#383040","M #D9C8B4"],["#001715","#012E26","#034159","#038C3E","#0CF25D"],["#131617","#30302F","#6C733D","#013B35","#05E8D1"],["#1A1E26","#283040","#405173","#5D75A6","#B9B4D9"],["#01132B","#023373","#0367A6","#F2E205","#D9B504"],["#13181A","#1D2426","#B6E1F2","#F25E5E","#404040"],["#211D1A","#383430","#A69E97","#F2EAE4","#736258"],["#000000","#424242","#898A8A","#E0E5E4","#0D0D0D"],]) const area={n:mathRand(),val:12,};if(area.n<0.25){area.val=6} else if(area.n<0.5){area.val=8} else if(area.n<0.75){area.val=12} let margin=cnv.height/6.18;window.$generativeTraits={"Palette":plt.clr,'Base Area':area.val,} console.log(window.$generativeTraits) const IsoX=cnv.width/2;const IsoY=cnv.height/2;let IsoW=4;let IsoH=IsoW/2;function rdmColor(palette,a){const couleurs=palette;const couleurHex=couleurs[Math.floor(mathRand()*couleurs.length)];const alpha=a;const r=parseInt(couleurHex.slice(1,3),16);const g=parseInt(couleurHex.slice(3,5),16);const b=parseInt(couleurHex.slice(5,7),16);const couleurRGBA=`rgba(${r},${g},${b},${alpha})`;M return couleurRGBA;} function isoToScreenX(localX,localY){return IsoX+(localX-localY)*IsoW;} function isoToScreenY(localX,localY){return IsoY+(localX+localY)*IsoH;} function drawCube(isoX,isoY){ctx.lineWidth=0.5;ctx.strokeStyle=rdmColor(plt.clr,mathRand()*200);if(mathRand()<0.25){ctx.shadowColor=rdmColor(plt.clr,mathRand()*25);ctx.shadowBlur=mathRand()*100;} else{ctx.shadowColor=rdmColor(plt.clr,0);ctx.shadowBlur=0;} ctx.fillStyle=plt.clr[2];ctx.beginPath();ctx.moveTo(isoToScreenX(isoX,isoY),isoToScreenY(isoX,isoY)M );ctx.lineTo(isoToScreenX(isoX,isoY-1),isoToScreenY(isoX,isoY-1));ctx.lineTo(isoToScreenX(isoX-1,isoY-1),isoToScreenY(isoX-1,isoY-1));ctx.lineTo(isoToScreenX(isoX-1,isoY),isoToScreenY(isoX-1,isoY));ctx.closePath();ctx.fill();ctx.stroke();ctx.fillStyle=plt.clr[3];ctx.beginPath();ctx.moveTo(isoToScreenX(isoX+1,isoY+1),isoToScreenY(isoX+1,isoY+1));ctx.lineTo(isoToScreenX(isoX,isoY),isoToScreenY(isoX,isoY));ctx.lineTo(isoToScreenX(isoX-1,isoY),isoToScreenY(isoX-1,isoY));ctx.lineTo(isoToScreenX(isoX,isoY+1),isoToScreenYM (isoX,isoY+1));ctx.closePath();ctx.fill();ctx.stroke();ctx.strokeStyle=plt.clr[3];ctx.fillStyle=plt.clr[2];ctx.beginPath();ctx.moveTo(isoToScreenX(isoX+1,isoY+1),isoToScreenY(isoX+1,isoY+1));ctx.lineTo(isoToScreenX(isoX+1,isoY),isoToScreenY(isoX+1,isoY));ctx.lineTo(isoToScreenX(isoX,isoY-1),isoToScreenY(isoX,isoY-1));ctx.lineTo(isoToScreenX(isoX,isoY),isoToScreenY(isoX,isoY));ctx.closePath();ctx.fill();ctx.stroke();} function drawCubes(x,y,zone,h){ctx.save() for(let x=0;x<zone;x++){for(let y=0;y<M zone;y++){let nbr=Math.floor(mathRand()*mapPrice);for(let z=0;z<nbr*h;z++){drawCube(x-z,y-z);}}} function drawScene(time){fetch(url).then(response=>response.json()).then(data=>{console.log(data) const maxBtcPrice=500000;btcPrice=Math.floor(data.market_price_usd);const constrainedBtcPrice=Math.min(btcPrice,maxBtcPrice);mapPrice=mapRange(constrainedBtcPrice,0,maxBtcPrice,8,25) const maxTradeVol=50000;tradeVol=Math.floor(data.trade_volume_btc);const constrainedTradeVol=Math.min(tradeVol,maxTradeVol);mapM Vol=mapRange(constrainedTradeVol,0,maxTradeVol,1,50) mapTotalMinted=mapRange(totalBTC,1900000,21000000,1,10) totalBTC=Math.floor(data.totalbc/100000000);let mint=21000000-totalBTC;let mapBTC=mapRange(totalBTC,19000000,21000000,cnv.height/10,cnv.height/25) hash_rate=data.hash_rate;let minValue=500000000;let maxValue=800000000000;let mappedHashRate=mapRange(hash_rate,minValue,maxValue,cnv.height*0.01314,cnv.height*0.01618);console.log('HRATE: '+hash_rate+'|||||||'+mappedHashRate+' PRIX: '+btcPrice) ber=btcPrice.toLocaleString('us-US',{style:'currency',currency:'USD',minimumFractionDigits:0});const totalNumber=totalBTC.toLocaleString('us-US',{maximumFractionDigits:0});const restMint=mint.toLocaleString('us-US',{maximumFractionDigits:0});const tradeNumber=tradeVol.toLocaleString('us-US',{maximumFractionDigits:0});const centerX=cnv.width/2;const centerY=cnv.height/2;const radius=Math.sqrt(Math.pow(centerX,2)+Math.pow(centerY,2));const gradient=ctx.createRadialGradient(centerX,centerY,0,centerX,centerY,radius);grM adient.addColorStop(0,plt.clr[1]);gradient.addColorStop(1,plt.clr[0]);ctx.fillStyle=gradient;ctx.fillRect(0,0,cnv.width,cnv.height);if(mathRand()<0.5){IsoW=mappedHashRate;} else{IsoW=-mappedHashRate;} let scl=mapBTC;for(let x=-cnv.width/2+margin*1.5;x<cnv.width/2-margin;x+=scl){for(let y=-cnv.height/2+margin*1.5;y<cnv.height/2-margin;y+=scl){funkyBezier(x,y) drawCubes(x,y,Math.floor(mathRand()*area.val+2),mathRand());}} addGrain(cnv,31.4)}).catch(error=>{console.error(error);});} al(drawScene,3600000);function funkyBezier(x,y){ctx.save() ctx.translate(cnv.width/2,cnv.height/2) for(let i=0;i<mapVol;i++){const dirX=mathRand()*2-1;const dirY=mathRand()*2-1;const len=mathRand()*cnv.height/3+5;const x1=x+len*(mathRand()*0.5+0.2)*dirX;const y1=y+len*(mathRand()*0.5+0.2)*dirY;const x2=x+len*(mathRand()*0.5+0.5)*dirX;const y2=y+len*(mathRand()*0.5+0.5)*dirY;const x3=x+len*(mathRand()*0.5+0.8)*dirX;const y3=y+len*(mathRand()*0.5+0.8)*dirY;for(let halo=mathRand()*25;halo>0;halo--){ctx.beginPath();ctxM .moveTo(x,y);ctx.bezierCurveTo(x1,y1,x2,y2,x3,y3);ctx.filter='blur('+halo+'px)' ctx.strokeStyle=chooseRdm(plt.clr);ctx.lineWidth=mathRand()*2;ctx.lineCap="round";ctx.stroke();}} function mapRange(value,in_min,in_max,out_min,out_max){return(value-in_min)*(out_max-out_min)/(in_max-in_min)+out_min;} function addGrain(canvas,graininess){const ctx=cnv.getContext('2d');const width=cnv.width;const height=cnv.height;const pixels=ctx.getImageData(0,0,width,height);for(let i=0;i<pixels.data.length;i+=4){const M r=pixels.data[i];const g=pixels.data[i+1];const b=pixels.data[i+2];const alpha=pixels.data[i+3];const random=mathRand();const offset=(random-0.5)*graininess;pixels.data[i]=Math.max(0,Math.min(255,r+offset));pixels.data[i+1]=Math.max(0,Math.min(255,g+offset));pixels.data[i+2]=Math.max(0,Math.min(255,b+offset));pixels.data[i+3]=alpha;} ctx.putImageData(pixels,0,0);} function mathRandBetween(a,b){if(!b){return mathRand()*a} return mathRand()*(b-a)+a} function chooseRdm(arr){const randomIndex=Math.floor(mathRand()*arr.2length);return arr[randomIndex];}</script> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xap/1.0/mm/" xmlns:stEvtM ="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMM:History> <rdf:Seq> <M rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </rdf:Seq> </xmpMM:HistM ory> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> sMuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuu text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 -{"p":"sns","op":"reg","name":"tatacliq.sats"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 ){"p":"sns","op":"reg","name":"gilt.sats"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! qiTXtXML:com.adobe.xmp ' id='W5M0MpCehiHzreSzNTczkc9d'?> <x:xmpmeta xmlns:x='adobe:ns:meta/'> <rdf:RDF xmlns:rdf='http://www.w3.org/1999/02/22-rdf-syntax-ns#'> <rdf:Description rdf:about='' xmlns:Attrib='http://ns.attribution.com/ads/1.0/'> <rdf:li rdf:parseType='Resource'> <Attrib:Created>2023-04-08</Attrib:Created> <Attrib:ExtId>7d76fb1a-5c16M -469c-865c-227b5dee5e7e</Attrib:ExtId> <Attrib:FbId>525265914179580</Attrib:FbId> <Attrib:TouchType>2</Attrib:TouchType> <rdf:Description rdf:about='' xmlns:dc='http://purl.org/dc/elements/1.1/'> <rdf:li xml:lang='x-default'>Jesus - 8</rdf:li> <rdf:Description rdf:about='' xmlns:pdf='http://ns.adobe.com/pdf/1.3/'> <pdf:Author>Lion's Logistics</pdf:AuthM <rdf:Description rdf:about='' xmlns:xmp='http://ns.adobe.com/xap/1.0/'> <xmp:CreatorTool>Canva</xmp:CreatorTool> text/plain;charset=utf-8 ({"p":"sns","op":"reg","name":"888.sats"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"nako","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! /ViaBTC/Mined by kzsl/, text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 "p":"sns","op":"reg","name":"ddd.unisatt" text/plain;charset=utf-8 FjDOUT:EC8FBA6D4F31C679407B63C509063C3857753C1050E9DCCB9581355225CD2951 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! %&'()*456789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz &'()*56789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! qiTXtXML:com.adobe.xmp ' id='W5M0MpCehiHzreSzNTczkc9d'?> <x:xmpmeta xmlns:x='adobe:ns:meta/'> <rdf:RDF xmlns:rdf='http://www.w3.org/1999/02/22-rdf-syntax-ns#'> <rdf:Description rdf:about='' xmlns:Attrib='http://ns.attribution.com/ads/1.0/'> <rdf:li rdf:parseType='Resource'> <Attrib:Created>2023-04-08</Attrib:Created> <Attrib:ExtId>4e9e5f4d-d5f4-4214-M aa47-056859d0483d</Attrib:ExtId> <Attrib:FbId>525265914179580</Attrib:FbId> <Attrib:TouchType>2</Attrib:TouchType> <rdf:Description rdf:about='' xmlns:dc='http://purl.org/dc/elements/1.1/'> <rdf:li xml:lang='x-default'>Jesus - 4</rdf:li> <rdf:Description rdf:about='' xmlns:pdf='http://ns.adobe.com/pdf/1.3/'> <pdf:Author>Lion's Logistics</pdf:Author> <rdf:Description rdf:about='' xmlns:xmp='http://ns.adobe.com/xap/1.0/'> <xmp:CreatorTool>Canva</xmp:CreatorTool> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> text/html;charset=utf-8 <meta charset="UTF-8"> <title>Desaturated Abstraction by SMLDMS</title> <script id="snippet-random-code" type="text/javascript"> // DO NOT EDIT THIS SECTION let seed = window.location.href.split('/').find(t => t.includes('i0')); if (seed == null) { const alphabet = "0123456789abcdefghijklmnopqrstuvwsyz"; seed = new URLSearchParams(window.location.search).get("seed") || Array(64).fill(0).map(_ => aM lphabet[(Math.random() * alphabet.length) | 0]).join('') + "i0"; let pattern = "seed="; for (let i = 0; i < seed.length - pattern.length; ++i) { if (seed.substring(i, i + pattern.length) == pattern) { seed = seed.substring(i + pattern.length); break; function cyrb128($) { let _ = 1779033703, u = 3144134277, i = 1013904242, l = 2773480762; for (let n = 0, r; n < $.length; n++) _ = u ^ Math.imul(_ ^ (r = $.charCodeAt(n)), 597399067), u = i ^ Math.imul(u ^ r, 2869860233), i = l ^ Math.imul(i ^ r, 951274213), l = _ ^ Math.imul(l ^ r, 2716044179); return _ = Math.imul(i ^ _ >>> 18, 597399067), u = Math.imul(l ^ u >>> 22, 2869860233), i = Math.imul(_ ^ i >>> 17, 951274213), l = Math.imul(u ^ l >>> 19, 2716044179), [(_ ^ u ^ i ^ l) >>> 0, (u ^ _) >>> 0, (i ^ _) >>> 0, (l ^ _) >>> 0] function sfc32($, _, u, i) { return function () { u >>>= 0, i >>>= 0; var l = ($ >>>= 0) + (_ >>>= 0) | 0; return $ = _ ^ _ >>> 9, _ = u + (u << 3) | 0, u = (u = u << 21 | u >>> 11) + (l = l + (i = i + 1 | 0) | 0) | 0, (l >>> 0) / 4294967296 let mathRand = sfc32(...cyrb128(seed)); position: fixed; right: 0; bottom: 0; color: rgb(255, 255, 255); background-color: rgb(255, 255, 255); display: flex; justify-content: center; align-items: center; margin: 0; padding: 0; font-size: 0.8em; object-fit: contain; max-height: 100%; max-width: 100%; #fullScreen { display: flex; position: fixed; right: 0; bottom: 0; left: 0; justify-content: center; align-items: center; #fullScreen canvas { object-fit: contain; max-height: 100%; max-width: 100%; <canvas id="cnv"> <div id="fullScreen"> <script defer src="https://static.cloudflareinsights.com/beacon.min.js/v2b4487d741ca48dcbadcaf954e159fc616M 80799950996" integrity="sha512-D/jdE0CypeVxFadTejKGTzmwyV10c1pxZk/AqjJuZbaJwGMyNHY3q/mTPWqMUnFACfCTunhZUVcd4cV78dK1pQ==" data-cf-beacon='{"rayId":"7b4d2655cf28f99d","version":"2023.3.0","b":1,"token":"6c07c178c94442f695e7a0a2aaee641a","si":100}' crossorigin="anonymous"></script> <script type="text/javascript"> window.devicePixelRatio = 2; const canvas = document.getElementById('cnv'); const ctx = cnv.getContext('2d'); n: mathRand(), if (mode.n < 0.33) { mode.val = 1.618; mode.name = 'SLOW' else if (mode.n < 0.66) { mode.val = 3.14; mode.name = 'NORMAL' mode.val = 4.758; mode.name = 'FAST' let postRect = { n: mathRand(), if (postRect.n < 0.25) { postRect.val = true; postRect.name = 'On' postRect.val = false; n: mathRand(), if (bgc.n < 0.5) { bgc.val = 95; bgc.name = 'LIGHT' bgc.val = 5; bgc.name = 'DARK' n: mathRand(), if (lum.n < 0.5) { lum.val = 95; lum.name = 'LIGHT' lum.val = 5; lum.name = 'DARK' n: mathRand(), if (shad.n < 0.5) { shad.val = -mathRand() * 10; shad.name = 'UP' shad.val = mathRand() * 10; shad.name = 'DOWN' window.$generativeTraits = { "Mode": mode.name, "Add Rectangles": postRect.name, "Bg": bgc.name, "Frame": lum.name, ////////////////////// let myTitle = "Desaturated Abstraction" console.log(myTitle + "M console.log(window.$generativeTraits) let startClr = 180 + mathRand() * 360; let ngone = Math.floor(mathRand() * 8 + 2); let inRadius = mathRandBetween(1.1618, 0.314); let nRect = Math.floor(mathRandBetween(10, 25)) let globalSize = 1920; cnv.width = globalSize; cnv.height = globalSize * 1.4142; frame(mathRandBetween(cnv.width * 0.1618, cnv.width * 0.314)); constructor(x, y, o) { this.y = y; this.speedX = mathRand() * 4 - 2; this.speedY = mathRand() * 2 + o; this.maxSize = mathRand() * cnv.height / 5 + cnv.width / 18 this.size = mathRand() * cnv.height / 10 + cnv.height / 50; // this.size = mathRand() * cnv.height / 25 + cnv.height / 10; this.angle = mathRand() * 0.618; this.velo = mathRand() * 0.25 + 0.125; this.veloAngle = mathRand() * 0.0314 - 0.01618; ctx.save() this.x += this.speedX + Math.sin(this.angle); this.y += this.speedY + Math.sin(this.angle); this.size -= this.velo; this.angle += this.veloAngle; if (this.size < this.maxSize && this.size > cnv.height / 250) { if (mathRand() < 0.25) { ctx.shadowColor = 'hsl(' + startClr + ',' + mapRange(this.size, 0, this.maxSize, 50, 5) + '%,10%)'; ctx.shadowOffM ctx.shadowBlur = mapRange(this.size, 0, this.maxSize, 100, 10); else { ctx.shadowColor = 'hsl(' + startClr + ',50%,50%)'; ctx.shadowOffsetY = 0; ctx.shadowBlur = 5; ctx.shadowColor = "black"; ctx.shadowOffsetY = shad.val; ctx.shadowBlur = 10; ctx.strokeStyle = 'hsl(' + mapRange(this.size, thisM .maxSize, startClr, startClr + 18, 0) + ',0%,100%)'; ctx.fillStyle = 'hsl(' + mapRange(this.size, this.maxSize, startClr, startClr + 18, 0) + ',0%,100%)'; ctx.save() ctx.translate(this.x, this.y) ctx.rotate(this.angle * 0.5) abstract(0, 0, this.size, inRadius, ngone) ctx.restore() requestAnimationFrame(this.update.bind(this)); console.log(sproutM count++; if (count == sprout * 2) { if (postRect.val == true) { // ctx.fillStyle = 'hsl(' + startClr + ',100%,50%'; ctx.globalCompositeOperation = 'overlay'; ctx.save() for (let i = 0; i < nRect; i++) { ctx.rect(mathRand() * cnv.width, mathRand() * cnv.height, mathRand() * cnv.width / 50, mathRand() * cnv.height) ctx.fill(); ctx.strokeStyle = "rgba(1, 1, 1, 0)"; } } ctx.restore() addGrain(cnv, globalSize / 25) let sprout = Math.floor(mathRandBetween(10, 23)) let marge = mathRandBetween(0.1618, 0.314) for (let i = 0; i < sprout; i++) { const root = new Root(mathRandBetween(cnv.width * marge, cnv.width * (1 - marge)), mathRaM ndBetween(cnv.height * (0.1 + marge * 0.618), cnv.height * (0.9 - marge * 0.618)), mode.val); root.update(); for (let i = 0; i < sprout; i++) { const root = new Root(mathRandBetween(cnv.width * marge, cnv.width * (1 - marge)), mathRandBetween(cnv.height * (0.1 + marge * 0.618), cnv.height * (0.9 - marge * 0.618)), -mode.val); root.update(); function mapRange(value, inputMin, inputMax, outputMin, outputMax) { return ((value - inputMin) * (outputMax - M outputMin)) / (inputMax - inputMin) + outputMin; ctx.fillStyle = 'hsl(' + startClr + ',00%,' + bgc.val + '%)'; ctx.rect(0, 0, cnv.width, cnv.height) ctx.restore() function abstract(x, y, radius, inset, n) { ctx.beginPath(); ctx.translate(x, y) ctx.moveTo(0, 0 - radius); ctx.globalCompositeOperation = 'xor'; for (let i = 0; i < n; i++) { ctx.rotate(Math.PI / n) ctx.lineTo(0, 0 - (radius * inset)); ctx.rotate(Math.PI / n) ctx.lineTo(0, 0 - (radius)); ctx.restore() ctx.closePath() ctx.stroke(); function frame(s) { ctx.strokeStyle = 'hsl(' + startClr + ',5%,' + lum.val + '%)'; ctx.lineWidth = s; ctx.stroke() ctx.rect(0, 0, cnv.width, cnv.height) ctx.restore() function addGrain(canvas, graininess) { const ctx = canvas.getContext('2d'); const width = canvas.width; const height = canvas.height; const pixels = ctx.getImageData(0, 0, width, height); for (let i = 0; i < pixels.data.length; i += 4) { const r = pixels.data[i]; const g = pixels.data[i + 1]; const b = pixels.data[i + 2]; const alpha = pixels.data[i + 3]; const random = mathRand(); onst offset = (random - 0.5) * graininess; pixels.data[i] = Math.max(0, Math.min(255, r + offset)); pixels.data[i + 1] = Math.max(0, Math.min(255, g + offset)); pixels.data[i + 2] = Math.max(0, Math.min(255, b + offset)); pixels.data[i + 3] = alpha; ctx.putImageData(pixels, 0, 0); function mathRandBetween(a, b) { return mathRand() * a return mathRand() * (b - a) + a function saveCanvasAsPNG(canvas) { document.addEventListener('keydown', function (event) { if (event.key === 's' || event.key === 'S' || event.key === 'd' || event.key === 'D') { const ctx = canvas.getContext('2d'); const width = canvas.width; const height = canvas.height; const pixelRatio = (event.key === 'd' || event.key === 'D') ? window.devicePixelRatio * 4 : window.devicePixelRatio; const canvasCopy M = document.createElement('canvas'); canvasCopy.width = width * pixelRatio; canvasCopy.height = height * pixelRatio; const ctxCopy = canvasCopy.getContext('2d'); ctxCopy.imageSmoothingEnabled = false; ctxCopy.drawImage(canvas, 0, 0, width, height, 0, 0, width * pixelRatio, height * pixelRatio); const url = canvasCopy.toDataURL('image/png'); const link = document.createElement('a'); link.download = 'canvas.png'; link.href = url; link.click(); saveCanvasAsPNG(cnv); function timer(t) { setTimeout(function () { location.reload(true); text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! riTXtXML:com.adobe.xmp ' id='W5M0MpCehiHzreSzNTczkc9d'?> <x:xmpmeta xmlns:x='adobe:ns:meta/'> <rdf:RDF xmlns:rdf='http://www.w3.org/1999/02/22-rdf-syntax-ns#'> <rdf:Description rdf:about='' xmlns:Attrib='http://ns.attribution.com/ads/1M <rdf:li rdf:parseType='Resource'> <Attrib:Created>2023-04-08</Attrib:Created> <Attrib:ExtId>9676f951-622f-4284-b17d-8de1b9e819a3</Attrib:ExtId> <Attrib:FbId>525265914179580</Attrib:FbId> <Attrib:TouchType>2</Attrib:TouchType> <rdf:Description rdf:about='' xmlns:dc='http://purl.org/dc/elements/1.1/'> <rdf:li xml:lang='x-default'>Jesus - 16</rdf:li> <rdf:Description rdf:about='' xmlns:pdf='http://ns.adobe.com/pdf/1.3/'> <pdf:Author>Lion's Logistics</pdf:Author> <rdf:Description rdf:about='' xmlns:xmp='http://ns.adobe.com/xap/1.0/'> <xmp:CreatorTool>Canva</xmp:CreatorTool> <?xpacket end='r'?>y text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 .{"p":"sns","op":"reg","name":"claypepes.sats"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"nako","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! qiTXtXML:com.adobe.xmp ' id='W5M0MpCehiHzreSzNTczkc9d'?> <x:xmpmeta xmlns:x='adobe:ns:meta/'> <rdf:RDF xmlns:rdf='http://www.w3.org/1999/02/22-rdf-syntax-ns#'> <rdf:Description rdf:about='' xmlns:Attrib='http://ns.attribution.com/ads/1.0/'> <rdf:li rdf:parseType='Resource'> <Attrib:Created>2023-04-08</Attrib:Created> <Attrib:ExtId>244ce0c1-e974-4bM 0d-82c6-12b9580693bf</Attrib:ExtId> <Attrib:FbId>525265914179580</Attrib:FbId> <Attrib:TouchType>2</Attrib:TouchType> <rdf:Description rdf:about='' xmlns:dc='http://purl.org/dc/elements/1.1/'> <rdf:li xml:lang='x-default'>Jesus - 7</rdf:li> <rdf:Description rdf:about='' xmlns:pdf='http://ns.adobe.com/pdf/1.3/'> <pdf:Author>Lion's Logistics</pdf:Author>M <rdf:Description rdf:about='' xmlns:xmp='http://ns.adobe.com/xap/1.0/'> <xmp:CreatorTool>Canva</xmp:CreatorTool> <?xpacket end='r'?>Lh text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! +{"p":"sns","op":"reg","name":"broken.sats"}h! 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"nako","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 :{"p":"brc-20","op":"mint","tick":"sats","amt":"100000000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xap/1.0/mm/" xmlns:stEvtM ="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMM:History> <rdf:Seq> <M rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </rdf:Seq> </xmpMM:HistM ory> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> sMuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuu text/html;charset=utf-8 <meta charset="UTF-8"> <title>GENERATIVE BTC LOGO</title> <script type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/p5.js/1.5.0/p5.min.js"></script> <script id="snippet-contract-code" type="text/javascript"> const tokenIdRand = (Math.floor(Math.random() * 1000000) + 1) * 1000000 + (Math.floor(Math.random() * 100) + 1); let tokenData = { "tokenId": tokenIdRand, "seed": tokenIdRand.toString(), <script id="snippet-random-code" type="text/javascript"> const urlSeed = new URLSearchParams(window.location.search).get('seed'); if (urlSeed && urlSeed.length > 0) { tokenData.seed = urlSeed; const seed = tokenData.seed function cyrb128($) { let _ = 1779033703, u = 3144134277, i = 1013904242, l = 2773480762; for (let n = 0, r; n < $.length; n++) _ = u ^ Math.imul(_ ^ (r = $.charCodeAt(n)), 597399067), u = i ^ Math.iM mul(u ^ r, 2869860233), i = l ^ Math.imul(i ^ r, 951274213), l = _ ^ Math.imul(l ^ r, 2716044179); return _ = Math.imul(i ^ _ >>> 18, 597399067), u = Math.imul(l ^ u >>> 22, 2869860233), i = Math.imul(_ ^ i >>> 17, 951274213), l = Math.imul(u ^ l >>> 19, 2716044179), [(_ ^ u ^ i ^ l) >>> 0, (u ^ _) >>> 0, (i ^ _) >>> 0, (l ^ _) >>> 0] function sfc32($, _, u, i) { return function () { u >>>= 0, i >>>= 0; var l = ($ >>>= 0) + (_ >>>= 0) | 0; return $ = _ ^ _ >>> 9, _ = u + (u << 3) | 0, u = (u = u << 21 | u >>> 11) + (l = l + (i = i + 1 | 0) | 0) | 0, (l >>> 0) / 4294967296 // IMPORTANT: Instead of Math.random(), use this function mathRand() for random number generation. // This function generates a random number between 0 and 1 with on-chain seed. let mathRand = sfc32(...cyrb128(seed)); position: fixed; right: 0; bottom: 0; left: 0; color: rgb(255, 255, 255); background-color: rgb(0, 0, 0); display: flex; justify-content: center; align-items: center; margin: 0; padding: 0; font-size: 0.8em; /* overflow: hidden; */ object-fit: contain; max-height: 100%; max-width: 100%; #fullScreen { display: flex; position: fixed; right: 0; bottom: 0; left: 0; justify-content: center; align-items: center; #fullScreen canvas { object-fit: contain; max-height: 100%; max-width: 100%; color: rgb(249, 249, 249); opacity: 0.75; background-color: rgb(23, 23, 23); border-radius: 10px; padding-top: 0%; width: auto; height: auto; position: fixed; text-align: center; justify-content: center; align-items: center; top: 50%; left: 50%; -webkit-transform: translate(-50%, -50%); transform: translate(-50%, -50%); #progress h2 { display: block; font-size: 0.9rem; color: rgb(239, 239, 239); margin: 5% font-size: 0.75rem; display: block; margin: 5% #progress hr { width: 75%; margin-bottom: 10% <div id="fullScreen"> <div id="progress"> <script type="text/javascript"> ////////////////INFO & FEATURES let title = "Generative BTC Logo"; let st; const rand = mathRand(); let cnv; let maxBrush = Math.floor(randBetween(500, 1500)) function clr(rand) { if (rand > 0.75) { return 240 } else { return 10 } window.$generativeTraits = { "BG Color": clr(rand), "Force": Math.floor(randBetween(1, 5)), "Brush Size": maxBrush, console.loM g(title + " | smldms 2023.02") console.log(window.$generativeTraits) let img; let balls = []; let maxFrame = 1500; let maxForce = 1; function preload() { img = loadImage('https://gateway.pinata.cloud/ipfs/QmQVs9Xpa5e1JDooNiTPWct2kEorxwqk92A1HkHrn8jx1V'); function setup() { randomSeed(seed); noiseSeed(seed); cnv = createCanvas(1920, 1920, WEBGL); cnv.parent(fullScreen) img.resize(width, height) background(clr(rand)); function draw() { rotateY(sin(frameCount * 0.05) / 25) translate(-width / 2, -height / 2, frameCount * 0.25) let x = mathRand() * width let y = mathRand() * height for (let i = 0; i < balls.length; i++) { balls[i].draw(); balls[i].update(); balls[i].changeColour(); } for (let i = 0; i < balls.length; i++) { if (balls[i].radius < 0) { balls.splice(i, mathRand() * 2); } } if (frameCount < maxFrame) { for (let i = 0; i < 5; i++) { balls.push(neM w Ball(x, y, color(img.get(x + mathRand() * 2, y + mathRand() * 2)))); } } else { noLoop() print('stop') // saver() // timer(2000) } class Ball { constructor(mX, mY, c) { this.location = createVector(mX, mY); this.radius = randBetween(0M this.r = red(c); this.g = green(c); this.b = blue(c); this.a = alpha(c); this.xOff = 0.0; this.yOff = 0.0; } update() { this.radius -= mathRand() * 0.00025; let force = randBetween(0.5, maxForce) this.xOff = this.xOff + randBetween(-force, force); this.nX = noise(this.location.x) * this.xOff; this.yOff = this.yOff + randBetween(-force, force); this.nY = noise(this.location.y) * this.yOff; this.location.x += this.nX; this.location.y += this.nY; } changeColour() { this.c = color(img.get(this.location.x, this.location.y)); this.r = red(this.c); this.g = green(this.c); this.b = blue(this.c); this.a = alpha(this.c); } draw() { noStroke(); fill(this.r, this.g, this.b); let brushSize = round(randBetween(1, maxBrush)); if (this.a > 10) { strokeWeight(randBetween(0.25,0.5)) if (clr(rand) == 240) { stroke(10) } else { stroke(250) } ellipse(this.location.x, this.location.y, this.radius * brushSize, this.radius * brushSize); } else { fill(this.r, this.g, this.b, 100) noStroke() rect(this.location.x, this.location.y, thisM .radius * brushSize / randBetween(2.5, 5)); } } function randBetween(a, b) { if (!b) { return mathRand() * a } return mathRand() * (b - a) + a function keyTyped() { if (keyCode === 83) { // if "s" is pressed save(title + '.png'); } function timer(t) { setTimeout(function () { location.reload(true); }, t); function saver() { save(title + '.png'); </script> <script defer src="https://static.cloudflareinsights.com/beacon.min.js/v2b4487d741ca48dcbadcaf954e159fc61680799950996" integrity="sha512-D/jdE0CypeVxFadTejKGTzmwyV10c1pxZk/AqjJuZbaJwGMyNHY3q/mTPWqMUnFACfCTL unhZUVcd4cV78dK1pQ==" data-cf-beacon='{"rayId":"7b4ceb9e880aa21d","version":"2023.3.0","b":1,"token":"6c07c178c94442f695e7a0a2aaee641a","si":100}' crossorigin="anonymous"></script> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! <svg xmlns='http://www.w3.org/2000/svg' xmlns:xlink='http://www.w3.org/1999/xlink' image-rendering='pixelated' viewBox='0 0 800 800'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoCAMAAAC7IEhfAAAAV1BMVEW17XO47niw62zW9bHQ9KSy7G+77n3e97/b97vZ9rfT9KrJ8pa+74Gt62io6WLB8Ifg+MLF8Y7M85ur6mWm6V6i51nN9KDH8ZKe51bD8YvY9rXA8ISk6FvHn0/rAAABS0lEQVQ4y5XVwVKEMBCE4RFlNWpQCIiBff/n9M/MVKja09gXPXzVDbuQlV+ybM fd1naZSch56ci5lmtb1vm3NiDmYqnEUzziqhZqUy6l66lF7ScEx29ntdvsk/OmUeaTQZw7W0PmlORuGmqRTuqMNVeusqRVLa5fSnbJ53z80+z4r7VK4D3cw1LL8kGXBQl1yR8DiDoZ68WChLguQ4cvB3j3QSzIuNuwO9uyBurRxscKz4qhDHEdKx8E/lCLraZVSKGzD2gdLHqh2tnEqi+TBCs2l9OZJyaRVDlnashZ290q61Mq2LcPILXOFFLJrzCjrVHKV3Pg4iC9roblvolIrfdugLXshjFilbxvUS/Rldy59m4t8gOkRpn/D+HT8ZuIfT/gDD3+F4Yci/JiFH9zwqxB+ucKva/gACB8p4UMqfOxFD9Lw0Rw/7MM/H39y5Ub9cztS7AAAAABJRU5ErkJggg=='/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtM ml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAIVBMVEUAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABt0UjBAAAAC3RSTlMAYEJYVDQnGBNOTJeVFx8AAAAzSURBVCjPYxgFo2BIAvZULRdDYZdFYQUIsSZBONCACxoiBIVxqESYqeksKGgyCWgmiQAAX5gI535S03cAAAAASUVORK5CYII='/></foreignObject><g class='effect2'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeM AAAAIVBMVEUAAAC4V/81ElWHNdDOb//kp//Xiv/BYv/DaPOvUvOoT+pDxXriAAAAAXRSTlMAQObYZgAAAJxJREFUKM/VzsENAiEQheHJVLCsS4y3HbYBhVjA6nCXSAMmlmAD9mKhyg183I3v+OUnA/1gzgHNbPK38igadW5Rdi+1+dSGJj1UW2SZ9Hkv7xvLMX5KU6HYcwiH7c34KrTThUJZjSavBBO77gF56qBIAuQ0WsAl+Q0BHv2Ad4LgHXKGcHJF4zQgLuWXeL2DHApCWhBT6qU9ZPrLvQGHVxYdg8Be0wAAAABJRU5ErkJggg=='/></foreignObject></g><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAM oBAMAAAB+0KVeAAAAG1BMVEUAAAAnDQislnWTg2q9qIhZVlLLtaE7NzLezLzZuBaIAAAAAXRSTlMAQObYZgAAAHtJREFUKM9jGAWDEYhiEWMsDcAiGGyOKShurKReXi6AZqSRSpqTKqogY7GSi1uasiCqYJGyiluGk6gAqqCwiktak6giFkFBVMFikKCSgCCKoGAwUFAZ3UnGRm5JphiCQBCIHh6mgYLBAujeDBdgLEUXFBQUYBQECtIZAADsZxPbfZk9RAAAAABJRU5ErkJggg=='/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoAgMAAADxkFD+AAAADFBMVEUAAADfcSauSwjBXRkAUmM JRAAAAAXRSTlMAQObYZgAAAB5JREFUGNNjGAWUAu7QOBhTG8HUrdsBY6o3TKC6pQCYogQ329qTgAAAAABJRU5ErkJggg=='/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAG1BMVEUAAAAAAAAyPDlZVlIiIDT///+brbf5DwSsMjIRdaP7AAAAAXRSTlMAQObYZgAAAFdJREFUKM9jGAWDEQhgEWMUwSbo6IKpXMRRKLExCV1QSUxRUAlVkNFFWTGwMVAQVdDJ2DCwMFBIAFVQ2FiwUEjIEF1QsVBZkBFFkAEoKKgsgGqoIMPwBgCeRAo+7AxeoAAAAABJRU5ErkJggM g=='/></foreignObject><g class='effect'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAJ1BMVEUAAAAnDQich2aslnW9qIiTg2o7NzLezLxZVlIAAADsmJnNd3jDXV6RqQwDAAAAAXRSTlMAQObYZgAAAFNJREFUKM9jGAWMgggKIbhaEASkF6IolelQcS931hFA1Z9kbOJipIYuaBrsYhqGKeiOKaga7FKkiOamDGVjo5mNaC4VbFLSnAnTjRAFAoZRMLAAAEOoDnwejNL6AAAAAElFTkSuQmCC'/></foreignObject></g><g class='effect'><foreignObject x='0' M y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoCAMAAAC7IEhfAAAANlBMVEUAAAAAAAD+4i79rynJkRrJkhtjRAX8+gBa6fL8/Px0y/i6/3f9+wFgxACMDQDE5funEgHlFwAtbfBFAAAAAXRSTlMAQObYZgAAAFhJREFUOMvtzTkOgEAIQFHW2WfU+19WrOyG2BoeCTQ/Af5vgA9tuObn7jvBhMhoO6MXpkE5+SETsdoiJ+x6ajmqdrn24dSlrRWZsrzXzFTIfQ34ghBC+OYGBPgBrK83adAAAAAASUVORK5CYII='/></foreignObject></g><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://wM ww.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoAgMAAADxkFD+AAAADFBMVEUAAAABJT4AFiUHQ23+DLtgAAAAAXRSTlMAQObYZgAAABtJREFUGNNjGAUDAwK+NtWIQJiqYU1TE0jUDgDx8wRKlG8mXgAAAABJRU5ErkJggg=='/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAD1BMVEUAAAA4Nif/+tXWFRWfm4Ebj0ltAAAAAXRSTlMAQObYZgAAAC9JREFUKM9jGAUjCM zAKAgGGoJOSkiOGoLKRsSKmoDEWQSVjI0xBFWUVRey2D0MAAD11A960kM/YAAAAAElFTkSuQmCC'/></foreignObject><g class='effect2'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAJFBMVEUAAAAAAAAsIyD/UgCpo6HYAAC3AgP78jb/gQD/UwB6c3FmX11QnDWoAAAAAXRSTlMAQObYZgAAAD9JREFUKM9jGAWkACYXQQYWQTRBFcc0ASBCFdSSKDYEIlRBbcnJgcLGgaiCSoqhgoqhUO0IUUEGJkGGUTBEAADusAbVn7WU8QAAAABJRU5ErkJggg=='/></foreignObjecMe t></g><style> .effect { animation: 0.75s effect infinite alternate ease-in-out; } @keyframes effect { from { transform: translateY(0px); } to { transform: translateY(2.5%); } }.effect2 { animation: 0.75s effect2 infinite alternate ease-in-out; } @keyframes effect2 { from { transform: translateY(0px); } to { transform: translateY(1.5%); } } </style> </svg>h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":" 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"nako","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! <svg xmlns='http://www.w3.org/2000/svg' xmlns:xlink='http://www.w3.org/1999/xlink' image-rendering='pixelated' viewBox='0 0 800 800'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoCAMAAAC7IEhfAAAAV1BMVEW17XO47niw62zW9bHQ9KSy7G+77n3e97/b97vZ9rfT9KrJ8pa+74Gt62io6WLB8Ifg+MLF8Y7M85ur6mWm6V6i51nN9KDH8ZKe51bD8YvY9rXA8ISk6FvHn0/rAAABS0lEQVQ4y5XVwVKEMBCE4RFlNWpQCIiBff/n9M/MVKja09gXPXzVDbuQlV+ybM fd1naZSch56ci5lmtb1vm3NiDmYqnEUzziqhZqUy6l66lF7ScEx29ntdvsk/OmUeaTQZw7W0PmlORuGmqRTuqMNVeusqRVLa5fSnbJ53z80+z4r7VK4D3cw1LL8kGXBQl1yR8DiDoZ68WChLguQ4cvB3j3QSzIuNuwO9uyBurRxscKz4qhDHEdKx8E/lCLraZVSKGzD2gdLHqh2tnEqi+TBCs2l9OZJyaRVDlnashZ290q61Mq2LcPILXOFFLJrzCjrVHKV3Pg4iC9roblvolIrfdugLXshjFilbxvUS/Rldy59m4t8gOkRpn/D+HT8ZuIfT/gDD3+F4Yci/JiFH9zwqxB+ucKva/gACB8p4UMqfOxFD9Lw0Rw/7MM/H39y5Ub9cztS7AAAAABJRU5ErkJggg=='/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtM ml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAIVBMVEUAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABt0UjBAAAAC3RSTlMAYEJYVDQnGBNOTJeVFx8AAAAzSURBVCjPYxgFo2BIAvZULRdDYZdFYQUIsSZBONCACxoiBIVxqESYqeksKGgyCWgmiQAAX5gI535S03cAAAAASUVORK5CYII='/></foreignObject><g class='effect2'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeM AAAAG1BMVEUAAADr5NgnDQgpppHbT1T80mVUPi642c47KyCRCVr4AAAAAXRSTlMAQObYZgAAAJVJREFUKM/Ny0EOgjAQheFJT8Ck1XWlEbbFEtY2TtxjUuPSJlyAheH6soTOHIB/+eU9OG5qzRZm24tzrwLrGXWX7P68nJGivu2wnXEiHHq7PS+Iz6jDtEX180C5xDACywUkjoNhqEKmii2bPjJUqBE4vj3HU/pyTB9gXZPhqMa7gEZC8gI+JAyVgDkAr+kEVAhCNRy9P9yME4lALjE3AAAAAElFTkSuQmCC'/></foreignObject></g><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAG1BM MVEUAAAAnDQislnWTg2q9qIhZVlLLtaE7NzLezLzZuBaIAAAAAXRSTlMAQObYZgAAAHtJREFUKM9jGAWDEYhiEWMsDcAiGGyOKShurKReXi6AZqSRSpqTKqogY7GSi1uasiCqYJGyiluGk6gAqqCwiktak6giFkFBVMFikKCSgCCKoGAwUFAZ3UnGRm5JphiCQBCIHh6mgYLBAujeDBdgLEUXFBQUYBQECtIZAADsZxPbfZk9RAAAAABJRU5ErkJggg=='/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAG1BMVEUAAAAnDQgwYIImk9QyrPWk2vHfniaZaQ/2/zE/kcM gZAAAAAXRSTlMAQObYZgAAADVJREFUKM9jGAWjgB6gvCytI10AVUzIxdjY2Ahd0NVYSSmQAU0wWFHQVQBd0IiB0UmAYVAAAJ7BBia+zwL9AAAAAElFTkSuQmCC'/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAG1BMVEUAAAAAAAAyPDlZVlIiIDT///+brbf5DwSsMjIRdaP7AAAAAXRSTlMAQObYZgAAAFdJREFUKM9jGAWDEQhgEWMUwSbo6IKpXMRRKLExCV1QSUxRUAlVkNFFWTGwMVAQVdDJ2DCwMFBIAFVQ2FiwUEjIEF1QsVBZkBFFkAEoKKgsgGqoIMPwBM gCeRAo+7AxeoAAAAABJRU5ErkJggg=='/></foreignObject><g class='effect'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAJ1BMVEUAAAAnDQich2aslnW9qIiTg2o7NzLezLxZVlIAAADsmJnNd3jDXV6RqQwDAAAAAXRSTlMAQObYZgAAAFNJREFUKM9jGAWMgggKIbhaEASkF6IolelQcS931hFA1Z9kbOJipIYuaBrsYhqGKeiOKaga7FKkiOamDGVjo5mNaC4VbFLSnAnTjRAFAoZRMLAAAEOoDnwejNL6AAAAAElFTkSuQmCC'/></foreignObject></g><g class='eM ffect'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAFVBMVEUAAADOACaPABvU0tL///4AAACmpqYAkMveAAAAAXRSTlMAQObYZgAAAFBJREFUKM9jGMxAWERYAF2M0dDR0RBdUE1YBEMpU5KhI4ZSNTVloEo0payhYIBmZlJSkpGTAaqRWB2pgEXQKYFIlYzYVLKoYbMogWEUDFoAAGlPCg5h5SvhAAAAAElFTkSuQmCC'/></foreignObject></g><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' heightM ='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoAgMAAADxkFD+AAAACVBMVEUAAAAAAADT09O5Y3cbAAAAAXRSTlMAQObYZgAAABhJREFUGNNjGAUDBCIdU2HMMMdIBxJ1AwB5TAIwT//nMwAAAABJRU5ErkJggg=='/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoAgMAAADxkFD+AAAADFBMVEUAAACbrbfL2/z////gt0c0AAAAAXRSTlMAQObYZgAAAClJREFUGNNjGAWkgQMQSgCIC8AsRkEGBo4OMJPZGMSFiCrBdTABmVQHAM CN2AnJyX01fAAAAAElFTkSuQmCC'/></foreignObject><g class='effect2'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAElBMVEUAAADL2/wyAwEAAACZrdf///9WFtVaAAAAAXRSTlMAQObYZgAAACVJREFUKM9jGAWUAyZBEEIDKqYCQIQuaCwARBjaFYCIYRQMYQAAEJICLeWJ8q8AAAAASUVORK5CYII='/></foreignObject></g><style> .effect { animation: 0.75s effect infinite alternate ease-in-out; } @keyframes effect { from {L transform: translateY(0px); } to { transform: translateY(2.5%); } }.effect2 { animation: 0.75s effect2 infinite alternate ease-in-out; } @keyframes effect2 { from { transform: translateY(0px); } to { transform: translateY(1.5%); } } </style> </svg>h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"nako","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 0{"p":"sns","op":"reg","name":"luxuryabode.sats"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/html;charset=utf-8 <meta charset="UTF-8"> <title>Ordinals Sprout</title> <script sandbox="allow-scripts" type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/p5.js/1.5.0/p5.min.js"></script> <script id="snippet-random-code" type="text/javascript"> // DO NOT EDIT THIS SECTION let seed = window.location.href.split('/').find(t => t.includes('i0')); if (seed == null) { const alphabet = "0123456789abcdeM fghijklmnopqrstuvwsyz"; seed = new URLSearchParams(window.location.search).get("seed") || Array(64).fill(0).map(_ => alphabet[(Math.random() * alphabet.length) | 0]).join('') + "i0"; let pattern = "seed="; for (let i = 0; i < seed.length - pattern.length; ++i) { if (seed.substring(i, i + pattern.length) == pattern) { seed = seed.substring(i + pattern.length); break; function cyrb128($) { let _ = 1779033703, u = 3144134277, i = 1013904242, l = 2773480762; for (let n = 0, r; n < $.length; n++) _ = u ^ Math.imul(_ ^ (r = $.charCodeAt(n)), 597399067), u = i ^ Math.imul(u ^ r, 2869860233), i = l ^ Math.imul(i ^ r, 951274213), l = _ ^ Math.imul(l ^ r, 2716044179); return _ = Math.imul(i ^ _ >>> 18, 597399067), u = Math.imul(l ^ u >>> 22, 2869860233), i = Math.imul(_ ^ i >>> 17, 951274213), l = Math.imul(u ^ l >>> 19, 271604M 4179), [(_ ^ u ^ i ^ l) >>> 0, (u ^ _) >>> 0, (i ^ _) >>> 0, (l ^ _) >>> 0] function sfc32($, _, u, i) { return function () { u >>>= 0, i >>>= 0; var l = ($ >>>= 0) + (_ >>>= 0) | 0; return $ = _ ^ _ >>> 9, _ = u + (u << 3) | 0, u = (u = u << 21 | u >>> 11) + (l = l + (i = i + 1 | 0) | 0) | 0, (l >>> 0) / 4294967296 let mathRand = sfc32(...cyrb128(seed)); display: flex; position: fixed; right: 0; bottom: 0; color: #fff; background-color: #000; justify-content: center; align-items: center; margin: 0; padding: 0; font-size: .8em #fullScreen canvas, object-fit: contain; max-height: 100%; max-width: 100% #fullScreen { justify-content: center; align-items: center <script type="text/javascript"> const rand = mathRand(); //////////////// FEATURES let myTitle = "ORDINALS SPROUT"; console.log(myTitle + " | SMLDMS 2023.02") let globalSize = 1000; let myString = "ORDINALS" let textAlpha = 160; let strokeAlpha = 127; let strokeColor = 0; let strokeSize = 1; let fontSize; let fontSampleFactor = mathRandBetween(0.15, 0.33); //How many points there are: the higher the number, the closer together they are (more detail) let simplifyFactor = 0.0; // 0 is normal let noiseZoom = mathRandBetween(0.033, 0.01) //how zoomed in the perlin noise is (0.05 to 0.01) let noiseOctaves = mathRandBetween(1, M 50); //The number of octaves for the noise let noiseFalloff = mathRandBetween(0.4, 0.6); //The falloff for the noise layers let zOffsetChange = 0.1; //How much the noise field changes in the z direction each frame let individualZOffset = 0.01; //how far away the points/lines are from each other in the z noise axies (the bigger the number, the more chaotic) let speedFactor = mathRandBetween(10, 100); let lineSpeed = speedFactor; //the maximum amount each point can move M let points = []; let startingPoints; let maxFrame = 100; function preload() { font = loadFont("https://gateway.pinata.cloud/ipfs/QmYhhjHt9J8N1CXQnHdNRAt7c1BmzyUsdw8s1stfeDJrP5"); function setup() { randomSeed(seed); noiseSeed(seed); cnv = createCanvas(globalSize * 1.77, globalSize); cnv.parent('fullScreen'); rectMode(CENTER) angleMode(DEGREES) pixelDensity(2) fontSize = width * 0.1618 textFont(font); textSize(fontSize); textAlign(CENTER, BASELINE) noFill() stroke(strokeColor); strokeWeight(strokeSize) background(0) for (let i = 0; i < 25; i++) { push() fill(255) noStroke() rect(mathRand() * width, mathRand() * height, mathRandBetweenM pop() fill(255) noStroke() rect(width / 2, height / 2, width, height * 0.45) for (let i = 0; i < 50; i++) { push() fill(0) noStroke() rect(mathRand() * width, mathRand() * height, mathRandBetween(5, 150)) pop() grainy(15) noiseDetail(noiseOctaves, noiseFalloffM translate(0, 50) makeTxt(myString, width / 2, height * 0.55); grainy(5) function makeTxt(string, x, y) { startingPoints = font.textToPoints(string, x - textWidth(string) / 2, y, fontSize, { sampleFactor: fontSampleFactor, simplifyThreshold: simplifyFactor for (let p = 0; p < startingPoints.length; p++) { points[p] = startingPoints[p]; pointsM [p].zOffset = random(); if (showText) { stroke(strokeColor, strokeAlpha); fill(255, 255); text(myString, x, y); for (let i = 0; i <= maxFrame; i++) { for (let pt = 0; pt < points.length; pt++) { let p = points[pt]; let noiseX = p.x * noiseZoom; let noiseY = p.y * noiseZoom; let noiseZ = frameCount * zOffsetM Change + p.zOffset * individualZOffset; lineSpeed = map(pt, 0, startingPoints.length, -speedFactor, speedFactor) let newPX = p.x + map(noise(noiseX, noiseY, noiseZ), 0, 1, -lineSpeed, lineSpeed); let newPY = p.y + map(noise(noiseX, noiseY, noiseZ + 23), 0, 1, -lineSpeed, lineSpeed); if (i < maxFrame) { rect(p.x, p.y, globalSize / 125) } else { } p.x = newPX; p.y = newPY; function grainy(force) { _seed = floor(mathRand() * 999999) randomSeed(_seed) noiseSeed(_seed) loadPixels(); let d = pixelDensity(); let halfImage = 4 * (width * d) * (height * d); for (let i = 0; i < halfImage; i += 4) { grainAmount = random(-force, force); pixels[i] = M pixels[i] + grainAmount; pixels[i + 1] = pixels[i + 1] + grainAmount; pixels[i + 2] = pixels[i + 2] + grainAmount; pixels[i + 3] = pixels[i + 3] + grainAmount updatePixels(); function keyTyped() { if (keyCode === 83) { // if "s" is pressed save(myTitle + '.png'); function mathRandBetween(a, b) { if (!b) { return mathRandM return mathRand() * (b - a) + a <div id="fullScreen"> </div> <script defer src="https://static.cloudflareinsights.com/beacon.min.js/v2b4487d741ca48dcbadcaf954e159fc61680799950996" integrity="sha512-D/jdE0CypeVxFadTejKGTzmwyV10c1pxZk/AqjJuZbaJwGMyNHY3q/mTPWqMUnFACfCTunhZUVcd4cV78dK1pQ==" data-cf-beacon='{"rayId":"7b4cebdd78a4a1e7","version":"2023.3.0","b":1,"token":"6c07c178c94442f695e7a0a2aaee641a","si":100}' crossorigin="anonymous"></script> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"nako","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! <svg xmlns='http://www.w3.org/2000/svg' xmlns:xlink='http://www.w3.org/1999/xlink' image-rendering='pixelated' viewBox='0 0 800 800'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoCAMAAAC7IEhfAAAARVBMVEXinc3flMjhmMrkoc/y0OnlptLz1OruxOLruNzpsdjmqtTdjMPsvN7nrdbtwODbhsHxy+bwyOTej8bqtNrxzefZgr7ZgL0cO9EEAAABH0lEQVQ4y8TPSQ7CMBBE0Q4zCRCIY9//qNRgt8QJqA0Inn7L0Vqt67ouy7JtE3bo4/dtw8/4s9bWwo5MKnKwpM pYxXFfHXLdDRgWzozpjM8ZPWknSGuA4ixyY0FMjBkWU54FCd5kDI7r3EYMi6uuRDjWoUm5aKbCopox0ZFQPjZY0ZegddoXq1UdbJPUiwnRi1z7SlIQ/juyjkf7IAeGQI3troIhSDjhNDrJntmOiaipJpaAO2+0nbbfUcSYFHeRd1IA0VHndSUJfdtC9C+amk74d4ykO2lk6OZ4jiMsOyqVE0rcHnAfc7TwlDef/w29jdUAAAACCAOj/ay4woVKqYXo9u/A+4YeiY9bB7Spsub6uDcCS8kg1ew1p09zY9/sAJFQ4OREZSsoAAAAASUVORK5CYII='/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAM AAAoBAMAAAB+0KVeAAAAIVBMVEUAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABt0UjBAAAAC3RSTlMAYEJYVDQnGBNOTJeVFx8AAAAzSURBVCjPYxgFo2BIAvZULRdDYZdFYQUIsSZBONCACxoiBIVxqESYqeksKGgyCWgmiQAAX5gI535S03cAAAAASUVORK5CYII='/></foreignObject><g class='effect2'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAG1BMVEUAAADr5NgnDQgpppHbT1T80mVUPi642c47KyCRCVr4AAAAAXRSTlMAQObYZgAAAJVJREFUKM/NM y0EOgjAQheFJT8Ck1XWlEbbFEtY2TtxjUuPSJlyAheH6soTOHIB/+eU9OG5qzRZm24tzrwLrGXWX7P68nJGivu2wnXEiHHq7PS+Iz6jDtEX180C5xDACywUkjoNhqEKmii2bPjJUqBE4vj3HU/pyTB9gXZPhqMa7gEZC8gI+JAyVgDkAr+kEVAhCNRy9P9yME4lALjE3AAAAAElFTkSuQmCC'/></foreignObject></g><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAG1BMVEUAAAAnDQislnWTg2q9qIhZVlLLtaE7NzLezLzZuBaIAAAAAXRSTlMAQObYZgAAAHtJREFUKM9jGAWDEYhM iEWMsDcAiGGyOKShurKReXi6AZqSRSpqTKqogY7GSi1uasiCqYJGyiluGk6gAqqCwiktak6giFkFBVMFikKCSgCCKoGAwUFAZ3UnGRm5JphiCQBCIHh6mgYLBAujeDBdgLEUXFBQUYBQECtIZAADsZxPbfZk9RAAAAABJRU5ErkJggg=='/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAGFBMVEUAAADpYpcnDQjMVYSuAEUiIDTL2/ybrbdSTJP4AAAAAXRSTlMAQObYZgAAAC9JREFUKM9jGAWjgB4gtDQ1NRVNTMVQUFDQRAFD0MTZCUOlk5KxApogkM/EMEgAAOM ScBSOfzAY3AAAAAElFTkSuQmCC'/></foreignObject><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAElBMVEUAAADdnc4nDQjGY67+ue40Ly62gXI6AAAAAXRSTlMAQObYZgAAAFZJREFUKM9jGAWDEShjEWMyNsAiKGjs4hKAJqgo4mhsbKyALigkqIImyGQIFFRyVkIVNBFSVFRRUlRAFRQUFFJxVhZA1a4sKKjirIBmPbOhoKAww8gCAF/KCBN7d7EaAAAAAElFTkSuQmCC'/></foreignObject><g class='effect'><foreignObject x='0' y='0' width='800' heighM t='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAJ1BMVEUAAAAnDQich2aslnW9qIiTg2o7NzLezLxZVlIAAADsmJnNd3jDXV6RqQwDAAAAAXRSTlMAQObYZgAAAFNJREFUKM9jGAWMgggKIbhaEASkF6IolelQcS931hFA1Z9kbOJipIYuaBrsYhqGKeiOKaga7FKkiOamDGVjo5mNaC4VbFLSnAnTjRAFAoZRMLAAAEOoDnwejNL6AAAAAElFTkSuQmCC'/></foreignObject></g><g class='effect'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800M ' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoAQMAAAC2MCouAAAAA1BMVEUAAACnej3aAAAAAXRSTlMAQObYZgAAAAtJREFUCNdjGGEAAADwAAFOldjfAAAAAElFTkSuQmCC'/></foreignObject></g><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoAgMAAADxkFD+AAAADFBMVEUAAAAnDQhZVlI7NzL2q9zyAAAAAXRSTlMAQObYZgAAABdJREFUGNNjGAUDBKocX8KYoY6hpOoGAJNDApChKFBbAAAAAElFTkSuQmCC'/></foreignObject><foreigM nObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoAQMAAAC2MCouAAAAA1BMVEUAAACnej3aAAAAAXRSTlMAQObYZgAAAAtJREFUCNdjGGEAAADwAAFOldjfAAAAAElFTkSuQmCC'/></foreignObject><g class='effect2'><foreignObject x='0' y='0' width='800' height='800'><img xmlns='http://www.w3.org/1999/xhtml' height='800' width='800' src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACgAAAAoBAMAAAB+0KVeAAAAElBMVEUAAAAyAwHL2/wAAM ACZrdf///8rJjHUAAAAAXRSTlMAQObYZgAAACxJREFUKM9jGAVUAIICjEroYoyqCiKmCmiCIkYKIsbogoyCDIxKAgyjYAgDAMy1Agaj/iRZAAAAAElFTkSuQmCC'/></foreignObject></g><style> .effect { animation: 0.75s effect infinite alternate ease-in-out; } @keyframes effect { from { transform: translateY(0px); } to { transform: translateY(2.5%); } }.effect2 { animation: 0.75s effect2 infinite alternate ease-in-out; } @keyframes effect2 { from { transform: translateY(0px); } to { transform: translateY(1.5%); } } </style> </svg>h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! qiTXtXML:com.adobe.xmp ' id='W5M0MpCehiHzreSzNTczkc9d'?> <x:xmpmeta xmlns:x='adobe:ns:meta/'> <rdf:RDF xmlns:rdf='http://www.w3.org/1999/02/22-rdf-syntax-ns#'> <rdf:Description rdf:about='' xmlns:Attrib='http://ns.attribution.com/ads/1.0/'> <rdf:li rdf:parseType='Resource'> <Attrib:Created>2023-04-08</Attrib:Created> <Attrib:ExtId>57dc2d0f-cc84-4cf3-9b9M 0-5b3ed447d83a</Attrib:ExtId> <Attrib:FbId>525265914179580</Attrib:FbId> <Attrib:TouchType>2</Attrib:TouchType> <rdf:Description rdf:about='' xmlns:dc='http://purl.org/dc/elements/1.1/'> <rdf:li xml:lang='x-default'>Jesus - 5</rdf:li> <rdf:Description rdf:about='' xmlns:pdf='http://ns.adobe.com/pdf/1.3/'> <pdf:Author>Lion's Logistics</pdf:Author> <rdf:Description rdf:about='' xmlns:xmp='http://ns.adobe.com/xap/1.0/'> <xmp:CreatorTool>Canva</xmp:CreatorTool> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":" text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! Bj@=:ETH.ETH:0x878ACdFa16080259ae52aB9BD50EfEce9000BF09:13920317::0 text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"transfer","tick":"gold","amt":"31"}h! FjDOUT:DBE703EE4C591650931BDFDAC52F32A383D16C43C29E01EE177D23ADC148F30C text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 "p":"sns","op":"reg","name":"1a.unisatt" text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 !22222222222222222222222222222222222222222222222222 %&'()*456789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz &'()*56789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/html;charset=utf-8 <meta charset="UTF-8"> <title>Zombie Pixels</title> height: 100%; background: black; display: flex; align-items: center; justify-content: center; border: 4px solid red; margin: 10px; position: relative; right: 10px; width: 300px; padding: 10px; background-color: rgba(0, 0, 0, 0.8); border-radius: 5px; text-align: center; color: white; #pause-button { display: 'block'; visibility: 'visible'; margin: 0px; width: 200px; justify-content: center; #restart-button { display: 'block'; margin: 0px; width: 200px; justify-content: center; <div id="controls"> 1>ZOMBIE PIXELS</h1> <h2>@BTC_RetroArcade</h2> <h3>How To Play:</h3> <p>Use the arrow keys to move the player.<br> Avoid the red zombie pixels!<br> Don't touch the edge! <button id="pause-button">Pause</button> <button id="restart-button">Restart Game</button> <canvas id="game-canvas" width="600" height="600"></canvas> // Created by Shane Masters 2023 for @BTC_RetroArcade the initial number of opposing team members let initialNumOpponents = 4; let maxOpponents = 40; // Create an array to hold the opposing team member objects const opponents = []; // Get the canvas and context const gamecanvas = document.getElementById("game-canvas"); const canvasctx = gamecanvas.getContext("2d"); let playerX = gamecanvas.width / 2; let playerY = gamecanvas.height / 2; // Set the player's radius const playerRadM const playerSize = playerRadius*2; // Set the size of the opposing team squares const opponentSize = 20; const pauseButton = document.getElementById("pause-button"); pauseButton.addEventListener("click", pauseGame); // Get the restart button element and add an event listener to it const restartButton = document.getElementById("restart-button"); restartButton.addEventListener("click", restartGame); let isPaused = false; nction initializePlayers() for (let index = 0; index < initialNumOpponents; index++) { addOpponent(); drawPlayer(playerX, playerY); // Set the player's speed const playerSpeed = 0.5; // Move the player with arrow keys function movePlayer(deltaTime) if(isPaused) return; // Calculate the distance to move based on player speed and deM const distance = playerSpeed * deltaTime; // Check for arrow key presses and move player accordingly if (keys.ArrowUp && playerY > 0) { playerY -= distance; if (keys.ArrowDown && playerY < gamecanvas.height) { playerY += distance; if (keys.ArrowLeft && playerX > 0) { playerX -= distance; if (keys.ArrowRight && playerX < gamecanvas.width) { playerX += distance; // Ensure player stays inside the canvas playerX = Math.max(0, Math.min(playerX, gamecanvas.width)); playerY = Math.max(0, Math.min(playerY, gamecanvas.height)); // Check if player is outside canvas and end game if true if (playerX === 0 || playerX === gamecanvas.width || playerY === 0 || playerY === gamecanvas.height) endGame(); // Set up keyboardM const keys = {}; document.addEventListener("keydown", e => { keys[e.code] = true; document.addEventListener("keyup", e => { keys[e.code] = false; // add an event listener to the game over condition document.addEventListener('gameOver', () => { // change the display property of the restart button to show it again restartButton.style.visibility = 'visible'; pauseButton.style.visibility = 'hidden';M // Define a custom game over event const gameOverEvent = new Event('gameOver'); function drawPlayer(positionX, positionY) // Get the canvas element and its context const canvas = document.getElementById("game-canvas"); const ctx = canvas.getContext("2d"); // Set the player's color to cyan ctx.fillStyle = "cyan"; // Draw the player circle ctx.beginPath(); ctx.arc(positioM nX, positionY, playerRadius, 0, 2 * Math.PI); ctx.fill(); function drawOpponents() const canvas = document.getElementById("game-canvas"); const ctx = canvas.getContext("2d"); // Draw the opposing team members as squares opponents.forEach(opponent => // Set the color of the opposing team members to red ctx.fillStyle = "orange"; ctx.fillRect(opponent.x, opponent.y, oM pponentSize, opponentSize); function addOpponent() // Generate initial positions for the opposing team members const opponentX = Math.floor(Math.random() * (gamecanvas.width - opponentSize)); const opponentY = Math.floor(Math.random() * (gamecanvas.height - opponentSize)); if(opponents.length > maxOpponents) return; if(gameStarted == false) if(gameOver) return; if(isPaused) return; if(checkSpawningCollisions(opponentX, opponentY) == false) return; opponents.push({ x: opponentX, y: opponentY }); let lastUpdateTime = performance.now(); // get the current time in milliseconds let deltaTime = 0; function updateDelM const currentTime = performance.now(); // get the current time in milliseconds deltaTime = currentTime - lastUpdateTime; // calculate the time difference lastUpdateTime = currentTime; // update the last update time // Set the time interval to add a new opponent const intervalTime = 5000; // 5 seconds // Start the interval timer to add opponents const opponentInterval = setInterval(addOpponent, intervalTime); function checkSpawningCollisions(newOpponentX, newOpponentY) const thresholdDistance = 20; // Check if the new opponent is too close to the player const dx = playerX - (newOpponentX + opponentSize / 2); const dy = playerY - (newOpponentY + opponentSize / 2); const distanceFromPlayer = Math.sqrt(dx * dx + dy * dy); if (distanceFromPlayer < playerSize / 2 + opponentSize / 2 + thresholdDistance) return faM return true; function checkCollisions() // Check if any opponent has collided with the player for (const opponent of opponents) const dx = playerX - (opponent.x + opponentSize / 2); const dy = playerY - (opponent.y + opponentSize / 2); const distance = Math.sqrt(dx * dx + dy * dy); if (distance < playerSize / 2 + opponentSize / 2) // The player has collided with an opponent, end the game endGame(); return; function displayGameOverMessage() // Get the canvas element and its context const canvas = document.getElementById("game-canvas"); const ctx = canvas.getContext("2d"); // Display the "Game Over" message ctx.font = "72px Arial"; ctx.fillStyle = "white"; ctx.textAlign = "center"; ctx.fillText("Game Over", gamecanvas.width / 2, gamecanvas.height / 2); if(gameScore > highScore) localStorage.setItem('zombiePixelsHighScore', gameScore); function endGame() // Set the game over flag to true gameOver = true; document.dispatchEvent(gameOverEvent); // Set the wait time and jitter range for the opposM const waitTimeMin = 1000; // 1 second const waitTimeMax = 5000; // 3 seconds const jitterRange = 2; // 5 pixels // Set the speed of the opposing team members in pixels per second const opponentSpeed = 200; // Set the countdown time for the start of the game const countdownTime = 3000; // 3 seconds // Set a flag to indicate if the game has started let gameStarted = false; // Create a variable to store the time elapseM d since the start of the game let elapsedTime = 0; let lastplayerTime = 0; gameOver = false; // Create a game loop that updates the positions of the opposing team members function gameLoop() // Get the canvas element and its context const canvas = document.getElementById("game-canvas"); const ctx = canvas.getContext("2d"); // Clear the canvas ctx.clearRect(0, 0, canvas.width, canvas.height); // Check if the game has started if (!gameStarted) updateDeltaTime(); // If not, update the elapsed time elapsedTime += deltaTime; //Added here instead of below to remove the timer gameStarted = true; restartButton.style.visibility = 'hidden'; initializePlayers(); // Check if the countdown has finished if (elapsedTime >= couM // If so, set the flag to indicate that the game has started gameStarted = true; initializePlayers(); else // If not, draw the countdown on the canvas const countdown = Math.ceil((countdownTime - elapsedTime) / 1000); ctx.font = "72px Arial"; ctx.fillStyle = "white"; ctx.texM ctx.fillText(countdown, canvas.width / 2, canvas.height / 2); // Request the next frame of the game loop requestAnimationFrame(gameLoop); return; if(gameStarted) updateDeltaTime(); drawOpponents(); checkCollisions(); if(gameOver == false) if(!isM moveOpponents(); movePlayer(deltaTime); // Update the game score and draw it in the top left of the canvas gameScore += deltaTime / 1000; displayGameOverMessage(); drawPlayer(playerX, playerY); ctx.font = "24px Arial"; ctx.fillStyle = "white"; ctx.baseline = 'top'; ctx.textAlign = 'left'; ctx.fillText(`Score: ${Math.floor(gameScore)}`, 10, 40); displayHighScore(); // Request the next frame of the game loop requestAnimationFrame(gameLoop); function moveOpponents() // Update the positions of the opposing team members opponents.forEach(opponent => // Check if the opponent is waiting if (!opponent.waitTime) // If not, set a new wait time and jitter value opponent.waitTime = Math.floor(Math.random() * (waitTimeMax - waitTimeMin)) + waitTimeMin; opponent.jitter = { x: Math.floor(Math.random() * (jitterRange * 2)) - jitterRange, y: Math.floor(Math.random() * (jitterRange * 2)) - jitterRange }; opponent.jitterTime = 0; else // If so, update the jitter valM opponent.jitterTime += deltaTime; if (opponent.jitterTime >= 1000 / 60) { opponent.jitter.x = Math.floor(Math.random() * (jitterRange * 2)) - jitterRange; opponent.jitter.y = Math.floor(Math.random() * (jitterRange * 2)) - jitterRange; opponent.jitterTime = 0; } // Subtract the time elapsed since the last frame from the wait time opponent.waitTime -= deltaTime; if (opponent.waitTime <= 0) { // If the wait time has elapsed, reset it and calculate a new direction towards the player opponent.waitTime = 0; const dx = playerX - (opponent.x + opponentSize / 2); const dy = playerY - (opponent.y + opponentSize / 2); const distance = Math.sqrt(dx * dx + dy * dy); M opponent.dx = dx / distance * opponentSpeed; opponent.dy = dy / distance * opponentSpeed; } // Update the position of the opponent based on its direction and jitter value opponent.x += (opponent.dx || 0) * deltaTime / 1000 + opponent.jitter.x; opponent.y += (opponent.dy || 0) * deltaTime / 1000 + opponent.jitter.y; // Draw the opponent at its updated position //ctx.filM lRect(opponent.x, opponent.y, opponentSize, opponentSize); function pauseGame() isPaused = !isPaused; const pauseButtonText = isPaused ? "Resume" : "Pause"; pauseButton.innerText = pauseButtonText; // Function to restart the game function restartGame() //Redisplay highscore highScore = localStorage.getItem('zombiePixelsHighScore') || 0; // Reset any necessary gM pauseButton.style.visibility = 'visible'; restartButton.style.visibility = 'hidden'; playerX = gamecanvas.width / 2; playerY = gamecanvas.height / 2; gameScore = 0; opponents.length = 0; gameOver = false; initializePlayers(); function displayHighScore() // Get the canvas element and its context const canvas = document.getElementById("game-canvas"); const ctx = canvas.getContext("2d"); ctx.font = "24px Arial"; ctx.fillStyle = "cyan"; ctx.baseline = 'bottom'; ctx.textAlign = 'left'; ctx.fillText(`High Score: ${Math.floor(highScore)}`, 10, 20); // Start the game loop let lastFrameTime = Date.now(); let gameScore = 0; let highScore = localStorage.getItem('zombiePixelsHighScore') || 0; text/plain;charset=utf-8 @{"p":"brc-20","op":"deploy","tick":" ","max":"300","lim":"1"}h! text/plain;charset=utf-8 @{"p":"brc-20","op":"deploy","tick":" ","max":"300","lim":"1"}h! text/plain;charset=utf-8 @{"p":"brc-20","op":"deploy","tick":" ","max":"300","lim":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10k","amt":"1"}h! text/plain;charset=utf-8 /{"p":"sns","op":"reg","name":"evangelion.sats"}h! text/plain;charset=utf-8 +{"p":"sns","op":"reg","name":" text/plain;charset=utf-8 +{"p":"sns","op":"reg","name":" text/plain;charset=utf-8 +{"p":"sns","op":"reg","name":" text/plain;charset=utf-8 +{"p":"sns","op":"reg","name":" 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"JEUS","amt":"777"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"JEUS","amt":"777"}h! text/plain;charset=utf-8 1d/Foundry USA Pool #dropgold/ Bj@=:ETH.ETH:0xe54119f9CbD77e97802Aa1470b35cDB2a1D04b17:22733487::0 HjF=:BNB.TWT-8C2:bnb1c48eg622z27l67wfmffl7pqq4n05qw7xj0m363:4923825051::0 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 Lb{"p":"orditalk.org","op":"create_user","name":"Thoth","profile_picture_inscription_id":"c7c38d49"}h! text/plain;charset=utf-8 %&'()*456789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz &'()*56789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz text/plain;charset=utf-8 text/plain;charset=utf-8 @{"p":"brc-20","op":"deploy","tick":" ","max":"300","lim":"1"}h! text/plain;charset=utf-8 @{"p":"brc-20","op":"deploy","tick":" ","max":"300","lim":"1"}h! text/html;charset=utf-8 <meta charset="utf-8" /> position: relative; width: var(--width); height: var(--height); border: 1px solid blue; position: relative; <div id="upload"> <input id="inputUpload" type="file"> function e(e){"use strict";return new function e(t){let n="global"==t?window:this;n.canvas=document.createElement("canvas");let r=n.canvas.getContext("2d");n.width=100,n.height=100,n.canvas.width=n.width,n.canvas.height=n.height,"offscreen"!=t&&(document.body?document.body.appendChild(n.canvas):window.addEventListener("load",(function(){document.body.appendChild(n.canvas)}))),g(),n.MAGIC=161533525,n.RGB=0,n.HSV=1,n.HM SB=1,n.CHORD=0,n.PIE=1,n.OPEN=2,n.RADIUS=1,n.CORNER=2,n.CORNERS=3,n.ROUND="round",n.SQUARE="butt",n.PROJECT="square",n.MITER="miter",n.BEVEL="bevel",n.CLOSE=1,n.BLEND="source-over",n.REMOVE="destination-out",n.ADD="lighter",n.DARKEST="darken",n.LIGHTEST="lighten",n.DIFFERENCE="difference",n.SUBTRACT="subtract",n.EXCLUSION="exclusion",n.MULTIPLY="multiply",n.SCREEN="screen",n.REPLACE="copy",n.OVERLAY="overlay",n.HARD_LIGHT="hard-light",n.SOFT_LIGHT="soft-light",n.DODGE="color-dodge",n.BURN="color-burn",n.NORMAL="norM mal",n.ITALIC="italic",n.BOLD="bold",n.BOLDITALIC="italic bold",n.CENTER="center",n.LEFT="left",n.RIGHT="right",n.TOP="top",n.BOTTOM="bottom",n.BASELINE="alphabetic",n.LANDSCAPE="landscape",n.PORTRAIT="portrait",n.ALT=18,n.BACKSPACE=8,n.CONTROL=17,n.DELETE=46,n.DOWN_ARROW=40,n.ENTER=13,n.ESCAPE=27,n.LEFT_ARROW=37,n.OPTION=18,n.RETURN=13,n.RIGHT_ARROW=39,n.SHIFT=16,n.TAB=9,n.UP_ARROW=38,n.HALF_PI=Math.PI/2,n.PI=Math.PI,n.QUARTER_PI=Math.PI/4,n.TAU=2*Math.PI,n.TWO_PI=2*Math.PI,n.THRESHOLD=1,n.GRAY=2,n.OPAQUE=3,n.INVEM RT=4,n.POSTERIZE=5,n.DILATE=6,n.ERODE=7,n.BLUR=8,n.ARROW="default",n.CROSS="crosshair",n.HAND="pointer",n.MOVE="move",n.TEXT="text",n.VIDEO={video:!0,audio:!1},n.AUDIO={video:!1,audio:!0},n.SHR3=1,n.LCG=2,n.HARDWARE_FILTERS=!0,n.hint=function(e,t){n[e]=t},n.frameCount=0,n.mouseX=0,n.mouseY=0,n.pmouseX=0,n.pmouseY=0,n.mouseButton=null,n.keyIsPressed=!1,n.mouseIsPressed=!1,n.key=null,n.keyCode=null,n.pixels=null,n.accelerationX=0,n.accelerationY=0,n.accelerationZ=0,n.rotationX=0,n.rotationY=0,n.rotationZ=0,n.relRotatM ionX=0,n.relRotationY=0,n.relRotationZ=0,n.pAccelerationX=0,n.pAccelerationY=0,n.pAccelerationZ=0,n.pRotationX=0,n.pRotationY=0,n.pRotationZ=0,n.pRelRotationX=0,n.pRelRotationY=0,n.pRelRotationZ=0,n.touches=[],n._styleCache=[{colorMode:n.RGB,noStroke:!1,noFill:!1,ellipseMode:n.CENTER,rectMode:n.CORNER,curveDetail:20,curveAlpha:0,textFont:"sans-serif",textSize:12,textLeading:12,textStyle:"normal"}],n._style=n._styleCache[n._styleCache.length-1],n._noLoop=!1,n._pixelDensity=1,n._frameRate=null,n._tint=null;let i=nullM ,o=!0,a=[],l=null,s=0,h={},c=0,u=null,f=null,d=null;Object.defineProperty(n,"deviceOrientation",{get:function(){return 90==Math.abs(window.orientation)?n.LANDSCAPE:n.PORTRAIT}}),Object.defineProperty(n,"windowWidth",{get:function(){return window.innerWidth}}),Object.defineProperty(n,"windowHeight",{get:function(){return window.innerHeight}}),Object.defineProperty(n,"drawingContext",{get:function(){return r}}),n.createCanvas=function(e,t){return n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t,g(),n.canvas},nM .resizeCanvas=function(e,t){n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t},n.createGraphics=n.createImage=function(t,n){let r=new e("offscreen");return r.createCanvas(t,n),r.noLoop(),r},n.pixelDensity=function(e){return null==e||(n._pixelDensity=e,n.canvas.width=Math.ceil(n.width*e),n.canvas.height=Math.ceil(n.height*e),n.canvas.style.width=n.width+"px",n.canvas.style.height=n.height+"px",r.scale(n._pixelDensity,n._pixelDensity),g()),n._pixelDensity},n.map=function(e,t,n,r,i,o){let a=r+1*(e-t)/(n-t)*(i-r)M ;return o?r<i?Math.min(Math.max(a,r),i):Math.min(Math.max(a,i),r):a},n.lerp=function(e,t,n){return e*(1-n)+t*n},n.constrain=function(e,t,n){return Math.min(Math.max(e,t),n)},n.dist=function(){return 4==arguments.length?Math.hypot(arguments[0]-arguments[2],arguments[1]-arguments[3]):Math.hypot(arguments[0]-arguments[3],arguments[1]-arguments[4],arguments[2]-arguments[5])},n.norm=function(e,t,r){return n.map(e,t,r,0,1)},n.sq=function(e){return e*e},n.fract=function(e){return e-Math.floor(e)},n.degrees=function(e){retM urn 180*e/Math.PI},n.radians=function(e){return e*Math.PI/180},n.abs=Math.abs,n.ceil=Math.ceil,n.exp=Math.exp,n.floor=Math.floor,n.log=Math.log,n.mag=Math.hypot,n.max=Math.max,n.min=Math.min,n.round=Math.round,n.sqrt=Math.sqrt,n.sin=Math.sin,n.cos=Math.cos,n.tan=Math.tan,n.asin=Math.asin,n.acos=Math.acos,n.atan=Math.atan,n.atan2=Math.atan2,n.Vector=function(e,t,r){let i=this;i.x=e||0,i.y=t||0,i.z=r||0;let o=null,a=null;function l(e,t,n){return null!=e.x?e:null!=t?{x:e,y:t,z:n||0}:{x:e,y:e,z:e}}function s(){null==a&M &(a=i.x*i.x+i.y*i.y+i.z*i.z,o=Math.sqrt(a))}function h(){a=null,o=null}i.set=function(e,t,n){i.x=e||0,i.y=t||0,i.z=n||0},i.copy=function(){return new n.Vector(i.x,i.y,i.z)},i.add=function(){let e=l.apply(null,arguments);return i.x+=e.x,i.y+=e.y,i.z+=e.z,h(),i},i.rem=function(){let e=l.apply(null,arguments);return i.x%=e.x,i.y%=e.y,i.z%=e.z,h(),i},i.sub=function(){let e=l.apply(null,arguments);return i.x-=e.x,i.y-=e.y,i.z-=e.z,h(),i},i.mult=function(){let e=l.apply(null,arguments);return i.x*=e.x,i.y*=e.y,i.z*=e.z,hM (),i},i.div=function(){let e=l.apply(null,arguments);return i.x/=e.x,i.y/=e.y,i.z/=e.z,h(),i},i.mag=function(){return s(),o},i.magSq=function(){return s(),a},i.dot=function(){let e=l.apply(null,arguments);return i.x*e.x+i.y*e.y+i.z*e.z},i.dist=function(){let e=l.apply(null,arguments),t=i.x-e.x,n=i.y-e.y,r=i.z-e.z;return Math.sqrt(t*t+n*n+r*r)},i.cross=function(){let e=l.apply(null,arguments),t=i.y*e.z-i.z*e.y,n=i.z*e.x-i.x*e.z,r=i.x*e.y-i.y*e.x;return i.x=t,i.y=n,i.z=r,h(),i},i.normalize=function(){s();let e=o;retuM rn i.x/=e,i.y/=e,i.z/=e,o=1,a=1,i},i.limit=function(e){s();if(o>e){let t=e/o;i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e}return i},i.setMag=function(e){s();let t=e/o;return i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e,i},i.heading=function(){return Math.atan2(i.y,i.x)},i.rotate=function(e){let t=Math.cos(e),n=Math.sin(e),r=i.x*t-i.y*n,o=i.x*n+i.y*t;return i.x=r,i.y=o,i},i.angleBetween=function(){let e=l.apply(null,arguments);const t=i.dot(e)/(i.mag()*e.mag());let n;return n=Math.acos(Math.min(1,Math.max(-1,t))),n*Math.sign(i.cross(e).z||1)},M i.lerp=function(e,t){return i.x=i.x*(1-t)+e.x*t,i.y=i.y*(1-t)+e.y*t,i.z=i.z*(1-t)+e.z*t,h(),i},i.reflect=function(e){return e.normalize(),i.sub(e.mult(2*i.dot(e)))},i.array=function(){return[i.x,i.y,i.z]},i.equals=function(e,t){return null==t&&null==(t=Number.EPSILON)&&(t=0),Math.abs(e.x-i.x)<t&&Math.abs(e.y-i.y)<t&&Math.abs(e.z-i.z)<t},i.fromAngle=function(e,t){return null==t&&(t=1),o=t,a=t*t,i.x=t*Math.cos(e),i.y=t*Math.sin(e),i.z=0,i},i.fromAngles=function(e,t,n){null==n&&(n=1),o=n,a=n*n;const r=Math.cos(t),l=MaM th.sin(t),s=Math.cos(e),h=Math.sin(e);return i.x=n*h*l,i.y=-n*s,i.z=n*h*r,i},i.random2D=function(){return o=1,a=1,i.fromAngle(Math.random()*Math.PI*2)},i.random3D=function(){return o=1,a=1,i.fromAngles(Math.random()*Math.PI*2,Math.random()*Math.PI*2)},i.toString=function(){return`[${i.x}, ${i.y}, ${i.z}]`}},n.Vector.add=function(e,t){return new n.Vector(e.x+t.x,e.y+t.y,e.z+t.z)},n.Vector.rem=function(e,t){return new n.Vector(e.x%t.x,e.y%t.y,e.z%t.z)},n.Vector.sub=function(e,t){return new n.Vector(e.x-t.x,e.y-t.y,e.M z-t.z)},n.Vector.mult=function(e,t){return null==t.x?new n.Vector(e.x*t,e.y*t,e.z*t):new n.Vector(e.x*t.x,e.y*t.y,e.z*t.z)},n.Vector.div=function(e,t){return null==t.x?new n.Vector(e.x/t,e.y/t,e.z/t):new n.Vector(e.x/t.x,e.y/t.y,e.z/t.z)},n.Vector.dist=function(e,t){return Math.hypot(e.x-t.x,e.y-t.y,e.z-t.z)},n.Vector.cross=function(e,t){return new n.Vector(e.y*t.z-e.z*t.y,e.z*t.x-e.x*t.z,e.x*t.y-e.y*t.x)},n.Vector.lerp=function(e,t,r){return new n.Vector(e.x*(1-r)+t.x*r,e.y=e.y*(1-r)+t.y*r,e.z=e.z*(1-r)+t.z*r)},n.M Vector.equals=function(e,t,n){return e.equals(t,n)};for(let e of["fromAngle","fromAngles","random2D","random3D"])n.Vector[e]=function(t,r,i){return(new n.Vector)[e](t,r,i)};function x(e,t,n){let r,i,o,a,l,s,h,c,u;if(0==t)return[255*(r=n),255*(i=n),255*(o=n)];switch((a=e)>360&&(a=0),h=n*(1-t),c=n*(1-t*(s=(a/=60)-(l=~~a))),u=n*(1-t*(1-s)),l){case 0:r=n,i=u,o=h;break;case 1:r=c,i=n,o=h;break;case 2:r=h,i=n,o=u;break;case 3:r=h,i=c,o=n;break;case 4:r=u,i=h,o=n;break;default:r=n,i=h,o=c}return[255*r,255*i,255*o]}functioM n g(){r.fillStyle="white",r.strokeStyle="black",r.lineCap="round",r.lineJoin="miter"}function p(e){if(0<=e&&e<2*Math.PI)return e;for(;e<0;)e+=2*Math.PI;for(;e>=Math.PI;)e-=2*Math.PI;return e}function m(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;let c=p(a),u=p(l);r.beginPath();for(let a=0;a<h+1;a++){let l=a/h,s=n.lerp(c,u,l),f=Math.cos(s)*i/2,d=Math.sin(s)*o/2;r[a?"lineTo":"moveTo"](e+f,t+d)}s==n.CHORD?r.closePath():s==n.PIE&&(r.lineTo(e,t),r.closePath()),n._style.noFill||r.fill(),n._style.noStrokM e||r.stroke()}function b(e,t,i,o){n._style.noFill&&n._style.noStroke||(r.beginPath(),r.ellipse(e,t,i/2,o/2,0,0,2*Math.PI),n._style.noFill||r.fill(),n._style.noStroke||r.stroke())}function y(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;if(null==a)return function(e,t,i,o){n._style.noFill||r.fillRect(e,t,i,o),n._style.noStroke||r.strokeRect(e,t,i,o)}(e,t,i,o);if(null==l)return y(e,t,i,o,a,a,a,a);const c=Math.min(Math.abs(o),Math.abs(i))/2;a=Math.min(c,a),l=Math.min(c,l),h=Math.min(c,h),s=Math.min(c,s)M ,r.beginPath(),r.moveTo(e+a,t),r.arcTo(e+i,t,e+i,t+o,l),r.arcTo(e+i,t+o,e,t+o,s),r.arcTo(e,t+o,e,t,h),r.arcTo(e,t,e+i,t,a),r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke()}function w(){a=[]}n.createVector=function(e,t,r){return new n.Vector(e,t,r)},n.curvePoint=function(e,t,n,r,i){const o=i*i*i,a=i*i;return e*(-.5*o+a-.5*i)+t*(1.5*o-2.5*a+1)+n*(-1.5*o+2*a+.5*i)+r*(.5*o-.5*a)},n.bezierPoint=function(e,t,n,r,i){const o=1-i;return Math.pow(o,3)*e+3*Math.pow(o,2)*i*t+3*o*Math.pow(i,2)*n+Math.pow(i,M 3)*r},n.curveTangent=function(e,t,n,r,i){const o=i*i;return e*(-3*o/2+2*i-.5)+t*(9*o/2-5*i)+n*(-9*o/2+4*i+.5)+r*(3*o/2-i)},n.bezierTangent=function(e,t,n,r,i){const o=1-i;return 3*r*Math.pow(i,2)-3*n*Math.pow(i,2)+6*n*o*i-6*t*o*i+3*t*Math.pow(o,2)-3*e*Math.pow(o,2)},n.Color=function(e,t,n,r){let i=this;i.MAGIC=786698,i._r=e,i._g=t,i._b=n,i._a=r,i._h=0,i._s=0,i._v=0,i._hsvInferred=!1,i.setRed=function(e){i._r=e,i._hsvInferred=!1},i.setGreen=function(e){i._g=e,i._hsvInferred=!1},i.setBlue=function(e){i._b=e,i._hsvInfM erred=!1},i.setAlpha=function(e){i._a=e/255,i._hsvInferred=!1},i._inferHSV=function(){i._hsvInferred||([i._h,i._s,i._v]=function(e,t,n){let r,i,o,a,l;return r=e<t?e<n?e:n:t<n?t:n,0==(l=100*(i=e>t?e>n?e:n:t>n?t:n)/255)?[o=0,a=0,l]:0==(a=100*(i-r)/i)?[o=0,a,l]:(o=i==e?0+60*(t-n)/(i-r):i==t?120+60*(n-e)/(i-r):240+60*(e-t)/(i-r),[o,a,l])}(i._r,i._g,i._b),i._hsvInferred=!0)},i.toString=function(){return`rgba(${Math.round(i._r)},${Math.round(i._g)},${Math.round(i._b)},${~~(1e3*i._a)/1e3})`}},n.colorMode=function(e){n._stM yle.colorMode=e},n.color=function(){if(1==arguments.length&&786698==arguments[0].MAGIC)return arguments[0];if(n._style.colorMode==n.RGB){if(1==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],1);if(2==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],arguments[1]/255);if(3==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],1);if(4==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],arguments[3]/255)}else{if(1==argumeM nts.length)return new n.Color(...x(0,0,arguments[0]/100),1);if(2==arguments.length)return new n.Color(...x(0,0,arguments[0]/100),arguments[1]/255);if(3==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),1);if(4==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),arguments[3])}return null},n.red=function(e){return e._r},n.green=function(e){return e._g},n.blue=function(e){return e._b},n.alpha=function(e){return 255*e._a},n.hue=function(e){reM turn e._inferHSV(),e._h},n.saturation=function(e){return e._inferHSV(),e._s},n.brightness=function(e){return e._inferHSV(),e._v},n.lightness=function(e){return 100*(.2126*e._r+.7152*e._g+.0722*e._b)/255},n.lerpColor=function(e,t,r){return n._style.colorMode==n.RGB?new n.Color(n.constrain(n.lerp(e._r,t._r,r),0,255),n.constrain(n.lerp(e._g,t._g,r),0,255),n.constrain(n.lerp(e._b,t._b,r),0,255),n.constrain(n.lerp(e._a,t._a,r),0,1)):(e._inferHSV(),t._inferHSV(),new n.Color(n.constrain(function(e,t,r){var i=[[Math.abs(t-M e),n.map(r,0,1,e,t)],[Math.abs(t+360-e),n.map(r,0,1,e,t+360)],[Math.abs(t-360-e),n.map(r,0,1,e,t-360)]];return i.sort(((e,t)=>e[0]-t[0])),(i[0][1]+720)%360}(e._h,t._h,r),0,360),n.constrain(n.lerp(e._s,t._s,r),0,100),n.constrain(n.lerp(e._v,t._v,r),0,100),n.constrain(n.lerp(e._a,t._a,r),0,1)))},n.strokeWeight=function(e){n._style_noStroke=!1,r.lineWidth=e},n.stroke=function(){if(n._style.noStroke=!1,"string"==typeof arguments[0])return void(r.strokeStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._sM tyle.noStroke=!0:r.strokeStyle=e},n.noStroke=function(){n._style.noStroke=!0},n.fill=function(){if(n._style.noFill=!1,"string"==typeof arguments[0])return void(r.fillStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._style.noFill=!0:r.fillStyle=e},n.noFill=function(){n._style.noFill=!0},n.blendMode=function(e){r.globalCompositeOperation=e},n.strokeCap=function(e){r.lineCap=e},n.strokeJoin=function(e){r.lineJoin=e},n.ellipseMode=function(e){n._style.ellipseMode=e},n.rectMode=function(e){n._style.rectM Mode=e},n.curveDetail=function(e){n._style.curveDetail=e},n.curveAlpha=function(e){n._style.curveAlpha=e},n.curveTightness=function(e){n._style.curveAlpha=e},n.clear=function(){r.clearRect(0,0,n.width,n.height)},n.background=function(){if(arguments[0]&&arguments[0].MAGIC==n.MAGIC)return n.image(arguments[0],0,0,n.width,n.height);r.save(),r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity),r.fillStyle="string"==typeof arguments[0]?arguments[0]:n.color(...Array.from(arguments)),r.fillRect(0,0,n.width,n.heightM ),r.restore()},n.line=function(e,t,i,o){n._style.noStroke||(r.beginPath(),r.moveTo(e,t),r.lineTo(i,o),r.stroke())},n.arc=function(e,t,r,i,o,a,l,s){if(o==a)return n.ellipse(e,t,r,i);null==s&&(s=25),null==l&&(l=n.PIE),n._style.ellipseMode==n.CENTER?m(e,t,r,i,o,a,l,s):n._style.ellipseMode==n.RADIUS?m(e,t,2*r,2*i,o,a,l,s):n._style.ellipseMode==n.CORNER?m(e+r/2,t+i/2,r,i,o,a,l,s):n._style.ellipseMode==n.CORNERS&&m((e+r)/2,(t+i)/2,r-e,i-t,o,a,l,s)},n.ellipse=function(e,t,r,i){null==i&&(i=r),n._style.ellipseMode==n.CENTERM ?b(e,t,r,i):n._style.ellipseMode==n.RADIUS?b(e,t,2*r,2*i):n._style.ellipseMode==n.CORNER?b(e+r/2,t+i/2,r,i):n._style.ellipseMode==n.CORNERS&&b((e+r)/2,(t+i)/2,r-e,i-t)},n.circle=function(e,t,r){return n.ellipse(e,t,r,r)},n.point=function(e,t){e.x&&(t=e.y,e=e.x),r.beginPath(),r.ellipse(e,t,.4,.4,0,0,2*Math.PI),r.stroke()},n.rect=function(e,t,r,i,o,a,l,s){n._style.rectMode==n.CENTER?y(e-r/2,t-i/2,r,i,o,a,l,s):n._style.rectMode==n.RADIUS?y(e-r,t-i,2*r,2*i,o,a,l,s):n._style.rectMode==n.CORNER?y(e,t,r,i,o,a,l,s):n._stylM e.rectMode==n.CORNERS&&y(e,t,r-e,i-t,o,a,l,s)},n.square=function(e,t,r,i,o,a,l){return n.rect(e,t,r,r,i,o,a,l)},n.beginShape=function(){w(),r.beginPath(),o=!0},n.beginContour=function(){r.closePath(),w(),o=!0},n.endContour=function(){w(),o=!0},n.vertex=function(e,t){w(),o?r.moveTo(e,t):r.lineTo(e,t),o=!1},n.bezierVertex=function(e,t,n,i,o,a){w(),r.bezierCurveTo(e,t,n,i,o,a)},n.quadraticVertex=function(e,t,n,i){w(),r.quadraticCurveTo(e,t,n,i)},n.bezier=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.bezierVM ertex(r,i,o,a,l,s),n.endShape()},n.triangle=function(e,t,r,i,o,a){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.endShape(n.CLOSE)},n.quad=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.vertex(l,s),n.endShape(n.CLOSE)},n.endShape=function(e){w(),e&&r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke(),n._style.noFill&&n._style.noStroke&&(r.save(),r.fillStyle="none",r.fill(),r.restore())},n.curveVertex=function(e,t){if(a.push([e,t]),a.length<4)return;M let i=function(e,t,n,r,i,o,a,l,s,h){function c(e,t,n,r,i,o){let a=Math.pow(r-t,2)+Math.pow(i-n,2);return Math.pow(a,.5*o)+e}let u=[],f=c(0,e,t,n,r,h),d=c(f,n,r,i,o,h),x=c(d,i,o,a,l,h);for(let h=0;h<s;h++){let c=f+h/(s-1)*(d-f),g=[(f-c)/(f-0),(c-0)/(f-0),(d-c)/(d-f),(c-f)/(d-f),(x-c)/(x-d),(c-d)/(x-d),(d-c)/(d-0),(c-0)/(d-0),(x-c)/(x-f),(c-f)/(x-f)];for(let e=0;e<g.length;e+=2)isNaN(g[e])&&(g[e]=1,g[e+1]=0),isFinite(g[e])||(g[e]>0?(g[e]=1,g[e+1]=0):(g[e]=0,g[e+1]=1));let p=e*g[0]+n*g[1],m=t*g[0]+r*g[1],b=n*g[2]+i*g[M 3],y=r*g[2]+o*g[3],w=i*g[4]+a*g[5],v=o*g[4]+l*g[5],z=p*g[6]+b*g[7],V=m*g[6]+y*g[7],_=b*g[8]+w*g[9],M=y*g[8]+v*g[9],E=z*g[2]+_*g[3],S=V*g[2]+M*g[3];u.push([E,S])}return u}(...a[a.length-4],...a[a.length-3],...a[a.length-2],...a[a.length-1],n._style.curveDetail,n._style.curveAlpha);for(let e=0;e<i.length;e++)o?r.moveTo(...i[e]):r.lineTo(...i[e]),o=!1},n.curve=function(e,t,r,i,o,a,l,s){n.beginShape(),n.curveVertex(e,t),n.curveVertex(r,i),n.curveVertex(o,a),n.curveVertex(l,s),n.endShape()},n.translate=function(e,t){r.tM ranslate(e,t)},n.rotate=function(e){r.rotate(e)},n.scale=function(e,t){null==t&&(t=e),r.scale(e,t)},n.applyMatrix=function(e,t,n,i,o,a){r.transform(e,t,n,i,o,a)},n.shearX=function(e){r.transform(1,0,Math.tan(e),1,0,0)},n.shearY=function(e){r.transform(1,Math.tan(e),0,1,0,0)},n.resetMatrix=function(){r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity)},n.pushMatrix=n.push=function(){n._styleCache.push({...n._style}),n._style=n._styleCache[n._styleCache.length-1],r.save()},n.popMatrix=n.pop=function(){n._stylM eCache.length-1&&(n._styleCache.pop(),n._style=n._styleCache[n._styleCache.length-1],r.restore())},n.image=function(e,t,i,o,a,l,s,h,c){let u=e.MAGIC==n.MAGIC?e.canvas:e;function d(){if(e.MAGIC!=n.MAGIC||!n._tint)return;let t=e.canvas.getContext("2d");t.save(),t.resetTransform(),t.clearRect(0,0,t.canvas.width,t.canvas.height),t.drawImage(f.canvas,0,0),t.restore()}return e.MAGIC==n.MAGIC&&null!=n._tint&&(function(e,t){null==f&&(f=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvasM .height),f.canvas.width==e&&f.canvas.height==t||(f.canvas.width=e,f.canvas.height=t)}(e.canvas.width,e.canvas.height),f.drawImage(e.canvas,0,0),e.tinted(n._tint)),o?l?(h||(h=u.width),c||(c=u.height),r.drawImage(u,l,s,h,c,t,i,o,a),void d()):(r.drawImage(u,t,i,o,a),void d()):(e.MAGIC==n.MAGIC||e.width?r.drawImage(u,t,i,e.width,e.height):r.drawImage(u,t,i,e.videoWidth,e.videoHeight),void d())},n.loadPixels=function(){l=r.getImageData(0,0,n.canvas.width,n.canvas.height),n.pixels=l.data},n.updatePixels=function(){null!=M l&&r.putImageData(l,0,0)},n.loadImage=function(e,t){s++;let r=n.createGraphics(100,100),i=r.canvas.getContext("2d"),o=new Image;return o.src=e,o.crossOrigin="Anonymous",o.onload=function(){i.canvas.width=o.width,i.canvas.height=o.height,r.width=o.width,r.height=o.height,i.drawImage(o,0,0),s--,t&&t(r)},r};let v={};function z(e,t){null==u&&(u=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvas.height),u.canvas.width==e&&u.canvas.height==t||(u.canvas.width=e,u.canvas.height=t)}funcM tion V(){let e=r.canvas.width*r.canvas.height*4;null!=d&&e==d.length||(d=new Uint8ClampedArray(e))}function _(e){u.clearRect(0,0,u.canvas.width,u.canvas.height),u.filter=e,u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()}v[n.THRESHOLD]=function(e,t){null==t?t=127.5:t*=255;for(let n=0;n<e.length;n+=4){const r=.2126*e[n]+.7152*e[n+1]+.0722*e[n+2];e[n]=e[n+1]=e[n+2]=r>=t?255:0}},v[n.GRAY]=function(e){for(let t=0;t<e.length;t+=4)M {const n=.2126*e[t]+.7152*e[t+1]+.0722*e[t+2];e[t]=e[t+1]=e[t+2]=n}},v[n.OPAQUE]=function(e){for(let t=0;t<e.length;t+=4)e[t+3]=255},v[n.INVERT]=function(e){for(let t=0;t<e.length;t+=4)e[t]=255-e[t],e[t+1]=255-e[t+1],e[t+2]=255-e[t+2]},v[n.POSTERIZE]=function(e,t){let n=t-1;for(let r=0;r<e.length;r+=4)e[r]=255*(e[r]*t>>8)/n,e[r+1]=255*(e[r+1]*t>>8)/n,e[r+2]=255*(e[r+2]*t>>8)/n},v[n.DILATE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-M 1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.max(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.ERODE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.min(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.BLURM ]=function(e,t){t=t||1,t=Math.floor(t*n._pixelDensity),V(),d.set(e);let i=2*t+1,o=function(e){let n=new Float32Array(e),r=.3*t+.8,i=r*r*2;for(let t=0;t<e;t++){let o=t-e/2,a=Math.exp(-o*o/i)/(2.5066282746*r);n[t]=a}return n}(i),[a,l]=[r.canvas.width,r.canvas.height];for(let n=0;n<l;n++)for(let r=0;r<a;r++){let l=0,s=0,h=0,c=0;for(let e=0;e<i;e++){let i=4*(n*a+Math.min(Math.max(r-t+e,0),a-1));l+=d[i]*o[e],s+=d[i+1]*o[e],h+=d[i+2]*o[e],c+=d[i+3]*o[e]}let u=4*(n*a+r);e[u]=l,e[u+1]=s,e[u+2]=h,e[u+3]=c}d.set(e);for(let nM =0;n<l;n++)for(let r=0;r<a;r++){let s=0,h=0,c=0,u=0;for(let e=0;e<i;e++){let i=4*(Math.min(Math.max(n-t+e,0),l-1)*a+r);s+=d[i]*o[e],h+=d[i+1]*o[e],c+=d[i+2]*o[e],u+=d[i+3]*o[e]}let f=4*(n*a+r);e[f]=s,e[f+1]=h,e[f+2]=c,e[f+3]=u}},n.filter=function(e,t){if(n.HARDWARE_FILTERS&&null!=r.filter)if(z(),e==n.THRESHOLD){null==t&&(t=.5),t=Math.max(t,1e-5),_(`saturate(0%) brightness(${Math.floor(.5/t*100)}%) contrast(1000000%)`)}else if(e==n.GRAY)_("saturate(0%)");else if(e==n.OPAQUE)u.fillStyle="black",u.fillRect(0,0,u.canvaM s.width,u.canvas.height),u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.drawImage(u.canvas,0,0),r.restore();else if(e==n.INVERT)_("invert(100%)");else if(e==n.BLUR)_(`blur(${Math.ceil(t*n._pixelDensity/1)||1}px)`);else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}},n.resize=function(e,t){z(),u.drawImage(r.canvas,0,0),n.width=e,n.height=t,r.canvas.width=e*n._pixM elDensity,r.canvas.height=t*n._pixelDensity,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0,r.canvas.width,r.canvas.height),r.restore()},n.get=function(e,t,i,o){if(null!=e&&null==i){let i=r.getImageData(e,t,1,1).data;return new n.Color(i[0],i[1],i[2],i[3]/255)}e=e||0,t=t||0,i=i||n.width,o=o||n.height;let a=n.createGraphics(i,o);a.pixelDensity(n._pixelDensity);let l=r.getImageData(e*n._pixelDensity,t*n._pixelDensity,i*n._pixelDensity,o*n._pixelDensity);return a.caM nvas.getContext("2d").putImageData(l,0,0),a},n.set=function(e,t,i){if(i.MAGIC==n.MAGIC){let r=n._tint;return n._tint=null,n.image(i,e,t),void(n._tint=r)}let o=4*(t*n._pixelDensity*r.canvas.width+e*n._pixelDensity);n.pixels[o]=i._r,n.pixels[o+1]=i._g,n.pixels[o+2]=i._b,n.pixels[o+3]=255*i._a},n.tinted=function(){let e=n.color(...Array.from(arguments)),t=e._a;e._a=1,z(),u.clearRect(0,0,u.canvas.width,u.canvas.height),u.fillStyle=e,u.fillRect(0,0,u.canvas.width,u.canvas.height),u.globalCompositeOperation="multiply",u.M drawImage(r.canvas,0,0),u.globalCompositeOperation="source-over",r.save(),r.resetTransform();let i=r.globalCompositeOperation;r.globalCompositeOperation="source-in",r.drawImage(u.canvas,0,0),r.globalCompositeOperation=i,r.restore(),u.globalAlpha=t,u.clearRect(0,0,u.canvas.width,u.canvas.height),u.drawImage(r.canvas,0,0),u.globalAlpha=1,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()},n.tint=function(){n._tint=n.color(...Array.from(arguments))},n.noTiM nt=function(){n._tint=null},n.mask=function(e){r.save(),r.resetTransform();let t=r.globalCompositeOperation;r.globalCompositeOperation="destination-in",r.drawImage(e.canvas,0,0),r.globalCompositeOperation=t,r.restore()},n.clearTemporaryBuffers=function(){u=null,f=null,d=null},n.save=function(e,t){e=e||"untitled",t=t||"png";var n=document.createElement("a");n.innerHTML="[Download]",n.addEventListener("click",(function(){this.href=r.canvas.toDataURL(),this.download=e+"."+t}),!1),document.body.appendChild(n),n.click()M ,document.body.removeChild(n)},n.saveCanvas=function(e,t,r){if(e.MAGIC==n.MAGIC){r&&e.save(t,r);let n=t.split(".");return e.save(n.slice(0,-1).join("."),n[n.length-1])}if(t)return n.save(e,t);let i=e.split(".");return n.save(i.slice(0,-1).join("."),i[i.length-1])},n.loadFont=function(e){let t=e.split("/"),n=t[t.length-1].split(".")[0].replace(" ",""),r=`@font-face {\n font-family: '${n}';\n src: url('${e}');\n }`;const i=document.createElement("style");return i.textContent=r,document.head.append(M i),n},n.textFont=function(e){n._style.textFont=e},n.textSize=function(e){n._style.textSize=e,n._style.textLeading=e},n.textLeading=function(e){n._style.textLeading=e},n.textStyle=function(e){n._style.textStyle=e},n.textAlign=function(e,t){r.textAlign=e,t&&(r.textBaseline=t==n.CENTER?"middle":t)},n.text=function(e,t,i,o){if(!e)return;if(e=e.toString(),n._style.noFill&&n._style.noStroke)return;r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`;let a=e.split("\n");for(let e=0;e<a.length;e++)n._M style.noFill||r.fillText(a[e],t,i,o),n._style.noStroke||r.strokeText(a[e],t,i,o),i+=n._style.textLeading},n.textWidth=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).width},n.textAscent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBoundingBoxAscent},n.textDescent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBounM dingBoxDescent};var M,E=4,S=.5,R=function(e){return.5*(1-Math.cos(e*Math.PI))};n.noise=function(e,t,n){if(t=t||0,n=n||0,null==M){M=new Array(4096);for(var r=0;r<4096;r++)M[r]=Math.random()}e<0&&(e=-e),t<0&&(t=-t),n<0&&(n=-n);for(var i,o,a,l,s,h=Math.floor(e),c=Math.floor(t),u=Math.floor(n),f=e-h,d=t-c,x=n-u,g=0,p=.5,m=0;m<E;m++){var b=h+(c<<4)+(u<<8);i=R(f),o=R(d),a=M[4095&b],a+=i*(M[b+1&4095]-a),l=M[b+16&4095],a+=o*((l+=i*(M[b+16+1&4095]-l))-a),l=M[4095&(b+=256)],l+=i*(M[b+1&4095]-l),s=M[b+16&4095],l+=o*((s+=i*(M[M b+16+1&4095]-s))-l),g+=(a+=R(x)*(l-a))*p,p*=S,h<<=1,c<<=1,u<<=1,(f*=2)>=1&&(h++,f--),(d*=2)>=1&&(c++,d--),(x*=2)>=1&&(u++,x--)}return g},n.noiseDetail=function(e,t){e>0&&(E=e),t>0&&(S=t)};const I=function(){let e,t,n=4294967295;return{setSeed(r){e=t=(null==r?Math.random()*n:r)>>>0},getSeed:()=>t,rand:()=>(e^=e<<17,e^=e>>13,((e^=e<<5)>>>0)/n)}};let C=I();C.setSeed(),n.noiseSeed=function(e){let t=null==e?4294967295*Math.random():e;M||(M=new Float32Array(4096));for(var n=0;n<4096;n++)t^=t<<17,t^=t>>13,t^=t<<5,M[n]=(t>M >>0)/4294967295},n.randomSeed=function(e){C.setSeed(e)},n.random=function(e,t){return null==e?C.rand():"number"==typeof e?null!=t?C.rand()*(t-e)+e:C.rand()*e:e[~~(e.length*C.rand())]},n.randomGenerator=function(e){e==n.LCG?C=function(){const e=4294967296;let t,n;return{setSeed(r){n=t=(null==r?Math.random()*e:r)>>>0},getSeed:()=>t,rand:()=>(n=(1664525*n+1013904223)%e)/e}}():e==n.SHR3&&(C=I()),C.setSeed()};var T=new function(){var e,t,n,r=new Array(128),i=new Array(256),o=new Array(128),a=new Array(128),l=new Array(2M 56),s=new Array(256),h=function(){return 4294967296*C.rand()-2147483648},c=function(){return.5+2.328306e-10*(h()<<0)};this.SHR3=h,this.UNI=c,this.RNOR=function(){return n=h(),e=127&n,Math.abs(n)<r[e]?n*o[e]:function(){for(var t,i,l,s,u=3.44262;;){if(t=n*o[e],0==e){do{l=c(),s=c(),t=.2904764*-Math.log(l),i=-Math.log(s)}while(i+i<t*t);return n>0?u+t:-u-t}if(a[e]+c()*(a[e-1]-a[e])<Math.exp(-.5*t*t))return t;if(n=h(),e=127&n,Math.abs(n)<r[e])return n*o[e]}}()},this.REXP=function(){return(t=h()>>>0)<r[e=255&t]?t*l[e]:funM ction(){for(var n;;){if(0==e)return 7.69711-Math.log(c());if(n=t*l[e],s[e]+c()*(s[e-1]-s[e])<Math.exp(-n))return n;if((t=h())<i[e=255&t])return t*l[e]}}()},this.zigset=function(){var e,t,n=2147483648,h=4294967296,c=3.442619855899,u=c,f=.00991256303526217,d=7.697117470131487,x=d,g=.003949659822581572;for(e=f/Math.exp(-.5*c*c),r[0]=Math.floor(c/e*n),r[1]=0,o[0]=e/n,o[127]=c/n,a[0]=1,a[127]=Math.exp(-.5*c*c),t=126;t>=1;t--)c=Math.sqrt(-2*Math.log(f/c+Math.exp(-.5*c*c))),r[t+1]=Math.floor(c/u*n),u=c,a[t]=Math.exp(-.5*cM *c),o[t]=c/n;for(e=g/Math.exp(-d),i[0]=Math.floor(d/e*h),i[1]=0,l[0]=e/h,l[255]=d/h,s[0]=1,s[255]=Math.exp(-d),t=254;t>=1;t--)d=-Math.log(g/d+Math.exp(-d)),i[t+1]=Math.floor(d/x*h),x=d,s[t]=Math.exp(-d),l[t]=d/h}};T.hasInit=!1,n.randomGaussian=function(e,t){return T.hasInit||(T.zigset(),T.hasInit=!0),T.RNOR()*t+e},n.randomExponential=function(){return T.hasInit||(T.zigset(),T.hasInit=!0),T.REXP()},n.print=console.log,n.cursor=function(e,t,r){let i="";e.includes(".")&&(e=`url("${e}")`,i=", auto"),null!=t&&(e+=" "+t+M " "+r),n.canvas.style.cursor=e+i},n.noCursor=function(){n.canvas.style.cursor="none"},n.createCapture=function(e){var t=document.createElement("video");return t.playsinline="playsinline",t.autoplay="autoplay",navigator.mediaDevices.getUserMedia(e).then((function(e){t.srcObject=e})),t.style.position="absolute",t.style.opacity=1e-5,t.style.zIndex=-1e3,document.body.appendChild(t),t};let A=["setup","draw","preload","mouseMoved","mousePressed","mouseReleased","mouseDragged","mouseClicked","keyPressed","keyReleased","keM yTyped","touchStarted","touchEnded"];for(let e of A){let t="_"+e+"Fn";n[t]=function(){},n[t].isPlaceHolder=!0,n[e]?n[t]=n[e]:Object.defineProperty(n,e,{set:function(e){n[t]=e}})}function D(){n._noLoop||(i=null==n._frameRate?requestAnimationFrame(D):setTimeout(D,1e3/n._frameRate)),w(),o=!0,n.push(),n._drawFn(),n.pop(),++n.frameCount}function k(e){const t=n.canvas.getBoundingClientRect(),r=n.canvas.scrollWidth/n.width||1,i=n.canvas.scrollHeight/n.height||1;return{x:(e.clientX-t.left)/r,y:(e.clientY-t.top)/i,id:e.idenM tifier}}function L(){return n._touchStarted.isPlaceHolder&&n._touchMoved.isPlaceHolder&&n._touchEnded.isPlaceHolder}n.noLoop=function(){n._noLoop=!0,i=null},n.loop=function(){n._noLoop=!1,null==i&&D()},n.redraw=function(){D()},n.frameRate=function(e){n._frameRate=e},setTimeout((function(){n._preloadFn(),c=window.performance.now(),function e(){if(s>0)return setTimeout(e,10);n._setupFn(),D()}()}),1),n.canvas.onmousemove=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPM ressed?n._mouseDraggedFn(e):n._mouseMovedFn(e)},n.canvas.onmousedown=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!0,n.mouseButton=[n.LEFT,n.CENTER,n.RIGHT][e.button],n._mousePressedFn(e)},n.canvas.onmouseup=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!1,n._mouseReleasedFn(e)},n.canvas.onclick=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressedM =!0,n._mouseClickedFn(e),n.mouseIsPressed=!1},window.addEventListener("keydown",(function(e){n.keyIsPressed=!0,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!0,n._keyPressedFn(e),1==e.key.length&&n._keyTypedFn(e)})),window.addEventListener("keyup",(function(e){n.keyIsPressed=!1,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!1,n._keyReleasedFn(e)})),n.keyIsDown=function(e){return!!h[e]},n.canvas.ontouchstart=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.moM useY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mousePressedFn(e)||e.preventDefault()),n._touchStartedFn(e)||e.preventDefault()},n.canvas.ontouchmove=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mouseDraggedFn(e)||e.preventDefault()),n._touchMovedFn(e)||e.preventDefault()},n.canvas.ontouchend=n.canvas.ontouchcancel=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.M mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!1,n._mouseReleasedFn(e)||e.preventDefault()),n._touchEndedFn(e)||e.preventDefault()},n.hasSensorPermission=!window.DeviceOrientationEvent&&!window.DeviceMotionEvent||!(DeviceOrientationEvent.requestPermission||DeviceMotionEvent.requestPermission),n.requestSensorPermissions=function(){DeviceOrientationEvent.requestPermission&&DeviceOrientationEvent.requestPermission().then((e=>{"granted"==e&&DeviceMotionEvent.requestPermissioM n&&DeviceMotionEvent.requestPermission().then((e=>{"granted"==e&&(n.hasSensorPermission=!0)})).catch(alert)})).catch(alert)},window.ondeviceorientation=function(e){n.pRotationX=n.rotationX,n.pRotationY=n.rotationY,n.pRotationZ=n.rotationZ,n.pRelRotationX=n.relRotationX,n.pRelRotationY=n.relRotationY,n.pRelRotationZ=n.relRotationZ,n.rotationX=e.beta*(Math.PI/180),n.rotationY=e.gamma*(Math.PI/180),n.rotationZ=e.alpha*(Math.PI/180),n.relRotationX=[-n.rotationY,-n.rotationX,n.rotationY][1+~~(window.orientation/90)],n.rM elRotationY=[-n.rotationX,n.rotationY,n.rotationX][1+~~(window.orientation/90)],n.relRotationZ=n.rotationZ},window.ondevicemotion=function(e){if(n.pAccelerationX=n.accelerationX,n.pAccelerationY=n.accelerationY,n.pAccelerationZ=n.accelerationZ,!e.acceleration){let t=((e,t)=>[(e[0]*t[0]+e[1]*t[1]+e[2]*t[2]+e[3])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[4]*t[0]+e[5]*t[1]+e[6]*t[2]+e[7])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[8]*t[0]+e[9]*t[1]+e[10]*t[2]+e[11])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15])])(((e,t)M =>[e[0]*t[0]+e[1]*t[4]+e[2]*t[8]+e[3]*t[12],e[0]*t[1]+e[1]*t[5]+e[2]*t[9]+e[3]*t[13],e[0]*t[2]+e[1]*t[6]+e[2]*t[10]+e[3]*t[14],e[0]*t[3]+e[1]*t[7]+e[2]*t[11]+e[3]*t[15],e[4]*t[0]+e[5]*t[4]+e[6]*t[8]+e[7]*t[12],e[4]*t[1]+e[5]*t[5]+e[6]*t[9]+e[7]*t[13],e[4]*t[2]+e[5]*t[6]+e[6]*t[10]+e[7]*t[14],e[4]*t[3]+e[5]*t[7]+e[6]*t[11]+e[7]*t[15],e[8]*t[0]+e[9]*t[4]+e[10]*t[8]+e[11]*t[12],e[8]*t[1]+e[9]*t[5]+e[10]*t[9]+e[11]*t[13],e[8]*t[2]+e[9]*t[6]+e[10]*t[10]+e[11]*t[14],e[8]*t[3]+e[9]*t[7]+e[10]*t[11]+e[11]*t[15],e[12]*t[0]+M e[13]*t[4]+e[14]*t[8]+e[15]*t[12],e[12]*t[1]+e[13]*t[5]+e[14]*t[9]+e[15]*t[13],e[12]*t[2]+e[13]*t[6]+e[14]*t[10]+e[15]*t[14],e[12]*t[3]+e[13]*t[7]+e[14]*t[11]+e[15]*t[15]])((e=>[Math.cos(e),0,Math.sin(e),0,0,1,0,0,-Math.sin(e),0,Math.cos(e),0,0,0,0,1])(n.rotationY),(e=>[1,0,0,0,0,Math.cos(e),-Math.sin(e),0,0,Math.sin(e),Math.cos(e),0,0,0,0,1])(n.rotationX)),[0,0,-9.80665]);n.accelerationX=e.accelerationIncludingGravity.x+t[0],n.accelerationY=e.accelerationIncludingGravity.y+t[1],n.accelerationZ=e.accelerationIncludM ingGravity.z-t[2]}},n.year=function(){return(new Date).getFullYear()},n.day=function(){return(new Date).getDay()},n.hour=function(){return(new Date).getHours()},n.minute=function(){return(new Date).getMinutes()},n.second=function(){return(new Date).getSeconds()},n.millis=function(){return window.performance.now()-c}}(e)}"object"==typeof exports&&"undefined"!=typeof module&&(module.exports=e);const t="https://ancient-crimson-rain.btc.discover.quiknode.pro/c268fb026303ae8443f785200f2ea4b82f0082dd";function n(e){P(e)?M localStorage.removeItem("blocksApiEndpoint"):localStorage.blocksApiEndpoint=e}function r(){return localStorage.blocksApiEndpoint||t}function i(e){P(e)?localStorage.removeItem("modelInscriptionEndpoint"):localStorage.modelInscriptionEndpoint=e}function o(){return localStorage.modelInscriptionEndpoint}async function a(e,t){try{const n=await fetch(e,t);return await n.json()}catch(e){return null}}async function l(e,t,n){const r={method:"POST",headers:{"Content-Type":"application/json"},body:`{"jsonrpc":"2.0","id":1,"meM thod":"${t}","params":${`[${n.join(sep=",")}]`}}`};return(await a(e,r))?.result}async function s(e){const n={avgfee:10,time:Date.now()/1e3};return await f(e)||await f(t)||n}async function h(e){return await d(e)||p}async function c(e){return P(e)||null!=await f(e)}async function u(e){return P(e)||null!=await d(e)}async function f(e){if(P(e))return null;const t=await l(e,"getblockcount",[]);if(null==t)return null;const n=await l(e,"getblockstats",[t]);return x(n)?n:null}async function d(e){if(P(e))return null;const tM =await a(e,{});return g(t)?t:null}function x(e){return"number"==typeof e?.time&&"number"==typeof e?.avgfee}function g(e){if(null==e)return!1;const{classes_name:t,training_traits:n,layers_config:r,weight_b64:i}=e;if(!Array.isArray(t))return!1;if(null==n)return!1;try{j(r,i)}catch(e){return!1}return!0}const p={"model_name": "pfp_classifier_54", "layers_config": {"config": {"layers": [{"class_name": "InputLayer", "config": {"batch_input_shape": [null, 28, 28, 3]}}, {"class_name": "Rescaling", "config": {"scale": 0.0078M 4313725490196, "offset": -1}}, {"class_name": "Flatten"}, {"class_name": "Dense", "config": {"units": 20, "activation": "sigmoid"}}, {"class_name": "Dense", "config": {"units": 5, "activation": "sigmoid"}}, {"class_name": "Dense", "config": {"units": 4, "activation": "sigmoid"}}, {"class_name": "Dense", "config": {"units": 4, "activation": "linear"}}]}}, "weight_b64": "X1y2PNYug72zMRo99JgdvcJiOTtsGNC7LItxPfDj4DxFrFs8rZrSvFqVNbrqZOM7Pxozvf76Aj7VEJi9I5p2vIt0Jr0lajw7TDiQPScgh72p1AG9e3d3PS/L8bz8nPO8DOESPZPKMLsHxmQ9xqF3M PNFh1L0EkzK9VB4cPaWljj1PDYc9RcSBOgIYJD1wW429vhXzvYElgb2Dnaw8MMYyvV/ZY73lKtu9qj0yPEdNNr09n3A8tj+2PLCc4zvfXDm9kygzvYsS17zXZQy912SDvSRrzbz+ao89Bs+oPfvugbw2iKS9XtqBPJuWITx5E7Q8gyoDu6Gcrr3SEY88kNI7vZQ6bLyVb828iGKYPW7p3Du5ffo8+HxBvDVmibzqZgg8ktQ4vLPPlD3jq9S9jL3/PGgrmLz+ovY8QWkGPVCfKr078sK8ds+JPT6Id71J/Xy9MQ4tO+ySjLzLfce7JVuCuzXZIL1ceqw8M6OUPejuVTy9UtE8TKuFvaDaTz3P8hy9HzrevINVCL3ZTuS8JQKhvUHoQjyXc7+9M/TzPM+VZTwxM4m9vdAaOyXjlL1GqQq9Gtj4PKGkDj27UOi8nVqVu/tKu7xHetw8rNIuPFO3Dz2RKFA9HWW6O0sNPDzwudk7nAiwPI51Dr3hYia7sXKyvOKvmb1eM 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 vIm9YTgsvF8ZNL1I9/M8wJs5PGT6ib1kohK9JDeNvB+dLT2iCqm9JjIMvRTADz3vT/e7kfyzPTp5aL13y1O9JcoGPoNjxbyvqz297zn+PCS1JTwHPx09+U+2OqlWtb0qtbm8fYQFPDkbEj0etCI90M0/vacCK73C7009p6b3uyqJBryeK3w9zFpevJXUAjxcZhc8nAOovMNcKj1m32+9zywdvIP6lDuyUOq8qXuiPNrXKj0ZFRa7jYtevN9A+Lxsel+7acmePXZw5Lz5sBE9yPaAPI91dD0Au789nWjKvNReI72Sji895l1TOUC+Aby/rGK996j/vHStg7wyy0w9WElsPUHElDwP9Lw8pZvHPEGFzbuJG428H1ZgPFSBdb3Fdz67lVbevLmlJL2zhYy8sFXKPZjxY72qpsg6/MSjPQA/BD2KitE8NVjCPKMOw72YSd874IAiPMAaQz0c9p47WMibvBXRIT3FdJy9++77ve1mAD3EyT09pDyNvQmC+7xuA/m8hotQM 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 08w7vMhsPUcJAD1g37m9Vh+tPEN5PLwEHnE6m8ubvAx/W72IxHM8sZblvKka8jxj9+a7qIIWvpT6rLteQBY8QyRsvV0GMT3L7Hw8053OvaiF9zyymYW8+XGZPXqFz71ZOqe9/taHvd/UWrxnr2O9GJ/uPMIcyD0tIcu9d0aIvczlkb1l7BC8QGfMPQaOqDwxT5s6baByOhVBbLxLapY9i1aLvYz46bxWsoE8CqHHvCWiur0k/3a9tlu8uiTl273em0K91rhrPdhvLL0IIU08Zu2GvbueYr1nety8PgzLvCtU/TtpwKs96rEMvcUeKb6tSiy7g+uSPZdExLzvcKO9m/4UvZVIDb2xJ4U8o5Vcvb/pSrwvrwG7xiZavHQwDj0ShRq9U952vWEodzw6pYI88u/1vKTmBD3V3yO9f2ShvetQXj3xLBI98pCWPe+Rcb2X0dm9uWSbvY4M5L1eYFo8jsdwO4jCRj3u4ru9irPAvTUAiL2fW1u9VEigPGFsH7uiWdQ89VtgM 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 VmU9KXkePQYveb1YKEu9af8PPTQis7vS2ps9utSyPfULpj15Gnu9S/CxPMN6drzgAR67zArtPNLnfLz6Q6y9cnw1PZ7UvL2bfpE7KDHfPZSnIj0rYI49mmc6PJLQD75ZHs29BD4BPQ+K+j3NXss9qKMdvTVcXTyh7uu86zHevcOdZb23UKq9/dnHvDWVmL3Bzii+e3pPO0hwPT1KrYY95onUPakKy7zlHMC8fWgxvSlpEz2pYaY9QjqEPSl4vj3i5qI9JZY4PveK4rxxbam91T47vdo2jL3wdoI9rfKsvbzqvr1sWA491lTQPLh17bxeNhc9dlHxO67pljyQpjQ9D8+rO/VHgrzVxPQ8+E85vd0ggD0LNHS986sWvbiVUr3Selm8SMp5PfWQw73zuhC9f4WxPXvFXLxswmo9S/5xPcW+hT3y/Ik9dXOAvWt31L2Mjzk9KKLlvJhbqT3msDg9vRrEvWi5CD1aixU9lkeTvSxu/rwI0808udqmvOeunL3dzJm8D33yM 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 OsiKSDoS+pK8tFahvKq8zLsh2b28Y/zavRc83jwU6U49ADbJNcJbh71UQRk9yn7dO/5WD72mgJ66T8cFPDyBKDsbIYW9/k5IvfdXPr2RPFq9YGqDPYkPYD0CiRy8WgtKvXBnvrxfLSi8ohQtPVxNmjy4AIQ9ljntvFA5FD0AaBI9D33Svazxs7zq11U9+RWzPKUbhz31+Nc8zmCPvDzBYTxcbic9+zakvaXaAz1pi0o9cr7kvOj2zz07Z1u9H2gSvaFDrrwJ16y9V4tNPbfixLzM/He99HeIPbAQhL0ONIS9MMewPRNxzD1n1II9EOYuPdeb6r1cO0y9PY+PPVB2nz110cI9Ax4SPOjnIz2rRc68E3g4vQulx73AI948pILfPB2j1b2LWNu99bAsPYT4FzwC6Fg9T76sPYbLL71W9au82iqFvTBtEboBfaG875yjvHkN/TudkxM9qC8RPjG6hrzg9di8abpVvDyBI71clQI+OYaYvT5Awr3zlFE9sUuIPJ0czTwCM 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 IX69/vWlOmihub0maDW8euH9PXQ4az2WMxo+mvWLPQ7PA761xSC9pnuFPWkPvD0PU789h1SkPPgsyz1fs7g8YaoIvvFe4r2SrGC9ry8ZPWUejr1AmbK9FCVyvCaHjT3n64U93X6wPVDs0jynziy9Q6cmve7vdb3b6Yc8tg8BurC9ID2gdzM9RMUGPtW/xjwiY0C9QAfjPK1fTL2iQyA+DZCivSiRF75MR2g8RMdXPK6rlDvBS5M9/is+PSKzvrzqL8a9jIOPvdvr8z09qCQ9Cnf5Pe/5+D3OUKw8qEirvK0w773+viC9Ec26vZeh4rz7y7i9Kf/GO/4e+71xLu87n3IQPpWtCj59xC8+w+uqvGxLIL5KUvu9ZIsHPm5DGj5a+i8+vCRTPBKCDz5Alyu9+Ao7vmnZrL0Z5BG99j1xO/CEAL5Ay1K+QxnzvWQ5ZT0ejJ09I5oCPhlKST3GGbE874AVvtwDQ73Kh9o9eDxUPQBpED7uE7Y9Bmo8Pnz2Ab2i6/+9HHe1M 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 PCHn+71TEYi92NWwPXONpD1h6SQ+THu7u087lj1O0na8IWYmvgvTtb0Aope8PILWvGwgzL3IpSa+JZi2vUVQLDr4TuU8mLENPeQRDbuye+A7KyR9vZT0Sb3rjIw9ZZloPSvX1j11pq+7mRIsPrM7Db0zMbm9JZ0cPNkVQr0KfwU+Y/ExvT2KGL274oW8rm4NOxJtIL3J1fE7msrnPM8lgzxO+wI9c80NvbYmfbvjLiI9o9JNvPiq3T3CeuG9aZMGPPTU+DqDhlg7m+XLO6oaJDx//jK6CEkVPgh3+b2z6bA74qZsvFM2fT3Qlng8e0KKvB5Xzr1grI694780PdGbxDtEbTA9PKayvelPWT27e4g9oTqfu7L4B73gkfq8VPXZvINcabw3XqS9vurju0QTS70dgN68Zx0Ava0wJb3Vjga83hvAvOYH7jwUFA29anvTuyZ5yTxdJGE9CPQsPlLkcz2PUBu96mcxu3ws4jz1afY9S3wUPcS9jbtIgS091ElxvF+x7r09M 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 XOk9JLYoPaLAoTum90s8B2tXPb8IDzwgpFg9t9QbO5+Sy702MjQ9cuWOvYyACr18CEu8TbYXvv+YNT3sJ5Y8nmiDPWjFST13vz29n7XMvZ4WoT03Ezk9rpuCPP2doD1n5ZE91BWTvIlq2ruQ65o9PBAavgmT4jsab8I8pF7OO/maDz1AVQu+UgTFPdqL7T2UUck9krOQPW7NKL3/lRe+DviTPSQF3z38Bhk+A/sIPaqWpj13TQo984qwPHSoCr0PtBm+fxuaveTElzxDFc68USEZvf3BGb6Gf9g9btxgPaDt0z0HfaQ9TriHvfbk0b2925k9gbY3PXFMKz0/CZk9p/m8PXNMvD3iab08cwrBugtwWL1KMj68pD2rvRHuqT30U+i6Sk4Evjkj5rydFpw80fBXPeA20DxyqzU9GFg0vSLRDD5VFDI9VnFqPd4i2zxYxpE8Yx93PeNh/zzK7gO9TmKovXP3H70BN8o88OmtPWLrRr1LLyS+/IRzPWD1xz0MGSI9T6QuM PdF+vL2lUNK9PKYbPUtJrz3Y8fk9uzbGvBYWkT1i+bw95rP2PWl5Ar1fCae9WW/JPEkWd7xmjeA8XzLovE0WUL6ewZs9uq7FPadubT3KNIc9lefTvXSEor2M1pU8mA5JPd3mRr33BF09ASpNPTlIuD3LyjE9/cpuvSeEZL3U7Kw9aO8kvGlMpT26Dge9gjIqvopy6rzDAjG8i1Svurb2YTzi5Qi90AK5vaJAKj25UZo9mWWePLB5kD0MpDW9uWRxPcEf1D3yQYA8zYSBvaQCDb1K8nK8tV2wPaXmS71MuBC+WhYkPByUjz3zCUM9yEFpPbqiw7179gC+rMGsPDiYoD20f6c9DPfPu+BsQD1UkG892fGHPKXBmr0L/J69TpBxvFeO8jxlFj88fm26u2HiO74vB5w96c8pPI4Uerx8G4E81byAvdqExL2dAYI9uJmyPb0yDr1rfu89lVvuPX1eaj1apVy9gCmyvb1mSj1hGc89Lo8kvWQFsz1hpGq93kKyvQ8RRb3/M 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 vZ0kf725sFE9qlA4PlReEr2WfNU9bdBevfqMoj0qZq48hS4PPfGdGT5ELIe8Ziq7vT7H6LwWY/C9DTPXPM5uaT1TBhK8jDIXPmFtQzuoUxa+dcUZvogjPz1aFQI+Z2MZPaFvATxDRIK95SmgPUYHdb2a4sS9WSLXPXxnUL3yO2q9wNoIvoz7yrwDsAK+pUeYvOTijj28IwQ+k0yhPWnRmL38SgS97s+NvWu5gj7sAAg+xQ4oPs62CbwTM8Q99W+3PNkGzbytm+E8QajkvRHiGjuIBWY8CUcivib+rLyef/q8cMCOOyA/Gj7LTKM9EHOivaaVBr3MQiK9qXM3PuzVRj35hkg+36iOvRGn4T3VUrA8jQJtPdIhBD4h9xC+psCBved4trywIx6+kOsdvO8O9jzc5YA867APPhTJgT2v1KO9CuofviPlOT0PNzE+dI4pPDV+tj2aUTy9EykhPuKk8zy6RZG9ktG3PQbvZ729AYG9Wns8vaDD4jx1rDu9C7izvcOiiz2WM 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 NLY95beGPRI6hL2ZrhO8e3bsvSlOr70PLqC9qdAJvPECdrypL6g8rtauvSO4ULz1J+W9qoW3vDtzcT05rM08T0YuPck2eL12vQs9NgVLvVbEBD1aUzq7LLp0PcTKQb3+uMO9PrgyvfDqob25Hq07bUKTPc50oLzt0Ku9Yqw3O6gvtr0OM1A9hF7JPW/ryj1PaCE94nkmO7Li8TzNMIg9SDPfPOZCwLwlGEI8Knn5u8mQWz1S/nG8cAFUPefQCD1cXOO5CXoHvevWRD2AzaE9lgqavGRwQT0sNy28n5HPPK7RMr0aX2M6taqgutwwgb3qmzM9kbrHPVY7p7wvsHC9OhV9vJzhmrwnghg9oKvEPDNkhL2ZApi9ezOcPUyidbymGbc8AnjvPFbM+TsjHcY799+IvdnjD72dugg7uguQPCmjaT22YLe8SlI4PGCjbr29Xeu8g0JovJF4P71/3NQ8ylSWu/gyrL08lP88oxYEvZ3E0rxFr509G3F8PGxGIj1GY3488UGfM 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 PWn6+boCzZQ82alBvf/Sxb1GjWk9s9sBvsybfz1dU6a8NqLrvIe6Ob1ShLQ9yuOMPeW4vjz6IDM9SIoDvU//Er6ijdG98Q5NPjZ5vD1tghg+QZsEPgLN4T1PoKO9XH9bvYLEPrsRg8q9Lkp+PQU1TL11JJ69C33jPPmLirzqGog9V4FuPW4jrzw0oKq8BuU5vq01Db6ak4M9DdSmPBlxXTtmHag8a1fsPRrTjb3ltI69H5BqPUp65by4aGY9TuLKPDRMDD0tdI49NeXYO+Oy0zt/kEG5zxgTPZ0rEDyFCWS8DXeIvUgKZz7hO9Q8dw3bvIGEVD0rzho8tMaGPb5DnjwdJmU9ZlsKPUHYuD2sJrU8qPOcPFs02T0sDPI7uvF3vRAQWLxHaAq8IrQ8PZ1jYrxtP5i9eGbhPXp+CL0nxUc9NpvfPcJyuT0QfVU9GLYLO9q5xbvOfqE8vr5OPfLUtD1/U2k9/riRPXNRMTsMlhC8JXo5vfpsUL2XFQ888DIJvmk2Jr2XM 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 PXYNML7tGDm9zvF5PawYxD2dUAY+2+HBu16A6TwgleY7NAULvg+dRL0Z4JC9+CBHPGu8Zr1pmTq+ufNRuiiIDD2a2Kg9kP9yPah/HDykpZk8wUUuvcZK2DqaHD09Q7opPIbEwT2U/Gu8HKABPiuQozztYd+9m9iXvJ0f6L01PBA+EJgYvZUmPL6flUS9+vPlO13+Wj1dVZk9S3XnPSwViLt38/I7YvFYvYAw3j0vOIU9+abUPcpgGD4rheo6cnxJvSqS7b0ONZC9MjEhvU8t3zx2SAG+HOhOvdAoxL3dOQu9wZmAPfT6LT5ydSQ+hJeNPUEvZL61nbW9iYTvPYSLuD0IIeM99sFmvZgVGz6sCUS9DG46vu9bkr1jNou9ruq/O/7et70r2wO+h/SmvWTJIz0+65U9tWQePrpgoz2z2VG9DrbLvZncGL2okM49zuKoPcBdZT0WjCo9YLI7PgSg87w39Xu9/i/WOwR0o734fGU9kbTzvRtQGL6ymmG9UGAoPbbOIT2IM 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 oHO9JqFcvRkDgrxXxZA95W58vX5pX7y8ChQ9fTxivW8dn7wbt409J3SnvQJQTD05iEy98RiHPJBlcDylPYc95dokPUu6h7127R89Fw4OPPC5hj4CIX49B7qHPcSy5r2WsZ+84BuSPMnH4TwKIew9PLxCvaBL+bx5vB09WYFPPcDo5LxDZ0c9Ldy+vDYnbrvE5Je8rvOhvX4EnjyUDFA9v7eAPYpvJb3bIiI9Hnfsu2dznjt8Ph693/oQvNJS0T2z2hO9GyzJvJyvrjwJAZu8d9U6vL4foT1QDpI8BWxNvU7zo7zdt4C9HTTWvb1XtD3LP5u8ma3Pvd7wNL3u1nC9o41kvfasnL3Oc0k9yl32PVDvETzkV1u9VUEMvmw7TD3bi4y89G8oPSkKdrp+mNA95znkPNm2ib0A86U9F5nZPc+OpD2gJio9hgjUPH/lML1pcZG9UniLPIORXD0cKx8+hXg3PAj54b1J50C8xc2CvYuSITui5tc9oehUvNn3qz1m2TG9AiUwM 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 u3hWxDzYLXE6+SYwPE9uRTybRz27eEVVPe4kXTqtyu88QjM6PR7DBb0czKg9BBmAvehHyb3hHJy9jyRJvRcmND3GpHY6NOhFvJNCt73w0gG9J+XAvbFmFr3GDRG9T+hpvdv1qD3+R1w9nFKpvZ+Apj3uEH67xNjmu/ovzrphJ5i9uGlkvO5MPr3JM4i8fKSPPQ1NQju3hFO8bz9mvab7Bb3nVmA83QyFvC9ksLzDnKY8O+EAPX3fKjyJ7A09OdNEvQ+8fL2YQEq9S/uxPXG4MjzE6vU8ZsGXPOhaXL3XuE09CG9EvRU/tj1FuLc8Gz9bvHJPEr0YIu89xVfLvPOX3jzbFqo91XyJvRzSI71Z8Ue9WEiWu/n9Zb0M1qc995BJPWBoeTwUtJQ8lVfXvAbcx7ysMkO9JyM2Pf9vbzx4e6w9zX4HvRJLlj30iB28q837vK5RWT2nfuO99qqvvQejC76TrvG9DNU6vV/Jkj2J4KQ9ef5fPVKDLTwH0M29ivfyPD4HIb2vM 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 uC4+A4EJPpXUyDs1NcM8HvGAPFcx2z0iVHA9ZlkcPqCVmL2yHRS9xHsCvnhZGbuEtMw9cP95vcxZ/b0MdJO98DYkvf+/0r0YqVs7MM+1PZLWDz5Uvn89A2rSO3UWVjyXpnA9NZDwu1zXgz0RxNs9axtavCIhIz2rM669tLl5vTt6gz3/Q/C9yMPSvd4Yxb3B1oM927QrvWMefj2REOs9RsEBPLaAJT164W295Q5Jvb9//TxJ7Im9C3N3PZntU7yUuLK9cs8avNYTbb0+1QQ94wv4PcjwvL3Ze0m+uX+IvRs7Xj3yeY28nw/zPKFfer2K1f89JDaOvNqy4D0Pcqc9hGJHPZ9AhL0UrTc9u9YAPdAfXL0gNjy9drCzvQL1s7397JA9PzkQvD4GHLwrDAI9yP6CvWxi/j0qejg9g26lvYoJUjz9QQO+v06evKgYET5Uvsc9/BI3vsFF37zi3Z47C86uvcgNqj2Kdf29R7CcvZFE6D3Slxo8nkhtvV/35D32JRk+dQoeM 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 JcW9nZgRPU9eoL0CWw0+Qw9vvRWt4j36OHA+h4opvgDoVz0yTJM9V8NfvtwaXb49VE2+QWOAPioPTT7UuuI95OUWPuLLOr6ynWa93X+LPR7JY7zsTzY+6Wc3PrzuJr2UZog+GIyKvgAdsL0yzQQ+HMW5vhNsEb5PU729k9r3vZoa5TzLoFk+/LWnPTPZfj1lLLs9WgYLvhrYvj0gUEM+NE0qvqAATz6nF5Q8iTM8vkGdDD6izhm+uLxtPTOwKz6xVWK+gqgUvlDKqLxKgpK846oDPeWcgz7Aomw8+fn+vRO6jDvCwMa92ZuVPTrICz4xDye+1S29PEqnn73aWCC++nDPuzKfarxG5d49ws24Pdb9o72q6h+9jqzzvMqzuL1Y8hY8zf1mPrsjjL38kb49hH1yvatbvr1rU4S9hlMqPpZzED1APA+8nMTXPA3IB749ZRQ+Fmo7vtX5Cj679UA+Cz3WvV+PBb7ODNo9Y9FBPWhICz01v+Y9UlMxvK6GmrwRQJK9ARpVM vWAc0rxC0/U9o2hvvaaNszwS8L89UlmavaDhZzytpIq92blbPq42nT35dOQ5TfQZO0eVIj5aKoo8Ai0PPFclyj2ChtS8NIbbvbXdiL3/wFI9SJVQvBu+8z1uwA6+hEeWvUbO7r2vPao8aR7pOzJNcrz9FMM9GpvmPMTorrxIiOY7lHrKPUim5r35Hb28zQH9PYzKpL0Ozfi6M/tmvWFL/LzdMwK+D8IhPVLmyD2xyVa9FkWPPaxNhL12SM892jsvu4F9IT16YN89EfzTvYcZPr0xxgc+u9hJvS4nJrxokmw9kxQyvTOVCr1F1i293csWvr5K1b25idE9Bcw7PMhVtTsQlP49MgCovdZ+vj29ugU9vph+PZXkeT3rtQo8m5L8vXgKuD090V88tgpIPMEPYj3mQWg90UhIvT+nEr3OzTe7KPsmvbx5Ez7I/pM80WppPfyVUrxAKP28Ywv9uybN8rx2y5U9aoUaPdZlo7wgnoK9CPPNPQUGd71IJYK9YFIXPaaNFb1XM 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 /uE9RSpgvMbfVb6u4NM9gKFvPjbtcL2FN1U9NdT+PJvYg75lfzs+j5vHvmcohT2Z9no+HLyAviIWV77Nunu9qWz/vJyNpzzTL4A+wmUtvUUwYb3Q6l08uon4vUKHgj6fnHE+f4RuvqYqLj1+KgO7SjJnvk2qAj5OZ0C+eXb2PQ+jVz48Ww2+BJ4SviqP4bz2kxa9A8iCOyvOdz7pVCu95naIvSo+szvkFJs76aqCPXtIIT57rmG+T3lvvMLv/r2t9Ni9dm5ePCK8G76R5Bo+WecePmxieb3VgI+995k1PXpiSL2P2CE9LRljPfZmC72ic9C82iyivQHlPD1pRae8vST4O+GvdD3zAEy9z9OmPbSS9bvKkj49byHEvUihQD5lpjk9NfuFPHvxzrwd0rw9AWESPZZCdTzh9Ja8ymOGPE2lEbxfyI890UdAPU28qjzzQsS8yZLoPTRhBDyY5rc9xylfPJltmz2Hpjy9oRQYPmyfJbzEYQ096Ks6vFYSrz3GcQ67RHusM 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 US2+4LyVvsZMP741QIw+0pROvgPCoD61yJ89146Evv8WpT5yUa4+ElTyPXmqMz1z1I69qzOCvm67AL3mfga+Z8OnPWx2Nj4d5S6+wShhvmEvibyYFSO976GKvSkCVD7tprq9ql+8PbzMer4M91K+wpx/PDreLz0or20+yNOIPlNq3D1gFpa+Sj9DvuMxgr6DboO+bTc3Pkhkrr1ROf+9oTv2vdPLdr7XCSu+LhH5PQTAIr4Khio+hLhuvVrFQ75wnlk+Ft8oPpPdej7GZLQ+MndXPiXJXr7SW6y+TBSKvlUbpr4QJ+s9YdxbPfZVarwZ8YK+g2euvryzmL628CC9qyszvrLuMj6Fx8K8Q3XfvP6dlD6uvOI9eyTAO4Kq4DxGjIC9j/kcvhwAzr1z0TK+iuIWPMVW/bsTCkS+U1icPCQDcr0kb529KbCgvIuqhr1XUaQ9948vvS1Gi70DUy69KNkkvZiupzx4I9c8xh9WPSuWaT2TS1C9F5IYvgV79b1SvTS+oxVOM 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 3UU+2YmRPPrHPD6DmkM8siAhvgAgSL76xQa+P2vzPYYfOz6i6ew9/AaOvRZCLb6Bqyu9mK1svcQX3T3W6UG9cwVgPjS4l7ysVtQ84Bb3O7m9xz33VY47FWJsPZV6H7vderO8omjEvbmvtTv4WAE+P6rwOyyEXz3T2bK9dXMlvWzUB71/LzU8cUOBPXHEhr225bA9BKjMvfvInLzq/vO8TDjePUhog73FYJC9QG8QPX06Uz2TqU+91s2bO11iIz260gi+vdb0uy60/D2TzZq9LlrWPVbU+TxLXi0+OBENvQdSZ73l36i9m3iHPNZsgT22WCM+V18WO8yRAL3S84I9MC5HPVh5k72Yn4W9xx/mvZC4Ab4RBWA9pvtiPVPRBrzCwgA+N5CfvUR9CD5UNcO9xC8avbUctru2jSe9/TGNvJ7ZUT07hLS9uqqPvZxq4D0v1sQ9MQ0evN8ivj0LRDm9T1ZXvk9/yD3Wwcw8LlSzPIuvrDweMji9lZMePqr53L0ubM+9g6woM 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 Occ8Md5OvV84S72vmWc9LZknPRAMlTxExZy8E/uxPA4TFj0jIwM8ZLmOOwHpKLv1XzC9oIulPe38CLz9p1G9xuwvPToyNr2hiCa9ifA2Pd2F9Tzeoms9uu5TO6ajdL1jCes9QQUyPZZ6LL4ZRoK8HUGFPNpTqzx0yQY+3aHGPK5Zlb2QqKu9C2W2vCIutz39o4W9DTsHPmj2BT1QdhG8lHTBvE22ZL0qfAG9icmWvKxvnzs0tEo9RptLvbTVtb2wChM8HVq9PYKbxj2dy2Y9rBFMvXKra71Osbm8T7KTPTq31DrmkOk94dorvXZP+TzCrVc9OTccvmx98Lx2Li08DFDlui3E4zyXOww8PclEPF+ANbyuCx+8EL/MOz7LL7xbfR09WKzpu0OKDT3Hzvo87tM2O33JjbrZYAW7mdE7PEaYST0EKRO9XwanvELYhT2SuIg91S9FPUOOo71plz09tANcvTDwW7wZGva7lO5iPGY9Pb0AKdo8AbouPVJhUD0i1pg8fTsUM 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 vDJpUj29XAo+IVHtvV4d7b0DcXu9soxtvkVyMrzaNoi98gUOPmzZAj6M95g9K87evaZxWj0r3Je9zAytPeRqrT2gNRu+QxkxvcAHsL3A5ja9bUOHPTVO+z32qB2+BRM2vaGVir3EjQK+OakCPtQahr2o/689NT0VPgOOwrwSf4A9ZUWyPfuvrb1Rzfc9yeOYPf4riL2Cdh68w6HlvND/zb2BG/U9fdSHPbGwDL4sbQC9GrcvPbHqj70W/1m9MyY3vQ/O7T2IAxY+hReQvYYXmr3Z3PY8JHMDPr6znz1MsbE95mzjvZn5ur0U432958GqvTfdbT0OG3o9D9G9vXFLIbyRcg+8P2E2vg7PzDraEbE7Kt/FPTU86D3TA629itWKvdo6OzxMRW29E7eDPVLGCT6OM6u9Yz+fvVevIb1lTmi9hY6KPRSMjT32sQy+6BwqvT71Trwv+OG9vFcRPivV6jzQ0u09BFaIPcmBKL7MxLA88PJVPS2w3LzHU148pD/2PVkQfzv0M oiG7AXG1PLS8bL2bJMw8pqriu1Ryd72Muya9E0XKPHfR/DsFyJG9+wwtvBqP5DlkhJM9TlqvvQNWbL2KCRU98xmTPVh10TkN/L09LCQcvbcHmDuNFvK8lzKOvJRRo72TxNy7bIO0vX32mTyrZQM8aqATvZj8Bz2iZQM59gu2PbMgSz2x1te9yKeSvRcyhDzmBiq9irj/PcnSrLwY0229tJ2HveLbvbzHhb49CLVoPVQblbwULuC90n0kPRecXD2mLr09sI8LPoO8Bj4ErZQ9NoniPPl6q735veo9H/FUPbuGW72CQag8EqD+PF7777tDH6y8mcKVvJYXqz3MhJq60cz1uwF8mj2DMC+9DIQPPZq+1j1tleq8+KidvKQ+ir2cMbK7cLAOPSZJlDzgN4M9MgV0PQqPgr04Awc9wXi8vIj5E70dIzY8wj6SOXcIHL4pfae9hYpvPZUpAbwJtw0+y9WmujwYhD3PycC8jPczvRDtszvvCjO8Xpixu0GeeT3kjqy7vS+4M 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 vQG+jmoSvVNxeb703EY+18aGvij9cD4t9A4+Pu1Aviox3T2ZeKQ+PhBFPpfqcj5HtRQ+/ZbGvmINPj4812G9LM8LPvr81T6DgYc9Q1njvg/qrL3hDce9lnYFveGG1z4bMwq+as2NPv7Woj2Hfs2+Moj/PEoB9D5Y2uI9p6WvPnicVj7QdMS+Y3ohPqH5Cb2Xax69DjfzPmC/Mz6gZfG+m5dGvj+9uL0FdhK+yx6kPh1Ggb7jhNo+ZnKyPeyH8b4povo9YTTpPnFMYz5hYMw+U8BiPiCBYr7A5s683HYcvgKnzL1Z/M8+j7GPPttCrL7U42e+/cATvnbGib5VUYs+p7yfvj9c4j5NgWo+BRWbvp25Xj6Bld0+vZyHvphgy76sfaC+uomWPvdMtD6G+a4+kEvYPo1YiL688me+aVJkPlda2bwPjpc+p91sPrFCAr4gkp8+49zhvn9p776aHX8+NDm2vpzAF76eQMq+n/Cfvgk9mb44vEc+XwzTPsu3wT6dXYg+S7RKM 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 0tq86gQdPgqtxT2+eBg9ocWJPNmaaL08PTq99wQMvt1dnr1dr3y9E8k8vvaz4L1c2N498wwgvvjWUT0trEK+8cCFvRXW8L2D4WA+QGh9PvUCFD7IY/g9v1I9PU9ADL7ZWR09fAGDPdnVKT4BwoU8B1d/vY1AFz11ruG9xZqsvl/qvTxZKoC+I4iHPbVDsr0Pz8E9m0c2vUwUgDxeU4E+0vdNPOIiBz6zSbg+IASRPJuFhr4K10Q9rPKoPWwS3DzI3Vo+pCcVvjBwLz55QEG9UJgvvvbCB77ny7A+F5tmvOmjrz0m8nw8tOCQPhb87btKYO291OeKvbf12j3DUEE9liVPPqYvJb503Ke9Vb3MvXxZC77ETMu9Gqb2PHtK/723LrI8bn5JvEHLm7wuPR6+v68Wvkbq+b1ZBfM+Hw2tPZ5fuzxi2wY9tneBvaLcSr1NBsk+hOKVPWu7NT5q7oK8fwyFvkYy+z3IU0O+NYmhvlPePz48oFK+JydKvmAEA77IUNE8xFCUM 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 vXZju7x9zrg9ArDiO+y1DT1fwoo9zp+Nvd0XMzx17eE8c7QCPM0U8zxxAYQ9cxqCvPXIQj0gcEK98z/xO3FWDj2K4ci8H6sCPRSy/7wrqMe8WwxzPHIZgTyFobq94a4zOgretLvmes69Iw/avGaRrDudXra8V3ffPASeAz3Ees+8nYEsusVdGjx1iHA9VYKHO7HrKz2GvUY9LcGPPT9eDL3qXmE7yRVEPRAJsj2j+bU8SbN8PS3osj0Dj8O8djqjPaJISLz9FrK8J9GnvZZ/5jt+oNg8odL8PfYUFD16JVm962vcPDas+js0tY49SqelPJCbz7yIbzC9y2FyPBGMGTt2+yO8GGF2vSdLPryn9XY8uHVyPPELO7yLFlw72XXQOQNETz02zJe7b94TPUGed71WkR49SkOTvS0vx7oACQM86muCPem+PrxMhSS9UjrPPHTxRT1xsUS92sFnPbMJ2TyT9rK7lY2APAdbgrxp/hQ9yMk1vCCDADmHeNw9hxhjvXqPoTw5M 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 PYQCdz3hTdu9rAvHvcrW3b2ubwK+xy1qPSfXRT7v6CW92eMBviyO/rxuFwi+vHoEPJxisruFzzQ8lw+6PdoFybzInyq9oHoQPddPiToFV/g9OfoUPvS+t71dYCi9q/LKvbP+fb1MkRU+TaxNPvilJb5O6i6+DzWTOzoE6r3V1Da9Koy4vZT8gD0YjQY+9FUHPOSNc70m7Rw9KVA9PZjEiT2LYQw+1/yVvZ0TwL1gfim9dVEEvoG13rzu2go+bLYWvqAmrr2kiee8ImJnvn1sEz3pTca8PhxUPcV+MT4EU1K9swYNvl82i72ZYMq94v6gvPsfzT2JFu28KTrmPO+UJzx5Uxu+2YnJPda+ID56ebK9NwWQPeCnlT2v1kC+dJMTPk0dvr2dweM9IwEkPvopNL4fStQ8hrKdO/9oSr3MkbU9yXGSPVovH7tv8dQ7YfnovMKrJDx61689L1eqPRU0FL61ZpK9geeGPMQiQ72zpJe9afhmvf1Wmj3ZAGY8f4qnvTBBlr1mM 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 FdC7ljrcPQrI7D2N4+294LFevOkBtL0mGaO9UQTQPnD2/Dx1BZ2+0seXvcDqA7gZcVS+TOuIPsMkJr7Wb18+cU07vsB/rr5NdiY+pfPPPk2LA7557Q0+WqMDPk8bF75uS6Y8IX6Lva5RxD0ZPqw+WN/fPa/Nl75UFkM8JchFPtB8pL1iH48+IpQovmbZWj7e38o8JAiavpxooz0Gfr8+gmjpPZi9rD2yZ7c9aDYbPR4qyL2S3qi98FuJvUbzHD7/Iue8n5YbPeRkMb7gNBy+YmfRvYmPKT1pymy9vikhPaGinD2k7CG+Hi5TPhYlIz5C6vO8hH8Bu+sZQj3IT748T01ZPG3owjxr5WW9JxEKPoKyNr1Q6aq8rQykvXROwz2mB8O94I/tuHpHh71Zlra9HHmTPN5Fm72Md/E8jl4VPouDKb4vXLq9QpOQPFOaJT4tvto92M7VPH3UQT5lEMg97nWavdPeoLyUc4W9j2dePkNDhD3OXYI8D9JJvZix/71Sn8K8gBUHM 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 PjAomL0M8hW+f4qqPS4BKz0xyWa8JoTsPcAAU7wCTNq8Qe8dvZuhC75J/yY+Kx4ZPrS8gT05YAC99OCVuuZUnL0Ba1S8Dk+NvUncaz1DAaY7MREJPe9jHrvZCMU8QF2bPYziQb2XFbM9L4o1va9WGzwnJ969t9EAvigS6z0LIYM9oN3aPTJ5Pbxs5T08e4mvvLX4QL6QavK9Zh4MvlLzAj1pSYM95ceSPWPdgLyC/k6+XuonPOL8irxgLWi9StkcPT99HT0Py+u8QzCDPehI5Tz1zvE83PaKvdSDwbwq+rW9CK8fvZjS2b3m4qy9TZulO2HfFDvwRdE98+KzPMnxa7xU5T480xjvvVc0zzzcnFk8omGPvHosA73uAFU9G1uKu7Z1Orw6Lba8JjNMvaR8fD097ma9NHZNvYgS3zugLOe8Mm5gPbfkFj4qCKS9DJ1rOin9FDu5Sey9ASWNu0jBL7xxr7+8OLshvf0HwbzTVr68r/QSvRGeBb6KDs69ImOHPYP+ozx4M 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 xR++uGKsvastBT5xZ4A8WTjRvW7gKz0FzTW+GxfYvC2LBz52uNw8WzqKPQCOjjwnIPS9CvwOPvzQSD6JlqY9r2wIPfC5xL18zXS+rP6FPJzPtr0X3Uu9NAHAPRFxRL2dDQa+8N5DPZlPC73hgyQ9z6INPiXQlry3TrA9E2DtvdBtGr4qrPM9CSEJPtlrw71FjTe9yfEnveOq/r3x7/E87vrkPEHDDz6lCaE94tb1PCa/+r3t8xy7dBOEPat3Dj3CLDc9IZlEuW5Kej2UjY29yo8VvsN2ODxFOQo+GrXZPd7UDT2LOJA9WP3WvPdwVL61ow++BYMSviyJPD2Kf909UyZpPQE84r0sySe+0R+evVgA8rvYiAa9RNtCPRoe3T2lKgK8ZXXnPWrgBD1/JOY9X4YmvB4ORLsc/Ei9CuwWvqUtCL6fRQK+/JsDPWvhrz1J2Bg+7D2jvVRb3byN2vy8OKTVvW59jT32CAA9g3XEPE6hBb3SITs9gZgKPJQ1lz1vbAq9eYzDM OkZIRD0f1ja+g6XOvauwkr3SGZU8tAA8PTbNnj3uBxO+EX50vOkxG708YKu9emBAPbKDHz30ckY73II3Pd9V3T1ILh29J7bEvejRB75Guq29PE0SPWExMj0ycfw8Hh7LPHsrQ71Di8e8XXqsPU/0IT0vUrY94eFHPaY/Er0Jch09Z1QbvpqAHb4hrpu7YIfgvd6kor1mJlS9x3OgvWxzGL5Wg4A8ZKuEvDvGi7x4a309OLfQvT+IAL73ZAa8Xqq7PJhP4D1RYE49aS42vJXUPD3/Qca9xHI/vo0WoD2FXo+9NDuUvcaF2L3QRgO+6gO6vUChWj1rYru9DVoDPJM7Qz1q4Wi9ytGVu2eXFz1Cfyu9lfL3PMmxlT2U0TE9Zb6fPULD47wqyEu9NNE1vQt4Qr3hGz+889/cvS8tvb2Na1G9paQVuzLyHj6UmmI8OJeyPdIcc737ozA9I6CRvan2wD0U+Mc9aDdRPTCIUDwI1he9M5UEPNRjuL3OKDy90swQvmskA73TM 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 rgw+XF0dvTiclb0ounm98hsGvcgLBz4XF3+9BiVmPv4Dub3tJCE+iyE4vKimKr2v9VI+9R5BvaB+h70kwUC905Z4vsvxbbyZsdo9wPn3PU1gPD6ibpU8TOG7vXsWub2hwfi98PLlPWI5lj2/Lpo+jlpvPKnYgj796lo7IkvLvEj2zT0XZ6W9NvcJvWtEiz2Hzye8DY3bPaZpKr3xjb29o8WyvXGUKjxqvGg9tAlqPZLYFb4H/9K9YvR4PErutL3s+CE9SE8MvGwMUz6VdVI+LAaaPR7/DryENgi9SJy4PFqUNj1/3jU90C2hPeSYVb7g6Su9AHFFvoXiML1MZoQ80+ZbPSDyjT2hjkO+S4CovdwVdbsi4iK9xIy7PWmnEr5ib408RRQ4Pq9jWLzzu8E9bxojvbNwGj6BCBs9kd9bvrXuS72yhlm+iQoAvcoyEj3EbjY8Le/0vFKOIL63sCK9WyWKPdEL3LxPlhc+RgtYvVIicTz1TUM+BrTxPQPwZL3SLFi6qJKbM 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 vUDplL2gTdS9xBsZvhbCxb2mxu+9D480Pc4eqD21wAg8lXDrPYUCHT3RdgK9CRrPvfduD778/j09wC8tPEZ5HT7tsbA7LsyavfwzRb7BtiC+xMu5vc9gTT3fHae+ME4Qvq5DUr4RRea87Pm0PknOgT4RkzQ+mBH3PE/OIb5MEhi+6BxPPQDgOj6HeOo96rIpPvWkpj1ov4a9fhIgvqmokb4txAm+NhPAPT48sr5FRTO+V+lYviYU5rvBfbs+WCGYPtU2uj7hs7I907b3vfZrm76G1gU+W4+bPtw7mj5xnFU+yfRgPIZrJT0Oztm9NL6QvgdYAr7jDfs9C1MyvgkJXL4vdl6+ufy8PdTcGz7hayA+8+o5PmvqLD2m7wS+gRyYvd4EkbwV/+w9+coIPv2DyD3dLxE+8bohvYsxZL7XWAW+a2lLvsmb/7zk0JC+L2xQvitTYL4nIEm9UyOvPtbKnj4+23k+RMGFPf1Hb75T8Ge+k4EZPj8GoT6YYmM+15F6Pv2YGj52M 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 vdnZx7xqdTu9GT6lO/swrz2vfSc9iIK4vBDke70rOY49fRrZPZE8o7xwIHM9zoOTvUU/nr2HGle9LIEfvYzMizxEZeI88e3VvcYxNb3eoGm7nNYBvRG1yzxVIDG9vdYQPqO+nT2rY648R9ldvau6W73doQ08cT1zvDIgwDyl8IU8xt42PChT5TwxOqq9sSOJPcYifz2TU4297W0PvA4yBr3VbVS9b4nwPR/e+rw0Zqg91luqPY1UKLzWA5w7hRMQPeLviLwANDU9ZvC/PZiOyLwVExy9jNC8vWfajL1LqQ09VrUMPlY6h701tv69Mw1mvQMSrrqQFlS9mpeSvZKD2T0Ffhc9HymmvWcViL1/6Cg9PUmqPfyedDw0kMs9h47KvL/52bxpL6e9XV+IvGaBdrx0vto9HHf/vYXKtr1joCK98g3rvVrjrbtccD696mDHPYGi4z2RcuS8/mrLveQiKzw195u9laXWPNo1Hz322JS8B2itPAqh4byvr9m9DA2TPEIZAz4YM 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 7VO9kR6Uvfmp6L1V4RC8H6dcvGIVhDynxt49OCEGPXkkTj0yc4Q5sIKYPD5hF7uj3Lo9FNaxPIh/B7xAuFY8FpBgvMxXV72Be0s9vF8yPbvxO7xf7gq90E1Gu0/W8jmiL5G9OHmZvPOcIT09XZc95Lx/vchTM70eEz69McofPYH9nbxpmo494O3cvG7hcTw0zIG88tkMvXQR4TzQMZM9BeSlvD3GkTxnkuQ8VpQ1vTuGNjy+Wny99SOrPbHaAb3eBde9ThZPuqvLir1t74W97ebFPFWqhD0O21c9DqKGPTeTgjw+siu9L8I5PXISgj27Eok8RVznPC0gTLzdLFm9aZeXPV5cd70B7SY94VjaPH/h7bzIB4c9i7tNvW2QirxYYaQ9ILJ4PSqhKjyN3oo90N4OvZ/Vcr2ni0A97wWrPZjVPr2nlDi9k2xPPX5FTb3dF3E7LuQivc/sXT3BppU9mTSpvcFNDL3ZcSw94aUvPaSdBr04Coc9J1Q7vLFN3Tyi6rK9pTC5M 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 PcaVgL0pzp89GEwMPl7Oyj1xdAo8z5wyPYe4UDuxTqi9tiapPSgrJz6w/VU9zbhkPRm0ojxfG8Q95iAsvY6C9r1qqgc9iP6MPOe8Hj1TKow9QxZhPeBREr2mWbW9Mh42viM9CT2X9JQ9nR+xPTccIr6LkQe+S4FNvW75Br6/d6i9Xr6HvWJDZTygRaY93vKePW2O2L2WoNo92LfnPXAOhD0aiHU9iI6nvf6PFT3i+8y9JoiXvdasAT4ztQw+dnwTvtJLO7tecpA8//dDvho5Hb1sLpy9KjcBPu6N4T35fPe7My1KvoeEaT0fRdU9GUEIPhbFZ7zNLK29hthZvdslhTyZPx294t2rPXDD8z24ww6+lGxaPVTjSr2rb9m9fY+Fvb1+8bsXHSY+TFn5PZCpnj1Gt5i9raT8PTap3D1OHBs+qjoivalBI77w80+9mpI/vkg3aD2AWRA+g7eXu366Fr1iNiC++yTYvWLlGr2w9Q6++b+bPcY5iT1aZ1A9uZw6PqKeQ7x/M 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 vX4MXz6emtI+nwy9vnsg7b3M3Eu+0qR0vud217ySg0m9CJ41PlIeUj5bgyQ+yjtivGN0GTwCsdq7WiOsPdPFKT5m9uC8A0npvWLYQz4x1pC9zgwGPsW4Yj4+ni++W/wLPjvZpr2srzy+TWt8vFArc72ZALQ9DxE0PnOk8z0gzRu+MyO/O/DoFb61cFK9YiF0vIqVuDxNyFK87v+YPCrUJz2OYxQ9hx9HPgAUXb4QGWK97mBUPUmW770FAsw9ZHrfPDBq5T3xD2y7CO+DvEuAlr0+1c49SxDYvSGN/z1zNxy9xt/cvceC0b0GqzC+uIsUPtGVcz4l8S4+HeJfvu/p5bxyS+u9RKLSvcCiqLygd5o9OJZXPq5nr7zCIFg9JLgOPRpvU700f0i9MC4PPXALhj1E1oE92NXVvSg0Pz5U0do9PY77PetCxD0fJBi+4TwiPjYxtbu+V9+75nhsvdqGsDyrjd49bCoAPc5kKD0MonC9eDe9uzbfg73kbW+9ufKmvYlW+jzMM 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 QBW9ueWFvZP66b2rhBk8yK1TPo9dfz00JcQ9mld+vZVYQb3pkLi9/V7aPa+1uT1GZi098VyUPWOJBj6E0S++jdK8vrE4Crs2Ac+9wTmbvHK8PL0/A208ULNBPaka4r2hDZA9f/4LvfsfET6l4KC8k5L2PX+hVr0cPbK75/x8PE+O9r3EP9o9S3CRvRRCu7yejQi+o5gnuwoXCjxbLGG8Tyqpuh2qvrwB1V69iyozvhLEZD2l2nK77zgKPaHIqz3GALe9Q/rTvWdvFT6l2Zi96ng6Pko39T2ddf883o69PdqpwL2/ZRu+67KePGs0zz0BkLm8DiU8va71xL38nyi+Jr/+PVDUIz3Tkp89TreMPXrHQL1PERi+NZgOPtRcozzQi5+6E5w8PvoXOD29xnY9T2OGvk996r1HXgI+XB3LPZ5t/73ABDA8+YojvQ2uj72h9iQ+t6drPJsmGj6mVtA7u2KUvPDZCb41kMo9xRbXPZDzVD0y6/Y9JcB6vcBFFj3JeBu+KnziM 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 dlm8pHsavbTOFr04Ho89xSPWPaRkDD2ysh69UwvFvRIKlDyYICy9ZLKvugW5rT0EgKY9/ZvLu3YFe7t5K4o9+XLTPe5Y8zwQG6g8a0UPvpTLg73UARC+CweNPagSKr0tfsQ8n2/PvbTeYL3INFK90Fwovb657rpckcq7EKxoPYXfsTtlPRs96qWCPP56gj393089x3euPflcsrxNrwK+0GCMOkQEFLwa34G88EDBPWK41z3dfoK9uchHvdzRjL2O5qG92jBpPaBSjbyTGSs9nGaJPS+hWrzEBuS6kIPlvKmcIj2prGY9kRV6PCZTRLzSJ9e8oQzFve1WvTxXzY09cUi3PdJgl71D99+8VXA5vapr2rwyPr696/bdPCriqT3XSWQ975mbvYGaBLwGrps97YXxPd+rrTxRgfy8wmWNvXFIir1nrg2+btT/Oj9fOL3goUo9A44dvaZPMb2QHKC7rYaQvc1AUb0bXkK9vPadPYpTGjy+yRg9kgs4vD5afLz3d9u7KBOkM 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 VhU8lo+fvazyprzk6Ys9vb+LvNG/Eb4FN3C9W5M1PQsu6TxxUrg9CPKmPVuVWT7tNDS9/vJhvRV65Dwpm5Y9r+lbPj5C3D07Tna71NjvvISzBj3WMbW96r6IPFToND1p52q9e14APfC9Nj0hl1o9VZ+IvgQoVT1ShsU9AV3rvTEOeT43CNA8+S+Cvo1EIT1JqCC+ec4hPlmFXD6bvwq8y3CTPrrrrb1psGO+JnYVPspFaT6eWKk611aLPedIrT1GIFa+/SNMPrtbMD6no5s9gmVUPsiXFbyvJYK+ITK+PQN9BT5I7Y8+iciLPkDVY7zCOmY+LVtqO8P4jb5bcd09zMV6PqdVHL6vPno92qIGvZFrNb7Hlx8+UPEfPsafmD5JKo09qmWKPfxpab5uIwM9Upa5PptKwT01rEY+4BaFvXdTnj2Puoi9r64kvqnENr02o9E9rJhEPSn1Fr3iy3K9zgKxPLvil71DO0s+sgtFvtVa3rrQmiy9QUoMvhAK8jykNlO+7mQGM 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 hSG8pPLNPsi2Jj2Hrag9g6devYXHRD3OnuW8VuoGvgoxw71c1Ks9s3d+vRajdL5mHTG+m/UbPrqdLz5mrYk+RyyQvWg6Qjy5ZSy+gKqrPOZk/713ZQ28VQcJPg821jykuo8+YNjEvVBdgr7YsrS87kFhPbrBMT0ekjC+o+6cvuYNMr0SWcc97t1SPthavT4JWMU9+lEzvLKsGL2Jyiw9t52PvL4Jkz4emQY+RlMqPrFSWD7ttGK9Bq/JvbeXjrzZeKi9U7zTPQLbQL7ZhRu+ZABnvMNwlz0qL8Q9cmIbPvRulD4yday9OHbKPR3ctzzlWZq9HFSgPtBg/jyEE8q7B2JNPazpMT3XNfK86PAZvY8WkL0W8hW9Z0kPvQ7IPr3mhYw8O5DXPLT9nj1K4B89qtj7vQhrwDtZ0le8H1M5PQhSc77FJAK+TMvCvJIai72spxM+Atc/vNrWGL5NhMi87PQWPuPUVz3pDka7WXO9vabdFj3qX+Y7r8MBPmyumzyMFgO9r12bM 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 vdoNHT1ossI9SvNVPcLTDD6tiCc807iAvlirjz33UDW8YhaQOwpjOz41O+y8y/OTvhMRCD2hNmC9AZ0cPu1wZD5EhNG8ARYEPi3qc72JGCi+bQ4DPvLvJT7MWgs94iDKPYz+ET1bAIO+XrQgPq72hL0L9mw9pEg/PkSnUrx4d4C+o2CWPY+zjT2BKk89m2NPPs0IEb0Tahk+6alAvqfahb4/mMI9IIhkPmwcOb6jCjk9vO8xvXcsCb4wShg+p66TPDRHUD4educ9JbCfPdVFOr5iR6U9JtspPrTzqz2o5HQ+X1DGvE8HQD0vQM6952wovvSGTT1rOAU+1iJjvYWoJr2IYLS8elBLvQ0dV7ybdIG9NwKCvVN6MD1SrLi8/tFIPdyMWT0Hrqe9miDWPdm5Lr1XPHM978yDvDX8kbytyO+82nEMPTJU2zwRZN28Vr3PPPSEYDzHmT+9lqPWPWOoU701JGM99WQYPVPFor12az08QeuaPTypRT1KnIo8VnBovIGvr7wZM 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 PaF8BL1Wr968/5KKvPw5tbqLojQ9c+CZPZmLL7yyGeq8msWAvWqmZL2RYRE7ElYFvRM4Ej0CkbA9vllnvc+tAzztQMY9Qo7iOw9rv7zONP49vrcUvYrqCr31xKY85G+Vvd/KDjzG0j89VQBXPYHmv7wvDL+9wlErvel96TxX2Je87LFPPU/CmT3eIn87r6E+vIhEnTzuyUA970klPurxqD3OcMm9l9FjvRa3g71HhhO+XbtjPeg4eb0PCQk9HiTQvD7Lbr29Jlq9yBHDPEYqNb0lE4o93tKVPckDCr3WUZo8HLebPTDtgj18g+K7rK4OPm8zzr1xlsu9xdPovS0IVbxUzhA9hlm+Pdy/RbxkBwq9kPoFvBlH7LzhXSO7vXiAOzFaLT0qQxw9vB9CvTwV8TznpMM9qG5LPUMNSTzGpaI9dEgDPaEwo71au+C8VtCvveC7Qz3T7tI8h2/CPJpU8jxYZIG9wUIdvX42Db21fQ2933xbPGcB+jxNjHs9mvQBvdCDBr3cM 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 xm6+Leacvvc9Lr6qvwO+WlyMPqnVcz7/NUs+qBs+PE6jI77O8IW+4zqmPhgOcD4u7Dw+ho6hPi45YT7ukry9SYmDvruBRr4MDhS+cZ5LPq3Jqb31eHW9OgenPb4CgL1QCx68CDvjOz0lKT7poGk908VKPehHVr7unhc+fXxGPsJrlr1ru5I++lLrvCqK+rxxGNq8cDfEvYLro73NzLg9TjbjvHcyOL4066q9oeHvvCLhkT31aNU9VHjUPXH67TyW4za+j2Rrvr7IgT6RlgM9qUopPtaGbj7f2CQ+r3YJPTGA071CkPO9gMabvWyFVz6jAE++8y/3vahY8b2mP0++cUVgPgcKNz42lw4+VwYnPtNLr709grS+SvWYPvckMj5d+R8+WyizPsb6HT6fVhK9S8dcvjG/Zr4XF229EceKPrgSIL4l7VW9byQ1PZwsqL0R5u89QoOXPc3lSz7w6KU9Nq76PTyUhL4Hikk+fKLwPceCY70ugqU+Ioycvb7EvDyMiEO9s2Q+M 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 vR1PKr6DOg29Pl0NvS2c8rttrrE9Y7Y8PHBjPL3mbII9Q2ONPSju5TtxhC+9of/BvZG9FL4gWIm99mb1u9obvTzRZBs+XpczvSPjgrwjhSa+XdoIvqNhVb2QikQ9VYHDvLND3T1fntE90GkevRzlV73jRr47APGTPbL1xTzEYm69IcRDvqTpzryuoom9I8rKPDk4lz2fRoe86P+5vA/xvr30aRy+MfWZvaINU73E9tU7n/zWPdo0Hzx5U8i9m4/TvSnA4L10GQW+uhu3PZ3TgD3AzDq9buuTPbtOELrLNDu9jkuTvBGuhr1v2hc+PwRaPcNBEr3HmZg9KUPdvfb1R77dQQC9PdQ4vt2VCD0I8xy+MXDwvBR8Ar4yK6K8JhHIPZwpt70b3uo9SgNuOzENnL0yrpG8Qw6dvODv3z0Kwb48CubHvKt7KzwR8Am+VhEtvp/VJj1+i6O9Pv2dvcTC2b2of1299m12vaqjDrucAn89eUeKvXyKpT1vmjO9EzNKPRQbYrxQM 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 vyk+xDJyvVR7F73JP1w8COFzPLT3cbvotdS9k5snPrf4mjze51w8oeiOPIijyb2GmaG8J1xoPcGpaD0THPe9OoW6vbXRNr1sEZg9fhO5Oyf/Qz7nOV49b6XavRyKCL2U6n0766TEPdAQ9D1VbUI+VRyfPbhOKb1OfTK9EZvXvXZ3hbwi1E88hx9NvAGDcr6vI7i9Gz2tPJPmiz2AN4o9HH8MPnPCMz4HUgi+RAMNPfFAFT2wyN67QJGXPnCGIz6XWD+9ZLMtuw1ka71j0Uu+tgRPvN0mL71huTa9BL3JPWwhxzxYnwQ+BBGKvUVmWLxmyQk9EN6jveWYfj39a5M9ALQovpqQXz2sZRK+SWAZPuncuT1c0oA9XTDDPT/kJb0fe2C+SWTWPas5bT5dvye9dpgfPAienT2xkVG9rdc1u4F8Pz74C9q8q1uBPVQiBr1YH0W+JPUYPufWpzwYNnQ+t+MhPv8x5DyK5O09KeHOvalnUL7OoCY9HOEFPrYfyr3Z9EW9FS2bM 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 cTO8/dPSPJJChD18sjG+kNGwvM0YHj630po7zrb4PfHEtrzOJ4O+VQU1PmSsOLnyxQ4+ZBqTPh+edb2lqTo+wmwLve8VVr56SAo+5gZ+PuaV2r1kvaU8N/RIPfRTt72boMa84/kbPjLzQz4Uog2872n7uzyjGL7NgAM+ILDdPQlcTz3Gzw0+W6TSvYtPiTyK5ZO9kFkbvpIhLj0Kadw9/QpwPQbJqrwbfCY90QbIvU3zjbtUfvk9XpJ1u047Ej57wna9LbRLvvFrLT6tApC9cTW8Pbf9BT5M/ky8hhwLPpSFirzpG4q+2Y5tPohwZj6GNzI9Urc9Om5/ED0Fngu+qlthPJ+zCz5sZUO9pw74PQL9pLuCc2e+lwtaPtOiyzmoU/E97Hl9PjVIybtncec9Nxi5PDF0QL71jDw+6MclPm2vq72txYU9xZUNPrK7hb2HuQa95pUpPqK7BD79pco8sILrPTg8Yb76UTk+7PcBPpXlqbvbLm0+SUHlvU811jt8gxc9/ddDM 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 PmetQ76yrDm+Jrg8PS1oZz4wcDs9CWwAPiQw0jzVvzc9aSg9vuWFDL6j/ki+ouZUPSRSRr10hTa9cBKOvdsQ371l2uw9xWJqva6U/D1LBBs+N/DYvKrQF753cpu86HzlPeZ7IbxZ5Sk+SSyqO5bejj1pYk+9Ivm4vSoHob2h2Dg+8xYUvn6jZz0SApC94BT9vQMoHz5QmDQ74RMTPu+MAD62xGW9b5ESvtJt97wDhp09Ps9fPZ9tID5YrfW7Y459PVQ1971KFB++b4YZvqZMzD1RAO69DZWjPbsA1706m+G9zUAOPg2thrsKsp49DPQZPsqth70PpwC+ZhA4vbfapT3RY068t3NDPkW9dL2Rl4494bzZvXBWIb5ra9u9lZXiPYFxlb2Fy5E8pxtrvCXUo72+O389n7fYvBu4xj3zSEs+8uwNvXoGGb6aWrS8E1J6PTFJoTxe8z0+xoFtPGs9yz2iHkq9/jnrve93DL7a6EM+qSgMvXqYoj1chUw8aDutvYMsaT1HM 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 8cg9+fDOvaW4DL0m2qA91p4tvR+Vyz03VOQ9dNNxvazAoj2Ngm4910CzPK16gT3OZxU++FWyvUzScbwvt7K8gqcZvee88T3zcLk99dZ7vWfb2zz0PGy9E60Evrb41jxw5vi96hgYPpjbvz3+RJK8QZrIvGh1rT1Mb8e89vqxPRBQlD1K+ym+dGgVPCBMpDyu41+9JXvDPWoRADsfTAa+vMlHPbIqe73ewHC8IrOlPX1O2Tv41ws+Y1PKPcfN4b2UG9C7QVkUPRzafD2+a4Y989EBPrWr1L0WuEg8p3UgPYhrHTyWhGc9A0n5PKVDSr3BVK8910R+PMizPrxBiZs7QNPavJyyAD7zaWM9GHKfvEo0hT2u0tw9xfnavc5LKr2f3LK7iwuSvXLJOD4MyaA9+ffDPf6suT021WK9S8i6vTSpIT680rM9TGC/uxDJED0VwyS8iqBWPKG6BLxOpui74x8Lvuc2gTwcmJ+9EdWUPfaV9byH7K29TcZsPck5Fz1A3ng9sf/iM 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 vEoQlj13r4W9+7lbvYSucLt6vrc8XP6PvZwfC7zm1t87HemPPdjeqL26eaC94yn4PFDUHzw91f27C1sxPWD4jr1EdSO9hZy6vI7TPj0y+ME9CLWlvAoxyDsz1xM9xO4fOrOUK7s2ok+9kHeuvCvXgLzVLz+8E7jxvLL3gr0uQgI5D8kePc8LTDwbeGc97nIvvK/fYzzZij+7JYxbPcCJLj2izyw9RfPMu0eu1jxC3ii79mWHvRFzTr0hy909LdM/PDRAsz1uLAk+coc4vbeNozwUeXu8j8RzvdbH8T21Jrs97twjPLtJR7xdafK71kWXvcv5UT18c2i9jO+zPfhjgzy9X728gnwmPT7L6T0cXLs99JaZPRmijD0vsOa9bdwvvcnZlr10a728+iABPelymr3in4+96vZjveutmL3ZdsC8GcJ/PFiugL0qhK07IMA7OiOwRr2I6KI93ySPvMueCT0PnnA9Ar2QPTkRHb6fwHU8dE9Muw6+CL0axIk99BRsuxFOCb0dM 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 vhx4cb4IjfE8yU8RPoDmmD36waE7/mnDveglhj05ndO9yvmMvp4aID590fq8pkwQviGnKzu8V4G98H05PVBC+DzlUm49An6yPblpMr08yQ2+GkaFuxDZ1zwIzTA+wLMRPS6vP7w5Poa9lLqXPQBr8LsHLuO9GfnRPW5x9DucQ0s8s0ojvsrur71Gs7i9PbwzPU0bKT42HQg+SnkzPiqDkr1GR8q9MwSFvSCe9D3QF/A9j8oWPta0pz1S12w9HFM9vU8SQ75JV069veMYvhPYg7x5qNW9YE/RvSwcBr6QTbw9eRYpPuoeOj5sQqw9Zv/kvbEuT77jlje9p2k8Pg9e5z1lruY9WyRVva7XBT5KZG29Z9WXvrUeoT05R/S9IphbvSPrD75I9xC+uxuEvWW6e7y8Lgs+1+cCPmY1sj3r7+a9bSKBvVYqirttWQw+98YiPmYKDTw/4xq9aAt9PXaOFr0y7ki+KFGUPd5S+b22maO75IWXvZPrMb3QM9E8nGbPvGM/Dz6DM 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 5WO9bAIWvbC4NLwLkCM90InpPHf+L71D+Ks79Ez6OpNwDLwIpDc90bnRvXSZOL08NLe8gG5ZPXb//z0KGtw9HVT7PWvhhb3K2DK9yBwkPbfutj2swxQ+2SkWPNTexryYwRO94qRPvaYfzzuNq3o94DgFvj/knL33TFi9XnmOPE2Pjr198pI8+CsNPXeHRj25kjo9p9HkvMoS4L3ibLk8CVisvNpGmj17gcI907vAvVdgUz1DdOa9JiZavHS7FTv2/RC+8ZDVvIh1d7wvSr68Axudux2u5DzJzYU9jIcnPSiX4D33zOS901YcvUpNXzy+RaU8oZXuPbm+lD1G5Vm8WcSNPNk72L2UqBU9YniwPVXR5L2fdRS8yV3uvEVjur3CNa28lPunPJ0KMD1OE609QUusPYLcAL2AWZE8GgutPap8Rj0tQ7o9RqtVPe1CSL0ZpLK75kTSvT7yhrwA9LE9MDALvmiRz73WzgY8OGyEPaam6r3vvko7V0tRPaukijyp2Y89QQogM 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 4gQ+tSWQPen6LT5kW3e9bydLvoabrb3X9zi+32FjPVHbYT2Fx+48X168vYtyvL2EvP2999XuvYYX6r1GvFA9dFA4PsiFCD184O89K1cAvWMwOj0trZw8/rfzPYU0Fj2T8gS9FiejvT3OVr3zuMg8XSG9PRYynT26ss+9MUkEO5PCIL472du9RR9VPNh6Ezx0+rc9noivOyv9zLvNWyc9/KNvvElvODwSvdE98o5CPfBf+73/1Ou9Sb+pvb6Lsb27Afg9+EgDPh5XhbylP7y8/P4svRNwQb5ADNa8IBeHvLLdEz5Zsws+eFlyvc8Ol73fBS4+5FwIPrcNHT4fXuI8IvYcvnyn7b2h/jS+2ZKcvLILIT1uPOg9LklCvX6TCb5NrAC+2Vktvmj6sbyKBY09/J5oPq8+pD2fM/M955CrvfBli7yGMnc92gA/PiAzMD1g9VC9jyrgvTXIzb3wKWO93PMOPvSzFD793qC8tvioOzkTwL13TJ69IyiiPK8XrD0dwA4+2xR+M PZXXvLygJoQ9pff+OZ36Er3qAXc9p0jgPSZwOr10OKK814Hnu0npSL0E3dA9j5LJPX+aUb3i5DC7YbXTvadLBb6Ja4G80Lb9PCqvjj00A+Q9eKo7O5q9kb3KDcg933V7PRVgyj14nxU9zam0vYmiv72rcJK9JzxfPV+WqTzTz5493EtFvW1Rkr3zlyC+ZJo+vltc6ryVwq49lqgAPo5uRj2voqM9WgkovVxYRT2lPoI9UxsOPjbHkDtApcK9L6+VvYz/Vb2TwKE8dHZ2Pe4dtT27/rG9Drt5PSO0Z73IkrS9/ok+vHZ2oj0bUAo+MjV3vI/ehLytLMg8sTuIu9Cgcb0bwaw9Qrg6PCc7Ib3Aage9ZbIcvLaYlbyoLTg9yGuLPQDk2bwrK5m8cpc1vYKbir2BsTY8Ou+NO91suTx1aJO8hJdqvehIML2/YZA9uKekPKz3uz2SwgY9iGsQvoR5M77OnYW97NBJvZzZjjpxKg49nZLzvFVaw7353+C9Dwa4veOC0byQM 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 PXr2eb2WUUa8zx+1vLKzyb2aXUI9NmJGveCb7L0sfkC6J91ovVWPH72dypk9LQWkvVw8IbxK2sM8RkQDvsmF17zgwbU95CYfvTITLj18aZ68yBbYvfNBQT3Iele9LfSLvHnWwj0TtZK7ldoEvqBBgbzwa8G9Dv4RPHm+AD5yhEm93HmmOohy3jxVPi6+u5hrvL6MvT3Wr3c8RzUVPekBtbpz+PG9eglhPaSCub1kC3S9dA3UO+WRWb2njTU7e5abvXFx2b343gq9Mgu/PbG/hz3H8ku9MsbsPYBqQ70DJl28R8ftPUuVsr2uoCI9sJbWvB3YCb3zoiO6LamwvEB5lbsMIs07YMJBvfa2j73IGXS94CJqvWX0ibwExL89fGu9vF9tOLwD1648VMQSvjeRp70pCiA+Zq4uveSa6Lx+ZVK9daASvuReLLztcrC8zAWIvIecmD3O7cW7PwDWvZCvVr05sce9xvJMvQLM2z31Gki9ZnLUvMcCID3xMvW99guJO+DP6T1XM 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 OzAu6T2nuZ88BtX6O8ZbGD3B/ow9YyQbvSmrIL3qtOS9n0hivaw8Kr17+AA+n58ePe+mbb2o1aG9g1KgvXZr47xhDAq9q1JOvXbdhz1ioco9JW8wvMLsp73YeZw91Q8APorcmD06YMU8jbKbvb/jML68wvW9CztsPf5X3j1GEc686CutvKD2mb1PLQi+r+SHvbP8Or2cnS69nlwWPj4F57yeNIo9g151vQeoHz3c7MQ956LcPfcA67xqij+8nVXMvERQvb0riCI9Q1ugPRWowT3BRzk8NCaWvWmrE74CHe67JfJcPe46jz1YMgA+Q16iPLb6cj364rw8byZQPPLX0Ty1PZc9ITfKPLAxt7znHKS9Tr3/vYoU0rzddho+H276PG3nBz1lDNu9QBylvY3KnL0sEWG98810vAXWCz6WY5E9xN9pvbea4LpNAyY+pPUvPmpeRD29HKq8WngavqLQQb4qmDm+iAgeO3MqfD0EWPC8OP1QvIrTFr4mdom9dW0nviQqGL3yM 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 vSOAEb3xFs69bSjQO4oDBT6owN49ih8dvRgicLzKNhI9UxAuPuHebj0op7e90Vq0vbnkMr66JvG9n0CBPd08NDxbj3S9EasDvNS8v70Tjrq9Igl8vV3a7r24v7y86ru0Pat2lrzOA0w9h8MxPLjlJj2zVTW98dxIPVOw37yWjnO8B8TEvCf5qr3Dv4Q9wzi/PWsaxrsnyzI9BMcCu3gqZbx0K9K896EJPZZIlrzRY9c86rT3vM54J709nJ09gkzPOzZWpzqiPBI+IcSAveeCAjw73pq9WSxBPHZj8TzYR/89CT4iPOojCrx4QS49CjGnvfnUF71bC4y9hQoHPf1dyT2UFWY7IGkSvl4NULs0WwE+yxYOPm0pyz1z0mK9Edw0vbH85r1ZUoq92P3hPa+mUD0OWeG9OTRbvTxk5L1JkvG9nYhVvedsAb67Lwc9dwkJPusxUL0LZsK79AYIPVwSOD2WTkQ90cNIPfx+470sEQ89PbkNvpdpvL3MWtE9n4qnPfGt57swM 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 PfbYnryV+IE7hgkpPeHE37xf+Gc9wSGxPdbhiTv1yWa99VYAPfg0G72QSEI9iFJdu6UIt7u2rYc99EihvUdEib2q1Z89gn/evDH0uT3aurY9XZkuPc+e0TxFnvE8TpIFvUSmLz0mOeQ9SgpOPY3SF73rq2y80X9DvccVJr0Yu8m9eHCpvPlS+T3zNzK9Fv2CvSKnDr1ukwg+xeMAPqI1wj2PRrC9Z6gRve0d+bxyEn+9ulTaPS0n4j2QKmi8ujJHvUNFQr3sPRK+v0BivRtHrL30ZDy7AOQJPil11b3c5qM9PlfcPPxJHb0NYho9e3jJPdpnr7sjHp49qjiRPdrFMj33/Ic9+G34PcbQrTxsL808PGD6O/duZr3+3sQ8tVIPPQOt67wqAcE9ohJPu6+rc7tN1f49f3nLvGnlFzq3GK492m+MPGxIgb2A2Du9Xpevu5SaajwheAQ+qeUAPn6VgzoOvww9HJyCvUU81r3L29m9BVlVvX4iRj0XcbY9JvkUvTMcAL4xM 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 +Ik9IzEFPp/BRj0gHuQ9roJcO/gRez1dzoE9jUwdPrtz2r1stjC8A4OovfE0eDweDEU7EHGgPTxDQj3iUSC9g2/OvEyYC75kryq8o7MtvWvoaz1xDSY+YT2Tu1+iUz3DoOE8bOVePP/Naj2Q29s9cuIAPTxJjb2RPFG9pgPNvAGzJTwe1AE+MIi3PSRyvDxxk3c7yY+KvIrPab2wWiu8RHZjPY9aRD0IsKU8mnpZvWhG+72Mi909p0UDPvHZjT00EfI7eOaNvQr/5L0Brvm9C6U2PAgLkz1EYGk9Go0zvdZCwL1SUZ+950quvTKwS701u7M9WvU7PvAZgTveBmI91e7CukCcpD3GPWw8j8kGPpkiYDywz0y7PSXNvVzE1LrKAhg9jjxMPR99aD0nggK8ZxIsPZPtlr0gN5i9VxODPC9Lvj1uNCQ+46NIPNMbWT2i7Zg9xMnvO0EQzTuxN6E9I5oOPegQi70w5Fq9yRGjvWreBb0vgfc9ADwLPgfbQbzfM3g8EGmdM 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 56i9nb6UPQnGur1xJTG+5OeePUV/AL0LzKc8Ck35PZ8FwrsMOLW9cUFTvTGyw72+gy49UWrCPS1JCb30OEA9fo3vu/9Ehr3cS6E9EcwPPguQ2bxUKS49RB22vOkkg72aElW9+pxvvUdX572iuVI97t31vXKi2L0+hIE9svqPPIksAj0EuVQ9Bfj3vfjNoL1oiim9SNsOvnsWIj302/M9aOafvQtDgbxVTBS+kPwwvoW3ATxrGk88fQ8pvZQhuD2gyv+8G9SUvQeeDD0AXy29pGgjPWtujT18OTy8Cp2kvVF4O70W5jC+MBjUO7+1ET7pOxC9XdcWvUs8nr2gC8O9/VQHPdPEgL37u5+8bw68PVyCIbzObSm84uEzPGPuM7sBtPA9dZrVO4HcSr1NutS9CQ9mvWqeJL0cVXU9ryZbPbBqDb3IqmK9kjZuvYncuL22UKW9B3aFPUdkUD1xSEA7xb9dvYLVRL00iho93b7cPPsP1T1XiMI8F8g4vd2z2709ai69bVPSM 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 0d24OPuCPa7bgb09kCM8GugLPWz9Zj052vO8m4HOvatAbLtmtgu9URU9vOZ1Fjz80Fs7JZ7KvSiMNb3lFtS8O0pvPZalDz2ODES9Kf0Nvm6u1TzYgW69NyOwPFbUrzy0nuw83B82PKtMoD27bB295bYMPQUaCD05UoC8i0VJPX72qzyQtBO9XhvPPDG47bwBUaQ9hGuEPXKDir1aulS9Lukgvg4Wn71PPDG90CZfPS46CD6+gSQ9sJ4FPhBJ3LwLnr68qgsRPdOwxT1D9eU9aEwuPUlI+bzZxjy6CM9evffQizxhSVo81f5QvoPIsb1sJVy9YMKrujmogb01oWq5rWeKPVWyRD2iMMM9Laslvdxf/b2EfGU8yERYvb65OT0/yu49lmKSvRG4fLzIYwq+M2CQPOotYz2882m97vr5vT7dqL094VC91jHPPG0LXz3N0qg9JI+kPdTZVj3PdTq8B6avO2vAwD1x4BQ97aLYPTIRzjzb1Uq9zJs+PRMDOb2mwlu8rWWEM 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 vZEyVjyKvA29sg6LPDxPPD35n8M7eYmVvMJB+L0tk6w99xaYPfD6vD3sxXo81NnOvDnF4bvwXMq8JC+Fuxy9Qr2j5BU80PFMPfHtDb03Y2y9YYy5vUCMiL3+LeW89daLPXuykD3AIZY9wXWlvY0SBb0s4Cg9iiScPY1Bqbzzk2w9Q38OuzyYYbtIXxq8A+0UPT5+hj1szq48zxJcPZkAoLwzkmG9w1hOvfqEEb0bwJY9DKkFvEydR7outCE828KrvcosDLxcKUE9RY2hPdra4jumGDE9OsWMPbxPQ72FZuE9lSktPbI847xgN8e81bp7vU9xqL3niZy8uE0fvXSGi70Rm8o9hl8FvnEbu72hVsk8N5PRPJinTbwUQiI9PQUZPNllEzufzfC8AjEDvCon0Dz3DgA9A7WHvR5RBD0+oJ+9fmw5vit9nb2uGYe9zXxMPcWQnT1TqwO9ude+vd/cD71ObIW9GlrsPfiYlD0Etuo803woPPVvWD0y/aC91GoPPdrOfT30M 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 fi++eVQtvvtvEb3Az2A+ougHPkB5Fb5fMTa+wdzKvaOmEL5+5di9l9n2PUSSMj7aCaw9FMs4PUo4p70g4Sk+lQs2PrtYUD5FTcW8I6kkvi5sHr6SkCC+spzEvZLhMT7fXas9Y0bivT8H673pyYG+U9ohvpOiBb6kduM9JltEPiAd8D0XCJ09XNeFvQ/a3j2UNbo9csFLPj8YhTyqi/G9S2CRvSzV2b1ppeq93YVRPqWnCj580zW8LUe2u7z1Hb4ukuG9S+2mvWkQxz1jMBU+/QiePfoqLTzlKIc65Ormu4/9SL0yeLo9hAI1PacPhr0BB6S9zwv5vTCfQL4nd+g93H/FPZeaFT1nC5u9sgl2unRn/r3wDu289HJHPbmTiLyhGuA9fYBsPbA7Ir4maaS80d7hOwblDj2z/DM9nF4EvdthAT1FUZM8RXw3vlaeHTyTIyc+Ia5HPOjIBbxZfMu89AYlvlH317zDlby828iwvQbnTz6N6oU90lAxvlbUwL128Ze9EQHLM 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 JHi/5PSHPssqbL/SaGu+UzJZvwO2mL8UYNS/j/XjPh36178d+jO+GZIDPjDxNT+ZtU6/gTT1Pnhshr/73w0+2EyQv1qs1D4aKcG/x8cyP/5JqT/DbFy/Jk7FPz9/sb6gSXA/gVfEP7P5jz9TcaU9VKzRP/H3M74tG1k/Wil9vySwoT/WWyy/1bmWP0QwSr+SRum/iGwnP4TOxb9Jk5c+ADq6Pr7+4b47ZzQ+eJKevugs0j6mZDLAY6ggvw9nzj6rcg9AkAbCv8y/GEB5+hlAkyH3vx8s7b+zxvS/y0fiv2RqGkCxYfq/i74cQI/AMkB16KK/cgcPwHJpsb/3n7W/uqYXQI2WHkAikSG/X3PivynAAMBGfCPArhIcwL/FeUCi//e/osyjv8QzFcBKnx+9iTUkQCAvm7+M2va/aJKnv5oFQEAuNnU/2uMlP13VQ8D4iDHAqza0PO85Oz8qSAa+TPOqvw==", "training_traits": {"structure_gen": "TriM angle", "n_layers": 3, "max_nodes": 20, "activation_func": "Sigmoid", "epoch_num": 11}, "classes_name": ["Cryptoadz", "Cryptopunks", "Moonbirds", "Nouns"]},m=25,b=50,y=59+11/12,w=59+11.5/12,v=60;function z(e,t){const n=Math.log(1-t)/Math.log(1-e);return e=>1-Math.pow(1-e,n)}class V{constructor(e,t,n){const{model:r,inputDim:i}=j(t,n);this.model=r,this.inputDim=i,this.iteration=0,this.stage=0;const o=new Date(parseInt(e.birthYear),0,1).getTime(),a=new Date(parseInt(e.birthYear)+1,0,1).getTime();this.birthDate=new DatM e(Math.floor((o+a)/2));const l=zr.filter((t=>t[0]==e.lifeCycle))[0][2];this.growSpeed=365/l,this.cycleLength=60*l*24*3600*1e3,this.growthFunc=z(.4,.8)}updateAge(e){const t=(e.getTime()-this.birthDate.getTime())/31536e6*this.growSpeed;this.iteration=Math.floor(t/60);const n=t-60*this.iteration;let r;this.age=n;let i,o=0;if(n<25){let e=map(n,0,25,0,1);o=this.growthFunc(e),r=(25-n)/60,this.stage=1,this.stageRatio=map(n,0,25,0,1)}else n<50?(o=1,r=(50-n)/60,this.stage=2,this.stageRatio=map(n,25,50,0,1)):n<y?(o=map(n,50,M y,1,0),r=(y-n)/60,this.stage=3,this.stageRatio=map(n,50,y,0,1)):n<w?(o=0,r=(w-n)/60,this.stage=4,this.stageRatio=map(n,y,w,0,1)):n<60&&(o=0,r=(60-n)/60,this.stage=5,this.stageRatio=map(n,w,60,0,1));n<50?i=map(n,0,50,0,780/880):n<w?i=map(n,50,w,780/880,800/880):n<60&&(i=map(n,w,60,800/880,1)),this.nextStateTimestamp=Math.round(e.getTime()+this.cycleLength*r),this.statePercentage=round(100*i);let a=(25-n)/60;a<0&&(a+=1),this.nextStableTimestamp=Math.round(e.getTime()+this.cycleLength*a),this.growth=o,this.model.updatM eNeurons(o,this.iteration)}getBrainStatus(){return{totalNeurons:this.model.getTotalNeurons(),neuronsLife:this.model.getNeuronsLife(),stage:this.stage,inputDim:this.inputDim,stageRatio:this.stageRatio,age:this.age,growth:this.growth,nextStateTimestamp:this.nextStateTimestamp,nextStableTimestamp:this.nextStableTimestamp,rebirthCount:max(this.iteration,0),statePercentage:this.statePercentage}}classifyImage(e){const t=new G(e,1,e.length);return this.model.forward(t).mat[0]}}class M{constructor(e,t,n,r,i){this.p=e,this.M v=t,this.size=n,this.shape=i,this.col=r}getRadius(){return 1==Oe?1*this.size/2:2==Oe?7*this.size/16:3==Oe||4==Oe?4*this.size/7:0}update(){this.p.add(this.v)}draw(e,t,n,r){const i=this.p.x*r,o=this.p.y*r,a=this.size*r,{col:l,shape:s}=this;let h,c;1==n?h=c=l:2==n?(h=dr(t,1),c=l):(h=dr(t,0),c=dr(l,1));e.stroke(dr(c,map(1,0,1,.25,1))),e.fill(dr(h,map(1,0,1,.15,1))),3==n&&e.fill(dr(h,0)),1==s?e.ellipse(i,o,a,a):2==s?e.rect(i,o,7*a/8,7*a/8):3==s&&(e.beginShape(),e.vertex(i-4*a/7,o),e.vertex(i,o-4*a/7),e.vertex(i+4*a/7,o)M ,e.vertex(i,o+4*a/7),e.endShape(CLOSE))}}class E{constructor(e,t,n,r,i,o,a){this.center=e,this.len=t,this.angle=n,this.v=r,this.angV=i,this.c1=o,this.c2=a}getEndpoints(){const e=createVector(this.len/2*cos(this.angle),this.len/2*sin(this.angle));return[Vector.add(this.center,e),Vector.sub(this.center,e)]}update(){this.center.add(this.v),this.angle+=this.angV}draw(e,t){const[n,r]=this.getEndpoints(),i=n.x*t,o=n.y*t,a=r.x*t,l=r.y*t,s=this.c1,h=this.c2;var c=e.drawingContext.createLinearGradient(i,o,a,l);c.addColorStoM p(0,s),c.addColorStop(1,h),e.drawingContext.strokeStyle=c,e.drawingContext.globalAlpha=1,e.line(i,o,a,l),e.drawingContext.globalAlpha=1}}function S(e,t){const n=random(TAU),r=random(e,t);return createVector(r*cos(n),r*sin(n))}class R{constructor(e,t,n,r,i){this.wall=n,this.maxR=i;const o=t.length;this.nodes=[];for(let a=0;a<o;++a){const o=[],l=.25*t[a];for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),l=S(.02*i,.05*i),s=random(10,25)*i;o.push(new M(t,l,s,e[a],r))}this.nodeM s.push(o)}const a=A(e);a.unshift(e[0]),a.push(e[e.length-1]),this.lines=[];for(let e=0;e<=o;++e){const r=[],l=(0==e?1:t[e-1])*(e==o?1:t[e])*1.5;for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),o=random(5*i,10*i),l=random(TAU),s=S(.02*i,.05*i),h=random(2e-4,.001);r.push(new E(t,o,l,s,h,a[e],a[e+1]))}this.lines.push(r)}}reflectNode(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,{p:o,v:a}=e,l=e.getRadius();(o.x-l<t&&a.x<0||o.x+l>r&&a.x>0)&&(a.x=-a.x),(o.y-l<n&&a.y<0||M o.y+l>i&&a.y>0)&&(a.y=-a.y)}reflectLine(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,[o,a]=e.getEndpoints(),l=e.v;(min(o.x,a.x)<t&&l.x<0||max(o.x,a.x)>r&&l.x>0)&&(l.x=-l.x),(min(o.y,a.y)<n&&l.y<0||max(o.y,a.y)>i&&l.y>0)&&(l.y=-l.y)}update(){for(const e of this.lines)for(const t of e)t.update(),this.reflectLine(t);for(const e of this.nodes)for(const t of e)t.update(),this.reflectNode(t)}draw(e,t,n,r,i){const o=i/this.maxR;for(const t of this.lines){const n=t.length*r;for(let r=0;r<n;++r)t[r].draw(e,o)}for(cM onst i of this.nodes){const a=i.length*r;for(let r=0;r<a;++r)i[r].draw(e,t,n,o)}}}function I(e,t){re(e),e.fill(0),e.rect(0,0,500,500),ie(e),e.noStroke(),e.fill(dr(cr("#000000"),.5)),e.push(),e.translate(250,250),e.scale(t),e.translate(-250,-250),e.beginShape(),e.vertex(235.2,24.9),e.bezierVertex(215,24.6,185,11.4,164.8,11),e.bezierVertex(147.2,10.7,129.3,10.4,112.2,14.7),e.bezierVertex(95.1,19,78.5,28.5,69.6,43.8),e.bezierVertex(57.699,64.199,61.599,90.199,70.199,112.2),e.bezierVertex(78.799,134.2,91.6,154.6,97.199M ,177.5),e.bezierVertex(102.499,199.2,100.899,222.5,92.799,243.2),e.bezierVertex(83,268,64.6,288.3,48.9,310),e.bezierVertex(33.2,331.7,24.5,337.5,26.599,364.1),e.bezierVertex(28.2,384.1,61.399,404.2,75.7,418.3),e.bezierVertex(90,432.4,73.7,488.2,91.9,496.7),e.bezierVertex(124.2,511.6,159,472.5,194.3,468.1),e.bezierVertex(211.6,465.9,267.4,501.5,283.9,495.9),e.bezierVertex(340.7,476.7,298.599,428.9,355.4,409.7),e.bezierVertex(370.799,404.5,454.5,407.6,464.4,394.8),e.bezierVertex(478.599,376.3,474.7,349.3,464.299,328.M 4),e.bezierVertex(453.9,307.5,438.099,289.5,428.699,268.2),e.bezierVertex(412,230,419,182.6,446.1,150.9),e.bezierVertex(449.7,146.7,453.6,142.7,455.8,137.6),e.bezierVertex(459.4,129.299,457.5,119.6,454.8,111),e.bezierVertex(443.2,73.4,417.3,40.4,383.6,20.299),e.bezierVertex(358.1,5,343.2,-.4,313.5,0),e.bezierVertex(287.5,.4,261.6,25.4,235.2,24.9),e.endShape(),e.pop()}function C(e,t,n,r,i,o){let a,l,s;re(t),t.fill(0),t.rect(0,0,500,500),ie(t),t.noStroke(),t.fill(dr(n,.5)),1==i?(l=0,s=25,a=map(o,0,25,500,0)):a=0,t.reM ct(0,a,500,500),e.noStroke(),e.fill(r),e.rect(0,0,500,500),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(8M 4.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),M e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,1M 12.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),e.fill(n),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3M ),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7M ,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierM Vertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1M ,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),re(e),e.fill(r),e.beginShape(),e.vertex(184.3,473.2),e.bezierVertex(164,473.2,144.7,462.099,134,444.3),e.bezierVertex(131.7,440.5,129.1,438.5,125,437.1),e.bezierVertex(97.3,428.1,80.5,400.6,85.2,371.8),e.bezierVertex(86.3,365.1,85.8,364.1,79.9,361.2),e.bezierVertex(57.2,349.8,46.2,323.3,54.3,299.7),e.bezierVertex(54.7,298.599,55.1,297.7,55.5,296.9),e.bezierVertex(55.6,296.599,55.8,296.4,55.9,296.099),e.vertex(57.9,291.499),e.vertex(62.5,29M 3.599),e.bezierVertex(64.9,294.7,67.3,295.799,69.5,296.9),e.bezierVertex(74.5,299.299,79.1,301.599,83.9,303.099),e.bezierVertex(89.8,304.9,96.5,305.499,102.7,305.9),e.bezierVertex(102.8,305.9,102.9,305.9,103,305.9),e.bezierVertex(106.6,305.9,108.9,302.799,109,299.799),e.bezierVertex(109.1,296.199,106.6,293.4,102.7,292.799),e.bezierVertex(101.3,292.599,99.9,292.4,98.4,292.299),e.bezierVertex(94.3,291.799,90.1,291.299,86,289.9),e.bezierVertex(68.9,284,56.5,270.2,52.7,252.799),e.bezierVertex(48.9,235.499,54.5,217.7,67M .6,205.299),e.bezierVertex(71.9,201.299,72.7,198.1,70.8,192.399),e.bezierVertex(64.2,172.2,68.8,153.99,84.2,139.599),e.bezierVertex(94.2,130.199,105.5,125.399,117.8,125.399),e.bezierVertex(124.3,125.399,131.1,126.799,137.8,129.599),e.bezierVertex(157,137.399,167.9,152.799,169.4,173.99),e.vertex(169.4,174.399),e.bezierVertex(169.5,175.899,169.6,177.2,169.9,178.299),e.bezierVertex(170.7,181.2,173.2,183.2,176.1,183.2),e.bezierVertex(176.299,183.2,176.5,183.2,176.7,183.2),e.bezierVertex(180.1,182.899,182.6,180.299,182.M 7,177),e.bezierVertex(183.1,162,178.299,148.2,168.399,136.1),e.bezierVertex(158.2,123.5,144.899,115.8,128.799,113.199),e.bezierVertex(123.499,112.299,120.399,109.799,118.899,104.99),e.bezierVertex(113.899,89.699,120.699,72.299,134.899,64.499),e.bezierVertex(139.99,61.699,145.799,60.199,151.7,60.199),e.bezierVertex(162.2,60.199,171.899,64.799,178.1,72.699),e.bezierVertex(179.6,74.6,180.799,76.6,181.9,78.499),e.vertex(182.2,79.099),e.bezierVertex(183.2,80.699,185.2,83.299,188.4,83.299),e.bezierVertex(189.5,83.299,190M .6,82.99,191.7,82.399),e.bezierVertex(195.1,80.599,196,76.99,194,72.799),e.bezierVertex(190.1,64.799,184.1,58.499,175.6,53.299),e.bezierVertex(174.6,52.699,173.7,52.099,172.5,51.499),e.vertex(170.5,50.299),e.vertex(163,45.899),e.vertex(170.5,41.599),e.bezierVertex(182,34.99,193.1,30.799,204.4,28.599),e.bezierVertex(208.6,27.799,212.9,27.399,217.2,27.399),e.bezierVertex(217.6,27.399,217.9,27.399,218.3,27.399),e.bezierVertex(231.4,27.599,242.7,38.199,243,50.599),e.bezierVertex(243.4,64.899,243.3,78.99,243.2,93.799),eM .bezierVertex(243.2,99.799,243.1,105.899,243.1,112.099),e.vertex(243.1,119.199),e.vertex(236.4,116.799),e.bezierVertex(235.7,116.499,235,116.299,234.4,115.99),e.bezierVertex(233.4,115.599,232.6,115.299,232,115.199),e.bezierVertex(230.6,114.899,229.2,114.599,227.8,114.299),e.bezierVertex(223.8,113.499,220.1,112.699,216.4,112.499),e.vertex(216.2,112.499),e.bezierVertex(212.5,112.499,210.7,115.599,210.6,118.599),e.bezierVertex(210.4,122.399,212.7,125.099,216.4,125.399),e.bezierVertex(230.1,126.399,238.9,133.099,242.3,M 145.199),e.bezierVertex(243.2,148.399,243.2,151.599,243.2,154.499),e.vertex(243.2,155.099),e.bezierVertex(243.2,254.199,243.2,330,243.2,400.599),e.bezierVertex(243.2,401.99,243.2,403.4,243.2,404.9),e.bezierVertex(243.3,411.099,243.3,417.599,242.3,423.9),e.bezierVertex(238.1,449.2,219.6,467.799,194,472.5),e.bezierVertex(190.9,472.9,187.6,473.2,184.3,473.2),e.endShape(),e.beginShape(),e.vertex(315.8,473.1),e.bezierVertex(309.3,473.1,302.8,472,296.5,469.9),e.bezierVertex(270.4,461,253.8,434.9,257.1,407.9),e.bezierVertM ex(260,384,273.8,366.8,297,358.3),e.bezierVertex(297.7,358.1,298.3,357.8,299,357.6),e.bezierVertex(299.8,357.3,300.6,357.1,301.2,356.8),e.bezierVertex(304.3,355.4,306,351.8,304.9,348.7),e.bezierVertex(304,345.9,301.7,344.2,299,344.2),e.bezierVertex(298.6,344.2,298.1,344.2,297.6,344.3),e.bezierVertex(288.1,346.3,279,350.9,269.7,358.3),e.bezierVertex(268.9,358.9,268.1,359.6,267.2,360.4),e.vertex(265.5,361.8),e.vertex(258.5,367.6),e.vertex(257.4,358.6),e.bezierVertex(257.3,358,257.3,357.5,257.2,357.1),e.bezierVertex(2M 57,356,256.9,354.9,256.9,353.7),e.bezierVertex(256.9,334.8,256.9,316,256.9,297.1),e.bezierVertex(256.9,260.3,256.9,222.3,256.8,185),e.bezierVertex(256.8,170.7,268.3,158.8,282.5,158.4),e.bezierVertex(284.8,158.3,286.7,157.6,287.9,156.2),e.bezierVertex(289.099,154.9,289.599,153.2,289.5,151.3),e.bezierVertex(289.3,147.5,286.7,145.1,282.7,145.1),e.bezierVertex(282.5,145.1,282.2,145.1,282,145.1),e.bezierVertex(278.8,145.3,275.5,146.1,272,146.9),e.bezierVertex(270.9,147.2,269.8,147.4,268.6,147.7),e.bezierVertex(267.9,147M .9,267,148.2,265.8,148.7),e.bezierVertex(265.1,149,264.4,149.3,263.5,149.6),e.vertex(256.8,152),e.vertex(256.8,114.6),e.bezierVertex(256.8,95,256.8,75.4,256.8,55.9),e.bezierVertex(256.8,38,267.2,27.3,284.6,27.3),e.bezierVertex(285.3,27.3,285.9,27.3,286.6,27.3),e.bezierVertex(299,27.9,318.7,34.5,329.6,41.9),e.vertex(336.1,46.3),e.vertex(324.4,53.3),e.bezierVertex(316.2,58.2,310.2,64.6,306,72.9),e.bezierVertex(304.2,76.4,305.1,78.5,306.1,80),e.bezierVertex(307.4,81.9,309.4,83,311.6,83),e.bezierVertex(313.7,83,315.7,8M 1.9,317.1,80.1),e.bezierVertex(317.4,79.7,317.8,79,318.1,78.4),e.bezierVertex(318.4,77.9,318.7,77.3,319,76.8),e.bezierVertex(325.3,66.2,336.3,59.9,348.5,59.9),e.bezierVertex(353.2,59.9,357.8,60.8,362.1,62.7),e.bezierVertex(377.6,69.3,386,86.7,381.7,103.2),e.bezierVertex(380.7,107.1,378.5,111.8,371.1,113.1),e.bezierVertex(342.7,118.1,322.2,139.1,317.8,167.8),e.bezierVertex(317.4,170.3,317.3,173.2,317.4,176.5),e.bezierVertex(317.5,180,320.1,182.8,323.5,183),e.bezierVertex(323.6,183,323.8,183,323.9,183),e.bezierVertexM (327.1,183,329.8,180.6,330.3,177.2),e.bezierVertex(330.6,175.7,330.7,174,330.9,172.3),e.bezierVertex(331.1,169.8,331.4,167.3,332,164.7),e.bezierVertex(337.3,141.9,357.7,125.4,380.7,125.4),e.bezierVertex(382.5,125.4,384.3,125.5,386.1,125.7),e.bezierVertex(412.8,128.9,432.6,150.9,432,176.9),e.bezierVertex(431.9,182.3,430.9,187.7,429.1,192.7),e.bezierVertex(427.2,197.9,428,201,432.3,205),e.bezierVertex(446.8,218.7,451.8,236,446.6,255),e.bezierVertex(441.4,274,428.3,286.5,408.7,291.3),e.bezierVertex(406.1,291.9,403.6,2M 92.1,401.1,292.3),e.bezierVertex(400,292.4,398.9,292.5,397.9,292.6),e.bezierVertex(393.6,293.1,390.9,295.7,391,299.5),e.bezierVertex(391.1,303.4,394,305.8,398.5,305.8),e.bezierVertex(409.9,305.8,420.8,302.6,431.1,296.4),e.bezierVertex(431.8,296,432.5,295.5,433.2,295.1),e.bezierVertex(433.8,294.7,434.5,294.3,435.2,293.9),e.bezierVertex(436,293.4,436.6,293.2,437.2,293.1),e.bezierVertex(437.4,293,437.7,292.9,438.1,292.8),e.vertex(442.5,291.4),e.vertex(444.2,295.7),e.bezierVertex(450.9,312.4,449.5,328.4,440,343.4),e.beM zierVertex(435.3,350.8,428.7,356.7,420.2,361.1),e.bezierVertex(414.3,364.1,413.7,365.2,414.8,371.7),e.bezierVertex(419.5,400.2,403,427.6,375.6,436.9),e.bezierVertex(371,438.5,368.3,440.7,365.8,444.7),e.bezierVertex(355.2,462.5,336.4,473.1,315.8,473.1),e.bezierVertex(315.8,473.1,315.8,473.1,315.8,473.1),e.endShape(),ie(e),e.fill(n),e.beginShape(),e.vertex(120.2,279.9),e.bezierVertex(117.9,279.9,112.4,279.299,112.2,273.599),e.bezierVertex(112,267.7,117.4,266.7,119.7,266.599),e.bezierVertex(133.1,265.799,143.1,259.499M ,149.3,247.899),e.bezierVertex(149.6,247.299,150.1,246.399,150.3,245.399),e.bezierVertex(150.6,244.299,150.5,243.299,150.5,242.7),e.bezierVertex(150.5,242.6,150.5,242.5,150.5,242.299),e.vertex(150.3,238.799),e.vertex(141.1,235.99),e.bezierVertex(114.6,227.799,95.6,202.499,95.9,175.799),e.bezierVertex(95.9,173.99,96.4,168.199,102.2,168.199),e.bezierVertex(102.6,168.199,103,168.199,103.4,168.299),e.bezierVertex(104.8,168.499,108.2,168.899,109.2,175.599),e.bezierVertex(109.3,176.599,109.5,177.599,109.6,178.499),e.beziM erVertex(110.4,184.199,111.3,189.99,113.7,195.499),e.bezierVertex(121.9,213.99,139.5,225.499,159.7,225.499),e.bezierVertex(172.1,225.499,184.1,220.899,193.5,212.599),e.bezierVertex(194,212.199,194.4,211.799,194.8,211.399),e.bezierVertex(195.1,211.099,195.5,210.799,195.8,210.399),e.bezierVertex(197.4,208.99,199.2,208.2,200.9,208.2),e.bezierVertex(202.5,208.2,204,208.899,205.3,210.1),e.bezierVertex(208,212.9,207.9,216.9,205,219.9),e.bezierVertex(196.5,228.6,186.3,234.3,174.7,236.8),e.bezierVertex(168.799,238.1,165.6,M 241,163.899,246.7),e.bezierVertex(158.3,265.9,139.9,279.7,120.2,279.9),e.vertex(120.2,279.9),e.endShape(),e.beginShape(),e.vertex(187.2,427.5),e.bezierVertex(183.799,427.5,181.299,425.3,180.799,422),e.bezierVertex(180.6,420.8,180.499,419.5,180.399,418.1),e.bezierVertex(180.299,417,180.2,415.8,180.099,414.7),e.bezierVertex(177.199,390.5,156.699,371.3,132.399,370.2),e.bezierVertex(131.99,370.2,131.499,370.2,131.099,370.2),e.bezierVertex(130.699,370.2,130.299,370.2,129.799,370.2),e.bezierVertex(125.99,369.9,123.199,36M 7.2,123.099,363.6),e.bezierVertex(122.99,360.2,125.799,357.3,129.599,356.9),e.bezierVertex(130.499,356.8,131.499,356.8,132.599,356.7),e.bezierVertex(133.199,356.7,133.799,356.7,134.399,356.6),e.vertex(138.299,356.4),e.vertex(139.1,352.6),e.bezierVertex(139.5,350.7,139.799,348.9,140.2,347),e.bezierVertex(140.899,343.4,141.5,340,142.399,336.8),e.bezierVertex(150.099,310.7,174.399,292,201.399,291.3),e.vertex(201.599,291.3),e.bezierVertex(203.699,291.3,206.299,292,208.299,293.2),e.bezierVertex(210.499,294.5,210.699,297M .5,209.99,299.8),e.bezierVertex(209.499,301.5,208.199,303.9,203.299,304.7),e.bezierVertex(202.199,304.9,200.99,305,199.799,305.2),e.bezierVertex(194.499,305.9,188.99,306.599,183.799,308.9),e.bezierVertex(165.499,316.799,155.199,331.299,152.99,352),e.bezierVertex(152.399,357.8,154.499,361.7,159.699,364.5),e.bezierVertex(178.199,374.4,189.399,390,193.099,410.9),e.bezierVertex(193.699,414.299,193.899,418,193.599,422),e.bezierVertex(193.399,425.2,190.899,427.5,187.399,427.5),e.vertex(187.2,427.5),e.endShape(),e.beginShM ape(),e.vertex(364.3,281.1),e.bezierVertex(346.3,280.6,332.9,272.8,323.5,257),e.bezierVertex(321.6,253.9,320.4,250.2,319.2,246.7),e.bezierVertex(317.7,242.2,315,239.799,310.5,238.799),e.bezierVertex(298.5,236.299,288,230.7,279.4,222.1),e.bezierVertex(276.7,219.4,274.9,215.299,278,211.9),e.bezierVertex(279.4,210.3,281,209.6,282.6,209.6),e.bezierVertex(284.4,209.6,286.4,210.6,288.3,212.5),e.bezierVertex(297.8,221.8,310.4,226.9,323.9,226.9),e.bezierVertex(340.2,226.9,355.1,219.3,364.8,206.2),e.bezierVertex(371,197.8,3M 74.2,188.5,374.5,178.5),e.vertex(374.5,177.9),e.bezierVertex(374.5,177,374.5,176.1,374.7,175.4),e.bezierVertex(375.3,171.8,377.9,169.5,381.3,169.5),e.bezierVertex(381.4,169.5,381.5,169.5,381.7,169.5),e.bezierVertex(385.4,169.7,388,172.4,388,176.1),e.bezierVertex(388.1,190.7,383.4,204,374.2,215.8),e.bezierVertex(365.8,226.5,354.7,233.9,341.2,237.9),e.bezierVertex(340,238.3,338.7,238.6,337.3,239.1),e.bezierVertex(335.9,239.6,335.1,240.4,334.7,240.9),e.bezierVertex(334.599,241,334.5,241.1,334.4,241.2),e.vertex(331.799M ,243.6),e.vertex(333.199,246.8),e.bezierVertex(338.199,258,346.799,264.9,358.699,267.3),e.bezierVertex(360.199,267.6,361.599,267.7,362.99,267.9),e.bezierVertex(363.599,268,364.299,268,364.899,268.1),e.bezierVertex(369.099,268.6,371.799,271.4,371.499,275),e.bezierVertex(371.199,278.6,368.299,281.2,364.399,281.2),e.vertex(364.3,281.1),e.endShape(),e.beginShape(),e.vertex(323.9,437),e.bezierVertex(323.7,437,323.5,437,323.299,437),e.bezierVertex(319.599,436.7,317.299,434.1,317.4,430.2),e.bezierVertex(317.9,406.099,328.M 299,388,349.5,375),e.bezierVertex(350.7,374.2,352,373.5,353.4,372.8),e.bezierVertex(354.099,372.4,354.7,372.1,355.299,371.7),e.vertex(357.499,370.5),e.vertex(357.799,368),e.bezierVertex(360.4,346.6,345.199,323.7,323.9,317),e.bezierVertex(319.099,315.5,314.099,314.9,309.299,314.4),e.vertex(308.199,314.299),e.bezierVertex(305.99,314.099,300.799,312.9,300.899,307.299),e.bezierVertex(300.99,303.499,303.899,300.9,308.099,300.9),e.vertex(308.299,300.9),e.bezierVertex(327.099,301.299,343.099,308.7,355.699,322.9),e.bezierVM ertex(364.299,332.5,369.399,344.099,370.99,357.299),e.bezierVertex(371.099,358.4,371.299,359.4,371.499,360.499),e.bezierVertex(371.599,360.99,371.699,361.499,371.799,361.99),e.vertex(372.499,365.899),e.vertex(377.899,366.199),e.bezierVertex(378.799,366.299,379.699,366.299,380.599,366.399),e.bezierVertex(385.099,366.699,387.899,369.399,387.799,373.299),e.bezierVertex(387.699,377.099,384.99,379.599,380.799,379.799),e.bezierVertex(369.799,380.199,359.99,383.299,351.899,389.299),e.bezierVertex(338.799,398.799,331.699,4M 11.699,330.699,427.499),e.vertex(330.699,428.299),e.bezierVertex(330.599,429.199,330.599,430.099,330.499,430.799),e.bezierVertex(330,434.7,327.5,437,323.9,437),e.endShape()}function T(e){return e[0].map(((t,n)=>e.map((e=>e[n]))))}function A(e){return e.map((e=>Array.isArray(e)?A(e):e))}function D(e,t){return floor(random(e,t))}function k(e){let t=0;for(const n of e)t+=n[1];let n=random(t),r=0;for(const t of e)if(r+=t[1],n<r)return t[0];return null}function L(e){for(let t=1;t<e.length;++t){let n=D(0,t),r=e[t];e[t]=eM [n],e[n]=r}}function P(e){return null==e||""===e}function O(e){return new Promise((t=>setTimeout(t,e)))}function F(e,t,n){let r=0;for(let i=1;i<=1e3;++i)for(let o=1;o<=1e3;++o)if(e*o%(t*i)==0){let e=1*i/o;abs(e-n)<abs(r-n)&&(r=e)}return r}function N(){let e=60*(new Date).getTimezoneOffset()*1e3;return new Date(Date.now()-e).toISOString().slice(0,-1)}function B(e,t,n){let r;if(push(),textSize(e),textWidth(t)<=n)r=t;else for(let e=0;e<t.length;++e){const i=t.slice(0,e+1)+"...";if(textWidth(i)>n){r=i;break}}return popM (),r}function Y(e){var t=e%10,n=e%100;return 1==t&&11!=n?e+"st":2==t&&12!=n?e+"nd":3==t&&13!=n?e+"rd":e+"th"}class G{constructor(e,t,n){this.n=t,this.m=n,this.mat=[];let r=0;for(let t=0;t<this.n;++t){this.mat.push([]);for(let n=0;n<this.m;++n)this.mat[t].push(r<e.length?e[r]:0),r+=1}return this}copy(){return new G(this.mat.flat(),this.n,this.m)}}class H{static __linear=e=>e;static __relu=e=>Math.max(e,0);static __leaky_relu=e=>e>0?e:.2*e;static __sigmoid=e=>1/(1+Math.exp(-e));static __tanh=e=>Math.tanh(e);static __M apply_unary_op(e,t){const n=e.copy();for(let e=0;e<n.n;++e)for(let r=0;r<n.m;++r)n.mat[e][r]=t(n.mat[e][r]);return n}static linear=e=>H.__apply_unary_op(e,H.__linear);static relu=e=>H.__apply_unary_op(e,H.__relu);static leaky_relu=e=>H.__apply_unary_op(e,H.__leaky_relu);static sigmoid=e=>H.__apply_unary_op(e,H.__sigmoid);static tanh=e=>H.__apply_unary_op(e,H.__tanh);static __add=(e,t)=>e+t;static __mul=(e,t)=>e*t;static __apply_binary_op=(e,t,n)=>{"object"!=typeof t&&(t=new G([t],1,1));const r=e.copy();for(let e=0;M e<r.n;++e)for(let i=0;i<r.m;++i)r.mat[e][i]=n(r.mat[e][i],t.mat[e%t.n][i%t.m]);return r};static mul=(e,t)=>H.__apply_binary_op(e,t,H.__mul);static add=(e,t)=>H.__apply_binary_op(e,t,H.__add);static matMul(e,t){const n=new G([],e.n,t.m);for(let r=0;r<n.n;++r)for(let i=0;i<n.m;++i)for(let o=0;o<e.m;++o)n.mat[r][i]+=e.mat[r][o]*t.mat[o][i];return n}static softmax(e){const t=H.__apply_unary_op(e,(e=>Math.exp(e))),n=t.mat.flat().reduce(((e,t)=>e+t));for(let r=0;r<e.n;++r)for(let i=0;i<e.m;++i)t.mat[r][i]/=n;return t}}clM ass ${constructor(e,t){this.scale=e,this.offset=t}forward(e){return H.add(H.mul(e,this.scale),this.offset)}}class X{constructor(){}forward(e){return e.map((e=>e.flat()))}}class W{constructor(e,t,n,r){this.out_dim=e,this.activation=t,this.w=n,this.b=r}forward(e){const t=H.add(H.matMul(e,this.w),this.b);return null==this.activation?t:this.activation(t)}}class U{constructor(e,t,n){this.preprocessLayers=e,this.hiddenLayers=t,this.outputLayer=n,this.totalNeurons=this.hiddenLayers.map((e=>e.out_dim)),this.currentOrders=[M ],this.currentIteration=null}updateNeurons(e,t){if(t!=this.currentIteration){this.currentOrders=[];for(let e=0;e<this.totalNeurons.length;++e){randomSeed(100*(t+1)+e);const n=[];for(let t=0;t<this.totalNeurons[e];++t)n.push(t);L(n),this.currentOrders.push(n)}this.currentIteration=t}const n=A(this.totalNeurons),r=n.reduce(((e,t)=>e+t))*(1-e);for(let e=0;e<r;++e){const t=n.map(((e,t)=>(e-1)/this.totalNeurons[t]));n[t.map(((e,t)=>[e,t])).reduce(((e,t)=>t[0]>e[0]?t:e))[1]]-=Math.min(r-e,1)}this.neuronsLife=[];for(let eM =0;e<n.length;++e){const t=this.currentOrders[e],r=Array(this.totalNeurons[e]).fill(0);for(let i=0;i<n[e];++i)r[t[i]]=Math.min(n[e]-i,1);this.neuronsLife.push(r)}}getTotalNeurons(){return A(this.totalNeurons)}getNeuronsLife(){return A(this.neuronsLife)}forward(e){for(const t of this.preprocessLayers)e=t.forward(e);for(const[t,n]of this.hiddenLayers.entries()){e=n.forward(e);const r=new G(this.neuronsLife[t],1,e.m);e=H.mul(e,r)}return e=this.outputLayer.forward(e),H.softmax(e)}}function q(e){switch(e){case"relu":retM urn H.relu;case"sigmoid":return H.sigmoid;case"tanh":return H.tanh;case"leaky_relu":return H.leaky_relu;default:return H.linear}}function j(e,t){const n=[],r=[],i=Z(t);let o=null,a=0,l=[];for(const t of e.config.layers)if("InputLayer"==t.class_name)o=t.config.batch_input_shape.slice(1),l=o;else if("Rescaling"==t.class_name)n.push(new $(t.config.scale,t.config.offset));else if("Flatten"==t.class_name)o=[o.reduce(((e,t)=>e*t))];else if("Dense"==t.class_name){const e=[t.config.units],n=o[0]*e[0],l=e[0],s=i.subarray(a,M a+n);a+=n;const h=i.subarray(a,a+l);a+=l;const c=new G(s,o[0],e[0]),u=new G(h,1,e[0]),f=q(t.config.activation);r.push(new W(e[0],f,c,u)),o=e}const s=r.pop();return{model:new U(n,r,s),inputDim:l}}function Z(e){const t=window.atob(e),n=t.length/Float32Array.BYTES_PER_ELEMENT,r=new DataView(new ArrayBuffer(Float32Array.BYTES_PER_ELEMENT)),i=new Float32Array(n);let o=0;for(let e=0;e<n;e++){o=4*e;for(let e=0;e<4;++e)r.setUint8(e,t.charCodeAt(o+e));i[e]=r.getFloat32(0,!0)}return i}class K{constructor(e){this.elt=e,this._M events={},this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight}position(){if(0===arguments.length)return{x:this.elt.offsetLeft,y:this.elt.offsetTop};var e="absolute";return"static"!==arguments[2]&&"fixed"!==arguments[2]&&"relative"!==arguments[2]&&"sticky"!==arguments[2]&&"initial"!==arguments[2]&&"inherit"!==arguments[2]||(e=arguments[2]),this.elt.style.position=e,this.elt.style.left=arguments[0]+"px",this.elt.style.top=arguments[1]+"px",this.x=arguments[0],this.y=arguments[1],this}show(){return this.M elt.style.display="block",this}hide(){return this.elt.style.display="none",this}size(e,t){if(0===arguments.length)return{width:this.elt.offsetWidth,height:this.elt.offsetHeight};var n=e,r=t;if(n!==te||r!==te){if(n===te?n=t*this.width/this.height:r===te&&(r=e*this.height/this.width),this.elt instanceof HTMLCanvasElement){var i,o={},a=this.elt.getContext("2d");for(i in a)o[i]=a[i];for(i in this.elt.setAttribute("width",n*this._pInst._pixelDensity),this.elt.setAttribute("height",r*this._pInst._pixelDensity),this.elt.sM tyle.width=n+"px",this.elt.style.height=r+"px",this._pInst.scale(this._pInst._pixelDensity,this._pInst._pixelDensity),o)this.elt.getContext("2d")[i]=o[i]}else this.elt.style.width=n+"px",this.elt.style.height=r+"px",this.elt.width=n,this.elt.height=r;this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight,this._pInst&&this._pInst._curElement&&this._pInst._curElement.elt===this.elt&&(this._pInst._setProperty("width",this.elt.offsetWidth),this._pInst._setProperty("height",this.elt.offsetHeight))}return thisM }style(e,t){if(t instanceof Color&&(t="rgba("+t.levels[0]+","+t.levels[1]+","+t.levels[2]+","+t.levels[3]/255+")"),void 0===t){if(-1===e.indexOf(":"))return window.getComputedStyle(this.elt).getPropertyValue(e);for(var n=e.split(";"),r=0;r<n.length;r++){var i=n[r].split(":");i[0]&&i[1]&&(this.elt.style[i[0].trim()]=i[1].trim())}}else if(this.elt.style[e]=t,"width"===e||"height"===e||"left"===e||"top"===e){var o=window.getComputedStyle(this.elt).getPropertyValue(e).replace(/[^\d.]/g,"");this[e]=Math.round(parseFloatM (o,10))}return this}value(){return arguments.length>0?(this.elt.value=arguments[0],this):"range"===this.elt.type?parseFloat(this.elt.value):this.elt.value}mouseClicked(e){return this._adjustListener("click",e,this),this}isFocused(){return document.activeElement===this.elt}_adjustListener(e,t,n){return!1===t?this._detachListener(e,n):this._attachListener(e,t,n),this}_attachListener(e,t,n){n._events[e]&&this._detachListener(e,n);var r=t.bind(n);n.elt.addEventListener(e,r,!1),n._events[e]=r}_detachListener(e,t){var n=M t._events[e];t.elt.removeEventListener(e,n,!1),t._events[e]=null}}function J(e,t){var n=document.createElement("button");return n.innerHTML=e,t&&(n.value=t),ee(n)}function Q(e){var t=arguments.length>1&&void 0!==arguments[1]&&arguments[1],n=function(t){var n=!0,r=!1,i=void 0;try{for(var o,a=t.target.files[Symbol.iterator]();!(n=(o=a.next()).done);n=!0){var l=o.value;File._load(l,e)}}catch(e){r=!0,i=e}finally{try{n||null==a.return||a.return()}finally{if(r)throw i}}};if(window.File&&window.FileReader&&window.FileListM &&window.Blob){var r=document.createElement("input");return r.setAttribute("type","file"),t&&r.setAttribute("multiple",!0),r.addEventListener("change",n,!1),ee(r)}}function ee(e){return document.body.appendChild(e),new K(e)}createImg=function(){var e,t=document.createElement("img"),n=arguments;return n.length>1&&"string"==typeof n[1]&&(t.alt=n[1]),n.length>2&&"string"==typeof n[2]&&(t.crossOrigin=n[2]),t.src=n[0],e=ee(t,this),t.addEventListener("load",(function(){e.width=t.offsetWidth||t.width,e.height=t.offsetHeigM ht||t.height;var r=n[n.length-1];"function"==typeof r&&r(e)})),e},createInput=function(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:"",t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:"text",n=document.createElement("input");return n.setAttribute("value",e),n.setAttribute("type",t),ee(n,this)};const te="auto";function ne(e){re(e);const t=e._rectMode;e.rectMode(CORNER),e.rect(0,0,e.width,e.height),e.rectMode(t),ie(e)}function re(e){e.push(),e.fill(255,255,255,255),e.blendMode(REMOVE)}functiM on ie(e){e.blendMode(BLEND),e.pop()}File=function(e,t){this.file=e,this._pInst=t;var n=e.type.split("/");this.type=n[0],this.subtype=n[1],this.name=e.name,this.size=e.size,this.data=void 0},File._createLoader=function(e,t){var n=new FileReader;return n.onload=function(n){var r=new File(e);if("application/json"===r.file.type)r.data=JSON.parse(n.target.result);else if("text/xml"===r.file.type){var i=(new DOMParser).parseFromString(n.target.result,"text/xml");r.data=new XML(i.documentElement)}else r.data=n.target.resuM lt;t(r)},n},File._load=function(e,t){if(/^text\//.test(e.type)||"application/json"===e.type)File._createLoader(e,t).readAsText(e);else if(/^(video|audio)\//.test(e.type)){var n=new File(e);n.data=URL.createObjectURL(e),t(n)}else File._createLoader(e,t).readAsDataURL(e)},XML=function(e){if(e)this.DOM=e;else{var t=document.implementation.createDocument(null,"doc");this.DOM=t.createElement("root")}},document.addEventListener("DOMContentLoaded",(function(){addEventListener("mousemove",(e=>{window.mouseX=e.pageX,window.M mouseY=e.pageY}))})),new e("global");const oe="55";let ae,le,se,he,ce,ue,fe,de,xe,ge,pe,me,be,ye,we,ve,ze,Ve,_e,Me,Ee,Se,Re,Ie,Ce,Te,Ae,De,ke,Le,Pe,Oe,Fe,Ne,Be,Ye,Ge,He,$e,Xe,We,Ue,qe,je,Ze,Ke,Je,Qe,et,tt,nt,rt,it,ot,at,lt,st,ht,ct,ut,ft,dt,xt,gt,pt,mt,bt,yt,wt,vt,zt,Vt,_t,Mt,Et,St,Rt,It,Ct,Tt,At=!1,Dt=!1,kt=!0,Lt=!1,Pt=!1;const Ot=[" ","Growing","Stable","Decaying","Dead","Rebirth"];let Ft,Nt,Bt,Yt,Gt,Ht,$t,Xt,Wt,Ut,qt,jt,Zt,Kt,Jt,Qt,en,tn,nn,rn,on,an,ln,sn,hn=0,cn=0,un=0,fn=!1,dn=!0,xn=!0,gn=null,pn=null,mn=null,M bn=!1,yn=!1,wn=null,vn=null,zn=!1;async function setup(){let e=windowWidth,t=windowHeight;createCanvas(e,t),et=createGraphics(e,t),Xe=createGraphics(e,t),$e=createGraphics(e,t),We=createGraphics(e,t),Ue=createGraphics(e,t),qe=createGraphics(e,t),Qe=createGraphics(e,t),je=createGraphics(e,t),Ze=createGraphics(e,t),Ke=createGraphics(e,t),Je=createGraphics(e,t),tt=createGraphics(500,500),nt=createGraphics(500,500),rt=createGraphics(500,500),_n(),Mn(),Sn(),await En(),Gn(),Rn(),bn=!0}function _n(){Et=parseInt(oe),randomM Seed(Et),noiseSeed(Et)}function Mn(){Wt=Ir(p.training_traits),Cr(Wt)}async function En(){let e;Jt=r(),Qt=o(),[Xt,e]=await Promise.all([s(Jt),h(Qt)]),Ut=new V(Wt.visual,e.layers_config,e.weight_b64),Ut.updateAge(new Date),_n(),Wt.training=e.training_traits,Ht=e.model_name,$t=e.classes_name}function Sn(){le=min(width,height)/1024,ut=Rr.findIndex((e=>e[0]===Wt.visual.colorPalette)),ft=[["#ffffff","#231f20","#231f20"],["#231f20","#ffffff","#ffffff"],["#104da8","#ffffff","#ffffff"],["#722F1F","#FCE1B2","#FCE1B2"],["#e88M 120","#f9f2e5","#f9f2e5"],["#f6b941","#2E2E2E","#2E2E2E"],["#45daaa","#012221","#012221"],["#F1F1F1","#328DFE","#328DFE"],["#111822","#D3EB8D","#D3EB8D"],["#713FF9","#D6D5E6","#D6D5E6"],["#FBDA9D","#795106","#795106"],["#8f5b62","#ead0d0","#ead0d0"],["#eae4cb","#508cac","#508cac"],["#ffc6cc","#cc313d","#cc313d"],["#60A900","#E0FE00","#E0FE00"],["#507DBE","#D0D1D3","#D0D1D3"],["#305848","#E8F2EE","#E8F2EE"],["#2a2634","#5b6988","#cb78a2","#5b6988"],["#590e29","#fd5e53","#fd5e53","#ffe373"],["#0a141d","#57d4e4","#328M 195","#2A9ECF","#0ab6a8","#57d4e4"],["#3a2d28","#d5c2ac","#df6338","#3d9895","#d5c2ac"],["#030706","#77c4d9","#77c4d9","#77c4d9","#ffffff","#ffffff","#e72020","#e72020"],["#3a4664","#92f5ff","#f9ff94","#eaa0a2","#55dde0"],["#fbfaff","#f04bb1","#f04bb1","#fac373","#82cef0","#8b31ce"],["#000000","#ffffff","#ff0002","#f26522","#fdff00","#00ff03","#01fffe","#0000ff","#ff00ff"]];for(let e=0;e<ft.length;++e)for(let t=0;t<ft[e].length;++t)ft[e][t]=cr(ft[e][t]);pt=[],ct=ft[ut][0],st=ft[ut][1]}function Rn(){gn=document.querM ySelector("#upload"),pn=document.querySelector("#inputUpload"),gn.addEventListener("dblclick",(()=>{if(!Lt&&!yn)if(In(Ie)&&cn==Ve-1)pn.click();else{if(4!=Pe&&5!=Pe&&(In(Ie)||cn!=Ve-1))return;fn=!0,dn=!0,Bt=0,un=0}})),pn.addEventListener("click",(()=>{pn.value=null,gn.style.display="block"})),pn.addEventListener("change",(()=>{const[e]=pn.files;e?(se=null,gn.style.display="none",Tn(URL.createObjectURL(e)),mn=e):gn.style.display="block"}))}function In(e){for(let t=0;t<e.length;++t){let n=0;for(let r=0;r<e[t].length;+M +r)e[t][r]>0&&++n;if(0==n)return!1}return!0}function Cn(){null!=se&&(un=0,Pt=!0,he=0,ue=0,drewLineAnim=!0,ce=(ae/2+we/2)/le,loadImage(se.elt.src,(e=>{const[t,n,r]=Gt,i=createGraphics(t,n);i.image(e,0,0,t,n),i.loadPixels();const o=i.pixels.filter(((e,t)=>t%4!=3)),a=Ut.classifyImage(o);Zt=T([a,$t.map((e=>e.toUpperCase()))]).sort(((e,t)=>e[0]>t[0]?-1:1))})))}function Tn(e){se=createImg(e,""),se.hide(),Cn()}function An(){zn||(ce+=(width-ae-we)/tn/le),re(Xe),Xe.rect(ce*le,0,width,height),ie(Xe),un>=ge&&1==kt&&(kt=!1,un-M =ge),kt&&(re($e),$e.strokeWeight(2*Fe),Jn(he,ze,ct,ct,$e),ie($e)),un>=ge&&0==kt&&(kt=!0,un-=ge,he+=1,he==en&&(++ue,he=0,ce=(ae/2+we/2)/le,1==ue&&(Pt=!1,Dn(),ye=millis())))}function Dn(){At=!0,pe=!1,me=!1,tryButton=br("Try Again",width/2-225*le,height/2+265*le,290*le,40*le,kn),closeResultButton=br("Close",width/2+75*le,height/2+265*le,150*le,40*le,Ln)}function kn(){At=!1,tryButton.hide(),closeResultButton.hide(),pn.click()}function Ln(){Yt=!0,At=!1,Gn(),tryButton.hide(),closeResultButton.hide(),gn.style.display="bloM ck",se=null}function keyTyped(){bn&&!1===yn&&!1===yr()&&("i"!==key&&"I"!==key||(Dt=!Dt),"b"!==key&&"B"!==key||(xn=!xn),"s"!==key&&"S"!==key||!1!==Lt||saveCanvasAtCurrentTime(),"k"!==key&&"K"!==key||!1!==Lt||save4KCanvasAtCurrentTime(),"u"!==key&&"U"!==key||!1!==Lt||!1!==At||!1!==fn||!1!==Pt||On())}function On(){Lt=!0,wn=null,vn=null,submitButton=br("Submit",width/2-155*le,height/2+115*le,150*le,40*le,Fn),closeSettingButton=br("Close",width/2+5*le,height/2+115*le,150*le,40*le,Yn),vt=createInput(),vt.position(width/2M -252.5*le,height/2-40*le),vt.size(500*le,25*le),vt.style("font-size","15px"),vt.value(Jt||""),zt=createInput(),zt.position(width/2-252.2*le,height/2+35*le),zt.size(500*le,25*le),zt.style("font-size","15px"),zt.value(Qt||"")}function Fn(){Vt=vt.value(),_t=zt.value(),submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide(),Lt=!1,yn=!0,Nn()}async function Nn(){[wn,vn,_]=await Promise.all([c(Vt),u(_t),O(1e3)]),yn=!1,wn&&vn?(n(Vt),i(_t),window.location.reload()):(Lt=!0,submitButton.show(),closeSettingButton.shoM w(),vt.show(),zt.show())}function Bn(){Je.textFont("Trebuchet MS"),Je.noStroke(),pr(Je,600*le,200*le),Je.strokeWeight(1*le),Je.stroke(xt),Je.fill(xt),Je.textSize(50*le),Je.text("update()",width/2,height/2+2.5*le)}function Yn(){wn=null,vn=null,Lt=!1,submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide()}function Gn(){_n(),nn=Date.now(),pe=!1,me=!1,St=Wt.training.structure_gen,Rt=Wt.visual.birthYear,It=Wt.visual.lifeCycle,Ct=Wt.training.epoch_num,Tt=Wt.training.activation_func,Ft=Mr.findIndex((e=>e[0]==Wt.M visual.hardwareAcceleration))+1,1==Ft?(Nt=30,fe=40):2==Ft?(Nt=15,fe=20):(Nt=2,fe=10);const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$tM ),ae=100*le,ht=50*le,Oe=Sr.findIndex((e=>e[0]==Wt.visual.nodeShape))+1,dt=Er.findIndex((e=>e[0]==Wt.visual.nodeFill))+1,lt=_r.findIndex((e=>e[0]==Wt.visual.pattern))+1,de=Math.tanh(Math.log10(Xt.avgfeerate)),de=map(de,0,1,.2,.8),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e]M .length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,weM =(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,at=.7,pt=[],xt=ft[ut][2],gt=ft[ut][ft[utM ].length-1];for(let e=3;e<ft[ut].length-1;e++)pt.push(ft[ut][e]);mt=sr(xt,gt,pt,width),bt=[],wt=[],yt=width/(Ve-1);for(let e=0;e<Ve;e++)bt.push(hr(mt,yt*e/width)),wt.push(hr(mt,yt*e/width));wt.unshift(bt[0]),wt.push(bt[bt.length-1]),hn=0,cn=0,un=0,Yt=!0;const n={xLeft:ae/8,xRight:width-ae/8,yTop:ae/8,yBottom:height-ae/8},r=Ce.map((e=>e.length));jt=new R(bt,r,n,Oe,le)}function Hn(e,t){let n=Ce[e].length;return[e*we+we/2+ae/2,height/2-(n-1)/2*ve+t*ve]}function $n(e,t){le=min(e,t)/1024,ae=100*le,ht=50*le,we=(e-ae)/Ve,M ve=(t-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}xe=floor(De.length*de),Le=[],ke=[],ge=floor(map(de,.2,.8,15,2));for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,mt=sr(xt,gt,pt,e),bt=[],wt=[],yt=e/(Ve-1);for(let t=0;t<Ve;t++)bt.push(hr(mt,yt*t/e)),wt.push(hr(mt,yt*t/e))M ;wt.unshift(bt[0]),wt.push(bt[bt.length-1])}function Xn(){const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),inputNodes=1,Ye=1,Ge=[],HM e=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshM ift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xM e=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le}function Wn(){jt.update();const e=4==Pe?0:Kt;jt.draw(Qe,ct,dt,e,le)}function Un(){if(!bn)return ar(),void et.image(je,0,0);if(4==Pe||5==Pe)return Wn(),void et.image(Qe,0,0);un>=Nt&&hn<Ve&&(hn++,un=0);for(let e=0;e<hn;e++)1==dt?it=ot=bt[e]:(it=ct,ot=bt[e]),Kn(e,it,ot,$e);un>=Nt&&cn<Ve-1&&(cn++,M un=0);for(let e=0;e<cn;e++)Zn(e)}function qn(){et.background(ct),Ue.background(255),Ue.rectMode(CENTER),ne(Ue),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),Ue.stroke(st),Ue.strokeWeight(8*le),Ue.fill(ct),Qe.background(255),Qe.rectMode(CENTER),ne(Qe),Qe.strokeWeight(le),qe.background(255),qe.rectMode(CENTER),ne(qe),qe.textAlign(LEFT),$e.background(255),$e.rectMode(CENTER),ne($e),Xe.background(255),ne(Xe),Xe.strokeWeight(Ne),We.background(255),We.rectMode(CENTER),ne(We),We.fill(st),We.stroke(st),We.strokeWeight(.1*M le),er(lt),We.noStroke(),xn&&(We.rect(ae/16,height/2,ae/8,height),We.rect(width-ae/16,height/2,ae/8,height),We.rect(width/2,ae/16,width,ae/8),We.rect(width/2,height-ae/16,width,ae/8)),Ze.background(255),Ze.rectMode(CENTER),ne(Ze),Ze.textAlign(CENTER,CENTER),Ze.textStyle(BOLD),Ze.stroke(st),Ze.strokeWeight(8*le),Ze.fill(ct),je.background(255),je.rectMode(CENTER),ne(je),je.textAlign(CENTER,CENTER),je.textStyle(BOLD),Ke.background(255),Ke.rectMode(CENTER),ne(Ke),Ke.textAlign(CENTER,CENTER),Ke.textStyle(BOLD),Ke.strokeM (st),Ke.strokeWeight(8*le),Ke.fill(ct),Je.background(255),Je.rectMode(CENTER),ne(Je),Je.textAlign(CENTER,CENTER),Je.textStyle(BOLD),Je.stroke(st),Je.strokeWeight(8*le),Je.fill(ct),Un(),et.image(We,0,0),Pt&&An(),et.image(Xe,0,0),et.image($e,0,0),At&&(tr(),et.image(Ue,0,0)),fn&&(lr(),et.image(Ze,0,0)),Lt&&(or(),et.image(Ke,0,0)),Dt&&(ir(),et.image(qe,0,0)),yn&&(Bn(),et.image(Je,0,0))}function draw(){const e=Date.now();bn&&(Ut.updateAge(new Date(e)),Xn()),qn(),image(et,0,0),zn||un++}function Zn(e){let t,n=Ce[e].lengthM ,r=Ce[e+1].length;for(let i=0;i<n;i++){const[n,o]=Hn(e,i);for(let a=0;a<r;a++){const[r,l]=Hn(e+1,a);t=map(min(Ce[e][i],Ce[e+1][a]),0,1,0,.5),ur(n,o,r,l,bt[e],bt[e+1],Xe,t)}}}function Kn(e,t,n,r){let i,o,a,l=Ce[e].length;for(let s=0;s<l;s++){const[l,h]=Hn(e,s);i=Ce[e][s],a=map(Be,1/30,1,3,10),o=map(Ce[e][s],0,1,2*a,0)*le,o<1.5*le&&(o=0),Qn(l,h,ze,Oe,t,n,o,i,r)}}function Jn(e,t,n,r,i){for(let o=0;o<Le[e].length;o++)Qn(Le[e][o][0],Le[e][o][1],t,Oe,n,r,0,1,i)}function Qn(e,t,n,r,i,o,a,l,s){s.stroke(dr(o,map(l,0,1,.25,1M ))),s.fill(dr(i,map(l,0,1,.15,1))),s.strokeWeight(Fe),fr([a],s),3==dt&&s.fill(dr(i,0)),1==r?s.ellipse(e,t,n):2==r?s.rect(e,t,7*n/8,7*n/8):3==r&&(s.beginShape(),s.vertex(e-4*n/7,t),s.vertex(e,t-4*n/7),s.vertex(e+4*n/7,t),s.vertex(e,t+4*n/7),s.endShape(CLOSE))}function er(e){if(1==e);else if(2==e){We.strokeWeight(1*le);for(let e=ht/4;e<width+ht/4;e+=ht)for(let t=ht/4;t<height+ht/4;t+=ht)We.point(e,t)}else if(3==e){ht=25*le;for(let e=ht/2;e<height+ht/2;e+=ht)We.line(0,e,width,e);for(let e=ht/2;e<width+ht/2;e+=ht)We.liM ne(e,0,e,height)}}function tr(){Ue.textFont("Trebuchet MS"),Ue.textAlign(LEFT,CENTER),Ue.noStroke(),pr(Ue,800*le,500*le),Ue.noStroke(),Ue.fill(dr(st,.75)),Ue.rect(width/2,height/2-100*le,800*le,300*le,25*le,25*le,0,0),Ue.fill(st),Ue.rect(width/2-250*le,height/2-100*le,225*le,225*le),Ue.image(se.elt,width/2-357.5*le,height/2-207.5*le,215*le,215*le);let e=100*Zt[0][0];Ue.fill(ct),Ue.textSize(25*le),Ue.textStyle(NORMAL),1==me&&(e>=0&&e<20?Ue.text("I have a feeling this image belongs to",width/2-100*le,height/2-170*le)M :e>=20&&e<40?Ue.text("I have a hunch this image belongs to",width/2-100*le,height/2-170*le):e>=40&&e<60?Ue.text("I think this image belongs to",width/2-100*le,height/2-170*le):e>=60&&e<80?Ue.text("I'm almost certain this image belongs to",width/2-100*le,height/2-170*le):Ue.text("I'm positive this image belongs to",width/2-100*le,height/2-170*le));let t=e.toFixed(2);"100.00"==t&&(t="100"),1==me&&Ue.text("I'm "+t+"% confident that I'm right!",width/2-100*le,height/2-25*le),example=Zt.map((e=>e[1])),be=Ue.textWidth('"M FIDENZAAAA"'),defaultPhrase=Ue.textWidth('"PERPENDICULAR INHABITATION"'),Ue.textStyle(BOLD);const n=me?example[0]:random(example);if(1===n.split(" ").length){let e=75*be/Ue.textWidth('"'+n+'"');e>75&&(e=75),Ue.textSize(e*le),Ue.text('"'+n+'"',width/2-100*le,height/2-90*le)}else nr(width/2-100*le,height/2-90*le,460*le,110*le,n,Ue);if(millis()-ye>1500&&(me=!0),C(tt,nt,st,ct,Pe,Mt),Ue.image(nt,width/2-370*le,height/2+70*le,80*le,80*le),3==Pe){let e;e=map(Mt,50,60,.25,1.3),I(rt,e),Ue.image(rt,width/2-370*le,height/2+70M *le,80*le,80*le)}let r,i;Ue.image(tt,width/2-370*le,height/2+70*le,80*le,80*le),Ue.fill(xt),Ue.textSize(40*le),Ue.text("INTELLIGENCE INFO",width/2-275*le,height/2+115*le),Ue.textSize(18*le),Ue.textStyle(NORMAL),Ue.circle(width/2-360*le,height/2+180*le,7.5*le),1==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s growing and getting smarter by the day.`:2==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s stable and it has reached peak performance.`:3==Pe&&(r=`Your Perceptron is ${Math.ceil(Mt)} yM s decaying and losing its luster.`),i=2==Pe?"The Perceptron remains stable for some time before entering the decay phase.":`Wait until ${new Date(an).toLocaleString("en-US")} for your Perceptron to reach its peak performance.`,Ue.text(r,width/2-350*le,height/2+180*le),Ue.circle(width/2-360*le,height/2+210*le,7.5*le),Ue.text(i,width/2-350*le,height/2+210*le),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),gr(Ue,width/2-225*le,width/2+65*le,height/2+265*le,height/2+305*le,"SELECT ANOTHER IMAGE"),gr(Ue,wM idth/2+75*le,width/2+225*le,height/2+265*le,height/2+305*le,"CLOSE")}function nr(e,t,n,r,i,o){let a=i.split(" "),l=75*be/o.textWidth('"'+i+'"'),s=0,h=[],c=[],u=[],f="",d="";if(l>=50)l>75&&(l=75),o.textSize(l*le),o.text('"'+i+'"',e,t);else if(l<50){if(l=50*defaultPhrase/o.textWidth('"'+i+'"'),l>30){if(l>50&&(l=50),[f,d]=rr(l,n,s,h,c,a,f,d,Ue),0==c.length)return o.textSize(l*le),void o.text('"'+i+'"',e,t);for(s=0,h=[],c=[];o.textWidth(d)>n/le;)l=l*n/le/o.textWidth(d),f="",d="",[f,d]=rr(l,n,s,h,c,a,f,d,Ue)}else{l=30,oM .textSize(l);for(let e=0;e<a.length;e++)s+=o.textWidth(" "+a[e]),s<=n/le?h.push(a[e]):s>n/le&&s<=n/le*2?c.push(a[e]):u.push(a[e]);for(let e=1;e<h.length;e++)f=f+" "+h[e];if(f='"'+h[0]+f,0==u.length){for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+c[c.length-1]+'"'}else if(1==c.length)d="... "+u[u.length-1]+'"';else{for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+"... "+u[u.length-1]+'"'}}o.textSize(l*le);let r=1.25*(o.textDescent()+o.textAscent());o.text(f,e,t-r/2),o.text(d,e,t+r/2)}}function rr(e,t,n,r,i,o,a,l,s){s.teM xtSize(e);for(let e=0;e<o.length;e++)(n+=s.textWidth(" "+o[e]))<=t/le?r.push(o[e]):i.push(o[e]);for(let e=1;e<r.length;e++)a=a+" "+r[e];if(a='"'+r[0]+a,0==i.length&&(a+='"',l=""),1==i.length)l=i[i.length-1]+'"';else{for(let e=0;e<i.length-1;e++)l=l+i[e]+" ";l=l+i[i.length-1]+'"'}return[a,l]}function ir(){const e=45*le;qe.textFont("Tahoma"),qe.stroke(st),qe.strokeWeight(2*le),qe.fill(ct),qe.rect(width/2,e/2+height-87.5*le,600*le,90*le),qe.fill(st),qe.rect(width/2-150*le,e+height-170*le,300*le,30*le),qe.fill(ct),qe.rM ect(width/2+150*le,e+height-170*le,300*le,30*le),qe.noStroke(),qe.fill(ct),qe.textSize(15*le),qe.textStyle(BOLD),qe.text("PERCEPTRON INFORMATION",width/2-285*le,e+height-165*le),qe.fill(xt),qe.text("ARTWORK NAME:",width/2+10*le,e+height-165*le),qe.textAlign(RIGHT),qe.textStyle(ITALIC),qe.text("Perceptron #"+Et,width/2+285*le,e+height-165*le);const[t,n]=It.split(" ");let r;"60 Years"===It?r="1 Year":"60 Months"===It?r="1 Month":"60 Weeks"===It?r="1 Week":"60 Days"===It?r="1 Day":"12 Hours"===It&&(r="12 Minutes"),datM a=[["AI MODEL NAME:",B(12*le,Ht,140*le)],["SCALE:","1:"+Te],["NUMBER OF CLASSES:",$t.length],["BIRTH YEAR:",Rt],["NUMBER OF REBIRTHS:",sn.toString()],["AGE:",`${Math.ceil(Mt)} Perceptron Years`],["ONE PERCEPTRON YEAR:",`${r}`],["STATE:",Ot[Pe]],["ACTIVE NEURONS:",`${round(ln*rn)} / ${ln}`],["NEXT STATE TIME:",vr(new Date(on))]],qe.fill(xt);const i=data.length/2;for(let t=0;t<data.length;++t){const n=t<i,r=n?width/2-285*le:width/2+10*le,o=n?width/2-10*le:width/2+285*le,a=e+height-(135-t%i*15)*le;qe.textStyle(BOLD),qM e.textAlign(LEFT),qe.textSize(12*le),qe.text(data[t][0],r,a),qe.textStyle(ITALIC),qe.textAlign(RIGHT),qe.textSize(12*le),qe.text(data[t][1],o,a)}}function or(){Ke.textFont("Trebuchet MS"),Ke.noStroke(),pr(Ke,600*le,200*le),gr(Ke,width/2-155*le,width/2-5*le,height/2+115*le,height/2+155*le,"UPDATE"),gr(Ke,width/2+5*le,width/2+155*le,height/2+115*le,height/2+155*le,"CLOSE"),Ke.textAlign(LEFT),Ke.fill(xt),Ke.text("UPDATE BITCOIN FULL NODE ADDRESS",width/2-252.5*le,height/2-55*le),Ke.text("UPDATE MODEL ADDRESS",width/2-M 252.5*le,height/2+20*le),Ke.textAlign(RIGHT),Ke.textStyle(ITALIC),Ke.textSize(15*le),0==wn&&Ke.text("(*) Invalid Address",width/2+252.5*le,height/2-53*le),0==vn&&Ke.text("(*) Invalid Model",width/2+252.5*le,height/2+23*le)}function ar(){je.textFont("Trebuchet MS"),je.fill(st),je.textSize(50*le),je.stroke(st),je.strokeWeight(1*le),je.text("main()",width/2,height/2)}function lr(){un>=20&&1==dn&&(dn=!1,un=0),dn&&(Ze.textFont("Trebuchet MS"),Ze.stroke(st),Ze.fill(ct),Ze.rect(width/2,height/2,600*le,150*le,25*le),Ze.filM l(xt),Ze.textSize(75*le),Ze.noStroke(),1==Pe?Ze.text("GROWING",width/2,height/2+5*le):3==Pe?Ze.text("AGING",width/2,height/2+5*le):4==Pe?Ze.text("DEAD",width/2,height/2+5*le):5==Pe&&Ze.text("BIRTH",width/2,height/2+5*le)),un>=20&&0==dn&&(dn=!0,un=0,Bt++,3==Bt&&(fn=!1))}function sr(e,t,n,r){let i=[],o=r/(n.length+1),a=color(e),l=color(t);i.push(a);for(let e=0;e<n.length;e++){let t=color(n[e]);for(let e=1;e<=o;e++){let n=lerpColor(a,t,e/o);i.push(n)}a=t}for(let e=1;e<o;e++){let t=lerpColor(a,l,e/o);i.push(t)}if(i.pusM h(l),i.length>r)i.splice(r);else if(i.length<r){let e=i[i.length-1];for(;i.length<r;)i.push(e)}return i}function hr(e,t){let n=e.length,r=Math.floor(t*n);return r>=n&&(r=n-1),e[r]}function cr(e){e=e.replace("#","");var t=parseInt(e,16);return color(t>>16&255,t>>8&255,255&t)}function ur(e,t,n,r,i,o,a,l){var s=a.drawingContext.createLinearGradient(e,t,n,r);s.addColorStop(0,i),s.addColorStop(1,o),a.drawingContext.strokeStyle=s,a.drawingContext.globalAlpha=l,a.line(e,t,n,r),a.drawingContext.globalAlpha=1}function fr(e,M t){t.drawingContext.setLineDash(e)}function dr(e,t){let n=color(e),r=red(n),i=green(n),o=blue(n);return color(r,i,o,255*t)}function xr(e,t,n,r){return mouseX>e&&mouseX<t&&mouseY>n&&mouseY<r}function gr(e,t,n,r,i,o){e.strokeWeight(1*le),e.stroke(st);const[a,l]=xr(t,n,r,i)?[xt,ct]:[ct,xt];e.fill(a),e.push(),e.rectMode(CORNERS),e.rect(t,r,n,i,5*le),e.pop(),e.noStroke(),e.textSize(20*le),e.fill(l),e.text(o,(t+n)/2,(46*r+54*i)/100)}function pr(e,t,n){e.fill(0,0,0,75),e.rect(width/2,height/2,width,height),e.stroke(st),e.M fill(ct),e.rect(width/2,height/2,t,n,25*le)}function mr(e,t){resizeCanvas(e,t,!0),Xe.resizeCanvas(e,t,!0),$e.resizeCanvas(e,t,!0),We.resizeCanvas(e,t,!0),Ue.resizeCanvas(e,t,!0),qe.resizeCanvas(e,t,!0),Qe.resizeCanvas(e,t,!0),je.resizeCanvas(e,t,!0),Ze.resizeCanvas(e,t,!0),Ke.resizeCanvas(e,t,!0),Je.resizeCanvas(e,t,!0),et.resizeCanvas(e,t,!0)}function br(e,t,n,r,i,o){const a=J(e);return a.position(t,n),a.size(r,i),a.style("opacity","0"),a.mouseClicked(o),a}function yr(){return null!=vt&&vt?.isFocused()||null!=zt&&M zt?.isFocused()}function wr(e,t,n,r){let i;if(e<=3){i=`Hey ${String.fromCodePoint(128075)}, I'm ${n}, ${t} years old. I can detect ${r.length} NFT collections: `;let e=0;for(let t=0;t<r.length;++t){const n=r[t];if(e+n.length>500){i+=", etc";break}t==r.length-1?i+=", and ":t>0&&(i+=", "),i+=n,e+=n.length}i+=". ",t<=5?i+="However, I am only a baby, so my recognition ability is not accurate. I'm in the state of Growing both looks and intelligence.":t<=13?i+="I am now a child. My recognition ability is becoming better,M but still not very accurate. I'm in the state of Growing both looks and intelligence.":t<=25?i+="I have grown up to be a teen. My recognition ability almost reaches the peak, but I will still mess up sometimes. I'm in the state of Growing both looks and intelligence.":t<=50?i+="I finally reach adulthood. My recognition is fully functional now. I'm in the Stable state, where I am the most intelligent with all neurons activated.":t<=60&&(i+="I am now an old Perceptron, so my recognition ability is no longer the bestM . I'm in the Decaying state, meaning that my neurons are dying, and my intelligence is decreasing over time.")}else 4==e?i=`${n} is Dead. However, this is not the end to its story...`:5==e&&(i=`${n} is now in the Rebirth state, and is preparing to start a new life.`);return i}function vr(e){const t=e.getDate(),n=e.toLocaleString("en-US",{month:"long"}),r=e.getFullYear();let i=e.getHours().toString();1==i.length&&(i="0"+i);let o=e.getMinutes().toString();return 1==o.length&&(o="0"+o),`${Y(t)} ${n} ${r} | ${i}:${o}`}M saveCanvasAtCurrentTime=()=>{save(N())},save4KCanvasAtCurrentTime=()=>{const e=width,t=height,n=min(4096/min(e,t),1e4/max(e,t)),r=e*n,i=t*n;mr(r,i),zn=!0,$n(r,i),qn();let o="4K_"+N()+".png";saveCanvas(et,o),mr(e,t),$n(e,t),zn=!1};const zr=[["60 Years",3,365],["60 Months",40,30],["60 Weeks",37,7],["60 Days",20,1]],Vr=[["1943",1],["1951",1.5],["1957",2],["1969",2.5],["1970",3],["1980",3.5],["1982",4],["1986",4.5],["1988",5],["1997",5.5],["1998",6],["2002",6.5],["2009",7],["2012",7.5],["2014",8],["2015",8.5],["2016",9M ],["2023",15]],_r=[["Plain",20],["Dotted",40],["Squared",40]],Mr=[["Basic",30],["Standard",60],["Advanced",10]],Er=[["MNIST",70],["CIFAR",25],["IMAGENET",5]],Sr=[["Theano",60],["Torch",30],["TensorFlow",10]],Rr=[["Whitepaper",2],["Blackboard",2],["Blueprint",2],["Nak",74/14],["Jims",74/14],["Level 10",74/14],["Flips",74/14],["Level 14",74/14],["III",74/14],["XMB",74/14],["Info",74/14],["Adventure",74/14],["Marigold",74/14],["Phoenix",74/14],["Love",74/14],["Cachet",74/14],["Human",74/14],["Twilight",3],["Sunset",3]M ,["Aurora",3],["Liminal Space",3],["D Vu",3],["Lucid Dream",3],["Parallel",1],["Multiverse",1]];function Ir(e){for(let e=0;e<100;++e)random(1);return{visual:{pattern:k(_r),hardwareAcceleration:k(Mr),nodeFill:k(Er),nodeShape:k(Sr),colorPalette:k(Rr),lifeCycle:k(zr),birthYear:k(Vr)},training:e}}function Cr(e){window.$generativeTraits={"Network Architecture":e.training.structure_gen,"Hidden Layers":e.training.n_layers,"Max Neurons Per Hidden Layer":e.training.max_nodes,"Activation Function":e.training.activation_M func,"Training Epochs":e.training.epoch_num,Dataset:e.visual.nodeFill,"Deep Learning Framework":e.visual.nodeShape,"Hardware Acceleration":e.visual.hardwareAcceleration,"Paper Pattern":e.visual.pattern,"Life Cycle":e.visual.lifeCycle,"Birth Year":e.visual.birthYear,"Color Palette":e.visual.colorPalette}} <script defer src="https://static.cloudflareinsights.com/beacon.min.js/v2b4487d741ca48dcbadcaf954e159fc61680799950996" integrity="sha512-D/jdE0CypeVxFadTejKGTzmwyV10c1pxZk/AqjJuZbaJwGMyNHY3q/mTPWqMUL nFACfCTunhZUVcd4cV78dK1pQ==" data-cf-beacon='{"rayId":"7b4cfa4afbd23ffe","version":"2023.3.0","b":1,"token":"6c07c178c94442f695e7a0a2aaee641a","si":100}' crossorigin="anonymous"></script> text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"JEUS","amt":"777"}h! text/plain;charset=utf-8 ({"p":"sns","op":"reg","name":" XMP DataXMP<?xpacket begin=" " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 7.1-c000 79.ccf84e0, 2022/06/22-22:13:26 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:xmpMM="http://ns.adobe.com/xap/1.0/mm/" xmlns:stRef="http://ns.adobe.com/xap/1.0/sType/ResourceRef#" xmp:CreatorTool="Adobe Photoshop 22.5 (Windows)" xmpMM:InstaM nceID="xmp.iid:8A436FBDD62811EDA842EE613FD35091" xmpMM:DocumentID="xmp.did:8A436FBED62811EDA842EE613FD35091"> <xmpMM:DerivedFrom stRef:instanceID="xmp.iid:8A436FBBD62811EDA842EE613FD35091" stRef:documentID="xmp.did:8A436FBCD62811EDA842EE613FD35091"/> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> ~}|{zyxwvutsrqponmlkjihgfedcba`_^]\[ZYXWVUTSRQPONMLKJIHGFEDCBA@?>=<;:98765432M XMP DataXMP<?xpacket begin=" " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 7.1-c000 79.ccf84e0, 2022/06/22-22:13:26 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:xmpMM="http://ns.adobe.com/xap/1.0/mm/" xmlns:stRef="http://ns.adobe.com/xap/1.0/sType/ResourceRef#" xmp:CreatorTool="Adobe Photoshop 22.5 (Windows)" xmpMM:InstaM nceID="xmp.iid:2EE4938AD62911EDB10EC2EBFE3F1043" xmpMM:DocumentID="xmp.did:2EE4938BD62911EDB10EC2EBFE3F1043"> <xmpMM:DerivedFrom stRef:instanceID="xmp.iid:2EE49388D62911EDB10EC2EBFE3F1043" stRef:documentID="xmp.did:2EE49389D62911EDB10EC2EBFE3F1043"/> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> ~}|{zyxwvutsrqponmlkjihgfedcba`_^]\[ZYXWVUTSRQPONMLKJIHGFEDCBA@?>=<;:98765432M XMP DataXMP<?xpacket begin=" " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 7.1-c000 79.ccf84e0, 2022/06/22-22:13:26 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:xmpMM="http://ns.adobe.com/xap/1.0/mm/" xmlns:stRef="http://ns.adobe.com/xap/1.0/sType/ResourceRef#" xmp:CreatorTool="Adobe Photoshop 22.5 (Windows)" xmpMM:InstaM nceID="xmp.iid:69330EEBD62911EDAF0ADCF7F2CE998D" xmpMM:DocumentID="xmp.did:69330EECD62911EDAF0ADCF7F2CE998D"> <xmpMM:DerivedFrom stRef:instanceID="xmp.iid:69330EE9D62911EDAF0ADCF7F2CE998D" stRef:documentID="xmp.did:69330EEAD62911EDAF0ADCF7F2CE998D"/> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> ~}|{zyxwvutsrqponmlkjihgfedcba`_^]\[ZYXWVUTSRQPONMLKJIHGFEDCBA@?>=<;:98765432M 2iTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 9.0-c000 137.da4a7e5, 2022/11/27-09:35:03 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:photoshop="http://ns.adobe.com/photoshop/1.0/" xmlns:xmpMM="http://ns.adobe.com/xapM /1.0/mm/" xmlns:stEvt="http://ns.adobe.com/xap/1.0/sType/ResourceEvent#" xmp:CreatorTool="Adobe Photoshop 24.1 (Windows)" xmp:CreateDate="2023-03-06T09:50:00-05:00" xmp:ModifyDate="2023-03-06T10:05:43-05:00" xmp:MetadataDate="2023-03-06T10:05:43-05:00" dc:format="image/png" photoshop:ColorMode="3" xmpMM:InstanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" xmpMM:DocumentID="adobe:docid:photoshop:a9980e5d-12d4-6e4f-ae17-4020b81aaaa9" xmpMM:OriginalDocumentID="xmp.did:8b05b474-2032-014c-baeb-d7f687c78db6"> <xmpMMM :History> <rdf:Seq> <rdf:li stEvt:action="created" stEvt:instanceID="xmp.iid:8b05b474-2032-014c-baeb-d7f687c78db6" stEvt:when="2023-03-06T09:50:00-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)"/> <rdf:li stEvt:action="converted" stEvt:parameters="from application/vnd.adobe.photoshop to image/png"/> <rdf:li stEvt:action="saved" stEvt:instanceID="xmp.iid:e45fe10d-f897-3f47-8e30-1b65931ac15c" stEvt:when="2023-03-06T10:05:43-05:00" stEvt:softwareAgent="Adobe Photoshop 24.1 (Windows)" stEvt:changed="/"/> </M rdf:Seq> </xmpMM:History> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> text/html;charset=utf-8 <meta charset="utf-8" /> position: relative; width: var(--width); height: var(--height); border: 1px solid blue; position: relative; <div id="upload"> <input id="inputUpload" type="file"> function e(e){"use strict";return new function e(t){let n="global"==t?window:this;n.canvas=document.createElement("canvas");let r=n.canvas.getContext("2d");n.width=100,n.height=100,n.canvas.width=n.width,n.canvas.height=n.height,"offscreen"!=t&&(document.body?document.body.appendChild(n.canvas):window.addEventListener("load",(function(){document.body.appendChild(n.canvas)}))),g(),n.MAGIC=161533525,n.RGB=0,n.HSV=1,n.HM SB=1,n.CHORD=0,n.PIE=1,n.OPEN=2,n.RADIUS=1,n.CORNER=2,n.CORNERS=3,n.ROUND="round",n.SQUARE="butt",n.PROJECT="square",n.MITER="miter",n.BEVEL="bevel",n.CLOSE=1,n.BLEND="source-over",n.REMOVE="destination-out",n.ADD="lighter",n.DARKEST="darken",n.LIGHTEST="lighten",n.DIFFERENCE="difference",n.SUBTRACT="subtract",n.EXCLUSION="exclusion",n.MULTIPLY="multiply",n.SCREEN="screen",n.REPLACE="copy",n.OVERLAY="overlay",n.HARD_LIGHT="hard-light",n.SOFT_LIGHT="soft-light",n.DODGE="color-dodge",n.BURN="color-burn",n.NORMAL="norM mal",n.ITALIC="italic",n.BOLD="bold",n.BOLDITALIC="italic bold",n.CENTER="center",n.LEFT="left",n.RIGHT="right",n.TOP="top",n.BOTTOM="bottom",n.BASELINE="alphabetic",n.LANDSCAPE="landscape",n.PORTRAIT="portrait",n.ALT=18,n.BACKSPACE=8,n.CONTROL=17,n.DELETE=46,n.DOWN_ARROW=40,n.ENTER=13,n.ESCAPE=27,n.LEFT_ARROW=37,n.OPTION=18,n.RETURN=13,n.RIGHT_ARROW=39,n.SHIFT=16,n.TAB=9,n.UP_ARROW=38,n.HALF_PI=Math.PI/2,n.PI=Math.PI,n.QUARTER_PI=Math.PI/4,n.TAU=2*Math.PI,n.TWO_PI=2*Math.PI,n.THRESHOLD=1,n.GRAY=2,n.OPAQUE=3,n.INVEM RT=4,n.POSTERIZE=5,n.DILATE=6,n.ERODE=7,n.BLUR=8,n.ARROW="default",n.CROSS="crosshair",n.HAND="pointer",n.MOVE="move",n.TEXT="text",n.VIDEO={video:!0,audio:!1},n.AUDIO={video:!1,audio:!0},n.SHR3=1,n.LCG=2,n.HARDWARE_FILTERS=!0,n.hint=function(e,t){n[e]=t},n.frameCount=0,n.mouseX=0,n.mouseY=0,n.pmouseX=0,n.pmouseY=0,n.mouseButton=null,n.keyIsPressed=!1,n.mouseIsPressed=!1,n.key=null,n.keyCode=null,n.pixels=null,n.accelerationX=0,n.accelerationY=0,n.accelerationZ=0,n.rotationX=0,n.rotationY=0,n.rotationZ=0,n.relRotatM ionX=0,n.relRotationY=0,n.relRotationZ=0,n.pAccelerationX=0,n.pAccelerationY=0,n.pAccelerationZ=0,n.pRotationX=0,n.pRotationY=0,n.pRotationZ=0,n.pRelRotationX=0,n.pRelRotationY=0,n.pRelRotationZ=0,n.touches=[],n._styleCache=[{colorMode:n.RGB,noStroke:!1,noFill:!1,ellipseMode:n.CENTER,rectMode:n.CORNER,curveDetail:20,curveAlpha:0,textFont:"sans-serif",textSize:12,textLeading:12,textStyle:"normal"}],n._style=n._styleCache[n._styleCache.length-1],n._noLoop=!1,n._pixelDensity=1,n._frameRate=null,n._tint=null;let i=nullM ,o=!0,a=[],l=null,s=0,h={},c=0,u=null,f=null,d=null;Object.defineProperty(n,"deviceOrientation",{get:function(){return 90==Math.abs(window.orientation)?n.LANDSCAPE:n.PORTRAIT}}),Object.defineProperty(n,"windowWidth",{get:function(){return window.innerWidth}}),Object.defineProperty(n,"windowHeight",{get:function(){return window.innerHeight}}),Object.defineProperty(n,"drawingContext",{get:function(){return r}}),n.createCanvas=function(e,t){return n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t,g(),n.canvas},nM .resizeCanvas=function(e,t){n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t},n.createGraphics=n.createImage=function(t,n){let r=new e("offscreen");return r.createCanvas(t,n),r.noLoop(),r},n.pixelDensity=function(e){return null==e||(n._pixelDensity=e,n.canvas.width=Math.ceil(n.width*e),n.canvas.height=Math.ceil(n.height*e),n.canvas.style.width=n.width+"px",n.canvas.style.height=n.height+"px",r.scale(n._pixelDensity,n._pixelDensity),g()),n._pixelDensity},n.map=function(e,t,n,r,i,o){let a=r+1*(e-t)/(n-t)*(i-r)M ;return o?r<i?Math.min(Math.max(a,r),i):Math.min(Math.max(a,i),r):a},n.lerp=function(e,t,n){return e*(1-n)+t*n},n.constrain=function(e,t,n){return Math.min(Math.max(e,t),n)},n.dist=function(){return 4==arguments.length?Math.hypot(arguments[0]-arguments[2],arguments[1]-arguments[3]):Math.hypot(arguments[0]-arguments[3],arguments[1]-arguments[4],arguments[2]-arguments[5])},n.norm=function(e,t,r){return n.map(e,t,r,0,1)},n.sq=function(e){return e*e},n.fract=function(e){return e-Math.floor(e)},n.degrees=function(e){retM urn 180*e/Math.PI},n.radians=function(e){return e*Math.PI/180},n.abs=Math.abs,n.ceil=Math.ceil,n.exp=Math.exp,n.floor=Math.floor,n.log=Math.log,n.mag=Math.hypot,n.max=Math.max,n.min=Math.min,n.round=Math.round,n.sqrt=Math.sqrt,n.sin=Math.sin,n.cos=Math.cos,n.tan=Math.tan,n.asin=Math.asin,n.acos=Math.acos,n.atan=Math.atan,n.atan2=Math.atan2,n.Vector=function(e,t,r){let i=this;i.x=e||0,i.y=t||0,i.z=r||0;let o=null,a=null;function l(e,t,n){return null!=e.x?e:null!=t?{x:e,y:t,z:n||0}:{x:e,y:e,z:e}}function s(){null==a&M &(a=i.x*i.x+i.y*i.y+i.z*i.z,o=Math.sqrt(a))}function h(){a=null,o=null}i.set=function(e,t,n){i.x=e||0,i.y=t||0,i.z=n||0},i.copy=function(){return new n.Vector(i.x,i.y,i.z)},i.add=function(){let e=l.apply(null,arguments);return i.x+=e.x,i.y+=e.y,i.z+=e.z,h(),i},i.rem=function(){let e=l.apply(null,arguments);return i.x%=e.x,i.y%=e.y,i.z%=e.z,h(),i},i.sub=function(){let e=l.apply(null,arguments);return i.x-=e.x,i.y-=e.y,i.z-=e.z,h(),i},i.mult=function(){let e=l.apply(null,arguments);return i.x*=e.x,i.y*=e.y,i.z*=e.z,hM (),i},i.div=function(){let e=l.apply(null,arguments);return i.x/=e.x,i.y/=e.y,i.z/=e.z,h(),i},i.mag=function(){return s(),o},i.magSq=function(){return s(),a},i.dot=function(){let e=l.apply(null,arguments);return i.x*e.x+i.y*e.y+i.z*e.z},i.dist=function(){let e=l.apply(null,arguments),t=i.x-e.x,n=i.y-e.y,r=i.z-e.z;return Math.sqrt(t*t+n*n+r*r)},i.cross=function(){let e=l.apply(null,arguments),t=i.y*e.z-i.z*e.y,n=i.z*e.x-i.x*e.z,r=i.x*e.y-i.y*e.x;return i.x=t,i.y=n,i.z=r,h(),i},i.normalize=function(){s();let e=o;retuM rn i.x/=e,i.y/=e,i.z/=e,o=1,a=1,i},i.limit=function(e){s();if(o>e){let t=e/o;i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e}return i},i.setMag=function(e){s();let t=e/o;return i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e,i},i.heading=function(){return Math.atan2(i.y,i.x)},i.rotate=function(e){let t=Math.cos(e),n=Math.sin(e),r=i.x*t-i.y*n,o=i.x*n+i.y*t;return i.x=r,i.y=o,i},i.angleBetween=function(){let e=l.apply(null,arguments);const t=i.dot(e)/(i.mag()*e.mag());let n;return n=Math.acos(Math.min(1,Math.max(-1,t))),n*Math.sign(i.cross(e).z||1)},M i.lerp=function(e,t){return i.x=i.x*(1-t)+e.x*t,i.y=i.y*(1-t)+e.y*t,i.z=i.z*(1-t)+e.z*t,h(),i},i.reflect=function(e){return e.normalize(),i.sub(e.mult(2*i.dot(e)))},i.array=function(){return[i.x,i.y,i.z]},i.equals=function(e,t){return null==t&&null==(t=Number.EPSILON)&&(t=0),Math.abs(e.x-i.x)<t&&Math.abs(e.y-i.y)<t&&Math.abs(e.z-i.z)<t},i.fromAngle=function(e,t){return null==t&&(t=1),o=t,a=t*t,i.x=t*Math.cos(e),i.y=t*Math.sin(e),i.z=0,i},i.fromAngles=function(e,t,n){null==n&&(n=1),o=n,a=n*n;const r=Math.cos(t),l=MaM th.sin(t),s=Math.cos(e),h=Math.sin(e);return i.x=n*h*l,i.y=-n*s,i.z=n*h*r,i},i.random2D=function(){return o=1,a=1,i.fromAngle(Math.random()*Math.PI*2)},i.random3D=function(){return o=1,a=1,i.fromAngles(Math.random()*Math.PI*2,Math.random()*Math.PI*2)},i.toString=function(){return`[${i.x}, ${i.y}, ${i.z}]`}},n.Vector.add=function(e,t){return new n.Vector(e.x+t.x,e.y+t.y,e.z+t.z)},n.Vector.rem=function(e,t){return new n.Vector(e.x%t.x,e.y%t.y,e.z%t.z)},n.Vector.sub=function(e,t){return new n.Vector(e.x-t.x,e.y-t.y,e.M z-t.z)},n.Vector.mult=function(e,t){return null==t.x?new n.Vector(e.x*t,e.y*t,e.z*t):new n.Vector(e.x*t.x,e.y*t.y,e.z*t.z)},n.Vector.div=function(e,t){return null==t.x?new n.Vector(e.x/t,e.y/t,e.z/t):new n.Vector(e.x/t.x,e.y/t.y,e.z/t.z)},n.Vector.dist=function(e,t){return Math.hypot(e.x-t.x,e.y-t.y,e.z-t.z)},n.Vector.cross=function(e,t){return new n.Vector(e.y*t.z-e.z*t.y,e.z*t.x-e.x*t.z,e.x*t.y-e.y*t.x)},n.Vector.lerp=function(e,t,r){return new n.Vector(e.x*(1-r)+t.x*r,e.y=e.y*(1-r)+t.y*r,e.z=e.z*(1-r)+t.z*r)},n.M Vector.equals=function(e,t,n){return e.equals(t,n)};for(let e of["fromAngle","fromAngles","random2D","random3D"])n.Vector[e]=function(t,r,i){return(new n.Vector)[e](t,r,i)};function x(e,t,n){let r,i,o,a,l,s,h,c,u;if(0==t)return[255*(r=n),255*(i=n),255*(o=n)];switch((a=e)>360&&(a=0),h=n*(1-t),c=n*(1-t*(s=(a/=60)-(l=~~a))),u=n*(1-t*(1-s)),l){case 0:r=n,i=u,o=h;break;case 1:r=c,i=n,o=h;break;case 2:r=h,i=n,o=u;break;case 3:r=h,i=c,o=n;break;case 4:r=u,i=h,o=n;break;default:r=n,i=h,o=c}return[255*r,255*i,255*o]}functioM n g(){r.fillStyle="white",r.strokeStyle="black",r.lineCap="round",r.lineJoin="miter"}function p(e){if(0<=e&&e<2*Math.PI)return e;for(;e<0;)e+=2*Math.PI;for(;e>=Math.PI;)e-=2*Math.PI;return e}function m(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;let c=p(a),u=p(l);r.beginPath();for(let a=0;a<h+1;a++){let l=a/h,s=n.lerp(c,u,l),f=Math.cos(s)*i/2,d=Math.sin(s)*o/2;r[a?"lineTo":"moveTo"](e+f,t+d)}s==n.CHORD?r.closePath():s==n.PIE&&(r.lineTo(e,t),r.closePath()),n._style.noFill||r.fill(),n._style.noStrokM e||r.stroke()}function b(e,t,i,o){n._style.noFill&&n._style.noStroke||(r.beginPath(),r.ellipse(e,t,i/2,o/2,0,0,2*Math.PI),n._style.noFill||r.fill(),n._style.noStroke||r.stroke())}function y(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;if(null==a)return function(e,t,i,o){n._style.noFill||r.fillRect(e,t,i,o),n._style.noStroke||r.strokeRect(e,t,i,o)}(e,t,i,o);if(null==l)return y(e,t,i,o,a,a,a,a);const c=Math.min(Math.abs(o),Math.abs(i))/2;a=Math.min(c,a),l=Math.min(c,l),h=Math.min(c,h),s=Math.min(c,s)M ,r.beginPath(),r.moveTo(e+a,t),r.arcTo(e+i,t,e+i,t+o,l),r.arcTo(e+i,t+o,e,t+o,s),r.arcTo(e,t+o,e,t,h),r.arcTo(e,t,e+i,t,a),r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke()}function w(){a=[]}n.createVector=function(e,t,r){return new n.Vector(e,t,r)},n.curvePoint=function(e,t,n,r,i){const o=i*i*i,a=i*i;return e*(-.5*o+a-.5*i)+t*(1.5*o-2.5*a+1)+n*(-1.5*o+2*a+.5*i)+r*(.5*o-.5*a)},n.bezierPoint=function(e,t,n,r,i){const o=1-i;return Math.pow(o,3)*e+3*Math.pow(o,2)*i*t+3*o*Math.pow(i,2)*n+Math.pow(i,M 3)*r},n.curveTangent=function(e,t,n,r,i){const o=i*i;return e*(-3*o/2+2*i-.5)+t*(9*o/2-5*i)+n*(-9*o/2+4*i+.5)+r*(3*o/2-i)},n.bezierTangent=function(e,t,n,r,i){const o=1-i;return 3*r*Math.pow(i,2)-3*n*Math.pow(i,2)+6*n*o*i-6*t*o*i+3*t*Math.pow(o,2)-3*e*Math.pow(o,2)},n.Color=function(e,t,n,r){let i=this;i.MAGIC=786698,i._r=e,i._g=t,i._b=n,i._a=r,i._h=0,i._s=0,i._v=0,i._hsvInferred=!1,i.setRed=function(e){i._r=e,i._hsvInferred=!1},i.setGreen=function(e){i._g=e,i._hsvInferred=!1},i.setBlue=function(e){i._b=e,i._hsvInfM erred=!1},i.setAlpha=function(e){i._a=e/255,i._hsvInferred=!1},i._inferHSV=function(){i._hsvInferred||([i._h,i._s,i._v]=function(e,t,n){let r,i,o,a,l;return r=e<t?e<n?e:n:t<n?t:n,0==(l=100*(i=e>t?e>n?e:n:t>n?t:n)/255)?[o=0,a=0,l]:0==(a=100*(i-r)/i)?[o=0,a,l]:(o=i==e?0+60*(t-n)/(i-r):i==t?120+60*(n-e)/(i-r):240+60*(e-t)/(i-r),[o,a,l])}(i._r,i._g,i._b),i._hsvInferred=!0)},i.toString=function(){return`rgba(${Math.round(i._r)},${Math.round(i._g)},${Math.round(i._b)},${~~(1e3*i._a)/1e3})`}},n.colorMode=function(e){n._stM yle.colorMode=e},n.color=function(){if(1==arguments.length&&786698==arguments[0].MAGIC)return arguments[0];if(n._style.colorMode==n.RGB){if(1==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],1);if(2==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],arguments[1]/255);if(3==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],1);if(4==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],arguments[3]/255)}else{if(1==argumeM nts.length)return new n.Color(...x(0,0,arguments[0]/100),1);if(2==arguments.length)return new n.Color(...x(0,0,arguments[0]/100),arguments[1]/255);if(3==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),1);if(4==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),arguments[3])}return null},n.red=function(e){return e._r},n.green=function(e){return e._g},n.blue=function(e){return e._b},n.alpha=function(e){return 255*e._a},n.hue=function(e){reM turn e._inferHSV(),e._h},n.saturation=function(e){return e._inferHSV(),e._s},n.brightness=function(e){return e._inferHSV(),e._v},n.lightness=function(e){return 100*(.2126*e._r+.7152*e._g+.0722*e._b)/255},n.lerpColor=function(e,t,r){return n._style.colorMode==n.RGB?new n.Color(n.constrain(n.lerp(e._r,t._r,r),0,255),n.constrain(n.lerp(e._g,t._g,r),0,255),n.constrain(n.lerp(e._b,t._b,r),0,255),n.constrain(n.lerp(e._a,t._a,r),0,1)):(e._inferHSV(),t._inferHSV(),new n.Color(n.constrain(function(e,t,r){var i=[[Math.abs(t-M e),n.map(r,0,1,e,t)],[Math.abs(t+360-e),n.map(r,0,1,e,t+360)],[Math.abs(t-360-e),n.map(r,0,1,e,t-360)]];return i.sort(((e,t)=>e[0]-t[0])),(i[0][1]+720)%360}(e._h,t._h,r),0,360),n.constrain(n.lerp(e._s,t._s,r),0,100),n.constrain(n.lerp(e._v,t._v,r),0,100),n.constrain(n.lerp(e._a,t._a,r),0,1)))},n.strokeWeight=function(e){n._style_noStroke=!1,r.lineWidth=e},n.stroke=function(){if(n._style.noStroke=!1,"string"==typeof arguments[0])return void(r.strokeStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._sM tyle.noStroke=!0:r.strokeStyle=e},n.noStroke=function(){n._style.noStroke=!0},n.fill=function(){if(n._style.noFill=!1,"string"==typeof arguments[0])return void(r.fillStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._style.noFill=!0:r.fillStyle=e},n.noFill=function(){n._style.noFill=!0},n.blendMode=function(e){r.globalCompositeOperation=e},n.strokeCap=function(e){r.lineCap=e},n.strokeJoin=function(e){r.lineJoin=e},n.ellipseMode=function(e){n._style.ellipseMode=e},n.rectMode=function(e){n._style.rectM Mode=e},n.curveDetail=function(e){n._style.curveDetail=e},n.curveAlpha=function(e){n._style.curveAlpha=e},n.curveTightness=function(e){n._style.curveAlpha=e},n.clear=function(){r.clearRect(0,0,n.width,n.height)},n.background=function(){if(arguments[0]&&arguments[0].MAGIC==n.MAGIC)return n.image(arguments[0],0,0,n.width,n.height);r.save(),r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity),r.fillStyle="string"==typeof arguments[0]?arguments[0]:n.color(...Array.from(arguments)),r.fillRect(0,0,n.width,n.heightM ),r.restore()},n.line=function(e,t,i,o){n._style.noStroke||(r.beginPath(),r.moveTo(e,t),r.lineTo(i,o),r.stroke())},n.arc=function(e,t,r,i,o,a,l,s){if(o==a)return n.ellipse(e,t,r,i);null==s&&(s=25),null==l&&(l=n.PIE),n._style.ellipseMode==n.CENTER?m(e,t,r,i,o,a,l,s):n._style.ellipseMode==n.RADIUS?m(e,t,2*r,2*i,o,a,l,s):n._style.ellipseMode==n.CORNER?m(e+r/2,t+i/2,r,i,o,a,l,s):n._style.ellipseMode==n.CORNERS&&m((e+r)/2,(t+i)/2,r-e,i-t,o,a,l,s)},n.ellipse=function(e,t,r,i){null==i&&(i=r),n._style.ellipseMode==n.CENTERM ?b(e,t,r,i):n._style.ellipseMode==n.RADIUS?b(e,t,2*r,2*i):n._style.ellipseMode==n.CORNER?b(e+r/2,t+i/2,r,i):n._style.ellipseMode==n.CORNERS&&b((e+r)/2,(t+i)/2,r-e,i-t)},n.circle=function(e,t,r){return n.ellipse(e,t,r,r)},n.point=function(e,t){e.x&&(t=e.y,e=e.x),r.beginPath(),r.ellipse(e,t,.4,.4,0,0,2*Math.PI),r.stroke()},n.rect=function(e,t,r,i,o,a,l,s){n._style.rectMode==n.CENTER?y(e-r/2,t-i/2,r,i,o,a,l,s):n._style.rectMode==n.RADIUS?y(e-r,t-i,2*r,2*i,o,a,l,s):n._style.rectMode==n.CORNER?y(e,t,r,i,o,a,l,s):n._stylM e.rectMode==n.CORNERS&&y(e,t,r-e,i-t,o,a,l,s)},n.square=function(e,t,r,i,o,a,l){return n.rect(e,t,r,r,i,o,a,l)},n.beginShape=function(){w(),r.beginPath(),o=!0},n.beginContour=function(){r.closePath(),w(),o=!0},n.endContour=function(){w(),o=!0},n.vertex=function(e,t){w(),o?r.moveTo(e,t):r.lineTo(e,t),o=!1},n.bezierVertex=function(e,t,n,i,o,a){w(),r.bezierCurveTo(e,t,n,i,o,a)},n.quadraticVertex=function(e,t,n,i){w(),r.quadraticCurveTo(e,t,n,i)},n.bezier=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.bezierVM ertex(r,i,o,a,l,s),n.endShape()},n.triangle=function(e,t,r,i,o,a){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.endShape(n.CLOSE)},n.quad=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.vertex(l,s),n.endShape(n.CLOSE)},n.endShape=function(e){w(),e&&r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke(),n._style.noFill&&n._style.noStroke&&(r.save(),r.fillStyle="none",r.fill(),r.restore())},n.curveVertex=function(e,t){if(a.push([e,t]),a.length<4)return;M let i=function(e,t,n,r,i,o,a,l,s,h){function c(e,t,n,r,i,o){let a=Math.pow(r-t,2)+Math.pow(i-n,2);return Math.pow(a,.5*o)+e}let u=[],f=c(0,e,t,n,r,h),d=c(f,n,r,i,o,h),x=c(d,i,o,a,l,h);for(let h=0;h<s;h++){let c=f+h/(s-1)*(d-f),g=[(f-c)/(f-0),(c-0)/(f-0),(d-c)/(d-f),(c-f)/(d-f),(x-c)/(x-d),(c-d)/(x-d),(d-c)/(d-0),(c-0)/(d-0),(x-c)/(x-f),(c-f)/(x-f)];for(let e=0;e<g.length;e+=2)isNaN(g[e])&&(g[e]=1,g[e+1]=0),isFinite(g[e])||(g[e]>0?(g[e]=1,g[e+1]=0):(g[e]=0,g[e+1]=1));let p=e*g[0]+n*g[1],m=t*g[0]+r*g[1],b=n*g[2]+i*g[M 3],y=r*g[2]+o*g[3],w=i*g[4]+a*g[5],v=o*g[4]+l*g[5],z=p*g[6]+b*g[7],V=m*g[6]+y*g[7],_=b*g[8]+w*g[9],M=y*g[8]+v*g[9],E=z*g[2]+_*g[3],S=V*g[2]+M*g[3];u.push([E,S])}return u}(...a[a.length-4],...a[a.length-3],...a[a.length-2],...a[a.length-1],n._style.curveDetail,n._style.curveAlpha);for(let e=0;e<i.length;e++)o?r.moveTo(...i[e]):r.lineTo(...i[e]),o=!1},n.curve=function(e,t,r,i,o,a,l,s){n.beginShape(),n.curveVertex(e,t),n.curveVertex(r,i),n.curveVertex(o,a),n.curveVertex(l,s),n.endShape()},n.translate=function(e,t){r.tM ranslate(e,t)},n.rotate=function(e){r.rotate(e)},n.scale=function(e,t){null==t&&(t=e),r.scale(e,t)},n.applyMatrix=function(e,t,n,i,o,a){r.transform(e,t,n,i,o,a)},n.shearX=function(e){r.transform(1,0,Math.tan(e),1,0,0)},n.shearY=function(e){r.transform(1,Math.tan(e),0,1,0,0)},n.resetMatrix=function(){r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity)},n.pushMatrix=n.push=function(){n._styleCache.push({...n._style}),n._style=n._styleCache[n._styleCache.length-1],r.save()},n.popMatrix=n.pop=function(){n._stylM eCache.length-1&&(n._styleCache.pop(),n._style=n._styleCache[n._styleCache.length-1],r.restore())},n.image=function(e,t,i,o,a,l,s,h,c){let u=e.MAGIC==n.MAGIC?e.canvas:e;function d(){if(e.MAGIC!=n.MAGIC||!n._tint)return;let t=e.canvas.getContext("2d");t.save(),t.resetTransform(),t.clearRect(0,0,t.canvas.width,t.canvas.height),t.drawImage(f.canvas,0,0),t.restore()}return e.MAGIC==n.MAGIC&&null!=n._tint&&(function(e,t){null==f&&(f=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvasM .height),f.canvas.width==e&&f.canvas.height==t||(f.canvas.width=e,f.canvas.height=t)}(e.canvas.width,e.canvas.height),f.drawImage(e.canvas,0,0),e.tinted(n._tint)),o?l?(h||(h=u.width),c||(c=u.height),r.drawImage(u,l,s,h,c,t,i,o,a),void d()):(r.drawImage(u,t,i,o,a),void d()):(e.MAGIC==n.MAGIC||e.width?r.drawImage(u,t,i,e.width,e.height):r.drawImage(u,t,i,e.videoWidth,e.videoHeight),void d())},n.loadPixels=function(){l=r.getImageData(0,0,n.canvas.width,n.canvas.height),n.pixels=l.data},n.updatePixels=function(){null!=M l&&r.putImageData(l,0,0)},n.loadImage=function(e,t){s++;let r=n.createGraphics(100,100),i=r.canvas.getContext("2d"),o=new Image;return o.src=e,o.crossOrigin="Anonymous",o.onload=function(){i.canvas.width=o.width,i.canvas.height=o.height,r.width=o.width,r.height=o.height,i.drawImage(o,0,0),s--,t&&t(r)},r};let v={};function z(e,t){null==u&&(u=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvas.height),u.canvas.width==e&&u.canvas.height==t||(u.canvas.width=e,u.canvas.height=t)}funcM tion V(){let e=r.canvas.width*r.canvas.height*4;null!=d&&e==d.length||(d=new Uint8ClampedArray(e))}function _(e){u.clearRect(0,0,u.canvas.width,u.canvas.height),u.filter=e,u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()}v[n.THRESHOLD]=function(e,t){null==t?t=127.5:t*=255;for(let n=0;n<e.length;n+=4){const r=.2126*e[n]+.7152*e[n+1]+.0722*e[n+2];e[n]=e[n+1]=e[n+2]=r>=t?255:0}},v[n.GRAY]=function(e){for(let t=0;t<e.length;t+=4)M {const n=.2126*e[t]+.7152*e[t+1]+.0722*e[t+2];e[t]=e[t+1]=e[t+2]=n}},v[n.OPAQUE]=function(e){for(let t=0;t<e.length;t+=4)e[t+3]=255},v[n.INVERT]=function(e){for(let t=0;t<e.length;t+=4)e[t]=255-e[t],e[t+1]=255-e[t+1],e[t+2]=255-e[t+2]},v[n.POSTERIZE]=function(e,t){let n=t-1;for(let r=0;r<e.length;r+=4)e[r]=255*(e[r]*t>>8)/n,e[r+1]=255*(e[r+1]*t>>8)/n,e[r+2]=255*(e[r+2]*t>>8)/n},v[n.DILATE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-M 1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.max(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.ERODE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.min(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.BLURM ]=function(e,t){t=t||1,t=Math.floor(t*n._pixelDensity),V(),d.set(e);let i=2*t+1,o=function(e){let n=new Float32Array(e),r=.3*t+.8,i=r*r*2;for(let t=0;t<e;t++){let o=t-e/2,a=Math.exp(-o*o/i)/(2.5066282746*r);n[t]=a}return n}(i),[a,l]=[r.canvas.width,r.canvas.height];for(let n=0;n<l;n++)for(let r=0;r<a;r++){let l=0,s=0,h=0,c=0;for(let e=0;e<i;e++){let i=4*(n*a+Math.min(Math.max(r-t+e,0),a-1));l+=d[i]*o[e],s+=d[i+1]*o[e],h+=d[i+2]*o[e],c+=d[i+3]*o[e]}let u=4*(n*a+r);e[u]=l,e[u+1]=s,e[u+2]=h,e[u+3]=c}d.set(e);for(let nM =0;n<l;n++)for(let r=0;r<a;r++){let s=0,h=0,c=0,u=0;for(let e=0;e<i;e++){let i=4*(Math.min(Math.max(n-t+e,0),l-1)*a+r);s+=d[i]*o[e],h+=d[i+1]*o[e],c+=d[i+2]*o[e],u+=d[i+3]*o[e]}let f=4*(n*a+r);e[f]=s,e[f+1]=h,e[f+2]=c,e[f+3]=u}},n.filter=function(e,t){if(n.HARDWARE_FILTERS&&null!=r.filter)if(z(),e==n.THRESHOLD){null==t&&(t=.5),t=Math.max(t,1e-5),_(`saturate(0%) brightness(${Math.floor(.5/t*100)}%) contrast(1000000%)`)}else if(e==n.GRAY)_("saturate(0%)");else if(e==n.OPAQUE)u.fillStyle="black",u.fillRect(0,0,u.canvaM s.width,u.canvas.height),u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.drawImage(u.canvas,0,0),r.restore();else if(e==n.INVERT)_("invert(100%)");else if(e==n.BLUR)_(`blur(${Math.ceil(t*n._pixelDensity/1)||1}px)`);else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}},n.resize=function(e,t){z(),u.drawImage(r.canvas,0,0),n.width=e,n.height=t,r.canvas.width=e*n._pixM elDensity,r.canvas.height=t*n._pixelDensity,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0,r.canvas.width,r.canvas.height),r.restore()},n.get=function(e,t,i,o){if(null!=e&&null==i){let i=r.getImageData(e,t,1,1).data;return new n.Color(i[0],i[1],i[2],i[3]/255)}e=e||0,t=t||0,i=i||n.width,o=o||n.height;let a=n.createGraphics(i,o);a.pixelDensity(n._pixelDensity);let l=r.getImageData(e*n._pixelDensity,t*n._pixelDensity,i*n._pixelDensity,o*n._pixelDensity);return a.caM nvas.getContext("2d").putImageData(l,0,0),a},n.set=function(e,t,i){if(i.MAGIC==n.MAGIC){let r=n._tint;return n._tint=null,n.image(i,e,t),void(n._tint=r)}let o=4*(t*n._pixelDensity*r.canvas.width+e*n._pixelDensity);n.pixels[o]=i._r,n.pixels[o+1]=i._g,n.pixels[o+2]=i._b,n.pixels[o+3]=255*i._a},n.tinted=function(){let e=n.color(...Array.from(arguments)),t=e._a;e._a=1,z(),u.clearRect(0,0,u.canvas.width,u.canvas.height),u.fillStyle=e,u.fillRect(0,0,u.canvas.width,u.canvas.height),u.globalCompositeOperation="multiply",u.M drawImage(r.canvas,0,0),u.globalCompositeOperation="source-over",r.save(),r.resetTransform();let i=r.globalCompositeOperation;r.globalCompositeOperation="source-in",r.drawImage(u.canvas,0,0),r.globalCompositeOperation=i,r.restore(),u.globalAlpha=t,u.clearRect(0,0,u.canvas.width,u.canvas.height),u.drawImage(r.canvas,0,0),u.globalAlpha=1,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()},n.tint=function(){n._tint=n.color(...Array.from(arguments))},n.noTiM nt=function(){n._tint=null},n.mask=function(e){r.save(),r.resetTransform();let t=r.globalCompositeOperation;r.globalCompositeOperation="destination-in",r.drawImage(e.canvas,0,0),r.globalCompositeOperation=t,r.restore()},n.clearTemporaryBuffers=function(){u=null,f=null,d=null},n.save=function(e,t){e=e||"untitled",t=t||"png";var n=document.createElement("a");n.innerHTML="[Download]",n.addEventListener("click",(function(){this.href=r.canvas.toDataURL(),this.download=e+"."+t}),!1),document.body.appendChild(n),n.click()M ,document.body.removeChild(n)},n.saveCanvas=function(e,t,r){if(e.MAGIC==n.MAGIC){r&&e.save(t,r);let n=t.split(".");return e.save(n.slice(0,-1).join("."),n[n.length-1])}if(t)return n.save(e,t);let i=e.split(".");return n.save(i.slice(0,-1).join("."),i[i.length-1])},n.loadFont=function(e){let t=e.split("/"),n=t[t.length-1].split(".")[0].replace(" ",""),r=`@font-face {\n font-family: '${n}';\n src: url('${e}');\n }`;const i=document.createElement("style");return i.textContent=r,document.head.append(M i),n},n.textFont=function(e){n._style.textFont=e},n.textSize=function(e){n._style.textSize=e,n._style.textLeading=e},n.textLeading=function(e){n._style.textLeading=e},n.textStyle=function(e){n._style.textStyle=e},n.textAlign=function(e,t){r.textAlign=e,t&&(r.textBaseline=t==n.CENTER?"middle":t)},n.text=function(e,t,i,o){if(!e)return;if(e=e.toString(),n._style.noFill&&n._style.noStroke)return;r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`;let a=e.split("\n");for(let e=0;e<a.length;e++)n._M style.noFill||r.fillText(a[e],t,i,o),n._style.noStroke||r.strokeText(a[e],t,i,o),i+=n._style.textLeading},n.textWidth=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).width},n.textAscent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBoundingBoxAscent},n.textDescent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBounM dingBoxDescent};var M,E=4,S=.5,R=function(e){return.5*(1-Math.cos(e*Math.PI))};n.noise=function(e,t,n){if(t=t||0,n=n||0,null==M){M=new Array(4096);for(var r=0;r<4096;r++)M[r]=Math.random()}e<0&&(e=-e),t<0&&(t=-t),n<0&&(n=-n);for(var i,o,a,l,s,h=Math.floor(e),c=Math.floor(t),u=Math.floor(n),f=e-h,d=t-c,x=n-u,g=0,p=.5,m=0;m<E;m++){var b=h+(c<<4)+(u<<8);i=R(f),o=R(d),a=M[4095&b],a+=i*(M[b+1&4095]-a),l=M[b+16&4095],a+=o*((l+=i*(M[b+16+1&4095]-l))-a),l=M[4095&(b+=256)],l+=i*(M[b+1&4095]-l),s=M[b+16&4095],l+=o*((s+=i*(M[M b+16+1&4095]-s))-l),g+=(a+=R(x)*(l-a))*p,p*=S,h<<=1,c<<=1,u<<=1,(f*=2)>=1&&(h++,f--),(d*=2)>=1&&(c++,d--),(x*=2)>=1&&(u++,x--)}return g},n.noiseDetail=function(e,t){e>0&&(E=e),t>0&&(S=t)};const I=function(){let e,t,n=4294967295;return{setSeed(r){e=t=(null==r?Math.random()*n:r)>>>0},getSeed:()=>t,rand:()=>(e^=e<<17,e^=e>>13,((e^=e<<5)>>>0)/n)}};let C=I();C.setSeed(),n.noiseSeed=function(e){let t=null==e?4294967295*Math.random():e;M||(M=new Float32Array(4096));for(var n=0;n<4096;n++)t^=t<<17,t^=t>>13,t^=t<<5,M[n]=(t>M >>0)/4294967295},n.randomSeed=function(e){C.setSeed(e)},n.random=function(e,t){return null==e?C.rand():"number"==typeof e?null!=t?C.rand()*(t-e)+e:C.rand()*e:e[~~(e.length*C.rand())]},n.randomGenerator=function(e){e==n.LCG?C=function(){const e=4294967296;let t,n;return{setSeed(r){n=t=(null==r?Math.random()*e:r)>>>0},getSeed:()=>t,rand:()=>(n=(1664525*n+1013904223)%e)/e}}():e==n.SHR3&&(C=I()),C.setSeed()};var T=new function(){var e,t,n,r=new Array(128),i=new Array(256),o=new Array(128),a=new Array(128),l=new Array(2M 56),s=new Array(256),h=function(){return 4294967296*C.rand()-2147483648},c=function(){return.5+2.328306e-10*(h()<<0)};this.SHR3=h,this.UNI=c,this.RNOR=function(){return n=h(),e=127&n,Math.abs(n)<r[e]?n*o[e]:function(){for(var t,i,l,s,u=3.44262;;){if(t=n*o[e],0==e){do{l=c(),s=c(),t=.2904764*-Math.log(l),i=-Math.log(s)}while(i+i<t*t);return n>0?u+t:-u-t}if(a[e]+c()*(a[e-1]-a[e])<Math.exp(-.5*t*t))return t;if(n=h(),e=127&n,Math.abs(n)<r[e])return n*o[e]}}()},this.REXP=function(){return(t=h()>>>0)<r[e=255&t]?t*l[e]:funM ction(){for(var n;;){if(0==e)return 7.69711-Math.log(c());if(n=t*l[e],s[e]+c()*(s[e-1]-s[e])<Math.exp(-n))return n;if((t=h())<i[e=255&t])return t*l[e]}}()},this.zigset=function(){var e,t,n=2147483648,h=4294967296,c=3.442619855899,u=c,f=.00991256303526217,d=7.697117470131487,x=d,g=.003949659822581572;for(e=f/Math.exp(-.5*c*c),r[0]=Math.floor(c/e*n),r[1]=0,o[0]=e/n,o[127]=c/n,a[0]=1,a[127]=Math.exp(-.5*c*c),t=126;t>=1;t--)c=Math.sqrt(-2*Math.log(f/c+Math.exp(-.5*c*c))),r[t+1]=Math.floor(c/u*n),u=c,a[t]=Math.exp(-.5*cM *c),o[t]=c/n;for(e=g/Math.exp(-d),i[0]=Math.floor(d/e*h),i[1]=0,l[0]=e/h,l[255]=d/h,s[0]=1,s[255]=Math.exp(-d),t=254;t>=1;t--)d=-Math.log(g/d+Math.exp(-d)),i[t+1]=Math.floor(d/x*h),x=d,s[t]=Math.exp(-d),l[t]=d/h}};T.hasInit=!1,n.randomGaussian=function(e,t){return T.hasInit||(T.zigset(),T.hasInit=!0),T.RNOR()*t+e},n.randomExponential=function(){return T.hasInit||(T.zigset(),T.hasInit=!0),T.REXP()},n.print=console.log,n.cursor=function(e,t,r){let i="";e.includes(".")&&(e=`url("${e}")`,i=", auto"),null!=t&&(e+=" "+t+M " "+r),n.canvas.style.cursor=e+i},n.noCursor=function(){n.canvas.style.cursor="none"},n.createCapture=function(e){var t=document.createElement("video");return t.playsinline="playsinline",t.autoplay="autoplay",navigator.mediaDevices.getUserMedia(e).then((function(e){t.srcObject=e})),t.style.position="absolute",t.style.opacity=1e-5,t.style.zIndex=-1e3,document.body.appendChild(t),t};let A=["setup","draw","preload","mouseMoved","mousePressed","mouseReleased","mouseDragged","mouseClicked","keyPressed","keyReleased","keM yTyped","touchStarted","touchEnded"];for(let e of A){let t="_"+e+"Fn";n[t]=function(){},n[t].isPlaceHolder=!0,n[e]?n[t]=n[e]:Object.defineProperty(n,e,{set:function(e){n[t]=e}})}function D(){n._noLoop||(i=null==n._frameRate?requestAnimationFrame(D):setTimeout(D,1e3/n._frameRate)),w(),o=!0,n.push(),n._drawFn(),n.pop(),++n.frameCount}function k(e){const t=n.canvas.getBoundingClientRect(),r=n.canvas.scrollWidth/n.width||1,i=n.canvas.scrollHeight/n.height||1;return{x:(e.clientX-t.left)/r,y:(e.clientY-t.top)/i,id:e.idenM tifier}}function L(){return n._touchStarted.isPlaceHolder&&n._touchMoved.isPlaceHolder&&n._touchEnded.isPlaceHolder}n.noLoop=function(){n._noLoop=!0,i=null},n.loop=function(){n._noLoop=!1,null==i&&D()},n.redraw=function(){D()},n.frameRate=function(e){n._frameRate=e},setTimeout((function(){n._preloadFn(),c=window.performance.now(),function e(){if(s>0)return setTimeout(e,10);n._setupFn(),D()}()}),1),n.canvas.onmousemove=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPM ressed?n._mouseDraggedFn(e):n._mouseMovedFn(e)},n.canvas.onmousedown=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!0,n.mouseButton=[n.LEFT,n.CENTER,n.RIGHT][e.button],n._mousePressedFn(e)},n.canvas.onmouseup=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!1,n._mouseReleasedFn(e)},n.canvas.onclick=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressedM =!0,n._mouseClickedFn(e),n.mouseIsPressed=!1},window.addEventListener("keydown",(function(e){n.keyIsPressed=!0,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!0,n._keyPressedFn(e),1==e.key.length&&n._keyTypedFn(e)})),window.addEventListener("keyup",(function(e){n.keyIsPressed=!1,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!1,n._keyReleasedFn(e)})),n.keyIsDown=function(e){return!!h[e]},n.canvas.ontouchstart=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.moM useY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mousePressedFn(e)||e.preventDefault()),n._touchStartedFn(e)||e.preventDefault()},n.canvas.ontouchmove=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mouseDraggedFn(e)||e.preventDefault()),n._touchMovedFn(e)||e.preventDefault()},n.canvas.ontouchend=n.canvas.ontouchcancel=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.M mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!1,n._mouseReleasedFn(e)||e.preventDefault()),n._touchEndedFn(e)||e.preventDefault()},n.hasSensorPermission=!window.DeviceOrientationEvent&&!window.DeviceMotionEvent||!(DeviceOrientationEvent.requestPermission||DeviceMotionEvent.requestPermission),n.requestSensorPermissions=function(){DeviceOrientationEvent.requestPermission&&DeviceOrientationEvent.requestPermission().then((e=>{"granted"==e&&DeviceMotionEvent.requestPermissioM n&&DeviceMotionEvent.requestPermission().then((e=>{"granted"==e&&(n.hasSensorPermission=!0)})).catch(alert)})).catch(alert)},window.ondeviceorientation=function(e){n.pRotationX=n.rotationX,n.pRotationY=n.rotationY,n.pRotationZ=n.rotationZ,n.pRelRotationX=n.relRotationX,n.pRelRotationY=n.relRotationY,n.pRelRotationZ=n.relRotationZ,n.rotationX=e.beta*(Math.PI/180),n.rotationY=e.gamma*(Math.PI/180),n.rotationZ=e.alpha*(Math.PI/180),n.relRotationX=[-n.rotationY,-n.rotationX,n.rotationY][1+~~(window.orientation/90)],n.rM elRotationY=[-n.rotationX,n.rotationY,n.rotationX][1+~~(window.orientation/90)],n.relRotationZ=n.rotationZ},window.ondevicemotion=function(e){if(n.pAccelerationX=n.accelerationX,n.pAccelerationY=n.accelerationY,n.pAccelerationZ=n.accelerationZ,!e.acceleration){let t=((e,t)=>[(e[0]*t[0]+e[1]*t[1]+e[2]*t[2]+e[3])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[4]*t[0]+e[5]*t[1]+e[6]*t[2]+e[7])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[8]*t[0]+e[9]*t[1]+e[10]*t[2]+e[11])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15])])(((e,t)M =>[e[0]*t[0]+e[1]*t[4]+e[2]*t[8]+e[3]*t[12],e[0]*t[1]+e[1]*t[5]+e[2]*t[9]+e[3]*t[13],e[0]*t[2]+e[1]*t[6]+e[2]*t[10]+e[3]*t[14],e[0]*t[3]+e[1]*t[7]+e[2]*t[11]+e[3]*t[15],e[4]*t[0]+e[5]*t[4]+e[6]*t[8]+e[7]*t[12],e[4]*t[1]+e[5]*t[5]+e[6]*t[9]+e[7]*t[13],e[4]*t[2]+e[5]*t[6]+e[6]*t[10]+e[7]*t[14],e[4]*t[3]+e[5]*t[7]+e[6]*t[11]+e[7]*t[15],e[8]*t[0]+e[9]*t[4]+e[10]*t[8]+e[11]*t[12],e[8]*t[1]+e[9]*t[5]+e[10]*t[9]+e[11]*t[13],e[8]*t[2]+e[9]*t[6]+e[10]*t[10]+e[11]*t[14],e[8]*t[3]+e[9]*t[7]+e[10]*t[11]+e[11]*t[15],e[12]*t[0]+M e[13]*t[4]+e[14]*t[8]+e[15]*t[12],e[12]*t[1]+e[13]*t[5]+e[14]*t[9]+e[15]*t[13],e[12]*t[2]+e[13]*t[6]+e[14]*t[10]+e[15]*t[14],e[12]*t[3]+e[13]*t[7]+e[14]*t[11]+e[15]*t[15]])((e=>[Math.cos(e),0,Math.sin(e),0,0,1,0,0,-Math.sin(e),0,Math.cos(e),0,0,0,0,1])(n.rotationY),(e=>[1,0,0,0,0,Math.cos(e),-Math.sin(e),0,0,Math.sin(e),Math.cos(e),0,0,0,0,1])(n.rotationX)),[0,0,-9.80665]);n.accelerationX=e.accelerationIncludingGravity.x+t[0],n.accelerationY=e.accelerationIncludingGravity.y+t[1],n.accelerationZ=e.accelerationIncludM ingGravity.z-t[2]}},n.year=function(){return(new Date).getFullYear()},n.day=function(){return(new Date).getDay()},n.hour=function(){return(new Date).getHours()},n.minute=function(){return(new Date).getMinutes()},n.second=function(){return(new Date).getSeconds()},n.millis=function(){return window.performance.now()-c}}(e)}"object"==typeof exports&&"undefined"!=typeof module&&(module.exports=e);const t="https://ancient-crimson-rain.btc.discover.quiknode.pro/c268fb026303ae8443f785200f2ea4b82f0082dd";function n(e){P(e)?M localStorage.removeItem("blocksApiEndpoint"):localStorage.blocksApiEndpoint=e}function r(){return localStorage.blocksApiEndpoint||t}function i(e){P(e)?localStorage.removeItem("modelInscriptionEndpoint"):localStorage.modelInscriptionEndpoint=e}function o(){return localStorage.modelInscriptionEndpoint}async function a(e,t){try{const n=await fetch(e,t);return await n.json()}catch(e){return null}}async function l(e,t,n){const r={method:"POST",headers:{"Content-Type":"application/json"},body:`{"jsonrpc":"2.0","id":1,"meM thod":"${t}","params":${`[${n.join(sep=",")}]`}}`};return(await a(e,r))?.result}async function s(e){const n={avgfee:10,time:Date.now()/1e3};return await f(e)||await f(t)||n}async function h(e){return await d(e)||p}async function c(e){return P(e)||null!=await f(e)}async function u(e){return P(e)||null!=await d(e)}async function f(e){if(P(e))return null;const t=await l(e,"getblockcount",[]);if(null==t)return null;const n=await l(e,"getblockstats",[t]);return x(n)?n:null}async function d(e){if(P(e))return null;const tM =await a(e,{});return g(t)?t:null}function x(e){return"number"==typeof e?.time&&"number"==typeof e?.avgfee}function g(e){if(null==e)return!1;const{classes_name:t,training_traits:n,layers_config:r,weight_b64:i}=e;if(!Array.isArray(t))return!1;if(null==n)return!1;try{j(r,i)}catch(e){return!1}return!0}const p={"model_name": "pfp_classifier_88", "layers_config": {"config": {"layers": [{"class_name": "InputLayer", "config": {"batch_input_shape": [null, 28, 28, 3]}}, {"class_name": "Rescaling", "config": {"scale": 0.0078M 4313725490196, "offset": -1}}, {"class_name": "Flatten"}, {"class_name": "Dense", "config": {"units": 5, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 5, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 2, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 2, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 4, "activation": "linear"}}]}}, "weight_b64": "Oo5LvSCFK7tYIFQ8XMFCvfui3jsl+sW9dJQ8PLZpez07HLG8rrjqvduiIrox87s9iQzcO2+1y7x3njG8jXOoPC0M 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 91VtCvlrNBr1jwdM8XcgsPUrrljxERhy9org8vbEuEj2xSUs9teldvG+paT3cLVu9QHrfPYL9lz2amcS8euwgvqD8Kzy4gGo8YcCMvJspsDwlAf28c3lTve5XVj1DHd+8Ap0rPaklNDy5n4Q8tEbOPYBwIT1bJDq95VnIverQgryZnZg9sxqiu+4+rjwV3FG9z1gSvSY1hz1wxD09VgScvPa1ED2guAy7RqqePDtQprw6pq28t4YOvr1KKr2Bpbg7RdLkO+cdkT39NZ+8pjbGvHBJCT10kSY9Hapiu9Rdnj0JCvw8LC+HPCsXGT2zuAQ9/YIuvu70ALxlm488NMxyvDnrSzso+B69AcnPO3nlpTvotnq5ucpxPYRbkT3iQMa7+T4ePMypI7zcht08mlFEvsaUoTqhbe28mQPvvJjk17suDiO7UUxAvROGXz2T2D48LRt0PGTggj2Fxg09wvlyPO+yVruNSpE7tnrCvWhUvrwXuJK8TuEbvU4cij1LTwY9sDtUu2mM 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 6XJzMvRRWAb0xRO08YKzUu9ztxztHqCM8cDDuvDnB5jyr+ZY95Cg+u+2TCD13lF693UraPZ0/Rz22Z6g7P0sXvgYrM70Y+Xs9egECPTDm3jzzHgy9AWfUOktYpz2HA/G7yTxvvTHa8LtRMyW9YhY2PVwKoD247ym81vQfvtlOJjwu2n09+i9TvDNfaL3IoqS7gMGXvDwixz2aloo9shLkvPuwUD37ZKO9NJfFPbBMnT22noG7k+5ZvvSxrjucP7s97ImhvP8yLb16Bgq9K1tvvbeAyT292Gw9+BxTvMU1GT1HHJi8rJTQPRkArT1YGLO7sPbmvQGH6ruYiC49eOcCPaUCUr1/39q8p1FQvXMwJzxpGqq8o55DO2tlsjw2Owc9mRe4PJX7zLxq5OS8UtGDvb8vsbtkb2m8NFgBvT1QkzygV7+7q9rZvGGryzyH/Ps8yyerPBcHDT07MB48q7auPME6G719vEs95vAcvjBLHzzLwOo8jijPPLyoCz1/Lgu9zuXxOveM 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 96FB5vanPJb2zypq6enopvedmezxmyAs7vix2PfNUTjugA1C9nYq+PFm8Zj0Ji+k8s+W0vKCnET0OOoa81L1uvSu3DT2bhUu9JosjvAUZRj0PHoI6VyzsPOP2Uryv6wa94WhhPUWAMTux55K8DuJEPWjRsrsiWAW8Af33vendBz1zC5C8bmEjvbEThzu+Chu9YywkvdRbgT1CHk88qzEJPAtN3btZDiq9cHu9PBfhSz1P5cG8eJA+vjZ6l73iuu88+q4HPRLfMLrnyIS9gaxpvSe9OTx3TBI9sXkPPYXYlLwbVNi75L3dPdO01jw794O9Ag0svon34bwDm5U9huTRPL5Ea71vfa28nYLBPFTK4D1FhDs9cHIQvfEZSD1s9Zy9VhyXPcDb3D2/t/S8RfbwvdjvSr0+I1E9USN5PfFVOjsGJeS7NNi8vAVW5jzZVoo9ltw5vTLbhD05tOq8UU3JPfvwej0LAk87O1MuvpDKDDvwwYM9CVcXPawwG71+JZK9yfNmvXLM 1nj1zHuw8ciD2PAgzzLxbd5S8J9VWPSUnQT1fO7K9Iu8Tvkufdb3dvZs9lzdwPJEryjypVy29efvoOxrG0j0yegc9u4xOPOmkUT36DNE7whGdPabACz1ugIW9J6RDvg4djr0/Dqk9t32AvGVst7zhaIO9pzuqvLKbmD28biA8l8iDvJwsNLyMfBw7jsAaPQ9dQ7xfXza9k44NvqLKFj34PpA8CC9ivBu7DTxW8p48oD4EPftHwbw63DE9KvuOPWzuMT1HrQo9nWngPAtZSL3MA4G80PG6veEOXD1PD9+8mCoOvPd2Cj0UhUg7thk6O8uZADxbT6w8z7S2Ozo1lj0UqkI9m49/PU3dD7xNAmQ8nqMEvolUD70eAxe8oHC1OySTfz00wzM8KhIPvVJ+HDwv6ym8eLAdPPShqLwheUe9qMy1PO3+5zy0tkq8wOJAvlTYjbx/4SA9qTq6PIFDirszJka9JGwHvaxVLz0YcDG8zt3HPI5w3Twoj6G8Q3OePR9GKz17hbGM 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 80JfbvfbRnDxyK9G8wZMXvYFzbj0tNMW75A0EvRHTfz26HaE7mMgTOk1ZVj2cyrq7vtkZPMd8hD21zhM9s07rvVAlEzw2hcc8Phk9vH07jTxaq2+8ocovvLmTNj1x3I49iTQfvZkqez3ieW29hJnjPK6QTjwX9CU8z6Q9vg7Tazyt4bo9VhAwvVXUA7wPB2o8PncovcGZxzz8NYC8RMlUPGDIWT1nhQu9xspLPQ91Hz1G7oS8wqQlvt1VS7w2d9w9ET2evFkdrjx8SG+9BStCPEOQqzxFzTA84M9RvWCyU7xCwT46dIvvPasGyz06SYu5oHYGvhfWmb0gZpU9nssmPSIYnrqvko69w/Ujve2l2z1siUM9lalxvdcWhLzcXRA8bNOAPQS1Nj243zO91Ef6vfSJErz86NE9nBs2Pc2DrDzaqVm7nwqtvGTnJD1lNVg9Q12Yu98VkzxMhhe9M80kPV0TyTuvI9874Oe5vcpoqDx52aE94fdpvZOLAb1AdRC9CtwwvT5M 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 8A4IbvnynRjw/8+A7WQVBvA++GLxPwC08mIjtPPLJFbzbY0m9fvmRPQuTXz2xZAI96Zy5O0P9j7zbbcg81MiYvDUtdT0Kaxi9yp8ivHeX47zs52y8/60ePBk5z71T5pO8kixgPVoZvj36rhC9w9JyvSfIpDs6qY+8tP/JvIiUyrzgnyO9jOuCPWjeYLqSvYk6PE4oOkKoCL1tKU296cUoPQVOBTzuYRQ91uIJvS6UDz2HJAI9SXO0vBSY8DzQwqO3y4pfvFDdZD1Kxv480V75usCvEL073PU8mOwwvAG0dz1GIAk8TdbGvNd6BbqXNvy8WOH/vesBAr37zaG9bi2PPMhzoLykhXo9UpnwO3H9Ob2yCIo8yWMGPP4eqj05VwY8LgIsvWMOmbuiqAy8iR0Zvi34Hbygfh69LVMkvA0y0zz4hm09WDFnOzM7xjmJI1s95psgvbO097nR+Da8xeoZPEbhLD0FE2U73iW0vez6uTwLhgW92SNaPctFFLy1vaG8GckYPfLM 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 +Pc6CPDsA8b3P+JO9oG2Pvd4isD2PtCW8PcZYuxSBmb0cLfM9NhICvvu8Nryqt7S9/YWxvVX0wz1dMwM9FWbIPfWpwb3sf3W9N535Pc9CBL46cPQ8r0uHPQoZjr1SrVA+gjQWvsu+Mj0yAZ09zZO5vQBaoz2kXfS7TE4+Pk6ieT0lI529ZACiOx37lrxDsUo9/5NYvb0sdD2WFP09a+sKvsbDkjw0tWO71Gj5PJd71z1FbrK8jwN7PQ9ivrxk2lM9U347PcIwU70qKQS9fapTvBt2mztAXzE9YTWFvHO4Bj2/lUQ8sdgBPbFfID3gikO9hrr6PSbwkT2eWB89KAAnPTMUPbyRL3I987dVPbDCcb1ppqa9RSTouoH+1j30aAI+COu3vc2F2b2ZvoM9VQ8ZPiq/fD3mx2W80lpkvY7rfbtg9Pg9FDYNu2ZZGr7STdm813lJPC+9qLzzWYM9Y7sbveoT0DvTDIU9NEiXPSmCET0iN8m8o8iYPdTTHb1hlR89j1vXvPAM 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 9TXOuPdURCD7C8gC+AL2bvNhsGT3lazY9fhkdPflFuj26lvk9vjnVvXTAZL3pxF89kumZPDp+0zwC4/u8A4wYPVC0Jj0/X429KRPyPEdxor3vMoc9vudbPEzcNrzFQfK99fUjPaXVjbuIWGo9B5w7vUHvV723Ftw9n4NTPL24db2e+C29nbKxvZIBzT1RaG88uYjwvDOvez2IzWS7cwFIvefYWDzLOOk7ctQvPIS37btgbdG8p/czu4vswr2iGYO6mU4iOom7kTxIZgi9cq0lOuH3hzytVAq9qNacPfKv3j2HkbW9kMzRvCGvqL0jsUM9GQ1LPGpZsL1axXq9q+Cmu2r/Er38nA89TYFRO+2GkTxEo1W9y+3cO7HBsTx4jAS9zJZhvAUhHjuReDc81PFgvYgisL1HabS7OK9cvMaSgTxwZFa6EPlUvccviLwEUSG9Ap5BPVrgbj2CwkW9H2DlPAKkGDwFjUQ9hT64vVI9Tj3ivG88FAw0vUhF0TywLbs8hDxlvc4M 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 2RT0Ib5i99qntO28RAb3OUTO9dyHvPaOO9L0eYl89FXcCvb95qb1Ji2c8p8Etvb8bQD3hf1k8CdICvV/HHb0RB+Q8/H+1vaZbxTv5yuq8TAkoPHb/HT3u2Jq9I2eEvEAD9b002E49PTPfPVgLWr0HHxO9u+ujvCyMr72Prb49qJUTPYVihz161BM9/lOQvaUjxT2VSWI7lZ9bPSyHXb3nk4i9WydMPR/iAz12QxS9FNN7vTSSFb0l4qk9HmvtPFBBZrr3fp+9Tm8HvWeeBz0A7AE7Lyg1PRelSDunMvi7yA4APkCuAb3HuUa9lSoovdcggL27+Qe810qivQh4k71bpSg9l/qqPEqR2z1FEce9pa8XPX4sXbw+l0w9izgtPnXbqL2AcyK8mUi7PO/1wzwa/G88bmMQvfm+ubuaIYk9Z4t8Pcg9QD0XhDm9jdboPRPZBD0/bbo9yiTDPfEb+rw1Ihk8DVxku85FMT3p+Zu97SzDvEYvrr2jNg09VYGCPWq3Yb1jeA0M 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 zXLybxTy9XbuHPDv/uT30Ti29dzIQvJrFIb2sURy8KtaXvXJadros6am8W5fau00QHT1kuhw8YiiVvJgFyDzXKR+7m8UQvPwQyTxMopQ8e3nxuyTGLb07SGm8927NvC/BQj3/n6I8bsr7Oxyo5zsZUuK8tWftvAF1KjtfxuM8b8cBPSGTbD3iT8i8uaeUu9u2ej0N8Rk8eGLlvFDBljwMGgA8HhQqPQ59V7wf0k+9Bzj5O1ygXz0zsh09UgSaPIKQ3Lw5aLS8ZMdePKi+DTsxebo7Re7TvZk0ybwP/wO7nnU1PRmENjx7Lhu9+lT/PZ4dubzharK9kjoIPt6+yDxlpu89iAbyvVrJBb4PqaY9fLsSvfP+mj2C2Ku9YJmmvB+lxD0zg9K6zBYcPXHKN72fvJe9x67ausxWuT0LW8M94LdevVxVj7xMGt08K6wMuy3XmDySh8E70l/TPFOxMD0xFCa92bxIPHp9zbyVC6Y8bBPZuqW+gT2nrIU9WF2OPLNBQL1kZxGM 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 9RDU6vM//8z2Dxwy9gQbZvffQkj3/OCA8gD+uvMgJ27sgXkg9P/kXvUjzHr1UbQi7uhyPPL8gkz2OhcG9CefQvMYf+DxQnpw9o9lpPd/cnrzJq1O9vpWNvbI+nj0JBZI9ktrMvARZlb23A469NcCSPfXWAD7xVgC+pYoKvVbhhL3we4o94DoMPlrl870IsO281g+8OlIMhj3fnsc8ancmve6HBr3Ahzq96Q29Pcys2j0Ri5W92JkavdtDIby4+He8UP7tPDm+PLzCBRm9QWtrvavYCD7n9Yc9nFqcvVFpL7wlHTY8P9w4PotiKD7Ci0W+xA+jvO7uLr2eFgA9sfyhPdDBiL1CfCS7MJTfvSq2ajv9InI9tlo3vVYA8Tz1ID477q6iPaEguz3VjD29pKjUulXXdL0zUC87dGouPAMI2Tvof0w8M6cKvWZB/jzLZwW9wBetPDkX9DzyUYE9TmM2O+zcSD2kKZ+9BdPTPQGDErzLLgM9gpLbPfVw2L0hlhQ9DX/9PM9M 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 qlz1G0xg+oHuxvcj8HTsRqnM8U5L1PWfmBD7ekDO+C2rxvIVKlTvSol09OIWyPYwq/rzgXJ47pYCuvdKGlD0Agpo9GVe8vcWnubwAsnS92FkLPq/VVT5vrwq+uFZavQ2uyDtY1u88H57DPEVJSr3HRSu9WXqhvWmaST2XU+Q9KvKZvfcYjTqBcqu93u43PpcaGz4Qhx6+IdrevWRFyL3J/AQ93lFmPEP/JDwbyRe9QnoFvYTD4z2RBZQ9GjYIvvpzrLydvw++7MQZPhahCz7Zcze+L/K5vET39b2vZ608J1aePdp60Ly8xHg7NXiHvL+hAj4kuQE+oRQavsZskj1O/P29+2HhPaDiHz7SRe69VBk4vZ2IGr5Xyxc9OUWFPfH6ab3ThZi8F4UDPWS9XT3ig9o8DEE0vZmPlT3mKu+9enckPf0zCz537+29QjFAPZFSXL7ozeQ7M/QkPW4g2L0P3yG7rcg/PQopBT0J+iW8LkDXvRVvpz2Qw6C9T7KNPcuWuj3mBAeM 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 ygbwVwEU9K6sVvU5hGT2lz6I8BPdKPJQ+IDwv2nA8s7gAvhvijTtwb4k8BYEiPTiM0TsvuCk9aIYzvStI9DxNl+m8sy6+PN2bPzxUiW69ude3PM56bbtmvWO8HOrTvequQT3ECpK8fraLvP7Y6DyJyFI9HA5nvLjlpbxAc2e8FrIUvIyapT2tQsI8ZAf7vDpXLj3BSiq83G9avfTTrTyxxD09E6ezPAkOPz0WpUI7NXvovIH0IDs6WQC824SpO2gPmj1DPnG89sWkvdQzh728zgY9CVCyvdSRaj36i7M8UNcrPX3j8Lw/maq7eet1PU7cLL0fM926vUPLPXQAkD1XtQK9yDX4vX6Q9rxFFcY9kS2UvcWgQbyCYLK9WVR5PLKXXjyaeGk9G4PJPBznyb0Hh7O9d5ODPWkHTD3s/62815KGvYg1ab367qk9FJNuvV9KyTwY6iy8jMgFvLW/MT2kGn0749axPQXtGL1YpTa9rmepPZFldjyo8XU9+kt2vcW2yL3CP0gM 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 YkL1yv+O9sjPJPaNqJz5/F6U91yQovlO4I76/2LI91zrYPG28gz2ZsF69Slm5vZYOBj1i6XU98hc3PDVB8r3FK4G9Q7PdPVmpkj1v9G49hZMGvqt/q73eOaM9hRyLvSK7vj1IiNe9sWYCvapskz0foDU9teWHPWkEoL18Way94h2LPUYoAj58BNU9lRI2vjkM9r10xRY+EAqIvQd/2T3/+ay9QDjlvTOiBD3Yg6o9Urq5PaxjBL5Z9fu95UHdPQ21Aj7Exuk9fUQrvlbMpb0I0Z09cJwIvYt3Sj3qGOC9H9A9vcXe+D1xqOA8NSbHPRqAar3ptdy9n8j5PVB+Xz0Rstc8H4SUvXn+wb2KH4s9tBh0vScBlz1AKHq9JsGpvVQGZj1TR+A8DA9gPbER173oQ0+9+6jbPSVx4D0WSNw9YSrvvdfQDL5ACxA+NAfsu6fyXD11atG9zY/FvVEJjj28EZo98GcoPfzQMr1zXuq9IoSTPahGvz01z3g7ulMSvm+EjL2JKM8M 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 /QGoyPrz5FT/QMC6+GR1Qv/hnZr+P2ks/2j8AP7oKaj+uk6s/vgD1v2qizT4=", "training_traits": {"structure_gen": "Triangle", "n_layers": 4, "max_nodes": 5, "activation_func": "ReLU", "epoch_num": 6}, "classes_name": ["Cryptoadz", "Cryptopunks", "Moonbirds", "Nouns"]},m=25,b=50,y=59+11/12,w=59+11.5/12,v=60;function z(e,t){const n=Math.log(1-t)/Math.log(1-e);return e=>1-Math.pow(1-e,n)}class V{constructor(e,t,n){const{model:r,inputDim:i}=j(t,n);this.model=r,this.inputDim=i,this.iteration=0,this.stage=0;const o=new Date(parseInt(M e.birthYear),0,1).getTime(),a=new Date(parseInt(e.birthYear)+1,0,1).getTime();this.birthDate=new Date(Math.floor((o+a)/2));const l=zr.filter((t=>t[0]==e.lifeCycle))[0][2];this.growSpeed=365/l,this.cycleLength=60*l*24*3600*1e3,this.growthFunc=z(.4,.8)}updateAge(e){const t=(e.getTime()-this.birthDate.getTime())/31536e6*this.growSpeed;this.iteration=Math.floor(t/60);const n=t-60*this.iteration;let r;this.age=n;let i,o=0;if(n<25){let e=map(n,0,25,0,1);o=this.growthFunc(e),r=(25-n)/60,this.stage=1,this.stageRatio=map(n,M 0,25,0,1)}else n<50?(o=1,r=(50-n)/60,this.stage=2,this.stageRatio=map(n,25,50,0,1)):n<y?(o=map(n,50,y,1,0),r=(y-n)/60,this.stage=3,this.stageRatio=map(n,50,y,0,1)):n<w?(o=0,r=(w-n)/60,this.stage=4,this.stageRatio=map(n,y,w,0,1)):n<60&&(o=0,r=(60-n)/60,this.stage=5,this.stageRatio=map(n,w,60,0,1));n<50?i=map(n,0,50,0,780/880):n<w?i=map(n,50,w,780/880,800/880):n<60&&(i=map(n,w,60,800/880,1)),this.nextStateTimestamp=Math.round(e.getTime()+this.cycleLength*r),this.statePercentage=round(100*i);let a=(25-n)/60;a<0&&(a+=1M ),this.nextStableTimestamp=Math.round(e.getTime()+this.cycleLength*a),this.growth=o,this.model.updateNeurons(o,this.iteration)}getBrainStatus(){return{totalNeurons:this.model.getTotalNeurons(),neuronsLife:this.model.getNeuronsLife(),stage:this.stage,inputDim:this.inputDim,stageRatio:this.stageRatio,age:this.age,growth:this.growth,nextStateTimestamp:this.nextStateTimestamp,nextStableTimestamp:this.nextStableTimestamp,rebirthCount:max(this.iteration,0),statePercentage:this.statePercentage}}classifyImage(e){const t=neM w G(e,1,e.length);return this.model.forward(t).mat[0]}}class M{constructor(e,t,n,r,i){this.p=e,this.v=t,this.size=n,this.shape=i,this.col=r}getRadius(){return 1==Oe?1*this.size/2:2==Oe?7*this.size/16:3==Oe||4==Oe?4*this.size/7:0}update(){this.p.add(this.v)}draw(e,t,n,r){const i=this.p.x*r,o=this.p.y*r,a=this.size*r,{col:l,shape:s}=this;let h,c;1==n?h=c=l:2==n?(h=dr(t,1),c=l):(h=dr(t,0),c=dr(l,1));e.stroke(dr(c,map(1,0,1,.25,1))),e.fill(dr(h,map(1,0,1,.15,1))),3==n&&e.fill(dr(h,0)),1==s?e.ellipse(i,o,a,a):2==s?e.recM t(i,o,7*a/8,7*a/8):3==s&&(e.beginShape(),e.vertex(i-4*a/7,o),e.vertex(i,o-4*a/7),e.vertex(i+4*a/7,o),e.vertex(i,o+4*a/7),e.endShape(CLOSE))}}class E{constructor(e,t,n,r,i,o,a){this.center=e,this.len=t,this.angle=n,this.v=r,this.angV=i,this.c1=o,this.c2=a}getEndpoints(){const e=createVector(this.len/2*cos(this.angle),this.len/2*sin(this.angle));return[Vector.add(this.center,e),Vector.sub(this.center,e)]}update(){this.center.add(this.v),this.angle+=this.angV}draw(e,t){const[n,r]=this.getEndpoints(),i=n.x*t,o=n.y*t,a=M r.x*t,l=r.y*t,s=this.c1,h=this.c2;var c=e.drawingContext.createLinearGradient(i,o,a,l);c.addColorStop(0,s),c.addColorStop(1,h),e.drawingContext.strokeStyle=c,e.drawingContext.globalAlpha=1,e.line(i,o,a,l),e.drawingContext.globalAlpha=1}}function S(e,t){const n=random(TAU),r=random(e,t);return createVector(r*cos(n),r*sin(n))}class R{constructor(e,t,n,r,i){this.wall=n,this.maxR=i;const o=t.length;this.nodes=[];for(let a=0;a<o;++a){const o=[],l=.25*t[a];for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRightM ),random(n.yTop,n.yBottom)),l=S(.02*i,.05*i),s=random(10,25)*i;o.push(new M(t,l,s,e[a],r))}this.nodes.push(o)}const a=A(e);a.unshift(e[0]),a.push(e[e.length-1]),this.lines=[];for(let e=0;e<=o;++e){const r=[],l=(0==e?1:t[e-1])*(e==o?1:t[e])*1.5;for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),o=random(5*i,10*i),l=random(TAU),s=S(.02*i,.05*i),h=random(2e-4,.001);r.push(new E(t,o,l,s,h,a[e],a[e+1]))}this.lines.push(r)}}reflectNode(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=M this.wall,{p:o,v:a}=e,l=e.getRadius();(o.x-l<t&&a.x<0||o.x+l>r&&a.x>0)&&(a.x=-a.x),(o.y-l<n&&a.y<0||o.y+l>i&&a.y>0)&&(a.y=-a.y)}reflectLine(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,[o,a]=e.getEndpoints(),l=e.v;(min(o.x,a.x)<t&&l.x<0||max(o.x,a.x)>r&&l.x>0)&&(l.x=-l.x),(min(o.y,a.y)<n&&l.y<0||max(o.y,a.y)>i&&l.y>0)&&(l.y=-l.y)}update(){for(const e of this.lines)for(const t of e)t.update(),this.reflectLine(t);for(const e of this.nodes)for(const t of e)t.update(),this.reflectNode(t)}draw(e,t,n,r,i){const M o=i/this.maxR;for(const t of this.lines){const n=t.length*r;for(let r=0;r<n;++r)t[r].draw(e,o)}for(const i of this.nodes){const a=i.length*r;for(let r=0;r<a;++r)i[r].draw(e,t,n,o)}}}function I(e,t){re(e),e.fill(0),e.rect(0,0,500,500),ie(e),e.noStroke(),e.fill(dr(cr("#000000"),.5)),e.push(),e.translate(250,250),e.scale(t),e.translate(-250,-250),e.beginShape(),e.vertex(235.2,24.9),e.bezierVertex(215,24.6,185,11.4,164.8,11),e.bezierVertex(147.2,10.7,129.3,10.4,112.2,14.7),e.bezierVertex(95.1,19,78.5,28.5,69.6,43.8),e.M bezierVertex(57.699,64.199,61.599,90.199,70.199,112.2),e.bezierVertex(78.799,134.2,91.6,154.6,97.199,177.5),e.bezierVertex(102.499,199.2,100.899,222.5,92.799,243.2),e.bezierVertex(83,268,64.6,288.3,48.9,310),e.bezierVertex(33.2,331.7,24.5,337.5,26.599,364.1),e.bezierVertex(28.2,384.1,61.399,404.2,75.7,418.3),e.bezierVertex(90,432.4,73.7,488.2,91.9,496.7),e.bezierVertex(124.2,511.6,159,472.5,194.3,468.1),e.bezierVertex(211.6,465.9,267.4,501.5,283.9,495.9),e.bezierVertex(340.7,476.7,298.599,428.9,355.4,409.7),e.bezieM rVertex(370.799,404.5,454.5,407.6,464.4,394.8),e.bezierVertex(478.599,376.3,474.7,349.3,464.299,328.4),e.bezierVertex(453.9,307.5,438.099,289.5,428.699,268.2),e.bezierVertex(412,230,419,182.6,446.1,150.9),e.bezierVertex(449.7,146.7,453.6,142.7,455.8,137.6),e.bezierVertex(459.4,129.299,457.5,119.6,454.8,111),e.bezierVertex(443.2,73.4,417.3,40.4,383.6,20.299),e.bezierVertex(358.1,5,343.2,-.4,313.5,0),e.bezierVertex(287.5,.4,261.6,25.4,235.2,24.9),e.endShape(),e.pop()}function C(e,t,n,r,i,o){let a,l,s;re(t),t.fill(0),M t.rect(0,0,500,500),ie(t),t.noStroke(),t.fill(dr(n,.5)),1==i?(l=0,s=25,a=map(o,0,25,500,0)):a=0,t.rect(0,a,500,500),e.noStroke(),e.fill(r),e.rect(0,0,500,500),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203M .8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,1M 09),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104M .5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),e.fill(n),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7M ),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(M 43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.beziM erVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,4M 58.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),re(e),e.fill(r),e.beginShape(),e.vertex(184.3,473.2),e.bezierVertex(164,473.2,144.7,462.099,134,444.3),e.bezierVertex(131.7,440.5,129.1,438.5,125,437.1),e.bezierVertex(97.3,428.1,80.5,400.6,85.2,371.8),e.bezierVertex(86.3,365.1,85.8,364.1,79.9,361.2),e.bezierVertex(57.2,349.8,46.2,323.3,54.3,299.7),e.bezierVertex(54.7,298.599,55.1,297.7,55.5M ,296.9),e.bezierVertex(55.6,296.599,55.8,296.4,55.9,296.099),e.vertex(57.9,291.499),e.vertex(62.5,293.599),e.bezierVertex(64.9,294.7,67.3,295.799,69.5,296.9),e.bezierVertex(74.5,299.299,79.1,301.599,83.9,303.099),e.bezierVertex(89.8,304.9,96.5,305.499,102.7,305.9),e.bezierVertex(102.8,305.9,102.9,305.9,103,305.9),e.bezierVertex(106.6,305.9,108.9,302.799,109,299.799),e.bezierVertex(109.1,296.199,106.6,293.4,102.7,292.799),e.bezierVertex(101.3,292.599,99.9,292.4,98.4,292.299),e.bezierVertex(94.3,291.799,90.1,291.299,M 86,289.9),e.bezierVertex(68.9,284,56.5,270.2,52.7,252.799),e.bezierVertex(48.9,235.499,54.5,217.7,67.6,205.299),e.bezierVertex(71.9,201.299,72.7,198.1,70.8,192.399),e.bezierVertex(64.2,172.2,68.8,153.99,84.2,139.599),e.bezierVertex(94.2,130.199,105.5,125.399,117.8,125.399),e.bezierVertex(124.3,125.399,131.1,126.799,137.8,129.599),e.bezierVertex(157,137.399,167.9,152.799,169.4,173.99),e.vertex(169.4,174.399),e.bezierVertex(169.5,175.899,169.6,177.2,169.9,178.299),e.bezierVertex(170.7,181.2,173.2,183.2,176.1,183.2),eM .bezierVertex(176.299,183.2,176.5,183.2,176.7,183.2),e.bezierVertex(180.1,182.899,182.6,180.299,182.7,177),e.bezierVertex(183.1,162,178.299,148.2,168.399,136.1),e.bezierVertex(158.2,123.5,144.899,115.8,128.799,113.199),e.bezierVertex(123.499,112.299,120.399,109.799,118.899,104.99),e.bezierVertex(113.899,89.699,120.699,72.299,134.899,64.499),e.bezierVertex(139.99,61.699,145.799,60.199,151.7,60.199),e.bezierVertex(162.2,60.199,171.899,64.799,178.1,72.699),e.bezierVertex(179.6,74.6,180.799,76.6,181.9,78.499),e.vertex(M 182.2,79.099),e.bezierVertex(183.2,80.699,185.2,83.299,188.4,83.299),e.bezierVertex(189.5,83.299,190.6,82.99,191.7,82.399),e.bezierVertex(195.1,80.599,196,76.99,194,72.799),e.bezierVertex(190.1,64.799,184.1,58.499,175.6,53.299),e.bezierVertex(174.6,52.699,173.7,52.099,172.5,51.499),e.vertex(170.5,50.299),e.vertex(163,45.899),e.vertex(170.5,41.599),e.bezierVertex(182,34.99,193.1,30.799,204.4,28.599),e.bezierVertex(208.6,27.799,212.9,27.399,217.2,27.399),e.bezierVertex(217.6,27.399,217.9,27.399,218.3,27.399),e.bezierM Vertex(231.4,27.599,242.7,38.199,243,50.599),e.bezierVertex(243.4,64.899,243.3,78.99,243.2,93.799),e.bezierVertex(243.2,99.799,243.1,105.899,243.1,112.099),e.vertex(243.1,119.199),e.vertex(236.4,116.799),e.bezierVertex(235.7,116.499,235,116.299,234.4,115.99),e.bezierVertex(233.4,115.599,232.6,115.299,232,115.199),e.bezierVertex(230.6,114.899,229.2,114.599,227.8,114.299),e.bezierVertex(223.8,113.499,220.1,112.699,216.4,112.499),e.vertex(216.2,112.499),e.bezierVertex(212.5,112.499,210.7,115.599,210.6,118.599),e.bezieM rVertex(210.4,122.399,212.7,125.099,216.4,125.399),e.bezierVertex(230.1,126.399,238.9,133.099,242.3,145.199),e.bezierVertex(243.2,148.399,243.2,151.599,243.2,154.499),e.vertex(243.2,155.099),e.bezierVertex(243.2,254.199,243.2,330,243.2,400.599),e.bezierVertex(243.2,401.99,243.2,403.4,243.2,404.9),e.bezierVertex(243.3,411.099,243.3,417.599,242.3,423.9),e.bezierVertex(238.1,449.2,219.6,467.799,194,472.5),e.bezierVertex(190.9,472.9,187.6,473.2,184.3,473.2),e.endShape(),e.beginShape(),e.vertex(315.8,473.1),e.bezierVertM ex(309.3,473.1,302.8,472,296.5,469.9),e.bezierVertex(270.4,461,253.8,434.9,257.1,407.9),e.bezierVertex(260,384,273.8,366.8,297,358.3),e.bezierVertex(297.7,358.1,298.3,357.8,299,357.6),e.bezierVertex(299.8,357.3,300.6,357.1,301.2,356.8),e.bezierVertex(304.3,355.4,306,351.8,304.9,348.7),e.bezierVertex(304,345.9,301.7,344.2,299,344.2),e.bezierVertex(298.6,344.2,298.1,344.2,297.6,344.3),e.bezierVertex(288.1,346.3,279,350.9,269.7,358.3),e.bezierVertex(268.9,358.9,268.1,359.6,267.2,360.4),e.vertex(265.5,361.8),e.vertex(2M 58.5,367.6),e.vertex(257.4,358.6),e.bezierVertex(257.3,358,257.3,357.5,257.2,357.1),e.bezierVertex(257,356,256.9,354.9,256.9,353.7),e.bezierVertex(256.9,334.8,256.9,316,256.9,297.1),e.bezierVertex(256.9,260.3,256.9,222.3,256.8,185),e.bezierVertex(256.8,170.7,268.3,158.8,282.5,158.4),e.bezierVertex(284.8,158.3,286.7,157.6,287.9,156.2),e.bezierVertex(289.099,154.9,289.599,153.2,289.5,151.3),e.bezierVertex(289.3,147.5,286.7,145.1,282.7,145.1),e.bezierVertex(282.5,145.1,282.2,145.1,282,145.1),e.bezierVertex(278.8,145.3M ,275.5,146.1,272,146.9),e.bezierVertex(270.9,147.2,269.8,147.4,268.6,147.7),e.bezierVertex(267.9,147.9,267,148.2,265.8,148.7),e.bezierVertex(265.1,149,264.4,149.3,263.5,149.6),e.vertex(256.8,152),e.vertex(256.8,114.6),e.bezierVertex(256.8,95,256.8,75.4,256.8,55.9),e.bezierVertex(256.8,38,267.2,27.3,284.6,27.3),e.bezierVertex(285.3,27.3,285.9,27.3,286.6,27.3),e.bezierVertex(299,27.9,318.7,34.5,329.6,41.9),e.vertex(336.1,46.3),e.vertex(324.4,53.3),e.bezierVertex(316.2,58.2,310.2,64.6,306,72.9),e.bezierVertex(304.2,76M .4,305.1,78.5,306.1,80),e.bezierVertex(307.4,81.9,309.4,83,311.6,83),e.bezierVertex(313.7,83,315.7,81.9,317.1,80.1),e.bezierVertex(317.4,79.7,317.8,79,318.1,78.4),e.bezierVertex(318.4,77.9,318.7,77.3,319,76.8),e.bezierVertex(325.3,66.2,336.3,59.9,348.5,59.9),e.bezierVertex(353.2,59.9,357.8,60.8,362.1,62.7),e.bezierVertex(377.6,69.3,386,86.7,381.7,103.2),e.bezierVertex(380.7,107.1,378.5,111.8,371.1,113.1),e.bezierVertex(342.7,118.1,322.2,139.1,317.8,167.8),e.bezierVertex(317.4,170.3,317.3,173.2,317.4,176.5),e.bezierM Vertex(317.5,180,320.1,182.8,323.5,183),e.bezierVertex(323.6,183,323.8,183,323.9,183),e.bezierVertex(327.1,183,329.8,180.6,330.3,177.2),e.bezierVertex(330.6,175.7,330.7,174,330.9,172.3),e.bezierVertex(331.1,169.8,331.4,167.3,332,164.7),e.bezierVertex(337.3,141.9,357.7,125.4,380.7,125.4),e.bezierVertex(382.5,125.4,384.3,125.5,386.1,125.7),e.bezierVertex(412.8,128.9,432.6,150.9,432,176.9),e.bezierVertex(431.9,182.3,430.9,187.7,429.1,192.7),e.bezierVertex(427.2,197.9,428,201,432.3,205),e.bezierVertex(446.8,218.7,451.8M ,236,446.6,255),e.bezierVertex(441.4,274,428.3,286.5,408.7,291.3),e.bezierVertex(406.1,291.9,403.6,292.1,401.1,292.3),e.bezierVertex(400,292.4,398.9,292.5,397.9,292.6),e.bezierVertex(393.6,293.1,390.9,295.7,391,299.5),e.bezierVertex(391.1,303.4,394,305.8,398.5,305.8),e.bezierVertex(409.9,305.8,420.8,302.6,431.1,296.4),e.bezierVertex(431.8,296,432.5,295.5,433.2,295.1),e.bezierVertex(433.8,294.7,434.5,294.3,435.2,293.9),e.bezierVertex(436,293.4,436.6,293.2,437.2,293.1),e.bezierVertex(437.4,293,437.7,292.9,438.1,292.8M ),e.vertex(442.5,291.4),e.vertex(444.2,295.7),e.bezierVertex(450.9,312.4,449.5,328.4,440,343.4),e.bezierVertex(435.3,350.8,428.7,356.7,420.2,361.1),e.bezierVertex(414.3,364.1,413.7,365.2,414.8,371.7),e.bezierVertex(419.5,400.2,403,427.6,375.6,436.9),e.bezierVertex(371,438.5,368.3,440.7,365.8,444.7),e.bezierVertex(355.2,462.5,336.4,473.1,315.8,473.1),e.bezierVertex(315.8,473.1,315.8,473.1,315.8,473.1),e.endShape(),ie(e),e.fill(n),e.beginShape(),e.vertex(120.2,279.9),e.bezierVertex(117.9,279.9,112.4,279.299,112.2,273M .599),e.bezierVertex(112,267.7,117.4,266.7,119.7,266.599),e.bezierVertex(133.1,265.799,143.1,259.499,149.3,247.899),e.bezierVertex(149.6,247.299,150.1,246.399,150.3,245.399),e.bezierVertex(150.6,244.299,150.5,243.299,150.5,242.7),e.bezierVertex(150.5,242.6,150.5,242.5,150.5,242.299),e.vertex(150.3,238.799),e.vertex(141.1,235.99),e.bezierVertex(114.6,227.799,95.6,202.499,95.9,175.799),e.bezierVertex(95.9,173.99,96.4,168.199,102.2,168.199),e.bezierVertex(102.6,168.199,103,168.199,103.4,168.299),e.bezierVertex(104.8,1M 68.499,108.2,168.899,109.2,175.599),e.bezierVertex(109.3,176.599,109.5,177.599,109.6,178.499),e.bezierVertex(110.4,184.199,111.3,189.99,113.7,195.499),e.bezierVertex(121.9,213.99,139.5,225.499,159.7,225.499),e.bezierVertex(172.1,225.499,184.1,220.899,193.5,212.599),e.bezierVertex(194,212.199,194.4,211.799,194.8,211.399),e.bezierVertex(195.1,211.099,195.5,210.799,195.8,210.399),e.bezierVertex(197.4,208.99,199.2,208.2,200.9,208.2),e.bezierVertex(202.5,208.2,204,208.899,205.3,210.1),e.bezierVertex(208,212.9,207.9,216.M 9,205,219.9),e.bezierVertex(196.5,228.6,186.3,234.3,174.7,236.8),e.bezierVertex(168.799,238.1,165.6,241,163.899,246.7),e.bezierVertex(158.3,265.9,139.9,279.7,120.2,279.9),e.vertex(120.2,279.9),e.endShape(),e.beginShape(),e.vertex(187.2,427.5),e.bezierVertex(183.799,427.5,181.299,425.3,180.799,422),e.bezierVertex(180.6,420.8,180.499,419.5,180.399,418.1),e.bezierVertex(180.299,417,180.2,415.8,180.099,414.7),e.bezierVertex(177.199,390.5,156.699,371.3,132.399,370.2),e.bezierVertex(131.99,370.2,131.499,370.2,131.099,370M .2),e.bezierVertex(130.699,370.2,130.299,370.2,129.799,370.2),e.bezierVertex(125.99,369.9,123.199,367.2,123.099,363.6),e.bezierVertex(122.99,360.2,125.799,357.3,129.599,356.9),e.bezierVertex(130.499,356.8,131.499,356.8,132.599,356.7),e.bezierVertex(133.199,356.7,133.799,356.7,134.399,356.6),e.vertex(138.299,356.4),e.vertex(139.1,352.6),e.bezierVertex(139.5,350.7,139.799,348.9,140.2,347),e.bezierVertex(140.899,343.4,141.5,340,142.399,336.8),e.bezierVertex(150.099,310.7,174.399,292,201.399,291.3),e.vertex(201.599,291M .3),e.bezierVertex(203.699,291.3,206.299,292,208.299,293.2),e.bezierVertex(210.499,294.5,210.699,297.5,209.99,299.8),e.bezierVertex(209.499,301.5,208.199,303.9,203.299,304.7),e.bezierVertex(202.199,304.9,200.99,305,199.799,305.2),e.bezierVertex(194.499,305.9,188.99,306.599,183.799,308.9),e.bezierVertex(165.499,316.799,155.199,331.299,152.99,352),e.bezierVertex(152.399,357.8,154.499,361.7,159.699,364.5),e.bezierVertex(178.199,374.4,189.399,390,193.099,410.9),e.bezierVertex(193.699,414.299,193.899,418,193.599,422),e.M bezierVertex(193.399,425.2,190.899,427.5,187.399,427.5),e.vertex(187.2,427.5),e.endShape(),e.beginShape(),e.vertex(364.3,281.1),e.bezierVertex(346.3,280.6,332.9,272.8,323.5,257),e.bezierVertex(321.6,253.9,320.4,250.2,319.2,246.7),e.bezierVertex(317.7,242.2,315,239.799,310.5,238.799),e.bezierVertex(298.5,236.299,288,230.7,279.4,222.1),e.bezierVertex(276.7,219.4,274.9,215.299,278,211.9),e.bezierVertex(279.4,210.3,281,209.6,282.6,209.6),e.bezierVertex(284.4,209.6,286.4,210.6,288.3,212.5),e.bezierVertex(297.8,221.8,310M .4,226.9,323.9,226.9),e.bezierVertex(340.2,226.9,355.1,219.3,364.8,206.2),e.bezierVertex(371,197.8,374.2,188.5,374.5,178.5),e.vertex(374.5,177.9),e.bezierVertex(374.5,177,374.5,176.1,374.7,175.4),e.bezierVertex(375.3,171.8,377.9,169.5,381.3,169.5),e.bezierVertex(381.4,169.5,381.5,169.5,381.7,169.5),e.bezierVertex(385.4,169.7,388,172.4,388,176.1),e.bezierVertex(388.1,190.7,383.4,204,374.2,215.8),e.bezierVertex(365.8,226.5,354.7,233.9,341.2,237.9),e.bezierVertex(340,238.3,338.7,238.6,337.3,239.1),e.bezierVertex(335.9M ,239.6,335.1,240.4,334.7,240.9),e.bezierVertex(334.599,241,334.5,241.1,334.4,241.2),e.vertex(331.799,243.6),e.vertex(333.199,246.8),e.bezierVertex(338.199,258,346.799,264.9,358.699,267.3),e.bezierVertex(360.199,267.6,361.599,267.7,362.99,267.9),e.bezierVertex(363.599,268,364.299,268,364.899,268.1),e.bezierVertex(369.099,268.6,371.799,271.4,371.499,275),e.bezierVertex(371.199,278.6,368.299,281.2,364.399,281.2),e.vertex(364.3,281.1),e.endShape(),e.beginShape(),e.vertex(323.9,437),e.bezierVertex(323.7,437,323.5,437,32M 3.299,437),e.bezierVertex(319.599,436.7,317.299,434.1,317.4,430.2),e.bezierVertex(317.9,406.099,328.299,388,349.5,375),e.bezierVertex(350.7,374.2,352,373.5,353.4,372.8),e.bezierVertex(354.099,372.4,354.7,372.1,355.299,371.7),e.vertex(357.499,370.5),e.vertex(357.799,368),e.bezierVertex(360.4,346.6,345.199,323.7,323.9,317),e.bezierVertex(319.099,315.5,314.099,314.9,309.299,314.4),e.vertex(308.199,314.299),e.bezierVertex(305.99,314.099,300.799,312.9,300.899,307.299),e.bezierVertex(300.99,303.499,303.899,300.9,308.099,M 300.9),e.vertex(308.299,300.9),e.bezierVertex(327.099,301.299,343.099,308.7,355.699,322.9),e.bezierVertex(364.299,332.5,369.399,344.099,370.99,357.299),e.bezierVertex(371.099,358.4,371.299,359.4,371.499,360.499),e.bezierVertex(371.599,360.99,371.699,361.499,371.799,361.99),e.vertex(372.499,365.899),e.vertex(377.899,366.199),e.bezierVertex(378.799,366.299,379.699,366.299,380.599,366.399),e.bezierVertex(385.099,366.699,387.899,369.399,387.799,373.299),e.bezierVertex(387.699,377.099,384.99,379.599,380.799,379.799),e.bM ezierVertex(369.799,380.199,359.99,383.299,351.899,389.299),e.bezierVertex(338.799,398.799,331.699,411.699,330.699,427.499),e.vertex(330.699,428.299),e.bezierVertex(330.599,429.199,330.599,430.099,330.499,430.799),e.bezierVertex(330,434.7,327.5,437,323.9,437),e.endShape()}function T(e){return e[0].map(((t,n)=>e.map((e=>e[n]))))}function A(e){return e.map((e=>Array.isArray(e)?A(e):e))}function D(e,t){return floor(random(e,t))}function k(e){let t=0;for(const n of e)t+=n[1];let n=random(t),r=0;for(const t of e)if(r+=tM [1],n<r)return t[0];return null}function L(e){for(let t=1;t<e.length;++t){let n=D(0,t),r=e[t];e[t]=e[n],e[n]=r}}function P(e){return null==e||""===e}function O(e){return new Promise((t=>setTimeout(t,e)))}function F(e,t,n){let r=0;for(let i=1;i<=1e3;++i)for(let o=1;o<=1e3;++o)if(e*o%(t*i)==0){let e=1*i/o;abs(e-n)<abs(r-n)&&(r=e)}return r}function N(){let e=60*(new Date).getTimezoneOffset()*1e3;return new Date(Date.now()-e).toISOString().slice(0,-1)}function B(e,t,n){let r;if(push(),textSize(e),textWidth(t)<=n)r=t;elM se for(let e=0;e<t.length;++e){const i=t.slice(0,e+1)+"...";if(textWidth(i)>n){r=i;break}}return pop(),r}function Y(e){var t=e%10,n=e%100;return 1==t&&11!=n?e+"st":2==t&&12!=n?e+"nd":3==t&&13!=n?e+"rd":e+"th"}class G{constructor(e,t,n){this.n=t,this.m=n,this.mat=[];let r=0;for(let t=0;t<this.n;++t){this.mat.push([]);for(let n=0;n<this.m;++n)this.mat[t].push(r<e.length?e[r]:0),r+=1}return this}copy(){return new G(this.mat.flat(),this.n,this.m)}}class H{static __linear=e=>e;static __relu=e=>Math.max(e,0);static __leaM ky_relu=e=>e>0?e:.2*e;static __sigmoid=e=>1/(1+Math.exp(-e));static __tanh=e=>Math.tanh(e);static __apply_unary_op(e,t){const n=e.copy();for(let e=0;e<n.n;++e)for(let r=0;r<n.m;++r)n.mat[e][r]=t(n.mat[e][r]);return n}static linear=e=>H.__apply_unary_op(e,H.__linear);static relu=e=>H.__apply_unary_op(e,H.__relu);static leaky_relu=e=>H.__apply_unary_op(e,H.__leaky_relu);static sigmoid=e=>H.__apply_unary_op(e,H.__sigmoid);static tanh=e=>H.__apply_unary_op(e,H.__tanh);static __add=(e,t)=>e+t;static __mul=(e,t)=>e*t;staM tic __apply_binary_op=(e,t,n)=>{"object"!=typeof t&&(t=new G([t],1,1));const r=e.copy();for(let e=0;e<r.n;++e)for(let i=0;i<r.m;++i)r.mat[e][i]=n(r.mat[e][i],t.mat[e%t.n][i%t.m]);return r};static mul=(e,t)=>H.__apply_binary_op(e,t,H.__mul);static add=(e,t)=>H.__apply_binary_op(e,t,H.__add);static matMul(e,t){const n=new G([],e.n,t.m);for(let r=0;r<n.n;++r)for(let i=0;i<n.m;++i)for(let o=0;o<e.m;++o)n.mat[r][i]+=e.mat[r][o]*t.mat[o][i];return n}static softmax(e){const t=H.__apply_unary_op(e,(e=>Math.exp(e))),n=t.matM .flat().reduce(((e,t)=>e+t));for(let r=0;r<e.n;++r)for(let i=0;i<e.m;++i)t.mat[r][i]/=n;return t}}class ${constructor(e,t){this.scale=e,this.offset=t}forward(e){return H.add(H.mul(e,this.scale),this.offset)}}class X{constructor(){}forward(e){return e.map((e=>e.flat()))}}class W{constructor(e,t,n,r){this.out_dim=e,this.activation=t,this.w=n,this.b=r}forward(e){const t=H.add(H.matMul(e,this.w),this.b);return null==this.activation?t:this.activation(t)}}class U{constructor(e,t,n){this.preprocessLayers=e,this.hiddenLayeM rs=t,this.outputLayer=n,this.totalNeurons=this.hiddenLayers.map((e=>e.out_dim)),this.currentOrders=[],this.currentIteration=null}updateNeurons(e,t){if(t!=this.currentIteration){this.currentOrders=[];for(let e=0;e<this.totalNeurons.length;++e){randomSeed(100*(t+1)+e);const n=[];for(let t=0;t<this.totalNeurons[e];++t)n.push(t);L(n),this.currentOrders.push(n)}this.currentIteration=t}const n=A(this.totalNeurons),r=n.reduce(((e,t)=>e+t))*(1-e);for(let e=0;e<r;++e){const t=n.map(((e,t)=>(e-1)/this.totalNeurons[t]));n[t.mM ap(((e,t)=>[e,t])).reduce(((e,t)=>t[0]>e[0]?t:e))[1]]-=Math.min(r-e,1)}this.neuronsLife=[];for(let e=0;e<n.length;++e){const t=this.currentOrders[e],r=Array(this.totalNeurons[e]).fill(0);for(let i=0;i<n[e];++i)r[t[i]]=Math.min(n[e]-i,1);this.neuronsLife.push(r)}}getTotalNeurons(){return A(this.totalNeurons)}getNeuronsLife(){return A(this.neuronsLife)}forward(e){for(const t of this.preprocessLayers)e=t.forward(e);for(const[t,n]of this.hiddenLayers.entries()){e=n.forward(e);const r=new G(this.neuronsLife[t],1,e.m);e=M H.mul(e,r)}return e=this.outputLayer.forward(e),H.softmax(e)}}function q(e){switch(e){case"relu":return H.relu;case"sigmoid":return H.sigmoid;case"tanh":return H.tanh;case"leaky_relu":return H.leaky_relu;default:return H.linear}}function j(e,t){const n=[],r=[],i=Z(t);let o=null,a=0,l=[];for(const t of e.config.layers)if("InputLayer"==t.class_name)o=t.config.batch_input_shape.slice(1),l=o;else if("Rescaling"==t.class_name)n.push(new $(t.config.scale,t.config.offset));else if("Flatten"==t.class_name)o=[o.reduce(((e,tM )=>e*t))];else if("Dense"==t.class_name){const e=[t.config.units],n=o[0]*e[0],l=e[0],s=i.subarray(a,a+n);a+=n;const h=i.subarray(a,a+l);a+=l;const c=new G(s,o[0],e[0]),u=new G(h,1,e[0]),f=q(t.config.activation);r.push(new W(e[0],f,c,u)),o=e}const s=r.pop();return{model:new U(n,r,s),inputDim:l}}function Z(e){const t=window.atob(e),n=t.length/Float32Array.BYTES_PER_ELEMENT,r=new DataView(new ArrayBuffer(Float32Array.BYTES_PER_ELEMENT)),i=new Float32Array(n);let o=0;for(let e=0;e<n;e++){o=4*e;for(let e=0;e<4;++e)r.setM Uint8(e,t.charCodeAt(o+e));i[e]=r.getFloat32(0,!0)}return i}class K{constructor(e){this.elt=e,this._events={},this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight}position(){if(0===arguments.length)return{x:this.elt.offsetLeft,y:this.elt.offsetTop};var e="absolute";return"static"!==arguments[2]&&"fixed"!==arguments[2]&&"relative"!==arguments[2]&&"sticky"!==arguments[2]&&"initial"!==arguments[2]&&"inherit"!==arguments[2]||(e=arguments[2]),this.elt.style.position=e,this.elt.style.left=arguments[0]+"px",tM his.elt.style.top=arguments[1]+"px",this.x=arguments[0],this.y=arguments[1],this}show(){return this.elt.style.display="block",this}hide(){return this.elt.style.display="none",this}size(e,t){if(0===arguments.length)return{width:this.elt.offsetWidth,height:this.elt.offsetHeight};var n=e,r=t;if(n!==te||r!==te){if(n===te?n=t*this.width/this.height:r===te&&(r=e*this.height/this.width),this.elt instanceof HTMLCanvasElement){var i,o={},a=this.elt.getContext("2d");for(i in a)o[i]=a[i];for(i in this.elt.setAttribute("width"M ,n*this._pInst._pixelDensity),this.elt.setAttribute("height",r*this._pInst._pixelDensity),this.elt.style.width=n+"px",this.elt.style.height=r+"px",this._pInst.scale(this._pInst._pixelDensity,this._pInst._pixelDensity),o)this.elt.getContext("2d")[i]=o[i]}else this.elt.style.width=n+"px",this.elt.style.height=r+"px",this.elt.width=n,this.elt.height=r;this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight,this._pInst&&this._pInst._curElement&&this._pInst._curElement.elt===this.elt&&(this._pInst._setPropertyM ("width",this.elt.offsetWidth),this._pInst._setProperty("height",this.elt.offsetHeight))}return this}style(e,t){if(t instanceof Color&&(t="rgba("+t.levels[0]+","+t.levels[1]+","+t.levels[2]+","+t.levels[3]/255+")"),void 0===t){if(-1===e.indexOf(":"))return window.getComputedStyle(this.elt).getPropertyValue(e);for(var n=e.split(";"),r=0;r<n.length;r++){var i=n[r].split(":");i[0]&&i[1]&&(this.elt.style[i[0].trim()]=i[1].trim())}}else if(this.elt.style[e]=t,"width"===e||"height"===e||"left"===e||"top"===e){var o=windoM w.getComputedStyle(this.elt).getPropertyValue(e).replace(/[^\d.]/g,"");this[e]=Math.round(parseFloat(o,10))}return this}value(){return arguments.length>0?(this.elt.value=arguments[0],this):"range"===this.elt.type?parseFloat(this.elt.value):this.elt.value}mouseClicked(e){return this._adjustListener("click",e,this),this}isFocused(){return document.activeElement===this.elt}_adjustListener(e,t,n){return!1===t?this._detachListener(e,n):this._attachListener(e,t,n),this}_attachListener(e,t,n){n._events[e]&&this._detachLisM tener(e,n);var r=t.bind(n);n.elt.addEventListener(e,r,!1),n._events[e]=r}_detachListener(e,t){var n=t._events[e];t.elt.removeEventListener(e,n,!1),t._events[e]=null}}function J(e,t){var n=document.createElement("button");return n.innerHTML=e,t&&(n.value=t),ee(n)}function Q(e){var t=arguments.length>1&&void 0!==arguments[1]&&arguments[1],n=function(t){var n=!0,r=!1,i=void 0;try{for(var o,a=t.target.files[Symbol.iterator]();!(n=(o=a.next()).done);n=!0){var l=o.value;File._load(l,e)}}catch(e){r=!0,i=e}finally{try{n||nM ull==a.return||a.return()}finally{if(r)throw i}}};if(window.File&&window.FileReader&&window.FileList&&window.Blob){var r=document.createElement("input");return r.setAttribute("type","file"),t&&r.setAttribute("multiple",!0),r.addEventListener("change",n,!1),ee(r)}}function ee(e){return document.body.appendChild(e),new K(e)}createImg=function(){var e,t=document.createElement("img"),n=arguments;return n.length>1&&"string"==typeof n[1]&&(t.alt=n[1]),n.length>2&&"string"==typeof n[2]&&(t.crossOrigin=n[2]),t.src=n[0],e=eM e(t,this),t.addEventListener("load",(function(){e.width=t.offsetWidth||t.width,e.height=t.offsetHeight||t.height;var r=n[n.length-1];"function"==typeof r&&r(e)})),e},createInput=function(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:"",t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:"text",n=document.createElement("input");return n.setAttribute("value",e),n.setAttribute("type",t),ee(n,this)};const te="auto";function ne(e){re(e);const t=e._rectMode;e.rectMode(CORNER),e.rect(0,0,e.width,e.heM ight),e.rectMode(t),ie(e)}function re(e){e.push(),e.fill(255,255,255,255),e.blendMode(REMOVE)}function ie(e){e.blendMode(BLEND),e.pop()}File=function(e,t){this.file=e,this._pInst=t;var n=e.type.split("/");this.type=n[0],this.subtype=n[1],this.name=e.name,this.size=e.size,this.data=void 0},File._createLoader=function(e,t){var n=new FileReader;return n.onload=function(n){var r=new File(e);if("application/json"===r.file.type)r.data=JSON.parse(n.target.result);else if("text/xml"===r.file.type){var i=(new DOMParser).parM seFromString(n.target.result,"text/xml");r.data=new XML(i.documentElement)}else r.data=n.target.result;t(r)},n},File._load=function(e,t){if(/^text\//.test(e.type)||"application/json"===e.type)File._createLoader(e,t).readAsText(e);else if(/^(video|audio)\//.test(e.type)){var n=new File(e);n.data=URL.createObjectURL(e),t(n)}else File._createLoader(e,t).readAsDataURL(e)},XML=function(e){if(e)this.DOM=e;else{var t=document.implementation.createDocument(null,"doc");this.DOM=t.createElement("root")}},document.addEventLisM tener("DOMContentLoaded",(function(){addEventListener("mousemove",(e=>{window.mouseX=e.pageX,window.mouseY=e.pageY}))})),new e("global");const oe="89";let ae,le,se,he,ce,ue,fe,de,xe,ge,pe,me,be,ye,we,ve,ze,Ve,_e,Me,Ee,Se,Re,Ie,Ce,Te,Ae,De,ke,Le,Pe,Oe,Fe,Ne,Be,Ye,Ge,He,$e,Xe,We,Ue,qe,je,Ze,Ke,Je,Qe,et,tt,nt,rt,it,ot,at,lt,st,ht,ct,ut,ft,dt,xt,gt,pt,mt,bt,yt,wt,vt,zt,Vt,_t,Mt,Et,St,Rt,It,Ct,Tt,At=!1,Dt=!1,kt=!0,Lt=!1,Pt=!1;const Ot=[" ","Growing","Stable","Decaying","Dead","Rebirth"];let Ft,Nt,Bt,Yt,Gt,Ht,$t,Xt,Wt,UtM ,qt,jt,Zt,Kt,Jt,Qt,en,tn,nn,rn,on,an,ln,sn,hn=0,cn=0,un=0,fn=!1,dn=!0,xn=!0,gn=null,pn=null,mn=null,bn=!1,yn=!1,wn=null,vn=null,zn=!1;async function setup(){let e=windowWidth,t=windowHeight;createCanvas(e,t),et=createGraphics(e,t),Xe=createGraphics(e,t),$e=createGraphics(e,t),We=createGraphics(e,t),Ue=createGraphics(e,t),qe=createGraphics(e,t),Qe=createGraphics(e,t),je=createGraphics(e,t),Ze=createGraphics(e,t),Ke=createGraphics(e,t),Je=createGraphics(e,t),tt=createGraphics(500,500),nt=createGraphics(500,500),rt=crM eateGraphics(500,500),_n(),Mn(),Sn(),await En(),Gn(),Rn(),bn=!0}function _n(){Et=parseInt(oe),randomSeed(Et),noiseSeed(Et)}function Mn(){Wt=Ir(p.training_traits),Cr(Wt)}async function En(){let e;Jt=r(),Qt=o(),[Xt,e]=await Promise.all([s(Jt),h(Qt)]),Ut=new V(Wt.visual,e.layers_config,e.weight_b64),Ut.updateAge(new Date),_n(),Wt.training=e.training_traits,Ht=e.model_name,$t=e.classes_name}function Sn(){le=min(width,height)/1024,ut=Rr.findIndex((e=>e[0]===Wt.visual.colorPalette)),ft=[["#ffffff","#231f20","#231f20"],["M #231f20","#ffffff","#ffffff"],["#104da8","#ffffff","#ffffff"],["#722F1F","#FCE1B2","#FCE1B2"],["#e88120","#f9f2e5","#f9f2e5"],["#f6b941","#2E2E2E","#2E2E2E"],["#45daaa","#012221","#012221"],["#F1F1F1","#328DFE","#328DFE"],["#111822","#D3EB8D","#D3EB8D"],["#713FF9","#D6D5E6","#D6D5E6"],["#FBDA9D","#795106","#795106"],["#8f5b62","#ead0d0","#ead0d0"],["#eae4cb","#508cac","#508cac"],["#ffc6cc","#cc313d","#cc313d"],["#60A900","#E0FE00","#E0FE00"],["#507DBE","#D0D1D3","#D0D1D3"],["#305848","#E8F2EE","#E8F2EE"],["#2a2634"M ,"#5b6988","#cb78a2","#5b6988"],["#590e29","#fd5e53","#fd5e53","#ffe373"],["#0a141d","#57d4e4","#328195","#2A9ECF","#0ab6a8","#57d4e4"],["#3a2d28","#d5c2ac","#df6338","#3d9895","#d5c2ac"],["#030706","#77c4d9","#77c4d9","#77c4d9","#ffffff","#ffffff","#e72020","#e72020"],["#3a4664","#92f5ff","#f9ff94","#eaa0a2","#55dde0"],["#fbfaff","#f04bb1","#f04bb1","#fac373","#82cef0","#8b31ce"],["#000000","#ffffff","#ff0002","#f26522","#fdff00","#00ff03","#01fffe","#0000ff","#ff00ff"]];for(let e=0;e<ft.length;++e)for(let t=0;t<fM t[e].length;++t)ft[e][t]=cr(ft[e][t]);pt=[],ct=ft[ut][0],st=ft[ut][1]}function Rn(){gn=document.querySelector("#upload"),pn=document.querySelector("#inputUpload"),gn.addEventListener("dblclick",(()=>{if(!Lt&&!yn)if(In(Ie)&&cn==Ve-1)pn.click();else{if(4!=Pe&&5!=Pe&&(In(Ie)||cn!=Ve-1))return;fn=!0,dn=!0,Bt=0,un=0}})),pn.addEventListener("click",(()=>{pn.value=null,gn.style.display="block"})),pn.addEventListener("change",(()=>{const[e]=pn.files;e?(se=null,gn.style.display="none",Tn(URL.createObjectURL(e)),mn=e):gn.styM le.display="block"}))}function In(e){for(let t=0;t<e.length;++t){let n=0;for(let r=0;r<e[t].length;++r)e[t][r]>0&&++n;if(0==n)return!1}return!0}function Cn(){null!=se&&(un=0,Pt=!0,he=0,ue=0,drewLineAnim=!0,ce=(ae/2+we/2)/le,loadImage(se.elt.src,(e=>{const[t,n,r]=Gt,i=createGraphics(t,n);i.image(e,0,0,t,n),i.loadPixels();const o=i.pixels.filter(((e,t)=>t%4!=3)),a=Ut.classifyImage(o);Zt=T([a,$t.map((e=>e.toUpperCase()))]).sort(((e,t)=>e[0]>t[0]?-1:1))})))}function Tn(e){se=createImg(e,""),se.hide(),Cn()}function An()M {zn||(ce+=(width-ae-we)/tn/le),re(Xe),Xe.rect(ce*le,0,width,height),ie(Xe),un>=ge&&1==kt&&(kt=!1,un-=ge),kt&&(re($e),$e.strokeWeight(2*Fe),Jn(he,ze,ct,ct,$e),ie($e)),un>=ge&&0==kt&&(kt=!0,un-=ge,he+=1,he==en&&(++ue,he=0,ce=(ae/2+we/2)/le,1==ue&&(Pt=!1,Dn(),ye=millis())))}function Dn(){At=!0,pe=!1,me=!1,tryButton=br("Try Again",width/2-225*le,height/2+265*le,290*le,40*le,kn),closeResultButton=br("Close",width/2+75*le,height/2+265*le,150*le,40*le,Ln)}function kn(){At=!1,tryButton.hide(),closeResultButton.hide(),pn.clM ick()}function Ln(){Yt=!0,At=!1,Gn(),tryButton.hide(),closeResultButton.hide(),gn.style.display="block",se=null}function keyTyped(){bn&&!1===yn&&!1===yr()&&("i"!==key&&"I"!==key||(Dt=!Dt),"b"!==key&&"B"!==key||(xn=!xn),"s"!==key&&"S"!==key||!1!==Lt||saveCanvasAtCurrentTime(),"k"!==key&&"K"!==key||!1!==Lt||save4KCanvasAtCurrentTime(),"u"!==key&&"U"!==key||!1!==Lt||!1!==At||!1!==fn||!1!==Pt||On())}function On(){Lt=!0,wn=null,vn=null,submitButton=br("Submit",width/2-155*le,height/2+115*le,150*le,40*le,Fn),closeSettingM Button=br("Close",width/2+5*le,height/2+115*le,150*le,40*le,Yn),vt=createInput(),vt.position(width/2-252.5*le,height/2-40*le),vt.size(500*le,25*le),vt.style("font-size","15px"),vt.value(Jt||""),zt=createInput(),zt.position(width/2-252.2*le,height/2+35*le),zt.size(500*le,25*le),zt.style("font-size","15px"),zt.value(Qt||"")}function Fn(){Vt=vt.value(),_t=zt.value(),submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide(),Lt=!1,yn=!0,Nn()}async function Nn(){[wn,vn,_]=await Promise.all([c(Vt),u(_t),O(1e3)]),yM n=!1,wn&&vn?(n(Vt),i(_t),window.location.reload()):(Lt=!0,submitButton.show(),closeSettingButton.show(),vt.show(),zt.show())}function Bn(){Je.textFont("Trebuchet MS"),Je.noStroke(),pr(Je,600*le,200*le),Je.strokeWeight(1*le),Je.stroke(xt),Je.fill(xt),Je.textSize(50*le),Je.text("update()",width/2,height/2+2.5*le)}function Yn(){wn=null,vn=null,Lt=!1,submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide()}function Gn(){_n(),nn=Date.now(),pe=!1,me=!1,St=Wt.training.structure_gen,Rt=Wt.visual.birthYear,It=Wt.viM sual.lifeCycle,Ct=Wt.training.epoch_num,Tt=Wt.training.activation_func,Ft=Mr.findIndex((e=>e[0]==Wt.visual.hardwareAcceleration))+1,1==Ft?(Nt=30,fe=40):2==Ft?(Nt=15,fe=20):(Nt=2,fe=10);const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vM r(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),ae=100*le,ht=50*le,Oe=Sr.findIndex((e=>e[0]==Wt.visual.nodeShape))+1,dt=Er.findIndex((e=>e[0]==Wt.visual.nodeFill))+1,lt=_r.findIndex((e=>e[0]==Wt.visual.pattern))+1,de=Math.tanh(Math.log10(Xt.avgfeerate)),de=map(de,0,1,.2,.8),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);forM (let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&M &Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/M Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,at=.7,pt=[],xt=ft[ut][2],gt=ft[ut][ft[ut].length-1];for(let e=3;e<ft[ut].length-1;e++)pt.push(ft[ut][e]);mt=sr(xt,gt,pt,width),bt=[],wt=[],yt=width/(Ve-1);for(let e=0;e<Ve;e++)bt.push(hr(mt,yt*e/width)),wt.push(hr(mt,yt*e/width));wt.unshift(bt[0]),wt.push(bt[bt.length-1]),hn=0,cn=0,un=0,Yt=!0;const n={xLeft:ae/8,xRight:width-ae/8,yTop:ae/8,yBottom:height-ae/8},r=Ce.map((e=>e.length));jt=new R(bt,r,n,Oe,le)}function Hn(e,t){let n=Ce[e].length;return[e*we+weM /2+ae/2,height/2-(n-1)/2*ve+t*ve]}function $n(e,t){le=min(e,t)/1024,ae=100*le,ht=50*le,we=(e-ae)/Ve,ve=(t-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}xe=floor(De.length*de),Le=[],ke=[],ge=floor(map(de,.2,.8,15,2));for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,mt=sr(xtM ,gt,pt,e),bt=[],wt=[],yt=e/(Ve-1);for(let t=0;t<Ve;t++)bt.push(hr(mt,yt*t/e)),wt.push(hr(mt,yt*t/e));wt.unshift(bt[0]),wt.push(bt[bt.length-1])}function Xn(){const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebM irthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,rM =min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=HnM (e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le}function Wn(){jt.update();const e=4==Pe?0:Kt;jt.draw(Qe,ct,dt,e,le)}function Un(){if(!bn)return ar(),void et.image(je,0,0);if(4==Pe||5==Pe)return Wn(),void et.image(Qe,0,0);un>=Nt&&hn<Ve&&(hn++,M un=0);for(let e=0;e<hn;e++)1==dt?it=ot=bt[e]:(it=ct,ot=bt[e]),Kn(e,it,ot,$e);un>=Nt&&cn<Ve-1&&(cn++,un=0);for(let e=0;e<cn;e++)Zn(e)}function qn(){et.background(ct),Ue.background(255),Ue.rectMode(CENTER),ne(Ue),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),Ue.stroke(st),Ue.strokeWeight(8*le),Ue.fill(ct),Qe.background(255),Qe.rectMode(CENTER),ne(Qe),Qe.strokeWeight(le),qe.background(255),qe.rectMode(CENTER),ne(qe),qe.textAlign(LEFT),$e.background(255),$e.rectMode(CENTER),ne($e),Xe.background(255),ne(Xe),Xe.strokeWeM ight(Ne),We.background(255),We.rectMode(CENTER),ne(We),We.fill(st),We.stroke(st),We.strokeWeight(.1*le),er(lt),We.noStroke(),xn&&(We.rect(ae/16,height/2,ae/8,height),We.rect(width-ae/16,height/2,ae/8,height),We.rect(width/2,ae/16,width,ae/8),We.rect(width/2,height-ae/16,width,ae/8)),Ze.background(255),Ze.rectMode(CENTER),ne(Ze),Ze.textAlign(CENTER,CENTER),Ze.textStyle(BOLD),Ze.stroke(st),Ze.strokeWeight(8*le),Ze.fill(ct),je.background(255),je.rectMode(CENTER),ne(je),je.textAlign(CENTER,CENTER),je.textStyle(BOLD),KeM .background(255),Ke.rectMode(CENTER),ne(Ke),Ke.textAlign(CENTER,CENTER),Ke.textStyle(BOLD),Ke.stroke(st),Ke.strokeWeight(8*le),Ke.fill(ct),Je.background(255),Je.rectMode(CENTER),ne(Je),Je.textAlign(CENTER,CENTER),Je.textStyle(BOLD),Je.stroke(st),Je.strokeWeight(8*le),Je.fill(ct),Un(),et.image(We,0,0),Pt&&An(),et.image(Xe,0,0),et.image($e,0,0),At&&(tr(),et.image(Ue,0,0)),fn&&(lr(),et.image(Ze,0,0)),Lt&&(or(),et.image(Ke,0,0)),Dt&&(ir(),et.image(qe,0,0)),yn&&(Bn(),et.image(Je,0,0))}function draw(){const e=Date.now();M bn&&(Ut.updateAge(new Date(e)),Xn()),qn(),image(et,0,0),zn||un++}function Zn(e){let t,n=Ce[e].length,r=Ce[e+1].length;for(let i=0;i<n;i++){const[n,o]=Hn(e,i);for(let a=0;a<r;a++){const[r,l]=Hn(e+1,a);t=map(min(Ce[e][i],Ce[e+1][a]),0,1,0,.5),ur(n,o,r,l,bt[e],bt[e+1],Xe,t)}}}function Kn(e,t,n,r){let i,o,a,l=Ce[e].length;for(let s=0;s<l;s++){const[l,h]=Hn(e,s);i=Ce[e][s],a=map(Be,1/30,1,3,10),o=map(Ce[e][s],0,1,2*a,0)*le,o<1.5*le&&(o=0),Qn(l,h,ze,Oe,t,n,o,i,r)}}function Jn(e,t,n,r,i){for(let o=0;o<Le[e].length;o++)Qn(M Le[e][o][0],Le[e][o][1],t,Oe,n,r,0,1,i)}function Qn(e,t,n,r,i,o,a,l,s){s.stroke(dr(o,map(l,0,1,.25,1))),s.fill(dr(i,map(l,0,1,.15,1))),s.strokeWeight(Fe),fr([a],s),3==dt&&s.fill(dr(i,0)),1==r?s.ellipse(e,t,n):2==r?s.rect(e,t,7*n/8,7*n/8):3==r&&(s.beginShape(),s.vertex(e-4*n/7,t),s.vertex(e,t-4*n/7),s.vertex(e+4*n/7,t),s.vertex(e,t+4*n/7),s.endShape(CLOSE))}function er(e){if(1==e);else if(2==e){We.strokeWeight(1*le);for(let e=ht/4;e<width+ht/4;e+=ht)for(let t=ht/4;t<height+ht/4;t+=ht)We.point(e,t)}else if(3==e){ht=2M 5*le;for(let e=ht/2;e<height+ht/2;e+=ht)We.line(0,e,width,e);for(let e=ht/2;e<width+ht/2;e+=ht)We.line(e,0,e,height)}}function tr(){Ue.textFont("Trebuchet MS"),Ue.textAlign(LEFT,CENTER),Ue.noStroke(),pr(Ue,800*le,500*le),Ue.noStroke(),Ue.fill(dr(st,.75)),Ue.rect(width/2,height/2-100*le,800*le,300*le,25*le,25*le,0,0),Ue.fill(st),Ue.rect(width/2-250*le,height/2-100*le,225*le,225*le),Ue.image(se.elt,width/2-357.5*le,height/2-207.5*le,215*le,215*le);let e=100*Zt[0][0];Ue.fill(ct),Ue.textSize(25*le),Ue.textStyle(NORMAL)M ,1==me&&(e>=0&&e<20?Ue.text("I have a feeling this image belongs to",width/2-100*le,height/2-170*le):e>=20&&e<40?Ue.text("I have a hunch this image belongs to",width/2-100*le,height/2-170*le):e>=40&&e<60?Ue.text("I think this image belongs to",width/2-100*le,height/2-170*le):e>=60&&e<80?Ue.text("I'm almost certain this image belongs to",width/2-100*le,height/2-170*le):Ue.text("I'm positive this image belongs to",width/2-100*le,height/2-170*le));let t=e.toFixed(2);"100.00"==t&&(t="100"),1==me&&Ue.text("I'm "+t+"% coM nfident that I'm right!",width/2-100*le,height/2-25*le),example=Zt.map((e=>e[1])),be=Ue.textWidth('"FIDENZAAAA"'),defaultPhrase=Ue.textWidth('"PERPENDICULAR INHABITATION"'),Ue.textStyle(BOLD);const n=me?example[0]:random(example);if(1===n.split(" ").length){let e=75*be/Ue.textWidth('"'+n+'"');e>75&&(e=75),Ue.textSize(e*le),Ue.text('"'+n+'"',width/2-100*le,height/2-90*le)}else nr(width/2-100*le,height/2-90*le,460*le,110*le,n,Ue);if(millis()-ye>1500&&(me=!0),C(tt,nt,st,ct,Pe,Mt),Ue.image(nt,width/2-370*le,height/2+70M *le,80*le,80*le),3==Pe){let e;e=map(Mt,50,60,.25,1.3),I(rt,e),Ue.image(rt,width/2-370*le,height/2+70*le,80*le,80*le)}let r,i;Ue.image(tt,width/2-370*le,height/2+70*le,80*le,80*le),Ue.fill(xt),Ue.textSize(40*le),Ue.text("INTELLIGENCE INFO",width/2-275*le,height/2+115*le),Ue.textSize(18*le),Ue.textStyle(NORMAL),Ue.circle(width/2-360*le,height/2+180*le,7.5*le),1==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s growing and getting smarter by the day.`:2==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. M s stable and it has reached peak performance.`:3==Pe&&(r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s decaying and losing its luster.`),i=2==Pe?"The Perceptron remains stable for some time before entering the decay phase.":`Wait until ${new Date(an).toLocaleString("en-US")} for your Perceptron to reach its peak performance.`,Ue.text(r,width/2-350*le,height/2+180*le),Ue.circle(width/2-360*le,height/2+210*le,7.5*le),Ue.text(i,width/2-350*le,height/2+210*le),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLDM ),gr(Ue,width/2-225*le,width/2+65*le,height/2+265*le,height/2+305*le,"SELECT ANOTHER IMAGE"),gr(Ue,width/2+75*le,width/2+225*le,height/2+265*le,height/2+305*le,"CLOSE")}function nr(e,t,n,r,i,o){let a=i.split(" "),l=75*be/o.textWidth('"'+i+'"'),s=0,h=[],c=[],u=[],f="",d="";if(l>=50)l>75&&(l=75),o.textSize(l*le),o.text('"'+i+'"',e,t);else if(l<50){if(l=50*defaultPhrase/o.textWidth('"'+i+'"'),l>30){if(l>50&&(l=50),[f,d]=rr(l,n,s,h,c,a,f,d,Ue),0==c.length)return o.textSize(l*le),void o.text('"'+i+'"',e,t);for(s=0,h=[],M c=[];o.textWidth(d)>n/le;)l=l*n/le/o.textWidth(d),f="",d="",[f,d]=rr(l,n,s,h,c,a,f,d,Ue)}else{l=30,o.textSize(l);for(let e=0;e<a.length;e++)s+=o.textWidth(" "+a[e]),s<=n/le?h.push(a[e]):s>n/le&&s<=n/le*2?c.push(a[e]):u.push(a[e]);for(let e=1;e<h.length;e++)f=f+" "+h[e];if(f='"'+h[0]+f,0==u.length){for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+c[c.length-1]+'"'}else if(1==c.length)d="... "+u[u.length-1]+'"';else{for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+"... "+u[u.length-1]+'"'}}o.textSize(l*le);let r=1.25*(o.teM xtDescent()+o.textAscent());o.text(f,e,t-r/2),o.text(d,e,t+r/2)}}function rr(e,t,n,r,i,o,a,l,s){s.textSize(e);for(let e=0;e<o.length;e++)(n+=s.textWidth(" "+o[e]))<=t/le?r.push(o[e]):i.push(o[e]);for(let e=1;e<r.length;e++)a=a+" "+r[e];if(a='"'+r[0]+a,0==i.length&&(a+='"',l=""),1==i.length)l=i[i.length-1]+'"';else{for(let e=0;e<i.length-1;e++)l=l+i[e]+" ";l=l+i[i.length-1]+'"'}return[a,l]}function ir(){const e=45*le;qe.textFont("Tahoma"),qe.stroke(st),qe.strokeWeight(2*le),qe.fill(ct),qe.rect(width/2,e/2+height-87.M 5*le,600*le,90*le),qe.fill(st),qe.rect(width/2-150*le,e+height-170*le,300*le,30*le),qe.fill(ct),qe.rect(width/2+150*le,e+height-170*le,300*le,30*le),qe.noStroke(),qe.fill(ct),qe.textSize(15*le),qe.textStyle(BOLD),qe.text("PERCEPTRON INFORMATION",width/2-285*le,e+height-165*le),qe.fill(xt),qe.text("ARTWORK NAME:",width/2+10*le,e+height-165*le),qe.textAlign(RIGHT),qe.textStyle(ITALIC),qe.text("Perceptron #"+Et,width/2+285*le,e+height-165*le);const[t,n]=It.split(" ");let r;"60 Years"===It?r="1 Year":"60 Months"===It?rM ="1 Month":"60 Weeks"===It?r="1 Week":"60 Days"===It?r="1 Day":"12 Hours"===It&&(r="12 Minutes"),data=[["AI MODEL NAME:",B(12*le,Ht,140*le)],["SCALE:","1:"+Te],["NUMBER OF CLASSES:",$t.length],["BIRTH YEAR:",Rt],["NUMBER OF REBIRTHS:",sn.toString()],["AGE:",`${Math.ceil(Mt)} Perceptron Years`],["ONE PERCEPTRON YEAR:",`${r}`],["STATE:",Ot[Pe]],["ACTIVE NEURONS:",`${round(ln*rn)} / ${ln}`],["NEXT STATE TIME:",vr(new Date(on))]],qe.fill(xt);const i=data.length/2;for(let t=0;t<data.length;++t){const n=t<i,r=n?width/2-2M 85*le:width/2+10*le,o=n?width/2-10*le:width/2+285*le,a=e+height-(135-t%i*15)*le;qe.textStyle(BOLD),qe.textAlign(LEFT),qe.textSize(12*le),qe.text(data[t][0],r,a),qe.textStyle(ITALIC),qe.textAlign(RIGHT),qe.textSize(12*le),qe.text(data[t][1],o,a)}}function or(){Ke.textFont("Trebuchet MS"),Ke.noStroke(),pr(Ke,600*le,200*le),gr(Ke,width/2-155*le,width/2-5*le,height/2+115*le,height/2+155*le,"UPDATE"),gr(Ke,width/2+5*le,width/2+155*le,height/2+115*le,height/2+155*le,"CLOSE"),Ke.textAlign(LEFT),Ke.fill(xt),Ke.text("UPDATEM BITCOIN FULL NODE ADDRESS",width/2-252.5*le,height/2-55*le),Ke.text("UPDATE MODEL ADDRESS",width/2-252.5*le,height/2+20*le),Ke.textAlign(RIGHT),Ke.textStyle(ITALIC),Ke.textSize(15*le),0==wn&&Ke.text("(*) Invalid Address",width/2+252.5*le,height/2-53*le),0==vn&&Ke.text("(*) Invalid Model",width/2+252.5*le,height/2+23*le)}function ar(){je.textFont("Trebuchet MS"),je.fill(st),je.textSize(50*le),je.stroke(st),je.strokeWeight(1*le),je.text("main()",width/2,height/2)}function lr(){un>=20&&1==dn&&(dn=!1,un=0),dn&&(Ze.texM tFont("Trebuchet MS"),Ze.stroke(st),Ze.fill(ct),Ze.rect(width/2,height/2,600*le,150*le,25*le),Ze.fill(xt),Ze.textSize(75*le),Ze.noStroke(),1==Pe?Ze.text("GROWING",width/2,height/2+5*le):3==Pe?Ze.text("AGING",width/2,height/2+5*le):4==Pe?Ze.text("DEAD",width/2,height/2+5*le):5==Pe&&Ze.text("BIRTH",width/2,height/2+5*le)),un>=20&&0==dn&&(dn=!0,un=0,Bt++,3==Bt&&(fn=!1))}function sr(e,t,n,r){let i=[],o=r/(n.length+1),a=color(e),l=color(t);i.push(a);for(let e=0;e<n.length;e++){let t=color(n[e]);for(let e=1;e<=o;e++){letM n=lerpColor(a,t,e/o);i.push(n)}a=t}for(let e=1;e<o;e++){let t=lerpColor(a,l,e/o);i.push(t)}if(i.push(l),i.length>r)i.splice(r);else if(i.length<r){let e=i[i.length-1];for(;i.length<r;)i.push(e)}return i}function hr(e,t){let n=e.length,r=Math.floor(t*n);return r>=n&&(r=n-1),e[r]}function cr(e){e=e.replace("#","");var t=parseInt(e,16);return color(t>>16&255,t>>8&255,255&t)}function ur(e,t,n,r,i,o,a,l){var s=a.drawingContext.createLinearGradient(e,t,n,r);s.addColorStop(0,i),s.addColorStop(1,o),a.drawingContext.strokeM Style=s,a.drawingContext.globalAlpha=l,a.line(e,t,n,r),a.drawingContext.globalAlpha=1}function fr(e,t){t.drawingContext.setLineDash(e)}function dr(e,t){let n=color(e),r=red(n),i=green(n),o=blue(n);return color(r,i,o,255*t)}function xr(e,t,n,r){return mouseX>e&&mouseX<t&&mouseY>n&&mouseY<r}function gr(e,t,n,r,i,o){e.strokeWeight(1*le),e.stroke(st);const[a,l]=xr(t,n,r,i)?[xt,ct]:[ct,xt];e.fill(a),e.push(),e.rectMode(CORNERS),e.rect(t,r,n,i,5*le),e.pop(),e.noStroke(),e.textSize(20*le),e.fill(l),e.text(o,(t+n)/2,(46*r+M 54*i)/100)}function pr(e,t,n){e.fill(0,0,0,75),e.rect(width/2,height/2,width,height),e.stroke(st),e.fill(ct),e.rect(width/2,height/2,t,n,25*le)}function mr(e,t){resizeCanvas(e,t,!0),Xe.resizeCanvas(e,t,!0),$e.resizeCanvas(e,t,!0),We.resizeCanvas(e,t,!0),Ue.resizeCanvas(e,t,!0),qe.resizeCanvas(e,t,!0),Qe.resizeCanvas(e,t,!0),je.resizeCanvas(e,t,!0),Ze.resizeCanvas(e,t,!0),Ke.resizeCanvas(e,t,!0),Je.resizeCanvas(e,t,!0),et.resizeCanvas(e,t,!0)}function br(e,t,n,r,i,o){const a=J(e);return a.position(t,n),a.size(r,i),aM .style("opacity","0"),a.mouseClicked(o),a}function yr(){return null!=vt&&vt?.isFocused()||null!=zt&&zt?.isFocused()}function wr(e,t,n,r){let i;if(e<=3){i=`Hey ${String.fromCodePoint(128075)}, I'm ${n}, ${t} years old. I can detect ${r.length} NFT collections: `;let e=0;for(let t=0;t<r.length;++t){const n=r[t];if(e+n.length>500){i+=", etc";break}t==r.length-1?i+=", and ":t>0&&(i+=", "),i+=n,e+=n.length}i+=". ",t<=5?i+="However, I am only a baby, so my recognition ability is not accurate. I'm in the state of Growing M both looks and intelligence.":t<=13?i+="I am now a child. My recognition ability is becoming better, but still not very accurate. I'm in the state of Growing both looks and intelligence.":t<=25?i+="I have grown up to be a teen. My recognition ability almost reaches the peak, but I will still mess up sometimes. I'm in the state of Growing both looks and intelligence.":t<=50?i+="I finally reach adulthood. My recognition is fully functional now. I'm in the Stable state, where I am the most intelligent with all neuronsM activated.":t<=60&&(i+="I am now an old Perceptron, so my recognition ability is no longer the best. I'm in the Decaying state, meaning that my neurons are dying, and my intelligence is decreasing over time.")}else 4==e?i=`${n} is Dead. However, this is not the end to its story...`:5==e&&(i=`${n} is now in the Rebirth state, and is preparing to start a new life.`);return i}function vr(e){const t=e.getDate(),n=e.toLocaleString("en-US",{month:"long"}),r=e.getFullYear();let i=e.getHours().toString();1==i.length&&(i="M 0"+i);let o=e.getMinutes().toString();return 1==o.length&&(o="0"+o),`${Y(t)} ${n} ${r} | ${i}:${o}`}saveCanvasAtCurrentTime=()=>{save(N())},save4KCanvasAtCurrentTime=()=>{const e=width,t=height,n=min(4096/min(e,t),1e4/max(e,t)),r=e*n,i=t*n;mr(r,i),zn=!0,$n(r,i),qn();let o="4K_"+N()+".png";saveCanvas(et,o),mr(e,t),$n(e,t),zn=!1};const zr=[["60 Years",3,365],["60 Months",40,30],["60 Weeks",37,7],["60 Days",20,1]],Vr=[["1943",1],["1951",1.5],["1957",2],["1969",2.5],["1970",3],["1980",3.5],["1982",4],["1986",4.5],["198M 8",5],["1997",5.5],["1998",6],["2002",6.5],["2009",7],["2012",7.5],["2014",8],["2015",8.5],["2016",9],["2023",15]],_r=[["Plain",20],["Dotted",40],["Squared",40]],Mr=[["Basic",30],["Standard",60],["Advanced",10]],Er=[["MNIST",70],["CIFAR",25],["IMAGENET",5]],Sr=[["Theano",60],["Torch",30],["TensorFlow",10]],Rr=[["Whitepaper",2],["Blackboard",2],["Blueprint",2],["Nak",74/14],["Jims",74/14],["Level 10",74/14],["Flips",74/14],["Level 14",74/14],["III",74/14],["XMB",74/14],["Info",74/14],["Adventure",74/14],["Marigold",M 74/14],["Phoenix",74/14],["Love",74/14],["Cachet",74/14],["Human",74/14],["Twilight",3],["Sunset",3],["Aurora",3],["Liminal Space",3],["D Vu",3],["Lucid Dream",3],["Parallel",1],["Multiverse",1]];function Ir(e){for(let e=0;e<100;++e)random(1);return{visual:{pattern:k(_r),hardwareAcceleration:k(Mr),nodeFill:k(Er),nodeShape:k(Sr),colorPalette:k(Rr),lifeCycle:k(zr),birthYear:k(Vr)},training:e}}function Cr(e){window.$generativeTraits={"Network Architecture":e.training.structure_gen,"Hidden Layers":e.training.n_layM ers,"Max Neurons Per Hidden Layer":e.training.max_nodes,"Activation Function":e.training.activation_func,"Training Epochs":e.training.epoch_num,Dataset:e.visual.nodeFill,"Deep Learning Framework":e.visual.nodeShape,"Hardware Acceleration":e.visual.hardwareAcceleration,"Paper Pattern":e.visual.pattern,"Life Cycle":e.visual.lifeCycle,"Birth Year":e.visual.birthYear,"Color Palette":e.visual.colorPalette}} <script defer src="https://static.cloudflareinsights.com/beacon.min.js/v2b4487d741ca48dcbadcaf954eM0 159fc61680799950996" integrity="sha512-D/jdE0CypeVxFadTejKGTzmwyV10c1pxZk/AqjJuZbaJwGMyNHY3q/mTPWqMUnFACfCTunhZUVcd4cV78dK1pQ==" data-cf-beacon='{"rayId":"7b4cfa4399b0a1e6","version":"2023.3.0","b":1,"token":"6c07c178c94442f695e7a0a2aaee641a","si":100}' crossorigin="anonymous"></script> text/plain;charset=utf-8 ({"p":"sns","op":"reg","name":" XMP DataXMP<?xpacket begin=" " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 7.1-c000 79.ccf84e0, 2022/06/22-22:13:26 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:xmpMM="http://ns.adobe.com/xap/1.0/mm/" xmlns:stRef="http://ns.adobe.com/xap/1.0/sType/ResourceRef#" xmp:CreatorTool="Adobe Photoshop 22.5 (Windows)" xmpMM:InstaM nceID="xmp.iid:9B55C5B9D62811EDBABAA8C2C69743D7" xmpMM:DocumentID="xmp.did:9B55C5BAD62811EDBABAA8C2C69743D7"> <xmpMM:DerivedFrom stRef:instanceID="xmp.iid:9B55C5B7D62811EDBABAA8C2C69743D7" stRef:documentID="xmp.did:9B55C5B8D62811EDBABAA8C2C69743D7"/> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> ~}|{zyxwvutsrqponmlkjihgfedcba`_^]\[ZYXWVUTSRQPONMLKJIHGFEDCBA@?>=<;:98765432M text/plain;charset=utf-8 text/plain;charset=utf-8 ({"p":"sns","op":"reg","name":" text/plain;charset=utf-8 ({"p":"sns","op":"reg","name":" text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"JEUS","amt":"777"}h! Compressed by jpeg-recompress text/html;charset=utf-8 <meta charset="utf-8" /> position: relative; width: var(--width); height: var(--height); border: 1px solid blue; position: relative; <div id="upload"> <input id="inputUpload" type="file"> function e(e){"use strict";return new function e(t){let n="global"==t?window:this;n.canvas=document.createElement("canvas");let r=n.canvas.getContext("2d");n.width=100,n.height=100,n.canvas.width=n.width,n.canvas.height=n.height,"offscreen"!=t&&(document.body?document.body.appendChild(n.canvas):window.addEventListener("load",(function(){document.body.appendChild(n.canvas)}))),g(),n.MAGIC=161533525,n.RGB=0,n.HSV=1,n.HM SB=1,n.CHORD=0,n.PIE=1,n.OPEN=2,n.RADIUS=1,n.CORNER=2,n.CORNERS=3,n.ROUND="round",n.SQUARE="butt",n.PROJECT="square",n.MITER="miter",n.BEVEL="bevel",n.CLOSE=1,n.BLEND="source-over",n.REMOVE="destination-out",n.ADD="lighter",n.DARKEST="darken",n.LIGHTEST="lighten",n.DIFFERENCE="difference",n.SUBTRACT="subtract",n.EXCLUSION="exclusion",n.MULTIPLY="multiply",n.SCREEN="screen",n.REPLACE="copy",n.OVERLAY="overlay",n.HARD_LIGHT="hard-light",n.SOFT_LIGHT="soft-light",n.DODGE="color-dodge",n.BURN="color-burn",n.NORMAL="norM mal",n.ITALIC="italic",n.BOLD="bold",n.BOLDITALIC="italic bold",n.CENTER="center",n.LEFT="left",n.RIGHT="right",n.TOP="top",n.BOTTOM="bottom",n.BASELINE="alphabetic",n.LANDSCAPE="landscape",n.PORTRAIT="portrait",n.ALT=18,n.BACKSPACE=8,n.CONTROL=17,n.DELETE=46,n.DOWN_ARROW=40,n.ENTER=13,n.ESCAPE=27,n.LEFT_ARROW=37,n.OPTION=18,n.RETURN=13,n.RIGHT_ARROW=39,n.SHIFT=16,n.TAB=9,n.UP_ARROW=38,n.HALF_PI=Math.PI/2,n.PI=Math.PI,n.QUARTER_PI=Math.PI/4,n.TAU=2*Math.PI,n.TWO_PI=2*Math.PI,n.THRESHOLD=1,n.GRAY=2,n.OPAQUE=3,n.INVEM RT=4,n.POSTERIZE=5,n.DILATE=6,n.ERODE=7,n.BLUR=8,n.ARROW="default",n.CROSS="crosshair",n.HAND="pointer",n.MOVE="move",n.TEXT="text",n.VIDEO={video:!0,audio:!1},n.AUDIO={video:!1,audio:!0},n.SHR3=1,n.LCG=2,n.HARDWARE_FILTERS=!0,n.hint=function(e,t){n[e]=t},n.frameCount=0,n.mouseX=0,n.mouseY=0,n.pmouseX=0,n.pmouseY=0,n.mouseButton=null,n.keyIsPressed=!1,n.mouseIsPressed=!1,n.key=null,n.keyCode=null,n.pixels=null,n.accelerationX=0,n.accelerationY=0,n.accelerationZ=0,n.rotationX=0,n.rotationY=0,n.rotationZ=0,n.relRotatM ionX=0,n.relRotationY=0,n.relRotationZ=0,n.pAccelerationX=0,n.pAccelerationY=0,n.pAccelerationZ=0,n.pRotationX=0,n.pRotationY=0,n.pRotationZ=0,n.pRelRotationX=0,n.pRelRotationY=0,n.pRelRotationZ=0,n.touches=[],n._styleCache=[{colorMode:n.RGB,noStroke:!1,noFill:!1,ellipseMode:n.CENTER,rectMode:n.CORNER,curveDetail:20,curveAlpha:0,textFont:"sans-serif",textSize:12,textLeading:12,textStyle:"normal"}],n._style=n._styleCache[n._styleCache.length-1],n._noLoop=!1,n._pixelDensity=1,n._frameRate=null,n._tint=null;let i=nullM ,o=!0,a=[],l=null,s=0,h={},c=0,u=null,f=null,d=null;Object.defineProperty(n,"deviceOrientation",{get:function(){return 90==Math.abs(window.orientation)?n.LANDSCAPE:n.PORTRAIT}}),Object.defineProperty(n,"windowWidth",{get:function(){return window.innerWidth}}),Object.defineProperty(n,"windowHeight",{get:function(){return window.innerHeight}}),Object.defineProperty(n,"drawingContext",{get:function(){return r}}),n.createCanvas=function(e,t){return n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t,g(),n.canvas},nM .resizeCanvas=function(e,t){n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t},n.createGraphics=n.createImage=function(t,n){let r=new e("offscreen");return r.createCanvas(t,n),r.noLoop(),r},n.pixelDensity=function(e){return null==e||(n._pixelDensity=e,n.canvas.width=Math.ceil(n.width*e),n.canvas.height=Math.ceil(n.height*e),n.canvas.style.width=n.width+"px",n.canvas.style.height=n.height+"px",r.scale(n._pixelDensity,n._pixelDensity),g()),n._pixelDensity},n.map=function(e,t,n,r,i,o){let a=r+1*(e-t)/(n-t)*(i-r)M ;return o?r<i?Math.min(Math.max(a,r),i):Math.min(Math.max(a,i),r):a},n.lerp=function(e,t,n){return e*(1-n)+t*n},n.constrain=function(e,t,n){return Math.min(Math.max(e,t),n)},n.dist=function(){return 4==arguments.length?Math.hypot(arguments[0]-arguments[2],arguments[1]-arguments[3]):Math.hypot(arguments[0]-arguments[3],arguments[1]-arguments[4],arguments[2]-arguments[5])},n.norm=function(e,t,r){return n.map(e,t,r,0,1)},n.sq=function(e){return e*e},n.fract=function(e){return e-Math.floor(e)},n.degrees=function(e){retM urn 180*e/Math.PI},n.radians=function(e){return e*Math.PI/180},n.abs=Math.abs,n.ceil=Math.ceil,n.exp=Math.exp,n.floor=Math.floor,n.log=Math.log,n.mag=Math.hypot,n.max=Math.max,n.min=Math.min,n.round=Math.round,n.sqrt=Math.sqrt,n.sin=Math.sin,n.cos=Math.cos,n.tan=Math.tan,n.asin=Math.asin,n.acos=Math.acos,n.atan=Math.atan,n.atan2=Math.atan2,n.Vector=function(e,t,r){let i=this;i.x=e||0,i.y=t||0,i.z=r||0;let o=null,a=null;function l(e,t,n){return null!=e.x?e:null!=t?{x:e,y:t,z:n||0}:{x:e,y:e,z:e}}function s(){null==a&M &(a=i.x*i.x+i.y*i.y+i.z*i.z,o=Math.sqrt(a))}function h(){a=null,o=null}i.set=function(e,t,n){i.x=e||0,i.y=t||0,i.z=n||0},i.copy=function(){return new n.Vector(i.x,i.y,i.z)},i.add=function(){let e=l.apply(null,arguments);return i.x+=e.x,i.y+=e.y,i.z+=e.z,h(),i},i.rem=function(){let e=l.apply(null,arguments);return i.x%=e.x,i.y%=e.y,i.z%=e.z,h(),i},i.sub=function(){let e=l.apply(null,arguments);return i.x-=e.x,i.y-=e.y,i.z-=e.z,h(),i},i.mult=function(){let e=l.apply(null,arguments);return i.x*=e.x,i.y*=e.y,i.z*=e.z,hM (),i},i.div=function(){let e=l.apply(null,arguments);return i.x/=e.x,i.y/=e.y,i.z/=e.z,h(),i},i.mag=function(){return s(),o},i.magSq=function(){return s(),a},i.dot=function(){let e=l.apply(null,arguments);return i.x*e.x+i.y*e.y+i.z*e.z},i.dist=function(){let e=l.apply(null,arguments),t=i.x-e.x,n=i.y-e.y,r=i.z-e.z;return Math.sqrt(t*t+n*n+r*r)},i.cross=function(){let e=l.apply(null,arguments),t=i.y*e.z-i.z*e.y,n=i.z*e.x-i.x*e.z,r=i.x*e.y-i.y*e.x;return i.x=t,i.y=n,i.z=r,h(),i},i.normalize=function(){s();let e=o;retuM rn i.x/=e,i.y/=e,i.z/=e,o=1,a=1,i},i.limit=function(e){s();if(o>e){let t=e/o;i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e}return i},i.setMag=function(e){s();let t=e/o;return i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e,i},i.heading=function(){return Math.atan2(i.y,i.x)},i.rotate=function(e){let t=Math.cos(e),n=Math.sin(e),r=i.x*t-i.y*n,o=i.x*n+i.y*t;return i.x=r,i.y=o,i},i.angleBetween=function(){let e=l.apply(null,arguments);const t=i.dot(e)/(i.mag()*e.mag());let n;return n=Math.acos(Math.min(1,Math.max(-1,t))),n*Math.sign(i.cross(e).z||1)},M i.lerp=function(e,t){return i.x=i.x*(1-t)+e.x*t,i.y=i.y*(1-t)+e.y*t,i.z=i.z*(1-t)+e.z*t,h(),i},i.reflect=function(e){return e.normalize(),i.sub(e.mult(2*i.dot(e)))},i.array=function(){return[i.x,i.y,i.z]},i.equals=function(e,t){return null==t&&null==(t=Number.EPSILON)&&(t=0),Math.abs(e.x-i.x)<t&&Math.abs(e.y-i.y)<t&&Math.abs(e.z-i.z)<t},i.fromAngle=function(e,t){return null==t&&(t=1),o=t,a=t*t,i.x=t*Math.cos(e),i.y=t*Math.sin(e),i.z=0,i},i.fromAngles=function(e,t,n){null==n&&(n=1),o=n,a=n*n;const r=Math.cos(t),l=MaM th.sin(t),s=Math.cos(e),h=Math.sin(e);return i.x=n*h*l,i.y=-n*s,i.z=n*h*r,i},i.random2D=function(){return o=1,a=1,i.fromAngle(Math.random()*Math.PI*2)},i.random3D=function(){return o=1,a=1,i.fromAngles(Math.random()*Math.PI*2,Math.random()*Math.PI*2)},i.toString=function(){return`[${i.x}, ${i.y}, ${i.z}]`}},n.Vector.add=function(e,t){return new n.Vector(e.x+t.x,e.y+t.y,e.z+t.z)},n.Vector.rem=function(e,t){return new n.Vector(e.x%t.x,e.y%t.y,e.z%t.z)},n.Vector.sub=function(e,t){return new n.Vector(e.x-t.x,e.y-t.y,e.M z-t.z)},n.Vector.mult=function(e,t){return null==t.x?new n.Vector(e.x*t,e.y*t,e.z*t):new n.Vector(e.x*t.x,e.y*t.y,e.z*t.z)},n.Vector.div=function(e,t){return null==t.x?new n.Vector(e.x/t,e.y/t,e.z/t):new n.Vector(e.x/t.x,e.y/t.y,e.z/t.z)},n.Vector.dist=function(e,t){return Math.hypot(e.x-t.x,e.y-t.y,e.z-t.z)},n.Vector.cross=function(e,t){return new n.Vector(e.y*t.z-e.z*t.y,e.z*t.x-e.x*t.z,e.x*t.y-e.y*t.x)},n.Vector.lerp=function(e,t,r){return new n.Vector(e.x*(1-r)+t.x*r,e.y=e.y*(1-r)+t.y*r,e.z=e.z*(1-r)+t.z*r)},n.M Vector.equals=function(e,t,n){return e.equals(t,n)};for(let e of["fromAngle","fromAngles","random2D","random3D"])n.Vector[e]=function(t,r,i){return(new n.Vector)[e](t,r,i)};function x(e,t,n){let r,i,o,a,l,s,h,c,u;if(0==t)return[255*(r=n),255*(i=n),255*(o=n)];switch((a=e)>360&&(a=0),h=n*(1-t),c=n*(1-t*(s=(a/=60)-(l=~~a))),u=n*(1-t*(1-s)),l){case 0:r=n,i=u,o=h;break;case 1:r=c,i=n,o=h;break;case 2:r=h,i=n,o=u;break;case 3:r=h,i=c,o=n;break;case 4:r=u,i=h,o=n;break;default:r=n,i=h,o=c}return[255*r,255*i,255*o]}functioM n g(){r.fillStyle="white",r.strokeStyle="black",r.lineCap="round",r.lineJoin="miter"}function p(e){if(0<=e&&e<2*Math.PI)return e;for(;e<0;)e+=2*Math.PI;for(;e>=Math.PI;)e-=2*Math.PI;return e}function m(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;let c=p(a),u=p(l);r.beginPath();for(let a=0;a<h+1;a++){let l=a/h,s=n.lerp(c,u,l),f=Math.cos(s)*i/2,d=Math.sin(s)*o/2;r[a?"lineTo":"moveTo"](e+f,t+d)}s==n.CHORD?r.closePath():s==n.PIE&&(r.lineTo(e,t),r.closePath()),n._style.noFill||r.fill(),n._style.noStrokM e||r.stroke()}function b(e,t,i,o){n._style.noFill&&n._style.noStroke||(r.beginPath(),r.ellipse(e,t,i/2,o/2,0,0,2*Math.PI),n._style.noFill||r.fill(),n._style.noStroke||r.stroke())}function y(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;if(null==a)return function(e,t,i,o){n._style.noFill||r.fillRect(e,t,i,o),n._style.noStroke||r.strokeRect(e,t,i,o)}(e,t,i,o);if(null==l)return y(e,t,i,o,a,a,a,a);const c=Math.min(Math.abs(o),Math.abs(i))/2;a=Math.min(c,a),l=Math.min(c,l),h=Math.min(c,h),s=Math.min(c,s)M ,r.beginPath(),r.moveTo(e+a,t),r.arcTo(e+i,t,e+i,t+o,l),r.arcTo(e+i,t+o,e,t+o,s),r.arcTo(e,t+o,e,t,h),r.arcTo(e,t,e+i,t,a),r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke()}function w(){a=[]}n.createVector=function(e,t,r){return new n.Vector(e,t,r)},n.curvePoint=function(e,t,n,r,i){const o=i*i*i,a=i*i;return e*(-.5*o+a-.5*i)+t*(1.5*o-2.5*a+1)+n*(-1.5*o+2*a+.5*i)+r*(.5*o-.5*a)},n.bezierPoint=function(e,t,n,r,i){const o=1-i;return Math.pow(o,3)*e+3*Math.pow(o,2)*i*t+3*o*Math.pow(i,2)*n+Math.pow(i,M 3)*r},n.curveTangent=function(e,t,n,r,i){const o=i*i;return e*(-3*o/2+2*i-.5)+t*(9*o/2-5*i)+n*(-9*o/2+4*i+.5)+r*(3*o/2-i)},n.bezierTangent=function(e,t,n,r,i){const o=1-i;return 3*r*Math.pow(i,2)-3*n*Math.pow(i,2)+6*n*o*i-6*t*o*i+3*t*Math.pow(o,2)-3*e*Math.pow(o,2)},n.Color=function(e,t,n,r){let i=this;i.MAGIC=786698,i._r=e,i._g=t,i._b=n,i._a=r,i._h=0,i._s=0,i._v=0,i._hsvInferred=!1,i.setRed=function(e){i._r=e,i._hsvInferred=!1},i.setGreen=function(e){i._g=e,i._hsvInferred=!1},i.setBlue=function(e){i._b=e,i._hsvInfM erred=!1},i.setAlpha=function(e){i._a=e/255,i._hsvInferred=!1},i._inferHSV=function(){i._hsvInferred||([i._h,i._s,i._v]=function(e,t,n){let r,i,o,a,l;return r=e<t?e<n?e:n:t<n?t:n,0==(l=100*(i=e>t?e>n?e:n:t>n?t:n)/255)?[o=0,a=0,l]:0==(a=100*(i-r)/i)?[o=0,a,l]:(o=i==e?0+60*(t-n)/(i-r):i==t?120+60*(n-e)/(i-r):240+60*(e-t)/(i-r),[o,a,l])}(i._r,i._g,i._b),i._hsvInferred=!0)},i.toString=function(){return`rgba(${Math.round(i._r)},${Math.round(i._g)},${Math.round(i._b)},${~~(1e3*i._a)/1e3})`}},n.colorMode=function(e){n._stM yle.colorMode=e},n.color=function(){if(1==arguments.length&&786698==arguments[0].MAGIC)return arguments[0];if(n._style.colorMode==n.RGB){if(1==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],1);if(2==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],arguments[1]/255);if(3==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],1);if(4==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],arguments[3]/255)}else{if(1==argumeM nts.length)return new n.Color(...x(0,0,arguments[0]/100),1);if(2==arguments.length)return new n.Color(...x(0,0,arguments[0]/100),arguments[1]/255);if(3==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),1);if(4==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),arguments[3])}return null},n.red=function(e){return e._r},n.green=function(e){return e._g},n.blue=function(e){return e._b},n.alpha=function(e){return 255*e._a},n.hue=function(e){reM turn e._inferHSV(),e._h},n.saturation=function(e){return e._inferHSV(),e._s},n.brightness=function(e){return e._inferHSV(),e._v},n.lightness=function(e){return 100*(.2126*e._r+.7152*e._g+.0722*e._b)/255},n.lerpColor=function(e,t,r){return n._style.colorMode==n.RGB?new n.Color(n.constrain(n.lerp(e._r,t._r,r),0,255),n.constrain(n.lerp(e._g,t._g,r),0,255),n.constrain(n.lerp(e._b,t._b,r),0,255),n.constrain(n.lerp(e._a,t._a,r),0,1)):(e._inferHSV(),t._inferHSV(),new n.Color(n.constrain(function(e,t,r){var i=[[Math.abs(t-M e),n.map(r,0,1,e,t)],[Math.abs(t+360-e),n.map(r,0,1,e,t+360)],[Math.abs(t-360-e),n.map(r,0,1,e,t-360)]];return i.sort(((e,t)=>e[0]-t[0])),(i[0][1]+720)%360}(e._h,t._h,r),0,360),n.constrain(n.lerp(e._s,t._s,r),0,100),n.constrain(n.lerp(e._v,t._v,r),0,100),n.constrain(n.lerp(e._a,t._a,r),0,1)))},n.strokeWeight=function(e){n._style_noStroke=!1,r.lineWidth=e},n.stroke=function(){if(n._style.noStroke=!1,"string"==typeof arguments[0])return void(r.strokeStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._sM tyle.noStroke=!0:r.strokeStyle=e},n.noStroke=function(){n._style.noStroke=!0},n.fill=function(){if(n._style.noFill=!1,"string"==typeof arguments[0])return void(r.fillStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._style.noFill=!0:r.fillStyle=e},n.noFill=function(){n._style.noFill=!0},n.blendMode=function(e){r.globalCompositeOperation=e},n.strokeCap=function(e){r.lineCap=e},n.strokeJoin=function(e){r.lineJoin=e},n.ellipseMode=function(e){n._style.ellipseMode=e},n.rectMode=function(e){n._style.rectM Mode=e},n.curveDetail=function(e){n._style.curveDetail=e},n.curveAlpha=function(e){n._style.curveAlpha=e},n.curveTightness=function(e){n._style.curveAlpha=e},n.clear=function(){r.clearRect(0,0,n.width,n.height)},n.background=function(){if(arguments[0]&&arguments[0].MAGIC==n.MAGIC)return n.image(arguments[0],0,0,n.width,n.height);r.save(),r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity),r.fillStyle="string"==typeof arguments[0]?arguments[0]:n.color(...Array.from(arguments)),r.fillRect(0,0,n.width,n.heightM ),r.restore()},n.line=function(e,t,i,o){n._style.noStroke||(r.beginPath(),r.moveTo(e,t),r.lineTo(i,o),r.stroke())},n.arc=function(e,t,r,i,o,a,l,s){if(o==a)return n.ellipse(e,t,r,i);null==s&&(s=25),null==l&&(l=n.PIE),n._style.ellipseMode==n.CENTER?m(e,t,r,i,o,a,l,s):n._style.ellipseMode==n.RADIUS?m(e,t,2*r,2*i,o,a,l,s):n._style.ellipseMode==n.CORNER?m(e+r/2,t+i/2,r,i,o,a,l,s):n._style.ellipseMode==n.CORNERS&&m((e+r)/2,(t+i)/2,r-e,i-t,o,a,l,s)},n.ellipse=function(e,t,r,i){null==i&&(i=r),n._style.ellipseMode==n.CENTERM ?b(e,t,r,i):n._style.ellipseMode==n.RADIUS?b(e,t,2*r,2*i):n._style.ellipseMode==n.CORNER?b(e+r/2,t+i/2,r,i):n._style.ellipseMode==n.CORNERS&&b((e+r)/2,(t+i)/2,r-e,i-t)},n.circle=function(e,t,r){return n.ellipse(e,t,r,r)},n.point=function(e,t){e.x&&(t=e.y,e=e.x),r.beginPath(),r.ellipse(e,t,.4,.4,0,0,2*Math.PI),r.stroke()},n.rect=function(e,t,r,i,o,a,l,s){n._style.rectMode==n.CENTER?y(e-r/2,t-i/2,r,i,o,a,l,s):n._style.rectMode==n.RADIUS?y(e-r,t-i,2*r,2*i,o,a,l,s):n._style.rectMode==n.CORNER?y(e,t,r,i,o,a,l,s):n._stylM e.rectMode==n.CORNERS&&y(e,t,r-e,i-t,o,a,l,s)},n.square=function(e,t,r,i,o,a,l){return n.rect(e,t,r,r,i,o,a,l)},n.beginShape=function(){w(),r.beginPath(),o=!0},n.beginContour=function(){r.closePath(),w(),o=!0},n.endContour=function(){w(),o=!0},n.vertex=function(e,t){w(),o?r.moveTo(e,t):r.lineTo(e,t),o=!1},n.bezierVertex=function(e,t,n,i,o,a){w(),r.bezierCurveTo(e,t,n,i,o,a)},n.quadraticVertex=function(e,t,n,i){w(),r.quadraticCurveTo(e,t,n,i)},n.bezier=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.bezierVM ertex(r,i,o,a,l,s),n.endShape()},n.triangle=function(e,t,r,i,o,a){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.endShape(n.CLOSE)},n.quad=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.vertex(l,s),n.endShape(n.CLOSE)},n.endShape=function(e){w(),e&&r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke(),n._style.noFill&&n._style.noStroke&&(r.save(),r.fillStyle="none",r.fill(),r.restore())},n.curveVertex=function(e,t){if(a.push([e,t]),a.length<4)return;M let i=function(e,t,n,r,i,o,a,l,s,h){function c(e,t,n,r,i,o){let a=Math.pow(r-t,2)+Math.pow(i-n,2);return Math.pow(a,.5*o)+e}let u=[],f=c(0,e,t,n,r,h),d=c(f,n,r,i,o,h),x=c(d,i,o,a,l,h);for(let h=0;h<s;h++){let c=f+h/(s-1)*(d-f),g=[(f-c)/(f-0),(c-0)/(f-0),(d-c)/(d-f),(c-f)/(d-f),(x-c)/(x-d),(c-d)/(x-d),(d-c)/(d-0),(c-0)/(d-0),(x-c)/(x-f),(c-f)/(x-f)];for(let e=0;e<g.length;e+=2)isNaN(g[e])&&(g[e]=1,g[e+1]=0),isFinite(g[e])||(g[e]>0?(g[e]=1,g[e+1]=0):(g[e]=0,g[e+1]=1));let p=e*g[0]+n*g[1],m=t*g[0]+r*g[1],b=n*g[2]+i*g[M 3],y=r*g[2]+o*g[3],w=i*g[4]+a*g[5],v=o*g[4]+l*g[5],z=p*g[6]+b*g[7],V=m*g[6]+y*g[7],_=b*g[8]+w*g[9],M=y*g[8]+v*g[9],E=z*g[2]+_*g[3],S=V*g[2]+M*g[3];u.push([E,S])}return u}(...a[a.length-4],...a[a.length-3],...a[a.length-2],...a[a.length-1],n._style.curveDetail,n._style.curveAlpha);for(let e=0;e<i.length;e++)o?r.moveTo(...i[e]):r.lineTo(...i[e]),o=!1},n.curve=function(e,t,r,i,o,a,l,s){n.beginShape(),n.curveVertex(e,t),n.curveVertex(r,i),n.curveVertex(o,a),n.curveVertex(l,s),n.endShape()},n.translate=function(e,t){r.tM ranslate(e,t)},n.rotate=function(e){r.rotate(e)},n.scale=function(e,t){null==t&&(t=e),r.scale(e,t)},n.applyMatrix=function(e,t,n,i,o,a){r.transform(e,t,n,i,o,a)},n.shearX=function(e){r.transform(1,0,Math.tan(e),1,0,0)},n.shearY=function(e){r.transform(1,Math.tan(e),0,1,0,0)},n.resetMatrix=function(){r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity)},n.pushMatrix=n.push=function(){n._styleCache.push({...n._style}),n._style=n._styleCache[n._styleCache.length-1],r.save()},n.popMatrix=n.pop=function(){n._stylM eCache.length-1&&(n._styleCache.pop(),n._style=n._styleCache[n._styleCache.length-1],r.restore())},n.image=function(e,t,i,o,a,l,s,h,c){let u=e.MAGIC==n.MAGIC?e.canvas:e;function d(){if(e.MAGIC!=n.MAGIC||!n._tint)return;let t=e.canvas.getContext("2d");t.save(),t.resetTransform(),t.clearRect(0,0,t.canvas.width,t.canvas.height),t.drawImage(f.canvas,0,0),t.restore()}return e.MAGIC==n.MAGIC&&null!=n._tint&&(function(e,t){null==f&&(f=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvasM .height),f.canvas.width==e&&f.canvas.height==t||(f.canvas.width=e,f.canvas.height=t)}(e.canvas.width,e.canvas.height),f.drawImage(e.canvas,0,0),e.tinted(n._tint)),o?l?(h||(h=u.width),c||(c=u.height),r.drawImage(u,l,s,h,c,t,i,o,a),void d()):(r.drawImage(u,t,i,o,a),void d()):(e.MAGIC==n.MAGIC||e.width?r.drawImage(u,t,i,e.width,e.height):r.drawImage(u,t,i,e.videoWidth,e.videoHeight),void d())},n.loadPixels=function(){l=r.getImageData(0,0,n.canvas.width,n.canvas.height),n.pixels=l.data},n.updatePixels=function(){null!=M l&&r.putImageData(l,0,0)},n.loadImage=function(e,t){s++;let r=n.createGraphics(100,100),i=r.canvas.getContext("2d"),o=new Image;return o.src=e,o.crossOrigin="Anonymous",o.onload=function(){i.canvas.width=o.width,i.canvas.height=o.height,r.width=o.width,r.height=o.height,i.drawImage(o,0,0),s--,t&&t(r)},r};let v={};function z(e,t){null==u&&(u=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvas.height),u.canvas.width==e&&u.canvas.height==t||(u.canvas.width=e,u.canvas.height=t)}funcM tion V(){let e=r.canvas.width*r.canvas.height*4;null!=d&&e==d.length||(d=new Uint8ClampedArray(e))}function _(e){u.clearRect(0,0,u.canvas.width,u.canvas.height),u.filter=e,u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()}v[n.THRESHOLD]=function(e,t){null==t?t=127.5:t*=255;for(let n=0;n<e.length;n+=4){const r=.2126*e[n]+.7152*e[n+1]+.0722*e[n+2];e[n]=e[n+1]=e[n+2]=r>=t?255:0}},v[n.GRAY]=function(e){for(let t=0;t<e.length;t+=4)M {const n=.2126*e[t]+.7152*e[t+1]+.0722*e[t+2];e[t]=e[t+1]=e[t+2]=n}},v[n.OPAQUE]=function(e){for(let t=0;t<e.length;t+=4)e[t+3]=255},v[n.INVERT]=function(e){for(let t=0;t<e.length;t+=4)e[t]=255-e[t],e[t+1]=255-e[t+1],e[t+2]=255-e[t+2]},v[n.POSTERIZE]=function(e,t){let n=t-1;for(let r=0;r<e.length;r+=4)e[r]=255*(e[r]*t>>8)/n,e[r+1]=255*(e[r+1]*t>>8)/n,e[r+2]=255*(e[r+2]*t>>8)/n},v[n.DILATE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-M 1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.max(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.ERODE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.min(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.BLURM ]=function(e,t){t=t||1,t=Math.floor(t*n._pixelDensity),V(),d.set(e);let i=2*t+1,o=function(e){let n=new Float32Array(e),r=.3*t+.8,i=r*r*2;for(let t=0;t<e;t++){let o=t-e/2,a=Math.exp(-o*o/i)/(2.5066282746*r);n[t]=a}return n}(i),[a,l]=[r.canvas.width,r.canvas.height];for(let n=0;n<l;n++)for(let r=0;r<a;r++){let l=0,s=0,h=0,c=0;for(let e=0;e<i;e++){let i=4*(n*a+Math.min(Math.max(r-t+e,0),a-1));l+=d[i]*o[e],s+=d[i+1]*o[e],h+=d[i+2]*o[e],c+=d[i+3]*o[e]}let u=4*(n*a+r);e[u]=l,e[u+1]=s,e[u+2]=h,e[u+3]=c}d.set(e);for(let nM =0;n<l;n++)for(let r=0;r<a;r++){let s=0,h=0,c=0,u=0;for(let e=0;e<i;e++){let i=4*(Math.min(Math.max(n-t+e,0),l-1)*a+r);s+=d[i]*o[e],h+=d[i+1]*o[e],c+=d[i+2]*o[e],u+=d[i+3]*o[e]}let f=4*(n*a+r);e[f]=s,e[f+1]=h,e[f+2]=c,e[f+3]=u}},n.filter=function(e,t){if(n.HARDWARE_FILTERS&&null!=r.filter)if(z(),e==n.THRESHOLD){null==t&&(t=.5),t=Math.max(t,1e-5),_(`saturate(0%) brightness(${Math.floor(.5/t*100)}%) contrast(1000000%)`)}else if(e==n.GRAY)_("saturate(0%)");else if(e==n.OPAQUE)u.fillStyle="black",u.fillRect(0,0,u.canvaM s.width,u.canvas.height),u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.drawImage(u.canvas,0,0),r.restore();else if(e==n.INVERT)_("invert(100%)");else if(e==n.BLUR)_(`blur(${Math.ceil(t*n._pixelDensity/1)||1}px)`);else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}},n.resize=function(e,t){z(),u.drawImage(r.canvas,0,0),n.width=e,n.height=t,r.canvas.width=e*n._pixM elDensity,r.canvas.height=t*n._pixelDensity,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0,r.canvas.width,r.canvas.height),r.restore()},n.get=function(e,t,i,o){if(null!=e&&null==i){let i=r.getImageData(e,t,1,1).data;return new n.Color(i[0],i[1],i[2],i[3]/255)}e=e||0,t=t||0,i=i||n.width,o=o||n.height;let a=n.createGraphics(i,o);a.pixelDensity(n._pixelDensity);let l=r.getImageData(e*n._pixelDensity,t*n._pixelDensity,i*n._pixelDensity,o*n._pixelDensity);return a.caM nvas.getContext("2d").putImageData(l,0,0),a},n.set=function(e,t,i){if(i.MAGIC==n.MAGIC){let r=n._tint;return n._tint=null,n.image(i,e,t),void(n._tint=r)}let o=4*(t*n._pixelDensity*r.canvas.width+e*n._pixelDensity);n.pixels[o]=i._r,n.pixels[o+1]=i._g,n.pixels[o+2]=i._b,n.pixels[o+3]=255*i._a},n.tinted=function(){let e=n.color(...Array.from(arguments)),t=e._a;e._a=1,z(),u.clearRect(0,0,u.canvas.width,u.canvas.height),u.fillStyle=e,u.fillRect(0,0,u.canvas.width,u.canvas.height),u.globalCompositeOperation="multiply",u.M drawImage(r.canvas,0,0),u.globalCompositeOperation="source-over",r.save(),r.resetTransform();let i=r.globalCompositeOperation;r.globalCompositeOperation="source-in",r.drawImage(u.canvas,0,0),r.globalCompositeOperation=i,r.restore(),u.globalAlpha=t,u.clearRect(0,0,u.canvas.width,u.canvas.height),u.drawImage(r.canvas,0,0),u.globalAlpha=1,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()},n.tint=function(){n._tint=n.color(...Array.from(arguments))},n.noTiM nt=function(){n._tint=null},n.mask=function(e){r.save(),r.resetTransform();let t=r.globalCompositeOperation;r.globalCompositeOperation="destination-in",r.drawImage(e.canvas,0,0),r.globalCompositeOperation=t,r.restore()},n.clearTemporaryBuffers=function(){u=null,f=null,d=null},n.save=function(e,t){e=e||"untitled",t=t||"png";var n=document.createElement("a");n.innerHTML="[Download]",n.addEventListener("click",(function(){this.href=r.canvas.toDataURL(),this.download=e+"."+t}),!1),document.body.appendChild(n),n.click()M ,document.body.removeChild(n)},n.saveCanvas=function(e,t,r){if(e.MAGIC==n.MAGIC){r&&e.save(t,r);let n=t.split(".");return e.save(n.slice(0,-1).join("."),n[n.length-1])}if(t)return n.save(e,t);let i=e.split(".");return n.save(i.slice(0,-1).join("."),i[i.length-1])},n.loadFont=function(e){let t=e.split("/"),n=t[t.length-1].split(".")[0].replace(" ",""),r=`@font-face {\n font-family: '${n}';\n src: url('${e}');\n }`;const i=document.createElement("style");return i.textContent=r,document.head.append(M i),n},n.textFont=function(e){n._style.textFont=e},n.textSize=function(e){n._style.textSize=e,n._style.textLeading=e},n.textLeading=function(e){n._style.textLeading=e},n.textStyle=function(e){n._style.textStyle=e},n.textAlign=function(e,t){r.textAlign=e,t&&(r.textBaseline=t==n.CENTER?"middle":t)},n.text=function(e,t,i,o){if(!e)return;if(e=e.toString(),n._style.noFill&&n._style.noStroke)return;r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`;let a=e.split("\n");for(let e=0;e<a.length;e++)n._M style.noFill||r.fillText(a[e],t,i,o),n._style.noStroke||r.strokeText(a[e],t,i,o),i+=n._style.textLeading},n.textWidth=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).width},n.textAscent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBoundingBoxAscent},n.textDescent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBounM dingBoxDescent};var M,E=4,S=.5,R=function(e){return.5*(1-Math.cos(e*Math.PI))};n.noise=function(e,t,n){if(t=t||0,n=n||0,null==M){M=new Array(4096);for(var r=0;r<4096;r++)M[r]=Math.random()}e<0&&(e=-e),t<0&&(t=-t),n<0&&(n=-n);for(var i,o,a,l,s,h=Math.floor(e),c=Math.floor(t),u=Math.floor(n),f=e-h,d=t-c,x=n-u,g=0,p=.5,m=0;m<E;m++){var b=h+(c<<4)+(u<<8);i=R(f),o=R(d),a=M[4095&b],a+=i*(M[b+1&4095]-a),l=M[b+16&4095],a+=o*((l+=i*(M[b+16+1&4095]-l))-a),l=M[4095&(b+=256)],l+=i*(M[b+1&4095]-l),s=M[b+16&4095],l+=o*((s+=i*(M[M b+16+1&4095]-s))-l),g+=(a+=R(x)*(l-a))*p,p*=S,h<<=1,c<<=1,u<<=1,(f*=2)>=1&&(h++,f--),(d*=2)>=1&&(c++,d--),(x*=2)>=1&&(u++,x--)}return g},n.noiseDetail=function(e,t){e>0&&(E=e),t>0&&(S=t)};const I=function(){let e,t,n=4294967295;return{setSeed(r){e=t=(null==r?Math.random()*n:r)>>>0},getSeed:()=>t,rand:()=>(e^=e<<17,e^=e>>13,((e^=e<<5)>>>0)/n)}};let C=I();C.setSeed(),n.noiseSeed=function(e){let t=null==e?4294967295*Math.random():e;M||(M=new Float32Array(4096));for(var n=0;n<4096;n++)t^=t<<17,t^=t>>13,t^=t<<5,M[n]=(t>M >>0)/4294967295},n.randomSeed=function(e){C.setSeed(e)},n.random=function(e,t){return null==e?C.rand():"number"==typeof e?null!=t?C.rand()*(t-e)+e:C.rand()*e:e[~~(e.length*C.rand())]},n.randomGenerator=function(e){e==n.LCG?C=function(){const e=4294967296;let t,n;return{setSeed(r){n=t=(null==r?Math.random()*e:r)>>>0},getSeed:()=>t,rand:()=>(n=(1664525*n+1013904223)%e)/e}}():e==n.SHR3&&(C=I()),C.setSeed()};var T=new function(){var e,t,n,r=new Array(128),i=new Array(256),o=new Array(128),a=new Array(128),l=new Array(2M 56),s=new Array(256),h=function(){return 4294967296*C.rand()-2147483648},c=function(){return.5+2.328306e-10*(h()<<0)};this.SHR3=h,this.UNI=c,this.RNOR=function(){return n=h(),e=127&n,Math.abs(n)<r[e]?n*o[e]:function(){for(var t,i,l,s,u=3.44262;;){if(t=n*o[e],0==e){do{l=c(),s=c(),t=.2904764*-Math.log(l),i=-Math.log(s)}while(i+i<t*t);return n>0?u+t:-u-t}if(a[e]+c()*(a[e-1]-a[e])<Math.exp(-.5*t*t))return t;if(n=h(),e=127&n,Math.abs(n)<r[e])return n*o[e]}}()},this.REXP=function(){return(t=h()>>>0)<r[e=255&t]?t*l[e]:funM ction(){for(var n;;){if(0==e)return 7.69711-Math.log(c());if(n=t*l[e],s[e]+c()*(s[e-1]-s[e])<Math.exp(-n))return n;if((t=h())<i[e=255&t])return t*l[e]}}()},this.zigset=function(){var e,t,n=2147483648,h=4294967296,c=3.442619855899,u=c,f=.00991256303526217,d=7.697117470131487,x=d,g=.003949659822581572;for(e=f/Math.exp(-.5*c*c),r[0]=Math.floor(c/e*n),r[1]=0,o[0]=e/n,o[127]=c/n,a[0]=1,a[127]=Math.exp(-.5*c*c),t=126;t>=1;t--)c=Math.sqrt(-2*Math.log(f/c+Math.exp(-.5*c*c))),r[t+1]=Math.floor(c/u*n),u=c,a[t]=Math.exp(-.5*cM *c),o[t]=c/n;for(e=g/Math.exp(-d),i[0]=Math.floor(d/e*h),i[1]=0,l[0]=e/h,l[255]=d/h,s[0]=1,s[255]=Math.exp(-d),t=254;t>=1;t--)d=-Math.log(g/d+Math.exp(-d)),i[t+1]=Math.floor(d/x*h),x=d,s[t]=Math.exp(-d),l[t]=d/h}};T.hasInit=!1,n.randomGaussian=function(e,t){return T.hasInit||(T.zigset(),T.hasInit=!0),T.RNOR()*t+e},n.randomExponential=function(){return T.hasInit||(T.zigset(),T.hasInit=!0),T.REXP()},n.print=console.log,n.cursor=function(e,t,r){let i="";e.includes(".")&&(e=`url("${e}")`,i=", auto"),null!=t&&(e+=" "+t+M " "+r),n.canvas.style.cursor=e+i},n.noCursor=function(){n.canvas.style.cursor="none"},n.createCapture=function(e){var t=document.createElement("video");return t.playsinline="playsinline",t.autoplay="autoplay",navigator.mediaDevices.getUserMedia(e).then((function(e){t.srcObject=e})),t.style.position="absolute",t.style.opacity=1e-5,t.style.zIndex=-1e3,document.body.appendChild(t),t};let A=["setup","draw","preload","mouseMoved","mousePressed","mouseReleased","mouseDragged","mouseClicked","keyPressed","keyReleased","keM yTyped","touchStarted","touchEnded"];for(let e of A){let t="_"+e+"Fn";n[t]=function(){},n[t].isPlaceHolder=!0,n[e]?n[t]=n[e]:Object.defineProperty(n,e,{set:function(e){n[t]=e}})}function D(){n._noLoop||(i=null==n._frameRate?requestAnimationFrame(D):setTimeout(D,1e3/n._frameRate)),w(),o=!0,n.push(),n._drawFn(),n.pop(),++n.frameCount}function k(e){const t=n.canvas.getBoundingClientRect(),r=n.canvas.scrollWidth/n.width||1,i=n.canvas.scrollHeight/n.height||1;return{x:(e.clientX-t.left)/r,y:(e.clientY-t.top)/i,id:e.idenM tifier}}function L(){return n._touchStarted.isPlaceHolder&&n._touchMoved.isPlaceHolder&&n._touchEnded.isPlaceHolder}n.noLoop=function(){n._noLoop=!0,i=null},n.loop=function(){n._noLoop=!1,null==i&&D()},n.redraw=function(){D()},n.frameRate=function(e){n._frameRate=e},setTimeout((function(){n._preloadFn(),c=window.performance.now(),function e(){if(s>0)return setTimeout(e,10);n._setupFn(),D()}()}),1),n.canvas.onmousemove=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPM ressed?n._mouseDraggedFn(e):n._mouseMovedFn(e)},n.canvas.onmousedown=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!0,n.mouseButton=[n.LEFT,n.CENTER,n.RIGHT][e.button],n._mousePressedFn(e)},n.canvas.onmouseup=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!1,n._mouseReleasedFn(e)},n.canvas.onclick=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressedM =!0,n._mouseClickedFn(e),n.mouseIsPressed=!1},window.addEventListener("keydown",(function(e){n.keyIsPressed=!0,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!0,n._keyPressedFn(e),1==e.key.length&&n._keyTypedFn(e)})),window.addEventListener("keyup",(function(e){n.keyIsPressed=!1,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!1,n._keyReleasedFn(e)})),n.keyIsDown=function(e){return!!h[e]},n.canvas.ontouchstart=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.moM useY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mousePressedFn(e)||e.preventDefault()),n._touchStartedFn(e)||e.preventDefault()},n.canvas.ontouchmove=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mouseDraggedFn(e)||e.preventDefault()),n._touchMovedFn(e)||e.preventDefault()},n.canvas.ontouchend=n.canvas.ontouchcancel=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.M mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!1,n._mouseReleasedFn(e)||e.preventDefault()),n._touchEndedFn(e)||e.preventDefault()},n.hasSensorPermission=!window.DeviceOrientationEvent&&!window.DeviceMotionEvent||!(DeviceOrientationEvent.requestPermission||DeviceMotionEvent.requestPermission),n.requestSensorPermissions=function(){DeviceOrientationEvent.requestPermission&&DeviceOrientationEvent.requestPermission().then((e=>{"granted"==e&&DeviceMotionEvent.requestPermissioM n&&DeviceMotionEvent.requestPermission().then((e=>{"granted"==e&&(n.hasSensorPermission=!0)})).catch(alert)})).catch(alert)},window.ondeviceorientation=function(e){n.pRotationX=n.rotationX,n.pRotationY=n.rotationY,n.pRotationZ=n.rotationZ,n.pRelRotationX=n.relRotationX,n.pRelRotationY=n.relRotationY,n.pRelRotationZ=n.relRotationZ,n.rotationX=e.beta*(Math.PI/180),n.rotationY=e.gamma*(Math.PI/180),n.rotationZ=e.alpha*(Math.PI/180),n.relRotationX=[-n.rotationY,-n.rotationX,n.rotationY][1+~~(window.orientation/90)],n.rM elRotationY=[-n.rotationX,n.rotationY,n.rotationX][1+~~(window.orientation/90)],n.relRotationZ=n.rotationZ},window.ondevicemotion=function(e){if(n.pAccelerationX=n.accelerationX,n.pAccelerationY=n.accelerationY,n.pAccelerationZ=n.accelerationZ,!e.acceleration){let t=((e,t)=>[(e[0]*t[0]+e[1]*t[1]+e[2]*t[2]+e[3])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[4]*t[0]+e[5]*t[1]+e[6]*t[2]+e[7])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[8]*t[0]+e[9]*t[1]+e[10]*t[2]+e[11])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15])])(((e,t)M =>[e[0]*t[0]+e[1]*t[4]+e[2]*t[8]+e[3]*t[12],e[0]*t[1]+e[1]*t[5]+e[2]*t[9]+e[3]*t[13],e[0]*t[2]+e[1]*t[6]+e[2]*t[10]+e[3]*t[14],e[0]*t[3]+e[1]*t[7]+e[2]*t[11]+e[3]*t[15],e[4]*t[0]+e[5]*t[4]+e[6]*t[8]+e[7]*t[12],e[4]*t[1]+e[5]*t[5]+e[6]*t[9]+e[7]*t[13],e[4]*t[2]+e[5]*t[6]+e[6]*t[10]+e[7]*t[14],e[4]*t[3]+e[5]*t[7]+e[6]*t[11]+e[7]*t[15],e[8]*t[0]+e[9]*t[4]+e[10]*t[8]+e[11]*t[12],e[8]*t[1]+e[9]*t[5]+e[10]*t[9]+e[11]*t[13],e[8]*t[2]+e[9]*t[6]+e[10]*t[10]+e[11]*t[14],e[8]*t[3]+e[9]*t[7]+e[10]*t[11]+e[11]*t[15],e[12]*t[0]+M e[13]*t[4]+e[14]*t[8]+e[15]*t[12],e[12]*t[1]+e[13]*t[5]+e[14]*t[9]+e[15]*t[13],e[12]*t[2]+e[13]*t[6]+e[14]*t[10]+e[15]*t[14],e[12]*t[3]+e[13]*t[7]+e[14]*t[11]+e[15]*t[15]])((e=>[Math.cos(e),0,Math.sin(e),0,0,1,0,0,-Math.sin(e),0,Math.cos(e),0,0,0,0,1])(n.rotationY),(e=>[1,0,0,0,0,Math.cos(e),-Math.sin(e),0,0,Math.sin(e),Math.cos(e),0,0,0,0,1])(n.rotationX)),[0,0,-9.80665]);n.accelerationX=e.accelerationIncludingGravity.x+t[0],n.accelerationY=e.accelerationIncludingGravity.y+t[1],n.accelerationZ=e.accelerationIncludM ingGravity.z-t[2]}},n.year=function(){return(new Date).getFullYear()},n.day=function(){return(new Date).getDay()},n.hour=function(){return(new Date).getHours()},n.minute=function(){return(new Date).getMinutes()},n.second=function(){return(new Date).getSeconds()},n.millis=function(){return window.performance.now()-c}}(e)}"object"==typeof exports&&"undefined"!=typeof module&&(module.exports=e);const t="https://ancient-crimson-rain.btc.discover.quiknode.pro/c268fb026303ae8443f785200f2ea4b82f0082dd";function n(e){P(e)?M localStorage.removeItem("blocksApiEndpoint"):localStorage.blocksApiEndpoint=e}function r(){return localStorage.blocksApiEndpoint||t}function i(e){P(e)?localStorage.removeItem("modelInscriptionEndpoint"):localStorage.modelInscriptionEndpoint=e}function o(){return localStorage.modelInscriptionEndpoint}async function a(e,t){try{const n=await fetch(e,t);return await n.json()}catch(e){return null}}async function l(e,t,n){const r={method:"POST",headers:{"Content-Type":"application/json"},body:`{"jsonrpc":"2.0","id":1,"meM thod":"${t}","params":${`[${n.join(sep=",")}]`}}`};return(await a(e,r))?.result}async function s(e){const n={avgfee:10,time:Date.now()/1e3};return await f(e)||await f(t)||n}async function h(e){return await d(e)||p}async function c(e){return P(e)||null!=await f(e)}async function u(e){return P(e)||null!=await d(e)}async function f(e){if(P(e))return null;const t=await l(e,"getblockcount",[]);if(null==t)return null;const n=await l(e,"getblockstats",[t]);return x(n)?n:null}async function d(e){if(P(e))return null;const tM =await a(e,{});return g(t)?t:null}function x(e){return"number"==typeof e?.time&&"number"==typeof e?.avgfee}function g(e){if(null==e)return!1;const{classes_name:t,training_traits:n,layers_config:r,weight_b64:i}=e;if(!Array.isArray(t))return!1;if(null==n)return!1;try{j(r,i)}catch(e){return!1}return!0}const p={"model_name": "pfp_classifier_85", "layers_config": {"config": {"layers": [{"class_name": "InputLayer", "config": {"batch_input_shape": [null, 28, 28, 3]}}, {"class_name": "Rescaling", "config": {"scale": 0.0078M 4313725490196, "offset": -1}}, {"class_name": "Flatten"}, {"class_name": "Dense", "config": {"units": 3, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 15, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 4, "activation": "linear"}}]}}, "weight_b64": "w0qcvJJ7lbuO3Dc89MRWPQjvoDtC4S694DBxPdPl/7wCToG8oAklPWRkXTy1tVw9IFc4vDQpW7zvi3S7pVw4vAzeCTxIG4W8ZuDvPAWKf72A8149cmZsPdkOiDsGLhs96emQPXnTlrw7OII9csYjPdlkfLwyVbk89NGxPG8tJb1EgBo8uU+0vCQ9zrzC5SI95yhKPW//zTyTqja7ftJCPYNGJL2MgV89FMoZM vaEMnTwyo1w9peUPvSGMPrsdaNm8s9A0Pbn92bzPIO68CaKWPClkTDzZ07a838iguu+hZLsbxVe9AV1NPRpkTb02eWS7tUgTvVOvGLyXFIS75fa2PLw5rDytxwC9mmLGPHp86byLxl88Deimu8abUL24qDo8oss4PI0+xbwjdt47OQ0BPbkZ8LxO5KU8Cs2BPIImor0C/sI8/o0lPbzAnL1Kx2G9Vlz3ugeonb1bLaW8IScdPfiKdb03aAq9gvIbvSjwVbzrQxW90fBNPW1Cpr376Ry9vFBFvOl/M7yt5hS90+DdvDDm/byCkIe9wt6FPbxy/rz1V9K86KhiPUayO72oKO08hqMTvQtsrbxiC9S8hckqPegbiTy9AY48auoQvV4IAb2YpTc8t1ztvDEDNDxw5oS9tEuYPBil9TsdP/m8wKscPQ29iL1IMc47RrwaPYogP724Kic7Dj2HPVy3prwES5W8391MO3L8ZrzQTh89avGivEo+J70DNyK9XdsTPVC0jjvqM qBW9ZINePZMcZ70IpxI9pPpnPQXcibxUCd28akxPPTzLN71MLp88nwMiPb9tgr3U+LG8Q4X5O1bFbb0GBfA8vQ+UO1TZsDsFkqm76ofEPFTCQr2syEg9GZvAPOZVFzzKgG86T5RmPd1Qh7yDKI67MicwPZLiL73iDrc8uC8gPWxuRTwEy488if4YPa0oT70tnR08iBwevUZfqr27PHY6k1IIvcjJSLytweM81pU7Pb9JiLxL4bO7I+UevXaJOb3hsmC8lV8tPb4/Cr0hfL+8tOi6uwS7lb2hZva8MdG6vFQVw703xj493CLhPMGzmbxcYl69nQ8cPXgSoL2m5O08zMdAPUvtTL29rfo5hXjGu35sTz1Znwi9NStrvDoPDb3SYN08WWJDuy/pnrwtSIo9gbztPD1jNj2Ewf67psuJPW2rlLu/4CA9VqoGvWhXkbtRY447yvSuvITprzu6hbu8OOSNPWGsxbzBaMW8+PXYvInuiL3gsQY97DUMvfobtjxU5ny5n0hDM PVGQnTidTi88ejZdvBIe6ryBkYQ8ZnwHvfFP5bwHeMc8sNI3u9M3Ub2Gg7i7KGObPBuKrrz4KWM8omFUPRnjgDw6Ys08/lljPaakF71+ZTe955iFPOtkHT0NSSQ92WRNOvviKz1EYQc97K2pO/NAorw1GS691c+SPbrCSb3b6M28TW6LPHy5RD2lBRm9C183uxPVH73gs5a8vhH9ulflIj2aJxM9oPTHvDZ2xruDU6I7yB2ePR7JsbwFid48qF+VOVd6W7wt7o48+WSTPL4eMT0OVzU89C6TPQVUGr0DMxA86H0QO5dGXbwXRQM9P241vfwKh71366w8qyw1PDtwk71gY9O8acYJvBUoHb1k8246KzIzvP+q0bwaXG07va2SPchbir0O6jW9vzGUuxhQab0RW4U72Ouxu/1+jTwv0ly91BmOvC3qIb3Vz7+89fGdPA9Job2AB3W8TM4lvIV9YjyYKbW8GlOOPfTlO72Cqju7CiRmPSY9/btAqLA8629APeDX6Lz1M 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 D9k8gh4+vWrlP71oGbc8oPWaPGBRvzydvWe9IwMtvW4LJ72cHhC7bwKevUMvxjyRKn68YepKvZNVSLp7DZm8A2OJPOXd4DwC5p49rseavb7mODoQMxA9JpdBPAnMaDwM5cM9ooWPvbGB8LzEvZA8LG2Rva43erzoDA09JQYlPP0c6TxUnIk9+zF5vUmZYL2OzSa9inZ/vRZSjrvgm4699h3/PJ9TvbuT6vu8Is/WO5bcKTzsL8q9iGuZvT1HWDzPpim9VY5BPeh9tryM1/u9ddNRvZ0mEb25TrS93Sq1vdJ7Rz0mSMe7gXwnPUp19Lsip269hbnEvYKEor1/pVW9ulsFvnESN73mwhw92WiUu75OPbvdvR29el/0vKKqgL3xAIy8CcO6vW62VbzaV0G8JYyAvfxFObuOspC9TxphPXbJSb2Pt9g97ikfPTMTarxW7g09KXlcPXssjD0EBVE9vbKWPeQIvzyWTe89WNSGPZ/RrbwSIsQ9CVaHPJ+1zT28vPs9JnDxM 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 vRrKNL1Y2EI9y1svvCGKmj2Txka95r2hPNlXNj2AMrO9HupqPPAHvj3mdHg7iRFkvCsGxTxvujm8IkcMvWS/Ybqwma69O+IXvPnVfz34hcS8jgbCPBq3cb3pFtw8wRWTPKerob1m1kA9m6FXPXwSk737pSw9yZA8vAekeDzf2uM7y2UgvFmuJ73SyLS8ofP5vEZ7vbprFME8mRCKO2C0CT1TKoI9ZIeAvc2+WrzmvGM9H22BvGx2LDwfMcU8hd2Cve18q7uipJQ9FNKHvX/RwryU5Ac+pKQNvQKeED0ZtO49y0/HvTB5bT0ADQQ8UJ88vd+UojyrILU8J2ebvaE94jzrTB88FBGvvbd3hz277kC9uATbvP1UGjwIcYg8+gtVvbrw8zvQ+0a9FjJ6vPe1w7xECCw9nk5sPDzv4Tz3oX28YZH9O6LxIj3H1567qZ8gu58kar0ML2s7bk7yO8sxxb1aM7k9+T+LPYUlDb1tHK07h2kCvQXpmzxsgNu8szf9vOZdGj3nM 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 vefJ+T2zQQg9qNt/O9Xq+zv0zS28XtUpPXHuHr0jaJG8bmVfPZlF173WLIa9YdPLPJ9WF771x7e81t2uvYyfnb1TRse9GJ+PvTfpnr25Kg6+KYVXvZ1PWL1eBji9LFmDPBhzrT3ZooA8FDu+vBJ04T0BVhS9mAalu7kJA7260MW8cLZOPE3DuTsfPws+luU3O03Trj0HdMw9mTU7vcHuHD1k9Vc995FfPeGpwT1hNhM+4ZGLvZp6Oj5N0No9uhHnva0+tj1QKvY9HZ0WvcMbQz0HOFM8CMTNvb55Vj3gFTu9V88avlOb0DtCDta8PXtvvSrFDb1H6769QBgMvQp1ub0C4ga+DsDDvEtnL77ErO69N07wvORxq737Zlu9pEodPRud973Xx7m9T8uFvYDsM76Cj/m99KHpvL8bpr2V36u9sTQ+OqlkHb7Yzqa9KE6KvSPjI74upaa9rMZ8PM0bsrwvdkm9wKYHvJT4Lr3HVZO967i0vMWRjr0Z58C99c3zPTKGMT1+M 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 PoonrDvkji28vOcwPgmRODxWKIW9P0zEPf5CBr2yB5a9fbWCPdzS4r2+nMC8BzEAvQuOK77RM9m9qCB4PP+kDr7Fwv67l3DtvNukB77+S1e9wYhUvefiU74kHRq+DzEAvUR2Er7Uywm+7iSPvTR65r3p+p69WGTXvcw0vb0xUwC+wkfJvXsv073uxrS99LxnPOJbxbt8jIe9FCJivfTDlT2GPwS+YWABvggLzb2H1qK9BuYUPRVwfLyZo3K9ylf7POD2uz2ouSq9YCM2veSow711uSe+IamjPTzbNT3Z95c80Xc2Peu+Cj2xyZu9C2zJPOY1Yr2Z1em9dVMRPj5SED0NhwA+p2QiPuIyXD2KbIa5mU9ePc5+f70I1BO9AKHFPeLVgr0LgDY+r9V5Pfv2+L1vCYo8ZgMcPffoj73eH3Q9UcY0PbjGqL15Jco9oqK1PHmAFL6yVMS9+QSBPR5H9b1o6JI8mGMHPQGyrbzPW+29JjRYvHLSSb3Ix8W9+wWNPYppnb0vM 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 vAkJQb2tGZO9tvx2O3SNAL2pdxO+I/zgPbjiSLxuckW9T3QjPUvwiLxyCJ859dQwvPWQsjyr9l29aCe7PQ9smjyr/Bk9dVchPbHPOTzdSIA9J5+RuwWmGz0+giM9gWo7PQDKgD3dqVM9OSsXO41XcDw2S1Y7lYKZPKFONT3pyp+8iNwfPYTRFbsN1Fg9TgDsPDeKYz1Lmg49VjUXPeGdGj1Avzi9J+CLPebiODzajDe9XZiOvItBtrzRUKW9P3FFPFlVRbwcj069ry24PPrFVz2wuu08NAJBPNhylD3yFyM9tC2NPe/4LD2gwZy8xVDLPH6AUD39PDY8EuaMPZ56Hj3Qh+m8VZ1vPWGYm7lY3gm9BGORPWbUiz0fe7s8P5iHu1HfOj0EIwc8JCqsPQE+cDvP16o7mwYEPfoghT0AwqC6Drj0vFe+HT3zpjW9pixBPf2NmT1+QTg77fagvEEANb2I/5i9Ty+nvGkCOzxEz+a9aiI9vRIyRbuIIR2+DkqavU0Mfb23M +Qy++0/wvfxvGb6E4M+9pwSMvIzH+Lzn7KC9i9+VvV9gFr0oA529M3b/vQIVjL1t2hI8BrvRvWTZX7oXBNu8tE/svblcNbvHacO7B8qMvQmq3rtbf4E9IT17vXYJh7xlZpc9dl0PPHUVej0LzIY9489WvZIBGD0zJsk9h6mWPFfNIj37fbE9y6KkPdWplbvunKs99IHePOJw17vV4tk8JFRoPQfUMb2wdTM8oOgePlYWWz2Ucl86cFgCPov5nrz+ASO8cCYzPR7zer15YzI9sZWiPcbXxjzbNHy8Qb7GPRUUx7t9DFY8SFeNPHtHZb3c6yc9xEK3PVHmnLzF1hG9ttKAPepBE71V4cW81RhTPS86GL0W6xQ81FP/PdaXET0ll/Y8yUCpPefg3bwV1Xa8AQBpO7UzE70ajrq8IdFuPbRFeT054iW9yoaqPb4mZj0/RIu8MVCaPXF1VL2BVRQ98k/qPQorKTwSgo8943WUPd7Cjz2sbPs8EIlbPf4mtb1rK3Y8gmzfM 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 F4s+wKFtvgAI2T5rmOC+01b9PsSkB78QS2S9ioi+PlxbHT75Yh8/f06IvwXBzj45tZW+gaqevmSgGD/Gd+G+66eHPo92pb5z1yo/k4LIvfCyGL8bqRM/0R9LPg==", "training_traits": {"structure_gen": "Random", "n_layers": 2, "max_nodes": 15, "activation_func": "ReLU", "epoch_num": 4}, "classes_name": ["Cryptoadz", "Cryptopunks", "Moonbirds", "Nouns"]},m=25,b=50,y=59+11/12,w=59+11.5/12,v=60;function z(e,t){const n=Math.log(1-t)/Math.log(1-e);return e=>1-Math.pow(1-e,n)}class V{constructor(e,t,n){const{model:r,inputDim:i}=j(t,n);this.model=r,this.inputM Dim=i,this.iteration=0,this.stage=0;const o=new Date(parseInt(e.birthYear),0,1).getTime(),a=new Date(parseInt(e.birthYear)+1,0,1).getTime();this.birthDate=new Date(Math.floor((o+a)/2));const l=zr.filter((t=>t[0]==e.lifeCycle))[0][2];this.growSpeed=365/l,this.cycleLength=60*l*24*3600*1e3,this.growthFunc=z(.4,.8)}updateAge(e){const t=(e.getTime()-this.birthDate.getTime())/31536e6*this.growSpeed;this.iteration=Math.floor(t/60);const n=t-60*this.iteration;let r;this.age=n;let i,o=0;if(n<25){let e=map(n,0,25,0,1);o=thisM .growthFunc(e),r=(25-n)/60,this.stage=1,this.stageRatio=map(n,0,25,0,1)}else n<50?(o=1,r=(50-n)/60,this.stage=2,this.stageRatio=map(n,25,50,0,1)):n<y?(o=map(n,50,y,1,0),r=(y-n)/60,this.stage=3,this.stageRatio=map(n,50,y,0,1)):n<w?(o=0,r=(w-n)/60,this.stage=4,this.stageRatio=map(n,y,w,0,1)):n<60&&(o=0,r=(60-n)/60,this.stage=5,this.stageRatio=map(n,w,60,0,1));n<50?i=map(n,0,50,0,780/880):n<w?i=map(n,50,w,780/880,800/880):n<60&&(i=map(n,w,60,800/880,1)),this.nextStateTimestamp=Math.round(e.getTime()+this.cycleLength*rM ),this.statePercentage=round(100*i);let a=(25-n)/60;a<0&&(a+=1),this.nextStableTimestamp=Math.round(e.getTime()+this.cycleLength*a),this.growth=o,this.model.updateNeurons(o,this.iteration)}getBrainStatus(){return{totalNeurons:this.model.getTotalNeurons(),neuronsLife:this.model.getNeuronsLife(),stage:this.stage,inputDim:this.inputDim,stageRatio:this.stageRatio,age:this.age,growth:this.growth,nextStateTimestamp:this.nextStateTimestamp,nextStableTimestamp:this.nextStableTimestamp,rebirthCount:max(this.iteration,0),staM tePercentage:this.statePercentage}}classifyImage(e){const t=new G(e,1,e.length);return this.model.forward(t).mat[0]}}class M{constructor(e,t,n,r,i){this.p=e,this.v=t,this.size=n,this.shape=i,this.col=r}getRadius(){return 1==Oe?1*this.size/2:2==Oe?7*this.size/16:3==Oe||4==Oe?4*this.size/7:0}update(){this.p.add(this.v)}draw(e,t,n,r){const i=this.p.x*r,o=this.p.y*r,a=this.size*r,{col:l,shape:s}=this;let h,c;1==n?h=c=l:2==n?(h=dr(t,1),c=l):(h=dr(t,0),c=dr(l,1));e.stroke(dr(c,map(1,0,1,.25,1))),e.fill(dr(h,map(1,0,1,.15M ,1))),3==n&&e.fill(dr(h,0)),1==s?e.ellipse(i,o,a,a):2==s?e.rect(i,o,7*a/8,7*a/8):3==s&&(e.beginShape(),e.vertex(i-4*a/7,o),e.vertex(i,o-4*a/7),e.vertex(i+4*a/7,o),e.vertex(i,o+4*a/7),e.endShape(CLOSE))}}class E{constructor(e,t,n,r,i,o,a){this.center=e,this.len=t,this.angle=n,this.v=r,this.angV=i,this.c1=o,this.c2=a}getEndpoints(){const e=createVector(this.len/2*cos(this.angle),this.len/2*sin(this.angle));return[Vector.add(this.center,e),Vector.sub(this.center,e)]}update(){this.center.add(this.v),this.angle+=this.anM gV}draw(e,t){const[n,r]=this.getEndpoints(),i=n.x*t,o=n.y*t,a=r.x*t,l=r.y*t,s=this.c1,h=this.c2;var c=e.drawingContext.createLinearGradient(i,o,a,l);c.addColorStop(0,s),c.addColorStop(1,h),e.drawingContext.strokeStyle=c,e.drawingContext.globalAlpha=1,e.line(i,o,a,l),e.drawingContext.globalAlpha=1}}function S(e,t){const n=random(TAU),r=random(e,t);return createVector(r*cos(n),r*sin(n))}class R{constructor(e,t,n,r,i){this.wall=n,this.maxR=i;const o=t.length;this.nodes=[];for(let a=0;a<o;++a){const o=[],l=.25*t[a];forM (let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),l=S(.02*i,.05*i),s=random(10,25)*i;o.push(new M(t,l,s,e[a],r))}this.nodes.push(o)}const a=A(e);a.unshift(e[0]),a.push(e[e.length-1]),this.lines=[];for(let e=0;e<=o;++e){const r=[],l=(0==e?1:t[e-1])*(e==o?1:t[e])*1.5;for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),o=random(5*i,10*i),l=random(TAU),s=S(.02*i,.05*i),h=random(2e-4,.001);r.push(new E(t,o,l,s,h,a[e],a[e+1]))}this.lines.pusM h(r)}}reflectNode(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,{p:o,v:a}=e,l=e.getRadius();(o.x-l<t&&a.x<0||o.x+l>r&&a.x>0)&&(a.x=-a.x),(o.y-l<n&&a.y<0||o.y+l>i&&a.y>0)&&(a.y=-a.y)}reflectLine(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,[o,a]=e.getEndpoints(),l=e.v;(min(o.x,a.x)<t&&l.x<0||max(o.x,a.x)>r&&l.x>0)&&(l.x=-l.x),(min(o.y,a.y)<n&&l.y<0||max(o.y,a.y)>i&&l.y>0)&&(l.y=-l.y)}update(){for(const e of this.lines)for(const t of e)t.update(),this.reflectLine(t);for(const e of this.nodes)for(consM t t of e)t.update(),this.reflectNode(t)}draw(e,t,n,r,i){const o=i/this.maxR;for(const t of this.lines){const n=t.length*r;for(let r=0;r<n;++r)t[r].draw(e,o)}for(const i of this.nodes){const a=i.length*r;for(let r=0;r<a;++r)i[r].draw(e,t,n,o)}}}function I(e,t){re(e),e.fill(0),e.rect(0,0,500,500),ie(e),e.noStroke(),e.fill(dr(cr("#000000"),.5)),e.push(),e.translate(250,250),e.scale(t),e.translate(-250,-250),e.beginShape(),e.vertex(235.2,24.9),e.bezierVertex(215,24.6,185,11.4,164.8,11),e.bezierVertex(147.2,10.7,129.3,1M 0.4,112.2,14.7),e.bezierVertex(95.1,19,78.5,28.5,69.6,43.8),e.bezierVertex(57.699,64.199,61.599,90.199,70.199,112.2),e.bezierVertex(78.799,134.2,91.6,154.6,97.199,177.5),e.bezierVertex(102.499,199.2,100.899,222.5,92.799,243.2),e.bezierVertex(83,268,64.6,288.3,48.9,310),e.bezierVertex(33.2,331.7,24.5,337.5,26.599,364.1),e.bezierVertex(28.2,384.1,61.399,404.2,75.7,418.3),e.bezierVertex(90,432.4,73.7,488.2,91.9,496.7),e.bezierVertex(124.2,511.6,159,472.5,194.3,468.1),e.bezierVertex(211.6,465.9,267.4,501.5,283.9,495.9)M ,e.bezierVertex(340.7,476.7,298.599,428.9,355.4,409.7),e.bezierVertex(370.799,404.5,454.5,407.6,464.4,394.8),e.bezierVertex(478.599,376.3,474.7,349.3,464.299,328.4),e.bezierVertex(453.9,307.5,438.099,289.5,428.699,268.2),e.bezierVertex(412,230,419,182.6,446.1,150.9),e.bezierVertex(449.7,146.7,453.6,142.7,455.8,137.6),e.bezierVertex(459.4,129.299,457.5,119.6,454.8,111),e.bezierVertex(443.2,73.4,417.3,40.4,383.6,20.299),e.bezierVertex(358.1,5,343.2,-.4,313.5,0),e.bezierVertex(287.5,.4,261.6,25.4,235.2,24.9),e.endShapM e(),e.pop()}function C(e,t,n,r,i,o){let a,l,s;re(t),t.fill(0),t.rect(0,0,500,500),ie(t),t.noStroke(),t.fill(dr(n,.5)),1==i?(l=0,s=25,a=map(o,0,25,500,0)):a=0,t.rect(0,a,500,500),e.noStroke(),e.fill(r),e.rect(0,0,500,500),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierM Vertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.39M 9,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,3M 70.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),e.fill(n),e.beginShape(),e.vertex(4M 35.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.M bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,19M 2.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,4M 48.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),re(e),e.fill(r),e.beginShape(),e.vertex(184.3,473.2),e.bezierVertex(164,473.2,144.7,462.099,134,444.3),e.bezierVertex(131.7,440.5,129.1,438.5,125,437.1),e.bezierVertex(97.3,428.1,80.5,400.6,85.2,371.8),e.bezierVertex(86.3,365.1,85.8,364.1,79.9,361.2),e.bezierVertex(57.2,349.8,46.2M ,323.3,54.3,299.7),e.bezierVertex(54.7,298.599,55.1,297.7,55.5,296.9),e.bezierVertex(55.6,296.599,55.8,296.4,55.9,296.099),e.vertex(57.9,291.499),e.vertex(62.5,293.599),e.bezierVertex(64.9,294.7,67.3,295.799,69.5,296.9),e.bezierVertex(74.5,299.299,79.1,301.599,83.9,303.099),e.bezierVertex(89.8,304.9,96.5,305.499,102.7,305.9),e.bezierVertex(102.8,305.9,102.9,305.9,103,305.9),e.bezierVertex(106.6,305.9,108.9,302.799,109,299.799),e.bezierVertex(109.1,296.199,106.6,293.4,102.7,292.799),e.bezierVertex(101.3,292.599,99.9M ,292.4,98.4,292.299),e.bezierVertex(94.3,291.799,90.1,291.299,86,289.9),e.bezierVertex(68.9,284,56.5,270.2,52.7,252.799),e.bezierVertex(48.9,235.499,54.5,217.7,67.6,205.299),e.bezierVertex(71.9,201.299,72.7,198.1,70.8,192.399),e.bezierVertex(64.2,172.2,68.8,153.99,84.2,139.599),e.bezierVertex(94.2,130.199,105.5,125.399,117.8,125.399),e.bezierVertex(124.3,125.399,131.1,126.799,137.8,129.599),e.bezierVertex(157,137.399,167.9,152.799,169.4,173.99),e.vertex(169.4,174.399),e.bezierVertex(169.5,175.899,169.6,177.2,169.9,M 178.299),e.bezierVertex(170.7,181.2,173.2,183.2,176.1,183.2),e.bezierVertex(176.299,183.2,176.5,183.2,176.7,183.2),e.bezierVertex(180.1,182.899,182.6,180.299,182.7,177),e.bezierVertex(183.1,162,178.299,148.2,168.399,136.1),e.bezierVertex(158.2,123.5,144.899,115.8,128.799,113.199),e.bezierVertex(123.499,112.299,120.399,109.799,118.899,104.99),e.bezierVertex(113.899,89.699,120.699,72.299,134.899,64.499),e.bezierVertex(139.99,61.699,145.799,60.199,151.7,60.199),e.bezierVertex(162.2,60.199,171.899,64.799,178.1,72.699),M e.bezierVertex(179.6,74.6,180.799,76.6,181.9,78.499),e.vertex(182.2,79.099),e.bezierVertex(183.2,80.699,185.2,83.299,188.4,83.299),e.bezierVertex(189.5,83.299,190.6,82.99,191.7,82.399),e.bezierVertex(195.1,80.599,196,76.99,194,72.799),e.bezierVertex(190.1,64.799,184.1,58.499,175.6,53.299),e.bezierVertex(174.6,52.699,173.7,52.099,172.5,51.499),e.vertex(170.5,50.299),e.vertex(163,45.899),e.vertex(170.5,41.599),e.bezierVertex(182,34.99,193.1,30.799,204.4,28.599),e.bezierVertex(208.6,27.799,212.9,27.399,217.2,27.399),eM .bezierVertex(217.6,27.399,217.9,27.399,218.3,27.399),e.bezierVertex(231.4,27.599,242.7,38.199,243,50.599),e.bezierVertex(243.4,64.899,243.3,78.99,243.2,93.799),e.bezierVertex(243.2,99.799,243.1,105.899,243.1,112.099),e.vertex(243.1,119.199),e.vertex(236.4,116.799),e.bezierVertex(235.7,116.499,235,116.299,234.4,115.99),e.bezierVertex(233.4,115.599,232.6,115.299,232,115.199),e.bezierVertex(230.6,114.899,229.2,114.599,227.8,114.299),e.bezierVertex(223.8,113.499,220.1,112.699,216.4,112.499),e.vertex(216.2,112.499),e.bM ezierVertex(212.5,112.499,210.7,115.599,210.6,118.599),e.bezierVertex(210.4,122.399,212.7,125.099,216.4,125.399),e.bezierVertex(230.1,126.399,238.9,133.099,242.3,145.199),e.bezierVertex(243.2,148.399,243.2,151.599,243.2,154.499),e.vertex(243.2,155.099),e.bezierVertex(243.2,254.199,243.2,330,243.2,400.599),e.bezierVertex(243.2,401.99,243.2,403.4,243.2,404.9),e.bezierVertex(243.3,411.099,243.3,417.599,242.3,423.9),e.bezierVertex(238.1,449.2,219.6,467.799,194,472.5),e.bezierVertex(190.9,472.9,187.6,473.2,184.3,473.2),M e.endShape(),e.beginShape(),e.vertex(315.8,473.1),e.bezierVertex(309.3,473.1,302.8,472,296.5,469.9),e.bezierVertex(270.4,461,253.8,434.9,257.1,407.9),e.bezierVertex(260,384,273.8,366.8,297,358.3),e.bezierVertex(297.7,358.1,298.3,357.8,299,357.6),e.bezierVertex(299.8,357.3,300.6,357.1,301.2,356.8),e.bezierVertex(304.3,355.4,306,351.8,304.9,348.7),e.bezierVertex(304,345.9,301.7,344.2,299,344.2),e.bezierVertex(298.6,344.2,298.1,344.2,297.6,344.3),e.bezierVertex(288.1,346.3,279,350.9,269.7,358.3),e.bezierVertex(268.9,3M 58.9,268.1,359.6,267.2,360.4),e.vertex(265.5,361.8),e.vertex(258.5,367.6),e.vertex(257.4,358.6),e.bezierVertex(257.3,358,257.3,357.5,257.2,357.1),e.bezierVertex(257,356,256.9,354.9,256.9,353.7),e.bezierVertex(256.9,334.8,256.9,316,256.9,297.1),e.bezierVertex(256.9,260.3,256.9,222.3,256.8,185),e.bezierVertex(256.8,170.7,268.3,158.8,282.5,158.4),e.bezierVertex(284.8,158.3,286.7,157.6,287.9,156.2),e.bezierVertex(289.099,154.9,289.599,153.2,289.5,151.3),e.bezierVertex(289.3,147.5,286.7,145.1,282.7,145.1),e.bezierVertexM (282.5,145.1,282.2,145.1,282,145.1),e.bezierVertex(278.8,145.3,275.5,146.1,272,146.9),e.bezierVertex(270.9,147.2,269.8,147.4,268.6,147.7),e.bezierVertex(267.9,147.9,267,148.2,265.8,148.7),e.bezierVertex(265.1,149,264.4,149.3,263.5,149.6),e.vertex(256.8,152),e.vertex(256.8,114.6),e.bezierVertex(256.8,95,256.8,75.4,256.8,55.9),e.bezierVertex(256.8,38,267.2,27.3,284.6,27.3),e.bezierVertex(285.3,27.3,285.9,27.3,286.6,27.3),e.bezierVertex(299,27.9,318.7,34.5,329.6,41.9),e.vertex(336.1,46.3),e.vertex(324.4,53.3),e.bezierM Vertex(316.2,58.2,310.2,64.6,306,72.9),e.bezierVertex(304.2,76.4,305.1,78.5,306.1,80),e.bezierVertex(307.4,81.9,309.4,83,311.6,83),e.bezierVertex(313.7,83,315.7,81.9,317.1,80.1),e.bezierVertex(317.4,79.7,317.8,79,318.1,78.4),e.bezierVertex(318.4,77.9,318.7,77.3,319,76.8),e.bezierVertex(325.3,66.2,336.3,59.9,348.5,59.9),e.bezierVertex(353.2,59.9,357.8,60.8,362.1,62.7),e.bezierVertex(377.6,69.3,386,86.7,381.7,103.2),e.bezierVertex(380.7,107.1,378.5,111.8,371.1,113.1),e.bezierVertex(342.7,118.1,322.2,139.1,317.8,167.8M ),e.bezierVertex(317.4,170.3,317.3,173.2,317.4,176.5),e.bezierVertex(317.5,180,320.1,182.8,323.5,183),e.bezierVertex(323.6,183,323.8,183,323.9,183),e.bezierVertex(327.1,183,329.8,180.6,330.3,177.2),e.bezierVertex(330.6,175.7,330.7,174,330.9,172.3),e.bezierVertex(331.1,169.8,331.4,167.3,332,164.7),e.bezierVertex(337.3,141.9,357.7,125.4,380.7,125.4),e.bezierVertex(382.5,125.4,384.3,125.5,386.1,125.7),e.bezierVertex(412.8,128.9,432.6,150.9,432,176.9),e.bezierVertex(431.9,182.3,430.9,187.7,429.1,192.7),e.bezierVertex(4M 27.2,197.9,428,201,432.3,205),e.bezierVertex(446.8,218.7,451.8,236,446.6,255),e.bezierVertex(441.4,274,428.3,286.5,408.7,291.3),e.bezierVertex(406.1,291.9,403.6,292.1,401.1,292.3),e.bezierVertex(400,292.4,398.9,292.5,397.9,292.6),e.bezierVertex(393.6,293.1,390.9,295.7,391,299.5),e.bezierVertex(391.1,303.4,394,305.8,398.5,305.8),e.bezierVertex(409.9,305.8,420.8,302.6,431.1,296.4),e.bezierVertex(431.8,296,432.5,295.5,433.2,295.1),e.bezierVertex(433.8,294.7,434.5,294.3,435.2,293.9),e.bezierVertex(436,293.4,436.6,293.2M ,437.2,293.1),e.bezierVertex(437.4,293,437.7,292.9,438.1,292.8),e.vertex(442.5,291.4),e.vertex(444.2,295.7),e.bezierVertex(450.9,312.4,449.5,328.4,440,343.4),e.bezierVertex(435.3,350.8,428.7,356.7,420.2,361.1),e.bezierVertex(414.3,364.1,413.7,365.2,414.8,371.7),e.bezierVertex(419.5,400.2,403,427.6,375.6,436.9),e.bezierVertex(371,438.5,368.3,440.7,365.8,444.7),e.bezierVertex(355.2,462.5,336.4,473.1,315.8,473.1),e.bezierVertex(315.8,473.1,315.8,473.1,315.8,473.1),e.endShape(),ie(e),e.fill(n),e.beginShape(),e.vertex(1M 20.2,279.9),e.bezierVertex(117.9,279.9,112.4,279.299,112.2,273.599),e.bezierVertex(112,267.7,117.4,266.7,119.7,266.599),e.bezierVertex(133.1,265.799,143.1,259.499,149.3,247.899),e.bezierVertex(149.6,247.299,150.1,246.399,150.3,245.399),e.bezierVertex(150.6,244.299,150.5,243.299,150.5,242.7),e.bezierVertex(150.5,242.6,150.5,242.5,150.5,242.299),e.vertex(150.3,238.799),e.vertex(141.1,235.99),e.bezierVertex(114.6,227.799,95.6,202.499,95.9,175.799),e.bezierVertex(95.9,173.99,96.4,168.199,102.2,168.199),e.bezierVertex(1M 02.6,168.199,103,168.199,103.4,168.299),e.bezierVertex(104.8,168.499,108.2,168.899,109.2,175.599),e.bezierVertex(109.3,176.599,109.5,177.599,109.6,178.499),e.bezierVertex(110.4,184.199,111.3,189.99,113.7,195.499),e.bezierVertex(121.9,213.99,139.5,225.499,159.7,225.499),e.bezierVertex(172.1,225.499,184.1,220.899,193.5,212.599),e.bezierVertex(194,212.199,194.4,211.799,194.8,211.399),e.bezierVertex(195.1,211.099,195.5,210.799,195.8,210.399),e.bezierVertex(197.4,208.99,199.2,208.2,200.9,208.2),e.bezierVertex(202.5,208.M 2,204,208.899,205.3,210.1),e.bezierVertex(208,212.9,207.9,216.9,205,219.9),e.bezierVertex(196.5,228.6,186.3,234.3,174.7,236.8),e.bezierVertex(168.799,238.1,165.6,241,163.899,246.7),e.bezierVertex(158.3,265.9,139.9,279.7,120.2,279.9),e.vertex(120.2,279.9),e.endShape(),e.beginShape(),e.vertex(187.2,427.5),e.bezierVertex(183.799,427.5,181.299,425.3,180.799,422),e.bezierVertex(180.6,420.8,180.499,419.5,180.399,418.1),e.bezierVertex(180.299,417,180.2,415.8,180.099,414.7),e.bezierVertex(177.199,390.5,156.699,371.3,132.39M 9,370.2),e.bezierVertex(131.99,370.2,131.499,370.2,131.099,370.2),e.bezierVertex(130.699,370.2,130.299,370.2,129.799,370.2),e.bezierVertex(125.99,369.9,123.199,367.2,123.099,363.6),e.bezierVertex(122.99,360.2,125.799,357.3,129.599,356.9),e.bezierVertex(130.499,356.8,131.499,356.8,132.599,356.7),e.bezierVertex(133.199,356.7,133.799,356.7,134.399,356.6),e.vertex(138.299,356.4),e.vertex(139.1,352.6),e.bezierVertex(139.5,350.7,139.799,348.9,140.2,347),e.bezierVertex(140.899,343.4,141.5,340,142.399,336.8),e.bezierVertexM (150.099,310.7,174.399,292,201.399,291.3),e.vertex(201.599,291.3),e.bezierVertex(203.699,291.3,206.299,292,208.299,293.2),e.bezierVertex(210.499,294.5,210.699,297.5,209.99,299.8),e.bezierVertex(209.499,301.5,208.199,303.9,203.299,304.7),e.bezierVertex(202.199,304.9,200.99,305,199.799,305.2),e.bezierVertex(194.499,305.9,188.99,306.599,183.799,308.9),e.bezierVertex(165.499,316.799,155.199,331.299,152.99,352),e.bezierVertex(152.399,357.8,154.499,361.7,159.699,364.5),e.bezierVertex(178.199,374.4,189.399,390,193.099,410M .9),e.bezierVertex(193.699,414.299,193.899,418,193.599,422),e.bezierVertex(193.399,425.2,190.899,427.5,187.399,427.5),e.vertex(187.2,427.5),e.endShape(),e.beginShape(),e.vertex(364.3,281.1),e.bezierVertex(346.3,280.6,332.9,272.8,323.5,257),e.bezierVertex(321.6,253.9,320.4,250.2,319.2,246.7),e.bezierVertex(317.7,242.2,315,239.799,310.5,238.799),e.bezierVertex(298.5,236.299,288,230.7,279.4,222.1),e.bezierVertex(276.7,219.4,274.9,215.299,278,211.9),e.bezierVertex(279.4,210.3,281,209.6,282.6,209.6),e.bezierVertex(284.4M ,209.6,286.4,210.6,288.3,212.5),e.bezierVertex(297.8,221.8,310.4,226.9,323.9,226.9),e.bezierVertex(340.2,226.9,355.1,219.3,364.8,206.2),e.bezierVertex(371,197.8,374.2,188.5,374.5,178.5),e.vertex(374.5,177.9),e.bezierVertex(374.5,177,374.5,176.1,374.7,175.4),e.bezierVertex(375.3,171.8,377.9,169.5,381.3,169.5),e.bezierVertex(381.4,169.5,381.5,169.5,381.7,169.5),e.bezierVertex(385.4,169.7,388,172.4,388,176.1),e.bezierVertex(388.1,190.7,383.4,204,374.2,215.8),e.bezierVertex(365.8,226.5,354.7,233.9,341.2,237.9),e.bezierM Vertex(340,238.3,338.7,238.6,337.3,239.1),e.bezierVertex(335.9,239.6,335.1,240.4,334.7,240.9),e.bezierVertex(334.599,241,334.5,241.1,334.4,241.2),e.vertex(331.799,243.6),e.vertex(333.199,246.8),e.bezierVertex(338.199,258,346.799,264.9,358.699,267.3),e.bezierVertex(360.199,267.6,361.599,267.7,362.99,267.9),e.bezierVertex(363.599,268,364.299,268,364.899,268.1),e.bezierVertex(369.099,268.6,371.799,271.4,371.499,275),e.bezierVertex(371.199,278.6,368.299,281.2,364.399,281.2),e.vertex(364.3,281.1),e.endShape(),e.beginShaM pe(),e.vertex(323.9,437),e.bezierVertex(323.7,437,323.5,437,323.299,437),e.bezierVertex(319.599,436.7,317.299,434.1,317.4,430.2),e.bezierVertex(317.9,406.099,328.299,388,349.5,375),e.bezierVertex(350.7,374.2,352,373.5,353.4,372.8),e.bezierVertex(354.099,372.4,354.7,372.1,355.299,371.7),e.vertex(357.499,370.5),e.vertex(357.799,368),e.bezierVertex(360.4,346.6,345.199,323.7,323.9,317),e.bezierVertex(319.099,315.5,314.099,314.9,309.299,314.4),e.vertex(308.199,314.299),e.bezierVertex(305.99,314.099,300.799,312.9,300.899M ,307.299),e.bezierVertex(300.99,303.499,303.899,300.9,308.099,300.9),e.vertex(308.299,300.9),e.bezierVertex(327.099,301.299,343.099,308.7,355.699,322.9),e.bezierVertex(364.299,332.5,369.399,344.099,370.99,357.299),e.bezierVertex(371.099,358.4,371.299,359.4,371.499,360.499),e.bezierVertex(371.599,360.99,371.699,361.499,371.799,361.99),e.vertex(372.499,365.899),e.vertex(377.899,366.199),e.bezierVertex(378.799,366.299,379.699,366.299,380.599,366.399),e.bezierVertex(385.099,366.699,387.899,369.399,387.799,373.299),e.beM zierVertex(387.699,377.099,384.99,379.599,380.799,379.799),e.bezierVertex(369.799,380.199,359.99,383.299,351.899,389.299),e.bezierVertex(338.799,398.799,331.699,411.699,330.699,427.499),e.vertex(330.699,428.299),e.bezierVertex(330.599,429.199,330.599,430.099,330.499,430.799),e.bezierVertex(330,434.7,327.5,437,323.9,437),e.endShape()}function T(e){return e[0].map(((t,n)=>e.map((e=>e[n]))))}function A(e){return e.map((e=>Array.isArray(e)?A(e):e))}function D(e,t){return floor(random(e,t))}function k(e){let t=0;for(conM st n of e)t+=n[1];let n=random(t),r=0;for(const t of e)if(r+=t[1],n<r)return t[0];return null}function L(e){for(let t=1;t<e.length;++t){let n=D(0,t),r=e[t];e[t]=e[n],e[n]=r}}function P(e){return null==e||""===e}function O(e){return new Promise((t=>setTimeout(t,e)))}function F(e,t,n){let r=0;for(let i=1;i<=1e3;++i)for(let o=1;o<=1e3;++o)if(e*o%(t*i)==0){let e=1*i/o;abs(e-n)<abs(r-n)&&(r=e)}return r}function N(){let e=60*(new Date).getTimezoneOffset()*1e3;return new Date(Date.now()-e).toISOString().slice(0,-1)}functiM on B(e,t,n){let r;if(push(),textSize(e),textWidth(t)<=n)r=t;else for(let e=0;e<t.length;++e){const i=t.slice(0,e+1)+"...";if(textWidth(i)>n){r=i;break}}return pop(),r}function Y(e){var t=e%10,n=e%100;return 1==t&&11!=n?e+"st":2==t&&12!=n?e+"nd":3==t&&13!=n?e+"rd":e+"th"}class G{constructor(e,t,n){this.n=t,this.m=n,this.mat=[];let r=0;for(let t=0;t<this.n;++t){this.mat.push([]);for(let n=0;n<this.m;++n)this.mat[t].push(r<e.length?e[r]:0),r+=1}return this}copy(){return new G(this.mat.flat(),this.n,this.m)}}class H{stM atic __linear=e=>e;static __relu=e=>Math.max(e,0);static __leaky_relu=e=>e>0?e:.2*e;static __sigmoid=e=>1/(1+Math.exp(-e));static __tanh=e=>Math.tanh(e);static __apply_unary_op(e,t){const n=e.copy();for(let e=0;e<n.n;++e)for(let r=0;r<n.m;++r)n.mat[e][r]=t(n.mat[e][r]);return n}static linear=e=>H.__apply_unary_op(e,H.__linear);static relu=e=>H.__apply_unary_op(e,H.__relu);static leaky_relu=e=>H.__apply_unary_op(e,H.__leaky_relu);static sigmoid=e=>H.__apply_unary_op(e,H.__sigmoid);static tanh=e=>H.__apply_unary_op(eM ,H.__tanh);static __add=(e,t)=>e+t;static __mul=(e,t)=>e*t;static __apply_binary_op=(e,t,n)=>{"object"!=typeof t&&(t=new G([t],1,1));const r=e.copy();for(let e=0;e<r.n;++e)for(let i=0;i<r.m;++i)r.mat[e][i]=n(r.mat[e][i],t.mat[e%t.n][i%t.m]);return r};static mul=(e,t)=>H.__apply_binary_op(e,t,H.__mul);static add=(e,t)=>H.__apply_binary_op(e,t,H.__add);static matMul(e,t){const n=new G([],e.n,t.m);for(let r=0;r<n.n;++r)for(let i=0;i<n.m;++i)for(let o=0;o<e.m;++o)n.mat[r][i]+=e.mat[r][o]*t.mat[o][i];return n}static sofM tmax(e){const t=H.__apply_unary_op(e,(e=>Math.exp(e))),n=t.mat.flat().reduce(((e,t)=>e+t));for(let r=0;r<e.n;++r)for(let i=0;i<e.m;++i)t.mat[r][i]/=n;return t}}class ${constructor(e,t){this.scale=e,this.offset=t}forward(e){return H.add(H.mul(e,this.scale),this.offset)}}class X{constructor(){}forward(e){return e.map((e=>e.flat()))}}class W{constructor(e,t,n,r){this.out_dim=e,this.activation=t,this.w=n,this.b=r}forward(e){const t=H.add(H.matMul(e,this.w),this.b);return null==this.activation?t:this.activation(t)}}clasM s U{constructor(e,t,n){this.preprocessLayers=e,this.hiddenLayers=t,this.outputLayer=n,this.totalNeurons=this.hiddenLayers.map((e=>e.out_dim)),this.currentOrders=[],this.currentIteration=null}updateNeurons(e,t){if(t!=this.currentIteration){this.currentOrders=[];for(let e=0;e<this.totalNeurons.length;++e){randomSeed(100*(t+1)+e);const n=[];for(let t=0;t<this.totalNeurons[e];++t)n.push(t);L(n),this.currentOrders.push(n)}this.currentIteration=t}const n=A(this.totalNeurons),r=n.reduce(((e,t)=>e+t))*(1-e);for(let e=0;e<rM ;++e){const t=n.map(((e,t)=>(e-1)/this.totalNeurons[t]));n[t.map(((e,t)=>[e,t])).reduce(((e,t)=>t[0]>e[0]?t:e))[1]]-=Math.min(r-e,1)}this.neuronsLife=[];for(let e=0;e<n.length;++e){const t=this.currentOrders[e],r=Array(this.totalNeurons[e]).fill(0);for(let i=0;i<n[e];++i)r[t[i]]=Math.min(n[e]-i,1);this.neuronsLife.push(r)}}getTotalNeurons(){return A(this.totalNeurons)}getNeuronsLife(){return A(this.neuronsLife)}forward(e){for(const t of this.preprocessLayers)e=t.forward(e);for(const[t,n]of this.hiddenLayers.entriesM ()){e=n.forward(e);const r=new G(this.neuronsLife[t],1,e.m);e=H.mul(e,r)}return e=this.outputLayer.forward(e),H.softmax(e)}}function q(e){switch(e){case"relu":return H.relu;case"sigmoid":return H.sigmoid;case"tanh":return H.tanh;case"leaky_relu":return H.leaky_relu;default:return H.linear}}function j(e,t){const n=[],r=[],i=Z(t);let o=null,a=0,l=[];for(const t of e.config.layers)if("InputLayer"==t.class_name)o=t.config.batch_input_shape.slice(1),l=o;else if("Rescaling"==t.class_name)n.push(new $(t.config.scale,t.conM fig.offset));else if("Flatten"==t.class_name)o=[o.reduce(((e,t)=>e*t))];else if("Dense"==t.class_name){const e=[t.config.units],n=o[0]*e[0],l=e[0],s=i.subarray(a,a+n);a+=n;const h=i.subarray(a,a+l);a+=l;const c=new G(s,o[0],e[0]),u=new G(h,1,e[0]),f=q(t.config.activation);r.push(new W(e[0],f,c,u)),o=e}const s=r.pop();return{model:new U(n,r,s),inputDim:l}}function Z(e){const t=window.atob(e),n=t.length/Float32Array.BYTES_PER_ELEMENT,r=new DataView(new ArrayBuffer(Float32Array.BYTES_PER_ELEMENT)),i=new Float32Array(nM );let o=0;for(let e=0;e<n;e++){o=4*e;for(let e=0;e<4;++e)r.setUint8(e,t.charCodeAt(o+e));i[e]=r.getFloat32(0,!0)}return i}class K{constructor(e){this.elt=e,this._events={},this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight}position(){if(0===arguments.length)return{x:this.elt.offsetLeft,y:this.elt.offsetTop};var e="absolute";return"static"!==arguments[2]&&"fixed"!==arguments[2]&&"relative"!==arguments[2]&&"sticky"!==arguments[2]&&"initial"!==arguments[2]&&"inherit"!==arguments[2]||(e=arguments[2]),thiM s.elt.style.position=e,this.elt.style.left=arguments[0]+"px",this.elt.style.top=arguments[1]+"px",this.x=arguments[0],this.y=arguments[1],this}show(){return this.elt.style.display="block",this}hide(){return this.elt.style.display="none",this}size(e,t){if(0===arguments.length)return{width:this.elt.offsetWidth,height:this.elt.offsetHeight};var n=e,r=t;if(n!==te||r!==te){if(n===te?n=t*this.width/this.height:r===te&&(r=e*this.height/this.width),this.elt instanceof HTMLCanvasElement){var i,o={},a=this.elt.getContext("2dM ");for(i in a)o[i]=a[i];for(i in this.elt.setAttribute("width",n*this._pInst._pixelDensity),this.elt.setAttribute("height",r*this._pInst._pixelDensity),this.elt.style.width=n+"px",this.elt.style.height=r+"px",this._pInst.scale(this._pInst._pixelDensity,this._pInst._pixelDensity),o)this.elt.getContext("2d")[i]=o[i]}else this.elt.style.width=n+"px",this.elt.style.height=r+"px",this.elt.width=n,this.elt.height=r;this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight,this._pInst&&this._pInst._curElement&&thiM s._pInst._curElement.elt===this.elt&&(this._pInst._setProperty("width",this.elt.offsetWidth),this._pInst._setProperty("height",this.elt.offsetHeight))}return this}style(e,t){if(t instanceof Color&&(t="rgba("+t.levels[0]+","+t.levels[1]+","+t.levels[2]+","+t.levels[3]/255+")"),void 0===t){if(-1===e.indexOf(":"))return window.getComputedStyle(this.elt).getPropertyValue(e);for(var n=e.split(";"),r=0;r<n.length;r++){var i=n[r].split(":");i[0]&&i[1]&&(this.elt.style[i[0].trim()]=i[1].trim())}}else if(this.elt.style[e]=tM ,"width"===e||"height"===e||"left"===e||"top"===e){var o=window.getComputedStyle(this.elt).getPropertyValue(e).replace(/[^\d.]/g,"");this[e]=Math.round(parseFloat(o,10))}return this}value(){return arguments.length>0?(this.elt.value=arguments[0],this):"range"===this.elt.type?parseFloat(this.elt.value):this.elt.value}mouseClicked(e){return this._adjustListener("click",e,this),this}isFocused(){return document.activeElement===this.elt}_adjustListener(e,t,n){return!1===t?this._detachListener(e,n):this._attachListener(e,M t,n),this}_attachListener(e,t,n){n._events[e]&&this._detachListener(e,n);var r=t.bind(n);n.elt.addEventListener(e,r,!1),n._events[e]=r}_detachListener(e,t){var n=t._events[e];t.elt.removeEventListener(e,n,!1),t._events[e]=null}}function J(e,t){var n=document.createElement("button");return n.innerHTML=e,t&&(n.value=t),ee(n)}function Q(e){var t=arguments.length>1&&void 0!==arguments[1]&&arguments[1],n=function(t){var n=!0,r=!1,i=void 0;try{for(var o,a=t.target.files[Symbol.iterator]();!(n=(o=a.next()).done);n=!0){varM l=o.value;File._load(l,e)}}catch(e){r=!0,i=e}finally{try{n||null==a.return||a.return()}finally{if(r)throw i}}};if(window.File&&window.FileReader&&window.FileList&&window.Blob){var r=document.createElement("input");return r.setAttribute("type","file"),t&&r.setAttribute("multiple",!0),r.addEventListener("change",n,!1),ee(r)}}function ee(e){return document.body.appendChild(e),new K(e)}createImg=function(){var e,t=document.createElement("img"),n=arguments;return n.length>1&&"string"==typeof n[1]&&(t.alt=n[1]),n.lengthM >2&&"string"==typeof n[2]&&(t.crossOrigin=n[2]),t.src=n[0],e=ee(t,this),t.addEventListener("load",(function(){e.width=t.offsetWidth||t.width,e.height=t.offsetHeight||t.height;var r=n[n.length-1];"function"==typeof r&&r(e)})),e},createInput=function(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:"",t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:"text",n=document.createElement("input");return n.setAttribute("value",e),n.setAttribute("type",t),ee(n,this)};const te="auto";function ne(e){re(e);M const t=e._rectMode;e.rectMode(CORNER),e.rect(0,0,e.width,e.height),e.rectMode(t),ie(e)}function re(e){e.push(),e.fill(255,255,255,255),e.blendMode(REMOVE)}function ie(e){e.blendMode(BLEND),e.pop()}File=function(e,t){this.file=e,this._pInst=t;var n=e.type.split("/");this.type=n[0],this.subtype=n[1],this.name=e.name,this.size=e.size,this.data=void 0},File._createLoader=function(e,t){var n=new FileReader;return n.onload=function(n){var r=new File(e);if("application/json"===r.file.type)r.data=JSON.parse(n.target.resulM t);else if("text/xml"===r.file.type){var i=(new DOMParser).parseFromString(n.target.result,"text/xml");r.data=new XML(i.documentElement)}else r.data=n.target.result;t(r)},n},File._load=function(e,t){if(/^text\//.test(e.type)||"application/json"===e.type)File._createLoader(e,t).readAsText(e);else if(/^(video|audio)\//.test(e.type)){var n=new File(e);n.data=URL.createObjectURL(e),t(n)}else File._createLoader(e,t).readAsDataURL(e)},XML=function(e){if(e)this.DOM=e;else{var t=document.implementation.createDocument(null,M "doc");this.DOM=t.createElement("root")}},document.addEventListener("DOMContentLoaded",(function(){addEventListener("mousemove",(e=>{window.mouseX=e.pageX,window.mouseY=e.pageY}))})),new e("global");const oe="86";let ae,le,se,he,ce,ue,fe,de,xe,ge,pe,me,be,ye,we,ve,ze,Ve,_e,Me,Ee,Se,Re,Ie,Ce,Te,Ae,De,ke,Le,Pe,Oe,Fe,Ne,Be,Ye,Ge,He,$e,Xe,We,Ue,qe,je,Ze,Ke,Je,Qe,et,tt,nt,rt,it,ot,at,lt,st,ht,ct,ut,ft,dt,xt,gt,pt,mt,bt,yt,wt,vt,zt,Vt,_t,Mt,Et,St,Rt,It,Ct,Tt,At=!1,Dt=!1,kt=!0,Lt=!1,Pt=!1;const Ot=[" ","Growing","Stable",M "Decaying","Dead","Rebirth"];let Ft,Nt,Bt,Yt,Gt,Ht,$t,Xt,Wt,Ut,qt,jt,Zt,Kt,Jt,Qt,en,tn,nn,rn,on,an,ln,sn,hn=0,cn=0,un=0,fn=!1,dn=!0,xn=!0,gn=null,pn=null,mn=null,bn=!1,yn=!1,wn=null,vn=null,zn=!1;async function setup(){let e=windowWidth,t=windowHeight;createCanvas(e,t),et=createGraphics(e,t),Xe=createGraphics(e,t),$e=createGraphics(e,t),We=createGraphics(e,t),Ue=createGraphics(e,t),qe=createGraphics(e,t),Qe=createGraphics(e,t),je=createGraphics(e,t),Ze=createGraphics(e,t),Ke=createGraphics(e,t),Je=createGraphics(e,M t),tt=createGraphics(500,500),nt=createGraphics(500,500),rt=createGraphics(500,500),_n(),Mn(),Sn(),await En(),Gn(),Rn(),bn=!0}function _n(){Et=parseInt(oe),randomSeed(Et),noiseSeed(Et)}function Mn(){Wt=Ir(p.training_traits),Cr(Wt)}async function En(){let e;Jt=r(),Qt=o(),[Xt,e]=await Promise.all([s(Jt),h(Qt)]),Ut=new V(Wt.visual,e.layers_config,e.weight_b64),Ut.updateAge(new Date),_n(),Wt.training=e.training_traits,Ht=e.model_name,$t=e.classes_name}function Sn(){le=min(width,height)/1024,ut=Rr.findIndex((e=>e[0]===WM t.visual.colorPalette)),ft=[["#ffffff","#231f20","#231f20"],["#231f20","#ffffff","#ffffff"],["#104da8","#ffffff","#ffffff"],["#722F1F","#FCE1B2","#FCE1B2"],["#e88120","#f9f2e5","#f9f2e5"],["#f6b941","#2E2E2E","#2E2E2E"],["#45daaa","#012221","#012221"],["#F1F1F1","#328DFE","#328DFE"],["#111822","#D3EB8D","#D3EB8D"],["#713FF9","#D6D5E6","#D6D5E6"],["#FBDA9D","#795106","#795106"],["#8f5b62","#ead0d0","#ead0d0"],["#eae4cb","#508cac","#508cac"],["#ffc6cc","#cc313d","#cc313d"],["#60A900","#E0FE00","#E0FE00"],["#507DBE","M #D0D1D3","#D0D1D3"],["#305848","#E8F2EE","#E8F2EE"],["#2a2634","#5b6988","#cb78a2","#5b6988"],["#590e29","#fd5e53","#fd5e53","#ffe373"],["#0a141d","#57d4e4","#328195","#2A9ECF","#0ab6a8","#57d4e4"],["#3a2d28","#d5c2ac","#df6338","#3d9895","#d5c2ac"],["#030706","#77c4d9","#77c4d9","#77c4d9","#ffffff","#ffffff","#e72020","#e72020"],["#3a4664","#92f5ff","#f9ff94","#eaa0a2","#55dde0"],["#fbfaff","#f04bb1","#f04bb1","#fac373","#82cef0","#8b31ce"],["#000000","#ffffff","#ff0002","#f26522","#fdff00","#00ff03","#01fffe","#0M 000ff","#ff00ff"]];for(let e=0;e<ft.length;++e)for(let t=0;t<ft[e].length;++t)ft[e][t]=cr(ft[e][t]);pt=[],ct=ft[ut][0],st=ft[ut][1]}function Rn(){gn=document.querySelector("#upload"),pn=document.querySelector("#inputUpload"),gn.addEventListener("dblclick",(()=>{if(!Lt&&!yn)if(In(Ie)&&cn==Ve-1)pn.click();else{if(4!=Pe&&5!=Pe&&(In(Ie)||cn!=Ve-1))return;fn=!0,dn=!0,Bt=0,un=0}})),pn.addEventListener("click",(()=>{pn.value=null,gn.style.display="block"})),pn.addEventListener("change",(()=>{const[e]=pn.files;e?(se=null,gM n.style.display="none",Tn(URL.createObjectURL(e)),mn=e):gn.style.display="block"}))}function In(e){for(let t=0;t<e.length;++t){let n=0;for(let r=0;r<e[t].length;++r)e[t][r]>0&&++n;if(0==n)return!1}return!0}function Cn(){null!=se&&(un=0,Pt=!0,he=0,ue=0,drewLineAnim=!0,ce=(ae/2+we/2)/le,loadImage(se.elt.src,(e=>{const[t,n,r]=Gt,i=createGraphics(t,n);i.image(e,0,0,t,n),i.loadPixels();const o=i.pixels.filter(((e,t)=>t%4!=3)),a=Ut.classifyImage(o);Zt=T([a,$t.map((e=>e.toUpperCase()))]).sort(((e,t)=>e[0]>t[0]?-1:1))})))}M function Tn(e){se=createImg(e,""),se.hide(),Cn()}function An(){zn||(ce+=(width-ae-we)/tn/le),re(Xe),Xe.rect(ce*le,0,width,height),ie(Xe),un>=ge&&1==kt&&(kt=!1,un-=ge),kt&&(re($e),$e.strokeWeight(2*Fe),Jn(he,ze,ct,ct,$e),ie($e)),un>=ge&&0==kt&&(kt=!0,un-=ge,he+=1,he==en&&(++ue,he=0,ce=(ae/2+we/2)/le,1==ue&&(Pt=!1,Dn(),ye=millis())))}function Dn(){At=!0,pe=!1,me=!1,tryButton=br("Try Again",width/2-225*le,height/2+265*le,290*le,40*le,kn),closeResultButton=br("Close",width/2+75*le,height/2+265*le,150*le,40*le,Ln)}functM ion kn(){At=!1,tryButton.hide(),closeResultButton.hide(),pn.click()}function Ln(){Yt=!0,At=!1,Gn(),tryButton.hide(),closeResultButton.hide(),gn.style.display="block",se=null}function keyTyped(){bn&&!1===yn&&!1===yr()&&("i"!==key&&"I"!==key||(Dt=!Dt),"b"!==key&&"B"!==key||(xn=!xn),"s"!==key&&"S"!==key||!1!==Lt||saveCanvasAtCurrentTime(),"k"!==key&&"K"!==key||!1!==Lt||save4KCanvasAtCurrentTime(),"u"!==key&&"U"!==key||!1!==Lt||!1!==At||!1!==fn||!1!==Pt||On())}function On(){Lt=!0,wn=null,vn=null,submitButton=br("SubmitM ",width/2-155*le,height/2+115*le,150*le,40*le,Fn),closeSettingButton=br("Close",width/2+5*le,height/2+115*le,150*le,40*le,Yn),vt=createInput(),vt.position(width/2-252.5*le,height/2-40*le),vt.size(500*le,25*le),vt.style("font-size","15px"),vt.value(Jt||""),zt=createInput(),zt.position(width/2-252.2*le,height/2+35*le),zt.size(500*le,25*le),zt.style("font-size","15px"),zt.value(Qt||"")}function Fn(){Vt=vt.value(),_t=zt.value(),submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide(),Lt=!1,yn=!0,Nn()}async funM ction Nn(){[wn,vn,_]=await Promise.all([c(Vt),u(_t),O(1e3)]),yn=!1,wn&&vn?(n(Vt),i(_t),window.location.reload()):(Lt=!0,submitButton.show(),closeSettingButton.show(),vt.show(),zt.show())}function Bn(){Je.textFont("Trebuchet MS"),Je.noStroke(),pr(Je,600*le,200*le),Je.strokeWeight(1*le),Je.stroke(xt),Je.fill(xt),Je.textSize(50*le),Je.text("update()",width/2,height/2+2.5*le)}function Yn(){wn=null,vn=null,Lt=!1,submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide()}function Gn(){_n(),nn=Date.now(),pe=!1,me=!M 1,St=Wt.training.structure_gen,Rt=Wt.visual.birthYear,It=Wt.visual.lifeCycle,Ct=Wt.training.epoch_num,Tt=Wt.training.activation_func,Ft=Mr.findIndex((e=>e[0]==Wt.visual.hardwareAcceleration))+1,1==Ft?(Nt=30,fe=40):2==Ft?(Nt=15,fe=20):(Nt=2,fe=10);const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePeM rcentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),ae=100*le,ht=50*le,Oe=Sr.findIndex((e=>e[0]==Wt.visual.nodeShape))+1,dt=Er.findIndex((e=>e[0]==Wt.visual.nodeFill))+1,lt=_r.findIndex((e=>e[0]==Wt.visual.pattern))+1,de=Math.tanh(Math.log10(Xt.avgfeerate)),de=map(de,0,1,.2,.8),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.pM ush(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(M Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.lM ength);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,at=.7,pt=[],xt=ft[ut][2],gt=ft[ut][ft[ut].length-1];for(let e=3;e<ft[ut].length-1;e++)pt.push(ft[ut][e]);mt=sr(xt,gt,pt,width),bt=[],wt=[],yt=width/(Ve-1);for(let e=0;e<Ve;e++)bt.push(hr(mt,yt*e/width)),wt.push(hr(mt,yt*e/width));wt.unshift(bt[0]),wt.push(bt[bt.length-1]),hn=0,cn=0,un=0,Yt=!0;const n={xLeft:ae/8,xRight:width-ae/8,yTop:ae/8,yBottom:height-ae/8},r=Ce.map((e=>e.length));jt=new R(btM ,r,n,Oe,le)}function Hn(e,t){let n=Ce[e].length;return[e*we+we/2+ae/2,height/2-(n-1)/2*ve+t*ve]}function $n(e,t){le=min(e,t)/1024,ae=100*le,ht=50*le,we=(e-ae)/Ve,ve=(t-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}xe=floor(De.length*de),Le=[],ke=[],ge=floor(map(de,.2,.8,15,2));for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_M e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,mt=sr(xt,gt,pt,e),bt=[],wt=[],yt=e/(Ve-1);for(let t=0;t<Ve;t++)bt.push(hr(mt,yt*t/e)),wt.push(hr(mt,yt*t/e));wt.unshift(bt[0]),wt.push(bt[bt.length-1])}function Xn(){const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=M Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.leM ngth;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=M Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le}function Wn(){jt.update();const e=4==Pe?0:Kt;jt.draw(Qe,ct,dt,e,le)}function Un(){if(!bn)return ar(),void et.image(je,0,0);if(4==Pe|M |5==Pe)return Wn(),void et.image(Qe,0,0);un>=Nt&&hn<Ve&&(hn++,un=0);for(let e=0;e<hn;e++)1==dt?it=ot=bt[e]:(it=ct,ot=bt[e]),Kn(e,it,ot,$e);un>=Nt&&cn<Ve-1&&(cn++,un=0);for(let e=0;e<cn;e++)Zn(e)}function qn(){et.background(ct),Ue.background(255),Ue.rectMode(CENTER),ne(Ue),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),Ue.stroke(st),Ue.strokeWeight(8*le),Ue.fill(ct),Qe.background(255),Qe.rectMode(CENTER),ne(Qe),Qe.strokeWeight(le),qe.background(255),qe.rectMode(CENTER),ne(qe),qe.textAlign(LEFT),$e.background(255),$eM .rectMode(CENTER),ne($e),Xe.background(255),ne(Xe),Xe.strokeWeight(Ne),We.background(255),We.rectMode(CENTER),ne(We),We.fill(st),We.stroke(st),We.strokeWeight(.1*le),er(lt),We.noStroke(),xn&&(We.rect(ae/16,height/2,ae/8,height),We.rect(width-ae/16,height/2,ae/8,height),We.rect(width/2,ae/16,width,ae/8),We.rect(width/2,height-ae/16,width,ae/8)),Ze.background(255),Ze.rectMode(CENTER),ne(Ze),Ze.textAlign(CENTER,CENTER),Ze.textStyle(BOLD),Ze.stroke(st),Ze.strokeWeight(8*le),Ze.fill(ct),je.background(255),je.rectMode(CEM NTER),ne(je),je.textAlign(CENTER,CENTER),je.textStyle(BOLD),Ke.background(255),Ke.rectMode(CENTER),ne(Ke),Ke.textAlign(CENTER,CENTER),Ke.textStyle(BOLD),Ke.stroke(st),Ke.strokeWeight(8*le),Ke.fill(ct),Je.background(255),Je.rectMode(CENTER),ne(Je),Je.textAlign(CENTER,CENTER),Je.textStyle(BOLD),Je.stroke(st),Je.strokeWeight(8*le),Je.fill(ct),Un(),et.image(We,0,0),Pt&&An(),et.image(Xe,0,0),et.image($e,0,0),At&&(tr(),et.image(Ue,0,0)),fn&&(lr(),et.image(Ze,0,0)),Lt&&(or(),et.image(Ke,0,0)),Dt&&(ir(),et.image(qe,0,0)),yM n&&(Bn(),et.image(Je,0,0))}function draw(){const e=Date.now();bn&&(Ut.updateAge(new Date(e)),Xn()),qn(),image(et,0,0),zn||un++}function Zn(e){let t,n=Ce[e].length,r=Ce[e+1].length;for(let i=0;i<n;i++){const[n,o]=Hn(e,i);for(let a=0;a<r;a++){const[r,l]=Hn(e+1,a);t=map(min(Ce[e][i],Ce[e+1][a]),0,1,0,.5),ur(n,o,r,l,bt[e],bt[e+1],Xe,t)}}}function Kn(e,t,n,r){let i,o,a,l=Ce[e].length;for(let s=0;s<l;s++){const[l,h]=Hn(e,s);i=Ce[e][s],a=map(Be,1/30,1,3,10),o=map(Ce[e][s],0,1,2*a,0)*le,o<1.5*le&&(o=0),Qn(l,h,ze,Oe,t,n,o,iM ,r)}}function Jn(e,t,n,r,i){for(let o=0;o<Le[e].length;o++)Qn(Le[e][o][0],Le[e][o][1],t,Oe,n,r,0,1,i)}function Qn(e,t,n,r,i,o,a,l,s){s.stroke(dr(o,map(l,0,1,.25,1))),s.fill(dr(i,map(l,0,1,.15,1))),s.strokeWeight(Fe),fr([a],s),3==dt&&s.fill(dr(i,0)),1==r?s.ellipse(e,t,n):2==r?s.rect(e,t,7*n/8,7*n/8):3==r&&(s.beginShape(),s.vertex(e-4*n/7,t),s.vertex(e,t-4*n/7),s.vertex(e+4*n/7,t),s.vertex(e,t+4*n/7),s.endShape(CLOSE))}function er(e){if(1==e);else if(2==e){We.strokeWeight(1*le);for(let e=ht/4;e<width+ht/4;e+=ht)for(lM et t=ht/4;t<height+ht/4;t+=ht)We.point(e,t)}else if(3==e){ht=25*le;for(let e=ht/2;e<height+ht/2;e+=ht)We.line(0,e,width,e);for(let e=ht/2;e<width+ht/2;e+=ht)We.line(e,0,e,height)}}function tr(){Ue.textFont("Trebuchet MS"),Ue.textAlign(LEFT,CENTER),Ue.noStroke(),pr(Ue,800*le,500*le),Ue.noStroke(),Ue.fill(dr(st,.75)),Ue.rect(width/2,height/2-100*le,800*le,300*le,25*le,25*le,0,0),Ue.fill(st),Ue.rect(width/2-250*le,height/2-100*le,225*le,225*le),Ue.image(se.elt,width/2-357.5*le,height/2-207.5*le,215*le,215*le);let e=10M 0*Zt[0][0];Ue.fill(ct),Ue.textSize(25*le),Ue.textStyle(NORMAL),1==me&&(e>=0&&e<20?Ue.text("I have a feeling this image belongs to",width/2-100*le,height/2-170*le):e>=20&&e<40?Ue.text("I have a hunch this image belongs to",width/2-100*le,height/2-170*le):e>=40&&e<60?Ue.text("I think this image belongs to",width/2-100*le,height/2-170*le):e>=60&&e<80?Ue.text("I'm almost certain this image belongs to",width/2-100*le,height/2-170*le):Ue.text("I'm positive this image belongs to",width/2-100*le,height/2-170*le));let t=e.tM oFixed(2);"100.00"==t&&(t="100"),1==me&&Ue.text("I'm "+t+"% confident that I'm right!",width/2-100*le,height/2-25*le),example=Zt.map((e=>e[1])),be=Ue.textWidth('"FIDENZAAAA"'),defaultPhrase=Ue.textWidth('"PERPENDICULAR INHABITATION"'),Ue.textStyle(BOLD);const n=me?example[0]:random(example);if(1===n.split(" ").length){let e=75*be/Ue.textWidth('"'+n+'"');e>75&&(e=75),Ue.textSize(e*le),Ue.text('"'+n+'"',width/2-100*le,height/2-90*le)}else nr(width/2-100*le,height/2-90*le,460*le,110*le,n,Ue);if(millis()-ye>1500&&(me=!M 0),C(tt,nt,st,ct,Pe,Mt),Ue.image(nt,width/2-370*le,height/2+70*le,80*le,80*le),3==Pe){let e;e=map(Mt,50,60,.25,1.3),I(rt,e),Ue.image(rt,width/2-370*le,height/2+70*le,80*le,80*le)}let r,i;Ue.image(tt,width/2-370*le,height/2+70*le,80*le,80*le),Ue.fill(xt),Ue.textSize(40*le),Ue.text("INTELLIGENCE INFO",width/2-275*le,height/2+115*le),Ue.textSize(18*le),Ue.textStyle(NORMAL),Ue.circle(width/2-360*le,height/2+180*le,7.5*le),1==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s growing and getting smarter by the M day.`:2==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s stable and it has reached peak performance.`:3==Pe&&(r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s decaying and losing its luster.`),i=2==Pe?"The Perceptron remains stable for some time before entering the decay phase.":`Wait until ${new Date(an).toLocaleString("en-US")} for your Perceptron to reach its peak performance.`,Ue.text(r,width/2-350*le,height/2+180*le),Ue.circle(width/2-360*le,height/2+210*le,7.5*le),Ue.text(i,width/2-350*le,M height/2+210*le),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),gr(Ue,width/2-225*le,width/2+65*le,height/2+265*le,height/2+305*le,"SELECT ANOTHER IMAGE"),gr(Ue,width/2+75*le,width/2+225*le,height/2+265*le,height/2+305*le,"CLOSE")}function nr(e,t,n,r,i,o){let a=i.split(" "),l=75*be/o.textWidth('"'+i+'"'),s=0,h=[],c=[],u=[],f="",d="";if(l>=50)l>75&&(l=75),o.textSize(l*le),o.text('"'+i+'"',e,t);else if(l<50){if(l=50*defaultPhrase/o.textWidth('"'+i+'"'),l>30){if(l>50&&(l=50),[f,d]=rr(l,n,s,h,c,a,f,d,Ue),0==c.length)reM turn o.textSize(l*le),void o.text('"'+i+'"',e,t);for(s=0,h=[],c=[];o.textWidth(d)>n/le;)l=l*n/le/o.textWidth(d),f="",d="",[f,d]=rr(l,n,s,h,c,a,f,d,Ue)}else{l=30,o.textSize(l);for(let e=0;e<a.length;e++)s+=o.textWidth(" "+a[e]),s<=n/le?h.push(a[e]):s>n/le&&s<=n/le*2?c.push(a[e]):u.push(a[e]);for(let e=1;e<h.length;e++)f=f+" "+h[e];if(f='"'+h[0]+f,0==u.length){for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+c[c.length-1]+'"'}else if(1==c.length)d="... "+u[u.length-1]+'"';else{for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";dM =d+"... "+u[u.length-1]+'"'}}o.textSize(l*le);let r=1.25*(o.textDescent()+o.textAscent());o.text(f,e,t-r/2),o.text(d,e,t+r/2)}}function rr(e,t,n,r,i,o,a,l,s){s.textSize(e);for(let e=0;e<o.length;e++)(n+=s.textWidth(" "+o[e]))<=t/le?r.push(o[e]):i.push(o[e]);for(let e=1;e<r.length;e++)a=a+" "+r[e];if(a='"'+r[0]+a,0==i.length&&(a+='"',l=""),1==i.length)l=i[i.length-1]+'"';else{for(let e=0;e<i.length-1;e++)l=l+i[e]+" ";l=l+i[i.length-1]+'"'}return[a,l]}function ir(){const e=45*le;qe.textFont("Tahoma"),qe.stroke(st),qeM .strokeWeight(2*le),qe.fill(ct),qe.rect(width/2,e/2+height-87.5*le,600*le,90*le),qe.fill(st),qe.rect(width/2-150*le,e+height-170*le,300*le,30*le),qe.fill(ct),qe.rect(width/2+150*le,e+height-170*le,300*le,30*le),qe.noStroke(),qe.fill(ct),qe.textSize(15*le),qe.textStyle(BOLD),qe.text("PERCEPTRON INFORMATION",width/2-285*le,e+height-165*le),qe.fill(xt),qe.text("ARTWORK NAME:",width/2+10*le,e+height-165*le),qe.textAlign(RIGHT),qe.textStyle(ITALIC),qe.text("Perceptron #"+Et,width/2+285*le,e+height-165*le);const[t,n]=It.M split(" ");let r;"60 Years"===It?r="1 Year":"60 Months"===It?r="1 Month":"60 Weeks"===It?r="1 Week":"60 Days"===It?r="1 Day":"12 Hours"===It&&(r="12 Minutes"),data=[["AI MODEL NAME:",B(12*le,Ht,140*le)],["SCALE:","1:"+Te],["NUMBER OF CLASSES:",$t.length],["BIRTH YEAR:",Rt],["NUMBER OF REBIRTHS:",sn.toString()],["AGE:",`${Math.ceil(Mt)} Perceptron Years`],["ONE PERCEPTRON YEAR:",`${r}`],["STATE:",Ot[Pe]],["ACTIVE NEURONS:",`${round(ln*rn)} / ${ln}`],["NEXT STATE TIME:",vr(new Date(on))]],qe.fill(xt);const i=data.lenM gth/2;for(let t=0;t<data.length;++t){const n=t<i,r=n?width/2-285*le:width/2+10*le,o=n?width/2-10*le:width/2+285*le,a=e+height-(135-t%i*15)*le;qe.textStyle(BOLD),qe.textAlign(LEFT),qe.textSize(12*le),qe.text(data[t][0],r,a),qe.textStyle(ITALIC),qe.textAlign(RIGHT),qe.textSize(12*le),qe.text(data[t][1],o,a)}}function or(){Ke.textFont("Trebuchet MS"),Ke.noStroke(),pr(Ke,600*le,200*le),gr(Ke,width/2-155*le,width/2-5*le,height/2+115*le,height/2+155*le,"UPDATE"),gr(Ke,width/2+5*le,width/2+155*le,height/2+115*le,height/2+M 155*le,"CLOSE"),Ke.textAlign(LEFT),Ke.fill(xt),Ke.text("UPDATE BITCOIN FULL NODE ADDRESS",width/2-252.5*le,height/2-55*le),Ke.text("UPDATE MODEL ADDRESS",width/2-252.5*le,height/2+20*le),Ke.textAlign(RIGHT),Ke.textStyle(ITALIC),Ke.textSize(15*le),0==wn&&Ke.text("(*) Invalid Address",width/2+252.5*le,height/2-53*le),0==vn&&Ke.text("(*) Invalid Model",width/2+252.5*le,height/2+23*le)}function ar(){je.textFont("Trebuchet MS"),je.fill(st),je.textSize(50*le),je.stroke(st),je.strokeWeight(1*le),je.text("main()",width/2,hM eight/2)}function lr(){un>=20&&1==dn&&(dn=!1,un=0),dn&&(Ze.textFont("Trebuchet MS"),Ze.stroke(st),Ze.fill(ct),Ze.rect(width/2,height/2,600*le,150*le,25*le),Ze.fill(xt),Ze.textSize(75*le),Ze.noStroke(),1==Pe?Ze.text("GROWING",width/2,height/2+5*le):3==Pe?Ze.text("AGING",width/2,height/2+5*le):4==Pe?Ze.text("DEAD",width/2,height/2+5*le):5==Pe&&Ze.text("BIRTH",width/2,height/2+5*le)),un>=20&&0==dn&&(dn=!0,un=0,Bt++,3==Bt&&(fn=!1))}function sr(e,t,n,r){let i=[],o=r/(n.length+1),a=color(e),l=color(t);i.push(a);for(let eM =0;e<n.length;e++){let t=color(n[e]);for(let e=1;e<=o;e++){let n=lerpColor(a,t,e/o);i.push(n)}a=t}for(let e=1;e<o;e++){let t=lerpColor(a,l,e/o);i.push(t)}if(i.push(l),i.length>r)i.splice(r);else if(i.length<r){let e=i[i.length-1];for(;i.length<r;)i.push(e)}return i}function hr(e,t){let n=e.length,r=Math.floor(t*n);return r>=n&&(r=n-1),e[r]}function cr(e){e=e.replace("#","");var t=parseInt(e,16);return color(t>>16&255,t>>8&255,255&t)}function ur(e,t,n,r,i,o,a,l){var s=a.drawingContext.createLinearGradient(e,t,n,r);sM .addColorStop(0,i),s.addColorStop(1,o),a.drawingContext.strokeStyle=s,a.drawingContext.globalAlpha=l,a.line(e,t,n,r),a.drawingContext.globalAlpha=1}function fr(e,t){t.drawingContext.setLineDash(e)}function dr(e,t){let n=color(e),r=red(n),i=green(n),o=blue(n);return color(r,i,o,255*t)}function xr(e,t,n,r){return mouseX>e&&mouseX<t&&mouseY>n&&mouseY<r}function gr(e,t,n,r,i,o){e.strokeWeight(1*le),e.stroke(st);const[a,l]=xr(t,n,r,i)?[xt,ct]:[ct,xt];e.fill(a),e.push(),e.rectMode(CORNERS),e.rect(t,r,n,i,5*le),e.pop(),e.M noStroke(),e.textSize(20*le),e.fill(l),e.text(o,(t+n)/2,(46*r+54*i)/100)}function pr(e,t,n){e.fill(0,0,0,75),e.rect(width/2,height/2,width,height),e.stroke(st),e.fill(ct),e.rect(width/2,height/2,t,n,25*le)}function mr(e,t){resizeCanvas(e,t,!0),Xe.resizeCanvas(e,t,!0),$e.resizeCanvas(e,t,!0),We.resizeCanvas(e,t,!0),Ue.resizeCanvas(e,t,!0),qe.resizeCanvas(e,t,!0),Qe.resizeCanvas(e,t,!0),je.resizeCanvas(e,t,!0),Ze.resizeCanvas(e,t,!0),Ke.resizeCanvas(e,t,!0),Je.resizeCanvas(e,t,!0),et.resizeCanvas(e,t,!0)}function br(M e,t,n,r,i,o){const a=J(e);return a.position(t,n),a.size(r,i),a.style("opacity","0"),a.mouseClicked(o),a}function yr(){return null!=vt&&vt?.isFocused()||null!=zt&&zt?.isFocused()}function wr(e,t,n,r){let i;if(e<=3){i=`Hey ${String.fromCodePoint(128075)}, I'm ${n}, ${t} years old. I can detect ${r.length} NFT collections: `;let e=0;for(let t=0;t<r.length;++t){const n=r[t];if(e+n.length>500){i+=", etc";break}t==r.length-1?i+=", and ":t>0&&(i+=", "),i+=n,e+=n.length}i+=". ",t<=5?i+="However, I am only a baby, so my recM ognition ability is not accurate. I'm in the state of Growing both looks and intelligence.":t<=13?i+="I am now a child. My recognition ability is becoming better, but still not very accurate. I'm in the state of Growing both looks and intelligence.":t<=25?i+="I have grown up to be a teen. My recognition ability almost reaches the peak, but I will still mess up sometimes. I'm in the state of Growing both looks and intelligence.":t<=50?i+="I finally reach adulthood. My recognition is fully functional now. I'm in the M Stable state, where I am the most intelligent with all neurons activated.":t<=60&&(i+="I am now an old Perceptron, so my recognition ability is no longer the best. I'm in the Decaying state, meaning that my neurons are dying, and my intelligence is decreasing over time.")}else 4==e?i=`${n} is Dead. However, this is not the end to its story...`:5==e&&(i=`${n} is now in the Rebirth state, and is preparing to start a new life.`);return i}function vr(e){const t=e.getDate(),n=e.toLocaleString("en-US",{month:"long"}),r=eM .getFullYear();let i=e.getHours().toString();1==i.length&&(i="0"+i);let o=e.getMinutes().toString();return 1==o.length&&(o="0"+o),`${Y(t)} ${n} ${r} | ${i}:${o}`}saveCanvasAtCurrentTime=()=>{save(N())},save4KCanvasAtCurrentTime=()=>{const e=width,t=height,n=min(4096/min(e,t),1e4/max(e,t)),r=e*n,i=t*n;mr(r,i),zn=!0,$n(r,i),qn();let o="4K_"+N()+".png";saveCanvas(et,o),mr(e,t),$n(e,t),zn=!1};const zr=[["60 Years",3,365],["60 Months",40,30],["60 Weeks",37,7],["60 Days",20,1]],Vr=[["1943",1],["1951",1.5],["1957",2],["19M 69",2.5],["1970",3],["1980",3.5],["1982",4],["1986",4.5],["1988",5],["1997",5.5],["1998",6],["2002",6.5],["2009",7],["2012",7.5],["2014",8],["2015",8.5],["2016",9],["2023",15]],_r=[["Plain",20],["Dotted",40],["Squared",40]],Mr=[["Basic",30],["Standard",60],["Advanced",10]],Er=[["MNIST",70],["CIFAR",25],["IMAGENET",5]],Sr=[["Theano",60],["Torch",30],["TensorFlow",10]],Rr=[["Whitepaper",2],["Blackboard",2],["Blueprint",2],["Nak",74/14],["Jims",74/14],["Level 10",74/14],["Flips",74/14],["Level 14",74/14],["III",74/14]M ,["XMB",74/14],["Info",74/14],["Adventure",74/14],["Marigold",74/14],["Phoenix",74/14],["Love",74/14],["Cachet",74/14],["Human",74/14],["Twilight",3],["Sunset",3],["Aurora",3],["Liminal Space",3],["D Vu",3],["Lucid Dream",3],["Parallel",1],["Multiverse",1]];function Ir(e){for(let e=0;e<100;++e)random(1);return{visual:{pattern:k(_r),hardwareAcceleration:k(Mr),nodeFill:k(Er),nodeShape:k(Sr),colorPalette:k(Rr),lifeCycle:k(zr),birthYear:k(Vr)},training:e}}function Cr(e){window.$generativeTraits={"Network ArchitectM ure":e.training.structure_gen,"Hidden Layers":e.training.n_layers,"Max Neurons Per Hidden Layer":e.training.max_nodes,"Activation Function":e.training.activation_func,"Training Epochs":e.training.epoch_num,Dataset:e.visual.nodeFill,"Deep Learning Framework":e.visual.nodeShape,"Hardware Acceleration":e.visual.hardwareAcceleration,"Paper Pattern":e.visual.pattern,"Life Cycle":e.visual.lifeCycle,"Birth Year":e.visual.birthYear,"Color Palette":e.visual.colorPalette}} <script defer src="https://static.clMn oudflareinsights.com/beacon.min.js/v2b4487d741ca48dcbadcaf954e159fc61680799950996" integrity="sha512-D/jdE0CypeVxFadTejKGTzmwyV10c1pxZk/AqjJuZbaJwGMyNHY3q/mTPWqMUnFACfCTunhZUVcd4cV78dK1pQ==" data-cf-beacon='{"rayId":"7b4c9f850d2853fb","version":"2023.3.0","b":1,"token":"6c07c178c94442f695e7a0a2aaee641a","si":100}' crossorigin="anonymous"></script> text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 1{"p":"sns","op":"reg","name":" XMP DataXMP<?xpacket begin=" " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 7.1-c000 79.ccf84e0, 2022/06/22-22:13:26 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:xmpMM="http://ns.adobe.com/xap/1.0/mm/" xmlns:stRef="http://ns.adobe.com/xap/1.0/sType/ResourceRef#" xmp:CreatorTool="Adobe Photoshop 22.5 (Windows)" xmpMM:InstaM nceID="xmp.iid:AF482BD0D62911ED8727BA58B35C8F87" xmpMM:DocumentID="xmp.did:AF482BD1D62911ED8727BA58B35C8F87"> <xmpMM:DerivedFrom stRef:instanceID="xmp.iid:AF482BCED62911ED8727BA58B35C8F87" stRef:documentID="xmp.did:AF482BCFD62911ED8727BA58B35C8F87"/> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> ~}|{zyxwvutsrqponmlkjihgfedcba`_^]\[ZYXWVUTSRQPONMLKJIHGFEDCBA@?>=<;:98765432M XMP DataXMP<?xpacket begin=" " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 7.1-c000 79.ccf84e0, 2022/06/22-22:13:26 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmlns:xmpMM="http://ns.adobe.com/xap/1.0/mm/" xmlns:stRef="http://ns.adobe.com/xap/1.0/sType/ResourceRef#" xmp:CreatorTool="Adobe Photoshop 22.5 (Windows)" xmpMM:InstaM nceID="xmp.iid:4BFDB86DD62911ED9E9FBB83C4AC22AB" xmpMM:DocumentID="xmp.did:4BFDB86ED62911ED9E9FBB83C4AC22AB"> <xmpMM:DerivedFrom stRef:instanceID="xmp.iid:4BFDB86BD62911ED9E9FBB83C4AC22AB" stRef:documentID="xmp.did:4BFDB86CD62911ED9E9FBB83C4AC22AB"/> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> ~}|{zyxwvutsrqponmlkjihgfedcba`_^]\[ZYXWVUTSRQPONMLKJIHGFEDCBA@?>=<;:98765432M {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "moon"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "cape"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "blue fire"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "dragon wings"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "moon"}, {"trait_type": "Body", "value": "silver"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "honey pot"}, {"trait_type": "Eyes", "value": "golden"}, {"trait_type": "Headgear", "value": "skull"}, {"trait_type": "Artifacts", "value": "broadsword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "midas touch"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "sword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "whale"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "pauldrons"}]} text/html;charset=utf-8 <meta charset="utf-8" /> position: relative; width: var(--width); height: var(--height); border: 1px solid blue; position: relative; <div id="upload"> <input id="inputUpload" type="file"> function e(e){"use strict";return new function e(t){let n="global"==t?window:this;n.canvas=document.createElement("canvas");let r=n.canvas.getContext("2d");n.width=100,n.height=100,n.canvas.width=n.width,n.canvas.height=n.height,"offscreen"!=t&&(document.body?document.body.appendChild(n.canvas):window.addEventListener("load",(function(){document.body.appendChild(n.canvas)}))),g(),n.MAGIC=161533525,n.RGB=0,n.HSV=1,n.HM SB=1,n.CHORD=0,n.PIE=1,n.OPEN=2,n.RADIUS=1,n.CORNER=2,n.CORNERS=3,n.ROUND="round",n.SQUARE="butt",n.PROJECT="square",n.MITER="miter",n.BEVEL="bevel",n.CLOSE=1,n.BLEND="source-over",n.REMOVE="destination-out",n.ADD="lighter",n.DARKEST="darken",n.LIGHTEST="lighten",n.DIFFERENCE="difference",n.SUBTRACT="subtract",n.EXCLUSION="exclusion",n.MULTIPLY="multiply",n.SCREEN="screen",n.REPLACE="copy",n.OVERLAY="overlay",n.HARD_LIGHT="hard-light",n.SOFT_LIGHT="soft-light",n.DODGE="color-dodge",n.BURN="color-burn",n.NORMAL="norM mal",n.ITALIC="italic",n.BOLD="bold",n.BOLDITALIC="italic bold",n.CENTER="center",n.LEFT="left",n.RIGHT="right",n.TOP="top",n.BOTTOM="bottom",n.BASELINE="alphabetic",n.LANDSCAPE="landscape",n.PORTRAIT="portrait",n.ALT=18,n.BACKSPACE=8,n.CONTROL=17,n.DELETE=46,n.DOWN_ARROW=40,n.ENTER=13,n.ESCAPE=27,n.LEFT_ARROW=37,n.OPTION=18,n.RETURN=13,n.RIGHT_ARROW=39,n.SHIFT=16,n.TAB=9,n.UP_ARROW=38,n.HALF_PI=Math.PI/2,n.PI=Math.PI,n.QUARTER_PI=Math.PI/4,n.TAU=2*Math.PI,n.TWO_PI=2*Math.PI,n.THRESHOLD=1,n.GRAY=2,n.OPAQUE=3,n.INVEM RT=4,n.POSTERIZE=5,n.DILATE=6,n.ERODE=7,n.BLUR=8,n.ARROW="default",n.CROSS="crosshair",n.HAND="pointer",n.MOVE="move",n.TEXT="text",n.VIDEO={video:!0,audio:!1},n.AUDIO={video:!1,audio:!0},n.SHR3=1,n.LCG=2,n.HARDWARE_FILTERS=!0,n.hint=function(e,t){n[e]=t},n.frameCount=0,n.mouseX=0,n.mouseY=0,n.pmouseX=0,n.pmouseY=0,n.mouseButton=null,n.keyIsPressed=!1,n.mouseIsPressed=!1,n.key=null,n.keyCode=null,n.pixels=null,n.accelerationX=0,n.accelerationY=0,n.accelerationZ=0,n.rotationX=0,n.rotationY=0,n.rotationZ=0,n.relRotatM ionX=0,n.relRotationY=0,n.relRotationZ=0,n.pAccelerationX=0,n.pAccelerationY=0,n.pAccelerationZ=0,n.pRotationX=0,n.pRotationY=0,n.pRotationZ=0,n.pRelRotationX=0,n.pRelRotationY=0,n.pRelRotationZ=0,n.touches=[],n._styleCache=[{colorMode:n.RGB,noStroke:!1,noFill:!1,ellipseMode:n.CENTER,rectMode:n.CORNER,curveDetail:20,curveAlpha:0,textFont:"sans-serif",textSize:12,textLeading:12,textStyle:"normal"}],n._style=n._styleCache[n._styleCache.length-1],n._noLoop=!1,n._pixelDensity=1,n._frameRate=null,n._tint=null;let i=nullM ,o=!0,a=[],l=null,s=0,h={},c=0,u=null,f=null,d=null;Object.defineProperty(n,"deviceOrientation",{get:function(){return 90==Math.abs(window.orientation)?n.LANDSCAPE:n.PORTRAIT}}),Object.defineProperty(n,"windowWidth",{get:function(){return window.innerWidth}}),Object.defineProperty(n,"windowHeight",{get:function(){return window.innerHeight}}),Object.defineProperty(n,"drawingContext",{get:function(){return r}}),n.createCanvas=function(e,t){return n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t,g(),n.canvas},nM .resizeCanvas=function(e,t){n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t},n.createGraphics=n.createImage=function(t,n){let r=new e("offscreen");return r.createCanvas(t,n),r.noLoop(),r},n.pixelDensity=function(e){return null==e||(n._pixelDensity=e,n.canvas.width=Math.ceil(n.width*e),n.canvas.height=Math.ceil(n.height*e),n.canvas.style.width=n.width+"px",n.canvas.style.height=n.height+"px",r.scale(n._pixelDensity,n._pixelDensity),g()),n._pixelDensity},n.map=function(e,t,n,r,i,o){let a=r+1*(e-t)/(n-t)*(i-r)M ;return o?r<i?Math.min(Math.max(a,r),i):Math.min(Math.max(a,i),r):a},n.lerp=function(e,t,n){return e*(1-n)+t*n},n.constrain=function(e,t,n){return Math.min(Math.max(e,t),n)},n.dist=function(){return 4==arguments.length?Math.hypot(arguments[0]-arguments[2],arguments[1]-arguments[3]):Math.hypot(arguments[0]-arguments[3],arguments[1]-arguments[4],arguments[2]-arguments[5])},n.norm=function(e,t,r){return n.map(e,t,r,0,1)},n.sq=function(e){return e*e},n.fract=function(e){return e-Math.floor(e)},n.degrees=function(e){retM urn 180*e/Math.PI},n.radians=function(e){return e*Math.PI/180},n.abs=Math.abs,n.ceil=Math.ceil,n.exp=Math.exp,n.floor=Math.floor,n.log=Math.log,n.mag=Math.hypot,n.max=Math.max,n.min=Math.min,n.round=Math.round,n.sqrt=Math.sqrt,n.sin=Math.sin,n.cos=Math.cos,n.tan=Math.tan,n.asin=Math.asin,n.acos=Math.acos,n.atan=Math.atan,n.atan2=Math.atan2,n.Vector=function(e,t,r){let i=this;i.x=e||0,i.y=t||0,i.z=r||0;let o=null,a=null;function l(e,t,n){return null!=e.x?e:null!=t?{x:e,y:t,z:n||0}:{x:e,y:e,z:e}}function s(){null==a&M &(a=i.x*i.x+i.y*i.y+i.z*i.z,o=Math.sqrt(a))}function h(){a=null,o=null}i.set=function(e,t,n){i.x=e||0,i.y=t||0,i.z=n||0},i.copy=function(){return new n.Vector(i.x,i.y,i.z)},i.add=function(){let e=l.apply(null,arguments);return i.x+=e.x,i.y+=e.y,i.z+=e.z,h(),i},i.rem=function(){let e=l.apply(null,arguments);return i.x%=e.x,i.y%=e.y,i.z%=e.z,h(),i},i.sub=function(){let e=l.apply(null,arguments);return i.x-=e.x,i.y-=e.y,i.z-=e.z,h(),i},i.mult=function(){let e=l.apply(null,arguments);return i.x*=e.x,i.y*=e.y,i.z*=e.z,hM (),i},i.div=function(){let e=l.apply(null,arguments);return i.x/=e.x,i.y/=e.y,i.z/=e.z,h(),i},i.mag=function(){return s(),o},i.magSq=function(){return s(),a},i.dot=function(){let e=l.apply(null,arguments);return i.x*e.x+i.y*e.y+i.z*e.z},i.dist=function(){let e=l.apply(null,arguments),t=i.x-e.x,n=i.y-e.y,r=i.z-e.z;return Math.sqrt(t*t+n*n+r*r)},i.cross=function(){let e=l.apply(null,arguments),t=i.y*e.z-i.z*e.y,n=i.z*e.x-i.x*e.z,r=i.x*e.y-i.y*e.x;return i.x=t,i.y=n,i.z=r,h(),i},i.normalize=function(){s();let e=o;retuM rn i.x/=e,i.y/=e,i.z/=e,o=1,a=1,i},i.limit=function(e){s();if(o>e){let t=e/o;i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e}return i},i.setMag=function(e){s();let t=e/o;return i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e,i},i.heading=function(){return Math.atan2(i.y,i.x)},i.rotate=function(e){let t=Math.cos(e),n=Math.sin(e),r=i.x*t-i.y*n,o=i.x*n+i.y*t;return i.x=r,i.y=o,i},i.angleBetween=function(){let e=l.apply(null,arguments);const t=i.dot(e)/(i.mag()*e.mag());let n;return n=Math.acos(Math.min(1,Math.max(-1,t))),n*Math.sign(i.cross(e).z||1)},M i.lerp=function(e,t){return i.x=i.x*(1-t)+e.x*t,i.y=i.y*(1-t)+e.y*t,i.z=i.z*(1-t)+e.z*t,h(),i},i.reflect=function(e){return e.normalize(),i.sub(e.mult(2*i.dot(e)))},i.array=function(){return[i.x,i.y,i.z]},i.equals=function(e,t){return null==t&&null==(t=Number.EPSILON)&&(t=0),Math.abs(e.x-i.x)<t&&Math.abs(e.y-i.y)<t&&Math.abs(e.z-i.z)<t},i.fromAngle=function(e,t){return null==t&&(t=1),o=t,a=t*t,i.x=t*Math.cos(e),i.y=t*Math.sin(e),i.z=0,i},i.fromAngles=function(e,t,n){null==n&&(n=1),o=n,a=n*n;const r=Math.cos(t),l=MaM th.sin(t),s=Math.cos(e),h=Math.sin(e);return i.x=n*h*l,i.y=-n*s,i.z=n*h*r,i},i.random2D=function(){return o=1,a=1,i.fromAngle(Math.random()*Math.PI*2)},i.random3D=function(){return o=1,a=1,i.fromAngles(Math.random()*Math.PI*2,Math.random()*Math.PI*2)},i.toString=function(){return`[${i.x}, ${i.y}, ${i.z}]`}},n.Vector.add=function(e,t){return new n.Vector(e.x+t.x,e.y+t.y,e.z+t.z)},n.Vector.rem=function(e,t){return new n.Vector(e.x%t.x,e.y%t.y,e.z%t.z)},n.Vector.sub=function(e,t){return new n.Vector(e.x-t.x,e.y-t.y,e.M z-t.z)},n.Vector.mult=function(e,t){return null==t.x?new n.Vector(e.x*t,e.y*t,e.z*t):new n.Vector(e.x*t.x,e.y*t.y,e.z*t.z)},n.Vector.div=function(e,t){return null==t.x?new n.Vector(e.x/t,e.y/t,e.z/t):new n.Vector(e.x/t.x,e.y/t.y,e.z/t.z)},n.Vector.dist=function(e,t){return Math.hypot(e.x-t.x,e.y-t.y,e.z-t.z)},n.Vector.cross=function(e,t){return new n.Vector(e.y*t.z-e.z*t.y,e.z*t.x-e.x*t.z,e.x*t.y-e.y*t.x)},n.Vector.lerp=function(e,t,r){return new n.Vector(e.x*(1-r)+t.x*r,e.y=e.y*(1-r)+t.y*r,e.z=e.z*(1-r)+t.z*r)},n.M Vector.equals=function(e,t,n){return e.equals(t,n)};for(let e of["fromAngle","fromAngles","random2D","random3D"])n.Vector[e]=function(t,r,i){return(new n.Vector)[e](t,r,i)};function x(e,t,n){let r,i,o,a,l,s,h,c,u;if(0==t)return[255*(r=n),255*(i=n),255*(o=n)];switch((a=e)>360&&(a=0),h=n*(1-t),c=n*(1-t*(s=(a/=60)-(l=~~a))),u=n*(1-t*(1-s)),l){case 0:r=n,i=u,o=h;break;case 1:r=c,i=n,o=h;break;case 2:r=h,i=n,o=u;break;case 3:r=h,i=c,o=n;break;case 4:r=u,i=h,o=n;break;default:r=n,i=h,o=c}return[255*r,255*i,255*o]}functioM n g(){r.fillStyle="white",r.strokeStyle="black",r.lineCap="round",r.lineJoin="miter"}function p(e){if(0<=e&&e<2*Math.PI)return e;for(;e<0;)e+=2*Math.PI;for(;e>=Math.PI;)e-=2*Math.PI;return e}function m(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;let c=p(a),u=p(l);r.beginPath();for(let a=0;a<h+1;a++){let l=a/h,s=n.lerp(c,u,l),f=Math.cos(s)*i/2,d=Math.sin(s)*o/2;r[a?"lineTo":"moveTo"](e+f,t+d)}s==n.CHORD?r.closePath():s==n.PIE&&(r.lineTo(e,t),r.closePath()),n._style.noFill||r.fill(),n._style.noStrokM e||r.stroke()}function b(e,t,i,o){n._style.noFill&&n._style.noStroke||(r.beginPath(),r.ellipse(e,t,i/2,o/2,0,0,2*Math.PI),n._style.noFill||r.fill(),n._style.noStroke||r.stroke())}function y(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;if(null==a)return function(e,t,i,o){n._style.noFill||r.fillRect(e,t,i,o),n._style.noStroke||r.strokeRect(e,t,i,o)}(e,t,i,o);if(null==l)return y(e,t,i,o,a,a,a,a);const c=Math.min(Math.abs(o),Math.abs(i))/2;a=Math.min(c,a),l=Math.min(c,l),h=Math.min(c,h),s=Math.min(c,s)M ,r.beginPath(),r.moveTo(e+a,t),r.arcTo(e+i,t,e+i,t+o,l),r.arcTo(e+i,t+o,e,t+o,s),r.arcTo(e,t+o,e,t,h),r.arcTo(e,t,e+i,t,a),r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke()}function w(){a=[]}n.createVector=function(e,t,r){return new n.Vector(e,t,r)},n.curvePoint=function(e,t,n,r,i){const o=i*i*i,a=i*i;return e*(-.5*o+a-.5*i)+t*(1.5*o-2.5*a+1)+n*(-1.5*o+2*a+.5*i)+r*(.5*o-.5*a)},n.bezierPoint=function(e,t,n,r,i){const o=1-i;return Math.pow(o,3)*e+3*Math.pow(o,2)*i*t+3*o*Math.pow(i,2)*n+Math.pow(i,M 3)*r},n.curveTangent=function(e,t,n,r,i){const o=i*i;return e*(-3*o/2+2*i-.5)+t*(9*o/2-5*i)+n*(-9*o/2+4*i+.5)+r*(3*o/2-i)},n.bezierTangent=function(e,t,n,r,i){const o=1-i;return 3*r*Math.pow(i,2)-3*n*Math.pow(i,2)+6*n*o*i-6*t*o*i+3*t*Math.pow(o,2)-3*e*Math.pow(o,2)},n.Color=function(e,t,n,r){let i=this;i.MAGIC=786698,i._r=e,i._g=t,i._b=n,i._a=r,i._h=0,i._s=0,i._v=0,i._hsvInferred=!1,i.setRed=function(e){i._r=e,i._hsvInferred=!1},i.setGreen=function(e){i._g=e,i._hsvInferred=!1},i.setBlue=function(e){i._b=e,i._hsvInfM erred=!1},i.setAlpha=function(e){i._a=e/255,i._hsvInferred=!1},i._inferHSV=function(){i._hsvInferred||([i._h,i._s,i._v]=function(e,t,n){let r,i,o,a,l;return r=e<t?e<n?e:n:t<n?t:n,0==(l=100*(i=e>t?e>n?e:n:t>n?t:n)/255)?[o=0,a=0,l]:0==(a=100*(i-r)/i)?[o=0,a,l]:(o=i==e?0+60*(t-n)/(i-r):i==t?120+60*(n-e)/(i-r):240+60*(e-t)/(i-r),[o,a,l])}(i._r,i._g,i._b),i._hsvInferred=!0)},i.toString=function(){return`rgba(${Math.round(i._r)},${Math.round(i._g)},${Math.round(i._b)},${~~(1e3*i._a)/1e3})`}},n.colorMode=function(e){n._stM yle.colorMode=e},n.color=function(){if(1==arguments.length&&786698==arguments[0].MAGIC)return arguments[0];if(n._style.colorMode==n.RGB){if(1==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],1);if(2==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],arguments[1]/255);if(3==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],1);if(4==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],arguments[3]/255)}else{if(1==argumeM nts.length)return new n.Color(...x(0,0,arguments[0]/100),1);if(2==arguments.length)return new n.Color(...x(0,0,arguments[0]/100),arguments[1]/255);if(3==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),1);if(4==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),arguments[3])}return null},n.red=function(e){return e._r},n.green=function(e){return e._g},n.blue=function(e){return e._b},n.alpha=function(e){return 255*e._a},n.hue=function(e){reM turn e._inferHSV(),e._h},n.saturation=function(e){return e._inferHSV(),e._s},n.brightness=function(e){return e._inferHSV(),e._v},n.lightness=function(e){return 100*(.2126*e._r+.7152*e._g+.0722*e._b)/255},n.lerpColor=function(e,t,r){return n._style.colorMode==n.RGB?new n.Color(n.constrain(n.lerp(e._r,t._r,r),0,255),n.constrain(n.lerp(e._g,t._g,r),0,255),n.constrain(n.lerp(e._b,t._b,r),0,255),n.constrain(n.lerp(e._a,t._a,r),0,1)):(e._inferHSV(),t._inferHSV(),new n.Color(n.constrain(function(e,t,r){var i=[[Math.abs(t-M e),n.map(r,0,1,e,t)],[Math.abs(t+360-e),n.map(r,0,1,e,t+360)],[Math.abs(t-360-e),n.map(r,0,1,e,t-360)]];return i.sort(((e,t)=>e[0]-t[0])),(i[0][1]+720)%360}(e._h,t._h,r),0,360),n.constrain(n.lerp(e._s,t._s,r),0,100),n.constrain(n.lerp(e._v,t._v,r),0,100),n.constrain(n.lerp(e._a,t._a,r),0,1)))},n.strokeWeight=function(e){n._style_noStroke=!1,r.lineWidth=e},n.stroke=function(){if(n._style.noStroke=!1,"string"==typeof arguments[0])return void(r.strokeStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._sM tyle.noStroke=!0:r.strokeStyle=e},n.noStroke=function(){n._style.noStroke=!0},n.fill=function(){if(n._style.noFill=!1,"string"==typeof arguments[0])return void(r.fillStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._style.noFill=!0:r.fillStyle=e},n.noFill=function(){n._style.noFill=!0},n.blendMode=function(e){r.globalCompositeOperation=e},n.strokeCap=function(e){r.lineCap=e},n.strokeJoin=function(e){r.lineJoin=e},n.ellipseMode=function(e){n._style.ellipseMode=e},n.rectMode=function(e){n._style.rectM Mode=e},n.curveDetail=function(e){n._style.curveDetail=e},n.curveAlpha=function(e){n._style.curveAlpha=e},n.curveTightness=function(e){n._style.curveAlpha=e},n.clear=function(){r.clearRect(0,0,n.width,n.height)},n.background=function(){if(arguments[0]&&arguments[0].MAGIC==n.MAGIC)return n.image(arguments[0],0,0,n.width,n.height);r.save(),r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity),r.fillStyle="string"==typeof arguments[0]?arguments[0]:n.color(...Array.from(arguments)),r.fillRect(0,0,n.width,n.heightM ),r.restore()},n.line=function(e,t,i,o){n._style.noStroke||(r.beginPath(),r.moveTo(e,t),r.lineTo(i,o),r.stroke())},n.arc=function(e,t,r,i,o,a,l,s){if(o==a)return n.ellipse(e,t,r,i);null==s&&(s=25),null==l&&(l=n.PIE),n._style.ellipseMode==n.CENTER?m(e,t,r,i,o,a,l,s):n._style.ellipseMode==n.RADIUS?m(e,t,2*r,2*i,o,a,l,s):n._style.ellipseMode==n.CORNER?m(e+r/2,t+i/2,r,i,o,a,l,s):n._style.ellipseMode==n.CORNERS&&m((e+r)/2,(t+i)/2,r-e,i-t,o,a,l,s)},n.ellipse=function(e,t,r,i){null==i&&(i=r),n._style.ellipseMode==n.CENTERM ?b(e,t,r,i):n._style.ellipseMode==n.RADIUS?b(e,t,2*r,2*i):n._style.ellipseMode==n.CORNER?b(e+r/2,t+i/2,r,i):n._style.ellipseMode==n.CORNERS&&b((e+r)/2,(t+i)/2,r-e,i-t)},n.circle=function(e,t,r){return n.ellipse(e,t,r,r)},n.point=function(e,t){e.x&&(t=e.y,e=e.x),r.beginPath(),r.ellipse(e,t,.4,.4,0,0,2*Math.PI),r.stroke()},n.rect=function(e,t,r,i,o,a,l,s){n._style.rectMode==n.CENTER?y(e-r/2,t-i/2,r,i,o,a,l,s):n._style.rectMode==n.RADIUS?y(e-r,t-i,2*r,2*i,o,a,l,s):n._style.rectMode==n.CORNER?y(e,t,r,i,o,a,l,s):n._stylM e.rectMode==n.CORNERS&&y(e,t,r-e,i-t,o,a,l,s)},n.square=function(e,t,r,i,o,a,l){return n.rect(e,t,r,r,i,o,a,l)},n.beginShape=function(){w(),r.beginPath(),o=!0},n.beginContour=function(){r.closePath(),w(),o=!0},n.endContour=function(){w(),o=!0},n.vertex=function(e,t){w(),o?r.moveTo(e,t):r.lineTo(e,t),o=!1},n.bezierVertex=function(e,t,n,i,o,a){w(),r.bezierCurveTo(e,t,n,i,o,a)},n.quadraticVertex=function(e,t,n,i){w(),r.quadraticCurveTo(e,t,n,i)},n.bezier=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.bezierVM ertex(r,i,o,a,l,s),n.endShape()},n.triangle=function(e,t,r,i,o,a){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.endShape(n.CLOSE)},n.quad=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.vertex(l,s),n.endShape(n.CLOSE)},n.endShape=function(e){w(),e&&r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke(),n._style.noFill&&n._style.noStroke&&(r.save(),r.fillStyle="none",r.fill(),r.restore())},n.curveVertex=function(e,t){if(a.push([e,t]),a.length<4)return;M let i=function(e,t,n,r,i,o,a,l,s,h){function c(e,t,n,r,i,o){let a=Math.pow(r-t,2)+Math.pow(i-n,2);return Math.pow(a,.5*o)+e}let u=[],f=c(0,e,t,n,r,h),d=c(f,n,r,i,o,h),x=c(d,i,o,a,l,h);for(let h=0;h<s;h++){let c=f+h/(s-1)*(d-f),g=[(f-c)/(f-0),(c-0)/(f-0),(d-c)/(d-f),(c-f)/(d-f),(x-c)/(x-d),(c-d)/(x-d),(d-c)/(d-0),(c-0)/(d-0),(x-c)/(x-f),(c-f)/(x-f)];for(let e=0;e<g.length;e+=2)isNaN(g[e])&&(g[e]=1,g[e+1]=0),isFinite(g[e])||(g[e]>0?(g[e]=1,g[e+1]=0):(g[e]=0,g[e+1]=1));let p=e*g[0]+n*g[1],m=t*g[0]+r*g[1],b=n*g[2]+i*g[M 3],y=r*g[2]+o*g[3],w=i*g[4]+a*g[5],v=o*g[4]+l*g[5],z=p*g[6]+b*g[7],V=m*g[6]+y*g[7],_=b*g[8]+w*g[9],M=y*g[8]+v*g[9],E=z*g[2]+_*g[3],S=V*g[2]+M*g[3];u.push([E,S])}return u}(...a[a.length-4],...a[a.length-3],...a[a.length-2],...a[a.length-1],n._style.curveDetail,n._style.curveAlpha);for(let e=0;e<i.length;e++)o?r.moveTo(...i[e]):r.lineTo(...i[e]),o=!1},n.curve=function(e,t,r,i,o,a,l,s){n.beginShape(),n.curveVertex(e,t),n.curveVertex(r,i),n.curveVertex(o,a),n.curveVertex(l,s),n.endShape()},n.translate=function(e,t){r.tM ranslate(e,t)},n.rotate=function(e){r.rotate(e)},n.scale=function(e,t){null==t&&(t=e),r.scale(e,t)},n.applyMatrix=function(e,t,n,i,o,a){r.transform(e,t,n,i,o,a)},n.shearX=function(e){r.transform(1,0,Math.tan(e),1,0,0)},n.shearY=function(e){r.transform(1,Math.tan(e),0,1,0,0)},n.resetMatrix=function(){r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity)},n.pushMatrix=n.push=function(){n._styleCache.push({...n._style}),n._style=n._styleCache[n._styleCache.length-1],r.save()},n.popMatrix=n.pop=function(){n._stylM eCache.length-1&&(n._styleCache.pop(),n._style=n._styleCache[n._styleCache.length-1],r.restore())},n.image=function(e,t,i,o,a,l,s,h,c){let u=e.MAGIC==n.MAGIC?e.canvas:e;function d(){if(e.MAGIC!=n.MAGIC||!n._tint)return;let t=e.canvas.getContext("2d");t.save(),t.resetTransform(),t.clearRect(0,0,t.canvas.width,t.canvas.height),t.drawImage(f.canvas,0,0),t.restore()}return e.MAGIC==n.MAGIC&&null!=n._tint&&(function(e,t){null==f&&(f=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvasM .height),f.canvas.width==e&&f.canvas.height==t||(f.canvas.width=e,f.canvas.height=t)}(e.canvas.width,e.canvas.height),f.drawImage(e.canvas,0,0),e.tinted(n._tint)),o?l?(h||(h=u.width),c||(c=u.height),r.drawImage(u,l,s,h,c,t,i,o,a),void d()):(r.drawImage(u,t,i,o,a),void d()):(e.MAGIC==n.MAGIC||e.width?r.drawImage(u,t,i,e.width,e.height):r.drawImage(u,t,i,e.videoWidth,e.videoHeight),void d())},n.loadPixels=function(){l=r.getImageData(0,0,n.canvas.width,n.canvas.height),n.pixels=l.data},n.updatePixels=function(){null!=M l&&r.putImageData(l,0,0)},n.loadImage=function(e,t){s++;let r=n.createGraphics(100,100),i=r.canvas.getContext("2d"),o=new Image;return o.src=e,o.crossOrigin="Anonymous",o.onload=function(){i.canvas.width=o.width,i.canvas.height=o.height,r.width=o.width,r.height=o.height,i.drawImage(o,0,0),s--,t&&t(r)},r};let v={};function z(e,t){null==u&&(u=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvas.height),u.canvas.width==e&&u.canvas.height==t||(u.canvas.width=e,u.canvas.height=t)}funcM tion V(){let e=r.canvas.width*r.canvas.height*4;null!=d&&e==d.length||(d=new Uint8ClampedArray(e))}function _(e){u.clearRect(0,0,u.canvas.width,u.canvas.height),u.filter=e,u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()}v[n.THRESHOLD]=function(e,t){null==t?t=127.5:t*=255;for(let n=0;n<e.length;n+=4){const r=.2126*e[n]+.7152*e[n+1]+.0722*e[n+2];e[n]=e[n+1]=e[n+2]=r>=t?255:0}},v[n.GRAY]=function(e){for(let t=0;t<e.length;t+=4)M {const n=.2126*e[t]+.7152*e[t+1]+.0722*e[t+2];e[t]=e[t+1]=e[t+2]=n}},v[n.OPAQUE]=function(e){for(let t=0;t<e.length;t+=4)e[t+3]=255},v[n.INVERT]=function(e){for(let t=0;t<e.length;t+=4)e[t]=255-e[t],e[t+1]=255-e[t+1],e[t+2]=255-e[t+2]},v[n.POSTERIZE]=function(e,t){let n=t-1;for(let r=0;r<e.length;r+=4)e[r]=255*(e[r]*t>>8)/n,e[r+1]=255*(e[r+1]*t>>8)/n,e[r+2]=255*(e[r+2]*t>>8)/n},v[n.DILATE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-M 1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.max(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.ERODE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.min(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.BLURM ]=function(e,t){t=t||1,t=Math.floor(t*n._pixelDensity),V(),d.set(e);let i=2*t+1,o=function(e){let n=new Float32Array(e),r=.3*t+.8,i=r*r*2;for(let t=0;t<e;t++){let o=t-e/2,a=Math.exp(-o*o/i)/(2.5066282746*r);n[t]=a}return n}(i),[a,l]=[r.canvas.width,r.canvas.height];for(let n=0;n<l;n++)for(let r=0;r<a;r++){let l=0,s=0,h=0,c=0;for(let e=0;e<i;e++){let i=4*(n*a+Math.min(Math.max(r-t+e,0),a-1));l+=d[i]*o[e],s+=d[i+1]*o[e],h+=d[i+2]*o[e],c+=d[i+3]*o[e]}let u=4*(n*a+r);e[u]=l,e[u+1]=s,e[u+2]=h,e[u+3]=c}d.set(e);for(let nM =0;n<l;n++)for(let r=0;r<a;r++){let s=0,h=0,c=0,u=0;for(let e=0;e<i;e++){let i=4*(Math.min(Math.max(n-t+e,0),l-1)*a+r);s+=d[i]*o[e],h+=d[i+1]*o[e],c+=d[i+2]*o[e],u+=d[i+3]*o[e]}let f=4*(n*a+r);e[f]=s,e[f+1]=h,e[f+2]=c,e[f+3]=u}},n.filter=function(e,t){if(n.HARDWARE_FILTERS&&null!=r.filter)if(z(),e==n.THRESHOLD){null==t&&(t=.5),t=Math.max(t,1e-5),_(`saturate(0%) brightness(${Math.floor(.5/t*100)}%) contrast(1000000%)`)}else if(e==n.GRAY)_("saturate(0%)");else if(e==n.OPAQUE)u.fillStyle="black",u.fillRect(0,0,u.canvaM s.width,u.canvas.height),u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.drawImage(u.canvas,0,0),r.restore();else if(e==n.INVERT)_("invert(100%)");else if(e==n.BLUR)_(`blur(${Math.ceil(t*n._pixelDensity/1)||1}px)`);else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}},n.resize=function(e,t){z(),u.drawImage(r.canvas,0,0),n.width=e,n.height=t,r.canvas.width=e*n._pixM elDensity,r.canvas.height=t*n._pixelDensity,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0,r.canvas.width,r.canvas.height),r.restore()},n.get=function(e,t,i,o){if(null!=e&&null==i){let i=r.getImageData(e,t,1,1).data;return new n.Color(i[0],i[1],i[2],i[3]/255)}e=e||0,t=t||0,i=i||n.width,o=o||n.height;let a=n.createGraphics(i,o);a.pixelDensity(n._pixelDensity);let l=r.getImageData(e*n._pixelDensity,t*n._pixelDensity,i*n._pixelDensity,o*n._pixelDensity);return a.caM nvas.getContext("2d").putImageData(l,0,0),a},n.set=function(e,t,i){if(i.MAGIC==n.MAGIC){let r=n._tint;return n._tint=null,n.image(i,e,t),void(n._tint=r)}let o=4*(t*n._pixelDensity*r.canvas.width+e*n._pixelDensity);n.pixels[o]=i._r,n.pixels[o+1]=i._g,n.pixels[o+2]=i._b,n.pixels[o+3]=255*i._a},n.tinted=function(){let e=n.color(...Array.from(arguments)),t=e._a;e._a=1,z(),u.clearRect(0,0,u.canvas.width,u.canvas.height),u.fillStyle=e,u.fillRect(0,0,u.canvas.width,u.canvas.height),u.globalCompositeOperation="multiply",u.M drawImage(r.canvas,0,0),u.globalCompositeOperation="source-over",r.save(),r.resetTransform();let i=r.globalCompositeOperation;r.globalCompositeOperation="source-in",r.drawImage(u.canvas,0,0),r.globalCompositeOperation=i,r.restore(),u.globalAlpha=t,u.clearRect(0,0,u.canvas.width,u.canvas.height),u.drawImage(r.canvas,0,0),u.globalAlpha=1,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()},n.tint=function(){n._tint=n.color(...Array.from(arguments))},n.noTiM nt=function(){n._tint=null},n.mask=function(e){r.save(),r.resetTransform();let t=r.globalCompositeOperation;r.globalCompositeOperation="destination-in",r.drawImage(e.canvas,0,0),r.globalCompositeOperation=t,r.restore()},n.clearTemporaryBuffers=function(){u=null,f=null,d=null},n.save=function(e,t){e=e||"untitled",t=t||"png";var n=document.createElement("a");n.innerHTML="[Download]",n.addEventListener("click",(function(){this.href=r.canvas.toDataURL(),this.download=e+"."+t}),!1),document.body.appendChild(n),n.click()M ,document.body.removeChild(n)},n.saveCanvas=function(e,t,r){if(e.MAGIC==n.MAGIC){r&&e.save(t,r);let n=t.split(".");return e.save(n.slice(0,-1).join("."),n[n.length-1])}if(t)return n.save(e,t);let i=e.split(".");return n.save(i.slice(0,-1).join("."),i[i.length-1])},n.loadFont=function(e){let t=e.split("/"),n=t[t.length-1].split(".")[0].replace(" ",""),r=`@font-face {\n font-family: '${n}';\n src: url('${e}');\n }`;const i=document.createElement("style");return i.textContent=r,document.head.append(M i),n},n.textFont=function(e){n._style.textFont=e},n.textSize=function(e){n._style.textSize=e,n._style.textLeading=e},n.textLeading=function(e){n._style.textLeading=e},n.textStyle=function(e){n._style.textStyle=e},n.textAlign=function(e,t){r.textAlign=e,t&&(r.textBaseline=t==n.CENTER?"middle":t)},n.text=function(e,t,i,o){if(!e)return;if(e=e.toString(),n._style.noFill&&n._style.noStroke)return;r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`;let a=e.split("\n");for(let e=0;e<a.length;e++)n._M style.noFill||r.fillText(a[e],t,i,o),n._style.noStroke||r.strokeText(a[e],t,i,o),i+=n._style.textLeading},n.textWidth=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).width},n.textAscent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBoundingBoxAscent},n.textDescent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBounM dingBoxDescent};var M,E=4,S=.5,R=function(e){return.5*(1-Math.cos(e*Math.PI))};n.noise=function(e,t,n){if(t=t||0,n=n||0,null==M){M=new Array(4096);for(var r=0;r<4096;r++)M[r]=Math.random()}e<0&&(e=-e),t<0&&(t=-t),n<0&&(n=-n);for(var i,o,a,l,s,h=Math.floor(e),c=Math.floor(t),u=Math.floor(n),f=e-h,d=t-c,x=n-u,g=0,p=.5,m=0;m<E;m++){var b=h+(c<<4)+(u<<8);i=R(f),o=R(d),a=M[4095&b],a+=i*(M[b+1&4095]-a),l=M[b+16&4095],a+=o*((l+=i*(M[b+16+1&4095]-l))-a),l=M[4095&(b+=256)],l+=i*(M[b+1&4095]-l),s=M[b+16&4095],l+=o*((s+=i*(M[M b+16+1&4095]-s))-l),g+=(a+=R(x)*(l-a))*p,p*=S,h<<=1,c<<=1,u<<=1,(f*=2)>=1&&(h++,f--),(d*=2)>=1&&(c++,d--),(x*=2)>=1&&(u++,x--)}return g},n.noiseDetail=function(e,t){e>0&&(E=e),t>0&&(S=t)};const I=function(){let e,t,n=4294967295;return{setSeed(r){e=t=(null==r?Math.random()*n:r)>>>0},getSeed:()=>t,rand:()=>(e^=e<<17,e^=e>>13,((e^=e<<5)>>>0)/n)}};let C=I();C.setSeed(),n.noiseSeed=function(e){let t=null==e?4294967295*Math.random():e;M||(M=new Float32Array(4096));for(var n=0;n<4096;n++)t^=t<<17,t^=t>>13,t^=t<<5,M[n]=(t>M >>0)/4294967295},n.randomSeed=function(e){C.setSeed(e)},n.random=function(e,t){return null==e?C.rand():"number"==typeof e?null!=t?C.rand()*(t-e)+e:C.rand()*e:e[~~(e.length*C.rand())]},n.randomGenerator=function(e){e==n.LCG?C=function(){const e=4294967296;let t,n;return{setSeed(r){n=t=(null==r?Math.random()*e:r)>>>0},getSeed:()=>t,rand:()=>(n=(1664525*n+1013904223)%e)/e}}():e==n.SHR3&&(C=I()),C.setSeed()};var T=new function(){var e,t,n,r=new Array(128),i=new Array(256),o=new Array(128),a=new Array(128),l=new Array(2M 56),s=new Array(256),h=function(){return 4294967296*C.rand()-2147483648},c=function(){return.5+2.328306e-10*(h()<<0)};this.SHR3=h,this.UNI=c,this.RNOR=function(){return n=h(),e=127&n,Math.abs(n)<r[e]?n*o[e]:function(){for(var t,i,l,s,u=3.44262;;){if(t=n*o[e],0==e){do{l=c(),s=c(),t=.2904764*-Math.log(l),i=-Math.log(s)}while(i+i<t*t);return n>0?u+t:-u-t}if(a[e]+c()*(a[e-1]-a[e])<Math.exp(-.5*t*t))return t;if(n=h(),e=127&n,Math.abs(n)<r[e])return n*o[e]}}()},this.REXP=function(){return(t=h()>>>0)<r[e=255&t]?t*l[e]:funM ction(){for(var n;;){if(0==e)return 7.69711-Math.log(c());if(n=t*l[e],s[e]+c()*(s[e-1]-s[e])<Math.exp(-n))return n;if((t=h())<i[e=255&t])return t*l[e]}}()},this.zigset=function(){var e,t,n=2147483648,h=4294967296,c=3.442619855899,u=c,f=.00991256303526217,d=7.697117470131487,x=d,g=.003949659822581572;for(e=f/Math.exp(-.5*c*c),r[0]=Math.floor(c/e*n),r[1]=0,o[0]=e/n,o[127]=c/n,a[0]=1,a[127]=Math.exp(-.5*c*c),t=126;t>=1;t--)c=Math.sqrt(-2*Math.log(f/c+Math.exp(-.5*c*c))),r[t+1]=Math.floor(c/u*n),u=c,a[t]=Math.exp(-.5*cM *c),o[t]=c/n;for(e=g/Math.exp(-d),i[0]=Math.floor(d/e*h),i[1]=0,l[0]=e/h,l[255]=d/h,s[0]=1,s[255]=Math.exp(-d),t=254;t>=1;t--)d=-Math.log(g/d+Math.exp(-d)),i[t+1]=Math.floor(d/x*h),x=d,s[t]=Math.exp(-d),l[t]=d/h}};T.hasInit=!1,n.randomGaussian=function(e,t){return T.hasInit||(T.zigset(),T.hasInit=!0),T.RNOR()*t+e},n.randomExponential=function(){return T.hasInit||(T.zigset(),T.hasInit=!0),T.REXP()},n.print=console.log,n.cursor=function(e,t,r){let i="";e.includes(".")&&(e=`url("${e}")`,i=", auto"),null!=t&&(e+=" "+t+M " "+r),n.canvas.style.cursor=e+i},n.noCursor=function(){n.canvas.style.cursor="none"},n.createCapture=function(e){var t=document.createElement("video");return t.playsinline="playsinline",t.autoplay="autoplay",navigator.mediaDevices.getUserMedia(e).then((function(e){t.srcObject=e})),t.style.position="absolute",t.style.opacity=1e-5,t.style.zIndex=-1e3,document.body.appendChild(t),t};let A=["setup","draw","preload","mouseMoved","mousePressed","mouseReleased","mouseDragged","mouseClicked","keyPressed","keyReleased","keM yTyped","touchStarted","touchEnded"];for(let e of A){let t="_"+e+"Fn";n[t]=function(){},n[t].isPlaceHolder=!0,n[e]?n[t]=n[e]:Object.defineProperty(n,e,{set:function(e){n[t]=e}})}function D(){n._noLoop||(i=null==n._frameRate?requestAnimationFrame(D):setTimeout(D,1e3/n._frameRate)),w(),o=!0,n.push(),n._drawFn(),n.pop(),++n.frameCount}function k(e){const t=n.canvas.getBoundingClientRect(),r=n.canvas.scrollWidth/n.width||1,i=n.canvas.scrollHeight/n.height||1;return{x:(e.clientX-t.left)/r,y:(e.clientY-t.top)/i,id:e.idenM tifier}}function L(){return n._touchStarted.isPlaceHolder&&n._touchMoved.isPlaceHolder&&n._touchEnded.isPlaceHolder}n.noLoop=function(){n._noLoop=!0,i=null},n.loop=function(){n._noLoop=!1,null==i&&D()},n.redraw=function(){D()},n.frameRate=function(e){n._frameRate=e},setTimeout((function(){n._preloadFn(),c=window.performance.now(),function e(){if(s>0)return setTimeout(e,10);n._setupFn(),D()}()}),1),n.canvas.onmousemove=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPM ressed?n._mouseDraggedFn(e):n._mouseMovedFn(e)},n.canvas.onmousedown=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!0,n.mouseButton=[n.LEFT,n.CENTER,n.RIGHT][e.button],n._mousePressedFn(e)},n.canvas.onmouseup=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!1,n._mouseReleasedFn(e)},n.canvas.onclick=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressedM =!0,n._mouseClickedFn(e),n.mouseIsPressed=!1},window.addEventListener("keydown",(function(e){n.keyIsPressed=!0,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!0,n._keyPressedFn(e),1==e.key.length&&n._keyTypedFn(e)})),window.addEventListener("keyup",(function(e){n.keyIsPressed=!1,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!1,n._keyReleasedFn(e)})),n.keyIsDown=function(e){return!!h[e]},n.canvas.ontouchstart=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.moM useY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mousePressedFn(e)||e.preventDefault()),n._touchStartedFn(e)||e.preventDefault()},n.canvas.ontouchmove=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mouseDraggedFn(e)||e.preventDefault()),n._touchMovedFn(e)||e.preventDefault()},n.canvas.ontouchend=n.canvas.ontouchcancel=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.M mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!1,n._mouseReleasedFn(e)||e.preventDefault()),n._touchEndedFn(e)||e.preventDefault()},n.hasSensorPermission=!window.DeviceOrientationEvent&&!window.DeviceMotionEvent||!(DeviceOrientationEvent.requestPermission||DeviceMotionEvent.requestPermission),n.requestSensorPermissions=function(){DeviceOrientationEvent.requestPermission&&DeviceOrientationEvent.requestPermission().then((e=>{"granted"==e&&DeviceMotionEvent.requestPermissioM n&&DeviceMotionEvent.requestPermission().then((e=>{"granted"==e&&(n.hasSensorPermission=!0)})).catch(alert)})).catch(alert)},window.ondeviceorientation=function(e){n.pRotationX=n.rotationX,n.pRotationY=n.rotationY,n.pRotationZ=n.rotationZ,n.pRelRotationX=n.relRotationX,n.pRelRotationY=n.relRotationY,n.pRelRotationZ=n.relRotationZ,n.rotationX=e.beta*(Math.PI/180),n.rotationY=e.gamma*(Math.PI/180),n.rotationZ=e.alpha*(Math.PI/180),n.relRotationX=[-n.rotationY,-n.rotationX,n.rotationY][1+~~(window.orientation/90)],n.rM elRotationY=[-n.rotationX,n.rotationY,n.rotationX][1+~~(window.orientation/90)],n.relRotationZ=n.rotationZ},window.ondevicemotion=function(e){if(n.pAccelerationX=n.accelerationX,n.pAccelerationY=n.accelerationY,n.pAccelerationZ=n.accelerationZ,!e.acceleration){let t=((e,t)=>[(e[0]*t[0]+e[1]*t[1]+e[2]*t[2]+e[3])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[4]*t[0]+e[5]*t[1]+e[6]*t[2]+e[7])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[8]*t[0]+e[9]*t[1]+e[10]*t[2]+e[11])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15])])(((e,t)M =>[e[0]*t[0]+e[1]*t[4]+e[2]*t[8]+e[3]*t[12],e[0]*t[1]+e[1]*t[5]+e[2]*t[9]+e[3]*t[13],e[0]*t[2]+e[1]*t[6]+e[2]*t[10]+e[3]*t[14],e[0]*t[3]+e[1]*t[7]+e[2]*t[11]+e[3]*t[15],e[4]*t[0]+e[5]*t[4]+e[6]*t[8]+e[7]*t[12],e[4]*t[1]+e[5]*t[5]+e[6]*t[9]+e[7]*t[13],e[4]*t[2]+e[5]*t[6]+e[6]*t[10]+e[7]*t[14],e[4]*t[3]+e[5]*t[7]+e[6]*t[11]+e[7]*t[15],e[8]*t[0]+e[9]*t[4]+e[10]*t[8]+e[11]*t[12],e[8]*t[1]+e[9]*t[5]+e[10]*t[9]+e[11]*t[13],e[8]*t[2]+e[9]*t[6]+e[10]*t[10]+e[11]*t[14],e[8]*t[3]+e[9]*t[7]+e[10]*t[11]+e[11]*t[15],e[12]*t[0]+M e[13]*t[4]+e[14]*t[8]+e[15]*t[12],e[12]*t[1]+e[13]*t[5]+e[14]*t[9]+e[15]*t[13],e[12]*t[2]+e[13]*t[6]+e[14]*t[10]+e[15]*t[14],e[12]*t[3]+e[13]*t[7]+e[14]*t[11]+e[15]*t[15]])((e=>[Math.cos(e),0,Math.sin(e),0,0,1,0,0,-Math.sin(e),0,Math.cos(e),0,0,0,0,1])(n.rotationY),(e=>[1,0,0,0,0,Math.cos(e),-Math.sin(e),0,0,Math.sin(e),Math.cos(e),0,0,0,0,1])(n.rotationX)),[0,0,-9.80665]);n.accelerationX=e.accelerationIncludingGravity.x+t[0],n.accelerationY=e.accelerationIncludingGravity.y+t[1],n.accelerationZ=e.accelerationIncludM ingGravity.z-t[2]}},n.year=function(){return(new Date).getFullYear()},n.day=function(){return(new Date).getDay()},n.hour=function(){return(new Date).getHours()},n.minute=function(){return(new Date).getMinutes()},n.second=function(){return(new Date).getSeconds()},n.millis=function(){return window.performance.now()-c}}(e)}"object"==typeof exports&&"undefined"!=typeof module&&(module.exports=e);const t="https://ancient-crimson-rain.btc.discover.quiknode.pro/c268fb026303ae8443f785200f2ea4b82f0082dd";function n(e){P(e)?M localStorage.removeItem("blocksApiEndpoint"):localStorage.blocksApiEndpoint=e}function r(){return localStorage.blocksApiEndpoint||t}function i(e){P(e)?localStorage.removeItem("modelInscriptionEndpoint"):localStorage.modelInscriptionEndpoint=e}function o(){return localStorage.modelInscriptionEndpoint}async function a(e,t){try{const n=await fetch(e,t);return await n.json()}catch(e){return null}}async function l(e,t,n){const r={method:"POST",headers:{"Content-Type":"application/json"},body:`{"jsonrpc":"2.0","id":1,"meM thod":"${t}","params":${`[${n.join(sep=",")}]`}}`};return(await a(e,r))?.result}async function s(e){const n={avgfee:10,time:Date.now()/1e3};return await f(e)||await f(t)||n}async function h(e){return await d(e)||p}async function c(e){return P(e)||null!=await f(e)}async function u(e){return P(e)||null!=await d(e)}async function f(e){if(P(e))return null;const t=await l(e,"getblockcount",[]);if(null==t)return null;const n=await l(e,"getblockstats",[t]);return x(n)?n:null}async function d(e){if(P(e))return null;const tM =await a(e,{});return g(t)?t:null}function x(e){return"number"==typeof e?.time&&"number"==typeof e?.avgfee}function g(e){if(null==e)return!1;const{classes_name:t,training_traits:n,layers_config:r,weight_b64:i}=e;if(!Array.isArray(t))return!1;if(null==n)return!1;try{j(r,i)}catch(e){return!1}return!0}const p={"model_name": "pfp_classifier_521", "layers_config": {"config": {"layers": [{"class_name": "InputLayer", "config": {"batch_input_shape": [null, 28, 28, 3]}}, {"class_name": "Rescaling", "config": {"scale": 0.007M 84313725490196, "offset": -1}}, {"class_name": "Flatten"}, {"class_name": "Dense", "config": {"units": 18, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 7, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 18, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 7, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 18, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 7, "activation": "relu"}}, {"class_name": "Dense", "config"M : {"units": 4, "activation": "linear"}}]}}, "weight_b64": "nm2tvAgnrbzO5F895e3fu0HUaz1/IL28VMNjOhbnaD0PP6I8JX0OPZX1DT25NoM9CmyuPJ4QuzxU3K295BruvCUKfjxIHPW7WwU6vRQ2RD2wGIq9uyb8vEncRz0UUe+8oUA2PSickbpUnsU9wbwFPDAGVLzVuL29/ZO3PJ5SLz1YU607mZAFPclys7zBvs08mKk1PdYx5zzokOG4KIZIuntP7TqCFoQ7PgYyPcvSm70GfJC9+1YCPMNqND3izr29QTsUvYj73rt2pjY8PjCcvDv3mzyIDiS9j7emPHJthTuwZtA9qfnGPA7C0Dxyg189cUtPvfmxED3bpG07bUrxPONh9ryeqya9bYk+vVqEorskyCW9lEesvfPceb2MDgC9V9tVvO6NbT2H1bW987Hlve6gGj39H7U8z2TovCLmRTvQc9c9MnGQPSRiuzvVypK9Ruh8OgpFrz1STM 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 SpI/zy1rvM8Q/e5vEGt+zyFD7o9P7o9PVNMXbw4zaK8HN8sPXdr77pzdV+814oDPeS7Yr1P9O87OfK0PCJofbxbMhg9qBlWPDLN0bzaM6i8lKhrPLFRPbyD7qS9OKhLPWHy1rwgWZu9UlXbO6FmPj39ogC9tJpNPWTHI72afLk6+ypOO40C+DvAmFq7973gvGgwjbyPPqQ9GowYvdR3yDxZCVo8Z/wWPL6E0jyd1wG7MmnxvB+6iT1+OO698iQDvfFXBrzq1Sa9gUgcvEWOhruwITi9B8PCvZuUHD0kPoa8fCOAvFx17Tw6sIw9fCSIPP6TWzx+9IS9SucSPdXdhj2eFZS9pkdJvGkzDb0edwG9lKhJPcVaHD2jufg86jq0PT/fkzx2NGw8XAkhPYUYXb0+5qy9mM6zPJlDEj1OJoG9LZ3fvPW+gz3TETw8m9eSPElY3rwvhM6888hivfKpLbydvTk9Sh8kPFwmLzq1D1A9+6rDvAeq8Dz8zAQ97jj0O6kWDjzi4M 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 ZW9M4jkuu0tKbzGt0O9OycQvQA0C7lfAx69yae7Pf8tAr2mnLQ8wCwOPGwfALxFSD88jqIgPScVcjy3KYo9qaP3PPhp0DyO9Sw9WpXQvFNKjbtBC8w8i5iJvCLqYj22jl69f0N5vXhYjLyEowM9sTUdPeseFzwk+uC9XtXyvXr14rukKoQ9c8NQve/MA71yHpQ9+UsZPC+EJz021pC9i3xPPSN18rzBPGm9dhUmO5WlhL2ZoWA9m8qHPRCev7zs7jg9a4yVPdeDLbx4ODI9mtDEO/hwfb2bQ3+93eAKPGcdcz0j9pq9bQYNPJSdFD0HQGK9O/kMPdzDb7vugxO9+7hQPRgkijtmFTw9tbxnPaKvtjxHZxA94x+CPDnLhTv5MPm8Dfo+vcshZjs5lAS8Fi0Pu7TDdDvSYve8MZkQvYQCCLwKD4q7FdtJvERw87ybH+e98Vvnve/rdzzRyKk9jhyOvaQkgzzKp749q4kiPX4kPLwPmFK9D/cyvAcy57vCr7I7SOqWPM 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 Na9nyYoveoTH70xA2k8IUgdvagikj3K2I+9aVHevfKEgr2TVlU8quI/vWtDqTwx2wQ+TQ66PAhHjDzzHzi9ZfoZPVdEcDwdaJa9w+qAO6hXljx3BAa9NvBgPaCfJj3gT4A8kPqhPQCllr0a8DM7GNBOvLbMRTwPqB69J7PiPCpYQryrDOG7VlAzvUwXGr3/1H+8FeiBPeQPQL0GMgW99WKRvd9bCb0q8g08cMu1Pcwjj7yaiJk86JRou1WkXD2DH0g9iNuiu00p3LwRwyg8H1lpvCBqUDx4wJm918x4va5ICD0Cbvq8r1EUvOMpR7swrY69X97LvULhhLw7gFA9+JKuu8oHyDswU/c9MJITPX58RTzDPPs7ZI19PEZbybyyk0m9+xiBO2LNeTye2yk8kB3vvLXq+bw1/hk9RZMUPXhJmr2A0WS9hR9OvTdnBz2asJa919sYvUDcPzzlWXG9iHMivZF7Dj06pyq9Ir9JuuNDbbyFiqs8XFesPA4x5Lvw7bw9eOEGPM 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 Ky9/DGAOwgqIbw82Ua9L/pOO5jvR70lEE08HAAkPPMInzwwQ3a8f9uBPb43vzvHkjE8bH84vbkPsruqW8G8RVu+OsGAGT3bH8M9Ka09vRqIZj2Fh/i9mR4gvc0CX7zgAYE7CDttvAonwjy0OFa9ayEFvTlWCj1V8nU92hjtPE8Hkz0RuJQ9cWLdPPkecb36Z+w7fhFGu/4QQz2FaG29LahPvT9ZkzwotBI92vCUPWOFKr0CJbe8LNo8PXXCeD1RR+U7bKBePQ7Y9LxTZpq9Db58PWRw8jzWQ5K87ar6POmC7zy2QGW9wIy6PF7mLr38nA68pX15vGEHDb2x2649JAwTPezIxT0s4DA8wChzPBi+w7waPqi821yfO4l2AzzAtvY8g033PBEPdz3vBse9hh5pvQzzBj3i/pO8p9caPT2gWDywkou9SIKwvQ+XsT013nM7ppGVvOTS17zwEMI9dXCTvKHUHT2c2fS85aN5vJyXZz0khOy8grNQPdRtFzzP1r88xdlEPM 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 7M9qF17PMUsUjxvlT48yqpsvMErkzlY5wi95zcjvY3lRr3qfAu9Wv/RPOW9lLyJITk8UTvfO4CHubwAPj692KJEPXFCHjwbG8i9UO6EvDpo37wpYHG7SRaovL9FgD0Qd1G8GbrsPAJipTzAOC+9poe6vESBgbzw/AI8UW5yvMRhAT0rD0Q9CFzJuUHuPb1kSz29pJ0IPZeH7bsKu7Q82/Q1vQ3ndTzzsWS9qWVivbbcLL0u2k88+tJEPTol4DouyH29goblvQUrZz0uUyU8VQsrvSXsVr2vUrY9i/UvvB8J7Dygip29Zi8hPMwYkDuWqFA8XAmJPMHIprwmQgk83pZSPTaEc7yNv2a8x/UZPUQGSjxrBH69luyzPHDrkb1J5Zq9F47tu6IbIj3FfsG8/cQTO5hcrD3Rrh09UKCcPa1xVL2TijY9+nZZvLWxeD192o09p6inPQAl/jy/dYc77yNLvfWe5DupEFY9nnOkPE6iqDy+J3A9V6EhPYstQT1j8fy91gE6vM 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 TQ7Jt0mPKiOLD0XsE29AxWZvahU+7zyPhC9PA+ovb2SWj0H4QE9hB+/PeiUEL1ygFw7EQ4nvcsThj2IA7M8ENs5PNr1RL0tly29Lm6+vIwyGz36fCk9HmGDPL8VGL3xyVC9LJ9CvP6JtTzrApm9TqOfPPwbr7wbyZC9tW5fvLhurzyHcN47PneFPQfddL2CgwA9UJMpvQWLdrxx4IY8BdSLPU6EGj1rbai8h8SBu3iYND24rS09Uw2tPI/0BL2gosE8Re5Lu+Bk9DbdUAG9MwpMvVMjGj2X2C89sH4FvRAeP72NY5C9FKuBvZ+vVL0SDXo8Gh20vO6FKz2E0cY88WGLPS2w97xKnVW9gxOlPC4vDzz3rVy9Fm6kPUJWIb1l5Hw7FHskPS0pK72F+gu8KgbYPU0+Frw8qmm6tXKqPFF0Dz3Dr7O92RfyPE6pPD2Ywoa91bl1OwF5uTwDNmU7Vu28PZioj72ErqG8lj9ZPJAIybyTGh492FyvPWU2VLyyzDA6qvjBvM 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 DS9MxwpvHcCSzy0Yzi9dQmaPZKIZr3m+H28PXsnPE+9AbnYJjk9fOfCPXXC1LvDZ0I93i1iPDgfCD1SrMW9aUgzPF9j1DtmtyS9WAazurBlTj3KLY2987zBPeV5Pb1gtrY8+KybPNt2/TyIc5M8UTaoPQoijbuGRvs87GUNvQr3hjpZA8e8JGkevTCdUL0yhb87jHwEOqfqz7svEKe9a8WbvUZyZL2E4IW8bUGZPF5eE73g6am8eJDZvRAZ17xuP8g8wR9HvayiZbxGqZQ9hh4yO0h1kruS2Im9Phq9PJ+nGj1poiK9e4hjPaisbTwarRc8C7kaPChOaT2frNg76PEnPV+O/LxZ9gU6s/YePXKdT719Aw+9z89pPO/wUjwuA++9bCcUvTUmFjr8MbU8M4o3PQEftr0vLw69F2ARvZwI9zuIgfU8OEEYvD5l1jz45SM9yKyCvYZv8zxxdGU7TsENOzjY8jySWng9YlnePNzyWz3Jp5W917ZmvIoBFLsYbgo8CsvCvM 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 Y49gkLNu8LDPD1MPt89JrO4PazR4ry4DOO98kcFvSwAFz2qApK9fKI/PYb6NL0Nzao72pSAPGIEHzw7PaS8XpCrPa6+0bw1IpQ8FuWMOUuiujwSlba96AhMPHsONT0WrP+9LsW9PPV4uTx/bly90maxuT6Tn70wJeu8PFUJPOU00bz5qIc9tvlmPYfkkzpEe1Y87Q/mvLi8R7tBfOI596fsPJw84DwZrGy8vNqEPEsFIz3k9S29W8eivYU4NDuf72y8f1oEPfGoNrpxHwK9AQK2vZnyMT2f5XY9MASxvYfUGjxY5Xs9fTOePR9esbzJ8AK+Dt42PTQIjbwhmii9ljAJPcEsQ70FGZm8XhcxPOlfTT2COik9giXuu5GP1zyBLRC9EGPsPPFdGr2tFOi9YRAaPA+74zvsKJO9zoQlvMz32zp1/rk8cmmGPRKowb1nw1o83STYPKTc6rxFiHw8i10qPS6ghT3j/CU9t3E9O6u0VT2Md688VIIZPWDfM72wBjY9pV6DOM 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 BTtXT3hyDC9/VckPUuh37wqpay91NshPSSBHr1WnIU9JxfwvJqePb0sxo655HsVPUHl7ru+ZGC8dbf4PPpQm7xbfzS9jppSvXee2ry1cru9fZLBPNP6trwwyQu9GQFDuxCRBz0xg8y8sguvvXr1Gjs/kjC9OoSGPA69mz1HQZM9FVfwPNFHYb1t5bG81YIovd6cUL1pe8G8ccIRvOCvhjsg4mY7wGGGO5lUdD1zIos83/ahvMZ0H72KBp47MusSvWU3UT3jVIO9SJvrvCjLyTxaj4O8IsmBOgA1Pzyf0UW9//AZOi1CXL0QSxy9YBNVPWe7Qzwb8FE929dAPHH467slhkC8fgUUPXyn1jxpwQg9YzOsvPoXILyDa/S84Gjjud/5OzyhmG69ZBEIPGyzT7wuhv48edKgO7qprjxKmRy9wRAtvaQmnL3Og8S8jXcQvRy4kD0OM4M9xTPVuyiUJ73FyiQ9vSQ7PIkldLz5OeW7wrXJuzriUjzG95a8gyRsPZhJmTyy/M 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 UgdVz3YEqa98fitvcGEETs1iSk9/A1qvGqkfDsJRZ09I96pPUHwdjxfgIS9z3RTPdckfT3Y0B68oSW1vIQxF73OsFw8MN4ivLQ2FjxA8iq8azuCO16juTvwMMg6sJTPvH4eWDyB9ta9MdYzvKc7XD0F7e69rahDPQ1lILsrpea8WseQPIvmL7xRW0w9cMDTvJSbLj3/xgY9UKUGPfjQwrzWFlU9YroYvR77Dr177yc9S+iBPHXIojs87mO835M+vH861LzzQtS9dgwkvfa8HD0nxgq8aEMEPW/Gxzw/Eq29jEpvvWa5/Lv4Vxw9SaK1vCG9DbwBuPg9mbp6OxI42rycK1C9IXDDu2R7aT2Yu2S6DaMxPdzRgLy7nwc9fleXvKGUc7uKbc+7RD5FPVKy/TzX7+28W7Mvu+PpHLyo59+8b2ucOkAwED0CZaW9v/RRPSw9kj1NgJA8gS1gPXtAkb0hQOk8OrHYvMu/7bzS5tA8ux4RPOqvWjuASw29m3mYPLLfXD0VKM 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 4+7yV44PaQjIL1bSEy9tkyeu3OjJz26zzk960KOvdlpmzwjFye7PAq7PespFLquRRG9RYsavAXhxjyjIhc7V5L9PIA0kz0QjY+86sXVvBmm0zwiE7q7U+abvRAtuLwpSxc8YqOJvNmn37xP5G+98MLzvLtqOj1QwAY83igGvV+Qozxj05S9HPlEvcCRMz1FmQC91NI+PasWGb0bnik68KM9veSicr29mQ29r5kRvAczDD1RCla9aLk5OrEhNjwFuz48vX5Fur3JsLyw/Re8q852PIiDK7zLCV290ZsIu/1RLb1PbIm9AUMjva3wJz13Jpk7w+3zPHdeJT1K2pW750pDPW08MzxyYGG9AOvSPGu4CD39zVy8NDB9O9Lb/LuHi+S8VLyyPPlJOrtVsbE8PkEuvdTTY72Tc0s9EZlpPPNIv7waum691rg4PAFPD707btG8zF7VO6DqOrwl2zm9MiLEvW/47bzh+gQ9SwTau3sfQD3b+Yw96skkPLAGb71ybRQ8kfSHPM 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 AKlOzoJ64g9j0Z1vPwO4LyN4NE7KP1SvC4JlDyEFSs94BiKPIaxDjxLt6S7QZCUu5t+/Dt4x6K9si5RvSK/O73l84o9wJ1fPYif5zuGaCW9ciXfvbOb1bxjT3U9RaaMvOaWCLxLZfo9COG3PUL5HD2/UwG+l9MiPfSKs7yqFgW9WIKBPUKaM7wlYZ09KGyZPfxFKD0HXJq6JtiLPaQFtbofplQ7tdiEvApCW7x+dfq9TtHpPB0dLjyKcZW9mMY9Ou3Tr7wA5YW9D/7PuwjKiL2OeJU8Mp5evZ+axbz3aIE9um79PA8ATD3idm88x1qCvfpR6jzs21A9frl8vCL0YDwbLxm8GEoqvZi3RLzHhT69/0CcvP1MT71puI87jKeeuZfmqjwEA9C9wj2HvduPGL1S9Zo8LvFQveoCJD2LIKM94R5OPTE8R7tM/lu8JfYgPVrq0Dwmy5K9sa1XPR5CGb3H+/e7AWlhvF+5mbsEmqq8/cNAPYwpJryLgBO9ejBUvV6jQr0Q+M 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 TW0n7wsMvO94lyaPej/j7wdzPm8ba+Bu2Elu7yBfma9mvq2Pc4xqrySIRA9H7ERvflHXz0kYAe8cp+LPUS2YT0zrau8SgdGvXVF9LuwEBQ9u1OQPU25Ar205Nu3WaStO1m40rw72Ky9Y5vovLJDJ70dEy09ZFTSPAhEaD1SMBW9e/cYvRiaFj33Jji8a5G5vMqOgzz+sbM9wTMQPefS1TzqBg28A0kaPUXvbD14eBe94QnrPCoDr7n6tiE8W1ezPOXxczwJzEI8ULpuu8pqhTyyyp874ORZvWYcD72GDjq9xnRAPABmvzwFjHi9mYyVu+aFpTuB71O96z77PExCHb38Vs68afvyPIGujTyQOrY9B0d/PGAEvDs7fnM9Qh33vPWHRj2a9h29NPDPvGKoKb2EanE8reQvvSq21bzW2+y9onK3vQN80bzPbCs9QUcJvK5Ok7s9Iee9aKC8vaRzhzz1hU48DepTvX+SJT2EIKI9qc75PFxU6LyJU7q951LRvCxLpLyszM 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 cB9ZLw/VXk9reqNvfACAz2lBYQ9GLSfPF+fS72XEdS83UkNPY2E1ryCF6G9GcY9Pf8MLz3rTNA8Jx0BvVWtBjwOu4w7frp4PN+CUr3J49u7thITPZV2AD3GACG9EhAtPePHRT1KHLC9hFgBPSbjjj36+CE7r23pPAoaQjuj2/W8LysKvbmRlTwgOdY8HYlFPaq0UT2f2+68ckAKvequq7yw+J28rkENPCX4jTxiUa45vgCnPFLuKj3GcL6987IEvTogprzWXcM76YynPCOhMLzx8UG9H9KPvYk2HDwPdUi9TGDivHTpI7186Cs9z+RxPdlPAjzMPCk9qE93uyO1pjy2V4O9UlkCPVEhBL2bS+G8Zb4xvWEtH73fKVA9+XgFPSSRHD3tocy89L49PXJNJL2DPdi9nuGkvA8VAbxDvni95uEYvVgY/LvAWAE9sNqHPSFxEb2yrgS8oNQfvQ6Ghz2AQUQ9YJlQvCEDDT0Pkps9l/0UPKQw8bzKDAk9M+wsPPAVET05KM 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 fCtMD2H/CO93qNzPAU7Rz0440I8NkkdPXATn7vRtD08lZuJPai1IT1YM1A9CqCGvSCJrD0IQBM9qzTpPUwPQ70T97U9I5MUvlkbTLzwf+m9Af1dPcgOYzyRLSY9mkxPPXWz3jtsWFW9fhr9vCGkGD1DPhM9VA7IPLaVlzyNoI093W02Ps985L0eE9i8VNQ1vU5QrLyRw9W83i8pPHbGFD03GA273g6xu36GW7trBbO8qGtBPH/Muj09xFg8+esqPDU0qLuWO7w9Ig4WPu2avr0/or09fJmEvQpoHz2B4Sm95dyZvC6yN7opiyY9tYyBvEsrxrwKWJ87grv5PDuIlD3w3S89mYvmvJgC4T0C4qg9UDQYPS0khr2RSJS8vHq+vXqONz39pA494yltPalzrL2uZ9y8kOoXPQPtjz1WNai8Fk2mO3mHgT2l9gS7jRyRvM0asj2M1X89wnc3Pu/Nf716ML48mPb9vQ9+Hr3+nJU5SNSzPc8GSDtyRmO9XFFRvAVqUz3whM 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 Va6Q4g8PeJUG7wK5uo8qHW4PUfb1j3j2Xa8WUBZvfblc72ln4M9BMyGu3wNFr1VCti7Zan6PePD4jwDj8+95uh5PYEtmj2PIYg8hbPZvPkKXz18xZM8RcU7vMZUkDxrf6u8zH3ivJUZPLw7kRA9iLQbPV8ePDzabAu8XfoiOpe+ED1bV3s8NyVoPVZtLD1b/Ju8MfYDPRr2/jw+dNC88lCyOvGBjTw+tlq6CYudvV8ZXD2N+3U9uPNGPHn3u72JrgO+G6m5PU3TvLlnysE8D1MNvZuH/zy3/Y08/1P7vCNICT60dZg9isFpPdHICj3w9ty8YKzSOtxZfj2ijRc+uQgfPYLvsLs91Q2+7lVSPssNwz2SSMO8HeqXOS0MsT2tUzk8acIDvE7e9D3r6HY8OBwQvYSLWD1aiFq9rqssPdfp+DyANwO8ljmWPfEjMD1quK+9NYm2PFYxgD3gwIw9VtJru6HLcDzFUHS8C5syPfRcNT42hj68j8zTPGGOKb0ghYk7DNfKvM T9yb71hm6y8k9SMPW/VbD0EYz++xLG4PaQNvD0lY4q9iw09vR1lcDxsrEM8fBGqPJy8BD6CwB09t1zNPZJ2AD5HPoO9cgHovUIebryddgs9YGltuzKyTT0as+e9Bua5PRDXbj0jOiO92K+RPN0BIT0pTCo9zsIfvJA5Zj57gnS8Y7O3PDXZyjxl6gu9QDIgvU8chLz80IW9LR/mPam6Cz426C2+iVFqvWhnwT1oe3g9DmCzPD7VHr2XRAM90PwdPliPFj6J1UY98v+0vCYG7jysshK986zWvY9Lzr0dPTO+jkGavMyJqT3OnhS+ZCplPQzqUD2mHxa+gp21PfGRSr3MG+c99E+pPTA3JT5tvy09Yx51vTM5mTzsO5W7MYEAvuYbo72EcVi97LNmPZXS5z0BHPy9wHk0PUQrDT7k0Ny9jW9tPUf+6rm7xiY+licgPUYrSD6Aq0Y8KsN5vSazDjwuYYO8y9bbvRRgJ72uN7W9b+mePY7e0T278Qm+TYa9vaHkzT3ddM 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 GY82b2aPMM1gTxhlGU9CVYivHG/hrwlEyE9E68hvbgQrb2g7t29/M5gO2BPjD0Jr6W9BhJHvdn9gjxPPF28jvaJPFAqxb2BDxk9GgK6OmWAhT3CiWM93AczPf4iGb3fLCo9a4GKPUXkOb2Mtyo9JNVEuyZeyTwyWIG8qn/xvdBdUbyLEcG9yDYBvmGc/byDA4W9gN6NvCYQyT2jJhC939OpvVNqwL2NXsY9jJUzvC8f37wKz948jn+JO8gUgD1qc6I80FvQvUdssTzW6ho9fYR6PJ2+Kr0z8Ni8jDAgPTgHDj0dtbc5ovwaPfvA9r2CSxE9+QZzPYkHDr2ORDW9CDshPRhcgj09k4W95vCjvR9t27xnT6q7sGdrPWmPPL11VYu8pXuNO/0UgT088lY8oKZ3PSIgtbzFViQ87/EVPVMpGb118927SpaDuxEtKD3Q2G89rTKGu0z8MzvlEze960JyvYQU2TzNWM08hePhvFKjiz3cRNW92wrHvVnR0r0Mj549EnTzvM 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 vi8PsDavGYys72/NsS8eBCZPX0VMDwhuRu9QbAuvWkJwb2HqqI9squoPUYhKTuK9cY9D4MfPB/QCjx2oXi9mfY+ve1ZRjz6EEm9DCkKvSbh4rznxBG980SnPLqA4zyz7RI+cv0hPbicTL34vZw8OV6VPQ63a72K10q9Nq2Su2cacD1wUAi+EfW6vI2tlz33CWs8cSVWPMbLGr1HqYi8X39pvTr1dL3T2mq9n1QsvHe9Ur3paGY8hyARPaLn0z3418K8ubolPfjymTsGWLw9TZArvQ6ZaD3M0S09HROJvSwbwLs1e5M8lHrRO/MRV7ytYwK+fU+DvDk2E70SfpE9slCTO4Gbnz2W+Bg9jGIwPUvLV7xh8jG9w1MgvfgtDLvc8pu8gSm5PCk+Yb06Wru8Rv5vPZ9Irby9FOs8VgnMvPGmg7zyGs68cVMHPB4mHDxu/o29mCWAPGP4iL2Da4C9WLoNvd24Xj0lb5M8doURPABzf7sW5Qm94n1uvR6b17zVkNi9c54DvM 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 f19Er2INgO9UZ66vI2N97z6Ihq9Ds0TvYKiDL1qYJ68YayyPaNiE7yD7wi+BFWBPbZTYbqrtoc9KYEKvh3WI70CVKY93kP7u1tzKD25JGs9Mqv9PURpfj0Qffe9TzDzvCR2YLyiAsc9dWPEPdju7j2AH0q+8n4KPjg46DoBH3c8Us5KvRSR/zykaqU9iANvvSjLuD1wVuS8kjmzPXHtvT18LzS+/EOOvTA4y73qqv+7hS8fPqz3MT5rjhG+JiPUvO7Fq7xeLrc9ExpFvVHjWbzRvGc9wGGtPBYemTsk1pC8HGFkPQkAyT3IkRG+dZ3dvfQEDb7TYZa9XhQ6PYbshT2spRS+ndYuOv0H6Lz7ASy9tq2rvWKxHjzkij8+L2CyPXe4vT18LOI9hy7BPPDKH7zxnt+8cgjGvYgaqL18YYU9XLMUPaIpFz44szi+ecuQPf1xSr3GehW9NBjlvOAsiDxrxDM+PlAfPSnwCT7bohs9eygGPD5dkbyvW5290iqpvYRF2r14UM 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 Ia9WxiWPHrF1bwzZfY9DwEZvZkdH71PgsM90lm3vfmC+bxxebe9PlRQOmmYzjzuipq9BgC0vOtecr3f1tO7jtRoPV91YT0C7r+8CEPiPEDbb73ROqI9uQFvvb+wHb242I48lgXmOleYMb1Buwa95R96uiJeh7w5M+48BGBZO4vxY70JjeS74xIoPZK/kjt0Jgu9ZX2fPP+3lr21IRc9vg+WvXl9xrw3kjY8q4QXPHc3CzyuOru77SqDvbqSYr0QxwS+SFuLPaIBVz07IjG93t07PDnPrT35ucS840qOPfL+7zwVrxE+VEidPc73Hr0Ia/w9oNDavWZThT181Xm8HzaXvVo+hr0pDBq+5razvYMPTzxg+j09NUNGvF1uej0JWoy9KI2mPVWEVzzA/CI9upeSOrRKu7zaAbM9cMYlvUPvDzxEMQw6wGsfPXnZb73suMq9fAPMvAYdpz1xXhm9KemlPMhIjj27vYm9H97Yu7KY3LzWAUw9C6ICPaNuLL3nUY28g86WPM 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 bYWwL0D1xQ9Fm1BPS1Hcr4aO1I9ee/cPQBrPD2IYFC+3ty0O6ZZOr0mnSw+AterPR29Gz2GXNi9lJsDPZXlkTs63Cs+1r3ePa9z5r1piIu9GPXMvVe4kr7Pew498votPnW1/T2D1Sy+uoRPPNF1Q7wVL6g9QEBLPauKcj3SlMG9eX6NPUvgArviaKM9b6auPMf/6b3VI4q9asYKvQula75tcDk9tqaFPCTxgD1+4RG+MYYZPjVbFL1twFI+0jwfvDMeOT3tSkK94fSJvbudSb0lfNA9IS6RPUm6PL26H9q9LwKkvGHBiL4wt6U9/4YKPY77cL3WjPm9ayEyPv6iw72yEQ4+BzoSPS2TEj53nUQ9KoHFvKKgwTyHpYQ9lofePfJ6uzu83Q+91CKGvao3pb5zgp28zvDfu6Q6lD0IYN482MJePvwPgz07cLE9Q529O2m5HD3uf5Y9qnYqvXWpab28mxC9GHiAPStfyLtnKCm9JyGqvao4k74xrKY8fYpbvSzgML3IuM 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 U3yxT39bMi7GPtTPeywPj1AtPM8/fQ2vSIOWLonWJQ9ghMxvRMsUTq6zLA8knZAvaWrBL218pI9U1e6PSDdEzyU+j6+YqmpPTPWs7yIUbk9Eme2vUkcyDwZ+eG7OP00PEJO1T16khI9Fy4VPojYKj2/Tf29TXKCvZ77Sr3+zyQ+1QijPXPirT2QLQi+10LVPI4SmL2thPg8W0lOvXO+pjzjdR09XXy/PHPLHz7667k9b8gNPrazqDzXbzq++3jvvE5ElL1+TRM+Us+cPZG6jT0z/ZW9iAoxPQuDFD0bah8+oH6hvVuOOrzmBb+7a777OzkAijwfur094g7pPG4s7jyvg5K9Cwn7vRtIxr1p7Au+7ykzugaTbzwSyPi9tYeSPQxCiL3EgBO8XQ8lvTmdY70qR709MOX0PQVR/TwEvJ09Pe93Pbvq1zu09z49Jm8vvrOv6b2XDBe8lwNtPDgRwj3TjQe+84SePaMX77yYcci9ZJZXvH/Njr0heNw991Z9PcTlN73ydM 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 RGxHz1O5dq8zTPqO3KVfL3FZ6y7rs4zPeSzAT0T7JM8D5+VvWEQS73983M9/RinPVB0w7yrNRg+99RlvcxKPrwd5XO9YFFNvQOB+TwPqUK8TR0TPUeovb1g4Ve9dSLwPP4hvDuef7E9iVmUuSBeBb1GI/c7UWqYOji/WL21Ki49p7MOvMWgqTxPGTW9jw1PvaYROj1AC0Q9DNUtPd4MF71gpYu9LGmVPOtlQr0zrZq7Fn+Su0rcOjxp8s28KiWGPFYKGz3UyI+9V7OAPVijMjsr3tM9YRS2vOc9BT24MWM9Q07DvC7CN70WFUK9DZD+PCdlML16XaS9InXzvaHOh73/q0Q9f/vsPBYTDj3C3Qy7WWk3Pfnw5TzCe+i8FdpPvSD5DL2YEiq892GEPENi97q3gYs78VeiPFUiEL2rBwA9GVoCPAjkybzmukC966ylPbR4Q7yHg3q9V8+8vCpftbyrbje9JF2Yu+S/Nj3ZnTw9HcD5vOoDSLzYzn+9k8yuvQAJiL0BGM 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 3k8/tsKvfUylb0Qr8u8KFPLOwR6PL2IipQ8H3KjvNKEbj2dkEo9DY84PaVX473/HXU9sUsbPUXRcTokshq8GSc8PYzQ7TzkqgM8w51EvDLOB7xWLLi8x4+dPfQNC77yTY28Z16bPSOnoTuiPSU9t+U3Pcbahz2IjyY95f4WvP1YcbyNCQI+njahPXPzhjwqw4i99GVBPaDTrjwCbA49y2GWuxLtqr1CrEU9feJEPf6YL71YBzi9l0A6PUeM/D2jI/68uX39ve/z2Dyd554891zGvDRGvryXA/M84JyPPTHlRL1AiL08N35dO0gACbxmwCK9KZpEvKKiqD3IaT0926XCPaFK5rtShZW8Y/U5PS1RRb3OBWi9wAWyvMxwBzy/GcE8dxEPveuEYz14BJQ8ghxsOkCYC72zJd48ZfqLPY9iSb2cdFS9iVDgPGlzez1BIYM8YKnsPDr1Jj4ipGQ88FP4upQ2uLwsJ608X9X3PYtUST3bDZc9qW0zvQjXhbwYO6o9e6OOPM 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 Qe9z6CyPGRzmz2V5Yq9XGCSvTYCDb2B9oc90t3IPM6PI73YDuc9tFf+vBB11Lxvcei9G3xVvSWHQT3RhM+84CjpvEMIoLzcLbG8/1IjPS0OB70TIWU9gU3YPMKQTr0d6wG9jtsIPZDear0a6ai93e0Ovb7Xd71wMQ+9d2BhvUkKUL0mT/a6oSXtvCN1Lbwc1lg64ZB9vBEyuTzqsok99FXVPFcKg72roY49AcY5vV5yorz1eQK8NfRcPSs82jw81gm8uXuTO0/0kDy89UA9UoSVvQyM8bw5zSw9RNcoPVv/JD3aQQK9ErSOva0nZLwzQ9c9xwy+vJg8s7ym5D882fbkPAhbLj1hUoi9XMHZvH2XjLoeny68lqyyuwCRNbxiXc+8D1ILPX8WLj0Zoo09G+kXPeo1GTvZ36U9+RG0PcwlqTrhTxK8B282vfOXxjzcnW691ISPvF5RYDyXH8+8y5LIvEy5er1v+dU854WLvS3N4DwC8IO9djxqvWHB/7w4UwY8SxfzvM 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 7o7FaqxvR/lvjyG2fk8/0omPI7Mi73QsR49lC52Pd5fLT1JdoG7mUQCPdgYjr1QL5A80zQcOn4RULwHaBq9USs7PUTUsz11jsy99nkuPdDClTyVlmu8DJxfu1F6Lj3sBIA9lFY7PVemMD1M62a8HMqUvVTzHjy0AII89RKTPXEUoL0A+968zAEevPFppT06m+W9qivsPWTlOz6EA489SEwjvZ7iyL19HMA8Q+nrPb2E2z0V9eQ7GHS+veO/Kz2Bs9493v9zPeRnjL2iNlg8z3m0vaePED7Sct29ErtqvEmPej4RZpU9pwIqvT9sKb0hK+c86zvZPXV8sz2+JQs9l4/bvevTiD24PXY8HJM2PBNzDL4Ynlc8E89CvUgqkT09pti9dQk9Pfi0Dj7p0209FIiavePFt7tYgIc9iRdCvrCMir2aJEa9FA22PXUeXD3cP0G+GY82vR86FT6MV9u8LN4dvU11Bb63VBs+VoVfPmx24j09xyI+9Ie6PZ+QGD4Hf3C+Ybo/vM mCu2b0i00E91JiDPVJY/j2zYXi+H7mhvbiBrj0ThbA7G4MhvaJxGL6TvOw9WQXgPXSrED7e/ws9W+QZPnZhNj7G+TG+7/NJvSRRmjtyDHk8QmB8PX1jmz1rl02+83gwPSrFHz1vybo9mkiLvZWYKr7uZII9kml0PH4gqj0bRZ89n9nePUU7qD3G71K+EuEhvv3i873/WZq8a74JPuDrqDsRPGG+2mTpvVTDsz31Zcm882cGPLtb4b09cVI+bvEyPo0tOrxeTps9ZgnVPUNnzz2ognu+ZYe5vWOO/72V5+C8rnK9PbdyUz7y9nC+feGrvcpB4z2g8oo9LMYsPOW9a778YlY+8suqPZNVzLuoYN87yjETPiUAVT6lMEi+p12ova3hh71VJ7g8VygAPpMX/z0aRme+LOXtO87RLrwdY4g9EP4bvs6BI77MU+I9mmFsvZ4fuL3n92c92YDwPTMVJD6Kn0u+GVNcO9oP2Dt+QS6+v5OGvfsusj1wEPE71PYcvl5nzj0gcM 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 wo9W3uCvOrmeLwgoDk95tcFvby0rzvghns9nJx+vVNjLr0z5ji98XsVvYvexTwpkYU9D/lyur/Uu7ye4AA8Zr6NveOK17wg0XW9wubcu4sUUD15Q6G8yrmGvS5Bhz0UlMc9SpS8vBk6k70o1609v4mGO8VpjjzeB9W95L/TOr4l/DqdEq69dH5mvC1//zxgh5+8WCYSPdNYsDz5ugY9uhdXPFeMUz3cjJE7VAM2PLAakb0ZIQ49GvYMvVaTLj1kvzy9immOvZXQWj0XbK488n4ZvZ6SiTzt6uw8O4n9PCwhprwrIyk9eqWlPa9QVjyKDB89P3Q8PFPKKj2WyiA9LyTlvFxu3DyhAq27+r6mvJqBHbwYGOC8mNoavR0n+TzW8gq9vcuIvD9I9Dww3Me9ZNgLvRzXZr3hjnc9+zUZveOpVz1g9Yg9tkIGPQs11rvGK1i9fG9TvFiZEz3SYIy7cw4OPSVdsryt4T+9lrb3O3/eRD2mNQa8NUoHPVeDST26ArC8NIRtuM 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 +w9onsQvTZ2qTo/Owi+I+vLvQvyCDoMXEC9ms93PVDCAz1E7nG9hGZevbTtWb34CQK+ZOZovHvLFL2IEVo8kdOqPczelLwZIf+9qfSVvfXKij3ySUE+5PU8PSoZxbwkWQQ+iL3Yu2WT9jwOL6A8IYaAvZXSubp0pGG9o2tkPP0TPTz+hR09cm+BPWrtvb0Idr29L/CvubEaaD3hRCA+eVCQvcDhCT1CZRw8AOUvPMpsjTwQ9Da8tA5rvUBCNb1c3L+9Zz17vX00LT0rqJE8DP3+O61ckL2Zzwu8NZGYvXdGq702U5Q9goxoPGqDWDuOukm9yWlSvaZcrT0utrI7d/1MvHAzYzw1lI87EzVQvL8FJ74pWAk8v8ihPRDti7w6cAq8eQoBPPS87j3LpXo80iPZvPHqwrzb9tQ9gTvwPEJvyzwX92C9KboBPEpeyLzCZAE976wbvKfTxb2r4OQ8KSj6PK4HwL1WcOk8AB4mvV1fnz1Jibw9YLknvg/52TyDQe085y23PM 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 wWcn70uJmW8y3OGPdFLpb30XCM7VKpgPcttcT07w+O9A/nXPSXWqj2NumU9HOciOyryZr3HPrk8eKf3PPBLsr1b85Y9QWn4PHGT1z1z03g7fgsIPqm+vj3oxRU82E+GPcfAZ7zemA+8MHdEO/wWlD2iPok9NvS5vXRFvjzT7Zc98zlmvaatij2bYL27AIJVPWWezz1salK8lGEIPVuD4j0hnzC7UC49PMMjHr1DHLA98f2RvL+/GD3uazy86iKavZXxx72TTgw+giDHvRh+gz2iS/29AhorPary+j3qAEy94iTEPRzOKj6ppHk994emvZIr670PZP49ugghPRLa77tcQLi8uO8cvcmDrz035P88ISMVvGKb7D1PYxc9ShpBPjui9DzFzd47t6dkPoLhfD2UUaK9gaS6PYdN/7y2a4M9kwKEPJLDAb5G6AO9EJOQu9li6T1liwq7TlAcvUcR3T0fT5i94UkYPshnK7zHVZi8Fc4gPszqmT2Nc1m9e9pBPRyQZ70kcM 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 5a9Zd0MPiRyO7xR6VW8CasiPoluFzz/8ig+La0LPEMB9L0cMQE8SJQmPO+qk71YHx0+LV2qvTF7PD0RW2S9qoQpPcuvtzwuxD09uvHmPebzIr2idsm9CW+aPaT9Tz3BKCY9oaP1PG0bVLwJwg87XoeRvb0aLT2jqD49+XICu0DKCD0gpYW94mTQvLG3CT3wAfW9rCR2PFcuk73AIZA9nugjPRbAY7pKXyQ8QAHdPD6wPL3C40A8O4J5vcqYLD6LIyW9VI9wPJzOTT36qVq9SlzCPRN+lz3mnzW8DaORvYe+yb2S1As+tOjePXtS4T1ifCg9nbd/vBO5Yr1HK2s9xIFIugubZL1U4kQ9vKFsvS4w/T3rNra9OgzbPWI++z0HgyS8x2NzPD/U0r0Xl4M9zRaJPVoA4Dz1vxC8OgluvdlRDD2D2I896IqcvN2Qlzs4nQW9Y0zVPE6gyT3QGTW9kl4UvJbfKj6BkqO94vjDvKtmd71Go0Y+pyEnPZ1rjj3+mYu9iry5vM 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 FC9+kPPPWsXxT0DSRm+zco3PpsGTz4fEbu7p1cnvZosCr4AVTE+0MGPPf6kqzk7LGc9VkkVvQmUTDzldzO95Uy6vEsCIT09soG9byZ3PHhaIT2+ACO6SHcZPsfJNr38u0c9C5vXPABA6b2cdiY9UssZPVkKsr1nOJG916KwO1XtLz71VqW8pkc+vW3ZFT3iAkO9bpNdPBvlK7xbT949EKSmu9iobj0odJw8wcAKPQrsCL3lPLY9gAqZO7f9Pb0stqa8t2+EPGFt0T2OWqe8+a+1vS7K2z1K/YG9AqzkPUcKhD0AUFC9jM0avKTDYDxa3dW8ggNLvTui6L2IbYE9dcmBPVMu0btnOYo9TizsPAObhz12xvu9gA0JPUrLG70/MkA9gH/ovXgHar0tFx87i3GLPDhNcb41fZU9mAskPk+Agzwg36u9urUXPcUTc73CuEg894mzPLjuDz59F9a9jogyvVepz72PcLC7ZKAEvge9mb02kbo9Y0IRvnYscb6jJ1w9mY2LPM 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 SdNFz0ZkaU8lOaivfdyPLyZ9o09S+gCvaLml7y2ddO8iDVOvYUN+D2Cglu9SiamPVeq+by2wxA9w2OFvZldYr2ZUs88w195PHODAj28BRA9Z8xSvSzaJzx0EEA91HN/PMyOpb1dqBS8XxKKvAmRqT0oc6c8upHiO/AO1bxo6FA9Im+ZPPYk3z2SmM48UBJ6PZXpJr3qX549JrrOPJUjh71OKh+9nLntOwd5v70L2k46mAniPaOHlT3g0g09+hRuvQbBzr0T1W89TeD0vSdrDr3vjdw9XukOviOGSr1D4CU9j+1Rvf8jVz0pRQQ8Q5TivJzc4b0yjIy84SA8PUErPT1zISo9mpPzvXZDUT120oM9H9yUvc7W4TwPvJY9ebiguwb9BL3esFi73Mb1vfB0DL2PEvw9suutPeQHrD1nW449siCKPH1KGr6z2xY8jFxjvQWUBr6D2As+UuuHvRr53j3Z0v29FpuZvXWMWz2aAqQ9aIPuPdKgjr2ORL29KeujOzmY1j0LhM 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 XK9p6eevcmQrrwDNuq7J9T1vNmOJz2wki88JFLDPDw7cj0VbY89lVHNvfVhjz1+EQK9A7UYvZDM1bxBofU8gkOcvdW5Wz3kJz89S+7/vOsyfL35zYk9yfY+vP5D47wGD3G8u+UWPJucCL3YLI88DdZ2vaCuzjxm+Q29T1RbPf0JmzytLdO8BIBjPFqKjz1qdJW8RmcvPKtm/rw6D448Xw+0vUu+fLtdnrE8WyUnvA3hLL1tr4Q8r85kvRmU6byrwuY8X/BCPGh0pbx2cAS+OC1Qvc1zPDxi9Om818n5vbH9mj2NyRy8Z6+vPWNzA7311pe9DDDdPdgNvT1jp0s8maW4vWZZF7nH8SM9BiMfvSnLB71m2Iu9zSuZvdEuoD1BiKU8DdSRO5zLB70kuuq6KGWcPcVeej3sGQW9VAGZPXGjOD0/7a08Q8rXvRI7Ej2cjks9LrIqPWOrML2QcHm8AFLKPL+SFT3BrYw8dAAPPLb1Gz0dsia8yW+cO2aEZzvlhbO8fjS9uM 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 kw9HPcDO2D9q7zhwkc9IICFPfLdKL0SzRU+qqM6vLYSk7z7HZw9aGhgvSC48737C8y9hB/yPfLWfT19hcu8oUy7veh9lT3WIX692nc5PG4wvL2VLQs+j/pmvA4qOr0f8Z08twR3vVjliT3LcvK8VzNpvSX4I762mL29sVsDPQQpCT3Itue8i7sUvllXIz5jNYM8vpSuPWJ5L71YBMQ9PQodPrt/gLwfSzY97D+TvcMXwLtAIJY9KVLEPS92hL1KzmG7ywd0Pf8iOzzU7P+7MLIqvVOz5r2enVY9WPw7vX5Tlr3pmBg9Ne+uPdjycL3f6PQ9SAiCvM4Tor3RyBI9CH7xvMFvzL3cuRY8cGMEPr0BC72w1qS9uK2vvUV50DyMRWg8Zzz3u9Qnlr3O/w8+EDTJvRdRgbuRRsg9DGDpPIm6Czw84o28FRGNvWVfRr7GigO+t5WCPRtRdjyxgQS9yzUKvvsEUj7kqOG85r/GPQNSRL2qheA9IeytPdIJ4zxpf9A8Pv5SvM BF9ojuIfXM9RcxcPSnzir2YEkg9k9q3vKoyG73h65Y8zjBEvWYGir3wp8g7SsEdvW/9trw/+fU7FpVQPTRZcj0ShtY9vvGlvI/qAr5Rahy96DiNPHeA+bz5PP28quVzPaMxnr3Zrae7v6atvfeiXj1axgQ84KQVPRqslr154rg9z/+8vTHsVjzGLA09rTN8vOhNAL0s0Gs70u2nOkpCs72ZXK+98nMCvRRSvb0r3eO8HE50vVmW3D0peK682la3PYMycTwscNS8MiP6uV8wgD2N3V49ses5vZjbfb05GFI7yt29Pe9zDL1opSA+gbSPvIPfKr3ZI9s9GHcjvePZM77wSES8r6qpvRZHzrxFV4q9BHQWOl5JvD27wDs9glciPfAkPb6rr807oPR6vM96G7zRO5M8CB8EumSu3L3A5Z09D+0mvUQgALt3DYY8UD+WPGUxpbsZ5Cm69sq4veaktLyKaFW8ieahPYQLwr0CV5A79XgZvdM9pL1flIg9HqaPvfNZ4LyPHM TW9s99ovWU/2D3NXfs88d9rPY+IfDxW+hG+CO/zvF8hhzwQOuq84hbEvJqf270128K7oCgQu1yptjxXmyE+BkM0vfLt8TwJroU9zbBgPZwMBr4YD2I9T1jdu/JMmL2vPQG+CIvWPctj8jynWZg9FoGyPKmib74EOUi9U/lEPUiRIr0uI2A9SyEKOzD5Jr1dnWc92EBjPCiwaDxWPmE8aifsOqFvsTwRZS++MFiPvVry0bsJcpi972nRPDxI/73cotu8cmh0veEj8rwEkYK7fm5UO7HC9by3Ib86Z0Hfu1ABhT1Y/wO8H7QIPeofALsnSiy+EBo4vEzAv7xgwDy91Dz2vLfDlr1WJGk96pWrvBJLBb2mI7w9zlVdvSDyPT2TGDy8BfUAPE716Dt1LiG9S4ILPvuXAr2Kx/i8Cp7zPeIrlT3n6pY9EULNvJDSP75pjzS9G4OrvWt1zr2c7pe74lZrPTLgsrtJ5D09d4ndvB+rOD5+lUO9i0dwPgVtbb2TnQu+GZkJPM ZiLsru6Z629S312vPR2BL4Lm6w9r0vbvBLhbr3k62+8KPxvu0gTOb3+DGm84OlgPdGdET4KqBc7ab0mPg3JC7yXiE6+x+AjPbcxILwIHka9mvgSvRL84L0F3cW8+bOUvd3A5rzwX3A9RBqnO67QIr1IX+K83iuCPR/MJD55Vaa9D+fLPSDz3b2EXxW9D88PPnNsxjvUVZ09NGELPEtPfb1MBXS9qh2GvWSfvr3H1Cy9sDOMPRc1hb30Rq29JyIZO41msD6NAWK9JqJmPm9rujtiTnC9bNGaPR5RCr1+axy7MGQRPB8OQL1+psi8Oz57vTl+0L1CdU89bKJFuv/0BL3yyS+9rUsqPZyvgz7NiGg9lunHPUaQAL2MFju+NckBPSMAjb3reqm9kBQ2vWHFPjxfr9O7ntXDvWrXi70Y/A8+TRWxPPpLpL0LRaW8xzepPdAB5D0v5JI8RTx2PRFxtL2Fp0m9xiNePfmz5T0r3s+6KBr/PAuEWr1q6uW9Qho9vRB+yr2i5M 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 pQ8GRcCvWY+uL12bom97+vJPDcZjL06FTq9TXGRvZ51AD5o/G68iTw3PtUitrxp95q9oQaSPdSFtz10St29PH4rOk3SWD3z+iE8DtmNvaN4q72uV1S9qMB1uxCyfT0PcMK8Ip2FvU6bcjx/F1a9PS9lPcLAIL175Wk6ElcAPd5Z77wNtGC9WsdhvT/SSj0quUk9C0GWvffmr7258Qi9dh5/vP25yTzSWWi9iVo7PB+usD1Kgpi92xyfvJhEj7ovQdY9wNSLPdzn2byelqG9bIsQPGG5Fryf5S47kF+nvAe92js9uJK8+zVKPZ3rUryv/Xe9kD+GPTmepzxusPs7ERyqPdgPaTzgS8W8/WqzPIDwkT1olpe9eERKPYRxhz0Do/06Q1UvvUNmN70nFIi9OYD/u9E9SD2IQg29M9HNPGMiwbygMSM9qojlvOIvnb1nEog9Gl66PcWXDjzMErQ7yc7aPN37SD0gZUe9o4+ovQQ5mr0mCja9/DK5PelzxT28sc69tmSZPM 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 D9ChrxVLfM86cIBPcQq0jxCb4c87+jkPAH5Eb2fjGg8SCO7Pekno7ylKJy6OY01PbJDm70npKW9YS6LO3Dn2jwRzPM8GcySvXDjZTp9YwE9dAg/Pamlub3ODBw9mQy9PdJlZz1bxB49oatxPZF/ejww3k896DqQO3i4+7wYDGq9P7raPRFSCr1vnIM9Yc9iPUkiWToIPVm9gNuPPVJC0r2osp09gMRQPEfTND6FjRk9QPsPPDzoIL2GcLk87uzJPKfORLybNcS9HNXSPVJCTj1W3MS8PH4dPRNRaT1Fyxy9EfkgPNCXnr0nKT+9Ma2mO6Xh7T0E3Ju8HyCvPc8I1z38Eae7dS+YPX5HA722ziS+sZqcPSLVkz12+NC8rxwxvfEMx7z2b0k9VBYGvFrWbb1VYuU8DWBDPb56Iz6U8ii96KcmPV6nzDuagHg8fTcdPfl80711B5u96aaqPXzhgbu+Fgg+AeE9PTskrDwkHoG8R7pRPRfKH77xcmo9hELYPSivfz7N8M 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 p+8qqiPPCj2ub1OKXE9szO/uyekk7x6ibe9JgWIOz83UT6O9Lo9MREYPj6E8Dw0rAu+dNtUPOUV2LyJs869Oe7VPFxivL3LyS+9C82svXio972eQy+8ZnZLPRZJj70acYW9nmlWvXFODD6pxFC9LeLxPcFvD77S4Cg9vufePUCX8TyRswc+snfWPRP7tryU5QK+bkuovUyMB76+jpS918xWPQLPzL2LNVq7ekLavRBZgD5C4MO8KOh6Pq0MortBawe9uonBPWKfL73ZZAm8PatSPfcXgDzbMjW9OOTsvLomA746QKU8wHUOuzWAdb19lSG92GMEveRcgD7hTzs9ZnvZPZea/zzBPxy+Z9BWPSAzTL256Gs7B+yEvVi3gzufOaW9yG/IvdGYR72udPc9PmmgPTPatLyyOoC8/r3IPII3oT2Hb8c857apPSXEz736vWO8Udl9PfLShz1wL5O6DtSNPPRXK70Y9729d5/nu07miL1MGG8941/LPaFcLb2n9B+971Y6OM 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 eqrnLwe4Ke8reWNPfABJj6as+A71t+lPQRTfz2bPlW+bNEbvcTPRztx14g9iYkXPWqxV72v91C8U5tUvaIAKr2gH5I9R2msPNEaR7yzvlc9/5x9PdDUjTybX3e82QCrPb7Rg70Vd8q7lAdQPam5XD3+zeY9RLsePT5Yq723epS9Bq+nPCBmaL3tdIY8JwQgvINqyTuLSfG8SztPPGT0yT1CH4087wPhPX3D87wy3De9+HgPPdaGoTxYqmW8uawLPK5ACD0mV5U9vdEJvRycT70xqm897XLLu+/jLD0gOYi9DUWHPA416j2mWBG9k7QsPXqxgT3nKIO9IpRJPQ9V0jz4jxw8HvSFvYwmLLyAtRy8NG8QPIZLjTxlNWM92icQPGtPQr3aoaA9mV8hPQDVw7xN4ck8ppVGPUMWAr3lRfG7mkOCPVXK/zydTqg9eQ5IvcNPW739uiK9xYmkPSdY5jzwiBC8O8hNvUzaGzx+nrI9hR2hPFZODT0uHBE9PIbQPEsxn7uy8M 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 QI8JM24vbSXPz2wpY+9QEWVvWDw1Dycm5U9xwZ7vWCrw7wiD448T0hxu0+nXD0wW909FZWkPHSwQ706tcg9/JdRPCXRRb1ZuBS79GtdvT3aSTxKelk85ZNpPI7ikLxLRsU9FJo1PMUh8jt8BnA8zoRcPc7Scz2QFhq7fj3Su4zJqjzZRNs9FmMAPthGkL2fRQm6kdurvRR5xT11cmg72nABvngeGL22TII8bv8yvbyYlLqNhWW8LlhmO/UBvbzyGqw9+nqnup5QLT2hkbY9F/RVPTRsXb38T1o9KFTyvaOhhT1UKwm85zWLPJ3TOb1DvJ89KZmWvYbNuzvlgd883dx8PBEkSz2Dynk9n1evvB8/U72BbPI8Hvw3vGz0FL1HBfw8mnhVvfLHOT0/SIA9vXh5PT/Vozz6/y09AuqMPNSVHL0FPyC8bywqO9KNWLyVxIg94pp7vU8aJT2W9KQ9QvrKPJmRab0zTwY8JciOvZgJyT1LUpC6QUuSvQIfnztAmUC9veRjPM LlwgTsWydE9NBMgPC/3Jj3jdaI8mOuJOytJ8TsnmyY7yBfJPTBMjb3TNBY80/k2vUThLz1ILIg6EK0DPXDO9LucRbo8rDDoO+fm4LwVLJg8ku9lO2I7mz0S0S04AMVHvdW5Y73Tn3M9dZWBvdhByr0jbYo8qu7tO/OHhzowcMU8pCAXPI6K3j1s6IY8/HIBvfcfNz3OBV09DlzSu/AvSj2IQwE9f3JNvbj9Zz2WVaY9v5KFPEbZzb2CJFU9vuGjvSuAHz1/ZbC8fUdNPDuGfD06PkI8YQcRvYODYDu7d1k8zHpjvAE9jz3hpx09SS0qPHYMDz0aOyM9ha1/PRaAMb3l0Tu9slv7vKDL0z0IS045ioOVu/2zYbzxTv+7bHkmOw40WTwdS8w93kWpvJ37mrpU7MC9zQ5CPRjSBLtlaEE94J7ovQCF1ryG8P+7ziHhPCYAFD0CIoM9IIv8PbwfOz31Pim9GbTDvTx7qT05+I89MaGiPBldVDwwaK68oqKgveEUDT1rOM 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 KE8FnN9vS9eMr2E+NG9MJ6IvMdagjz8YJK8C6yAPepsqbsamHc9KUOwvGEpsb1VrEC9GMrFPFrRgr1ALts8WhgEvUIdJry1Db688tiPO9/sqr2tJSu9FtCEvK0yODwUhks9e9bFPMekXrr/3QA97uGavRL14b1wqDc9G+xkvZtP27yu2qu8JiqSveQ+H7x6xLM9EMmau+ZZBL07zrg8FRSGvNAJxjzfX5G8ak+ZPOHs6jziPbY8STT8Owwbx72EeiM8Jjd2uWaC1TzMxd29+xKGPVUaQL1vr0Q9J3lZPAsPwb0QjZO9h9REPRrTnjwkJgW9qhnOPZ0HDD3BLk4836pUPN44xry8uBi9Z2HQO3MjyLvBGLI7wYwmvW+5qDzH2w+9sd6VPEVxMr0I8569ULoqPSdqoTyeq389jLh4PMHfTj0Fij08z0V1vf5Smr0ag0M8oJssvRtBWDxr50U85LyPvQFelbsrO509rmIKvdSgnL2nkgA9tbH+OwiK2zuOyXW8gjczvM 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 Ku9kiINvOnI0zyNdP48yQ9tPUqibL22Jyi9ne6GPXx0Eb0MOjK9x/E0vaRyCj0I9c29Toh0PbQVk73jYeO7TtZfPdcsIzsnu+u95zvOvDV3Zz1OvLE9oQk8vdtdkjyuhFK9q4FSvXZIqDqC+fU7PLDkvANlnzzZUIu9oojfu+iXG71pgM49ffG7PfpL/LzRXIA8MRKrvJjEUz3Vb6I9oSb+O7rhcLqIc9a9f/9XPTwZBb1bon88n4ORvYTl1DwZyqe9jcOoPel99juyJaw9EDOMPcbRBb3Opi69GbNCvZBzFb2fYho91z9aPQjRGjwpgYK8VL9tPU64J723Lwg8IHObPJpBhLw46+g6qauyvKB+NzwfHgS9xBSwulSrf73tH5+94GlrvbxBqD1a8xg9NYJUO9fdVz3/aK68wrZGvVQeBL4yQqu8ozYBPYpZO7uwoeg8Fyo1vIV8BL34XEw9wmApPbVt8rz8Y049BjHhvFWQkrwJNtm8tACvPJr+XbvO7H69oGKDPM 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 T4ODz1FFa09ui7zPFuZVbzqBLU9AT64vMZxobymyr69hWohvJObQby3xeA88p6XvSqgML0McjY9/VTiPRRy8zzRZgM8gul4O9FYaj22zpM9JD9ivfZutbwHkFk9zimBvdkfBbxLMum8KOa6vAOWNL0vj2Q8XDVhvbWb+jsVI5891k9CvpyjI74D1j++qEP2PKEQBj5oD329xVSVvptxfj1LBIK+er2QPb6yzr2hVts+y+n9PaZper1MOCM+vdLRvZ/pED6ugjQ+R8ndPXnUaD4/EhE99guxvuCrar2Jm4A+AMnqvmKXk71AKa++QPHrPJk1vz6w5JQ9pLPWvTcFJr5brww/9JGHvtNHAr5MO6Y7AhSqvVXABL7zaQG+Bw1sPi1edL54bIc9aaPKvtUUkb0hDke+ZSyFPo4m0j4d3kM+JYKivhFnsb7FtXC+ICv+PpepHz/QYjg+xbNrvuuROz4gq/Y+DUA5Pmf33T4OwCO+i43+vVlNOD0cj7a9Ff+4vgF1Yz4n9M 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 6U+wpOPvuX8mLvtnf4+PeECPVcYQ7z95/8+Kl7RvrcM1L7RULo+th2kvhXtj72441C+ZCyCPuCGAb/TgUW+dHi1vojoND9cGq8+XEtiPmN0AL8iNA4/YNC1vhhs5L72XBQ/Jq1avRgYiL7Ckva93A9uPk1V6T5RHsO+bSK/vbIWmj7SIcs8ymQsvU20tz6GP5E94RtFvonSBT8zJkG+YGtPvnvH4L2M7fM+Fh6Vvkh8YL6dPvu8lf3ivmT4pD300hc7LcU0PQ5Rw7wJSiK8hl6YPn/dNL5pqj29VSx6vlp8Nj8HUEK/hoKFvECnYD7G3+2+EuxCP2jsC78PegS/5+8rv8pcnz7M7wA/SKH5PsAgAz5IlJ49fgJWPSAgID56Hp4+NGAzvwf+RL7myRy/QF3Hvi2RUr6ohKI+A0o1v6Dz4725kZ4+QVeGvqSXDD8zSII9Z1fRvrDUnL4=", "training_traits": {"structure_gen": "Zigzag", "n_layeM rs": 6, "max_nodes": 18, "activation_func": "ReLU", "epoch_num": 6}, "classes_name": ["Cryptoadz", "Cryptopunks", "Moonbirds", "Nouns"]},m=25,b=50,y=59+11/12,w=59+11.5/12,v=60;function z(e,t){const n=Math.log(1-t)/Math.log(1-e);return e=>1-Math.pow(1-e,n)}class V{constructor(e,t,n){const{model:r,inputDim:i}=j(t,n);this.model=r,this.inputDim=i,this.iteration=0,this.stage=0;const o=new Date(parseInt(e.birthYear),0,1).getTime(),a=new Date(parseInt(e.birthYear)+1,0,1).getTime();this.birthDate=new Date(Math.floor((o+a)/M 2));const l=zr.filter((t=>t[0]==e.lifeCycle))[0][2];this.growSpeed=365/l,this.cycleLength=60*l*24*3600*1e3,this.growthFunc=z(.4,.8)}updateAge(e){const t=(e.getTime()-this.birthDate.getTime())/31536e6*this.growSpeed;this.iteration=Math.floor(t/60);const n=t-60*this.iteration;let r;this.age=n;let i,o=0;if(n<25){let e=map(n,0,25,0,1);o=this.growthFunc(e),r=(25-n)/60,this.stage=1,this.stageRatio=map(n,0,25,0,1)}else n<50?(o=1,r=(50-n)/60,this.stage=2,this.stageRatio=map(n,25,50,0,1)):n<y?(o=map(n,50,y,1,0),r=(y-n)/60,tM his.stage=3,this.stageRatio=map(n,50,y,0,1)):n<w?(o=0,r=(w-n)/60,this.stage=4,this.stageRatio=map(n,y,w,0,1)):n<60&&(o=0,r=(60-n)/60,this.stage=5,this.stageRatio=map(n,w,60,0,1));n<50?i=map(n,0,50,0,780/880):n<w?i=map(n,50,w,780/880,800/880):n<60&&(i=map(n,w,60,800/880,1)),this.nextStateTimestamp=Math.round(e.getTime()+this.cycleLength*r),this.statePercentage=round(100*i);let a=(25-n)/60;a<0&&(a+=1),this.nextStableTimestamp=Math.round(e.getTime()+this.cycleLength*a),this.growth=o,this.model.updateNeurons(o,this.iteM ration)}getBrainStatus(){return{totalNeurons:this.model.getTotalNeurons(),neuronsLife:this.model.getNeuronsLife(),stage:this.stage,inputDim:this.inputDim,stageRatio:this.stageRatio,age:this.age,growth:this.growth,nextStateTimestamp:this.nextStateTimestamp,nextStableTimestamp:this.nextStableTimestamp,rebirthCount:max(this.iteration,0),statePercentage:this.statePercentage}}classifyImage(e){const t=new G(e,1,e.length);return this.model.forward(t).mat[0]}}class M{constructor(e,t,n,r,i){this.p=e,this.v=t,this.size=n,thiM s.shape=i,this.col=r}getRadius(){return 1==Oe?1*this.size/2:2==Oe?7*this.size/16:3==Oe||4==Oe?4*this.size/7:0}update(){this.p.add(this.v)}draw(e,t,n,r){const i=this.p.x*r,o=this.p.y*r,a=this.size*r,{col:l,shape:s}=this;let h,c;1==n?h=c=l:2==n?(h=dr(t,1),c=l):(h=dr(t,0),c=dr(l,1));e.stroke(dr(c,map(1,0,1,.25,1))),e.fill(dr(h,map(1,0,1,.15,1))),3==n&&e.fill(dr(h,0)),1==s?e.ellipse(i,o,a,a):2==s?e.rect(i,o,7*a/8,7*a/8):3==s&&(e.beginShape(),e.vertex(i-4*a/7,o),e.vertex(i,o-4*a/7),e.vertex(i+4*a/7,o),e.vertex(i,o+4*a/7M ),e.endShape(CLOSE))}}class E{constructor(e,t,n,r,i,o,a){this.center=e,this.len=t,this.angle=n,this.v=r,this.angV=i,this.c1=o,this.c2=a}getEndpoints(){const e=createVector(this.len/2*cos(this.angle),this.len/2*sin(this.angle));return[Vector.add(this.center,e),Vector.sub(this.center,e)]}update(){this.center.add(this.v),this.angle+=this.angV}draw(e,t){const[n,r]=this.getEndpoints(),i=n.x*t,o=n.y*t,a=r.x*t,l=r.y*t,s=this.c1,h=this.c2;var c=e.drawingContext.createLinearGradient(i,o,a,l);c.addColorStop(0,s),c.addColorStM op(1,h),e.drawingContext.strokeStyle=c,e.drawingContext.globalAlpha=1,e.line(i,o,a,l),e.drawingContext.globalAlpha=1}}function S(e,t){const n=random(TAU),r=random(e,t);return createVector(r*cos(n),r*sin(n))}class R{constructor(e,t,n,r,i){this.wall=n,this.maxR=i;const o=t.length;this.nodes=[];for(let a=0;a<o;++a){const o=[],l=.25*t[a];for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),l=S(.02*i,.05*i),s=random(10,25)*i;o.push(new M(t,l,s,e[a],r))}this.nodes.push(o)}const a=AM (e);a.unshift(e[0]),a.push(e[e.length-1]),this.lines=[];for(let e=0;e<=o;++e){const r=[],l=(0==e?1:t[e-1])*(e==o?1:t[e])*1.5;for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),o=random(5*i,10*i),l=random(TAU),s=S(.02*i,.05*i),h=random(2e-4,.001);r.push(new E(t,o,l,s,h,a[e],a[e+1]))}this.lines.push(r)}}reflectNode(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,{p:o,v:a}=e,l=e.getRadius();(o.x-l<t&&a.x<0||o.x+l>r&&a.x>0)&&(a.x=-a.x),(o.y-l<n&&a.y<0||o.y+l>i&&a.y>0)&&(aM .y=-a.y)}reflectLine(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,[o,a]=e.getEndpoints(),l=e.v;(min(o.x,a.x)<t&&l.x<0||max(o.x,a.x)>r&&l.x>0)&&(l.x=-l.x),(min(o.y,a.y)<n&&l.y<0||max(o.y,a.y)>i&&l.y>0)&&(l.y=-l.y)}update(){for(const e of this.lines)for(const t of e)t.update(),this.reflectLine(t);for(const e of this.nodes)for(const t of e)t.update(),this.reflectNode(t)}draw(e,t,n,r,i){const o=i/this.maxR;for(const t of this.lines){const n=t.length*r;for(let r=0;r<n;++r)t[r].draw(e,o)}for(const i of this.nodeM s){const a=i.length*r;for(let r=0;r<a;++r)i[r].draw(e,t,n,o)}}}function I(e,t){re(e),e.fill(0),e.rect(0,0,500,500),ie(e),e.noStroke(),e.fill(dr(cr("#000000"),.5)),e.push(),e.translate(250,250),e.scale(t),e.translate(-250,-250),e.beginShape(),e.vertex(235.2,24.9),e.bezierVertex(215,24.6,185,11.4,164.8,11),e.bezierVertex(147.2,10.7,129.3,10.4,112.2,14.7),e.bezierVertex(95.1,19,78.5,28.5,69.6,43.8),e.bezierVertex(57.699,64.199,61.599,90.199,70.199,112.2),e.bezierVertex(78.799,134.2,91.6,154.6,97.199,177.5),e.bezierVerM tex(102.499,199.2,100.899,222.5,92.799,243.2),e.bezierVertex(83,268,64.6,288.3,48.9,310),e.bezierVertex(33.2,331.7,24.5,337.5,26.599,364.1),e.bezierVertex(28.2,384.1,61.399,404.2,75.7,418.3),e.bezierVertex(90,432.4,73.7,488.2,91.9,496.7),e.bezierVertex(124.2,511.6,159,472.5,194.3,468.1),e.bezierVertex(211.6,465.9,267.4,501.5,283.9,495.9),e.bezierVertex(340.7,476.7,298.599,428.9,355.4,409.7),e.bezierVertex(370.799,404.5,454.5,407.6,464.4,394.8),e.bezierVertex(478.599,376.3,474.7,349.3,464.299,328.4),e.bezierVertex(4M 53.9,307.5,438.099,289.5,428.699,268.2),e.bezierVertex(412,230,419,182.6,446.1,150.9),e.bezierVertex(449.7,146.7,453.6,142.7,455.8,137.6),e.bezierVertex(459.4,129.299,457.5,119.6,454.8,111),e.bezierVertex(443.2,73.4,417.3,40.4,383.6,20.299),e.bezierVertex(358.1,5,343.2,-.4,313.5,0),e.bezierVertex(287.5,.4,261.6,25.4,235.2,24.9),e.endShape(),e.pop()}function C(e,t,n,r,i,o){let a,l,s;re(t),t.fill(0),t.rect(0,0,500,500),ie(t),t.noStroke(),t.fill(dr(n,.5)),1==i?(l=0,s=25,a=map(o,0,25,500,0)):a=0,t.rect(0,a,500,500),e.nM oStroke(),e.fill(r),e.rect(0,0,500,500),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.M 9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.M 4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVerteM x(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),e.fill(n),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(34M 8.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,5M 1.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,27M 7.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezieM rVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),re(e),e.fill(r),e.beginShape(),e.vertex(184.3,473.2),e.bezierVertex(164,473.2,144.7,462.099,134,444.3),e.bezierVertex(131.7,440.5,129.1,438.5,125,437.1),e.bezierVertex(97.3,428.1,80.5,400.6,85.2,371.8),e.bezierVertex(86.3,365.1,85.8,364.1,79.9,361.2),e.bezierVertex(57.2,349.8,46.2,323.3,54.3,299.7),e.bezierVertex(54.7,298.599,55.1,297.7,55.5,296.9),e.bezierVertex(55.6,296.599,55.8,296.4,55.9,296.099),e.vertex(57.9,291.499),e.vertex(62.5,293.599),e.bezierVertM ex(64.9,294.7,67.3,295.799,69.5,296.9),e.bezierVertex(74.5,299.299,79.1,301.599,83.9,303.099),e.bezierVertex(89.8,304.9,96.5,305.499,102.7,305.9),e.bezierVertex(102.8,305.9,102.9,305.9,103,305.9),e.bezierVertex(106.6,305.9,108.9,302.799,109,299.799),e.bezierVertex(109.1,296.199,106.6,293.4,102.7,292.799),e.bezierVertex(101.3,292.599,99.9,292.4,98.4,292.299),e.bezierVertex(94.3,291.799,90.1,291.299,86,289.9),e.bezierVertex(68.9,284,56.5,270.2,52.7,252.799),e.bezierVertex(48.9,235.499,54.5,217.7,67.6,205.299),e.bezieM rVertex(71.9,201.299,72.7,198.1,70.8,192.399),e.bezierVertex(64.2,172.2,68.8,153.99,84.2,139.599),e.bezierVertex(94.2,130.199,105.5,125.399,117.8,125.399),e.bezierVertex(124.3,125.399,131.1,126.799,137.8,129.599),e.bezierVertex(157,137.399,167.9,152.799,169.4,173.99),e.vertex(169.4,174.399),e.bezierVertex(169.5,175.899,169.6,177.2,169.9,178.299),e.bezierVertex(170.7,181.2,173.2,183.2,176.1,183.2),e.bezierVertex(176.299,183.2,176.5,183.2,176.7,183.2),e.bezierVertex(180.1,182.899,182.6,180.299,182.7,177),e.bezierVertM ex(183.1,162,178.299,148.2,168.399,136.1),e.bezierVertex(158.2,123.5,144.899,115.8,128.799,113.199),e.bezierVertex(123.499,112.299,120.399,109.799,118.899,104.99),e.bezierVertex(113.899,89.699,120.699,72.299,134.899,64.499),e.bezierVertex(139.99,61.699,145.799,60.199,151.7,60.199),e.bezierVertex(162.2,60.199,171.899,64.799,178.1,72.699),e.bezierVertex(179.6,74.6,180.799,76.6,181.9,78.499),e.vertex(182.2,79.099),e.bezierVertex(183.2,80.699,185.2,83.299,188.4,83.299),e.bezierVertex(189.5,83.299,190.6,82.99,191.7,82.3M 99),e.bezierVertex(195.1,80.599,196,76.99,194,72.799),e.bezierVertex(190.1,64.799,184.1,58.499,175.6,53.299),e.bezierVertex(174.6,52.699,173.7,52.099,172.5,51.499),e.vertex(170.5,50.299),e.vertex(163,45.899),e.vertex(170.5,41.599),e.bezierVertex(182,34.99,193.1,30.799,204.4,28.599),e.bezierVertex(208.6,27.799,212.9,27.399,217.2,27.399),e.bezierVertex(217.6,27.399,217.9,27.399,218.3,27.399),e.bezierVertex(231.4,27.599,242.7,38.199,243,50.599),e.bezierVertex(243.4,64.899,243.3,78.99,243.2,93.799),e.bezierVertex(243.2M ,99.799,243.1,105.899,243.1,112.099),e.vertex(243.1,119.199),e.vertex(236.4,116.799),e.bezierVertex(235.7,116.499,235,116.299,234.4,115.99),e.bezierVertex(233.4,115.599,232.6,115.299,232,115.199),e.bezierVertex(230.6,114.899,229.2,114.599,227.8,114.299),e.bezierVertex(223.8,113.499,220.1,112.699,216.4,112.499),e.vertex(216.2,112.499),e.bezierVertex(212.5,112.499,210.7,115.599,210.6,118.599),e.bezierVertex(210.4,122.399,212.7,125.099,216.4,125.399),e.bezierVertex(230.1,126.399,238.9,133.099,242.3,145.199),e.bezierVeM rtex(243.2,148.399,243.2,151.599,243.2,154.499),e.vertex(243.2,155.099),e.bezierVertex(243.2,254.199,243.2,330,243.2,400.599),e.bezierVertex(243.2,401.99,243.2,403.4,243.2,404.9),e.bezierVertex(243.3,411.099,243.3,417.599,242.3,423.9),e.bezierVertex(238.1,449.2,219.6,467.799,194,472.5),e.bezierVertex(190.9,472.9,187.6,473.2,184.3,473.2),e.endShape(),e.beginShape(),e.vertex(315.8,473.1),e.bezierVertex(309.3,473.1,302.8,472,296.5,469.9),e.bezierVertex(270.4,461,253.8,434.9,257.1,407.9),e.bezierVertex(260,384,273.8,36M 6.8,297,358.3),e.bezierVertex(297.7,358.1,298.3,357.8,299,357.6),e.bezierVertex(299.8,357.3,300.6,357.1,301.2,356.8),e.bezierVertex(304.3,355.4,306,351.8,304.9,348.7),e.bezierVertex(304,345.9,301.7,344.2,299,344.2),e.bezierVertex(298.6,344.2,298.1,344.2,297.6,344.3),e.bezierVertex(288.1,346.3,279,350.9,269.7,358.3),e.bezierVertex(268.9,358.9,268.1,359.6,267.2,360.4),e.vertex(265.5,361.8),e.vertex(258.5,367.6),e.vertex(257.4,358.6),e.bezierVertex(257.3,358,257.3,357.5,257.2,357.1),e.bezierVertex(257,356,256.9,354.9,M 256.9,353.7),e.bezierVertex(256.9,334.8,256.9,316,256.9,297.1),e.bezierVertex(256.9,260.3,256.9,222.3,256.8,185),e.bezierVertex(256.8,170.7,268.3,158.8,282.5,158.4),e.bezierVertex(284.8,158.3,286.7,157.6,287.9,156.2),e.bezierVertex(289.099,154.9,289.599,153.2,289.5,151.3),e.bezierVertex(289.3,147.5,286.7,145.1,282.7,145.1),e.bezierVertex(282.5,145.1,282.2,145.1,282,145.1),e.bezierVertex(278.8,145.3,275.5,146.1,272,146.9),e.bezierVertex(270.9,147.2,269.8,147.4,268.6,147.7),e.bezierVertex(267.9,147.9,267,148.2,265.8,M 148.7),e.bezierVertex(265.1,149,264.4,149.3,263.5,149.6),e.vertex(256.8,152),e.vertex(256.8,114.6),e.bezierVertex(256.8,95,256.8,75.4,256.8,55.9),e.bezierVertex(256.8,38,267.2,27.3,284.6,27.3),e.bezierVertex(285.3,27.3,285.9,27.3,286.6,27.3),e.bezierVertex(299,27.9,318.7,34.5,329.6,41.9),e.vertex(336.1,46.3),e.vertex(324.4,53.3),e.bezierVertex(316.2,58.2,310.2,64.6,306,72.9),e.bezierVertex(304.2,76.4,305.1,78.5,306.1,80),e.bezierVertex(307.4,81.9,309.4,83,311.6,83),e.bezierVertex(313.7,83,315.7,81.9,317.1,80.1),e.bM ezierVertex(317.4,79.7,317.8,79,318.1,78.4),e.bezierVertex(318.4,77.9,318.7,77.3,319,76.8),e.bezierVertex(325.3,66.2,336.3,59.9,348.5,59.9),e.bezierVertex(353.2,59.9,357.8,60.8,362.1,62.7),e.bezierVertex(377.6,69.3,386,86.7,381.7,103.2),e.bezierVertex(380.7,107.1,378.5,111.8,371.1,113.1),e.bezierVertex(342.7,118.1,322.2,139.1,317.8,167.8),e.bezierVertex(317.4,170.3,317.3,173.2,317.4,176.5),e.bezierVertex(317.5,180,320.1,182.8,323.5,183),e.bezierVertex(323.6,183,323.8,183,323.9,183),e.bezierVertex(327.1,183,329.8,18M 0.6,330.3,177.2),e.bezierVertex(330.6,175.7,330.7,174,330.9,172.3),e.bezierVertex(331.1,169.8,331.4,167.3,332,164.7),e.bezierVertex(337.3,141.9,357.7,125.4,380.7,125.4),e.bezierVertex(382.5,125.4,384.3,125.5,386.1,125.7),e.bezierVertex(412.8,128.9,432.6,150.9,432,176.9),e.bezierVertex(431.9,182.3,430.9,187.7,429.1,192.7),e.bezierVertex(427.2,197.9,428,201,432.3,205),e.bezierVertex(446.8,218.7,451.8,236,446.6,255),e.bezierVertex(441.4,274,428.3,286.5,408.7,291.3),e.bezierVertex(406.1,291.9,403.6,292.1,401.1,292.3),eM .bezierVertex(400,292.4,398.9,292.5,397.9,292.6),e.bezierVertex(393.6,293.1,390.9,295.7,391,299.5),e.bezierVertex(391.1,303.4,394,305.8,398.5,305.8),e.bezierVertex(409.9,305.8,420.8,302.6,431.1,296.4),e.bezierVertex(431.8,296,432.5,295.5,433.2,295.1),e.bezierVertex(433.8,294.7,434.5,294.3,435.2,293.9),e.bezierVertex(436,293.4,436.6,293.2,437.2,293.1),e.bezierVertex(437.4,293,437.7,292.9,438.1,292.8),e.vertex(442.5,291.4),e.vertex(444.2,295.7),e.bezierVertex(450.9,312.4,449.5,328.4,440,343.4),e.bezierVertex(435.3,35M 0.8,428.7,356.7,420.2,361.1),e.bezierVertex(414.3,364.1,413.7,365.2,414.8,371.7),e.bezierVertex(419.5,400.2,403,427.6,375.6,436.9),e.bezierVertex(371,438.5,368.3,440.7,365.8,444.7),e.bezierVertex(355.2,462.5,336.4,473.1,315.8,473.1),e.bezierVertex(315.8,473.1,315.8,473.1,315.8,473.1),e.endShape(),ie(e),e.fill(n),e.beginShape(),e.vertex(120.2,279.9),e.bezierVertex(117.9,279.9,112.4,279.299,112.2,273.599),e.bezierVertex(112,267.7,117.4,266.7,119.7,266.599),e.bezierVertex(133.1,265.799,143.1,259.499,149.3,247.899),e.bM ezierVertex(149.6,247.299,150.1,246.399,150.3,245.399),e.bezierVertex(150.6,244.299,150.5,243.299,150.5,242.7),e.bezierVertex(150.5,242.6,150.5,242.5,150.5,242.299),e.vertex(150.3,238.799),e.vertex(141.1,235.99),e.bezierVertex(114.6,227.799,95.6,202.499,95.9,175.799),e.bezierVertex(95.9,173.99,96.4,168.199,102.2,168.199),e.bezierVertex(102.6,168.199,103,168.199,103.4,168.299),e.bezierVertex(104.8,168.499,108.2,168.899,109.2,175.599),e.bezierVertex(109.3,176.599,109.5,177.599,109.6,178.499),e.bezierVertex(110.4,184.M 199,111.3,189.99,113.7,195.499),e.bezierVertex(121.9,213.99,139.5,225.499,159.7,225.499),e.bezierVertex(172.1,225.499,184.1,220.899,193.5,212.599),e.bezierVertex(194,212.199,194.4,211.799,194.8,211.399),e.bezierVertex(195.1,211.099,195.5,210.799,195.8,210.399),e.bezierVertex(197.4,208.99,199.2,208.2,200.9,208.2),e.bezierVertex(202.5,208.2,204,208.899,205.3,210.1),e.bezierVertex(208,212.9,207.9,216.9,205,219.9),e.bezierVertex(196.5,228.6,186.3,234.3,174.7,236.8),e.bezierVertex(168.799,238.1,165.6,241,163.899,246.7),M e.bezierVertex(158.3,265.9,139.9,279.7,120.2,279.9),e.vertex(120.2,279.9),e.endShape(),e.beginShape(),e.vertex(187.2,427.5),e.bezierVertex(183.799,427.5,181.299,425.3,180.799,422),e.bezierVertex(180.6,420.8,180.499,419.5,180.399,418.1),e.bezierVertex(180.299,417,180.2,415.8,180.099,414.7),e.bezierVertex(177.199,390.5,156.699,371.3,132.399,370.2),e.bezierVertex(131.99,370.2,131.499,370.2,131.099,370.2),e.bezierVertex(130.699,370.2,130.299,370.2,129.799,370.2),e.bezierVertex(125.99,369.9,123.199,367.2,123.099,363.6),M e.bezierVertex(122.99,360.2,125.799,357.3,129.599,356.9),e.bezierVertex(130.499,356.8,131.499,356.8,132.599,356.7),e.bezierVertex(133.199,356.7,133.799,356.7,134.399,356.6),e.vertex(138.299,356.4),e.vertex(139.1,352.6),e.bezierVertex(139.5,350.7,139.799,348.9,140.2,347),e.bezierVertex(140.899,343.4,141.5,340,142.399,336.8),e.bezierVertex(150.099,310.7,174.399,292,201.399,291.3),e.vertex(201.599,291.3),e.bezierVertex(203.699,291.3,206.299,292,208.299,293.2),e.bezierVertex(210.499,294.5,210.699,297.5,209.99,299.8),e.M bezierVertex(209.499,301.5,208.199,303.9,203.299,304.7),e.bezierVertex(202.199,304.9,200.99,305,199.799,305.2),e.bezierVertex(194.499,305.9,188.99,306.599,183.799,308.9),e.bezierVertex(165.499,316.799,155.199,331.299,152.99,352),e.bezierVertex(152.399,357.8,154.499,361.7,159.699,364.5),e.bezierVertex(178.199,374.4,189.399,390,193.099,410.9),e.bezierVertex(193.699,414.299,193.899,418,193.599,422),e.bezierVertex(193.399,425.2,190.899,427.5,187.399,427.5),e.vertex(187.2,427.5),e.endShape(),e.beginShape(),e.vertex(364.M 3,281.1),e.bezierVertex(346.3,280.6,332.9,272.8,323.5,257),e.bezierVertex(321.6,253.9,320.4,250.2,319.2,246.7),e.bezierVertex(317.7,242.2,315,239.799,310.5,238.799),e.bezierVertex(298.5,236.299,288,230.7,279.4,222.1),e.bezierVertex(276.7,219.4,274.9,215.299,278,211.9),e.bezierVertex(279.4,210.3,281,209.6,282.6,209.6),e.bezierVertex(284.4,209.6,286.4,210.6,288.3,212.5),e.bezierVertex(297.8,221.8,310.4,226.9,323.9,226.9),e.bezierVertex(340.2,226.9,355.1,219.3,364.8,206.2),e.bezierVertex(371,197.8,374.2,188.5,374.5,17M 8.5),e.vertex(374.5,177.9),e.bezierVertex(374.5,177,374.5,176.1,374.7,175.4),e.bezierVertex(375.3,171.8,377.9,169.5,381.3,169.5),e.bezierVertex(381.4,169.5,381.5,169.5,381.7,169.5),e.bezierVertex(385.4,169.7,388,172.4,388,176.1),e.bezierVertex(388.1,190.7,383.4,204,374.2,215.8),e.bezierVertex(365.8,226.5,354.7,233.9,341.2,237.9),e.bezierVertex(340,238.3,338.7,238.6,337.3,239.1),e.bezierVertex(335.9,239.6,335.1,240.4,334.7,240.9),e.bezierVertex(334.599,241,334.5,241.1,334.4,241.2),e.vertex(331.799,243.6),e.vertex(33M 3.199,246.8),e.bezierVertex(338.199,258,346.799,264.9,358.699,267.3),e.bezierVertex(360.199,267.6,361.599,267.7,362.99,267.9),e.bezierVertex(363.599,268,364.299,268,364.899,268.1),e.bezierVertex(369.099,268.6,371.799,271.4,371.499,275),e.bezierVertex(371.199,278.6,368.299,281.2,364.399,281.2),e.vertex(364.3,281.1),e.endShape(),e.beginShape(),e.vertex(323.9,437),e.bezierVertex(323.7,437,323.5,437,323.299,437),e.bezierVertex(319.599,436.7,317.299,434.1,317.4,430.2),e.bezierVertex(317.9,406.099,328.299,388,349.5,375),M e.bezierVertex(350.7,374.2,352,373.5,353.4,372.8),e.bezierVertex(354.099,372.4,354.7,372.1,355.299,371.7),e.vertex(357.499,370.5),e.vertex(357.799,368),e.bezierVertex(360.4,346.6,345.199,323.7,323.9,317),e.bezierVertex(319.099,315.5,314.099,314.9,309.299,314.4),e.vertex(308.199,314.299),e.bezierVertex(305.99,314.099,300.799,312.9,300.899,307.299),e.bezierVertex(300.99,303.499,303.899,300.9,308.099,300.9),e.vertex(308.299,300.9),e.bezierVertex(327.099,301.299,343.099,308.7,355.699,322.9),e.bezierVertex(364.299,332.5M ,369.399,344.099,370.99,357.299),e.bezierVertex(371.099,358.4,371.299,359.4,371.499,360.499),e.bezierVertex(371.599,360.99,371.699,361.499,371.799,361.99),e.vertex(372.499,365.899),e.vertex(377.899,366.199),e.bezierVertex(378.799,366.299,379.699,366.299,380.599,366.399),e.bezierVertex(385.099,366.699,387.899,369.399,387.799,373.299),e.bezierVertex(387.699,377.099,384.99,379.599,380.799,379.799),e.bezierVertex(369.799,380.199,359.99,383.299,351.899,389.299),e.bezierVertex(338.799,398.799,331.699,411.699,330.699,427.M 499),e.vertex(330.699,428.299),e.bezierVertex(330.599,429.199,330.599,430.099,330.499,430.799),e.bezierVertex(330,434.7,327.5,437,323.9,437),e.endShape()}function T(e){return e[0].map(((t,n)=>e.map((e=>e[n]))))}function A(e){return e.map((e=>Array.isArray(e)?A(e):e))}function D(e,t){return floor(random(e,t))}function k(e){let t=0;for(const n of e)t+=n[1];let n=random(t),r=0;for(const t of e)if(r+=t[1],n<r)return t[0];return null}function L(e){for(let t=1;t<e.length;++t){let n=D(0,t),r=e[t];e[t]=e[n],e[n]=r}}functioM n P(e){return null==e||""===e}function O(e){return new Promise((t=>setTimeout(t,e)))}function F(e,t,n){let r=0;for(let i=1;i<=1e3;++i)for(let o=1;o<=1e3;++o)if(e*o%(t*i)==0){let e=1*i/o;abs(e-n)<abs(r-n)&&(r=e)}return r}function N(){let e=60*(new Date).getTimezoneOffset()*1e3;return new Date(Date.now()-e).toISOString().slice(0,-1)}function B(e,t,n){let r;if(push(),textSize(e),textWidth(t)<=n)r=t;else for(let e=0;e<t.length;++e){const i=t.slice(0,e+1)+"...";if(textWidth(i)>n){r=i;break}}return pop(),r}function Y(e){M var t=e%10,n=e%100;return 1==t&&11!=n?e+"st":2==t&&12!=n?e+"nd":3==t&&13!=n?e+"rd":e+"th"}class G{constructor(e,t,n){this.n=t,this.m=n,this.mat=[];let r=0;for(let t=0;t<this.n;++t){this.mat.push([]);for(let n=0;n<this.m;++n)this.mat[t].push(r<e.length?e[r]:0),r+=1}return this}copy(){return new G(this.mat.flat(),this.n,this.m)}}class H{static __linear=e=>e;static __relu=e=>Math.max(e,0);static __leaky_relu=e=>e>0?e:.2*e;static __sigmoid=e=>1/(1+Math.exp(-e));static __tanh=e=>Math.tanh(e);static __apply_unary_op(e,t)M {const n=e.copy();for(let e=0;e<n.n;++e)for(let r=0;r<n.m;++r)n.mat[e][r]=t(n.mat[e][r]);return n}static linear=e=>H.__apply_unary_op(e,H.__linear);static relu=e=>H.__apply_unary_op(e,H.__relu);static leaky_relu=e=>H.__apply_unary_op(e,H.__leaky_relu);static sigmoid=e=>H.__apply_unary_op(e,H.__sigmoid);static tanh=e=>H.__apply_unary_op(e,H.__tanh);static __add=(e,t)=>e+t;static __mul=(e,t)=>e*t;static __apply_binary_op=(e,t,n)=>{"object"!=typeof t&&(t=new G([t],1,1));const r=e.copy();for(let e=0;e<r.n;++e)for(let iM =0;i<r.m;++i)r.mat[e][i]=n(r.mat[e][i],t.mat[e%t.n][i%t.m]);return r};static mul=(e,t)=>H.__apply_binary_op(e,t,H.__mul);static add=(e,t)=>H.__apply_binary_op(e,t,H.__add);static matMul(e,t){const n=new G([],e.n,t.m);for(let r=0;r<n.n;++r)for(let i=0;i<n.m;++i)for(let o=0;o<e.m;++o)n.mat[r][i]+=e.mat[r][o]*t.mat[o][i];return n}static softmax(e){const t=H.__apply_unary_op(e,(e=>Math.exp(e))),n=t.mat.flat().reduce(((e,t)=>e+t));for(let r=0;r<e.n;++r)for(let i=0;i<e.m;++i)t.mat[r][i]/=n;return t}}class ${constructor(eM ,t){this.scale=e,this.offset=t}forward(e){return H.add(H.mul(e,this.scale),this.offset)}}class X{constructor(){}forward(e){return e.map((e=>e.flat()))}}class W{constructor(e,t,n,r){this.out_dim=e,this.activation=t,this.w=n,this.b=r}forward(e){const t=H.add(H.matMul(e,this.w),this.b);return null==this.activation?t:this.activation(t)}}class U{constructor(e,t,n){this.preprocessLayers=e,this.hiddenLayers=t,this.outputLayer=n,this.totalNeurons=this.hiddenLayers.map((e=>e.out_dim)),this.currentOrders=[],this.currentIteraM tion=null}updateNeurons(e,t){if(t!=this.currentIteration){this.currentOrders=[];for(let e=0;e<this.totalNeurons.length;++e){randomSeed(100*(t+1)+e);const n=[];for(let t=0;t<this.totalNeurons[e];++t)n.push(t);L(n),this.currentOrders.push(n)}this.currentIteration=t}const n=A(this.totalNeurons),r=n.reduce(((e,t)=>e+t))*(1-e);for(let e=0;e<r;++e){const t=n.map(((e,t)=>(e-1)/this.totalNeurons[t]));n[t.map(((e,t)=>[e,t])).reduce(((e,t)=>t[0]>e[0]?t:e))[1]]-=Math.min(r-e,1)}this.neuronsLife=[];for(let e=0;e<n.length;++e){M const t=this.currentOrders[e],r=Array(this.totalNeurons[e]).fill(0);for(let i=0;i<n[e];++i)r[t[i]]=Math.min(n[e]-i,1);this.neuronsLife.push(r)}}getTotalNeurons(){return A(this.totalNeurons)}getNeuronsLife(){return A(this.neuronsLife)}forward(e){for(const t of this.preprocessLayers)e=t.forward(e);for(const[t,n]of this.hiddenLayers.entries()){e=n.forward(e);const r=new G(this.neuronsLife[t],1,e.m);e=H.mul(e,r)}return e=this.outputLayer.forward(e),H.softmax(e)}}function q(e){switch(e){case"relu":return H.relu;case"sigM moid":return H.sigmoid;case"tanh":return H.tanh;case"leaky_relu":return H.leaky_relu;default:return H.linear}}function j(e,t){const n=[],r=[],i=Z(t);let o=null,a=0,l=[];for(const t of e.config.layers)if("InputLayer"==t.class_name)o=t.config.batch_input_shape.slice(1),l=o;else if("Rescaling"==t.class_name)n.push(new $(t.config.scale,t.config.offset));else if("Flatten"==t.class_name)o=[o.reduce(((e,t)=>e*t))];else if("Dense"==t.class_name){const e=[t.config.units],n=o[0]*e[0],l=e[0],s=i.subarray(a,a+n);a+=n;const h=iM .subarray(a,a+l);a+=l;const c=new G(s,o[0],e[0]),u=new G(h,1,e[0]),f=q(t.config.activation);r.push(new W(e[0],f,c,u)),o=e}const s=r.pop();return{model:new U(n,r,s),inputDim:l}}function Z(e){const t=window.atob(e),n=t.length/Float32Array.BYTES_PER_ELEMENT,r=new DataView(new ArrayBuffer(Float32Array.BYTES_PER_ELEMENT)),i=new Float32Array(n);let o=0;for(let e=0;e<n;e++){o=4*e;for(let e=0;e<4;++e)r.setUint8(e,t.charCodeAt(o+e));i[e]=r.getFloat32(0,!0)}return i}class K{constructor(e){this.elt=e,this._events={},this.widtM h=this.elt.offsetWidth,this.height=this.elt.offsetHeight}position(){if(0===arguments.length)return{x:this.elt.offsetLeft,y:this.elt.offsetTop};var e="absolute";return"static"!==arguments[2]&&"fixed"!==arguments[2]&&"relative"!==arguments[2]&&"sticky"!==arguments[2]&&"initial"!==arguments[2]&&"inherit"!==arguments[2]||(e=arguments[2]),this.elt.style.position=e,this.elt.style.left=arguments[0]+"px",this.elt.style.top=arguments[1]+"px",this.x=arguments[0],this.y=arguments[1],this}show(){return this.elt.style.display="M block",this}hide(){return this.elt.style.display="none",this}size(e,t){if(0===arguments.length)return{width:this.elt.offsetWidth,height:this.elt.offsetHeight};var n=e,r=t;if(n!==te||r!==te){if(n===te?n=t*this.width/this.height:r===te&&(r=e*this.height/this.width),this.elt instanceof HTMLCanvasElement){var i,o={},a=this.elt.getContext("2d");for(i in a)o[i]=a[i];for(i in this.elt.setAttribute("width",n*this._pInst._pixelDensity),this.elt.setAttribute("height",r*this._pInst._pixelDensity),this.elt.style.width=n+"px",tM his.elt.style.height=r+"px",this._pInst.scale(this._pInst._pixelDensity,this._pInst._pixelDensity),o)this.elt.getContext("2d")[i]=o[i]}else this.elt.style.width=n+"px",this.elt.style.height=r+"px",this.elt.width=n,this.elt.height=r;this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight,this._pInst&&this._pInst._curElement&&this._pInst._curElement.elt===this.elt&&(this._pInst._setProperty("width",this.elt.offsetWidth),this._pInst._setProperty("height",this.elt.offsetHeight))}return this}style(e,t){if(t inM stanceof Color&&(t="rgba("+t.levels[0]+","+t.levels[1]+","+t.levels[2]+","+t.levels[3]/255+")"),void 0===t){if(-1===e.indexOf(":"))return window.getComputedStyle(this.elt).getPropertyValue(e);for(var n=e.split(";"),r=0;r<n.length;r++){var i=n[r].split(":");i[0]&&i[1]&&(this.elt.style[i[0].trim()]=i[1].trim())}}else if(this.elt.style[e]=t,"width"===e||"height"===e||"left"===e||"top"===e){var o=window.getComputedStyle(this.elt).getPropertyValue(e).replace(/[^\d.]/g,"");this[e]=Math.round(parseFloat(o,10))}return thisM }value(){return arguments.length>0?(this.elt.value=arguments[0],this):"range"===this.elt.type?parseFloat(this.elt.value):this.elt.value}mouseClicked(e){return this._adjustListener("click",e,this),this}isFocused(){return document.activeElement===this.elt}_adjustListener(e,t,n){return!1===t?this._detachListener(e,n):this._attachListener(e,t,n),this}_attachListener(e,t,n){n._events[e]&&this._detachListener(e,n);var r=t.bind(n);n.elt.addEventListener(e,r,!1),n._events[e]=r}_detachListener(e,t){var n=t._events[e];t.elt.M removeEventListener(e,n,!1),t._events[e]=null}}function J(e,t){var n=document.createElement("button");return n.innerHTML=e,t&&(n.value=t),ee(n)}function Q(e){var t=arguments.length>1&&void 0!==arguments[1]&&arguments[1],n=function(t){var n=!0,r=!1,i=void 0;try{for(var o,a=t.target.files[Symbol.iterator]();!(n=(o=a.next()).done);n=!0){var l=o.value;File._load(l,e)}}catch(e){r=!0,i=e}finally{try{n||null==a.return||a.return()}finally{if(r)throw i}}};if(window.File&&window.FileReader&&window.FileList&&window.Blob){var M r=document.createElement("input");return r.setAttribute("type","file"),t&&r.setAttribute("multiple",!0),r.addEventListener("change",n,!1),ee(r)}}function ee(e){return document.body.appendChild(e),new K(e)}createImg=function(){var e,t=document.createElement("img"),n=arguments;return n.length>1&&"string"==typeof n[1]&&(t.alt=n[1]),n.length>2&&"string"==typeof n[2]&&(t.crossOrigin=n[2]),t.src=n[0],e=ee(t,this),t.addEventListener("load",(function(){e.width=t.offsetWidth||t.width,e.height=t.offsetHeight||t.height;var r=M n[n.length-1];"function"==typeof r&&r(e)})),e},createInput=function(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:"",t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:"text",n=document.createElement("input");return n.setAttribute("value",e),n.setAttribute("type",t),ee(n,this)};const te="auto";function ne(e){re(e);const t=e._rectMode;e.rectMode(CORNER),e.rect(0,0,e.width,e.height),e.rectMode(t),ie(e)}function re(e){e.push(),e.fill(255,255,255,255),e.blendMode(REMOVE)}function ie(e){e.blendModM e(BLEND),e.pop()}File=function(e,t){this.file=e,this._pInst=t;var n=e.type.split("/");this.type=n[0],this.subtype=n[1],this.name=e.name,this.size=e.size,this.data=void 0},File._createLoader=function(e,t){var n=new FileReader;return n.onload=function(n){var r=new File(e);if("application/json"===r.file.type)r.data=JSON.parse(n.target.result);else if("text/xml"===r.file.type){var i=(new DOMParser).parseFromString(n.target.result,"text/xml");r.data=new XML(i.documentElement)}else r.data=n.target.result;t(r)},n},File._lM oad=function(e,t){if(/^text\//.test(e.type)||"application/json"===e.type)File._createLoader(e,t).readAsText(e);else if(/^(video|audio)\//.test(e.type)){var n=new File(e);n.data=URL.createObjectURL(e),t(n)}else File._createLoader(e,t).readAsDataURL(e)},XML=function(e){if(e)this.DOM=e;else{var t=document.implementation.createDocument(null,"doc");this.DOM=t.createElement("root")}},document.addEventListener("DOMContentLoaded",(function(){addEventListener("mousemove",(e=>{window.mouseX=e.pageX,window.mouseY=e.pageY}))})M ),new e("global");const oe="522";let ae,le,se,he,ce,ue,fe,de,xe,ge,pe,me,be,ye,we,ve,ze,Ve,_e,Me,Ee,Se,Re,Ie,Ce,Te,Ae,De,ke,Le,Pe,Oe,Fe,Ne,Be,Ye,Ge,He,$e,Xe,We,Ue,qe,je,Ze,Ke,Je,Qe,et,tt,nt,rt,it,ot,at,lt,st,ht,ct,ut,ft,dt,xt,gt,pt,mt,bt,yt,wt,vt,zt,Vt,_t,Mt,Et,St,Rt,It,Ct,Tt,At=!1,Dt=!1,kt=!0,Lt=!1,Pt=!1;const Ot=[" ","Growing","Stable","Decaying","Dead","Rebirth"];let Ft,Nt,Bt,Yt,Gt,Ht,$t,Xt,Wt,Ut,qt,jt,Zt,Kt,Jt,Qt,en,tn,nn,rn,on,an,ln,sn,hn=0,cn=0,un=0,fn=!1,dn=!0,xn=!0,gn=null,pn=null,mn=null,bn=!1,yn=!1,wn=nulM l,vn=null,zn=!1;async function setup(){let e=windowWidth,t=windowHeight;createCanvas(e,t),et=createGraphics(e,t),Xe=createGraphics(e,t),$e=createGraphics(e,t),We=createGraphics(e,t),Ue=createGraphics(e,t),qe=createGraphics(e,t),Qe=createGraphics(e,t),je=createGraphics(e,t),Ze=createGraphics(e,t),Ke=createGraphics(e,t),Je=createGraphics(e,t),tt=createGraphics(500,500),nt=createGraphics(500,500),rt=createGraphics(500,500),_n(),Mn(),Sn(),await En(),Gn(),Rn(),bn=!0}function _n(){Et=parseInt(oe),randomSeed(Et),noiseSeedM (Et)}function Mn(){Wt=Ir(p.training_traits),Cr(Wt)}async function En(){let e;Jt=r(),Qt=o(),[Xt,e]=await Promise.all([s(Jt),h(Qt)]),Ut=new V(Wt.visual,e.layers_config,e.weight_b64),Ut.updateAge(new Date),_n(),Wt.training=e.training_traits,Ht=e.model_name,$t=e.classes_name}function Sn(){le=min(width,height)/1024,ut=Rr.findIndex((e=>e[0]===Wt.visual.colorPalette)),ft=[["#ffffff","#231f20","#231f20"],["#231f20","#ffffff","#ffffff"],["#104da8","#ffffff","#ffffff"],["#722F1F","#FCE1B2","#FCE1B2"],["#e88120","#f9f2e5","#fM 9f2e5"],["#f6b941","#2E2E2E","#2E2E2E"],["#45daaa","#012221","#012221"],["#F1F1F1","#328DFE","#328DFE"],["#111822","#D3EB8D","#D3EB8D"],["#713FF9","#D6D5E6","#D6D5E6"],["#FBDA9D","#795106","#795106"],["#8f5b62","#ead0d0","#ead0d0"],["#eae4cb","#508cac","#508cac"],["#ffc6cc","#cc313d","#cc313d"],["#60A900","#E0FE00","#E0FE00"],["#507DBE","#D0D1D3","#D0D1D3"],["#305848","#E8F2EE","#E8F2EE"],["#2a2634","#5b6988","#cb78a2","#5b6988"],["#590e29","#fd5e53","#fd5e53","#ffe373"],["#0a141d","#57d4e4","#328195","#2A9ECF","#0M ab6a8","#57d4e4"],["#3a2d28","#d5c2ac","#df6338","#3d9895","#d5c2ac"],["#030706","#77c4d9","#77c4d9","#77c4d9","#ffffff","#ffffff","#e72020","#e72020"],["#3a4664","#92f5ff","#f9ff94","#eaa0a2","#55dde0"],["#fbfaff","#f04bb1","#f04bb1","#fac373","#82cef0","#8b31ce"],["#000000","#ffffff","#ff0002","#f26522","#fdff00","#00ff03","#01fffe","#0000ff","#ff00ff"]];for(let e=0;e<ft.length;++e)for(let t=0;t<ft[e].length;++t)ft[e][t]=cr(ft[e][t]);pt=[],ct=ft[ut][0],st=ft[ut][1]}function Rn(){gn=document.querySelector("#uploadM "),pn=document.querySelector("#inputUpload"),gn.addEventListener("dblclick",(()=>{if(!Lt&&!yn)if(In(Ie)&&cn==Ve-1)pn.click();else{if(4!=Pe&&5!=Pe&&(In(Ie)||cn!=Ve-1))return;fn=!0,dn=!0,Bt=0,un=0}})),pn.addEventListener("click",(()=>{pn.value=null,gn.style.display="block"})),pn.addEventListener("change",(()=>{const[e]=pn.files;e?(se=null,gn.style.display="none",Tn(URL.createObjectURL(e)),mn=e):gn.style.display="block"}))}function In(e){for(let t=0;t<e.length;++t){let n=0;for(let r=0;r<e[t].length;++r)e[t][r]>0&&++n;M if(0==n)return!1}return!0}function Cn(){null!=se&&(un=0,Pt=!0,he=0,ue=0,drewLineAnim=!0,ce=(ae/2+we/2)/le,loadImage(se.elt.src,(e=>{const[t,n,r]=Gt,i=createGraphics(t,n);i.image(e,0,0,t,n),i.loadPixels();const o=i.pixels.filter(((e,t)=>t%4!=3)),a=Ut.classifyImage(o);Zt=T([a,$t.map((e=>e.toUpperCase()))]).sort(((e,t)=>e[0]>t[0]?-1:1))})))}function Tn(e){se=createImg(e,""),se.hide(),Cn()}function An(){zn||(ce+=(width-ae-we)/tn/le),re(Xe),Xe.rect(ce*le,0,width,height),ie(Xe),un>=ge&&1==kt&&(kt=!1,un-=ge),kt&&(re($e),$M e.strokeWeight(2*Fe),Jn(he,ze,ct,ct,$e),ie($e)),un>=ge&&0==kt&&(kt=!0,un-=ge,he+=1,he==en&&(++ue,he=0,ce=(ae/2+we/2)/le,1==ue&&(Pt=!1,Dn(),ye=millis())))}function Dn(){At=!0,pe=!1,me=!1,tryButton=br("Try Again",width/2-225*le,height/2+265*le,290*le,40*le,kn),closeResultButton=br("Close",width/2+75*le,height/2+265*le,150*le,40*le,Ln)}function kn(){At=!1,tryButton.hide(),closeResultButton.hide(),pn.click()}function Ln(){Yt=!0,At=!1,Gn(),tryButton.hide(),closeResultButton.hide(),gn.style.display="block",se=null}functiM on keyTyped(){bn&&!1===yn&&!1===yr()&&("i"!==key&&"I"!==key||(Dt=!Dt),"b"!==key&&"B"!==key||(xn=!xn),"s"!==key&&"S"!==key||!1!==Lt||saveCanvasAtCurrentTime(),"k"!==key&&"K"!==key||!1!==Lt||save4KCanvasAtCurrentTime(),"u"!==key&&"U"!==key||!1!==Lt||!1!==At||!1!==fn||!1!==Pt||On())}function On(){Lt=!0,wn=null,vn=null,submitButton=br("Submit",width/2-155*le,height/2+115*le,150*le,40*le,Fn),closeSettingButton=br("Close",width/2+5*le,height/2+115*le,150*le,40*le,Yn),vt=createInput(),vt.position(width/2-252.5*le,height/2M -40*le),vt.size(500*le,25*le),vt.style("font-size","15px"),vt.value(Jt||""),zt=createInput(),zt.position(width/2-252.2*le,height/2+35*le),zt.size(500*le,25*le),zt.style("font-size","15px"),zt.value(Qt||"")}function Fn(){Vt=vt.value(),_t=zt.value(),submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide(),Lt=!1,yn=!0,Nn()}async function Nn(){[wn,vn,_]=await Promise.all([c(Vt),u(_t),O(1e3)]),yn=!1,wn&&vn?(n(Vt),i(_t),window.location.reload()):(Lt=!0,submitButton.show(),closeSettingButton.show(),vt.show(),zt.sM how())}function Bn(){Je.textFont("Trebuchet MS"),Je.noStroke(),pr(Je,600*le,200*le),Je.strokeWeight(1*le),Je.stroke(xt),Je.fill(xt),Je.textSize(50*le),Je.text("update()",width/2,height/2+2.5*le)}function Yn(){wn=null,vn=null,Lt=!1,submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide()}function Gn(){_n(),nn=Date.now(),pe=!1,me=!1,St=Wt.training.structure_gen,Rt=Wt.visual.birthYear,It=Wt.visual.lifeCycle,Ct=Wt.training.epoch_num,Tt=Wt.training.activation_func,Ft=Mr.findIndex((e=>e[0]==Wt.visual.hardwareAccM eleration))+1,1==Ft?(Nt=30,fe=40):2==Ft?(Nt=15,fe=20):(Nt=2,fe=10);const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),ae=100*le,ht=50*M le,Oe=Sr.findIndex((e=>e[0]==Wt.visual.nodeShape))+1,dt=Er.findIndex((e=>e[0]==Wt.visual.nodeFill))+1,lt=_r.findIndex((e=>e[0]==Wt.visual.pattern))+1,de=Math.tanh(Math.log10(Xt.avgfeerate)),de=map(de,0,1,.2,.8),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=maxM (...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=M (height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,at=.7,pt=[],xt=ft[ut][2],gt=ft[ut][ft[ut].length-1];for(leM t e=3;e<ft[ut].length-1;e++)pt.push(ft[ut][e]);mt=sr(xt,gt,pt,width),bt=[],wt=[],yt=width/(Ve-1);for(let e=0;e<Ve;e++)bt.push(hr(mt,yt*e/width)),wt.push(hr(mt,yt*e/width));wt.unshift(bt[0]),wt.push(bt[bt.length-1]),hn=0,cn=0,un=0,Yt=!0;const n={xLeft:ae/8,xRight:width-ae/8,yTop:ae/8,yBottom:height-ae/8},r=Ce.map((e=>e.length));jt=new R(bt,r,n,Oe,le)}function Hn(e,t){let n=Ce[e].length;return[e*we+we/2+ae/2,height/2-(n-1)/2*ve+t*ve]}function $n(e,t){le=min(e,t)/1024,ae=100*le,ht=50*le,we=(e-ae)/Ve,ve=(t-2*ae)/_e,ze=M min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}xe=floor(De.length*de),Le=[],ke=[],ge=floor(map(de,.2,.8,15,2));for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,mt=sr(xt,gt,pt,e),bt=[],wt=[],yt=e/(Ve-1);for(let t=0;t<Ve;t++)bt.push(hr(mt,yt*t/e)),wt.push(hr(mt,yt*t/e));wt.unshift(bt[0])M ,wt.push(bt[bt.length-1])}function Xn(){const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLM ife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){forM (let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*M de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le}function Wn(){jt.update();const e=4==Pe?0:Kt;jt.draw(Qe,ct,dt,e,le)}function Un(){if(!bn)return ar(),void et.image(je,0,0);if(4==Pe||5==Pe)return Wn(),void et.image(Qe,0,0);un>=Nt&&hn<Ve&&(hn++,un=0);for(let e=0;e<hn;e++)1==dt?it=ot=bt[e]:(it=ct,ot=bt[e]),Kn(e,it,ot,$e);un>=Nt&&cn<Ve-1&&(cn++,un=0);for(let e=0;M e<cn;e++)Zn(e)}function qn(){et.background(ct),Ue.background(255),Ue.rectMode(CENTER),ne(Ue),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),Ue.stroke(st),Ue.strokeWeight(8*le),Ue.fill(ct),Qe.background(255),Qe.rectMode(CENTER),ne(Qe),Qe.strokeWeight(le),qe.background(255),qe.rectMode(CENTER),ne(qe),qe.textAlign(LEFT),$e.background(255),$e.rectMode(CENTER),ne($e),Xe.background(255),ne(Xe),Xe.strokeWeight(Ne),We.background(255),We.rectMode(CENTER),ne(We),We.fill(st),We.stroke(st),We.strokeWeight(.1*le),er(lt),We.noStM roke(),xn&&(We.rect(ae/16,height/2,ae/8,height),We.rect(width-ae/16,height/2,ae/8,height),We.rect(width/2,ae/16,width,ae/8),We.rect(width/2,height-ae/16,width,ae/8)),Ze.background(255),Ze.rectMode(CENTER),ne(Ze),Ze.textAlign(CENTER,CENTER),Ze.textStyle(BOLD),Ze.stroke(st),Ze.strokeWeight(8*le),Ze.fill(ct),je.background(255),je.rectMode(CENTER),ne(je),je.textAlign(CENTER,CENTER),je.textStyle(BOLD),Ke.background(255),Ke.rectMode(CENTER),ne(Ke),Ke.textAlign(CENTER,CENTER),Ke.textStyle(BOLD),Ke.stroke(st),Ke.strokeWeigM ht(8*le),Ke.fill(ct),Je.background(255),Je.rectMode(CENTER),ne(Je),Je.textAlign(CENTER,CENTER),Je.textStyle(BOLD),Je.stroke(st),Je.strokeWeight(8*le),Je.fill(ct),Un(),et.image(We,0,0),Pt&&An(),et.image(Xe,0,0),et.image($e,0,0),At&&(tr(),et.image(Ue,0,0)),fn&&(lr(),et.image(Ze,0,0)),Lt&&(or(),et.image(Ke,0,0)),Dt&&(ir(),et.image(qe,0,0)),yn&&(Bn(),et.image(Je,0,0))}function draw(){const e=Date.now();bn&&(Ut.updateAge(new Date(e)),Xn()),qn(),image(et,0,0),zn||un++}function Zn(e){let t,n=Ce[e].length,r=Ce[e+1].length;M for(let i=0;i<n;i++){const[n,o]=Hn(e,i);for(let a=0;a<r;a++){const[r,l]=Hn(e+1,a);t=map(min(Ce[e][i],Ce[e+1][a]),0,1,0,.5),ur(n,o,r,l,bt[e],bt[e+1],Xe,t)}}}function Kn(e,t,n,r){let i,o,a,l=Ce[e].length;for(let s=0;s<l;s++){const[l,h]=Hn(e,s);i=Ce[e][s],a=map(Be,1/30,1,3,10),o=map(Ce[e][s],0,1,2*a,0)*le,o<1.5*le&&(o=0),Qn(l,h,ze,Oe,t,n,o,i,r)}}function Jn(e,t,n,r,i){for(let o=0;o<Le[e].length;o++)Qn(Le[e][o][0],Le[e][o][1],t,Oe,n,r,0,1,i)}function Qn(e,t,n,r,i,o,a,l,s){s.stroke(dr(o,map(l,0,1,.25,1))),s.fill(dr(i,maM p(l,0,1,.15,1))),s.strokeWeight(Fe),fr([a],s),3==dt&&s.fill(dr(i,0)),1==r?s.ellipse(e,t,n):2==r?s.rect(e,t,7*n/8,7*n/8):3==r&&(s.beginShape(),s.vertex(e-4*n/7,t),s.vertex(e,t-4*n/7),s.vertex(e+4*n/7,t),s.vertex(e,t+4*n/7),s.endShape(CLOSE))}function er(e){if(1==e);else if(2==e){We.strokeWeight(1*le);for(let e=ht/4;e<width+ht/4;e+=ht)for(let t=ht/4;t<height+ht/4;t+=ht)We.point(e,t)}else if(3==e){ht=25*le;for(let e=ht/2;e<height+ht/2;e+=ht)We.line(0,e,width,e);for(let e=ht/2;e<width+ht/2;e+=ht)We.line(e,0,e,height)}}M function tr(){Ue.textFont("Trebuchet MS"),Ue.textAlign(LEFT,CENTER),Ue.noStroke(),pr(Ue,800*le,500*le),Ue.noStroke(),Ue.fill(dr(st,.75)),Ue.rect(width/2,height/2-100*le,800*le,300*le,25*le,25*le,0,0),Ue.fill(st),Ue.rect(width/2-250*le,height/2-100*le,225*le,225*le),Ue.image(se.elt,width/2-357.5*le,height/2-207.5*le,215*le,215*le);let e=100*Zt[0][0];Ue.fill(ct),Ue.textSize(25*le),Ue.textStyle(NORMAL),1==me&&(e>=0&&e<20?Ue.text("I have a feeling this image belongs to",width/2-100*le,height/2-170*le):e>=20&&e<40?Ue.teM xt("I have a hunch this image belongs to",width/2-100*le,height/2-170*le):e>=40&&e<60?Ue.text("I think this image belongs to",width/2-100*le,height/2-170*le):e>=60&&e<80?Ue.text("I'm almost certain this image belongs to",width/2-100*le,height/2-170*le):Ue.text("I'm positive this image belongs to",width/2-100*le,height/2-170*le));let t=e.toFixed(2);"100.00"==t&&(t="100"),1==me&&Ue.text("I'm "+t+"% confident that I'm right!",width/2-100*le,height/2-25*le),example=Zt.map((e=>e[1])),be=Ue.textWidth('"FIDENZAAAA"'),defaM ultPhrase=Ue.textWidth('"PERPENDICULAR INHABITATION"'),Ue.textStyle(BOLD);const n=me?example[0]:random(example);if(1===n.split(" ").length){let e=75*be/Ue.textWidth('"'+n+'"');e>75&&(e=75),Ue.textSize(e*le),Ue.text('"'+n+'"',width/2-100*le,height/2-90*le)}else nr(width/2-100*le,height/2-90*le,460*le,110*le,n,Ue);if(millis()-ye>1500&&(me=!0),C(tt,nt,st,ct,Pe,Mt),Ue.image(nt,width/2-370*le,height/2+70*le,80*le,80*le),3==Pe){let e;e=map(Mt,50,60,.25,1.3),I(rt,e),Ue.image(rt,width/2-370*le,height/2+70*le,80*le,80*le)}lM et r,i;Ue.image(tt,width/2-370*le,height/2+70*le,80*le,80*le),Ue.fill(xt),Ue.textSize(40*le),Ue.text("INTELLIGENCE INFO",width/2-275*le,height/2+115*le),Ue.textSize(18*le),Ue.textStyle(NORMAL),Ue.circle(width/2-360*le,height/2+180*le,7.5*le),1==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s growing and getting smarter by the day.`:2==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s stable and it has reached peak performance.`:3==Pe&&(r=`Your Perceptron is ${Math.ceil(Mt)} years old. It ecaying and losing its luster.`),i=2==Pe?"The Perceptron remains stable for some time before entering the decay phase.":`Wait until ${new Date(an).toLocaleString("en-US")} for your Perceptron to reach its peak performance.`,Ue.text(r,width/2-350*le,height/2+180*le),Ue.circle(width/2-360*le,height/2+210*le,7.5*le),Ue.text(i,width/2-350*le,height/2+210*le),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),gr(Ue,width/2-225*le,width/2+65*le,height/2+265*le,height/2+305*le,"SELECT ANOTHER IMAGE"),gr(Ue,width/2+75*le,widthM /2+225*le,height/2+265*le,height/2+305*le,"CLOSE")}function nr(e,t,n,r,i,o){let a=i.split(" "),l=75*be/o.textWidth('"'+i+'"'),s=0,h=[],c=[],u=[],f="",d="";if(l>=50)l>75&&(l=75),o.textSize(l*le),o.text('"'+i+'"',e,t);else if(l<50){if(l=50*defaultPhrase/o.textWidth('"'+i+'"'),l>30){if(l>50&&(l=50),[f,d]=rr(l,n,s,h,c,a,f,d,Ue),0==c.length)return o.textSize(l*le),void o.text('"'+i+'"',e,t);for(s=0,h=[],c=[];o.textWidth(d)>n/le;)l=l*n/le/o.textWidth(d),f="",d="",[f,d]=rr(l,n,s,h,c,a,f,d,Ue)}else{l=30,o.textSize(l);for(lM et e=0;e<a.length;e++)s+=o.textWidth(" "+a[e]),s<=n/le?h.push(a[e]):s>n/le&&s<=n/le*2?c.push(a[e]):u.push(a[e]);for(let e=1;e<h.length;e++)f=f+" "+h[e];if(f='"'+h[0]+f,0==u.length){for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+c[c.length-1]+'"'}else if(1==c.length)d="... "+u[u.length-1]+'"';else{for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+"... "+u[u.length-1]+'"'}}o.textSize(l*le);let r=1.25*(o.textDescent()+o.textAscent());o.text(f,e,t-r/2),o.text(d,e,t+r/2)}}function rr(e,t,n,r,i,o,a,l,s){s.textSize(e);for(let M e=0;e<o.length;e++)(n+=s.textWidth(" "+o[e]))<=t/le?r.push(o[e]):i.push(o[e]);for(let e=1;e<r.length;e++)a=a+" "+r[e];if(a='"'+r[0]+a,0==i.length&&(a+='"',l=""),1==i.length)l=i[i.length-1]+'"';else{for(let e=0;e<i.length-1;e++)l=l+i[e]+" ";l=l+i[i.length-1]+'"'}return[a,l]}function ir(){const e=45*le;qe.textFont("Tahoma"),qe.stroke(st),qe.strokeWeight(2*le),qe.fill(ct),qe.rect(width/2,e/2+height-87.5*le,600*le,90*le),qe.fill(st),qe.rect(width/2-150*le,e+height-170*le,300*le,30*le),qe.fill(ct),qe.rect(width/2+150*leM ,e+height-170*le,300*le,30*le),qe.noStroke(),qe.fill(ct),qe.textSize(15*le),qe.textStyle(BOLD),qe.text("PERCEPTRON INFORMATION",width/2-285*le,e+height-165*le),qe.fill(xt),qe.text("ARTWORK NAME:",width/2+10*le,e+height-165*le),qe.textAlign(RIGHT),qe.textStyle(ITALIC),qe.text("Perceptron #"+Et,width/2+285*le,e+height-165*le);const[t,n]=It.split(" ");let r;"60 Years"===It?r="1 Year":"60 Months"===It?r="1 Month":"60 Weeks"===It?r="1 Week":"60 Days"===It?r="1 Day":"12 Hours"===It&&(r="12 Minutes"),data=[["AI MODEL NAMEM :",B(12*le,Ht,140*le)],["SCALE:","1:"+Te],["NUMBER OF CLASSES:",$t.length],["BIRTH YEAR:",Rt],["NUMBER OF REBIRTHS:",sn.toString()],["AGE:",`${Math.ceil(Mt)} Perceptron Years`],["ONE PERCEPTRON YEAR:",`${r}`],["STATE:",Ot[Pe]],["ACTIVE NEURONS:",`${round(ln*rn)} / ${ln}`],["NEXT STATE TIME:",vr(new Date(on))]],qe.fill(xt);const i=data.length/2;for(let t=0;t<data.length;++t){const n=t<i,r=n?width/2-285*le:width/2+10*le,o=n?width/2-10*le:width/2+285*le,a=e+height-(135-t%i*15)*le;qe.textStyle(BOLD),qe.textAlign(LEFT),M qe.textSize(12*le),qe.text(data[t][0],r,a),qe.textStyle(ITALIC),qe.textAlign(RIGHT),qe.textSize(12*le),qe.text(data[t][1],o,a)}}function or(){Ke.textFont("Trebuchet MS"),Ke.noStroke(),pr(Ke,600*le,200*le),gr(Ke,width/2-155*le,width/2-5*le,height/2+115*le,height/2+155*le,"UPDATE"),gr(Ke,width/2+5*le,width/2+155*le,height/2+115*le,height/2+155*le,"CLOSE"),Ke.textAlign(LEFT),Ke.fill(xt),Ke.text("UPDATE BITCOIN FULL NODE ADDRESS",width/2-252.5*le,height/2-55*le),Ke.text("UPDATE MODEL ADDRESS",width/2-252.5*le,height/2+M 20*le),Ke.textAlign(RIGHT),Ke.textStyle(ITALIC),Ke.textSize(15*le),0==wn&&Ke.text("(*) Invalid Address",width/2+252.5*le,height/2-53*le),0==vn&&Ke.text("(*) Invalid Model",width/2+252.5*le,height/2+23*le)}function ar(){je.textFont("Trebuchet MS"),je.fill(st),je.textSize(50*le),je.stroke(st),je.strokeWeight(1*le),je.text("main()",width/2,height/2)}function lr(){un>=20&&1==dn&&(dn=!1,un=0),dn&&(Ze.textFont("Trebuchet MS"),Ze.stroke(st),Ze.fill(ct),Ze.rect(width/2,height/2,600*le,150*le,25*le),Ze.fill(xt),Ze.textSize(M 75*le),Ze.noStroke(),1==Pe?Ze.text("GROWING",width/2,height/2+5*le):3==Pe?Ze.text("AGING",width/2,height/2+5*le):4==Pe?Ze.text("DEAD",width/2,height/2+5*le):5==Pe&&Ze.text("BIRTH",width/2,height/2+5*le)),un>=20&&0==dn&&(dn=!0,un=0,Bt++,3==Bt&&(fn=!1))}function sr(e,t,n,r){let i=[],o=r/(n.length+1),a=color(e),l=color(t);i.push(a);for(let e=0;e<n.length;e++){let t=color(n[e]);for(let e=1;e<=o;e++){let n=lerpColor(a,t,e/o);i.push(n)}a=t}for(let e=1;e<o;e++){let t=lerpColor(a,l,e/o);i.push(t)}if(i.push(l),i.length>r)i.M splice(r);else if(i.length<r){let e=i[i.length-1];for(;i.length<r;)i.push(e)}return i}function hr(e,t){let n=e.length,r=Math.floor(t*n);return r>=n&&(r=n-1),e[r]}function cr(e){e=e.replace("#","");var t=parseInt(e,16);return color(t>>16&255,t>>8&255,255&t)}function ur(e,t,n,r,i,o,a,l){var s=a.drawingContext.createLinearGradient(e,t,n,r);s.addColorStop(0,i),s.addColorStop(1,o),a.drawingContext.strokeStyle=s,a.drawingContext.globalAlpha=l,a.line(e,t,n,r),a.drawingContext.globalAlpha=1}function fr(e,t){t.drawingContexM t.setLineDash(e)}function dr(e,t){let n=color(e),r=red(n),i=green(n),o=blue(n);return color(r,i,o,255*t)}function xr(e,t,n,r){return mouseX>e&&mouseX<t&&mouseY>n&&mouseY<r}function gr(e,t,n,r,i,o){e.strokeWeight(1*le),e.stroke(st);const[a,l]=xr(t,n,r,i)?[xt,ct]:[ct,xt];e.fill(a),e.push(),e.rectMode(CORNERS),e.rect(t,r,n,i,5*le),e.pop(),e.noStroke(),e.textSize(20*le),e.fill(l),e.text(o,(t+n)/2,(46*r+54*i)/100)}function pr(e,t,n){e.fill(0,0,0,75),e.rect(width/2,height/2,width,height),e.stroke(st),e.fill(ct),e.rect(wiM dth/2,height/2,t,n,25*le)}function mr(e,t){resizeCanvas(e,t,!0),Xe.resizeCanvas(e,t,!0),$e.resizeCanvas(e,t,!0),We.resizeCanvas(e,t,!0),Ue.resizeCanvas(e,t,!0),qe.resizeCanvas(e,t,!0),Qe.resizeCanvas(e,t,!0),je.resizeCanvas(e,t,!0),Ze.resizeCanvas(e,t,!0),Ke.resizeCanvas(e,t,!0),Je.resizeCanvas(e,t,!0),et.resizeCanvas(e,t,!0)}function br(e,t,n,r,i,o){const a=J(e);return a.position(t,n),a.size(r,i),a.style("opacity","0"),a.mouseClicked(o),a}function yr(){return null!=vt&&vt?.isFocused()||null!=zt&&zt?.isFocused()}fuM nction wr(e,t,n,r){let i;if(e<=3){i=`Hey ${String.fromCodePoint(128075)}, I'm ${n}, ${t} years old. I can detect ${r.length} NFT collections: `;let e=0;for(let t=0;t<r.length;++t){const n=r[t];if(e+n.length>500){i+=", etc";break}t==r.length-1?i+=", and ":t>0&&(i+=", "),i+=n,e+=n.length}i+=". ",t<=5?i+="However, I am only a baby, so my recognition ability is not accurate. I'm in the state of Growing both looks and intelligence.":t<=13?i+="I am now a child. My recognition ability is becoming better, but still not verM y accurate. I'm in the state of Growing both looks and intelligence.":t<=25?i+="I have grown up to be a teen. My recognition ability almost reaches the peak, but I will still mess up sometimes. I'm in the state of Growing both looks and intelligence.":t<=50?i+="I finally reach adulthood. My recognition is fully functional now. I'm in the Stable state, where I am the most intelligent with all neurons activated.":t<=60&&(i+="I am now an old Perceptron, so my recognition ability is no longer the best. I'm in the DecayM ing state, meaning that my neurons are dying, and my intelligence is decreasing over time.")}else 4==e?i=`${n} is Dead. However, this is not the end to its story...`:5==e&&(i=`${n} is now in the Rebirth state, and is preparing to start a new life.`);return i}function vr(e){const t=e.getDate(),n=e.toLocaleString("en-US",{month:"long"}),r=e.getFullYear();let i=e.getHours().toString();1==i.length&&(i="0"+i);let o=e.getMinutes().toString();return 1==o.length&&(o="0"+o),`${Y(t)} ${n} ${r} | ${i}:${o}`}saveCanvasAtCurrenM tTime=()=>{save(N())},save4KCanvasAtCurrentTime=()=>{const e=width,t=height,n=min(4096/min(e,t),1e4/max(e,t)),r=e*n,i=t*n;mr(r,i),zn=!0,$n(r,i),qn();let o="4K_"+N()+".png";saveCanvas(et,o),mr(e,t),$n(e,t),zn=!1};const zr=[["60 Years",3,365],["60 Months",40,30],["60 Weeks",37,7],["60 Days",20,1]],Vr=[["1943",1],["1951",1.5],["1957",2],["1969",2.5],["1970",3],["1980",3.5],["1982",4],["1986",4.5],["1988",5],["1997",5.5],["1998",6],["2002",6.5],["2009",7],["2012",7.5],["2014",8],["2015",8.5],["2016",9],["2023",15]],_r=M [["Plain",20],["Dotted",40],["Squared",40]],Mr=[["Basic",30],["Standard",60],["Advanced",10]],Er=[["MNIST",70],["CIFAR",25],["IMAGENET",5]],Sr=[["Theano",60],["Torch",30],["TensorFlow",10]],Rr=[["Whitepaper",2],["Blackboard",2],["Blueprint",2],["Nak",74/14],["Jims",74/14],["Level 10",74/14],["Flips",74/14],["Level 14",74/14],["III",74/14],["XMB",74/14],["Info",74/14],["Adventure",74/14],["Marigold",74/14],["Phoenix",74/14],["Love",74/14],["Cachet",74/14],["Human",74/14],["Twilight",3],["Sunset",3],["Aurora",3],["LiM Vu",3],["Lucid Dream",3],["Parallel",1],["Multiverse",1]];function Ir(e){for(let e=0;e<100;++e)random(1);return{visual:{pattern:k(_r),hardwareAcceleration:k(Mr),nodeFill:k(Er),nodeShape:k(Sr),colorPalette:k(Rr),lifeCycle:k(zr),birthYear:k(Vr)},training:e}}function Cr(e){window.$generativeTraits={"Network Architecture":e.training.structure_gen,"Hidden Layers":e.training.n_layers,"Max Neurons Per Hidden Layer":e.training.max_nodes,"Activation Function":e.training.activation_func,"Training EpoM chs":e.training.epoch_num,Dataset:e.visual.nodeFill,"Deep Learning Framework":e.visual.nodeShape,"Hardware Acceleration":e.visual.hardwareAcceleration,"Paper Pattern":e.visual.pattern,"Life Cycle":e.visual.lifeCycle,"Birth Year":e.visual.birthYear,"Color Palette":e.visual.colorPalette}} <script defer src="https://static.cloudflareinsights.com/beacon.min.js/v2b4487d741ca48dcbadcaf954e159fc61680799950996" integrity="sha512-D/jdE0CypeVxFadTejKGTzmwyV10c1pxZk/AqjJuZbaJwGMyNHY3q/mTPWqMUnFACfCTunhZUVcd4cVL 78dK1pQ==" data-cf-beacon='{"rayId":"7b48ed4fcf0aa22c","version":"2023.3.0","b":1,"token":"6c07c178c94442f695e7a0a2aaee641a","si":100}' crossorigin="anonymous"></script> {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "golden armor"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "undead"}, {"trait_type": "Artifacts", "value": "pauldrons"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "rainbow"}, {"trait_type": "Claws", "value": "bloody"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "sword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "axe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "tiger"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "shield"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "axe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "tribal tattoo"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "honey pot"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "skull"}, {"trait_type": "Artifacts", "value": "dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "pirate flag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "sword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "rainbow"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "eagle"}]} text/plain;charset=utf-8 {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "tiger"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "moon"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "pirate flag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "bloody"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "lamp"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "ghostly companion"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "fire sword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "moon"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "honey pot"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "lamp"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "skull"}, {"trait_type": "Artifacts", "value": "pauldrons"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "laser beams"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "bag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "laser"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "sword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "rainbow"}, {"trait_type": "Claws", "value": "bloody"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "undead"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "robot"}, {"trait_type": "Mane", "value": "rainbow"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "arrow wounds"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "fire"}, {"trait_type": "Claws", "value": "bloody"}, {"trait_type": "Eyes", "value": "laser"}, {"trait_type": "Headgear", "value": "skull"}, {"trait_type": "Artifacts", "value": "frozen staff"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "parrot"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "pauldrons"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "axe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "sword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "blue fire"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "golden armor"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "pauldrons"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "bloody"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "parrot"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "undead"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "lamp"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "skull"}, {"trait_type": "Artifacts", "value": "shield"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "golden armor"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "cape"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "rainbow"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "skull"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "crown"}, {"trait_type": "Artifacts", "value": "dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "lamp"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "tribal tattoo"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "ghostly companioM {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "shield"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "rainbow"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "shield"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "midas touch"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "broadsword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "golden armor"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "dagger"}]} text/plain;charset=utf-8 -{"p":"sns","op":"reg","name":"polarity.sats"}h! {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "laser"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "poisoned dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "mage robes"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "skull"}, {"trait_type": "Artifacts", "value": "sword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "moon"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "wizard staff"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "golden armor"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "tribal tattoo"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "wizard staff"}]} text/plain;charset=utf-8 text/plain;charset=utf-8 1d/Foundry USA Pool #dropgold/ Robinhood BTC wallet text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! <svg xmlns="http://www.w3.org/2000/svg" preserveAspectRatio="xMinYMin meet" viewBox="0 0 350 350"><style>.base { fill: white; font-family: serif; font-size: 14px; }</style><rect width="100%" height="100%" fill="black" /><text x="10" y="20" class="base">Wand</text><text x="10" y="40" class="base">Ornate Chestplate</text><text x="10" y="60" class="base">Ancient Helm</text><text x="10" y="80" class="base">Linen Sash</text><text x="10" y="100" class="base">Hard Leather Boots</text><text x="10" y="120" class="base">LeatL her Gloves of Detection</text><text x="10" y="140" class="base">Necklace</text><text x="10" y="160" class="base">Gold Ring</text></svg>h! IjGREFUND:79D045FC38749E31BE9CBB076B0F7276569A3D2D24E94194A2A40693121396A0 text/plain;charset=utf-8 "p":"sns","op":"reg","name":"66666.unisat" FjDOUT:44B5968C1D0D5E218D7C644785FD5A8EF271729C4ADABE18C157F3A2A67520B3 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/html;charset=utf-8 <meta charset="utf-8" /> position: relative; width: var(--width); height: var(--height); border: 1px solid blue; position: relative; <div id="upload"> <input id="inputUpload" type="file"> function e(e){"use strict";return new function e(t){let n="global"==t?window:this;n.canvas=document.createElement("canvas");let r=n.canvas.getContext("2d");n.width=100,n.height=100,n.canvas.width=n.width,n.canvas.height=n.height,"offscreen"!=t&&(document.body?document.body.appendChild(n.canvas):window.addEventListener("load",(function(){document.body.appendChild(n.canvas)}))),g(),n.MAGIC=161533525,n.RGB=0,n.HSV=1,n.HM SB=1,n.CHORD=0,n.PIE=1,n.OPEN=2,n.RADIUS=1,n.CORNER=2,n.CORNERS=3,n.ROUND="round",n.SQUARE="butt",n.PROJECT="square",n.MITER="miter",n.BEVEL="bevel",n.CLOSE=1,n.BLEND="source-over",n.REMOVE="destination-out",n.ADD="lighter",n.DARKEST="darken",n.LIGHTEST="lighten",n.DIFFERENCE="difference",n.SUBTRACT="subtract",n.EXCLUSION="exclusion",n.MULTIPLY="multiply",n.SCREEN="screen",n.REPLACE="copy",n.OVERLAY="overlay",n.HARD_LIGHT="hard-light",n.SOFT_LIGHT="soft-light",n.DODGE="color-dodge",n.BURN="color-burn",n.NORMAL="norM mal",n.ITALIC="italic",n.BOLD="bold",n.BOLDITALIC="italic bold",n.CENTER="center",n.LEFT="left",n.RIGHT="right",n.TOP="top",n.BOTTOM="bottom",n.BASELINE="alphabetic",n.LANDSCAPE="landscape",n.PORTRAIT="portrait",n.ALT=18,n.BACKSPACE=8,n.CONTROL=17,n.DELETE=46,n.DOWN_ARROW=40,n.ENTER=13,n.ESCAPE=27,n.LEFT_ARROW=37,n.OPTION=18,n.RETURN=13,n.RIGHT_ARROW=39,n.SHIFT=16,n.TAB=9,n.UP_ARROW=38,n.HALF_PI=Math.PI/2,n.PI=Math.PI,n.QUARTER_PI=Math.PI/4,n.TAU=2*Math.PI,n.TWO_PI=2*Math.PI,n.THRESHOLD=1,n.GRAY=2,n.OPAQUE=3,n.INVEM RT=4,n.POSTERIZE=5,n.DILATE=6,n.ERODE=7,n.BLUR=8,n.ARROW="default",n.CROSS="crosshair",n.HAND="pointer",n.MOVE="move",n.TEXT="text",n.VIDEO={video:!0,audio:!1},n.AUDIO={video:!1,audio:!0},n.SHR3=1,n.LCG=2,n.HARDWARE_FILTERS=!0,n.hint=function(e,t){n[e]=t},n.frameCount=0,n.mouseX=0,n.mouseY=0,n.pmouseX=0,n.pmouseY=0,n.mouseButton=null,n.keyIsPressed=!1,n.mouseIsPressed=!1,n.key=null,n.keyCode=null,n.pixels=null,n.accelerationX=0,n.accelerationY=0,n.accelerationZ=0,n.rotationX=0,n.rotationY=0,n.rotationZ=0,n.relRotatM ionX=0,n.relRotationY=0,n.relRotationZ=0,n.pAccelerationX=0,n.pAccelerationY=0,n.pAccelerationZ=0,n.pRotationX=0,n.pRotationY=0,n.pRotationZ=0,n.pRelRotationX=0,n.pRelRotationY=0,n.pRelRotationZ=0,n.touches=[],n._styleCache=[{colorMode:n.RGB,noStroke:!1,noFill:!1,ellipseMode:n.CENTER,rectMode:n.CORNER,curveDetail:20,curveAlpha:0,textFont:"sans-serif",textSize:12,textLeading:12,textStyle:"normal"}],n._style=n._styleCache[n._styleCache.length-1],n._noLoop=!1,n._pixelDensity=1,n._frameRate=null,n._tint=null;let i=nullM ,o=!0,a=[],l=null,s=0,h={},c=0,u=null,f=null,d=null;Object.defineProperty(n,"deviceOrientation",{get:function(){return 90==Math.abs(window.orientation)?n.LANDSCAPE:n.PORTRAIT}}),Object.defineProperty(n,"windowWidth",{get:function(){return window.innerWidth}}),Object.defineProperty(n,"windowHeight",{get:function(){return window.innerHeight}}),Object.defineProperty(n,"drawingContext",{get:function(){return r}}),n.createCanvas=function(e,t){return n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t,g(),n.canvas},nM .resizeCanvas=function(e,t){n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t},n.createGraphics=n.createImage=function(t,n){let r=new e("offscreen");return r.createCanvas(t,n),r.noLoop(),r},n.pixelDensity=function(e){return null==e||(n._pixelDensity=e,n.canvas.width=Math.ceil(n.width*e),n.canvas.height=Math.ceil(n.height*e),n.canvas.style.width=n.width+"px",n.canvas.style.height=n.height+"px",r.scale(n._pixelDensity,n._pixelDensity),g()),n._pixelDensity},n.map=function(e,t,n,r,i,o){let a=r+1*(e-t)/(n-t)*(i-r)M ;return o?r<i?Math.min(Math.max(a,r),i):Math.min(Math.max(a,i),r):a},n.lerp=function(e,t,n){return e*(1-n)+t*n},n.constrain=function(e,t,n){return Math.min(Math.max(e,t),n)},n.dist=function(){return 4==arguments.length?Math.hypot(arguments[0]-arguments[2],arguments[1]-arguments[3]):Math.hypot(arguments[0]-arguments[3],arguments[1]-arguments[4],arguments[2]-arguments[5])},n.norm=function(e,t,r){return n.map(e,t,r,0,1)},n.sq=function(e){return e*e},n.fract=function(e){return e-Math.floor(e)},n.degrees=function(e){retM urn 180*e/Math.PI},n.radians=function(e){return e*Math.PI/180},n.abs=Math.abs,n.ceil=Math.ceil,n.exp=Math.exp,n.floor=Math.floor,n.log=Math.log,n.mag=Math.hypot,n.max=Math.max,n.min=Math.min,n.round=Math.round,n.sqrt=Math.sqrt,n.sin=Math.sin,n.cos=Math.cos,n.tan=Math.tan,n.asin=Math.asin,n.acos=Math.acos,n.atan=Math.atan,n.atan2=Math.atan2,n.Vector=function(e,t,r){let i=this;i.x=e||0,i.y=t||0,i.z=r||0;let o=null,a=null;function l(e,t,n){return null!=e.x?e:null!=t?{x:e,y:t,z:n||0}:{x:e,y:e,z:e}}function s(){null==a&M &(a=i.x*i.x+i.y*i.y+i.z*i.z,o=Math.sqrt(a))}function h(){a=null,o=null}i.set=function(e,t,n){i.x=e||0,i.y=t||0,i.z=n||0},i.copy=function(){return new n.Vector(i.x,i.y,i.z)},i.add=function(){let e=l.apply(null,arguments);return i.x+=e.x,i.y+=e.y,i.z+=e.z,h(),i},i.rem=function(){let e=l.apply(null,arguments);return i.x%=e.x,i.y%=e.y,i.z%=e.z,h(),i},i.sub=function(){let e=l.apply(null,arguments);return i.x-=e.x,i.y-=e.y,i.z-=e.z,h(),i},i.mult=function(){let e=l.apply(null,arguments);return i.x*=e.x,i.y*=e.y,i.z*=e.z,hM (),i},i.div=function(){let e=l.apply(null,arguments);return i.x/=e.x,i.y/=e.y,i.z/=e.z,h(),i},i.mag=function(){return s(),o},i.magSq=function(){return s(),a},i.dot=function(){let e=l.apply(null,arguments);return i.x*e.x+i.y*e.y+i.z*e.z},i.dist=function(){let e=l.apply(null,arguments),t=i.x-e.x,n=i.y-e.y,r=i.z-e.z;return Math.sqrt(t*t+n*n+r*r)},i.cross=function(){let e=l.apply(null,arguments),t=i.y*e.z-i.z*e.y,n=i.z*e.x-i.x*e.z,r=i.x*e.y-i.y*e.x;return i.x=t,i.y=n,i.z=r,h(),i},i.normalize=function(){s();let e=o;retuM rn i.x/=e,i.y/=e,i.z/=e,o=1,a=1,i},i.limit=function(e){s();if(o>e){let t=e/o;i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e}return i},i.setMag=function(e){s();let t=e/o;return i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e,i},i.heading=function(){return Math.atan2(i.y,i.x)},i.rotate=function(e){let t=Math.cos(e),n=Math.sin(e),r=i.x*t-i.y*n,o=i.x*n+i.y*t;return i.x=r,i.y=o,i},i.angleBetween=function(){let e=l.apply(null,arguments);const t=i.dot(e)/(i.mag()*e.mag());let n;return n=Math.acos(Math.min(1,Math.max(-1,t))),n*Math.sign(i.cross(e).z||1)},M i.lerp=function(e,t){return i.x=i.x*(1-t)+e.x*t,i.y=i.y*(1-t)+e.y*t,i.z=i.z*(1-t)+e.z*t,h(),i},i.reflect=function(e){return e.normalize(),i.sub(e.mult(2*i.dot(e)))},i.array=function(){return[i.x,i.y,i.z]},i.equals=function(e,t){return null==t&&null==(t=Number.EPSILON)&&(t=0),Math.abs(e.x-i.x)<t&&Math.abs(e.y-i.y)<t&&Math.abs(e.z-i.z)<t},i.fromAngle=function(e,t){return null==t&&(t=1),o=t,a=t*t,i.x=t*Math.cos(e),i.y=t*Math.sin(e),i.z=0,i},i.fromAngles=function(e,t,n){null==n&&(n=1),o=n,a=n*n;const r=Math.cos(t),l=MaM th.sin(t),s=Math.cos(e),h=Math.sin(e);return i.x=n*h*l,i.y=-n*s,i.z=n*h*r,i},i.random2D=function(){return o=1,a=1,i.fromAngle(Math.random()*Math.PI*2)},i.random3D=function(){return o=1,a=1,i.fromAngles(Math.random()*Math.PI*2,Math.random()*Math.PI*2)},i.toString=function(){return`[${i.x}, ${i.y}, ${i.z}]`}},n.Vector.add=function(e,t){return new n.Vector(e.x+t.x,e.y+t.y,e.z+t.z)},n.Vector.rem=function(e,t){return new n.Vector(e.x%t.x,e.y%t.y,e.z%t.z)},n.Vector.sub=function(e,t){return new n.Vector(e.x-t.x,e.y-t.y,e.M z-t.z)},n.Vector.mult=function(e,t){return null==t.x?new n.Vector(e.x*t,e.y*t,e.z*t):new n.Vector(e.x*t.x,e.y*t.y,e.z*t.z)},n.Vector.div=function(e,t){return null==t.x?new n.Vector(e.x/t,e.y/t,e.z/t):new n.Vector(e.x/t.x,e.y/t.y,e.z/t.z)},n.Vector.dist=function(e,t){return Math.hypot(e.x-t.x,e.y-t.y,e.z-t.z)},n.Vector.cross=function(e,t){return new n.Vector(e.y*t.z-e.z*t.y,e.z*t.x-e.x*t.z,e.x*t.y-e.y*t.x)},n.Vector.lerp=function(e,t,r){return new n.Vector(e.x*(1-r)+t.x*r,e.y=e.y*(1-r)+t.y*r,e.z=e.z*(1-r)+t.z*r)},n.M Vector.equals=function(e,t,n){return e.equals(t,n)};for(let e of["fromAngle","fromAngles","random2D","random3D"])n.Vector[e]=function(t,r,i){return(new n.Vector)[e](t,r,i)};function x(e,t,n){let r,i,o,a,l,s,h,c,u;if(0==t)return[255*(r=n),255*(i=n),255*(o=n)];switch((a=e)>360&&(a=0),h=n*(1-t),c=n*(1-t*(s=(a/=60)-(l=~~a))),u=n*(1-t*(1-s)),l){case 0:r=n,i=u,o=h;break;case 1:r=c,i=n,o=h;break;case 2:r=h,i=n,o=u;break;case 3:r=h,i=c,o=n;break;case 4:r=u,i=h,o=n;break;default:r=n,i=h,o=c}return[255*r,255*i,255*o]}functioM n g(){r.fillStyle="white",r.strokeStyle="black",r.lineCap="round",r.lineJoin="miter"}function p(e){if(0<=e&&e<2*Math.PI)return e;for(;e<0;)e+=2*Math.PI;for(;e>=Math.PI;)e-=2*Math.PI;return e}function m(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;let c=p(a),u=p(l);r.beginPath();for(let a=0;a<h+1;a++){let l=a/h,s=n.lerp(c,u,l),f=Math.cos(s)*i/2,d=Math.sin(s)*o/2;r[a?"lineTo":"moveTo"](e+f,t+d)}s==n.CHORD?r.closePath():s==n.PIE&&(r.lineTo(e,t),r.closePath()),n._style.noFill||r.fill(),n._style.noStrokM e||r.stroke()}function b(e,t,i,o){n._style.noFill&&n._style.noStroke||(r.beginPath(),r.ellipse(e,t,i/2,o/2,0,0,2*Math.PI),n._style.noFill||r.fill(),n._style.noStroke||r.stroke())}function y(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;if(null==a)return function(e,t,i,o){n._style.noFill||r.fillRect(e,t,i,o),n._style.noStroke||r.strokeRect(e,t,i,o)}(e,t,i,o);if(null==l)return y(e,t,i,o,a,a,a,a);const c=Math.min(Math.abs(o),Math.abs(i))/2;a=Math.min(c,a),l=Math.min(c,l),h=Math.min(c,h),s=Math.min(c,s)M ,r.beginPath(),r.moveTo(e+a,t),r.arcTo(e+i,t,e+i,t+o,l),r.arcTo(e+i,t+o,e,t+o,s),r.arcTo(e,t+o,e,t,h),r.arcTo(e,t,e+i,t,a),r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke()}function w(){a=[]}n.createVector=function(e,t,r){return new n.Vector(e,t,r)},n.curvePoint=function(e,t,n,r,i){const o=i*i*i,a=i*i;return e*(-.5*o+a-.5*i)+t*(1.5*o-2.5*a+1)+n*(-1.5*o+2*a+.5*i)+r*(.5*o-.5*a)},n.bezierPoint=function(e,t,n,r,i){const o=1-i;return Math.pow(o,3)*e+3*Math.pow(o,2)*i*t+3*o*Math.pow(i,2)*n+Math.pow(i,M 3)*r},n.curveTangent=function(e,t,n,r,i){const o=i*i;return e*(-3*o/2+2*i-.5)+t*(9*o/2-5*i)+n*(-9*o/2+4*i+.5)+r*(3*o/2-i)},n.bezierTangent=function(e,t,n,r,i){const o=1-i;return 3*r*Math.pow(i,2)-3*n*Math.pow(i,2)+6*n*o*i-6*t*o*i+3*t*Math.pow(o,2)-3*e*Math.pow(o,2)},n.Color=function(e,t,n,r){let i=this;i.MAGIC=786698,i._r=e,i._g=t,i._b=n,i._a=r,i._h=0,i._s=0,i._v=0,i._hsvInferred=!1,i.setRed=function(e){i._r=e,i._hsvInferred=!1},i.setGreen=function(e){i._g=e,i._hsvInferred=!1},i.setBlue=function(e){i._b=e,i._hsvInfM erred=!1},i.setAlpha=function(e){i._a=e/255,i._hsvInferred=!1},i._inferHSV=function(){i._hsvInferred||([i._h,i._s,i._v]=function(e,t,n){let r,i,o,a,l;return r=e<t?e<n?e:n:t<n?t:n,0==(l=100*(i=e>t?e>n?e:n:t>n?t:n)/255)?[o=0,a=0,l]:0==(a=100*(i-r)/i)?[o=0,a,l]:(o=i==e?0+60*(t-n)/(i-r):i==t?120+60*(n-e)/(i-r):240+60*(e-t)/(i-r),[o,a,l])}(i._r,i._g,i._b),i._hsvInferred=!0)},i.toString=function(){return`rgba(${Math.round(i._r)},${Math.round(i._g)},${Math.round(i._b)},${~~(1e3*i._a)/1e3})`}},n.colorMode=function(e){n._stM yle.colorMode=e},n.color=function(){if(1==arguments.length&&786698==arguments[0].MAGIC)return arguments[0];if(n._style.colorMode==n.RGB){if(1==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],1);if(2==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],arguments[1]/255);if(3==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],1);if(4==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],arguments[3]/255)}else{if(1==argumeM nts.length)return new n.Color(...x(0,0,arguments[0]/100),1);if(2==arguments.length)return new n.Color(...x(0,0,arguments[0]/100),arguments[1]/255);if(3==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),1);if(4==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),arguments[3])}return null},n.red=function(e){return e._r},n.green=function(e){return e._g},n.blue=function(e){return e._b},n.alpha=function(e){return 255*e._a},n.hue=function(e){reM turn e._inferHSV(),e._h},n.saturation=function(e){return e._inferHSV(),e._s},n.brightness=function(e){return e._inferHSV(),e._v},n.lightness=function(e){return 100*(.2126*e._r+.7152*e._g+.0722*e._b)/255},n.lerpColor=function(e,t,r){return n._style.colorMode==n.RGB?new n.Color(n.constrain(n.lerp(e._r,t._r,r),0,255),n.constrain(n.lerp(e._g,t._g,r),0,255),n.constrain(n.lerp(e._b,t._b,r),0,255),n.constrain(n.lerp(e._a,t._a,r),0,1)):(e._inferHSV(),t._inferHSV(),new n.Color(n.constrain(function(e,t,r){var i=[[Math.abs(t-M e),n.map(r,0,1,e,t)],[Math.abs(t+360-e),n.map(r,0,1,e,t+360)],[Math.abs(t-360-e),n.map(r,0,1,e,t-360)]];return i.sort(((e,t)=>e[0]-t[0])),(i[0][1]+720)%360}(e._h,t._h,r),0,360),n.constrain(n.lerp(e._s,t._s,r),0,100),n.constrain(n.lerp(e._v,t._v,r),0,100),n.constrain(n.lerp(e._a,t._a,r),0,1)))},n.strokeWeight=function(e){n._style_noStroke=!1,r.lineWidth=e},n.stroke=function(){if(n._style.noStroke=!1,"string"==typeof arguments[0])return void(r.strokeStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._sM tyle.noStroke=!0:r.strokeStyle=e},n.noStroke=function(){n._style.noStroke=!0},n.fill=function(){if(n._style.noFill=!1,"string"==typeof arguments[0])return void(r.fillStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._style.noFill=!0:r.fillStyle=e},n.noFill=function(){n._style.noFill=!0},n.blendMode=function(e){r.globalCompositeOperation=e},n.strokeCap=function(e){r.lineCap=e},n.strokeJoin=function(e){r.lineJoin=e},n.ellipseMode=function(e){n._style.ellipseMode=e},n.rectMode=function(e){n._style.rectM Mode=e},n.curveDetail=function(e){n._style.curveDetail=e},n.curveAlpha=function(e){n._style.curveAlpha=e},n.curveTightness=function(e){n._style.curveAlpha=e},n.clear=function(){r.clearRect(0,0,n.width,n.height)},n.background=function(){if(arguments[0]&&arguments[0].MAGIC==n.MAGIC)return n.image(arguments[0],0,0,n.width,n.height);r.save(),r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity),r.fillStyle="string"==typeof arguments[0]?arguments[0]:n.color(...Array.from(arguments)),r.fillRect(0,0,n.width,n.heightM ),r.restore()},n.line=function(e,t,i,o){n._style.noStroke||(r.beginPath(),r.moveTo(e,t),r.lineTo(i,o),r.stroke())},n.arc=function(e,t,r,i,o,a,l,s){if(o==a)return n.ellipse(e,t,r,i);null==s&&(s=25),null==l&&(l=n.PIE),n._style.ellipseMode==n.CENTER?m(e,t,r,i,o,a,l,s):n._style.ellipseMode==n.RADIUS?m(e,t,2*r,2*i,o,a,l,s):n._style.ellipseMode==n.CORNER?m(e+r/2,t+i/2,r,i,o,a,l,s):n._style.ellipseMode==n.CORNERS&&m((e+r)/2,(t+i)/2,r-e,i-t,o,a,l,s)},n.ellipse=function(e,t,r,i){null==i&&(i=r),n._style.ellipseMode==n.CENTERM ?b(e,t,r,i):n._style.ellipseMode==n.RADIUS?b(e,t,2*r,2*i):n._style.ellipseMode==n.CORNER?b(e+r/2,t+i/2,r,i):n._style.ellipseMode==n.CORNERS&&b((e+r)/2,(t+i)/2,r-e,i-t)},n.circle=function(e,t,r){return n.ellipse(e,t,r,r)},n.point=function(e,t){e.x&&(t=e.y,e=e.x),r.beginPath(),r.ellipse(e,t,.4,.4,0,0,2*Math.PI),r.stroke()},n.rect=function(e,t,r,i,o,a,l,s){n._style.rectMode==n.CENTER?y(e-r/2,t-i/2,r,i,o,a,l,s):n._style.rectMode==n.RADIUS?y(e-r,t-i,2*r,2*i,o,a,l,s):n._style.rectMode==n.CORNER?y(e,t,r,i,o,a,l,s):n._stylM e.rectMode==n.CORNERS&&y(e,t,r-e,i-t,o,a,l,s)},n.square=function(e,t,r,i,o,a,l){return n.rect(e,t,r,r,i,o,a,l)},n.beginShape=function(){w(),r.beginPath(),o=!0},n.beginContour=function(){r.closePath(),w(),o=!0},n.endContour=function(){w(),o=!0},n.vertex=function(e,t){w(),o?r.moveTo(e,t):r.lineTo(e,t),o=!1},n.bezierVertex=function(e,t,n,i,o,a){w(),r.bezierCurveTo(e,t,n,i,o,a)},n.quadraticVertex=function(e,t,n,i){w(),r.quadraticCurveTo(e,t,n,i)},n.bezier=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.bezierVM ertex(r,i,o,a,l,s),n.endShape()},n.triangle=function(e,t,r,i,o,a){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.endShape(n.CLOSE)},n.quad=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.vertex(l,s),n.endShape(n.CLOSE)},n.endShape=function(e){w(),e&&r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke(),n._style.noFill&&n._style.noStroke&&(r.save(),r.fillStyle="none",r.fill(),r.restore())},n.curveVertex=function(e,t){if(a.push([e,t]),a.length<4)return;M let i=function(e,t,n,r,i,o,a,l,s,h){function c(e,t,n,r,i,o){let a=Math.pow(r-t,2)+Math.pow(i-n,2);return Math.pow(a,.5*o)+e}let u=[],f=c(0,e,t,n,r,h),d=c(f,n,r,i,o,h),x=c(d,i,o,a,l,h);for(let h=0;h<s;h++){let c=f+h/(s-1)*(d-f),g=[(f-c)/(f-0),(c-0)/(f-0),(d-c)/(d-f),(c-f)/(d-f),(x-c)/(x-d),(c-d)/(x-d),(d-c)/(d-0),(c-0)/(d-0),(x-c)/(x-f),(c-f)/(x-f)];for(let e=0;e<g.length;e+=2)isNaN(g[e])&&(g[e]=1,g[e+1]=0),isFinite(g[e])||(g[e]>0?(g[e]=1,g[e+1]=0):(g[e]=0,g[e+1]=1));let p=e*g[0]+n*g[1],m=t*g[0]+r*g[1],b=n*g[2]+i*g[M 3],y=r*g[2]+o*g[3],w=i*g[4]+a*g[5],v=o*g[4]+l*g[5],z=p*g[6]+b*g[7],V=m*g[6]+y*g[7],_=b*g[8]+w*g[9],M=y*g[8]+v*g[9],E=z*g[2]+_*g[3],S=V*g[2]+M*g[3];u.push([E,S])}return u}(...a[a.length-4],...a[a.length-3],...a[a.length-2],...a[a.length-1],n._style.curveDetail,n._style.curveAlpha);for(let e=0;e<i.length;e++)o?r.moveTo(...i[e]):r.lineTo(...i[e]),o=!1},n.curve=function(e,t,r,i,o,a,l,s){n.beginShape(),n.curveVertex(e,t),n.curveVertex(r,i),n.curveVertex(o,a),n.curveVertex(l,s),n.endShape()},n.translate=function(e,t){r.tM ranslate(e,t)},n.rotate=function(e){r.rotate(e)},n.scale=function(e,t){null==t&&(t=e),r.scale(e,t)},n.applyMatrix=function(e,t,n,i,o,a){r.transform(e,t,n,i,o,a)},n.shearX=function(e){r.transform(1,0,Math.tan(e),1,0,0)},n.shearY=function(e){r.transform(1,Math.tan(e),0,1,0,0)},n.resetMatrix=function(){r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity)},n.pushMatrix=n.push=function(){n._styleCache.push({...n._style}),n._style=n._styleCache[n._styleCache.length-1],r.save()},n.popMatrix=n.pop=function(){n._stylM eCache.length-1&&(n._styleCache.pop(),n._style=n._styleCache[n._styleCache.length-1],r.restore())},n.image=function(e,t,i,o,a,l,s,h,c){let u=e.MAGIC==n.MAGIC?e.canvas:e;function d(){if(e.MAGIC!=n.MAGIC||!n._tint)return;let t=e.canvas.getContext("2d");t.save(),t.resetTransform(),t.clearRect(0,0,t.canvas.width,t.canvas.height),t.drawImage(f.canvas,0,0),t.restore()}return e.MAGIC==n.MAGIC&&null!=n._tint&&(function(e,t){null==f&&(f=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvasM .height),f.canvas.width==e&&f.canvas.height==t||(f.canvas.width=e,f.canvas.height=t)}(e.canvas.width,e.canvas.height),f.drawImage(e.canvas,0,0),e.tinted(n._tint)),o?l?(h||(h=u.width),c||(c=u.height),r.drawImage(u,l,s,h,c,t,i,o,a),void d()):(r.drawImage(u,t,i,o,a),void d()):(e.MAGIC==n.MAGIC||e.width?r.drawImage(u,t,i,e.width,e.height):r.drawImage(u,t,i,e.videoWidth,e.videoHeight),void d())},n.loadPixels=function(){l=r.getImageData(0,0,n.canvas.width,n.canvas.height),n.pixels=l.data},n.updatePixels=function(){null!=M l&&r.putImageData(l,0,0)},n.loadImage=function(e,t){s++;let r=n.createGraphics(100,100),i=r.canvas.getContext("2d"),o=new Image;return o.src=e,o.crossOrigin="Anonymous",o.onload=function(){i.canvas.width=o.width,i.canvas.height=o.height,r.width=o.width,r.height=o.height,i.drawImage(o,0,0),s--,t&&t(r)},r};let v={};function z(e,t){null==u&&(u=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvas.height),u.canvas.width==e&&u.canvas.height==t||(u.canvas.width=e,u.canvas.height=t)}funcM tion V(){let e=r.canvas.width*r.canvas.height*4;null!=d&&e==d.length||(d=new Uint8ClampedArray(e))}function _(e){u.clearRect(0,0,u.canvas.width,u.canvas.height),u.filter=e,u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()}v[n.THRESHOLD]=function(e,t){null==t?t=127.5:t*=255;for(let n=0;n<e.length;n+=4){const r=.2126*e[n]+.7152*e[n+1]+.0722*e[n+2];e[n]=e[n+1]=e[n+2]=r>=t?255:0}},v[n.GRAY]=function(e){for(let t=0;t<e.length;t+=4)M {const n=.2126*e[t]+.7152*e[t+1]+.0722*e[t+2];e[t]=e[t+1]=e[t+2]=n}},v[n.OPAQUE]=function(e){for(let t=0;t<e.length;t+=4)e[t+3]=255},v[n.INVERT]=function(e){for(let t=0;t<e.length;t+=4)e[t]=255-e[t],e[t+1]=255-e[t+1],e[t+2]=255-e[t+2]},v[n.POSTERIZE]=function(e,t){let n=t-1;for(let r=0;r<e.length;r+=4)e[r]=255*(e[r]*t>>8)/n,e[r+1]=255*(e[r+1]*t>>8)/n,e[r+2]=255*(e[r+2]*t>>8)/n},v[n.DILATE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-M 1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.max(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.ERODE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.min(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.BLURM ]=function(e,t){t=t||1,t=Math.floor(t*n._pixelDensity),V(),d.set(e);let i=2*t+1,o=function(e){let n=new Float32Array(e),r=.3*t+.8,i=r*r*2;for(let t=0;t<e;t++){let o=t-e/2,a=Math.exp(-o*o/i)/(2.5066282746*r);n[t]=a}return n}(i),[a,l]=[r.canvas.width,r.canvas.height];for(let n=0;n<l;n++)for(let r=0;r<a;r++){let l=0,s=0,h=0,c=0;for(let e=0;e<i;e++){let i=4*(n*a+Math.min(Math.max(r-t+e,0),a-1));l+=d[i]*o[e],s+=d[i+1]*o[e],h+=d[i+2]*o[e],c+=d[i+3]*o[e]}let u=4*(n*a+r);e[u]=l,e[u+1]=s,e[u+2]=h,e[u+3]=c}d.set(e);for(let nM =0;n<l;n++)for(let r=0;r<a;r++){let s=0,h=0,c=0,u=0;for(let e=0;e<i;e++){let i=4*(Math.min(Math.max(n-t+e,0),l-1)*a+r);s+=d[i]*o[e],h+=d[i+1]*o[e],c+=d[i+2]*o[e],u+=d[i+3]*o[e]}let f=4*(n*a+r);e[f]=s,e[f+1]=h,e[f+2]=c,e[f+3]=u}},n.filter=function(e,t){if(n.HARDWARE_FILTERS&&null!=r.filter)if(z(),e==n.THRESHOLD){null==t&&(t=.5),t=Math.max(t,1e-5),_(`saturate(0%) brightness(${Math.floor(.5/t*100)}%) contrast(1000000%)`)}else if(e==n.GRAY)_("saturate(0%)");else if(e==n.OPAQUE)u.fillStyle="black",u.fillRect(0,0,u.canvaM s.width,u.canvas.height),u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.drawImage(u.canvas,0,0),r.restore();else if(e==n.INVERT)_("invert(100%)");else if(e==n.BLUR)_(`blur(${Math.ceil(t*n._pixelDensity/1)||1}px)`);else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}},n.resize=function(e,t){z(),u.drawImage(r.canvas,0,0),n.width=e,n.height=t,r.canvas.width=e*n._pixM elDensity,r.canvas.height=t*n._pixelDensity,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0,r.canvas.width,r.canvas.height),r.restore()},n.get=function(e,t,i,o){if(null!=e&&null==i){let i=r.getImageData(e,t,1,1).data;return new n.Color(i[0],i[1],i[2],i[3]/255)}e=e||0,t=t||0,i=i||n.width,o=o||n.height;let a=n.createGraphics(i,o);a.pixelDensity(n._pixelDensity);let l=r.getImageData(e*n._pixelDensity,t*n._pixelDensity,i*n._pixelDensity,o*n._pixelDensity);return a.caM nvas.getContext("2d").putImageData(l,0,0),a},n.set=function(e,t,i){if(i.MAGIC==n.MAGIC){let r=n._tint;return n._tint=null,n.image(i,e,t),void(n._tint=r)}let o=4*(t*n._pixelDensity*r.canvas.width+e*n._pixelDensity);n.pixels[o]=i._r,n.pixels[o+1]=i._g,n.pixels[o+2]=i._b,n.pixels[o+3]=255*i._a},n.tinted=function(){let e=n.color(...Array.from(arguments)),t=e._a;e._a=1,z(),u.clearRect(0,0,u.canvas.width,u.canvas.height),u.fillStyle=e,u.fillRect(0,0,u.canvas.width,u.canvas.height),u.globalCompositeOperation="multiply",u.M drawImage(r.canvas,0,0),u.globalCompositeOperation="source-over",r.save(),r.resetTransform();let i=r.globalCompositeOperation;r.globalCompositeOperation="source-in",r.drawImage(u.canvas,0,0),r.globalCompositeOperation=i,r.restore(),u.globalAlpha=t,u.clearRect(0,0,u.canvas.width,u.canvas.height),u.drawImage(r.canvas,0,0),u.globalAlpha=1,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()},n.tint=function(){n._tint=n.color(...Array.from(arguments))},n.noTiM nt=function(){n._tint=null},n.mask=function(e){r.save(),r.resetTransform();let t=r.globalCompositeOperation;r.globalCompositeOperation="destination-in",r.drawImage(e.canvas,0,0),r.globalCompositeOperation=t,r.restore()},n.clearTemporaryBuffers=function(){u=null,f=null,d=null},n.save=function(e,t){e=e||"untitled",t=t||"png";var n=document.createElement("a");n.innerHTML="[Download]",n.addEventListener("click",(function(){this.href=r.canvas.toDataURL(),this.download=e+"."+t}),!1),document.body.appendChild(n),n.click()M ,document.body.removeChild(n)},n.saveCanvas=function(e,t,r){if(e.MAGIC==n.MAGIC){r&&e.save(t,r);let n=t.split(".");return e.save(n.slice(0,-1).join("."),n[n.length-1])}if(t)return n.save(e,t);let i=e.split(".");return n.save(i.slice(0,-1).join("."),i[i.length-1])},n.loadFont=function(e){let t=e.split("/"),n=t[t.length-1].split(".")[0].replace(" ",""),r=`@font-face {\n font-family: '${n}';\n src: url('${e}');\n }`;const i=document.createElement("style");return i.textContent=r,document.head.append(M i),n},n.textFont=function(e){n._style.textFont=e},n.textSize=function(e){n._style.textSize=e,n._style.textLeading=e},n.textLeading=function(e){n._style.textLeading=e},n.textStyle=function(e){n._style.textStyle=e},n.textAlign=function(e,t){r.textAlign=e,t&&(r.textBaseline=t==n.CENTER?"middle":t)},n.text=function(e,t,i,o){if(!e)return;if(e=e.toString(),n._style.noFill&&n._style.noStroke)return;r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`;let a=e.split("\n");for(let e=0;e<a.length;e++)n._M style.noFill||r.fillText(a[e],t,i,o),n._style.noStroke||r.strokeText(a[e],t,i,o),i+=n._style.textLeading},n.textWidth=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).width},n.textAscent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBoundingBoxAscent},n.textDescent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBounM dingBoxDescent};var M,E=4,S=.5,R=function(e){return.5*(1-Math.cos(e*Math.PI))};n.noise=function(e,t,n){if(t=t||0,n=n||0,null==M){M=new Array(4096);for(var r=0;r<4096;r++)M[r]=Math.random()}e<0&&(e=-e),t<0&&(t=-t),n<0&&(n=-n);for(var i,o,a,l,s,h=Math.floor(e),c=Math.floor(t),u=Math.floor(n),f=e-h,d=t-c,x=n-u,g=0,p=.5,m=0;m<E;m++){var b=h+(c<<4)+(u<<8);i=R(f),o=R(d),a=M[4095&b],a+=i*(M[b+1&4095]-a),l=M[b+16&4095],a+=o*((l+=i*(M[b+16+1&4095]-l))-a),l=M[4095&(b+=256)],l+=i*(M[b+1&4095]-l),s=M[b+16&4095],l+=o*((s+=i*(M[M b+16+1&4095]-s))-l),g+=(a+=R(x)*(l-a))*p,p*=S,h<<=1,c<<=1,u<<=1,(f*=2)>=1&&(h++,f--),(d*=2)>=1&&(c++,d--),(x*=2)>=1&&(u++,x--)}return g},n.noiseDetail=function(e,t){e>0&&(E=e),t>0&&(S=t)};const I=function(){let e,t,n=4294967295;return{setSeed(r){e=t=(null==r?Math.random()*n:r)>>>0},getSeed:()=>t,rand:()=>(e^=e<<17,e^=e>>13,((e^=e<<5)>>>0)/n)}};let C=I();C.setSeed(),n.noiseSeed=function(e){let t=null==e?4294967295*Math.random():e;M||(M=new Float32Array(4096));for(var n=0;n<4096;n++)t^=t<<17,t^=t>>13,t^=t<<5,M[n]=(t>M >>0)/4294967295},n.randomSeed=function(e){C.setSeed(e)},n.random=function(e,t){return null==e?C.rand():"number"==typeof e?null!=t?C.rand()*(t-e)+e:C.rand()*e:e[~~(e.length*C.rand())]},n.randomGenerator=function(e){e==n.LCG?C=function(){const e=4294967296;let t,n;return{setSeed(r){n=t=(null==r?Math.random()*e:r)>>>0},getSeed:()=>t,rand:()=>(n=(1664525*n+1013904223)%e)/e}}():e==n.SHR3&&(C=I()),C.setSeed()};var T=new function(){var e,t,n,r=new Array(128),i=new Array(256),o=new Array(128),a=new Array(128),l=new Array(2M 56),s=new Array(256),h=function(){return 4294967296*C.rand()-2147483648},c=function(){return.5+2.328306e-10*(h()<<0)};this.SHR3=h,this.UNI=c,this.RNOR=function(){return n=h(),e=127&n,Math.abs(n)<r[e]?n*o[e]:function(){for(var t,i,l,s,u=3.44262;;){if(t=n*o[e],0==e){do{l=c(),s=c(),t=.2904764*-Math.log(l),i=-Math.log(s)}while(i+i<t*t);return n>0?u+t:-u-t}if(a[e]+c()*(a[e-1]-a[e])<Math.exp(-.5*t*t))return t;if(n=h(),e=127&n,Math.abs(n)<r[e])return n*o[e]}}()},this.REXP=function(){return(t=h()>>>0)<r[e=255&t]?t*l[e]:funM ction(){for(var n;;){if(0==e)return 7.69711-Math.log(c());if(n=t*l[e],s[e]+c()*(s[e-1]-s[e])<Math.exp(-n))return n;if((t=h())<i[e=255&t])return t*l[e]}}()},this.zigset=function(){var e,t,n=2147483648,h=4294967296,c=3.442619855899,u=c,f=.00991256303526217,d=7.697117470131487,x=d,g=.003949659822581572;for(e=f/Math.exp(-.5*c*c),r[0]=Math.floor(c/e*n),r[1]=0,o[0]=e/n,o[127]=c/n,a[0]=1,a[127]=Math.exp(-.5*c*c),t=126;t>=1;t--)c=Math.sqrt(-2*Math.log(f/c+Math.exp(-.5*c*c))),r[t+1]=Math.floor(c/u*n),u=c,a[t]=Math.exp(-.5*cM *c),o[t]=c/n;for(e=g/Math.exp(-d),i[0]=Math.floor(d/e*h),i[1]=0,l[0]=e/h,l[255]=d/h,s[0]=1,s[255]=Math.exp(-d),t=254;t>=1;t--)d=-Math.log(g/d+Math.exp(-d)),i[t+1]=Math.floor(d/x*h),x=d,s[t]=Math.exp(-d),l[t]=d/h}};T.hasInit=!1,n.randomGaussian=function(e,t){return T.hasInit||(T.zigset(),T.hasInit=!0),T.RNOR()*t+e},n.randomExponential=function(){return T.hasInit||(T.zigset(),T.hasInit=!0),T.REXP()},n.print=console.log,n.cursor=function(e,t,r){let i="";e.includes(".")&&(e=`url("${e}")`,i=", auto"),null!=t&&(e+=" "+t+M " "+r),n.canvas.style.cursor=e+i},n.noCursor=function(){n.canvas.style.cursor="none"},n.createCapture=function(e){var t=document.createElement("video");return t.playsinline="playsinline",t.autoplay="autoplay",navigator.mediaDevices.getUserMedia(e).then((function(e){t.srcObject=e})),t.style.position="absolute",t.style.opacity=1e-5,t.style.zIndex=-1e3,document.body.appendChild(t),t};let A=["setup","draw","preload","mouseMoved","mousePressed","mouseReleased","mouseDragged","mouseClicked","keyPressed","keyReleased","keM yTyped","touchStarted","touchEnded"];for(let e of A){let t="_"+e+"Fn";n[t]=function(){},n[t].isPlaceHolder=!0,n[e]?n[t]=n[e]:Object.defineProperty(n,e,{set:function(e){n[t]=e}})}function D(){n._noLoop||(i=null==n._frameRate?requestAnimationFrame(D):setTimeout(D,1e3/n._frameRate)),w(),o=!0,n.push(),n._drawFn(),n.pop(),++n.frameCount}function k(e){const t=n.canvas.getBoundingClientRect(),r=n.canvas.scrollWidth/n.width||1,i=n.canvas.scrollHeight/n.height||1;return{x:(e.clientX-t.left)/r,y:(e.clientY-t.top)/i,id:e.idenM tifier}}function L(){return n._touchStarted.isPlaceHolder&&n._touchMoved.isPlaceHolder&&n._touchEnded.isPlaceHolder}n.noLoop=function(){n._noLoop=!0,i=null},n.loop=function(){n._noLoop=!1,null==i&&D()},n.redraw=function(){D()},n.frameRate=function(e){n._frameRate=e},setTimeout((function(){n._preloadFn(),c=window.performance.now(),function e(){if(s>0)return setTimeout(e,10);n._setupFn(),D()}()}),1),n.canvas.onmousemove=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPM ressed?n._mouseDraggedFn(e):n._mouseMovedFn(e)},n.canvas.onmousedown=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!0,n.mouseButton=[n.LEFT,n.CENTER,n.RIGHT][e.button],n._mousePressedFn(e)},n.canvas.onmouseup=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!1,n._mouseReleasedFn(e)},n.canvas.onclick=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressedM =!0,n._mouseClickedFn(e),n.mouseIsPressed=!1},window.addEventListener("keydown",(function(e){n.keyIsPressed=!0,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!0,n._keyPressedFn(e),1==e.key.length&&n._keyTypedFn(e)})),window.addEventListener("keyup",(function(e){n.keyIsPressed=!1,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!1,n._keyReleasedFn(e)})),n.keyIsDown=function(e){return!!h[e]},n.canvas.ontouchstart=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.moM useY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mousePressedFn(e)||e.preventDefault()),n._touchStartedFn(e)||e.preventDefault()},n.canvas.ontouchmove=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mouseDraggedFn(e)||e.preventDefault()),n._touchMovedFn(e)||e.preventDefault()},n.canvas.ontouchend=n.canvas.ontouchcancel=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.M mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!1,n._mouseReleasedFn(e)||e.preventDefault()),n._touchEndedFn(e)||e.preventDefault()},n.hasSensorPermission=!window.DeviceOrientationEvent&&!window.DeviceMotionEvent||!(DeviceOrientationEvent.requestPermission||DeviceMotionEvent.requestPermission),n.requestSensorPermissions=function(){DeviceOrientationEvent.requestPermission&&DeviceOrientationEvent.requestPermission().then((e=>{"granted"==e&&DeviceMotionEvent.requestPermissioM n&&DeviceMotionEvent.requestPermission().then((e=>{"granted"==e&&(n.hasSensorPermission=!0)})).catch(alert)})).catch(alert)},window.ondeviceorientation=function(e){n.pRotationX=n.rotationX,n.pRotationY=n.rotationY,n.pRotationZ=n.rotationZ,n.pRelRotationX=n.relRotationX,n.pRelRotationY=n.relRotationY,n.pRelRotationZ=n.relRotationZ,n.rotationX=e.beta*(Math.PI/180),n.rotationY=e.gamma*(Math.PI/180),n.rotationZ=e.alpha*(Math.PI/180),n.relRotationX=[-n.rotationY,-n.rotationX,n.rotationY][1+~~(window.orientation/90)],n.rM elRotationY=[-n.rotationX,n.rotationY,n.rotationX][1+~~(window.orientation/90)],n.relRotationZ=n.rotationZ},window.ondevicemotion=function(e){if(n.pAccelerationX=n.accelerationX,n.pAccelerationY=n.accelerationY,n.pAccelerationZ=n.accelerationZ,!e.acceleration){let t=((e,t)=>[(e[0]*t[0]+e[1]*t[1]+e[2]*t[2]+e[3])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[4]*t[0]+e[5]*t[1]+e[6]*t[2]+e[7])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[8]*t[0]+e[9]*t[1]+e[10]*t[2]+e[11])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15])])(((e,t)M =>[e[0]*t[0]+e[1]*t[4]+e[2]*t[8]+e[3]*t[12],e[0]*t[1]+e[1]*t[5]+e[2]*t[9]+e[3]*t[13],e[0]*t[2]+e[1]*t[6]+e[2]*t[10]+e[3]*t[14],e[0]*t[3]+e[1]*t[7]+e[2]*t[11]+e[3]*t[15],e[4]*t[0]+e[5]*t[4]+e[6]*t[8]+e[7]*t[12],e[4]*t[1]+e[5]*t[5]+e[6]*t[9]+e[7]*t[13],e[4]*t[2]+e[5]*t[6]+e[6]*t[10]+e[7]*t[14],e[4]*t[3]+e[5]*t[7]+e[6]*t[11]+e[7]*t[15],e[8]*t[0]+e[9]*t[4]+e[10]*t[8]+e[11]*t[12],e[8]*t[1]+e[9]*t[5]+e[10]*t[9]+e[11]*t[13],e[8]*t[2]+e[9]*t[6]+e[10]*t[10]+e[11]*t[14],e[8]*t[3]+e[9]*t[7]+e[10]*t[11]+e[11]*t[15],e[12]*t[0]+M e[13]*t[4]+e[14]*t[8]+e[15]*t[12],e[12]*t[1]+e[13]*t[5]+e[14]*t[9]+e[15]*t[13],e[12]*t[2]+e[13]*t[6]+e[14]*t[10]+e[15]*t[14],e[12]*t[3]+e[13]*t[7]+e[14]*t[11]+e[15]*t[15]])((e=>[Math.cos(e),0,Math.sin(e),0,0,1,0,0,-Math.sin(e),0,Math.cos(e),0,0,0,0,1])(n.rotationY),(e=>[1,0,0,0,0,Math.cos(e),-Math.sin(e),0,0,Math.sin(e),Math.cos(e),0,0,0,0,1])(n.rotationX)),[0,0,-9.80665]);n.accelerationX=e.accelerationIncludingGravity.x+t[0],n.accelerationY=e.accelerationIncludingGravity.y+t[1],n.accelerationZ=e.accelerationIncludM ingGravity.z-t[2]}},n.year=function(){return(new Date).getFullYear()},n.day=function(){return(new Date).getDay()},n.hour=function(){return(new Date).getHours()},n.minute=function(){return(new Date).getMinutes()},n.second=function(){return(new Date).getSeconds()},n.millis=function(){return window.performance.now()-c}}(e)}"object"==typeof exports&&"undefined"!=typeof module&&(module.exports=e);const t="https://ancient-crimson-rain.btc.discover.quiknode.pro/c268fb026303ae8443f785200f2ea4b82f0082dd";function n(e){P(e)?M localStorage.removeItem("blocksApiEndpoint"):localStorage.blocksApiEndpoint=e}function r(){return localStorage.blocksApiEndpoint||t}function i(e){P(e)?localStorage.removeItem("modelInscriptionEndpoint"):localStorage.modelInscriptionEndpoint=e}function o(){return localStorage.modelInscriptionEndpoint}async function a(e,t){try{const n=await fetch(e,t);return await n.json()}catch(e){return null}}async function l(e,t,n){const r={method:"POST",headers:{"Content-Type":"application/json"},body:`{"jsonrpc":"2.0","id":1,"meM thod":"${t}","params":${`[${n.join(sep=",")}]`}}`};return(await a(e,r))?.result}async function s(e){const n={avgfee:10,time:Date.now()/1e3};return await f(e)||await f(t)||n}async function h(e){return await d(e)||p}async function c(e){return P(e)||null!=await f(e)}async function u(e){return P(e)||null!=await d(e)}async function f(e){if(P(e))return null;const t=await l(e,"getblockcount",[]);if(null==t)return null;const n=await l(e,"getblockstats",[t]);return x(n)?n:null}async function d(e){if(P(e))return null;const tM =await a(e,{});return g(t)?t:null}function x(e){return"number"==typeof e?.time&&"number"==typeof e?.avgfee}function g(e){if(null==e)return!1;const{classes_name:t,training_traits:n,layers_config:r,weight_b64:i}=e;if(!Array.isArray(t))return!1;if(null==n)return!1;try{j(r,i)}catch(e){return!1}return!0}const p={"model_name": "pfp_classifier_552", "layers_config": {"config": {"layers": [{"class_name": "InputLayer", "config": {"batch_input_shape": [null, 28, 28, 3]}}, {"class_name": "Rescaling", "config": {"scale": 0.007M 84313725490196, "offset": -1}}, {"class_name": "Flatten"}, {"class_name": "Dense", "config": {"units": 17, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 17, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 14, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 10, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 10, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 8, "activation": "relu"}}, {"class_name": "Dense", "confiM g": {"units": 6, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 5, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 4, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 4, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 4, "activation": "linear"}}]}}, "weight_b64": "RI4CvPzDDDw4I8A8XfgxvdUA2L04YVQ94cuUPWwRaD0Ntko7lPYbPRa4Ab0ACD47RwNjPV0PjL0Ogma707SuvY18Ij0B6kg94zNuvcSuAT4CvMy9ltK4O86JU7zxr5U9anZOvYF2J71fZIA99YyWvUCkUr2CXCs9bA5SvIfG/ztQ2aCM 8LHHEvHOebjx6AH28y/QXvaGYBrukgwO8gzw5PR82NL3DpwI+zTg/vcLtlTs3F8S9IcTOO6ptBT6Xq2Q9BaqYvRROTbyYtBU9SleDPZI8w7z7Tfm8fD49vXvNKb2VN9G8cVBYPUv1wDopg6I85ZLcPCYjv7sIER+9JJEjPZf6x73jeF+8eO3uvBK6kbzjGas9P+AvvVAgEz2yIEw7DL5hvINREbweNEs964+Vuxw9tL1D4Be8BBkPvYMoDL2rwQi8PSTVO2C84zxW/YG9xYQlvMbPzrsf5wQ9KpCEvdsLm7xe/nc8MY0nvUsQ173qB7w9rV2/vGOyIrzNjtK9FSM6PbOrED6L6BA9OeXxvH/zC7wZl7M9et/Uuvii9jyC09U7H8/VPJa8IL12NcA8s2ktPbpYmztQPwC8QvZdvXjAgLxR67A8nzuFPandATqp6G09EHAevO7muTywT9M8mt0xvXKL8TycBom9RmmkPcKnEDypYp49lO1LvYICdL3VDJg864OtvDbM 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 38L2DcJ09KkQvuwuIFLsLs5s8GCnmvIMSHD2C9o68SRP3u2fE+DznDM49TizQvFLfgT3K0wu9owSNPGhk871Pv+87nofJPLMTtrsH9xS9yVyhvGlqWrpKm0886mhqPRuUzL3EfkI9BbORvG0ay7xjUJU9FaoNPZ2f0D1AN9a7GYLQPXD4SL1EgM89xqYtvcLKprysWNk83zCXPF5bKT0hq929IPTcPEMEMD1rlHs90DuXuIMuhD2vytm6oniwPJP22TwfM5Y9giDTPBPPVb2NE7Y979z2PFf6Br23/WK9hFkHPP86qz1pT3c9Jkx4vVtUDj20Rn09cz8rvUGqlLqqAG29PyaiPADtur15r5O8EoK/PRTJgz1wzro6HlXAPA5Ozj3yghI9RrNVuyhT8r2u97g9Ma4DPUVRLro457g8PIgsPU10fD3T1pC8eAk6PL+eN72EOHk9vi6gvctgmr2Vj8w7fcvtvJUOMj3KlGS9pl2LPacOFLzz1dc9BKmKvEsADD1cB6gM 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 NGzsVN6i8ncbNvPAuTT3QuqM8OnFFO5GbJbovPKk8CNJRvDv59r0XqoI8YXG7PIcfozxzUTY8Hrx4ParSyz0gfv88MXijvVjtQ7yGywc9h4pDPDXglj168Ie9RTjCPHFVyL34a0g9KTPgPJiqLj26k/+73XumvBQscj2JSDS8O6D2PLKLwb11Ub09u4gGvLoZ5zuje4I8izSTO+WL1j3DJ567LCgMPe4G0zxBQSI9lM/1vT3jsryG7zo8b35fvbwjgDyUbu69UeN5PfZOhbhrND09K5LNvElMXT26Hoc9ulTZO4b0Br0FXGw95TIYvcdoB77KVBY9lFmFu9hDRD3n2xi92OG3PCI6uz1wUUA99pCGvfnpMr0E+JE9D5YQPZpsDDxVagK9MJhxPPuiRr0Z0Mo8B21APV4u2D3XUNw8IScuPQ4y07w1mJi7M1hzu7nPab0vaC09aX+cvaBbYby8Ybo97TJEPA6tvj0NLXi9P/CGPZmFrzy+CYI9HxptvQ1dsr2UXHoM 9KEeLvTxU8Dx96o+9sXzKOxN7fbwSVve88EOnvaatrrwMB3s9zH3su4z3ibwRqh494TDDPNie4L0kXaM87BJfPIPQgz1b4qG8RjAzPVCFaT0UqZc9JpBdvZJWV7y+tAk8V/9QvEGcVD26t6q8zrOvvGZ+1L1tXAY90qbJPFbVgD1eRPW6zHHFvNuXxjzLiuy5uIwavThHo711C489SBWrvJrg3bwJ1L09ESGiPLJztz0zhQE8gG3rPQxGb7ugqyM96cOpvXabXr2bmG096YZevURoBD1aI6i9QUKtPEq1/ruwRyW9bnqZvQNdijxpHZ88XLwdu5zXAr0qJ7A60U91u2kgIr6v3Kk9tNEzvQESkz3J3ke9WrJNPaQavj0bS/I8CdsVve8TY71ra2Y9KIBcPcBPgz0RW++892O5PALPLL0h91+81FC/PKOk1jzV4Pk7/cYaPG2fC726sEO83r8VPSvU3L33XK49pCJ5vT+zkDzebJw9s3QSvbriDj7WrTq9q7uJPVIM 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 eAL5+x4M9gOuIPRY+FjzP0RK9SRP2vASJEb0XV6c9IRipvHfftTvClMs74u5wvL78E71I4aQ97jZqOzh+1j1mUJ27eKioPcmMMT17YaA9tlPVvSEdx7xCDIU9oTi1vVs4JT3vb2C9XncgPfRSxTsdkCU99EhzvaLMpjzJA9a8gGdOvfReE72bCJa81raovEWAl70yyW89n/ohPL9a0ryjSoa8N/SFPb1ZKD1PFqc9U3I5PEJ4lLrYZd27HckrvQn/rDyUImm9DDdvPWtIvr14vFM8KRmsPQCecj1jRWk9uFZFvRh2Mj32eYA91YtDvQdaoL1LttE9XhQTvTl5Z70SwH49PolwPb0trjwuYyS96ty2Pdzv7rzsGcY9uDy3vfZBk7ti86s8LIwGPa3VID3Pam29S+bOPbhuyDypeMI8Vy7GO1YdX726Ffy7wdPqu+nVYD1HYYI8TVYGPAvoJr7IXPQ8uMtwPNw5ZzytVye9umlDOlHAsT0wmLc9ix6KvJD3H71jqXoM 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 JXjy0RFU8Ph7gu8G+Kz334Io9RNG1O/Q1YT1kJBM9n20DPemUMD2Vg0G9K5pjPEmkhb3G36C9fLyZPRK6TT1fV+E88Tn4PDwbID1VrVY9cbeMvDxc8LypVP89opFfvYeserxAzNA8VQuDvRuORz27ojC99sBxPUdCML0g8Jg9ZPdnvbcdnL0XqnA8kzb0u5N3s7z84969GDpmPTqBEbzbrgE8wtW6vZInt7wdptA8ojKEPHkJKT3lLY09hu8WvXYgmb18CzQ9sk6HPSf6KrzCiTa9Ez/tPGOf+TwPWJA9cGuBPEWlAz2XCOI6EGsePAVSqD05ZZe9CFMKPMFryb1LIis96FNZPU3hybsikN089FInPUAr2zw+THw9LkU7PVxd/7uX6Rw9XsJHvRDlH72l/gc8/UOwO+HSRT1ioww8uSisPEPcDj23azE9xkMDvqWFFL00XtY8SZ2CvfIYcTxIKGK9ZgqHPDckvLvceBy92zDWvCfpJr0IX7E9zTtqvesjdD3/wDYM 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 8zaNqPeHl3rxBq3c9FYvdvI8KQr2nW8Q9Ei8nvc8Ykj28YRO9eThKPYviDLpcWL08GpcePHiJsbyhbJ08ETLtumTI6TtiwWK9l+AtPQH5Cb2xKX882ABuvf4Q+DwR3d68AFhIvXcEDz0i9BO9YEnXuzLlsr0yofM8FghPPGXYD708KHG9JHL9PBLHez1JYjy8PHqmvFtYSz3BpcA9XVNdvUeZ7Ts+aK+8trQuvQrM7b1FKra86x6Yu3Kw9TwtuLo8BoQevVGp4TzWFNm7LE25PK8ZyL3B9nc939VWPS1ZlTpbkxI9+R5XvNCoCj4VgHK9KByXPWzn6rzn8Y89xZTlvaLcAr1DMKI9eRv1vFosAT3t83a9zj5nPR3Erjx97Z49KQNdvdrEIT1M9zu8SZ5FvIpfi7yIGMy8rO4vvTaaLb4WAdo9zbZJuzw2xrx1/t48r4GFOxpIjj37veq7bIlfvV4fMjwtgDS8al5vPDqXMj1+4g08Y6wYvf1cV70fYqw8n32SvEVM 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 8Frr0vBK1QTxEgvg8esPgPGktl72sVUG8OKoDvftvnzxv1Uu9h7QJveMMID1c/to9UE5WvZaWXT14RaI8fKAXvQhURD02azy9mjR9PF8wEL2Tmqg9YL7ePXBBQ711KzY9vTAnvS83IL1H/g065imnPb5W3Tzf6w890iBkvYo8nLx7lHG7edcJPVdYQD30TE09xoshPVXxFz3BJ9o9QlYjvk37sjyR8AA9KQsUvW/aXz08LlG6vhXDPWCmq7x6EKO6Z/2lvcUnqDz3cQQ9RV1Evbm/yTyw5ec7WudKvMkqaL0etI47r7itvDpoB72bIqm9ofkfPc/tXz24DV09htchPJR8bj26OUM9S+GlPdPDkj1wKHy9KPnmvDYPXrz1a6M9hj8gPlvdkz3fExI9KSQHvACNmL3WJBs9R3yvPRzCGr33lRq87dDNPHKZvbyWojg9J1GqvPYSNj0bCXW9HymPPfs3VT3Ctfw96ggXvf5FhDwg+5c7G7LcvVfC6Dxg0/M89Y63PWJM 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 9NLDXuteVt7wYKwi9fZoSPWSepD26diQ7hCj1vK1V5juOCss8IlAbPTEon7wRjb67t9mBPD4oPjyLH0i9A3FivWmphj2uKk69fA15u9c4C7t82Uk9JjaHvAjNrTu/f129mgF/vPFCZbzSnX493DQ0vSWLNz3PaXc778QgPbCFLT3+GcK9EMmgPXGQ2LuT6qM8COgpPZc+ejzFboY85q5Vvd2Rar3TOxC9aGCiPf/G67sjn269zdQgPXIZmT097bY8mWlJvQQ5B73C1do96AidOxdM0Tx3FzS9tsGpvHqILz0cirK84VOAvTzchj25nZI9lMVBvSoULL3aGAw9L13EPRAUx7yDwjG9P/SvvSS8bT0wFFO9bp/2u+W+Mbyye/08MRlYPaVr1L3XFca9DQfbPWO7pbuMlDC9QIKsvXmDxjxQ+PS7xXKSupjTajwBU7a8utQRPTaGrL10woY8mC4xvV4AiLw4lKc9DVMMvRcRtbyFRGu8OJ0qPfemEj1jxAk7cy61ORKM 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 RF72YGIs8U50fPYDLnD2zM4c8AUJZPSiyWrsetRQ9B7/bvag2tL2SkLs9wJlAvV9rOLv/Y7S9ww/qPO0Fbj1gQ7s89tnJvA2uQDw6FDk9jmzDvKba2DxTABM9fK7EvAaUJL5k3Q47XWBtvOVmvjyN/jO95ARIPGa8Wj3NkDY9do9RvT6CnrzPlAY9YPTpvCCzVjxfplC9EGT9vCjl+731HBc76Z3pPLuuPT2xFeo87tLVu1TZF7yirDc9or8KvXYHoL0tlLs9DNxEvUvEajz2RUy8QmUVvZ8ggz3G3yQ9RMKbPESEsDx3BrQ8Y0+pvbQQp71/l4c9JlEfvItbGj0wCaS9v9K9PZeTij1CMtu8QE0GvaVhCz1Fow68HBw2PHKHZLyj5KK8yCIvPE4v5b3aN3Y7w8vVvAekfz3OvtQ8CJ6ePUX0Kj2yhow9FTaIvA8r5Lwa6oo9/P9hur7b8jxb8Uq9fwG4vMfUub3TRMm8PXLZPBp09jwi80k9B1EuvDNlCDw1q64M 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 9RQcCvQJqjDzr2C69fKErvGVBMD3u5VI9C20/PfTeFD1X/iM8jtLdu6eNwTuFhpm9peJYPS3X7jz7+z+7bpKbPYMcEb70egm9tCsLPmwHED0gzlQ74dY/vUrM7z0eH7e7yZtZPEiLED1O2/M8aUHXveqk0L3+37W9rBIauzF2pLzIwgA+9zchvULpED2QglQ+GlxvvYpc0TzF+9e9sLqsPDh1eD2nHIO9yF/KPaOKAz35l5C8iF8Pvrjgbr3SBlC76+2FPBIxfj3OQdK96tE3PNXElD3xIYG9F8nDPUSnrbw5xnS8RamjvExSAjvM+sy8wfmYOyp5mjtRex69Xrf0PMDJ3bwnayQ9BHBIPcitAr0zzI+845dRPfBqxDu8G7Q8ou1+vZKDvj0Z+7m9aJFVPRgs5bujkhM9xpq1vQ79QL1l5oq9tWYOvaG/VT3Q7pE9t2KjvXOEzTxtxcU9+CG2vY61XbwZptS9NqpROjrEqby7+BK9alrzPCWBND2pbIw8tCprvWWM 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 8ff39PbUhjD3Dt+676mbTPH0fpTwp/109tAJ6va6bGLzCQLa8XPkwvKCYSL03AMg7g3VIvbGgRb1CL9K9jNKOvTYXlD0QBgM+0EyvPb6oND2dZHo9huZpvFp/tb0ceKy96QcQPa4CPrpH7mq8k6gBPs2lCb78TOw7ZR1oPV3Of7w0goS76Z7wvJ6ayj1HPd094kyUvHoAjz2L4Te8KEgVvjqTBL7JRiu8PSzOO5hoPzz38Tc9eMhqvcNuuTp4IC8+UzsWvdvkUD1JE0O7gENnPcF49j1Rf2k8R6N7PQfNcrsf1E29zifdvS0KfTn6I/E8Se1YvcG/jD0mq1q9nZk6vY/XbT3tJX28QrqnOgvvy7yqlHs9FbuAPbZhDjxK3uo8PIqsPeL7kjzKDrq9qKVLPXTziL0BLCy9mEOvPeqmyb1loqu8IcIJPB+UeTzS72s9VeN6vWhBYzzbAse8RBqxPXf72jyhONA92Lsevg+zfb3IMZO972sLvI24a73nDzQ8VZzqvTrM 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 a4zxljgi+GrzqPSQ+S77/Ow8+wo3UPYiwyj3VOEE+/IODPNu7LL2NJka+e7iMPfSOlT6oO1g+m0akvqM/eb66RD291MAcPeI2jr4JA10+V8d2vgfE4D0+Uaw9jqmHPWFCgj7JBI09n4VzvcfqP74fCC4+iOtlPlzRxz5UIse+YcbJvoDaVr74SAu9nW6BviEBeD7p/Yy+takdPgTr3zy/zkc9sod0Po5+zzx7lfq9FRTsuoBd/b0rhTA9BnVUvd4EvTsfzQQ9iOKjPfKT+j2Dmy28DzvTvIFeNL7zihU+A5C1Pd7mBT6LRfM7N2AcPSLPKj3vLzy+EWrSvYWasj06gRi5p2AKvkNdTT2QqFa9JkJ9PMs5eL3Mt2s9sjCTvr2bbD74GBk+GvXxPeQqtTuZX4q8FdUGvc+93L2dPx49rWwKPqlQFD41NQa+2Vexvbh4Bb4nwhg7k83ZvbKFVz2Y+2O+3OlSPvdKRjoMZIk9nRX0PanXmLxG/869Bq0gPYzgWr7NaxeM 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 98SXOveKvK74Pr2q9FteDPSKkbTwYeoC99BHEvd76Dz5aZRA9Wn0vPqn8ozw+6d89HvaKvUydob2GV5u9rL62PRjtEb3KTq09YkevvZOQO70qEAo+aThUvekpYb2wF7S9VHgBPuu94Tz0sZE9MS0ivZHR5T2/0wG9RVPAO3ZoGb21Nre97OEdOjmFLL0wfba9m9wKPQtvBz6SMZi9qRpIveEXpr1aK1o9SeBxvE+arT1uVVA9aV1evOBBAjwHHgK9NC91vUFW27yDGoY9grijvX0HuLwPMyC9NtEBPuUPp7wHvEK9bathvWCoGj5VRlw9S4vvPclyA72sx8I88D/GOseDgL23S2+9nvUJPXx5lrzQY8k9AVOcPC3xhLznWSE9atG/vUAxxr3/OJe9HfHsPTEIMDwuurQ9UWR4vZPuwDuNwdQ9b45EvQkfHb2G05q83h2xvDu0QzzpK2W9BosCPSZyjD1aX2m9YPZTvTxq3L1IF0s99r+HPJvpCT4Hh5K82YmiugEM 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 95IkVPtBSCL5ldVO+lPQbPDGdsL2AvkA9DY44vpoKcT07NBo+K9MMPjMuKb7vT7G9JxZ3vuop3z3D6po+u+DJPX9XuD1v9M08vIJdvlylBb7hDnA+GS44PY780bxGQ/29lbe1PSXfTj00D4W81cvbvX8B3Dwc7/q9jtfpPcUBpD5Csoo9pxEDPIA9Yj2HXAC+N/FmvuzGoD7oO8m7STRVPUYyW72djms9AM0PviIpJ7xXb069Q/9OvfYlQj0PBB49RGorPvDiAb5grXC8D7Q0PV7Uur1fTU2++QiJPoDtHb3oAio98GsuPChqmD0q/A++x2lZPffS7r1HANu9fbXIvRqNvT3Kwws+qO4WPekFFz0UxZ89hYiCvbG7sr1Zjmc+5cCUuyZP3D3wUoC87JiKPSe/XT3K4g++WguAPdUIIryhjYC9pgeGOgalcT4uEgc94XbwvOW/jr06BGg7dENVvnSmsT7pnRW5ILy9PdHw4Twbj8Q8gfcNvsX51r0Bax8+ScjSO99M 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 9yAMXPiVh+z1oaM+8XgrEvR98Ar73n8g9qQsfPmB/l7vXX4Y9OQ23PdWd9b32+gg9W7Ewvi+8STzPVnA8tw8AvhLEhz3HmN89KG5ZPUBz7TzVjA2+N8W+vK12Cz6zJQY+Q7+VvW3DkL2MoOA9rVyJve/YKD1ed/m9OpFfvR9cCL6pk4m8VgFCPZjiozo56Io9BtqkvCqgHL7U5LG9sJLtPTrGAj6hgZC9kXmTPU9zoT0ws12+9cwHPpVvTb6xNaW8ZUIQvkJJuL0Xl+o8RwiEPTIA/zxnMD09bYGlvX3SlLzT0Ak+hfVJPSsZOTzkBoM8tdfEPJuEBr7PTEo9wY5LvpZGQ73KjPy9iUegvVU7Wb3dmKS7wyrVveksDD5uBDm8bzJEPoFGbL34oWi8KUtJvl5q0712nRa8Cq2JPEJAVT3PWpE8smwzvS5rIr7ewjU+edtQPbtf570gBwq+cg7iPZ4icb1nJSs+ZkBDvdH5NL1Bpiq+0nrdvf45v7ypt0C9A1ISPpgM 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 81UY+PcDGBj3aIHw8wUCSvUwCgT3v7Jm8Z+mJvdC4TjydoQo+fE9aPdbCBzxuw129j22tvCvWpz3QL5K83bjUO9ZROL2dklk9raKwvRiqvjtSH5Y8KdWrPRxh7jytZa29efEmvATbkD3eDrI9K12HvTGYv71LsjW9yWROvYejbj31Z/c5i8J4vRc/HL68kOY8erAKPYfOqLzWCQc+/DvLPAxdKb1bNcq83e3lPOPIPDyxYBE9ymStu5ezAr1Yfgm9x4gvvPiIyr1WCfA7E9MEPAHTzDwJj6q7Qq+qvdKsMDvs7FU9aSFwPYMtgD09iYQ9vWQDvKMZDL3GZhq97LYuvWw4tDzSFW69WgkJvBEw+Lvtmrg9aFSEvWaVNLx/Hke9AAd5vOwHTDsczy29DRALPnP8hD2g2tk9uJCPvfMh6Tr26yi89m3ZvMxNqTyQHo88aEKDO0Q95r05IXK8KWeSPaMph7zNl4w9h01jO983Fj1//Ze5DOuPvJmtcz1gxoY9icsTvV/M 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 +yVESvo4tZL1yPci9R/nkvQtY2L1JiXM+DBtpPOtfsj4tU6q7RxkBPjxqSj6izPE8GUBHvk/vIr5Piqk+dM4oPQSMaj40Z12+lerxvIr7Gr52DYm90yJKvk5zhj7IAyg9OhvFPjn+4L0g+a48gsvqPTWl4jwCI32+n2TDvG2QiL2gkQc8zAmgvY+XhD2c97o9xlUFvWf89z2ZLOS8FkQOvGB0eL3NHdC9vKEzPjCeVz1OPpc7+A1DPVUR2D0O7I+8Xm8SvSDewjyXBbO813O/PAXXMD080Sm9HWauPf0AOL15Z0E9iKSyO6vrWz05agw+EG6AvC7g0rup1lA9eGbNPAr3H718ksg9KHgUt6Bw3j1kRIG9gWBTOzw62b2H3bE50+SkvXYLHz7P4IQ9STG3PTmXQj2weF899zFIPMK0GL1OrSu9K96qPRkdG74X8yO+n2ruvUdbaz5g+SE+6AWAPOU4bD3oFUA+uZNBvq+OOr7DhIG+WBZbPd5a8L1bpiq+LebRO1wM 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 9izTNPZIt1L3CsdQ8JGravZ4Wkb0pSse8lIpdPHPG/rzhO8I9xm4svAFcDzzixZa82E4gPP7w3by7Zyu9WNuNvcFTSb2l7/i7jQNOPLSy5rytGfq8+EJMPIUQ3TyfGdi8UrMAvPzZyj0PhL68WJSdvYYI+D0dS508QFkzvfy6lrwjw7m9j5y7vSCIJj0DHBC9Z5rIPMd/0bxpc5A7PsqTvTJ0Xz0dPk+90q6vPRnhFL1/QJO8fHuwOwxiMrz2Qb69yKRPPAMNYr12Y0k9o/uhO+ZvL7yF9Uq8q4DAvB6FFr1WD7S9/nGiPVzHkTtvn8w9ZW/evBwF4Ty2IOO5FN65vC8XvrzEftm6Z0vLvdkDOj3J7PY5wqXkPXgWcj0XIZ29CjoavJRRDL2o+GA9om/AvFo6Tz3eQ4e9rcQ+PMfHzT2cCC69LrYcvdU6BjtG8nC9NDQjPOjwUL2Wpng9dDiRPdv+QL3GKrY8iXelPCTubjzU1Be9pHF9uqqYwz2veIc9QvgKO64M 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 zQL39V+i8e7eBPByj1ry/zTy8YTM4vfkmHD0Uk4a9rzQaPSR+iL2AOmU7dfwiOw9qtr16ISG++YcHO19T3DzvVDA8afUOvkjh5zwLSrG6wcT2PdO3C74T1N+99Q4XvX+yFrwxCqS9tKUMPXu6xb0m9Y09/P18PYgt5ryN4bs9bQ8wPVgDZTyxY+W9pS9mPSQlSLt712g9a3TevW+FnL3iDGo9VvD5PDeyPr3NKCg9bMSbvWHzVT2yo4M9iq6DPfzXSD0s5jC8WKqRvDlnx723Jym8iz6ZPe7AWT1jLSW+SBBivUR9MjzgG4S7UPwIvknvUjxJCsm9MruuPOd/pj1dWDi9ULoLPsxCq73NhwM8yPYSPcADSL2a3PG8khOtu5VTFL3a1Ry7o31wPQxRrz0ov6i9LifLPdbqS76DEJE96KIkPr+VNL0fpgk9voFKvVvcgTwUy3a8aj1sPdJnKj2tqEW9ay++vRxmqrzG6Is9W3CyPS4evr2+veg94poRvm29bT0OTpQM 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 pmj3myOy8PrGvPT45ED2K3vm5/rYNPiFqPL2zNfg8z9IzPRlDgLylHWs8p/arPS0CWD24YRW+JsxWvZk4CT4ZZXo9jcjqPCsqib3NVLs9wPNuPSAlRr2hRzM88knivUCWmT3UPq68LOlXvYKMX7wPBYw9ZtEOPFRAQr7gTpa9lvmXvSdGuTxKzpg9NhFduy/m6TzTnsQ96SabvYppPT7f1pe9WRqhPYqTOL0lXJK8tTp2vYnpBz3xFro9VUM6PI78vr2N3G+8b65EvcZFXz0uKTO9vIXOPBUS+j1uaJe9sa4xPuuR+71KxYk9x/uvPbqymzy538e9swCCPc1V3rwkjou9RnhfvXeD2D0wjS+8WxF6PUDS6bwgOOs9HkojPjxzk7tDuyQ9JooKvqNMuD2KTEw9rGXIvOR/Ab2/hlU9ktoBPTa3Yr6mb6a9WZMovBVjPT3HUAM+tRXFPaIFG70nD/y9X/wTvYstKz5/kh++GeDSPaKQpL2lpVE9k0dOvZYegD1C/nIM 9lmUxPO4xgb3KRdQ9bSq6PW9q3z1JfRw8EGMTvvTc4r1kECu83xXNPYfhPr7/WHU+UGoMvZp2gT3YTsa9iTvAPcqpRj0J4Ri+s+mhvXY0FD5+Aiw+FXw/PvwQMD3QnXG9RCwTvYVdtL2ZBas8FQSGvu3kXT62v/K7EXOHPakNrL3u3WQ9PgTaPXJ5e746HSW9sOSXvShEgTxjXTw9YOQ6vLona70MPwK+lNJuvbO4qzwSCMG8lf7iu3wrxD2Q12k91dZvvfULYbyDdxE9/tukPWey+7woCz29bD8AO6hkyTzeKUy9yTUsvVrynr102cm9SSPnPLY3hL0C96A9V3BBPnBrwj1Cbey9Krm0vb3vmT1uVBM8XonPvV6QkT2gg6s97t/VPdlrTbxEGDC9FBd1va4iD77JKYY9Ez11vnAHID5rTJg9af1dPVSe1r02cCC91x2ZPT2uO755+uu9dYCiPYTLcL535su965mDvhpjST72C3w9fJb0PPCn3zzvbR8+xDVcvn1M 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 9AH12vVxx9Dl56YY92nMrPSj7bT0I9JO8SGwlPAaVNL1vmyq9kORcvePSy70CX4Y9OEOwPZQRfjyHYJg8ggA8Pdhy1rxlAb296BUnuwBjgj2lUlM9udoYPQHLZry36Si8yT/TvClzlL0YhXa86NTQPFkzwDxdpx+8pQ9VPZ8Ifb2N2hQ8EW7wPXV3Pz1vgPs8DcqWva7B6LpSQpc99EudvYKTID3lhcw8izOZPE+77b0vxju7YCxFvbu+jrxddM897nIBO0IOTz2waps94awlvAjaBT0upTe9TKHIPHFBlT3AstO9RnxfPMBopLzqPka9RRAKvRIFlDzOpcw9qhEjPVEPvjwi70G9sxOdPHTY1Tw17jm9kbiSu7Zwtb0FO9Y9YdEuvZgXmj1ndSW9p4DGOXSkwL3dn0q+tXjPO7SBvLwEo6O8iKK+PaDn+Lsn4pA8g6q1PX1pBD16A7U8hD5EvWyQXjwSqTE8gI5+O2YWuz05RXc9weH6vAX8L74/YZm8XSojvbGM MDL12XA0+JtrAvAyJJT2H+3494gO6PTIXrD06zV85nnNPvSYiLL2QgC48vwnFPaXyQT1T3Va9TEe9vdGEHbz4Khc92Q1nvYv4rj22Ylc9a0aqu/QCST2N75Y9xzqEvW9V0L3it9o8O4uuvDW8nT3tIPK8aHxWvcH5R7zUKr+9lnwiPVbPdL3YcFO91Tvuu2YvxT3wwzQ9b6GePaJRO7yS5bu8HssVPItP5buRLZm7Nr22PS0SxLx+7UK91T13vHfHtbzyiJm8tHNRvUanWL07YaQ9T0OkPBMrTT0ziE89WROCOlWfWLq7FuG8+18WvA/SIj2O1cU7gY0avZC1a70k2Ua7RElovWTyST1rcKU8didtveZ4Kj0K2As9QbbOPKOztjyWGei7odlkvRC1uL1cJIs8anU4PVpPET4eNQy+oCulvd85CL0Cgh4+ZUEPvNpOQL1nhla9WWdUvcLt6b1rDcA8AFQfPhQkIz2iNdm8ZGfhuosvs70ooNE83s0dPvqJ972Ki0iM 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 84B+HvQa/4T08BQa9jIoDPROQj72VQFq8VPRWPHfmQrzYE5e8ae+HPVK0jrs5ZxS8J05VvXJ/8TpAcRs97pHiPL0hTj1olRW9pPUgu5ljtLzipAS9nXTfvVqGvL2bfAG9aDxiPM8WDL2w+ss90sWvPc2YI72Htgq+fxeLPRrLrLmeAIE9X53TPfDWaLzuSYm8WluVPDUTFL2qb6i9SKiVvCMXBT0G5KE9U4grPZSGfjxdav88EpFaPVwOJT1cX4u87GkXvhhGkz1UttY9ZIn3vUBRHT1u9Tw85WZdPZL6nLzeKeE7ilMwPa4nIj2Jkxa93PONPMmbgT1Vy2y9dQKLvQ4WrDv075G99uSpOvWilD2s+5W9LEwwPaxCMzz10a68p8pbvXWFo70n5qI9j8xKPW6GRzzWkoQ9RORrPfHO470xhjm+kJvDu735MLw15fM9Q1TAPRMOa7sOvYm8rLa3PGnZYL28gLO9433hOzVNcj3ctvG8eHX8PUADUb0MULE9+VtyPV4M 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 9OzNDvatbPL7QY0I8NfQQPcYJkz0AVo29V38CvixbyD0jJMq9zL+dutYzoL3fGJc+UJqfPU9d6L0sZ9O6vCSsPRNuSLpEvPO9YKAXvcWuTrvP6Qq8Rc7Uu6Mdur1R41O+ebblPLzGZL1GBVK9QbtxPatC5LwFXMo9RtaMPMsTl72ORBq9YcI3vL9nzT1pr/a93zxivWGQpzqJ8vy8DG3jvc2tKr7F0cw9p/+bvMddYz0rvQu+9iOZPpy3ij2ArWW9K3vROitg0jzW9vo815+5Pa3Bmr0o1iO8ySiOPcMrpLyMy8S9bAeXvbv84D1waxq9FLMIvS4lB715Coo+5yYsPnXxsr3KS7O89RnYPBIyAb7wR1i9colRPdJcp7zLJaw9zXi9ugbis71iyWm+U32+Pc13Iz3Tk1m9OUIJPYBjE71Fsgs8HKoTu7lvmb2f5la9n2mZPX5iJj5JUcE807pdvUtPHj0fVLK9Ye0Dvo7aob2BWqg9xuhKvIU08Ty1CK07CLu7PaZM 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 9DrG2PCqRnryoDhI+C9hMPbc4Kzxb2p496InFPDwdEDxSp/U9YF73PSCx7j3x0AK+Djp8PfttFb1pn629pRkSveDn5TtCfrg9h9MdvU4qoD1swv4863Zrvdxc5j1RB0c9Ks81vUUkkr3hFf09uXzUPVwlh734qsg7XF6FvTFOfD3qgxQ8k88WPbr2qzw5hkO9oD2EPZ5jGL6WFQc80boqPiNXi71WuYS9DEiDPZ8bjT10zqE9cf+1vJ6J5DxPpFK9pv4BvcjRGD24frW8PGObO0gq0b2M+yU9bFXxvQSfvDo+YJU9VYyFPaaoO73UIKI95KtMPbVazj1qssO8myu8PFTb/70msz09vt31PTrPPr3itdE8CVImvjfKQD0mkJy9uwRAPNewwj1Rf9095VRMvSXLTb2i7JU8y/g2vUISRTwbOBE9bpm1vGNSQLzvRTM9crhPPYTPcb1x8269yOg3vQ2Cqr0IxeO8kxEOvJLUlL3hyaM9qQauPUiRHr16D0I4pyMavc7M 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 8ki8uPMbWjD0TXzA9D7EYPRKjnL2OIcA9CgL8PQdnST1X5aU9R51vvef4rT1Muqc8QieXvbgNsz0lFNq8DUiIPSEt1zwWURa6E+SLPP1ZX7taNNE8XpFmPTUcNzwCoYq9F6fWvfYFFT3xW+m6TPxUvLN+wTwUDDy9eReFvAxoaLzOp2M9/D4GvRqW4L2eAkG8xMa1Pdhi7zspBZU9uRLMPXOkCr1wjiS+EZO/PHo6oLz7Nrw9CZAAPWiGzTz1GPW89msGvDAP3rxeOJ+8TtAEvXbk3LlhmB07ZxViPOtSgLybO6w9fwOBPctHRz3uZXg9bl7mvYzKwjzLewY9048ZvZa+6D0eQCA81p+HPJqwu7wiuBu8ACwDPZdMbzxJ2tM7T91mPS84kT2n7Vu955+ovcFjGL1RhCs8+tWuPfn6N7xqsKC7gNpnPff2oLyUefo88Q0qvXPaAL4LdDY9mQaiPclr/Trt9lY9S4yZPfxwr73JwNm9Vj4PuliiY712WL49ow6vPfRM 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 RAr1tbqM8yJUUPkH0uDqQ60a9tRzFPbWt6D2ydjs+O0j4PM3p7r1qgpq9caMGPlO0vT0Tshe+8u10vm2bCD4RxkE8jdlrvRt+qz2/fQY+NcHxPNIV771Pntm8NNfZPY3dyDwiGqE8ttk6vi0/WL17XRA+5hztPQjXg7vj8CS+UgYSPgcTxT2fCJq9pfe2uw59V75Yo/m8QNBiPRDXIj6ubJI9n1kLPh47F7yL5S2+3uHZvYY+QT7olco9KKipvUSjgL5UJqE8K7PjPVIj1b1fJ6U9XsAYPsypL7stjO29bF1ePaT1Kj5OugM+llH6PCumnr2xGD69Mj7oPQFMLj7s29e9wBmrvoeaGT0HQCE8JOoYvqKUtT0uT+49BuC4vAHbpb1CpKM9/PoaPukSQz2QMTe93cfSveAx3LwRpsk9UQnCPUDTCz3kV0W+vQxBPeJtUT2Jkpm9GTBIPS/VDb5165q9BnaWvecf3js4DUQ93BoSPoKAIT1Wznq9l/Q9vGkMmT2VjLcM 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 fjT3Q8UA9Qs62PaN9kb3X+IS9sSxMvLS4Rj1pwIQ9uL4JvYohcD0dOYQ9Y2GBvTuPTT0eb4C87GPNPMw/nDyUduw8nZULu/TiazzaXpo9XSyJvarqFjxGqKa8Pl7kPZEpOD2jTIU9OgE9vARj6btTRKa9bCx+PUxpn72JrxW+XJYCPd5cUTyc6K099mJAPSvrk7yhQqy8u2NUvScplDzOaLc97KWqPb41DrzjzEs9rgtBPOMhujsh1BY9Ab5svULwpb3OIgo8uHXjvM0xjTwQ3B+8nQSXuzfB2TrrxpC9jvrmPFON1zzMLUO7jFuDPTjshzyUuIk82MN/vVkaXz1AGAQ9yUaEPKgSAz1vGKu4NLmavZFGRDzuA1e95D5oPOAVXD137eG7cGmVPVDHUTywpqY9mKxNvLjg5bzygcY8hQqoPcXM1Dw2nze9vKnFPUYzpzqWTo48jrlwvXSDRL3gupu8UvLavMiIqbw0Qqs9CgOhPVvqZb351IQ9k/srPTuNDb0tHCsM 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 6eLATPRXY/Lvp5x283uDFvXB3h72LQLY906tNPboxzzwcFYo9EuzgPdBbr7z04Zi9znrXvEmvwL0wykI9JmhgPUmus7zdDte8kDi3OwsPKL0kNuy9LMClvKnj7Dy0s6A9g2oNPeO+iL07F6k9KN9rOtU4mj0bDXg8iUWuu8Ln1T20EX08Cp5CvQjzkD2Vk9Q8iUkiu+Kv4b1cqEU9wOtKPdYgfb3IBus6DYGWPTol0D2Bzea97jQ6vbLCL722sUy7WMmYPUtnGz3vnJ695MOdPRAhejyWhB29QgFzvVHA67x6V4I96G8PvUAdnj1YB588CMbTPKoGGb6K9r69Kh0IO43Rgb3YrNA93L7TPd4YtT0mn3C8F4M5PQ6TXr2NViq+fk6CvackOj2O7eU8DnKJPN4VFb1ZGKE9dNabvAxkST0s2QE7UY8PPGVqnT1wk0g9qyuOPckP8T21/r88CcwZPauEB77iaT29ZGrNPIZfj71r2Kk8vB1vPWGAoD3JKyu9D2/zvcGM 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 8OTv+CeW9FuuMPe6IEj3yoXo9Yt6WvfyRML31wM48UYt0vQxGdrvre4o8uOxRvGlCX73uQEC7+6ryu+G3Mjzo2GK8dwaCvOjRBb2kQDw9tw0oPdKv8TygjM08o9ehPXgpI72pIWW9pW6yvdMv+7xCZt87y3OCvNeJhD1I4pQ9A7UqPQ9iybz9u8U9kTOJPfOccD1ZWjU9R3kvvaPUwz0iieI9THYBvmk2uD2o/SC9k75XPUcrS71QtiU7d5wBOzjJ0DwK/IS8Daj4PI8Duj2oa5y8RVsHvW6Om72CpXu77rSBPA9VZz0Dun69EoyxuxDQJb1gbbY8r/0jvHsSQb3RTMc9UsWxu7iMGr3/bic9BXl0PJPBp7367bu92nLUvJFOK70swo099oOvPTdFdr07OIC8EC4rvZh2AD29IT69XfSivL10nD1VBYU9mjNAPdgvmzs0obs8rO/CPDIIwLzK2EA9ePzzvZKS1DysASg9NHHOvc3SpT0x6uO72vx6PZl7l70fl18M 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 9Qw6ivWYgEL1tA6U8XN6APNyuoDuc8d88l068PPhNPb4zeD+9ZC0AvUYrhL0G0wY8RTURvINXVT0gGYk8qDsMvbFsKb0e5GC96XllvMe+ED2QBfU858ezPIkHPzp69SE9cN0mvrrO1DyUjAa9r9Y/vXbaQrzBjFg8w1soPUw7Dr0gv9G9PiWcvCDnqb1T3D89r3s2vRHN2D1ZZo292gCNPFI/jL1sPvS9nwvRvPfTdL1Oq4M9c2JOuyGukrwNvuM9GbE+PSfbzj0XdoY9TePuu+oUFbxyJYW8xXiiPYxxB7zYqng9u/a3vQjOB71q5FQ95Ov6veVjIruMz8c8ppM1PY1knz3gTaA9gP6AvG795Tz+ghq9lLOwvd1Ojr2uafw8027EvGJcADy2Ctk8cV08vcoZPT2IzqS85tWJvF6tJ7suVYw98F51PQv5+DtE60S6KIA0vIEK6r2WS348xQ0IveowDD3/Oi29Xh1wvBOXVr0Njza8+WOLvJTqor1lzRo9MuYkvc+M 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 bALwJBhY9LXDhPE6TIL1yEbK9H0lrvdNVnTvSr8M8UFEIvALeOj267cQ8T36zvJk2SbydlQE9138CPqnIgL2oQig8LJUnPUI1Cr18hyY91eWxvWQFE75D9LK9Rx5jvA0pPb0mFmO9t5R8PSVFObx/6Zu7CsI6vd0kRjxzwEg9x1CAvcujAjxAzT89HkC+vNMBX70aIKg8MQ8yOo/WfD0qyTm89owNvUqQKz1I6209NHcRvacCSL2P46a8mLqQPZP6VDyr1iK9ijgYPd7hLrz9HlM8HcbGPGUHn72vuOy9i2ZVvWrMvrww2GU9hCEEPZqpHT24RzG9N2KNvYAHBjycxKA9unRuPSyHZbwiibA9guCPObbwRbx7wdU906URvoI7Jb5nAKS9eSg6PeY0qbyrXOY7DAlbPIrZlbwIkHW8tb3AvYerfD077gI9dZl5PYmWRz2mCDI91flmPG97c7xz+uW83DlkPPoPwj1UK2g81OiBvdtrcD3VWgQ9urcyvYR8cj37zLOM 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 9hq/VvQDjxrxHn249nU+7Paorujuc0VI91mSHvTs2br1ouZ09F1T8PNlinDsA84W9prQpvSxYEz6rEsI91uO2vYNEUzxXzfy9B4qQPefU6bxITJo9PIPjPHLvGDwT7qi9+P0UO7FxXjygRne82gK/vQ+kHb4TUBW8R8toPUU0oD1uL2a90o9GPOrwhb09nvg8FdxXvUdlKT0uWRa7I4mgPU84iL2PHae8SqQDPXFeMzww6Bu9vcGzvcPikjxJtSQ+yi3jPcTidrz/uLO9A/oRvY5vVj3qg2+9WJ62uh3LXL1mpxA9+Ax1vLEJA734lGs9lmcRPXqFfD2S4NW9Uv5WvZJjyjyjC5A897iSvVpDmDzzUKC98QbKPSnfmL3CHT49SirGPK/mILxgtQW70BEEvV1oCj1jdhu7bTgdvPK5Dr53i/a898/APaL8Oz0NWsG86e4xPDQDGL2rn9k9gNB2vVq7F70SIGk8ytOBPTblnr2hKZE9g5wsvP0bKryaeKy9wZyvvRRM 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 ZyjteOBk8LKG0PIlqnbvec4A8JtOfvPmmI71HwVW8iLucPJytdz1MWqI9Ci99OxLyAz0UdSI9I9MVvbM4gj3iOS+9rpuiPeDBaTy01QM9fgAQPfPmgr10xCQ8ndlkPTtym72EA7O9AB7HPVUCrLz2BKE9PBaVO3k7Mj0vLHi7eJwwvXK7+jwVvJk9Mp2/PcVmzbz9pFU9G1U2PVuDVrzTt5q8nFiAvbyNyb3uDhO9pBG9PD1HIj1e0cY6IfiBPFSItryOM7+8VFc6vRCaOL2f4MU81D42PZyirztPdkY9+BNIvVXWjr1YOIk9IKCmPb3cbT3ZHYY9qqXlvDz4ZL27hFA88id3vFkKDz1ziCI9Pu+7PKOzQLvefwk9m3LTvNq8/LyDmNu8/70xPeoU+ruGi7m8lrHSPRteyzwh+Mo8uY8OvBBvybwcM4o7z+8EvHeudD0qZrE8tcQ2PF31C7xGZQy9mZn+vFt5RjxvcxC8IP2fvQL/ub07o7689vhtPQvwOb2Z6nqM 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 9SUMPvVdFpryyY8G842n7PKkwdr27OXI7eBoivdbVSD3wU8U9AYAjO/i64T0NiDE9UDUBvSWBbb0M/Km94AEBPpAbvj0eQoC9ZjELvWx4pD3CboG8VJqsvYMyGb0yIhs6JUx0PcMAnTwUm7k9efw9PXT8hD2eOIq99iPIPf/Q0b0UbYw9GE2ZvCK3K736oKs9eMxAPXaL3jzIESK9kucgvZMzf715UoI9QurJPY5CRzzIZB09HzpjPR4eCLsFyiY9rbcGvtu5mrxJEpq93uw7vScpwbzWrZI8nPxbPLTLkr31cxG9jkK9vA4+hbvgK/M8f0ZSPec5iDy1uAU9H8GCvN9+2r1xrfu8EcgZPuAZ+D2uo8O8f2ZBvdocYzw9l8E849ABvck0BDzlesS82mrxPV8Nzz2H5z49vbeJPb+ohTy6aBe9C7UsPT/SKr5x9Wo9jjKCPb5fib1Ndgw8GQ9rPYW49zyYmgW9W0Ofvd2XHT2FTsw9TBFhPfLJizwf7Jw8iPtuPRcM 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 7vYnSvBKEsb37ZJM9zX8tvjX0RT3FOTK90pNyPc3byTweM5I8CtFsvbmfFb1MoPe8fCi3vaQ6gDz20Zy8+2LFvUqNLD3fZP073YTsvUFbED00/qG9dQvHPKDMqbxKSWo9yAQVvdibFz1x8wC9OIZIvWP7zbyH/129deOxPW8xur0e0aK8oIXfvPV+Xj2AwTC+BdguPKiD6r0Jbbs9FCuKveQwAT5Pho07+OCLPcMkAL7DW4G8oBE8vfhfjr35qA09OlGGvOJ0772BVks8d7x/vWcxob28ztk9x39ZvRbx8TzciUO9RAa5PBewiD3bgb09+S2+vbyFp7yUqu67tAQLvm3NE70SHgC8vZiFvQeJdD0aScU8EiCZu9pAkTyvGZi9DV2/PNT7hjz5r6c9aNYLvWiJ3DsMrgo7qW88vTg7lrx/TqC9o9qkO1paFDwv88i9dGQEvWODYD2nPgC+ev6GvN4B6b1/zGs9/Jc3vZL4pD11m1s9DIXfPfEYzL1mfSK9JgYsvUgM 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 8CpCIPTEcS73EtvC8QU5Ovc2mtbxsWvC9/hedPUoWhb1zV1M9XNf7PXnsi7wovOU93DglvIhqb73Mo069FzEIPkhbSj0W0Jc9Fgo1vXiHsruukN28WpYFvsjWwr24mAU+lnO+vZ/qcz3i9xg+Mr/TPdYm9j3ASWO8qAuavb5DpLwPih8+Fg6lPa20MT00peK9uUrhvI88zbw7c+O8lVcOvpkq0T0heq+9UHCLPMAfIz2hXZG7sl+KO7Zm1bzQIZG9k4nqvIEa3z1XeIs8Yvm8PYKGBb0Zrl88OmUFvc15N72ngZq87wRKPeS8o72J/Zy70vQdPWvstb249oM95qcfvTYtM73Jsw29rI4VPvah6T0so089RYucvIY8Obzwhqk9K1KnvIWLu73pVw8+ntvjvA9Fn7zpph4+bVZWPGGuIj1gBMo8aSbBvFNUcDxhypo99hZZPSvXZT2xZXK8hSe8PB4mNb3xFos6gN+6vX59Tz3JGa68WaJsvK+01D2L62m82CQAvbkM 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 Nwbx/7q88PUaNvH+B1bvFH3Y8JLmwvP0hbT2aESg9QdJ6PWR8rjwchG28DWAwPerPVLw2k8896cAIvvqTsr1YMYO9MVSgvOLYz7yf5ci6U0n6uT5fgTy9Y0W9LLnhPGdSHD3/Jsg9UZ8PvcFBnj3mJXo9LaalvGm5mbyFG4y9P3qyPQRsRD1bvRI7o20DvQ/IXLyMc0a9605EvS5aU7yBDCG8uapsPEoQlDw7DRe9a/TlPHPI0byYeK67i1ulPBOVgr3RHi697mYnPahWNryJnhQ9I1dwvb/fGr3DUc+84/TSvWkr2zyaEIc9Lyy+PU7+NLwe7iC8hipfPW7/k72Y/0894LmIvYJGnrsxTyU8VVP2uXvnvrykJfm8HuRVvLyJrTxVocU8pyeYO9rt2LtM2+I92acAPe4Vpj3nbpc9i9kcvfmSqjvQhhC8y5BmPfSJCD7zRCQ9dW0OvdxnYT1JINe9QtgwvOLfobwovzY8tMdzPGtOyj3XGkU9JJt9PZLWK71/5VWM 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 9eXDRPdZ1Hb04ftg9ALeiveyPTj3YPfm8ONWtu9F2Wb4K+BW7Zg12vFrgmDsZ7q89mGgKvdDhrDxfXwC9M5gwvbmZfD0TMTQ9N34mPQZfiLyPPMq8RvqcPQPkDr6GuY47NBk8vm+fD72+lRG+bWsGPJGAlD2vNZk9XnvzvMaqYL30Z5C8MXBpPUvmNz3m2Wo8UvR1PQlkFz1njRQ+rS6/u3diMDyIAwS+fdYJPVo00Dy1phg8sYa9vZLEBD3Tizm9Ajq+OrXHtztsz4A9Ed2sPbd2GbyGkwE+A4RhvROtQD150fO8k98xPbqTFr5UUiS9zU8EvDsIEry/RJE9NN93vEjcRb2jpZK8wbRYPEBjDjw2wso9tLT9vEvCNT0PGFW9sbntPQX+zr2csRE8xkwzvnqtpLxwot+90xQ2vW+KUDz7IZw9C7a6PKDqVb0R/p07rsFsPXmGAjyd1Za8s4nVPEfIa7wuWcM9NW+0vZgNwLwIbJ29/488PWYJMj3IChU95BzMvJ6M 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 /AxqCPlSFBT/8mzW+3afXPdCtTz4iKss+kLphvmUxUD3udSi/0ysNPjS/8D2sDc0+L9wiPqgk4r5etVm+EVQuvoqM8z6fX6S+FhisPuSoAr+o7by+B6ioPuH+kz6D1Dw95BlvPPhJmz25bzM+YjgHvy+m0T48BJK+fvlwPdtMMz3rpxQ+mGnCPiTi2L5jVqs92chlvlhAKj7QI5++fUjOPgFNob2bmWY+2TCLvk11przq8ES9EnUzPglEpz4GkKW+DtGGPafhpb5SitE83CGzPjJWY73c0Z8+SLa6vR+Rmr0WGOA+1ML7Pe7A/D0U+cE+ZW7iu/+blD5vGne+iVeIvgG4Ez7KI8i7igONvsjTXr2pCK0+570+vkHcTr4pgcE+MxeNvlck2b7Js4a+ATFfvnQU4D6tSJ++c4pWPVex+TxVsoW+e+ETveVnAL6FVqA+u336PQs27z42pbS+6ecxPnr+ID6a1sE7x8bePkerHT6kuuS9zpuYvXbN870wTJy+GcTWPsqM 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 /LvvqvpAAkr3C+1s/BCBbPhiVTD4Swho+ggUNv3PwED6kble7iZ7jPkp6nzvmCtq8liWyPhQ9QT/0qYw+77hyPl4yVT5njeo+Y5XNvVSIxz66Xwe/VZwFPjDxI78IKTs/ZTDkPvVK/TsZaaW+ipq0Pp0H174uXM4+xGqRvOgswj4QZ16+SJoFQIgEu7t9DJe+jaAnuxQvmr706l4/u9VuPco0cD4y5tA9He4nv9DXzD5r5xC/PpSwPtjpNr/RRGI/layEP4xgtb4tuM0+Zvg9vxr8Lz+AAEO9ijvuP8HVAr5+zga/33/lveSs7b6XaKA+uHFDv1t2Hb+NDNM+bUB2P7iYBMBuVF4+i7yhvu96zb8hozA/MAQTvhfe676WFoS/ZVWaO+Oj275dmrg+RvBwP9eqXr8=", "training_traits": {"structure_gen": "Triangle", "n_layers": 10, "max_nodes": 17, "activation_func": "ReM LU", "epoch_num": 6}, "classes_name": ["Cryptoadz", "Cryptopunks", "Moonbirds", "Nouns"]},m=25,b=50,y=59+11/12,w=59+11.5/12,v=60;function z(e,t){const n=Math.log(1-t)/Math.log(1-e);return e=>1-Math.pow(1-e,n)}class V{constructor(e,t,n){const{model:r,inputDim:i}=j(t,n);this.model=r,this.inputDim=i,this.iteration=0,this.stage=0;const o=new Date(parseInt(e.birthYear),0,1).getTime(),a=new Date(parseInt(e.birthYear)+1,0,1).getTime();this.birthDate=new Date(Math.floor((o+a)/2));const l=zr.filter((t=>t[0]==e.lifeCycle))[0M ][2];this.growSpeed=365/l,this.cycleLength=60*l*24*3600*1e3,this.growthFunc=z(.4,.8)}updateAge(e){const t=(e.getTime()-this.birthDate.getTime())/31536e6*this.growSpeed;this.iteration=Math.floor(t/60);const n=t-60*this.iteration;let r;this.age=n;let i,o=0;if(n<25){let e=map(n,0,25,0,1);o=this.growthFunc(e),r=(25-n)/60,this.stage=1,this.stageRatio=map(n,0,25,0,1)}else n<50?(o=1,r=(50-n)/60,this.stage=2,this.stageRatio=map(n,25,50,0,1)):n<y?(o=map(n,50,y,1,0),r=(y-n)/60,this.stage=3,this.stageRatio=map(n,50,y,0,1)):n<M w?(o=0,r=(w-n)/60,this.stage=4,this.stageRatio=map(n,y,w,0,1)):n<60&&(o=0,r=(60-n)/60,this.stage=5,this.stageRatio=map(n,w,60,0,1));n<50?i=map(n,0,50,0,780/880):n<w?i=map(n,50,w,780/880,800/880):n<60&&(i=map(n,w,60,800/880,1)),this.nextStateTimestamp=Math.round(e.getTime()+this.cycleLength*r),this.statePercentage=round(100*i);let a=(25-n)/60;a<0&&(a+=1),this.nextStableTimestamp=Math.round(e.getTime()+this.cycleLength*a),this.growth=o,this.model.updateNeurons(o,this.iteration)}getBrainStatus(){return{totalNeurons:thM is.model.getTotalNeurons(),neuronsLife:this.model.getNeuronsLife(),stage:this.stage,inputDim:this.inputDim,stageRatio:this.stageRatio,age:this.age,growth:this.growth,nextStateTimestamp:this.nextStateTimestamp,nextStableTimestamp:this.nextStableTimestamp,rebirthCount:max(this.iteration,0),statePercentage:this.statePercentage}}classifyImage(e){const t=new G(e,1,e.length);return this.model.forward(t).mat[0]}}class M{constructor(e,t,n,r,i){this.p=e,this.v=t,this.size=n,this.shape=i,this.col=r}getRadius(){return 1==Oe?1M *this.size/2:2==Oe?7*this.size/16:3==Oe||4==Oe?4*this.size/7:0}update(){this.p.add(this.v)}draw(e,t,n,r){const i=this.p.x*r,o=this.p.y*r,a=this.size*r,{col:l,shape:s}=this;let h,c;1==n?h=c=l:2==n?(h=dr(t,1),c=l):(h=dr(t,0),c=dr(l,1));e.stroke(dr(c,map(1,0,1,.25,1))),e.fill(dr(h,map(1,0,1,.15,1))),3==n&&e.fill(dr(h,0)),1==s?e.ellipse(i,o,a,a):2==s?e.rect(i,o,7*a/8,7*a/8):3==s&&(e.beginShape(),e.vertex(i-4*a/7,o),e.vertex(i,o-4*a/7),e.vertex(i+4*a/7,o),e.vertex(i,o+4*a/7),e.endShape(CLOSE))}}class E{constructor(e,t,nM ,r,i,o,a){this.center=e,this.len=t,this.angle=n,this.v=r,this.angV=i,this.c1=o,this.c2=a}getEndpoints(){const e=createVector(this.len/2*cos(this.angle),this.len/2*sin(this.angle));return[Vector.add(this.center,e),Vector.sub(this.center,e)]}update(){this.center.add(this.v),this.angle+=this.angV}draw(e,t){const[n,r]=this.getEndpoints(),i=n.x*t,o=n.y*t,a=r.x*t,l=r.y*t,s=this.c1,h=this.c2;var c=e.drawingContext.createLinearGradient(i,o,a,l);c.addColorStop(0,s),c.addColorStop(1,h),e.drawingContext.strokeStyle=c,e.drawinM gContext.globalAlpha=1,e.line(i,o,a,l),e.drawingContext.globalAlpha=1}}function S(e,t){const n=random(TAU),r=random(e,t);return createVector(r*cos(n),r*sin(n))}class R{constructor(e,t,n,r,i){this.wall=n,this.maxR=i;const o=t.length;this.nodes=[];for(let a=0;a<o;++a){const o=[],l=.25*t[a];for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),l=S(.02*i,.05*i),s=random(10,25)*i;o.push(new M(t,l,s,e[a],r))}this.nodes.push(o)}const a=A(e);a.unshift(e[0]),a.push(e[e.length-1]),this.M lines=[];for(let e=0;e<=o;++e){const r=[],l=(0==e?1:t[e-1])*(e==o?1:t[e])*1.5;for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),o=random(5*i,10*i),l=random(TAU),s=S(.02*i,.05*i),h=random(2e-4,.001);r.push(new E(t,o,l,s,h,a[e],a[e+1]))}this.lines.push(r)}}reflectNode(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,{p:o,v:a}=e,l=e.getRadius();(o.x-l<t&&a.x<0||o.x+l>r&&a.x>0)&&(a.x=-a.x),(o.y-l<n&&a.y<0||o.y+l>i&&a.y>0)&&(a.y=-a.y)}reflectLine(e){const{xLeft:t,yTop:n,xRM ight:r,yBottom:i}=this.wall,[o,a]=e.getEndpoints(),l=e.v;(min(o.x,a.x)<t&&l.x<0||max(o.x,a.x)>r&&l.x>0)&&(l.x=-l.x),(min(o.y,a.y)<n&&l.y<0||max(o.y,a.y)>i&&l.y>0)&&(l.y=-l.y)}update(){for(const e of this.lines)for(const t of e)t.update(),this.reflectLine(t);for(const e of this.nodes)for(const t of e)t.update(),this.reflectNode(t)}draw(e,t,n,r,i){const o=i/this.maxR;for(const t of this.lines){const n=t.length*r;for(let r=0;r<n;++r)t[r].draw(e,o)}for(const i of this.nodes){const a=i.length*r;for(let r=0;r<a;++r)i[r].M draw(e,t,n,o)}}}function I(e,t){re(e),e.fill(0),e.rect(0,0,500,500),ie(e),e.noStroke(),e.fill(dr(cr("#000000"),.5)),e.push(),e.translate(250,250),e.scale(t),e.translate(-250,-250),e.beginShape(),e.vertex(235.2,24.9),e.bezierVertex(215,24.6,185,11.4,164.8,11),e.bezierVertex(147.2,10.7,129.3,10.4,112.2,14.7),e.bezierVertex(95.1,19,78.5,28.5,69.6,43.8),e.bezierVertex(57.699,64.199,61.599,90.199,70.199,112.2),e.bezierVertex(78.799,134.2,91.6,154.6,97.199,177.5),e.bezierVertex(102.499,199.2,100.899,222.5,92.799,243.2),eM .bezierVertex(83,268,64.6,288.3,48.9,310),e.bezierVertex(33.2,331.7,24.5,337.5,26.599,364.1),e.bezierVertex(28.2,384.1,61.399,404.2,75.7,418.3),e.bezierVertex(90,432.4,73.7,488.2,91.9,496.7),e.bezierVertex(124.2,511.6,159,472.5,194.3,468.1),e.bezierVertex(211.6,465.9,267.4,501.5,283.9,495.9),e.bezierVertex(340.7,476.7,298.599,428.9,355.4,409.7),e.bezierVertex(370.799,404.5,454.5,407.6,464.4,394.8),e.bezierVertex(478.599,376.3,474.7,349.3,464.299,328.4),e.bezierVertex(453.9,307.5,438.099,289.5,428.699,268.2),e.bezieM rVertex(412,230,419,182.6,446.1,150.9),e.bezierVertex(449.7,146.7,453.6,142.7,455.8,137.6),e.bezierVertex(459.4,129.299,457.5,119.6,454.8,111),e.bezierVertex(443.2,73.4,417.3,40.4,383.6,20.299),e.bezierVertex(358.1,5,343.2,-.4,313.5,0),e.bezierVertex(287.5,.4,261.6,25.4,235.2,24.9),e.endShape(),e.pop()}function C(e,t,n,r,i,o){let a,l,s;re(t),t.fill(0),t.rect(0,0,500,500),ie(t),t.noStroke(),t.fill(dr(n,.5)),1==i?(l=0,s=25,a=map(o,0,25,500,0)):a=0,t.rect(0,a,500,500),e.noStroke(),e.fill(r),e.rect(0,0,500,500),e.beginM Shape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,37M 3.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(15M 4.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVeM rtex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),e.fill(n),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertexM (252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7M ,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.M 1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.M endShape(),re(e),e.fill(r),e.beginShape(),e.vertex(184.3,473.2),e.bezierVertex(164,473.2,144.7,462.099,134,444.3),e.bezierVertex(131.7,440.5,129.1,438.5,125,437.1),e.bezierVertex(97.3,428.1,80.5,400.6,85.2,371.8),e.bezierVertex(86.3,365.1,85.8,364.1,79.9,361.2),e.bezierVertex(57.2,349.8,46.2,323.3,54.3,299.7),e.bezierVertex(54.7,298.599,55.1,297.7,55.5,296.9),e.bezierVertex(55.6,296.599,55.8,296.4,55.9,296.099),e.vertex(57.9,291.499),e.vertex(62.5,293.599),e.bezierVertex(64.9,294.7,67.3,295.799,69.5,296.9),e.bezierM Vertex(74.5,299.299,79.1,301.599,83.9,303.099),e.bezierVertex(89.8,304.9,96.5,305.499,102.7,305.9),e.bezierVertex(102.8,305.9,102.9,305.9,103,305.9),e.bezierVertex(106.6,305.9,108.9,302.799,109,299.799),e.bezierVertex(109.1,296.199,106.6,293.4,102.7,292.799),e.bezierVertex(101.3,292.599,99.9,292.4,98.4,292.299),e.bezierVertex(94.3,291.799,90.1,291.299,86,289.9),e.bezierVertex(68.9,284,56.5,270.2,52.7,252.799),e.bezierVertex(48.9,235.499,54.5,217.7,67.6,205.299),e.bezierVertex(71.9,201.299,72.7,198.1,70.8,192.399),eM .bezierVertex(64.2,172.2,68.8,153.99,84.2,139.599),e.bezierVertex(94.2,130.199,105.5,125.399,117.8,125.399),e.bezierVertex(124.3,125.399,131.1,126.799,137.8,129.599),e.bezierVertex(157,137.399,167.9,152.799,169.4,173.99),e.vertex(169.4,174.399),e.bezierVertex(169.5,175.899,169.6,177.2,169.9,178.299),e.bezierVertex(170.7,181.2,173.2,183.2,176.1,183.2),e.bezierVertex(176.299,183.2,176.5,183.2,176.7,183.2),e.bezierVertex(180.1,182.899,182.6,180.299,182.7,177),e.bezierVertex(183.1,162,178.299,148.2,168.399,136.1),e.bezM ierVertex(158.2,123.5,144.899,115.8,128.799,113.199),e.bezierVertex(123.499,112.299,120.399,109.799,118.899,104.99),e.bezierVertex(113.899,89.699,120.699,72.299,134.899,64.499),e.bezierVertex(139.99,61.699,145.799,60.199,151.7,60.199),e.bezierVertex(162.2,60.199,171.899,64.799,178.1,72.699),e.bezierVertex(179.6,74.6,180.799,76.6,181.9,78.499),e.vertex(182.2,79.099),e.bezierVertex(183.2,80.699,185.2,83.299,188.4,83.299),e.bezierVertex(189.5,83.299,190.6,82.99,191.7,82.399),e.bezierVertex(195.1,80.599,196,76.99,194,7M 2.799),e.bezierVertex(190.1,64.799,184.1,58.499,175.6,53.299),e.bezierVertex(174.6,52.699,173.7,52.099,172.5,51.499),e.vertex(170.5,50.299),e.vertex(163,45.899),e.vertex(170.5,41.599),e.bezierVertex(182,34.99,193.1,30.799,204.4,28.599),e.bezierVertex(208.6,27.799,212.9,27.399,217.2,27.399),e.bezierVertex(217.6,27.399,217.9,27.399,218.3,27.399),e.bezierVertex(231.4,27.599,242.7,38.199,243,50.599),e.bezierVertex(243.4,64.899,243.3,78.99,243.2,93.799),e.bezierVertex(243.2,99.799,243.1,105.899,243.1,112.099),e.vertex(2M 43.1,119.199),e.vertex(236.4,116.799),e.bezierVertex(235.7,116.499,235,116.299,234.4,115.99),e.bezierVertex(233.4,115.599,232.6,115.299,232,115.199),e.bezierVertex(230.6,114.899,229.2,114.599,227.8,114.299),e.bezierVertex(223.8,113.499,220.1,112.699,216.4,112.499),e.vertex(216.2,112.499),e.bezierVertex(212.5,112.499,210.7,115.599,210.6,118.599),e.bezierVertex(210.4,122.399,212.7,125.099,216.4,125.399),e.bezierVertex(230.1,126.399,238.9,133.099,242.3,145.199),e.bezierVertex(243.2,148.399,243.2,151.599,243.2,154.499)M ,e.vertex(243.2,155.099),e.bezierVertex(243.2,254.199,243.2,330,243.2,400.599),e.bezierVertex(243.2,401.99,243.2,403.4,243.2,404.9),e.bezierVertex(243.3,411.099,243.3,417.599,242.3,423.9),e.bezierVertex(238.1,449.2,219.6,467.799,194,472.5),e.bezierVertex(190.9,472.9,187.6,473.2,184.3,473.2),e.endShape(),e.beginShape(),e.vertex(315.8,473.1),e.bezierVertex(309.3,473.1,302.8,472,296.5,469.9),e.bezierVertex(270.4,461,253.8,434.9,257.1,407.9),e.bezierVertex(260,384,273.8,366.8,297,358.3),e.bezierVertex(297.7,358.1,298.3M ,357.8,299,357.6),e.bezierVertex(299.8,357.3,300.6,357.1,301.2,356.8),e.bezierVertex(304.3,355.4,306,351.8,304.9,348.7),e.bezierVertex(304,345.9,301.7,344.2,299,344.2),e.bezierVertex(298.6,344.2,298.1,344.2,297.6,344.3),e.bezierVertex(288.1,346.3,279,350.9,269.7,358.3),e.bezierVertex(268.9,358.9,268.1,359.6,267.2,360.4),e.vertex(265.5,361.8),e.vertex(258.5,367.6),e.vertex(257.4,358.6),e.bezierVertex(257.3,358,257.3,357.5,257.2,357.1),e.bezierVertex(257,356,256.9,354.9,256.9,353.7),e.bezierVertex(256.9,334.8,256.9,3M 16,256.9,297.1),e.bezierVertex(256.9,260.3,256.9,222.3,256.8,185),e.bezierVertex(256.8,170.7,268.3,158.8,282.5,158.4),e.bezierVertex(284.8,158.3,286.7,157.6,287.9,156.2),e.bezierVertex(289.099,154.9,289.599,153.2,289.5,151.3),e.bezierVertex(289.3,147.5,286.7,145.1,282.7,145.1),e.bezierVertex(282.5,145.1,282.2,145.1,282,145.1),e.bezierVertex(278.8,145.3,275.5,146.1,272,146.9),e.bezierVertex(270.9,147.2,269.8,147.4,268.6,147.7),e.bezierVertex(267.9,147.9,267,148.2,265.8,148.7),e.bezierVertex(265.1,149,264.4,149.3,263M .5,149.6),e.vertex(256.8,152),e.vertex(256.8,114.6),e.bezierVertex(256.8,95,256.8,75.4,256.8,55.9),e.bezierVertex(256.8,38,267.2,27.3,284.6,27.3),e.bezierVertex(285.3,27.3,285.9,27.3,286.6,27.3),e.bezierVertex(299,27.9,318.7,34.5,329.6,41.9),e.vertex(336.1,46.3),e.vertex(324.4,53.3),e.bezierVertex(316.2,58.2,310.2,64.6,306,72.9),e.bezierVertex(304.2,76.4,305.1,78.5,306.1,80),e.bezierVertex(307.4,81.9,309.4,83,311.6,83),e.bezierVertex(313.7,83,315.7,81.9,317.1,80.1),e.bezierVertex(317.4,79.7,317.8,79,318.1,78.4),e.bM ezierVertex(318.4,77.9,318.7,77.3,319,76.8),e.bezierVertex(325.3,66.2,336.3,59.9,348.5,59.9),e.bezierVertex(353.2,59.9,357.8,60.8,362.1,62.7),e.bezierVertex(377.6,69.3,386,86.7,381.7,103.2),e.bezierVertex(380.7,107.1,378.5,111.8,371.1,113.1),e.bezierVertex(342.7,118.1,322.2,139.1,317.8,167.8),e.bezierVertex(317.4,170.3,317.3,173.2,317.4,176.5),e.bezierVertex(317.5,180,320.1,182.8,323.5,183),e.bezierVertex(323.6,183,323.8,183,323.9,183),e.bezierVertex(327.1,183,329.8,180.6,330.3,177.2),e.bezierVertex(330.6,175.7,330M .7,174,330.9,172.3),e.bezierVertex(331.1,169.8,331.4,167.3,332,164.7),e.bezierVertex(337.3,141.9,357.7,125.4,380.7,125.4),e.bezierVertex(382.5,125.4,384.3,125.5,386.1,125.7),e.bezierVertex(412.8,128.9,432.6,150.9,432,176.9),e.bezierVertex(431.9,182.3,430.9,187.7,429.1,192.7),e.bezierVertex(427.2,197.9,428,201,432.3,205),e.bezierVertex(446.8,218.7,451.8,236,446.6,255),e.bezierVertex(441.4,274,428.3,286.5,408.7,291.3),e.bezierVertex(406.1,291.9,403.6,292.1,401.1,292.3),e.bezierVertex(400,292.4,398.9,292.5,397.9,292.6M ),e.bezierVertex(393.6,293.1,390.9,295.7,391,299.5),e.bezierVertex(391.1,303.4,394,305.8,398.5,305.8),e.bezierVertex(409.9,305.8,420.8,302.6,431.1,296.4),e.bezierVertex(431.8,296,432.5,295.5,433.2,295.1),e.bezierVertex(433.8,294.7,434.5,294.3,435.2,293.9),e.bezierVertex(436,293.4,436.6,293.2,437.2,293.1),e.bezierVertex(437.4,293,437.7,292.9,438.1,292.8),e.vertex(442.5,291.4),e.vertex(444.2,295.7),e.bezierVertex(450.9,312.4,449.5,328.4,440,343.4),e.bezierVertex(435.3,350.8,428.7,356.7,420.2,361.1),e.bezierVertex(414M .3,364.1,413.7,365.2,414.8,371.7),e.bezierVertex(419.5,400.2,403,427.6,375.6,436.9),e.bezierVertex(371,438.5,368.3,440.7,365.8,444.7),e.bezierVertex(355.2,462.5,336.4,473.1,315.8,473.1),e.bezierVertex(315.8,473.1,315.8,473.1,315.8,473.1),e.endShape(),ie(e),e.fill(n),e.beginShape(),e.vertex(120.2,279.9),e.bezierVertex(117.9,279.9,112.4,279.299,112.2,273.599),e.bezierVertex(112,267.7,117.4,266.7,119.7,266.599),e.bezierVertex(133.1,265.799,143.1,259.499,149.3,247.899),e.bezierVertex(149.6,247.299,150.1,246.399,150.3,2M 45.399),e.bezierVertex(150.6,244.299,150.5,243.299,150.5,242.7),e.bezierVertex(150.5,242.6,150.5,242.5,150.5,242.299),e.vertex(150.3,238.799),e.vertex(141.1,235.99),e.bezierVertex(114.6,227.799,95.6,202.499,95.9,175.799),e.bezierVertex(95.9,173.99,96.4,168.199,102.2,168.199),e.bezierVertex(102.6,168.199,103,168.199,103.4,168.299),e.bezierVertex(104.8,168.499,108.2,168.899,109.2,175.599),e.bezierVertex(109.3,176.599,109.5,177.599,109.6,178.499),e.bezierVertex(110.4,184.199,111.3,189.99,113.7,195.499),e.bezierVertex(M 121.9,213.99,139.5,225.499,159.7,225.499),e.bezierVertex(172.1,225.499,184.1,220.899,193.5,212.599),e.bezierVertex(194,212.199,194.4,211.799,194.8,211.399),e.bezierVertex(195.1,211.099,195.5,210.799,195.8,210.399),e.bezierVertex(197.4,208.99,199.2,208.2,200.9,208.2),e.bezierVertex(202.5,208.2,204,208.899,205.3,210.1),e.bezierVertex(208,212.9,207.9,216.9,205,219.9),e.bezierVertex(196.5,228.6,186.3,234.3,174.7,236.8),e.bezierVertex(168.799,238.1,165.6,241,163.899,246.7),e.bezierVertex(158.3,265.9,139.9,279.7,120.2,27M 9.9),e.vertex(120.2,279.9),e.endShape(),e.beginShape(),e.vertex(187.2,427.5),e.bezierVertex(183.799,427.5,181.299,425.3,180.799,422),e.bezierVertex(180.6,420.8,180.499,419.5,180.399,418.1),e.bezierVertex(180.299,417,180.2,415.8,180.099,414.7),e.bezierVertex(177.199,390.5,156.699,371.3,132.399,370.2),e.bezierVertex(131.99,370.2,131.499,370.2,131.099,370.2),e.bezierVertex(130.699,370.2,130.299,370.2,129.799,370.2),e.bezierVertex(125.99,369.9,123.199,367.2,123.099,363.6),e.bezierVertex(122.99,360.2,125.799,357.3,129.5M 99,356.9),e.bezierVertex(130.499,356.8,131.499,356.8,132.599,356.7),e.bezierVertex(133.199,356.7,133.799,356.7,134.399,356.6),e.vertex(138.299,356.4),e.vertex(139.1,352.6),e.bezierVertex(139.5,350.7,139.799,348.9,140.2,347),e.bezierVertex(140.899,343.4,141.5,340,142.399,336.8),e.bezierVertex(150.099,310.7,174.399,292,201.399,291.3),e.vertex(201.599,291.3),e.bezierVertex(203.699,291.3,206.299,292,208.299,293.2),e.bezierVertex(210.499,294.5,210.699,297.5,209.99,299.8),e.bezierVertex(209.499,301.5,208.199,303.9,203.29M 9,304.7),e.bezierVertex(202.199,304.9,200.99,305,199.799,305.2),e.bezierVertex(194.499,305.9,188.99,306.599,183.799,308.9),e.bezierVertex(165.499,316.799,155.199,331.299,152.99,352),e.bezierVertex(152.399,357.8,154.499,361.7,159.699,364.5),e.bezierVertex(178.199,374.4,189.399,390,193.099,410.9),e.bezierVertex(193.699,414.299,193.899,418,193.599,422),e.bezierVertex(193.399,425.2,190.899,427.5,187.399,427.5),e.vertex(187.2,427.5),e.endShape(),e.beginShape(),e.vertex(364.3,281.1),e.bezierVertex(346.3,280.6,332.9,272.8M ,323.5,257),e.bezierVertex(321.6,253.9,320.4,250.2,319.2,246.7),e.bezierVertex(317.7,242.2,315,239.799,310.5,238.799),e.bezierVertex(298.5,236.299,288,230.7,279.4,222.1),e.bezierVertex(276.7,219.4,274.9,215.299,278,211.9),e.bezierVertex(279.4,210.3,281,209.6,282.6,209.6),e.bezierVertex(284.4,209.6,286.4,210.6,288.3,212.5),e.bezierVertex(297.8,221.8,310.4,226.9,323.9,226.9),e.bezierVertex(340.2,226.9,355.1,219.3,364.8,206.2),e.bezierVertex(371,197.8,374.2,188.5,374.5,178.5),e.vertex(374.5,177.9),e.bezierVertex(374.5M ,177,374.5,176.1,374.7,175.4),e.bezierVertex(375.3,171.8,377.9,169.5,381.3,169.5),e.bezierVertex(381.4,169.5,381.5,169.5,381.7,169.5),e.bezierVertex(385.4,169.7,388,172.4,388,176.1),e.bezierVertex(388.1,190.7,383.4,204,374.2,215.8),e.bezierVertex(365.8,226.5,354.7,233.9,341.2,237.9),e.bezierVertex(340,238.3,338.7,238.6,337.3,239.1),e.bezierVertex(335.9,239.6,335.1,240.4,334.7,240.9),e.bezierVertex(334.599,241,334.5,241.1,334.4,241.2),e.vertex(331.799,243.6),e.vertex(333.199,246.8),e.bezierVertex(338.199,258,346.799M ,264.9,358.699,267.3),e.bezierVertex(360.199,267.6,361.599,267.7,362.99,267.9),e.bezierVertex(363.599,268,364.299,268,364.899,268.1),e.bezierVertex(369.099,268.6,371.799,271.4,371.499,275),e.bezierVertex(371.199,278.6,368.299,281.2,364.399,281.2),e.vertex(364.3,281.1),e.endShape(),e.beginShape(),e.vertex(323.9,437),e.bezierVertex(323.7,437,323.5,437,323.299,437),e.bezierVertex(319.599,436.7,317.299,434.1,317.4,430.2),e.bezierVertex(317.9,406.099,328.299,388,349.5,375),e.bezierVertex(350.7,374.2,352,373.5,353.4,372.M 8),e.bezierVertex(354.099,372.4,354.7,372.1,355.299,371.7),e.vertex(357.499,370.5),e.vertex(357.799,368),e.bezierVertex(360.4,346.6,345.199,323.7,323.9,317),e.bezierVertex(319.099,315.5,314.099,314.9,309.299,314.4),e.vertex(308.199,314.299),e.bezierVertex(305.99,314.099,300.799,312.9,300.899,307.299),e.bezierVertex(300.99,303.499,303.899,300.9,308.099,300.9),e.vertex(308.299,300.9),e.bezierVertex(327.099,301.299,343.099,308.7,355.699,322.9),e.bezierVertex(364.299,332.5,369.399,344.099,370.99,357.299),e.bezierVertexM (371.099,358.4,371.299,359.4,371.499,360.499),e.bezierVertex(371.599,360.99,371.699,361.499,371.799,361.99),e.vertex(372.499,365.899),e.vertex(377.899,366.199),e.bezierVertex(378.799,366.299,379.699,366.299,380.599,366.399),e.bezierVertex(385.099,366.699,387.899,369.399,387.799,373.299),e.bezierVertex(387.699,377.099,384.99,379.599,380.799,379.799),e.bezierVertex(369.799,380.199,359.99,383.299,351.899,389.299),e.bezierVertex(338.799,398.799,331.699,411.699,330.699,427.499),e.vertex(330.699,428.299),e.bezierVertex(3M 30.599,429.199,330.599,430.099,330.499,430.799),e.bezierVertex(330,434.7,327.5,437,323.9,437),e.endShape()}function T(e){return e[0].map(((t,n)=>e.map((e=>e[n]))))}function A(e){return e.map((e=>Array.isArray(e)?A(e):e))}function D(e,t){return floor(random(e,t))}function k(e){let t=0;for(const n of e)t+=n[1];let n=random(t),r=0;for(const t of e)if(r+=t[1],n<r)return t[0];return null}function L(e){for(let t=1;t<e.length;++t){let n=D(0,t),r=e[t];e[t]=e[n],e[n]=r}}function P(e){return null==e||""===e}function O(e){retM urn new Promise((t=>setTimeout(t,e)))}function F(e,t,n){let r=0;for(let i=1;i<=1e3;++i)for(let o=1;o<=1e3;++o)if(e*o%(t*i)==0){let e=1*i/o;abs(e-n)<abs(r-n)&&(r=e)}return r}function N(){let e=60*(new Date).getTimezoneOffset()*1e3;return new Date(Date.now()-e).toISOString().slice(0,-1)}function B(e,t,n){let r;if(push(),textSize(e),textWidth(t)<=n)r=t;else for(let e=0;e<t.length;++e){const i=t.slice(0,e+1)+"...";if(textWidth(i)>n){r=i;break}}return pop(),r}function Y(e){var t=e%10,n=e%100;return 1==t&&11!=n?e+"st":2=M =t&&12!=n?e+"nd":3==t&&13!=n?e+"rd":e+"th"}class G{constructor(e,t,n){this.n=t,this.m=n,this.mat=[];let r=0;for(let t=0;t<this.n;++t){this.mat.push([]);for(let n=0;n<this.m;++n)this.mat[t].push(r<e.length?e[r]:0),r+=1}return this}copy(){return new G(this.mat.flat(),this.n,this.m)}}class H{static __linear=e=>e;static __relu=e=>Math.max(e,0);static __leaky_relu=e=>e>0?e:.2*e;static __sigmoid=e=>1/(1+Math.exp(-e));static __tanh=e=>Math.tanh(e);static __apply_unary_op(e,t){const n=e.copy();for(let e=0;e<n.n;++e)for(letM r=0;r<n.m;++r)n.mat[e][r]=t(n.mat[e][r]);return n}static linear=e=>H.__apply_unary_op(e,H.__linear);static relu=e=>H.__apply_unary_op(e,H.__relu);static leaky_relu=e=>H.__apply_unary_op(e,H.__leaky_relu);static sigmoid=e=>H.__apply_unary_op(e,H.__sigmoid);static tanh=e=>H.__apply_unary_op(e,H.__tanh);static __add=(e,t)=>e+t;static __mul=(e,t)=>e*t;static __apply_binary_op=(e,t,n)=>{"object"!=typeof t&&(t=new G([t],1,1));const r=e.copy();for(let e=0;e<r.n;++e)for(let i=0;i<r.m;++i)r.mat[e][i]=n(r.mat[e][i],t.mat[e%M t.n][i%t.m]);return r};static mul=(e,t)=>H.__apply_binary_op(e,t,H.__mul);static add=(e,t)=>H.__apply_binary_op(e,t,H.__add);static matMul(e,t){const n=new G([],e.n,t.m);for(let r=0;r<n.n;++r)for(let i=0;i<n.m;++i)for(let o=0;o<e.m;++o)n.mat[r][i]+=e.mat[r][o]*t.mat[o][i];return n}static softmax(e){const t=H.__apply_unary_op(e,(e=>Math.exp(e))),n=t.mat.flat().reduce(((e,t)=>e+t));for(let r=0;r<e.n;++r)for(let i=0;i<e.m;++i)t.mat[r][i]/=n;return t}}class ${constructor(e,t){this.scale=e,this.offset=t}forward(e){returM n H.add(H.mul(e,this.scale),this.offset)}}class X{constructor(){}forward(e){return e.map((e=>e.flat()))}}class W{constructor(e,t,n,r){this.out_dim=e,this.activation=t,this.w=n,this.b=r}forward(e){const t=H.add(H.matMul(e,this.w),this.b);return null==this.activation?t:this.activation(t)}}class U{constructor(e,t,n){this.preprocessLayers=e,this.hiddenLayers=t,this.outputLayer=n,this.totalNeurons=this.hiddenLayers.map((e=>e.out_dim)),this.currentOrders=[],this.currentIteration=null}updateNeurons(e,t){if(t!=this.currentM Iteration){this.currentOrders=[];for(let e=0;e<this.totalNeurons.length;++e){randomSeed(100*(t+1)+e);const n=[];for(let t=0;t<this.totalNeurons[e];++t)n.push(t);L(n),this.currentOrders.push(n)}this.currentIteration=t}const n=A(this.totalNeurons),r=n.reduce(((e,t)=>e+t))*(1-e);for(let e=0;e<r;++e){const t=n.map(((e,t)=>(e-1)/this.totalNeurons[t]));n[t.map(((e,t)=>[e,t])).reduce(((e,t)=>t[0]>e[0]?t:e))[1]]-=Math.min(r-e,1)}this.neuronsLife=[];for(let e=0;e<n.length;++e){const t=this.currentOrders[e],r=Array(this.totaM lNeurons[e]).fill(0);for(let i=0;i<n[e];++i)r[t[i]]=Math.min(n[e]-i,1);this.neuronsLife.push(r)}}getTotalNeurons(){return A(this.totalNeurons)}getNeuronsLife(){return A(this.neuronsLife)}forward(e){for(const t of this.preprocessLayers)e=t.forward(e);for(const[t,n]of this.hiddenLayers.entries()){e=n.forward(e);const r=new G(this.neuronsLife[t],1,e.m);e=H.mul(e,r)}return e=this.outputLayer.forward(e),H.softmax(e)}}function q(e){switch(e){case"relu":return H.relu;case"sigmoid":return H.sigmoid;case"tanh":return H.tanhM ;case"leaky_relu":return H.leaky_relu;default:return H.linear}}function j(e,t){const n=[],r=[],i=Z(t);let o=null,a=0,l=[];for(const t of e.config.layers)if("InputLayer"==t.class_name)o=t.config.batch_input_shape.slice(1),l=o;else if("Rescaling"==t.class_name)n.push(new $(t.config.scale,t.config.offset));else if("Flatten"==t.class_name)o=[o.reduce(((e,t)=>e*t))];else if("Dense"==t.class_name){const e=[t.config.units],n=o[0]*e[0],l=e[0],s=i.subarray(a,a+n);a+=n;const h=i.subarray(a,a+l);a+=l;const c=new G(s,o[0],e[0]M ),u=new G(h,1,e[0]),f=q(t.config.activation);r.push(new W(e[0],f,c,u)),o=e}const s=r.pop();return{model:new U(n,r,s),inputDim:l}}function Z(e){const t=window.atob(e),n=t.length/Float32Array.BYTES_PER_ELEMENT,r=new DataView(new ArrayBuffer(Float32Array.BYTES_PER_ELEMENT)),i=new Float32Array(n);let o=0;for(let e=0;e<n;e++){o=4*e;for(let e=0;e<4;++e)r.setUint8(e,t.charCodeAt(o+e));i[e]=r.getFloat32(0,!0)}return i}class K{constructor(e){this.elt=e,this._events={},this.width=this.elt.offsetWidth,this.height=this.elt.offM setHeight}position(){if(0===arguments.length)return{x:this.elt.offsetLeft,y:this.elt.offsetTop};var e="absolute";return"static"!==arguments[2]&&"fixed"!==arguments[2]&&"relative"!==arguments[2]&&"sticky"!==arguments[2]&&"initial"!==arguments[2]&&"inherit"!==arguments[2]||(e=arguments[2]),this.elt.style.position=e,this.elt.style.left=arguments[0]+"px",this.elt.style.top=arguments[1]+"px",this.x=arguments[0],this.y=arguments[1],this}show(){return this.elt.style.display="block",this}hide(){return this.elt.style.displaM y="none",this}size(e,t){if(0===arguments.length)return{width:this.elt.offsetWidth,height:this.elt.offsetHeight};var n=e,r=t;if(n!==te||r!==te){if(n===te?n=t*this.width/this.height:r===te&&(r=e*this.height/this.width),this.elt instanceof HTMLCanvasElement){var i,o={},a=this.elt.getContext("2d");for(i in a)o[i]=a[i];for(i in this.elt.setAttribute("width",n*this._pInst._pixelDensity),this.elt.setAttribute("height",r*this._pInst._pixelDensity),this.elt.style.width=n+"px",this.elt.style.height=r+"px",this._pInst.scale(tM his._pInst._pixelDensity,this._pInst._pixelDensity),o)this.elt.getContext("2d")[i]=o[i]}else this.elt.style.width=n+"px",this.elt.style.height=r+"px",this.elt.width=n,this.elt.height=r;this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight,this._pInst&&this._pInst._curElement&&this._pInst._curElement.elt===this.elt&&(this._pInst._setProperty("width",this.elt.offsetWidth),this._pInst._setProperty("height",this.elt.offsetHeight))}return this}style(e,t){if(t instanceof Color&&(t="rgba("+t.levels[0]+","+t.leM vels[1]+","+t.levels[2]+","+t.levels[3]/255+")"),void 0===t){if(-1===e.indexOf(":"))return window.getComputedStyle(this.elt).getPropertyValue(e);for(var n=e.split(";"),r=0;r<n.length;r++){var i=n[r].split(":");i[0]&&i[1]&&(this.elt.style[i[0].trim()]=i[1].trim())}}else if(this.elt.style[e]=t,"width"===e||"height"===e||"left"===e||"top"===e){var o=window.getComputedStyle(this.elt).getPropertyValue(e).replace(/[^\d.]/g,"");this[e]=Math.round(parseFloat(o,10))}return this}value(){return arguments.length>0?(this.elt.vaM lue=arguments[0],this):"range"===this.elt.type?parseFloat(this.elt.value):this.elt.value}mouseClicked(e){return this._adjustListener("click",e,this),this}isFocused(){return document.activeElement===this.elt}_adjustListener(e,t,n){return!1===t?this._detachListener(e,n):this._attachListener(e,t,n),this}_attachListener(e,t,n){n._events[e]&&this._detachListener(e,n);var r=t.bind(n);n.elt.addEventListener(e,r,!1),n._events[e]=r}_detachListener(e,t){var n=t._events[e];t.elt.removeEventListener(e,n,!1),t._events[e]=null}}M function J(e,t){var n=document.createElement("button");return n.innerHTML=e,t&&(n.value=t),ee(n)}function Q(e){var t=arguments.length>1&&void 0!==arguments[1]&&arguments[1],n=function(t){var n=!0,r=!1,i=void 0;try{for(var o,a=t.target.files[Symbol.iterator]();!(n=(o=a.next()).done);n=!0){var l=o.value;File._load(l,e)}}catch(e){r=!0,i=e}finally{try{n||null==a.return||a.return()}finally{if(r)throw i}}};if(window.File&&window.FileReader&&window.FileList&&window.Blob){var r=document.createElement("input");return r.setAM ttribute("type","file"),t&&r.setAttribute("multiple",!0),r.addEventListener("change",n,!1),ee(r)}}function ee(e){return document.body.appendChild(e),new K(e)}createImg=function(){var e,t=document.createElement("img"),n=arguments;return n.length>1&&"string"==typeof n[1]&&(t.alt=n[1]),n.length>2&&"string"==typeof n[2]&&(t.crossOrigin=n[2]),t.src=n[0],e=ee(t,this),t.addEventListener("load",(function(){e.width=t.offsetWidth||t.width,e.height=t.offsetHeight||t.height;var r=n[n.length-1];"function"==typeof r&&r(e)})),e},M createInput=function(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:"",t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:"text",n=document.createElement("input");return n.setAttribute("value",e),n.setAttribute("type",t),ee(n,this)};const te="auto";function ne(e){re(e);const t=e._rectMode;e.rectMode(CORNER),e.rect(0,0,e.width,e.height),e.rectMode(t),ie(e)}function re(e){e.push(),e.fill(255,255,255,255),e.blendMode(REMOVE)}function ie(e){e.blendMode(BLEND),e.pop()}File=function(e,t){this.file=eM ,this._pInst=t;var n=e.type.split("/");this.type=n[0],this.subtype=n[1],this.name=e.name,this.size=e.size,this.data=void 0},File._createLoader=function(e,t){var n=new FileReader;return n.onload=function(n){var r=new File(e);if("application/json"===r.file.type)r.data=JSON.parse(n.target.result);else if("text/xml"===r.file.type){var i=(new DOMParser).parseFromString(n.target.result,"text/xml");r.data=new XML(i.documentElement)}else r.data=n.target.result;t(r)},n},File._load=function(e,t){if(/^text\//.test(e.type)||"aM pplication/json"===e.type)File._createLoader(e,t).readAsText(e);else if(/^(video|audio)\//.test(e.type)){var n=new File(e);n.data=URL.createObjectURL(e),t(n)}else File._createLoader(e,t).readAsDataURL(e)},XML=function(e){if(e)this.DOM=e;else{var t=document.implementation.createDocument(null,"doc");this.DOM=t.createElement("root")}},document.addEventListener("DOMContentLoaded",(function(){addEventListener("mousemove",(e=>{window.mouseX=e.pageX,window.mouseY=e.pageY}))})),new e("global");const oe="553";let ae,le,se,hM e,ce,ue,fe,de,xe,ge,pe,me,be,ye,we,ve,ze,Ve,_e,Me,Ee,Se,Re,Ie,Ce,Te,Ae,De,ke,Le,Pe,Oe,Fe,Ne,Be,Ye,Ge,He,$e,Xe,We,Ue,qe,je,Ze,Ke,Je,Qe,et,tt,nt,rt,it,ot,at,lt,st,ht,ct,ut,ft,dt,xt,gt,pt,mt,bt,yt,wt,vt,zt,Vt,_t,Mt,Et,St,Rt,It,Ct,Tt,At=!1,Dt=!1,kt=!0,Lt=!1,Pt=!1;const Ot=[" ","Growing","Stable","Decaying","Dead","Rebirth"];let Ft,Nt,Bt,Yt,Gt,Ht,$t,Xt,Wt,Ut,qt,jt,Zt,Kt,Jt,Qt,en,tn,nn,rn,on,an,ln,sn,hn=0,cn=0,un=0,fn=!1,dn=!0,xn=!0,gn=null,pn=null,mn=null,bn=!1,yn=!1,wn=null,vn=null,zn=!1;async function setup(){let e=wiM ndowWidth,t=windowHeight;createCanvas(e,t),et=createGraphics(e,t),Xe=createGraphics(e,t),$e=createGraphics(e,t),We=createGraphics(e,t),Ue=createGraphics(e,t),qe=createGraphics(e,t),Qe=createGraphics(e,t),je=createGraphics(e,t),Ze=createGraphics(e,t),Ke=createGraphics(e,t),Je=createGraphics(e,t),tt=createGraphics(500,500),nt=createGraphics(500,500),rt=createGraphics(500,500),_n(),Mn(),Sn(),await En(),Gn(),Rn(),bn=!0}function _n(){Et=parseInt(oe),randomSeed(Et),noiseSeed(Et)}function Mn(){Wt=Ir(p.training_traits),Cr(M Wt)}async function En(){let e;Jt=r(),Qt=o(),[Xt,e]=await Promise.all([s(Jt),h(Qt)]),Ut=new V(Wt.visual,e.layers_config,e.weight_b64),Ut.updateAge(new Date),_n(),Wt.training=e.training_traits,Ht=e.model_name,$t=e.classes_name}function Sn(){le=min(width,height)/1024,ut=Rr.findIndex((e=>e[0]===Wt.visual.colorPalette)),ft=[["#ffffff","#231f20","#231f20"],["#231f20","#ffffff","#ffffff"],["#104da8","#ffffff","#ffffff"],["#722F1F","#FCE1B2","#FCE1B2"],["#e88120","#f9f2e5","#f9f2e5"],["#f6b941","#2E2E2E","#2E2E2E"],["#45daM aa","#012221","#012221"],["#F1F1F1","#328DFE","#328DFE"],["#111822","#D3EB8D","#D3EB8D"],["#713FF9","#D6D5E6","#D6D5E6"],["#FBDA9D","#795106","#795106"],["#8f5b62","#ead0d0","#ead0d0"],["#eae4cb","#508cac","#508cac"],["#ffc6cc","#cc313d","#cc313d"],["#60A900","#E0FE00","#E0FE00"],["#507DBE","#D0D1D3","#D0D1D3"],["#305848","#E8F2EE","#E8F2EE"],["#2a2634","#5b6988","#cb78a2","#5b6988"],["#590e29","#fd5e53","#fd5e53","#ffe373"],["#0a141d","#57d4e4","#328195","#2A9ECF","#0ab6a8","#57d4e4"],["#3a2d28","#d5c2ac","#df6338M ","#3d9895","#d5c2ac"],["#030706","#77c4d9","#77c4d9","#77c4d9","#ffffff","#ffffff","#e72020","#e72020"],["#3a4664","#92f5ff","#f9ff94","#eaa0a2","#55dde0"],["#fbfaff","#f04bb1","#f04bb1","#fac373","#82cef0","#8b31ce"],["#000000","#ffffff","#ff0002","#f26522","#fdff00","#00ff03","#01fffe","#0000ff","#ff00ff"]];for(let e=0;e<ft.length;++e)for(let t=0;t<ft[e].length;++t)ft[e][t]=cr(ft[e][t]);pt=[],ct=ft[ut][0],st=ft[ut][1]}function Rn(){gn=document.querySelector("#upload"),pn=document.querySelector("#inputUpload"),gnM .addEventListener("dblclick",(()=>{if(!Lt&&!yn)if(In(Ie)&&cn==Ve-1)pn.click();else{if(4!=Pe&&5!=Pe&&(In(Ie)||cn!=Ve-1))return;fn=!0,dn=!0,Bt=0,un=0}})),pn.addEventListener("click",(()=>{pn.value=null,gn.style.display="block"})),pn.addEventListener("change",(()=>{const[e]=pn.files;e?(se=null,gn.style.display="none",Tn(URL.createObjectURL(e)),mn=e):gn.style.display="block"}))}function In(e){for(let t=0;t<e.length;++t){let n=0;for(let r=0;r<e[t].length;++r)e[t][r]>0&&++n;if(0==n)return!1}return!0}function Cn(){null!=sM e&&(un=0,Pt=!0,he=0,ue=0,drewLineAnim=!0,ce=(ae/2+we/2)/le,loadImage(se.elt.src,(e=>{const[t,n,r]=Gt,i=createGraphics(t,n);i.image(e,0,0,t,n),i.loadPixels();const o=i.pixels.filter(((e,t)=>t%4!=3)),a=Ut.classifyImage(o);Zt=T([a,$t.map((e=>e.toUpperCase()))]).sort(((e,t)=>e[0]>t[0]?-1:1))})))}function Tn(e){se=createImg(e,""),se.hide(),Cn()}function An(){zn||(ce+=(width-ae-we)/tn/le),re(Xe),Xe.rect(ce*le,0,width,height),ie(Xe),un>=ge&&1==kt&&(kt=!1,un-=ge),kt&&(re($e),$e.strokeWeight(2*Fe),Jn(he,ze,ct,ct,$e),ie($e))M ,un>=ge&&0==kt&&(kt=!0,un-=ge,he+=1,he==en&&(++ue,he=0,ce=(ae/2+we/2)/le,1==ue&&(Pt=!1,Dn(),ye=millis())))}function Dn(){At=!0,pe=!1,me=!1,tryButton=br("Try Again",width/2-225*le,height/2+265*le,290*le,40*le,kn),closeResultButton=br("Close",width/2+75*le,height/2+265*le,150*le,40*le,Ln)}function kn(){At=!1,tryButton.hide(),closeResultButton.hide(),pn.click()}function Ln(){Yt=!0,At=!1,Gn(),tryButton.hide(),closeResultButton.hide(),gn.style.display="block",se=null}function keyTyped(){bn&&!1===yn&&!1===yr()&&("i"!==keM y&&"I"!==key||(Dt=!Dt),"b"!==key&&"B"!==key||(xn=!xn),"s"!==key&&"S"!==key||!1!==Lt||saveCanvasAtCurrentTime(),"k"!==key&&"K"!==key||!1!==Lt||save4KCanvasAtCurrentTime(),"u"!==key&&"U"!==key||!1!==Lt||!1!==At||!1!==fn||!1!==Pt||On())}function On(){Lt=!0,wn=null,vn=null,submitButton=br("Submit",width/2-155*le,height/2+115*le,150*le,40*le,Fn),closeSettingButton=br("Close",width/2+5*le,height/2+115*le,150*le,40*le,Yn),vt=createInput(),vt.position(width/2-252.5*le,height/2-40*le),vt.size(500*le,25*le),vt.style("font-siM ze","15px"),vt.value(Jt||""),zt=createInput(),zt.position(width/2-252.2*le,height/2+35*le),zt.size(500*le,25*le),zt.style("font-size","15px"),zt.value(Qt||"")}function Fn(){Vt=vt.value(),_t=zt.value(),submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide(),Lt=!1,yn=!0,Nn()}async function Nn(){[wn,vn,_]=await Promise.all([c(Vt),u(_t),O(1e3)]),yn=!1,wn&&vn?(n(Vt),i(_t),window.location.reload()):(Lt=!0,submitButton.show(),closeSettingButton.show(),vt.show(),zt.show())}function Bn(){Je.textFont("Trebuchet MS"M ),Je.noStroke(),pr(Je,600*le,200*le),Je.strokeWeight(1*le),Je.stroke(xt),Je.fill(xt),Je.textSize(50*le),Je.text("update()",width/2,height/2+2.5*le)}function Yn(){wn=null,vn=null,Lt=!1,submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide()}function Gn(){_n(),nn=Date.now(),pe=!1,me=!1,St=Wt.training.structure_gen,Rt=Wt.visual.birthYear,It=Wt.visual.lifeCycle,Ct=Wt.training.epoch_num,Tt=Wt.training.activation_func,Ft=Mr.findIndex((e=>e[0]==Wt.visual.hardwareAcceleration))+1,1==Ft?(Nt=30,fe=40):2==Ft?(Nt=15,M fe=20):(Nt=2,fe=10);const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),ae=100*le,ht=50*le,Oe=Sr.findIndex((e=>e[0]==Wt.visual.nodeShapM e))+1,dt=Er.findIndex((e=>e[0]==Wt.visual.nodeFill))+1,lt=_r.findIndex((e=>e[0]==Wt.visual.pattern))+1,de=Math.tanh(Math.log10(Xt.avgfeerate)),de=map(de,0,1,.2,.8),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)M ),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let M e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,at=.7,pt=[],xt=ft[ut][2],gt=ft[ut][ft[ut].length-1];for(let e=3;e<ft[ut].length-1;e++)pt.push(ft[ut][e]);M mt=sr(xt,gt,pt,width),bt=[],wt=[],yt=width/(Ve-1);for(let e=0;e<Ve;e++)bt.push(hr(mt,yt*e/width)),wt.push(hr(mt,yt*e/width));wt.unshift(bt[0]),wt.push(bt[bt.length-1]),hn=0,cn=0,un=0,Yt=!0;const n={xLeft:ae/8,xRight:width-ae/8,yTop:ae/8,yBottom:height-ae/8},r=Ce.map((e=>e.length));jt=new R(bt,r,n,Oe,le)}function Hn(e,t){let n=Ce[e].length;return[e*we+we/2+ae/2,height/2-(n-1)/2*ve+t*ve]}function $n(e,t){le=min(e,t)/1024,ae=100*le,ht=50*le,we=(e-ae)/Ve,ve=(t-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++)M {let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}xe=floor(De.length*de),Le=[],ke=[],ge=floor(map(de,.2,.8,15,2));for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,mt=sr(xt,gt,pt,e),bt=[],wt=[],yt=e/(Ve-1);for(let t=0;t<Ve;t++)bt.push(hr(mt,yt*t/e)),wt.push(hr(mt,yt*t/e));wt.unshift(bt[0]),wt.push(bt[bt.length-1])}function Xn(){const eM =Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(M ((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;M n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let eM =0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le}function Wn(){jt.update();const e=4==Pe?0:Kt;jt.draw(Qe,ct,dt,e,le)}function Un(){if(!bn)return ar(),void et.image(je,0,0);if(4==Pe||5==Pe)return Wn(),void et.image(Qe,0,0);un>=Nt&&hn<Ve&&(hn++,un=0);for(let e=0;e<hn;e++)1==dt?it=ot=bt[e]:(it=ct,ot=bt[e]),Kn(e,it,ot,$e);un>=Nt&&cn<Ve-1&&(cn++,un=0);for(let e=0;e<cn;e++)Zn(e)}function qn(){et.background(ct),M Ue.background(255),Ue.rectMode(CENTER),ne(Ue),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),Ue.stroke(st),Ue.strokeWeight(8*le),Ue.fill(ct),Qe.background(255),Qe.rectMode(CENTER),ne(Qe),Qe.strokeWeight(le),qe.background(255),qe.rectMode(CENTER),ne(qe),qe.textAlign(LEFT),$e.background(255),$e.rectMode(CENTER),ne($e),Xe.background(255),ne(Xe),Xe.strokeWeight(Ne),We.background(255),We.rectMode(CENTER),ne(We),We.fill(st),We.stroke(st),We.strokeWeight(.1*le),er(lt),We.noStroke(),xn&&(We.rect(ae/16,height/2,ae/8,height)M ,We.rect(width-ae/16,height/2,ae/8,height),We.rect(width/2,ae/16,width,ae/8),We.rect(width/2,height-ae/16,width,ae/8)),Ze.background(255),Ze.rectMode(CENTER),ne(Ze),Ze.textAlign(CENTER,CENTER),Ze.textStyle(BOLD),Ze.stroke(st),Ze.strokeWeight(8*le),Ze.fill(ct),je.background(255),je.rectMode(CENTER),ne(je),je.textAlign(CENTER,CENTER),je.textStyle(BOLD),Ke.background(255),Ke.rectMode(CENTER),ne(Ke),Ke.textAlign(CENTER,CENTER),Ke.textStyle(BOLD),Ke.stroke(st),Ke.strokeWeight(8*le),Ke.fill(ct),Je.background(255),Je.rectM Mode(CENTER),ne(Je),Je.textAlign(CENTER,CENTER),Je.textStyle(BOLD),Je.stroke(st),Je.strokeWeight(8*le),Je.fill(ct),Un(),et.image(We,0,0),Pt&&An(),et.image(Xe,0,0),et.image($e,0,0),At&&(tr(),et.image(Ue,0,0)),fn&&(lr(),et.image(Ze,0,0)),Lt&&(or(),et.image(Ke,0,0)),Dt&&(ir(),et.image(qe,0,0)),yn&&(Bn(),et.image(Je,0,0))}function draw(){const e=Date.now();bn&&(Ut.updateAge(new Date(e)),Xn()),qn(),image(et,0,0),zn||un++}function Zn(e){let t,n=Ce[e].length,r=Ce[e+1].length;for(let i=0;i<n;i++){const[n,o]=Hn(e,i);for(letM a=0;a<r;a++){const[r,l]=Hn(e+1,a);t=map(min(Ce[e][i],Ce[e+1][a]),0,1,0,.5),ur(n,o,r,l,bt[e],bt[e+1],Xe,t)}}}function Kn(e,t,n,r){let i,o,a,l=Ce[e].length;for(let s=0;s<l;s++){const[l,h]=Hn(e,s);i=Ce[e][s],a=map(Be,1/30,1,3,10),o=map(Ce[e][s],0,1,2*a,0)*le,o<1.5*le&&(o=0),Qn(l,h,ze,Oe,t,n,o,i,r)}}function Jn(e,t,n,r,i){for(let o=0;o<Le[e].length;o++)Qn(Le[e][o][0],Le[e][o][1],t,Oe,n,r,0,1,i)}function Qn(e,t,n,r,i,o,a,l,s){s.stroke(dr(o,map(l,0,1,.25,1))),s.fill(dr(i,map(l,0,1,.15,1))),s.strokeWeight(Fe),fr([a],s),3M ==dt&&s.fill(dr(i,0)),1==r?s.ellipse(e,t,n):2==r?s.rect(e,t,7*n/8,7*n/8):3==r&&(s.beginShape(),s.vertex(e-4*n/7,t),s.vertex(e,t-4*n/7),s.vertex(e+4*n/7,t),s.vertex(e,t+4*n/7),s.endShape(CLOSE))}function er(e){if(1==e);else if(2==e){We.strokeWeight(1*le);for(let e=ht/4;e<width+ht/4;e+=ht)for(let t=ht/4;t<height+ht/4;t+=ht)We.point(e,t)}else if(3==e){ht=25*le;for(let e=ht/2;e<height+ht/2;e+=ht)We.line(0,e,width,e);for(let e=ht/2;e<width+ht/2;e+=ht)We.line(e,0,e,height)}}function tr(){Ue.textFont("Trebuchet MS"),Ue.teM xtAlign(LEFT,CENTER),Ue.noStroke(),pr(Ue,800*le,500*le),Ue.noStroke(),Ue.fill(dr(st,.75)),Ue.rect(width/2,height/2-100*le,800*le,300*le,25*le,25*le,0,0),Ue.fill(st),Ue.rect(width/2-250*le,height/2-100*le,225*le,225*le),Ue.image(se.elt,width/2-357.5*le,height/2-207.5*le,215*le,215*le);let e=100*Zt[0][0];Ue.fill(ct),Ue.textSize(25*le),Ue.textStyle(NORMAL),1==me&&(e>=0&&e<20?Ue.text("I have a feeling this image belongs to",width/2-100*le,height/2-170*le):e>=20&&e<40?Ue.text("I have a hunch this image belongs to",widthM /2-100*le,height/2-170*le):e>=40&&e<60?Ue.text("I think this image belongs to",width/2-100*le,height/2-170*le):e>=60&&e<80?Ue.text("I'm almost certain this image belongs to",width/2-100*le,height/2-170*le):Ue.text("I'm positive this image belongs to",width/2-100*le,height/2-170*le));let t=e.toFixed(2);"100.00"==t&&(t="100"),1==me&&Ue.text("I'm "+t+"% confident that I'm right!",width/2-100*le,height/2-25*le),example=Zt.map((e=>e[1])),be=Ue.textWidth('"FIDENZAAAA"'),defaultPhrase=Ue.textWidth('"PERPENDICULAR INHABITAM TION"'),Ue.textStyle(BOLD);const n=me?example[0]:random(example);if(1===n.split(" ").length){let e=75*be/Ue.textWidth('"'+n+'"');e>75&&(e=75),Ue.textSize(e*le),Ue.text('"'+n+'"',width/2-100*le,height/2-90*le)}else nr(width/2-100*le,height/2-90*le,460*le,110*le,n,Ue);if(millis()-ye>1500&&(me=!0),C(tt,nt,st,ct,Pe,Mt),Ue.image(nt,width/2-370*le,height/2+70*le,80*le,80*le),3==Pe){let e;e=map(Mt,50,60,.25,1.3),I(rt,e),Ue.image(rt,width/2-370*le,height/2+70*le,80*le,80*le)}let r,i;Ue.image(tt,width/2-370*le,height/2+70*lM e,80*le,80*le),Ue.fill(xt),Ue.textSize(40*le),Ue.text("INTELLIGENCE INFO",width/2-275*le,height/2+115*le),Ue.textSize(18*le),Ue.textStyle(NORMAL),Ue.circle(width/2-360*le,height/2+180*le,7.5*le),1==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s growing and getting smarter by the day.`:2==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s stable and it has reached peak performance.`:3==Pe&&(r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s decaying and losing its luster.`),i=2==Pe?"The PM erceptron remains stable for some time before entering the decay phase.":`Wait until ${new Date(an).toLocaleString("en-US")} for your Perceptron to reach its peak performance.`,Ue.text(r,width/2-350*le,height/2+180*le),Ue.circle(width/2-360*le,height/2+210*le,7.5*le),Ue.text(i,width/2-350*le,height/2+210*le),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),gr(Ue,width/2-225*le,width/2+65*le,height/2+265*le,height/2+305*le,"SELECT ANOTHER IMAGE"),gr(Ue,width/2+75*le,width/2+225*le,height/2+265*le,height/2+305*le,"CLOSM E")}function nr(e,t,n,r,i,o){let a=i.split(" "),l=75*be/o.textWidth('"'+i+'"'),s=0,h=[],c=[],u=[],f="",d="";if(l>=50)l>75&&(l=75),o.textSize(l*le),o.text('"'+i+'"',e,t);else if(l<50){if(l=50*defaultPhrase/o.textWidth('"'+i+'"'),l>30){if(l>50&&(l=50),[f,d]=rr(l,n,s,h,c,a,f,d,Ue),0==c.length)return o.textSize(l*le),void o.text('"'+i+'"',e,t);for(s=0,h=[],c=[];o.textWidth(d)>n/le;)l=l*n/le/o.textWidth(d),f="",d="",[f,d]=rr(l,n,s,h,c,a,f,d,Ue)}else{l=30,o.textSize(l);for(let e=0;e<a.length;e++)s+=o.textWidth(" "+a[e]),M s<=n/le?h.push(a[e]):s>n/le&&s<=n/le*2?c.push(a[e]):u.push(a[e]);for(let e=1;e<h.length;e++)f=f+" "+h[e];if(f='"'+h[0]+f,0==u.length){for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+c[c.length-1]+'"'}else if(1==c.length)d="... "+u[u.length-1]+'"';else{for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+"... "+u[u.length-1]+'"'}}o.textSize(l*le);let r=1.25*(o.textDescent()+o.textAscent());o.text(f,e,t-r/2),o.text(d,e,t+r/2)}}function rr(e,t,n,r,i,o,a,l,s){s.textSize(e);for(let e=0;e<o.length;e++)(n+=s.textWidth(" "+o[e]))<=M t/le?r.push(o[e]):i.push(o[e]);for(let e=1;e<r.length;e++)a=a+" "+r[e];if(a='"'+r[0]+a,0==i.length&&(a+='"',l=""),1==i.length)l=i[i.length-1]+'"';else{for(let e=0;e<i.length-1;e++)l=l+i[e]+" ";l=l+i[i.length-1]+'"'}return[a,l]}function ir(){const e=45*le;qe.textFont("Tahoma"),qe.stroke(st),qe.strokeWeight(2*le),qe.fill(ct),qe.rect(width/2,e/2+height-87.5*le,600*le,90*le),qe.fill(st),qe.rect(width/2-150*le,e+height-170*le,300*le,30*le),qe.fill(ct),qe.rect(width/2+150*le,e+height-170*le,300*le,30*le),qe.noStroke(),qeM .fill(ct),qe.textSize(15*le),qe.textStyle(BOLD),qe.text("PERCEPTRON INFORMATION",width/2-285*le,e+height-165*le),qe.fill(xt),qe.text("ARTWORK NAME:",width/2+10*le,e+height-165*le),qe.textAlign(RIGHT),qe.textStyle(ITALIC),qe.text("Perceptron #"+Et,width/2+285*le,e+height-165*le);const[t,n]=It.split(" ");let r;"60 Years"===It?r="1 Year":"60 Months"===It?r="1 Month":"60 Weeks"===It?r="1 Week":"60 Days"===It?r="1 Day":"12 Hours"===It&&(r="12 Minutes"),data=[["AI MODEL NAME:",B(12*le,Ht,140*le)],["SCALE:","1:"+Te],["NUMM BER OF CLASSES:",$t.length],["BIRTH YEAR:",Rt],["NUMBER OF REBIRTHS:",sn.toString()],["AGE:",`${Math.ceil(Mt)} Perceptron Years`],["ONE PERCEPTRON YEAR:",`${r}`],["STATE:",Ot[Pe]],["ACTIVE NEURONS:",`${round(ln*rn)} / ${ln}`],["NEXT STATE TIME:",vr(new Date(on))]],qe.fill(xt);const i=data.length/2;for(let t=0;t<data.length;++t){const n=t<i,r=n?width/2-285*le:width/2+10*le,o=n?width/2-10*le:width/2+285*le,a=e+height-(135-t%i*15)*le;qe.textStyle(BOLD),qe.textAlign(LEFT),qe.textSize(12*le),qe.text(data[t][0],r,a),qe.tM extStyle(ITALIC),qe.textAlign(RIGHT),qe.textSize(12*le),qe.text(data[t][1],o,a)}}function or(){Ke.textFont("Trebuchet MS"),Ke.noStroke(),pr(Ke,600*le,200*le),gr(Ke,width/2-155*le,width/2-5*le,height/2+115*le,height/2+155*le,"UPDATE"),gr(Ke,width/2+5*le,width/2+155*le,height/2+115*le,height/2+155*le,"CLOSE"),Ke.textAlign(LEFT),Ke.fill(xt),Ke.text("UPDATE BITCOIN FULL NODE ADDRESS",width/2-252.5*le,height/2-55*le),Ke.text("UPDATE MODEL ADDRESS",width/2-252.5*le,height/2+20*le),Ke.textAlign(RIGHT),Ke.textStyle(ITALIC)M ,Ke.textSize(15*le),0==wn&&Ke.text("(*) Invalid Address",width/2+252.5*le,height/2-53*le),0==vn&&Ke.text("(*) Invalid Model",width/2+252.5*le,height/2+23*le)}function ar(){je.textFont("Trebuchet MS"),je.fill(st),je.textSize(50*le),je.stroke(st),je.strokeWeight(1*le),je.text("main()",width/2,height/2)}function lr(){un>=20&&1==dn&&(dn=!1,un=0),dn&&(Ze.textFont("Trebuchet MS"),Ze.stroke(st),Ze.fill(ct),Ze.rect(width/2,height/2,600*le,150*le,25*le),Ze.fill(xt),Ze.textSize(75*le),Ze.noStroke(),1==Pe?Ze.text("GROWING",wiM dth/2,height/2+5*le):3==Pe?Ze.text("AGING",width/2,height/2+5*le):4==Pe?Ze.text("DEAD",width/2,height/2+5*le):5==Pe&&Ze.text("BIRTH",width/2,height/2+5*le)),un>=20&&0==dn&&(dn=!0,un=0,Bt++,3==Bt&&(fn=!1))}function sr(e,t,n,r){let i=[],o=r/(n.length+1),a=color(e),l=color(t);i.push(a);for(let e=0;e<n.length;e++){let t=color(n[e]);for(let e=1;e<=o;e++){let n=lerpColor(a,t,e/o);i.push(n)}a=t}for(let e=1;e<o;e++){let t=lerpColor(a,l,e/o);i.push(t)}if(i.push(l),i.length>r)i.splice(r);else if(i.length<r){let e=i[i.length-M 1];for(;i.length<r;)i.push(e)}return i}function hr(e,t){let n=e.length,r=Math.floor(t*n);return r>=n&&(r=n-1),e[r]}function cr(e){e=e.replace("#","");var t=parseInt(e,16);return color(t>>16&255,t>>8&255,255&t)}function ur(e,t,n,r,i,o,a,l){var s=a.drawingContext.createLinearGradient(e,t,n,r);s.addColorStop(0,i),s.addColorStop(1,o),a.drawingContext.strokeStyle=s,a.drawingContext.globalAlpha=l,a.line(e,t,n,r),a.drawingContext.globalAlpha=1}function fr(e,t){t.drawingContext.setLineDash(e)}function dr(e,t){let n=color(eM ),r=red(n),i=green(n),o=blue(n);return color(r,i,o,255*t)}function xr(e,t,n,r){return mouseX>e&&mouseX<t&&mouseY>n&&mouseY<r}function gr(e,t,n,r,i,o){e.strokeWeight(1*le),e.stroke(st);const[a,l]=xr(t,n,r,i)?[xt,ct]:[ct,xt];e.fill(a),e.push(),e.rectMode(CORNERS),e.rect(t,r,n,i,5*le),e.pop(),e.noStroke(),e.textSize(20*le),e.fill(l),e.text(o,(t+n)/2,(46*r+54*i)/100)}function pr(e,t,n){e.fill(0,0,0,75),e.rect(width/2,height/2,width,height),e.stroke(st),e.fill(ct),e.rect(width/2,height/2,t,n,25*le)}function mr(e,t){resiM zeCanvas(e,t,!0),Xe.resizeCanvas(e,t,!0),$e.resizeCanvas(e,t,!0),We.resizeCanvas(e,t,!0),Ue.resizeCanvas(e,t,!0),qe.resizeCanvas(e,t,!0),Qe.resizeCanvas(e,t,!0),je.resizeCanvas(e,t,!0),Ze.resizeCanvas(e,t,!0),Ke.resizeCanvas(e,t,!0),Je.resizeCanvas(e,t,!0),et.resizeCanvas(e,t,!0)}function br(e,t,n,r,i,o){const a=J(e);return a.position(t,n),a.size(r,i),a.style("opacity","0"),a.mouseClicked(o),a}function yr(){return null!=vt&&vt?.isFocused()||null!=zt&&zt?.isFocused()}function wr(e,t,n,r){let i;if(e<=3){i=`Hey ${StriM ng.fromCodePoint(128075)}, I'm ${n}, ${t} years old. I can detect ${r.length} NFT collections: `;let e=0;for(let t=0;t<r.length;++t){const n=r[t];if(e+n.length>500){i+=", etc";break}t==r.length-1?i+=", and ":t>0&&(i+=", "),i+=n,e+=n.length}i+=". ",t<=5?i+="However, I am only a baby, so my recognition ability is not accurate. I'm in the state of Growing both looks and intelligence.":t<=13?i+="I am now a child. My recognition ability is becoming better, but still not very accurate. I'm in the state of Growing both loM oks and intelligence.":t<=25?i+="I have grown up to be a teen. My recognition ability almost reaches the peak, but I will still mess up sometimes. I'm in the state of Growing both looks and intelligence.":t<=50?i+="I finally reach adulthood. My recognition is fully functional now. I'm in the Stable state, where I am the most intelligent with all neurons activated.":t<=60&&(i+="I am now an old Perceptron, so my recognition ability is no longer the best. I'm in the Decaying state, meaning that my neurons are dying, aM nd my intelligence is decreasing over time.")}else 4==e?i=`${n} is Dead. However, this is not the end to its story...`:5==e&&(i=`${n} is now in the Rebirth state, and is preparing to start a new life.`);return i}function vr(e){const t=e.getDate(),n=e.toLocaleString("en-US",{month:"long"}),r=e.getFullYear();let i=e.getHours().toString();1==i.length&&(i="0"+i);let o=e.getMinutes().toString();return 1==o.length&&(o="0"+o),`${Y(t)} ${n} ${r} | ${i}:${o}`}saveCanvasAtCurrentTime=()=>{save(N())},save4KCanvasAtCurrentTimeM =()=>{const e=width,t=height,n=min(4096/min(e,t),1e4/max(e,t)),r=e*n,i=t*n;mr(r,i),zn=!0,$n(r,i),qn();let o="4K_"+N()+".png";saveCanvas(et,o),mr(e,t),$n(e,t),zn=!1};const zr=[["60 Years",3,365],["60 Months",40,30],["60 Weeks",37,7],["60 Days",20,1]],Vr=[["1943",1],["1951",1.5],["1957",2],["1969",2.5],["1970",3],["1980",3.5],["1982",4],["1986",4.5],["1988",5],["1997",5.5],["1998",6],["2002",6.5],["2009",7],["2012",7.5],["2014",8],["2015",8.5],["2016",9],["2023",15]],_r=[["Plain",20],["Dotted",40],["Squared",40]],Mr=M [["Basic",30],["Standard",60],["Advanced",10]],Er=[["MNIST",70],["CIFAR",25],["IMAGENET",5]],Sr=[["Theano",60],["Torch",30],["TensorFlow",10]],Rr=[["Whitepaper",2],["Blackboard",2],["Blueprint",2],["Nak",74/14],["Jims",74/14],["Level 10",74/14],["Flips",74/14],["Level 14",74/14],["III",74/14],["XMB",74/14],["Info",74/14],["Adventure",74/14],["Marigold",74/14],["Phoenix",74/14],["Love",74/14],["Cachet",74/14],["Human",74/14],["Twilight",3],["Sunset",3],["Aurora",3],["Liminal Space",3],["D Vu",3],["Lucid Dream",M 3],["Parallel",1],["Multiverse",1]];function Ir(e){for(let e=0;e<100;++e)random(1);return{visual:{pattern:k(_r),hardwareAcceleration:k(Mr),nodeFill:k(Er),nodeShape:k(Sr),colorPalette:k(Rr),lifeCycle:k(zr),birthYear:k(Vr)},training:e}}function Cr(e){window.$generativeTraits={"Network Architecture":e.training.structure_gen,"Hidden Layers":e.training.n_layers,"Max Neurons Per Hidden Layer":e.training.max_nodes,"Activation Function":e.training.activation_func,"Training Epochs":e.training.epoch_num,Dataset:e.visual.nodeM Fill,"Deep Learning Framework":e.visual.nodeShape,"Hardware Acceleration":e.visual.hardwareAcceleration,"Paper Pattern":e.visual.pattern,"Life Cycle":e.visual.lifeCycle,"Birth Year":e.visual.birthYear,"Color Palette":e.visual.colorPalette}} <script defer src="https://static.cloudflareinsights.com/beacon.min.js/v2b4487d741ca48dcbadcaf954e159fc61680799950996" integrity="sha512-D/jdE0CypeVxFadTejKGTzmwyV10c1pxZk/AqjJuZbaJwGMyNHY3q/mTPWqMUnFACfCTunhZUVcd4cV78dK1pQ==" data-cf-beacon='{"rayId":"7b4e426228L 20ab3b","version":"2023.3.0","b":1,"token":"6c07c178c94442f695e7a0a2aaee641a","si":100}' crossorigin="anonymous"></script> text/plain;charset=utf-8 @{"p":"brc-20","op":"deploy","tick":" ","max":"300","lim":"1"}h! text/html;charset=utf-8 <meta charset="utf-8" /> position: relative; width: var(--width); height: var(--height); border: 1px solid blue; position: relative; <div id="upload"> <input id="inputUpload" type="file"> function e(e){"use strict";return new function e(t){let n="global"==t?window:this;n.canvas=document.createElement("canvas");let r=n.canvas.getContext("2d");n.width=100,n.height=100,n.canvas.width=n.width,n.canvas.height=n.height,"offscreen"!=t&&(document.body?document.body.appendChild(n.canvas):window.addEventListener("load",(function(){document.body.appendChild(n.canvas)}))),g(),n.MAGIC=161533525,n.RGB=0,n.HSV=1,n.HM SB=1,n.CHORD=0,n.PIE=1,n.OPEN=2,n.RADIUS=1,n.CORNER=2,n.CORNERS=3,n.ROUND="round",n.SQUARE="butt",n.PROJECT="square",n.MITER="miter",n.BEVEL="bevel",n.CLOSE=1,n.BLEND="source-over",n.REMOVE="destination-out",n.ADD="lighter",n.DARKEST="darken",n.LIGHTEST="lighten",n.DIFFERENCE="difference",n.SUBTRACT="subtract",n.EXCLUSION="exclusion",n.MULTIPLY="multiply",n.SCREEN="screen",n.REPLACE="copy",n.OVERLAY="overlay",n.HARD_LIGHT="hard-light",n.SOFT_LIGHT="soft-light",n.DODGE="color-dodge",n.BURN="color-burn",n.NORMAL="norM mal",n.ITALIC="italic",n.BOLD="bold",n.BOLDITALIC="italic bold",n.CENTER="center",n.LEFT="left",n.RIGHT="right",n.TOP="top",n.BOTTOM="bottom",n.BASELINE="alphabetic",n.LANDSCAPE="landscape",n.PORTRAIT="portrait",n.ALT=18,n.BACKSPACE=8,n.CONTROL=17,n.DELETE=46,n.DOWN_ARROW=40,n.ENTER=13,n.ESCAPE=27,n.LEFT_ARROW=37,n.OPTION=18,n.RETURN=13,n.RIGHT_ARROW=39,n.SHIFT=16,n.TAB=9,n.UP_ARROW=38,n.HALF_PI=Math.PI/2,n.PI=Math.PI,n.QUARTER_PI=Math.PI/4,n.TAU=2*Math.PI,n.TWO_PI=2*Math.PI,n.THRESHOLD=1,n.GRAY=2,n.OPAQUE=3,n.INVEM RT=4,n.POSTERIZE=5,n.DILATE=6,n.ERODE=7,n.BLUR=8,n.ARROW="default",n.CROSS="crosshair",n.HAND="pointer",n.MOVE="move",n.TEXT="text",n.VIDEO={video:!0,audio:!1},n.AUDIO={video:!1,audio:!0},n.SHR3=1,n.LCG=2,n.HARDWARE_FILTERS=!0,n.hint=function(e,t){n[e]=t},n.frameCount=0,n.mouseX=0,n.mouseY=0,n.pmouseX=0,n.pmouseY=0,n.mouseButton=null,n.keyIsPressed=!1,n.mouseIsPressed=!1,n.key=null,n.keyCode=null,n.pixels=null,n.accelerationX=0,n.accelerationY=0,n.accelerationZ=0,n.rotationX=0,n.rotationY=0,n.rotationZ=0,n.relRotatM ionX=0,n.relRotationY=0,n.relRotationZ=0,n.pAccelerationX=0,n.pAccelerationY=0,n.pAccelerationZ=0,n.pRotationX=0,n.pRotationY=0,n.pRotationZ=0,n.pRelRotationX=0,n.pRelRotationY=0,n.pRelRotationZ=0,n.touches=[],n._styleCache=[{colorMode:n.RGB,noStroke:!1,noFill:!1,ellipseMode:n.CENTER,rectMode:n.CORNER,curveDetail:20,curveAlpha:0,textFont:"sans-serif",textSize:12,textLeading:12,textStyle:"normal"}],n._style=n._styleCache[n._styleCache.length-1],n._noLoop=!1,n._pixelDensity=1,n._frameRate=null,n._tint=null;let i=nullM ,o=!0,a=[],l=null,s=0,h={},c=0,u=null,f=null,d=null;Object.defineProperty(n,"deviceOrientation",{get:function(){return 90==Math.abs(window.orientation)?n.LANDSCAPE:n.PORTRAIT}}),Object.defineProperty(n,"windowWidth",{get:function(){return window.innerWidth}}),Object.defineProperty(n,"windowHeight",{get:function(){return window.innerHeight}}),Object.defineProperty(n,"drawingContext",{get:function(){return r}}),n.createCanvas=function(e,t){return n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t,g(),n.canvas},nM .resizeCanvas=function(e,t){n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t},n.createGraphics=n.createImage=function(t,n){let r=new e("offscreen");return r.createCanvas(t,n),r.noLoop(),r},n.pixelDensity=function(e){return null==e||(n._pixelDensity=e,n.canvas.width=Math.ceil(n.width*e),n.canvas.height=Math.ceil(n.height*e),n.canvas.style.width=n.width+"px",n.canvas.style.height=n.height+"px",r.scale(n._pixelDensity,n._pixelDensity),g()),n._pixelDensity},n.map=function(e,t,n,r,i,o){let a=r+1*(e-t)/(n-t)*(i-r)M ;return o?r<i?Math.min(Math.max(a,r),i):Math.min(Math.max(a,i),r):a},n.lerp=function(e,t,n){return e*(1-n)+t*n},n.constrain=function(e,t,n){return Math.min(Math.max(e,t),n)},n.dist=function(){return 4==arguments.length?Math.hypot(arguments[0]-arguments[2],arguments[1]-arguments[3]):Math.hypot(arguments[0]-arguments[3],arguments[1]-arguments[4],arguments[2]-arguments[5])},n.norm=function(e,t,r){return n.map(e,t,r,0,1)},n.sq=function(e){return e*e},n.fract=function(e){return e-Math.floor(e)},n.degrees=function(e){retM urn 180*e/Math.PI},n.radians=function(e){return e*Math.PI/180},n.abs=Math.abs,n.ceil=Math.ceil,n.exp=Math.exp,n.floor=Math.floor,n.log=Math.log,n.mag=Math.hypot,n.max=Math.max,n.min=Math.min,n.round=Math.round,n.sqrt=Math.sqrt,n.sin=Math.sin,n.cos=Math.cos,n.tan=Math.tan,n.asin=Math.asin,n.acos=Math.acos,n.atan=Math.atan,n.atan2=Math.atan2,n.Vector=function(e,t,r){let i=this;i.x=e||0,i.y=t||0,i.z=r||0;let o=null,a=null;function l(e,t,n){return null!=e.x?e:null!=t?{x:e,y:t,z:n||0}:{x:e,y:e,z:e}}function s(){null==a&M &(a=i.x*i.x+i.y*i.y+i.z*i.z,o=Math.sqrt(a))}function h(){a=null,o=null}i.set=function(e,t,n){i.x=e||0,i.y=t||0,i.z=n||0},i.copy=function(){return new n.Vector(i.x,i.y,i.z)},i.add=function(){let e=l.apply(null,arguments);return i.x+=e.x,i.y+=e.y,i.z+=e.z,h(),i},i.rem=function(){let e=l.apply(null,arguments);return i.x%=e.x,i.y%=e.y,i.z%=e.z,h(),i},i.sub=function(){let e=l.apply(null,arguments);return i.x-=e.x,i.y-=e.y,i.z-=e.z,h(),i},i.mult=function(){let e=l.apply(null,arguments);return i.x*=e.x,i.y*=e.y,i.z*=e.z,hM (),i},i.div=function(){let e=l.apply(null,arguments);return i.x/=e.x,i.y/=e.y,i.z/=e.z,h(),i},i.mag=function(){return s(),o},i.magSq=function(){return s(),a},i.dot=function(){let e=l.apply(null,arguments);return i.x*e.x+i.y*e.y+i.z*e.z},i.dist=function(){let e=l.apply(null,arguments),t=i.x-e.x,n=i.y-e.y,r=i.z-e.z;return Math.sqrt(t*t+n*n+r*r)},i.cross=function(){let e=l.apply(null,arguments),t=i.y*e.z-i.z*e.y,n=i.z*e.x-i.x*e.z,r=i.x*e.y-i.y*e.x;return i.x=t,i.y=n,i.z=r,h(),i},i.normalize=function(){s();let e=o;retuM rn i.x/=e,i.y/=e,i.z/=e,o=1,a=1,i},i.limit=function(e){s();if(o>e){let t=e/o;i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e}return i},i.setMag=function(e){s();let t=e/o;return i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e,i},i.heading=function(){return Math.atan2(i.y,i.x)},i.rotate=function(e){let t=Math.cos(e),n=Math.sin(e),r=i.x*t-i.y*n,o=i.x*n+i.y*t;return i.x=r,i.y=o,i},i.angleBetween=function(){let e=l.apply(null,arguments);const t=i.dot(e)/(i.mag()*e.mag());let n;return n=Math.acos(Math.min(1,Math.max(-1,t))),n*Math.sign(i.cross(e).z||1)},M i.lerp=function(e,t){return i.x=i.x*(1-t)+e.x*t,i.y=i.y*(1-t)+e.y*t,i.z=i.z*(1-t)+e.z*t,h(),i},i.reflect=function(e){return e.normalize(),i.sub(e.mult(2*i.dot(e)))},i.array=function(){return[i.x,i.y,i.z]},i.equals=function(e,t){return null==t&&null==(t=Number.EPSILON)&&(t=0),Math.abs(e.x-i.x)<t&&Math.abs(e.y-i.y)<t&&Math.abs(e.z-i.z)<t},i.fromAngle=function(e,t){return null==t&&(t=1),o=t,a=t*t,i.x=t*Math.cos(e),i.y=t*Math.sin(e),i.z=0,i},i.fromAngles=function(e,t,n){null==n&&(n=1),o=n,a=n*n;const r=Math.cos(t),l=MaM th.sin(t),s=Math.cos(e),h=Math.sin(e);return i.x=n*h*l,i.y=-n*s,i.z=n*h*r,i},i.random2D=function(){return o=1,a=1,i.fromAngle(Math.random()*Math.PI*2)},i.random3D=function(){return o=1,a=1,i.fromAngles(Math.random()*Math.PI*2,Math.random()*Math.PI*2)},i.toString=function(){return`[${i.x}, ${i.y}, ${i.z}]`}},n.Vector.add=function(e,t){return new n.Vector(e.x+t.x,e.y+t.y,e.z+t.z)},n.Vector.rem=function(e,t){return new n.Vector(e.x%t.x,e.y%t.y,e.z%t.z)},n.Vector.sub=function(e,t){return new n.Vector(e.x-t.x,e.y-t.y,e.M z-t.z)},n.Vector.mult=function(e,t){return null==t.x?new n.Vector(e.x*t,e.y*t,e.z*t):new n.Vector(e.x*t.x,e.y*t.y,e.z*t.z)},n.Vector.div=function(e,t){return null==t.x?new n.Vector(e.x/t,e.y/t,e.z/t):new n.Vector(e.x/t.x,e.y/t.y,e.z/t.z)},n.Vector.dist=function(e,t){return Math.hypot(e.x-t.x,e.y-t.y,e.z-t.z)},n.Vector.cross=function(e,t){return new n.Vector(e.y*t.z-e.z*t.y,e.z*t.x-e.x*t.z,e.x*t.y-e.y*t.x)},n.Vector.lerp=function(e,t,r){return new n.Vector(e.x*(1-r)+t.x*r,e.y=e.y*(1-r)+t.y*r,e.z=e.z*(1-r)+t.z*r)},n.M Vector.equals=function(e,t,n){return e.equals(t,n)};for(let e of["fromAngle","fromAngles","random2D","random3D"])n.Vector[e]=function(t,r,i){return(new n.Vector)[e](t,r,i)};function x(e,t,n){let r,i,o,a,l,s,h,c,u;if(0==t)return[255*(r=n),255*(i=n),255*(o=n)];switch((a=e)>360&&(a=0),h=n*(1-t),c=n*(1-t*(s=(a/=60)-(l=~~a))),u=n*(1-t*(1-s)),l){case 0:r=n,i=u,o=h;break;case 1:r=c,i=n,o=h;break;case 2:r=h,i=n,o=u;break;case 3:r=h,i=c,o=n;break;case 4:r=u,i=h,o=n;break;default:r=n,i=h,o=c}return[255*r,255*i,255*o]}functioM n g(){r.fillStyle="white",r.strokeStyle="black",r.lineCap="round",r.lineJoin="miter"}function p(e){if(0<=e&&e<2*Math.PI)return e;for(;e<0;)e+=2*Math.PI;for(;e>=Math.PI;)e-=2*Math.PI;return e}function m(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;let c=p(a),u=p(l);r.beginPath();for(let a=0;a<h+1;a++){let l=a/h,s=n.lerp(c,u,l),f=Math.cos(s)*i/2,d=Math.sin(s)*o/2;r[a?"lineTo":"moveTo"](e+f,t+d)}s==n.CHORD?r.closePath():s==n.PIE&&(r.lineTo(e,t),r.closePath()),n._style.noFill||r.fill(),n._style.noStrokM e||r.stroke()}function b(e,t,i,o){n._style.noFill&&n._style.noStroke||(r.beginPath(),r.ellipse(e,t,i/2,o/2,0,0,2*Math.PI),n._style.noFill||r.fill(),n._style.noStroke||r.stroke())}function y(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;if(null==a)return function(e,t,i,o){n._style.noFill||r.fillRect(e,t,i,o),n._style.noStroke||r.strokeRect(e,t,i,o)}(e,t,i,o);if(null==l)return y(e,t,i,o,a,a,a,a);const c=Math.min(Math.abs(o),Math.abs(i))/2;a=Math.min(c,a),l=Math.min(c,l),h=Math.min(c,h),s=Math.min(c,s)M ,r.beginPath(),r.moveTo(e+a,t),r.arcTo(e+i,t,e+i,t+o,l),r.arcTo(e+i,t+o,e,t+o,s),r.arcTo(e,t+o,e,t,h),r.arcTo(e,t,e+i,t,a),r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke()}function w(){a=[]}n.createVector=function(e,t,r){return new n.Vector(e,t,r)},n.curvePoint=function(e,t,n,r,i){const o=i*i*i,a=i*i;return e*(-.5*o+a-.5*i)+t*(1.5*o-2.5*a+1)+n*(-1.5*o+2*a+.5*i)+r*(.5*o-.5*a)},n.bezierPoint=function(e,t,n,r,i){const o=1-i;return Math.pow(o,3)*e+3*Math.pow(o,2)*i*t+3*o*Math.pow(i,2)*n+Math.pow(i,M 3)*r},n.curveTangent=function(e,t,n,r,i){const o=i*i;return e*(-3*o/2+2*i-.5)+t*(9*o/2-5*i)+n*(-9*o/2+4*i+.5)+r*(3*o/2-i)},n.bezierTangent=function(e,t,n,r,i){const o=1-i;return 3*r*Math.pow(i,2)-3*n*Math.pow(i,2)+6*n*o*i-6*t*o*i+3*t*Math.pow(o,2)-3*e*Math.pow(o,2)},n.Color=function(e,t,n,r){let i=this;i.MAGIC=786698,i._r=e,i._g=t,i._b=n,i._a=r,i._h=0,i._s=0,i._v=0,i._hsvInferred=!1,i.setRed=function(e){i._r=e,i._hsvInferred=!1},i.setGreen=function(e){i._g=e,i._hsvInferred=!1},i.setBlue=function(e){i._b=e,i._hsvInfM erred=!1},i.setAlpha=function(e){i._a=e/255,i._hsvInferred=!1},i._inferHSV=function(){i._hsvInferred||([i._h,i._s,i._v]=function(e,t,n){let r,i,o,a,l;return r=e<t?e<n?e:n:t<n?t:n,0==(l=100*(i=e>t?e>n?e:n:t>n?t:n)/255)?[o=0,a=0,l]:0==(a=100*(i-r)/i)?[o=0,a,l]:(o=i==e?0+60*(t-n)/(i-r):i==t?120+60*(n-e)/(i-r):240+60*(e-t)/(i-r),[o,a,l])}(i._r,i._g,i._b),i._hsvInferred=!0)},i.toString=function(){return`rgba(${Math.round(i._r)},${Math.round(i._g)},${Math.round(i._b)},${~~(1e3*i._a)/1e3})`}},n.colorMode=function(e){n._stM yle.colorMode=e},n.color=function(){if(1==arguments.length&&786698==arguments[0].MAGIC)return arguments[0];if(n._style.colorMode==n.RGB){if(1==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],1);if(2==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],arguments[1]/255);if(3==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],1);if(4==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],arguments[3]/255)}else{if(1==argumeM nts.length)return new n.Color(...x(0,0,arguments[0]/100),1);if(2==arguments.length)return new n.Color(...x(0,0,arguments[0]/100),arguments[1]/255);if(3==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),1);if(4==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),arguments[3])}return null},n.red=function(e){return e._r},n.green=function(e){return e._g},n.blue=function(e){return e._b},n.alpha=function(e){return 255*e._a},n.hue=function(e){reM turn e._inferHSV(),e._h},n.saturation=function(e){return e._inferHSV(),e._s},n.brightness=function(e){return e._inferHSV(),e._v},n.lightness=function(e){return 100*(.2126*e._r+.7152*e._g+.0722*e._b)/255},n.lerpColor=function(e,t,r){return n._style.colorMode==n.RGB?new n.Color(n.constrain(n.lerp(e._r,t._r,r),0,255),n.constrain(n.lerp(e._g,t._g,r),0,255),n.constrain(n.lerp(e._b,t._b,r),0,255),n.constrain(n.lerp(e._a,t._a,r),0,1)):(e._inferHSV(),t._inferHSV(),new n.Color(n.constrain(function(e,t,r){var i=[[Math.abs(t-M e),n.map(r,0,1,e,t)],[Math.abs(t+360-e),n.map(r,0,1,e,t+360)],[Math.abs(t-360-e),n.map(r,0,1,e,t-360)]];return i.sort(((e,t)=>e[0]-t[0])),(i[0][1]+720)%360}(e._h,t._h,r),0,360),n.constrain(n.lerp(e._s,t._s,r),0,100),n.constrain(n.lerp(e._v,t._v,r),0,100),n.constrain(n.lerp(e._a,t._a,r),0,1)))},n.strokeWeight=function(e){n._style_noStroke=!1,r.lineWidth=e},n.stroke=function(){if(n._style.noStroke=!1,"string"==typeof arguments[0])return void(r.strokeStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._sM tyle.noStroke=!0:r.strokeStyle=e},n.noStroke=function(){n._style.noStroke=!0},n.fill=function(){if(n._style.noFill=!1,"string"==typeof arguments[0])return void(r.fillStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._style.noFill=!0:r.fillStyle=e},n.noFill=function(){n._style.noFill=!0},n.blendMode=function(e){r.globalCompositeOperation=e},n.strokeCap=function(e){r.lineCap=e},n.strokeJoin=function(e){r.lineJoin=e},n.ellipseMode=function(e){n._style.ellipseMode=e},n.rectMode=function(e){n._style.rectM Mode=e},n.curveDetail=function(e){n._style.curveDetail=e},n.curveAlpha=function(e){n._style.curveAlpha=e},n.curveTightness=function(e){n._style.curveAlpha=e},n.clear=function(){r.clearRect(0,0,n.width,n.height)},n.background=function(){if(arguments[0]&&arguments[0].MAGIC==n.MAGIC)return n.image(arguments[0],0,0,n.width,n.height);r.save(),r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity),r.fillStyle="string"==typeof arguments[0]?arguments[0]:n.color(...Array.from(arguments)),r.fillRect(0,0,n.width,n.heightM ),r.restore()},n.line=function(e,t,i,o){n._style.noStroke||(r.beginPath(),r.moveTo(e,t),r.lineTo(i,o),r.stroke())},n.arc=function(e,t,r,i,o,a,l,s){if(o==a)return n.ellipse(e,t,r,i);null==s&&(s=25),null==l&&(l=n.PIE),n._style.ellipseMode==n.CENTER?m(e,t,r,i,o,a,l,s):n._style.ellipseMode==n.RADIUS?m(e,t,2*r,2*i,o,a,l,s):n._style.ellipseMode==n.CORNER?m(e+r/2,t+i/2,r,i,o,a,l,s):n._style.ellipseMode==n.CORNERS&&m((e+r)/2,(t+i)/2,r-e,i-t,o,a,l,s)},n.ellipse=function(e,t,r,i){null==i&&(i=r),n._style.ellipseMode==n.CENTERM ?b(e,t,r,i):n._style.ellipseMode==n.RADIUS?b(e,t,2*r,2*i):n._style.ellipseMode==n.CORNER?b(e+r/2,t+i/2,r,i):n._style.ellipseMode==n.CORNERS&&b((e+r)/2,(t+i)/2,r-e,i-t)},n.circle=function(e,t,r){return n.ellipse(e,t,r,r)},n.point=function(e,t){e.x&&(t=e.y,e=e.x),r.beginPath(),r.ellipse(e,t,.4,.4,0,0,2*Math.PI),r.stroke()},n.rect=function(e,t,r,i,o,a,l,s){n._style.rectMode==n.CENTER?y(e-r/2,t-i/2,r,i,o,a,l,s):n._style.rectMode==n.RADIUS?y(e-r,t-i,2*r,2*i,o,a,l,s):n._style.rectMode==n.CORNER?y(e,t,r,i,o,a,l,s):n._stylM e.rectMode==n.CORNERS&&y(e,t,r-e,i-t,o,a,l,s)},n.square=function(e,t,r,i,o,a,l){return n.rect(e,t,r,r,i,o,a,l)},n.beginShape=function(){w(),r.beginPath(),o=!0},n.beginContour=function(){r.closePath(),w(),o=!0},n.endContour=function(){w(),o=!0},n.vertex=function(e,t){w(),o?r.moveTo(e,t):r.lineTo(e,t),o=!1},n.bezierVertex=function(e,t,n,i,o,a){w(),r.bezierCurveTo(e,t,n,i,o,a)},n.quadraticVertex=function(e,t,n,i){w(),r.quadraticCurveTo(e,t,n,i)},n.bezier=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.bezierVM ertex(r,i,o,a,l,s),n.endShape()},n.triangle=function(e,t,r,i,o,a){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.endShape(n.CLOSE)},n.quad=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.vertex(l,s),n.endShape(n.CLOSE)},n.endShape=function(e){w(),e&&r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke(),n._style.noFill&&n._style.noStroke&&(r.save(),r.fillStyle="none",r.fill(),r.restore())},n.curveVertex=function(e,t){if(a.push([e,t]),a.length<4)return;M let i=function(e,t,n,r,i,o,a,l,s,h){function c(e,t,n,r,i,o){let a=Math.pow(r-t,2)+Math.pow(i-n,2);return Math.pow(a,.5*o)+e}let u=[],f=c(0,e,t,n,r,h),d=c(f,n,r,i,o,h),x=c(d,i,o,a,l,h);for(let h=0;h<s;h++){let c=f+h/(s-1)*(d-f),g=[(f-c)/(f-0),(c-0)/(f-0),(d-c)/(d-f),(c-f)/(d-f),(x-c)/(x-d),(c-d)/(x-d),(d-c)/(d-0),(c-0)/(d-0),(x-c)/(x-f),(c-f)/(x-f)];for(let e=0;e<g.length;e+=2)isNaN(g[e])&&(g[e]=1,g[e+1]=0),isFinite(g[e])||(g[e]>0?(g[e]=1,g[e+1]=0):(g[e]=0,g[e+1]=1));let p=e*g[0]+n*g[1],m=t*g[0]+r*g[1],b=n*g[2]+i*g[M 3],y=r*g[2]+o*g[3],w=i*g[4]+a*g[5],v=o*g[4]+l*g[5],z=p*g[6]+b*g[7],V=m*g[6]+y*g[7],_=b*g[8]+w*g[9],M=y*g[8]+v*g[9],E=z*g[2]+_*g[3],S=V*g[2]+M*g[3];u.push([E,S])}return u}(...a[a.length-4],...a[a.length-3],...a[a.length-2],...a[a.length-1],n._style.curveDetail,n._style.curveAlpha);for(let e=0;e<i.length;e++)o?r.moveTo(...i[e]):r.lineTo(...i[e]),o=!1},n.curve=function(e,t,r,i,o,a,l,s){n.beginShape(),n.curveVertex(e,t),n.curveVertex(r,i),n.curveVertex(o,a),n.curveVertex(l,s),n.endShape()},n.translate=function(e,t){r.tM ranslate(e,t)},n.rotate=function(e){r.rotate(e)},n.scale=function(e,t){null==t&&(t=e),r.scale(e,t)},n.applyMatrix=function(e,t,n,i,o,a){r.transform(e,t,n,i,o,a)},n.shearX=function(e){r.transform(1,0,Math.tan(e),1,0,0)},n.shearY=function(e){r.transform(1,Math.tan(e),0,1,0,0)},n.resetMatrix=function(){r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity)},n.pushMatrix=n.push=function(){n._styleCache.push({...n._style}),n._style=n._styleCache[n._styleCache.length-1],r.save()},n.popMatrix=n.pop=function(){n._stylM eCache.length-1&&(n._styleCache.pop(),n._style=n._styleCache[n._styleCache.length-1],r.restore())},n.image=function(e,t,i,o,a,l,s,h,c){let u=e.MAGIC==n.MAGIC?e.canvas:e;function d(){if(e.MAGIC!=n.MAGIC||!n._tint)return;let t=e.canvas.getContext("2d");t.save(),t.resetTransform(),t.clearRect(0,0,t.canvas.width,t.canvas.height),t.drawImage(f.canvas,0,0),t.restore()}return e.MAGIC==n.MAGIC&&null!=n._tint&&(function(e,t){null==f&&(f=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvasM .height),f.canvas.width==e&&f.canvas.height==t||(f.canvas.width=e,f.canvas.height=t)}(e.canvas.width,e.canvas.height),f.drawImage(e.canvas,0,0),e.tinted(n._tint)),o?l?(h||(h=u.width),c||(c=u.height),r.drawImage(u,l,s,h,c,t,i,o,a),void d()):(r.drawImage(u,t,i,o,a),void d()):(e.MAGIC==n.MAGIC||e.width?r.drawImage(u,t,i,e.width,e.height):r.drawImage(u,t,i,e.videoWidth,e.videoHeight),void d())},n.loadPixels=function(){l=r.getImageData(0,0,n.canvas.width,n.canvas.height),n.pixels=l.data},n.updatePixels=function(){null!=M l&&r.putImageData(l,0,0)},n.loadImage=function(e,t){s++;let r=n.createGraphics(100,100),i=r.canvas.getContext("2d"),o=new Image;return o.src=e,o.crossOrigin="Anonymous",o.onload=function(){i.canvas.width=o.width,i.canvas.height=o.height,r.width=o.width,r.height=o.height,i.drawImage(o,0,0),s--,t&&t(r)},r};let v={};function z(e,t){null==u&&(u=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvas.height),u.canvas.width==e&&u.canvas.height==t||(u.canvas.width=e,u.canvas.height=t)}funcM tion V(){let e=r.canvas.width*r.canvas.height*4;null!=d&&e==d.length||(d=new Uint8ClampedArray(e))}function _(e){u.clearRect(0,0,u.canvas.width,u.canvas.height),u.filter=e,u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()}v[n.THRESHOLD]=function(e,t){null==t?t=127.5:t*=255;for(let n=0;n<e.length;n+=4){const r=.2126*e[n]+.7152*e[n+1]+.0722*e[n+2];e[n]=e[n+1]=e[n+2]=r>=t?255:0}},v[n.GRAY]=function(e){for(let t=0;t<e.length;t+=4)M {const n=.2126*e[t]+.7152*e[t+1]+.0722*e[t+2];e[t]=e[t+1]=e[t+2]=n}},v[n.OPAQUE]=function(e){for(let t=0;t<e.length;t+=4)e[t+3]=255},v[n.INVERT]=function(e){for(let t=0;t<e.length;t+=4)e[t]=255-e[t],e[t+1]=255-e[t+1],e[t+2]=255-e[t+2]},v[n.POSTERIZE]=function(e,t){let n=t-1;for(let r=0;r<e.length;r+=4)e[r]=255*(e[r]*t>>8)/n,e[r+1]=255*(e[r+1]*t>>8)/n,e[r+2]=255*(e[r+2]*t>>8)/n},v[n.DILATE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-M 1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.max(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.ERODE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.min(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.BLURM ]=function(e,t){t=t||1,t=Math.floor(t*n._pixelDensity),V(),d.set(e);let i=2*t+1,o=function(e){let n=new Float32Array(e),r=.3*t+.8,i=r*r*2;for(let t=0;t<e;t++){let o=t-e/2,a=Math.exp(-o*o/i)/(2.5066282746*r);n[t]=a}return n}(i),[a,l]=[r.canvas.width,r.canvas.height];for(let n=0;n<l;n++)for(let r=0;r<a;r++){let l=0,s=0,h=0,c=0;for(let e=0;e<i;e++){let i=4*(n*a+Math.min(Math.max(r-t+e,0),a-1));l+=d[i]*o[e],s+=d[i+1]*o[e],h+=d[i+2]*o[e],c+=d[i+3]*o[e]}let u=4*(n*a+r);e[u]=l,e[u+1]=s,e[u+2]=h,e[u+3]=c}d.set(e);for(let nM =0;n<l;n++)for(let r=0;r<a;r++){let s=0,h=0,c=0,u=0;for(let e=0;e<i;e++){let i=4*(Math.min(Math.max(n-t+e,0),l-1)*a+r);s+=d[i]*o[e],h+=d[i+1]*o[e],c+=d[i+2]*o[e],u+=d[i+3]*o[e]}let f=4*(n*a+r);e[f]=s,e[f+1]=h,e[f+2]=c,e[f+3]=u}},n.filter=function(e,t){if(n.HARDWARE_FILTERS&&null!=r.filter)if(z(),e==n.THRESHOLD){null==t&&(t=.5),t=Math.max(t,1e-5),_(`saturate(0%) brightness(${Math.floor(.5/t*100)}%) contrast(1000000%)`)}else if(e==n.GRAY)_("saturate(0%)");else if(e==n.OPAQUE)u.fillStyle="black",u.fillRect(0,0,u.canvaM s.width,u.canvas.height),u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.drawImage(u.canvas,0,0),r.restore();else if(e==n.INVERT)_("invert(100%)");else if(e==n.BLUR)_(`blur(${Math.ceil(t*n._pixelDensity/1)||1}px)`);else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}},n.resize=function(e,t){z(),u.drawImage(r.canvas,0,0),n.width=e,n.height=t,r.canvas.width=e*n._pixM elDensity,r.canvas.height=t*n._pixelDensity,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0,r.canvas.width,r.canvas.height),r.restore()},n.get=function(e,t,i,o){if(null!=e&&null==i){let i=r.getImageData(e,t,1,1).data;return new n.Color(i[0],i[1],i[2],i[3]/255)}e=e||0,t=t||0,i=i||n.width,o=o||n.height;let a=n.createGraphics(i,o);a.pixelDensity(n._pixelDensity);let l=r.getImageData(e*n._pixelDensity,t*n._pixelDensity,i*n._pixelDensity,o*n._pixelDensity);return a.caM nvas.getContext("2d").putImageData(l,0,0),a},n.set=function(e,t,i){if(i.MAGIC==n.MAGIC){let r=n._tint;return n._tint=null,n.image(i,e,t),void(n._tint=r)}let o=4*(t*n._pixelDensity*r.canvas.width+e*n._pixelDensity);n.pixels[o]=i._r,n.pixels[o+1]=i._g,n.pixels[o+2]=i._b,n.pixels[o+3]=255*i._a},n.tinted=function(){let e=n.color(...Array.from(arguments)),t=e._a;e._a=1,z(),u.clearRect(0,0,u.canvas.width,u.canvas.height),u.fillStyle=e,u.fillRect(0,0,u.canvas.width,u.canvas.height),u.globalCompositeOperation="multiply",u.M drawImage(r.canvas,0,0),u.globalCompositeOperation="source-over",r.save(),r.resetTransform();let i=r.globalCompositeOperation;r.globalCompositeOperation="source-in",r.drawImage(u.canvas,0,0),r.globalCompositeOperation=i,r.restore(),u.globalAlpha=t,u.clearRect(0,0,u.canvas.width,u.canvas.height),u.drawImage(r.canvas,0,0),u.globalAlpha=1,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()},n.tint=function(){n._tint=n.color(...Array.from(arguments))},n.noTiM nt=function(){n._tint=null},n.mask=function(e){r.save(),r.resetTransform();let t=r.globalCompositeOperation;r.globalCompositeOperation="destination-in",r.drawImage(e.canvas,0,0),r.globalCompositeOperation=t,r.restore()},n.clearTemporaryBuffers=function(){u=null,f=null,d=null},n.save=function(e,t){e=e||"untitled",t=t||"png";var n=document.createElement("a");n.innerHTML="[Download]",n.addEventListener("click",(function(){this.href=r.canvas.toDataURL(),this.download=e+"."+t}),!1),document.body.appendChild(n),n.click()M ,document.body.removeChild(n)},n.saveCanvas=function(e,t,r){if(e.MAGIC==n.MAGIC){r&&e.save(t,r);let n=t.split(".");return e.save(n.slice(0,-1).join("."),n[n.length-1])}if(t)return n.save(e,t);let i=e.split(".");return n.save(i.slice(0,-1).join("."),i[i.length-1])},n.loadFont=function(e){let t=e.split("/"),n=t[t.length-1].split(".")[0].replace(" ",""),r=`@font-face {\n font-family: '${n}';\n src: url('${e}');\n }`;const i=document.createElement("style");return i.textContent=r,document.head.append(M i),n},n.textFont=function(e){n._style.textFont=e},n.textSize=function(e){n._style.textSize=e,n._style.textLeading=e},n.textLeading=function(e){n._style.textLeading=e},n.textStyle=function(e){n._style.textStyle=e},n.textAlign=function(e,t){r.textAlign=e,t&&(r.textBaseline=t==n.CENTER?"middle":t)},n.text=function(e,t,i,o){if(!e)return;if(e=e.toString(),n._style.noFill&&n._style.noStroke)return;r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`;let a=e.split("\n");for(let e=0;e<a.length;e++)n._M style.noFill||r.fillText(a[e],t,i,o),n._style.noStroke||r.strokeText(a[e],t,i,o),i+=n._style.textLeading},n.textWidth=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).width},n.textAscent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBoundingBoxAscent},n.textDescent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBounM dingBoxDescent};var M,E=4,S=.5,R=function(e){return.5*(1-Math.cos(e*Math.PI))};n.noise=function(e,t,n){if(t=t||0,n=n||0,null==M){M=new Array(4096);for(var r=0;r<4096;r++)M[r]=Math.random()}e<0&&(e=-e),t<0&&(t=-t),n<0&&(n=-n);for(var i,o,a,l,s,h=Math.floor(e),c=Math.floor(t),u=Math.floor(n),f=e-h,d=t-c,x=n-u,g=0,p=.5,m=0;m<E;m++){var b=h+(c<<4)+(u<<8);i=R(f),o=R(d),a=M[4095&b],a+=i*(M[b+1&4095]-a),l=M[b+16&4095],a+=o*((l+=i*(M[b+16+1&4095]-l))-a),l=M[4095&(b+=256)],l+=i*(M[b+1&4095]-l),s=M[b+16&4095],l+=o*((s+=i*(M[M b+16+1&4095]-s))-l),g+=(a+=R(x)*(l-a))*p,p*=S,h<<=1,c<<=1,u<<=1,(f*=2)>=1&&(h++,f--),(d*=2)>=1&&(c++,d--),(x*=2)>=1&&(u++,x--)}return g},n.noiseDetail=function(e,t){e>0&&(E=e),t>0&&(S=t)};const I=function(){let e,t,n=4294967295;return{setSeed(r){e=t=(null==r?Math.random()*n:r)>>>0},getSeed:()=>t,rand:()=>(e^=e<<17,e^=e>>13,((e^=e<<5)>>>0)/n)}};let C=I();C.setSeed(),n.noiseSeed=function(e){let t=null==e?4294967295*Math.random():e;M||(M=new Float32Array(4096));for(var n=0;n<4096;n++)t^=t<<17,t^=t>>13,t^=t<<5,M[n]=(t>M >>0)/4294967295},n.randomSeed=function(e){C.setSeed(e)},n.random=function(e,t){return null==e?C.rand():"number"==typeof e?null!=t?C.rand()*(t-e)+e:C.rand()*e:e[~~(e.length*C.rand())]},n.randomGenerator=function(e){e==n.LCG?C=function(){const e=4294967296;let t,n;return{setSeed(r){n=t=(null==r?Math.random()*e:r)>>>0},getSeed:()=>t,rand:()=>(n=(1664525*n+1013904223)%e)/e}}():e==n.SHR3&&(C=I()),C.setSeed()};var T=new function(){var e,t,n,r=new Array(128),i=new Array(256),o=new Array(128),a=new Array(128),l=new Array(2M 56),s=new Array(256),h=function(){return 4294967296*C.rand()-2147483648},c=function(){return.5+2.328306e-10*(h()<<0)};this.SHR3=h,this.UNI=c,this.RNOR=function(){return n=h(),e=127&n,Math.abs(n)<r[e]?n*o[e]:function(){for(var t,i,l,s,u=3.44262;;){if(t=n*o[e],0==e){do{l=c(),s=c(),t=.2904764*-Math.log(l),i=-Math.log(s)}while(i+i<t*t);return n>0?u+t:-u-t}if(a[e]+c()*(a[e-1]-a[e])<Math.exp(-.5*t*t))return t;if(n=h(),e=127&n,Math.abs(n)<r[e])return n*o[e]}}()},this.REXP=function(){return(t=h()>>>0)<r[e=255&t]?t*l[e]:funM ction(){for(var n;;){if(0==e)return 7.69711-Math.log(c());if(n=t*l[e],s[e]+c()*(s[e-1]-s[e])<Math.exp(-n))return n;if((t=h())<i[e=255&t])return t*l[e]}}()},this.zigset=function(){var e,t,n=2147483648,h=4294967296,c=3.442619855899,u=c,f=.00991256303526217,d=7.697117470131487,x=d,g=.003949659822581572;for(e=f/Math.exp(-.5*c*c),r[0]=Math.floor(c/e*n),r[1]=0,o[0]=e/n,o[127]=c/n,a[0]=1,a[127]=Math.exp(-.5*c*c),t=126;t>=1;t--)c=Math.sqrt(-2*Math.log(f/c+Math.exp(-.5*c*c))),r[t+1]=Math.floor(c/u*n),u=c,a[t]=Math.exp(-.5*cM *c),o[t]=c/n;for(e=g/Math.exp(-d),i[0]=Math.floor(d/e*h),i[1]=0,l[0]=e/h,l[255]=d/h,s[0]=1,s[255]=Math.exp(-d),t=254;t>=1;t--)d=-Math.log(g/d+Math.exp(-d)),i[t+1]=Math.floor(d/x*h),x=d,s[t]=Math.exp(-d),l[t]=d/h}};T.hasInit=!1,n.randomGaussian=function(e,t){return T.hasInit||(T.zigset(),T.hasInit=!0),T.RNOR()*t+e},n.randomExponential=function(){return T.hasInit||(T.zigset(),T.hasInit=!0),T.REXP()},n.print=console.log,n.cursor=function(e,t,r){let i="";e.includes(".")&&(e=`url("${e}")`,i=", auto"),null!=t&&(e+=" "+t+M " "+r),n.canvas.style.cursor=e+i},n.noCursor=function(){n.canvas.style.cursor="none"},n.createCapture=function(e){var t=document.createElement("video");return t.playsinline="playsinline",t.autoplay="autoplay",navigator.mediaDevices.getUserMedia(e).then((function(e){t.srcObject=e})),t.style.position="absolute",t.style.opacity=1e-5,t.style.zIndex=-1e3,document.body.appendChild(t),t};let A=["setup","draw","preload","mouseMoved","mousePressed","mouseReleased","mouseDragged","mouseClicked","keyPressed","keyReleased","keM yTyped","touchStarted","touchEnded"];for(let e of A){let t="_"+e+"Fn";n[t]=function(){},n[t].isPlaceHolder=!0,n[e]?n[t]=n[e]:Object.defineProperty(n,e,{set:function(e){n[t]=e}})}function D(){n._noLoop||(i=null==n._frameRate?requestAnimationFrame(D):setTimeout(D,1e3/n._frameRate)),w(),o=!0,n.push(),n._drawFn(),n.pop(),++n.frameCount}function k(e){const t=n.canvas.getBoundingClientRect(),r=n.canvas.scrollWidth/n.width||1,i=n.canvas.scrollHeight/n.height||1;return{x:(e.clientX-t.left)/r,y:(e.clientY-t.top)/i,id:e.idenM tifier}}function L(){return n._touchStarted.isPlaceHolder&&n._touchMoved.isPlaceHolder&&n._touchEnded.isPlaceHolder}n.noLoop=function(){n._noLoop=!0,i=null},n.loop=function(){n._noLoop=!1,null==i&&D()},n.redraw=function(){D()},n.frameRate=function(e){n._frameRate=e},setTimeout((function(){n._preloadFn(),c=window.performance.now(),function e(){if(s>0)return setTimeout(e,10);n._setupFn(),D()}()}),1),n.canvas.onmousemove=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPM ressed?n._mouseDraggedFn(e):n._mouseMovedFn(e)},n.canvas.onmousedown=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!0,n.mouseButton=[n.LEFT,n.CENTER,n.RIGHT][e.button],n._mousePressedFn(e)},n.canvas.onmouseup=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!1,n._mouseReleasedFn(e)},n.canvas.onclick=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressedM =!0,n._mouseClickedFn(e),n.mouseIsPressed=!1},window.addEventListener("keydown",(function(e){n.keyIsPressed=!0,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!0,n._keyPressedFn(e),1==e.key.length&&n._keyTypedFn(e)})),window.addEventListener("keyup",(function(e){n.keyIsPressed=!1,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!1,n._keyReleasedFn(e)})),n.keyIsDown=function(e){return!!h[e]},n.canvas.ontouchstart=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.moM useY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mousePressedFn(e)||e.preventDefault()),n._touchStartedFn(e)||e.preventDefault()},n.canvas.ontouchmove=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mouseDraggedFn(e)||e.preventDefault()),n._touchMovedFn(e)||e.preventDefault()},n.canvas.ontouchend=n.canvas.ontouchcancel=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.M mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!1,n._mouseReleasedFn(e)||e.preventDefault()),n._touchEndedFn(e)||e.preventDefault()},n.hasSensorPermission=!window.DeviceOrientationEvent&&!window.DeviceMotionEvent||!(DeviceOrientationEvent.requestPermission||DeviceMotionEvent.requestPermission),n.requestSensorPermissions=function(){DeviceOrientationEvent.requestPermission&&DeviceOrientationEvent.requestPermission().then((e=>{"granted"==e&&DeviceMotionEvent.requestPermissioM n&&DeviceMotionEvent.requestPermission().then((e=>{"granted"==e&&(n.hasSensorPermission=!0)})).catch(alert)})).catch(alert)},window.ondeviceorientation=function(e){n.pRotationX=n.rotationX,n.pRotationY=n.rotationY,n.pRotationZ=n.rotationZ,n.pRelRotationX=n.relRotationX,n.pRelRotationY=n.relRotationY,n.pRelRotationZ=n.relRotationZ,n.rotationX=e.beta*(Math.PI/180),n.rotationY=e.gamma*(Math.PI/180),n.rotationZ=e.alpha*(Math.PI/180),n.relRotationX=[-n.rotationY,-n.rotationX,n.rotationY][1+~~(window.orientation/90)],n.rM elRotationY=[-n.rotationX,n.rotationY,n.rotationX][1+~~(window.orientation/90)],n.relRotationZ=n.rotationZ},window.ondevicemotion=function(e){if(n.pAccelerationX=n.accelerationX,n.pAccelerationY=n.accelerationY,n.pAccelerationZ=n.accelerationZ,!e.acceleration){let t=((e,t)=>[(e[0]*t[0]+e[1]*t[1]+e[2]*t[2]+e[3])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[4]*t[0]+e[5]*t[1]+e[6]*t[2]+e[7])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[8]*t[0]+e[9]*t[1]+e[10]*t[2]+e[11])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15])])(((e,t)M =>[e[0]*t[0]+e[1]*t[4]+e[2]*t[8]+e[3]*t[12],e[0]*t[1]+e[1]*t[5]+e[2]*t[9]+e[3]*t[13],e[0]*t[2]+e[1]*t[6]+e[2]*t[10]+e[3]*t[14],e[0]*t[3]+e[1]*t[7]+e[2]*t[11]+e[3]*t[15],e[4]*t[0]+e[5]*t[4]+e[6]*t[8]+e[7]*t[12],e[4]*t[1]+e[5]*t[5]+e[6]*t[9]+e[7]*t[13],e[4]*t[2]+e[5]*t[6]+e[6]*t[10]+e[7]*t[14],e[4]*t[3]+e[5]*t[7]+e[6]*t[11]+e[7]*t[15],e[8]*t[0]+e[9]*t[4]+e[10]*t[8]+e[11]*t[12],e[8]*t[1]+e[9]*t[5]+e[10]*t[9]+e[11]*t[13],e[8]*t[2]+e[9]*t[6]+e[10]*t[10]+e[11]*t[14],e[8]*t[3]+e[9]*t[7]+e[10]*t[11]+e[11]*t[15],e[12]*t[0]+M e[13]*t[4]+e[14]*t[8]+e[15]*t[12],e[12]*t[1]+e[13]*t[5]+e[14]*t[9]+e[15]*t[13],e[12]*t[2]+e[13]*t[6]+e[14]*t[10]+e[15]*t[14],e[12]*t[3]+e[13]*t[7]+e[14]*t[11]+e[15]*t[15]])((e=>[Math.cos(e),0,Math.sin(e),0,0,1,0,0,-Math.sin(e),0,Math.cos(e),0,0,0,0,1])(n.rotationY),(e=>[1,0,0,0,0,Math.cos(e),-Math.sin(e),0,0,Math.sin(e),Math.cos(e),0,0,0,0,1])(n.rotationX)),[0,0,-9.80665]);n.accelerationX=e.accelerationIncludingGravity.x+t[0],n.accelerationY=e.accelerationIncludingGravity.y+t[1],n.accelerationZ=e.accelerationIncludM ingGravity.z-t[2]}},n.year=function(){return(new Date).getFullYear()},n.day=function(){return(new Date).getDay()},n.hour=function(){return(new Date).getHours()},n.minute=function(){return(new Date).getMinutes()},n.second=function(){return(new Date).getSeconds()},n.millis=function(){return window.performance.now()-c}}(e)}"object"==typeof exports&&"undefined"!=typeof module&&(module.exports=e);const t="https://ancient-crimson-rain.btc.discover.quiknode.pro/c268fb026303ae8443f785200f2ea4b82f0082dd";function n(e){P(e)?M localStorage.removeItem("blocksApiEndpoint"):localStorage.blocksApiEndpoint=e}function r(){return localStorage.blocksApiEndpoint||t}function i(e){P(e)?localStorage.removeItem("modelInscriptionEndpoint"):localStorage.modelInscriptionEndpoint=e}function o(){return localStorage.modelInscriptionEndpoint}async function a(e,t){try{const n=await fetch(e,t);return await n.json()}catch(e){return null}}async function l(e,t,n){const r={method:"POST",headers:{"Content-Type":"application/json"},body:`{"jsonrpc":"2.0","id":1,"meM thod":"${t}","params":${`[${n.join(sep=",")}]`}}`};return(await a(e,r))?.result}async function s(e){const n={avgfee:10,time:Date.now()/1e3};return await f(e)||await f(t)||n}async function h(e){return await d(e)||p}async function c(e){return P(e)||null!=await f(e)}async function u(e){return P(e)||null!=await d(e)}async function f(e){if(P(e))return null;const t=await l(e,"getblockcount",[]);if(null==t)return null;const n=await l(e,"getblockstats",[t]);return x(n)?n:null}async function d(e){if(P(e))return null;const tM =await a(e,{});return g(t)?t:null}function x(e){return"number"==typeof e?.time&&"number"==typeof e?.avgfee}function g(e){if(null==e)return!1;const{classes_name:t,training_traits:n,layers_config:r,weight_b64:i}=e;if(!Array.isArray(t))return!1;if(null==n)return!1;try{j(r,i)}catch(e){return!1}return!0}const p={"model_name": "pfp_classifier_248", "layers_config": {"config": {"layers": [{"class_name": "InputLayer", "config": {"batch_input_shape": [null, 28, 28, 3]}}, {"class_name": "Rescaling", "config": {"scale": 0.007M 84313725490196, "offset": -1}}, {"class_name": "Flatten"}, {"class_name": "Dense", "config": {"units": 8, "activation": "leaky_relu"}}, {"class_name": "Dense", "config": {"units": 5, "activation": "leaky_relu"}}, {"class_name": "Dense", "config": {"units": 9, "activation": "leaky_relu"}}, {"class_name": "Dense", "config": {"units": 11, "activation": "leaky_relu"}}, {"class_name": "Dense", "config": {"units": 4, "activation": "leaky_relu"}}, {"class_name": "Dense", "config": {"units": 4, "activation": "leaky_relu"}}M , {"class_name": "Dense", "config": {"units": 11, "activation": "leaky_relu"}}, {"class_name": "Dense", "config": {"units": 9, "activation": "leaky_relu"}}, {"class_name": "Dense", "config": {"units": 5, "activation": "leaky_relu"}}, {"class_name": "Dense", "config": {"units": 8, "activation": "leaky_relu"}}, {"class_name": "Dense", "config": {"units": 4, "activation": "linear"}}]}}, "weight_b64": "8AEJPBWPjrycg6Y9htUsvEE2P7zfzHK8ZvC/PQC7Jr1c7q09KKR5vdCdrDtw0PE87V6rPFLIm71yTE49jg12PaDr7rrQqu278drkPL8N8DqV7fs9b1z+uTM 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 1Q7r2AC628tYjSPezKIz2KuI498vHdvfc/lT0CC3I9oeoSvZ6ArzyqrnA9H1aqPeqlM70Ilpg68I9WPf/Jgb2+UpA9gp+BvSo+ID5V/gg9pcEIvjnG2b3yq7w9GENdPWEIAL7d05I8xs/ZPXfMZroyIxs9S/PdvEm0cz1lsHE9k//bvFrU8DyU+RA+yBTEPc6ZJT2IkZU8I1PJPCnirr3zmpo9pC7xu5Yh3z3uUmS8fpKCvT5Bx7wJepI87Ng9PR/BSr3zr6I7AbYIPqWVADz1zc89b6CKvbv8WD3GLxk7IvAxvaFUJj3cQQo7iB/dPJnp9LrY2wy9MUiMPaYCqbzo/589W6uMPICDXT1o0Cq9Iu2Yvag4Lb0uiAG70cM1O5v/5b0+opI80iCvuyX3vbwnbN09nbSlvKACmz1/c6O66EMyvCtcyT3Mhnk8mamVPH80Y73JqRY9Qeo4POp6FL3s8J49npmbPb8ocLwYDgC9v+3YvV+ZKr1YM1q5GX8iPPcpA757dkM 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 K9+NsnvD+SnTwqI189KeyAPSik1DwYBR48WxVoPSfjMDtgSx0+GIGvO2oVJD4dzas84jSHvZmfQrwr3QA++J7GPFk2h72P3kw9+Xe1PSfxEr2+DbM98n5ZvH/yET3nAh68iLSAvWMf/jx9cOI9NseYPS3s2zwHHky9GFKNPW42rDydN5A97dHXu145Bj76dVc9j8jfvSMLfb0Hjog9F/jnPftxo71L1AO9AMTTPakHaTw3Wao9gP2+vGfljD0D8Js976eMuG4nCb0gcP49FR/HPIPYa7zUdhQ8NaPkPTDDZDwJFMY9W3m2vKE1Nz6UmE09GtnnvU4Wnb1ekkY9nDj+Pd7PC75ZfEG9e7MfPn17oD3KxPU9/+i4vR29mD2NQ8c94G1ivPzTfLyyAvk9zda9PJi5Lz0HbKC8DniOPerC3ryHW7A95tbkvCRe7T1jTKk7l+EBvvQn/rwQF8A8NM4RPV06Lr3e18687UB3Pf5KErvtaHA9AqxYOjycET12a2w9G/vsvDM 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 o9HL67PEuAtL0qcAE801qavK3Vgz2/kfA8+aupvUCHKT0tTFg8+MKPvOIhVL0zttA8tPOmPIXHgj1brrG9souMPSNamDxC+Sy8GeAmvKRjv7p7/sM8eK0WPbiNeb0n5II93lUQPQlZyb3FBqC9jDk7vN75RD1BGN28fh4ovvcb1j0i0ty69gUouy8yML2sZRQ9c3nlPDHgOr1ZBWa96sy6Opv7ozxJyIu9g8EnvObgZz0MkCM9KGq2vNhFzb26hzA9hZprPFI2br07Qme9ConQPDeUqD09ce+8U3D9vZGvtj1H/LA91TCzvdoJi727nju9Q4SwPQhdqDm9N1u8bGJ+PW8yeDzcodS8mobCu/2JGbyDe3k93kfEvBM4X70eNYA9dV3ZPSyFe73cmQK8PwwyPQ1O8z3lAYI9C9YXvrzqLj3bVNI9ISTePIEHyL07UMq76JYUPfEhdz1zmIm9dkGRu6kFjLsRRNe87QAHvbeKTb1dU5E9nASxu73uP71/sYg9FrgePoM 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 mRYTxFTw89M4U4vIAwi7xFlrk8BGI4PST2uj1jo4K9F3i7PVNDzj2xxz89t6I/vd/mYryOZrw9MsEJPq0A2rw4AVw9T7vBPch0MjmweU+9UZmBPQsJ1TwSXdQ9riHUvHmp5jy9CMk9buBWvZLqNTwFsho936TIu9K4sT1zaxi9MQfoPZGi7j0wHeA9mGhrvXVNnD02Qka7MAzaPTVkhjyo9BO9RfPOPSXxET3VCpO8Yp8IPWqoNz3miZI9IAuRvUoSij06UcQ9m9qyvFwKlT1jz3U94F96vRetFz0X0wO9dpjMPZN4Bj1hESY+LHGsvAfznDwJW3y8m5+cPSY2OzwbrKq9TF+MPQL++jxEJf88zXltu9vmGr0m1Z49iP8RPZJrlry2vvY9NH7HPCl08TwbWGE9O2N5veDAVb1D1xc8tqACPJrsLzxERgI+cAsXPSlySTwkMZQ9Ea/XPQgZkLzHTrG9gSPqPPlBpj26Ja09KZCmvcUysryzBKU9Ctu7OxFro7154TM 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 u8Bt0EPO1SWj2awu27k50hPe8U5Ttr/De9C+GlO2CMG7yqUW89OJo6vPfo6rw6c8a88CmfvO6UoTxKwGk9Zp8QO0HlSr0jgke9rV4CPPiTUb0iq+A9OY5YvPRWiz0LZEY9CTXtO3+LsjxFNHe8Q1r4Pdsuwz30gNa8uPinPCGTBb3dpCk+JitiPaXq3Tz5om095irFvJWysbwPZ1o7mxNKPYn8izxO1iu5VKgdvRnsxrtf0xE+8TC8vCwgGz1sEQo9KlDEu2Nv2LxLkLq9WBNPO2KGgz1fDAg9wFObvJQ25zzPj4s9+1aMvKzcpb34oei8sA66vUP59TwzJFw7Ucowu4D7sTyoJXO9P0CUvYoIuLqmki8+5vdMvQt2hT3wY1k6pZL/O0J70bxfGAc5lyMrvBy6Zb2N68Y917x4PdSEoL215yM9Pz0evTjuMj0YvYK9g8wfvqXA5D3rQ7w8BZrHvX5yt71CQp69UqjxPLWtir1VnXK9vqI0PUQulzwzzXi9SXpkPQM 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 hEHT5vKSW8wVdrPcI5tTzaX2g9TQAWPgmBfbxc8k89GZQlPY5RgL06WSy70kvOOqzwyj17vgI+mHyLvWyShz3fPwA+TUlMvekp472trlo9fiygPZaGCT4zZDk9aG5XvIjC+z3lCC49DJRJPZE2kzxrKpw91qoPPmFwrb3DZgm9A37HPZbBiTt11ju9MVpAPNaTLzzBSuU9bRzKvHJ1OrtvLsY9rtDAvW2kI72pqpE9wKAiO1SmjT2uRxy9A+icPPXl87wM3Rk9J8cZvcMjUTyMu+27PxmAPZMaFTzB3Yw9mYdmva6ngb25UQC82uRuPdsT6rzlrkU87YcQPNtfLzy9l+88pnmMvFC5ar3kTiw9wzO3OoMVKDqZaWe9nkc5vasmizwzoiY9ueJMPT9YtLsTdPY8ZaMqPL6P6jwSb5C9vnxcvVDDxDxbCf89K1xuvDJHI7vjF369g2SkvHKxrLxsyYy98lyZOyO77j280a683c9+PEg2TL3FhNy7u6TdvMHIujxoefM 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 rX7b1i/vY9ckTWu0XKYD2VKG08BXk7vhSOIb19X6o9hIF3vf3Ngr3M6xy8kYU6Pe4hQTwlQ1w8nGGnPAXb1j15XzW988kRvXrLMb30LZg9rJatPXAoT7tsr806x1O3Pa8Qxr1HF5A9rZadvQBYCj4wT009NjpVvm7RTL2+Oco9vNJePfARoL02DZK9Ge26PRnI6jy2AWU9F9DsuoSvFz2nuog9z8Mvu+ZRi7zGkbU9eXJyPfhWejyoJ9i8vZz/PIGSqrzM1eo9ssH4vAP/AD57IBo96aSxvRzIh7yIb1E9VC6qPRM2wb1yxyA9PijmPZ9RCTzuOhg9WR2vvaqFCT2cV/Y8oVv2vIT9CL23EIc9Zb5NPSFl8Dz45qI7QabcPIbakb2YCfg98u3rPOnH6j3ePG08pfCtvSrSPb0h/T89+dhnPadjrr1LNzy9Sm65PREppruqFQI9HeaEvN+4VD3xjhc77p5avAA7FT3Tm4M9o4G2PfnhJz1IvEA7yM2XPRJOAb3ziaM 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 sStT2k6b492//VvP/0Qz2mlf096RG9O4eFgT2jhT29kiAwPGZHQTsAEow7eQOzvBdvU719Lb49BmA9PY2xjb3so5k9mQaavW22hjpHMdO9q6KZPZOBjL0/aCc9HnRfvY7szDz8x4I9uugLvEwU77wRNoI9GSWuvGo8zj1e9ru9At9aPQp70DyzS2k7FCjMOtq5pr34/mQ9cLK7PbcoxL3cZ3O8q4MNvnoMtDzoMWm9HPt7PUYU6r3MhyE9vYJxvTAo8bwmiGI9P7rMvFzi9TtoYYI9xh3VPNRQmD3Alb29kwjnPBNHkD1DNS69MNzaPH0KFryhky8+UDidPTZAQb2dRCw9AP9nPJrJQL0P5569qBLIPUEihzzy5mI92FgpvQT9ULzVTTs+0zBovPDygTyoCQw9PQXDPOoU/TkruVS97uWRPbSWMD1Yz8u9um4/vIoP5rzgxrE9NlyHPUStmL1IlJw92FWDPKYj1r1uAQS9er7uPaLSAz2rhA09pOi3vZOdfD0u7UM 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 kcx72OTQ4+G+NBPb4Ttb5PQdo7PHKJPIlG4zwBuoq+DVwcvbpP5T1MyxI9UkZsvtZNvTw2pg+9beWKvB7kpr0/rXq9SqIkvFhvDDt6sA6+EBtvPUnoV70ADwq9rgt7vMkGAT3qaNo9Bwf5PLlvlL1/Ojc93xoCu6ZDuzyry8O9h62EPR8SAr1quSE9tLclvUw3s7xx4yO7VncXuuX7ir08DbQ9pq1yvcxWorxOSaA8xMdUvBTp+r1TTka88pqPPRHCiT08KQ09MOiyPRbc+j1TO9q9uBkXvRZT0jv2WPo9yS0PPi0TML2SNKS87J4PPuok47vVvzC8MMiYvM6CET6D0po9hdswvYOEnz2inM89aeGqvDx3eb0xtm49c4lbvDpC2D002ZS96QOiPU26XDzSute7SQuzunqnc7vbIZC78OK6PVt5xL0Tr7w8T26BvGz1ULz+/RO9CUfUutiAdT1pD189uq/gvW4GcD3glOQ9f2mOvRJBp7301q88IZEDPRNSPb0ft9M W9EuJfvZppUb22suE8PS4fPe8Lpb0vZlI9CylUPL/MEL5KCIO9aTc/vJqcATsZkAg9h1W/vFIrurxzUO+9PNlKvWNjgr0pT4I8QK3pvHuOBT1XvCW9jG61u7GhHT0bSdW9LcATPZIDS7y8FAK9+G2/vDrTwL0V2Eo9Vt8Lu/8U6L1Qr3i92NyHveLa7zy4s3C9gwiDPYWAtzxXgNG8O0gXvubPi70WBqA8rlxiPAF7sDlvq5W8MPCWvdEVEDzpF6a8ytGUPQaZuzxbFJi9rGSPPFrRsbyEKhM+tSmfPOpHu7xYOmq8MzplPJ+o970abiA9HQ4PPQsInrxuJJc8cd+Hvf5euLyPaxc+DAp7vILqsj1ekNU8gSA4vd8VqT3cAvA8ssGpPSpWej0nyna9Vx9APT9sI70WuAM+MHBIvJnR9D3+YHU9ZHa2vKVvCr0uNZ68gbl5PXm0v73JxkO8Z1GGPfdsh7zJ65Q9QOQ9vSI4CT2/zlc9DcCSvWmJLj0xWaU9NZ7RvGM 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 SKPL7iBLs9BzwvPEkf2LzzBra98SAvPf+COb2Fyzy8G2Y2vQSpXTysAqu8tMjvPEcqh70Uygi9jurmPIi7ILyqjJE9gNEvPd9bTb0zJFc9Gv63ve3iq7zgAIa9A+EGPaoWW70ihC09CP7NvQOsV735MiI8CsKZPb60p7zDvRw9WHBAu4wApbtyAM07k/OYPQM2BTwilYW9EKEMvPiMDj2wW9o9VH3EPZ26mjyBxuw9uaWcvIhOtr2nPIQ74aJ+PfnxQ7wB0t88Bz6VuvTrEzzMHuY9QHpPvYyMKb3Ashw9nhA1vOefVr3rvaG96qkuPb8/Br5kCK86acORPPOKv70dZkQ9sR7pPFzxib1Nsjo9rdcWvn+C5rxfuo69P75xPc7/pzzu7c87EoX9vX9ZrTsAvbs9eJ8TvQGdDrwmmsQ6zhNIveOESL3InO09rJckPZZFD77pISc9xiGrPQEmg71nTzm9TmpivHai5DxXRNu82fJwvhluuD1wPsY9kJvJvcRWnbvDm/M 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 e9c8cJvB4Qcz0ITBi9FTy4va3Km73l+dg8BsS7PN5mq73eTKg7Zsvoula/vL06oZQ8hmaQvUzWTbu4ibi8Gf5kvblBIL0RKgW9FljcuwrUU72i9Gm93peNvDI6Bb1zR8y93A8rPfAAQr2Zcd07iH4rvYvirr3Foy08+YqtPYArHb0C1129oXJNvUfbVb0/Kck9z+04PJJ6Xr3CyNo8biN7vV2nuL0Bx8a8vIavPe77mb0tgTy9LPJ/O+LEJjt/Zrs87+mTO34h4Lw8+Di865wkPDFHUjzMQee8ZBi+u59cMj1KSgS93mFGPf3SiDtV9AY+IziGvXoxLzzXtIq9QQ4dvXram71f/DG9KXOYPSPYCDxT+1e8ZL2FvPFkq72j77o9zX+KPMQ/ATteuhm9gzcHvABZ+LcnSZK9SOkNPUPhCDy95I28DXpcPO3K8rwQJ8Q94V9+O2IThL1fNy08Utm7vVmBybyBrpa83czvvGau+L20RDm9ZoUKPdC5T73Vzkk8Z7jhPDM 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 4sWLx2CxE8ObWnu+KeDb78sS09xI7HvTxzQL1hE9q9H62hvcOUIL69TSc7sVqwva1HyjwN9Hm9zRoTvRYYn71De+28yyASvV7127yJriy+s09/PZUsDLz9M7m9Yew8PaGT67y6ARm+JQjFu19fBT6DTKU8BKgAvvI3LDyeZF07MnOfvXoYSr55J429vSgTPs8ePz152LG9nUlUup7vcz1p4ry9Qgs9PFYwhr1T+aQ8sQeYPBu5WL03cAq9KfjJu7hTYj3+qQe+mAkKvBytEj5o2Zk8Pj91vsaaEj2ax8y9CkAzPZ8Z1L1VZXW7iEGWPVJTuDxiJla+B1mTPfUbLb7aUmA993fiPYxxAD0eM569XoH+PNvp+r0vbmQ8f0OavTvQtT0d/IQ88PeiPVbKlD2XROe9tv0nvpHZlT3/gRG+RfxfPtY0cj1FQwc+47GqPIhI7r1Ma0q+KhXdPf+ZIr6IHSY+tMFRPu8E1T1sbs+9W13qvQ62WL4rNg0+NBwVPi9/R77PAiM G+7tlnvmXR7T08CaM9FWp2Pgo7Or4wtzw+7qltvj6UGL5uF2G+NSJFPlsQ5D0Lr1A+5aYIvq0kDD6TQx6+Xpc0vcZXBb6KKdU9bmfPPZBgKj76PMy9CY29PWEC077OWoS+qMjQvgPqHL4V+ac+Epu2Piv6nL734K49dIqqvoLlEb6mWbK+BHGYvcS5qD6Df5U+hfyqvl9CrD3zc3e+Ih/CvXnalb4X8NY8vadbPr0AiT65hVm+kAkFvjymsb0uzDc9ZDTxvWXHeL5fJgA+ZVwpOyh0kr18k4M8WcwXvRoiIz5gsjg9cF2oPQTcoLzm8AY9YqZVvbzfmD0hw9i9DHbPPQz7QL72PRo+jDapPQZncD5xUBW+s3eGPCB41bynHa691hUWvfrOojymDgy96AU1vg8VSLyTxc+85ugGPiE7ZD3jSFg+idFBPmGbh75+40u+3uY1PqF2m71PeM88QWfLPfdsbj2Zz+s9hnDtvcVP/r3zMMM9wOgjPiCWrL0AIBy+lXYVvgM 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 Spq70f+Iu99oYWvnueeLulER2+SsK6PYymM75G37m9EiGgPIDURj4gFiO+JTggPafh37z1G5G8WpV/vVLpwT1KDQq9EvYzPuj3J76V8mI9KqEJvE24er0l51W+acS5PbGbOrzrjgg+NzzIvXylgT0wlHE9x2NlvcEEM77jLRA+7MIrvXR8wr3GJZQ9UymMvMN98718Lcq8v4xLPU5wxDyRUV29iTqovb/Daz2lU+S8Y0ANvsH217zz9a+9Pl9WPCWWijwIstg5hF84PMFtVj0dRgs9BV25vcP5tDzfiWs9YaXsvPVmuL19KpA8N/uAvZTPQb2BMoA89eI5PKPVgb2APk89wjQwvjPdPD3yXIa8xBOAvOlCkrxGiOA9slNtPG24Wrw2F6W9LMuQPAQZgb1W4u08vtZBvGPblT0KcmI96tQeve07xDz/JMO9hj5ZPapRNb3vPg89gEo4vfAny7ssFEO961XlPJGlc72nQhA9DR6YvC1YYDxgZV695rfqPBaBwL2cmhM 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 89b7fJO+giebw0AeG7Lxunvfga9Lq/vvS9AWFdPbLu8LzIPje830YCvv0fjTte2Ve8qY0iPcYoLb5DOfk8NOK8vWWxgzzz1EK+0IapPZF8q7p6INE81wgOvp2GTz1LKJU9Aj2SPMRIxr1eZnk7ZlMYvZ/o6byXf0+9Mf9uPFOG57yq8ya8YNKwPQ2Pi70lWja86Uh9vVOPcbxTqb88Kx88vX0n3rxbZoM8e1hEvUuZXzyf3Lu86BXru5v40TxGlWw7Z+MfvT0Tgj3Xpxm8PywevfKFVD1ZYVc+psuRPSFplTzePIW9KpULPlbYOj0ppQQ97RSXvbZ2ZT514d09UXuePfFvr70hfIg+6DaCvDQi5D2sDYo9SBqRPUhIZDsnqo89BxSMvd35Vj7Eog09rURAviCdMb0pZRg8j2JfPVWJVL535vA8TETPvRwjqL3km9+9+pifvT5zv71apLK8TUQ5vkDNpjxprRe9eZoDvVdd0ryEbLC7IIS3u58eqrzSFWC+L4QuvYM 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 e9aNIWvXqoU74xJUq7bA6evenWc7x6NdW9bwp1vcWuHL0LVki8f7i3PF1W/Dy4Jz2+28eOO1F+Yr2eOQu921EFPkwFc72wpeq9HcvdO4sbRz5+RVW+sFnjvdmQ3T0C1MQ8hTPKvJzsk7476fc7gs5/Pp5gsL2rnCu+t3cMvEARkj2c3a+9TubdvZsHKbxZB1A9VfaZvBn6JL67Pfo8G0EauyiwDT7raZq+oLCmvNILhD7B8Nu9KeyBvjDaqz0qjxy+dGiGPWqJzb7DiF67x+fePYPmuzuEf8K+Gn4BvNP0qTxky4o91lePvodirr0fgio9vG6NPIQSlb4sSYs9+dHQvcK5SL3+m/K9nwD0O7mJMLyXOmG9UGsjvkZ9ajyQmD6+eVDRvSxhhL060HS95eqvvbGMpLzwbF++odMjvW7B7r0KEpm9V3QMPTtBZLzPXHq9LBdqvA1eU73jERg9GhzlvbAn7L0FeBM+kUOvvOi18r3H9wO+ZMnJvKUDE73DdMq9OLw3vhM 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 G+OErQvBW1DT4k2eU8YxcIvhm4kz1Kifq9z/59vTpb0L0Efjo8v1DfPWPMPj3E1w2+hHpBPdE1+r0KNV6+/PXdvV2iuj0riak8drn8Oyaw47yMPTm9D1aSvTzsl75SfjK+J1YGvVnnJj7GFg6+hnsnvq2JhD0vxU+9qxlfvq2QE77ZReq91priPXEV8r2OvWy9CsQSvlB7x73aSPk9MaSMPdTyPr5CD2a9GD0Ivc9Bk7yWeqq96NETvqYhOb2Xiv+8on3CvXiLHz03bAm8vLqYu+55173gRRm90W+lvfmJ1Ts1Vy++2bJBum8Fpb2/0ZO8m/NBvSQJCD69pfa98QsxPeyAMb3ckD08smzevZKoiz1wpGm7WvDnO9NxWL78ooI9rkPJPNadILxT0Ba+suSlPY51FLwCZaY9SICtvcEJHj71vDg8dEcovbDQPr4klnU9NDFivR7EqL16MDc+K6cTu3PF9r2LGAy8xV4QPtjclrurkxu96YyRvkoAaj50XpQ8jxkAvuM +kbL3Z6xo+2/6dPP4JgD1o/L+9Gj02PmogMj1AlEI9QwY4vecQND3yvJ67yukVvDi9Zb3oIPI85m+yPL6fdL2mcfE8wzTiPYPrvDnWtsS8aDsIvluZSz0iWeC82KCHPA+iLbo1LME9wMLCvAP+qj2VmdC9aJFqPWqd0bzwXp49Saqqvd8Y8j1xR1q9nD96PVFtSjygoYe9qH3YPKAwfT0vQYq8TPOHPBJ+DbwQ/Hc9aEdIvSoN0rzAVwO7IRiNPf4lKjxS9c88PQKhPevqo7y0kx28+2yevatZkLyJtLE9tqmguz4EpzxozhK7Am2NvcXlnz0B89y80MF1PXEQ6L1m9MG7QNcJvnEnlbwac/W80yYHPMKh7b3FLd084zV3vfTOOr3ulX69bzb3Pex3nb39CQs9sqGtvZLGZTuIptg80VrLvCPRh7zo5Zg727wEvh6yAD1OLeQ9HvfXPMVpIb5yqvY7fjxxvd114DuFFyS9zjbkPIv6zz3BHKk9lrQZvt3DiL0lqFM 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 K8QnSGPWy1uTw1N4y9PNwAPUDqAD4JHBG9+ROaPQfaQz2ykN09YgrovSb5ZLyHDHs8ROv0PaxsFr3bOiE+8UmUPbCGmTzkebK9xXOBPe1fHTz0S9g9D73lOh710D3obtI888oMvTEfAz57Mim+N0yKvOU9Dj2wg/s9bsynvYiVg70pbpQ9O7U4PVy51L0WAYu9RDHnO8YgCDwA7mO9n0N9Pf0PybwxpLk8/RTpvTdx0r0L3AI9NERQPXiW3Lz0d4g8mi/CvVlJQj0rh308x7ovPSY4Kb4Cr6q8xpSHvZe1jr2Mzki97QZYPFIIn7yJk7c9lSoTvolMr7yqnwa+qmblPadGwL2ebmo9jstKPTjH2bsSOsC8A6/hPGpli70Wx5Q9iT/JvYKsmb2MzUA+j7jkPDk3SL74AtQ7GRQrPTuX9bv1Rn29ugqfva14uj1eS8m7p7xQvqQTAr0H/Z68J0qBPU7A6r08Vey9dxFPPYRXZL1Vn/+9T9vRu41zyrxgVw27ByiJvTM 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 7BHD1AuBi9SlklPX+maDxSlxm9z6MbvQN6Rj56Mwu8Ro0JvhJBAr62LIc+xb/UPUXBBr4ydOy9dAkyPt2w1TwVSQ++UP5JvjXzyz7ptG49l7syvjvhGLymC54+3EZvveU9SD30rsS9sG5JPgRR2jxrcha+EI/evCX5aD4VkIk7lWyhvYacRL2PAPw9paQhPboj372FeMG9iGdtPeElAzzdTzO+aUgXviuW7z3/nte7CEPXvUcCCD1WsRk+442AvShzzjurBqe9L2clPjfEpTwQfS6+2y0CvWrdgD1fQSq9dmcwvcE6H74VchI9ztuhvBCEj71tv6w8e0RIvRTwyLxgnCS+mO6Kvpufm7zJFq69m44pvl0wMz0fhRE9LqYSvVivBL2xESK++xUYPpaOhrsedGC+AuSiPTQFyzxHepu9QCwEvC7mv70GvDW9t2+Pva07Fj0Nohi9IXIbvVQvGjwJNbK9B156voXB273cLRq+7LigvTGFzD1bGzW9UGEnvcscIL2t6QM 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 Q+pZ2uvP0/X72EYaq7Tj8GuuvpvLwn33y993UpvUq54j2bp4Y99yHWvWt64L27p2q8leXYPaEqZb3u+AE83TQSPlGWiD33SOO9iroVOyBCkj0c+Ki8D41PvQjNtDxB4iE+QgUWvXlT4L0L9tM9aVm5PYHp8rztE628eWcOvlnHzz0qYqS9whIwvoz7hz2Cwtc8156cO78ph73T3ya+rgimPd8PoL1hWDC+PH2sPRhhij2k9hK+O0rXPcmet7tsvSY+twzxvZBB6ztArYQ9hQDEPW7Gfr2A/w89bh71vecCDj2NyZ29DLygvateED18zxU9lETEvU3pfLy6EwW+LYniPQOlEr6HNUK+NAU5Pvxicz2mjNO96tevPbL617zgHMY9fL/VvZh2ED4UYVs95hCmPdlulLxRCSE9A0cNvv5DRbwd15q9G08fvYVCojwb9xU9RKwpvb907bvxuQO+ZpqEOzj5kr1Ty7+8wvQePRxhmj07Dla96VwQPqNPwTu2t5y7VLTQvAM 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 q8fvEmvjv9irxAg/29uMAAvLXwjr2vuIQ9V7zlu7rLNb2+0re7CnFaPdFRo71TiQK9rgbCPPu1pT1Bqzk9vH+/PDyoRr1icVY9HoCdvdslxrtlyh+8y9YmPb1qJ72ShR48D2YYvoeP9jwkl+y9rhNKvAUMJb5BIAm9688SPasuTLzae669lBtuPUGYyr2se/c8CnClvLZO4T2iKpi86fOJuohUET2ay5Y8bow2vWZ1jrxXL807peoAvM77z73OVoE8CJorva5otbxJZBK+fNWQPZHw9b31qBC9PnJCOrOSu7zmnvG9QoFuPVx8Lb1zzAa9glJ1PRXpKz46mAG+hl1evV3pDD6fSps8/vEGvgWhejt+f4O88ZzsPenH7b0P/CG7vaI5vPV2br2DhSe+en4NPV5c6L37lKY9guMvvTjdQrwphbe9kOlEPU3RDr56Tfa7A8KlPXQ4yT0isLC9uh5CPREFCD5a3AO9Hl8KvJON8Dz5OmQ97pDJPazSir0QAeA9ES+OPWM 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 k9ASOYOsocEb2+9Iy8Wr+uPMwVaD1MFU29X5V5u3o7SD1ETOM8mNkXvUWuRz0MJqA9T7VoPWsZEb698/w8nqGtvEj7ETwuppe9YDdkvJ4py71y5c28G6XsvGGdfzsT3bQ9vaU6PB7+ob3xJ1Y7TPYNPReq5TxrJUK9wPBMvNxEKj3i1aI6LpYgvaOU5zxRZvC8B8qGPTS8N71kHS66gaKLvS+Ymzs6jge+yCQAPa2Xp71YwRw93e/NvO8xNzpIrTQ8d4CCu7s3x73aonO9lnjGPAgtND3tDIE9sTARvRaru7zvU7Q9I2QrvSqA4TyPoIS7Ifa8POl49rtkMkO8aAkuvrZHWTuEw4u90eAoPTf1FL6KA3i9L0Mlvf/jEz0hakq9Aw5lPTfEwb1JH4S9sg+TvESw2z1fhcs85ZAJPfE++7xQZHg9the5O8SfzzwuBDs97H7jPBTd5L0RK5y9t41gvQjAlTyelxq+yh+SvHEuAL7+3ha90Mb4vFgCwLz80p+881TdPAM 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 Y+IB1MPTAscL5aCrm+1d0RP+1wOr+oRI++iSE+vtdbab6sxni9wMzlvoSHJD9KbUQ/cqwJP1RfML84VAS/ygfKPjfGd771/q8+9QECPzcXmT2QF+a+qFYbv8I61r6hhJ0+2PVvPlaokj5uRPc+7tcMP7WISr5JxgI/HSsHP1QCnT5nPEC/NVI1v6Ichj5X8UI/cekcPwM/KL8GaGa9E0wmPhZ5AD+Np0A+SmYLP+Eayr1+5w0/CmfWvkvRHD9M5cq9jR8BPyZyCT5y+SS/oW1CPhk9Hr+jSR2/VVkpPw/L675/Ffo9OmAFPxehqj5S3o491wYJv8IJVb95lJG9Hj4WP+Mlr76B0Da/lgoKv6uRRz9uHfG+XOgwvgyTfD4iKOe+j+9Jva4/f77rjmU+324cPxpGsr1hEpS+B+Rxvc9Wh764c4s+IRHjPsXXgD5VQc6+i5XnPcXcOT4ELA2/ri5CvZ0TM75HaH8+EwOUPRfOBr8kXYU+B27QPrOGqT7nCym95XL9PiM 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 nnjz59PWo+FwQivx1JlL4JCQE/bNKcPhWw/T5NCLm+WV8ov/ArW77HE3I/8If0vgz8/T6IzSk/+5L1PFwsmL5nABA+Ayo/vuPVRL+0k1U/w3upPFn0QD8xUxY/NXMdvlLVwL7eiPg8GTJ4vV2u/D6H7Na9QgYLP5NRgj5a8su8WpX2PU7EtL7RRDO9sCPsvh1abz+ZIUe/x6C5vjchGj9hUga/yD7wPrrZSb/ZIWO+mhSpPlSsbz6KMxC/qIILPxr6Sj/YNca+mRIFPws4zjvemzq+NkRnvgA4Nz4BxRm/Z4c1PrZwzz7jBJU+v+/tPl+Ytr4aRrk+8G/WPr3Wdj9+V4m+PdmNPcY1O78Hc0O+j4LhPpn+S749Goi+", "training_traits": {"structure_gen": "Symmetric", "n_layers": 10, "max_nodes": 11, "activation_func": "LeakyReLU", "epoch_num": 6}, "classeM s_name": ["Cryptoadz", "Cryptopunks", "Moonbirds", "Nouns"]},m=25,b=50,y=59+11/12,w=59+11.5/12,v=60;function z(e,t){const n=Math.log(1-t)/Math.log(1-e);return e=>1-Math.pow(1-e,n)}class V{constructor(e,t,n){const{model:r,inputDim:i}=j(t,n);this.model=r,this.inputDim=i,this.iteration=0,this.stage=0;const o=new Date(parseInt(e.birthYear),0,1).getTime(),a=new Date(parseInt(e.birthYear)+1,0,1).getTime();this.birthDate=new Date(Math.floor((o+a)/2));const l=zr.filter((t=>t[0]==e.lifeCycle))[0][2];this.growSpeed=365/l,thiM s.cycleLength=60*l*24*3600*1e3,this.growthFunc=z(.4,.8)}updateAge(e){const t=(e.getTime()-this.birthDate.getTime())/31536e6*this.growSpeed;this.iteration=Math.floor(t/60);const n=t-60*this.iteration;let r;this.age=n;let i,o=0;if(n<25){let e=map(n,0,25,0,1);o=this.growthFunc(e),r=(25-n)/60,this.stage=1,this.stageRatio=map(n,0,25,0,1)}else n<50?(o=1,r=(50-n)/60,this.stage=2,this.stageRatio=map(n,25,50,0,1)):n<y?(o=map(n,50,y,1,0),r=(y-n)/60,this.stage=3,this.stageRatio=map(n,50,y,0,1)):n<w?(o=0,r=(w-n)/60,this.stage=M 4,this.stageRatio=map(n,y,w,0,1)):n<60&&(o=0,r=(60-n)/60,this.stage=5,this.stageRatio=map(n,w,60,0,1));n<50?i=map(n,0,50,0,780/880):n<w?i=map(n,50,w,780/880,800/880):n<60&&(i=map(n,w,60,800/880,1)),this.nextStateTimestamp=Math.round(e.getTime()+this.cycleLength*r),this.statePercentage=round(100*i);let a=(25-n)/60;a<0&&(a+=1),this.nextStableTimestamp=Math.round(e.getTime()+this.cycleLength*a),this.growth=o,this.model.updateNeurons(o,this.iteration)}getBrainStatus(){return{totalNeurons:this.model.getTotalNeurons(),neM uronsLife:this.model.getNeuronsLife(),stage:this.stage,inputDim:this.inputDim,stageRatio:this.stageRatio,age:this.age,growth:this.growth,nextStateTimestamp:this.nextStateTimestamp,nextStableTimestamp:this.nextStableTimestamp,rebirthCount:max(this.iteration,0),statePercentage:this.statePercentage}}classifyImage(e){const t=new G(e,1,e.length);return this.model.forward(t).mat[0]}}class M{constructor(e,t,n,r,i){this.p=e,this.v=t,this.size=n,this.shape=i,this.col=r}getRadius(){return 1==Oe?1*this.size/2:2==Oe?7*this.sizM e/16:3==Oe||4==Oe?4*this.size/7:0}update(){this.p.add(this.v)}draw(e,t,n,r){const i=this.p.x*r,o=this.p.y*r,a=this.size*r,{col:l,shape:s}=this;let h,c;1==n?h=c=l:2==n?(h=dr(t,1),c=l):(h=dr(t,0),c=dr(l,1));e.stroke(dr(c,map(1,0,1,.25,1))),e.fill(dr(h,map(1,0,1,.15,1))),3==n&&e.fill(dr(h,0)),1==s?e.ellipse(i,o,a,a):2==s?e.rect(i,o,7*a/8,7*a/8):3==s&&(e.beginShape(),e.vertex(i-4*a/7,o),e.vertex(i,o-4*a/7),e.vertex(i+4*a/7,o),e.vertex(i,o+4*a/7),e.endShape(CLOSE))}}class E{constructor(e,t,n,r,i,o,a){this.center=e,this.M len=t,this.angle=n,this.v=r,this.angV=i,this.c1=o,this.c2=a}getEndpoints(){const e=createVector(this.len/2*cos(this.angle),this.len/2*sin(this.angle));return[Vector.add(this.center,e),Vector.sub(this.center,e)]}update(){this.center.add(this.v),this.angle+=this.angV}draw(e,t){const[n,r]=this.getEndpoints(),i=n.x*t,o=n.y*t,a=r.x*t,l=r.y*t,s=this.c1,h=this.c2;var c=e.drawingContext.createLinearGradient(i,o,a,l);c.addColorStop(0,s),c.addColorStop(1,h),e.drawingContext.strokeStyle=c,e.drawingContext.globalAlpha=1,e.lineM (i,o,a,l),e.drawingContext.globalAlpha=1}}function S(e,t){const n=random(TAU),r=random(e,t);return createVector(r*cos(n),r*sin(n))}class R{constructor(e,t,n,r,i){this.wall=n,this.maxR=i;const o=t.length;this.nodes=[];for(let a=0;a<o;++a){const o=[],l=.25*t[a];for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),l=S(.02*i,.05*i),s=random(10,25)*i;o.push(new M(t,l,s,e[a],r))}this.nodes.push(o)}const a=A(e);a.unshift(e[0]),a.push(e[e.length-1]),this.lines=[];for(let e=0;e<=o;++eM ){const r=[],l=(0==e?1:t[e-1])*(e==o?1:t[e])*1.5;for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),o=random(5*i,10*i),l=random(TAU),s=S(.02*i,.05*i),h=random(2e-4,.001);r.push(new E(t,o,l,s,h,a[e],a[e+1]))}this.lines.push(r)}}reflectNode(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,{p:o,v:a}=e,l=e.getRadius();(o.x-l<t&&a.x<0||o.x+l>r&&a.x>0)&&(a.x=-a.x),(o.y-l<n&&a.y<0||o.y+l>i&&a.y>0)&&(a.y=-a.y)}reflectLine(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,[M o,a]=e.getEndpoints(),l=e.v;(min(o.x,a.x)<t&&l.x<0||max(o.x,a.x)>r&&l.x>0)&&(l.x=-l.x),(min(o.y,a.y)<n&&l.y<0||max(o.y,a.y)>i&&l.y>0)&&(l.y=-l.y)}update(){for(const e of this.lines)for(const t of e)t.update(),this.reflectLine(t);for(const e of this.nodes)for(const t of e)t.update(),this.reflectNode(t)}draw(e,t,n,r,i){const o=i/this.maxR;for(const t of this.lines){const n=t.length*r;for(let r=0;r<n;++r)t[r].draw(e,o)}for(const i of this.nodes){const a=i.length*r;for(let r=0;r<a;++r)i[r].draw(e,t,n,o)}}}function I(e,M t){re(e),e.fill(0),e.rect(0,0,500,500),ie(e),e.noStroke(),e.fill(dr(cr("#000000"),.5)),e.push(),e.translate(250,250),e.scale(t),e.translate(-250,-250),e.beginShape(),e.vertex(235.2,24.9),e.bezierVertex(215,24.6,185,11.4,164.8,11),e.bezierVertex(147.2,10.7,129.3,10.4,112.2,14.7),e.bezierVertex(95.1,19,78.5,28.5,69.6,43.8),e.bezierVertex(57.699,64.199,61.599,90.199,70.199,112.2),e.bezierVertex(78.799,134.2,91.6,154.6,97.199,177.5),e.bezierVertex(102.499,199.2,100.899,222.5,92.799,243.2),e.bezierVertex(83,268,64.6,288M .3,48.9,310),e.bezierVertex(33.2,331.7,24.5,337.5,26.599,364.1),e.bezierVertex(28.2,384.1,61.399,404.2,75.7,418.3),e.bezierVertex(90,432.4,73.7,488.2,91.9,496.7),e.bezierVertex(124.2,511.6,159,472.5,194.3,468.1),e.bezierVertex(211.6,465.9,267.4,501.5,283.9,495.9),e.bezierVertex(340.7,476.7,298.599,428.9,355.4,409.7),e.bezierVertex(370.799,404.5,454.5,407.6,464.4,394.8),e.bezierVertex(478.599,376.3,474.7,349.3,464.299,328.4),e.bezierVertex(453.9,307.5,438.099,289.5,428.699,268.2),e.bezierVertex(412,230,419,182.6,446M .1,150.9),e.bezierVertex(449.7,146.7,453.6,142.7,455.8,137.6),e.bezierVertex(459.4,129.299,457.5,119.6,454.8,111),e.bezierVertex(443.2,73.4,417.3,40.4,383.6,20.299),e.bezierVertex(358.1,5,343.2,-.4,313.5,0),e.bezierVertex(287.5,.4,261.6,25.4,235.2,24.9),e.endShape(),e.pop()}function C(e,t,n,r,i,o){let a,l,s;re(t),t.fill(0),t.rect(0,0,500,500),ie(t),t.noStroke(),t.fill(dr(n,.5)),1==i?(l=0,s=25,a=map(o,0,25,500,0)):a=0,t.rect(0,a,500,500),e.noStroke(),e.fill(r),e.rect(0,0,500,500),e.beginShape(),e.vertex(435.2,373.8)M ,e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVerteM x(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),eM .bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,M 451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),e.fill(n),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.M 3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(7M 7.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVeM rtex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),re(e),e.fill(r),e.M beginShape(),e.vertex(184.3,473.2),e.bezierVertex(164,473.2,144.7,462.099,134,444.3),e.bezierVertex(131.7,440.5,129.1,438.5,125,437.1),e.bezierVertex(97.3,428.1,80.5,400.6,85.2,371.8),e.bezierVertex(86.3,365.1,85.8,364.1,79.9,361.2),e.bezierVertex(57.2,349.8,46.2,323.3,54.3,299.7),e.bezierVertex(54.7,298.599,55.1,297.7,55.5,296.9),e.bezierVertex(55.6,296.599,55.8,296.4,55.9,296.099),e.vertex(57.9,291.499),e.vertex(62.5,293.599),e.bezierVertex(64.9,294.7,67.3,295.799,69.5,296.9),e.bezierVertex(74.5,299.299,79.1,301.M 599,83.9,303.099),e.bezierVertex(89.8,304.9,96.5,305.499,102.7,305.9),e.bezierVertex(102.8,305.9,102.9,305.9,103,305.9),e.bezierVertex(106.6,305.9,108.9,302.799,109,299.799),e.bezierVertex(109.1,296.199,106.6,293.4,102.7,292.799),e.bezierVertex(101.3,292.599,99.9,292.4,98.4,292.299),e.bezierVertex(94.3,291.799,90.1,291.299,86,289.9),e.bezierVertex(68.9,284,56.5,270.2,52.7,252.799),e.bezierVertex(48.9,235.499,54.5,217.7,67.6,205.299),e.bezierVertex(71.9,201.299,72.7,198.1,70.8,192.399),e.bezierVertex(64.2,172.2,68.8M ,153.99,84.2,139.599),e.bezierVertex(94.2,130.199,105.5,125.399,117.8,125.399),e.bezierVertex(124.3,125.399,131.1,126.799,137.8,129.599),e.bezierVertex(157,137.399,167.9,152.799,169.4,173.99),e.vertex(169.4,174.399),e.bezierVertex(169.5,175.899,169.6,177.2,169.9,178.299),e.bezierVertex(170.7,181.2,173.2,183.2,176.1,183.2),e.bezierVertex(176.299,183.2,176.5,183.2,176.7,183.2),e.bezierVertex(180.1,182.899,182.6,180.299,182.7,177),e.bezierVertex(183.1,162,178.299,148.2,168.399,136.1),e.bezierVertex(158.2,123.5,144.899M ,115.8,128.799,113.199),e.bezierVertex(123.499,112.299,120.399,109.799,118.899,104.99),e.bezierVertex(113.899,89.699,120.699,72.299,134.899,64.499),e.bezierVertex(139.99,61.699,145.799,60.199,151.7,60.199),e.bezierVertex(162.2,60.199,171.899,64.799,178.1,72.699),e.bezierVertex(179.6,74.6,180.799,76.6,181.9,78.499),e.vertex(182.2,79.099),e.bezierVertex(183.2,80.699,185.2,83.299,188.4,83.299),e.bezierVertex(189.5,83.299,190.6,82.99,191.7,82.399),e.bezierVertex(195.1,80.599,196,76.99,194,72.799),e.bezierVertex(190.1,6M 4.799,184.1,58.499,175.6,53.299),e.bezierVertex(174.6,52.699,173.7,52.099,172.5,51.499),e.vertex(170.5,50.299),e.vertex(163,45.899),e.vertex(170.5,41.599),e.bezierVertex(182,34.99,193.1,30.799,204.4,28.599),e.bezierVertex(208.6,27.799,212.9,27.399,217.2,27.399),e.bezierVertex(217.6,27.399,217.9,27.399,218.3,27.399),e.bezierVertex(231.4,27.599,242.7,38.199,243,50.599),e.bezierVertex(243.4,64.899,243.3,78.99,243.2,93.799),e.bezierVertex(243.2,99.799,243.1,105.899,243.1,112.099),e.vertex(243.1,119.199),e.vertex(236.4,M 116.799),e.bezierVertex(235.7,116.499,235,116.299,234.4,115.99),e.bezierVertex(233.4,115.599,232.6,115.299,232,115.199),e.bezierVertex(230.6,114.899,229.2,114.599,227.8,114.299),e.bezierVertex(223.8,113.499,220.1,112.699,216.4,112.499),e.vertex(216.2,112.499),e.bezierVertex(212.5,112.499,210.7,115.599,210.6,118.599),e.bezierVertex(210.4,122.399,212.7,125.099,216.4,125.399),e.bezierVertex(230.1,126.399,238.9,133.099,242.3,145.199),e.bezierVertex(243.2,148.399,243.2,151.599,243.2,154.499),e.vertex(243.2,155.099),e.beM zierVertex(243.2,254.199,243.2,330,243.2,400.599),e.bezierVertex(243.2,401.99,243.2,403.4,243.2,404.9),e.bezierVertex(243.3,411.099,243.3,417.599,242.3,423.9),e.bezierVertex(238.1,449.2,219.6,467.799,194,472.5),e.bezierVertex(190.9,472.9,187.6,473.2,184.3,473.2),e.endShape(),e.beginShape(),e.vertex(315.8,473.1),e.bezierVertex(309.3,473.1,302.8,472,296.5,469.9),e.bezierVertex(270.4,461,253.8,434.9,257.1,407.9),e.bezierVertex(260,384,273.8,366.8,297,358.3),e.bezierVertex(297.7,358.1,298.3,357.8,299,357.6),e.bezierVerM tex(299.8,357.3,300.6,357.1,301.2,356.8),e.bezierVertex(304.3,355.4,306,351.8,304.9,348.7),e.bezierVertex(304,345.9,301.7,344.2,299,344.2),e.bezierVertex(298.6,344.2,298.1,344.2,297.6,344.3),e.bezierVertex(288.1,346.3,279,350.9,269.7,358.3),e.bezierVertex(268.9,358.9,268.1,359.6,267.2,360.4),e.vertex(265.5,361.8),e.vertex(258.5,367.6),e.vertex(257.4,358.6),e.bezierVertex(257.3,358,257.3,357.5,257.2,357.1),e.bezierVertex(257,356,256.9,354.9,256.9,353.7),e.bezierVertex(256.9,334.8,256.9,316,256.9,297.1),e.bezierVerteM x(256.9,260.3,256.9,222.3,256.8,185),e.bezierVertex(256.8,170.7,268.3,158.8,282.5,158.4),e.bezierVertex(284.8,158.3,286.7,157.6,287.9,156.2),e.bezierVertex(289.099,154.9,289.599,153.2,289.5,151.3),e.bezierVertex(289.3,147.5,286.7,145.1,282.7,145.1),e.bezierVertex(282.5,145.1,282.2,145.1,282,145.1),e.bezierVertex(278.8,145.3,275.5,146.1,272,146.9),e.bezierVertex(270.9,147.2,269.8,147.4,268.6,147.7),e.bezierVertex(267.9,147.9,267,148.2,265.8,148.7),e.bezierVertex(265.1,149,264.4,149.3,263.5,149.6),e.vertex(256.8,152)M ,e.vertex(256.8,114.6),e.bezierVertex(256.8,95,256.8,75.4,256.8,55.9),e.bezierVertex(256.8,38,267.2,27.3,284.6,27.3),e.bezierVertex(285.3,27.3,285.9,27.3,286.6,27.3),e.bezierVertex(299,27.9,318.7,34.5,329.6,41.9),e.vertex(336.1,46.3),e.vertex(324.4,53.3),e.bezierVertex(316.2,58.2,310.2,64.6,306,72.9),e.bezierVertex(304.2,76.4,305.1,78.5,306.1,80),e.bezierVertex(307.4,81.9,309.4,83,311.6,83),e.bezierVertex(313.7,83,315.7,81.9,317.1,80.1),e.bezierVertex(317.4,79.7,317.8,79,318.1,78.4),e.bezierVertex(318.4,77.9,318.7,M 77.3,319,76.8),e.bezierVertex(325.3,66.2,336.3,59.9,348.5,59.9),e.bezierVertex(353.2,59.9,357.8,60.8,362.1,62.7),e.bezierVertex(377.6,69.3,386,86.7,381.7,103.2),e.bezierVertex(380.7,107.1,378.5,111.8,371.1,113.1),e.bezierVertex(342.7,118.1,322.2,139.1,317.8,167.8),e.bezierVertex(317.4,170.3,317.3,173.2,317.4,176.5),e.bezierVertex(317.5,180,320.1,182.8,323.5,183),e.bezierVertex(323.6,183,323.8,183,323.9,183),e.bezierVertex(327.1,183,329.8,180.6,330.3,177.2),e.bezierVertex(330.6,175.7,330.7,174,330.9,172.3),e.bezierVM ertex(331.1,169.8,331.4,167.3,332,164.7),e.bezierVertex(337.3,141.9,357.7,125.4,380.7,125.4),e.bezierVertex(382.5,125.4,384.3,125.5,386.1,125.7),e.bezierVertex(412.8,128.9,432.6,150.9,432,176.9),e.bezierVertex(431.9,182.3,430.9,187.7,429.1,192.7),e.bezierVertex(427.2,197.9,428,201,432.3,205),e.bezierVertex(446.8,218.7,451.8,236,446.6,255),e.bezierVertex(441.4,274,428.3,286.5,408.7,291.3),e.bezierVertex(406.1,291.9,403.6,292.1,401.1,292.3),e.bezierVertex(400,292.4,398.9,292.5,397.9,292.6),e.bezierVertex(393.6,293.1,M 390.9,295.7,391,299.5),e.bezierVertex(391.1,303.4,394,305.8,398.5,305.8),e.bezierVertex(409.9,305.8,420.8,302.6,431.1,296.4),e.bezierVertex(431.8,296,432.5,295.5,433.2,295.1),e.bezierVertex(433.8,294.7,434.5,294.3,435.2,293.9),e.bezierVertex(436,293.4,436.6,293.2,437.2,293.1),e.bezierVertex(437.4,293,437.7,292.9,438.1,292.8),e.vertex(442.5,291.4),e.vertex(444.2,295.7),e.bezierVertex(450.9,312.4,449.5,328.4,440,343.4),e.bezierVertex(435.3,350.8,428.7,356.7,420.2,361.1),e.bezierVertex(414.3,364.1,413.7,365.2,414.8,37M 1.7),e.bezierVertex(419.5,400.2,403,427.6,375.6,436.9),e.bezierVertex(371,438.5,368.3,440.7,365.8,444.7),e.bezierVertex(355.2,462.5,336.4,473.1,315.8,473.1),e.bezierVertex(315.8,473.1,315.8,473.1,315.8,473.1),e.endShape(),ie(e),e.fill(n),e.beginShape(),e.vertex(120.2,279.9),e.bezierVertex(117.9,279.9,112.4,279.299,112.2,273.599),e.bezierVertex(112,267.7,117.4,266.7,119.7,266.599),e.bezierVertex(133.1,265.799,143.1,259.499,149.3,247.899),e.bezierVertex(149.6,247.299,150.1,246.399,150.3,245.399),e.bezierVertex(150.6,M 244.299,150.5,243.299,150.5,242.7),e.bezierVertex(150.5,242.6,150.5,242.5,150.5,242.299),e.vertex(150.3,238.799),e.vertex(141.1,235.99),e.bezierVertex(114.6,227.799,95.6,202.499,95.9,175.799),e.bezierVertex(95.9,173.99,96.4,168.199,102.2,168.199),e.bezierVertex(102.6,168.199,103,168.199,103.4,168.299),e.bezierVertex(104.8,168.499,108.2,168.899,109.2,175.599),e.bezierVertex(109.3,176.599,109.5,177.599,109.6,178.499),e.bezierVertex(110.4,184.199,111.3,189.99,113.7,195.499),e.bezierVertex(121.9,213.99,139.5,225.499,15M 9.7,225.499),e.bezierVertex(172.1,225.499,184.1,220.899,193.5,212.599),e.bezierVertex(194,212.199,194.4,211.799,194.8,211.399),e.bezierVertex(195.1,211.099,195.5,210.799,195.8,210.399),e.bezierVertex(197.4,208.99,199.2,208.2,200.9,208.2),e.bezierVertex(202.5,208.2,204,208.899,205.3,210.1),e.bezierVertex(208,212.9,207.9,216.9,205,219.9),e.bezierVertex(196.5,228.6,186.3,234.3,174.7,236.8),e.bezierVertex(168.799,238.1,165.6,241,163.899,246.7),e.bezierVertex(158.3,265.9,139.9,279.7,120.2,279.9),e.vertex(120.2,279.9),e.M endShape(),e.beginShape(),e.vertex(187.2,427.5),e.bezierVertex(183.799,427.5,181.299,425.3,180.799,422),e.bezierVertex(180.6,420.8,180.499,419.5,180.399,418.1),e.bezierVertex(180.299,417,180.2,415.8,180.099,414.7),e.bezierVertex(177.199,390.5,156.699,371.3,132.399,370.2),e.bezierVertex(131.99,370.2,131.499,370.2,131.099,370.2),e.bezierVertex(130.699,370.2,130.299,370.2,129.799,370.2),e.bezierVertex(125.99,369.9,123.199,367.2,123.099,363.6),e.bezierVertex(122.99,360.2,125.799,357.3,129.599,356.9),e.bezierVertex(130.M 499,356.8,131.499,356.8,132.599,356.7),e.bezierVertex(133.199,356.7,133.799,356.7,134.399,356.6),e.vertex(138.299,356.4),e.vertex(139.1,352.6),e.bezierVertex(139.5,350.7,139.799,348.9,140.2,347),e.bezierVertex(140.899,343.4,141.5,340,142.399,336.8),e.bezierVertex(150.099,310.7,174.399,292,201.399,291.3),e.vertex(201.599,291.3),e.bezierVertex(203.699,291.3,206.299,292,208.299,293.2),e.bezierVertex(210.499,294.5,210.699,297.5,209.99,299.8),e.bezierVertex(209.499,301.5,208.199,303.9,203.299,304.7),e.bezierVertex(202.1M 99,304.9,200.99,305,199.799,305.2),e.bezierVertex(194.499,305.9,188.99,306.599,183.799,308.9),e.bezierVertex(165.499,316.799,155.199,331.299,152.99,352),e.bezierVertex(152.399,357.8,154.499,361.7,159.699,364.5),e.bezierVertex(178.199,374.4,189.399,390,193.099,410.9),e.bezierVertex(193.699,414.299,193.899,418,193.599,422),e.bezierVertex(193.399,425.2,190.899,427.5,187.399,427.5),e.vertex(187.2,427.5),e.endShape(),e.beginShape(),e.vertex(364.3,281.1),e.bezierVertex(346.3,280.6,332.9,272.8,323.5,257),e.bezierVertex(32M 1.6,253.9,320.4,250.2,319.2,246.7),e.bezierVertex(317.7,242.2,315,239.799,310.5,238.799),e.bezierVertex(298.5,236.299,288,230.7,279.4,222.1),e.bezierVertex(276.7,219.4,274.9,215.299,278,211.9),e.bezierVertex(279.4,210.3,281,209.6,282.6,209.6),e.bezierVertex(284.4,209.6,286.4,210.6,288.3,212.5),e.bezierVertex(297.8,221.8,310.4,226.9,323.9,226.9),e.bezierVertex(340.2,226.9,355.1,219.3,364.8,206.2),e.bezierVertex(371,197.8,374.2,188.5,374.5,178.5),e.vertex(374.5,177.9),e.bezierVertex(374.5,177,374.5,176.1,374.7,175.4)M ,e.bezierVertex(375.3,171.8,377.9,169.5,381.3,169.5),e.bezierVertex(381.4,169.5,381.5,169.5,381.7,169.5),e.bezierVertex(385.4,169.7,388,172.4,388,176.1),e.bezierVertex(388.1,190.7,383.4,204,374.2,215.8),e.bezierVertex(365.8,226.5,354.7,233.9,341.2,237.9),e.bezierVertex(340,238.3,338.7,238.6,337.3,239.1),e.bezierVertex(335.9,239.6,335.1,240.4,334.7,240.9),e.bezierVertex(334.599,241,334.5,241.1,334.4,241.2),e.vertex(331.799,243.6),e.vertex(333.199,246.8),e.bezierVertex(338.199,258,346.799,264.9,358.699,267.3),e.bezieM rVertex(360.199,267.6,361.599,267.7,362.99,267.9),e.bezierVertex(363.599,268,364.299,268,364.899,268.1),e.bezierVertex(369.099,268.6,371.799,271.4,371.499,275),e.bezierVertex(371.199,278.6,368.299,281.2,364.399,281.2),e.vertex(364.3,281.1),e.endShape(),e.beginShape(),e.vertex(323.9,437),e.bezierVertex(323.7,437,323.5,437,323.299,437),e.bezierVertex(319.599,436.7,317.299,434.1,317.4,430.2),e.bezierVertex(317.9,406.099,328.299,388,349.5,375),e.bezierVertex(350.7,374.2,352,373.5,353.4,372.8),e.bezierVertex(354.099,372M .4,354.7,372.1,355.299,371.7),e.vertex(357.499,370.5),e.vertex(357.799,368),e.bezierVertex(360.4,346.6,345.199,323.7,323.9,317),e.bezierVertex(319.099,315.5,314.099,314.9,309.299,314.4),e.vertex(308.199,314.299),e.bezierVertex(305.99,314.099,300.799,312.9,300.899,307.299),e.bezierVertex(300.99,303.499,303.899,300.9,308.099,300.9),e.vertex(308.299,300.9),e.bezierVertex(327.099,301.299,343.099,308.7,355.699,322.9),e.bezierVertex(364.299,332.5,369.399,344.099,370.99,357.299),e.bezierVertex(371.099,358.4,371.299,359.4,M 371.499,360.499),e.bezierVertex(371.599,360.99,371.699,361.499,371.799,361.99),e.vertex(372.499,365.899),e.vertex(377.899,366.199),e.bezierVertex(378.799,366.299,379.699,366.299,380.599,366.399),e.bezierVertex(385.099,366.699,387.899,369.399,387.799,373.299),e.bezierVertex(387.699,377.099,384.99,379.599,380.799,379.799),e.bezierVertex(369.799,380.199,359.99,383.299,351.899,389.299),e.bezierVertex(338.799,398.799,331.699,411.699,330.699,427.499),e.vertex(330.699,428.299),e.bezierVertex(330.599,429.199,330.599,430.09M 9,330.499,430.799),e.bezierVertex(330,434.7,327.5,437,323.9,437),e.endShape()}function T(e){return e[0].map(((t,n)=>e.map((e=>e[n]))))}function A(e){return e.map((e=>Array.isArray(e)?A(e):e))}function D(e,t){return floor(random(e,t))}function k(e){let t=0;for(const n of e)t+=n[1];let n=random(t),r=0;for(const t of e)if(r+=t[1],n<r)return t[0];return null}function L(e){for(let t=1;t<e.length;++t){let n=D(0,t),r=e[t];e[t]=e[n],e[n]=r}}function P(e){return null==e||""===e}function O(e){return new Promise((t=>setTimeouM t(t,e)))}function F(e,t,n){let r=0;for(let i=1;i<=1e3;++i)for(let o=1;o<=1e3;++o)if(e*o%(t*i)==0){let e=1*i/o;abs(e-n)<abs(r-n)&&(r=e)}return r}function N(){let e=60*(new Date).getTimezoneOffset()*1e3;return new Date(Date.now()-e).toISOString().slice(0,-1)}function B(e,t,n){let r;if(push(),textSize(e),textWidth(t)<=n)r=t;else for(let e=0;e<t.length;++e){const i=t.slice(0,e+1)+"...";if(textWidth(i)>n){r=i;break}}return pop(),r}function Y(e){var t=e%10,n=e%100;return 1==t&&11!=n?e+"st":2==t&&12!=n?e+"nd":3==t&&13!=n?M e+"rd":e+"th"}class G{constructor(e,t,n){this.n=t,this.m=n,this.mat=[];let r=0;for(let t=0;t<this.n;++t){this.mat.push([]);for(let n=0;n<this.m;++n)this.mat[t].push(r<e.length?e[r]:0),r+=1}return this}copy(){return new G(this.mat.flat(),this.n,this.m)}}class H{static __linear=e=>e;static __relu=e=>Math.max(e,0);static __leaky_relu=e=>e>0?e:.2*e;static __sigmoid=e=>1/(1+Math.exp(-e));static __tanh=e=>Math.tanh(e);static __apply_unary_op(e,t){const n=e.copy();for(let e=0;e<n.n;++e)for(let r=0;r<n.m;++r)n.mat[e][r]=t(M n.mat[e][r]);return n}static linear=e=>H.__apply_unary_op(e,H.__linear);static relu=e=>H.__apply_unary_op(e,H.__relu);static leaky_relu=e=>H.__apply_unary_op(e,H.__leaky_relu);static sigmoid=e=>H.__apply_unary_op(e,H.__sigmoid);static tanh=e=>H.__apply_unary_op(e,H.__tanh);static __add=(e,t)=>e+t;static __mul=(e,t)=>e*t;static __apply_binary_op=(e,t,n)=>{"object"!=typeof t&&(t=new G([t],1,1));const r=e.copy();for(let e=0;e<r.n;++e)for(let i=0;i<r.m;++i)r.mat[e][i]=n(r.mat[e][i],t.mat[e%t.n][i%t.m]);return r};staticM mul=(e,t)=>H.__apply_binary_op(e,t,H.__mul);static add=(e,t)=>H.__apply_binary_op(e,t,H.__add);static matMul(e,t){const n=new G([],e.n,t.m);for(let r=0;r<n.n;++r)for(let i=0;i<n.m;++i)for(let o=0;o<e.m;++o)n.mat[r][i]+=e.mat[r][o]*t.mat[o][i];return n}static softmax(e){const t=H.__apply_unary_op(e,(e=>Math.exp(e))),n=t.mat.flat().reduce(((e,t)=>e+t));for(let r=0;r<e.n;++r)for(let i=0;i<e.m;++i)t.mat[r][i]/=n;return t}}class ${constructor(e,t){this.scale=e,this.offset=t}forward(e){return H.add(H.mul(e,this.scale),tM his.offset)}}class X{constructor(){}forward(e){return e.map((e=>e.flat()))}}class W{constructor(e,t,n,r){this.out_dim=e,this.activation=t,this.w=n,this.b=r}forward(e){const t=H.add(H.matMul(e,this.w),this.b);return null==this.activation?t:this.activation(t)}}class U{constructor(e,t,n){this.preprocessLayers=e,this.hiddenLayers=t,this.outputLayer=n,this.totalNeurons=this.hiddenLayers.map((e=>e.out_dim)),this.currentOrders=[],this.currentIteration=null}updateNeurons(e,t){if(t!=this.currentIteration){this.currentOrdersM =[];for(let e=0;e<this.totalNeurons.length;++e){randomSeed(100*(t+1)+e);const n=[];for(let t=0;t<this.totalNeurons[e];++t)n.push(t);L(n),this.currentOrders.push(n)}this.currentIteration=t}const n=A(this.totalNeurons),r=n.reduce(((e,t)=>e+t))*(1-e);for(let e=0;e<r;++e){const t=n.map(((e,t)=>(e-1)/this.totalNeurons[t]));n[t.map(((e,t)=>[e,t])).reduce(((e,t)=>t[0]>e[0]?t:e))[1]]-=Math.min(r-e,1)}this.neuronsLife=[];for(let e=0;e<n.length;++e){const t=this.currentOrders[e],r=Array(this.totalNeurons[e]).fill(0);for(let M i=0;i<n[e];++i)r[t[i]]=Math.min(n[e]-i,1);this.neuronsLife.push(r)}}getTotalNeurons(){return A(this.totalNeurons)}getNeuronsLife(){return A(this.neuronsLife)}forward(e){for(const t of this.preprocessLayers)e=t.forward(e);for(const[t,n]of this.hiddenLayers.entries()){e=n.forward(e);const r=new G(this.neuronsLife[t],1,e.m);e=H.mul(e,r)}return e=this.outputLayer.forward(e),H.softmax(e)}}function q(e){switch(e){case"relu":return H.relu;case"sigmoid":return H.sigmoid;case"tanh":return H.tanh;case"leaky_relu":return H.leM aky_relu;default:return H.linear}}function j(e,t){const n=[],r=[],i=Z(t);let o=null,a=0,l=[];for(const t of e.config.layers)if("InputLayer"==t.class_name)o=t.config.batch_input_shape.slice(1),l=o;else if("Rescaling"==t.class_name)n.push(new $(t.config.scale,t.config.offset));else if("Flatten"==t.class_name)o=[o.reduce(((e,t)=>e*t))];else if("Dense"==t.class_name){const e=[t.config.units],n=o[0]*e[0],l=e[0],s=i.subarray(a,a+n);a+=n;const h=i.subarray(a,a+l);a+=l;const c=new G(s,o[0],e[0]),u=new G(h,1,e[0]),f=q(t.conM fig.activation);r.push(new W(e[0],f,c,u)),o=e}const s=r.pop();return{model:new U(n,r,s),inputDim:l}}function Z(e){const t=window.atob(e),n=t.length/Float32Array.BYTES_PER_ELEMENT,r=new DataView(new ArrayBuffer(Float32Array.BYTES_PER_ELEMENT)),i=new Float32Array(n);let o=0;for(let e=0;e<n;e++){o=4*e;for(let e=0;e<4;++e)r.setUint8(e,t.charCodeAt(o+e));i[e]=r.getFloat32(0,!0)}return i}class K{constructor(e){this.elt=e,this._events={},this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight}position(){if(0===aM rguments.length)return{x:this.elt.offsetLeft,y:this.elt.offsetTop};var e="absolute";return"static"!==arguments[2]&&"fixed"!==arguments[2]&&"relative"!==arguments[2]&&"sticky"!==arguments[2]&&"initial"!==arguments[2]&&"inherit"!==arguments[2]||(e=arguments[2]),this.elt.style.position=e,this.elt.style.left=arguments[0]+"px",this.elt.style.top=arguments[1]+"px",this.x=arguments[0],this.y=arguments[1],this}show(){return this.elt.style.display="block",this}hide(){return this.elt.style.display="none",this}size(e,t){if(0=M ==arguments.length)return{width:this.elt.offsetWidth,height:this.elt.offsetHeight};var n=e,r=t;if(n!==te||r!==te){if(n===te?n=t*this.width/this.height:r===te&&(r=e*this.height/this.width),this.elt instanceof HTMLCanvasElement){var i,o={},a=this.elt.getContext("2d");for(i in a)o[i]=a[i];for(i in this.elt.setAttribute("width",n*this._pInst._pixelDensity),this.elt.setAttribute("height",r*this._pInst._pixelDensity),this.elt.style.width=n+"px",this.elt.style.height=r+"px",this._pInst.scale(this._pInst._pixelDensity,thisM ._pInst._pixelDensity),o)this.elt.getContext("2d")[i]=o[i]}else this.elt.style.width=n+"px",this.elt.style.height=r+"px",this.elt.width=n,this.elt.height=r;this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight,this._pInst&&this._pInst._curElement&&this._pInst._curElement.elt===this.elt&&(this._pInst._setProperty("width",this.elt.offsetWidth),this._pInst._setProperty("height",this.elt.offsetHeight))}return this}style(e,t){if(t instanceof Color&&(t="rgba("+t.levels[0]+","+t.levels[1]+","+t.levels[2]+","+tM .levels[3]/255+")"),void 0===t){if(-1===e.indexOf(":"))return window.getComputedStyle(this.elt).getPropertyValue(e);for(var n=e.split(";"),r=0;r<n.length;r++){var i=n[r].split(":");i[0]&&i[1]&&(this.elt.style[i[0].trim()]=i[1].trim())}}else if(this.elt.style[e]=t,"width"===e||"height"===e||"left"===e||"top"===e){var o=window.getComputedStyle(this.elt).getPropertyValue(e).replace(/[^\d.]/g,"");this[e]=Math.round(parseFloat(o,10))}return this}value(){return arguments.length>0?(this.elt.value=arguments[0],this):"rangeM "===this.elt.type?parseFloat(this.elt.value):this.elt.value}mouseClicked(e){return this._adjustListener("click",e,this),this}isFocused(){return document.activeElement===this.elt}_adjustListener(e,t,n){return!1===t?this._detachListener(e,n):this._attachListener(e,t,n),this}_attachListener(e,t,n){n._events[e]&&this._detachListener(e,n);var r=t.bind(n);n.elt.addEventListener(e,r,!1),n._events[e]=r}_detachListener(e,t){var n=t._events[e];t.elt.removeEventListener(e,n,!1),t._events[e]=null}}function J(e,t){var n=documenM t.createElement("button");return n.innerHTML=e,t&&(n.value=t),ee(n)}function Q(e){var t=arguments.length>1&&void 0!==arguments[1]&&arguments[1],n=function(t){var n=!0,r=!1,i=void 0;try{for(var o,a=t.target.files[Symbol.iterator]();!(n=(o=a.next()).done);n=!0){var l=o.value;File._load(l,e)}}catch(e){r=!0,i=e}finally{try{n||null==a.return||a.return()}finally{if(r)throw i}}};if(window.File&&window.FileReader&&window.FileList&&window.Blob){var r=document.createElement("input");return r.setAttribute("type","file"),t&&r.M setAttribute("multiple",!0),r.addEventListener("change",n,!1),ee(r)}}function ee(e){return document.body.appendChild(e),new K(e)}createImg=function(){var e,t=document.createElement("img"),n=arguments;return n.length>1&&"string"==typeof n[1]&&(t.alt=n[1]),n.length>2&&"string"==typeof n[2]&&(t.crossOrigin=n[2]),t.src=n[0],e=ee(t,this),t.addEventListener("load",(function(){e.width=t.offsetWidth||t.width,e.height=t.offsetHeight||t.height;var r=n[n.length-1];"function"==typeof r&&r(e)})),e},createInput=function(){var e=M arguments.length>0&&void 0!==arguments[0]?arguments[0]:"",t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:"text",n=document.createElement("input");return n.setAttribute("value",e),n.setAttribute("type",t),ee(n,this)};const te="auto";function ne(e){re(e);const t=e._rectMode;e.rectMode(CORNER),e.rect(0,0,e.width,e.height),e.rectMode(t),ie(e)}function re(e){e.push(),e.fill(255,255,255,255),e.blendMode(REMOVE)}function ie(e){e.blendMode(BLEND),e.pop()}File=function(e,t){this.file=e,this._pInst=t;var n=e.type.sM plit("/");this.type=n[0],this.subtype=n[1],this.name=e.name,this.size=e.size,this.data=void 0},File._createLoader=function(e,t){var n=new FileReader;return n.onload=function(n){var r=new File(e);if("application/json"===r.file.type)r.data=JSON.parse(n.target.result);else if("text/xml"===r.file.type){var i=(new DOMParser).parseFromString(n.target.result,"text/xml");r.data=new XML(i.documentElement)}else r.data=n.target.result;t(r)},n},File._load=function(e,t){if(/^text\//.test(e.type)||"application/json"===e.type)FilM e._createLoader(e,t).readAsText(e);else if(/^(video|audio)\//.test(e.type)){var n=new File(e);n.data=URL.createObjectURL(e),t(n)}else File._createLoader(e,t).readAsDataURL(e)},XML=function(e){if(e)this.DOM=e;else{var t=document.implementation.createDocument(null,"doc");this.DOM=t.createElement("root")}},document.addEventListener("DOMContentLoaded",(function(){addEventListener("mousemove",(e=>{window.mouseX=e.pageX,window.mouseY=e.pageY}))})),new e("global");const oe="249";let ae,le,se,he,ce,ue,fe,de,xe,ge,pe,me,be,M ye,we,ve,ze,Ve,_e,Me,Ee,Se,Re,Ie,Ce,Te,Ae,De,ke,Le,Pe,Oe,Fe,Ne,Be,Ye,Ge,He,$e,Xe,We,Ue,qe,je,Ze,Ke,Je,Qe,et,tt,nt,rt,it,ot,at,lt,st,ht,ct,ut,ft,dt,xt,gt,pt,mt,bt,yt,wt,vt,zt,Vt,_t,Mt,Et,St,Rt,It,Ct,Tt,At=!1,Dt=!1,kt=!0,Lt=!1,Pt=!1;const Ot=[" ","Growing","Stable","Decaying","Dead","Rebirth"];let Ft,Nt,Bt,Yt,Gt,Ht,$t,Xt,Wt,Ut,qt,jt,Zt,Kt,Jt,Qt,en,tn,nn,rn,on,an,ln,sn,hn=0,cn=0,un=0,fn=!1,dn=!0,xn=!0,gn=null,pn=null,mn=null,bn=!1,yn=!1,wn=null,vn=null,zn=!1;async function setup(){let e=windowWidth,t=windowHeight;creaM teCanvas(e,t),et=createGraphics(e,t),Xe=createGraphics(e,t),$e=createGraphics(e,t),We=createGraphics(e,t),Ue=createGraphics(e,t),qe=createGraphics(e,t),Qe=createGraphics(e,t),je=createGraphics(e,t),Ze=createGraphics(e,t),Ke=createGraphics(e,t),Je=createGraphics(e,t),tt=createGraphics(500,500),nt=createGraphics(500,500),rt=createGraphics(500,500),_n(),Mn(),Sn(),await En(),Gn(),Rn(),bn=!0}function _n(){Et=parseInt(oe),randomSeed(Et),noiseSeed(Et)}function Mn(){Wt=Ir(p.training_traits),Cr(Wt)}async function En(){let eM ;Jt=r(),Qt=o(),[Xt,e]=await Promise.all([s(Jt),h(Qt)]),Ut=new V(Wt.visual,e.layers_config,e.weight_b64),Ut.updateAge(new Date),_n(),Wt.training=e.training_traits,Ht=e.model_name,$t=e.classes_name}function Sn(){le=min(width,height)/1024,ut=Rr.findIndex((e=>e[0]===Wt.visual.colorPalette)),ft=[["#ffffff","#231f20","#231f20"],["#231f20","#ffffff","#ffffff"],["#104da8","#ffffff","#ffffff"],["#722F1F","#FCE1B2","#FCE1B2"],["#e88120","#f9f2e5","#f9f2e5"],["#f6b941","#2E2E2E","#2E2E2E"],["#45daaa","#012221","#012221"],["#FM 1F1F1","#328DFE","#328DFE"],["#111822","#D3EB8D","#D3EB8D"],["#713FF9","#D6D5E6","#D6D5E6"],["#FBDA9D","#795106","#795106"],["#8f5b62","#ead0d0","#ead0d0"],["#eae4cb","#508cac","#508cac"],["#ffc6cc","#cc313d","#cc313d"],["#60A900","#E0FE00","#E0FE00"],["#507DBE","#D0D1D3","#D0D1D3"],["#305848","#E8F2EE","#E8F2EE"],["#2a2634","#5b6988","#cb78a2","#5b6988"],["#590e29","#fd5e53","#fd5e53","#ffe373"],["#0a141d","#57d4e4","#328195","#2A9ECF","#0ab6a8","#57d4e4"],["#3a2d28","#d5c2ac","#df6338","#3d9895","#d5c2ac"],["#030M 706","#77c4d9","#77c4d9","#77c4d9","#ffffff","#ffffff","#e72020","#e72020"],["#3a4664","#92f5ff","#f9ff94","#eaa0a2","#55dde0"],["#fbfaff","#f04bb1","#f04bb1","#fac373","#82cef0","#8b31ce"],["#000000","#ffffff","#ff0002","#f26522","#fdff00","#00ff03","#01fffe","#0000ff","#ff00ff"]];for(let e=0;e<ft.length;++e)for(let t=0;t<ft[e].length;++t)ft[e][t]=cr(ft[e][t]);pt=[],ct=ft[ut][0],st=ft[ut][1]}function Rn(){gn=document.querySelector("#upload"),pn=document.querySelector("#inputUpload"),gn.addEventListener("dblclick",M (()=>{if(!Lt&&!yn)if(In(Ie)&&cn==Ve-1)pn.click();else{if(4!=Pe&&5!=Pe&&(In(Ie)||cn!=Ve-1))return;fn=!0,dn=!0,Bt=0,un=0}})),pn.addEventListener("click",(()=>{pn.value=null,gn.style.display="block"})),pn.addEventListener("change",(()=>{const[e]=pn.files;e?(se=null,gn.style.display="none",Tn(URL.createObjectURL(e)),mn=e):gn.style.display="block"}))}function In(e){for(let t=0;t<e.length;++t){let n=0;for(let r=0;r<e[t].length;++r)e[t][r]>0&&++n;if(0==n)return!1}return!0}function Cn(){null!=se&&(un=0,Pt=!0,he=0,ue=0,drewM LineAnim=!0,ce=(ae/2+we/2)/le,loadImage(se.elt.src,(e=>{const[t,n,r]=Gt,i=createGraphics(t,n);i.image(e,0,0,t,n),i.loadPixels();const o=i.pixels.filter(((e,t)=>t%4!=3)),a=Ut.classifyImage(o);Zt=T([a,$t.map((e=>e.toUpperCase()))]).sort(((e,t)=>e[0]>t[0]?-1:1))})))}function Tn(e){se=createImg(e,""),se.hide(),Cn()}function An(){zn||(ce+=(width-ae-we)/tn/le),re(Xe),Xe.rect(ce*le,0,width,height),ie(Xe),un>=ge&&1==kt&&(kt=!1,un-=ge),kt&&(re($e),$e.strokeWeight(2*Fe),Jn(he,ze,ct,ct,$e),ie($e)),un>=ge&&0==kt&&(kt=!0,un-=geM ,he+=1,he==en&&(++ue,he=0,ce=(ae/2+we/2)/le,1==ue&&(Pt=!1,Dn(),ye=millis())))}function Dn(){At=!0,pe=!1,me=!1,tryButton=br("Try Again",width/2-225*le,height/2+265*le,290*le,40*le,kn),closeResultButton=br("Close",width/2+75*le,height/2+265*le,150*le,40*le,Ln)}function kn(){At=!1,tryButton.hide(),closeResultButton.hide(),pn.click()}function Ln(){Yt=!0,At=!1,Gn(),tryButton.hide(),closeResultButton.hide(),gn.style.display="block",se=null}function keyTyped(){bn&&!1===yn&&!1===yr()&&("i"!==key&&"I"!==key||(Dt=!Dt),"b"!==M key&&"B"!==key||(xn=!xn),"s"!==key&&"S"!==key||!1!==Lt||saveCanvasAtCurrentTime(),"k"!==key&&"K"!==key||!1!==Lt||save4KCanvasAtCurrentTime(),"u"!==key&&"U"!==key||!1!==Lt||!1!==At||!1!==fn||!1!==Pt||On())}function On(){Lt=!0,wn=null,vn=null,submitButton=br("Submit",width/2-155*le,height/2+115*le,150*le,40*le,Fn),closeSettingButton=br("Close",width/2+5*le,height/2+115*le,150*le,40*le,Yn),vt=createInput(),vt.position(width/2-252.5*le,height/2-40*le),vt.size(500*le,25*le),vt.style("font-size","15px"),vt.value(Jt||""),M zt=createInput(),zt.position(width/2-252.2*le,height/2+35*le),zt.size(500*le,25*le),zt.style("font-size","15px"),zt.value(Qt||"")}function Fn(){Vt=vt.value(),_t=zt.value(),submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide(),Lt=!1,yn=!0,Nn()}async function Nn(){[wn,vn,_]=await Promise.all([c(Vt),u(_t),O(1e3)]),yn=!1,wn&&vn?(n(Vt),i(_t),window.location.reload()):(Lt=!0,submitButton.show(),closeSettingButton.show(),vt.show(),zt.show())}function Bn(){Je.textFont("Trebuchet MS"),Je.noStroke(),pr(Je,600*le,M 200*le),Je.strokeWeight(1*le),Je.stroke(xt),Je.fill(xt),Je.textSize(50*le),Je.text("update()",width/2,height/2+2.5*le)}function Yn(){wn=null,vn=null,Lt=!1,submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide()}function Gn(){_n(),nn=Date.now(),pe=!1,me=!1,St=Wt.training.structure_gen,Rt=Wt.visual.birthYear,It=Wt.visual.lifeCycle,Ct=Wt.training.epoch_num,Tt=Wt.training.activation_func,Ft=Mr.findIndex((e=>e[0]==Wt.visual.hardwareAcceleration))+1,1==Ft?(Nt=30,fe=40):2==Ft?(Nt=15,fe=20):(Nt=2,fe=10);const e=UM t.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),ae=100*le,ht=50*le,Oe=Sr.findIndex((e=>e[0]==Wt.visual.nodeShape))+1,dt=Er.findIndex((e=>e[0M ]==Wt.visual.nodeFill))+1,lt=_r.findIndex((e=>e[0]==Wt.visual.pattern))+1,de=Math.tanh(Math.log10(Xt.avgfeerate)),de=map(de,0,1,.2,.8),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.lengM th;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=CeM [e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,at=.7,pt=[],xt=ft[ut][2],gt=ft[ut][ft[ut].length-1];for(let e=3;e<ft[ut].length-1;e++)pt.push(ft[ut][e]);mt=sr(xt,gt,pt,width),bt=[],wM t=[],yt=width/(Ve-1);for(let e=0;e<Ve;e++)bt.push(hr(mt,yt*e/width)),wt.push(hr(mt,yt*e/width));wt.unshift(bt[0]),wt.push(bt[bt.length-1]),hn=0,cn=0,un=0,Yt=!0;const n={xLeft:ae/8,xRight:width-ae/8,yTop:ae/8,yBottom:height-ae/8},r=Ce.map((e=>e.length));jt=new R(bt,r,n,Oe,le)}function Hn(e,t){let n=Ce[e].length;return[e*we+we/2+ae/2,height/2-(n-1)/2*ve+t*ve]}function $n(e,t){le=min(e,t)/1024,ae=100*le,ht=50*le,we=(e-ae)/Ve,ve=(t-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let nM =0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}xe=floor(De.length*de),Le=[],ke=[],ge=floor(map(de,.2,.8,15,2));for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,mt=sr(xt,gt,pt,e),bt=[],wt=[],yt=e/(Ve-1);for(let t=0;t<Ve;t++)bt.push(hr(mt,yt*t/e)),wt.push(hr(mt,yt*t/e));wt.unshift(bt[0]),wt.push(bt[bt.length-1])}function Xn(){const e=Ut.getBrainStatus();Gt=e.inpM utDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<YM e;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][nM ]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(randM om(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le}function Wn(){jt.update();const e=4==Pe?0:Kt;jt.draw(Qe,ct,dt,e,le)}function Un(){if(!bn)return ar(),void et.image(je,0,0);if(4==Pe||5==Pe)return Wn(),void et.image(Qe,0,0);un>=Nt&&hn<Ve&&(hn++,un=0);for(let e=0;e<hn;e++)1==dt?it=ot=bt[e]:(it=ct,ot=bt[e]),Kn(e,it,ot,$e);un>=Nt&&cn<Ve-1&&(cn++,un=0);for(let e=0;e<cn;e++)Zn(e)}function qn(){et.background(ct),Ue.background(255),Ue.rectModM e(CENTER),ne(Ue),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),Ue.stroke(st),Ue.strokeWeight(8*le),Ue.fill(ct),Qe.background(255),Qe.rectMode(CENTER),ne(Qe),Qe.strokeWeight(le),qe.background(255),qe.rectMode(CENTER),ne(qe),qe.textAlign(LEFT),$e.background(255),$e.rectMode(CENTER),ne($e),Xe.background(255),ne(Xe),Xe.strokeWeight(Ne),We.background(255),We.rectMode(CENTER),ne(We),We.fill(st),We.stroke(st),We.strokeWeight(.1*le),er(lt),We.noStroke(),xn&&(We.rect(ae/16,height/2,ae/8,height),We.rect(width-ae/16,height/2M ,ae/8,height),We.rect(width/2,ae/16,width,ae/8),We.rect(width/2,height-ae/16,width,ae/8)),Ze.background(255),Ze.rectMode(CENTER),ne(Ze),Ze.textAlign(CENTER,CENTER),Ze.textStyle(BOLD),Ze.stroke(st),Ze.strokeWeight(8*le),Ze.fill(ct),je.background(255),je.rectMode(CENTER),ne(je),je.textAlign(CENTER,CENTER),je.textStyle(BOLD),Ke.background(255),Ke.rectMode(CENTER),ne(Ke),Ke.textAlign(CENTER,CENTER),Ke.textStyle(BOLD),Ke.stroke(st),Ke.strokeWeight(8*le),Ke.fill(ct),Je.background(255),Je.rectMode(CENTER),ne(Je),Je.textAlM ign(CENTER,CENTER),Je.textStyle(BOLD),Je.stroke(st),Je.strokeWeight(8*le),Je.fill(ct),Un(),et.image(We,0,0),Pt&&An(),et.image(Xe,0,0),et.image($e,0,0),At&&(tr(),et.image(Ue,0,0)),fn&&(lr(),et.image(Ze,0,0)),Lt&&(or(),et.image(Ke,0,0)),Dt&&(ir(),et.image(qe,0,0)),yn&&(Bn(),et.image(Je,0,0))}function draw(){const e=Date.now();bn&&(Ut.updateAge(new Date(e)),Xn()),qn(),image(et,0,0),zn||un++}function Zn(e){let t,n=Ce[e].length,r=Ce[e+1].length;for(let i=0;i<n;i++){const[n,o]=Hn(e,i);for(let a=0;a<r;a++){const[r,l]=Hn(eM +1,a);t=map(min(Ce[e][i],Ce[e+1][a]),0,1,0,.5),ur(n,o,r,l,bt[e],bt[e+1],Xe,t)}}}function Kn(e,t,n,r){let i,o,a,l=Ce[e].length;for(let s=0;s<l;s++){const[l,h]=Hn(e,s);i=Ce[e][s],a=map(Be,1/30,1,3,10),o=map(Ce[e][s],0,1,2*a,0)*le,o<1.5*le&&(o=0),Qn(l,h,ze,Oe,t,n,o,i,r)}}function Jn(e,t,n,r,i){for(let o=0;o<Le[e].length;o++)Qn(Le[e][o][0],Le[e][o][1],t,Oe,n,r,0,1,i)}function Qn(e,t,n,r,i,o,a,l,s){s.stroke(dr(o,map(l,0,1,.25,1))),s.fill(dr(i,map(l,0,1,.15,1))),s.strokeWeight(Fe),fr([a],s),3==dt&&s.fill(dr(i,0)),1==r?s.M ellipse(e,t,n):2==r?s.rect(e,t,7*n/8,7*n/8):3==r&&(s.beginShape(),s.vertex(e-4*n/7,t),s.vertex(e,t-4*n/7),s.vertex(e+4*n/7,t),s.vertex(e,t+4*n/7),s.endShape(CLOSE))}function er(e){if(1==e);else if(2==e){We.strokeWeight(1*le);for(let e=ht/4;e<width+ht/4;e+=ht)for(let t=ht/4;t<height+ht/4;t+=ht)We.point(e,t)}else if(3==e){ht=25*le;for(let e=ht/2;e<height+ht/2;e+=ht)We.line(0,e,width,e);for(let e=ht/2;e<width+ht/2;e+=ht)We.line(e,0,e,height)}}function tr(){Ue.textFont("Trebuchet MS"),Ue.textAlign(LEFT,CENTER),Ue.noStrM oke(),pr(Ue,800*le,500*le),Ue.noStroke(),Ue.fill(dr(st,.75)),Ue.rect(width/2,height/2-100*le,800*le,300*le,25*le,25*le,0,0),Ue.fill(st),Ue.rect(width/2-250*le,height/2-100*le,225*le,225*le),Ue.image(se.elt,width/2-357.5*le,height/2-207.5*le,215*le,215*le);let e=100*Zt[0][0];Ue.fill(ct),Ue.textSize(25*le),Ue.textStyle(NORMAL),1==me&&(e>=0&&e<20?Ue.text("I have a feeling this image belongs to",width/2-100*le,height/2-170*le):e>=20&&e<40?Ue.text("I have a hunch this image belongs to",width/2-100*le,height/2-170*le):e>M =40&&e<60?Ue.text("I think this image belongs to",width/2-100*le,height/2-170*le):e>=60&&e<80?Ue.text("I'm almost certain this image belongs to",width/2-100*le,height/2-170*le):Ue.text("I'm positive this image belongs to",width/2-100*le,height/2-170*le));let t=e.toFixed(2);"100.00"==t&&(t="100"),1==me&&Ue.text("I'm "+t+"% confident that I'm right!",width/2-100*le,height/2-25*le),example=Zt.map((e=>e[1])),be=Ue.textWidth('"FIDENZAAAA"'),defaultPhrase=Ue.textWidth('"PERPENDICULAR INHABITATION"'),Ue.textStyle(BOLD);coM nst n=me?example[0]:random(example);if(1===n.split(" ").length){let e=75*be/Ue.textWidth('"'+n+'"');e>75&&(e=75),Ue.textSize(e*le),Ue.text('"'+n+'"',width/2-100*le,height/2-90*le)}else nr(width/2-100*le,height/2-90*le,460*le,110*le,n,Ue);if(millis()-ye>1500&&(me=!0),C(tt,nt,st,ct,Pe,Mt),Ue.image(nt,width/2-370*le,height/2+70*le,80*le,80*le),3==Pe){let e;e=map(Mt,50,60,.25,1.3),I(rt,e),Ue.image(rt,width/2-370*le,height/2+70*le,80*le,80*le)}let r,i;Ue.image(tt,width/2-370*le,height/2+70*le,80*le,80*le),Ue.fill(xt),UeM .textSize(40*le),Ue.text("INTELLIGENCE INFO",width/2-275*le,height/2+115*le),Ue.textSize(18*le),Ue.textStyle(NORMAL),Ue.circle(width/2-360*le,height/2+180*le,7.5*le),1==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s growing and getting smarter by the day.`:2==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s stable and it has reached peak performance.`:3==Pe&&(r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s decaying and losing its luster.`),i=2==Pe?"The Perceptron remains stable for M some time before entering the decay phase.":`Wait until ${new Date(an).toLocaleString("en-US")} for your Perceptron to reach its peak performance.`,Ue.text(r,width/2-350*le,height/2+180*le),Ue.circle(width/2-360*le,height/2+210*le,7.5*le),Ue.text(i,width/2-350*le,height/2+210*le),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),gr(Ue,width/2-225*le,width/2+65*le,height/2+265*le,height/2+305*le,"SELECT ANOTHER IMAGE"),gr(Ue,width/2+75*le,width/2+225*le,height/2+265*le,height/2+305*le,"CLOSE")}function nr(e,t,n,r,i,o){M let a=i.split(" "),l=75*be/o.textWidth('"'+i+'"'),s=0,h=[],c=[],u=[],f="",d="";if(l>=50)l>75&&(l=75),o.textSize(l*le),o.text('"'+i+'"',e,t);else if(l<50){if(l=50*defaultPhrase/o.textWidth('"'+i+'"'),l>30){if(l>50&&(l=50),[f,d]=rr(l,n,s,h,c,a,f,d,Ue),0==c.length)return o.textSize(l*le),void o.text('"'+i+'"',e,t);for(s=0,h=[],c=[];o.textWidth(d)>n/le;)l=l*n/le/o.textWidth(d),f="",d="",[f,d]=rr(l,n,s,h,c,a,f,d,Ue)}else{l=30,o.textSize(l);for(let e=0;e<a.length;e++)s+=o.textWidth(" "+a[e]),s<=n/le?h.push(a[e]):s>n/le&&M s<=n/le*2?c.push(a[e]):u.push(a[e]);for(let e=1;e<h.length;e++)f=f+" "+h[e];if(f='"'+h[0]+f,0==u.length){for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+c[c.length-1]+'"'}else if(1==c.length)d="... "+u[u.length-1]+'"';else{for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+"... "+u[u.length-1]+'"'}}o.textSize(l*le);let r=1.25*(o.textDescent()+o.textAscent());o.text(f,e,t-r/2),o.text(d,e,t+r/2)}}function rr(e,t,n,r,i,o,a,l,s){s.textSize(e);for(let e=0;e<o.length;e++)(n+=s.textWidth(" "+o[e]))<=t/le?r.push(o[e]):i.push(o[e]M );for(let e=1;e<r.length;e++)a=a+" "+r[e];if(a='"'+r[0]+a,0==i.length&&(a+='"',l=""),1==i.length)l=i[i.length-1]+'"';else{for(let e=0;e<i.length-1;e++)l=l+i[e]+" ";l=l+i[i.length-1]+'"'}return[a,l]}function ir(){const e=45*le;qe.textFont("Tahoma"),qe.stroke(st),qe.strokeWeight(2*le),qe.fill(ct),qe.rect(width/2,e/2+height-87.5*le,600*le,90*le),qe.fill(st),qe.rect(width/2-150*le,e+height-170*le,300*le,30*le),qe.fill(ct),qe.rect(width/2+150*le,e+height-170*le,300*le,30*le),qe.noStroke(),qe.fill(ct),qe.textSize(15*le),M qe.textStyle(BOLD),qe.text("PERCEPTRON INFORMATION",width/2-285*le,e+height-165*le),qe.fill(xt),qe.text("ARTWORK NAME:",width/2+10*le,e+height-165*le),qe.textAlign(RIGHT),qe.textStyle(ITALIC),qe.text("Perceptron #"+Et,width/2+285*le,e+height-165*le);const[t,n]=It.split(" ");let r;"60 Years"===It?r="1 Year":"60 Months"===It?r="1 Month":"60 Weeks"===It?r="1 Week":"60 Days"===It?r="1 Day":"12 Hours"===It&&(r="12 Minutes"),data=[["AI MODEL NAME:",B(12*le,Ht,140*le)],["SCALE:","1:"+Te],["NUMBER OF CLASSES:",$t.length],[M "BIRTH YEAR:",Rt],["NUMBER OF REBIRTHS:",sn.toString()],["AGE:",`${Math.ceil(Mt)} Perceptron Years`],["ONE PERCEPTRON YEAR:",`${r}`],["STATE:",Ot[Pe]],["ACTIVE NEURONS:",`${round(ln*rn)} / ${ln}`],["NEXT STATE TIME:",vr(new Date(on))]],qe.fill(xt);const i=data.length/2;for(let t=0;t<data.length;++t){const n=t<i,r=n?width/2-285*le:width/2+10*le,o=n?width/2-10*le:width/2+285*le,a=e+height-(135-t%i*15)*le;qe.textStyle(BOLD),qe.textAlign(LEFT),qe.textSize(12*le),qe.text(data[t][0],r,a),qe.textStyle(ITALIC),qe.textAlignM (RIGHT),qe.textSize(12*le),qe.text(data[t][1],o,a)}}function or(){Ke.textFont("Trebuchet MS"),Ke.noStroke(),pr(Ke,600*le,200*le),gr(Ke,width/2-155*le,width/2-5*le,height/2+115*le,height/2+155*le,"UPDATE"),gr(Ke,width/2+5*le,width/2+155*le,height/2+115*le,height/2+155*le,"CLOSE"),Ke.textAlign(LEFT),Ke.fill(xt),Ke.text("UPDATE BITCOIN FULL NODE ADDRESS",width/2-252.5*le,height/2-55*le),Ke.text("UPDATE MODEL ADDRESS",width/2-252.5*le,height/2+20*le),Ke.textAlign(RIGHT),Ke.textStyle(ITALIC),Ke.textSize(15*le),0==wn&&KeM .text("(*) Invalid Address",width/2+252.5*le,height/2-53*le),0==vn&&Ke.text("(*) Invalid Model",width/2+252.5*le,height/2+23*le)}function ar(){je.textFont("Trebuchet MS"),je.fill(st),je.textSize(50*le),je.stroke(st),je.strokeWeight(1*le),je.text("main()",width/2,height/2)}function lr(){un>=20&&1==dn&&(dn=!1,un=0),dn&&(Ze.textFont("Trebuchet MS"),Ze.stroke(st),Ze.fill(ct),Ze.rect(width/2,height/2,600*le,150*le,25*le),Ze.fill(xt),Ze.textSize(75*le),Ze.noStroke(),1==Pe?Ze.text("GROWING",width/2,height/2+5*le):3==Pe?ZeM .text("AGING",width/2,height/2+5*le):4==Pe?Ze.text("DEAD",width/2,height/2+5*le):5==Pe&&Ze.text("BIRTH",width/2,height/2+5*le)),un>=20&&0==dn&&(dn=!0,un=0,Bt++,3==Bt&&(fn=!1))}function sr(e,t,n,r){let i=[],o=r/(n.length+1),a=color(e),l=color(t);i.push(a);for(let e=0;e<n.length;e++){let t=color(n[e]);for(let e=1;e<=o;e++){let n=lerpColor(a,t,e/o);i.push(n)}a=t}for(let e=1;e<o;e++){let t=lerpColor(a,l,e/o);i.push(t)}if(i.push(l),i.length>r)i.splice(r);else if(i.length<r){let e=i[i.length-1];for(;i.length<r;)i.push(e)M }return i}function hr(e,t){let n=e.length,r=Math.floor(t*n);return r>=n&&(r=n-1),e[r]}function cr(e){e=e.replace("#","");var t=parseInt(e,16);return color(t>>16&255,t>>8&255,255&t)}function ur(e,t,n,r,i,o,a,l){var s=a.drawingContext.createLinearGradient(e,t,n,r);s.addColorStop(0,i),s.addColorStop(1,o),a.drawingContext.strokeStyle=s,a.drawingContext.globalAlpha=l,a.line(e,t,n,r),a.drawingContext.globalAlpha=1}function fr(e,t){t.drawingContext.setLineDash(e)}function dr(e,t){let n=color(e),r=red(n),i=green(n),o=blue(M n);return color(r,i,o,255*t)}function xr(e,t,n,r){return mouseX>e&&mouseX<t&&mouseY>n&&mouseY<r}function gr(e,t,n,r,i,o){e.strokeWeight(1*le),e.stroke(st);const[a,l]=xr(t,n,r,i)?[xt,ct]:[ct,xt];e.fill(a),e.push(),e.rectMode(CORNERS),e.rect(t,r,n,i,5*le),e.pop(),e.noStroke(),e.textSize(20*le),e.fill(l),e.text(o,(t+n)/2,(46*r+54*i)/100)}function pr(e,t,n){e.fill(0,0,0,75),e.rect(width/2,height/2,width,height),e.stroke(st),e.fill(ct),e.rect(width/2,height/2,t,n,25*le)}function mr(e,t){resizeCanvas(e,t,!0),Xe.resizeCanM vas(e,t,!0),$e.resizeCanvas(e,t,!0),We.resizeCanvas(e,t,!0),Ue.resizeCanvas(e,t,!0),qe.resizeCanvas(e,t,!0),Qe.resizeCanvas(e,t,!0),je.resizeCanvas(e,t,!0),Ze.resizeCanvas(e,t,!0),Ke.resizeCanvas(e,t,!0),Je.resizeCanvas(e,t,!0),et.resizeCanvas(e,t,!0)}function br(e,t,n,r,i,o){const a=J(e);return a.position(t,n),a.size(r,i),a.style("opacity","0"),a.mouseClicked(o),a}function yr(){return null!=vt&&vt?.isFocused()||null!=zt&&zt?.isFocused()}function wr(e,t,n,r){let i;if(e<=3){i=`Hey ${String.fromCodePoint(128075)}, I'M m ${n}, ${t} years old. I can detect ${r.length} NFT collections: `;let e=0;for(let t=0;t<r.length;++t){const n=r[t];if(e+n.length>500){i+=", etc";break}t==r.length-1?i+=", and ":t>0&&(i+=", "),i+=n,e+=n.length}i+=". ",t<=5?i+="However, I am only a baby, so my recognition ability is not accurate. I'm in the state of Growing both looks and intelligence.":t<=13?i+="I am now a child. My recognition ability is becoming better, but still not very accurate. I'm in the state of Growing both looks and intelligence.":t<=25?M i+="I have grown up to be a teen. My recognition ability almost reaches the peak, but I will still mess up sometimes. I'm in the state of Growing both looks and intelligence.":t<=50?i+="I finally reach adulthood. My recognition is fully functional now. I'm in the Stable state, where I am the most intelligent with all neurons activated.":t<=60&&(i+="I am now an old Perceptron, so my recognition ability is no longer the best. I'm in the Decaying state, meaning that my neurons are dying, and my intelligence is decreasM ing over time.")}else 4==e?i=`${n} is Dead. However, this is not the end to its story...`:5==e&&(i=`${n} is now in the Rebirth state, and is preparing to start a new life.`);return i}function vr(e){const t=e.getDate(),n=e.toLocaleString("en-US",{month:"long"}),r=e.getFullYear();let i=e.getHours().toString();1==i.length&&(i="0"+i);let o=e.getMinutes().toString();return 1==o.length&&(o="0"+o),`${Y(t)} ${n} ${r} | ${i}:${o}`}saveCanvasAtCurrentTime=()=>{save(N())},save4KCanvasAtCurrentTime=()=>{const e=width,t=height,M n=min(4096/min(e,t),1e4/max(e,t)),r=e*n,i=t*n;mr(r,i),zn=!0,$n(r,i),qn();let o="4K_"+N()+".png";saveCanvas(et,o),mr(e,t),$n(e,t),zn=!1};const zr=[["60 Years",3,365],["60 Months",40,30],["60 Weeks",37,7],["60 Days",20,1]],Vr=[["1943",1],["1951",1.5],["1957",2],["1969",2.5],["1970",3],["1980",3.5],["1982",4],["1986",4.5],["1988",5],["1997",5.5],["1998",6],["2002",6.5],["2009",7],["2012",7.5],["2014",8],["2015",8.5],["2016",9],["2023",15]],_r=[["Plain",20],["Dotted",40],["Squared",40]],Mr=[["Basic",30],["Standard",60]M ,["Advanced",10]],Er=[["MNIST",70],["CIFAR",25],["IMAGENET",5]],Sr=[["Theano",60],["Torch",30],["TensorFlow",10]],Rr=[["Whitepaper",2],["Blackboard",2],["Blueprint",2],["Nak",74/14],["Jims",74/14],["Level 10",74/14],["Flips",74/14],["Level 14",74/14],["III",74/14],["XMB",74/14],["Info",74/14],["Adventure",74/14],["Marigold",74/14],["Phoenix",74/14],["Love",74/14],["Cachet",74/14],["Human",74/14],["Twilight",3],["Sunset",3],["Aurora",3],["Liminal Space",3],["D Vu",3],["Lucid Dream",3],["Parallel",1],["MultiversM e",1]];function Ir(e){for(let e=0;e<100;++e)random(1);return{visual:{pattern:k(_r),hardwareAcceleration:k(Mr),nodeFill:k(Er),nodeShape:k(Sr),colorPalette:k(Rr),lifeCycle:k(zr),birthYear:k(Vr)},training:e}}function Cr(e){window.$generativeTraits={"Network Architecture":e.training.structure_gen,"Hidden Layers":e.training.n_layers,"Max Neurons Per Hidden Layer":e.training.max_nodes,"Activation Function":e.training.activation_func,"Training Epochs":e.training.epoch_num,Dataset:e.visual.nodeFill,"Deep Learning FrameworkM ":e.visual.nodeShape,"Hardware Acceleration":e.visual.hardwareAcceleration,"Paper Pattern":e.visual.pattern,"Life Cycle":e.visual.lifeCycle,"Birth Year":e.visual.birthYear,"Color Palette":e.visual.colorPalette}} <script defer src="https://static.cloudflareinsights.com/beacon.min.js/v2b4487d741ca48dcbadcaf954e159fc61680799950996" integrity="sha512-D/jdE0CypeVxFadTejKGTzmwyV10c1pxZk/AqjJuZbaJwGMyNHY3q/mTPWqMUnFACfCTunhZUVcd4cV78dK1pQ==" data-cf-beacon='{"rayId":"7b4e4285a950a216","version":"2023.3.0",Ln"b":1,"token":"6c07c178c94442f695e7a0a2aaee641a","si":100}' crossorigin="anonymous"></script> text/plain;charset=utf-8 @{"p":"brc-20","op":"deploy","tick":" ","max":"500","lim":"1"}h! text/plain;charset=utf-8 "p":"sns","op":"reg","name":"ddd.unisat" !22222222222222222222222222222222222222222222222222 %&'()*456789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz &'()*56789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "cape"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "honey pot"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "arrow wounds"}]} text/plain;charset=utf-8 {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "pauldrons"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "tiger"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "moon"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "fire"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "cape"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "bloody"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "cape"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "tiger"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "golden armor"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "bloody"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "eagle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "undead"}, {"trait_type": "Artifacts", "value": "axe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "golden"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "badger"}, {"trait_type": "Artifacts", "value": "pauldrons"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "fire"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "badger"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "diamond hands"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "pirate flag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "skull"}, {"trait_type": "Artifacts", "value": "fire sword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "tribal tattoo"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "bloody"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "axe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "fire"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "skull"}, {"trait_type": "Artifacts", "value": "shield"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "mage robes"}, {"trait_type": "Mane", "value": "fire"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "honey pot"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "bag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "golden armor"}, {"trait_type": "Mane", "value": "blue fire"}, {"trait_type": "Claws", "value": "honey pot"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "mage robes"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "badger"}, {"trait_type": "Artifacts", "value": "parrot"}]} text/plain;charset=utf-8 6{"p":"brc-20","op":"mint","tick":"1M","amt":"1000000"}h! text/plain;charset=utf-8 6{"p":"sns","op":"reg","name":"universalpictures.sats"}h! {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "fire"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "pauldrons"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "rainbow"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "laser"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "fire"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "orc"}, {"trait_type": "Mane", "value": "dragon"}, {"trait_type": "Claws", "value": "fire"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "shield"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "zombie"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "wizard staff"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "moon"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "undead"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "moon"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "fire"}, {"trait_type": "Claws", "value": "honey pot"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "quiver"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "axe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "shield"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "tribal tattoo"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "golden"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "axe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "wizard staff"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "orc"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "badger"}, {"trait_type": "Artifacts", "value": "lamp"}]} text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"rssc","amt":"1000"}h! {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "moon"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "fire"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "arrow wounds"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "honey pot"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "sword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "golden armor"}, {"trait_type": "Mane", "value": "fire"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "wizard staff"}]} text/html;charset=utf-8 <meta charset="utf-8" /> position: relative; width: var(--width); height: var(--height); border: 1px solid blue; position: relative; <div id="upload"> <input id="inputUpload" type="file"> function e(e){"use strict";return new function e(t){let n="global"==t?window:this;n.canvas=document.createElement("canvas");let r=n.canvas.getContext("2d");n.width=100,n.height=100,n.canvas.width=n.width,n.canvas.height=n.height,"offscreen"!=t&&(document.body?document.body.appendChild(n.canvas):window.addEventListener("load",(function(){document.body.appendChild(n.canvas)}))),g(),n.MAGIC=161533525,n.RGB=0,n.HSV=1,n.HM SB=1,n.CHORD=0,n.PIE=1,n.OPEN=2,n.RADIUS=1,n.CORNER=2,n.CORNERS=3,n.ROUND="round",n.SQUARE="butt",n.PROJECT="square",n.MITER="miter",n.BEVEL="bevel",n.CLOSE=1,n.BLEND="source-over",n.REMOVE="destination-out",n.ADD="lighter",n.DARKEST="darken",n.LIGHTEST="lighten",n.DIFFERENCE="difference",n.SUBTRACT="subtract",n.EXCLUSION="exclusion",n.MULTIPLY="multiply",n.SCREEN="screen",n.REPLACE="copy",n.OVERLAY="overlay",n.HARD_LIGHT="hard-light",n.SOFT_LIGHT="soft-light",n.DODGE="color-dodge",n.BURN="color-burn",n.NORMAL="norM mal",n.ITALIC="italic",n.BOLD="bold",n.BOLDITALIC="italic bold",n.CENTER="center",n.LEFT="left",n.RIGHT="right",n.TOP="top",n.BOTTOM="bottom",n.BASELINE="alphabetic",n.LANDSCAPE="landscape",n.PORTRAIT="portrait",n.ALT=18,n.BACKSPACE=8,n.CONTROL=17,n.DELETE=46,n.DOWN_ARROW=40,n.ENTER=13,n.ESCAPE=27,n.LEFT_ARROW=37,n.OPTION=18,n.RETURN=13,n.RIGHT_ARROW=39,n.SHIFT=16,n.TAB=9,n.UP_ARROW=38,n.HALF_PI=Math.PI/2,n.PI=Math.PI,n.QUARTER_PI=Math.PI/4,n.TAU=2*Math.PI,n.TWO_PI=2*Math.PI,n.THRESHOLD=1,n.GRAY=2,n.OPAQUE=3,n.INVEM RT=4,n.POSTERIZE=5,n.DILATE=6,n.ERODE=7,n.BLUR=8,n.ARROW="default",n.CROSS="crosshair",n.HAND="pointer",n.MOVE="move",n.TEXT="text",n.VIDEO={video:!0,audio:!1},n.AUDIO={video:!1,audio:!0},n.SHR3=1,n.LCG=2,n.HARDWARE_FILTERS=!0,n.hint=function(e,t){n[e]=t},n.frameCount=0,n.mouseX=0,n.mouseY=0,n.pmouseX=0,n.pmouseY=0,n.mouseButton=null,n.keyIsPressed=!1,n.mouseIsPressed=!1,n.key=null,n.keyCode=null,n.pixels=null,n.accelerationX=0,n.accelerationY=0,n.accelerationZ=0,n.rotationX=0,n.rotationY=0,n.rotationZ=0,n.relRotatM ionX=0,n.relRotationY=0,n.relRotationZ=0,n.pAccelerationX=0,n.pAccelerationY=0,n.pAccelerationZ=0,n.pRotationX=0,n.pRotationY=0,n.pRotationZ=0,n.pRelRotationX=0,n.pRelRotationY=0,n.pRelRotationZ=0,n.touches=[],n._styleCache=[{colorMode:n.RGB,noStroke:!1,noFill:!1,ellipseMode:n.CENTER,rectMode:n.CORNER,curveDetail:20,curveAlpha:0,textFont:"sans-serif",textSize:12,textLeading:12,textStyle:"normal"}],n._style=n._styleCache[n._styleCache.length-1],n._noLoop=!1,n._pixelDensity=1,n._frameRate=null,n._tint=null;let i=nullM ,o=!0,a=[],l=null,s=0,h={},c=0,u=null,f=null,d=null;Object.defineProperty(n,"deviceOrientation",{get:function(){return 90==Math.abs(window.orientation)?n.LANDSCAPE:n.PORTRAIT}}),Object.defineProperty(n,"windowWidth",{get:function(){return window.innerWidth}}),Object.defineProperty(n,"windowHeight",{get:function(){return window.innerHeight}}),Object.defineProperty(n,"drawingContext",{get:function(){return r}}),n.createCanvas=function(e,t){return n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t,g(),n.canvas},nM .resizeCanvas=function(e,t){n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t},n.createGraphics=n.createImage=function(t,n){let r=new e("offscreen");return r.createCanvas(t,n),r.noLoop(),r},n.pixelDensity=function(e){return null==e||(n._pixelDensity=e,n.canvas.width=Math.ceil(n.width*e),n.canvas.height=Math.ceil(n.height*e),n.canvas.style.width=n.width+"px",n.canvas.style.height=n.height+"px",r.scale(n._pixelDensity,n._pixelDensity),g()),n._pixelDensity},n.map=function(e,t,n,r,i,o){let a=r+1*(e-t)/(n-t)*(i-r)M ;return o?r<i?Math.min(Math.max(a,r),i):Math.min(Math.max(a,i),r):a},n.lerp=function(e,t,n){return e*(1-n)+t*n},n.constrain=function(e,t,n){return Math.min(Math.max(e,t),n)},n.dist=function(){return 4==arguments.length?Math.hypot(arguments[0]-arguments[2],arguments[1]-arguments[3]):Math.hypot(arguments[0]-arguments[3],arguments[1]-arguments[4],arguments[2]-arguments[5])},n.norm=function(e,t,r){return n.map(e,t,r,0,1)},n.sq=function(e){return e*e},n.fract=function(e){return e-Math.floor(e)},n.degrees=function(e){retM urn 180*e/Math.PI},n.radians=function(e){return e*Math.PI/180},n.abs=Math.abs,n.ceil=Math.ceil,n.exp=Math.exp,n.floor=Math.floor,n.log=Math.log,n.mag=Math.hypot,n.max=Math.max,n.min=Math.min,n.round=Math.round,n.sqrt=Math.sqrt,n.sin=Math.sin,n.cos=Math.cos,n.tan=Math.tan,n.asin=Math.asin,n.acos=Math.acos,n.atan=Math.atan,n.atan2=Math.atan2,n.Vector=function(e,t,r){let i=this;i.x=e||0,i.y=t||0,i.z=r||0;let o=null,a=null;function l(e,t,n){return null!=e.x?e:null!=t?{x:e,y:t,z:n||0}:{x:e,y:e,z:e}}function s(){null==a&M &(a=i.x*i.x+i.y*i.y+i.z*i.z,o=Math.sqrt(a))}function h(){a=null,o=null}i.set=function(e,t,n){i.x=e||0,i.y=t||0,i.z=n||0},i.copy=function(){return new n.Vector(i.x,i.y,i.z)},i.add=function(){let e=l.apply(null,arguments);return i.x+=e.x,i.y+=e.y,i.z+=e.z,h(),i},i.rem=function(){let e=l.apply(null,arguments);return i.x%=e.x,i.y%=e.y,i.z%=e.z,h(),i},i.sub=function(){let e=l.apply(null,arguments);return i.x-=e.x,i.y-=e.y,i.z-=e.z,h(),i},i.mult=function(){let e=l.apply(null,arguments);return i.x*=e.x,i.y*=e.y,i.z*=e.z,hM (),i},i.div=function(){let e=l.apply(null,arguments);return i.x/=e.x,i.y/=e.y,i.z/=e.z,h(),i},i.mag=function(){return s(),o},i.magSq=function(){return s(),a},i.dot=function(){let e=l.apply(null,arguments);return i.x*e.x+i.y*e.y+i.z*e.z},i.dist=function(){let e=l.apply(null,arguments),t=i.x-e.x,n=i.y-e.y,r=i.z-e.z;return Math.sqrt(t*t+n*n+r*r)},i.cross=function(){let e=l.apply(null,arguments),t=i.y*e.z-i.z*e.y,n=i.z*e.x-i.x*e.z,r=i.x*e.y-i.y*e.x;return i.x=t,i.y=n,i.z=r,h(),i},i.normalize=function(){s();let e=o;retuM rn i.x/=e,i.y/=e,i.z/=e,o=1,a=1,i},i.limit=function(e){s();if(o>e){let t=e/o;i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e}return i},i.setMag=function(e){s();let t=e/o;return i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e,i},i.heading=function(){return Math.atan2(i.y,i.x)},i.rotate=function(e){let t=Math.cos(e),n=Math.sin(e),r=i.x*t-i.y*n,o=i.x*n+i.y*t;return i.x=r,i.y=o,i},i.angleBetween=function(){let e=l.apply(null,arguments);const t=i.dot(e)/(i.mag()*e.mag());let n;return n=Math.acos(Math.min(1,Math.max(-1,t))),n*Math.sign(i.cross(e).z||1)},M i.lerp=function(e,t){return i.x=i.x*(1-t)+e.x*t,i.y=i.y*(1-t)+e.y*t,i.z=i.z*(1-t)+e.z*t,h(),i},i.reflect=function(e){return e.normalize(),i.sub(e.mult(2*i.dot(e)))},i.array=function(){return[i.x,i.y,i.z]},i.equals=function(e,t){return null==t&&null==(t=Number.EPSILON)&&(t=0),Math.abs(e.x-i.x)<t&&Math.abs(e.y-i.y)<t&&Math.abs(e.z-i.z)<t},i.fromAngle=function(e,t){return null==t&&(t=1),o=t,a=t*t,i.x=t*Math.cos(e),i.y=t*Math.sin(e),i.z=0,i},i.fromAngles=function(e,t,n){null==n&&(n=1),o=n,a=n*n;const r=Math.cos(t),l=MaM th.sin(t),s=Math.cos(e),h=Math.sin(e);return i.x=n*h*l,i.y=-n*s,i.z=n*h*r,i},i.random2D=function(){return o=1,a=1,i.fromAngle(Math.random()*Math.PI*2)},i.random3D=function(){return o=1,a=1,i.fromAngles(Math.random()*Math.PI*2,Math.random()*Math.PI*2)},i.toString=function(){return`[${i.x}, ${i.y}, ${i.z}]`}},n.Vector.add=function(e,t){return new n.Vector(e.x+t.x,e.y+t.y,e.z+t.z)},n.Vector.rem=function(e,t){return new n.Vector(e.x%t.x,e.y%t.y,e.z%t.z)},n.Vector.sub=function(e,t){return new n.Vector(e.x-t.x,e.y-t.y,e.M z-t.z)},n.Vector.mult=function(e,t){return null==t.x?new n.Vector(e.x*t,e.y*t,e.z*t):new n.Vector(e.x*t.x,e.y*t.y,e.z*t.z)},n.Vector.div=function(e,t){return null==t.x?new n.Vector(e.x/t,e.y/t,e.z/t):new n.Vector(e.x/t.x,e.y/t.y,e.z/t.z)},n.Vector.dist=function(e,t){return Math.hypot(e.x-t.x,e.y-t.y,e.z-t.z)},n.Vector.cross=function(e,t){return new n.Vector(e.y*t.z-e.z*t.y,e.z*t.x-e.x*t.z,e.x*t.y-e.y*t.x)},n.Vector.lerp=function(e,t,r){return new n.Vector(e.x*(1-r)+t.x*r,e.y=e.y*(1-r)+t.y*r,e.z=e.z*(1-r)+t.z*r)},n.M Vector.equals=function(e,t,n){return e.equals(t,n)};for(let e of["fromAngle","fromAngles","random2D","random3D"])n.Vector[e]=function(t,r,i){return(new n.Vector)[e](t,r,i)};function x(e,t,n){let r,i,o,a,l,s,h,c,u;if(0==t)return[255*(r=n),255*(i=n),255*(o=n)];switch((a=e)>360&&(a=0),h=n*(1-t),c=n*(1-t*(s=(a/=60)-(l=~~a))),u=n*(1-t*(1-s)),l){case 0:r=n,i=u,o=h;break;case 1:r=c,i=n,o=h;break;case 2:r=h,i=n,o=u;break;case 3:r=h,i=c,o=n;break;case 4:r=u,i=h,o=n;break;default:r=n,i=h,o=c}return[255*r,255*i,255*o]}functioM n g(){r.fillStyle="white",r.strokeStyle="black",r.lineCap="round",r.lineJoin="miter"}function p(e){if(0<=e&&e<2*Math.PI)return e;for(;e<0;)e+=2*Math.PI;for(;e>=Math.PI;)e-=2*Math.PI;return e}function m(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;let c=p(a),u=p(l);r.beginPath();for(let a=0;a<h+1;a++){let l=a/h,s=n.lerp(c,u,l),f=Math.cos(s)*i/2,d=Math.sin(s)*o/2;r[a?"lineTo":"moveTo"](e+f,t+d)}s==n.CHORD?r.closePath():s==n.PIE&&(r.lineTo(e,t),r.closePath()),n._style.noFill||r.fill(),n._style.noStrokM e||r.stroke()}function b(e,t,i,o){n._style.noFill&&n._style.noStroke||(r.beginPath(),r.ellipse(e,t,i/2,o/2,0,0,2*Math.PI),n._style.noFill||r.fill(),n._style.noStroke||r.stroke())}function y(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;if(null==a)return function(e,t,i,o){n._style.noFill||r.fillRect(e,t,i,o),n._style.noStroke||r.strokeRect(e,t,i,o)}(e,t,i,o);if(null==l)return y(e,t,i,o,a,a,a,a);const c=Math.min(Math.abs(o),Math.abs(i))/2;a=Math.min(c,a),l=Math.min(c,l),h=Math.min(c,h),s=Math.min(c,s)M ,r.beginPath(),r.moveTo(e+a,t),r.arcTo(e+i,t,e+i,t+o,l),r.arcTo(e+i,t+o,e,t+o,s),r.arcTo(e,t+o,e,t,h),r.arcTo(e,t,e+i,t,a),r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke()}function w(){a=[]}n.createVector=function(e,t,r){return new n.Vector(e,t,r)},n.curvePoint=function(e,t,n,r,i){const o=i*i*i,a=i*i;return e*(-.5*o+a-.5*i)+t*(1.5*o-2.5*a+1)+n*(-1.5*o+2*a+.5*i)+r*(.5*o-.5*a)},n.bezierPoint=function(e,t,n,r,i){const o=1-i;return Math.pow(o,3)*e+3*Math.pow(o,2)*i*t+3*o*Math.pow(i,2)*n+Math.pow(i,M 3)*r},n.curveTangent=function(e,t,n,r,i){const o=i*i;return e*(-3*o/2+2*i-.5)+t*(9*o/2-5*i)+n*(-9*o/2+4*i+.5)+r*(3*o/2-i)},n.bezierTangent=function(e,t,n,r,i){const o=1-i;return 3*r*Math.pow(i,2)-3*n*Math.pow(i,2)+6*n*o*i-6*t*o*i+3*t*Math.pow(o,2)-3*e*Math.pow(o,2)},n.Color=function(e,t,n,r){let i=this;i.MAGIC=786698,i._r=e,i._g=t,i._b=n,i._a=r,i._h=0,i._s=0,i._v=0,i._hsvInferred=!1,i.setRed=function(e){i._r=e,i._hsvInferred=!1},i.setGreen=function(e){i._g=e,i._hsvInferred=!1},i.setBlue=function(e){i._b=e,i._hsvInfM erred=!1},i.setAlpha=function(e){i._a=e/255,i._hsvInferred=!1},i._inferHSV=function(){i._hsvInferred||([i._h,i._s,i._v]=function(e,t,n){let r,i,o,a,l;return r=e<t?e<n?e:n:t<n?t:n,0==(l=100*(i=e>t?e>n?e:n:t>n?t:n)/255)?[o=0,a=0,l]:0==(a=100*(i-r)/i)?[o=0,a,l]:(o=i==e?0+60*(t-n)/(i-r):i==t?120+60*(n-e)/(i-r):240+60*(e-t)/(i-r),[o,a,l])}(i._r,i._g,i._b),i._hsvInferred=!0)},i.toString=function(){return`rgba(${Math.round(i._r)},${Math.round(i._g)},${Math.round(i._b)},${~~(1e3*i._a)/1e3})`}},n.colorMode=function(e){n._stM yle.colorMode=e},n.color=function(){if(1==arguments.length&&786698==arguments[0].MAGIC)return arguments[0];if(n._style.colorMode==n.RGB){if(1==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],1);if(2==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],arguments[1]/255);if(3==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],1);if(4==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],arguments[3]/255)}else{if(1==argumeM nts.length)return new n.Color(...x(0,0,arguments[0]/100),1);if(2==arguments.length)return new n.Color(...x(0,0,arguments[0]/100),arguments[1]/255);if(3==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),1);if(4==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),arguments[3])}return null},n.red=function(e){return e._r},n.green=function(e){return e._g},n.blue=function(e){return e._b},n.alpha=function(e){return 255*e._a},n.hue=function(e){reM turn e._inferHSV(),e._h},n.saturation=function(e){return e._inferHSV(),e._s},n.brightness=function(e){return e._inferHSV(),e._v},n.lightness=function(e){return 100*(.2126*e._r+.7152*e._g+.0722*e._b)/255},n.lerpColor=function(e,t,r){return n._style.colorMode==n.RGB?new n.Color(n.constrain(n.lerp(e._r,t._r,r),0,255),n.constrain(n.lerp(e._g,t._g,r),0,255),n.constrain(n.lerp(e._b,t._b,r),0,255),n.constrain(n.lerp(e._a,t._a,r),0,1)):(e._inferHSV(),t._inferHSV(),new n.Color(n.constrain(function(e,t,r){var i=[[Math.abs(t-M e),n.map(r,0,1,e,t)],[Math.abs(t+360-e),n.map(r,0,1,e,t+360)],[Math.abs(t-360-e),n.map(r,0,1,e,t-360)]];return i.sort(((e,t)=>e[0]-t[0])),(i[0][1]+720)%360}(e._h,t._h,r),0,360),n.constrain(n.lerp(e._s,t._s,r),0,100),n.constrain(n.lerp(e._v,t._v,r),0,100),n.constrain(n.lerp(e._a,t._a,r),0,1)))},n.strokeWeight=function(e){n._style_noStroke=!1,r.lineWidth=e},n.stroke=function(){if(n._style.noStroke=!1,"string"==typeof arguments[0])return void(r.strokeStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._sM tyle.noStroke=!0:r.strokeStyle=e},n.noStroke=function(){n._style.noStroke=!0},n.fill=function(){if(n._style.noFill=!1,"string"==typeof arguments[0])return void(r.fillStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._style.noFill=!0:r.fillStyle=e},n.noFill=function(){n._style.noFill=!0},n.blendMode=function(e){r.globalCompositeOperation=e},n.strokeCap=function(e){r.lineCap=e},n.strokeJoin=function(e){r.lineJoin=e},n.ellipseMode=function(e){n._style.ellipseMode=e},n.rectMode=function(e){n._style.rectM Mode=e},n.curveDetail=function(e){n._style.curveDetail=e},n.curveAlpha=function(e){n._style.curveAlpha=e},n.curveTightness=function(e){n._style.curveAlpha=e},n.clear=function(){r.clearRect(0,0,n.width,n.height)},n.background=function(){if(arguments[0]&&arguments[0].MAGIC==n.MAGIC)return n.image(arguments[0],0,0,n.width,n.height);r.save(),r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity),r.fillStyle="string"==typeof arguments[0]?arguments[0]:n.color(...Array.from(arguments)),r.fillRect(0,0,n.width,n.heightM ),r.restore()},n.line=function(e,t,i,o){n._style.noStroke||(r.beginPath(),r.moveTo(e,t),r.lineTo(i,o),r.stroke())},n.arc=function(e,t,r,i,o,a,l,s){if(o==a)return n.ellipse(e,t,r,i);null==s&&(s=25),null==l&&(l=n.PIE),n._style.ellipseMode==n.CENTER?m(e,t,r,i,o,a,l,s):n._style.ellipseMode==n.RADIUS?m(e,t,2*r,2*i,o,a,l,s):n._style.ellipseMode==n.CORNER?m(e+r/2,t+i/2,r,i,o,a,l,s):n._style.ellipseMode==n.CORNERS&&m((e+r)/2,(t+i)/2,r-e,i-t,o,a,l,s)},n.ellipse=function(e,t,r,i){null==i&&(i=r),n._style.ellipseMode==n.CENTERM ?b(e,t,r,i):n._style.ellipseMode==n.RADIUS?b(e,t,2*r,2*i):n._style.ellipseMode==n.CORNER?b(e+r/2,t+i/2,r,i):n._style.ellipseMode==n.CORNERS&&b((e+r)/2,(t+i)/2,r-e,i-t)},n.circle=function(e,t,r){return n.ellipse(e,t,r,r)},n.point=function(e,t){e.x&&(t=e.y,e=e.x),r.beginPath(),r.ellipse(e,t,.4,.4,0,0,2*Math.PI),r.stroke()},n.rect=function(e,t,r,i,o,a,l,s){n._style.rectMode==n.CENTER?y(e-r/2,t-i/2,r,i,o,a,l,s):n._style.rectMode==n.RADIUS?y(e-r,t-i,2*r,2*i,o,a,l,s):n._style.rectMode==n.CORNER?y(e,t,r,i,o,a,l,s):n._stylM e.rectMode==n.CORNERS&&y(e,t,r-e,i-t,o,a,l,s)},n.square=function(e,t,r,i,o,a,l){return n.rect(e,t,r,r,i,o,a,l)},n.beginShape=function(){w(),r.beginPath(),o=!0},n.beginContour=function(){r.closePath(),w(),o=!0},n.endContour=function(){w(),o=!0},n.vertex=function(e,t){w(),o?r.moveTo(e,t):r.lineTo(e,t),o=!1},n.bezierVertex=function(e,t,n,i,o,a){w(),r.bezierCurveTo(e,t,n,i,o,a)},n.quadraticVertex=function(e,t,n,i){w(),r.quadraticCurveTo(e,t,n,i)},n.bezier=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.bezierVM ertex(r,i,o,a,l,s),n.endShape()},n.triangle=function(e,t,r,i,o,a){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.endShape(n.CLOSE)},n.quad=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.vertex(l,s),n.endShape(n.CLOSE)},n.endShape=function(e){w(),e&&r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke(),n._style.noFill&&n._style.noStroke&&(r.save(),r.fillStyle="none",r.fill(),r.restore())},n.curveVertex=function(e,t){if(a.push([e,t]),a.length<4)return;M let i=function(e,t,n,r,i,o,a,l,s,h){function c(e,t,n,r,i,o){let a=Math.pow(r-t,2)+Math.pow(i-n,2);return Math.pow(a,.5*o)+e}let u=[],f=c(0,e,t,n,r,h),d=c(f,n,r,i,o,h),x=c(d,i,o,a,l,h);for(let h=0;h<s;h++){let c=f+h/(s-1)*(d-f),g=[(f-c)/(f-0),(c-0)/(f-0),(d-c)/(d-f),(c-f)/(d-f),(x-c)/(x-d),(c-d)/(x-d),(d-c)/(d-0),(c-0)/(d-0),(x-c)/(x-f),(c-f)/(x-f)];for(let e=0;e<g.length;e+=2)isNaN(g[e])&&(g[e]=1,g[e+1]=0),isFinite(g[e])||(g[e]>0?(g[e]=1,g[e+1]=0):(g[e]=0,g[e+1]=1));let p=e*g[0]+n*g[1],m=t*g[0]+r*g[1],b=n*g[2]+i*g[M 3],y=r*g[2]+o*g[3],w=i*g[4]+a*g[5],v=o*g[4]+l*g[5],z=p*g[6]+b*g[7],V=m*g[6]+y*g[7],_=b*g[8]+w*g[9],M=y*g[8]+v*g[9],E=z*g[2]+_*g[3],S=V*g[2]+M*g[3];u.push([E,S])}return u}(...a[a.length-4],...a[a.length-3],...a[a.length-2],...a[a.length-1],n._style.curveDetail,n._style.curveAlpha);for(let e=0;e<i.length;e++)o?r.moveTo(...i[e]):r.lineTo(...i[e]),o=!1},n.curve=function(e,t,r,i,o,a,l,s){n.beginShape(),n.curveVertex(e,t),n.curveVertex(r,i),n.curveVertex(o,a),n.curveVertex(l,s),n.endShape()},n.translate=function(e,t){r.tM ranslate(e,t)},n.rotate=function(e){r.rotate(e)},n.scale=function(e,t){null==t&&(t=e),r.scale(e,t)},n.applyMatrix=function(e,t,n,i,o,a){r.transform(e,t,n,i,o,a)},n.shearX=function(e){r.transform(1,0,Math.tan(e),1,0,0)},n.shearY=function(e){r.transform(1,Math.tan(e),0,1,0,0)},n.resetMatrix=function(){r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity)},n.pushMatrix=n.push=function(){n._styleCache.push({...n._style}),n._style=n._styleCache[n._styleCache.length-1],r.save()},n.popMatrix=n.pop=function(){n._stylM eCache.length-1&&(n._styleCache.pop(),n._style=n._styleCache[n._styleCache.length-1],r.restore())},n.image=function(e,t,i,o,a,l,s,h,c){let u=e.MAGIC==n.MAGIC?e.canvas:e;function d(){if(e.MAGIC!=n.MAGIC||!n._tint)return;let t=e.canvas.getContext("2d");t.save(),t.resetTransform(),t.clearRect(0,0,t.canvas.width,t.canvas.height),t.drawImage(f.canvas,0,0),t.restore()}return e.MAGIC==n.MAGIC&&null!=n._tint&&(function(e,t){null==f&&(f=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvasM .height),f.canvas.width==e&&f.canvas.height==t||(f.canvas.width=e,f.canvas.height=t)}(e.canvas.width,e.canvas.height),f.drawImage(e.canvas,0,0),e.tinted(n._tint)),o?l?(h||(h=u.width),c||(c=u.height),r.drawImage(u,l,s,h,c,t,i,o,a),void d()):(r.drawImage(u,t,i,o,a),void d()):(e.MAGIC==n.MAGIC||e.width?r.drawImage(u,t,i,e.width,e.height):r.drawImage(u,t,i,e.videoWidth,e.videoHeight),void d())},n.loadPixels=function(){l=r.getImageData(0,0,n.canvas.width,n.canvas.height),n.pixels=l.data},n.updatePixels=function(){null!=M l&&r.putImageData(l,0,0)},n.loadImage=function(e,t){s++;let r=n.createGraphics(100,100),i=r.canvas.getContext("2d"),o=new Image;return o.src=e,o.crossOrigin="Anonymous",o.onload=function(){i.canvas.width=o.width,i.canvas.height=o.height,r.width=o.width,r.height=o.height,i.drawImage(o,0,0),s--,t&&t(r)},r};let v={};function z(e,t){null==u&&(u=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvas.height),u.canvas.width==e&&u.canvas.height==t||(u.canvas.width=e,u.canvas.height=t)}funcM tion V(){let e=r.canvas.width*r.canvas.height*4;null!=d&&e==d.length||(d=new Uint8ClampedArray(e))}function _(e){u.clearRect(0,0,u.canvas.width,u.canvas.height),u.filter=e,u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()}v[n.THRESHOLD]=function(e,t){null==t?t=127.5:t*=255;for(let n=0;n<e.length;n+=4){const r=.2126*e[n]+.7152*e[n+1]+.0722*e[n+2];e[n]=e[n+1]=e[n+2]=r>=t?255:0}},v[n.GRAY]=function(e){for(let t=0;t<e.length;t+=4)M {const n=.2126*e[t]+.7152*e[t+1]+.0722*e[t+2];e[t]=e[t+1]=e[t+2]=n}},v[n.OPAQUE]=function(e){for(let t=0;t<e.length;t+=4)e[t+3]=255},v[n.INVERT]=function(e){for(let t=0;t<e.length;t+=4)e[t]=255-e[t],e[t+1]=255-e[t+1],e[t+2]=255-e[t+2]},v[n.POSTERIZE]=function(e,t){let n=t-1;for(let r=0;r<e.length;r+=4)e[r]=255*(e[r]*t>>8)/n,e[r+1]=255*(e[r+1]*t>>8)/n,e[r+2]=255*(e[r+2]*t>>8)/n},v[n.DILATE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-M 1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.max(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.ERODE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.min(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.BLURM ]=function(e,t){t=t||1,t=Math.floor(t*n._pixelDensity),V(),d.set(e);let i=2*t+1,o=function(e){let n=new Float32Array(e),r=.3*t+.8,i=r*r*2;for(let t=0;t<e;t++){let o=t-e/2,a=Math.exp(-o*o/i)/(2.5066282746*r);n[t]=a}return n}(i),[a,l]=[r.canvas.width,r.canvas.height];for(let n=0;n<l;n++)for(let r=0;r<a;r++){let l=0,s=0,h=0,c=0;for(let e=0;e<i;e++){let i=4*(n*a+Math.min(Math.max(r-t+e,0),a-1));l+=d[i]*o[e],s+=d[i+1]*o[e],h+=d[i+2]*o[e],c+=d[i+3]*o[e]}let u=4*(n*a+r);e[u]=l,e[u+1]=s,e[u+2]=h,e[u+3]=c}d.set(e);for(let nM =0;n<l;n++)for(let r=0;r<a;r++){let s=0,h=0,c=0,u=0;for(let e=0;e<i;e++){let i=4*(Math.min(Math.max(n-t+e,0),l-1)*a+r);s+=d[i]*o[e],h+=d[i+1]*o[e],c+=d[i+2]*o[e],u+=d[i+3]*o[e]}let f=4*(n*a+r);e[f]=s,e[f+1]=h,e[f+2]=c,e[f+3]=u}},n.filter=function(e,t){if(n.HARDWARE_FILTERS&&null!=r.filter)if(z(),e==n.THRESHOLD){null==t&&(t=.5),t=Math.max(t,1e-5),_(`saturate(0%) brightness(${Math.floor(.5/t*100)}%) contrast(1000000%)`)}else if(e==n.GRAY)_("saturate(0%)");else if(e==n.OPAQUE)u.fillStyle="black",u.fillRect(0,0,u.canvaM s.width,u.canvas.height),u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.drawImage(u.canvas,0,0),r.restore();else if(e==n.INVERT)_("invert(100%)");else if(e==n.BLUR)_(`blur(${Math.ceil(t*n._pixelDensity/1)||1}px)`);else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}},n.resize=function(e,t){z(),u.drawImage(r.canvas,0,0),n.width=e,n.height=t,r.canvas.width=e*n._pixM elDensity,r.canvas.height=t*n._pixelDensity,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0,r.canvas.width,r.canvas.height),r.restore()},n.get=function(e,t,i,o){if(null!=e&&null==i){let i=r.getImageData(e,t,1,1).data;return new n.Color(i[0],i[1],i[2],i[3]/255)}e=e||0,t=t||0,i=i||n.width,o=o||n.height;let a=n.createGraphics(i,o);a.pixelDensity(n._pixelDensity);let l=r.getImageData(e*n._pixelDensity,t*n._pixelDensity,i*n._pixelDensity,o*n._pixelDensity);return a.caM nvas.getContext("2d").putImageData(l,0,0),a},n.set=function(e,t,i){if(i.MAGIC==n.MAGIC){let r=n._tint;return n._tint=null,n.image(i,e,t),void(n._tint=r)}let o=4*(t*n._pixelDensity*r.canvas.width+e*n._pixelDensity);n.pixels[o]=i._r,n.pixels[o+1]=i._g,n.pixels[o+2]=i._b,n.pixels[o+3]=255*i._a},n.tinted=function(){let e=n.color(...Array.from(arguments)),t=e._a;e._a=1,z(),u.clearRect(0,0,u.canvas.width,u.canvas.height),u.fillStyle=e,u.fillRect(0,0,u.canvas.width,u.canvas.height),u.globalCompositeOperation="multiply",u.M drawImage(r.canvas,0,0),u.globalCompositeOperation="source-over",r.save(),r.resetTransform();let i=r.globalCompositeOperation;r.globalCompositeOperation="source-in",r.drawImage(u.canvas,0,0),r.globalCompositeOperation=i,r.restore(),u.globalAlpha=t,u.clearRect(0,0,u.canvas.width,u.canvas.height),u.drawImage(r.canvas,0,0),u.globalAlpha=1,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()},n.tint=function(){n._tint=n.color(...Array.from(arguments))},n.noTiM nt=function(){n._tint=null},n.mask=function(e){r.save(),r.resetTransform();let t=r.globalCompositeOperation;r.globalCompositeOperation="destination-in",r.drawImage(e.canvas,0,0),r.globalCompositeOperation=t,r.restore()},n.clearTemporaryBuffers=function(){u=null,f=null,d=null},n.save=function(e,t){e=e||"untitled",t=t||"png";var n=document.createElement("a");n.innerHTML="[Download]",n.addEventListener("click",(function(){this.href=r.canvas.toDataURL(),this.download=e+"."+t}),!1),document.body.appendChild(n),n.click()M ,document.body.removeChild(n)},n.saveCanvas=function(e,t,r){if(e.MAGIC==n.MAGIC){r&&e.save(t,r);let n=t.split(".");return e.save(n.slice(0,-1).join("."),n[n.length-1])}if(t)return n.save(e,t);let i=e.split(".");return n.save(i.slice(0,-1).join("."),i[i.length-1])},n.loadFont=function(e){let t=e.split("/"),n=t[t.length-1].split(".")[0].replace(" ",""),r=`@font-face {\n font-family: '${n}';\n src: url('${e}');\n }`;const i=document.createElement("style");return i.textContent=r,document.head.append(M i),n},n.textFont=function(e){n._style.textFont=e},n.textSize=function(e){n._style.textSize=e,n._style.textLeading=e},n.textLeading=function(e){n._style.textLeading=e},n.textStyle=function(e){n._style.textStyle=e},n.textAlign=function(e,t){r.textAlign=e,t&&(r.textBaseline=t==n.CENTER?"middle":t)},n.text=function(e,t,i,o){if(!e)return;if(e=e.toString(),n._style.noFill&&n._style.noStroke)return;r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`;let a=e.split("\n");for(let e=0;e<a.length;e++)n._M style.noFill||r.fillText(a[e],t,i,o),n._style.noStroke||r.strokeText(a[e],t,i,o),i+=n._style.textLeading},n.textWidth=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).width},n.textAscent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBoundingBoxAscent},n.textDescent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBounM dingBoxDescent};var M,E=4,S=.5,R=function(e){return.5*(1-Math.cos(e*Math.PI))};n.noise=function(e,t,n){if(t=t||0,n=n||0,null==M){M=new Array(4096);for(var r=0;r<4096;r++)M[r]=Math.random()}e<0&&(e=-e),t<0&&(t=-t),n<0&&(n=-n);for(var i,o,a,l,s,h=Math.floor(e),c=Math.floor(t),u=Math.floor(n),f=e-h,d=t-c,x=n-u,g=0,p=.5,m=0;m<E;m++){var b=h+(c<<4)+(u<<8);i=R(f),o=R(d),a=M[4095&b],a+=i*(M[b+1&4095]-a),l=M[b+16&4095],a+=o*((l+=i*(M[b+16+1&4095]-l))-a),l=M[4095&(b+=256)],l+=i*(M[b+1&4095]-l),s=M[b+16&4095],l+=o*((s+=i*(M[M b+16+1&4095]-s))-l),g+=(a+=R(x)*(l-a))*p,p*=S,h<<=1,c<<=1,u<<=1,(f*=2)>=1&&(h++,f--),(d*=2)>=1&&(c++,d--),(x*=2)>=1&&(u++,x--)}return g},n.noiseDetail=function(e,t){e>0&&(E=e),t>0&&(S=t)};const I=function(){let e,t,n=4294967295;return{setSeed(r){e=t=(null==r?Math.random()*n:r)>>>0},getSeed:()=>t,rand:()=>(e^=e<<17,e^=e>>13,((e^=e<<5)>>>0)/n)}};let C=I();C.setSeed(),n.noiseSeed=function(e){let t=null==e?4294967295*Math.random():e;M||(M=new Float32Array(4096));for(var n=0;n<4096;n++)t^=t<<17,t^=t>>13,t^=t<<5,M[n]=(t>M >>0)/4294967295},n.randomSeed=function(e){C.setSeed(e)},n.random=function(e,t){return null==e?C.rand():"number"==typeof e?null!=t?C.rand()*(t-e)+e:C.rand()*e:e[~~(e.length*C.rand())]},n.randomGenerator=function(e){e==n.LCG?C=function(){const e=4294967296;let t,n;return{setSeed(r){n=t=(null==r?Math.random()*e:r)>>>0},getSeed:()=>t,rand:()=>(n=(1664525*n+1013904223)%e)/e}}():e==n.SHR3&&(C=I()),C.setSeed()};var T=new function(){var e,t,n,r=new Array(128),i=new Array(256),o=new Array(128),a=new Array(128),l=new Array(2M 56),s=new Array(256),h=function(){return 4294967296*C.rand()-2147483648},c=function(){return.5+2.328306e-10*(h()<<0)};this.SHR3=h,this.UNI=c,this.RNOR=function(){return n=h(),e=127&n,Math.abs(n)<r[e]?n*o[e]:function(){for(var t,i,l,s,u=3.44262;;){if(t=n*o[e],0==e){do{l=c(),s=c(),t=.2904764*-Math.log(l),i=-Math.log(s)}while(i+i<t*t);return n>0?u+t:-u-t}if(a[e]+c()*(a[e-1]-a[e])<Math.exp(-.5*t*t))return t;if(n=h(),e=127&n,Math.abs(n)<r[e])return n*o[e]}}()},this.REXP=function(){return(t=h()>>>0)<r[e=255&t]?t*l[e]:funM ction(){for(var n;;){if(0==e)return 7.69711-Math.log(c());if(n=t*l[e],s[e]+c()*(s[e-1]-s[e])<Math.exp(-n))return n;if((t=h())<i[e=255&t])return t*l[e]}}()},this.zigset=function(){var e,t,n=2147483648,h=4294967296,c=3.442619855899,u=c,f=.00991256303526217,d=7.697117470131487,x=d,g=.003949659822581572;for(e=f/Math.exp(-.5*c*c),r[0]=Math.floor(c/e*n),r[1]=0,o[0]=e/n,o[127]=c/n,a[0]=1,a[127]=Math.exp(-.5*c*c),t=126;t>=1;t--)c=Math.sqrt(-2*Math.log(f/c+Math.exp(-.5*c*c))),r[t+1]=Math.floor(c/u*n),u=c,a[t]=Math.exp(-.5*cM *c),o[t]=c/n;for(e=g/Math.exp(-d),i[0]=Math.floor(d/e*h),i[1]=0,l[0]=e/h,l[255]=d/h,s[0]=1,s[255]=Math.exp(-d),t=254;t>=1;t--)d=-Math.log(g/d+Math.exp(-d)),i[t+1]=Math.floor(d/x*h),x=d,s[t]=Math.exp(-d),l[t]=d/h}};T.hasInit=!1,n.randomGaussian=function(e,t){return T.hasInit||(T.zigset(),T.hasInit=!0),T.RNOR()*t+e},n.randomExponential=function(){return T.hasInit||(T.zigset(),T.hasInit=!0),T.REXP()},n.print=console.log,n.cursor=function(e,t,r){let i="";e.includes(".")&&(e=`url("${e}")`,i=", auto"),null!=t&&(e+=" "+t+M " "+r),n.canvas.style.cursor=e+i},n.noCursor=function(){n.canvas.style.cursor="none"},n.createCapture=function(e){var t=document.createElement("video");return t.playsinline="playsinline",t.autoplay="autoplay",navigator.mediaDevices.getUserMedia(e).then((function(e){t.srcObject=e})),t.style.position="absolute",t.style.opacity=1e-5,t.style.zIndex=-1e3,document.body.appendChild(t),t};let A=["setup","draw","preload","mouseMoved","mousePressed","mouseReleased","mouseDragged","mouseClicked","keyPressed","keyReleased","keM yTyped","touchStarted","touchEnded"];for(let e of A){let t="_"+e+"Fn";n[t]=function(){},n[t].isPlaceHolder=!0,n[e]?n[t]=n[e]:Object.defineProperty(n,e,{set:function(e){n[t]=e}})}function D(){n._noLoop||(i=null==n._frameRate?requestAnimationFrame(D):setTimeout(D,1e3/n._frameRate)),w(),o=!0,n.push(),n._drawFn(),n.pop(),++n.frameCount}function k(e){const t=n.canvas.getBoundingClientRect(),r=n.canvas.scrollWidth/n.width||1,i=n.canvas.scrollHeight/n.height||1;return{x:(e.clientX-t.left)/r,y:(e.clientY-t.top)/i,id:e.idenM tifier}}function L(){return n._touchStarted.isPlaceHolder&&n._touchMoved.isPlaceHolder&&n._touchEnded.isPlaceHolder}n.noLoop=function(){n._noLoop=!0,i=null},n.loop=function(){n._noLoop=!1,null==i&&D()},n.redraw=function(){D()},n.frameRate=function(e){n._frameRate=e},setTimeout((function(){n._preloadFn(),c=window.performance.now(),function e(){if(s>0)return setTimeout(e,10);n._setupFn(),D()}()}),1),n.canvas.onmousemove=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPM ressed?n._mouseDraggedFn(e):n._mouseMovedFn(e)},n.canvas.onmousedown=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!0,n.mouseButton=[n.LEFT,n.CENTER,n.RIGHT][e.button],n._mousePressedFn(e)},n.canvas.onmouseup=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!1,n._mouseReleasedFn(e)},n.canvas.onclick=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressedM =!0,n._mouseClickedFn(e),n.mouseIsPressed=!1},window.addEventListener("keydown",(function(e){n.keyIsPressed=!0,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!0,n._keyPressedFn(e),1==e.key.length&&n._keyTypedFn(e)})),window.addEventListener("keyup",(function(e){n.keyIsPressed=!1,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!1,n._keyReleasedFn(e)})),n.keyIsDown=function(e){return!!h[e]},n.canvas.ontouchstart=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.moM useY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mousePressedFn(e)||e.preventDefault()),n._touchStartedFn(e)||e.preventDefault()},n.canvas.ontouchmove=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mouseDraggedFn(e)||e.preventDefault()),n._touchMovedFn(e)||e.preventDefault()},n.canvas.ontouchend=n.canvas.ontouchcancel=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.M mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!1,n._mouseReleasedFn(e)||e.preventDefault()),n._touchEndedFn(e)||e.preventDefault()},n.hasSensorPermission=!window.DeviceOrientationEvent&&!window.DeviceMotionEvent||!(DeviceOrientationEvent.requestPermission||DeviceMotionEvent.requestPermission),n.requestSensorPermissions=function(){DeviceOrientationEvent.requestPermission&&DeviceOrientationEvent.requestPermission().then((e=>{"granted"==e&&DeviceMotionEvent.requestPermissioM n&&DeviceMotionEvent.requestPermission().then((e=>{"granted"==e&&(n.hasSensorPermission=!0)})).catch(alert)})).catch(alert)},window.ondeviceorientation=function(e){n.pRotationX=n.rotationX,n.pRotationY=n.rotationY,n.pRotationZ=n.rotationZ,n.pRelRotationX=n.relRotationX,n.pRelRotationY=n.relRotationY,n.pRelRotationZ=n.relRotationZ,n.rotationX=e.beta*(Math.PI/180),n.rotationY=e.gamma*(Math.PI/180),n.rotationZ=e.alpha*(Math.PI/180),n.relRotationX=[-n.rotationY,-n.rotationX,n.rotationY][1+~~(window.orientation/90)],n.rM elRotationY=[-n.rotationX,n.rotationY,n.rotationX][1+~~(window.orientation/90)],n.relRotationZ=n.rotationZ},window.ondevicemotion=function(e){if(n.pAccelerationX=n.accelerationX,n.pAccelerationY=n.accelerationY,n.pAccelerationZ=n.accelerationZ,!e.acceleration){let t=((e,t)=>[(e[0]*t[0]+e[1]*t[1]+e[2]*t[2]+e[3])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[4]*t[0]+e[5]*t[1]+e[6]*t[2]+e[7])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[8]*t[0]+e[9]*t[1]+e[10]*t[2]+e[11])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15])])(((e,t)M =>[e[0]*t[0]+e[1]*t[4]+e[2]*t[8]+e[3]*t[12],e[0]*t[1]+e[1]*t[5]+e[2]*t[9]+e[3]*t[13],e[0]*t[2]+e[1]*t[6]+e[2]*t[10]+e[3]*t[14],e[0]*t[3]+e[1]*t[7]+e[2]*t[11]+e[3]*t[15],e[4]*t[0]+e[5]*t[4]+e[6]*t[8]+e[7]*t[12],e[4]*t[1]+e[5]*t[5]+e[6]*t[9]+e[7]*t[13],e[4]*t[2]+e[5]*t[6]+e[6]*t[10]+e[7]*t[14],e[4]*t[3]+e[5]*t[7]+e[6]*t[11]+e[7]*t[15],e[8]*t[0]+e[9]*t[4]+e[10]*t[8]+e[11]*t[12],e[8]*t[1]+e[9]*t[5]+e[10]*t[9]+e[11]*t[13],e[8]*t[2]+e[9]*t[6]+e[10]*t[10]+e[11]*t[14],e[8]*t[3]+e[9]*t[7]+e[10]*t[11]+e[11]*t[15],e[12]*t[0]+M e[13]*t[4]+e[14]*t[8]+e[15]*t[12],e[12]*t[1]+e[13]*t[5]+e[14]*t[9]+e[15]*t[13],e[12]*t[2]+e[13]*t[6]+e[14]*t[10]+e[15]*t[14],e[12]*t[3]+e[13]*t[7]+e[14]*t[11]+e[15]*t[15]])((e=>[Math.cos(e),0,Math.sin(e),0,0,1,0,0,-Math.sin(e),0,Math.cos(e),0,0,0,0,1])(n.rotationY),(e=>[1,0,0,0,0,Math.cos(e),-Math.sin(e),0,0,Math.sin(e),Math.cos(e),0,0,0,0,1])(n.rotationX)),[0,0,-9.80665]);n.accelerationX=e.accelerationIncludingGravity.x+t[0],n.accelerationY=e.accelerationIncludingGravity.y+t[1],n.accelerationZ=e.accelerationIncludM ingGravity.z-t[2]}},n.year=function(){return(new Date).getFullYear()},n.day=function(){return(new Date).getDay()},n.hour=function(){return(new Date).getHours()},n.minute=function(){return(new Date).getMinutes()},n.second=function(){return(new Date).getSeconds()},n.millis=function(){return window.performance.now()-c}}(e)}"object"==typeof exports&&"undefined"!=typeof module&&(module.exports=e);const t="https://ancient-crimson-rain.btc.discover.quiknode.pro/c268fb026303ae8443f785200f2ea4b82f0082dd";function n(e){P(e)?M localStorage.removeItem("blocksApiEndpoint"):localStorage.blocksApiEndpoint=e}function r(){return localStorage.blocksApiEndpoint||t}function i(e){P(e)?localStorage.removeItem("modelInscriptionEndpoint"):localStorage.modelInscriptionEndpoint=e}function o(){return localStorage.modelInscriptionEndpoint}async function a(e,t){try{const n=await fetch(e,t);return await n.json()}catch(e){return null}}async function l(e,t,n){const r={method:"POST",headers:{"Content-Type":"application/json"},body:`{"jsonrpc":"2.0","id":1,"meM thod":"${t}","params":${`[${n.join(sep=",")}]`}}`};return(await a(e,r))?.result}async function s(e){const n={avgfee:10,time:Date.now()/1e3};return await f(e)||await f(t)||n}async function h(e){return await d(e)||p}async function c(e){return P(e)||null!=await f(e)}async function u(e){return P(e)||null!=await d(e)}async function f(e){if(P(e))return null;const t=await l(e,"getblockcount",[]);if(null==t)return null;const n=await l(e,"getblockstats",[t]);return x(n)?n:null}async function d(e){if(P(e))return null;const tM =await a(e,{});return g(t)?t:null}function x(e){return"number"==typeof e?.time&&"number"==typeof e?.avgfee}function g(e){if(null==e)return!1;const{classes_name:t,training_traits:n,layers_config:r,weight_b64:i}=e;if(!Array.isArray(t))return!1;if(null==n)return!1;try{j(r,i)}catch(e){return!1}return!0}const p={"model_name": "pfp_classifier_417", "layers_config": {"config": {"layers": [{"class_name": "InputLayer", "config": {"batch_input_shape": [null, 28, 28, 3]}}, {"class_name": "Rescaling", "config": {"scale": 0.007M 84313725490196, "offset": -1}}, {"class_name": "Flatten"}, {"class_name": "Dense", "config": {"units": 6, "activation": "sigmoid"}}, {"class_name": "Dense", "config": {"units": 4, "activation": "sigmoid"}}, {"class_name": "Dense", "config": {"units": 6, "activation": "sigmoid"}}, {"class_name": "Dense", "config": {"units": 4, "activation": "sigmoid"}}, {"class_name": "Dense", "config": {"units": 4, "activation": "linear"}}]}}, "weight_b64": "/kZ0uQVIn7xsxUc9zRk5u1WiyzzwDqs9MXelPJjh5L3coMo88UOfvQdXZz0Bx8090eZ9ul4dIzM 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 2fJFe8SAv1vTEJhj1ca+48Dim4PRWvR739rfe8JzKwvakzUz0TnNs9jQaYPVkFvbzH9Km9VgSrvRQq7zxNBJU96qXuPZVYEL1qEfy8kGMAvuon7z32FwA+hZIZPqbPnb227Li8PxCIveIcmj3xpQI+jm60PXuAhL2dptG9++3lveVx0D1HiDU9oxaCPbcdrr37vTW9DeBHvegztT0etNM8Dk/jPamVzr3XjpK94NnHvX2upz3h7o09Viu0PXTQrLyja4W9FErJvJmAYD3tEb49/+vnOy8KCL2uR4a9Cm2bvQGmpz0cxrI91doFPqbvv73i6l2909kYvobSij3N2lM9t9TbPPn2RL11MRa+SoAVvAlC+zzwbvw8kkcEPOMCr72D0/K7t1fdvQ0yij3xk8k99Fa2PYMEBL2JR1a9YOQLvui73j3Qz7s9jBJ5uzuLaL1LUgG+48WdvV/dkD2HD5c9pemjPRhlyr0jGxI8qY/uvYm7IT3BrG094cEuPf+X071y5l292jM 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 KqulM1DT2TZ868M1wnPOULpbqvTxs9Nh/FPMqI6LzZJyS9IJLivJm1TbvtAEg96fOpPL7MCzurcYM9DlxTPe+6/7w41VS8OtkoPHGK77vTjEe9IaG9PWjuaDwtWWg8lpZpPVAHNTw7fo49ZjgkPYe4nDyb5y49uXsZPM32jT34oyM91ILHPTrEm70M03K9s4/TuoHgqD34+4G9YpMFPVqxcr1aN6W7sIBQvISXRD3X1vY8EuuiPQEACjzWZ3E8Fvl9PITfFLtYfjm8wAXEPQeD172qI9O9/9tOPfFTvj3tUjS9+SMWPmkHBb0Y2rG80+UYvTBud7xgViC54ETQPZzjqL2m+2O8CdIVvXcwxjz9nXm8Pkt8PSYakby9qK29553HPGnhB72iyyG9XkJTPDeRFbxEhgm9C4fpvE1RzLtCiH88QwesPeYiUTymzsO81InlO3a8BLwxZI69c3YqvZYSKDzJAxc9zAG2PYS/zbye61q7S/yavNyD4Tw2X+Q8udz3PBJvSrM 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 v9vZd/ET6R7yA+D2/mPRg+FL426Di8aQ/GveE01T1a+Q4+0UVkvXCZzL0NA+O9hRCsPY672T0WSFO8lsbRPBe85b1ngd68wV2rO8dLjj2h0d099xdWPLvTZ73EGIC9b0/fPDjOWT1Dh149FVvCvM12FT2Qs4a9ANqBPVRzY7s7D8M8W+DPvBothb1tQo29pkOFPej1Sz0Gic480q+KvESFhj0+oJ69H76mPbZ2oL3uqQW8SP0FvKu4NT22q8e9aFobvQqBpD3eIXs8wqqGvAzEez28t769egePPZmVfz3kArg9KFJbvQC4sj1qY/i9gdFlPbyIu70luNK8uU4CPhh8nbySNsm8beddu9i0wz2Clco9u+CBPVbeCT3VDh48imbPvJKLCT2SVqg9SsIaPDha7j0U8hI9g9lCvXdzEb1gY/Q8nygVPokgKL0tplk9ebcYvIp7jDw6bKo9WczZPWSJUj2MJWw9kQ0dvZAT0T0abwM+v/IFPtVOWz2OwIM99C/HvZlF3DM 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 IhvvYlgD4AVGe+vpRvPULN471A5/e8xP26vXPeUD5WrBW+3B4TPe8frL1mbcq8Zf8wviwbOz5jVxq+YUkLPr3SIr7ND8q9gGIPu1YmPD6U28i9BN2WPcAcGr02/Ts8HVeyvHzaUj7ryVA8H6LNPS77vr2CA4c9Fl6bvfgCRT6pehm95dvXPfOxMb57ZBy8C3mkO4dqvT0IlZa9GWmqPLQYJLxMPm69Qy4uvbL8ID4UDWq9HT0nPf0ct73BoBs9L6hdPUo31j2gxTi996HQPP6YeLxppDu7rAcIPhjxGb3L5wg+mx+Lvbj3uj3KeUA9bNL9PRQxorx38W88v0xdPRk58zt5tAo9qLcCPr4IG70tBp09r1UBOYDJXbzuqVk9bKO/PRMGnr3i9Dc83C+rPAMpUj1VYTM9jMIHPr00eb2a6Lk8CqA9vbMvoj2qz049ZSmDPU+Mxr3GViY9kDsuPfUIirsyeSA8979ZvOoLWDwS3Is8PSRpvVQhQT2TmVK8qLZXPXAAjLM 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 7JvU3nJj2RGmS+X61JPU4WJr1Hlxy8NAJQvRRdAD6ljFa+ytdOPBtqNb17oV09i0rovNavxj06PTK+uEyWvfN13zwZXY08Mjz6vC04xT3k2Em+I+yrPDvPWT2Cwgs9wO45vTCsmD0QS0m+3/yXvbjRKD0KOC09ks2nPC/9pjsidws8uRGsPfo2Hr3ALyq9jSwcvfX4BT3Fm2e9ZrjZPY93/L2PdgG+Hwf3vNqDLj162ho8K+4yPCyxuDyQYJg8gaWXPdHu8b3Cdhs+qvdcPcRVWD0JGqE8WwhvPfzB9b3XWvY9JhbBPUNmeb1ifAS9pXoiPRWb0jwih6o9F7SWPPHeOryhXU+8XzFovXrk7D01Qp690zZDu0v/6z1TIbU8oLPJvb6yCD4M0LW9Z1F0PXSkoT2zI6a8w7OtvY74hT2OHvu8B91lvQ/JPD1rCMS7iwgjPP77Gzw8xGI+q6bPvVELjj1hZng9niNOPb0per0s51E+dgCtveJUwzzxHlo9cfYgPD1BEDM 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 0r1Te9z92FPTkElr2VkmG9rV0Evnqrnj0ytoy95YPaPNtLQrxb5b69aoSxvYaYyT0adxm+cO3SO1lgnjx3nHE9lJTxvZ81uj3djj2+ROThuyajMD3g1G89JkoHvVeqDz4LzHO+HLm9vZ2YgT3Fjfw9zj5LvYl/vz0VSnq8IrcLPFfTnzzo+LI8EXK8vasxBj5XHRO9CTUcvE0VML3mkau9r8OjvQrgOD7gVK+95hwqvMMlhj3hoqE8r68lPvcn9L24evE9AmLFvMgQWD1Goo89Q3pdPb0wir3Xow4+yxmEvGLYHL3FQCU8td8uPZ3xZD0nrh0+2spnve5XljnbAts80IY2PY/aoby0Yik8x1qyvJRF0j2ZPrE97GRKvX1RwTtW0Ra9TrXhvN62A73FU708yO7XvLaN9Dxm9IM8I1smvURvBj3irTu8gccAPBhfJz2XHtA9ka4DPYpWojw6RFk98JudPEyFVb2/Fvw98HalPWIsDT1N9zu86/Urvb0WB72MXN09NaM 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 wYvjzcYD5Jly6+nQDyPXoZIr2Y9CK8HGnavemOJD5d7mC+ovCmPZ5D8bzB3tg70Wi3vbQQDj7VCZW8znXNvNFlVL34Rym8hfviPaNsEb7dnm4+LVHpvNzOabycL5i8eSn9Pby7Tb7iAHQ+RJAIPtz0LbxVHDG99PQiPmDEOb7ATHI+ZUuSPPio7LxovU294I65vOlcdz1nKSo9fQLrPUZjNb2/3BW9okesu0U3xDzyhDm9tMM/PtwNPL2BjGy9CKMPPX5UYL24FPU9zGc5PQ6AJLxnz4o8AcIdvmBrvT1PULa8+PIrPhTR17104+C8zDc2vjjB5D3Sft69wL0CPcM8lLz+w5s9r6aAPcCAnb1Y7Gk9olhjvu71pz13ti4+yVqMvs0maT1LyDO+aoU4Pm3oJ74ZoSG+5zrhvvMxRT5IG9a+SXFgPhjaXb4iOEe+j+7bvsO/5j1/Wna+sJGouz89AL6eO7698GIaPkELf74vh4A+WzEavkprXj6ory4+fMXJO5EZ2LM 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 17eoI94jrzPHpf5Dzuzbq7LEcRvjUOqT2bpwa+Bu83Pmm3b74dTiG+sYNLvrkPPj6jtlC+tKKKPubDib4qum2+K1A2vsKiBz5YZOW9BX1yPsR8ML5qsCO+jZcjvu13tD1oCBS+hyY4Pgt5E766SBa+VeYSvk43Xz3W07K9eNBVPlr1O745yjC++4rKvay4gDwLMdK907nUPS5poL01dSW+0t0yvTrkmTuSvtG8J6HlO4OKpru9lWy9PuakvWdWBDwIfkQ939pWuzGDgb0HhJG9kJmDPautubxw7Kw9QaLiPPRzIrygdy29CtvSvTimJ71v6sy9y7+QvWZSeD21Oss9rWtJvbqdzTo766C9dPaWvAz5hTwgTgC9a6uavK+wpbt3FWe8xK29vSUeDT3Oga47eFZovaLRvj1CbJU7H3F1vfJmaj1V0wU9vuYhvvg52j3j5Ca+pybwPBA2Sb3X0HS86av+vYpjHT17s/O9g9+vveL+TrzaJAi9nlEfPDF12rz6IlU+V8M 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 72Yg2+XEQiPkzuDb7fouq9h2epvrsXHT7iPhO+Jh69PfsczrxIaxW+IjYfvpsU5D0Pn1y+SL8UvmkyVD5chaw9UyZEvlpnQD5Hs16+090MvvCidT0VFIe8Zb+ivhPU0T2GZ12+QdVyvu8Dgz06FLG9dv0mPoJn+L1IVPQ9yowCPawBA7wu2pq9/N5HPdDyDz0q+9e8MYSuPYYinL1VxxS+/aOtPG6fTb2FHJq93z6VvA+qpL2w3qa9/myZPYsLh71+1wo+27OOPNgizjysgzs9m0j6PbzHgL3B2gk+DNeivPAGAz2vXcQ9CNG7PUvdzr2iFlw9/KXPvQNFE73cOlI9ehXzugwqhbtwEdA9dMygPNaT87t84Yc9hyQrvVPOej1SL1y96i98vMngOb1mvVo9pJuvvVF1ezyqGKa9pC9Vva+R5rufscI7faBmveI2Bb1XXiu9F+pTvMmeDjx/BBU99dVzvZKw3zwf3eW7JOamvEjTA73RJjo9rIPovBkLUL2lShu8QWM SlvcVWkj2wAss9zFqJPXi3lb0mYd49xVUVvbFegT207Ss9VB75OxaMib3FDE49KvLsPHXSE73Mk8Y8K+tBPf/p5L0HZPM9d8movA6ryjztmTI8WesJvp423D38QQC9ITE0PgHLT756Xw6+BGFCvucXvz1y+ba9fHOTPg3xir7nX4O+qz8Fvhznoz08F6a9njIiPnhQBr5JdwG+phhDvlz97D2+5im+IR8VPscrH76tsUa+EOaJvdyOErw+Hma9ORw4PnSGtr0zffW9BraAvOSqCD1uihg9lSP2PTws8r2sT4y9mtcauxpXOb0471k7jwRwPUWBhr1NmaS9YmnmvNnTpL2fMgs+yMo6vVXszDzhw7O9xIWJPTg8/715wLE9KVtLvRI6+rwbT4c7eK6BvY6C/jx/pWG9LLTJvPCpdryGzjY9pGR/vS+uZbzgqco8lyJhvdE9Ij3EXEA9MxU8PE0+oL0Qwd08FUIkvQF+6jxQ3QM90/VsvTG0Cz2eykW8kXT6vGEjfLM 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 gEvcbcgb12Afg9WCmAvS2RDjzdloG7x5LNPXBtlL02WyM+UYz9vYgemD2fhkk9Z4olvfmjLDsssyS96AXWveHGvzyXcAQ97acbvkHOSD1Mzdm8NgKwvdyjgTwXkNi8CVaBvSPwgT3zqg+93GHGvDbxHrtKqoS8Fo7jvQhbjj08Tgc+wAuZPXrw7b0tyuy929Qevm08/j29SgS9DFsUPhAkGL7BeSO+EBUWvmrmEj5GoqO9PrYBPiMNLL5R4Ba+XPZuvRYBlD2r0UA8HD3JvLnxuLzWNjY8AADdPBpJujwaK8O8Clf2vOVRxrwyz809I9q+uxTdmz329Gy8TstDvktFkj3+zQ4+6EGAvaW+9T0Vkie+EHk7vjojTD60Zpo+2PPgPblTxbsxUAW8ls9yvkZqez7uopU+4CRAveJKTj0z6rS9Gl5FvtqRYD1bRAE+wk8kPL0tgzxQZw0+WRS1PU8lcL0dHNm90wE9PSyLYzweEec90QBLPpzfsb3PuOO896dXvZISf7M 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 qDPCoYaL7S0Re9z6jqvQYReLw0HrW9AEkcPbb1N70xfh67VZF7vluNCz6/fSS+3dYZvno0pL13sJ69b4iZvjglQj6T57m+SqOpPAGAI72eer27iUqIvkcWgT3bgn6+BEO4PbItmbyP/548GXV/vtvwQT7Lk5O+qCm4vPn3ZzvGMT28DTwPvrR8Hj6GyLC+ECWqvCRUtry9Z1o9mb/4vX5lmT19m4m+s8HLvXdQ1j3nSR0+aysmvswcoD0dTUK+CauLvmt6YT4JHCY+I0ffPN5aYj0IAmK8zH6xPdEpFb3440S9iU+SPufv6L3R6dQ9Ne70vX77zz2q6+49wLzTPUJKyrxefpe9MWWKvuC7CT6YUiM+sBKIPsHHIb7tpxI+a6mnveMifT2dx909jDeuPqtPn75SW5E+XcRiPbtbxj21R5c92DQjPoKgF76ee0I+BMtAvLMbLj6DrBU+38JaPqlzKL4cSmE+N3WRveLIvz1qngE+Pa4dPoCOP75jknU+Wp6lPgBiErM 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 0k/E890Zh0PXVCC72CEZy9FzpTPLVttb2lJwc+fLSIPGbFoDkqTay9qEQEvFofiL1cByk7jr0vvU577bwIejQ9FPOuPY+sEb5n1Us9gLBNvSh4+DvU4P053HVTPT9LM74aINc9TJhou3JNMzwFKJQ8HlNHu4yesL1Vqls961UKvoSdkD1G65U9p98FvRFWCb0lpdO7QOQfvnGMVj2jd/Y9KFwIPcar/L2wBO+8UFXRvVnD6j10zbE9dSrNveSRyj2cmpU8e5qqPTDRD73z97i97bddvgMh+j1NMOK9CNkYPiAKI77yu/O9MA0OvnFB7D1Dhq29ba+hPfqe+r1wxoW9uwykvZO3KD4pONy8lNj/PZGES71NJWy9bJ9rvTQJWD1lZ7A849dIPUYywL2YHLq8HquyvFBsET0Rd2M9tsSSvShWxDtIhw48Z4zkvDLeAj7dY7G9thHqvTpc8j0LPic+KMTrPd0b3Dy3Kka8kFB4vnXndz5GWpk+c8MkPS2DTbytXTK9UmM 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 6SPdQmtr3eC4c+g5OwPmpqZb5Li42+pC24PtQsjL7AXJY+yk1IvoQQKz4WUDo+TqaTPrP0q75X+b8+PlAePZFPmz0BsNg8qRNjPkpTQr43LaE+t73QvJ1tkj3N76s8BLiUvsuNaD64NFC9qqiUPp5kML4nzie+zv+OvlCGmD5stRa+8+C1Pq8IL77oGYW+2gitvqFcXT4dhgG+5baPPTG58L3Xjk++MvS2O17uTT17r2u8GZUXvjBJij54oIU++BYePX9Zpr03ZOE9CBaVvs9vxD7o0Zo+alVovu14AT19C+W9shF7vgO2fj6A0PI9RTGbO3CvcL3x6WO9RpxlvfsshT1KCZ88htAavKs8dzw3cqS9IyDAPIir4D2bKBI9qYkzvhVwWrz/fNq9HxUIvvImNz0V6YU7RZypvLpE3bxKyIW8ax2sPYMhxb2cNoy9f1jFO3mbmjxZsra9QTYiPRAUxL3pN7G91UXVPJ6oFL10Z788CTU+vQiz+72FEhe7Co1zvay2ujM 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 kkPcMvv7tNVpi9BiMKPUvqsL1zOxU9mnc6PY/WaL19HtC9lcGRva0nu7xsI2+9PH0CPuh6qb3dI/i9fybRvAZDur1RZvy7uUk+PZiTx7yb+869IL68PO7+d72kQni8mldaPa4Xj70WXF692oAcPIYMwrzoZmS8aHxFPReRCLyeEhg9MFsSvFYRtr3q0+g9KDXOPAasJr2cZ8U6YFZRPSMU973Hc+09TqEku4XDajzUuf48AHjUParQPb4K8/Y9C3w7vvRFRz60+Tk+UQKyPdWSw71WpM09oKnGvbC92z2c/NU9WqwjPstZYL6QCB8+y9AwvoIaFT6uETo+7FvpPOzukL2iwRY815zNvA6uhD1Xio09aGQWvkhnvTwUbPG8DHehufxJSz0IRly8uoOGvbP7M7323qG9iPWPvdtV1Lzbc7k9t4E/vryB+D0A98O7MeCgPvfFJr6zxHy+z4IbvrDyWT6q8Ja9mCiTPjpKXr4i6IG+YHQYvhUdQD1REis9jmAGPkFOsrM 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 6VCVa9NsUhvaohpzzyIGi99UVMPYWxVr1yquy874XRPBENqbw6nzA7l00+vf2S67wknia9gnucu5ceLr3xOa49bxIoPi6pxb1wxem9+SfBvUMaqj1V5Ce9h9wNPhhC573SqrC9CQXzvY8LILw9yP282GqxPS5NV70NC6q9RU/qOxKxxb1I5Mk9a5i7vbyeFz0HPJg9qynGvfeGsL3UyIY85jrfvB/slT229JI9u3jOvZM3vr3J+ZI9H0WFvTuhKT25qYA9218EPj0LVr5kUoU+fkRQvoKRHD4dUQg+gRG8PRl6Nb4gupA+shEovsOtRD5K//c9m8rDPVMZjr65x7w+IHLvvX2oHT6IdwM+/z0ZPVi+Ar4nPzM+UG6ZvQBEBj59PL890DiGPScyv73C+4I+96TQvcaeFz1Yuvg9kOsbPUXNK74sPGw+zILQOA7tzz03DfQ95+/5vTEA0T0R0yA9l6KCPeMfN72vc569+ZgDvug8qT2IXXw9UDyiPeUwH75zkAi+yGM 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 2x3AC+NrYOPVIBZ71R6wO+ajWHvXanS733DKM9U9oovbcDbbznYbS7ElwHvmHqHz6AmjI8MI0/PlK6Nb7GFQe+1p5AvjiQjD3iQOC93kQJPqnf373YlIK984BLvpoSqrwgCvu8M7PnPZUUEL4zRi2+jO3kPZAVK70bo409GWvcPN0vYT1GvVA9gzR+vK+kCr1PbzG8yQYTvK2z5jzJaEY9mgkIvpqVLL33V6I98EaOPY7p3L1WSze9DFgVPlK3O77kCTo9fWSgvlr/gT4lO0o+qqkzPoSNWr44dcw979KHvlJ+iT42aTA+1bSIPdUbKr4B/+U9zKAlvgj0+T2N7Tc+PpThPbi1B77RoQY+Hngwvjn5yj2e6rY9LhH4Pb8NHb6UDSk+aQwsvnMvSz5F4zQ+GP5kPh1Ne77REbc+xAYkvpjQED44kB4+0dmKvPKSxbychJQ82WsdvfZrnD3hYsg8L2EhPa1DMr2u1ac9EgEBvseZvD0xfrk9YI20PSlZzL3Cz44+BlM 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 2Vu7Wj5rycQMi8ktGmPYc6Ur3ASmG8rYMivR+KRb0QoP+8M8TyPE6rRLqHGgq9+cvpPfhLXb19+pQ9AMOtveAwoT1lrVA9KcHHPVeFEr2ucb48g7qpPDg8ET3v7XY7SpxDPBXCHb1uGFA8IQ1FPLULNDyb1x29YRGfPVUPIzzxTFQ9ISeWvemzHz23O3o8AkaYPZerer1yAeI9oJ+aPMuNkj3FhIo7SE7gPWYijb3nDKo8mtgyvZ7PjDwcRKS8c+9WPXUVh7sP7Ho80DQVPcoNnr0B1nm9qNDjPA4c7rxg4aE81zMMPK65bjpdRFO9C/ehPar5Tb3P4+c9GD84vS9137zzGSs9Xat3O6c0sz3VLIu8GjKWPGb6br2wn6s5eW0tPS1AJz133gw+xflRveN+b7zUVqo8rTLZPc1jx73aWhU+nJ5dvFFqQL3uR5U9l2IdPlt5X70xUyk+OisBvmO2qjzFmvo9tQgxPjWyQ71zmS0+bsQPvO2NGzy4I+U96Z8YPmdBKrM 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 o9vJGlyDwBe+y9RHNCvNfLeL31zmE5STd6Pc6aUDwRwM483nPNvLTLS72wCt+8nVCvPMxssr1p+Lg9vWsvPS8iPzsUupe7kZ6qvGxrtD2ZOxG+QL1nubuxjr0zgFy9u8QuvUKLfj04lgS92bz1PPnuAr0aXmy8GhIROtX1sLzv6Y89v5m3vIZE57qlUoe83e1fvEpwyz0C/669vRN7vSB3U70Ebo+9LPZ/vZCEujykKk+9HW8du4ew2rs23Ae960cePexrHL2QTz89yvcfPNCu87yyqhE7PKwWPWhYdj36kIG9QNgHvQpPhr23ehO9ZE44vPnM5zwzd4u8yDFTvcDTtL06Oam8ZboqPbMp07p3fw4+ev/qu/CatLuSWXE71ou2PYzad733zuQ9PpoNviDEOz1vRQI9A5/fPSxHFr6m1kQ+1pFovBfxP72xRX896bstPbdpQL6zuJI+FKpLPGFWJrxow9M8J5VDPg/CDb4rKo09dA2wvQknwD3EWZQ9dcJlPhEhT7M 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 7zPda/TL4Ivh++/IWkvYxAxT3vxV+9YukdPjiAGL5MyAW+X6YMvfHVyrz2F4c9fU+LPTeQ071iIBG+EJNovVtq5z1hOoq9uSWEPOeo5r0ZUo+9ln7OvaCTLT0qNs+8/IrFPTjKGr6Rlea9a9N5vUDPNDxTIuM8xoecPaLFIL43fd+9xCBnvfAThD38xPC9DajSPfqS0b0q2Ja9zfTSvZUV1z2OAwi+S2/4PWLN173lYxG+r4y7vB6olT1UWo08TPtxPT7a7b15xuO9wsykvff6pj32PZS9NwpjPTlpHr6we7G9/ihivW5r8D0TBUi9WETVPVs32r06PB2+IZjYvWTmsj0ilPc7eu63PTEvAr7UjO69jtfaOmN+673Ufso9OuZkvPBiprxwkMS81IWnu0xbsr3Ih8w9hdAIPfGWGb6iNRC+8y8IvRw6jL2bBek9BgPaPTQpEr0aNvq9UWd4PVCCAL7tdOw9sqV9vc2Mr7yXv/E7nEtKvegO2b38BBA+zUudPbsJ1LM 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 0bsXM9q9rZPaAn6701eBu9vlyYPO82F73jRRQ+LjeqPYjwYbzT8cI7ixl8PfB8kT3rKCI9KllkvfGGPL3nYgO9z/qKPVRcvj22NeU9mUMLPRPZQr00AEs8uuGyPXHGQry9lV0+ON6DPQuzgLijBVy8r6ijPQ1TUTxEYAQ+/2fXvBAHvL2LjUI9+r7xPT/5ND3oFT0+ub9XOiVeAj3xtCs97TBEPvVm+L1+DX8+/JHOPKIUzTzfqJA9T/7qPAkkjD17jfo9kFB7PLICKr0dTg89bGUmPsJZw7yO+Sk+9s0sPCRxljzyyH49THRYPu/KqL0V9ZQ+QBNaPQoJBT0BFt473sbkPX4bFDzcspY9J+lHvGuEUrwH03Q8RLoiPkAo+jySMGM+Agw1PRuiaLq5CLo87bMCPk4JGr3W960++ljdubhbKz3koZ88gf7RPRTtjbyDfNI9sF3xvZO4Mb0MmKY9/NkrPiwqFT0GU3U+SZGJvQdYCr0WLNg9wqhmPisf5L1Cy8U+J0M 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 TOvyJfmz6FzR1AOI9LwIx5yj6H/0jAFCU1QJMNNEBHkKM/yy20v5SyHkB8cx6/3H59P/LLib8dXQbAnfPtP0/o7b4FYDJA2xcEwKTe2D5A4pi+6C6XP/cghb0H1fq8U6d7vsZJqb8qYEbAiqYkPg0TS8Aqsvm/sCqIv7jQFcC9OC7Ayl0iQGMgtT/NTwlALiKdP0oVYb7vRR/AibEmvpsyE8DmGQ1AOCGoPwo/4T9DX6M/Ee3qv/55B8Aj5yrABB0CwDOIAz8ZDb4+4V+TPa96Iz8Qy78/98bSv/gOsT+x6ELAmILav62gzL9MBixAaYOvv+u+G0BnLFa/lbTTvq3RrL9xxhPAbEaGvzMAM0BANFq/Ahuhv5i8yT+E/BzAHfzWPw==", "training_traits": {"structure_gen": "Zigzag", "n_layers": 4, "max_nodes": 6, "activation_func": "Sigmoid", "epoch_num": 11}, "M classes_name": ["Cryptoadz", "Cryptopunks", "Moonbirds", "Nouns"]},m=25,b=50,y=59+11/12,w=59+11.5/12,v=60;function z(e,t){const n=Math.log(1-t)/Math.log(1-e);return e=>1-Math.pow(1-e,n)}class V{constructor(e,t,n){const{model:r,inputDim:i}=j(t,n);this.model=r,this.inputDim=i,this.iteration=0,this.stage=0;const o=new Date(parseInt(e.birthYear),0,1).getTime(),a=new Date(parseInt(e.birthYear)+1,0,1).getTime();this.birthDate=new Date(Math.floor((o+a)/2));const l=zr.filter((t=>t[0]==e.lifeCycle))[0][2];this.growSpeed=365M /l,this.cycleLength=60*l*24*3600*1e3,this.growthFunc=z(.4,.8)}updateAge(e){const t=(e.getTime()-this.birthDate.getTime())/31536e6*this.growSpeed;this.iteration=Math.floor(t/60);const n=t-60*this.iteration;let r;this.age=n;let i,o=0;if(n<25){let e=map(n,0,25,0,1);o=this.growthFunc(e),r=(25-n)/60,this.stage=1,this.stageRatio=map(n,0,25,0,1)}else n<50?(o=1,r=(50-n)/60,this.stage=2,this.stageRatio=map(n,25,50,0,1)):n<y?(o=map(n,50,y,1,0),r=(y-n)/60,this.stage=3,this.stageRatio=map(n,50,y,0,1)):n<w?(o=0,r=(w-n)/60,this.M stage=4,this.stageRatio=map(n,y,w,0,1)):n<60&&(o=0,r=(60-n)/60,this.stage=5,this.stageRatio=map(n,w,60,0,1));n<50?i=map(n,0,50,0,780/880):n<w?i=map(n,50,w,780/880,800/880):n<60&&(i=map(n,w,60,800/880,1)),this.nextStateTimestamp=Math.round(e.getTime()+this.cycleLength*r),this.statePercentage=round(100*i);let a=(25-n)/60;a<0&&(a+=1),this.nextStableTimestamp=Math.round(e.getTime()+this.cycleLength*a),this.growth=o,this.model.updateNeurons(o,this.iteration)}getBrainStatus(){return{totalNeurons:this.model.getTotalNeuronM s(),neuronsLife:this.model.getNeuronsLife(),stage:this.stage,inputDim:this.inputDim,stageRatio:this.stageRatio,age:this.age,growth:this.growth,nextStateTimestamp:this.nextStateTimestamp,nextStableTimestamp:this.nextStableTimestamp,rebirthCount:max(this.iteration,0),statePercentage:this.statePercentage}}classifyImage(e){const t=new G(e,1,e.length);return this.model.forward(t).mat[0]}}class M{constructor(e,t,n,r,i){this.p=e,this.v=t,this.size=n,this.shape=i,this.col=r}getRadius(){return 1==Oe?1*this.size/2:2==Oe?7*thM is.size/16:3==Oe||4==Oe?4*this.size/7:0}update(){this.p.add(this.v)}draw(e,t,n,r){const i=this.p.x*r,o=this.p.y*r,a=this.size*r,{col:l,shape:s}=this;let h,c;1==n?h=c=l:2==n?(h=dr(t,1),c=l):(h=dr(t,0),c=dr(l,1));e.stroke(dr(c,map(1,0,1,.25,1))),e.fill(dr(h,map(1,0,1,.15,1))),3==n&&e.fill(dr(h,0)),1==s?e.ellipse(i,o,a,a):2==s?e.rect(i,o,7*a/8,7*a/8):3==s&&(e.beginShape(),e.vertex(i-4*a/7,o),e.vertex(i,o-4*a/7),e.vertex(i+4*a/7,o),e.vertex(i,o+4*a/7),e.endShape(CLOSE))}}class E{constructor(e,t,n,r,i,o,a){this.center=eM ,this.len=t,this.angle=n,this.v=r,this.angV=i,this.c1=o,this.c2=a}getEndpoints(){const e=createVector(this.len/2*cos(this.angle),this.len/2*sin(this.angle));return[Vector.add(this.center,e),Vector.sub(this.center,e)]}update(){this.center.add(this.v),this.angle+=this.angV}draw(e,t){const[n,r]=this.getEndpoints(),i=n.x*t,o=n.y*t,a=r.x*t,l=r.y*t,s=this.c1,h=this.c2;var c=e.drawingContext.createLinearGradient(i,o,a,l);c.addColorStop(0,s),c.addColorStop(1,h),e.drawingContext.strokeStyle=c,e.drawingContext.globalAlpha=1,M e.line(i,o,a,l),e.drawingContext.globalAlpha=1}}function S(e,t){const n=random(TAU),r=random(e,t);return createVector(r*cos(n),r*sin(n))}class R{constructor(e,t,n,r,i){this.wall=n,this.maxR=i;const o=t.length;this.nodes=[];for(let a=0;a<o;++a){const o=[],l=.25*t[a];for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),l=S(.02*i,.05*i),s=random(10,25)*i;o.push(new M(t,l,s,e[a],r))}this.nodes.push(o)}const a=A(e);a.unshift(e[0]),a.push(e[e.length-1]),this.lines=[];for(let e=0;e<M =o;++e){const r=[],l=(0==e?1:t[e-1])*(e==o?1:t[e])*1.5;for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),o=random(5*i,10*i),l=random(TAU),s=S(.02*i,.05*i),h=random(2e-4,.001);r.push(new E(t,o,l,s,h,a[e],a[e+1]))}this.lines.push(r)}}reflectNode(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,{p:o,v:a}=e,l=e.getRadius();(o.x-l<t&&a.x<0||o.x+l>r&&a.x>0)&&(a.x=-a.x),(o.y-l<n&&a.y<0||o.y+l>i&&a.y>0)&&(a.y=-a.y)}reflectLine(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.M wall,[o,a]=e.getEndpoints(),l=e.v;(min(o.x,a.x)<t&&l.x<0||max(o.x,a.x)>r&&l.x>0)&&(l.x=-l.x),(min(o.y,a.y)<n&&l.y<0||max(o.y,a.y)>i&&l.y>0)&&(l.y=-l.y)}update(){for(const e of this.lines)for(const t of e)t.update(),this.reflectLine(t);for(const e of this.nodes)for(const t of e)t.update(),this.reflectNode(t)}draw(e,t,n,r,i){const o=i/this.maxR;for(const t of this.lines){const n=t.length*r;for(let r=0;r<n;++r)t[r].draw(e,o)}for(const i of this.nodes){const a=i.length*r;for(let r=0;r<a;++r)i[r].draw(e,t,n,o)}}}functioM n I(e,t){re(e),e.fill(0),e.rect(0,0,500,500),ie(e),e.noStroke(),e.fill(dr(cr("#000000"),.5)),e.push(),e.translate(250,250),e.scale(t),e.translate(-250,-250),e.beginShape(),e.vertex(235.2,24.9),e.bezierVertex(215,24.6,185,11.4,164.8,11),e.bezierVertex(147.2,10.7,129.3,10.4,112.2,14.7),e.bezierVertex(95.1,19,78.5,28.5,69.6,43.8),e.bezierVertex(57.699,64.199,61.599,90.199,70.199,112.2),e.bezierVertex(78.799,134.2,91.6,154.6,97.199,177.5),e.bezierVertex(102.499,199.2,100.899,222.5,92.799,243.2),e.bezierVertex(83,268,64M .6,288.3,48.9,310),e.bezierVertex(33.2,331.7,24.5,337.5,26.599,364.1),e.bezierVertex(28.2,384.1,61.399,404.2,75.7,418.3),e.bezierVertex(90,432.4,73.7,488.2,91.9,496.7),e.bezierVertex(124.2,511.6,159,472.5,194.3,468.1),e.bezierVertex(211.6,465.9,267.4,501.5,283.9,495.9),e.bezierVertex(340.7,476.7,298.599,428.9,355.4,409.7),e.bezierVertex(370.799,404.5,454.5,407.6,464.4,394.8),e.bezierVertex(478.599,376.3,474.7,349.3,464.299,328.4),e.bezierVertex(453.9,307.5,438.099,289.5,428.699,268.2),e.bezierVertex(412,230,419,182M .6,446.1,150.9),e.bezierVertex(449.7,146.7,453.6,142.7,455.8,137.6),e.bezierVertex(459.4,129.299,457.5,119.6,454.8,111),e.bezierVertex(443.2,73.4,417.3,40.4,383.6,20.299),e.bezierVertex(358.1,5,343.2,-.4,313.5,0),e.bezierVertex(287.5,.4,261.6,25.4,235.2,24.9),e.endShape(),e.pop()}function C(e,t,n,r,i,o){let a,l,s;re(t),t.fill(0),t.rect(0,0,500,500),ie(t),t.noStroke(),t.fill(dr(n,.5)),1==i?(l=0,s=25,a=map(o,0,25,500,0)):a=0,t.rect(0,a,500,500),e.noStroke(),e.fill(r),e.rect(0,0,500,500),e.beginShape(),e.vertex(435.2,M 373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezieM rVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,1M 2.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,M 195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),e.fill(n),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.M 1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVeM rtex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.beM zierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),re(e),e.fillM (r),e.beginShape(),e.vertex(184.3,473.2),e.bezierVertex(164,473.2,144.7,462.099,134,444.3),e.bezierVertex(131.7,440.5,129.1,438.5,125,437.1),e.bezierVertex(97.3,428.1,80.5,400.6,85.2,371.8),e.bezierVertex(86.3,365.1,85.8,364.1,79.9,361.2),e.bezierVertex(57.2,349.8,46.2,323.3,54.3,299.7),e.bezierVertex(54.7,298.599,55.1,297.7,55.5,296.9),e.bezierVertex(55.6,296.599,55.8,296.4,55.9,296.099),e.vertex(57.9,291.499),e.vertex(62.5,293.599),e.bezierVertex(64.9,294.7,67.3,295.799,69.5,296.9),e.bezierVertex(74.5,299.299,79.M 1,301.599,83.9,303.099),e.bezierVertex(89.8,304.9,96.5,305.499,102.7,305.9),e.bezierVertex(102.8,305.9,102.9,305.9,103,305.9),e.bezierVertex(106.6,305.9,108.9,302.799,109,299.799),e.bezierVertex(109.1,296.199,106.6,293.4,102.7,292.799),e.bezierVertex(101.3,292.599,99.9,292.4,98.4,292.299),e.bezierVertex(94.3,291.799,90.1,291.299,86,289.9),e.bezierVertex(68.9,284,56.5,270.2,52.7,252.799),e.bezierVertex(48.9,235.499,54.5,217.7,67.6,205.299),e.bezierVertex(71.9,201.299,72.7,198.1,70.8,192.399),e.bezierVertex(64.2,172.M 2,68.8,153.99,84.2,139.599),e.bezierVertex(94.2,130.199,105.5,125.399,117.8,125.399),e.bezierVertex(124.3,125.399,131.1,126.799,137.8,129.599),e.bezierVertex(157,137.399,167.9,152.799,169.4,173.99),e.vertex(169.4,174.399),e.bezierVertex(169.5,175.899,169.6,177.2,169.9,178.299),e.bezierVertex(170.7,181.2,173.2,183.2,176.1,183.2),e.bezierVertex(176.299,183.2,176.5,183.2,176.7,183.2),e.bezierVertex(180.1,182.899,182.6,180.299,182.7,177),e.bezierVertex(183.1,162,178.299,148.2,168.399,136.1),e.bezierVertex(158.2,123.5,1M 44.899,115.8,128.799,113.199),e.bezierVertex(123.499,112.299,120.399,109.799,118.899,104.99),e.bezierVertex(113.899,89.699,120.699,72.299,134.899,64.499),e.bezierVertex(139.99,61.699,145.799,60.199,151.7,60.199),e.bezierVertex(162.2,60.199,171.899,64.799,178.1,72.699),e.bezierVertex(179.6,74.6,180.799,76.6,181.9,78.499),e.vertex(182.2,79.099),e.bezierVertex(183.2,80.699,185.2,83.299,188.4,83.299),e.bezierVertex(189.5,83.299,190.6,82.99,191.7,82.399),e.bezierVertex(195.1,80.599,196,76.99,194,72.799),e.bezierVertex(1M 90.1,64.799,184.1,58.499,175.6,53.299),e.bezierVertex(174.6,52.699,173.7,52.099,172.5,51.499),e.vertex(170.5,50.299),e.vertex(163,45.899),e.vertex(170.5,41.599),e.bezierVertex(182,34.99,193.1,30.799,204.4,28.599),e.bezierVertex(208.6,27.799,212.9,27.399,217.2,27.399),e.bezierVertex(217.6,27.399,217.9,27.399,218.3,27.399),e.bezierVertex(231.4,27.599,242.7,38.199,243,50.599),e.bezierVertex(243.4,64.899,243.3,78.99,243.2,93.799),e.bezierVertex(243.2,99.799,243.1,105.899,243.1,112.099),e.vertex(243.1,119.199),e.vertex(M 236.4,116.799),e.bezierVertex(235.7,116.499,235,116.299,234.4,115.99),e.bezierVertex(233.4,115.599,232.6,115.299,232,115.199),e.bezierVertex(230.6,114.899,229.2,114.599,227.8,114.299),e.bezierVertex(223.8,113.499,220.1,112.699,216.4,112.499),e.vertex(216.2,112.499),e.bezierVertex(212.5,112.499,210.7,115.599,210.6,118.599),e.bezierVertex(210.4,122.399,212.7,125.099,216.4,125.399),e.bezierVertex(230.1,126.399,238.9,133.099,242.3,145.199),e.bezierVertex(243.2,148.399,243.2,151.599,243.2,154.499),e.vertex(243.2,155.099M ),e.bezierVertex(243.2,254.199,243.2,330,243.2,400.599),e.bezierVertex(243.2,401.99,243.2,403.4,243.2,404.9),e.bezierVertex(243.3,411.099,243.3,417.599,242.3,423.9),e.bezierVertex(238.1,449.2,219.6,467.799,194,472.5),e.bezierVertex(190.9,472.9,187.6,473.2,184.3,473.2),e.endShape(),e.beginShape(),e.vertex(315.8,473.1),e.bezierVertex(309.3,473.1,302.8,472,296.5,469.9),e.bezierVertex(270.4,461,253.8,434.9,257.1,407.9),e.bezierVertex(260,384,273.8,366.8,297,358.3),e.bezierVertex(297.7,358.1,298.3,357.8,299,357.6),e.bezM ierVertex(299.8,357.3,300.6,357.1,301.2,356.8),e.bezierVertex(304.3,355.4,306,351.8,304.9,348.7),e.bezierVertex(304,345.9,301.7,344.2,299,344.2),e.bezierVertex(298.6,344.2,298.1,344.2,297.6,344.3),e.bezierVertex(288.1,346.3,279,350.9,269.7,358.3),e.bezierVertex(268.9,358.9,268.1,359.6,267.2,360.4),e.vertex(265.5,361.8),e.vertex(258.5,367.6),e.vertex(257.4,358.6),e.bezierVertex(257.3,358,257.3,357.5,257.2,357.1),e.bezierVertex(257,356,256.9,354.9,256.9,353.7),e.bezierVertex(256.9,334.8,256.9,316,256.9,297.1),e.bezieM rVertex(256.9,260.3,256.9,222.3,256.8,185),e.bezierVertex(256.8,170.7,268.3,158.8,282.5,158.4),e.bezierVertex(284.8,158.3,286.7,157.6,287.9,156.2),e.bezierVertex(289.099,154.9,289.599,153.2,289.5,151.3),e.bezierVertex(289.3,147.5,286.7,145.1,282.7,145.1),e.bezierVertex(282.5,145.1,282.2,145.1,282,145.1),e.bezierVertex(278.8,145.3,275.5,146.1,272,146.9),e.bezierVertex(270.9,147.2,269.8,147.4,268.6,147.7),e.bezierVertex(267.9,147.9,267,148.2,265.8,148.7),e.bezierVertex(265.1,149,264.4,149.3,263.5,149.6),e.vertex(256.M 8,152),e.vertex(256.8,114.6),e.bezierVertex(256.8,95,256.8,75.4,256.8,55.9),e.bezierVertex(256.8,38,267.2,27.3,284.6,27.3),e.bezierVertex(285.3,27.3,285.9,27.3,286.6,27.3),e.bezierVertex(299,27.9,318.7,34.5,329.6,41.9),e.vertex(336.1,46.3),e.vertex(324.4,53.3),e.bezierVertex(316.2,58.2,310.2,64.6,306,72.9),e.bezierVertex(304.2,76.4,305.1,78.5,306.1,80),e.bezierVertex(307.4,81.9,309.4,83,311.6,83),e.bezierVertex(313.7,83,315.7,81.9,317.1,80.1),e.bezierVertex(317.4,79.7,317.8,79,318.1,78.4),e.bezierVertex(318.4,77.9,M 318.7,77.3,319,76.8),e.bezierVertex(325.3,66.2,336.3,59.9,348.5,59.9),e.bezierVertex(353.2,59.9,357.8,60.8,362.1,62.7),e.bezierVertex(377.6,69.3,386,86.7,381.7,103.2),e.bezierVertex(380.7,107.1,378.5,111.8,371.1,113.1),e.bezierVertex(342.7,118.1,322.2,139.1,317.8,167.8),e.bezierVertex(317.4,170.3,317.3,173.2,317.4,176.5),e.bezierVertex(317.5,180,320.1,182.8,323.5,183),e.bezierVertex(323.6,183,323.8,183,323.9,183),e.bezierVertex(327.1,183,329.8,180.6,330.3,177.2),e.bezierVertex(330.6,175.7,330.7,174,330.9,172.3),e.bM ezierVertex(331.1,169.8,331.4,167.3,332,164.7),e.bezierVertex(337.3,141.9,357.7,125.4,380.7,125.4),e.bezierVertex(382.5,125.4,384.3,125.5,386.1,125.7),e.bezierVertex(412.8,128.9,432.6,150.9,432,176.9),e.bezierVertex(431.9,182.3,430.9,187.7,429.1,192.7),e.bezierVertex(427.2,197.9,428,201,432.3,205),e.bezierVertex(446.8,218.7,451.8,236,446.6,255),e.bezierVertex(441.4,274,428.3,286.5,408.7,291.3),e.bezierVertex(406.1,291.9,403.6,292.1,401.1,292.3),e.bezierVertex(400,292.4,398.9,292.5,397.9,292.6),e.bezierVertex(393.6,M 293.1,390.9,295.7,391,299.5),e.bezierVertex(391.1,303.4,394,305.8,398.5,305.8),e.bezierVertex(409.9,305.8,420.8,302.6,431.1,296.4),e.bezierVertex(431.8,296,432.5,295.5,433.2,295.1),e.bezierVertex(433.8,294.7,434.5,294.3,435.2,293.9),e.bezierVertex(436,293.4,436.6,293.2,437.2,293.1),e.bezierVertex(437.4,293,437.7,292.9,438.1,292.8),e.vertex(442.5,291.4),e.vertex(444.2,295.7),e.bezierVertex(450.9,312.4,449.5,328.4,440,343.4),e.bezierVertex(435.3,350.8,428.7,356.7,420.2,361.1),e.bezierVertex(414.3,364.1,413.7,365.2,41M 4.8,371.7),e.bezierVertex(419.5,400.2,403,427.6,375.6,436.9),e.bezierVertex(371,438.5,368.3,440.7,365.8,444.7),e.bezierVertex(355.2,462.5,336.4,473.1,315.8,473.1),e.bezierVertex(315.8,473.1,315.8,473.1,315.8,473.1),e.endShape(),ie(e),e.fill(n),e.beginShape(),e.vertex(120.2,279.9),e.bezierVertex(117.9,279.9,112.4,279.299,112.2,273.599),e.bezierVertex(112,267.7,117.4,266.7,119.7,266.599),e.bezierVertex(133.1,265.799,143.1,259.499,149.3,247.899),e.bezierVertex(149.6,247.299,150.1,246.399,150.3,245.399),e.bezierVertex(M 150.6,244.299,150.5,243.299,150.5,242.7),e.bezierVertex(150.5,242.6,150.5,242.5,150.5,242.299),e.vertex(150.3,238.799),e.vertex(141.1,235.99),e.bezierVertex(114.6,227.799,95.6,202.499,95.9,175.799),e.bezierVertex(95.9,173.99,96.4,168.199,102.2,168.199),e.bezierVertex(102.6,168.199,103,168.199,103.4,168.299),e.bezierVertex(104.8,168.499,108.2,168.899,109.2,175.599),e.bezierVertex(109.3,176.599,109.5,177.599,109.6,178.499),e.bezierVertex(110.4,184.199,111.3,189.99,113.7,195.499),e.bezierVertex(121.9,213.99,139.5,225.M 499,159.7,225.499),e.bezierVertex(172.1,225.499,184.1,220.899,193.5,212.599),e.bezierVertex(194,212.199,194.4,211.799,194.8,211.399),e.bezierVertex(195.1,211.099,195.5,210.799,195.8,210.399),e.bezierVertex(197.4,208.99,199.2,208.2,200.9,208.2),e.bezierVertex(202.5,208.2,204,208.899,205.3,210.1),e.bezierVertex(208,212.9,207.9,216.9,205,219.9),e.bezierVertex(196.5,228.6,186.3,234.3,174.7,236.8),e.bezierVertex(168.799,238.1,165.6,241,163.899,246.7),e.bezierVertex(158.3,265.9,139.9,279.7,120.2,279.9),e.vertex(120.2,279M .9),e.endShape(),e.beginShape(),e.vertex(187.2,427.5),e.bezierVertex(183.799,427.5,181.299,425.3,180.799,422),e.bezierVertex(180.6,420.8,180.499,419.5,180.399,418.1),e.bezierVertex(180.299,417,180.2,415.8,180.099,414.7),e.bezierVertex(177.199,390.5,156.699,371.3,132.399,370.2),e.bezierVertex(131.99,370.2,131.499,370.2,131.099,370.2),e.bezierVertex(130.699,370.2,130.299,370.2,129.799,370.2),e.bezierVertex(125.99,369.9,123.199,367.2,123.099,363.6),e.bezierVertex(122.99,360.2,125.799,357.3,129.599,356.9),e.bezierVerteM x(130.499,356.8,131.499,356.8,132.599,356.7),e.bezierVertex(133.199,356.7,133.799,356.7,134.399,356.6),e.vertex(138.299,356.4),e.vertex(139.1,352.6),e.bezierVertex(139.5,350.7,139.799,348.9,140.2,347),e.bezierVertex(140.899,343.4,141.5,340,142.399,336.8),e.bezierVertex(150.099,310.7,174.399,292,201.399,291.3),e.vertex(201.599,291.3),e.bezierVertex(203.699,291.3,206.299,292,208.299,293.2),e.bezierVertex(210.499,294.5,210.699,297.5,209.99,299.8),e.bezierVertex(209.499,301.5,208.199,303.9,203.299,304.7),e.bezierVertexM (202.199,304.9,200.99,305,199.799,305.2),e.bezierVertex(194.499,305.9,188.99,306.599,183.799,308.9),e.bezierVertex(165.499,316.799,155.199,331.299,152.99,352),e.bezierVertex(152.399,357.8,154.499,361.7,159.699,364.5),e.bezierVertex(178.199,374.4,189.399,390,193.099,410.9),e.bezierVertex(193.699,414.299,193.899,418,193.599,422),e.bezierVertex(193.399,425.2,190.899,427.5,187.399,427.5),e.vertex(187.2,427.5),e.endShape(),e.beginShape(),e.vertex(364.3,281.1),e.bezierVertex(346.3,280.6,332.9,272.8,323.5,257),e.bezierVerM tex(321.6,253.9,320.4,250.2,319.2,246.7),e.bezierVertex(317.7,242.2,315,239.799,310.5,238.799),e.bezierVertex(298.5,236.299,288,230.7,279.4,222.1),e.bezierVertex(276.7,219.4,274.9,215.299,278,211.9),e.bezierVertex(279.4,210.3,281,209.6,282.6,209.6),e.bezierVertex(284.4,209.6,286.4,210.6,288.3,212.5),e.bezierVertex(297.8,221.8,310.4,226.9,323.9,226.9),e.bezierVertex(340.2,226.9,355.1,219.3,364.8,206.2),e.bezierVertex(371,197.8,374.2,188.5,374.5,178.5),e.vertex(374.5,177.9),e.bezierVertex(374.5,177,374.5,176.1,374.7,M 175.4),e.bezierVertex(375.3,171.8,377.9,169.5,381.3,169.5),e.bezierVertex(381.4,169.5,381.5,169.5,381.7,169.5),e.bezierVertex(385.4,169.7,388,172.4,388,176.1),e.bezierVertex(388.1,190.7,383.4,204,374.2,215.8),e.bezierVertex(365.8,226.5,354.7,233.9,341.2,237.9),e.bezierVertex(340,238.3,338.7,238.6,337.3,239.1),e.bezierVertex(335.9,239.6,335.1,240.4,334.7,240.9),e.bezierVertex(334.599,241,334.5,241.1,334.4,241.2),e.vertex(331.799,243.6),e.vertex(333.199,246.8),e.bezierVertex(338.199,258,346.799,264.9,358.699,267.3),eM .bezierVertex(360.199,267.6,361.599,267.7,362.99,267.9),e.bezierVertex(363.599,268,364.299,268,364.899,268.1),e.bezierVertex(369.099,268.6,371.799,271.4,371.499,275),e.bezierVertex(371.199,278.6,368.299,281.2,364.399,281.2),e.vertex(364.3,281.1),e.endShape(),e.beginShape(),e.vertex(323.9,437),e.bezierVertex(323.7,437,323.5,437,323.299,437),e.bezierVertex(319.599,436.7,317.299,434.1,317.4,430.2),e.bezierVertex(317.9,406.099,328.299,388,349.5,375),e.bezierVertex(350.7,374.2,352,373.5,353.4,372.8),e.bezierVertex(354.0M 99,372.4,354.7,372.1,355.299,371.7),e.vertex(357.499,370.5),e.vertex(357.799,368),e.bezierVertex(360.4,346.6,345.199,323.7,323.9,317),e.bezierVertex(319.099,315.5,314.099,314.9,309.299,314.4),e.vertex(308.199,314.299),e.bezierVertex(305.99,314.099,300.799,312.9,300.899,307.299),e.bezierVertex(300.99,303.499,303.899,300.9,308.099,300.9),e.vertex(308.299,300.9),e.bezierVertex(327.099,301.299,343.099,308.7,355.699,322.9),e.bezierVertex(364.299,332.5,369.399,344.099,370.99,357.299),e.bezierVertex(371.099,358.4,371.299,M 359.4,371.499,360.499),e.bezierVertex(371.599,360.99,371.699,361.499,371.799,361.99),e.vertex(372.499,365.899),e.vertex(377.899,366.199),e.bezierVertex(378.799,366.299,379.699,366.299,380.599,366.399),e.bezierVertex(385.099,366.699,387.899,369.399,387.799,373.299),e.bezierVertex(387.699,377.099,384.99,379.599,380.799,379.799),e.bezierVertex(369.799,380.199,359.99,383.299,351.899,389.299),e.bezierVertex(338.799,398.799,331.699,411.699,330.699,427.499),e.vertex(330.699,428.299),e.bezierVertex(330.599,429.199,330.599,M 430.099,330.499,430.799),e.bezierVertex(330,434.7,327.5,437,323.9,437),e.endShape()}function T(e){return e[0].map(((t,n)=>e.map((e=>e[n]))))}function A(e){return e.map((e=>Array.isArray(e)?A(e):e))}function D(e,t){return floor(random(e,t))}function k(e){let t=0;for(const n of e)t+=n[1];let n=random(t),r=0;for(const t of e)if(r+=t[1],n<r)return t[0];return null}function L(e){for(let t=1;t<e.length;++t){let n=D(0,t),r=e[t];e[t]=e[n],e[n]=r}}function P(e){return null==e||""===e}function O(e){return new Promise((t=>setM Timeout(t,e)))}function F(e,t,n){let r=0;for(let i=1;i<=1e3;++i)for(let o=1;o<=1e3;++o)if(e*o%(t*i)==0){let e=1*i/o;abs(e-n)<abs(r-n)&&(r=e)}return r}function N(){let e=60*(new Date).getTimezoneOffset()*1e3;return new Date(Date.now()-e).toISOString().slice(0,-1)}function B(e,t,n){let r;if(push(),textSize(e),textWidth(t)<=n)r=t;else for(let e=0;e<t.length;++e){const i=t.slice(0,e+1)+"...";if(textWidth(i)>n){r=i;break}}return pop(),r}function Y(e){var t=e%10,n=e%100;return 1==t&&11!=n?e+"st":2==t&&12!=n?e+"nd":3==t&&M 13!=n?e+"rd":e+"th"}class G{constructor(e,t,n){this.n=t,this.m=n,this.mat=[];let r=0;for(let t=0;t<this.n;++t){this.mat.push([]);for(let n=0;n<this.m;++n)this.mat[t].push(r<e.length?e[r]:0),r+=1}return this}copy(){return new G(this.mat.flat(),this.n,this.m)}}class H{static __linear=e=>e;static __relu=e=>Math.max(e,0);static __leaky_relu=e=>e>0?e:.2*e;static __sigmoid=e=>1/(1+Math.exp(-e));static __tanh=e=>Math.tanh(e);static __apply_unary_op(e,t){const n=e.copy();for(let e=0;e<n.n;++e)for(let r=0;r<n.m;++r)n.mat[e]M [r]=t(n.mat[e][r]);return n}static linear=e=>H.__apply_unary_op(e,H.__linear);static relu=e=>H.__apply_unary_op(e,H.__relu);static leaky_relu=e=>H.__apply_unary_op(e,H.__leaky_relu);static sigmoid=e=>H.__apply_unary_op(e,H.__sigmoid);static tanh=e=>H.__apply_unary_op(e,H.__tanh);static __add=(e,t)=>e+t;static __mul=(e,t)=>e*t;static __apply_binary_op=(e,t,n)=>{"object"!=typeof t&&(t=new G([t],1,1));const r=e.copy();for(let e=0;e<r.n;++e)for(let i=0;i<r.m;++i)r.mat[e][i]=n(r.mat[e][i],t.mat[e%t.n][i%t.m]);return r};M static mul=(e,t)=>H.__apply_binary_op(e,t,H.__mul);static add=(e,t)=>H.__apply_binary_op(e,t,H.__add);static matMul(e,t){const n=new G([],e.n,t.m);for(let r=0;r<n.n;++r)for(let i=0;i<n.m;++i)for(let o=0;o<e.m;++o)n.mat[r][i]+=e.mat[r][o]*t.mat[o][i];return n}static softmax(e){const t=H.__apply_unary_op(e,(e=>Math.exp(e))),n=t.mat.flat().reduce(((e,t)=>e+t));for(let r=0;r<e.n;++r)for(let i=0;i<e.m;++i)t.mat[r][i]/=n;return t}}class ${constructor(e,t){this.scale=e,this.offset=t}forward(e){return H.add(H.mul(e,this.scM ale),this.offset)}}class X{constructor(){}forward(e){return e.map((e=>e.flat()))}}class W{constructor(e,t,n,r){this.out_dim=e,this.activation=t,this.w=n,this.b=r}forward(e){const t=H.add(H.matMul(e,this.w),this.b);return null==this.activation?t:this.activation(t)}}class U{constructor(e,t,n){this.preprocessLayers=e,this.hiddenLayers=t,this.outputLayer=n,this.totalNeurons=this.hiddenLayers.map((e=>e.out_dim)),this.currentOrders=[],this.currentIteration=null}updateNeurons(e,t){if(t!=this.currentIteration){this.currentM Orders=[];for(let e=0;e<this.totalNeurons.length;++e){randomSeed(100*(t+1)+e);const n=[];for(let t=0;t<this.totalNeurons[e];++t)n.push(t);L(n),this.currentOrders.push(n)}this.currentIteration=t}const n=A(this.totalNeurons),r=n.reduce(((e,t)=>e+t))*(1-e);for(let e=0;e<r;++e){const t=n.map(((e,t)=>(e-1)/this.totalNeurons[t]));n[t.map(((e,t)=>[e,t])).reduce(((e,t)=>t[0]>e[0]?t:e))[1]]-=Math.min(r-e,1)}this.neuronsLife=[];for(let e=0;e<n.length;++e){const t=this.currentOrders[e],r=Array(this.totalNeurons[e]).fill(0);foM r(let i=0;i<n[e];++i)r[t[i]]=Math.min(n[e]-i,1);this.neuronsLife.push(r)}}getTotalNeurons(){return A(this.totalNeurons)}getNeuronsLife(){return A(this.neuronsLife)}forward(e){for(const t of this.preprocessLayers)e=t.forward(e);for(const[t,n]of this.hiddenLayers.entries()){e=n.forward(e);const r=new G(this.neuronsLife[t],1,e.m);e=H.mul(e,r)}return e=this.outputLayer.forward(e),H.softmax(e)}}function q(e){switch(e){case"relu":return H.relu;case"sigmoid":return H.sigmoid;case"tanh":return H.tanh;case"leaky_relu":returM n H.leaky_relu;default:return H.linear}}function j(e,t){const n=[],r=[],i=Z(t);let o=null,a=0,l=[];for(const t of e.config.layers)if("InputLayer"==t.class_name)o=t.config.batch_input_shape.slice(1),l=o;else if("Rescaling"==t.class_name)n.push(new $(t.config.scale,t.config.offset));else if("Flatten"==t.class_name)o=[o.reduce(((e,t)=>e*t))];else if("Dense"==t.class_name){const e=[t.config.units],n=o[0]*e[0],l=e[0],s=i.subarray(a,a+n);a+=n;const h=i.subarray(a,a+l);a+=l;const c=new G(s,o[0],e[0]),u=new G(h,1,e[0]),f=qM (t.config.activation);r.push(new W(e[0],f,c,u)),o=e}const s=r.pop();return{model:new U(n,r,s),inputDim:l}}function Z(e){const t=window.atob(e),n=t.length/Float32Array.BYTES_PER_ELEMENT,r=new DataView(new ArrayBuffer(Float32Array.BYTES_PER_ELEMENT)),i=new Float32Array(n);let o=0;for(let e=0;e<n;e++){o=4*e;for(let e=0;e<4;++e)r.setUint8(e,t.charCodeAt(o+e));i[e]=r.getFloat32(0,!0)}return i}class K{constructor(e){this.elt=e,this._events={},this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight}position(){ifM (0===arguments.length)return{x:this.elt.offsetLeft,y:this.elt.offsetTop};var e="absolute";return"static"!==arguments[2]&&"fixed"!==arguments[2]&&"relative"!==arguments[2]&&"sticky"!==arguments[2]&&"initial"!==arguments[2]&&"inherit"!==arguments[2]||(e=arguments[2]),this.elt.style.position=e,this.elt.style.left=arguments[0]+"px",this.elt.style.top=arguments[1]+"px",this.x=arguments[0],this.y=arguments[1],this}show(){return this.elt.style.display="block",this}hide(){return this.elt.style.display="none",this}size(e,t)M {if(0===arguments.length)return{width:this.elt.offsetWidth,height:this.elt.offsetHeight};var n=e,r=t;if(n!==te||r!==te){if(n===te?n=t*this.width/this.height:r===te&&(r=e*this.height/this.width),this.elt instanceof HTMLCanvasElement){var i,o={},a=this.elt.getContext("2d");for(i in a)o[i]=a[i];for(i in this.elt.setAttribute("width",n*this._pInst._pixelDensity),this.elt.setAttribute("height",r*this._pInst._pixelDensity),this.elt.style.width=n+"px",this.elt.style.height=r+"px",this._pInst.scale(this._pInst._pixelDensitM y,this._pInst._pixelDensity),o)this.elt.getContext("2d")[i]=o[i]}else this.elt.style.width=n+"px",this.elt.style.height=r+"px",this.elt.width=n,this.elt.height=r;this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight,this._pInst&&this._pInst._curElement&&this._pInst._curElement.elt===this.elt&&(this._pInst._setProperty("width",this.elt.offsetWidth),this._pInst._setProperty("height",this.elt.offsetHeight))}return this}style(e,t){if(t instanceof Color&&(t="rgba("+t.levels[0]+","+t.levels[1]+","+t.levels[2]M +","+t.levels[3]/255+")"),void 0===t){if(-1===e.indexOf(":"))return window.getComputedStyle(this.elt).getPropertyValue(e);for(var n=e.split(";"),r=0;r<n.length;r++){var i=n[r].split(":");i[0]&&i[1]&&(this.elt.style[i[0].trim()]=i[1].trim())}}else if(this.elt.style[e]=t,"width"===e||"height"===e||"left"===e||"top"===e){var o=window.getComputedStyle(this.elt).getPropertyValue(e).replace(/[^\d.]/g,"");this[e]=Math.round(parseFloat(o,10))}return this}value(){return arguments.length>0?(this.elt.value=arguments[0],this):M "range"===this.elt.type?parseFloat(this.elt.value):this.elt.value}mouseClicked(e){return this._adjustListener("click",e,this),this}isFocused(){return document.activeElement===this.elt}_adjustListener(e,t,n){return!1===t?this._detachListener(e,n):this._attachListener(e,t,n),this}_attachListener(e,t,n){n._events[e]&&this._detachListener(e,n);var r=t.bind(n);n.elt.addEventListener(e,r,!1),n._events[e]=r}_detachListener(e,t){var n=t._events[e];t.elt.removeEventListener(e,n,!1),t._events[e]=null}}function J(e,t){var n=dM ocument.createElement("button");return n.innerHTML=e,t&&(n.value=t),ee(n)}function Q(e){var t=arguments.length>1&&void 0!==arguments[1]&&arguments[1],n=function(t){var n=!0,r=!1,i=void 0;try{for(var o,a=t.target.files[Symbol.iterator]();!(n=(o=a.next()).done);n=!0){var l=o.value;File._load(l,e)}}catch(e){r=!0,i=e}finally{try{n||null==a.return||a.return()}finally{if(r)throw i}}};if(window.File&&window.FileReader&&window.FileList&&window.Blob){var r=document.createElement("input");return r.setAttribute("type","file")M ,t&&r.setAttribute("multiple",!0),r.addEventListener("change",n,!1),ee(r)}}function ee(e){return document.body.appendChild(e),new K(e)}createImg=function(){var e,t=document.createElement("img"),n=arguments;return n.length>1&&"string"==typeof n[1]&&(t.alt=n[1]),n.length>2&&"string"==typeof n[2]&&(t.crossOrigin=n[2]),t.src=n[0],e=ee(t,this),t.addEventListener("load",(function(){e.width=t.offsetWidth||t.width,e.height=t.offsetHeight||t.height;var r=n[n.length-1];"function"==typeof r&&r(e)})),e},createInput=function(){M var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:"",t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:"text",n=document.createElement("input");return n.setAttribute("value",e),n.setAttribute("type",t),ee(n,this)};const te="auto";function ne(e){re(e);const t=e._rectMode;e.rectMode(CORNER),e.rect(0,0,e.width,e.height),e.rectMode(t),ie(e)}function re(e){e.push(),e.fill(255,255,255,255),e.blendMode(REMOVE)}function ie(e){e.blendMode(BLEND),e.pop()}File=function(e,t){this.file=e,this._pInst=t;var n=e.M type.split("/");this.type=n[0],this.subtype=n[1],this.name=e.name,this.size=e.size,this.data=void 0},File._createLoader=function(e,t){var n=new FileReader;return n.onload=function(n){var r=new File(e);if("application/json"===r.file.type)r.data=JSON.parse(n.target.result);else if("text/xml"===r.file.type){var i=(new DOMParser).parseFromString(n.target.result,"text/xml");r.data=new XML(i.documentElement)}else r.data=n.target.result;t(r)},n},File._load=function(e,t){if(/^text\//.test(e.type)||"application/json"===e.tyM pe)File._createLoader(e,t).readAsText(e);else if(/^(video|audio)\//.test(e.type)){var n=new File(e);n.data=URL.createObjectURL(e),t(n)}else File._createLoader(e,t).readAsDataURL(e)},XML=function(e){if(e)this.DOM=e;else{var t=document.implementation.createDocument(null,"doc");this.DOM=t.createElement("root")}},document.addEventListener("DOMContentLoaded",(function(){addEventListener("mousemove",(e=>{window.mouseX=e.pageX,window.mouseY=e.pageY}))})),new e("global");const oe="418";let ae,le,se,he,ce,ue,fe,de,xe,ge,pe,M me,be,ye,we,ve,ze,Ve,_e,Me,Ee,Se,Re,Ie,Ce,Te,Ae,De,ke,Le,Pe,Oe,Fe,Ne,Be,Ye,Ge,He,$e,Xe,We,Ue,qe,je,Ze,Ke,Je,Qe,et,tt,nt,rt,it,ot,at,lt,st,ht,ct,ut,ft,dt,xt,gt,pt,mt,bt,yt,wt,vt,zt,Vt,_t,Mt,Et,St,Rt,It,Ct,Tt,At=!1,Dt=!1,kt=!0,Lt=!1,Pt=!1;const Ot=[" ","Growing","Stable","Decaying","Dead","Rebirth"];let Ft,Nt,Bt,Yt,Gt,Ht,$t,Xt,Wt,Ut,qt,jt,Zt,Kt,Jt,Qt,en,tn,nn,rn,on,an,ln,sn,hn=0,cn=0,un=0,fn=!1,dn=!0,xn=!0,gn=null,pn=null,mn=null,bn=!1,yn=!1,wn=null,vn=null,zn=!1;async function setup(){let e=windowWidth,t=windowHeighM t;createCanvas(e,t),et=createGraphics(e,t),Xe=createGraphics(e,t),$e=createGraphics(e,t),We=createGraphics(e,t),Ue=createGraphics(e,t),qe=createGraphics(e,t),Qe=createGraphics(e,t),je=createGraphics(e,t),Ze=createGraphics(e,t),Ke=createGraphics(e,t),Je=createGraphics(e,t),tt=createGraphics(500,500),nt=createGraphics(500,500),rt=createGraphics(500,500),_n(),Mn(),Sn(),await En(),Gn(),Rn(),bn=!0}function _n(){Et=parseInt(oe),randomSeed(Et),noiseSeed(Et)}function Mn(){Wt=Ir(p.training_traits),Cr(Wt)}async function En()M {let e;Jt=r(),Qt=o(),[Xt,e]=await Promise.all([s(Jt),h(Qt)]),Ut=new V(Wt.visual,e.layers_config,e.weight_b64),Ut.updateAge(new Date),_n(),Wt.training=e.training_traits,Ht=e.model_name,$t=e.classes_name}function Sn(){le=min(width,height)/1024,ut=Rr.findIndex((e=>e[0]===Wt.visual.colorPalette)),ft=[["#ffffff","#231f20","#231f20"],["#231f20","#ffffff","#ffffff"],["#104da8","#ffffff","#ffffff"],["#722F1F","#FCE1B2","#FCE1B2"],["#e88120","#f9f2e5","#f9f2e5"],["#f6b941","#2E2E2E","#2E2E2E"],["#45daaa","#012221","#012221"M ],["#F1F1F1","#328DFE","#328DFE"],["#111822","#D3EB8D","#D3EB8D"],["#713FF9","#D6D5E6","#D6D5E6"],["#FBDA9D","#795106","#795106"],["#8f5b62","#ead0d0","#ead0d0"],["#eae4cb","#508cac","#508cac"],["#ffc6cc","#cc313d","#cc313d"],["#60A900","#E0FE00","#E0FE00"],["#507DBE","#D0D1D3","#D0D1D3"],["#305848","#E8F2EE","#E8F2EE"],["#2a2634","#5b6988","#cb78a2","#5b6988"],["#590e29","#fd5e53","#fd5e53","#ffe373"],["#0a141d","#57d4e4","#328195","#2A9ECF","#0ab6a8","#57d4e4"],["#3a2d28","#d5c2ac","#df6338","#3d9895","#d5c2ac"],M ["#030706","#77c4d9","#77c4d9","#77c4d9","#ffffff","#ffffff","#e72020","#e72020"],["#3a4664","#92f5ff","#f9ff94","#eaa0a2","#55dde0"],["#fbfaff","#f04bb1","#f04bb1","#fac373","#82cef0","#8b31ce"],["#000000","#ffffff","#ff0002","#f26522","#fdff00","#00ff03","#01fffe","#0000ff","#ff00ff"]];for(let e=0;e<ft.length;++e)for(let t=0;t<ft[e].length;++t)ft[e][t]=cr(ft[e][t]);pt=[],ct=ft[ut][0],st=ft[ut][1]}function Rn(){gn=document.querySelector("#upload"),pn=document.querySelector("#inputUpload"),gn.addEventListener("dblcM lick",(()=>{if(!Lt&&!yn)if(In(Ie)&&cn==Ve-1)pn.click();else{if(4!=Pe&&5!=Pe&&(In(Ie)||cn!=Ve-1))return;fn=!0,dn=!0,Bt=0,un=0}})),pn.addEventListener("click",(()=>{pn.value=null,gn.style.display="block"})),pn.addEventListener("change",(()=>{const[e]=pn.files;e?(se=null,gn.style.display="none",Tn(URL.createObjectURL(e)),mn=e):gn.style.display="block"}))}function In(e){for(let t=0;t<e.length;++t){let n=0;for(let r=0;r<e[t].length;++r)e[t][r]>0&&++n;if(0==n)return!1}return!0}function Cn(){null!=se&&(un=0,Pt=!0,he=0,ue=M 0,drewLineAnim=!0,ce=(ae/2+we/2)/le,loadImage(se.elt.src,(e=>{const[t,n,r]=Gt,i=createGraphics(t,n);i.image(e,0,0,t,n),i.loadPixels();const o=i.pixels.filter(((e,t)=>t%4!=3)),a=Ut.classifyImage(o);Zt=T([a,$t.map((e=>e.toUpperCase()))]).sort(((e,t)=>e[0]>t[0]?-1:1))})))}function Tn(e){se=createImg(e,""),se.hide(),Cn()}function An(){zn||(ce+=(width-ae-we)/tn/le),re(Xe),Xe.rect(ce*le,0,width,height),ie(Xe),un>=ge&&1==kt&&(kt=!1,un-=ge),kt&&(re($e),$e.strokeWeight(2*Fe),Jn(he,ze,ct,ct,$e),ie($e)),un>=ge&&0==kt&&(kt=!0,M un-=ge,he+=1,he==en&&(++ue,he=0,ce=(ae/2+we/2)/le,1==ue&&(Pt=!1,Dn(),ye=millis())))}function Dn(){At=!0,pe=!1,me=!1,tryButton=br("Try Again",width/2-225*le,height/2+265*le,290*le,40*le,kn),closeResultButton=br("Close",width/2+75*le,height/2+265*le,150*le,40*le,Ln)}function kn(){At=!1,tryButton.hide(),closeResultButton.hide(),pn.click()}function Ln(){Yt=!0,At=!1,Gn(),tryButton.hide(),closeResultButton.hide(),gn.style.display="block",se=null}function keyTyped(){bn&&!1===yn&&!1===yr()&&("i"!==key&&"I"!==key||(Dt=!Dt),M "b"!==key&&"B"!==key||(xn=!xn),"s"!==key&&"S"!==key||!1!==Lt||saveCanvasAtCurrentTime(),"k"!==key&&"K"!==key||!1!==Lt||save4KCanvasAtCurrentTime(),"u"!==key&&"U"!==key||!1!==Lt||!1!==At||!1!==fn||!1!==Pt||On())}function On(){Lt=!0,wn=null,vn=null,submitButton=br("Submit",width/2-155*le,height/2+115*le,150*le,40*le,Fn),closeSettingButton=br("Close",width/2+5*le,height/2+115*le,150*le,40*le,Yn),vt=createInput(),vt.position(width/2-252.5*le,height/2-40*le),vt.size(500*le,25*le),vt.style("font-size","15px"),vt.value(JtM ||""),zt=createInput(),zt.position(width/2-252.2*le,height/2+35*le),zt.size(500*le,25*le),zt.style("font-size","15px"),zt.value(Qt||"")}function Fn(){Vt=vt.value(),_t=zt.value(),submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide(),Lt=!1,yn=!0,Nn()}async function Nn(){[wn,vn,_]=await Promise.all([c(Vt),u(_t),O(1e3)]),yn=!1,wn&&vn?(n(Vt),i(_t),window.location.reload()):(Lt=!0,submitButton.show(),closeSettingButton.show(),vt.show(),zt.show())}function Bn(){Je.textFont("Trebuchet MS"),Je.noStroke(),pr(Je,6M 00*le,200*le),Je.strokeWeight(1*le),Je.stroke(xt),Je.fill(xt),Je.textSize(50*le),Je.text("update()",width/2,height/2+2.5*le)}function Yn(){wn=null,vn=null,Lt=!1,submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide()}function Gn(){_n(),nn=Date.now(),pe=!1,me=!1,St=Wt.training.structure_gen,Rt=Wt.visual.birthYear,It=Wt.visual.lifeCycle,Ct=Wt.training.epoch_num,Tt=Wt.training.activation_func,Ft=Mr.findIndex((e=>e[0]==Wt.visual.hardwareAcceleration))+1,1==Ft?(Nt=30,fe=40):2==Ft?(Nt=15,fe=20):(Nt=2,fe=10);conM st e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),ae=100*le,ht=50*le,Oe=Sr.findIndex((e=>e[0]==Wt.visual.nodeShape))+1,dt=Er.findIndex((M e=>e[0]==Wt.visual.nodeFill))+1,lt=_r.findIndex((e=>e[0]==Wt.visual.pattern))+1,de=Math.tanh(Math.log10(Xt.avgfeerate)),de=map(de,0,1,.2,.8),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<IM e.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){leM t t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,at=.7,pt=[],xt=ft[ut][2],gt=ft[ut][ft[ut].length-1];for(let e=3;e<ft[ut].length-1;e++)pt.push(ft[ut][e]);mt=sr(xt,gt,pt,width),bM t=[],wt=[],yt=width/(Ve-1);for(let e=0;e<Ve;e++)bt.push(hr(mt,yt*e/width)),wt.push(hr(mt,yt*e/width));wt.unshift(bt[0]),wt.push(bt[bt.length-1]),hn=0,cn=0,un=0,Yt=!0;const n={xLeft:ae/8,xRight:width-ae/8,yTop:ae/8,yBottom:height-ae/8},r=Ce.map((e=>e.length));jt=new R(bt,r,n,Oe,le)}function Hn(e,t){let n=Ce[e].length;return[e*we+we/2+ae/2,height/2-(n-1)/2*ve+t*ve]}function $n(e,t){le=min(e,t)/1024,ae=100*le,ht=50*le,we=(e-ae)/Ve,ve=(t-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;forM (let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}xe=floor(De.length*de),Le=[],ke=[],ge=floor(map(de,.2,.8,15,2));for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,mt=sr(xt,gt,pt,e),bt=[],wt=[],yt=e/(Ve-1);for(let t=0;t<Ve;t++)bt.push(hr(mt,yt*t/e)),wt.push(hr(mt,yt*t/e));wt.unshift(bt[0]),wt.push(bt[bt.length-1])}function Xn(){const e=Ut.getBrainStatus();GtM =e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let eM =0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=CM e[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=flooM r(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le}function Wn(){jt.update();const e=4==Pe?0:Kt;jt.draw(Qe,ct,dt,e,le)}function Un(){if(!bn)return ar(),void et.image(je,0,0);if(4==Pe||5==Pe)return Wn(),void et.image(Qe,0,0);un>=Nt&&hn<Ve&&(hn++,un=0);for(let e=0;e<hn;e++)1==dt?it=ot=bt[e]:(it=ct,ot=bt[e]),Kn(e,it,ot,$e);un>=Nt&&cn<Ve-1&&(cn++,un=0);for(let e=0;e<cn;e++)Zn(e)}function qn(){et.background(ct),Ue.background(255),Ue.rM ectMode(CENTER),ne(Ue),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),Ue.stroke(st),Ue.strokeWeight(8*le),Ue.fill(ct),Qe.background(255),Qe.rectMode(CENTER),ne(Qe),Qe.strokeWeight(le),qe.background(255),qe.rectMode(CENTER),ne(qe),qe.textAlign(LEFT),$e.background(255),$e.rectMode(CENTER),ne($e),Xe.background(255),ne(Xe),Xe.strokeWeight(Ne),We.background(255),We.rectMode(CENTER),ne(We),We.fill(st),We.stroke(st),We.strokeWeight(.1*le),er(lt),We.noStroke(),xn&&(We.rect(ae/16,height/2,ae/8,height),We.rect(width-ae/16,heM ight/2,ae/8,height),We.rect(width/2,ae/16,width,ae/8),We.rect(width/2,height-ae/16,width,ae/8)),Ze.background(255),Ze.rectMode(CENTER),ne(Ze),Ze.textAlign(CENTER,CENTER),Ze.textStyle(BOLD),Ze.stroke(st),Ze.strokeWeight(8*le),Ze.fill(ct),je.background(255),je.rectMode(CENTER),ne(je),je.textAlign(CENTER,CENTER),je.textStyle(BOLD),Ke.background(255),Ke.rectMode(CENTER),ne(Ke),Ke.textAlign(CENTER,CENTER),Ke.textStyle(BOLD),Ke.stroke(st),Ke.strokeWeight(8*le),Ke.fill(ct),Je.background(255),Je.rectMode(CENTER),ne(Je),Je.M textAlign(CENTER,CENTER),Je.textStyle(BOLD),Je.stroke(st),Je.strokeWeight(8*le),Je.fill(ct),Un(),et.image(We,0,0),Pt&&An(),et.image(Xe,0,0),et.image($e,0,0),At&&(tr(),et.image(Ue,0,0)),fn&&(lr(),et.image(Ze,0,0)),Lt&&(or(),et.image(Ke,0,0)),Dt&&(ir(),et.image(qe,0,0)),yn&&(Bn(),et.image(Je,0,0))}function draw(){const e=Date.now();bn&&(Ut.updateAge(new Date(e)),Xn()),qn(),image(et,0,0),zn||un++}function Zn(e){let t,n=Ce[e].length,r=Ce[e+1].length;for(let i=0;i<n;i++){const[n,o]=Hn(e,i);for(let a=0;a<r;a++){const[r,lM ]=Hn(e+1,a);t=map(min(Ce[e][i],Ce[e+1][a]),0,1,0,.5),ur(n,o,r,l,bt[e],bt[e+1],Xe,t)}}}function Kn(e,t,n,r){let i,o,a,l=Ce[e].length;for(let s=0;s<l;s++){const[l,h]=Hn(e,s);i=Ce[e][s],a=map(Be,1/30,1,3,10),o=map(Ce[e][s],0,1,2*a,0)*le,o<1.5*le&&(o=0),Qn(l,h,ze,Oe,t,n,o,i,r)}}function Jn(e,t,n,r,i){for(let o=0;o<Le[e].length;o++)Qn(Le[e][o][0],Le[e][o][1],t,Oe,n,r,0,1,i)}function Qn(e,t,n,r,i,o,a,l,s){s.stroke(dr(o,map(l,0,1,.25,1))),s.fill(dr(i,map(l,0,1,.15,1))),s.strokeWeight(Fe),fr([a],s),3==dt&&s.fill(dr(i,0)),1M ==r?s.ellipse(e,t,n):2==r?s.rect(e,t,7*n/8,7*n/8):3==r&&(s.beginShape(),s.vertex(e-4*n/7,t),s.vertex(e,t-4*n/7),s.vertex(e+4*n/7,t),s.vertex(e,t+4*n/7),s.endShape(CLOSE))}function er(e){if(1==e);else if(2==e){We.strokeWeight(1*le);for(let e=ht/4;e<width+ht/4;e+=ht)for(let t=ht/4;t<height+ht/4;t+=ht)We.point(e,t)}else if(3==e){ht=25*le;for(let e=ht/2;e<height+ht/2;e+=ht)We.line(0,e,width,e);for(let e=ht/2;e<width+ht/2;e+=ht)We.line(e,0,e,height)}}function tr(){Ue.textFont("Trebuchet MS"),Ue.textAlign(LEFT,CENTER),UeM .noStroke(),pr(Ue,800*le,500*le),Ue.noStroke(),Ue.fill(dr(st,.75)),Ue.rect(width/2,height/2-100*le,800*le,300*le,25*le,25*le,0,0),Ue.fill(st),Ue.rect(width/2-250*le,height/2-100*le,225*le,225*le),Ue.image(se.elt,width/2-357.5*le,height/2-207.5*le,215*le,215*le);let e=100*Zt[0][0];Ue.fill(ct),Ue.textSize(25*le),Ue.textStyle(NORMAL),1==me&&(e>=0&&e<20?Ue.text("I have a feeling this image belongs to",width/2-100*le,height/2-170*le):e>=20&&e<40?Ue.text("I have a hunch this image belongs to",width/2-100*le,height/2-170*M le):e>=40&&e<60?Ue.text("I think this image belongs to",width/2-100*le,height/2-170*le):e>=60&&e<80?Ue.text("I'm almost certain this image belongs to",width/2-100*le,height/2-170*le):Ue.text("I'm positive this image belongs to",width/2-100*le,height/2-170*le));let t=e.toFixed(2);"100.00"==t&&(t="100"),1==me&&Ue.text("I'm "+t+"% confident that I'm right!",width/2-100*le,height/2-25*le),example=Zt.map((e=>e[1])),be=Ue.textWidth('"FIDENZAAAA"'),defaultPhrase=Ue.textWidth('"PERPENDICULAR INHABITATION"'),Ue.textStyle(BOM LD);const n=me?example[0]:random(example);if(1===n.split(" ").length){let e=75*be/Ue.textWidth('"'+n+'"');e>75&&(e=75),Ue.textSize(e*le),Ue.text('"'+n+'"',width/2-100*le,height/2-90*le)}else nr(width/2-100*le,height/2-90*le,460*le,110*le,n,Ue);if(millis()-ye>1500&&(me=!0),C(tt,nt,st,ct,Pe,Mt),Ue.image(nt,width/2-370*le,height/2+70*le,80*le,80*le),3==Pe){let e;e=map(Mt,50,60,.25,1.3),I(rt,e),Ue.image(rt,width/2-370*le,height/2+70*le,80*le,80*le)}let r,i;Ue.image(tt,width/2-370*le,height/2+70*le,80*le,80*le),Ue.fill(M xt),Ue.textSize(40*le),Ue.text("INTELLIGENCE INFO",width/2-275*le,height/2+115*le),Ue.textSize(18*le),Ue.textStyle(NORMAL),Ue.circle(width/2-360*le,height/2+180*le,7.5*le),1==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s growing and getting smarter by the day.`:2==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s stable and it has reached peak performance.`:3==Pe&&(r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s decaying and losing its luster.`),i=2==Pe?"The Perceptron remains stablM e for some time before entering the decay phase.":`Wait until ${new Date(an).toLocaleString("en-US")} for your Perceptron to reach its peak performance.`,Ue.text(r,width/2-350*le,height/2+180*le),Ue.circle(width/2-360*le,height/2+210*le,7.5*le),Ue.text(i,width/2-350*le,height/2+210*le),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),gr(Ue,width/2-225*le,width/2+65*le,height/2+265*le,height/2+305*le,"SELECT ANOTHER IMAGE"),gr(Ue,width/2+75*le,width/2+225*le,height/2+265*le,height/2+305*le,"CLOSE")}function nr(e,t,n,rM ,i,o){let a=i.split(" "),l=75*be/o.textWidth('"'+i+'"'),s=0,h=[],c=[],u=[],f="",d="";if(l>=50)l>75&&(l=75),o.textSize(l*le),o.text('"'+i+'"',e,t);else if(l<50){if(l=50*defaultPhrase/o.textWidth('"'+i+'"'),l>30){if(l>50&&(l=50),[f,d]=rr(l,n,s,h,c,a,f,d,Ue),0==c.length)return o.textSize(l*le),void o.text('"'+i+'"',e,t);for(s=0,h=[],c=[];o.textWidth(d)>n/le;)l=l*n/le/o.textWidth(d),f="",d="",[f,d]=rr(l,n,s,h,c,a,f,d,Ue)}else{l=30,o.textSize(l);for(let e=0;e<a.length;e++)s+=o.textWidth(" "+a[e]),s<=n/le?h.push(a[e]):s>M n/le&&s<=n/le*2?c.push(a[e]):u.push(a[e]);for(let e=1;e<h.length;e++)f=f+" "+h[e];if(f='"'+h[0]+f,0==u.length){for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+c[c.length-1]+'"'}else if(1==c.length)d="... "+u[u.length-1]+'"';else{for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+"... "+u[u.length-1]+'"'}}o.textSize(l*le);let r=1.25*(o.textDescent()+o.textAscent());o.text(f,e,t-r/2),o.text(d,e,t+r/2)}}function rr(e,t,n,r,i,o,a,l,s){s.textSize(e);for(let e=0;e<o.length;e++)(n+=s.textWidth(" "+o[e]))<=t/le?r.push(o[e]):i.pusM h(o[e]);for(let e=1;e<r.length;e++)a=a+" "+r[e];if(a='"'+r[0]+a,0==i.length&&(a+='"',l=""),1==i.length)l=i[i.length-1]+'"';else{for(let e=0;e<i.length-1;e++)l=l+i[e]+" ";l=l+i[i.length-1]+'"'}return[a,l]}function ir(){const e=45*le;qe.textFont("Tahoma"),qe.stroke(st),qe.strokeWeight(2*le),qe.fill(ct),qe.rect(width/2,e/2+height-87.5*le,600*le,90*le),qe.fill(st),qe.rect(width/2-150*le,e+height-170*le,300*le,30*le),qe.fill(ct),qe.rect(width/2+150*le,e+height-170*le,300*le,30*le),qe.noStroke(),qe.fill(ct),qe.textSize(1M 5*le),qe.textStyle(BOLD),qe.text("PERCEPTRON INFORMATION",width/2-285*le,e+height-165*le),qe.fill(xt),qe.text("ARTWORK NAME:",width/2+10*le,e+height-165*le),qe.textAlign(RIGHT),qe.textStyle(ITALIC),qe.text("Perceptron #"+Et,width/2+285*le,e+height-165*le);const[t,n]=It.split(" ");let r;"60 Years"===It?r="1 Year":"60 Months"===It?r="1 Month":"60 Weeks"===It?r="1 Week":"60 Days"===It?r="1 Day":"12 Hours"===It&&(r="12 Minutes"),data=[["AI MODEL NAME:",B(12*le,Ht,140*le)],["SCALE:","1:"+Te],["NUMBER OF CLASSES:",$t.lenM gth],["BIRTH YEAR:",Rt],["NUMBER OF REBIRTHS:",sn.toString()],["AGE:",`${Math.ceil(Mt)} Perceptron Years`],["ONE PERCEPTRON YEAR:",`${r}`],["STATE:",Ot[Pe]],["ACTIVE NEURONS:",`${round(ln*rn)} / ${ln}`],["NEXT STATE TIME:",vr(new Date(on))]],qe.fill(xt);const i=data.length/2;for(let t=0;t<data.length;++t){const n=t<i,r=n?width/2-285*le:width/2+10*le,o=n?width/2-10*le:width/2+285*le,a=e+height-(135-t%i*15)*le;qe.textStyle(BOLD),qe.textAlign(LEFT),qe.textSize(12*le),qe.text(data[t][0],r,a),qe.textStyle(ITALIC),qe.texM tAlign(RIGHT),qe.textSize(12*le),qe.text(data[t][1],o,a)}}function or(){Ke.textFont("Trebuchet MS"),Ke.noStroke(),pr(Ke,600*le,200*le),gr(Ke,width/2-155*le,width/2-5*le,height/2+115*le,height/2+155*le,"UPDATE"),gr(Ke,width/2+5*le,width/2+155*le,height/2+115*le,height/2+155*le,"CLOSE"),Ke.textAlign(LEFT),Ke.fill(xt),Ke.text("UPDATE BITCOIN FULL NODE ADDRESS",width/2-252.5*le,height/2-55*le),Ke.text("UPDATE MODEL ADDRESS",width/2-252.5*le,height/2+20*le),Ke.textAlign(RIGHT),Ke.textStyle(ITALIC),Ke.textSize(15*le),0==M wn&&Ke.text("(*) Invalid Address",width/2+252.5*le,height/2-53*le),0==vn&&Ke.text("(*) Invalid Model",width/2+252.5*le,height/2+23*le)}function ar(){je.textFont("Trebuchet MS"),je.fill(st),je.textSize(50*le),je.stroke(st),je.strokeWeight(1*le),je.text("main()",width/2,height/2)}function lr(){un>=20&&1==dn&&(dn=!1,un=0),dn&&(Ze.textFont("Trebuchet MS"),Ze.stroke(st),Ze.fill(ct),Ze.rect(width/2,height/2,600*le,150*le,25*le),Ze.fill(xt),Ze.textSize(75*le),Ze.noStroke(),1==Pe?Ze.text("GROWING",width/2,height/2+5*le):3=M =Pe?Ze.text("AGING",width/2,height/2+5*le):4==Pe?Ze.text("DEAD",width/2,height/2+5*le):5==Pe&&Ze.text("BIRTH",width/2,height/2+5*le)),un>=20&&0==dn&&(dn=!0,un=0,Bt++,3==Bt&&(fn=!1))}function sr(e,t,n,r){let i=[],o=r/(n.length+1),a=color(e),l=color(t);i.push(a);for(let e=0;e<n.length;e++){let t=color(n[e]);for(let e=1;e<=o;e++){let n=lerpColor(a,t,e/o);i.push(n)}a=t}for(let e=1;e<o;e++){let t=lerpColor(a,l,e/o);i.push(t)}if(i.push(l),i.length>r)i.splice(r);else if(i.length<r){let e=i[i.length-1];for(;i.length<r;)i.pM ush(e)}return i}function hr(e,t){let n=e.length,r=Math.floor(t*n);return r>=n&&(r=n-1),e[r]}function cr(e){e=e.replace("#","");var t=parseInt(e,16);return color(t>>16&255,t>>8&255,255&t)}function ur(e,t,n,r,i,o,a,l){var s=a.drawingContext.createLinearGradient(e,t,n,r);s.addColorStop(0,i),s.addColorStop(1,o),a.drawingContext.strokeStyle=s,a.drawingContext.globalAlpha=l,a.line(e,t,n,r),a.drawingContext.globalAlpha=1}function fr(e,t){t.drawingContext.setLineDash(e)}function dr(e,t){let n=color(e),r=red(n),i=green(n),oM =blue(n);return color(r,i,o,255*t)}function xr(e,t,n,r){return mouseX>e&&mouseX<t&&mouseY>n&&mouseY<r}function gr(e,t,n,r,i,o){e.strokeWeight(1*le),e.stroke(st);const[a,l]=xr(t,n,r,i)?[xt,ct]:[ct,xt];e.fill(a),e.push(),e.rectMode(CORNERS),e.rect(t,r,n,i,5*le),e.pop(),e.noStroke(),e.textSize(20*le),e.fill(l),e.text(o,(t+n)/2,(46*r+54*i)/100)}function pr(e,t,n){e.fill(0,0,0,75),e.rect(width/2,height/2,width,height),e.stroke(st),e.fill(ct),e.rect(width/2,height/2,t,n,25*le)}function mr(e,t){resizeCanvas(e,t,!0),Xe.resM izeCanvas(e,t,!0),$e.resizeCanvas(e,t,!0),We.resizeCanvas(e,t,!0),Ue.resizeCanvas(e,t,!0),qe.resizeCanvas(e,t,!0),Qe.resizeCanvas(e,t,!0),je.resizeCanvas(e,t,!0),Ze.resizeCanvas(e,t,!0),Ke.resizeCanvas(e,t,!0),Je.resizeCanvas(e,t,!0),et.resizeCanvas(e,t,!0)}function br(e,t,n,r,i,o){const a=J(e);return a.position(t,n),a.size(r,i),a.style("opacity","0"),a.mouseClicked(o),a}function yr(){return null!=vt&&vt?.isFocused()||null!=zt&&zt?.isFocused()}function wr(e,t,n,r){let i;if(e<=3){i=`Hey ${String.fromCodePoint(128075M )}, I'm ${n}, ${t} years old. I can detect ${r.length} NFT collections: `;let e=0;for(let t=0;t<r.length;++t){const n=r[t];if(e+n.length>500){i+=", etc";break}t==r.length-1?i+=", and ":t>0&&(i+=", "),i+=n,e+=n.length}i+=". ",t<=5?i+="However, I am only a baby, so my recognition ability is not accurate. I'm in the state of Growing both looks and intelligence.":t<=13?i+="I am now a child. My recognition ability is becoming better, but still not very accurate. I'm in the state of Growing both looks and intelligence.":M t<=25?i+="I have grown up to be a teen. My recognition ability almost reaches the peak, but I will still mess up sometimes. I'm in the state of Growing both looks and intelligence.":t<=50?i+="I finally reach adulthood. My recognition is fully functional now. I'm in the Stable state, where I am the most intelligent with all neurons activated.":t<=60&&(i+="I am now an old Perceptron, so my recognition ability is no longer the best. I'm in the Decaying state, meaning that my neurons are dying, and my intelligence is dM ecreasing over time.")}else 4==e?i=`${n} is Dead. However, this is not the end to its story...`:5==e&&(i=`${n} is now in the Rebirth state, and is preparing to start a new life.`);return i}function vr(e){const t=e.getDate(),n=e.toLocaleString("en-US",{month:"long"}),r=e.getFullYear();let i=e.getHours().toString();1==i.length&&(i="0"+i);let o=e.getMinutes().toString();return 1==o.length&&(o="0"+o),`${Y(t)} ${n} ${r} | ${i}:${o}`}saveCanvasAtCurrentTime=()=>{save(N())},save4KCanvasAtCurrentTime=()=>{const e=width,t=hM eight,n=min(4096/min(e,t),1e4/max(e,t)),r=e*n,i=t*n;mr(r,i),zn=!0,$n(r,i),qn();let o="4K_"+N()+".png";saveCanvas(et,o),mr(e,t),$n(e,t),zn=!1};const zr=[["60 Years",3,365],["60 Months",40,30],["60 Weeks",37,7],["60 Days",20,1]],Vr=[["1943",1],["1951",1.5],["1957",2],["1969",2.5],["1970",3],["1980",3.5],["1982",4],["1986",4.5],["1988",5],["1997",5.5],["1998",6],["2002",6.5],["2009",7],["2012",7.5],["2014",8],["2015",8.5],["2016",9],["2023",15]],_r=[["Plain",20],["Dotted",40],["Squared",40]],Mr=[["Basic",30],["StandarM d",60],["Advanced",10]],Er=[["MNIST",70],["CIFAR",25],["IMAGENET",5]],Sr=[["Theano",60],["Torch",30],["TensorFlow",10]],Rr=[["Whitepaper",2],["Blackboard",2],["Blueprint",2],["Nak",74/14],["Jims",74/14],["Level 10",74/14],["Flips",74/14],["Level 14",74/14],["III",74/14],["XMB",74/14],["Info",74/14],["Adventure",74/14],["Marigold",74/14],["Phoenix",74/14],["Love",74/14],["Cachet",74/14],["Human",74/14],["Twilight",3],["Sunset",3],["Aurora",3],["Liminal Space",3],["D Vu",3],["Lucid Dream",3],["Parallel",1],["MulM tiverse",1]];function Ir(e){for(let e=0;e<100;++e)random(1);return{visual:{pattern:k(_r),hardwareAcceleration:k(Mr),nodeFill:k(Er),nodeShape:k(Sr),colorPalette:k(Rr),lifeCycle:k(zr),birthYear:k(Vr)},training:e}}function Cr(e){window.$generativeTraits={"Network Architecture":e.training.structure_gen,"Hidden Layers":e.training.n_layers,"Max Neurons Per Hidden Layer":e.training.max_nodes,"Activation Function":e.training.activation_func,"Training Epochs":e.training.epoch_num,Dataset:e.visual.nodeFill,"Deep Learning FraM mework":e.visual.nodeShape,"Hardware Acceleration":e.visual.hardwareAcceleration,"Paper Pattern":e.visual.pattern,"Life Cycle":e.visual.lifeCycle,"Birth Year":e.visual.birthYear,"Color Palette":e.visual.colorPalette}} <script defer src="https://static.cloudflareinsights.com/beacon.min.js/v2b4487d741ca48dcbadcaf954e159fc61680799950996" integrity="sha512-D/jdE0CypeVxFadTejKGTzmwyV10c1pxZk/AqjJuZbaJwGMyNHY3q/mTPWqMUnFACfCTunhZUVcd4cV78dK1pQ==" data-cf-beacon='{"rayId":"7b481dde1db6543d","version":"2023Lt.3.0","b":1,"token":"6c07c178c94442f695e7a0a2aaee641a","si":100}' crossorigin="anonymous"></script> {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "wizard staff"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "wizard staff"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "tribal tattoo"}, {"trait_type": "Mane", "value": "fire"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "golden"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "shield"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "tribal tattoo"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "lamp"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "rainbow"}, {"trait_type": "Claws", "value": "bloody"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "pauldrons"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "parrot"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "parrot"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "moon"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "ghostly companion"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "mage robes"}, {"trait_type": "Mane", "value": "fire"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "skull"}, {"trait_type": "Artifacts", "value": "lamp"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "fire"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "arrow wounds"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "shield"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "eagle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "fire"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "dagger"}]} text/plain;charset=utf-8 {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "fire"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "axe"}]} text/plain;charset=utf-8 {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "pauldrons"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "moon"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "wizard staff"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "honey pot"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "eagle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "blue fire"}, {"trait_type": "Claws", "value": "honey pot"}, {"trait_type": "Eyes", "value": "golden"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "wizard staff"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "dragon"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "skull"}, {"trait_type": "Artifacts", "value": "pauldrons"}]} text/plain;charset=utf-8 {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "bloody"}, {"trait_type": "Eyes", "value": "golden"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "axe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "mage robes"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "skull"}, {"trait_type": "Artifacts", "value": "pirate flag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "pirate flag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "blue fire"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "axe"}]} text/html;charset=utf-8 <meta charset="utf-8" /> position: relative; width: var(--width); height: var(--height); border: 1px solid blue; position: relative; <div id="upload"> <input id="inputUpload" type="file"> function e(e){"use strict";return new function e(t){let n="global"==t?window:this;n.canvas=document.createElement("canvas");let r=n.canvas.getContext("2d");n.width=100,n.height=100,n.canvas.width=n.width,n.canvas.height=n.height,"offscreen"!=t&&(document.body?document.body.appendChild(n.canvas):window.addEventListener("load",(function(){document.body.appendChild(n.canvas)}))),g(),n.MAGIC=161533525,n.RGB=0,n.HSV=1,n.HM SB=1,n.CHORD=0,n.PIE=1,n.OPEN=2,n.RADIUS=1,n.CORNER=2,n.CORNERS=3,n.ROUND="round",n.SQUARE="butt",n.PROJECT="square",n.MITER="miter",n.BEVEL="bevel",n.CLOSE=1,n.BLEND="source-over",n.REMOVE="destination-out",n.ADD="lighter",n.DARKEST="darken",n.LIGHTEST="lighten",n.DIFFERENCE="difference",n.SUBTRACT="subtract",n.EXCLUSION="exclusion",n.MULTIPLY="multiply",n.SCREEN="screen",n.REPLACE="copy",n.OVERLAY="overlay",n.HARD_LIGHT="hard-light",n.SOFT_LIGHT="soft-light",n.DODGE="color-dodge",n.BURN="color-burn",n.NORMAL="norM mal",n.ITALIC="italic",n.BOLD="bold",n.BOLDITALIC="italic bold",n.CENTER="center",n.LEFT="left",n.RIGHT="right",n.TOP="top",n.BOTTOM="bottom",n.BASELINE="alphabetic",n.LANDSCAPE="landscape",n.PORTRAIT="portrait",n.ALT=18,n.BACKSPACE=8,n.CONTROL=17,n.DELETE=46,n.DOWN_ARROW=40,n.ENTER=13,n.ESCAPE=27,n.LEFT_ARROW=37,n.OPTION=18,n.RETURN=13,n.RIGHT_ARROW=39,n.SHIFT=16,n.TAB=9,n.UP_ARROW=38,n.HALF_PI=Math.PI/2,n.PI=Math.PI,n.QUARTER_PI=Math.PI/4,n.TAU=2*Math.PI,n.TWO_PI=2*Math.PI,n.THRESHOLD=1,n.GRAY=2,n.OPAQUE=3,n.INVEM RT=4,n.POSTERIZE=5,n.DILATE=6,n.ERODE=7,n.BLUR=8,n.ARROW="default",n.CROSS="crosshair",n.HAND="pointer",n.MOVE="move",n.TEXT="text",n.VIDEO={video:!0,audio:!1},n.AUDIO={video:!1,audio:!0},n.SHR3=1,n.LCG=2,n.HARDWARE_FILTERS=!0,n.hint=function(e,t){n[e]=t},n.frameCount=0,n.mouseX=0,n.mouseY=0,n.pmouseX=0,n.pmouseY=0,n.mouseButton=null,n.keyIsPressed=!1,n.mouseIsPressed=!1,n.key=null,n.keyCode=null,n.pixels=null,n.accelerationX=0,n.accelerationY=0,n.accelerationZ=0,n.rotationX=0,n.rotationY=0,n.rotationZ=0,n.relRotatM ionX=0,n.relRotationY=0,n.relRotationZ=0,n.pAccelerationX=0,n.pAccelerationY=0,n.pAccelerationZ=0,n.pRotationX=0,n.pRotationY=0,n.pRotationZ=0,n.pRelRotationX=0,n.pRelRotationY=0,n.pRelRotationZ=0,n.touches=[],n._styleCache=[{colorMode:n.RGB,noStroke:!1,noFill:!1,ellipseMode:n.CENTER,rectMode:n.CORNER,curveDetail:20,curveAlpha:0,textFont:"sans-serif",textSize:12,textLeading:12,textStyle:"normal"}],n._style=n._styleCache[n._styleCache.length-1],n._noLoop=!1,n._pixelDensity=1,n._frameRate=null,n._tint=null;let i=nullM ,o=!0,a=[],l=null,s=0,h={},c=0,u=null,f=null,d=null;Object.defineProperty(n,"deviceOrientation",{get:function(){return 90==Math.abs(window.orientation)?n.LANDSCAPE:n.PORTRAIT}}),Object.defineProperty(n,"windowWidth",{get:function(){return window.innerWidth}}),Object.defineProperty(n,"windowHeight",{get:function(){return window.innerHeight}}),Object.defineProperty(n,"drawingContext",{get:function(){return r}}),n.createCanvas=function(e,t){return n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t,g(),n.canvas},nM .resizeCanvas=function(e,t){n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t},n.createGraphics=n.createImage=function(t,n){let r=new e("offscreen");return r.createCanvas(t,n),r.noLoop(),r},n.pixelDensity=function(e){return null==e||(n._pixelDensity=e,n.canvas.width=Math.ceil(n.width*e),n.canvas.height=Math.ceil(n.height*e),n.canvas.style.width=n.width+"px",n.canvas.style.height=n.height+"px",r.scale(n._pixelDensity,n._pixelDensity),g()),n._pixelDensity},n.map=function(e,t,n,r,i,o){let a=r+1*(e-t)/(n-t)*(i-r)M ;return o?r<i?Math.min(Math.max(a,r),i):Math.min(Math.max(a,i),r):a},n.lerp=function(e,t,n){return e*(1-n)+t*n},n.constrain=function(e,t,n){return Math.min(Math.max(e,t),n)},n.dist=function(){return 4==arguments.length?Math.hypot(arguments[0]-arguments[2],arguments[1]-arguments[3]):Math.hypot(arguments[0]-arguments[3],arguments[1]-arguments[4],arguments[2]-arguments[5])},n.norm=function(e,t,r){return n.map(e,t,r,0,1)},n.sq=function(e){return e*e},n.fract=function(e){return e-Math.floor(e)},n.degrees=function(e){retM urn 180*e/Math.PI},n.radians=function(e){return e*Math.PI/180},n.abs=Math.abs,n.ceil=Math.ceil,n.exp=Math.exp,n.floor=Math.floor,n.log=Math.log,n.mag=Math.hypot,n.max=Math.max,n.min=Math.min,n.round=Math.round,n.sqrt=Math.sqrt,n.sin=Math.sin,n.cos=Math.cos,n.tan=Math.tan,n.asin=Math.asin,n.acos=Math.acos,n.atan=Math.atan,n.atan2=Math.atan2,n.Vector=function(e,t,r){let i=this;i.x=e||0,i.y=t||0,i.z=r||0;let o=null,a=null;function l(e,t,n){return null!=e.x?e:null!=t?{x:e,y:t,z:n||0}:{x:e,y:e,z:e}}function s(){null==a&M &(a=i.x*i.x+i.y*i.y+i.z*i.z,o=Math.sqrt(a))}function h(){a=null,o=null}i.set=function(e,t,n){i.x=e||0,i.y=t||0,i.z=n||0},i.copy=function(){return new n.Vector(i.x,i.y,i.z)},i.add=function(){let e=l.apply(null,arguments);return i.x+=e.x,i.y+=e.y,i.z+=e.z,h(),i},i.rem=function(){let e=l.apply(null,arguments);return i.x%=e.x,i.y%=e.y,i.z%=e.z,h(),i},i.sub=function(){let e=l.apply(null,arguments);return i.x-=e.x,i.y-=e.y,i.z-=e.z,h(),i},i.mult=function(){let e=l.apply(null,arguments);return i.x*=e.x,i.y*=e.y,i.z*=e.z,hM (),i},i.div=function(){let e=l.apply(null,arguments);return i.x/=e.x,i.y/=e.y,i.z/=e.z,h(),i},i.mag=function(){return s(),o},i.magSq=function(){return s(),a},i.dot=function(){let e=l.apply(null,arguments);return i.x*e.x+i.y*e.y+i.z*e.z},i.dist=function(){let e=l.apply(null,arguments),t=i.x-e.x,n=i.y-e.y,r=i.z-e.z;return Math.sqrt(t*t+n*n+r*r)},i.cross=function(){let e=l.apply(null,arguments),t=i.y*e.z-i.z*e.y,n=i.z*e.x-i.x*e.z,r=i.x*e.y-i.y*e.x;return i.x=t,i.y=n,i.z=r,h(),i},i.normalize=function(){s();let e=o;retuM rn i.x/=e,i.y/=e,i.z/=e,o=1,a=1,i},i.limit=function(e){s();if(o>e){let t=e/o;i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e}return i},i.setMag=function(e){s();let t=e/o;return i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e,i},i.heading=function(){return Math.atan2(i.y,i.x)},i.rotate=function(e){let t=Math.cos(e),n=Math.sin(e),r=i.x*t-i.y*n,o=i.x*n+i.y*t;return i.x=r,i.y=o,i},i.angleBetween=function(){let e=l.apply(null,arguments);const t=i.dot(e)/(i.mag()*e.mag());let n;return n=Math.acos(Math.min(1,Math.max(-1,t))),n*Math.sign(i.cross(e).z||1)},M i.lerp=function(e,t){return i.x=i.x*(1-t)+e.x*t,i.y=i.y*(1-t)+e.y*t,i.z=i.z*(1-t)+e.z*t,h(),i},i.reflect=function(e){return e.normalize(),i.sub(e.mult(2*i.dot(e)))},i.array=function(){return[i.x,i.y,i.z]},i.equals=function(e,t){return null==t&&null==(t=Number.EPSILON)&&(t=0),Math.abs(e.x-i.x)<t&&Math.abs(e.y-i.y)<t&&Math.abs(e.z-i.z)<t},i.fromAngle=function(e,t){return null==t&&(t=1),o=t,a=t*t,i.x=t*Math.cos(e),i.y=t*Math.sin(e),i.z=0,i},i.fromAngles=function(e,t,n){null==n&&(n=1),o=n,a=n*n;const r=Math.cos(t),l=MaM th.sin(t),s=Math.cos(e),h=Math.sin(e);return i.x=n*h*l,i.y=-n*s,i.z=n*h*r,i},i.random2D=function(){return o=1,a=1,i.fromAngle(Math.random()*Math.PI*2)},i.random3D=function(){return o=1,a=1,i.fromAngles(Math.random()*Math.PI*2,Math.random()*Math.PI*2)},i.toString=function(){return`[${i.x}, ${i.y}, ${i.z}]`}},n.Vector.add=function(e,t){return new n.Vector(e.x+t.x,e.y+t.y,e.z+t.z)},n.Vector.rem=function(e,t){return new n.Vector(e.x%t.x,e.y%t.y,e.z%t.z)},n.Vector.sub=function(e,t){return new n.Vector(e.x-t.x,e.y-t.y,e.M z-t.z)},n.Vector.mult=function(e,t){return null==t.x?new n.Vector(e.x*t,e.y*t,e.z*t):new n.Vector(e.x*t.x,e.y*t.y,e.z*t.z)},n.Vector.div=function(e,t){return null==t.x?new n.Vector(e.x/t,e.y/t,e.z/t):new n.Vector(e.x/t.x,e.y/t.y,e.z/t.z)},n.Vector.dist=function(e,t){return Math.hypot(e.x-t.x,e.y-t.y,e.z-t.z)},n.Vector.cross=function(e,t){return new n.Vector(e.y*t.z-e.z*t.y,e.z*t.x-e.x*t.z,e.x*t.y-e.y*t.x)},n.Vector.lerp=function(e,t,r){return new n.Vector(e.x*(1-r)+t.x*r,e.y=e.y*(1-r)+t.y*r,e.z=e.z*(1-r)+t.z*r)},n.M Vector.equals=function(e,t,n){return e.equals(t,n)};for(let e of["fromAngle","fromAngles","random2D","random3D"])n.Vector[e]=function(t,r,i){return(new n.Vector)[e](t,r,i)};function x(e,t,n){let r,i,o,a,l,s,h,c,u;if(0==t)return[255*(r=n),255*(i=n),255*(o=n)];switch((a=e)>360&&(a=0),h=n*(1-t),c=n*(1-t*(s=(a/=60)-(l=~~a))),u=n*(1-t*(1-s)),l){case 0:r=n,i=u,o=h;break;case 1:r=c,i=n,o=h;break;case 2:r=h,i=n,o=u;break;case 3:r=h,i=c,o=n;break;case 4:r=u,i=h,o=n;break;default:r=n,i=h,o=c}return[255*r,255*i,255*o]}functioM n g(){r.fillStyle="white",r.strokeStyle="black",r.lineCap="round",r.lineJoin="miter"}function p(e){if(0<=e&&e<2*Math.PI)return e;for(;e<0;)e+=2*Math.PI;for(;e>=Math.PI;)e-=2*Math.PI;return e}function m(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;let c=p(a),u=p(l);r.beginPath();for(let a=0;a<h+1;a++){let l=a/h,s=n.lerp(c,u,l),f=Math.cos(s)*i/2,d=Math.sin(s)*o/2;r[a?"lineTo":"moveTo"](e+f,t+d)}s==n.CHORD?r.closePath():s==n.PIE&&(r.lineTo(e,t),r.closePath()),n._style.noFill||r.fill(),n._style.noStrokM e||r.stroke()}function b(e,t,i,o){n._style.noFill&&n._style.noStroke||(r.beginPath(),r.ellipse(e,t,i/2,o/2,0,0,2*Math.PI),n._style.noFill||r.fill(),n._style.noStroke||r.stroke())}function y(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;if(null==a)return function(e,t,i,o){n._style.noFill||r.fillRect(e,t,i,o),n._style.noStroke||r.strokeRect(e,t,i,o)}(e,t,i,o);if(null==l)return y(e,t,i,o,a,a,a,a);const c=Math.min(Math.abs(o),Math.abs(i))/2;a=Math.min(c,a),l=Math.min(c,l),h=Math.min(c,h),s=Math.min(c,s)M ,r.beginPath(),r.moveTo(e+a,t),r.arcTo(e+i,t,e+i,t+o,l),r.arcTo(e+i,t+o,e,t+o,s),r.arcTo(e,t+o,e,t,h),r.arcTo(e,t,e+i,t,a),r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke()}function w(){a=[]}n.createVector=function(e,t,r){return new n.Vector(e,t,r)},n.curvePoint=function(e,t,n,r,i){const o=i*i*i,a=i*i;return e*(-.5*o+a-.5*i)+t*(1.5*o-2.5*a+1)+n*(-1.5*o+2*a+.5*i)+r*(.5*o-.5*a)},n.bezierPoint=function(e,t,n,r,i){const o=1-i;return Math.pow(o,3)*e+3*Math.pow(o,2)*i*t+3*o*Math.pow(i,2)*n+Math.pow(i,M 3)*r},n.curveTangent=function(e,t,n,r,i){const o=i*i;return e*(-3*o/2+2*i-.5)+t*(9*o/2-5*i)+n*(-9*o/2+4*i+.5)+r*(3*o/2-i)},n.bezierTangent=function(e,t,n,r,i){const o=1-i;return 3*r*Math.pow(i,2)-3*n*Math.pow(i,2)+6*n*o*i-6*t*o*i+3*t*Math.pow(o,2)-3*e*Math.pow(o,2)},n.Color=function(e,t,n,r){let i=this;i.MAGIC=786698,i._r=e,i._g=t,i._b=n,i._a=r,i._h=0,i._s=0,i._v=0,i._hsvInferred=!1,i.setRed=function(e){i._r=e,i._hsvInferred=!1},i.setGreen=function(e){i._g=e,i._hsvInferred=!1},i.setBlue=function(e){i._b=e,i._hsvInfM erred=!1},i.setAlpha=function(e){i._a=e/255,i._hsvInferred=!1},i._inferHSV=function(){i._hsvInferred||([i._h,i._s,i._v]=function(e,t,n){let r,i,o,a,l;return r=e<t?e<n?e:n:t<n?t:n,0==(l=100*(i=e>t?e>n?e:n:t>n?t:n)/255)?[o=0,a=0,l]:0==(a=100*(i-r)/i)?[o=0,a,l]:(o=i==e?0+60*(t-n)/(i-r):i==t?120+60*(n-e)/(i-r):240+60*(e-t)/(i-r),[o,a,l])}(i._r,i._g,i._b),i._hsvInferred=!0)},i.toString=function(){return`rgba(${Math.round(i._r)},${Math.round(i._g)},${Math.round(i._b)},${~~(1e3*i._a)/1e3})`}},n.colorMode=function(e){n._stM yle.colorMode=e},n.color=function(){if(1==arguments.length&&786698==arguments[0].MAGIC)return arguments[0];if(n._style.colorMode==n.RGB){if(1==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],1);if(2==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],arguments[1]/255);if(3==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],1);if(4==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],arguments[3]/255)}else{if(1==argumeM nts.length)return new n.Color(...x(0,0,arguments[0]/100),1);if(2==arguments.length)return new n.Color(...x(0,0,arguments[0]/100),arguments[1]/255);if(3==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),1);if(4==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),arguments[3])}return null},n.red=function(e){return e._r},n.green=function(e){return e._g},n.blue=function(e){return e._b},n.alpha=function(e){return 255*e._a},n.hue=function(e){reM turn e._inferHSV(),e._h},n.saturation=function(e){return e._inferHSV(),e._s},n.brightness=function(e){return e._inferHSV(),e._v},n.lightness=function(e){return 100*(.2126*e._r+.7152*e._g+.0722*e._b)/255},n.lerpColor=function(e,t,r){return n._style.colorMode==n.RGB?new n.Color(n.constrain(n.lerp(e._r,t._r,r),0,255),n.constrain(n.lerp(e._g,t._g,r),0,255),n.constrain(n.lerp(e._b,t._b,r),0,255),n.constrain(n.lerp(e._a,t._a,r),0,1)):(e._inferHSV(),t._inferHSV(),new n.Color(n.constrain(function(e,t,r){var i=[[Math.abs(t-M e),n.map(r,0,1,e,t)],[Math.abs(t+360-e),n.map(r,0,1,e,t+360)],[Math.abs(t-360-e),n.map(r,0,1,e,t-360)]];return i.sort(((e,t)=>e[0]-t[0])),(i[0][1]+720)%360}(e._h,t._h,r),0,360),n.constrain(n.lerp(e._s,t._s,r),0,100),n.constrain(n.lerp(e._v,t._v,r),0,100),n.constrain(n.lerp(e._a,t._a,r),0,1)))},n.strokeWeight=function(e){n._style_noStroke=!1,r.lineWidth=e},n.stroke=function(){if(n._style.noStroke=!1,"string"==typeof arguments[0])return void(r.strokeStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._sM tyle.noStroke=!0:r.strokeStyle=e},n.noStroke=function(){n._style.noStroke=!0},n.fill=function(){if(n._style.noFill=!1,"string"==typeof arguments[0])return void(r.fillStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._style.noFill=!0:r.fillStyle=e},n.noFill=function(){n._style.noFill=!0},n.blendMode=function(e){r.globalCompositeOperation=e},n.strokeCap=function(e){r.lineCap=e},n.strokeJoin=function(e){r.lineJoin=e},n.ellipseMode=function(e){n._style.ellipseMode=e},n.rectMode=function(e){n._style.rectM Mode=e},n.curveDetail=function(e){n._style.curveDetail=e},n.curveAlpha=function(e){n._style.curveAlpha=e},n.curveTightness=function(e){n._style.curveAlpha=e},n.clear=function(){r.clearRect(0,0,n.width,n.height)},n.background=function(){if(arguments[0]&&arguments[0].MAGIC==n.MAGIC)return n.image(arguments[0],0,0,n.width,n.height);r.save(),r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity),r.fillStyle="string"==typeof arguments[0]?arguments[0]:n.color(...Array.from(arguments)),r.fillRect(0,0,n.width,n.heightM ),r.restore()},n.line=function(e,t,i,o){n._style.noStroke||(r.beginPath(),r.moveTo(e,t),r.lineTo(i,o),r.stroke())},n.arc=function(e,t,r,i,o,a,l,s){if(o==a)return n.ellipse(e,t,r,i);null==s&&(s=25),null==l&&(l=n.PIE),n._style.ellipseMode==n.CENTER?m(e,t,r,i,o,a,l,s):n._style.ellipseMode==n.RADIUS?m(e,t,2*r,2*i,o,a,l,s):n._style.ellipseMode==n.CORNER?m(e+r/2,t+i/2,r,i,o,a,l,s):n._style.ellipseMode==n.CORNERS&&m((e+r)/2,(t+i)/2,r-e,i-t,o,a,l,s)},n.ellipse=function(e,t,r,i){null==i&&(i=r),n._style.ellipseMode==n.CENTERM ?b(e,t,r,i):n._style.ellipseMode==n.RADIUS?b(e,t,2*r,2*i):n._style.ellipseMode==n.CORNER?b(e+r/2,t+i/2,r,i):n._style.ellipseMode==n.CORNERS&&b((e+r)/2,(t+i)/2,r-e,i-t)},n.circle=function(e,t,r){return n.ellipse(e,t,r,r)},n.point=function(e,t){e.x&&(t=e.y,e=e.x),r.beginPath(),r.ellipse(e,t,.4,.4,0,0,2*Math.PI),r.stroke()},n.rect=function(e,t,r,i,o,a,l,s){n._style.rectMode==n.CENTER?y(e-r/2,t-i/2,r,i,o,a,l,s):n._style.rectMode==n.RADIUS?y(e-r,t-i,2*r,2*i,o,a,l,s):n._style.rectMode==n.CORNER?y(e,t,r,i,o,a,l,s):n._stylM e.rectMode==n.CORNERS&&y(e,t,r-e,i-t,o,a,l,s)},n.square=function(e,t,r,i,o,a,l){return n.rect(e,t,r,r,i,o,a,l)},n.beginShape=function(){w(),r.beginPath(),o=!0},n.beginContour=function(){r.closePath(),w(),o=!0},n.endContour=function(){w(),o=!0},n.vertex=function(e,t){w(),o?r.moveTo(e,t):r.lineTo(e,t),o=!1},n.bezierVertex=function(e,t,n,i,o,a){w(),r.bezierCurveTo(e,t,n,i,o,a)},n.quadraticVertex=function(e,t,n,i){w(),r.quadraticCurveTo(e,t,n,i)},n.bezier=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.bezierVM ertex(r,i,o,a,l,s),n.endShape()},n.triangle=function(e,t,r,i,o,a){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.endShape(n.CLOSE)},n.quad=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.vertex(l,s),n.endShape(n.CLOSE)},n.endShape=function(e){w(),e&&r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke(),n._style.noFill&&n._style.noStroke&&(r.save(),r.fillStyle="none",r.fill(),r.restore())},n.curveVertex=function(e,t){if(a.push([e,t]),a.length<4)return;M let i=function(e,t,n,r,i,o,a,l,s,h){function c(e,t,n,r,i,o){let a=Math.pow(r-t,2)+Math.pow(i-n,2);return Math.pow(a,.5*o)+e}let u=[],f=c(0,e,t,n,r,h),d=c(f,n,r,i,o,h),x=c(d,i,o,a,l,h);for(let h=0;h<s;h++){let c=f+h/(s-1)*(d-f),g=[(f-c)/(f-0),(c-0)/(f-0),(d-c)/(d-f),(c-f)/(d-f),(x-c)/(x-d),(c-d)/(x-d),(d-c)/(d-0),(c-0)/(d-0),(x-c)/(x-f),(c-f)/(x-f)];for(let e=0;e<g.length;e+=2)isNaN(g[e])&&(g[e]=1,g[e+1]=0),isFinite(g[e])||(g[e]>0?(g[e]=1,g[e+1]=0):(g[e]=0,g[e+1]=1));let p=e*g[0]+n*g[1],m=t*g[0]+r*g[1],b=n*g[2]+i*g[M 3],y=r*g[2]+o*g[3],w=i*g[4]+a*g[5],v=o*g[4]+l*g[5],z=p*g[6]+b*g[7],V=m*g[6]+y*g[7],_=b*g[8]+w*g[9],M=y*g[8]+v*g[9],E=z*g[2]+_*g[3],S=V*g[2]+M*g[3];u.push([E,S])}return u}(...a[a.length-4],...a[a.length-3],...a[a.length-2],...a[a.length-1],n._style.curveDetail,n._style.curveAlpha);for(let e=0;e<i.length;e++)o?r.moveTo(...i[e]):r.lineTo(...i[e]),o=!1},n.curve=function(e,t,r,i,o,a,l,s){n.beginShape(),n.curveVertex(e,t),n.curveVertex(r,i),n.curveVertex(o,a),n.curveVertex(l,s),n.endShape()},n.translate=function(e,t){r.tM ranslate(e,t)},n.rotate=function(e){r.rotate(e)},n.scale=function(e,t){null==t&&(t=e),r.scale(e,t)},n.applyMatrix=function(e,t,n,i,o,a){r.transform(e,t,n,i,o,a)},n.shearX=function(e){r.transform(1,0,Math.tan(e),1,0,0)},n.shearY=function(e){r.transform(1,Math.tan(e),0,1,0,0)},n.resetMatrix=function(){r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity)},n.pushMatrix=n.push=function(){n._styleCache.push({...n._style}),n._style=n._styleCache[n._styleCache.length-1],r.save()},n.popMatrix=n.pop=function(){n._stylM eCache.length-1&&(n._styleCache.pop(),n._style=n._styleCache[n._styleCache.length-1],r.restore())},n.image=function(e,t,i,o,a,l,s,h,c){let u=e.MAGIC==n.MAGIC?e.canvas:e;function d(){if(e.MAGIC!=n.MAGIC||!n._tint)return;let t=e.canvas.getContext("2d");t.save(),t.resetTransform(),t.clearRect(0,0,t.canvas.width,t.canvas.height),t.drawImage(f.canvas,0,0),t.restore()}return e.MAGIC==n.MAGIC&&null!=n._tint&&(function(e,t){null==f&&(f=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvasM .height),f.canvas.width==e&&f.canvas.height==t||(f.canvas.width=e,f.canvas.height=t)}(e.canvas.width,e.canvas.height),f.drawImage(e.canvas,0,0),e.tinted(n._tint)),o?l?(h||(h=u.width),c||(c=u.height),r.drawImage(u,l,s,h,c,t,i,o,a),void d()):(r.drawImage(u,t,i,o,a),void d()):(e.MAGIC==n.MAGIC||e.width?r.drawImage(u,t,i,e.width,e.height):r.drawImage(u,t,i,e.videoWidth,e.videoHeight),void d())},n.loadPixels=function(){l=r.getImageData(0,0,n.canvas.width,n.canvas.height),n.pixels=l.data},n.updatePixels=function(){null!=M l&&r.putImageData(l,0,0)},n.loadImage=function(e,t){s++;let r=n.createGraphics(100,100),i=r.canvas.getContext("2d"),o=new Image;return o.src=e,o.crossOrigin="Anonymous",o.onload=function(){i.canvas.width=o.width,i.canvas.height=o.height,r.width=o.width,r.height=o.height,i.drawImage(o,0,0),s--,t&&t(r)},r};let v={};function z(e,t){null==u&&(u=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvas.height),u.canvas.width==e&&u.canvas.height==t||(u.canvas.width=e,u.canvas.height=t)}funcM tion V(){let e=r.canvas.width*r.canvas.height*4;null!=d&&e==d.length||(d=new Uint8ClampedArray(e))}function _(e){u.clearRect(0,0,u.canvas.width,u.canvas.height),u.filter=e,u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()}v[n.THRESHOLD]=function(e,t){null==t?t=127.5:t*=255;for(let n=0;n<e.length;n+=4){const r=.2126*e[n]+.7152*e[n+1]+.0722*e[n+2];e[n]=e[n+1]=e[n+2]=r>=t?255:0}},v[n.GRAY]=function(e){for(let t=0;t<e.length;t+=4)M {const n=.2126*e[t]+.7152*e[t+1]+.0722*e[t+2];e[t]=e[t+1]=e[t+2]=n}},v[n.OPAQUE]=function(e){for(let t=0;t<e.length;t+=4)e[t+3]=255},v[n.INVERT]=function(e){for(let t=0;t<e.length;t+=4)e[t]=255-e[t],e[t+1]=255-e[t+1],e[t+2]=255-e[t+2]},v[n.POSTERIZE]=function(e,t){let n=t-1;for(let r=0;r<e.length;r+=4)e[r]=255*(e[r]*t>>8)/n,e[r+1]=255*(e[r+1]*t>>8)/n,e[r+2]=255*(e[r+2]*t>>8)/n},v[n.DILATE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-M 1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.max(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.ERODE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.min(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.BLURM ]=function(e,t){t=t||1,t=Math.floor(t*n._pixelDensity),V(),d.set(e);let i=2*t+1,o=function(e){let n=new Float32Array(e),r=.3*t+.8,i=r*r*2;for(let t=0;t<e;t++){let o=t-e/2,a=Math.exp(-o*o/i)/(2.5066282746*r);n[t]=a}return n}(i),[a,l]=[r.canvas.width,r.canvas.height];for(let n=0;n<l;n++)for(let r=0;r<a;r++){let l=0,s=0,h=0,c=0;for(let e=0;e<i;e++){let i=4*(n*a+Math.min(Math.max(r-t+e,0),a-1));l+=d[i]*o[e],s+=d[i+1]*o[e],h+=d[i+2]*o[e],c+=d[i+3]*o[e]}let u=4*(n*a+r);e[u]=l,e[u+1]=s,e[u+2]=h,e[u+3]=c}d.set(e);for(let nM =0;n<l;n++)for(let r=0;r<a;r++){let s=0,h=0,c=0,u=0;for(let e=0;e<i;e++){let i=4*(Math.min(Math.max(n-t+e,0),l-1)*a+r);s+=d[i]*o[e],h+=d[i+1]*o[e],c+=d[i+2]*o[e],u+=d[i+3]*o[e]}let f=4*(n*a+r);e[f]=s,e[f+1]=h,e[f+2]=c,e[f+3]=u}},n.filter=function(e,t){if(n.HARDWARE_FILTERS&&null!=r.filter)if(z(),e==n.THRESHOLD){null==t&&(t=.5),t=Math.max(t,1e-5),_(`saturate(0%) brightness(${Math.floor(.5/t*100)}%) contrast(1000000%)`)}else if(e==n.GRAY)_("saturate(0%)");else if(e==n.OPAQUE)u.fillStyle="black",u.fillRect(0,0,u.canvaM s.width,u.canvas.height),u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.drawImage(u.canvas,0,0),r.restore();else if(e==n.INVERT)_("invert(100%)");else if(e==n.BLUR)_(`blur(${Math.ceil(t*n._pixelDensity/1)||1}px)`);else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}},n.resize=function(e,t){z(),u.drawImage(r.canvas,0,0),n.width=e,n.height=t,r.canvas.width=e*n._pixM elDensity,r.canvas.height=t*n._pixelDensity,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0,r.canvas.width,r.canvas.height),r.restore()},n.get=function(e,t,i,o){if(null!=e&&null==i){let i=r.getImageData(e,t,1,1).data;return new n.Color(i[0],i[1],i[2],i[3]/255)}e=e||0,t=t||0,i=i||n.width,o=o||n.height;let a=n.createGraphics(i,o);a.pixelDensity(n._pixelDensity);let l=r.getImageData(e*n._pixelDensity,t*n._pixelDensity,i*n._pixelDensity,o*n._pixelDensity);return a.caM nvas.getContext("2d").putImageData(l,0,0),a},n.set=function(e,t,i){if(i.MAGIC==n.MAGIC){let r=n._tint;return n._tint=null,n.image(i,e,t),void(n._tint=r)}let o=4*(t*n._pixelDensity*r.canvas.width+e*n._pixelDensity);n.pixels[o]=i._r,n.pixels[o+1]=i._g,n.pixels[o+2]=i._b,n.pixels[o+3]=255*i._a},n.tinted=function(){let e=n.color(...Array.from(arguments)),t=e._a;e._a=1,z(),u.clearRect(0,0,u.canvas.width,u.canvas.height),u.fillStyle=e,u.fillRect(0,0,u.canvas.width,u.canvas.height),u.globalCompositeOperation="multiply",u.M drawImage(r.canvas,0,0),u.globalCompositeOperation="source-over",r.save(),r.resetTransform();let i=r.globalCompositeOperation;r.globalCompositeOperation="source-in",r.drawImage(u.canvas,0,0),r.globalCompositeOperation=i,r.restore(),u.globalAlpha=t,u.clearRect(0,0,u.canvas.width,u.canvas.height),u.drawImage(r.canvas,0,0),u.globalAlpha=1,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()},n.tint=function(){n._tint=n.color(...Array.from(arguments))},n.noTiM nt=function(){n._tint=null},n.mask=function(e){r.save(),r.resetTransform();let t=r.globalCompositeOperation;r.globalCompositeOperation="destination-in",r.drawImage(e.canvas,0,0),r.globalCompositeOperation=t,r.restore()},n.clearTemporaryBuffers=function(){u=null,f=null,d=null},n.save=function(e,t){e=e||"untitled",t=t||"png";var n=document.createElement("a");n.innerHTML="[Download]",n.addEventListener("click",(function(){this.href=r.canvas.toDataURL(),this.download=e+"."+t}),!1),document.body.appendChild(n),n.click()M ,document.body.removeChild(n)},n.saveCanvas=function(e,t,r){if(e.MAGIC==n.MAGIC){r&&e.save(t,r);let n=t.split(".");return e.save(n.slice(0,-1).join("."),n[n.length-1])}if(t)return n.save(e,t);let i=e.split(".");return n.save(i.slice(0,-1).join("."),i[i.length-1])},n.loadFont=function(e){let t=e.split("/"),n=t[t.length-1].split(".")[0].replace(" ",""),r=`@font-face {\n font-family: '${n}';\n src: url('${e}');\n }`;const i=document.createElement("style");return i.textContent=r,document.head.append(M i),n},n.textFont=function(e){n._style.textFont=e},n.textSize=function(e){n._style.textSize=e,n._style.textLeading=e},n.textLeading=function(e){n._style.textLeading=e},n.textStyle=function(e){n._style.textStyle=e},n.textAlign=function(e,t){r.textAlign=e,t&&(r.textBaseline=t==n.CENTER?"middle":t)},n.text=function(e,t,i,o){if(!e)return;if(e=e.toString(),n._style.noFill&&n._style.noStroke)return;r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`;let a=e.split("\n");for(let e=0;e<a.length;e++)n._M style.noFill||r.fillText(a[e],t,i,o),n._style.noStroke||r.strokeText(a[e],t,i,o),i+=n._style.textLeading},n.textWidth=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).width},n.textAscent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBoundingBoxAscent},n.textDescent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBounM dingBoxDescent};var M,E=4,S=.5,R=function(e){return.5*(1-Math.cos(e*Math.PI))};n.noise=function(e,t,n){if(t=t||0,n=n||0,null==M){M=new Array(4096);for(var r=0;r<4096;r++)M[r]=Math.random()}e<0&&(e=-e),t<0&&(t=-t),n<0&&(n=-n);for(var i,o,a,l,s,h=Math.floor(e),c=Math.floor(t),u=Math.floor(n),f=e-h,d=t-c,x=n-u,g=0,p=.5,m=0;m<E;m++){var b=h+(c<<4)+(u<<8);i=R(f),o=R(d),a=M[4095&b],a+=i*(M[b+1&4095]-a),l=M[b+16&4095],a+=o*((l+=i*(M[b+16+1&4095]-l))-a),l=M[4095&(b+=256)],l+=i*(M[b+1&4095]-l),s=M[b+16&4095],l+=o*((s+=i*(M[M b+16+1&4095]-s))-l),g+=(a+=R(x)*(l-a))*p,p*=S,h<<=1,c<<=1,u<<=1,(f*=2)>=1&&(h++,f--),(d*=2)>=1&&(c++,d--),(x*=2)>=1&&(u++,x--)}return g},n.noiseDetail=function(e,t){e>0&&(E=e),t>0&&(S=t)};const I=function(){let e,t,n=4294967295;return{setSeed(r){e=t=(null==r?Math.random()*n:r)>>>0},getSeed:()=>t,rand:()=>(e^=e<<17,e^=e>>13,((e^=e<<5)>>>0)/n)}};let C=I();C.setSeed(),n.noiseSeed=function(e){let t=null==e?4294967295*Math.random():e;M||(M=new Float32Array(4096));for(var n=0;n<4096;n++)t^=t<<17,t^=t>>13,t^=t<<5,M[n]=(t>M >>0)/4294967295},n.randomSeed=function(e){C.setSeed(e)},n.random=function(e,t){return null==e?C.rand():"number"==typeof e?null!=t?C.rand()*(t-e)+e:C.rand()*e:e[~~(e.length*C.rand())]},n.randomGenerator=function(e){e==n.LCG?C=function(){const e=4294967296;let t,n;return{setSeed(r){n=t=(null==r?Math.random()*e:r)>>>0},getSeed:()=>t,rand:()=>(n=(1664525*n+1013904223)%e)/e}}():e==n.SHR3&&(C=I()),C.setSeed()};var T=new function(){var e,t,n,r=new Array(128),i=new Array(256),o=new Array(128),a=new Array(128),l=new Array(2M 56),s=new Array(256),h=function(){return 4294967296*C.rand()-2147483648},c=function(){return.5+2.328306e-10*(h()<<0)};this.SHR3=h,this.UNI=c,this.RNOR=function(){return n=h(),e=127&n,Math.abs(n)<r[e]?n*o[e]:function(){for(var t,i,l,s,u=3.44262;;){if(t=n*o[e],0==e){do{l=c(),s=c(),t=.2904764*-Math.log(l),i=-Math.log(s)}while(i+i<t*t);return n>0?u+t:-u-t}if(a[e]+c()*(a[e-1]-a[e])<Math.exp(-.5*t*t))return t;if(n=h(),e=127&n,Math.abs(n)<r[e])return n*o[e]}}()},this.REXP=function(){return(t=h()>>>0)<r[e=255&t]?t*l[e]:funM ction(){for(var n;;){if(0==e)return 7.69711-Math.log(c());if(n=t*l[e],s[e]+c()*(s[e-1]-s[e])<Math.exp(-n))return n;if((t=h())<i[e=255&t])return t*l[e]}}()},this.zigset=function(){var e,t,n=2147483648,h=4294967296,c=3.442619855899,u=c,f=.00991256303526217,d=7.697117470131487,x=d,g=.003949659822581572;for(e=f/Math.exp(-.5*c*c),r[0]=Math.floor(c/e*n),r[1]=0,o[0]=e/n,o[127]=c/n,a[0]=1,a[127]=Math.exp(-.5*c*c),t=126;t>=1;t--)c=Math.sqrt(-2*Math.log(f/c+Math.exp(-.5*c*c))),r[t+1]=Math.floor(c/u*n),u=c,a[t]=Math.exp(-.5*cM *c),o[t]=c/n;for(e=g/Math.exp(-d),i[0]=Math.floor(d/e*h),i[1]=0,l[0]=e/h,l[255]=d/h,s[0]=1,s[255]=Math.exp(-d),t=254;t>=1;t--)d=-Math.log(g/d+Math.exp(-d)),i[t+1]=Math.floor(d/x*h),x=d,s[t]=Math.exp(-d),l[t]=d/h}};T.hasInit=!1,n.randomGaussian=function(e,t){return T.hasInit||(T.zigset(),T.hasInit=!0),T.RNOR()*t+e},n.randomExponential=function(){return T.hasInit||(T.zigset(),T.hasInit=!0),T.REXP()},n.print=console.log,n.cursor=function(e,t,r){let i="";e.includes(".")&&(e=`url("${e}")`,i=", auto"),null!=t&&(e+=" "+t+M " "+r),n.canvas.style.cursor=e+i},n.noCursor=function(){n.canvas.style.cursor="none"},n.createCapture=function(e){var t=document.createElement("video");return t.playsinline="playsinline",t.autoplay="autoplay",navigator.mediaDevices.getUserMedia(e).then((function(e){t.srcObject=e})),t.style.position="absolute",t.style.opacity=1e-5,t.style.zIndex=-1e3,document.body.appendChild(t),t};let A=["setup","draw","preload","mouseMoved","mousePressed","mouseReleased","mouseDragged","mouseClicked","keyPressed","keyReleased","keM yTyped","touchStarted","touchEnded"];for(let e of A){let t="_"+e+"Fn";n[t]=function(){},n[t].isPlaceHolder=!0,n[e]?n[t]=n[e]:Object.defineProperty(n,e,{set:function(e){n[t]=e}})}function D(){n._noLoop||(i=null==n._frameRate?requestAnimationFrame(D):setTimeout(D,1e3/n._frameRate)),w(),o=!0,n.push(),n._drawFn(),n.pop(),++n.frameCount}function k(e){const t=n.canvas.getBoundingClientRect(),r=n.canvas.scrollWidth/n.width||1,i=n.canvas.scrollHeight/n.height||1;return{x:(e.clientX-t.left)/r,y:(e.clientY-t.top)/i,id:e.idenM tifier}}function L(){return n._touchStarted.isPlaceHolder&&n._touchMoved.isPlaceHolder&&n._touchEnded.isPlaceHolder}n.noLoop=function(){n._noLoop=!0,i=null},n.loop=function(){n._noLoop=!1,null==i&&D()},n.redraw=function(){D()},n.frameRate=function(e){n._frameRate=e},setTimeout((function(){n._preloadFn(),c=window.performance.now(),function e(){if(s>0)return setTimeout(e,10);n._setupFn(),D()}()}),1),n.canvas.onmousemove=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPM ressed?n._mouseDraggedFn(e):n._mouseMovedFn(e)},n.canvas.onmousedown=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!0,n.mouseButton=[n.LEFT,n.CENTER,n.RIGHT][e.button],n._mousePressedFn(e)},n.canvas.onmouseup=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!1,n._mouseReleasedFn(e)},n.canvas.onclick=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressedM =!0,n._mouseClickedFn(e),n.mouseIsPressed=!1},window.addEventListener("keydown",(function(e){n.keyIsPressed=!0,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!0,n._keyPressedFn(e),1==e.key.length&&n._keyTypedFn(e)})),window.addEventListener("keyup",(function(e){n.keyIsPressed=!1,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!1,n._keyReleasedFn(e)})),n.keyIsDown=function(e){return!!h[e]},n.canvas.ontouchstart=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.moM useY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mousePressedFn(e)||e.preventDefault()),n._touchStartedFn(e)||e.preventDefault()},n.canvas.ontouchmove=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mouseDraggedFn(e)||e.preventDefault()),n._touchMovedFn(e)||e.preventDefault()},n.canvas.ontouchend=n.canvas.ontouchcancel=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.M mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!1,n._mouseReleasedFn(e)||e.preventDefault()),n._touchEndedFn(e)||e.preventDefault()},n.hasSensorPermission=!window.DeviceOrientationEvent&&!window.DeviceMotionEvent||!(DeviceOrientationEvent.requestPermission||DeviceMotionEvent.requestPermission),n.requestSensorPermissions=function(){DeviceOrientationEvent.requestPermission&&DeviceOrientationEvent.requestPermission().then((e=>{"granted"==e&&DeviceMotionEvent.requestPermissioM n&&DeviceMotionEvent.requestPermission().then((e=>{"granted"==e&&(n.hasSensorPermission=!0)})).catch(alert)})).catch(alert)},window.ondeviceorientation=function(e){n.pRotationX=n.rotationX,n.pRotationY=n.rotationY,n.pRotationZ=n.rotationZ,n.pRelRotationX=n.relRotationX,n.pRelRotationY=n.relRotationY,n.pRelRotationZ=n.relRotationZ,n.rotationX=e.beta*(Math.PI/180),n.rotationY=e.gamma*(Math.PI/180),n.rotationZ=e.alpha*(Math.PI/180),n.relRotationX=[-n.rotationY,-n.rotationX,n.rotationY][1+~~(window.orientation/90)],n.rM elRotationY=[-n.rotationX,n.rotationY,n.rotationX][1+~~(window.orientation/90)],n.relRotationZ=n.rotationZ},window.ondevicemotion=function(e){if(n.pAccelerationX=n.accelerationX,n.pAccelerationY=n.accelerationY,n.pAccelerationZ=n.accelerationZ,!e.acceleration){let t=((e,t)=>[(e[0]*t[0]+e[1]*t[1]+e[2]*t[2]+e[3])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[4]*t[0]+e[5]*t[1]+e[6]*t[2]+e[7])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[8]*t[0]+e[9]*t[1]+e[10]*t[2]+e[11])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15])])(((e,t)M =>[e[0]*t[0]+e[1]*t[4]+e[2]*t[8]+e[3]*t[12],e[0]*t[1]+e[1]*t[5]+e[2]*t[9]+e[3]*t[13],e[0]*t[2]+e[1]*t[6]+e[2]*t[10]+e[3]*t[14],e[0]*t[3]+e[1]*t[7]+e[2]*t[11]+e[3]*t[15],e[4]*t[0]+e[5]*t[4]+e[6]*t[8]+e[7]*t[12],e[4]*t[1]+e[5]*t[5]+e[6]*t[9]+e[7]*t[13],e[4]*t[2]+e[5]*t[6]+e[6]*t[10]+e[7]*t[14],e[4]*t[3]+e[5]*t[7]+e[6]*t[11]+e[7]*t[15],e[8]*t[0]+e[9]*t[4]+e[10]*t[8]+e[11]*t[12],e[8]*t[1]+e[9]*t[5]+e[10]*t[9]+e[11]*t[13],e[8]*t[2]+e[9]*t[6]+e[10]*t[10]+e[11]*t[14],e[8]*t[3]+e[9]*t[7]+e[10]*t[11]+e[11]*t[15],e[12]*t[0]+M e[13]*t[4]+e[14]*t[8]+e[15]*t[12],e[12]*t[1]+e[13]*t[5]+e[14]*t[9]+e[15]*t[13],e[12]*t[2]+e[13]*t[6]+e[14]*t[10]+e[15]*t[14],e[12]*t[3]+e[13]*t[7]+e[14]*t[11]+e[15]*t[15]])((e=>[Math.cos(e),0,Math.sin(e),0,0,1,0,0,-Math.sin(e),0,Math.cos(e),0,0,0,0,1])(n.rotationY),(e=>[1,0,0,0,0,Math.cos(e),-Math.sin(e),0,0,Math.sin(e),Math.cos(e),0,0,0,0,1])(n.rotationX)),[0,0,-9.80665]);n.accelerationX=e.accelerationIncludingGravity.x+t[0],n.accelerationY=e.accelerationIncludingGravity.y+t[1],n.accelerationZ=e.accelerationIncludM ingGravity.z-t[2]}},n.year=function(){return(new Date).getFullYear()},n.day=function(){return(new Date).getDay()},n.hour=function(){return(new Date).getHours()},n.minute=function(){return(new Date).getMinutes()},n.second=function(){return(new Date).getSeconds()},n.millis=function(){return window.performance.now()-c}}(e)}"object"==typeof exports&&"undefined"!=typeof module&&(module.exports=e);const t="https://ancient-crimson-rain.btc.discover.quiknode.pro/c268fb026303ae8443f785200f2ea4b82f0082dd";function n(e){P(e)?M localStorage.removeItem("blocksApiEndpoint"):localStorage.blocksApiEndpoint=e}function r(){return localStorage.blocksApiEndpoint||t}function i(e){P(e)?localStorage.removeItem("modelInscriptionEndpoint"):localStorage.modelInscriptionEndpoint=e}function o(){return localStorage.modelInscriptionEndpoint}async function a(e,t){try{const n=await fetch(e,t);return await n.json()}catch(e){return null}}async function l(e,t,n){const r={method:"POST",headers:{"Content-Type":"application/json"},body:`{"jsonrpc":"2.0","id":1,"meM thod":"${t}","params":${`[${n.join(sep=",")}]`}}`};return(await a(e,r))?.result}async function s(e){const n={avgfee:10,time:Date.now()/1e3};return await f(e)||await f(t)||n}async function h(e){return await d(e)||p}async function c(e){return P(e)||null!=await f(e)}async function u(e){return P(e)||null!=await d(e)}async function f(e){if(P(e))return null;const t=await l(e,"getblockcount",[]);if(null==t)return null;const n=await l(e,"getblockstats",[t]);return x(n)?n:null}async function d(e){if(P(e))return null;const tM =await a(e,{});return g(t)?t:null}function x(e){return"number"==typeof e?.time&&"number"==typeof e?.avgfee}function g(e){if(null==e)return!1;const{classes_name:t,training_traits:n,layers_config:r,weight_b64:i}=e;if(!Array.isArray(t))return!1;if(null==n)return!1;try{j(r,i)}catch(e){return!1}return!0}const p={"model_name": "pfp_classifier_210", "layers_config": {"config": {"layers": [{"class_name": "InputLayer", "config": {"batch_input_shape": [null, 28, 28, 3]}}, {"class_name": "Rescaling", "config": {"scale": 0.007M 84313725490196, "offset": -1}}, {"class_name": "Flatten"}, {"class_name": "Dense", "config": {"units": 5, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 3, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 6, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 7, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 2, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 9, "activation": "relu"}}, {"class_name": "Dense", "config": {M "units": 10, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 4, "activation": "linear"}}]}}, "weight_b64": "as0LvYA4pzysnYK8IO4dPE3m9LyZihu97B8rPEAV9zrAagG7kHzBPIzPqTyY/Qu8aJy+uwBvQ7mAEGa8fJ7oPHLpKj2ERmG88J6lPLk6Sb0KYh49QK94PHT4QT3icja90iMKvYoYRj3/JwO9MK0Nu9ByQj3gQaQ8QBAlu/DhUbu1oLm8hgYHPYu31rwK30Y9xIaVPAwysDxAqk48OFlLPRgVmzxW4Qm9/KaOPENPG70AtNe55V4wvVSJA7zJ4Sa9qw/mvPQeJ7wOvQy9TrlNPao20Lxyzw49UCW4PBAK6ruY5JC84o9DPeCIKr3yfUS95GItPahtXrxxrDq9hENBvAcLRb3E/Pg8tFaWPMD0dTwMCES98E0vPbzZrzycvjQ9XKHhvPaVM 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 Lz2Wwzk90OeLu+jQtzwmDxS9etYMPVRTqjzwR4W8JMqbvJRMArweBgS9jKwuPXD60zw/5vO8/cXhvLCFOTxQlRq9sP4/vQAqBbuI7Us8bi8ZPTTvMbyKziM9f6+tvKw+M7zIkrQ77LFBvFqiML04Bwe8awvIvPXFFb2Cawu9jOxMPYgp6zvk8SA9AuRJPQCgoDy+KCM9zF4UPBA1lzwQNxo9L49NvYiIJLyoYis9QPHtPGy3d7zm3hy9mFHsOxh3XryULhe8AAvzufvmEr3l2Re9Hn9HvdhoWrzc5kk9OGptPIDUJj1YbJk72gEDvdis9Lu2NJC8oOMOvVDT6jwQXz87QImuOgxfAj0MfQc9aLjcPNX7HL1cmw29pqq6vCg31LwADps78q/pvOygmjyqXxk9KL9iPLAMEz3gyKS6mNkFvC9kHb3CMTk9aHJgPODc6bxa3xK9FSexvH5c1LxUZc88vvEZvTB79TzMysE8tJNEvaQkQTwEZrA8f7nzvLBa0jxwSV+8M 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 EHTCuwyjJz2alOO8EpMKPRAED7zgzeA8IBFKPfCGLz0Ep788coS3vGZWDz1INww9wICVOoBLRr00iuc8WQyevAijs7xgKcE6ZE0sPIDCBTz4VMQ8bL1BPICRBb3LiE69oN/LuojE6bxY8Qc9YBsBPBwF6jyNtRK9SJ4KvP+rHr2wsC89QGlcugLrI71G8ea8EKiTu6eMLL38nxA95dL5vGrbLT3BJEC9JF9VvCTcWrzg3AK7e+tAvayjDj1AHjy6KIvsPGniFL3gk0Y71E6oPHwn2bwwu1072ARxPGubQr1gMJa6gaRAveArYrz0cOA8jHmGPE7CRj3895a8AABYOAqdKD3cuWG8fKfePNAkdDtcUIQ8IJxRvCHKSr3XAhy90gm/vCxyHj0gyRI7yL7NO0IXFz3EN+g8zDbePBCrRDyioZy8wEiMvElVDL1gpHO8GD45vZTJzzxmeE49Xk0hvZAusbuMrre81MklPKmN27x47qy7WAOmu0BGjDw0k9g8HLgzvXrlM mLxCJhK90koYPVATR7yA7EO8AAbyuvDRvbxYOoo8APHMPHxdDD14rvg8OKttPC2M8LzQxko9815GvTUoPL3mEBY9vBVXvADEozyAKww9jIfZPDWCF72cgKg8VB7nvAwnE71gBi29vv5LPTRlPz24WYQ8tDy6PHTluTxA8gW9XDwqvX7HQz2SjiU9kcAavQzDObwPN8G8bM4ZPepTMT0KHS29PFXpPFZMJT0Z20G9UCPdvCiG5zwqI0o9EMXXPCRLwDw415w8EGb/PLilejzy4dW8tEKdPJA7PT16qBA9AA6RuYybFbxqVyI9ABYDO0CR9jyESQk8dvQLPcCpWrtACS27TrAJPWUDyLzIZTQ9X19OvcYaMT18GAC9vRS3vCxaubzO9PO81rXYvGY0Dj0PhLy8YTwevUziiDzkSYe8+iQMvdJzy7xUIyS8APqVuwzUSbwYx9g71jU7PYD0dLxi2gy9qvq5vAwzSj2oAc885G3RPJqGKr18rIc8QnMvPTzDGryFbxy9M 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 Fc7SvFqmOj3bBta8RM5LvFDVg7vVCMS8vN0zvVoTRz2gwns824tAvRi1Jr04Zks8oioAvcxszzyojkY9PP5JvA5LJD1Gmya9QATEuxBSNz0AuB46kGlHO5gMgbvknTs9fMtJPSQW1rwA02Y87mwBPTVR0ryAS1M8gNIYPETtIT0WJAS9HswgPVi4HrzAONY8sCpVPC7tTD282Cg9xMXoPFxeKT0kuRc9nFIwPeGuOL0yoAG9QG6yO8ohQL1QpKs7iGioPLJVr7y318q8YHwVu4BkuDsRA/C8ej2bvJA9IruSDge9nOc1PIBUnjkCwyO9QA4tuw6mGD0AhAM9EsyCvFDIwLt8tDI8eBRGPRzGMD2OJ8O8YI16u5v7Jr0oD7Q8CAAMPXQajLwmbAc9Dq84vft8IL0EfAW8KaVKvYIoCL3ELZ08kPUzO9B0Bz1wSlM89B4PPPYARz3uiyu9+FRJPBDouzxWASw9ZyIWvUjAlLxg1j89SItfPKbDuryAjl68hCa9PChPM 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 8DxC1Ug95FwZvQRZCz2aYw8942NHvXS+LrwEOqe8MBnaPEQsJj3guFm8wBkhu6ByVrxAnRA94NnquqB3Bjxi0AY9HkwnPQDvsrogOty7s7DvvM47RT1kBPM84CCjvEhr6TzAipQ8YlUOPSjhqjziozW9cFjjPNz5Wbwk6om8JIiTPAR0JrwWvhs9hBzgPEC9gbrgBgG9lPSHvMC0jTuwPPu7jg08PSAIu7ppBLW8utWPvFnov7z2nDm97bI6veq/TT3IqBc9PJtKvfCvSL2c7TU8UMPMvCiq1jzAQ2e7FWqwvACkqTwkuxO90ASXuw75LT2QXVs8BIonvN4gTD3wc0s8nrw4vcCSUjxwYye9gDkcu67lMj0YxpG8yK/zuwJbCD0UE7i8yWf6vDB1CrvY+bq7a0xJvSaqhbyCqRM9rtkevSCKhzykIoc80LT7PFA/YDyAOfw6Lwm3vOYQ67yc7j+8pGA5vbhP8DtEu+I8JpAsPQRRnzxgh0s8zAUiPMCIDTwYlIo8M 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 Pr0ksIM8cPNoOxyKIz18nU+8lJpKvcvjTL2sbgq9wClOPRuxEb3Jwaa8NGYevAgynjtQchE9NJcUPACLzLvEDbI8IJbPuxAdRT0d50O97WbYvBRyMLw950m9SJ5DPR7LhLyIXNE8iPUGPds5F70QVhi9YMjrvNzHzjxQRgQ7zNkAPUQecbx49Dc9JvwcPcAWYzs8vNy8mc49vbQLFD2MVzY98nolPcbLLT3oIdk8MURBvYG39Ly433c8bPC6PDSfmTyIv8Q8iDW+PIjL5Ty0yxe9MAy4PLSTPb3KnJW8vPlAvevTubwQM8U8WHoZvbAakLuIt3m8gDFKvPRgIz1IJMy8QPYQPHy9qTyECsM8EPxnPAY+8LzWEQe9FYBMvfQUPb3gNrs7xek0vRgSOD0avUQ9eOjSvD47srxArto8zIN2vHbODz22oDE9gFBEPY6iJj1ZORO97MgpveQWLD1qNOO84A4MvUa+Dr3gcv883wHZvLCHSL0YHFS8ADu1u3I/Dr0WES49M 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 8bstb9i8Zk8TPfirDrz4igi9APqMumChuzyU1+E80D+KvCyDJD04/iq9IA11PNq7DT0kX568fNiEvMipgTz4Msa8HGErPdhg4DyaMCK9JIDHPNkwJL3Pt7e8qAdJvHBSPz3DID69AIw4OUhAZzwyNUk9EG0xPYSH67zFjiG9SJf6uxTDRD2V3Ri9+HgjPZFd0bwUIzQ88XAHvUji5Dso0zi9ZF6uPNmkS70UFzW8dINCvHqPOj0QdAs8OYv4vNASZTxAjUC6JLwtvJaoGT0nbuK8wH+CPAaHq7yPer+8hLsgPXifX7wUlc48wB7Nu5yuAjx8A+08s4EkvbiQBT2QGpY8wkhEPSAt+7s8DyM8IGk1O3CNZzswvjS7vFfOPDw0RT0ufDo9SJgHPTJCIr04m1Q8CE5IPP4jSz1OJiI9nFvOPPkL3Lyg3uC7JIqhPGBCRzy4QlA8xB73PFLMAT2AsLm8uIchPJD9Bj2FywS9fXC9vGfEHr0guL862HxfvKscQ70e54q8M 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 jDtw3ro8lHgfvARoHb2AItY6iK4zPA1GRr1gnEU8VEQ2vSjqxDxgXsE7aOLpOyy4HL2Yxhw9Zp6HvLjfFzyYU5K84CyzO/4OIb2MI/o828cMvXTNS7xYmlu8JuBJvcAKpDzoU2a8+HAXvCJfh7wAN8K7rPMBvZBfVzuIRYe7jLglvczs9jzwaBG8XGw1PUnx4rzG3EA9uk8TPUh5H70oBx+8MJjFO4Rm6jzGWgE9YN0evNyKSr24c2o8AHvoOZ8mQ72cASA8MZHAvGmAPr3AMks9PmxJPdCmuDzpmAa94y8qvaLgIT1w4iC8JF1BvTBlN7ywyzQ90s9DPbJWz7ziHBg9UOSzO927L71hOx29nBMAPV0J0rygJE09bug0PbSzwDzwFAG7XOxNPWxgMz089Rs8Gv0ivYbWO73AcRs9UxdIvWz7pTw40D08jDgsPRDcSD2oS8+7ZBs/PbiuWzxizg69gMmkPEQoCbxyThK9OMOauyCjXTzS85u8JFvePDiXs7uD2hq9M 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 B700Ipk8sEnqPHh8ory0PZI8mDpcvOQyJ71AkVS8oB07PT4NBr19UBy90Ja9PNBDOr3cjEq8IF/qO5oqGb0faA29uAMtvEoR2rydWz29AHYsuhC4ZTxa2TU9iLtKPGSZGDw6JEE9EMNGPVf2Q72FXMC8fNCePABYiLvMUkg9SPXMPDwpMjx6lR291JUdvLAPGz3IxUg8+MFuPGXlGb206kk9OVIhvTRELT1k2Dc9sMhgvPT5ZrxI+EY8Hp2HvF78Db0argq9rlQFvZhwR7x84nC81JTIPCSrQz20Ui+9EC9lPFwdvLwX2jC9vseUvMQahTx+TaG84oCOvEqCEz1Itq88864pvRjSaDwyvMS8OO1DPeoxhbzoTwI89qXIvEHltLwJ9e68JlwWPf5N3LxOZgM9oHLHOsav97wcRDg9PM9NPfNDGL0LTJ68iNa2vMw1QDwtMqK8/Cg0PaDHH70rQtG8HAfQvGDcDD34Z029IBAnvau+N70INNW8OBxAvC2ONb24vvq8M 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 tM0jvMzmST3AOKc8nqhOPfl1pbxwu9k8/pFIvcQAwDxVyv28gJk+OyRJIL3SDcm8IHzeujIwM72gw9y87MlNvEjlJzysdy28aAvCO7CCwLtAgUC75AsyPW7lAD1QSec87OTvPB+AAr3AwB89JKpBPPT0Brya4im9SLArvVbMED3Q8RE7MFB/O57GIz1Mw7q8TlRCPVBOKD1eDjA9pk9NPciKVby2Lhw9NbIqvUgpQ71INIq8fJAaveikLD2gSd08en0UvVZtFT0p3O28oJrgO2z5Fj0oACO9gIH/udaSKT2yjB29gIeOupShNr3mVye9+KD1u5P0Tb1QVVe8BApEPc4MRT3ANf68gHlGvfzhSbxDpsi8puMivYAvMr3gEj47arqEvPiGcTwUu608uOrEPLgs+Tsz3Ba99B5HPXOiRL1ASuY8TBYrPdiXRrzKKDm9QDbvPPDOiDxwsYM8DLcpPUaYlbzQRha74p8DPTus9byoKxq8YM8mPM6XFD0xWDy9AMLUuRIvM 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 uzwgoQO9OPbNPHAsBj1L5+K8TsyZvHZlOD3WWM687DcuPdrmDb2s1ag8iZfDvJJ3Jz3YrIu84NZIPeC1zrwAwds8uGblPNghHjyohbk8LvgaPWB3qDw8Q8M860BDvbR3ebzghYI7EH0gPI6+LT2wIho7IMmJPBoBKT1wH227KIcSvHA4KDy6Y0k9xfHWvJiqkztFYDC9BiqnvH5cDD0auC69FrwxvUiYkDx1Kt+8wMw8u6Bz3jqQ+yW9arIXPVQKHLxeaAG9fHX7PLBxsLtYNdK7UOIjPen2B73wN009cDgNvC71ED3BdTu9410WvYhH2DtPhAW9AIpPOhyIsry29Bq9AG/0PABL/jq4oCs9nHH7PGAwkzyMCbk89qbovEjo7bus0nq8aNMyPLj1grymXCO9MJcLO9irWjxk1Um9dGGPPDZJSz38myq9dFvfPNGrybw5EKm8WMEivPCMUbwE+yK87qYqvS5/77ycNea8Uy4dvUMa0bzKby895DhsvLiQ+DwxOji9M 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 P73o86s8ORPzvGjiGzwMBj08P+tFvVyG8zxsub08QGEVvdgIzzzAIgs7NuYEPX4fNb0578K8aBERvWXZOr0APJg86CfWPG6iQj2Chxu9k3I4vYist7zUibo8DDZOvDCyibw+lAy9yB63PKvnE73L6K+8CuQwPdyRMLxsGJw8wu8YvUzuJj2oyio8+E/Mu/0ysbxYGAS9UIkAOwy0UbyYuno8THc5vZAwDzxwFAs9JtOTvI7zCr2g4xo7uQctvVDUZrwU2fq8vI8+vUfLTb0Ajec8lm8xvfbpPD0oaEw96Na0u7hu8jyMaWS8SH2kPJToQL1w5XY8IIQDvWP+5bzgvKc6MOVbu/DMgbu8LQQ9dde7vDhQaDx+RQs9UOlYPFwrKD30xBA8THrKPPbrpbxUDMM8rHjUvKLNq7yYemK8VkcnPV8wKL08HAU9uJpGvObgLT1CNwk9lEWcPFh9pzsAXfe5wI2MupDAND0E05m8mDUlPI7ZQ7041D099A7JPAIgOL3YtDQ9M 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 G71RHq68GP9LPAkgIb1Iudk7W2mxvICkwLtiJBI91I7dvGo7NL3OECM9IMylvG7pGb3UzhI9VF4CPIUPo7x4DE08BwcYveiSAj1I3PY7d/muvNgWnzxM1iE9CM7SPNyu2zw0vlS8wL4su1n7R71E1/I84JqIPAbcBj1EDgs9qBKHu1QxU7ychYM8AJC3N9CAEz1Qm9Y8DHZNvYeT2LyPLCS9APz0unxNyTzfjRO90MRqO48qQb04vRm9gMLOuaWxw7yYfxY9muAhPU83rLx4FNQ77A8EvTp+LD2IQEQ9iZIPvdBWybvzgkO9rn0KvawV6DzAKJK6zxT/vDx3GbwYxy+8+IEfPYhoMT0YLns8LKlBPciTTj2kGhU8kHoVPIGwurz06gU9GEREvGnS6rxUHMs8GKicuyAPzrwJBPm8dNCaPDBzE7wwHUW82IVUPDS0DL0Y1Nw8/Iq3PCqIOr14k+O7CMHwO8k+5Lxs9Ic8VvSRvGBV8zpBDOu8n+k7vSiukDwwDbY8M 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 AF05u6AVljwIaKE7kDNOPJZDC71Q21u7MLHZO4TQEj3YGiO9pP25PBg8Vzz+Sxe9aA1vvGBmn7ocNRw8mHvaPLwvjzws4hc98Hx7u6z0Ez04VP28GIcHPXAsArwc2D49YPCzPAR8yryrzRa9EL2Au2QhSbxQIAm9LMihvGArLz32oRW9+Ec5PRQnxDzkCCM8HJ3SPPpfn7wwqSY9iBNAvNZgNz1oOsc8SKe2PI6RDz0444A7YDlMvAsuRb16Hwg9+If9u5IFIb0QV7q7HFUnPUhLvTygdji9eBuQO4qFSz1wqvo856E1veBI4jrkLUU8GAWGvNT0erzMtYO8bKBIPdgesDvwYM48GM/UPGgLdbzYqvO7WND+PO+TFb17DuW8DB4tvUALertensK8mFJnvBhm3zx0ZkY9EjsePSR/LrzAJ408qLSCvMxjAD04u/48qOgDvQBQojw4Vyi9FsPTvAo4Az3ko6a8SUYLvVlC0byGEUg9vJmxPFjbkjyiKCC9hhFBvZi2M 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 96IvvUELqbymLks9cs5EvYCbQjueohY9rDrxPFRlCz2QzjI8cj+2vA18ubw4UDM9wKmXOtQCo7wA1pu7Hb/PvABp6LtuAYy8eMhRPO9hC71a/hu9IHDIOqCJfzxkmiK8FAlGPYCYuDocmpS8+sJDve7YKb1whH+7kFz/O6BQSrzQRdk8qm0gPUAr5zvUWR09TggTPWbKAb3NSeK8VB5bvIyOmTyIg048SNavu8wHBD0B1ku914/rvOgaCrz8xRy9f0qwvBhrHz0gwLO6K0kXvZCqAD2Q3Ko8rKI/PKyxPD0TRiC9YN0DvWqjwrw2LtC8U9GtvJA+A7vslk68FLRGPR18Rr3sFJa8mu8lPUBnqzsB5d28wAMHupwy0jxgyrc8coQEvaBj3jy8d528sLvvOxi7Fz3oFv88UHDYPDwDuLzGjiY9tfX/vG4UGz1nJDO9SgAlPdChtbvDtaK8UvxHvZYVCT3c2zw9AFBQumCdM7zQCUQ7xAMJPbSR3TzQUhy9KADJO8BXM 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 Ej2gK6O+yO2XPrzY+b7Amfu9CJzEvVAfoj5OMIo+LlOlPqoXmD5cNIG+sKZ8PhzZmT5U76m9kMcfPkBk2T5wO7q+jLzQPmDEKT4YX4Q+plXoPgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACoy/0+ED0hPxGmuL6Qn1M9XhQbP3DAjT0YEpk9hN+dvhs93L70G4+++HgKvrh15j7SF6Y+aDPvvcUKD79ClT++CHPqPrK5DT9ARdI8ONblPSScW74jFQG/KKKLvgKwBD9A7dq+VBLAPpwdPj407ue+1ldpvt0Ok77kAws/WysEv2AT/z64c8o+8LYivbCXTr1GR7G+rIzRPtYkvr5IowI/YlKDvsKU0z1keaE9TxTWPQ==", "training_traits": {"structure_gen": "Random", "n_layers": 7, "max_nodes": 10, "activation_func": "ReLU", "epoch_num"M : 6}, "classes_name": ["Cryptoadz", "Cryptopunks", "Moonbirds", "Nouns"]},m=25,b=50,y=59+11/12,w=59+11.5/12,v=60;function z(e,t){const n=Math.log(1-t)/Math.log(1-e);return e=>1-Math.pow(1-e,n)}class V{constructor(e,t,n){const{model:r,inputDim:i}=j(t,n);this.model=r,this.inputDim=i,this.iteration=0,this.stage=0;const o=new Date(parseInt(e.birthYear),0,1).getTime(),a=new Date(parseInt(e.birthYear)+1,0,1).getTime();this.birthDate=new Date(Math.floor((o+a)/2));const l=zr.filter((t=>t[0]==e.lifeCycle))[0][2];this.growSpM eed=365/l,this.cycleLength=60*l*24*3600*1e3,this.growthFunc=z(.4,.8)}updateAge(e){const t=(e.getTime()-this.birthDate.getTime())/31536e6*this.growSpeed;this.iteration=Math.floor(t/60);const n=t-60*this.iteration;let r;this.age=n;let i,o=0;if(n<25){let e=map(n,0,25,0,1);o=this.growthFunc(e),r=(25-n)/60,this.stage=1,this.stageRatio=map(n,0,25,0,1)}else n<50?(o=1,r=(50-n)/60,this.stage=2,this.stageRatio=map(n,25,50,0,1)):n<y?(o=map(n,50,y,1,0),r=(y-n)/60,this.stage=3,this.stageRatio=map(n,50,y,0,1)):n<w?(o=0,r=(w-n)/6M 0,this.stage=4,this.stageRatio=map(n,y,w,0,1)):n<60&&(o=0,r=(60-n)/60,this.stage=5,this.stageRatio=map(n,w,60,0,1));n<50?i=map(n,0,50,0,780/880):n<w?i=map(n,50,w,780/880,800/880):n<60&&(i=map(n,w,60,800/880,1)),this.nextStateTimestamp=Math.round(e.getTime()+this.cycleLength*r),this.statePercentage=round(100*i);let a=(25-n)/60;a<0&&(a+=1),this.nextStableTimestamp=Math.round(e.getTime()+this.cycleLength*a),this.growth=o,this.model.updateNeurons(o,this.iteration)}getBrainStatus(){return{totalNeurons:this.model.getTotaM lNeurons(),neuronsLife:this.model.getNeuronsLife(),stage:this.stage,inputDim:this.inputDim,stageRatio:this.stageRatio,age:this.age,growth:this.growth,nextStateTimestamp:this.nextStateTimestamp,nextStableTimestamp:this.nextStableTimestamp,rebirthCount:max(this.iteration,0),statePercentage:this.statePercentage}}classifyImage(e){const t=new G(e,1,e.length);return this.model.forward(t).mat[0]}}class M{constructor(e,t,n,r,i){this.p=e,this.v=t,this.size=n,this.shape=i,this.col=r}getRadius(){return 1==Oe?1*this.size/2:2==M Oe?7*this.size/16:3==Oe||4==Oe?4*this.size/7:0}update(){this.p.add(this.v)}draw(e,t,n,r){const i=this.p.x*r,o=this.p.y*r,a=this.size*r,{col:l,shape:s}=this;let h,c;1==n?h=c=l:2==n?(h=dr(t,1),c=l):(h=dr(t,0),c=dr(l,1));e.stroke(dr(c,map(1,0,1,.25,1))),e.fill(dr(h,map(1,0,1,.15,1))),3==n&&e.fill(dr(h,0)),1==s?e.ellipse(i,o,a,a):2==s?e.rect(i,o,7*a/8,7*a/8):3==s&&(e.beginShape(),e.vertex(i-4*a/7,o),e.vertex(i,o-4*a/7),e.vertex(i+4*a/7,o),e.vertex(i,o+4*a/7),e.endShape(CLOSE))}}class E{constructor(e,t,n,r,i,o,a){this.cM enter=e,this.len=t,this.angle=n,this.v=r,this.angV=i,this.c1=o,this.c2=a}getEndpoints(){const e=createVector(this.len/2*cos(this.angle),this.len/2*sin(this.angle));return[Vector.add(this.center,e),Vector.sub(this.center,e)]}update(){this.center.add(this.v),this.angle+=this.angV}draw(e,t){const[n,r]=this.getEndpoints(),i=n.x*t,o=n.y*t,a=r.x*t,l=r.y*t,s=this.c1,h=this.c2;var c=e.drawingContext.createLinearGradient(i,o,a,l);c.addColorStop(0,s),c.addColorStop(1,h),e.drawingContext.strokeStyle=c,e.drawingContext.globalAM lpha=1,e.line(i,o,a,l),e.drawingContext.globalAlpha=1}}function S(e,t){const n=random(TAU),r=random(e,t);return createVector(r*cos(n),r*sin(n))}class R{constructor(e,t,n,r,i){this.wall=n,this.maxR=i;const o=t.length;this.nodes=[];for(let a=0;a<o;++a){const o=[],l=.25*t[a];for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),l=S(.02*i,.05*i),s=random(10,25)*i;o.push(new M(t,l,s,e[a],r))}this.nodes.push(o)}const a=A(e);a.unshift(e[0]),a.push(e[e.length-1]),this.lines=[];for(letM e=0;e<=o;++e){const r=[],l=(0==e?1:t[e-1])*(e==o?1:t[e])*1.5;for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),o=random(5*i,10*i),l=random(TAU),s=S(.02*i,.05*i),h=random(2e-4,.001);r.push(new E(t,o,l,s,h,a[e],a[e+1]))}this.lines.push(r)}}reflectNode(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,{p:o,v:a}=e,l=e.getRadius();(o.x-l<t&&a.x<0||o.x+l>r&&a.x>0)&&(a.x=-a.x),(o.y-l<n&&a.y<0||o.y+l>i&&a.y>0)&&(a.y=-a.y)}reflectLine(e){const{xLeft:t,yTop:n,xRight:r,yBottom:iM }=this.wall,[o,a]=e.getEndpoints(),l=e.v;(min(o.x,a.x)<t&&l.x<0||max(o.x,a.x)>r&&l.x>0)&&(l.x=-l.x),(min(o.y,a.y)<n&&l.y<0||max(o.y,a.y)>i&&l.y>0)&&(l.y=-l.y)}update(){for(const e of this.lines)for(const t of e)t.update(),this.reflectLine(t);for(const e of this.nodes)for(const t of e)t.update(),this.reflectNode(t)}draw(e,t,n,r,i){const o=i/this.maxR;for(const t of this.lines){const n=t.length*r;for(let r=0;r<n;++r)t[r].draw(e,o)}for(const i of this.nodes){const a=i.length*r;for(let r=0;r<a;++r)i[r].draw(e,t,n,o)}}}M function I(e,t){re(e),e.fill(0),e.rect(0,0,500,500),ie(e),e.noStroke(),e.fill(dr(cr("#000000"),.5)),e.push(),e.translate(250,250),e.scale(t),e.translate(-250,-250),e.beginShape(),e.vertex(235.2,24.9),e.bezierVertex(215,24.6,185,11.4,164.8,11),e.bezierVertex(147.2,10.7,129.3,10.4,112.2,14.7),e.bezierVertex(95.1,19,78.5,28.5,69.6,43.8),e.bezierVertex(57.699,64.199,61.599,90.199,70.199,112.2),e.bezierVertex(78.799,134.2,91.6,154.6,97.199,177.5),e.bezierVertex(102.499,199.2,100.899,222.5,92.799,243.2),e.bezierVertex(83M ,268,64.6,288.3,48.9,310),e.bezierVertex(33.2,331.7,24.5,337.5,26.599,364.1),e.bezierVertex(28.2,384.1,61.399,404.2,75.7,418.3),e.bezierVertex(90,432.4,73.7,488.2,91.9,496.7),e.bezierVertex(124.2,511.6,159,472.5,194.3,468.1),e.bezierVertex(211.6,465.9,267.4,501.5,283.9,495.9),e.bezierVertex(340.7,476.7,298.599,428.9,355.4,409.7),e.bezierVertex(370.799,404.5,454.5,407.6,464.4,394.8),e.bezierVertex(478.599,376.3,474.7,349.3,464.299,328.4),e.bezierVertex(453.9,307.5,438.099,289.5,428.699,268.2),e.bezierVertex(412,230,M 419,182.6,446.1,150.9),e.bezierVertex(449.7,146.7,453.6,142.7,455.8,137.6),e.bezierVertex(459.4,129.299,457.5,119.6,454.8,111),e.bezierVertex(443.2,73.4,417.3,40.4,383.6,20.299),e.bezierVertex(358.1,5,343.2,-.4,313.5,0),e.bezierVertex(287.5,.4,261.6,25.4,235.2,24.9),e.endShape(),e.pop()}function C(e,t,n,r,i,o){let a,l,s;re(t),t.fill(0),t.rect(0,0,500,500),ie(t),t.noStroke(),t.fill(dr(n,.5)),1==i?(l=0,s=25,a=map(o,0,25,500,0)):a=0,t.rect(0,a,500,500),e.noStroke(),e.fill(r),e.rect(0,0,500,500),e.beginShape(),e.vertexM (435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),M e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,M 192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4M ,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),e.fill(n),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251M .4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bM ezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.M 1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),re(e)M ,e.fill(r),e.beginShape(),e.vertex(184.3,473.2),e.bezierVertex(164,473.2,144.7,462.099,134,444.3),e.bezierVertex(131.7,440.5,129.1,438.5,125,437.1),e.bezierVertex(97.3,428.1,80.5,400.6,85.2,371.8),e.bezierVertex(86.3,365.1,85.8,364.1,79.9,361.2),e.bezierVertex(57.2,349.8,46.2,323.3,54.3,299.7),e.bezierVertex(54.7,298.599,55.1,297.7,55.5,296.9),e.bezierVertex(55.6,296.599,55.8,296.4,55.9,296.099),e.vertex(57.9,291.499),e.vertex(62.5,293.599),e.bezierVertex(64.9,294.7,67.3,295.799,69.5,296.9),e.bezierVertex(74.5,299.M 299,79.1,301.599,83.9,303.099),e.bezierVertex(89.8,304.9,96.5,305.499,102.7,305.9),e.bezierVertex(102.8,305.9,102.9,305.9,103,305.9),e.bezierVertex(106.6,305.9,108.9,302.799,109,299.799),e.bezierVertex(109.1,296.199,106.6,293.4,102.7,292.799),e.bezierVertex(101.3,292.599,99.9,292.4,98.4,292.299),e.bezierVertex(94.3,291.799,90.1,291.299,86,289.9),e.bezierVertex(68.9,284,56.5,270.2,52.7,252.799),e.bezierVertex(48.9,235.499,54.5,217.7,67.6,205.299),e.bezierVertex(71.9,201.299,72.7,198.1,70.8,192.399),e.bezierVertex(64M .2,172.2,68.8,153.99,84.2,139.599),e.bezierVertex(94.2,130.199,105.5,125.399,117.8,125.399),e.bezierVertex(124.3,125.399,131.1,126.799,137.8,129.599),e.bezierVertex(157,137.399,167.9,152.799,169.4,173.99),e.vertex(169.4,174.399),e.bezierVertex(169.5,175.899,169.6,177.2,169.9,178.299),e.bezierVertex(170.7,181.2,173.2,183.2,176.1,183.2),e.bezierVertex(176.299,183.2,176.5,183.2,176.7,183.2),e.bezierVertex(180.1,182.899,182.6,180.299,182.7,177),e.bezierVertex(183.1,162,178.299,148.2,168.399,136.1),e.bezierVertex(158.2,M 123.5,144.899,115.8,128.799,113.199),e.bezierVertex(123.499,112.299,120.399,109.799,118.899,104.99),e.bezierVertex(113.899,89.699,120.699,72.299,134.899,64.499),e.bezierVertex(139.99,61.699,145.799,60.199,151.7,60.199),e.bezierVertex(162.2,60.199,171.899,64.799,178.1,72.699),e.bezierVertex(179.6,74.6,180.799,76.6,181.9,78.499),e.vertex(182.2,79.099),e.bezierVertex(183.2,80.699,185.2,83.299,188.4,83.299),e.bezierVertex(189.5,83.299,190.6,82.99,191.7,82.399),e.bezierVertex(195.1,80.599,196,76.99,194,72.799),e.bezierVM ertex(190.1,64.799,184.1,58.499,175.6,53.299),e.bezierVertex(174.6,52.699,173.7,52.099,172.5,51.499),e.vertex(170.5,50.299),e.vertex(163,45.899),e.vertex(170.5,41.599),e.bezierVertex(182,34.99,193.1,30.799,204.4,28.599),e.bezierVertex(208.6,27.799,212.9,27.399,217.2,27.399),e.bezierVertex(217.6,27.399,217.9,27.399,218.3,27.399),e.bezierVertex(231.4,27.599,242.7,38.199,243,50.599),e.bezierVertex(243.4,64.899,243.3,78.99,243.2,93.799),e.bezierVertex(243.2,99.799,243.1,105.899,243.1,112.099),e.vertex(243.1,119.199),e.M vertex(236.4,116.799),e.bezierVertex(235.7,116.499,235,116.299,234.4,115.99),e.bezierVertex(233.4,115.599,232.6,115.299,232,115.199),e.bezierVertex(230.6,114.899,229.2,114.599,227.8,114.299),e.bezierVertex(223.8,113.499,220.1,112.699,216.4,112.499),e.vertex(216.2,112.499),e.bezierVertex(212.5,112.499,210.7,115.599,210.6,118.599),e.bezierVertex(210.4,122.399,212.7,125.099,216.4,125.399),e.bezierVertex(230.1,126.399,238.9,133.099,242.3,145.199),e.bezierVertex(243.2,148.399,243.2,151.599,243.2,154.499),e.vertex(243.2,M 155.099),e.bezierVertex(243.2,254.199,243.2,330,243.2,400.599),e.bezierVertex(243.2,401.99,243.2,403.4,243.2,404.9),e.bezierVertex(243.3,411.099,243.3,417.599,242.3,423.9),e.bezierVertex(238.1,449.2,219.6,467.799,194,472.5),e.bezierVertex(190.9,472.9,187.6,473.2,184.3,473.2),e.endShape(),e.beginShape(),e.vertex(315.8,473.1),e.bezierVertex(309.3,473.1,302.8,472,296.5,469.9),e.bezierVertex(270.4,461,253.8,434.9,257.1,407.9),e.bezierVertex(260,384,273.8,366.8,297,358.3),e.bezierVertex(297.7,358.1,298.3,357.8,299,357.6M ),e.bezierVertex(299.8,357.3,300.6,357.1,301.2,356.8),e.bezierVertex(304.3,355.4,306,351.8,304.9,348.7),e.bezierVertex(304,345.9,301.7,344.2,299,344.2),e.bezierVertex(298.6,344.2,298.1,344.2,297.6,344.3),e.bezierVertex(288.1,346.3,279,350.9,269.7,358.3),e.bezierVertex(268.9,358.9,268.1,359.6,267.2,360.4),e.vertex(265.5,361.8),e.vertex(258.5,367.6),e.vertex(257.4,358.6),e.bezierVertex(257.3,358,257.3,357.5,257.2,357.1),e.bezierVertex(257,356,256.9,354.9,256.9,353.7),e.bezierVertex(256.9,334.8,256.9,316,256.9,297.1),M e.bezierVertex(256.9,260.3,256.9,222.3,256.8,185),e.bezierVertex(256.8,170.7,268.3,158.8,282.5,158.4),e.bezierVertex(284.8,158.3,286.7,157.6,287.9,156.2),e.bezierVertex(289.099,154.9,289.599,153.2,289.5,151.3),e.bezierVertex(289.3,147.5,286.7,145.1,282.7,145.1),e.bezierVertex(282.5,145.1,282.2,145.1,282,145.1),e.bezierVertex(278.8,145.3,275.5,146.1,272,146.9),e.bezierVertex(270.9,147.2,269.8,147.4,268.6,147.7),e.bezierVertex(267.9,147.9,267,148.2,265.8,148.7),e.bezierVertex(265.1,149,264.4,149.3,263.5,149.6),e.vertM ex(256.8,152),e.vertex(256.8,114.6),e.bezierVertex(256.8,95,256.8,75.4,256.8,55.9),e.bezierVertex(256.8,38,267.2,27.3,284.6,27.3),e.bezierVertex(285.3,27.3,285.9,27.3,286.6,27.3),e.bezierVertex(299,27.9,318.7,34.5,329.6,41.9),e.vertex(336.1,46.3),e.vertex(324.4,53.3),e.bezierVertex(316.2,58.2,310.2,64.6,306,72.9),e.bezierVertex(304.2,76.4,305.1,78.5,306.1,80),e.bezierVertex(307.4,81.9,309.4,83,311.6,83),e.bezierVertex(313.7,83,315.7,81.9,317.1,80.1),e.bezierVertex(317.4,79.7,317.8,79,318.1,78.4),e.bezierVertex(318.M 4,77.9,318.7,77.3,319,76.8),e.bezierVertex(325.3,66.2,336.3,59.9,348.5,59.9),e.bezierVertex(353.2,59.9,357.8,60.8,362.1,62.7),e.bezierVertex(377.6,69.3,386,86.7,381.7,103.2),e.bezierVertex(380.7,107.1,378.5,111.8,371.1,113.1),e.bezierVertex(342.7,118.1,322.2,139.1,317.8,167.8),e.bezierVertex(317.4,170.3,317.3,173.2,317.4,176.5),e.bezierVertex(317.5,180,320.1,182.8,323.5,183),e.bezierVertex(323.6,183,323.8,183,323.9,183),e.bezierVertex(327.1,183,329.8,180.6,330.3,177.2),e.bezierVertex(330.6,175.7,330.7,174,330.9,172M .3),e.bezierVertex(331.1,169.8,331.4,167.3,332,164.7),e.bezierVertex(337.3,141.9,357.7,125.4,380.7,125.4),e.bezierVertex(382.5,125.4,384.3,125.5,386.1,125.7),e.bezierVertex(412.8,128.9,432.6,150.9,432,176.9),e.bezierVertex(431.9,182.3,430.9,187.7,429.1,192.7),e.bezierVertex(427.2,197.9,428,201,432.3,205),e.bezierVertex(446.8,218.7,451.8,236,446.6,255),e.bezierVertex(441.4,274,428.3,286.5,408.7,291.3),e.bezierVertex(406.1,291.9,403.6,292.1,401.1,292.3),e.bezierVertex(400,292.4,398.9,292.5,397.9,292.6),e.bezierVertexM (393.6,293.1,390.9,295.7,391,299.5),e.bezierVertex(391.1,303.4,394,305.8,398.5,305.8),e.bezierVertex(409.9,305.8,420.8,302.6,431.1,296.4),e.bezierVertex(431.8,296,432.5,295.5,433.2,295.1),e.bezierVertex(433.8,294.7,434.5,294.3,435.2,293.9),e.bezierVertex(436,293.4,436.6,293.2,437.2,293.1),e.bezierVertex(437.4,293,437.7,292.9,438.1,292.8),e.vertex(442.5,291.4),e.vertex(444.2,295.7),e.bezierVertex(450.9,312.4,449.5,328.4,440,343.4),e.bezierVertex(435.3,350.8,428.7,356.7,420.2,361.1),e.bezierVertex(414.3,364.1,413.7,3M 65.2,414.8,371.7),e.bezierVertex(419.5,400.2,403,427.6,375.6,436.9),e.bezierVertex(371,438.5,368.3,440.7,365.8,444.7),e.bezierVertex(355.2,462.5,336.4,473.1,315.8,473.1),e.bezierVertex(315.8,473.1,315.8,473.1,315.8,473.1),e.endShape(),ie(e),e.fill(n),e.beginShape(),e.vertex(120.2,279.9),e.bezierVertex(117.9,279.9,112.4,279.299,112.2,273.599),e.bezierVertex(112,267.7,117.4,266.7,119.7,266.599),e.bezierVertex(133.1,265.799,143.1,259.499,149.3,247.899),e.bezierVertex(149.6,247.299,150.1,246.399,150.3,245.399),e.bezierM Vertex(150.6,244.299,150.5,243.299,150.5,242.7),e.bezierVertex(150.5,242.6,150.5,242.5,150.5,242.299),e.vertex(150.3,238.799),e.vertex(141.1,235.99),e.bezierVertex(114.6,227.799,95.6,202.499,95.9,175.799),e.bezierVertex(95.9,173.99,96.4,168.199,102.2,168.199),e.bezierVertex(102.6,168.199,103,168.199,103.4,168.299),e.bezierVertex(104.8,168.499,108.2,168.899,109.2,175.599),e.bezierVertex(109.3,176.599,109.5,177.599,109.6,178.499),e.bezierVertex(110.4,184.199,111.3,189.99,113.7,195.499),e.bezierVertex(121.9,213.99,139M .5,225.499,159.7,225.499),e.bezierVertex(172.1,225.499,184.1,220.899,193.5,212.599),e.bezierVertex(194,212.199,194.4,211.799,194.8,211.399),e.bezierVertex(195.1,211.099,195.5,210.799,195.8,210.399),e.bezierVertex(197.4,208.99,199.2,208.2,200.9,208.2),e.bezierVertex(202.5,208.2,204,208.899,205.3,210.1),e.bezierVertex(208,212.9,207.9,216.9,205,219.9),e.bezierVertex(196.5,228.6,186.3,234.3,174.7,236.8),e.bezierVertex(168.799,238.1,165.6,241,163.899,246.7),e.bezierVertex(158.3,265.9,139.9,279.7,120.2,279.9),e.vertex(12M 0.2,279.9),e.endShape(),e.beginShape(),e.vertex(187.2,427.5),e.bezierVertex(183.799,427.5,181.299,425.3,180.799,422),e.bezierVertex(180.6,420.8,180.499,419.5,180.399,418.1),e.bezierVertex(180.299,417,180.2,415.8,180.099,414.7),e.bezierVertex(177.199,390.5,156.699,371.3,132.399,370.2),e.bezierVertex(131.99,370.2,131.499,370.2,131.099,370.2),e.bezierVertex(130.699,370.2,130.299,370.2,129.799,370.2),e.bezierVertex(125.99,369.9,123.199,367.2,123.099,363.6),e.bezierVertex(122.99,360.2,125.799,357.3,129.599,356.9),e.beziM erVertex(130.499,356.8,131.499,356.8,132.599,356.7),e.bezierVertex(133.199,356.7,133.799,356.7,134.399,356.6),e.vertex(138.299,356.4),e.vertex(139.1,352.6),e.bezierVertex(139.5,350.7,139.799,348.9,140.2,347),e.bezierVertex(140.899,343.4,141.5,340,142.399,336.8),e.bezierVertex(150.099,310.7,174.399,292,201.399,291.3),e.vertex(201.599,291.3),e.bezierVertex(203.699,291.3,206.299,292,208.299,293.2),e.bezierVertex(210.499,294.5,210.699,297.5,209.99,299.8),e.bezierVertex(209.499,301.5,208.199,303.9,203.299,304.7),e.bezieM rVertex(202.199,304.9,200.99,305,199.799,305.2),e.bezierVertex(194.499,305.9,188.99,306.599,183.799,308.9),e.bezierVertex(165.499,316.799,155.199,331.299,152.99,352),e.bezierVertex(152.399,357.8,154.499,361.7,159.699,364.5),e.bezierVertex(178.199,374.4,189.399,390,193.099,410.9),e.bezierVertex(193.699,414.299,193.899,418,193.599,422),e.bezierVertex(193.399,425.2,190.899,427.5,187.399,427.5),e.vertex(187.2,427.5),e.endShape(),e.beginShape(),e.vertex(364.3,281.1),e.bezierVertex(346.3,280.6,332.9,272.8,323.5,257),e.beM zierVertex(321.6,253.9,320.4,250.2,319.2,246.7),e.bezierVertex(317.7,242.2,315,239.799,310.5,238.799),e.bezierVertex(298.5,236.299,288,230.7,279.4,222.1),e.bezierVertex(276.7,219.4,274.9,215.299,278,211.9),e.bezierVertex(279.4,210.3,281,209.6,282.6,209.6),e.bezierVertex(284.4,209.6,286.4,210.6,288.3,212.5),e.bezierVertex(297.8,221.8,310.4,226.9,323.9,226.9),e.bezierVertex(340.2,226.9,355.1,219.3,364.8,206.2),e.bezierVertex(371,197.8,374.2,188.5,374.5,178.5),e.vertex(374.5,177.9),e.bezierVertex(374.5,177,374.5,176.1M ,374.7,175.4),e.bezierVertex(375.3,171.8,377.9,169.5,381.3,169.5),e.bezierVertex(381.4,169.5,381.5,169.5,381.7,169.5),e.bezierVertex(385.4,169.7,388,172.4,388,176.1),e.bezierVertex(388.1,190.7,383.4,204,374.2,215.8),e.bezierVertex(365.8,226.5,354.7,233.9,341.2,237.9),e.bezierVertex(340,238.3,338.7,238.6,337.3,239.1),e.bezierVertex(335.9,239.6,335.1,240.4,334.7,240.9),e.bezierVertex(334.599,241,334.5,241.1,334.4,241.2),e.vertex(331.799,243.6),e.vertex(333.199,246.8),e.bezierVertex(338.199,258,346.799,264.9,358.699,2M 67.3),e.bezierVertex(360.199,267.6,361.599,267.7,362.99,267.9),e.bezierVertex(363.599,268,364.299,268,364.899,268.1),e.bezierVertex(369.099,268.6,371.799,271.4,371.499,275),e.bezierVertex(371.199,278.6,368.299,281.2,364.399,281.2),e.vertex(364.3,281.1),e.endShape(),e.beginShape(),e.vertex(323.9,437),e.bezierVertex(323.7,437,323.5,437,323.299,437),e.bezierVertex(319.599,436.7,317.299,434.1,317.4,430.2),e.bezierVertex(317.9,406.099,328.299,388,349.5,375),e.bezierVertex(350.7,374.2,352,373.5,353.4,372.8),e.bezierVerteM x(354.099,372.4,354.7,372.1,355.299,371.7),e.vertex(357.499,370.5),e.vertex(357.799,368),e.bezierVertex(360.4,346.6,345.199,323.7,323.9,317),e.bezierVertex(319.099,315.5,314.099,314.9,309.299,314.4),e.vertex(308.199,314.299),e.bezierVertex(305.99,314.099,300.799,312.9,300.899,307.299),e.bezierVertex(300.99,303.499,303.899,300.9,308.099,300.9),e.vertex(308.299,300.9),e.bezierVertex(327.099,301.299,343.099,308.7,355.699,322.9),e.bezierVertex(364.299,332.5,369.399,344.099,370.99,357.299),e.bezierVertex(371.099,358.4,3M 71.299,359.4,371.499,360.499),e.bezierVertex(371.599,360.99,371.699,361.499,371.799,361.99),e.vertex(372.499,365.899),e.vertex(377.899,366.199),e.bezierVertex(378.799,366.299,379.699,366.299,380.599,366.399),e.bezierVertex(385.099,366.699,387.899,369.399,387.799,373.299),e.bezierVertex(387.699,377.099,384.99,379.599,380.799,379.799),e.bezierVertex(369.799,380.199,359.99,383.299,351.899,389.299),e.bezierVertex(338.799,398.799,331.699,411.699,330.699,427.499),e.vertex(330.699,428.299),e.bezierVertex(330.599,429.199,3M 30.599,430.099,330.499,430.799),e.bezierVertex(330,434.7,327.5,437,323.9,437),e.endShape()}function T(e){return e[0].map(((t,n)=>e.map((e=>e[n]))))}function A(e){return e.map((e=>Array.isArray(e)?A(e):e))}function D(e,t){return floor(random(e,t))}function k(e){let t=0;for(const n of e)t+=n[1];let n=random(t),r=0;for(const t of e)if(r+=t[1],n<r)return t[0];return null}function L(e){for(let t=1;t<e.length;++t){let n=D(0,t),r=e[t];e[t]=e[n],e[n]=r}}function P(e){return null==e||""===e}function O(e){return new Promise(M (t=>setTimeout(t,e)))}function F(e,t,n){let r=0;for(let i=1;i<=1e3;++i)for(let o=1;o<=1e3;++o)if(e*o%(t*i)==0){let e=1*i/o;abs(e-n)<abs(r-n)&&(r=e)}return r}function N(){let e=60*(new Date).getTimezoneOffset()*1e3;return new Date(Date.now()-e).toISOString().slice(0,-1)}function B(e,t,n){let r;if(push(),textSize(e),textWidth(t)<=n)r=t;else for(let e=0;e<t.length;++e){const i=t.slice(0,e+1)+"...";if(textWidth(i)>n){r=i;break}}return pop(),r}function Y(e){var t=e%10,n=e%100;return 1==t&&11!=n?e+"st":2==t&&12!=n?e+"nd"M :3==t&&13!=n?e+"rd":e+"th"}class G{constructor(e,t,n){this.n=t,this.m=n,this.mat=[];let r=0;for(let t=0;t<this.n;++t){this.mat.push([]);for(let n=0;n<this.m;++n)this.mat[t].push(r<e.length?e[r]:0),r+=1}return this}copy(){return new G(this.mat.flat(),this.n,this.m)}}class H{static __linear=e=>e;static __relu=e=>Math.max(e,0);static __leaky_relu=e=>e>0?e:.2*e;static __sigmoid=e=>1/(1+Math.exp(-e));static __tanh=e=>Math.tanh(e);static __apply_unary_op(e,t){const n=e.copy();for(let e=0;e<n.n;++e)for(let r=0;r<n.m;++r)nM .mat[e][r]=t(n.mat[e][r]);return n}static linear=e=>H.__apply_unary_op(e,H.__linear);static relu=e=>H.__apply_unary_op(e,H.__relu);static leaky_relu=e=>H.__apply_unary_op(e,H.__leaky_relu);static sigmoid=e=>H.__apply_unary_op(e,H.__sigmoid);static tanh=e=>H.__apply_unary_op(e,H.__tanh);static __add=(e,t)=>e+t;static __mul=(e,t)=>e*t;static __apply_binary_op=(e,t,n)=>{"object"!=typeof t&&(t=new G([t],1,1));const r=e.copy();for(let e=0;e<r.n;++e)for(let i=0;i<r.m;++i)r.mat[e][i]=n(r.mat[e][i],t.mat[e%t.n][i%t.m]);retM urn r};static mul=(e,t)=>H.__apply_binary_op(e,t,H.__mul);static add=(e,t)=>H.__apply_binary_op(e,t,H.__add);static matMul(e,t){const n=new G([],e.n,t.m);for(let r=0;r<n.n;++r)for(let i=0;i<n.m;++i)for(let o=0;o<e.m;++o)n.mat[r][i]+=e.mat[r][o]*t.mat[o][i];return n}static softmax(e){const t=H.__apply_unary_op(e,(e=>Math.exp(e))),n=t.mat.flat().reduce(((e,t)=>e+t));for(let r=0;r<e.n;++r)for(let i=0;i<e.m;++i)t.mat[r][i]/=n;return t}}class ${constructor(e,t){this.scale=e,this.offset=t}forward(e){return H.add(H.mul(e,M this.scale),this.offset)}}class X{constructor(){}forward(e){return e.map((e=>e.flat()))}}class W{constructor(e,t,n,r){this.out_dim=e,this.activation=t,this.w=n,this.b=r}forward(e){const t=H.add(H.matMul(e,this.w),this.b);return null==this.activation?t:this.activation(t)}}class U{constructor(e,t,n){this.preprocessLayers=e,this.hiddenLayers=t,this.outputLayer=n,this.totalNeurons=this.hiddenLayers.map((e=>e.out_dim)),this.currentOrders=[],this.currentIteration=null}updateNeurons(e,t){if(t!=this.currentIteration){this.M currentOrders=[];for(let e=0;e<this.totalNeurons.length;++e){randomSeed(100*(t+1)+e);const n=[];for(let t=0;t<this.totalNeurons[e];++t)n.push(t);L(n),this.currentOrders.push(n)}this.currentIteration=t}const n=A(this.totalNeurons),r=n.reduce(((e,t)=>e+t))*(1-e);for(let e=0;e<r;++e){const t=n.map(((e,t)=>(e-1)/this.totalNeurons[t]));n[t.map(((e,t)=>[e,t])).reduce(((e,t)=>t[0]>e[0]?t:e))[1]]-=Math.min(r-e,1)}this.neuronsLife=[];for(let e=0;e<n.length;++e){const t=this.currentOrders[e],r=Array(this.totalNeurons[e]).filM l(0);for(let i=0;i<n[e];++i)r[t[i]]=Math.min(n[e]-i,1);this.neuronsLife.push(r)}}getTotalNeurons(){return A(this.totalNeurons)}getNeuronsLife(){return A(this.neuronsLife)}forward(e){for(const t of this.preprocessLayers)e=t.forward(e);for(const[t,n]of this.hiddenLayers.entries()){e=n.forward(e);const r=new G(this.neuronsLife[t],1,e.m);e=H.mul(e,r)}return e=this.outputLayer.forward(e),H.softmax(e)}}function q(e){switch(e){case"relu":return H.relu;case"sigmoid":return H.sigmoid;case"tanh":return H.tanh;case"leaky_reluM ":return H.leaky_relu;default:return H.linear}}function j(e,t){const n=[],r=[],i=Z(t);let o=null,a=0,l=[];for(const t of e.config.layers)if("InputLayer"==t.class_name)o=t.config.batch_input_shape.slice(1),l=o;else if("Rescaling"==t.class_name)n.push(new $(t.config.scale,t.config.offset));else if("Flatten"==t.class_name)o=[o.reduce(((e,t)=>e*t))];else if("Dense"==t.class_name){const e=[t.config.units],n=o[0]*e[0],l=e[0],s=i.subarray(a,a+n);a+=n;const h=i.subarray(a,a+l);a+=l;const c=new G(s,o[0],e[0]),u=new G(h,1,e[M 0]),f=q(t.config.activation);r.push(new W(e[0],f,c,u)),o=e}const s=r.pop();return{model:new U(n,r,s),inputDim:l}}function Z(e){const t=window.atob(e),n=t.length/Float32Array.BYTES_PER_ELEMENT,r=new DataView(new ArrayBuffer(Float32Array.BYTES_PER_ELEMENT)),i=new Float32Array(n);let o=0;for(let e=0;e<n;e++){o=4*e;for(let e=0;e<4;++e)r.setUint8(e,t.charCodeAt(o+e));i[e]=r.getFloat32(0,!0)}return i}class K{constructor(e){this.elt=e,this._events={},this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight}positiM on(){if(0===arguments.length)return{x:this.elt.offsetLeft,y:this.elt.offsetTop};var e="absolute";return"static"!==arguments[2]&&"fixed"!==arguments[2]&&"relative"!==arguments[2]&&"sticky"!==arguments[2]&&"initial"!==arguments[2]&&"inherit"!==arguments[2]||(e=arguments[2]),this.elt.style.position=e,this.elt.style.left=arguments[0]+"px",this.elt.style.top=arguments[1]+"px",this.x=arguments[0],this.y=arguments[1],this}show(){return this.elt.style.display="block",this}hide(){return this.elt.style.display="none",this}siM ze(e,t){if(0===arguments.length)return{width:this.elt.offsetWidth,height:this.elt.offsetHeight};var n=e,r=t;if(n!==te||r!==te){if(n===te?n=t*this.width/this.height:r===te&&(r=e*this.height/this.width),this.elt instanceof HTMLCanvasElement){var i,o={},a=this.elt.getContext("2d");for(i in a)o[i]=a[i];for(i in this.elt.setAttribute("width",n*this._pInst._pixelDensity),this.elt.setAttribute("height",r*this._pInst._pixelDensity),this.elt.style.width=n+"px",this.elt.style.height=r+"px",this._pInst.scale(this._pInst._pixeM lDensity,this._pInst._pixelDensity),o)this.elt.getContext("2d")[i]=o[i]}else this.elt.style.width=n+"px",this.elt.style.height=r+"px",this.elt.width=n,this.elt.height=r;this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight,this._pInst&&this._pInst._curElement&&this._pInst._curElement.elt===this.elt&&(this._pInst._setProperty("width",this.elt.offsetWidth),this._pInst._setProperty("height",this.elt.offsetHeight))}return this}style(e,t){if(t instanceof Color&&(t="rgba("+t.levels[0]+","+t.levels[1]+","+t.leM vels[2]+","+t.levels[3]/255+")"),void 0===t){if(-1===e.indexOf(":"))return window.getComputedStyle(this.elt).getPropertyValue(e);for(var n=e.split(";"),r=0;r<n.length;r++){var i=n[r].split(":");i[0]&&i[1]&&(this.elt.style[i[0].trim()]=i[1].trim())}}else if(this.elt.style[e]=t,"width"===e||"height"===e||"left"===e||"top"===e){var o=window.getComputedStyle(this.elt).getPropertyValue(e).replace(/[^\d.]/g,"");this[e]=Math.round(parseFloat(o,10))}return this}value(){return arguments.length>0?(this.elt.value=arguments[0]M ,this):"range"===this.elt.type?parseFloat(this.elt.value):this.elt.value}mouseClicked(e){return this._adjustListener("click",e,this),this}isFocused(){return document.activeElement===this.elt}_adjustListener(e,t,n){return!1===t?this._detachListener(e,n):this._attachListener(e,t,n),this}_attachListener(e,t,n){n._events[e]&&this._detachListener(e,n);var r=t.bind(n);n.elt.addEventListener(e,r,!1),n._events[e]=r}_detachListener(e,t){var n=t._events[e];t.elt.removeEventListener(e,n,!1),t._events[e]=null}}function J(e,t){M var n=document.createElement("button");return n.innerHTML=e,t&&(n.value=t),ee(n)}function Q(e){var t=arguments.length>1&&void 0!==arguments[1]&&arguments[1],n=function(t){var n=!0,r=!1,i=void 0;try{for(var o,a=t.target.files[Symbol.iterator]();!(n=(o=a.next()).done);n=!0){var l=o.value;File._load(l,e)}}catch(e){r=!0,i=e}finally{try{n||null==a.return||a.return()}finally{if(r)throw i}}};if(window.File&&window.FileReader&&window.FileList&&window.Blob){var r=document.createElement("input");return r.setAttribute("type",M "file"),t&&r.setAttribute("multiple",!0),r.addEventListener("change",n,!1),ee(r)}}function ee(e){return document.body.appendChild(e),new K(e)}createImg=function(){var e,t=document.createElement("img"),n=arguments;return n.length>1&&"string"==typeof n[1]&&(t.alt=n[1]),n.length>2&&"string"==typeof n[2]&&(t.crossOrigin=n[2]),t.src=n[0],e=ee(t,this),t.addEventListener("load",(function(){e.width=t.offsetWidth||t.width,e.height=t.offsetHeight||t.height;var r=n[n.length-1];"function"==typeof r&&r(e)})),e},createInput=funcM tion(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:"",t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:"text",n=document.createElement("input");return n.setAttribute("value",e),n.setAttribute("type",t),ee(n,this)};const te="auto";function ne(e){re(e);const t=e._rectMode;e.rectMode(CORNER),e.rect(0,0,e.width,e.height),e.rectMode(t),ie(e)}function re(e){e.push(),e.fill(255,255,255,255),e.blendMode(REMOVE)}function ie(e){e.blendMode(BLEND),e.pop()}File=function(e,t){this.file=e,this._pInst=t;vM ar n=e.type.split("/");this.type=n[0],this.subtype=n[1],this.name=e.name,this.size=e.size,this.data=void 0},File._createLoader=function(e,t){var n=new FileReader;return n.onload=function(n){var r=new File(e);if("application/json"===r.file.type)r.data=JSON.parse(n.target.result);else if("text/xml"===r.file.type){var i=(new DOMParser).parseFromString(n.target.result,"text/xml");r.data=new XML(i.documentElement)}else r.data=n.target.result;t(r)},n},File._load=function(e,t){if(/^text\//.test(e.type)||"application/json"M ===e.type)File._createLoader(e,t).readAsText(e);else if(/^(video|audio)\//.test(e.type)){var n=new File(e);n.data=URL.createObjectURL(e),t(n)}else File._createLoader(e,t).readAsDataURL(e)},XML=function(e){if(e)this.DOM=e;else{var t=document.implementation.createDocument(null,"doc");this.DOM=t.createElement("root")}},document.addEventListener("DOMContentLoaded",(function(){addEventListener("mousemove",(e=>{window.mouseX=e.pageX,window.mouseY=e.pageY}))})),new e("global");const oe="211";let ae,le,se,he,ce,ue,fe,de,xeM ,ge,pe,me,be,ye,we,ve,ze,Ve,_e,Me,Ee,Se,Re,Ie,Ce,Te,Ae,De,ke,Le,Pe,Oe,Fe,Ne,Be,Ye,Ge,He,$e,Xe,We,Ue,qe,je,Ze,Ke,Je,Qe,et,tt,nt,rt,it,ot,at,lt,st,ht,ct,ut,ft,dt,xt,gt,pt,mt,bt,yt,wt,vt,zt,Vt,_t,Mt,Et,St,Rt,It,Ct,Tt,At=!1,Dt=!1,kt=!0,Lt=!1,Pt=!1;const Ot=[" ","Growing","Stable","Decaying","Dead","Rebirth"];let Ft,Nt,Bt,Yt,Gt,Ht,$t,Xt,Wt,Ut,qt,jt,Zt,Kt,Jt,Qt,en,tn,nn,rn,on,an,ln,sn,hn=0,cn=0,un=0,fn=!1,dn=!0,xn=!0,gn=null,pn=null,mn=null,bn=!1,yn=!1,wn=null,vn=null,zn=!1;async function setup(){let e=windowWidth,t=windM owHeight;createCanvas(e,t),et=createGraphics(e,t),Xe=createGraphics(e,t),$e=createGraphics(e,t),We=createGraphics(e,t),Ue=createGraphics(e,t),qe=createGraphics(e,t),Qe=createGraphics(e,t),je=createGraphics(e,t),Ze=createGraphics(e,t),Ke=createGraphics(e,t),Je=createGraphics(e,t),tt=createGraphics(500,500),nt=createGraphics(500,500),rt=createGraphics(500,500),_n(),Mn(),Sn(),await En(),Gn(),Rn(),bn=!0}function _n(){Et=parseInt(oe),randomSeed(Et),noiseSeed(Et)}function Mn(){Wt=Ir(p.training_traits),Cr(Wt)}async functiM on En(){let e;Jt=r(),Qt=o(),[Xt,e]=await Promise.all([s(Jt),h(Qt)]),Ut=new V(Wt.visual,e.layers_config,e.weight_b64),Ut.updateAge(new Date),_n(),Wt.training=e.training_traits,Ht=e.model_name,$t=e.classes_name}function Sn(){le=min(width,height)/1024,ut=Rr.findIndex((e=>e[0]===Wt.visual.colorPalette)),ft=[["#ffffff","#231f20","#231f20"],["#231f20","#ffffff","#ffffff"],["#104da8","#ffffff","#ffffff"],["#722F1F","#FCE1B2","#FCE1B2"],["#e88120","#f9f2e5","#f9f2e5"],["#f6b941","#2E2E2E","#2E2E2E"],["#45daaa","#012221","#M 012221"],["#F1F1F1","#328DFE","#328DFE"],["#111822","#D3EB8D","#D3EB8D"],["#713FF9","#D6D5E6","#D6D5E6"],["#FBDA9D","#795106","#795106"],["#8f5b62","#ead0d0","#ead0d0"],["#eae4cb","#508cac","#508cac"],["#ffc6cc","#cc313d","#cc313d"],["#60A900","#E0FE00","#E0FE00"],["#507DBE","#D0D1D3","#D0D1D3"],["#305848","#E8F2EE","#E8F2EE"],["#2a2634","#5b6988","#cb78a2","#5b6988"],["#590e29","#fd5e53","#fd5e53","#ffe373"],["#0a141d","#57d4e4","#328195","#2A9ECF","#0ab6a8","#57d4e4"],["#3a2d28","#d5c2ac","#df6338","#3d9895","#d5M c2ac"],["#030706","#77c4d9","#77c4d9","#77c4d9","#ffffff","#ffffff","#e72020","#e72020"],["#3a4664","#92f5ff","#f9ff94","#eaa0a2","#55dde0"],["#fbfaff","#f04bb1","#f04bb1","#fac373","#82cef0","#8b31ce"],["#000000","#ffffff","#ff0002","#f26522","#fdff00","#00ff03","#01fffe","#0000ff","#ff00ff"]];for(let e=0;e<ft.length;++e)for(let t=0;t<ft[e].length;++t)ft[e][t]=cr(ft[e][t]);pt=[],ct=ft[ut][0],st=ft[ut][1]}function Rn(){gn=document.querySelector("#upload"),pn=document.querySelector("#inputUpload"),gn.addEventListeneM r("dblclick",(()=>{if(!Lt&&!yn)if(In(Ie)&&cn==Ve-1)pn.click();else{if(4!=Pe&&5!=Pe&&(In(Ie)||cn!=Ve-1))return;fn=!0,dn=!0,Bt=0,un=0}})),pn.addEventListener("click",(()=>{pn.value=null,gn.style.display="block"})),pn.addEventListener("change",(()=>{const[e]=pn.files;e?(se=null,gn.style.display="none",Tn(URL.createObjectURL(e)),mn=e):gn.style.display="block"}))}function In(e){for(let t=0;t<e.length;++t){let n=0;for(let r=0;r<e[t].length;++r)e[t][r]>0&&++n;if(0==n)return!1}return!0}function Cn(){null!=se&&(un=0,Pt=!0,hM e=0,ue=0,drewLineAnim=!0,ce=(ae/2+we/2)/le,loadImage(se.elt.src,(e=>{const[t,n,r]=Gt,i=createGraphics(t,n);i.image(e,0,0,t,n),i.loadPixels();const o=i.pixels.filter(((e,t)=>t%4!=3)),a=Ut.classifyImage(o);Zt=T([a,$t.map((e=>e.toUpperCase()))]).sort(((e,t)=>e[0]>t[0]?-1:1))})))}function Tn(e){se=createImg(e,""),se.hide(),Cn()}function An(){zn||(ce+=(width-ae-we)/tn/le),re(Xe),Xe.rect(ce*le,0,width,height),ie(Xe),un>=ge&&1==kt&&(kt=!1,un-=ge),kt&&(re($e),$e.strokeWeight(2*Fe),Jn(he,ze,ct,ct,$e),ie($e)),un>=ge&&0==kt&&M (kt=!0,un-=ge,he+=1,he==en&&(++ue,he=0,ce=(ae/2+we/2)/le,1==ue&&(Pt=!1,Dn(),ye=millis())))}function Dn(){At=!0,pe=!1,me=!1,tryButton=br("Try Again",width/2-225*le,height/2+265*le,290*le,40*le,kn),closeResultButton=br("Close",width/2+75*le,height/2+265*le,150*le,40*le,Ln)}function kn(){At=!1,tryButton.hide(),closeResultButton.hide(),pn.click()}function Ln(){Yt=!0,At=!1,Gn(),tryButton.hide(),closeResultButton.hide(),gn.style.display="block",se=null}function keyTyped(){bn&&!1===yn&&!1===yr()&&("i"!==key&&"I"!==key||(DM t=!Dt),"b"!==key&&"B"!==key||(xn=!xn),"s"!==key&&"S"!==key||!1!==Lt||saveCanvasAtCurrentTime(),"k"!==key&&"K"!==key||!1!==Lt||save4KCanvasAtCurrentTime(),"u"!==key&&"U"!==key||!1!==Lt||!1!==At||!1!==fn||!1!==Pt||On())}function On(){Lt=!0,wn=null,vn=null,submitButton=br("Submit",width/2-155*le,height/2+115*le,150*le,40*le,Fn),closeSettingButton=br("Close",width/2+5*le,height/2+115*le,150*le,40*le,Yn),vt=createInput(),vt.position(width/2-252.5*le,height/2-40*le),vt.size(500*le,25*le),vt.style("font-size","15px"),vt.vM alue(Jt||""),zt=createInput(),zt.position(width/2-252.2*le,height/2+35*le),zt.size(500*le,25*le),zt.style("font-size","15px"),zt.value(Qt||"")}function Fn(){Vt=vt.value(),_t=zt.value(),submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide(),Lt=!1,yn=!0,Nn()}async function Nn(){[wn,vn,_]=await Promise.all([c(Vt),u(_t),O(1e3)]),yn=!1,wn&&vn?(n(Vt),i(_t),window.location.reload()):(Lt=!0,submitButton.show(),closeSettingButton.show(),vt.show(),zt.show())}function Bn(){Je.textFont("Trebuchet MS"),Je.noStroke(),M pr(Je,600*le,200*le),Je.strokeWeight(1*le),Je.stroke(xt),Je.fill(xt),Je.textSize(50*le),Je.text("update()",width/2,height/2+2.5*le)}function Yn(){wn=null,vn=null,Lt=!1,submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide()}function Gn(){_n(),nn=Date.now(),pe=!1,me=!1,St=Wt.training.structure_gen,Rt=Wt.visual.birthYear,It=Wt.visual.lifeCycle,Ct=Wt.training.epoch_num,Tt=Wt.training.activation_func,Ft=Mr.findIndex((e=>e[0]==Wt.visual.hardwareAcceleration))+1,1==Ft?(Nt=30,fe=40):2==Ft?(Nt=15,fe=20):(Nt=2,fe=M 10);const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),ae=100*le,ht=50*le,Oe=Sr.findIndex((e=>e[0]==Wt.visual.nodeShape))+1,dt=Er.findM Index((e=>e[0]==Wt.visual.nodeFill))+1,lt=_r.findIndex((e=>e[0]==Wt.visual.pattern))+1,de=Math.tanh(Math.log10(Xt.avgfeerate)),de=map(de,0,1,.2,.8),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let M e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;M e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,at=.7,pt=[],xt=ft[ut][2],gt=ft[ut][ft[ut].length-1];for(let e=3;e<ft[ut].length-1;e++)pt.push(ft[ut][e]);mt=sr(xt,gt,pt,wM idth),bt=[],wt=[],yt=width/(Ve-1);for(let e=0;e<Ve;e++)bt.push(hr(mt,yt*e/width)),wt.push(hr(mt,yt*e/width));wt.unshift(bt[0]),wt.push(bt[bt.length-1]),hn=0,cn=0,un=0,Yt=!0;const n={xLeft:ae/8,xRight:width-ae/8,yTop:ae/8,yBottom:height-ae/8},r=Ce.map((e=>e.length));jt=new R(bt,r,n,Oe,le)}function Hn(e,t){let n=Ce[e].length;return[e*we+we/2+ae/2,height/2-(n-1)/2*ve+t*ve]}function $n(e,t){le=min(e,t)/1024,ae=100*le,ht=50*le,we=(e-ae)/Ve,ve=(t-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].lenM gth;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}xe=floor(De.length*de),Le=[],ke=[],ge=floor(map(de,.2,.8,15,2));for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,mt=sr(xt,gt,pt,e),bt=[],wt=[],yt=e/(Ve-1);for(let t=0;t<Ve;t++)bt.push(hr(mt,yt*t/e)),wt.push(hr(mt,yt*t/e));wt.unshift(bt[0]),wt.push(bt[bt.length-1])}function Xn(){const e=Ut.getBrainStatM us();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));foM r(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;nM ++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){letM e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le}function Wn(){jt.update();const e=4==Pe?0:Kt;jt.draw(Qe,ct,dt,e,le)}function Un(){if(!bn)return ar(),void et.image(je,0,0);if(4==Pe||5==Pe)return Wn(),void et.image(Qe,0,0);un>=Nt&&hn<Ve&&(hn++,un=0);for(let e=0;e<hn;e++)1==dt?it=ot=bt[e]:(it=ct,ot=bt[e]),Kn(e,it,ot,$e);un>=Nt&&cn<Ve-1&&(cn++,un=0);for(let e=0;e<cn;e++)Zn(e)}function qn(){et.background(ct),Ue.background(25M 5),Ue.rectMode(CENTER),ne(Ue),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),Ue.stroke(st),Ue.strokeWeight(8*le),Ue.fill(ct),Qe.background(255),Qe.rectMode(CENTER),ne(Qe),Qe.strokeWeight(le),qe.background(255),qe.rectMode(CENTER),ne(qe),qe.textAlign(LEFT),$e.background(255),$e.rectMode(CENTER),ne($e),Xe.background(255),ne(Xe),Xe.strokeWeight(Ne),We.background(255),We.rectMode(CENTER),ne(We),We.fill(st),We.stroke(st),We.strokeWeight(.1*le),er(lt),We.noStroke(),xn&&(We.rect(ae/16,height/2,ae/8,height),We.rect(width-aM e/16,height/2,ae/8,height),We.rect(width/2,ae/16,width,ae/8),We.rect(width/2,height-ae/16,width,ae/8)),Ze.background(255),Ze.rectMode(CENTER),ne(Ze),Ze.textAlign(CENTER,CENTER),Ze.textStyle(BOLD),Ze.stroke(st),Ze.strokeWeight(8*le),Ze.fill(ct),je.background(255),je.rectMode(CENTER),ne(je),je.textAlign(CENTER,CENTER),je.textStyle(BOLD),Ke.background(255),Ke.rectMode(CENTER),ne(Ke),Ke.textAlign(CENTER,CENTER),Ke.textStyle(BOLD),Ke.stroke(st),Ke.strokeWeight(8*le),Ke.fill(ct),Je.background(255),Je.rectMode(CENTER),ne(M Je),Je.textAlign(CENTER,CENTER),Je.textStyle(BOLD),Je.stroke(st),Je.strokeWeight(8*le),Je.fill(ct),Un(),et.image(We,0,0),Pt&&An(),et.image(Xe,0,0),et.image($e,0,0),At&&(tr(),et.image(Ue,0,0)),fn&&(lr(),et.image(Ze,0,0)),Lt&&(or(),et.image(Ke,0,0)),Dt&&(ir(),et.image(qe,0,0)),yn&&(Bn(),et.image(Je,0,0))}function draw(){const e=Date.now();bn&&(Ut.updateAge(new Date(e)),Xn()),qn(),image(et,0,0),zn||un++}function Zn(e){let t,n=Ce[e].length,r=Ce[e+1].length;for(let i=0;i<n;i++){const[n,o]=Hn(e,i);for(let a=0;a<r;a++){coM nst[r,l]=Hn(e+1,a);t=map(min(Ce[e][i],Ce[e+1][a]),0,1,0,.5),ur(n,o,r,l,bt[e],bt[e+1],Xe,t)}}}function Kn(e,t,n,r){let i,o,a,l=Ce[e].length;for(let s=0;s<l;s++){const[l,h]=Hn(e,s);i=Ce[e][s],a=map(Be,1/30,1,3,10),o=map(Ce[e][s],0,1,2*a,0)*le,o<1.5*le&&(o=0),Qn(l,h,ze,Oe,t,n,o,i,r)}}function Jn(e,t,n,r,i){for(let o=0;o<Le[e].length;o++)Qn(Le[e][o][0],Le[e][o][1],t,Oe,n,r,0,1,i)}function Qn(e,t,n,r,i,o,a,l,s){s.stroke(dr(o,map(l,0,1,.25,1))),s.fill(dr(i,map(l,0,1,.15,1))),s.strokeWeight(Fe),fr([a],s),3==dt&&s.fill(dr(M i,0)),1==r?s.ellipse(e,t,n):2==r?s.rect(e,t,7*n/8,7*n/8):3==r&&(s.beginShape(),s.vertex(e-4*n/7,t),s.vertex(e,t-4*n/7),s.vertex(e+4*n/7,t),s.vertex(e,t+4*n/7),s.endShape(CLOSE))}function er(e){if(1==e);else if(2==e){We.strokeWeight(1*le);for(let e=ht/4;e<width+ht/4;e+=ht)for(let t=ht/4;t<height+ht/4;t+=ht)We.point(e,t)}else if(3==e){ht=25*le;for(let e=ht/2;e<height+ht/2;e+=ht)We.line(0,e,width,e);for(let e=ht/2;e<width+ht/2;e+=ht)We.line(e,0,e,height)}}function tr(){Ue.textFont("Trebuchet MS"),Ue.textAlign(LEFT,CENM TER),Ue.noStroke(),pr(Ue,800*le,500*le),Ue.noStroke(),Ue.fill(dr(st,.75)),Ue.rect(width/2,height/2-100*le,800*le,300*le,25*le,25*le,0,0),Ue.fill(st),Ue.rect(width/2-250*le,height/2-100*le,225*le,225*le),Ue.image(se.elt,width/2-357.5*le,height/2-207.5*le,215*le,215*le);let e=100*Zt[0][0];Ue.fill(ct),Ue.textSize(25*le),Ue.textStyle(NORMAL),1==me&&(e>=0&&e<20?Ue.text("I have a feeling this image belongs to",width/2-100*le,height/2-170*le):e>=20&&e<40?Ue.text("I have a hunch this image belongs to",width/2-100*le,heightM /2-170*le):e>=40&&e<60?Ue.text("I think this image belongs to",width/2-100*le,height/2-170*le):e>=60&&e<80?Ue.text("I'm almost certain this image belongs to",width/2-100*le,height/2-170*le):Ue.text("I'm positive this image belongs to",width/2-100*le,height/2-170*le));let t=e.toFixed(2);"100.00"==t&&(t="100"),1==me&&Ue.text("I'm "+t+"% confident that I'm right!",width/2-100*le,height/2-25*le),example=Zt.map((e=>e[1])),be=Ue.textWidth('"FIDENZAAAA"'),defaultPhrase=Ue.textWidth('"PERPENDICULAR INHABITATION"'),Ue.textSM tyle(BOLD);const n=me?example[0]:random(example);if(1===n.split(" ").length){let e=75*be/Ue.textWidth('"'+n+'"');e>75&&(e=75),Ue.textSize(e*le),Ue.text('"'+n+'"',width/2-100*le,height/2-90*le)}else nr(width/2-100*le,height/2-90*le,460*le,110*le,n,Ue);if(millis()-ye>1500&&(me=!0),C(tt,nt,st,ct,Pe,Mt),Ue.image(nt,width/2-370*le,height/2+70*le,80*le,80*le),3==Pe){let e;e=map(Mt,50,60,.25,1.3),I(rt,e),Ue.image(rt,width/2-370*le,height/2+70*le,80*le,80*le)}let r,i;Ue.image(tt,width/2-370*le,height/2+70*le,80*le,80*le),UM e.fill(xt),Ue.textSize(40*le),Ue.text("INTELLIGENCE INFO",width/2-275*le,height/2+115*le),Ue.textSize(18*le),Ue.textStyle(NORMAL),Ue.circle(width/2-360*le,height/2+180*le,7.5*le),1==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s growing and getting smarter by the day.`:2==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s stable and it has reached peak performance.`:3==Pe&&(r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s decaying and losing its luster.`),i=2==Pe?"The Perceptron remainM s stable for some time before entering the decay phase.":`Wait until ${new Date(an).toLocaleString("en-US")} for your Perceptron to reach its peak performance.`,Ue.text(r,width/2-350*le,height/2+180*le),Ue.circle(width/2-360*le,height/2+210*le,7.5*le),Ue.text(i,width/2-350*le,height/2+210*le),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),gr(Ue,width/2-225*le,width/2+65*le,height/2+265*le,height/2+305*le,"SELECT ANOTHER IMAGE"),gr(Ue,width/2+75*le,width/2+225*le,height/2+265*le,height/2+305*le,"CLOSE")}function nr(M e,t,n,r,i,o){let a=i.split(" "),l=75*be/o.textWidth('"'+i+'"'),s=0,h=[],c=[],u=[],f="",d="";if(l>=50)l>75&&(l=75),o.textSize(l*le),o.text('"'+i+'"',e,t);else if(l<50){if(l=50*defaultPhrase/o.textWidth('"'+i+'"'),l>30){if(l>50&&(l=50),[f,d]=rr(l,n,s,h,c,a,f,d,Ue),0==c.length)return o.textSize(l*le),void o.text('"'+i+'"',e,t);for(s=0,h=[],c=[];o.textWidth(d)>n/le;)l=l*n/le/o.textWidth(d),f="",d="",[f,d]=rr(l,n,s,h,c,a,f,d,Ue)}else{l=30,o.textSize(l);for(let e=0;e<a.length;e++)s+=o.textWidth(" "+a[e]),s<=n/le?h.push(aM [e]):s>n/le&&s<=n/le*2?c.push(a[e]):u.push(a[e]);for(let e=1;e<h.length;e++)f=f+" "+h[e];if(f='"'+h[0]+f,0==u.length){for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+c[c.length-1]+'"'}else if(1==c.length)d="... "+u[u.length-1]+'"';else{for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+"... "+u[u.length-1]+'"'}}o.textSize(l*le);let r=1.25*(o.textDescent()+o.textAscent());o.text(f,e,t-r/2),o.text(d,e,t+r/2)}}function rr(e,t,n,r,i,o,a,l,s){s.textSize(e);for(let e=0;e<o.length;e++)(n+=s.textWidth(" "+o[e]))<=t/le?r.push(o[e]M ):i.push(o[e]);for(let e=1;e<r.length;e++)a=a+" "+r[e];if(a='"'+r[0]+a,0==i.length&&(a+='"',l=""),1==i.length)l=i[i.length-1]+'"';else{for(let e=0;e<i.length-1;e++)l=l+i[e]+" ";l=l+i[i.length-1]+'"'}return[a,l]}function ir(){const e=45*le;qe.textFont("Tahoma"),qe.stroke(st),qe.strokeWeight(2*le),qe.fill(ct),qe.rect(width/2,e/2+height-87.5*le,600*le,90*le),qe.fill(st),qe.rect(width/2-150*le,e+height-170*le,300*le,30*le),qe.fill(ct),qe.rect(width/2+150*le,e+height-170*le,300*le,30*le),qe.noStroke(),qe.fill(ct),qe.texM tSize(15*le),qe.textStyle(BOLD),qe.text("PERCEPTRON INFORMATION",width/2-285*le,e+height-165*le),qe.fill(xt),qe.text("ARTWORK NAME:",width/2+10*le,e+height-165*le),qe.textAlign(RIGHT),qe.textStyle(ITALIC),qe.text("Perceptron #"+Et,width/2+285*le,e+height-165*le);const[t,n]=It.split(" ");let r;"60 Years"===It?r="1 Year":"60 Months"===It?r="1 Month":"60 Weeks"===It?r="1 Week":"60 Days"===It?r="1 Day":"12 Hours"===It&&(r="12 Minutes"),data=[["AI MODEL NAME:",B(12*le,Ht,140*le)],["SCALE:","1:"+Te],["NUMBER OF CLASSES:"M ,$t.length],["BIRTH YEAR:",Rt],["NUMBER OF REBIRTHS:",sn.toString()],["AGE:",`${Math.ceil(Mt)} Perceptron Years`],["ONE PERCEPTRON YEAR:",`${r}`],["STATE:",Ot[Pe]],["ACTIVE NEURONS:",`${round(ln*rn)} / ${ln}`],["NEXT STATE TIME:",vr(new Date(on))]],qe.fill(xt);const i=data.length/2;for(let t=0;t<data.length;++t){const n=t<i,r=n?width/2-285*le:width/2+10*le,o=n?width/2-10*le:width/2+285*le,a=e+height-(135-t%i*15)*le;qe.textStyle(BOLD),qe.textAlign(LEFT),qe.textSize(12*le),qe.text(data[t][0],r,a),qe.textStyle(ITALIC)M ,qe.textAlign(RIGHT),qe.textSize(12*le),qe.text(data[t][1],o,a)}}function or(){Ke.textFont("Trebuchet MS"),Ke.noStroke(),pr(Ke,600*le,200*le),gr(Ke,width/2-155*le,width/2-5*le,height/2+115*le,height/2+155*le,"UPDATE"),gr(Ke,width/2+5*le,width/2+155*le,height/2+115*le,height/2+155*le,"CLOSE"),Ke.textAlign(LEFT),Ke.fill(xt),Ke.text("UPDATE BITCOIN FULL NODE ADDRESS",width/2-252.5*le,height/2-55*le),Ke.text("UPDATE MODEL ADDRESS",width/2-252.5*le,height/2+20*le),Ke.textAlign(RIGHT),Ke.textStyle(ITALIC),Ke.textSize(15*M le),0==wn&&Ke.text("(*) Invalid Address",width/2+252.5*le,height/2-53*le),0==vn&&Ke.text("(*) Invalid Model",width/2+252.5*le,height/2+23*le)}function ar(){je.textFont("Trebuchet MS"),je.fill(st),je.textSize(50*le),je.stroke(st),je.strokeWeight(1*le),je.text("main()",width/2,height/2)}function lr(){un>=20&&1==dn&&(dn=!1,un=0),dn&&(Ze.textFont("Trebuchet MS"),Ze.stroke(st),Ze.fill(ct),Ze.rect(width/2,height/2,600*le,150*le,25*le),Ze.fill(xt),Ze.textSize(75*le),Ze.noStroke(),1==Pe?Ze.text("GROWING",width/2,height/2+5M *le):3==Pe?Ze.text("AGING",width/2,height/2+5*le):4==Pe?Ze.text("DEAD",width/2,height/2+5*le):5==Pe&&Ze.text("BIRTH",width/2,height/2+5*le)),un>=20&&0==dn&&(dn=!0,un=0,Bt++,3==Bt&&(fn=!1))}function sr(e,t,n,r){let i=[],o=r/(n.length+1),a=color(e),l=color(t);i.push(a);for(let e=0;e<n.length;e++){let t=color(n[e]);for(let e=1;e<=o;e++){let n=lerpColor(a,t,e/o);i.push(n)}a=t}for(let e=1;e<o;e++){let t=lerpColor(a,l,e/o);i.push(t)}if(i.push(l),i.length>r)i.splice(r);else if(i.length<r){let e=i[i.length-1];for(;i.lengthM <r;)i.push(e)}return i}function hr(e,t){let n=e.length,r=Math.floor(t*n);return r>=n&&(r=n-1),e[r]}function cr(e){e=e.replace("#","");var t=parseInt(e,16);return color(t>>16&255,t>>8&255,255&t)}function ur(e,t,n,r,i,o,a,l){var s=a.drawingContext.createLinearGradient(e,t,n,r);s.addColorStop(0,i),s.addColorStop(1,o),a.drawingContext.strokeStyle=s,a.drawingContext.globalAlpha=l,a.line(e,t,n,r),a.drawingContext.globalAlpha=1}function fr(e,t){t.drawingContext.setLineDash(e)}function dr(e,t){let n=color(e),r=red(n),i=greM en(n),o=blue(n);return color(r,i,o,255*t)}function xr(e,t,n,r){return mouseX>e&&mouseX<t&&mouseY>n&&mouseY<r}function gr(e,t,n,r,i,o){e.strokeWeight(1*le),e.stroke(st);const[a,l]=xr(t,n,r,i)?[xt,ct]:[ct,xt];e.fill(a),e.push(),e.rectMode(CORNERS),e.rect(t,r,n,i,5*le),e.pop(),e.noStroke(),e.textSize(20*le),e.fill(l),e.text(o,(t+n)/2,(46*r+54*i)/100)}function pr(e,t,n){e.fill(0,0,0,75),e.rect(width/2,height/2,width,height),e.stroke(st),e.fill(ct),e.rect(width/2,height/2,t,n,25*le)}function mr(e,t){resizeCanvas(e,t,!0)M ,Xe.resizeCanvas(e,t,!0),$e.resizeCanvas(e,t,!0),We.resizeCanvas(e,t,!0),Ue.resizeCanvas(e,t,!0),qe.resizeCanvas(e,t,!0),Qe.resizeCanvas(e,t,!0),je.resizeCanvas(e,t,!0),Ze.resizeCanvas(e,t,!0),Ke.resizeCanvas(e,t,!0),Je.resizeCanvas(e,t,!0),et.resizeCanvas(e,t,!0)}function br(e,t,n,r,i,o){const a=J(e);return a.position(t,n),a.size(r,i),a.style("opacity","0"),a.mouseClicked(o),a}function yr(){return null!=vt&&vt?.isFocused()||null!=zt&&zt?.isFocused()}function wr(e,t,n,r){let i;if(e<=3){i=`Hey ${String.fromCodePointM (128075)}, I'm ${n}, ${t} years old. I can detect ${r.length} NFT collections: `;let e=0;for(let t=0;t<r.length;++t){const n=r[t];if(e+n.length>500){i+=", etc";break}t==r.length-1?i+=", and ":t>0&&(i+=", "),i+=n,e+=n.length}i+=". ",t<=5?i+="However, I am only a baby, so my recognition ability is not accurate. I'm in the state of Growing both looks and intelligence.":t<=13?i+="I am now a child. My recognition ability is becoming better, but still not very accurate. I'm in the state of Growing both looks and intelligM ence.":t<=25?i+="I have grown up to be a teen. My recognition ability almost reaches the peak, but I will still mess up sometimes. I'm in the state of Growing both looks and intelligence.":t<=50?i+="I finally reach adulthood. My recognition is fully functional now. I'm in the Stable state, where I am the most intelligent with all neurons activated.":t<=60&&(i+="I am now an old Perceptron, so my recognition ability is no longer the best. I'm in the Decaying state, meaning that my neurons are dying, and my intelligenM ce is decreasing over time.")}else 4==e?i=`${n} is Dead. However, this is not the end to its story...`:5==e&&(i=`${n} is now in the Rebirth state, and is preparing to start a new life.`);return i}function vr(e){const t=e.getDate(),n=e.toLocaleString("en-US",{month:"long"}),r=e.getFullYear();let i=e.getHours().toString();1==i.length&&(i="0"+i);let o=e.getMinutes().toString();return 1==o.length&&(o="0"+o),`${Y(t)} ${n} ${r} | ${i}:${o}`}saveCanvasAtCurrentTime=()=>{save(N())},save4KCanvasAtCurrentTime=()=>{const e=wiM dth,t=height,n=min(4096/min(e,t),1e4/max(e,t)),r=e*n,i=t*n;mr(r,i),zn=!0,$n(r,i),qn();let o="4K_"+N()+".png";saveCanvas(et,o),mr(e,t),$n(e,t),zn=!1};const zr=[["60 Years",3,365],["60 Months",40,30],["60 Weeks",37,7],["60 Days",20,1]],Vr=[["1943",1],["1951",1.5],["1957",2],["1969",2.5],["1970",3],["1980",3.5],["1982",4],["1986",4.5],["1988",5],["1997",5.5],["1998",6],["2002",6.5],["2009",7],["2012",7.5],["2014",8],["2015",8.5],["2016",9],["2023",15]],_r=[["Plain",20],["Dotted",40],["Squared",40]],Mr=[["Basic",30],["M Standard",60],["Advanced",10]],Er=[["MNIST",70],["CIFAR",25],["IMAGENET",5]],Sr=[["Theano",60],["Torch",30],["TensorFlow",10]],Rr=[["Whitepaper",2],["Blackboard",2],["Blueprint",2],["Nak",74/14],["Jims",74/14],["Level 10",74/14],["Flips",74/14],["Level 14",74/14],["III",74/14],["XMB",74/14],["Info",74/14],["Adventure",74/14],["Marigold",74/14],["Phoenix",74/14],["Love",74/14],["Cachet",74/14],["Human",74/14],["Twilight",3],["Sunset",3],["Aurora",3],["Liminal Space",3],["D Vu",3],["Lucid Dream",3],["Parallel",1M ],["Multiverse",1]];function Ir(e){for(let e=0;e<100;++e)random(1);return{visual:{pattern:k(_r),hardwareAcceleration:k(Mr),nodeFill:k(Er),nodeShape:k(Sr),colorPalette:k(Rr),lifeCycle:k(zr),birthYear:k(Vr)},training:e}}function Cr(e){window.$generativeTraits={"Network Architecture":e.training.structure_gen,"Hidden Layers":e.training.n_layers,"Max Neurons Per Hidden Layer":e.training.max_nodes,"Activation Function":e.training.activation_func,"Training Epochs":e.training.epoch_num,Dataset:e.visual.nodeFill,"Deep LearnM ing Framework":e.visual.nodeShape,"Hardware Acceleration":e.visual.hardwareAcceleration,"Paper Pattern":e.visual.pattern,"Life Cycle":e.visual.lifeCycle,"Birth Year":e.visual.birthYear,"Color Palette":e.visual.colorPalette}} <script defer src="https://static.cloudflareinsights.com/beacon.min.js/v2b4487d741ca48dcbadcaf954e159fc61680799950996" integrity="sha512-D/jdE0CypeVxFadTejKGTzmwyV10c1pxZk/AqjJuZbaJwGMyNHY3q/mTPWqMUnFACfCTunhZUVcd4cV78dK1pQ==" data-cf-beacon='{"rayId":"7b48a78ea9d653e9","versionL{":"2023.3.0","b":1,"token":"6c07c178c94442f695e7a0a2aaee641a","si":100}' crossorigin="anonymous"></script> {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "golden armor"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "midas touch"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "golden armor"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"JEUS","amt":"777"}h! {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "tiger"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "undead"}, {"trait_type": "Artifacts", "value": "axe"}]} text/plain;charset=utf-8 {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "moon"}, {"trait_type": "Body", "value": "mage robes"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "dagger"}]} text/html;charset=utf-8 <meta charset="utf-8" /> position: relative; width: var(--width); height: var(--height); border: 1px solid blue; position: relative; <div id="upload"> <input id="inputUpload" type="file"> function e(e){"use strict";return new function e(t){let n="global"==t?window:this;n.canvas=document.createElement("canvas");let r=n.canvas.getContext("2d");n.width=100,n.height=100,n.canvas.width=n.width,n.canvas.height=n.height,"offscreen"!=t&&(document.body?document.body.appendChild(n.canvas):window.addEventListener("load",(function(){document.body.appendChild(n.canvas)}))),g(),n.MAGIC=161533525,n.RGB=0,n.HSV=1,n.HM SB=1,n.CHORD=0,n.PIE=1,n.OPEN=2,n.RADIUS=1,n.CORNER=2,n.CORNERS=3,n.ROUND="round",n.SQUARE="butt",n.PROJECT="square",n.MITER="miter",n.BEVEL="bevel",n.CLOSE=1,n.BLEND="source-over",n.REMOVE="destination-out",n.ADD="lighter",n.DARKEST="darken",n.LIGHTEST="lighten",n.DIFFERENCE="difference",n.SUBTRACT="subtract",n.EXCLUSION="exclusion",n.MULTIPLY="multiply",n.SCREEN="screen",n.REPLACE="copy",n.OVERLAY="overlay",n.HARD_LIGHT="hard-light",n.SOFT_LIGHT="soft-light",n.DODGE="color-dodge",n.BURN="color-burn",n.NORMAL="norM mal",n.ITALIC="italic",n.BOLD="bold",n.BOLDITALIC="italic bold",n.CENTER="center",n.LEFT="left",n.RIGHT="right",n.TOP="top",n.BOTTOM="bottom",n.BASELINE="alphabetic",n.LANDSCAPE="landscape",n.PORTRAIT="portrait",n.ALT=18,n.BACKSPACE=8,n.CONTROL=17,n.DELETE=46,n.DOWN_ARROW=40,n.ENTER=13,n.ESCAPE=27,n.LEFT_ARROW=37,n.OPTION=18,n.RETURN=13,n.RIGHT_ARROW=39,n.SHIFT=16,n.TAB=9,n.UP_ARROW=38,n.HALF_PI=Math.PI/2,n.PI=Math.PI,n.QUARTER_PI=Math.PI/4,n.TAU=2*Math.PI,n.TWO_PI=2*Math.PI,n.THRESHOLD=1,n.GRAY=2,n.OPAQUE=3,n.INVEM RT=4,n.POSTERIZE=5,n.DILATE=6,n.ERODE=7,n.BLUR=8,n.ARROW="default",n.CROSS="crosshair",n.HAND="pointer",n.MOVE="move",n.TEXT="text",n.VIDEO={video:!0,audio:!1},n.AUDIO={video:!1,audio:!0},n.SHR3=1,n.LCG=2,n.HARDWARE_FILTERS=!0,n.hint=function(e,t){n[e]=t},n.frameCount=0,n.mouseX=0,n.mouseY=0,n.pmouseX=0,n.pmouseY=0,n.mouseButton=null,n.keyIsPressed=!1,n.mouseIsPressed=!1,n.key=null,n.keyCode=null,n.pixels=null,n.accelerationX=0,n.accelerationY=0,n.accelerationZ=0,n.rotationX=0,n.rotationY=0,n.rotationZ=0,n.relRotatM ionX=0,n.relRotationY=0,n.relRotationZ=0,n.pAccelerationX=0,n.pAccelerationY=0,n.pAccelerationZ=0,n.pRotationX=0,n.pRotationY=0,n.pRotationZ=0,n.pRelRotationX=0,n.pRelRotationY=0,n.pRelRotationZ=0,n.touches=[],n._styleCache=[{colorMode:n.RGB,noStroke:!1,noFill:!1,ellipseMode:n.CENTER,rectMode:n.CORNER,curveDetail:20,curveAlpha:0,textFont:"sans-serif",textSize:12,textLeading:12,textStyle:"normal"}],n._style=n._styleCache[n._styleCache.length-1],n._noLoop=!1,n._pixelDensity=1,n._frameRate=null,n._tint=null;let i=nullM ,o=!0,a=[],l=null,s=0,h={},c=0,u=null,f=null,d=null;Object.defineProperty(n,"deviceOrientation",{get:function(){return 90==Math.abs(window.orientation)?n.LANDSCAPE:n.PORTRAIT}}),Object.defineProperty(n,"windowWidth",{get:function(){return window.innerWidth}}),Object.defineProperty(n,"windowHeight",{get:function(){return window.innerHeight}}),Object.defineProperty(n,"drawingContext",{get:function(){return r}}),n.createCanvas=function(e,t){return n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t,g(),n.canvas},nM .resizeCanvas=function(e,t){n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t},n.createGraphics=n.createImage=function(t,n){let r=new e("offscreen");return r.createCanvas(t,n),r.noLoop(),r},n.pixelDensity=function(e){return null==e||(n._pixelDensity=e,n.canvas.width=Math.ceil(n.width*e),n.canvas.height=Math.ceil(n.height*e),n.canvas.style.width=n.width+"px",n.canvas.style.height=n.height+"px",r.scale(n._pixelDensity,n._pixelDensity),g()),n._pixelDensity},n.map=function(e,t,n,r,i,o){let a=r+1*(e-t)/(n-t)*(i-r)M ;return o?r<i?Math.min(Math.max(a,r),i):Math.min(Math.max(a,i),r):a},n.lerp=function(e,t,n){return e*(1-n)+t*n},n.constrain=function(e,t,n){return Math.min(Math.max(e,t),n)},n.dist=function(){return 4==arguments.length?Math.hypot(arguments[0]-arguments[2],arguments[1]-arguments[3]):Math.hypot(arguments[0]-arguments[3],arguments[1]-arguments[4],arguments[2]-arguments[5])},n.norm=function(e,t,r){return n.map(e,t,r,0,1)},n.sq=function(e){return e*e},n.fract=function(e){return e-Math.floor(e)},n.degrees=function(e){retM urn 180*e/Math.PI},n.radians=function(e){return e*Math.PI/180},n.abs=Math.abs,n.ceil=Math.ceil,n.exp=Math.exp,n.floor=Math.floor,n.log=Math.log,n.mag=Math.hypot,n.max=Math.max,n.min=Math.min,n.round=Math.round,n.sqrt=Math.sqrt,n.sin=Math.sin,n.cos=Math.cos,n.tan=Math.tan,n.asin=Math.asin,n.acos=Math.acos,n.atan=Math.atan,n.atan2=Math.atan2,n.Vector=function(e,t,r){let i=this;i.x=e||0,i.y=t||0,i.z=r||0;let o=null,a=null;function l(e,t,n){return null!=e.x?e:null!=t?{x:e,y:t,z:n||0}:{x:e,y:e,z:e}}function s(){null==a&M &(a=i.x*i.x+i.y*i.y+i.z*i.z,o=Math.sqrt(a))}function h(){a=null,o=null}i.set=function(e,t,n){i.x=e||0,i.y=t||0,i.z=n||0},i.copy=function(){return new n.Vector(i.x,i.y,i.z)},i.add=function(){let e=l.apply(null,arguments);return i.x+=e.x,i.y+=e.y,i.z+=e.z,h(),i},i.rem=function(){let e=l.apply(null,arguments);return i.x%=e.x,i.y%=e.y,i.z%=e.z,h(),i},i.sub=function(){let e=l.apply(null,arguments);return i.x-=e.x,i.y-=e.y,i.z-=e.z,h(),i},i.mult=function(){let e=l.apply(null,arguments);return i.x*=e.x,i.y*=e.y,i.z*=e.z,hM (),i},i.div=function(){let e=l.apply(null,arguments);return i.x/=e.x,i.y/=e.y,i.z/=e.z,h(),i},i.mag=function(){return s(),o},i.magSq=function(){return s(),a},i.dot=function(){let e=l.apply(null,arguments);return i.x*e.x+i.y*e.y+i.z*e.z},i.dist=function(){let e=l.apply(null,arguments),t=i.x-e.x,n=i.y-e.y,r=i.z-e.z;return Math.sqrt(t*t+n*n+r*r)},i.cross=function(){let e=l.apply(null,arguments),t=i.y*e.z-i.z*e.y,n=i.z*e.x-i.x*e.z,r=i.x*e.y-i.y*e.x;return i.x=t,i.y=n,i.z=r,h(),i},i.normalize=function(){s();let e=o;retuM rn i.x/=e,i.y/=e,i.z/=e,o=1,a=1,i},i.limit=function(e){s();if(o>e){let t=e/o;i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e}return i},i.setMag=function(e){s();let t=e/o;return i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e,i},i.heading=function(){return Math.atan2(i.y,i.x)},i.rotate=function(e){let t=Math.cos(e),n=Math.sin(e),r=i.x*t-i.y*n,o=i.x*n+i.y*t;return i.x=r,i.y=o,i},i.angleBetween=function(){let e=l.apply(null,arguments);const t=i.dot(e)/(i.mag()*e.mag());let n;return n=Math.acos(Math.min(1,Math.max(-1,t))),n*Math.sign(i.cross(e).z||1)},M i.lerp=function(e,t){return i.x=i.x*(1-t)+e.x*t,i.y=i.y*(1-t)+e.y*t,i.z=i.z*(1-t)+e.z*t,h(),i},i.reflect=function(e){return e.normalize(),i.sub(e.mult(2*i.dot(e)))},i.array=function(){return[i.x,i.y,i.z]},i.equals=function(e,t){return null==t&&null==(t=Number.EPSILON)&&(t=0),Math.abs(e.x-i.x)<t&&Math.abs(e.y-i.y)<t&&Math.abs(e.z-i.z)<t},i.fromAngle=function(e,t){return null==t&&(t=1),o=t,a=t*t,i.x=t*Math.cos(e),i.y=t*Math.sin(e),i.z=0,i},i.fromAngles=function(e,t,n){null==n&&(n=1),o=n,a=n*n;const r=Math.cos(t),l=MaM th.sin(t),s=Math.cos(e),h=Math.sin(e);return i.x=n*h*l,i.y=-n*s,i.z=n*h*r,i},i.random2D=function(){return o=1,a=1,i.fromAngle(Math.random()*Math.PI*2)},i.random3D=function(){return o=1,a=1,i.fromAngles(Math.random()*Math.PI*2,Math.random()*Math.PI*2)},i.toString=function(){return`[${i.x}, ${i.y}, ${i.z}]`}},n.Vector.add=function(e,t){return new n.Vector(e.x+t.x,e.y+t.y,e.z+t.z)},n.Vector.rem=function(e,t){return new n.Vector(e.x%t.x,e.y%t.y,e.z%t.z)},n.Vector.sub=function(e,t){return new n.Vector(e.x-t.x,e.y-t.y,e.M z-t.z)},n.Vector.mult=function(e,t){return null==t.x?new n.Vector(e.x*t,e.y*t,e.z*t):new n.Vector(e.x*t.x,e.y*t.y,e.z*t.z)},n.Vector.div=function(e,t){return null==t.x?new n.Vector(e.x/t,e.y/t,e.z/t):new n.Vector(e.x/t.x,e.y/t.y,e.z/t.z)},n.Vector.dist=function(e,t){return Math.hypot(e.x-t.x,e.y-t.y,e.z-t.z)},n.Vector.cross=function(e,t){return new n.Vector(e.y*t.z-e.z*t.y,e.z*t.x-e.x*t.z,e.x*t.y-e.y*t.x)},n.Vector.lerp=function(e,t,r){return new n.Vector(e.x*(1-r)+t.x*r,e.y=e.y*(1-r)+t.y*r,e.z=e.z*(1-r)+t.z*r)},n.M Vector.equals=function(e,t,n){return e.equals(t,n)};for(let e of["fromAngle","fromAngles","random2D","random3D"])n.Vector[e]=function(t,r,i){return(new n.Vector)[e](t,r,i)};function x(e,t,n){let r,i,o,a,l,s,h,c,u;if(0==t)return[255*(r=n),255*(i=n),255*(o=n)];switch((a=e)>360&&(a=0),h=n*(1-t),c=n*(1-t*(s=(a/=60)-(l=~~a))),u=n*(1-t*(1-s)),l){case 0:r=n,i=u,o=h;break;case 1:r=c,i=n,o=h;break;case 2:r=h,i=n,o=u;break;case 3:r=h,i=c,o=n;break;case 4:r=u,i=h,o=n;break;default:r=n,i=h,o=c}return[255*r,255*i,255*o]}functioM n g(){r.fillStyle="white",r.strokeStyle="black",r.lineCap="round",r.lineJoin="miter"}function p(e){if(0<=e&&e<2*Math.PI)return e;for(;e<0;)e+=2*Math.PI;for(;e>=Math.PI;)e-=2*Math.PI;return e}function m(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;let c=p(a),u=p(l);r.beginPath();for(let a=0;a<h+1;a++){let l=a/h,s=n.lerp(c,u,l),f=Math.cos(s)*i/2,d=Math.sin(s)*o/2;r[a?"lineTo":"moveTo"](e+f,t+d)}s==n.CHORD?r.closePath():s==n.PIE&&(r.lineTo(e,t),r.closePath()),n._style.noFill||r.fill(),n._style.noStrokM e||r.stroke()}function b(e,t,i,o){n._style.noFill&&n._style.noStroke||(r.beginPath(),r.ellipse(e,t,i/2,o/2,0,0,2*Math.PI),n._style.noFill||r.fill(),n._style.noStroke||r.stroke())}function y(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;if(null==a)return function(e,t,i,o){n._style.noFill||r.fillRect(e,t,i,o),n._style.noStroke||r.strokeRect(e,t,i,o)}(e,t,i,o);if(null==l)return y(e,t,i,o,a,a,a,a);const c=Math.min(Math.abs(o),Math.abs(i))/2;a=Math.min(c,a),l=Math.min(c,l),h=Math.min(c,h),s=Math.min(c,s)M ,r.beginPath(),r.moveTo(e+a,t),r.arcTo(e+i,t,e+i,t+o,l),r.arcTo(e+i,t+o,e,t+o,s),r.arcTo(e,t+o,e,t,h),r.arcTo(e,t,e+i,t,a),r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke()}function w(){a=[]}n.createVector=function(e,t,r){return new n.Vector(e,t,r)},n.curvePoint=function(e,t,n,r,i){const o=i*i*i,a=i*i;return e*(-.5*o+a-.5*i)+t*(1.5*o-2.5*a+1)+n*(-1.5*o+2*a+.5*i)+r*(.5*o-.5*a)},n.bezierPoint=function(e,t,n,r,i){const o=1-i;return Math.pow(o,3)*e+3*Math.pow(o,2)*i*t+3*o*Math.pow(i,2)*n+Math.pow(i,M 3)*r},n.curveTangent=function(e,t,n,r,i){const o=i*i;return e*(-3*o/2+2*i-.5)+t*(9*o/2-5*i)+n*(-9*o/2+4*i+.5)+r*(3*o/2-i)},n.bezierTangent=function(e,t,n,r,i){const o=1-i;return 3*r*Math.pow(i,2)-3*n*Math.pow(i,2)+6*n*o*i-6*t*o*i+3*t*Math.pow(o,2)-3*e*Math.pow(o,2)},n.Color=function(e,t,n,r){let i=this;i.MAGIC=786698,i._r=e,i._g=t,i._b=n,i._a=r,i._h=0,i._s=0,i._v=0,i._hsvInferred=!1,i.setRed=function(e){i._r=e,i._hsvInferred=!1},i.setGreen=function(e){i._g=e,i._hsvInferred=!1},i.setBlue=function(e){i._b=e,i._hsvInfM erred=!1},i.setAlpha=function(e){i._a=e/255,i._hsvInferred=!1},i._inferHSV=function(){i._hsvInferred||([i._h,i._s,i._v]=function(e,t,n){let r,i,o,a,l;return r=e<t?e<n?e:n:t<n?t:n,0==(l=100*(i=e>t?e>n?e:n:t>n?t:n)/255)?[o=0,a=0,l]:0==(a=100*(i-r)/i)?[o=0,a,l]:(o=i==e?0+60*(t-n)/(i-r):i==t?120+60*(n-e)/(i-r):240+60*(e-t)/(i-r),[o,a,l])}(i._r,i._g,i._b),i._hsvInferred=!0)},i.toString=function(){return`rgba(${Math.round(i._r)},${Math.round(i._g)},${Math.round(i._b)},${~~(1e3*i._a)/1e3})`}},n.colorMode=function(e){n._stM yle.colorMode=e},n.color=function(){if(1==arguments.length&&786698==arguments[0].MAGIC)return arguments[0];if(n._style.colorMode==n.RGB){if(1==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],1);if(2==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],arguments[1]/255);if(3==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],1);if(4==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],arguments[3]/255)}else{if(1==argumeM nts.length)return new n.Color(...x(0,0,arguments[0]/100),1);if(2==arguments.length)return new n.Color(...x(0,0,arguments[0]/100),arguments[1]/255);if(3==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),1);if(4==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),arguments[3])}return null},n.red=function(e){return e._r},n.green=function(e){return e._g},n.blue=function(e){return e._b},n.alpha=function(e){return 255*e._a},n.hue=function(e){reM turn e._inferHSV(),e._h},n.saturation=function(e){return e._inferHSV(),e._s},n.brightness=function(e){return e._inferHSV(),e._v},n.lightness=function(e){return 100*(.2126*e._r+.7152*e._g+.0722*e._b)/255},n.lerpColor=function(e,t,r){return n._style.colorMode==n.RGB?new n.Color(n.constrain(n.lerp(e._r,t._r,r),0,255),n.constrain(n.lerp(e._g,t._g,r),0,255),n.constrain(n.lerp(e._b,t._b,r),0,255),n.constrain(n.lerp(e._a,t._a,r),0,1)):(e._inferHSV(),t._inferHSV(),new n.Color(n.constrain(function(e,t,r){var i=[[Math.abs(t-M e),n.map(r,0,1,e,t)],[Math.abs(t+360-e),n.map(r,0,1,e,t+360)],[Math.abs(t-360-e),n.map(r,0,1,e,t-360)]];return i.sort(((e,t)=>e[0]-t[0])),(i[0][1]+720)%360}(e._h,t._h,r),0,360),n.constrain(n.lerp(e._s,t._s,r),0,100),n.constrain(n.lerp(e._v,t._v,r),0,100),n.constrain(n.lerp(e._a,t._a,r),0,1)))},n.strokeWeight=function(e){n._style_noStroke=!1,r.lineWidth=e},n.stroke=function(){if(n._style.noStroke=!1,"string"==typeof arguments[0])return void(r.strokeStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._sM tyle.noStroke=!0:r.strokeStyle=e},n.noStroke=function(){n._style.noStroke=!0},n.fill=function(){if(n._style.noFill=!1,"string"==typeof arguments[0])return void(r.fillStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._style.noFill=!0:r.fillStyle=e},n.noFill=function(){n._style.noFill=!0},n.blendMode=function(e){r.globalCompositeOperation=e},n.strokeCap=function(e){r.lineCap=e},n.strokeJoin=function(e){r.lineJoin=e},n.ellipseMode=function(e){n._style.ellipseMode=e},n.rectMode=function(e){n._style.rectM Mode=e},n.curveDetail=function(e){n._style.curveDetail=e},n.curveAlpha=function(e){n._style.curveAlpha=e},n.curveTightness=function(e){n._style.curveAlpha=e},n.clear=function(){r.clearRect(0,0,n.width,n.height)},n.background=function(){if(arguments[0]&&arguments[0].MAGIC==n.MAGIC)return n.image(arguments[0],0,0,n.width,n.height);r.save(),r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity),r.fillStyle="string"==typeof arguments[0]?arguments[0]:n.color(...Array.from(arguments)),r.fillRect(0,0,n.width,n.heightM ),r.restore()},n.line=function(e,t,i,o){n._style.noStroke||(r.beginPath(),r.moveTo(e,t),r.lineTo(i,o),r.stroke())},n.arc=function(e,t,r,i,o,a,l,s){if(o==a)return n.ellipse(e,t,r,i);null==s&&(s=25),null==l&&(l=n.PIE),n._style.ellipseMode==n.CENTER?m(e,t,r,i,o,a,l,s):n._style.ellipseMode==n.RADIUS?m(e,t,2*r,2*i,o,a,l,s):n._style.ellipseMode==n.CORNER?m(e+r/2,t+i/2,r,i,o,a,l,s):n._style.ellipseMode==n.CORNERS&&m((e+r)/2,(t+i)/2,r-e,i-t,o,a,l,s)},n.ellipse=function(e,t,r,i){null==i&&(i=r),n._style.ellipseMode==n.CENTERM ?b(e,t,r,i):n._style.ellipseMode==n.RADIUS?b(e,t,2*r,2*i):n._style.ellipseMode==n.CORNER?b(e+r/2,t+i/2,r,i):n._style.ellipseMode==n.CORNERS&&b((e+r)/2,(t+i)/2,r-e,i-t)},n.circle=function(e,t,r){return n.ellipse(e,t,r,r)},n.point=function(e,t){e.x&&(t=e.y,e=e.x),r.beginPath(),r.ellipse(e,t,.4,.4,0,0,2*Math.PI),r.stroke()},n.rect=function(e,t,r,i,o,a,l,s){n._style.rectMode==n.CENTER?y(e-r/2,t-i/2,r,i,o,a,l,s):n._style.rectMode==n.RADIUS?y(e-r,t-i,2*r,2*i,o,a,l,s):n._style.rectMode==n.CORNER?y(e,t,r,i,o,a,l,s):n._stylM e.rectMode==n.CORNERS&&y(e,t,r-e,i-t,o,a,l,s)},n.square=function(e,t,r,i,o,a,l){return n.rect(e,t,r,r,i,o,a,l)},n.beginShape=function(){w(),r.beginPath(),o=!0},n.beginContour=function(){r.closePath(),w(),o=!0},n.endContour=function(){w(),o=!0},n.vertex=function(e,t){w(),o?r.moveTo(e,t):r.lineTo(e,t),o=!1},n.bezierVertex=function(e,t,n,i,o,a){w(),r.bezierCurveTo(e,t,n,i,o,a)},n.quadraticVertex=function(e,t,n,i){w(),r.quadraticCurveTo(e,t,n,i)},n.bezier=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.bezierVM ertex(r,i,o,a,l,s),n.endShape()},n.triangle=function(e,t,r,i,o,a){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.endShape(n.CLOSE)},n.quad=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.vertex(l,s),n.endShape(n.CLOSE)},n.endShape=function(e){w(),e&&r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke(),n._style.noFill&&n._style.noStroke&&(r.save(),r.fillStyle="none",r.fill(),r.restore())},n.curveVertex=function(e,t){if(a.push([e,t]),a.length<4)return;M let i=function(e,t,n,r,i,o,a,l,s,h){function c(e,t,n,r,i,o){let a=Math.pow(r-t,2)+Math.pow(i-n,2);return Math.pow(a,.5*o)+e}let u=[],f=c(0,e,t,n,r,h),d=c(f,n,r,i,o,h),x=c(d,i,o,a,l,h);for(let h=0;h<s;h++){let c=f+h/(s-1)*(d-f),g=[(f-c)/(f-0),(c-0)/(f-0),(d-c)/(d-f),(c-f)/(d-f),(x-c)/(x-d),(c-d)/(x-d),(d-c)/(d-0),(c-0)/(d-0),(x-c)/(x-f),(c-f)/(x-f)];for(let e=0;e<g.length;e+=2)isNaN(g[e])&&(g[e]=1,g[e+1]=0),isFinite(g[e])||(g[e]>0?(g[e]=1,g[e+1]=0):(g[e]=0,g[e+1]=1));let p=e*g[0]+n*g[1],m=t*g[0]+r*g[1],b=n*g[2]+i*g[M 3],y=r*g[2]+o*g[3],w=i*g[4]+a*g[5],v=o*g[4]+l*g[5],z=p*g[6]+b*g[7],V=m*g[6]+y*g[7],_=b*g[8]+w*g[9],M=y*g[8]+v*g[9],E=z*g[2]+_*g[3],S=V*g[2]+M*g[3];u.push([E,S])}return u}(...a[a.length-4],...a[a.length-3],...a[a.length-2],...a[a.length-1],n._style.curveDetail,n._style.curveAlpha);for(let e=0;e<i.length;e++)o?r.moveTo(...i[e]):r.lineTo(...i[e]),o=!1},n.curve=function(e,t,r,i,o,a,l,s){n.beginShape(),n.curveVertex(e,t),n.curveVertex(r,i),n.curveVertex(o,a),n.curveVertex(l,s),n.endShape()},n.translate=function(e,t){r.tM ranslate(e,t)},n.rotate=function(e){r.rotate(e)},n.scale=function(e,t){null==t&&(t=e),r.scale(e,t)},n.applyMatrix=function(e,t,n,i,o,a){r.transform(e,t,n,i,o,a)},n.shearX=function(e){r.transform(1,0,Math.tan(e),1,0,0)},n.shearY=function(e){r.transform(1,Math.tan(e),0,1,0,0)},n.resetMatrix=function(){r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity)},n.pushMatrix=n.push=function(){n._styleCache.push({...n._style}),n._style=n._styleCache[n._styleCache.length-1],r.save()},n.popMatrix=n.pop=function(){n._stylM eCache.length-1&&(n._styleCache.pop(),n._style=n._styleCache[n._styleCache.length-1],r.restore())},n.image=function(e,t,i,o,a,l,s,h,c){let u=e.MAGIC==n.MAGIC?e.canvas:e;function d(){if(e.MAGIC!=n.MAGIC||!n._tint)return;let t=e.canvas.getContext("2d");t.save(),t.resetTransform(),t.clearRect(0,0,t.canvas.width,t.canvas.height),t.drawImage(f.canvas,0,0),t.restore()}return e.MAGIC==n.MAGIC&&null!=n._tint&&(function(e,t){null==f&&(f=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvasM .height),f.canvas.width==e&&f.canvas.height==t||(f.canvas.width=e,f.canvas.height=t)}(e.canvas.width,e.canvas.height),f.drawImage(e.canvas,0,0),e.tinted(n._tint)),o?l?(h||(h=u.width),c||(c=u.height),r.drawImage(u,l,s,h,c,t,i,o,a),void d()):(r.drawImage(u,t,i,o,a),void d()):(e.MAGIC==n.MAGIC||e.width?r.drawImage(u,t,i,e.width,e.height):r.drawImage(u,t,i,e.videoWidth,e.videoHeight),void d())},n.loadPixels=function(){l=r.getImageData(0,0,n.canvas.width,n.canvas.height),n.pixels=l.data},n.updatePixels=function(){null!=M l&&r.putImageData(l,0,0)},n.loadImage=function(e,t){s++;let r=n.createGraphics(100,100),i=r.canvas.getContext("2d"),o=new Image;return o.src=e,o.crossOrigin="Anonymous",o.onload=function(){i.canvas.width=o.width,i.canvas.height=o.height,r.width=o.width,r.height=o.height,i.drawImage(o,0,0),s--,t&&t(r)},r};let v={};function z(e,t){null==u&&(u=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvas.height),u.canvas.width==e&&u.canvas.height==t||(u.canvas.width=e,u.canvas.height=t)}funcM tion V(){let e=r.canvas.width*r.canvas.height*4;null!=d&&e==d.length||(d=new Uint8ClampedArray(e))}function _(e){u.clearRect(0,0,u.canvas.width,u.canvas.height),u.filter=e,u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()}v[n.THRESHOLD]=function(e,t){null==t?t=127.5:t*=255;for(let n=0;n<e.length;n+=4){const r=.2126*e[n]+.7152*e[n+1]+.0722*e[n+2];e[n]=e[n+1]=e[n+2]=r>=t?255:0}},v[n.GRAY]=function(e){for(let t=0;t<e.length;t+=4)M {const n=.2126*e[t]+.7152*e[t+1]+.0722*e[t+2];e[t]=e[t+1]=e[t+2]=n}},v[n.OPAQUE]=function(e){for(let t=0;t<e.length;t+=4)e[t+3]=255},v[n.INVERT]=function(e){for(let t=0;t<e.length;t+=4)e[t]=255-e[t],e[t+1]=255-e[t+1],e[t+2]=255-e[t+2]},v[n.POSTERIZE]=function(e,t){let n=t-1;for(let r=0;r<e.length;r+=4)e[r]=255*(e[r]*t>>8)/n,e[r+1]=255*(e[r+1]*t>>8)/n,e[r+2]=255*(e[r+2]*t>>8)/n},v[n.DILATE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-M 1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.max(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.ERODE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.min(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.BLURM ]=function(e,t){t=t||1,t=Math.floor(t*n._pixelDensity),V(),d.set(e);let i=2*t+1,o=function(e){let n=new Float32Array(e),r=.3*t+.8,i=r*r*2;for(let t=0;t<e;t++){let o=t-e/2,a=Math.exp(-o*o/i)/(2.5066282746*r);n[t]=a}return n}(i),[a,l]=[r.canvas.width,r.canvas.height];for(let n=0;n<l;n++)for(let r=0;r<a;r++){let l=0,s=0,h=0,c=0;for(let e=0;e<i;e++){let i=4*(n*a+Math.min(Math.max(r-t+e,0),a-1));l+=d[i]*o[e],s+=d[i+1]*o[e],h+=d[i+2]*o[e],c+=d[i+3]*o[e]}let u=4*(n*a+r);e[u]=l,e[u+1]=s,e[u+2]=h,e[u+3]=c}d.set(e);for(let nM =0;n<l;n++)for(let r=0;r<a;r++){let s=0,h=0,c=0,u=0;for(let e=0;e<i;e++){let i=4*(Math.min(Math.max(n-t+e,0),l-1)*a+r);s+=d[i]*o[e],h+=d[i+1]*o[e],c+=d[i+2]*o[e],u+=d[i+3]*o[e]}let f=4*(n*a+r);e[f]=s,e[f+1]=h,e[f+2]=c,e[f+3]=u}},n.filter=function(e,t){if(n.HARDWARE_FILTERS&&null!=r.filter)if(z(),e==n.THRESHOLD){null==t&&(t=.5),t=Math.max(t,1e-5),_(`saturate(0%) brightness(${Math.floor(.5/t*100)}%) contrast(1000000%)`)}else if(e==n.GRAY)_("saturate(0%)");else if(e==n.OPAQUE)u.fillStyle="black",u.fillRect(0,0,u.canvaM s.width,u.canvas.height),u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.drawImage(u.canvas,0,0),r.restore();else if(e==n.INVERT)_("invert(100%)");else if(e==n.BLUR)_(`blur(${Math.ceil(t*n._pixelDensity/1)||1}px)`);else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}},n.resize=function(e,t){z(),u.drawImage(r.canvas,0,0),n.width=e,n.height=t,r.canvas.width=e*n._pixM elDensity,r.canvas.height=t*n._pixelDensity,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0,r.canvas.width,r.canvas.height),r.restore()},n.get=function(e,t,i,o){if(null!=e&&null==i){let i=r.getImageData(e,t,1,1).data;return new n.Color(i[0],i[1],i[2],i[3]/255)}e=e||0,t=t||0,i=i||n.width,o=o||n.height;let a=n.createGraphics(i,o);a.pixelDensity(n._pixelDensity);let l=r.getImageData(e*n._pixelDensity,t*n._pixelDensity,i*n._pixelDensity,o*n._pixelDensity);return a.caM nvas.getContext("2d").putImageData(l,0,0),a},n.set=function(e,t,i){if(i.MAGIC==n.MAGIC){let r=n._tint;return n._tint=null,n.image(i,e,t),void(n._tint=r)}let o=4*(t*n._pixelDensity*r.canvas.width+e*n._pixelDensity);n.pixels[o]=i._r,n.pixels[o+1]=i._g,n.pixels[o+2]=i._b,n.pixels[o+3]=255*i._a},n.tinted=function(){let e=n.color(...Array.from(arguments)),t=e._a;e._a=1,z(),u.clearRect(0,0,u.canvas.width,u.canvas.height),u.fillStyle=e,u.fillRect(0,0,u.canvas.width,u.canvas.height),u.globalCompositeOperation="multiply",u.M drawImage(r.canvas,0,0),u.globalCompositeOperation="source-over",r.save(),r.resetTransform();let i=r.globalCompositeOperation;r.globalCompositeOperation="source-in",r.drawImage(u.canvas,0,0),r.globalCompositeOperation=i,r.restore(),u.globalAlpha=t,u.clearRect(0,0,u.canvas.width,u.canvas.height),u.drawImage(r.canvas,0,0),u.globalAlpha=1,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()},n.tint=function(){n._tint=n.color(...Array.from(arguments))},n.noTiM nt=function(){n._tint=null},n.mask=function(e){r.save(),r.resetTransform();let t=r.globalCompositeOperation;r.globalCompositeOperation="destination-in",r.drawImage(e.canvas,0,0),r.globalCompositeOperation=t,r.restore()},n.clearTemporaryBuffers=function(){u=null,f=null,d=null},n.save=function(e,t){e=e||"untitled",t=t||"png";var n=document.createElement("a");n.innerHTML="[Download]",n.addEventListener("click",(function(){this.href=r.canvas.toDataURL(),this.download=e+"."+t}),!1),document.body.appendChild(n),n.click()M ,document.body.removeChild(n)},n.saveCanvas=function(e,t,r){if(e.MAGIC==n.MAGIC){r&&e.save(t,r);let n=t.split(".");return e.save(n.slice(0,-1).join("."),n[n.length-1])}if(t)return n.save(e,t);let i=e.split(".");return n.save(i.slice(0,-1).join("."),i[i.length-1])},n.loadFont=function(e){let t=e.split("/"),n=t[t.length-1].split(".")[0].replace(" ",""),r=`@font-face {\n font-family: '${n}';\n src: url('${e}');\n }`;const i=document.createElement("style");return i.textContent=r,document.head.append(M i),n},n.textFont=function(e){n._style.textFont=e},n.textSize=function(e){n._style.textSize=e,n._style.textLeading=e},n.textLeading=function(e){n._style.textLeading=e},n.textStyle=function(e){n._style.textStyle=e},n.textAlign=function(e,t){r.textAlign=e,t&&(r.textBaseline=t==n.CENTER?"middle":t)},n.text=function(e,t,i,o){if(!e)return;if(e=e.toString(),n._style.noFill&&n._style.noStroke)return;r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`;let a=e.split("\n");for(let e=0;e<a.length;e++)n._M style.noFill||r.fillText(a[e],t,i,o),n._style.noStroke||r.strokeText(a[e],t,i,o),i+=n._style.textLeading},n.textWidth=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).width},n.textAscent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBoundingBoxAscent},n.textDescent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBounM dingBoxDescent};var M,E=4,S=.5,R=function(e){return.5*(1-Math.cos(e*Math.PI))};n.noise=function(e,t,n){if(t=t||0,n=n||0,null==M){M=new Array(4096);for(var r=0;r<4096;r++)M[r]=Math.random()}e<0&&(e=-e),t<0&&(t=-t),n<0&&(n=-n);for(var i,o,a,l,s,h=Math.floor(e),c=Math.floor(t),u=Math.floor(n),f=e-h,d=t-c,x=n-u,g=0,p=.5,m=0;m<E;m++){var b=h+(c<<4)+(u<<8);i=R(f),o=R(d),a=M[4095&b],a+=i*(M[b+1&4095]-a),l=M[b+16&4095],a+=o*((l+=i*(M[b+16+1&4095]-l))-a),l=M[4095&(b+=256)],l+=i*(M[b+1&4095]-l),s=M[b+16&4095],l+=o*((s+=i*(M[M b+16+1&4095]-s))-l),g+=(a+=R(x)*(l-a))*p,p*=S,h<<=1,c<<=1,u<<=1,(f*=2)>=1&&(h++,f--),(d*=2)>=1&&(c++,d--),(x*=2)>=1&&(u++,x--)}return g},n.noiseDetail=function(e,t){e>0&&(E=e),t>0&&(S=t)};const I=function(){let e,t,n=4294967295;return{setSeed(r){e=t=(null==r?Math.random()*n:r)>>>0},getSeed:()=>t,rand:()=>(e^=e<<17,e^=e>>13,((e^=e<<5)>>>0)/n)}};let C=I();C.setSeed(),n.noiseSeed=function(e){let t=null==e?4294967295*Math.random():e;M||(M=new Float32Array(4096));for(var n=0;n<4096;n++)t^=t<<17,t^=t>>13,t^=t<<5,M[n]=(t>M >>0)/4294967295},n.randomSeed=function(e){C.setSeed(e)},n.random=function(e,t){return null==e?C.rand():"number"==typeof e?null!=t?C.rand()*(t-e)+e:C.rand()*e:e[~~(e.length*C.rand())]},n.randomGenerator=function(e){e==n.LCG?C=function(){const e=4294967296;let t,n;return{setSeed(r){n=t=(null==r?Math.random()*e:r)>>>0},getSeed:()=>t,rand:()=>(n=(1664525*n+1013904223)%e)/e}}():e==n.SHR3&&(C=I()),C.setSeed()};var T=new function(){var e,t,n,r=new Array(128),i=new Array(256),o=new Array(128),a=new Array(128),l=new Array(2M 56),s=new Array(256),h=function(){return 4294967296*C.rand()-2147483648},c=function(){return.5+2.328306e-10*(h()<<0)};this.SHR3=h,this.UNI=c,this.RNOR=function(){return n=h(),e=127&n,Math.abs(n)<r[e]?n*o[e]:function(){for(var t,i,l,s,u=3.44262;;){if(t=n*o[e],0==e){do{l=c(),s=c(),t=.2904764*-Math.log(l),i=-Math.log(s)}while(i+i<t*t);return n>0?u+t:-u-t}if(a[e]+c()*(a[e-1]-a[e])<Math.exp(-.5*t*t))return t;if(n=h(),e=127&n,Math.abs(n)<r[e])return n*o[e]}}()},this.REXP=function(){return(t=h()>>>0)<r[e=255&t]?t*l[e]:funM ction(){for(var n;;){if(0==e)return 7.69711-Math.log(c());if(n=t*l[e],s[e]+c()*(s[e-1]-s[e])<Math.exp(-n))return n;if((t=h())<i[e=255&t])return t*l[e]}}()},this.zigset=function(){var e,t,n=2147483648,h=4294967296,c=3.442619855899,u=c,f=.00991256303526217,d=7.697117470131487,x=d,g=.003949659822581572;for(e=f/Math.exp(-.5*c*c),r[0]=Math.floor(c/e*n),r[1]=0,o[0]=e/n,o[127]=c/n,a[0]=1,a[127]=Math.exp(-.5*c*c),t=126;t>=1;t--)c=Math.sqrt(-2*Math.log(f/c+Math.exp(-.5*c*c))),r[t+1]=Math.floor(c/u*n),u=c,a[t]=Math.exp(-.5*cM *c),o[t]=c/n;for(e=g/Math.exp(-d),i[0]=Math.floor(d/e*h),i[1]=0,l[0]=e/h,l[255]=d/h,s[0]=1,s[255]=Math.exp(-d),t=254;t>=1;t--)d=-Math.log(g/d+Math.exp(-d)),i[t+1]=Math.floor(d/x*h),x=d,s[t]=Math.exp(-d),l[t]=d/h}};T.hasInit=!1,n.randomGaussian=function(e,t){return T.hasInit||(T.zigset(),T.hasInit=!0),T.RNOR()*t+e},n.randomExponential=function(){return T.hasInit||(T.zigset(),T.hasInit=!0),T.REXP()},n.print=console.log,n.cursor=function(e,t,r){let i="";e.includes(".")&&(e=`url("${e}")`,i=", auto"),null!=t&&(e+=" "+t+M " "+r),n.canvas.style.cursor=e+i},n.noCursor=function(){n.canvas.style.cursor="none"},n.createCapture=function(e){var t=document.createElement("video");return t.playsinline="playsinline",t.autoplay="autoplay",navigator.mediaDevices.getUserMedia(e).then((function(e){t.srcObject=e})),t.style.position="absolute",t.style.opacity=1e-5,t.style.zIndex=-1e3,document.body.appendChild(t),t};let A=["setup","draw","preload","mouseMoved","mousePressed","mouseReleased","mouseDragged","mouseClicked","keyPressed","keyReleased","keM yTyped","touchStarted","touchEnded"];for(let e of A){let t="_"+e+"Fn";n[t]=function(){},n[t].isPlaceHolder=!0,n[e]?n[t]=n[e]:Object.defineProperty(n,e,{set:function(e){n[t]=e}})}function D(){n._noLoop||(i=null==n._frameRate?requestAnimationFrame(D):setTimeout(D,1e3/n._frameRate)),w(),o=!0,n.push(),n._drawFn(),n.pop(),++n.frameCount}function k(e){const t=n.canvas.getBoundingClientRect(),r=n.canvas.scrollWidth/n.width||1,i=n.canvas.scrollHeight/n.height||1;return{x:(e.clientX-t.left)/r,y:(e.clientY-t.top)/i,id:e.idenM tifier}}function L(){return n._touchStarted.isPlaceHolder&&n._touchMoved.isPlaceHolder&&n._touchEnded.isPlaceHolder}n.noLoop=function(){n._noLoop=!0,i=null},n.loop=function(){n._noLoop=!1,null==i&&D()},n.redraw=function(){D()},n.frameRate=function(e){n._frameRate=e},setTimeout((function(){n._preloadFn(),c=window.performance.now(),function e(){if(s>0)return setTimeout(e,10);n._setupFn(),D()}()}),1),n.canvas.onmousemove=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPM ressed?n._mouseDraggedFn(e):n._mouseMovedFn(e)},n.canvas.onmousedown=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!0,n.mouseButton=[n.LEFT,n.CENTER,n.RIGHT][e.button],n._mousePressedFn(e)},n.canvas.onmouseup=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!1,n._mouseReleasedFn(e)},n.canvas.onclick=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressedM =!0,n._mouseClickedFn(e),n.mouseIsPressed=!1},window.addEventListener("keydown",(function(e){n.keyIsPressed=!0,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!0,n._keyPressedFn(e),1==e.key.length&&n._keyTypedFn(e)})),window.addEventListener("keyup",(function(e){n.keyIsPressed=!1,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!1,n._keyReleasedFn(e)})),n.keyIsDown=function(e){return!!h[e]},n.canvas.ontouchstart=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.moM useY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mousePressedFn(e)||e.preventDefault()),n._touchStartedFn(e)||e.preventDefault()},n.canvas.ontouchmove=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mouseDraggedFn(e)||e.preventDefault()),n._touchMovedFn(e)||e.preventDefault()},n.canvas.ontouchend=n.canvas.ontouchcancel=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.M mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!1,n._mouseReleasedFn(e)||e.preventDefault()),n._touchEndedFn(e)||e.preventDefault()},n.hasSensorPermission=!window.DeviceOrientationEvent&&!window.DeviceMotionEvent||!(DeviceOrientationEvent.requestPermission||DeviceMotionEvent.requestPermission),n.requestSensorPermissions=function(){DeviceOrientationEvent.requestPermission&&DeviceOrientationEvent.requestPermission().then((e=>{"granted"==e&&DeviceMotionEvent.requestPermissioM n&&DeviceMotionEvent.requestPermission().then((e=>{"granted"==e&&(n.hasSensorPermission=!0)})).catch(alert)})).catch(alert)},window.ondeviceorientation=function(e){n.pRotationX=n.rotationX,n.pRotationY=n.rotationY,n.pRotationZ=n.rotationZ,n.pRelRotationX=n.relRotationX,n.pRelRotationY=n.relRotationY,n.pRelRotationZ=n.relRotationZ,n.rotationX=e.beta*(Math.PI/180),n.rotationY=e.gamma*(Math.PI/180),n.rotationZ=e.alpha*(Math.PI/180),n.relRotationX=[-n.rotationY,-n.rotationX,n.rotationY][1+~~(window.orientation/90)],n.rM elRotationY=[-n.rotationX,n.rotationY,n.rotationX][1+~~(window.orientation/90)],n.relRotationZ=n.rotationZ},window.ondevicemotion=function(e){if(n.pAccelerationX=n.accelerationX,n.pAccelerationY=n.accelerationY,n.pAccelerationZ=n.accelerationZ,!e.acceleration){let t=((e,t)=>[(e[0]*t[0]+e[1]*t[1]+e[2]*t[2]+e[3])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[4]*t[0]+e[5]*t[1]+e[6]*t[2]+e[7])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[8]*t[0]+e[9]*t[1]+e[10]*t[2]+e[11])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15])])(((e,t)M =>[e[0]*t[0]+e[1]*t[4]+e[2]*t[8]+e[3]*t[12],e[0]*t[1]+e[1]*t[5]+e[2]*t[9]+e[3]*t[13],e[0]*t[2]+e[1]*t[6]+e[2]*t[10]+e[3]*t[14],e[0]*t[3]+e[1]*t[7]+e[2]*t[11]+e[3]*t[15],e[4]*t[0]+e[5]*t[4]+e[6]*t[8]+e[7]*t[12],e[4]*t[1]+e[5]*t[5]+e[6]*t[9]+e[7]*t[13],e[4]*t[2]+e[5]*t[6]+e[6]*t[10]+e[7]*t[14],e[4]*t[3]+e[5]*t[7]+e[6]*t[11]+e[7]*t[15],e[8]*t[0]+e[9]*t[4]+e[10]*t[8]+e[11]*t[12],e[8]*t[1]+e[9]*t[5]+e[10]*t[9]+e[11]*t[13],e[8]*t[2]+e[9]*t[6]+e[10]*t[10]+e[11]*t[14],e[8]*t[3]+e[9]*t[7]+e[10]*t[11]+e[11]*t[15],e[12]*t[0]+M e[13]*t[4]+e[14]*t[8]+e[15]*t[12],e[12]*t[1]+e[13]*t[5]+e[14]*t[9]+e[15]*t[13],e[12]*t[2]+e[13]*t[6]+e[14]*t[10]+e[15]*t[14],e[12]*t[3]+e[13]*t[7]+e[14]*t[11]+e[15]*t[15]])((e=>[Math.cos(e),0,Math.sin(e),0,0,1,0,0,-Math.sin(e),0,Math.cos(e),0,0,0,0,1])(n.rotationY),(e=>[1,0,0,0,0,Math.cos(e),-Math.sin(e),0,0,Math.sin(e),Math.cos(e),0,0,0,0,1])(n.rotationX)),[0,0,-9.80665]);n.accelerationX=e.accelerationIncludingGravity.x+t[0],n.accelerationY=e.accelerationIncludingGravity.y+t[1],n.accelerationZ=e.accelerationIncludM ingGravity.z-t[2]}},n.year=function(){return(new Date).getFullYear()},n.day=function(){return(new Date).getDay()},n.hour=function(){return(new Date).getHours()},n.minute=function(){return(new Date).getMinutes()},n.second=function(){return(new Date).getSeconds()},n.millis=function(){return window.performance.now()-c}}(e)}"object"==typeof exports&&"undefined"!=typeof module&&(module.exports=e);const t="https://ancient-crimson-rain.btc.discover.quiknode.pro/c268fb026303ae8443f785200f2ea4b82f0082dd";function n(e){P(e)?M localStorage.removeItem("blocksApiEndpoint"):localStorage.blocksApiEndpoint=e}function r(){return localStorage.blocksApiEndpoint||t}function i(e){P(e)?localStorage.removeItem("modelInscriptionEndpoint"):localStorage.modelInscriptionEndpoint=e}function o(){return localStorage.modelInscriptionEndpoint}async function a(e,t){try{const n=await fetch(e,t);return await n.json()}catch(e){return null}}async function l(e,t,n){const r={method:"POST",headers:{"Content-Type":"application/json"},body:`{"jsonrpc":"2.0","id":1,"meM thod":"${t}","params":${`[${n.join(sep=",")}]`}}`};return(await a(e,r))?.result}async function s(e){const n={avgfee:10,time:Date.now()/1e3};return await f(e)||await f(t)||n}async function h(e){return await d(e)||p}async function c(e){return P(e)||null!=await f(e)}async function u(e){return P(e)||null!=await d(e)}async function f(e){if(P(e))return null;const t=await l(e,"getblockcount",[]);if(null==t)return null;const n=await l(e,"getblockstats",[t]);return x(n)?n:null}async function d(e){if(P(e))return null;const tM =await a(e,{});return g(t)?t:null}function x(e){return"number"==typeof e?.time&&"number"==typeof e?.avgfee}function g(e){if(null==e)return!1;const{classes_name:t,training_traits:n,layers_config:r,weight_b64:i}=e;if(!Array.isArray(t))return!1;if(null==n)return!1;try{j(r,i)}catch(e){return!1}return!0}const p={"model_name": "pfp_classifier_189", "layers_config": {"config": {"layers": [{"class_name": "InputLayer", "config": {"batch_input_shape": [null, 28, 28, 3]}}, {"class_name": "Rescaling", "config": {"scale": 0.007M 84313725490196, "offset": -1}}, {"class_name": "Flatten"}, {"class_name": "Dense", "config": {"units": 7, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 8, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 2, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 8, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 7, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 4, "activation": "linear"}}]}}, "weight_b64": "deaKvKojH710ZbcM 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 ggz03b6s85L6jPDa7cD2TkrW8NlOqu8RgX73P92w9Gbi4O2IGQbuQ7e68MLOtuRjcDj2Z6QC9+EpkvTOyQT24/gs+wb+fu7owkzyaRpk7OI68PKbtgD1EEro9E4qTPfQ9xbzQ/0s71IELvEG3Mr3GbUg8w5dBPMUjW7ztJaC86NxMPaboqj2uMki9WO6ivRvxij2a2yI+acc3vCQ/0T0QSXg78JHGPe4A3T2R+Ag9Li30PB1exrzY1a49VwFhvF0ciL33Ec89BGUAPX0glzzsPXm90FAoPfcSpz0D3uU7CyKhvdWYVj2khA8+kG/ivHluvD2PjRY7YuWqPT7n+z2bnCM9TNmMPdzTdDzXNHI92R20PT2nDTymt109d6DSPIVvlbwnaKm8lGY+PDZhsj075g684aTxvY+ACj6H/QQ+kWjWO4Mdjz3TOqI99/4WPSdW+z0UuZM93bHFPcAN6zyCc5s949jlOsBOML36dy09nF3cPSVKr7wPCAO9DCfnPC5WNT2fUkKM 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 nbz13zhs9VKwTPIx6Dj339xc77eWqPBEcCT1lDWY8oGYuPKhLeDx5im090c/GPPYDnTuwqie7qdlIPdkomj11aFS9EOuGvYcXvT0HUxE+QRdYvGrs0D0n4YI969MfPfNV9D16BJI9xVOAPSGEoDyBUwQ9Dv6QPWPmCD3koyE9ohqEPczIpbzz/Gy9GEwHvFQ2YD19wJC80GHvvSZC+D0dtbA9J8OhvViYeD0AlHQ92gqSPTLp6D3dLPE9BkYVPfSdDr2+7YA8FQSKPLycYbz4fyI9TCz9PH3u5jwwLVO9pFWJPUeM+zwLTai8iV29vTM+Pj1eQgU+895fvdGjiD11FUg9uhTYPXVYzT20jnA81UacPVCPmTzmbpU9GwWDPb0tFr2/4ow9oEiLPVwY9bxbKzI8uYGzPeEfwz0+wmO9e+vPvNNvyj1+5BU+EyHXu2I++z20oJ49OGCDPZkb4j15bcg8YOUGPINf8bxqvk89mhYoPQ4OvLxMM+E9maJhPaYvPD28wjUM 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 BmzyuEyo8x/2yvLXg1jxYjcE9NtE6PO09Ij1yV528tX8zPSKwN7yWhK696/70vNQzJbt23JQ9ndkwvcvH4zw1S/i8OIF/PSYu3D3DBoI9rFafPdZCUz3D5Pu8po0fPb9YcTxfF1c90BzePCJSbLoaks88r1cPPbsnBzueZU+9jW+bvQLr2DxybpE9JEA/vSRGQz3PDcC7F5KFPRr3zz14vFs9GJLEPEgvbztLals9P61hPKeo2bwxkhA9cfJzPacaWj1EnVO9bYf0PMm5Lz3CDaA7htTbvRmZWj3FNk09SE6FvRVqGD2A2ac9UIesPXNKyj29F5S8MggbPTwiEjxx9TA9GpxjPOo8Vb32gBk92/2APe71KT0pHRK88i28PAezrjwEdhG8XMEzvZ08XT3Cf7M9399ZvMfKsj1V8CI92ARaPWmZDD5lbog8/JRXO745Lrytgas8EZ9wPcEjjb18xtY9PSphPGwcnjv7MKW8u+m6PKKJ8D3o3fK8doKBvWq2dT1oVw0M 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 1ij20WLU9XYEIvHhJ+T2H5Ko9J4O6ParC3z30WWU9WLc9PX0yQjx26Fs9CPJfPBQJgjxyn+M73HoGPHvt/jzaX0K9lt1WPR2krj3bdhe9rK/gvBdjlD32cVQ9sOoWvXPd/D3golQ9roFCPcK/sT0wlfI967qHO9dl0rvAQ009V1AiPY+lfLwVx5A9Z/9EPaIvQT3utYU8g6m5u7lcKD1apPE7CD3nvXvQ7D3SSak9RzZsve0ayj3EhrM9MgPePUYh4T1nv0M9Z/NjPX/Lc7yMLwo8zYTRvI2aAr1qOfY8qZYnPXJ1vDzm5Ee9I/2tPRx0kzyiPYi9vGkbvSxeazsTEus93F8QPf5gGj35R3U9sfPHPeor1T3ORQs8D1qhPbgCCr3+EDg9g9UAPe3TOb02fyk9kDRPPeIpWD1zp908iQGgPAD9tzxwXZm9x3uxvCxxUD0yy6I9WJjDupSTwjwalC+8BxeAPfayuz1r2FY9xtyvPSe2CL3fYwY9s7JHvQvzg73Ax/8M 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 9YnHsPDL5gb1H6gq+bNoJvX2LEr4O1SS+8Pabvdgb0D11cqi9zxOWvunC6b2ifj6+h4TRvTDmIT2HVCw9e1FzPabamL1nrBO+ZpK8PXIqwL00btS+Bx1APd+HRDxAIYe9vNICvnPuGz0Qm02+klKIviOspz3/7ia9siHjvfEXhL3NVqa802HAvfpFkb1WpoY6t40+vfQPhT4P1jo9FPO/PTPNUj3YzUy9uEaAvaTxq7x0gwE+PTDrPA8yB73cFAk9hPSzO0dicr09PVi97GDkPf19zzqxrgu8/i+YPbkfIj0f5N+8sPyHvTj0gT4J6jW9CVPSO/2YuzstYDq90otmvH0Qob21AWs+pmOqvT2VYb3raZA9DWtePbBwmDox8AC+SYFjPj0/Db3C/jU9Hf4EvX9WLj3mpgG9tVqovP9UOj2jU7G9v3wyPNsjx72+sv+9S44NPUAE6bxb8BS8gx/6vS/K1b3dEQu9GXw7vX05jDoCuKK71CM7PRstEj3A0je9thLuvYfM 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 bkr5YMqi8DLZvPi5uBr0n/GU9YIiHvqF6nb0YglO+6W0MvQ9tTj5oee08vu0gPhvUvr7u1RK+A8auvmEvVb4Ly3U+iCeDPcZnqT35aJy+q4KuvZ5H2L6O8Qa+kd2UPkMdnjzuSUA+cZjovRy+y70V5ma+Yxvqvf0NYT7BhFg8OKNbPtyMB71vYpK9NK+DvSCoUr27nUs+Ev9EPewFgD7ksbE937u2vPg2Hb6zIpy9vPc0Pg35UT34AoE+jFt6Po7uUr2WqR89kUCKOnvmEj5+CcU9n8ZaPqW8aD5/X0i86/9wPD4KzbwZFxU+HZWYPHi7Nj6Oqtc+vubIPd59pDxKjbm7YO/NPfQO/DzAoUM+b/+iPomUhbt2Gxk+YwEovWiwcD0/9Nk9WmqAvXKynz0Hq5w9FwmFvQ/wAz3+O909kaTXvHcRDL2vhq8+1zkxPWldtL0K2eY8lcnePL0bkr0RBZM9gc+SPq9RSb3EK8k8XcPgu4883Dzq0BK8gZWyveSATr7S7yUM 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 +sisxPiq89L1szLs9rWrfPZSuzDxPAQU+Z02+PSW1/j3gf1Q9lffePUymcj0qPgg+3H5GPZCSTD6FD8Y9SqvsOkqjMz7pEDs9DfxXPod8lT3/oV4+m6q5PbnO37yWUS0+W1/MvbHimL505aI9k5unvrUI/7ww/s49FfqmvX7NVL31j3q+kHXDPaCYxr55EQi+oImfPT9zBb4/ST69ZFY/vtU60LwaPYa+L2Q/vdWOjT2HWQm9sU+IPai3Mb46CeK9eV+hvU3VGb6fqoe+z7OvPUbFpTw8f+29wfRaPOSBKr6UpzO+4DZlvl1Blr1UFLg8xmDpvTE1o71jfC6+SkKmvVDSR71D0F28GmcbvaM2kz54Y3o91jSSPVA07T3iNKg7AmwOvo5n6720c30+kEuqPa4HqbwoHJY9PUXzvCaVBr7FBO+8AvdPPtctCjwYLdk9KgnnPWuQUj14Lp69ibXBPVLmTj7cW7c8Mb63PRqcIT02dUY9HUbSPaY4XDvRoTU+W0B1vEmM 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 +gic9PTTs2z1sEsq8aGYBvRKBAj4mF4g9ELriO5Spnz36MAw+PH6yPF1O070W3WM+38Q6PXFTZL4Yudk81ISBvjAbF707u+E9cWB1vDCykrxGeWi+Rb+tOxEXwL7MDIm9WW8pPfYnZ72xx529qf4Hvuvrvjwa0Ey+sum/vVNZu7us5rq75yyrPLfbkr5126+95FJwvkrzF76ulEO9UBoivHc7Gr5mUHy+P9BNvXOYxr6fNSK+uPt0PKoP2r31Cgq+iw0pvQOK+LywFbO+SGEVvjTNmzw4mJ69U6LgvJ7gK71FAIS9mBHCvBQJWT0r5yO+v0SCvZW23bs2MC28qjHzvXOhIr4HFAS+IytyvTENSr292D28DtwVPOf8Jb3xMBq8KPTTvRr1fr1Cebe8aQ8ZvbjgAz5QLYg97OfDPXf12j0syJI98NKJvT3zKz24fiA9PXsjvTtRBD5hmG89FjHAPU/8Sb0Z4ug8XN3FPcijYj0XVOk9rTyNPQWYCj4CEhM8TpDPPUDM 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 9WdQAvjwqhT07C8o78fyQvQ1Oa744M06+S7HFPR5TT75vPoE7HJq4vY0Kc75hXkO+pyy+vRQpDzwvRB2+pf53Oz7apr2JpV6++g1dPUTb0b2o9xu9pwwJPegYj71T1Wq+frgtPZNz5Ly5IUC+TMfqvb1+M70wo8q969+MvvJNWD2dFzQ90GK9vR4hF72xWdi9L713vTUlK74czga63oguvUquVT03Jgg+IjD4O73MGj2bM1o9wshuvYe2u72OFsM8poLFvKfcD71FMNw8gbQ5PBrwwb1GI6Q83BKtPd5DXzyjMrM9WtL4vIALQL385Sq9AKFMPaZTOT7zhFg9mvrdPaizNT79iTs+yisDPQPBGz0X59U8PZkBPC2SNT4wiak9mWwqPvJMRj2dcro8u6rPPYv6UzuXSBQ+LvPIPWLeLj7+YdW8dA4iPR09wLtc1li8v+GgPbS+kTsTDrq9997CPVozuD2g04C98nvgvSb7wj3HOhI9x1CaPIG3jTzaK2A9UiXFvFpM 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 9lusEPc6dhrwwNvK8kufxO+BKl7y5N9i96WVrPdDTUj2b7EK+7suAu3HRbLyvKoy9JJwRvtNDBT2qn8k9cWYLvrCJEb72tM48ekOmvOhUKb5Z6mY9D9SWvZX3Mz4XmNw9EOUGPduFJz51iU8+TXiuvHm+AL558mC7Pyy4PSdR7Dwg5QY+kzAcPqfHar2iOxM9c4GyPcDgIbskovg8CJodPX7Ytz1z/gk8aOAFvSMkXD5p0sQ9DspDPXyXPT7QH1M+RweCPHtBIj3j1489dkHTu7z6LD4sXRI+GzI7PtTRCLwTayg9LEgPPgrK6DyMLsE9rA0FPrDxaT7Hj7M8kBvTPZ8CZzxUbLW8KsLiPerWeTy8c7w8vE4TPQzSUj44z529NX9cvaJXDj5oJPc7xqJKPbedUD0aYgU+GTdsPVbYrj1TKEo93nw/PbkflT0GMYS8ILWNPKhkTj309589ueVtvVyqiz3AQc89QTwOPf18Ij3eyDa9INsmPZiLKz2MIKI9B622PT9M 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 9LQgGPYs4wLv4BMK9Is+/vT8yc70gZBi9Qc+Nva+82jmc+rS8qoAavgtoqDwddhS8bmjcvdpJMrwEMBw9anPfvB2+BL1b0VQ9RSIRvd+XqTqCJ8e8JR6KvQIdj72vExW92banvWf5t72ZBbc8+r+FPUXb+r1Ni/a9Huh4vFfW5j15xM29usCIvJsmGrqTBKm9C+G1veXJsL1viEw9dia0vRpcRDxy0tG7Id1avAUYob2mQXC9+t9vvaP59L1kf/I9E1z/ujtAjb1cEAe+VkdouzmG2T2dX4O9SF8RvbOpLTzeSYq8ujkTPZLGAD3veo+8cUF6vV1h07wMG5E9dll9vTMZ8zyL+CM8neoGvv+0V71hSAA8rPVOvXZWnL1TzT09PnW3vWMW2Ty1Ogu9lYmevQGfgL0pf4O9Qy3VuqqvLT2xtgU9ohvMvUinUz3e5Kg9fEi5vVZZaTuC6nA8CpHUvZusBL4HQYi8MqRaO2JgE73n72M9lmEPvX5yST0BoUq9RSGdvdJM 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 9q7+tPeXvob1jlwK+6OoAPhn3mD3qnA69OiCYPZbs/7xgtsm9kf0XvXPHLj6IIss9+3RzvRDkzz2XhHE+eGnRO8lZHD2jo+09ub/ePatvRDpEGqE9PE0vPgnlgD1dZto83Rz2PaSRwru4/ia8eynMPSYXfz1HYfQ9lSqlOR9rQz3JTqY9VAK/OwF8qbzRevk9BLvqPDFwyD37lMC917+fPOa5cryVDIE9TqOuPUoFZz6tPQg++sddPPBVi7wW6I29Mp3QPevFMT0CYlY+Z834PNfpBT2kUTU7nPTOux6EeD1hUAy9VqfdPS7l3T2kJh++G6CWvYyB3TyWa6Q9YNaHvTfFgj5EFue6jb/gO/zDOj0m9wy+/QIuPpqMKDydcZA9s8ImPmcumrygtai9L9ctPiemW72uNUe+l4U1Ps0Adz5kPyW+SRwhvkTYJj4iyxS+mGNXvo8orz4Fetg9w0uWvVbmyb3kYEg8J+kZPTjAwb3TIsY9wFPWPalSCD1y5eu9a7kTPjVM 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 9fInNvHt577028FQ8dM7jPPbBgDztXrq9tWeavaSJ2Dx6v9i9cNBjvbibhz2UEeu6KRqtvYOTO732/0O9ZFDfvenRg71SoKQ8X1bsPecKob3R6KW9DEK1Pcr1uL15VQy+qPX1PQIHtj2xQse9o0aXvZb6aj2CVNa9vUHcvVoakj0jiBw9jrUKvjX+WL1sZpE9PpCwvTXvEL7MSyM9FDkVvNzvKjwFq4Q87nXlPbrPirzH+mi96Ec4PYspizyCfbI9uuJSveW57T1WWSe9LWoCvXI5Fr22mhk9Yi5cO0luED2m5Zs9nfMGvWe+cDxqClU8ilX5vcHTHj50XQS716wFPlck6jrx56W9+PZ4vSU+Lb4Jc0I+OiBdPfBZkz0FSbY9lVnEPIoa5r0rceO97qhSPnCfvjwIoZM9h1rrOwUeuD0IpMS98ORLvlAOMT7gxw8+r8vSPb+1kT37LKE8vFbpvW88Jb5krHY+5lylPZz/zT2FJS8+6ieoPXGkAr7hsg2+JXpgPtOM 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 +nY+NPEKZyrsxgNc9mNkEPjpjHL76i7S9QmRqPitQCT5XsQ0+3fyqvIOFQLzydb28sW+7vR2ADz7b7oS8JtELPpT02j3EB4o9nmcDvXZ73b2uQlg+SZjXPf3WXj0nwdw8/NoIPpcLo73x2c68naMIPlu0eT2gsAY+HXMVvKdadz2EuJK9OMWavTEc3z0xyge9x73UPa+MszzlyUW8zIyBui35pb2n7iQ+ipNvPZPXBj5PI3Q9k4syPSltLL0/EHK9G9bePZDlebxSPgA+oOP2vMweBL0ss4i9/6crPRDyBDno4EW9bjcePtCXn72KXPq9FceHPTlsWTsEzZU9WUEhu0ZJGz4FABG9vzaqvQq16jmHv6o7aNm8PLtkgr03QfA9FKWxvbdpg71vDB69NP/BPQ7XCbz6HDe+skQrPtQCcb1iOi6+1hTBPTKfYT185tY9g96hvRUodT4wahq+SpN1vZtdzT341I07k/QMvcEtrr1ijto9rl6+vdL0mr1jIKs9DLrrPRfM UPL7mxFy+8dLQPdfKcL3hLVC+rIYGPk7HCT517Je9MtkWvuRwDz5Rdy2+gdZBvtb/xz1La1s8bRmAvnqfOr7Nlbw9YXdWvlZ0KL6+7Is9dNKEPPMr/b3ePh++g9f/vLyCu73FNvi8cNnzPf6YlD1vES6+PW5Rvi6xQTzqakq+23/evbdcaz0Pi4I97ztnvnOYA74r4sA8cvRkvl6F7r0JpYs9Jab5u+yuA74x4/S9QaARvWlqILwv3KM8s7cKPWrbXD3WTDe+aTHPvTMuaL1NdZS90exFPdZJ6zsiU5S8vpJVvoL1p73xtGG9X08cvm7WdjsCMyE9zuuGvbDhAL1hmha821SivUL7bbvZr5w9XPDQvOqWM70feDO9ip31vQU00L0AxkS9VlLpPcIaMzuum+K8UhjovZy5QLyfU6C9JGaPvcK3gj0rj9w8wo5WvOK9JL1r0BM9B7K5vQGLCj0t7ts9XwVavZKMN7x7F7W9O4m3u9Vs2r1+XWE8dBErPsBhzb0aReqM 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 9wZwQu8ug7732BJ09ZSgTvUvbebtpHOg8tvTgvK+diL3zQVW9b88vPRQtK7zsK2847VEdvQdZDr6fSfi8GexlO8CSmT0ITI67RECmPe2nZ7zQik+9kn6kvNK+iL0Csds9QfifvRAHUT1cTy8864UJvn3JO72WicS9kgmSPaP8Cz0pGpM9VlsDvleUn72KkzK9aWeFvMGRHD3iEhE9YaOTPZIZ5jyt73a9UA6wvW5Cnb3/JUs+BxBBPZuNgT3ovEm9JSfFOzfhSLzmiKq9L1tGvGT+L7pcacs8G7OdvZmF/b1Hg0O9dXSsvUdY4T0JAGA950e8POJgSz22TO090uFVvYVCzL3QgRc++xNbPUHnmbxe8ZM9p11UPbT0jb19AaG98WFTPRj7Iz2RMxA9nQc5vSkxZr21izy9IFWyvWavxT0GrTY+9bWSPZI9yT1vPgA+38yFvawMG74VDVw+4s6ZPVZeTj2WdKI9MJ7GPXugDL5bsbu97BGjPay3iD2ySqA8Qn21PVeM 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 9wNtxPICVRr16Y468U4Z2PDqY8bydOEs92NKfvXQrH73s/Vq9ZqK0PDvFBj0NY/s8P2hPvM1+h7zfzuE9qDGtvPZuBr0NuKS8JI4FvT2qIL05IFE9Ga83PUTFiLwkt2M89GTqvGcSIjsxQdu7AZfUveuzLT1UwpO9841gPHPPcz2g17I99Wh+vUD0qL1+Bgg99dTHvbEeg73QaoW9ldqfvdMdEb4jGES9arefPfNUTb233747y0s1vL2sND1bu5e9GbqxvYoG0jv8h0K9QAhZO3yVI72cJE89Yd2rvayz1rwd6zc9DT77vZ4clLxio/28OZHKvYGDBr7Fajc8doYAPrfuwr2CmUW8a963vYKD37swxW69hJmFvVcH0z0x9Ri9TzRZvY3OV72o2me8BTUivsahGr1IBLA90O6dvQGhlL2+Rii95Ki+veRETb5yJ227p8CBPX1dFr5scok8qLtUvbyqwjxX/cy9prG8vQwnqTy90wa+3PL2vVG6DDq0jYo9maw0vkoM NJjycZY89FBbNvQ3keb0bh/C9fvqJvW0nYL6USCS7h6y9Pc51IL6gjhW9na5gvRuVqD2BhCq+yZAcvQuxhD0jFg2+PUWOvDYjAT1XbIU8PVAgvqBW5jy+P+c9As4FvhuMnr0mhAK9wbrlvZ8dPL7P8pW7b5GzPfMA7b1cAQG+E8d3vGWdlj1rt0W++IlSvc7efT0B0DG+jk2wvac24jyWnnc9at4avpy4Hb0uo8Q9mX/KvTWVIb495eu9HOu7vdD1O75kDS09lhnLPfKfIr4+PAi+173PvQ3AEz0G6ha+5JFJvR+CgT2cyda9oXWjvQhf37y0Khg9FpIGvrGwg7xCws09lji9ves8Nr5gt329La0/vcyvgb6BSR28OQD4PXZ2/r3Cw1q9r2mNvU23vTpchCe+lHzMvQNGwT1Tfze+ts3YvQScbL3SHUM9J2Unvm5tGT1gl2M93+5Nvdd/QL7UaaK8mJo8vYR+Ob52o2M9bQ3OPZPuB75mhRa+GNKCvfulPT0QsheM 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 4hL6XCQW+jpzyvnKvjb1lFzY/iWTWvtrXSTuA8qY+jRL7N0H12z65udO8MlbevSgC1D5pA/O9C/M9v0RxGj++L/e+nargPWw+7T1WCfq+b90DP/sv7b5D3By/by3XPpsHyb0S5qW+m0IeP5tQBz8/QJs+vakTv8ZqTL5uXUO/ktsqvyZLtb7puQM814jwPoHILT828Tq+YxvJPg5tMj+cFym5YUMtv54UCr/VE/e+t4j4vkVRaL4gQXe+1yCiPYSTJb6VO/U95klPPWF1Mb7Jwby9NCrzvfHcAT9LMcS+Mf9oP+Uzrb4rWRK9aRSIvt1qaL/E77I+9JNDv1er9T4BlrG+UTxvP9yLwr3UnsO+m4UQv+oEQ7/RTZq/mcfFvYaUPD2z5uq+fGwrvln7+z6JIQU//QE/v9Z4Xz50NiC+t6ukvtcpHr+Quj++mbi5vnVmKr9kXP0+POEav6TSPr8G82c/AAAAAAAAAABh5x2/N7nNPbntBj9AH4k/AAAAADukm76+FeUM +aOV7Pq0sCr9J9p6+2aOuvu+QG7+gMqk8LWrlvjAyHb3A2yQ+zkSsPgCAJ70g0B69Rg3ZPhEw4r7qVh6//brDPmMzob683IY++lz+vhMQJT/xoM8+uPm8PdlCID5CIGu+0YG+PuKOZb36KSM/lLkJP/UQED7EWke/CPIfv0V2SL/rOuI9ehwBP8zPTz9zHIU8D5wHvwxZfb7CBOy+AFqQPlTI9L3s682+emXmvv7j0z4YTGi+rUwcP0P1rL7lNgo/BWqHvfFSLT83fAA/jgeLvuSSKD//C4K+Di31vpAtTT9NQZO95ZPOvQAAAACB11y9PS6KP8QO1L2bDmA+wxEvPuvyfD1zcZK/UnQdv7j3Ir9fYME+puGEPeLp8D65Lh0/q8dZuzo/ij90DRK+8EF3vq/5GT8A9gM8p5mGv+kjub5EbUe/bBiZvpfmpz/fkZm/0hy4vw0+oL9DnPu+/7ViPr50V7+8jNO+WOQaP9tUrr5D2Nm9Dl5tvg==", "training_trM aits": {"structure_gen": "Symmetric", "n_layers": 5, "max_nodes": 8, "activation_func": "ReLU", "epoch_num": 5}, "classes_name": ["Cryptoadz", "Cryptopunks", "Moonbirds", "Nouns"]},m=25,b=50,y=59+11/12,w=59+11.5/12,v=60;function z(e,t){const n=Math.log(1-t)/Math.log(1-e);return e=>1-Math.pow(1-e,n)}class V{constructor(e,t,n){const{model:r,inputDim:i}=j(t,n);this.model=r,this.inputDim=i,this.iteration=0,this.stage=0;const o=new Date(parseInt(e.birthYear),0,1).getTime(),a=new Date(parseInt(e.birthYear)+1,0,1).getTimeM ();this.birthDate=new Date(Math.floor((o+a)/2));const l=zr.filter((t=>t[0]==e.lifeCycle))[0][2];this.growSpeed=365/l,this.cycleLength=60*l*24*3600*1e3,this.growthFunc=z(.4,.8)}updateAge(e){const t=(e.getTime()-this.birthDate.getTime())/31536e6*this.growSpeed;this.iteration=Math.floor(t/60);const n=t-60*this.iteration;let r;this.age=n;let i,o=0;if(n<25){let e=map(n,0,25,0,1);o=this.growthFunc(e),r=(25-n)/60,this.stage=1,this.stageRatio=map(n,0,25,0,1)}else n<50?(o=1,r=(50-n)/60,this.stage=2,this.stageRatio=map(n,25,M 50,0,1)):n<y?(o=map(n,50,y,1,0),r=(y-n)/60,this.stage=3,this.stageRatio=map(n,50,y,0,1)):n<w?(o=0,r=(w-n)/60,this.stage=4,this.stageRatio=map(n,y,w,0,1)):n<60&&(o=0,r=(60-n)/60,this.stage=5,this.stageRatio=map(n,w,60,0,1));n<50?i=map(n,0,50,0,780/880):n<w?i=map(n,50,w,780/880,800/880):n<60&&(i=map(n,w,60,800/880,1)),this.nextStateTimestamp=Math.round(e.getTime()+this.cycleLength*r),this.statePercentage=round(100*i);let a=(25-n)/60;a<0&&(a+=1),this.nextStableTimestamp=Math.round(e.getTime()+this.cycleLength*a),this.M growth=o,this.model.updateNeurons(o,this.iteration)}getBrainStatus(){return{totalNeurons:this.model.getTotalNeurons(),neuronsLife:this.model.getNeuronsLife(),stage:this.stage,inputDim:this.inputDim,stageRatio:this.stageRatio,age:this.age,growth:this.growth,nextStateTimestamp:this.nextStateTimestamp,nextStableTimestamp:this.nextStableTimestamp,rebirthCount:max(this.iteration,0),statePercentage:this.statePercentage}}classifyImage(e){const t=new G(e,1,e.length);return this.model.forward(t).mat[0]}}class M{constructor(M e,t,n,r,i){this.p=e,this.v=t,this.size=n,this.shape=i,this.col=r}getRadius(){return 1==Oe?1*this.size/2:2==Oe?7*this.size/16:3==Oe||4==Oe?4*this.size/7:0}update(){this.p.add(this.v)}draw(e,t,n,r){const i=this.p.x*r,o=this.p.y*r,a=this.size*r,{col:l,shape:s}=this;let h,c;1==n?h=c=l:2==n?(h=dr(t,1),c=l):(h=dr(t,0),c=dr(l,1));e.stroke(dr(c,map(1,0,1,.25,1))),e.fill(dr(h,map(1,0,1,.15,1))),3==n&&e.fill(dr(h,0)),1==s?e.ellipse(i,o,a,a):2==s?e.rect(i,o,7*a/8,7*a/8):3==s&&(e.beginShape(),e.vertex(i-4*a/7,o),e.vertex(i,o-4M *a/7),e.vertex(i+4*a/7,o),e.vertex(i,o+4*a/7),e.endShape(CLOSE))}}class E{constructor(e,t,n,r,i,o,a){this.center=e,this.len=t,this.angle=n,this.v=r,this.angV=i,this.c1=o,this.c2=a}getEndpoints(){const e=createVector(this.len/2*cos(this.angle),this.len/2*sin(this.angle));return[Vector.add(this.center,e),Vector.sub(this.center,e)]}update(){this.center.add(this.v),this.angle+=this.angV}draw(e,t){const[n,r]=this.getEndpoints(),i=n.x*t,o=n.y*t,a=r.x*t,l=r.y*t,s=this.c1,h=this.c2;var c=e.drawingContext.createLinearGradieM nt(i,o,a,l);c.addColorStop(0,s),c.addColorStop(1,h),e.drawingContext.strokeStyle=c,e.drawingContext.globalAlpha=1,e.line(i,o,a,l),e.drawingContext.globalAlpha=1}}function S(e,t){const n=random(TAU),r=random(e,t);return createVector(r*cos(n),r*sin(n))}class R{constructor(e,t,n,r,i){this.wall=n,this.maxR=i;const o=t.length;this.nodes=[];for(let a=0;a<o;++a){const o=[],l=.25*t[a];for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),l=S(.02*i,.05*i),s=random(10,25)*i;o.push(new MM (t,l,s,e[a],r))}this.nodes.push(o)}const a=A(e);a.unshift(e[0]),a.push(e[e.length-1]),this.lines=[];for(let e=0;e<=o;++e){const r=[],l=(0==e?1:t[e-1])*(e==o?1:t[e])*1.5;for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),o=random(5*i,10*i),l=random(TAU),s=S(.02*i,.05*i),h=random(2e-4,.001);r.push(new E(t,o,l,s,h,a[e],a[e+1]))}this.lines.push(r)}}reflectNode(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,{p:o,v:a}=e,l=e.getRadius();(o.x-l<t&&a.x<0||o.x+l>r&&a.x>0)&&(a.M x=-a.x),(o.y-l<n&&a.y<0||o.y+l>i&&a.y>0)&&(a.y=-a.y)}reflectLine(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,[o,a]=e.getEndpoints(),l=e.v;(min(o.x,a.x)<t&&l.x<0||max(o.x,a.x)>r&&l.x>0)&&(l.x=-l.x),(min(o.y,a.y)<n&&l.y<0||max(o.y,a.y)>i&&l.y>0)&&(l.y=-l.y)}update(){for(const e of this.lines)for(const t of e)t.update(),this.reflectLine(t);for(const e of this.nodes)for(const t of e)t.update(),this.reflectNode(t)}draw(e,t,n,r,i){const o=i/this.maxR;for(const t of this.lines){const n=t.length*r;for(let r=0;r<nM ;++r)t[r].draw(e,o)}for(const i of this.nodes){const a=i.length*r;for(let r=0;r<a;++r)i[r].draw(e,t,n,o)}}}function I(e,t){re(e),e.fill(0),e.rect(0,0,500,500),ie(e),e.noStroke(),e.fill(dr(cr("#000000"),.5)),e.push(),e.translate(250,250),e.scale(t),e.translate(-250,-250),e.beginShape(),e.vertex(235.2,24.9),e.bezierVertex(215,24.6,185,11.4,164.8,11),e.bezierVertex(147.2,10.7,129.3,10.4,112.2,14.7),e.bezierVertex(95.1,19,78.5,28.5,69.6,43.8),e.bezierVertex(57.699,64.199,61.599,90.199,70.199,112.2),e.bezierVertex(78.79M 9,134.2,91.6,154.6,97.199,177.5),e.bezierVertex(102.499,199.2,100.899,222.5,92.799,243.2),e.bezierVertex(83,268,64.6,288.3,48.9,310),e.bezierVertex(33.2,331.7,24.5,337.5,26.599,364.1),e.bezierVertex(28.2,384.1,61.399,404.2,75.7,418.3),e.bezierVertex(90,432.4,73.7,488.2,91.9,496.7),e.bezierVertex(124.2,511.6,159,472.5,194.3,468.1),e.bezierVertex(211.6,465.9,267.4,501.5,283.9,495.9),e.bezierVertex(340.7,476.7,298.599,428.9,355.4,409.7),e.bezierVertex(370.799,404.5,454.5,407.6,464.4,394.8),e.bezierVertex(478.599,376.3M ,474.7,349.3,464.299,328.4),e.bezierVertex(453.9,307.5,438.099,289.5,428.699,268.2),e.bezierVertex(412,230,419,182.6,446.1,150.9),e.bezierVertex(449.7,146.7,453.6,142.7,455.8,137.6),e.bezierVertex(459.4,129.299,457.5,119.6,454.8,111),e.bezierVertex(443.2,73.4,417.3,40.4,383.6,20.299),e.bezierVertex(358.1,5,343.2,-.4,313.5,0),e.bezierVertex(287.5,.4,261.6,25.4,235.2,24.9),e.endShape(),e.pop()}function C(e,t,n,r,i,o){let a,l,s;re(t),t.fill(0),t.rect(0,0,500,500),ie(t),t.noStroke(),t.fill(dr(n,.5)),1==i?(l=0,s=25,a=maM p(o,0,25,500,0)):a=0,t.rect(0,a,500,500),e.noStroke(),e.fill(r),e.rect(0,0,500,500),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.M 7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.M 7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.M 7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),e.fill(n),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,M 453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,1M 97.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,M 21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVerteM x(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),re(e),e.fill(r),e.beginShape(),e.vertex(184.3,473.2),e.bezierVertex(164,473.2,144.7,462.099,134,444.3),e.bezierVertex(131.7,440.5,129.1,438.5,125,437.1),e.bezierVertex(97.3,428.1,80.5,400.6,85.2,371.8),e.bezierVertex(86.3,365.1,85.8,364.1,79.9,361.2),e.bezierVertex(57.2,349.8,46.2,323.3,54.3,299.7),e.bezierVertex(54.7,298.599,55.1,297.7,55.5,296.9),e.bezierVertex(55.6,296.599,55.8,296.4,55.9,296.099),e.vertex(57.9,M 291.499),e.vertex(62.5,293.599),e.bezierVertex(64.9,294.7,67.3,295.799,69.5,296.9),e.bezierVertex(74.5,299.299,79.1,301.599,83.9,303.099),e.bezierVertex(89.8,304.9,96.5,305.499,102.7,305.9),e.bezierVertex(102.8,305.9,102.9,305.9,103,305.9),e.bezierVertex(106.6,305.9,108.9,302.799,109,299.799),e.bezierVertex(109.1,296.199,106.6,293.4,102.7,292.799),e.bezierVertex(101.3,292.599,99.9,292.4,98.4,292.299),e.bezierVertex(94.3,291.799,90.1,291.299,86,289.9),e.bezierVertex(68.9,284,56.5,270.2,52.7,252.799),e.bezierVertex(4M 8.9,235.499,54.5,217.7,67.6,205.299),e.bezierVertex(71.9,201.299,72.7,198.1,70.8,192.399),e.bezierVertex(64.2,172.2,68.8,153.99,84.2,139.599),e.bezierVertex(94.2,130.199,105.5,125.399,117.8,125.399),e.bezierVertex(124.3,125.399,131.1,126.799,137.8,129.599),e.bezierVertex(157,137.399,167.9,152.799,169.4,173.99),e.vertex(169.4,174.399),e.bezierVertex(169.5,175.899,169.6,177.2,169.9,178.299),e.bezierVertex(170.7,181.2,173.2,183.2,176.1,183.2),e.bezierVertex(176.299,183.2,176.5,183.2,176.7,183.2),e.bezierVertex(180.1,1M 82.899,182.6,180.299,182.7,177),e.bezierVertex(183.1,162,178.299,148.2,168.399,136.1),e.bezierVertex(158.2,123.5,144.899,115.8,128.799,113.199),e.bezierVertex(123.499,112.299,120.399,109.799,118.899,104.99),e.bezierVertex(113.899,89.699,120.699,72.299,134.899,64.499),e.bezierVertex(139.99,61.699,145.799,60.199,151.7,60.199),e.bezierVertex(162.2,60.199,171.899,64.799,178.1,72.699),e.bezierVertex(179.6,74.6,180.799,76.6,181.9,78.499),e.vertex(182.2,79.099),e.bezierVertex(183.2,80.699,185.2,83.299,188.4,83.299),e.beziM erVertex(189.5,83.299,190.6,82.99,191.7,82.399),e.bezierVertex(195.1,80.599,196,76.99,194,72.799),e.bezierVertex(190.1,64.799,184.1,58.499,175.6,53.299),e.bezierVertex(174.6,52.699,173.7,52.099,172.5,51.499),e.vertex(170.5,50.299),e.vertex(163,45.899),e.vertex(170.5,41.599),e.bezierVertex(182,34.99,193.1,30.799,204.4,28.599),e.bezierVertex(208.6,27.799,212.9,27.399,217.2,27.399),e.bezierVertex(217.6,27.399,217.9,27.399,218.3,27.399),e.bezierVertex(231.4,27.599,242.7,38.199,243,50.599),e.bezierVertex(243.4,64.899,24M 3.3,78.99,243.2,93.799),e.bezierVertex(243.2,99.799,243.1,105.899,243.1,112.099),e.vertex(243.1,119.199),e.vertex(236.4,116.799),e.bezierVertex(235.7,116.499,235,116.299,234.4,115.99),e.bezierVertex(233.4,115.599,232.6,115.299,232,115.199),e.bezierVertex(230.6,114.899,229.2,114.599,227.8,114.299),e.bezierVertex(223.8,113.499,220.1,112.699,216.4,112.499),e.vertex(216.2,112.499),e.bezierVertex(212.5,112.499,210.7,115.599,210.6,118.599),e.bezierVertex(210.4,122.399,212.7,125.099,216.4,125.399),e.bezierVertex(230.1,126M .399,238.9,133.099,242.3,145.199),e.bezierVertex(243.2,148.399,243.2,151.599,243.2,154.499),e.vertex(243.2,155.099),e.bezierVertex(243.2,254.199,243.2,330,243.2,400.599),e.bezierVertex(243.2,401.99,243.2,403.4,243.2,404.9),e.bezierVertex(243.3,411.099,243.3,417.599,242.3,423.9),e.bezierVertex(238.1,449.2,219.6,467.799,194,472.5),e.bezierVertex(190.9,472.9,187.6,473.2,184.3,473.2),e.endShape(),e.beginShape(),e.vertex(315.8,473.1),e.bezierVertex(309.3,473.1,302.8,472,296.5,469.9),e.bezierVertex(270.4,461,253.8,434.9,M 257.1,407.9),e.bezierVertex(260,384,273.8,366.8,297,358.3),e.bezierVertex(297.7,358.1,298.3,357.8,299,357.6),e.bezierVertex(299.8,357.3,300.6,357.1,301.2,356.8),e.bezierVertex(304.3,355.4,306,351.8,304.9,348.7),e.bezierVertex(304,345.9,301.7,344.2,299,344.2),e.bezierVertex(298.6,344.2,298.1,344.2,297.6,344.3),e.bezierVertex(288.1,346.3,279,350.9,269.7,358.3),e.bezierVertex(268.9,358.9,268.1,359.6,267.2,360.4),e.vertex(265.5,361.8),e.vertex(258.5,367.6),e.vertex(257.4,358.6),e.bezierVertex(257.3,358,257.3,357.5,257.M 2,357.1),e.bezierVertex(257,356,256.9,354.9,256.9,353.7),e.bezierVertex(256.9,334.8,256.9,316,256.9,297.1),e.bezierVertex(256.9,260.3,256.9,222.3,256.8,185),e.bezierVertex(256.8,170.7,268.3,158.8,282.5,158.4),e.bezierVertex(284.8,158.3,286.7,157.6,287.9,156.2),e.bezierVertex(289.099,154.9,289.599,153.2,289.5,151.3),e.bezierVertex(289.3,147.5,286.7,145.1,282.7,145.1),e.bezierVertex(282.5,145.1,282.2,145.1,282,145.1),e.bezierVertex(278.8,145.3,275.5,146.1,272,146.9),e.bezierVertex(270.9,147.2,269.8,147.4,268.6,147.7)M ,e.bezierVertex(267.9,147.9,267,148.2,265.8,148.7),e.bezierVertex(265.1,149,264.4,149.3,263.5,149.6),e.vertex(256.8,152),e.vertex(256.8,114.6),e.bezierVertex(256.8,95,256.8,75.4,256.8,55.9),e.bezierVertex(256.8,38,267.2,27.3,284.6,27.3),e.bezierVertex(285.3,27.3,285.9,27.3,286.6,27.3),e.bezierVertex(299,27.9,318.7,34.5,329.6,41.9),e.vertex(336.1,46.3),e.vertex(324.4,53.3),e.bezierVertex(316.2,58.2,310.2,64.6,306,72.9),e.bezierVertex(304.2,76.4,305.1,78.5,306.1,80),e.bezierVertex(307.4,81.9,309.4,83,311.6,83),e.beziM erVertex(313.7,83,315.7,81.9,317.1,80.1),e.bezierVertex(317.4,79.7,317.8,79,318.1,78.4),e.bezierVertex(318.4,77.9,318.7,77.3,319,76.8),e.bezierVertex(325.3,66.2,336.3,59.9,348.5,59.9),e.bezierVertex(353.2,59.9,357.8,60.8,362.1,62.7),e.bezierVertex(377.6,69.3,386,86.7,381.7,103.2),e.bezierVertex(380.7,107.1,378.5,111.8,371.1,113.1),e.bezierVertex(342.7,118.1,322.2,139.1,317.8,167.8),e.bezierVertex(317.4,170.3,317.3,173.2,317.4,176.5),e.bezierVertex(317.5,180,320.1,182.8,323.5,183),e.bezierVertex(323.6,183,323.8,183,M 323.9,183),e.bezierVertex(327.1,183,329.8,180.6,330.3,177.2),e.bezierVertex(330.6,175.7,330.7,174,330.9,172.3),e.bezierVertex(331.1,169.8,331.4,167.3,332,164.7),e.bezierVertex(337.3,141.9,357.7,125.4,380.7,125.4),e.bezierVertex(382.5,125.4,384.3,125.5,386.1,125.7),e.bezierVertex(412.8,128.9,432.6,150.9,432,176.9),e.bezierVertex(431.9,182.3,430.9,187.7,429.1,192.7),e.bezierVertex(427.2,197.9,428,201,432.3,205),e.bezierVertex(446.8,218.7,451.8,236,446.6,255),e.bezierVertex(441.4,274,428.3,286.5,408.7,291.3),e.bezierVM ertex(406.1,291.9,403.6,292.1,401.1,292.3),e.bezierVertex(400,292.4,398.9,292.5,397.9,292.6),e.bezierVertex(393.6,293.1,390.9,295.7,391,299.5),e.bezierVertex(391.1,303.4,394,305.8,398.5,305.8),e.bezierVertex(409.9,305.8,420.8,302.6,431.1,296.4),e.bezierVertex(431.8,296,432.5,295.5,433.2,295.1),e.bezierVertex(433.8,294.7,434.5,294.3,435.2,293.9),e.bezierVertex(436,293.4,436.6,293.2,437.2,293.1),e.bezierVertex(437.4,293,437.7,292.9,438.1,292.8),e.vertex(442.5,291.4),e.vertex(444.2,295.7),e.bezierVertex(450.9,312.4,44M 9.5,328.4,440,343.4),e.bezierVertex(435.3,350.8,428.7,356.7,420.2,361.1),e.bezierVertex(414.3,364.1,413.7,365.2,414.8,371.7),e.bezierVertex(419.5,400.2,403,427.6,375.6,436.9),e.bezierVertex(371,438.5,368.3,440.7,365.8,444.7),e.bezierVertex(355.2,462.5,336.4,473.1,315.8,473.1),e.bezierVertex(315.8,473.1,315.8,473.1,315.8,473.1),e.endShape(),ie(e),e.fill(n),e.beginShape(),e.vertex(120.2,279.9),e.bezierVertex(117.9,279.9,112.4,279.299,112.2,273.599),e.bezierVertex(112,267.7,117.4,266.7,119.7,266.599),e.bezierVertex(13M 3.1,265.799,143.1,259.499,149.3,247.899),e.bezierVertex(149.6,247.299,150.1,246.399,150.3,245.399),e.bezierVertex(150.6,244.299,150.5,243.299,150.5,242.7),e.bezierVertex(150.5,242.6,150.5,242.5,150.5,242.299),e.vertex(150.3,238.799),e.vertex(141.1,235.99),e.bezierVertex(114.6,227.799,95.6,202.499,95.9,175.799),e.bezierVertex(95.9,173.99,96.4,168.199,102.2,168.199),e.bezierVertex(102.6,168.199,103,168.199,103.4,168.299),e.bezierVertex(104.8,168.499,108.2,168.899,109.2,175.599),e.bezierVertex(109.3,176.599,109.5,177.M 599,109.6,178.499),e.bezierVertex(110.4,184.199,111.3,189.99,113.7,195.499),e.bezierVertex(121.9,213.99,139.5,225.499,159.7,225.499),e.bezierVertex(172.1,225.499,184.1,220.899,193.5,212.599),e.bezierVertex(194,212.199,194.4,211.799,194.8,211.399),e.bezierVertex(195.1,211.099,195.5,210.799,195.8,210.399),e.bezierVertex(197.4,208.99,199.2,208.2,200.9,208.2),e.bezierVertex(202.5,208.2,204,208.899,205.3,210.1),e.bezierVertex(208,212.9,207.9,216.9,205,219.9),e.bezierVertex(196.5,228.6,186.3,234.3,174.7,236.8),e.bezierVeM rtex(168.799,238.1,165.6,241,163.899,246.7),e.bezierVertex(158.3,265.9,139.9,279.7,120.2,279.9),e.vertex(120.2,279.9),e.endShape(),e.beginShape(),e.vertex(187.2,427.5),e.bezierVertex(183.799,427.5,181.299,425.3,180.799,422),e.bezierVertex(180.6,420.8,180.499,419.5,180.399,418.1),e.bezierVertex(180.299,417,180.2,415.8,180.099,414.7),e.bezierVertex(177.199,390.5,156.699,371.3,132.399,370.2),e.bezierVertex(131.99,370.2,131.499,370.2,131.099,370.2),e.bezierVertex(130.699,370.2,130.299,370.2,129.799,370.2),e.bezierVerteM x(125.99,369.9,123.199,367.2,123.099,363.6),e.bezierVertex(122.99,360.2,125.799,357.3,129.599,356.9),e.bezierVertex(130.499,356.8,131.499,356.8,132.599,356.7),e.bezierVertex(133.199,356.7,133.799,356.7,134.399,356.6),e.vertex(138.299,356.4),e.vertex(139.1,352.6),e.bezierVertex(139.5,350.7,139.799,348.9,140.2,347),e.bezierVertex(140.899,343.4,141.5,340,142.399,336.8),e.bezierVertex(150.099,310.7,174.399,292,201.399,291.3),e.vertex(201.599,291.3),e.bezierVertex(203.699,291.3,206.299,292,208.299,293.2),e.bezierVertex(M 210.499,294.5,210.699,297.5,209.99,299.8),e.bezierVertex(209.499,301.5,208.199,303.9,203.299,304.7),e.bezierVertex(202.199,304.9,200.99,305,199.799,305.2),e.bezierVertex(194.499,305.9,188.99,306.599,183.799,308.9),e.bezierVertex(165.499,316.799,155.199,331.299,152.99,352),e.bezierVertex(152.399,357.8,154.499,361.7,159.699,364.5),e.bezierVertex(178.199,374.4,189.399,390,193.099,410.9),e.bezierVertex(193.699,414.299,193.899,418,193.599,422),e.bezierVertex(193.399,425.2,190.899,427.5,187.399,427.5),e.vertex(187.2,427.M 5),e.endShape(),e.beginShape(),e.vertex(364.3,281.1),e.bezierVertex(346.3,280.6,332.9,272.8,323.5,257),e.bezierVertex(321.6,253.9,320.4,250.2,319.2,246.7),e.bezierVertex(317.7,242.2,315,239.799,310.5,238.799),e.bezierVertex(298.5,236.299,288,230.7,279.4,222.1),e.bezierVertex(276.7,219.4,274.9,215.299,278,211.9),e.bezierVertex(279.4,210.3,281,209.6,282.6,209.6),e.bezierVertex(284.4,209.6,286.4,210.6,288.3,212.5),e.bezierVertex(297.8,221.8,310.4,226.9,323.9,226.9),e.bezierVertex(340.2,226.9,355.1,219.3,364.8,206.2),eM .bezierVertex(371,197.8,374.2,188.5,374.5,178.5),e.vertex(374.5,177.9),e.bezierVertex(374.5,177,374.5,176.1,374.7,175.4),e.bezierVertex(375.3,171.8,377.9,169.5,381.3,169.5),e.bezierVertex(381.4,169.5,381.5,169.5,381.7,169.5),e.bezierVertex(385.4,169.7,388,172.4,388,176.1),e.bezierVertex(388.1,190.7,383.4,204,374.2,215.8),e.bezierVertex(365.8,226.5,354.7,233.9,341.2,237.9),e.bezierVertex(340,238.3,338.7,238.6,337.3,239.1),e.bezierVertex(335.9,239.6,335.1,240.4,334.7,240.9),e.bezierVertex(334.599,241,334.5,241.1,334.M 4,241.2),e.vertex(331.799,243.6),e.vertex(333.199,246.8),e.bezierVertex(338.199,258,346.799,264.9,358.699,267.3),e.bezierVertex(360.199,267.6,361.599,267.7,362.99,267.9),e.bezierVertex(363.599,268,364.299,268,364.899,268.1),e.bezierVertex(369.099,268.6,371.799,271.4,371.499,275),e.bezierVertex(371.199,278.6,368.299,281.2,364.399,281.2),e.vertex(364.3,281.1),e.endShape(),e.beginShape(),e.vertex(323.9,437),e.bezierVertex(323.7,437,323.5,437,323.299,437),e.bezierVertex(319.599,436.7,317.299,434.1,317.4,430.2),e.bezierM Vertex(317.9,406.099,328.299,388,349.5,375),e.bezierVertex(350.7,374.2,352,373.5,353.4,372.8),e.bezierVertex(354.099,372.4,354.7,372.1,355.299,371.7),e.vertex(357.499,370.5),e.vertex(357.799,368),e.bezierVertex(360.4,346.6,345.199,323.7,323.9,317),e.bezierVertex(319.099,315.5,314.099,314.9,309.299,314.4),e.vertex(308.199,314.299),e.bezierVertex(305.99,314.099,300.799,312.9,300.899,307.299),e.bezierVertex(300.99,303.499,303.899,300.9,308.099,300.9),e.vertex(308.299,300.9),e.bezierVertex(327.099,301.299,343.099,308.7M ,355.699,322.9),e.bezierVertex(364.299,332.5,369.399,344.099,370.99,357.299),e.bezierVertex(371.099,358.4,371.299,359.4,371.499,360.499),e.bezierVertex(371.599,360.99,371.699,361.499,371.799,361.99),e.vertex(372.499,365.899),e.vertex(377.899,366.199),e.bezierVertex(378.799,366.299,379.699,366.299,380.599,366.399),e.bezierVertex(385.099,366.699,387.899,369.399,387.799,373.299),e.bezierVertex(387.699,377.099,384.99,379.599,380.799,379.799),e.bezierVertex(369.799,380.199,359.99,383.299,351.899,389.299),e.bezierVertex(M 338.799,398.799,331.699,411.699,330.699,427.499),e.vertex(330.699,428.299),e.bezierVertex(330.599,429.199,330.599,430.099,330.499,430.799),e.bezierVertex(330,434.7,327.5,437,323.9,437),e.endShape()}function T(e){return e[0].map(((t,n)=>e.map((e=>e[n]))))}function A(e){return e.map((e=>Array.isArray(e)?A(e):e))}function D(e,t){return floor(random(e,t))}function k(e){let t=0;for(const n of e)t+=n[1];let n=random(t),r=0;for(const t of e)if(r+=t[1],n<r)return t[0];return null}function L(e){for(let t=1;t<e.length;++t){lM et n=D(0,t),r=e[t];e[t]=e[n],e[n]=r}}function P(e){return null==e||""===e}function O(e){return new Promise((t=>setTimeout(t,e)))}function F(e,t,n){let r=0;for(let i=1;i<=1e3;++i)for(let o=1;o<=1e3;++o)if(e*o%(t*i)==0){let e=1*i/o;abs(e-n)<abs(r-n)&&(r=e)}return r}function N(){let e=60*(new Date).getTimezoneOffset()*1e3;return new Date(Date.now()-e).toISOString().slice(0,-1)}function B(e,t,n){let r;if(push(),textSize(e),textWidth(t)<=n)r=t;else for(let e=0;e<t.length;++e){const i=t.slice(0,e+1)+"...";if(textWidth(i)M >n){r=i;break}}return pop(),r}function Y(e){var t=e%10,n=e%100;return 1==t&&11!=n?e+"st":2==t&&12!=n?e+"nd":3==t&&13!=n?e+"rd":e+"th"}class G{constructor(e,t,n){this.n=t,this.m=n,this.mat=[];let r=0;for(let t=0;t<this.n;++t){this.mat.push([]);for(let n=0;n<this.m;++n)this.mat[t].push(r<e.length?e[r]:0),r+=1}return this}copy(){return new G(this.mat.flat(),this.n,this.m)}}class H{static __linear=e=>e;static __relu=e=>Math.max(e,0);static __leaky_relu=e=>e>0?e:.2*e;static __sigmoid=e=>1/(1+Math.exp(-e));static __tanh=M e=>Math.tanh(e);static __apply_unary_op(e,t){const n=e.copy();for(let e=0;e<n.n;++e)for(let r=0;r<n.m;++r)n.mat[e][r]=t(n.mat[e][r]);return n}static linear=e=>H.__apply_unary_op(e,H.__linear);static relu=e=>H.__apply_unary_op(e,H.__relu);static leaky_relu=e=>H.__apply_unary_op(e,H.__leaky_relu);static sigmoid=e=>H.__apply_unary_op(e,H.__sigmoid);static tanh=e=>H.__apply_unary_op(e,H.__tanh);static __add=(e,t)=>e+t;static __mul=(e,t)=>e*t;static __apply_binary_op=(e,t,n)=>{"object"!=typeof t&&(t=new G([t],1,1));consM t r=e.copy();for(let e=0;e<r.n;++e)for(let i=0;i<r.m;++i)r.mat[e][i]=n(r.mat[e][i],t.mat[e%t.n][i%t.m]);return r};static mul=(e,t)=>H.__apply_binary_op(e,t,H.__mul);static add=(e,t)=>H.__apply_binary_op(e,t,H.__add);static matMul(e,t){const n=new G([],e.n,t.m);for(let r=0;r<n.n;++r)for(let i=0;i<n.m;++i)for(let o=0;o<e.m;++o)n.mat[r][i]+=e.mat[r][o]*t.mat[o][i];return n}static softmax(e){const t=H.__apply_unary_op(e,(e=>Math.exp(e))),n=t.mat.flat().reduce(((e,t)=>e+t));for(let r=0;r<e.n;++r)for(let i=0;i<e.m;++i)t.M mat[r][i]/=n;return t}}class ${constructor(e,t){this.scale=e,this.offset=t}forward(e){return H.add(H.mul(e,this.scale),this.offset)}}class X{constructor(){}forward(e){return e.map((e=>e.flat()))}}class W{constructor(e,t,n,r){this.out_dim=e,this.activation=t,this.w=n,this.b=r}forward(e){const t=H.add(H.matMul(e,this.w),this.b);return null==this.activation?t:this.activation(t)}}class U{constructor(e,t,n){this.preprocessLayers=e,this.hiddenLayers=t,this.outputLayer=n,this.totalNeurons=this.hiddenLayers.map((e=>e.out_dM im)),this.currentOrders=[],this.currentIteration=null}updateNeurons(e,t){if(t!=this.currentIteration){this.currentOrders=[];for(let e=0;e<this.totalNeurons.length;++e){randomSeed(100*(t+1)+e);const n=[];for(let t=0;t<this.totalNeurons[e];++t)n.push(t);L(n),this.currentOrders.push(n)}this.currentIteration=t}const n=A(this.totalNeurons),r=n.reduce(((e,t)=>e+t))*(1-e);for(let e=0;e<r;++e){const t=n.map(((e,t)=>(e-1)/this.totalNeurons[t]));n[t.map(((e,t)=>[e,t])).reduce(((e,t)=>t[0]>e[0]?t:e))[1]]-=Math.min(r-e,1)}thisM .neuronsLife=[];for(let e=0;e<n.length;++e){const t=this.currentOrders[e],r=Array(this.totalNeurons[e]).fill(0);for(let i=0;i<n[e];++i)r[t[i]]=Math.min(n[e]-i,1);this.neuronsLife.push(r)}}getTotalNeurons(){return A(this.totalNeurons)}getNeuronsLife(){return A(this.neuronsLife)}forward(e){for(const t of this.preprocessLayers)e=t.forward(e);for(const[t,n]of this.hiddenLayers.entries()){e=n.forward(e);const r=new G(this.neuronsLife[t],1,e.m);e=H.mul(e,r)}return e=this.outputLayer.forward(e),H.softmax(e)}}function q(e)M {switch(e){case"relu":return H.relu;case"sigmoid":return H.sigmoid;case"tanh":return H.tanh;case"leaky_relu":return H.leaky_relu;default:return H.linear}}function j(e,t){const n=[],r=[],i=Z(t);let o=null,a=0,l=[];for(const t of e.config.layers)if("InputLayer"==t.class_name)o=t.config.batch_input_shape.slice(1),l=o;else if("Rescaling"==t.class_name)n.push(new $(t.config.scale,t.config.offset));else if("Flatten"==t.class_name)o=[o.reduce(((e,t)=>e*t))];else if("Dense"==t.class_name){const e=[t.config.units],n=o[0]*e[M 0],l=e[0],s=i.subarray(a,a+n);a+=n;const h=i.subarray(a,a+l);a+=l;const c=new G(s,o[0],e[0]),u=new G(h,1,e[0]),f=q(t.config.activation);r.push(new W(e[0],f,c,u)),o=e}const s=r.pop();return{model:new U(n,r,s),inputDim:l}}function Z(e){const t=window.atob(e),n=t.length/Float32Array.BYTES_PER_ELEMENT,r=new DataView(new ArrayBuffer(Float32Array.BYTES_PER_ELEMENT)),i=new Float32Array(n);let o=0;for(let e=0;e<n;e++){o=4*e;for(let e=0;e<4;++e)r.setUint8(e,t.charCodeAt(o+e));i[e]=r.getFloat32(0,!0)}return i}class K{construM ctor(e){this.elt=e,this._events={},this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight}position(){if(0===arguments.length)return{x:this.elt.offsetLeft,y:this.elt.offsetTop};var e="absolute";return"static"!==arguments[2]&&"fixed"!==arguments[2]&&"relative"!==arguments[2]&&"sticky"!==arguments[2]&&"initial"!==arguments[2]&&"inherit"!==arguments[2]||(e=arguments[2]),this.elt.style.position=e,this.elt.style.left=arguments[0]+"px",this.elt.style.top=arguments[1]+"px",this.x=arguments[0],this.y=arguments[1]M ,this}show(){return this.elt.style.display="block",this}hide(){return this.elt.style.display="none",this}size(e,t){if(0===arguments.length)return{width:this.elt.offsetWidth,height:this.elt.offsetHeight};var n=e,r=t;if(n!==te||r!==te){if(n===te?n=t*this.width/this.height:r===te&&(r=e*this.height/this.width),this.elt instanceof HTMLCanvasElement){var i,o={},a=this.elt.getContext("2d");for(i in a)o[i]=a[i];for(i in this.elt.setAttribute("width",n*this._pInst._pixelDensity),this.elt.setAttribute("height",r*this._pInst.M _pixelDensity),this.elt.style.width=n+"px",this.elt.style.height=r+"px",this._pInst.scale(this._pInst._pixelDensity,this._pInst._pixelDensity),o)this.elt.getContext("2d")[i]=o[i]}else this.elt.style.width=n+"px",this.elt.style.height=r+"px",this.elt.width=n,this.elt.height=r;this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight,this._pInst&&this._pInst._curElement&&this._pInst._curElement.elt===this.elt&&(this._pInst._setProperty("width",this.elt.offsetWidth),this._pInst._setProperty("height",this.elt.oM ffsetHeight))}return this}style(e,t){if(t instanceof Color&&(t="rgba("+t.levels[0]+","+t.levels[1]+","+t.levels[2]+","+t.levels[3]/255+")"),void 0===t){if(-1===e.indexOf(":"))return window.getComputedStyle(this.elt).getPropertyValue(e);for(var n=e.split(";"),r=0;r<n.length;r++){var i=n[r].split(":");i[0]&&i[1]&&(this.elt.style[i[0].trim()]=i[1].trim())}}else if(this.elt.style[e]=t,"width"===e||"height"===e||"left"===e||"top"===e){var o=window.getComputedStyle(this.elt).getPropertyValue(e).replace(/[^\d.]/g,"");thisM [e]=Math.round(parseFloat(o,10))}return this}value(){return arguments.length>0?(this.elt.value=arguments[0],this):"range"===this.elt.type?parseFloat(this.elt.value):this.elt.value}mouseClicked(e){return this._adjustListener("click",e,this),this}isFocused(){return document.activeElement===this.elt}_adjustListener(e,t,n){return!1===t?this._detachListener(e,n):this._attachListener(e,t,n),this}_attachListener(e,t,n){n._events[e]&&this._detachListener(e,n);var r=t.bind(n);n.elt.addEventListener(e,r,!1),n._events[e]=r}_dM etachListener(e,t){var n=t._events[e];t.elt.removeEventListener(e,n,!1),t._events[e]=null}}function J(e,t){var n=document.createElement("button");return n.innerHTML=e,t&&(n.value=t),ee(n)}function Q(e){var t=arguments.length>1&&void 0!==arguments[1]&&arguments[1],n=function(t){var n=!0,r=!1,i=void 0;try{for(var o,a=t.target.files[Symbol.iterator]();!(n=(o=a.next()).done);n=!0){var l=o.value;File._load(l,e)}}catch(e){r=!0,i=e}finally{try{n||null==a.return||a.return()}finally{if(r)throw i}}};if(window.File&&window.FiM leReader&&window.FileList&&window.Blob){var r=document.createElement("input");return r.setAttribute("type","file"),t&&r.setAttribute("multiple",!0),r.addEventListener("change",n,!1),ee(r)}}function ee(e){return document.body.appendChild(e),new K(e)}createImg=function(){var e,t=document.createElement("img"),n=arguments;return n.length>1&&"string"==typeof n[1]&&(t.alt=n[1]),n.length>2&&"string"==typeof n[2]&&(t.crossOrigin=n[2]),t.src=n[0],e=ee(t,this),t.addEventListener("load",(function(){e.width=t.offsetWidth||t.wiM dth,e.height=t.offsetHeight||t.height;var r=n[n.length-1];"function"==typeof r&&r(e)})),e},createInput=function(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:"",t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:"text",n=document.createElement("input");return n.setAttribute("value",e),n.setAttribute("type",t),ee(n,this)};const te="auto";function ne(e){re(e);const t=e._rectMode;e.rectMode(CORNER),e.rect(0,0,e.width,e.height),e.rectMode(t),ie(e)}function re(e){e.push(),e.fill(255,255,255,255),eM .blendMode(REMOVE)}function ie(e){e.blendMode(BLEND),e.pop()}File=function(e,t){this.file=e,this._pInst=t;var n=e.type.split("/");this.type=n[0],this.subtype=n[1],this.name=e.name,this.size=e.size,this.data=void 0},File._createLoader=function(e,t){var n=new FileReader;return n.onload=function(n){var r=new File(e);if("application/json"===r.file.type)r.data=JSON.parse(n.target.result);else if("text/xml"===r.file.type){var i=(new DOMParser).parseFromString(n.target.result,"text/xml");r.data=new XML(i.documentElement)}M else r.data=n.target.result;t(r)},n},File._load=function(e,t){if(/^text\//.test(e.type)||"application/json"===e.type)File._createLoader(e,t).readAsText(e);else if(/^(video|audio)\//.test(e.type)){var n=new File(e);n.data=URL.createObjectURL(e),t(n)}else File._createLoader(e,t).readAsDataURL(e)},XML=function(e){if(e)this.DOM=e;else{var t=document.implementation.createDocument(null,"doc");this.DOM=t.createElement("root")}},document.addEventListener("DOMContentLoaded",(function(){addEventListener("mousemove",(e=>{windM ow.mouseX=e.pageX,window.mouseY=e.pageY}))})),new e("global");const oe="190";let ae,le,se,he,ce,ue,fe,de,xe,ge,pe,me,be,ye,we,ve,ze,Ve,_e,Me,Ee,Se,Re,Ie,Ce,Te,Ae,De,ke,Le,Pe,Oe,Fe,Ne,Be,Ye,Ge,He,$e,Xe,We,Ue,qe,je,Ze,Ke,Je,Qe,et,tt,nt,rt,it,ot,at,lt,st,ht,ct,ut,ft,dt,xt,gt,pt,mt,bt,yt,wt,vt,zt,Vt,_t,Mt,Et,St,Rt,It,Ct,Tt,At=!1,Dt=!1,kt=!0,Lt=!1,Pt=!1;const Ot=[" ","Growing","Stable","Decaying","Dead","Rebirth"];let Ft,Nt,Bt,Yt,Gt,Ht,$t,Xt,Wt,Ut,qt,jt,Zt,Kt,Jt,Qt,en,tn,nn,rn,on,an,ln,sn,hn=0,cn=0,un=0,fn=!1,dn=!0,xn=!M 0,gn=null,pn=null,mn=null,bn=!1,yn=!1,wn=null,vn=null,zn=!1;async function setup(){let e=windowWidth,t=windowHeight;createCanvas(e,t),et=createGraphics(e,t),Xe=createGraphics(e,t),$e=createGraphics(e,t),We=createGraphics(e,t),Ue=createGraphics(e,t),qe=createGraphics(e,t),Qe=createGraphics(e,t),je=createGraphics(e,t),Ze=createGraphics(e,t),Ke=createGraphics(e,t),Je=createGraphics(e,t),tt=createGraphics(500,500),nt=createGraphics(500,500),rt=createGraphics(500,500),_n(),Mn(),Sn(),await En(),Gn(),Rn(),bn=!0}function _M n(){Et=parseInt(oe),randomSeed(Et),noiseSeed(Et)}function Mn(){Wt=Ir(p.training_traits),Cr(Wt)}async function En(){let e;Jt=r(),Qt=o(),[Xt,e]=await Promise.all([s(Jt),h(Qt)]),Ut=new V(Wt.visual,e.layers_config,e.weight_b64),Ut.updateAge(new Date),_n(),Wt.training=e.training_traits,Ht=e.model_name,$t=e.classes_name}function Sn(){le=min(width,height)/1024,ut=Rr.findIndex((e=>e[0]===Wt.visual.colorPalette)),ft=[["#ffffff","#231f20","#231f20"],["#231f20","#ffffff","#ffffff"],["#104da8","#ffffff","#ffffff"],["#722F1F","M #FCE1B2","#FCE1B2"],["#e88120","#f9f2e5","#f9f2e5"],["#f6b941","#2E2E2E","#2E2E2E"],["#45daaa","#012221","#012221"],["#F1F1F1","#328DFE","#328DFE"],["#111822","#D3EB8D","#D3EB8D"],["#713FF9","#D6D5E6","#D6D5E6"],["#FBDA9D","#795106","#795106"],["#8f5b62","#ead0d0","#ead0d0"],["#eae4cb","#508cac","#508cac"],["#ffc6cc","#cc313d","#cc313d"],["#60A900","#E0FE00","#E0FE00"],["#507DBE","#D0D1D3","#D0D1D3"],["#305848","#E8F2EE","#E8F2EE"],["#2a2634","#5b6988","#cb78a2","#5b6988"],["#590e29","#fd5e53","#fd5e53","#ffe373"],M ["#0a141d","#57d4e4","#328195","#2A9ECF","#0ab6a8","#57d4e4"],["#3a2d28","#d5c2ac","#df6338","#3d9895","#d5c2ac"],["#030706","#77c4d9","#77c4d9","#77c4d9","#ffffff","#ffffff","#e72020","#e72020"],["#3a4664","#92f5ff","#f9ff94","#eaa0a2","#55dde0"],["#fbfaff","#f04bb1","#f04bb1","#fac373","#82cef0","#8b31ce"],["#000000","#ffffff","#ff0002","#f26522","#fdff00","#00ff03","#01fffe","#0000ff","#ff00ff"]];for(let e=0;e<ft.length;++e)for(let t=0;t<ft[e].length;++t)ft[e][t]=cr(ft[e][t]);pt=[],ct=ft[ut][0],st=ft[ut][1]}funcM tion Rn(){gn=document.querySelector("#upload"),pn=document.querySelector("#inputUpload"),gn.addEventListener("dblclick",(()=>{if(!Lt&&!yn)if(In(Ie)&&cn==Ve-1)pn.click();else{if(4!=Pe&&5!=Pe&&(In(Ie)||cn!=Ve-1))return;fn=!0,dn=!0,Bt=0,un=0}})),pn.addEventListener("click",(()=>{pn.value=null,gn.style.display="block"})),pn.addEventListener("change",(()=>{const[e]=pn.files;e?(se=null,gn.style.display="none",Tn(URL.createObjectURL(e)),mn=e):gn.style.display="block"}))}function In(e){for(let t=0;t<e.length;++t){let n=0;fM or(let r=0;r<e[t].length;++r)e[t][r]>0&&++n;if(0==n)return!1}return!0}function Cn(){null!=se&&(un=0,Pt=!0,he=0,ue=0,drewLineAnim=!0,ce=(ae/2+we/2)/le,loadImage(se.elt.src,(e=>{const[t,n,r]=Gt,i=createGraphics(t,n);i.image(e,0,0,t,n),i.loadPixels();const o=i.pixels.filter(((e,t)=>t%4!=3)),a=Ut.classifyImage(o);Zt=T([a,$t.map((e=>e.toUpperCase()))]).sort(((e,t)=>e[0]>t[0]?-1:1))})))}function Tn(e){se=createImg(e,""),se.hide(),Cn()}function An(){zn||(ce+=(width-ae-we)/tn/le),re(Xe),Xe.rect(ce*le,0,width,height),ie(Xe)M ,un>=ge&&1==kt&&(kt=!1,un-=ge),kt&&(re($e),$e.strokeWeight(2*Fe),Jn(he,ze,ct,ct,$e),ie($e)),un>=ge&&0==kt&&(kt=!0,un-=ge,he+=1,he==en&&(++ue,he=0,ce=(ae/2+we/2)/le,1==ue&&(Pt=!1,Dn(),ye=millis())))}function Dn(){At=!0,pe=!1,me=!1,tryButton=br("Try Again",width/2-225*le,height/2+265*le,290*le,40*le,kn),closeResultButton=br("Close",width/2+75*le,height/2+265*le,150*le,40*le,Ln)}function kn(){At=!1,tryButton.hide(),closeResultButton.hide(),pn.click()}function Ln(){Yt=!0,At=!1,Gn(),tryButton.hide(),closeResultButton.hiM de(),gn.style.display="block",se=null}function keyTyped(){bn&&!1===yn&&!1===yr()&&("i"!==key&&"I"!==key||(Dt=!Dt),"b"!==key&&"B"!==key||(xn=!xn),"s"!==key&&"S"!==key||!1!==Lt||saveCanvasAtCurrentTime(),"k"!==key&&"K"!==key||!1!==Lt||save4KCanvasAtCurrentTime(),"u"!==key&&"U"!==key||!1!==Lt||!1!==At||!1!==fn||!1!==Pt||On())}function On(){Lt=!0,wn=null,vn=null,submitButton=br("Submit",width/2-155*le,height/2+115*le,150*le,40*le,Fn),closeSettingButton=br("Close",width/2+5*le,height/2+115*le,150*le,40*le,Yn),vt=createIM nput(),vt.position(width/2-252.5*le,height/2-40*le),vt.size(500*le,25*le),vt.style("font-size","15px"),vt.value(Jt||""),zt=createInput(),zt.position(width/2-252.2*le,height/2+35*le),zt.size(500*le,25*le),zt.style("font-size","15px"),zt.value(Qt||"")}function Fn(){Vt=vt.value(),_t=zt.value(),submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide(),Lt=!1,yn=!0,Nn()}async function Nn(){[wn,vn,_]=await Promise.all([c(Vt),u(_t),O(1e3)]),yn=!1,wn&&vn?(n(Vt),i(_t),window.location.reload()):(Lt=!0,submitButton.shoM w(),closeSettingButton.show(),vt.show(),zt.show())}function Bn(){Je.textFont("Trebuchet MS"),Je.noStroke(),pr(Je,600*le,200*le),Je.strokeWeight(1*le),Je.stroke(xt),Je.fill(xt),Je.textSize(50*le),Je.text("update()",width/2,height/2+2.5*le)}function Yn(){wn=null,vn=null,Lt=!1,submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide()}function Gn(){_n(),nn=Date.now(),pe=!1,me=!1,St=Wt.training.structure_gen,Rt=Wt.visual.birthYear,It=Wt.visual.lifeCycle,Ct=Wt.training.epoch_num,Tt=Wt.training.activation_func,Ft=M Mr.findIndex((e=>e[0]==Wt.visual.hardwareAcceleration))+1,1==Ft?(Nt=30,fe=40):2==Ft?(Nt=15,fe=20):(Nt=2,fe=10);const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(M Mt),`Perceptron #${Et}`,$t),ae=100*le,ht=50*le,Oe=Sr.findIndex((e=>e[0]==Wt.visual.nodeShape))+1,dt=Er.findIndex((e=>e[0]==Wt.visual.nodeFill))+1,lt=_r.findIndex((e=>e[0]==Wt.visual.pattern))+1,de=Math.tanh(Math.log10(Xt.avgfeerate)),de=map(de,0,1,.2,.8),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<IM e.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=M max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,at=.7,pt=[],xtM =ft[ut][2],gt=ft[ut][ft[ut].length-1];for(let e=3;e<ft[ut].length-1;e++)pt.push(ft[ut][e]);mt=sr(xt,gt,pt,width),bt=[],wt=[],yt=width/(Ve-1);for(let e=0;e<Ve;e++)bt.push(hr(mt,yt*e/width)),wt.push(hr(mt,yt*e/width));wt.unshift(bt[0]),wt.push(bt[bt.length-1]),hn=0,cn=0,un=0,Yt=!0;const n={xLeft:ae/8,xRight:width-ae/8,yTop:ae/8,yBottom:height-ae/8},r=Ce.map((e=>e.length));jt=new R(bt,r,n,Oe,le)}function Hn(e,t){let n=Ce[e].length;return[e*we+we/2+ae/2,height/2-(n-1)/2*ve+t*ve]}function $n(e,t){le=min(e,t)/1024,ae=100M *le,ht=50*le,we=(e-ae)/Ve,ve=(t-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}xe=floor(De.length*de),Le=[],ke=[],ge=floor(map(de,.2,.8,15,2));for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,mt=sr(xt,gt,pt,e),bt=[],wt=[],yt=e/(Ve-1);for(let t=0;t<Ve;t++)bt.push(hr(mt,yt*t/M e)),wt.push(hr(mt,yt*t/e));wt.unshift(bt[0]),wt.push(bt[bt.length-1])}function Xn(){const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t)M ,inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),M n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,M 1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le}function Wn(){jt.update();const e=4==Pe?0:Kt;jt.draw(Qe,ct,dt,e,le)}function Un(){if(!bn)return ar(),void et.image(je,0,0);if(4==Pe||5==Pe)return Wn(),void et.image(Qe,0,0);un>=Nt&&hn<Ve&&(hn++,un=0);for(let e=0;e<hn;e++)1==dt?it=ot=bt[e]:(it=ct,ot=bt[e]),Kn(e,it,ot,$M e);un>=Nt&&cn<Ve-1&&(cn++,un=0);for(let e=0;e<cn;e++)Zn(e)}function qn(){et.background(ct),Ue.background(255),Ue.rectMode(CENTER),ne(Ue),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),Ue.stroke(st),Ue.strokeWeight(8*le),Ue.fill(ct),Qe.background(255),Qe.rectMode(CENTER),ne(Qe),Qe.strokeWeight(le),qe.background(255),qe.rectMode(CENTER),ne(qe),qe.textAlign(LEFT),$e.background(255),$e.rectMode(CENTER),ne($e),Xe.background(255),ne(Xe),Xe.strokeWeight(Ne),We.background(255),We.rectMode(CENTER),ne(We),We.fill(st),We.stroM ke(st),We.strokeWeight(.1*le),er(lt),We.noStroke(),xn&&(We.rect(ae/16,height/2,ae/8,height),We.rect(width-ae/16,height/2,ae/8,height),We.rect(width/2,ae/16,width,ae/8),We.rect(width/2,height-ae/16,width,ae/8)),Ze.background(255),Ze.rectMode(CENTER),ne(Ze),Ze.textAlign(CENTER,CENTER),Ze.textStyle(BOLD),Ze.stroke(st),Ze.strokeWeight(8*le),Ze.fill(ct),je.background(255),je.rectMode(CENTER),ne(je),je.textAlign(CENTER,CENTER),je.textStyle(BOLD),Ke.background(255),Ke.rectMode(CENTER),ne(Ke),Ke.textAlign(CENTER,CENTER),KeM .textStyle(BOLD),Ke.stroke(st),Ke.strokeWeight(8*le),Ke.fill(ct),Je.background(255),Je.rectMode(CENTER),ne(Je),Je.textAlign(CENTER,CENTER),Je.textStyle(BOLD),Je.stroke(st),Je.strokeWeight(8*le),Je.fill(ct),Un(),et.image(We,0,0),Pt&&An(),et.image(Xe,0,0),et.image($e,0,0),At&&(tr(),et.image(Ue,0,0)),fn&&(lr(),et.image(Ze,0,0)),Lt&&(or(),et.image(Ke,0,0)),Dt&&(ir(),et.image(qe,0,0)),yn&&(Bn(),et.image(Je,0,0))}function draw(){const e=Date.now();bn&&(Ut.updateAge(new Date(e)),Xn()),qn(),image(et,0,0),zn||un++}function M Zn(e){let t,n=Ce[e].length,r=Ce[e+1].length;for(let i=0;i<n;i++){const[n,o]=Hn(e,i);for(let a=0;a<r;a++){const[r,l]=Hn(e+1,a);t=map(min(Ce[e][i],Ce[e+1][a]),0,1,0,.5),ur(n,o,r,l,bt[e],bt[e+1],Xe,t)}}}function Kn(e,t,n,r){let i,o,a,l=Ce[e].length;for(let s=0;s<l;s++){const[l,h]=Hn(e,s);i=Ce[e][s],a=map(Be,1/30,1,3,10),o=map(Ce[e][s],0,1,2*a,0)*le,o<1.5*le&&(o=0),Qn(l,h,ze,Oe,t,n,o,i,r)}}function Jn(e,t,n,r,i){for(let o=0;o<Le[e].length;o++)Qn(Le[e][o][0],Le[e][o][1],t,Oe,n,r,0,1,i)}function Qn(e,t,n,r,i,o,a,l,s){s.sM troke(dr(o,map(l,0,1,.25,1))),s.fill(dr(i,map(l,0,1,.15,1))),s.strokeWeight(Fe),fr([a],s),3==dt&&s.fill(dr(i,0)),1==r?s.ellipse(e,t,n):2==r?s.rect(e,t,7*n/8,7*n/8):3==r&&(s.beginShape(),s.vertex(e-4*n/7,t),s.vertex(e,t-4*n/7),s.vertex(e+4*n/7,t),s.vertex(e,t+4*n/7),s.endShape(CLOSE))}function er(e){if(1==e);else if(2==e){We.strokeWeight(1*le);for(let e=ht/4;e<width+ht/4;e+=ht)for(let t=ht/4;t<height+ht/4;t+=ht)We.point(e,t)}else if(3==e){ht=25*le;for(let e=ht/2;e<height+ht/2;e+=ht)We.line(0,e,width,e);for(let e=ht/M 2;e<width+ht/2;e+=ht)We.line(e,0,e,height)}}function tr(){Ue.textFont("Trebuchet MS"),Ue.textAlign(LEFT,CENTER),Ue.noStroke(),pr(Ue,800*le,500*le),Ue.noStroke(),Ue.fill(dr(st,.75)),Ue.rect(width/2,height/2-100*le,800*le,300*le,25*le,25*le,0,0),Ue.fill(st),Ue.rect(width/2-250*le,height/2-100*le,225*le,225*le),Ue.image(se.elt,width/2-357.5*le,height/2-207.5*le,215*le,215*le);let e=100*Zt[0][0];Ue.fill(ct),Ue.textSize(25*le),Ue.textStyle(NORMAL),1==me&&(e>=0&&e<20?Ue.text("I have a feeling this image belongs to",widthM /2-100*le,height/2-170*le):e>=20&&e<40?Ue.text("I have a hunch this image belongs to",width/2-100*le,height/2-170*le):e>=40&&e<60?Ue.text("I think this image belongs to",width/2-100*le,height/2-170*le):e>=60&&e<80?Ue.text("I'm almost certain this image belongs to",width/2-100*le,height/2-170*le):Ue.text("I'm positive this image belongs to",width/2-100*le,height/2-170*le));let t=e.toFixed(2);"100.00"==t&&(t="100"),1==me&&Ue.text("I'm "+t+"% confident that I'm right!",width/2-100*le,height/2-25*le),example=Zt.map((e=M >e[1])),be=Ue.textWidth('"FIDENZAAAA"'),defaultPhrase=Ue.textWidth('"PERPENDICULAR INHABITATION"'),Ue.textStyle(BOLD);const n=me?example[0]:random(example);if(1===n.split(" ").length){let e=75*be/Ue.textWidth('"'+n+'"');e>75&&(e=75),Ue.textSize(e*le),Ue.text('"'+n+'"',width/2-100*le,height/2-90*le)}else nr(width/2-100*le,height/2-90*le,460*le,110*le,n,Ue);if(millis()-ye>1500&&(me=!0),C(tt,nt,st,ct,Pe,Mt),Ue.image(nt,width/2-370*le,height/2+70*le,80*le,80*le),3==Pe){let e;e=map(Mt,50,60,.25,1.3),I(rt,e),Ue.image(rt,M width/2-370*le,height/2+70*le,80*le,80*le)}let r,i;Ue.image(tt,width/2-370*le,height/2+70*le,80*le,80*le),Ue.fill(xt),Ue.textSize(40*le),Ue.text("INTELLIGENCE INFO",width/2-275*le,height/2+115*le),Ue.textSize(18*le),Ue.textStyle(NORMAL),Ue.circle(width/2-360*le,height/2+180*le,7.5*le),1==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s growing and getting smarter by the day.`:2==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s stable and it has reached peak performance.`:3==Pe&&(r=`Your PercepM tron is ${Math.ceil(Mt)} years old. It s decaying and losing its luster.`),i=2==Pe?"The Perceptron remains stable for some time before entering the decay phase.":`Wait until ${new Date(an).toLocaleString("en-US")} for your Perceptron to reach its peak performance.`,Ue.text(r,width/2-350*le,height/2+180*le),Ue.circle(width/2-360*le,height/2+210*le,7.5*le),Ue.text(i,width/2-350*le,height/2+210*le),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),gr(Ue,width/2-225*le,width/2+65*le,height/2+265*le,height/2+305*le,"SELEM CT ANOTHER IMAGE"),gr(Ue,width/2+75*le,width/2+225*le,height/2+265*le,height/2+305*le,"CLOSE")}function nr(e,t,n,r,i,o){let a=i.split(" "),l=75*be/o.textWidth('"'+i+'"'),s=0,h=[],c=[],u=[],f="",d="";if(l>=50)l>75&&(l=75),o.textSize(l*le),o.text('"'+i+'"',e,t);else if(l<50){if(l=50*defaultPhrase/o.textWidth('"'+i+'"'),l>30){if(l>50&&(l=50),[f,d]=rr(l,n,s,h,c,a,f,d,Ue),0==c.length)return o.textSize(l*le),void o.text('"'+i+'"',e,t);for(s=0,h=[],c=[];o.textWidth(d)>n/le;)l=l*n/le/o.textWidth(d),f="",d="",[f,d]=rr(l,n,sM ,h,c,a,f,d,Ue)}else{l=30,o.textSize(l);for(let e=0;e<a.length;e++)s+=o.textWidth(" "+a[e]),s<=n/le?h.push(a[e]):s>n/le&&s<=n/le*2?c.push(a[e]):u.push(a[e]);for(let e=1;e<h.length;e++)f=f+" "+h[e];if(f='"'+h[0]+f,0==u.length){for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+c[c.length-1]+'"'}else if(1==c.length)d="... "+u[u.length-1]+'"';else{for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+"... "+u[u.length-1]+'"'}}o.textSize(l*le);let r=1.25*(o.textDescent()+o.textAscent());o.text(f,e,t-r/2),o.text(d,e,t+r/2)}}function M rr(e,t,n,r,i,o,a,l,s){s.textSize(e);for(let e=0;e<o.length;e++)(n+=s.textWidth(" "+o[e]))<=t/le?r.push(o[e]):i.push(o[e]);for(let e=1;e<r.length;e++)a=a+" "+r[e];if(a='"'+r[0]+a,0==i.length&&(a+='"',l=""),1==i.length)l=i[i.length-1]+'"';else{for(let e=0;e<i.length-1;e++)l=l+i[e]+" ";l=l+i[i.length-1]+'"'}return[a,l]}function ir(){const e=45*le;qe.textFont("Tahoma"),qe.stroke(st),qe.strokeWeight(2*le),qe.fill(ct),qe.rect(width/2,e/2+height-87.5*le,600*le,90*le),qe.fill(st),qe.rect(width/2-150*le,e+height-170*le,300*M le,30*le),qe.fill(ct),qe.rect(width/2+150*le,e+height-170*le,300*le,30*le),qe.noStroke(),qe.fill(ct),qe.textSize(15*le),qe.textStyle(BOLD),qe.text("PERCEPTRON INFORMATION",width/2-285*le,e+height-165*le),qe.fill(xt),qe.text("ARTWORK NAME:",width/2+10*le,e+height-165*le),qe.textAlign(RIGHT),qe.textStyle(ITALIC),qe.text("Perceptron #"+Et,width/2+285*le,e+height-165*le);const[t,n]=It.split(" ");let r;"60 Years"===It?r="1 Year":"60 Months"===It?r="1 Month":"60 Weeks"===It?r="1 Week":"60 Days"===It?r="1 Day":"12 Hours"=M ==It&&(r="12 Minutes"),data=[["AI MODEL NAME:",B(12*le,Ht,140*le)],["SCALE:","1:"+Te],["NUMBER OF CLASSES:",$t.length],["BIRTH YEAR:",Rt],["NUMBER OF REBIRTHS:",sn.toString()],["AGE:",`${Math.ceil(Mt)} Perceptron Years`],["ONE PERCEPTRON YEAR:",`${r}`],["STATE:",Ot[Pe]],["ACTIVE NEURONS:",`${round(ln*rn)} / ${ln}`],["NEXT STATE TIME:",vr(new Date(on))]],qe.fill(xt);const i=data.length/2;for(let t=0;t<data.length;++t){const n=t<i,r=n?width/2-285*le:width/2+10*le,o=n?width/2-10*le:width/2+285*le,a=e+height-(135-t%i*1M 5)*le;qe.textStyle(BOLD),qe.textAlign(LEFT),qe.textSize(12*le),qe.text(data[t][0],r,a),qe.textStyle(ITALIC),qe.textAlign(RIGHT),qe.textSize(12*le),qe.text(data[t][1],o,a)}}function or(){Ke.textFont("Trebuchet MS"),Ke.noStroke(),pr(Ke,600*le,200*le),gr(Ke,width/2-155*le,width/2-5*le,height/2+115*le,height/2+155*le,"UPDATE"),gr(Ke,width/2+5*le,width/2+155*le,height/2+115*le,height/2+155*le,"CLOSE"),Ke.textAlign(LEFT),Ke.fill(xt),Ke.text("UPDATE BITCOIN FULL NODE ADDRESS",width/2-252.5*le,height/2-55*le),Ke.text("UPDAM TE MODEL ADDRESS",width/2-252.5*le,height/2+20*le),Ke.textAlign(RIGHT),Ke.textStyle(ITALIC),Ke.textSize(15*le),0==wn&&Ke.text("(*) Invalid Address",width/2+252.5*le,height/2-53*le),0==vn&&Ke.text("(*) Invalid Model",width/2+252.5*le,height/2+23*le)}function ar(){je.textFont("Trebuchet MS"),je.fill(st),je.textSize(50*le),je.stroke(st),je.strokeWeight(1*le),je.text("main()",width/2,height/2)}function lr(){un>=20&&1==dn&&(dn=!1,un=0),dn&&(Ze.textFont("Trebuchet MS"),Ze.stroke(st),Ze.fill(ct),Ze.rect(width/2,height/2,6M 00*le,150*le,25*le),Ze.fill(xt),Ze.textSize(75*le),Ze.noStroke(),1==Pe?Ze.text("GROWING",width/2,height/2+5*le):3==Pe?Ze.text("AGING",width/2,height/2+5*le):4==Pe?Ze.text("DEAD",width/2,height/2+5*le):5==Pe&&Ze.text("BIRTH",width/2,height/2+5*le)),un>=20&&0==dn&&(dn=!0,un=0,Bt++,3==Bt&&(fn=!1))}function sr(e,t,n,r){let i=[],o=r/(n.length+1),a=color(e),l=color(t);i.push(a);for(let e=0;e<n.length;e++){let t=color(n[e]);for(let e=1;e<=o;e++){let n=lerpColor(a,t,e/o);i.push(n)}a=t}for(let e=1;e<o;e++){let t=lerpColor(aM ,l,e/o);i.push(t)}if(i.push(l),i.length>r)i.splice(r);else if(i.length<r){let e=i[i.length-1];for(;i.length<r;)i.push(e)}return i}function hr(e,t){let n=e.length,r=Math.floor(t*n);return r>=n&&(r=n-1),e[r]}function cr(e){e=e.replace("#","");var t=parseInt(e,16);return color(t>>16&255,t>>8&255,255&t)}function ur(e,t,n,r,i,o,a,l){var s=a.drawingContext.createLinearGradient(e,t,n,r);s.addColorStop(0,i),s.addColorStop(1,o),a.drawingContext.strokeStyle=s,a.drawingContext.globalAlpha=l,a.line(e,t,n,r),a.drawingContext.glM obalAlpha=1}function fr(e,t){t.drawingContext.setLineDash(e)}function dr(e,t){let n=color(e),r=red(n),i=green(n),o=blue(n);return color(r,i,o,255*t)}function xr(e,t,n,r){return mouseX>e&&mouseX<t&&mouseY>n&&mouseY<r}function gr(e,t,n,r,i,o){e.strokeWeight(1*le),e.stroke(st);const[a,l]=xr(t,n,r,i)?[xt,ct]:[ct,xt];e.fill(a),e.push(),e.rectMode(CORNERS),e.rect(t,r,n,i,5*le),e.pop(),e.noStroke(),e.textSize(20*le),e.fill(l),e.text(o,(t+n)/2,(46*r+54*i)/100)}function pr(e,t,n){e.fill(0,0,0,75),e.rect(width/2,height/2,widM th,height),e.stroke(st),e.fill(ct),e.rect(width/2,height/2,t,n,25*le)}function mr(e,t){resizeCanvas(e,t,!0),Xe.resizeCanvas(e,t,!0),$e.resizeCanvas(e,t,!0),We.resizeCanvas(e,t,!0),Ue.resizeCanvas(e,t,!0),qe.resizeCanvas(e,t,!0),Qe.resizeCanvas(e,t,!0),je.resizeCanvas(e,t,!0),Ze.resizeCanvas(e,t,!0),Ke.resizeCanvas(e,t,!0),Je.resizeCanvas(e,t,!0),et.resizeCanvas(e,t,!0)}function br(e,t,n,r,i,o){const a=J(e);return a.position(t,n),a.size(r,i),a.style("opacity","0"),a.mouseClicked(o),a}function yr(){return null!=vt&&vM t?.isFocused()||null!=zt&&zt?.isFocused()}function wr(e,t,n,r){let i;if(e<=3){i=`Hey ${String.fromCodePoint(128075)}, I'm ${n}, ${t} years old. I can detect ${r.length} NFT collections: `;let e=0;for(let t=0;t<r.length;++t){const n=r[t];if(e+n.length>500){i+=", etc";break}t==r.length-1?i+=", and ":t>0&&(i+=", "),i+=n,e+=n.length}i+=". ",t<=5?i+="However, I am only a baby, so my recognition ability is not accurate. I'm in the state of Growing both looks and intelligence.":t<=13?i+="I am now a child. My recognition aM bility is becoming better, but still not very accurate. I'm in the state of Growing both looks and intelligence.":t<=25?i+="I have grown up to be a teen. My recognition ability almost reaches the peak, but I will still mess up sometimes. I'm in the state of Growing both looks and intelligence.":t<=50?i+="I finally reach adulthood. My recognition is fully functional now. I'm in the Stable state, where I am the most intelligent with all neurons activated.":t<=60&&(i+="I am now an old Perceptron, so my recognition abiM lity is no longer the best. I'm in the Decaying state, meaning that my neurons are dying, and my intelligence is decreasing over time.")}else 4==e?i=`${n} is Dead. However, this is not the end to its story...`:5==e&&(i=`${n} is now in the Rebirth state, and is preparing to start a new life.`);return i}function vr(e){const t=e.getDate(),n=e.toLocaleString("en-US",{month:"long"}),r=e.getFullYear();let i=e.getHours().toString();1==i.length&&(i="0"+i);let o=e.getMinutes().toString();return 1==o.length&&(o="0"+o),`${Y(tM )} ${n} ${r} | ${i}:${o}`}saveCanvasAtCurrentTime=()=>{save(N())},save4KCanvasAtCurrentTime=()=>{const e=width,t=height,n=min(4096/min(e,t),1e4/max(e,t)),r=e*n,i=t*n;mr(r,i),zn=!0,$n(r,i),qn();let o="4K_"+N()+".png";saveCanvas(et,o),mr(e,t),$n(e,t),zn=!1};const zr=[["60 Years",3,365],["60 Months",40,30],["60 Weeks",37,7],["60 Days",20,1]],Vr=[["1943",1],["1951",1.5],["1957",2],["1969",2.5],["1970",3],["1980",3.5],["1982",4],["1986",4.5],["1988",5],["1997",5.5],["1998",6],["2002",6.5],["2009",7],["2012",7.5],["2014"M ,8],["2015",8.5],["2016",9],["2023",15]],_r=[["Plain",20],["Dotted",40],["Squared",40]],Mr=[["Basic",30],["Standard",60],["Advanced",10]],Er=[["MNIST",70],["CIFAR",25],["IMAGENET",5]],Sr=[["Theano",60],["Torch",30],["TensorFlow",10]],Rr=[["Whitepaper",2],["Blackboard",2],["Blueprint",2],["Nak",74/14],["Jims",74/14],["Level 10",74/14],["Flips",74/14],["Level 14",74/14],["III",74/14],["XMB",74/14],["Info",74/14],["Adventure",74/14],["Marigold",74/14],["Phoenix",74/14],["Love",74/14],["Cachet",74/14],["Human",74/14],[M "Twilight",3],["Sunset",3],["Aurora",3],["Liminal Space",3],["D Vu",3],["Lucid Dream",3],["Parallel",1],["Multiverse",1]];function Ir(e){for(let e=0;e<100;++e)random(1);return{visual:{pattern:k(_r),hardwareAcceleration:k(Mr),nodeFill:k(Er),nodeShape:k(Sr),colorPalette:k(Rr),lifeCycle:k(zr),birthYear:k(Vr)},training:e}}function Cr(e){window.$generativeTraits={"Network Architecture":e.training.structure_gen,"Hidden Layers":e.training.n_layers,"Max Neurons Per Hidden Layer":e.training.max_nodes,"Activation FunctiM on":e.training.activation_func,"Training Epochs":e.training.epoch_num,Dataset:e.visual.nodeFill,"Deep Learning Framework":e.visual.nodeShape,"Hardware Acceleration":e.visual.hardwareAcceleration,"Paper Pattern":e.visual.pattern,"Life Cycle":e.visual.lifeCycle,"Birth Year":e.visual.birthYear,"Color Palette":e.visual.colorPalette}} <script defer src="https://static.cloudflareinsights.com/beacon.min.js/v2b4487d741ca48dcbadcaf954e159fc61680799950996" integrity="sha512-D/jdE0CypeVxFadTejKGTzmwyV10c1pxZk/L AqjJuZbaJwGMyNHY3q/mTPWqMUnFACfCTunhZUVcd4cV78dK1pQ==" data-cf-beacon='{"rayId":"7b481bb47cc1a1e4","version":"2023.3.0","b":1,"token":"6c07c178c94442f695e7a0a2aaee641a","si":100}' crossorigin="anonymous"></script> {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "tiger"}, {"trait_type": "Mane", "value": "blue fire"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "frozen staff"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "honey pot"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "wizard staff"}]} text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "undead"}, {"trait_type": "Artifacts", "value": "parrot"}]} text/plain;charset=utf-8 ({"p":"sns","op":"reg","name":" {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "rainbow"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "bag"}]} text/html;charset=utf-8 <meta charset="utf-8" /> position: relative; width: var(--width); height: var(--height); border: 1px solid blue; position: relative; <div id="upload"> <input id="inputUpload" type="file"> function e(e){"use strict";return new function e(t){let n="global"==t?window:this;n.canvas=document.createElement("canvas");let r=n.canvas.getContext("2d");n.width=100,n.height=100,n.canvas.width=n.width,n.canvas.height=n.height,"offscreen"!=t&&(document.body?document.body.appendChild(n.canvas):window.addEventListener("load",(function(){document.body.appendChild(n.canvas)}))),g(),n.MAGIC=161533525,n.RGB=0,n.HSV=1,n.HM SB=1,n.CHORD=0,n.PIE=1,n.OPEN=2,n.RADIUS=1,n.CORNER=2,n.CORNERS=3,n.ROUND="round",n.SQUARE="butt",n.PROJECT="square",n.MITER="miter",n.BEVEL="bevel",n.CLOSE=1,n.BLEND="source-over",n.REMOVE="destination-out",n.ADD="lighter",n.DARKEST="darken",n.LIGHTEST="lighten",n.DIFFERENCE="difference",n.SUBTRACT="subtract",n.EXCLUSION="exclusion",n.MULTIPLY="multiply",n.SCREEN="screen",n.REPLACE="copy",n.OVERLAY="overlay",n.HARD_LIGHT="hard-light",n.SOFT_LIGHT="soft-light",n.DODGE="color-dodge",n.BURN="color-burn",n.NORMAL="norM mal",n.ITALIC="italic",n.BOLD="bold",n.BOLDITALIC="italic bold",n.CENTER="center",n.LEFT="left",n.RIGHT="right",n.TOP="top",n.BOTTOM="bottom",n.BASELINE="alphabetic",n.LANDSCAPE="landscape",n.PORTRAIT="portrait",n.ALT=18,n.BACKSPACE=8,n.CONTROL=17,n.DELETE=46,n.DOWN_ARROW=40,n.ENTER=13,n.ESCAPE=27,n.LEFT_ARROW=37,n.OPTION=18,n.RETURN=13,n.RIGHT_ARROW=39,n.SHIFT=16,n.TAB=9,n.UP_ARROW=38,n.HALF_PI=Math.PI/2,n.PI=Math.PI,n.QUARTER_PI=Math.PI/4,n.TAU=2*Math.PI,n.TWO_PI=2*Math.PI,n.THRESHOLD=1,n.GRAY=2,n.OPAQUE=3,n.INVEM RT=4,n.POSTERIZE=5,n.DILATE=6,n.ERODE=7,n.BLUR=8,n.ARROW="default",n.CROSS="crosshair",n.HAND="pointer",n.MOVE="move",n.TEXT="text",n.VIDEO={video:!0,audio:!1},n.AUDIO={video:!1,audio:!0},n.SHR3=1,n.LCG=2,n.HARDWARE_FILTERS=!0,n.hint=function(e,t){n[e]=t},n.frameCount=0,n.mouseX=0,n.mouseY=0,n.pmouseX=0,n.pmouseY=0,n.mouseButton=null,n.keyIsPressed=!1,n.mouseIsPressed=!1,n.key=null,n.keyCode=null,n.pixels=null,n.accelerationX=0,n.accelerationY=0,n.accelerationZ=0,n.rotationX=0,n.rotationY=0,n.rotationZ=0,n.relRotatM ionX=0,n.relRotationY=0,n.relRotationZ=0,n.pAccelerationX=0,n.pAccelerationY=0,n.pAccelerationZ=0,n.pRotationX=0,n.pRotationY=0,n.pRotationZ=0,n.pRelRotationX=0,n.pRelRotationY=0,n.pRelRotationZ=0,n.touches=[],n._styleCache=[{colorMode:n.RGB,noStroke:!1,noFill:!1,ellipseMode:n.CENTER,rectMode:n.CORNER,curveDetail:20,curveAlpha:0,textFont:"sans-serif",textSize:12,textLeading:12,textStyle:"normal"}],n._style=n._styleCache[n._styleCache.length-1],n._noLoop=!1,n._pixelDensity=1,n._frameRate=null,n._tint=null;let i=nullM ,o=!0,a=[],l=null,s=0,h={},c=0,u=null,f=null,d=null;Object.defineProperty(n,"deviceOrientation",{get:function(){return 90==Math.abs(window.orientation)?n.LANDSCAPE:n.PORTRAIT}}),Object.defineProperty(n,"windowWidth",{get:function(){return window.innerWidth}}),Object.defineProperty(n,"windowHeight",{get:function(){return window.innerHeight}}),Object.defineProperty(n,"drawingContext",{get:function(){return r}}),n.createCanvas=function(e,t){return n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t,g(),n.canvas},nM .resizeCanvas=function(e,t){n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t},n.createGraphics=n.createImage=function(t,n){let r=new e("offscreen");return r.createCanvas(t,n),r.noLoop(),r},n.pixelDensity=function(e){return null==e||(n._pixelDensity=e,n.canvas.width=Math.ceil(n.width*e),n.canvas.height=Math.ceil(n.height*e),n.canvas.style.width=n.width+"px",n.canvas.style.height=n.height+"px",r.scale(n._pixelDensity,n._pixelDensity),g()),n._pixelDensity},n.map=function(e,t,n,r,i,o){let a=r+1*(e-t)/(n-t)*(i-r)M ;return o?r<i?Math.min(Math.max(a,r),i):Math.min(Math.max(a,i),r):a},n.lerp=function(e,t,n){return e*(1-n)+t*n},n.constrain=function(e,t,n){return Math.min(Math.max(e,t),n)},n.dist=function(){return 4==arguments.length?Math.hypot(arguments[0]-arguments[2],arguments[1]-arguments[3]):Math.hypot(arguments[0]-arguments[3],arguments[1]-arguments[4],arguments[2]-arguments[5])},n.norm=function(e,t,r){return n.map(e,t,r,0,1)},n.sq=function(e){return e*e},n.fract=function(e){return e-Math.floor(e)},n.degrees=function(e){retM urn 180*e/Math.PI},n.radians=function(e){return e*Math.PI/180},n.abs=Math.abs,n.ceil=Math.ceil,n.exp=Math.exp,n.floor=Math.floor,n.log=Math.log,n.mag=Math.hypot,n.max=Math.max,n.min=Math.min,n.round=Math.round,n.sqrt=Math.sqrt,n.sin=Math.sin,n.cos=Math.cos,n.tan=Math.tan,n.asin=Math.asin,n.acos=Math.acos,n.atan=Math.atan,n.atan2=Math.atan2,n.Vector=function(e,t,r){let i=this;i.x=e||0,i.y=t||0,i.z=r||0;let o=null,a=null;function l(e,t,n){return null!=e.x?e:null!=t?{x:e,y:t,z:n||0}:{x:e,y:e,z:e}}function s(){null==a&M &(a=i.x*i.x+i.y*i.y+i.z*i.z,o=Math.sqrt(a))}function h(){a=null,o=null}i.set=function(e,t,n){i.x=e||0,i.y=t||0,i.z=n||0},i.copy=function(){return new n.Vector(i.x,i.y,i.z)},i.add=function(){let e=l.apply(null,arguments);return i.x+=e.x,i.y+=e.y,i.z+=e.z,h(),i},i.rem=function(){let e=l.apply(null,arguments);return i.x%=e.x,i.y%=e.y,i.z%=e.z,h(),i},i.sub=function(){let e=l.apply(null,arguments);return i.x-=e.x,i.y-=e.y,i.z-=e.z,h(),i},i.mult=function(){let e=l.apply(null,arguments);return i.x*=e.x,i.y*=e.y,i.z*=e.z,hM (),i},i.div=function(){let e=l.apply(null,arguments);return i.x/=e.x,i.y/=e.y,i.z/=e.z,h(),i},i.mag=function(){return s(),o},i.magSq=function(){return s(),a},i.dot=function(){let e=l.apply(null,arguments);return i.x*e.x+i.y*e.y+i.z*e.z},i.dist=function(){let e=l.apply(null,arguments),t=i.x-e.x,n=i.y-e.y,r=i.z-e.z;return Math.sqrt(t*t+n*n+r*r)},i.cross=function(){let e=l.apply(null,arguments),t=i.y*e.z-i.z*e.y,n=i.z*e.x-i.x*e.z,r=i.x*e.y-i.y*e.x;return i.x=t,i.y=n,i.z=r,h(),i},i.normalize=function(){s();let e=o;retuM rn i.x/=e,i.y/=e,i.z/=e,o=1,a=1,i},i.limit=function(e){s();if(o>e){let t=e/o;i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e}return i},i.setMag=function(e){s();let t=e/o;return i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e,i},i.heading=function(){return Math.atan2(i.y,i.x)},i.rotate=function(e){let t=Math.cos(e),n=Math.sin(e),r=i.x*t-i.y*n,o=i.x*n+i.y*t;return i.x=r,i.y=o,i},i.angleBetween=function(){let e=l.apply(null,arguments);const t=i.dot(e)/(i.mag()*e.mag());let n;return n=Math.acos(Math.min(1,Math.max(-1,t))),n*Math.sign(i.cross(e).z||1)},M i.lerp=function(e,t){return i.x=i.x*(1-t)+e.x*t,i.y=i.y*(1-t)+e.y*t,i.z=i.z*(1-t)+e.z*t,h(),i},i.reflect=function(e){return e.normalize(),i.sub(e.mult(2*i.dot(e)))},i.array=function(){return[i.x,i.y,i.z]},i.equals=function(e,t){return null==t&&null==(t=Number.EPSILON)&&(t=0),Math.abs(e.x-i.x)<t&&Math.abs(e.y-i.y)<t&&Math.abs(e.z-i.z)<t},i.fromAngle=function(e,t){return null==t&&(t=1),o=t,a=t*t,i.x=t*Math.cos(e),i.y=t*Math.sin(e),i.z=0,i},i.fromAngles=function(e,t,n){null==n&&(n=1),o=n,a=n*n;const r=Math.cos(t),l=MaM th.sin(t),s=Math.cos(e),h=Math.sin(e);return i.x=n*h*l,i.y=-n*s,i.z=n*h*r,i},i.random2D=function(){return o=1,a=1,i.fromAngle(Math.random()*Math.PI*2)},i.random3D=function(){return o=1,a=1,i.fromAngles(Math.random()*Math.PI*2,Math.random()*Math.PI*2)},i.toString=function(){return`[${i.x}, ${i.y}, ${i.z}]`}},n.Vector.add=function(e,t){return new n.Vector(e.x+t.x,e.y+t.y,e.z+t.z)},n.Vector.rem=function(e,t){return new n.Vector(e.x%t.x,e.y%t.y,e.z%t.z)},n.Vector.sub=function(e,t){return new n.Vector(e.x-t.x,e.y-t.y,e.M z-t.z)},n.Vector.mult=function(e,t){return null==t.x?new n.Vector(e.x*t,e.y*t,e.z*t):new n.Vector(e.x*t.x,e.y*t.y,e.z*t.z)},n.Vector.div=function(e,t){return null==t.x?new n.Vector(e.x/t,e.y/t,e.z/t):new n.Vector(e.x/t.x,e.y/t.y,e.z/t.z)},n.Vector.dist=function(e,t){return Math.hypot(e.x-t.x,e.y-t.y,e.z-t.z)},n.Vector.cross=function(e,t){return new n.Vector(e.y*t.z-e.z*t.y,e.z*t.x-e.x*t.z,e.x*t.y-e.y*t.x)},n.Vector.lerp=function(e,t,r){return new n.Vector(e.x*(1-r)+t.x*r,e.y=e.y*(1-r)+t.y*r,e.z=e.z*(1-r)+t.z*r)},n.M Vector.equals=function(e,t,n){return e.equals(t,n)};for(let e of["fromAngle","fromAngles","random2D","random3D"])n.Vector[e]=function(t,r,i){return(new n.Vector)[e](t,r,i)};function x(e,t,n){let r,i,o,a,l,s,h,c,u;if(0==t)return[255*(r=n),255*(i=n),255*(o=n)];switch((a=e)>360&&(a=0),h=n*(1-t),c=n*(1-t*(s=(a/=60)-(l=~~a))),u=n*(1-t*(1-s)),l){case 0:r=n,i=u,o=h;break;case 1:r=c,i=n,o=h;break;case 2:r=h,i=n,o=u;break;case 3:r=h,i=c,o=n;break;case 4:r=u,i=h,o=n;break;default:r=n,i=h,o=c}return[255*r,255*i,255*o]}functioM n g(){r.fillStyle="white",r.strokeStyle="black",r.lineCap="round",r.lineJoin="miter"}function p(e){if(0<=e&&e<2*Math.PI)return e;for(;e<0;)e+=2*Math.PI;for(;e>=Math.PI;)e-=2*Math.PI;return e}function m(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;let c=p(a),u=p(l);r.beginPath();for(let a=0;a<h+1;a++){let l=a/h,s=n.lerp(c,u,l),f=Math.cos(s)*i/2,d=Math.sin(s)*o/2;r[a?"lineTo":"moveTo"](e+f,t+d)}s==n.CHORD?r.closePath():s==n.PIE&&(r.lineTo(e,t),r.closePath()),n._style.noFill||r.fill(),n._style.noStrokM e||r.stroke()}function b(e,t,i,o){n._style.noFill&&n._style.noStroke||(r.beginPath(),r.ellipse(e,t,i/2,o/2,0,0,2*Math.PI),n._style.noFill||r.fill(),n._style.noStroke||r.stroke())}function y(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;if(null==a)return function(e,t,i,o){n._style.noFill||r.fillRect(e,t,i,o),n._style.noStroke||r.strokeRect(e,t,i,o)}(e,t,i,o);if(null==l)return y(e,t,i,o,a,a,a,a);const c=Math.min(Math.abs(o),Math.abs(i))/2;a=Math.min(c,a),l=Math.min(c,l),h=Math.min(c,h),s=Math.min(c,s)M ,r.beginPath(),r.moveTo(e+a,t),r.arcTo(e+i,t,e+i,t+o,l),r.arcTo(e+i,t+o,e,t+o,s),r.arcTo(e,t+o,e,t,h),r.arcTo(e,t,e+i,t,a),r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke()}function w(){a=[]}n.createVector=function(e,t,r){return new n.Vector(e,t,r)},n.curvePoint=function(e,t,n,r,i){const o=i*i*i,a=i*i;return e*(-.5*o+a-.5*i)+t*(1.5*o-2.5*a+1)+n*(-1.5*o+2*a+.5*i)+r*(.5*o-.5*a)},n.bezierPoint=function(e,t,n,r,i){const o=1-i;return Math.pow(o,3)*e+3*Math.pow(o,2)*i*t+3*o*Math.pow(i,2)*n+Math.pow(i,M 3)*r},n.curveTangent=function(e,t,n,r,i){const o=i*i;return e*(-3*o/2+2*i-.5)+t*(9*o/2-5*i)+n*(-9*o/2+4*i+.5)+r*(3*o/2-i)},n.bezierTangent=function(e,t,n,r,i){const o=1-i;return 3*r*Math.pow(i,2)-3*n*Math.pow(i,2)+6*n*o*i-6*t*o*i+3*t*Math.pow(o,2)-3*e*Math.pow(o,2)},n.Color=function(e,t,n,r){let i=this;i.MAGIC=786698,i._r=e,i._g=t,i._b=n,i._a=r,i._h=0,i._s=0,i._v=0,i._hsvInferred=!1,i.setRed=function(e){i._r=e,i._hsvInferred=!1},i.setGreen=function(e){i._g=e,i._hsvInferred=!1},i.setBlue=function(e){i._b=e,i._hsvInfM erred=!1},i.setAlpha=function(e){i._a=e/255,i._hsvInferred=!1},i._inferHSV=function(){i._hsvInferred||([i._h,i._s,i._v]=function(e,t,n){let r,i,o,a,l;return r=e<t?e<n?e:n:t<n?t:n,0==(l=100*(i=e>t?e>n?e:n:t>n?t:n)/255)?[o=0,a=0,l]:0==(a=100*(i-r)/i)?[o=0,a,l]:(o=i==e?0+60*(t-n)/(i-r):i==t?120+60*(n-e)/(i-r):240+60*(e-t)/(i-r),[o,a,l])}(i._r,i._g,i._b),i._hsvInferred=!0)},i.toString=function(){return`rgba(${Math.round(i._r)},${Math.round(i._g)},${Math.round(i._b)},${~~(1e3*i._a)/1e3})`}},n.colorMode=function(e){n._stM yle.colorMode=e},n.color=function(){if(1==arguments.length&&786698==arguments[0].MAGIC)return arguments[0];if(n._style.colorMode==n.RGB){if(1==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],1);if(2==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],arguments[1]/255);if(3==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],1);if(4==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],arguments[3]/255)}else{if(1==argumeM nts.length)return new n.Color(...x(0,0,arguments[0]/100),1);if(2==arguments.length)return new n.Color(...x(0,0,arguments[0]/100),arguments[1]/255);if(3==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),1);if(4==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),arguments[3])}return null},n.red=function(e){return e._r},n.green=function(e){return e._g},n.blue=function(e){return e._b},n.alpha=function(e){return 255*e._a},n.hue=function(e){reM turn e._inferHSV(),e._h},n.saturation=function(e){return e._inferHSV(),e._s},n.brightness=function(e){return e._inferHSV(),e._v},n.lightness=function(e){return 100*(.2126*e._r+.7152*e._g+.0722*e._b)/255},n.lerpColor=function(e,t,r){return n._style.colorMode==n.RGB?new n.Color(n.constrain(n.lerp(e._r,t._r,r),0,255),n.constrain(n.lerp(e._g,t._g,r),0,255),n.constrain(n.lerp(e._b,t._b,r),0,255),n.constrain(n.lerp(e._a,t._a,r),0,1)):(e._inferHSV(),t._inferHSV(),new n.Color(n.constrain(function(e,t,r){var i=[[Math.abs(t-M e),n.map(r,0,1,e,t)],[Math.abs(t+360-e),n.map(r,0,1,e,t+360)],[Math.abs(t-360-e),n.map(r,0,1,e,t-360)]];return i.sort(((e,t)=>e[0]-t[0])),(i[0][1]+720)%360}(e._h,t._h,r),0,360),n.constrain(n.lerp(e._s,t._s,r),0,100),n.constrain(n.lerp(e._v,t._v,r),0,100),n.constrain(n.lerp(e._a,t._a,r),0,1)))},n.strokeWeight=function(e){n._style_noStroke=!1,r.lineWidth=e},n.stroke=function(){if(n._style.noStroke=!1,"string"==typeof arguments[0])return void(r.strokeStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._sM tyle.noStroke=!0:r.strokeStyle=e},n.noStroke=function(){n._style.noStroke=!0},n.fill=function(){if(n._style.noFill=!1,"string"==typeof arguments[0])return void(r.fillStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._style.noFill=!0:r.fillStyle=e},n.noFill=function(){n._style.noFill=!0},n.blendMode=function(e){r.globalCompositeOperation=e},n.strokeCap=function(e){r.lineCap=e},n.strokeJoin=function(e){r.lineJoin=e},n.ellipseMode=function(e){n._style.ellipseMode=e},n.rectMode=function(e){n._style.rectM Mode=e},n.curveDetail=function(e){n._style.curveDetail=e},n.curveAlpha=function(e){n._style.curveAlpha=e},n.curveTightness=function(e){n._style.curveAlpha=e},n.clear=function(){r.clearRect(0,0,n.width,n.height)},n.background=function(){if(arguments[0]&&arguments[0].MAGIC==n.MAGIC)return n.image(arguments[0],0,0,n.width,n.height);r.save(),r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity),r.fillStyle="string"==typeof arguments[0]?arguments[0]:n.color(...Array.from(arguments)),r.fillRect(0,0,n.width,n.heightM ),r.restore()},n.line=function(e,t,i,o){n._style.noStroke||(r.beginPath(),r.moveTo(e,t),r.lineTo(i,o),r.stroke())},n.arc=function(e,t,r,i,o,a,l,s){if(o==a)return n.ellipse(e,t,r,i);null==s&&(s=25),null==l&&(l=n.PIE),n._style.ellipseMode==n.CENTER?m(e,t,r,i,o,a,l,s):n._style.ellipseMode==n.RADIUS?m(e,t,2*r,2*i,o,a,l,s):n._style.ellipseMode==n.CORNER?m(e+r/2,t+i/2,r,i,o,a,l,s):n._style.ellipseMode==n.CORNERS&&m((e+r)/2,(t+i)/2,r-e,i-t,o,a,l,s)},n.ellipse=function(e,t,r,i){null==i&&(i=r),n._style.ellipseMode==n.CENTERM ?b(e,t,r,i):n._style.ellipseMode==n.RADIUS?b(e,t,2*r,2*i):n._style.ellipseMode==n.CORNER?b(e+r/2,t+i/2,r,i):n._style.ellipseMode==n.CORNERS&&b((e+r)/2,(t+i)/2,r-e,i-t)},n.circle=function(e,t,r){return n.ellipse(e,t,r,r)},n.point=function(e,t){e.x&&(t=e.y,e=e.x),r.beginPath(),r.ellipse(e,t,.4,.4,0,0,2*Math.PI),r.stroke()},n.rect=function(e,t,r,i,o,a,l,s){n._style.rectMode==n.CENTER?y(e-r/2,t-i/2,r,i,o,a,l,s):n._style.rectMode==n.RADIUS?y(e-r,t-i,2*r,2*i,o,a,l,s):n._style.rectMode==n.CORNER?y(e,t,r,i,o,a,l,s):n._stylM e.rectMode==n.CORNERS&&y(e,t,r-e,i-t,o,a,l,s)},n.square=function(e,t,r,i,o,a,l){return n.rect(e,t,r,r,i,o,a,l)},n.beginShape=function(){w(),r.beginPath(),o=!0},n.beginContour=function(){r.closePath(),w(),o=!0},n.endContour=function(){w(),o=!0},n.vertex=function(e,t){w(),o?r.moveTo(e,t):r.lineTo(e,t),o=!1},n.bezierVertex=function(e,t,n,i,o,a){w(),r.bezierCurveTo(e,t,n,i,o,a)},n.quadraticVertex=function(e,t,n,i){w(),r.quadraticCurveTo(e,t,n,i)},n.bezier=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.bezierVM ertex(r,i,o,a,l,s),n.endShape()},n.triangle=function(e,t,r,i,o,a){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.endShape(n.CLOSE)},n.quad=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.vertex(l,s),n.endShape(n.CLOSE)},n.endShape=function(e){w(),e&&r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke(),n._style.noFill&&n._style.noStroke&&(r.save(),r.fillStyle="none",r.fill(),r.restore())},n.curveVertex=function(e,t){if(a.push([e,t]),a.length<4)return;M let i=function(e,t,n,r,i,o,a,l,s,h){function c(e,t,n,r,i,o){let a=Math.pow(r-t,2)+Math.pow(i-n,2);return Math.pow(a,.5*o)+e}let u=[],f=c(0,e,t,n,r,h),d=c(f,n,r,i,o,h),x=c(d,i,o,a,l,h);for(let h=0;h<s;h++){let c=f+h/(s-1)*(d-f),g=[(f-c)/(f-0),(c-0)/(f-0),(d-c)/(d-f),(c-f)/(d-f),(x-c)/(x-d),(c-d)/(x-d),(d-c)/(d-0),(c-0)/(d-0),(x-c)/(x-f),(c-f)/(x-f)];for(let e=0;e<g.length;e+=2)isNaN(g[e])&&(g[e]=1,g[e+1]=0),isFinite(g[e])||(g[e]>0?(g[e]=1,g[e+1]=0):(g[e]=0,g[e+1]=1));let p=e*g[0]+n*g[1],m=t*g[0]+r*g[1],b=n*g[2]+i*g[M 3],y=r*g[2]+o*g[3],w=i*g[4]+a*g[5],v=o*g[4]+l*g[5],z=p*g[6]+b*g[7],V=m*g[6]+y*g[7],_=b*g[8]+w*g[9],M=y*g[8]+v*g[9],E=z*g[2]+_*g[3],S=V*g[2]+M*g[3];u.push([E,S])}return u}(...a[a.length-4],...a[a.length-3],...a[a.length-2],...a[a.length-1],n._style.curveDetail,n._style.curveAlpha);for(let e=0;e<i.length;e++)o?r.moveTo(...i[e]):r.lineTo(...i[e]),o=!1},n.curve=function(e,t,r,i,o,a,l,s){n.beginShape(),n.curveVertex(e,t),n.curveVertex(r,i),n.curveVertex(o,a),n.curveVertex(l,s),n.endShape()},n.translate=function(e,t){r.tM ranslate(e,t)},n.rotate=function(e){r.rotate(e)},n.scale=function(e,t){null==t&&(t=e),r.scale(e,t)},n.applyMatrix=function(e,t,n,i,o,a){r.transform(e,t,n,i,o,a)},n.shearX=function(e){r.transform(1,0,Math.tan(e),1,0,0)},n.shearY=function(e){r.transform(1,Math.tan(e),0,1,0,0)},n.resetMatrix=function(){r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity)},n.pushMatrix=n.push=function(){n._styleCache.push({...n._style}),n._style=n._styleCache[n._styleCache.length-1],r.save()},n.popMatrix=n.pop=function(){n._stylM eCache.length-1&&(n._styleCache.pop(),n._style=n._styleCache[n._styleCache.length-1],r.restore())},n.image=function(e,t,i,o,a,l,s,h,c){let u=e.MAGIC==n.MAGIC?e.canvas:e;function d(){if(e.MAGIC!=n.MAGIC||!n._tint)return;let t=e.canvas.getContext("2d");t.save(),t.resetTransform(),t.clearRect(0,0,t.canvas.width,t.canvas.height),t.drawImage(f.canvas,0,0),t.restore()}return e.MAGIC==n.MAGIC&&null!=n._tint&&(function(e,t){null==f&&(f=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvasM .height),f.canvas.width==e&&f.canvas.height==t||(f.canvas.width=e,f.canvas.height=t)}(e.canvas.width,e.canvas.height),f.drawImage(e.canvas,0,0),e.tinted(n._tint)),o?l?(h||(h=u.width),c||(c=u.height),r.drawImage(u,l,s,h,c,t,i,o,a),void d()):(r.drawImage(u,t,i,o,a),void d()):(e.MAGIC==n.MAGIC||e.width?r.drawImage(u,t,i,e.width,e.height):r.drawImage(u,t,i,e.videoWidth,e.videoHeight),void d())},n.loadPixels=function(){l=r.getImageData(0,0,n.canvas.width,n.canvas.height),n.pixels=l.data},n.updatePixels=function(){null!=M l&&r.putImageData(l,0,0)},n.loadImage=function(e,t){s++;let r=n.createGraphics(100,100),i=r.canvas.getContext("2d"),o=new Image;return o.src=e,o.crossOrigin="Anonymous",o.onload=function(){i.canvas.width=o.width,i.canvas.height=o.height,r.width=o.width,r.height=o.height,i.drawImage(o,0,0),s--,t&&t(r)},r};let v={};function z(e,t){null==u&&(u=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvas.height),u.canvas.width==e&&u.canvas.height==t||(u.canvas.width=e,u.canvas.height=t)}funcM tion V(){let e=r.canvas.width*r.canvas.height*4;null!=d&&e==d.length||(d=new Uint8ClampedArray(e))}function _(e){u.clearRect(0,0,u.canvas.width,u.canvas.height),u.filter=e,u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()}v[n.THRESHOLD]=function(e,t){null==t?t=127.5:t*=255;for(let n=0;n<e.length;n+=4){const r=.2126*e[n]+.7152*e[n+1]+.0722*e[n+2];e[n]=e[n+1]=e[n+2]=r>=t?255:0}},v[n.GRAY]=function(e){for(let t=0;t<e.length;t+=4)M {const n=.2126*e[t]+.7152*e[t+1]+.0722*e[t+2];e[t]=e[t+1]=e[t+2]=n}},v[n.OPAQUE]=function(e){for(let t=0;t<e.length;t+=4)e[t+3]=255},v[n.INVERT]=function(e){for(let t=0;t<e.length;t+=4)e[t]=255-e[t],e[t+1]=255-e[t+1],e[t+2]=255-e[t+2]},v[n.POSTERIZE]=function(e,t){let n=t-1;for(let r=0;r<e.length;r+=4)e[r]=255*(e[r]*t>>8)/n,e[r+1]=255*(e[r+1]*t>>8)/n,e[r+2]=255*(e[r+2]*t>>8)/n},v[n.DILATE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-M 1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.max(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.ERODE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.min(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.BLURM ]=function(e,t){t=t||1,t=Math.floor(t*n._pixelDensity),V(),d.set(e);let i=2*t+1,o=function(e){let n=new Float32Array(e),r=.3*t+.8,i=r*r*2;for(let t=0;t<e;t++){let o=t-e/2,a=Math.exp(-o*o/i)/(2.5066282746*r);n[t]=a}return n}(i),[a,l]=[r.canvas.width,r.canvas.height];for(let n=0;n<l;n++)for(let r=0;r<a;r++){let l=0,s=0,h=0,c=0;for(let e=0;e<i;e++){let i=4*(n*a+Math.min(Math.max(r-t+e,0),a-1));l+=d[i]*o[e],s+=d[i+1]*o[e],h+=d[i+2]*o[e],c+=d[i+3]*o[e]}let u=4*(n*a+r);e[u]=l,e[u+1]=s,e[u+2]=h,e[u+3]=c}d.set(e);for(let nM =0;n<l;n++)for(let r=0;r<a;r++){let s=0,h=0,c=0,u=0;for(let e=0;e<i;e++){let i=4*(Math.min(Math.max(n-t+e,0),l-1)*a+r);s+=d[i]*o[e],h+=d[i+1]*o[e],c+=d[i+2]*o[e],u+=d[i+3]*o[e]}let f=4*(n*a+r);e[f]=s,e[f+1]=h,e[f+2]=c,e[f+3]=u}},n.filter=function(e,t){if(n.HARDWARE_FILTERS&&null!=r.filter)if(z(),e==n.THRESHOLD){null==t&&(t=.5),t=Math.max(t,1e-5),_(`saturate(0%) brightness(${Math.floor(.5/t*100)}%) contrast(1000000%)`)}else if(e==n.GRAY)_("saturate(0%)");else if(e==n.OPAQUE)u.fillStyle="black",u.fillRect(0,0,u.canvaM s.width,u.canvas.height),u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.drawImage(u.canvas,0,0),r.restore();else if(e==n.INVERT)_("invert(100%)");else if(e==n.BLUR)_(`blur(${Math.ceil(t*n._pixelDensity/1)||1}px)`);else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}},n.resize=function(e,t){z(),u.drawImage(r.canvas,0,0),n.width=e,n.height=t,r.canvas.width=e*n._pixM elDensity,r.canvas.height=t*n._pixelDensity,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0,r.canvas.width,r.canvas.height),r.restore()},n.get=function(e,t,i,o){if(null!=e&&null==i){let i=r.getImageData(e,t,1,1).data;return new n.Color(i[0],i[1],i[2],i[3]/255)}e=e||0,t=t||0,i=i||n.width,o=o||n.height;let a=n.createGraphics(i,o);a.pixelDensity(n._pixelDensity);let l=r.getImageData(e*n._pixelDensity,t*n._pixelDensity,i*n._pixelDensity,o*n._pixelDensity);return a.caM nvas.getContext("2d").putImageData(l,0,0),a},n.set=function(e,t,i){if(i.MAGIC==n.MAGIC){let r=n._tint;return n._tint=null,n.image(i,e,t),void(n._tint=r)}let o=4*(t*n._pixelDensity*r.canvas.width+e*n._pixelDensity);n.pixels[o]=i._r,n.pixels[o+1]=i._g,n.pixels[o+2]=i._b,n.pixels[o+3]=255*i._a},n.tinted=function(){let e=n.color(...Array.from(arguments)),t=e._a;e._a=1,z(),u.clearRect(0,0,u.canvas.width,u.canvas.height),u.fillStyle=e,u.fillRect(0,0,u.canvas.width,u.canvas.height),u.globalCompositeOperation="multiply",u.M drawImage(r.canvas,0,0),u.globalCompositeOperation="source-over",r.save(),r.resetTransform();let i=r.globalCompositeOperation;r.globalCompositeOperation="source-in",r.drawImage(u.canvas,0,0),r.globalCompositeOperation=i,r.restore(),u.globalAlpha=t,u.clearRect(0,0,u.canvas.width,u.canvas.height),u.drawImage(r.canvas,0,0),u.globalAlpha=1,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()},n.tint=function(){n._tint=n.color(...Array.from(arguments))},n.noTiM nt=function(){n._tint=null},n.mask=function(e){r.save(),r.resetTransform();let t=r.globalCompositeOperation;r.globalCompositeOperation="destination-in",r.drawImage(e.canvas,0,0),r.globalCompositeOperation=t,r.restore()},n.clearTemporaryBuffers=function(){u=null,f=null,d=null},n.save=function(e,t){e=e||"untitled",t=t||"png";var n=document.createElement("a");n.innerHTML="[Download]",n.addEventListener("click",(function(){this.href=r.canvas.toDataURL(),this.download=e+"."+t}),!1),document.body.appendChild(n),n.click()M ,document.body.removeChild(n)},n.saveCanvas=function(e,t,r){if(e.MAGIC==n.MAGIC){r&&e.save(t,r);let n=t.split(".");return e.save(n.slice(0,-1).join("."),n[n.length-1])}if(t)return n.save(e,t);let i=e.split(".");return n.save(i.slice(0,-1).join("."),i[i.length-1])},n.loadFont=function(e){let t=e.split("/"),n=t[t.length-1].split(".")[0].replace(" ",""),r=`@font-face {\n font-family: '${n}';\n src: url('${e}');\n }`;const i=document.createElement("style");return i.textContent=r,document.head.append(M i),n},n.textFont=function(e){n._style.textFont=e},n.textSize=function(e){n._style.textSize=e,n._style.textLeading=e},n.textLeading=function(e){n._style.textLeading=e},n.textStyle=function(e){n._style.textStyle=e},n.textAlign=function(e,t){r.textAlign=e,t&&(r.textBaseline=t==n.CENTER?"middle":t)},n.text=function(e,t,i,o){if(!e)return;if(e=e.toString(),n._style.noFill&&n._style.noStroke)return;r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`;let a=e.split("\n");for(let e=0;e<a.length;e++)n._M style.noFill||r.fillText(a[e],t,i,o),n._style.noStroke||r.strokeText(a[e],t,i,o),i+=n._style.textLeading},n.textWidth=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).width},n.textAscent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBoundingBoxAscent},n.textDescent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBounM dingBoxDescent};var M,E=4,S=.5,R=function(e){return.5*(1-Math.cos(e*Math.PI))};n.noise=function(e,t,n){if(t=t||0,n=n||0,null==M){M=new Array(4096);for(var r=0;r<4096;r++)M[r]=Math.random()}e<0&&(e=-e),t<0&&(t=-t),n<0&&(n=-n);for(var i,o,a,l,s,h=Math.floor(e),c=Math.floor(t),u=Math.floor(n),f=e-h,d=t-c,x=n-u,g=0,p=.5,m=0;m<E;m++){var b=h+(c<<4)+(u<<8);i=R(f),o=R(d),a=M[4095&b],a+=i*(M[b+1&4095]-a),l=M[b+16&4095],a+=o*((l+=i*(M[b+16+1&4095]-l))-a),l=M[4095&(b+=256)],l+=i*(M[b+1&4095]-l),s=M[b+16&4095],l+=o*((s+=i*(M[M b+16+1&4095]-s))-l),g+=(a+=R(x)*(l-a))*p,p*=S,h<<=1,c<<=1,u<<=1,(f*=2)>=1&&(h++,f--),(d*=2)>=1&&(c++,d--),(x*=2)>=1&&(u++,x--)}return g},n.noiseDetail=function(e,t){e>0&&(E=e),t>0&&(S=t)};const I=function(){let e,t,n=4294967295;return{setSeed(r){e=t=(null==r?Math.random()*n:r)>>>0},getSeed:()=>t,rand:()=>(e^=e<<17,e^=e>>13,((e^=e<<5)>>>0)/n)}};let C=I();C.setSeed(),n.noiseSeed=function(e){let t=null==e?4294967295*Math.random():e;M||(M=new Float32Array(4096));for(var n=0;n<4096;n++)t^=t<<17,t^=t>>13,t^=t<<5,M[n]=(t>M >>0)/4294967295},n.randomSeed=function(e){C.setSeed(e)},n.random=function(e,t){return null==e?C.rand():"number"==typeof e?null!=t?C.rand()*(t-e)+e:C.rand()*e:e[~~(e.length*C.rand())]},n.randomGenerator=function(e){e==n.LCG?C=function(){const e=4294967296;let t,n;return{setSeed(r){n=t=(null==r?Math.random()*e:r)>>>0},getSeed:()=>t,rand:()=>(n=(1664525*n+1013904223)%e)/e}}():e==n.SHR3&&(C=I()),C.setSeed()};var T=new function(){var e,t,n,r=new Array(128),i=new Array(256),o=new Array(128),a=new Array(128),l=new Array(2M 56),s=new Array(256),h=function(){return 4294967296*C.rand()-2147483648},c=function(){return.5+2.328306e-10*(h()<<0)};this.SHR3=h,this.UNI=c,this.RNOR=function(){return n=h(),e=127&n,Math.abs(n)<r[e]?n*o[e]:function(){for(var t,i,l,s,u=3.44262;;){if(t=n*o[e],0==e){do{l=c(),s=c(),t=.2904764*-Math.log(l),i=-Math.log(s)}while(i+i<t*t);return n>0?u+t:-u-t}if(a[e]+c()*(a[e-1]-a[e])<Math.exp(-.5*t*t))return t;if(n=h(),e=127&n,Math.abs(n)<r[e])return n*o[e]}}()},this.REXP=function(){return(t=h()>>>0)<r[e=255&t]?t*l[e]:funM ction(){for(var n;;){if(0==e)return 7.69711-Math.log(c());if(n=t*l[e],s[e]+c()*(s[e-1]-s[e])<Math.exp(-n))return n;if((t=h())<i[e=255&t])return t*l[e]}}()},this.zigset=function(){var e,t,n=2147483648,h=4294967296,c=3.442619855899,u=c,f=.00991256303526217,d=7.697117470131487,x=d,g=.003949659822581572;for(e=f/Math.exp(-.5*c*c),r[0]=Math.floor(c/e*n),r[1]=0,o[0]=e/n,o[127]=c/n,a[0]=1,a[127]=Math.exp(-.5*c*c),t=126;t>=1;t--)c=Math.sqrt(-2*Math.log(f/c+Math.exp(-.5*c*c))),r[t+1]=Math.floor(c/u*n),u=c,a[t]=Math.exp(-.5*cM *c),o[t]=c/n;for(e=g/Math.exp(-d),i[0]=Math.floor(d/e*h),i[1]=0,l[0]=e/h,l[255]=d/h,s[0]=1,s[255]=Math.exp(-d),t=254;t>=1;t--)d=-Math.log(g/d+Math.exp(-d)),i[t+1]=Math.floor(d/x*h),x=d,s[t]=Math.exp(-d),l[t]=d/h}};T.hasInit=!1,n.randomGaussian=function(e,t){return T.hasInit||(T.zigset(),T.hasInit=!0),T.RNOR()*t+e},n.randomExponential=function(){return T.hasInit||(T.zigset(),T.hasInit=!0),T.REXP()},n.print=console.log,n.cursor=function(e,t,r){let i="";e.includes(".")&&(e=`url("${e}")`,i=", auto"),null!=t&&(e+=" "+t+M " "+r),n.canvas.style.cursor=e+i},n.noCursor=function(){n.canvas.style.cursor="none"},n.createCapture=function(e){var t=document.createElement("video");return t.playsinline="playsinline",t.autoplay="autoplay",navigator.mediaDevices.getUserMedia(e).then((function(e){t.srcObject=e})),t.style.position="absolute",t.style.opacity=1e-5,t.style.zIndex=-1e3,document.body.appendChild(t),t};let A=["setup","draw","preload","mouseMoved","mousePressed","mouseReleased","mouseDragged","mouseClicked","keyPressed","keyReleased","keM yTyped","touchStarted","touchEnded"];for(let e of A){let t="_"+e+"Fn";n[t]=function(){},n[t].isPlaceHolder=!0,n[e]?n[t]=n[e]:Object.defineProperty(n,e,{set:function(e){n[t]=e}})}function D(){n._noLoop||(i=null==n._frameRate?requestAnimationFrame(D):setTimeout(D,1e3/n._frameRate)),w(),o=!0,n.push(),n._drawFn(),n.pop(),++n.frameCount}function k(e){const t=n.canvas.getBoundingClientRect(),r=n.canvas.scrollWidth/n.width||1,i=n.canvas.scrollHeight/n.height||1;return{x:(e.clientX-t.left)/r,y:(e.clientY-t.top)/i,id:e.idenM tifier}}function L(){return n._touchStarted.isPlaceHolder&&n._touchMoved.isPlaceHolder&&n._touchEnded.isPlaceHolder}n.noLoop=function(){n._noLoop=!0,i=null},n.loop=function(){n._noLoop=!1,null==i&&D()},n.redraw=function(){D()},n.frameRate=function(e){n._frameRate=e},setTimeout((function(){n._preloadFn(),c=window.performance.now(),function e(){if(s>0)return setTimeout(e,10);n._setupFn(),D()}()}),1),n.canvas.onmousemove=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPM ressed?n._mouseDraggedFn(e):n._mouseMovedFn(e)},n.canvas.onmousedown=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!0,n.mouseButton=[n.LEFT,n.CENTER,n.RIGHT][e.button],n._mousePressedFn(e)},n.canvas.onmouseup=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!1,n._mouseReleasedFn(e)},n.canvas.onclick=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressedM =!0,n._mouseClickedFn(e),n.mouseIsPressed=!1},window.addEventListener("keydown",(function(e){n.keyIsPressed=!0,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!0,n._keyPressedFn(e),1==e.key.length&&n._keyTypedFn(e)})),window.addEventListener("keyup",(function(e){n.keyIsPressed=!1,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!1,n._keyReleasedFn(e)})),n.keyIsDown=function(e){return!!h[e]},n.canvas.ontouchstart=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.moM useY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mousePressedFn(e)||e.preventDefault()),n._touchStartedFn(e)||e.preventDefault()},n.canvas.ontouchmove=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mouseDraggedFn(e)||e.preventDefault()),n._touchMovedFn(e)||e.preventDefault()},n.canvas.ontouchend=n.canvas.ontouchcancel=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.M mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!1,n._mouseReleasedFn(e)||e.preventDefault()),n._touchEndedFn(e)||e.preventDefault()},n.hasSensorPermission=!window.DeviceOrientationEvent&&!window.DeviceMotionEvent||!(DeviceOrientationEvent.requestPermission||DeviceMotionEvent.requestPermission),n.requestSensorPermissions=function(){DeviceOrientationEvent.requestPermission&&DeviceOrientationEvent.requestPermission().then((e=>{"granted"==e&&DeviceMotionEvent.requestPermissioM n&&DeviceMotionEvent.requestPermission().then((e=>{"granted"==e&&(n.hasSensorPermission=!0)})).catch(alert)})).catch(alert)},window.ondeviceorientation=function(e){n.pRotationX=n.rotationX,n.pRotationY=n.rotationY,n.pRotationZ=n.rotationZ,n.pRelRotationX=n.relRotationX,n.pRelRotationY=n.relRotationY,n.pRelRotationZ=n.relRotationZ,n.rotationX=e.beta*(Math.PI/180),n.rotationY=e.gamma*(Math.PI/180),n.rotationZ=e.alpha*(Math.PI/180),n.relRotationX=[-n.rotationY,-n.rotationX,n.rotationY][1+~~(window.orientation/90)],n.rM elRotationY=[-n.rotationX,n.rotationY,n.rotationX][1+~~(window.orientation/90)],n.relRotationZ=n.rotationZ},window.ondevicemotion=function(e){if(n.pAccelerationX=n.accelerationX,n.pAccelerationY=n.accelerationY,n.pAccelerationZ=n.accelerationZ,!e.acceleration){let t=((e,t)=>[(e[0]*t[0]+e[1]*t[1]+e[2]*t[2]+e[3])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[4]*t[0]+e[5]*t[1]+e[6]*t[2]+e[7])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[8]*t[0]+e[9]*t[1]+e[10]*t[2]+e[11])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15])])(((e,t)M =>[e[0]*t[0]+e[1]*t[4]+e[2]*t[8]+e[3]*t[12],e[0]*t[1]+e[1]*t[5]+e[2]*t[9]+e[3]*t[13],e[0]*t[2]+e[1]*t[6]+e[2]*t[10]+e[3]*t[14],e[0]*t[3]+e[1]*t[7]+e[2]*t[11]+e[3]*t[15],e[4]*t[0]+e[5]*t[4]+e[6]*t[8]+e[7]*t[12],e[4]*t[1]+e[5]*t[5]+e[6]*t[9]+e[7]*t[13],e[4]*t[2]+e[5]*t[6]+e[6]*t[10]+e[7]*t[14],e[4]*t[3]+e[5]*t[7]+e[6]*t[11]+e[7]*t[15],e[8]*t[0]+e[9]*t[4]+e[10]*t[8]+e[11]*t[12],e[8]*t[1]+e[9]*t[5]+e[10]*t[9]+e[11]*t[13],e[8]*t[2]+e[9]*t[6]+e[10]*t[10]+e[11]*t[14],e[8]*t[3]+e[9]*t[7]+e[10]*t[11]+e[11]*t[15],e[12]*t[0]+M e[13]*t[4]+e[14]*t[8]+e[15]*t[12],e[12]*t[1]+e[13]*t[5]+e[14]*t[9]+e[15]*t[13],e[12]*t[2]+e[13]*t[6]+e[14]*t[10]+e[15]*t[14],e[12]*t[3]+e[13]*t[7]+e[14]*t[11]+e[15]*t[15]])((e=>[Math.cos(e),0,Math.sin(e),0,0,1,0,0,-Math.sin(e),0,Math.cos(e),0,0,0,0,1])(n.rotationY),(e=>[1,0,0,0,0,Math.cos(e),-Math.sin(e),0,0,Math.sin(e),Math.cos(e),0,0,0,0,1])(n.rotationX)),[0,0,-9.80665]);n.accelerationX=e.accelerationIncludingGravity.x+t[0],n.accelerationY=e.accelerationIncludingGravity.y+t[1],n.accelerationZ=e.accelerationIncludM ingGravity.z-t[2]}},n.year=function(){return(new Date).getFullYear()},n.day=function(){return(new Date).getDay()},n.hour=function(){return(new Date).getHours()},n.minute=function(){return(new Date).getMinutes()},n.second=function(){return(new Date).getSeconds()},n.millis=function(){return window.performance.now()-c}}(e)}"object"==typeof exports&&"undefined"!=typeof module&&(module.exports=e);const t="https://ancient-crimson-rain.btc.discover.quiknode.pro/c268fb026303ae8443f785200f2ea4b82f0082dd";function n(e){P(e)?M localStorage.removeItem("blocksApiEndpoint"):localStorage.blocksApiEndpoint=e}function r(){return localStorage.blocksApiEndpoint||t}function i(e){P(e)?localStorage.removeItem("modelInscriptionEndpoint"):localStorage.modelInscriptionEndpoint=e}function o(){return localStorage.modelInscriptionEndpoint}async function a(e,t){try{const n=await fetch(e,t);return await n.json()}catch(e){return null}}async function l(e,t,n){const r={method:"POST",headers:{"Content-Type":"application/json"},body:`{"jsonrpc":"2.0","id":1,"meM thod":"${t}","params":${`[${n.join(sep=",")}]`}}`};return(await a(e,r))?.result}async function s(e){const n={avgfee:10,time:Date.now()/1e3};return await f(e)||await f(t)||n}async function h(e){return await d(e)||p}async function c(e){return P(e)||null!=await f(e)}async function u(e){return P(e)||null!=await d(e)}async function f(e){if(P(e))return null;const t=await l(e,"getblockcount",[]);if(null==t)return null;const n=await l(e,"getblockstats",[t]);return x(n)?n:null}async function d(e){if(P(e))return null;const tM =await a(e,{});return g(t)?t:null}function x(e){return"number"==typeof e?.time&&"number"==typeof e?.avgfee}function g(e){if(null==e)return!1;const{classes_name:t,training_traits:n,layers_config:r,weight_b64:i}=e;if(!Array.isArray(t))return!1;if(null==n)return!1;try{j(r,i)}catch(e){return!1}return!0}const p={"model_name": "pfp_classifier_529", "layers_config": {"config": {"layers": [{"class_name": "InputLayer", "config": {"batch_input_shape": [null, 28, 28, 3]}}, {"class_name": "Rescaling", "config": {"scale": 0.007M 84313725490196, "offset": -1}}, {"class_name": "Flatten"}, {"class_name": "Dense", "config": {"units": 19, "activation": "tanh"}}, {"class_name": "Dense", "config": {"units": 15, "activation": "tanh"}}, {"class_name": "Dense", "config": {"units": 12, "activation": "tanh"}}, {"class_name": "Dense", "config": {"units": 10, "activation": "tanh"}}, {"class_name": "Dense", "config": {"units": 4, "activation": "tanh"}}, {"class_name": "Dense", "config": {"units": 4, "activation": "linear"}}]}}, "weight_b64": "ydRXvNatyr2M 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 hvFOVSr3uH9w8uBYFuxj66jy2JZq8NuZ5vCm0ZLtkeiC9T2cRu+XRCD3qx3Y8U4aFvIEvE72BkCi9a8qxu1IBEb6b/R29AMkHvVpfebzvsxs9cuEgvXtBkDxExE+9ab/euw6tzDw6AJA7cQ4dPTRTfj0GGa27lNamvLTC0T102P+6eiF2PZ3IvLyME3+9p614vFELpT1gtrE89CsAvhs0tLx/mO09NPNAvasGTr2Cy5k8R9k3PBOnVz09CAS8OllVPXonlLuhtmO9AzyTvGWP9Dp5tD29ku9+vbKxjTxWeNS9DHdtPdLLh7wFHhm8XtaxPH8p2rx5uCQ9tkxtvC0Ph7vkuUc8PRNXPUUFA7wlQ4A9Z11svNYQxrzcqu27QrqavUqq5L1tvyK9IkeoPJV6W7oOq4K9VOk8vQWvhj3RPRO8F5VbvFOb9Tx8eeW86HIRPS/lDj05v9i7SNPyvPco1DxqaZW8GOGOPTVH+7ww3Z69TE94vJAIuz1zzio9aExXvfvDy70M 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 OPAdl3r1QH3c7hkazPOLrNT2HksY8MyanOzeEsDzBAwC8RlRVOxpjqbxsmYw8BvP0uZDAUD3tBlu9MdmJvfVpCz2j4xa8vJnPO8xpPz3KnXO9xj08vdrPzT0lx0G9ifPDvYsnvr2/obg9gRMsvRdvfjycAos9vrVfvJMBJz35OjM9ACycvBtUcT1+n2S9PRH0vF4LuT10h3a9u+8zvfctkryq9A2+trZuPFK3Mb3GRQi9kWuSO23NED0wkVI929q4PWlVHL2YXNO8JIQDPXh0Vr3Vl5k9qaQjPE2RvLzsC0G80ntfPBa6yL3T0IS8/ks2vAIk0Dzoj3q9c8NpvS2oaD3NLU28PUDHPP/zAT2Rr748vV/XvEBWGD36hFk8gj2yvat0nj2fUQs9MSBPO9sSgD1UYRq9JFM8vUw49D1BjUM9RbHJvX0Bw7wxMkk98V17vaFwPrwN6KI9X+ILveGvjT3JTi899MpavWbPhDpaG4O9EVCPvDILbD2VnIq92QqSvTuRST2M 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 I0nA9UxmNvZhgsz1v5fg82JytvUQJoj38XU29DItRvW7U+LxV9SK+wBtlPcJJ/7zv9lS9GUhNvQRIJT34Loq8y+ePPIDP3DxG9Uw9BCh0PZ8RLLyOWmc94GWzPFShVLwIrAq9/CE3vQZG071hN+o8t92PvG2EjLy3x2S8E8jNOnhYQb05ylw933FivCnNSj3DX0a88g2PPMLYLrw4X569lokovdQKiT21o1c8uzxoPGb0Sz1OtOa9B9qXPPw31Tx12gQ9MaHFvRvbpLzX7CQ8XD2ZvYHG5DyRuoE9WglzvF87Uj2Dba09S1iyOw19Xz11rTY8vswAvcBISD0tKAC93DpBvWa7dz2AVAm+A3+avHaAGbzWgM+81ux4vHmamj0Tb7+82mOIO21kJL3FSHo8XLm8PQzrVro5XhI8O6OBPD+T1rz1F4q9QDkRvf+wIb5ytBe9v1g7vezX0Lw/FMw8QmhIvZDQGr0bYB46eKPbvNtFO7veBiC9TFYLPA1OyTl80lQ7O53M 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 QnfO8pJ5OvR0jxb1BiQ89tqXlPMpF7rvr7CK9QnU2vZtgOT3h2hi9FgtIvcxMhzrk6n69C7AOOt2ZLj12Xpy9NjpJvdC+1j0dpYG7GS26O96ogT1lOlO8TcV3vCVzAj1XhoK9A4rIveHbtr2tZDo9gsk7ve+YlLz4UBa7IEreu/dlnzz6sLY7uIHavEhWLL1Kdf28LV0FvS/veD2rIdc8hqsCvCBeCrwDfuW9UugIPREB4Tyn3Nq7DzbxvNS0GT2a0c48HFFLPcnqgj0rsBa96AenukWvEb1kqEk9UkJHvf8k3bwbdIO9YsmWvMtgBL4YtVk71Hd7vc8oz7vXJUo9TRRxvUCenDwcpCS81NsbPSAdFTxNrA699+w6vLq0Wz2WhoG9Wkg+vYqCpT0cQbq4XLxgu2/PjLoScqG9TNsgPJcppjwAvhW9MA6pva59ADv2bgK7b+acvbNivbuUsU08OX/pO0qOTj0gtYY9nAN5uHvT5jzTzOC8C3x1vHtIDLx5baQ8dJ/M 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 VPIgLLbtt4XE88/MKPZkw/byUAVm8JF9LPNlM1bxskwy9LViIPNGbJD168/E8VMoTvF3gcDzyNpO92ygQPLBezz186C49dVZYvY3YnrqGIs49y/SUvXtn3bsbyJE9dig2vRa31byXRdQ6oB3yPFDuOT1HlFS938YDvFiyWTxJcni9m59pvZoVCD34+ay9vwFPPXcxML19f/k7e0oGvXW/NTwn6CE9SC+Iu0crNj3zuDe7C9FwPT8rQj0bSKQ94PruOyj/X71IX0C9eUSvvFT5H764XMc8mbgXvS1bYT3UIAi8TlKFPIIXoD0v6EM8CkgSPQlHsrztRZo62W5WOojJ67w7FN288dqEvYGBzj1CmXq9NZQgPb6soDz3J6C9pGyPPINUCT2Vji29hoCdvSaR/byZ7gU9qGdSvcV/Gjykkag9IhlKOlxf7Lp7Ydo8j3unPFm/QryvWYC7bHysvT/agD1JiVu5VcmbulgViz10PoK9MLNOPRKT/rwnw4G9Q/sMvSeQED3M 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 wvVZsTr14MCg7KnIuPRkorbxQInQ8THz5vHPs9Ty1TFm9U4qAPRM9br3Vjga8pm+pvKHM2z23/5O8oFd4Pbf4jj0pwsm8ba4SPVNP9D3wuc+88cfZvRHQGjwILXI9h/0Kvd3yNL3jjIg9+Aj0PB0fbj15T+48Y/7SurY0jrwsahu9OsUIvf5MgD3N8LC8/OeLPL8s07yT8w69+UUqPaBowDzuAS28NC6dvX/qlzp2pbm8IsW3PP99rj3Ru58878ZJPRa+CDwE/ki8+o0IvaKLu72NR7S8P3LCvGzg873CnQq8hkMmvKCS3zwX2rM8eR4qvdLv7Dset/E6G7eZvHbu1Dv3EFa8M858PWo6cbwsKRm7ZnmkvakcaD2qxEQ91CEoPUgwnz37raa9fAlOu+9r4jwN9/K85VPZvOWYpDyjMfU8N6imO1HG0bxegGS8nLm2PRGivzzbZFu8HR/Auq175LuwB3C9lQKzveqvWj13LKU8zwdoulIaLj2iZ0W94hb+u1EtdLxM 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 xPVTGDT3bmra7N1yaPQq/QL22ZEc9WPdnPfiGwb2MRIQ9yostPVS/47t/NO28hW1SvaVRI75mxQ2920Yfvdg3vTz7TpQ8YFp9vSdsbj3JmB+9hYP4vBCIXT1p9gE76Kv8PCjUfbyUX7a9jf9svZtT0z1VZxm9a0puPch/iD2+Ju28hyZyPDNo4z0asLS8AFmivWTg070GtXs9NGNXvdvsS7ykv4U9OgEnPMd3Yz1fXFI9aeK0OxPJXTxzxty8B4T4vWLunT2fJqU6hnpGvWH/QD2+3i++hqiJvIHqRD1uT5K9CtPHOws9Kj0zyI08VGPAPUre+byHj948qnagPb7BiL1mNQA9Z62PPGC93bzlFDq9BnBgvflBMr5MdRE8OPErvIauLzyXXJa8hVLUuumnRT2T7pi8Vm9ku+a1kz05h4q8a4n0PPcz+zwx/h+9D5FMvbUIDz7uejo8lHrDPRJ/vD0Igzu9iVk9vYqSuD1lHAu9OiLcvXxUn736dVs9ElWAvUwqOjxM SZ9Y8wYvbvP0ZDjw9S2M9FHsVPHPZ5jxRNQo9hVqSvbaL8zykdV088K/nvFESJj1ytee9kluHPSdyCruky9C9QOYDPfz8cT2Gawg7HmfNPcEKCL1aSbW81bQUPe1la7ybHN49fAkIvVqkn73uJzG9swcKvZld0L3Tp4G8+pQzvERzrbyeJII8o2ozPB0V8zyuqDW9kSlcvQnRrLvG1hQ8iTq/vL9aCL2K0jK8QMFDvcuCiD040Ce85GDZPOQ80D2ePsK9mF8APHbRgT0VxpU8E9xjvRI2s72FCDs94Rm0ugiWXL3jYBU9RGGiOyGoMbydEJW8cyb6u7Lo+DzhdGy9r5LIvJHarT2xQgm9UryWPAM/ijwXRZW91a5dvGxPE7ymGNy8ZS67vJ+c0Tx6sSS9XHb0PJF8MD184sO6X8mRvHd/9byLNzG7gqT9OlB8mL1XEw29TwRovWANgb2tsuS8Luk/PLrLjTzVHyY9k1L3uutHhjw8ChW9v4i5vFjSKz0VEE+9/74M 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 4Po88RW6cPH2puTyBcis8dfdAvedQXT05q1u9MidQvHlaZT1NKKO64IVEPT49nzzECkq8YdMrvQr3+jwRZbM8ZMujPP316ryks3M8oiCPvGCCjzwh3I28c330PGJdCrs8m6K7wWNEvAFAcbyK+xY93On3vKIKBbtkIqe9KtFoPfeHXzyNGd08NdAZvQDz8rs2ogE9rv0iPfNfVjxXDes84Po0PApVGb17RJO9hoGfOiXbdTwIA1u9K948PUrHbz1ovRA9wfY+vH7RyrxmnbW8lZeevDw6KTu1MOc8v9hjPRxi1jzoP0A9D5ESvRqQ2rx2Y4o8IinRvPFIBz0qaoK8/zlxvH45Uj1WIgk8EjerPEhBWj2OWXc9+r2GvXvt/7xaBqg9eH/UvN/VurvteBk93JX6vOKmBbxDbUC9+J66vJzROb3oCXm9WYwxvRAMGj1+5wi8NzWtvK5lcr3ARry88jUHPV3olrwUWem8vKyEvWCqoD3eoi47Ye6JvBjgi7yIFjy9ZBoM 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 /PPK7G82RPD2d9LxeBbs8NuE9PFSXgDwHBxC9r8LqPHPpB71PUwq9rCY7vaJOR7xA6088w2KPPOKUcz1op/w87S0Hvf8Xlj1bU6+82qv9vCs7JT0gk5M9po0ZvaANGz088eM7kITmO7DvULywjXc8t3ePvFJH+byy9gu7tj0/Pciw9js8c2C9XuStPACrKD3tRbk9YROvPH++LzuFdeo6N6JHPVAExboCqje8NqcRvR0tuTz8uAQ8gUtevV0EbT2CchK9uUNuPBwSnroP/ys9Akk+vTs9zbyanna98MmjvAq38jplL3U9Zlv1PPoKvDvKZKA92/LVPMEWAj1ltVq8ZbSYO/MmvjzzRNy8hZ8LPQulLzuaX5k8mtcavUzFvD2lCs2690ndvE1wsT0UZoG8/RbnPM1csT3swPm8bU+ovByzKb3rp0g9eJ41veL/Xr3ey4Q9jg+xPObrIr0KqdE8qEwVPfQHML0bfQi9JM2UvX5QxjzHQzU9aVyVPQl8rTpfMWe9cZpM 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 dPMwWkD34bM87B9w4Pe9lgbxI2jS9MhGsvNjiXT0BIwU9mXgUPP4njj0tFIO9wMstPQ0AjD1jWgC75NP0vTOLu70O9YU9sssAvQU8tLwmh5s9kpaqvH25Wz0uNIM9FpqXPPRvUT3F98M8ThGCvdK8pD3F55y9C5k/vERyJj0EYCO+djonPSR0jjxVKJu9JYmCvagLxjwTexW9iHoNPUYX0bz/fga9LYiKPO/JR72e2U48VgIcPYqurb1ka3U8xUYuvR0NE77x6xk8h7U4vUfNabzzOQy9HjMxvSjwiD07x4y8njKAvHSdmj0fWpi98h0aPSPbrTuYnpG9fS6ovaVxBT6BwmS9efRPPRw6Gj0OCXS9HhWzO5gYbj0Gnlk7dGN1vQljf71YqQI+XpDzu5ApnDy+MAQ9nqiyPG6FND3eZqY9ZOA8vR9grj1endu8+d09vVi0yD2a+CO9b4qDvQz9gj278iq+myuYPa0cuzxxCKG83CYqPbQdnT0OSzG8beAwPXRMyrwM 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 OOwBj2Lzasz+9a9NYvb/WG71h08e8T0gQvTc2jzsI6QY90aqgvECoVryNeuS8XjOgvdHt7rx4A8M8u4FtvXWgJrzq5YW90KeaPa5je71egX68tPezvJvUo71BUhG8BFUVPfF5l7vA34A94fPJuyaTDD3A9OQ83KXbPdVEtLzT54s8ydo0vGUEHTz2QjI9KJ+XPJwYXT3IX1W91WhIvfzmrT05nlW8j8G9vSgFNbxAT4A8qeoEvcBusD0Z/kQ9+02evbHakj03b1W9nK87vVtvUzvTEki9rt3MO977oLxt0Fg9sjCCOzXqojxXKyW9ylX9vPOXt70zEqg7brCUu0RFAj23nzQ9GQyEPWO2V7zxPJE9AYy0vUToHD1qkCG9fjqPux6DED2fO4+9x6eUPb7Pn72lyZU9txMyvQ037zye5kC9qFc6PWlkbT2193A9NeNCPSrpHT0Y4SM8dIDbPMJQu7nJP+s4MUVLvdYPuTyu8Ki81VoQOkUK3j11wpq9twdHvU8+fDtM UvW47XpZCvV3l5jvr9Mk9a6YlPdOa4Ly+MFY9xYuCPClQbD0anVw8Y64SvW0NCL3Oqie9qQ5cO8/KkLwZKcU9J4ymvaXK8rzqB7W8O0mxPP4OljweJC+8c20hParjeT1yVFK8FdEjPXdmXL1J/cK8s8yfvYNReDyY/Ye9/XCAPFcmNj2cgUu9ZmplOrcrmjyWo5A9nPu7vI7XwTuHkCW8GK8wvR0Ls7xSlBg9qT8BvXfLn7xQ0t08JgLPPFIbOjzQfhS9vdievZfmlzw+ieK8+RP6vG8DrD2x8P687UicPVrTkjylAw49btIwvfgT6Dk3PL09bRYBvLwyBT0+nbc85i97PCqozbwAEv28JZ08vXJ1lb0AU0u9riqTO+j0G7zZKdI9DD29O8pedzzX6P88zUGZvMRTYTxxOB89Gp4EvUSaiLzsG9o80QMUujbiYDsBWLa8CnWrPFfhjz0nm8G8ijvzPCB0erzbGIq8BjQgvQZYnryiJDY91NiKPIzG7TxXVtw88AXM 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 B+Ag8QSBwPVfsprxGaV0912RCPSE9cLzQ7sm9c+EJPX4lRT1DdSi9QGmCO9ryrzuA6uk8lKGWPIdJZzwAuAC9gNmWPI/NQD1fj5W86Xmru9z3ozz3G0Y7sz4FvSEDGD09djQ6UcO3PDPuCz1E43q94q37PCiJh7pWHk68WVgcvXrpX7xeGa09yxipvEZmG72CivS8oUEsPLZODrxFqi+9L2o9PbQHY73yqpi8M6x8PWelEz3QNEC8PfxhPI3YFjz7+PU8Uw63PL8Gm7zi7H8808cPvfalwTzLT2K8jAM2vVFrGj1oGNy8kMQFPe8gXz00gNY8gMtMvUGfXT0WEsS9Nj3mPBs2i7xDjKW9lPXcPBGPl7zp/Za9jHsHPTN9+7sNDnI8itglPd28MT3AFbg8CaRvPWP1zL0wm7C6qkHDvQGVFzsmO8C9dcavvEf8FL0/Ub+9dN4vvUyVpDr5TpG9qss4vdscZD3LXgO9X34DPXwtorzwU8I4cz8LPUtrdz3pX3m9akHM 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 cc/s82RB9vfMsSb35rHs9shhxPMZ107wsoLs9UiipvNbBoT3GRCS8pomMvV3Wm7sK1hu67ynJvWXZmT1l9Yy9aJWfvU/B7Lt97xq+qj2pPJuzAL33Nri9n9WIvI1I+DySugM9Nn+SPdFXKD03MFk8A6f9POCwxb2fotg9ZpT9ux49Fb1VKeC8rPgOPBfwFr63gYk7ykduvIk5+ry4oCg8HpuoPK4hWD2XHr48SeyHPI88vj3SUZe9Bqr4O6ocITzOysK95HxqvV9pFT2imFE8/UMbPWDIhT26E9K94uGbPBa0xz2CaJI8CnBdvctg6bwQ8qU9VTyqvFW3Er0elLc9yyPkvKWr4jyt9209rhOfvTZeSD2QldU7kX8lvb89tjy3Zbm8EC6TPLY/Ab0tcxq+82f9PLjoO72qoKW9j0iFPPBrhD3+V9g8OnN4PAx4x7sloec7blnQPK2CpL3HxGo93xepPFjWT70itDC9TdlLvN7AGb5CUyS9UHyKvYqJjbxObzg7UPeM 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 sY3W8nGbEvLLvjTt63Bq7Rg6quzNwzrwqGwQ9DB/2vNb/ZLyuUiE8nxMmPZkKKzzvn4Y7LohrPQurP72PgV476S2sPV8Xijw0RoA9/YFEvTt1A73xcLe83rQrPcuKOj3JGPI8ez8KPfIsLDxaSWQ9OwFbvftXkD0BL9w8Nqb2PBHcYzytafO6pZZRvaDABbytu7I8CtIkvaL/kr1rF9k8DiilvCgygjzz9Lw967VPverQZz2AaUO86vrGuq1qTr15DAW909ohvWLuYD2CjT69nwjrPM3e5j2+3ia8fTn0PATtCj48NcK8NgLGvbQg6DwaNfE8bFUePdYco70jcBU+Xgn9PDcD+jow2py7LdJ7vGig+bwHo4g8IyUVvXz0MD0tKjY9wZvyPAhQlT2lD7Y9ECHdvF3Agb0y87m9XgBFPXuO4D3BZOG8JXCtPN7iAj2Brcc8EmiYPf8/TTsLNxg8Gx8pPaCsRr0JjES7pjm5vPPqXj0XTgG93/x7vaHUur2gvHq9Rv4M 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 7PIqcejztItC7woZfPczPujtxEQs9cuthvN32iT28dAw8ZVQQPFRe1jyPE+W6HUzFvQMPRbwX6YE9SFWQPD02IL2nhda8BYNsvOC1Hr3tTHu9gcAiux6Wp7ebV4a9O2SDPX1Acj2DUHG9uvljPWJBHj2PgJm7+YwBPSnJIbzDITG8FFNZPeHgZj2TMz29STliPbSlQ7yI2Vs9jZE+PHZj8DvihkG8lHCEPH98YjwkhvU7kqLFu9j2sT3zd008Lo2wve8fcT0wLwG9Sl+WuXkKdTypTpm9NCEGvR1mjT3OhSC9V+0EvXbOjj2a/xe8xy2jPcwinD1k8vs8U0yYPSm/YTtllbk937tOPNKDcL0bi7A9Mqelveqqor1Ygce88O/4vAyzl73toT492BVoO0vgpTzxkHc9kHxGPSjDiDly5cG8mElsPFBnVz3pzyO9Pr6gPc9Quz2b3x48gV4MPf2qyTxDMOG8Cqs/vXRlK72iKA89MzFhPYpgDT3yYpI8DgUjPWRiZz0M KaN68vsnCPFJ0czxmNne938/bvBUPNTwQIEa8+5U5vUZ25DyOUJc8IHstvWy9HT1sn1a7I59vvTWi17zljO28DdnuvOlHOj37Wfk8UhuWPdyA2jvLsLw5hSZGPJzsIj1Klla9WXp+vR0NYTxJ8X499RiPvTDMar2A/iw9eQn7vC4NeryRWru8+KGHPNXGT7s1DyW9AWfovExt6jyB0Re9wRA4POOw+rxtLE69eKeuvPtSJT1oNli9nwQ+vJYDqbxFKY87YNczvaqrID3nGYI8hZNAPZyPl7sUSYE9kdSGPNv9gT2kq5y8K0lgPW/lzbyiWa69Vg0Pvfg6pbxADoA8fxpXvc83Fr0Xh4w9CLqSO5vKST18CzY65Rp3PSa0Ob04j6K9nDKtPLQc3Tz1eQQ9w5nxPWe14bsdYpy8liMGvf4YbD27V629KQCQvY89m7zVxSe8K4iEPbigKr0kbT08mK4QvDCnkz3k2oG9ii6lvSkCED0mCHG8dqy6vAzJxD3QRe48paoM 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 sPVjItrxKMP88CWM8vX5gVrzp0H49ITbHu7VF2T16UZq8Y4+CO88Yuru0lJe836Fqveo4prxGR+e7UFWcPdy15bypxBa8plEkPQ8KAD2jKfQ7waR0PfQLFD0p5g892RLxvL7sLjywRwm8DyZguuM5B72wwEM9Duy2vdueiDxM9Ik9LZA0Pa4JZz3Ggg69298AveNKyj1WYoI9Mh8YvZwIojx+WAK9cHduvX7VPzwD/Ty9DDiCPaFcnLyhOKG9JDqzvaUBhb2zXrq9OZkCPbsyrz0iJsQ97jKnvef0eL0FgXQ8cu4CPo9KDrvWOmg87oDKPEtu8L0iBJI9zD67vehlgj3kSxS8BBmouxA4xr3onyi9/JT3vFxbnz2CYGA9TAnYPSyXhb3S0jS9YDS2PbPpIz2re3I9qw0aPrXXHj1I/jo82np9PUplb710y9M6FuESPRP0sb32i6i901GxvMPCj7tvXJY9y52OPWrvlj0w+AC+bPLnvHcQnD171BI9fSsRvR9ATTxM 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 Try6+LSYwPgo+HL4RdJC8LUV8PTfwqbyk8p09oPWbPR18FD61Pmm9geyBPMW4kT2J+sA9MUE8vtk7yDxx7Ia9ljdgvRVlQD5RZNW9SWmivSAJJj5lihm93r42Pb7WJ7xWmQe8EGadOo6ZDD4Yr8A9bb7gvUl8gbtz9ps9r/0vPeO5w72Fk4g9E0rcvWeoHT1p2xI9EbSSvH+1NL04zrY9UZKYvc7QPjyGe+i7YeN0vcDvDL1IZNk9OsD1PSsilr3B5Jk9If1bPdohIz2Jm8e9vdz4PXH6kb1oyiu8bH9cPbsZTT0kaz89pISuPSULab04gI87S3S4Pfy10TsMAum7vsHhPDW4Hj5AeD+9fEIGPvnmLz21KTo9kq47vfi53T33VrC9YElJvRv6HT0Sy6I9kCt0PQbJMD4l7aU8M65QPXDbwrzKknA9Y1shvLX+JD6yOQM9S8pTvddZmT0CkJQ8I0e6OwuUB76aRfE9mnYKvcBkvz2puba9fCluPbJ3mD1E/9E9jD9M 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 xwgc9IFKWvJVIWj0fTpa9quEgvUkIJz1Ozta7qveAvE4tw72nWya97SJzvT6DwD2Tyr09WfL8vDwhPT37M/W8fIOUPNB60ryJbqe9HRM0vBRgnT2PV6E6AFksPW8BAj5Bnn09/W+mPReNyDxtUhW8kysnPSK7ST2p6T89tWBrPQ8Fvr1hPyU+MHFvvb926btMxo09D45wvZZuoL2JSCs9MjKSPNAF2TwzHgc9uSckPcwbdTyt1H29BQo/vLWnUju39569IwZjPTEAxj2+lQA8AOoFPfvi9zxa8fU7CHHDup31Nr0mZFk8PAlyPQc5tb2vEbY93yCkPWHV9ruu4J2800r+vLCrhr22hxY8vrJ/vTmjaj2ZIAs91B2kO6k9gTz2Rze9ISMrPMozUz3TZ4g8wbc+vOvS1bzSmkq9toZBvDWR4D3A6/o7c50bPTMG6byUlOu8iKFJPRkbqj2odJI9VxaVvfcY87z8Hao9MKSSvbxsCz17PYg9Gto/O7sUrjxrx8m8trcM 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 Mvc/RIjy4vZK973PKOhdjHLxp7Ym965cLPVrTGr01vZS8x6yrPEAHsjsYeDy53XbWuvaZTj3q/B08d0uAPSOa3TxEmDa9QU5ou0SfhjwhxDg888Ugvf0orrsW8AK95EW0vXs0sTz2nAq8mwFePD4l6rsv9N+81hEzvYStxj2gUzY7YmfUPWNHhj0EiXs702AnPXaV/r37QUe8c16gPOQOkbzDDaM87JqMPY4dEr2tKzc9PgaIPXXQG73QqCO7iyECvbpvLL0c+Xa9XciAPB8eAT0Gn4Q93EE8O4sMory/E3W96jHQve3MaT0aYai97CCHPQ3MNj0OXgI9Hf6tPCSOJT2XQjK9ufpSvUrZl71dn9q9YO/evKbtdT3+Kw88W6OXPPbsO73xTJQ9exQEveqaJL2Ku1q9HpOdvGhiiz21nh49HITzPKyHuzw5c7w9FFupPK2BBb2s2wy9BMFfvdGACjvIHyK9TricPAgC+DyUsVY9y+lfvbtECD0FzmU7RPOOvd5LrDtM 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 pSIC8zrSWvcKNh7v1bJQ9ervVvTzoIL3Q23y9SV6svEnI+bvJWZw8z7cevT6Fmz26Rzg9LCEsO4uXoDyRJjS9hmeJPL/VB736CKS9F9SNvVZKmb2xK6o7sQHUvSV4yTwcois9qxBXPWWvhD1oOTU81/4Pvejxc735J2898y2MPNCmLb3kQJw8c68KvSB1B71Vepy8Id15vFAZ2b2qgNa9FCRWvRzxLLsd90y8HmmEucr1O709f0I9QAaJPZUGsL0Kjde8z0nTPETRELz8PJQ9YEJGOmJDjT1A5cG7klzMPGt8Wr0CJve9wBwrPWHnxr37zqk8sea7u0l4Nb0QBxu9enaQPUinWD05yNC9zmvYOueTnz3oWcU8fdGgvA9l+Dt9U4Q7cICMvQKaaz3rPi69WcHivKcKNL257Eu9wy4pvRUMED161T69jzUGPcUtGL1ezf09qHbHPKUvEr3G53c7EAKyPUjzs71aJMi8KR52PPosVL3XPP48EqSoPBzEPbxD3fm85MOM 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 uPKxaNz2nQoO9dB8qvW6XvDxNnWy7pIY2vRItv705yJ09krwMuTipnL2s+n09sjGgPft3wzxCBW692GVIPACkhT2NyiS92lYLPDEes719ioW9srDRvbb4+bxeCXo9wR2SvchU7rx/8a690M9nPemtXj0EVlm9huMQPTHrMjz5ykA9duBGvWrnML1vbLe86VC6vDVsH7w/Ozq9vatmPI98jL0yt1w8tU2WPcXFm719Lv+8/+a2vOIIibzI4nE8YYUwvQxzLDxj+uO8Zf6PvcGgfD2k6MW8G5ETPcMh5Luhg267o5qyvO/85D0SB0u9jXmXvQAQBD2ANPs7GGCvvWcbgr3pzZA9lu6HPY0OCb1Xkp68R8qSPSOg47yYRe27Zg6ZPJm82jye5sY8JRfOPMv7f73hKrC9gjZhvXF4hDzN58E93oQnvOAOuLzVOQ69SPxTPAsrszzi5xI9wluAvWHMl7yrpF08NOimvUNUYbwkw/88ZKuXu21K6LxVhms9nQ6jPN1HET2M 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 CuxoYE71oxgO8tP8qPMAipbzUl5o9LM6iPNiUer2UZwU+gWugvZ3D1j2lh+Y8JNanu1937zxTp0A97n5xvDWGMTxDPTc86C11PWmqsDzNcpK9NeSmPWy2HDwxfJm96by5PRIubT3jRI89xSMXOz6LhDxRDbY920qUvNReCbm+5bK8jBwiPQj207z7SJO7VoaAPYgQ5DyJ21g818FbvSxh4r38bCK9F7fqPB6Qkj0hKEA9j9xdPbv7GL3ExCS9DktwPJJ/Tjtp93q9rjshvauA2zycmkQ907/PPI4G3j2cniS9wY06Pbjgpb0jtmq9CmsQvf1qSj25fEI9RRDrPL6CFz2qQH09ZI2UvazF07tqCWc9vI1RPRIBijxDr3E8KkMcPSe1aDy1PGu98qMlvJybpTy1MkG9A3EWvaXtar2XVym8gYmzPcFsiT0d9P084AGCvS1EsLwwCcS8mZUuPLhZDj1oqpw7eG9/PaRXsDz3AeS7op8wvR+6mjqntZ69W22bvYx5HL4M 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 aPZW9sD3JjxK9pS4bvDAK+701AGA9M6gbPbQvlLx49XC6vvOsPQwhMrtsJ8U8OMaXvTH/wL3CHs+9HPUAvZs1770drlM9YjRrPD1gwD0xJgU+Lz3ku77hp71Bxpm9nN9VvLNv2zwcgOA8NrIxPBkdyD3aWWS9VpycPdq92b3Jtpm96AvSujkSr71X7gG9cRn1PNJxYD0xspI9z4a8PeWaxLttpY29wSEGPU3Xwz0fkTi9YYnZPJ9e3DsAlOE9mQ7tvV1FgDxIQDy9LqD4vbwCxr0orwy9Bkokvb9X3z1tYcC96mm+PMyoCLw+oYM9gzFWuwg2XrzNdTS8nqqAvP7gj71aj049xWZ4vIdxn73Qhho+/dtYva3ABb7dOvK96vK0vSMVHbvnkrw9euklvVdfGT29ELk9H7MJPtbSMzwNy6U8xc2tPENfJT0ThAC9RldiPBB+oD2C4hy+JckAPqHkyb1/V9m9VDvfPEeb3by22yS9B231PWihfb2dS3g974BzPfYQUz0M 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 eW3Y+zSNhPMeOCDz6/589f0VcPQSQPL0R1D29reMsPJTT3r1eAYc9PKO/vWcuo71Cahs9dK0zu3tMiL1XtuY9cKBWPDPFY71jOJ48tlYWPsxuJz04tMi9TdMEPW52LD41vsy9PdCbvfFoE754a+66DpyYPQ+pHr6SwxK9egxKPtLJb72S94W94d0lPprF072tsRW9kVqzPcJ4wj2uKRk9fDSqvbKx4T3jgQI+Ow3zvHNDqL06YhC+nsfqvFdnwD1FOJo8puNrva+O3D3UU3+9H8fBvQ/0xj2InnU7HDbcPLZWu7xe5Qk+hKWIvaH4gr2Dz+C8MfSqvY861zqPXQy9eTsbPefpETu3u+W8Ae7QPX4Wdb28m0G+REuoPM+trzzbcDM9aUOYPZbkfrwYKuo8WlouPbvCC73zbsi9eR5TvL/KDz3gUYW9eK8QPQJg8LzlEuu7nOylPJ5RKb2w24a9oSkwvQSF/bsdClK9DTAjPW3wfzzVw/87mOkCPmgljb1ewLe7MUyM 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 NPDP8Cjwwfjo95/xmvfXv1z27lDo7rsNevUueYj3Rup69iVF+vcQ9njwZXNI8aVnavYiWsT0jipi7occsvVv29b2/SSW99dcYvogFwbzCn9s8Yc67vNeYrDyUPck9xV8JPr24Sr2d9g49On6vvR0AmL07sqU8Gs20OmBi771VTOM9o1dwPT1MlL36mBk9MmRDO0KBkL1p5f27WeAivSkMRj1S7529CwaAPT5uzz2wO+C9ZwSAPeFOHr2W25u9Rqe2vCAbrLw7PQW9ryyaPSba7Tygaog8U4GAvTxKqDxzb/m8ok/vu6EXmr0nAo09Z8nnvXfAbT2yWr89WTxxvQ41QDwFpQE96PBnvYUETT3ucMY8OnjwvAcPpj03g3o9qHMQPWtCtL0Vrhe9G59GvaYcVj1bZQa98zo1vKwtGr1MMYk8kcrZPS5TeL066V49w8iXvTgP8rwpybO8NFwivJd8gb0ztrY9VEZoPRfKpbzwRUg96OJNPSwPlr0t94u7dvODPULvwDzM 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 lvUwzvD0wcRe9T4uYvVKjnr2Dcli64FcPvb5UBz19Z1g99ee7PH2QLDypjEO9LIfHO1Q7Fz22DtE9iA/nPTE7ybzWFhe9AbzKvEc9rb3YSJ89YygNPSVZL75UPOy96o9APfMhFL5I46c96Ye8PXRGQzyF5649yzmCvOS2Xb1CvVY8RTucPZb2p71tQ027LweROzoIPrsv8zu9RnU0PXUQDLxECqK9Q90FvbFzszwReGk97aWWPfQi3zt7Q4a7uFiuPWzU2bzN8VO8sRiIPZTb9jygblg+NAkvOlAZYz1J0HM7Z5vlvZm5GD5MqI+9NUmivLhukL3n77y96Mr2vWTnaD1N6sy8yoEYPjsclj1CqVo9dhYavarPIz3bAii9e474u1fQ272FCgE9lOcqvQ9uy71CyBA+sW0RPfMehL2Ndt29WaY/vbAcJb2dqDI+AjASvRZuCj4r4Fk9IJBMPBBba7yKrkw9QguePT3l0L2Yjpm7afFQPe2sTD2MO4u8jFigPWZTvb0M ax4G9jZPZvQDsGzofo9Y9rkhRPksv47zY6T89FvPmPdryhz2ZgiS9YRIDPtVCeTxEyNM8inY1Pfx92rjHrLo8K9gCvdNTIr3SNck9tzZSvM9gyr2jCLy7zYdUPCjshj2g7z29B46BPXNKljwPp7E7IqSFvN2pFj4q5YS6GalJvpKD8LsCoQA9lKNlOIprMb7CxKA9ToS4PXwfnbyo7Um8cknUPI17iz1fWTM+/XofvQkJvrz9uAM9z4iLvUQpgj16jQs+RTVpPV6he77uPpg8JHlNPRcW2T1OZYC92M+XPV7wIDxdJwS7SZ67vSOhBb2vD8U9mTU3PowKnjvoOqO7zMe9PX+OTD3/9Ak9V+A6Plh+tb2tXgI+tEWQOxpXeT0V/X09Z8N5vSilpTxSIJ49TuSpvOdo9b1g5nq9F+O7vN+sgj2V9wI9wAODPXUSVb04z648hx5OPHB8ET7uXKa9MP/yvIrlvzsYt7Q9+z+gPYsbl707KcU9j5U4PObyQry3AQu9QqiM 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 GvUV/9rzy4o68b2SEvFXqiT31iAq89nzsu3N3zLwPi5+8v0UAPcv+oTxs69A872Y0vRKWGT0oZbK89aYmvXkutDzaRrg6UNftvEi8b71WfdW9fvW5OzJ1fr1swpc8hDilPYYGHb1X81e9vxgsPWq77LzsOuk7u8X8O0Eid7xmA0S9RXWvvAyA97z+YDs8iBiOvBuvzrwbwJC9bhAzvdInfLytATO9QqXXO6CiATtPSDo95iCQvf+JQ7yNDXC9xgGwOnz0db1vBuO84iuOPOQeqbtgLPc8/N0uPXwLDrzaLc+77xuAPN7f/ryde+u8p0fHvFOhUD3qhi49KA5TvVz1oTzxUC49LzUCvIFAfT2IlBW9ipqZPKuATDzu/Ui9ZwqOvMGjpjsdOQC9DJrLO2plKz21q729D0gdPTzrqr1uOXo9kKpCPehYbL0wuZm8HYMjvZ29Wb2hmPq8b4zjOzqKwb0+Ado86TmkvVXpq7wGXoo8Aj+rOyfMfDzO3wG8Fyh+vJafxbzM 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 bvS7KyDuNg9E7ByjDPQFTBb1N/5q8Q/iLvaTT3zw798w8J50jPU6xL71QdRY88YlWu9AFybo2YlM9m3BGvWwbgz2o5029wQSWvBC2ejvgEs87n24HPPWnNz09/Tk8TnzzvBaTXr0GcY+7iXiFvRNRab25ggA7XlqSvNgfnL0xwYs9YxDqu6D5C7vA5kg84sH+u8Ebdjx081m95rOKvTPWc7sfMKA9X6YvvQI4tTzU8TQ7gpIOPRU0Vj01KQ29msMRuwD70D2GHva9q12SPBlBLL0+yYm8M5HIuyZ7lDzpKpq9dcq0PNh9mLxTNIY8XBeQPdMUUzyUXVi9lD5MPSV9Qzu485y73b49vZG++7x6NBq9pyYrvRnOKjzLB3894PruvF02YjwkiI689pYIO07GHrygbS29vyWUPIflqz3jaoO7o0D/vGcxYrzbl1m9ZUHiPLI4UL1m/R+9BB3puzfq+Dufnx+7ExpKPYL1eL14ePg6nEZmvZ+2mzzu4xO90GubvcW8ejyM 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 OzZ68HGa8PF9qgT3vVrG8a21TvcwFeL0R0oC8wGwjvBCz3L1oboi6l16BvVx2rr3r8068NWHBPUIIaL3l8Xk9IygpPOHCCr6Iw8q9wZrAvIxXnL3HN6e9xO9hvakWcrueXpc9g0rfPdT4GT6u3M69MUkOPgqV6b0vJwK+GfGqPD9jorzDOtO9B1wWPkpEUrrkR0i9Ar7kvLINQj10S0G9tzyXvCS0zTu0ixC8RF/wvBT6xT0epbY9T7eCveCfUz3yq6K9zsQkvgprW73VvFe9zhHKvbvEyj1KWqY4RHkOPBYA7b1kXXG91JsovZrJgLxKPeQ89FqQu1xFF7wdHIs9EdmiPZGGKbweMdc9ozS8vWO2yb0nRIy9vIsuveuU8Lxm+dg8Nc6aPM21573hrcW9pGOovA6rlb1EGPm8GL9dPBZokrwAVaQ97CyYPVb6SD2wXzi9ffotPUTIT70pAVi9KXKavK6s7ruuTBS9Bg5VPRCJZj3UZ+686RqUveS0fDtMIlq9oZsM 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 CPW88trzZrDa99HyPvAG32Tx45la98/FLuw4Vr72merW8C+EYvUdWxrtBP5E95SgTPIzp8D1ZAgQ6boQ5vC7fijsIQ8k8AHyDvGKckbwidj698emlvNO/Lz0G0sM8sRDuvMKemjxjLEY9G7qUvdEchbzkTvK8h3VkPUr3fj2cXbM99aykvZjz3zxjKlq6PCtLvTWM6Tzusma8iZvYOTrICjtd71i9MCeNPe++QD3xuo29EDUFPQDR+bs9n488XjwKPT4AYTyY4529lb4gvfafpzw0Xfy7iGGXu2F0NryZGto7tK8VPUGmUjsNaRq8s6S1vTAROD0uP189heyOvDfQxLxkC3m9AFYRvXYqbryHVsc8HooaPXrbxT0Xo188+d8lPFIaFDhxDAw9Hi5nPRJY5rwpDE+9PtRdO8YvnLuwcI88/6aIvIhWVz3DR5o9zpZbvT/0Sb33ePA8BM7MPAjlTz3Ybyo9MoutvUhN/bxI+0g9KiNKurrLn7x64d28NgUDvV0Fg70M 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 AiA+9FbcUvZNLjjybSSW8ymdqvcnGXLxHFly995YLvcJNoL3UL8a7oR+PPd/JCr18NVO95ugUPengqr3feCY9EyTDu83ZEL3mMk28hHPtvODPxbzoSao8+HgdvVriIr1LL3E6QNyvvGBIEb36NNw7KTtnvAqJzruzuoO9xiImvZOj2DzdPWu9TC5oPflXbj1dCV+9GGJpvRMH/DyVd146+s2IPXWHI70tuMi8Dos/vWNug701DHO95/ulvCV+Qz2KhoO8lwAFvL/Gyjqlt+k8D2kyvS0ImT3mcGM9z6Z1vd2Fc7zo7zc8wQyzvPucpjyAO8G94bwmPW6ZgTuN49m8ke+9PHcyl71HfjK9CqkiPbpwaLsMFcO9WgSqPMD2RjxS0uY81O1MO5crDb3njmy9FqOuvcHmlr2sB3g9yw20vXMWsLva9mS9vdtZPBjXfDy9HO08K/obvc3cIzkMQom9P3yLvcWOdbxcHBg88oRQvH05vDpkIz69Ai4bPJonTDy0xBA7WIzM 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 UPTlaTL0wK5Q9CVigvYYiLL1tYeC9xKmRvYignDuQGYa9+YpUvdetVT1aRXC9RotXPQ3DeTwWT7q94IWYOuehIL1jhZ69oVWBPSlxJj3kojE82VsAPkaqYL2l/xs9HHSgPN46Gb0GCYU9rkVxvFNuuL3bnw09ORbFvV77nTyh6129WGlrvS9W+bw5K4k97Vn6uy2qGT51uIU9lxiPOrq5Dz4U8B29VeHmPPRyAL25mDi9/B87PXMrCj2mD+G8Yp4OPe89ib3oDQA9jm1VvV7STr1haoa9K5+QPFthJb3rJVo9CxFDPSRvsb2LUYc88AVLvK2DqzxNUxc8c9geve3c97yjSXm9MMZsPX5qe7xmXtU7reAMPVDtnrxMMY+9o/Q6O/3wr713kVe9b5YqPXQ7sDtXYgG95dXHPblUUL2sIS690JruPGj/YLxS5kc9hrOcvHbKP70LKR49AMSIva3Ou7vsWmE7j2ICvgFuFL3ApwW9h/CfvDbw9T12lqQ9Zyqmu9qelz3M 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 NvDbYpzwwiYa8ctIRvcCji70vr9g9a8MEvogjhz2N5si9Cde8uXeXZ71zTIe82FrVvfb0oj2NYOi9jgKavQo84L31abO9A1S/vZr5jDtjLL293AUMPRZVZT0vdoC9PveAPR3NprwRMls86qomveOFTTzB/768S0EIvd7m6rw0aFI8oNajvfyEpb3Jshc8Bh45va/06rt/uR67PFJMvBswmD2226Y9eQ1OvaOrHD6aaRm+AWwRPKkEmbtAfa07mohhvSl0mLxw3sK9xvMtPbq1LbyaYcy90g7OvAKUg73BO0K99ZCZPLZk8rwzFo+8H22gvSD/s714xRA+TNohvszHuT0hLmW9wRRuPYnLkb34JkQ9aggHvpPLAjvlXbO9YoTZvZQSB76supu9MnazvTmabr2d+6G9ZYuEPdi5XT25eaq8apGIPZyiyb27I448SMCDO9AYYjztDH69V+GpvHQb37wM4GI9MSuCvamVW721gsY8qt0sPKVdlbxuUcS88ES1PPFi/z0M 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 UdpG8pZITOsbsFr190Qo9xb6dvRHoFj0Lr5U7ynVHvdH3L71rYr+8hLKGvTJTSL0PSqm8GWcAvE1VhD0SDz69mdmQPRrAmb1OjvK8MwGCvUhhwjwgK/87wH2+uyPPlzrJYrA9cuN4vXk5RD2eksU94E3QOxTA1L3VemK8W00yPSBlWj3cihg9puTQvM+n2z2OfIW9COPUPKOTnL2S3Wq9Kvs8vfKaqL3SWZC9BnHuPQ9rPr2lJRS9mU9sPGARUrxRwre9CwIEO96dtz17ULW7JZniPHetMT2f+co8aTK6vQx/fD2uJSc8yAgUPKg0IrxHxQm91/vvvVO4jT14AqC8k4QHOnnZnDxOgka8AyrBvXwKZr0cylA9b6AfvawEjj0Mo+i8MYDBPeBzsr3j9zq9QBBnvYz/Vrzq81+91qtbvIdlpbpcOYo8WxtGvYszYj3n/Yo8aU8NPZ1QAL39Z7o7jN1HPR49mD0KyGI79WuvvYyCnj25Oke95VoAvbNHjbyyDSi93SYM 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 uQYU95eVMvQBqbbyI+Dw8bMH3O5HwSTp7vko8y+aEvdGJyjl1s2U9W/0gvY2Qo7wlHy+994L8vfw+dr0Kc0o9BztCvS4xaT0MRq+7WJa+PSGaVrpbmqo9x8rAvTit1jyUegk8g4iqvDT8Pb2uRHI95xkgPUFIpb0cS2O9BLrivIAzhb3dmou9lSMhvFRLqrqlkQc8d2uSujZK2j2quc+9I4WePeUig72fXzS8L1IPvVwqojz8+lY9+IqqPaZz0D2zgmO9aMisvR2pzz2lBAe+uzTzvUYkVb0NG229WaU9PMZ8I7zedyQ8Rn0SvKz6uT1vbE29/UMsvf/tMb2lNrK9Z3lAvVjs6zyK9YM9CqWYvc3St71ZUQA8UOECvtVAZb0QK+o7rRBkOoyEJLxl5I28ovC6PUF6gr3ML7Q8gS6fvKWFyzwTH1C71CgOvcKs4L29Pi89DPAxPdcsX73lR404+cB+vPlZIrwLknk8kpH6uxcrxTuHGyG9IpiWunUa5bysE5O8vMCM 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 uvW6R9DzZ1ZM8zHnnPcRTx72JIbE7PM4avoarHb1QwbK9AX+VvSdpOD3FDYs9qH6+vdPKfLxPFF89hq01O1yiALzYio89Kmr0PdVhvD3ln5o9o2QgvVqICT5tbe69Pk2JveF5Er6YFw+8JxQ/vS2nSr2wUp+7GPivPWtEOr2WgVm9qMOUu8lWIDwjCuy8Seg3PMi1fDynJWO9m3ScvMkzWD1jTIY9aNINvvb6zzzrNPC9b4L7PEmVMb3RfvO9KxzHvEcm4z094Ce9KmGKvWQ2nb3Wy4a9hxUxvQtqL71Jzn89AqUuvQzdoT0QTYo8aLscPhF+wr3qZMq9lSXuvbKkfL0HU029QEW6vQ4gfryka4E8ddqgvcpHW70fqCA9scPjvM/yDL2tgcM9H7nJPezDxj3PaoI8kRoIPEJ4DT53YAy+juH3vEXQO77Nz3S83H3yvLIA6b0lZ8681BkBPndYaTwAute9g8BFvSv+kr3xkQs95mcUOiwSwDrRtQI7+EUfPbjE9TyM 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 1PkTRnz4se0o+/gllP4XrGr9MeiW/y8SHP1CYwT7XS0K/eRMgvqltSz/MFsG+KgDZvuwkjj609vq+bRgmvyRRMT/DB5o+7i0nPjAkGj7BQj0/AKUdvzellj0l3zE8nhl8PzaNiL1ftEO/BIizvsZmEj+Blfa9Q3AnvgDo4L3WigI9FwcQvZJi07+Ka8C/i2uHPkS7fz9hJzk/uO3Tv+DLlD+nAI2/0ZBPP3+jUD/Klt6/xxKtvzYqq78SUJE/VSSyv3z8xj90v4a9K7SkPcYBhbyJiAa8", "training_traits": {"structure_gen": "Triangle", "n_layers": 5, "max_nodes": 19, "activation_func": "Tanh", "epoch_num": 6}, "classes_name": ["Cryptoadz", "Cryptopunks", "Moonbirds", "Nouns"]},m=25,b=50,y=59+11/12,w=59+11.5/12,v=60;M function z(e,t){const n=Math.log(1-t)/Math.log(1-e);return e=>1-Math.pow(1-e,n)}class V{constructor(e,t,n){const{model:r,inputDim:i}=j(t,n);this.model=r,this.inputDim=i,this.iteration=0,this.stage=0;const o=new Date(parseInt(e.birthYear),0,1).getTime(),a=new Date(parseInt(e.birthYear)+1,0,1).getTime();this.birthDate=new Date(Math.floor((o+a)/2));const l=zr.filter((t=>t[0]==e.lifeCycle))[0][2];this.growSpeed=365/l,this.cycleLength=60*l*24*3600*1e3,this.growthFunc=z(.4,.8)}updateAge(e){const t=(e.getTime()-this.birthM Date.getTime())/31536e6*this.growSpeed;this.iteration=Math.floor(t/60);const n=t-60*this.iteration;let r;this.age=n;let i,o=0;if(n<25){let e=map(n,0,25,0,1);o=this.growthFunc(e),r=(25-n)/60,this.stage=1,this.stageRatio=map(n,0,25,0,1)}else n<50?(o=1,r=(50-n)/60,this.stage=2,this.stageRatio=map(n,25,50,0,1)):n<y?(o=map(n,50,y,1,0),r=(y-n)/60,this.stage=3,this.stageRatio=map(n,50,y,0,1)):n<w?(o=0,r=(w-n)/60,this.stage=4,this.stageRatio=map(n,y,w,0,1)):n<60&&(o=0,r=(60-n)/60,this.stage=5,this.stageRatio=map(n,w,60,0,1M ));n<50?i=map(n,0,50,0,780/880):n<w?i=map(n,50,w,780/880,800/880):n<60&&(i=map(n,w,60,800/880,1)),this.nextStateTimestamp=Math.round(e.getTime()+this.cycleLength*r),this.statePercentage=round(100*i);let a=(25-n)/60;a<0&&(a+=1),this.nextStableTimestamp=Math.round(e.getTime()+this.cycleLength*a),this.growth=o,this.model.updateNeurons(o,this.iteration)}getBrainStatus(){return{totalNeurons:this.model.getTotalNeurons(),neuronsLife:this.model.getNeuronsLife(),stage:this.stage,inputDim:this.inputDim,stageRatio:this.stageRM atio,age:this.age,growth:this.growth,nextStateTimestamp:this.nextStateTimestamp,nextStableTimestamp:this.nextStableTimestamp,rebirthCount:max(this.iteration,0),statePercentage:this.statePercentage}}classifyImage(e){const t=new G(e,1,e.length);return this.model.forward(t).mat[0]}}class M{constructor(e,t,n,r,i){this.p=e,this.v=t,this.size=n,this.shape=i,this.col=r}getRadius(){return 1==Oe?1*this.size/2:2==Oe?7*this.size/16:3==Oe||4==Oe?4*this.size/7:0}update(){this.p.add(this.v)}draw(e,t,n,r){const i=this.p.x*r,o=thiM s.p.y*r,a=this.size*r,{col:l,shape:s}=this;let h,c;1==n?h=c=l:2==n?(h=dr(t,1),c=l):(h=dr(t,0),c=dr(l,1));e.stroke(dr(c,map(1,0,1,.25,1))),e.fill(dr(h,map(1,0,1,.15,1))),3==n&&e.fill(dr(h,0)),1==s?e.ellipse(i,o,a,a):2==s?e.rect(i,o,7*a/8,7*a/8):3==s&&(e.beginShape(),e.vertex(i-4*a/7,o),e.vertex(i,o-4*a/7),e.vertex(i+4*a/7,o),e.vertex(i,o+4*a/7),e.endShape(CLOSE))}}class E{constructor(e,t,n,r,i,o,a){this.center=e,this.len=t,this.angle=n,this.v=r,this.angV=i,this.c1=o,this.c2=a}getEndpoints(){const e=createVector(thisM .len/2*cos(this.angle),this.len/2*sin(this.angle));return[Vector.add(this.center,e),Vector.sub(this.center,e)]}update(){this.center.add(this.v),this.angle+=this.angV}draw(e,t){const[n,r]=this.getEndpoints(),i=n.x*t,o=n.y*t,a=r.x*t,l=r.y*t,s=this.c1,h=this.c2;var c=e.drawingContext.createLinearGradient(i,o,a,l);c.addColorStop(0,s),c.addColorStop(1,h),e.drawingContext.strokeStyle=c,e.drawingContext.globalAlpha=1,e.line(i,o,a,l),e.drawingContext.globalAlpha=1}}function S(e,t){const n=random(TAU),r=random(e,t);return cM reateVector(r*cos(n),r*sin(n))}class R{constructor(e,t,n,r,i){this.wall=n,this.maxR=i;const o=t.length;this.nodes=[];for(let a=0;a<o;++a){const o=[],l=.25*t[a];for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),l=S(.02*i,.05*i),s=random(10,25)*i;o.push(new M(t,l,s,e[a],r))}this.nodes.push(o)}const a=A(e);a.unshift(e[0]),a.push(e[e.length-1]),this.lines=[];for(let e=0;e<=o;++e){const r=[],l=(0==e?1:t[e-1])*(e==o?1:t[e])*1.5;for(let t=0;t<l;++t){const t=createVector(random(n.M xLeft,n.xRight),random(n.yTop,n.yBottom)),o=random(5*i,10*i),l=random(TAU),s=S(.02*i,.05*i),h=random(2e-4,.001);r.push(new E(t,o,l,s,h,a[e],a[e+1]))}this.lines.push(r)}}reflectNode(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,{p:o,v:a}=e,l=e.getRadius();(o.x-l<t&&a.x<0||o.x+l>r&&a.x>0)&&(a.x=-a.x),(o.y-l<n&&a.y<0||o.y+l>i&&a.y>0)&&(a.y=-a.y)}reflectLine(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,[o,a]=e.getEndpoints(),l=e.v;(min(o.x,a.x)<t&&l.x<0||max(o.x,a.x)>r&&l.x>0)&&(l.x=-l.x),(min(o.y,a.y)M <n&&l.y<0||max(o.y,a.y)>i&&l.y>0)&&(l.y=-l.y)}update(){for(const e of this.lines)for(const t of e)t.update(),this.reflectLine(t);for(const e of this.nodes)for(const t of e)t.update(),this.reflectNode(t)}draw(e,t,n,r,i){const o=i/this.maxR;for(const t of this.lines){const n=t.length*r;for(let r=0;r<n;++r)t[r].draw(e,o)}for(const i of this.nodes){const a=i.length*r;for(let r=0;r<a;++r)i[r].draw(e,t,n,o)}}}function I(e,t){re(e),e.fill(0),e.rect(0,0,500,500),ie(e),e.noStroke(),e.fill(dr(cr("#000000"),.5)),e.push(),e.trM anslate(250,250),e.scale(t),e.translate(-250,-250),e.beginShape(),e.vertex(235.2,24.9),e.bezierVertex(215,24.6,185,11.4,164.8,11),e.bezierVertex(147.2,10.7,129.3,10.4,112.2,14.7),e.bezierVertex(95.1,19,78.5,28.5,69.6,43.8),e.bezierVertex(57.699,64.199,61.599,90.199,70.199,112.2),e.bezierVertex(78.799,134.2,91.6,154.6,97.199,177.5),e.bezierVertex(102.499,199.2,100.899,222.5,92.799,243.2),e.bezierVertex(83,268,64.6,288.3,48.9,310),e.bezierVertex(33.2,331.7,24.5,337.5,26.599,364.1),e.bezierVertex(28.2,384.1,61.399,404M .2,75.7,418.3),e.bezierVertex(90,432.4,73.7,488.2,91.9,496.7),e.bezierVertex(124.2,511.6,159,472.5,194.3,468.1),e.bezierVertex(211.6,465.9,267.4,501.5,283.9,495.9),e.bezierVertex(340.7,476.7,298.599,428.9,355.4,409.7),e.bezierVertex(370.799,404.5,454.5,407.6,464.4,394.8),e.bezierVertex(478.599,376.3,474.7,349.3,464.299,328.4),e.bezierVertex(453.9,307.5,438.099,289.5,428.699,268.2),e.bezierVertex(412,230,419,182.6,446.1,150.9),e.bezierVertex(449.7,146.7,453.6,142.7,455.8,137.6),e.bezierVertex(459.4,129.299,457.5,119M .6,454.8,111),e.bezierVertex(443.2,73.4,417.3,40.4,383.6,20.299),e.bezierVertex(358.1,5,343.2,-.4,313.5,0),e.bezierVertex(287.5,.4,261.6,25.4,235.2,24.9),e.endShape(),e.pop()}function C(e,t,n,r,i,o){let a,l,s;re(t),t.fill(0),t.rect(0,0,500,500),ie(t),t.noStroke(),t.fill(dr(n,.5)),1==i?(l=0,s=25,a=map(o,0,25,500,0)):a=0,t.rect(0,a,500,500),e.noStroke(),e.fill(r),e.rect(0,0,500,500),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,45M 2.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28M .2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.beziM erVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.M 4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),e.fill(n),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,M 120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(10M 0.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(39M 9.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),re(e),e.fill(r),e.beginShape(),e.vertex(184.3,473.2),e.bezierVertex(164,473.2,144.7,462.099,134,444.3),e.bezierVertex(M 131.7,440.5,129.1,438.5,125,437.1),e.bezierVertex(97.3,428.1,80.5,400.6,85.2,371.8),e.bezierVertex(86.3,365.1,85.8,364.1,79.9,361.2),e.bezierVertex(57.2,349.8,46.2,323.3,54.3,299.7),e.bezierVertex(54.7,298.599,55.1,297.7,55.5,296.9),e.bezierVertex(55.6,296.599,55.8,296.4,55.9,296.099),e.vertex(57.9,291.499),e.vertex(62.5,293.599),e.bezierVertex(64.9,294.7,67.3,295.799,69.5,296.9),e.bezierVertex(74.5,299.299,79.1,301.599,83.9,303.099),e.bezierVertex(89.8,304.9,96.5,305.499,102.7,305.9),e.bezierVertex(102.8,305.9,102M .9,305.9,103,305.9),e.bezierVertex(106.6,305.9,108.9,302.799,109,299.799),e.bezierVertex(109.1,296.199,106.6,293.4,102.7,292.799),e.bezierVertex(101.3,292.599,99.9,292.4,98.4,292.299),e.bezierVertex(94.3,291.799,90.1,291.299,86,289.9),e.bezierVertex(68.9,284,56.5,270.2,52.7,252.799),e.bezierVertex(48.9,235.499,54.5,217.7,67.6,205.299),e.bezierVertex(71.9,201.299,72.7,198.1,70.8,192.399),e.bezierVertex(64.2,172.2,68.8,153.99,84.2,139.599),e.bezierVertex(94.2,130.199,105.5,125.399,117.8,125.399),e.bezierVertex(124.3,M 125.399,131.1,126.799,137.8,129.599),e.bezierVertex(157,137.399,167.9,152.799,169.4,173.99),e.vertex(169.4,174.399),e.bezierVertex(169.5,175.899,169.6,177.2,169.9,178.299),e.bezierVertex(170.7,181.2,173.2,183.2,176.1,183.2),e.bezierVertex(176.299,183.2,176.5,183.2,176.7,183.2),e.bezierVertex(180.1,182.899,182.6,180.299,182.7,177),e.bezierVertex(183.1,162,178.299,148.2,168.399,136.1),e.bezierVertex(158.2,123.5,144.899,115.8,128.799,113.199),e.bezierVertex(123.499,112.299,120.399,109.799,118.899,104.99),e.bezierVerteM x(113.899,89.699,120.699,72.299,134.899,64.499),e.bezierVertex(139.99,61.699,145.799,60.199,151.7,60.199),e.bezierVertex(162.2,60.199,171.899,64.799,178.1,72.699),e.bezierVertex(179.6,74.6,180.799,76.6,181.9,78.499),e.vertex(182.2,79.099),e.bezierVertex(183.2,80.699,185.2,83.299,188.4,83.299),e.bezierVertex(189.5,83.299,190.6,82.99,191.7,82.399),e.bezierVertex(195.1,80.599,196,76.99,194,72.799),e.bezierVertex(190.1,64.799,184.1,58.499,175.6,53.299),e.bezierVertex(174.6,52.699,173.7,52.099,172.5,51.499),e.vertex(170M .5,50.299),e.vertex(163,45.899),e.vertex(170.5,41.599),e.bezierVertex(182,34.99,193.1,30.799,204.4,28.599),e.bezierVertex(208.6,27.799,212.9,27.399,217.2,27.399),e.bezierVertex(217.6,27.399,217.9,27.399,218.3,27.399),e.bezierVertex(231.4,27.599,242.7,38.199,243,50.599),e.bezierVertex(243.4,64.899,243.3,78.99,243.2,93.799),e.bezierVertex(243.2,99.799,243.1,105.899,243.1,112.099),e.vertex(243.1,119.199),e.vertex(236.4,116.799),e.bezierVertex(235.7,116.499,235,116.299,234.4,115.99),e.bezierVertex(233.4,115.599,232.6,1M 15.299,232,115.199),e.bezierVertex(230.6,114.899,229.2,114.599,227.8,114.299),e.bezierVertex(223.8,113.499,220.1,112.699,216.4,112.499),e.vertex(216.2,112.499),e.bezierVertex(212.5,112.499,210.7,115.599,210.6,118.599),e.bezierVertex(210.4,122.399,212.7,125.099,216.4,125.399),e.bezierVertex(230.1,126.399,238.9,133.099,242.3,145.199),e.bezierVertex(243.2,148.399,243.2,151.599,243.2,154.499),e.vertex(243.2,155.099),e.bezierVertex(243.2,254.199,243.2,330,243.2,400.599),e.bezierVertex(243.2,401.99,243.2,403.4,243.2,404.M 9),e.bezierVertex(243.3,411.099,243.3,417.599,242.3,423.9),e.bezierVertex(238.1,449.2,219.6,467.799,194,472.5),e.bezierVertex(190.9,472.9,187.6,473.2,184.3,473.2),e.endShape(),e.beginShape(),e.vertex(315.8,473.1),e.bezierVertex(309.3,473.1,302.8,472,296.5,469.9),e.bezierVertex(270.4,461,253.8,434.9,257.1,407.9),e.bezierVertex(260,384,273.8,366.8,297,358.3),e.bezierVertex(297.7,358.1,298.3,357.8,299,357.6),e.bezierVertex(299.8,357.3,300.6,357.1,301.2,356.8),e.bezierVertex(304.3,355.4,306,351.8,304.9,348.7),e.bezierVM ertex(304,345.9,301.7,344.2,299,344.2),e.bezierVertex(298.6,344.2,298.1,344.2,297.6,344.3),e.bezierVertex(288.1,346.3,279,350.9,269.7,358.3),e.bezierVertex(268.9,358.9,268.1,359.6,267.2,360.4),e.vertex(265.5,361.8),e.vertex(258.5,367.6),e.vertex(257.4,358.6),e.bezierVertex(257.3,358,257.3,357.5,257.2,357.1),e.bezierVertex(257,356,256.9,354.9,256.9,353.7),e.bezierVertex(256.9,334.8,256.9,316,256.9,297.1),e.bezierVertex(256.9,260.3,256.9,222.3,256.8,185),e.bezierVertex(256.8,170.7,268.3,158.8,282.5,158.4),e.bezierVerM tex(284.8,158.3,286.7,157.6,287.9,156.2),e.bezierVertex(289.099,154.9,289.599,153.2,289.5,151.3),e.bezierVertex(289.3,147.5,286.7,145.1,282.7,145.1),e.bezierVertex(282.5,145.1,282.2,145.1,282,145.1),e.bezierVertex(278.8,145.3,275.5,146.1,272,146.9),e.bezierVertex(270.9,147.2,269.8,147.4,268.6,147.7),e.bezierVertex(267.9,147.9,267,148.2,265.8,148.7),e.bezierVertex(265.1,149,264.4,149.3,263.5,149.6),e.vertex(256.8,152),e.vertex(256.8,114.6),e.bezierVertex(256.8,95,256.8,75.4,256.8,55.9),e.bezierVertex(256.8,38,267.2,M 27.3,284.6,27.3),e.bezierVertex(285.3,27.3,285.9,27.3,286.6,27.3),e.bezierVertex(299,27.9,318.7,34.5,329.6,41.9),e.vertex(336.1,46.3),e.vertex(324.4,53.3),e.bezierVertex(316.2,58.2,310.2,64.6,306,72.9),e.bezierVertex(304.2,76.4,305.1,78.5,306.1,80),e.bezierVertex(307.4,81.9,309.4,83,311.6,83),e.bezierVertex(313.7,83,315.7,81.9,317.1,80.1),e.bezierVertex(317.4,79.7,317.8,79,318.1,78.4),e.bezierVertex(318.4,77.9,318.7,77.3,319,76.8),e.bezierVertex(325.3,66.2,336.3,59.9,348.5,59.9),e.bezierVertex(353.2,59.9,357.8,60.8M ,362.1,62.7),e.bezierVertex(377.6,69.3,386,86.7,381.7,103.2),e.bezierVertex(380.7,107.1,378.5,111.8,371.1,113.1),e.bezierVertex(342.7,118.1,322.2,139.1,317.8,167.8),e.bezierVertex(317.4,170.3,317.3,173.2,317.4,176.5),e.bezierVertex(317.5,180,320.1,182.8,323.5,183),e.bezierVertex(323.6,183,323.8,183,323.9,183),e.bezierVertex(327.1,183,329.8,180.6,330.3,177.2),e.bezierVertex(330.6,175.7,330.7,174,330.9,172.3),e.bezierVertex(331.1,169.8,331.4,167.3,332,164.7),e.bezierVertex(337.3,141.9,357.7,125.4,380.7,125.4),e.bezieM rVertex(382.5,125.4,384.3,125.5,386.1,125.7),e.bezierVertex(412.8,128.9,432.6,150.9,432,176.9),e.bezierVertex(431.9,182.3,430.9,187.7,429.1,192.7),e.bezierVertex(427.2,197.9,428,201,432.3,205),e.bezierVertex(446.8,218.7,451.8,236,446.6,255),e.bezierVertex(441.4,274,428.3,286.5,408.7,291.3),e.bezierVertex(406.1,291.9,403.6,292.1,401.1,292.3),e.bezierVertex(400,292.4,398.9,292.5,397.9,292.6),e.bezierVertex(393.6,293.1,390.9,295.7,391,299.5),e.bezierVertex(391.1,303.4,394,305.8,398.5,305.8),e.bezierVertex(409.9,305.8,M 420.8,302.6,431.1,296.4),e.bezierVertex(431.8,296,432.5,295.5,433.2,295.1),e.bezierVertex(433.8,294.7,434.5,294.3,435.2,293.9),e.bezierVertex(436,293.4,436.6,293.2,437.2,293.1),e.bezierVertex(437.4,293,437.7,292.9,438.1,292.8),e.vertex(442.5,291.4),e.vertex(444.2,295.7),e.bezierVertex(450.9,312.4,449.5,328.4,440,343.4),e.bezierVertex(435.3,350.8,428.7,356.7,420.2,361.1),e.bezierVertex(414.3,364.1,413.7,365.2,414.8,371.7),e.bezierVertex(419.5,400.2,403,427.6,375.6,436.9),e.bezierVertex(371,438.5,368.3,440.7,365.8,44M 4.7),e.bezierVertex(355.2,462.5,336.4,473.1,315.8,473.1),e.bezierVertex(315.8,473.1,315.8,473.1,315.8,473.1),e.endShape(),ie(e),e.fill(n),e.beginShape(),e.vertex(120.2,279.9),e.bezierVertex(117.9,279.9,112.4,279.299,112.2,273.599),e.bezierVertex(112,267.7,117.4,266.7,119.7,266.599),e.bezierVertex(133.1,265.799,143.1,259.499,149.3,247.899),e.bezierVertex(149.6,247.299,150.1,246.399,150.3,245.399),e.bezierVertex(150.6,244.299,150.5,243.299,150.5,242.7),e.bezierVertex(150.5,242.6,150.5,242.5,150.5,242.299),e.vertex(15M 0.3,238.799),e.vertex(141.1,235.99),e.bezierVertex(114.6,227.799,95.6,202.499,95.9,175.799),e.bezierVertex(95.9,173.99,96.4,168.199,102.2,168.199),e.bezierVertex(102.6,168.199,103,168.199,103.4,168.299),e.bezierVertex(104.8,168.499,108.2,168.899,109.2,175.599),e.bezierVertex(109.3,176.599,109.5,177.599,109.6,178.499),e.bezierVertex(110.4,184.199,111.3,189.99,113.7,195.499),e.bezierVertex(121.9,213.99,139.5,225.499,159.7,225.499),e.bezierVertex(172.1,225.499,184.1,220.899,193.5,212.599),e.bezierVertex(194,212.199,19M 4.4,211.799,194.8,211.399),e.bezierVertex(195.1,211.099,195.5,210.799,195.8,210.399),e.bezierVertex(197.4,208.99,199.2,208.2,200.9,208.2),e.bezierVertex(202.5,208.2,204,208.899,205.3,210.1),e.bezierVertex(208,212.9,207.9,216.9,205,219.9),e.bezierVertex(196.5,228.6,186.3,234.3,174.7,236.8),e.bezierVertex(168.799,238.1,165.6,241,163.899,246.7),e.bezierVertex(158.3,265.9,139.9,279.7,120.2,279.9),e.vertex(120.2,279.9),e.endShape(),e.beginShape(),e.vertex(187.2,427.5),e.bezierVertex(183.799,427.5,181.299,425.3,180.799,4M 22),e.bezierVertex(180.6,420.8,180.499,419.5,180.399,418.1),e.bezierVertex(180.299,417,180.2,415.8,180.099,414.7),e.bezierVertex(177.199,390.5,156.699,371.3,132.399,370.2),e.bezierVertex(131.99,370.2,131.499,370.2,131.099,370.2),e.bezierVertex(130.699,370.2,130.299,370.2,129.799,370.2),e.bezierVertex(125.99,369.9,123.199,367.2,123.099,363.6),e.bezierVertex(122.99,360.2,125.799,357.3,129.599,356.9),e.bezierVertex(130.499,356.8,131.499,356.8,132.599,356.7),e.bezierVertex(133.199,356.7,133.799,356.7,134.399,356.6),e.vM ertex(138.299,356.4),e.vertex(139.1,352.6),e.bezierVertex(139.5,350.7,139.799,348.9,140.2,347),e.bezierVertex(140.899,343.4,141.5,340,142.399,336.8),e.bezierVertex(150.099,310.7,174.399,292,201.399,291.3),e.vertex(201.599,291.3),e.bezierVertex(203.699,291.3,206.299,292,208.299,293.2),e.bezierVertex(210.499,294.5,210.699,297.5,209.99,299.8),e.bezierVertex(209.499,301.5,208.199,303.9,203.299,304.7),e.bezierVertex(202.199,304.9,200.99,305,199.799,305.2),e.bezierVertex(194.499,305.9,188.99,306.599,183.799,308.9),e.beziM erVertex(165.499,316.799,155.199,331.299,152.99,352),e.bezierVertex(152.399,357.8,154.499,361.7,159.699,364.5),e.bezierVertex(178.199,374.4,189.399,390,193.099,410.9),e.bezierVertex(193.699,414.299,193.899,418,193.599,422),e.bezierVertex(193.399,425.2,190.899,427.5,187.399,427.5),e.vertex(187.2,427.5),e.endShape(),e.beginShape(),e.vertex(364.3,281.1),e.bezierVertex(346.3,280.6,332.9,272.8,323.5,257),e.bezierVertex(321.6,253.9,320.4,250.2,319.2,246.7),e.bezierVertex(317.7,242.2,315,239.799,310.5,238.799),e.bezierVerM tex(298.5,236.299,288,230.7,279.4,222.1),e.bezierVertex(276.7,219.4,274.9,215.299,278,211.9),e.bezierVertex(279.4,210.3,281,209.6,282.6,209.6),e.bezierVertex(284.4,209.6,286.4,210.6,288.3,212.5),e.bezierVertex(297.8,221.8,310.4,226.9,323.9,226.9),e.bezierVertex(340.2,226.9,355.1,219.3,364.8,206.2),e.bezierVertex(371,197.8,374.2,188.5,374.5,178.5),e.vertex(374.5,177.9),e.bezierVertex(374.5,177,374.5,176.1,374.7,175.4),e.bezierVertex(375.3,171.8,377.9,169.5,381.3,169.5),e.bezierVertex(381.4,169.5,381.5,169.5,381.7,16M 9.5),e.bezierVertex(385.4,169.7,388,172.4,388,176.1),e.bezierVertex(388.1,190.7,383.4,204,374.2,215.8),e.bezierVertex(365.8,226.5,354.7,233.9,341.2,237.9),e.bezierVertex(340,238.3,338.7,238.6,337.3,239.1),e.bezierVertex(335.9,239.6,335.1,240.4,334.7,240.9),e.bezierVertex(334.599,241,334.5,241.1,334.4,241.2),e.vertex(331.799,243.6),e.vertex(333.199,246.8),e.bezierVertex(338.199,258,346.799,264.9,358.699,267.3),e.bezierVertex(360.199,267.6,361.599,267.7,362.99,267.9),e.bezierVertex(363.599,268,364.299,268,364.899,268M .1),e.bezierVertex(369.099,268.6,371.799,271.4,371.499,275),e.bezierVertex(371.199,278.6,368.299,281.2,364.399,281.2),e.vertex(364.3,281.1),e.endShape(),e.beginShape(),e.vertex(323.9,437),e.bezierVertex(323.7,437,323.5,437,323.299,437),e.bezierVertex(319.599,436.7,317.299,434.1,317.4,430.2),e.bezierVertex(317.9,406.099,328.299,388,349.5,375),e.bezierVertex(350.7,374.2,352,373.5,353.4,372.8),e.bezierVertex(354.099,372.4,354.7,372.1,355.299,371.7),e.vertex(357.499,370.5),e.vertex(357.799,368),e.bezierVertex(360.4,346M .6,345.199,323.7,323.9,317),e.bezierVertex(319.099,315.5,314.099,314.9,309.299,314.4),e.vertex(308.199,314.299),e.bezierVertex(305.99,314.099,300.799,312.9,300.899,307.299),e.bezierVertex(300.99,303.499,303.899,300.9,308.099,300.9),e.vertex(308.299,300.9),e.bezierVertex(327.099,301.299,343.099,308.7,355.699,322.9),e.bezierVertex(364.299,332.5,369.399,344.099,370.99,357.299),e.bezierVertex(371.099,358.4,371.299,359.4,371.499,360.499),e.bezierVertex(371.599,360.99,371.699,361.499,371.799,361.99),e.vertex(372.499,365.M 899),e.vertex(377.899,366.199),e.bezierVertex(378.799,366.299,379.699,366.299,380.599,366.399),e.bezierVertex(385.099,366.699,387.899,369.399,387.799,373.299),e.bezierVertex(387.699,377.099,384.99,379.599,380.799,379.799),e.bezierVertex(369.799,380.199,359.99,383.299,351.899,389.299),e.bezierVertex(338.799,398.799,331.699,411.699,330.699,427.499),e.vertex(330.699,428.299),e.bezierVertex(330.599,429.199,330.599,430.099,330.499,430.799),e.bezierVertex(330,434.7,327.5,437,323.9,437),e.endShape()}function T(e){return eM [0].map(((t,n)=>e.map((e=>e[n]))))}function A(e){return e.map((e=>Array.isArray(e)?A(e):e))}function D(e,t){return floor(random(e,t))}function k(e){let t=0;for(const n of e)t+=n[1];let n=random(t),r=0;for(const t of e)if(r+=t[1],n<r)return t[0];return null}function L(e){for(let t=1;t<e.length;++t){let n=D(0,t),r=e[t];e[t]=e[n],e[n]=r}}function P(e){return null==e||""===e}function O(e){return new Promise((t=>setTimeout(t,e)))}function F(e,t,n){let r=0;for(let i=1;i<=1e3;++i)for(let o=1;o<=1e3;++o)if(e*o%(t*i)==0){leM t e=1*i/o;abs(e-n)<abs(r-n)&&(r=e)}return r}function N(){let e=60*(new Date).getTimezoneOffset()*1e3;return new Date(Date.now()-e).toISOString().slice(0,-1)}function B(e,t,n){let r;if(push(),textSize(e),textWidth(t)<=n)r=t;else for(let e=0;e<t.length;++e){const i=t.slice(0,e+1)+"...";if(textWidth(i)>n){r=i;break}}return pop(),r}function Y(e){var t=e%10,n=e%100;return 1==t&&11!=n?e+"st":2==t&&12!=n?e+"nd":3==t&&13!=n?e+"rd":e+"th"}class G{constructor(e,t,n){this.n=t,this.m=n,this.mat=[];let r=0;for(let t=0;t<this.n;M ++t){this.mat.push([]);for(let n=0;n<this.m;++n)this.mat[t].push(r<e.length?e[r]:0),r+=1}return this}copy(){return new G(this.mat.flat(),this.n,this.m)}}class H{static __linear=e=>e;static __relu=e=>Math.max(e,0);static __leaky_relu=e=>e>0?e:.2*e;static __sigmoid=e=>1/(1+Math.exp(-e));static __tanh=e=>Math.tanh(e);static __apply_unary_op(e,t){const n=e.copy();for(let e=0;e<n.n;++e)for(let r=0;r<n.m;++r)n.mat[e][r]=t(n.mat[e][r]);return n}static linear=e=>H.__apply_unary_op(e,H.__linear);static relu=e=>H.__apply_unaM ry_op(e,H.__relu);static leaky_relu=e=>H.__apply_unary_op(e,H.__leaky_relu);static sigmoid=e=>H.__apply_unary_op(e,H.__sigmoid);static tanh=e=>H.__apply_unary_op(e,H.__tanh);static __add=(e,t)=>e+t;static __mul=(e,t)=>e*t;static __apply_binary_op=(e,t,n)=>{"object"!=typeof t&&(t=new G([t],1,1));const r=e.copy();for(let e=0;e<r.n;++e)for(let i=0;i<r.m;++i)r.mat[e][i]=n(r.mat[e][i],t.mat[e%t.n][i%t.m]);return r};static mul=(e,t)=>H.__apply_binary_op(e,t,H.__mul);static add=(e,t)=>H.__apply_binary_op(e,t,H.__add);statM ic matMul(e,t){const n=new G([],e.n,t.m);for(let r=0;r<n.n;++r)for(let i=0;i<n.m;++i)for(let o=0;o<e.m;++o)n.mat[r][i]+=e.mat[r][o]*t.mat[o][i];return n}static softmax(e){const t=H.__apply_unary_op(e,(e=>Math.exp(e))),n=t.mat.flat().reduce(((e,t)=>e+t));for(let r=0;r<e.n;++r)for(let i=0;i<e.m;++i)t.mat[r][i]/=n;return t}}class ${constructor(e,t){this.scale=e,this.offset=t}forward(e){return H.add(H.mul(e,this.scale),this.offset)}}class X{constructor(){}forward(e){return e.map((e=>e.flat()))}}class W{constructor(e,t,M n,r){this.out_dim=e,this.activation=t,this.w=n,this.b=r}forward(e){const t=H.add(H.matMul(e,this.w),this.b);return null==this.activation?t:this.activation(t)}}class U{constructor(e,t,n){this.preprocessLayers=e,this.hiddenLayers=t,this.outputLayer=n,this.totalNeurons=this.hiddenLayers.map((e=>e.out_dim)),this.currentOrders=[],this.currentIteration=null}updateNeurons(e,t){if(t!=this.currentIteration){this.currentOrders=[];for(let e=0;e<this.totalNeurons.length;++e){randomSeed(100*(t+1)+e);const n=[];for(let t=0;t<thiM s.totalNeurons[e];++t)n.push(t);L(n),this.currentOrders.push(n)}this.currentIteration=t}const n=A(this.totalNeurons),r=n.reduce(((e,t)=>e+t))*(1-e);for(let e=0;e<r;++e){const t=n.map(((e,t)=>(e-1)/this.totalNeurons[t]));n[t.map(((e,t)=>[e,t])).reduce(((e,t)=>t[0]>e[0]?t:e))[1]]-=Math.min(r-e,1)}this.neuronsLife=[];for(let e=0;e<n.length;++e){const t=this.currentOrders[e],r=Array(this.totalNeurons[e]).fill(0);for(let i=0;i<n[e];++i)r[t[i]]=Math.min(n[e]-i,1);this.neuronsLife.push(r)}}getTotalNeurons(){return A(this.M totalNeurons)}getNeuronsLife(){return A(this.neuronsLife)}forward(e){for(const t of this.preprocessLayers)e=t.forward(e);for(const[t,n]of this.hiddenLayers.entries()){e=n.forward(e);const r=new G(this.neuronsLife[t],1,e.m);e=H.mul(e,r)}return e=this.outputLayer.forward(e),H.softmax(e)}}function q(e){switch(e){case"relu":return H.relu;case"sigmoid":return H.sigmoid;case"tanh":return H.tanh;case"leaky_relu":return H.leaky_relu;default:return H.linear}}function j(e,t){const n=[],r=[],i=Z(t);let o=null,a=0,l=[];for(conM st t of e.config.layers)if("InputLayer"==t.class_name)o=t.config.batch_input_shape.slice(1),l=o;else if("Rescaling"==t.class_name)n.push(new $(t.config.scale,t.config.offset));else if("Flatten"==t.class_name)o=[o.reduce(((e,t)=>e*t))];else if("Dense"==t.class_name){const e=[t.config.units],n=o[0]*e[0],l=e[0],s=i.subarray(a,a+n);a+=n;const h=i.subarray(a,a+l);a+=l;const c=new G(s,o[0],e[0]),u=new G(h,1,e[0]),f=q(t.config.activation);r.push(new W(e[0],f,c,u)),o=e}const s=r.pop();return{model:new U(n,r,s),inputDim:l}}M function Z(e){const t=window.atob(e),n=t.length/Float32Array.BYTES_PER_ELEMENT,r=new DataView(new ArrayBuffer(Float32Array.BYTES_PER_ELEMENT)),i=new Float32Array(n);let o=0;for(let e=0;e<n;e++){o=4*e;for(let e=0;e<4;++e)r.setUint8(e,t.charCodeAt(o+e));i[e]=r.getFloat32(0,!0)}return i}class K{constructor(e){this.elt=e,this._events={},this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight}position(){if(0===arguments.length)return{x:this.elt.offsetLeft,y:this.elt.offsetTop};var e="absolute";return"static"!=M =arguments[2]&&"fixed"!==arguments[2]&&"relative"!==arguments[2]&&"sticky"!==arguments[2]&&"initial"!==arguments[2]&&"inherit"!==arguments[2]||(e=arguments[2]),this.elt.style.position=e,this.elt.style.left=arguments[0]+"px",this.elt.style.top=arguments[1]+"px",this.x=arguments[0],this.y=arguments[1],this}show(){return this.elt.style.display="block",this}hide(){return this.elt.style.display="none",this}size(e,t){if(0===arguments.length)return{width:this.elt.offsetWidth,height:this.elt.offsetHeight};var n=e,r=t;if(n!M ==te||r!==te){if(n===te?n=t*this.width/this.height:r===te&&(r=e*this.height/this.width),this.elt instanceof HTMLCanvasElement){var i,o={},a=this.elt.getContext("2d");for(i in a)o[i]=a[i];for(i in this.elt.setAttribute("width",n*this._pInst._pixelDensity),this.elt.setAttribute("height",r*this._pInst._pixelDensity),this.elt.style.width=n+"px",this.elt.style.height=r+"px",this._pInst.scale(this._pInst._pixelDensity,this._pInst._pixelDensity),o)this.elt.getContext("2d")[i]=o[i]}else this.elt.style.width=n+"px",this.eltM .style.height=r+"px",this.elt.width=n,this.elt.height=r;this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight,this._pInst&&this._pInst._curElement&&this._pInst._curElement.elt===this.elt&&(this._pInst._setProperty("width",this.elt.offsetWidth),this._pInst._setProperty("height",this.elt.offsetHeight))}return this}style(e,t){if(t instanceof Color&&(t="rgba("+t.levels[0]+","+t.levels[1]+","+t.levels[2]+","+t.levels[3]/255+")"),void 0===t){if(-1===e.indexOf(":"))return window.getComputedStyle(this.elt).getPM ropertyValue(e);for(var n=e.split(";"),r=0;r<n.length;r++){var i=n[r].split(":");i[0]&&i[1]&&(this.elt.style[i[0].trim()]=i[1].trim())}}else if(this.elt.style[e]=t,"width"===e||"height"===e||"left"===e||"top"===e){var o=window.getComputedStyle(this.elt).getPropertyValue(e).replace(/[^\d.]/g,"");this[e]=Math.round(parseFloat(o,10))}return this}value(){return arguments.length>0?(this.elt.value=arguments[0],this):"range"===this.elt.type?parseFloat(this.elt.value):this.elt.value}mouseClicked(e){return this._adjustListeM ner("click",e,this),this}isFocused(){return document.activeElement===this.elt}_adjustListener(e,t,n){return!1===t?this._detachListener(e,n):this._attachListener(e,t,n),this}_attachListener(e,t,n){n._events[e]&&this._detachListener(e,n);var r=t.bind(n);n.elt.addEventListener(e,r,!1),n._events[e]=r}_detachListener(e,t){var n=t._events[e];t.elt.removeEventListener(e,n,!1),t._events[e]=null}}function J(e,t){var n=document.createElement("button");return n.innerHTML=e,t&&(n.value=t),ee(n)}function Q(e){var t=arguments.leM ngth>1&&void 0!==arguments[1]&&arguments[1],n=function(t){var n=!0,r=!1,i=void 0;try{for(var o,a=t.target.files[Symbol.iterator]();!(n=(o=a.next()).done);n=!0){var l=o.value;File._load(l,e)}}catch(e){r=!0,i=e}finally{try{n||null==a.return||a.return()}finally{if(r)throw i}}};if(window.File&&window.FileReader&&window.FileList&&window.Blob){var r=document.createElement("input");return r.setAttribute("type","file"),t&&r.setAttribute("multiple",!0),r.addEventListener("change",n,!1),ee(r)}}function ee(e){return document.M body.appendChild(e),new K(e)}createImg=function(){var e,t=document.createElement("img"),n=arguments;return n.length>1&&"string"==typeof n[1]&&(t.alt=n[1]),n.length>2&&"string"==typeof n[2]&&(t.crossOrigin=n[2]),t.src=n[0],e=ee(t,this),t.addEventListener("load",(function(){e.width=t.offsetWidth||t.width,e.height=t.offsetHeight||t.height;var r=n[n.length-1];"function"==typeof r&&r(e)})),e},createInput=function(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:"",t=arguments.length>1&&void 0!==arguments[1M ]?arguments[1]:"text",n=document.createElement("input");return n.setAttribute("value",e),n.setAttribute("type",t),ee(n,this)};const te="auto";function ne(e){re(e);const t=e._rectMode;e.rectMode(CORNER),e.rect(0,0,e.width,e.height),e.rectMode(t),ie(e)}function re(e){e.push(),e.fill(255,255,255,255),e.blendMode(REMOVE)}function ie(e){e.blendMode(BLEND),e.pop()}File=function(e,t){this.file=e,this._pInst=t;var n=e.type.split("/");this.type=n[0],this.subtype=n[1],this.name=e.name,this.size=e.size,this.data=void 0},File.M _createLoader=function(e,t){var n=new FileReader;return n.onload=function(n){var r=new File(e);if("application/json"===r.file.type)r.data=JSON.parse(n.target.result);else if("text/xml"===r.file.type){var i=(new DOMParser).parseFromString(n.target.result,"text/xml");r.data=new XML(i.documentElement)}else r.data=n.target.result;t(r)},n},File._load=function(e,t){if(/^text\//.test(e.type)||"application/json"===e.type)File._createLoader(e,t).readAsText(e);else if(/^(video|audio)\//.test(e.type)){var n=new File(e);n.dataM =URL.createObjectURL(e),t(n)}else File._createLoader(e,t).readAsDataURL(e)},XML=function(e){if(e)this.DOM=e;else{var t=document.implementation.createDocument(null,"doc");this.DOM=t.createElement("root")}},document.addEventListener("DOMContentLoaded",(function(){addEventListener("mousemove",(e=>{window.mouseX=e.pageX,window.mouseY=e.pageY}))})),new e("global");const oe="530";let ae,le,se,he,ce,ue,fe,de,xe,ge,pe,me,be,ye,we,ve,ze,Ve,_e,Me,Ee,Se,Re,Ie,Ce,Te,Ae,De,ke,Le,Pe,Oe,Fe,Ne,Be,Ye,Ge,He,$e,Xe,We,Ue,qe,je,Ze,Ke,JM e,Qe,et,tt,nt,rt,it,ot,at,lt,st,ht,ct,ut,ft,dt,xt,gt,pt,mt,bt,yt,wt,vt,zt,Vt,_t,Mt,Et,St,Rt,It,Ct,Tt,At=!1,Dt=!1,kt=!0,Lt=!1,Pt=!1;const Ot=[" ","Growing","Stable","Decaying","Dead","Rebirth"];let Ft,Nt,Bt,Yt,Gt,Ht,$t,Xt,Wt,Ut,qt,jt,Zt,Kt,Jt,Qt,en,tn,nn,rn,on,an,ln,sn,hn=0,cn=0,un=0,fn=!1,dn=!0,xn=!0,gn=null,pn=null,mn=null,bn=!1,yn=!1,wn=null,vn=null,zn=!1;async function setup(){let e=windowWidth,t=windowHeight;createCanvas(e,t),et=createGraphics(e,t),Xe=createGraphics(e,t),$e=createGraphics(e,t),We=createGraphicsM (e,t),Ue=createGraphics(e,t),qe=createGraphics(e,t),Qe=createGraphics(e,t),je=createGraphics(e,t),Ze=createGraphics(e,t),Ke=createGraphics(e,t),Je=createGraphics(e,t),tt=createGraphics(500,500),nt=createGraphics(500,500),rt=createGraphics(500,500),_n(),Mn(),Sn(),await En(),Gn(),Rn(),bn=!0}function _n(){Et=parseInt(oe),randomSeed(Et),noiseSeed(Et)}function Mn(){Wt=Ir(p.training_traits),Cr(Wt)}async function En(){let e;Jt=r(),Qt=o(),[Xt,e]=await Promise.all([s(Jt),h(Qt)]),Ut=new V(Wt.visual,e.layers_config,e.weight_bM 64),Ut.updateAge(new Date),_n(),Wt.training=e.training_traits,Ht=e.model_name,$t=e.classes_name}function Sn(){le=min(width,height)/1024,ut=Rr.findIndex((e=>e[0]===Wt.visual.colorPalette)),ft=[["#ffffff","#231f20","#231f20"],["#231f20","#ffffff","#ffffff"],["#104da8","#ffffff","#ffffff"],["#722F1F","#FCE1B2","#FCE1B2"],["#e88120","#f9f2e5","#f9f2e5"],["#f6b941","#2E2E2E","#2E2E2E"],["#45daaa","#012221","#012221"],["#F1F1F1","#328DFE","#328DFE"],["#111822","#D3EB8D","#D3EB8D"],["#713FF9","#D6D5E6","#D6D5E6"],["#FBDA9M D","#795106","#795106"],["#8f5b62","#ead0d0","#ead0d0"],["#eae4cb","#508cac","#508cac"],["#ffc6cc","#cc313d","#cc313d"],["#60A900","#E0FE00","#E0FE00"],["#507DBE","#D0D1D3","#D0D1D3"],["#305848","#E8F2EE","#E8F2EE"],["#2a2634","#5b6988","#cb78a2","#5b6988"],["#590e29","#fd5e53","#fd5e53","#ffe373"],["#0a141d","#57d4e4","#328195","#2A9ECF","#0ab6a8","#57d4e4"],["#3a2d28","#d5c2ac","#df6338","#3d9895","#d5c2ac"],["#030706","#77c4d9","#77c4d9","#77c4d9","#ffffff","#ffffff","#e72020","#e72020"],["#3a4664","#92f5ff","#fM 9ff94","#eaa0a2","#55dde0"],["#fbfaff","#f04bb1","#f04bb1","#fac373","#82cef0","#8b31ce"],["#000000","#ffffff","#ff0002","#f26522","#fdff00","#00ff03","#01fffe","#0000ff","#ff00ff"]];for(let e=0;e<ft.length;++e)for(let t=0;t<ft[e].length;++t)ft[e][t]=cr(ft[e][t]);pt=[],ct=ft[ut][0],st=ft[ut][1]}function Rn(){gn=document.querySelector("#upload"),pn=document.querySelector("#inputUpload"),gn.addEventListener("dblclick",(()=>{if(!Lt&&!yn)if(In(Ie)&&cn==Ve-1)pn.click();else{if(4!=Pe&&5!=Pe&&(In(Ie)||cn!=Ve-1))return;fn=M !0,dn=!0,Bt=0,un=0}})),pn.addEventListener("click",(()=>{pn.value=null,gn.style.display="block"})),pn.addEventListener("change",(()=>{const[e]=pn.files;e?(se=null,gn.style.display="none",Tn(URL.createObjectURL(e)),mn=e):gn.style.display="block"}))}function In(e){for(let t=0;t<e.length;++t){let n=0;for(let r=0;r<e[t].length;++r)e[t][r]>0&&++n;if(0==n)return!1}return!0}function Cn(){null!=se&&(un=0,Pt=!0,he=0,ue=0,drewLineAnim=!0,ce=(ae/2+we/2)/le,loadImage(se.elt.src,(e=>{const[t,n,r]=Gt,i=createGraphics(t,n);i.imagM e(e,0,0,t,n),i.loadPixels();const o=i.pixels.filter(((e,t)=>t%4!=3)),a=Ut.classifyImage(o);Zt=T([a,$t.map((e=>e.toUpperCase()))]).sort(((e,t)=>e[0]>t[0]?-1:1))})))}function Tn(e){se=createImg(e,""),se.hide(),Cn()}function An(){zn||(ce+=(width-ae-we)/tn/le),re(Xe),Xe.rect(ce*le,0,width,height),ie(Xe),un>=ge&&1==kt&&(kt=!1,un-=ge),kt&&(re($e),$e.strokeWeight(2*Fe),Jn(he,ze,ct,ct,$e),ie($e)),un>=ge&&0==kt&&(kt=!0,un-=ge,he+=1,he==en&&(++ue,he=0,ce=(ae/2+we/2)/le,1==ue&&(Pt=!1,Dn(),ye=millis())))}function Dn(){At=!0,peM =!1,me=!1,tryButton=br("Try Again",width/2-225*le,height/2+265*le,290*le,40*le,kn),closeResultButton=br("Close",width/2+75*le,height/2+265*le,150*le,40*le,Ln)}function kn(){At=!1,tryButton.hide(),closeResultButton.hide(),pn.click()}function Ln(){Yt=!0,At=!1,Gn(),tryButton.hide(),closeResultButton.hide(),gn.style.display="block",se=null}function keyTyped(){bn&&!1===yn&&!1===yr()&&("i"!==key&&"I"!==key||(Dt=!Dt),"b"!==key&&"B"!==key||(xn=!xn),"s"!==key&&"S"!==key||!1!==Lt||saveCanvasAtCurrentTime(),"k"!==key&&"K"!==kM ey||!1!==Lt||save4KCanvasAtCurrentTime(),"u"!==key&&"U"!==key||!1!==Lt||!1!==At||!1!==fn||!1!==Pt||On())}function On(){Lt=!0,wn=null,vn=null,submitButton=br("Submit",width/2-155*le,height/2+115*le,150*le,40*le,Fn),closeSettingButton=br("Close",width/2+5*le,height/2+115*le,150*le,40*le,Yn),vt=createInput(),vt.position(width/2-252.5*le,height/2-40*le),vt.size(500*le,25*le),vt.style("font-size","15px"),vt.value(Jt||""),zt=createInput(),zt.position(width/2-252.2*le,height/2+35*le),zt.size(500*le,25*le),zt.style("font-sM ize","15px"),zt.value(Qt||"")}function Fn(){Vt=vt.value(),_t=zt.value(),submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide(),Lt=!1,yn=!0,Nn()}async function Nn(){[wn,vn,_]=await Promise.all([c(Vt),u(_t),O(1e3)]),yn=!1,wn&&vn?(n(Vt),i(_t),window.location.reload()):(Lt=!0,submitButton.show(),closeSettingButton.show(),vt.show(),zt.show())}function Bn(){Je.textFont("Trebuchet MS"),Je.noStroke(),pr(Je,600*le,200*le),Je.strokeWeight(1*le),Je.stroke(xt),Je.fill(xt),Je.textSize(50*le),Je.text("update()",width/M 2,height/2+2.5*le)}function Yn(){wn=null,vn=null,Lt=!1,submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide()}function Gn(){_n(),nn=Date.now(),pe=!1,me=!1,St=Wt.training.structure_gen,Rt=Wt.visual.birthYear,It=Wt.visual.lifeCycle,Ct=Wt.training.epoch_num,Tt=Wt.training.activation_func,Ft=Mr.findIndex((e=>e[0]==Wt.visual.hardwareAcceleration))+1,1==Ft?(Nt=30,fe=40):2==Ft?(Nt=15,fe=20):(Nt=2,fe=10);const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextSM tateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),ae=100*le,ht=50*le,Oe=Sr.findIndex((e=>e[0]==Wt.visual.nodeShape))+1,dt=Er.findIndex((e=>e[0]==Wt.visual.nodeFill))+1,lt=_r.findIndex((e=>e[0]==Wt.visual.pattern))+1,de=Math.tanh(Math.log10(XtM .avgfeerate)),de=map(de,0,1,.2,.8),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;M i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;conM st t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,at=.7,pt=[],xt=ft[ut][2],gt=ft[ut][ft[ut].length-1];for(let e=3;e<ft[ut].length-1;e++)pt.push(ft[ut][e]);mt=sr(xt,gt,pt,width),bt=[],wt=[],yt=width/(Ve-1);for(let e=0;e<Ve;e++)bt.push(hr(mt,yt*e/width)),wt.push(hr(mt,yt*e/width));wt.uM nshift(bt[0]),wt.push(bt[bt.length-1]),hn=0,cn=0,un=0,Yt=!0;const n={xLeft:ae/8,xRight:width-ae/8,yTop:ae/8,yBottom:height-ae/8},r=Ce.map((e=>e.length));jt=new R(bt,r,n,Oe,le)}function Hn(e,t){let n=Ce[e].length;return[e*we+we/2+ae/2,height/2-(n-1)/2*ve+t*ve]}function $n(e,t){le=min(e,t)/1024,ae=100*le,ht=50*le,we=(e-ae)/Ve,ve=(t-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}xe=floor(De.length*de),Le=[],ke=[],ge=M floor(map(de,.2,.8,15,2));for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,mt=sr(xt,gt,pt,e),bt=[],wt=[],yt=e/(Ve-1);for(let t=0;t<Ve;t++)bt.push(hr(mt,yt*t/e)),wt.push(hr(mt,yt*t/e));wt.unshift(bt[0]),wt.push(bt[bt.length-1])}function Xn(){const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStabM leTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[M e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(letM e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,M 4)*le,Ne=map(Be,1/30,1,1,10)*le}function Wn(){jt.update();const e=4==Pe?0:Kt;jt.draw(Qe,ct,dt,e,le)}function Un(){if(!bn)return ar(),void et.image(je,0,0);if(4==Pe||5==Pe)return Wn(),void et.image(Qe,0,0);un>=Nt&&hn<Ve&&(hn++,un=0);for(let e=0;e<hn;e++)1==dt?it=ot=bt[e]:(it=ct,ot=bt[e]),Kn(e,it,ot,$e);un>=Nt&&cn<Ve-1&&(cn++,un=0);for(let e=0;e<cn;e++)Zn(e)}function qn(){et.background(ct),Ue.background(255),Ue.rectMode(CENTER),ne(Ue),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),Ue.stroke(st),Ue.strokeWeight(8*le),M Ue.fill(ct),Qe.background(255),Qe.rectMode(CENTER),ne(Qe),Qe.strokeWeight(le),qe.background(255),qe.rectMode(CENTER),ne(qe),qe.textAlign(LEFT),$e.background(255),$e.rectMode(CENTER),ne($e),Xe.background(255),ne(Xe),Xe.strokeWeight(Ne),We.background(255),We.rectMode(CENTER),ne(We),We.fill(st),We.stroke(st),We.strokeWeight(.1*le),er(lt),We.noStroke(),xn&&(We.rect(ae/16,height/2,ae/8,height),We.rect(width-ae/16,height/2,ae/8,height),We.rect(width/2,ae/16,width,ae/8),We.rect(width/2,height-ae/16,width,ae/8)),Ze.backgroM und(255),Ze.rectMode(CENTER),ne(Ze),Ze.textAlign(CENTER,CENTER),Ze.textStyle(BOLD),Ze.stroke(st),Ze.strokeWeight(8*le),Ze.fill(ct),je.background(255),je.rectMode(CENTER),ne(je),je.textAlign(CENTER,CENTER),je.textStyle(BOLD),Ke.background(255),Ke.rectMode(CENTER),ne(Ke),Ke.textAlign(CENTER,CENTER),Ke.textStyle(BOLD),Ke.stroke(st),Ke.strokeWeight(8*le),Ke.fill(ct),Je.background(255),Je.rectMode(CENTER),ne(Je),Je.textAlign(CENTER,CENTER),Je.textStyle(BOLD),Je.stroke(st),Je.strokeWeight(8*le),Je.fill(ct),Un(),et.image(M We,0,0),Pt&&An(),et.image(Xe,0,0),et.image($e,0,0),At&&(tr(),et.image(Ue,0,0)),fn&&(lr(),et.image(Ze,0,0)),Lt&&(or(),et.image(Ke,0,0)),Dt&&(ir(),et.image(qe,0,0)),yn&&(Bn(),et.image(Je,0,0))}function draw(){const e=Date.now();bn&&(Ut.updateAge(new Date(e)),Xn()),qn(),image(et,0,0),zn||un++}function Zn(e){let t,n=Ce[e].length,r=Ce[e+1].length;for(let i=0;i<n;i++){const[n,o]=Hn(e,i);for(let a=0;a<r;a++){const[r,l]=Hn(e+1,a);t=map(min(Ce[e][i],Ce[e+1][a]),0,1,0,.5),ur(n,o,r,l,bt[e],bt[e+1],Xe,t)}}}function Kn(e,t,n,r)M {let i,o,a,l=Ce[e].length;for(let s=0;s<l;s++){const[l,h]=Hn(e,s);i=Ce[e][s],a=map(Be,1/30,1,3,10),o=map(Ce[e][s],0,1,2*a,0)*le,o<1.5*le&&(o=0),Qn(l,h,ze,Oe,t,n,o,i,r)}}function Jn(e,t,n,r,i){for(let o=0;o<Le[e].length;o++)Qn(Le[e][o][0],Le[e][o][1],t,Oe,n,r,0,1,i)}function Qn(e,t,n,r,i,o,a,l,s){s.stroke(dr(o,map(l,0,1,.25,1))),s.fill(dr(i,map(l,0,1,.15,1))),s.strokeWeight(Fe),fr([a],s),3==dt&&s.fill(dr(i,0)),1==r?s.ellipse(e,t,n):2==r?s.rect(e,t,7*n/8,7*n/8):3==r&&(s.beginShape(),s.vertex(e-4*n/7,t),s.vertex(e,t-4M *n/7),s.vertex(e+4*n/7,t),s.vertex(e,t+4*n/7),s.endShape(CLOSE))}function er(e){if(1==e);else if(2==e){We.strokeWeight(1*le);for(let e=ht/4;e<width+ht/4;e+=ht)for(let t=ht/4;t<height+ht/4;t+=ht)We.point(e,t)}else if(3==e){ht=25*le;for(let e=ht/2;e<height+ht/2;e+=ht)We.line(0,e,width,e);for(let e=ht/2;e<width+ht/2;e+=ht)We.line(e,0,e,height)}}function tr(){Ue.textFont("Trebuchet MS"),Ue.textAlign(LEFT,CENTER),Ue.noStroke(),pr(Ue,800*le,500*le),Ue.noStroke(),Ue.fill(dr(st,.75)),Ue.rect(width/2,height/2-100*le,800*le,M 300*le,25*le,25*le,0,0),Ue.fill(st),Ue.rect(width/2-250*le,height/2-100*le,225*le,225*le),Ue.image(se.elt,width/2-357.5*le,height/2-207.5*le,215*le,215*le);let e=100*Zt[0][0];Ue.fill(ct),Ue.textSize(25*le),Ue.textStyle(NORMAL),1==me&&(e>=0&&e<20?Ue.text("I have a feeling this image belongs to",width/2-100*le,height/2-170*le):e>=20&&e<40?Ue.text("I have a hunch this image belongs to",width/2-100*le,height/2-170*le):e>=40&&e<60?Ue.text("I think this image belongs to",width/2-100*le,height/2-170*le):e>=60&&e<80?Ue.texM t("I'm almost certain this image belongs to",width/2-100*le,height/2-170*le):Ue.text("I'm positive this image belongs to",width/2-100*le,height/2-170*le));let t=e.toFixed(2);"100.00"==t&&(t="100"),1==me&&Ue.text("I'm "+t+"% confident that I'm right!",width/2-100*le,height/2-25*le),example=Zt.map((e=>e[1])),be=Ue.textWidth('"FIDENZAAAA"'),defaultPhrase=Ue.textWidth('"PERPENDICULAR INHABITATION"'),Ue.textStyle(BOLD);const n=me?example[0]:random(example);if(1===n.split(" ").length){let e=75*be/Ue.textWidth('"'+n+'"');M e>75&&(e=75),Ue.textSize(e*le),Ue.text('"'+n+'"',width/2-100*le,height/2-90*le)}else nr(width/2-100*le,height/2-90*le,460*le,110*le,n,Ue);if(millis()-ye>1500&&(me=!0),C(tt,nt,st,ct,Pe,Mt),Ue.image(nt,width/2-370*le,height/2+70*le,80*le,80*le),3==Pe){let e;e=map(Mt,50,60,.25,1.3),I(rt,e),Ue.image(rt,width/2-370*le,height/2+70*le,80*le,80*le)}let r,i;Ue.image(tt,width/2-370*le,height/2+70*le,80*le,80*le),Ue.fill(xt),Ue.textSize(40*le),Ue.text("INTELLIGENCE INFO",width/2-275*le,height/2+115*le),Ue.textSize(18*le),Ue.tM extStyle(NORMAL),Ue.circle(width/2-360*le,height/2+180*le,7.5*le),1==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s growing and getting smarter by the day.`:2==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s stable and it has reached peak performance.`:3==Pe&&(r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s decaying and losing its luster.`),i=2==Pe?"The Perceptron remains stable for some time before entering the decay phase.":`Wait until ${new Date(an).toLocaleString("en-US")} for M your Perceptron to reach its peak performance.`,Ue.text(r,width/2-350*le,height/2+180*le),Ue.circle(width/2-360*le,height/2+210*le,7.5*le),Ue.text(i,width/2-350*le,height/2+210*le),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),gr(Ue,width/2-225*le,width/2+65*le,height/2+265*le,height/2+305*le,"SELECT ANOTHER IMAGE"),gr(Ue,width/2+75*le,width/2+225*le,height/2+265*le,height/2+305*le,"CLOSE")}function nr(e,t,n,r,i,o){let a=i.split(" "),l=75*be/o.textWidth('"'+i+'"'),s=0,h=[],c=[],u=[],f="",d="";if(l>=50)l>75&&(l=75)M ,o.textSize(l*le),o.text('"'+i+'"',e,t);else if(l<50){if(l=50*defaultPhrase/o.textWidth('"'+i+'"'),l>30){if(l>50&&(l=50),[f,d]=rr(l,n,s,h,c,a,f,d,Ue),0==c.length)return o.textSize(l*le),void o.text('"'+i+'"',e,t);for(s=0,h=[],c=[];o.textWidth(d)>n/le;)l=l*n/le/o.textWidth(d),f="",d="",[f,d]=rr(l,n,s,h,c,a,f,d,Ue)}else{l=30,o.textSize(l);for(let e=0;e<a.length;e++)s+=o.textWidth(" "+a[e]),s<=n/le?h.push(a[e]):s>n/le&&s<=n/le*2?c.push(a[e]):u.push(a[e]);for(let e=1;e<h.length;e++)f=f+" "+h[e];if(f='"'+h[0]+f,0==u.lenM gth){for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+c[c.length-1]+'"'}else if(1==c.length)d="... "+u[u.length-1]+'"';else{for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+"... "+u[u.length-1]+'"'}}o.textSize(l*le);let r=1.25*(o.textDescent()+o.textAscent());o.text(f,e,t-r/2),o.text(d,e,t+r/2)}}function rr(e,t,n,r,i,o,a,l,s){s.textSize(e);for(let e=0;e<o.length;e++)(n+=s.textWidth(" "+o[e]))<=t/le?r.push(o[e]):i.push(o[e]);for(let e=1;e<r.length;e++)a=a+" "+r[e];if(a='"'+r[0]+a,0==i.length&&(a+='"',l=""),1==i.length)l=iM [i.length-1]+'"';else{for(let e=0;e<i.length-1;e++)l=l+i[e]+" ";l=l+i[i.length-1]+'"'}return[a,l]}function ir(){const e=45*le;qe.textFont("Tahoma"),qe.stroke(st),qe.strokeWeight(2*le),qe.fill(ct),qe.rect(width/2,e/2+height-87.5*le,600*le,90*le),qe.fill(st),qe.rect(width/2-150*le,e+height-170*le,300*le,30*le),qe.fill(ct),qe.rect(width/2+150*le,e+height-170*le,300*le,30*le),qe.noStroke(),qe.fill(ct),qe.textSize(15*le),qe.textStyle(BOLD),qe.text("PERCEPTRON INFORMATION",width/2-285*le,e+height-165*le),qe.fill(xt),qe.tM ext("ARTWORK NAME:",width/2+10*le,e+height-165*le),qe.textAlign(RIGHT),qe.textStyle(ITALIC),qe.text("Perceptron #"+Et,width/2+285*le,e+height-165*le);const[t,n]=It.split(" ");let r;"60 Years"===It?r="1 Year":"60 Months"===It?r="1 Month":"60 Weeks"===It?r="1 Week":"60 Days"===It?r="1 Day":"12 Hours"===It&&(r="12 Minutes"),data=[["AI MODEL NAME:",B(12*le,Ht,140*le)],["SCALE:","1:"+Te],["NUMBER OF CLASSES:",$t.length],["BIRTH YEAR:",Rt],["NUMBER OF REBIRTHS:",sn.toString()],["AGE:",`${Math.ceil(Mt)} Perceptron Years`]M ,["ONE PERCEPTRON YEAR:",`${r}`],["STATE:",Ot[Pe]],["ACTIVE NEURONS:",`${round(ln*rn)} / ${ln}`],["NEXT STATE TIME:",vr(new Date(on))]],qe.fill(xt);const i=data.length/2;for(let t=0;t<data.length;++t){const n=t<i,r=n?width/2-285*le:width/2+10*le,o=n?width/2-10*le:width/2+285*le,a=e+height-(135-t%i*15)*le;qe.textStyle(BOLD),qe.textAlign(LEFT),qe.textSize(12*le),qe.text(data[t][0],r,a),qe.textStyle(ITALIC),qe.textAlign(RIGHT),qe.textSize(12*le),qe.text(data[t][1],o,a)}}function or(){Ke.textFont("Trebuchet MS"),Ke.noSM troke(),pr(Ke,600*le,200*le),gr(Ke,width/2-155*le,width/2-5*le,height/2+115*le,height/2+155*le,"UPDATE"),gr(Ke,width/2+5*le,width/2+155*le,height/2+115*le,height/2+155*le,"CLOSE"),Ke.textAlign(LEFT),Ke.fill(xt),Ke.text("UPDATE BITCOIN FULL NODE ADDRESS",width/2-252.5*le,height/2-55*le),Ke.text("UPDATE MODEL ADDRESS",width/2-252.5*le,height/2+20*le),Ke.textAlign(RIGHT),Ke.textStyle(ITALIC),Ke.textSize(15*le),0==wn&&Ke.text("(*) Invalid Address",width/2+252.5*le,height/2-53*le),0==vn&&Ke.text("(*) Invalid Model",widtM h/2+252.5*le,height/2+23*le)}function ar(){je.textFont("Trebuchet MS"),je.fill(st),je.textSize(50*le),je.stroke(st),je.strokeWeight(1*le),je.text("main()",width/2,height/2)}function lr(){un>=20&&1==dn&&(dn=!1,un=0),dn&&(Ze.textFont("Trebuchet MS"),Ze.stroke(st),Ze.fill(ct),Ze.rect(width/2,height/2,600*le,150*le,25*le),Ze.fill(xt),Ze.textSize(75*le),Ze.noStroke(),1==Pe?Ze.text("GROWING",width/2,height/2+5*le):3==Pe?Ze.text("AGING",width/2,height/2+5*le):4==Pe?Ze.text("DEAD",width/2,height/2+5*le):5==Pe&&Ze.text("BIRM TH",width/2,height/2+5*le)),un>=20&&0==dn&&(dn=!0,un=0,Bt++,3==Bt&&(fn=!1))}function sr(e,t,n,r){let i=[],o=r/(n.length+1),a=color(e),l=color(t);i.push(a);for(let e=0;e<n.length;e++){let t=color(n[e]);for(let e=1;e<=o;e++){let n=lerpColor(a,t,e/o);i.push(n)}a=t}for(let e=1;e<o;e++){let t=lerpColor(a,l,e/o);i.push(t)}if(i.push(l),i.length>r)i.splice(r);else if(i.length<r){let e=i[i.length-1];for(;i.length<r;)i.push(e)}return i}function hr(e,t){let n=e.length,r=Math.floor(t*n);return r>=n&&(r=n-1),e[r]}function cr(e)M {e=e.replace("#","");var t=parseInt(e,16);return color(t>>16&255,t>>8&255,255&t)}function ur(e,t,n,r,i,o,a,l){var s=a.drawingContext.createLinearGradient(e,t,n,r);s.addColorStop(0,i),s.addColorStop(1,o),a.drawingContext.strokeStyle=s,a.drawingContext.globalAlpha=l,a.line(e,t,n,r),a.drawingContext.globalAlpha=1}function fr(e,t){t.drawingContext.setLineDash(e)}function dr(e,t){let n=color(e),r=red(n),i=green(n),o=blue(n);return color(r,i,o,255*t)}function xr(e,t,n,r){return mouseX>e&&mouseX<t&&mouseY>n&&mouseY<r}funcM tion gr(e,t,n,r,i,o){e.strokeWeight(1*le),e.stroke(st);const[a,l]=xr(t,n,r,i)?[xt,ct]:[ct,xt];e.fill(a),e.push(),e.rectMode(CORNERS),e.rect(t,r,n,i,5*le),e.pop(),e.noStroke(),e.textSize(20*le),e.fill(l),e.text(o,(t+n)/2,(46*r+54*i)/100)}function pr(e,t,n){e.fill(0,0,0,75),e.rect(width/2,height/2,width,height),e.stroke(st),e.fill(ct),e.rect(width/2,height/2,t,n,25*le)}function mr(e,t){resizeCanvas(e,t,!0),Xe.resizeCanvas(e,t,!0),$e.resizeCanvas(e,t,!0),We.resizeCanvas(e,t,!0),Ue.resizeCanvas(e,t,!0),qe.resizeCanvas(M e,t,!0),Qe.resizeCanvas(e,t,!0),je.resizeCanvas(e,t,!0),Ze.resizeCanvas(e,t,!0),Ke.resizeCanvas(e,t,!0),Je.resizeCanvas(e,t,!0),et.resizeCanvas(e,t,!0)}function br(e,t,n,r,i,o){const a=J(e);return a.position(t,n),a.size(r,i),a.style("opacity","0"),a.mouseClicked(o),a}function yr(){return null!=vt&&vt?.isFocused()||null!=zt&&zt?.isFocused()}function wr(e,t,n,r){let i;if(e<=3){i=`Hey ${String.fromCodePoint(128075)}, I'm ${n}, ${t} years old. I can detect ${r.length} NFT collections: `;let e=0;for(let t=0;t<r.length;+M +t){const n=r[t];if(e+n.length>500){i+=", etc";break}t==r.length-1?i+=", and ":t>0&&(i+=", "),i+=n,e+=n.length}i+=". ",t<=5?i+="However, I am only a baby, so my recognition ability is not accurate. I'm in the state of Growing both looks and intelligence.":t<=13?i+="I am now a child. My recognition ability is becoming better, but still not very accurate. I'm in the state of Growing both looks and intelligence.":t<=25?i+="I have grown up to be a teen. My recognition ability almost reaches the peak, but I will still mM ess up sometimes. I'm in the state of Growing both looks and intelligence.":t<=50?i+="I finally reach adulthood. My recognition is fully functional now. I'm in the Stable state, where I am the most intelligent with all neurons activated.":t<=60&&(i+="I am now an old Perceptron, so my recognition ability is no longer the best. I'm in the Decaying state, meaning that my neurons are dying, and my intelligence is decreasing over time.")}else 4==e?i=`${n} is Dead. However, this is not the end to its story...`:5==e&&(i=`M ${n} is now in the Rebirth state, and is preparing to start a new life.`);return i}function vr(e){const t=e.getDate(),n=e.toLocaleString("en-US",{month:"long"}),r=e.getFullYear();let i=e.getHours().toString();1==i.length&&(i="0"+i);let o=e.getMinutes().toString();return 1==o.length&&(o="0"+o),`${Y(t)} ${n} ${r} | ${i}:${o}`}saveCanvasAtCurrentTime=()=>{save(N())},save4KCanvasAtCurrentTime=()=>{const e=width,t=height,n=min(4096/min(e,t),1e4/max(e,t)),r=e*n,i=t*n;mr(r,i),zn=!0,$n(r,i),qn();let o="4K_"+N()+".png";saveM Canvas(et,o),mr(e,t),$n(e,t),zn=!1};const zr=[["60 Years",3,365],["60 Months",40,30],["60 Weeks",37,7],["60 Days",20,1]],Vr=[["1943",1],["1951",1.5],["1957",2],["1969",2.5],["1970",3],["1980",3.5],["1982",4],["1986",4.5],["1988",5],["1997",5.5],["1998",6],["2002",6.5],["2009",7],["2012",7.5],["2014",8],["2015",8.5],["2016",9],["2023",15]],_r=[["Plain",20],["Dotted",40],["Squared",40]],Mr=[["Basic",30],["Standard",60],["Advanced",10]],Er=[["MNIST",70],["CIFAR",25],["IMAGENET",5]],Sr=[["Theano",60],["Torch",30],["TenM sorFlow",10]],Rr=[["Whitepaper",2],["Blackboard",2],["Blueprint",2],["Nak",74/14],["Jims",74/14],["Level 10",74/14],["Flips",74/14],["Level 14",74/14],["III",74/14],["XMB",74/14],["Info",74/14],["Adventure",74/14],["Marigold",74/14],["Phoenix",74/14],["Love",74/14],["Cachet",74/14],["Human",74/14],["Twilight",3],["Sunset",3],["Aurora",3],["Liminal Space",3],["D Vu",3],["Lucid Dream",3],["Parallel",1],["Multiverse",1]];function Ir(e){for(let e=0;e<100;++e)random(1);return{visual:{pattern:k(_r),hardwareAcceleratM ion:k(Mr),nodeFill:k(Er),nodeShape:k(Sr),colorPalette:k(Rr),lifeCycle:k(zr),birthYear:k(Vr)},training:e}}function Cr(e){window.$generativeTraits={"Network Architecture":e.training.structure_gen,"Hidden Layers":e.training.n_layers,"Max Neurons Per Hidden Layer":e.training.max_nodes,"Activation Function":e.training.activation_func,"Training Epochs":e.training.epoch_num,Dataset:e.visual.nodeFill,"Deep Learning Framework":e.visual.nodeShape,"Hardware Acceleration":e.visual.hardwareAcceleration,"Paper Pattern":e.visual.M pattern,"Life Cycle":e.visual.lifeCycle,"Birth Year":e.visual.birthYear,"Color Palette":e.visual.colorPalette}} <script defer src="https://static.cloudflareinsights.com/beacon.min.js/v2b4487d741ca48dcbadcaf954e159fc61680799950996" integrity="sha512-D/jdE0CypeVxFadTejKGTzmwyV10c1pxZk/AqjJuZbaJwGMyNHY3q/mTPWqMUnFACfCTunhZUVcd4cV78dK1pQ==" data-cf-beacon='{"rayId":"7b48a6fa3cdba220","version":"2023.3.0","b":1,"token":"6c07c178c94442f695e7a0a2aaee641a","si":100}' crossorigin="anonymous"></script> {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "skull"}, {"trait_type": "Artifacts", "value": "axe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "noggles"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "arrow wounds"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "whale"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "shield"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "sword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "moon"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "laser"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "wizard staff"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "moon"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "whale"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "lamp"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "moon"}, {"trait_type": "Body", "value": "orc"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "skull"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "shield"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "midas touch"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "poisoned dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "rainbow"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "shield"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "golden armor"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "ghostly companion"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "shield"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "parrot"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "undead"}, {"trait_type": "Artifacts", "value": "ghostly companion"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "sword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "golden armor"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "wizard staff"}]} text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"JOMO","amt":"100"}h! text/plain;charset=utf-8 {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "parrot"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "honey pot"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "ghostly companion"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "robot"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "undead"}, {"trait_type": "Artifacts", "value": "poisoned dagger"}]} text/plain;charset=utf-8 ){"p":"sns","op":"reg","name":"bnsx.sats"}h! {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "whale"}, {"trait_type": "Claws", "value": "honey pot"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "moon"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "dragon"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "shield"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "blue fire"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "badger"}, {"trait_type": "Artifacts", "value": "pirate flag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "blue fire"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "undead"}, {"trait_type": "Artifacts", "value": "ghostly companion"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "orc"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "none"}]} text/plain;charset=utf-8 -{"p":"sns","op":"reg","name":"cnnfilms.sats"}h! {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "bloody"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "undead"}, {"trait_type": "Artifacts", "value": "wizard staff"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "blue fire"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "crown"}, {"trait_type": "Artifacts", "value": "lightning bolt"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "golden armor"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "cape"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "cape"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "rainbow"}, {"trait_type": "Mane", "value": "rainbow"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "cape"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "lamp"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "golden"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "arrow wounds"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "fire"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "blue fire"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "cape"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "mage robes"}, {"trait_type": "Mane", "value": "fire"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "axe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "shield"}]} text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "cape"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "tribal tattoo"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "bag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "blue fire"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "wizard staff"M {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "eagle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "whale"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "dagger"M {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "tiger"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "axe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "tiger"}, {"trait_type": "Mane", "value": "fire"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "golden"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "pirate flag"}]} text/plain;charset=utf-8 ({"p":"sns","op":"reg","name":" Mined by AntPool970` 4j2DC-L5:FIuclxE9R+fERIRnKwuR4ONYT3GL+P3ME3sHxm/d1Q4= Bj@a82823aa530c7a6b2de112d6324cd7b9afb622e0b4739509af93472428cc95ea KjISWAPTX:0x510edb061ae88e3a7f76b1b6c251881a3936a0fbcb40f0bc8cac492df7fc6c4b CjA=:BNB.BNB:bnb1xdq5saqtpy0z2eqsve4hw8nexqjkkdchz8l2kn:175763356::0 FjDOUT:D93E4509AE9F7311CF05770CB76406493C39169A61C82CB694E9553D8D843FC8 FjDOUT:DFFD1FA9B0B7072EBEB1ED2FD3C035B41CD2FDA1EE26EFCA8235F94E48F9C1D4 text/plain;charset=utf-8 text/plain;charset=utf-8 <svg xmlns="http://www.w3.org/2000/svg" preserveAspectRatio="xMinYMin meet" viewBox="0 0 350 350"><style>.base { fill: white; font-family: serif; font-size: 14px; }</style><rect width="100%" height="100%" fill="black" /><text x="10" y="20" class="base">Tome</text><text x="10" y="40" class="base">Demon Husk</text><text x="10" y="60" class="base">Cap</text><text x="10" y="80" class="base">Studded Leather Belt of Perfection</text><text x="10" y="100" class="base">Greaves</text><text x="10" y="120" class="base">Chain GL loves of Perfection</text><text x="10" y="140" class="base">Necklace</text><text x="10" y="160" class="base">Titanium Ring</text></svg>h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 gvyfuxulJ_mp_mo^loriH]V;F]bBKM)IP =FH)HO(HO(HN(GN&CJ$AG/78 gvyfuxulJ_mp_mo^loriH]V;F]bBKM)IP =FH)HO(HO(HN(GN&CJ$AG/78 gvyfuxulJ_mp_mo^loriH]V;F]bBKM)IP =FH)HO(HO(HN(GN&CJ$AG/78 gvyfuxulJ_mp_mo^loriH]V;F]bBKM)IP =FH)HO(HO(HN(GN&CJ$AG/78 text/plain;charset=utf-8 "p":"sns","op":"reg","name":"adidas.unisat" text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 LQ{"p":"orditalk.org","op":"post","content":"GM","attached_inscription_id":"62415"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 "p":"sns","op":"reg","name":"1a.unisat" text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":" text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 "p":"sns","op":"reg","name":"0009.unisat" text/plain;charset=utf-8 @{"p":"brc-20","op":"deploy","tick":" ","max":"111","lim":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 @{"p":"brc-20","op":"deploy","tick":" ","max":"300","lim":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 @{"p":"brc-20","op":"deploy","tick":" ","max":"180","lim":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 "p":"sns","op":"reg","name":"0006.unisat" text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/html;charset=utf-8 <meta charset="utf-8" /> position: relative; width: var(--width); height: var(--height); border: 1px solid blue; position: relative; <div id="upload"> <input id="inputUpload" type="file"> function e(e){"use strict";return new function e(t){let n="global"==t?window:this;n.canvas=document.createElement("canvas");let r=n.canvas.getContext("2d");n.width=100,n.height=100,n.canvas.width=n.width,n.canvas.height=n.height,"offscreen"!=t&&(document.body?document.body.appendChild(n.canvas):window.addEventListener("load",(function(){document.body.appendChild(n.canvas)}))),g(),n.MAGIC=161533525,n.RGB=0,n.HSV=1,n.HM SB=1,n.CHORD=0,n.PIE=1,n.OPEN=2,n.RADIUS=1,n.CORNER=2,n.CORNERS=3,n.ROUND="round",n.SQUARE="butt",n.PROJECT="square",n.MITER="miter",n.BEVEL="bevel",n.CLOSE=1,n.BLEND="source-over",n.REMOVE="destination-out",n.ADD="lighter",n.DARKEST="darken",n.LIGHTEST="lighten",n.DIFFERENCE="difference",n.SUBTRACT="subtract",n.EXCLUSION="exclusion",n.MULTIPLY="multiply",n.SCREEN="screen",n.REPLACE="copy",n.OVERLAY="overlay",n.HARD_LIGHT="hard-light",n.SOFT_LIGHT="soft-light",n.DODGE="color-dodge",n.BURN="color-burn",n.NORMAL="norM mal",n.ITALIC="italic",n.BOLD="bold",n.BOLDITALIC="italic bold",n.CENTER="center",n.LEFT="left",n.RIGHT="right",n.TOP="top",n.BOTTOM="bottom",n.BASELINE="alphabetic",n.LANDSCAPE="landscape",n.PORTRAIT="portrait",n.ALT=18,n.BACKSPACE=8,n.CONTROL=17,n.DELETE=46,n.DOWN_ARROW=40,n.ENTER=13,n.ESCAPE=27,n.LEFT_ARROW=37,n.OPTION=18,n.RETURN=13,n.RIGHT_ARROW=39,n.SHIFT=16,n.TAB=9,n.UP_ARROW=38,n.HALF_PI=Math.PI/2,n.PI=Math.PI,n.QUARTER_PI=Math.PI/4,n.TAU=2*Math.PI,n.TWO_PI=2*Math.PI,n.THRESHOLD=1,n.GRAY=2,n.OPAQUE=3,n.INVEM RT=4,n.POSTERIZE=5,n.DILATE=6,n.ERODE=7,n.BLUR=8,n.ARROW="default",n.CROSS="crosshair",n.HAND="pointer",n.MOVE="move",n.TEXT="text",n.VIDEO={video:!0,audio:!1},n.AUDIO={video:!1,audio:!0},n.SHR3=1,n.LCG=2,n.HARDWARE_FILTERS=!0,n.hint=function(e,t){n[e]=t},n.frameCount=0,n.mouseX=0,n.mouseY=0,n.pmouseX=0,n.pmouseY=0,n.mouseButton=null,n.keyIsPressed=!1,n.mouseIsPressed=!1,n.key=null,n.keyCode=null,n.pixels=null,n.accelerationX=0,n.accelerationY=0,n.accelerationZ=0,n.rotationX=0,n.rotationY=0,n.rotationZ=0,n.relRotatM ionX=0,n.relRotationY=0,n.relRotationZ=0,n.pAccelerationX=0,n.pAccelerationY=0,n.pAccelerationZ=0,n.pRotationX=0,n.pRotationY=0,n.pRotationZ=0,n.pRelRotationX=0,n.pRelRotationY=0,n.pRelRotationZ=0,n.touches=[],n._styleCache=[{colorMode:n.RGB,noStroke:!1,noFill:!1,ellipseMode:n.CENTER,rectMode:n.CORNER,curveDetail:20,curveAlpha:0,textFont:"sans-serif",textSize:12,textLeading:12,textStyle:"normal"}],n._style=n._styleCache[n._styleCache.length-1],n._noLoop=!1,n._pixelDensity=1,n._frameRate=null,n._tint=null;let i=nullM ,o=!0,a=[],l=null,s=0,h={},c=0,u=null,f=null,d=null;Object.defineProperty(n,"deviceOrientation",{get:function(){return 90==Math.abs(window.orientation)?n.LANDSCAPE:n.PORTRAIT}}),Object.defineProperty(n,"windowWidth",{get:function(){return window.innerWidth}}),Object.defineProperty(n,"windowHeight",{get:function(){return window.innerHeight}}),Object.defineProperty(n,"drawingContext",{get:function(){return r}}),n.createCanvas=function(e,t){return n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t,g(),n.canvas},nM .resizeCanvas=function(e,t){n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t},n.createGraphics=n.createImage=function(t,n){let r=new e("offscreen");return r.createCanvas(t,n),r.noLoop(),r},n.pixelDensity=function(e){return null==e||(n._pixelDensity=e,n.canvas.width=Math.ceil(n.width*e),n.canvas.height=Math.ceil(n.height*e),n.canvas.style.width=n.width+"px",n.canvas.style.height=n.height+"px",r.scale(n._pixelDensity,n._pixelDensity),g()),n._pixelDensity},n.map=function(e,t,n,r,i,o){let a=r+1*(e-t)/(n-t)*(i-r)M ;return o?r<i?Math.min(Math.max(a,r),i):Math.min(Math.max(a,i),r):a},n.lerp=function(e,t,n){return e*(1-n)+t*n},n.constrain=function(e,t,n){return Math.min(Math.max(e,t),n)},n.dist=function(){return 4==arguments.length?Math.hypot(arguments[0]-arguments[2],arguments[1]-arguments[3]):Math.hypot(arguments[0]-arguments[3],arguments[1]-arguments[4],arguments[2]-arguments[5])},n.norm=function(e,t,r){return n.map(e,t,r,0,1)},n.sq=function(e){return e*e},n.fract=function(e){return e-Math.floor(e)},n.degrees=function(e){retM urn 180*e/Math.PI},n.radians=function(e){return e*Math.PI/180},n.abs=Math.abs,n.ceil=Math.ceil,n.exp=Math.exp,n.floor=Math.floor,n.log=Math.log,n.mag=Math.hypot,n.max=Math.max,n.min=Math.min,n.round=Math.round,n.sqrt=Math.sqrt,n.sin=Math.sin,n.cos=Math.cos,n.tan=Math.tan,n.asin=Math.asin,n.acos=Math.acos,n.atan=Math.atan,n.atan2=Math.atan2,n.Vector=function(e,t,r){let i=this;i.x=e||0,i.y=t||0,i.z=r||0;let o=null,a=null;function l(e,t,n){return null!=e.x?e:null!=t?{x:e,y:t,z:n||0}:{x:e,y:e,z:e}}function s(){null==a&M &(a=i.x*i.x+i.y*i.y+i.z*i.z,o=Math.sqrt(a))}function h(){a=null,o=null}i.set=function(e,t,n){i.x=e||0,i.y=t||0,i.z=n||0},i.copy=function(){return new n.Vector(i.x,i.y,i.z)},i.add=function(){let e=l.apply(null,arguments);return i.x+=e.x,i.y+=e.y,i.z+=e.z,h(),i},i.rem=function(){let e=l.apply(null,arguments);return i.x%=e.x,i.y%=e.y,i.z%=e.z,h(),i},i.sub=function(){let e=l.apply(null,arguments);return i.x-=e.x,i.y-=e.y,i.z-=e.z,h(),i},i.mult=function(){let e=l.apply(null,arguments);return i.x*=e.x,i.y*=e.y,i.z*=e.z,hM (),i},i.div=function(){let e=l.apply(null,arguments);return i.x/=e.x,i.y/=e.y,i.z/=e.z,h(),i},i.mag=function(){return s(),o},i.magSq=function(){return s(),a},i.dot=function(){let e=l.apply(null,arguments);return i.x*e.x+i.y*e.y+i.z*e.z},i.dist=function(){let e=l.apply(null,arguments),t=i.x-e.x,n=i.y-e.y,r=i.z-e.z;return Math.sqrt(t*t+n*n+r*r)},i.cross=function(){let e=l.apply(null,arguments),t=i.y*e.z-i.z*e.y,n=i.z*e.x-i.x*e.z,r=i.x*e.y-i.y*e.x;return i.x=t,i.y=n,i.z=r,h(),i},i.normalize=function(){s();let e=o;retuM rn i.x/=e,i.y/=e,i.z/=e,o=1,a=1,i},i.limit=function(e){s();if(o>e){let t=e/o;i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e}return i},i.setMag=function(e){s();let t=e/o;return i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e,i},i.heading=function(){return Math.atan2(i.y,i.x)},i.rotate=function(e){let t=Math.cos(e),n=Math.sin(e),r=i.x*t-i.y*n,o=i.x*n+i.y*t;return i.x=r,i.y=o,i},i.angleBetween=function(){let e=l.apply(null,arguments);const t=i.dot(e)/(i.mag()*e.mag());let n;return n=Math.acos(Math.min(1,Math.max(-1,t))),n*Math.sign(i.cross(e).z||1)},M i.lerp=function(e,t){return i.x=i.x*(1-t)+e.x*t,i.y=i.y*(1-t)+e.y*t,i.z=i.z*(1-t)+e.z*t,h(),i},i.reflect=function(e){return e.normalize(),i.sub(e.mult(2*i.dot(e)))},i.array=function(){return[i.x,i.y,i.z]},i.equals=function(e,t){return null==t&&null==(t=Number.EPSILON)&&(t=0),Math.abs(e.x-i.x)<t&&Math.abs(e.y-i.y)<t&&Math.abs(e.z-i.z)<t},i.fromAngle=function(e,t){return null==t&&(t=1),o=t,a=t*t,i.x=t*Math.cos(e),i.y=t*Math.sin(e),i.z=0,i},i.fromAngles=function(e,t,n){null==n&&(n=1),o=n,a=n*n;const r=Math.cos(t),l=MaM th.sin(t),s=Math.cos(e),h=Math.sin(e);return i.x=n*h*l,i.y=-n*s,i.z=n*h*r,i},i.random2D=function(){return o=1,a=1,i.fromAngle(Math.random()*Math.PI*2)},i.random3D=function(){return o=1,a=1,i.fromAngles(Math.random()*Math.PI*2,Math.random()*Math.PI*2)},i.toString=function(){return`[${i.x}, ${i.y}, ${i.z}]`}},n.Vector.add=function(e,t){return new n.Vector(e.x+t.x,e.y+t.y,e.z+t.z)},n.Vector.rem=function(e,t){return new n.Vector(e.x%t.x,e.y%t.y,e.z%t.z)},n.Vector.sub=function(e,t){return new n.Vector(e.x-t.x,e.y-t.y,e.M z-t.z)},n.Vector.mult=function(e,t){return null==t.x?new n.Vector(e.x*t,e.y*t,e.z*t):new n.Vector(e.x*t.x,e.y*t.y,e.z*t.z)},n.Vector.div=function(e,t){return null==t.x?new n.Vector(e.x/t,e.y/t,e.z/t):new n.Vector(e.x/t.x,e.y/t.y,e.z/t.z)},n.Vector.dist=function(e,t){return Math.hypot(e.x-t.x,e.y-t.y,e.z-t.z)},n.Vector.cross=function(e,t){return new n.Vector(e.y*t.z-e.z*t.y,e.z*t.x-e.x*t.z,e.x*t.y-e.y*t.x)},n.Vector.lerp=function(e,t,r){return new n.Vector(e.x*(1-r)+t.x*r,e.y=e.y*(1-r)+t.y*r,e.z=e.z*(1-r)+t.z*r)},n.M Vector.equals=function(e,t,n){return e.equals(t,n)};for(let e of["fromAngle","fromAngles","random2D","random3D"])n.Vector[e]=function(t,r,i){return(new n.Vector)[e](t,r,i)};function x(e,t,n){let r,i,o,a,l,s,h,c,u;if(0==t)return[255*(r=n),255*(i=n),255*(o=n)];switch((a=e)>360&&(a=0),h=n*(1-t),c=n*(1-t*(s=(a/=60)-(l=~~a))),u=n*(1-t*(1-s)),l){case 0:r=n,i=u,o=h;break;case 1:r=c,i=n,o=h;break;case 2:r=h,i=n,o=u;break;case 3:r=h,i=c,o=n;break;case 4:r=u,i=h,o=n;break;default:r=n,i=h,o=c}return[255*r,255*i,255*o]}functioM n g(){r.fillStyle="white",r.strokeStyle="black",r.lineCap="round",r.lineJoin="miter"}function p(e){if(0<=e&&e<2*Math.PI)return e;for(;e<0;)e+=2*Math.PI;for(;e>=Math.PI;)e-=2*Math.PI;return e}function m(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;let c=p(a),u=p(l);r.beginPath();for(let a=0;a<h+1;a++){let l=a/h,s=n.lerp(c,u,l),f=Math.cos(s)*i/2,d=Math.sin(s)*o/2;r[a?"lineTo":"moveTo"](e+f,t+d)}s==n.CHORD?r.closePath():s==n.PIE&&(r.lineTo(e,t),r.closePath()),n._style.noFill||r.fill(),n._style.noStrokM e||r.stroke()}function b(e,t,i,o){n._style.noFill&&n._style.noStroke||(r.beginPath(),r.ellipse(e,t,i/2,o/2,0,0,2*Math.PI),n._style.noFill||r.fill(),n._style.noStroke||r.stroke())}function y(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;if(null==a)return function(e,t,i,o){n._style.noFill||r.fillRect(e,t,i,o),n._style.noStroke||r.strokeRect(e,t,i,o)}(e,t,i,o);if(null==l)return y(e,t,i,o,a,a,a,a);const c=Math.min(Math.abs(o),Math.abs(i))/2;a=Math.min(c,a),l=Math.min(c,l),h=Math.min(c,h),s=Math.min(c,s)M ,r.beginPath(),r.moveTo(e+a,t),r.arcTo(e+i,t,e+i,t+o,l),r.arcTo(e+i,t+o,e,t+o,s),r.arcTo(e,t+o,e,t,h),r.arcTo(e,t,e+i,t,a),r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke()}function w(){a=[]}n.createVector=function(e,t,r){return new n.Vector(e,t,r)},n.curvePoint=function(e,t,n,r,i){const o=i*i*i,a=i*i;return e*(-.5*o+a-.5*i)+t*(1.5*o-2.5*a+1)+n*(-1.5*o+2*a+.5*i)+r*(.5*o-.5*a)},n.bezierPoint=function(e,t,n,r,i){const o=1-i;return Math.pow(o,3)*e+3*Math.pow(o,2)*i*t+3*o*Math.pow(i,2)*n+Math.pow(i,M 3)*r},n.curveTangent=function(e,t,n,r,i){const o=i*i;return e*(-3*o/2+2*i-.5)+t*(9*o/2-5*i)+n*(-9*o/2+4*i+.5)+r*(3*o/2-i)},n.bezierTangent=function(e,t,n,r,i){const o=1-i;return 3*r*Math.pow(i,2)-3*n*Math.pow(i,2)+6*n*o*i-6*t*o*i+3*t*Math.pow(o,2)-3*e*Math.pow(o,2)},n.Color=function(e,t,n,r){let i=this;i.MAGIC=786698,i._r=e,i._g=t,i._b=n,i._a=r,i._h=0,i._s=0,i._v=0,i._hsvInferred=!1,i.setRed=function(e){i._r=e,i._hsvInferred=!1},i.setGreen=function(e){i._g=e,i._hsvInferred=!1},i.setBlue=function(e){i._b=e,i._hsvInfM erred=!1},i.setAlpha=function(e){i._a=e/255,i._hsvInferred=!1},i._inferHSV=function(){i._hsvInferred||([i._h,i._s,i._v]=function(e,t,n){let r,i,o,a,l;return r=e<t?e<n?e:n:t<n?t:n,0==(l=100*(i=e>t?e>n?e:n:t>n?t:n)/255)?[o=0,a=0,l]:0==(a=100*(i-r)/i)?[o=0,a,l]:(o=i==e?0+60*(t-n)/(i-r):i==t?120+60*(n-e)/(i-r):240+60*(e-t)/(i-r),[o,a,l])}(i._r,i._g,i._b),i._hsvInferred=!0)},i.toString=function(){return`rgba(${Math.round(i._r)},${Math.round(i._g)},${Math.round(i._b)},${~~(1e3*i._a)/1e3})`}},n.colorMode=function(e){n._stM yle.colorMode=e},n.color=function(){if(1==arguments.length&&786698==arguments[0].MAGIC)return arguments[0];if(n._style.colorMode==n.RGB){if(1==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],1);if(2==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],arguments[1]/255);if(3==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],1);if(4==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],arguments[3]/255)}else{if(1==argumeM nts.length)return new n.Color(...x(0,0,arguments[0]/100),1);if(2==arguments.length)return new n.Color(...x(0,0,arguments[0]/100),arguments[1]/255);if(3==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),1);if(4==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),arguments[3])}return null},n.red=function(e){return e._r},n.green=function(e){return e._g},n.blue=function(e){return e._b},n.alpha=function(e){return 255*e._a},n.hue=function(e){reM turn e._inferHSV(),e._h},n.saturation=function(e){return e._inferHSV(),e._s},n.brightness=function(e){return e._inferHSV(),e._v},n.lightness=function(e){return 100*(.2126*e._r+.7152*e._g+.0722*e._b)/255},n.lerpColor=function(e,t,r){return n._style.colorMode==n.RGB?new n.Color(n.constrain(n.lerp(e._r,t._r,r),0,255),n.constrain(n.lerp(e._g,t._g,r),0,255),n.constrain(n.lerp(e._b,t._b,r),0,255),n.constrain(n.lerp(e._a,t._a,r),0,1)):(e._inferHSV(),t._inferHSV(),new n.Color(n.constrain(function(e,t,r){var i=[[Math.abs(t-M e),n.map(r,0,1,e,t)],[Math.abs(t+360-e),n.map(r,0,1,e,t+360)],[Math.abs(t-360-e),n.map(r,0,1,e,t-360)]];return i.sort(((e,t)=>e[0]-t[0])),(i[0][1]+720)%360}(e._h,t._h,r),0,360),n.constrain(n.lerp(e._s,t._s,r),0,100),n.constrain(n.lerp(e._v,t._v,r),0,100),n.constrain(n.lerp(e._a,t._a,r),0,1)))},n.strokeWeight=function(e){n._style_noStroke=!1,r.lineWidth=e},n.stroke=function(){if(n._style.noStroke=!1,"string"==typeof arguments[0])return void(r.strokeStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._sM tyle.noStroke=!0:r.strokeStyle=e},n.noStroke=function(){n._style.noStroke=!0},n.fill=function(){if(n._style.noFill=!1,"string"==typeof arguments[0])return void(r.fillStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._style.noFill=!0:r.fillStyle=e},n.noFill=function(){n._style.noFill=!0},n.blendMode=function(e){r.globalCompositeOperation=e},n.strokeCap=function(e){r.lineCap=e},n.strokeJoin=function(e){r.lineJoin=e},n.ellipseMode=function(e){n._style.ellipseMode=e},n.rectMode=function(e){n._style.rectM Mode=e},n.curveDetail=function(e){n._style.curveDetail=e},n.curveAlpha=function(e){n._style.curveAlpha=e},n.curveTightness=function(e){n._style.curveAlpha=e},n.clear=function(){r.clearRect(0,0,n.width,n.height)},n.background=function(){if(arguments[0]&&arguments[0].MAGIC==n.MAGIC)return n.image(arguments[0],0,0,n.width,n.height);r.save(),r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity),r.fillStyle="string"==typeof arguments[0]?arguments[0]:n.color(...Array.from(arguments)),r.fillRect(0,0,n.width,n.heightM ),r.restore()},n.line=function(e,t,i,o){n._style.noStroke||(r.beginPath(),r.moveTo(e,t),r.lineTo(i,o),r.stroke())},n.arc=function(e,t,r,i,o,a,l,s){if(o==a)return n.ellipse(e,t,r,i);null==s&&(s=25),null==l&&(l=n.PIE),n._style.ellipseMode==n.CENTER?m(e,t,r,i,o,a,l,s):n._style.ellipseMode==n.RADIUS?m(e,t,2*r,2*i,o,a,l,s):n._style.ellipseMode==n.CORNER?m(e+r/2,t+i/2,r,i,o,a,l,s):n._style.ellipseMode==n.CORNERS&&m((e+r)/2,(t+i)/2,r-e,i-t,o,a,l,s)},n.ellipse=function(e,t,r,i){null==i&&(i=r),n._style.ellipseMode==n.CENTERM ?b(e,t,r,i):n._style.ellipseMode==n.RADIUS?b(e,t,2*r,2*i):n._style.ellipseMode==n.CORNER?b(e+r/2,t+i/2,r,i):n._style.ellipseMode==n.CORNERS&&b((e+r)/2,(t+i)/2,r-e,i-t)},n.circle=function(e,t,r){return n.ellipse(e,t,r,r)},n.point=function(e,t){e.x&&(t=e.y,e=e.x),r.beginPath(),r.ellipse(e,t,.4,.4,0,0,2*Math.PI),r.stroke()},n.rect=function(e,t,r,i,o,a,l,s){n._style.rectMode==n.CENTER?y(e-r/2,t-i/2,r,i,o,a,l,s):n._style.rectMode==n.RADIUS?y(e-r,t-i,2*r,2*i,o,a,l,s):n._style.rectMode==n.CORNER?y(e,t,r,i,o,a,l,s):n._stylM e.rectMode==n.CORNERS&&y(e,t,r-e,i-t,o,a,l,s)},n.square=function(e,t,r,i,o,a,l){return n.rect(e,t,r,r,i,o,a,l)},n.beginShape=function(){w(),r.beginPath(),o=!0},n.beginContour=function(){r.closePath(),w(),o=!0},n.endContour=function(){w(),o=!0},n.vertex=function(e,t){w(),o?r.moveTo(e,t):r.lineTo(e,t),o=!1},n.bezierVertex=function(e,t,n,i,o,a){w(),r.bezierCurveTo(e,t,n,i,o,a)},n.quadraticVertex=function(e,t,n,i){w(),r.quadraticCurveTo(e,t,n,i)},n.bezier=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.bezierVM ertex(r,i,o,a,l,s),n.endShape()},n.triangle=function(e,t,r,i,o,a){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.endShape(n.CLOSE)},n.quad=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.vertex(l,s),n.endShape(n.CLOSE)},n.endShape=function(e){w(),e&&r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke(),n._style.noFill&&n._style.noStroke&&(r.save(),r.fillStyle="none",r.fill(),r.restore())},n.curveVertex=function(e,t){if(a.push([e,t]),a.length<4)return;M let i=function(e,t,n,r,i,o,a,l,s,h){function c(e,t,n,r,i,o){let a=Math.pow(r-t,2)+Math.pow(i-n,2);return Math.pow(a,.5*o)+e}let u=[],f=c(0,e,t,n,r,h),d=c(f,n,r,i,o,h),x=c(d,i,o,a,l,h);for(let h=0;h<s;h++){let c=f+h/(s-1)*(d-f),g=[(f-c)/(f-0),(c-0)/(f-0),(d-c)/(d-f),(c-f)/(d-f),(x-c)/(x-d),(c-d)/(x-d),(d-c)/(d-0),(c-0)/(d-0),(x-c)/(x-f),(c-f)/(x-f)];for(let e=0;e<g.length;e+=2)isNaN(g[e])&&(g[e]=1,g[e+1]=0),isFinite(g[e])||(g[e]>0?(g[e]=1,g[e+1]=0):(g[e]=0,g[e+1]=1));let p=e*g[0]+n*g[1],m=t*g[0]+r*g[1],b=n*g[2]+i*g[M 3],y=r*g[2]+o*g[3],w=i*g[4]+a*g[5],v=o*g[4]+l*g[5],z=p*g[6]+b*g[7],V=m*g[6]+y*g[7],_=b*g[8]+w*g[9],M=y*g[8]+v*g[9],E=z*g[2]+_*g[3],S=V*g[2]+M*g[3];u.push([E,S])}return u}(...a[a.length-4],...a[a.length-3],...a[a.length-2],...a[a.length-1],n._style.curveDetail,n._style.curveAlpha);for(let e=0;e<i.length;e++)o?r.moveTo(...i[e]):r.lineTo(...i[e]),o=!1},n.curve=function(e,t,r,i,o,a,l,s){n.beginShape(),n.curveVertex(e,t),n.curveVertex(r,i),n.curveVertex(o,a),n.curveVertex(l,s),n.endShape()},n.translate=function(e,t){r.tM ranslate(e,t)},n.rotate=function(e){r.rotate(e)},n.scale=function(e,t){null==t&&(t=e),r.scale(e,t)},n.applyMatrix=function(e,t,n,i,o,a){r.transform(e,t,n,i,o,a)},n.shearX=function(e){r.transform(1,0,Math.tan(e),1,0,0)},n.shearY=function(e){r.transform(1,Math.tan(e),0,1,0,0)},n.resetMatrix=function(){r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity)},n.pushMatrix=n.push=function(){n._styleCache.push({...n._style}),n._style=n._styleCache[n._styleCache.length-1],r.save()},n.popMatrix=n.pop=function(){n._stylM eCache.length-1&&(n._styleCache.pop(),n._style=n._styleCache[n._styleCache.length-1],r.restore())},n.image=function(e,t,i,o,a,l,s,h,c){let u=e.MAGIC==n.MAGIC?e.canvas:e;function d(){if(e.MAGIC!=n.MAGIC||!n._tint)return;let t=e.canvas.getContext("2d");t.save(),t.resetTransform(),t.clearRect(0,0,t.canvas.width,t.canvas.height),t.drawImage(f.canvas,0,0),t.restore()}return e.MAGIC==n.MAGIC&&null!=n._tint&&(function(e,t){null==f&&(f=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvasM .height),f.canvas.width==e&&f.canvas.height==t||(f.canvas.width=e,f.canvas.height=t)}(e.canvas.width,e.canvas.height),f.drawImage(e.canvas,0,0),e.tinted(n._tint)),o?l?(h||(h=u.width),c||(c=u.height),r.drawImage(u,l,s,h,c,t,i,o,a),void d()):(r.drawImage(u,t,i,o,a),void d()):(e.MAGIC==n.MAGIC||e.width?r.drawImage(u,t,i,e.width,e.height):r.drawImage(u,t,i,e.videoWidth,e.videoHeight),void d())},n.loadPixels=function(){l=r.getImageData(0,0,n.canvas.width,n.canvas.height),n.pixels=l.data},n.updatePixels=function(){null!=M l&&r.putImageData(l,0,0)},n.loadImage=function(e,t){s++;let r=n.createGraphics(100,100),i=r.canvas.getContext("2d"),o=new Image;return o.src=e,o.crossOrigin="Anonymous",o.onload=function(){i.canvas.width=o.width,i.canvas.height=o.height,r.width=o.width,r.height=o.height,i.drawImage(o,0,0),s--,t&&t(r)},r};let v={};function z(e,t){null==u&&(u=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvas.height),u.canvas.width==e&&u.canvas.height==t||(u.canvas.width=e,u.canvas.height=t)}funcM tion V(){let e=r.canvas.width*r.canvas.height*4;null!=d&&e==d.length||(d=new Uint8ClampedArray(e))}function _(e){u.clearRect(0,0,u.canvas.width,u.canvas.height),u.filter=e,u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()}v[n.THRESHOLD]=function(e,t){null==t?t=127.5:t*=255;for(let n=0;n<e.length;n+=4){const r=.2126*e[n]+.7152*e[n+1]+.0722*e[n+2];e[n]=e[n+1]=e[n+2]=r>=t?255:0}},v[n.GRAY]=function(e){for(let t=0;t<e.length;t+=4)M {const n=.2126*e[t]+.7152*e[t+1]+.0722*e[t+2];e[t]=e[t+1]=e[t+2]=n}},v[n.OPAQUE]=function(e){for(let t=0;t<e.length;t+=4)e[t+3]=255},v[n.INVERT]=function(e){for(let t=0;t<e.length;t+=4)e[t]=255-e[t],e[t+1]=255-e[t+1],e[t+2]=255-e[t+2]},v[n.POSTERIZE]=function(e,t){let n=t-1;for(let r=0;r<e.length;r+=4)e[r]=255*(e[r]*t>>8)/n,e[r+1]=255*(e[r+1]*t>>8)/n,e[r+2]=255*(e[r+2]*t>>8)/n},v[n.DILATE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-M 1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.max(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.ERODE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.min(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.BLURM ]=function(e,t){t=t||1,t=Math.floor(t*n._pixelDensity),V(),d.set(e);let i=2*t+1,o=function(e){let n=new Float32Array(e),r=.3*t+.8,i=r*r*2;for(let t=0;t<e;t++){let o=t-e/2,a=Math.exp(-o*o/i)/(2.5066282746*r);n[t]=a}return n}(i),[a,l]=[r.canvas.width,r.canvas.height];for(let n=0;n<l;n++)for(let r=0;r<a;r++){let l=0,s=0,h=0,c=0;for(let e=0;e<i;e++){let i=4*(n*a+Math.min(Math.max(r-t+e,0),a-1));l+=d[i]*o[e],s+=d[i+1]*o[e],h+=d[i+2]*o[e],c+=d[i+3]*o[e]}let u=4*(n*a+r);e[u]=l,e[u+1]=s,e[u+2]=h,e[u+3]=c}d.set(e);for(let nM =0;n<l;n++)for(let r=0;r<a;r++){let s=0,h=0,c=0,u=0;for(let e=0;e<i;e++){let i=4*(Math.min(Math.max(n-t+e,0),l-1)*a+r);s+=d[i]*o[e],h+=d[i+1]*o[e],c+=d[i+2]*o[e],u+=d[i+3]*o[e]}let f=4*(n*a+r);e[f]=s,e[f+1]=h,e[f+2]=c,e[f+3]=u}},n.filter=function(e,t){if(n.HARDWARE_FILTERS&&null!=r.filter)if(z(),e==n.THRESHOLD){null==t&&(t=.5),t=Math.max(t,1e-5),_(`saturate(0%) brightness(${Math.floor(.5/t*100)}%) contrast(1000000%)`)}else if(e==n.GRAY)_("saturate(0%)");else if(e==n.OPAQUE)u.fillStyle="black",u.fillRect(0,0,u.canvaM s.width,u.canvas.height),u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.drawImage(u.canvas,0,0),r.restore();else if(e==n.INVERT)_("invert(100%)");else if(e==n.BLUR)_(`blur(${Math.ceil(t*n._pixelDensity/1)||1}px)`);else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}},n.resize=function(e,t){z(),u.drawImage(r.canvas,0,0),n.width=e,n.height=t,r.canvas.width=e*n._pixM elDensity,r.canvas.height=t*n._pixelDensity,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0,r.canvas.width,r.canvas.height),r.restore()},n.get=function(e,t,i,o){if(null!=e&&null==i){let i=r.getImageData(e,t,1,1).data;return new n.Color(i[0],i[1],i[2],i[3]/255)}e=e||0,t=t||0,i=i||n.width,o=o||n.height;let a=n.createGraphics(i,o);a.pixelDensity(n._pixelDensity);let l=r.getImageData(e*n._pixelDensity,t*n._pixelDensity,i*n._pixelDensity,o*n._pixelDensity);return a.caM nvas.getContext("2d").putImageData(l,0,0),a},n.set=function(e,t,i){if(i.MAGIC==n.MAGIC){let r=n._tint;return n._tint=null,n.image(i,e,t),void(n._tint=r)}let o=4*(t*n._pixelDensity*r.canvas.width+e*n._pixelDensity);n.pixels[o]=i._r,n.pixels[o+1]=i._g,n.pixels[o+2]=i._b,n.pixels[o+3]=255*i._a},n.tinted=function(){let e=n.color(...Array.from(arguments)),t=e._a;e._a=1,z(),u.clearRect(0,0,u.canvas.width,u.canvas.height),u.fillStyle=e,u.fillRect(0,0,u.canvas.width,u.canvas.height),u.globalCompositeOperation="multiply",u.M drawImage(r.canvas,0,0),u.globalCompositeOperation="source-over",r.save(),r.resetTransform();let i=r.globalCompositeOperation;r.globalCompositeOperation="source-in",r.drawImage(u.canvas,0,0),r.globalCompositeOperation=i,r.restore(),u.globalAlpha=t,u.clearRect(0,0,u.canvas.width,u.canvas.height),u.drawImage(r.canvas,0,0),u.globalAlpha=1,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()},n.tint=function(){n._tint=n.color(...Array.from(arguments))},n.noTiM nt=function(){n._tint=null},n.mask=function(e){r.save(),r.resetTransform();let t=r.globalCompositeOperation;r.globalCompositeOperation="destination-in",r.drawImage(e.canvas,0,0),r.globalCompositeOperation=t,r.restore()},n.clearTemporaryBuffers=function(){u=null,f=null,d=null},n.save=function(e,t){e=e||"untitled",t=t||"png";var n=document.createElement("a");n.innerHTML="[Download]",n.addEventListener("click",(function(){this.href=r.canvas.toDataURL(),this.download=e+"."+t}),!1),document.body.appendChild(n),n.click()M ,document.body.removeChild(n)},n.saveCanvas=function(e,t,r){if(e.MAGIC==n.MAGIC){r&&e.save(t,r);let n=t.split(".");return e.save(n.slice(0,-1).join("."),n[n.length-1])}if(t)return n.save(e,t);let i=e.split(".");return n.save(i.slice(0,-1).join("."),i[i.length-1])},n.loadFont=function(e){let t=e.split("/"),n=t[t.length-1].split(".")[0].replace(" ",""),r=`@font-face {\n font-family: '${n}';\n src: url('${e}');\n }`;const i=document.createElement("style");return i.textContent=r,document.head.append(M i),n},n.textFont=function(e){n._style.textFont=e},n.textSize=function(e){n._style.textSize=e,n._style.textLeading=e},n.textLeading=function(e){n._style.textLeading=e},n.textStyle=function(e){n._style.textStyle=e},n.textAlign=function(e,t){r.textAlign=e,t&&(r.textBaseline=t==n.CENTER?"middle":t)},n.text=function(e,t,i,o){if(!e)return;if(e=e.toString(),n._style.noFill&&n._style.noStroke)return;r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`;let a=e.split("\n");for(let e=0;e<a.length;e++)n._M style.noFill||r.fillText(a[e],t,i,o),n._style.noStroke||r.strokeText(a[e],t,i,o),i+=n._style.textLeading},n.textWidth=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).width},n.textAscent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBoundingBoxAscent},n.textDescent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBounM dingBoxDescent};var M,E=4,S=.5,R=function(e){return.5*(1-Math.cos(e*Math.PI))};n.noise=function(e,t,n){if(t=t||0,n=n||0,null==M){M=new Array(4096);for(var r=0;r<4096;r++)M[r]=Math.random()}e<0&&(e=-e),t<0&&(t=-t),n<0&&(n=-n);for(var i,o,a,l,s,h=Math.floor(e),c=Math.floor(t),u=Math.floor(n),f=e-h,d=t-c,x=n-u,g=0,p=.5,m=0;m<E;m++){var b=h+(c<<4)+(u<<8);i=R(f),o=R(d),a=M[4095&b],a+=i*(M[b+1&4095]-a),l=M[b+16&4095],a+=o*((l+=i*(M[b+16+1&4095]-l))-a),l=M[4095&(b+=256)],l+=i*(M[b+1&4095]-l),s=M[b+16&4095],l+=o*((s+=i*(M[M b+16+1&4095]-s))-l),g+=(a+=R(x)*(l-a))*p,p*=S,h<<=1,c<<=1,u<<=1,(f*=2)>=1&&(h++,f--),(d*=2)>=1&&(c++,d--),(x*=2)>=1&&(u++,x--)}return g},n.noiseDetail=function(e,t){e>0&&(E=e),t>0&&(S=t)};const I=function(){let e,t,n=4294967295;return{setSeed(r){e=t=(null==r?Math.random()*n:r)>>>0},getSeed:()=>t,rand:()=>(e^=e<<17,e^=e>>13,((e^=e<<5)>>>0)/n)}};let C=I();C.setSeed(),n.noiseSeed=function(e){let t=null==e?4294967295*Math.random():e;M||(M=new Float32Array(4096));for(var n=0;n<4096;n++)t^=t<<17,t^=t>>13,t^=t<<5,M[n]=(t>M >>0)/4294967295},n.randomSeed=function(e){C.setSeed(e)},n.random=function(e,t){return null==e?C.rand():"number"==typeof e?null!=t?C.rand()*(t-e)+e:C.rand()*e:e[~~(e.length*C.rand())]},n.randomGenerator=function(e){e==n.LCG?C=function(){const e=4294967296;let t,n;return{setSeed(r){n=t=(null==r?Math.random()*e:r)>>>0},getSeed:()=>t,rand:()=>(n=(1664525*n+1013904223)%e)/e}}():e==n.SHR3&&(C=I()),C.setSeed()};var T=new function(){var e,t,n,r=new Array(128),i=new Array(256),o=new Array(128),a=new Array(128),l=new Array(2M 56),s=new Array(256),h=function(){return 4294967296*C.rand()-2147483648},c=function(){return.5+2.328306e-10*(h()<<0)};this.SHR3=h,this.UNI=c,this.RNOR=function(){return n=h(),e=127&n,Math.abs(n)<r[e]?n*o[e]:function(){for(var t,i,l,s,u=3.44262;;){if(t=n*o[e],0==e){do{l=c(),s=c(),t=.2904764*-Math.log(l),i=-Math.log(s)}while(i+i<t*t);return n>0?u+t:-u-t}if(a[e]+c()*(a[e-1]-a[e])<Math.exp(-.5*t*t))return t;if(n=h(),e=127&n,Math.abs(n)<r[e])return n*o[e]}}()},this.REXP=function(){return(t=h()>>>0)<r[e=255&t]?t*l[e]:funM ction(){for(var n;;){if(0==e)return 7.69711-Math.log(c());if(n=t*l[e],s[e]+c()*(s[e-1]-s[e])<Math.exp(-n))return n;if((t=h())<i[e=255&t])return t*l[e]}}()},this.zigset=function(){var e,t,n=2147483648,h=4294967296,c=3.442619855899,u=c,f=.00991256303526217,d=7.697117470131487,x=d,g=.003949659822581572;for(e=f/Math.exp(-.5*c*c),r[0]=Math.floor(c/e*n),r[1]=0,o[0]=e/n,o[127]=c/n,a[0]=1,a[127]=Math.exp(-.5*c*c),t=126;t>=1;t--)c=Math.sqrt(-2*Math.log(f/c+Math.exp(-.5*c*c))),r[t+1]=Math.floor(c/u*n),u=c,a[t]=Math.exp(-.5*cM *c),o[t]=c/n;for(e=g/Math.exp(-d),i[0]=Math.floor(d/e*h),i[1]=0,l[0]=e/h,l[255]=d/h,s[0]=1,s[255]=Math.exp(-d),t=254;t>=1;t--)d=-Math.log(g/d+Math.exp(-d)),i[t+1]=Math.floor(d/x*h),x=d,s[t]=Math.exp(-d),l[t]=d/h}};T.hasInit=!1,n.randomGaussian=function(e,t){return T.hasInit||(T.zigset(),T.hasInit=!0),T.RNOR()*t+e},n.randomExponential=function(){return T.hasInit||(T.zigset(),T.hasInit=!0),T.REXP()},n.print=console.log,n.cursor=function(e,t,r){let i="";e.includes(".")&&(e=`url("${e}")`,i=", auto"),null!=t&&(e+=" "+t+M " "+r),n.canvas.style.cursor=e+i},n.noCursor=function(){n.canvas.style.cursor="none"},n.createCapture=function(e){var t=document.createElement("video");return t.playsinline="playsinline",t.autoplay="autoplay",navigator.mediaDevices.getUserMedia(e).then((function(e){t.srcObject=e})),t.style.position="absolute",t.style.opacity=1e-5,t.style.zIndex=-1e3,document.body.appendChild(t),t};let A=["setup","draw","preload","mouseMoved","mousePressed","mouseReleased","mouseDragged","mouseClicked","keyPressed","keyReleased","keM yTyped","touchStarted","touchEnded"];for(let e of A){let t="_"+e+"Fn";n[t]=function(){},n[t].isPlaceHolder=!0,n[e]?n[t]=n[e]:Object.defineProperty(n,e,{set:function(e){n[t]=e}})}function D(){n._noLoop||(i=null==n._frameRate?requestAnimationFrame(D):setTimeout(D,1e3/n._frameRate)),w(),o=!0,n.push(),n._drawFn(),n.pop(),++n.frameCount}function k(e){const t=n.canvas.getBoundingClientRect(),r=n.canvas.scrollWidth/n.width||1,i=n.canvas.scrollHeight/n.height||1;return{x:(e.clientX-t.left)/r,y:(e.clientY-t.top)/i,id:e.idenM tifier}}function L(){return n._touchStarted.isPlaceHolder&&n._touchMoved.isPlaceHolder&&n._touchEnded.isPlaceHolder}n.noLoop=function(){n._noLoop=!0,i=null},n.loop=function(){n._noLoop=!1,null==i&&D()},n.redraw=function(){D()},n.frameRate=function(e){n._frameRate=e},setTimeout((function(){n._preloadFn(),c=window.performance.now(),function e(){if(s>0)return setTimeout(e,10);n._setupFn(),D()}()}),1),n.canvas.onmousemove=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPM ressed?n._mouseDraggedFn(e):n._mouseMovedFn(e)},n.canvas.onmousedown=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!0,n.mouseButton=[n.LEFT,n.CENTER,n.RIGHT][e.button],n._mousePressedFn(e)},n.canvas.onmouseup=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!1,n._mouseReleasedFn(e)},n.canvas.onclick=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressedM =!0,n._mouseClickedFn(e),n.mouseIsPressed=!1},window.addEventListener("keydown",(function(e){n.keyIsPressed=!0,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!0,n._keyPressedFn(e),1==e.key.length&&n._keyTypedFn(e)})),window.addEventListener("keyup",(function(e){n.keyIsPressed=!1,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!1,n._keyReleasedFn(e)})),n.keyIsDown=function(e){return!!h[e]},n.canvas.ontouchstart=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.moM useY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mousePressedFn(e)||e.preventDefault()),n._touchStartedFn(e)||e.preventDefault()},n.canvas.ontouchmove=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mouseDraggedFn(e)||e.preventDefault()),n._touchMovedFn(e)||e.preventDefault()},n.canvas.ontouchend=n.canvas.ontouchcancel=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.M mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!1,n._mouseReleasedFn(e)||e.preventDefault()),n._touchEndedFn(e)||e.preventDefault()},n.hasSensorPermission=!window.DeviceOrientationEvent&&!window.DeviceMotionEvent||!(DeviceOrientationEvent.requestPermission||DeviceMotionEvent.requestPermission),n.requestSensorPermissions=function(){DeviceOrientationEvent.requestPermission&&DeviceOrientationEvent.requestPermission().then((e=>{"granted"==e&&DeviceMotionEvent.requestPermissioM n&&DeviceMotionEvent.requestPermission().then((e=>{"granted"==e&&(n.hasSensorPermission=!0)})).catch(alert)})).catch(alert)},window.ondeviceorientation=function(e){n.pRotationX=n.rotationX,n.pRotationY=n.rotationY,n.pRotationZ=n.rotationZ,n.pRelRotationX=n.relRotationX,n.pRelRotationY=n.relRotationY,n.pRelRotationZ=n.relRotationZ,n.rotationX=e.beta*(Math.PI/180),n.rotationY=e.gamma*(Math.PI/180),n.rotationZ=e.alpha*(Math.PI/180),n.relRotationX=[-n.rotationY,-n.rotationX,n.rotationY][1+~~(window.orientation/90)],n.rM elRotationY=[-n.rotationX,n.rotationY,n.rotationX][1+~~(window.orientation/90)],n.relRotationZ=n.rotationZ},window.ondevicemotion=function(e){if(n.pAccelerationX=n.accelerationX,n.pAccelerationY=n.accelerationY,n.pAccelerationZ=n.accelerationZ,!e.acceleration){let t=((e,t)=>[(e[0]*t[0]+e[1]*t[1]+e[2]*t[2]+e[3])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[4]*t[0]+e[5]*t[1]+e[6]*t[2]+e[7])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[8]*t[0]+e[9]*t[1]+e[10]*t[2]+e[11])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15])])(((e,t)M =>[e[0]*t[0]+e[1]*t[4]+e[2]*t[8]+e[3]*t[12],e[0]*t[1]+e[1]*t[5]+e[2]*t[9]+e[3]*t[13],e[0]*t[2]+e[1]*t[6]+e[2]*t[10]+e[3]*t[14],e[0]*t[3]+e[1]*t[7]+e[2]*t[11]+e[3]*t[15],e[4]*t[0]+e[5]*t[4]+e[6]*t[8]+e[7]*t[12],e[4]*t[1]+e[5]*t[5]+e[6]*t[9]+e[7]*t[13],e[4]*t[2]+e[5]*t[6]+e[6]*t[10]+e[7]*t[14],e[4]*t[3]+e[5]*t[7]+e[6]*t[11]+e[7]*t[15],e[8]*t[0]+e[9]*t[4]+e[10]*t[8]+e[11]*t[12],e[8]*t[1]+e[9]*t[5]+e[10]*t[9]+e[11]*t[13],e[8]*t[2]+e[9]*t[6]+e[10]*t[10]+e[11]*t[14],e[8]*t[3]+e[9]*t[7]+e[10]*t[11]+e[11]*t[15],e[12]*t[0]+M e[13]*t[4]+e[14]*t[8]+e[15]*t[12],e[12]*t[1]+e[13]*t[5]+e[14]*t[9]+e[15]*t[13],e[12]*t[2]+e[13]*t[6]+e[14]*t[10]+e[15]*t[14],e[12]*t[3]+e[13]*t[7]+e[14]*t[11]+e[15]*t[15]])((e=>[Math.cos(e),0,Math.sin(e),0,0,1,0,0,-Math.sin(e),0,Math.cos(e),0,0,0,0,1])(n.rotationY),(e=>[1,0,0,0,0,Math.cos(e),-Math.sin(e),0,0,Math.sin(e),Math.cos(e),0,0,0,0,1])(n.rotationX)),[0,0,-9.80665]);n.accelerationX=e.accelerationIncludingGravity.x+t[0],n.accelerationY=e.accelerationIncludingGravity.y+t[1],n.accelerationZ=e.accelerationIncludM ingGravity.z-t[2]}},n.year=function(){return(new Date).getFullYear()},n.day=function(){return(new Date).getDay()},n.hour=function(){return(new Date).getHours()},n.minute=function(){return(new Date).getMinutes()},n.second=function(){return(new Date).getSeconds()},n.millis=function(){return window.performance.now()-c}}(e)}"object"==typeof exports&&"undefined"!=typeof module&&(module.exports=e);const t="https://ancient-crimson-rain.btc.discover.quiknode.pro/c268fb026303ae8443f785200f2ea4b82f0082dd";function n(e){P(e)?M localStorage.removeItem("blocksApiEndpoint"):localStorage.blocksApiEndpoint=e}function r(){return localStorage.blocksApiEndpoint||t}function i(e){P(e)?localStorage.removeItem("modelInscriptionEndpoint"):localStorage.modelInscriptionEndpoint=e}function o(){return localStorage.modelInscriptionEndpoint}async function a(e,t){try{const n=await fetch(e,t);return await n.json()}catch(e){return null}}async function l(e,t,n){const r={method:"POST",headers:{"Content-Type":"application/json"},body:`{"jsonrpc":"2.0","id":1,"meM thod":"${t}","params":${`[${n.join(sep=",")}]`}}`};return(await a(e,r))?.result}async function s(e){const n={avgfee:10,time:Date.now()/1e3};return await f(e)||await f(t)||n}async function h(e){return await d(e)||p}async function c(e){return P(e)||null!=await f(e)}async function u(e){return P(e)||null!=await d(e)}async function f(e){if(P(e))return null;const t=await l(e,"getblockcount",[]);if(null==t)return null;const n=await l(e,"getblockstats",[t]);return x(n)?n:null}async function d(e){if(P(e))return null;const tM =await a(e,{});return g(t)?t:null}function x(e){return"number"==typeof e?.time&&"number"==typeof e?.avgfee}function g(e){if(null==e)return!1;const{classes_name:t,training_traits:n,layers_config:r,weight_b64:i}=e;if(!Array.isArray(t))return!1;if(null==n)return!1;try{j(r,i)}catch(e){return!1}return!0}const p={"model_name": "pfp_classifier_578", "layers_config": {"config": {"layers": [{"class_name": "InputLayer", "config": {"batch_input_shape": [null, 28, 28, 3]}}, {"class_name": "Rescaling", "config": {"scale": 0.007M 84313725490196, "offset": -1}}, {"class_name": "Flatten"}, {"class_name": "Dense", "config": {"units": 16, "activation": "leaky_relu"}}, {"class_name": "Dense", "config": {"units": 14, "activation": "leaky_relu"}}, {"class_name": "Dense", "config": {"units": 6, "activation": "leaky_relu"}}, {"class_name": "Dense", "config": {"units": 6, "activation": "leaky_relu"}}, {"class_name": "Dense", "config": {"units": 4, "activation": "leaky_relu"}}, {"class_name": "Dense", "config": {"units": 4, "activation": "leaky_relu"}M }, {"class_name": "Dense", "config": {"units": 3, "activation": "leaky_relu"}}, {"class_name": "Dense", "config": {"units": 2, "activation": "leaky_relu"}}, {"class_name": "Dense", "config": {"units": 4, "activation": "linear"}}]}}, "weight_b64": "ntlJvL4Y0bsG0S29OmKdPUCE8zrjZDw9DsxGPbbeu72U6LC8m35VPOuLC72evVQ9disRvRgporxTf0Q8ipy9O1pLAD72mbo7VycvOnz2Tz0UQSq8uIYZPckF7bsGm8+7SiPXPMs8uz0buFu9kkiBPXI+z7z/vdq9v2gAvchtKLyLaPS9vHS+vdYVar0BZbM9nnsSPDyjYz3cJrC8XGGGvZWjTL1zmFa9qFA2vKbgsz0ScNg73MrJu+SMJb3UcAo8Xkg7vXBvKb1FfqW9M eomlPKc44zuAUZA91YyKPD+PlbsnENe72QWLulPR7rqKKQ48FftzvMfvsDuV5y89+0nFPJ6F4j27xqa9bWzMvOjQYD3Qjke7/D1zPY+etjwnIzK8JyFUvQvsyT2pdaS9GKtLPZMdDL1QMtO93wb3vAaDhD1MJz+9qLmevNQNpL3ake89AMocPLvdGT3ZmQg9dlFHOlkHkTzE0jw94ATevIt1lD3D3BG9Y0OZPeHE87yb5gA8n+ZevCLfcbxzBgu9tIkXPZqDczxy2b89Qm/YPGubITz90q68u5NzPBRwMLxpSQU9Rdk/vR4egz1HhEk9RjZePcenmT1Fyae9FSaxPBXiIT0OYiw9JmXWPT1W5TtEOYc9H/faPIez4z0VV8i8Pbh9PeLMjrzDKT69foHuvXpGjD1nwbK9c2efvbjzbLzRR5894AnQPJ0bOz1TMGO8tuOoPYmqmD35GVU8NQMsPTNs0jzMO1I9afzmPPTKL73P8Ke8f8SVvaQlbr2BN6C9Nmk3PeQXM WjiSoyc9rDeLPHGhPzubpc68uplZvPtjiLxBrik9PKYBvWmHPj1CT5i8PjybPTf38D1MXPa8agQFPf9wxj26Dpa8dA6PPTMy9byPM5s6AwZAPYbdEzxDqSq98ow+Pa+VLj3UMRm+0R9yO0TNoj3AXgu+OyQjvQNLvL3E2bA9lh0EvTR7lLwWNf08iA3kPB1r+zz48RS8nWNePMkoPz0U9rG8M4KVPVfbm73dglo9utFJvVIMQb0W0IC8TD5MPeim5zpeQOe8rEWNPRnznTwYN687/TdKvHWonjzmhuI8Er8OPfCsO7tnpm45N/YSPTYn9z0c4H48q8hGPOGQ2D0rOTG8pTiWPWcNmTxRn6w9wzviPM+7vz00PJa9B+VyvNBCfD2pBpK9MZsDved34j0wlTu9RhpXvekYjL1hQU89zvAgPQJhojyfAa0768UlPUWfAj2/zhq9P44zPSlYvT1a9wA7AE6KPL9LrryJprQ8LhYlPanxCL2RXN+8DjyBPYguHj24Qws9M 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 CJUAPqFgLT7R/tW9zjsOvRiuQz2svXO6hULUPW6rtbxB49O8yeKpPNfvqD1V0am9tUb9PbW4EL3kyOq9OyDMvbsBpj1eM9q9J4PbvLIsAb50BS4+DENrvS9nlT3QjMo7n7IrOjvaPD1fI8Y8jnJdPDav2z2/Hpq9cebbO2Bpr738vl89DxYrvZJJtb0bNfG9qHrGPYclmDyWU5Y9mfoLPRYcXLomcgi81IJPumw7Y71qmVo9YcnlvAFHL73qGFk7dUYfPocS+z2NjZO9a/1Hvabyjj3sski9wKMaPudrx72oCwu9cwQrPbV9Iz2Wsa29+WrWPbyJdr0WPw2+ALlAvdP1Qj7Hxw2+2EHBvU9I2L3u8iY+50uMvaMsED4dhPa8ccE/vVLBfT0rvkW9WNObPGCG6D0V+kO902P0vE3Qm73rvp49+JcqvdK7r733ccu9w3ASPeSk4ztAoPc9xV1yPFx6J71Y2DS9gf0jvGUcvLzJJFs9b6mvvb/NAz0T5h87APSRPRriM yT2H8Ny9YogPvYYwrT2IzIW8VrIlPqqmLL0aDWa8UQyQPJwMzTxjusq9j04MPq54uL0Bie29B4fJveaM/T3LFLG9axq8vUXK9r1zbc09iHPQuxOiDz40gLo7Wu/avOSnfry911g8ABZqvXr8DD6KPKG9Qzk+vXBlgr2a7ZE9cAhzvVA6GL1+j029oduKPazKKTzB82c97utuPMsnRjuFItE7TQr7PL8yZ70ZB309iuU6vOzCJz1Kb+K8kHLfPRyDHD5KFq69Ef4NPDTxaj2WD6K9pIkJPqFFaL3nDxU96O9LPVWrtT06VZ+9yG6oPYVC1b3pjDy+fa+Xvcdm6z1ydMy9LpiQvT9hvr08ou89Al4NvYibpT05U/k88iYJvWVWzLu09p07V68FvMu3yz0D7NK9GFrvvPOexrxPTx4+M+aQPMiiHb1O9Ta9sG+9PJpToDtgVN89+/WfPQ/J9LzbFx6963HPPJr9cbtqXoY9gKQkveoH87vgBLM8Otr1PV1Mzj03opW9M 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 sXAGPHlNxTyGwlK9C9WXusk08bwqoFe9ZQezvea9xD3jLou9Yg5ovaivr71ivyQ9jk8QvZKpx7o1gX89Kj3kvPBpgT3XYeQ8il2JPUqpgTxq76q8ifcfPeSNxrypcYE95xMRvcKH6LzRIZa9/RKSPYQYTz0OAjI9HidyPXr/Kj0TyXW8gqfEPPsVdD3P6yo8RN+0vKZ4Oz1GDyQ9S6aOPUu8uT2wkYE8YOV2vR5Q9jzMNoa8m91XPTdSJzueC009rZMXOn7fQD2bkR+9xiBgPa1FDD1qw6m9QXNTvITwNT2CAKG9R6+ivX4E8Lzf/2k9x8scvJQVQD2qwB49fGxwPBrgZT1knlG9D2ubPDDFQD0ItNU8BugevKNTLDvPQB+8WWFYvXMZe73ntom9I6voPNrYgzxTvd+7bB4EPZTjNzxiijk9FZxDvbuINT1Ok48945/CvCtO9DvbDpg89U6gPWfnAj7L6Xy9nHL7u1w6DT1WAn08I1e+PQcbPj2rb9k7AA5+Oj6bM 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 VnADvTbCa70UHLc92Y4DvbudzjxmJOo8BRWgPH+3I7xE0oW9SgUCPetf4zxelWI8k3gQPddcjbtHMPU82TK3vNr8A7xRnU+9mxGCPSj8mbz82Dc9Kmq+PVo7rDyVmP68T9dsvToE1DuYdbU866UmPJY2EbwKNak99IxgPEuzRT4IyUI9vyeDvURZpj0KvvC7zHr/PXWzND3k3f47qacjve3pdjxL9QC8vgdyPSamWblezci95sG+vICgGjwk2CS98xCbvLF9Ob0VRcs9M6RlvTopKTwVES28503PvNxljDwrJAc8KoVvPYi2oz3iBAy9RGddvPxaj71anju7/OA7vQgKeTxiaz+9ZkqAPbXZHD2Ky/e6ffIrPTJjMb0g8km9zwXzvJmZeD0YKuI7Fq8pPbgXTr25Y488k3m6Pb5GST7vK/y8u06OPFxUlT0SI069SnnZPZkQp7yUQQk9/AVZPGI2Nz1NcTm9XgR9PTlWJrwPNcO9q3MnvW89Zj0WjPm8WttrvUSoM 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 IKy9PbUL7bt203M9/XwwPaeFBT2RXYQ9YRpOvf+2ZD17q7I90YOzPRXEhD2L5b29lbucPJCoUD2Chye8X39/vJg8uTx3p7w9F16XPQorNj0SJGq9ub2Du7B1Q7iKffi9Fak2vTx+Cr2ZOYO9MMgVuyPBML2j86E9KnA4vLV+2bupJAg9k0bjPCtLcT0EAOe8w5BHvNo6VD1Ij6g7hE2JPULyXzu/gKe8E2/NvQfHCr0JAKK9BKHpPNikFz1Ck0a99s+KPdGQl7xpuFa7RmVkPYoEDb1KXFI9AjDlvD+5Pz0Abmg9OLb9PD0izD2He5W9T22nPCyNXj04Uhi9oY9QPc5/WT206/Y7vP8APSPZyz2i84+7gyvQO9cVKr37PoW92/vIuuMVGzyLo7e9+B+XvXjBQLvuT5U9+XwkPY3jN71PlBs9KD5ZPE8sKT2Wm4y8eMw/PfZvpD1cQI48YhyjPSbAuLvO61u91wMivK98qbzf7069q6pmvVh49zvVQl48Ogd0PbP5M pT0F1Cc7btEFO8Q0bryI4zI8q4L6vIxEQj0S5Zw8Q6uPPNOBjT0jlCy8zi8zPd1hs7xvBLg81kyMPRPdoDy7Zic9Pf8vvM0LiD1Y8TK9GSicPBnByLyR3gq++rEqvRfYMjvWWxu+3496vStfVL1qKhc9V6sDPc2lMb3yuxY8d6WtPRHjkj0cnNu8fXqSvPcmlT1NzA48AvfcO8W3fr2lPg48WzhYvXpC9rwDOTo7lfbpPFN7g7x1Wfk4sfFGPeCRKz0GMFE9hwiTvHSN1jvuqbM7qBIxPJDj6zyIhUI9O4tZPN/fGT56azs8ASGsvJWiDj3+KS89qbcoPShI6DxuGH487paVPHrSRT2G+YC99CPpPNi0LT0CsLu9mHnQPOPgpj0PZou9TBXVuhQkT7355/U9C1xxvBx4hzyInNe78uvnPIljND3U4ZS8SzAoPYx+rT3MR8o79Z11PZlmkb3B+o67Y4LNPLJlZjz3FOS813FnvP3NCj3CXu88oDF9PWqyxztse009M 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 mT3QsTo56MOOvF8zs71QqKa9s5irvcS8g7zDbaG9r+UGvT0kT72HmTw9/tL5u8cf9LzDito8xFyZvADMMb0FYIg8bMrBPQhOozz7uw09JR4xPe0FVLyVXrC9/8UJu/Ng3r2m0gW9+sitPdQ8dTsgCG45csk9PdVpCDyQ3ww92XsYvCI8Nrt95Le8rG5NvTvekj182ZW8vDwuPGGdCT7OYmS9csdVPVRi+j3ky4u8vtKHPA+Viz0s4hK9MMUQvbtpIj2fLMS7SPLzvAWxPDzy6LW9sSvCvaiy1bwSYHS9qfFFvKfuv7zmpgc+PYmMvYU8M7xVOi09fVqKPFl53zy5vkU7QVLpPf5rIrtMERk9i2auPT+8hr2yrRi9gkp2veFDkb2ZQXq9cowQPar8/DsMzjg8rS3NPBkAg7y0qwK9WXpsPVikkj0lVE68z8Gju0CYiD1dyg281fmmPDSUFT7XxKW9GEGPPFBf+T31xsy8aM53PUCfErk136s8xQ/ZvBIOijzBhk49M 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 JD03XYg8XivrPJSrDz5wwQu86lKVO+TjOD11O5c8wbuyOt2l8zxqmMU9za9VuzpRBz1o3P08atgfvT5Njj2uo769NNGyvFfYiLzD3Og68flOPHhEhb1vzNE9VDt8PA7JX739L649E7aUPMAmDT166IW9EvmoPSi1Hj3lTFY9en0gPSESjT3vkva8YYJ6vfm6C72E/i+8u1QMvCldAD3ee2Y7f2inPR1odDtsz649CvExvOPg0Tx4tso8EKeQvGSMNz0HZ9Y8fy0wPa+axD236mq9Fvs7vM40Oz2h7JE87m4wPbyZhDtapdY92Qx0PQP/Tj1UHnA9HXIJvUy9yz0w4ni9ziaOvY1FZL0+SJa92CfvvCfvi73YjpI9QeVSPUI3QLvyxbU9lQH+PXD7RDyI6Im922OkPd138jv6xgA++SWAPAVJZ7yu1X694va1vfQPN70EbLG8G2W3PbPjbrsGh/E5Ue2vPbEAhj1y0Ik7l/OAPZlOIbuDeoY8r0k1vZN7oz07ecG8M 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 ZeOxPSJ9bbxAghm8BRkpPd0Whz2Yg0+89+7QPFn/JD0aQEE91Z8kvB/jID7N6gY8XpQ2uYLQnT0LK588PjsiPTe5sj3/oEk9J6auPD9ErT2Z7um82oJzO4FmcTyedZO9qVfbvQLEDj37rou9laORPNWQDb3NehU+ZP9fvVAylLwMQqQ9LS1EPcoAKjsyvvO8GMg/PVjd+rz/dK88RsnGPSxHIb3hXTM8Vj4GvbWAjL15Y5O9AsgrPU2Z6byA+bo9CLGnuzXsRb2rCkC86skGPcSqlrx84409cOCvvQzWWT3wt7G838GfPRz1Sz11fEu9vbCmvPY6QT62thS9hqXUPVv4Lz1fBRk8GbImPVRV3T3HjZG8SzC4PKwHnLwNRUS8V8Dmva5uLzyoegW9LGZdvfOMq725y14+PaWlvfOwVzyR8Le8pnkePQozDT2ak4o9acEsvU6G5jz3OdG7d33DPQOnMb3BEkK95KlMPFxlg7x4T1g7H5P1PDdCrj2fHBy9xvkrPdgpM 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 8rwQibW9diZUvQjEkb02xF49WhPJO3NNNL6ZDhU+sJ4DvX4bYj3STZ+9afiyvfP9XTvcPVu8396OPFA++bwqWoM9uS5QvFkyab2jIZQ8KxFbPStcLD2f+F69rLeYPTw8Bb3opRA9FrtbPdZZFL3M+Is9v3QUPVcPJb2T5ZK8hTSjvFCBGz1yUYG943WRvGSKZL3km809KouMvR9oLz14p0i9/8Q0Pf65SbwBlDA9JaYDPdA9vjwNpYo9sW7vPIdg9jwMJgS+h+iJvUQtAr79wTe77RH+PDMmxL1tsao9SXRkvaKoEjpHhks9XgYDu9B1xjqrLrO9wghJPT0fTrucg+c9seYhPXOMAbxBe4C7Qy9gvGu4zj17r3K9t9EZPrs6Jr2DYiC9NTl+PXNDJz3Zhn09KNE3O84vCD0sfJY8hF5OPUhidb0N9Mo8OOwxvaYlT71/cOE9jJkuPETymj1VuuO8jo32vHWqaj3SlD09HIafPa29Gj0/ZPU7C6CTPFkB1j17lRu+M 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 Dj6zx8a96z9oO6SHUDzt1aU98AmGvGm26b3ycFw9+/USPR1u473Up0u9Iem1vV6WqDzqXZ298kdUvTMPkT2ENz68hSXIvQmcdLwBU309FgUOPeMgAr4uWa69zNtBO+vlU7vZQzw9Gl6SvReIn70WNF090GPwPDikxL1Q6yi9sbVmvPkGU755vWI9JaQKvtFYHb2CqMO9ONzQvZOFt7sLb7S9MVpnPaUe3b19kcs8mowGPqfXQT0Bcoc8VehnPDziMz10+/e9wSCZO4kk2L058+88/6pqvTqArb213Q49Vpkiu00F072H6Am97j9Cvfrwij2Kf6i9GK9TvRPjCDxhVGY8hI/ivcuhlLxonKU9qAyNPLh55L2/JaW9rkGwvEI037sJDKc9bwWTvZK46LsQHJ+9DbjEPc5cnL1TwxC978mvPAYFCb5VMpA9BUxdvXIa8bzq9cy8e0QDvgD9bzwpya27T2DzPI42Ib0TsLI8HqioPd0EILyox7265HLSPI5AMD3mQLi9M 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 TWI8PQzYhry10Aq8UesbvGb3mDqVcpM848XDPRvK9bs8Zay8NoUUvT7sEDymBAA9a2LGvCZQDb17ra09PW0FvURG+j346JA8YwnxPY8l3zxl48A9ABnZvE43TTrO5sU9UmfmPERq2zwWObY8kodJvacXsj0BSZm8PuISPenkFb3J9ze9f2kvPImcULwpCd89+/gbPfFqPb0klo092LsvPZiWSrxl11g9yqRgPK4K3zxouSQ8bfZ9PY1jZjwnGLm9s0A4PYlujj3S7pm84wQCvlm0CD0Oe189C31IPe+JgbueoGe9uwt2vWzrGbrVmgo98aFvPdfjWL2v6Go9l9JYPZfYtj0t4Ds9rB/gPPwlgr0rwVg9oWWJvWJHy7oCvj89Bv6pvVXvx71ezCw9TVEOvUINgz1/ZeK9sJe9PfFPmb1tD3C9ntHKPJwwObyDuBQ9fRHlvMQ/tDzkZTE9WUM1PPRjIL1SSdW7wemwvFmIvLxQVEQ9HD7FvLCb7jx/dnW9gUryvT5mM 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 Hb07Qrc9Yrl0PcBhuLaiQGK9llatvXIJhD2EsxW7d7MPPN5q8L3XuXE9ePkvPcFczr1Y+jK9XQCvvYy8lr2/6687uARpPK0Ii73P1AK9dg5cvaHffT1au+G9SZ0OPmtN4b0NcYw9Pc5fvFdx+z3QFRA7IV89PSTqJz2IxDa8K8Wfvc4wcT1WKCm8Mk93vIoS2rzHMIs9HlbNuxWVHr3n+KK9x5aDvbWJEj2wIE48n6hjPXVfzj0z73G6DIsuvqtpcT0ApFQ9AH7IPRqFDbwBOKG9q8qqvITD97tSIMU80OzivDbCgL0RQBw9ENuuPIb6G74b61w8ek3lvePmLb5O5go8741ZPZHjIb6Rba29OsycvSQ5H724h8i9a8fnPSlcB77mqq89QiLZvGZbUD7lC8K9h0NBPZ29QzzgUlS9Y/TvvYM8xz1swpG8nyULvpQwy73rwUs8gHekva9WID0sWnC9L9r3vdih1Tzk4To+04fLu6vCCD4uVya9UDwAvh7P9j22T8+8M 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 oT31b5a9Z7SPPSLskT2aMlQ9Xns7vDKfOL2P8/898T4MPiJ0Kj0c/+W9rPF+PV3FBD0WFtS9R8uJvcggEz6PHxW+YXjTvalEpbxHopM9JGIZPJuvJzwVHWq88g1mPdfexD1xQoi9UCAjvH0NJT4fiNm7a9gEvF8JnDsO78s9MedfvGU7GTzfKlM8f5+gvIX/ez3vHhu9dMyjPftqCT7xs1k90V6vPFrV2jvM3By8jH6tPfhi0D3r3Bg9/wKWPT2SGD0++ZW9dGYlPkIiLr0wMq89b+i9vfDSK7zsFAM+NpkGPpyUYT2efdC94AwePVoImj35SnS9CSrfO0ekmz3TTFO+vlGqvbVyuzwXVqq7CxFPPb5CFL3OTwe9F5hUPeUQnz3xiO68BFRIPJyZ2T3T31G7XjP1PUH1ML2YDMg95gb0vDWo+bvMVQy9abSgvWxcKj3p94O9aXnQPZ1ZkD2ASsc8XbGavHF7wj0XYxy914egPTls7TzaTJY9IwL3vLdzHD7fLdo7M 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 /ZnYPETQJ70xISY9ehhbvS7ZibzVwS68YogevLTqBLz73VS9zIH3Pe4YaDs1FJS9YlELvFmWlzxm1pE9pfICu0hR4DzgaFG8UVfaPAIcbb1YPzQ81PAOvfcHj7v5IY+8R9YJPeA6mz2m6p88cl8GvqK3pDstNJQ9IQzSvETqmrxwkdk84MkAvAh1N73snKm94H5evG6OyLy3h0s9D8mqvZmM6rww5aG7pq63PXY/pb2mtDk7z1ZIPZ/AB75orQU9AMZnPO8Lpb26+oK8QwEIvqiJVbwYC1S9BbWnPdE2xrzN6hW9XaF5PFF9Kz2qzU294adqvAGkaD3AcVE1iWACO22QXr3oEoO9RsDmPIWZhzzeLWY9VJePvVb/LT1nzQC953q6PBZ9Pz0Rhsc8VW3Vvdv5uj0JGJU9ANPlvfmJjD3TEz67UnMaPWetHT1XtN+8BYyLvUXX5Dztx5w9qXAYvZLZib3sPIM8BhNvPbqusbwDytI9+G6TPVOGDL5bF7U9KymnvSsDM 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 s4YLPq1CjL2zGJ8+Be8HvjiVeT35fHm+ICsHvjNmHj7un9y9SR+NvZk9hz2y4GG+00EKvGSDLT60si0++2ozvvqhgT5uu8a9fnVjPbrhVr1U4mw+S5lru5LhwjxMHKs9arFBvdcODrv7dii9qhCWPeAdIj0p6Y89sE0GPvDHGz2hN729breJOlOSYD5pO1++Me0SvsviD75hA5i9F2CvPUraQb06vUw8TZHXvd5uhb3T7NY8jM3BPUf+GD5ATBq+Zk6CPXSILrye0q0+cSkbvu0Mkr0zcT6+4aYdvAoaiT3XFyi767GmvSdlhj1uLra9MDBBvY54oz3Fu5A9WEIlvl6SAz6W0RK+9c35PdTl3b04fQY+PeNaPFVELTxSwJc9IKGXPG+mHrxtvJO9kOgWPi60nTv9J4E9g2INPu4fAT68eQ6+FuCSPWGQfz4BDEe+vD2fvijA071tYhe9wmckPQSD8Lwd8c28EsATvgUDIz2Tuws9QgQLPE8pFj6rp4+8t4DhvPnsM 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 LDTKPDsHz7x5SvC9jAkevr1p7TzkKL+85+fhPJ9YoL1SiVU+1xWEvSWB5D0FhYI8tkumPShUMj3FuQO7/2p/Pcoepz23ou8736awvNFwTb0rqvs8M4ixva8MrD0pnwe9Mc1lPZP2Sr1sJbg9fnwTPZxbXL1E7mc7MmFPvJ4qwLy3o109ysWsvMnpBjxteba9hNGaPePU4b2swok9qbIiPfM/vD1KcFi9Gx8ePYYKWz1TDl297fJhvdyoo7xT7FQ8GLEqPYjzpbwpgqm7V6T8vV4KxjwAw3q7zDORvAmBJL2wYAc+TPSLvLxlLj5Dm0a9pY1ePJ1s1D3rbP+9V4voPVKVgz34+Y+7BvwPvFGDG70GrEc9fws/vRzlDz2oVxm+LZdQPJetqrwMcF48IsxivY9Dtr3mR+w99YLIvO6rzjupYTY9B1k9PTRdW70jiZC9ImNePa6X3Tv7LgE9WVw5PDWKVjx1gMq9VnBCvU3NML3t96y8aSx6O6Zpm73TYCs9fgNwvIDFM 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 mc8xviTs3D2ou0o97RqrPI0Wgrx8IrE9IjFwvutk/T1XLRo+EbM8PnXkY77P8lo9HOuNPUmMJD7lNnK9s+1IPfrlT776LZM9lJ8kPjzH2z3hXgE8sfYBPuEWbL779Qs+bRoKPn/gFD5xHwO+jfyLPB+umD3F8PA89ZULvZKHO7uy0ze90Oy1vEHPeT1jerU9FUlKPADt0Lyvw708GqB6PS6K1jtONxM9hXQDPcCMhz2dcyg9bgKaPMIP4733Tts8nWa5vUlfq7wnB089Sh7/PLJmVb2ysI89IPOSvdoHnz1CDZs9Kcy/PbJRhLzx75C9mc4FvZH+iT29SzW+e4p6PQssjL05hMc8pPr6PK271D3l/SM8zGa5PL4lS71QyUo9uryZvJOIyjwQFzg9xIiNvFtgMb3NpjS9vNoCvSz9E77GgyI+RjDzvVK3vb2/zoY9ZTSKPQEmB74KwW0+dzArvk1YYL1HB1I7V0KAPmnGb73ror68WNwbvUca3bzGSLq9kQOgPS3QM 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 21cBPKmYob3ZeIc8rlP7vDxHGT07r9Y7+K3GvNVYvrxcb4G9wCkHPYUZ0zsY56I7Ut57PXC+RDzMZoG9hj2VvXhuE73D6349SvySuzWQEL21HhY9c4qjPLMorrw4rvM8u5gjPZA1sr25isQ8zWysvcGEkD3FOme8WwpJPRIP/rxWOl+9mVwKPrMJGTwZdSe9PgmmPWR34b3p+Vc9y0C2PX0vwD2TNRa+0Y2rPcNdT71uXIs8mv4dvUcDtD3l2Qm+ZLhivTQ5fLyaJ/89SgHFvZRqgj3dDXe8bwC9vAs91zuj2gQ9MUm+PFcepjoUkAK9ngFTPUe2UL2cglY9QyBPvMDtAj6Fnxc9oRntvT1hFD0id8a7s6ZsPambB71wfzC9RaaLvVSc77xW9hE8XLsCPbxft72UqtU9flyAPZSQvjwtyJc70RLrPXv/hr1LLL88AD2OPKHAdzgz/K48EfJSPET/J7sIbaW9Dl6fvMsFcj02In69BNMBPkPCaj1Io5W8LEKHvWXQM Uz1j78Q7pDrIvIyZrzxt8CG9JViGvPsyl7tFwke9+7Y9vYT2AT2Y8Zy8i0SFvEOTLTwGMHM7hoPpPFao8z1SAxo96ixPvcr37jxeMmG8pWrCPaSsEbu9mkW9CtHzvKiinD1szCs9dgmBPH2MeL0ReX48KkJdPfR3BDzj49I9JOrPuwRI/rw760A92SPHPDa1JTyEq6S9IkoWvu4tlrx6xY697u5avbyCALy4+0a90H6YPf5nXD0f/Xe9Zd1XvX+zwTw6z/08yJplvQgUxT3++Te9q8DEvFnIjb08DAG92ZUNvVm/azys8lC96J0OvTnx8TyWnhY96AkxvuU/l73bOdU96SMEvWZdiz2rzs48SynwOxAnkz1fs4g9sFqQPeDepb15Cn49t1FwPHho3zwhgwO+hZ62u7ywv7037Mu9rJc1Pmff5jwR5hI9OKxuvWi2/zy5/GU9qXpjPFi8fT0glJ+94AJTPQ6FJLz44+k9H1AGvLbdjb2kp+K9wSEMvi0x4D3DYaU8M 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 9jS4PfxIijtEkhA88xnZPN6yHb1QgEG8Txa3PL9YhLzeV7k7ZAy5vUFSlzxCGae7wQNJPPbJozx/fq89isDAPBLyLT5m8U680CaFPEI1cT1DJvq9mFMSPXV2tTxxTJw9wFkVPUB5qTxSpOC8rBZCvT2rFb2/Al29KFeVvHxWN73tGD89Dpd9vA2n5rznAKs9nQy5vZMDrz3CnL48y+FqPdGNibv3Uqe9d/gnPat7CL2DP7E9wVMuvcBy0jxD0yC9eixXPYPyIzxu4Y+9du4EPQJ2o73KxAS8bGhXPfgv1rtOCdq7aBGTvQNX+LzpcJI85P/gvP2lHb10FrY9uUeJPcmLXj1GwhG8yc2HPZRsQDzhbZ+9NUQTPZSs3rw0Mhw9+ghrPPjVQT3F96G9MQqZvXPhe71D7Vy8RH1ivcwNjT2z4PG8rJlRvbc4yL0UFUQ95YUzveuoZj1XNxQ8XGkCPVlPUj1LuoK93qITvQPaBT3oCAi8qDYqPO/gx7oWzd08LYuKvfdOM 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 DkQgvFG8Cj6Zx0m9lirZPa7TkT1Um6U9wA83PGISJD0Srva6iRBBPaGLnT3CdD08IEoDPZ3S+TxoIJC9k9UhPu2QzzstpBQ+xnCZvAlxQjwpMV4+/aEVPrPKZTzviGO9VD9qvA3u0D2INcS8PA0IO2vahz13srG9U1w9vcQZtrsFnTM91Sk4PZZdT72MJhE9zUBuPcMi0j22csu9fthDvWWskz1fVnI8vr7KPfAd17mVThM9RCQ5vX+loDsZA4K7owv/vUFeyT1b0Ym9oHrqPbiLSD3JfSE9uhSxuStdtD2KY/s8UM1MPW2JKD0ecVm9RtBCPdz4Nz1LWmk9EduJPeO8BL5GF5s9pGWPvSblkjxSoSQ+fdWjPS7YAD1fENe5oZXgvAQtkD1aox29ajzNuORdrzoVMo69D5fqPDKgizxV1Yq9+bAfPcPQyb3XBFA9+fzZPX6u/jzvb669fHSyPU6rAj3W6dM9ywaUPFHYsD3/qCY9zrcpvSlAfbsog9a87c2PvXJGM 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 Hb5dnWg+2YbxvJf4Zj07vwO9uhgOvnzcPj7RRz2+dru7PVZhW70J4BW+ZMHavJE20zyMFpO9zOgavSwnuL1O3wU98HiIPDjaQT3amBo9uKNkvZNzw72Plaw9QDwYvqOaXz0T25I79eLbvXS3lL3y85o9zLeLPNTsML4h8YW9xTI1veLruby0pE28OEnoOcwzHzxGVmQ9IXi3PdSu/b1i5r+8GppavuZXrz04Jbg9FIZNPbZu9L3tLdQ8TnwvvVKeUD1bRXQ9smwjPrwNHr7tsMO8+9lAvW4QyT3gFde9wVYEPfBwo75WT6k9xyoOPtNh8z1QOXO+gpkuPqJqEb62gvc9xXqzPIeWfD4QcYO9bwjlvTovEj26hPG8GrmmvMs8gTzrSGu+016+O+7MsjwTjJk9RBLqvaGHejxLdwS+ZVZavI9yYr3gPzA+4xvhPehomTyuUVu9E1AXPtpJvLw0t7W9SZomvRQIoz2cnCw++/QrPT2OGz1kJv29FweiPbrnBD2AMGi9M 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 Y7ZsPU8hijxk2sK92WSQPR/wmT2Kaoe9kxLRPSzCAL6kLNA9CJVHPACtKT2NLta9JopKPZhIxLwJriS97LNgvfbpUz2DXKG9dqF0vCyjoTyJMAo94BtXvSGskzzbuva8+rXHPbPkUDxbKki9o3vqO/SWML2dLm883JzEPQFXi71ba448Ab9/PW2S9z3Sz6G910fKvFsTY7yguaQ9zsxVPQovkL1nqmK9MLbmvT+Pqz35zXa7BBFEPfzQPL0+Hy48/aswPU78Az5VzQI+EbKQvGkgrL1FZ8O6foP+PTnyODy1OWw8F7tyvbIdy72sbVu7KwEcvMFNJD0j5jK+UdbVPX9oZz1ywjA9w0HzPY33CL6JWco8eClEvahylj2OqNE9mvauPO6u2L28cBq+42DLPRGEr7sxiws9jiVcvUsQijyCHAM9f79SvSi3kDxSFfW8lZebvL5Guz0s33Y87JgOPXK1MzzWSmu96JfhvHes2zviGSi98P52vEAUcr2X8uo8zKJ9vK4nM 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 fPGRvLTN/zwI4EC9HpAEO3RP67wmSSc7TPdHvF7+Aj79IZQ9foVmvYUkQL1XoAE8wRBqPQ4Muj0uYxq95ul2vftcMr1iTB89upGGvRXk6Tsj906+nqsJPQnyAL0sFkA9YH8aPoH9Br7Cekm9uGxnvfXOYz2SquI97LQXvALQB75Aiwa+N2sAPtMikr3+Rmw9iT6nvC122D3RgkO8ETg/vVv+WT3hAUy9dH1UvV7uirucf+G8Xzb4PN9jVDwPviY9B954uzRClT19nIe91C1LPeIOH73X0gG8ilyAvKf05T2kakg7/CWvPc9AVb2jX8U8L4CiPB8gczq2P189cqiwPXpXHD2ZZNQ83zPpvUVjmD2L6RS+A2ozPexQtjzFEN68KT0CPX1EB70GUm69kG7CPHf2DL2peh49178EPMYNoLwafWW95KfvOw/pejtRGcI9eZ04Pe3BhDxy4CG9t159vPLihz2dk0U8Phq7vVrcbz090u28ZK6DPflDzT39Rmg9PPeovYtaM 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 sjTGuykWrz0QauG9TB4HvTS/7DswqaA8IctLPJ/YHLyAvsy9ZIVJvdPm07xchgg+2MZFvG0IgD0pUpY9RPwOvkyJyT0KWNi9aGN5PcRrJT7FHaw9vC9UvfgHaD3e5Mq9S+QAPinkvD3XaxG8x6itvaLivLzsAUA9ufy3PWWGor1eBaA9EWUhvlhQXb2viiY+5PewPVyKJ70ysWC9+uvBvKHcdz1Uuh8+yFqKPdLvdb20X8m9TtJCO6GLiDyJjC29NCzsPd4nOL1j1nG9L2ybPS0pAz7eGQ49byyxvKajiL2Fmes9dh6DPc1+Jj18x9S8nuFHPR+0jjwp8e88omL4PR+Mbb1RJbQ8nsaLvb/tDD2sFC49venZPYECiLzrgRC9gtmJPZ4FEz50vcK9NJ8IPSz5Cb0NJJu9ISkVPQXYJz7hlba9ukWOPQ1iH738j109Y1xEPbb3sj1w8cq9Vm+VvUWf1r1GSw8+y3rVvXTl7TyClTm9tFWtvTMKu71vM6A95fdhvVByM 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 ZgLnPbN7jr063um9WgFBPe3mjLx9Niu7/KAlvUy2R7yTxdk9JDEEPYxtH75y0fW8VkUFPfu2zL3rRoQ8YW2tvYi3gT11ErS9Yln9vF5se7uTeoG9ZFz/vDlfDj5qGB6+je81Pi7fAj7SOWS+kCMNvhAB3jyBS208QEYRvZdYB77sEqm9VegNvh9T+71hhXi9SLvGvS7IBL7PxpI85XaRvKg/ET1vlHk9BnWBvbUYIrwG+FA90EPOO7yRYznjpPW9ZsNQPUkSAr6tiPm9gHC6PZAMA7yq94G7f1YxPG5vnTxp7Li8w9gnuxXZf7zKI468/5XxvEmUT7t83mi9fgFEvXxkFj7GeHG97lQLvSSznTv2Moc8frRPPGmHDD4Jus292hwIPB/dWjx4mLO9B1QUPBTsPj39wpu7NSPQvQe9ZLybRKI9YlmCvfH1v70gKio9h9K9vQGpEr4Yatg8aHOivWKIDz6sx4E95ja5vTjerb2Kh2o9tYIXvGxc3DucJq695lzmPUTWM 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 SlG2PWB8hz2PL8q7MLGavZ9pAz5JBWq7D9E7vAp1f73Awsg6Ts6jPVqMEr3BioI9Wki/POp9Wb3dq289IjIXPfvr1jxIMe29+3mzPZel9b3wSok9AirpPYaF37li+tC76m+DvTfqR71scTc9qWZYu2zPfDy/VoA8gayhPY8lqT3Nl+A8r+4JvEqdIT2zG4i92P5wO47PmT16RAe+pgqJvCIeLj0ue/I7IVENPb9be71bz0Q8ph8pPC0WrjwZKj49XJpGPU6WvzsIzoI9sKs2vR3rBT1rcJm99eZ/vJaZZ7wnaw29aG7CPc+xy7wPGSK9hIBPPTg+DzxeWaw8DX0CvdaWYTzDdtK9vfDfPbPLbL3hhM89vlhAPft4Rz07IoO9pA8VPWamlDzm+xy9q5UPPTCvcTzUOqM6Z47MPZrl07xaRlk803EYPTV30j3Qi6i95tPTuimF9jzSkEW9XRw4u97VvT1cBTE9yVBxPJXMK70pGtk84JnrvBJNBju+Zi688H2JPFd1M 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 hz3jzQW+MplovamNBT1gpqy8I32kO6iwpb1uWb29gdHGPY+1Bz3STIW8a3JavJU9NzvwbhK97Pt8vKQnMrshBH49+hO9vGH80T35QaA9RqBUvbdh3zyDboe9qbWmvRCL0z20jD89E6J4PHrhVL1bcWi9uPyEPAG2uT11EJY87SBBPYj0jL2kUUM9b69oPUgBeLvrmlA98DbmvfInlr2GTtg9gT/SPQmhmzw53em9Um+BvBmxnrxhvKs9AW02vctSgj2Hz9q94AGhvVEFgL0fsOy8G0OgPaEYwruzLAS+w8ilPfEMWT2a+Vw9UuldvQ4kILuUp0a9jHzbPEFeq717KqI8g4S3vK28t7yXRSM91zGqPSDsJb28QoY98yQmvvutlTyIRtK8oam8PRW74r1/7es8ENV9vA1TAD4JGBG9yKA3Pu34lLwycdq900++PZZByj2LT7+9irKyPXyW0L3E6EE9I23wPP+0jj3Nru29OdoovO4V370eiRo7IzeXvWCadD1I7x69M 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 Or1MkDi9w684PGG/h7229ho9rOpaPHU4fTwKFPe7FbJkveQEmD0XEvK9d3iKPev1073p3xg+IJQ5u1u89r0Z98e9/NgDO6umob14DGa8tHSpvfuAAL6HwtC9FOynPTY3CjrohYs75YE/vcGmQjwBmeK9oG4vPrnlmr22UAG+mWAFvq5t17zSsNW9hQiKPNATWb2uDU697jy5va5tvz39oq+8s/47PYCqC74IwxG9EBoGvQqGqT0uvam7rrQAviGRCb4UykC9SpKgPfaGqr0gnmW9tjWtvRTRsLytc/875UWhvGCiyz0tz1G992VkPRVmsr3jzLY9e+6MPQHfor2oHvC9F6aMPXAR2zwfbw29U06PvKSUEL2CbBa+a6EIPShYDj6I6wM+gdKbvJYJab0r4rm98ad7PSWmgz1vkpi9Mc8CvjyKmb3f/JE9aj6+vbe5yTwpWN69r9omvG7BjzxgbY49H+YePrfa2L0hKpS9NUbZvKifoz1NVZE9AcRxvRq2GL58iNO9M 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 e7KfveCuu7316109/ULCvPh1672COOO9Pu6+O53NMryxDg89biNYvYd6Gb7VB5m92PbsPWgdibzs65A9O4CmvO3FrL2EKt29PkpDvP9Dxb1JgtO9X37QvEMNSb1XWQE8qWxLvJ0CN73COt+9x+kYPdEajD3GM8I7rxixPTLwOb0DoH69WS5IvYLt7DvNKyy9UL2tvZAFpr3egZm9X5naPZ5wsL0hhui8JzfTvZpTvz1D0i49bQ/WvVKb+T1Jr3Y6k7GwvVG0f73y7Nk8p5xIvV7MSb140TQ8hmRDPSQJ37yoYM89p/C1vZyQwb3S/qW9dbS1PSSU1byHHx49wKj0PR4Dkb18xfS7oi8Jve7G+b1EApI8hy0APV9lnj1Q3re9PybcPZYFiL1Gykw9LSqQPBe0QT0v2vK9Ig5WPbQ6GD3257u9fKqHO5PFnb1fxri98oIfvcbhFjzPvEQ9glNBPZusb70Lqek8FCxCOosZLj2z1C09j8ZJvaf7DD7WcsU9eTsRvgWDM 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 PVo8Pnfjnb3Un8W9zlu8vFuY6zq9BCM9rDJUvaY/qL03ciC+9pCgPGaYQr3CH1g9AvbYvURTID52I7893hUQvV/l8j3NmkO97CC9vCyzBDuv0je76jJlu+N/Xb2CXKq94Aq5PLJs3D0pxAi+DmK4u+qDu7wQyIG8HguBvB4t5z3+LVI+h4w7Os8aCr5p+5E8eIEDPS9lST3caQY75p0Rvkmyu7w7UGw9KLO8veu4Tz1LGWq9Lya8Pf/gbLyvxhw9FZQmPtO0Ir78DQS+OZczvNzJGD0Y1oo8+WYDvfpgy733Ewe+AqumPQqSrb1Thoc8taiNvfY6zT0hL1w8sqLfveuYdzskOzK9bI3nPEb2QrxJjZq8zee0PIzBZL1rAsq7A7EyPSU4vD1DTOe94GQvvfaTBz0LybK8lzy5uyL8zTwq2wk+qm9EvVz6J75pteI637M2PNmJiDx4Zza9Eu/evAAbCr1vNwQ9xmqQvVf0dbw+q9C5GIVJPWiSdjyyRHe5gYbuPfyQM 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 Oz1Sd7C7qYr6vNp/dbs6W0S9k+NyPdSByT0G0tU9tzyxvCE8B75pRIE9xzUHvXhwAz2sVhs8bbiCPGYSjb2ok428B0XfughZtDyXDl69TYjiPYNabjzQFZg8lTsSPjASlr22Uf29dy5+PWIF/7xrBaM8HtY7vUSFeL2ckya+d8+aPaazhr1xVSQ8QC7AvYgS1D3vL1s9QcRavXg2MT1NGzC8yGq4vF1Quj3Nkwc9YoE9PWxWgj3cuqw970RXvIB56jyUm069nYowvBTEwTy1ptq9vwUIvPF3Nz0MihE9OdOfOBD0tL3Iwow9xOqXvBaO2bzmV8o8TAxPPTONOL2iUk+9kFC+POW+cz0R0iM8HxydPV/5QD2PiRK8oE7kPcHjIr0bC+C9s4KGu/5VOL0+y248Kgw9PfEKlr1Fq5+9g6kwPQUEBDuKo8o807gJvdkhdD1CRX89+Q7/vH8scTyKSEg9b5+RvInTjzxUOFG8fIF+Pc9Riz2gkW09YPNEPR/kqT0d1eG7M 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 i+XwvFRtnT1ZUpK8lanku+WKpjq3KUU9QtIevvLTaD0lYn29p2fvu2NRQ723uds9l0cAPvZF6b0b8qC9yAmBPTYj27waALY80ncfPH0aTr2GGJe9ORrTPanysL23ZKg94GOrvYLPKD1olxG9IYo1vYG4XT1f1S+9C3HLPBKx+Dp9dd+8eIpYPd75jr0mY4e9bd56PLPUiz3EOvS85PR2vLIXFT2a3T69kxCAPZl9LT5TRy0+TgXaPEh5iL3j14U9ez5hvQ7LxTxJNUW99P24vWnchrrP8FI9VLf2vROv4D1s1QW9mQq1Pe9vRb2NDj49Dy1CPqRXPb7j9HK9px0ZPXfJ47zK+Iw9FJ+BvOnDzb1ohQ2+cigSPvgm1r2Ju4o9uiiEvQ1w3T3TxkU8xjWqvS14kz0QtT48UxwYvWR9aT3Chjw9nrA/PfcUv71ehQa9tuLxvJE6BD4dOru8UTaJO5lgP7x2ka69vooxvF6Ooz3ZXOE9kcEQPawlCL7ll+Q822w3vXtQM 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 2LRGPW2OjT0tVAi9fWOJPbZTur22UpM9vwMJPYUX8jx6nca9b4SrvSugkDwpGbA9ZAQsvQY2yT27Gau9M6EcPbcD1D21gx09DkmXPHhIFT7C2q69LRqfPcRc0T3WM1a9Nwiuu9stZj1vt8093AUIPvMqAr1+4HA9dQ8uvppbBDwgprk9SZqXPc4KoD3z5pI93tIcvgfyjj0jvUY9eQKOPC5H2L1LcLC9ScpgPV0ULb1Sq2q95nsLPfDtt70XHl09XVTWPZL0dD3Qa/C6GykBPqMmEb6EGI09u8yYPXhoez1r3oq8xqHfvMWfOz0d2wI95E1+vZquJT0N+xC+iuqyPWErND2I14i7HYGrPFxldj04KQ6+AbMCPns1nj2tIAy9XWxUvci+CT3GrNE9GjAEPlCyGbynGeg9AkvavcEq6jwVN5Y9DtNGPWh4CjwF9FM9j7IEvsZa/z1QCGU9FRk+vH/CF76Feka9cRUGPmK4oL1OlGa9U7asPThNw71dYoE9VotEPVRpM 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 +bSRvnuvWTwR9RQ+gTI6vuGGAD+YOV+/ybB9P503Wr+h4CS/Z1+qvhjqDT+2xPU+8GMqP6aXAj6SvnQ/W8+jvzycGD2BS+Y+oJKmvrphz75YhLO/+hsIP/8z4T6YFLy+4LcKvw==", "training_traits": {"structure_gen": "Triangle", "n_layers": 8, "max_nodes": 16, "activation_func": "LeakyReLU", "epoch_num": 6}, "classes_name": ["Cryptoadz", "Cryptopunks", "Moonbirds", "Nouns"]},m=25,b=50,y=59+11/12,w=59+11.5/12,v=60;function z(e,t){const n=Math.log(1-t)/Math.log(1-e);return e=>1-Math.pow(1-e,n)}class V{constructor(e,t,n){const{model:r,inputDim:i}=j(t,n);thisM .model=r,this.inputDim=i,this.iteration=0,this.stage=0;const o=new Date(parseInt(e.birthYear),0,1).getTime(),a=new Date(parseInt(e.birthYear)+1,0,1).getTime();this.birthDate=new Date(Math.floor((o+a)/2));const l=zr.filter((t=>t[0]==e.lifeCycle))[0][2];this.growSpeed=365/l,this.cycleLength=60*l*24*3600*1e3,this.growthFunc=z(.4,.8)}updateAge(e){const t=(e.getTime()-this.birthDate.getTime())/31536e6*this.growSpeed;this.iteration=Math.floor(t/60);const n=t-60*this.iteration;let r;this.age=n;let i,o=0;if(n<25){let e=mapM (n,0,25,0,1);o=this.growthFunc(e),r=(25-n)/60,this.stage=1,this.stageRatio=map(n,0,25,0,1)}else n<50?(o=1,r=(50-n)/60,this.stage=2,this.stageRatio=map(n,25,50,0,1)):n<y?(o=map(n,50,y,1,0),r=(y-n)/60,this.stage=3,this.stageRatio=map(n,50,y,0,1)):n<w?(o=0,r=(w-n)/60,this.stage=4,this.stageRatio=map(n,y,w,0,1)):n<60&&(o=0,r=(60-n)/60,this.stage=5,this.stageRatio=map(n,w,60,0,1));n<50?i=map(n,0,50,0,780/880):n<w?i=map(n,50,w,780/880,800/880):n<60&&(i=map(n,w,60,800/880,1)),this.nextStateTimestamp=Math.round(e.getTime()M +this.cycleLength*r),this.statePercentage=round(100*i);let a=(25-n)/60;a<0&&(a+=1),this.nextStableTimestamp=Math.round(e.getTime()+this.cycleLength*a),this.growth=o,this.model.updateNeurons(o,this.iteration)}getBrainStatus(){return{totalNeurons:this.model.getTotalNeurons(),neuronsLife:this.model.getNeuronsLife(),stage:this.stage,inputDim:this.inputDim,stageRatio:this.stageRatio,age:this.age,growth:this.growth,nextStateTimestamp:this.nextStateTimestamp,nextStableTimestamp:this.nextStableTimestamp,rebirthCount:max(thM is.iteration,0),statePercentage:this.statePercentage}}classifyImage(e){const t=new G(e,1,e.length);return this.model.forward(t).mat[0]}}class M{constructor(e,t,n,r,i){this.p=e,this.v=t,this.size=n,this.shape=i,this.col=r}getRadius(){return 1==Oe?1*this.size/2:2==Oe?7*this.size/16:3==Oe||4==Oe?4*this.size/7:0}update(){this.p.add(this.v)}draw(e,t,n,r){const i=this.p.x*r,o=this.p.y*r,a=this.size*r,{col:l,shape:s}=this;let h,c;1==n?h=c=l:2==n?(h=dr(t,1),c=l):(h=dr(t,0),c=dr(l,1));e.stroke(dr(c,map(1,0,1,.25,1))),e.fillM (dr(h,map(1,0,1,.15,1))),3==n&&e.fill(dr(h,0)),1==s?e.ellipse(i,o,a,a):2==s?e.rect(i,o,7*a/8,7*a/8):3==s&&(e.beginShape(),e.vertex(i-4*a/7,o),e.vertex(i,o-4*a/7),e.vertex(i+4*a/7,o),e.vertex(i,o+4*a/7),e.endShape(CLOSE))}}class E{constructor(e,t,n,r,i,o,a){this.center=e,this.len=t,this.angle=n,this.v=r,this.angV=i,this.c1=o,this.c2=a}getEndpoints(){const e=createVector(this.len/2*cos(this.angle),this.len/2*sin(this.angle));return[Vector.add(this.center,e),Vector.sub(this.center,e)]}update(){this.center.add(this.v),M this.angle+=this.angV}draw(e,t){const[n,r]=this.getEndpoints(),i=n.x*t,o=n.y*t,a=r.x*t,l=r.y*t,s=this.c1,h=this.c2;var c=e.drawingContext.createLinearGradient(i,o,a,l);c.addColorStop(0,s),c.addColorStop(1,h),e.drawingContext.strokeStyle=c,e.drawingContext.globalAlpha=1,e.line(i,o,a,l),e.drawingContext.globalAlpha=1}}function S(e,t){const n=random(TAU),r=random(e,t);return createVector(r*cos(n),r*sin(n))}class R{constructor(e,t,n,r,i){this.wall=n,this.maxR=i;const o=t.length;this.nodes=[];for(let a=0;a<o;++a){const M o=[],l=.25*t[a];for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),l=S(.02*i,.05*i),s=random(10,25)*i;o.push(new M(t,l,s,e[a],r))}this.nodes.push(o)}const a=A(e);a.unshift(e[0]),a.push(e[e.length-1]),this.lines=[];for(let e=0;e<=o;++e){const r=[],l=(0==e?1:t[e-1])*(e==o?1:t[e])*1.5;for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),o=random(5*i,10*i),l=random(TAU),s=S(.02*i,.05*i),h=random(2e-4,.001);r.push(new E(t,o,l,s,h,a[e],a[e+M 1]))}this.lines.push(r)}}reflectNode(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,{p:o,v:a}=e,l=e.getRadius();(o.x-l<t&&a.x<0||o.x+l>r&&a.x>0)&&(a.x=-a.x),(o.y-l<n&&a.y<0||o.y+l>i&&a.y>0)&&(a.y=-a.y)}reflectLine(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,[o,a]=e.getEndpoints(),l=e.v;(min(o.x,a.x)<t&&l.x<0||max(o.x,a.x)>r&&l.x>0)&&(l.x=-l.x),(min(o.y,a.y)<n&&l.y<0||max(o.y,a.y)>i&&l.y>0)&&(l.y=-l.y)}update(){for(const e of this.lines)for(const t of e)t.update(),this.reflectLine(t);for(const e of M this.nodes)for(const t of e)t.update(),this.reflectNode(t)}draw(e,t,n,r,i){const o=i/this.maxR;for(const t of this.lines){const n=t.length*r;for(let r=0;r<n;++r)t[r].draw(e,o)}for(const i of this.nodes){const a=i.length*r;for(let r=0;r<a;++r)i[r].draw(e,t,n,o)}}}function I(e,t){re(e),e.fill(0),e.rect(0,0,500,500),ie(e),e.noStroke(),e.fill(dr(cr("#000000"),.5)),e.push(),e.translate(250,250),e.scale(t),e.translate(-250,-250),e.beginShape(),e.vertex(235.2,24.9),e.bezierVertex(215,24.6,185,11.4,164.8,11),e.bezierVertexM (147.2,10.7,129.3,10.4,112.2,14.7),e.bezierVertex(95.1,19,78.5,28.5,69.6,43.8),e.bezierVertex(57.699,64.199,61.599,90.199,70.199,112.2),e.bezierVertex(78.799,134.2,91.6,154.6,97.199,177.5),e.bezierVertex(102.499,199.2,100.899,222.5,92.799,243.2),e.bezierVertex(83,268,64.6,288.3,48.9,310),e.bezierVertex(33.2,331.7,24.5,337.5,26.599,364.1),e.bezierVertex(28.2,384.1,61.399,404.2,75.7,418.3),e.bezierVertex(90,432.4,73.7,488.2,91.9,496.7),e.bezierVertex(124.2,511.6,159,472.5,194.3,468.1),e.bezierVertex(211.6,465.9,267.4M ,501.5,283.9,495.9),e.bezierVertex(340.7,476.7,298.599,428.9,355.4,409.7),e.bezierVertex(370.799,404.5,454.5,407.6,464.4,394.8),e.bezierVertex(478.599,376.3,474.7,349.3,464.299,328.4),e.bezierVertex(453.9,307.5,438.099,289.5,428.699,268.2),e.bezierVertex(412,230,419,182.6,446.1,150.9),e.bezierVertex(449.7,146.7,453.6,142.7,455.8,137.6),e.bezierVertex(459.4,129.299,457.5,119.6,454.8,111),e.bezierVertex(443.2,73.4,417.3,40.4,383.6,20.299),e.bezierVertex(358.1,5,343.2,-.4,313.5,0),e.bezierVertex(287.5,.4,261.6,25.4,23M 5.2,24.9),e.endShape(),e.pop()}function C(e,t,n,r,i,o){let a,l,s;re(t),t.fill(0),t.rect(0,0,500,500),ie(t),t.noStroke(),t.fill(dr(n,.5)),1==i?(l=0,s=25,a=map(o,0,25,500,0)):a=0,t.rect(0,a,500,500),e.noStroke(),e.fill(r),e.rect(0,0,500,500),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,25M 0.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertexM (77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierM Vertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),e.fill(n),e.begiM nShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,3M 73.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(1M 54.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVM ertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),re(e),e.fill(r),e.beginShape(),e.vertex(184.3,473.2),e.bezierVertex(164,473.2,144.7,462.099,134,444.3),e.bezierVertex(131.7,440.5,129.1,438.5,125,437.1),e.bezierVertex(97.3,428.1,80.5,400.6,85.2,371.8),e.bezierVertex(86.3,365.1,85.8,364.1,79.9,361.2),e.bezierVerM tex(57.2,349.8,46.2,323.3,54.3,299.7),e.bezierVertex(54.7,298.599,55.1,297.7,55.5,296.9),e.bezierVertex(55.6,296.599,55.8,296.4,55.9,296.099),e.vertex(57.9,291.499),e.vertex(62.5,293.599),e.bezierVertex(64.9,294.7,67.3,295.799,69.5,296.9),e.bezierVertex(74.5,299.299,79.1,301.599,83.9,303.099),e.bezierVertex(89.8,304.9,96.5,305.499,102.7,305.9),e.bezierVertex(102.8,305.9,102.9,305.9,103,305.9),e.bezierVertex(106.6,305.9,108.9,302.799,109,299.799),e.bezierVertex(109.1,296.199,106.6,293.4,102.7,292.799),e.bezierVertexM (101.3,292.599,99.9,292.4,98.4,292.299),e.bezierVertex(94.3,291.799,90.1,291.299,86,289.9),e.bezierVertex(68.9,284,56.5,270.2,52.7,252.799),e.bezierVertex(48.9,235.499,54.5,217.7,67.6,205.299),e.bezierVertex(71.9,201.299,72.7,198.1,70.8,192.399),e.bezierVertex(64.2,172.2,68.8,153.99,84.2,139.599),e.bezierVertex(94.2,130.199,105.5,125.399,117.8,125.399),e.bezierVertex(124.3,125.399,131.1,126.799,137.8,129.599),e.bezierVertex(157,137.399,167.9,152.799,169.4,173.99),e.vertex(169.4,174.399),e.bezierVertex(169.5,175.899M ,169.6,177.2,169.9,178.299),e.bezierVertex(170.7,181.2,173.2,183.2,176.1,183.2),e.bezierVertex(176.299,183.2,176.5,183.2,176.7,183.2),e.bezierVertex(180.1,182.899,182.6,180.299,182.7,177),e.bezierVertex(183.1,162,178.299,148.2,168.399,136.1),e.bezierVertex(158.2,123.5,144.899,115.8,128.799,113.199),e.bezierVertex(123.499,112.299,120.399,109.799,118.899,104.99),e.bezierVertex(113.899,89.699,120.699,72.299,134.899,64.499),e.bezierVertex(139.99,61.699,145.799,60.199,151.7,60.199),e.bezierVertex(162.2,60.199,171.899,64M .799,178.1,72.699),e.bezierVertex(179.6,74.6,180.799,76.6,181.9,78.499),e.vertex(182.2,79.099),e.bezierVertex(183.2,80.699,185.2,83.299,188.4,83.299),e.bezierVertex(189.5,83.299,190.6,82.99,191.7,82.399),e.bezierVertex(195.1,80.599,196,76.99,194,72.799),e.bezierVertex(190.1,64.799,184.1,58.499,175.6,53.299),e.bezierVertex(174.6,52.699,173.7,52.099,172.5,51.499),e.vertex(170.5,50.299),e.vertex(163,45.899),e.vertex(170.5,41.599),e.bezierVertex(182,34.99,193.1,30.799,204.4,28.599),e.bezierVertex(208.6,27.799,212.9,27.M 399,217.2,27.399),e.bezierVertex(217.6,27.399,217.9,27.399,218.3,27.399),e.bezierVertex(231.4,27.599,242.7,38.199,243,50.599),e.bezierVertex(243.4,64.899,243.3,78.99,243.2,93.799),e.bezierVertex(243.2,99.799,243.1,105.899,243.1,112.099),e.vertex(243.1,119.199),e.vertex(236.4,116.799),e.bezierVertex(235.7,116.499,235,116.299,234.4,115.99),e.bezierVertex(233.4,115.599,232.6,115.299,232,115.199),e.bezierVertex(230.6,114.899,229.2,114.599,227.8,114.299),e.bezierVertex(223.8,113.499,220.1,112.699,216.4,112.499),e.vertexM (216.2,112.499),e.bezierVertex(212.5,112.499,210.7,115.599,210.6,118.599),e.bezierVertex(210.4,122.399,212.7,125.099,216.4,125.399),e.bezierVertex(230.1,126.399,238.9,133.099,242.3,145.199),e.bezierVertex(243.2,148.399,243.2,151.599,243.2,154.499),e.vertex(243.2,155.099),e.bezierVertex(243.2,254.199,243.2,330,243.2,400.599),e.bezierVertex(243.2,401.99,243.2,403.4,243.2,404.9),e.bezierVertex(243.3,411.099,243.3,417.599,242.3,423.9),e.bezierVertex(238.1,449.2,219.6,467.799,194,472.5),e.bezierVertex(190.9,472.9,187.6,M 473.2,184.3,473.2),e.endShape(),e.beginShape(),e.vertex(315.8,473.1),e.bezierVertex(309.3,473.1,302.8,472,296.5,469.9),e.bezierVertex(270.4,461,253.8,434.9,257.1,407.9),e.bezierVertex(260,384,273.8,366.8,297,358.3),e.bezierVertex(297.7,358.1,298.3,357.8,299,357.6),e.bezierVertex(299.8,357.3,300.6,357.1,301.2,356.8),e.bezierVertex(304.3,355.4,306,351.8,304.9,348.7),e.bezierVertex(304,345.9,301.7,344.2,299,344.2),e.bezierVertex(298.6,344.2,298.1,344.2,297.6,344.3),e.bezierVertex(288.1,346.3,279,350.9,269.7,358.3),e.bM ezierVertex(268.9,358.9,268.1,359.6,267.2,360.4),e.vertex(265.5,361.8),e.vertex(258.5,367.6),e.vertex(257.4,358.6),e.bezierVertex(257.3,358,257.3,357.5,257.2,357.1),e.bezierVertex(257,356,256.9,354.9,256.9,353.7),e.bezierVertex(256.9,334.8,256.9,316,256.9,297.1),e.bezierVertex(256.9,260.3,256.9,222.3,256.8,185),e.bezierVertex(256.8,170.7,268.3,158.8,282.5,158.4),e.bezierVertex(284.8,158.3,286.7,157.6,287.9,156.2),e.bezierVertex(289.099,154.9,289.599,153.2,289.5,151.3),e.bezierVertex(289.3,147.5,286.7,145.1,282.7,14M 5.1),e.bezierVertex(282.5,145.1,282.2,145.1,282,145.1),e.bezierVertex(278.8,145.3,275.5,146.1,272,146.9),e.bezierVertex(270.9,147.2,269.8,147.4,268.6,147.7),e.bezierVertex(267.9,147.9,267,148.2,265.8,148.7),e.bezierVertex(265.1,149,264.4,149.3,263.5,149.6),e.vertex(256.8,152),e.vertex(256.8,114.6),e.bezierVertex(256.8,95,256.8,75.4,256.8,55.9),e.bezierVertex(256.8,38,267.2,27.3,284.6,27.3),e.bezierVertex(285.3,27.3,285.9,27.3,286.6,27.3),e.bezierVertex(299,27.9,318.7,34.5,329.6,41.9),e.vertex(336.1,46.3),e.vertex(3M 24.4,53.3),e.bezierVertex(316.2,58.2,310.2,64.6,306,72.9),e.bezierVertex(304.2,76.4,305.1,78.5,306.1,80),e.bezierVertex(307.4,81.9,309.4,83,311.6,83),e.bezierVertex(313.7,83,315.7,81.9,317.1,80.1),e.bezierVertex(317.4,79.7,317.8,79,318.1,78.4),e.bezierVertex(318.4,77.9,318.7,77.3,319,76.8),e.bezierVertex(325.3,66.2,336.3,59.9,348.5,59.9),e.bezierVertex(353.2,59.9,357.8,60.8,362.1,62.7),e.bezierVertex(377.6,69.3,386,86.7,381.7,103.2),e.bezierVertex(380.7,107.1,378.5,111.8,371.1,113.1),e.bezierVertex(342.7,118.1,322.M 2,139.1,317.8,167.8),e.bezierVertex(317.4,170.3,317.3,173.2,317.4,176.5),e.bezierVertex(317.5,180,320.1,182.8,323.5,183),e.bezierVertex(323.6,183,323.8,183,323.9,183),e.bezierVertex(327.1,183,329.8,180.6,330.3,177.2),e.bezierVertex(330.6,175.7,330.7,174,330.9,172.3),e.bezierVertex(331.1,169.8,331.4,167.3,332,164.7),e.bezierVertex(337.3,141.9,357.7,125.4,380.7,125.4),e.bezierVertex(382.5,125.4,384.3,125.5,386.1,125.7),e.bezierVertex(412.8,128.9,432.6,150.9,432,176.9),e.bezierVertex(431.9,182.3,430.9,187.7,429.1,192.M 7),e.bezierVertex(427.2,197.9,428,201,432.3,205),e.bezierVertex(446.8,218.7,451.8,236,446.6,255),e.bezierVertex(441.4,274,428.3,286.5,408.7,291.3),e.bezierVertex(406.1,291.9,403.6,292.1,401.1,292.3),e.bezierVertex(400,292.4,398.9,292.5,397.9,292.6),e.bezierVertex(393.6,293.1,390.9,295.7,391,299.5),e.bezierVertex(391.1,303.4,394,305.8,398.5,305.8),e.bezierVertex(409.9,305.8,420.8,302.6,431.1,296.4),e.bezierVertex(431.8,296,432.5,295.5,433.2,295.1),e.bezierVertex(433.8,294.7,434.5,294.3,435.2,293.9),e.bezierVertex(43M 6,293.4,436.6,293.2,437.2,293.1),e.bezierVertex(437.4,293,437.7,292.9,438.1,292.8),e.vertex(442.5,291.4),e.vertex(444.2,295.7),e.bezierVertex(450.9,312.4,449.5,328.4,440,343.4),e.bezierVertex(435.3,350.8,428.7,356.7,420.2,361.1),e.bezierVertex(414.3,364.1,413.7,365.2,414.8,371.7),e.bezierVertex(419.5,400.2,403,427.6,375.6,436.9),e.bezierVertex(371,438.5,368.3,440.7,365.8,444.7),e.bezierVertex(355.2,462.5,336.4,473.1,315.8,473.1),e.bezierVertex(315.8,473.1,315.8,473.1,315.8,473.1),e.endShape(),ie(e),e.fill(n),e.begiM nShape(),e.vertex(120.2,279.9),e.bezierVertex(117.9,279.9,112.4,279.299,112.2,273.599),e.bezierVertex(112,267.7,117.4,266.7,119.7,266.599),e.bezierVertex(133.1,265.799,143.1,259.499,149.3,247.899),e.bezierVertex(149.6,247.299,150.1,246.399,150.3,245.399),e.bezierVertex(150.6,244.299,150.5,243.299,150.5,242.7),e.bezierVertex(150.5,242.6,150.5,242.5,150.5,242.299),e.vertex(150.3,238.799),e.vertex(141.1,235.99),e.bezierVertex(114.6,227.799,95.6,202.499,95.9,175.799),e.bezierVertex(95.9,173.99,96.4,168.199,102.2,168.19M 9),e.bezierVertex(102.6,168.199,103,168.199,103.4,168.299),e.bezierVertex(104.8,168.499,108.2,168.899,109.2,175.599),e.bezierVertex(109.3,176.599,109.5,177.599,109.6,178.499),e.bezierVertex(110.4,184.199,111.3,189.99,113.7,195.499),e.bezierVertex(121.9,213.99,139.5,225.499,159.7,225.499),e.bezierVertex(172.1,225.499,184.1,220.899,193.5,212.599),e.bezierVertex(194,212.199,194.4,211.799,194.8,211.399),e.bezierVertex(195.1,211.099,195.5,210.799,195.8,210.399),e.bezierVertex(197.4,208.99,199.2,208.2,200.9,208.2),e.beziM erVertex(202.5,208.2,204,208.899,205.3,210.1),e.bezierVertex(208,212.9,207.9,216.9,205,219.9),e.bezierVertex(196.5,228.6,186.3,234.3,174.7,236.8),e.bezierVertex(168.799,238.1,165.6,241,163.899,246.7),e.bezierVertex(158.3,265.9,139.9,279.7,120.2,279.9),e.vertex(120.2,279.9),e.endShape(),e.beginShape(),e.vertex(187.2,427.5),e.bezierVertex(183.799,427.5,181.299,425.3,180.799,422),e.bezierVertex(180.6,420.8,180.499,419.5,180.399,418.1),e.bezierVertex(180.299,417,180.2,415.8,180.099,414.7),e.bezierVertex(177.199,390.5,1M 56.699,371.3,132.399,370.2),e.bezierVertex(131.99,370.2,131.499,370.2,131.099,370.2),e.bezierVertex(130.699,370.2,130.299,370.2,129.799,370.2),e.bezierVertex(125.99,369.9,123.199,367.2,123.099,363.6),e.bezierVertex(122.99,360.2,125.799,357.3,129.599,356.9),e.bezierVertex(130.499,356.8,131.499,356.8,132.599,356.7),e.bezierVertex(133.199,356.7,133.799,356.7,134.399,356.6),e.vertex(138.299,356.4),e.vertex(139.1,352.6),e.bezierVertex(139.5,350.7,139.799,348.9,140.2,347),e.bezierVertex(140.899,343.4,141.5,340,142.399,33M 6.8),e.bezierVertex(150.099,310.7,174.399,292,201.399,291.3),e.vertex(201.599,291.3),e.bezierVertex(203.699,291.3,206.299,292,208.299,293.2),e.bezierVertex(210.499,294.5,210.699,297.5,209.99,299.8),e.bezierVertex(209.499,301.5,208.199,303.9,203.299,304.7),e.bezierVertex(202.199,304.9,200.99,305,199.799,305.2),e.bezierVertex(194.499,305.9,188.99,306.599,183.799,308.9),e.bezierVertex(165.499,316.799,155.199,331.299,152.99,352),e.bezierVertex(152.399,357.8,154.499,361.7,159.699,364.5),e.bezierVertex(178.199,374.4,189.M 399,390,193.099,410.9),e.bezierVertex(193.699,414.299,193.899,418,193.599,422),e.bezierVertex(193.399,425.2,190.899,427.5,187.399,427.5),e.vertex(187.2,427.5),e.endShape(),e.beginShape(),e.vertex(364.3,281.1),e.bezierVertex(346.3,280.6,332.9,272.8,323.5,257),e.bezierVertex(321.6,253.9,320.4,250.2,319.2,246.7),e.bezierVertex(317.7,242.2,315,239.799,310.5,238.799),e.bezierVertex(298.5,236.299,288,230.7,279.4,222.1),e.bezierVertex(276.7,219.4,274.9,215.299,278,211.9),e.bezierVertex(279.4,210.3,281,209.6,282.6,209.6),eM .bezierVertex(284.4,209.6,286.4,210.6,288.3,212.5),e.bezierVertex(297.8,221.8,310.4,226.9,323.9,226.9),e.bezierVertex(340.2,226.9,355.1,219.3,364.8,206.2),e.bezierVertex(371,197.8,374.2,188.5,374.5,178.5),e.vertex(374.5,177.9),e.bezierVertex(374.5,177,374.5,176.1,374.7,175.4),e.bezierVertex(375.3,171.8,377.9,169.5,381.3,169.5),e.bezierVertex(381.4,169.5,381.5,169.5,381.7,169.5),e.bezierVertex(385.4,169.7,388,172.4,388,176.1),e.bezierVertex(388.1,190.7,383.4,204,374.2,215.8),e.bezierVertex(365.8,226.5,354.7,233.9,34M 1.2,237.9),e.bezierVertex(340,238.3,338.7,238.6,337.3,239.1),e.bezierVertex(335.9,239.6,335.1,240.4,334.7,240.9),e.bezierVertex(334.599,241,334.5,241.1,334.4,241.2),e.vertex(331.799,243.6),e.vertex(333.199,246.8),e.bezierVertex(338.199,258,346.799,264.9,358.699,267.3),e.bezierVertex(360.199,267.6,361.599,267.7,362.99,267.9),e.bezierVertex(363.599,268,364.299,268,364.899,268.1),e.bezierVertex(369.099,268.6,371.799,271.4,371.499,275),e.bezierVertex(371.199,278.6,368.299,281.2,364.399,281.2),e.vertex(364.3,281.1),e.enM dShape(),e.beginShape(),e.vertex(323.9,437),e.bezierVertex(323.7,437,323.5,437,323.299,437),e.bezierVertex(319.599,436.7,317.299,434.1,317.4,430.2),e.bezierVertex(317.9,406.099,328.299,388,349.5,375),e.bezierVertex(350.7,374.2,352,373.5,353.4,372.8),e.bezierVertex(354.099,372.4,354.7,372.1,355.299,371.7),e.vertex(357.499,370.5),e.vertex(357.799,368),e.bezierVertex(360.4,346.6,345.199,323.7,323.9,317),e.bezierVertex(319.099,315.5,314.099,314.9,309.299,314.4),e.vertex(308.199,314.299),e.bezierVertex(305.99,314.099,30M 0.799,312.9,300.899,307.299),e.bezierVertex(300.99,303.499,303.899,300.9,308.099,300.9),e.vertex(308.299,300.9),e.bezierVertex(327.099,301.299,343.099,308.7,355.699,322.9),e.bezierVertex(364.299,332.5,369.399,344.099,370.99,357.299),e.bezierVertex(371.099,358.4,371.299,359.4,371.499,360.499),e.bezierVertex(371.599,360.99,371.699,361.499,371.799,361.99),e.vertex(372.499,365.899),e.vertex(377.899,366.199),e.bezierVertex(378.799,366.299,379.699,366.299,380.599,366.399),e.bezierVertex(385.099,366.699,387.899,369.399,38M 7.799,373.299),e.bezierVertex(387.699,377.099,384.99,379.599,380.799,379.799),e.bezierVertex(369.799,380.199,359.99,383.299,351.899,389.299),e.bezierVertex(338.799,398.799,331.699,411.699,330.699,427.499),e.vertex(330.699,428.299),e.bezierVertex(330.599,429.199,330.599,430.099,330.499,430.799),e.bezierVertex(330,434.7,327.5,437,323.9,437),e.endShape()}function T(e){return e[0].map(((t,n)=>e.map((e=>e[n]))))}function A(e){return e.map((e=>Array.isArray(e)?A(e):e))}function D(e,t){return floor(random(e,t))}function kM (e){let t=0;for(const n of e)t+=n[1];let n=random(t),r=0;for(const t of e)if(r+=t[1],n<r)return t[0];return null}function L(e){for(let t=1;t<e.length;++t){let n=D(0,t),r=e[t];e[t]=e[n],e[n]=r}}function P(e){return null==e||""===e}function O(e){return new Promise((t=>setTimeout(t,e)))}function F(e,t,n){let r=0;for(let i=1;i<=1e3;++i)for(let o=1;o<=1e3;++o)if(e*o%(t*i)==0){let e=1*i/o;abs(e-n)<abs(r-n)&&(r=e)}return r}function N(){let e=60*(new Date).getTimezoneOffset()*1e3;return new Date(Date.now()-e).toISOString()M .slice(0,-1)}function B(e,t,n){let r;if(push(),textSize(e),textWidth(t)<=n)r=t;else for(let e=0;e<t.length;++e){const i=t.slice(0,e+1)+"...";if(textWidth(i)>n){r=i;break}}return pop(),r}function Y(e){var t=e%10,n=e%100;return 1==t&&11!=n?e+"st":2==t&&12!=n?e+"nd":3==t&&13!=n?e+"rd":e+"th"}class G{constructor(e,t,n){this.n=t,this.m=n,this.mat=[];let r=0;for(let t=0;t<this.n;++t){this.mat.push([]);for(let n=0;n<this.m;++n)this.mat[t].push(r<e.length?e[r]:0),r+=1}return this}copy(){return new G(this.mat.flat(),this.n,M this.m)}}class H{static __linear=e=>e;static __relu=e=>Math.max(e,0);static __leaky_relu=e=>e>0?e:.2*e;static __sigmoid=e=>1/(1+Math.exp(-e));static __tanh=e=>Math.tanh(e);static __apply_unary_op(e,t){const n=e.copy();for(let e=0;e<n.n;++e)for(let r=0;r<n.m;++r)n.mat[e][r]=t(n.mat[e][r]);return n}static linear=e=>H.__apply_unary_op(e,H.__linear);static relu=e=>H.__apply_unary_op(e,H.__relu);static leaky_relu=e=>H.__apply_unary_op(e,H.__leaky_relu);static sigmoid=e=>H.__apply_unary_op(e,H.__sigmoid);static tanh=e=>HM .__apply_unary_op(e,H.__tanh);static __add=(e,t)=>e+t;static __mul=(e,t)=>e*t;static __apply_binary_op=(e,t,n)=>{"object"!=typeof t&&(t=new G([t],1,1));const r=e.copy();for(let e=0;e<r.n;++e)for(let i=0;i<r.m;++i)r.mat[e][i]=n(r.mat[e][i],t.mat[e%t.n][i%t.m]);return r};static mul=(e,t)=>H.__apply_binary_op(e,t,H.__mul);static add=(e,t)=>H.__apply_binary_op(e,t,H.__add);static matMul(e,t){const n=new G([],e.n,t.m);for(let r=0;r<n.n;++r)for(let i=0;i<n.m;++i)for(let o=0;o<e.m;++o)n.mat[r][i]+=e.mat[r][o]*t.mat[o][i];M return n}static softmax(e){const t=H.__apply_unary_op(e,(e=>Math.exp(e))),n=t.mat.flat().reduce(((e,t)=>e+t));for(let r=0;r<e.n;++r)for(let i=0;i<e.m;++i)t.mat[r][i]/=n;return t}}class ${constructor(e,t){this.scale=e,this.offset=t}forward(e){return H.add(H.mul(e,this.scale),this.offset)}}class X{constructor(){}forward(e){return e.map((e=>e.flat()))}}class W{constructor(e,t,n,r){this.out_dim=e,this.activation=t,this.w=n,this.b=r}forward(e){const t=H.add(H.matMul(e,this.w),this.b);return null==this.activation?t:this.M activation(t)}}class U{constructor(e,t,n){this.preprocessLayers=e,this.hiddenLayers=t,this.outputLayer=n,this.totalNeurons=this.hiddenLayers.map((e=>e.out_dim)),this.currentOrders=[],this.currentIteration=null}updateNeurons(e,t){if(t!=this.currentIteration){this.currentOrders=[];for(let e=0;e<this.totalNeurons.length;++e){randomSeed(100*(t+1)+e);const n=[];for(let t=0;t<this.totalNeurons[e];++t)n.push(t);L(n),this.currentOrders.push(n)}this.currentIteration=t}const n=A(this.totalNeurons),r=n.reduce(((e,t)=>e+t))*(1M -e);for(let e=0;e<r;++e){const t=n.map(((e,t)=>(e-1)/this.totalNeurons[t]));n[t.map(((e,t)=>[e,t])).reduce(((e,t)=>t[0]>e[0]?t:e))[1]]-=Math.min(r-e,1)}this.neuronsLife=[];for(let e=0;e<n.length;++e){const t=this.currentOrders[e],r=Array(this.totalNeurons[e]).fill(0);for(let i=0;i<n[e];++i)r[t[i]]=Math.min(n[e]-i,1);this.neuronsLife.push(r)}}getTotalNeurons(){return A(this.totalNeurons)}getNeuronsLife(){return A(this.neuronsLife)}forward(e){for(const t of this.preprocessLayers)e=t.forward(e);for(const[t,n]of this.hM iddenLayers.entries()){e=n.forward(e);const r=new G(this.neuronsLife[t],1,e.m);e=H.mul(e,r)}return e=this.outputLayer.forward(e),H.softmax(e)}}function q(e){switch(e){case"relu":return H.relu;case"sigmoid":return H.sigmoid;case"tanh":return H.tanh;case"leaky_relu":return H.leaky_relu;default:return H.linear}}function j(e,t){const n=[],r=[],i=Z(t);let o=null,a=0,l=[];for(const t of e.config.layers)if("InputLayer"==t.class_name)o=t.config.batch_input_shape.slice(1),l=o;else if("Rescaling"==t.class_name)n.push(new $(tM .config.scale,t.config.offset));else if("Flatten"==t.class_name)o=[o.reduce(((e,t)=>e*t))];else if("Dense"==t.class_name){const e=[t.config.units],n=o[0]*e[0],l=e[0],s=i.subarray(a,a+n);a+=n;const h=i.subarray(a,a+l);a+=l;const c=new G(s,o[0],e[0]),u=new G(h,1,e[0]),f=q(t.config.activation);r.push(new W(e[0],f,c,u)),o=e}const s=r.pop();return{model:new U(n,r,s),inputDim:l}}function Z(e){const t=window.atob(e),n=t.length/Float32Array.BYTES_PER_ELEMENT,r=new DataView(new ArrayBuffer(Float32Array.BYTES_PER_ELEMENT)),iM =new Float32Array(n);let o=0;for(let e=0;e<n;e++){o=4*e;for(let e=0;e<4;++e)r.setUint8(e,t.charCodeAt(o+e));i[e]=r.getFloat32(0,!0)}return i}class K{constructor(e){this.elt=e,this._events={},this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight}position(){if(0===arguments.length)return{x:this.elt.offsetLeft,y:this.elt.offsetTop};var e="absolute";return"static"!==arguments[2]&&"fixed"!==arguments[2]&&"relative"!==arguments[2]&&"sticky"!==arguments[2]&&"initial"!==arguments[2]&&"inherit"!==arguments[2]||(M e=arguments[2]),this.elt.style.position=e,this.elt.style.left=arguments[0]+"px",this.elt.style.top=arguments[1]+"px",this.x=arguments[0],this.y=arguments[1],this}show(){return this.elt.style.display="block",this}hide(){return this.elt.style.display="none",this}size(e,t){if(0===arguments.length)return{width:this.elt.offsetWidth,height:this.elt.offsetHeight};var n=e,r=t;if(n!==te||r!==te){if(n===te?n=t*this.width/this.height:r===te&&(r=e*this.height/this.width),this.elt instanceof HTMLCanvasElement){var i,o={},a=thisM .elt.getContext("2d");for(i in a)o[i]=a[i];for(i in this.elt.setAttribute("width",n*this._pInst._pixelDensity),this.elt.setAttribute("height",r*this._pInst._pixelDensity),this.elt.style.width=n+"px",this.elt.style.height=r+"px",this._pInst.scale(this._pInst._pixelDensity,this._pInst._pixelDensity),o)this.elt.getContext("2d")[i]=o[i]}else this.elt.style.width=n+"px",this.elt.style.height=r+"px",this.elt.width=n,this.elt.height=r;this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight,this._pInst&&this._pInM st._curElement&&this._pInst._curElement.elt===this.elt&&(this._pInst._setProperty("width",this.elt.offsetWidth),this._pInst._setProperty("height",this.elt.offsetHeight))}return this}style(e,t){if(t instanceof Color&&(t="rgba("+t.levels[0]+","+t.levels[1]+","+t.levels[2]+","+t.levels[3]/255+")"),void 0===t){if(-1===e.indexOf(":"))return window.getComputedStyle(this.elt).getPropertyValue(e);for(var n=e.split(";"),r=0;r<n.length;r++){var i=n[r].split(":");i[0]&&i[1]&&(this.elt.style[i[0].trim()]=i[1].trim())}}else if(M this.elt.style[e]=t,"width"===e||"height"===e||"left"===e||"top"===e){var o=window.getComputedStyle(this.elt).getPropertyValue(e).replace(/[^\d.]/g,"");this[e]=Math.round(parseFloat(o,10))}return this}value(){return arguments.length>0?(this.elt.value=arguments[0],this):"range"===this.elt.type?parseFloat(this.elt.value):this.elt.value}mouseClicked(e){return this._adjustListener("click",e,this),this}isFocused(){return document.activeElement===this.elt}_adjustListener(e,t,n){return!1===t?this._detachListener(e,n):thisM ._attachListener(e,t,n),this}_attachListener(e,t,n){n._events[e]&&this._detachListener(e,n);var r=t.bind(n);n.elt.addEventListener(e,r,!1),n._events[e]=r}_detachListener(e,t){var n=t._events[e];t.elt.removeEventListener(e,n,!1),t._events[e]=null}}function J(e,t){var n=document.createElement("button");return n.innerHTML=e,t&&(n.value=t),ee(n)}function Q(e){var t=arguments.length>1&&void 0!==arguments[1]&&arguments[1],n=function(t){var n=!0,r=!1,i=void 0;try{for(var o,a=t.target.files[Symbol.iterator]();!(n=(o=a.nextM ()).done);n=!0){var l=o.value;File._load(l,e)}}catch(e){r=!0,i=e}finally{try{n||null==a.return||a.return()}finally{if(r)throw i}}};if(window.File&&window.FileReader&&window.FileList&&window.Blob){var r=document.createElement("input");return r.setAttribute("type","file"),t&&r.setAttribute("multiple",!0),r.addEventListener("change",n,!1),ee(r)}}function ee(e){return document.body.appendChild(e),new K(e)}createImg=function(){var e,t=document.createElement("img"),n=arguments;return n.length>1&&"string"==typeof n[1]&&(tM .alt=n[1]),n.length>2&&"string"==typeof n[2]&&(t.crossOrigin=n[2]),t.src=n[0],e=ee(t,this),t.addEventListener("load",(function(){e.width=t.offsetWidth||t.width,e.height=t.offsetHeight||t.height;var r=n[n.length-1];"function"==typeof r&&r(e)})),e},createInput=function(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:"",t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:"text",n=document.createElement("input");return n.setAttribute("value",e),n.setAttribute("type",t),ee(n,this)};const te="auto";fuM nction ne(e){re(e);const t=e._rectMode;e.rectMode(CORNER),e.rect(0,0,e.width,e.height),e.rectMode(t),ie(e)}function re(e){e.push(),e.fill(255,255,255,255),e.blendMode(REMOVE)}function ie(e){e.blendMode(BLEND),e.pop()}File=function(e,t){this.file=e,this._pInst=t;var n=e.type.split("/");this.type=n[0],this.subtype=n[1],this.name=e.name,this.size=e.size,this.data=void 0},File._createLoader=function(e,t){var n=new FileReader;return n.onload=function(n){var r=new File(e);if("application/json"===r.file.type)r.data=JSON.pM arse(n.target.result);else if("text/xml"===r.file.type){var i=(new DOMParser).parseFromString(n.target.result,"text/xml");r.data=new XML(i.documentElement)}else r.data=n.target.result;t(r)},n},File._load=function(e,t){if(/^text\//.test(e.type)||"application/json"===e.type)File._createLoader(e,t).readAsText(e);else if(/^(video|audio)\//.test(e.type)){var n=new File(e);n.data=URL.createObjectURL(e),t(n)}else File._createLoader(e,t).readAsDataURL(e)},XML=function(e){if(e)this.DOM=e;else{var t=document.implementation.cM reateDocument(null,"doc");this.DOM=t.createElement("root")}},document.addEventListener("DOMContentLoaded",(function(){addEventListener("mousemove",(e=>{window.mouseX=e.pageX,window.mouseY=e.pageY}))})),new e("global");const oe="579";let ae,le,se,he,ce,ue,fe,de,xe,ge,pe,me,be,ye,we,ve,ze,Ve,_e,Me,Ee,Se,Re,Ie,Ce,Te,Ae,De,ke,Le,Pe,Oe,Fe,Ne,Be,Ye,Ge,He,$e,Xe,We,Ue,qe,je,Ze,Ke,Je,Qe,et,tt,nt,rt,it,ot,at,lt,st,ht,ct,ut,ft,dt,xt,gt,pt,mt,bt,yt,wt,vt,zt,Vt,_t,Mt,Et,St,Rt,It,Ct,Tt,At=!1,Dt=!1,kt=!0,Lt=!1,Pt=!1;const Ot=[" "M ,"Growing","Stable","Decaying","Dead","Rebirth"];let Ft,Nt,Bt,Yt,Gt,Ht,$t,Xt,Wt,Ut,qt,jt,Zt,Kt,Jt,Qt,en,tn,nn,rn,on,an,ln,sn,hn=0,cn=0,un=0,fn=!1,dn=!0,xn=!0,gn=null,pn=null,mn=null,bn=!1,yn=!1,wn=null,vn=null,zn=!1;async function setup(){let e=windowWidth,t=windowHeight;createCanvas(e,t),et=createGraphics(e,t),Xe=createGraphics(e,t),$e=createGraphics(e,t),We=createGraphics(e,t),Ue=createGraphics(e,t),qe=createGraphics(e,t),Qe=createGraphics(e,t),je=createGraphics(e,t),Ze=createGraphics(e,t),Ke=createGraphics(e,t),M Je=createGraphics(e,t),tt=createGraphics(500,500),nt=createGraphics(500,500),rt=createGraphics(500,500),_n(),Mn(),Sn(),await En(),Gn(),Rn(),bn=!0}function _n(){Et=parseInt(oe),randomSeed(Et),noiseSeed(Et)}function Mn(){Wt=Ir(p.training_traits),Cr(Wt)}async function En(){let e;Jt=r(),Qt=o(),[Xt,e]=await Promise.all([s(Jt),h(Qt)]),Ut=new V(Wt.visual,e.layers_config,e.weight_b64),Ut.updateAge(new Date),_n(),Wt.training=e.training_traits,Ht=e.model_name,$t=e.classes_name}function Sn(){le=min(width,height)/1024,ut=Rr.fiM ndIndex((e=>e[0]===Wt.visual.colorPalette)),ft=[["#ffffff","#231f20","#231f20"],["#231f20","#ffffff","#ffffff"],["#104da8","#ffffff","#ffffff"],["#722F1F","#FCE1B2","#FCE1B2"],["#e88120","#f9f2e5","#f9f2e5"],["#f6b941","#2E2E2E","#2E2E2E"],["#45daaa","#012221","#012221"],["#F1F1F1","#328DFE","#328DFE"],["#111822","#D3EB8D","#D3EB8D"],["#713FF9","#D6D5E6","#D6D5E6"],["#FBDA9D","#795106","#795106"],["#8f5b62","#ead0d0","#ead0d0"],["#eae4cb","#508cac","#508cac"],["#ffc6cc","#cc313d","#cc313d"],["#60A900","#E0FE00","#EM 0FE00"],["#507DBE","#D0D1D3","#D0D1D3"],["#305848","#E8F2EE","#E8F2EE"],["#2a2634","#5b6988","#cb78a2","#5b6988"],["#590e29","#fd5e53","#fd5e53","#ffe373"],["#0a141d","#57d4e4","#328195","#2A9ECF","#0ab6a8","#57d4e4"],["#3a2d28","#d5c2ac","#df6338","#3d9895","#d5c2ac"],["#030706","#77c4d9","#77c4d9","#77c4d9","#ffffff","#ffffff","#e72020","#e72020"],["#3a4664","#92f5ff","#f9ff94","#eaa0a2","#55dde0"],["#fbfaff","#f04bb1","#f04bb1","#fac373","#82cef0","#8b31ce"],["#000000","#ffffff","#ff0002","#f26522","#fdff00","#0M 0ff03","#01fffe","#0000ff","#ff00ff"]];for(let e=0;e<ft.length;++e)for(let t=0;t<ft[e].length;++t)ft[e][t]=cr(ft[e][t]);pt=[],ct=ft[ut][0],st=ft[ut][1]}function Rn(){gn=document.querySelector("#upload"),pn=document.querySelector("#inputUpload"),gn.addEventListener("dblclick",(()=>{if(!Lt&&!yn)if(In(Ie)&&cn==Ve-1)pn.click();else{if(4!=Pe&&5!=Pe&&(In(Ie)||cn!=Ve-1))return;fn=!0,dn=!0,Bt=0,un=0}})),pn.addEventListener("click",(()=>{pn.value=null,gn.style.display="block"})),pn.addEventListener("change",(()=>{const[e]=pM n.files;e?(se=null,gn.style.display="none",Tn(URL.createObjectURL(e)),mn=e):gn.style.display="block"}))}function In(e){for(let t=0;t<e.length;++t){let n=0;for(let r=0;r<e[t].length;++r)e[t][r]>0&&++n;if(0==n)return!1}return!0}function Cn(){null!=se&&(un=0,Pt=!0,he=0,ue=0,drewLineAnim=!0,ce=(ae/2+we/2)/le,loadImage(se.elt.src,(e=>{const[t,n,r]=Gt,i=createGraphics(t,n);i.image(e,0,0,t,n),i.loadPixels();const o=i.pixels.filter(((e,t)=>t%4!=3)),a=Ut.classifyImage(o);Zt=T([a,$t.map((e=>e.toUpperCase()))]).sort(((e,t)=>eM [0]>t[0]?-1:1))})))}function Tn(e){se=createImg(e,""),se.hide(),Cn()}function An(){zn||(ce+=(width-ae-we)/tn/le),re(Xe),Xe.rect(ce*le,0,width,height),ie(Xe),un>=ge&&1==kt&&(kt=!1,un-=ge),kt&&(re($e),$e.strokeWeight(2*Fe),Jn(he,ze,ct,ct,$e),ie($e)),un>=ge&&0==kt&&(kt=!0,un-=ge,he+=1,he==en&&(++ue,he=0,ce=(ae/2+we/2)/le,1==ue&&(Pt=!1,Dn(),ye=millis())))}function Dn(){At=!0,pe=!1,me=!1,tryButton=br("Try Again",width/2-225*le,height/2+265*le,290*le,40*le,kn),closeResultButton=br("Close",width/2+75*le,height/2+265*le,15M 0*le,40*le,Ln)}function kn(){At=!1,tryButton.hide(),closeResultButton.hide(),pn.click()}function Ln(){Yt=!0,At=!1,Gn(),tryButton.hide(),closeResultButton.hide(),gn.style.display="block",se=null}function keyTyped(){bn&&!1===yn&&!1===yr()&&("i"!==key&&"I"!==key||(Dt=!Dt),"b"!==key&&"B"!==key||(xn=!xn),"s"!==key&&"S"!==key||!1!==Lt||saveCanvasAtCurrentTime(),"k"!==key&&"K"!==key||!1!==Lt||save4KCanvasAtCurrentTime(),"u"!==key&&"U"!==key||!1!==Lt||!1!==At||!1!==fn||!1!==Pt||On())}function On(){Lt=!0,wn=null,vn=null,subM mitButton=br("Submit",width/2-155*le,height/2+115*le,150*le,40*le,Fn),closeSettingButton=br("Close",width/2+5*le,height/2+115*le,150*le,40*le,Yn),vt=createInput(),vt.position(width/2-252.5*le,height/2-40*le),vt.size(500*le,25*le),vt.style("font-size","15px"),vt.value(Jt||""),zt=createInput(),zt.position(width/2-252.2*le,height/2+35*le),zt.size(500*le,25*le),zt.style("font-size","15px"),zt.value(Qt||"")}function Fn(){Vt=vt.value(),_t=zt.value(),submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide(),Lt=!1,M yn=!0,Nn()}async function Nn(){[wn,vn,_]=await Promise.all([c(Vt),u(_t),O(1e3)]),yn=!1,wn&&vn?(n(Vt),i(_t),window.location.reload()):(Lt=!0,submitButton.show(),closeSettingButton.show(),vt.show(),zt.show())}function Bn(){Je.textFont("Trebuchet MS"),Je.noStroke(),pr(Je,600*le,200*le),Je.strokeWeight(1*le),Je.stroke(xt),Je.fill(xt),Je.textSize(50*le),Je.text("update()",width/2,height/2+2.5*le)}function Yn(){wn=null,vn=null,Lt=!1,submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide()}function Gn(){_n(),nn=DM ate.now(),pe=!1,me=!1,St=Wt.training.structure_gen,Rt=Wt.visual.birthYear,It=Wt.visual.lifeCycle,Ct=Wt.training.epoch_num,Tt=Wt.training.activation_func,Ft=Mr.findIndex((e=>e[0]==Wt.visual.hardwareAcceleration))+1,1==Ft?(Nt=30,fe=40):2==Ft?(Nt=15,fe=20):(Nt=2,fe=10);const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$stateM Percentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),ae=100*le,ht=50*le,Oe=Sr.findIndex((e=>e[0]==Wt.visual.nodeShape))+1,dt=Er.findIndex((e=>e[0]==Wt.visual.nodeFill))+1,lt=_r.findIndex((e=>e[0]==Wt.visual.pattern))+1,de=Math.tanh(Math.log10(Xt.avgfeerate)),de=map(de,0,1,.2,.8),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(lM et e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)M 0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=M floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,at=.7,pt=[],xt=ft[ut][2],gt=ft[ut][ft[ut].length-1];for(let e=3;e<ft[ut].length-1;e++)pt.push(ft[ut][e]);mt=sr(xt,gt,pt,width),bt=[],wt=[],yt=width/(Ve-1);for(let e=0;e<Ve;e++)bt.push(hr(mt,yt*e/width)),wt.push(hr(mt,yt*e/width));wt.unshift(bt[0]),wt.push(bt[bt.length-1]),hn=0,cn=0,un=0,Yt=!0;const n={xLeft:ae/8,xRight:width-ae/8,yTop:ae/8,yBottom:height-ae/8},r=Ce.map((e=>e.M length));jt=new R(bt,r,n,Oe,le)}function Hn(e,t){let n=Ce[e].length;return[e*we+we/2+ae/2,height/2-(n-1)/2*ve+t*ve]}function $n(e,t){le=min(e,t)/1024,ae=100*le,ht=50*le,we=(e-ae)/Ve,ve=(t-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}xe=floor(De.length*de),Le=[],ke=[],ge=floor(map(de,.2,.8,15,2));for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),kM e=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,mt=sr(xt,gt,pt,e),bt=[],wt=[],yt=e/(Ve-1);for(let t=0;t<Ve;t++)bt.push(hr(mt,yt*t/e)),wt.push(hr(mt,yt*t/e));wt.unshift(bt[0]),wt.push(bt[bt.length-1])}function Xn(){const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentagM e,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==AeM )for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<CM e.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le}function Wn(){jt.update();const e=4==Pe?0:Kt;jt.draw(Qe,ct,dt,e,le)}function Un(){if(!bn)return ar(),void et.imaM ge(je,0,0);if(4==Pe||5==Pe)return Wn(),void et.image(Qe,0,0);un>=Nt&&hn<Ve&&(hn++,un=0);for(let e=0;e<hn;e++)1==dt?it=ot=bt[e]:(it=ct,ot=bt[e]),Kn(e,it,ot,$e);un>=Nt&&cn<Ve-1&&(cn++,un=0);for(let e=0;e<cn;e++)Zn(e)}function qn(){et.background(ct),Ue.background(255),Ue.rectMode(CENTER),ne(Ue),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),Ue.stroke(st),Ue.strokeWeight(8*le),Ue.fill(ct),Qe.background(255),Qe.rectMode(CENTER),ne(Qe),Qe.strokeWeight(le),qe.background(255),qe.rectMode(CENTER),ne(qe),qe.textAlign(LEFT),$M e.background(255),$e.rectMode(CENTER),ne($e),Xe.background(255),ne(Xe),Xe.strokeWeight(Ne),We.background(255),We.rectMode(CENTER),ne(We),We.fill(st),We.stroke(st),We.strokeWeight(.1*le),er(lt),We.noStroke(),xn&&(We.rect(ae/16,height/2,ae/8,height),We.rect(width-ae/16,height/2,ae/8,height),We.rect(width/2,ae/16,width,ae/8),We.rect(width/2,height-ae/16,width,ae/8)),Ze.background(255),Ze.rectMode(CENTER),ne(Ze),Ze.textAlign(CENTER,CENTER),Ze.textStyle(BOLD),Ze.stroke(st),Ze.strokeWeight(8*le),Ze.fill(ct),je.backgroundM (255),je.rectMode(CENTER),ne(je),je.textAlign(CENTER,CENTER),je.textStyle(BOLD),Ke.background(255),Ke.rectMode(CENTER),ne(Ke),Ke.textAlign(CENTER,CENTER),Ke.textStyle(BOLD),Ke.stroke(st),Ke.strokeWeight(8*le),Ke.fill(ct),Je.background(255),Je.rectMode(CENTER),ne(Je),Je.textAlign(CENTER,CENTER),Je.textStyle(BOLD),Je.stroke(st),Je.strokeWeight(8*le),Je.fill(ct),Un(),et.image(We,0,0),Pt&&An(),et.image(Xe,0,0),et.image($e,0,0),At&&(tr(),et.image(Ue,0,0)),fn&&(lr(),et.image(Ze,0,0)),Lt&&(or(),et.image(Ke,0,0)),Dt&&(ir()M ,et.image(qe,0,0)),yn&&(Bn(),et.image(Je,0,0))}function draw(){const e=Date.now();bn&&(Ut.updateAge(new Date(e)),Xn()),qn(),image(et,0,0),zn||un++}function Zn(e){let t,n=Ce[e].length,r=Ce[e+1].length;for(let i=0;i<n;i++){const[n,o]=Hn(e,i);for(let a=0;a<r;a++){const[r,l]=Hn(e+1,a);t=map(min(Ce[e][i],Ce[e+1][a]),0,1,0,.5),ur(n,o,r,l,bt[e],bt[e+1],Xe,t)}}}function Kn(e,t,n,r){let i,o,a,l=Ce[e].length;for(let s=0;s<l;s++){const[l,h]=Hn(e,s);i=Ce[e][s],a=map(Be,1/30,1,3,10),o=map(Ce[e][s],0,1,2*a,0)*le,o<1.5*le&&(o=0),M Qn(l,h,ze,Oe,t,n,o,i,r)}}function Jn(e,t,n,r,i){for(let o=0;o<Le[e].length;o++)Qn(Le[e][o][0],Le[e][o][1],t,Oe,n,r,0,1,i)}function Qn(e,t,n,r,i,o,a,l,s){s.stroke(dr(o,map(l,0,1,.25,1))),s.fill(dr(i,map(l,0,1,.15,1))),s.strokeWeight(Fe),fr([a],s),3==dt&&s.fill(dr(i,0)),1==r?s.ellipse(e,t,n):2==r?s.rect(e,t,7*n/8,7*n/8):3==r&&(s.beginShape(),s.vertex(e-4*n/7,t),s.vertex(e,t-4*n/7),s.vertex(e+4*n/7,t),s.vertex(e,t+4*n/7),s.endShape(CLOSE))}function er(e){if(1==e);else if(2==e){We.strokeWeight(1*le);for(let e=ht/4;e<wiM dth+ht/4;e+=ht)for(let t=ht/4;t<height+ht/4;t+=ht)We.point(e,t)}else if(3==e){ht=25*le;for(let e=ht/2;e<height+ht/2;e+=ht)We.line(0,e,width,e);for(let e=ht/2;e<width+ht/2;e+=ht)We.line(e,0,e,height)}}function tr(){Ue.textFont("Trebuchet MS"),Ue.textAlign(LEFT,CENTER),Ue.noStroke(),pr(Ue,800*le,500*le),Ue.noStroke(),Ue.fill(dr(st,.75)),Ue.rect(width/2,height/2-100*le,800*le,300*le,25*le,25*le,0,0),Ue.fill(st),Ue.rect(width/2-250*le,height/2-100*le,225*le,225*le),Ue.image(se.elt,width/2-357.5*le,height/2-207.5*le,215M *le,215*le);let e=100*Zt[0][0];Ue.fill(ct),Ue.textSize(25*le),Ue.textStyle(NORMAL),1==me&&(e>=0&&e<20?Ue.text("I have a feeling this image belongs to",width/2-100*le,height/2-170*le):e>=20&&e<40?Ue.text("I have a hunch this image belongs to",width/2-100*le,height/2-170*le):e>=40&&e<60?Ue.text("I think this image belongs to",width/2-100*le,height/2-170*le):e>=60&&e<80?Ue.text("I'm almost certain this image belongs to",width/2-100*le,height/2-170*le):Ue.text("I'm positive this image belongs to",width/2-100*le,height/M 2-170*le));let t=e.toFixed(2);"100.00"==t&&(t="100"),1==me&&Ue.text("I'm "+t+"% confident that I'm right!",width/2-100*le,height/2-25*le),example=Zt.map((e=>e[1])),be=Ue.textWidth('"FIDENZAAAA"'),defaultPhrase=Ue.textWidth('"PERPENDICULAR INHABITATION"'),Ue.textStyle(BOLD);const n=me?example[0]:random(example);if(1===n.split(" ").length){let e=75*be/Ue.textWidth('"'+n+'"');e>75&&(e=75),Ue.textSize(e*le),Ue.text('"'+n+'"',width/2-100*le,height/2-90*le)}else nr(width/2-100*le,height/2-90*le,460*le,110*le,n,Ue);if(milM lis()-ye>1500&&(me=!0),C(tt,nt,st,ct,Pe,Mt),Ue.image(nt,width/2-370*le,height/2+70*le,80*le,80*le),3==Pe){let e;e=map(Mt,50,60,.25,1.3),I(rt,e),Ue.image(rt,width/2-370*le,height/2+70*le,80*le,80*le)}let r,i;Ue.image(tt,width/2-370*le,height/2+70*le,80*le,80*le),Ue.fill(xt),Ue.textSize(40*le),Ue.text("INTELLIGENCE INFO",width/2-275*le,height/2+115*le),Ue.textSize(18*le),Ue.textStyle(NORMAL),Ue.circle(width/2-360*le,height/2+180*le,7.5*le),1==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It ting smarter by the day.`:2==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s stable and it has reached peak performance.`:3==Pe&&(r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s decaying and losing its luster.`),i=2==Pe?"The Perceptron remains stable for some time before entering the decay phase.":`Wait until ${new Date(an).toLocaleString("en-US")} for your Perceptron to reach its peak performance.`,Ue.text(r,width/2-350*le,height/2+180*le),Ue.circle(width/2-360*le,height/2+210*le,7.5*le),Ue.teM xt(i,width/2-350*le,height/2+210*le),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),gr(Ue,width/2-225*le,width/2+65*le,height/2+265*le,height/2+305*le,"SELECT ANOTHER IMAGE"),gr(Ue,width/2+75*le,width/2+225*le,height/2+265*le,height/2+305*le,"CLOSE")}function nr(e,t,n,r,i,o){let a=i.split(" "),l=75*be/o.textWidth('"'+i+'"'),s=0,h=[],c=[],u=[],f="",d="";if(l>=50)l>75&&(l=75),o.textSize(l*le),o.text('"'+i+'"',e,t);else if(l<50){if(l=50*defaultPhrase/o.textWidth('"'+i+'"'),l>30){if(l>50&&(l=50),[f,d]=rr(l,n,s,h,c,a,f,M d,Ue),0==c.length)return o.textSize(l*le),void o.text('"'+i+'"',e,t);for(s=0,h=[],c=[];o.textWidth(d)>n/le;)l=l*n/le/o.textWidth(d),f="",d="",[f,d]=rr(l,n,s,h,c,a,f,d,Ue)}else{l=30,o.textSize(l);for(let e=0;e<a.length;e++)s+=o.textWidth(" "+a[e]),s<=n/le?h.push(a[e]):s>n/le&&s<=n/le*2?c.push(a[e]):u.push(a[e]);for(let e=1;e<h.length;e++)f=f+" "+h[e];if(f='"'+h[0]+f,0==u.length){for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+c[c.length-1]+'"'}else if(1==c.length)d="... "+u[u.length-1]+'"';else{for(let e=0;e<c.length-M 1;e++)d=d+c[e]+" ";d=d+"... "+u[u.length-1]+'"'}}o.textSize(l*le);let r=1.25*(o.textDescent()+o.textAscent());o.text(f,e,t-r/2),o.text(d,e,t+r/2)}}function rr(e,t,n,r,i,o,a,l,s){s.textSize(e);for(let e=0;e<o.length;e++)(n+=s.textWidth(" "+o[e]))<=t/le?r.push(o[e]):i.push(o[e]);for(let e=1;e<r.length;e++)a=a+" "+r[e];if(a='"'+r[0]+a,0==i.length&&(a+='"',l=""),1==i.length)l=i[i.length-1]+'"';else{for(let e=0;e<i.length-1;e++)l=l+i[e]+" ";l=l+i[i.length-1]+'"'}return[a,l]}function ir(){const e=45*le;qe.textFont("TahomM a"),qe.stroke(st),qe.strokeWeight(2*le),qe.fill(ct),qe.rect(width/2,e/2+height-87.5*le,600*le,90*le),qe.fill(st),qe.rect(width/2-150*le,e+height-170*le,300*le,30*le),qe.fill(ct),qe.rect(width/2+150*le,e+height-170*le,300*le,30*le),qe.noStroke(),qe.fill(ct),qe.textSize(15*le),qe.textStyle(BOLD),qe.text("PERCEPTRON INFORMATION",width/2-285*le,e+height-165*le),qe.fill(xt),qe.text("ARTWORK NAME:",width/2+10*le,e+height-165*le),qe.textAlign(RIGHT),qe.textStyle(ITALIC),qe.text("Perceptron #"+Et,width/2+285*le,e+height-16M 5*le);const[t,n]=It.split(" ");let r;"60 Years"===It?r="1 Year":"60 Months"===It?r="1 Month":"60 Weeks"===It?r="1 Week":"60 Days"===It?r="1 Day":"12 Hours"===It&&(r="12 Minutes"),data=[["AI MODEL NAME:",B(12*le,Ht,140*le)],["SCALE:","1:"+Te],["NUMBER OF CLASSES:",$t.length],["BIRTH YEAR:",Rt],["NUMBER OF REBIRTHS:",sn.toString()],["AGE:",`${Math.ceil(Mt)} Perceptron Years`],["ONE PERCEPTRON YEAR:",`${r}`],["STATE:",Ot[Pe]],["ACTIVE NEURONS:",`${round(ln*rn)} / ${ln}`],["NEXT STATE TIME:",vr(new Date(on))]],qe.fill(M xt);const i=data.length/2;for(let t=0;t<data.length;++t){const n=t<i,r=n?width/2-285*le:width/2+10*le,o=n?width/2-10*le:width/2+285*le,a=e+height-(135-t%i*15)*le;qe.textStyle(BOLD),qe.textAlign(LEFT),qe.textSize(12*le),qe.text(data[t][0],r,a),qe.textStyle(ITALIC),qe.textAlign(RIGHT),qe.textSize(12*le),qe.text(data[t][1],o,a)}}function or(){Ke.textFont("Trebuchet MS"),Ke.noStroke(),pr(Ke,600*le,200*le),gr(Ke,width/2-155*le,width/2-5*le,height/2+115*le,height/2+155*le,"UPDATE"),gr(Ke,width/2+5*le,width/2+155*le,heighM t/2+115*le,height/2+155*le,"CLOSE"),Ke.textAlign(LEFT),Ke.fill(xt),Ke.text("UPDATE BITCOIN FULL NODE ADDRESS",width/2-252.5*le,height/2-55*le),Ke.text("UPDATE MODEL ADDRESS",width/2-252.5*le,height/2+20*le),Ke.textAlign(RIGHT),Ke.textStyle(ITALIC),Ke.textSize(15*le),0==wn&&Ke.text("(*) Invalid Address",width/2+252.5*le,height/2-53*le),0==vn&&Ke.text("(*) Invalid Model",width/2+252.5*le,height/2+23*le)}function ar(){je.textFont("Trebuchet MS"),je.fill(st),je.textSize(50*le),je.stroke(st),je.strokeWeight(1*le),je.texM t("main()",width/2,height/2)}function lr(){un>=20&&1==dn&&(dn=!1,un=0),dn&&(Ze.textFont("Trebuchet MS"),Ze.stroke(st),Ze.fill(ct),Ze.rect(width/2,height/2,600*le,150*le,25*le),Ze.fill(xt),Ze.textSize(75*le),Ze.noStroke(),1==Pe?Ze.text("GROWING",width/2,height/2+5*le):3==Pe?Ze.text("AGING",width/2,height/2+5*le):4==Pe?Ze.text("DEAD",width/2,height/2+5*le):5==Pe&&Ze.text("BIRTH",width/2,height/2+5*le)),un>=20&&0==dn&&(dn=!0,un=0,Bt++,3==Bt&&(fn=!1))}function sr(e,t,n,r){let i=[],o=r/(n.length+1),a=color(e),l=color(t)M ;i.push(a);for(let e=0;e<n.length;e++){let t=color(n[e]);for(let e=1;e<=o;e++){let n=lerpColor(a,t,e/o);i.push(n)}a=t}for(let e=1;e<o;e++){let t=lerpColor(a,l,e/o);i.push(t)}if(i.push(l),i.length>r)i.splice(r);else if(i.length<r){let e=i[i.length-1];for(;i.length<r;)i.push(e)}return i}function hr(e,t){let n=e.length,r=Math.floor(t*n);return r>=n&&(r=n-1),e[r]}function cr(e){e=e.replace("#","");var t=parseInt(e,16);return color(t>>16&255,t>>8&255,255&t)}function ur(e,t,n,r,i,o,a,l){var s=a.drawingContext.createLineaM rGradient(e,t,n,r);s.addColorStop(0,i),s.addColorStop(1,o),a.drawingContext.strokeStyle=s,a.drawingContext.globalAlpha=l,a.line(e,t,n,r),a.drawingContext.globalAlpha=1}function fr(e,t){t.drawingContext.setLineDash(e)}function dr(e,t){let n=color(e),r=red(n),i=green(n),o=blue(n);return color(r,i,o,255*t)}function xr(e,t,n,r){return mouseX>e&&mouseX<t&&mouseY>n&&mouseY<r}function gr(e,t,n,r,i,o){e.strokeWeight(1*le),e.stroke(st);const[a,l]=xr(t,n,r,i)?[xt,ct]:[ct,xt];e.fill(a),e.push(),e.rectMode(CORNERS),e.rect(t,r,M n,i,5*le),e.pop(),e.noStroke(),e.textSize(20*le),e.fill(l),e.text(o,(t+n)/2,(46*r+54*i)/100)}function pr(e,t,n){e.fill(0,0,0,75),e.rect(width/2,height/2,width,height),e.stroke(st),e.fill(ct),e.rect(width/2,height/2,t,n,25*le)}function mr(e,t){resizeCanvas(e,t,!0),Xe.resizeCanvas(e,t,!0),$e.resizeCanvas(e,t,!0),We.resizeCanvas(e,t,!0),Ue.resizeCanvas(e,t,!0),qe.resizeCanvas(e,t,!0),Qe.resizeCanvas(e,t,!0),je.resizeCanvas(e,t,!0),Ze.resizeCanvas(e,t,!0),Ke.resizeCanvas(e,t,!0),Je.resizeCanvas(e,t,!0),et.resizeCanvas(M e,t,!0)}function br(e,t,n,r,i,o){const a=J(e);return a.position(t,n),a.size(r,i),a.style("opacity","0"),a.mouseClicked(o),a}function yr(){return null!=vt&&vt?.isFocused()||null!=zt&&zt?.isFocused()}function wr(e,t,n,r){let i;if(e<=3){i=`Hey ${String.fromCodePoint(128075)}, I'm ${n}, ${t} years old. I can detect ${r.length} NFT collections: `;let e=0;for(let t=0;t<r.length;++t){const n=r[t];if(e+n.length>500){i+=", etc";break}t==r.length-1?i+=", and ":t>0&&(i+=", "),i+=n,e+=n.length}i+=". ",t<=5?i+="However, I am onM ly a baby, so my recognition ability is not accurate. I'm in the state of Growing both looks and intelligence.":t<=13?i+="I am now a child. My recognition ability is becoming better, but still not very accurate. I'm in the state of Growing both looks and intelligence.":t<=25?i+="I have grown up to be a teen. My recognition ability almost reaches the peak, but I will still mess up sometimes. I'm in the state of Growing both looks and intelligence.":t<=50?i+="I finally reach adulthood. My recognition is fully functioM nal now. I'm in the Stable state, where I am the most intelligent with all neurons activated.":t<=60&&(i+="I am now an old Perceptron, so my recognition ability is no longer the best. I'm in the Decaying state, meaning that my neurons are dying, and my intelligence is decreasing over time.")}else 4==e?i=`${n} is Dead. However, this is not the end to its story...`:5==e&&(i=`${n} is now in the Rebirth state, and is preparing to start a new life.`);return i}function vr(e){const t=e.getDate(),n=e.toLocaleString("en-US"M ,{month:"long"}),r=e.getFullYear();let i=e.getHours().toString();1==i.length&&(i="0"+i);let o=e.getMinutes().toString();return 1==o.length&&(o="0"+o),`${Y(t)} ${n} ${r} | ${i}:${o}`}saveCanvasAtCurrentTime=()=>{save(N())},save4KCanvasAtCurrentTime=()=>{const e=width,t=height,n=min(4096/min(e,t),1e4/max(e,t)),r=e*n,i=t*n;mr(r,i),zn=!0,$n(r,i),qn();let o="4K_"+N()+".png";saveCanvas(et,o),mr(e,t),$n(e,t),zn=!1};const zr=[["60 Years",3,365],["60 Months",40,30],["60 Weeks",37,7],["60 Days",20,1]],Vr=[["1943",1],["1951",M 1.5],["1957",2],["1969",2.5],["1970",3],["1980",3.5],["1982",4],["1986",4.5],["1988",5],["1997",5.5],["1998",6],["2002",6.5],["2009",7],["2012",7.5],["2014",8],["2015",8.5],["2016",9],["2023",15]],_r=[["Plain",20],["Dotted",40],["Squared",40]],Mr=[["Basic",30],["Standard",60],["Advanced",10]],Er=[["MNIST",70],["CIFAR",25],["IMAGENET",5]],Sr=[["Theano",60],["Torch",30],["TensorFlow",10]],Rr=[["Whitepaper",2],["Blackboard",2],["Blueprint",2],["Nak",74/14],["Jims",74/14],["Level 10",74/14],["Flips",74/14],["Level 14",M 74/14],["III",74/14],["XMB",74/14],["Info",74/14],["Adventure",74/14],["Marigold",74/14],["Phoenix",74/14],["Love",74/14],["Cachet",74/14],["Human",74/14],["Twilight",3],["Sunset",3],["Aurora",3],["Liminal Space",3],["D Vu",3],["Lucid Dream",3],["Parallel",1],["Multiverse",1]];function Ir(e){for(let e=0;e<100;++e)random(1);return{visual:{pattern:k(_r),hardwareAcceleration:k(Mr),nodeFill:k(Er),nodeShape:k(Sr),colorPalette:k(Rr),lifeCycle:k(zr),birthYear:k(Vr)},training:e}}function Cr(e){window.$generativeTraitsM ={"Network Architecture":e.training.structure_gen,"Hidden Layers":e.training.n_layers,"Max Neurons Per Hidden Layer":e.training.max_nodes,"Activation Function":e.training.activation_func,"Training Epochs":e.training.epoch_num,Dataset:e.visual.nodeFill,"Deep Learning Framework":e.visual.nodeShape,"Hardware Acceleration":e.visual.hardwareAcceleration,"Paper Pattern":e.visual.pattern,"Life Cycle":e.visual.lifeCycle,"Birth Year":e.visual.birthYear,"Color Palette":e.visual.colorPalette}} c="https://static.cloudflareinsights.com/beacon.min.js/v2b4487d741ca48dcbadcaf954e159fc61680799950996" integrity="sha512-D/jdE0CypeVxFadTejKGTzmwyV10c1pxZk/AqjJuZbaJwGMyNHY3q/mTPWqMUnFACfCTunhZUVcd4cV78dK1pQ==" data-cf-beacon='{"rayId":"7b481d4d7c945443","version":"2023.3.0","b":1,"token":"6c07c178c94442f695e7a0a2aaee641a","si":100}' crossorigin="anonymous"></script> {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "midas touch"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "parrot"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "axe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "arrow wounds"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "sword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "orc"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "bloody"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "wizard staff"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "cape"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "fire"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "poisoned dagger"}]M text/plain;charset=utf-8 {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "rainbow"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "whale"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "undead"}, {"trait_type": "Artifacts", "value": "wizard staff"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "golden armor"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "laser beams"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "axe"}]}M {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "badger"}, {"trait_type": "Artifacts", "value": "pirate flag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "tribal tattoo"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "shield"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "orc"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "bloody"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "lightning bolt"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "zombie"}, {"trait_type": "Mane", "value": "fire"}, {"trait_type": "Claws", "value": "bloody"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "shield"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "golden armor"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "axe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "golden"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "shield"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "sword"}]} text/html;charset=utf-8 <meta charset="utf-8" /> position: relative; width: var(--width); height: var(--height); border: 1px solid blue; position: relative; <div id="upload"> <input id="inputUpload" type="file"> function e(e){"use strict";return new function e(t){let n="global"==t?window:this;n.canvas=document.createElement("canvas");let r=n.canvas.getContext("2d");n.width=100,n.height=100,n.canvas.width=n.width,n.canvas.height=n.height,"offscreen"!=t&&(document.body?document.body.appendChild(n.canvas):window.addEventListener("load",(function(){document.body.appendChild(n.canvas)}))),g(),n.MAGIC=161533525,n.RGB=0,n.HSV=1,n.HM SB=1,n.CHORD=0,n.PIE=1,n.OPEN=2,n.RADIUS=1,n.CORNER=2,n.CORNERS=3,n.ROUND="round",n.SQUARE="butt",n.PROJECT="square",n.MITER="miter",n.BEVEL="bevel",n.CLOSE=1,n.BLEND="source-over",n.REMOVE="destination-out",n.ADD="lighter",n.DARKEST="darken",n.LIGHTEST="lighten",n.DIFFERENCE="difference",n.SUBTRACT="subtract",n.EXCLUSION="exclusion",n.MULTIPLY="multiply",n.SCREEN="screen",n.REPLACE="copy",n.OVERLAY="overlay",n.HARD_LIGHT="hard-light",n.SOFT_LIGHT="soft-light",n.DODGE="color-dodge",n.BURN="color-burn",n.NORMAL="norM mal",n.ITALIC="italic",n.BOLD="bold",n.BOLDITALIC="italic bold",n.CENTER="center",n.LEFT="left",n.RIGHT="right",n.TOP="top",n.BOTTOM="bottom",n.BASELINE="alphabetic",n.LANDSCAPE="landscape",n.PORTRAIT="portrait",n.ALT=18,n.BACKSPACE=8,n.CONTROL=17,n.DELETE=46,n.DOWN_ARROW=40,n.ENTER=13,n.ESCAPE=27,n.LEFT_ARROW=37,n.OPTION=18,n.RETURN=13,n.RIGHT_ARROW=39,n.SHIFT=16,n.TAB=9,n.UP_ARROW=38,n.HALF_PI=Math.PI/2,n.PI=Math.PI,n.QUARTER_PI=Math.PI/4,n.TAU=2*Math.PI,n.TWO_PI=2*Math.PI,n.THRESHOLD=1,n.GRAY=2,n.OPAQUE=3,n.INVEM RT=4,n.POSTERIZE=5,n.DILATE=6,n.ERODE=7,n.BLUR=8,n.ARROW="default",n.CROSS="crosshair",n.HAND="pointer",n.MOVE="move",n.TEXT="text",n.VIDEO={video:!0,audio:!1},n.AUDIO={video:!1,audio:!0},n.SHR3=1,n.LCG=2,n.HARDWARE_FILTERS=!0,n.hint=function(e,t){n[e]=t},n.frameCount=0,n.mouseX=0,n.mouseY=0,n.pmouseX=0,n.pmouseY=0,n.mouseButton=null,n.keyIsPressed=!1,n.mouseIsPressed=!1,n.key=null,n.keyCode=null,n.pixels=null,n.accelerationX=0,n.accelerationY=0,n.accelerationZ=0,n.rotationX=0,n.rotationY=0,n.rotationZ=0,n.relRotatM ionX=0,n.relRotationY=0,n.relRotationZ=0,n.pAccelerationX=0,n.pAccelerationY=0,n.pAccelerationZ=0,n.pRotationX=0,n.pRotationY=0,n.pRotationZ=0,n.pRelRotationX=0,n.pRelRotationY=0,n.pRelRotationZ=0,n.touches=[],n._styleCache=[{colorMode:n.RGB,noStroke:!1,noFill:!1,ellipseMode:n.CENTER,rectMode:n.CORNER,curveDetail:20,curveAlpha:0,textFont:"sans-serif",textSize:12,textLeading:12,textStyle:"normal"}],n._style=n._styleCache[n._styleCache.length-1],n._noLoop=!1,n._pixelDensity=1,n._frameRate=null,n._tint=null;let i=nullM ,o=!0,a=[],l=null,s=0,h={},c=0,u=null,f=null,d=null;Object.defineProperty(n,"deviceOrientation",{get:function(){return 90==Math.abs(window.orientation)?n.LANDSCAPE:n.PORTRAIT}}),Object.defineProperty(n,"windowWidth",{get:function(){return window.innerWidth}}),Object.defineProperty(n,"windowHeight",{get:function(){return window.innerHeight}}),Object.defineProperty(n,"drawingContext",{get:function(){return r}}),n.createCanvas=function(e,t){return n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t,g(),n.canvas},nM .resizeCanvas=function(e,t){n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t},n.createGraphics=n.createImage=function(t,n){let r=new e("offscreen");return r.createCanvas(t,n),r.noLoop(),r},n.pixelDensity=function(e){return null==e||(n._pixelDensity=e,n.canvas.width=Math.ceil(n.width*e),n.canvas.height=Math.ceil(n.height*e),n.canvas.style.width=n.width+"px",n.canvas.style.height=n.height+"px",r.scale(n._pixelDensity,n._pixelDensity),g()),n._pixelDensity},n.map=function(e,t,n,r,i,o){let a=r+1*(e-t)/(n-t)*(i-r)M ;return o?r<i?Math.min(Math.max(a,r),i):Math.min(Math.max(a,i),r):a},n.lerp=function(e,t,n){return e*(1-n)+t*n},n.constrain=function(e,t,n){return Math.min(Math.max(e,t),n)},n.dist=function(){return 4==arguments.length?Math.hypot(arguments[0]-arguments[2],arguments[1]-arguments[3]):Math.hypot(arguments[0]-arguments[3],arguments[1]-arguments[4],arguments[2]-arguments[5])},n.norm=function(e,t,r){return n.map(e,t,r,0,1)},n.sq=function(e){return e*e},n.fract=function(e){return e-Math.floor(e)},n.degrees=function(e){retM urn 180*e/Math.PI},n.radians=function(e){return e*Math.PI/180},n.abs=Math.abs,n.ceil=Math.ceil,n.exp=Math.exp,n.floor=Math.floor,n.log=Math.log,n.mag=Math.hypot,n.max=Math.max,n.min=Math.min,n.round=Math.round,n.sqrt=Math.sqrt,n.sin=Math.sin,n.cos=Math.cos,n.tan=Math.tan,n.asin=Math.asin,n.acos=Math.acos,n.atan=Math.atan,n.atan2=Math.atan2,n.Vector=function(e,t,r){let i=this;i.x=e||0,i.y=t||0,i.z=r||0;let o=null,a=null;function l(e,t,n){return null!=e.x?e:null!=t?{x:e,y:t,z:n||0}:{x:e,y:e,z:e}}function s(){null==a&M &(a=i.x*i.x+i.y*i.y+i.z*i.z,o=Math.sqrt(a))}function h(){a=null,o=null}i.set=function(e,t,n){i.x=e||0,i.y=t||0,i.z=n||0},i.copy=function(){return new n.Vector(i.x,i.y,i.z)},i.add=function(){let e=l.apply(null,arguments);return i.x+=e.x,i.y+=e.y,i.z+=e.z,h(),i},i.rem=function(){let e=l.apply(null,arguments);return i.x%=e.x,i.y%=e.y,i.z%=e.z,h(),i},i.sub=function(){let e=l.apply(null,arguments);return i.x-=e.x,i.y-=e.y,i.z-=e.z,h(),i},i.mult=function(){let e=l.apply(null,arguments);return i.x*=e.x,i.y*=e.y,i.z*=e.z,hM (),i},i.div=function(){let e=l.apply(null,arguments);return i.x/=e.x,i.y/=e.y,i.z/=e.z,h(),i},i.mag=function(){return s(),o},i.magSq=function(){return s(),a},i.dot=function(){let e=l.apply(null,arguments);return i.x*e.x+i.y*e.y+i.z*e.z},i.dist=function(){let e=l.apply(null,arguments),t=i.x-e.x,n=i.y-e.y,r=i.z-e.z;return Math.sqrt(t*t+n*n+r*r)},i.cross=function(){let e=l.apply(null,arguments),t=i.y*e.z-i.z*e.y,n=i.z*e.x-i.x*e.z,r=i.x*e.y-i.y*e.x;return i.x=t,i.y=n,i.z=r,h(),i},i.normalize=function(){s();let e=o;retuM rn i.x/=e,i.y/=e,i.z/=e,o=1,a=1,i},i.limit=function(e){s();if(o>e){let t=e/o;i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e}return i},i.setMag=function(e){s();let t=e/o;return i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e,i},i.heading=function(){return Math.atan2(i.y,i.x)},i.rotate=function(e){let t=Math.cos(e),n=Math.sin(e),r=i.x*t-i.y*n,o=i.x*n+i.y*t;return i.x=r,i.y=o,i},i.angleBetween=function(){let e=l.apply(null,arguments);const t=i.dot(e)/(i.mag()*e.mag());let n;return n=Math.acos(Math.min(1,Math.max(-1,t))),n*Math.sign(i.cross(e).z||1)},M i.lerp=function(e,t){return i.x=i.x*(1-t)+e.x*t,i.y=i.y*(1-t)+e.y*t,i.z=i.z*(1-t)+e.z*t,h(),i},i.reflect=function(e){return e.normalize(),i.sub(e.mult(2*i.dot(e)))},i.array=function(){return[i.x,i.y,i.z]},i.equals=function(e,t){return null==t&&null==(t=Number.EPSILON)&&(t=0),Math.abs(e.x-i.x)<t&&Math.abs(e.y-i.y)<t&&Math.abs(e.z-i.z)<t},i.fromAngle=function(e,t){return null==t&&(t=1),o=t,a=t*t,i.x=t*Math.cos(e),i.y=t*Math.sin(e),i.z=0,i},i.fromAngles=function(e,t,n){null==n&&(n=1),o=n,a=n*n;const r=Math.cos(t),l=MaM th.sin(t),s=Math.cos(e),h=Math.sin(e);return i.x=n*h*l,i.y=-n*s,i.z=n*h*r,i},i.random2D=function(){return o=1,a=1,i.fromAngle(Math.random()*Math.PI*2)},i.random3D=function(){return o=1,a=1,i.fromAngles(Math.random()*Math.PI*2,Math.random()*Math.PI*2)},i.toString=function(){return`[${i.x}, ${i.y}, ${i.z}]`}},n.Vector.add=function(e,t){return new n.Vector(e.x+t.x,e.y+t.y,e.z+t.z)},n.Vector.rem=function(e,t){return new n.Vector(e.x%t.x,e.y%t.y,e.z%t.z)},n.Vector.sub=function(e,t){return new n.Vector(e.x-t.x,e.y-t.y,e.M z-t.z)},n.Vector.mult=function(e,t){return null==t.x?new n.Vector(e.x*t,e.y*t,e.z*t):new n.Vector(e.x*t.x,e.y*t.y,e.z*t.z)},n.Vector.div=function(e,t){return null==t.x?new n.Vector(e.x/t,e.y/t,e.z/t):new n.Vector(e.x/t.x,e.y/t.y,e.z/t.z)},n.Vector.dist=function(e,t){return Math.hypot(e.x-t.x,e.y-t.y,e.z-t.z)},n.Vector.cross=function(e,t){return new n.Vector(e.y*t.z-e.z*t.y,e.z*t.x-e.x*t.z,e.x*t.y-e.y*t.x)},n.Vector.lerp=function(e,t,r){return new n.Vector(e.x*(1-r)+t.x*r,e.y=e.y*(1-r)+t.y*r,e.z=e.z*(1-r)+t.z*r)},n.M Vector.equals=function(e,t,n){return e.equals(t,n)};for(let e of["fromAngle","fromAngles","random2D","random3D"])n.Vector[e]=function(t,r,i){return(new n.Vector)[e](t,r,i)};function x(e,t,n){let r,i,o,a,l,s,h,c,u;if(0==t)return[255*(r=n),255*(i=n),255*(o=n)];switch((a=e)>360&&(a=0),h=n*(1-t),c=n*(1-t*(s=(a/=60)-(l=~~a))),u=n*(1-t*(1-s)),l){case 0:r=n,i=u,o=h;break;case 1:r=c,i=n,o=h;break;case 2:r=h,i=n,o=u;break;case 3:r=h,i=c,o=n;break;case 4:r=u,i=h,o=n;break;default:r=n,i=h,o=c}return[255*r,255*i,255*o]}functioM n g(){r.fillStyle="white",r.strokeStyle="black",r.lineCap="round",r.lineJoin="miter"}function p(e){if(0<=e&&e<2*Math.PI)return e;for(;e<0;)e+=2*Math.PI;for(;e>=Math.PI;)e-=2*Math.PI;return e}function m(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;let c=p(a),u=p(l);r.beginPath();for(let a=0;a<h+1;a++){let l=a/h,s=n.lerp(c,u,l),f=Math.cos(s)*i/2,d=Math.sin(s)*o/2;r[a?"lineTo":"moveTo"](e+f,t+d)}s==n.CHORD?r.closePath():s==n.PIE&&(r.lineTo(e,t),r.closePath()),n._style.noFill||r.fill(),n._style.noStrokM e||r.stroke()}function b(e,t,i,o){n._style.noFill&&n._style.noStroke||(r.beginPath(),r.ellipse(e,t,i/2,o/2,0,0,2*Math.PI),n._style.noFill||r.fill(),n._style.noStroke||r.stroke())}function y(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;if(null==a)return function(e,t,i,o){n._style.noFill||r.fillRect(e,t,i,o),n._style.noStroke||r.strokeRect(e,t,i,o)}(e,t,i,o);if(null==l)return y(e,t,i,o,a,a,a,a);const c=Math.min(Math.abs(o),Math.abs(i))/2;a=Math.min(c,a),l=Math.min(c,l),h=Math.min(c,h),s=Math.min(c,s)M ,r.beginPath(),r.moveTo(e+a,t),r.arcTo(e+i,t,e+i,t+o,l),r.arcTo(e+i,t+o,e,t+o,s),r.arcTo(e,t+o,e,t,h),r.arcTo(e,t,e+i,t,a),r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke()}function w(){a=[]}n.createVector=function(e,t,r){return new n.Vector(e,t,r)},n.curvePoint=function(e,t,n,r,i){const o=i*i*i,a=i*i;return e*(-.5*o+a-.5*i)+t*(1.5*o-2.5*a+1)+n*(-1.5*o+2*a+.5*i)+r*(.5*o-.5*a)},n.bezierPoint=function(e,t,n,r,i){const o=1-i;return Math.pow(o,3)*e+3*Math.pow(o,2)*i*t+3*o*Math.pow(i,2)*n+Math.pow(i,M 3)*r},n.curveTangent=function(e,t,n,r,i){const o=i*i;return e*(-3*o/2+2*i-.5)+t*(9*o/2-5*i)+n*(-9*o/2+4*i+.5)+r*(3*o/2-i)},n.bezierTangent=function(e,t,n,r,i){const o=1-i;return 3*r*Math.pow(i,2)-3*n*Math.pow(i,2)+6*n*o*i-6*t*o*i+3*t*Math.pow(o,2)-3*e*Math.pow(o,2)},n.Color=function(e,t,n,r){let i=this;i.MAGIC=786698,i._r=e,i._g=t,i._b=n,i._a=r,i._h=0,i._s=0,i._v=0,i._hsvInferred=!1,i.setRed=function(e){i._r=e,i._hsvInferred=!1},i.setGreen=function(e){i._g=e,i._hsvInferred=!1},i.setBlue=function(e){i._b=e,i._hsvInfM erred=!1},i.setAlpha=function(e){i._a=e/255,i._hsvInferred=!1},i._inferHSV=function(){i._hsvInferred||([i._h,i._s,i._v]=function(e,t,n){let r,i,o,a,l;return r=e<t?e<n?e:n:t<n?t:n,0==(l=100*(i=e>t?e>n?e:n:t>n?t:n)/255)?[o=0,a=0,l]:0==(a=100*(i-r)/i)?[o=0,a,l]:(o=i==e?0+60*(t-n)/(i-r):i==t?120+60*(n-e)/(i-r):240+60*(e-t)/(i-r),[o,a,l])}(i._r,i._g,i._b),i._hsvInferred=!0)},i.toString=function(){return`rgba(${Math.round(i._r)},${Math.round(i._g)},${Math.round(i._b)},${~~(1e3*i._a)/1e3})`}},n.colorMode=function(e){n._stM yle.colorMode=e},n.color=function(){if(1==arguments.length&&786698==arguments[0].MAGIC)return arguments[0];if(n._style.colorMode==n.RGB){if(1==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],1);if(2==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],arguments[1]/255);if(3==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],1);if(4==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],arguments[3]/255)}else{if(1==argumeM nts.length)return new n.Color(...x(0,0,arguments[0]/100),1);if(2==arguments.length)return new n.Color(...x(0,0,arguments[0]/100),arguments[1]/255);if(3==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),1);if(4==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),arguments[3])}return null},n.red=function(e){return e._r},n.green=function(e){return e._g},n.blue=function(e){return e._b},n.alpha=function(e){return 255*e._a},n.hue=function(e){reM turn e._inferHSV(),e._h},n.saturation=function(e){return e._inferHSV(),e._s},n.brightness=function(e){return e._inferHSV(),e._v},n.lightness=function(e){return 100*(.2126*e._r+.7152*e._g+.0722*e._b)/255},n.lerpColor=function(e,t,r){return n._style.colorMode==n.RGB?new n.Color(n.constrain(n.lerp(e._r,t._r,r),0,255),n.constrain(n.lerp(e._g,t._g,r),0,255),n.constrain(n.lerp(e._b,t._b,r),0,255),n.constrain(n.lerp(e._a,t._a,r),0,1)):(e._inferHSV(),t._inferHSV(),new n.Color(n.constrain(function(e,t,r){var i=[[Math.abs(t-M e),n.map(r,0,1,e,t)],[Math.abs(t+360-e),n.map(r,0,1,e,t+360)],[Math.abs(t-360-e),n.map(r,0,1,e,t-360)]];return i.sort(((e,t)=>e[0]-t[0])),(i[0][1]+720)%360}(e._h,t._h,r),0,360),n.constrain(n.lerp(e._s,t._s,r),0,100),n.constrain(n.lerp(e._v,t._v,r),0,100),n.constrain(n.lerp(e._a,t._a,r),0,1)))},n.strokeWeight=function(e){n._style_noStroke=!1,r.lineWidth=e},n.stroke=function(){if(n._style.noStroke=!1,"string"==typeof arguments[0])return void(r.strokeStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._sM tyle.noStroke=!0:r.strokeStyle=e},n.noStroke=function(){n._style.noStroke=!0},n.fill=function(){if(n._style.noFill=!1,"string"==typeof arguments[0])return void(r.fillStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._style.noFill=!0:r.fillStyle=e},n.noFill=function(){n._style.noFill=!0},n.blendMode=function(e){r.globalCompositeOperation=e},n.strokeCap=function(e){r.lineCap=e},n.strokeJoin=function(e){r.lineJoin=e},n.ellipseMode=function(e){n._style.ellipseMode=e},n.rectMode=function(e){n._style.rectM Mode=e},n.curveDetail=function(e){n._style.curveDetail=e},n.curveAlpha=function(e){n._style.curveAlpha=e},n.curveTightness=function(e){n._style.curveAlpha=e},n.clear=function(){r.clearRect(0,0,n.width,n.height)},n.background=function(){if(arguments[0]&&arguments[0].MAGIC==n.MAGIC)return n.image(arguments[0],0,0,n.width,n.height);r.save(),r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity),r.fillStyle="string"==typeof arguments[0]?arguments[0]:n.color(...Array.from(arguments)),r.fillRect(0,0,n.width,n.heightM ),r.restore()},n.line=function(e,t,i,o){n._style.noStroke||(r.beginPath(),r.moveTo(e,t),r.lineTo(i,o),r.stroke())},n.arc=function(e,t,r,i,o,a,l,s){if(o==a)return n.ellipse(e,t,r,i);null==s&&(s=25),null==l&&(l=n.PIE),n._style.ellipseMode==n.CENTER?m(e,t,r,i,o,a,l,s):n._style.ellipseMode==n.RADIUS?m(e,t,2*r,2*i,o,a,l,s):n._style.ellipseMode==n.CORNER?m(e+r/2,t+i/2,r,i,o,a,l,s):n._style.ellipseMode==n.CORNERS&&m((e+r)/2,(t+i)/2,r-e,i-t,o,a,l,s)},n.ellipse=function(e,t,r,i){null==i&&(i=r),n._style.ellipseMode==n.CENTERM ?b(e,t,r,i):n._style.ellipseMode==n.RADIUS?b(e,t,2*r,2*i):n._style.ellipseMode==n.CORNER?b(e+r/2,t+i/2,r,i):n._style.ellipseMode==n.CORNERS&&b((e+r)/2,(t+i)/2,r-e,i-t)},n.circle=function(e,t,r){return n.ellipse(e,t,r,r)},n.point=function(e,t){e.x&&(t=e.y,e=e.x),r.beginPath(),r.ellipse(e,t,.4,.4,0,0,2*Math.PI),r.stroke()},n.rect=function(e,t,r,i,o,a,l,s){n._style.rectMode==n.CENTER?y(e-r/2,t-i/2,r,i,o,a,l,s):n._style.rectMode==n.RADIUS?y(e-r,t-i,2*r,2*i,o,a,l,s):n._style.rectMode==n.CORNER?y(e,t,r,i,o,a,l,s):n._stylM e.rectMode==n.CORNERS&&y(e,t,r-e,i-t,o,a,l,s)},n.square=function(e,t,r,i,o,a,l){return n.rect(e,t,r,r,i,o,a,l)},n.beginShape=function(){w(),r.beginPath(),o=!0},n.beginContour=function(){r.closePath(),w(),o=!0},n.endContour=function(){w(),o=!0},n.vertex=function(e,t){w(),o?r.moveTo(e,t):r.lineTo(e,t),o=!1},n.bezierVertex=function(e,t,n,i,o,a){w(),r.bezierCurveTo(e,t,n,i,o,a)},n.quadraticVertex=function(e,t,n,i){w(),r.quadraticCurveTo(e,t,n,i)},n.bezier=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.bezierVM ertex(r,i,o,a,l,s),n.endShape()},n.triangle=function(e,t,r,i,o,a){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.endShape(n.CLOSE)},n.quad=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.vertex(l,s),n.endShape(n.CLOSE)},n.endShape=function(e){w(),e&&r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke(),n._style.noFill&&n._style.noStroke&&(r.save(),r.fillStyle="none",r.fill(),r.restore())},n.curveVertex=function(e,t){if(a.push([e,t]),a.length<4)return;M let i=function(e,t,n,r,i,o,a,l,s,h){function c(e,t,n,r,i,o){let a=Math.pow(r-t,2)+Math.pow(i-n,2);return Math.pow(a,.5*o)+e}let u=[],f=c(0,e,t,n,r,h),d=c(f,n,r,i,o,h),x=c(d,i,o,a,l,h);for(let h=0;h<s;h++){let c=f+h/(s-1)*(d-f),g=[(f-c)/(f-0),(c-0)/(f-0),(d-c)/(d-f),(c-f)/(d-f),(x-c)/(x-d),(c-d)/(x-d),(d-c)/(d-0),(c-0)/(d-0),(x-c)/(x-f),(c-f)/(x-f)];for(let e=0;e<g.length;e+=2)isNaN(g[e])&&(g[e]=1,g[e+1]=0),isFinite(g[e])||(g[e]>0?(g[e]=1,g[e+1]=0):(g[e]=0,g[e+1]=1));let p=e*g[0]+n*g[1],m=t*g[0]+r*g[1],b=n*g[2]+i*g[M 3],y=r*g[2]+o*g[3],w=i*g[4]+a*g[5],v=o*g[4]+l*g[5],z=p*g[6]+b*g[7],V=m*g[6]+y*g[7],_=b*g[8]+w*g[9],M=y*g[8]+v*g[9],E=z*g[2]+_*g[3],S=V*g[2]+M*g[3];u.push([E,S])}return u}(...a[a.length-4],...a[a.length-3],...a[a.length-2],...a[a.length-1],n._style.curveDetail,n._style.curveAlpha);for(let e=0;e<i.length;e++)o?r.moveTo(...i[e]):r.lineTo(...i[e]),o=!1},n.curve=function(e,t,r,i,o,a,l,s){n.beginShape(),n.curveVertex(e,t),n.curveVertex(r,i),n.curveVertex(o,a),n.curveVertex(l,s),n.endShape()},n.translate=function(e,t){r.tM ranslate(e,t)},n.rotate=function(e){r.rotate(e)},n.scale=function(e,t){null==t&&(t=e),r.scale(e,t)},n.applyMatrix=function(e,t,n,i,o,a){r.transform(e,t,n,i,o,a)},n.shearX=function(e){r.transform(1,0,Math.tan(e),1,0,0)},n.shearY=function(e){r.transform(1,Math.tan(e),0,1,0,0)},n.resetMatrix=function(){r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity)},n.pushMatrix=n.push=function(){n._styleCache.push({...n._style}),n._style=n._styleCache[n._styleCache.length-1],r.save()},n.popMatrix=n.pop=function(){n._stylM eCache.length-1&&(n._styleCache.pop(),n._style=n._styleCache[n._styleCache.length-1],r.restore())},n.image=function(e,t,i,o,a,l,s,h,c){let u=e.MAGIC==n.MAGIC?e.canvas:e;function d(){if(e.MAGIC!=n.MAGIC||!n._tint)return;let t=e.canvas.getContext("2d");t.save(),t.resetTransform(),t.clearRect(0,0,t.canvas.width,t.canvas.height),t.drawImage(f.canvas,0,0),t.restore()}return e.MAGIC==n.MAGIC&&null!=n._tint&&(function(e,t){null==f&&(f=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvasM .height),f.canvas.width==e&&f.canvas.height==t||(f.canvas.width=e,f.canvas.height=t)}(e.canvas.width,e.canvas.height),f.drawImage(e.canvas,0,0),e.tinted(n._tint)),o?l?(h||(h=u.width),c||(c=u.height),r.drawImage(u,l,s,h,c,t,i,o,a),void d()):(r.drawImage(u,t,i,o,a),void d()):(e.MAGIC==n.MAGIC||e.width?r.drawImage(u,t,i,e.width,e.height):r.drawImage(u,t,i,e.videoWidth,e.videoHeight),void d())},n.loadPixels=function(){l=r.getImageData(0,0,n.canvas.width,n.canvas.height),n.pixels=l.data},n.updatePixels=function(){null!=M l&&r.putImageData(l,0,0)},n.loadImage=function(e,t){s++;let r=n.createGraphics(100,100),i=r.canvas.getContext("2d"),o=new Image;return o.src=e,o.crossOrigin="Anonymous",o.onload=function(){i.canvas.width=o.width,i.canvas.height=o.height,r.width=o.width,r.height=o.height,i.drawImage(o,0,0),s--,t&&t(r)},r};let v={};function z(e,t){null==u&&(u=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvas.height),u.canvas.width==e&&u.canvas.height==t||(u.canvas.width=e,u.canvas.height=t)}funcM tion V(){let e=r.canvas.width*r.canvas.height*4;null!=d&&e==d.length||(d=new Uint8ClampedArray(e))}function _(e){u.clearRect(0,0,u.canvas.width,u.canvas.height),u.filter=e,u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()}v[n.THRESHOLD]=function(e,t){null==t?t=127.5:t*=255;for(let n=0;n<e.length;n+=4){const r=.2126*e[n]+.7152*e[n+1]+.0722*e[n+2];e[n]=e[n+1]=e[n+2]=r>=t?255:0}},v[n.GRAY]=function(e){for(let t=0;t<e.length;t+=4)M {const n=.2126*e[t]+.7152*e[t+1]+.0722*e[t+2];e[t]=e[t+1]=e[t+2]=n}},v[n.OPAQUE]=function(e){for(let t=0;t<e.length;t+=4)e[t+3]=255},v[n.INVERT]=function(e){for(let t=0;t<e.length;t+=4)e[t]=255-e[t],e[t+1]=255-e[t+1],e[t+2]=255-e[t+2]},v[n.POSTERIZE]=function(e,t){let n=t-1;for(let r=0;r<e.length;r+=4)e[r]=255*(e[r]*t>>8)/n,e[r+1]=255*(e[r+1]*t>>8)/n,e[r+2]=255*(e[r+2]*t>>8)/n},v[n.DILATE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-M 1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.max(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.ERODE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.min(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.BLURM ]=function(e,t){t=t||1,t=Math.floor(t*n._pixelDensity),V(),d.set(e);let i=2*t+1,o=function(e){let n=new Float32Array(e),r=.3*t+.8,i=r*r*2;for(let t=0;t<e;t++){let o=t-e/2,a=Math.exp(-o*o/i)/(2.5066282746*r);n[t]=a}return n}(i),[a,l]=[r.canvas.width,r.canvas.height];for(let n=0;n<l;n++)for(let r=0;r<a;r++){let l=0,s=0,h=0,c=0;for(let e=0;e<i;e++){let i=4*(n*a+Math.min(Math.max(r-t+e,0),a-1));l+=d[i]*o[e],s+=d[i+1]*o[e],h+=d[i+2]*o[e],c+=d[i+3]*o[e]}let u=4*(n*a+r);e[u]=l,e[u+1]=s,e[u+2]=h,e[u+3]=c}d.set(e);for(let nM =0;n<l;n++)for(let r=0;r<a;r++){let s=0,h=0,c=0,u=0;for(let e=0;e<i;e++){let i=4*(Math.min(Math.max(n-t+e,0),l-1)*a+r);s+=d[i]*o[e],h+=d[i+1]*o[e],c+=d[i+2]*o[e],u+=d[i+3]*o[e]}let f=4*(n*a+r);e[f]=s,e[f+1]=h,e[f+2]=c,e[f+3]=u}},n.filter=function(e,t){if(n.HARDWARE_FILTERS&&null!=r.filter)if(z(),e==n.THRESHOLD){null==t&&(t=.5),t=Math.max(t,1e-5),_(`saturate(0%) brightness(${Math.floor(.5/t*100)}%) contrast(1000000%)`)}else if(e==n.GRAY)_("saturate(0%)");else if(e==n.OPAQUE)u.fillStyle="black",u.fillRect(0,0,u.canvaM s.width,u.canvas.height),u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.drawImage(u.canvas,0,0),r.restore();else if(e==n.INVERT)_("invert(100%)");else if(e==n.BLUR)_(`blur(${Math.ceil(t*n._pixelDensity/1)||1}px)`);else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}},n.resize=function(e,t){z(),u.drawImage(r.canvas,0,0),n.width=e,n.height=t,r.canvas.width=e*n._pixM elDensity,r.canvas.height=t*n._pixelDensity,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0,r.canvas.width,r.canvas.height),r.restore()},n.get=function(e,t,i,o){if(null!=e&&null==i){let i=r.getImageData(e,t,1,1).data;return new n.Color(i[0],i[1],i[2],i[3]/255)}e=e||0,t=t||0,i=i||n.width,o=o||n.height;let a=n.createGraphics(i,o);a.pixelDensity(n._pixelDensity);let l=r.getImageData(e*n._pixelDensity,t*n._pixelDensity,i*n._pixelDensity,o*n._pixelDensity);return a.caM nvas.getContext("2d").putImageData(l,0,0),a},n.set=function(e,t,i){if(i.MAGIC==n.MAGIC){let r=n._tint;return n._tint=null,n.image(i,e,t),void(n._tint=r)}let o=4*(t*n._pixelDensity*r.canvas.width+e*n._pixelDensity);n.pixels[o]=i._r,n.pixels[o+1]=i._g,n.pixels[o+2]=i._b,n.pixels[o+3]=255*i._a},n.tinted=function(){let e=n.color(...Array.from(arguments)),t=e._a;e._a=1,z(),u.clearRect(0,0,u.canvas.width,u.canvas.height),u.fillStyle=e,u.fillRect(0,0,u.canvas.width,u.canvas.height),u.globalCompositeOperation="multiply",u.M drawImage(r.canvas,0,0),u.globalCompositeOperation="source-over",r.save(),r.resetTransform();let i=r.globalCompositeOperation;r.globalCompositeOperation="source-in",r.drawImage(u.canvas,0,0),r.globalCompositeOperation=i,r.restore(),u.globalAlpha=t,u.clearRect(0,0,u.canvas.width,u.canvas.height),u.drawImage(r.canvas,0,0),u.globalAlpha=1,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()},n.tint=function(){n._tint=n.color(...Array.from(arguments))},n.noTiM nt=function(){n._tint=null},n.mask=function(e){r.save(),r.resetTransform();let t=r.globalCompositeOperation;r.globalCompositeOperation="destination-in",r.drawImage(e.canvas,0,0),r.globalCompositeOperation=t,r.restore()},n.clearTemporaryBuffers=function(){u=null,f=null,d=null},n.save=function(e,t){e=e||"untitled",t=t||"png";var n=document.createElement("a");n.innerHTML="[Download]",n.addEventListener("click",(function(){this.href=r.canvas.toDataURL(),this.download=e+"."+t}),!1),document.body.appendChild(n),n.click()M ,document.body.removeChild(n)},n.saveCanvas=function(e,t,r){if(e.MAGIC==n.MAGIC){r&&e.save(t,r);let n=t.split(".");return e.save(n.slice(0,-1).join("."),n[n.length-1])}if(t)return n.save(e,t);let i=e.split(".");return n.save(i.slice(0,-1).join("."),i[i.length-1])},n.loadFont=function(e){let t=e.split("/"),n=t[t.length-1].split(".")[0].replace(" ",""),r=`@font-face {\n font-family: '${n}';\n src: url('${e}');\n }`;const i=document.createElement("style");return i.textContent=r,document.head.append(M i),n},n.textFont=function(e){n._style.textFont=e},n.textSize=function(e){n._style.textSize=e,n._style.textLeading=e},n.textLeading=function(e){n._style.textLeading=e},n.textStyle=function(e){n._style.textStyle=e},n.textAlign=function(e,t){r.textAlign=e,t&&(r.textBaseline=t==n.CENTER?"middle":t)},n.text=function(e,t,i,o){if(!e)return;if(e=e.toString(),n._style.noFill&&n._style.noStroke)return;r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`;let a=e.split("\n");for(let e=0;e<a.length;e++)n._M style.noFill||r.fillText(a[e],t,i,o),n._style.noStroke||r.strokeText(a[e],t,i,o),i+=n._style.textLeading},n.textWidth=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).width},n.textAscent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBoundingBoxAscent},n.textDescent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBounM dingBoxDescent};var M,E=4,S=.5,R=function(e){return.5*(1-Math.cos(e*Math.PI))};n.noise=function(e,t,n){if(t=t||0,n=n||0,null==M){M=new Array(4096);for(var r=0;r<4096;r++)M[r]=Math.random()}e<0&&(e=-e),t<0&&(t=-t),n<0&&(n=-n);for(var i,o,a,l,s,h=Math.floor(e),c=Math.floor(t),u=Math.floor(n),f=e-h,d=t-c,x=n-u,g=0,p=.5,m=0;m<E;m++){var b=h+(c<<4)+(u<<8);i=R(f),o=R(d),a=M[4095&b],a+=i*(M[b+1&4095]-a),l=M[b+16&4095],a+=o*((l+=i*(M[b+16+1&4095]-l))-a),l=M[4095&(b+=256)],l+=i*(M[b+1&4095]-l),s=M[b+16&4095],l+=o*((s+=i*(M[M b+16+1&4095]-s))-l),g+=(a+=R(x)*(l-a))*p,p*=S,h<<=1,c<<=1,u<<=1,(f*=2)>=1&&(h++,f--),(d*=2)>=1&&(c++,d--),(x*=2)>=1&&(u++,x--)}return g},n.noiseDetail=function(e,t){e>0&&(E=e),t>0&&(S=t)};const I=function(){let e,t,n=4294967295;return{setSeed(r){e=t=(null==r?Math.random()*n:r)>>>0},getSeed:()=>t,rand:()=>(e^=e<<17,e^=e>>13,((e^=e<<5)>>>0)/n)}};let C=I();C.setSeed(),n.noiseSeed=function(e){let t=null==e?4294967295*Math.random():e;M||(M=new Float32Array(4096));for(var n=0;n<4096;n++)t^=t<<17,t^=t>>13,t^=t<<5,M[n]=(t>M >>0)/4294967295},n.randomSeed=function(e){C.setSeed(e)},n.random=function(e,t){return null==e?C.rand():"number"==typeof e?null!=t?C.rand()*(t-e)+e:C.rand()*e:e[~~(e.length*C.rand())]},n.randomGenerator=function(e){e==n.LCG?C=function(){const e=4294967296;let t,n;return{setSeed(r){n=t=(null==r?Math.random()*e:r)>>>0},getSeed:()=>t,rand:()=>(n=(1664525*n+1013904223)%e)/e}}():e==n.SHR3&&(C=I()),C.setSeed()};var T=new function(){var e,t,n,r=new Array(128),i=new Array(256),o=new Array(128),a=new Array(128),l=new Array(2M 56),s=new Array(256),h=function(){return 4294967296*C.rand()-2147483648},c=function(){return.5+2.328306e-10*(h()<<0)};this.SHR3=h,this.UNI=c,this.RNOR=function(){return n=h(),e=127&n,Math.abs(n)<r[e]?n*o[e]:function(){for(var t,i,l,s,u=3.44262;;){if(t=n*o[e],0==e){do{l=c(),s=c(),t=.2904764*-Math.log(l),i=-Math.log(s)}while(i+i<t*t);return n>0?u+t:-u-t}if(a[e]+c()*(a[e-1]-a[e])<Math.exp(-.5*t*t))return t;if(n=h(),e=127&n,Math.abs(n)<r[e])return n*o[e]}}()},this.REXP=function(){return(t=h()>>>0)<r[e=255&t]?t*l[e]:funM ction(){for(var n;;){if(0==e)return 7.69711-Math.log(c());if(n=t*l[e],s[e]+c()*(s[e-1]-s[e])<Math.exp(-n))return n;if((t=h())<i[e=255&t])return t*l[e]}}()},this.zigset=function(){var e,t,n=2147483648,h=4294967296,c=3.442619855899,u=c,f=.00991256303526217,d=7.697117470131487,x=d,g=.003949659822581572;for(e=f/Math.exp(-.5*c*c),r[0]=Math.floor(c/e*n),r[1]=0,o[0]=e/n,o[127]=c/n,a[0]=1,a[127]=Math.exp(-.5*c*c),t=126;t>=1;t--)c=Math.sqrt(-2*Math.log(f/c+Math.exp(-.5*c*c))),r[t+1]=Math.floor(c/u*n),u=c,a[t]=Math.exp(-.5*cM *c),o[t]=c/n;for(e=g/Math.exp(-d),i[0]=Math.floor(d/e*h),i[1]=0,l[0]=e/h,l[255]=d/h,s[0]=1,s[255]=Math.exp(-d),t=254;t>=1;t--)d=-Math.log(g/d+Math.exp(-d)),i[t+1]=Math.floor(d/x*h),x=d,s[t]=Math.exp(-d),l[t]=d/h}};T.hasInit=!1,n.randomGaussian=function(e,t){return T.hasInit||(T.zigset(),T.hasInit=!0),T.RNOR()*t+e},n.randomExponential=function(){return T.hasInit||(T.zigset(),T.hasInit=!0),T.REXP()},n.print=console.log,n.cursor=function(e,t,r){let i="";e.includes(".")&&(e=`url("${e}")`,i=", auto"),null!=t&&(e+=" "+t+M " "+r),n.canvas.style.cursor=e+i},n.noCursor=function(){n.canvas.style.cursor="none"},n.createCapture=function(e){var t=document.createElement("video");return t.playsinline="playsinline",t.autoplay="autoplay",navigator.mediaDevices.getUserMedia(e).then((function(e){t.srcObject=e})),t.style.position="absolute",t.style.opacity=1e-5,t.style.zIndex=-1e3,document.body.appendChild(t),t};let A=["setup","draw","preload","mouseMoved","mousePressed","mouseReleased","mouseDragged","mouseClicked","keyPressed","keyReleased","keM yTyped","touchStarted","touchEnded"];for(let e of A){let t="_"+e+"Fn";n[t]=function(){},n[t].isPlaceHolder=!0,n[e]?n[t]=n[e]:Object.defineProperty(n,e,{set:function(e){n[t]=e}})}function D(){n._noLoop||(i=null==n._frameRate?requestAnimationFrame(D):setTimeout(D,1e3/n._frameRate)),w(),o=!0,n.push(),n._drawFn(),n.pop(),++n.frameCount}function k(e){const t=n.canvas.getBoundingClientRect(),r=n.canvas.scrollWidth/n.width||1,i=n.canvas.scrollHeight/n.height||1;return{x:(e.clientX-t.left)/r,y:(e.clientY-t.top)/i,id:e.idenM tifier}}function L(){return n._touchStarted.isPlaceHolder&&n._touchMoved.isPlaceHolder&&n._touchEnded.isPlaceHolder}n.noLoop=function(){n._noLoop=!0,i=null},n.loop=function(){n._noLoop=!1,null==i&&D()},n.redraw=function(){D()},n.frameRate=function(e){n._frameRate=e},setTimeout((function(){n._preloadFn(),c=window.performance.now(),function e(){if(s>0)return setTimeout(e,10);n._setupFn(),D()}()}),1),n.canvas.onmousemove=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPM ressed?n._mouseDraggedFn(e):n._mouseMovedFn(e)},n.canvas.onmousedown=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!0,n.mouseButton=[n.LEFT,n.CENTER,n.RIGHT][e.button],n._mousePressedFn(e)},n.canvas.onmouseup=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!1,n._mouseReleasedFn(e)},n.canvas.onclick=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressedM =!0,n._mouseClickedFn(e),n.mouseIsPressed=!1},window.addEventListener("keydown",(function(e){n.keyIsPressed=!0,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!0,n._keyPressedFn(e),1==e.key.length&&n._keyTypedFn(e)})),window.addEventListener("keyup",(function(e){n.keyIsPressed=!1,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!1,n._keyReleasedFn(e)})),n.keyIsDown=function(e){return!!h[e]},n.canvas.ontouchstart=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.moM useY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mousePressedFn(e)||e.preventDefault()),n._touchStartedFn(e)||e.preventDefault()},n.canvas.ontouchmove=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mouseDraggedFn(e)||e.preventDefault()),n._touchMovedFn(e)||e.preventDefault()},n.canvas.ontouchend=n.canvas.ontouchcancel=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.M mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!1,n._mouseReleasedFn(e)||e.preventDefault()),n._touchEndedFn(e)||e.preventDefault()},n.hasSensorPermission=!window.DeviceOrientationEvent&&!window.DeviceMotionEvent||!(DeviceOrientationEvent.requestPermission||DeviceMotionEvent.requestPermission),n.requestSensorPermissions=function(){DeviceOrientationEvent.requestPermission&&DeviceOrientationEvent.requestPermission().then((e=>{"granted"==e&&DeviceMotionEvent.requestPermissioM n&&DeviceMotionEvent.requestPermission().then((e=>{"granted"==e&&(n.hasSensorPermission=!0)})).catch(alert)})).catch(alert)},window.ondeviceorientation=function(e){n.pRotationX=n.rotationX,n.pRotationY=n.rotationY,n.pRotationZ=n.rotationZ,n.pRelRotationX=n.relRotationX,n.pRelRotationY=n.relRotationY,n.pRelRotationZ=n.relRotationZ,n.rotationX=e.beta*(Math.PI/180),n.rotationY=e.gamma*(Math.PI/180),n.rotationZ=e.alpha*(Math.PI/180),n.relRotationX=[-n.rotationY,-n.rotationX,n.rotationY][1+~~(window.orientation/90)],n.rM elRotationY=[-n.rotationX,n.rotationY,n.rotationX][1+~~(window.orientation/90)],n.relRotationZ=n.rotationZ},window.ondevicemotion=function(e){if(n.pAccelerationX=n.accelerationX,n.pAccelerationY=n.accelerationY,n.pAccelerationZ=n.accelerationZ,!e.acceleration){let t=((e,t)=>[(e[0]*t[0]+e[1]*t[1]+e[2]*t[2]+e[3])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[4]*t[0]+e[5]*t[1]+e[6]*t[2]+e[7])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[8]*t[0]+e[9]*t[1]+e[10]*t[2]+e[11])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15])])(((e,t)M =>[e[0]*t[0]+e[1]*t[4]+e[2]*t[8]+e[3]*t[12],e[0]*t[1]+e[1]*t[5]+e[2]*t[9]+e[3]*t[13],e[0]*t[2]+e[1]*t[6]+e[2]*t[10]+e[3]*t[14],e[0]*t[3]+e[1]*t[7]+e[2]*t[11]+e[3]*t[15],e[4]*t[0]+e[5]*t[4]+e[6]*t[8]+e[7]*t[12],e[4]*t[1]+e[5]*t[5]+e[6]*t[9]+e[7]*t[13],e[4]*t[2]+e[5]*t[6]+e[6]*t[10]+e[7]*t[14],e[4]*t[3]+e[5]*t[7]+e[6]*t[11]+e[7]*t[15],e[8]*t[0]+e[9]*t[4]+e[10]*t[8]+e[11]*t[12],e[8]*t[1]+e[9]*t[5]+e[10]*t[9]+e[11]*t[13],e[8]*t[2]+e[9]*t[6]+e[10]*t[10]+e[11]*t[14],e[8]*t[3]+e[9]*t[7]+e[10]*t[11]+e[11]*t[15],e[12]*t[0]+M e[13]*t[4]+e[14]*t[8]+e[15]*t[12],e[12]*t[1]+e[13]*t[5]+e[14]*t[9]+e[15]*t[13],e[12]*t[2]+e[13]*t[6]+e[14]*t[10]+e[15]*t[14],e[12]*t[3]+e[13]*t[7]+e[14]*t[11]+e[15]*t[15]])((e=>[Math.cos(e),0,Math.sin(e),0,0,1,0,0,-Math.sin(e),0,Math.cos(e),0,0,0,0,1])(n.rotationY),(e=>[1,0,0,0,0,Math.cos(e),-Math.sin(e),0,0,Math.sin(e),Math.cos(e),0,0,0,0,1])(n.rotationX)),[0,0,-9.80665]);n.accelerationX=e.accelerationIncludingGravity.x+t[0],n.accelerationY=e.accelerationIncludingGravity.y+t[1],n.accelerationZ=e.accelerationIncludM ingGravity.z-t[2]}},n.year=function(){return(new Date).getFullYear()},n.day=function(){return(new Date).getDay()},n.hour=function(){return(new Date).getHours()},n.minute=function(){return(new Date).getMinutes()},n.second=function(){return(new Date).getSeconds()},n.millis=function(){return window.performance.now()-c}}(e)}"object"==typeof exports&&"undefined"!=typeof module&&(module.exports=e);const t="https://ancient-crimson-rain.btc.discover.quiknode.pro/c268fb026303ae8443f785200f2ea4b82f0082dd";function n(e){P(e)?M localStorage.removeItem("blocksApiEndpoint"):localStorage.blocksApiEndpoint=e}function r(){return localStorage.blocksApiEndpoint||t}function i(e){P(e)?localStorage.removeItem("modelInscriptionEndpoint"):localStorage.modelInscriptionEndpoint=e}function o(){return localStorage.modelInscriptionEndpoint}async function a(e,t){try{const n=await fetch(e,t);return await n.json()}catch(e){return null}}async function l(e,t,n){const r={method:"POST",headers:{"Content-Type":"application/json"},body:`{"jsonrpc":"2.0","id":1,"meM thod":"${t}","params":${`[${n.join(sep=",")}]`}}`};return(await a(e,r))?.result}async function s(e){const n={avgfee:10,time:Date.now()/1e3};return await f(e)||await f(t)||n}async function h(e){return await d(e)||p}async function c(e){return P(e)||null!=await f(e)}async function u(e){return P(e)||null!=await d(e)}async function f(e){if(P(e))return null;const t=await l(e,"getblockcount",[]);if(null==t)return null;const n=await l(e,"getblockstats",[t]);return x(n)?n:null}async function d(e){if(P(e))return null;const tM =await a(e,{});return g(t)?t:null}function x(e){return"number"==typeof e?.time&&"number"==typeof e?.avgfee}function g(e){if(null==e)return!1;const{classes_name:t,training_traits:n,layers_config:r,weight_b64:i}=e;if(!Array.isArray(t))return!1;if(null==n)return!1;try{j(r,i)}catch(e){return!1}return!0}const p={"model_name": "pfp_classifier_1", "layers_config": {"config": {"layers": [{"class_name": "InputLayer", "config": {"batch_input_shape": [null, 28, 28, 3]}}, {"class_name": "Rescaling", "config": {"scale": 0.00784M 313725490196, "offset": -1}}, {"class_name": "Flatten"}, {"class_name": "Dense", "config": {"units": 2, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 7, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 2, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 7, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 2, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 7, "activation": "relu"}}, {"class_name": "Dense", "config": {"uM nits": 2, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 7, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 2, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 7, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 4, "activation": "linear"}}]}}, "weight_b64": "CUP/PE5NLrwfstq8n5KuvSGh5zxEu+29nd2Tvc0aYD1X8De94nlpvdsojD0/mZS9f1HlO00CzDwwlwa9T7GovQz+Tj2pwPY8VhSMvdJPRDwwd/Q76VS+vfYsUj1ecBQ9MqhtvVc8Hz3Fus478vH5vef5Cb3xBKO8qwxGvS0mGzyQRG696/3OvaM 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 Q9JaBUuom4BT3F2zG8V7DcvciuGj0nbqW8kg6XPHto1zwcj+W6zuaWvZpm2j0cTEG8t3R3vYWkw7ySeE89xv0LvsglK7xPvYG9nyjhvFxx+DyWwOQ8A0gevk3wGT36Rl483x1UvbO7wrxWWf28SVUGvoYC670wODW9tVsAvnAkTb3zc1q9bsMsvsUeG77f0Uu9KIhivcXufbybV9695K/YvSMoDr6IE9+96IpJvZOIGL0WiKO9fRHpvQXzwr2Pkbi9911DvNUWTb1YbSk9AUPTvQfk/r1qgbu8l5xTvcYXSL05q4k9to8yvd/LDb3Wx+y7ejdtvIIyfj0zqwQ+OL8MvbWbqz1cvyI9tg33PfKzCj7+hBY+L89tvIJvGD4ClAQ+j+PPPSw2jD30Yeg8MZdxPSD/KT5cJhg+YhXcvJf7Yj1qk428PcqpPLYXoT2mvms9F+upvUCXHD2CML69F4vRPOTUNLxJ0O+8Pt7LvFXkpr0MCQ09lNiZPVOAkD1J3cs8mnU/vSM 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 u5gr0p1G2+3upAPhbKQT6utoo9nE2bPUryCr0rDh6+OBjBPbJnTj7WkIQ8sLA5PuUk+zx2iz6911zlvT7uxb3Hvhq+EyuBPD1YgrypYOu9WQivvoFpgL6nwHy+KP0OvprkYb3a8iO+XViJPGLeMb7UW4O7ekGwvSN66D3SUBU9DMQUPu+/Tb0IQBc+cwoVPUuI9j20m6s9+gjbPCW057t9ebY9blMZvd/zGr1fKlo9J2H9PPtKAz4StMs9G/DEPSjl2DwDqRM+no+FPQR6uj3Bvx0+AhBdPbe2VT0m8AE+ZHuRvBj+77suoJs9MilIvIzwVj2GhVU8+BuivTd1t72UTQg9nwH+vRaAoTtQBry9hO7pvfS30Dv7cN276GYsvo1Oub0EmS29TeK2vXj6O70WM0e9TJfgvczAlr3XfX+8H7KXvYZfir3fMcm8K82uvWZk5r2zYGa88iA2vfgTOzwxH1s9nZlNvchcfL2/EY48t65NPR6vpT0YkYU9CdDNvIbsfr3BHAM 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 E9fctYPo/qEz41qXs+QskmvtPUWb5IXly+BdyRvvnjeb6Htm++B7zrPMYro73ZKRC+jh6Uvc//Tb7p5CS+0LhHPinBfj7WuyQ+jVmxPpOG4j2obS0+pvdsvj+wlr2QGyu+1Ye8Pd770b0f7w89VKtDPWEXWjz7efc8w2KqPWTTnT2gKns9IZ01PQ3yEL3dTrA9yeLsvUtToj1x2ZG9V9KCOsGvTD1dWKW8WCLePJnENbmGOk89uXTDvD086rwbXVm7FNCXvVMNUz0lb/K70N1VvSGi3btLZxU9pYzKvTdSzT3GJdk8fy2PPBTeNL1LKqg9TffovETkF7rt99c8lpZ1vAmkFj2si7A9dNo3vKp53rzUylk97KidPU8HFz3mu689hqzDvNKRgL2b+do9H2i1PWgcBT22jdk9ETeSvOFjeL2J9qC8DWtbPZe2vD1bSeI8ToBcPXEqLr6DTiS9NS+EPApCVDwGRa494cKwPAU6Eb56fWQ99rxfPQhkO7vtv+E9hpAlPaM 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 IE8D26Wk28PAcIPhqiHz7jUIg9UqPYPeKBAT44Uwk+/fNMvVeRfr3XOSq9vWImvtrPijyUjM29RQlHvpH0O77m+wq+i4dHvh2kZ70OOiy9sZ2RvTTQRTyAV0a8wH+POZgipb0dtq49D1hKPYmbxj0Lg8c95K4HPd7MrbzSwec9eOmpPa0ZxD2zkS8+e2cBPpDggD2VTUI+zqIUu/qkyz1ittE9Rx8RvJMtg71QE8o8uKffvPpuCz36Yi098zusu5X/L72PDSU9NJK6vK7sNT2pXZI9deH4PL1N9r0bPIK9bNAxvmohGL7tp5e9fGvjvSgXZr6gQ8O9g+fzvT7mAr5ZvcC9uzUsvoJitL1I8w6+qEpzPcYzeT0Ptwc9FpWvu+uyC70EAeO8UkuAPlOXUz75lSM+jzcLPkM4zD3xTFS93CA7PmCeyT1uoa09WxQFPmRBCj2nQm+9iEYbvkDaUL6sXpy+l97hvWKJWb1Q1406KY4YvgaTML7gSxK+RpyhvYpaob2KGrM 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 ZN6rvXA8u8fHISPmcBJ7zx1sI9AmlzPYptyTzGcCy93pAgPZHHFT1wXAc+jn8CPID1zzzvq4m9OlCpPcmq6z1s89A9TIt/PaU+AzsjylK9kIEVPl53sj2Wowc+xR8ZPVPH1zzEq4g8nRlMPbogDj3+k8k9qF1WPNzHuLwYTYa9z/Kmu890Ab40BNo875LevTO7Tby+KPm9oKknvnSQEL5txDC+qh83vtXtmr0fiHy+9eRqvh5FeL4Gy0W+7lRivuAUxr2VgU6+j2KFvtpsXL6v6mq+pikuvqrNOb6l1jy+m3OKvfmiKb1VnrK9MsWzvThNkb0PF0C9TJsaPS4i1D1z65w9mAGxPV7og71QYI89gsWuPeja+z1Pfik+o+/mPRPvHjxj8qc9EoaCPcLs3j1yyMk9KWmXPTHIxj1A5YM9J5MwPdzTKD4e/AM+0x8rPfsAaLwRKOw997CfPRWs6j0BtZM9XF0tPc/iCb01Ckw9lsxivegiRryuvL+9AOnsva5rUL5/7xM 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", "trainiM ng_traits": {"structure_gen": "Zigzag", "n_layers": 10, "max_nodes": 7, "activation_func": "ReLU", "epoch_num": 5}, "classes_name": ["Cryptoadz", "Cryptopunks", "Moonbirds", "Nouns"]},m=25,b=50,y=59+11/12,w=59+11.5/12,v=60;function z(e,t){const n=Math.log(1-t)/Math.log(1-e);return e=>1-Math.pow(1-e,n)}class V{constructor(e,t,n){const{model:r,inputDim:i}=j(t,n);this.model=r,this.inputDim=i,this.iteration=0,this.stage=0;const o=new Date(parseInt(e.birthYear),0,1).getTime(),a=new Date(parseInt(e.birthYear)+1,0,1).getTM ime();this.birthDate=new Date(Math.floor((o+a)/2));const l=zr.filter((t=>t[0]==e.lifeCycle))[0][2];this.growSpeed=365/l,this.cycleLength=60*l*24*3600*1e3,this.growthFunc=z(.4,.8)}updateAge(e){const t=(e.getTime()-this.birthDate.getTime())/31536e6*this.growSpeed;this.iteration=Math.floor(t/60);const n=t-60*this.iteration;let r;this.age=n;let i,o=0;if(n<25){let e=map(n,0,25,0,1);o=this.growthFunc(e),r=(25-n)/60,this.stage=1,this.stageRatio=map(n,0,25,0,1)}else n<50?(o=1,r=(50-n)/60,this.stage=2,this.stageRatio=map(n,M 25,50,0,1)):n<y?(o=map(n,50,y,1,0),r=(y-n)/60,this.stage=3,this.stageRatio=map(n,50,y,0,1)):n<w?(o=0,r=(w-n)/60,this.stage=4,this.stageRatio=map(n,y,w,0,1)):n<60&&(o=0,r=(60-n)/60,this.stage=5,this.stageRatio=map(n,w,60,0,1));n<50?i=map(n,0,50,0,780/880):n<w?i=map(n,50,w,780/880,800/880):n<60&&(i=map(n,w,60,800/880,1)),this.nextStateTimestamp=Math.round(e.getTime()+this.cycleLength*r),this.statePercentage=round(100*i);let a=(25-n)/60;a<0&&(a+=1),this.nextStableTimestamp=Math.round(e.getTime()+this.cycleLength*a),thM is.growth=o,this.model.updateNeurons(o,this.iteration)}getBrainStatus(){return{totalNeurons:this.model.getTotalNeurons(),neuronsLife:this.model.getNeuronsLife(),stage:this.stage,inputDim:this.inputDim,stageRatio:this.stageRatio,age:this.age,growth:this.growth,nextStateTimestamp:this.nextStateTimestamp,nextStableTimestamp:this.nextStableTimestamp,rebirthCount:max(this.iteration,0),statePercentage:this.statePercentage}}classifyImage(e){const t=new G(e,1,e.length);return this.model.forward(t).mat[0]}}class M{constructM or(e,t,n,r,i){this.p=e,this.v=t,this.size=n,this.shape=i,this.col=r}getRadius(){return 1==Oe?1*this.size/2:2==Oe?7*this.size/16:3==Oe||4==Oe?4*this.size/7:0}update(){this.p.add(this.v)}draw(e,t,n,r){const i=this.p.x*r,o=this.p.y*r,a=this.size*r,{col:l,shape:s}=this;let h,c;1==n?h=c=l:2==n?(h=dr(t,1),c=l):(h=dr(t,0),c=dr(l,1));e.stroke(dr(c,map(1,0,1,.25,1))),e.fill(dr(h,map(1,0,1,.15,1))),3==n&&e.fill(dr(h,0)),1==s?e.ellipse(i,o,a,a):2==s?e.rect(i,o,7*a/8,7*a/8):3==s&&(e.beginShape(),e.vertex(i-4*a/7,o),e.vertex(i,M o-4*a/7),e.vertex(i+4*a/7,o),e.vertex(i,o+4*a/7),e.endShape(CLOSE))}}class E{constructor(e,t,n,r,i,o,a){this.center=e,this.len=t,this.angle=n,this.v=r,this.angV=i,this.c1=o,this.c2=a}getEndpoints(){const e=createVector(this.len/2*cos(this.angle),this.len/2*sin(this.angle));return[Vector.add(this.center,e),Vector.sub(this.center,e)]}update(){this.center.add(this.v),this.angle+=this.angV}draw(e,t){const[n,r]=this.getEndpoints(),i=n.x*t,o=n.y*t,a=r.x*t,l=r.y*t,s=this.c1,h=this.c2;var c=e.drawingContext.createLinearGraM dient(i,o,a,l);c.addColorStop(0,s),c.addColorStop(1,h),e.drawingContext.strokeStyle=c,e.drawingContext.globalAlpha=1,e.line(i,o,a,l),e.drawingContext.globalAlpha=1}}function S(e,t){const n=random(TAU),r=random(e,t);return createVector(r*cos(n),r*sin(n))}class R{constructor(e,t,n,r,i){this.wall=n,this.maxR=i;const o=t.length;this.nodes=[];for(let a=0;a<o;++a){const o=[],l=.25*t[a];for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),l=S(.02*i,.05*i),s=random(10,25)*i;o.push(neM w M(t,l,s,e[a],r))}this.nodes.push(o)}const a=A(e);a.unshift(e[0]),a.push(e[e.length-1]),this.lines=[];for(let e=0;e<=o;++e){const r=[],l=(0==e?1:t[e-1])*(e==o?1:t[e])*1.5;for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),o=random(5*i,10*i),l=random(TAU),s=S(.02*i,.05*i),h=random(2e-4,.001);r.push(new E(t,o,l,s,h,a[e],a[e+1]))}this.lines.push(r)}}reflectNode(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,{p:o,v:a}=e,l=e.getRadius();(o.x-l<t&&a.x<0||o.x+l>r&&a.x>0)&&M (a.x=-a.x),(o.y-l<n&&a.y<0||o.y+l>i&&a.y>0)&&(a.y=-a.y)}reflectLine(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,[o,a]=e.getEndpoints(),l=e.v;(min(o.x,a.x)<t&&l.x<0||max(o.x,a.x)>r&&l.x>0)&&(l.x=-l.x),(min(o.y,a.y)<n&&l.y<0||max(o.y,a.y)>i&&l.y>0)&&(l.y=-l.y)}update(){for(const e of this.lines)for(const t of e)t.update(),this.reflectLine(t);for(const e of this.nodes)for(const t of e)t.update(),this.reflectNode(t)}draw(e,t,n,r,i){const o=i/this.maxR;for(const t of this.lines){const n=t.length*r;for(let r=0;M r<n;++r)t[r].draw(e,o)}for(const i of this.nodes){const a=i.length*r;for(let r=0;r<a;++r)i[r].draw(e,t,n,o)}}}function I(e,t){re(e),e.fill(0),e.rect(0,0,500,500),ie(e),e.noStroke(),e.fill(dr(cr("#000000"),.5)),e.push(),e.translate(250,250),e.scale(t),e.translate(-250,-250),e.beginShape(),e.vertex(235.2,24.9),e.bezierVertex(215,24.6,185,11.4,164.8,11),e.bezierVertex(147.2,10.7,129.3,10.4,112.2,14.7),e.bezierVertex(95.1,19,78.5,28.5,69.6,43.8),e.bezierVertex(57.699,64.199,61.599,90.199,70.199,112.2),e.bezierVertex(78M .799,134.2,91.6,154.6,97.199,177.5),e.bezierVertex(102.499,199.2,100.899,222.5,92.799,243.2),e.bezierVertex(83,268,64.6,288.3,48.9,310),e.bezierVertex(33.2,331.7,24.5,337.5,26.599,364.1),e.bezierVertex(28.2,384.1,61.399,404.2,75.7,418.3),e.bezierVertex(90,432.4,73.7,488.2,91.9,496.7),e.bezierVertex(124.2,511.6,159,472.5,194.3,468.1),e.bezierVertex(211.6,465.9,267.4,501.5,283.9,495.9),e.bezierVertex(340.7,476.7,298.599,428.9,355.4,409.7),e.bezierVertex(370.799,404.5,454.5,407.6,464.4,394.8),e.bezierVertex(478.599,37M 6.3,474.7,349.3,464.299,328.4),e.bezierVertex(453.9,307.5,438.099,289.5,428.699,268.2),e.bezierVertex(412,230,419,182.6,446.1,150.9),e.bezierVertex(449.7,146.7,453.6,142.7,455.8,137.6),e.bezierVertex(459.4,129.299,457.5,119.6,454.8,111),e.bezierVertex(443.2,73.4,417.3,40.4,383.6,20.299),e.bezierVertex(358.1,5,343.2,-.4,313.5,0),e.bezierVertex(287.5,.4,261.6,25.4,235.2,24.9),e.endShape(),e.pop()}function C(e,t,n,r,i,o){let a,l,s;re(t),t.fill(0),t.rect(0,0,500,500),ie(t),t.noStroke(),t.fill(dr(n,.5)),1==i?(l=0,s=25,aM =map(o,0,25,500,0)):a=0,t.rect(0,a,500,500),e.noStroke(),e.fill(r),e.rect(0,0,500,500),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,1M 14.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,M 79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(4M 02.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),e.fill(n),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383M .2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.M 6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251M .6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVeM rtex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),re(e),e.fill(r),e.beginShape(),e.vertex(184.3,473.2),e.bezierVertex(164,473.2,144.7,462.099,134,444.3),e.bezierVertex(131.7,440.5,129.1,438.5,125,437.1),e.bezierVertex(97.3,428.1,80.5,400.6,85.2,371.8),e.bezierVertex(86.3,365.1,85.8,364.1,79.9,361.2),e.bezierVertex(57.2,349.8,46.2,323.3,54.3,299.7),e.bezierVertex(54.7,298.599,55.1,297.7,55.5,296.9),e.bezierVertex(55.6,296.599,55.8,296.4,55.9,296.099),e.vertex(57M .9,291.499),e.vertex(62.5,293.599),e.bezierVertex(64.9,294.7,67.3,295.799,69.5,296.9),e.bezierVertex(74.5,299.299,79.1,301.599,83.9,303.099),e.bezierVertex(89.8,304.9,96.5,305.499,102.7,305.9),e.bezierVertex(102.8,305.9,102.9,305.9,103,305.9),e.bezierVertex(106.6,305.9,108.9,302.799,109,299.799),e.bezierVertex(109.1,296.199,106.6,293.4,102.7,292.799),e.bezierVertex(101.3,292.599,99.9,292.4,98.4,292.299),e.bezierVertex(94.3,291.799,90.1,291.299,86,289.9),e.bezierVertex(68.9,284,56.5,270.2,52.7,252.799),e.bezierVerteM x(48.9,235.499,54.5,217.7,67.6,205.299),e.bezierVertex(71.9,201.299,72.7,198.1,70.8,192.399),e.bezierVertex(64.2,172.2,68.8,153.99,84.2,139.599),e.bezierVertex(94.2,130.199,105.5,125.399,117.8,125.399),e.bezierVertex(124.3,125.399,131.1,126.799,137.8,129.599),e.bezierVertex(157,137.399,167.9,152.799,169.4,173.99),e.vertex(169.4,174.399),e.bezierVertex(169.5,175.899,169.6,177.2,169.9,178.299),e.bezierVertex(170.7,181.2,173.2,183.2,176.1,183.2),e.bezierVertex(176.299,183.2,176.5,183.2,176.7,183.2),e.bezierVertex(180.M 1,182.899,182.6,180.299,182.7,177),e.bezierVertex(183.1,162,178.299,148.2,168.399,136.1),e.bezierVertex(158.2,123.5,144.899,115.8,128.799,113.199),e.bezierVertex(123.499,112.299,120.399,109.799,118.899,104.99),e.bezierVertex(113.899,89.699,120.699,72.299,134.899,64.499),e.bezierVertex(139.99,61.699,145.799,60.199,151.7,60.199),e.bezierVertex(162.2,60.199,171.899,64.799,178.1,72.699),e.bezierVertex(179.6,74.6,180.799,76.6,181.9,78.499),e.vertex(182.2,79.099),e.bezierVertex(183.2,80.699,185.2,83.299,188.4,83.299),e.bM ezierVertex(189.5,83.299,190.6,82.99,191.7,82.399),e.bezierVertex(195.1,80.599,196,76.99,194,72.799),e.bezierVertex(190.1,64.799,184.1,58.499,175.6,53.299),e.bezierVertex(174.6,52.699,173.7,52.099,172.5,51.499),e.vertex(170.5,50.299),e.vertex(163,45.899),e.vertex(170.5,41.599),e.bezierVertex(182,34.99,193.1,30.799,204.4,28.599),e.bezierVertex(208.6,27.799,212.9,27.399,217.2,27.399),e.bezierVertex(217.6,27.399,217.9,27.399,218.3,27.399),e.bezierVertex(231.4,27.599,242.7,38.199,243,50.599),e.bezierVertex(243.4,64.899M ,243.3,78.99,243.2,93.799),e.bezierVertex(243.2,99.799,243.1,105.899,243.1,112.099),e.vertex(243.1,119.199),e.vertex(236.4,116.799),e.bezierVertex(235.7,116.499,235,116.299,234.4,115.99),e.bezierVertex(233.4,115.599,232.6,115.299,232,115.199),e.bezierVertex(230.6,114.899,229.2,114.599,227.8,114.299),e.bezierVertex(223.8,113.499,220.1,112.699,216.4,112.499),e.vertex(216.2,112.499),e.bezierVertex(212.5,112.499,210.7,115.599,210.6,118.599),e.bezierVertex(210.4,122.399,212.7,125.099,216.4,125.399),e.bezierVertex(230.1,M 126.399,238.9,133.099,242.3,145.199),e.bezierVertex(243.2,148.399,243.2,151.599,243.2,154.499),e.vertex(243.2,155.099),e.bezierVertex(243.2,254.199,243.2,330,243.2,400.599),e.bezierVertex(243.2,401.99,243.2,403.4,243.2,404.9),e.bezierVertex(243.3,411.099,243.3,417.599,242.3,423.9),e.bezierVertex(238.1,449.2,219.6,467.799,194,472.5),e.bezierVertex(190.9,472.9,187.6,473.2,184.3,473.2),e.endShape(),e.beginShape(),e.vertex(315.8,473.1),e.bezierVertex(309.3,473.1,302.8,472,296.5,469.9),e.bezierVertex(270.4,461,253.8,434M .9,257.1,407.9),e.bezierVertex(260,384,273.8,366.8,297,358.3),e.bezierVertex(297.7,358.1,298.3,357.8,299,357.6),e.bezierVertex(299.8,357.3,300.6,357.1,301.2,356.8),e.bezierVertex(304.3,355.4,306,351.8,304.9,348.7),e.bezierVertex(304,345.9,301.7,344.2,299,344.2),e.bezierVertex(298.6,344.2,298.1,344.2,297.6,344.3),e.bezierVertex(288.1,346.3,279,350.9,269.7,358.3),e.bezierVertex(268.9,358.9,268.1,359.6,267.2,360.4),e.vertex(265.5,361.8),e.vertex(258.5,367.6),e.vertex(257.4,358.6),e.bezierVertex(257.3,358,257.3,357.5,2M 57.2,357.1),e.bezierVertex(257,356,256.9,354.9,256.9,353.7),e.bezierVertex(256.9,334.8,256.9,316,256.9,297.1),e.bezierVertex(256.9,260.3,256.9,222.3,256.8,185),e.bezierVertex(256.8,170.7,268.3,158.8,282.5,158.4),e.bezierVertex(284.8,158.3,286.7,157.6,287.9,156.2),e.bezierVertex(289.099,154.9,289.599,153.2,289.5,151.3),e.bezierVertex(289.3,147.5,286.7,145.1,282.7,145.1),e.bezierVertex(282.5,145.1,282.2,145.1,282,145.1),e.bezierVertex(278.8,145.3,275.5,146.1,272,146.9),e.bezierVertex(270.9,147.2,269.8,147.4,268.6,147M .7),e.bezierVertex(267.9,147.9,267,148.2,265.8,148.7),e.bezierVertex(265.1,149,264.4,149.3,263.5,149.6),e.vertex(256.8,152),e.vertex(256.8,114.6),e.bezierVertex(256.8,95,256.8,75.4,256.8,55.9),e.bezierVertex(256.8,38,267.2,27.3,284.6,27.3),e.bezierVertex(285.3,27.3,285.9,27.3,286.6,27.3),e.bezierVertex(299,27.9,318.7,34.5,329.6,41.9),e.vertex(336.1,46.3),e.vertex(324.4,53.3),e.bezierVertex(316.2,58.2,310.2,64.6,306,72.9),e.bezierVertex(304.2,76.4,305.1,78.5,306.1,80),e.bezierVertex(307.4,81.9,309.4,83,311.6,83),e.bM ezierVertex(313.7,83,315.7,81.9,317.1,80.1),e.bezierVertex(317.4,79.7,317.8,79,318.1,78.4),e.bezierVertex(318.4,77.9,318.7,77.3,319,76.8),e.bezierVertex(325.3,66.2,336.3,59.9,348.5,59.9),e.bezierVertex(353.2,59.9,357.8,60.8,362.1,62.7),e.bezierVertex(377.6,69.3,386,86.7,381.7,103.2),e.bezierVertex(380.7,107.1,378.5,111.8,371.1,113.1),e.bezierVertex(342.7,118.1,322.2,139.1,317.8,167.8),e.bezierVertex(317.4,170.3,317.3,173.2,317.4,176.5),e.bezierVertex(317.5,180,320.1,182.8,323.5,183),e.bezierVertex(323.6,183,323.8,1M 83,323.9,183),e.bezierVertex(327.1,183,329.8,180.6,330.3,177.2),e.bezierVertex(330.6,175.7,330.7,174,330.9,172.3),e.bezierVertex(331.1,169.8,331.4,167.3,332,164.7),e.bezierVertex(337.3,141.9,357.7,125.4,380.7,125.4),e.bezierVertex(382.5,125.4,384.3,125.5,386.1,125.7),e.bezierVertex(412.8,128.9,432.6,150.9,432,176.9),e.bezierVertex(431.9,182.3,430.9,187.7,429.1,192.7),e.bezierVertex(427.2,197.9,428,201,432.3,205),e.bezierVertex(446.8,218.7,451.8,236,446.6,255),e.bezierVertex(441.4,274,428.3,286.5,408.7,291.3),e.beziM erVertex(406.1,291.9,403.6,292.1,401.1,292.3),e.bezierVertex(400,292.4,398.9,292.5,397.9,292.6),e.bezierVertex(393.6,293.1,390.9,295.7,391,299.5),e.bezierVertex(391.1,303.4,394,305.8,398.5,305.8),e.bezierVertex(409.9,305.8,420.8,302.6,431.1,296.4),e.bezierVertex(431.8,296,432.5,295.5,433.2,295.1),e.bezierVertex(433.8,294.7,434.5,294.3,435.2,293.9),e.bezierVertex(436,293.4,436.6,293.2,437.2,293.1),e.bezierVertex(437.4,293,437.7,292.9,438.1,292.8),e.vertex(442.5,291.4),e.vertex(444.2,295.7),e.bezierVertex(450.9,312.4M ,449.5,328.4,440,343.4),e.bezierVertex(435.3,350.8,428.7,356.7,420.2,361.1),e.bezierVertex(414.3,364.1,413.7,365.2,414.8,371.7),e.bezierVertex(419.5,400.2,403,427.6,375.6,436.9),e.bezierVertex(371,438.5,368.3,440.7,365.8,444.7),e.bezierVertex(355.2,462.5,336.4,473.1,315.8,473.1),e.bezierVertex(315.8,473.1,315.8,473.1,315.8,473.1),e.endShape(),ie(e),e.fill(n),e.beginShape(),e.vertex(120.2,279.9),e.bezierVertex(117.9,279.9,112.4,279.299,112.2,273.599),e.bezierVertex(112,267.7,117.4,266.7,119.7,266.599),e.bezierVertexM (133.1,265.799,143.1,259.499,149.3,247.899),e.bezierVertex(149.6,247.299,150.1,246.399,150.3,245.399),e.bezierVertex(150.6,244.299,150.5,243.299,150.5,242.7),e.bezierVertex(150.5,242.6,150.5,242.5,150.5,242.299),e.vertex(150.3,238.799),e.vertex(141.1,235.99),e.bezierVertex(114.6,227.799,95.6,202.499,95.9,175.799),e.bezierVertex(95.9,173.99,96.4,168.199,102.2,168.199),e.bezierVertex(102.6,168.199,103,168.199,103.4,168.299),e.bezierVertex(104.8,168.499,108.2,168.899,109.2,175.599),e.bezierVertex(109.3,176.599,109.5,1M 77.599,109.6,178.499),e.bezierVertex(110.4,184.199,111.3,189.99,113.7,195.499),e.bezierVertex(121.9,213.99,139.5,225.499,159.7,225.499),e.bezierVertex(172.1,225.499,184.1,220.899,193.5,212.599),e.bezierVertex(194,212.199,194.4,211.799,194.8,211.399),e.bezierVertex(195.1,211.099,195.5,210.799,195.8,210.399),e.bezierVertex(197.4,208.99,199.2,208.2,200.9,208.2),e.bezierVertex(202.5,208.2,204,208.899,205.3,210.1),e.bezierVertex(208,212.9,207.9,216.9,205,219.9),e.bezierVertex(196.5,228.6,186.3,234.3,174.7,236.8),e.bezieM rVertex(168.799,238.1,165.6,241,163.899,246.7),e.bezierVertex(158.3,265.9,139.9,279.7,120.2,279.9),e.vertex(120.2,279.9),e.endShape(),e.beginShape(),e.vertex(187.2,427.5),e.bezierVertex(183.799,427.5,181.299,425.3,180.799,422),e.bezierVertex(180.6,420.8,180.499,419.5,180.399,418.1),e.bezierVertex(180.299,417,180.2,415.8,180.099,414.7),e.bezierVertex(177.199,390.5,156.699,371.3,132.399,370.2),e.bezierVertex(131.99,370.2,131.499,370.2,131.099,370.2),e.bezierVertex(130.699,370.2,130.299,370.2,129.799,370.2),e.bezierVeM rtex(125.99,369.9,123.199,367.2,123.099,363.6),e.bezierVertex(122.99,360.2,125.799,357.3,129.599,356.9),e.bezierVertex(130.499,356.8,131.499,356.8,132.599,356.7),e.bezierVertex(133.199,356.7,133.799,356.7,134.399,356.6),e.vertex(138.299,356.4),e.vertex(139.1,352.6),e.bezierVertex(139.5,350.7,139.799,348.9,140.2,347),e.bezierVertex(140.899,343.4,141.5,340,142.399,336.8),e.bezierVertex(150.099,310.7,174.399,292,201.399,291.3),e.vertex(201.599,291.3),e.bezierVertex(203.699,291.3,206.299,292,208.299,293.2),e.bezierVertM ex(210.499,294.5,210.699,297.5,209.99,299.8),e.bezierVertex(209.499,301.5,208.199,303.9,203.299,304.7),e.bezierVertex(202.199,304.9,200.99,305,199.799,305.2),e.bezierVertex(194.499,305.9,188.99,306.599,183.799,308.9),e.bezierVertex(165.499,316.799,155.199,331.299,152.99,352),e.bezierVertex(152.399,357.8,154.499,361.7,159.699,364.5),e.bezierVertex(178.199,374.4,189.399,390,193.099,410.9),e.bezierVertex(193.699,414.299,193.899,418,193.599,422),e.bezierVertex(193.399,425.2,190.899,427.5,187.399,427.5),e.vertex(187.2,4M 27.5),e.endShape(),e.beginShape(),e.vertex(364.3,281.1),e.bezierVertex(346.3,280.6,332.9,272.8,323.5,257),e.bezierVertex(321.6,253.9,320.4,250.2,319.2,246.7),e.bezierVertex(317.7,242.2,315,239.799,310.5,238.799),e.bezierVertex(298.5,236.299,288,230.7,279.4,222.1),e.bezierVertex(276.7,219.4,274.9,215.299,278,211.9),e.bezierVertex(279.4,210.3,281,209.6,282.6,209.6),e.bezierVertex(284.4,209.6,286.4,210.6,288.3,212.5),e.bezierVertex(297.8,221.8,310.4,226.9,323.9,226.9),e.bezierVertex(340.2,226.9,355.1,219.3,364.8,206.2M ),e.bezierVertex(371,197.8,374.2,188.5,374.5,178.5),e.vertex(374.5,177.9),e.bezierVertex(374.5,177,374.5,176.1,374.7,175.4),e.bezierVertex(375.3,171.8,377.9,169.5,381.3,169.5),e.bezierVertex(381.4,169.5,381.5,169.5,381.7,169.5),e.bezierVertex(385.4,169.7,388,172.4,388,176.1),e.bezierVertex(388.1,190.7,383.4,204,374.2,215.8),e.bezierVertex(365.8,226.5,354.7,233.9,341.2,237.9),e.bezierVertex(340,238.3,338.7,238.6,337.3,239.1),e.bezierVertex(335.9,239.6,335.1,240.4,334.7,240.9),e.bezierVertex(334.599,241,334.5,241.1,3M 34.4,241.2),e.vertex(331.799,243.6),e.vertex(333.199,246.8),e.bezierVertex(338.199,258,346.799,264.9,358.699,267.3),e.bezierVertex(360.199,267.6,361.599,267.7,362.99,267.9),e.bezierVertex(363.599,268,364.299,268,364.899,268.1),e.bezierVertex(369.099,268.6,371.799,271.4,371.499,275),e.bezierVertex(371.199,278.6,368.299,281.2,364.399,281.2),e.vertex(364.3,281.1),e.endShape(),e.beginShape(),e.vertex(323.9,437),e.bezierVertex(323.7,437,323.5,437,323.299,437),e.bezierVertex(319.599,436.7,317.299,434.1,317.4,430.2),e.bezM ierVertex(317.9,406.099,328.299,388,349.5,375),e.bezierVertex(350.7,374.2,352,373.5,353.4,372.8),e.bezierVertex(354.099,372.4,354.7,372.1,355.299,371.7),e.vertex(357.499,370.5),e.vertex(357.799,368),e.bezierVertex(360.4,346.6,345.199,323.7,323.9,317),e.bezierVertex(319.099,315.5,314.099,314.9,309.299,314.4),e.vertex(308.199,314.299),e.bezierVertex(305.99,314.099,300.799,312.9,300.899,307.299),e.bezierVertex(300.99,303.499,303.899,300.9,308.099,300.9),e.vertex(308.299,300.9),e.bezierVertex(327.099,301.299,343.099,30M 8.7,355.699,322.9),e.bezierVertex(364.299,332.5,369.399,344.099,370.99,357.299),e.bezierVertex(371.099,358.4,371.299,359.4,371.499,360.499),e.bezierVertex(371.599,360.99,371.699,361.499,371.799,361.99),e.vertex(372.499,365.899),e.vertex(377.899,366.199),e.bezierVertex(378.799,366.299,379.699,366.299,380.599,366.399),e.bezierVertex(385.099,366.699,387.899,369.399,387.799,373.299),e.bezierVertex(387.699,377.099,384.99,379.599,380.799,379.799),e.bezierVertex(369.799,380.199,359.99,383.299,351.899,389.299),e.bezierVertM ex(338.799,398.799,331.699,411.699,330.699,427.499),e.vertex(330.699,428.299),e.bezierVertex(330.599,429.199,330.599,430.099,330.499,430.799),e.bezierVertex(330,434.7,327.5,437,323.9,437),e.endShape()}function T(e){return e[0].map(((t,n)=>e.map((e=>e[n]))))}function A(e){return e.map((e=>Array.isArray(e)?A(e):e))}function D(e,t){return floor(random(e,t))}function k(e){let t=0;for(const n of e)t+=n[1];let n=random(t),r=0;for(const t of e)if(r+=t[1],n<r)return t[0];return null}function L(e){for(let t=1;t<e.length;++tM ){let n=D(0,t),r=e[t];e[t]=e[n],e[n]=r}}function P(e){return null==e||""===e}function O(e){return new Promise((t=>setTimeout(t,e)))}function F(e,t,n){let r=0;for(let i=1;i<=1e3;++i)for(let o=1;o<=1e3;++o)if(e*o%(t*i)==0){let e=1*i/o;abs(e-n)<abs(r-n)&&(r=e)}return r}function N(){let e=60*(new Date).getTimezoneOffset()*1e3;return new Date(Date.now()-e).toISOString().slice(0,-1)}function B(e,t,n){let r;if(push(),textSize(e),textWidth(t)<=n)r=t;else for(let e=0;e<t.length;++e){const i=t.slice(0,e+1)+"...";if(textWidthM (i)>n){r=i;break}}return pop(),r}function Y(e){var t=e%10,n=e%100;return 1==t&&11!=n?e+"st":2==t&&12!=n?e+"nd":3==t&&13!=n?e+"rd":e+"th"}class G{constructor(e,t,n){this.n=t,this.m=n,this.mat=[];let r=0;for(let t=0;t<this.n;++t){this.mat.push([]);for(let n=0;n<this.m;++n)this.mat[t].push(r<e.length?e[r]:0),r+=1}return this}copy(){return new G(this.mat.flat(),this.n,this.m)}}class H{static __linear=e=>e;static __relu=e=>Math.max(e,0);static __leaky_relu=e=>e>0?e:.2*e;static __sigmoid=e=>1/(1+Math.exp(-e));static __taM nh=e=>Math.tanh(e);static __apply_unary_op(e,t){const n=e.copy();for(let e=0;e<n.n;++e)for(let r=0;r<n.m;++r)n.mat[e][r]=t(n.mat[e][r]);return n}static linear=e=>H.__apply_unary_op(e,H.__linear);static relu=e=>H.__apply_unary_op(e,H.__relu);static leaky_relu=e=>H.__apply_unary_op(e,H.__leaky_relu);static sigmoid=e=>H.__apply_unary_op(e,H.__sigmoid);static tanh=e=>H.__apply_unary_op(e,H.__tanh);static __add=(e,t)=>e+t;static __mul=(e,t)=>e*t;static __apply_binary_op=(e,t,n)=>{"object"!=typeof t&&(t=new G([t],1,1));cM onst r=e.copy();for(let e=0;e<r.n;++e)for(let i=0;i<r.m;++i)r.mat[e][i]=n(r.mat[e][i],t.mat[e%t.n][i%t.m]);return r};static mul=(e,t)=>H.__apply_binary_op(e,t,H.__mul);static add=(e,t)=>H.__apply_binary_op(e,t,H.__add);static matMul(e,t){const n=new G([],e.n,t.m);for(let r=0;r<n.n;++r)for(let i=0;i<n.m;++i)for(let o=0;o<e.m;++o)n.mat[r][i]+=e.mat[r][o]*t.mat[o][i];return n}static softmax(e){const t=H.__apply_unary_op(e,(e=>Math.exp(e))),n=t.mat.flat().reduce(((e,t)=>e+t));for(let r=0;r<e.n;++r)for(let i=0;i<e.m;++iM )t.mat[r][i]/=n;return t}}class ${constructor(e,t){this.scale=e,this.offset=t}forward(e){return H.add(H.mul(e,this.scale),this.offset)}}class X{constructor(){}forward(e){return e.map((e=>e.flat()))}}class W{constructor(e,t,n,r){this.out_dim=e,this.activation=t,this.w=n,this.b=r}forward(e){const t=H.add(H.matMul(e,this.w),this.b);return null==this.activation?t:this.activation(t)}}class U{constructor(e,t,n){this.preprocessLayers=e,this.hiddenLayers=t,this.outputLayer=n,this.totalNeurons=this.hiddenLayers.map((e=>e.ouM t_dim)),this.currentOrders=[],this.currentIteration=null}updateNeurons(e,t){if(t!=this.currentIteration){this.currentOrders=[];for(let e=0;e<this.totalNeurons.length;++e){randomSeed(100*(t+1)+e);const n=[];for(let t=0;t<this.totalNeurons[e];++t)n.push(t);L(n),this.currentOrders.push(n)}this.currentIteration=t}const n=A(this.totalNeurons),r=n.reduce(((e,t)=>e+t))*(1-e);for(let e=0;e<r;++e){const t=n.map(((e,t)=>(e-1)/this.totalNeurons[t]));n[t.map(((e,t)=>[e,t])).reduce(((e,t)=>t[0]>e[0]?t:e))[1]]-=Math.min(r-e,1)}tM his.neuronsLife=[];for(let e=0;e<n.length;++e){const t=this.currentOrders[e],r=Array(this.totalNeurons[e]).fill(0);for(let i=0;i<n[e];++i)r[t[i]]=Math.min(n[e]-i,1);this.neuronsLife.push(r)}}getTotalNeurons(){return A(this.totalNeurons)}getNeuronsLife(){return A(this.neuronsLife)}forward(e){for(const t of this.preprocessLayers)e=t.forward(e);for(const[t,n]of this.hiddenLayers.entries()){e=n.forward(e);const r=new G(this.neuronsLife[t],1,e.m);e=H.mul(e,r)}return e=this.outputLayer.forward(e),H.softmax(e)}}function qM (e){switch(e){case"relu":return H.relu;case"sigmoid":return H.sigmoid;case"tanh":return H.tanh;case"leaky_relu":return H.leaky_relu;default:return H.linear}}function j(e,t){const n=[],r=[],i=Z(t);let o=null,a=0,l=[];for(const t of e.config.layers)if("InputLayer"==t.class_name)o=t.config.batch_input_shape.slice(1),l=o;else if("Rescaling"==t.class_name)n.push(new $(t.config.scale,t.config.offset));else if("Flatten"==t.class_name)o=[o.reduce(((e,t)=>e*t))];else if("Dense"==t.class_name){const e=[t.config.units],n=o[0]M *e[0],l=e[0],s=i.subarray(a,a+n);a+=n;const h=i.subarray(a,a+l);a+=l;const c=new G(s,o[0],e[0]),u=new G(h,1,e[0]),f=q(t.config.activation);r.push(new W(e[0],f,c,u)),o=e}const s=r.pop();return{model:new U(n,r,s),inputDim:l}}function Z(e){const t=window.atob(e),n=t.length/Float32Array.BYTES_PER_ELEMENT,r=new DataView(new ArrayBuffer(Float32Array.BYTES_PER_ELEMENT)),i=new Float32Array(n);let o=0;for(let e=0;e<n;e++){o=4*e;for(let e=0;e<4;++e)r.setUint8(e,t.charCodeAt(o+e));i[e]=r.getFloat32(0,!0)}return i}class K{consM tructor(e){this.elt=e,this._events={},this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight}position(){if(0===arguments.length)return{x:this.elt.offsetLeft,y:this.elt.offsetTop};var e="absolute";return"static"!==arguments[2]&&"fixed"!==arguments[2]&&"relative"!==arguments[2]&&"sticky"!==arguments[2]&&"initial"!==arguments[2]&&"inherit"!==arguments[2]||(e=arguments[2]),this.elt.style.position=e,this.elt.style.left=arguments[0]+"px",this.elt.style.top=arguments[1]+"px",this.x=arguments[0],this.y=argumentsM [1],this}show(){return this.elt.style.display="block",this}hide(){return this.elt.style.display="none",this}size(e,t){if(0===arguments.length)return{width:this.elt.offsetWidth,height:this.elt.offsetHeight};var n=e,r=t;if(n!==te||r!==te){if(n===te?n=t*this.width/this.height:r===te&&(r=e*this.height/this.width),this.elt instanceof HTMLCanvasElement){var i,o={},a=this.elt.getContext("2d");for(i in a)o[i]=a[i];for(i in this.elt.setAttribute("width",n*this._pInst._pixelDensity),this.elt.setAttribute("height",r*this._pInM st._pixelDensity),this.elt.style.width=n+"px",this.elt.style.height=r+"px",this._pInst.scale(this._pInst._pixelDensity,this._pInst._pixelDensity),o)this.elt.getContext("2d")[i]=o[i]}else this.elt.style.width=n+"px",this.elt.style.height=r+"px",this.elt.width=n,this.elt.height=r;this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight,this._pInst&&this._pInst._curElement&&this._pInst._curElement.elt===this.elt&&(this._pInst._setProperty("width",this.elt.offsetWidth),this._pInst._setProperty("height",this.elM t.offsetHeight))}return this}style(e,t){if(t instanceof Color&&(t="rgba("+t.levels[0]+","+t.levels[1]+","+t.levels[2]+","+t.levels[3]/255+")"),void 0===t){if(-1===e.indexOf(":"))return window.getComputedStyle(this.elt).getPropertyValue(e);for(var n=e.split(";"),r=0;r<n.length;r++){var i=n[r].split(":");i[0]&&i[1]&&(this.elt.style[i[0].trim()]=i[1].trim())}}else if(this.elt.style[e]=t,"width"===e||"height"===e||"left"===e||"top"===e){var o=window.getComputedStyle(this.elt).getPropertyValue(e).replace(/[^\d.]/g,"");tM his[e]=Math.round(parseFloat(o,10))}return this}value(){return arguments.length>0?(this.elt.value=arguments[0],this):"range"===this.elt.type?parseFloat(this.elt.value):this.elt.value}mouseClicked(e){return this._adjustListener("click",e,this),this}isFocused(){return document.activeElement===this.elt}_adjustListener(e,t,n){return!1===t?this._detachListener(e,n):this._attachListener(e,t,n),this}_attachListener(e,t,n){n._events[e]&&this._detachListener(e,n);var r=t.bind(n);n.elt.addEventListener(e,r,!1),n._events[e]=rM }_detachListener(e,t){var n=t._events[e];t.elt.removeEventListener(e,n,!1),t._events[e]=null}}function J(e,t){var n=document.createElement("button");return n.innerHTML=e,t&&(n.value=t),ee(n)}function Q(e){var t=arguments.length>1&&void 0!==arguments[1]&&arguments[1],n=function(t){var n=!0,r=!1,i=void 0;try{for(var o,a=t.target.files[Symbol.iterator]();!(n=(o=a.next()).done);n=!0){var l=o.value;File._load(l,e)}}catch(e){r=!0,i=e}finally{try{n||null==a.return||a.return()}finally{if(r)throw i}}};if(window.File&&windowM .FileReader&&window.FileList&&window.Blob){var r=document.createElement("input");return r.setAttribute("type","file"),t&&r.setAttribute("multiple",!0),r.addEventListener("change",n,!1),ee(r)}}function ee(e){return document.body.appendChild(e),new K(e)}createImg=function(){var e,t=document.createElement("img"),n=arguments;return n.length>1&&"string"==typeof n[1]&&(t.alt=n[1]),n.length>2&&"string"==typeof n[2]&&(t.crossOrigin=n[2]),t.src=n[0],e=ee(t,this),t.addEventListener("load",(function(){e.width=t.offsetWidth||tM .width,e.height=t.offsetHeight||t.height;var r=n[n.length-1];"function"==typeof r&&r(e)})),e},createInput=function(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:"",t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:"text",n=document.createElement("input");return n.setAttribute("value",e),n.setAttribute("type",t),ee(n,this)};const te="auto";function ne(e){re(e);const t=e._rectMode;e.rectMode(CORNER),e.rect(0,0,e.width,e.height),e.rectMode(t),ie(e)}function re(e){e.push(),e.fill(255,255,255,255M ),e.blendMode(REMOVE)}function ie(e){e.blendMode(BLEND),e.pop()}File=function(e,t){this.file=e,this._pInst=t;var n=e.type.split("/");this.type=n[0],this.subtype=n[1],this.name=e.name,this.size=e.size,this.data=void 0},File._createLoader=function(e,t){var n=new FileReader;return n.onload=function(n){var r=new File(e);if("application/json"===r.file.type)r.data=JSON.parse(n.target.result);else if("text/xml"===r.file.type){var i=(new DOMParser).parseFromString(n.target.result,"text/xml");r.data=new XML(i.documentElemenM t)}else r.data=n.target.result;t(r)},n},File._load=function(e,t){if(/^text\//.test(e.type)||"application/json"===e.type)File._createLoader(e,t).readAsText(e);else if(/^(video|audio)\//.test(e.type)){var n=new File(e);n.data=URL.createObjectURL(e),t(n)}else File._createLoader(e,t).readAsDataURL(e)},XML=function(e){if(e)this.DOM=e;else{var t=document.implementation.createDocument(null,"doc");this.DOM=t.createElement("root")}},document.addEventListener("DOMContentLoaded",(function(){addEventListener("mousemove",(e=>{wM indow.mouseX=e.pageX,window.mouseY=e.pageY}))})),new e("global");const oe="2";let ae,le,se,he,ce,ue,fe,de,xe,ge,pe,me,be,ye,we,ve,ze,Ve,_e,Me,Ee,Se,Re,Ie,Ce,Te,Ae,De,ke,Le,Pe,Oe,Fe,Ne,Be,Ye,Ge,He,$e,Xe,We,Ue,qe,je,Ze,Ke,Je,Qe,et,tt,nt,rt,it,ot,at,lt,st,ht,ct,ut,ft,dt,xt,gt,pt,mt,bt,yt,wt,vt,zt,Vt,_t,Mt,Et,St,Rt,It,Ct,Tt,At=!1,Dt=!1,kt=!0,Lt=!1,Pt=!1;const Ot=[" ","Growing","Stable","Decaying","Dead","Rebirth"];let Ft,Nt,Bt,Yt,Gt,Ht,$t,Xt,Wt,Ut,qt,jt,Zt,Kt,Jt,Qt,en,tn,nn,rn,on,an,ln,sn,hn=0,cn=0,un=0,fn=!1,dn=!0,xn=M !0,gn=null,pn=null,mn=null,bn=!1,yn=!1,wn=null,vn=null,zn=!1;async function setup(){let e=windowWidth,t=windowHeight;createCanvas(e,t),et=createGraphics(e,t),Xe=createGraphics(e,t),$e=createGraphics(e,t),We=createGraphics(e,t),Ue=createGraphics(e,t),qe=createGraphics(e,t),Qe=createGraphics(e,t),je=createGraphics(e,t),Ze=createGraphics(e,t),Ke=createGraphics(e,t),Je=createGraphics(e,t),tt=createGraphics(500,500),nt=createGraphics(500,500),rt=createGraphics(500,500),_n(),Mn(),Sn(),await En(),Gn(),Rn(),bn=!0}function M _n(){Et=parseInt(oe),randomSeed(Et),noiseSeed(Et)}function Mn(){Wt=Ir(p.training_traits),Cr(Wt)}async function En(){let e;Jt=r(),Qt=o(),[Xt,e]=await Promise.all([s(Jt),h(Qt)]),Ut=new V(Wt.visual,e.layers_config,e.weight_b64),Ut.updateAge(new Date),_n(),Wt.training=e.training_traits,Ht=e.model_name,$t=e.classes_name}function Sn(){le=min(width,height)/1024,ut=Rr.findIndex((e=>e[0]===Wt.visual.colorPalette)),ft=[["#ffffff","#231f20","#231f20"],["#231f20","#ffffff","#ffffff"],["#104da8","#ffffff","#ffffff"],["#722F1F",M "#FCE1B2","#FCE1B2"],["#e88120","#f9f2e5","#f9f2e5"],["#f6b941","#2E2E2E","#2E2E2E"],["#45daaa","#012221","#012221"],["#F1F1F1","#328DFE","#328DFE"],["#111822","#D3EB8D","#D3EB8D"],["#713FF9","#D6D5E6","#D6D5E6"],["#FBDA9D","#795106","#795106"],["#8f5b62","#ead0d0","#ead0d0"],["#eae4cb","#508cac","#508cac"],["#ffc6cc","#cc313d","#cc313d"],["#60A900","#E0FE00","#E0FE00"],["#507DBE","#D0D1D3","#D0D1D3"],["#305848","#E8F2EE","#E8F2EE"],["#2a2634","#5b6988","#cb78a2","#5b6988"],["#590e29","#fd5e53","#fd5e53","#ffe373"]M ,["#0a141d","#57d4e4","#328195","#2A9ECF","#0ab6a8","#57d4e4"],["#3a2d28","#d5c2ac","#df6338","#3d9895","#d5c2ac"],["#030706","#77c4d9","#77c4d9","#77c4d9","#ffffff","#ffffff","#e72020","#e72020"],["#3a4664","#92f5ff","#f9ff94","#eaa0a2","#55dde0"],["#fbfaff","#f04bb1","#f04bb1","#fac373","#82cef0","#8b31ce"],["#000000","#ffffff","#ff0002","#f26522","#fdff00","#00ff03","#01fffe","#0000ff","#ff00ff"]];for(let e=0;e<ft.length;++e)for(let t=0;t<ft[e].length;++t)ft[e][t]=cr(ft[e][t]);pt=[],ct=ft[ut][0],st=ft[ut][1]}funM ction Rn(){gn=document.querySelector("#upload"),pn=document.querySelector("#inputUpload"),gn.addEventListener("dblclick",(()=>{if(!Lt&&!yn)if(In(Ie)&&cn==Ve-1)pn.click();else{if(4!=Pe&&5!=Pe&&(In(Ie)||cn!=Ve-1))return;fn=!0,dn=!0,Bt=0,un=0}})),pn.addEventListener("click",(()=>{pn.value=null,gn.style.display="block"})),pn.addEventListener("change",(()=>{const[e]=pn.files;e?(se=null,gn.style.display="none",Tn(URL.createObjectURL(e)),mn=e):gn.style.display="block"}))}function In(e){for(let t=0;t<e.length;++t){let n=0;M for(let r=0;r<e[t].length;++r)e[t][r]>0&&++n;if(0==n)return!1}return!0}function Cn(){null!=se&&(un=0,Pt=!0,he=0,ue=0,drewLineAnim=!0,ce=(ae/2+we/2)/le,loadImage(se.elt.src,(e=>{const[t,n,r]=Gt,i=createGraphics(t,n);i.image(e,0,0,t,n),i.loadPixels();const o=i.pixels.filter(((e,t)=>t%4!=3)),a=Ut.classifyImage(o);Zt=T([a,$t.map((e=>e.toUpperCase()))]).sort(((e,t)=>e[0]>t[0]?-1:1))})))}function Tn(e){se=createImg(e,""),se.hide(),Cn()}function An(){zn||(ce+=(width-ae-we)/tn/le),re(Xe),Xe.rect(ce*le,0,width,height),ie(XeM ),un>=ge&&1==kt&&(kt=!1,un-=ge),kt&&(re($e),$e.strokeWeight(2*Fe),Jn(he,ze,ct,ct,$e),ie($e)),un>=ge&&0==kt&&(kt=!0,un-=ge,he+=1,he==en&&(++ue,he=0,ce=(ae/2+we/2)/le,1==ue&&(Pt=!1,Dn(),ye=millis())))}function Dn(){At=!0,pe=!1,me=!1,tryButton=br("Try Again",width/2-225*le,height/2+265*le,290*le,40*le,kn),closeResultButton=br("Close",width/2+75*le,height/2+265*le,150*le,40*le,Ln)}function kn(){At=!1,tryButton.hide(),closeResultButton.hide(),pn.click()}function Ln(){Yt=!0,At=!1,Gn(),tryButton.hide(),closeResultButton.hM ide(),gn.style.display="block",se=null}function keyTyped(){bn&&!1===yn&&!1===yr()&&("i"!==key&&"I"!==key||(Dt=!Dt),"b"!==key&&"B"!==key||(xn=!xn),"s"!==key&&"S"!==key||!1!==Lt||saveCanvasAtCurrentTime(),"k"!==key&&"K"!==key||!1!==Lt||save4KCanvasAtCurrentTime(),"u"!==key&&"U"!==key||!1!==Lt||!1!==At||!1!==fn||!1!==Pt||On())}function On(){Lt=!0,wn=null,vn=null,submitButton=br("Submit",width/2-155*le,height/2+115*le,150*le,40*le,Fn),closeSettingButton=br("Close",width/2+5*le,height/2+115*le,150*le,40*le,Yn),vt=createM Input(),vt.position(width/2-252.5*le,height/2-40*le),vt.size(500*le,25*le),vt.style("font-size","15px"),vt.value(Jt||""),zt=createInput(),zt.position(width/2-252.2*le,height/2+35*le),zt.size(500*le,25*le),zt.style("font-size","15px"),zt.value(Qt||"")}function Fn(){Vt=vt.value(),_t=zt.value(),submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide(),Lt=!1,yn=!0,Nn()}async function Nn(){[wn,vn,_]=await Promise.all([c(Vt),u(_t),O(1e3)]),yn=!1,wn&&vn?(n(Vt),i(_t),window.location.reload()):(Lt=!0,submitButton.shM ow(),closeSettingButton.show(),vt.show(),zt.show())}function Bn(){Je.textFont("Trebuchet MS"),Je.noStroke(),pr(Je,600*le,200*le),Je.strokeWeight(1*le),Je.stroke(xt),Je.fill(xt),Je.textSize(50*le),Je.text("update()",width/2,height/2+2.5*le)}function Yn(){wn=null,vn=null,Lt=!1,submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide()}function Gn(){_n(),nn=Date.now(),pe=!1,me=!1,St=Wt.training.structure_gen,Rt=Wt.visual.birthYear,It=Wt.visual.lifeCycle,Ct=Wt.training.epoch_num,Tt=Wt.training.activation_func,FtM =Mr.findIndex((e=>e[0]==Wt.visual.hardwareAcceleration))+1,1==Ft?(Nt=30,fe=40):2==Ft?(Nt=15,fe=20):(Nt=2,fe=10);const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceilM (Mt),`Perceptron #${Et}`,$t),ae=100*le,ht=50*le,Oe=Sr.findIndex((e=>e[0]==Wt.visual.nodeShape))+1,dt=Er.findIndex((e=>e[0]==Wt.visual.nodeFill))+1,lt=_r.findIndex((e=>e[0]==Wt.visual.pattern))+1,de=Math.tanh(Math.log10(Xt.avgfeerate)),de=map(de,0,1,.2,.8),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<M Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_eM =max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,at=.7,pt=[],xM t=ft[ut][2],gt=ft[ut][ft[ut].length-1];for(let e=3;e<ft[ut].length-1;e++)pt.push(ft[ut][e]);mt=sr(xt,gt,pt,width),bt=[],wt=[],yt=width/(Ve-1);for(let e=0;e<Ve;e++)bt.push(hr(mt,yt*e/width)),wt.push(hr(mt,yt*e/width));wt.unshift(bt[0]),wt.push(bt[bt.length-1]),hn=0,cn=0,un=0,Yt=!0;const n={xLeft:ae/8,xRight:width-ae/8,yTop:ae/8,yBottom:height-ae/8},r=Ce.map((e=>e.length));jt=new R(bt,r,n,Oe,le)}function Hn(e,t){let n=Ce[e].length;return[e*we+we/2+ae/2,height/2-(n-1)/2*ve+t*ve]}function $n(e,t){le=min(e,t)/1024,ae=10M 0*le,ht=50*le,we=(e-ae)/Ve,ve=(t-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}xe=floor(De.length*de),Le=[],ke=[],ge=floor(map(de,.2,.8,15,2));for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,mt=sr(xt,gt,pt,e),bt=[],wt=[],yt=e/(Ve-1);for(let t=0;t<Ve;t++)bt.push(hr(mt,yt*tM /e)),wt.push(hr(mt,yt*t/e));wt.unshift(bt[0]),wt.push(bt[bt.length-1])}function Xn(){const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$tM ),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n)M ,n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2M ,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le}function Wn(){jt.update();const e=4==Pe?0:Kt;jt.draw(Qe,ct,dt,e,le)}function Un(){if(!bn)return ar(),void et.image(je,0,0);if(4==Pe||5==Pe)return Wn(),void et.image(Qe,0,0);un>=Nt&&hn<Ve&&(hn++,un=0);for(let e=0;e<hn;e++)1==dt?it=ot=bt[e]:(it=ct,ot=bt[e]),Kn(e,it,ot,M $e);un>=Nt&&cn<Ve-1&&(cn++,un=0);for(let e=0;e<cn;e++)Zn(e)}function qn(){et.background(ct),Ue.background(255),Ue.rectMode(CENTER),ne(Ue),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),Ue.stroke(st),Ue.strokeWeight(8*le),Ue.fill(ct),Qe.background(255),Qe.rectMode(CENTER),ne(Qe),Qe.strokeWeight(le),qe.background(255),qe.rectMode(CENTER),ne(qe),qe.textAlign(LEFT),$e.background(255),$e.rectMode(CENTER),ne($e),Xe.background(255),ne(Xe),Xe.strokeWeight(Ne),We.background(255),We.rectMode(CENTER),ne(We),We.fill(st),We.strM oke(st),We.strokeWeight(.1*le),er(lt),We.noStroke(),xn&&(We.rect(ae/16,height/2,ae/8,height),We.rect(width-ae/16,height/2,ae/8,height),We.rect(width/2,ae/16,width,ae/8),We.rect(width/2,height-ae/16,width,ae/8)),Ze.background(255),Ze.rectMode(CENTER),ne(Ze),Ze.textAlign(CENTER,CENTER),Ze.textStyle(BOLD),Ze.stroke(st),Ze.strokeWeight(8*le),Ze.fill(ct),je.background(255),je.rectMode(CENTER),ne(je),je.textAlign(CENTER,CENTER),je.textStyle(BOLD),Ke.background(255),Ke.rectMode(CENTER),ne(Ke),Ke.textAlign(CENTER,CENTER),KM e.textStyle(BOLD),Ke.stroke(st),Ke.strokeWeight(8*le),Ke.fill(ct),Je.background(255),Je.rectMode(CENTER),ne(Je),Je.textAlign(CENTER,CENTER),Je.textStyle(BOLD),Je.stroke(st),Je.strokeWeight(8*le),Je.fill(ct),Un(),et.image(We,0,0),Pt&&An(),et.image(Xe,0,0),et.image($e,0,0),At&&(tr(),et.image(Ue,0,0)),fn&&(lr(),et.image(Ze,0,0)),Lt&&(or(),et.image(Ke,0,0)),Dt&&(ir(),et.image(qe,0,0)),yn&&(Bn(),et.image(Je,0,0))}function draw(){const e=Date.now();bn&&(Ut.updateAge(new Date(e)),Xn()),qn(),image(et,0,0),zn||un++}functionM Zn(e){let t,n=Ce[e].length,r=Ce[e+1].length;for(let i=0;i<n;i++){const[n,o]=Hn(e,i);for(let a=0;a<r;a++){const[r,l]=Hn(e+1,a);t=map(min(Ce[e][i],Ce[e+1][a]),0,1,0,.5),ur(n,o,r,l,bt[e],bt[e+1],Xe,t)}}}function Kn(e,t,n,r){let i,o,a,l=Ce[e].length;for(let s=0;s<l;s++){const[l,h]=Hn(e,s);i=Ce[e][s],a=map(Be,1/30,1,3,10),o=map(Ce[e][s],0,1,2*a,0)*le,o<1.5*le&&(o=0),Qn(l,h,ze,Oe,t,n,o,i,r)}}function Jn(e,t,n,r,i){for(let o=0;o<Le[e].length;o++)Qn(Le[e][o][0],Le[e][o][1],t,Oe,n,r,0,1,i)}function Qn(e,t,n,r,i,o,a,l,s){s.M stroke(dr(o,map(l,0,1,.25,1))),s.fill(dr(i,map(l,0,1,.15,1))),s.strokeWeight(Fe),fr([a],s),3==dt&&s.fill(dr(i,0)),1==r?s.ellipse(e,t,n):2==r?s.rect(e,t,7*n/8,7*n/8):3==r&&(s.beginShape(),s.vertex(e-4*n/7,t),s.vertex(e,t-4*n/7),s.vertex(e+4*n/7,t),s.vertex(e,t+4*n/7),s.endShape(CLOSE))}function er(e){if(1==e);else if(2==e){We.strokeWeight(1*le);for(let e=ht/4;e<width+ht/4;e+=ht)for(let t=ht/4;t<height+ht/4;t+=ht)We.point(e,t)}else if(3==e){ht=25*le;for(let e=ht/2;e<height+ht/2;e+=ht)We.line(0,e,width,e);for(let e=htM /2;e<width+ht/2;e+=ht)We.line(e,0,e,height)}}function tr(){Ue.textFont("Trebuchet MS"),Ue.textAlign(LEFT,CENTER),Ue.noStroke(),pr(Ue,800*le,500*le),Ue.noStroke(),Ue.fill(dr(st,.75)),Ue.rect(width/2,height/2-100*le,800*le,300*le,25*le,25*le,0,0),Ue.fill(st),Ue.rect(width/2-250*le,height/2-100*le,225*le,225*le),Ue.image(se.elt,width/2-357.5*le,height/2-207.5*le,215*le,215*le);let e=100*Zt[0][0];Ue.fill(ct),Ue.textSize(25*le),Ue.textStyle(NORMAL),1==me&&(e>=0&&e<20?Ue.text("I have a feeling this image belongs to",widtM h/2-100*le,height/2-170*le):e>=20&&e<40?Ue.text("I have a hunch this image belongs to",width/2-100*le,height/2-170*le):e>=40&&e<60?Ue.text("I think this image belongs to",width/2-100*le,height/2-170*le):e>=60&&e<80?Ue.text("I'm almost certain this image belongs to",width/2-100*le,height/2-170*le):Ue.text("I'm positive this image belongs to",width/2-100*le,height/2-170*le));let t=e.toFixed(2);"100.00"==t&&(t="100"),1==me&&Ue.text("I'm "+t+"% confident that I'm right!",width/2-100*le,height/2-25*le),example=Zt.map((eM =>e[1])),be=Ue.textWidth('"FIDENZAAAA"'),defaultPhrase=Ue.textWidth('"PERPENDICULAR INHABITATION"'),Ue.textStyle(BOLD);const n=me?example[0]:random(example);if(1===n.split(" ").length){let e=75*be/Ue.textWidth('"'+n+'"');e>75&&(e=75),Ue.textSize(e*le),Ue.text('"'+n+'"',width/2-100*le,height/2-90*le)}else nr(width/2-100*le,height/2-90*le,460*le,110*le,n,Ue);if(millis()-ye>1500&&(me=!0),C(tt,nt,st,ct,Pe,Mt),Ue.image(nt,width/2-370*le,height/2+70*le,80*le,80*le),3==Pe){let e;e=map(Mt,50,60,.25,1.3),I(rt,e),Ue.image(rtM ,width/2-370*le,height/2+70*le,80*le,80*le)}let r,i;Ue.image(tt,width/2-370*le,height/2+70*le,80*le,80*le),Ue.fill(xt),Ue.textSize(40*le),Ue.text("INTELLIGENCE INFO",width/2-275*le,height/2+115*le),Ue.textSize(18*le),Ue.textStyle(NORMAL),Ue.circle(width/2-360*le,height/2+180*le,7.5*le),1==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s growing and getting smarter by the day.`:2==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s stable and it has reached peak performance.`:3==Pe&&(r=`Your PerceM ptron is ${Math.ceil(Mt)} years old. It s decaying and losing its luster.`),i=2==Pe?"The Perceptron remains stable for some time before entering the decay phase.":`Wait until ${new Date(an).toLocaleString("en-US")} for your Perceptron to reach its peak performance.`,Ue.text(r,width/2-350*le,height/2+180*le),Ue.circle(width/2-360*le,height/2+210*le,7.5*le),Ue.text(i,width/2-350*le,height/2+210*le),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),gr(Ue,width/2-225*le,width/2+65*le,height/2+265*le,height/2+305*le,"SELM ECT ANOTHER IMAGE"),gr(Ue,width/2+75*le,width/2+225*le,height/2+265*le,height/2+305*le,"CLOSE")}function nr(e,t,n,r,i,o){let a=i.split(" "),l=75*be/o.textWidth('"'+i+'"'),s=0,h=[],c=[],u=[],f="",d="";if(l>=50)l>75&&(l=75),o.textSize(l*le),o.text('"'+i+'"',e,t);else if(l<50){if(l=50*defaultPhrase/o.textWidth('"'+i+'"'),l>30){if(l>50&&(l=50),[f,d]=rr(l,n,s,h,c,a,f,d,Ue),0==c.length)return o.textSize(l*le),void o.text('"'+i+'"',e,t);for(s=0,h=[],c=[];o.textWidth(d)>n/le;)l=l*n/le/o.textWidth(d),f="",d="",[f,d]=rr(l,n,M s,h,c,a,f,d,Ue)}else{l=30,o.textSize(l);for(let e=0;e<a.length;e++)s+=o.textWidth(" "+a[e]),s<=n/le?h.push(a[e]):s>n/le&&s<=n/le*2?c.push(a[e]):u.push(a[e]);for(let e=1;e<h.length;e++)f=f+" "+h[e];if(f='"'+h[0]+f,0==u.length){for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+c[c.length-1]+'"'}else if(1==c.length)d="... "+u[u.length-1]+'"';else{for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+"... "+u[u.length-1]+'"'}}o.textSize(l*le);let r=1.25*(o.textDescent()+o.textAscent());o.text(f,e,t-r/2),o.text(d,e,t+r/2)}}functionM rr(e,t,n,r,i,o,a,l,s){s.textSize(e);for(let e=0;e<o.length;e++)(n+=s.textWidth(" "+o[e]))<=t/le?r.push(o[e]):i.push(o[e]);for(let e=1;e<r.length;e++)a=a+" "+r[e];if(a='"'+r[0]+a,0==i.length&&(a+='"',l=""),1==i.length)l=i[i.length-1]+'"';else{for(let e=0;e<i.length-1;e++)l=l+i[e]+" ";l=l+i[i.length-1]+'"'}return[a,l]}function ir(){const e=45*le;qe.textFont("Tahoma"),qe.stroke(st),qe.strokeWeight(2*le),qe.fill(ct),qe.rect(width/2,e/2+height-87.5*le,600*le,90*le),qe.fill(st),qe.rect(width/2-150*le,e+height-170*le,300M *le,30*le),qe.fill(ct),qe.rect(width/2+150*le,e+height-170*le,300*le,30*le),qe.noStroke(),qe.fill(ct),qe.textSize(15*le),qe.textStyle(BOLD),qe.text("PERCEPTRON INFORMATION",width/2-285*le,e+height-165*le),qe.fill(xt),qe.text("ARTWORK NAME:",width/2+10*le,e+height-165*le),qe.textAlign(RIGHT),qe.textStyle(ITALIC),qe.text("Perceptron #"+Et,width/2+285*le,e+height-165*le);const[t,n]=It.split(" ");let r;"60 Years"===It?r="1 Year":"60 Months"===It?r="1 Month":"60 Weeks"===It?r="1 Week":"60 Days"===It?r="1 Day":"12 Hours"M ===It&&(r="12 Minutes"),data=[["AI MODEL NAME:",B(12*le,Ht,140*le)],["SCALE:","1:"+Te],["NUMBER OF CLASSES:",$t.length],["BIRTH YEAR:",Rt],["NUMBER OF REBIRTHS:",sn.toString()],["AGE:",`${Math.ceil(Mt)} Perceptron Years`],["ONE PERCEPTRON YEAR:",`${r}`],["STATE:",Ot[Pe]],["ACTIVE NEURONS:",`${round(ln*rn)} / ${ln}`],["NEXT STATE TIME:",vr(new Date(on))]],qe.fill(xt);const i=data.length/2;for(let t=0;t<data.length;++t){const n=t<i,r=n?width/2-285*le:width/2+10*le,o=n?width/2-10*le:width/2+285*le,a=e+height-(135-t%i*M 15)*le;qe.textStyle(BOLD),qe.textAlign(LEFT),qe.textSize(12*le),qe.text(data[t][0],r,a),qe.textStyle(ITALIC),qe.textAlign(RIGHT),qe.textSize(12*le),qe.text(data[t][1],o,a)}}function or(){Ke.textFont("Trebuchet MS"),Ke.noStroke(),pr(Ke,600*le,200*le),gr(Ke,width/2-155*le,width/2-5*le,height/2+115*le,height/2+155*le,"UPDATE"),gr(Ke,width/2+5*le,width/2+155*le,height/2+115*le,height/2+155*le,"CLOSE"),Ke.textAlign(LEFT),Ke.fill(xt),Ke.text("UPDATE BITCOIN FULL NODE ADDRESS",width/2-252.5*le,height/2-55*le),Ke.text("UPDM ATE MODEL ADDRESS",width/2-252.5*le,height/2+20*le),Ke.textAlign(RIGHT),Ke.textStyle(ITALIC),Ke.textSize(15*le),0==wn&&Ke.text("(*) Invalid Address",width/2+252.5*le,height/2-53*le),0==vn&&Ke.text("(*) Invalid Model",width/2+252.5*le,height/2+23*le)}function ar(){je.textFont("Trebuchet MS"),je.fill(st),je.textSize(50*le),je.stroke(st),je.strokeWeight(1*le),je.text("main()",width/2,height/2)}function lr(){un>=20&&1==dn&&(dn=!1,un=0),dn&&(Ze.textFont("Trebuchet MS"),Ze.stroke(st),Ze.fill(ct),Ze.rect(width/2,height/2,M 600*le,150*le,25*le),Ze.fill(xt),Ze.textSize(75*le),Ze.noStroke(),1==Pe?Ze.text("GROWING",width/2,height/2+5*le):3==Pe?Ze.text("AGING",width/2,height/2+5*le):4==Pe?Ze.text("DEAD",width/2,height/2+5*le):5==Pe&&Ze.text("BIRTH",width/2,height/2+5*le)),un>=20&&0==dn&&(dn=!0,un=0,Bt++,3==Bt&&(fn=!1))}function sr(e,t,n,r){let i=[],o=r/(n.length+1),a=color(e),l=color(t);i.push(a);for(let e=0;e<n.length;e++){let t=color(n[e]);for(let e=1;e<=o;e++){let n=lerpColor(a,t,e/o);i.push(n)}a=t}for(let e=1;e<o;e++){let t=lerpColor(M a,l,e/o);i.push(t)}if(i.push(l),i.length>r)i.splice(r);else if(i.length<r){let e=i[i.length-1];for(;i.length<r;)i.push(e)}return i}function hr(e,t){let n=e.length,r=Math.floor(t*n);return r>=n&&(r=n-1),e[r]}function cr(e){e=e.replace("#","");var t=parseInt(e,16);return color(t>>16&255,t>>8&255,255&t)}function ur(e,t,n,r,i,o,a,l){var s=a.drawingContext.createLinearGradient(e,t,n,r);s.addColorStop(0,i),s.addColorStop(1,o),a.drawingContext.strokeStyle=s,a.drawingContext.globalAlpha=l,a.line(e,t,n,r),a.drawingContext.gM lobalAlpha=1}function fr(e,t){t.drawingContext.setLineDash(e)}function dr(e,t){let n=color(e),r=red(n),i=green(n),o=blue(n);return color(r,i,o,255*t)}function xr(e,t,n,r){return mouseX>e&&mouseX<t&&mouseY>n&&mouseY<r}function gr(e,t,n,r,i,o){e.strokeWeight(1*le),e.stroke(st);const[a,l]=xr(t,n,r,i)?[xt,ct]:[ct,xt];e.fill(a),e.push(),e.rectMode(CORNERS),e.rect(t,r,n,i,5*le),e.pop(),e.noStroke(),e.textSize(20*le),e.fill(l),e.text(o,(t+n)/2,(46*r+54*i)/100)}function pr(e,t,n){e.fill(0,0,0,75),e.rect(width/2,height/2,wiM dth,height),e.stroke(st),e.fill(ct),e.rect(width/2,height/2,t,n,25*le)}function mr(e,t){resizeCanvas(e,t,!0),Xe.resizeCanvas(e,t,!0),$e.resizeCanvas(e,t,!0),We.resizeCanvas(e,t,!0),Ue.resizeCanvas(e,t,!0),qe.resizeCanvas(e,t,!0),Qe.resizeCanvas(e,t,!0),je.resizeCanvas(e,t,!0),Ze.resizeCanvas(e,t,!0),Ke.resizeCanvas(e,t,!0),Je.resizeCanvas(e,t,!0),et.resizeCanvas(e,t,!0)}function br(e,t,n,r,i,o){const a=J(e);return a.position(t,n),a.size(r,i),a.style("opacity","0"),a.mouseClicked(o),a}function yr(){return null!=vt&&M vt?.isFocused()||null!=zt&&zt?.isFocused()}function wr(e,t,n,r){let i;if(e<=3){i=`Hey ${String.fromCodePoint(128075)}, I'm ${n}, ${t} years old. I can detect ${r.length} NFT collections: `;let e=0;for(let t=0;t<r.length;++t){const n=r[t];if(e+n.length>500){i+=", etc";break}t==r.length-1?i+=", and ":t>0&&(i+=", "),i+=n,e+=n.length}i+=". ",t<=5?i+="However, I am only a baby, so my recognition ability is not accurate. I'm in the state of Growing both looks and intelligence.":t<=13?i+="I am now a child. My recognition M ability is becoming better, but still not very accurate. I'm in the state of Growing both looks and intelligence.":t<=25?i+="I have grown up to be a teen. My recognition ability almost reaches the peak, but I will still mess up sometimes. I'm in the state of Growing both looks and intelligence.":t<=50?i+="I finally reach adulthood. My recognition is fully functional now. I'm in the Stable state, where I am the most intelligent with all neurons activated.":t<=60&&(i+="I am now an old Perceptron, so my recognition abM ility is no longer the best. I'm in the Decaying state, meaning that my neurons are dying, and my intelligence is decreasing over time.")}else 4==e?i=`${n} is Dead. However, this is not the end to its story...`:5==e&&(i=`${n} is now in the Rebirth state, and is preparing to start a new life.`);return i}function vr(e){const t=e.getDate(),n=e.toLocaleString("en-US",{month:"long"}),r=e.getFullYear();let i=e.getHours().toString();1==i.length&&(i="0"+i);let o=e.getMinutes().toString();return 1==o.length&&(o="0"+o),`${Y(M t)} ${n} ${r} | ${i}:${o}`}saveCanvasAtCurrentTime=()=>{save(N())},save4KCanvasAtCurrentTime=()=>{const e=width,t=height,n=min(4096/min(e,t),1e4/max(e,t)),r=e*n,i=t*n;mr(r,i),zn=!0,$n(r,i),qn();let o="4K_"+N()+".png";saveCanvas(et,o),mr(e,t),$n(e,t),zn=!1};const zr=[["60 Years",3,365],["60 Months",40,30],["60 Weeks",37,7],["60 Days",20,1]],Vr=[["1943",1],["1951",1.5],["1957",2],["1969",2.5],["1970",3],["1980",3.5],["1982",4],["1986",4.5],["1988",5],["1997",5.5],["1998",6],["2002",6.5],["2009",7],["2012",7.5],["2014M ",8],["2015",8.5],["2016",9],["2023",15]],_r=[["Plain",20],["Dotted",40],["Squared",40]],Mr=[["Basic",30],["Standard",60],["Advanced",10]],Er=[["MNIST",70],["CIFAR",25],["IMAGENET",5]],Sr=[["Theano",60],["Torch",30],["TensorFlow",10]],Rr=[["Whitepaper",2],["Blackboard",2],["Blueprint",2],["Nak",74/14],["Jims",74/14],["Level 10",74/14],["Flips",74/14],["Level 14",74/14],["III",74/14],["XMB",74/14],["Info",74/14],["Adventure",74/14],["Marigold",74/14],["Phoenix",74/14],["Love",74/14],["Cachet",74/14],["Human",74/14],M ["Twilight",3],["Sunset",3],["Aurora",3],["Liminal Space",3],["D Vu",3],["Lucid Dream",3],["Parallel",1],["Multiverse",1]];function Ir(e){for(let e=0;e<100;++e)random(1);return{visual:{pattern:k(_r),hardwareAcceleration:k(Mr),nodeFill:k(Er),nodeShape:k(Sr),colorPalette:k(Rr),lifeCycle:k(zr),birthYear:k(Vr)},training:e}}function Cr(e){window.$generativeTraits={"Network Architecture":e.training.structure_gen,"Hidden Layers":e.training.n_layers,"Max Neurons Per Hidden Layer":e.training.max_nodes,"Activation FunctM ion":e.training.activation_func,"Training Epochs":e.training.epoch_num,Dataset:e.visual.nodeFill,"Deep Learning Framework":e.visual.nodeShape,"Hardware Acceleration":e.visual.hardwareAcceleration,"Paper Pattern":e.visual.pattern,"Life Cycle":e.visual.lifeCycle,"Birth Year":e.visual.birthYear,"Color Palette":e.visual.colorPalette}} <script defer src="https://static.cloudflareinsights.com/beacon.min.js/v2b4487d741ca48dcbadcaf954e159fc61680799950996" integrity="sha512-D/jdE0CypeVxFadTejKGTzmwyV10c1pxZkL /AqjJuZbaJwGMyNHY3q/mTPWqMUnFACfCTunhZUVcd4cV78dK1pQ==" data-cf-beacon='{"rayId":"7b48a7957ce753ef","version":"2023.3.0","b":1,"token":"6c07c178c94442f695e7a0a2aaee641a","si":100}' crossorigin="anonymous"></script> {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "pauldrons"}]} text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "bag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "badger"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "tiger"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "honey pot"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "arrow wounds"}]} xr:d:DAFffdozyTk:5,j:2347504877,t:23040805 http://ns.adobe.com/xap/1.0/ <x:xmpmeta xmlns:x='adobe:ns:meta/'> <rdf:RDF xmlns:rdf='http://www.w3.org/1999/02/22-rdf-syntax-ns#'> <rdf:Description rdf:about='' xmlns:dc='http://purl.org/dc/elements/1.1/'> <rdf:li xml:lang='x-default'>Untitled design - 1</rdf:li> </rdf:Description> <rdf:Description rdf:about='' xmlns:Attrib='http://ns.attribution.com/ads/1.0/'> <Attrib:Ads> <rdf:li rdf:parseType='Resource'> <Attrib:Created>2023-04-08</Attrib:Created> <Attrib:ExtId>1ed1d569-4826-436e-89f0-93ca78f69ec9</Attrib:ExtId> <Attrib:FbId>525265914179580</Attrib:FbId> <Attrib:TouchType>2</Attrib:TouchType> </Attrib:Ads> </rdf:Description> <rdf:Description rdf:about='' xmlns:pdf='http://ns.adobe.com/pdf/1.3/'> <pdf:Author>Mitchell Westhead</pdf:Author> </rdf:Description> <rdf:Description rdf:about='' xmlns:xmp='http://ns.adobe.com/xap/1.0/'> <xmp:CreatorTool>Canva</xmp:CreatorTool> </rdf:Description> </x:xmpmeta> (((((((((((((((((((((((((((((((((((((((((((((((((( %&'()*456789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz &'()*56789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "tiger"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "blue fire"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "badger"}, {"trait_type": "Artifacts", "value": "none"}]} xxxxxxxxxxxxxxxxxxxxxxx text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! FjDOUT:66CA4483A18F9BD7A7EA28A61BEBD943CDAFC7604B287BB101C11AB0C2F6CA2F Bj@=:ETH.ETH:0xe54119f9CbD77e97802Aa1470b35cDB2a1D04b17:11135161::0 text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! FjDOUT:5B8D423B3FB93D889EFF4AC1170A92BBDC195F81F0E3214612C6A826C7420C9C text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":" text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 @{"p":"brc-20","op":"deploy","tick":" ","max":"500","lim":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":" text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 "p":"sns","op":"reg","name":"era.unisat" text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/html;charset=utf-8 <meta charset="utf-8" /> position: relative; width: var(--width); height: var(--height); border: 1px solid blue; position: relative; <div id="upload"> <input id="inputUpload" type="file"> function e(e){"use strict";return new function e(t){let n="global"==t?window:this;n.canvas=document.createElement("canvas");let r=n.canvas.getContext("2d");n.width=100,n.height=100,n.canvas.width=n.width,n.canvas.height=n.height,"offscreen"!=t&&(document.body?document.body.appendChild(n.canvas):window.addEventListener("load",(function(){document.body.appendChild(n.canvas)}))),g(),n.MAGIC=161533525,n.RGB=0,n.HSV=1,n.HM SB=1,n.CHORD=0,n.PIE=1,n.OPEN=2,n.RADIUS=1,n.CORNER=2,n.CORNERS=3,n.ROUND="round",n.SQUARE="butt",n.PROJECT="square",n.MITER="miter",n.BEVEL="bevel",n.CLOSE=1,n.BLEND="source-over",n.REMOVE="destination-out",n.ADD="lighter",n.DARKEST="darken",n.LIGHTEST="lighten",n.DIFFERENCE="difference",n.SUBTRACT="subtract",n.EXCLUSION="exclusion",n.MULTIPLY="multiply",n.SCREEN="screen",n.REPLACE="copy",n.OVERLAY="overlay",n.HARD_LIGHT="hard-light",n.SOFT_LIGHT="soft-light",n.DODGE="color-dodge",n.BURN="color-burn",n.NORMAL="norM mal",n.ITALIC="italic",n.BOLD="bold",n.BOLDITALIC="italic bold",n.CENTER="center",n.LEFT="left",n.RIGHT="right",n.TOP="top",n.BOTTOM="bottom",n.BASELINE="alphabetic",n.LANDSCAPE="landscape",n.PORTRAIT="portrait",n.ALT=18,n.BACKSPACE=8,n.CONTROL=17,n.DELETE=46,n.DOWN_ARROW=40,n.ENTER=13,n.ESCAPE=27,n.LEFT_ARROW=37,n.OPTION=18,n.RETURN=13,n.RIGHT_ARROW=39,n.SHIFT=16,n.TAB=9,n.UP_ARROW=38,n.HALF_PI=Math.PI/2,n.PI=Math.PI,n.QUARTER_PI=Math.PI/4,n.TAU=2*Math.PI,n.TWO_PI=2*Math.PI,n.THRESHOLD=1,n.GRAY=2,n.OPAQUE=3,n.INVEM RT=4,n.POSTERIZE=5,n.DILATE=6,n.ERODE=7,n.BLUR=8,n.ARROW="default",n.CROSS="crosshair",n.HAND="pointer",n.MOVE="move",n.TEXT="text",n.VIDEO={video:!0,audio:!1},n.AUDIO={video:!1,audio:!0},n.SHR3=1,n.LCG=2,n.HARDWARE_FILTERS=!0,n.hint=function(e,t){n[e]=t},n.frameCount=0,n.mouseX=0,n.mouseY=0,n.pmouseX=0,n.pmouseY=0,n.mouseButton=null,n.keyIsPressed=!1,n.mouseIsPressed=!1,n.key=null,n.keyCode=null,n.pixels=null,n.accelerationX=0,n.accelerationY=0,n.accelerationZ=0,n.rotationX=0,n.rotationY=0,n.rotationZ=0,n.relRotatM ionX=0,n.relRotationY=0,n.relRotationZ=0,n.pAccelerationX=0,n.pAccelerationY=0,n.pAccelerationZ=0,n.pRotationX=0,n.pRotationY=0,n.pRotationZ=0,n.pRelRotationX=0,n.pRelRotationY=0,n.pRelRotationZ=0,n.touches=[],n._styleCache=[{colorMode:n.RGB,noStroke:!1,noFill:!1,ellipseMode:n.CENTER,rectMode:n.CORNER,curveDetail:20,curveAlpha:0,textFont:"sans-serif",textSize:12,textLeading:12,textStyle:"normal"}],n._style=n._styleCache[n._styleCache.length-1],n._noLoop=!1,n._pixelDensity=1,n._frameRate=null,n._tint=null;let i=nullM ,o=!0,a=[],l=null,s=0,h={},c=0,u=null,f=null,d=null;Object.defineProperty(n,"deviceOrientation",{get:function(){return 90==Math.abs(window.orientation)?n.LANDSCAPE:n.PORTRAIT}}),Object.defineProperty(n,"windowWidth",{get:function(){return window.innerWidth}}),Object.defineProperty(n,"windowHeight",{get:function(){return window.innerHeight}}),Object.defineProperty(n,"drawingContext",{get:function(){return r}}),n.createCanvas=function(e,t){return n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t,g(),n.canvas},nM .resizeCanvas=function(e,t){n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t},n.createGraphics=n.createImage=function(t,n){let r=new e("offscreen");return r.createCanvas(t,n),r.noLoop(),r},n.pixelDensity=function(e){return null==e||(n._pixelDensity=e,n.canvas.width=Math.ceil(n.width*e),n.canvas.height=Math.ceil(n.height*e),n.canvas.style.width=n.width+"px",n.canvas.style.height=n.height+"px",r.scale(n._pixelDensity,n._pixelDensity),g()),n._pixelDensity},n.map=function(e,t,n,r,i,o){let a=r+1*(e-t)/(n-t)*(i-r)M ;return o?r<i?Math.min(Math.max(a,r),i):Math.min(Math.max(a,i),r):a},n.lerp=function(e,t,n){return e*(1-n)+t*n},n.constrain=function(e,t,n){return Math.min(Math.max(e,t),n)},n.dist=function(){return 4==arguments.length?Math.hypot(arguments[0]-arguments[2],arguments[1]-arguments[3]):Math.hypot(arguments[0]-arguments[3],arguments[1]-arguments[4],arguments[2]-arguments[5])},n.norm=function(e,t,r){return n.map(e,t,r,0,1)},n.sq=function(e){return e*e},n.fract=function(e){return e-Math.floor(e)},n.degrees=function(e){retM urn 180*e/Math.PI},n.radians=function(e){return e*Math.PI/180},n.abs=Math.abs,n.ceil=Math.ceil,n.exp=Math.exp,n.floor=Math.floor,n.log=Math.log,n.mag=Math.hypot,n.max=Math.max,n.min=Math.min,n.round=Math.round,n.sqrt=Math.sqrt,n.sin=Math.sin,n.cos=Math.cos,n.tan=Math.tan,n.asin=Math.asin,n.acos=Math.acos,n.atan=Math.atan,n.atan2=Math.atan2,n.Vector=function(e,t,r){let i=this;i.x=e||0,i.y=t||0,i.z=r||0;let o=null,a=null;function l(e,t,n){return null!=e.x?e:null!=t?{x:e,y:t,z:n||0}:{x:e,y:e,z:e}}function s(){null==a&M &(a=i.x*i.x+i.y*i.y+i.z*i.z,o=Math.sqrt(a))}function h(){a=null,o=null}i.set=function(e,t,n){i.x=e||0,i.y=t||0,i.z=n||0},i.copy=function(){return new n.Vector(i.x,i.y,i.z)},i.add=function(){let e=l.apply(null,arguments);return i.x+=e.x,i.y+=e.y,i.z+=e.z,h(),i},i.rem=function(){let e=l.apply(null,arguments);return i.x%=e.x,i.y%=e.y,i.z%=e.z,h(),i},i.sub=function(){let e=l.apply(null,arguments);return i.x-=e.x,i.y-=e.y,i.z-=e.z,h(),i},i.mult=function(){let e=l.apply(null,arguments);return i.x*=e.x,i.y*=e.y,i.z*=e.z,hM (),i},i.div=function(){let e=l.apply(null,arguments);return i.x/=e.x,i.y/=e.y,i.z/=e.z,h(),i},i.mag=function(){return s(),o},i.magSq=function(){return s(),a},i.dot=function(){let e=l.apply(null,arguments);return i.x*e.x+i.y*e.y+i.z*e.z},i.dist=function(){let e=l.apply(null,arguments),t=i.x-e.x,n=i.y-e.y,r=i.z-e.z;return Math.sqrt(t*t+n*n+r*r)},i.cross=function(){let e=l.apply(null,arguments),t=i.y*e.z-i.z*e.y,n=i.z*e.x-i.x*e.z,r=i.x*e.y-i.y*e.x;return i.x=t,i.y=n,i.z=r,h(),i},i.normalize=function(){s();let e=o;retuM rn i.x/=e,i.y/=e,i.z/=e,o=1,a=1,i},i.limit=function(e){s();if(o>e){let t=e/o;i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e}return i},i.setMag=function(e){s();let t=e/o;return i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e,i},i.heading=function(){return Math.atan2(i.y,i.x)},i.rotate=function(e){let t=Math.cos(e),n=Math.sin(e),r=i.x*t-i.y*n,o=i.x*n+i.y*t;return i.x=r,i.y=o,i},i.angleBetween=function(){let e=l.apply(null,arguments);const t=i.dot(e)/(i.mag()*e.mag());let n;return n=Math.acos(Math.min(1,Math.max(-1,t))),n*Math.sign(i.cross(e).z||1)},M i.lerp=function(e,t){return i.x=i.x*(1-t)+e.x*t,i.y=i.y*(1-t)+e.y*t,i.z=i.z*(1-t)+e.z*t,h(),i},i.reflect=function(e){return e.normalize(),i.sub(e.mult(2*i.dot(e)))},i.array=function(){return[i.x,i.y,i.z]},i.equals=function(e,t){return null==t&&null==(t=Number.EPSILON)&&(t=0),Math.abs(e.x-i.x)<t&&Math.abs(e.y-i.y)<t&&Math.abs(e.z-i.z)<t},i.fromAngle=function(e,t){return null==t&&(t=1),o=t,a=t*t,i.x=t*Math.cos(e),i.y=t*Math.sin(e),i.z=0,i},i.fromAngles=function(e,t,n){null==n&&(n=1),o=n,a=n*n;const r=Math.cos(t),l=MaM th.sin(t),s=Math.cos(e),h=Math.sin(e);return i.x=n*h*l,i.y=-n*s,i.z=n*h*r,i},i.random2D=function(){return o=1,a=1,i.fromAngle(Math.random()*Math.PI*2)},i.random3D=function(){return o=1,a=1,i.fromAngles(Math.random()*Math.PI*2,Math.random()*Math.PI*2)},i.toString=function(){return`[${i.x}, ${i.y}, ${i.z}]`}},n.Vector.add=function(e,t){return new n.Vector(e.x+t.x,e.y+t.y,e.z+t.z)},n.Vector.rem=function(e,t){return new n.Vector(e.x%t.x,e.y%t.y,e.z%t.z)},n.Vector.sub=function(e,t){return new n.Vector(e.x-t.x,e.y-t.y,e.M z-t.z)},n.Vector.mult=function(e,t){return null==t.x?new n.Vector(e.x*t,e.y*t,e.z*t):new n.Vector(e.x*t.x,e.y*t.y,e.z*t.z)},n.Vector.div=function(e,t){return null==t.x?new n.Vector(e.x/t,e.y/t,e.z/t):new n.Vector(e.x/t.x,e.y/t.y,e.z/t.z)},n.Vector.dist=function(e,t){return Math.hypot(e.x-t.x,e.y-t.y,e.z-t.z)},n.Vector.cross=function(e,t){return new n.Vector(e.y*t.z-e.z*t.y,e.z*t.x-e.x*t.z,e.x*t.y-e.y*t.x)},n.Vector.lerp=function(e,t,r){return new n.Vector(e.x*(1-r)+t.x*r,e.y=e.y*(1-r)+t.y*r,e.z=e.z*(1-r)+t.z*r)},n.M Vector.equals=function(e,t,n){return e.equals(t,n)};for(let e of["fromAngle","fromAngles","random2D","random3D"])n.Vector[e]=function(t,r,i){return(new n.Vector)[e](t,r,i)};function x(e,t,n){let r,i,o,a,l,s,h,c,u;if(0==t)return[255*(r=n),255*(i=n),255*(o=n)];switch((a=e)>360&&(a=0),h=n*(1-t),c=n*(1-t*(s=(a/=60)-(l=~~a))),u=n*(1-t*(1-s)),l){case 0:r=n,i=u,o=h;break;case 1:r=c,i=n,o=h;break;case 2:r=h,i=n,o=u;break;case 3:r=h,i=c,o=n;break;case 4:r=u,i=h,o=n;break;default:r=n,i=h,o=c}return[255*r,255*i,255*o]}functioM n g(){r.fillStyle="white",r.strokeStyle="black",r.lineCap="round",r.lineJoin="miter"}function p(e){if(0<=e&&e<2*Math.PI)return e;for(;e<0;)e+=2*Math.PI;for(;e>=Math.PI;)e-=2*Math.PI;return e}function m(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;let c=p(a),u=p(l);r.beginPath();for(let a=0;a<h+1;a++){let l=a/h,s=n.lerp(c,u,l),f=Math.cos(s)*i/2,d=Math.sin(s)*o/2;r[a?"lineTo":"moveTo"](e+f,t+d)}s==n.CHORD?r.closePath():s==n.PIE&&(r.lineTo(e,t),r.closePath()),n._style.noFill||r.fill(),n._style.noStrokM e||r.stroke()}function b(e,t,i,o){n._style.noFill&&n._style.noStroke||(r.beginPath(),r.ellipse(e,t,i/2,o/2,0,0,2*Math.PI),n._style.noFill||r.fill(),n._style.noStroke||r.stroke())}function y(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;if(null==a)return function(e,t,i,o){n._style.noFill||r.fillRect(e,t,i,o),n._style.noStroke||r.strokeRect(e,t,i,o)}(e,t,i,o);if(null==l)return y(e,t,i,o,a,a,a,a);const c=Math.min(Math.abs(o),Math.abs(i))/2;a=Math.min(c,a),l=Math.min(c,l),h=Math.min(c,h),s=Math.min(c,s)M ,r.beginPath(),r.moveTo(e+a,t),r.arcTo(e+i,t,e+i,t+o,l),r.arcTo(e+i,t+o,e,t+o,s),r.arcTo(e,t+o,e,t,h),r.arcTo(e,t,e+i,t,a),r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke()}function w(){a=[]}n.createVector=function(e,t,r){return new n.Vector(e,t,r)},n.curvePoint=function(e,t,n,r,i){const o=i*i*i,a=i*i;return e*(-.5*o+a-.5*i)+t*(1.5*o-2.5*a+1)+n*(-1.5*o+2*a+.5*i)+r*(.5*o-.5*a)},n.bezierPoint=function(e,t,n,r,i){const o=1-i;return Math.pow(o,3)*e+3*Math.pow(o,2)*i*t+3*o*Math.pow(i,2)*n+Math.pow(i,M 3)*r},n.curveTangent=function(e,t,n,r,i){const o=i*i;return e*(-3*o/2+2*i-.5)+t*(9*o/2-5*i)+n*(-9*o/2+4*i+.5)+r*(3*o/2-i)},n.bezierTangent=function(e,t,n,r,i){const o=1-i;return 3*r*Math.pow(i,2)-3*n*Math.pow(i,2)+6*n*o*i-6*t*o*i+3*t*Math.pow(o,2)-3*e*Math.pow(o,2)},n.Color=function(e,t,n,r){let i=this;i.MAGIC=786698,i._r=e,i._g=t,i._b=n,i._a=r,i._h=0,i._s=0,i._v=0,i._hsvInferred=!1,i.setRed=function(e){i._r=e,i._hsvInferred=!1},i.setGreen=function(e){i._g=e,i._hsvInferred=!1},i.setBlue=function(e){i._b=e,i._hsvInfM erred=!1},i.setAlpha=function(e){i._a=e/255,i._hsvInferred=!1},i._inferHSV=function(){i._hsvInferred||([i._h,i._s,i._v]=function(e,t,n){let r,i,o,a,l;return r=e<t?e<n?e:n:t<n?t:n,0==(l=100*(i=e>t?e>n?e:n:t>n?t:n)/255)?[o=0,a=0,l]:0==(a=100*(i-r)/i)?[o=0,a,l]:(o=i==e?0+60*(t-n)/(i-r):i==t?120+60*(n-e)/(i-r):240+60*(e-t)/(i-r),[o,a,l])}(i._r,i._g,i._b),i._hsvInferred=!0)},i.toString=function(){return`rgba(${Math.round(i._r)},${Math.round(i._g)},${Math.round(i._b)},${~~(1e3*i._a)/1e3})`}},n.colorMode=function(e){n._stM yle.colorMode=e},n.color=function(){if(1==arguments.length&&786698==arguments[0].MAGIC)return arguments[0];if(n._style.colorMode==n.RGB){if(1==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],1);if(2==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],arguments[1]/255);if(3==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],1);if(4==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],arguments[3]/255)}else{if(1==argumeM nts.length)return new n.Color(...x(0,0,arguments[0]/100),1);if(2==arguments.length)return new n.Color(...x(0,0,arguments[0]/100),arguments[1]/255);if(3==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),1);if(4==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),arguments[3])}return null},n.red=function(e){return e._r},n.green=function(e){return e._g},n.blue=function(e){return e._b},n.alpha=function(e){return 255*e._a},n.hue=function(e){reM turn e._inferHSV(),e._h},n.saturation=function(e){return e._inferHSV(),e._s},n.brightness=function(e){return e._inferHSV(),e._v},n.lightness=function(e){return 100*(.2126*e._r+.7152*e._g+.0722*e._b)/255},n.lerpColor=function(e,t,r){return n._style.colorMode==n.RGB?new n.Color(n.constrain(n.lerp(e._r,t._r,r),0,255),n.constrain(n.lerp(e._g,t._g,r),0,255),n.constrain(n.lerp(e._b,t._b,r),0,255),n.constrain(n.lerp(e._a,t._a,r),0,1)):(e._inferHSV(),t._inferHSV(),new n.Color(n.constrain(function(e,t,r){var i=[[Math.abs(t-M e),n.map(r,0,1,e,t)],[Math.abs(t+360-e),n.map(r,0,1,e,t+360)],[Math.abs(t-360-e),n.map(r,0,1,e,t-360)]];return i.sort(((e,t)=>e[0]-t[0])),(i[0][1]+720)%360}(e._h,t._h,r),0,360),n.constrain(n.lerp(e._s,t._s,r),0,100),n.constrain(n.lerp(e._v,t._v,r),0,100),n.constrain(n.lerp(e._a,t._a,r),0,1)))},n.strokeWeight=function(e){n._style_noStroke=!1,r.lineWidth=e},n.stroke=function(){if(n._style.noStroke=!1,"string"==typeof arguments[0])return void(r.strokeStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._sM tyle.noStroke=!0:r.strokeStyle=e},n.noStroke=function(){n._style.noStroke=!0},n.fill=function(){if(n._style.noFill=!1,"string"==typeof arguments[0])return void(r.fillStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._style.noFill=!0:r.fillStyle=e},n.noFill=function(){n._style.noFill=!0},n.blendMode=function(e){r.globalCompositeOperation=e},n.strokeCap=function(e){r.lineCap=e},n.strokeJoin=function(e){r.lineJoin=e},n.ellipseMode=function(e){n._style.ellipseMode=e},n.rectMode=function(e){n._style.rectM Mode=e},n.curveDetail=function(e){n._style.curveDetail=e},n.curveAlpha=function(e){n._style.curveAlpha=e},n.curveTightness=function(e){n._style.curveAlpha=e},n.clear=function(){r.clearRect(0,0,n.width,n.height)},n.background=function(){if(arguments[0]&&arguments[0].MAGIC==n.MAGIC)return n.image(arguments[0],0,0,n.width,n.height);r.save(),r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity),r.fillStyle="string"==typeof arguments[0]?arguments[0]:n.color(...Array.from(arguments)),r.fillRect(0,0,n.width,n.heightM ),r.restore()},n.line=function(e,t,i,o){n._style.noStroke||(r.beginPath(),r.moveTo(e,t),r.lineTo(i,o),r.stroke())},n.arc=function(e,t,r,i,o,a,l,s){if(o==a)return n.ellipse(e,t,r,i);null==s&&(s=25),null==l&&(l=n.PIE),n._style.ellipseMode==n.CENTER?m(e,t,r,i,o,a,l,s):n._style.ellipseMode==n.RADIUS?m(e,t,2*r,2*i,o,a,l,s):n._style.ellipseMode==n.CORNER?m(e+r/2,t+i/2,r,i,o,a,l,s):n._style.ellipseMode==n.CORNERS&&m((e+r)/2,(t+i)/2,r-e,i-t,o,a,l,s)},n.ellipse=function(e,t,r,i){null==i&&(i=r),n._style.ellipseMode==n.CENTERM ?b(e,t,r,i):n._style.ellipseMode==n.RADIUS?b(e,t,2*r,2*i):n._style.ellipseMode==n.CORNER?b(e+r/2,t+i/2,r,i):n._style.ellipseMode==n.CORNERS&&b((e+r)/2,(t+i)/2,r-e,i-t)},n.circle=function(e,t,r){return n.ellipse(e,t,r,r)},n.point=function(e,t){e.x&&(t=e.y,e=e.x),r.beginPath(),r.ellipse(e,t,.4,.4,0,0,2*Math.PI),r.stroke()},n.rect=function(e,t,r,i,o,a,l,s){n._style.rectMode==n.CENTER?y(e-r/2,t-i/2,r,i,o,a,l,s):n._style.rectMode==n.RADIUS?y(e-r,t-i,2*r,2*i,o,a,l,s):n._style.rectMode==n.CORNER?y(e,t,r,i,o,a,l,s):n._stylM e.rectMode==n.CORNERS&&y(e,t,r-e,i-t,o,a,l,s)},n.square=function(e,t,r,i,o,a,l){return n.rect(e,t,r,r,i,o,a,l)},n.beginShape=function(){w(),r.beginPath(),o=!0},n.beginContour=function(){r.closePath(),w(),o=!0},n.endContour=function(){w(),o=!0},n.vertex=function(e,t){w(),o?r.moveTo(e,t):r.lineTo(e,t),o=!1},n.bezierVertex=function(e,t,n,i,o,a){w(),r.bezierCurveTo(e,t,n,i,o,a)},n.quadraticVertex=function(e,t,n,i){w(),r.quadraticCurveTo(e,t,n,i)},n.bezier=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.bezierVM ertex(r,i,o,a,l,s),n.endShape()},n.triangle=function(e,t,r,i,o,a){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.endShape(n.CLOSE)},n.quad=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.vertex(l,s),n.endShape(n.CLOSE)},n.endShape=function(e){w(),e&&r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke(),n._style.noFill&&n._style.noStroke&&(r.save(),r.fillStyle="none",r.fill(),r.restore())},n.curveVertex=function(e,t){if(a.push([e,t]),a.length<4)return;M let i=function(e,t,n,r,i,o,a,l,s,h){function c(e,t,n,r,i,o){let a=Math.pow(r-t,2)+Math.pow(i-n,2);return Math.pow(a,.5*o)+e}let u=[],f=c(0,e,t,n,r,h),d=c(f,n,r,i,o,h),x=c(d,i,o,a,l,h);for(let h=0;h<s;h++){let c=f+h/(s-1)*(d-f),g=[(f-c)/(f-0),(c-0)/(f-0),(d-c)/(d-f),(c-f)/(d-f),(x-c)/(x-d),(c-d)/(x-d),(d-c)/(d-0),(c-0)/(d-0),(x-c)/(x-f),(c-f)/(x-f)];for(let e=0;e<g.length;e+=2)isNaN(g[e])&&(g[e]=1,g[e+1]=0),isFinite(g[e])||(g[e]>0?(g[e]=1,g[e+1]=0):(g[e]=0,g[e+1]=1));let p=e*g[0]+n*g[1],m=t*g[0]+r*g[1],b=n*g[2]+i*g[M 3],y=r*g[2]+o*g[3],w=i*g[4]+a*g[5],v=o*g[4]+l*g[5],z=p*g[6]+b*g[7],V=m*g[6]+y*g[7],_=b*g[8]+w*g[9],M=y*g[8]+v*g[9],E=z*g[2]+_*g[3],S=V*g[2]+M*g[3];u.push([E,S])}return u}(...a[a.length-4],...a[a.length-3],...a[a.length-2],...a[a.length-1],n._style.curveDetail,n._style.curveAlpha);for(let e=0;e<i.length;e++)o?r.moveTo(...i[e]):r.lineTo(...i[e]),o=!1},n.curve=function(e,t,r,i,o,a,l,s){n.beginShape(),n.curveVertex(e,t),n.curveVertex(r,i),n.curveVertex(o,a),n.curveVertex(l,s),n.endShape()},n.translate=function(e,t){r.tM ranslate(e,t)},n.rotate=function(e){r.rotate(e)},n.scale=function(e,t){null==t&&(t=e),r.scale(e,t)},n.applyMatrix=function(e,t,n,i,o,a){r.transform(e,t,n,i,o,a)},n.shearX=function(e){r.transform(1,0,Math.tan(e),1,0,0)},n.shearY=function(e){r.transform(1,Math.tan(e),0,1,0,0)},n.resetMatrix=function(){r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity)},n.pushMatrix=n.push=function(){n._styleCache.push({...n._style}),n._style=n._styleCache[n._styleCache.length-1],r.save()},n.popMatrix=n.pop=function(){n._stylM eCache.length-1&&(n._styleCache.pop(),n._style=n._styleCache[n._styleCache.length-1],r.restore())},n.image=function(e,t,i,o,a,l,s,h,c){let u=e.MAGIC==n.MAGIC?e.canvas:e;function d(){if(e.MAGIC!=n.MAGIC||!n._tint)return;let t=e.canvas.getContext("2d");t.save(),t.resetTransform(),t.clearRect(0,0,t.canvas.width,t.canvas.height),t.drawImage(f.canvas,0,0),t.restore()}return e.MAGIC==n.MAGIC&&null!=n._tint&&(function(e,t){null==f&&(f=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvasM .height),f.canvas.width==e&&f.canvas.height==t||(f.canvas.width=e,f.canvas.height=t)}(e.canvas.width,e.canvas.height),f.drawImage(e.canvas,0,0),e.tinted(n._tint)),o?l?(h||(h=u.width),c||(c=u.height),r.drawImage(u,l,s,h,c,t,i,o,a),void d()):(r.drawImage(u,t,i,o,a),void d()):(e.MAGIC==n.MAGIC||e.width?r.drawImage(u,t,i,e.width,e.height):r.drawImage(u,t,i,e.videoWidth,e.videoHeight),void d())},n.loadPixels=function(){l=r.getImageData(0,0,n.canvas.width,n.canvas.height),n.pixels=l.data},n.updatePixels=function(){null!=M l&&r.putImageData(l,0,0)},n.loadImage=function(e,t){s++;let r=n.createGraphics(100,100),i=r.canvas.getContext("2d"),o=new Image;return o.src=e,o.crossOrigin="Anonymous",o.onload=function(){i.canvas.width=o.width,i.canvas.height=o.height,r.width=o.width,r.height=o.height,i.drawImage(o,0,0),s--,t&&t(r)},r};let v={};function z(e,t){null==u&&(u=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvas.height),u.canvas.width==e&&u.canvas.height==t||(u.canvas.width=e,u.canvas.height=t)}funcM tion V(){let e=r.canvas.width*r.canvas.height*4;null!=d&&e==d.length||(d=new Uint8ClampedArray(e))}function _(e){u.clearRect(0,0,u.canvas.width,u.canvas.height),u.filter=e,u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()}v[n.THRESHOLD]=function(e,t){null==t?t=127.5:t*=255;for(let n=0;n<e.length;n+=4){const r=.2126*e[n]+.7152*e[n+1]+.0722*e[n+2];e[n]=e[n+1]=e[n+2]=r>=t?255:0}},v[n.GRAY]=function(e){for(let t=0;t<e.length;t+=4)M {const n=.2126*e[t]+.7152*e[t+1]+.0722*e[t+2];e[t]=e[t+1]=e[t+2]=n}},v[n.OPAQUE]=function(e){for(let t=0;t<e.length;t+=4)e[t+3]=255},v[n.INVERT]=function(e){for(let t=0;t<e.length;t+=4)e[t]=255-e[t],e[t+1]=255-e[t+1],e[t+2]=255-e[t+2]},v[n.POSTERIZE]=function(e,t){let n=t-1;for(let r=0;r<e.length;r+=4)e[r]=255*(e[r]*t>>8)/n,e[r+1]=255*(e[r+1]*t>>8)/n,e[r+2]=255*(e[r+2]*t>>8)/n},v[n.DILATE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-M 1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.max(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.ERODE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.min(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.BLURM ]=function(e,t){t=t||1,t=Math.floor(t*n._pixelDensity),V(),d.set(e);let i=2*t+1,o=function(e){let n=new Float32Array(e),r=.3*t+.8,i=r*r*2;for(let t=0;t<e;t++){let o=t-e/2,a=Math.exp(-o*o/i)/(2.5066282746*r);n[t]=a}return n}(i),[a,l]=[r.canvas.width,r.canvas.height];for(let n=0;n<l;n++)for(let r=0;r<a;r++){let l=0,s=0,h=0,c=0;for(let e=0;e<i;e++){let i=4*(n*a+Math.min(Math.max(r-t+e,0),a-1));l+=d[i]*o[e],s+=d[i+1]*o[e],h+=d[i+2]*o[e],c+=d[i+3]*o[e]}let u=4*(n*a+r);e[u]=l,e[u+1]=s,e[u+2]=h,e[u+3]=c}d.set(e);for(let nM =0;n<l;n++)for(let r=0;r<a;r++){let s=0,h=0,c=0,u=0;for(let e=0;e<i;e++){let i=4*(Math.min(Math.max(n-t+e,0),l-1)*a+r);s+=d[i]*o[e],h+=d[i+1]*o[e],c+=d[i+2]*o[e],u+=d[i+3]*o[e]}let f=4*(n*a+r);e[f]=s,e[f+1]=h,e[f+2]=c,e[f+3]=u}},n.filter=function(e,t){if(n.HARDWARE_FILTERS&&null!=r.filter)if(z(),e==n.THRESHOLD){null==t&&(t=.5),t=Math.max(t,1e-5),_(`saturate(0%) brightness(${Math.floor(.5/t*100)}%) contrast(1000000%)`)}else if(e==n.GRAY)_("saturate(0%)");else if(e==n.OPAQUE)u.fillStyle="black",u.fillRect(0,0,u.canvaM s.width,u.canvas.height),u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.drawImage(u.canvas,0,0),r.restore();else if(e==n.INVERT)_("invert(100%)");else if(e==n.BLUR)_(`blur(${Math.ceil(t*n._pixelDensity/1)||1}px)`);else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}},n.resize=function(e,t){z(),u.drawImage(r.canvas,0,0),n.width=e,n.height=t,r.canvas.width=e*n._pixM elDensity,r.canvas.height=t*n._pixelDensity,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0,r.canvas.width,r.canvas.height),r.restore()},n.get=function(e,t,i,o){if(null!=e&&null==i){let i=r.getImageData(e,t,1,1).data;return new n.Color(i[0],i[1],i[2],i[3]/255)}e=e||0,t=t||0,i=i||n.width,o=o||n.height;let a=n.createGraphics(i,o);a.pixelDensity(n._pixelDensity);let l=r.getImageData(e*n._pixelDensity,t*n._pixelDensity,i*n._pixelDensity,o*n._pixelDensity);return a.caM nvas.getContext("2d").putImageData(l,0,0),a},n.set=function(e,t,i){if(i.MAGIC==n.MAGIC){let r=n._tint;return n._tint=null,n.image(i,e,t),void(n._tint=r)}let o=4*(t*n._pixelDensity*r.canvas.width+e*n._pixelDensity);n.pixels[o]=i._r,n.pixels[o+1]=i._g,n.pixels[o+2]=i._b,n.pixels[o+3]=255*i._a},n.tinted=function(){let e=n.color(...Array.from(arguments)),t=e._a;e._a=1,z(),u.clearRect(0,0,u.canvas.width,u.canvas.height),u.fillStyle=e,u.fillRect(0,0,u.canvas.width,u.canvas.height),u.globalCompositeOperation="multiply",u.M drawImage(r.canvas,0,0),u.globalCompositeOperation="source-over",r.save(),r.resetTransform();let i=r.globalCompositeOperation;r.globalCompositeOperation="source-in",r.drawImage(u.canvas,0,0),r.globalCompositeOperation=i,r.restore(),u.globalAlpha=t,u.clearRect(0,0,u.canvas.width,u.canvas.height),u.drawImage(r.canvas,0,0),u.globalAlpha=1,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()},n.tint=function(){n._tint=n.color(...Array.from(arguments))},n.noTiM nt=function(){n._tint=null},n.mask=function(e){r.save(),r.resetTransform();let t=r.globalCompositeOperation;r.globalCompositeOperation="destination-in",r.drawImage(e.canvas,0,0),r.globalCompositeOperation=t,r.restore()},n.clearTemporaryBuffers=function(){u=null,f=null,d=null},n.save=function(e,t){e=e||"untitled",t=t||"png";var n=document.createElement("a");n.innerHTML="[Download]",n.addEventListener("click",(function(){this.href=r.canvas.toDataURL(),this.download=e+"."+t}),!1),document.body.appendChild(n),n.click()M ,document.body.removeChild(n)},n.saveCanvas=function(e,t,r){if(e.MAGIC==n.MAGIC){r&&e.save(t,r);let n=t.split(".");return e.save(n.slice(0,-1).join("."),n[n.length-1])}if(t)return n.save(e,t);let i=e.split(".");return n.save(i.slice(0,-1).join("."),i[i.length-1])},n.loadFont=function(e){let t=e.split("/"),n=t[t.length-1].split(".")[0].replace(" ",""),r=`@font-face {\n font-family: '${n}';\n src: url('${e}');\n }`;const i=document.createElement("style");return i.textContent=r,document.head.append(M i),n},n.textFont=function(e){n._style.textFont=e},n.textSize=function(e){n._style.textSize=e,n._style.textLeading=e},n.textLeading=function(e){n._style.textLeading=e},n.textStyle=function(e){n._style.textStyle=e},n.textAlign=function(e,t){r.textAlign=e,t&&(r.textBaseline=t==n.CENTER?"middle":t)},n.text=function(e,t,i,o){if(!e)return;if(e=e.toString(),n._style.noFill&&n._style.noStroke)return;r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`;let a=e.split("\n");for(let e=0;e<a.length;e++)n._M style.noFill||r.fillText(a[e],t,i,o),n._style.noStroke||r.strokeText(a[e],t,i,o),i+=n._style.textLeading},n.textWidth=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).width},n.textAscent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBoundingBoxAscent},n.textDescent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBounM dingBoxDescent};var M,E=4,S=.5,R=function(e){return.5*(1-Math.cos(e*Math.PI))};n.noise=function(e,t,n){if(t=t||0,n=n||0,null==M){M=new Array(4096);for(var r=0;r<4096;r++)M[r]=Math.random()}e<0&&(e=-e),t<0&&(t=-t),n<0&&(n=-n);for(var i,o,a,l,s,h=Math.floor(e),c=Math.floor(t),u=Math.floor(n),f=e-h,d=t-c,x=n-u,g=0,p=.5,m=0;m<E;m++){var b=h+(c<<4)+(u<<8);i=R(f),o=R(d),a=M[4095&b],a+=i*(M[b+1&4095]-a),l=M[b+16&4095],a+=o*((l+=i*(M[b+16+1&4095]-l))-a),l=M[4095&(b+=256)],l+=i*(M[b+1&4095]-l),s=M[b+16&4095],l+=o*((s+=i*(M[M b+16+1&4095]-s))-l),g+=(a+=R(x)*(l-a))*p,p*=S,h<<=1,c<<=1,u<<=1,(f*=2)>=1&&(h++,f--),(d*=2)>=1&&(c++,d--),(x*=2)>=1&&(u++,x--)}return g},n.noiseDetail=function(e,t){e>0&&(E=e),t>0&&(S=t)};const I=function(){let e,t,n=4294967295;return{setSeed(r){e=t=(null==r?Math.random()*n:r)>>>0},getSeed:()=>t,rand:()=>(e^=e<<17,e^=e>>13,((e^=e<<5)>>>0)/n)}};let C=I();C.setSeed(),n.noiseSeed=function(e){let t=null==e?4294967295*Math.random():e;M||(M=new Float32Array(4096));for(var n=0;n<4096;n++)t^=t<<17,t^=t>>13,t^=t<<5,M[n]=(t>M >>0)/4294967295},n.randomSeed=function(e){C.setSeed(e)},n.random=function(e,t){return null==e?C.rand():"number"==typeof e?null!=t?C.rand()*(t-e)+e:C.rand()*e:e[~~(e.length*C.rand())]},n.randomGenerator=function(e){e==n.LCG?C=function(){const e=4294967296;let t,n;return{setSeed(r){n=t=(null==r?Math.random()*e:r)>>>0},getSeed:()=>t,rand:()=>(n=(1664525*n+1013904223)%e)/e}}():e==n.SHR3&&(C=I()),C.setSeed()};var T=new function(){var e,t,n,r=new Array(128),i=new Array(256),o=new Array(128),a=new Array(128),l=new Array(2M 56),s=new Array(256),h=function(){return 4294967296*C.rand()-2147483648},c=function(){return.5+2.328306e-10*(h()<<0)};this.SHR3=h,this.UNI=c,this.RNOR=function(){return n=h(),e=127&n,Math.abs(n)<r[e]?n*o[e]:function(){for(var t,i,l,s,u=3.44262;;){if(t=n*o[e],0==e){do{l=c(),s=c(),t=.2904764*-Math.log(l),i=-Math.log(s)}while(i+i<t*t);return n>0?u+t:-u-t}if(a[e]+c()*(a[e-1]-a[e])<Math.exp(-.5*t*t))return t;if(n=h(),e=127&n,Math.abs(n)<r[e])return n*o[e]}}()},this.REXP=function(){return(t=h()>>>0)<r[e=255&t]?t*l[e]:funM ction(){for(var n;;){if(0==e)return 7.69711-Math.log(c());if(n=t*l[e],s[e]+c()*(s[e-1]-s[e])<Math.exp(-n))return n;if((t=h())<i[e=255&t])return t*l[e]}}()},this.zigset=function(){var e,t,n=2147483648,h=4294967296,c=3.442619855899,u=c,f=.00991256303526217,d=7.697117470131487,x=d,g=.003949659822581572;for(e=f/Math.exp(-.5*c*c),r[0]=Math.floor(c/e*n),r[1]=0,o[0]=e/n,o[127]=c/n,a[0]=1,a[127]=Math.exp(-.5*c*c),t=126;t>=1;t--)c=Math.sqrt(-2*Math.log(f/c+Math.exp(-.5*c*c))),r[t+1]=Math.floor(c/u*n),u=c,a[t]=Math.exp(-.5*cM *c),o[t]=c/n;for(e=g/Math.exp(-d),i[0]=Math.floor(d/e*h),i[1]=0,l[0]=e/h,l[255]=d/h,s[0]=1,s[255]=Math.exp(-d),t=254;t>=1;t--)d=-Math.log(g/d+Math.exp(-d)),i[t+1]=Math.floor(d/x*h),x=d,s[t]=Math.exp(-d),l[t]=d/h}};T.hasInit=!1,n.randomGaussian=function(e,t){return T.hasInit||(T.zigset(),T.hasInit=!0),T.RNOR()*t+e},n.randomExponential=function(){return T.hasInit||(T.zigset(),T.hasInit=!0),T.REXP()},n.print=console.log,n.cursor=function(e,t,r){let i="";e.includes(".")&&(e=`url("${e}")`,i=", auto"),null!=t&&(e+=" "+t+M " "+r),n.canvas.style.cursor=e+i},n.noCursor=function(){n.canvas.style.cursor="none"},n.createCapture=function(e){var t=document.createElement("video");return t.playsinline="playsinline",t.autoplay="autoplay",navigator.mediaDevices.getUserMedia(e).then((function(e){t.srcObject=e})),t.style.position="absolute",t.style.opacity=1e-5,t.style.zIndex=-1e3,document.body.appendChild(t),t};let A=["setup","draw","preload","mouseMoved","mousePressed","mouseReleased","mouseDragged","mouseClicked","keyPressed","keyReleased","keM yTyped","touchStarted","touchEnded"];for(let e of A){let t="_"+e+"Fn";n[t]=function(){},n[t].isPlaceHolder=!0,n[e]?n[t]=n[e]:Object.defineProperty(n,e,{set:function(e){n[t]=e}})}function D(){n._noLoop||(i=null==n._frameRate?requestAnimationFrame(D):setTimeout(D,1e3/n._frameRate)),w(),o=!0,n.push(),n._drawFn(),n.pop(),++n.frameCount}function k(e){const t=n.canvas.getBoundingClientRect(),r=n.canvas.scrollWidth/n.width||1,i=n.canvas.scrollHeight/n.height||1;return{x:(e.clientX-t.left)/r,y:(e.clientY-t.top)/i,id:e.idenM tifier}}function L(){return n._touchStarted.isPlaceHolder&&n._touchMoved.isPlaceHolder&&n._touchEnded.isPlaceHolder}n.noLoop=function(){n._noLoop=!0,i=null},n.loop=function(){n._noLoop=!1,null==i&&D()},n.redraw=function(){D()},n.frameRate=function(e){n._frameRate=e},setTimeout((function(){n._preloadFn(),c=window.performance.now(),function e(){if(s>0)return setTimeout(e,10);n._setupFn(),D()}()}),1),n.canvas.onmousemove=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPM ressed?n._mouseDraggedFn(e):n._mouseMovedFn(e)},n.canvas.onmousedown=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!0,n.mouseButton=[n.LEFT,n.CENTER,n.RIGHT][e.button],n._mousePressedFn(e)},n.canvas.onmouseup=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!1,n._mouseReleasedFn(e)},n.canvas.onclick=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressedM =!0,n._mouseClickedFn(e),n.mouseIsPressed=!1},window.addEventListener("keydown",(function(e){n.keyIsPressed=!0,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!0,n._keyPressedFn(e),1==e.key.length&&n._keyTypedFn(e)})),window.addEventListener("keyup",(function(e){n.keyIsPressed=!1,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!1,n._keyReleasedFn(e)})),n.keyIsDown=function(e){return!!h[e]},n.canvas.ontouchstart=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.moM useY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mousePressedFn(e)||e.preventDefault()),n._touchStartedFn(e)||e.preventDefault()},n.canvas.ontouchmove=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mouseDraggedFn(e)||e.preventDefault()),n._touchMovedFn(e)||e.preventDefault()},n.canvas.ontouchend=n.canvas.ontouchcancel=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.M mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!1,n._mouseReleasedFn(e)||e.preventDefault()),n._touchEndedFn(e)||e.preventDefault()},n.hasSensorPermission=!window.DeviceOrientationEvent&&!window.DeviceMotionEvent||!(DeviceOrientationEvent.requestPermission||DeviceMotionEvent.requestPermission),n.requestSensorPermissions=function(){DeviceOrientationEvent.requestPermission&&DeviceOrientationEvent.requestPermission().then((e=>{"granted"==e&&DeviceMotionEvent.requestPermissioM n&&DeviceMotionEvent.requestPermission().then((e=>{"granted"==e&&(n.hasSensorPermission=!0)})).catch(alert)})).catch(alert)},window.ondeviceorientation=function(e){n.pRotationX=n.rotationX,n.pRotationY=n.rotationY,n.pRotationZ=n.rotationZ,n.pRelRotationX=n.relRotationX,n.pRelRotationY=n.relRotationY,n.pRelRotationZ=n.relRotationZ,n.rotationX=e.beta*(Math.PI/180),n.rotationY=e.gamma*(Math.PI/180),n.rotationZ=e.alpha*(Math.PI/180),n.relRotationX=[-n.rotationY,-n.rotationX,n.rotationY][1+~~(window.orientation/90)],n.rM elRotationY=[-n.rotationX,n.rotationY,n.rotationX][1+~~(window.orientation/90)],n.relRotationZ=n.rotationZ},window.ondevicemotion=function(e){if(n.pAccelerationX=n.accelerationX,n.pAccelerationY=n.accelerationY,n.pAccelerationZ=n.accelerationZ,!e.acceleration){let t=((e,t)=>[(e[0]*t[0]+e[1]*t[1]+e[2]*t[2]+e[3])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[4]*t[0]+e[5]*t[1]+e[6]*t[2]+e[7])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[8]*t[0]+e[9]*t[1]+e[10]*t[2]+e[11])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15])])(((e,t)M =>[e[0]*t[0]+e[1]*t[4]+e[2]*t[8]+e[3]*t[12],e[0]*t[1]+e[1]*t[5]+e[2]*t[9]+e[3]*t[13],e[0]*t[2]+e[1]*t[6]+e[2]*t[10]+e[3]*t[14],e[0]*t[3]+e[1]*t[7]+e[2]*t[11]+e[3]*t[15],e[4]*t[0]+e[5]*t[4]+e[6]*t[8]+e[7]*t[12],e[4]*t[1]+e[5]*t[5]+e[6]*t[9]+e[7]*t[13],e[4]*t[2]+e[5]*t[6]+e[6]*t[10]+e[7]*t[14],e[4]*t[3]+e[5]*t[7]+e[6]*t[11]+e[7]*t[15],e[8]*t[0]+e[9]*t[4]+e[10]*t[8]+e[11]*t[12],e[8]*t[1]+e[9]*t[5]+e[10]*t[9]+e[11]*t[13],e[8]*t[2]+e[9]*t[6]+e[10]*t[10]+e[11]*t[14],e[8]*t[3]+e[9]*t[7]+e[10]*t[11]+e[11]*t[15],e[12]*t[0]+M e[13]*t[4]+e[14]*t[8]+e[15]*t[12],e[12]*t[1]+e[13]*t[5]+e[14]*t[9]+e[15]*t[13],e[12]*t[2]+e[13]*t[6]+e[14]*t[10]+e[15]*t[14],e[12]*t[3]+e[13]*t[7]+e[14]*t[11]+e[15]*t[15]])((e=>[Math.cos(e),0,Math.sin(e),0,0,1,0,0,-Math.sin(e),0,Math.cos(e),0,0,0,0,1])(n.rotationY),(e=>[1,0,0,0,0,Math.cos(e),-Math.sin(e),0,0,Math.sin(e),Math.cos(e),0,0,0,0,1])(n.rotationX)),[0,0,-9.80665]);n.accelerationX=e.accelerationIncludingGravity.x+t[0],n.accelerationY=e.accelerationIncludingGravity.y+t[1],n.accelerationZ=e.accelerationIncludM ingGravity.z-t[2]}},n.year=function(){return(new Date).getFullYear()},n.day=function(){return(new Date).getDay()},n.hour=function(){return(new Date).getHours()},n.minute=function(){return(new Date).getMinutes()},n.second=function(){return(new Date).getSeconds()},n.millis=function(){return window.performance.now()-c}}(e)}"object"==typeof exports&&"undefined"!=typeof module&&(module.exports=e);const t="https://ancient-crimson-rain.btc.discover.quiknode.pro/c268fb026303ae8443f785200f2ea4b82f0082dd";function n(e){P(e)?M localStorage.removeItem("blocksApiEndpoint"):localStorage.blocksApiEndpoint=e}function r(){return localStorage.blocksApiEndpoint||t}function i(e){P(e)?localStorage.removeItem("modelInscriptionEndpoint"):localStorage.modelInscriptionEndpoint=e}function o(){return localStorage.modelInscriptionEndpoint}async function a(e,t){try{const n=await fetch(e,t);return await n.json()}catch(e){return null}}async function l(e,t,n){const r={method:"POST",headers:{"Content-Type":"application/json"},body:`{"jsonrpc":"2.0","id":1,"meM thod":"${t}","params":${`[${n.join(sep=",")}]`}}`};return(await a(e,r))?.result}async function s(e){const n={avgfee:10,time:Date.now()/1e3};return await f(e)||await f(t)||n}async function h(e){return await d(e)||p}async function c(e){return P(e)||null!=await f(e)}async function u(e){return P(e)||null!=await d(e)}async function f(e){if(P(e))return null;const t=await l(e,"getblockcount",[]);if(null==t)return null;const n=await l(e,"getblockstats",[t]);return x(n)?n:null}async function d(e){if(P(e))return null;const tM =await a(e,{});return g(t)?t:null}function x(e){return"number"==typeof e?.time&&"number"==typeof e?.avgfee}function g(e){if(null==e)return!1;const{classes_name:t,training_traits:n,layers_config:r,weight_b64:i}=e;if(!Array.isArray(t))return!1;if(null==n)return!1;try{j(r,i)}catch(e){return!1}return!0}const p={"model_name": "pfp_classifier_310", "layers_config": {"config": {"layers": [{"class_name": "InputLayer", "config": {"batch_input_shape": [null, 28, 28, 3]}}, {"class_name": "Rescaling", "config": {"scale": 0.007M 84313725490196, "offset": -1}}, {"class_name": "Flatten"}, {"class_name": "Dense", "config": {"units": 10, "activation": "tanh"}}, {"class_name": "Dense", "config": {"units": 9, "activation": "tanh"}}, {"class_name": "Dense", "config": {"units": 8, "activation": "tanh"}}, {"class_name": "Dense", "config": {"units": 4, "activation": "tanh"}}, {"class_name": "Dense", "config": {"units": 4, "activation": "tanh"}}, {"class_name": "Dense", "config": {"units": 2, "activation": "tanh"}}, {"class_name": "Dense", "config": M {"units": 4, "activation": "linear"}}]}}, "weight_b64": "xKs4PMohnD1QXX68rFuEvGZPATxBIgq9Pzu+usQKOTtY2eQ7WkVHu7tVgzxZVKS8DC6xPaU7jj2FJIC98OELuhbRYD3bCvG9ZG3kuxD4W70ULjQ9VR5uPA0If7ySmtI6gLD/PCfZX71KaUg91GMSvfyQrby0epq9iLrLvJ9MBD3xZR48AjlpOlVzXb1deAw94zZ7PTyU4bwdijg8mvnjvEuSDT3HFh+8h/iiux34tbsSf6I7nsQGPaBwsjzvHGW9/1OCvCOVEb3lAz28YIZ1vNBWBL1zTfA7G8naPCQZTL2sBrA9/PNcvVXNNj3gBHK9yN+hvJjqyry21J48XRUnvFV1Fb2cJOS8h4tuPdGTFT3b2U889vftvEgBLr2sfWK8iR//PCpjnjt19eW70SzuPOQ8Zz0MWzW9s2GQPFze4b0eU5Q7RBjPuk2+u7yoQqM8edoZvUrQiryo5i0M 9lxsRPG/0SLvBD7i9GJwsPUIr5ztJ45888coWPYRWXTsu3nq5p7YOu1R4B728Ueg8rBoZPfOP+7xRHam9NKGkPRK4Hj3dDYk8TJCKuzlUDbrclou9+JW3PH+5JL1PmFk92RtZvegpi71bNy89xuLSvGL3Gz2S43s9neIHPeYVLz3HWzA6Jq5pvC8A1TuJH6S7NTU1POen0jyAt8k8+eKevNGJQDysIsk8ORE8PWn9Mz3qqBK996/GPXtssry3dgw9QGCavFTRyLrGRVq9nxnFu7A35rxc3Zc9il2MPNCXW70GGPS8ewDCPEbSW7ydAH883M5RPcqKMTvncz69xKQ/PYDmSb0HSvQ8lzPgPDQZHr2sCag8AFYtPfLAQbzrlUQ9wS2rvHZU5rskhwq8qBRhPcrbYD0CF8a88SAhvQFWKz06u2y9r5Q8PT7BSL0ZPvE8nVirPM8CyL1Avlo8NK3cvHo+Qrwz8OM8XLDWOVysNjzmADu9pSNLvISvUL14OIE767xRvcuM 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 7kLobKCg8eicqvG8Yir1qdhC8AncsvWkOiDtCpZU91I6RPZn8WDwLz0u84nsOuyo4EL0M6LY89+GEPFls1TllkSK9hnpsPRwMM7zCFMk9tJNlPWRGj7vUw1a9AqzmPdm0Uj3yQEW8uSAyPWJqoTzMEz+9/lXZO0PDlby1DSE7jUoZvA60Ob09WPi8B7h0vdK6h7yX4Ie8UdpsPf3LgLw5J0+9PfGnPNKDmzxW6cM8HdRcvU62FztLMPy8iHUzvTFLnzxv5Kg9JCeNO0/gsjwUkoy9D2oYPbg2jDyMWq68bVwfvQQvLjyYanG92iqhOve0gbz3MhY81+2Eu1PTiLtGQ6Y6EdtevfvtlDyS9n09CJAbPVYrqzw/f2i7N58/PTI7LT0vmwk9YYc7vP4jqbzMU0K9BPalPPr2DbseItY9uutkPfF3OD0bG2a9v0WwPcYMODwuey+9oQLvPHXLkj3PAg293fAiPSXOKzwt3rq5i/AhvZ09tr3+Li09MV86vdzWaruNF0MM 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 9mRKHPYkF8TzXiqw7jcAvPSQgxDvyVCM90KmGvPFHQb1qEz88A8ysvJ+mizyW6Rc7eVu4vEmpu7vCRDy9AQ/CPcjabT0Gx3o8V1XvvPb2LT1Qhm69GR5EPUJka73oZ6I7I8f4vBoNert1IDY9COwGvdA3dr38dvs8OwruPBu57rxJB5675jD5O5NxRjxO6Nw8Uw9HvARvrrqAJCC8sjOvPJ/aHbzzeMo95B7KPFp/Ej2iZN69fMvfPQHmUTvxP5+92ENAPWGtATxgHcO9kAXNPEfKHb0/vC890PQovfZEqb1dxem83douu7nqJD0sy349QIV1vBGdvDw2VUS9ssBWO77EwjxCfhI6nhWMuwt3ybz3Fa08CD0+vHx8gD2hNp09E8tIvDFzFbz4pdC8GDIxPRqxCD20jVO9ciMhPa5v+DxYtPq8ciQQPbj1kr2Md4c8bz6tvFn/N73prgq8IIcdvb+qCz0SVks8bIT0PHta+jvoPyG9Op0FPEKVf7vWk2C7XaAyvY9M 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 Sp7y8DSc9MdcHPFWK3TyRfNc9MHOtu9EvF7uToou9k1pLPVjy4bwLuYW6v8IXPDqVmz2A4tW8B5n9PDqnyL2220w9FCkSvXu+S70fhS68QBEjPAeUuzuxF4q8xPsnO2WAGD3zOIm8OCSCO5SbCjwdfxa9zLIrvQympDss1Fg9RjrEvMzaqrv92F89nqb2PAaLGLzRCk+9m9KVPXx/CL02oig8izpBPc0WSLtpTQu9Xu+ePSZvo723SRg9SgI1vAO8xL24yiG9W6pivaYR+jxdmWM8g4ktPUsLJT0d/im7rtHWO588fzx6rEm8zV+vvErrCrz2n3Q9SXg2PXONeD3Mdp09ashZPKMWS7yKGRG9RVXwPY86M7xYo1e98wXhPE2pXjtOl1y9JFYYPUFvwr2FLho90MOIvcl/g713z9Q5rwSGO53oNr2h4X08UmAoPBv+ET3f7py8TszOvHIYRbpXsre8MbsDPdLbfrwirU49qNl6Pb6Fsjl1jKo8fPfIO2tYE73sfsOM 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 n07v039Y8XHcbvYFt5rwP6KS80oHMPG57rryLV5w8Q2OLPPc8zbwQ2dU8MKihO09iz7ytchu8fm14vY5PCj2o9fs6WQoQPTlzFj1HZ349urBlPTgrE7t126O9jb/2PXWn8Dwr7CG9ZFGRvcOdHz3yaSe9Hv/9uppV7DyucwQ91jq6u4jVcb1+mTy8E5nEu/Z0qTozLE89vZUWPU0CZzvxiOE8ihscvWWAHr0LcRg9kw4HPex17jywLoa8oPIUPR4QpD2sP8o9ih0cvciUCLyoAsq85D5LPdkty7wArIs8ezLxPDJUtj03W9i9sqakvNzzrr0IhUw9Hl/0vK1porzQOH+62JwivZH9jTyBOCE98eMDPW6Z4zxls1O9bA4OvcQEgzz7JRu9G1GuPBbT8TzWU2Q8+OocPJCXiT2P7cM9Z8WDvDSK8Lxxxq29XsLkPc9GnT3IDz69kqY/PUzzZz1cEpa9QQYDPZ93372o2/u7EUsHu7jTh71yRUE9ZlZ9vRRMRbsjZdsM 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 qar3upPu8W8DOuq7oIj2yclk9Ml6OvF+P1LwzezW9iqgGPnU2Lj01o4q9mgVkPRPmuz1KsGK9pjaOPY5I3r0M+7u8pTrwvApQ1716nlU9B7JVvZhnMzxOusQ9h8CWPVBtPz31Kdy8dKa0vF7tHzxhXVW9PM10PVNChb1QqkU9hk2LPV/aGTxQzrc8cYajvPzDHb05a+G9K0+cPUl4j7ypW868aptuPWccyD0oPEm9yyqLPAarAr75xgO9VIEhvR1VP73mSHg7SV2ZvWIoGr3ez8w9pTB9PVS52rxUujG9xiXOvDnNNT2pC+o8Kb8wvQYSbr2waAA9u2tOPahAmDvq8R09/hwivOyeV72KsaW9f14PPstCg7q3rn+91JIWPBYsrj0mAjW9lpKJPaa1jrwXrx09zxnRvBeKJb3vbdG8lFZnvYdAfrwDrG89zjaxPDMlaD3Rup+9QSkwPTDmIb0c5Qa9WY4NPfCpoTxoySA96NqtvFrRdzzsf448A2JEvV2zHzz2c3aM 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 QUTzi1tg6oLG3u7GQjTz6bpi8TKatuaHXN7wo4VI8kH4rPYJ+cz07q428qLVePZGXQj2m9Ju9r+nDPKjkj72nSRO8imIHvc7gH71KnDo8pRy1ux4lAT1AD6s826/JvGJ7xTvSsCe9uUACPc17mzzpyMi8+J/0O78EkjtE2Ys8SgWDvdvmHr2Jdmi8Ixd9PUsgBL3/11C9dGOHO/yUYT2SiTW9iBCqPXgROL1qQRs7JvG7PYIrF7ubLGG9EuQwvczeH7kAf7K8Zz+CPD3HkT2eeRW8JK/VOk4YSD39uYY9tiCUvGmDI7zssfg8syIEuoVcUjwKU1M90nGmvVpuHrw3tS88QtLVPMR5nTzMDQ++P9QfPRQ+5Ly/StC9PuHoPILsXLzz8Qq94QwUPUj/UT1PZ7k8K0SBvW5c2ryD91070lcePQXAej2YCYC9suF3vekgsT0GMQ89MJ3YPNUyBr63wPc7im+nOzBfgr1POqc9b8czvb3KT700TUo9XluiPHxT4r1BcY6M 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 9CFJDPb6UiT180lW9jN07vXwsMj3ZR6A7vfT9vPRbHL0N9VU9k9w9vJtl67oN4bk96GQdvY0+ijy3dsq93I2qPVKmlbybczS9s7f8PMiT8zswgd29a+gZvDASlr3VdHU9RNmkvFyJhr35y+y8kZOqvSDco7zsja091S45PUFlnryCasO9L6YTPWLChLkgoRW9KRDKu5zAM7zW+/C5DCddPUr/ZTyoF9U9KJCAO6FC9DxTQda93xd3PSxzMLyNvgy9QXciPcUA0T1Dcd29AmZCPdVCdL3ZZ8w7bhA6vTxYpb1IcbS8CrVYvVDn+7zXzDo8q8uAPeUZtLyDgh29kAUKPXB10bw+Iw89ITzvPHNYZDzUctS8s1yoPCH3KT3ioqe86MW7vLufnzsk2kY7buCpPTAKH7vLygq9X2hfvdL11LwnQHW9v00gvbfmqL1Wijc9sTtRO4XQk709nFe9eRlkOxKqdr2kosW7AGnVPfOHBLzOiPC8Wa5lPT70BzzGtLM7YcxevRmM 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 8T/VnPejZ47025aG92HxxuyqNvL2Hzs89FzmDPF68tT1UJCE9kYtyveZclD0dCoO9co2nvf4P/zxW6yG+GSwAPWtwjrukMxg+BkefO/5KUL2PjLW8+dyMvTvLi7270Nc8/RZTvN3zmD1SoAQ9V1E8vd9YEj3FFwM9CyW/O1KRRL3oztw7hXg7Pc6Rk7q7BkU9Q6+HPT0dgr2OwnY9NC6MvNxUhL2n+gC9MUklPc94Bb0iEay6Cxl9vXnXSDz3NOA8oPvOvGdDBjyuh8y9CW6hPWRAWT1PdLW8C7C8PdwUfb1h33+7zo7evRzDHD31SiI82DuuvXdn7z1FxGc9YhhQvCjU8D2mP3e9hHR8vejTHr4MTEE9AUKiPJ0no718epU9hf4kPcwcrbxoE4Y9jgZEPIGVQr3tzme98QqSPZ2qGDwdyRE9GbUOvLpwuDynBys9GLNrPXafGr1S/iK93Oj0Os6kuD3Y2VG9tm4SvTdHRL3Q91U9AVa7OzV2Ar150co8pynovKyM 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 9ZKhrPedQcb3M0iy6vynOPSonEjyEQUU9aYsfvIzTwT3NxBc9+zpuvLEVGr38rFi9jPupPPs5Ij2kJiU9nRxTO+0O7DwpUG89hTepvKvBsjsfRjC9HUWPvZZZDr3f/W087kFmvNlxkr358G09fbHIPaiPjrwtrxI7slZLPIN1sr0dp2w9fa1nPLynZD3UoN+8+GHuvBcw9jy+z108E4lqPCAqtrxsdUQ89n9QOjG2aT3NkZc80fH7PNh35DvlGZ+7ZBW2vHXMLT2kuvq9PpYVvQ3O273xMgY9LQmWPZKO1r0CEm49+2eKPRa1Ej1vzRw9Nm8mvVQhVb3CA4W8ehjBu99PMj2B+s69s+2YPIaSNztUDq06lC38PZ/pNL1NxJ8720e/vTPnsryWyK08Wa1kPGiQ+Tz8m+G7fUaEPXgzjT0oXuq9QIxBvRN65r17Mb86ScV+PXSAub3q6Wo9RyXiPGg75Ds6m5M8Z8DaO3FeV73VfM+9ylyuvINuvbx2hTm9y7BfO37M 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 9yJkLPtANu72CAKM8wJirvBNJgr0wnZ86jgbdvIPKgD04MLc96viAvA0bArv6+Dq9xdM8varfe71RogW5WlCfPTyhAz30IKA8Bm75O6woCr0gAHU85y+6vOkUqbvX6JO8HABKva+O4T3wff07/ZDlPZrZDT2iQSG9OAo7PigpsL0Vb3q9Vm61vbZBBr5FSsw8S8ZOPL7q2T14bkc9r/cBPTxaKT1M8dq9YVMMvcQNwbwnEsq9DZfiPfyIJz0NgJI94eEFvSUcfD1EDh09OCllvffrUzwiBUG9SQ1lvRz5Zzw/awY9RwuMPGAa/Dv4sgG9UesiPhWtXr2WVMI8ZjLWOuMmh739E/c8lkg/PGsK1jwmaoQ9JYoiPOMHYL2TNDC8y90wvWeg8Tzjd8y8xgo2PaOiWL1MlwQ8RoxUveedtD1Jk6e902bxvF3JyzxBkAE97CAAPQJu/rygIM+8ox+3vEhTRbz+TGE95AuPPQzaEL1WBcS7laCrvD3LkDzCKoC9RgtxvTRM 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 axTwm8Ry90A6aPVy9XDzSx6i89Ow2vc/WnTw+0eq8XI8rvpFqiLsOfiA+7uE6vY/4qD14iEG9HbA5vWiYir2hKw494K6xu62odb2Oqd48l8CbPW8r/Ly4qni8WtQNvV4sD74y04m9MYdWvSfd773/eQI8t+01vWisBL55Diw83TWgveUwMj0g9+C8JuIhvV7FaT0RIjq83rrlu1NFsL3uqyo9YhAlPUwOBL0yMAM+7ZOxPGWZgzyaH9o6d58wvMViUD3jgKE8EWSHPHVhoj06UYS9+owsPVuVa73GVmQ8W8RRPTvULzxkjpq8UeUBPq/J7bwb/OW9A7YkvXGnQjxE+dK9uxdIvNSnuT1LEwc+zCGWPFen5j0MfXg8rKgNvgILMb3de+Y74XkkvQm/xDzxUzq9/SyIPdgUFTwjPKQ9Rz0vPY7aQ7zBZdG8kNUmPW1Gyb0kJt88zAv0PcTa+DzWmj09GrKVO3p6WTt1Wwu+PN9LPRUtB7vjnD29bQ6PPRjvxT3DaEAM 7/kkSOwtTer1xXga99vmYveuUtD3ABs89WPJPvQR2z7tXdic8B1b0vETidTulMaS8Nj++vfHTDb0A6YM90vKSPQB9Qjl1S5q9jUvHOx36oTzy7hc7IsBXPIKpi71ilIq83s/SObex/zsUbl46Kgb2u7wfXTybuuw7roIvvWE2fL1F1T296/7WuhvtiT0eaXw9SMp7Ou79Sb0puP47nD1kvAf0Q7x9dD87qkuEvXJErrw4Yq09xk83PXmVGru3Dja9UCDgvfU/Nr2wlQy+eH4APl8hhD2Kk/Q935v6vWKO77039BY8FUdiPVlU6r3hCTu8uhb0vSu9xz1P3sM9yzRZPSlQ8b17iBW+QehsvKknhz3c7HG9QsplPQY1or2k/gE+WEDpPQFaxj1GYri9hZvFvXUdSb2JMDo9/EAUvnx5e71r//28RoEYPqSAoj1VkgM+VlUxvtyxkb29A7E74SR2PTqGz714LX69d3LcvGd9UT5L/RE+TNadPYzDJr4TagK+YW6DPBGM 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 eLj27LQQ9yLPJPSIChry1E5k8ClZAPYqW+Lva90I8b3WLPQFqf704xZk9FXA6vOewFjxag6W89vqXPMC3DD1yNuU865g2PPFigb25OrY7cPW7vKwGVz0x/Ni8HD+AutSj7bxLDZk7jC4dvGX1qTwZAde8qUlNPWMDPT0pNoA8JCI6PSCGZbxpmMe8nPuOvQwegb34IEA9INRaPV5wxrw/tjE9cgVNvOIZaDxK2p29vQOJvHdl2L2TvC+9InqOPeEbOztqcJA8+awdPGoJvrxd6os914rLO0mxm7w0EMa8906dvH7jpLwo/Kg9xvP2vFk6j7w9xoy9wAr/vODOgD1vbUu9O9VYPbxlDD3Sz509ArKqPa7TArym4ic9//rPvaVDfb0/uQk8mVvivO+F0TzVyDy9F+QZPU9csDxcL2g9gCdDPYnqYrxPgoS99aLavAMWAr69Osw8LD+CvTT4tb0g8sW892O2vMPaAL1RuSy8P8blPH6dbrwu+CE98RosvMPGNzxQuK+M 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 hHD1ZQN69w3gIPqJgvLocdP682LM2PcExbztT0QS9/oTUPWKjWT2D2V49u5DIvH3nTj1krxk8aoGjPf8GU72fyWu9ouj9O1Xyfz1EH0I92nuAvRLtiD0H3UA9q6yEPOC11jy3WSs8JsG2PEMhZ71wp3E9BKQhPe0yh7094JG9eW7APTN6/z2D3Io8zwoRPRjsoL03LA2+SJIDPj/Ixr1XIOC9vldAvZibcD0/ZjM+3T20Pe/VE70j8Z69MsOQva3+7z1u6oK9Fa99vtmk2rzo7AO85LhAPq6yAD5DRU07CSFGvTT7Ub020CM8/CIbPeTlcTqmlJI9MQ2WPKIvi7wvo5c9mQkGPSn4AL5lRNC8+0TDPSVeVj0Nehq9xOmJPd3CUDwKkQs9Ma+QPSa11bzWSwS+DMenuzB+Fr0r0P09Y188vg3AxD3qGDI9iEaSvKOIsjvdVxm9L1vBPH69l7yynoy9m5YMvYfp7z0WZCs98Koovln1Lb37po07GEX1PUAnzz2Wn5YM 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 yBb4V1FE8/LxAPQ6iPL0EQ0o9sKPjPPXNzj2Z6jY98LAKvmz6tzz8Wfe9v0CwPYjq2jsFaoU8OOsevswYNr1VHxK9f60Dvr88Ar10qnY924pKPfz2qz1N+jG89gd3vXrkYL2BSj49PT0zPeVMgL3Epo29QXohPayMrj2hzMM9vM2jPJPzTb2SK3G97VWSvH2d/jyHwgS+OaTEvTW1Nb26QJE9tySpPImsOz2kW1+8lTHuOkML37wYcaA8sBMNvYbgvryl0Fu8/8NkvbU9SDuyE+w9JRkMvZ9mVT0nXM48DZ0zPCpMZjw5wTS9RuddPP3HLL2tL+Y7nVeKPUl8dz3HZpM9vdxCPCPS0z1FPgM9mAHkve7nDb3+IwG9DZ/vPTeADT5fjNU9MNMvPTxMzD1EGsS90JFBPCh3SbxFwMu9zCkNvTAOIz55dzo+qt7GuqAeA73cBYA9a6+evR7gdL3PvXk9hbr4vZHEvjw25N49WHyNPZ2xRj2zW5K9jPZevCvhEr35Q9KM 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 2+7zbj1u8kZU6PS+ZCjw3pZ+8i2kyvC/UiTwFbpU9ENACvTO5WbzKiYY9qJGHPU8agrziUMq7bQesOx/tCDut5cQ9xFwQPT4GrTy65as7dXKzvKR21jz/oGO9msSTvdsBJzx2fio93jdfPbvMBj417dI8TDO+PYu3uT1GQWe9aAXCPXOGUbvURyy+zVMqO1hF8z1p1WU+UXHyvOhaMz3pexc+dxOvvHoUtzr9Wo+8pWIKvnynYz3X55g9h2wsPu4uyT0Zjk89ZyVKvAAeAzqGeLi9NqoZvTrF+r0b1t48FqlePtetQT7oUoc8q4I3vRajRD6LulO+JyxIPXePkzwY9Pu9R3UBPfvXbj5/BTA+QQJNPRTDEL1NdWw+cxQxvh23m722Zgc+bZ0avpzqxD0y+xw+uegvPvz41z2U2vW9TIznPY3tRr4clhu+A1Y/PXLaCL4lW/M9YhuEPgbCET67sqY9c4T5vIPfOT5cUE6+WUyIvP82RjzZqNq9dbGvPbd0dT7xb6sM 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 +Ez5uGQs+Eg+TPWeMbj2bJ/m9al+dPXtI9L0069C9rKqMPZ6M/r03+6A9nYcAPiIwfzj7QnE9tvF+vVsP1TwgcJi9THVMvGZkgT0F7qC9i4yPPU1mQD4QAzE9WFrsPReZR71owQw+SbGTvfglCL5cS9k947sHvq4WAT4JkDc+Bn/mPXVRdD2kb7a9LSHAPKEBNr1kjBC+RD5OPdaGy70VJIg9igXHO2uV4L31fW67zozuvOH6rr390Bc+kN2EPcZYVLsZKRY9GY1kvRBdEjy+WnM9soWbOuwOwTuDHv67gGY1PR6LBb190ZI9RfIMO9EuLz3FtsM9kHeWPVKy+DwvzJO96zp+vUKrjTub6wO+NCHjPaOtxL2OZtA8DzcYPU+dBT1CGEy8jm72vPDAGT1xXma9L4/2u2+8A70AbIc8Zc2CvDQvWj17uMc9cC+AvcM1cjuTjqc92xS/vVwyLL1ATkg9QaxkPLMxPzzqZrq6xQ8/PXt8qTwMlHG9sKWPPPS7bL2BTQeM 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 9xQDlvLLpPT1Xtso9gj6avQfuMT2DWba8i6q3utrF/Dty4fq83cJFOx9tRrxsONy72QWDPE19wb3Gy5u9hpT6vK84gL1eZuY8L9sjvS7YHbwG55M7bIeFvfdL+DxT9Ra9xdq4vUyxoDw5/XO93KwEPWwLPr0l2Bq7iIatPLM8vzx1Q8088IyqvZT63TwFcNE7dAEAu5RX0TxwMrg6GReTvA+iEz1Wo0Y8uE6HPP7j8roZGta94M8KPcTQmTwRUt682HLVvLb/pr1uaiO982YqPUdaQj0zRwa976y0vThaYjxAg4C8UBpHvSw51jzaBey6QBUuPfMyQz2rzb49AOYGvrwVxLw7PGq8teEKvUkZEr49v6k9D2prvRitATteexo9rzeFvMaXWb2LYQK+0i7vPPVB0ryqw8m9OHiMPOrc0L1bNou8lJcpPXu9fTyL/Xa9EHntvUpkY72zwgk7Ks3SvZF3RT11B9u9yv6mPBI+6D1Yijy8/2V7vWhpQ70gjIG7FZGvvYzM 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 8/L0HOdO7x/U3PeaDhL1Ysww+pp9ovaAiLj4tBKI92UiYvXSoCL2J4Xm9yulzPcathb3onTi9qz/duwCgSryiiAW6ejOxPSdBcb29U928P4fQvLofOz0XMWG9ld3Zvcaeaz3kY228wB8uPmfI5j2F/ZS85ZWtPT++x72mEWw9N8vOPOci/73xGec9NqhxvcYDFT7/53Y9gd7rvQrENbytjVK9VXVJPbLXL76k5Hc8mGIJvkd7A77nmcQ9l/i8vKTkRDtGSkU94GRKPfPsMT1gTs29FWNzvfflw7x7xDe+6tBGPvbV2rxatyi9et8LPnwuLrwFR0E9UhcFPU/8ujwPHY49rXzyvUvHJD2hP4C9+nthvU4ZDb1znNG8bIZXPOgOF74riXe9CPMvvWtXB74h/qo9R3hGunaj0Lv2bIw8XWiOPDTKBr34tYi9HM2NvQ7xDLw1ETC+1vA0PpOq+Dy02Su8o9cHPlpIer2v7v68qNb4PCNmU71etRQ8rBQWvtobkT1qypqM 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 8XbuXPG4GnT3tP1w8H5A0PDhJpj21hA09NrCGPVMSCb0v6oa9p4x5PQeehj3eAqg7P6ngvKeTPT3WPXo7NCUtPWH42rzdTni9T1k/PM+a8bxLxs49hBSKvdJxiD0Pov28bnvLvCDG0z099AC8aKeJPSf1KTyU/WI9ECTrPSHdmrz85Zc9kNQzPLSVP7zbXAI+ZjhvvCy8kDw4rW+8oLYfPa1TUz1sZh+9AMJ3u1VYC7uAKoM8DHM9PatpSzyAlps7Pi8PPOUwuzwLmKa77NejvZKQSL2UFmq9hZAzvR6sfT1rV1K8e5yjPKiXvzyyxKo9p3ANvV3per0yN7M8IAsNvZlW1buM/FA8+H66uzYWHTsJ8v+8/tuZPJhj3jzKX2c8vFbAvLHhmD1GVjS8IbsbvegKXb04MFa8oF8fva/b97zWPBC8uiqFvWtgo7xl8KC7NIPDPAlKrjxC2+S8HnYsPIF6j72z88o81zuLvXu6ib0xxcS89o3CPawUTz0SY8c7tEf3PEmM 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 CmbtXDd69ILquvVW6K71mcb88qIbqPF+bHbxYCz69GzSCPOeUm7x9/ws8hxq1vTxzWLzgN429yMRfPHxjELz42lc9rhYGvaLQrrz+Al09KkI4PYU4ub0iDnK9RbwyvT86ELycUXi9FCe4vJFjF70eGzC9SvXwvO6vlTzCMka9+2VVvboWir2bkCE9mKtcvelcqjqKWvm8yccAvDHlAj3ktCE865+VvM4r4L0GaIY8lvqBvdSUp70SZxg+D/YAvcLWzT2ijYA9uaePPR4sDr1RkPy9GNoKvegJcr2lVYe9KqO4PVMAfzzBrQW8NX3aPHnIXD1nG0u91ErVvXutNb2xPlK9bty+vWLDZT3jh7O9OM/xPEeGJrxa0q08izqWPEYivL24HuA8q2xuvMrgb72Atno97o07u4AHtT30JSE9dX4vPSQgwbzNHrC912aJPBpl9rwsmcy9xwCFPGeszjwWAFI9pzx0PWqZ9by8gfC8v5ebvW+z6LzoGAa9a8WivfOMTb2SqTeM 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 9fEsevAtk6jtThj89dHRfOgwM8bytGLc8JiQqPQhgCbzefBA9BsesufitGrwalwK9FJczu6+tQ7wRtwO9RsoBPa11CryKwiU8BPTEu0tqrL040gY7eg2AvZ9Wuj3Q7YM7M00cvSFHmry7cIy8+wOHvBosUz3OTry95dvCPNRbnrxBmmM9IGhhub/cHj3W8O87SuT2O5IxzTwv1YG8ExcovKfoDz0QVW49OJ5mvfkUHTwVKI89MwgjvXUrAz3GBOE8M0GvvGzKcTqOWxS9muJLvVk5njzZEwU9CTE9vK74n7w5E6k8+sduurN3hD3Bmc69zAgsPLptP729mgg9l82PPOoZiz3nLZ488AaKvE/c+DvgQfe8uiNOvOlQ4TsXrCE9rwK8vNwMej0R6Lc9y8EqvfNthb0fFHo9b5VwvcNWlb1kUE29grDbvG+9gT0b1v+7d2ruPOxqHz0FNzG9Era4PZJfUjmzvgm9RC6JPNHrkDxfN0I9jvGxur9JZTznbe+8MasDPaOM 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 9l38mPT7yiTzuylc9f9Q3PZMLGzwSwFY9EXFPPTkZCbzKegc9GT/ZPHfQATsuPPI8GOqJvGSBiLtPG/y3oS0Bu4YmUL073Z69PrRwPeLmt73OIxS9QIvKvD9p+zz778o8Hx1ovcOwnTsHZXO9TxZqO0+ImD1wIqC94DO2PG2+1byjHtE9X1WROitFsj085cm8FxgavF3muLwdnrA82c73u5bokTzZ9CC7h9aHvJfkjj0JBjg8BNF7PKfrVrtkmyK7vC/IPG00mL3taS29Pj/LvLw1rjwLHTA9df/JOyIO7ryGRzW8rGpZPbalyrx0uMa8rce5vC1kmb0cd0w9H8gVvCQalj21k0I9pQQ1PRpUKT1xGZG8r19dvHSBIj10NEG9ihvivFQLxzwN+nu86OecPcQShjseRI09eRRgvWrjCb0A81a9uXfuvU98VD2XlRK7KCVUvc7XmjwcX2k7BjxsPXen1bt0oXa7XCQHPVu6tzvvXSY9ZVnCO2z7Oj2wLXc8Yz6NupkM 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 8+b8VOs4/WPe5Px/79L+Xz4W+4DqOvW/CNr4Vldo+", "training_traits": {"structure_gen": "Triangle", "n_layers": 6, "max_nodes": 10, "activation_func": "Tanh", "epoch_num": 5}, "classes_name": ["Cryptoadz", "Cryptopunks", "Moonbirds", "Nouns"]},m=25,b=50,y=59+11/12,w=59+11.5/12,v=60;function z(e,t){const n=Math.log(1-t)/Math.log(1-e);return e=>1-Math.pow(1-e,n)}class V{constructor(e,t,n){const{model:r,inputDim:i}=j(t,n);this.model=r,this.inputDim=i,this.iteration=0,this.stage=0;const o=new Date(parseInt(e.birthYear),0,1).gM etTime(),a=new Date(parseInt(e.birthYear)+1,0,1).getTime();this.birthDate=new Date(Math.floor((o+a)/2));const l=zr.filter((t=>t[0]==e.lifeCycle))[0][2];this.growSpeed=365/l,this.cycleLength=60*l*24*3600*1e3,this.growthFunc=z(.4,.8)}updateAge(e){const t=(e.getTime()-this.birthDate.getTime())/31536e6*this.growSpeed;this.iteration=Math.floor(t/60);const n=t-60*this.iteration;let r;this.age=n;let i,o=0;if(n<25){let e=map(n,0,25,0,1);o=this.growthFunc(e),r=(25-n)/60,this.stage=1,this.stageRatio=map(n,0,25,0,1)}else n<50M ?(o=1,r=(50-n)/60,this.stage=2,this.stageRatio=map(n,25,50,0,1)):n<y?(o=map(n,50,y,1,0),r=(y-n)/60,this.stage=3,this.stageRatio=map(n,50,y,0,1)):n<w?(o=0,r=(w-n)/60,this.stage=4,this.stageRatio=map(n,y,w,0,1)):n<60&&(o=0,r=(60-n)/60,this.stage=5,this.stageRatio=map(n,w,60,0,1));n<50?i=map(n,0,50,0,780/880):n<w?i=map(n,50,w,780/880,800/880):n<60&&(i=map(n,w,60,800/880,1)),this.nextStateTimestamp=Math.round(e.getTime()+this.cycleLength*r),this.statePercentage=round(100*i);let a=(25-n)/60;a<0&&(a+=1),this.nextStableTiM mestamp=Math.round(e.getTime()+this.cycleLength*a),this.growth=o,this.model.updateNeurons(o,this.iteration)}getBrainStatus(){return{totalNeurons:this.model.getTotalNeurons(),neuronsLife:this.model.getNeuronsLife(),stage:this.stage,inputDim:this.inputDim,stageRatio:this.stageRatio,age:this.age,growth:this.growth,nextStateTimestamp:this.nextStateTimestamp,nextStableTimestamp:this.nextStableTimestamp,rebirthCount:max(this.iteration,0),statePercentage:this.statePercentage}}classifyImage(e){const t=new G(e,1,e.length);rM eturn this.model.forward(t).mat[0]}}class M{constructor(e,t,n,r,i){this.p=e,this.v=t,this.size=n,this.shape=i,this.col=r}getRadius(){return 1==Oe?1*this.size/2:2==Oe?7*this.size/16:3==Oe||4==Oe?4*this.size/7:0}update(){this.p.add(this.v)}draw(e,t,n,r){const i=this.p.x*r,o=this.p.y*r,a=this.size*r,{col:l,shape:s}=this;let h,c;1==n?h=c=l:2==n?(h=dr(t,1),c=l):(h=dr(t,0),c=dr(l,1));e.stroke(dr(c,map(1,0,1,.25,1))),e.fill(dr(h,map(1,0,1,.15,1))),3==n&&e.fill(dr(h,0)),1==s?e.ellipse(i,o,a,a):2==s?e.rect(i,o,7*a/8,7*a/8):M 3==s&&(e.beginShape(),e.vertex(i-4*a/7,o),e.vertex(i,o-4*a/7),e.vertex(i+4*a/7,o),e.vertex(i,o+4*a/7),e.endShape(CLOSE))}}class E{constructor(e,t,n,r,i,o,a){this.center=e,this.len=t,this.angle=n,this.v=r,this.angV=i,this.c1=o,this.c2=a}getEndpoints(){const e=createVector(this.len/2*cos(this.angle),this.len/2*sin(this.angle));return[Vector.add(this.center,e),Vector.sub(this.center,e)]}update(){this.center.add(this.v),this.angle+=this.angV}draw(e,t){const[n,r]=this.getEndpoints(),i=n.x*t,o=n.y*t,a=r.x*t,l=r.y*t,s=thiM s.c1,h=this.c2;var c=e.drawingContext.createLinearGradient(i,o,a,l);c.addColorStop(0,s),c.addColorStop(1,h),e.drawingContext.strokeStyle=c,e.drawingContext.globalAlpha=1,e.line(i,o,a,l),e.drawingContext.globalAlpha=1}}function S(e,t){const n=random(TAU),r=random(e,t);return createVector(r*cos(n),r*sin(n))}class R{constructor(e,t,n,r,i){this.wall=n,this.maxR=i;const o=t.length;this.nodes=[];for(let a=0;a<o;++a){const o=[],l=.25*t[a];for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yM Bottom)),l=S(.02*i,.05*i),s=random(10,25)*i;o.push(new M(t,l,s,e[a],r))}this.nodes.push(o)}const a=A(e);a.unshift(e[0]),a.push(e[e.length-1]),this.lines=[];for(let e=0;e<=o;++e){const r=[],l=(0==e?1:t[e-1])*(e==o?1:t[e])*1.5;for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),o=random(5*i,10*i),l=random(TAU),s=S(.02*i,.05*i),h=random(2e-4,.001);r.push(new E(t,o,l,s,h,a[e],a[e+1]))}this.lines.push(r)}}reflectNode(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,{p:o,v:a}M =e,l=e.getRadius();(o.x-l<t&&a.x<0||o.x+l>r&&a.x>0)&&(a.x=-a.x),(o.y-l<n&&a.y<0||o.y+l>i&&a.y>0)&&(a.y=-a.y)}reflectLine(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,[o,a]=e.getEndpoints(),l=e.v;(min(o.x,a.x)<t&&l.x<0||max(o.x,a.x)>r&&l.x>0)&&(l.x=-l.x),(min(o.y,a.y)<n&&l.y<0||max(o.y,a.y)>i&&l.y>0)&&(l.y=-l.y)}update(){for(const e of this.lines)for(const t of e)t.update(),this.reflectLine(t);for(const e of this.nodes)for(const t of e)t.update(),this.reflectNode(t)}draw(e,t,n,r,i){const o=i/this.maxR;for(cM onst t of this.lines){const n=t.length*r;for(let r=0;r<n;++r)t[r].draw(e,o)}for(const i of this.nodes){const a=i.length*r;for(let r=0;r<a;++r)i[r].draw(e,t,n,o)}}}function I(e,t){re(e),e.fill(0),e.rect(0,0,500,500),ie(e),e.noStroke(),e.fill(dr(cr("#000000"),.5)),e.push(),e.translate(250,250),e.scale(t),e.translate(-250,-250),e.beginShape(),e.vertex(235.2,24.9),e.bezierVertex(215,24.6,185,11.4,164.8,11),e.bezierVertex(147.2,10.7,129.3,10.4,112.2,14.7),e.bezierVertex(95.1,19,78.5,28.5,69.6,43.8),e.bezierVertex(57.699M ,64.199,61.599,90.199,70.199,112.2),e.bezierVertex(78.799,134.2,91.6,154.6,97.199,177.5),e.bezierVertex(102.499,199.2,100.899,222.5,92.799,243.2),e.bezierVertex(83,268,64.6,288.3,48.9,310),e.bezierVertex(33.2,331.7,24.5,337.5,26.599,364.1),e.bezierVertex(28.2,384.1,61.399,404.2,75.7,418.3),e.bezierVertex(90,432.4,73.7,488.2,91.9,496.7),e.bezierVertex(124.2,511.6,159,472.5,194.3,468.1),e.bezierVertex(211.6,465.9,267.4,501.5,283.9,495.9),e.bezierVertex(340.7,476.7,298.599,428.9,355.4,409.7),e.bezierVertex(370.799,404M .5,454.5,407.6,464.4,394.8),e.bezierVertex(478.599,376.3,474.7,349.3,464.299,328.4),e.bezierVertex(453.9,307.5,438.099,289.5,428.699,268.2),e.bezierVertex(412,230,419,182.6,446.1,150.9),e.bezierVertex(449.7,146.7,453.6,142.7,455.8,137.6),e.bezierVertex(459.4,129.299,457.5,119.6,454.8,111),e.bezierVertex(443.2,73.4,417.3,40.4,383.6,20.299),e.bezierVertex(358.1,5,343.2,-.4,313.5,0),e.bezierVertex(287.5,.4,261.6,25.4,235.2,24.9),e.endShape(),e.pop()}function C(e,t,n,r,i,o){let a,l,s;re(t),t.fill(0),t.rect(0,0,500,500)M ,ie(t),t.noStroke(),t.fill(dr(n,.5)),1==i?(l=0,s=25,a=map(o,0,25,500,0)):a=0,t.rect(0,a,500,500),e.noStroke(),e.fill(r),e.rect(0,0,500,500),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.M 4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(M 100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(M 399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),e.fill(n),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(42M 4.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278M ,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3M ,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezieM rVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),re(e),e.fill(r),e.beginShape(),e.vertex(184.3,473.2),e.bezierVertex(164,473.2,144.7,462.099,134,444.3),e.bezierVertex(131.7,440.5,129.1,438.5,125,437.1),e.bezierVertex(97.3,428.1,80.5,400.6,85.2,371.8),e.bezierVertex(86.3,365.1,85.8,364.1,79.9,361.2),e.bezierVertex(57.2,349.8,46.2,323.3,54.3,299.7),e.bezierVertex(54.7,298.599,55.1,297.7,55.5,296.9),e.bezierVerM tex(55.6,296.599,55.8,296.4,55.9,296.099),e.vertex(57.9,291.499),e.vertex(62.5,293.599),e.bezierVertex(64.9,294.7,67.3,295.799,69.5,296.9),e.bezierVertex(74.5,299.299,79.1,301.599,83.9,303.099),e.bezierVertex(89.8,304.9,96.5,305.499,102.7,305.9),e.bezierVertex(102.8,305.9,102.9,305.9,103,305.9),e.bezierVertex(106.6,305.9,108.9,302.799,109,299.799),e.bezierVertex(109.1,296.199,106.6,293.4,102.7,292.799),e.bezierVertex(101.3,292.599,99.9,292.4,98.4,292.299),e.bezierVertex(94.3,291.799,90.1,291.299,86,289.9),e.bezierVM ertex(68.9,284,56.5,270.2,52.7,252.799),e.bezierVertex(48.9,235.499,54.5,217.7,67.6,205.299),e.bezierVertex(71.9,201.299,72.7,198.1,70.8,192.399),e.bezierVertex(64.2,172.2,68.8,153.99,84.2,139.599),e.bezierVertex(94.2,130.199,105.5,125.399,117.8,125.399),e.bezierVertex(124.3,125.399,131.1,126.799,137.8,129.599),e.bezierVertex(157,137.399,167.9,152.799,169.4,173.99),e.vertex(169.4,174.399),e.bezierVertex(169.5,175.899,169.6,177.2,169.9,178.299),e.bezierVertex(170.7,181.2,173.2,183.2,176.1,183.2),e.bezierVertex(176.2M 99,183.2,176.5,183.2,176.7,183.2),e.bezierVertex(180.1,182.899,182.6,180.299,182.7,177),e.bezierVertex(183.1,162,178.299,148.2,168.399,136.1),e.bezierVertex(158.2,123.5,144.899,115.8,128.799,113.199),e.bezierVertex(123.499,112.299,120.399,109.799,118.899,104.99),e.bezierVertex(113.899,89.699,120.699,72.299,134.899,64.499),e.bezierVertex(139.99,61.699,145.799,60.199,151.7,60.199),e.bezierVertex(162.2,60.199,171.899,64.799,178.1,72.699),e.bezierVertex(179.6,74.6,180.799,76.6,181.9,78.499),e.vertex(182.2,79.099),e.bezM ierVertex(183.2,80.699,185.2,83.299,188.4,83.299),e.bezierVertex(189.5,83.299,190.6,82.99,191.7,82.399),e.bezierVertex(195.1,80.599,196,76.99,194,72.799),e.bezierVertex(190.1,64.799,184.1,58.499,175.6,53.299),e.bezierVertex(174.6,52.699,173.7,52.099,172.5,51.499),e.vertex(170.5,50.299),e.vertex(163,45.899),e.vertex(170.5,41.599),e.bezierVertex(182,34.99,193.1,30.799,204.4,28.599),e.bezierVertex(208.6,27.799,212.9,27.399,217.2,27.399),e.bezierVertex(217.6,27.399,217.9,27.399,218.3,27.399),e.bezierVertex(231.4,27.599M ,242.7,38.199,243,50.599),e.bezierVertex(243.4,64.899,243.3,78.99,243.2,93.799),e.bezierVertex(243.2,99.799,243.1,105.899,243.1,112.099),e.vertex(243.1,119.199),e.vertex(236.4,116.799),e.bezierVertex(235.7,116.499,235,116.299,234.4,115.99),e.bezierVertex(233.4,115.599,232.6,115.299,232,115.199),e.bezierVertex(230.6,114.899,229.2,114.599,227.8,114.299),e.bezierVertex(223.8,113.499,220.1,112.699,216.4,112.499),e.vertex(216.2,112.499),e.bezierVertex(212.5,112.499,210.7,115.599,210.6,118.599),e.bezierVertex(210.4,122.3M 99,212.7,125.099,216.4,125.399),e.bezierVertex(230.1,126.399,238.9,133.099,242.3,145.199),e.bezierVertex(243.2,148.399,243.2,151.599,243.2,154.499),e.vertex(243.2,155.099),e.bezierVertex(243.2,254.199,243.2,330,243.2,400.599),e.bezierVertex(243.2,401.99,243.2,403.4,243.2,404.9),e.bezierVertex(243.3,411.099,243.3,417.599,242.3,423.9),e.bezierVertex(238.1,449.2,219.6,467.799,194,472.5),e.bezierVertex(190.9,472.9,187.6,473.2,184.3,473.2),e.endShape(),e.beginShape(),e.vertex(315.8,473.1),e.bezierVertex(309.3,473.1,302.M 8,472,296.5,469.9),e.bezierVertex(270.4,461,253.8,434.9,257.1,407.9),e.bezierVertex(260,384,273.8,366.8,297,358.3),e.bezierVertex(297.7,358.1,298.3,357.8,299,357.6),e.bezierVertex(299.8,357.3,300.6,357.1,301.2,356.8),e.bezierVertex(304.3,355.4,306,351.8,304.9,348.7),e.bezierVertex(304,345.9,301.7,344.2,299,344.2),e.bezierVertex(298.6,344.2,298.1,344.2,297.6,344.3),e.bezierVertex(288.1,346.3,279,350.9,269.7,358.3),e.bezierVertex(268.9,358.9,268.1,359.6,267.2,360.4),e.vertex(265.5,361.8),e.vertex(258.5,367.6),e.verteM x(257.4,358.6),e.bezierVertex(257.3,358,257.3,357.5,257.2,357.1),e.bezierVertex(257,356,256.9,354.9,256.9,353.7),e.bezierVertex(256.9,334.8,256.9,316,256.9,297.1),e.bezierVertex(256.9,260.3,256.9,222.3,256.8,185),e.bezierVertex(256.8,170.7,268.3,158.8,282.5,158.4),e.bezierVertex(284.8,158.3,286.7,157.6,287.9,156.2),e.bezierVertex(289.099,154.9,289.599,153.2,289.5,151.3),e.bezierVertex(289.3,147.5,286.7,145.1,282.7,145.1),e.bezierVertex(282.5,145.1,282.2,145.1,282,145.1),e.bezierVertex(278.8,145.3,275.5,146.1,272,14M 6.9),e.bezierVertex(270.9,147.2,269.8,147.4,268.6,147.7),e.bezierVertex(267.9,147.9,267,148.2,265.8,148.7),e.bezierVertex(265.1,149,264.4,149.3,263.5,149.6),e.vertex(256.8,152),e.vertex(256.8,114.6),e.bezierVertex(256.8,95,256.8,75.4,256.8,55.9),e.bezierVertex(256.8,38,267.2,27.3,284.6,27.3),e.bezierVertex(285.3,27.3,285.9,27.3,286.6,27.3),e.bezierVertex(299,27.9,318.7,34.5,329.6,41.9),e.vertex(336.1,46.3),e.vertex(324.4,53.3),e.bezierVertex(316.2,58.2,310.2,64.6,306,72.9),e.bezierVertex(304.2,76.4,305.1,78.5,306.1M ,80),e.bezierVertex(307.4,81.9,309.4,83,311.6,83),e.bezierVertex(313.7,83,315.7,81.9,317.1,80.1),e.bezierVertex(317.4,79.7,317.8,79,318.1,78.4),e.bezierVertex(318.4,77.9,318.7,77.3,319,76.8),e.bezierVertex(325.3,66.2,336.3,59.9,348.5,59.9),e.bezierVertex(353.2,59.9,357.8,60.8,362.1,62.7),e.bezierVertex(377.6,69.3,386,86.7,381.7,103.2),e.bezierVertex(380.7,107.1,378.5,111.8,371.1,113.1),e.bezierVertex(342.7,118.1,322.2,139.1,317.8,167.8),e.bezierVertex(317.4,170.3,317.3,173.2,317.4,176.5),e.bezierVertex(317.5,180,32M 0.1,182.8,323.5,183),e.bezierVertex(323.6,183,323.8,183,323.9,183),e.bezierVertex(327.1,183,329.8,180.6,330.3,177.2),e.bezierVertex(330.6,175.7,330.7,174,330.9,172.3),e.bezierVertex(331.1,169.8,331.4,167.3,332,164.7),e.bezierVertex(337.3,141.9,357.7,125.4,380.7,125.4),e.bezierVertex(382.5,125.4,384.3,125.5,386.1,125.7),e.bezierVertex(412.8,128.9,432.6,150.9,432,176.9),e.bezierVertex(431.9,182.3,430.9,187.7,429.1,192.7),e.bezierVertex(427.2,197.9,428,201,432.3,205),e.bezierVertex(446.8,218.7,451.8,236,446.6,255),e.bM ezierVertex(441.4,274,428.3,286.5,408.7,291.3),e.bezierVertex(406.1,291.9,403.6,292.1,401.1,292.3),e.bezierVertex(400,292.4,398.9,292.5,397.9,292.6),e.bezierVertex(393.6,293.1,390.9,295.7,391,299.5),e.bezierVertex(391.1,303.4,394,305.8,398.5,305.8),e.bezierVertex(409.9,305.8,420.8,302.6,431.1,296.4),e.bezierVertex(431.8,296,432.5,295.5,433.2,295.1),e.bezierVertex(433.8,294.7,434.5,294.3,435.2,293.9),e.bezierVertex(436,293.4,436.6,293.2,437.2,293.1),e.bezierVertex(437.4,293,437.7,292.9,438.1,292.8),e.vertex(442.5,29M 1.4),e.vertex(444.2,295.7),e.bezierVertex(450.9,312.4,449.5,328.4,440,343.4),e.bezierVertex(435.3,350.8,428.7,356.7,420.2,361.1),e.bezierVertex(414.3,364.1,413.7,365.2,414.8,371.7),e.bezierVertex(419.5,400.2,403,427.6,375.6,436.9),e.bezierVertex(371,438.5,368.3,440.7,365.8,444.7),e.bezierVertex(355.2,462.5,336.4,473.1,315.8,473.1),e.bezierVertex(315.8,473.1,315.8,473.1,315.8,473.1),e.endShape(),ie(e),e.fill(n),e.beginShape(),e.vertex(120.2,279.9),e.bezierVertex(117.9,279.9,112.4,279.299,112.2,273.599),e.bezierVerteM x(112,267.7,117.4,266.7,119.7,266.599),e.bezierVertex(133.1,265.799,143.1,259.499,149.3,247.899),e.bezierVertex(149.6,247.299,150.1,246.399,150.3,245.399),e.bezierVertex(150.6,244.299,150.5,243.299,150.5,242.7),e.bezierVertex(150.5,242.6,150.5,242.5,150.5,242.299),e.vertex(150.3,238.799),e.vertex(141.1,235.99),e.bezierVertex(114.6,227.799,95.6,202.499,95.9,175.799),e.bezierVertex(95.9,173.99,96.4,168.199,102.2,168.199),e.bezierVertex(102.6,168.199,103,168.199,103.4,168.299),e.bezierVertex(104.8,168.499,108.2,168.89M 9,109.2,175.599),e.bezierVertex(109.3,176.599,109.5,177.599,109.6,178.499),e.bezierVertex(110.4,184.199,111.3,189.99,113.7,195.499),e.bezierVertex(121.9,213.99,139.5,225.499,159.7,225.499),e.bezierVertex(172.1,225.499,184.1,220.899,193.5,212.599),e.bezierVertex(194,212.199,194.4,211.799,194.8,211.399),e.bezierVertex(195.1,211.099,195.5,210.799,195.8,210.399),e.bezierVertex(197.4,208.99,199.2,208.2,200.9,208.2),e.bezierVertex(202.5,208.2,204,208.899,205.3,210.1),e.bezierVertex(208,212.9,207.9,216.9,205,219.9),e.beziM erVertex(196.5,228.6,186.3,234.3,174.7,236.8),e.bezierVertex(168.799,238.1,165.6,241,163.899,246.7),e.bezierVertex(158.3,265.9,139.9,279.7,120.2,279.9),e.vertex(120.2,279.9),e.endShape(),e.beginShape(),e.vertex(187.2,427.5),e.bezierVertex(183.799,427.5,181.299,425.3,180.799,422),e.bezierVertex(180.6,420.8,180.499,419.5,180.399,418.1),e.bezierVertex(180.299,417,180.2,415.8,180.099,414.7),e.bezierVertex(177.199,390.5,156.699,371.3,132.399,370.2),e.bezierVertex(131.99,370.2,131.499,370.2,131.099,370.2),e.bezierVertex(M 130.699,370.2,130.299,370.2,129.799,370.2),e.bezierVertex(125.99,369.9,123.199,367.2,123.099,363.6),e.bezierVertex(122.99,360.2,125.799,357.3,129.599,356.9),e.bezierVertex(130.499,356.8,131.499,356.8,132.599,356.7),e.bezierVertex(133.199,356.7,133.799,356.7,134.399,356.6),e.vertex(138.299,356.4),e.vertex(139.1,352.6),e.bezierVertex(139.5,350.7,139.799,348.9,140.2,347),e.bezierVertex(140.899,343.4,141.5,340,142.399,336.8),e.bezierVertex(150.099,310.7,174.399,292,201.399,291.3),e.vertex(201.599,291.3),e.bezierVertex(M 203.699,291.3,206.299,292,208.299,293.2),e.bezierVertex(210.499,294.5,210.699,297.5,209.99,299.8),e.bezierVertex(209.499,301.5,208.199,303.9,203.299,304.7),e.bezierVertex(202.199,304.9,200.99,305,199.799,305.2),e.bezierVertex(194.499,305.9,188.99,306.599,183.799,308.9),e.bezierVertex(165.499,316.799,155.199,331.299,152.99,352),e.bezierVertex(152.399,357.8,154.499,361.7,159.699,364.5),e.bezierVertex(178.199,374.4,189.399,390,193.099,410.9),e.bezierVertex(193.699,414.299,193.899,418,193.599,422),e.bezierVertex(193.39M 9,425.2,190.899,427.5,187.399,427.5),e.vertex(187.2,427.5),e.endShape(),e.beginShape(),e.vertex(364.3,281.1),e.bezierVertex(346.3,280.6,332.9,272.8,323.5,257),e.bezierVertex(321.6,253.9,320.4,250.2,319.2,246.7),e.bezierVertex(317.7,242.2,315,239.799,310.5,238.799),e.bezierVertex(298.5,236.299,288,230.7,279.4,222.1),e.bezierVertex(276.7,219.4,274.9,215.299,278,211.9),e.bezierVertex(279.4,210.3,281,209.6,282.6,209.6),e.bezierVertex(284.4,209.6,286.4,210.6,288.3,212.5),e.bezierVertex(297.8,221.8,310.4,226.9,323.9,226.M 9),e.bezierVertex(340.2,226.9,355.1,219.3,364.8,206.2),e.bezierVertex(371,197.8,374.2,188.5,374.5,178.5),e.vertex(374.5,177.9),e.bezierVertex(374.5,177,374.5,176.1,374.7,175.4),e.bezierVertex(375.3,171.8,377.9,169.5,381.3,169.5),e.bezierVertex(381.4,169.5,381.5,169.5,381.7,169.5),e.bezierVertex(385.4,169.7,388,172.4,388,176.1),e.bezierVertex(388.1,190.7,383.4,204,374.2,215.8),e.bezierVertex(365.8,226.5,354.7,233.9,341.2,237.9),e.bezierVertex(340,238.3,338.7,238.6,337.3,239.1),e.bezierVertex(335.9,239.6,335.1,240.4,M 334.7,240.9),e.bezierVertex(334.599,241,334.5,241.1,334.4,241.2),e.vertex(331.799,243.6),e.vertex(333.199,246.8),e.bezierVertex(338.199,258,346.799,264.9,358.699,267.3),e.bezierVertex(360.199,267.6,361.599,267.7,362.99,267.9),e.bezierVertex(363.599,268,364.299,268,364.899,268.1),e.bezierVertex(369.099,268.6,371.799,271.4,371.499,275),e.bezierVertex(371.199,278.6,368.299,281.2,364.399,281.2),e.vertex(364.3,281.1),e.endShape(),e.beginShape(),e.vertex(323.9,437),e.bezierVertex(323.7,437,323.5,437,323.299,437),e.bezierM Vertex(319.599,436.7,317.299,434.1,317.4,430.2),e.bezierVertex(317.9,406.099,328.299,388,349.5,375),e.bezierVertex(350.7,374.2,352,373.5,353.4,372.8),e.bezierVertex(354.099,372.4,354.7,372.1,355.299,371.7),e.vertex(357.499,370.5),e.vertex(357.799,368),e.bezierVertex(360.4,346.6,345.199,323.7,323.9,317),e.bezierVertex(319.099,315.5,314.099,314.9,309.299,314.4),e.vertex(308.199,314.299),e.bezierVertex(305.99,314.099,300.799,312.9,300.899,307.299),e.bezierVertex(300.99,303.499,303.899,300.9,308.099,300.9),e.vertex(308M .299,300.9),e.bezierVertex(327.099,301.299,343.099,308.7,355.699,322.9),e.bezierVertex(364.299,332.5,369.399,344.099,370.99,357.299),e.bezierVertex(371.099,358.4,371.299,359.4,371.499,360.499),e.bezierVertex(371.599,360.99,371.699,361.499,371.799,361.99),e.vertex(372.499,365.899),e.vertex(377.899,366.199),e.bezierVertex(378.799,366.299,379.699,366.299,380.599,366.399),e.bezierVertex(385.099,366.699,387.899,369.399,387.799,373.299),e.bezierVertex(387.699,377.099,384.99,379.599,380.799,379.799),e.bezierVertex(369.799M ,380.199,359.99,383.299,351.899,389.299),e.bezierVertex(338.799,398.799,331.699,411.699,330.699,427.499),e.vertex(330.699,428.299),e.bezierVertex(330.599,429.199,330.599,430.099,330.499,430.799),e.bezierVertex(330,434.7,327.5,437,323.9,437),e.endShape()}function T(e){return e[0].map(((t,n)=>e.map((e=>e[n]))))}function A(e){return e.map((e=>Array.isArray(e)?A(e):e))}function D(e,t){return floor(random(e,t))}function k(e){let t=0;for(const n of e)t+=n[1];let n=random(t),r=0;for(const t of e)if(r+=t[1],n<r)return t[0]M ;return null}function L(e){for(let t=1;t<e.length;++t){let n=D(0,t),r=e[t];e[t]=e[n],e[n]=r}}function P(e){return null==e||""===e}function O(e){return new Promise((t=>setTimeout(t,e)))}function F(e,t,n){let r=0;for(let i=1;i<=1e3;++i)for(let o=1;o<=1e3;++o)if(e*o%(t*i)==0){let e=1*i/o;abs(e-n)<abs(r-n)&&(r=e)}return r}function N(){let e=60*(new Date).getTimezoneOffset()*1e3;return new Date(Date.now()-e).toISOString().slice(0,-1)}function B(e,t,n){let r;if(push(),textSize(e),textWidth(t)<=n)r=t;else for(let e=0;e<t.M length;++e){const i=t.slice(0,e+1)+"...";if(textWidth(i)>n){r=i;break}}return pop(),r}function Y(e){var t=e%10,n=e%100;return 1==t&&11!=n?e+"st":2==t&&12!=n?e+"nd":3==t&&13!=n?e+"rd":e+"th"}class G{constructor(e,t,n){this.n=t,this.m=n,this.mat=[];let r=0;for(let t=0;t<this.n;++t){this.mat.push([]);for(let n=0;n<this.m;++n)this.mat[t].push(r<e.length?e[r]:0),r+=1}return this}copy(){return new G(this.mat.flat(),this.n,this.m)}}class H{static __linear=e=>e;static __relu=e=>Math.max(e,0);static __leaky_relu=e=>e>0?e:.2M *e;static __sigmoid=e=>1/(1+Math.exp(-e));static __tanh=e=>Math.tanh(e);static __apply_unary_op(e,t){const n=e.copy();for(let e=0;e<n.n;++e)for(let r=0;r<n.m;++r)n.mat[e][r]=t(n.mat[e][r]);return n}static linear=e=>H.__apply_unary_op(e,H.__linear);static relu=e=>H.__apply_unary_op(e,H.__relu);static leaky_relu=e=>H.__apply_unary_op(e,H.__leaky_relu);static sigmoid=e=>H.__apply_unary_op(e,H.__sigmoid);static tanh=e=>H.__apply_unary_op(e,H.__tanh);static __add=(e,t)=>e+t;static __mul=(e,t)=>e*t;static __apply_binary_M op=(e,t,n)=>{"object"!=typeof t&&(t=new G([t],1,1));const r=e.copy();for(let e=0;e<r.n;++e)for(let i=0;i<r.m;++i)r.mat[e][i]=n(r.mat[e][i],t.mat[e%t.n][i%t.m]);return r};static mul=(e,t)=>H.__apply_binary_op(e,t,H.__mul);static add=(e,t)=>H.__apply_binary_op(e,t,H.__add);static matMul(e,t){const n=new G([],e.n,t.m);for(let r=0;r<n.n;++r)for(let i=0;i<n.m;++i)for(let o=0;o<e.m;++o)n.mat[r][i]+=e.mat[r][o]*t.mat[o][i];return n}static softmax(e){const t=H.__apply_unary_op(e,(e=>Math.exp(e))),n=t.mat.flat().reduce(((e,M t)=>e+t));for(let r=0;r<e.n;++r)for(let i=0;i<e.m;++i)t.mat[r][i]/=n;return t}}class ${constructor(e,t){this.scale=e,this.offset=t}forward(e){return H.add(H.mul(e,this.scale),this.offset)}}class X{constructor(){}forward(e){return e.map((e=>e.flat()))}}class W{constructor(e,t,n,r){this.out_dim=e,this.activation=t,this.w=n,this.b=r}forward(e){const t=H.add(H.matMul(e,this.w),this.b);return null==this.activation?t:this.activation(t)}}class U{constructor(e,t,n){this.preprocessLayers=e,this.hiddenLayers=t,this.outputLayM er=n,this.totalNeurons=this.hiddenLayers.map((e=>e.out_dim)),this.currentOrders=[],this.currentIteration=null}updateNeurons(e,t){if(t!=this.currentIteration){this.currentOrders=[];for(let e=0;e<this.totalNeurons.length;++e){randomSeed(100*(t+1)+e);const n=[];for(let t=0;t<this.totalNeurons[e];++t)n.push(t);L(n),this.currentOrders.push(n)}this.currentIteration=t}const n=A(this.totalNeurons),r=n.reduce(((e,t)=>e+t))*(1-e);for(let e=0;e<r;++e){const t=n.map(((e,t)=>(e-1)/this.totalNeurons[t]));n[t.map(((e,t)=>[e,t])).M reduce(((e,t)=>t[0]>e[0]?t:e))[1]]-=Math.min(r-e,1)}this.neuronsLife=[];for(let e=0;e<n.length;++e){const t=this.currentOrders[e],r=Array(this.totalNeurons[e]).fill(0);for(let i=0;i<n[e];++i)r[t[i]]=Math.min(n[e]-i,1);this.neuronsLife.push(r)}}getTotalNeurons(){return A(this.totalNeurons)}getNeuronsLife(){return A(this.neuronsLife)}forward(e){for(const t of this.preprocessLayers)e=t.forward(e);for(const[t,n]of this.hiddenLayers.entries()){e=n.forward(e);const r=new G(this.neuronsLife[t],1,e.m);e=H.mul(e,r)}return eM =this.outputLayer.forward(e),H.softmax(e)}}function q(e){switch(e){case"relu":return H.relu;case"sigmoid":return H.sigmoid;case"tanh":return H.tanh;case"leaky_relu":return H.leaky_relu;default:return H.linear}}function j(e,t){const n=[],r=[],i=Z(t);let o=null,a=0,l=[];for(const t of e.config.layers)if("InputLayer"==t.class_name)o=t.config.batch_input_shape.slice(1),l=o;else if("Rescaling"==t.class_name)n.push(new $(t.config.scale,t.config.offset));else if("Flatten"==t.class_name)o=[o.reduce(((e,t)=>e*t))];else if("M Dense"==t.class_name){const e=[t.config.units],n=o[0]*e[0],l=e[0],s=i.subarray(a,a+n);a+=n;const h=i.subarray(a,a+l);a+=l;const c=new G(s,o[0],e[0]),u=new G(h,1,e[0]),f=q(t.config.activation);r.push(new W(e[0],f,c,u)),o=e}const s=r.pop();return{model:new U(n,r,s),inputDim:l}}function Z(e){const t=window.atob(e),n=t.length/Float32Array.BYTES_PER_ELEMENT,r=new DataView(new ArrayBuffer(Float32Array.BYTES_PER_ELEMENT)),i=new Float32Array(n);let o=0;for(let e=0;e<n;e++){o=4*e;for(let e=0;e<4;++e)r.setUint8(e,t.charCodeAM t(o+e));i[e]=r.getFloat32(0,!0)}return i}class K{constructor(e){this.elt=e,this._events={},this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight}position(){if(0===arguments.length)return{x:this.elt.offsetLeft,y:this.elt.offsetTop};var e="absolute";return"static"!==arguments[2]&&"fixed"!==arguments[2]&&"relative"!==arguments[2]&&"sticky"!==arguments[2]&&"initial"!==arguments[2]&&"inherit"!==arguments[2]||(e=arguments[2]),this.elt.style.position=e,this.elt.style.left=arguments[0]+"px",this.elt.style.top=aM rguments[1]+"px",this.x=arguments[0],this.y=arguments[1],this}show(){return this.elt.style.display="block",this}hide(){return this.elt.style.display="none",this}size(e,t){if(0===arguments.length)return{width:this.elt.offsetWidth,height:this.elt.offsetHeight};var n=e,r=t;if(n!==te||r!==te){if(n===te?n=t*this.width/this.height:r===te&&(r=e*this.height/this.width),this.elt instanceof HTMLCanvasElement){var i,o={},a=this.elt.getContext("2d");for(i in a)o[i]=a[i];for(i in this.elt.setAttribute("width",n*this._pInst._pixM elDensity),this.elt.setAttribute("height",r*this._pInst._pixelDensity),this.elt.style.width=n+"px",this.elt.style.height=r+"px",this._pInst.scale(this._pInst._pixelDensity,this._pInst._pixelDensity),o)this.elt.getContext("2d")[i]=o[i]}else this.elt.style.width=n+"px",this.elt.style.height=r+"px",this.elt.width=n,this.elt.height=r;this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight,this._pInst&&this._pInst._curElement&&this._pInst._curElement.elt===this.elt&&(this._pInst._setProperty("width",this.elt.oM ffsetWidth),this._pInst._setProperty("height",this.elt.offsetHeight))}return this}style(e,t){if(t instanceof Color&&(t="rgba("+t.levels[0]+","+t.levels[1]+","+t.levels[2]+","+t.levels[3]/255+")"),void 0===t){if(-1===e.indexOf(":"))return window.getComputedStyle(this.elt).getPropertyValue(e);for(var n=e.split(";"),r=0;r<n.length;r++){var i=n[r].split(":");i[0]&&i[1]&&(this.elt.style[i[0].trim()]=i[1].trim())}}else if(this.elt.style[e]=t,"width"===e||"height"===e||"left"===e||"top"===e){var o=window.getComputedStyle(M this.elt).getPropertyValue(e).replace(/[^\d.]/g,"");this[e]=Math.round(parseFloat(o,10))}return this}value(){return arguments.length>0?(this.elt.value=arguments[0],this):"range"===this.elt.type?parseFloat(this.elt.value):this.elt.value}mouseClicked(e){return this._adjustListener("click",e,this),this}isFocused(){return document.activeElement===this.elt}_adjustListener(e,t,n){return!1===t?this._detachListener(e,n):this._attachListener(e,t,n),this}_attachListener(e,t,n){n._events[e]&&this._detachListener(e,n);var r=t.M bind(n);n.elt.addEventListener(e,r,!1),n._events[e]=r}_detachListener(e,t){var n=t._events[e];t.elt.removeEventListener(e,n,!1),t._events[e]=null}}function J(e,t){var n=document.createElement("button");return n.innerHTML=e,t&&(n.value=t),ee(n)}function Q(e){var t=arguments.length>1&&void 0!==arguments[1]&&arguments[1],n=function(t){var n=!0,r=!1,i=void 0;try{for(var o,a=t.target.files[Symbol.iterator]();!(n=(o=a.next()).done);n=!0){var l=o.value;File._load(l,e)}}catch(e){r=!0,i=e}finally{try{n||null==a.return||a.reM turn()}finally{if(r)throw i}}};if(window.File&&window.FileReader&&window.FileList&&window.Blob){var r=document.createElement("input");return r.setAttribute("type","file"),t&&r.setAttribute("multiple",!0),r.addEventListener("change",n,!1),ee(r)}}function ee(e){return document.body.appendChild(e),new K(e)}createImg=function(){var e,t=document.createElement("img"),n=arguments;return n.length>1&&"string"==typeof n[1]&&(t.alt=n[1]),n.length>2&&"string"==typeof n[2]&&(t.crossOrigin=n[2]),t.src=n[0],e=ee(t,this),t.addEvenM tListener("load",(function(){e.width=t.offsetWidth||t.width,e.height=t.offsetHeight||t.height;var r=n[n.length-1];"function"==typeof r&&r(e)})),e},createInput=function(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:"",t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:"text",n=document.createElement("input");return n.setAttribute("value",e),n.setAttribute("type",t),ee(n,this)};const te="auto";function ne(e){re(e);const t=e._rectMode;e.rectMode(CORNER),e.rect(0,0,e.width,e.height),e.rectMode(t)M ,ie(e)}function re(e){e.push(),e.fill(255,255,255,255),e.blendMode(REMOVE)}function ie(e){e.blendMode(BLEND),e.pop()}File=function(e,t){this.file=e,this._pInst=t;var n=e.type.split("/");this.type=n[0],this.subtype=n[1],this.name=e.name,this.size=e.size,this.data=void 0},File._createLoader=function(e,t){var n=new FileReader;return n.onload=function(n){var r=new File(e);if("application/json"===r.file.type)r.data=JSON.parse(n.target.result);else if("text/xml"===r.file.type){var i=(new DOMParser).parseFromString(n.targM et.result,"text/xml");r.data=new XML(i.documentElement)}else r.data=n.target.result;t(r)},n},File._load=function(e,t){if(/^text\//.test(e.type)||"application/json"===e.type)File._createLoader(e,t).readAsText(e);else if(/^(video|audio)\//.test(e.type)){var n=new File(e);n.data=URL.createObjectURL(e),t(n)}else File._createLoader(e,t).readAsDataURL(e)},XML=function(e){if(e)this.DOM=e;else{var t=document.implementation.createDocument(null,"doc");this.DOM=t.createElement("root")}},document.addEventListener("DOMContentLoM aded",(function(){addEventListener("mousemove",(e=>{window.mouseX=e.pageX,window.mouseY=e.pageY}))})),new e("global");const oe="311";let ae,le,se,he,ce,ue,fe,de,xe,ge,pe,me,be,ye,we,ve,ze,Ve,_e,Me,Ee,Se,Re,Ie,Ce,Te,Ae,De,ke,Le,Pe,Oe,Fe,Ne,Be,Ye,Ge,He,$e,Xe,We,Ue,qe,je,Ze,Ke,Je,Qe,et,tt,nt,rt,it,ot,at,lt,st,ht,ct,ut,ft,dt,xt,gt,pt,mt,bt,yt,wt,vt,zt,Vt,_t,Mt,Et,St,Rt,It,Ct,Tt,At=!1,Dt=!1,kt=!0,Lt=!1,Pt=!1;const Ot=[" ","Growing","Stable","Decaying","Dead","Rebirth"];let Ft,Nt,Bt,Yt,Gt,Ht,$t,Xt,Wt,Ut,qt,jt,Zt,Kt,Jt,QtM ,en,tn,nn,rn,on,an,ln,sn,hn=0,cn=0,un=0,fn=!1,dn=!0,xn=!0,gn=null,pn=null,mn=null,bn=!1,yn=!1,wn=null,vn=null,zn=!1;async function setup(){let e=windowWidth,t=windowHeight;createCanvas(e,t),et=createGraphics(e,t),Xe=createGraphics(e,t),$e=createGraphics(e,t),We=createGraphics(e,t),Ue=createGraphics(e,t),qe=createGraphics(e,t),Qe=createGraphics(e,t),je=createGraphics(e,t),Ze=createGraphics(e,t),Ke=createGraphics(e,t),Je=createGraphics(e,t),tt=createGraphics(500,500),nt=createGraphics(500,500),rt=createGraphics(500,5M 00),_n(),Mn(),Sn(),await En(),Gn(),Rn(),bn=!0}function _n(){Et=parseInt(oe),randomSeed(Et),noiseSeed(Et)}function Mn(){Wt=Ir(p.training_traits),Cr(Wt)}async function En(){let e;Jt=r(),Qt=o(),[Xt,e]=await Promise.all([s(Jt),h(Qt)]),Ut=new V(Wt.visual,e.layers_config,e.weight_b64),Ut.updateAge(new Date),_n(),Wt.training=e.training_traits,Ht=e.model_name,$t=e.classes_name}function Sn(){le=min(width,height)/1024,ut=Rr.findIndex((e=>e[0]===Wt.visual.colorPalette)),ft=[["#ffffff","#231f20","#231f20"],["#231f20","#ffffff"M ,"#ffffff"],["#104da8","#ffffff","#ffffff"],["#722F1F","#FCE1B2","#FCE1B2"],["#e88120","#f9f2e5","#f9f2e5"],["#f6b941","#2E2E2E","#2E2E2E"],["#45daaa","#012221","#012221"],["#F1F1F1","#328DFE","#328DFE"],["#111822","#D3EB8D","#D3EB8D"],["#713FF9","#D6D5E6","#D6D5E6"],["#FBDA9D","#795106","#795106"],["#8f5b62","#ead0d0","#ead0d0"],["#eae4cb","#508cac","#508cac"],["#ffc6cc","#cc313d","#cc313d"],["#60A900","#E0FE00","#E0FE00"],["#507DBE","#D0D1D3","#D0D1D3"],["#305848","#E8F2EE","#E8F2EE"],["#2a2634","#5b6988","#cb78aM 2","#5b6988"],["#590e29","#fd5e53","#fd5e53","#ffe373"],["#0a141d","#57d4e4","#328195","#2A9ECF","#0ab6a8","#57d4e4"],["#3a2d28","#d5c2ac","#df6338","#3d9895","#d5c2ac"],["#030706","#77c4d9","#77c4d9","#77c4d9","#ffffff","#ffffff","#e72020","#e72020"],["#3a4664","#92f5ff","#f9ff94","#eaa0a2","#55dde0"],["#fbfaff","#f04bb1","#f04bb1","#fac373","#82cef0","#8b31ce"],["#000000","#ffffff","#ff0002","#f26522","#fdff00","#00ff03","#01fffe","#0000ff","#ff00ff"]];for(let e=0;e<ft.length;++e)for(let t=0;t<ft[e].length;++t)ftM [e][t]=cr(ft[e][t]);pt=[],ct=ft[ut][0],st=ft[ut][1]}function Rn(){gn=document.querySelector("#upload"),pn=document.querySelector("#inputUpload"),gn.addEventListener("dblclick",(()=>{if(!Lt&&!yn)if(In(Ie)&&cn==Ve-1)pn.click();else{if(4!=Pe&&5!=Pe&&(In(Ie)||cn!=Ve-1))return;fn=!0,dn=!0,Bt=0,un=0}})),pn.addEventListener("click",(()=>{pn.value=null,gn.style.display="block"})),pn.addEventListener("change",(()=>{const[e]=pn.files;e?(se=null,gn.style.display="none",Tn(URL.createObjectURL(e)),mn=e):gn.style.display="block"M }))}function In(e){for(let t=0;t<e.length;++t){let n=0;for(let r=0;r<e[t].length;++r)e[t][r]>0&&++n;if(0==n)return!1}return!0}function Cn(){null!=se&&(un=0,Pt=!0,he=0,ue=0,drewLineAnim=!0,ce=(ae/2+we/2)/le,loadImage(se.elt.src,(e=>{const[t,n,r]=Gt,i=createGraphics(t,n);i.image(e,0,0,t,n),i.loadPixels();const o=i.pixels.filter(((e,t)=>t%4!=3)),a=Ut.classifyImage(o);Zt=T([a,$t.map((e=>e.toUpperCase()))]).sort(((e,t)=>e[0]>t[0]?-1:1))})))}function Tn(e){se=createImg(e,""),se.hide(),Cn()}function An(){zn||(ce+=(width-aM e-we)/tn/le),re(Xe),Xe.rect(ce*le,0,width,height),ie(Xe),un>=ge&&1==kt&&(kt=!1,un-=ge),kt&&(re($e),$e.strokeWeight(2*Fe),Jn(he,ze,ct,ct,$e),ie($e)),un>=ge&&0==kt&&(kt=!0,un-=ge,he+=1,he==en&&(++ue,he=0,ce=(ae/2+we/2)/le,1==ue&&(Pt=!1,Dn(),ye=millis())))}function Dn(){At=!0,pe=!1,me=!1,tryButton=br("Try Again",width/2-225*le,height/2+265*le,290*le,40*le,kn),closeResultButton=br("Close",width/2+75*le,height/2+265*le,150*le,40*le,Ln)}function kn(){At=!1,tryButton.hide(),closeResultButton.hide(),pn.click()}function Ln(M ){Yt=!0,At=!1,Gn(),tryButton.hide(),closeResultButton.hide(),gn.style.display="block",se=null}function keyTyped(){bn&&!1===yn&&!1===yr()&&("i"!==key&&"I"!==key||(Dt=!Dt),"b"!==key&&"B"!==key||(xn=!xn),"s"!==key&&"S"!==key||!1!==Lt||saveCanvasAtCurrentTime(),"k"!==key&&"K"!==key||!1!==Lt||save4KCanvasAtCurrentTime(),"u"!==key&&"U"!==key||!1!==Lt||!1!==At||!1!==fn||!1!==Pt||On())}function On(){Lt=!0,wn=null,vn=null,submitButton=br("Submit",width/2-155*le,height/2+115*le,150*le,40*le,Fn),closeSettingButton=br("Close",M width/2+5*le,height/2+115*le,150*le,40*le,Yn),vt=createInput(),vt.position(width/2-252.5*le,height/2-40*le),vt.size(500*le,25*le),vt.style("font-size","15px"),vt.value(Jt||""),zt=createInput(),zt.position(width/2-252.2*le,height/2+35*le),zt.size(500*le,25*le),zt.style("font-size","15px"),zt.value(Qt||"")}function Fn(){Vt=vt.value(),_t=zt.value(),submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide(),Lt=!1,yn=!0,Nn()}async function Nn(){[wn,vn,_]=await Promise.all([c(Vt),u(_t),O(1e3)]),yn=!1,wn&&vn?(n(Vt)M ,i(_t),window.location.reload()):(Lt=!0,submitButton.show(),closeSettingButton.show(),vt.show(),zt.show())}function Bn(){Je.textFont("Trebuchet MS"),Je.noStroke(),pr(Je,600*le,200*le),Je.strokeWeight(1*le),Je.stroke(xt),Je.fill(xt),Je.textSize(50*le),Je.text("update()",width/2,height/2+2.5*le)}function Yn(){wn=null,vn=null,Lt=!1,submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide()}function Gn(){_n(),nn=Date.now(),pe=!1,me=!1,St=Wt.training.structure_gen,Rt=Wt.visual.birthYear,It=Wt.visual.lifeCycle,Ct=M Wt.training.epoch_num,Tt=Wt.training.activation_func,Ft=Mr.findIndex((e=>e[0]==Wt.visual.hardwareAcceleration))+1,1==Ft?(Nt=30,fe=40):2==Ft?(Nt=15,fe=20):(Nt=2,fe=10);const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),wiM ndow.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),ae=100*le,ht=50*le,Oe=Sr.findIndex((e=>e[0]==Wt.visual.nodeShape))+1,dt=Er.findIndex((e=>e[0]==Wt.visual.nodeFill))+1,lt=_r.findIndex((e=>e[0]==Wt.visual.pattern))+1,de=Math.tanh(Math.log10(Xt.avgfeerate)),de=map(de,0,1,.2,.8),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.lengM th;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=M [];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(BeM ,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,at=.7,pt=[],xt=ft[ut][2],gt=ft[ut][ft[ut].length-1];for(let e=3;e<ft[ut].length-1;e++)pt.push(ft[ut][e]);mt=sr(xt,gt,pt,width),bt=[],wt=[],yt=width/(Ve-1);for(let e=0;e<Ve;e++)bt.push(hr(mt,yt*e/width)),wt.push(hr(mt,yt*e/width));wt.unshift(bt[0]),wt.push(bt[bt.length-1]),hn=0,cn=0,un=0,Yt=!0;const n={xLeft:ae/8,xRight:width-ae/8,yTop:ae/8,yBottom:height-ae/8},r=Ce.map((e=>e.length));jt=new R(bt,r,n,Oe,le)}function Hn(e,t){let n=Ce[e].length;return[e*we+we/2+ae/2,height/2-(M n-1)/2*ve+t*ve]}function $n(e,t){le=min(e,t)/1024,ae=100*le,ht=50*le,we=(e-ae)/Ve,ve=(t-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}xe=floor(De.length*de),Le=[],ke=[],ge=floor(map(de,.2,.8,15,2));for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,mt=sr(xt,gt,pt,e),bt=[],wtM =[],yt=e/(Ve-1);for(let t=0;t<Ve;t++)bt.push(hr(mt,yt*t/e)),wt.push(hr(mt,yt*t/e));wt.unshift(bt[0]),wt.push(bt[bt.length-1])}function Xn(){const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,windoM w.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-M t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,rM ])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le}function Wn(){jt.update();const e=4==Pe?0:Kt;jt.draw(Qe,ct,dt,e,le)}function Un(){if(!bn)return ar(),void et.image(je,0,0);if(4==Pe||5==Pe)return Wn(),void et.image(Qe,0,0);un>=Nt&&hn<Ve&&(hn++,un=0);for(let e=0;M e<hn;e++)1==dt?it=ot=bt[e]:(it=ct,ot=bt[e]),Kn(e,it,ot,$e);un>=Nt&&cn<Ve-1&&(cn++,un=0);for(let e=0;e<cn;e++)Zn(e)}function qn(){et.background(ct),Ue.background(255),Ue.rectMode(CENTER),ne(Ue),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),Ue.stroke(st),Ue.strokeWeight(8*le),Ue.fill(ct),Qe.background(255),Qe.rectMode(CENTER),ne(Qe),Qe.strokeWeight(le),qe.background(255),qe.rectMode(CENTER),ne(qe),qe.textAlign(LEFT),$e.background(255),$e.rectMode(CENTER),ne($e),Xe.background(255),ne(Xe),Xe.strokeWeight(Ne),We.backgrM ound(255),We.rectMode(CENTER),ne(We),We.fill(st),We.stroke(st),We.strokeWeight(.1*le),er(lt),We.noStroke(),xn&&(We.rect(ae/16,height/2,ae/8,height),We.rect(width-ae/16,height/2,ae/8,height),We.rect(width/2,ae/16,width,ae/8),We.rect(width/2,height-ae/16,width,ae/8)),Ze.background(255),Ze.rectMode(CENTER),ne(Ze),Ze.textAlign(CENTER,CENTER),Ze.textStyle(BOLD),Ze.stroke(st),Ze.strokeWeight(8*le),Ze.fill(ct),je.background(255),je.rectMode(CENTER),ne(je),je.textAlign(CENTER,CENTER),je.textStyle(BOLD),Ke.background(255),KM e.rectMode(CENTER),ne(Ke),Ke.textAlign(CENTER,CENTER),Ke.textStyle(BOLD),Ke.stroke(st),Ke.strokeWeight(8*le),Ke.fill(ct),Je.background(255),Je.rectMode(CENTER),ne(Je),Je.textAlign(CENTER,CENTER),Je.textStyle(BOLD),Je.stroke(st),Je.strokeWeight(8*le),Je.fill(ct),Un(),et.image(We,0,0),Pt&&An(),et.image(Xe,0,0),et.image($e,0,0),At&&(tr(),et.image(Ue,0,0)),fn&&(lr(),et.image(Ze,0,0)),Lt&&(or(),et.image(Ke,0,0)),Dt&&(ir(),et.image(qe,0,0)),yn&&(Bn(),et.image(Je,0,0))}function draw(){const e=Date.now();bn&&(Ut.updateAge(M new Date(e)),Xn()),qn(),image(et,0,0),zn||un++}function Zn(e){let t,n=Ce[e].length,r=Ce[e+1].length;for(let i=0;i<n;i++){const[n,o]=Hn(e,i);for(let a=0;a<r;a++){const[r,l]=Hn(e+1,a);t=map(min(Ce[e][i],Ce[e+1][a]),0,1,0,.5),ur(n,o,r,l,bt[e],bt[e+1],Xe,t)}}}function Kn(e,t,n,r){let i,o,a,l=Ce[e].length;for(let s=0;s<l;s++){const[l,h]=Hn(e,s);i=Ce[e][s],a=map(Be,1/30,1,3,10),o=map(Ce[e][s],0,1,2*a,0)*le,o<1.5*le&&(o=0),Qn(l,h,ze,Oe,t,n,o,i,r)}}function Jn(e,t,n,r,i){for(let o=0;o<Le[e].length;o++)Qn(Le[e][o][0],Le[e][M o][1],t,Oe,n,r,0,1,i)}function Qn(e,t,n,r,i,o,a,l,s){s.stroke(dr(o,map(l,0,1,.25,1))),s.fill(dr(i,map(l,0,1,.15,1))),s.strokeWeight(Fe),fr([a],s),3==dt&&s.fill(dr(i,0)),1==r?s.ellipse(e,t,n):2==r?s.rect(e,t,7*n/8,7*n/8):3==r&&(s.beginShape(),s.vertex(e-4*n/7,t),s.vertex(e,t-4*n/7),s.vertex(e+4*n/7,t),s.vertex(e,t+4*n/7),s.endShape(CLOSE))}function er(e){if(1==e);else if(2==e){We.strokeWeight(1*le);for(let e=ht/4;e<width+ht/4;e+=ht)for(let t=ht/4;t<height+ht/4;t+=ht)We.point(e,t)}else if(3==e){ht=25*le;for(let e=ht/M 2;e<height+ht/2;e+=ht)We.line(0,e,width,e);for(let e=ht/2;e<width+ht/2;e+=ht)We.line(e,0,e,height)}}function tr(){Ue.textFont("Trebuchet MS"),Ue.textAlign(LEFT,CENTER),Ue.noStroke(),pr(Ue,800*le,500*le),Ue.noStroke(),Ue.fill(dr(st,.75)),Ue.rect(width/2,height/2-100*le,800*le,300*le,25*le,25*le,0,0),Ue.fill(st),Ue.rect(width/2-250*le,height/2-100*le,225*le,225*le),Ue.image(se.elt,width/2-357.5*le,height/2-207.5*le,215*le,215*le);let e=100*Zt[0][0];Ue.fill(ct),Ue.textSize(25*le),Ue.textStyle(NORMAL),1==me&&(e>=0&&e<2M 0?Ue.text("I have a feeling this image belongs to",width/2-100*le,height/2-170*le):e>=20&&e<40?Ue.text("I have a hunch this image belongs to",width/2-100*le,height/2-170*le):e>=40&&e<60?Ue.text("I think this image belongs to",width/2-100*le,height/2-170*le):e>=60&&e<80?Ue.text("I'm almost certain this image belongs to",width/2-100*le,height/2-170*le):Ue.text("I'm positive this image belongs to",width/2-100*le,height/2-170*le));let t=e.toFixed(2);"100.00"==t&&(t="100"),1==me&&Ue.text("I'm "+t+"% confident that I'm rM ight!",width/2-100*le,height/2-25*le),example=Zt.map((e=>e[1])),be=Ue.textWidth('"FIDENZAAAA"'),defaultPhrase=Ue.textWidth('"PERPENDICULAR INHABITATION"'),Ue.textStyle(BOLD);const n=me?example[0]:random(example);if(1===n.split(" ").length){let e=75*be/Ue.textWidth('"'+n+'"');e>75&&(e=75),Ue.textSize(e*le),Ue.text('"'+n+'"',width/2-100*le,height/2-90*le)}else nr(width/2-100*le,height/2-90*le,460*le,110*le,n,Ue);if(millis()-ye>1500&&(me=!0),C(tt,nt,st,ct,Pe,Mt),Ue.image(nt,width/2-370*le,height/2+70*le,80*le,80*le),3M ==Pe){let e;e=map(Mt,50,60,.25,1.3),I(rt,e),Ue.image(rt,width/2-370*le,height/2+70*le,80*le,80*le)}let r,i;Ue.image(tt,width/2-370*le,height/2+70*le,80*le,80*le),Ue.fill(xt),Ue.textSize(40*le),Ue.text("INTELLIGENCE INFO",width/2-275*le,height/2+115*le),Ue.textSize(18*le),Ue.textStyle(NORMAL),Ue.circle(width/2-360*le,height/2+180*le,7.5*le),1==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s growing and getting smarter by the day.`:2==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It it has reached peak performance.`:3==Pe&&(r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s decaying and losing its luster.`),i=2==Pe?"The Perceptron remains stable for some time before entering the decay phase.":`Wait until ${new Date(an).toLocaleString("en-US")} for your Perceptron to reach its peak performance.`,Ue.text(r,width/2-350*le,height/2+180*le),Ue.circle(width/2-360*le,height/2+210*le,7.5*le),Ue.text(i,width/2-350*le,height/2+210*le),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),gr(Ue,width/2-22M 5*le,width/2+65*le,height/2+265*le,height/2+305*le,"SELECT ANOTHER IMAGE"),gr(Ue,width/2+75*le,width/2+225*le,height/2+265*le,height/2+305*le,"CLOSE")}function nr(e,t,n,r,i,o){let a=i.split(" "),l=75*be/o.textWidth('"'+i+'"'),s=0,h=[],c=[],u=[],f="",d="";if(l>=50)l>75&&(l=75),o.textSize(l*le),o.text('"'+i+'"',e,t);else if(l<50){if(l=50*defaultPhrase/o.textWidth('"'+i+'"'),l>30){if(l>50&&(l=50),[f,d]=rr(l,n,s,h,c,a,f,d,Ue),0==c.length)return o.textSize(l*le),void o.text('"'+i+'"',e,t);for(s=0,h=[],c=[];o.textWidth(dM )>n/le;)l=l*n/le/o.textWidth(d),f="",d="",[f,d]=rr(l,n,s,h,c,a,f,d,Ue)}else{l=30,o.textSize(l);for(let e=0;e<a.length;e++)s+=o.textWidth(" "+a[e]),s<=n/le?h.push(a[e]):s>n/le&&s<=n/le*2?c.push(a[e]):u.push(a[e]);for(let e=1;e<h.length;e++)f=f+" "+h[e];if(f='"'+h[0]+f,0==u.length){for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+c[c.length-1]+'"'}else if(1==c.length)d="... "+u[u.length-1]+'"';else{for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+"... "+u[u.length-1]+'"'}}o.textSize(l*le);let r=1.25*(o.textDescent()+o.textM Ascent());o.text(f,e,t-r/2),o.text(d,e,t+r/2)}}function rr(e,t,n,r,i,o,a,l,s){s.textSize(e);for(let e=0;e<o.length;e++)(n+=s.textWidth(" "+o[e]))<=t/le?r.push(o[e]):i.push(o[e]);for(let e=1;e<r.length;e++)a=a+" "+r[e];if(a='"'+r[0]+a,0==i.length&&(a+='"',l=""),1==i.length)l=i[i.length-1]+'"';else{for(let e=0;e<i.length-1;e++)l=l+i[e]+" ";l=l+i[i.length-1]+'"'}return[a,l]}function ir(){const e=45*le;qe.textFont("Tahoma"),qe.stroke(st),qe.strokeWeight(2*le),qe.fill(ct),qe.rect(width/2,e/2+height-87.5*le,600*le,90*le)M ,qe.fill(st),qe.rect(width/2-150*le,e+height-170*le,300*le,30*le),qe.fill(ct),qe.rect(width/2+150*le,e+height-170*le,300*le,30*le),qe.noStroke(),qe.fill(ct),qe.textSize(15*le),qe.textStyle(BOLD),qe.text("PERCEPTRON INFORMATION",width/2-285*le,e+height-165*le),qe.fill(xt),qe.text("ARTWORK NAME:",width/2+10*le,e+height-165*le),qe.textAlign(RIGHT),qe.textStyle(ITALIC),qe.text("Perceptron #"+Et,width/2+285*le,e+height-165*le);const[t,n]=It.split(" ");let r;"60 Years"===It?r="1 Year":"60 Months"===It?r="1 Month":"60 WeeM ks"===It?r="1 Week":"60 Days"===It?r="1 Day":"12 Hours"===It&&(r="12 Minutes"),data=[["AI MODEL NAME:",B(12*le,Ht,140*le)],["SCALE:","1:"+Te],["NUMBER OF CLASSES:",$t.length],["BIRTH YEAR:",Rt],["NUMBER OF REBIRTHS:",sn.toString()],["AGE:",`${Math.ceil(Mt)} Perceptron Years`],["ONE PERCEPTRON YEAR:",`${r}`],["STATE:",Ot[Pe]],["ACTIVE NEURONS:",`${round(ln*rn)} / ${ln}`],["NEXT STATE TIME:",vr(new Date(on))]],qe.fill(xt);const i=data.length/2;for(let t=0;t<data.length;++t){const n=t<i,r=n?width/2-285*le:width/2+10*lM e,o=n?width/2-10*le:width/2+285*le,a=e+height-(135-t%i*15)*le;qe.textStyle(BOLD),qe.textAlign(LEFT),qe.textSize(12*le),qe.text(data[t][0],r,a),qe.textStyle(ITALIC),qe.textAlign(RIGHT),qe.textSize(12*le),qe.text(data[t][1],o,a)}}function or(){Ke.textFont("Trebuchet MS"),Ke.noStroke(),pr(Ke,600*le,200*le),gr(Ke,width/2-155*le,width/2-5*le,height/2+115*le,height/2+155*le,"UPDATE"),gr(Ke,width/2+5*le,width/2+155*le,height/2+115*le,height/2+155*le,"CLOSE"),Ke.textAlign(LEFT),Ke.fill(xt),Ke.text("UPDATE BITCOIN FULL NODEM ADDRESS",width/2-252.5*le,height/2-55*le),Ke.text("UPDATE MODEL ADDRESS",width/2-252.5*le,height/2+20*le),Ke.textAlign(RIGHT),Ke.textStyle(ITALIC),Ke.textSize(15*le),0==wn&&Ke.text("(*) Invalid Address",width/2+252.5*le,height/2-53*le),0==vn&&Ke.text("(*) Invalid Model",width/2+252.5*le,height/2+23*le)}function ar(){je.textFont("Trebuchet MS"),je.fill(st),je.textSize(50*le),je.stroke(st),je.strokeWeight(1*le),je.text("main()",width/2,height/2)}function lr(){un>=20&&1==dn&&(dn=!1,un=0),dn&&(Ze.textFont("Trebuchet MM S"),Ze.stroke(st),Ze.fill(ct),Ze.rect(width/2,height/2,600*le,150*le,25*le),Ze.fill(xt),Ze.textSize(75*le),Ze.noStroke(),1==Pe?Ze.text("GROWING",width/2,height/2+5*le):3==Pe?Ze.text("AGING",width/2,height/2+5*le):4==Pe?Ze.text("DEAD",width/2,height/2+5*le):5==Pe&&Ze.text("BIRTH",width/2,height/2+5*le)),un>=20&&0==dn&&(dn=!0,un=0,Bt++,3==Bt&&(fn=!1))}function sr(e,t,n,r){let i=[],o=r/(n.length+1),a=color(e),l=color(t);i.push(a);for(let e=0;e<n.length;e++){let t=color(n[e]);for(let e=1;e<=o;e++){let n=lerpColor(a,t,eM /o);i.push(n)}a=t}for(let e=1;e<o;e++){let t=lerpColor(a,l,e/o);i.push(t)}if(i.push(l),i.length>r)i.splice(r);else if(i.length<r){let e=i[i.length-1];for(;i.length<r;)i.push(e)}return i}function hr(e,t){let n=e.length,r=Math.floor(t*n);return r>=n&&(r=n-1),e[r]}function cr(e){e=e.replace("#","");var t=parseInt(e,16);return color(t>>16&255,t>>8&255,255&t)}function ur(e,t,n,r,i,o,a,l){var s=a.drawingContext.createLinearGradient(e,t,n,r);s.addColorStop(0,i),s.addColorStop(1,o),a.drawingContext.strokeStyle=s,a.drawingCM ontext.globalAlpha=l,a.line(e,t,n,r),a.drawingContext.globalAlpha=1}function fr(e,t){t.drawingContext.setLineDash(e)}function dr(e,t){let n=color(e),r=red(n),i=green(n),o=blue(n);return color(r,i,o,255*t)}function xr(e,t,n,r){return mouseX>e&&mouseX<t&&mouseY>n&&mouseY<r}function gr(e,t,n,r,i,o){e.strokeWeight(1*le),e.stroke(st);const[a,l]=xr(t,n,r,i)?[xt,ct]:[ct,xt];e.fill(a),e.push(),e.rectMode(CORNERS),e.rect(t,r,n,i,5*le),e.pop(),e.noStroke(),e.textSize(20*le),e.fill(l),e.text(o,(t+n)/2,(46*r+54*i)/100)}functioM n pr(e,t,n){e.fill(0,0,0,75),e.rect(width/2,height/2,width,height),e.stroke(st),e.fill(ct),e.rect(width/2,height/2,t,n,25*le)}function mr(e,t){resizeCanvas(e,t,!0),Xe.resizeCanvas(e,t,!0),$e.resizeCanvas(e,t,!0),We.resizeCanvas(e,t,!0),Ue.resizeCanvas(e,t,!0),qe.resizeCanvas(e,t,!0),Qe.resizeCanvas(e,t,!0),je.resizeCanvas(e,t,!0),Ze.resizeCanvas(e,t,!0),Ke.resizeCanvas(e,t,!0),Je.resizeCanvas(e,t,!0),et.resizeCanvas(e,t,!0)}function br(e,t,n,r,i,o){const a=J(e);return a.position(t,n),a.size(r,i),a.style("opacity","M 0"),a.mouseClicked(o),a}function yr(){return null!=vt&&vt?.isFocused()||null!=zt&&zt?.isFocused()}function wr(e,t,n,r){let i;if(e<=3){i=`Hey ${String.fromCodePoint(128075)}, I'm ${n}, ${t} years old. I can detect ${r.length} NFT collections: `;let e=0;for(let t=0;t<r.length;++t){const n=r[t];if(e+n.length>500){i+=", etc";break}t==r.length-1?i+=", and ":t>0&&(i+=", "),i+=n,e+=n.length}i+=". ",t<=5?i+="However, I am only a baby, so my recognition ability is not accurate. I'm in the state of Growing both looks and intM elligence.":t<=13?i+="I am now a child. My recognition ability is becoming better, but still not very accurate. I'm in the state of Growing both looks and intelligence.":t<=25?i+="I have grown up to be a teen. My recognition ability almost reaches the peak, but I will still mess up sometimes. I'm in the state of Growing both looks and intelligence.":t<=50?i+="I finally reach adulthood. My recognition is fully functional now. I'm in the Stable state, where I am the most intelligent with all neurons activated.":t<=60M &&(i+="I am now an old Perceptron, so my recognition ability is no longer the best. I'm in the Decaying state, meaning that my neurons are dying, and my intelligence is decreasing over time.")}else 4==e?i=`${n} is Dead. However, this is not the end to its story...`:5==e&&(i=`${n} is now in the Rebirth state, and is preparing to start a new life.`);return i}function vr(e){const t=e.getDate(),n=e.toLocaleString("en-US",{month:"long"}),r=e.getFullYear();let i=e.getHours().toString();1==i.length&&(i="0"+i);let o=e.getMM inutes().toString();return 1==o.length&&(o="0"+o),`${Y(t)} ${n} ${r} | ${i}:${o}`}saveCanvasAtCurrentTime=()=>{save(N())},save4KCanvasAtCurrentTime=()=>{const e=width,t=height,n=min(4096/min(e,t),1e4/max(e,t)),r=e*n,i=t*n;mr(r,i),zn=!0,$n(r,i),qn();let o="4K_"+N()+".png";saveCanvas(et,o),mr(e,t),$n(e,t),zn=!1};const zr=[["60 Years",3,365],["60 Months",40,30],["60 Weeks",37,7],["60 Days",20,1]],Vr=[["1943",1],["1951",1.5],["1957",2],["1969",2.5],["1970",3],["1980",3.5],["1982",4],["1986",4.5],["1988",5],["1997",5.5]M ,["1998",6],["2002",6.5],["2009",7],["2012",7.5],["2014",8],["2015",8.5],["2016",9],["2023",15]],_r=[["Plain",20],["Dotted",40],["Squared",40]],Mr=[["Basic",30],["Standard",60],["Advanced",10]],Er=[["MNIST",70],["CIFAR",25],["IMAGENET",5]],Sr=[["Theano",60],["Torch",30],["TensorFlow",10]],Rr=[["Whitepaper",2],["Blackboard",2],["Blueprint",2],["Nak",74/14],["Jims",74/14],["Level 10",74/14],["Flips",74/14],["Level 14",74/14],["III",74/14],["XMB",74/14],["Info",74/14],["Adventure",74/14],["Marigold",74/14],["Phoenix",M 74/14],["Love",74/14],["Cachet",74/14],["Human",74/14],["Twilight",3],["Sunset",3],["Aurora",3],["Liminal Space",3],["D Vu",3],["Lucid Dream",3],["Parallel",1],["Multiverse",1]];function Ir(e){for(let e=0;e<100;++e)random(1);return{visual:{pattern:k(_r),hardwareAcceleration:k(Mr),nodeFill:k(Er),nodeShape:k(Sr),colorPalette:k(Rr),lifeCycle:k(zr),birthYear:k(Vr)},training:e}}function Cr(e){window.$generativeTraits={"Network Architecture":e.training.structure_gen,"Hidden Layers":e.training.n_layers,"Max Neurons PM er Hidden Layer":e.training.max_nodes,"Activation Function":e.training.activation_func,"Training Epochs":e.training.epoch_num,Dataset:e.visual.nodeFill,"Deep Learning Framework":e.visual.nodeShape,"Hardware Acceleration":e.visual.hardwareAcceleration,"Paper Pattern":e.visual.pattern,"Life Cycle":e.visual.lifeCycle,"Birth Year":e.visual.birthYear,"Color Palette":e.visual.colorPalette}} <script defer src="https://static.cloudflareinsights.com/beacon.min.js/v2b4487d741ca48dcbadcaf954e159fc6168079995099M 6" integrity="sha512-D/jdE0CypeVxFadTejKGTzmwyV10c1pxZk/AqjJuZbaJwGMyNHY3q/mTPWqMUnFACfCTunhZUVcd4cV78dK1pQ==" data-cf-beacon='{"rayId":"7b4840f5c9ce5419","version":"2023.3.0","b":1,"token":"6c07c178c94442f695e7a0a2aaee641a","si":100}' crossorigin="anonymous"></script> text/html;charset=utf-8 <meta charset="utf-8" /> position: relative; width: var(--width); height: var(--height); border: 1px solid blue; position: relative; <div id="upload"> <input id="inputUpload" type="file"> function e(e){"use strict";return new function e(t){let n="global"==t?window:this;n.canvas=document.createElement("canvas");let r=n.canvas.getContext("2d");n.width=100,n.height=100,n.canvas.width=n.width,n.canvas.height=n.height,"offscreen"!=t&&(document.body?document.body.appendChild(n.canvas):window.addEventListener("load",(function(){document.body.appendChild(n.canvas)}))),g(),n.MAGIC=161533525,n.RGB=0,n.HSV=1,n.HM SB=1,n.CHORD=0,n.PIE=1,n.OPEN=2,n.RADIUS=1,n.CORNER=2,n.CORNERS=3,n.ROUND="round",n.SQUARE="butt",n.PROJECT="square",n.MITER="miter",n.BEVEL="bevel",n.CLOSE=1,n.BLEND="source-over",n.REMOVE="destination-out",n.ADD="lighter",n.DARKEST="darken",n.LIGHTEST="lighten",n.DIFFERENCE="difference",n.SUBTRACT="subtract",n.EXCLUSION="exclusion",n.MULTIPLY="multiply",n.SCREEN="screen",n.REPLACE="copy",n.OVERLAY="overlay",n.HARD_LIGHT="hard-light",n.SOFT_LIGHT="soft-light",n.DODGE="color-dodge",n.BURN="color-burn",n.NORMAL="norM mal",n.ITALIC="italic",n.BOLD="bold",n.BOLDITALIC="italic bold",n.CENTER="center",n.LEFT="left",n.RIGHT="right",n.TOP="top",n.BOTTOM="bottom",n.BASELINE="alphabetic",n.LANDSCAPE="landscape",n.PORTRAIT="portrait",n.ALT=18,n.BACKSPACE=8,n.CONTROL=17,n.DELETE=46,n.DOWN_ARROW=40,n.ENTER=13,n.ESCAPE=27,n.LEFT_ARROW=37,n.OPTION=18,n.RETURN=13,n.RIGHT_ARROW=39,n.SHIFT=16,n.TAB=9,n.UP_ARROW=38,n.HALF_PI=Math.PI/2,n.PI=Math.PI,n.QUARTER_PI=Math.PI/4,n.TAU=2*Math.PI,n.TWO_PI=2*Math.PI,n.THRESHOLD=1,n.GRAY=2,n.OPAQUE=3,n.INVEM RT=4,n.POSTERIZE=5,n.DILATE=6,n.ERODE=7,n.BLUR=8,n.ARROW="default",n.CROSS="crosshair",n.HAND="pointer",n.MOVE="move",n.TEXT="text",n.VIDEO={video:!0,audio:!1},n.AUDIO={video:!1,audio:!0},n.SHR3=1,n.LCG=2,n.HARDWARE_FILTERS=!0,n.hint=function(e,t){n[e]=t},n.frameCount=0,n.mouseX=0,n.mouseY=0,n.pmouseX=0,n.pmouseY=0,n.mouseButton=null,n.keyIsPressed=!1,n.mouseIsPressed=!1,n.key=null,n.keyCode=null,n.pixels=null,n.accelerationX=0,n.accelerationY=0,n.accelerationZ=0,n.rotationX=0,n.rotationY=0,n.rotationZ=0,n.relRotatM ionX=0,n.relRotationY=0,n.relRotationZ=0,n.pAccelerationX=0,n.pAccelerationY=0,n.pAccelerationZ=0,n.pRotationX=0,n.pRotationY=0,n.pRotationZ=0,n.pRelRotationX=0,n.pRelRotationY=0,n.pRelRotationZ=0,n.touches=[],n._styleCache=[{colorMode:n.RGB,noStroke:!1,noFill:!1,ellipseMode:n.CENTER,rectMode:n.CORNER,curveDetail:20,curveAlpha:0,textFont:"sans-serif",textSize:12,textLeading:12,textStyle:"normal"}],n._style=n._styleCache[n._styleCache.length-1],n._noLoop=!1,n._pixelDensity=1,n._frameRate=null,n._tint=null;let i=nullM ,o=!0,a=[],l=null,s=0,h={},c=0,u=null,f=null,d=null;Object.defineProperty(n,"deviceOrientation",{get:function(){return 90==Math.abs(window.orientation)?n.LANDSCAPE:n.PORTRAIT}}),Object.defineProperty(n,"windowWidth",{get:function(){return window.innerWidth}}),Object.defineProperty(n,"windowHeight",{get:function(){return window.innerHeight}}),Object.defineProperty(n,"drawingContext",{get:function(){return r}}),n.createCanvas=function(e,t){return n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t,g(),n.canvas},nM .resizeCanvas=function(e,t){n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t},n.createGraphics=n.createImage=function(t,n){let r=new e("offscreen");return r.createCanvas(t,n),r.noLoop(),r},n.pixelDensity=function(e){return null==e||(n._pixelDensity=e,n.canvas.width=Math.ceil(n.width*e),n.canvas.height=Math.ceil(n.height*e),n.canvas.style.width=n.width+"px",n.canvas.style.height=n.height+"px",r.scale(n._pixelDensity,n._pixelDensity),g()),n._pixelDensity},n.map=function(e,t,n,r,i,o){let a=r+1*(e-t)/(n-t)*(i-r)M ;return o?r<i?Math.min(Math.max(a,r),i):Math.min(Math.max(a,i),r):a},n.lerp=function(e,t,n){return e*(1-n)+t*n},n.constrain=function(e,t,n){return Math.min(Math.max(e,t),n)},n.dist=function(){return 4==arguments.length?Math.hypot(arguments[0]-arguments[2],arguments[1]-arguments[3]):Math.hypot(arguments[0]-arguments[3],arguments[1]-arguments[4],arguments[2]-arguments[5])},n.norm=function(e,t,r){return n.map(e,t,r,0,1)},n.sq=function(e){return e*e},n.fract=function(e){return e-Math.floor(e)},n.degrees=function(e){retM urn 180*e/Math.PI},n.radians=function(e){return e*Math.PI/180},n.abs=Math.abs,n.ceil=Math.ceil,n.exp=Math.exp,n.floor=Math.floor,n.log=Math.log,n.mag=Math.hypot,n.max=Math.max,n.min=Math.min,n.round=Math.round,n.sqrt=Math.sqrt,n.sin=Math.sin,n.cos=Math.cos,n.tan=Math.tan,n.asin=Math.asin,n.acos=Math.acos,n.atan=Math.atan,n.atan2=Math.atan2,n.Vector=function(e,t,r){let i=this;i.x=e||0,i.y=t||0,i.z=r||0;let o=null,a=null;function l(e,t,n){return null!=e.x?e:null!=t?{x:e,y:t,z:n||0}:{x:e,y:e,z:e}}function s(){null==a&M &(a=i.x*i.x+i.y*i.y+i.z*i.z,o=Math.sqrt(a))}function h(){a=null,o=null}i.set=function(e,t,n){i.x=e||0,i.y=t||0,i.z=n||0},i.copy=function(){return new n.Vector(i.x,i.y,i.z)},i.add=function(){let e=l.apply(null,arguments);return i.x+=e.x,i.y+=e.y,i.z+=e.z,h(),i},i.rem=function(){let e=l.apply(null,arguments);return i.x%=e.x,i.y%=e.y,i.z%=e.z,h(),i},i.sub=function(){let e=l.apply(null,arguments);return i.x-=e.x,i.y-=e.y,i.z-=e.z,h(),i},i.mult=function(){let e=l.apply(null,arguments);return i.x*=e.x,i.y*=e.y,i.z*=e.z,hM (),i},i.div=function(){let e=l.apply(null,arguments);return i.x/=e.x,i.y/=e.y,i.z/=e.z,h(),i},i.mag=function(){return s(),o},i.magSq=function(){return s(),a},i.dot=function(){let e=l.apply(null,arguments);return i.x*e.x+i.y*e.y+i.z*e.z},i.dist=function(){let e=l.apply(null,arguments),t=i.x-e.x,n=i.y-e.y,r=i.z-e.z;return Math.sqrt(t*t+n*n+r*r)},i.cross=function(){let e=l.apply(null,arguments),t=i.y*e.z-i.z*e.y,n=i.z*e.x-i.x*e.z,r=i.x*e.y-i.y*e.x;return i.x=t,i.y=n,i.z=r,h(),i},i.normalize=function(){s();let e=o;retuM rn i.x/=e,i.y/=e,i.z/=e,o=1,a=1,i},i.limit=function(e){s();if(o>e){let t=e/o;i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e}return i},i.setMag=function(e){s();let t=e/o;return i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e,i},i.heading=function(){return Math.atan2(i.y,i.x)},i.rotate=function(e){let t=Math.cos(e),n=Math.sin(e),r=i.x*t-i.y*n,o=i.x*n+i.y*t;return i.x=r,i.y=o,i},i.angleBetween=function(){let e=l.apply(null,arguments);const t=i.dot(e)/(i.mag()*e.mag());let n;return n=Math.acos(Math.min(1,Math.max(-1,t))),n*Math.sign(i.cross(e).z||1)},M i.lerp=function(e,t){return i.x=i.x*(1-t)+e.x*t,i.y=i.y*(1-t)+e.y*t,i.z=i.z*(1-t)+e.z*t,h(),i},i.reflect=function(e){return e.normalize(),i.sub(e.mult(2*i.dot(e)))},i.array=function(){return[i.x,i.y,i.z]},i.equals=function(e,t){return null==t&&null==(t=Number.EPSILON)&&(t=0),Math.abs(e.x-i.x)<t&&Math.abs(e.y-i.y)<t&&Math.abs(e.z-i.z)<t},i.fromAngle=function(e,t){return null==t&&(t=1),o=t,a=t*t,i.x=t*Math.cos(e),i.y=t*Math.sin(e),i.z=0,i},i.fromAngles=function(e,t,n){null==n&&(n=1),o=n,a=n*n;const r=Math.cos(t),l=MaM th.sin(t),s=Math.cos(e),h=Math.sin(e);return i.x=n*h*l,i.y=-n*s,i.z=n*h*r,i},i.random2D=function(){return o=1,a=1,i.fromAngle(Math.random()*Math.PI*2)},i.random3D=function(){return o=1,a=1,i.fromAngles(Math.random()*Math.PI*2,Math.random()*Math.PI*2)},i.toString=function(){return`[${i.x}, ${i.y}, ${i.z}]`}},n.Vector.add=function(e,t){return new n.Vector(e.x+t.x,e.y+t.y,e.z+t.z)},n.Vector.rem=function(e,t){return new n.Vector(e.x%t.x,e.y%t.y,e.z%t.z)},n.Vector.sub=function(e,t){return new n.Vector(e.x-t.x,e.y-t.y,e.M z-t.z)},n.Vector.mult=function(e,t){return null==t.x?new n.Vector(e.x*t,e.y*t,e.z*t):new n.Vector(e.x*t.x,e.y*t.y,e.z*t.z)},n.Vector.div=function(e,t){return null==t.x?new n.Vector(e.x/t,e.y/t,e.z/t):new n.Vector(e.x/t.x,e.y/t.y,e.z/t.z)},n.Vector.dist=function(e,t){return Math.hypot(e.x-t.x,e.y-t.y,e.z-t.z)},n.Vector.cross=function(e,t){return new n.Vector(e.y*t.z-e.z*t.y,e.z*t.x-e.x*t.z,e.x*t.y-e.y*t.x)},n.Vector.lerp=function(e,t,r){return new n.Vector(e.x*(1-r)+t.x*r,e.y=e.y*(1-r)+t.y*r,e.z=e.z*(1-r)+t.z*r)},n.M Vector.equals=function(e,t,n){return e.equals(t,n)};for(let e of["fromAngle","fromAngles","random2D","random3D"])n.Vector[e]=function(t,r,i){return(new n.Vector)[e](t,r,i)};function x(e,t,n){let r,i,o,a,l,s,h,c,u;if(0==t)return[255*(r=n),255*(i=n),255*(o=n)];switch((a=e)>360&&(a=0),h=n*(1-t),c=n*(1-t*(s=(a/=60)-(l=~~a))),u=n*(1-t*(1-s)),l){case 0:r=n,i=u,o=h;break;case 1:r=c,i=n,o=h;break;case 2:r=h,i=n,o=u;break;case 3:r=h,i=c,o=n;break;case 4:r=u,i=h,o=n;break;default:r=n,i=h,o=c}return[255*r,255*i,255*o]}functioM n g(){r.fillStyle="white",r.strokeStyle="black",r.lineCap="round",r.lineJoin="miter"}function p(e){if(0<=e&&e<2*Math.PI)return e;for(;e<0;)e+=2*Math.PI;for(;e>=Math.PI;)e-=2*Math.PI;return e}function m(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;let c=p(a),u=p(l);r.beginPath();for(let a=0;a<h+1;a++){let l=a/h,s=n.lerp(c,u,l),f=Math.cos(s)*i/2,d=Math.sin(s)*o/2;r[a?"lineTo":"moveTo"](e+f,t+d)}s==n.CHORD?r.closePath():s==n.PIE&&(r.lineTo(e,t),r.closePath()),n._style.noFill||r.fill(),n._style.noStrokM e||r.stroke()}function b(e,t,i,o){n._style.noFill&&n._style.noStroke||(r.beginPath(),r.ellipse(e,t,i/2,o/2,0,0,2*Math.PI),n._style.noFill||r.fill(),n._style.noStroke||r.stroke())}function y(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;if(null==a)return function(e,t,i,o){n._style.noFill||r.fillRect(e,t,i,o),n._style.noStroke||r.strokeRect(e,t,i,o)}(e,t,i,o);if(null==l)return y(e,t,i,o,a,a,a,a);const c=Math.min(Math.abs(o),Math.abs(i))/2;a=Math.min(c,a),l=Math.min(c,l),h=Math.min(c,h),s=Math.min(c,s)M ,r.beginPath(),r.moveTo(e+a,t),r.arcTo(e+i,t,e+i,t+o,l),r.arcTo(e+i,t+o,e,t+o,s),r.arcTo(e,t+o,e,t,h),r.arcTo(e,t,e+i,t,a),r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke()}function w(){a=[]}n.createVector=function(e,t,r){return new n.Vector(e,t,r)},n.curvePoint=function(e,t,n,r,i){const o=i*i*i,a=i*i;return e*(-.5*o+a-.5*i)+t*(1.5*o-2.5*a+1)+n*(-1.5*o+2*a+.5*i)+r*(.5*o-.5*a)},n.bezierPoint=function(e,t,n,r,i){const o=1-i;return Math.pow(o,3)*e+3*Math.pow(o,2)*i*t+3*o*Math.pow(i,2)*n+Math.pow(i,M 3)*r},n.curveTangent=function(e,t,n,r,i){const o=i*i;return e*(-3*o/2+2*i-.5)+t*(9*o/2-5*i)+n*(-9*o/2+4*i+.5)+r*(3*o/2-i)},n.bezierTangent=function(e,t,n,r,i){const o=1-i;return 3*r*Math.pow(i,2)-3*n*Math.pow(i,2)+6*n*o*i-6*t*o*i+3*t*Math.pow(o,2)-3*e*Math.pow(o,2)},n.Color=function(e,t,n,r){let i=this;i.MAGIC=786698,i._r=e,i._g=t,i._b=n,i._a=r,i._h=0,i._s=0,i._v=0,i._hsvInferred=!1,i.setRed=function(e){i._r=e,i._hsvInferred=!1},i.setGreen=function(e){i._g=e,i._hsvInferred=!1},i.setBlue=function(e){i._b=e,i._hsvInfM erred=!1},i.setAlpha=function(e){i._a=e/255,i._hsvInferred=!1},i._inferHSV=function(){i._hsvInferred||([i._h,i._s,i._v]=function(e,t,n){let r,i,o,a,l;return r=e<t?e<n?e:n:t<n?t:n,0==(l=100*(i=e>t?e>n?e:n:t>n?t:n)/255)?[o=0,a=0,l]:0==(a=100*(i-r)/i)?[o=0,a,l]:(o=i==e?0+60*(t-n)/(i-r):i==t?120+60*(n-e)/(i-r):240+60*(e-t)/(i-r),[o,a,l])}(i._r,i._g,i._b),i._hsvInferred=!0)},i.toString=function(){return`rgba(${Math.round(i._r)},${Math.round(i._g)},${Math.round(i._b)},${~~(1e3*i._a)/1e3})`}},n.colorMode=function(e){n._stM yle.colorMode=e},n.color=function(){if(1==arguments.length&&786698==arguments[0].MAGIC)return arguments[0];if(n._style.colorMode==n.RGB){if(1==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],1);if(2==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],arguments[1]/255);if(3==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],1);if(4==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],arguments[3]/255)}else{if(1==argumeM nts.length)return new n.Color(...x(0,0,arguments[0]/100),1);if(2==arguments.length)return new n.Color(...x(0,0,arguments[0]/100),arguments[1]/255);if(3==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),1);if(4==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),arguments[3])}return null},n.red=function(e){return e._r},n.green=function(e){return e._g},n.blue=function(e){return e._b},n.alpha=function(e){return 255*e._a},n.hue=function(e){reM turn e._inferHSV(),e._h},n.saturation=function(e){return e._inferHSV(),e._s},n.brightness=function(e){return e._inferHSV(),e._v},n.lightness=function(e){return 100*(.2126*e._r+.7152*e._g+.0722*e._b)/255},n.lerpColor=function(e,t,r){return n._style.colorMode==n.RGB?new n.Color(n.constrain(n.lerp(e._r,t._r,r),0,255),n.constrain(n.lerp(e._g,t._g,r),0,255),n.constrain(n.lerp(e._b,t._b,r),0,255),n.constrain(n.lerp(e._a,t._a,r),0,1)):(e._inferHSV(),t._inferHSV(),new n.Color(n.constrain(function(e,t,r){var i=[[Math.abs(t-M e),n.map(r,0,1,e,t)],[Math.abs(t+360-e),n.map(r,0,1,e,t+360)],[Math.abs(t-360-e),n.map(r,0,1,e,t-360)]];return i.sort(((e,t)=>e[0]-t[0])),(i[0][1]+720)%360}(e._h,t._h,r),0,360),n.constrain(n.lerp(e._s,t._s,r),0,100),n.constrain(n.lerp(e._v,t._v,r),0,100),n.constrain(n.lerp(e._a,t._a,r),0,1)))},n.strokeWeight=function(e){n._style_noStroke=!1,r.lineWidth=e},n.stroke=function(){if(n._style.noStroke=!1,"string"==typeof arguments[0])return void(r.strokeStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._sM tyle.noStroke=!0:r.strokeStyle=e},n.noStroke=function(){n._style.noStroke=!0},n.fill=function(){if(n._style.noFill=!1,"string"==typeof arguments[0])return void(r.fillStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._style.noFill=!0:r.fillStyle=e},n.noFill=function(){n._style.noFill=!0},n.blendMode=function(e){r.globalCompositeOperation=e},n.strokeCap=function(e){r.lineCap=e},n.strokeJoin=function(e){r.lineJoin=e},n.ellipseMode=function(e){n._style.ellipseMode=e},n.rectMode=function(e){n._style.rectM Mode=e},n.curveDetail=function(e){n._style.curveDetail=e},n.curveAlpha=function(e){n._style.curveAlpha=e},n.curveTightness=function(e){n._style.curveAlpha=e},n.clear=function(){r.clearRect(0,0,n.width,n.height)},n.background=function(){if(arguments[0]&&arguments[0].MAGIC==n.MAGIC)return n.image(arguments[0],0,0,n.width,n.height);r.save(),r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity),r.fillStyle="string"==typeof arguments[0]?arguments[0]:n.color(...Array.from(arguments)),r.fillRect(0,0,n.width,n.heightM ),r.restore()},n.line=function(e,t,i,o){n._style.noStroke||(r.beginPath(),r.moveTo(e,t),r.lineTo(i,o),r.stroke())},n.arc=function(e,t,r,i,o,a,l,s){if(o==a)return n.ellipse(e,t,r,i);null==s&&(s=25),null==l&&(l=n.PIE),n._style.ellipseMode==n.CENTER?m(e,t,r,i,o,a,l,s):n._style.ellipseMode==n.RADIUS?m(e,t,2*r,2*i,o,a,l,s):n._style.ellipseMode==n.CORNER?m(e+r/2,t+i/2,r,i,o,a,l,s):n._style.ellipseMode==n.CORNERS&&m((e+r)/2,(t+i)/2,r-e,i-t,o,a,l,s)},n.ellipse=function(e,t,r,i){null==i&&(i=r),n._style.ellipseMode==n.CENTERM ?b(e,t,r,i):n._style.ellipseMode==n.RADIUS?b(e,t,2*r,2*i):n._style.ellipseMode==n.CORNER?b(e+r/2,t+i/2,r,i):n._style.ellipseMode==n.CORNERS&&b((e+r)/2,(t+i)/2,r-e,i-t)},n.circle=function(e,t,r){return n.ellipse(e,t,r,r)},n.point=function(e,t){e.x&&(t=e.y,e=e.x),r.beginPath(),r.ellipse(e,t,.4,.4,0,0,2*Math.PI),r.stroke()},n.rect=function(e,t,r,i,o,a,l,s){n._style.rectMode==n.CENTER?y(e-r/2,t-i/2,r,i,o,a,l,s):n._style.rectMode==n.RADIUS?y(e-r,t-i,2*r,2*i,o,a,l,s):n._style.rectMode==n.CORNER?y(e,t,r,i,o,a,l,s):n._stylM e.rectMode==n.CORNERS&&y(e,t,r-e,i-t,o,a,l,s)},n.square=function(e,t,r,i,o,a,l){return n.rect(e,t,r,r,i,o,a,l)},n.beginShape=function(){w(),r.beginPath(),o=!0},n.beginContour=function(){r.closePath(),w(),o=!0},n.endContour=function(){w(),o=!0},n.vertex=function(e,t){w(),o?r.moveTo(e,t):r.lineTo(e,t),o=!1},n.bezierVertex=function(e,t,n,i,o,a){w(),r.bezierCurveTo(e,t,n,i,o,a)},n.quadraticVertex=function(e,t,n,i){w(),r.quadraticCurveTo(e,t,n,i)},n.bezier=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.bezierVM ertex(r,i,o,a,l,s),n.endShape()},n.triangle=function(e,t,r,i,o,a){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.endShape(n.CLOSE)},n.quad=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.vertex(l,s),n.endShape(n.CLOSE)},n.endShape=function(e){w(),e&&r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke(),n._style.noFill&&n._style.noStroke&&(r.save(),r.fillStyle="none",r.fill(),r.restore())},n.curveVertex=function(e,t){if(a.push([e,t]),a.length<4)return;M let i=function(e,t,n,r,i,o,a,l,s,h){function c(e,t,n,r,i,o){let a=Math.pow(r-t,2)+Math.pow(i-n,2);return Math.pow(a,.5*o)+e}let u=[],f=c(0,e,t,n,r,h),d=c(f,n,r,i,o,h),x=c(d,i,o,a,l,h);for(let h=0;h<s;h++){let c=f+h/(s-1)*(d-f),g=[(f-c)/(f-0),(c-0)/(f-0),(d-c)/(d-f),(c-f)/(d-f),(x-c)/(x-d),(c-d)/(x-d),(d-c)/(d-0),(c-0)/(d-0),(x-c)/(x-f),(c-f)/(x-f)];for(let e=0;e<g.length;e+=2)isNaN(g[e])&&(g[e]=1,g[e+1]=0),isFinite(g[e])||(g[e]>0?(g[e]=1,g[e+1]=0):(g[e]=0,g[e+1]=1));let p=e*g[0]+n*g[1],m=t*g[0]+r*g[1],b=n*g[2]+i*g[M 3],y=r*g[2]+o*g[3],w=i*g[4]+a*g[5],v=o*g[4]+l*g[5],z=p*g[6]+b*g[7],V=m*g[6]+y*g[7],_=b*g[8]+w*g[9],M=y*g[8]+v*g[9],E=z*g[2]+_*g[3],S=V*g[2]+M*g[3];u.push([E,S])}return u}(...a[a.length-4],...a[a.length-3],...a[a.length-2],...a[a.length-1],n._style.curveDetail,n._style.curveAlpha);for(let e=0;e<i.length;e++)o?r.moveTo(...i[e]):r.lineTo(...i[e]),o=!1},n.curve=function(e,t,r,i,o,a,l,s){n.beginShape(),n.curveVertex(e,t),n.curveVertex(r,i),n.curveVertex(o,a),n.curveVertex(l,s),n.endShape()},n.translate=function(e,t){r.tM ranslate(e,t)},n.rotate=function(e){r.rotate(e)},n.scale=function(e,t){null==t&&(t=e),r.scale(e,t)},n.applyMatrix=function(e,t,n,i,o,a){r.transform(e,t,n,i,o,a)},n.shearX=function(e){r.transform(1,0,Math.tan(e),1,0,0)},n.shearY=function(e){r.transform(1,Math.tan(e),0,1,0,0)},n.resetMatrix=function(){r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity)},n.pushMatrix=n.push=function(){n._styleCache.push({...n._style}),n._style=n._styleCache[n._styleCache.length-1],r.save()},n.popMatrix=n.pop=function(){n._stylM eCache.length-1&&(n._styleCache.pop(),n._style=n._styleCache[n._styleCache.length-1],r.restore())},n.image=function(e,t,i,o,a,l,s,h,c){let u=e.MAGIC==n.MAGIC?e.canvas:e;function d(){if(e.MAGIC!=n.MAGIC||!n._tint)return;let t=e.canvas.getContext("2d");t.save(),t.resetTransform(),t.clearRect(0,0,t.canvas.width,t.canvas.height),t.drawImage(f.canvas,0,0),t.restore()}return e.MAGIC==n.MAGIC&&null!=n._tint&&(function(e,t){null==f&&(f=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvasM .height),f.canvas.width==e&&f.canvas.height==t||(f.canvas.width=e,f.canvas.height=t)}(e.canvas.width,e.canvas.height),f.drawImage(e.canvas,0,0),e.tinted(n._tint)),o?l?(h||(h=u.width),c||(c=u.height),r.drawImage(u,l,s,h,c,t,i,o,a),void d()):(r.drawImage(u,t,i,o,a),void d()):(e.MAGIC==n.MAGIC||e.width?r.drawImage(u,t,i,e.width,e.height):r.drawImage(u,t,i,e.videoWidth,e.videoHeight),void d())},n.loadPixels=function(){l=r.getImageData(0,0,n.canvas.width,n.canvas.height),n.pixels=l.data},n.updatePixels=function(){null!=M l&&r.putImageData(l,0,0)},n.loadImage=function(e,t){s++;let r=n.createGraphics(100,100),i=r.canvas.getContext("2d"),o=new Image;return o.src=e,o.crossOrigin="Anonymous",o.onload=function(){i.canvas.width=o.width,i.canvas.height=o.height,r.width=o.width,r.height=o.height,i.drawImage(o,0,0),s--,t&&t(r)},r};let v={};function z(e,t){null==u&&(u=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvas.height),u.canvas.width==e&&u.canvas.height==t||(u.canvas.width=e,u.canvas.height=t)}funcM tion V(){let e=r.canvas.width*r.canvas.height*4;null!=d&&e==d.length||(d=new Uint8ClampedArray(e))}function _(e){u.clearRect(0,0,u.canvas.width,u.canvas.height),u.filter=e,u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()}v[n.THRESHOLD]=function(e,t){null==t?t=127.5:t*=255;for(let n=0;n<e.length;n+=4){const r=.2126*e[n]+.7152*e[n+1]+.0722*e[n+2];e[n]=e[n+1]=e[n+2]=r>=t?255:0}},v[n.GRAY]=function(e){for(let t=0;t<e.length;t+=4)M {const n=.2126*e[t]+.7152*e[t+1]+.0722*e[t+2];e[t]=e[t+1]=e[t+2]=n}},v[n.OPAQUE]=function(e){for(let t=0;t<e.length;t+=4)e[t+3]=255},v[n.INVERT]=function(e){for(let t=0;t<e.length;t+=4)e[t]=255-e[t],e[t+1]=255-e[t+1],e[t+2]=255-e[t+2]},v[n.POSTERIZE]=function(e,t){let n=t-1;for(let r=0;r<e.length;r+=4)e[r]=255*(e[r]*t>>8)/n,e[r+1]=255*(e[r+1]*t>>8)/n,e[r+2]=255*(e[r+2]*t>>8)/n},v[n.DILATE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-M 1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.max(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.ERODE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.min(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.BLURM ]=function(e,t){t=t||1,t=Math.floor(t*n._pixelDensity),V(),d.set(e);let i=2*t+1,o=function(e){let n=new Float32Array(e),r=.3*t+.8,i=r*r*2;for(let t=0;t<e;t++){let o=t-e/2,a=Math.exp(-o*o/i)/(2.5066282746*r);n[t]=a}return n}(i),[a,l]=[r.canvas.width,r.canvas.height];for(let n=0;n<l;n++)for(let r=0;r<a;r++){let l=0,s=0,h=0,c=0;for(let e=0;e<i;e++){let i=4*(n*a+Math.min(Math.max(r-t+e,0),a-1));l+=d[i]*o[e],s+=d[i+1]*o[e],h+=d[i+2]*o[e],c+=d[i+3]*o[e]}let u=4*(n*a+r);e[u]=l,e[u+1]=s,e[u+2]=h,e[u+3]=c}d.set(e);for(let nM =0;n<l;n++)for(let r=0;r<a;r++){let s=0,h=0,c=0,u=0;for(let e=0;e<i;e++){let i=4*(Math.min(Math.max(n-t+e,0),l-1)*a+r);s+=d[i]*o[e],h+=d[i+1]*o[e],c+=d[i+2]*o[e],u+=d[i+3]*o[e]}let f=4*(n*a+r);e[f]=s,e[f+1]=h,e[f+2]=c,e[f+3]=u}},n.filter=function(e,t){if(n.HARDWARE_FILTERS&&null!=r.filter)if(z(),e==n.THRESHOLD){null==t&&(t=.5),t=Math.max(t,1e-5),_(`saturate(0%) brightness(${Math.floor(.5/t*100)}%) contrast(1000000%)`)}else if(e==n.GRAY)_("saturate(0%)");else if(e==n.OPAQUE)u.fillStyle="black",u.fillRect(0,0,u.canvaM s.width,u.canvas.height),u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.drawImage(u.canvas,0,0),r.restore();else if(e==n.INVERT)_("invert(100%)");else if(e==n.BLUR)_(`blur(${Math.ceil(t*n._pixelDensity/1)||1}px)`);else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}},n.resize=function(e,t){z(),u.drawImage(r.canvas,0,0),n.width=e,n.height=t,r.canvas.width=e*n._pixM elDensity,r.canvas.height=t*n._pixelDensity,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0,r.canvas.width,r.canvas.height),r.restore()},n.get=function(e,t,i,o){if(null!=e&&null==i){let i=r.getImageData(e,t,1,1).data;return new n.Color(i[0],i[1],i[2],i[3]/255)}e=e||0,t=t||0,i=i||n.width,o=o||n.height;let a=n.createGraphics(i,o);a.pixelDensity(n._pixelDensity);let l=r.getImageData(e*n._pixelDensity,t*n._pixelDensity,i*n._pixelDensity,o*n._pixelDensity);return a.caM nvas.getContext("2d").putImageData(l,0,0),a},n.set=function(e,t,i){if(i.MAGIC==n.MAGIC){let r=n._tint;return n._tint=null,n.image(i,e,t),void(n._tint=r)}let o=4*(t*n._pixelDensity*r.canvas.width+e*n._pixelDensity);n.pixels[o]=i._r,n.pixels[o+1]=i._g,n.pixels[o+2]=i._b,n.pixels[o+3]=255*i._a},n.tinted=function(){let e=n.color(...Array.from(arguments)),t=e._a;e._a=1,z(),u.clearRect(0,0,u.canvas.width,u.canvas.height),u.fillStyle=e,u.fillRect(0,0,u.canvas.width,u.canvas.height),u.globalCompositeOperation="multiply",u.M drawImage(r.canvas,0,0),u.globalCompositeOperation="source-over",r.save(),r.resetTransform();let i=r.globalCompositeOperation;r.globalCompositeOperation="source-in",r.drawImage(u.canvas,0,0),r.globalCompositeOperation=i,r.restore(),u.globalAlpha=t,u.clearRect(0,0,u.canvas.width,u.canvas.height),u.drawImage(r.canvas,0,0),u.globalAlpha=1,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()},n.tint=function(){n._tint=n.color(...Array.from(arguments))},n.noTiM nt=function(){n._tint=null},n.mask=function(e){r.save(),r.resetTransform();let t=r.globalCompositeOperation;r.globalCompositeOperation="destination-in",r.drawImage(e.canvas,0,0),r.globalCompositeOperation=t,r.restore()},n.clearTemporaryBuffers=function(){u=null,f=null,d=null},n.save=function(e,t){e=e||"untitled",t=t||"png";var n=document.createElement("a");n.innerHTML="[Download]",n.addEventListener("click",(function(){this.href=r.canvas.toDataURL(),this.download=e+"."+t}),!1),document.body.appendChild(n),n.click()M ,document.body.removeChild(n)},n.saveCanvas=function(e,t,r){if(e.MAGIC==n.MAGIC){r&&e.save(t,r);let n=t.split(".");return e.save(n.slice(0,-1).join("."),n[n.length-1])}if(t)return n.save(e,t);let i=e.split(".");return n.save(i.slice(0,-1).join("."),i[i.length-1])},n.loadFont=function(e){let t=e.split("/"),n=t[t.length-1].split(".")[0].replace(" ",""),r=`@font-face {\n font-family: '${n}';\n src: url('${e}');\n }`;const i=document.createElement("style");return i.textContent=r,document.head.append(M i),n},n.textFont=function(e){n._style.textFont=e},n.textSize=function(e){n._style.textSize=e,n._style.textLeading=e},n.textLeading=function(e){n._style.textLeading=e},n.textStyle=function(e){n._style.textStyle=e},n.textAlign=function(e,t){r.textAlign=e,t&&(r.textBaseline=t==n.CENTER?"middle":t)},n.text=function(e,t,i,o){if(!e)return;if(e=e.toString(),n._style.noFill&&n._style.noStroke)return;r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`;let a=e.split("\n");for(let e=0;e<a.length;e++)n._M style.noFill||r.fillText(a[e],t,i,o),n._style.noStroke||r.strokeText(a[e],t,i,o),i+=n._style.textLeading},n.textWidth=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).width},n.textAscent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBoundingBoxAscent},n.textDescent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBounM dingBoxDescent};var M,E=4,S=.5,R=function(e){return.5*(1-Math.cos(e*Math.PI))};n.noise=function(e,t,n){if(t=t||0,n=n||0,null==M){M=new Array(4096);for(var r=0;r<4096;r++)M[r]=Math.random()}e<0&&(e=-e),t<0&&(t=-t),n<0&&(n=-n);for(var i,o,a,l,s,h=Math.floor(e),c=Math.floor(t),u=Math.floor(n),f=e-h,d=t-c,x=n-u,g=0,p=.5,m=0;m<E;m++){var b=h+(c<<4)+(u<<8);i=R(f),o=R(d),a=M[4095&b],a+=i*(M[b+1&4095]-a),l=M[b+16&4095],a+=o*((l+=i*(M[b+16+1&4095]-l))-a),l=M[4095&(b+=256)],l+=i*(M[b+1&4095]-l),s=M[b+16&4095],l+=o*((s+=i*(M[M b+16+1&4095]-s))-l),g+=(a+=R(x)*(l-a))*p,p*=S,h<<=1,c<<=1,u<<=1,(f*=2)>=1&&(h++,f--),(d*=2)>=1&&(c++,d--),(x*=2)>=1&&(u++,x--)}return g},n.noiseDetail=function(e,t){e>0&&(E=e),t>0&&(S=t)};const I=function(){let e,t,n=4294967295;return{setSeed(r){e=t=(null==r?Math.random()*n:r)>>>0},getSeed:()=>t,rand:()=>(e^=e<<17,e^=e>>13,((e^=e<<5)>>>0)/n)}};let C=I();C.setSeed(),n.noiseSeed=function(e){let t=null==e?4294967295*Math.random():e;M||(M=new Float32Array(4096));for(var n=0;n<4096;n++)t^=t<<17,t^=t>>13,t^=t<<5,M[n]=(t>M >>0)/4294967295},n.randomSeed=function(e){C.setSeed(e)},n.random=function(e,t){return null==e?C.rand():"number"==typeof e?null!=t?C.rand()*(t-e)+e:C.rand()*e:e[~~(e.length*C.rand())]},n.randomGenerator=function(e){e==n.LCG?C=function(){const e=4294967296;let t,n;return{setSeed(r){n=t=(null==r?Math.random()*e:r)>>>0},getSeed:()=>t,rand:()=>(n=(1664525*n+1013904223)%e)/e}}():e==n.SHR3&&(C=I()),C.setSeed()};var T=new function(){var e,t,n,r=new Array(128),i=new Array(256),o=new Array(128),a=new Array(128),l=new Array(2M 56),s=new Array(256),h=function(){return 4294967296*C.rand()-2147483648},c=function(){return.5+2.328306e-10*(h()<<0)};this.SHR3=h,this.UNI=c,this.RNOR=function(){return n=h(),e=127&n,Math.abs(n)<r[e]?n*o[e]:function(){for(var t,i,l,s,u=3.44262;;){if(t=n*o[e],0==e){do{l=c(),s=c(),t=.2904764*-Math.log(l),i=-Math.log(s)}while(i+i<t*t);return n>0?u+t:-u-t}if(a[e]+c()*(a[e-1]-a[e])<Math.exp(-.5*t*t))return t;if(n=h(),e=127&n,Math.abs(n)<r[e])return n*o[e]}}()},this.REXP=function(){return(t=h()>>>0)<r[e=255&t]?t*l[e]:funM ction(){for(var n;;){if(0==e)return 7.69711-Math.log(c());if(n=t*l[e],s[e]+c()*(s[e-1]-s[e])<Math.exp(-n))return n;if((t=h())<i[e=255&t])return t*l[e]}}()},this.zigset=function(){var e,t,n=2147483648,h=4294967296,c=3.442619855899,u=c,f=.00991256303526217,d=7.697117470131487,x=d,g=.003949659822581572;for(e=f/Math.exp(-.5*c*c),r[0]=Math.floor(c/e*n),r[1]=0,o[0]=e/n,o[127]=c/n,a[0]=1,a[127]=Math.exp(-.5*c*c),t=126;t>=1;t--)c=Math.sqrt(-2*Math.log(f/c+Math.exp(-.5*c*c))),r[t+1]=Math.floor(c/u*n),u=c,a[t]=Math.exp(-.5*cM *c),o[t]=c/n;for(e=g/Math.exp(-d),i[0]=Math.floor(d/e*h),i[1]=0,l[0]=e/h,l[255]=d/h,s[0]=1,s[255]=Math.exp(-d),t=254;t>=1;t--)d=-Math.log(g/d+Math.exp(-d)),i[t+1]=Math.floor(d/x*h),x=d,s[t]=Math.exp(-d),l[t]=d/h}};T.hasInit=!1,n.randomGaussian=function(e,t){return T.hasInit||(T.zigset(),T.hasInit=!0),T.RNOR()*t+e},n.randomExponential=function(){return T.hasInit||(T.zigset(),T.hasInit=!0),T.REXP()},n.print=console.log,n.cursor=function(e,t,r){let i="";e.includes(".")&&(e=`url("${e}")`,i=", auto"),null!=t&&(e+=" "+t+M " "+r),n.canvas.style.cursor=e+i},n.noCursor=function(){n.canvas.style.cursor="none"},n.createCapture=function(e){var t=document.createElement("video");return t.playsinline="playsinline",t.autoplay="autoplay",navigator.mediaDevices.getUserMedia(e).then((function(e){t.srcObject=e})),t.style.position="absolute",t.style.opacity=1e-5,t.style.zIndex=-1e3,document.body.appendChild(t),t};let A=["setup","draw","preload","mouseMoved","mousePressed","mouseReleased","mouseDragged","mouseClicked","keyPressed","keyReleased","keM yTyped","touchStarted","touchEnded"];for(let e of A){let t="_"+e+"Fn";n[t]=function(){},n[t].isPlaceHolder=!0,n[e]?n[t]=n[e]:Object.defineProperty(n,e,{set:function(e){n[t]=e}})}function D(){n._noLoop||(i=null==n._frameRate?requestAnimationFrame(D):setTimeout(D,1e3/n._frameRate)),w(),o=!0,n.push(),n._drawFn(),n.pop(),++n.frameCount}function k(e){const t=n.canvas.getBoundingClientRect(),r=n.canvas.scrollWidth/n.width||1,i=n.canvas.scrollHeight/n.height||1;return{x:(e.clientX-t.left)/r,y:(e.clientY-t.top)/i,id:e.idenM tifier}}function L(){return n._touchStarted.isPlaceHolder&&n._touchMoved.isPlaceHolder&&n._touchEnded.isPlaceHolder}n.noLoop=function(){n._noLoop=!0,i=null},n.loop=function(){n._noLoop=!1,null==i&&D()},n.redraw=function(){D()},n.frameRate=function(e){n._frameRate=e},setTimeout((function(){n._preloadFn(),c=window.performance.now(),function e(){if(s>0)return setTimeout(e,10);n._setupFn(),D()}()}),1),n.canvas.onmousemove=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPM ressed?n._mouseDraggedFn(e):n._mouseMovedFn(e)},n.canvas.onmousedown=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!0,n.mouseButton=[n.LEFT,n.CENTER,n.RIGHT][e.button],n._mousePressedFn(e)},n.canvas.onmouseup=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!1,n._mouseReleasedFn(e)},n.canvas.onclick=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressedM =!0,n._mouseClickedFn(e),n.mouseIsPressed=!1},window.addEventListener("keydown",(function(e){n.keyIsPressed=!0,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!0,n._keyPressedFn(e),1==e.key.length&&n._keyTypedFn(e)})),window.addEventListener("keyup",(function(e){n.keyIsPressed=!1,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!1,n._keyReleasedFn(e)})),n.keyIsDown=function(e){return!!h[e]},n.canvas.ontouchstart=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.moM useY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mousePressedFn(e)||e.preventDefault()),n._touchStartedFn(e)||e.preventDefault()},n.canvas.ontouchmove=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mouseDraggedFn(e)||e.preventDefault()),n._touchMovedFn(e)||e.preventDefault()},n.canvas.ontouchend=n.canvas.ontouchcancel=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.M mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!1,n._mouseReleasedFn(e)||e.preventDefault()),n._touchEndedFn(e)||e.preventDefault()},n.hasSensorPermission=!window.DeviceOrientationEvent&&!window.DeviceMotionEvent||!(DeviceOrientationEvent.requestPermission||DeviceMotionEvent.requestPermission),n.requestSensorPermissions=function(){DeviceOrientationEvent.requestPermission&&DeviceOrientationEvent.requestPermission().then((e=>{"granted"==e&&DeviceMotionEvent.requestPermissioM n&&DeviceMotionEvent.requestPermission().then((e=>{"granted"==e&&(n.hasSensorPermission=!0)})).catch(alert)})).catch(alert)},window.ondeviceorientation=function(e){n.pRotationX=n.rotationX,n.pRotationY=n.rotationY,n.pRotationZ=n.rotationZ,n.pRelRotationX=n.relRotationX,n.pRelRotationY=n.relRotationY,n.pRelRotationZ=n.relRotationZ,n.rotationX=e.beta*(Math.PI/180),n.rotationY=e.gamma*(Math.PI/180),n.rotationZ=e.alpha*(Math.PI/180),n.relRotationX=[-n.rotationY,-n.rotationX,n.rotationY][1+~~(window.orientation/90)],n.rM elRotationY=[-n.rotationX,n.rotationY,n.rotationX][1+~~(window.orientation/90)],n.relRotationZ=n.rotationZ},window.ondevicemotion=function(e){if(n.pAccelerationX=n.accelerationX,n.pAccelerationY=n.accelerationY,n.pAccelerationZ=n.accelerationZ,!e.acceleration){let t=((e,t)=>[(e[0]*t[0]+e[1]*t[1]+e[2]*t[2]+e[3])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[4]*t[0]+e[5]*t[1]+e[6]*t[2]+e[7])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[8]*t[0]+e[9]*t[1]+e[10]*t[2]+e[11])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15])])(((e,t)M =>[e[0]*t[0]+e[1]*t[4]+e[2]*t[8]+e[3]*t[12],e[0]*t[1]+e[1]*t[5]+e[2]*t[9]+e[3]*t[13],e[0]*t[2]+e[1]*t[6]+e[2]*t[10]+e[3]*t[14],e[0]*t[3]+e[1]*t[7]+e[2]*t[11]+e[3]*t[15],e[4]*t[0]+e[5]*t[4]+e[6]*t[8]+e[7]*t[12],e[4]*t[1]+e[5]*t[5]+e[6]*t[9]+e[7]*t[13],e[4]*t[2]+e[5]*t[6]+e[6]*t[10]+e[7]*t[14],e[4]*t[3]+e[5]*t[7]+e[6]*t[11]+e[7]*t[15],e[8]*t[0]+e[9]*t[4]+e[10]*t[8]+e[11]*t[12],e[8]*t[1]+e[9]*t[5]+e[10]*t[9]+e[11]*t[13],e[8]*t[2]+e[9]*t[6]+e[10]*t[10]+e[11]*t[14],e[8]*t[3]+e[9]*t[7]+e[10]*t[11]+e[11]*t[15],e[12]*t[0]+M e[13]*t[4]+e[14]*t[8]+e[15]*t[12],e[12]*t[1]+e[13]*t[5]+e[14]*t[9]+e[15]*t[13],e[12]*t[2]+e[13]*t[6]+e[14]*t[10]+e[15]*t[14],e[12]*t[3]+e[13]*t[7]+e[14]*t[11]+e[15]*t[15]])((e=>[Math.cos(e),0,Math.sin(e),0,0,1,0,0,-Math.sin(e),0,Math.cos(e),0,0,0,0,1])(n.rotationY),(e=>[1,0,0,0,0,Math.cos(e),-Math.sin(e),0,0,Math.sin(e),Math.cos(e),0,0,0,0,1])(n.rotationX)),[0,0,-9.80665]);n.accelerationX=e.accelerationIncludingGravity.x+t[0],n.accelerationY=e.accelerationIncludingGravity.y+t[1],n.accelerationZ=e.accelerationIncludM ingGravity.z-t[2]}},n.year=function(){return(new Date).getFullYear()},n.day=function(){return(new Date).getDay()},n.hour=function(){return(new Date).getHours()},n.minute=function(){return(new Date).getMinutes()},n.second=function(){return(new Date).getSeconds()},n.millis=function(){return window.performance.now()-c}}(e)}"object"==typeof exports&&"undefined"!=typeof module&&(module.exports=e);const t="https://ancient-crimson-rain.btc.discover.quiknode.pro/c268fb026303ae8443f785200f2ea4b82f0082dd";function n(e){P(e)?M localStorage.removeItem("blocksApiEndpoint"):localStorage.blocksApiEndpoint=e}function r(){return localStorage.blocksApiEndpoint||t}function i(e){P(e)?localStorage.removeItem("modelInscriptionEndpoint"):localStorage.modelInscriptionEndpoint=e}function o(){return localStorage.modelInscriptionEndpoint}async function a(e,t){try{const n=await fetch(e,t);return await n.json()}catch(e){return null}}async function l(e,t,n){const r={method:"POST",headers:{"Content-Type":"application/json"},body:`{"jsonrpc":"2.0","id":1,"meM thod":"${t}","params":${`[${n.join(sep=",")}]`}}`};return(await a(e,r))?.result}async function s(e){const n={avgfee:10,time:Date.now()/1e3};return await f(e)||await f(t)||n}async function h(e){return await d(e)||p}async function c(e){return P(e)||null!=await f(e)}async function u(e){return P(e)||null!=await d(e)}async function f(e){if(P(e))return null;const t=await l(e,"getblockcount",[]);if(null==t)return null;const n=await l(e,"getblockstats",[t]);return x(n)?n:null}async function d(e){if(P(e))return null;const tM =await a(e,{});return g(t)?t:null}function x(e){return"number"==typeof e?.time&&"number"==typeof e?.avgfee}function g(e){if(null==e)return!1;const{classes_name:t,training_traits:n,layers_config:r,weight_b64:i}=e;if(!Array.isArray(t))return!1;if(null==n)return!1;try{j(r,i)}catch(e){return!1}return!0}const p={"model_name": "pfp_classifier_422", "layers_config": {"config": {"layers": [{"class_name": "InputLayer", "config": {"batch_input_shape": [null, 28, 28, 3]}}, {"class_name": "Rescaling", "config": {"scale": 0.007M 84313725490196, "offset": -1}}, {"class_name": "Flatten"}, {"class_name": "Dense", "config": {"units": 7, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 7, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 6, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 5, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 4, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 4, "activation": "relu"}}, {"class_name": "Dense", "config": {M "units": 4, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 3, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 3, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 3, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 4, "activation": "linear"}}]}}, "weight_b64": "QTQ3PfM6BT2QWTY8ZaNHPQfD0bzc1928REd+vP7g0Tw3aii9INapOlCUdTsMiAO8biu/PHJOlTyCvfY8dVksvYtLDT3YgAQ8jDw3vFGKQT02Rbw86jnIvOBMY7zGqTW9broUvQDRTLxo4Du9MtGBPBwBPrz1ug+9aoyPPMAlRbsATTQ8QGgwM 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 if48ikAHvYGoCD0lVQ89gLQZPG5mzDyVoxK9lKByPHBlqLxgcue8KHeOu/5xP714iB29j5s8PSNjnbyZ1wE9sNN0u5K/tDxBUMi84Nm1uxDoML26+xG9GBTEu8/2Pr3Nswq9lzRFPaQMKr2o9pG7MnvdPDPFGD333S29dCccvXiK5zveKJW8yyEePfRxLDwQmak70BKOO+ykcLwdGxE9gG/yOaizmTsw0bQ74G+ZO1akszwiVqe8o+emvACYhDlEjXQ8rVUhPSJQDr3a2r88Z6gAPSUXMz0fp009UJ9CPBjj+rww2Sy8FoG4vJRO+LzQORU8AB0Ous5PszyO8Im8T203vXRSdzw4Hxa9634+vWzzZzwTcya9jO2qvEo04zwecJ68jlo4vVvRnbygx3C8QNH4uiVRSj2CTpg8QE9Puqal3jwbJTU93EFdPHPx8rztYjw9cN0oO9ygHzxWaJo8/drwvDN7C71MvWE8Y0YnvXCR5zuJvT49+NUDPAac/Dzjy+K8PLoDM 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 NgI8c+EmPQKZujzybrU8gKsRu5DPGTtPHkI9UQcVPfFPET09wB+95WwXPcD82bpP1Q49gPxcuwBJcLnePdA8Gj7UvLPXJz2InKA7NdwOvT8HCz157Rc9ZHxIvPQyqLzKI708PgLyPFj7hTvPoUS9Ayu7vIJAqjwZ7ze99rQ9vVZj8Ly1IxM9ND58vDC8LTxxzvq879wcvRXjHj2boBy9StuKPFr+yTzKZvw8U2E/PRS1LDxsozo8+AnNO15gP70o9xs8vzkFPWz0cDwQgb67Kg4BvS5KzDzHDRM98I5ou6B0Hzys6ki8Im3YPJj8A70yTO08nrXePPzUJjwyuEu9P6krPasQOT0AuCw6jGJCvdz6Sbx1TCy9Jh7bPOZ5D722p5m8iQwTPeAfULtD9Ag9eLcNvNQ/a7zeMMs820q8vJylaDxKPYQ8btyQPHdUAj3w/Fk72m5GvZe/1LyrXks9ICvguoRvVzzUFz29b46pvCfOGr2NSkM94/whPfCngDtOaro8C6sYM PTqBrTxYTCg89zg7PUD5qbqjEK684uD4vDMCxLzw2Qu7ttTWvLUfHT3yKNs8gvQ2vWeoIz3phz09JsX9vFxACjxYuiY8RyksPb9jLj1MlDo8BDtnPJLdjDwV3QC9z4vXvO4kizx2NfE8gPoxvOWPOT0UrQI85IV2PHh18DtJJjo9pr8YvXtpHz0SCQS9+DjsuzBFGbwjbBM9q/koPTDJBrshmgE9sOYdva+QCz2D80k99n7/PJ3EHz0kLMm8TgLpPPCXA73VEEa9+p+LvL6IuTxBevi8hHLQvGttJT1QGue7sMEVu9vSJD0R+Tc92viPPLCB1Ts4uuO7t7cGPRy5ZDzcDAm9Kp6LvNJ69bxkVFQ8sOXKu5kQGz0CAag8+GwFvGg4+rsSGTS9aCinuwSZfbwgt9K6P4/BvC1N3LxUSpW8f9WivJWdRT1M/VE89PB5PPg2J7y4lNq7WHbrvHa0xDz+f0S9WRMkvYT7bzxJ6RA9fuIZvRQcK7z/Iho9Z0/UvKRTK7y3M 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 PBzVXbx0qU88CIkKvDD1NTzdMAI915MAPQ1NRb0kD1W8IKuIO6kmTD0wsgo8bpTMPMzwCL1k4Hg8u4soPU6Kobz20sY85McyvWLx1DwOVMo8H6IfPe4Tlrzo5+U7Mj8SvQDo4ztbgEI9XCZTPFANFruK3rc8lvvXPFRPArzbEDY9q5/tvAAG/jnYGpY7AlvwPC+8Gj2f3wM9lWs3PaDI/rsGoYG8PYCpvIAaCbvaMhy9gPqyOXhLhrxKRe28RfAgPT4XJL0A+6q7alDuPHncDj1j9jY9+xA5PeRcZryZZwY9TkyZvOR2B72hQzm98a0iPVjNRbykTn48oJFOO2plojy4jze8sbsBvdZE6DwuVAu9cs1BvRinBL029Zc8i8JAPYBE6jp7xEo98A8XOwhb2TsIe3e8s/4IPT9zRL3WSie9gwXJvJj0ATw0khm9TfL6vKwmQTw2DN88iKOQu5/FLL2ATEA85r7iPBgqabxJoBq9Pa+2vOo1kjyIDQK9nJ8BPGp79jw3M 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 VAi9FbQCPeILGL1GXPI8N31CPZv0FT0WDcg8AR0IPVFTDL2H+Cg9xqjZvHw7Ibzqe7c8JUQ5PdRzaLwPmja9qI85PL4r4DwwlMU7IL9CvFDfA72OkP08ZZJFPWBzEjxe6oo8MNWlO3AcnDuAJ4g7+cj5vDPSRj0oQg688NNjO0TzbzwkiQO9nL1UPMSzVjyGKeE8cA3NvOMYAD2pGAQ9vWM0PUAYwjtwdiA8GjOdPFue7bxTCEW9WzIWPZqj2DyDdTU9pWn8vNCmODwCzC29QNANO/lbET0QExa9QK5KvA0PRD1Weok8hBgLvQQMUjyeLoM8MUvAvNKH+Lw++zO9VAIEvYZLjLySWJI80FIFu1jfBb0EuCg89zsGPVqi/DxNedC8EA1kvPFBBT1ULy28V4XavKbMlTym3gm9sBoKPE1YND2QEgy92o3jPJF+TT2YaDC94Bafu4FvKj3cdg+8PhaNvCBKZLvglZW8Um6zvLocQb34Zp28ABRrOZgcQDx09wa844c9M 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 PILWuTz88kC8A6sxvdCppbtrw8i8AFdFOpAvjjvdRAM9LqqTPDrArTzQXpa75ehJPclQAT0sPl28EqtIvdOtqrwLdTI9h1UKPb0zSz3gT4680GMxPPDRlrwAo+W89j8WvX+EJj00ukm8BP4QPJZ2wjwTrxC9QJckPAOcxrzITmS8xpw1vS6NmrzHF02938ISPTrqwzy+Zrg8sIwUvQmmPD1bgbq8FiuOvEvl8ryc8no8gDXyu1PfvbylFTE9lOAXvFBUs7tQ+R27GCdMvEpviTxgSas6p8YTPdAZZ7xwTSy8Od9NvcxoML2nNyI9BMQePCcvRz1MJ1o8cBZbvEM0KT3Y44i8FIC4vPgW7Dusd388tbDIvMp3sLw+eYo8O4kivR73qDxo6oO7oAznOsDWPDyCMdA8s5rzvHzjTzzolMu84MLiu4VoQz26md485v68PPo/rDxinow8UjCSPFWsDz2dSR49Y4UXPXCZ5LtyufA8YDfMu4lmBz1gNNo6s7waPeB2BrtqM 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 vLB9DztDsCO9jtz7PCDqLrvdH0k9BNhXvHuK7ryApzu7PArnvL4Cxjwpxjq9EIsTvKi0Ab1A/HU6oygWPVsx3rzRpxU9mNwyvOysAjzQ5Bu8OirvPJJv1jzbSjY9pjH0PIqsR73N4UU9AuAAvYgpIbw4Yjk8DjDjPIDxqbvoNZA7lPJHvXCyaLurLQA9fp21PPTuXDy8UFA8zBNqPACQN7eWUyu9c91GPbfXMz0Ui7a8FN1NPATASbzEmHO80lgAvVWbRT0xWEY9YPA1O4DzBr0ybAG9UKlWvHD+VrzT0De9nAu3vFHC5ryKZt48l3U6PeBroLxI37w7YlT2PKaM4jyIAq07WBvIO9j7B70dgtO8vsPOPIC4qzuOyvQ8RP9svA6ZJb0Sotc8AAByubhyrTvpqxM9QGhzOp8jGz2z2R09Ik6oPH0OST0BokM9++ocvdhiDTxekKu8NzMJPTLjjTzqIec8aAwmvGtWn7xKhRq9bPgbvdiM3rtYrb677wwQvei97ju7M 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 PYA2A7wmyNY8CyedvPoijTxznBc9dK1uvGBqArtRYCI9CC2NvOyYcDygQo07bNBdvGVuNz0njuS8c3HlvABoXruHJRc92OzIu72hLD3jPy89UVIRPcHLFT1nUBw9UD7VO7pfS72gYcm84OBdO/OtLr3340o90Hefu4CqML1ASSS9rxA1vY+AIb3G57I8SR1KPYAVK7vxCkq9LtSqvMlaN70OVIw8cuAIvbb0M72mGCm9BNV5PMYI/zwwt3y7yqULvd7PPb2vhy09wNEZvX11Gz1+7I+82MhSvH6eG73UBW08cr2NPEIVsjz0hTi9cczJvNVbQD2nbx69Wuo1vbxbDbw0GZ28WtXAvLA8ILt0yW080bQ1PfTfRLxnT0Q9TP47vIC4kTvevK48AHQXPIAw7Lsadag8P9A5PWHR0bxs9GA8M1w9PUQePbyKW7K8cqvyPABuu7uUh0s88qLuPDKQkbwhtC09lFa2vNUcsLzNqko9aCv6u9V3KL1acv88RRcxvUoKhTxGM 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 OwZ/irxczHE8dEoWvUB/orti9Mg8EDtEvUWmK72+gOQ81IYTvBlWRz2/tkU9QLruOyit1Ltgxj27dXEgPYbSiTwydgW9qNXeu71UNj2F1c+8yJdRvH66iTzmBxG9M5lDPe8OBT3tSk09kOJOO/KDJr3MgGQ88fIevcB6NLvYIPK7yZqxvCqOtjwdZc283RUMverBpzwULnY81my+PKONQL1n2jK9Cmm3PPP6Kr1ewsE8puPcPN3JGj1Yj2K8oABsvPjoL7z6naC8lM38vHZUgjwT1Tk9VOl3PN1pFD3twE09wNU+vWLjNL29wkU9cFCQu6KbvzyMZzK8OEPAO1YWJ73sAkI8uOwePCyDMrz7MLa8Kh3iPGAQ3TtdGCE9XigqvTg8/TslJyo9QNMCvOFrIT0gFac7Qr3jvMBrVroQdRA7eVBKPfQvQDwyRZM8fj37PPgZizsMLEg86+UdPYTjazwhFCU9B6Y8PXCDLruLN+68IMTGuvkIEb1wkTK97z0/vVE3SL1AM 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 POzIW7zfGxG9aCSEu6qn3jzCUoC8HCnevDLBRr1cJXI8krmZvOC9dDtY00i9yckMPfztQryw3ya7b9gIPe9bID1yavw82fVMPXKFjjx86mo88nSbvNDkijssBE+8pa84PdRBJDzXkAA9jsk5vfBrSbxUz0C8nr2JPGD7brzr+To9B7EEPaPYH70Vm0k9FAg+PCoJtTzgPKO7BMEjPBS0Q7zvmRY9Ks70vAhpkrxw1iG79orOvAD0YLsr5D89dibyPMkOJj1DYPa8T7E9Pfkvqbypghy9TXkBPZeUCz14j/I7bBNlvBxuFrwSVY48ANNPO3MuKb1wASO9h70bPZLUBL0xRhM9lfsXPUHZIz1mRZi8dkHrPPQMD71AH6a6KOpNvJpsDr1goJK6lCx1PBTDRb2AAZ+7ABiLOevRHj1xbhQ9E5IUPa2kLD17pQc9yjlLvSDt3rrQrSG8YK7vOgAWGDpmiUG9z90rPfhzDb23LRC94qfoPMzfXzwoUBu93V5MPVDOWrvBM 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 PYKg97zdi++80K+ZO2pp6DyQnhQ7+B8XvYgkYLwWS4k8nOcsvFyTc7yAQ187qwAzPYjPibuI8SS87L9HPDsvMj1i2pw8NMFBPANrwbznkyY90lbTPB8HtrxRMBk9bkPePAI01jwqipk80vCrPHFkBz0urTu9qlEivZT0RDxtZzK9IQQhveswSj12Tx+9RvT6PIDstbn1owm9xwZFPYK6/jzAqr66iFCPvJzNlLywGQc77wsXPREYML1Znwg9xp7CPNDorbtbpEG9S4savf5e+jwtWS89XvW+PBBcRrwl0iI9U7kdvSvzt7zi4Te9iToXPZoIIr1AIS28+jHtvGLiGL3p5rK8AIQwPDYq6zwA7xk5gSI3PboKiDwQ6Tw7ZD4wPKp9qTw2dKK8FhKrvIV73by+e5k8kkdLvaGlvbwsOwK9AFPQOUEYRL3+3tc8vAd7PEXFAD2LOTa95WwQPUMtprxi2428MWMlPajjS73gTpg6eZLOvMy3UjzokdW7oMC6u15exTxnM W0u9pB4svMgBjDso3cE7Tr29PBT7Jr3J8qy8YMMBPGm9tryrURw9KTAnPQdOPj2jjUY931cIPcRMG72MfTu829PpvEBK+jtsGGO8FBkWvZjPITz7/RM9meBEPa5ym7wKFNk8Hc5DPZoVyLwIQle8AP/Rudqh9jzbiiI9ztS/PFhR8zvJqhG9NMx0vOL6yjxGLD69bo3pPIDzBrq/igI9mrfsvOC4N7w+mEa9sgTZPAM1Gz0MXgQ86+oPvU79i7z2BKA8639KPUqrmjygCly8HC4/vdpK1jxZOy89tKjEvJ0P+Lys/we8uW8ZvV5PpDw0Roy8E+shPeSUBr0mXsM8ChmRPEHRJz1DukW9GlDJPBrn9DyBzgE9BFBOPIVaIb3sM2E8v9xMvY4yjbwg0D+9X4umvLj1brxJ8SW9oLcavLOgPj2a36S82/D8vDKijLzsLEC9VHNsPDufLj3CPKo8JXTNvJCR5btDuhI9eYhGPXgZJbzBoig9/mCQvHQgh7w+QIE85LbNM 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 2cK7krEBvegoJb1InVG8M64OveEtET2X3Cc9rMgMPEEcQj2EmXY8vhfpvJhJVbzbRiC9kCFru5rMPb0nQD89sjTcPMjClzuRqSc9QH7QOlK7yjzQLks7ZyYWPS6NpjyQ0Ym7+NwdvdghqLtN00U9iq+XvMB3M7uKB428Y4A3PWZfhTzQ6zS8INCAOpwQIjxklRG9KsitvLz8fzzA1Ia8+BKaO0XQRL2tKQU9Ut+MvEW7HT2f9RU9BqDkPASYHL0vpCI9yC9vvFLWB73uk7E8Lz5JPahCErwAyAA7JcsWPdD5cju8Cw88xILhvBxGfTzyh4w86leXPGlJRD2LBxI9Mak8PWC1O7z27CK9Az0vvbRMDjzMcuO8rLQtvbRAM72Ux2+8GtndPF3IJT1oUK87BV0avTLZi7wSXMw8s3ohPdRkTL1Q0jw8rNxCvZivGb1AbLA7X9odPdow3zxRREQ9WAMwvFlnQ72ga2g76qLDPEofDr3hjgg9rgH1vHxSFb1F7QA9L4YEM vVniRD1qaK08LyTzvPpsmzwKUe68Z4gkvSjSi7viM5Y8ij3RPMfNSj0FnUM9Ko8HvXmyBb3kJnC8gNTTOzWkHT3VWEg9gBVmOz9HQL0HytS8MaVAvbM1Bj3U/ks86CZNvQ8DSr3A+hk7iqX5PJ59jjxg7Jm8komiPHyLEDxsIWq8Rb8LPVbsEb1IwAu9VkAtvSpYSr3AoVW8IC8uO4BwoTrL3xY9FM4lPH4ZI73IqI87ine8vHxYSTzg2wO9Bmr9PJlhIL2xAAc93OJTPORARL0Yx7e70rXdvL/rAD0EfhA8SToUPT5Yijw5s9a8sMsBPHD0VbtCieM8INGPO/t/LT2WQhy9J7UXPTxnBr3CKLG8YwgLPdC4SDvIkmC8oB1OO9AY/ztLMhk9FUUoPfq6rDwPzyg9EGcbO/hFYrwMmSe9WX4yPUzR8rxsyWY8rNPRvD4iIL1R/Ni8sMwKvVhA/ztglh48AJTmuKGa5byAZlK8TJEPvXRKF7wA2fk7cAzhuwCFLTqgM 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 KSK9Aj/IvGD+mzunxUG9r1ciPQJL1Ty7ubC8N+MovVQxS71+HIC8gAHSO8KlkLyQljq8PFufvKSuTTyApTC63y1CPQvGKj2WVL28jNohvHolpjyVaDA9tLdfvOy+HTzws8y7cP96u494s7yO7so8p9e4vB1tSz1YeYG7guz+PGC01LrANKk6j+hAPQY3wDzqoy290Omvu41VPr0AVr05+9dIvfBjN7scLHk8kJZtuy0YTT1IIM274OjAOhWq87xwxQG91G0EPED9jLz+Egu9CHTDvPqh6byId5e7WJ9dvEiIrrtdGU09BAxGvfVxS71AWsO6/78DPXGaNT10oRW9E+oivcOwCj0BrSE9XbBDPeLg6zw0wTI8jyEDPXl1GD0Ky4U8hrHSPCL1wDwA8DO87+kZvfSdgbzy88o8pJdqPPacqTyaP8w8etDWPNt0n7zkEQm9nAKjvEjYLTx8wTo8ADCzuxDkMrtCUYs8lcpKvXx8IrzGYYg8MDAaOz9eP71wxRk8+JtRM 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 vNDZjrsAQp44kDQ8vQwDUTxP9cW8XIUyvct2Nz3MiYK8kEQGvRG5Ej0YK8o7RChhPAvV1byo/hM8uSoxvRKMtLy/5xc9GHuNOyDfD7sg+qG6AKhPO2YwozwsWzm9gFqQO3jHPr3J1kE9hv/2PH74hLy/hdO8zLGNvMPMuLzcsdC8HFVEvIANF7vhs0M9Or+EPDqISr2gBR+7QAgfO+sQID1kMT69Vgc2vRDALjx+76g84AQUu+gBHbw/I0E9TUApvQrRlLxq0IY8Tmk2vdZJyjz4qCG8gPFmunzhAL3bSw89AJkfvZibS7zDdqG8tpC2PL6xMb3q7gi9nBHQvDS+SDyGzyS91suQvILJmbw1iAw9aADOu5cOED1/tLO8xKUBvIouJb22uTW9gN/9vNHdCb0kGAO8agD3POfVC71e8988MxAwvYX6Kz1pTB89DGqXvGSvRDzFrTQ9nLZ2vOrx6Dw43rA7uc4wPcD3m7pfjhA9vJcqvCXSAj3lNSs9bnHrPBG+Sb1IM 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 u+R2Hr2f//i8h4osPScTPT0uDei8L0owvZgSDb3Rsy09vPRRvKzyNb1Kqsw8XB1MPB8dNL0jJTg9+Nqcu3KIk7yNOkc9Ono8vcjLKrzIkhQ8ugWFvACWuTpMdBo8gX83PVa75TyRRS09LlUgvcQWRry+CfE8KVulvIDbFrsA+YY7CDQHvdzEazzROUY9zekkPXwlTL09J/+8lewuPa0b77ylnSi9HIY9vIaeEr1gpPI7M8rvvBQYDb34I+47QPk8vJi/NDzwV7G8cEMVPBlCMT30nyy8duqsvIg5Kbxovjm8GEVlvJVpn7zG+oA8KPOavAGyMj0eWuE8hzXBvJXnx7wJa0I9AOhaOlTeITzFGEA9ANfIOqCa6bppukA9KNTGu3uPI70kkGY8kMY+O2O2PT0gKTi8cDROvIf0sbxBJDU9gE/Ju7yRQL3FUCA9oM8pvMqIgrwRyiA9JJp6vBi8gTu4Ufe7rnkQvcCSZLuf6sq8wB8julQFObyeOvY8sDWlvCr0mrxUM 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 vBm9ZSFDPaDMFbz5zik9gvufvODDabwynDS91529vMjqjrw0gx+9OYshPUewz7yAm6w6przGPKr91DwR2S899P3/vNLGrjyUG2a81o6LPHDsDLzLH+287KddvPcPAr3Mooy8kDgUvBAYa7uz1jM9LjHKPDudMT3exCW9UEVgOywSOrzHgEo9oYcfPSr/nzw4zS29PqPwPAY8Cr28Vsi8FHtSvOAf2rpApJG7+MfrvECKkrpQlj+7qHOHuwWYKT2PnAK9T284PUZ//jxvRQ8913wXPXBmN71QLF+8UcGqvMC6MjwXbBM9mwghvUv7Aj2sMDK9cc4tPcBNLLxSHpy8mh+EPLCQdztXZa28rpC8PJXBET0xYbG8Ul6lPCzCfTyLJc28KGbrvBiULTyaQ+g8bS4lvYiUJL3Yiji9XCg9vNi4ibtetbs89JWPvJB1i7vgtwQ7IO9vu7wUkbxIGOw7f7kIPQBRKbkAbLy5oEoYuz9fIr05ER891vbtPG06TD0daxS9oK6vM 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 Vyq9f9EUPRM8F73Vga68Hr6kPCi35ztndhI9qdo9PV7II70MkFa8dF1BvDmTHT2TKSu9UzxEvXNJDj2XjDC9JGrrvKEsTb1oKwG9zoBDvRxNAbxnSx89yiuPPDihUbwsfym8urgovbJ8L71DDkU9BMrRvMA7Ajy21NC8pQIhPRrA9jxombW8rGHKvFi3nzuQqgA8HmDIPMUWBz2kro+8ADuVvMysYbxx9RQ9TJ4ovJP9Jj2VLy098DbVO7i3Qby+/7Q8I3MAveHgzLzsWxE8gL49O+Rjl7yqW7K8V5fbvOefNT2TdR89pIBoPA6GyjxCguK86P5Evd+GEr2DsfW8kbgwPatCGz1ICrU7kMgevS6R8jxrlj49youVvDasijxLGku9ViW9PEAJ1jpnZD499N11PHVTQr3dfUA9AFUMOr0SMj02U+48eagGPSopzzyHgR497oWFPDyE+bxgmuS6AIbOOqfvEz1Q1B08JkrBPFg6v7t4Qf27LBM0vUmoOD2vLBY9pL8yM 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 2wU9ER5APVT6LLwseQu9ZJ5evGATIjw4Lgi8FcUIPWQFPr1wYyU7cWHevKySSjz0bjW91Cw2PI/XQz2p2zU9H4IcPRLvyDxzZjG9eTI1PTpL6jw7MEU9EKQmvBjGTry/gS495PZsvGMUHz2wJdI7LLiPvP6FrTxD6zQ91rmOPCfLDT1AlpS6jEM8PD3uRL0o0xo8ymYBvU9cOz0uXeS8dOukvDkdJj1X6Qy9b6ctvXAT0zvgtgi9sKCXO/t3BT2go7q8wCyjOlgbPjw+zr888VcQPXS+Vzx2wY08nE5pPFBdNTuE+iK9aEExvej9BTw0TXa8fNVAvGo+jTxyNM48+A4nvNsUOD3RaQo9Q2ETPUuNSz3I4+E70OMLvRT0RTx9ETU9DI5UPExHYDx1WDw9dvrUPKAelbqhAw2976wcPbsN4rxzV0Y9mgnoPDE1FD0bRQM9Eb8svVc0LD2M13+8tPqSvB6vjTxjdDA9Bx4BvWC0yrr4uAG94hL0PDDpgDt1Ekk9mMigM 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 ahK9mcQdPWPWLD1fREc9Tv8JvdgUhztq8SS9QJ2nur46wjx2kv68ROUmvW5spTxI9tQ7+NGKO5ADXztptk09ybJIPfps0DwY39A7BQkRPQgvBDxm0u88gKndO1fvIL0omSG96poNvagN87teldc8jpz7POK/qzzoTaO8ZEskvYxJfzyZ+0g9PblMPf7Glrxghke9Pw0nvTD2g7vaKoM8gGj3upusGj1i/ME8GI4fvaBiBDwTevi8GpTEPCTbQ7345v+7pljpvMp+4DyQl/G7il3DPEMOTj04sSc8gOVDvDTep7yLNz497Y/OvCt837wfOSQ9V/cXPYYZ9jzgaik7XGQavG5GszwA8/+7R2s+veqnhTyg6Aq7gY4nPXY3vDxJRAa9kEU9vGqe2Dzq27I87eIsPY37Hr3gs4S6Yq/NPDgZ5TsCGJk8Bu7PPDq+zrxwfDw84M6KujyK5rwIB1S8FNguvGr5krxwLwu79JJePFfdAr0UoTQ8tzJOPStsEz3AUA06IHevM u+slLz32eY48pEpmvJDyQb2FdEM95TwRPTjWCL02eso8bYopvQqyl7ykvWS8kI4qOwAudrtlaEM9FmUHvY4qwjwMYMC85H4NvBsIEz0j8zs932RHPXD8+rxl4jY9Sbz0vAdBF73QF+M7ICFEu6DQc7uY2Bq9tqUivdesID3AiLq7hnafPJ12Pj1A26684DGHvGZi7DwjJAI93CIiPCDIobphuzC9frUNvdzMcTwAErQ4T8i1vJw3i7yOV5G8T3AQPcEROb1QOsu7Ujm+PNaUxTyBmjg9SPPPu3qM+zx0SB68+veAPCeIHj2rMwo9QCbWOiSRCr1cqDi9dT8Wva34Kz2AYrA6QEkaOjAiCDv+zku9NOobvUgQlLz0w0O9opvLPGY7AL2cvja9hYcLPZhU07tDrxG9NQ1FPVk6R72YEkQ8RNo2vEe4Cj0qUaM8A85APeNFQ73A3/i71SXKvDVYMj0nkSE9UO7su4RXP71NYAM9XKjPvNg0dbyazoW8OMcmvXUE27w6M 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 K3g8slHHvLiS1juzqTS9/nzHPI9fNT2CZZE8xFkNPGALi7qOdMw8h7UkPYaoMr3RqDS9TpJJvUlUTD2oZ5u86IO5vEnA8LxGy5K8Ce6hvFBwQL3oc9+7BR/LvJDjCLySG+M8MJC/u86jQ71GnCe9qAjOO3fkIT2AEAu6GBymu2gEbby40Y68xrEtvSq2Qr3CtzS9qlCuPP6M3Txi0PS86uAjvRBXyrtmYiW9cJ+VvJkyJj2kZ2a8su0uvXDURDu3GSs93S07PSZF+DzW8rI8DNY8PDJ46DwMRFk8WZlDPeyplryoAyO9HAxiPKBO2bwsEGc88bQYPXioybukTwq9MCIuvfA0nbu5vBI9kKy4O9bszTwoi4w7/jauPPG6Lz2TMBE9PlStPFNWPT0yyOs83TICPaDrCjy5ZCo9eByTvDpj4Dz+W/08KI/Eu/zJc7zjS728cOxLuzspFj1gfjU8ngDvPNlrML1ym4k8ABibuyg+O7zqgLG8XH1QvNPTLr3X1jC98x9JM 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 MTA8mI5ZvxSYJ7/4R7++AAAAAAAAAAAAAAAAnfDhvhh5K7/2FxQ/drAoP7hTTr5CgVs//hAaP0WpYr+QMGe+rCszP3zaM77gTim/YlKDvsKU0z1keaE9TxTWPQ==", "training_traits": {"structure_gen": "Triangle", "n_layers": 10, "max_nodes": 7, "activation_func": "ReLU", "epoch_num": 6}, "classes_name": ["Cryptoadz", "Cryptopunks", "Moonbirds", "Nouns"]},m=25,b=50,y=59+11/12,w=59+11.5/12,v=60;function z(e,t){const n=Math.log(1-t)/Math.log(1-e);return e=>1-Math.pow(1-e,n)}class V{constructor(e,t,n){const{model:r,inputDim:i}=j(t,n);this.model=r,this.inpM utDim=i,this.iteration=0,this.stage=0;const o=new Date(parseInt(e.birthYear),0,1).getTime(),a=new Date(parseInt(e.birthYear)+1,0,1).getTime();this.birthDate=new Date(Math.floor((o+a)/2));const l=zr.filter((t=>t[0]==e.lifeCycle))[0][2];this.growSpeed=365/l,this.cycleLength=60*l*24*3600*1e3,this.growthFunc=z(.4,.8)}updateAge(e){const t=(e.getTime()-this.birthDate.getTime())/31536e6*this.growSpeed;this.iteration=Math.floor(t/60);const n=t-60*this.iteration;let r;this.age=n;let i,o=0;if(n<25){let e=map(n,0,25,0,1);o=thM is.growthFunc(e),r=(25-n)/60,this.stage=1,this.stageRatio=map(n,0,25,0,1)}else n<50?(o=1,r=(50-n)/60,this.stage=2,this.stageRatio=map(n,25,50,0,1)):n<y?(o=map(n,50,y,1,0),r=(y-n)/60,this.stage=3,this.stageRatio=map(n,50,y,0,1)):n<w?(o=0,r=(w-n)/60,this.stage=4,this.stageRatio=map(n,y,w,0,1)):n<60&&(o=0,r=(60-n)/60,this.stage=5,this.stageRatio=map(n,w,60,0,1));n<50?i=map(n,0,50,0,780/880):n<w?i=map(n,50,w,780/880,800/880):n<60&&(i=map(n,w,60,800/880,1)),this.nextStateTimestamp=Math.round(e.getTime()+this.cycleLengthM *r),this.statePercentage=round(100*i);let a=(25-n)/60;a<0&&(a+=1),this.nextStableTimestamp=Math.round(e.getTime()+this.cycleLength*a),this.growth=o,this.model.updateNeurons(o,this.iteration)}getBrainStatus(){return{totalNeurons:this.model.getTotalNeurons(),neuronsLife:this.model.getNeuronsLife(),stage:this.stage,inputDim:this.inputDim,stageRatio:this.stageRatio,age:this.age,growth:this.growth,nextStateTimestamp:this.nextStateTimestamp,nextStableTimestamp:this.nextStableTimestamp,rebirthCount:max(this.iteration,0),sM tatePercentage:this.statePercentage}}classifyImage(e){const t=new G(e,1,e.length);return this.model.forward(t).mat[0]}}class M{constructor(e,t,n,r,i){this.p=e,this.v=t,this.size=n,this.shape=i,this.col=r}getRadius(){return 1==Oe?1*this.size/2:2==Oe?7*this.size/16:3==Oe||4==Oe?4*this.size/7:0}update(){this.p.add(this.v)}draw(e,t,n,r){const i=this.p.x*r,o=this.p.y*r,a=this.size*r,{col:l,shape:s}=this;let h,c;1==n?h=c=l:2==n?(h=dr(t,1),c=l):(h=dr(t,0),c=dr(l,1));e.stroke(dr(c,map(1,0,1,.25,1))),e.fill(dr(h,map(1,0,1,.M 15,1))),3==n&&e.fill(dr(h,0)),1==s?e.ellipse(i,o,a,a):2==s?e.rect(i,o,7*a/8,7*a/8):3==s&&(e.beginShape(),e.vertex(i-4*a/7,o),e.vertex(i,o-4*a/7),e.vertex(i+4*a/7,o),e.vertex(i,o+4*a/7),e.endShape(CLOSE))}}class E{constructor(e,t,n,r,i,o,a){this.center=e,this.len=t,this.angle=n,this.v=r,this.angV=i,this.c1=o,this.c2=a}getEndpoints(){const e=createVector(this.len/2*cos(this.angle),this.len/2*sin(this.angle));return[Vector.add(this.center,e),Vector.sub(this.center,e)]}update(){this.center.add(this.v),this.angle+=this.M angV}draw(e,t){const[n,r]=this.getEndpoints(),i=n.x*t,o=n.y*t,a=r.x*t,l=r.y*t,s=this.c1,h=this.c2;var c=e.drawingContext.createLinearGradient(i,o,a,l);c.addColorStop(0,s),c.addColorStop(1,h),e.drawingContext.strokeStyle=c,e.drawingContext.globalAlpha=1,e.line(i,o,a,l),e.drawingContext.globalAlpha=1}}function S(e,t){const n=random(TAU),r=random(e,t);return createVector(r*cos(n),r*sin(n))}class R{constructor(e,t,n,r,i){this.wall=n,this.maxR=i;const o=t.length;this.nodes=[];for(let a=0;a<o;++a){const o=[],l=.25*t[a];fM or(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),l=S(.02*i,.05*i),s=random(10,25)*i;o.push(new M(t,l,s,e[a],r))}this.nodes.push(o)}const a=A(e);a.unshift(e[0]),a.push(e[e.length-1]),this.lines=[];for(let e=0;e<=o;++e){const r=[],l=(0==e?1:t[e-1])*(e==o?1:t[e])*1.5;for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),o=random(5*i,10*i),l=random(TAU),s=S(.02*i,.05*i),h=random(2e-4,.001);r.push(new E(t,o,l,s,h,a[e],a[e+1]))}this.lines.pM ush(r)}}reflectNode(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,{p:o,v:a}=e,l=e.getRadius();(o.x-l<t&&a.x<0||o.x+l>r&&a.x>0)&&(a.x=-a.x),(o.y-l<n&&a.y<0||o.y+l>i&&a.y>0)&&(a.y=-a.y)}reflectLine(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,[o,a]=e.getEndpoints(),l=e.v;(min(o.x,a.x)<t&&l.x<0||max(o.x,a.x)>r&&l.x>0)&&(l.x=-l.x),(min(o.y,a.y)<n&&l.y<0||max(o.y,a.y)>i&&l.y>0)&&(l.y=-l.y)}update(){for(const e of this.lines)for(const t of e)t.update(),this.reflectLine(t);for(const e of this.nodes)for(coM nst t of e)t.update(),this.reflectNode(t)}draw(e,t,n,r,i){const o=i/this.maxR;for(const t of this.lines){const n=t.length*r;for(let r=0;r<n;++r)t[r].draw(e,o)}for(const i of this.nodes){const a=i.length*r;for(let r=0;r<a;++r)i[r].draw(e,t,n,o)}}}function I(e,t){re(e),e.fill(0),e.rect(0,0,500,500),ie(e),e.noStroke(),e.fill(dr(cr("#000000"),.5)),e.push(),e.translate(250,250),e.scale(t),e.translate(-250,-250),e.beginShape(),e.vertex(235.2,24.9),e.bezierVertex(215,24.6,185,11.4,164.8,11),e.bezierVertex(147.2,10.7,129.3M ,10.4,112.2,14.7),e.bezierVertex(95.1,19,78.5,28.5,69.6,43.8),e.bezierVertex(57.699,64.199,61.599,90.199,70.199,112.2),e.bezierVertex(78.799,134.2,91.6,154.6,97.199,177.5),e.bezierVertex(102.499,199.2,100.899,222.5,92.799,243.2),e.bezierVertex(83,268,64.6,288.3,48.9,310),e.bezierVertex(33.2,331.7,24.5,337.5,26.599,364.1),e.bezierVertex(28.2,384.1,61.399,404.2,75.7,418.3),e.bezierVertex(90,432.4,73.7,488.2,91.9,496.7),e.bezierVertex(124.2,511.6,159,472.5,194.3,468.1),e.bezierVertex(211.6,465.9,267.4,501.5,283.9,495.M 9),e.bezierVertex(340.7,476.7,298.599,428.9,355.4,409.7),e.bezierVertex(370.799,404.5,454.5,407.6,464.4,394.8),e.bezierVertex(478.599,376.3,474.7,349.3,464.299,328.4),e.bezierVertex(453.9,307.5,438.099,289.5,428.699,268.2),e.bezierVertex(412,230,419,182.6,446.1,150.9),e.bezierVertex(449.7,146.7,453.6,142.7,455.8,137.6),e.bezierVertex(459.4,129.299,457.5,119.6,454.8,111),e.bezierVertex(443.2,73.4,417.3,40.4,383.6,20.299),e.bezierVertex(358.1,5,343.2,-.4,313.5,0),e.bezierVertex(287.5,.4,261.6,25.4,235.2,24.9),e.endShM ape(),e.pop()}function C(e,t,n,r,i,o){let a,l,s;re(t),t.fill(0),t.rect(0,0,500,500),ie(t),t.noStroke(),t.fill(dr(n,.5)),1==i?(l=0,s=25,a=map(o,0,25,500,0)):a=0,t.rect(0,a,500,500),e.noStroke(),e.fill(r),e.rect(0,0,500,500),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.beziM erVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.M 399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3M ,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),e.fill(n),e.beginShape(),e.vertexM (435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),M e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,M 192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4M ,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),re(e),e.fill(r),e.beginShape(),e.vertex(184.3,473.2),e.bezierVertex(164,473.2,144.7,462.099,134,444.3),e.bezierVertex(131.7,440.5,129.1,438.5,125,437.1),e.bezierVertex(97.3,428.1,80.5,400.6,85.2,371.8),e.bezierVertex(86.3,365.1,85.8,364.1,79.9,361.2),e.bezierVertex(57.2,349.8,46M .2,323.3,54.3,299.7),e.bezierVertex(54.7,298.599,55.1,297.7,55.5,296.9),e.bezierVertex(55.6,296.599,55.8,296.4,55.9,296.099),e.vertex(57.9,291.499),e.vertex(62.5,293.599),e.bezierVertex(64.9,294.7,67.3,295.799,69.5,296.9),e.bezierVertex(74.5,299.299,79.1,301.599,83.9,303.099),e.bezierVertex(89.8,304.9,96.5,305.499,102.7,305.9),e.bezierVertex(102.8,305.9,102.9,305.9,103,305.9),e.bezierVertex(106.6,305.9,108.9,302.799,109,299.799),e.bezierVertex(109.1,296.199,106.6,293.4,102.7,292.799),e.bezierVertex(101.3,292.599,99M .9,292.4,98.4,292.299),e.bezierVertex(94.3,291.799,90.1,291.299,86,289.9),e.bezierVertex(68.9,284,56.5,270.2,52.7,252.799),e.bezierVertex(48.9,235.499,54.5,217.7,67.6,205.299),e.bezierVertex(71.9,201.299,72.7,198.1,70.8,192.399),e.bezierVertex(64.2,172.2,68.8,153.99,84.2,139.599),e.bezierVertex(94.2,130.199,105.5,125.399,117.8,125.399),e.bezierVertex(124.3,125.399,131.1,126.799,137.8,129.599),e.bezierVertex(157,137.399,167.9,152.799,169.4,173.99),e.vertex(169.4,174.399),e.bezierVertex(169.5,175.899,169.6,177.2,169.M 9,178.299),e.bezierVertex(170.7,181.2,173.2,183.2,176.1,183.2),e.bezierVertex(176.299,183.2,176.5,183.2,176.7,183.2),e.bezierVertex(180.1,182.899,182.6,180.299,182.7,177),e.bezierVertex(183.1,162,178.299,148.2,168.399,136.1),e.bezierVertex(158.2,123.5,144.899,115.8,128.799,113.199),e.bezierVertex(123.499,112.299,120.399,109.799,118.899,104.99),e.bezierVertex(113.899,89.699,120.699,72.299,134.899,64.499),e.bezierVertex(139.99,61.699,145.799,60.199,151.7,60.199),e.bezierVertex(162.2,60.199,171.899,64.799,178.1,72.699M ),e.bezierVertex(179.6,74.6,180.799,76.6,181.9,78.499),e.vertex(182.2,79.099),e.bezierVertex(183.2,80.699,185.2,83.299,188.4,83.299),e.bezierVertex(189.5,83.299,190.6,82.99,191.7,82.399),e.bezierVertex(195.1,80.599,196,76.99,194,72.799),e.bezierVertex(190.1,64.799,184.1,58.499,175.6,53.299),e.bezierVertex(174.6,52.699,173.7,52.099,172.5,51.499),e.vertex(170.5,50.299),e.vertex(163,45.899),e.vertex(170.5,41.599),e.bezierVertex(182,34.99,193.1,30.799,204.4,28.599),e.bezierVertex(208.6,27.799,212.9,27.399,217.2,27.399)M ,e.bezierVertex(217.6,27.399,217.9,27.399,218.3,27.399),e.bezierVertex(231.4,27.599,242.7,38.199,243,50.599),e.bezierVertex(243.4,64.899,243.3,78.99,243.2,93.799),e.bezierVertex(243.2,99.799,243.1,105.899,243.1,112.099),e.vertex(243.1,119.199),e.vertex(236.4,116.799),e.bezierVertex(235.7,116.499,235,116.299,234.4,115.99),e.bezierVertex(233.4,115.599,232.6,115.299,232,115.199),e.bezierVertex(230.6,114.899,229.2,114.599,227.8,114.299),e.bezierVertex(223.8,113.499,220.1,112.699,216.4,112.499),e.vertex(216.2,112.499),eM .bezierVertex(212.5,112.499,210.7,115.599,210.6,118.599),e.bezierVertex(210.4,122.399,212.7,125.099,216.4,125.399),e.bezierVertex(230.1,126.399,238.9,133.099,242.3,145.199),e.bezierVertex(243.2,148.399,243.2,151.599,243.2,154.499),e.vertex(243.2,155.099),e.bezierVertex(243.2,254.199,243.2,330,243.2,400.599),e.bezierVertex(243.2,401.99,243.2,403.4,243.2,404.9),e.bezierVertex(243.3,411.099,243.3,417.599,242.3,423.9),e.bezierVertex(238.1,449.2,219.6,467.799,194,472.5),e.bezierVertex(190.9,472.9,187.6,473.2,184.3,473.2M ),e.endShape(),e.beginShape(),e.vertex(315.8,473.1),e.bezierVertex(309.3,473.1,302.8,472,296.5,469.9),e.bezierVertex(270.4,461,253.8,434.9,257.1,407.9),e.bezierVertex(260,384,273.8,366.8,297,358.3),e.bezierVertex(297.7,358.1,298.3,357.8,299,357.6),e.bezierVertex(299.8,357.3,300.6,357.1,301.2,356.8),e.bezierVertex(304.3,355.4,306,351.8,304.9,348.7),e.bezierVertex(304,345.9,301.7,344.2,299,344.2),e.bezierVertex(298.6,344.2,298.1,344.2,297.6,344.3),e.bezierVertex(288.1,346.3,279,350.9,269.7,358.3),e.bezierVertex(268.9M ,358.9,268.1,359.6,267.2,360.4),e.vertex(265.5,361.8),e.vertex(258.5,367.6),e.vertex(257.4,358.6),e.bezierVertex(257.3,358,257.3,357.5,257.2,357.1),e.bezierVertex(257,356,256.9,354.9,256.9,353.7),e.bezierVertex(256.9,334.8,256.9,316,256.9,297.1),e.bezierVertex(256.9,260.3,256.9,222.3,256.8,185),e.bezierVertex(256.8,170.7,268.3,158.8,282.5,158.4),e.bezierVertex(284.8,158.3,286.7,157.6,287.9,156.2),e.bezierVertex(289.099,154.9,289.599,153.2,289.5,151.3),e.bezierVertex(289.3,147.5,286.7,145.1,282.7,145.1),e.bezierVertM ex(282.5,145.1,282.2,145.1,282,145.1),e.bezierVertex(278.8,145.3,275.5,146.1,272,146.9),e.bezierVertex(270.9,147.2,269.8,147.4,268.6,147.7),e.bezierVertex(267.9,147.9,267,148.2,265.8,148.7),e.bezierVertex(265.1,149,264.4,149.3,263.5,149.6),e.vertex(256.8,152),e.vertex(256.8,114.6),e.bezierVertex(256.8,95,256.8,75.4,256.8,55.9),e.bezierVertex(256.8,38,267.2,27.3,284.6,27.3),e.bezierVertex(285.3,27.3,285.9,27.3,286.6,27.3),e.bezierVertex(299,27.9,318.7,34.5,329.6,41.9),e.vertex(336.1,46.3),e.vertex(324.4,53.3),e.beziM erVertex(316.2,58.2,310.2,64.6,306,72.9),e.bezierVertex(304.2,76.4,305.1,78.5,306.1,80),e.bezierVertex(307.4,81.9,309.4,83,311.6,83),e.bezierVertex(313.7,83,315.7,81.9,317.1,80.1),e.bezierVertex(317.4,79.7,317.8,79,318.1,78.4),e.bezierVertex(318.4,77.9,318.7,77.3,319,76.8),e.bezierVertex(325.3,66.2,336.3,59.9,348.5,59.9),e.bezierVertex(353.2,59.9,357.8,60.8,362.1,62.7),e.bezierVertex(377.6,69.3,386,86.7,381.7,103.2),e.bezierVertex(380.7,107.1,378.5,111.8,371.1,113.1),e.bezierVertex(342.7,118.1,322.2,139.1,317.8,167M .8),e.bezierVertex(317.4,170.3,317.3,173.2,317.4,176.5),e.bezierVertex(317.5,180,320.1,182.8,323.5,183),e.bezierVertex(323.6,183,323.8,183,323.9,183),e.bezierVertex(327.1,183,329.8,180.6,330.3,177.2),e.bezierVertex(330.6,175.7,330.7,174,330.9,172.3),e.bezierVertex(331.1,169.8,331.4,167.3,332,164.7),e.bezierVertex(337.3,141.9,357.7,125.4,380.7,125.4),e.bezierVertex(382.5,125.4,384.3,125.5,386.1,125.7),e.bezierVertex(412.8,128.9,432.6,150.9,432,176.9),e.bezierVertex(431.9,182.3,430.9,187.7,429.1,192.7),e.bezierVertexM (427.2,197.9,428,201,432.3,205),e.bezierVertex(446.8,218.7,451.8,236,446.6,255),e.bezierVertex(441.4,274,428.3,286.5,408.7,291.3),e.bezierVertex(406.1,291.9,403.6,292.1,401.1,292.3),e.bezierVertex(400,292.4,398.9,292.5,397.9,292.6),e.bezierVertex(393.6,293.1,390.9,295.7,391,299.5),e.bezierVertex(391.1,303.4,394,305.8,398.5,305.8),e.bezierVertex(409.9,305.8,420.8,302.6,431.1,296.4),e.bezierVertex(431.8,296,432.5,295.5,433.2,295.1),e.bezierVertex(433.8,294.7,434.5,294.3,435.2,293.9),e.bezierVertex(436,293.4,436.6,293M .2,437.2,293.1),e.bezierVertex(437.4,293,437.7,292.9,438.1,292.8),e.vertex(442.5,291.4),e.vertex(444.2,295.7),e.bezierVertex(450.9,312.4,449.5,328.4,440,343.4),e.bezierVertex(435.3,350.8,428.7,356.7,420.2,361.1),e.bezierVertex(414.3,364.1,413.7,365.2,414.8,371.7),e.bezierVertex(419.5,400.2,403,427.6,375.6,436.9),e.bezierVertex(371,438.5,368.3,440.7,365.8,444.7),e.bezierVertex(355.2,462.5,336.4,473.1,315.8,473.1),e.bezierVertex(315.8,473.1,315.8,473.1,315.8,473.1),e.endShape(),ie(e),e.fill(n),e.beginShape(),e.vertexM (120.2,279.9),e.bezierVertex(117.9,279.9,112.4,279.299,112.2,273.599),e.bezierVertex(112,267.7,117.4,266.7,119.7,266.599),e.bezierVertex(133.1,265.799,143.1,259.499,149.3,247.899),e.bezierVertex(149.6,247.299,150.1,246.399,150.3,245.399),e.bezierVertex(150.6,244.299,150.5,243.299,150.5,242.7),e.bezierVertex(150.5,242.6,150.5,242.5,150.5,242.299),e.vertex(150.3,238.799),e.vertex(141.1,235.99),e.bezierVertex(114.6,227.799,95.6,202.499,95.9,175.799),e.bezierVertex(95.9,173.99,96.4,168.199,102.2,168.199),e.bezierVertexM (102.6,168.199,103,168.199,103.4,168.299),e.bezierVertex(104.8,168.499,108.2,168.899,109.2,175.599),e.bezierVertex(109.3,176.599,109.5,177.599,109.6,178.499),e.bezierVertex(110.4,184.199,111.3,189.99,113.7,195.499),e.bezierVertex(121.9,213.99,139.5,225.499,159.7,225.499),e.bezierVertex(172.1,225.499,184.1,220.899,193.5,212.599),e.bezierVertex(194,212.199,194.4,211.799,194.8,211.399),e.bezierVertex(195.1,211.099,195.5,210.799,195.8,210.399),e.bezierVertex(197.4,208.99,199.2,208.2,200.9,208.2),e.bezierVertex(202.5,20M 8.2,204,208.899,205.3,210.1),e.bezierVertex(208,212.9,207.9,216.9,205,219.9),e.bezierVertex(196.5,228.6,186.3,234.3,174.7,236.8),e.bezierVertex(168.799,238.1,165.6,241,163.899,246.7),e.bezierVertex(158.3,265.9,139.9,279.7,120.2,279.9),e.vertex(120.2,279.9),e.endShape(),e.beginShape(),e.vertex(187.2,427.5),e.bezierVertex(183.799,427.5,181.299,425.3,180.799,422),e.bezierVertex(180.6,420.8,180.499,419.5,180.399,418.1),e.bezierVertex(180.299,417,180.2,415.8,180.099,414.7),e.bezierVertex(177.199,390.5,156.699,371.3,132.M 399,370.2),e.bezierVertex(131.99,370.2,131.499,370.2,131.099,370.2),e.bezierVertex(130.699,370.2,130.299,370.2,129.799,370.2),e.bezierVertex(125.99,369.9,123.199,367.2,123.099,363.6),e.bezierVertex(122.99,360.2,125.799,357.3,129.599,356.9),e.bezierVertex(130.499,356.8,131.499,356.8,132.599,356.7),e.bezierVertex(133.199,356.7,133.799,356.7,134.399,356.6),e.vertex(138.299,356.4),e.vertex(139.1,352.6),e.bezierVertex(139.5,350.7,139.799,348.9,140.2,347),e.bezierVertex(140.899,343.4,141.5,340,142.399,336.8),e.bezierVertM ex(150.099,310.7,174.399,292,201.399,291.3),e.vertex(201.599,291.3),e.bezierVertex(203.699,291.3,206.299,292,208.299,293.2),e.bezierVertex(210.499,294.5,210.699,297.5,209.99,299.8),e.bezierVertex(209.499,301.5,208.199,303.9,203.299,304.7),e.bezierVertex(202.199,304.9,200.99,305,199.799,305.2),e.bezierVertex(194.499,305.9,188.99,306.599,183.799,308.9),e.bezierVertex(165.499,316.799,155.199,331.299,152.99,352),e.bezierVertex(152.399,357.8,154.499,361.7,159.699,364.5),e.bezierVertex(178.199,374.4,189.399,390,193.099,4M 10.9),e.bezierVertex(193.699,414.299,193.899,418,193.599,422),e.bezierVertex(193.399,425.2,190.899,427.5,187.399,427.5),e.vertex(187.2,427.5),e.endShape(),e.beginShape(),e.vertex(364.3,281.1),e.bezierVertex(346.3,280.6,332.9,272.8,323.5,257),e.bezierVertex(321.6,253.9,320.4,250.2,319.2,246.7),e.bezierVertex(317.7,242.2,315,239.799,310.5,238.799),e.bezierVertex(298.5,236.299,288,230.7,279.4,222.1),e.bezierVertex(276.7,219.4,274.9,215.299,278,211.9),e.bezierVertex(279.4,210.3,281,209.6,282.6,209.6),e.bezierVertex(284M .4,209.6,286.4,210.6,288.3,212.5),e.bezierVertex(297.8,221.8,310.4,226.9,323.9,226.9),e.bezierVertex(340.2,226.9,355.1,219.3,364.8,206.2),e.bezierVertex(371,197.8,374.2,188.5,374.5,178.5),e.vertex(374.5,177.9),e.bezierVertex(374.5,177,374.5,176.1,374.7,175.4),e.bezierVertex(375.3,171.8,377.9,169.5,381.3,169.5),e.bezierVertex(381.4,169.5,381.5,169.5,381.7,169.5),e.bezierVertex(385.4,169.7,388,172.4,388,176.1),e.bezierVertex(388.1,190.7,383.4,204,374.2,215.8),e.bezierVertex(365.8,226.5,354.7,233.9,341.2,237.9),e.beziM erVertex(340,238.3,338.7,238.6,337.3,239.1),e.bezierVertex(335.9,239.6,335.1,240.4,334.7,240.9),e.bezierVertex(334.599,241,334.5,241.1,334.4,241.2),e.vertex(331.799,243.6),e.vertex(333.199,246.8),e.bezierVertex(338.199,258,346.799,264.9,358.699,267.3),e.bezierVertex(360.199,267.6,361.599,267.7,362.99,267.9),e.bezierVertex(363.599,268,364.299,268,364.899,268.1),e.bezierVertex(369.099,268.6,371.799,271.4,371.499,275),e.bezierVertex(371.199,278.6,368.299,281.2,364.399,281.2),e.vertex(364.3,281.1),e.endShape(),e.beginSM hape(),e.vertex(323.9,437),e.bezierVertex(323.7,437,323.5,437,323.299,437),e.bezierVertex(319.599,436.7,317.299,434.1,317.4,430.2),e.bezierVertex(317.9,406.099,328.299,388,349.5,375),e.bezierVertex(350.7,374.2,352,373.5,353.4,372.8),e.bezierVertex(354.099,372.4,354.7,372.1,355.299,371.7),e.vertex(357.499,370.5),e.vertex(357.799,368),e.bezierVertex(360.4,346.6,345.199,323.7,323.9,317),e.bezierVertex(319.099,315.5,314.099,314.9,309.299,314.4),e.vertex(308.199,314.299),e.bezierVertex(305.99,314.099,300.799,312.9,300.8M 99,307.299),e.bezierVertex(300.99,303.499,303.899,300.9,308.099,300.9),e.vertex(308.299,300.9),e.bezierVertex(327.099,301.299,343.099,308.7,355.699,322.9),e.bezierVertex(364.299,332.5,369.399,344.099,370.99,357.299),e.bezierVertex(371.099,358.4,371.299,359.4,371.499,360.499),e.bezierVertex(371.599,360.99,371.699,361.499,371.799,361.99),e.vertex(372.499,365.899),e.vertex(377.899,366.199),e.bezierVertex(378.799,366.299,379.699,366.299,380.599,366.399),e.bezierVertex(385.099,366.699,387.899,369.399,387.799,373.299),e.M bezierVertex(387.699,377.099,384.99,379.599,380.799,379.799),e.bezierVertex(369.799,380.199,359.99,383.299,351.899,389.299),e.bezierVertex(338.799,398.799,331.699,411.699,330.699,427.499),e.vertex(330.699,428.299),e.bezierVertex(330.599,429.199,330.599,430.099,330.499,430.799),e.bezierVertex(330,434.7,327.5,437,323.9,437),e.endShape()}function T(e){return e[0].map(((t,n)=>e.map((e=>e[n]))))}function A(e){return e.map((e=>Array.isArray(e)?A(e):e))}function D(e,t){return floor(random(e,t))}function k(e){let t=0;for(cM onst n of e)t+=n[1];let n=random(t),r=0;for(const t of e)if(r+=t[1],n<r)return t[0];return null}function L(e){for(let t=1;t<e.length;++t){let n=D(0,t),r=e[t];e[t]=e[n],e[n]=r}}function P(e){return null==e||""===e}function O(e){return new Promise((t=>setTimeout(t,e)))}function F(e,t,n){let r=0;for(let i=1;i<=1e3;++i)for(let o=1;o<=1e3;++o)if(e*o%(t*i)==0){let e=1*i/o;abs(e-n)<abs(r-n)&&(r=e)}return r}function N(){let e=60*(new Date).getTimezoneOffset()*1e3;return new Date(Date.now()-e).toISOString().slice(0,-1)}funcM tion B(e,t,n){let r;if(push(),textSize(e),textWidth(t)<=n)r=t;else for(let e=0;e<t.length;++e){const i=t.slice(0,e+1)+"...";if(textWidth(i)>n){r=i;break}}return pop(),r}function Y(e){var t=e%10,n=e%100;return 1==t&&11!=n?e+"st":2==t&&12!=n?e+"nd":3==t&&13!=n?e+"rd":e+"th"}class G{constructor(e,t,n){this.n=t,this.m=n,this.mat=[];let r=0;for(let t=0;t<this.n;++t){this.mat.push([]);for(let n=0;n<this.m;++n)this.mat[t].push(r<e.length?e[r]:0),r+=1}return this}copy(){return new G(this.mat.flat(),this.n,this.m)}}class H{M static __linear=e=>e;static __relu=e=>Math.max(e,0);static __leaky_relu=e=>e>0?e:.2*e;static __sigmoid=e=>1/(1+Math.exp(-e));static __tanh=e=>Math.tanh(e);static __apply_unary_op(e,t){const n=e.copy();for(let e=0;e<n.n;++e)for(let r=0;r<n.m;++r)n.mat[e][r]=t(n.mat[e][r]);return n}static linear=e=>H.__apply_unary_op(e,H.__linear);static relu=e=>H.__apply_unary_op(e,H.__relu);static leaky_relu=e=>H.__apply_unary_op(e,H.__leaky_relu);static sigmoid=e=>H.__apply_unary_op(e,H.__sigmoid);static tanh=e=>H.__apply_unary_opM (e,H.__tanh);static __add=(e,t)=>e+t;static __mul=(e,t)=>e*t;static __apply_binary_op=(e,t,n)=>{"object"!=typeof t&&(t=new G([t],1,1));const r=e.copy();for(let e=0;e<r.n;++e)for(let i=0;i<r.m;++i)r.mat[e][i]=n(r.mat[e][i],t.mat[e%t.n][i%t.m]);return r};static mul=(e,t)=>H.__apply_binary_op(e,t,H.__mul);static add=(e,t)=>H.__apply_binary_op(e,t,H.__add);static matMul(e,t){const n=new G([],e.n,t.m);for(let r=0;r<n.n;++r)for(let i=0;i<n.m;++i)for(let o=0;o<e.m;++o)n.mat[r][i]+=e.mat[r][o]*t.mat[o][i];return n}static sM oftmax(e){const t=H.__apply_unary_op(e,(e=>Math.exp(e))),n=t.mat.flat().reduce(((e,t)=>e+t));for(let r=0;r<e.n;++r)for(let i=0;i<e.m;++i)t.mat[r][i]/=n;return t}}class ${constructor(e,t){this.scale=e,this.offset=t}forward(e){return H.add(H.mul(e,this.scale),this.offset)}}class X{constructor(){}forward(e){return e.map((e=>e.flat()))}}class W{constructor(e,t,n,r){this.out_dim=e,this.activation=t,this.w=n,this.b=r}forward(e){const t=H.add(H.matMul(e,this.w),this.b);return null==this.activation?t:this.activation(t)}}clM ass U{constructor(e,t,n){this.preprocessLayers=e,this.hiddenLayers=t,this.outputLayer=n,this.totalNeurons=this.hiddenLayers.map((e=>e.out_dim)),this.currentOrders=[],this.currentIteration=null}updateNeurons(e,t){if(t!=this.currentIteration){this.currentOrders=[];for(let e=0;e<this.totalNeurons.length;++e){randomSeed(100*(t+1)+e);const n=[];for(let t=0;t<this.totalNeurons[e];++t)n.push(t);L(n),this.currentOrders.push(n)}this.currentIteration=t}const n=A(this.totalNeurons),r=n.reduce(((e,t)=>e+t))*(1-e);for(let e=0;eM <r;++e){const t=n.map(((e,t)=>(e-1)/this.totalNeurons[t]));n[t.map(((e,t)=>[e,t])).reduce(((e,t)=>t[0]>e[0]?t:e))[1]]-=Math.min(r-e,1)}this.neuronsLife=[];for(let e=0;e<n.length;++e){const t=this.currentOrders[e],r=Array(this.totalNeurons[e]).fill(0);for(let i=0;i<n[e];++i)r[t[i]]=Math.min(n[e]-i,1);this.neuronsLife.push(r)}}getTotalNeurons(){return A(this.totalNeurons)}getNeuronsLife(){return A(this.neuronsLife)}forward(e){for(const t of this.preprocessLayers)e=t.forward(e);for(const[t,n]of this.hiddenLayers.entriM es()){e=n.forward(e);const r=new G(this.neuronsLife[t],1,e.m);e=H.mul(e,r)}return e=this.outputLayer.forward(e),H.softmax(e)}}function q(e){switch(e){case"relu":return H.relu;case"sigmoid":return H.sigmoid;case"tanh":return H.tanh;case"leaky_relu":return H.leaky_relu;default:return H.linear}}function j(e,t){const n=[],r=[],i=Z(t);let o=null,a=0,l=[];for(const t of e.config.layers)if("InputLayer"==t.class_name)o=t.config.batch_input_shape.slice(1),l=o;else if("Rescaling"==t.class_name)n.push(new $(t.config.scale,t.cM onfig.offset));else if("Flatten"==t.class_name)o=[o.reduce(((e,t)=>e*t))];else if("Dense"==t.class_name){const e=[t.config.units],n=o[0]*e[0],l=e[0],s=i.subarray(a,a+n);a+=n;const h=i.subarray(a,a+l);a+=l;const c=new G(s,o[0],e[0]),u=new G(h,1,e[0]),f=q(t.config.activation);r.push(new W(e[0],f,c,u)),o=e}const s=r.pop();return{model:new U(n,r,s),inputDim:l}}function Z(e){const t=window.atob(e),n=t.length/Float32Array.BYTES_PER_ELEMENT,r=new DataView(new ArrayBuffer(Float32Array.BYTES_PER_ELEMENT)),i=new Float32ArrayM (n);let o=0;for(let e=0;e<n;e++){o=4*e;for(let e=0;e<4;++e)r.setUint8(e,t.charCodeAt(o+e));i[e]=r.getFloat32(0,!0)}return i}class K{constructor(e){this.elt=e,this._events={},this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight}position(){if(0===arguments.length)return{x:this.elt.offsetLeft,y:this.elt.offsetTop};var e="absolute";return"static"!==arguments[2]&&"fixed"!==arguments[2]&&"relative"!==arguments[2]&&"sticky"!==arguments[2]&&"initial"!==arguments[2]&&"inherit"!==arguments[2]||(e=arguments[2]),tM his.elt.style.position=e,this.elt.style.left=arguments[0]+"px",this.elt.style.top=arguments[1]+"px",this.x=arguments[0],this.y=arguments[1],this}show(){return this.elt.style.display="block",this}hide(){return this.elt.style.display="none",this}size(e,t){if(0===arguments.length)return{width:this.elt.offsetWidth,height:this.elt.offsetHeight};var n=e,r=t;if(n!==te||r!==te){if(n===te?n=t*this.width/this.height:r===te&&(r=e*this.height/this.width),this.elt instanceof HTMLCanvasElement){var i,o={},a=this.elt.getContext("M 2d");for(i in a)o[i]=a[i];for(i in this.elt.setAttribute("width",n*this._pInst._pixelDensity),this.elt.setAttribute("height",r*this._pInst._pixelDensity),this.elt.style.width=n+"px",this.elt.style.height=r+"px",this._pInst.scale(this._pInst._pixelDensity,this._pInst._pixelDensity),o)this.elt.getContext("2d")[i]=o[i]}else this.elt.style.width=n+"px",this.elt.style.height=r+"px",this.elt.width=n,this.elt.height=r;this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight,this._pInst&&this._pInst._curElement&&tM his._pInst._curElement.elt===this.elt&&(this._pInst._setProperty("width",this.elt.offsetWidth),this._pInst._setProperty("height",this.elt.offsetHeight))}return this}style(e,t){if(t instanceof Color&&(t="rgba("+t.levels[0]+","+t.levels[1]+","+t.levels[2]+","+t.levels[3]/255+")"),void 0===t){if(-1===e.indexOf(":"))return window.getComputedStyle(this.elt).getPropertyValue(e);for(var n=e.split(";"),r=0;r<n.length;r++){var i=n[r].split(":");i[0]&&i[1]&&(this.elt.style[i[0].trim()]=i[1].trim())}}else if(this.elt.style[e]M =t,"width"===e||"height"===e||"left"===e||"top"===e){var o=window.getComputedStyle(this.elt).getPropertyValue(e).replace(/[^\d.]/g,"");this[e]=Math.round(parseFloat(o,10))}return this}value(){return arguments.length>0?(this.elt.value=arguments[0],this):"range"===this.elt.type?parseFloat(this.elt.value):this.elt.value}mouseClicked(e){return this._adjustListener("click",e,this),this}isFocused(){return document.activeElement===this.elt}_adjustListener(e,t,n){return!1===t?this._detachListener(e,n):this._attachListener(M e,t,n),this}_attachListener(e,t,n){n._events[e]&&this._detachListener(e,n);var r=t.bind(n);n.elt.addEventListener(e,r,!1),n._events[e]=r}_detachListener(e,t){var n=t._events[e];t.elt.removeEventListener(e,n,!1),t._events[e]=null}}function J(e,t){var n=document.createElement("button");return n.innerHTML=e,t&&(n.value=t),ee(n)}function Q(e){var t=arguments.length>1&&void 0!==arguments[1]&&arguments[1],n=function(t){var n=!0,r=!1,i=void 0;try{for(var o,a=t.target.files[Symbol.iterator]();!(n=(o=a.next()).done);n=!0){vM ar l=o.value;File._load(l,e)}}catch(e){r=!0,i=e}finally{try{n||null==a.return||a.return()}finally{if(r)throw i}}};if(window.File&&window.FileReader&&window.FileList&&window.Blob){var r=document.createElement("input");return r.setAttribute("type","file"),t&&r.setAttribute("multiple",!0),r.addEventListener("change",n,!1),ee(r)}}function ee(e){return document.body.appendChild(e),new K(e)}createImg=function(){var e,t=document.createElement("img"),n=arguments;return n.length>1&&"string"==typeof n[1]&&(t.alt=n[1]),n.lengM th>2&&"string"==typeof n[2]&&(t.crossOrigin=n[2]),t.src=n[0],e=ee(t,this),t.addEventListener("load",(function(){e.width=t.offsetWidth||t.width,e.height=t.offsetHeight||t.height;var r=n[n.length-1];"function"==typeof r&&r(e)})),e},createInput=function(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:"",t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:"text",n=document.createElement("input");return n.setAttribute("value",e),n.setAttribute("type",t),ee(n,this)};const te="auto";function ne(e){re(eM );const t=e._rectMode;e.rectMode(CORNER),e.rect(0,0,e.width,e.height),e.rectMode(t),ie(e)}function re(e){e.push(),e.fill(255,255,255,255),e.blendMode(REMOVE)}function ie(e){e.blendMode(BLEND),e.pop()}File=function(e,t){this.file=e,this._pInst=t;var n=e.type.split("/");this.type=n[0],this.subtype=n[1],this.name=e.name,this.size=e.size,this.data=void 0},File._createLoader=function(e,t){var n=new FileReader;return n.onload=function(n){var r=new File(e);if("application/json"===r.file.type)r.data=JSON.parse(n.target.resM ult);else if("text/xml"===r.file.type){var i=(new DOMParser).parseFromString(n.target.result,"text/xml");r.data=new XML(i.documentElement)}else r.data=n.target.result;t(r)},n},File._load=function(e,t){if(/^text\//.test(e.type)||"application/json"===e.type)File._createLoader(e,t).readAsText(e);else if(/^(video|audio)\//.test(e.type)){var n=new File(e);n.data=URL.createObjectURL(e),t(n)}else File._createLoader(e,t).readAsDataURL(e)},XML=function(e){if(e)this.DOM=e;else{var t=document.implementation.createDocument(nulM l,"doc");this.DOM=t.createElement("root")}},document.addEventListener("DOMContentLoaded",(function(){addEventListener("mousemove",(e=>{window.mouseX=e.pageX,window.mouseY=e.pageY}))})),new e("global");const oe="423";let ae,le,se,he,ce,ue,fe,de,xe,ge,pe,me,be,ye,we,ve,ze,Ve,_e,Me,Ee,Se,Re,Ie,Ce,Te,Ae,De,ke,Le,Pe,Oe,Fe,Ne,Be,Ye,Ge,He,$e,Xe,We,Ue,qe,je,Ze,Ke,Je,Qe,et,tt,nt,rt,it,ot,at,lt,st,ht,ct,ut,ft,dt,xt,gt,pt,mt,bt,yt,wt,vt,zt,Vt,_t,Mt,Et,St,Rt,It,Ct,Tt,At=!1,Dt=!1,kt=!0,Lt=!1,Pt=!1;const Ot=[" ","Growing","StablM e","Decaying","Dead","Rebirth"];let Ft,Nt,Bt,Yt,Gt,Ht,$t,Xt,Wt,Ut,qt,jt,Zt,Kt,Jt,Qt,en,tn,nn,rn,on,an,ln,sn,hn=0,cn=0,un=0,fn=!1,dn=!0,xn=!0,gn=null,pn=null,mn=null,bn=!1,yn=!1,wn=null,vn=null,zn=!1;async function setup(){let e=windowWidth,t=windowHeight;createCanvas(e,t),et=createGraphics(e,t),Xe=createGraphics(e,t),$e=createGraphics(e,t),We=createGraphics(e,t),Ue=createGraphics(e,t),qe=createGraphics(e,t),Qe=createGraphics(e,t),je=createGraphics(e,t),Ze=createGraphics(e,t),Ke=createGraphics(e,t),Je=createGraphicsM (e,t),tt=createGraphics(500,500),nt=createGraphics(500,500),rt=createGraphics(500,500),_n(),Mn(),Sn(),await En(),Gn(),Rn(),bn=!0}function _n(){Et=parseInt(oe),randomSeed(Et),noiseSeed(Et)}function Mn(){Wt=Ir(p.training_traits),Cr(Wt)}async function En(){let e;Jt=r(),Qt=o(),[Xt,e]=await Promise.all([s(Jt),h(Qt)]),Ut=new V(Wt.visual,e.layers_config,e.weight_b64),Ut.updateAge(new Date),_n(),Wt.training=e.training_traits,Ht=e.model_name,$t=e.classes_name}function Sn(){le=min(width,height)/1024,ut=Rr.findIndex((e=>e[0]=M ==Wt.visual.colorPalette)),ft=[["#ffffff","#231f20","#231f20"],["#231f20","#ffffff","#ffffff"],["#104da8","#ffffff","#ffffff"],["#722F1F","#FCE1B2","#FCE1B2"],["#e88120","#f9f2e5","#f9f2e5"],["#f6b941","#2E2E2E","#2E2E2E"],["#45daaa","#012221","#012221"],["#F1F1F1","#328DFE","#328DFE"],["#111822","#D3EB8D","#D3EB8D"],["#713FF9","#D6D5E6","#D6D5E6"],["#FBDA9D","#795106","#795106"],["#8f5b62","#ead0d0","#ead0d0"],["#eae4cb","#508cac","#508cac"],["#ffc6cc","#cc313d","#cc313d"],["#60A900","#E0FE00","#E0FE00"],["#507DBEM ","#D0D1D3","#D0D1D3"],["#305848","#E8F2EE","#E8F2EE"],["#2a2634","#5b6988","#cb78a2","#5b6988"],["#590e29","#fd5e53","#fd5e53","#ffe373"],["#0a141d","#57d4e4","#328195","#2A9ECF","#0ab6a8","#57d4e4"],["#3a2d28","#d5c2ac","#df6338","#3d9895","#d5c2ac"],["#030706","#77c4d9","#77c4d9","#77c4d9","#ffffff","#ffffff","#e72020","#e72020"],["#3a4664","#92f5ff","#f9ff94","#eaa0a2","#55dde0"],["#fbfaff","#f04bb1","#f04bb1","#fac373","#82cef0","#8b31ce"],["#000000","#ffffff","#ff0002","#f26522","#fdff00","#00ff03","#01fffe",M "#0000ff","#ff00ff"]];for(let e=0;e<ft.length;++e)for(let t=0;t<ft[e].length;++t)ft[e][t]=cr(ft[e][t]);pt=[],ct=ft[ut][0],st=ft[ut][1]}function Rn(){gn=document.querySelector("#upload"),pn=document.querySelector("#inputUpload"),gn.addEventListener("dblclick",(()=>{if(!Lt&&!yn)if(In(Ie)&&cn==Ve-1)pn.click();else{if(4!=Pe&&5!=Pe&&(In(Ie)||cn!=Ve-1))return;fn=!0,dn=!0,Bt=0,un=0}})),pn.addEventListener("click",(()=>{pn.value=null,gn.style.display="block"})),pn.addEventListener("change",(()=>{const[e]=pn.files;e?(se=nulM l,gn.style.display="none",Tn(URL.createObjectURL(e)),mn=e):gn.style.display="block"}))}function In(e){for(let t=0;t<e.length;++t){let n=0;for(let r=0;r<e[t].length;++r)e[t][r]>0&&++n;if(0==n)return!1}return!0}function Cn(){null!=se&&(un=0,Pt=!0,he=0,ue=0,drewLineAnim=!0,ce=(ae/2+we/2)/le,loadImage(se.elt.src,(e=>{const[t,n,r]=Gt,i=createGraphics(t,n);i.image(e,0,0,t,n),i.loadPixels();const o=i.pixels.filter(((e,t)=>t%4!=3)),a=Ut.classifyImage(o);Zt=T([a,$t.map((e=>e.toUpperCase()))]).sort(((e,t)=>e[0]>t[0]?-1:1))})M ))}function Tn(e){se=createImg(e,""),se.hide(),Cn()}function An(){zn||(ce+=(width-ae-we)/tn/le),re(Xe),Xe.rect(ce*le,0,width,height),ie(Xe),un>=ge&&1==kt&&(kt=!1,un-=ge),kt&&(re($e),$e.strokeWeight(2*Fe),Jn(he,ze,ct,ct,$e),ie($e)),un>=ge&&0==kt&&(kt=!0,un-=ge,he+=1,he==en&&(++ue,he=0,ce=(ae/2+we/2)/le,1==ue&&(Pt=!1,Dn(),ye=millis())))}function Dn(){At=!0,pe=!1,me=!1,tryButton=br("Try Again",width/2-225*le,height/2+265*le,290*le,40*le,kn),closeResultButton=br("Close",width/2+75*le,height/2+265*le,150*le,40*le,Ln)}fuM nction kn(){At=!1,tryButton.hide(),closeResultButton.hide(),pn.click()}function Ln(){Yt=!0,At=!1,Gn(),tryButton.hide(),closeResultButton.hide(),gn.style.display="block",se=null}function keyTyped(){bn&&!1===yn&&!1===yr()&&("i"!==key&&"I"!==key||(Dt=!Dt),"b"!==key&&"B"!==key||(xn=!xn),"s"!==key&&"S"!==key||!1!==Lt||saveCanvasAtCurrentTime(),"k"!==key&&"K"!==key||!1!==Lt||save4KCanvasAtCurrentTime(),"u"!==key&&"U"!==key||!1!==Lt||!1!==At||!1!==fn||!1!==Pt||On())}function On(){Lt=!0,wn=null,vn=null,submitButton=br("SubM mit",width/2-155*le,height/2+115*le,150*le,40*le,Fn),closeSettingButton=br("Close",width/2+5*le,height/2+115*le,150*le,40*le,Yn),vt=createInput(),vt.position(width/2-252.5*le,height/2-40*le),vt.size(500*le,25*le),vt.style("font-size","15px"),vt.value(Jt||""),zt=createInput(),zt.position(width/2-252.2*le,height/2+35*le),zt.size(500*le,25*le),zt.style("font-size","15px"),zt.value(Qt||"")}function Fn(){Vt=vt.value(),_t=zt.value(),submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide(),Lt=!1,yn=!0,Nn()}async M function Nn(){[wn,vn,_]=await Promise.all([c(Vt),u(_t),O(1e3)]),yn=!1,wn&&vn?(n(Vt),i(_t),window.location.reload()):(Lt=!0,submitButton.show(),closeSettingButton.show(),vt.show(),zt.show())}function Bn(){Je.textFont("Trebuchet MS"),Je.noStroke(),pr(Je,600*le,200*le),Je.strokeWeight(1*le),Je.stroke(xt),Je.fill(xt),Je.textSize(50*le),Je.text("update()",width/2,height/2+2.5*le)}function Yn(){wn=null,vn=null,Lt=!1,submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide()}function Gn(){_n(),nn=Date.now(),pe=!1,mM e=!1,St=Wt.training.structure_gen,Rt=Wt.visual.birthYear,It=Wt.visual.lifeCycle,Ct=Wt.training.epoch_num,Tt=Wt.training.activation_func,Ft=Mr.findIndex((e=>e[0]==Wt.visual.hardwareAcceleration))+1,1==Ft?(Nt=30,fe=40):2==Ft?(Nt=15,fe=20):(Nt=2,fe=10);const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statM ePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),ae=100*le,ht=50*le,Oe=Sr.findIndex((e=>e[0]==Wt.visual.nodeShape))+1,dt=Er.findIndex((e=>e[0]==Wt.visual.nodeFill))+1,lt=_r.findIndex((e=>e[0]==Wt.visual.pattern))+1,de=Math.tanh(Math.log10(Xt.avgfeerate)),de=map(de,0,1,.2,.8),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)GM e.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.puM sh(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*DM e.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,at=.7,pt=[],xt=ft[ut][2],gt=ft[ut][ft[ut].length-1];for(let e=3;e<ft[ut].length-1;e++)pt.push(ft[ut][e]);mt=sr(xt,gt,pt,width),bt=[],wt=[],yt=width/(Ve-1);for(let e=0;e<Ve;e++)bt.push(hr(mt,yt*e/width)),wt.push(hr(mt,yt*e/width));wt.unshift(bt[0]),wt.push(bt[bt.length-1]),hn=0,cn=0,un=0,Yt=!0;const n={xLeft:ae/8,xRight:width-ae/8,yTop:ae/8,yBottom:height-ae/8},r=Ce.map((e=>e.length));jt=new RM (bt,r,n,Oe,le)}function Hn(e,t){let n=Ce[e].length;return[e*we+we/2+ae/2,height/2-(n-1)/2*ve+t*ve]}function $n(e,t){le=min(e,t)/1024,ae=100*le,ht=50*le,we=(e-ae)/Ve,ve=(t-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}xe=floor(De.length*de),Le=[],ke=[],ge=floor(map(de,.2,.8,15,2));for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,M 1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,mt=sr(xt,gt,pt,e),bt=[],wt=[],yt=e/(Ve-1);for(let t=0;t<Ve;t++)bt.push(hr(mt,yt*t/e)),wt.push(hr(mt,yt*t/e));wt.unshift(bt[0]),wt.push(bt[bt.length-1])}function Xn(){const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextStaM te=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<IeM .length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){letM t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le}function Wn(){jt.update();const e=4==Pe?0:Kt;jt.draw(Qe,ct,dt,e,le)}function Un(){if(!bn)return ar(),void et.image(je,0,0);if(4==M Pe||5==Pe)return Wn(),void et.image(Qe,0,0);un>=Nt&&hn<Ve&&(hn++,un=0);for(let e=0;e<hn;e++)1==dt?it=ot=bt[e]:(it=ct,ot=bt[e]),Kn(e,it,ot,$e);un>=Nt&&cn<Ve-1&&(cn++,un=0);for(let e=0;e<cn;e++)Zn(e)}function qn(){et.background(ct),Ue.background(255),Ue.rectMode(CENTER),ne(Ue),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),Ue.stroke(st),Ue.strokeWeight(8*le),Ue.fill(ct),Qe.background(255),Qe.rectMode(CENTER),ne(Qe),Qe.strokeWeight(le),qe.background(255),qe.rectMode(CENTER),ne(qe),qe.textAlign(LEFT),$e.background(255)M ,$e.rectMode(CENTER),ne($e),Xe.background(255),ne(Xe),Xe.strokeWeight(Ne),We.background(255),We.rectMode(CENTER),ne(We),We.fill(st),We.stroke(st),We.strokeWeight(.1*le),er(lt),We.noStroke(),xn&&(We.rect(ae/16,height/2,ae/8,height),We.rect(width-ae/16,height/2,ae/8,height),We.rect(width/2,ae/16,width,ae/8),We.rect(width/2,height-ae/16,width,ae/8)),Ze.background(255),Ze.rectMode(CENTER),ne(Ze),Ze.textAlign(CENTER,CENTER),Ze.textStyle(BOLD),Ze.stroke(st),Ze.strokeWeight(8*le),Ze.fill(ct),je.background(255),je.rectModeM (CENTER),ne(je),je.textAlign(CENTER,CENTER),je.textStyle(BOLD),Ke.background(255),Ke.rectMode(CENTER),ne(Ke),Ke.textAlign(CENTER,CENTER),Ke.textStyle(BOLD),Ke.stroke(st),Ke.strokeWeight(8*le),Ke.fill(ct),Je.background(255),Je.rectMode(CENTER),ne(Je),Je.textAlign(CENTER,CENTER),Je.textStyle(BOLD),Je.stroke(st),Je.strokeWeight(8*le),Je.fill(ct),Un(),et.image(We,0,0),Pt&&An(),et.image(Xe,0,0),et.image($e,0,0),At&&(tr(),et.image(Ue,0,0)),fn&&(lr(),et.image(Ze,0,0)),Lt&&(or(),et.image(Ke,0,0)),Dt&&(ir(),et.image(qe,0,0)M ),yn&&(Bn(),et.image(Je,0,0))}function draw(){const e=Date.now();bn&&(Ut.updateAge(new Date(e)),Xn()),qn(),image(et,0,0),zn||un++}function Zn(e){let t,n=Ce[e].length,r=Ce[e+1].length;for(let i=0;i<n;i++){const[n,o]=Hn(e,i);for(let a=0;a<r;a++){const[r,l]=Hn(e+1,a);t=map(min(Ce[e][i],Ce[e+1][a]),0,1,0,.5),ur(n,o,r,l,bt[e],bt[e+1],Xe,t)}}}function Kn(e,t,n,r){let i,o,a,l=Ce[e].length;for(let s=0;s<l;s++){const[l,h]=Hn(e,s);i=Ce[e][s],a=map(Be,1/30,1,3,10),o=map(Ce[e][s],0,1,2*a,0)*le,o<1.5*le&&(o=0),Qn(l,h,ze,Oe,t,n,M o,i,r)}}function Jn(e,t,n,r,i){for(let o=0;o<Le[e].length;o++)Qn(Le[e][o][0],Le[e][o][1],t,Oe,n,r,0,1,i)}function Qn(e,t,n,r,i,o,a,l,s){s.stroke(dr(o,map(l,0,1,.25,1))),s.fill(dr(i,map(l,0,1,.15,1))),s.strokeWeight(Fe),fr([a],s),3==dt&&s.fill(dr(i,0)),1==r?s.ellipse(e,t,n):2==r?s.rect(e,t,7*n/8,7*n/8):3==r&&(s.beginShape(),s.vertex(e-4*n/7,t),s.vertex(e,t-4*n/7),s.vertex(e+4*n/7,t),s.vertex(e,t+4*n/7),s.endShape(CLOSE))}function er(e){if(1==e);else if(2==e){We.strokeWeight(1*le);for(let e=ht/4;e<width+ht/4;e+=ht)foM r(let t=ht/4;t<height+ht/4;t+=ht)We.point(e,t)}else if(3==e){ht=25*le;for(let e=ht/2;e<height+ht/2;e+=ht)We.line(0,e,width,e);for(let e=ht/2;e<width+ht/2;e+=ht)We.line(e,0,e,height)}}function tr(){Ue.textFont("Trebuchet MS"),Ue.textAlign(LEFT,CENTER),Ue.noStroke(),pr(Ue,800*le,500*le),Ue.noStroke(),Ue.fill(dr(st,.75)),Ue.rect(width/2,height/2-100*le,800*le,300*le,25*le,25*le,0,0),Ue.fill(st),Ue.rect(width/2-250*le,height/2-100*le,225*le,225*le),Ue.image(se.elt,width/2-357.5*le,height/2-207.5*le,215*le,215*le);let eM =100*Zt[0][0];Ue.fill(ct),Ue.textSize(25*le),Ue.textStyle(NORMAL),1==me&&(e>=0&&e<20?Ue.text("I have a feeling this image belongs to",width/2-100*le,height/2-170*le):e>=20&&e<40?Ue.text("I have a hunch this image belongs to",width/2-100*le,height/2-170*le):e>=40&&e<60?Ue.text("I think this image belongs to",width/2-100*le,height/2-170*le):e>=60&&e<80?Ue.text("I'm almost certain this image belongs to",width/2-100*le,height/2-170*le):Ue.text("I'm positive this image belongs to",width/2-100*le,height/2-170*le));let t=M e.toFixed(2);"100.00"==t&&(t="100"),1==me&&Ue.text("I'm "+t+"% confident that I'm right!",width/2-100*le,height/2-25*le),example=Zt.map((e=>e[1])),be=Ue.textWidth('"FIDENZAAAA"'),defaultPhrase=Ue.textWidth('"PERPENDICULAR INHABITATION"'),Ue.textStyle(BOLD);const n=me?example[0]:random(example);if(1===n.split(" ").length){let e=75*be/Ue.textWidth('"'+n+'"');e>75&&(e=75),Ue.textSize(e*le),Ue.text('"'+n+'"',width/2-100*le,height/2-90*le)}else nr(width/2-100*le,height/2-90*le,460*le,110*le,n,Ue);if(millis()-ye>1500&&(mM e=!0),C(tt,nt,st,ct,Pe,Mt),Ue.image(nt,width/2-370*le,height/2+70*le,80*le,80*le),3==Pe){let e;e=map(Mt,50,60,.25,1.3),I(rt,e),Ue.image(rt,width/2-370*le,height/2+70*le,80*le,80*le)}let r,i;Ue.image(tt,width/2-370*le,height/2+70*le,80*le,80*le),Ue.fill(xt),Ue.textSize(40*le),Ue.text("INTELLIGENCE INFO",width/2-275*le,height/2+115*le),Ue.textSize(18*le),Ue.textStyle(NORMAL),Ue.circle(width/2-360*le,height/2+180*le,7.5*le),1==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s growing and getting smarter by tM he day.`:2==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s stable and it has reached peak performance.`:3==Pe&&(r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s decaying and losing its luster.`),i=2==Pe?"The Perceptron remains stable for some time before entering the decay phase.":`Wait until ${new Date(an).toLocaleString("en-US")} for your Perceptron to reach its peak performance.`,Ue.text(r,width/2-350*le,height/2+180*le),Ue.circle(width/2-360*le,height/2+210*le,7.5*le),Ue.text(i,width/2-350*M le,height/2+210*le),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),gr(Ue,width/2-225*le,width/2+65*le,height/2+265*le,height/2+305*le,"SELECT ANOTHER IMAGE"),gr(Ue,width/2+75*le,width/2+225*le,height/2+265*le,height/2+305*le,"CLOSE")}function nr(e,t,n,r,i,o){let a=i.split(" "),l=75*be/o.textWidth('"'+i+'"'),s=0,h=[],c=[],u=[],f="",d="";if(l>=50)l>75&&(l=75),o.textSize(l*le),o.text('"'+i+'"',e,t);else if(l<50){if(l=50*defaultPhrase/o.textWidth('"'+i+'"'),l>30){if(l>50&&(l=50),[f,d]=rr(l,n,s,h,c,a,f,d,Ue),0==c.lengthM )return o.textSize(l*le),void o.text('"'+i+'"',e,t);for(s=0,h=[],c=[];o.textWidth(d)>n/le;)l=l*n/le/o.textWidth(d),f="",d="",[f,d]=rr(l,n,s,h,c,a,f,d,Ue)}else{l=30,o.textSize(l);for(let e=0;e<a.length;e++)s+=o.textWidth(" "+a[e]),s<=n/le?h.push(a[e]):s>n/le&&s<=n/le*2?c.push(a[e]):u.push(a[e]);for(let e=1;e<h.length;e++)f=f+" "+h[e];if(f='"'+h[0]+f,0==u.length){for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+c[c.length-1]+'"'}else if(1==c.length)d="... "+u[u.length-1]+'"';else{for(let e=0;e<c.length-1;e++)d=d+c[e]+" M ";d=d+"... "+u[u.length-1]+'"'}}o.textSize(l*le);let r=1.25*(o.textDescent()+o.textAscent());o.text(f,e,t-r/2),o.text(d,e,t+r/2)}}function rr(e,t,n,r,i,o,a,l,s){s.textSize(e);for(let e=0;e<o.length;e++)(n+=s.textWidth(" "+o[e]))<=t/le?r.push(o[e]):i.push(o[e]);for(let e=1;e<r.length;e++)a=a+" "+r[e];if(a='"'+r[0]+a,0==i.length&&(a+='"',l=""),1==i.length)l=i[i.length-1]+'"';else{for(let e=0;e<i.length-1;e++)l=l+i[e]+" ";l=l+i[i.length-1]+'"'}return[a,l]}function ir(){const e=45*le;qe.textFont("Tahoma"),qe.stroke(st)M ,qe.strokeWeight(2*le),qe.fill(ct),qe.rect(width/2,e/2+height-87.5*le,600*le,90*le),qe.fill(st),qe.rect(width/2-150*le,e+height-170*le,300*le,30*le),qe.fill(ct),qe.rect(width/2+150*le,e+height-170*le,300*le,30*le),qe.noStroke(),qe.fill(ct),qe.textSize(15*le),qe.textStyle(BOLD),qe.text("PERCEPTRON INFORMATION",width/2-285*le,e+height-165*le),qe.fill(xt),qe.text("ARTWORK NAME:",width/2+10*le,e+height-165*le),qe.textAlign(RIGHT),qe.textStyle(ITALIC),qe.text("Perceptron #"+Et,width/2+285*le,e+height-165*le);const[t,n]=M It.split(" ");let r;"60 Years"===It?r="1 Year":"60 Months"===It?r="1 Month":"60 Weeks"===It?r="1 Week":"60 Days"===It?r="1 Day":"12 Hours"===It&&(r="12 Minutes"),data=[["AI MODEL NAME:",B(12*le,Ht,140*le)],["SCALE:","1:"+Te],["NUMBER OF CLASSES:",$t.length],["BIRTH YEAR:",Rt],["NUMBER OF REBIRTHS:",sn.toString()],["AGE:",`${Math.ceil(Mt)} Perceptron Years`],["ONE PERCEPTRON YEAR:",`${r}`],["STATE:",Ot[Pe]],["ACTIVE NEURONS:",`${round(ln*rn)} / ${ln}`],["NEXT STATE TIME:",vr(new Date(on))]],qe.fill(xt);const i=data.M length/2;for(let t=0;t<data.length;++t){const n=t<i,r=n?width/2-285*le:width/2+10*le,o=n?width/2-10*le:width/2+285*le,a=e+height-(135-t%i*15)*le;qe.textStyle(BOLD),qe.textAlign(LEFT),qe.textSize(12*le),qe.text(data[t][0],r,a),qe.textStyle(ITALIC),qe.textAlign(RIGHT),qe.textSize(12*le),qe.text(data[t][1],o,a)}}function or(){Ke.textFont("Trebuchet MS"),Ke.noStroke(),pr(Ke,600*le,200*le),gr(Ke,width/2-155*le,width/2-5*le,height/2+115*le,height/2+155*le,"UPDATE"),gr(Ke,width/2+5*le,width/2+155*le,height/2+115*le,heightM /2+155*le,"CLOSE"),Ke.textAlign(LEFT),Ke.fill(xt),Ke.text("UPDATE BITCOIN FULL NODE ADDRESS",width/2-252.5*le,height/2-55*le),Ke.text("UPDATE MODEL ADDRESS",width/2-252.5*le,height/2+20*le),Ke.textAlign(RIGHT),Ke.textStyle(ITALIC),Ke.textSize(15*le),0==wn&&Ke.text("(*) Invalid Address",width/2+252.5*le,height/2-53*le),0==vn&&Ke.text("(*) Invalid Model",width/2+252.5*le,height/2+23*le)}function ar(){je.textFont("Trebuchet MS"),je.fill(st),je.textSize(50*le),je.stroke(st),je.strokeWeight(1*le),je.text("main()",width/M 2,height/2)}function lr(){un>=20&&1==dn&&(dn=!1,un=0),dn&&(Ze.textFont("Trebuchet MS"),Ze.stroke(st),Ze.fill(ct),Ze.rect(width/2,height/2,600*le,150*le,25*le),Ze.fill(xt),Ze.textSize(75*le),Ze.noStroke(),1==Pe?Ze.text("GROWING",width/2,height/2+5*le):3==Pe?Ze.text("AGING",width/2,height/2+5*le):4==Pe?Ze.text("DEAD",width/2,height/2+5*le):5==Pe&&Ze.text("BIRTH",width/2,height/2+5*le)),un>=20&&0==dn&&(dn=!0,un=0,Bt++,3==Bt&&(fn=!1))}function sr(e,t,n,r){let i=[],o=r/(n.length+1),a=color(e),l=color(t);i.push(a);for(leM t e=0;e<n.length;e++){let t=color(n[e]);for(let e=1;e<=o;e++){let n=lerpColor(a,t,e/o);i.push(n)}a=t}for(let e=1;e<o;e++){let t=lerpColor(a,l,e/o);i.push(t)}if(i.push(l),i.length>r)i.splice(r);else if(i.length<r){let e=i[i.length-1];for(;i.length<r;)i.push(e)}return i}function hr(e,t){let n=e.length,r=Math.floor(t*n);return r>=n&&(r=n-1),e[r]}function cr(e){e=e.replace("#","");var t=parseInt(e,16);return color(t>>16&255,t>>8&255,255&t)}function ur(e,t,n,r,i,o,a,l){var s=a.drawingContext.createLinearGradient(e,t,n,rM );s.addColorStop(0,i),s.addColorStop(1,o),a.drawingContext.strokeStyle=s,a.drawingContext.globalAlpha=l,a.line(e,t,n,r),a.drawingContext.globalAlpha=1}function fr(e,t){t.drawingContext.setLineDash(e)}function dr(e,t){let n=color(e),r=red(n),i=green(n),o=blue(n);return color(r,i,o,255*t)}function xr(e,t,n,r){return mouseX>e&&mouseX<t&&mouseY>n&&mouseY<r}function gr(e,t,n,r,i,o){e.strokeWeight(1*le),e.stroke(st);const[a,l]=xr(t,n,r,i)?[xt,ct]:[ct,xt];e.fill(a),e.push(),e.rectMode(CORNERS),e.rect(t,r,n,i,5*le),e.pop()M ,e.noStroke(),e.textSize(20*le),e.fill(l),e.text(o,(t+n)/2,(46*r+54*i)/100)}function pr(e,t,n){e.fill(0,0,0,75),e.rect(width/2,height/2,width,height),e.stroke(st),e.fill(ct),e.rect(width/2,height/2,t,n,25*le)}function mr(e,t){resizeCanvas(e,t,!0),Xe.resizeCanvas(e,t,!0),$e.resizeCanvas(e,t,!0),We.resizeCanvas(e,t,!0),Ue.resizeCanvas(e,t,!0),qe.resizeCanvas(e,t,!0),Qe.resizeCanvas(e,t,!0),je.resizeCanvas(e,t,!0),Ze.resizeCanvas(e,t,!0),Ke.resizeCanvas(e,t,!0),Je.resizeCanvas(e,t,!0),et.resizeCanvas(e,t,!0)}function M br(e,t,n,r,i,o){const a=J(e);return a.position(t,n),a.size(r,i),a.style("opacity","0"),a.mouseClicked(o),a}function yr(){return null!=vt&&vt?.isFocused()||null!=zt&&zt?.isFocused()}function wr(e,t,n,r){let i;if(e<=3){i=`Hey ${String.fromCodePoint(128075)}, I'm ${n}, ${t} years old. I can detect ${r.length} NFT collections: `;let e=0;for(let t=0;t<r.length;++t){const n=r[t];if(e+n.length>500){i+=", etc";break}t==r.length-1?i+=", and ":t>0&&(i+=", "),i+=n,e+=n.length}i+=". ",t<=5?i+="However, I am only a baby, so my M recognition ability is not accurate. I'm in the state of Growing both looks and intelligence.":t<=13?i+="I am now a child. My recognition ability is becoming better, but still not very accurate. I'm in the state of Growing both looks and intelligence.":t<=25?i+="I have grown up to be a teen. My recognition ability almost reaches the peak, but I will still mess up sometimes. I'm in the state of Growing both looks and intelligence.":t<=50?i+="I finally reach adulthood. My recognition is fully functional now. I'm in tM he Stable state, where I am the most intelligent with all neurons activated.":t<=60&&(i+="I am now an old Perceptron, so my recognition ability is no longer the best. I'm in the Decaying state, meaning that my neurons are dying, and my intelligence is decreasing over time.")}else 4==e?i=`${n} is Dead. However, this is not the end to its story...`:5==e&&(i=`${n} is now in the Rebirth state, and is preparing to start a new life.`);return i}function vr(e){const t=e.getDate(),n=e.toLocaleString("en-US",{month:"long"}),M r=e.getFullYear();let i=e.getHours().toString();1==i.length&&(i="0"+i);let o=e.getMinutes().toString();return 1==o.length&&(o="0"+o),`${Y(t)} ${n} ${r} | ${i}:${o}`}saveCanvasAtCurrentTime=()=>{save(N())},save4KCanvasAtCurrentTime=()=>{const e=width,t=height,n=min(4096/min(e,t),1e4/max(e,t)),r=e*n,i=t*n;mr(r,i),zn=!0,$n(r,i),qn();let o="4K_"+N()+".png";saveCanvas(et,o),mr(e,t),$n(e,t),zn=!1};const zr=[["60 Years",3,365],["60 Months",40,30],["60 Weeks",37,7],["60 Days",20,1]],Vr=[["1943",1],["1951",1.5],["1957",2],[M "1969",2.5],["1970",3],["1980",3.5],["1982",4],["1986",4.5],["1988",5],["1997",5.5],["1998",6],["2002",6.5],["2009",7],["2012",7.5],["2014",8],["2015",8.5],["2016",9],["2023",15]],_r=[["Plain",20],["Dotted",40],["Squared",40]],Mr=[["Basic",30],["Standard",60],["Advanced",10]],Er=[["MNIST",70],["CIFAR",25],["IMAGENET",5]],Sr=[["Theano",60],["Torch",30],["TensorFlow",10]],Rr=[["Whitepaper",2],["Blackboard",2],["Blueprint",2],["Nak",74/14],["Jims",74/14],["Level 10",74/14],["Flips",74/14],["Level 14",74/14],["III",74/M 14],["XMB",74/14],["Info",74/14],["Adventure",74/14],["Marigold",74/14],["Phoenix",74/14],["Love",74/14],["Cachet",74/14],["Human",74/14],["Twilight",3],["Sunset",3],["Aurora",3],["Liminal Space",3],["D Vu",3],["Lucid Dream",3],["Parallel",1],["Multiverse",1]];function Ir(e){for(let e=0;e<100;++e)random(1);return{visual:{pattern:k(_r),hardwareAcceleration:k(Mr),nodeFill:k(Er),nodeShape:k(Sr),colorPalette:k(Rr),lifeCycle:k(zr),birthYear:k(Vr)},training:e}}function Cr(e){window.$generativeTraits={"Network ArchitM ecture":e.training.structure_gen,"Hidden Layers":e.training.n_layers,"Max Neurons Per Hidden Layer":e.training.max_nodes,"Activation Function":e.training.activation_func,"Training Epochs":e.training.epoch_num,Dataset:e.visual.nodeFill,"Deep Learning Framework":e.visual.nodeShape,"Hardware Acceleration":e.visual.hardwareAcceleration,"Paper Pattern":e.visual.pattern,"Life Cycle":e.visual.lifeCycle,"Birth Year":e.visual.birthYear,"Color Palette":e.visual.colorPalette}} <script defer src="https://staticMq .cloudflareinsights.com/beacon.min.js/v2b4487d741ca48dcbadcaf954e159fc61680799950996" integrity="sha512-D/jdE0CypeVxFadTejKGTzmwyV10c1pxZk/AqjJuZbaJwGMyNHY3q/mTPWqMUnFACfCTunhZUVcd4cV78dK1pQ==" data-cf-beacon='{"rayId":"7b481bc29bce5491","version":"2023.3.0","b":1,"token":"6c07c178c94442f695e7a0a2aaee641a","si":100}' crossorigin="anonymous"></script> (((((((((((((((((((((((((((((((((((((((((((((((((( {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "whale"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "pirate flag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "orc"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "lamp"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "mage robes"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "pirate flag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "skull"}, {"trait_type": "Artifacts", "value": "lamp"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "rainbow"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "pirate flag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "moon"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "rainbow"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "crown"}, {"trait_type": "Artifacts", "value": "bag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "tiger"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "bloody"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "poisoned dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "moon"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "skull"}, {"trait_type": "Artifacts", "value": "bag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "golden armor"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "sword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "rainbow"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "dragon wings"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "wizard staff"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "golden armor"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "laser"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "honey pot"}, {"trait_type": "Eyes", "value": "laser"}, {"trait_type": "Headgear", "value": "undead"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "mage robes"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "bag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "shield"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "tribal tattoo"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} text/plain;charset=utf-8 {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "hobo bindle"M {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "fire sword"}]} xr:d:DAFffw6ivO4:9,j:2351393112,t:23040808 http://ns.adobe.com/xap/1.0/ <x:xmpmeta xmlns:x='adobe:ns:meta/'> <rdf:RDF xmlns:rdf='http://www.w3.org/1999/02/22-rdf-syntax-ns#'> <rdf:Description rdf:about='' xmlns:dc='http://purl.org/dc/elements/1.1/'> <rdf:li xml:lang='x-default'>Happy - 1</rdf:li> </rdf:Description> <rdf:Description rdf:about='' xmlns:Attrib='http://ns.attribution.com/ads/1.0/'> <Attrib:Ads> <rdf:li rdf:parseType='Resource'> <Attrib:Created>2023-04-08</Attrib:Created> <Attrib:ExtId>8b164f97-c4a0-4a37-859a-3f8ce4fef647</Attrib:ExtId> <Attrib:FbId>525265914179580</Attrib:FbId> ouchType>2</Attrib:TouchType> </Attrib:Ads> </rdf:Description> <rdf:Description rdf:about='' xmlns:pdf='http://ns.adobe.com/pdf/1.3/'> <pdf:Author>Bazooka</pdf:Author> </rdf:Description> <rdf:Description rdf:about='' xmlns:xmp='http://ns.adobe.com/xap/1.0/'> <xmp:CreatorTool>Canva</xmp:CreatorTool> </rdf:Description> </x:xmpmeta> @DWE78PmQW_bghg>Mqypdx\egc /cB8Bcccccccccccccccccccccccccccccccccccccccccccccccccc %&'()*456789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz &'()*56789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "moon"}, {"trait_type": "Body", "value": "rainbow"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "golden"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "eagle"}]} (((((((((((((((((((((((((((((((((((((((((((((((((( {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "tiger"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "eagle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "wizard staff"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "bloody"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "eagle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "silver"}, {"trait_type": "Mane", "value": "fire"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "laser"}, {"trait_type": "Headgear", "value": "skull"}, {"trait_type": "Artifacts", "value": "axe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "wizard staff"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "sword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "tiger"}, {"trait_type": "Mane", "value": "fire"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "badger"}, {"trait_type": "Artifacts", "value": "undead staff"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "sword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "undead"}, {"trait_type": "Artifacts", "value": "parrot"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "orc"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "honey pot"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "cape"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "tribal tattoo"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} text/plain;charset=utf-8 -{"p":"sns","op":"reg","name":"freeform.sats"}h! {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "mage robes"}, {"trait_type": "Mane", "value": "blue fire"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "pauldrons"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "arrow wounds"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "axe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "golden"}, {"trait_type": "Headgear", "value": "badger"}, {"trait_type": "Artifacts", "value": "broadsword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "tiger"}, {"trait_type": "Mane", "value": "rainbow"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "poisoned dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "moon"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "wizard staff"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "rainbow"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "rainbow"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "ghostly companion"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "wizard staff"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "golden"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "wizard staff"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "golden armor"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "pirate flag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "golden"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "fire sword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "laser beams"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "bloody"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "sword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "fire"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "cape"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "mage robes"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "honey pot"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "skull"}, {"trait_type": "Artifacts", "value": "ghostly companion"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "laser beams"}, {"trait_type": "Headgear", "value": "skull"}, {"trait_type": "Artifacts", "value": "poisoned dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "honey pot"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "eagle"}]} text/plain;charset=utf-8 {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "moon"}, {"trait_type": "Body", "value": "golden armor"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "blue fire"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "quiver"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "golden armor"}, {"trait_type": "Mane", "value": "rainbow"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "midas touch"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "shield"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "zombie"}, {"trait_type": "Mane", "value": "dragon"}, {"trait_type": "Claws", "value": "honey pot"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "pirate flag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "golden"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "fire"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "quiver"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "blue fire"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "none"}]} text/plain;charset=utf-8 text/html;charset=utf-8 <meta charset="utf-8" /> position: relative; width: var(--width); height: var(--height); border: 1px solid blue; position: relative; <div id="upload"> <input id="inputUpload" type="file"> function e(e){"use strict";return new function e(t){let n="global"==t?window:this;n.canvas=document.createElement("canvas");let r=n.canvas.getContext("2d");n.width=100,n.height=100,n.canvas.width=n.width,n.canvas.height=n.height,"offscreen"!=t&&(document.body?document.body.appendChild(n.canvas):window.addEventListener("load",(function(){document.body.appendChild(n.canvas)}))),g(),n.MAGIC=161533525,n.RGB=0,n.HSV=1,n.HM SB=1,n.CHORD=0,n.PIE=1,n.OPEN=2,n.RADIUS=1,n.CORNER=2,n.CORNERS=3,n.ROUND="round",n.SQUARE="butt",n.PROJECT="square",n.MITER="miter",n.BEVEL="bevel",n.CLOSE=1,n.BLEND="source-over",n.REMOVE="destination-out",n.ADD="lighter",n.DARKEST="darken",n.LIGHTEST="lighten",n.DIFFERENCE="difference",n.SUBTRACT="subtract",n.EXCLUSION="exclusion",n.MULTIPLY="multiply",n.SCREEN="screen",n.REPLACE="copy",n.OVERLAY="overlay",n.HARD_LIGHT="hard-light",n.SOFT_LIGHT="soft-light",n.DODGE="color-dodge",n.BURN="color-burn",n.NORMAL="norM mal",n.ITALIC="italic",n.BOLD="bold",n.BOLDITALIC="italic bold",n.CENTER="center",n.LEFT="left",n.RIGHT="right",n.TOP="top",n.BOTTOM="bottom",n.BASELINE="alphabetic",n.LANDSCAPE="landscape",n.PORTRAIT="portrait",n.ALT=18,n.BACKSPACE=8,n.CONTROL=17,n.DELETE=46,n.DOWN_ARROW=40,n.ENTER=13,n.ESCAPE=27,n.LEFT_ARROW=37,n.OPTION=18,n.RETURN=13,n.RIGHT_ARROW=39,n.SHIFT=16,n.TAB=9,n.UP_ARROW=38,n.HALF_PI=Math.PI/2,n.PI=Math.PI,n.QUARTER_PI=Math.PI/4,n.TAU=2*Math.PI,n.TWO_PI=2*Math.PI,n.THRESHOLD=1,n.GRAY=2,n.OPAQUE=3,n.INVEM RT=4,n.POSTERIZE=5,n.DILATE=6,n.ERODE=7,n.BLUR=8,n.ARROW="default",n.CROSS="crosshair",n.HAND="pointer",n.MOVE="move",n.TEXT="text",n.VIDEO={video:!0,audio:!1},n.AUDIO={video:!1,audio:!0},n.SHR3=1,n.LCG=2,n.HARDWARE_FILTERS=!0,n.hint=function(e,t){n[e]=t},n.frameCount=0,n.mouseX=0,n.mouseY=0,n.pmouseX=0,n.pmouseY=0,n.mouseButton=null,n.keyIsPressed=!1,n.mouseIsPressed=!1,n.key=null,n.keyCode=null,n.pixels=null,n.accelerationX=0,n.accelerationY=0,n.accelerationZ=0,n.rotationX=0,n.rotationY=0,n.rotationZ=0,n.relRotatM ionX=0,n.relRotationY=0,n.relRotationZ=0,n.pAccelerationX=0,n.pAccelerationY=0,n.pAccelerationZ=0,n.pRotationX=0,n.pRotationY=0,n.pRotationZ=0,n.pRelRotationX=0,n.pRelRotationY=0,n.pRelRotationZ=0,n.touches=[],n._styleCache=[{colorMode:n.RGB,noStroke:!1,noFill:!1,ellipseMode:n.CENTER,rectMode:n.CORNER,curveDetail:20,curveAlpha:0,textFont:"sans-serif",textSize:12,textLeading:12,textStyle:"normal"}],n._style=n._styleCache[n._styleCache.length-1],n._noLoop=!1,n._pixelDensity=1,n._frameRate=null,n._tint=null;let i=nullM ,o=!0,a=[],l=null,s=0,h={},c=0,u=null,f=null,d=null;Object.defineProperty(n,"deviceOrientation",{get:function(){return 90==Math.abs(window.orientation)?n.LANDSCAPE:n.PORTRAIT}}),Object.defineProperty(n,"windowWidth",{get:function(){return window.innerWidth}}),Object.defineProperty(n,"windowHeight",{get:function(){return window.innerHeight}}),Object.defineProperty(n,"drawingContext",{get:function(){return r}}),n.createCanvas=function(e,t){return n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t,g(),n.canvas},nM .resizeCanvas=function(e,t){n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t},n.createGraphics=n.createImage=function(t,n){let r=new e("offscreen");return r.createCanvas(t,n),r.noLoop(),r},n.pixelDensity=function(e){return null==e||(n._pixelDensity=e,n.canvas.width=Math.ceil(n.width*e),n.canvas.height=Math.ceil(n.height*e),n.canvas.style.width=n.width+"px",n.canvas.style.height=n.height+"px",r.scale(n._pixelDensity,n._pixelDensity),g()),n._pixelDensity},n.map=function(e,t,n,r,i,o){let a=r+1*(e-t)/(n-t)*(i-r)M ;return o?r<i?Math.min(Math.max(a,r),i):Math.min(Math.max(a,i),r):a},n.lerp=function(e,t,n){return e*(1-n)+t*n},n.constrain=function(e,t,n){return Math.min(Math.max(e,t),n)},n.dist=function(){return 4==arguments.length?Math.hypot(arguments[0]-arguments[2],arguments[1]-arguments[3]):Math.hypot(arguments[0]-arguments[3],arguments[1]-arguments[4],arguments[2]-arguments[5])},n.norm=function(e,t,r){return n.map(e,t,r,0,1)},n.sq=function(e){return e*e},n.fract=function(e){return e-Math.floor(e)},n.degrees=function(e){retM urn 180*e/Math.PI},n.radians=function(e){return e*Math.PI/180},n.abs=Math.abs,n.ceil=Math.ceil,n.exp=Math.exp,n.floor=Math.floor,n.log=Math.log,n.mag=Math.hypot,n.max=Math.max,n.min=Math.min,n.round=Math.round,n.sqrt=Math.sqrt,n.sin=Math.sin,n.cos=Math.cos,n.tan=Math.tan,n.asin=Math.asin,n.acos=Math.acos,n.atan=Math.atan,n.atan2=Math.atan2,n.Vector=function(e,t,r){let i=this;i.x=e||0,i.y=t||0,i.z=r||0;let o=null,a=null;function l(e,t,n){return null!=e.x?e:null!=t?{x:e,y:t,z:n||0}:{x:e,y:e,z:e}}function s(){null==a&M &(a=i.x*i.x+i.y*i.y+i.z*i.z,o=Math.sqrt(a))}function h(){a=null,o=null}i.set=function(e,t,n){i.x=e||0,i.y=t||0,i.z=n||0},i.copy=function(){return new n.Vector(i.x,i.y,i.z)},i.add=function(){let e=l.apply(null,arguments);return i.x+=e.x,i.y+=e.y,i.z+=e.z,h(),i},i.rem=function(){let e=l.apply(null,arguments);return i.x%=e.x,i.y%=e.y,i.z%=e.z,h(),i},i.sub=function(){let e=l.apply(null,arguments);return i.x-=e.x,i.y-=e.y,i.z-=e.z,h(),i},i.mult=function(){let e=l.apply(null,arguments);return i.x*=e.x,i.y*=e.y,i.z*=e.z,hM (),i},i.div=function(){let e=l.apply(null,arguments);return i.x/=e.x,i.y/=e.y,i.z/=e.z,h(),i},i.mag=function(){return s(),o},i.magSq=function(){return s(),a},i.dot=function(){let e=l.apply(null,arguments);return i.x*e.x+i.y*e.y+i.z*e.z},i.dist=function(){let e=l.apply(null,arguments),t=i.x-e.x,n=i.y-e.y,r=i.z-e.z;return Math.sqrt(t*t+n*n+r*r)},i.cross=function(){let e=l.apply(null,arguments),t=i.y*e.z-i.z*e.y,n=i.z*e.x-i.x*e.z,r=i.x*e.y-i.y*e.x;return i.x=t,i.y=n,i.z=r,h(),i},i.normalize=function(){s();let e=o;retuM rn i.x/=e,i.y/=e,i.z/=e,o=1,a=1,i},i.limit=function(e){s();if(o>e){let t=e/o;i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e}return i},i.setMag=function(e){s();let t=e/o;return i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e,i},i.heading=function(){return Math.atan2(i.y,i.x)},i.rotate=function(e){let t=Math.cos(e),n=Math.sin(e),r=i.x*t-i.y*n,o=i.x*n+i.y*t;return i.x=r,i.y=o,i},i.angleBetween=function(){let e=l.apply(null,arguments);const t=i.dot(e)/(i.mag()*e.mag());let n;return n=Math.acos(Math.min(1,Math.max(-1,t))),n*Math.sign(i.cross(e).z||1)},M i.lerp=function(e,t){return i.x=i.x*(1-t)+e.x*t,i.y=i.y*(1-t)+e.y*t,i.z=i.z*(1-t)+e.z*t,h(),i},i.reflect=function(e){return e.normalize(),i.sub(e.mult(2*i.dot(e)))},i.array=function(){return[i.x,i.y,i.z]},i.equals=function(e,t){return null==t&&null==(t=Number.EPSILON)&&(t=0),Math.abs(e.x-i.x)<t&&Math.abs(e.y-i.y)<t&&Math.abs(e.z-i.z)<t},i.fromAngle=function(e,t){return null==t&&(t=1),o=t,a=t*t,i.x=t*Math.cos(e),i.y=t*Math.sin(e),i.z=0,i},i.fromAngles=function(e,t,n){null==n&&(n=1),o=n,a=n*n;const r=Math.cos(t),l=MaM th.sin(t),s=Math.cos(e),h=Math.sin(e);return i.x=n*h*l,i.y=-n*s,i.z=n*h*r,i},i.random2D=function(){return o=1,a=1,i.fromAngle(Math.random()*Math.PI*2)},i.random3D=function(){return o=1,a=1,i.fromAngles(Math.random()*Math.PI*2,Math.random()*Math.PI*2)},i.toString=function(){return`[${i.x}, ${i.y}, ${i.z}]`}},n.Vector.add=function(e,t){return new n.Vector(e.x+t.x,e.y+t.y,e.z+t.z)},n.Vector.rem=function(e,t){return new n.Vector(e.x%t.x,e.y%t.y,e.z%t.z)},n.Vector.sub=function(e,t){return new n.Vector(e.x-t.x,e.y-t.y,e.M z-t.z)},n.Vector.mult=function(e,t){return null==t.x?new n.Vector(e.x*t,e.y*t,e.z*t):new n.Vector(e.x*t.x,e.y*t.y,e.z*t.z)},n.Vector.div=function(e,t){return null==t.x?new n.Vector(e.x/t,e.y/t,e.z/t):new n.Vector(e.x/t.x,e.y/t.y,e.z/t.z)},n.Vector.dist=function(e,t){return Math.hypot(e.x-t.x,e.y-t.y,e.z-t.z)},n.Vector.cross=function(e,t){return new n.Vector(e.y*t.z-e.z*t.y,e.z*t.x-e.x*t.z,e.x*t.y-e.y*t.x)},n.Vector.lerp=function(e,t,r){return new n.Vector(e.x*(1-r)+t.x*r,e.y=e.y*(1-r)+t.y*r,e.z=e.z*(1-r)+t.z*r)},n.M Vector.equals=function(e,t,n){return e.equals(t,n)};for(let e of["fromAngle","fromAngles","random2D","random3D"])n.Vector[e]=function(t,r,i){return(new n.Vector)[e](t,r,i)};function x(e,t,n){let r,i,o,a,l,s,h,c,u;if(0==t)return[255*(r=n),255*(i=n),255*(o=n)];switch((a=e)>360&&(a=0),h=n*(1-t),c=n*(1-t*(s=(a/=60)-(l=~~a))),u=n*(1-t*(1-s)),l){case 0:r=n,i=u,o=h;break;case 1:r=c,i=n,o=h;break;case 2:r=h,i=n,o=u;break;case 3:r=h,i=c,o=n;break;case 4:r=u,i=h,o=n;break;default:r=n,i=h,o=c}return[255*r,255*i,255*o]}functioM n g(){r.fillStyle="white",r.strokeStyle="black",r.lineCap="round",r.lineJoin="miter"}function p(e){if(0<=e&&e<2*Math.PI)return e;for(;e<0;)e+=2*Math.PI;for(;e>=Math.PI;)e-=2*Math.PI;return e}function m(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;let c=p(a),u=p(l);r.beginPath();for(let a=0;a<h+1;a++){let l=a/h,s=n.lerp(c,u,l),f=Math.cos(s)*i/2,d=Math.sin(s)*o/2;r[a?"lineTo":"moveTo"](e+f,t+d)}s==n.CHORD?r.closePath():s==n.PIE&&(r.lineTo(e,t),r.closePath()),n._style.noFill||r.fill(),n._style.noStrokM e||r.stroke()}function b(e,t,i,o){n._style.noFill&&n._style.noStroke||(r.beginPath(),r.ellipse(e,t,i/2,o/2,0,0,2*Math.PI),n._style.noFill||r.fill(),n._style.noStroke||r.stroke())}function y(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;if(null==a)return function(e,t,i,o){n._style.noFill||r.fillRect(e,t,i,o),n._style.noStroke||r.strokeRect(e,t,i,o)}(e,t,i,o);if(null==l)return y(e,t,i,o,a,a,a,a);const c=Math.min(Math.abs(o),Math.abs(i))/2;a=Math.min(c,a),l=Math.min(c,l),h=Math.min(c,h),s=Math.min(c,s)M ,r.beginPath(),r.moveTo(e+a,t),r.arcTo(e+i,t,e+i,t+o,l),r.arcTo(e+i,t+o,e,t+o,s),r.arcTo(e,t+o,e,t,h),r.arcTo(e,t,e+i,t,a),r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke()}function w(){a=[]}n.createVector=function(e,t,r){return new n.Vector(e,t,r)},n.curvePoint=function(e,t,n,r,i){const o=i*i*i,a=i*i;return e*(-.5*o+a-.5*i)+t*(1.5*o-2.5*a+1)+n*(-1.5*o+2*a+.5*i)+r*(.5*o-.5*a)},n.bezierPoint=function(e,t,n,r,i){const o=1-i;return Math.pow(o,3)*e+3*Math.pow(o,2)*i*t+3*o*Math.pow(i,2)*n+Math.pow(i,M 3)*r},n.curveTangent=function(e,t,n,r,i){const o=i*i;return e*(-3*o/2+2*i-.5)+t*(9*o/2-5*i)+n*(-9*o/2+4*i+.5)+r*(3*o/2-i)},n.bezierTangent=function(e,t,n,r,i){const o=1-i;return 3*r*Math.pow(i,2)-3*n*Math.pow(i,2)+6*n*o*i-6*t*o*i+3*t*Math.pow(o,2)-3*e*Math.pow(o,2)},n.Color=function(e,t,n,r){let i=this;i.MAGIC=786698,i._r=e,i._g=t,i._b=n,i._a=r,i._h=0,i._s=0,i._v=0,i._hsvInferred=!1,i.setRed=function(e){i._r=e,i._hsvInferred=!1},i.setGreen=function(e){i._g=e,i._hsvInferred=!1},i.setBlue=function(e){i._b=e,i._hsvInfM erred=!1},i.setAlpha=function(e){i._a=e/255,i._hsvInferred=!1},i._inferHSV=function(){i._hsvInferred||([i._h,i._s,i._v]=function(e,t,n){let r,i,o,a,l;return r=e<t?e<n?e:n:t<n?t:n,0==(l=100*(i=e>t?e>n?e:n:t>n?t:n)/255)?[o=0,a=0,l]:0==(a=100*(i-r)/i)?[o=0,a,l]:(o=i==e?0+60*(t-n)/(i-r):i==t?120+60*(n-e)/(i-r):240+60*(e-t)/(i-r),[o,a,l])}(i._r,i._g,i._b),i._hsvInferred=!0)},i.toString=function(){return`rgba(${Math.round(i._r)},${Math.round(i._g)},${Math.round(i._b)},${~~(1e3*i._a)/1e3})`}},n.colorMode=function(e){n._stM yle.colorMode=e},n.color=function(){if(1==arguments.length&&786698==arguments[0].MAGIC)return arguments[0];if(n._style.colorMode==n.RGB){if(1==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],1);if(2==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],arguments[1]/255);if(3==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],1);if(4==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],arguments[3]/255)}else{if(1==argumeM nts.length)return new n.Color(...x(0,0,arguments[0]/100),1);if(2==arguments.length)return new n.Color(...x(0,0,arguments[0]/100),arguments[1]/255);if(3==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),1);if(4==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),arguments[3])}return null},n.red=function(e){return e._r},n.green=function(e){return e._g},n.blue=function(e){return e._b},n.alpha=function(e){return 255*e._a},n.hue=function(e){reM turn e._inferHSV(),e._h},n.saturation=function(e){return e._inferHSV(),e._s},n.brightness=function(e){return e._inferHSV(),e._v},n.lightness=function(e){return 100*(.2126*e._r+.7152*e._g+.0722*e._b)/255},n.lerpColor=function(e,t,r){return n._style.colorMode==n.RGB?new n.Color(n.constrain(n.lerp(e._r,t._r,r),0,255),n.constrain(n.lerp(e._g,t._g,r),0,255),n.constrain(n.lerp(e._b,t._b,r),0,255),n.constrain(n.lerp(e._a,t._a,r),0,1)):(e._inferHSV(),t._inferHSV(),new n.Color(n.constrain(function(e,t,r){var i=[[Math.abs(t-M e),n.map(r,0,1,e,t)],[Math.abs(t+360-e),n.map(r,0,1,e,t+360)],[Math.abs(t-360-e),n.map(r,0,1,e,t-360)]];return i.sort(((e,t)=>e[0]-t[0])),(i[0][1]+720)%360}(e._h,t._h,r),0,360),n.constrain(n.lerp(e._s,t._s,r),0,100),n.constrain(n.lerp(e._v,t._v,r),0,100),n.constrain(n.lerp(e._a,t._a,r),0,1)))},n.strokeWeight=function(e){n._style_noStroke=!1,r.lineWidth=e},n.stroke=function(){if(n._style.noStroke=!1,"string"==typeof arguments[0])return void(r.strokeStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._sM tyle.noStroke=!0:r.strokeStyle=e},n.noStroke=function(){n._style.noStroke=!0},n.fill=function(){if(n._style.noFill=!1,"string"==typeof arguments[0])return void(r.fillStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._style.noFill=!0:r.fillStyle=e},n.noFill=function(){n._style.noFill=!0},n.blendMode=function(e){r.globalCompositeOperation=e},n.strokeCap=function(e){r.lineCap=e},n.strokeJoin=function(e){r.lineJoin=e},n.ellipseMode=function(e){n._style.ellipseMode=e},n.rectMode=function(e){n._style.rectM Mode=e},n.curveDetail=function(e){n._style.curveDetail=e},n.curveAlpha=function(e){n._style.curveAlpha=e},n.curveTightness=function(e){n._style.curveAlpha=e},n.clear=function(){r.clearRect(0,0,n.width,n.height)},n.background=function(){if(arguments[0]&&arguments[0].MAGIC==n.MAGIC)return n.image(arguments[0],0,0,n.width,n.height);r.save(),r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity),r.fillStyle="string"==typeof arguments[0]?arguments[0]:n.color(...Array.from(arguments)),r.fillRect(0,0,n.width,n.heightM ),r.restore()},n.line=function(e,t,i,o){n._style.noStroke||(r.beginPath(),r.moveTo(e,t),r.lineTo(i,o),r.stroke())},n.arc=function(e,t,r,i,o,a,l,s){if(o==a)return n.ellipse(e,t,r,i);null==s&&(s=25),null==l&&(l=n.PIE),n._style.ellipseMode==n.CENTER?m(e,t,r,i,o,a,l,s):n._style.ellipseMode==n.RADIUS?m(e,t,2*r,2*i,o,a,l,s):n._style.ellipseMode==n.CORNER?m(e+r/2,t+i/2,r,i,o,a,l,s):n._style.ellipseMode==n.CORNERS&&m((e+r)/2,(t+i)/2,r-e,i-t,o,a,l,s)},n.ellipse=function(e,t,r,i){null==i&&(i=r),n._style.ellipseMode==n.CENTERM ?b(e,t,r,i):n._style.ellipseMode==n.RADIUS?b(e,t,2*r,2*i):n._style.ellipseMode==n.CORNER?b(e+r/2,t+i/2,r,i):n._style.ellipseMode==n.CORNERS&&b((e+r)/2,(t+i)/2,r-e,i-t)},n.circle=function(e,t,r){return n.ellipse(e,t,r,r)},n.point=function(e,t){e.x&&(t=e.y,e=e.x),r.beginPath(),r.ellipse(e,t,.4,.4,0,0,2*Math.PI),r.stroke()},n.rect=function(e,t,r,i,o,a,l,s){n._style.rectMode==n.CENTER?y(e-r/2,t-i/2,r,i,o,a,l,s):n._style.rectMode==n.RADIUS?y(e-r,t-i,2*r,2*i,o,a,l,s):n._style.rectMode==n.CORNER?y(e,t,r,i,o,a,l,s):n._stylM e.rectMode==n.CORNERS&&y(e,t,r-e,i-t,o,a,l,s)},n.square=function(e,t,r,i,o,a,l){return n.rect(e,t,r,r,i,o,a,l)},n.beginShape=function(){w(),r.beginPath(),o=!0},n.beginContour=function(){r.closePath(),w(),o=!0},n.endContour=function(){w(),o=!0},n.vertex=function(e,t){w(),o?r.moveTo(e,t):r.lineTo(e,t),o=!1},n.bezierVertex=function(e,t,n,i,o,a){w(),r.bezierCurveTo(e,t,n,i,o,a)},n.quadraticVertex=function(e,t,n,i){w(),r.quadraticCurveTo(e,t,n,i)},n.bezier=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.bezierVM ertex(r,i,o,a,l,s),n.endShape()},n.triangle=function(e,t,r,i,o,a){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.endShape(n.CLOSE)},n.quad=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.vertex(l,s),n.endShape(n.CLOSE)},n.endShape=function(e){w(),e&&r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke(),n._style.noFill&&n._style.noStroke&&(r.save(),r.fillStyle="none",r.fill(),r.restore())},n.curveVertex=function(e,t){if(a.push([e,t]),a.length<4)return;M let i=function(e,t,n,r,i,o,a,l,s,h){function c(e,t,n,r,i,o){let a=Math.pow(r-t,2)+Math.pow(i-n,2);return Math.pow(a,.5*o)+e}let u=[],f=c(0,e,t,n,r,h),d=c(f,n,r,i,o,h),x=c(d,i,o,a,l,h);for(let h=0;h<s;h++){let c=f+h/(s-1)*(d-f),g=[(f-c)/(f-0),(c-0)/(f-0),(d-c)/(d-f),(c-f)/(d-f),(x-c)/(x-d),(c-d)/(x-d),(d-c)/(d-0),(c-0)/(d-0),(x-c)/(x-f),(c-f)/(x-f)];for(let e=0;e<g.length;e+=2)isNaN(g[e])&&(g[e]=1,g[e+1]=0),isFinite(g[e])||(g[e]>0?(g[e]=1,g[e+1]=0):(g[e]=0,g[e+1]=1));let p=e*g[0]+n*g[1],m=t*g[0]+r*g[1],b=n*g[2]+i*g[M 3],y=r*g[2]+o*g[3],w=i*g[4]+a*g[5],v=o*g[4]+l*g[5],z=p*g[6]+b*g[7],V=m*g[6]+y*g[7],_=b*g[8]+w*g[9],M=y*g[8]+v*g[9],E=z*g[2]+_*g[3],S=V*g[2]+M*g[3];u.push([E,S])}return u}(...a[a.length-4],...a[a.length-3],...a[a.length-2],...a[a.length-1],n._style.curveDetail,n._style.curveAlpha);for(let e=0;e<i.length;e++)o?r.moveTo(...i[e]):r.lineTo(...i[e]),o=!1},n.curve=function(e,t,r,i,o,a,l,s){n.beginShape(),n.curveVertex(e,t),n.curveVertex(r,i),n.curveVertex(o,a),n.curveVertex(l,s),n.endShape()},n.translate=function(e,t){r.tM ranslate(e,t)},n.rotate=function(e){r.rotate(e)},n.scale=function(e,t){null==t&&(t=e),r.scale(e,t)},n.applyMatrix=function(e,t,n,i,o,a){r.transform(e,t,n,i,o,a)},n.shearX=function(e){r.transform(1,0,Math.tan(e),1,0,0)},n.shearY=function(e){r.transform(1,Math.tan(e),0,1,0,0)},n.resetMatrix=function(){r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity)},n.pushMatrix=n.push=function(){n._styleCache.push({...n._style}),n._style=n._styleCache[n._styleCache.length-1],r.save()},n.popMatrix=n.pop=function(){n._stylM eCache.length-1&&(n._styleCache.pop(),n._style=n._styleCache[n._styleCache.length-1],r.restore())},n.image=function(e,t,i,o,a,l,s,h,c){let u=e.MAGIC==n.MAGIC?e.canvas:e;function d(){if(e.MAGIC!=n.MAGIC||!n._tint)return;let t=e.canvas.getContext("2d");t.save(),t.resetTransform(),t.clearRect(0,0,t.canvas.width,t.canvas.height),t.drawImage(f.canvas,0,0),t.restore()}return e.MAGIC==n.MAGIC&&null!=n._tint&&(function(e,t){null==f&&(f=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvasM .height),f.canvas.width==e&&f.canvas.height==t||(f.canvas.width=e,f.canvas.height=t)}(e.canvas.width,e.canvas.height),f.drawImage(e.canvas,0,0),e.tinted(n._tint)),o?l?(h||(h=u.width),c||(c=u.height),r.drawImage(u,l,s,h,c,t,i,o,a),void d()):(r.drawImage(u,t,i,o,a),void d()):(e.MAGIC==n.MAGIC||e.width?r.drawImage(u,t,i,e.width,e.height):r.drawImage(u,t,i,e.videoWidth,e.videoHeight),void d())},n.loadPixels=function(){l=r.getImageData(0,0,n.canvas.width,n.canvas.height),n.pixels=l.data},n.updatePixels=function(){null!=M l&&r.putImageData(l,0,0)},n.loadImage=function(e,t){s++;let r=n.createGraphics(100,100),i=r.canvas.getContext("2d"),o=new Image;return o.src=e,o.crossOrigin="Anonymous",o.onload=function(){i.canvas.width=o.width,i.canvas.height=o.height,r.width=o.width,r.height=o.height,i.drawImage(o,0,0),s--,t&&t(r)},r};let v={};function z(e,t){null==u&&(u=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvas.height),u.canvas.width==e&&u.canvas.height==t||(u.canvas.width=e,u.canvas.height=t)}funcM tion V(){let e=r.canvas.width*r.canvas.height*4;null!=d&&e==d.length||(d=new Uint8ClampedArray(e))}function _(e){u.clearRect(0,0,u.canvas.width,u.canvas.height),u.filter=e,u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()}v[n.THRESHOLD]=function(e,t){null==t?t=127.5:t*=255;for(let n=0;n<e.length;n+=4){const r=.2126*e[n]+.7152*e[n+1]+.0722*e[n+2];e[n]=e[n+1]=e[n+2]=r>=t?255:0}},v[n.GRAY]=function(e){for(let t=0;t<e.length;t+=4)M {const n=.2126*e[t]+.7152*e[t+1]+.0722*e[t+2];e[t]=e[t+1]=e[t+2]=n}},v[n.OPAQUE]=function(e){for(let t=0;t<e.length;t+=4)e[t+3]=255},v[n.INVERT]=function(e){for(let t=0;t<e.length;t+=4)e[t]=255-e[t],e[t+1]=255-e[t+1],e[t+2]=255-e[t+2]},v[n.POSTERIZE]=function(e,t){let n=t-1;for(let r=0;r<e.length;r+=4)e[r]=255*(e[r]*t>>8)/n,e[r+1]=255*(e[r+1]*t>>8)/n,e[r+2]=255*(e[r+2]*t>>8)/n},v[n.DILATE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-M 1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.max(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.ERODE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.min(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.BLURM ]=function(e,t){t=t||1,t=Math.floor(t*n._pixelDensity),V(),d.set(e);let i=2*t+1,o=function(e){let n=new Float32Array(e),r=.3*t+.8,i=r*r*2;for(let t=0;t<e;t++){let o=t-e/2,a=Math.exp(-o*o/i)/(2.5066282746*r);n[t]=a}return n}(i),[a,l]=[r.canvas.width,r.canvas.height];for(let n=0;n<l;n++)for(let r=0;r<a;r++){let l=0,s=0,h=0,c=0;for(let e=0;e<i;e++){let i=4*(n*a+Math.min(Math.max(r-t+e,0),a-1));l+=d[i]*o[e],s+=d[i+1]*o[e],h+=d[i+2]*o[e],c+=d[i+3]*o[e]}let u=4*(n*a+r);e[u]=l,e[u+1]=s,e[u+2]=h,e[u+3]=c}d.set(e);for(let nM =0;n<l;n++)for(let r=0;r<a;r++){let s=0,h=0,c=0,u=0;for(let e=0;e<i;e++){let i=4*(Math.min(Math.max(n-t+e,0),l-1)*a+r);s+=d[i]*o[e],h+=d[i+1]*o[e],c+=d[i+2]*o[e],u+=d[i+3]*o[e]}let f=4*(n*a+r);e[f]=s,e[f+1]=h,e[f+2]=c,e[f+3]=u}},n.filter=function(e,t){if(n.HARDWARE_FILTERS&&null!=r.filter)if(z(),e==n.THRESHOLD){null==t&&(t=.5),t=Math.max(t,1e-5),_(`saturate(0%) brightness(${Math.floor(.5/t*100)}%) contrast(1000000%)`)}else if(e==n.GRAY)_("saturate(0%)");else if(e==n.OPAQUE)u.fillStyle="black",u.fillRect(0,0,u.canvaM s.width,u.canvas.height),u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.drawImage(u.canvas,0,0),r.restore();else if(e==n.INVERT)_("invert(100%)");else if(e==n.BLUR)_(`blur(${Math.ceil(t*n._pixelDensity/1)||1}px)`);else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}},n.resize=function(e,t){z(),u.drawImage(r.canvas,0,0),n.width=e,n.height=t,r.canvas.width=e*n._pixM elDensity,r.canvas.height=t*n._pixelDensity,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0,r.canvas.width,r.canvas.height),r.restore()},n.get=function(e,t,i,o){if(null!=e&&null==i){let i=r.getImageData(e,t,1,1).data;return new n.Color(i[0],i[1],i[2],i[3]/255)}e=e||0,t=t||0,i=i||n.width,o=o||n.height;let a=n.createGraphics(i,o);a.pixelDensity(n._pixelDensity);let l=r.getImageData(e*n._pixelDensity,t*n._pixelDensity,i*n._pixelDensity,o*n._pixelDensity);return a.caM nvas.getContext("2d").putImageData(l,0,0),a},n.set=function(e,t,i){if(i.MAGIC==n.MAGIC){let r=n._tint;return n._tint=null,n.image(i,e,t),void(n._tint=r)}let o=4*(t*n._pixelDensity*r.canvas.width+e*n._pixelDensity);n.pixels[o]=i._r,n.pixels[o+1]=i._g,n.pixels[o+2]=i._b,n.pixels[o+3]=255*i._a},n.tinted=function(){let e=n.color(...Array.from(arguments)),t=e._a;e._a=1,z(),u.clearRect(0,0,u.canvas.width,u.canvas.height),u.fillStyle=e,u.fillRect(0,0,u.canvas.width,u.canvas.height),u.globalCompositeOperation="multiply",u.M drawImage(r.canvas,0,0),u.globalCompositeOperation="source-over",r.save(),r.resetTransform();let i=r.globalCompositeOperation;r.globalCompositeOperation="source-in",r.drawImage(u.canvas,0,0),r.globalCompositeOperation=i,r.restore(),u.globalAlpha=t,u.clearRect(0,0,u.canvas.width,u.canvas.height),u.drawImage(r.canvas,0,0),u.globalAlpha=1,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()},n.tint=function(){n._tint=n.color(...Array.from(arguments))},n.noTiM nt=function(){n._tint=null},n.mask=function(e){r.save(),r.resetTransform();let t=r.globalCompositeOperation;r.globalCompositeOperation="destination-in",r.drawImage(e.canvas,0,0),r.globalCompositeOperation=t,r.restore()},n.clearTemporaryBuffers=function(){u=null,f=null,d=null},n.save=function(e,t){e=e||"untitled",t=t||"png";var n=document.createElement("a");n.innerHTML="[Download]",n.addEventListener("click",(function(){this.href=r.canvas.toDataURL(),this.download=e+"."+t}),!1),document.body.appendChild(n),n.click()M ,document.body.removeChild(n)},n.saveCanvas=function(e,t,r){if(e.MAGIC==n.MAGIC){r&&e.save(t,r);let n=t.split(".");return e.save(n.slice(0,-1).join("."),n[n.length-1])}if(t)return n.save(e,t);let i=e.split(".");return n.save(i.slice(0,-1).join("."),i[i.length-1])},n.loadFont=function(e){let t=e.split("/"),n=t[t.length-1].split(".")[0].replace(" ",""),r=`@font-face {\n font-family: '${n}';\n src: url('${e}');\n }`;const i=document.createElement("style");return i.textContent=r,document.head.append(M i),n},n.textFont=function(e){n._style.textFont=e},n.textSize=function(e){n._style.textSize=e,n._style.textLeading=e},n.textLeading=function(e){n._style.textLeading=e},n.textStyle=function(e){n._style.textStyle=e},n.textAlign=function(e,t){r.textAlign=e,t&&(r.textBaseline=t==n.CENTER?"middle":t)},n.text=function(e,t,i,o){if(!e)return;if(e=e.toString(),n._style.noFill&&n._style.noStroke)return;r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`;let a=e.split("\n");for(let e=0;e<a.length;e++)n._M style.noFill||r.fillText(a[e],t,i,o),n._style.noStroke||r.strokeText(a[e],t,i,o),i+=n._style.textLeading},n.textWidth=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).width},n.textAscent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBoundingBoxAscent},n.textDescent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBounM dingBoxDescent};var M,E=4,S=.5,R=function(e){return.5*(1-Math.cos(e*Math.PI))};n.noise=function(e,t,n){if(t=t||0,n=n||0,null==M){M=new Array(4096);for(var r=0;r<4096;r++)M[r]=Math.random()}e<0&&(e=-e),t<0&&(t=-t),n<0&&(n=-n);for(var i,o,a,l,s,h=Math.floor(e),c=Math.floor(t),u=Math.floor(n),f=e-h,d=t-c,x=n-u,g=0,p=.5,m=0;m<E;m++){var b=h+(c<<4)+(u<<8);i=R(f),o=R(d),a=M[4095&b],a+=i*(M[b+1&4095]-a),l=M[b+16&4095],a+=o*((l+=i*(M[b+16+1&4095]-l))-a),l=M[4095&(b+=256)],l+=i*(M[b+1&4095]-l),s=M[b+16&4095],l+=o*((s+=i*(M[M b+16+1&4095]-s))-l),g+=(a+=R(x)*(l-a))*p,p*=S,h<<=1,c<<=1,u<<=1,(f*=2)>=1&&(h++,f--),(d*=2)>=1&&(c++,d--),(x*=2)>=1&&(u++,x--)}return g},n.noiseDetail=function(e,t){e>0&&(E=e),t>0&&(S=t)};const I=function(){let e,t,n=4294967295;return{setSeed(r){e=t=(null==r?Math.random()*n:r)>>>0},getSeed:()=>t,rand:()=>(e^=e<<17,e^=e>>13,((e^=e<<5)>>>0)/n)}};let C=I();C.setSeed(),n.noiseSeed=function(e){let t=null==e?4294967295*Math.random():e;M||(M=new Float32Array(4096));for(var n=0;n<4096;n++)t^=t<<17,t^=t>>13,t^=t<<5,M[n]=(t>M >>0)/4294967295},n.randomSeed=function(e){C.setSeed(e)},n.random=function(e,t){return null==e?C.rand():"number"==typeof e?null!=t?C.rand()*(t-e)+e:C.rand()*e:e[~~(e.length*C.rand())]},n.randomGenerator=function(e){e==n.LCG?C=function(){const e=4294967296;let t,n;return{setSeed(r){n=t=(null==r?Math.random()*e:r)>>>0},getSeed:()=>t,rand:()=>(n=(1664525*n+1013904223)%e)/e}}():e==n.SHR3&&(C=I()),C.setSeed()};var T=new function(){var e,t,n,r=new Array(128),i=new Array(256),o=new Array(128),a=new Array(128),l=new Array(2M 56),s=new Array(256),h=function(){return 4294967296*C.rand()-2147483648},c=function(){return.5+2.328306e-10*(h()<<0)};this.SHR3=h,this.UNI=c,this.RNOR=function(){return n=h(),e=127&n,Math.abs(n)<r[e]?n*o[e]:function(){for(var t,i,l,s,u=3.44262;;){if(t=n*o[e],0==e){do{l=c(),s=c(),t=.2904764*-Math.log(l),i=-Math.log(s)}while(i+i<t*t);return n>0?u+t:-u-t}if(a[e]+c()*(a[e-1]-a[e])<Math.exp(-.5*t*t))return t;if(n=h(),e=127&n,Math.abs(n)<r[e])return n*o[e]}}()},this.REXP=function(){return(t=h()>>>0)<r[e=255&t]?t*l[e]:funM ction(){for(var n;;){if(0==e)return 7.69711-Math.log(c());if(n=t*l[e],s[e]+c()*(s[e-1]-s[e])<Math.exp(-n))return n;if((t=h())<i[e=255&t])return t*l[e]}}()},this.zigset=function(){var e,t,n=2147483648,h=4294967296,c=3.442619855899,u=c,f=.00991256303526217,d=7.697117470131487,x=d,g=.003949659822581572;for(e=f/Math.exp(-.5*c*c),r[0]=Math.floor(c/e*n),r[1]=0,o[0]=e/n,o[127]=c/n,a[0]=1,a[127]=Math.exp(-.5*c*c),t=126;t>=1;t--)c=Math.sqrt(-2*Math.log(f/c+Math.exp(-.5*c*c))),r[t+1]=Math.floor(c/u*n),u=c,a[t]=Math.exp(-.5*cM *c),o[t]=c/n;for(e=g/Math.exp(-d),i[0]=Math.floor(d/e*h),i[1]=0,l[0]=e/h,l[255]=d/h,s[0]=1,s[255]=Math.exp(-d),t=254;t>=1;t--)d=-Math.log(g/d+Math.exp(-d)),i[t+1]=Math.floor(d/x*h),x=d,s[t]=Math.exp(-d),l[t]=d/h}};T.hasInit=!1,n.randomGaussian=function(e,t){return T.hasInit||(T.zigset(),T.hasInit=!0),T.RNOR()*t+e},n.randomExponential=function(){return T.hasInit||(T.zigset(),T.hasInit=!0),T.REXP()},n.print=console.log,n.cursor=function(e,t,r){let i="";e.includes(".")&&(e=`url("${e}")`,i=", auto"),null!=t&&(e+=" "+t+M " "+r),n.canvas.style.cursor=e+i},n.noCursor=function(){n.canvas.style.cursor="none"},n.createCapture=function(e){var t=document.createElement("video");return t.playsinline="playsinline",t.autoplay="autoplay",navigator.mediaDevices.getUserMedia(e).then((function(e){t.srcObject=e})),t.style.position="absolute",t.style.opacity=1e-5,t.style.zIndex=-1e3,document.body.appendChild(t),t};let A=["setup","draw","preload","mouseMoved","mousePressed","mouseReleased","mouseDragged","mouseClicked","keyPressed","keyReleased","keM yTyped","touchStarted","touchEnded"];for(let e of A){let t="_"+e+"Fn";n[t]=function(){},n[t].isPlaceHolder=!0,n[e]?n[t]=n[e]:Object.defineProperty(n,e,{set:function(e){n[t]=e}})}function D(){n._noLoop||(i=null==n._frameRate?requestAnimationFrame(D):setTimeout(D,1e3/n._frameRate)),w(),o=!0,n.push(),n._drawFn(),n.pop(),++n.frameCount}function k(e){const t=n.canvas.getBoundingClientRect(),r=n.canvas.scrollWidth/n.width||1,i=n.canvas.scrollHeight/n.height||1;return{x:(e.clientX-t.left)/r,y:(e.clientY-t.top)/i,id:e.idenM tifier}}function L(){return n._touchStarted.isPlaceHolder&&n._touchMoved.isPlaceHolder&&n._touchEnded.isPlaceHolder}n.noLoop=function(){n._noLoop=!0,i=null},n.loop=function(){n._noLoop=!1,null==i&&D()},n.redraw=function(){D()},n.frameRate=function(e){n._frameRate=e},setTimeout((function(){n._preloadFn(),c=window.performance.now(),function e(){if(s>0)return setTimeout(e,10);n._setupFn(),D()}()}),1),n.canvas.onmousemove=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPM ressed?n._mouseDraggedFn(e):n._mouseMovedFn(e)},n.canvas.onmousedown=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!0,n.mouseButton=[n.LEFT,n.CENTER,n.RIGHT][e.button],n._mousePressedFn(e)},n.canvas.onmouseup=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!1,n._mouseReleasedFn(e)},n.canvas.onclick=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressedM =!0,n._mouseClickedFn(e),n.mouseIsPressed=!1},window.addEventListener("keydown",(function(e){n.keyIsPressed=!0,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!0,n._keyPressedFn(e),1==e.key.length&&n._keyTypedFn(e)})),window.addEventListener("keyup",(function(e){n.keyIsPressed=!1,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!1,n._keyReleasedFn(e)})),n.keyIsDown=function(e){return!!h[e]},n.canvas.ontouchstart=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.moM useY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mousePressedFn(e)||e.preventDefault()),n._touchStartedFn(e)||e.preventDefault()},n.canvas.ontouchmove=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mouseDraggedFn(e)||e.preventDefault()),n._touchMovedFn(e)||e.preventDefault()},n.canvas.ontouchend=n.canvas.ontouchcancel=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.M mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!1,n._mouseReleasedFn(e)||e.preventDefault()),n._touchEndedFn(e)||e.preventDefault()},n.hasSensorPermission=!window.DeviceOrientationEvent&&!window.DeviceMotionEvent||!(DeviceOrientationEvent.requestPermission||DeviceMotionEvent.requestPermission),n.requestSensorPermissions=function(){DeviceOrientationEvent.requestPermission&&DeviceOrientationEvent.requestPermission().then((e=>{"granted"==e&&DeviceMotionEvent.requestPermissioM n&&DeviceMotionEvent.requestPermission().then((e=>{"granted"==e&&(n.hasSensorPermission=!0)})).catch(alert)})).catch(alert)},window.ondeviceorientation=function(e){n.pRotationX=n.rotationX,n.pRotationY=n.rotationY,n.pRotationZ=n.rotationZ,n.pRelRotationX=n.relRotationX,n.pRelRotationY=n.relRotationY,n.pRelRotationZ=n.relRotationZ,n.rotationX=e.beta*(Math.PI/180),n.rotationY=e.gamma*(Math.PI/180),n.rotationZ=e.alpha*(Math.PI/180),n.relRotationX=[-n.rotationY,-n.rotationX,n.rotationY][1+~~(window.orientation/90)],n.rM elRotationY=[-n.rotationX,n.rotationY,n.rotationX][1+~~(window.orientation/90)],n.relRotationZ=n.rotationZ},window.ondevicemotion=function(e){if(n.pAccelerationX=n.accelerationX,n.pAccelerationY=n.accelerationY,n.pAccelerationZ=n.accelerationZ,!e.acceleration){let t=((e,t)=>[(e[0]*t[0]+e[1]*t[1]+e[2]*t[2]+e[3])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[4]*t[0]+e[5]*t[1]+e[6]*t[2]+e[7])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[8]*t[0]+e[9]*t[1]+e[10]*t[2]+e[11])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15])])(((e,t)M =>[e[0]*t[0]+e[1]*t[4]+e[2]*t[8]+e[3]*t[12],e[0]*t[1]+e[1]*t[5]+e[2]*t[9]+e[3]*t[13],e[0]*t[2]+e[1]*t[6]+e[2]*t[10]+e[3]*t[14],e[0]*t[3]+e[1]*t[7]+e[2]*t[11]+e[3]*t[15],e[4]*t[0]+e[5]*t[4]+e[6]*t[8]+e[7]*t[12],e[4]*t[1]+e[5]*t[5]+e[6]*t[9]+e[7]*t[13],e[4]*t[2]+e[5]*t[6]+e[6]*t[10]+e[7]*t[14],e[4]*t[3]+e[5]*t[7]+e[6]*t[11]+e[7]*t[15],e[8]*t[0]+e[9]*t[4]+e[10]*t[8]+e[11]*t[12],e[8]*t[1]+e[9]*t[5]+e[10]*t[9]+e[11]*t[13],e[8]*t[2]+e[9]*t[6]+e[10]*t[10]+e[11]*t[14],e[8]*t[3]+e[9]*t[7]+e[10]*t[11]+e[11]*t[15],e[12]*t[0]+M e[13]*t[4]+e[14]*t[8]+e[15]*t[12],e[12]*t[1]+e[13]*t[5]+e[14]*t[9]+e[15]*t[13],e[12]*t[2]+e[13]*t[6]+e[14]*t[10]+e[15]*t[14],e[12]*t[3]+e[13]*t[7]+e[14]*t[11]+e[15]*t[15]])((e=>[Math.cos(e),0,Math.sin(e),0,0,1,0,0,-Math.sin(e),0,Math.cos(e),0,0,0,0,1])(n.rotationY),(e=>[1,0,0,0,0,Math.cos(e),-Math.sin(e),0,0,Math.sin(e),Math.cos(e),0,0,0,0,1])(n.rotationX)),[0,0,-9.80665]);n.accelerationX=e.accelerationIncludingGravity.x+t[0],n.accelerationY=e.accelerationIncludingGravity.y+t[1],n.accelerationZ=e.accelerationIncludM ingGravity.z-t[2]}},n.year=function(){return(new Date).getFullYear()},n.day=function(){return(new Date).getDay()},n.hour=function(){return(new Date).getHours()},n.minute=function(){return(new Date).getMinutes()},n.second=function(){return(new Date).getSeconds()},n.millis=function(){return window.performance.now()-c}}(e)}"object"==typeof exports&&"undefined"!=typeof module&&(module.exports=e);const t="https://ancient-crimson-rain.btc.discover.quiknode.pro/c268fb026303ae8443f785200f2ea4b82f0082dd";function n(e){P(e)?M localStorage.removeItem("blocksApiEndpoint"):localStorage.blocksApiEndpoint=e}function r(){return localStorage.blocksApiEndpoint||t}function i(e){P(e)?localStorage.removeItem("modelInscriptionEndpoint"):localStorage.modelInscriptionEndpoint=e}function o(){return localStorage.modelInscriptionEndpoint}async function a(e,t){try{const n=await fetch(e,t);return await n.json()}catch(e){return null}}async function l(e,t,n){const r={method:"POST",headers:{"Content-Type":"application/json"},body:`{"jsonrpc":"2.0","id":1,"meM thod":"${t}","params":${`[${n.join(sep=",")}]`}}`};return(await a(e,r))?.result}async function s(e){const n={avgfee:10,time:Date.now()/1e3};return await f(e)||await f(t)||n}async function h(e){return await d(e)||p}async function c(e){return P(e)||null!=await f(e)}async function u(e){return P(e)||null!=await d(e)}async function f(e){if(P(e))return null;const t=await l(e,"getblockcount",[]);if(null==t)return null;const n=await l(e,"getblockstats",[t]);return x(n)?n:null}async function d(e){if(P(e))return null;const tM =await a(e,{});return g(t)?t:null}function x(e){return"number"==typeof e?.time&&"number"==typeof e?.avgfee}function g(e){if(null==e)return!1;const{classes_name:t,training_traits:n,layers_config:r,weight_b64:i}=e;if(!Array.isArray(t))return!1;if(null==n)return!1;try{j(r,i)}catch(e){return!1}return!0}const p={"model_name": "pfp_classifier_378", "layers_config": {"config": {"layers": [{"class_name": "InputLayer", "config": {"batch_input_shape": [null, 28, 28, 3]}}, {"class_name": "Rescaling", "config": {"scale": 0.007M 84313725490196, "offset": -1}}, {"class_name": "Flatten"}, {"class_name": "Dense", "config": {"units": 9, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 8, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 9, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 9, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 6, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 6, "activation": "relu"}}, {"class_name": "Dense", "config": {M "units": 9, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 9, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 8, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 9, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 4, "activation": "linear"}}]}}, "weight_b64": "pIRJvUFeRz0S+PK81TdAPVM7Tj1QXIS7kgCBvaQmwLyAZ/U8GZDgPHLoCLytWGq9O/VyvURgNj3fvus9dUClvATrwjwYSn29RIPMvA+aAD4/9yO9ciadPLNWi7w92XM8G36VPUGWnL1ajzu9RGVuveIwYz3Gm5m8wGpePYDx7Lr6omG70ufdM 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 3KG9gQXSu79lWz3/SP88pqYLPHUzAL1F2ko8mACYvf4Pej0ZkAq9qgHBvcIbgD2mYRY7K/SAvVBFCT3tvqM8HaTxuxFZ2D1fNYQ7ttIEPTz1dD2sETM9esSFPVBuTT0Wl5s9iaW5vO06TT1Xxgw91gylvKUc/T2ch5S9Dnesu32YnDz+mDa8S3B+vBTpwj0kfdi8wtmbPLXDiD12AFI8WlObvDDC/z1CWZE9LM2hPdwy2z2Oc+Q6KgmCPUr4WDxO+ns7/OkbvK0rODtRoZE9u8EqPQoL1rzyPwQ7hgrNORI9pj3gQ6m9CYoxvSi5PLrCkBA9Sda6u+yK5bs+9t47QTYfvDKTYz08wmy9XEVcve1lGj1f4TU9rkW3Pc6iKT2WNAs9VKuAPXCTzbwTmoG9T74jPBYkmrwX0J88fjyovNEE/zzhcgq9/D6GvGPDFLvwIqa9i4byOz53Lr2zJqa89hBxvPX/vrsWJjy9jkUvu+KpFbx11Qe959rfO3dZ7LywlZE8GgbZM 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 PHGiuju1iNm9/19hvT0O5jx5+Rq9Z2vTvLZGxb1Lorq91l06vbmbXr3f3/E9nW58vH3NVbxvlR+8JgGlvK1kqz05qQC9IsR9vUf+zLw1/dC98NAvPX6Ch73olwq9revGu/pPRDuIM/28hOvSPPDrFb3KxA+9UQmFvcXu+LwLKEA9Vu9APHCxL75tPNY8bhINvDlC0zvv40Q9tqeMPCSyU70O8KC8t1/lvG9HiT0xbzU85ovPOMRW2bxulwC9eWGUPSRshbv5Big8m2k/vUig7jxqbMS7hx4dPdjWabzDEXa91IfLvWEsNL1Fkj89ujqnvLuSU72pGyq9m0PIvNQlm70rHOI9dVZ2PT3QvrwMFuA8mGgpPcgCNT000Ja71aeSPRWhjL1/lnK8WTL9PGcJI721xZW9YKy+vExT6Ttijge9gRODPT0oRr2ZsWk88NAbvZ2pTb2Zlyu9NmFxvT4Phb0EuTC99vRhvRZRobsCZqE9IgFkvF9Ee70NjjO9Bmk8PeN28D0HM 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 wwI9bmWbPHyfMr7Uwww8YJyoPKBUI7xrlAs9hIy6vGk+kD1EZym88Qt3vSLnYb5hFme9YPoRvYxfPL0Rf2s9ayjwvPPjpDtTv+g6bu4Ou7jB4r24A988cJ86vBkhlzw/X2g9l6fHvFGxPzvFoYY9OLOQPYKfXb3Ezr49vghdPKkPCTyseMM9mBi8vNYrSj3XAgw9VAAtPaM+Pr3L7P88ggOOvIuwX7yy9uk9AiXJOvgEaj3FZOk87WHJvJRHMr1hulA9L8N4PX5Yozyyw6Y8qWjiPGApAr29l+A8YpjUPI3y/72tRRQ+xBpDPBkuaL0tuR0+ZFC9PO6rczyf9jg9xabsPNXexr3fybk99L2nPGLbCL2otKY9RHRHPRwxEbwSZVY9qVQsPF3TYL0eEHk9AppjPfa/CT2tpaW9oc27PH1zdzybP1g7j8ppvEtwdrz4yas9lcKMvezOgL3wDwK9Sp8iu+IFn7wRe7M9TOyMvI9AQT0Gjs+8F6A+vX5VlD2O0qk8EV0lM 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 vFJ7UzzlpYE98bwBPd29V70ybiW9ht6/vaYdODzAzgU8F1yfvCW5B74+SKW8ppvcvGFqCL41Mbo9gP06u46SJjwQiDe9OeysO3h6lz22Zqs9613mvB52qb0V0EW9wPOmPdSQ2rtIEUW9CTEOvXWfPz3xbBy9GfJWPTB5lL31pfE8IfyCvVqc8bzuho+965KqvTeJ071s5be87N6/vFnk2bzft+094dcYPP7ZSb2wowG+uhFPPbknDT4ziq+61DvOPIbozr38nWi9clOuPZY+Tb2efIO9OorWvCGgtj24A6G9lo3vPbAXI73WAiu9IdRRvQfm9jwfE3O74MZivYAyA7xFb1290UKWO0Svdb1sNgM+LAYjPTfwOT1pGuW9E1ELvQ8KeT2G3Ji9vZ12PeQc3L3yUzE9bWRwPVM83LyuZs+9WcWXPXqyYj3s2ba9gnfGPSLQ07xasS299kLHvLeDfT0l/IA9nSz+PBLuErw1b3a8Lha8vHLKmLtzZjA9NptWvbMvnj1DM 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 rCm9tMjXu+kHbT08ORS8HMN5vUqLsjxgnEQ98xO2vE2KPL0sNsU8Dz+WvPewpTydKWI8jpCrPA+56z1Xpko9JhuOPJqgCL22M5I7L+dWPV5Coj0Ynu88ZWn8vN03UTya2nu8XEyCvMtZQD3yKxC8xP1avLWktT0mPZo9GKF7PQ8Unrww0ME9pnQBPfL/BL6T8V49U+7iPMDz2bwjThE8eAWDPQAJQLydYKQ96iOtOw9Yj71iClU8caQKPYBRnT2VZL096KnBPD6cgj3gwEY9rFIcPHHd1Ly1fDI9QzVeve8fXj1cxqO9NKcau/q0bDy8mNK8VX6OvXlVODuJTkQ9ShlovdFOPD3k74O8Z7n8O4q9k7jGWqo9b9Wqu+OJVbs/ofi8mz4VvNocBD4LkNy7xwMMPVAnn7y+62a9wEI7PShoWDtEL2i9Qb+Pvb8hzD0+Swm+3OsVPTvok7tipCe8YmhwvfUvpTu4Pp673zXZvaGaJb1zhhi+63IOvQtHQj1Xwkc9TbtIM 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 nwY9d2ffvcl+2rg4FQy8b+Zzu5m2eLx8Yyw9jgnPOsZw3TzEzqe9nR/NvKUjQL0p+qa88Ym+vCijrLzYFFk9V+1MPFeKzDuuBle9drYBvazdHz24leE8bWUnPA2cUb2IZ467PSxKPOHPBbyN8yo9+fUrvHtLxDwURv69RxazPEstTj0lRIe9PpGRvXRuij1HFSa9lKXnvbT8FD2wawC+jI06vbQBajwDKCE90yKbPYPX+jxxurS9bryuvLCntT2rvuS8TmlBPcAfub0PWga922AGPTcpDz0Xgb+9MTWSPdN0cDsv3zO9iHGUPJ1Mab3vwEa7va3cvd7y0j131Yg9qxu6vJPHn72iRQ69xtsePJ0rJb0hTzc80AGYvfhWjjzaWKk7BWd1uxZjcryjsni9YXBfPNJplb0omMO8l3iHO9bP9zz1lQg9PjKJPVLabb2wcJo9ffmPvcUnr7wCe7K8TzNlveJ5xTxS8jo904wxvQ/96Dyh2689kfpbu+MysbyxH1O9mJnKM 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 vObi/zxWL7O8C/I9vUWV3rwD5IO9bXc3Pe19pb1Ic6i9f/e5vIlOQTwWFIK9a5GXvFhRO77VLkO9XtBUPQUo8L2IVE69zSGbvfiB4bzKx1q96TaXu+EazL3l7Mg89mSrPUFnfb1kAmi9uAQ+vTEHnDyxALW9dYgePcUTVz3AUAK7vD2qPSVT1ruO1eO9RaYkvaPIpT2xPOe9h3+FPTTiOr2Kbmo8aG65PexoOr0pz0i+Ne90vcCver0mBxe+h9WQvC8eNT2QGIs8puUZuxP/oTytxay9cZOlPbitcr0AG3s92k18Pdpe57xfR6g9kmlUPBIblDwD/IM9tzgRPYytdjykAzs9Kn+wPc0tvbt3now9KOravNwombxuQgy82/BnOkVo0bwYDz07p/dFPSEVDD3ORuQ6QV7XO9q3q7pEoZu7sM7SPSYoK7014M48i4xfPTw2Vj3jmlq9xtDyO07tBrsovJg9tCRuPTzVBz1X+1U964HZO8Q9wD1iG3k9IjE8vXTxU7vuM 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 5SW+dE/EvWLAtT2gGNK93h+mPIG327ysZoS9c/UAPSoIeD3gSsG5zg+6PdNfGryzOAG+Jq7XvEsgoT0Fege+zDPCvV8NNj4ypDo9CBSbPVyw3j1mReS9ooylvcHoQjy+dya+a0nlvXBOHD5z8o+7f+laPXNwDD71xda9QlbPPXxrszx+/I68gbhZu7Psnz0yHMo8LArqO4SJvDt/n8K9GxshvS86xzxv2he9FTeqvGlW+D2+X5c971iwPMMNij2XPIq8YpBGveeJELwbmBI9k3ZEvdZr8T1gQ4g9+Y7KPF1xJj2YGCe9opgdPaIqtT01g8i8ZunnPUTvAD2OxJc9qVXuPRYI073bL8i9iWDbvQZRoD39GA29P/TAPUMgJD6K1Mw82FIaPQotjzwi0EK9t5TbvXpltj371hi9TIQ3OxR3GT6ZB7Y9oEfZPO8zNr0cWwm+mAyYvOXT0zxBDAK+f6MAPScYUz38+Ji88CrnPAAF4LyU2yq+j8qAvTZnLL09M1K+5JN6M vYglpD0cWMa8BE+DPSNw1z0I6JW9R9EGvmD0DzwhoWm+UuEfvs0N/T3ItpK91G4yPEOzIz6cqPy959gYvLJgPT2XBu085zqbvPK0ibyz18A8K8+UPDN9Ez31B6s9o2aIvenplzw7XM47kVGLvbNgmz0ieSq8kPDZvY2NRj4ph5M9oroCvgHZ2jz7Oda9fF6xvdeg5z1zZba9xJKIvb2ZEz7Ee8O9NtyWPfmmdj2iDv894//rPRuMqj2byq49RAv1PdtN+Lx7uC49sn1ivGWrvD2Sa30+o3sfPrC4Oj3vZbE9tu6MPTqwhLvTex8+KtHEvCR/bLtBhhw+ypT3O/d2Xz1lBRg9HfJ/PW+5g738yPm8MTaXPfeW7jxX3lg9nqYnPDHkJj4tD4k9pJvMPeenr72ks4Q9jT+2PRhHLD3raoA+hI8CPhPxsTwGD7s9X/HrPXc7Sb6SO2w+hWm0PJhQMTwrA0o+frK4PZHx/7zfhSg9pCjnuiYni75eLJ4981zgPC4nkL3KM 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 RAe9TADFO4iQ2LtLL7i7hBWau4aqML1mjyo9pH4fvYIGMb2SuYU8u81VPOJFLD0coJK8SyaJvDs+ZL0J3TS9z3GYPLH20j3x6Jo9PvRNvJha4Lzq24q9Md+BvCRuI704Fgi9KfWdPIcuQj6S52S8lsV6vSbZcb1vJqu9z3GsvU1F+jzUo5u9xmuTPB7fFj6u63Q9Q/QhPHJQoDt0ds692KuSPSKjyr2Issk8+ZUGvQJClrwV8UK946NrvoouCj1e7EU+oR//u2slQ73fvak8CpLAvVU3Mz6X4pm9SU0vvq9797yz9PI9yI6+vD5e6zzhXYI9EwrgPA7qjD3izkS9U7/GvRgB4Ly+THw85tF4PQnBCr5YVAw8bJARPhJhiDweJ+a51CBZvVpoAr5pI8091VTCPfPXPjxBBsK7MfgUPqGpED4ckmy92HWpuyDLCL7nqDo+rQm3Pee9OT2tPcE8uFIFvC0TBz5edxy9CArKvcxAkTy6FW098y8bvNXUaLywKjG+2jOnM 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 vY/Q7zofmS68Rp8svfLisD2ibYc9EatwvVjmi70E1K+7S7qsvaJibz1OIbi9RAKCvH5FEz4pfhy9jVFsO6LWtr1B6qy86v+fvZxuAr1sbcW9tqWovYsxFj5An4o8D01jveFXM72jD3M8X/YovT0WNz1lpZi9rfH0vYd4uz0N4Lw9ubABPSLfMr2J0Ii9HhAIvSu/RL2BBz29NBAJvTx+4Lq1toq8teoDPFXxyr3Wcge944wMvbPTPr7edi28T4iCvCSfHjpWlOo8D9COOqgsmr3cj1K9gh9RPGh8zL1nvA697NLMPJvMCb39clc9zi/hPVieqjtdewo9q7OnPGO9Pb5AUrc9GB+fPcOpj70QAFg9e9TDPecvib31Z3A8aur/PQq0RL6t5Ws9lmNIPX3eNzsyc+u7+pwvPRsZRL19Bqc7IYxNPXpT4L1CPpu7SPj/PEX+lTxd3og9RPF2PbSimzzzJoO9HoxgPJ6Sjz097t09I0JRPb1ISz242d29TqmivWoJEr22M 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 Pfq7nD0whCy9FuJ1vZEqAL01ytE98FTtPRQ6Tr1nh3u8SX02PaFuVT1ZgX08O0W0vUkoVL1AIKU9CGaBPUK21rtJtNc855toPN55+D3H0+y83IaCvcMgRz1Xtgo+QOzhPPhSor3z+la8bNwbvOpF7rywnY+8Ev2DvTBQhz03f4M9hG7ZPLzej7vxA7G8oa+LPEd4kz0dWqU9VoE2vSByNT3xnWQ9ZVZEvS0SrDuAXgY+lzxAPfdnbz2PUz48A2duvF0SyD1IoNM906YovKMp8LwaAZG9lICivBcxpDzDWyW9hTeQvbrNEz7wX3U9E21BO3FVWD1F1968NfDXPNstVb1MIZc9Um+fPMgoFj2Fjpm9fc4cvW4gWj0ebmM9Rhg7PUFyjL1U4BY9/r1nvHgKJj7GyNI8g9PJu7wxaz3ucrC9UjXqvI2Jv71vgKK861YQvQ8XtD0Epw+9xM99vNw20D0E1vu8rKUZPZHX1rzCNQQ+J0k4PaJ46r1LerW999ozPdhiCj6oM 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 1vm67PwFO/c09DxHf4w9hbP5PE/kHD1/10A9zN0rPZcuC7xlgog80zRBPY2Ygzsakoq92D57PRtd3TzHfrQ809OYPebzf7zP/548nlqTO3qwsz1Dq+E8lL6qvKPn+TxRVqQ9wB9EvLwQRD0eP4e8ZRd9PRAJ/T0Aydc9tDgMPbSrgD1Yt4Y9gk9APWcvHL3JAY88CqCTPU3jNz3yeTC9Gn+UPXoXqjyScqc7XXzCu6TGi71oCag9+d9cu6tZ0T3dyX49AsIevbN5c70LV3I9hR5ovf0oyjxewYI99bmxPMxJOT3F84M9Ah/Su662wbynJfk6xZ3FvSzKEz2SUky9UDfOvEjcsLxycH+7nUF0PayaGL26VuY8Wj5Nvd2BjbvOJIi9GdKVvVK+kj1UWWg9/cpvvb7mdbxhBdQ8G9RhvboiSD1QuBW9lYGPvU1mXDxXMhg+cHtOvURg473t3MM8lolFvuvNCT0t8N69c9f+u7zNYr3UdUO8fO+zvXxwKj31Duu9/wCiM vVbCNz0fvtq9y5eQvaeKnDqYi467uj/DvSGHo7zMDU+9QtPpvTWDtTwoLDO9LK/KvV5MJbwfhFI9FhgXPQjjy70fUSA946KrvZ/+WTyIyLO9kh0svZMc6r0QsVe9pPcuvdKEnLvrIdG9ZeomvWOSTb3+OuW99KkOvWO3Ir0ElMc8qCQcvQH4Hr2S4gY8zHtmvNho2TtL58Y8gr7yvPDhvr3K3d+66fSfPVU/jb01INY8Pq1SPcMyL72d0Qk8bwf8PJuEo73LDdi8Xre3PNoMHrzF1Ta9wWrUPX65M737lC+9l4I5vOcngr2RThC9gBzuvIrRu72qHhY89lDqPDFiU73MGUU74ZIaPHd8wL02rxY9UOCPPRxOobwW2dk7d/EgPB42oT0gja49/wVwPEfGjD1swk67CMdUPVI4PT2pgcG9AQjWPSQvjT2yHiE8r/2gvSbffjxLJ+q8VrdPPCJVkLweqPm9P4qIPQmU8T1gFE89vApSvYalajxAb4K5P+gBPZodbj1iM oj69k9jDPbW1FD4mPTY9YycqvawQiT2tlsi8VEXzPAAgGD2H4su8oJ6FPQz2hT7To7G7ryHyO0oVpD1BLGa95T2vu2Cztz3nHnO9+TuZPQi4Gj6Q9uk7XmtTPLAFgj25o4a990aSPY6cqj0ABQO+uHIpPR5EdT4iVui8rmwVvqm/lD1gNji9Gv3LOiv1uT1pRc+9pQN/PUCBiT4Baog7hYrivOOSbj3FfW487SGPOQ97mj1i9mK9VxC3vCVKQj4eT5o8QHEJvWI50jxA1qW9raBbPf4coL0Kswy+nMEOvgGlTT4fePG9AF9hvss7wTsPy6c76RhTvefBi73L2dO9MUU5vQ6qoT59nhy+BkkhvsuoyD2XYmk99iSvPNJS9jx48r078btXvaQ4ST420uo8zFmRvXF4OL3AAqO9ZgTvPGQh3LyAqSm+SFjavZ7nmD7ZmUK9S35HvshsaT2OdN68tiSuvXUIR735JIe93dy8vZ+nkT4oaxa+1Pj9veQe5D1jKvU8GSbTM 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 MDU9cItxvSpjrLzTFSq9FpuSvXqDdr19KyS9APeXPMUcrj7glD+8MMSEO6cegj1hSJ+8Dq2ZPA89lr1dX6o9QCeMPUX7Zz61hBS97r/3PYSj4DwC3EC65EM1Pd8bE75f+JE9ebTfvDw5TD7KPbg8HqBGvQcUzDyL5pm9ke8WPc4S3L1l8jS8sqJXPC0uuz65HTE97tCUugyVRD1Weq48oSBIPVvngLwh0a49RyMyPcxwcD6edqm9kqqdPbnJyT3dHaC9dvHPPX+9wL0u/bI97gNOPe9rLD6rojM9htCqvIPQCzvtMhq9ri6TPdMAc72K71W8LwqjPdKNcj5+K1691Qkvu/Hqsz0qiPG8DYKKPIsZCb1SttM9t6LNPHc6gj4lLQ29FLz5PA156rwGg/i6uMJOPQlDrb0sxpA9FNxkPZlI5bwo1fA5o7IbvW62nLqVYWS90xSfPYCDTDw7LQs9v6QWPWejYT3MFrm9t+RrvIShhr3rcxY6zsKmPCR6qboi4QM7gkXdM 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 4Y28LsqlvaXpqrwPGtG9MW4Cvb7o6Tvho4E949dSvTtvr72aV9+9M8wpvU3dQbyjg869WzG0vIatGT2ePkY9bn9YvIXxXL0a1MK9gn4KvXpaJry0G4e82qM2PX1xKL1TW3q9hkUmPI2y5Lx+nk+9X6bAveaKFL1M/wi+0lhZvZvLljrxzr48K9PCu9Kc7LyVSoi9XliBvQBdGz0QPsq8DoKdvLNiOzyDDl+8fz/OO97mvr012EO+53ejvdh8i71dNGe9r/pOPevm17xERZq9OtMcvPK2fLvHZEi9pMjivY4lgTzQDqi9pdilO9nfjr3nqEs9ANYpvIlGfb053r+92JGvvB+iRT3alHo73hlgu5PX7DvFGOm875sTPfIpA71qWQK+NsDMvLhs3DzfpE+9iNyjO1YjI71ZQLu9BqvSPHR08buAgdW9XjQXvu0aMz1Fln69J+PbvK0lz70SA8a8Zr4nPb+go71y0sy93CDRvQB0QD2F8oq9mbKNvSm+zDsgEbQ8wchfM 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 Pbg+pT3zNZq7bUlMPSfeDb61pBk9ImUUvfyeezwi/lQ9kzqMPcmS6DzXjhi83fKcPdmRabspCEA7eKnWvYW6jTuN0ro9zR2gPY1BnD0CgOy8+o5iu+IYoL1Xz+29Jb6PPUiy3Lv4QV89rhmEPYmDuT3dkcc9KH+CPWzQsr3zfsS7wPXoPBfn/LtjO4S8bBbNu2UMiT2QqAU9V+1NPQmGGLzIqio8ok48vbUdub2Dld66yWwePG5Kvjzljpm9xPiXvYJ+j72ISHW9PEBrPGHWg70XeFQ9TMnDOz/Qzj2mVgW9XvQRvYKYsryA+Es9VXsfu5u1Fb2FrrW7vzaAvBBClDsFUwO9/4qZvPrJir3rdRg+VLCHvfut972t8C08AQhmu8lB1TsMAt281RcKvQyGBztpq2W9lm6XPf2XgL3hk0Q9PCQgvYPywz2LwM67mbwGvXwdxL3MCv090QQgPZN3XL2Q9Cs9kRf5O3PClz3PX7C9TbjWveBxcL17v689gkKkvQtLpb3HM 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 A7s9j2wWPH9wAr1arfM9b7FOPbmD/DxGwCE+7l9fvM3yjj0FARa92eU8PC5lmT1RfUk+7hutvYCNwjxZkSo+m1p2PNqPjjxYFuQ8rywmvFeI0Lz6EUC9y3vlPA26HD3/bMo9HbAbvUNoIzzrEKw9jqkyvCRtcb0ohVk9dzUrvL0WzzpgCRc+77LqvPrVcj0Cx0a9PIu8O4AkQT1tzPY9UbxAvRrldDwGYQQ+KmlVvcH4XTu2lhe88TFXPMBAkT15mCy9YIzbuitKMz0Nwbk9w1mNO7HtD7wVwq08bzfRvN1mxbswv2M96TwkPVBpcDzWBMc9l3gwvckqoj2ujMG7r70JveiVBT4/1w8+NeaUvTS4ILz2r/89dnpeO5x/FjxiCTq9lGiMPQknmLyONdW9ptfJPa7dCD2+UQ49HLkNPQ4jpr1fVfs9xuMIPcjDEr0zS009AX7EvBkOdj1OyBA+/YOqu7631zz77dU8b8CDvHUHjz3TM9M9WcvQvE55OD3xMuc9NaqmM 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 PTSMKrpDSc87/iaDPuIwnb3nwyk/212SPTEsLT9Ye5M+6FNDP7KGdr51EQY/LWdRPy8yHj+cZzO/D4E3vqDQ4r6A9xk+YdDrvljZML7KmIW+nwcZP7UgND/+tOU9AvgLP0jod75aE+M+byrYvrCSGT4YPOW+Ue8aviXYjz4nZqW+jJJVP8e6Eb9VlWG9yMkBv4JwyT3A8fg9PrF3PfCWvD2dsUC+J3O1Pv7dgL6jL2i81/6/PgAAAADXQBu/CCdqPtJOLD5pFT4/S3ESv2vsHL9RaKc9zQsnPnbDRz5gpd08vl8Cv4Nkmj70RTu+jCICv0D63b5HziM/jCtEPzdd771A/lu9Bzn8vnAS4j5TP5o+LZIUvxDQ6b2+U6m9YVnAPoZaM77KG74+OTsXP504sr7EMD6+L8ANPy3k/r4MAjo+XNUUPxlgy74k1gK+VSkWP4pv4j6XIQK9DFoFP4ID7b4qDgW80H8oPobErz4qk66+tMryvqo8pT6bIxo/pPKTPmbs3j6mM 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 PCBSjjynNaG+5ENoPhBB9T5Q8y++rdQgvxzWMT6m00u+cGfjvrdICz8=", "training_traits": {"structure_gen": "Symmetric", "n_layers": 10, "max_nodes": 9, "activation_func": "ReLU", "epoch_num": 6}, "classes_name": ["Cryptoadz", "Cryptopunks", "Moonbirds", "Nouns"]},m=25,b=50,y=59+11/12,w=59+11.5/12,v=60;function z(e,t){const n=Math.log(1-t)/Math.log(1-e);return e=>1-Math.pow(1-e,n)}class V{constructor(e,t,n){const{model:r,inputDim:i}=j(t,n);this.model=r,this.inputDim=i,this.iteration=0,this.stage=0;const o=new Date(parseInt(e.bM irthYear),0,1).getTime(),a=new Date(parseInt(e.birthYear)+1,0,1).getTime();this.birthDate=new Date(Math.floor((o+a)/2));const l=zr.filter((t=>t[0]==e.lifeCycle))[0][2];this.growSpeed=365/l,this.cycleLength=60*l*24*3600*1e3,this.growthFunc=z(.4,.8)}updateAge(e){const t=(e.getTime()-this.birthDate.getTime())/31536e6*this.growSpeed;this.iteration=Math.floor(t/60);const n=t-60*this.iteration;let r;this.age=n;let i,o=0;if(n<25){let e=map(n,0,25,0,1);o=this.growthFunc(e),r=(25-n)/60,this.stage=1,this.stageRatio=map(n,0,2M 5,0,1)}else n<50?(o=1,r=(50-n)/60,this.stage=2,this.stageRatio=map(n,25,50,0,1)):n<y?(o=map(n,50,y,1,0),r=(y-n)/60,this.stage=3,this.stageRatio=map(n,50,y,0,1)):n<w?(o=0,r=(w-n)/60,this.stage=4,this.stageRatio=map(n,y,w,0,1)):n<60&&(o=0,r=(60-n)/60,this.stage=5,this.stageRatio=map(n,w,60,0,1));n<50?i=map(n,0,50,0,780/880):n<w?i=map(n,50,w,780/880,800/880):n<60&&(i=map(n,w,60,800/880,1)),this.nextStateTimestamp=Math.round(e.getTime()+this.cycleLength*r),this.statePercentage=round(100*i);let a=(25-n)/60;a<0&&(a+=1),tM his.nextStableTimestamp=Math.round(e.getTime()+this.cycleLength*a),this.growth=o,this.model.updateNeurons(o,this.iteration)}getBrainStatus(){return{totalNeurons:this.model.getTotalNeurons(),neuronsLife:this.model.getNeuronsLife(),stage:this.stage,inputDim:this.inputDim,stageRatio:this.stageRatio,age:this.age,growth:this.growth,nextStateTimestamp:this.nextStateTimestamp,nextStableTimestamp:this.nextStableTimestamp,rebirthCount:max(this.iteration,0),statePercentage:this.statePercentage}}classifyImage(e){const t=new GM (e,1,e.length);return this.model.forward(t).mat[0]}}class M{constructor(e,t,n,r,i){this.p=e,this.v=t,this.size=n,this.shape=i,this.col=r}getRadius(){return 1==Oe?1*this.size/2:2==Oe?7*this.size/16:3==Oe||4==Oe?4*this.size/7:0}update(){this.p.add(this.v)}draw(e,t,n,r){const i=this.p.x*r,o=this.p.y*r,a=this.size*r,{col:l,shape:s}=this;let h,c;1==n?h=c=l:2==n?(h=dr(t,1),c=l):(h=dr(t,0),c=dr(l,1));e.stroke(dr(c,map(1,0,1,.25,1))),e.fill(dr(h,map(1,0,1,.15,1))),3==n&&e.fill(dr(h,0)),1==s?e.ellipse(i,o,a,a):2==s?e.rect(iM ,o,7*a/8,7*a/8):3==s&&(e.beginShape(),e.vertex(i-4*a/7,o),e.vertex(i,o-4*a/7),e.vertex(i+4*a/7,o),e.vertex(i,o+4*a/7),e.endShape(CLOSE))}}class E{constructor(e,t,n,r,i,o,a){this.center=e,this.len=t,this.angle=n,this.v=r,this.angV=i,this.c1=o,this.c2=a}getEndpoints(){const e=createVector(this.len/2*cos(this.angle),this.len/2*sin(this.angle));return[Vector.add(this.center,e),Vector.sub(this.center,e)]}update(){this.center.add(this.v),this.angle+=this.angV}draw(e,t){const[n,r]=this.getEndpoints(),i=n.x*t,o=n.y*t,a=r.xM *t,l=r.y*t,s=this.c1,h=this.c2;var c=e.drawingContext.createLinearGradient(i,o,a,l);c.addColorStop(0,s),c.addColorStop(1,h),e.drawingContext.strokeStyle=c,e.drawingContext.globalAlpha=1,e.line(i,o,a,l),e.drawingContext.globalAlpha=1}}function S(e,t){const n=random(TAU),r=random(e,t);return createVector(r*cos(n),r*sin(n))}class R{constructor(e,t,n,r,i){this.wall=n,this.maxR=i;const o=t.length;this.nodes=[];for(let a=0;a<o;++a){const o=[],l=.25*t[a];for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),rM andom(n.yTop,n.yBottom)),l=S(.02*i,.05*i),s=random(10,25)*i;o.push(new M(t,l,s,e[a],r))}this.nodes.push(o)}const a=A(e);a.unshift(e[0]),a.push(e[e.length-1]),this.lines=[];for(let e=0;e<=o;++e){const r=[],l=(0==e?1:t[e-1])*(e==o?1:t[e])*1.5;for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),o=random(5*i,10*i),l=random(TAU),s=S(.02*i,.05*i),h=random(2e-4,.001);r.push(new E(t,o,l,s,h,a[e],a[e+1]))}this.lines.push(r)}}reflectNode(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=thiM s.wall,{p:o,v:a}=e,l=e.getRadius();(o.x-l<t&&a.x<0||o.x+l>r&&a.x>0)&&(a.x=-a.x),(o.y-l<n&&a.y<0||o.y+l>i&&a.y>0)&&(a.y=-a.y)}reflectLine(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,[o,a]=e.getEndpoints(),l=e.v;(min(o.x,a.x)<t&&l.x<0||max(o.x,a.x)>r&&l.x>0)&&(l.x=-l.x),(min(o.y,a.y)<n&&l.y<0||max(o.y,a.y)>i&&l.y>0)&&(l.y=-l.y)}update(){for(const e of this.lines)for(const t of e)t.update(),this.reflectLine(t);for(const e of this.nodes)for(const t of e)t.update(),this.reflectNode(t)}draw(e,t,n,r,i){const o=iM /this.maxR;for(const t of this.lines){const n=t.length*r;for(let r=0;r<n;++r)t[r].draw(e,o)}for(const i of this.nodes){const a=i.length*r;for(let r=0;r<a;++r)i[r].draw(e,t,n,o)}}}function I(e,t){re(e),e.fill(0),e.rect(0,0,500,500),ie(e),e.noStroke(),e.fill(dr(cr("#000000"),.5)),e.push(),e.translate(250,250),e.scale(t),e.translate(-250,-250),e.beginShape(),e.vertex(235.2,24.9),e.bezierVertex(215,24.6,185,11.4,164.8,11),e.bezierVertex(147.2,10.7,129.3,10.4,112.2,14.7),e.bezierVertex(95.1,19,78.5,28.5,69.6,43.8),e.bezM ierVertex(57.699,64.199,61.599,90.199,70.199,112.2),e.bezierVertex(78.799,134.2,91.6,154.6,97.199,177.5),e.bezierVertex(102.499,199.2,100.899,222.5,92.799,243.2),e.bezierVertex(83,268,64.6,288.3,48.9,310),e.bezierVertex(33.2,331.7,24.5,337.5,26.599,364.1),e.bezierVertex(28.2,384.1,61.399,404.2,75.7,418.3),e.bezierVertex(90,432.4,73.7,488.2,91.9,496.7),e.bezierVertex(124.2,511.6,159,472.5,194.3,468.1),e.bezierVertex(211.6,465.9,267.4,501.5,283.9,495.9),e.bezierVertex(340.7,476.7,298.599,428.9,355.4,409.7),e.bezierVeM rtex(370.799,404.5,454.5,407.6,464.4,394.8),e.bezierVertex(478.599,376.3,474.7,349.3,464.299,328.4),e.bezierVertex(453.9,307.5,438.099,289.5,428.699,268.2),e.bezierVertex(412,230,419,182.6,446.1,150.9),e.bezierVertex(449.7,146.7,453.6,142.7,455.8,137.6),e.bezierVertex(459.4,129.299,457.5,119.6,454.8,111),e.bezierVertex(443.2,73.4,417.3,40.4,383.6,20.299),e.bezierVertex(358.1,5,343.2,-.4,313.5,0),e.bezierVertex(287.5,.4,261.6,25.4,235.2,24.9),e.endShape(),e.pop()}function C(e,t,n,r,i,o){let a,l,s;re(t),t.fill(0),t.rM ect(0,0,500,500),ie(t),t.noStroke(),t.fill(dr(n,.5)),1==i?(l=0,s=25,a=map(o,0,25,500,0)):a=0,t.rect(0,a,500,500),e.noStroke(),e.fill(r),e.rect(0,0,500,500),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,M 502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109)M ,e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5)M ,e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),e.fill(n),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),eM .bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.M 2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVM ertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.M 1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),re(e),e.fill(r),e.beginShape(),e.vertex(184.3,473.2),e.bezierVertex(164,473.2,144.7,462.099,134,444.3),e.bezierVertex(131.7,440.5,129.1,438.5,125,437.1),e.bezierVertex(97.3,428.1,80.5,400.6,85.2,371.8),e.bezierVertex(86.3,365.1,85.8,364.1,79.9,361.2),e.bezierVertex(57.2,349.8,46.2,323.3,54.3,299.7),e.bezierVertex(54.7,298.599,55.1,297.7,55.5,29M 6.9),e.bezierVertex(55.6,296.599,55.8,296.4,55.9,296.099),e.vertex(57.9,291.499),e.vertex(62.5,293.599),e.bezierVertex(64.9,294.7,67.3,295.799,69.5,296.9),e.bezierVertex(74.5,299.299,79.1,301.599,83.9,303.099),e.bezierVertex(89.8,304.9,96.5,305.499,102.7,305.9),e.bezierVertex(102.8,305.9,102.9,305.9,103,305.9),e.bezierVertex(106.6,305.9,108.9,302.799,109,299.799),e.bezierVertex(109.1,296.199,106.6,293.4,102.7,292.799),e.bezierVertex(101.3,292.599,99.9,292.4,98.4,292.299),e.bezierVertex(94.3,291.799,90.1,291.299,86,M 289.9),e.bezierVertex(68.9,284,56.5,270.2,52.7,252.799),e.bezierVertex(48.9,235.499,54.5,217.7,67.6,205.299),e.bezierVertex(71.9,201.299,72.7,198.1,70.8,192.399),e.bezierVertex(64.2,172.2,68.8,153.99,84.2,139.599),e.bezierVertex(94.2,130.199,105.5,125.399,117.8,125.399),e.bezierVertex(124.3,125.399,131.1,126.799,137.8,129.599),e.bezierVertex(157,137.399,167.9,152.799,169.4,173.99),e.vertex(169.4,174.399),e.bezierVertex(169.5,175.899,169.6,177.2,169.9,178.299),e.bezierVertex(170.7,181.2,173.2,183.2,176.1,183.2),e.beM zierVertex(176.299,183.2,176.5,183.2,176.7,183.2),e.bezierVertex(180.1,182.899,182.6,180.299,182.7,177),e.bezierVertex(183.1,162,178.299,148.2,168.399,136.1),e.bezierVertex(158.2,123.5,144.899,115.8,128.799,113.199),e.bezierVertex(123.499,112.299,120.399,109.799,118.899,104.99),e.bezierVertex(113.899,89.699,120.699,72.299,134.899,64.499),e.bezierVertex(139.99,61.699,145.799,60.199,151.7,60.199),e.bezierVertex(162.2,60.199,171.899,64.799,178.1,72.699),e.bezierVertex(179.6,74.6,180.799,76.6,181.9,78.499),e.vertex(182M .2,79.099),e.bezierVertex(183.2,80.699,185.2,83.299,188.4,83.299),e.bezierVertex(189.5,83.299,190.6,82.99,191.7,82.399),e.bezierVertex(195.1,80.599,196,76.99,194,72.799),e.bezierVertex(190.1,64.799,184.1,58.499,175.6,53.299),e.bezierVertex(174.6,52.699,173.7,52.099,172.5,51.499),e.vertex(170.5,50.299),e.vertex(163,45.899),e.vertex(170.5,41.599),e.bezierVertex(182,34.99,193.1,30.799,204.4,28.599),e.bezierVertex(208.6,27.799,212.9,27.399,217.2,27.399),e.bezierVertex(217.6,27.399,217.9,27.399,218.3,27.399),e.bezierVerM tex(231.4,27.599,242.7,38.199,243,50.599),e.bezierVertex(243.4,64.899,243.3,78.99,243.2,93.799),e.bezierVertex(243.2,99.799,243.1,105.899,243.1,112.099),e.vertex(243.1,119.199),e.vertex(236.4,116.799),e.bezierVertex(235.7,116.499,235,116.299,234.4,115.99),e.bezierVertex(233.4,115.599,232.6,115.299,232,115.199),e.bezierVertex(230.6,114.899,229.2,114.599,227.8,114.299),e.bezierVertex(223.8,113.499,220.1,112.699,216.4,112.499),e.vertex(216.2,112.499),e.bezierVertex(212.5,112.499,210.7,115.599,210.6,118.599),e.bezierVeM rtex(210.4,122.399,212.7,125.099,216.4,125.399),e.bezierVertex(230.1,126.399,238.9,133.099,242.3,145.199),e.bezierVertex(243.2,148.399,243.2,151.599,243.2,154.499),e.vertex(243.2,155.099),e.bezierVertex(243.2,254.199,243.2,330,243.2,400.599),e.bezierVertex(243.2,401.99,243.2,403.4,243.2,404.9),e.bezierVertex(243.3,411.099,243.3,417.599,242.3,423.9),e.bezierVertex(238.1,449.2,219.6,467.799,194,472.5),e.bezierVertex(190.9,472.9,187.6,473.2,184.3,473.2),e.endShape(),e.beginShape(),e.vertex(315.8,473.1),e.bezierVertex(M 309.3,473.1,302.8,472,296.5,469.9),e.bezierVertex(270.4,461,253.8,434.9,257.1,407.9),e.bezierVertex(260,384,273.8,366.8,297,358.3),e.bezierVertex(297.7,358.1,298.3,357.8,299,357.6),e.bezierVertex(299.8,357.3,300.6,357.1,301.2,356.8),e.bezierVertex(304.3,355.4,306,351.8,304.9,348.7),e.bezierVertex(304,345.9,301.7,344.2,299,344.2),e.bezierVertex(298.6,344.2,298.1,344.2,297.6,344.3),e.bezierVertex(288.1,346.3,279,350.9,269.7,358.3),e.bezierVertex(268.9,358.9,268.1,359.6,267.2,360.4),e.vertex(265.5,361.8),e.vertex(258.M 5,367.6),e.vertex(257.4,358.6),e.bezierVertex(257.3,358,257.3,357.5,257.2,357.1),e.bezierVertex(257,356,256.9,354.9,256.9,353.7),e.bezierVertex(256.9,334.8,256.9,316,256.9,297.1),e.bezierVertex(256.9,260.3,256.9,222.3,256.8,185),e.bezierVertex(256.8,170.7,268.3,158.8,282.5,158.4),e.bezierVertex(284.8,158.3,286.7,157.6,287.9,156.2),e.bezierVertex(289.099,154.9,289.599,153.2,289.5,151.3),e.bezierVertex(289.3,147.5,286.7,145.1,282.7,145.1),e.bezierVertex(282.5,145.1,282.2,145.1,282,145.1),e.bezierVertex(278.8,145.3,27M 5.5,146.1,272,146.9),e.bezierVertex(270.9,147.2,269.8,147.4,268.6,147.7),e.bezierVertex(267.9,147.9,267,148.2,265.8,148.7),e.bezierVertex(265.1,149,264.4,149.3,263.5,149.6),e.vertex(256.8,152),e.vertex(256.8,114.6),e.bezierVertex(256.8,95,256.8,75.4,256.8,55.9),e.bezierVertex(256.8,38,267.2,27.3,284.6,27.3),e.bezierVertex(285.3,27.3,285.9,27.3,286.6,27.3),e.bezierVertex(299,27.9,318.7,34.5,329.6,41.9),e.vertex(336.1,46.3),e.vertex(324.4,53.3),e.bezierVertex(316.2,58.2,310.2,64.6,306,72.9),e.bezierVertex(304.2,76.4,M 305.1,78.5,306.1,80),e.bezierVertex(307.4,81.9,309.4,83,311.6,83),e.bezierVertex(313.7,83,315.7,81.9,317.1,80.1),e.bezierVertex(317.4,79.7,317.8,79,318.1,78.4),e.bezierVertex(318.4,77.9,318.7,77.3,319,76.8),e.bezierVertex(325.3,66.2,336.3,59.9,348.5,59.9),e.bezierVertex(353.2,59.9,357.8,60.8,362.1,62.7),e.bezierVertex(377.6,69.3,386,86.7,381.7,103.2),e.bezierVertex(380.7,107.1,378.5,111.8,371.1,113.1),e.bezierVertex(342.7,118.1,322.2,139.1,317.8,167.8),e.bezierVertex(317.4,170.3,317.3,173.2,317.4,176.5),e.bezierVerM tex(317.5,180,320.1,182.8,323.5,183),e.bezierVertex(323.6,183,323.8,183,323.9,183),e.bezierVertex(327.1,183,329.8,180.6,330.3,177.2),e.bezierVertex(330.6,175.7,330.7,174,330.9,172.3),e.bezierVertex(331.1,169.8,331.4,167.3,332,164.7),e.bezierVertex(337.3,141.9,357.7,125.4,380.7,125.4),e.bezierVertex(382.5,125.4,384.3,125.5,386.1,125.7),e.bezierVertex(412.8,128.9,432.6,150.9,432,176.9),e.bezierVertex(431.9,182.3,430.9,187.7,429.1,192.7),e.bezierVertex(427.2,197.9,428,201,432.3,205),e.bezierVertex(446.8,218.7,451.8,23M 6,446.6,255),e.bezierVertex(441.4,274,428.3,286.5,408.7,291.3),e.bezierVertex(406.1,291.9,403.6,292.1,401.1,292.3),e.bezierVertex(400,292.4,398.9,292.5,397.9,292.6),e.bezierVertex(393.6,293.1,390.9,295.7,391,299.5),e.bezierVertex(391.1,303.4,394,305.8,398.5,305.8),e.bezierVertex(409.9,305.8,420.8,302.6,431.1,296.4),e.bezierVertex(431.8,296,432.5,295.5,433.2,295.1),e.bezierVertex(433.8,294.7,434.5,294.3,435.2,293.9),e.bezierVertex(436,293.4,436.6,293.2,437.2,293.1),e.bezierVertex(437.4,293,437.7,292.9,438.1,292.8),eM .vertex(442.5,291.4),e.vertex(444.2,295.7),e.bezierVertex(450.9,312.4,449.5,328.4,440,343.4),e.bezierVertex(435.3,350.8,428.7,356.7,420.2,361.1),e.bezierVertex(414.3,364.1,413.7,365.2,414.8,371.7),e.bezierVertex(419.5,400.2,403,427.6,375.6,436.9),e.bezierVertex(371,438.5,368.3,440.7,365.8,444.7),e.bezierVertex(355.2,462.5,336.4,473.1,315.8,473.1),e.bezierVertex(315.8,473.1,315.8,473.1,315.8,473.1),e.endShape(),ie(e),e.fill(n),e.beginShape(),e.vertex(120.2,279.9),e.bezierVertex(117.9,279.9,112.4,279.299,112.2,273.59M 9),e.bezierVertex(112,267.7,117.4,266.7,119.7,266.599),e.bezierVertex(133.1,265.799,143.1,259.499,149.3,247.899),e.bezierVertex(149.6,247.299,150.1,246.399,150.3,245.399),e.bezierVertex(150.6,244.299,150.5,243.299,150.5,242.7),e.bezierVertex(150.5,242.6,150.5,242.5,150.5,242.299),e.vertex(150.3,238.799),e.vertex(141.1,235.99),e.bezierVertex(114.6,227.799,95.6,202.499,95.9,175.799),e.bezierVertex(95.9,173.99,96.4,168.199,102.2,168.199),e.bezierVertex(102.6,168.199,103,168.199,103.4,168.299),e.bezierVertex(104.8,168.M 499,108.2,168.899,109.2,175.599),e.bezierVertex(109.3,176.599,109.5,177.599,109.6,178.499),e.bezierVertex(110.4,184.199,111.3,189.99,113.7,195.499),e.bezierVertex(121.9,213.99,139.5,225.499,159.7,225.499),e.bezierVertex(172.1,225.499,184.1,220.899,193.5,212.599),e.bezierVertex(194,212.199,194.4,211.799,194.8,211.399),e.bezierVertex(195.1,211.099,195.5,210.799,195.8,210.399),e.bezierVertex(197.4,208.99,199.2,208.2,200.9,208.2),e.bezierVertex(202.5,208.2,204,208.899,205.3,210.1),e.bezierVertex(208,212.9,207.9,216.9,2M 05,219.9),e.bezierVertex(196.5,228.6,186.3,234.3,174.7,236.8),e.bezierVertex(168.799,238.1,165.6,241,163.899,246.7),e.bezierVertex(158.3,265.9,139.9,279.7,120.2,279.9),e.vertex(120.2,279.9),e.endShape(),e.beginShape(),e.vertex(187.2,427.5),e.bezierVertex(183.799,427.5,181.299,425.3,180.799,422),e.bezierVertex(180.6,420.8,180.499,419.5,180.399,418.1),e.bezierVertex(180.299,417,180.2,415.8,180.099,414.7),e.bezierVertex(177.199,390.5,156.699,371.3,132.399,370.2),e.bezierVertex(131.99,370.2,131.499,370.2,131.099,370.2)M ,e.bezierVertex(130.699,370.2,130.299,370.2,129.799,370.2),e.bezierVertex(125.99,369.9,123.199,367.2,123.099,363.6),e.bezierVertex(122.99,360.2,125.799,357.3,129.599,356.9),e.bezierVertex(130.499,356.8,131.499,356.8,132.599,356.7),e.bezierVertex(133.199,356.7,133.799,356.7,134.399,356.6),e.vertex(138.299,356.4),e.vertex(139.1,352.6),e.bezierVertex(139.5,350.7,139.799,348.9,140.2,347),e.bezierVertex(140.899,343.4,141.5,340,142.399,336.8),e.bezierVertex(150.099,310.7,174.399,292,201.399,291.3),e.vertex(201.599,291.3)M ,e.bezierVertex(203.699,291.3,206.299,292,208.299,293.2),e.bezierVertex(210.499,294.5,210.699,297.5,209.99,299.8),e.bezierVertex(209.499,301.5,208.199,303.9,203.299,304.7),e.bezierVertex(202.199,304.9,200.99,305,199.799,305.2),e.bezierVertex(194.499,305.9,188.99,306.599,183.799,308.9),e.bezierVertex(165.499,316.799,155.199,331.299,152.99,352),e.bezierVertex(152.399,357.8,154.499,361.7,159.699,364.5),e.bezierVertex(178.199,374.4,189.399,390,193.099,410.9),e.bezierVertex(193.699,414.299,193.899,418,193.599,422),e.bezM ierVertex(193.399,425.2,190.899,427.5,187.399,427.5),e.vertex(187.2,427.5),e.endShape(),e.beginShape(),e.vertex(364.3,281.1),e.bezierVertex(346.3,280.6,332.9,272.8,323.5,257),e.bezierVertex(321.6,253.9,320.4,250.2,319.2,246.7),e.bezierVertex(317.7,242.2,315,239.799,310.5,238.799),e.bezierVertex(298.5,236.299,288,230.7,279.4,222.1),e.bezierVertex(276.7,219.4,274.9,215.299,278,211.9),e.bezierVertex(279.4,210.3,281,209.6,282.6,209.6),e.bezierVertex(284.4,209.6,286.4,210.6,288.3,212.5),e.bezierVertex(297.8,221.8,310.4,M 226.9,323.9,226.9),e.bezierVertex(340.2,226.9,355.1,219.3,364.8,206.2),e.bezierVertex(371,197.8,374.2,188.5,374.5,178.5),e.vertex(374.5,177.9),e.bezierVertex(374.5,177,374.5,176.1,374.7,175.4),e.bezierVertex(375.3,171.8,377.9,169.5,381.3,169.5),e.bezierVertex(381.4,169.5,381.5,169.5,381.7,169.5),e.bezierVertex(385.4,169.7,388,172.4,388,176.1),e.bezierVertex(388.1,190.7,383.4,204,374.2,215.8),e.bezierVertex(365.8,226.5,354.7,233.9,341.2,237.9),e.bezierVertex(340,238.3,338.7,238.6,337.3,239.1),e.bezierVertex(335.9,23M 9.6,335.1,240.4,334.7,240.9),e.bezierVertex(334.599,241,334.5,241.1,334.4,241.2),e.vertex(331.799,243.6),e.vertex(333.199,246.8),e.bezierVertex(338.199,258,346.799,264.9,358.699,267.3),e.bezierVertex(360.199,267.6,361.599,267.7,362.99,267.9),e.bezierVertex(363.599,268,364.299,268,364.899,268.1),e.bezierVertex(369.099,268.6,371.799,271.4,371.499,275),e.bezierVertex(371.199,278.6,368.299,281.2,364.399,281.2),e.vertex(364.3,281.1),e.endShape(),e.beginShape(),e.vertex(323.9,437),e.bezierVertex(323.7,437,323.5,437,323.2M 99,437),e.bezierVertex(319.599,436.7,317.299,434.1,317.4,430.2),e.bezierVertex(317.9,406.099,328.299,388,349.5,375),e.bezierVertex(350.7,374.2,352,373.5,353.4,372.8),e.bezierVertex(354.099,372.4,354.7,372.1,355.299,371.7),e.vertex(357.499,370.5),e.vertex(357.799,368),e.bezierVertex(360.4,346.6,345.199,323.7,323.9,317),e.bezierVertex(319.099,315.5,314.099,314.9,309.299,314.4),e.vertex(308.199,314.299),e.bezierVertex(305.99,314.099,300.799,312.9,300.899,307.299),e.bezierVertex(300.99,303.499,303.899,300.9,308.099,300M .9),e.vertex(308.299,300.9),e.bezierVertex(327.099,301.299,343.099,308.7,355.699,322.9),e.bezierVertex(364.299,332.5,369.399,344.099,370.99,357.299),e.bezierVertex(371.099,358.4,371.299,359.4,371.499,360.499),e.bezierVertex(371.599,360.99,371.699,361.499,371.799,361.99),e.vertex(372.499,365.899),e.vertex(377.899,366.199),e.bezierVertex(378.799,366.299,379.699,366.299,380.599,366.399),e.bezierVertex(385.099,366.699,387.899,369.399,387.799,373.299),e.bezierVertex(387.699,377.099,384.99,379.599,380.799,379.799),e.beziM erVertex(369.799,380.199,359.99,383.299,351.899,389.299),e.bezierVertex(338.799,398.799,331.699,411.699,330.699,427.499),e.vertex(330.699,428.299),e.bezierVertex(330.599,429.199,330.599,430.099,330.499,430.799),e.bezierVertex(330,434.7,327.5,437,323.9,437),e.endShape()}function T(e){return e[0].map(((t,n)=>e.map((e=>e[n]))))}function A(e){return e.map((e=>Array.isArray(e)?A(e):e))}function D(e,t){return floor(random(e,t))}function k(e){let t=0;for(const n of e)t+=n[1];let n=random(t),r=0;for(const t of e)if(r+=t[1]M ,n<r)return t[0];return null}function L(e){for(let t=1;t<e.length;++t){let n=D(0,t),r=e[t];e[t]=e[n],e[n]=r}}function P(e){return null==e||""===e}function O(e){return new Promise((t=>setTimeout(t,e)))}function F(e,t,n){let r=0;for(let i=1;i<=1e3;++i)for(let o=1;o<=1e3;++o)if(e*o%(t*i)==0){let e=1*i/o;abs(e-n)<abs(r-n)&&(r=e)}return r}function N(){let e=60*(new Date).getTimezoneOffset()*1e3;return new Date(Date.now()-e).toISOString().slice(0,-1)}function B(e,t,n){let r;if(push(),textSize(e),textWidth(t)<=n)r=t;else M for(let e=0;e<t.length;++e){const i=t.slice(0,e+1)+"...";if(textWidth(i)>n){r=i;break}}return pop(),r}function Y(e){var t=e%10,n=e%100;return 1==t&&11!=n?e+"st":2==t&&12!=n?e+"nd":3==t&&13!=n?e+"rd":e+"th"}class G{constructor(e,t,n){this.n=t,this.m=n,this.mat=[];let r=0;for(let t=0;t<this.n;++t){this.mat.push([]);for(let n=0;n<this.m;++n)this.mat[t].push(r<e.length?e[r]:0),r+=1}return this}copy(){return new G(this.mat.flat(),this.n,this.m)}}class H{static __linear=e=>e;static __relu=e=>Math.max(e,0);static __leaky_M relu=e=>e>0?e:.2*e;static __sigmoid=e=>1/(1+Math.exp(-e));static __tanh=e=>Math.tanh(e);static __apply_unary_op(e,t){const n=e.copy();for(let e=0;e<n.n;++e)for(let r=0;r<n.m;++r)n.mat[e][r]=t(n.mat[e][r]);return n}static linear=e=>H.__apply_unary_op(e,H.__linear);static relu=e=>H.__apply_unary_op(e,H.__relu);static leaky_relu=e=>H.__apply_unary_op(e,H.__leaky_relu);static sigmoid=e=>H.__apply_unary_op(e,H.__sigmoid);static tanh=e=>H.__apply_unary_op(e,H.__tanh);static __add=(e,t)=>e+t;static __mul=(e,t)=>e*t;staticM __apply_binary_op=(e,t,n)=>{"object"!=typeof t&&(t=new G([t],1,1));const r=e.copy();for(let e=0;e<r.n;++e)for(let i=0;i<r.m;++i)r.mat[e][i]=n(r.mat[e][i],t.mat[e%t.n][i%t.m]);return r};static mul=(e,t)=>H.__apply_binary_op(e,t,H.__mul);static add=(e,t)=>H.__apply_binary_op(e,t,H.__add);static matMul(e,t){const n=new G([],e.n,t.m);for(let r=0;r<n.n;++r)for(let i=0;i<n.m;++i)for(let o=0;o<e.m;++o)n.mat[r][i]+=e.mat[r][o]*t.mat[o][i];return n}static softmax(e){const t=H.__apply_unary_op(e,(e=>Math.exp(e))),n=t.mat.flM at().reduce(((e,t)=>e+t));for(let r=0;r<e.n;++r)for(let i=0;i<e.m;++i)t.mat[r][i]/=n;return t}}class ${constructor(e,t){this.scale=e,this.offset=t}forward(e){return H.add(H.mul(e,this.scale),this.offset)}}class X{constructor(){}forward(e){return e.map((e=>e.flat()))}}class W{constructor(e,t,n,r){this.out_dim=e,this.activation=t,this.w=n,this.b=r}forward(e){const t=H.add(H.matMul(e,this.w),this.b);return null==this.activation?t:this.activation(t)}}class U{constructor(e,t,n){this.preprocessLayers=e,this.hiddenLayers=M t,this.outputLayer=n,this.totalNeurons=this.hiddenLayers.map((e=>e.out_dim)),this.currentOrders=[],this.currentIteration=null}updateNeurons(e,t){if(t!=this.currentIteration){this.currentOrders=[];for(let e=0;e<this.totalNeurons.length;++e){randomSeed(100*(t+1)+e);const n=[];for(let t=0;t<this.totalNeurons[e];++t)n.push(t);L(n),this.currentOrders.push(n)}this.currentIteration=t}const n=A(this.totalNeurons),r=n.reduce(((e,t)=>e+t))*(1-e);for(let e=0;e<r;++e){const t=n.map(((e,t)=>(e-1)/this.totalNeurons[t]));n[t.map(M ((e,t)=>[e,t])).reduce(((e,t)=>t[0]>e[0]?t:e))[1]]-=Math.min(r-e,1)}this.neuronsLife=[];for(let e=0;e<n.length;++e){const t=this.currentOrders[e],r=Array(this.totalNeurons[e]).fill(0);for(let i=0;i<n[e];++i)r[t[i]]=Math.min(n[e]-i,1);this.neuronsLife.push(r)}}getTotalNeurons(){return A(this.totalNeurons)}getNeuronsLife(){return A(this.neuronsLife)}forward(e){for(const t of this.preprocessLayers)e=t.forward(e);for(const[t,n]of this.hiddenLayers.entries()){e=n.forward(e);const r=new G(this.neuronsLife[t],1,e.m);e=H.mM ul(e,r)}return e=this.outputLayer.forward(e),H.softmax(e)}}function q(e){switch(e){case"relu":return H.relu;case"sigmoid":return H.sigmoid;case"tanh":return H.tanh;case"leaky_relu":return H.leaky_relu;default:return H.linear}}function j(e,t){const n=[],r=[],i=Z(t);let o=null,a=0,l=[];for(const t of e.config.layers)if("InputLayer"==t.class_name)o=t.config.batch_input_shape.slice(1),l=o;else if("Rescaling"==t.class_name)n.push(new $(t.config.scale,t.config.offset));else if("Flatten"==t.class_name)o=[o.reduce(((e,t)=>M e*t))];else if("Dense"==t.class_name){const e=[t.config.units],n=o[0]*e[0],l=e[0],s=i.subarray(a,a+n);a+=n;const h=i.subarray(a,a+l);a+=l;const c=new G(s,o[0],e[0]),u=new G(h,1,e[0]),f=q(t.config.activation);r.push(new W(e[0],f,c,u)),o=e}const s=r.pop();return{model:new U(n,r,s),inputDim:l}}function Z(e){const t=window.atob(e),n=t.length/Float32Array.BYTES_PER_ELEMENT,r=new DataView(new ArrayBuffer(Float32Array.BYTES_PER_ELEMENT)),i=new Float32Array(n);let o=0;for(let e=0;e<n;e++){o=4*e;for(let e=0;e<4;++e)r.setUinM t8(e,t.charCodeAt(o+e));i[e]=r.getFloat32(0,!0)}return i}class K{constructor(e){this.elt=e,this._events={},this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight}position(){if(0===arguments.length)return{x:this.elt.offsetLeft,y:this.elt.offsetTop};var e="absolute";return"static"!==arguments[2]&&"fixed"!==arguments[2]&&"relative"!==arguments[2]&&"sticky"!==arguments[2]&&"initial"!==arguments[2]&&"inherit"!==arguments[2]||(e=arguments[2]),this.elt.style.position=e,this.elt.style.left=arguments[0]+"px",thisM .elt.style.top=arguments[1]+"px",this.x=arguments[0],this.y=arguments[1],this}show(){return this.elt.style.display="block",this}hide(){return this.elt.style.display="none",this}size(e,t){if(0===arguments.length)return{width:this.elt.offsetWidth,height:this.elt.offsetHeight};var n=e,r=t;if(n!==te||r!==te){if(n===te?n=t*this.width/this.height:r===te&&(r=e*this.height/this.width),this.elt instanceof HTMLCanvasElement){var i,o={},a=this.elt.getContext("2d");for(i in a)o[i]=a[i];for(i in this.elt.setAttribute("width",n*M this._pInst._pixelDensity),this.elt.setAttribute("height",r*this._pInst._pixelDensity),this.elt.style.width=n+"px",this.elt.style.height=r+"px",this._pInst.scale(this._pInst._pixelDensity,this._pInst._pixelDensity),o)this.elt.getContext("2d")[i]=o[i]}else this.elt.style.width=n+"px",this.elt.style.height=r+"px",this.elt.width=n,this.elt.height=r;this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight,this._pInst&&this._pInst._curElement&&this._pInst._curElement.elt===this.elt&&(this._pInst._setProperty("wM idth",this.elt.offsetWidth),this._pInst._setProperty("height",this.elt.offsetHeight))}return this}style(e,t){if(t instanceof Color&&(t="rgba("+t.levels[0]+","+t.levels[1]+","+t.levels[2]+","+t.levels[3]/255+")"),void 0===t){if(-1===e.indexOf(":"))return window.getComputedStyle(this.elt).getPropertyValue(e);for(var n=e.split(";"),r=0;r<n.length;r++){var i=n[r].split(":");i[0]&&i[1]&&(this.elt.style[i[0].trim()]=i[1].trim())}}else if(this.elt.style[e]=t,"width"===e||"height"===e||"left"===e||"top"===e){var o=window.gM etComputedStyle(this.elt).getPropertyValue(e).replace(/[^\d.]/g,"");this[e]=Math.round(parseFloat(o,10))}return this}value(){return arguments.length>0?(this.elt.value=arguments[0],this):"range"===this.elt.type?parseFloat(this.elt.value):this.elt.value}mouseClicked(e){return this._adjustListener("click",e,this),this}isFocused(){return document.activeElement===this.elt}_adjustListener(e,t,n){return!1===t?this._detachListener(e,n):this._attachListener(e,t,n),this}_attachListener(e,t,n){n._events[e]&&this._detachListenM er(e,n);var r=t.bind(n);n.elt.addEventListener(e,r,!1),n._events[e]=r}_detachListener(e,t){var n=t._events[e];t.elt.removeEventListener(e,n,!1),t._events[e]=null}}function J(e,t){var n=document.createElement("button");return n.innerHTML=e,t&&(n.value=t),ee(n)}function Q(e){var t=arguments.length>1&&void 0!==arguments[1]&&arguments[1],n=function(t){var n=!0,r=!1,i=void 0;try{for(var o,a=t.target.files[Symbol.iterator]();!(n=(o=a.next()).done);n=!0){var l=o.value;File._load(l,e)}}catch(e){r=!0,i=e}finally{try{n||nullM ==a.return||a.return()}finally{if(r)throw i}}};if(window.File&&window.FileReader&&window.FileList&&window.Blob){var r=document.createElement("input");return r.setAttribute("type","file"),t&&r.setAttribute("multiple",!0),r.addEventListener("change",n,!1),ee(r)}}function ee(e){return document.body.appendChild(e),new K(e)}createImg=function(){var e,t=document.createElement("img"),n=arguments;return n.length>1&&"string"==typeof n[1]&&(t.alt=n[1]),n.length>2&&"string"==typeof n[2]&&(t.crossOrigin=n[2]),t.src=n[0],e=ee(tM ,this),t.addEventListener("load",(function(){e.width=t.offsetWidth||t.width,e.height=t.offsetHeight||t.height;var r=n[n.length-1];"function"==typeof r&&r(e)})),e},createInput=function(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:"",t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:"text",n=document.createElement("input");return n.setAttribute("value",e),n.setAttribute("type",t),ee(n,this)};const te="auto";function ne(e){re(e);const t=e._rectMode;e.rectMode(CORNER),e.rect(0,0,e.width,e.heighM t),e.rectMode(t),ie(e)}function re(e){e.push(),e.fill(255,255,255,255),e.blendMode(REMOVE)}function ie(e){e.blendMode(BLEND),e.pop()}File=function(e,t){this.file=e,this._pInst=t;var n=e.type.split("/");this.type=n[0],this.subtype=n[1],this.name=e.name,this.size=e.size,this.data=void 0},File._createLoader=function(e,t){var n=new FileReader;return n.onload=function(n){var r=new File(e);if("application/json"===r.file.type)r.data=JSON.parse(n.target.result);else if("text/xml"===r.file.type){var i=(new DOMParser).parseFM romString(n.target.result,"text/xml");r.data=new XML(i.documentElement)}else r.data=n.target.result;t(r)},n},File._load=function(e,t){if(/^text\//.test(e.type)||"application/json"===e.type)File._createLoader(e,t).readAsText(e);else if(/^(video|audio)\//.test(e.type)){var n=new File(e);n.data=URL.createObjectURL(e),t(n)}else File._createLoader(e,t).readAsDataURL(e)},XML=function(e){if(e)this.DOM=e;else{var t=document.implementation.createDocument(null,"doc");this.DOM=t.createElement("root")}},document.addEventListenM er("DOMContentLoaded",(function(){addEventListener("mousemove",(e=>{window.mouseX=e.pageX,window.mouseY=e.pageY}))})),new e("global");const oe="379";let ae,le,se,he,ce,ue,fe,de,xe,ge,pe,me,be,ye,we,ve,ze,Ve,_e,Me,Ee,Se,Re,Ie,Ce,Te,Ae,De,ke,Le,Pe,Oe,Fe,Ne,Be,Ye,Ge,He,$e,Xe,We,Ue,qe,je,Ze,Ke,Je,Qe,et,tt,nt,rt,it,ot,at,lt,st,ht,ct,ut,ft,dt,xt,gt,pt,mt,bt,yt,wt,vt,zt,Vt,_t,Mt,Et,St,Rt,It,Ct,Tt,At=!1,Dt=!1,kt=!0,Lt=!1,Pt=!1;const Ot=[" ","Growing","Stable","Decaying","Dead","Rebirth"];let Ft,Nt,Bt,Yt,Gt,Ht,$t,Xt,Wt,Ut,qM t,jt,Zt,Kt,Jt,Qt,en,tn,nn,rn,on,an,ln,sn,hn=0,cn=0,un=0,fn=!1,dn=!0,xn=!0,gn=null,pn=null,mn=null,bn=!1,yn=!1,wn=null,vn=null,zn=!1;async function setup(){let e=windowWidth,t=windowHeight;createCanvas(e,t),et=createGraphics(e,t),Xe=createGraphics(e,t),$e=createGraphics(e,t),We=createGraphics(e,t),Ue=createGraphics(e,t),qe=createGraphics(e,t),Qe=createGraphics(e,t),je=createGraphics(e,t),Ze=createGraphics(e,t),Ke=createGraphics(e,t),Je=createGraphics(e,t),tt=createGraphics(500,500),nt=createGraphics(500,500),rt=creaM teGraphics(500,500),_n(),Mn(),Sn(),await En(),Gn(),Rn(),bn=!0}function _n(){Et=parseInt(oe),randomSeed(Et),noiseSeed(Et)}function Mn(){Wt=Ir(p.training_traits),Cr(Wt)}async function En(){let e;Jt=r(),Qt=o(),[Xt,e]=await Promise.all([s(Jt),h(Qt)]),Ut=new V(Wt.visual,e.layers_config,e.weight_b64),Ut.updateAge(new Date),_n(),Wt.training=e.training_traits,Ht=e.model_name,$t=e.classes_name}function Sn(){le=min(width,height)/1024,ut=Rr.findIndex((e=>e[0]===Wt.visual.colorPalette)),ft=[["#ffffff","#231f20","#231f20"],["#2M 31f20","#ffffff","#ffffff"],["#104da8","#ffffff","#ffffff"],["#722F1F","#FCE1B2","#FCE1B2"],["#e88120","#f9f2e5","#f9f2e5"],["#f6b941","#2E2E2E","#2E2E2E"],["#45daaa","#012221","#012221"],["#F1F1F1","#328DFE","#328DFE"],["#111822","#D3EB8D","#D3EB8D"],["#713FF9","#D6D5E6","#D6D5E6"],["#FBDA9D","#795106","#795106"],["#8f5b62","#ead0d0","#ead0d0"],["#eae4cb","#508cac","#508cac"],["#ffc6cc","#cc313d","#cc313d"],["#60A900","#E0FE00","#E0FE00"],["#507DBE","#D0D1D3","#D0D1D3"],["#305848","#E8F2EE","#E8F2EE"],["#2a2634","M #5b6988","#cb78a2","#5b6988"],["#590e29","#fd5e53","#fd5e53","#ffe373"],["#0a141d","#57d4e4","#328195","#2A9ECF","#0ab6a8","#57d4e4"],["#3a2d28","#d5c2ac","#df6338","#3d9895","#d5c2ac"],["#030706","#77c4d9","#77c4d9","#77c4d9","#ffffff","#ffffff","#e72020","#e72020"],["#3a4664","#92f5ff","#f9ff94","#eaa0a2","#55dde0"],["#fbfaff","#f04bb1","#f04bb1","#fac373","#82cef0","#8b31ce"],["#000000","#ffffff","#ff0002","#f26522","#fdff00","#00ff03","#01fffe","#0000ff","#ff00ff"]];for(let e=0;e<ft.length;++e)for(let t=0;t<ft[M e].length;++t)ft[e][t]=cr(ft[e][t]);pt=[],ct=ft[ut][0],st=ft[ut][1]}function Rn(){gn=document.querySelector("#upload"),pn=document.querySelector("#inputUpload"),gn.addEventListener("dblclick",(()=>{if(!Lt&&!yn)if(In(Ie)&&cn==Ve-1)pn.click();else{if(4!=Pe&&5!=Pe&&(In(Ie)||cn!=Ve-1))return;fn=!0,dn=!0,Bt=0,un=0}})),pn.addEventListener("click",(()=>{pn.value=null,gn.style.display="block"})),pn.addEventListener("change",(()=>{const[e]=pn.files;e?(se=null,gn.style.display="none",Tn(URL.createObjectURL(e)),mn=e):gn.styleM .display="block"}))}function In(e){for(let t=0;t<e.length;++t){let n=0;for(let r=0;r<e[t].length;++r)e[t][r]>0&&++n;if(0==n)return!1}return!0}function Cn(){null!=se&&(un=0,Pt=!0,he=0,ue=0,drewLineAnim=!0,ce=(ae/2+we/2)/le,loadImage(se.elt.src,(e=>{const[t,n,r]=Gt,i=createGraphics(t,n);i.image(e,0,0,t,n),i.loadPixels();const o=i.pixels.filter(((e,t)=>t%4!=3)),a=Ut.classifyImage(o);Zt=T([a,$t.map((e=>e.toUpperCase()))]).sort(((e,t)=>e[0]>t[0]?-1:1))})))}function Tn(e){se=createImg(e,""),se.hide(),Cn()}function An(){zM n||(ce+=(width-ae-we)/tn/le),re(Xe),Xe.rect(ce*le,0,width,height),ie(Xe),un>=ge&&1==kt&&(kt=!1,un-=ge),kt&&(re($e),$e.strokeWeight(2*Fe),Jn(he,ze,ct,ct,$e),ie($e)),un>=ge&&0==kt&&(kt=!0,un-=ge,he+=1,he==en&&(++ue,he=0,ce=(ae/2+we/2)/le,1==ue&&(Pt=!1,Dn(),ye=millis())))}function Dn(){At=!0,pe=!1,me=!1,tryButton=br("Try Again",width/2-225*le,height/2+265*le,290*le,40*le,kn),closeResultButton=br("Close",width/2+75*le,height/2+265*le,150*le,40*le,Ln)}function kn(){At=!1,tryButton.hide(),closeResultButton.hide(),pn.clicM k()}function Ln(){Yt=!0,At=!1,Gn(),tryButton.hide(),closeResultButton.hide(),gn.style.display="block",se=null}function keyTyped(){bn&&!1===yn&&!1===yr()&&("i"!==key&&"I"!==key||(Dt=!Dt),"b"!==key&&"B"!==key||(xn=!xn),"s"!==key&&"S"!==key||!1!==Lt||saveCanvasAtCurrentTime(),"k"!==key&&"K"!==key||!1!==Lt||save4KCanvasAtCurrentTime(),"u"!==key&&"U"!==key||!1!==Lt||!1!==At||!1!==fn||!1!==Pt||On())}function On(){Lt=!0,wn=null,vn=null,submitButton=br("Submit",width/2-155*le,height/2+115*le,150*le,40*le,Fn),closeSettingBuM tton=br("Close",width/2+5*le,height/2+115*le,150*le,40*le,Yn),vt=createInput(),vt.position(width/2-252.5*le,height/2-40*le),vt.size(500*le,25*le),vt.style("font-size","15px"),vt.value(Jt||""),zt=createInput(),zt.position(width/2-252.2*le,height/2+35*le),zt.size(500*le,25*le),zt.style("font-size","15px"),zt.value(Qt||"")}function Fn(){Vt=vt.value(),_t=zt.value(),submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide(),Lt=!1,yn=!0,Nn()}async function Nn(){[wn,vn,_]=await Promise.all([c(Vt),u(_t),O(1e3)]),yn=M !1,wn&&vn?(n(Vt),i(_t),window.location.reload()):(Lt=!0,submitButton.show(),closeSettingButton.show(),vt.show(),zt.show())}function Bn(){Je.textFont("Trebuchet MS"),Je.noStroke(),pr(Je,600*le,200*le),Je.strokeWeight(1*le),Je.stroke(xt),Je.fill(xt),Je.textSize(50*le),Je.text("update()",width/2,height/2+2.5*le)}function Yn(){wn=null,vn=null,Lt=!1,submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide()}function Gn(){_n(),nn=Date.now(),pe=!1,me=!1,St=Wt.training.structure_gen,Rt=Wt.visual.birthYear,It=Wt.visuM al.lifeCycle,Ct=Wt.training.epoch_num,Tt=Wt.training.activation_func,Ft=Mr.findIndex((e=>e[0]==Wt.visual.hardwareAcceleration))+1,1==Ft?(Nt=30,fe=40):2==Ft?(Nt=15,fe=20):(Nt=2,fe=10);const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(M new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),ae=100*le,ht=50*le,Oe=Sr.findIndex((e=>e[0]==Wt.visual.nodeShape))+1,dt=Er.findIndex((e=>e[0]==Wt.visual.nodeFill))+1,lt=_r.findIndex((e=>e[0]==Wt.visual.pattern))+1,de=Math.tanh(Math.log10(Xt.avgfeerate)),de=map(de,0,1,.2,.8),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(lM et e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&CM e[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/VeM ,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,at=.7,pt=[],xt=ft[ut][2],gt=ft[ut][ft[ut].length-1];for(let e=3;e<ft[ut].length-1;e++)pt.push(ft[ut][e]);mt=sr(xt,gt,pt,width),bt=[],wt=[],yt=width/(Ve-1);for(let e=0;e<Ve;e++)bt.push(hr(mt,yt*e/width)),wt.push(hr(mt,yt*e/width));wt.unshift(bt[0]),wt.push(bt[bt.length-1]),hn=0,cn=0,un=0,Yt=!0;const n={xLeft:ae/8,xRight:width-ae/8,yTop:ae/8,yBottom:height-ae/8},r=Ce.map((e=>e.length));jt=new R(bt,r,n,Oe,le)}function Hn(e,t){let n=Ce[e].length;return[e*we+we/2M +ae/2,height/2-(n-1)/2*ve+t*ve]}function $n(e,t){le=min(e,t)/1024,ae=100*le,ht=50*le,we=(e-ae)/Ve,ve=(t-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}xe=floor(De.length*de),Le=[],ke=[],ge=floor(map(de,.2,.8,15,2));for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,mt=sr(xt,gM t,pt,e),bt=[],wt=[],yt=e/(Ve-1);for(let t=0;t<Ve;t++)bt.push(hr(mt,yt*t/e)),wt.push(hr(mt,yt*t/e));wt.unshift(bt[0]),wt.push(bt[bt.length-1])}function Xn(){const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirM thCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=mM in(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(eM ,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le}function Wn(){jt.update();const e=4==Pe?0:Kt;jt.draw(Qe,ct,dt,e,le)}function Un(){if(!bn)return ar(),void et.image(je,0,0);if(4==Pe||5==Pe)return Wn(),void et.image(Qe,0,0);un>=Nt&&hn<Ve&&(hn++,unM =0);for(let e=0;e<hn;e++)1==dt?it=ot=bt[e]:(it=ct,ot=bt[e]),Kn(e,it,ot,$e);un>=Nt&&cn<Ve-1&&(cn++,un=0);for(let e=0;e<cn;e++)Zn(e)}function qn(){et.background(ct),Ue.background(255),Ue.rectMode(CENTER),ne(Ue),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),Ue.stroke(st),Ue.strokeWeight(8*le),Ue.fill(ct),Qe.background(255),Qe.rectMode(CENTER),ne(Qe),Qe.strokeWeight(le),qe.background(255),qe.rectMode(CENTER),ne(qe),qe.textAlign(LEFT),$e.background(255),$e.rectMode(CENTER),ne($e),Xe.background(255),ne(Xe),Xe.strokeWeigM ht(Ne),We.background(255),We.rectMode(CENTER),ne(We),We.fill(st),We.stroke(st),We.strokeWeight(.1*le),er(lt),We.noStroke(),xn&&(We.rect(ae/16,height/2,ae/8,height),We.rect(width-ae/16,height/2,ae/8,height),We.rect(width/2,ae/16,width,ae/8),We.rect(width/2,height-ae/16,width,ae/8)),Ze.background(255),Ze.rectMode(CENTER),ne(Ze),Ze.textAlign(CENTER,CENTER),Ze.textStyle(BOLD),Ze.stroke(st),Ze.strokeWeight(8*le),Ze.fill(ct),je.background(255),je.rectMode(CENTER),ne(je),je.textAlign(CENTER,CENTER),je.textStyle(BOLD),Ke.bM ackground(255),Ke.rectMode(CENTER),ne(Ke),Ke.textAlign(CENTER,CENTER),Ke.textStyle(BOLD),Ke.stroke(st),Ke.strokeWeight(8*le),Ke.fill(ct),Je.background(255),Je.rectMode(CENTER),ne(Je),Je.textAlign(CENTER,CENTER),Je.textStyle(BOLD),Je.stroke(st),Je.strokeWeight(8*le),Je.fill(ct),Un(),et.image(We,0,0),Pt&&An(),et.image(Xe,0,0),et.image($e,0,0),At&&(tr(),et.image(Ue,0,0)),fn&&(lr(),et.image(Ze,0,0)),Lt&&(or(),et.image(Ke,0,0)),Dt&&(ir(),et.image(qe,0,0)),yn&&(Bn(),et.image(Je,0,0))}function draw(){const e=Date.now();bnM &&(Ut.updateAge(new Date(e)),Xn()),qn(),image(et,0,0),zn||un++}function Zn(e){let t,n=Ce[e].length,r=Ce[e+1].length;for(let i=0;i<n;i++){const[n,o]=Hn(e,i);for(let a=0;a<r;a++){const[r,l]=Hn(e+1,a);t=map(min(Ce[e][i],Ce[e+1][a]),0,1,0,.5),ur(n,o,r,l,bt[e],bt[e+1],Xe,t)}}}function Kn(e,t,n,r){let i,o,a,l=Ce[e].length;for(let s=0;s<l;s++){const[l,h]=Hn(e,s);i=Ce[e][s],a=map(Be,1/30,1,3,10),o=map(Ce[e][s],0,1,2*a,0)*le,o<1.5*le&&(o=0),Qn(l,h,ze,Oe,t,n,o,i,r)}}function Jn(e,t,n,r,i){for(let o=0;o<Le[e].length;o++)Qn(LeM [e][o][0],Le[e][o][1],t,Oe,n,r,0,1,i)}function Qn(e,t,n,r,i,o,a,l,s){s.stroke(dr(o,map(l,0,1,.25,1))),s.fill(dr(i,map(l,0,1,.15,1))),s.strokeWeight(Fe),fr([a],s),3==dt&&s.fill(dr(i,0)),1==r?s.ellipse(e,t,n):2==r?s.rect(e,t,7*n/8,7*n/8):3==r&&(s.beginShape(),s.vertex(e-4*n/7,t),s.vertex(e,t-4*n/7),s.vertex(e+4*n/7,t),s.vertex(e,t+4*n/7),s.endShape(CLOSE))}function er(e){if(1==e);else if(2==e){We.strokeWeight(1*le);for(let e=ht/4;e<width+ht/4;e+=ht)for(let t=ht/4;t<height+ht/4;t+=ht)We.point(e,t)}else if(3==e){ht=25*M le;for(let e=ht/2;e<height+ht/2;e+=ht)We.line(0,e,width,e);for(let e=ht/2;e<width+ht/2;e+=ht)We.line(e,0,e,height)}}function tr(){Ue.textFont("Trebuchet MS"),Ue.textAlign(LEFT,CENTER),Ue.noStroke(),pr(Ue,800*le,500*le),Ue.noStroke(),Ue.fill(dr(st,.75)),Ue.rect(width/2,height/2-100*le,800*le,300*le,25*le,25*le,0,0),Ue.fill(st),Ue.rect(width/2-250*le,height/2-100*le,225*le,225*le),Ue.image(se.elt,width/2-357.5*le,height/2-207.5*le,215*le,215*le);let e=100*Zt[0][0];Ue.fill(ct),Ue.textSize(25*le),Ue.textStyle(NORMAL),1M ==me&&(e>=0&&e<20?Ue.text("I have a feeling this image belongs to",width/2-100*le,height/2-170*le):e>=20&&e<40?Ue.text("I have a hunch this image belongs to",width/2-100*le,height/2-170*le):e>=40&&e<60?Ue.text("I think this image belongs to",width/2-100*le,height/2-170*le):e>=60&&e<80?Ue.text("I'm almost certain this image belongs to",width/2-100*le,height/2-170*le):Ue.text("I'm positive this image belongs to",width/2-100*le,height/2-170*le));let t=e.toFixed(2);"100.00"==t&&(t="100"),1==me&&Ue.text("I'm "+t+"% confM ident that I'm right!",width/2-100*le,height/2-25*le),example=Zt.map((e=>e[1])),be=Ue.textWidth('"FIDENZAAAA"'),defaultPhrase=Ue.textWidth('"PERPENDICULAR INHABITATION"'),Ue.textStyle(BOLD);const n=me?example[0]:random(example);if(1===n.split(" ").length){let e=75*be/Ue.textWidth('"'+n+'"');e>75&&(e=75),Ue.textSize(e*le),Ue.text('"'+n+'"',width/2-100*le,height/2-90*le)}else nr(width/2-100*le,height/2-90*le,460*le,110*le,n,Ue);if(millis()-ye>1500&&(me=!0),C(tt,nt,st,ct,Pe,Mt),Ue.image(nt,width/2-370*le,height/2+70*lM e,80*le,80*le),3==Pe){let e;e=map(Mt,50,60,.25,1.3),I(rt,e),Ue.image(rt,width/2-370*le,height/2+70*le,80*le,80*le)}let r,i;Ue.image(tt,width/2-370*le,height/2+70*le,80*le,80*le),Ue.fill(xt),Ue.textSize(40*le),Ue.text("INTELLIGENCE INFO",width/2-275*le,height/2+115*le),Ue.textSize(18*le),Ue.textStyle(NORMAL),Ue.circle(width/2-360*le,height/2+180*le,7.5*le),1==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s growing and getting smarter by the day.`:2==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. ItM s stable and it has reached peak performance.`:3==Pe&&(r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s decaying and losing its luster.`),i=2==Pe?"The Perceptron remains stable for some time before entering the decay phase.":`Wait until ${new Date(an).toLocaleString("en-US")} for your Perceptron to reach its peak performance.`,Ue.text(r,width/2-350*le,height/2+180*le),Ue.circle(width/2-360*le,height/2+210*le,7.5*le),Ue.text(i,width/2-350*le,height/2+210*le),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),M gr(Ue,width/2-225*le,width/2+65*le,height/2+265*le,height/2+305*le,"SELECT ANOTHER IMAGE"),gr(Ue,width/2+75*le,width/2+225*le,height/2+265*le,height/2+305*le,"CLOSE")}function nr(e,t,n,r,i,o){let a=i.split(" "),l=75*be/o.textWidth('"'+i+'"'),s=0,h=[],c=[],u=[],f="",d="";if(l>=50)l>75&&(l=75),o.textSize(l*le),o.text('"'+i+'"',e,t);else if(l<50){if(l=50*defaultPhrase/o.textWidth('"'+i+'"'),l>30){if(l>50&&(l=50),[f,d]=rr(l,n,s,h,c,a,f,d,Ue),0==c.length)return o.textSize(l*le),void o.text('"'+i+'"',e,t);for(s=0,h=[],c=M [];o.textWidth(d)>n/le;)l=l*n/le/o.textWidth(d),f="",d="",[f,d]=rr(l,n,s,h,c,a,f,d,Ue)}else{l=30,o.textSize(l);for(let e=0;e<a.length;e++)s+=o.textWidth(" "+a[e]),s<=n/le?h.push(a[e]):s>n/le&&s<=n/le*2?c.push(a[e]):u.push(a[e]);for(let e=1;e<h.length;e++)f=f+" "+h[e];if(f='"'+h[0]+f,0==u.length){for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+c[c.length-1]+'"'}else if(1==c.length)d="... "+u[u.length-1]+'"';else{for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+"... "+u[u.length-1]+'"'}}o.textSize(l*le);let r=1.25*(o.textM Descent()+o.textAscent());o.text(f,e,t-r/2),o.text(d,e,t+r/2)}}function rr(e,t,n,r,i,o,a,l,s){s.textSize(e);for(let e=0;e<o.length;e++)(n+=s.textWidth(" "+o[e]))<=t/le?r.push(o[e]):i.push(o[e]);for(let e=1;e<r.length;e++)a=a+" "+r[e];if(a='"'+r[0]+a,0==i.length&&(a+='"',l=""),1==i.length)l=i[i.length-1]+'"';else{for(let e=0;e<i.length-1;e++)l=l+i[e]+" ";l=l+i[i.length-1]+'"'}return[a,l]}function ir(){const e=45*le;qe.textFont("Tahoma"),qe.stroke(st),qe.strokeWeight(2*le),qe.fill(ct),qe.rect(width/2,e/2+height-87.5*M le,600*le,90*le),qe.fill(st),qe.rect(width/2-150*le,e+height-170*le,300*le,30*le),qe.fill(ct),qe.rect(width/2+150*le,e+height-170*le,300*le,30*le),qe.noStroke(),qe.fill(ct),qe.textSize(15*le),qe.textStyle(BOLD),qe.text("PERCEPTRON INFORMATION",width/2-285*le,e+height-165*le),qe.fill(xt),qe.text("ARTWORK NAME:",width/2+10*le,e+height-165*le),qe.textAlign(RIGHT),qe.textStyle(ITALIC),qe.text("Perceptron #"+Et,width/2+285*le,e+height-165*le);const[t,n]=It.split(" ");let r;"60 Years"===It?r="1 Year":"60 Months"===It?r="M 1 Month":"60 Weeks"===It?r="1 Week":"60 Days"===It?r="1 Day":"12 Hours"===It&&(r="12 Minutes"),data=[["AI MODEL NAME:",B(12*le,Ht,140*le)],["SCALE:","1:"+Te],["NUMBER OF CLASSES:",$t.length],["BIRTH YEAR:",Rt],["NUMBER OF REBIRTHS:",sn.toString()],["AGE:",`${Math.ceil(Mt)} Perceptron Years`],["ONE PERCEPTRON YEAR:",`${r}`],["STATE:",Ot[Pe]],["ACTIVE NEURONS:",`${round(ln*rn)} / ${ln}`],["NEXT STATE TIME:",vr(new Date(on))]],qe.fill(xt);const i=data.length/2;for(let t=0;t<data.length;++t){const n=t<i,r=n?width/2-285M *le:width/2+10*le,o=n?width/2-10*le:width/2+285*le,a=e+height-(135-t%i*15)*le;qe.textStyle(BOLD),qe.textAlign(LEFT),qe.textSize(12*le),qe.text(data[t][0],r,a),qe.textStyle(ITALIC),qe.textAlign(RIGHT),qe.textSize(12*le),qe.text(data[t][1],o,a)}}function or(){Ke.textFont("Trebuchet MS"),Ke.noStroke(),pr(Ke,600*le,200*le),gr(Ke,width/2-155*le,width/2-5*le,height/2+115*le,height/2+155*le,"UPDATE"),gr(Ke,width/2+5*le,width/2+155*le,height/2+115*le,height/2+155*le,"CLOSE"),Ke.textAlign(LEFT),Ke.fill(xt),Ke.text("UPDATE BM ITCOIN FULL NODE ADDRESS",width/2-252.5*le,height/2-55*le),Ke.text("UPDATE MODEL ADDRESS",width/2-252.5*le,height/2+20*le),Ke.textAlign(RIGHT),Ke.textStyle(ITALIC),Ke.textSize(15*le),0==wn&&Ke.text("(*) Invalid Address",width/2+252.5*le,height/2-53*le),0==vn&&Ke.text("(*) Invalid Model",width/2+252.5*le,height/2+23*le)}function ar(){je.textFont("Trebuchet MS"),je.fill(st),je.textSize(50*le),je.stroke(st),je.strokeWeight(1*le),je.text("main()",width/2,height/2)}function lr(){un>=20&&1==dn&&(dn=!1,un=0),dn&&(Ze.textFM ont("Trebuchet MS"),Ze.stroke(st),Ze.fill(ct),Ze.rect(width/2,height/2,600*le,150*le,25*le),Ze.fill(xt),Ze.textSize(75*le),Ze.noStroke(),1==Pe?Ze.text("GROWING",width/2,height/2+5*le):3==Pe?Ze.text("AGING",width/2,height/2+5*le):4==Pe?Ze.text("DEAD",width/2,height/2+5*le):5==Pe&&Ze.text("BIRTH",width/2,height/2+5*le)),un>=20&&0==dn&&(dn=!0,un=0,Bt++,3==Bt&&(fn=!1))}function sr(e,t,n,r){let i=[],o=r/(n.length+1),a=color(e),l=color(t);i.push(a);for(let e=0;e<n.length;e++){let t=color(n[e]);for(let e=1;e<=o;e++){let nM =lerpColor(a,t,e/o);i.push(n)}a=t}for(let e=1;e<o;e++){let t=lerpColor(a,l,e/o);i.push(t)}if(i.push(l),i.length>r)i.splice(r);else if(i.length<r){let e=i[i.length-1];for(;i.length<r;)i.push(e)}return i}function hr(e,t){let n=e.length,r=Math.floor(t*n);return r>=n&&(r=n-1),e[r]}function cr(e){e=e.replace("#","");var t=parseInt(e,16);return color(t>>16&255,t>>8&255,255&t)}function ur(e,t,n,r,i,o,a,l){var s=a.drawingContext.createLinearGradient(e,t,n,r);s.addColorStop(0,i),s.addColorStop(1,o),a.drawingContext.strokeStM yle=s,a.drawingContext.globalAlpha=l,a.line(e,t,n,r),a.drawingContext.globalAlpha=1}function fr(e,t){t.drawingContext.setLineDash(e)}function dr(e,t){let n=color(e),r=red(n),i=green(n),o=blue(n);return color(r,i,o,255*t)}function xr(e,t,n,r){return mouseX>e&&mouseX<t&&mouseY>n&&mouseY<r}function gr(e,t,n,r,i,o){e.strokeWeight(1*le),e.stroke(st);const[a,l]=xr(t,n,r,i)?[xt,ct]:[ct,xt];e.fill(a),e.push(),e.rectMode(CORNERS),e.rect(t,r,n,i,5*le),e.pop(),e.noStroke(),e.textSize(20*le),e.fill(l),e.text(o,(t+n)/2,(46*r+54M *i)/100)}function pr(e,t,n){e.fill(0,0,0,75),e.rect(width/2,height/2,width,height),e.stroke(st),e.fill(ct),e.rect(width/2,height/2,t,n,25*le)}function mr(e,t){resizeCanvas(e,t,!0),Xe.resizeCanvas(e,t,!0),$e.resizeCanvas(e,t,!0),We.resizeCanvas(e,t,!0),Ue.resizeCanvas(e,t,!0),qe.resizeCanvas(e,t,!0),Qe.resizeCanvas(e,t,!0),je.resizeCanvas(e,t,!0),Ze.resizeCanvas(e,t,!0),Ke.resizeCanvas(e,t,!0),Je.resizeCanvas(e,t,!0),et.resizeCanvas(e,t,!0)}function br(e,t,n,r,i,o){const a=J(e);return a.position(t,n),a.size(r,i),a.sM tyle("opacity","0"),a.mouseClicked(o),a}function yr(){return null!=vt&&vt?.isFocused()||null!=zt&&zt?.isFocused()}function wr(e,t,n,r){let i;if(e<=3){i=`Hey ${String.fromCodePoint(128075)}, I'm ${n}, ${t} years old. I can detect ${r.length} NFT collections: `;let e=0;for(let t=0;t<r.length;++t){const n=r[t];if(e+n.length>500){i+=", etc";break}t==r.length-1?i+=", and ":t>0&&(i+=", "),i+=n,e+=n.length}i+=". ",t<=5?i+="However, I am only a baby, so my recognition ability is not accurate. I'm in the state of Growing boM th looks and intelligence.":t<=13?i+="I am now a child. My recognition ability is becoming better, but still not very accurate. I'm in the state of Growing both looks and intelligence.":t<=25?i+="I have grown up to be a teen. My recognition ability almost reaches the peak, but I will still mess up sometimes. I'm in the state of Growing both looks and intelligence.":t<=50?i+="I finally reach adulthood. My recognition is fully functional now. I'm in the Stable state, where I am the most intelligent with all neurons aM ctivated.":t<=60&&(i+="I am now an old Perceptron, so my recognition ability is no longer the best. I'm in the Decaying state, meaning that my neurons are dying, and my intelligence is decreasing over time.")}else 4==e?i=`${n} is Dead. However, this is not the end to its story...`:5==e&&(i=`${n} is now in the Rebirth state, and is preparing to start a new life.`);return i}function vr(e){const t=e.getDate(),n=e.toLocaleString("en-US",{month:"long"}),r=e.getFullYear();let i=e.getHours().toString();1==i.length&&(i="0"M +i);let o=e.getMinutes().toString();return 1==o.length&&(o="0"+o),`${Y(t)} ${n} ${r} | ${i}:${o}`}saveCanvasAtCurrentTime=()=>{save(N())},save4KCanvasAtCurrentTime=()=>{const e=width,t=height,n=min(4096/min(e,t),1e4/max(e,t)),r=e*n,i=t*n;mr(r,i),zn=!0,$n(r,i),qn();let o="4K_"+N()+".png";saveCanvas(et,o),mr(e,t),$n(e,t),zn=!1};const zr=[["60 Years",3,365],["60 Months",40,30],["60 Weeks",37,7],["60 Days",20,1]],Vr=[["1943",1],["1951",1.5],["1957",2],["1969",2.5],["1970",3],["1980",3.5],["1982",4],["1986",4.5],["1988"M ,5],["1997",5.5],["1998",6],["2002",6.5],["2009",7],["2012",7.5],["2014",8],["2015",8.5],["2016",9],["2023",15]],_r=[["Plain",20],["Dotted",40],["Squared",40]],Mr=[["Basic",30],["Standard",60],["Advanced",10]],Er=[["MNIST",70],["CIFAR",25],["IMAGENET",5]],Sr=[["Theano",60],["Torch",30],["TensorFlow",10]],Rr=[["Whitepaper",2],["Blackboard",2],["Blueprint",2],["Nak",74/14],["Jims",74/14],["Level 10",74/14],["Flips",74/14],["Level 14",74/14],["III",74/14],["XMB",74/14],["Info",74/14],["Adventure",74/14],["Marigold",74M /14],["Phoenix",74/14],["Love",74/14],["Cachet",74/14],["Human",74/14],["Twilight",3],["Sunset",3],["Aurora",3],["Liminal Space",3],["D Vu",3],["Lucid Dream",3],["Parallel",1],["Multiverse",1]];function Ir(e){for(let e=0;e<100;++e)random(1);return{visual:{pattern:k(_r),hardwareAcceleration:k(Mr),nodeFill:k(Er),nodeShape:k(Sr),colorPalette:k(Rr),lifeCycle:k(zr),birthYear:k(Vr)},training:e}}function Cr(e){window.$generativeTraits={"Network Architecture":e.training.structure_gen,"Hidden Layers":e.training.n_layerM s,"Max Neurons Per Hidden Layer":e.training.max_nodes,"Activation Function":e.training.activation_func,"Training Epochs":e.training.epoch_num,Dataset:e.visual.nodeFill,"Deep Learning Framework":e.visual.nodeShape,"Hardware Acceleration":e.visual.hardwareAcceleration,"Paper Pattern":e.visual.pattern,"Life Cycle":e.visual.lifeCycle,"Birth Year":e.visual.birthYear,"Color Palette":e.visual.colorPalette}} <script defer src="https://static.cloudflareinsights.com/beacon.min.js/v2b4487d741ca48dcbadcaf954e15M. 9fc61680799950996" integrity="sha512-D/jdE0CypeVxFadTejKGTzmwyV10c1pxZk/AqjJuZbaJwGMyNHY3q/mTPWqMUnFACfCTunhZUVcd4cV78dK1pQ==" data-cf-beacon='{"rayId":"7b4840d74936a238","version":"2023.3.0","b":1,"token":"6c07c178c94442f695e7a0a2aaee641a","si":100}' crossorigin="anonymous"></script> {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "wizard staff"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "blue fire"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "wizard staff"}]} text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "dragon"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "pirate flag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "fire"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "frozen staff"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "undead"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} text/html;charset=utf-8 <meta charset="utf-8" /> position: relative; width: var(--width); height: var(--height); border: 1px solid blue; position: relative; <div id="upload"> <input id="inputUpload" type="file"> function e(e){"use strict";return new function e(t){let n="global"==t?window:this;n.canvas=document.createElement("canvas");let r=n.canvas.getContext("2d");n.width=100,n.height=100,n.canvas.width=n.width,n.canvas.height=n.height,"offscreen"!=t&&(document.body?document.body.appendChild(n.canvas):window.addEventListener("load",(function(){document.body.appendChild(n.canvas)}))),g(),n.MAGIC=161533525,n.RGB=0,n.HSV=1,n.HM SB=1,n.CHORD=0,n.PIE=1,n.OPEN=2,n.RADIUS=1,n.CORNER=2,n.CORNERS=3,n.ROUND="round",n.SQUARE="butt",n.PROJECT="square",n.MITER="miter",n.BEVEL="bevel",n.CLOSE=1,n.BLEND="source-over",n.REMOVE="destination-out",n.ADD="lighter",n.DARKEST="darken",n.LIGHTEST="lighten",n.DIFFERENCE="difference",n.SUBTRACT="subtract",n.EXCLUSION="exclusion",n.MULTIPLY="multiply",n.SCREEN="screen",n.REPLACE="copy",n.OVERLAY="overlay",n.HARD_LIGHT="hard-light",n.SOFT_LIGHT="soft-light",n.DODGE="color-dodge",n.BURN="color-burn",n.NORMAL="norM mal",n.ITALIC="italic",n.BOLD="bold",n.BOLDITALIC="italic bold",n.CENTER="center",n.LEFT="left",n.RIGHT="right",n.TOP="top",n.BOTTOM="bottom",n.BASELINE="alphabetic",n.LANDSCAPE="landscape",n.PORTRAIT="portrait",n.ALT=18,n.BACKSPACE=8,n.CONTROL=17,n.DELETE=46,n.DOWN_ARROW=40,n.ENTER=13,n.ESCAPE=27,n.LEFT_ARROW=37,n.OPTION=18,n.RETURN=13,n.RIGHT_ARROW=39,n.SHIFT=16,n.TAB=9,n.UP_ARROW=38,n.HALF_PI=Math.PI/2,n.PI=Math.PI,n.QUARTER_PI=Math.PI/4,n.TAU=2*Math.PI,n.TWO_PI=2*Math.PI,n.THRESHOLD=1,n.GRAY=2,n.OPAQUE=3,n.INVEM RT=4,n.POSTERIZE=5,n.DILATE=6,n.ERODE=7,n.BLUR=8,n.ARROW="default",n.CROSS="crosshair",n.HAND="pointer",n.MOVE="move",n.TEXT="text",n.VIDEO={video:!0,audio:!1},n.AUDIO={video:!1,audio:!0},n.SHR3=1,n.LCG=2,n.HARDWARE_FILTERS=!0,n.hint=function(e,t){n[e]=t},n.frameCount=0,n.mouseX=0,n.mouseY=0,n.pmouseX=0,n.pmouseY=0,n.mouseButton=null,n.keyIsPressed=!1,n.mouseIsPressed=!1,n.key=null,n.keyCode=null,n.pixels=null,n.accelerationX=0,n.accelerationY=0,n.accelerationZ=0,n.rotationX=0,n.rotationY=0,n.rotationZ=0,n.relRotatM ionX=0,n.relRotationY=0,n.relRotationZ=0,n.pAccelerationX=0,n.pAccelerationY=0,n.pAccelerationZ=0,n.pRotationX=0,n.pRotationY=0,n.pRotationZ=0,n.pRelRotationX=0,n.pRelRotationY=0,n.pRelRotationZ=0,n.touches=[],n._styleCache=[{colorMode:n.RGB,noStroke:!1,noFill:!1,ellipseMode:n.CENTER,rectMode:n.CORNER,curveDetail:20,curveAlpha:0,textFont:"sans-serif",textSize:12,textLeading:12,textStyle:"normal"}],n._style=n._styleCache[n._styleCache.length-1],n._noLoop=!1,n._pixelDensity=1,n._frameRate=null,n._tint=null;let i=nullM ,o=!0,a=[],l=null,s=0,h={},c=0,u=null,f=null,d=null;Object.defineProperty(n,"deviceOrientation",{get:function(){return 90==Math.abs(window.orientation)?n.LANDSCAPE:n.PORTRAIT}}),Object.defineProperty(n,"windowWidth",{get:function(){return window.innerWidth}}),Object.defineProperty(n,"windowHeight",{get:function(){return window.innerHeight}}),Object.defineProperty(n,"drawingContext",{get:function(){return r}}),n.createCanvas=function(e,t){return n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t,g(),n.canvas},nM .resizeCanvas=function(e,t){n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t},n.createGraphics=n.createImage=function(t,n){let r=new e("offscreen");return r.createCanvas(t,n),r.noLoop(),r},n.pixelDensity=function(e){return null==e||(n._pixelDensity=e,n.canvas.width=Math.ceil(n.width*e),n.canvas.height=Math.ceil(n.height*e),n.canvas.style.width=n.width+"px",n.canvas.style.height=n.height+"px",r.scale(n._pixelDensity,n._pixelDensity),g()),n._pixelDensity},n.map=function(e,t,n,r,i,o){let a=r+1*(e-t)/(n-t)*(i-r)M ;return o?r<i?Math.min(Math.max(a,r),i):Math.min(Math.max(a,i),r):a},n.lerp=function(e,t,n){return e*(1-n)+t*n},n.constrain=function(e,t,n){return Math.min(Math.max(e,t),n)},n.dist=function(){return 4==arguments.length?Math.hypot(arguments[0]-arguments[2],arguments[1]-arguments[3]):Math.hypot(arguments[0]-arguments[3],arguments[1]-arguments[4],arguments[2]-arguments[5])},n.norm=function(e,t,r){return n.map(e,t,r,0,1)},n.sq=function(e){return e*e},n.fract=function(e){return e-Math.floor(e)},n.degrees=function(e){retM urn 180*e/Math.PI},n.radians=function(e){return e*Math.PI/180},n.abs=Math.abs,n.ceil=Math.ceil,n.exp=Math.exp,n.floor=Math.floor,n.log=Math.log,n.mag=Math.hypot,n.max=Math.max,n.min=Math.min,n.round=Math.round,n.sqrt=Math.sqrt,n.sin=Math.sin,n.cos=Math.cos,n.tan=Math.tan,n.asin=Math.asin,n.acos=Math.acos,n.atan=Math.atan,n.atan2=Math.atan2,n.Vector=function(e,t,r){let i=this;i.x=e||0,i.y=t||0,i.z=r||0;let o=null,a=null;function l(e,t,n){return null!=e.x?e:null!=t?{x:e,y:t,z:n||0}:{x:e,y:e,z:e}}function s(){null==a&M &(a=i.x*i.x+i.y*i.y+i.z*i.z,o=Math.sqrt(a))}function h(){a=null,o=null}i.set=function(e,t,n){i.x=e||0,i.y=t||0,i.z=n||0},i.copy=function(){return new n.Vector(i.x,i.y,i.z)},i.add=function(){let e=l.apply(null,arguments);return i.x+=e.x,i.y+=e.y,i.z+=e.z,h(),i},i.rem=function(){let e=l.apply(null,arguments);return i.x%=e.x,i.y%=e.y,i.z%=e.z,h(),i},i.sub=function(){let e=l.apply(null,arguments);return i.x-=e.x,i.y-=e.y,i.z-=e.z,h(),i},i.mult=function(){let e=l.apply(null,arguments);return i.x*=e.x,i.y*=e.y,i.z*=e.z,hM (),i},i.div=function(){let e=l.apply(null,arguments);return i.x/=e.x,i.y/=e.y,i.z/=e.z,h(),i},i.mag=function(){return s(),o},i.magSq=function(){return s(),a},i.dot=function(){let e=l.apply(null,arguments);return i.x*e.x+i.y*e.y+i.z*e.z},i.dist=function(){let e=l.apply(null,arguments),t=i.x-e.x,n=i.y-e.y,r=i.z-e.z;return Math.sqrt(t*t+n*n+r*r)},i.cross=function(){let e=l.apply(null,arguments),t=i.y*e.z-i.z*e.y,n=i.z*e.x-i.x*e.z,r=i.x*e.y-i.y*e.x;return i.x=t,i.y=n,i.z=r,h(),i},i.normalize=function(){s();let e=o;retuM rn i.x/=e,i.y/=e,i.z/=e,o=1,a=1,i},i.limit=function(e){s();if(o>e){let t=e/o;i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e}return i},i.setMag=function(e){s();let t=e/o;return i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e,i},i.heading=function(){return Math.atan2(i.y,i.x)},i.rotate=function(e){let t=Math.cos(e),n=Math.sin(e),r=i.x*t-i.y*n,o=i.x*n+i.y*t;return i.x=r,i.y=o,i},i.angleBetween=function(){let e=l.apply(null,arguments);const t=i.dot(e)/(i.mag()*e.mag());let n;return n=Math.acos(Math.min(1,Math.max(-1,t))),n*Math.sign(i.cross(e).z||1)},M i.lerp=function(e,t){return i.x=i.x*(1-t)+e.x*t,i.y=i.y*(1-t)+e.y*t,i.z=i.z*(1-t)+e.z*t,h(),i},i.reflect=function(e){return e.normalize(),i.sub(e.mult(2*i.dot(e)))},i.array=function(){return[i.x,i.y,i.z]},i.equals=function(e,t){return null==t&&null==(t=Number.EPSILON)&&(t=0),Math.abs(e.x-i.x)<t&&Math.abs(e.y-i.y)<t&&Math.abs(e.z-i.z)<t},i.fromAngle=function(e,t){return null==t&&(t=1),o=t,a=t*t,i.x=t*Math.cos(e),i.y=t*Math.sin(e),i.z=0,i},i.fromAngles=function(e,t,n){null==n&&(n=1),o=n,a=n*n;const r=Math.cos(t),l=MaM th.sin(t),s=Math.cos(e),h=Math.sin(e);return i.x=n*h*l,i.y=-n*s,i.z=n*h*r,i},i.random2D=function(){return o=1,a=1,i.fromAngle(Math.random()*Math.PI*2)},i.random3D=function(){return o=1,a=1,i.fromAngles(Math.random()*Math.PI*2,Math.random()*Math.PI*2)},i.toString=function(){return`[${i.x}, ${i.y}, ${i.z}]`}},n.Vector.add=function(e,t){return new n.Vector(e.x+t.x,e.y+t.y,e.z+t.z)},n.Vector.rem=function(e,t){return new n.Vector(e.x%t.x,e.y%t.y,e.z%t.z)},n.Vector.sub=function(e,t){return new n.Vector(e.x-t.x,e.y-t.y,e.M z-t.z)},n.Vector.mult=function(e,t){return null==t.x?new n.Vector(e.x*t,e.y*t,e.z*t):new n.Vector(e.x*t.x,e.y*t.y,e.z*t.z)},n.Vector.div=function(e,t){return null==t.x?new n.Vector(e.x/t,e.y/t,e.z/t):new n.Vector(e.x/t.x,e.y/t.y,e.z/t.z)},n.Vector.dist=function(e,t){return Math.hypot(e.x-t.x,e.y-t.y,e.z-t.z)},n.Vector.cross=function(e,t){return new n.Vector(e.y*t.z-e.z*t.y,e.z*t.x-e.x*t.z,e.x*t.y-e.y*t.x)},n.Vector.lerp=function(e,t,r){return new n.Vector(e.x*(1-r)+t.x*r,e.y=e.y*(1-r)+t.y*r,e.z=e.z*(1-r)+t.z*r)},n.M Vector.equals=function(e,t,n){return e.equals(t,n)};for(let e of["fromAngle","fromAngles","random2D","random3D"])n.Vector[e]=function(t,r,i){return(new n.Vector)[e](t,r,i)};function x(e,t,n){let r,i,o,a,l,s,h,c,u;if(0==t)return[255*(r=n),255*(i=n),255*(o=n)];switch((a=e)>360&&(a=0),h=n*(1-t),c=n*(1-t*(s=(a/=60)-(l=~~a))),u=n*(1-t*(1-s)),l){case 0:r=n,i=u,o=h;break;case 1:r=c,i=n,o=h;break;case 2:r=h,i=n,o=u;break;case 3:r=h,i=c,o=n;break;case 4:r=u,i=h,o=n;break;default:r=n,i=h,o=c}return[255*r,255*i,255*o]}functioM n g(){r.fillStyle="white",r.strokeStyle="black",r.lineCap="round",r.lineJoin="miter"}function p(e){if(0<=e&&e<2*Math.PI)return e;for(;e<0;)e+=2*Math.PI;for(;e>=Math.PI;)e-=2*Math.PI;return e}function m(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;let c=p(a),u=p(l);r.beginPath();for(let a=0;a<h+1;a++){let l=a/h,s=n.lerp(c,u,l),f=Math.cos(s)*i/2,d=Math.sin(s)*o/2;r[a?"lineTo":"moveTo"](e+f,t+d)}s==n.CHORD?r.closePath():s==n.PIE&&(r.lineTo(e,t),r.closePath()),n._style.noFill||r.fill(),n._style.noStrokM e||r.stroke()}function b(e,t,i,o){n._style.noFill&&n._style.noStroke||(r.beginPath(),r.ellipse(e,t,i/2,o/2,0,0,2*Math.PI),n._style.noFill||r.fill(),n._style.noStroke||r.stroke())}function y(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;if(null==a)return function(e,t,i,o){n._style.noFill||r.fillRect(e,t,i,o),n._style.noStroke||r.strokeRect(e,t,i,o)}(e,t,i,o);if(null==l)return y(e,t,i,o,a,a,a,a);const c=Math.min(Math.abs(o),Math.abs(i))/2;a=Math.min(c,a),l=Math.min(c,l),h=Math.min(c,h),s=Math.min(c,s)M ,r.beginPath(),r.moveTo(e+a,t),r.arcTo(e+i,t,e+i,t+o,l),r.arcTo(e+i,t+o,e,t+o,s),r.arcTo(e,t+o,e,t,h),r.arcTo(e,t,e+i,t,a),r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke()}function w(){a=[]}n.createVector=function(e,t,r){return new n.Vector(e,t,r)},n.curvePoint=function(e,t,n,r,i){const o=i*i*i,a=i*i;return e*(-.5*o+a-.5*i)+t*(1.5*o-2.5*a+1)+n*(-1.5*o+2*a+.5*i)+r*(.5*o-.5*a)},n.bezierPoint=function(e,t,n,r,i){const o=1-i;return Math.pow(o,3)*e+3*Math.pow(o,2)*i*t+3*o*Math.pow(i,2)*n+Math.pow(i,M 3)*r},n.curveTangent=function(e,t,n,r,i){const o=i*i;return e*(-3*o/2+2*i-.5)+t*(9*o/2-5*i)+n*(-9*o/2+4*i+.5)+r*(3*o/2-i)},n.bezierTangent=function(e,t,n,r,i){const o=1-i;return 3*r*Math.pow(i,2)-3*n*Math.pow(i,2)+6*n*o*i-6*t*o*i+3*t*Math.pow(o,2)-3*e*Math.pow(o,2)},n.Color=function(e,t,n,r){let i=this;i.MAGIC=786698,i._r=e,i._g=t,i._b=n,i._a=r,i._h=0,i._s=0,i._v=0,i._hsvInferred=!1,i.setRed=function(e){i._r=e,i._hsvInferred=!1},i.setGreen=function(e){i._g=e,i._hsvInferred=!1},i.setBlue=function(e){i._b=e,i._hsvInfM erred=!1},i.setAlpha=function(e){i._a=e/255,i._hsvInferred=!1},i._inferHSV=function(){i._hsvInferred||([i._h,i._s,i._v]=function(e,t,n){let r,i,o,a,l;return r=e<t?e<n?e:n:t<n?t:n,0==(l=100*(i=e>t?e>n?e:n:t>n?t:n)/255)?[o=0,a=0,l]:0==(a=100*(i-r)/i)?[o=0,a,l]:(o=i==e?0+60*(t-n)/(i-r):i==t?120+60*(n-e)/(i-r):240+60*(e-t)/(i-r),[o,a,l])}(i._r,i._g,i._b),i._hsvInferred=!0)},i.toString=function(){return`rgba(${Math.round(i._r)},${Math.round(i._g)},${Math.round(i._b)},${~~(1e3*i._a)/1e3})`}},n.colorMode=function(e){n._stM yle.colorMode=e},n.color=function(){if(1==arguments.length&&786698==arguments[0].MAGIC)return arguments[0];if(n._style.colorMode==n.RGB){if(1==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],1);if(2==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],arguments[1]/255);if(3==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],1);if(4==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],arguments[3]/255)}else{if(1==argumeM nts.length)return new n.Color(...x(0,0,arguments[0]/100),1);if(2==arguments.length)return new n.Color(...x(0,0,arguments[0]/100),arguments[1]/255);if(3==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),1);if(4==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),arguments[3])}return null},n.red=function(e){return e._r},n.green=function(e){return e._g},n.blue=function(e){return e._b},n.alpha=function(e){return 255*e._a},n.hue=function(e){reM turn e._inferHSV(),e._h},n.saturation=function(e){return e._inferHSV(),e._s},n.brightness=function(e){return e._inferHSV(),e._v},n.lightness=function(e){return 100*(.2126*e._r+.7152*e._g+.0722*e._b)/255},n.lerpColor=function(e,t,r){return n._style.colorMode==n.RGB?new n.Color(n.constrain(n.lerp(e._r,t._r,r),0,255),n.constrain(n.lerp(e._g,t._g,r),0,255),n.constrain(n.lerp(e._b,t._b,r),0,255),n.constrain(n.lerp(e._a,t._a,r),0,1)):(e._inferHSV(),t._inferHSV(),new n.Color(n.constrain(function(e,t,r){var i=[[Math.abs(t-M e),n.map(r,0,1,e,t)],[Math.abs(t+360-e),n.map(r,0,1,e,t+360)],[Math.abs(t-360-e),n.map(r,0,1,e,t-360)]];return i.sort(((e,t)=>e[0]-t[0])),(i[0][1]+720)%360}(e._h,t._h,r),0,360),n.constrain(n.lerp(e._s,t._s,r),0,100),n.constrain(n.lerp(e._v,t._v,r),0,100),n.constrain(n.lerp(e._a,t._a,r),0,1)))},n.strokeWeight=function(e){n._style_noStroke=!1,r.lineWidth=e},n.stroke=function(){if(n._style.noStroke=!1,"string"==typeof arguments[0])return void(r.strokeStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._sM tyle.noStroke=!0:r.strokeStyle=e},n.noStroke=function(){n._style.noStroke=!0},n.fill=function(){if(n._style.noFill=!1,"string"==typeof arguments[0])return void(r.fillStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._style.noFill=!0:r.fillStyle=e},n.noFill=function(){n._style.noFill=!0},n.blendMode=function(e){r.globalCompositeOperation=e},n.strokeCap=function(e){r.lineCap=e},n.strokeJoin=function(e){r.lineJoin=e},n.ellipseMode=function(e){n._style.ellipseMode=e},n.rectMode=function(e){n._style.rectM Mode=e},n.curveDetail=function(e){n._style.curveDetail=e},n.curveAlpha=function(e){n._style.curveAlpha=e},n.curveTightness=function(e){n._style.curveAlpha=e},n.clear=function(){r.clearRect(0,0,n.width,n.height)},n.background=function(){if(arguments[0]&&arguments[0].MAGIC==n.MAGIC)return n.image(arguments[0],0,0,n.width,n.height);r.save(),r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity),r.fillStyle="string"==typeof arguments[0]?arguments[0]:n.color(...Array.from(arguments)),r.fillRect(0,0,n.width,n.heightM ),r.restore()},n.line=function(e,t,i,o){n._style.noStroke||(r.beginPath(),r.moveTo(e,t),r.lineTo(i,o),r.stroke())},n.arc=function(e,t,r,i,o,a,l,s){if(o==a)return n.ellipse(e,t,r,i);null==s&&(s=25),null==l&&(l=n.PIE),n._style.ellipseMode==n.CENTER?m(e,t,r,i,o,a,l,s):n._style.ellipseMode==n.RADIUS?m(e,t,2*r,2*i,o,a,l,s):n._style.ellipseMode==n.CORNER?m(e+r/2,t+i/2,r,i,o,a,l,s):n._style.ellipseMode==n.CORNERS&&m((e+r)/2,(t+i)/2,r-e,i-t,o,a,l,s)},n.ellipse=function(e,t,r,i){null==i&&(i=r),n._style.ellipseMode==n.CENTERM ?b(e,t,r,i):n._style.ellipseMode==n.RADIUS?b(e,t,2*r,2*i):n._style.ellipseMode==n.CORNER?b(e+r/2,t+i/2,r,i):n._style.ellipseMode==n.CORNERS&&b((e+r)/2,(t+i)/2,r-e,i-t)},n.circle=function(e,t,r){return n.ellipse(e,t,r,r)},n.point=function(e,t){e.x&&(t=e.y,e=e.x),r.beginPath(),r.ellipse(e,t,.4,.4,0,0,2*Math.PI),r.stroke()},n.rect=function(e,t,r,i,o,a,l,s){n._style.rectMode==n.CENTER?y(e-r/2,t-i/2,r,i,o,a,l,s):n._style.rectMode==n.RADIUS?y(e-r,t-i,2*r,2*i,o,a,l,s):n._style.rectMode==n.CORNER?y(e,t,r,i,o,a,l,s):n._stylM e.rectMode==n.CORNERS&&y(e,t,r-e,i-t,o,a,l,s)},n.square=function(e,t,r,i,o,a,l){return n.rect(e,t,r,r,i,o,a,l)},n.beginShape=function(){w(),r.beginPath(),o=!0},n.beginContour=function(){r.closePath(),w(),o=!0},n.endContour=function(){w(),o=!0},n.vertex=function(e,t){w(),o?r.moveTo(e,t):r.lineTo(e,t),o=!1},n.bezierVertex=function(e,t,n,i,o,a){w(),r.bezierCurveTo(e,t,n,i,o,a)},n.quadraticVertex=function(e,t,n,i){w(),r.quadraticCurveTo(e,t,n,i)},n.bezier=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.bezierVM ertex(r,i,o,a,l,s),n.endShape()},n.triangle=function(e,t,r,i,o,a){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.endShape(n.CLOSE)},n.quad=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.vertex(l,s),n.endShape(n.CLOSE)},n.endShape=function(e){w(),e&&r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke(),n._style.noFill&&n._style.noStroke&&(r.save(),r.fillStyle="none",r.fill(),r.restore())},n.curveVertex=function(e,t){if(a.push([e,t]),a.length<4)return;M let i=function(e,t,n,r,i,o,a,l,s,h){function c(e,t,n,r,i,o){let a=Math.pow(r-t,2)+Math.pow(i-n,2);return Math.pow(a,.5*o)+e}let u=[],f=c(0,e,t,n,r,h),d=c(f,n,r,i,o,h),x=c(d,i,o,a,l,h);for(let h=0;h<s;h++){let c=f+h/(s-1)*(d-f),g=[(f-c)/(f-0),(c-0)/(f-0),(d-c)/(d-f),(c-f)/(d-f),(x-c)/(x-d),(c-d)/(x-d),(d-c)/(d-0),(c-0)/(d-0),(x-c)/(x-f),(c-f)/(x-f)];for(let e=0;e<g.length;e+=2)isNaN(g[e])&&(g[e]=1,g[e+1]=0),isFinite(g[e])||(g[e]>0?(g[e]=1,g[e+1]=0):(g[e]=0,g[e+1]=1));let p=e*g[0]+n*g[1],m=t*g[0]+r*g[1],b=n*g[2]+i*g[M 3],y=r*g[2]+o*g[3],w=i*g[4]+a*g[5],v=o*g[4]+l*g[5],z=p*g[6]+b*g[7],V=m*g[6]+y*g[7],_=b*g[8]+w*g[9],M=y*g[8]+v*g[9],E=z*g[2]+_*g[3],S=V*g[2]+M*g[3];u.push([E,S])}return u}(...a[a.length-4],...a[a.length-3],...a[a.length-2],...a[a.length-1],n._style.curveDetail,n._style.curveAlpha);for(let e=0;e<i.length;e++)o?r.moveTo(...i[e]):r.lineTo(...i[e]),o=!1},n.curve=function(e,t,r,i,o,a,l,s){n.beginShape(),n.curveVertex(e,t),n.curveVertex(r,i),n.curveVertex(o,a),n.curveVertex(l,s),n.endShape()},n.translate=function(e,t){r.tM ranslate(e,t)},n.rotate=function(e){r.rotate(e)},n.scale=function(e,t){null==t&&(t=e),r.scale(e,t)},n.applyMatrix=function(e,t,n,i,o,a){r.transform(e,t,n,i,o,a)},n.shearX=function(e){r.transform(1,0,Math.tan(e),1,0,0)},n.shearY=function(e){r.transform(1,Math.tan(e),0,1,0,0)},n.resetMatrix=function(){r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity)},n.pushMatrix=n.push=function(){n._styleCache.push({...n._style}),n._style=n._styleCache[n._styleCache.length-1],r.save()},n.popMatrix=n.pop=function(){n._stylM eCache.length-1&&(n._styleCache.pop(),n._style=n._styleCache[n._styleCache.length-1],r.restore())},n.image=function(e,t,i,o,a,l,s,h,c){let u=e.MAGIC==n.MAGIC?e.canvas:e;function d(){if(e.MAGIC!=n.MAGIC||!n._tint)return;let t=e.canvas.getContext("2d");t.save(),t.resetTransform(),t.clearRect(0,0,t.canvas.width,t.canvas.height),t.drawImage(f.canvas,0,0),t.restore()}return e.MAGIC==n.MAGIC&&null!=n._tint&&(function(e,t){null==f&&(f=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvasM .height),f.canvas.width==e&&f.canvas.height==t||(f.canvas.width=e,f.canvas.height=t)}(e.canvas.width,e.canvas.height),f.drawImage(e.canvas,0,0),e.tinted(n._tint)),o?l?(h||(h=u.width),c||(c=u.height),r.drawImage(u,l,s,h,c,t,i,o,a),void d()):(r.drawImage(u,t,i,o,a),void d()):(e.MAGIC==n.MAGIC||e.width?r.drawImage(u,t,i,e.width,e.height):r.drawImage(u,t,i,e.videoWidth,e.videoHeight),void d())},n.loadPixels=function(){l=r.getImageData(0,0,n.canvas.width,n.canvas.height),n.pixels=l.data},n.updatePixels=function(){null!=M l&&r.putImageData(l,0,0)},n.loadImage=function(e,t){s++;let r=n.createGraphics(100,100),i=r.canvas.getContext("2d"),o=new Image;return o.src=e,o.crossOrigin="Anonymous",o.onload=function(){i.canvas.width=o.width,i.canvas.height=o.height,r.width=o.width,r.height=o.height,i.drawImage(o,0,0),s--,t&&t(r)},r};let v={};function z(e,t){null==u&&(u=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvas.height),u.canvas.width==e&&u.canvas.height==t||(u.canvas.width=e,u.canvas.height=t)}funcM tion V(){let e=r.canvas.width*r.canvas.height*4;null!=d&&e==d.length||(d=new Uint8ClampedArray(e))}function _(e){u.clearRect(0,0,u.canvas.width,u.canvas.height),u.filter=e,u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()}v[n.THRESHOLD]=function(e,t){null==t?t=127.5:t*=255;for(let n=0;n<e.length;n+=4){const r=.2126*e[n]+.7152*e[n+1]+.0722*e[n+2];e[n]=e[n+1]=e[n+2]=r>=t?255:0}},v[n.GRAY]=function(e){for(let t=0;t<e.length;t+=4)M {const n=.2126*e[t]+.7152*e[t+1]+.0722*e[t+2];e[t]=e[t+1]=e[t+2]=n}},v[n.OPAQUE]=function(e){for(let t=0;t<e.length;t+=4)e[t+3]=255},v[n.INVERT]=function(e){for(let t=0;t<e.length;t+=4)e[t]=255-e[t],e[t+1]=255-e[t+1],e[t+2]=255-e[t+2]},v[n.POSTERIZE]=function(e,t){let n=t-1;for(let r=0;r<e.length;r+=4)e[r]=255*(e[r]*t>>8)/n,e[r+1]=255*(e[r+1]*t>>8)/n,e[r+2]=255*(e[r+2]*t>>8)/n},v[n.DILATE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-M 1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.max(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.ERODE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.min(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.BLURM ]=function(e,t){t=t||1,t=Math.floor(t*n._pixelDensity),V(),d.set(e);let i=2*t+1,o=function(e){let n=new Float32Array(e),r=.3*t+.8,i=r*r*2;for(let t=0;t<e;t++){let o=t-e/2,a=Math.exp(-o*o/i)/(2.5066282746*r);n[t]=a}return n}(i),[a,l]=[r.canvas.width,r.canvas.height];for(let n=0;n<l;n++)for(let r=0;r<a;r++){let l=0,s=0,h=0,c=0;for(let e=0;e<i;e++){let i=4*(n*a+Math.min(Math.max(r-t+e,0),a-1));l+=d[i]*o[e],s+=d[i+1]*o[e],h+=d[i+2]*o[e],c+=d[i+3]*o[e]}let u=4*(n*a+r);e[u]=l,e[u+1]=s,e[u+2]=h,e[u+3]=c}d.set(e);for(let nM =0;n<l;n++)for(let r=0;r<a;r++){let s=0,h=0,c=0,u=0;for(let e=0;e<i;e++){let i=4*(Math.min(Math.max(n-t+e,0),l-1)*a+r);s+=d[i]*o[e],h+=d[i+1]*o[e],c+=d[i+2]*o[e],u+=d[i+3]*o[e]}let f=4*(n*a+r);e[f]=s,e[f+1]=h,e[f+2]=c,e[f+3]=u}},n.filter=function(e,t){if(n.HARDWARE_FILTERS&&null!=r.filter)if(z(),e==n.THRESHOLD){null==t&&(t=.5),t=Math.max(t,1e-5),_(`saturate(0%) brightness(${Math.floor(.5/t*100)}%) contrast(1000000%)`)}else if(e==n.GRAY)_("saturate(0%)");else if(e==n.OPAQUE)u.fillStyle="black",u.fillRect(0,0,u.canvaM s.width,u.canvas.height),u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.drawImage(u.canvas,0,0),r.restore();else if(e==n.INVERT)_("invert(100%)");else if(e==n.BLUR)_(`blur(${Math.ceil(t*n._pixelDensity/1)||1}px)`);else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}},n.resize=function(e,t){z(),u.drawImage(r.canvas,0,0),n.width=e,n.height=t,r.canvas.width=e*n._pixM elDensity,r.canvas.height=t*n._pixelDensity,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0,r.canvas.width,r.canvas.height),r.restore()},n.get=function(e,t,i,o){if(null!=e&&null==i){let i=r.getImageData(e,t,1,1).data;return new n.Color(i[0],i[1],i[2],i[3]/255)}e=e||0,t=t||0,i=i||n.width,o=o||n.height;let a=n.createGraphics(i,o);a.pixelDensity(n._pixelDensity);let l=r.getImageData(e*n._pixelDensity,t*n._pixelDensity,i*n._pixelDensity,o*n._pixelDensity);return a.caM nvas.getContext("2d").putImageData(l,0,0),a},n.set=function(e,t,i){if(i.MAGIC==n.MAGIC){let r=n._tint;return n._tint=null,n.image(i,e,t),void(n._tint=r)}let o=4*(t*n._pixelDensity*r.canvas.width+e*n._pixelDensity);n.pixels[o]=i._r,n.pixels[o+1]=i._g,n.pixels[o+2]=i._b,n.pixels[o+3]=255*i._a},n.tinted=function(){let e=n.color(...Array.from(arguments)),t=e._a;e._a=1,z(),u.clearRect(0,0,u.canvas.width,u.canvas.height),u.fillStyle=e,u.fillRect(0,0,u.canvas.width,u.canvas.height),u.globalCompositeOperation="multiply",u.M drawImage(r.canvas,0,0),u.globalCompositeOperation="source-over",r.save(),r.resetTransform();let i=r.globalCompositeOperation;r.globalCompositeOperation="source-in",r.drawImage(u.canvas,0,0),r.globalCompositeOperation=i,r.restore(),u.globalAlpha=t,u.clearRect(0,0,u.canvas.width,u.canvas.height),u.drawImage(r.canvas,0,0),u.globalAlpha=1,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()},n.tint=function(){n._tint=n.color(...Array.from(arguments))},n.noTiM nt=function(){n._tint=null},n.mask=function(e){r.save(),r.resetTransform();let t=r.globalCompositeOperation;r.globalCompositeOperation="destination-in",r.drawImage(e.canvas,0,0),r.globalCompositeOperation=t,r.restore()},n.clearTemporaryBuffers=function(){u=null,f=null,d=null},n.save=function(e,t){e=e||"untitled",t=t||"png";var n=document.createElement("a");n.innerHTML="[Download]",n.addEventListener("click",(function(){this.href=r.canvas.toDataURL(),this.download=e+"."+t}),!1),document.body.appendChild(n),n.click()M ,document.body.removeChild(n)},n.saveCanvas=function(e,t,r){if(e.MAGIC==n.MAGIC){r&&e.save(t,r);let n=t.split(".");return e.save(n.slice(0,-1).join("."),n[n.length-1])}if(t)return n.save(e,t);let i=e.split(".");return n.save(i.slice(0,-1).join("."),i[i.length-1])},n.loadFont=function(e){let t=e.split("/"),n=t[t.length-1].split(".")[0].replace(" ",""),r=`@font-face {\n font-family: '${n}';\n src: url('${e}');\n }`;const i=document.createElement("style");return i.textContent=r,document.head.append(M i),n},n.textFont=function(e){n._style.textFont=e},n.textSize=function(e){n._style.textSize=e,n._style.textLeading=e},n.textLeading=function(e){n._style.textLeading=e},n.textStyle=function(e){n._style.textStyle=e},n.textAlign=function(e,t){r.textAlign=e,t&&(r.textBaseline=t==n.CENTER?"middle":t)},n.text=function(e,t,i,o){if(!e)return;if(e=e.toString(),n._style.noFill&&n._style.noStroke)return;r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`;let a=e.split("\n");for(let e=0;e<a.length;e++)n._M style.noFill||r.fillText(a[e],t,i,o),n._style.noStroke||r.strokeText(a[e],t,i,o),i+=n._style.textLeading},n.textWidth=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).width},n.textAscent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBoundingBoxAscent},n.textDescent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBounM dingBoxDescent};var M,E=4,S=.5,R=function(e){return.5*(1-Math.cos(e*Math.PI))};n.noise=function(e,t,n){if(t=t||0,n=n||0,null==M){M=new Array(4096);for(var r=0;r<4096;r++)M[r]=Math.random()}e<0&&(e=-e),t<0&&(t=-t),n<0&&(n=-n);for(var i,o,a,l,s,h=Math.floor(e),c=Math.floor(t),u=Math.floor(n),f=e-h,d=t-c,x=n-u,g=0,p=.5,m=0;m<E;m++){var b=h+(c<<4)+(u<<8);i=R(f),o=R(d),a=M[4095&b],a+=i*(M[b+1&4095]-a),l=M[b+16&4095],a+=o*((l+=i*(M[b+16+1&4095]-l))-a),l=M[4095&(b+=256)],l+=i*(M[b+1&4095]-l),s=M[b+16&4095],l+=o*((s+=i*(M[M b+16+1&4095]-s))-l),g+=(a+=R(x)*(l-a))*p,p*=S,h<<=1,c<<=1,u<<=1,(f*=2)>=1&&(h++,f--),(d*=2)>=1&&(c++,d--),(x*=2)>=1&&(u++,x--)}return g},n.noiseDetail=function(e,t){e>0&&(E=e),t>0&&(S=t)};const I=function(){let e,t,n=4294967295;return{setSeed(r){e=t=(null==r?Math.random()*n:r)>>>0},getSeed:()=>t,rand:()=>(e^=e<<17,e^=e>>13,((e^=e<<5)>>>0)/n)}};let C=I();C.setSeed(),n.noiseSeed=function(e){let t=null==e?4294967295*Math.random():e;M||(M=new Float32Array(4096));for(var n=0;n<4096;n++)t^=t<<17,t^=t>>13,t^=t<<5,M[n]=(t>M >>0)/4294967295},n.randomSeed=function(e){C.setSeed(e)},n.random=function(e,t){return null==e?C.rand():"number"==typeof e?null!=t?C.rand()*(t-e)+e:C.rand()*e:e[~~(e.length*C.rand())]},n.randomGenerator=function(e){e==n.LCG?C=function(){const e=4294967296;let t,n;return{setSeed(r){n=t=(null==r?Math.random()*e:r)>>>0},getSeed:()=>t,rand:()=>(n=(1664525*n+1013904223)%e)/e}}():e==n.SHR3&&(C=I()),C.setSeed()};var T=new function(){var e,t,n,r=new Array(128),i=new Array(256),o=new Array(128),a=new Array(128),l=new Array(2M 56),s=new Array(256),h=function(){return 4294967296*C.rand()-2147483648},c=function(){return.5+2.328306e-10*(h()<<0)};this.SHR3=h,this.UNI=c,this.RNOR=function(){return n=h(),e=127&n,Math.abs(n)<r[e]?n*o[e]:function(){for(var t,i,l,s,u=3.44262;;){if(t=n*o[e],0==e){do{l=c(),s=c(),t=.2904764*-Math.log(l),i=-Math.log(s)}while(i+i<t*t);return n>0?u+t:-u-t}if(a[e]+c()*(a[e-1]-a[e])<Math.exp(-.5*t*t))return t;if(n=h(),e=127&n,Math.abs(n)<r[e])return n*o[e]}}()},this.REXP=function(){return(t=h()>>>0)<r[e=255&t]?t*l[e]:funM ction(){for(var n;;){if(0==e)return 7.69711-Math.log(c());if(n=t*l[e],s[e]+c()*(s[e-1]-s[e])<Math.exp(-n))return n;if((t=h())<i[e=255&t])return t*l[e]}}()},this.zigset=function(){var e,t,n=2147483648,h=4294967296,c=3.442619855899,u=c,f=.00991256303526217,d=7.697117470131487,x=d,g=.003949659822581572;for(e=f/Math.exp(-.5*c*c),r[0]=Math.floor(c/e*n),r[1]=0,o[0]=e/n,o[127]=c/n,a[0]=1,a[127]=Math.exp(-.5*c*c),t=126;t>=1;t--)c=Math.sqrt(-2*Math.log(f/c+Math.exp(-.5*c*c))),r[t+1]=Math.floor(c/u*n),u=c,a[t]=Math.exp(-.5*cM *c),o[t]=c/n;for(e=g/Math.exp(-d),i[0]=Math.floor(d/e*h),i[1]=0,l[0]=e/h,l[255]=d/h,s[0]=1,s[255]=Math.exp(-d),t=254;t>=1;t--)d=-Math.log(g/d+Math.exp(-d)),i[t+1]=Math.floor(d/x*h),x=d,s[t]=Math.exp(-d),l[t]=d/h}};T.hasInit=!1,n.randomGaussian=function(e,t){return T.hasInit||(T.zigset(),T.hasInit=!0),T.RNOR()*t+e},n.randomExponential=function(){return T.hasInit||(T.zigset(),T.hasInit=!0),T.REXP()},n.print=console.log,n.cursor=function(e,t,r){let i="";e.includes(".")&&(e=`url("${e}")`,i=", auto"),null!=t&&(e+=" "+t+M " "+r),n.canvas.style.cursor=e+i},n.noCursor=function(){n.canvas.style.cursor="none"},n.createCapture=function(e){var t=document.createElement("video");return t.playsinline="playsinline",t.autoplay="autoplay",navigator.mediaDevices.getUserMedia(e).then((function(e){t.srcObject=e})),t.style.position="absolute",t.style.opacity=1e-5,t.style.zIndex=-1e3,document.body.appendChild(t),t};let A=["setup","draw","preload","mouseMoved","mousePressed","mouseReleased","mouseDragged","mouseClicked","keyPressed","keyReleased","keM yTyped","touchStarted","touchEnded"];for(let e of A){let t="_"+e+"Fn";n[t]=function(){},n[t].isPlaceHolder=!0,n[e]?n[t]=n[e]:Object.defineProperty(n,e,{set:function(e){n[t]=e}})}function D(){n._noLoop||(i=null==n._frameRate?requestAnimationFrame(D):setTimeout(D,1e3/n._frameRate)),w(),o=!0,n.push(),n._drawFn(),n.pop(),++n.frameCount}function k(e){const t=n.canvas.getBoundingClientRect(),r=n.canvas.scrollWidth/n.width||1,i=n.canvas.scrollHeight/n.height||1;return{x:(e.clientX-t.left)/r,y:(e.clientY-t.top)/i,id:e.idenM tifier}}function L(){return n._touchStarted.isPlaceHolder&&n._touchMoved.isPlaceHolder&&n._touchEnded.isPlaceHolder}n.noLoop=function(){n._noLoop=!0,i=null},n.loop=function(){n._noLoop=!1,null==i&&D()},n.redraw=function(){D()},n.frameRate=function(e){n._frameRate=e},setTimeout((function(){n._preloadFn(),c=window.performance.now(),function e(){if(s>0)return setTimeout(e,10);n._setupFn(),D()}()}),1),n.canvas.onmousemove=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPM ressed?n._mouseDraggedFn(e):n._mouseMovedFn(e)},n.canvas.onmousedown=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!0,n.mouseButton=[n.LEFT,n.CENTER,n.RIGHT][e.button],n._mousePressedFn(e)},n.canvas.onmouseup=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!1,n._mouseReleasedFn(e)},n.canvas.onclick=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressedM =!0,n._mouseClickedFn(e),n.mouseIsPressed=!1},window.addEventListener("keydown",(function(e){n.keyIsPressed=!0,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!0,n._keyPressedFn(e),1==e.key.length&&n._keyTypedFn(e)})),window.addEventListener("keyup",(function(e){n.keyIsPressed=!1,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!1,n._keyReleasedFn(e)})),n.keyIsDown=function(e){return!!h[e]},n.canvas.ontouchstart=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.moM useY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mousePressedFn(e)||e.preventDefault()),n._touchStartedFn(e)||e.preventDefault()},n.canvas.ontouchmove=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mouseDraggedFn(e)||e.preventDefault()),n._touchMovedFn(e)||e.preventDefault()},n.canvas.ontouchend=n.canvas.ontouchcancel=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.M mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!1,n._mouseReleasedFn(e)||e.preventDefault()),n._touchEndedFn(e)||e.preventDefault()},n.hasSensorPermission=!window.DeviceOrientationEvent&&!window.DeviceMotionEvent||!(DeviceOrientationEvent.requestPermission||DeviceMotionEvent.requestPermission),n.requestSensorPermissions=function(){DeviceOrientationEvent.requestPermission&&DeviceOrientationEvent.requestPermission().then((e=>{"granted"==e&&DeviceMotionEvent.requestPermissioM n&&DeviceMotionEvent.requestPermission().then((e=>{"granted"==e&&(n.hasSensorPermission=!0)})).catch(alert)})).catch(alert)},window.ondeviceorientation=function(e){n.pRotationX=n.rotationX,n.pRotationY=n.rotationY,n.pRotationZ=n.rotationZ,n.pRelRotationX=n.relRotationX,n.pRelRotationY=n.relRotationY,n.pRelRotationZ=n.relRotationZ,n.rotationX=e.beta*(Math.PI/180),n.rotationY=e.gamma*(Math.PI/180),n.rotationZ=e.alpha*(Math.PI/180),n.relRotationX=[-n.rotationY,-n.rotationX,n.rotationY][1+~~(window.orientation/90)],n.rM elRotationY=[-n.rotationX,n.rotationY,n.rotationX][1+~~(window.orientation/90)],n.relRotationZ=n.rotationZ},window.ondevicemotion=function(e){if(n.pAccelerationX=n.accelerationX,n.pAccelerationY=n.accelerationY,n.pAccelerationZ=n.accelerationZ,!e.acceleration){let t=((e,t)=>[(e[0]*t[0]+e[1]*t[1]+e[2]*t[2]+e[3])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[4]*t[0]+e[5]*t[1]+e[6]*t[2]+e[7])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[8]*t[0]+e[9]*t[1]+e[10]*t[2]+e[11])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15])])(((e,t)M =>[e[0]*t[0]+e[1]*t[4]+e[2]*t[8]+e[3]*t[12],e[0]*t[1]+e[1]*t[5]+e[2]*t[9]+e[3]*t[13],e[0]*t[2]+e[1]*t[6]+e[2]*t[10]+e[3]*t[14],e[0]*t[3]+e[1]*t[7]+e[2]*t[11]+e[3]*t[15],e[4]*t[0]+e[5]*t[4]+e[6]*t[8]+e[7]*t[12],e[4]*t[1]+e[5]*t[5]+e[6]*t[9]+e[7]*t[13],e[4]*t[2]+e[5]*t[6]+e[6]*t[10]+e[7]*t[14],e[4]*t[3]+e[5]*t[7]+e[6]*t[11]+e[7]*t[15],e[8]*t[0]+e[9]*t[4]+e[10]*t[8]+e[11]*t[12],e[8]*t[1]+e[9]*t[5]+e[10]*t[9]+e[11]*t[13],e[8]*t[2]+e[9]*t[6]+e[10]*t[10]+e[11]*t[14],e[8]*t[3]+e[9]*t[7]+e[10]*t[11]+e[11]*t[15],e[12]*t[0]+M e[13]*t[4]+e[14]*t[8]+e[15]*t[12],e[12]*t[1]+e[13]*t[5]+e[14]*t[9]+e[15]*t[13],e[12]*t[2]+e[13]*t[6]+e[14]*t[10]+e[15]*t[14],e[12]*t[3]+e[13]*t[7]+e[14]*t[11]+e[15]*t[15]])((e=>[Math.cos(e),0,Math.sin(e),0,0,1,0,0,-Math.sin(e),0,Math.cos(e),0,0,0,0,1])(n.rotationY),(e=>[1,0,0,0,0,Math.cos(e),-Math.sin(e),0,0,Math.sin(e),Math.cos(e),0,0,0,0,1])(n.rotationX)),[0,0,-9.80665]);n.accelerationX=e.accelerationIncludingGravity.x+t[0],n.accelerationY=e.accelerationIncludingGravity.y+t[1],n.accelerationZ=e.accelerationIncludM ingGravity.z-t[2]}},n.year=function(){return(new Date).getFullYear()},n.day=function(){return(new Date).getDay()},n.hour=function(){return(new Date).getHours()},n.minute=function(){return(new Date).getMinutes()},n.second=function(){return(new Date).getSeconds()},n.millis=function(){return window.performance.now()-c}}(e)}"object"==typeof exports&&"undefined"!=typeof module&&(module.exports=e);const t="https://ancient-crimson-rain.btc.discover.quiknode.pro/c268fb026303ae8443f785200f2ea4b82f0082dd";function n(e){P(e)?M localStorage.removeItem("blocksApiEndpoint"):localStorage.blocksApiEndpoint=e}function r(){return localStorage.blocksApiEndpoint||t}function i(e){P(e)?localStorage.removeItem("modelInscriptionEndpoint"):localStorage.modelInscriptionEndpoint=e}function o(){return localStorage.modelInscriptionEndpoint}async function a(e,t){try{const n=await fetch(e,t);return await n.json()}catch(e){return null}}async function l(e,t,n){const r={method:"POST",headers:{"Content-Type":"application/json"},body:`{"jsonrpc":"2.0","id":1,"meM thod":"${t}","params":${`[${n.join(sep=",")}]`}}`};return(await a(e,r))?.result}async function s(e){const n={avgfee:10,time:Date.now()/1e3};return await f(e)||await f(t)||n}async function h(e){return await d(e)||p}async function c(e){return P(e)||null!=await f(e)}async function u(e){return P(e)||null!=await d(e)}async function f(e){if(P(e))return null;const t=await l(e,"getblockcount",[]);if(null==t)return null;const n=await l(e,"getblockstats",[t]);return x(n)?n:null}async function d(e){if(P(e))return null;const tM =await a(e,{});return g(t)?t:null}function x(e){return"number"==typeof e?.time&&"number"==typeof e?.avgfee}function g(e){if(null==e)return!1;const{classes_name:t,training_traits:n,layers_config:r,weight_b64:i}=e;if(!Array.isArray(t))return!1;if(null==n)return!1;try{j(r,i)}catch(e){return!1}return!0}const p={"model_name": "pfp_classifier_202", "layers_config": {"config": {"layers": [{"class_name": "InputLayer", "config": {"batch_input_shape": [null, 28, 28, 3]}}, {"class_name": "Rescaling", "config": {"scale": 0.007M 84313725490196, "offset": -1}}, {"class_name": "Flatten"}, {"class_name": "Dense", "config": {"units": 3, "activation": "leaky_relu"}}, {"class_name": "Dense", "config": {"units": 6, "activation": "leaky_relu"}}, {"class_name": "Dense", "config": {"units": 2, "activation": "leaky_relu"}}, {"class_name": "Dense", "config": {"units": 9, "activation": "leaky_relu"}}, {"class_name": "Dense", "config": {"units": 11, "activation": "leaky_relu"}}, {"class_name": "Dense", "config": {"units": 11, "activation": "leaky_relu"}M }, {"class_name": "Dense", "config": {"units": 5, "activation": "leaky_relu"}}, {"class_name": "Dense", "config": {"units": 4, "activation": "linear"}}]}}, "weight_b64": "D7CQvO2ngD03S7k8vK6UvE8MnD0upVW9wsu6PFjQgD367GG9VsAKPdMt8Lv/Mae6+bUgPWGAYT3L8+I78MViPQllLT0d13u9ygOcvO/jXbzqI+I83QgaPUe8Hz1XF5S9OPmWPT6jl7y4kJM85m0cvfEecT0c79W8pUzZPJcRND3DAwu8wdSiPXAnHzzuJGg9bnP5PHm6Oz1P8IQ9+3xPvLWIOj1nSta7nbTmPEL8kzxWDRQ9wKHRPCO2mD3x0Pu8zmXuutCFxj3KRw47dHxKPDp0MD3+wBm9U2DGvCulaD353sI878ksvCGHVj2fav48RUYHPf8Txz19ryY8RkIWPYnfoT3oRM 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 qi7RS6tvIL3rzwTDYU8EWByPf4YpD30WnG7NGiPPRf5VDzEI7k8sbeuPEZs6jvnDXw9U5r8O5Uf+jvvpDQ9GD14PWfxKj0Ij/c7fbYBPRpXJj37p5E8RkigvL4thD1/zI27zsNxPZCeuzyQ0MC81v0NvZwqSj2x4h298PRXPBtMjT1u1H69xupDvAQk0j0d8+S8bB1CvVbahj1aYPO88dwhPQqF7T3sDiG9NqQGPMxI0j38+jg8kZDOO2V8rj0gvEK80AnQPZ932D02AUm9a8nyPZpfbT0klhE9Y54KPWwYtz1sU0o8+8UNPVIRsj08NaG9Xai8PRMN7D3PWhi9GsvwvMNtBj1iK5U7/jIivPi2Fj7yOJq8A0a7PeJ3Wz1yybs8yFPqPNtc0Tzw6IG9tRoyvJMB9D3KD3O9i25qPJe+kz0CVyY8iNEovftcgLs2UqW9c2OCuzCQTD35Bky9p02uPBUdhD0TqKk81ly0PP6OVD0ISwm89yUPvYJ0+zxxKz29ZRc5PM 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 0T4WbyhJ4G8fLx4vR0hvrwnPmE8+tFpvdNnW70X/AS9N61bOpCFEr2qM228yrvmvMS5QL2oTze8QQAAPbpcUL1a9xE8+DWkOWWeWj0w/Ie9nkjbO23Qbr3EzX47E+RxvBKiDL3Z4Uy9NlbcvHTGET2wTrW7SAGePIFYSztbLgU8UwBTPTXDKTwG95K9Zb1vvOUpEj2heTS9XiSDvDxRib1xfE88B5yFPXOnnjxzdoS6PGWhvMKHwjtJp3+8jz8/PChSYL0M2RS9j5klPXf4krz1zEQ8w/TYvBS5Lr3ZPr08Z5jRPJmcCbwP+om8vjJtvbUQG72k90A92WsLPVTYLbxoxSy5W/xRPYkSWrzLmh68XKZUveHlhT3iDRO9zsxqPEv8hD072w+9GBpaPbBqaDt58jw8E9RIvGP7xTwhv5W9pcU0PKnLsD0unHq9ml+dPT/Iej27/MA8Jdl7PR3GtT0WjGK9lpnHPXOWGj54caq8YE5lPWfyXz0dXfc8xRx9u0BgsT1qRM 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 /28cT1hiQM9xhQ8O/W/qzxt4nA8DzW7PJfuyT3c2YW8bQBIvDg9Aj6fcVU8zqpyPJYz0T3mLyq9lBcevVdnWj0TbhM8Br6WPcaKEj4wMQS851lOPeRGqD2uCU69kBOYuxyROT3hhf07s/VYPYfLsz2FSju8kW6XPcQ2rj1Elf88rnjCPNKh2j1zjR4844Llunezsz0TtvM8EO+SvN3fAT5ql/w8F/2xPPrgkj0BGj07o4KyPedTFz79+IA8aHKtPYwVPD1DoGc8VlyPPSqDGj3nXTQ7T+zNPXc19z2Axd+81qPNPbmo3D1hOO68aW4AvQVyuD2kuO887hOrPHbN6z2HY8U79Dh/PQuOwT0cmCY8br98u0A0Vzv97Gc8lUnYPM864Dybe4q8RRFmvJ0kOj2ufVW9P6xkPbHbhTxH3x09aK2EPQpH5jw7bhI9xS0vPFk5AzxJO1O9E2IpPQ9cFr2wjAq9rqBYPNQFLDy9Nki9wNwwPalUIj15eq+7GO1hPcy3iL3SQM 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 ZPCibwGudE63SJ9PXnZBT2BMw+9pLdkPdeAO7yTBBm82pGDPWHbnb1clIi6JdqIPZBbGb1zfgW9zXSwvUwXnrzFnW09mX/VvOMgrDyanuM9oF4Ovfv59bxYfr06eHm0vZpQ2D09PR892D0PvWlnrby/Wpo9I1sivN02+Tu7jJ+8xfFHvf3iaLtiwpk9AYmavXkqSjw/ZRs9pAyFvVK/bDsgZsc8mIgVPY7kyjx9gIM7BW0IPAzR2bwIA6M99jHIvHR2Hzz1cHQ9zvIFPARnBbsd8as6zedOvUeoDDsMKjo9RgqEvOW04DzbD5Q8lJ0PvQF2ez3g0mu8AkdsPRuypj2z/aU8fkqivbwCED62BMi9GkT+vRhQ9zxcrRi9g1udPYHooz2qLwG9bpsEvRuyID4vsCS9JrKjveL/gL1zLjG973eaPbx60T3Uu0O8LsXLu09YGT5KV3i8K+nIO064Zb2ur/u9utMgPUJS2jr+PYC9uJ/GO75U/D3CV5y9VIe8vWJ7zjzLWM M+93UDFO6h0KLyKJg++Vhv8vZn+vD33rTG+PzKuvaDBMT2zPTC9f+IMvRSLiT2TPSu9yTewva33H7zY6Na9YSAevYYpsz0rVQ8+8iw2vb4APL1FgPo9xnn9vRd5iL0VUjc9kGb1vOhrmj2MtzA9PTyHPUmeDj0jb5M8skz6PM3aj70Wuw09/FowPYPr0z3ZYy+9SB+mPH+QWzxHUp69c+AxPXHhuL3LYjY9msu1O9xUOrxXWPm7WtQfPQf5db3mNQ+9j01PPcKlPbx8llc9A5BmvYNbl7oN2Qy8SWSAvUMcdLyFrOW8YpUuPJ4sbD0MU+G9Q4g3vGN79bxO3ms9wGwpvRoSQr0ypXo9q3VTPU4zrr1Ndkm9FrQovB1mBT0IjLe8/cKQPQy0pj2OYJu6ymSNvEA00rsVemC94P6gu9TqRjyMpkO98ah+vLYwwD1XIn07f5caPHTalDzAEh48hoNMu1aV3rx6jg084UT9vB9Zwj3G+8C8jrgTO8tHXjzqS1o8PEhdPM 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 f/5a70oAk89rFKavDjpxr0J0WE9NHiFvBoopb1eglM910JVvcjY1LzVcZc97yQJPZEutLySLT+80v4WPARtBb01dd88s0lwvWHxUD2Ar3G9jrKCPCRtLr3m69K8gHIjPCo7b7wsfSq9mP+RPSQ9qDyMbly8nYnHu9xUpbxmhPC5VkjfO1JAsr0SXIe8xgHtPOWNNLxHg0c9+RBnvcpgjj2Qpz89Oji1vXYyIT34iRU9R/MAvSo98jzUHC48mjJVPbmpTbtmqgE+j5aaPVmCT7wgiyi8pTf7O1EdZLzqhA48uxWSvcytuDu/k8I8D5lDvS+bgrs+xzc9mAcjvdOFobtKay097KnhPBKkj71EAKu5MbuZvCGCA74Y/rO9HSEcvb4hAr1QAAW9QCy9PYDVuL19VgA9vzbsPSPtMr2u1aI9byX1uc6sIjx2+rS8jOoyPQYnIL0qxMw9JaMePkmkRzxjrvI9NzbIPXEocz2lafk9xiZOvm//UT0pOD6+rBBjvnhqzbuq9M 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 JM8ZDVfPWcI2L22Z5I9wAFCPHeNOL7WR1o9cN5tPcso1b3PW2c9xFqePLyhfL0WXnM9tpBoPUQJC77jFms9BQ+QPODFXb3QcYg9OHJlPURFFr0cjC89qDP6uyYns7w71eg8Ej6GvVwnlr2T9Yk9zlj3PNTjBLvlC2a9zbqTvDcnRrsBNUa9Qe/GvUurOLvni8K8xff9PIeneD0Amrm8+1LdPIHvjbtDOhS94F3FOye+pbzSOFW9n6RjvAdaD772WnU91+NFPV6hor3ukb09EKSLPMnTK718xYA9jU//vJIeoT07vsw8fj/CvNpzxz3NpEK98WXDPBJHsD31FYm9BiWwu+rNTj3+eBo9GQUYPa0JoD238Le8BJRLvCeRHT2zt2C9PBUUvM/cWb3COq89EDoPvZDCBL7nhzU81w+4vRZ+hjtDgns9wJd9PdYCeb3Axoq9kowdvDroO70EEMu94DKhvT8hnT37KSy+SSwZPjdLsL3Al7Y8auUFPs3/C74e0qo9rHn9PM 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 +M9WbWePceMC729Trw9sdaXvRjgmT3qlfk8rwI3vUND2ryaB3c9w09uPRGFqj2YuOI70HxlvCqviT3gDYi90ik8Os5eqDt307y8cMguPcMm+jyu/LW9wbyxvKCstL1QFjY9uj/YPAArCrw0Z4m8HrebPXydSL3sCoU9ttvoO7y867wW2rI9+r2UPeocrbtMQIk9pXHbPGMPNb2D5g89Q4Y6vYwMfLzB2CG9C+lmvSg2X72yKBC9+lDfvEkMhL0+6A09rgorvYNHujytts+7jKQ5PPN3Z7wqFDm9e3/kO5m6pr2wTFE8qqQiPadLoL1cOb88ct2rOwx7Nr5TPbo97fsePShfjL2naZw9b0RRPWM0bL2tHUm7nKkGPSQKtL2Frus8UbvHvItspjxadXw8EPg8PPYpib3cMDQ9lCMFu8B8WL2fblU9bFMHvgy5HL3drAE9nPjVPArsibxQzg+9+HeEvcosFr3C8MO7DG/yvRSsdj3SsUm9xe2fPYOpxzzmZN48vR9tvM Ev3Qrz0JAC8sWxBvVle8TyPZEg87pwavVKbor1wNko94guIO69Nrb0fLKE9AIQRPTwtPL1lWQQ8W/sKvasTBj1N2Di940YKPKy7SbwNjiG9HIgsPdQXED00LGs8ahCOvEHmQz75KFW91dETvf41KD4j3Gq8FFJUPeXqEz5+MKO9od0XvkdvZL3LohE+oRa4vWWL0b0XbOk9Yh+kvW53mb0ed0Y9Gg52vE+z6zz2PWW9bQwNvvdAt7yWu++9Ivi/vb4N/rtWCOu9mCaAPWK3Ib5UwKo9VifaPQH6Pb4eJbc8UClWPACo773p02E9+qGlPZynozymu2I9j1iwPWVeEz12QT8+lW0/PWkbVj386p09PdSjPZBQpT3i+Rw+rBgHPnVMND64Hrg9Cy6JPZxRgj4RSqA9q4xQPXAkKT2Mbhw8cknvPGxXdz62G1K9/4mFPP+8jD6hDzW9QSrKPZM14bzKlo498IdXPLDOyD2TrTe8aDsSPcQiIT4/IhU9yjsDPrVzBb1zzM 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 3c90AY9vTVzSrww4m49EhWkPG960TyliiU94Y2wO7yZVzvCrRK8t2movd68RLyGFd67BIhjvIXPBD5nN5Y6SqNtvYLXWD294a48UtGgvdeStT01xFW9UadAvVoVjjmjJtq8kiX2ulfR1jzBfRY9LLDOOwBQBz0vpjQ8+IbYO7pOT74cJr08sV4iPe59Mb44Uo496EDBPHdFAb6x4L49AF8jPZduGT3Wk1e9fjG2Pa8BTD2Vc7C9076tPaFFET7++7m9hH5UvZmuOz7Ia5K82kq1vW7jQT6Imow8Qv/ePFyQsTxWw5u9P8UMvAXCHr0SRBE+9o0fvQYZkr0X8P09m9AZvfsnx73L8xk+u3glPXTB9Ty2dtW8zoIrvJmQD74Fxm28q6PivYKcAr6RcNI86hsLPj8E7r3xIY29apyRPLuUcb7BehO822zDPNEsgL5+oqE6lbcjPv3Is74MLYg91/XcPRpN4r6Ybyo+tO5Ouc0Zrb42aT8+0MwSPhJEsL4bPXs9qGXePM 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 Km9kuHSPQayB71WK6A8YwgPPgAvgrzjYQC8LU6FPS//cD0QdFE9unMCPv1X7jwPpIU8rwQnPl0EFD3zzR08Yqa3PYWGW7zG/IQ9wMDOuy/4kT1ZX4O83jMAvdSFkz346Gm9vft0Pc49DLwGxIC9SfQdPfPcCD6LgxG+9bkOPgkNCj7ht9K9B4eZPTXKIT5ozPS8eOQbPXEMCL0Qlc88qJtiPUEF4TyVU3W9V5F5PLUsx7ziavc8AKkGuybwKr2GNMw9qIgIvUr8kL03goQ8kpUdu3rkoLyhmZY9FiF9vQGWzz075a08kPruO/zx0z1aeQy9g+O1vcNOvj3IUAQ9VzP1vfxj5z0V6Vm94/wzvvgfPj2cNNE83ElAvjpDkD0hpyq9m4TUO/k9vTxwhYm54hGIvb8i9jqaare9eEdLvQKn67uo+aa9CfQevR3CTr2NhMK8M6b/vMmJg71dqGY9XCptvXPhPL1o2A07AwO5PNfPA717gXu8LpiOvDyXBb68RYq8SW5dvM 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 OKv3z0/W1+8L3S2vf2QYD6CRni9N8dEPZxyFD626Bu9OG+CvJ1wKD7i+ki9D0nVvZ8ddj6dth6+hplsvW/FJz4nSd69mNE3vBlWCj3kCXK9r7tBvcWTNz5A/0C+PYW3vKHbHT57Fv69C1qVPPBmUDwoMAS+iyObPbPKqD303K+93cE7PeBs1D0vxLa9nG15PZLcKL2mdP46gMSbPV6eT7qmfeK8e6IwPUABVjyvyA492JJ8PdEDjr2F4hE9NfGyPe+BG73bf8A9IgVaOwZTyr0bG0s9IS7MvQdiUT2FE7w83PKBvTas9jzZ61c9UypdvFQ9IjwZtPI6FepGvGVfOj6dg6e8SlhmvVzMLD7vvxu9wZ+UvUqngD3PN8M78Z76PCo7AT6iMHi92/abvePpaD0lwqu9qf0Xvh8AjT2rp3q9DqYCvRfrEj14Vg+9Oh8CvUCIGj1L7uC8/k0tvSF9Rj1HpYm9KKJ4PUfBlzzceWs8Ze2nvPgO5L2nQ408aZCkvU6mhL1qGM 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 bZpPj2IleA8U11evfls8D0LMqM9m0RRva1zVTwn6r480vLRvZxQeD398jY8RICXvc4/wT1np148YiiSvZB9DD0cTH48ztkWvlSCFD2txPo7aWeyvR5jXzzB0B298kGSvepwnL1Zu0G9m1EqvrNwk7zR4JW9sluBvezODr2zn9Q899v/vBNES7vZ4BK9vlvTvXmpSL0M3108CrU8Pft7zLyIxce8ob6bvSN6gb0KL+k7tKZGvd0BzL0CJlW8/YGJPRsAj70U2++84/0FvNgLkr1nUjU9Kuj4vHXWz73xVxg8rLYAPdf/v7zEMCm9QirOvGeB5r3T2Uk9TS4Fvb5t3bqWZSc9zthSPJJkOb1CzrI87orePHnK771c4n08u95IPD3f3LyuFz86YeoXPS1T2zyFMvE8Z9oHvQ8QKL3cLTY9NGCavUoCfL1F6tQ8QUTpvDlAZzu/1/s8TFwHvNEjbLzN0MQ8KlOwvfWaWL1Adqw9LfGNPO8JrTwU5727USitO08CerwGRM yA9NBSfvXLEzrznMkM8iweJva+LtDyp3SA9whemvLAWVL0fIag8nRUHvEGv+zzyp8M8lQI8vSqhk7y8Pmk8E7Yava/x7LxQiSk8y9A0vH8UDLxUoDS8hRqJPX90eb0a7Sg9WW/9vNvJ3b0rrmk9UVAHvaula71BoD885E79vN1lFL0hFjc92XjkvImAqr3t/xS9MMJjvVDuEb0Cpo48rk9kPfwVOL0TsR69bY0TOwn88b1vbU49JQBBvXsscL0X5Ui9KGBxPaD83b0Jenk9BgapPPXsHb7Ylvo8xTrPvL9bU732HeM88bzZPFbS1L0DGA4807KxvcGxgL2C6ui8+yiTvTafNL2zGcY8Y95uvVzJ8Lh0+dq8/+AQvXTSizwo28e8mJ7uvfocG70Jejm9j6ZQvSvHlD16nZe9BdkDvvYh9Tucksi8DBcDvpVzDT31S/W7yvhCvVGFVD1IyRa94a6AvSRyP7xQJ+C8O7kIvpoMU72UMpy9MwO2vcN9gTwTpIC6MdfOvM 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 siFfj9jGjk/QAMdv2ifp75ROqs+XeOaP2zbSz6Zqhe/WZMpv6jth7/UzFq/p1XjvlTD8L0cVRc+9iIZvzKg9L4pLG49bmSYvl8uTL65sPu7kB8+P6th/j3ZbOe+FBLHvvLqXr8GNJG+zzMCP9l+CL5Gthk/ppoFPTee5D6vqUW9SUzTPju0BT7KWGe/WpSEvlvrqL4MRKI+7jgovgYWR78V9VI+nngAP9cjGz99RA4+nyU+Pmdt2D7zqaQ+VKdkvZG2VD1xMwo9oPMyv7g6Ez9r560/udd/Ptquc7/CRzY/iIJLP5xQxb0fipu/nTCEv0fiIr9Pijm+kf9RvqiPmb+mogK/Ptr6vfDF/742LEk/yHhoPVWZrj4AsAq+YrB4vg==", "training_traits": {"structure_gen": "Random", "n_layers": 7, "max_nodes": 11, "activation_func": "LeakyReLU", "epoch_num": 4}, "cM lasses_name": ["Cryptoadz", "Cryptopunks", "Moonbirds", "Nouns"]},m=25,b=50,y=59+11/12,w=59+11.5/12,v=60;function z(e,t){const n=Math.log(1-t)/Math.log(1-e);return e=>1-Math.pow(1-e,n)}class V{constructor(e,t,n){const{model:r,inputDim:i}=j(t,n);this.model=r,this.inputDim=i,this.iteration=0,this.stage=0;const o=new Date(parseInt(e.birthYear),0,1).getTime(),a=new Date(parseInt(e.birthYear)+1,0,1).getTime();this.birthDate=new Date(Math.floor((o+a)/2));const l=zr.filter((t=>t[0]==e.lifeCycle))[0][2];this.growSpeed=365/M l,this.cycleLength=60*l*24*3600*1e3,this.growthFunc=z(.4,.8)}updateAge(e){const t=(e.getTime()-this.birthDate.getTime())/31536e6*this.growSpeed;this.iteration=Math.floor(t/60);const n=t-60*this.iteration;let r;this.age=n;let i,o=0;if(n<25){let e=map(n,0,25,0,1);o=this.growthFunc(e),r=(25-n)/60,this.stage=1,this.stageRatio=map(n,0,25,0,1)}else n<50?(o=1,r=(50-n)/60,this.stage=2,this.stageRatio=map(n,25,50,0,1)):n<y?(o=map(n,50,y,1,0),r=(y-n)/60,this.stage=3,this.stageRatio=map(n,50,y,0,1)):n<w?(o=0,r=(w-n)/60,this.sM tage=4,this.stageRatio=map(n,y,w,0,1)):n<60&&(o=0,r=(60-n)/60,this.stage=5,this.stageRatio=map(n,w,60,0,1));n<50?i=map(n,0,50,0,780/880):n<w?i=map(n,50,w,780/880,800/880):n<60&&(i=map(n,w,60,800/880,1)),this.nextStateTimestamp=Math.round(e.getTime()+this.cycleLength*r),this.statePercentage=round(100*i);let a=(25-n)/60;a<0&&(a+=1),this.nextStableTimestamp=Math.round(e.getTime()+this.cycleLength*a),this.growth=o,this.model.updateNeurons(o,this.iteration)}getBrainStatus(){return{totalNeurons:this.model.getTotalNeuronsM (),neuronsLife:this.model.getNeuronsLife(),stage:this.stage,inputDim:this.inputDim,stageRatio:this.stageRatio,age:this.age,growth:this.growth,nextStateTimestamp:this.nextStateTimestamp,nextStableTimestamp:this.nextStableTimestamp,rebirthCount:max(this.iteration,0),statePercentage:this.statePercentage}}classifyImage(e){const t=new G(e,1,e.length);return this.model.forward(t).mat[0]}}class M{constructor(e,t,n,r,i){this.p=e,this.v=t,this.size=n,this.shape=i,this.col=r}getRadius(){return 1==Oe?1*this.size/2:2==Oe?7*thiM s.size/16:3==Oe||4==Oe?4*this.size/7:0}update(){this.p.add(this.v)}draw(e,t,n,r){const i=this.p.x*r,o=this.p.y*r,a=this.size*r,{col:l,shape:s}=this;let h,c;1==n?h=c=l:2==n?(h=dr(t,1),c=l):(h=dr(t,0),c=dr(l,1));e.stroke(dr(c,map(1,0,1,.25,1))),e.fill(dr(h,map(1,0,1,.15,1))),3==n&&e.fill(dr(h,0)),1==s?e.ellipse(i,o,a,a):2==s?e.rect(i,o,7*a/8,7*a/8):3==s&&(e.beginShape(),e.vertex(i-4*a/7,o),e.vertex(i,o-4*a/7),e.vertex(i+4*a/7,o),e.vertex(i,o+4*a/7),e.endShape(CLOSE))}}class E{constructor(e,t,n,r,i,o,a){this.center=e,M this.len=t,this.angle=n,this.v=r,this.angV=i,this.c1=o,this.c2=a}getEndpoints(){const e=createVector(this.len/2*cos(this.angle),this.len/2*sin(this.angle));return[Vector.add(this.center,e),Vector.sub(this.center,e)]}update(){this.center.add(this.v),this.angle+=this.angV}draw(e,t){const[n,r]=this.getEndpoints(),i=n.x*t,o=n.y*t,a=r.x*t,l=r.y*t,s=this.c1,h=this.c2;var c=e.drawingContext.createLinearGradient(i,o,a,l);c.addColorStop(0,s),c.addColorStop(1,h),e.drawingContext.strokeStyle=c,e.drawingContext.globalAlpha=1,eM .line(i,o,a,l),e.drawingContext.globalAlpha=1}}function S(e,t){const n=random(TAU),r=random(e,t);return createVector(r*cos(n),r*sin(n))}class R{constructor(e,t,n,r,i){this.wall=n,this.maxR=i;const o=t.length;this.nodes=[];for(let a=0;a<o;++a){const o=[],l=.25*t[a];for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),l=S(.02*i,.05*i),s=random(10,25)*i;o.push(new M(t,l,s,e[a],r))}this.nodes.push(o)}const a=A(e);a.unshift(e[0]),a.push(e[e.length-1]),this.lines=[];for(let e=0;e<=M o;++e){const r=[],l=(0==e?1:t[e-1])*(e==o?1:t[e])*1.5;for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),o=random(5*i,10*i),l=random(TAU),s=S(.02*i,.05*i),h=random(2e-4,.001);r.push(new E(t,o,l,s,h,a[e],a[e+1]))}this.lines.push(r)}}reflectNode(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,{p:o,v:a}=e,l=e.getRadius();(o.x-l<t&&a.x<0||o.x+l>r&&a.x>0)&&(a.x=-a.x),(o.y-l<n&&a.y<0||o.y+l>i&&a.y>0)&&(a.y=-a.y)}reflectLine(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wM all,[o,a]=e.getEndpoints(),l=e.v;(min(o.x,a.x)<t&&l.x<0||max(o.x,a.x)>r&&l.x>0)&&(l.x=-l.x),(min(o.y,a.y)<n&&l.y<0||max(o.y,a.y)>i&&l.y>0)&&(l.y=-l.y)}update(){for(const e of this.lines)for(const t of e)t.update(),this.reflectLine(t);for(const e of this.nodes)for(const t of e)t.update(),this.reflectNode(t)}draw(e,t,n,r,i){const o=i/this.maxR;for(const t of this.lines){const n=t.length*r;for(let r=0;r<n;++r)t[r].draw(e,o)}for(const i of this.nodes){const a=i.length*r;for(let r=0;r<a;++r)i[r].draw(e,t,n,o)}}}functionM I(e,t){re(e),e.fill(0),e.rect(0,0,500,500),ie(e),e.noStroke(),e.fill(dr(cr("#000000"),.5)),e.push(),e.translate(250,250),e.scale(t),e.translate(-250,-250),e.beginShape(),e.vertex(235.2,24.9),e.bezierVertex(215,24.6,185,11.4,164.8,11),e.bezierVertex(147.2,10.7,129.3,10.4,112.2,14.7),e.bezierVertex(95.1,19,78.5,28.5,69.6,43.8),e.bezierVertex(57.699,64.199,61.599,90.199,70.199,112.2),e.bezierVertex(78.799,134.2,91.6,154.6,97.199,177.5),e.bezierVertex(102.499,199.2,100.899,222.5,92.799,243.2),e.bezierVertex(83,268,64.M 6,288.3,48.9,310),e.bezierVertex(33.2,331.7,24.5,337.5,26.599,364.1),e.bezierVertex(28.2,384.1,61.399,404.2,75.7,418.3),e.bezierVertex(90,432.4,73.7,488.2,91.9,496.7),e.bezierVertex(124.2,511.6,159,472.5,194.3,468.1),e.bezierVertex(211.6,465.9,267.4,501.5,283.9,495.9),e.bezierVertex(340.7,476.7,298.599,428.9,355.4,409.7),e.bezierVertex(370.799,404.5,454.5,407.6,464.4,394.8),e.bezierVertex(478.599,376.3,474.7,349.3,464.299,328.4),e.bezierVertex(453.9,307.5,438.099,289.5,428.699,268.2),e.bezierVertex(412,230,419,182.M 6,446.1,150.9),e.bezierVertex(449.7,146.7,453.6,142.7,455.8,137.6),e.bezierVertex(459.4,129.299,457.5,119.6,454.8,111),e.bezierVertex(443.2,73.4,417.3,40.4,383.6,20.299),e.bezierVertex(358.1,5,343.2,-.4,313.5,0),e.bezierVertex(287.5,.4,261.6,25.4,235.2,24.9),e.endShape(),e.pop()}function C(e,t,n,r,i,o){let a,l,s;re(t),t.fill(0),t.rect(0,0,500,500),ie(t),t.noStroke(),t.fill(dr(n,.5)),1==i?(l=0,s=25,a=map(o,0,25,500,0)):a=0,t.rect(0,a,500,500),e.noStroke(),e.fill(r),e.rect(0,0,500,500),e.beginShape(),e.vertex(435.2,3M 73.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierM Vertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12M .1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,1M 95.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),e.fill(n),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1M ,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVerM tex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezM ierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),re(e),e.fill(M r),e.beginShape(),e.vertex(184.3,473.2),e.bezierVertex(164,473.2,144.7,462.099,134,444.3),e.bezierVertex(131.7,440.5,129.1,438.5,125,437.1),e.bezierVertex(97.3,428.1,80.5,400.6,85.2,371.8),e.bezierVertex(86.3,365.1,85.8,364.1,79.9,361.2),e.bezierVertex(57.2,349.8,46.2,323.3,54.3,299.7),e.bezierVertex(54.7,298.599,55.1,297.7,55.5,296.9),e.bezierVertex(55.6,296.599,55.8,296.4,55.9,296.099),e.vertex(57.9,291.499),e.vertex(62.5,293.599),e.bezierVertex(64.9,294.7,67.3,295.799,69.5,296.9),e.bezierVertex(74.5,299.299,79.1M ,301.599,83.9,303.099),e.bezierVertex(89.8,304.9,96.5,305.499,102.7,305.9),e.bezierVertex(102.8,305.9,102.9,305.9,103,305.9),e.bezierVertex(106.6,305.9,108.9,302.799,109,299.799),e.bezierVertex(109.1,296.199,106.6,293.4,102.7,292.799),e.bezierVertex(101.3,292.599,99.9,292.4,98.4,292.299),e.bezierVertex(94.3,291.799,90.1,291.299,86,289.9),e.bezierVertex(68.9,284,56.5,270.2,52.7,252.799),e.bezierVertex(48.9,235.499,54.5,217.7,67.6,205.299),e.bezierVertex(71.9,201.299,72.7,198.1,70.8,192.399),e.bezierVertex(64.2,172.2M ,68.8,153.99,84.2,139.599),e.bezierVertex(94.2,130.199,105.5,125.399,117.8,125.399),e.bezierVertex(124.3,125.399,131.1,126.799,137.8,129.599),e.bezierVertex(157,137.399,167.9,152.799,169.4,173.99),e.vertex(169.4,174.399),e.bezierVertex(169.5,175.899,169.6,177.2,169.9,178.299),e.bezierVertex(170.7,181.2,173.2,183.2,176.1,183.2),e.bezierVertex(176.299,183.2,176.5,183.2,176.7,183.2),e.bezierVertex(180.1,182.899,182.6,180.299,182.7,177),e.bezierVertex(183.1,162,178.299,148.2,168.399,136.1),e.bezierVertex(158.2,123.5,14M 4.899,115.8,128.799,113.199),e.bezierVertex(123.499,112.299,120.399,109.799,118.899,104.99),e.bezierVertex(113.899,89.699,120.699,72.299,134.899,64.499),e.bezierVertex(139.99,61.699,145.799,60.199,151.7,60.199),e.bezierVertex(162.2,60.199,171.899,64.799,178.1,72.699),e.bezierVertex(179.6,74.6,180.799,76.6,181.9,78.499),e.vertex(182.2,79.099),e.bezierVertex(183.2,80.699,185.2,83.299,188.4,83.299),e.bezierVertex(189.5,83.299,190.6,82.99,191.7,82.399),e.bezierVertex(195.1,80.599,196,76.99,194,72.799),e.bezierVertex(19M 0.1,64.799,184.1,58.499,175.6,53.299),e.bezierVertex(174.6,52.699,173.7,52.099,172.5,51.499),e.vertex(170.5,50.299),e.vertex(163,45.899),e.vertex(170.5,41.599),e.bezierVertex(182,34.99,193.1,30.799,204.4,28.599),e.bezierVertex(208.6,27.799,212.9,27.399,217.2,27.399),e.bezierVertex(217.6,27.399,217.9,27.399,218.3,27.399),e.bezierVertex(231.4,27.599,242.7,38.199,243,50.599),e.bezierVertex(243.4,64.899,243.3,78.99,243.2,93.799),e.bezierVertex(243.2,99.799,243.1,105.899,243.1,112.099),e.vertex(243.1,119.199),e.vertex(2M 36.4,116.799),e.bezierVertex(235.7,116.499,235,116.299,234.4,115.99),e.bezierVertex(233.4,115.599,232.6,115.299,232,115.199),e.bezierVertex(230.6,114.899,229.2,114.599,227.8,114.299),e.bezierVertex(223.8,113.499,220.1,112.699,216.4,112.499),e.vertex(216.2,112.499),e.bezierVertex(212.5,112.499,210.7,115.599,210.6,118.599),e.bezierVertex(210.4,122.399,212.7,125.099,216.4,125.399),e.bezierVertex(230.1,126.399,238.9,133.099,242.3,145.199),e.bezierVertex(243.2,148.399,243.2,151.599,243.2,154.499),e.vertex(243.2,155.099)M ,e.bezierVertex(243.2,254.199,243.2,330,243.2,400.599),e.bezierVertex(243.2,401.99,243.2,403.4,243.2,404.9),e.bezierVertex(243.3,411.099,243.3,417.599,242.3,423.9),e.bezierVertex(238.1,449.2,219.6,467.799,194,472.5),e.bezierVertex(190.9,472.9,187.6,473.2,184.3,473.2),e.endShape(),e.beginShape(),e.vertex(315.8,473.1),e.bezierVertex(309.3,473.1,302.8,472,296.5,469.9),e.bezierVertex(270.4,461,253.8,434.9,257.1,407.9),e.bezierVertex(260,384,273.8,366.8,297,358.3),e.bezierVertex(297.7,358.1,298.3,357.8,299,357.6),e.beziM erVertex(299.8,357.3,300.6,357.1,301.2,356.8),e.bezierVertex(304.3,355.4,306,351.8,304.9,348.7),e.bezierVertex(304,345.9,301.7,344.2,299,344.2),e.bezierVertex(298.6,344.2,298.1,344.2,297.6,344.3),e.bezierVertex(288.1,346.3,279,350.9,269.7,358.3),e.bezierVertex(268.9,358.9,268.1,359.6,267.2,360.4),e.vertex(265.5,361.8),e.vertex(258.5,367.6),e.vertex(257.4,358.6),e.bezierVertex(257.3,358,257.3,357.5,257.2,357.1),e.bezierVertex(257,356,256.9,354.9,256.9,353.7),e.bezierVertex(256.9,334.8,256.9,316,256.9,297.1),e.bezierM Vertex(256.9,260.3,256.9,222.3,256.8,185),e.bezierVertex(256.8,170.7,268.3,158.8,282.5,158.4),e.bezierVertex(284.8,158.3,286.7,157.6,287.9,156.2),e.bezierVertex(289.099,154.9,289.599,153.2,289.5,151.3),e.bezierVertex(289.3,147.5,286.7,145.1,282.7,145.1),e.bezierVertex(282.5,145.1,282.2,145.1,282,145.1),e.bezierVertex(278.8,145.3,275.5,146.1,272,146.9),e.bezierVertex(270.9,147.2,269.8,147.4,268.6,147.7),e.bezierVertex(267.9,147.9,267,148.2,265.8,148.7),e.bezierVertex(265.1,149,264.4,149.3,263.5,149.6),e.vertex(256.8M ,152),e.vertex(256.8,114.6),e.bezierVertex(256.8,95,256.8,75.4,256.8,55.9),e.bezierVertex(256.8,38,267.2,27.3,284.6,27.3),e.bezierVertex(285.3,27.3,285.9,27.3,286.6,27.3),e.bezierVertex(299,27.9,318.7,34.5,329.6,41.9),e.vertex(336.1,46.3),e.vertex(324.4,53.3),e.bezierVertex(316.2,58.2,310.2,64.6,306,72.9),e.bezierVertex(304.2,76.4,305.1,78.5,306.1,80),e.bezierVertex(307.4,81.9,309.4,83,311.6,83),e.bezierVertex(313.7,83,315.7,81.9,317.1,80.1),e.bezierVertex(317.4,79.7,317.8,79,318.1,78.4),e.bezierVertex(318.4,77.9,3M 18.7,77.3,319,76.8),e.bezierVertex(325.3,66.2,336.3,59.9,348.5,59.9),e.bezierVertex(353.2,59.9,357.8,60.8,362.1,62.7),e.bezierVertex(377.6,69.3,386,86.7,381.7,103.2),e.bezierVertex(380.7,107.1,378.5,111.8,371.1,113.1),e.bezierVertex(342.7,118.1,322.2,139.1,317.8,167.8),e.bezierVertex(317.4,170.3,317.3,173.2,317.4,176.5),e.bezierVertex(317.5,180,320.1,182.8,323.5,183),e.bezierVertex(323.6,183,323.8,183,323.9,183),e.bezierVertex(327.1,183,329.8,180.6,330.3,177.2),e.bezierVertex(330.6,175.7,330.7,174,330.9,172.3),e.beM zierVertex(331.1,169.8,331.4,167.3,332,164.7),e.bezierVertex(337.3,141.9,357.7,125.4,380.7,125.4),e.bezierVertex(382.5,125.4,384.3,125.5,386.1,125.7),e.bezierVertex(412.8,128.9,432.6,150.9,432,176.9),e.bezierVertex(431.9,182.3,430.9,187.7,429.1,192.7),e.bezierVertex(427.2,197.9,428,201,432.3,205),e.bezierVertex(446.8,218.7,451.8,236,446.6,255),e.bezierVertex(441.4,274,428.3,286.5,408.7,291.3),e.bezierVertex(406.1,291.9,403.6,292.1,401.1,292.3),e.bezierVertex(400,292.4,398.9,292.5,397.9,292.6),e.bezierVertex(393.6,2M 93.1,390.9,295.7,391,299.5),e.bezierVertex(391.1,303.4,394,305.8,398.5,305.8),e.bezierVertex(409.9,305.8,420.8,302.6,431.1,296.4),e.bezierVertex(431.8,296,432.5,295.5,433.2,295.1),e.bezierVertex(433.8,294.7,434.5,294.3,435.2,293.9),e.bezierVertex(436,293.4,436.6,293.2,437.2,293.1),e.bezierVertex(437.4,293,437.7,292.9,438.1,292.8),e.vertex(442.5,291.4),e.vertex(444.2,295.7),e.bezierVertex(450.9,312.4,449.5,328.4,440,343.4),e.bezierVertex(435.3,350.8,428.7,356.7,420.2,361.1),e.bezierVertex(414.3,364.1,413.7,365.2,414M .8,371.7),e.bezierVertex(419.5,400.2,403,427.6,375.6,436.9),e.bezierVertex(371,438.5,368.3,440.7,365.8,444.7),e.bezierVertex(355.2,462.5,336.4,473.1,315.8,473.1),e.bezierVertex(315.8,473.1,315.8,473.1,315.8,473.1),e.endShape(),ie(e),e.fill(n),e.beginShape(),e.vertex(120.2,279.9),e.bezierVertex(117.9,279.9,112.4,279.299,112.2,273.599),e.bezierVertex(112,267.7,117.4,266.7,119.7,266.599),e.bezierVertex(133.1,265.799,143.1,259.499,149.3,247.899),e.bezierVertex(149.6,247.299,150.1,246.399,150.3,245.399),e.bezierVertex(1M 50.6,244.299,150.5,243.299,150.5,242.7),e.bezierVertex(150.5,242.6,150.5,242.5,150.5,242.299),e.vertex(150.3,238.799),e.vertex(141.1,235.99),e.bezierVertex(114.6,227.799,95.6,202.499,95.9,175.799),e.bezierVertex(95.9,173.99,96.4,168.199,102.2,168.199),e.bezierVertex(102.6,168.199,103,168.199,103.4,168.299),e.bezierVertex(104.8,168.499,108.2,168.899,109.2,175.599),e.bezierVertex(109.3,176.599,109.5,177.599,109.6,178.499),e.bezierVertex(110.4,184.199,111.3,189.99,113.7,195.499),e.bezierVertex(121.9,213.99,139.5,225.4M 99,159.7,225.499),e.bezierVertex(172.1,225.499,184.1,220.899,193.5,212.599),e.bezierVertex(194,212.199,194.4,211.799,194.8,211.399),e.bezierVertex(195.1,211.099,195.5,210.799,195.8,210.399),e.bezierVertex(197.4,208.99,199.2,208.2,200.9,208.2),e.bezierVertex(202.5,208.2,204,208.899,205.3,210.1),e.bezierVertex(208,212.9,207.9,216.9,205,219.9),e.bezierVertex(196.5,228.6,186.3,234.3,174.7,236.8),e.bezierVertex(168.799,238.1,165.6,241,163.899,246.7),e.bezierVertex(158.3,265.9,139.9,279.7,120.2,279.9),e.vertex(120.2,279.M 9),e.endShape(),e.beginShape(),e.vertex(187.2,427.5),e.bezierVertex(183.799,427.5,181.299,425.3,180.799,422),e.bezierVertex(180.6,420.8,180.499,419.5,180.399,418.1),e.bezierVertex(180.299,417,180.2,415.8,180.099,414.7),e.bezierVertex(177.199,390.5,156.699,371.3,132.399,370.2),e.bezierVertex(131.99,370.2,131.499,370.2,131.099,370.2),e.bezierVertex(130.699,370.2,130.299,370.2,129.799,370.2),e.bezierVertex(125.99,369.9,123.199,367.2,123.099,363.6),e.bezierVertex(122.99,360.2,125.799,357.3,129.599,356.9),e.bezierVertexM (130.499,356.8,131.499,356.8,132.599,356.7),e.bezierVertex(133.199,356.7,133.799,356.7,134.399,356.6),e.vertex(138.299,356.4),e.vertex(139.1,352.6),e.bezierVertex(139.5,350.7,139.799,348.9,140.2,347),e.bezierVertex(140.899,343.4,141.5,340,142.399,336.8),e.bezierVertex(150.099,310.7,174.399,292,201.399,291.3),e.vertex(201.599,291.3),e.bezierVertex(203.699,291.3,206.299,292,208.299,293.2),e.bezierVertex(210.499,294.5,210.699,297.5,209.99,299.8),e.bezierVertex(209.499,301.5,208.199,303.9,203.299,304.7),e.bezierVertex(M 202.199,304.9,200.99,305,199.799,305.2),e.bezierVertex(194.499,305.9,188.99,306.599,183.799,308.9),e.bezierVertex(165.499,316.799,155.199,331.299,152.99,352),e.bezierVertex(152.399,357.8,154.499,361.7,159.699,364.5),e.bezierVertex(178.199,374.4,189.399,390,193.099,410.9),e.bezierVertex(193.699,414.299,193.899,418,193.599,422),e.bezierVertex(193.399,425.2,190.899,427.5,187.399,427.5),e.vertex(187.2,427.5),e.endShape(),e.beginShape(),e.vertex(364.3,281.1),e.bezierVertex(346.3,280.6,332.9,272.8,323.5,257),e.bezierVertM ex(321.6,253.9,320.4,250.2,319.2,246.7),e.bezierVertex(317.7,242.2,315,239.799,310.5,238.799),e.bezierVertex(298.5,236.299,288,230.7,279.4,222.1),e.bezierVertex(276.7,219.4,274.9,215.299,278,211.9),e.bezierVertex(279.4,210.3,281,209.6,282.6,209.6),e.bezierVertex(284.4,209.6,286.4,210.6,288.3,212.5),e.bezierVertex(297.8,221.8,310.4,226.9,323.9,226.9),e.bezierVertex(340.2,226.9,355.1,219.3,364.8,206.2),e.bezierVertex(371,197.8,374.2,188.5,374.5,178.5),e.vertex(374.5,177.9),e.bezierVertex(374.5,177,374.5,176.1,374.7,1M 75.4),e.bezierVertex(375.3,171.8,377.9,169.5,381.3,169.5),e.bezierVertex(381.4,169.5,381.5,169.5,381.7,169.5),e.bezierVertex(385.4,169.7,388,172.4,388,176.1),e.bezierVertex(388.1,190.7,383.4,204,374.2,215.8),e.bezierVertex(365.8,226.5,354.7,233.9,341.2,237.9),e.bezierVertex(340,238.3,338.7,238.6,337.3,239.1),e.bezierVertex(335.9,239.6,335.1,240.4,334.7,240.9),e.bezierVertex(334.599,241,334.5,241.1,334.4,241.2),e.vertex(331.799,243.6),e.vertex(333.199,246.8),e.bezierVertex(338.199,258,346.799,264.9,358.699,267.3),e.M bezierVertex(360.199,267.6,361.599,267.7,362.99,267.9),e.bezierVertex(363.599,268,364.299,268,364.899,268.1),e.bezierVertex(369.099,268.6,371.799,271.4,371.499,275),e.bezierVertex(371.199,278.6,368.299,281.2,364.399,281.2),e.vertex(364.3,281.1),e.endShape(),e.beginShape(),e.vertex(323.9,437),e.bezierVertex(323.7,437,323.5,437,323.299,437),e.bezierVertex(319.599,436.7,317.299,434.1,317.4,430.2),e.bezierVertex(317.9,406.099,328.299,388,349.5,375),e.bezierVertex(350.7,374.2,352,373.5,353.4,372.8),e.bezierVertex(354.09M 9,372.4,354.7,372.1,355.299,371.7),e.vertex(357.499,370.5),e.vertex(357.799,368),e.bezierVertex(360.4,346.6,345.199,323.7,323.9,317),e.bezierVertex(319.099,315.5,314.099,314.9,309.299,314.4),e.vertex(308.199,314.299),e.bezierVertex(305.99,314.099,300.799,312.9,300.899,307.299),e.bezierVertex(300.99,303.499,303.899,300.9,308.099,300.9),e.vertex(308.299,300.9),e.bezierVertex(327.099,301.299,343.099,308.7,355.699,322.9),e.bezierVertex(364.299,332.5,369.399,344.099,370.99,357.299),e.bezierVertex(371.099,358.4,371.299,3M 59.4,371.499,360.499),e.bezierVertex(371.599,360.99,371.699,361.499,371.799,361.99),e.vertex(372.499,365.899),e.vertex(377.899,366.199),e.bezierVertex(378.799,366.299,379.699,366.299,380.599,366.399),e.bezierVertex(385.099,366.699,387.899,369.399,387.799,373.299),e.bezierVertex(387.699,377.099,384.99,379.599,380.799,379.799),e.bezierVertex(369.799,380.199,359.99,383.299,351.899,389.299),e.bezierVertex(338.799,398.799,331.699,411.699,330.699,427.499),e.vertex(330.699,428.299),e.bezierVertex(330.599,429.199,330.599,4M 30.099,330.499,430.799),e.bezierVertex(330,434.7,327.5,437,323.9,437),e.endShape()}function T(e){return e[0].map(((t,n)=>e.map((e=>e[n]))))}function A(e){return e.map((e=>Array.isArray(e)?A(e):e))}function D(e,t){return floor(random(e,t))}function k(e){let t=0;for(const n of e)t+=n[1];let n=random(t),r=0;for(const t of e)if(r+=t[1],n<r)return t[0];return null}function L(e){for(let t=1;t<e.length;++t){let n=D(0,t),r=e[t];e[t]=e[n],e[n]=r}}function P(e){return null==e||""===e}function O(e){return new Promise((t=>setTM imeout(t,e)))}function F(e,t,n){let r=0;for(let i=1;i<=1e3;++i)for(let o=1;o<=1e3;++o)if(e*o%(t*i)==0){let e=1*i/o;abs(e-n)<abs(r-n)&&(r=e)}return r}function N(){let e=60*(new Date).getTimezoneOffset()*1e3;return new Date(Date.now()-e).toISOString().slice(0,-1)}function B(e,t,n){let r;if(push(),textSize(e),textWidth(t)<=n)r=t;else for(let e=0;e<t.length;++e){const i=t.slice(0,e+1)+"...";if(textWidth(i)>n){r=i;break}}return pop(),r}function Y(e){var t=e%10,n=e%100;return 1==t&&11!=n?e+"st":2==t&&12!=n?e+"nd":3==t&&1M 3!=n?e+"rd":e+"th"}class G{constructor(e,t,n){this.n=t,this.m=n,this.mat=[];let r=0;for(let t=0;t<this.n;++t){this.mat.push([]);for(let n=0;n<this.m;++n)this.mat[t].push(r<e.length?e[r]:0),r+=1}return this}copy(){return new G(this.mat.flat(),this.n,this.m)}}class H{static __linear=e=>e;static __relu=e=>Math.max(e,0);static __leaky_relu=e=>e>0?e:.2*e;static __sigmoid=e=>1/(1+Math.exp(-e));static __tanh=e=>Math.tanh(e);static __apply_unary_op(e,t){const n=e.copy();for(let e=0;e<n.n;++e)for(let r=0;r<n.m;++r)n.mat[e][M r]=t(n.mat[e][r]);return n}static linear=e=>H.__apply_unary_op(e,H.__linear);static relu=e=>H.__apply_unary_op(e,H.__relu);static leaky_relu=e=>H.__apply_unary_op(e,H.__leaky_relu);static sigmoid=e=>H.__apply_unary_op(e,H.__sigmoid);static tanh=e=>H.__apply_unary_op(e,H.__tanh);static __add=(e,t)=>e+t;static __mul=(e,t)=>e*t;static __apply_binary_op=(e,t,n)=>{"object"!=typeof t&&(t=new G([t],1,1));const r=e.copy();for(let e=0;e<r.n;++e)for(let i=0;i<r.m;++i)r.mat[e][i]=n(r.mat[e][i],t.mat[e%t.n][i%t.m]);return r};sM tatic mul=(e,t)=>H.__apply_binary_op(e,t,H.__mul);static add=(e,t)=>H.__apply_binary_op(e,t,H.__add);static matMul(e,t){const n=new G([],e.n,t.m);for(let r=0;r<n.n;++r)for(let i=0;i<n.m;++i)for(let o=0;o<e.m;++o)n.mat[r][i]+=e.mat[r][o]*t.mat[o][i];return n}static softmax(e){const t=H.__apply_unary_op(e,(e=>Math.exp(e))),n=t.mat.flat().reduce(((e,t)=>e+t));for(let r=0;r<e.n;++r)for(let i=0;i<e.m;++i)t.mat[r][i]/=n;return t}}class ${constructor(e,t){this.scale=e,this.offset=t}forward(e){return H.add(H.mul(e,this.scaM le),this.offset)}}class X{constructor(){}forward(e){return e.map((e=>e.flat()))}}class W{constructor(e,t,n,r){this.out_dim=e,this.activation=t,this.w=n,this.b=r}forward(e){const t=H.add(H.matMul(e,this.w),this.b);return null==this.activation?t:this.activation(t)}}class U{constructor(e,t,n){this.preprocessLayers=e,this.hiddenLayers=t,this.outputLayer=n,this.totalNeurons=this.hiddenLayers.map((e=>e.out_dim)),this.currentOrders=[],this.currentIteration=null}updateNeurons(e,t){if(t!=this.currentIteration){this.currentOM rders=[];for(let e=0;e<this.totalNeurons.length;++e){randomSeed(100*(t+1)+e);const n=[];for(let t=0;t<this.totalNeurons[e];++t)n.push(t);L(n),this.currentOrders.push(n)}this.currentIteration=t}const n=A(this.totalNeurons),r=n.reduce(((e,t)=>e+t))*(1-e);for(let e=0;e<r;++e){const t=n.map(((e,t)=>(e-1)/this.totalNeurons[t]));n[t.map(((e,t)=>[e,t])).reduce(((e,t)=>t[0]>e[0]?t:e))[1]]-=Math.min(r-e,1)}this.neuronsLife=[];for(let e=0;e<n.length;++e){const t=this.currentOrders[e],r=Array(this.totalNeurons[e]).fill(0);forM (let i=0;i<n[e];++i)r[t[i]]=Math.min(n[e]-i,1);this.neuronsLife.push(r)}}getTotalNeurons(){return A(this.totalNeurons)}getNeuronsLife(){return A(this.neuronsLife)}forward(e){for(const t of this.preprocessLayers)e=t.forward(e);for(const[t,n]of this.hiddenLayers.entries()){e=n.forward(e);const r=new G(this.neuronsLife[t],1,e.m);e=H.mul(e,r)}return e=this.outputLayer.forward(e),H.softmax(e)}}function q(e){switch(e){case"relu":return H.relu;case"sigmoid":return H.sigmoid;case"tanh":return H.tanh;case"leaky_relu":returnM H.leaky_relu;default:return H.linear}}function j(e,t){const n=[],r=[],i=Z(t);let o=null,a=0,l=[];for(const t of e.config.layers)if("InputLayer"==t.class_name)o=t.config.batch_input_shape.slice(1),l=o;else if("Rescaling"==t.class_name)n.push(new $(t.config.scale,t.config.offset));else if("Flatten"==t.class_name)o=[o.reduce(((e,t)=>e*t))];else if("Dense"==t.class_name){const e=[t.config.units],n=o[0]*e[0],l=e[0],s=i.subarray(a,a+n);a+=n;const h=i.subarray(a,a+l);a+=l;const c=new G(s,o[0],e[0]),u=new G(h,1,e[0]),f=q(M t.config.activation);r.push(new W(e[0],f,c,u)),o=e}const s=r.pop();return{model:new U(n,r,s),inputDim:l}}function Z(e){const t=window.atob(e),n=t.length/Float32Array.BYTES_PER_ELEMENT,r=new DataView(new ArrayBuffer(Float32Array.BYTES_PER_ELEMENT)),i=new Float32Array(n);let o=0;for(let e=0;e<n;e++){o=4*e;for(let e=0;e<4;++e)r.setUint8(e,t.charCodeAt(o+e));i[e]=r.getFloat32(0,!0)}return i}class K{constructor(e){this.elt=e,this._events={},this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight}position(){if(M 0===arguments.length)return{x:this.elt.offsetLeft,y:this.elt.offsetTop};var e="absolute";return"static"!==arguments[2]&&"fixed"!==arguments[2]&&"relative"!==arguments[2]&&"sticky"!==arguments[2]&&"initial"!==arguments[2]&&"inherit"!==arguments[2]||(e=arguments[2]),this.elt.style.position=e,this.elt.style.left=arguments[0]+"px",this.elt.style.top=arguments[1]+"px",this.x=arguments[0],this.y=arguments[1],this}show(){return this.elt.style.display="block",this}hide(){return this.elt.style.display="none",this}size(e,t){M if(0===arguments.length)return{width:this.elt.offsetWidth,height:this.elt.offsetHeight};var n=e,r=t;if(n!==te||r!==te){if(n===te?n=t*this.width/this.height:r===te&&(r=e*this.height/this.width),this.elt instanceof HTMLCanvasElement){var i,o={},a=this.elt.getContext("2d");for(i in a)o[i]=a[i];for(i in this.elt.setAttribute("width",n*this._pInst._pixelDensity),this.elt.setAttribute("height",r*this._pInst._pixelDensity),this.elt.style.width=n+"px",this.elt.style.height=r+"px",this._pInst.scale(this._pInst._pixelDensityM ,this._pInst._pixelDensity),o)this.elt.getContext("2d")[i]=o[i]}else this.elt.style.width=n+"px",this.elt.style.height=r+"px",this.elt.width=n,this.elt.height=r;this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight,this._pInst&&this._pInst._curElement&&this._pInst._curElement.elt===this.elt&&(this._pInst._setProperty("width",this.elt.offsetWidth),this._pInst._setProperty("height",this.elt.offsetHeight))}return this}style(e,t){if(t instanceof Color&&(t="rgba("+t.levels[0]+","+t.levels[1]+","+t.levels[2]+M ","+t.levels[3]/255+")"),void 0===t){if(-1===e.indexOf(":"))return window.getComputedStyle(this.elt).getPropertyValue(e);for(var n=e.split(";"),r=0;r<n.length;r++){var i=n[r].split(":");i[0]&&i[1]&&(this.elt.style[i[0].trim()]=i[1].trim())}}else if(this.elt.style[e]=t,"width"===e||"height"===e||"left"===e||"top"===e){var o=window.getComputedStyle(this.elt).getPropertyValue(e).replace(/[^\d.]/g,"");this[e]=Math.round(parseFloat(o,10))}return this}value(){return arguments.length>0?(this.elt.value=arguments[0],this):"M range"===this.elt.type?parseFloat(this.elt.value):this.elt.value}mouseClicked(e){return this._adjustListener("click",e,this),this}isFocused(){return document.activeElement===this.elt}_adjustListener(e,t,n){return!1===t?this._detachListener(e,n):this._attachListener(e,t,n),this}_attachListener(e,t,n){n._events[e]&&this._detachListener(e,n);var r=t.bind(n);n.elt.addEventListener(e,r,!1),n._events[e]=r}_detachListener(e,t){var n=t._events[e];t.elt.removeEventListener(e,n,!1),t._events[e]=null}}function J(e,t){var n=doM cument.createElement("button");return n.innerHTML=e,t&&(n.value=t),ee(n)}function Q(e){var t=arguments.length>1&&void 0!==arguments[1]&&arguments[1],n=function(t){var n=!0,r=!1,i=void 0;try{for(var o,a=t.target.files[Symbol.iterator]();!(n=(o=a.next()).done);n=!0){var l=o.value;File._load(l,e)}}catch(e){r=!0,i=e}finally{try{n||null==a.return||a.return()}finally{if(r)throw i}}};if(window.File&&window.FileReader&&window.FileList&&window.Blob){var r=document.createElement("input");return r.setAttribute("type","file"),M t&&r.setAttribute("multiple",!0),r.addEventListener("change",n,!1),ee(r)}}function ee(e){return document.body.appendChild(e),new K(e)}createImg=function(){var e,t=document.createElement("img"),n=arguments;return n.length>1&&"string"==typeof n[1]&&(t.alt=n[1]),n.length>2&&"string"==typeof n[2]&&(t.crossOrigin=n[2]),t.src=n[0],e=ee(t,this),t.addEventListener("load",(function(){e.width=t.offsetWidth||t.width,e.height=t.offsetHeight||t.height;var r=n[n.length-1];"function"==typeof r&&r(e)})),e},createInput=function(){vM ar e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:"",t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:"text",n=document.createElement("input");return n.setAttribute("value",e),n.setAttribute("type",t),ee(n,this)};const te="auto";function ne(e){re(e);const t=e._rectMode;e.rectMode(CORNER),e.rect(0,0,e.width,e.height),e.rectMode(t),ie(e)}function re(e){e.push(),e.fill(255,255,255,255),e.blendMode(REMOVE)}function ie(e){e.blendMode(BLEND),e.pop()}File=function(e,t){this.file=e,this._pInst=t;var n=e.tM ype.split("/");this.type=n[0],this.subtype=n[1],this.name=e.name,this.size=e.size,this.data=void 0},File._createLoader=function(e,t){var n=new FileReader;return n.onload=function(n){var r=new File(e);if("application/json"===r.file.type)r.data=JSON.parse(n.target.result);else if("text/xml"===r.file.type){var i=(new DOMParser).parseFromString(n.target.result,"text/xml");r.data=new XML(i.documentElement)}else r.data=n.target.result;t(r)},n},File._load=function(e,t){if(/^text\//.test(e.type)||"application/json"===e.typM e)File._createLoader(e,t).readAsText(e);else if(/^(video|audio)\//.test(e.type)){var n=new File(e);n.data=URL.createObjectURL(e),t(n)}else File._createLoader(e,t).readAsDataURL(e)},XML=function(e){if(e)this.DOM=e;else{var t=document.implementation.createDocument(null,"doc");this.DOM=t.createElement("root")}},document.addEventListener("DOMContentLoaded",(function(){addEventListener("mousemove",(e=>{window.mouseX=e.pageX,window.mouseY=e.pageY}))})),new e("global");const oe="203";let ae,le,se,he,ce,ue,fe,de,xe,ge,pe,mM e,be,ye,we,ve,ze,Ve,_e,Me,Ee,Se,Re,Ie,Ce,Te,Ae,De,ke,Le,Pe,Oe,Fe,Ne,Be,Ye,Ge,He,$e,Xe,We,Ue,qe,je,Ze,Ke,Je,Qe,et,tt,nt,rt,it,ot,at,lt,st,ht,ct,ut,ft,dt,xt,gt,pt,mt,bt,yt,wt,vt,zt,Vt,_t,Mt,Et,St,Rt,It,Ct,Tt,At=!1,Dt=!1,kt=!0,Lt=!1,Pt=!1;const Ot=[" ","Growing","Stable","Decaying","Dead","Rebirth"];let Ft,Nt,Bt,Yt,Gt,Ht,$t,Xt,Wt,Ut,qt,jt,Zt,Kt,Jt,Qt,en,tn,nn,rn,on,an,ln,sn,hn=0,cn=0,un=0,fn=!1,dn=!0,xn=!0,gn=null,pn=null,mn=null,bn=!1,yn=!1,wn=null,vn=null,zn=!1;async function setup(){let e=windowWidth,t=windowHeightM ;createCanvas(e,t),et=createGraphics(e,t),Xe=createGraphics(e,t),$e=createGraphics(e,t),We=createGraphics(e,t),Ue=createGraphics(e,t),qe=createGraphics(e,t),Qe=createGraphics(e,t),je=createGraphics(e,t),Ze=createGraphics(e,t),Ke=createGraphics(e,t),Je=createGraphics(e,t),tt=createGraphics(500,500),nt=createGraphics(500,500),rt=createGraphics(500,500),_n(),Mn(),Sn(),await En(),Gn(),Rn(),bn=!0}function _n(){Et=parseInt(oe),randomSeed(Et),noiseSeed(Et)}function Mn(){Wt=Ir(p.training_traits),Cr(Wt)}async function En(){M let e;Jt=r(),Qt=o(),[Xt,e]=await Promise.all([s(Jt),h(Qt)]),Ut=new V(Wt.visual,e.layers_config,e.weight_b64),Ut.updateAge(new Date),_n(),Wt.training=e.training_traits,Ht=e.model_name,$t=e.classes_name}function Sn(){le=min(width,height)/1024,ut=Rr.findIndex((e=>e[0]===Wt.visual.colorPalette)),ft=[["#ffffff","#231f20","#231f20"],["#231f20","#ffffff","#ffffff"],["#104da8","#ffffff","#ffffff"],["#722F1F","#FCE1B2","#FCE1B2"],["#e88120","#f9f2e5","#f9f2e5"],["#f6b941","#2E2E2E","#2E2E2E"],["#45daaa","#012221","#012221"]M ,["#F1F1F1","#328DFE","#328DFE"],["#111822","#D3EB8D","#D3EB8D"],["#713FF9","#D6D5E6","#D6D5E6"],["#FBDA9D","#795106","#795106"],["#8f5b62","#ead0d0","#ead0d0"],["#eae4cb","#508cac","#508cac"],["#ffc6cc","#cc313d","#cc313d"],["#60A900","#E0FE00","#E0FE00"],["#507DBE","#D0D1D3","#D0D1D3"],["#305848","#E8F2EE","#E8F2EE"],["#2a2634","#5b6988","#cb78a2","#5b6988"],["#590e29","#fd5e53","#fd5e53","#ffe373"],["#0a141d","#57d4e4","#328195","#2A9ECF","#0ab6a8","#57d4e4"],["#3a2d28","#d5c2ac","#df6338","#3d9895","#d5c2ac"],[M "#030706","#77c4d9","#77c4d9","#77c4d9","#ffffff","#ffffff","#e72020","#e72020"],["#3a4664","#92f5ff","#f9ff94","#eaa0a2","#55dde0"],["#fbfaff","#f04bb1","#f04bb1","#fac373","#82cef0","#8b31ce"],["#000000","#ffffff","#ff0002","#f26522","#fdff00","#00ff03","#01fffe","#0000ff","#ff00ff"]];for(let e=0;e<ft.length;++e)for(let t=0;t<ft[e].length;++t)ft[e][t]=cr(ft[e][t]);pt=[],ct=ft[ut][0],st=ft[ut][1]}function Rn(){gn=document.querySelector("#upload"),pn=document.querySelector("#inputUpload"),gn.addEventListener("dblclM ick",(()=>{if(!Lt&&!yn)if(In(Ie)&&cn==Ve-1)pn.click();else{if(4!=Pe&&5!=Pe&&(In(Ie)||cn!=Ve-1))return;fn=!0,dn=!0,Bt=0,un=0}})),pn.addEventListener("click",(()=>{pn.value=null,gn.style.display="block"})),pn.addEventListener("change",(()=>{const[e]=pn.files;e?(se=null,gn.style.display="none",Tn(URL.createObjectURL(e)),mn=e):gn.style.display="block"}))}function In(e){for(let t=0;t<e.length;++t){let n=0;for(let r=0;r<e[t].length;++r)e[t][r]>0&&++n;if(0==n)return!1}return!0}function Cn(){null!=se&&(un=0,Pt=!0,he=0,ue=0M ,drewLineAnim=!0,ce=(ae/2+we/2)/le,loadImage(se.elt.src,(e=>{const[t,n,r]=Gt,i=createGraphics(t,n);i.image(e,0,0,t,n),i.loadPixels();const o=i.pixels.filter(((e,t)=>t%4!=3)),a=Ut.classifyImage(o);Zt=T([a,$t.map((e=>e.toUpperCase()))]).sort(((e,t)=>e[0]>t[0]?-1:1))})))}function Tn(e){se=createImg(e,""),se.hide(),Cn()}function An(){zn||(ce+=(width-ae-we)/tn/le),re(Xe),Xe.rect(ce*le,0,width,height),ie(Xe),un>=ge&&1==kt&&(kt=!1,un-=ge),kt&&(re($e),$e.strokeWeight(2*Fe),Jn(he,ze,ct,ct,$e),ie($e)),un>=ge&&0==kt&&(kt=!0,uM n-=ge,he+=1,he==en&&(++ue,he=0,ce=(ae/2+we/2)/le,1==ue&&(Pt=!1,Dn(),ye=millis())))}function Dn(){At=!0,pe=!1,me=!1,tryButton=br("Try Again",width/2-225*le,height/2+265*le,290*le,40*le,kn),closeResultButton=br("Close",width/2+75*le,height/2+265*le,150*le,40*le,Ln)}function kn(){At=!1,tryButton.hide(),closeResultButton.hide(),pn.click()}function Ln(){Yt=!0,At=!1,Gn(),tryButton.hide(),closeResultButton.hide(),gn.style.display="block",se=null}function keyTyped(){bn&&!1===yn&&!1===yr()&&("i"!==key&&"I"!==key||(Dt=!Dt),"M b"!==key&&"B"!==key||(xn=!xn),"s"!==key&&"S"!==key||!1!==Lt||saveCanvasAtCurrentTime(),"k"!==key&&"K"!==key||!1!==Lt||save4KCanvasAtCurrentTime(),"u"!==key&&"U"!==key||!1!==Lt||!1!==At||!1!==fn||!1!==Pt||On())}function On(){Lt=!0,wn=null,vn=null,submitButton=br("Submit",width/2-155*le,height/2+115*le,150*le,40*le,Fn),closeSettingButton=br("Close",width/2+5*le,height/2+115*le,150*le,40*le,Yn),vt=createInput(),vt.position(width/2-252.5*le,height/2-40*le),vt.size(500*le,25*le),vt.style("font-size","15px"),vt.value(Jt|M |""),zt=createInput(),zt.position(width/2-252.2*le,height/2+35*le),zt.size(500*le,25*le),zt.style("font-size","15px"),zt.value(Qt||"")}function Fn(){Vt=vt.value(),_t=zt.value(),submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide(),Lt=!1,yn=!0,Nn()}async function Nn(){[wn,vn,_]=await Promise.all([c(Vt),u(_t),O(1e3)]),yn=!1,wn&&vn?(n(Vt),i(_t),window.location.reload()):(Lt=!0,submitButton.show(),closeSettingButton.show(),vt.show(),zt.show())}function Bn(){Je.textFont("Trebuchet MS"),Je.noStroke(),pr(Je,60M 0*le,200*le),Je.strokeWeight(1*le),Je.stroke(xt),Je.fill(xt),Je.textSize(50*le),Je.text("update()",width/2,height/2+2.5*le)}function Yn(){wn=null,vn=null,Lt=!1,submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide()}function Gn(){_n(),nn=Date.now(),pe=!1,me=!1,St=Wt.training.structure_gen,Rt=Wt.visual.birthYear,It=Wt.visual.lifeCycle,Ct=Wt.training.epoch_num,Tt=Wt.training.activation_func,Ft=Mr.findIndex((e=>e[0]==Wt.visual.hardwareAcceleration))+1,1==Ft?(Nt=30,fe=40):2==Ft?(Nt=15,fe=20):(Nt=2,fe=10);consM t e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),ae=100*le,ht=50*le,Oe=Sr.findIndex((e=>e[0]==Wt.visual.nodeShape))+1,dt=Er.findIndex((eM =>e[0]==Wt.visual.nodeFill))+1,lt=_r.findIndex((e=>e[0]==Wt.visual.pattern))+1,de=Math.tanh(Math.log10(Xt.avgfeerate)),de=map(de,0,1,.2,.8),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<IeM .length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){letM t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,at=.7,pt=[],xt=ft[ut][2],gt=ft[ut][ft[ut].length-1];for(let e=3;e<ft[ut].length-1;e++)pt.push(ft[ut][e]);mt=sr(xt,gt,pt,width),btM =[],wt=[],yt=width/(Ve-1);for(let e=0;e<Ve;e++)bt.push(hr(mt,yt*e/width)),wt.push(hr(mt,yt*e/width));wt.unshift(bt[0]),wt.push(bt[bt.length-1]),hn=0,cn=0,un=0,Yt=!0;const n={xLeft:ae/8,xRight:width-ae/8,yTop:ae/8,yBottom:height-ae/8},r=Ce.map((e=>e.length));jt=new R(bt,r,n,Oe,le)}function Hn(e,t){let n=Ce[e].length;return[e*we+we/2+ae/2,height/2-(n-1)/2*ve+t*ve]}function $n(e,t){le=min(e,t)/1024,ae=100*le,ht=50*le,we=(e-ae)/Ve,ve=(t-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(M let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}xe=floor(De.length*de),Le=[],ke=[],ge=floor(map(de,.2,.8,15,2));for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,mt=sr(xt,gt,pt,e),bt=[],wt=[],yt=e/(Ve-1);for(let t=0;t<Ve;t++)bt.push(hr(mt,yt*t/e)),wt.push(hr(mt,yt*t/e));wt.unshift(bt[0]),wt.push(bt[bt.length-1])}function Xn(){const e=Ut.getBrainStatus();Gt=M e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=M 0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=CeM [e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floorM (random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le}function Wn(){jt.update();const e=4==Pe?0:Kt;jt.draw(Qe,ct,dt,e,le)}function Un(){if(!bn)return ar(),void et.image(je,0,0);if(4==Pe||5==Pe)return Wn(),void et.image(Qe,0,0);un>=Nt&&hn<Ve&&(hn++,un=0);for(let e=0;e<hn;e++)1==dt?it=ot=bt[e]:(it=ct,ot=bt[e]),Kn(e,it,ot,$e);un>=Nt&&cn<Ve-1&&(cn++,un=0);for(let e=0;e<cn;e++)Zn(e)}function qn(){et.background(ct),Ue.background(255),Ue.reM ctMode(CENTER),ne(Ue),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),Ue.stroke(st),Ue.strokeWeight(8*le),Ue.fill(ct),Qe.background(255),Qe.rectMode(CENTER),ne(Qe),Qe.strokeWeight(le),qe.background(255),qe.rectMode(CENTER),ne(qe),qe.textAlign(LEFT),$e.background(255),$e.rectMode(CENTER),ne($e),Xe.background(255),ne(Xe),Xe.strokeWeight(Ne),We.background(255),We.rectMode(CENTER),ne(We),We.fill(st),We.stroke(st),We.strokeWeight(.1*le),er(lt),We.noStroke(),xn&&(We.rect(ae/16,height/2,ae/8,height),We.rect(width-ae/16,heiM ght/2,ae/8,height),We.rect(width/2,ae/16,width,ae/8),We.rect(width/2,height-ae/16,width,ae/8)),Ze.background(255),Ze.rectMode(CENTER),ne(Ze),Ze.textAlign(CENTER,CENTER),Ze.textStyle(BOLD),Ze.stroke(st),Ze.strokeWeight(8*le),Ze.fill(ct),je.background(255),je.rectMode(CENTER),ne(je),je.textAlign(CENTER,CENTER),je.textStyle(BOLD),Ke.background(255),Ke.rectMode(CENTER),ne(Ke),Ke.textAlign(CENTER,CENTER),Ke.textStyle(BOLD),Ke.stroke(st),Ke.strokeWeight(8*le),Ke.fill(ct),Je.background(255),Je.rectMode(CENTER),ne(Je),Je.tM extAlign(CENTER,CENTER),Je.textStyle(BOLD),Je.stroke(st),Je.strokeWeight(8*le),Je.fill(ct),Un(),et.image(We,0,0),Pt&&An(),et.image(Xe,0,0),et.image($e,0,0),At&&(tr(),et.image(Ue,0,0)),fn&&(lr(),et.image(Ze,0,0)),Lt&&(or(),et.image(Ke,0,0)),Dt&&(ir(),et.image(qe,0,0)),yn&&(Bn(),et.image(Je,0,0))}function draw(){const e=Date.now();bn&&(Ut.updateAge(new Date(e)),Xn()),qn(),image(et,0,0),zn||un++}function Zn(e){let t,n=Ce[e].length,r=Ce[e+1].length;for(let i=0;i<n;i++){const[n,o]=Hn(e,i);for(let a=0;a<r;a++){const[r,l]M =Hn(e+1,a);t=map(min(Ce[e][i],Ce[e+1][a]),0,1,0,.5),ur(n,o,r,l,bt[e],bt[e+1],Xe,t)}}}function Kn(e,t,n,r){let i,o,a,l=Ce[e].length;for(let s=0;s<l;s++){const[l,h]=Hn(e,s);i=Ce[e][s],a=map(Be,1/30,1,3,10),o=map(Ce[e][s],0,1,2*a,0)*le,o<1.5*le&&(o=0),Qn(l,h,ze,Oe,t,n,o,i,r)}}function Jn(e,t,n,r,i){for(let o=0;o<Le[e].length;o++)Qn(Le[e][o][0],Le[e][o][1],t,Oe,n,r,0,1,i)}function Qn(e,t,n,r,i,o,a,l,s){s.stroke(dr(o,map(l,0,1,.25,1))),s.fill(dr(i,map(l,0,1,.15,1))),s.strokeWeight(Fe),fr([a],s),3==dt&&s.fill(dr(i,0)),1=M =r?s.ellipse(e,t,n):2==r?s.rect(e,t,7*n/8,7*n/8):3==r&&(s.beginShape(),s.vertex(e-4*n/7,t),s.vertex(e,t-4*n/7),s.vertex(e+4*n/7,t),s.vertex(e,t+4*n/7),s.endShape(CLOSE))}function er(e){if(1==e);else if(2==e){We.strokeWeight(1*le);for(let e=ht/4;e<width+ht/4;e+=ht)for(let t=ht/4;t<height+ht/4;t+=ht)We.point(e,t)}else if(3==e){ht=25*le;for(let e=ht/2;e<height+ht/2;e+=ht)We.line(0,e,width,e);for(let e=ht/2;e<width+ht/2;e+=ht)We.line(e,0,e,height)}}function tr(){Ue.textFont("Trebuchet MS"),Ue.textAlign(LEFT,CENTER),Ue.M noStroke(),pr(Ue,800*le,500*le),Ue.noStroke(),Ue.fill(dr(st,.75)),Ue.rect(width/2,height/2-100*le,800*le,300*le,25*le,25*le,0,0),Ue.fill(st),Ue.rect(width/2-250*le,height/2-100*le,225*le,225*le),Ue.image(se.elt,width/2-357.5*le,height/2-207.5*le,215*le,215*le);let e=100*Zt[0][0];Ue.fill(ct),Ue.textSize(25*le),Ue.textStyle(NORMAL),1==me&&(e>=0&&e<20?Ue.text("I have a feeling this image belongs to",width/2-100*le,height/2-170*le):e>=20&&e<40?Ue.text("I have a hunch this image belongs to",width/2-100*le,height/2-170*lM e):e>=40&&e<60?Ue.text("I think this image belongs to",width/2-100*le,height/2-170*le):e>=60&&e<80?Ue.text("I'm almost certain this image belongs to",width/2-100*le,height/2-170*le):Ue.text("I'm positive this image belongs to",width/2-100*le,height/2-170*le));let t=e.toFixed(2);"100.00"==t&&(t="100"),1==me&&Ue.text("I'm "+t+"% confident that I'm right!",width/2-100*le,height/2-25*le),example=Zt.map((e=>e[1])),be=Ue.textWidth('"FIDENZAAAA"'),defaultPhrase=Ue.textWidth('"PERPENDICULAR INHABITATION"'),Ue.textStyle(BOLM D);const n=me?example[0]:random(example);if(1===n.split(" ").length){let e=75*be/Ue.textWidth('"'+n+'"');e>75&&(e=75),Ue.textSize(e*le),Ue.text('"'+n+'"',width/2-100*le,height/2-90*le)}else nr(width/2-100*le,height/2-90*le,460*le,110*le,n,Ue);if(millis()-ye>1500&&(me=!0),C(tt,nt,st,ct,Pe,Mt),Ue.image(nt,width/2-370*le,height/2+70*le,80*le,80*le),3==Pe){let e;e=map(Mt,50,60,.25,1.3),I(rt,e),Ue.image(rt,width/2-370*le,height/2+70*le,80*le,80*le)}let r,i;Ue.image(tt,width/2-370*le,height/2+70*le,80*le,80*le),Ue.fill(xM t),Ue.textSize(40*le),Ue.text("INTELLIGENCE INFO",width/2-275*le,height/2+115*le),Ue.textSize(18*le),Ue.textStyle(NORMAL),Ue.circle(width/2-360*le,height/2+180*le,7.5*le),1==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s growing and getting smarter by the day.`:2==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s stable and it has reached peak performance.`:3==Pe&&(r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s decaying and losing its luster.`),i=2==Pe?"The Perceptron remains stableM for some time before entering the decay phase.":`Wait until ${new Date(an).toLocaleString("en-US")} for your Perceptron to reach its peak performance.`,Ue.text(r,width/2-350*le,height/2+180*le),Ue.circle(width/2-360*le,height/2+210*le,7.5*le),Ue.text(i,width/2-350*le,height/2+210*le),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),gr(Ue,width/2-225*le,width/2+65*le,height/2+265*le,height/2+305*le,"SELECT ANOTHER IMAGE"),gr(Ue,width/2+75*le,width/2+225*le,height/2+265*le,height/2+305*le,"CLOSE")}function nr(e,t,n,r,M i,o){let a=i.split(" "),l=75*be/o.textWidth('"'+i+'"'),s=0,h=[],c=[],u=[],f="",d="";if(l>=50)l>75&&(l=75),o.textSize(l*le),o.text('"'+i+'"',e,t);else if(l<50){if(l=50*defaultPhrase/o.textWidth('"'+i+'"'),l>30){if(l>50&&(l=50),[f,d]=rr(l,n,s,h,c,a,f,d,Ue),0==c.length)return o.textSize(l*le),void o.text('"'+i+'"',e,t);for(s=0,h=[],c=[];o.textWidth(d)>n/le;)l=l*n/le/o.textWidth(d),f="",d="",[f,d]=rr(l,n,s,h,c,a,f,d,Ue)}else{l=30,o.textSize(l);for(let e=0;e<a.length;e++)s+=o.textWidth(" "+a[e]),s<=n/le?h.push(a[e]):s>nM /le&&s<=n/le*2?c.push(a[e]):u.push(a[e]);for(let e=1;e<h.length;e++)f=f+" "+h[e];if(f='"'+h[0]+f,0==u.length){for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+c[c.length-1]+'"'}else if(1==c.length)d="... "+u[u.length-1]+'"';else{for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+"... "+u[u.length-1]+'"'}}o.textSize(l*le);let r=1.25*(o.textDescent()+o.textAscent());o.text(f,e,t-r/2),o.text(d,e,t+r/2)}}function rr(e,t,n,r,i,o,a,l,s){s.textSize(e);for(let e=0;e<o.length;e++)(n+=s.textWidth(" "+o[e]))<=t/le?r.push(o[e]):i.pushM (o[e]);for(let e=1;e<r.length;e++)a=a+" "+r[e];if(a='"'+r[0]+a,0==i.length&&(a+='"',l=""),1==i.length)l=i[i.length-1]+'"';else{for(let e=0;e<i.length-1;e++)l=l+i[e]+" ";l=l+i[i.length-1]+'"'}return[a,l]}function ir(){const e=45*le;qe.textFont("Tahoma"),qe.stroke(st),qe.strokeWeight(2*le),qe.fill(ct),qe.rect(width/2,e/2+height-87.5*le,600*le,90*le),qe.fill(st),qe.rect(width/2-150*le,e+height-170*le,300*le,30*le),qe.fill(ct),qe.rect(width/2+150*le,e+height-170*le,300*le,30*le),qe.noStroke(),qe.fill(ct),qe.textSize(15M *le),qe.textStyle(BOLD),qe.text("PERCEPTRON INFORMATION",width/2-285*le,e+height-165*le),qe.fill(xt),qe.text("ARTWORK NAME:",width/2+10*le,e+height-165*le),qe.textAlign(RIGHT),qe.textStyle(ITALIC),qe.text("Perceptron #"+Et,width/2+285*le,e+height-165*le);const[t,n]=It.split(" ");let r;"60 Years"===It?r="1 Year":"60 Months"===It?r="1 Month":"60 Weeks"===It?r="1 Week":"60 Days"===It?r="1 Day":"12 Hours"===It&&(r="12 Minutes"),data=[["AI MODEL NAME:",B(12*le,Ht,140*le)],["SCALE:","1:"+Te],["NUMBER OF CLASSES:",$t.lengM th],["BIRTH YEAR:",Rt],["NUMBER OF REBIRTHS:",sn.toString()],["AGE:",`${Math.ceil(Mt)} Perceptron Years`],["ONE PERCEPTRON YEAR:",`${r}`],["STATE:",Ot[Pe]],["ACTIVE NEURONS:",`${round(ln*rn)} / ${ln}`],["NEXT STATE TIME:",vr(new Date(on))]],qe.fill(xt);const i=data.length/2;for(let t=0;t<data.length;++t){const n=t<i,r=n?width/2-285*le:width/2+10*le,o=n?width/2-10*le:width/2+285*le,a=e+height-(135-t%i*15)*le;qe.textStyle(BOLD),qe.textAlign(LEFT),qe.textSize(12*le),qe.text(data[t][0],r,a),qe.textStyle(ITALIC),qe.textM Align(RIGHT),qe.textSize(12*le),qe.text(data[t][1],o,a)}}function or(){Ke.textFont("Trebuchet MS"),Ke.noStroke(),pr(Ke,600*le,200*le),gr(Ke,width/2-155*le,width/2-5*le,height/2+115*le,height/2+155*le,"UPDATE"),gr(Ke,width/2+5*le,width/2+155*le,height/2+115*le,height/2+155*le,"CLOSE"),Ke.textAlign(LEFT),Ke.fill(xt),Ke.text("UPDATE BITCOIN FULL NODE ADDRESS",width/2-252.5*le,height/2-55*le),Ke.text("UPDATE MODEL ADDRESS",width/2-252.5*le,height/2+20*le),Ke.textAlign(RIGHT),Ke.textStyle(ITALIC),Ke.textSize(15*le),0==wM n&&Ke.text("(*) Invalid Address",width/2+252.5*le,height/2-53*le),0==vn&&Ke.text("(*) Invalid Model",width/2+252.5*le,height/2+23*le)}function ar(){je.textFont("Trebuchet MS"),je.fill(st),je.textSize(50*le),je.stroke(st),je.strokeWeight(1*le),je.text("main()",width/2,height/2)}function lr(){un>=20&&1==dn&&(dn=!1,un=0),dn&&(Ze.textFont("Trebuchet MS"),Ze.stroke(st),Ze.fill(ct),Ze.rect(width/2,height/2,600*le,150*le,25*le),Ze.fill(xt),Ze.textSize(75*le),Ze.noStroke(),1==Pe?Ze.text("GROWING",width/2,height/2+5*le):3==M Pe?Ze.text("AGING",width/2,height/2+5*le):4==Pe?Ze.text("DEAD",width/2,height/2+5*le):5==Pe&&Ze.text("BIRTH",width/2,height/2+5*le)),un>=20&&0==dn&&(dn=!0,un=0,Bt++,3==Bt&&(fn=!1))}function sr(e,t,n,r){let i=[],o=r/(n.length+1),a=color(e),l=color(t);i.push(a);for(let e=0;e<n.length;e++){let t=color(n[e]);for(let e=1;e<=o;e++){let n=lerpColor(a,t,e/o);i.push(n)}a=t}for(let e=1;e<o;e++){let t=lerpColor(a,l,e/o);i.push(t)}if(i.push(l),i.length>r)i.splice(r);else if(i.length<r){let e=i[i.length-1];for(;i.length<r;)i.puM sh(e)}return i}function hr(e,t){let n=e.length,r=Math.floor(t*n);return r>=n&&(r=n-1),e[r]}function cr(e){e=e.replace("#","");var t=parseInt(e,16);return color(t>>16&255,t>>8&255,255&t)}function ur(e,t,n,r,i,o,a,l){var s=a.drawingContext.createLinearGradient(e,t,n,r);s.addColorStop(0,i),s.addColorStop(1,o),a.drawingContext.strokeStyle=s,a.drawingContext.globalAlpha=l,a.line(e,t,n,r),a.drawingContext.globalAlpha=1}function fr(e,t){t.drawingContext.setLineDash(e)}function dr(e,t){let n=color(e),r=red(n),i=green(n),o=M blue(n);return color(r,i,o,255*t)}function xr(e,t,n,r){return mouseX>e&&mouseX<t&&mouseY>n&&mouseY<r}function gr(e,t,n,r,i,o){e.strokeWeight(1*le),e.stroke(st);const[a,l]=xr(t,n,r,i)?[xt,ct]:[ct,xt];e.fill(a),e.push(),e.rectMode(CORNERS),e.rect(t,r,n,i,5*le),e.pop(),e.noStroke(),e.textSize(20*le),e.fill(l),e.text(o,(t+n)/2,(46*r+54*i)/100)}function pr(e,t,n){e.fill(0,0,0,75),e.rect(width/2,height/2,width,height),e.stroke(st),e.fill(ct),e.rect(width/2,height/2,t,n,25*le)}function mr(e,t){resizeCanvas(e,t,!0),Xe.resiM zeCanvas(e,t,!0),$e.resizeCanvas(e,t,!0),We.resizeCanvas(e,t,!0),Ue.resizeCanvas(e,t,!0),qe.resizeCanvas(e,t,!0),Qe.resizeCanvas(e,t,!0),je.resizeCanvas(e,t,!0),Ze.resizeCanvas(e,t,!0),Ke.resizeCanvas(e,t,!0),Je.resizeCanvas(e,t,!0),et.resizeCanvas(e,t,!0)}function br(e,t,n,r,i,o){const a=J(e);return a.position(t,n),a.size(r,i),a.style("opacity","0"),a.mouseClicked(o),a}function yr(){return null!=vt&&vt?.isFocused()||null!=zt&&zt?.isFocused()}function wr(e,t,n,r){let i;if(e<=3){i=`Hey ${String.fromCodePoint(128075)M }, I'm ${n}, ${t} years old. I can detect ${r.length} NFT collections: `;let e=0;for(let t=0;t<r.length;++t){const n=r[t];if(e+n.length>500){i+=", etc";break}t==r.length-1?i+=", and ":t>0&&(i+=", "),i+=n,e+=n.length}i+=". ",t<=5?i+="However, I am only a baby, so my recognition ability is not accurate. I'm in the state of Growing both looks and intelligence.":t<=13?i+="I am now a child. My recognition ability is becoming better, but still not very accurate. I'm in the state of Growing both looks and intelligence.":tM <=25?i+="I have grown up to be a teen. My recognition ability almost reaches the peak, but I will still mess up sometimes. I'm in the state of Growing both looks and intelligence.":t<=50?i+="I finally reach adulthood. My recognition is fully functional now. I'm in the Stable state, where I am the most intelligent with all neurons activated.":t<=60&&(i+="I am now an old Perceptron, so my recognition ability is no longer the best. I'm in the Decaying state, meaning that my neurons are dying, and my intelligence is deM creasing over time.")}else 4==e?i=`${n} is Dead. However, this is not the end to its story...`:5==e&&(i=`${n} is now in the Rebirth state, and is preparing to start a new life.`);return i}function vr(e){const t=e.getDate(),n=e.toLocaleString("en-US",{month:"long"}),r=e.getFullYear();let i=e.getHours().toString();1==i.length&&(i="0"+i);let o=e.getMinutes().toString();return 1==o.length&&(o="0"+o),`${Y(t)} ${n} ${r} | ${i}:${o}`}saveCanvasAtCurrentTime=()=>{save(N())},save4KCanvasAtCurrentTime=()=>{const e=width,t=heM ight,n=min(4096/min(e,t),1e4/max(e,t)),r=e*n,i=t*n;mr(r,i),zn=!0,$n(r,i),qn();let o="4K_"+N()+".png";saveCanvas(et,o),mr(e,t),$n(e,t),zn=!1};const zr=[["60 Years",3,365],["60 Months",40,30],["60 Weeks",37,7],["60 Days",20,1]],Vr=[["1943",1],["1951",1.5],["1957",2],["1969",2.5],["1970",3],["1980",3.5],["1982",4],["1986",4.5],["1988",5],["1997",5.5],["1998",6],["2002",6.5],["2009",7],["2012",7.5],["2014",8],["2015",8.5],["2016",9],["2023",15]],_r=[["Plain",20],["Dotted",40],["Squared",40]],Mr=[["Basic",30],["StandardM ",60],["Advanced",10]],Er=[["MNIST",70],["CIFAR",25],["IMAGENET",5]],Sr=[["Theano",60],["Torch",30],["TensorFlow",10]],Rr=[["Whitepaper",2],["Blackboard",2],["Blueprint",2],["Nak",74/14],["Jims",74/14],["Level 10",74/14],["Flips",74/14],["Level 14",74/14],["III",74/14],["XMB",74/14],["Info",74/14],["Adventure",74/14],["Marigold",74/14],["Phoenix",74/14],["Love",74/14],["Cachet",74/14],["Human",74/14],["Twilight",3],["Sunset",3],["Aurora",3],["Liminal Space",3],["D Vu",3],["Lucid Dream",3],["Parallel",1],["MultM iverse",1]];function Ir(e){for(let e=0;e<100;++e)random(1);return{visual:{pattern:k(_r),hardwareAcceleration:k(Mr),nodeFill:k(Er),nodeShape:k(Sr),colorPalette:k(Rr),lifeCycle:k(zr),birthYear:k(Vr)},training:e}}function Cr(e){window.$generativeTraits={"Network Architecture":e.training.structure_gen,"Hidden Layers":e.training.n_layers,"Max Neurons Per Hidden Layer":e.training.max_nodes,"Activation Function":e.training.activation_func,"Training Epochs":e.training.epoch_num,Dataset:e.visual.nodeFill,"Deep Learning FramM ework":e.visual.nodeShape,"Hardware Acceleration":e.visual.hardwareAcceleration,"Paper Pattern":e.visual.pattern,"Life Cycle":e.visual.lifeCycle,"Birth Year":e.visual.birthYear,"Color Palette":e.visual.colorPalette}} <script defer src="https://static.cloudflareinsights.com/beacon.min.js/v2b4487d741ca48dcbadcaf954e159fc61680799950996" integrity="sha512-D/jdE0CypeVxFadTejKGTzmwyV10c1pxZk/AqjJuZbaJwGMyNHY3q/mTPWqMUnFACfCTunhZUVcd4cV78dK1pQ==" data-cf-beacon='{"rayId":"7b481e2eaae1a20b","version":"2023.Ls3.0","b":1,"token":"6c07c178c94442f695e7a0a2aaee641a","si":100}' crossorigin="anonymous"></script> {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "honey pot"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "lamp"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "moon"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "fire"}, {"trait_type": "Claws", "value": "honey pot"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "wizard staff"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "bag"}]} text/plain;charset=utf-8 1{"p":"sns","op":"reg","name":"howardhughes.sats"}h! {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "pauldrons"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "rainbow"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "pirate flag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "crown"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "tiger"}, {"trait_type": "Mane", "value": "rainbow"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "golden"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "blue fire"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "broadsword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "golden armor"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "bloody"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "parrot"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "blue fire"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "cape"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "moon"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "skull"}, {"trait_type": "Artifacts", "value": "wizard staff"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "dagger"}]} text/html;charset=utf-8 <meta charset="utf-8" /> position: relative; width: var(--width); height: var(--height); border: 1px solid blue; position: relative; <div id="upload"> <input id="inputUpload" type="file"> function e(e){"use strict";return new function e(t){let n="global"==t?window:this;n.canvas=document.createElement("canvas");let r=n.canvas.getContext("2d");n.width=100,n.height=100,n.canvas.width=n.width,n.canvas.height=n.height,"offscreen"!=t&&(document.body?document.body.appendChild(n.canvas):window.addEventListener("load",(function(){document.body.appendChild(n.canvas)}))),g(),n.MAGIC=161533525,n.RGB=0,n.HSV=1,n.HM SB=1,n.CHORD=0,n.PIE=1,n.OPEN=2,n.RADIUS=1,n.CORNER=2,n.CORNERS=3,n.ROUND="round",n.SQUARE="butt",n.PROJECT="square",n.MITER="miter",n.BEVEL="bevel",n.CLOSE=1,n.BLEND="source-over",n.REMOVE="destination-out",n.ADD="lighter",n.DARKEST="darken",n.LIGHTEST="lighten",n.DIFFERENCE="difference",n.SUBTRACT="subtract",n.EXCLUSION="exclusion",n.MULTIPLY="multiply",n.SCREEN="screen",n.REPLACE="copy",n.OVERLAY="overlay",n.HARD_LIGHT="hard-light",n.SOFT_LIGHT="soft-light",n.DODGE="color-dodge",n.BURN="color-burn",n.NORMAL="norM mal",n.ITALIC="italic",n.BOLD="bold",n.BOLDITALIC="italic bold",n.CENTER="center",n.LEFT="left",n.RIGHT="right",n.TOP="top",n.BOTTOM="bottom",n.BASELINE="alphabetic",n.LANDSCAPE="landscape",n.PORTRAIT="portrait",n.ALT=18,n.BACKSPACE=8,n.CONTROL=17,n.DELETE=46,n.DOWN_ARROW=40,n.ENTER=13,n.ESCAPE=27,n.LEFT_ARROW=37,n.OPTION=18,n.RETURN=13,n.RIGHT_ARROW=39,n.SHIFT=16,n.TAB=9,n.UP_ARROW=38,n.HALF_PI=Math.PI/2,n.PI=Math.PI,n.QUARTER_PI=Math.PI/4,n.TAU=2*Math.PI,n.TWO_PI=2*Math.PI,n.THRESHOLD=1,n.GRAY=2,n.OPAQUE=3,n.INVEM RT=4,n.POSTERIZE=5,n.DILATE=6,n.ERODE=7,n.BLUR=8,n.ARROW="default",n.CROSS="crosshair",n.HAND="pointer",n.MOVE="move",n.TEXT="text",n.VIDEO={video:!0,audio:!1},n.AUDIO={video:!1,audio:!0},n.SHR3=1,n.LCG=2,n.HARDWARE_FILTERS=!0,n.hint=function(e,t){n[e]=t},n.frameCount=0,n.mouseX=0,n.mouseY=0,n.pmouseX=0,n.pmouseY=0,n.mouseButton=null,n.keyIsPressed=!1,n.mouseIsPressed=!1,n.key=null,n.keyCode=null,n.pixels=null,n.accelerationX=0,n.accelerationY=0,n.accelerationZ=0,n.rotationX=0,n.rotationY=0,n.rotationZ=0,n.relRotatM ionX=0,n.relRotationY=0,n.relRotationZ=0,n.pAccelerationX=0,n.pAccelerationY=0,n.pAccelerationZ=0,n.pRotationX=0,n.pRotationY=0,n.pRotationZ=0,n.pRelRotationX=0,n.pRelRotationY=0,n.pRelRotationZ=0,n.touches=[],n._styleCache=[{colorMode:n.RGB,noStroke:!1,noFill:!1,ellipseMode:n.CENTER,rectMode:n.CORNER,curveDetail:20,curveAlpha:0,textFont:"sans-serif",textSize:12,textLeading:12,textStyle:"normal"}],n._style=n._styleCache[n._styleCache.length-1],n._noLoop=!1,n._pixelDensity=1,n._frameRate=null,n._tint=null;let i=nullM ,o=!0,a=[],l=null,s=0,h={},c=0,u=null,f=null,d=null;Object.defineProperty(n,"deviceOrientation",{get:function(){return 90==Math.abs(window.orientation)?n.LANDSCAPE:n.PORTRAIT}}),Object.defineProperty(n,"windowWidth",{get:function(){return window.innerWidth}}),Object.defineProperty(n,"windowHeight",{get:function(){return window.innerHeight}}),Object.defineProperty(n,"drawingContext",{get:function(){return r}}),n.createCanvas=function(e,t){return n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t,g(),n.canvas},nM .resizeCanvas=function(e,t){n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t},n.createGraphics=n.createImage=function(t,n){let r=new e("offscreen");return r.createCanvas(t,n),r.noLoop(),r},n.pixelDensity=function(e){return null==e||(n._pixelDensity=e,n.canvas.width=Math.ceil(n.width*e),n.canvas.height=Math.ceil(n.height*e),n.canvas.style.width=n.width+"px",n.canvas.style.height=n.height+"px",r.scale(n._pixelDensity,n._pixelDensity),g()),n._pixelDensity},n.map=function(e,t,n,r,i,o){let a=r+1*(e-t)/(n-t)*(i-r)M ;return o?r<i?Math.min(Math.max(a,r),i):Math.min(Math.max(a,i),r):a},n.lerp=function(e,t,n){return e*(1-n)+t*n},n.constrain=function(e,t,n){return Math.min(Math.max(e,t),n)},n.dist=function(){return 4==arguments.length?Math.hypot(arguments[0]-arguments[2],arguments[1]-arguments[3]):Math.hypot(arguments[0]-arguments[3],arguments[1]-arguments[4],arguments[2]-arguments[5])},n.norm=function(e,t,r){return n.map(e,t,r,0,1)},n.sq=function(e){return e*e},n.fract=function(e){return e-Math.floor(e)},n.degrees=function(e){retM urn 180*e/Math.PI},n.radians=function(e){return e*Math.PI/180},n.abs=Math.abs,n.ceil=Math.ceil,n.exp=Math.exp,n.floor=Math.floor,n.log=Math.log,n.mag=Math.hypot,n.max=Math.max,n.min=Math.min,n.round=Math.round,n.sqrt=Math.sqrt,n.sin=Math.sin,n.cos=Math.cos,n.tan=Math.tan,n.asin=Math.asin,n.acos=Math.acos,n.atan=Math.atan,n.atan2=Math.atan2,n.Vector=function(e,t,r){let i=this;i.x=e||0,i.y=t||0,i.z=r||0;let o=null,a=null;function l(e,t,n){return null!=e.x?e:null!=t?{x:e,y:t,z:n||0}:{x:e,y:e,z:e}}function s(){null==a&M &(a=i.x*i.x+i.y*i.y+i.z*i.z,o=Math.sqrt(a))}function h(){a=null,o=null}i.set=function(e,t,n){i.x=e||0,i.y=t||0,i.z=n||0},i.copy=function(){return new n.Vector(i.x,i.y,i.z)},i.add=function(){let e=l.apply(null,arguments);return i.x+=e.x,i.y+=e.y,i.z+=e.z,h(),i},i.rem=function(){let e=l.apply(null,arguments);return i.x%=e.x,i.y%=e.y,i.z%=e.z,h(),i},i.sub=function(){let e=l.apply(null,arguments);return i.x-=e.x,i.y-=e.y,i.z-=e.z,h(),i},i.mult=function(){let e=l.apply(null,arguments);return i.x*=e.x,i.y*=e.y,i.z*=e.z,hM (),i},i.div=function(){let e=l.apply(null,arguments);return i.x/=e.x,i.y/=e.y,i.z/=e.z,h(),i},i.mag=function(){return s(),o},i.magSq=function(){return s(),a},i.dot=function(){let e=l.apply(null,arguments);return i.x*e.x+i.y*e.y+i.z*e.z},i.dist=function(){let e=l.apply(null,arguments),t=i.x-e.x,n=i.y-e.y,r=i.z-e.z;return Math.sqrt(t*t+n*n+r*r)},i.cross=function(){let e=l.apply(null,arguments),t=i.y*e.z-i.z*e.y,n=i.z*e.x-i.x*e.z,r=i.x*e.y-i.y*e.x;return i.x=t,i.y=n,i.z=r,h(),i},i.normalize=function(){s();let e=o;retuM rn i.x/=e,i.y/=e,i.z/=e,o=1,a=1,i},i.limit=function(e){s();if(o>e){let t=e/o;i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e}return i},i.setMag=function(e){s();let t=e/o;return i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e,i},i.heading=function(){return Math.atan2(i.y,i.x)},i.rotate=function(e){let t=Math.cos(e),n=Math.sin(e),r=i.x*t-i.y*n,o=i.x*n+i.y*t;return i.x=r,i.y=o,i},i.angleBetween=function(){let e=l.apply(null,arguments);const t=i.dot(e)/(i.mag()*e.mag());let n;return n=Math.acos(Math.min(1,Math.max(-1,t))),n*Math.sign(i.cross(e).z||1)},M i.lerp=function(e,t){return i.x=i.x*(1-t)+e.x*t,i.y=i.y*(1-t)+e.y*t,i.z=i.z*(1-t)+e.z*t,h(),i},i.reflect=function(e){return e.normalize(),i.sub(e.mult(2*i.dot(e)))},i.array=function(){return[i.x,i.y,i.z]},i.equals=function(e,t){return null==t&&null==(t=Number.EPSILON)&&(t=0),Math.abs(e.x-i.x)<t&&Math.abs(e.y-i.y)<t&&Math.abs(e.z-i.z)<t},i.fromAngle=function(e,t){return null==t&&(t=1),o=t,a=t*t,i.x=t*Math.cos(e),i.y=t*Math.sin(e),i.z=0,i},i.fromAngles=function(e,t,n){null==n&&(n=1),o=n,a=n*n;const r=Math.cos(t),l=MaM th.sin(t),s=Math.cos(e),h=Math.sin(e);return i.x=n*h*l,i.y=-n*s,i.z=n*h*r,i},i.random2D=function(){return o=1,a=1,i.fromAngle(Math.random()*Math.PI*2)},i.random3D=function(){return o=1,a=1,i.fromAngles(Math.random()*Math.PI*2,Math.random()*Math.PI*2)},i.toString=function(){return`[${i.x}, ${i.y}, ${i.z}]`}},n.Vector.add=function(e,t){return new n.Vector(e.x+t.x,e.y+t.y,e.z+t.z)},n.Vector.rem=function(e,t){return new n.Vector(e.x%t.x,e.y%t.y,e.z%t.z)},n.Vector.sub=function(e,t){return new n.Vector(e.x-t.x,e.y-t.y,e.M z-t.z)},n.Vector.mult=function(e,t){return null==t.x?new n.Vector(e.x*t,e.y*t,e.z*t):new n.Vector(e.x*t.x,e.y*t.y,e.z*t.z)},n.Vector.div=function(e,t){return null==t.x?new n.Vector(e.x/t,e.y/t,e.z/t):new n.Vector(e.x/t.x,e.y/t.y,e.z/t.z)},n.Vector.dist=function(e,t){return Math.hypot(e.x-t.x,e.y-t.y,e.z-t.z)},n.Vector.cross=function(e,t){return new n.Vector(e.y*t.z-e.z*t.y,e.z*t.x-e.x*t.z,e.x*t.y-e.y*t.x)},n.Vector.lerp=function(e,t,r){return new n.Vector(e.x*(1-r)+t.x*r,e.y=e.y*(1-r)+t.y*r,e.z=e.z*(1-r)+t.z*r)},n.M Vector.equals=function(e,t,n){return e.equals(t,n)};for(let e of["fromAngle","fromAngles","random2D","random3D"])n.Vector[e]=function(t,r,i){return(new n.Vector)[e](t,r,i)};function x(e,t,n){let r,i,o,a,l,s,h,c,u;if(0==t)return[255*(r=n),255*(i=n),255*(o=n)];switch((a=e)>360&&(a=0),h=n*(1-t),c=n*(1-t*(s=(a/=60)-(l=~~a))),u=n*(1-t*(1-s)),l){case 0:r=n,i=u,o=h;break;case 1:r=c,i=n,o=h;break;case 2:r=h,i=n,o=u;break;case 3:r=h,i=c,o=n;break;case 4:r=u,i=h,o=n;break;default:r=n,i=h,o=c}return[255*r,255*i,255*o]}functioM n g(){r.fillStyle="white",r.strokeStyle="black",r.lineCap="round",r.lineJoin="miter"}function p(e){if(0<=e&&e<2*Math.PI)return e;for(;e<0;)e+=2*Math.PI;for(;e>=Math.PI;)e-=2*Math.PI;return e}function m(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;let c=p(a),u=p(l);r.beginPath();for(let a=0;a<h+1;a++){let l=a/h,s=n.lerp(c,u,l),f=Math.cos(s)*i/2,d=Math.sin(s)*o/2;r[a?"lineTo":"moveTo"](e+f,t+d)}s==n.CHORD?r.closePath():s==n.PIE&&(r.lineTo(e,t),r.closePath()),n._style.noFill||r.fill(),n._style.noStrokM e||r.stroke()}function b(e,t,i,o){n._style.noFill&&n._style.noStroke||(r.beginPath(),r.ellipse(e,t,i/2,o/2,0,0,2*Math.PI),n._style.noFill||r.fill(),n._style.noStroke||r.stroke())}function y(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;if(null==a)return function(e,t,i,o){n._style.noFill||r.fillRect(e,t,i,o),n._style.noStroke||r.strokeRect(e,t,i,o)}(e,t,i,o);if(null==l)return y(e,t,i,o,a,a,a,a);const c=Math.min(Math.abs(o),Math.abs(i))/2;a=Math.min(c,a),l=Math.min(c,l),h=Math.min(c,h),s=Math.min(c,s)M ,r.beginPath(),r.moveTo(e+a,t),r.arcTo(e+i,t,e+i,t+o,l),r.arcTo(e+i,t+o,e,t+o,s),r.arcTo(e,t+o,e,t,h),r.arcTo(e,t,e+i,t,a),r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke()}function w(){a=[]}n.createVector=function(e,t,r){return new n.Vector(e,t,r)},n.curvePoint=function(e,t,n,r,i){const o=i*i*i,a=i*i;return e*(-.5*o+a-.5*i)+t*(1.5*o-2.5*a+1)+n*(-1.5*o+2*a+.5*i)+r*(.5*o-.5*a)},n.bezierPoint=function(e,t,n,r,i){const o=1-i;return Math.pow(o,3)*e+3*Math.pow(o,2)*i*t+3*o*Math.pow(i,2)*n+Math.pow(i,M 3)*r},n.curveTangent=function(e,t,n,r,i){const o=i*i;return e*(-3*o/2+2*i-.5)+t*(9*o/2-5*i)+n*(-9*o/2+4*i+.5)+r*(3*o/2-i)},n.bezierTangent=function(e,t,n,r,i){const o=1-i;return 3*r*Math.pow(i,2)-3*n*Math.pow(i,2)+6*n*o*i-6*t*o*i+3*t*Math.pow(o,2)-3*e*Math.pow(o,2)},n.Color=function(e,t,n,r){let i=this;i.MAGIC=786698,i._r=e,i._g=t,i._b=n,i._a=r,i._h=0,i._s=0,i._v=0,i._hsvInferred=!1,i.setRed=function(e){i._r=e,i._hsvInferred=!1},i.setGreen=function(e){i._g=e,i._hsvInferred=!1},i.setBlue=function(e){i._b=e,i._hsvInfM erred=!1},i.setAlpha=function(e){i._a=e/255,i._hsvInferred=!1},i._inferHSV=function(){i._hsvInferred||([i._h,i._s,i._v]=function(e,t,n){let r,i,o,a,l;return r=e<t?e<n?e:n:t<n?t:n,0==(l=100*(i=e>t?e>n?e:n:t>n?t:n)/255)?[o=0,a=0,l]:0==(a=100*(i-r)/i)?[o=0,a,l]:(o=i==e?0+60*(t-n)/(i-r):i==t?120+60*(n-e)/(i-r):240+60*(e-t)/(i-r),[o,a,l])}(i._r,i._g,i._b),i._hsvInferred=!0)},i.toString=function(){return`rgba(${Math.round(i._r)},${Math.round(i._g)},${Math.round(i._b)},${~~(1e3*i._a)/1e3})`}},n.colorMode=function(e){n._stM yle.colorMode=e},n.color=function(){if(1==arguments.length&&786698==arguments[0].MAGIC)return arguments[0];if(n._style.colorMode==n.RGB){if(1==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],1);if(2==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],arguments[1]/255);if(3==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],1);if(4==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],arguments[3]/255)}else{if(1==argumeM nts.length)return new n.Color(...x(0,0,arguments[0]/100),1);if(2==arguments.length)return new n.Color(...x(0,0,arguments[0]/100),arguments[1]/255);if(3==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),1);if(4==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),arguments[3])}return null},n.red=function(e){return e._r},n.green=function(e){return e._g},n.blue=function(e){return e._b},n.alpha=function(e){return 255*e._a},n.hue=function(e){reM turn e._inferHSV(),e._h},n.saturation=function(e){return e._inferHSV(),e._s},n.brightness=function(e){return e._inferHSV(),e._v},n.lightness=function(e){return 100*(.2126*e._r+.7152*e._g+.0722*e._b)/255},n.lerpColor=function(e,t,r){return n._style.colorMode==n.RGB?new n.Color(n.constrain(n.lerp(e._r,t._r,r),0,255),n.constrain(n.lerp(e._g,t._g,r),0,255),n.constrain(n.lerp(e._b,t._b,r),0,255),n.constrain(n.lerp(e._a,t._a,r),0,1)):(e._inferHSV(),t._inferHSV(),new n.Color(n.constrain(function(e,t,r){var i=[[Math.abs(t-M e),n.map(r,0,1,e,t)],[Math.abs(t+360-e),n.map(r,0,1,e,t+360)],[Math.abs(t-360-e),n.map(r,0,1,e,t-360)]];return i.sort(((e,t)=>e[0]-t[0])),(i[0][1]+720)%360}(e._h,t._h,r),0,360),n.constrain(n.lerp(e._s,t._s,r),0,100),n.constrain(n.lerp(e._v,t._v,r),0,100),n.constrain(n.lerp(e._a,t._a,r),0,1)))},n.strokeWeight=function(e){n._style_noStroke=!1,r.lineWidth=e},n.stroke=function(){if(n._style.noStroke=!1,"string"==typeof arguments[0])return void(r.strokeStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._sM tyle.noStroke=!0:r.strokeStyle=e},n.noStroke=function(){n._style.noStroke=!0},n.fill=function(){if(n._style.noFill=!1,"string"==typeof arguments[0])return void(r.fillStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._style.noFill=!0:r.fillStyle=e},n.noFill=function(){n._style.noFill=!0},n.blendMode=function(e){r.globalCompositeOperation=e},n.strokeCap=function(e){r.lineCap=e},n.strokeJoin=function(e){r.lineJoin=e},n.ellipseMode=function(e){n._style.ellipseMode=e},n.rectMode=function(e){n._style.rectM Mode=e},n.curveDetail=function(e){n._style.curveDetail=e},n.curveAlpha=function(e){n._style.curveAlpha=e},n.curveTightness=function(e){n._style.curveAlpha=e},n.clear=function(){r.clearRect(0,0,n.width,n.height)},n.background=function(){if(arguments[0]&&arguments[0].MAGIC==n.MAGIC)return n.image(arguments[0],0,0,n.width,n.height);r.save(),r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity),r.fillStyle="string"==typeof arguments[0]?arguments[0]:n.color(...Array.from(arguments)),r.fillRect(0,0,n.width,n.heightM ),r.restore()},n.line=function(e,t,i,o){n._style.noStroke||(r.beginPath(),r.moveTo(e,t),r.lineTo(i,o),r.stroke())},n.arc=function(e,t,r,i,o,a,l,s){if(o==a)return n.ellipse(e,t,r,i);null==s&&(s=25),null==l&&(l=n.PIE),n._style.ellipseMode==n.CENTER?m(e,t,r,i,o,a,l,s):n._style.ellipseMode==n.RADIUS?m(e,t,2*r,2*i,o,a,l,s):n._style.ellipseMode==n.CORNER?m(e+r/2,t+i/2,r,i,o,a,l,s):n._style.ellipseMode==n.CORNERS&&m((e+r)/2,(t+i)/2,r-e,i-t,o,a,l,s)},n.ellipse=function(e,t,r,i){null==i&&(i=r),n._style.ellipseMode==n.CENTERM ?b(e,t,r,i):n._style.ellipseMode==n.RADIUS?b(e,t,2*r,2*i):n._style.ellipseMode==n.CORNER?b(e+r/2,t+i/2,r,i):n._style.ellipseMode==n.CORNERS&&b((e+r)/2,(t+i)/2,r-e,i-t)},n.circle=function(e,t,r){return n.ellipse(e,t,r,r)},n.point=function(e,t){e.x&&(t=e.y,e=e.x),r.beginPath(),r.ellipse(e,t,.4,.4,0,0,2*Math.PI),r.stroke()},n.rect=function(e,t,r,i,o,a,l,s){n._style.rectMode==n.CENTER?y(e-r/2,t-i/2,r,i,o,a,l,s):n._style.rectMode==n.RADIUS?y(e-r,t-i,2*r,2*i,o,a,l,s):n._style.rectMode==n.CORNER?y(e,t,r,i,o,a,l,s):n._stylM e.rectMode==n.CORNERS&&y(e,t,r-e,i-t,o,a,l,s)},n.square=function(e,t,r,i,o,a,l){return n.rect(e,t,r,r,i,o,a,l)},n.beginShape=function(){w(),r.beginPath(),o=!0},n.beginContour=function(){r.closePath(),w(),o=!0},n.endContour=function(){w(),o=!0},n.vertex=function(e,t){w(),o?r.moveTo(e,t):r.lineTo(e,t),o=!1},n.bezierVertex=function(e,t,n,i,o,a){w(),r.bezierCurveTo(e,t,n,i,o,a)},n.quadraticVertex=function(e,t,n,i){w(),r.quadraticCurveTo(e,t,n,i)},n.bezier=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.bezierVM ertex(r,i,o,a,l,s),n.endShape()},n.triangle=function(e,t,r,i,o,a){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.endShape(n.CLOSE)},n.quad=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.vertex(l,s),n.endShape(n.CLOSE)},n.endShape=function(e){w(),e&&r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke(),n._style.noFill&&n._style.noStroke&&(r.save(),r.fillStyle="none",r.fill(),r.restore())},n.curveVertex=function(e,t){if(a.push([e,t]),a.length<4)return;M let i=function(e,t,n,r,i,o,a,l,s,h){function c(e,t,n,r,i,o){let a=Math.pow(r-t,2)+Math.pow(i-n,2);return Math.pow(a,.5*o)+e}let u=[],f=c(0,e,t,n,r,h),d=c(f,n,r,i,o,h),x=c(d,i,o,a,l,h);for(let h=0;h<s;h++){let c=f+h/(s-1)*(d-f),g=[(f-c)/(f-0),(c-0)/(f-0),(d-c)/(d-f),(c-f)/(d-f),(x-c)/(x-d),(c-d)/(x-d),(d-c)/(d-0),(c-0)/(d-0),(x-c)/(x-f),(c-f)/(x-f)];for(let e=0;e<g.length;e+=2)isNaN(g[e])&&(g[e]=1,g[e+1]=0),isFinite(g[e])||(g[e]>0?(g[e]=1,g[e+1]=0):(g[e]=0,g[e+1]=1));let p=e*g[0]+n*g[1],m=t*g[0]+r*g[1],b=n*g[2]+i*g[M 3],y=r*g[2]+o*g[3],w=i*g[4]+a*g[5],v=o*g[4]+l*g[5],z=p*g[6]+b*g[7],V=m*g[6]+y*g[7],_=b*g[8]+w*g[9],M=y*g[8]+v*g[9],E=z*g[2]+_*g[3],S=V*g[2]+M*g[3];u.push([E,S])}return u}(...a[a.length-4],...a[a.length-3],...a[a.length-2],...a[a.length-1],n._style.curveDetail,n._style.curveAlpha);for(let e=0;e<i.length;e++)o?r.moveTo(...i[e]):r.lineTo(...i[e]),o=!1},n.curve=function(e,t,r,i,o,a,l,s){n.beginShape(),n.curveVertex(e,t),n.curveVertex(r,i),n.curveVertex(o,a),n.curveVertex(l,s),n.endShape()},n.translate=function(e,t){r.tM ranslate(e,t)},n.rotate=function(e){r.rotate(e)},n.scale=function(e,t){null==t&&(t=e),r.scale(e,t)},n.applyMatrix=function(e,t,n,i,o,a){r.transform(e,t,n,i,o,a)},n.shearX=function(e){r.transform(1,0,Math.tan(e),1,0,0)},n.shearY=function(e){r.transform(1,Math.tan(e),0,1,0,0)},n.resetMatrix=function(){r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity)},n.pushMatrix=n.push=function(){n._styleCache.push({...n._style}),n._style=n._styleCache[n._styleCache.length-1],r.save()},n.popMatrix=n.pop=function(){n._stylM eCache.length-1&&(n._styleCache.pop(),n._style=n._styleCache[n._styleCache.length-1],r.restore())},n.image=function(e,t,i,o,a,l,s,h,c){let u=e.MAGIC==n.MAGIC?e.canvas:e;function d(){if(e.MAGIC!=n.MAGIC||!n._tint)return;let t=e.canvas.getContext("2d");t.save(),t.resetTransform(),t.clearRect(0,0,t.canvas.width,t.canvas.height),t.drawImage(f.canvas,0,0),t.restore()}return e.MAGIC==n.MAGIC&&null!=n._tint&&(function(e,t){null==f&&(f=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvasM .height),f.canvas.width==e&&f.canvas.height==t||(f.canvas.width=e,f.canvas.height=t)}(e.canvas.width,e.canvas.height),f.drawImage(e.canvas,0,0),e.tinted(n._tint)),o?l?(h||(h=u.width),c||(c=u.height),r.drawImage(u,l,s,h,c,t,i,o,a),void d()):(r.drawImage(u,t,i,o,a),void d()):(e.MAGIC==n.MAGIC||e.width?r.drawImage(u,t,i,e.width,e.height):r.drawImage(u,t,i,e.videoWidth,e.videoHeight),void d())},n.loadPixels=function(){l=r.getImageData(0,0,n.canvas.width,n.canvas.height),n.pixels=l.data},n.updatePixels=function(){null!=M l&&r.putImageData(l,0,0)},n.loadImage=function(e,t){s++;let r=n.createGraphics(100,100),i=r.canvas.getContext("2d"),o=new Image;return o.src=e,o.crossOrigin="Anonymous",o.onload=function(){i.canvas.width=o.width,i.canvas.height=o.height,r.width=o.width,r.height=o.height,i.drawImage(o,0,0),s--,t&&t(r)},r};let v={};function z(e,t){null==u&&(u=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvas.height),u.canvas.width==e&&u.canvas.height==t||(u.canvas.width=e,u.canvas.height=t)}funcM tion V(){let e=r.canvas.width*r.canvas.height*4;null!=d&&e==d.length||(d=new Uint8ClampedArray(e))}function _(e){u.clearRect(0,0,u.canvas.width,u.canvas.height),u.filter=e,u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()}v[n.THRESHOLD]=function(e,t){null==t?t=127.5:t*=255;for(let n=0;n<e.length;n+=4){const r=.2126*e[n]+.7152*e[n+1]+.0722*e[n+2];e[n]=e[n+1]=e[n+2]=r>=t?255:0}},v[n.GRAY]=function(e){for(let t=0;t<e.length;t+=4)M {const n=.2126*e[t]+.7152*e[t+1]+.0722*e[t+2];e[t]=e[t+1]=e[t+2]=n}},v[n.OPAQUE]=function(e){for(let t=0;t<e.length;t+=4)e[t+3]=255},v[n.INVERT]=function(e){for(let t=0;t<e.length;t+=4)e[t]=255-e[t],e[t+1]=255-e[t+1],e[t+2]=255-e[t+2]},v[n.POSTERIZE]=function(e,t){let n=t-1;for(let r=0;r<e.length;r+=4)e[r]=255*(e[r]*t>>8)/n,e[r+1]=255*(e[r+1]*t>>8)/n,e[r+2]=255*(e[r+2]*t>>8)/n},v[n.DILATE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-M 1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.max(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.ERODE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.min(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.BLURM ]=function(e,t){t=t||1,t=Math.floor(t*n._pixelDensity),V(),d.set(e);let i=2*t+1,o=function(e){let n=new Float32Array(e),r=.3*t+.8,i=r*r*2;for(let t=0;t<e;t++){let o=t-e/2,a=Math.exp(-o*o/i)/(2.5066282746*r);n[t]=a}return n}(i),[a,l]=[r.canvas.width,r.canvas.height];for(let n=0;n<l;n++)for(let r=0;r<a;r++){let l=0,s=0,h=0,c=0;for(let e=0;e<i;e++){let i=4*(n*a+Math.min(Math.max(r-t+e,0),a-1));l+=d[i]*o[e],s+=d[i+1]*o[e],h+=d[i+2]*o[e],c+=d[i+3]*o[e]}let u=4*(n*a+r);e[u]=l,e[u+1]=s,e[u+2]=h,e[u+3]=c}d.set(e);for(let nM =0;n<l;n++)for(let r=0;r<a;r++){let s=0,h=0,c=0,u=0;for(let e=0;e<i;e++){let i=4*(Math.min(Math.max(n-t+e,0),l-1)*a+r);s+=d[i]*o[e],h+=d[i+1]*o[e],c+=d[i+2]*o[e],u+=d[i+3]*o[e]}let f=4*(n*a+r);e[f]=s,e[f+1]=h,e[f+2]=c,e[f+3]=u}},n.filter=function(e,t){if(n.HARDWARE_FILTERS&&null!=r.filter)if(z(),e==n.THRESHOLD){null==t&&(t=.5),t=Math.max(t,1e-5),_(`saturate(0%) brightness(${Math.floor(.5/t*100)}%) contrast(1000000%)`)}else if(e==n.GRAY)_("saturate(0%)");else if(e==n.OPAQUE)u.fillStyle="black",u.fillRect(0,0,u.canvaM s.width,u.canvas.height),u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.drawImage(u.canvas,0,0),r.restore();else if(e==n.INVERT)_("invert(100%)");else if(e==n.BLUR)_(`blur(${Math.ceil(t*n._pixelDensity/1)||1}px)`);else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}},n.resize=function(e,t){z(),u.drawImage(r.canvas,0,0),n.width=e,n.height=t,r.canvas.width=e*n._pixM elDensity,r.canvas.height=t*n._pixelDensity,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0,r.canvas.width,r.canvas.height),r.restore()},n.get=function(e,t,i,o){if(null!=e&&null==i){let i=r.getImageData(e,t,1,1).data;return new n.Color(i[0],i[1],i[2],i[3]/255)}e=e||0,t=t||0,i=i||n.width,o=o||n.height;let a=n.createGraphics(i,o);a.pixelDensity(n._pixelDensity);let l=r.getImageData(e*n._pixelDensity,t*n._pixelDensity,i*n._pixelDensity,o*n._pixelDensity);return a.caM nvas.getContext("2d").putImageData(l,0,0),a},n.set=function(e,t,i){if(i.MAGIC==n.MAGIC){let r=n._tint;return n._tint=null,n.image(i,e,t),void(n._tint=r)}let o=4*(t*n._pixelDensity*r.canvas.width+e*n._pixelDensity);n.pixels[o]=i._r,n.pixels[o+1]=i._g,n.pixels[o+2]=i._b,n.pixels[o+3]=255*i._a},n.tinted=function(){let e=n.color(...Array.from(arguments)),t=e._a;e._a=1,z(),u.clearRect(0,0,u.canvas.width,u.canvas.height),u.fillStyle=e,u.fillRect(0,0,u.canvas.width,u.canvas.height),u.globalCompositeOperation="multiply",u.M drawImage(r.canvas,0,0),u.globalCompositeOperation="source-over",r.save(),r.resetTransform();let i=r.globalCompositeOperation;r.globalCompositeOperation="source-in",r.drawImage(u.canvas,0,0),r.globalCompositeOperation=i,r.restore(),u.globalAlpha=t,u.clearRect(0,0,u.canvas.width,u.canvas.height),u.drawImage(r.canvas,0,0),u.globalAlpha=1,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()},n.tint=function(){n._tint=n.color(...Array.from(arguments))},n.noTiM nt=function(){n._tint=null},n.mask=function(e){r.save(),r.resetTransform();let t=r.globalCompositeOperation;r.globalCompositeOperation="destination-in",r.drawImage(e.canvas,0,0),r.globalCompositeOperation=t,r.restore()},n.clearTemporaryBuffers=function(){u=null,f=null,d=null},n.save=function(e,t){e=e||"untitled",t=t||"png";var n=document.createElement("a");n.innerHTML="[Download]",n.addEventListener("click",(function(){this.href=r.canvas.toDataURL(),this.download=e+"."+t}),!1),document.body.appendChild(n),n.click()M ,document.body.removeChild(n)},n.saveCanvas=function(e,t,r){if(e.MAGIC==n.MAGIC){r&&e.save(t,r);let n=t.split(".");return e.save(n.slice(0,-1).join("."),n[n.length-1])}if(t)return n.save(e,t);let i=e.split(".");return n.save(i.slice(0,-1).join("."),i[i.length-1])},n.loadFont=function(e){let t=e.split("/"),n=t[t.length-1].split(".")[0].replace(" ",""),r=`@font-face {\n font-family: '${n}';\n src: url('${e}');\n }`;const i=document.createElement("style");return i.textContent=r,document.head.append(M i),n},n.textFont=function(e){n._style.textFont=e},n.textSize=function(e){n._style.textSize=e,n._style.textLeading=e},n.textLeading=function(e){n._style.textLeading=e},n.textStyle=function(e){n._style.textStyle=e},n.textAlign=function(e,t){r.textAlign=e,t&&(r.textBaseline=t==n.CENTER?"middle":t)},n.text=function(e,t,i,o){if(!e)return;if(e=e.toString(),n._style.noFill&&n._style.noStroke)return;r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`;let a=e.split("\n");for(let e=0;e<a.length;e++)n._M style.noFill||r.fillText(a[e],t,i,o),n._style.noStroke||r.strokeText(a[e],t,i,o),i+=n._style.textLeading},n.textWidth=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).width},n.textAscent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBoundingBoxAscent},n.textDescent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBounM dingBoxDescent};var M,E=4,S=.5,R=function(e){return.5*(1-Math.cos(e*Math.PI))};n.noise=function(e,t,n){if(t=t||0,n=n||0,null==M){M=new Array(4096);for(var r=0;r<4096;r++)M[r]=Math.random()}e<0&&(e=-e),t<0&&(t=-t),n<0&&(n=-n);for(var i,o,a,l,s,h=Math.floor(e),c=Math.floor(t),u=Math.floor(n),f=e-h,d=t-c,x=n-u,g=0,p=.5,m=0;m<E;m++){var b=h+(c<<4)+(u<<8);i=R(f),o=R(d),a=M[4095&b],a+=i*(M[b+1&4095]-a),l=M[b+16&4095],a+=o*((l+=i*(M[b+16+1&4095]-l))-a),l=M[4095&(b+=256)],l+=i*(M[b+1&4095]-l),s=M[b+16&4095],l+=o*((s+=i*(M[M b+16+1&4095]-s))-l),g+=(a+=R(x)*(l-a))*p,p*=S,h<<=1,c<<=1,u<<=1,(f*=2)>=1&&(h++,f--),(d*=2)>=1&&(c++,d--),(x*=2)>=1&&(u++,x--)}return g},n.noiseDetail=function(e,t){e>0&&(E=e),t>0&&(S=t)};const I=function(){let e,t,n=4294967295;return{setSeed(r){e=t=(null==r?Math.random()*n:r)>>>0},getSeed:()=>t,rand:()=>(e^=e<<17,e^=e>>13,((e^=e<<5)>>>0)/n)}};let C=I();C.setSeed(),n.noiseSeed=function(e){let t=null==e?4294967295*Math.random():e;M||(M=new Float32Array(4096));for(var n=0;n<4096;n++)t^=t<<17,t^=t>>13,t^=t<<5,M[n]=(t>M >>0)/4294967295},n.randomSeed=function(e){C.setSeed(e)},n.random=function(e,t){return null==e?C.rand():"number"==typeof e?null!=t?C.rand()*(t-e)+e:C.rand()*e:e[~~(e.length*C.rand())]},n.randomGenerator=function(e){e==n.LCG?C=function(){const e=4294967296;let t,n;return{setSeed(r){n=t=(null==r?Math.random()*e:r)>>>0},getSeed:()=>t,rand:()=>(n=(1664525*n+1013904223)%e)/e}}():e==n.SHR3&&(C=I()),C.setSeed()};var T=new function(){var e,t,n,r=new Array(128),i=new Array(256),o=new Array(128),a=new Array(128),l=new Array(2M 56),s=new Array(256),h=function(){return 4294967296*C.rand()-2147483648},c=function(){return.5+2.328306e-10*(h()<<0)};this.SHR3=h,this.UNI=c,this.RNOR=function(){return n=h(),e=127&n,Math.abs(n)<r[e]?n*o[e]:function(){for(var t,i,l,s,u=3.44262;;){if(t=n*o[e],0==e){do{l=c(),s=c(),t=.2904764*-Math.log(l),i=-Math.log(s)}while(i+i<t*t);return n>0?u+t:-u-t}if(a[e]+c()*(a[e-1]-a[e])<Math.exp(-.5*t*t))return t;if(n=h(),e=127&n,Math.abs(n)<r[e])return n*o[e]}}()},this.REXP=function(){return(t=h()>>>0)<r[e=255&t]?t*l[e]:funM ction(){for(var n;;){if(0==e)return 7.69711-Math.log(c());if(n=t*l[e],s[e]+c()*(s[e-1]-s[e])<Math.exp(-n))return n;if((t=h())<i[e=255&t])return t*l[e]}}()},this.zigset=function(){var e,t,n=2147483648,h=4294967296,c=3.442619855899,u=c,f=.00991256303526217,d=7.697117470131487,x=d,g=.003949659822581572;for(e=f/Math.exp(-.5*c*c),r[0]=Math.floor(c/e*n),r[1]=0,o[0]=e/n,o[127]=c/n,a[0]=1,a[127]=Math.exp(-.5*c*c),t=126;t>=1;t--)c=Math.sqrt(-2*Math.log(f/c+Math.exp(-.5*c*c))),r[t+1]=Math.floor(c/u*n),u=c,a[t]=Math.exp(-.5*cM *c),o[t]=c/n;for(e=g/Math.exp(-d),i[0]=Math.floor(d/e*h),i[1]=0,l[0]=e/h,l[255]=d/h,s[0]=1,s[255]=Math.exp(-d),t=254;t>=1;t--)d=-Math.log(g/d+Math.exp(-d)),i[t+1]=Math.floor(d/x*h),x=d,s[t]=Math.exp(-d),l[t]=d/h}};T.hasInit=!1,n.randomGaussian=function(e,t){return T.hasInit||(T.zigset(),T.hasInit=!0),T.RNOR()*t+e},n.randomExponential=function(){return T.hasInit||(T.zigset(),T.hasInit=!0),T.REXP()},n.print=console.log,n.cursor=function(e,t,r){let i="";e.includes(".")&&(e=`url("${e}")`,i=", auto"),null!=t&&(e+=" "+t+M " "+r),n.canvas.style.cursor=e+i},n.noCursor=function(){n.canvas.style.cursor="none"},n.createCapture=function(e){var t=document.createElement("video");return t.playsinline="playsinline",t.autoplay="autoplay",navigator.mediaDevices.getUserMedia(e).then((function(e){t.srcObject=e})),t.style.position="absolute",t.style.opacity=1e-5,t.style.zIndex=-1e3,document.body.appendChild(t),t};let A=["setup","draw","preload","mouseMoved","mousePressed","mouseReleased","mouseDragged","mouseClicked","keyPressed","keyReleased","keM yTyped","touchStarted","touchEnded"];for(let e of A){let t="_"+e+"Fn";n[t]=function(){},n[t].isPlaceHolder=!0,n[e]?n[t]=n[e]:Object.defineProperty(n,e,{set:function(e){n[t]=e}})}function D(){n._noLoop||(i=null==n._frameRate?requestAnimationFrame(D):setTimeout(D,1e3/n._frameRate)),w(),o=!0,n.push(),n._drawFn(),n.pop(),++n.frameCount}function k(e){const t=n.canvas.getBoundingClientRect(),r=n.canvas.scrollWidth/n.width||1,i=n.canvas.scrollHeight/n.height||1;return{x:(e.clientX-t.left)/r,y:(e.clientY-t.top)/i,id:e.idenM tifier}}function L(){return n._touchStarted.isPlaceHolder&&n._touchMoved.isPlaceHolder&&n._touchEnded.isPlaceHolder}n.noLoop=function(){n._noLoop=!0,i=null},n.loop=function(){n._noLoop=!1,null==i&&D()},n.redraw=function(){D()},n.frameRate=function(e){n._frameRate=e},setTimeout((function(){n._preloadFn(),c=window.performance.now(),function e(){if(s>0)return setTimeout(e,10);n._setupFn(),D()}()}),1),n.canvas.onmousemove=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPM ressed?n._mouseDraggedFn(e):n._mouseMovedFn(e)},n.canvas.onmousedown=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!0,n.mouseButton=[n.LEFT,n.CENTER,n.RIGHT][e.button],n._mousePressedFn(e)},n.canvas.onmouseup=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!1,n._mouseReleasedFn(e)},n.canvas.onclick=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressedM =!0,n._mouseClickedFn(e),n.mouseIsPressed=!1},window.addEventListener("keydown",(function(e){n.keyIsPressed=!0,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!0,n._keyPressedFn(e),1==e.key.length&&n._keyTypedFn(e)})),window.addEventListener("keyup",(function(e){n.keyIsPressed=!1,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!1,n._keyReleasedFn(e)})),n.keyIsDown=function(e){return!!h[e]},n.canvas.ontouchstart=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.moM useY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mousePressedFn(e)||e.preventDefault()),n._touchStartedFn(e)||e.preventDefault()},n.canvas.ontouchmove=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mouseDraggedFn(e)||e.preventDefault()),n._touchMovedFn(e)||e.preventDefault()},n.canvas.ontouchend=n.canvas.ontouchcancel=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.M mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!1,n._mouseReleasedFn(e)||e.preventDefault()),n._touchEndedFn(e)||e.preventDefault()},n.hasSensorPermission=!window.DeviceOrientationEvent&&!window.DeviceMotionEvent||!(DeviceOrientationEvent.requestPermission||DeviceMotionEvent.requestPermission),n.requestSensorPermissions=function(){DeviceOrientationEvent.requestPermission&&DeviceOrientationEvent.requestPermission().then((e=>{"granted"==e&&DeviceMotionEvent.requestPermissioM n&&DeviceMotionEvent.requestPermission().then((e=>{"granted"==e&&(n.hasSensorPermission=!0)})).catch(alert)})).catch(alert)},window.ondeviceorientation=function(e){n.pRotationX=n.rotationX,n.pRotationY=n.rotationY,n.pRotationZ=n.rotationZ,n.pRelRotationX=n.relRotationX,n.pRelRotationY=n.relRotationY,n.pRelRotationZ=n.relRotationZ,n.rotationX=e.beta*(Math.PI/180),n.rotationY=e.gamma*(Math.PI/180),n.rotationZ=e.alpha*(Math.PI/180),n.relRotationX=[-n.rotationY,-n.rotationX,n.rotationY][1+~~(window.orientation/90)],n.rM elRotationY=[-n.rotationX,n.rotationY,n.rotationX][1+~~(window.orientation/90)],n.relRotationZ=n.rotationZ},window.ondevicemotion=function(e){if(n.pAccelerationX=n.accelerationX,n.pAccelerationY=n.accelerationY,n.pAccelerationZ=n.accelerationZ,!e.acceleration){let t=((e,t)=>[(e[0]*t[0]+e[1]*t[1]+e[2]*t[2]+e[3])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[4]*t[0]+e[5]*t[1]+e[6]*t[2]+e[7])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[8]*t[0]+e[9]*t[1]+e[10]*t[2]+e[11])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15])])(((e,t)M =>[e[0]*t[0]+e[1]*t[4]+e[2]*t[8]+e[3]*t[12],e[0]*t[1]+e[1]*t[5]+e[2]*t[9]+e[3]*t[13],e[0]*t[2]+e[1]*t[6]+e[2]*t[10]+e[3]*t[14],e[0]*t[3]+e[1]*t[7]+e[2]*t[11]+e[3]*t[15],e[4]*t[0]+e[5]*t[4]+e[6]*t[8]+e[7]*t[12],e[4]*t[1]+e[5]*t[5]+e[6]*t[9]+e[7]*t[13],e[4]*t[2]+e[5]*t[6]+e[6]*t[10]+e[7]*t[14],e[4]*t[3]+e[5]*t[7]+e[6]*t[11]+e[7]*t[15],e[8]*t[0]+e[9]*t[4]+e[10]*t[8]+e[11]*t[12],e[8]*t[1]+e[9]*t[5]+e[10]*t[9]+e[11]*t[13],e[8]*t[2]+e[9]*t[6]+e[10]*t[10]+e[11]*t[14],e[8]*t[3]+e[9]*t[7]+e[10]*t[11]+e[11]*t[15],e[12]*t[0]+M e[13]*t[4]+e[14]*t[8]+e[15]*t[12],e[12]*t[1]+e[13]*t[5]+e[14]*t[9]+e[15]*t[13],e[12]*t[2]+e[13]*t[6]+e[14]*t[10]+e[15]*t[14],e[12]*t[3]+e[13]*t[7]+e[14]*t[11]+e[15]*t[15]])((e=>[Math.cos(e),0,Math.sin(e),0,0,1,0,0,-Math.sin(e),0,Math.cos(e),0,0,0,0,1])(n.rotationY),(e=>[1,0,0,0,0,Math.cos(e),-Math.sin(e),0,0,Math.sin(e),Math.cos(e),0,0,0,0,1])(n.rotationX)),[0,0,-9.80665]);n.accelerationX=e.accelerationIncludingGravity.x+t[0],n.accelerationY=e.accelerationIncludingGravity.y+t[1],n.accelerationZ=e.accelerationIncludM ingGravity.z-t[2]}},n.year=function(){return(new Date).getFullYear()},n.day=function(){return(new Date).getDay()},n.hour=function(){return(new Date).getHours()},n.minute=function(){return(new Date).getMinutes()},n.second=function(){return(new Date).getSeconds()},n.millis=function(){return window.performance.now()-c}}(e)}"object"==typeof exports&&"undefined"!=typeof module&&(module.exports=e);const t="https://ancient-crimson-rain.btc.discover.quiknode.pro/c268fb026303ae8443f785200f2ea4b82f0082dd";function n(e){P(e)?M localStorage.removeItem("blocksApiEndpoint"):localStorage.blocksApiEndpoint=e}function r(){return localStorage.blocksApiEndpoint||t}function i(e){P(e)?localStorage.removeItem("modelInscriptionEndpoint"):localStorage.modelInscriptionEndpoint=e}function o(){return localStorage.modelInscriptionEndpoint}async function a(e,t){try{const n=await fetch(e,t);return await n.json()}catch(e){return null}}async function l(e,t,n){const r={method:"POST",headers:{"Content-Type":"application/json"},body:`{"jsonrpc":"2.0","id":1,"meM thod":"${t}","params":${`[${n.join(sep=",")}]`}}`};return(await a(e,r))?.result}async function s(e){const n={avgfee:10,time:Date.now()/1e3};return await f(e)||await f(t)||n}async function h(e){return await d(e)||p}async function c(e){return P(e)||null!=await f(e)}async function u(e){return P(e)||null!=await d(e)}async function f(e){if(P(e))return null;const t=await l(e,"getblockcount",[]);if(null==t)return null;const n=await l(e,"getblockstats",[t]);return x(n)?n:null}async function d(e){if(P(e))return null;const tM =await a(e,{});return g(t)?t:null}function x(e){return"number"==typeof e?.time&&"number"==typeof e?.avgfee}function g(e){if(null==e)return!1;const{classes_name:t,training_traits:n,layers_config:r,weight_b64:i}=e;if(!Array.isArray(t))return!1;if(null==n)return!1;try{j(r,i)}catch(e){return!1}return!0}const p={"model_name": "pfp_classifier_421", "layers_config": {"config": {"layers": [{"class_name": "InputLayer", "config": {"batch_input_shape": [null, 28, 28, 3]}}, {"class_name": "Rescaling", "config": {"scale": 0.007M 84313725490196, "offset": -1}}, {"class_name": "Flatten"}, {"class_name": "Dense", "config": {"units": 10, "activation": "tanh"}}, {"class_name": "Dense", "config": {"units": 20, "activation": "tanh"}}, {"class_name": "Dense", "config": {"units": 20, "activation": "tanh"}}, {"class_name": "Dense", "config": {"units": 18, "activation": "tanh"}}, {"class_name": "Dense", "config": {"units": 17, "activation": "tanh"}}, {"class_name": "Dense", "config": {"units": 4, "activation": "tanh"}}, {"class_name": "Dense", "confiM g": {"units": 7, "activation": "tanh"}}, {"class_name": "Dense", "config": {"units": 9, "activation": "tanh"}}, {"class_name": "Dense", "config": {"units": 4, "activation": "linear"}}]}}, "weight_b64": "D26SPH/PBT0AN/48bvZDPWBbazwukaq8rusLPLiMmrsIFSm9PY9aPJ70Ob1fyHe8ojW1uv5D5DxIFoe8dzLovNtRRDwIbK28ERGLPYUxXr3dJYC8/W1YvYV3wbyLiZ+8lqlJPd3jBj0Kakg9qJjYvG796zynBUS9gDUVPA0+ej3jge8834XSvDGwUD1uHsM6cCitPTk1Sb3jLgY9/EkzvTqbSz0m9J882r+ePC5MxzxH2829IvZ4PWVN/LxQ9fi7L8VHuni+8juIOQi9BfdYvai0QzyoLKe8+xAPPG+0Lj3jfbY8840nPTqwM7xBkM 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 a+9A0yVPUB5Jbz3AZS8mr3LPGr6PD0cGwq8JXUYu+YbwjyexAi8fnVgvcmQa7tlqRS8q6K3PHL4JrxipZ89cbCIOw2TeLxEdJI814ELPT0pXj0vnlo9QVSLPTK8Szvo1jc99/y9OxA0MD38loo9slMWPWDCRj2OiA29JSb7PPuZrDuh9jS9V7yFO/pDPzvTrK28dyEhvSBMfb0bvAm9k16cPAaBfTpAz6E9L0gkPcXFUj30Dom8lq4DPHVSk7zUdqs8oKXMu9+scz2kEZc9LGwZPZ7xJbzylIg9XKgePTuCmTzsaIG8XVWAPTXmfj0/HWO97xRbPT26Gr1gM6W8sDUUPGV7ZT2RhLY8VJSOvBStBL00x8+6g+cGPXuwpT0bgQc9JnN3PBUmgT0XD4q7fGFJO3lpKjymmRK9G2MjvUUw0Tvh0WU9OxOvPWggVj2TwxC8Yi5oPA5Serx0Pgc96mB6PQ7QJzyi8cO9yFP4PKYgiTvhlS69jOyHPTKjMbvu2229QHNhvM 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 ZyXrjwokAs9CIyIPW5OQT2wyA+9lukwvXC56j3/Ztg8XURfvZ4Ggj1ZOeO7fkzJuy+IAbzcqB89u2FbPQJM87k/zuq8wgvgumGePb144sU9PniXPIUUkz1FFmi9nQTOPVfJm70je0S9FLcMPZLZGrvIVxa9Oi9PPPTpnL2AZke76U0YPWo6GbvVpD48Wj5GvaYtIz29VR47hdrePPkGTj1Tlje9gJhWvaGHfj1IJko8FTglvb4WRL2gXEK9WCuFvPpiFL3szec7rizmPBcWiD3gHkG979nFPVdUtr0GdB+9X+EXPRHmCzzMvpK8VPT6uw0wF72UNZo8kp0OPdn7uLtayJ08E5vaPGvDRD2ijFI8F1VgvY6/krwSIQ29LHm3OrqMKT3qDNY9WpgHPRgKjbxSUgW8vk4RvP83IrzyYqW8yN6euEQukbyzZPe9h2IjPafXuL3WW+O80yiOvAjEQDzCohK7Y5z7u2+0JDx5BBi9U+LLPI0P6LxdXRi9dhGLPQOFpDzRKM 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 B2zFj34LSE9IfrSPIkofz3VmxE97+f/uk3PCL2bhrK91P2kPVoK67wrpPM7s5K8vC09gbvw+qU8w36wvQc7KL3rBnm8yALju6/bPb358Uk9soZWO1vAcD1wphK93tSIvEUdujyhYv+84WTevEoRgLwczK09UD4wvEE3Q7yfYCw7McyovBD+ejvn8Dq9OLwSPdO0BT2W0b69//kaPWZYX7yUd1O98oL4PDAf8zwjOlS9K8XGPPEXtL0I3lG92u87O4YPNj2805w8YhFpPExji7zLmA49zSQfPdKaDTwR03i82We4uwLjrjwguKY9ZvFhPPj9tbu79ci7GEEjuwRPHTzFq9Y8Fw58PBirhjwLkba9HkSBPTiQcb0i+xQ7Vp34vFjvOL2JzAO9K0ulPA1plbysHys9pQfIPZ813jzQqzK8of6AvA81RD3cAYA8Em+Dvf0jKz3cSqm8tULoPOIEuzzMOIE9zDZeO1tDh71WahQ9AFnhPLkwmb1nPDk8mPtuPQWhrz1kbM 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 S9+erzHEwY9bXHQPJnz77zAQlm7JtBCOvcKJjzZlGA9Gp3mOwpi9jwvfu683h4LvEbGe7s+kAK+3YNdvVEmGL1wyw49UHiGPA+IOL2ZMJs8diCWvP8ikrs2njK9492vvWvpNr2l8GI8xCFzPRiRkrtgsZ88QewNvJncTr0JxOU8crc1vA71AL6Dpau9qJ7DPG17pDwIzB29X3ZevaGp/T1MPsq8VRyxPBwoiLvaH0e9yndfvXlY57y+2VM9xsTMu0lptr185O493tH+u6X2HT36iH49r10SvvMesb3IjaU8uJdeuueVmbyxWtS80f6dPa0VHz0b1Gk9X00qvJWHI71EBZ69nKyuPX61wzxNIby8VUOJvXxtLz6IV5s6PV0fvAfFxTstqsm7tVZxvZu/Wb0Ish688GZUvMp2z72s6Ok9UBQ/PLq3hz3cwj09Mw86vY9veb2rxyg9HdT9vFlaPb0YCYS8mY9yPYQIZL1D0aw8se8nPCfzr7yYuam9TrijvBraIj204M 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 G1u77zOy2I98o5+O/USOzuc9J680qifPTWOFr0x2Ee9Np2iO5QXtDyH0qm8qJYSPNewGLz0NJC9/C05PPRUlLzVlVc85bASvPTY5rqSwNU7JFUqPaddRz0mQRk97XCEvYZAFL03FY28Wgo9PQPk7rxw1G49QI2NPOy9x7yaZVw9lGELPflGkL1zuWC7+Ra+PQUCmj2dM369WlzJOTRELb0tdU+87Z2WPceAoTxfDKW9n6SwvJs4PrySKkA9u1uNPDK6kj04F4E9aLonvYI/QD0Gw4M9Z57wvJmrV7y4PmI97nK/OShxDD0Y4/y637gNvXPYR7y0d5U98moGvAalET3YOL48C88ZPQEAgzy8bdS9BChAPUUS1rxPaBu8Yu7euq/x2rvuxSW9IcpxvWp/bb1UTAm9s5EGvXdqnrxXg+48tr6vPF0rPL1kday8ewnEPJ4EzjzHLAq9IAnBvKVGDD0/eD09BmBpvRfE5rxk1iq9Fe74vJoMPj2eXrQ9GgkFPRDEnL3PiM 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 XRDNr2RUXa97lX2vWnq5Dv+sJY8R5nmPNNkE71FMMw9qTM4vhYwqT0PbKQ88vukvedf2L0+bR88ooqKvDcrk71Brge9mbYZPfZi0b10rrY8LGpUvPO5r7yoVsC7IkQ+PJ0tFb3YdpQ9ofCIPBnYBT30tQG+bLAtvf7gHr29+Qk88P5jvb41izxQ8gc9tcEJPbi4Mb2SPDc9F0HYvXfmHLx/c2+9xqzXue8vpr343IM90VCJvAx75Lq1oXi79MR2PX8YH77ZQAC92HBdvZyDmTwey928ZM4kvbPZ+LwDKMQ9M7JHO+XjxTsZIMi9lW9pvOosuTy7xgc+wBIIvOuFAb1nzRU9bqnTPaqaHzsXNbE8bYQIvijt9zwvOPs6GOd6PORMpzydUo68bnQCPPh7bTz98xE7+LhMPAsUvb2dNJA8Yp09PYON6jt+ip28uRu1vM78oryRuWk9BXAcvdH9kDvfv5y9K5OKPRVvjz3qkCw87CIzOrl7SrvUNJA96gKYPZZ4/jzhdM cY83ssBvizqJjxeMMY9i656PZC7Oz16uFm82AdtvGpcGD2QGwM9ZHYyPSRUO71KD2c9fibSPflS0jzxc5Q9kxV5vLcrBT6IN+Q7dZ6ovdWshL1Lka+9YvbJvEvRtDytRjW9FrnDPHBKurznQjQ9bKlMPPAxXzvCB2g9OMl6vX7AgzxIDjA97AW3vGlZTz1n4ME82OrCvOdRgT3VE4u73ZLvuhBJur0Ijwq8AehjPaZP+jv98249+VgFPU+2nj0d0rO9c0c6veQpo71vijC9qY0+vRqP/Dod5LK9qI06vQzQXz1SzSA9KNJlvW3HZL2ctKq8iY4rvYjx7juPK5o8En19vEQbfTyqeX88cX6PvIMlzb1eyqm8ioNLu2HvGr0iasy8iWFoPKHOjTyhMZ88xHXlPOuipD1Ezn288EaqvGhafTtVUpc9IrxfvMfOOLswoMW8zu+OPZ92bz3J5r09AnaoO/MnXr2cWIW9vbMlPZiHmr0TIgA9fs+yvO47NDzmDYI9/c07uM 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 ZXDG73PpOY8TR7Hu2BCDL1NK5A8Qx7NPCqHwbzjm6W6nMOcvPENvj2qw+k87cJyPbt4lD2tzYi9kF06vVN/Nz1T74s8ZrqQvR+Sk7yeWSA9S8KPPfDmODqeiT89byOlvdfCpL0pX6E8M1E7OoNuRr1TGgs9JeM0PW0/CT3T2So9CypgPJjWI73HhX69z7qru5EqeTwMogS9dvs1PXVt4D2f3iw9mdCtPDZyFj00Tmy9XPQuvbmo0rzGXEU9zgUJvjBisDm/sts9EzXGvUxL7rzVqBM9p5OIvVb8HruuejS94a+TvYOUt71cXWA9cfOwPZw5kL3gyc+8Q/3NvPAEg7287Bg8sdYgvemPtL0GDv+92gTHvIgRTj0znKA9b1Phu00Jiz22u0m9pHsguxs2a7xBqCM9vNJEvVhnfr21uIo9zdWfPXVhNr1r56o9s/Osvaf/aj2PLPw8rq9FPWeWSL2CJSE9gUoOvNNhw7x/zLW81DGxu/2Y3r2nxg+9TjIuPCxFH7tvrM 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 BFAAjzDUdS8FlYhPd/QyDw2/YC9GH1TPZatkbzXWCE9iujrvd2zWz0NSF89xn8KPe3Kd728b4s8BaoTvdoJsryscPk8tFcOPUlb5r0pVO+8JpByvR4ThT0JOl29tAfiPe6ty72g+5G9SrPEvZPoM72V9sG9r3X8O5CWeD0sTJ284LDYPUYgELzHGJe9tqF5vB0RVb3mpIe5LB4Vvghj5D3bvqc7BTSbPRNkbjta0SI9TXdSuxV9BzyJ0u66WF14PYzZB75co6M9ALj7vNhxwz1It/W8fkjBPf4Nlb0jFwq+gCFFvUxJnb2nLZ69PptWPYmWfL2wj1i8cloXPSNyIz2VzSO9dVuBvWeWcb2WPPM8O/Eovpg3CD3XvTq8UCTAPOrknzxySAc9atUnvPRfwL3N12O6lGmVvMrqAr5y3K+7Eb/6vcIqj73ES509RJboPKKUAr1CvgC+zH+zuyOeeT2/skS9Y31NPXxOk7293uK97tIrvZ5Ugz26PA09XGIsvb1PzbyLlM 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 ZerlT2xiBQ9yo3pPJhJ672XbCQ9g6zMPB5u6zzkEog9opocvZ4UAz48+ag9kpkTPXDgPj0wVsW88uQPPJzQ9zwthbw8kof0O0odOrybrt49h7LJPeAF4rw3j4Q9a/SivX1R+TtLgJc9wvZpvPVrxz3YZVG9DNzFuzN3iT0Sgfk8ATDnPNy/lbxJawQ9UtvZPdFGx7xF+lU9rw89Pbg5IT1/gje9uOo6usr8Zb1PHj49BhLKvJHpfDx2HZO8ny5bPNJJejzf49E9kv0NvQsT+TvDW7W9dcoYPfMM1jxlTEU9pvCRvdnLrj09fy05ziEwO9SXqLyC9ou70HzyvNHCljypX0U9K7Y3PEBdHr04BXY9k+y2PLSKYDyyR6u8SCKqvAKdz7sftg09OZUFPTkn7T2tdoa8TzilPTNyS7wSYAw9Wf8XPa5YoTyZ2ta9mrgcO9+3fjxqUC89+Y42vDDpMT2Hk1C7KB+JvUeZQb0WWhC9WgfOPCeZhzzdy4c9oXGpPLWoyrxS8M 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 bUFZL1QQpi78XjNPV12zjyt8H+8APk4ugiHIz05WVW97jtrPG2aszwhLes8bg1XvZCAjLzS1088LifVPH5xhz3eiNI8KDguOwvRkD1Z0mI9nCGJPEaDrr0qFYC9OOzzvEdYhL2d7Re7iBGHO/L6w7tkmYI9WbEuPSgthL0S7rq9rzjYPNcxh7wh5c+8UTO7PGrjSTxvFC+9yvxevA/UTD2AGcu7PIhTveyEc7yYNpG7EcliPUAIgj25BCo9bbEUPeH/kj0tFkG8b40Gvd3NYL1gVTq9wm6rvDXB5zzbvYO8TmrivOVpUzwZtCM9gD2gPDfiqb1tRVW9ltNrPM1o/zxKAz49nosJPbelMz0JFig8QeAqOz2gkLspZ1U9juzguwCuEDxdb3q9aDgiPWh3h7xQfxI9uM9UPYPvIb2GhcU8eoxNvBdImD1DWWu9KW5JvWvs47z87Xg9l+Y4PTkFPLwi2R69OF2UPHYLTzzpR2m8wVQdvTcgVL0ypqM93TyCvNM/kj2F2M 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 bO7bi6DvLuTjD0KaxA72efcvaW88TyyHa28CWtkPYjo0juCLei8VjuEPAl1bL1OFKM97b6fvDQQ7Lx5eMC8cSWxvJA3Try4qwc9q7u8PL4mjj2c3jA9q8GSPbC7Jb3LS8o8E98zPe631rz5uLe7zHqLPdE3mzxoVxg80UonPCGsFr3wxhk9wA48PXffwjxuq4y9TgylPIV88LynVSo9WAWtPCU6Tb1vfb89PjE+vYNhD7tpT509IEQ7vbg+K7xaqik9ItfFvNnlaz1sBQq8Tu2FPZPsTbrn9jQ999vgvFJu3zyupfE8zWCJPWGChTr3Rcy7pzrXPOKEgr3OBrM8bdmrulBPhjvLWiu90juHvH8Elr0kmRw9U4GDPUlOILokceU8z5mbPHrVEb1PfW48j1PrPHL6YT0PKwc9J6pmPFHUFz1rvuI78wyMuxfn8ruTcDM8XCwtvXzhqzxw7ow97ouEPN2UG7x6CJS9b8tqPa7yKb3dXWY8GXxxPKnMt7yHiw+9Tt+3vM 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 Z07N3KDO40VXLxYQDA9z3GzvGQlljzAjkQ9L70xvNU20zzYIqy8qsQHPbj/gj34SRk9GqWJPTEEpLwioHS8RUY7vK+7gr3c5P28pXQuvcTdhj2h6X47pnpiPAGmV73KANK8tXuWPGWF4Lqin708EnqdvH28Kb1bsQg9dldqPXfLOj3dcj09COobvalCr7xWexQ8XY/dPSl6kjxmUJq8Vo10PaosQzqffpo7HtQiPQ18Er20k3W8kAGcPCeop7zaJ/M9jrw+vB3UXT0nM9o7aaW5PA//HL0pJqa9P6+SPa2YIz0SX409xneyPSFjDT32wAQ8+CPhPFjx7LugzBE9sXNHvWKSjzpWRcs8zv/KO+M6MD0MgtA84ZgfPcywaT0QeIM9FLOnPKRXSr27D7q8pKT2Ok6ySrxpq5c92X9QvXwurbyLdss8zkFePaVrCLwK+Mq7AaeXPRVaHj0IwZO7bSfUPFbaiL23lty9WKHVvC6mAbs2hM27wzRHvSBi+DyPgtC8wqx0PM 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 1k8ObLQvH/Hqj1ovQ49rjwFveeBojw4Syg9VTeSPHZLujs4gLy9j6ojPWEVojyJ56Q9OXMWPO5hc7x5sVO95RA8PWKXKb0X9sU8sdw8Pcw/mb1VdaK9DyAKPT+kbL0w0ws90JU3PURr/Ds2GDg9RIrCO6wWWD2pwhG7MeUDvfiHy7uuQqy6Xn0gPCqroj0EKW686S75vGb4kjwqZdw6RF4tvIq2CL12fKs9gRzCvG6c8Lx13we7/KdmvWhBJb0T9hk9khW7PdacBL0Acay9AyEzPURURj27xos9vzSCPcY/C712ZRE90e89PUla8T1apHW7oKIPvYiROr3296g8W0i9O0Oihz12m608TMQXvXC6vrv/CDg9DQdovSXNZbwVGeM9IMc1vAo9Fj035dk9A9SWvfey9b0SJ7A53CtpOyvVK725OA29oxXxvBKkBrt0PuW9ZNuKPZ9C0TyhQPC9PFC3PI0yM7xwzXo8s4r3PAsi4Tz2cX48nfO+vUxkEz4yUWs9SQ39uM 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 A6++bAEvcHU+LxBrgi9wFCXPNwPKby/w0a9dq5KvVuCur100X09kmECPddm+7zZCBe8YxsyvHdXPz0bUim8lpZVvFWEuL0YKbi9Xkq5Pd+eSz0qnN+8IuZaPbIpAD2FXdI9nqqgvLYBWL25JIk9OEa3vLDVrD1v0R69PRddPeq55L3ON2a+DTIHvbtF071Qnhk8c+axvRSlYb3GtT++ciUUPmwyIT2lBc08e9hSvsYesr2hNCO+vOwEPs3Zub0qKZ+9ULfpvR3MzT13Xx49oC0dvaSTL74K6Ae9lesDvp1AzzzxTAG9j9CGvfwcALzuuYY911yOPcW0C70I6Uq++ynAvd7fm71tENg9BlkQvmCVrTcg6rO9Xo8fPBoFqrt/NM07NZ98vuVs2737t+q9w+X6PeuVBL7F5XS9F+0Ovlq/5brE4Tg9mRX3PGVYML7VhpW9iYO7vWdoojwAHju81XnWvWQSHb0MELM8+YjWvJF+6b1ar669LjTXPOLTl71kM7Q9ej3hvM 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 D0OID0mC9y88r+SPej8wDxsS2i9OKRVPFUn+ztmBOa877EPvX7HaT1SDh672UdOvSKvUbyhX2I9X88Euys7LDxsvSY9n4G+vAHkuDyIpx09Tkn9PA2xczzP2Ai9tzpcPbBkabwffAE9825dvcToMr3wf9Q9mK+4PeQVpDx0YFG9kVfqPMklUD0v7nm9tNMEPe5KJL3Pvo295+2QvPPRLT6lr/g8Xd0IPGHFjT0aSQM9Q5dwvO6SAb0z/1S9CFq4vV9O/7qfxxY+CYCmO2cNhLzWqOS8746LPdiV97xujri8wYmqvYDmw70gUHw9KbLfPTDCDL0wbUO913ixPVoQsz0Re5C9ttIBvQQrIb2Fom69LCWSPEvW+Dx02Ao9h1WHPaQDYT3ajUA9KCKKPaiW77wGL3K7cPdkvfDWEDyrwoU9hTuPPNtBMj3OkOa8pcpAvF+fmD01IVm8uGhDPL3QQL3aZlA9W0ZxPTXAQzxASgo9VsRaPDiL9rwy/Dg9UlSTu5QyGTwb9M 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 8C9gwfiPN6ZYz3S2129ooNfvXt2nT0Z6Lu8niwJvQkiXru9FUS82LsevR1U2z0WU1498iKYvS7/ML1C5zU955K7PCcJAD1CZPu8o5W4vDA9sru+QxC9F6eVPSmQtDz3RgE8XkwtPAuWrTzStj894I5YvbgASDv/U5a9rpc2vTFR57w1TyS9ncBnPbzLHzrV1vu7pCNbPD1G5D00StE8WiQyvU/OiTxzH4e9NnnUu2PAh7x1dyM8VLtbPG4PEj3hUI09SsyHPei8ozqPCbm99AmXvUvznDspHW09s+EevIo+Ij3zx+s9CuMrvKjFZT3BC1y9nyfuvek5zLycugk9Vn69PTMJIj1Ekxm9JiSYPVDtED2m5yk+byCAPYj48L2SMC+9uCMkPfMCgj1GxP27joRKvfjCoT1jVOI8gT5WPqgpaD0ENOS9SkvUvQ5LnD3cjgo9CHvFuyF+g705rDU+0LZAveuJID7gOZ67sJ9JOtjUiL3nV069+uQ0vGlPCb0F70q9oxqXvM 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 E28Mu6mPdcF8bzLgjA9qvkyvZThL719hBI9WISUvRPqN73dLR29RFIWPQzPzjxgCI49a+RmvNS5Ob3YZzU9Or89vK+MdT3w99k8se1APXsgF7yQIkI9aPJaPYL4l71+PVK9Xz/QvTTN2rwamII8IeW7PHoexD3UgUE9YmdBPfIgS7y31Do71B0mvbYcsL3Pvw29UbAAPMBhmjz6KKM8JQIzPXNcSLr3PHk9vXWsvGbqlzxyuFa8eiGnPDgFlTwM6KW9Xu03PZVJGz0sZCk9lvE5vaCfAL6+TjS9HsAdvQBAdz1VzTo85DkTuuAZ0jxr7Ne8A2ulPRpd073RwdO93jMSvuZEl7yqWFA9KlYTvXFfJ70L1AE7VPQqPQPyMjobs2u9v251vcCeKL7wGYu84nPVu1TBAj3XeX69qWbGvMBZDL3slKU84anFutfSM71vexG8NFKKvNM1uT1wfUG8Zhd3vU9KmL1CDq+9F2liPQ06n7yB3UW8/7CMvfo+Gj0TQ509BsckvM 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 erw07rjFjy89lNJOvOIqTydmtm8OiiIvRnxmbvuFpi9yYV5PMwQCb2ejSE9zhogPcdvSz3JQJw9j6/SvLJ2ib0wax+87Yd+O7m2DT1oyWg9kaYGPcTUH7ooaCE87apBPc+eKr29oa+9FT0PvaVaKr0bcKA8mjorPedjVz0U3CQ9Ryo1vTCIRzx9NbS81ZtLvNsfI72wNGe8L+szvYcwhLzqPqE8CHUuvV5DhT2PPdI9o5cDvTT5SL1hW/U8sS2lvP57Dj3rD4i8wiyhPS7jdL2kGoS81EkbPMjnAj3VNxu9EmryPN0ZcD1EaKI6gODsvFFUrb3AW3m993bFvXQBND0EpCU9oscFvNnIZTxcFUc8MPUgPY9qZr0yCYE7WYBVvcxkh72X8YA9z3vAPKW1Qb3+58Q8XWQwvJ1uHb1EgoK9ItzlvGFwjL22k5m9xA0kPS3SEj67HDe9NVvcPJaOJDw3o948tYKGvLQ9ob2ca7O7k9KHvVQuFz38dbE95d6tPG21kTz2cM 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 agJt7xv/8a7Te86PU2akz0E1c075/KKvQW1S722UYW9EIA/vcVInD14PSG9iSJOPeMdU7207ck8p62TvSXwpr1yI169fUuHvBt9ir2xnru8klRnvFhN9DyxYP28mirvPBCftLySYWO9NuBNvRMAx72G4po84o7UPFDpU7wYqKw9VDYTvbjYzj17m2A8w6DOveNphr01bou8zpmkPJw3RjwisVM7+oyaPB5KQ72NaF49cveGO9lXpL3Mfcm8TfmPvUHrrLyrSzc9pLwrvHQv+TscYfC8LIxPPGzZ6LxShLS9cErtvVwhXrxixFs9j6XGvMy8+LxL/wS9he5jvX2NzDwGZnW71t2tvXEEpb1oZE69bzoVvQFw9ztORog8Ksu7vBjZUb0zGgC9vDkbPYBtZLZHcs+8JPQePRpLzDygebu8lHejukP9YL3VDou92LvJu+1hu7zR/w09d3d5vN4YHD2rQME9st8oO0loV719lhU9b/qBPHcUlT1W/C69KJg4vMoziL1yDM 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 WA2UjycAcm8zzcRPRZGDT0EmzQ8zhXpPOWHkLuT1LK9sUQkvRO8nz05hN48GCRGPRMpPjxbS+68o/ytveYHjL2JeT29Y4P9vMyjOb1Iuha9yztmPVtMYbzxRVU9V+0EuxtKw7xWy6e82HkNva5KaL3GwDY9NFX7PNb3C73fMtW8ISxEvYLoHD0Taqg8rGmsu7e2t73pvT+9WKZBvWdABzswTf68vmWGPTTGODz0o249TdKxvdlTAr5YL2o8ElxmvbBRBTvFtRa87XU1veYCCDwhggo8j8S/u4A/M7383Iy97Iq/vECTfr3Q/Ai9h/T8vN6JmjpFZxA9PCiWvKtukzxddZO9CAsTvXzdnb0jGxW9Uq/+u9VwFbtuB6+9NJ6Zu86fnTuTPRI90h7zu10kB776G0S9vZZAvfYTbj1x1so7IUJ8vTUGFjyKmCc8gZOuPLArwL28E/O8JMUavVezHbyZbQY90kb1umg/ir2y/we7hRoJvXdxyz0LcFi9P9rSvbjNGb5kjM 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 fK8Tb0wwZa8sGPTvKcGAb32gZO8ngzQPCmcDD1I7V09vD0Ru3AuOrzNY6E8nq2BPM0wA71zp4U86SGHPeE+Zbx+jqW8az83vJXTyLzjO669GDDvvHmYKjy24KS9/ne2vOjA/rtCevE8/exmvFYJ9jzbO3A9knS+vRegNb3p31q9eRO5PJHIirwGeD09gWjyO6EJ3bznXSU9101ivNSSvrwl4Oc8r5g8vYgfhbx2Enw9HdF/PCMvubvpba68abtsPNd8Fz1IaZ+8mwFWvRzhQ71jt5M8Fl59O0WRJrpcQQg8ytEsvS5klDwjthQ8EHuuvTp4nDrGADm9isIFvCIJqTysaWu7FGQAPExRtjxnaGq8hXUaPUxxOrx/i6M8z9wWvakalDx+mV09JNvBPLELdz14ghQ8So4Iu8+emD0obsK9HWl4veOJgL2afpa9Y2UPvEqbTT3DCaw8svkzvNOzKryYWCU9yiGUvRa6hr2P5JK8Hy5NPWHmET2zeYQ7NjFJPCrPGb2xpM 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 sO96YCEPLJhEz0ocKc8RaOFvLRnujywdYW888WMvZixq71GCHS9PxeOvaPShrxqdo08pcZmPObiS72ajwg92F6SvLLrz71kSrC9ZkTSvWOlILwkMmO8OuCzuBuCS737y868ERfkPIdhhD0wnDO9QPAhvdWrUr2CuRS9tT6ZPXS3oz3Azs47QloqvZj7Jj1SqFK8r6YqveHw9ruMuMK8s9ptvYtl0DvF9xe7rGGsvG7g9brAfuM7js+lO8VOlb3nVGA7aHuGvUylKr2/kog9SqF8umaHADzuFxO9Qo71uktOuz1Qw5O9UKzPvTaA4L2GcYS9Z3k5PZrlELyKWLS81t47veOVRT1+6gA9j0LtvABiHb3ADeE8RTQfPONgkD30c5u8CA5Qu2+7m732inq80N2qPL7lrrt0UvS8UWF6vVJhTLxOxNM7sctYPfC2F70r+5a8OT9zvFYHjD2fUU+9ahuSvTbdE71+6SO9nuFQvaBvDrwK5m28EiAbvSsdYT2ULRS8CAEQvM 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 UiU+zvGgT69LjiiPTg+xD3rBYK88W92PXKjM71MZuK8aqUMPcdawD1BeUc9mo0uPVsKAL0h35Q9AUHpvIDLkL09lcs8gxWmvXoxDT1FFYI8aoznvIJVFLyvJmO90RfaPLNpp71vxUS99gSrvSHEgLwH3/M8UIbQPC3uF72W7FG8vMThPNcPHD1r2Ju9vu57vZpH57yLFJm9w0LCO1JPGj1oLyi9g4dJPAceCL3gKo09ZVdfO9cD+ryQXAy97uHevSFkxbwp7Ee9TPltvJw/ezx+67g8XUe1Pc+eobxfApS7JHHVPMEvSb1MJOk8KSBevD/L9LtRrma9xSvnPJXmebuyF+s6AX8TvUDm8DzuGdG8HB3zPJRhwzxOC4y8nXnhOwTx5Lzp/U08brgxPSZJGTzR+hW8UAMrvcyv8zwS1C69KDqruzEhabuxsIq9QxxbPRDb4TuxWDU95tp4PLs5ALzSiWQ9TklvvezINr2eFEC8WG77PJ9acrwaybU7KrBtPXysVjtdFM 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 zw90gyFPXFuDL3UdDC96QRhveFO4zuaAKc9fjYzPONpB7yL3jW9vOYmvC/Laz0+aDS9660lvR84A7122hy9dFkBvYBcI70U8XG6NUekvZkWZbyCasM9I2OkOyf1w73n+Bq9Q6/3PJNxiz1qTr69PL+2vFs4yb0mBTs9VayUPJP4TTxniQa9850UvVeCgrxQvKQ8SkEfvGag5jzowrA7FJaHO/guZT2v5Vm9V4pOvTVP1bwsr429/PuHvRwClL13rU49RKSLvRijiDyPvEQ9ZAQHvGN/GLykLZS9NyxtvSrQGjtgTAO9cUCjPJq/Fb7Bj0A9r+CxPTaT5TyzbnU7QAycvSplMzxWXsM68gYRPFJ2Fj12fsW8979zvfy0ED3HnCe9WDkbvUcO2Lxg/xG90JRUvd+6A71hcQK9fjiqvUCWpTxaJog94mu4POR/m7n75Sy9SBEUvL1GyjyknjW9MYwZvcuB8L0L8nM8U4lQPXdKkDvmj/m8OLC4vXmHE7y52Uy9oX+BPM 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 Fy9/ytFvR3rDj0ZkLk932Plu0+DZz3lC1i8I7pRvaa9VDtf5aC8psQvvC1ayzzmSz27XmU/PfHWZTusV4s9H6ygvAAG97sjYUs8Vn1IvWImKb1D4Rs8MknGu+olUz3mV9+8Js/RPNwQaD1GKbi8Sw6TPQVDjLxjT3+9pdMhPD3vgrw/TxE92StQPWR4gj1UW4M8e4MBu4JOBT2aJW+8BwJBO2EpVbqrrSU9sD6TPToCOb3dAik9eKDDPH+C3DyLD1487Y8MvfqK8juTwL28tNuOPdEplz16gSy8NfvFvKAmuLzLl7M8r0VzPVoUCr2Hok69E3QjvEIxuDzVX3c9+rwPvFLuwbs92iE8SApCvb0uAT2H0i294p2IvBDJUzvkYdM8sOKTPZrynzthlMC83XUTPTVh5TzsF/w8jXXvvIpB/zyyMFg9dzAtvdsYN7uwnqE686arvTaCiLx72j68ZIWkPd+/4jxUMwQ9ACEuPVeiC70/iAm8Ba7AvVulxbxcRGm7U7CxuM 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 pym9D4aNaK+ddgmvgGFAj80pGA+L0yZPS+puL73uQI/unJLvpYcAb/8vdG9qujcPmq+JL8bseA9Vb9svYgWEr/HtMS+nlQkvaOAhj1Sc0K6i7mIu2+9Jb9OIYo+A87iPthRXL6lIG8/nOsUPwMLhj3KJIG+JiB0vpS1Wr8PXSy/A5q+vl2xmb7QneI+MSS3PMEmVL/o+tG+usorvvmn6bzL/vI+kFI4P6obOL/58Ts/GgAHv7PGPr+1sLG9BVMFv7rMKz2++BU9lZUWPTg9oL3HA0271D2qvdRhRb0Q/Pc9mMuBPwwAPL+CRhs/CsKMPQQJuz4szk4/cycoPjKznT63Z7w+Qp07Pt4zLD8V9tC+DHYuvxXTLTyniS+/Wha+Pl4EpL4a22c+TTYev0/MQj/rsRk+mDRLvyqkWT/TrUg9ELJ7P0hh1T6vj0E/Tb6zvr+UYL3FWDI/AFUYvzBz1z6brQE+jJtpPbkwDD/jOJI+7cZxv1I8ET9e0Cy+StCXvR+jwL6FOM /q8QatsP0Kul74MMOM+HtkPvx4Jrj0UzGA/QZEcPwL0Xz7pvoQ+m2lmP71aRj/gP6W+vnlGvT5jqb6naZU+A+ucP43+ZL/kmw8/xUS5vk7d5T5+pmi/WhSNveVNnj3v/Bq93NfQPsBgPj6auLu9LxQaPvp9R73TMnS+eAR/Pz/WZL64ap+/a90vv8Flpb9XlIC8H+vNvacQcD+hkIe9yj+ov+f37j5IHFW/m5WPPkQoOj8YucI+AL6Jvz+jnbvjmUa/kafGPoankz8MM5g/Vb9Xv3pDKD9Np5u/qtWUvw7aL7+e+gg/gZpQPGkPFj0M1xO/WDXlPn3fBL9uO7i+s3Asv4M8y70VIO0+JklJvjV1WD62rh0+LNBKvg==", "training_traits": {"structure_gen": "Random", "n_layers": 8, "max_nodes": 20, "activation_func": "Tanh", "epoch_num": 5}, "classes_name":M ["Cryptoadz", "Cryptopunks", "Moonbirds", "Nouns"]},m=25,b=50,y=59+11/12,w=59+11.5/12,v=60;function z(e,t){const n=Math.log(1-t)/Math.log(1-e);return e=>1-Math.pow(1-e,n)}class V{constructor(e,t,n){const{model:r,inputDim:i}=j(t,n);this.model=r,this.inputDim=i,this.iteration=0,this.stage=0;const o=new Date(parseInt(e.birthYear),0,1).getTime(),a=new Date(parseInt(e.birthYear)+1,0,1).getTime();this.birthDate=new Date(Math.floor((o+a)/2));const l=zr.filter((t=>t[0]==e.lifeCycle))[0][2];this.growSpeed=365/l,this.cycleLM ength=60*l*24*3600*1e3,this.growthFunc=z(.4,.8)}updateAge(e){const t=(e.getTime()-this.birthDate.getTime())/31536e6*this.growSpeed;this.iteration=Math.floor(t/60);const n=t-60*this.iteration;let r;this.age=n;let i,o=0;if(n<25){let e=map(n,0,25,0,1);o=this.growthFunc(e),r=(25-n)/60,this.stage=1,this.stageRatio=map(n,0,25,0,1)}else n<50?(o=1,r=(50-n)/60,this.stage=2,this.stageRatio=map(n,25,50,0,1)):n<y?(o=map(n,50,y,1,0),r=(y-n)/60,this.stage=3,this.stageRatio=map(n,50,y,0,1)):n<w?(o=0,r=(w-n)/60,this.stage=4,this.sM tageRatio=map(n,y,w,0,1)):n<60&&(o=0,r=(60-n)/60,this.stage=5,this.stageRatio=map(n,w,60,0,1));n<50?i=map(n,0,50,0,780/880):n<w?i=map(n,50,w,780/880,800/880):n<60&&(i=map(n,w,60,800/880,1)),this.nextStateTimestamp=Math.round(e.getTime()+this.cycleLength*r),this.statePercentage=round(100*i);let a=(25-n)/60;a<0&&(a+=1),this.nextStableTimestamp=Math.round(e.getTime()+this.cycleLength*a),this.growth=o,this.model.updateNeurons(o,this.iteration)}getBrainStatus(){return{totalNeurons:this.model.getTotalNeurons(),neuronsLifM e:this.model.getNeuronsLife(),stage:this.stage,inputDim:this.inputDim,stageRatio:this.stageRatio,age:this.age,growth:this.growth,nextStateTimestamp:this.nextStateTimestamp,nextStableTimestamp:this.nextStableTimestamp,rebirthCount:max(this.iteration,0),statePercentage:this.statePercentage}}classifyImage(e){const t=new G(e,1,e.length);return this.model.forward(t).mat[0]}}class M{constructor(e,t,n,r,i){this.p=e,this.v=t,this.size=n,this.shape=i,this.col=r}getRadius(){return 1==Oe?1*this.size/2:2==Oe?7*this.size/16:3==M Oe||4==Oe?4*this.size/7:0}update(){this.p.add(this.v)}draw(e,t,n,r){const i=this.p.x*r,o=this.p.y*r,a=this.size*r,{col:l,shape:s}=this;let h,c;1==n?h=c=l:2==n?(h=dr(t,1),c=l):(h=dr(t,0),c=dr(l,1));e.stroke(dr(c,map(1,0,1,.25,1))),e.fill(dr(h,map(1,0,1,.15,1))),3==n&&e.fill(dr(h,0)),1==s?e.ellipse(i,o,a,a):2==s?e.rect(i,o,7*a/8,7*a/8):3==s&&(e.beginShape(),e.vertex(i-4*a/7,o),e.vertex(i,o-4*a/7),e.vertex(i+4*a/7,o),e.vertex(i,o+4*a/7),e.endShape(CLOSE))}}class E{constructor(e,t,n,r,i,o,a){this.center=e,this.len=t,thM is.angle=n,this.v=r,this.angV=i,this.c1=o,this.c2=a}getEndpoints(){const e=createVector(this.len/2*cos(this.angle),this.len/2*sin(this.angle));return[Vector.add(this.center,e),Vector.sub(this.center,e)]}update(){this.center.add(this.v),this.angle+=this.angV}draw(e,t){const[n,r]=this.getEndpoints(),i=n.x*t,o=n.y*t,a=r.x*t,l=r.y*t,s=this.c1,h=this.c2;var c=e.drawingContext.createLinearGradient(i,o,a,l);c.addColorStop(0,s),c.addColorStop(1,h),e.drawingContext.strokeStyle=c,e.drawingContext.globalAlpha=1,e.line(i,o,a,lM ),e.drawingContext.globalAlpha=1}}function S(e,t){const n=random(TAU),r=random(e,t);return createVector(r*cos(n),r*sin(n))}class R{constructor(e,t,n,r,i){this.wall=n,this.maxR=i;const o=t.length;this.nodes=[];for(let a=0;a<o;++a){const o=[],l=.25*t[a];for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),l=S(.02*i,.05*i),s=random(10,25)*i;o.push(new M(t,l,s,e[a],r))}this.nodes.push(o)}const a=A(e);a.unshift(e[0]),a.push(e[e.length-1]),this.lines=[];for(let e=0;e<=o;++e){const M r=[],l=(0==e?1:t[e-1])*(e==o?1:t[e])*1.5;for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),o=random(5*i,10*i),l=random(TAU),s=S(.02*i,.05*i),h=random(2e-4,.001);r.push(new E(t,o,l,s,h,a[e],a[e+1]))}this.lines.push(r)}}reflectNode(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,{p:o,v:a}=e,l=e.getRadius();(o.x-l<t&&a.x<0||o.x+l>r&&a.x>0)&&(a.x=-a.x),(o.y-l<n&&a.y<0||o.y+l>i&&a.y>0)&&(a.y=-a.y)}reflectLine(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,[o,a]=e.gM etEndpoints(),l=e.v;(min(o.x,a.x)<t&&l.x<0||max(o.x,a.x)>r&&l.x>0)&&(l.x=-l.x),(min(o.y,a.y)<n&&l.y<0||max(o.y,a.y)>i&&l.y>0)&&(l.y=-l.y)}update(){for(const e of this.lines)for(const t of e)t.update(),this.reflectLine(t);for(const e of this.nodes)for(const t of e)t.update(),this.reflectNode(t)}draw(e,t,n,r,i){const o=i/this.maxR;for(const t of this.lines){const n=t.length*r;for(let r=0;r<n;++r)t[r].draw(e,o)}for(const i of this.nodes){const a=i.length*r;for(let r=0;r<a;++r)i[r].draw(e,t,n,o)}}}function I(e,t){re(e)M ,e.fill(0),e.rect(0,0,500,500),ie(e),e.noStroke(),e.fill(dr(cr("#000000"),.5)),e.push(),e.translate(250,250),e.scale(t),e.translate(-250,-250),e.beginShape(),e.vertex(235.2,24.9),e.bezierVertex(215,24.6,185,11.4,164.8,11),e.bezierVertex(147.2,10.7,129.3,10.4,112.2,14.7),e.bezierVertex(95.1,19,78.5,28.5,69.6,43.8),e.bezierVertex(57.699,64.199,61.599,90.199,70.199,112.2),e.bezierVertex(78.799,134.2,91.6,154.6,97.199,177.5),e.bezierVertex(102.499,199.2,100.899,222.5,92.799,243.2),e.bezierVertex(83,268,64.6,288.3,48.9,M 310),e.bezierVertex(33.2,331.7,24.5,337.5,26.599,364.1),e.bezierVertex(28.2,384.1,61.399,404.2,75.7,418.3),e.bezierVertex(90,432.4,73.7,488.2,91.9,496.7),e.bezierVertex(124.2,511.6,159,472.5,194.3,468.1),e.bezierVertex(211.6,465.9,267.4,501.5,283.9,495.9),e.bezierVertex(340.7,476.7,298.599,428.9,355.4,409.7),e.bezierVertex(370.799,404.5,454.5,407.6,464.4,394.8),e.bezierVertex(478.599,376.3,474.7,349.3,464.299,328.4),e.bezierVertex(453.9,307.5,438.099,289.5,428.699,268.2),e.bezierVertex(412,230,419,182.6,446.1,150.9M ),e.bezierVertex(449.7,146.7,453.6,142.7,455.8,137.6),e.bezierVertex(459.4,129.299,457.5,119.6,454.8,111),e.bezierVertex(443.2,73.4,417.3,40.4,383.6,20.299),e.bezierVertex(358.1,5,343.2,-.4,313.5,0),e.bezierVertex(287.5,.4,261.6,25.4,235.2,24.9),e.endShape(),e.pop()}function C(e,t,n,r,i,o){let a,l,s;re(t),t.fill(0),t.rect(0,0,500,500),ie(t),t.noStroke(),t.fill(dr(n,.5)),1==i?(l=0,s=25,a=map(o,0,25,500,0)):a=0,t.rect(0,a,500,500),e.noStroke(),e.fill(r),e.rect(0,0,500,500),e.beginShape(),e.vertex(435.2,373.8),e.bezieM rVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,3M 50.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVM ertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,19M 8.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),e.fill(n),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6)M ,e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,11M 9.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364M .3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),re(e),e.fill(r),e.beginShaM pe(),e.vertex(184.3,473.2),e.bezierVertex(164,473.2,144.7,462.099,134,444.3),e.bezierVertex(131.7,440.5,129.1,438.5,125,437.1),e.bezierVertex(97.3,428.1,80.5,400.6,85.2,371.8),e.bezierVertex(86.3,365.1,85.8,364.1,79.9,361.2),e.bezierVertex(57.2,349.8,46.2,323.3,54.3,299.7),e.bezierVertex(54.7,298.599,55.1,297.7,55.5,296.9),e.bezierVertex(55.6,296.599,55.8,296.4,55.9,296.099),e.vertex(57.9,291.499),e.vertex(62.5,293.599),e.bezierVertex(64.9,294.7,67.3,295.799,69.5,296.9),e.bezierVertex(74.5,299.299,79.1,301.599,83.9M ,303.099),e.bezierVertex(89.8,304.9,96.5,305.499,102.7,305.9),e.bezierVertex(102.8,305.9,102.9,305.9,103,305.9),e.bezierVertex(106.6,305.9,108.9,302.799,109,299.799),e.bezierVertex(109.1,296.199,106.6,293.4,102.7,292.799),e.bezierVertex(101.3,292.599,99.9,292.4,98.4,292.299),e.bezierVertex(94.3,291.799,90.1,291.299,86,289.9),e.bezierVertex(68.9,284,56.5,270.2,52.7,252.799),e.bezierVertex(48.9,235.499,54.5,217.7,67.6,205.299),e.bezierVertex(71.9,201.299,72.7,198.1,70.8,192.399),e.bezierVertex(64.2,172.2,68.8,153.99,M 84.2,139.599),e.bezierVertex(94.2,130.199,105.5,125.399,117.8,125.399),e.bezierVertex(124.3,125.399,131.1,126.799,137.8,129.599),e.bezierVertex(157,137.399,167.9,152.799,169.4,173.99),e.vertex(169.4,174.399),e.bezierVertex(169.5,175.899,169.6,177.2,169.9,178.299),e.bezierVertex(170.7,181.2,173.2,183.2,176.1,183.2),e.bezierVertex(176.299,183.2,176.5,183.2,176.7,183.2),e.bezierVertex(180.1,182.899,182.6,180.299,182.7,177),e.bezierVertex(183.1,162,178.299,148.2,168.399,136.1),e.bezierVertex(158.2,123.5,144.899,115.8,1M 28.799,113.199),e.bezierVertex(123.499,112.299,120.399,109.799,118.899,104.99),e.bezierVertex(113.899,89.699,120.699,72.299,134.899,64.499),e.bezierVertex(139.99,61.699,145.799,60.199,151.7,60.199),e.bezierVertex(162.2,60.199,171.899,64.799,178.1,72.699),e.bezierVertex(179.6,74.6,180.799,76.6,181.9,78.499),e.vertex(182.2,79.099),e.bezierVertex(183.2,80.699,185.2,83.299,188.4,83.299),e.bezierVertex(189.5,83.299,190.6,82.99,191.7,82.399),e.bezierVertex(195.1,80.599,196,76.99,194,72.799),e.bezierVertex(190.1,64.799,18M 4.1,58.499,175.6,53.299),e.bezierVertex(174.6,52.699,173.7,52.099,172.5,51.499),e.vertex(170.5,50.299),e.vertex(163,45.899),e.vertex(170.5,41.599),e.bezierVertex(182,34.99,193.1,30.799,204.4,28.599),e.bezierVertex(208.6,27.799,212.9,27.399,217.2,27.399),e.bezierVertex(217.6,27.399,217.9,27.399,218.3,27.399),e.bezierVertex(231.4,27.599,242.7,38.199,243,50.599),e.bezierVertex(243.4,64.899,243.3,78.99,243.2,93.799),e.bezierVertex(243.2,99.799,243.1,105.899,243.1,112.099),e.vertex(243.1,119.199),e.vertex(236.4,116.799)M ,e.bezierVertex(235.7,116.499,235,116.299,234.4,115.99),e.bezierVertex(233.4,115.599,232.6,115.299,232,115.199),e.bezierVertex(230.6,114.899,229.2,114.599,227.8,114.299),e.bezierVertex(223.8,113.499,220.1,112.699,216.4,112.499),e.vertex(216.2,112.499),e.bezierVertex(212.5,112.499,210.7,115.599,210.6,118.599),e.bezierVertex(210.4,122.399,212.7,125.099,216.4,125.399),e.bezierVertex(230.1,126.399,238.9,133.099,242.3,145.199),e.bezierVertex(243.2,148.399,243.2,151.599,243.2,154.499),e.vertex(243.2,155.099),e.bezierVertM ex(243.2,254.199,243.2,330,243.2,400.599),e.bezierVertex(243.2,401.99,243.2,403.4,243.2,404.9),e.bezierVertex(243.3,411.099,243.3,417.599,242.3,423.9),e.bezierVertex(238.1,449.2,219.6,467.799,194,472.5),e.bezierVertex(190.9,472.9,187.6,473.2,184.3,473.2),e.endShape(),e.beginShape(),e.vertex(315.8,473.1),e.bezierVertex(309.3,473.1,302.8,472,296.5,469.9),e.bezierVertex(270.4,461,253.8,434.9,257.1,407.9),e.bezierVertex(260,384,273.8,366.8,297,358.3),e.bezierVertex(297.7,358.1,298.3,357.8,299,357.6),e.bezierVertex(299.M 8,357.3,300.6,357.1,301.2,356.8),e.bezierVertex(304.3,355.4,306,351.8,304.9,348.7),e.bezierVertex(304,345.9,301.7,344.2,299,344.2),e.bezierVertex(298.6,344.2,298.1,344.2,297.6,344.3),e.bezierVertex(288.1,346.3,279,350.9,269.7,358.3),e.bezierVertex(268.9,358.9,268.1,359.6,267.2,360.4),e.vertex(265.5,361.8),e.vertex(258.5,367.6),e.vertex(257.4,358.6),e.bezierVertex(257.3,358,257.3,357.5,257.2,357.1),e.bezierVertex(257,356,256.9,354.9,256.9,353.7),e.bezierVertex(256.9,334.8,256.9,316,256.9,297.1),e.bezierVertex(256.9,M 260.3,256.9,222.3,256.8,185),e.bezierVertex(256.8,170.7,268.3,158.8,282.5,158.4),e.bezierVertex(284.8,158.3,286.7,157.6,287.9,156.2),e.bezierVertex(289.099,154.9,289.599,153.2,289.5,151.3),e.bezierVertex(289.3,147.5,286.7,145.1,282.7,145.1),e.bezierVertex(282.5,145.1,282.2,145.1,282,145.1),e.bezierVertex(278.8,145.3,275.5,146.1,272,146.9),e.bezierVertex(270.9,147.2,269.8,147.4,268.6,147.7),e.bezierVertex(267.9,147.9,267,148.2,265.8,148.7),e.bezierVertex(265.1,149,264.4,149.3,263.5,149.6),e.vertex(256.8,152),e.verteM x(256.8,114.6),e.bezierVertex(256.8,95,256.8,75.4,256.8,55.9),e.bezierVertex(256.8,38,267.2,27.3,284.6,27.3),e.bezierVertex(285.3,27.3,285.9,27.3,286.6,27.3),e.bezierVertex(299,27.9,318.7,34.5,329.6,41.9),e.vertex(336.1,46.3),e.vertex(324.4,53.3),e.bezierVertex(316.2,58.2,310.2,64.6,306,72.9),e.bezierVertex(304.2,76.4,305.1,78.5,306.1,80),e.bezierVertex(307.4,81.9,309.4,83,311.6,83),e.bezierVertex(313.7,83,315.7,81.9,317.1,80.1),e.bezierVertex(317.4,79.7,317.8,79,318.1,78.4),e.bezierVertex(318.4,77.9,318.7,77.3,319M ,76.8),e.bezierVertex(325.3,66.2,336.3,59.9,348.5,59.9),e.bezierVertex(353.2,59.9,357.8,60.8,362.1,62.7),e.bezierVertex(377.6,69.3,386,86.7,381.7,103.2),e.bezierVertex(380.7,107.1,378.5,111.8,371.1,113.1),e.bezierVertex(342.7,118.1,322.2,139.1,317.8,167.8),e.bezierVertex(317.4,170.3,317.3,173.2,317.4,176.5),e.bezierVertex(317.5,180,320.1,182.8,323.5,183),e.bezierVertex(323.6,183,323.8,183,323.9,183),e.bezierVertex(327.1,183,329.8,180.6,330.3,177.2),e.bezierVertex(330.6,175.7,330.7,174,330.9,172.3),e.bezierVertex(33M 1.1,169.8,331.4,167.3,332,164.7),e.bezierVertex(337.3,141.9,357.7,125.4,380.7,125.4),e.bezierVertex(382.5,125.4,384.3,125.5,386.1,125.7),e.bezierVertex(412.8,128.9,432.6,150.9,432,176.9),e.bezierVertex(431.9,182.3,430.9,187.7,429.1,192.7),e.bezierVertex(427.2,197.9,428,201,432.3,205),e.bezierVertex(446.8,218.7,451.8,236,446.6,255),e.bezierVertex(441.4,274,428.3,286.5,408.7,291.3),e.bezierVertex(406.1,291.9,403.6,292.1,401.1,292.3),e.bezierVertex(400,292.4,398.9,292.5,397.9,292.6),e.bezierVertex(393.6,293.1,390.9,29M 5.7,391,299.5),e.bezierVertex(391.1,303.4,394,305.8,398.5,305.8),e.bezierVertex(409.9,305.8,420.8,302.6,431.1,296.4),e.bezierVertex(431.8,296,432.5,295.5,433.2,295.1),e.bezierVertex(433.8,294.7,434.5,294.3,435.2,293.9),e.bezierVertex(436,293.4,436.6,293.2,437.2,293.1),e.bezierVertex(437.4,293,437.7,292.9,438.1,292.8),e.vertex(442.5,291.4),e.vertex(444.2,295.7),e.bezierVertex(450.9,312.4,449.5,328.4,440,343.4),e.bezierVertex(435.3,350.8,428.7,356.7,420.2,361.1),e.bezierVertex(414.3,364.1,413.7,365.2,414.8,371.7),e.bM ezierVertex(419.5,400.2,403,427.6,375.6,436.9),e.bezierVertex(371,438.5,368.3,440.7,365.8,444.7),e.bezierVertex(355.2,462.5,336.4,473.1,315.8,473.1),e.bezierVertex(315.8,473.1,315.8,473.1,315.8,473.1),e.endShape(),ie(e),e.fill(n),e.beginShape(),e.vertex(120.2,279.9),e.bezierVertex(117.9,279.9,112.4,279.299,112.2,273.599),e.bezierVertex(112,267.7,117.4,266.7,119.7,266.599),e.bezierVertex(133.1,265.799,143.1,259.499,149.3,247.899),e.bezierVertex(149.6,247.299,150.1,246.399,150.3,245.399),e.bezierVertex(150.6,244.299,M 150.5,243.299,150.5,242.7),e.bezierVertex(150.5,242.6,150.5,242.5,150.5,242.299),e.vertex(150.3,238.799),e.vertex(141.1,235.99),e.bezierVertex(114.6,227.799,95.6,202.499,95.9,175.799),e.bezierVertex(95.9,173.99,96.4,168.199,102.2,168.199),e.bezierVertex(102.6,168.199,103,168.199,103.4,168.299),e.bezierVertex(104.8,168.499,108.2,168.899,109.2,175.599),e.bezierVertex(109.3,176.599,109.5,177.599,109.6,178.499),e.bezierVertex(110.4,184.199,111.3,189.99,113.7,195.499),e.bezierVertex(121.9,213.99,139.5,225.499,159.7,225.M 499),e.bezierVertex(172.1,225.499,184.1,220.899,193.5,212.599),e.bezierVertex(194,212.199,194.4,211.799,194.8,211.399),e.bezierVertex(195.1,211.099,195.5,210.799,195.8,210.399),e.bezierVertex(197.4,208.99,199.2,208.2,200.9,208.2),e.bezierVertex(202.5,208.2,204,208.899,205.3,210.1),e.bezierVertex(208,212.9,207.9,216.9,205,219.9),e.bezierVertex(196.5,228.6,186.3,234.3,174.7,236.8),e.bezierVertex(168.799,238.1,165.6,241,163.899,246.7),e.bezierVertex(158.3,265.9,139.9,279.7,120.2,279.9),e.vertex(120.2,279.9),e.endShapeM (),e.beginShape(),e.vertex(187.2,427.5),e.bezierVertex(183.799,427.5,181.299,425.3,180.799,422),e.bezierVertex(180.6,420.8,180.499,419.5,180.399,418.1),e.bezierVertex(180.299,417,180.2,415.8,180.099,414.7),e.bezierVertex(177.199,390.5,156.699,371.3,132.399,370.2),e.bezierVertex(131.99,370.2,131.499,370.2,131.099,370.2),e.bezierVertex(130.699,370.2,130.299,370.2,129.799,370.2),e.bezierVertex(125.99,369.9,123.199,367.2,123.099,363.6),e.bezierVertex(122.99,360.2,125.799,357.3,129.599,356.9),e.bezierVertex(130.499,356.M 8,131.499,356.8,132.599,356.7),e.bezierVertex(133.199,356.7,133.799,356.7,134.399,356.6),e.vertex(138.299,356.4),e.vertex(139.1,352.6),e.bezierVertex(139.5,350.7,139.799,348.9,140.2,347),e.bezierVertex(140.899,343.4,141.5,340,142.399,336.8),e.bezierVertex(150.099,310.7,174.399,292,201.399,291.3),e.vertex(201.599,291.3),e.bezierVertex(203.699,291.3,206.299,292,208.299,293.2),e.bezierVertex(210.499,294.5,210.699,297.5,209.99,299.8),e.bezierVertex(209.499,301.5,208.199,303.9,203.299,304.7),e.bezierVertex(202.199,304.9M ,200.99,305,199.799,305.2),e.bezierVertex(194.499,305.9,188.99,306.599,183.799,308.9),e.bezierVertex(165.499,316.799,155.199,331.299,152.99,352),e.bezierVertex(152.399,357.8,154.499,361.7,159.699,364.5),e.bezierVertex(178.199,374.4,189.399,390,193.099,410.9),e.bezierVertex(193.699,414.299,193.899,418,193.599,422),e.bezierVertex(193.399,425.2,190.899,427.5,187.399,427.5),e.vertex(187.2,427.5),e.endShape(),e.beginShape(),e.vertex(364.3,281.1),e.bezierVertex(346.3,280.6,332.9,272.8,323.5,257),e.bezierVertex(321.6,253.M 9,320.4,250.2,319.2,246.7),e.bezierVertex(317.7,242.2,315,239.799,310.5,238.799),e.bezierVertex(298.5,236.299,288,230.7,279.4,222.1),e.bezierVertex(276.7,219.4,274.9,215.299,278,211.9),e.bezierVertex(279.4,210.3,281,209.6,282.6,209.6),e.bezierVertex(284.4,209.6,286.4,210.6,288.3,212.5),e.bezierVertex(297.8,221.8,310.4,226.9,323.9,226.9),e.bezierVertex(340.2,226.9,355.1,219.3,364.8,206.2),e.bezierVertex(371,197.8,374.2,188.5,374.5,178.5),e.vertex(374.5,177.9),e.bezierVertex(374.5,177,374.5,176.1,374.7,175.4),e.bezieM rVertex(375.3,171.8,377.9,169.5,381.3,169.5),e.bezierVertex(381.4,169.5,381.5,169.5,381.7,169.5),e.bezierVertex(385.4,169.7,388,172.4,388,176.1),e.bezierVertex(388.1,190.7,383.4,204,374.2,215.8),e.bezierVertex(365.8,226.5,354.7,233.9,341.2,237.9),e.bezierVertex(340,238.3,338.7,238.6,337.3,239.1),e.bezierVertex(335.9,239.6,335.1,240.4,334.7,240.9),e.bezierVertex(334.599,241,334.5,241.1,334.4,241.2),e.vertex(331.799,243.6),e.vertex(333.199,246.8),e.bezierVertex(338.199,258,346.799,264.9,358.699,267.3),e.bezierVertex(M 360.199,267.6,361.599,267.7,362.99,267.9),e.bezierVertex(363.599,268,364.299,268,364.899,268.1),e.bezierVertex(369.099,268.6,371.799,271.4,371.499,275),e.bezierVertex(371.199,278.6,368.299,281.2,364.399,281.2),e.vertex(364.3,281.1),e.endShape(),e.beginShape(),e.vertex(323.9,437),e.bezierVertex(323.7,437,323.5,437,323.299,437),e.bezierVertex(319.599,436.7,317.299,434.1,317.4,430.2),e.bezierVertex(317.9,406.099,328.299,388,349.5,375),e.bezierVertex(350.7,374.2,352,373.5,353.4,372.8),e.bezierVertex(354.099,372.4,354.7M ,372.1,355.299,371.7),e.vertex(357.499,370.5),e.vertex(357.799,368),e.bezierVertex(360.4,346.6,345.199,323.7,323.9,317),e.bezierVertex(319.099,315.5,314.099,314.9,309.299,314.4),e.vertex(308.199,314.299),e.bezierVertex(305.99,314.099,300.799,312.9,300.899,307.299),e.bezierVertex(300.99,303.499,303.899,300.9,308.099,300.9),e.vertex(308.299,300.9),e.bezierVertex(327.099,301.299,343.099,308.7,355.699,322.9),e.bezierVertex(364.299,332.5,369.399,344.099,370.99,357.299),e.bezierVertex(371.099,358.4,371.299,359.4,371.499,M 360.499),e.bezierVertex(371.599,360.99,371.699,361.499,371.799,361.99),e.vertex(372.499,365.899),e.vertex(377.899,366.199),e.bezierVertex(378.799,366.299,379.699,366.299,380.599,366.399),e.bezierVertex(385.099,366.699,387.899,369.399,387.799,373.299),e.bezierVertex(387.699,377.099,384.99,379.599,380.799,379.799),e.bezierVertex(369.799,380.199,359.99,383.299,351.899,389.299),e.bezierVertex(338.799,398.799,331.699,411.699,330.699,427.499),e.vertex(330.699,428.299),e.bezierVertex(330.599,429.199,330.599,430.099,330.49M 9,430.799),e.bezierVertex(330,434.7,327.5,437,323.9,437),e.endShape()}function T(e){return e[0].map(((t,n)=>e.map((e=>e[n]))))}function A(e){return e.map((e=>Array.isArray(e)?A(e):e))}function D(e,t){return floor(random(e,t))}function k(e){let t=0;for(const n of e)t+=n[1];let n=random(t),r=0;for(const t of e)if(r+=t[1],n<r)return t[0];return null}function L(e){for(let t=1;t<e.length;++t){let n=D(0,t),r=e[t];e[t]=e[n],e[n]=r}}function P(e){return null==e||""===e}function O(e){return new Promise((t=>setTimeout(t,e)))M }function F(e,t,n){let r=0;for(let i=1;i<=1e3;++i)for(let o=1;o<=1e3;++o)if(e*o%(t*i)==0){let e=1*i/o;abs(e-n)<abs(r-n)&&(r=e)}return r}function N(){let e=60*(new Date).getTimezoneOffset()*1e3;return new Date(Date.now()-e).toISOString().slice(0,-1)}function B(e,t,n){let r;if(push(),textSize(e),textWidth(t)<=n)r=t;else for(let e=0;e<t.length;++e){const i=t.slice(0,e+1)+"...";if(textWidth(i)>n){r=i;break}}return pop(),r}function Y(e){var t=e%10,n=e%100;return 1==t&&11!=n?e+"st":2==t&&12!=n?e+"nd":3==t&&13!=n?e+"rd":eM +"th"}class G{constructor(e,t,n){this.n=t,this.m=n,this.mat=[];let r=0;for(let t=0;t<this.n;++t){this.mat.push([]);for(let n=0;n<this.m;++n)this.mat[t].push(r<e.length?e[r]:0),r+=1}return this}copy(){return new G(this.mat.flat(),this.n,this.m)}}class H{static __linear=e=>e;static __relu=e=>Math.max(e,0);static __leaky_relu=e=>e>0?e:.2*e;static __sigmoid=e=>1/(1+Math.exp(-e));static __tanh=e=>Math.tanh(e);static __apply_unary_op(e,t){const n=e.copy();for(let e=0;e<n.n;++e)for(let r=0;r<n.m;++r)n.mat[e][r]=t(n.mat[e]M [r]);return n}static linear=e=>H.__apply_unary_op(e,H.__linear);static relu=e=>H.__apply_unary_op(e,H.__relu);static leaky_relu=e=>H.__apply_unary_op(e,H.__leaky_relu);static sigmoid=e=>H.__apply_unary_op(e,H.__sigmoid);static tanh=e=>H.__apply_unary_op(e,H.__tanh);static __add=(e,t)=>e+t;static __mul=(e,t)=>e*t;static __apply_binary_op=(e,t,n)=>{"object"!=typeof t&&(t=new G([t],1,1));const r=e.copy();for(let e=0;e<r.n;++e)for(let i=0;i<r.m;++i)r.mat[e][i]=n(r.mat[e][i],t.mat[e%t.n][i%t.m]);return r};static mul=(e,M t)=>H.__apply_binary_op(e,t,H.__mul);static add=(e,t)=>H.__apply_binary_op(e,t,H.__add);static matMul(e,t){const n=new G([],e.n,t.m);for(let r=0;r<n.n;++r)for(let i=0;i<n.m;++i)for(let o=0;o<e.m;++o)n.mat[r][i]+=e.mat[r][o]*t.mat[o][i];return n}static softmax(e){const t=H.__apply_unary_op(e,(e=>Math.exp(e))),n=t.mat.flat().reduce(((e,t)=>e+t));for(let r=0;r<e.n;++r)for(let i=0;i<e.m;++i)t.mat[r][i]/=n;return t}}class ${constructor(e,t){this.scale=e,this.offset=t}forward(e){return H.add(H.mul(e,this.scale),this.offsM et)}}class X{constructor(){}forward(e){return e.map((e=>e.flat()))}}class W{constructor(e,t,n,r){this.out_dim=e,this.activation=t,this.w=n,this.b=r}forward(e){const t=H.add(H.matMul(e,this.w),this.b);return null==this.activation?t:this.activation(t)}}class U{constructor(e,t,n){this.preprocessLayers=e,this.hiddenLayers=t,this.outputLayer=n,this.totalNeurons=this.hiddenLayers.map((e=>e.out_dim)),this.currentOrders=[],this.currentIteration=null}updateNeurons(e,t){if(t!=this.currentIteration){this.currentOrders=[];for(M let e=0;e<this.totalNeurons.length;++e){randomSeed(100*(t+1)+e);const n=[];for(let t=0;t<this.totalNeurons[e];++t)n.push(t);L(n),this.currentOrders.push(n)}this.currentIteration=t}const n=A(this.totalNeurons),r=n.reduce(((e,t)=>e+t))*(1-e);for(let e=0;e<r;++e){const t=n.map(((e,t)=>(e-1)/this.totalNeurons[t]));n[t.map(((e,t)=>[e,t])).reduce(((e,t)=>t[0]>e[0]?t:e))[1]]-=Math.min(r-e,1)}this.neuronsLife=[];for(let e=0;e<n.length;++e){const t=this.currentOrders[e],r=Array(this.totalNeurons[e]).fill(0);for(let i=0;i<n[M e];++i)r[t[i]]=Math.min(n[e]-i,1);this.neuronsLife.push(r)}}getTotalNeurons(){return A(this.totalNeurons)}getNeuronsLife(){return A(this.neuronsLife)}forward(e){for(const t of this.preprocessLayers)e=t.forward(e);for(const[t,n]of this.hiddenLayers.entries()){e=n.forward(e);const r=new G(this.neuronsLife[t],1,e.m);e=H.mul(e,r)}return e=this.outputLayer.forward(e),H.softmax(e)}}function q(e){switch(e){case"relu":return H.relu;case"sigmoid":return H.sigmoid;case"tanh":return H.tanh;case"leaky_relu":return H.leaky_reluM ;default:return H.linear}}function j(e,t){const n=[],r=[],i=Z(t);let o=null,a=0,l=[];for(const t of e.config.layers)if("InputLayer"==t.class_name)o=t.config.batch_input_shape.slice(1),l=o;else if("Rescaling"==t.class_name)n.push(new $(t.config.scale,t.config.offset));else if("Flatten"==t.class_name)o=[o.reduce(((e,t)=>e*t))];else if("Dense"==t.class_name){const e=[t.config.units],n=o[0]*e[0],l=e[0],s=i.subarray(a,a+n);a+=n;const h=i.subarray(a,a+l);a+=l;const c=new G(s,o[0],e[0]),u=new G(h,1,e[0]),f=q(t.config.actiM vation);r.push(new W(e[0],f,c,u)),o=e}const s=r.pop();return{model:new U(n,r,s),inputDim:l}}function Z(e){const t=window.atob(e),n=t.length/Float32Array.BYTES_PER_ELEMENT,r=new DataView(new ArrayBuffer(Float32Array.BYTES_PER_ELEMENT)),i=new Float32Array(n);let o=0;for(let e=0;e<n;e++){o=4*e;for(let e=0;e<4;++e)r.setUint8(e,t.charCodeAt(o+e));i[e]=r.getFloat32(0,!0)}return i}class K{constructor(e){this.elt=e,this._events={},this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight}position(){if(0===argumentsM .length)return{x:this.elt.offsetLeft,y:this.elt.offsetTop};var e="absolute";return"static"!==arguments[2]&&"fixed"!==arguments[2]&&"relative"!==arguments[2]&&"sticky"!==arguments[2]&&"initial"!==arguments[2]&&"inherit"!==arguments[2]||(e=arguments[2]),this.elt.style.position=e,this.elt.style.left=arguments[0]+"px",this.elt.style.top=arguments[1]+"px",this.x=arguments[0],this.y=arguments[1],this}show(){return this.elt.style.display="block",this}hide(){return this.elt.style.display="none",this}size(e,t){if(0===argumeM nts.length)return{width:this.elt.offsetWidth,height:this.elt.offsetHeight};var n=e,r=t;if(n!==te||r!==te){if(n===te?n=t*this.width/this.height:r===te&&(r=e*this.height/this.width),this.elt instanceof HTMLCanvasElement){var i,o={},a=this.elt.getContext("2d");for(i in a)o[i]=a[i];for(i in this.elt.setAttribute("width",n*this._pInst._pixelDensity),this.elt.setAttribute("height",r*this._pInst._pixelDensity),this.elt.style.width=n+"px",this.elt.style.height=r+"px",this._pInst.scale(this._pInst._pixelDensity,this._pInst.M _pixelDensity),o)this.elt.getContext("2d")[i]=o[i]}else this.elt.style.width=n+"px",this.elt.style.height=r+"px",this.elt.width=n,this.elt.height=r;this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight,this._pInst&&this._pInst._curElement&&this._pInst._curElement.elt===this.elt&&(this._pInst._setProperty("width",this.elt.offsetWidth),this._pInst._setProperty("height",this.elt.offsetHeight))}return this}style(e,t){if(t instanceof Color&&(t="rgba("+t.levels[0]+","+t.levels[1]+","+t.levels[2]+","+t.levels[M 3]/255+")"),void 0===t){if(-1===e.indexOf(":"))return window.getComputedStyle(this.elt).getPropertyValue(e);for(var n=e.split(";"),r=0;r<n.length;r++){var i=n[r].split(":");i[0]&&i[1]&&(this.elt.style[i[0].trim()]=i[1].trim())}}else if(this.elt.style[e]=t,"width"===e||"height"===e||"left"===e||"top"===e){var o=window.getComputedStyle(this.elt).getPropertyValue(e).replace(/[^\d.]/g,"");this[e]=Math.round(parseFloat(o,10))}return this}value(){return arguments.length>0?(this.elt.value=arguments[0],this):"range"===thisM .elt.type?parseFloat(this.elt.value):this.elt.value}mouseClicked(e){return this._adjustListener("click",e,this),this}isFocused(){return document.activeElement===this.elt}_adjustListener(e,t,n){return!1===t?this._detachListener(e,n):this._attachListener(e,t,n),this}_attachListener(e,t,n){n._events[e]&&this._detachListener(e,n);var r=t.bind(n);n.elt.addEventListener(e,r,!1),n._events[e]=r}_detachListener(e,t){var n=t._events[e];t.elt.removeEventListener(e,n,!1),t._events[e]=null}}function J(e,t){var n=document.createM Element("button");return n.innerHTML=e,t&&(n.value=t),ee(n)}function Q(e){var t=arguments.length>1&&void 0!==arguments[1]&&arguments[1],n=function(t){var n=!0,r=!1,i=void 0;try{for(var o,a=t.target.files[Symbol.iterator]();!(n=(o=a.next()).done);n=!0){var l=o.value;File._load(l,e)}}catch(e){r=!0,i=e}finally{try{n||null==a.return||a.return()}finally{if(r)throw i}}};if(window.File&&window.FileReader&&window.FileList&&window.Blob){var r=document.createElement("input");return r.setAttribute("type","file"),t&&r.setAttriM bute("multiple",!0),r.addEventListener("change",n,!1),ee(r)}}function ee(e){return document.body.appendChild(e),new K(e)}createImg=function(){var e,t=document.createElement("img"),n=arguments;return n.length>1&&"string"==typeof n[1]&&(t.alt=n[1]),n.length>2&&"string"==typeof n[2]&&(t.crossOrigin=n[2]),t.src=n[0],e=ee(t,this),t.addEventListener("load",(function(){e.width=t.offsetWidth||t.width,e.height=t.offsetHeight||t.height;var r=n[n.length-1];"function"==typeof r&&r(e)})),e},createInput=function(){var e=argumentM s.length>0&&void 0!==arguments[0]?arguments[0]:"",t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:"text",n=document.createElement("input");return n.setAttribute("value",e),n.setAttribute("type",t),ee(n,this)};const te="auto";function ne(e){re(e);const t=e._rectMode;e.rectMode(CORNER),e.rect(0,0,e.width,e.height),e.rectMode(t),ie(e)}function re(e){e.push(),e.fill(255,255,255,255),e.blendMode(REMOVE)}function ie(e){e.blendMode(BLEND),e.pop()}File=function(e,t){this.file=e,this._pInst=t;var n=e.type.split("/"M );this.type=n[0],this.subtype=n[1],this.name=e.name,this.size=e.size,this.data=void 0},File._createLoader=function(e,t){var n=new FileReader;return n.onload=function(n){var r=new File(e);if("application/json"===r.file.type)r.data=JSON.parse(n.target.result);else if("text/xml"===r.file.type){var i=(new DOMParser).parseFromString(n.target.result,"text/xml");r.data=new XML(i.documentElement)}else r.data=n.target.result;t(r)},n},File._load=function(e,t){if(/^text\//.test(e.type)||"application/json"===e.type)File._creatM eLoader(e,t).readAsText(e);else if(/^(video|audio)\//.test(e.type)){var n=new File(e);n.data=URL.createObjectURL(e),t(n)}else File._createLoader(e,t).readAsDataURL(e)},XML=function(e){if(e)this.DOM=e;else{var t=document.implementation.createDocument(null,"doc");this.DOM=t.createElement("root")}},document.addEventListener("DOMContentLoaded",(function(){addEventListener("mousemove",(e=>{window.mouseX=e.pageX,window.mouseY=e.pageY}))})),new e("global");const oe="422";let ae,le,se,he,ce,ue,fe,de,xe,ge,pe,me,be,ye,we,veM ,ze,Ve,_e,Me,Ee,Se,Re,Ie,Ce,Te,Ae,De,ke,Le,Pe,Oe,Fe,Ne,Be,Ye,Ge,He,$e,Xe,We,Ue,qe,je,Ze,Ke,Je,Qe,et,tt,nt,rt,it,ot,at,lt,st,ht,ct,ut,ft,dt,xt,gt,pt,mt,bt,yt,wt,vt,zt,Vt,_t,Mt,Et,St,Rt,It,Ct,Tt,At=!1,Dt=!1,kt=!0,Lt=!1,Pt=!1;const Ot=[" ","Growing","Stable","Decaying","Dead","Rebirth"];let Ft,Nt,Bt,Yt,Gt,Ht,$t,Xt,Wt,Ut,qt,jt,Zt,Kt,Jt,Qt,en,tn,nn,rn,on,an,ln,sn,hn=0,cn=0,un=0,fn=!1,dn=!0,xn=!0,gn=null,pn=null,mn=null,bn=!1,yn=!1,wn=null,vn=null,zn=!1;async function setup(){let e=windowWidth,t=windowHeight;createCanvasM (e,t),et=createGraphics(e,t),Xe=createGraphics(e,t),$e=createGraphics(e,t),We=createGraphics(e,t),Ue=createGraphics(e,t),qe=createGraphics(e,t),Qe=createGraphics(e,t),je=createGraphics(e,t),Ze=createGraphics(e,t),Ke=createGraphics(e,t),Je=createGraphics(e,t),tt=createGraphics(500,500),nt=createGraphics(500,500),rt=createGraphics(500,500),_n(),Mn(),Sn(),await En(),Gn(),Rn(),bn=!0}function _n(){Et=parseInt(oe),randomSeed(Et),noiseSeed(Et)}function Mn(){Wt=Ir(p.training_traits),Cr(Wt)}async function En(){let e;Jt=r(),M Qt=o(),[Xt,e]=await Promise.all([s(Jt),h(Qt)]),Ut=new V(Wt.visual,e.layers_config,e.weight_b64),Ut.updateAge(new Date),_n(),Wt.training=e.training_traits,Ht=e.model_name,$t=e.classes_name}function Sn(){le=min(width,height)/1024,ut=Rr.findIndex((e=>e[0]===Wt.visual.colorPalette)),ft=[["#ffffff","#231f20","#231f20"],["#231f20","#ffffff","#ffffff"],["#104da8","#ffffff","#ffffff"],["#722F1F","#FCE1B2","#FCE1B2"],["#e88120","#f9f2e5","#f9f2e5"],["#f6b941","#2E2E2E","#2E2E2E"],["#45daaa","#012221","#012221"],["#F1F1F1","M #328DFE","#328DFE"],["#111822","#D3EB8D","#D3EB8D"],["#713FF9","#D6D5E6","#D6D5E6"],["#FBDA9D","#795106","#795106"],["#8f5b62","#ead0d0","#ead0d0"],["#eae4cb","#508cac","#508cac"],["#ffc6cc","#cc313d","#cc313d"],["#60A900","#E0FE00","#E0FE00"],["#507DBE","#D0D1D3","#D0D1D3"],["#305848","#E8F2EE","#E8F2EE"],["#2a2634","#5b6988","#cb78a2","#5b6988"],["#590e29","#fd5e53","#fd5e53","#ffe373"],["#0a141d","#57d4e4","#328195","#2A9ECF","#0ab6a8","#57d4e4"],["#3a2d28","#d5c2ac","#df6338","#3d9895","#d5c2ac"],["#030706","#7M 7c4d9","#77c4d9","#77c4d9","#ffffff","#ffffff","#e72020","#e72020"],["#3a4664","#92f5ff","#f9ff94","#eaa0a2","#55dde0"],["#fbfaff","#f04bb1","#f04bb1","#fac373","#82cef0","#8b31ce"],["#000000","#ffffff","#ff0002","#f26522","#fdff00","#00ff03","#01fffe","#0000ff","#ff00ff"]];for(let e=0;e<ft.length;++e)for(let t=0;t<ft[e].length;++t)ft[e][t]=cr(ft[e][t]);pt=[],ct=ft[ut][0],st=ft[ut][1]}function Rn(){gn=document.querySelector("#upload"),pn=document.querySelector("#inputUpload"),gn.addEventListener("dblclick",(()=>{ifM (!Lt&&!yn)if(In(Ie)&&cn==Ve-1)pn.click();else{if(4!=Pe&&5!=Pe&&(In(Ie)||cn!=Ve-1))return;fn=!0,dn=!0,Bt=0,un=0}})),pn.addEventListener("click",(()=>{pn.value=null,gn.style.display="block"})),pn.addEventListener("change",(()=>{const[e]=pn.files;e?(se=null,gn.style.display="none",Tn(URL.createObjectURL(e)),mn=e):gn.style.display="block"}))}function In(e){for(let t=0;t<e.length;++t){let n=0;for(let r=0;r<e[t].length;++r)e[t][r]>0&&++n;if(0==n)return!1}return!0}function Cn(){null!=se&&(un=0,Pt=!0,he=0,ue=0,drewLineAnimM =!0,ce=(ae/2+we/2)/le,loadImage(se.elt.src,(e=>{const[t,n,r]=Gt,i=createGraphics(t,n);i.image(e,0,0,t,n),i.loadPixels();const o=i.pixels.filter(((e,t)=>t%4!=3)),a=Ut.classifyImage(o);Zt=T([a,$t.map((e=>e.toUpperCase()))]).sort(((e,t)=>e[0]>t[0]?-1:1))})))}function Tn(e){se=createImg(e,""),se.hide(),Cn()}function An(){zn||(ce+=(width-ae-we)/tn/le),re(Xe),Xe.rect(ce*le,0,width,height),ie(Xe),un>=ge&&1==kt&&(kt=!1,un-=ge),kt&&(re($e),$e.strokeWeight(2*Fe),Jn(he,ze,ct,ct,$e),ie($e)),un>=ge&&0==kt&&(kt=!0,un-=ge,he+=1,hM e==en&&(++ue,he=0,ce=(ae/2+we/2)/le,1==ue&&(Pt=!1,Dn(),ye=millis())))}function Dn(){At=!0,pe=!1,me=!1,tryButton=br("Try Again",width/2-225*le,height/2+265*le,290*le,40*le,kn),closeResultButton=br("Close",width/2+75*le,height/2+265*le,150*le,40*le,Ln)}function kn(){At=!1,tryButton.hide(),closeResultButton.hide(),pn.click()}function Ln(){Yt=!0,At=!1,Gn(),tryButton.hide(),closeResultButton.hide(),gn.style.display="block",se=null}function keyTyped(){bn&&!1===yn&&!1===yr()&&("i"!==key&&"I"!==key||(Dt=!Dt),"b"!==key&&"B"M !==key||(xn=!xn),"s"!==key&&"S"!==key||!1!==Lt||saveCanvasAtCurrentTime(),"k"!==key&&"K"!==key||!1!==Lt||save4KCanvasAtCurrentTime(),"u"!==key&&"U"!==key||!1!==Lt||!1!==At||!1!==fn||!1!==Pt||On())}function On(){Lt=!0,wn=null,vn=null,submitButton=br("Submit",width/2-155*le,height/2+115*le,150*le,40*le,Fn),closeSettingButton=br("Close",width/2+5*le,height/2+115*le,150*le,40*le,Yn),vt=createInput(),vt.position(width/2-252.5*le,height/2-40*le),vt.size(500*le,25*le),vt.style("font-size","15px"),vt.value(Jt||""),zt=creatM eInput(),zt.position(width/2-252.2*le,height/2+35*le),zt.size(500*le,25*le),zt.style("font-size","15px"),zt.value(Qt||"")}function Fn(){Vt=vt.value(),_t=zt.value(),submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide(),Lt=!1,yn=!0,Nn()}async function Nn(){[wn,vn,_]=await Promise.all([c(Vt),u(_t),O(1e3)]),yn=!1,wn&&vn?(n(Vt),i(_t),window.location.reload()):(Lt=!0,submitButton.show(),closeSettingButton.show(),vt.show(),zt.show())}function Bn(){Je.textFont("Trebuchet MS"),Je.noStroke(),pr(Je,600*le,200*le),M Je.strokeWeight(1*le),Je.stroke(xt),Je.fill(xt),Je.textSize(50*le),Je.text("update()",width/2,height/2+2.5*le)}function Yn(){wn=null,vn=null,Lt=!1,submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide()}function Gn(){_n(),nn=Date.now(),pe=!1,me=!1,St=Wt.training.structure_gen,Rt=Wt.visual.birthYear,It=Wt.visual.lifeCycle,Ct=Wt.training.epoch_num,Tt=Wt.training.activation_func,Ft=Mr.findIndex((e=>e[0]==Wt.visual.hardwareAcceleration))+1,1==Ft?(Nt=30,fe=40):2==Ft?(Nt=15,fe=20):(Nt=2,fe=10);const e=Ut.getBraM inStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),ae=100*le,ht=50*le,Oe=Sr.findIndex((e=>e[0]==Wt.visual.nodeShape))+1,dt=Er.findIndex((e=>e[0]==Wt.viM sual.nodeFill))+1,lt=_r.findIndex((e=>e[0]==Wt.visual.pattern))+1,de=Math.tanh(Math.log10(Xt.avgfeerate)),de=map(de,0,1,.2,.8),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){M Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].lengM th;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,at=.7,pt=[],xt=ft[ut][2],gt=ft[ut][ft[ut].length-1];for(let e=3;e<ft[ut].length-1;e++)pt.push(ft[ut][e]);mt=sr(xt,gt,pt,width),bt=[],wt=[],yt=M width/(Ve-1);for(let e=0;e<Ve;e++)bt.push(hr(mt,yt*e/width)),wt.push(hr(mt,yt*e/width));wt.unshift(bt[0]),wt.push(bt[bt.length-1]),hn=0,cn=0,un=0,Yt=!0;const n={xLeft:ae/8,xRight:width-ae/8,yTop:ae/8,yBottom:height-ae/8},r=Ce.map((e=>e.length));jt=new R(bt,r,n,Oe,le)}function Hn(e,t){let n=Ce[e].length;return[e*we+we/2+ae/2,height/2-(n-1)/2*ve+t*ve]}function $n(e,t){le=min(e,t)/1024,ae=100*le,ht=50*le,we=(e-ae)/Ve,ve=(t-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;nM ++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}xe=floor(De.length*de),Le=[],ke=[],ge=floor(map(de,.2,.8,15,2));for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,mt=sr(xt,gt,pt,e),bt=[],wt=[],yt=e/(Ve-1);for(let t=0;t<Ve;t++)bt.push(hr(mt,yt*t/e)),wt.push(hr(mt,yt*t/e));wt.unshift(bt[0]),wt.push(bt[bt.length-1])}function Xn(){const e=Ut.getBrainStatus();Gt=e.inputDim,KtM =e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)GeM .push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.pusM h(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*DeM .length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le}function Wn(){jt.update();const e=4==Pe?0:Kt;jt.draw(Qe,ct,dt,e,le)}function Un(){if(!bn)return ar(),void et.image(je,0,0);if(4==Pe||5==Pe)return Wn(),void et.image(Qe,0,0);un>=Nt&&hn<Ve&&(hn++,un=0);for(let e=0;e<hn;e++)1==dt?it=ot=bt[e]:(it=ct,ot=bt[e]),Kn(e,it,ot,$e);un>=Nt&&cn<Ve-1&&(cn++,un=0);for(let e=0;e<cn;e++)Zn(e)}function qn(){et.background(ct),Ue.background(255),Ue.rectMode(CENTERM ),ne(Ue),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),Ue.stroke(st),Ue.strokeWeight(8*le),Ue.fill(ct),Qe.background(255),Qe.rectMode(CENTER),ne(Qe),Qe.strokeWeight(le),qe.background(255),qe.rectMode(CENTER),ne(qe),qe.textAlign(LEFT),$e.background(255),$e.rectMode(CENTER),ne($e),Xe.background(255),ne(Xe),Xe.strokeWeight(Ne),We.background(255),We.rectMode(CENTER),ne(We),We.fill(st),We.stroke(st),We.strokeWeight(.1*le),er(lt),We.noStroke(),xn&&(We.rect(ae/16,height/2,ae/8,height),We.rect(width-ae/16,height/2,ae/8,heM ight),We.rect(width/2,ae/16,width,ae/8),We.rect(width/2,height-ae/16,width,ae/8)),Ze.background(255),Ze.rectMode(CENTER),ne(Ze),Ze.textAlign(CENTER,CENTER),Ze.textStyle(BOLD),Ze.stroke(st),Ze.strokeWeight(8*le),Ze.fill(ct),je.background(255),je.rectMode(CENTER),ne(je),je.textAlign(CENTER,CENTER),je.textStyle(BOLD),Ke.background(255),Ke.rectMode(CENTER),ne(Ke),Ke.textAlign(CENTER,CENTER),Ke.textStyle(BOLD),Ke.stroke(st),Ke.strokeWeight(8*le),Ke.fill(ct),Je.background(255),Je.rectMode(CENTER),ne(Je),Je.textAlign(CENTM ER,CENTER),Je.textStyle(BOLD),Je.stroke(st),Je.strokeWeight(8*le),Je.fill(ct),Un(),et.image(We,0,0),Pt&&An(),et.image(Xe,0,0),et.image($e,0,0),At&&(tr(),et.image(Ue,0,0)),fn&&(lr(),et.image(Ze,0,0)),Lt&&(or(),et.image(Ke,0,0)),Dt&&(ir(),et.image(qe,0,0)),yn&&(Bn(),et.image(Je,0,0))}function draw(){const e=Date.now();bn&&(Ut.updateAge(new Date(e)),Xn()),qn(),image(et,0,0),zn||un++}function Zn(e){let t,n=Ce[e].length,r=Ce[e+1].length;for(let i=0;i<n;i++){const[n,o]=Hn(e,i);for(let a=0;a<r;a++){const[r,l]=Hn(e+1,a);t=M map(min(Ce[e][i],Ce[e+1][a]),0,1,0,.5),ur(n,o,r,l,bt[e],bt[e+1],Xe,t)}}}function Kn(e,t,n,r){let i,o,a,l=Ce[e].length;for(let s=0;s<l;s++){const[l,h]=Hn(e,s);i=Ce[e][s],a=map(Be,1/30,1,3,10),o=map(Ce[e][s],0,1,2*a,0)*le,o<1.5*le&&(o=0),Qn(l,h,ze,Oe,t,n,o,i,r)}}function Jn(e,t,n,r,i){for(let o=0;o<Le[e].length;o++)Qn(Le[e][o][0],Le[e][o][1],t,Oe,n,r,0,1,i)}function Qn(e,t,n,r,i,o,a,l,s){s.stroke(dr(o,map(l,0,1,.25,1))),s.fill(dr(i,map(l,0,1,.15,1))),s.strokeWeight(Fe),fr([a],s),3==dt&&s.fill(dr(i,0)),1==r?s.ellipse(M e,t,n):2==r?s.rect(e,t,7*n/8,7*n/8):3==r&&(s.beginShape(),s.vertex(e-4*n/7,t),s.vertex(e,t-4*n/7),s.vertex(e+4*n/7,t),s.vertex(e,t+4*n/7),s.endShape(CLOSE))}function er(e){if(1==e);else if(2==e){We.strokeWeight(1*le);for(let e=ht/4;e<width+ht/4;e+=ht)for(let t=ht/4;t<height+ht/4;t+=ht)We.point(e,t)}else if(3==e){ht=25*le;for(let e=ht/2;e<height+ht/2;e+=ht)We.line(0,e,width,e);for(let e=ht/2;e<width+ht/2;e+=ht)We.line(e,0,e,height)}}function tr(){Ue.textFont("Trebuchet MS"),Ue.textAlign(LEFT,CENTER),Ue.noStroke(),prM (Ue,800*le,500*le),Ue.noStroke(),Ue.fill(dr(st,.75)),Ue.rect(width/2,height/2-100*le,800*le,300*le,25*le,25*le,0,0),Ue.fill(st),Ue.rect(width/2-250*le,height/2-100*le,225*le,225*le),Ue.image(se.elt,width/2-357.5*le,height/2-207.5*le,215*le,215*le);let e=100*Zt[0][0];Ue.fill(ct),Ue.textSize(25*le),Ue.textStyle(NORMAL),1==me&&(e>=0&&e<20?Ue.text("I have a feeling this image belongs to",width/2-100*le,height/2-170*le):e>=20&&e<40?Ue.text("I have a hunch this image belongs to",width/2-100*le,height/2-170*le):e>=40&&e<6M 0?Ue.text("I think this image belongs to",width/2-100*le,height/2-170*le):e>=60&&e<80?Ue.text("I'm almost certain this image belongs to",width/2-100*le,height/2-170*le):Ue.text("I'm positive this image belongs to",width/2-100*le,height/2-170*le));let t=e.toFixed(2);"100.00"==t&&(t="100"),1==me&&Ue.text("I'm "+t+"% confident that I'm right!",width/2-100*le,height/2-25*le),example=Zt.map((e=>e[1])),be=Ue.textWidth('"FIDENZAAAA"'),defaultPhrase=Ue.textWidth('"PERPENDICULAR INHABITATION"'),Ue.textStyle(BOLD);const n=meM ?example[0]:random(example);if(1===n.split(" ").length){let e=75*be/Ue.textWidth('"'+n+'"');e>75&&(e=75),Ue.textSize(e*le),Ue.text('"'+n+'"',width/2-100*le,height/2-90*le)}else nr(width/2-100*le,height/2-90*le,460*le,110*le,n,Ue);if(millis()-ye>1500&&(me=!0),C(tt,nt,st,ct,Pe,Mt),Ue.image(nt,width/2-370*le,height/2+70*le,80*le,80*le),3==Pe){let e;e=map(Mt,50,60,.25,1.3),I(rt,e),Ue.image(rt,width/2-370*le,height/2+70*le,80*le,80*le)}let r,i;Ue.image(tt,width/2-370*le,height/2+70*le,80*le,80*le),Ue.fill(xt),Ue.textSizM e(40*le),Ue.text("INTELLIGENCE INFO",width/2-275*le,height/2+115*le),Ue.textSize(18*le),Ue.textStyle(NORMAL),Ue.circle(width/2-360*le,height/2+180*le,7.5*le),1==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s growing and getting smarter by the day.`:2==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s stable and it has reached peak performance.`:3==Pe&&(r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s decaying and losing its luster.`),i=2==Pe?"The Perceptron remains stable for some timM e before entering the decay phase.":`Wait until ${new Date(an).toLocaleString("en-US")} for your Perceptron to reach its peak performance.`,Ue.text(r,width/2-350*le,height/2+180*le),Ue.circle(width/2-360*le,height/2+210*le,7.5*le),Ue.text(i,width/2-350*le,height/2+210*le),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),gr(Ue,width/2-225*le,width/2+65*le,height/2+265*le,height/2+305*le,"SELECT ANOTHER IMAGE"),gr(Ue,width/2+75*le,width/2+225*le,height/2+265*le,height/2+305*le,"CLOSE")}function nr(e,t,n,r,i,o){let a=i.M split(" "),l=75*be/o.textWidth('"'+i+'"'),s=0,h=[],c=[],u=[],f="",d="";if(l>=50)l>75&&(l=75),o.textSize(l*le),o.text('"'+i+'"',e,t);else if(l<50){if(l=50*defaultPhrase/o.textWidth('"'+i+'"'),l>30){if(l>50&&(l=50),[f,d]=rr(l,n,s,h,c,a,f,d,Ue),0==c.length)return o.textSize(l*le),void o.text('"'+i+'"',e,t);for(s=0,h=[],c=[];o.textWidth(d)>n/le;)l=l*n/le/o.textWidth(d),f="",d="",[f,d]=rr(l,n,s,h,c,a,f,d,Ue)}else{l=30,o.textSize(l);for(let e=0;e<a.length;e++)s+=o.textWidth(" "+a[e]),s<=n/le?h.push(a[e]):s>n/le&&s<=n/le*M 2?c.push(a[e]):u.push(a[e]);for(let e=1;e<h.length;e++)f=f+" "+h[e];if(f='"'+h[0]+f,0==u.length){for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+c[c.length-1]+'"'}else if(1==c.length)d="... "+u[u.length-1]+'"';else{for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+"... "+u[u.length-1]+'"'}}o.textSize(l*le);let r=1.25*(o.textDescent()+o.textAscent());o.text(f,e,t-r/2),o.text(d,e,t+r/2)}}function rr(e,t,n,r,i,o,a,l,s){s.textSize(e);for(let e=0;e<o.length;e++)(n+=s.textWidth(" "+o[e]))<=t/le?r.push(o[e]):i.push(o[e]);for(leM t e=1;e<r.length;e++)a=a+" "+r[e];if(a='"'+r[0]+a,0==i.length&&(a+='"',l=""),1==i.length)l=i[i.length-1]+'"';else{for(let e=0;e<i.length-1;e++)l=l+i[e]+" ";l=l+i[i.length-1]+'"'}return[a,l]}function ir(){const e=45*le;qe.textFont("Tahoma"),qe.stroke(st),qe.strokeWeight(2*le),qe.fill(ct),qe.rect(width/2,e/2+height-87.5*le,600*le,90*le),qe.fill(st),qe.rect(width/2-150*le,e+height-170*le,300*le,30*le),qe.fill(ct),qe.rect(width/2+150*le,e+height-170*le,300*le,30*le),qe.noStroke(),qe.fill(ct),qe.textSize(15*le),qe.textSM tyle(BOLD),qe.text("PERCEPTRON INFORMATION",width/2-285*le,e+height-165*le),qe.fill(xt),qe.text("ARTWORK NAME:",width/2+10*le,e+height-165*le),qe.textAlign(RIGHT),qe.textStyle(ITALIC),qe.text("Perceptron #"+Et,width/2+285*le,e+height-165*le);const[t,n]=It.split(" ");let r;"60 Years"===It?r="1 Year":"60 Months"===It?r="1 Month":"60 Weeks"===It?r="1 Week":"60 Days"===It?r="1 Day":"12 Hours"===It&&(r="12 Minutes"),data=[["AI MODEL NAME:",B(12*le,Ht,140*le)],["SCALE:","1:"+Te],["NUMBER OF CLASSES:",$t.length],["BIRTH YM EAR:",Rt],["NUMBER OF REBIRTHS:",sn.toString()],["AGE:",`${Math.ceil(Mt)} Perceptron Years`],["ONE PERCEPTRON YEAR:",`${r}`],["STATE:",Ot[Pe]],["ACTIVE NEURONS:",`${round(ln*rn)} / ${ln}`],["NEXT STATE TIME:",vr(new Date(on))]],qe.fill(xt);const i=data.length/2;for(let t=0;t<data.length;++t){const n=t<i,r=n?width/2-285*le:width/2+10*le,o=n?width/2-10*le:width/2+285*le,a=e+height-(135-t%i*15)*le;qe.textStyle(BOLD),qe.textAlign(LEFT),qe.textSize(12*le),qe.text(data[t][0],r,a),qe.textStyle(ITALIC),qe.textAlign(RIGHT),M qe.textSize(12*le),qe.text(data[t][1],o,a)}}function or(){Ke.textFont("Trebuchet MS"),Ke.noStroke(),pr(Ke,600*le,200*le),gr(Ke,width/2-155*le,width/2-5*le,height/2+115*le,height/2+155*le,"UPDATE"),gr(Ke,width/2+5*le,width/2+155*le,height/2+115*le,height/2+155*le,"CLOSE"),Ke.textAlign(LEFT),Ke.fill(xt),Ke.text("UPDATE BITCOIN FULL NODE ADDRESS",width/2-252.5*le,height/2-55*le),Ke.text("UPDATE MODEL ADDRESS",width/2-252.5*le,height/2+20*le),Ke.textAlign(RIGHT),Ke.textStyle(ITALIC),Ke.textSize(15*le),0==wn&&Ke.text("(M *) Invalid Address",width/2+252.5*le,height/2-53*le),0==vn&&Ke.text("(*) Invalid Model",width/2+252.5*le,height/2+23*le)}function ar(){je.textFont("Trebuchet MS"),je.fill(st),je.textSize(50*le),je.stroke(st),je.strokeWeight(1*le),je.text("main()",width/2,height/2)}function lr(){un>=20&&1==dn&&(dn=!1,un=0),dn&&(Ze.textFont("Trebuchet MS"),Ze.stroke(st),Ze.fill(ct),Ze.rect(width/2,height/2,600*le,150*le,25*le),Ze.fill(xt),Ze.textSize(75*le),Ze.noStroke(),1==Pe?Ze.text("GROWING",width/2,height/2+5*le):3==Pe?Ze.text("AM GING",width/2,height/2+5*le):4==Pe?Ze.text("DEAD",width/2,height/2+5*le):5==Pe&&Ze.text("BIRTH",width/2,height/2+5*le)),un>=20&&0==dn&&(dn=!0,un=0,Bt++,3==Bt&&(fn=!1))}function sr(e,t,n,r){let i=[],o=r/(n.length+1),a=color(e),l=color(t);i.push(a);for(let e=0;e<n.length;e++){let t=color(n[e]);for(let e=1;e<=o;e++){let n=lerpColor(a,t,e/o);i.push(n)}a=t}for(let e=1;e<o;e++){let t=lerpColor(a,l,e/o);i.push(t)}if(i.push(l),i.length>r)i.splice(r);else if(i.length<r){let e=i[i.length-1];for(;i.length<r;)i.push(e)}return M i}function hr(e,t){let n=e.length,r=Math.floor(t*n);return r>=n&&(r=n-1),e[r]}function cr(e){e=e.replace("#","");var t=parseInt(e,16);return color(t>>16&255,t>>8&255,255&t)}function ur(e,t,n,r,i,o,a,l){var s=a.drawingContext.createLinearGradient(e,t,n,r);s.addColorStop(0,i),s.addColorStop(1,o),a.drawingContext.strokeStyle=s,a.drawingContext.globalAlpha=l,a.line(e,t,n,r),a.drawingContext.globalAlpha=1}function fr(e,t){t.drawingContext.setLineDash(e)}function dr(e,t){let n=color(e),r=red(n),i=green(n),o=blue(n);returM n color(r,i,o,255*t)}function xr(e,t,n,r){return mouseX>e&&mouseX<t&&mouseY>n&&mouseY<r}function gr(e,t,n,r,i,o){e.strokeWeight(1*le),e.stroke(st);const[a,l]=xr(t,n,r,i)?[xt,ct]:[ct,xt];e.fill(a),e.push(),e.rectMode(CORNERS),e.rect(t,r,n,i,5*le),e.pop(),e.noStroke(),e.textSize(20*le),e.fill(l),e.text(o,(t+n)/2,(46*r+54*i)/100)}function pr(e,t,n){e.fill(0,0,0,75),e.rect(width/2,height/2,width,height),e.stroke(st),e.fill(ct),e.rect(width/2,height/2,t,n,25*le)}function mr(e,t){resizeCanvas(e,t,!0),Xe.resizeCanvas(e,t,M !0),$e.resizeCanvas(e,t,!0),We.resizeCanvas(e,t,!0),Ue.resizeCanvas(e,t,!0),qe.resizeCanvas(e,t,!0),Qe.resizeCanvas(e,t,!0),je.resizeCanvas(e,t,!0),Ze.resizeCanvas(e,t,!0),Ke.resizeCanvas(e,t,!0),Je.resizeCanvas(e,t,!0),et.resizeCanvas(e,t,!0)}function br(e,t,n,r,i,o){const a=J(e);return a.position(t,n),a.size(r,i),a.style("opacity","0"),a.mouseClicked(o),a}function yr(){return null!=vt&&vt?.isFocused()||null!=zt&&zt?.isFocused()}function wr(e,t,n,r){let i;if(e<=3){i=`Hey ${String.fromCodePoint(128075)}, I'm ${n}, M ${t} years old. I can detect ${r.length} NFT collections: `;let e=0;for(let t=0;t<r.length;++t){const n=r[t];if(e+n.length>500){i+=", etc";break}t==r.length-1?i+=", and ":t>0&&(i+=", "),i+=n,e+=n.length}i+=". ",t<=5?i+="However, I am only a baby, so my recognition ability is not accurate. I'm in the state of Growing both looks and intelligence.":t<=13?i+="I am now a child. My recognition ability is becoming better, but still not very accurate. I'm in the state of Growing both looks and intelligence.":t<=25?i+="I haM ve grown up to be a teen. My recognition ability almost reaches the peak, but I will still mess up sometimes. I'm in the state of Growing both looks and intelligence.":t<=50?i+="I finally reach adulthood. My recognition is fully functional now. I'm in the Stable state, where I am the most intelligent with all neurons activated.":t<=60&&(i+="I am now an old Perceptron, so my recognition ability is no longer the best. I'm in the Decaying state, meaning that my neurons are dying, and my intelligence is decreasing overM time.")}else 4==e?i=`${n} is Dead. However, this is not the end to its story...`:5==e&&(i=`${n} is now in the Rebirth state, and is preparing to start a new life.`);return i}function vr(e){const t=e.getDate(),n=e.toLocaleString("en-US",{month:"long"}),r=e.getFullYear();let i=e.getHours().toString();1==i.length&&(i="0"+i);let o=e.getMinutes().toString();return 1==o.length&&(o="0"+o),`${Y(t)} ${n} ${r} | ${i}:${o}`}saveCanvasAtCurrentTime=()=>{save(N())},save4KCanvasAtCurrentTime=()=>{const e=width,t=height,n=min(40M 96/min(e,t),1e4/max(e,t)),r=e*n,i=t*n;mr(r,i),zn=!0,$n(r,i),qn();let o="4K_"+N()+".png";saveCanvas(et,o),mr(e,t),$n(e,t),zn=!1};const zr=[["60 Years",3,365],["60 Months",40,30],["60 Weeks",37,7],["60 Days",20,1]],Vr=[["1943",1],["1951",1.5],["1957",2],["1969",2.5],["1970",3],["1980",3.5],["1982",4],["1986",4.5],["1988",5],["1997",5.5],["1998",6],["2002",6.5],["2009",7],["2012",7.5],["2014",8],["2015",8.5],["2016",9],["2023",15]],_r=[["Plain",20],["Dotted",40],["Squared",40]],Mr=[["Basic",30],["Standard",60],["AdvanM ced",10]],Er=[["MNIST",70],["CIFAR",25],["IMAGENET",5]],Sr=[["Theano",60],["Torch",30],["TensorFlow",10]],Rr=[["Whitepaper",2],["Blackboard",2],["Blueprint",2],["Nak",74/14],["Jims",74/14],["Level 10",74/14],["Flips",74/14],["Level 14",74/14],["III",74/14],["XMB",74/14],["Info",74/14],["Adventure",74/14],["Marigold",74/14],["Phoenix",74/14],["Love",74/14],["Cachet",74/14],["Human",74/14],["Twilight",3],["Sunset",3],["Aurora",3],["Liminal Space",3],["D Vu",3],["Lucid Dream",3],["Parallel",1],["Multiverse",1]];fM unction Ir(e){for(let e=0;e<100;++e)random(1);return{visual:{pattern:k(_r),hardwareAcceleration:k(Mr),nodeFill:k(Er),nodeShape:k(Sr),colorPalette:k(Rr),lifeCycle:k(zr),birthYear:k(Vr)},training:e}}function Cr(e){window.$generativeTraits={"Network Architecture":e.training.structure_gen,"Hidden Layers":e.training.n_layers,"Max Neurons Per Hidden Layer":e.training.max_nodes,"Activation Function":e.training.activation_func,"Training Epochs":e.training.epoch_num,Dataset:e.visual.nodeFill,"Deep Learning Framework":e.visuM al.nodeShape,"Hardware Acceleration":e.visual.hardwareAcceleration,"Paper Pattern":e.visual.pattern,"Life Cycle":e.visual.lifeCycle,"Birth Year":e.visual.birthYear,"Color Palette":e.visual.colorPalette}} <script defer src="https://static.cloudflareinsights.com/beacon.min.js/v2b4487d741ca48dcbadcaf954e159fc61680799950996" integrity="sha512-D/jdE0CypeVxFadTejKGTzmwyV10c1pxZk/AqjJuZbaJwGMyNHY3q/mTPWqMUnFACfCTunhZUVcd4cV78dK1pQ==" data-cf-beacon='{"rayId":"7b48a7711990a1ea","version":"2023.3.0","b":1,"tLfoken":"6c07c178c94442f695e7a0a2aaee641a","si":100}' crossorigin="anonymous"></script> {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "rainbow"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "lamp"}]} text/plain;charset=utf-8 {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "blue fire"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "sword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "dragon"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "pirate flag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "golden armor"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "skull"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "laser"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "pirate flag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "rainbow"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "bag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "tiger"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "eagle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "quiver"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "orc"}, {"trait_type": "Mane", "value": "fire"}, {"trait_type": "Claws", "value": "blue fire"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "shield"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "axe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "rainbow"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "midas touch"}, {"trait_type": "Eyes", "value": "golden"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "bag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "badger"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "moon"}, {"trait_type": "Body", "value": "tiger"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "shield"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "pirate flag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "zombie"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "wizard staff"}]} text/plain;charset=utf-8 0{"p":"sns","op":"reg","name":"starstudios.sats"}h! {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "fire"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "axe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "moon"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "diamond hands"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "shield"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "silver"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "shield"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "midas touch"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "poisoned dagger"}]} text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"rssc","amt":"1000"}h! {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "cape"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "wizard staff"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "dragon"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "skull"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} text/plain;charset=utf-8 {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "golden"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "golden"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "undead staff"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "bloody"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "undead"}, {"trait_type": "Artifacts", "value": "frozen staff"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "honey pot"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "wizard staff"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "whale"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "zombie"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "badger"}, {"trait_type": "Artifacts", "value": "eagle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "broadsword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "crown"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "eagle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "golden armor"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "crown"}, {"trait_type": "Artifacts", "value": "eagle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "midas touch"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "badger"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "bloody"}, {"trait_type": "Eyes", "value": "golden"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "tiger"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "bloody"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "badger"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "golden armor"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "laser beams"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "tribal tattoo"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "arrow wounds"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "fire"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "pauldrons"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "skull"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "axe"}]} text/html;charset=utf-8 <meta charset="utf-8" /> position: relative; width: var(--width); height: var(--height); border: 1px solid blue; position: relative; <div id="upload"> <input id="inputUpload" type="file"> function e(e){"use strict";return new function e(t){let n="global"==t?window:this;n.canvas=document.createElement("canvas");let r=n.canvas.getContext("2d");n.width=100,n.height=100,n.canvas.width=n.width,n.canvas.height=n.height,"offscreen"!=t&&(document.body?document.body.appendChild(n.canvas):window.addEventListener("load",(function(){document.body.appendChild(n.canvas)}))),g(),n.MAGIC=161533525,n.RGB=0,n.HSV=1,n.HM SB=1,n.CHORD=0,n.PIE=1,n.OPEN=2,n.RADIUS=1,n.CORNER=2,n.CORNERS=3,n.ROUND="round",n.SQUARE="butt",n.PROJECT="square",n.MITER="miter",n.BEVEL="bevel",n.CLOSE=1,n.BLEND="source-over",n.REMOVE="destination-out",n.ADD="lighter",n.DARKEST="darken",n.LIGHTEST="lighten",n.DIFFERENCE="difference",n.SUBTRACT="subtract",n.EXCLUSION="exclusion",n.MULTIPLY="multiply",n.SCREEN="screen",n.REPLACE="copy",n.OVERLAY="overlay",n.HARD_LIGHT="hard-light",n.SOFT_LIGHT="soft-light",n.DODGE="color-dodge",n.BURN="color-burn",n.NORMAL="norM mal",n.ITALIC="italic",n.BOLD="bold",n.BOLDITALIC="italic bold",n.CENTER="center",n.LEFT="left",n.RIGHT="right",n.TOP="top",n.BOTTOM="bottom",n.BASELINE="alphabetic",n.LANDSCAPE="landscape",n.PORTRAIT="portrait",n.ALT=18,n.BACKSPACE=8,n.CONTROL=17,n.DELETE=46,n.DOWN_ARROW=40,n.ENTER=13,n.ESCAPE=27,n.LEFT_ARROW=37,n.OPTION=18,n.RETURN=13,n.RIGHT_ARROW=39,n.SHIFT=16,n.TAB=9,n.UP_ARROW=38,n.HALF_PI=Math.PI/2,n.PI=Math.PI,n.QUARTER_PI=Math.PI/4,n.TAU=2*Math.PI,n.TWO_PI=2*Math.PI,n.THRESHOLD=1,n.GRAY=2,n.OPAQUE=3,n.INVEM RT=4,n.POSTERIZE=5,n.DILATE=6,n.ERODE=7,n.BLUR=8,n.ARROW="default",n.CROSS="crosshair",n.HAND="pointer",n.MOVE="move",n.TEXT="text",n.VIDEO={video:!0,audio:!1},n.AUDIO={video:!1,audio:!0},n.SHR3=1,n.LCG=2,n.HARDWARE_FILTERS=!0,n.hint=function(e,t){n[e]=t},n.frameCount=0,n.mouseX=0,n.mouseY=0,n.pmouseX=0,n.pmouseY=0,n.mouseButton=null,n.keyIsPressed=!1,n.mouseIsPressed=!1,n.key=null,n.keyCode=null,n.pixels=null,n.accelerationX=0,n.accelerationY=0,n.accelerationZ=0,n.rotationX=0,n.rotationY=0,n.rotationZ=0,n.relRotatM ionX=0,n.relRotationY=0,n.relRotationZ=0,n.pAccelerationX=0,n.pAccelerationY=0,n.pAccelerationZ=0,n.pRotationX=0,n.pRotationY=0,n.pRotationZ=0,n.pRelRotationX=0,n.pRelRotationY=0,n.pRelRotationZ=0,n.touches=[],n._styleCache=[{colorMode:n.RGB,noStroke:!1,noFill:!1,ellipseMode:n.CENTER,rectMode:n.CORNER,curveDetail:20,curveAlpha:0,textFont:"sans-serif",textSize:12,textLeading:12,textStyle:"normal"}],n._style=n._styleCache[n._styleCache.length-1],n._noLoop=!1,n._pixelDensity=1,n._frameRate=null,n._tint=null;let i=nullM ,o=!0,a=[],l=null,s=0,h={},c=0,u=null,f=null,d=null;Object.defineProperty(n,"deviceOrientation",{get:function(){return 90==Math.abs(window.orientation)?n.LANDSCAPE:n.PORTRAIT}}),Object.defineProperty(n,"windowWidth",{get:function(){return window.innerWidth}}),Object.defineProperty(n,"windowHeight",{get:function(){return window.innerHeight}}),Object.defineProperty(n,"drawingContext",{get:function(){return r}}),n.createCanvas=function(e,t){return n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t,g(),n.canvas},nM .resizeCanvas=function(e,t){n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t},n.createGraphics=n.createImage=function(t,n){let r=new e("offscreen");return r.createCanvas(t,n),r.noLoop(),r},n.pixelDensity=function(e){return null==e||(n._pixelDensity=e,n.canvas.width=Math.ceil(n.width*e),n.canvas.height=Math.ceil(n.height*e),n.canvas.style.width=n.width+"px",n.canvas.style.height=n.height+"px",r.scale(n._pixelDensity,n._pixelDensity),g()),n._pixelDensity},n.map=function(e,t,n,r,i,o){let a=r+1*(e-t)/(n-t)*(i-r)M ;return o?r<i?Math.min(Math.max(a,r),i):Math.min(Math.max(a,i),r):a},n.lerp=function(e,t,n){return e*(1-n)+t*n},n.constrain=function(e,t,n){return Math.min(Math.max(e,t),n)},n.dist=function(){return 4==arguments.length?Math.hypot(arguments[0]-arguments[2],arguments[1]-arguments[3]):Math.hypot(arguments[0]-arguments[3],arguments[1]-arguments[4],arguments[2]-arguments[5])},n.norm=function(e,t,r){return n.map(e,t,r,0,1)},n.sq=function(e){return e*e},n.fract=function(e){return e-Math.floor(e)},n.degrees=function(e){retM urn 180*e/Math.PI},n.radians=function(e){return e*Math.PI/180},n.abs=Math.abs,n.ceil=Math.ceil,n.exp=Math.exp,n.floor=Math.floor,n.log=Math.log,n.mag=Math.hypot,n.max=Math.max,n.min=Math.min,n.round=Math.round,n.sqrt=Math.sqrt,n.sin=Math.sin,n.cos=Math.cos,n.tan=Math.tan,n.asin=Math.asin,n.acos=Math.acos,n.atan=Math.atan,n.atan2=Math.atan2,n.Vector=function(e,t,r){let i=this;i.x=e||0,i.y=t||0,i.z=r||0;let o=null,a=null;function l(e,t,n){return null!=e.x?e:null!=t?{x:e,y:t,z:n||0}:{x:e,y:e,z:e}}function s(){null==a&M &(a=i.x*i.x+i.y*i.y+i.z*i.z,o=Math.sqrt(a))}function h(){a=null,o=null}i.set=function(e,t,n){i.x=e||0,i.y=t||0,i.z=n||0},i.copy=function(){return new n.Vector(i.x,i.y,i.z)},i.add=function(){let e=l.apply(null,arguments);return i.x+=e.x,i.y+=e.y,i.z+=e.z,h(),i},i.rem=function(){let e=l.apply(null,arguments);return i.x%=e.x,i.y%=e.y,i.z%=e.z,h(),i},i.sub=function(){let e=l.apply(null,arguments);return i.x-=e.x,i.y-=e.y,i.z-=e.z,h(),i},i.mult=function(){let e=l.apply(null,arguments);return i.x*=e.x,i.y*=e.y,i.z*=e.z,hM (),i},i.div=function(){let e=l.apply(null,arguments);return i.x/=e.x,i.y/=e.y,i.z/=e.z,h(),i},i.mag=function(){return s(),o},i.magSq=function(){return s(),a},i.dot=function(){let e=l.apply(null,arguments);return i.x*e.x+i.y*e.y+i.z*e.z},i.dist=function(){let e=l.apply(null,arguments),t=i.x-e.x,n=i.y-e.y,r=i.z-e.z;return Math.sqrt(t*t+n*n+r*r)},i.cross=function(){let e=l.apply(null,arguments),t=i.y*e.z-i.z*e.y,n=i.z*e.x-i.x*e.z,r=i.x*e.y-i.y*e.x;return i.x=t,i.y=n,i.z=r,h(),i},i.normalize=function(){s();let e=o;retuM rn i.x/=e,i.y/=e,i.z/=e,o=1,a=1,i},i.limit=function(e){s();if(o>e){let t=e/o;i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e}return i},i.setMag=function(e){s();let t=e/o;return i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e,i},i.heading=function(){return Math.atan2(i.y,i.x)},i.rotate=function(e){let t=Math.cos(e),n=Math.sin(e),r=i.x*t-i.y*n,o=i.x*n+i.y*t;return i.x=r,i.y=o,i},i.angleBetween=function(){let e=l.apply(null,arguments);const t=i.dot(e)/(i.mag()*e.mag());let n;return n=Math.acos(Math.min(1,Math.max(-1,t))),n*Math.sign(i.cross(e).z||1)},M i.lerp=function(e,t){return i.x=i.x*(1-t)+e.x*t,i.y=i.y*(1-t)+e.y*t,i.z=i.z*(1-t)+e.z*t,h(),i},i.reflect=function(e){return e.normalize(),i.sub(e.mult(2*i.dot(e)))},i.array=function(){return[i.x,i.y,i.z]},i.equals=function(e,t){return null==t&&null==(t=Number.EPSILON)&&(t=0),Math.abs(e.x-i.x)<t&&Math.abs(e.y-i.y)<t&&Math.abs(e.z-i.z)<t},i.fromAngle=function(e,t){return null==t&&(t=1),o=t,a=t*t,i.x=t*Math.cos(e),i.y=t*Math.sin(e),i.z=0,i},i.fromAngles=function(e,t,n){null==n&&(n=1),o=n,a=n*n;const r=Math.cos(t),l=MaM th.sin(t),s=Math.cos(e),h=Math.sin(e);return i.x=n*h*l,i.y=-n*s,i.z=n*h*r,i},i.random2D=function(){return o=1,a=1,i.fromAngle(Math.random()*Math.PI*2)},i.random3D=function(){return o=1,a=1,i.fromAngles(Math.random()*Math.PI*2,Math.random()*Math.PI*2)},i.toString=function(){return`[${i.x}, ${i.y}, ${i.z}]`}},n.Vector.add=function(e,t){return new n.Vector(e.x+t.x,e.y+t.y,e.z+t.z)},n.Vector.rem=function(e,t){return new n.Vector(e.x%t.x,e.y%t.y,e.z%t.z)},n.Vector.sub=function(e,t){return new n.Vector(e.x-t.x,e.y-t.y,e.M z-t.z)},n.Vector.mult=function(e,t){return null==t.x?new n.Vector(e.x*t,e.y*t,e.z*t):new n.Vector(e.x*t.x,e.y*t.y,e.z*t.z)},n.Vector.div=function(e,t){return null==t.x?new n.Vector(e.x/t,e.y/t,e.z/t):new n.Vector(e.x/t.x,e.y/t.y,e.z/t.z)},n.Vector.dist=function(e,t){return Math.hypot(e.x-t.x,e.y-t.y,e.z-t.z)},n.Vector.cross=function(e,t){return new n.Vector(e.y*t.z-e.z*t.y,e.z*t.x-e.x*t.z,e.x*t.y-e.y*t.x)},n.Vector.lerp=function(e,t,r){return new n.Vector(e.x*(1-r)+t.x*r,e.y=e.y*(1-r)+t.y*r,e.z=e.z*(1-r)+t.z*r)},n.M Vector.equals=function(e,t,n){return e.equals(t,n)};for(let e of["fromAngle","fromAngles","random2D","random3D"])n.Vector[e]=function(t,r,i){return(new n.Vector)[e](t,r,i)};function x(e,t,n){let r,i,o,a,l,s,h,c,u;if(0==t)return[255*(r=n),255*(i=n),255*(o=n)];switch((a=e)>360&&(a=0),h=n*(1-t),c=n*(1-t*(s=(a/=60)-(l=~~a))),u=n*(1-t*(1-s)),l){case 0:r=n,i=u,o=h;break;case 1:r=c,i=n,o=h;break;case 2:r=h,i=n,o=u;break;case 3:r=h,i=c,o=n;break;case 4:r=u,i=h,o=n;break;default:r=n,i=h,o=c}return[255*r,255*i,255*o]}functioM n g(){r.fillStyle="white",r.strokeStyle="black",r.lineCap="round",r.lineJoin="miter"}function p(e){if(0<=e&&e<2*Math.PI)return e;for(;e<0;)e+=2*Math.PI;for(;e>=Math.PI;)e-=2*Math.PI;return e}function m(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;let c=p(a),u=p(l);r.beginPath();for(let a=0;a<h+1;a++){let l=a/h,s=n.lerp(c,u,l),f=Math.cos(s)*i/2,d=Math.sin(s)*o/2;r[a?"lineTo":"moveTo"](e+f,t+d)}s==n.CHORD?r.closePath():s==n.PIE&&(r.lineTo(e,t),r.closePath()),n._style.noFill||r.fill(),n._style.noStrokM e||r.stroke()}function b(e,t,i,o){n._style.noFill&&n._style.noStroke||(r.beginPath(),r.ellipse(e,t,i/2,o/2,0,0,2*Math.PI),n._style.noFill||r.fill(),n._style.noStroke||r.stroke())}function y(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;if(null==a)return function(e,t,i,o){n._style.noFill||r.fillRect(e,t,i,o),n._style.noStroke||r.strokeRect(e,t,i,o)}(e,t,i,o);if(null==l)return y(e,t,i,o,a,a,a,a);const c=Math.min(Math.abs(o),Math.abs(i))/2;a=Math.min(c,a),l=Math.min(c,l),h=Math.min(c,h),s=Math.min(c,s)M ,r.beginPath(),r.moveTo(e+a,t),r.arcTo(e+i,t,e+i,t+o,l),r.arcTo(e+i,t+o,e,t+o,s),r.arcTo(e,t+o,e,t,h),r.arcTo(e,t,e+i,t,a),r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke()}function w(){a=[]}n.createVector=function(e,t,r){return new n.Vector(e,t,r)},n.curvePoint=function(e,t,n,r,i){const o=i*i*i,a=i*i;return e*(-.5*o+a-.5*i)+t*(1.5*o-2.5*a+1)+n*(-1.5*o+2*a+.5*i)+r*(.5*o-.5*a)},n.bezierPoint=function(e,t,n,r,i){const o=1-i;return Math.pow(o,3)*e+3*Math.pow(o,2)*i*t+3*o*Math.pow(i,2)*n+Math.pow(i,M 3)*r},n.curveTangent=function(e,t,n,r,i){const o=i*i;return e*(-3*o/2+2*i-.5)+t*(9*o/2-5*i)+n*(-9*o/2+4*i+.5)+r*(3*o/2-i)},n.bezierTangent=function(e,t,n,r,i){const o=1-i;return 3*r*Math.pow(i,2)-3*n*Math.pow(i,2)+6*n*o*i-6*t*o*i+3*t*Math.pow(o,2)-3*e*Math.pow(o,2)},n.Color=function(e,t,n,r){let i=this;i.MAGIC=786698,i._r=e,i._g=t,i._b=n,i._a=r,i._h=0,i._s=0,i._v=0,i._hsvInferred=!1,i.setRed=function(e){i._r=e,i._hsvInferred=!1},i.setGreen=function(e){i._g=e,i._hsvInferred=!1},i.setBlue=function(e){i._b=e,i._hsvInfM erred=!1},i.setAlpha=function(e){i._a=e/255,i._hsvInferred=!1},i._inferHSV=function(){i._hsvInferred||([i._h,i._s,i._v]=function(e,t,n){let r,i,o,a,l;return r=e<t?e<n?e:n:t<n?t:n,0==(l=100*(i=e>t?e>n?e:n:t>n?t:n)/255)?[o=0,a=0,l]:0==(a=100*(i-r)/i)?[o=0,a,l]:(o=i==e?0+60*(t-n)/(i-r):i==t?120+60*(n-e)/(i-r):240+60*(e-t)/(i-r),[o,a,l])}(i._r,i._g,i._b),i._hsvInferred=!0)},i.toString=function(){return`rgba(${Math.round(i._r)},${Math.round(i._g)},${Math.round(i._b)},${~~(1e3*i._a)/1e3})`}},n.colorMode=function(e){n._stM yle.colorMode=e},n.color=function(){if(1==arguments.length&&786698==arguments[0].MAGIC)return arguments[0];if(n._style.colorMode==n.RGB){if(1==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],1);if(2==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],arguments[1]/255);if(3==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],1);if(4==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],arguments[3]/255)}else{if(1==argumeM nts.length)return new n.Color(...x(0,0,arguments[0]/100),1);if(2==arguments.length)return new n.Color(...x(0,0,arguments[0]/100),arguments[1]/255);if(3==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),1);if(4==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),arguments[3])}return null},n.red=function(e){return e._r},n.green=function(e){return e._g},n.blue=function(e){return e._b},n.alpha=function(e){return 255*e._a},n.hue=function(e){reM turn e._inferHSV(),e._h},n.saturation=function(e){return e._inferHSV(),e._s},n.brightness=function(e){return e._inferHSV(),e._v},n.lightness=function(e){return 100*(.2126*e._r+.7152*e._g+.0722*e._b)/255},n.lerpColor=function(e,t,r){return n._style.colorMode==n.RGB?new n.Color(n.constrain(n.lerp(e._r,t._r,r),0,255),n.constrain(n.lerp(e._g,t._g,r),0,255),n.constrain(n.lerp(e._b,t._b,r),0,255),n.constrain(n.lerp(e._a,t._a,r),0,1)):(e._inferHSV(),t._inferHSV(),new n.Color(n.constrain(function(e,t,r){var i=[[Math.abs(t-M e),n.map(r,0,1,e,t)],[Math.abs(t+360-e),n.map(r,0,1,e,t+360)],[Math.abs(t-360-e),n.map(r,0,1,e,t-360)]];return i.sort(((e,t)=>e[0]-t[0])),(i[0][1]+720)%360}(e._h,t._h,r),0,360),n.constrain(n.lerp(e._s,t._s,r),0,100),n.constrain(n.lerp(e._v,t._v,r),0,100),n.constrain(n.lerp(e._a,t._a,r),0,1)))},n.strokeWeight=function(e){n._style_noStroke=!1,r.lineWidth=e},n.stroke=function(){if(n._style.noStroke=!1,"string"==typeof arguments[0])return void(r.strokeStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._sM tyle.noStroke=!0:r.strokeStyle=e},n.noStroke=function(){n._style.noStroke=!0},n.fill=function(){if(n._style.noFill=!1,"string"==typeof arguments[0])return void(r.fillStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._style.noFill=!0:r.fillStyle=e},n.noFill=function(){n._style.noFill=!0},n.blendMode=function(e){r.globalCompositeOperation=e},n.strokeCap=function(e){r.lineCap=e},n.strokeJoin=function(e){r.lineJoin=e},n.ellipseMode=function(e){n._style.ellipseMode=e},n.rectMode=function(e){n._style.rectM Mode=e},n.curveDetail=function(e){n._style.curveDetail=e},n.curveAlpha=function(e){n._style.curveAlpha=e},n.curveTightness=function(e){n._style.curveAlpha=e},n.clear=function(){r.clearRect(0,0,n.width,n.height)},n.background=function(){if(arguments[0]&&arguments[0].MAGIC==n.MAGIC)return n.image(arguments[0],0,0,n.width,n.height);r.save(),r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity),r.fillStyle="string"==typeof arguments[0]?arguments[0]:n.color(...Array.from(arguments)),r.fillRect(0,0,n.width,n.heightM ),r.restore()},n.line=function(e,t,i,o){n._style.noStroke||(r.beginPath(),r.moveTo(e,t),r.lineTo(i,o),r.stroke())},n.arc=function(e,t,r,i,o,a,l,s){if(o==a)return n.ellipse(e,t,r,i);null==s&&(s=25),null==l&&(l=n.PIE),n._style.ellipseMode==n.CENTER?m(e,t,r,i,o,a,l,s):n._style.ellipseMode==n.RADIUS?m(e,t,2*r,2*i,o,a,l,s):n._style.ellipseMode==n.CORNER?m(e+r/2,t+i/2,r,i,o,a,l,s):n._style.ellipseMode==n.CORNERS&&m((e+r)/2,(t+i)/2,r-e,i-t,o,a,l,s)},n.ellipse=function(e,t,r,i){null==i&&(i=r),n._style.ellipseMode==n.CENTERM ?b(e,t,r,i):n._style.ellipseMode==n.RADIUS?b(e,t,2*r,2*i):n._style.ellipseMode==n.CORNER?b(e+r/2,t+i/2,r,i):n._style.ellipseMode==n.CORNERS&&b((e+r)/2,(t+i)/2,r-e,i-t)},n.circle=function(e,t,r){return n.ellipse(e,t,r,r)},n.point=function(e,t){e.x&&(t=e.y,e=e.x),r.beginPath(),r.ellipse(e,t,.4,.4,0,0,2*Math.PI),r.stroke()},n.rect=function(e,t,r,i,o,a,l,s){n._style.rectMode==n.CENTER?y(e-r/2,t-i/2,r,i,o,a,l,s):n._style.rectMode==n.RADIUS?y(e-r,t-i,2*r,2*i,o,a,l,s):n._style.rectMode==n.CORNER?y(e,t,r,i,o,a,l,s):n._stylM e.rectMode==n.CORNERS&&y(e,t,r-e,i-t,o,a,l,s)},n.square=function(e,t,r,i,o,a,l){return n.rect(e,t,r,r,i,o,a,l)},n.beginShape=function(){w(),r.beginPath(),o=!0},n.beginContour=function(){r.closePath(),w(),o=!0},n.endContour=function(){w(),o=!0},n.vertex=function(e,t){w(),o?r.moveTo(e,t):r.lineTo(e,t),o=!1},n.bezierVertex=function(e,t,n,i,o,a){w(),r.bezierCurveTo(e,t,n,i,o,a)},n.quadraticVertex=function(e,t,n,i){w(),r.quadraticCurveTo(e,t,n,i)},n.bezier=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.bezierVM ertex(r,i,o,a,l,s),n.endShape()},n.triangle=function(e,t,r,i,o,a){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.endShape(n.CLOSE)},n.quad=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.vertex(l,s),n.endShape(n.CLOSE)},n.endShape=function(e){w(),e&&r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke(),n._style.noFill&&n._style.noStroke&&(r.save(),r.fillStyle="none",r.fill(),r.restore())},n.curveVertex=function(e,t){if(a.push([e,t]),a.length<4)return;M let i=function(e,t,n,r,i,o,a,l,s,h){function c(e,t,n,r,i,o){let a=Math.pow(r-t,2)+Math.pow(i-n,2);return Math.pow(a,.5*o)+e}let u=[],f=c(0,e,t,n,r,h),d=c(f,n,r,i,o,h),x=c(d,i,o,a,l,h);for(let h=0;h<s;h++){let c=f+h/(s-1)*(d-f),g=[(f-c)/(f-0),(c-0)/(f-0),(d-c)/(d-f),(c-f)/(d-f),(x-c)/(x-d),(c-d)/(x-d),(d-c)/(d-0),(c-0)/(d-0),(x-c)/(x-f),(c-f)/(x-f)];for(let e=0;e<g.length;e+=2)isNaN(g[e])&&(g[e]=1,g[e+1]=0),isFinite(g[e])||(g[e]>0?(g[e]=1,g[e+1]=0):(g[e]=0,g[e+1]=1));let p=e*g[0]+n*g[1],m=t*g[0]+r*g[1],b=n*g[2]+i*g[M 3],y=r*g[2]+o*g[3],w=i*g[4]+a*g[5],v=o*g[4]+l*g[5],z=p*g[6]+b*g[7],V=m*g[6]+y*g[7],_=b*g[8]+w*g[9],M=y*g[8]+v*g[9],E=z*g[2]+_*g[3],S=V*g[2]+M*g[3];u.push([E,S])}return u}(...a[a.length-4],...a[a.length-3],...a[a.length-2],...a[a.length-1],n._style.curveDetail,n._style.curveAlpha);for(let e=0;e<i.length;e++)o?r.moveTo(...i[e]):r.lineTo(...i[e]),o=!1},n.curve=function(e,t,r,i,o,a,l,s){n.beginShape(),n.curveVertex(e,t),n.curveVertex(r,i),n.curveVertex(o,a),n.curveVertex(l,s),n.endShape()},n.translate=function(e,t){r.tM ranslate(e,t)},n.rotate=function(e){r.rotate(e)},n.scale=function(e,t){null==t&&(t=e),r.scale(e,t)},n.applyMatrix=function(e,t,n,i,o,a){r.transform(e,t,n,i,o,a)},n.shearX=function(e){r.transform(1,0,Math.tan(e),1,0,0)},n.shearY=function(e){r.transform(1,Math.tan(e),0,1,0,0)},n.resetMatrix=function(){r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity)},n.pushMatrix=n.push=function(){n._styleCache.push({...n._style}),n._style=n._styleCache[n._styleCache.length-1],r.save()},n.popMatrix=n.pop=function(){n._stylM eCache.length-1&&(n._styleCache.pop(),n._style=n._styleCache[n._styleCache.length-1],r.restore())},n.image=function(e,t,i,o,a,l,s,h,c){let u=e.MAGIC==n.MAGIC?e.canvas:e;function d(){if(e.MAGIC!=n.MAGIC||!n._tint)return;let t=e.canvas.getContext("2d");t.save(),t.resetTransform(),t.clearRect(0,0,t.canvas.width,t.canvas.height),t.drawImage(f.canvas,0,0),t.restore()}return e.MAGIC==n.MAGIC&&null!=n._tint&&(function(e,t){null==f&&(f=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvasM .height),f.canvas.width==e&&f.canvas.height==t||(f.canvas.width=e,f.canvas.height=t)}(e.canvas.width,e.canvas.height),f.drawImage(e.canvas,0,0),e.tinted(n._tint)),o?l?(h||(h=u.width),c||(c=u.height),r.drawImage(u,l,s,h,c,t,i,o,a),void d()):(r.drawImage(u,t,i,o,a),void d()):(e.MAGIC==n.MAGIC||e.width?r.drawImage(u,t,i,e.width,e.height):r.drawImage(u,t,i,e.videoWidth,e.videoHeight),void d())},n.loadPixels=function(){l=r.getImageData(0,0,n.canvas.width,n.canvas.height),n.pixels=l.data},n.updatePixels=function(){null!=M l&&r.putImageData(l,0,0)},n.loadImage=function(e,t){s++;let r=n.createGraphics(100,100),i=r.canvas.getContext("2d"),o=new Image;return o.src=e,o.crossOrigin="Anonymous",o.onload=function(){i.canvas.width=o.width,i.canvas.height=o.height,r.width=o.width,r.height=o.height,i.drawImage(o,0,0),s--,t&&t(r)},r};let v={};function z(e,t){null==u&&(u=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvas.height),u.canvas.width==e&&u.canvas.height==t||(u.canvas.width=e,u.canvas.height=t)}funcM tion V(){let e=r.canvas.width*r.canvas.height*4;null!=d&&e==d.length||(d=new Uint8ClampedArray(e))}function _(e){u.clearRect(0,0,u.canvas.width,u.canvas.height),u.filter=e,u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()}v[n.THRESHOLD]=function(e,t){null==t?t=127.5:t*=255;for(let n=0;n<e.length;n+=4){const r=.2126*e[n]+.7152*e[n+1]+.0722*e[n+2];e[n]=e[n+1]=e[n+2]=r>=t?255:0}},v[n.GRAY]=function(e){for(let t=0;t<e.length;t+=4)M {const n=.2126*e[t]+.7152*e[t+1]+.0722*e[t+2];e[t]=e[t+1]=e[t+2]=n}},v[n.OPAQUE]=function(e){for(let t=0;t<e.length;t+=4)e[t+3]=255},v[n.INVERT]=function(e){for(let t=0;t<e.length;t+=4)e[t]=255-e[t],e[t+1]=255-e[t+1],e[t+2]=255-e[t+2]},v[n.POSTERIZE]=function(e,t){let n=t-1;for(let r=0;r<e.length;r+=4)e[r]=255*(e[r]*t>>8)/n,e[r+1]=255*(e[r+1]*t>>8)/n,e[r+2]=255*(e[r+2]*t>>8)/n},v[n.DILATE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-M 1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.max(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.ERODE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.min(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.BLURM ]=function(e,t){t=t||1,t=Math.floor(t*n._pixelDensity),V(),d.set(e);let i=2*t+1,o=function(e){let n=new Float32Array(e),r=.3*t+.8,i=r*r*2;for(let t=0;t<e;t++){let o=t-e/2,a=Math.exp(-o*o/i)/(2.5066282746*r);n[t]=a}return n}(i),[a,l]=[r.canvas.width,r.canvas.height];for(let n=0;n<l;n++)for(let r=0;r<a;r++){let l=0,s=0,h=0,c=0;for(let e=0;e<i;e++){let i=4*(n*a+Math.min(Math.max(r-t+e,0),a-1));l+=d[i]*o[e],s+=d[i+1]*o[e],h+=d[i+2]*o[e],c+=d[i+3]*o[e]}let u=4*(n*a+r);e[u]=l,e[u+1]=s,e[u+2]=h,e[u+3]=c}d.set(e);for(let nM =0;n<l;n++)for(let r=0;r<a;r++){let s=0,h=0,c=0,u=0;for(let e=0;e<i;e++){let i=4*(Math.min(Math.max(n-t+e,0),l-1)*a+r);s+=d[i]*o[e],h+=d[i+1]*o[e],c+=d[i+2]*o[e],u+=d[i+3]*o[e]}let f=4*(n*a+r);e[f]=s,e[f+1]=h,e[f+2]=c,e[f+3]=u}},n.filter=function(e,t){if(n.HARDWARE_FILTERS&&null!=r.filter)if(z(),e==n.THRESHOLD){null==t&&(t=.5),t=Math.max(t,1e-5),_(`saturate(0%) brightness(${Math.floor(.5/t*100)}%) contrast(1000000%)`)}else if(e==n.GRAY)_("saturate(0%)");else if(e==n.OPAQUE)u.fillStyle="black",u.fillRect(0,0,u.canvaM s.width,u.canvas.height),u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.drawImage(u.canvas,0,0),r.restore();else if(e==n.INVERT)_("invert(100%)");else if(e==n.BLUR)_(`blur(${Math.ceil(t*n._pixelDensity/1)||1}px)`);else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}},n.resize=function(e,t){z(),u.drawImage(r.canvas,0,0),n.width=e,n.height=t,r.canvas.width=e*n._pixM elDensity,r.canvas.height=t*n._pixelDensity,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0,r.canvas.width,r.canvas.height),r.restore()},n.get=function(e,t,i,o){if(null!=e&&null==i){let i=r.getImageData(e,t,1,1).data;return new n.Color(i[0],i[1],i[2],i[3]/255)}e=e||0,t=t||0,i=i||n.width,o=o||n.height;let a=n.createGraphics(i,o);a.pixelDensity(n._pixelDensity);let l=r.getImageData(e*n._pixelDensity,t*n._pixelDensity,i*n._pixelDensity,o*n._pixelDensity);return a.caM nvas.getContext("2d").putImageData(l,0,0),a},n.set=function(e,t,i){if(i.MAGIC==n.MAGIC){let r=n._tint;return n._tint=null,n.image(i,e,t),void(n._tint=r)}let o=4*(t*n._pixelDensity*r.canvas.width+e*n._pixelDensity);n.pixels[o]=i._r,n.pixels[o+1]=i._g,n.pixels[o+2]=i._b,n.pixels[o+3]=255*i._a},n.tinted=function(){let e=n.color(...Array.from(arguments)),t=e._a;e._a=1,z(),u.clearRect(0,0,u.canvas.width,u.canvas.height),u.fillStyle=e,u.fillRect(0,0,u.canvas.width,u.canvas.height),u.globalCompositeOperation="multiply",u.M drawImage(r.canvas,0,0),u.globalCompositeOperation="source-over",r.save(),r.resetTransform();let i=r.globalCompositeOperation;r.globalCompositeOperation="source-in",r.drawImage(u.canvas,0,0),r.globalCompositeOperation=i,r.restore(),u.globalAlpha=t,u.clearRect(0,0,u.canvas.width,u.canvas.height),u.drawImage(r.canvas,0,0),u.globalAlpha=1,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()},n.tint=function(){n._tint=n.color(...Array.from(arguments))},n.noTiM nt=function(){n._tint=null},n.mask=function(e){r.save(),r.resetTransform();let t=r.globalCompositeOperation;r.globalCompositeOperation="destination-in",r.drawImage(e.canvas,0,0),r.globalCompositeOperation=t,r.restore()},n.clearTemporaryBuffers=function(){u=null,f=null,d=null},n.save=function(e,t){e=e||"untitled",t=t||"png";var n=document.createElement("a");n.innerHTML="[Download]",n.addEventListener("click",(function(){this.href=r.canvas.toDataURL(),this.download=e+"."+t}),!1),document.body.appendChild(n),n.click()M ,document.body.removeChild(n)},n.saveCanvas=function(e,t,r){if(e.MAGIC==n.MAGIC){r&&e.save(t,r);let n=t.split(".");return e.save(n.slice(0,-1).join("."),n[n.length-1])}if(t)return n.save(e,t);let i=e.split(".");return n.save(i.slice(0,-1).join("."),i[i.length-1])},n.loadFont=function(e){let t=e.split("/"),n=t[t.length-1].split(".")[0].replace(" ",""),r=`@font-face {\n font-family: '${n}';\n src: url('${e}');\n }`;const i=document.createElement("style");return i.textContent=r,document.head.append(M i),n},n.textFont=function(e){n._style.textFont=e},n.textSize=function(e){n._style.textSize=e,n._style.textLeading=e},n.textLeading=function(e){n._style.textLeading=e},n.textStyle=function(e){n._style.textStyle=e},n.textAlign=function(e,t){r.textAlign=e,t&&(r.textBaseline=t==n.CENTER?"middle":t)},n.text=function(e,t,i,o){if(!e)return;if(e=e.toString(),n._style.noFill&&n._style.noStroke)return;r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`;let a=e.split("\n");for(let e=0;e<a.length;e++)n._M style.noFill||r.fillText(a[e],t,i,o),n._style.noStroke||r.strokeText(a[e],t,i,o),i+=n._style.textLeading},n.textWidth=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).width},n.textAscent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBoundingBoxAscent},n.textDescent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBounM dingBoxDescent};var M,E=4,S=.5,R=function(e){return.5*(1-Math.cos(e*Math.PI))};n.noise=function(e,t,n){if(t=t||0,n=n||0,null==M){M=new Array(4096);for(var r=0;r<4096;r++)M[r]=Math.random()}e<0&&(e=-e),t<0&&(t=-t),n<0&&(n=-n);for(var i,o,a,l,s,h=Math.floor(e),c=Math.floor(t),u=Math.floor(n),f=e-h,d=t-c,x=n-u,g=0,p=.5,m=0;m<E;m++){var b=h+(c<<4)+(u<<8);i=R(f),o=R(d),a=M[4095&b],a+=i*(M[b+1&4095]-a),l=M[b+16&4095],a+=o*((l+=i*(M[b+16+1&4095]-l))-a),l=M[4095&(b+=256)],l+=i*(M[b+1&4095]-l),s=M[b+16&4095],l+=o*((s+=i*(M[M b+16+1&4095]-s))-l),g+=(a+=R(x)*(l-a))*p,p*=S,h<<=1,c<<=1,u<<=1,(f*=2)>=1&&(h++,f--),(d*=2)>=1&&(c++,d--),(x*=2)>=1&&(u++,x--)}return g},n.noiseDetail=function(e,t){e>0&&(E=e),t>0&&(S=t)};const I=function(){let e,t,n=4294967295;return{setSeed(r){e=t=(null==r?Math.random()*n:r)>>>0},getSeed:()=>t,rand:()=>(e^=e<<17,e^=e>>13,((e^=e<<5)>>>0)/n)}};let C=I();C.setSeed(),n.noiseSeed=function(e){let t=null==e?4294967295*Math.random():e;M||(M=new Float32Array(4096));for(var n=0;n<4096;n++)t^=t<<17,t^=t>>13,t^=t<<5,M[n]=(t>M >>0)/4294967295},n.randomSeed=function(e){C.setSeed(e)},n.random=function(e,t){return null==e?C.rand():"number"==typeof e?null!=t?C.rand()*(t-e)+e:C.rand()*e:e[~~(e.length*C.rand())]},n.randomGenerator=function(e){e==n.LCG?C=function(){const e=4294967296;let t,n;return{setSeed(r){n=t=(null==r?Math.random()*e:r)>>>0},getSeed:()=>t,rand:()=>(n=(1664525*n+1013904223)%e)/e}}():e==n.SHR3&&(C=I()),C.setSeed()};var T=new function(){var e,t,n,r=new Array(128),i=new Array(256),o=new Array(128),a=new Array(128),l=new Array(2M 56),s=new Array(256),h=function(){return 4294967296*C.rand()-2147483648},c=function(){return.5+2.328306e-10*(h()<<0)};this.SHR3=h,this.UNI=c,this.RNOR=function(){return n=h(),e=127&n,Math.abs(n)<r[e]?n*o[e]:function(){for(var t,i,l,s,u=3.44262;;){if(t=n*o[e],0==e){do{l=c(),s=c(),t=.2904764*-Math.log(l),i=-Math.log(s)}while(i+i<t*t);return n>0?u+t:-u-t}if(a[e]+c()*(a[e-1]-a[e])<Math.exp(-.5*t*t))return t;if(n=h(),e=127&n,Math.abs(n)<r[e])return n*o[e]}}()},this.REXP=function(){return(t=h()>>>0)<r[e=255&t]?t*l[e]:funM ction(){for(var n;;){if(0==e)return 7.69711-Math.log(c());if(n=t*l[e],s[e]+c()*(s[e-1]-s[e])<Math.exp(-n))return n;if((t=h())<i[e=255&t])return t*l[e]}}()},this.zigset=function(){var e,t,n=2147483648,h=4294967296,c=3.442619855899,u=c,f=.00991256303526217,d=7.697117470131487,x=d,g=.003949659822581572;for(e=f/Math.exp(-.5*c*c),r[0]=Math.floor(c/e*n),r[1]=0,o[0]=e/n,o[127]=c/n,a[0]=1,a[127]=Math.exp(-.5*c*c),t=126;t>=1;t--)c=Math.sqrt(-2*Math.log(f/c+Math.exp(-.5*c*c))),r[t+1]=Math.floor(c/u*n),u=c,a[t]=Math.exp(-.5*cM *c),o[t]=c/n;for(e=g/Math.exp(-d),i[0]=Math.floor(d/e*h),i[1]=0,l[0]=e/h,l[255]=d/h,s[0]=1,s[255]=Math.exp(-d),t=254;t>=1;t--)d=-Math.log(g/d+Math.exp(-d)),i[t+1]=Math.floor(d/x*h),x=d,s[t]=Math.exp(-d),l[t]=d/h}};T.hasInit=!1,n.randomGaussian=function(e,t){return T.hasInit||(T.zigset(),T.hasInit=!0),T.RNOR()*t+e},n.randomExponential=function(){return T.hasInit||(T.zigset(),T.hasInit=!0),T.REXP()},n.print=console.log,n.cursor=function(e,t,r){let i="";e.includes(".")&&(e=`url("${e}")`,i=", auto"),null!=t&&(e+=" "+t+M " "+r),n.canvas.style.cursor=e+i},n.noCursor=function(){n.canvas.style.cursor="none"},n.createCapture=function(e){var t=document.createElement("video");return t.playsinline="playsinline",t.autoplay="autoplay",navigator.mediaDevices.getUserMedia(e).then((function(e){t.srcObject=e})),t.style.position="absolute",t.style.opacity=1e-5,t.style.zIndex=-1e3,document.body.appendChild(t),t};let A=["setup","draw","preload","mouseMoved","mousePressed","mouseReleased","mouseDragged","mouseClicked","keyPressed","keyReleased","keM yTyped","touchStarted","touchEnded"];for(let e of A){let t="_"+e+"Fn";n[t]=function(){},n[t].isPlaceHolder=!0,n[e]?n[t]=n[e]:Object.defineProperty(n,e,{set:function(e){n[t]=e}})}function D(){n._noLoop||(i=null==n._frameRate?requestAnimationFrame(D):setTimeout(D,1e3/n._frameRate)),w(),o=!0,n.push(),n._drawFn(),n.pop(),++n.frameCount}function k(e){const t=n.canvas.getBoundingClientRect(),r=n.canvas.scrollWidth/n.width||1,i=n.canvas.scrollHeight/n.height||1;return{x:(e.clientX-t.left)/r,y:(e.clientY-t.top)/i,id:e.idenM tifier}}function L(){return n._touchStarted.isPlaceHolder&&n._touchMoved.isPlaceHolder&&n._touchEnded.isPlaceHolder}n.noLoop=function(){n._noLoop=!0,i=null},n.loop=function(){n._noLoop=!1,null==i&&D()},n.redraw=function(){D()},n.frameRate=function(e){n._frameRate=e},setTimeout((function(){n._preloadFn(),c=window.performance.now(),function e(){if(s>0)return setTimeout(e,10);n._setupFn(),D()}()}),1),n.canvas.onmousemove=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPM ressed?n._mouseDraggedFn(e):n._mouseMovedFn(e)},n.canvas.onmousedown=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!0,n.mouseButton=[n.LEFT,n.CENTER,n.RIGHT][e.button],n._mousePressedFn(e)},n.canvas.onmouseup=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!1,n._mouseReleasedFn(e)},n.canvas.onclick=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressedM =!0,n._mouseClickedFn(e),n.mouseIsPressed=!1},window.addEventListener("keydown",(function(e){n.keyIsPressed=!0,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!0,n._keyPressedFn(e),1==e.key.length&&n._keyTypedFn(e)})),window.addEventListener("keyup",(function(e){n.keyIsPressed=!1,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!1,n._keyReleasedFn(e)})),n.keyIsDown=function(e){return!!h[e]},n.canvas.ontouchstart=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.moM useY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mousePressedFn(e)||e.preventDefault()),n._touchStartedFn(e)||e.preventDefault()},n.canvas.ontouchmove=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mouseDraggedFn(e)||e.preventDefault()),n._touchMovedFn(e)||e.preventDefault()},n.canvas.ontouchend=n.canvas.ontouchcancel=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.M mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!1,n._mouseReleasedFn(e)||e.preventDefault()),n._touchEndedFn(e)||e.preventDefault()},n.hasSensorPermission=!window.DeviceOrientationEvent&&!window.DeviceMotionEvent||!(DeviceOrientationEvent.requestPermission||DeviceMotionEvent.requestPermission),n.requestSensorPermissions=function(){DeviceOrientationEvent.requestPermission&&DeviceOrientationEvent.requestPermission().then((e=>{"granted"==e&&DeviceMotionEvent.requestPermissioM n&&DeviceMotionEvent.requestPermission().then((e=>{"granted"==e&&(n.hasSensorPermission=!0)})).catch(alert)})).catch(alert)},window.ondeviceorientation=function(e){n.pRotationX=n.rotationX,n.pRotationY=n.rotationY,n.pRotationZ=n.rotationZ,n.pRelRotationX=n.relRotationX,n.pRelRotationY=n.relRotationY,n.pRelRotationZ=n.relRotationZ,n.rotationX=e.beta*(Math.PI/180),n.rotationY=e.gamma*(Math.PI/180),n.rotationZ=e.alpha*(Math.PI/180),n.relRotationX=[-n.rotationY,-n.rotationX,n.rotationY][1+~~(window.orientation/90)],n.rM elRotationY=[-n.rotationX,n.rotationY,n.rotationX][1+~~(window.orientation/90)],n.relRotationZ=n.rotationZ},window.ondevicemotion=function(e){if(n.pAccelerationX=n.accelerationX,n.pAccelerationY=n.accelerationY,n.pAccelerationZ=n.accelerationZ,!e.acceleration){let t=((e,t)=>[(e[0]*t[0]+e[1]*t[1]+e[2]*t[2]+e[3])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[4]*t[0]+e[5]*t[1]+e[6]*t[2]+e[7])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[8]*t[0]+e[9]*t[1]+e[10]*t[2]+e[11])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15])])(((e,t)M =>[e[0]*t[0]+e[1]*t[4]+e[2]*t[8]+e[3]*t[12],e[0]*t[1]+e[1]*t[5]+e[2]*t[9]+e[3]*t[13],e[0]*t[2]+e[1]*t[6]+e[2]*t[10]+e[3]*t[14],e[0]*t[3]+e[1]*t[7]+e[2]*t[11]+e[3]*t[15],e[4]*t[0]+e[5]*t[4]+e[6]*t[8]+e[7]*t[12],e[4]*t[1]+e[5]*t[5]+e[6]*t[9]+e[7]*t[13],e[4]*t[2]+e[5]*t[6]+e[6]*t[10]+e[7]*t[14],e[4]*t[3]+e[5]*t[7]+e[6]*t[11]+e[7]*t[15],e[8]*t[0]+e[9]*t[4]+e[10]*t[8]+e[11]*t[12],e[8]*t[1]+e[9]*t[5]+e[10]*t[9]+e[11]*t[13],e[8]*t[2]+e[9]*t[6]+e[10]*t[10]+e[11]*t[14],e[8]*t[3]+e[9]*t[7]+e[10]*t[11]+e[11]*t[15],e[12]*t[0]+M e[13]*t[4]+e[14]*t[8]+e[15]*t[12],e[12]*t[1]+e[13]*t[5]+e[14]*t[9]+e[15]*t[13],e[12]*t[2]+e[13]*t[6]+e[14]*t[10]+e[15]*t[14],e[12]*t[3]+e[13]*t[7]+e[14]*t[11]+e[15]*t[15]])((e=>[Math.cos(e),0,Math.sin(e),0,0,1,0,0,-Math.sin(e),0,Math.cos(e),0,0,0,0,1])(n.rotationY),(e=>[1,0,0,0,0,Math.cos(e),-Math.sin(e),0,0,Math.sin(e),Math.cos(e),0,0,0,0,1])(n.rotationX)),[0,0,-9.80665]);n.accelerationX=e.accelerationIncludingGravity.x+t[0],n.accelerationY=e.accelerationIncludingGravity.y+t[1],n.accelerationZ=e.accelerationIncludM ingGravity.z-t[2]}},n.year=function(){return(new Date).getFullYear()},n.day=function(){return(new Date).getDay()},n.hour=function(){return(new Date).getHours()},n.minute=function(){return(new Date).getMinutes()},n.second=function(){return(new Date).getSeconds()},n.millis=function(){return window.performance.now()-c}}(e)}"object"==typeof exports&&"undefined"!=typeof module&&(module.exports=e);const t="https://ancient-crimson-rain.btc.discover.quiknode.pro/c268fb026303ae8443f785200f2ea4b82f0082dd";function n(e){P(e)?M localStorage.removeItem("blocksApiEndpoint"):localStorage.blocksApiEndpoint=e}function r(){return localStorage.blocksApiEndpoint||t}function i(e){P(e)?localStorage.removeItem("modelInscriptionEndpoint"):localStorage.modelInscriptionEndpoint=e}function o(){return localStorage.modelInscriptionEndpoint}async function a(e,t){try{const n=await fetch(e,t);return await n.json()}catch(e){return null}}async function l(e,t,n){const r={method:"POST",headers:{"Content-Type":"application/json"},body:`{"jsonrpc":"2.0","id":1,"meM thod":"${t}","params":${`[${n.join(sep=",")}]`}}`};return(await a(e,r))?.result}async function s(e){const n={avgfee:10,time:Date.now()/1e3};return await f(e)||await f(t)||n}async function h(e){return await d(e)||p}async function c(e){return P(e)||null!=await f(e)}async function u(e){return P(e)||null!=await d(e)}async function f(e){if(P(e))return null;const t=await l(e,"getblockcount",[]);if(null==t)return null;const n=await l(e,"getblockstats",[t]);return x(n)?n:null}async function d(e){if(P(e))return null;const tM =await a(e,{});return g(t)?t:null}function x(e){return"number"==typeof e?.time&&"number"==typeof e?.avgfee}function g(e){if(null==e)return!1;const{classes_name:t,training_traits:n,layers_config:r,weight_b64:i}=e;if(!Array.isArray(t))return!1;if(null==n)return!1;try{j(r,i)}catch(e){return!1}return!0}const p={"model_name": "pfp_classifier_28", "layers_config": {"config": {"layers": [{"class_name": "InputLayer", "config": {"batch_input_shape": [null, 28, 28, 3]}}, {"class_name": "Rescaling", "config": {"scale": 0.0078M 4313725490196, "offset": -1}}, {"class_name": "Flatten"}, {"class_name": "Dense", "config": {"units": 12, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 10, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 9, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 9, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 4, "activation": "linear"}}]}}, "weight_b64": "Kuo/PRVwdb2AXeo8+sSzvN3M6zoqmlc9MUAbvXQv6LzS6aG85hbIuxlinT3rWwy8PvFdvW0Yazziocq952+gPM 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 aK9ia4Jvlsipzxchnc9ADPQPDxCKb1zvAQ98+0vPSRxkzuOzfm7D3bqvHTX9Lye4ia9EugpuziRGT2cKCU9nrpLPT3idT2yKwW9IX10vfiHE72PtX69uQgePF/5OL2hxzW9wf+QPTKcST14gag9Qb0svXm6TTwN54G9GOjiO7k9Lj08NDw8qqYJvQwqujt5zPK8W4XGvd6wGr1EZZs9sFQePbusx7ucqZK8s31fO2PYbbyVpKQ8Aj5lPLewhbwTt9a8iQxGPU8PLzth5Is9ZK0fPXMGB738bjG6THOEvTHlzryTcQC9gsDCPO+SzDwcvW89dSPqPRuhULx4kAE9wUHlvEFVazxPtiy9wbyrvYuvrTxC5p279CaAvFk/J720Oie9ehC2vcUeXbzoN9E9qU93O7USA7zOqUS9Bh1pPcD/mzwW/x499SHHPJB1Tb0M3mA9RcX4vOjd5bwpc0m7aWkGPTVBvTxxeR68Kp6GvRjIUz1FJwM93TC0PF+kYT3ToWc95gidPM 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 TcZEjvDo2w7AXyIvc/8nz1xGbQ9sCwwPTk8ijyqqYI80VzGvficzrxFaw47zx99vG64Lbz+s4Y8+UnqPNhSVTxtCjs8CK2ivGedCbxRKxU9kzKdO2Fk1rzQvuu8bjuZPTj+kD0pMOI8dMZTPHZ/iz1d9cy8VdtSvbkGIL3WT5Q7F7rUPYxnsjxIT/C8A0wIPW8sqDy0cRa9VM8Mvd5vZT0xXhs8tVTHPPTYi7l1/Aw95k+1uoUtS7v0yf48tbtlPeCSsLp5gbe8nOhqPP0pjztKMqM9AbDYuuBXcDxvYHk9E9HpvB4agr1VVxI82MtRPCqDez0n/iQ9Hi5pvV94kDtTpk49rDcWvRduEr2Wj409BA3bPKsvE72Frdi8civ0vEVYBDz+Btu81ruOPNnJdD3Sl5M9pV1GvXy9+jyYs1c97OVZvbaHVzyyVUE96N2UvE08D72ntiO9+DLpO+i/Lz081z+6IqENvGy0Ozv6zki9Fo8vPS1dHbzdmQs9KjYPPZqASzx3dM 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 5r3QDyr51U9RL0DPWhXvb2ryVo9A1JlPe3iPb3rSo+7Y6+mPBXlbrxDOwe9PpUnvKQKUD3d6Y480QgUPX7/Cb3dzhA96O09PfxPGL2NQFw9NEcUvW0UObwqCC08XVyMPGikEb3hmzk9QO4xOlvwJL2T7eu8m17ovCN4S71th3y7rpdnPU/LvbxNH9G8ipmzu6x4MLwy7+08GaCsPF5xG70XEEs8Ie9yvHq1Zb2uXJQ9rT93PRQGcrxFr628/UufPIiUuzyu+jo939MVvAKLGbwdfsE8trZ2PRutBL18NJQ9bi7GPEcUXL1auqw8Ja4xvfYfBz1J3X09soT4vDfpLr2BuKG84VOGvfIWIr0hdCQ9/u8aPaA55bxa4K46ZXmYvLMkRzx6DS88siunvKAzC7yQ+bm76swHPYz9Jr0h+z89b5JnPC8dbz3U+U48fQdwveRvID1PE2w9cOGFvMYcjr0On1g8ZYi7PZNLDz1UHwE9oq0MvG5ooDwJVws9LOeAusXLmTzRUM 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 JXLvDzgKPI7n2sfvXuv1jzcHQy9XoONu89oe70Bfwa926f+O6TS0LxK19E9NzCTPA3eQT3lT8a8h7V5vYcceT3kQoS9PogIvcboRjyRK8K96FZ4PdWRVj3x4rE9CDeCva4kkj02sxk92dQKvQVrIzzP5nG85YiRPLib2Tw8n129W30EvqoTNL3ecNY98G/rvG6RmrwEO9M8SpkzPRuzHD3x0LC7qU0nvAphjr30CJm93H4hPYP2E71Lz/c78ziFu2ih7rw5swO9UV0Ju4FeAbvtIT69y1uhu4MYaTwx9qO94DG3PIn4/Twh9I89udExvWFsZT0LYY08kRclvZN7ZDxhw+48vE4RPDe3Gr3TVK28RxhevVDSbr0J9ZQ91lTgPEuG6DxhzYI7wkI+PSpsrbx2xAE9CiALPFFDYL0fnH28NRa+O7UFOLyy+zc98vksvNJSRD3/s7A8C3XRvHtHzjsI2mG9lyXDvAR7OzrGGZC9h2QvPWlWRTqqOOU9mjoXveGxijxbGM 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 Wqjcr1IY4E9znpbu+dGZ7xa8Ru9ksKDPJ3NPz35tNU9AR0nvabFp70naoq93U8+PebkjLyi9V499XX4PEcZdTzDaIG86xeDvHTHAT3NZCA9vT45vSzn97y9sNe95YLRPWO8djxyOZ89t3RlvSiu+Txe8ZG8keu6u8XkOD3hvm87LUXEvMSrv7yVxJK8tdaPveQnW7vVy3U9VUS4PEhEQr0hHZ08iYCOPcDvNb2tz1U9b0N5PS1RzLywyYY8GrvaPGwAC7wD5C09f9yivDldMz08KLG64smjvBQR+TpFcFG9cfk8PUjk3jyYkTS965OiPXMrljyuuog9vDEIvfOOu7o1GKy8fW0gvMzBk7zkR7K8SQLaPCrl2DqfQxQ9iSESvROJFD2hMFQ96/EevPKGv70EWhC6eV8FPMdfNbzOvmY8Zsa0PDf+sjymhps9LpoBvSvtET1+0wo9bm4SvZoiJz32o8e8vKhPPQe0lTxavx29QmO7OyuEWzwOZJA8qfJPPTmZEz02aM 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 yhNKLxs0hM9EWzLPIE1gL3Wy9G8TDsePVBfirz2MFM9AiIGPN8wwzwtskI7WatPO7YsUr2S+Fk8I1OWPYYwRbw7HAO+jE+hvXPyJD1K9rM8ElayvB2+ID0DNoQ8Tk6SO1Bt3L14Gh89/E6mvFqlNL3v5ea8CL0dveHyB73WEte7R0SOvLPxy7znqHU9ZcWhPOx9D72i/ze9BircPPTcqb0jZ7C70TyAPUECd7xVNZk9bJM4PdXZ2TyPRQC9EbssPUwGmb0yeDw9/Z18PTTJjr3xNLC9M/GEvbVohz0ml2I9MYxrPd9J0bxPsqA8Kc6BPcXh372T/bi8KHsOvdsUqjyCz089KTwQvYS5GL3MNVe9kec5vYspXT3enem8Mb8hPVm5Or0kZRe9EUHaPfsA+7k+jd28QW0cPDhy1ryaL7O86AihulJQCDxKui694OXbPIxUxbzhsH08s3q/PTmcab3JZH29PLo8vTqvnTy6Obi8/SbKPKFYf735deK8TQmZvF8aCL3zVM 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 Wq9RaCpvEHTATsoM5U8Zx6VPZwSQDxAZw29zjZsvcoWvztz6O2801krPRcVZ70U4TO9odrUvD+5JL1CSgw6lGGhPRPtTrzkuNM9+23dvcLAmr2C+Z29/h7cvDiGxL3O3y48bevgPCVXE70He1289iEhPrikGr2PeOI7OciSvVfFBr5nSme9Bzl2PBEmO71/GNS8sqCoPMOnqbxMgXk8MIHvPdP8wbpfHIM9SpC1veCbxL3PA129HW4MPdNH0L1dOhW92E0dPU+BlLxBL9U8s2zyPfDPyT3sxf09vcrrvDZw3b21Gpq58J4QPJtxB7s+siq8ehHQPJ+vJz24dik9jv87PRY6CL2cJ6s7jnQ8O9OrP73lXUs9VhWSOwpWc70IY0O9CR4lvdkq/LwYIrw8eMjqPJJqXz0V0Js8GN8OPQtsnLxVCvY8UC9nO6aOBb1R+Fy9FcsGPaNr5TzQ4u48C2NJPR1kXD192Lw93ySbvLDWm7z/6Zo9188GvYRtVrwL/XO79L1ZvM 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 CA1HT1psze9upBeO/bv7b1P5Mg8jDZKPR72dz136/G7fVAXvduNyzwULZu71RpwvV63oDy+hMA8Iv9RPU/Fmr2lXVC7c7xIPO6XybzYI6+8c0v/PE6xpD332cc91MYFPU3DMD3ADYa9Ke09vQ6/vL2n0mw9DMZZPepVKj22nYO9SruEPa9Tlbv7gr892b3Pu9zCtLylI0G93V6tPA224rzsOJE85YKXPdxlEj1kiIO8r5z3PNXOez2OvQK9TQJTvd2HKz15ri08k3DNPUFs1b0cA8g8qo0mvKW4fzzWodA63iRvultQ8DyzpXA9HB+5PLBVJj0aDKK9xlHHuy9Bh73N5GQ9yhUhPU89CTs4WTm8L6pvPRpfBb1t5Mg9NEMjPezyq7yScnq85CgiPVNbor3JQQC8kG6NvMO3tjy4Thi9C9mzunAWADz1B7G8Tke2PcJDDT3huBk9UVOkPWwy2737xF69kdKJvVO/17tlsRy9BJqEPaRtdj1uG4a6QZ+vPcNVcz0WzM 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 abJsD0WoAm9sBn2vFWPCL38/Ce9nUWBPRldJj23VIs9L7ZBPf8ynT0py4a9MnktPHak+z0ROFG+WPX1PTbm1b08y2G8Eq/0vOfxJL1Baw29yBgIPT0xt706Jay8vqSXPZ0qED7NwO69XwhDPkgn6b3YqGW83ogbvZEDpr0uXEQ96e7KPAx7RTrFKaI78aGxPEzBEj47m4a9H8UdPd8gLL25d6a9tMo0PT+dsLzwUlw9D0ohPc9o/j2dBoC6vDitPNjUZz3wHOO973Y+Pbkh5r0dSYG8azNdPV3ar71EEmA9Yq7fPOrlq7yrCq689Y+rPYawmj01ALi97k69PcWRrb0BGpa9b3ZqPVZiObw61249F3svPcBbTD092VQ73pd9OxqxpzyJQaG9uXUQvX9Un70c/9O9TRzOPerAV7pPy649MSTFvCgvFD40b8e6yaxhvT5GRj3yz8a8eKKPPKSIGr1pNMO91kF0PSKOxb0onZs960KAPNO/WD10hoq9/DKBOxDkUz0GQM 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 evOir0DFMM8XiZwPe9RiDsTSUG9g3nOPa5fAL5/aqk8ancPPGK9JrxthQQ912TfPHj6RL01xg09Fsm0PTGpAzxrnPe9MViGvfuEir3+o+68SDysPLu3xj2QytU9UEkhPdN64D2JZEc9UEmKPMofbj2x0rO9t4atvcSNnL2eUhq+2eAyPnxrmTwyIno9x96kvBDETj2clhC9dDDiubxGuj25NI69LZghPQ/UDr5jOia+btIdPjKAG71pFxY9a7ZHPUjuBrvNa3w6hxiJuyXItDyYGvq92ki1vdRaDr7OT469WpO2PSK6Nj2vreY9WTHPvbWz2DoZkqi9k6ljvaJEHD2/yRM+i1vovGy8kj0FN4y9iKQ3PgWYP7qkVOM9pNUBvS5dHbyHOBu+PWizvRm3rj0hwgY9JTEWve4bzjw0ldC9vmzgPZ5wObwhmLM9ah0TvSy/UD20awK91FFUO6QBnj1Brl09xb4DO4SLSLx9qiW9QNMDvWdN5bx09K47MK6QvMzGbb2RFM 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 dM8J9yaPP2ubb1/YY+8kYyIvaiZob0rSbY9scENvejsyrwTks481OrXu93QKT1WviA9yBVhvEzbc7xRLc67+RYOPdOkAb2tNsw7qucMvAQCojuczj49nCi4PHst+LyJjDG8wBjdO4+Qgj1zSM08xqrpOVGXRL3XoJO8A9UDPLNCqjwqJA+9fJwyPIDuYj0tBYw9+l2HvEodwTxAwxU9rxpDvIUSg7wBKro8FkhzPUyOjTzlPQC9fBycPKRwZL2EKqC82DA5Pantuzz1ooi8+s0JvM6Kvjxdvca8JwmvPMLwXb3s4ig9DhE9PFWPtjwLmg+9PaoAPV8MoDu4LlI9YBhpPIXlAD0DdEc9ntgZvUmT07xfAW894kSRvNGK/jwgnoi8WT5qPfvywTwu77i8EM6svdiQwDyx6CQ8wbKcOp0tKL3NFlg8VD6fPNs16LzISgY9ky3PO9qpG71E2Uq9jpdMvO6JgL2OEVi9CaZbPKZ+K72n6rA8YwSBPErVNz3ynZo91hdxvM 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 EO9tXspPMZWsb3ejuu9hgWfPFzkszwII/g8ICGlvGIYYby7ZRC95QrluARZi71L/0S9GM2XvWz5qb1+B+G8xKsIvbVD871wdaM9CxPsu+LX6bz5eAc9aCAxPPXjgjwgWXi8PYlQvEufFb1YKa870z4jvbPAnrwCDs49Gk0IvdndQjybAYC90FOEPfp36rzVJTq9Dy6iPZKsu70vaIm9AqOhukM7AL6O/uQ8pdA+OnmytbzASG+8i3KtO9RFKDwQdQk9pGaWPJQALz2v6qY9QGkrvT5dPDzEDX29ItlsPNvO2bscW0c9pF1WvYVb3zxarZI6CRQDPlyCJT1I+Iw9HJ5BPH9kGTyDdK+9VmjovLOefj3J6ZS8yiOVPPdBVjxY3gm9HvkbPmGo47uhuYg981PaO77lFT0lyAK96u9qOBF8Xz3lcvw8A3+AvTzt9TxmY0o7/HS2vdSYcz1cUwS+xjdwPdfmBL7mOZ68MrQtPXQ7jL0jdty8qLj1PRZDc7xXaAo9KCkbOM 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 F2Rwb0mJHU8INwrPqtDJz493jA+SG1PvV2gzrx8YSS+w9a5Pbujer57fMU85QU+O3rqSL0sCcE9uvpFPmL0oD0HspM96i0FPdHmGr0Jx/y9vzJyPT5faL5DV/o8nNkBvfWRcbzjvFk9ZcupuigPjjv+FEc9ahvNu15Sh7wHgX69pkdIveqWEL0xHSA9tvzXvXSeTjsL87m9TEf9PeXD5j3L8wU979J1vQ3GCr2wjBa+PYszvc33Db6lp509fNqCvd0ILjwXhea8kCjvPWSNXD2dunm8WWx0PCoOlDrZ5BO+g2inPAYHB74QSQs9nzRcvdY3Gz3tfCm9vLjCvfAjDL0a/Z+9nTI8O4PDgr1c7LC8HcqivAgvxbgfYjA8Ju9iu7tkqD2oznu81aCau0v/G71tNU+9hvpPvQfO07zr+F08VpZYvUG4h7ySe+08p5xevHZgXjzq3828lqmMu5xn8Tv+JyK+SuBtPRFXQTuHeWK9bOldvGZpTrzUWm09/G1lPVD83Lwi/M 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 109y3LvPKxb0rwNxNw7Cosqvfn9Fr1vXES9j2hCvYSEIT3gfQg9XuxlPf+Lcz0oWHo7TuMlvVW12jxyuTs9m6MdPcsNrzuE2Iq8v5WuOybAiL3ludk8JVtbPRxLa7uoaZk9RoXKPJZx4b08a1m9Dw5lPRkuMDxaOQ+9CJAIvcPekz3TONw8EYFoPfcwdT3BR609Ssw8PNObkb1wYua8aCzqvGSpDL2RxyG9+6kkPWO5sz2/GCg+JkrXO8nzKz2DNWW87SuHvcEBqb0eZnI831CyPS8jRryBGTS96lKTPQmnRT2gyto9fRooPZmrB727RjC9Uw2oOjiRaj2TA1O8+HVOOmMin73QmLs9Zm5yPaTJSz2i+n49r2obvTE+tjz2lDs9EhhRPJegnzu5nYK9AQgrPHsFijwV5As8g8OrvEfEdTyWJgs95pciPQfLB70MQGk8aB/BvaoYVz2ESde7KKQPvSWvbDviGUE97Qy1vPeKHzziLgw8Qqe8vBqfH7w3i+q8VqQ2vM 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 uFoXj7bG0s+2zgXveCshb0iA0K+g6S1PUbRdL73ZIK7jWqQPILfHL1RmBI+ckU3PuoTzj3wrVU8suXmPCgb/bz+hMC9AK7NPMgzf77xl0o9VgxyvQDIrjp2omA9AIiOuyBk7rzDIt49BjSfPX/k8j3tIDM8DPcAvvw0ZrupqJQ8jkfFvZ8Z0L27Sum9NPY5PmtnHD3RsW09W8KqvMeXaT2xorG96yAbPfmMG76CJH48NgicvJOI5L281Ie9OVX2PTy5uD13atG75jGLvG2yoD30Ssm9x21VvdSnGb6wfro9EfCpvRT6GL0/OJm9s1qsvTVlTTwb6R89SRqPvOXwdb1IBqK9wVm9PF5RE7zmpKO7yEZeu891SD27cmI9ZVyiOySozbuTtoq9ci98PHBprb37L5u99XeMPSCexr1+udM8nGZ0PbYfjz3rYLE92AVmPAwjOzx5SWm9xxmlPLm9ZL24uca9yGRAvEgDir0tdUE9jPrHPXyHvT1VfOm8hD7bvdI3xb2HSM 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 z+yiD0tka+8LlVCvaYzjbrtz6e7+QOSPJVImr3GoqU8hc58PL7lQb0zq4W7BqabO8HDzT1DsJK8KRCwvab22TxTy6G70onoPF6Tq703vC29IcIvvITSNr1Xkd48HmcmPATgID01N728HJ7yvUAkhrxhNK48nDNvvcyTar1UhDC9SmpQPQVbuLxi3l08S8U0PNOA6j2+QC29Hupsvb3fHD31JsW8vys1vWyo8byOTwO+bzuwO8cGXL1890W85fbevNretD3ab5K9XBiyvbnXyTwgYpE8AAX8PBviujyhXsE8T7fcvc+J9b0P0Ca9zV70PGdDvDx/UAk7f79BvEK2lDxBnts86x5PPOIbzrsu5VO8xW6RvQ8DwL2WO4M7LL0SPLV4KT12vxQ8j8ayvNeZxT2PxcA86S95vR3Qpb0sMYG9mMn7vPJXlz2PRJA9ut4/vSq0G7xQMDy9y8XVPDVQYryXo+Q8pXi8PFSFzj3cHeM9tR+VvKPhZL0flaW8yFDHvPXS0r0l3M 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 wU9YTGyve7hFb2VmjG+Ol6tvUzEST0uuC49wOIpvQCmPj3Cvbs8EM+mvBsZiD2Crvy7KlJKPW2cej2wvkO9opgPPlLh1z1viLs94QuuvdKEkT2JHIo91FYxPUNV6Du1JQs9NTnKPJoUIL3BtAW+xPacPfMHlryUPqu8k+tTvYlEGT7ztVe8bryMvU3wjD2AoyI97gNMvLq8gr1jSfm9F742PYHumj2OtJE8Hw4/PWXYAryH9zI9gll1OejZqj3N+q+8fSI+PczKI7yzRzG9nIc1PnCXhj06tKw9WJmhvVzAKzyS/fs7GzfLO+4n1bzIr7y9ik2fvPDynr0g0pm9iaXhPScFjrzQRdw8E7UXveNLYDxenS09fSnZvICSoT1/JmG8efqBvEUuCb455Ca+E3EGPDORWD32uVI9NlkivM7+wb2yXLA9Z4wHPd1Uuj1J5Z+9uTJFPX4Ulj2iHgi9/fHNPQO4TD0fi5M9hRpVPCMiAT3Q1iY9BmbTPJ7rBL3Jr3u9fkiBvM 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 SS+c/oovGye4zpHB6U9ainwvKxmAD6hsmS8RAH1vOjUKb0iDIq9daaAvDe/pr3KQxK+jyLWvO0uPry4/r48oYVsvWKy5T3XZm096fYOupUrd72TYYq8mIP9vFxborzYeRa+FDCRPC9Zsj0Z4BY9ZzqfPPY8gz1vIhY9TSiMvQW+/TxtkRg8+8yHO41H1bz0Doq9lTC/PA5Y8Dxiu9M9/jievC/LAD5M3no7rV66u0UqwzsjVRM68DWHvBn4zr0cRAK+89q0u72OgD0T3dU9AkN7PKW9BT7MVLU8dtQ9PUq54rxFrBS9wg3lu+rj2L18O8+9PsE0vPgLwDzg6488lJGkPDouCT70rqI93viwvJKQBT2GtX68e71LvZRoYbzlhWq9zhUcvcyIhryjZzU9X1iwPa96GT6+iog9XD4BPBG34LzASFq95SGZvFIYOb3Qd9W9jMhRvCQVFD24jJI9pNGdu99YjD3a8hE9hVZgPddVPb1rtMu8VcuGvXV1Djx/QxS+STykvM 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 SjTkT3ISCQ9bsaZOuK+C709K5i9CiCLvCnilb3RrIu9uD8ePXtrRTzz1Y09Uay8OV4zXD3catW8Y6uQvT6KiLwaCoC9FWHEvJ/NRb203ii9HoBGPbjdEDviLCU9Sf7JPISQBD3SZcK8dr1NPWOq5jwkji89E9Xgu8E4DD69kLa9jx1NvPdek7ur6pI9l+envZOeTjw+mZO9//y2PEmy+jzHbTy9JcvLPDARnjxLsea8Rt2ZPL+kxTw55Yw96++Lu6DkrjufKqW8Q7AGPY4xsDyfU+i9vjEOPQdZxzwU2Uy9vVAkvEBsKzxuBpo8z+2BObSikz27v6u9AuAavYrDpLx+Hg+8U4G/O1qi6z3kWJk890iRvVmqKzyuyPY8mhfNvXOaTzxFx/e9wdSNO271jbyy9xq9gFxXPQdbGzw+h0u94rgAvDcDvLpwJP48dEqqvdr2ybwSx42986OFvYFZQr2j7NO9Tb4gPBvvjz27XQo9e0KGvcIgcD21ko49N6MAOwGwer2/aM qe9I74vPe5jorzYYoK84ISFvfiaCD5b+CY7ZZBDvdPvHr0pByI9BJNYvWH3G72LCqq9tdEUPEd0Z7x0pCA9yCqBPO2KpD3pJGm9TdXTPIdIOjzf6MA6NwV4vTWFyzv8Ng++sqxlPVbO6DvswLw8lNVjPAeq/T28jWe9bTo3PLqMezzzm1K7se4UvbKwS70vKha+Aqg6vRMYHb0WIJO9myVOvRnBQj5AaJk3OsVavUxDoLvfYni8McCuujwnWL262u28q6KwPFyCOjy+ve08fHBbvRUE9z29GKK9XN6WvWomtz09B6C9lm6svdom9rn3CCu9WOxivC19fT2RKZw9+tMoPSY7LD4gSI29FpsYvVJp4DxAl569y/advJNWlr2BHhO+N14tvZ/BubwyAny9XmwjPSWItD3Z7gA9VhgCvWysW7yqQpS9tOtdPZOJl72S1UU9BdyEPEpMkj3is4c9AdiFPWBPzzySZFy9kfkSPdNuiD0Nksu8EffcPGffWL2++sq8lAjzuM 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 LH3TTw26TI8IQN2PP/QSz1qD2M9JbVZvcoMCb3D4cq9so5CvKt8ejuLJIU8ahCOvdbrnjwF9Wu9unWMPIndED0hieY9DWCmvTVutTr3Pb69IksTvYpkEj1X8SU9InGPPIbANj0JQbC6c6WcO1GOjryAXky7K6h5vQl3Kj3ZsXy9DTijvHN2gL34EIY9kZCEPUbbDz1bXYw9hCWau/m7qD0LV3Y9kDZ1vYNZpzv1vR29HBA5Pdg3BD3L+8g8NbAqPWdvqT28yY48+o0GPfM6mD2TfsA9yPAMvQsm+Twgp8y9WL0MPY740DzRKde8bHwWO1lXZ7yiJ3K9n2BHPL8W4jv5SKm8l872vGIqCbttQ0O92u0zPb2vPb16rx49ZffrPd5GCL255HM97dEVvVdY+jwC4gW9RZa2PYxtXjtEX3q9ybg4PX9WhbyRj9M8myyhPTlBMDw0UUE9H02KvPLvcz3owng8IUmvPHZAm7zsxCu9zrYrPbi6aTzJLag80RIcPcnkAT2aeM Xk8g6MCPM8w0zzRqOA8KyoRPYa+uzvNu3+8Q85hvOTw/7rj0HW7M9LROm6ui7zl+sc781i9vOYgIr0sOoI8IPSKPSpt5jxoGey7TFPmu10Jjj1O+YI9I7AHPTOgdjskuag87ic0vY2VaTxtJ4y6c4rgPHy7eTzVkUC9K+iwvbD5az0BPCO93dylu50lXL35CQY95ByBvBxamL25lXe7UruCvER+Gj2lgKK9c6/8vPwNMb3Zr6s8L6GBvPcblLwbxlu9cPUZvexNxTrNXn27vNKKPa5IXz14fbO955+KvbdCiD0iIli76F8cvaO/jD2Tfi48n8l3PTsepbwmcGw9oBIGvTWJQz0ii2q9V/K9vZCl/DxURc+7+DjGu/cxU724Lxu98CWFPcGOIrz1xJC8F4l8uwhkQz2uyx29y3kXPfbu2zyca1g9LEqqPL+IeDy4rsQ84InqvKy9p7sGcTo9vkkuPYhoDzuonLS9HB/FvZSH0jwP6oq8HAJUvIpavjxUeZ08xJehPM 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 rA9a50jutGuLjuCabC9JFwDOmbTj71sqUS97/UnPKbADbzDCL08X2Quu18ENz0bxG09/8JrvHZDcD2Afou9eiSTPb0lKL0yGxw8ydaJPcjKU70NByM9yqAFvBjbH7sGtUs9m7TsPPRB+TyD2rw7q3OnPS4clroSRvE8PV3pvFSQOLxdL3Y9K1vXu0jBNz02Y9Q8ntvCPI0YKb1d6t69uHBQvOKGIL2LcjO90Go4PIOcbj2W8Us802i5PORlaj020aQ9UMVGvKJigDycyHC9y1yBO9RJVLzA6LG8Bh4JPcaN8jwW15o8sPu6Pc4OHTvIUay8O8HWu+GxBT3XEYu8V2+mPcpAX7xLSIa8/j+4vEq3gz18Ats8sc2DPK5ssDvRT947zk/cPLPvODy8/My9qrEvvXRyeb3mdxu9YZw/vdglcD3BoIc9eejBvGW0mzyMO1o9EsJlPD15qT11mru9JClOPWIfSrzfYmK8V4CBPek8Dz0OwAo9LFuAPb3+nTwEd908HiTCPM 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 Pa8thw+P/rTCL/CNJW+EIlwv5mhDj819CU/3zkfv9K2iT61M62+nzOlPW2P4L0=", "training_traits": {"structure_gen": "Triangle", "n_layers": 4, "max_nodes": 12, "activation_func": "ReLU", "epoch_num": 4}, "classes_name": ["Cryptoadz", "Cryptopunks", "Moonbirds", "Nouns"]},m=25,b=50,y=59+11/12,w=59+11.5/12,v=60;function z(e,t){const n=Math.log(1-t)/Math.log(1-e);return e=>1-Math.pow(1-e,n)}class V{constructor(e,t,n){const{model:r,inputDim:i}=j(t,n);this.model=r,this.inputDim=i,this.iteration=0,this.stage=0;const o=new Date(parseIM nt(e.birthYear),0,1).getTime(),a=new Date(parseInt(e.birthYear)+1,0,1).getTime();this.birthDate=new Date(Math.floor((o+a)/2));const l=zr.filter((t=>t[0]==e.lifeCycle))[0][2];this.growSpeed=365/l,this.cycleLength=60*l*24*3600*1e3,this.growthFunc=z(.4,.8)}updateAge(e){const t=(e.getTime()-this.birthDate.getTime())/31536e6*this.growSpeed;this.iteration=Math.floor(t/60);const n=t-60*this.iteration;let r;this.age=n;let i,o=0;if(n<25){let e=map(n,0,25,0,1);o=this.growthFunc(e),r=(25-n)/60,this.stage=1,this.stageRatio=mapM (n,0,25,0,1)}else n<50?(o=1,r=(50-n)/60,this.stage=2,this.stageRatio=map(n,25,50,0,1)):n<y?(o=map(n,50,y,1,0),r=(y-n)/60,this.stage=3,this.stageRatio=map(n,50,y,0,1)):n<w?(o=0,r=(w-n)/60,this.stage=4,this.stageRatio=map(n,y,w,0,1)):n<60&&(o=0,r=(60-n)/60,this.stage=5,this.stageRatio=map(n,w,60,0,1));n<50?i=map(n,0,50,0,780/880):n<w?i=map(n,50,w,780/880,800/880):n<60&&(i=map(n,w,60,800/880,1)),this.nextStateTimestamp=Math.round(e.getTime()+this.cycleLength*r),this.statePercentage=round(100*i);let a=(25-n)/60;a<0&&(aM +=1),this.nextStableTimestamp=Math.round(e.getTime()+this.cycleLength*a),this.growth=o,this.model.updateNeurons(o,this.iteration)}getBrainStatus(){return{totalNeurons:this.model.getTotalNeurons(),neuronsLife:this.model.getNeuronsLife(),stage:this.stage,inputDim:this.inputDim,stageRatio:this.stageRatio,age:this.age,growth:this.growth,nextStateTimestamp:this.nextStateTimestamp,nextStableTimestamp:this.nextStableTimestamp,rebirthCount:max(this.iteration,0),statePercentage:this.statePercentage}}classifyImage(e){const tM =new G(e,1,e.length);return this.model.forward(t).mat[0]}}class M{constructor(e,t,n,r,i){this.p=e,this.v=t,this.size=n,this.shape=i,this.col=r}getRadius(){return 1==Oe?1*this.size/2:2==Oe?7*this.size/16:3==Oe||4==Oe?4*this.size/7:0}update(){this.p.add(this.v)}draw(e,t,n,r){const i=this.p.x*r,o=this.p.y*r,a=this.size*r,{col:l,shape:s}=this;let h,c;1==n?h=c=l:2==n?(h=dr(t,1),c=l):(h=dr(t,0),c=dr(l,1));e.stroke(dr(c,map(1,0,1,.25,1))),e.fill(dr(h,map(1,0,1,.15,1))),3==n&&e.fill(dr(h,0)),1==s?e.ellipse(i,o,a,a):2==s?e.M rect(i,o,7*a/8,7*a/8):3==s&&(e.beginShape(),e.vertex(i-4*a/7,o),e.vertex(i,o-4*a/7),e.vertex(i+4*a/7,o),e.vertex(i,o+4*a/7),e.endShape(CLOSE))}}class E{constructor(e,t,n,r,i,o,a){this.center=e,this.len=t,this.angle=n,this.v=r,this.angV=i,this.c1=o,this.c2=a}getEndpoints(){const e=createVector(this.len/2*cos(this.angle),this.len/2*sin(this.angle));return[Vector.add(this.center,e),Vector.sub(this.center,e)]}update(){this.center.add(this.v),this.angle+=this.angV}draw(e,t){const[n,r]=this.getEndpoints(),i=n.x*t,o=n.y*tM ,a=r.x*t,l=r.y*t,s=this.c1,h=this.c2;var c=e.drawingContext.createLinearGradient(i,o,a,l);c.addColorStop(0,s),c.addColorStop(1,h),e.drawingContext.strokeStyle=c,e.drawingContext.globalAlpha=1,e.line(i,o,a,l),e.drawingContext.globalAlpha=1}}function S(e,t){const n=random(TAU),r=random(e,t);return createVector(r*cos(n),r*sin(n))}class R{constructor(e,t,n,r,i){this.wall=n,this.maxR=i;const o=t.length;this.nodes=[];for(let a=0;a<o;++a){const o=[],l=.25*t[a];for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRiM ght),random(n.yTop,n.yBottom)),l=S(.02*i,.05*i),s=random(10,25)*i;o.push(new M(t,l,s,e[a],r))}this.nodes.push(o)}const a=A(e);a.unshift(e[0]),a.push(e[e.length-1]),this.lines=[];for(let e=0;e<=o;++e){const r=[],l=(0==e?1:t[e-1])*(e==o?1:t[e])*1.5;for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),o=random(5*i,10*i),l=random(TAU),s=S(.02*i,.05*i),h=random(2e-4,.001);r.push(new E(t,o,l,s,h,a[e],a[e+1]))}this.lines.push(r)}}reflectNode(e){const{xLeft:t,yTop:n,xRight:r,yBottom:M i}=this.wall,{p:o,v:a}=e,l=e.getRadius();(o.x-l<t&&a.x<0||o.x+l>r&&a.x>0)&&(a.x=-a.x),(o.y-l<n&&a.y<0||o.y+l>i&&a.y>0)&&(a.y=-a.y)}reflectLine(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,[o,a]=e.getEndpoints(),l=e.v;(min(o.x,a.x)<t&&l.x<0||max(o.x,a.x)>r&&l.x>0)&&(l.x=-l.x),(min(o.y,a.y)<n&&l.y<0||max(o.y,a.y)>i&&l.y>0)&&(l.y=-l.y)}update(){for(const e of this.lines)for(const t of e)t.update(),this.reflectLine(t);for(const e of this.nodes)for(const t of e)t.update(),this.reflectNode(t)}draw(e,t,n,r,i){conM st o=i/this.maxR;for(const t of this.lines){const n=t.length*r;for(let r=0;r<n;++r)t[r].draw(e,o)}for(const i of this.nodes){const a=i.length*r;for(let r=0;r<a;++r)i[r].draw(e,t,n,o)}}}function I(e,t){re(e),e.fill(0),e.rect(0,0,500,500),ie(e),e.noStroke(),e.fill(dr(cr("#000000"),.5)),e.push(),e.translate(250,250),e.scale(t),e.translate(-250,-250),e.beginShape(),e.vertex(235.2,24.9),e.bezierVertex(215,24.6,185,11.4,164.8,11),e.bezierVertex(147.2,10.7,129.3,10.4,112.2,14.7),e.bezierVertex(95.1,19,78.5,28.5,69.6,43.8)M ,e.bezierVertex(57.699,64.199,61.599,90.199,70.199,112.2),e.bezierVertex(78.799,134.2,91.6,154.6,97.199,177.5),e.bezierVertex(102.499,199.2,100.899,222.5,92.799,243.2),e.bezierVertex(83,268,64.6,288.3,48.9,310),e.bezierVertex(33.2,331.7,24.5,337.5,26.599,364.1),e.bezierVertex(28.2,384.1,61.399,404.2,75.7,418.3),e.bezierVertex(90,432.4,73.7,488.2,91.9,496.7),e.bezierVertex(124.2,511.6,159,472.5,194.3,468.1),e.bezierVertex(211.6,465.9,267.4,501.5,283.9,495.9),e.bezierVertex(340.7,476.7,298.599,428.9,355.4,409.7),e.beM zierVertex(370.799,404.5,454.5,407.6,464.4,394.8),e.bezierVertex(478.599,376.3,474.7,349.3,464.299,328.4),e.bezierVertex(453.9,307.5,438.099,289.5,428.699,268.2),e.bezierVertex(412,230,419,182.6,446.1,150.9),e.bezierVertex(449.7,146.7,453.6,142.7,455.8,137.6),e.bezierVertex(459.4,129.299,457.5,119.6,454.8,111),e.bezierVertex(443.2,73.4,417.3,40.4,383.6,20.299),e.bezierVertex(358.1,5,343.2,-.4,313.5,0),e.bezierVertex(287.5,.4,261.6,25.4,235.2,24.9),e.endShape(),e.pop()}function C(e,t,n,r,i,o){let a,l,s;re(t),t.fill(M 0),t.rect(0,0,500,500),ie(t),t.noStroke(),t.fill(dr(n,.5)),1==i?(l=0,s=25,a=map(o,0,25,500,0)):a=0,t.rect(0,a,500,500),e.noStroke(),e.fill(r),e.rect(0,0,500,500),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(M 203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.M 7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,M 104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),e.fill(n),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,40M 2.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertM ex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bM ezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.M 7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),re(e),e.fill(r),e.beginShape(),e.vertex(184.3,473.2),e.bezierVertex(164,473.2,144.7,462.099,134,444.3),e.bezierVertex(131.7,440.5,129.1,438.5,125,437.1),e.bezierVertex(97.3,428.1,80.5,400.6,85.2,371.8),e.bezierVertex(86.3,365.1,85.8,364.1,79.9,361.2),e.bezierVertex(57.2,349.8,46.2,323.3,54.3,299.7),e.bezierVertex(54.7,298.599,55.1,297.7,5M 5.5,296.9),e.bezierVertex(55.6,296.599,55.8,296.4,55.9,296.099),e.vertex(57.9,291.499),e.vertex(62.5,293.599),e.bezierVertex(64.9,294.7,67.3,295.799,69.5,296.9),e.bezierVertex(74.5,299.299,79.1,301.599,83.9,303.099),e.bezierVertex(89.8,304.9,96.5,305.499,102.7,305.9),e.bezierVertex(102.8,305.9,102.9,305.9,103,305.9),e.bezierVertex(106.6,305.9,108.9,302.799,109,299.799),e.bezierVertex(109.1,296.199,106.6,293.4,102.7,292.799),e.bezierVertex(101.3,292.599,99.9,292.4,98.4,292.299),e.bezierVertex(94.3,291.799,90.1,291.2M 99,86,289.9),e.bezierVertex(68.9,284,56.5,270.2,52.7,252.799),e.bezierVertex(48.9,235.499,54.5,217.7,67.6,205.299),e.bezierVertex(71.9,201.299,72.7,198.1,70.8,192.399),e.bezierVertex(64.2,172.2,68.8,153.99,84.2,139.599),e.bezierVertex(94.2,130.199,105.5,125.399,117.8,125.399),e.bezierVertex(124.3,125.399,131.1,126.799,137.8,129.599),e.bezierVertex(157,137.399,167.9,152.799,169.4,173.99),e.vertex(169.4,174.399),e.bezierVertex(169.5,175.899,169.6,177.2,169.9,178.299),e.bezierVertex(170.7,181.2,173.2,183.2,176.1,183.2M ),e.bezierVertex(176.299,183.2,176.5,183.2,176.7,183.2),e.bezierVertex(180.1,182.899,182.6,180.299,182.7,177),e.bezierVertex(183.1,162,178.299,148.2,168.399,136.1),e.bezierVertex(158.2,123.5,144.899,115.8,128.799,113.199),e.bezierVertex(123.499,112.299,120.399,109.799,118.899,104.99),e.bezierVertex(113.899,89.699,120.699,72.299,134.899,64.499),e.bezierVertex(139.99,61.699,145.799,60.199,151.7,60.199),e.bezierVertex(162.2,60.199,171.899,64.799,178.1,72.699),e.bezierVertex(179.6,74.6,180.799,76.6,181.9,78.499),e.vertM ex(182.2,79.099),e.bezierVertex(183.2,80.699,185.2,83.299,188.4,83.299),e.bezierVertex(189.5,83.299,190.6,82.99,191.7,82.399),e.bezierVertex(195.1,80.599,196,76.99,194,72.799),e.bezierVertex(190.1,64.799,184.1,58.499,175.6,53.299),e.bezierVertex(174.6,52.699,173.7,52.099,172.5,51.499),e.vertex(170.5,50.299),e.vertex(163,45.899),e.vertex(170.5,41.599),e.bezierVertex(182,34.99,193.1,30.799,204.4,28.599),e.bezierVertex(208.6,27.799,212.9,27.399,217.2,27.399),e.bezierVertex(217.6,27.399,217.9,27.399,218.3,27.399),e.bezM ierVertex(231.4,27.599,242.7,38.199,243,50.599),e.bezierVertex(243.4,64.899,243.3,78.99,243.2,93.799),e.bezierVertex(243.2,99.799,243.1,105.899,243.1,112.099),e.vertex(243.1,119.199),e.vertex(236.4,116.799),e.bezierVertex(235.7,116.499,235,116.299,234.4,115.99),e.bezierVertex(233.4,115.599,232.6,115.299,232,115.199),e.bezierVertex(230.6,114.899,229.2,114.599,227.8,114.299),e.bezierVertex(223.8,113.499,220.1,112.699,216.4,112.499),e.vertex(216.2,112.499),e.bezierVertex(212.5,112.499,210.7,115.599,210.6,118.599),e.beM zierVertex(210.4,122.399,212.7,125.099,216.4,125.399),e.bezierVertex(230.1,126.399,238.9,133.099,242.3,145.199),e.bezierVertex(243.2,148.399,243.2,151.599,243.2,154.499),e.vertex(243.2,155.099),e.bezierVertex(243.2,254.199,243.2,330,243.2,400.599),e.bezierVertex(243.2,401.99,243.2,403.4,243.2,404.9),e.bezierVertex(243.3,411.099,243.3,417.599,242.3,423.9),e.bezierVertex(238.1,449.2,219.6,467.799,194,472.5),e.bezierVertex(190.9,472.9,187.6,473.2,184.3,473.2),e.endShape(),e.beginShape(),e.vertex(315.8,473.1),e.bezierVM ertex(309.3,473.1,302.8,472,296.5,469.9),e.bezierVertex(270.4,461,253.8,434.9,257.1,407.9),e.bezierVertex(260,384,273.8,366.8,297,358.3),e.bezierVertex(297.7,358.1,298.3,357.8,299,357.6),e.bezierVertex(299.8,357.3,300.6,357.1,301.2,356.8),e.bezierVertex(304.3,355.4,306,351.8,304.9,348.7),e.bezierVertex(304,345.9,301.7,344.2,299,344.2),e.bezierVertex(298.6,344.2,298.1,344.2,297.6,344.3),e.bezierVertex(288.1,346.3,279,350.9,269.7,358.3),e.bezierVertex(268.9,358.9,268.1,359.6,267.2,360.4),e.vertex(265.5,361.8),e.verteM x(258.5,367.6),e.vertex(257.4,358.6),e.bezierVertex(257.3,358,257.3,357.5,257.2,357.1),e.bezierVertex(257,356,256.9,354.9,256.9,353.7),e.bezierVertex(256.9,334.8,256.9,316,256.9,297.1),e.bezierVertex(256.9,260.3,256.9,222.3,256.8,185),e.bezierVertex(256.8,170.7,268.3,158.8,282.5,158.4),e.bezierVertex(284.8,158.3,286.7,157.6,287.9,156.2),e.bezierVertex(289.099,154.9,289.599,153.2,289.5,151.3),e.bezierVertex(289.3,147.5,286.7,145.1,282.7,145.1),e.bezierVertex(282.5,145.1,282.2,145.1,282,145.1),e.bezierVertex(278.8,14M 5.3,275.5,146.1,272,146.9),e.bezierVertex(270.9,147.2,269.8,147.4,268.6,147.7),e.bezierVertex(267.9,147.9,267,148.2,265.8,148.7),e.bezierVertex(265.1,149,264.4,149.3,263.5,149.6),e.vertex(256.8,152),e.vertex(256.8,114.6),e.bezierVertex(256.8,95,256.8,75.4,256.8,55.9),e.bezierVertex(256.8,38,267.2,27.3,284.6,27.3),e.bezierVertex(285.3,27.3,285.9,27.3,286.6,27.3),e.bezierVertex(299,27.9,318.7,34.5,329.6,41.9),e.vertex(336.1,46.3),e.vertex(324.4,53.3),e.bezierVertex(316.2,58.2,310.2,64.6,306,72.9),e.bezierVertex(304.2M ,76.4,305.1,78.5,306.1,80),e.bezierVertex(307.4,81.9,309.4,83,311.6,83),e.bezierVertex(313.7,83,315.7,81.9,317.1,80.1),e.bezierVertex(317.4,79.7,317.8,79,318.1,78.4),e.bezierVertex(318.4,77.9,318.7,77.3,319,76.8),e.bezierVertex(325.3,66.2,336.3,59.9,348.5,59.9),e.bezierVertex(353.2,59.9,357.8,60.8,362.1,62.7),e.bezierVertex(377.6,69.3,386,86.7,381.7,103.2),e.bezierVertex(380.7,107.1,378.5,111.8,371.1,113.1),e.bezierVertex(342.7,118.1,322.2,139.1,317.8,167.8),e.bezierVertex(317.4,170.3,317.3,173.2,317.4,176.5),e.bezM ierVertex(317.5,180,320.1,182.8,323.5,183),e.bezierVertex(323.6,183,323.8,183,323.9,183),e.bezierVertex(327.1,183,329.8,180.6,330.3,177.2),e.bezierVertex(330.6,175.7,330.7,174,330.9,172.3),e.bezierVertex(331.1,169.8,331.4,167.3,332,164.7),e.bezierVertex(337.3,141.9,357.7,125.4,380.7,125.4),e.bezierVertex(382.5,125.4,384.3,125.5,386.1,125.7),e.bezierVertex(412.8,128.9,432.6,150.9,432,176.9),e.bezierVertex(431.9,182.3,430.9,187.7,429.1,192.7),e.bezierVertex(427.2,197.9,428,201,432.3,205),e.bezierVertex(446.8,218.7,45M 1.8,236,446.6,255),e.bezierVertex(441.4,274,428.3,286.5,408.7,291.3),e.bezierVertex(406.1,291.9,403.6,292.1,401.1,292.3),e.bezierVertex(400,292.4,398.9,292.5,397.9,292.6),e.bezierVertex(393.6,293.1,390.9,295.7,391,299.5),e.bezierVertex(391.1,303.4,394,305.8,398.5,305.8),e.bezierVertex(409.9,305.8,420.8,302.6,431.1,296.4),e.bezierVertex(431.8,296,432.5,295.5,433.2,295.1),e.bezierVertex(433.8,294.7,434.5,294.3,435.2,293.9),e.bezierVertex(436,293.4,436.6,293.2,437.2,293.1),e.bezierVertex(437.4,293,437.7,292.9,438.1,29M 2.8),e.vertex(442.5,291.4),e.vertex(444.2,295.7),e.bezierVertex(450.9,312.4,449.5,328.4,440,343.4),e.bezierVertex(435.3,350.8,428.7,356.7,420.2,361.1),e.bezierVertex(414.3,364.1,413.7,365.2,414.8,371.7),e.bezierVertex(419.5,400.2,403,427.6,375.6,436.9),e.bezierVertex(371,438.5,368.3,440.7,365.8,444.7),e.bezierVertex(355.2,462.5,336.4,473.1,315.8,473.1),e.bezierVertex(315.8,473.1,315.8,473.1,315.8,473.1),e.endShape(),ie(e),e.fill(n),e.beginShape(),e.vertex(120.2,279.9),e.bezierVertex(117.9,279.9,112.4,279.299,112.2,M 273.599),e.bezierVertex(112,267.7,117.4,266.7,119.7,266.599),e.bezierVertex(133.1,265.799,143.1,259.499,149.3,247.899),e.bezierVertex(149.6,247.299,150.1,246.399,150.3,245.399),e.bezierVertex(150.6,244.299,150.5,243.299,150.5,242.7),e.bezierVertex(150.5,242.6,150.5,242.5,150.5,242.299),e.vertex(150.3,238.799),e.vertex(141.1,235.99),e.bezierVertex(114.6,227.799,95.6,202.499,95.9,175.799),e.bezierVertex(95.9,173.99,96.4,168.199,102.2,168.199),e.bezierVertex(102.6,168.199,103,168.199,103.4,168.299),e.bezierVertex(104.M 8,168.499,108.2,168.899,109.2,175.599),e.bezierVertex(109.3,176.599,109.5,177.599,109.6,178.499),e.bezierVertex(110.4,184.199,111.3,189.99,113.7,195.499),e.bezierVertex(121.9,213.99,139.5,225.499,159.7,225.499),e.bezierVertex(172.1,225.499,184.1,220.899,193.5,212.599),e.bezierVertex(194,212.199,194.4,211.799,194.8,211.399),e.bezierVertex(195.1,211.099,195.5,210.799,195.8,210.399),e.bezierVertex(197.4,208.99,199.2,208.2,200.9,208.2),e.bezierVertex(202.5,208.2,204,208.899,205.3,210.1),e.bezierVertex(208,212.9,207.9,2M 16.9,205,219.9),e.bezierVertex(196.5,228.6,186.3,234.3,174.7,236.8),e.bezierVertex(168.799,238.1,165.6,241,163.899,246.7),e.bezierVertex(158.3,265.9,139.9,279.7,120.2,279.9),e.vertex(120.2,279.9),e.endShape(),e.beginShape(),e.vertex(187.2,427.5),e.bezierVertex(183.799,427.5,181.299,425.3,180.799,422),e.bezierVertex(180.6,420.8,180.499,419.5,180.399,418.1),e.bezierVertex(180.299,417,180.2,415.8,180.099,414.7),e.bezierVertex(177.199,390.5,156.699,371.3,132.399,370.2),e.bezierVertex(131.99,370.2,131.499,370.2,131.099,M 370.2),e.bezierVertex(130.699,370.2,130.299,370.2,129.799,370.2),e.bezierVertex(125.99,369.9,123.199,367.2,123.099,363.6),e.bezierVertex(122.99,360.2,125.799,357.3,129.599,356.9),e.bezierVertex(130.499,356.8,131.499,356.8,132.599,356.7),e.bezierVertex(133.199,356.7,133.799,356.7,134.399,356.6),e.vertex(138.299,356.4),e.vertex(139.1,352.6),e.bezierVertex(139.5,350.7,139.799,348.9,140.2,347),e.bezierVertex(140.899,343.4,141.5,340,142.399,336.8),e.bezierVertex(150.099,310.7,174.399,292,201.399,291.3),e.vertex(201.599,M 291.3),e.bezierVertex(203.699,291.3,206.299,292,208.299,293.2),e.bezierVertex(210.499,294.5,210.699,297.5,209.99,299.8),e.bezierVertex(209.499,301.5,208.199,303.9,203.299,304.7),e.bezierVertex(202.199,304.9,200.99,305,199.799,305.2),e.bezierVertex(194.499,305.9,188.99,306.599,183.799,308.9),e.bezierVertex(165.499,316.799,155.199,331.299,152.99,352),e.bezierVertex(152.399,357.8,154.499,361.7,159.699,364.5),e.bezierVertex(178.199,374.4,189.399,390,193.099,410.9),e.bezierVertex(193.699,414.299,193.899,418,193.599,422)M ,e.bezierVertex(193.399,425.2,190.899,427.5,187.399,427.5),e.vertex(187.2,427.5),e.endShape(),e.beginShape(),e.vertex(364.3,281.1),e.bezierVertex(346.3,280.6,332.9,272.8,323.5,257),e.bezierVertex(321.6,253.9,320.4,250.2,319.2,246.7),e.bezierVertex(317.7,242.2,315,239.799,310.5,238.799),e.bezierVertex(298.5,236.299,288,230.7,279.4,222.1),e.bezierVertex(276.7,219.4,274.9,215.299,278,211.9),e.bezierVertex(279.4,210.3,281,209.6,282.6,209.6),e.bezierVertex(284.4,209.6,286.4,210.6,288.3,212.5),e.bezierVertex(297.8,221.8,M 310.4,226.9,323.9,226.9),e.bezierVertex(340.2,226.9,355.1,219.3,364.8,206.2),e.bezierVertex(371,197.8,374.2,188.5,374.5,178.5),e.vertex(374.5,177.9),e.bezierVertex(374.5,177,374.5,176.1,374.7,175.4),e.bezierVertex(375.3,171.8,377.9,169.5,381.3,169.5),e.bezierVertex(381.4,169.5,381.5,169.5,381.7,169.5),e.bezierVertex(385.4,169.7,388,172.4,388,176.1),e.bezierVertex(388.1,190.7,383.4,204,374.2,215.8),e.bezierVertex(365.8,226.5,354.7,233.9,341.2,237.9),e.bezierVertex(340,238.3,338.7,238.6,337.3,239.1),e.bezierVertex(33M 5.9,239.6,335.1,240.4,334.7,240.9),e.bezierVertex(334.599,241,334.5,241.1,334.4,241.2),e.vertex(331.799,243.6),e.vertex(333.199,246.8),e.bezierVertex(338.199,258,346.799,264.9,358.699,267.3),e.bezierVertex(360.199,267.6,361.599,267.7,362.99,267.9),e.bezierVertex(363.599,268,364.299,268,364.899,268.1),e.bezierVertex(369.099,268.6,371.799,271.4,371.499,275),e.bezierVertex(371.199,278.6,368.299,281.2,364.399,281.2),e.vertex(364.3,281.1),e.endShape(),e.beginShape(),e.vertex(323.9,437),e.bezierVertex(323.7,437,323.5,437M ,323.299,437),e.bezierVertex(319.599,436.7,317.299,434.1,317.4,430.2),e.bezierVertex(317.9,406.099,328.299,388,349.5,375),e.bezierVertex(350.7,374.2,352,373.5,353.4,372.8),e.bezierVertex(354.099,372.4,354.7,372.1,355.299,371.7),e.vertex(357.499,370.5),e.vertex(357.799,368),e.bezierVertex(360.4,346.6,345.199,323.7,323.9,317),e.bezierVertex(319.099,315.5,314.099,314.9,309.299,314.4),e.vertex(308.199,314.299),e.bezierVertex(305.99,314.099,300.799,312.9,300.899,307.299),e.bezierVertex(300.99,303.499,303.899,300.9,308.0M 99,300.9),e.vertex(308.299,300.9),e.bezierVertex(327.099,301.299,343.099,308.7,355.699,322.9),e.bezierVertex(364.299,332.5,369.399,344.099,370.99,357.299),e.bezierVertex(371.099,358.4,371.299,359.4,371.499,360.499),e.bezierVertex(371.599,360.99,371.699,361.499,371.799,361.99),e.vertex(372.499,365.899),e.vertex(377.899,366.199),e.bezierVertex(378.799,366.299,379.699,366.299,380.599,366.399),e.bezierVertex(385.099,366.699,387.899,369.399,387.799,373.299),e.bezierVertex(387.699,377.099,384.99,379.599,380.799,379.799),M e.bezierVertex(369.799,380.199,359.99,383.299,351.899,389.299),e.bezierVertex(338.799,398.799,331.699,411.699,330.699,427.499),e.vertex(330.699,428.299),e.bezierVertex(330.599,429.199,330.599,430.099,330.499,430.799),e.bezierVertex(330,434.7,327.5,437,323.9,437),e.endShape()}function T(e){return e[0].map(((t,n)=>e.map((e=>e[n]))))}function A(e){return e.map((e=>Array.isArray(e)?A(e):e))}function D(e,t){return floor(random(e,t))}function k(e){let t=0;for(const n of e)t+=n[1];let n=random(t),r=0;for(const t of e)if(rM +=t[1],n<r)return t[0];return null}function L(e){for(let t=1;t<e.length;++t){let n=D(0,t),r=e[t];e[t]=e[n],e[n]=r}}function P(e){return null==e||""===e}function O(e){return new Promise((t=>setTimeout(t,e)))}function F(e,t,n){let r=0;for(let i=1;i<=1e3;++i)for(let o=1;o<=1e3;++o)if(e*o%(t*i)==0){let e=1*i/o;abs(e-n)<abs(r-n)&&(r=e)}return r}function N(){let e=60*(new Date).getTimezoneOffset()*1e3;return new Date(Date.now()-e).toISOString().slice(0,-1)}function B(e,t,n){let r;if(push(),textSize(e),textWidth(t)<=n)r=tM ;else for(let e=0;e<t.length;++e){const i=t.slice(0,e+1)+"...";if(textWidth(i)>n){r=i;break}}return pop(),r}function Y(e){var t=e%10,n=e%100;return 1==t&&11!=n?e+"st":2==t&&12!=n?e+"nd":3==t&&13!=n?e+"rd":e+"th"}class G{constructor(e,t,n){this.n=t,this.m=n,this.mat=[];let r=0;for(let t=0;t<this.n;++t){this.mat.push([]);for(let n=0;n<this.m;++n)this.mat[t].push(r<e.length?e[r]:0),r+=1}return this}copy(){return new G(this.mat.flat(),this.n,this.m)}}class H{static __linear=e=>e;static __relu=e=>Math.max(e,0);static __M leaky_relu=e=>e>0?e:.2*e;static __sigmoid=e=>1/(1+Math.exp(-e));static __tanh=e=>Math.tanh(e);static __apply_unary_op(e,t){const n=e.copy();for(let e=0;e<n.n;++e)for(let r=0;r<n.m;++r)n.mat[e][r]=t(n.mat[e][r]);return n}static linear=e=>H.__apply_unary_op(e,H.__linear);static relu=e=>H.__apply_unary_op(e,H.__relu);static leaky_relu=e=>H.__apply_unary_op(e,H.__leaky_relu);static sigmoid=e=>H.__apply_unary_op(e,H.__sigmoid);static tanh=e=>H.__apply_unary_op(e,H.__tanh);static __add=(e,t)=>e+t;static __mul=(e,t)=>e*t;M static __apply_binary_op=(e,t,n)=>{"object"!=typeof t&&(t=new G([t],1,1));const r=e.copy();for(let e=0;e<r.n;++e)for(let i=0;i<r.m;++i)r.mat[e][i]=n(r.mat[e][i],t.mat[e%t.n][i%t.m]);return r};static mul=(e,t)=>H.__apply_binary_op(e,t,H.__mul);static add=(e,t)=>H.__apply_binary_op(e,t,H.__add);static matMul(e,t){const n=new G([],e.n,t.m);for(let r=0;r<n.n;++r)for(let i=0;i<n.m;++i)for(let o=0;o<e.m;++o)n.mat[r][i]+=e.mat[r][o]*t.mat[o][i];return n}static softmax(e){const t=H.__apply_unary_op(e,(e=>Math.exp(e))),n=t.M mat.flat().reduce(((e,t)=>e+t));for(let r=0;r<e.n;++r)for(let i=0;i<e.m;++i)t.mat[r][i]/=n;return t}}class ${constructor(e,t){this.scale=e,this.offset=t}forward(e){return H.add(H.mul(e,this.scale),this.offset)}}class X{constructor(){}forward(e){return e.map((e=>e.flat()))}}class W{constructor(e,t,n,r){this.out_dim=e,this.activation=t,this.w=n,this.b=r}forward(e){const t=H.add(H.matMul(e,this.w),this.b);return null==this.activation?t:this.activation(t)}}class U{constructor(e,t,n){this.preprocessLayers=e,this.hiddenLM ayers=t,this.outputLayer=n,this.totalNeurons=this.hiddenLayers.map((e=>e.out_dim)),this.currentOrders=[],this.currentIteration=null}updateNeurons(e,t){if(t!=this.currentIteration){this.currentOrders=[];for(let e=0;e<this.totalNeurons.length;++e){randomSeed(100*(t+1)+e);const n=[];for(let t=0;t<this.totalNeurons[e];++t)n.push(t);L(n),this.currentOrders.push(n)}this.currentIteration=t}const n=A(this.totalNeurons),r=n.reduce(((e,t)=>e+t))*(1-e);for(let e=0;e<r;++e){const t=n.map(((e,t)=>(e-1)/this.totalNeurons[t]));n[M t.map(((e,t)=>[e,t])).reduce(((e,t)=>t[0]>e[0]?t:e))[1]]-=Math.min(r-e,1)}this.neuronsLife=[];for(let e=0;e<n.length;++e){const t=this.currentOrders[e],r=Array(this.totalNeurons[e]).fill(0);for(let i=0;i<n[e];++i)r[t[i]]=Math.min(n[e]-i,1);this.neuronsLife.push(r)}}getTotalNeurons(){return A(this.totalNeurons)}getNeuronsLife(){return A(this.neuronsLife)}forward(e){for(const t of this.preprocessLayers)e=t.forward(e);for(const[t,n]of this.hiddenLayers.entries()){e=n.forward(e);const r=new G(this.neuronsLife[t],1,e.m)M ;e=H.mul(e,r)}return e=this.outputLayer.forward(e),H.softmax(e)}}function q(e){switch(e){case"relu":return H.relu;case"sigmoid":return H.sigmoid;case"tanh":return H.tanh;case"leaky_relu":return H.leaky_relu;default:return H.linear}}function j(e,t){const n=[],r=[],i=Z(t);let o=null,a=0,l=[];for(const t of e.config.layers)if("InputLayer"==t.class_name)o=t.config.batch_input_shape.slice(1),l=o;else if("Rescaling"==t.class_name)n.push(new $(t.config.scale,t.config.offset));else if("Flatten"==t.class_name)o=[o.reduce(((M e,t)=>e*t))];else if("Dense"==t.class_name){const e=[t.config.units],n=o[0]*e[0],l=e[0],s=i.subarray(a,a+n);a+=n;const h=i.subarray(a,a+l);a+=l;const c=new G(s,o[0],e[0]),u=new G(h,1,e[0]),f=q(t.config.activation);r.push(new W(e[0],f,c,u)),o=e}const s=r.pop();return{model:new U(n,r,s),inputDim:l}}function Z(e){const t=window.atob(e),n=t.length/Float32Array.BYTES_PER_ELEMENT,r=new DataView(new ArrayBuffer(Float32Array.BYTES_PER_ELEMENT)),i=new Float32Array(n);let o=0;for(let e=0;e<n;e++){o=4*e;for(let e=0;e<4;++e)r.M setUint8(e,t.charCodeAt(o+e));i[e]=r.getFloat32(0,!0)}return i}class K{constructor(e){this.elt=e,this._events={},this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight}position(){if(0===arguments.length)return{x:this.elt.offsetLeft,y:this.elt.offsetTop};var e="absolute";return"static"!==arguments[2]&&"fixed"!==arguments[2]&&"relative"!==arguments[2]&&"sticky"!==arguments[2]&&"initial"!==arguments[2]&&"inherit"!==arguments[2]||(e=arguments[2]),this.elt.style.position=e,this.elt.style.left=arguments[0]+"pxM ",this.elt.style.top=arguments[1]+"px",this.x=arguments[0],this.y=arguments[1],this}show(){return this.elt.style.display="block",this}hide(){return this.elt.style.display="none",this}size(e,t){if(0===arguments.length)return{width:this.elt.offsetWidth,height:this.elt.offsetHeight};var n=e,r=t;if(n!==te||r!==te){if(n===te?n=t*this.width/this.height:r===te&&(r=e*this.height/this.width),this.elt instanceof HTMLCanvasElement){var i,o={},a=this.elt.getContext("2d");for(i in a)o[i]=a[i];for(i in this.elt.setAttribute("widM th",n*this._pInst._pixelDensity),this.elt.setAttribute("height",r*this._pInst._pixelDensity),this.elt.style.width=n+"px",this.elt.style.height=r+"px",this._pInst.scale(this._pInst._pixelDensity,this._pInst._pixelDensity),o)this.elt.getContext("2d")[i]=o[i]}else this.elt.style.width=n+"px",this.elt.style.height=r+"px",this.elt.width=n,this.elt.height=r;this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight,this._pInst&&this._pInst._curElement&&this._pInst._curElement.elt===this.elt&&(this._pInst._setPropeM rty("width",this.elt.offsetWidth),this._pInst._setProperty("height",this.elt.offsetHeight))}return this}style(e,t){if(t instanceof Color&&(t="rgba("+t.levels[0]+","+t.levels[1]+","+t.levels[2]+","+t.levels[3]/255+")"),void 0===t){if(-1===e.indexOf(":"))return window.getComputedStyle(this.elt).getPropertyValue(e);for(var n=e.split(";"),r=0;r<n.length;r++){var i=n[r].split(":");i[0]&&i[1]&&(this.elt.style[i[0].trim()]=i[1].trim())}}else if(this.elt.style[e]=t,"width"===e||"height"===e||"left"===e||"top"===e){var o=wiM ndow.getComputedStyle(this.elt).getPropertyValue(e).replace(/[^\d.]/g,"");this[e]=Math.round(parseFloat(o,10))}return this}value(){return arguments.length>0?(this.elt.value=arguments[0],this):"range"===this.elt.type?parseFloat(this.elt.value):this.elt.value}mouseClicked(e){return this._adjustListener("click",e,this),this}isFocused(){return document.activeElement===this.elt}_adjustListener(e,t,n){return!1===t?this._detachListener(e,n):this._attachListener(e,t,n),this}_attachListener(e,t,n){n._events[e]&&this._detachM Listener(e,n);var r=t.bind(n);n.elt.addEventListener(e,r,!1),n._events[e]=r}_detachListener(e,t){var n=t._events[e];t.elt.removeEventListener(e,n,!1),t._events[e]=null}}function J(e,t){var n=document.createElement("button");return n.innerHTML=e,t&&(n.value=t),ee(n)}function Q(e){var t=arguments.length>1&&void 0!==arguments[1]&&arguments[1],n=function(t){var n=!0,r=!1,i=void 0;try{for(var o,a=t.target.files[Symbol.iterator]();!(n=(o=a.next()).done);n=!0){var l=o.value;File._load(l,e)}}catch(e){r=!0,i=e}finally{try{nM ||null==a.return||a.return()}finally{if(r)throw i}}};if(window.File&&window.FileReader&&window.FileList&&window.Blob){var r=document.createElement("input");return r.setAttribute("type","file"),t&&r.setAttribute("multiple",!0),r.addEventListener("change",n,!1),ee(r)}}function ee(e){return document.body.appendChild(e),new K(e)}createImg=function(){var e,t=document.createElement("img"),n=arguments;return n.length>1&&"string"==typeof n[1]&&(t.alt=n[1]),n.length>2&&"string"==typeof n[2]&&(t.crossOrigin=n[2]),t.src=n[0],M e=ee(t,this),t.addEventListener("load",(function(){e.width=t.offsetWidth||t.width,e.height=t.offsetHeight||t.height;var r=n[n.length-1];"function"==typeof r&&r(e)})),e},createInput=function(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:"",t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:"text",n=document.createElement("input");return n.setAttribute("value",e),n.setAttribute("type",t),ee(n,this)};const te="auto";function ne(e){re(e);const t=e._rectMode;e.rectMode(CORNER),e.rect(0,0,e.width,eM .height),e.rectMode(t),ie(e)}function re(e){e.push(),e.fill(255,255,255,255),e.blendMode(REMOVE)}function ie(e){e.blendMode(BLEND),e.pop()}File=function(e,t){this.file=e,this._pInst=t;var n=e.type.split("/");this.type=n[0],this.subtype=n[1],this.name=e.name,this.size=e.size,this.data=void 0},File._createLoader=function(e,t){var n=new FileReader;return n.onload=function(n){var r=new File(e);if("application/json"===r.file.type)r.data=JSON.parse(n.target.result);else if("text/xml"===r.file.type){var i=(new DOMParser).M parseFromString(n.target.result,"text/xml");r.data=new XML(i.documentElement)}else r.data=n.target.result;t(r)},n},File._load=function(e,t){if(/^text\//.test(e.type)||"application/json"===e.type)File._createLoader(e,t).readAsText(e);else if(/^(video|audio)\//.test(e.type)){var n=new File(e);n.data=URL.createObjectURL(e),t(n)}else File._createLoader(e,t).readAsDataURL(e)},XML=function(e){if(e)this.DOM=e;else{var t=document.implementation.createDocument(null,"doc");this.DOM=t.createElement("root")}},document.addEventM Listener("DOMContentLoaded",(function(){addEventListener("mousemove",(e=>{window.mouseX=e.pageX,window.mouseY=e.pageY}))})),new e("global");const oe="29";let ae,le,se,he,ce,ue,fe,de,xe,ge,pe,me,be,ye,we,ve,ze,Ve,_e,Me,Ee,Se,Re,Ie,Ce,Te,Ae,De,ke,Le,Pe,Oe,Fe,Ne,Be,Ye,Ge,He,$e,Xe,We,Ue,qe,je,Ze,Ke,Je,Qe,et,tt,nt,rt,it,ot,at,lt,st,ht,ct,ut,ft,dt,xt,gt,pt,mt,bt,yt,wt,vt,zt,Vt,_t,Mt,Et,St,Rt,It,Ct,Tt,At=!1,Dt=!1,kt=!0,Lt=!1,Pt=!1;const Ot=[" ","Growing","Stable","Decaying","Dead","Rebirth"];let Ft,Nt,Bt,Yt,Gt,Ht,$t,Xt,WtM ,Ut,qt,jt,Zt,Kt,Jt,Qt,en,tn,nn,rn,on,an,ln,sn,hn=0,cn=0,un=0,fn=!1,dn=!0,xn=!0,gn=null,pn=null,mn=null,bn=!1,yn=!1,wn=null,vn=null,zn=!1;async function setup(){let e=windowWidth,t=windowHeight;createCanvas(e,t),et=createGraphics(e,t),Xe=createGraphics(e,t),$e=createGraphics(e,t),We=createGraphics(e,t),Ue=createGraphics(e,t),qe=createGraphics(e,t),Qe=createGraphics(e,t),je=createGraphics(e,t),Ze=createGraphics(e,t),Ke=createGraphics(e,t),Je=createGraphics(e,t),tt=createGraphics(500,500),nt=createGraphics(500,500),rtM =createGraphics(500,500),_n(),Mn(),Sn(),await En(),Gn(),Rn(),bn=!0}function _n(){Et=parseInt(oe),randomSeed(Et),noiseSeed(Et)}function Mn(){Wt=Ir(p.training_traits),Cr(Wt)}async function En(){let e;Jt=r(),Qt=o(),[Xt,e]=await Promise.all([s(Jt),h(Qt)]),Ut=new V(Wt.visual,e.layers_config,e.weight_b64),Ut.updateAge(new Date),_n(),Wt.training=e.training_traits,Ht=e.model_name,$t=e.classes_name}function Sn(){le=min(width,height)/1024,ut=Rr.findIndex((e=>e[0]===Wt.visual.colorPalette)),ft=[["#ffffff","#231f20","#231f20"]M ,["#231f20","#ffffff","#ffffff"],["#104da8","#ffffff","#ffffff"],["#722F1F","#FCE1B2","#FCE1B2"],["#e88120","#f9f2e5","#f9f2e5"],["#f6b941","#2E2E2E","#2E2E2E"],["#45daaa","#012221","#012221"],["#F1F1F1","#328DFE","#328DFE"],["#111822","#D3EB8D","#D3EB8D"],["#713FF9","#D6D5E6","#D6D5E6"],["#FBDA9D","#795106","#795106"],["#8f5b62","#ead0d0","#ead0d0"],["#eae4cb","#508cac","#508cac"],["#ffc6cc","#cc313d","#cc313d"],["#60A900","#E0FE00","#E0FE00"],["#507DBE","#D0D1D3","#D0D1D3"],["#305848","#E8F2EE","#E8F2EE"],["#2a26M 34","#5b6988","#cb78a2","#5b6988"],["#590e29","#fd5e53","#fd5e53","#ffe373"],["#0a141d","#57d4e4","#328195","#2A9ECF","#0ab6a8","#57d4e4"],["#3a2d28","#d5c2ac","#df6338","#3d9895","#d5c2ac"],["#030706","#77c4d9","#77c4d9","#77c4d9","#ffffff","#ffffff","#e72020","#e72020"],["#3a4664","#92f5ff","#f9ff94","#eaa0a2","#55dde0"],["#fbfaff","#f04bb1","#f04bb1","#fac373","#82cef0","#8b31ce"],["#000000","#ffffff","#ff0002","#f26522","#fdff00","#00ff03","#01fffe","#0000ff","#ff00ff"]];for(let e=0;e<ft.length;++e)for(let t=0;M t<ft[e].length;++t)ft[e][t]=cr(ft[e][t]);pt=[],ct=ft[ut][0],st=ft[ut][1]}function Rn(){gn=document.querySelector("#upload"),pn=document.querySelector("#inputUpload"),gn.addEventListener("dblclick",(()=>{if(!Lt&&!yn)if(In(Ie)&&cn==Ve-1)pn.click();else{if(4!=Pe&&5!=Pe&&(In(Ie)||cn!=Ve-1))return;fn=!0,dn=!0,Bt=0,un=0}})),pn.addEventListener("click",(()=>{pn.value=null,gn.style.display="block"})),pn.addEventListener("change",(()=>{const[e]=pn.files;e?(se=null,gn.style.display="none",Tn(URL.createObjectURL(e)),mn=e):gn.M style.display="block"}))}function In(e){for(let t=0;t<e.length;++t){let n=0;for(let r=0;r<e[t].length;++r)e[t][r]>0&&++n;if(0==n)return!1}return!0}function Cn(){null!=se&&(un=0,Pt=!0,he=0,ue=0,drewLineAnim=!0,ce=(ae/2+we/2)/le,loadImage(se.elt.src,(e=>{const[t,n,r]=Gt,i=createGraphics(t,n);i.image(e,0,0,t,n),i.loadPixels();const o=i.pixels.filter(((e,t)=>t%4!=3)),a=Ut.classifyImage(o);Zt=T([a,$t.map((e=>e.toUpperCase()))]).sort(((e,t)=>e[0]>t[0]?-1:1))})))}function Tn(e){se=createImg(e,""),se.hide(),Cn()}function AM n(){zn||(ce+=(width-ae-we)/tn/le),re(Xe),Xe.rect(ce*le,0,width,height),ie(Xe),un>=ge&&1==kt&&(kt=!1,un-=ge),kt&&(re($e),$e.strokeWeight(2*Fe),Jn(he,ze,ct,ct,$e),ie($e)),un>=ge&&0==kt&&(kt=!0,un-=ge,he+=1,he==en&&(++ue,he=0,ce=(ae/2+we/2)/le,1==ue&&(Pt=!1,Dn(),ye=millis())))}function Dn(){At=!0,pe=!1,me=!1,tryButton=br("Try Again",width/2-225*le,height/2+265*le,290*le,40*le,kn),closeResultButton=br("Close",width/2+75*le,height/2+265*le,150*le,40*le,Ln)}function kn(){At=!1,tryButton.hide(),closeResultButton.hide(),pnM .click()}function Ln(){Yt=!0,At=!1,Gn(),tryButton.hide(),closeResultButton.hide(),gn.style.display="block",se=null}function keyTyped(){bn&&!1===yn&&!1===yr()&&("i"!==key&&"I"!==key||(Dt=!Dt),"b"!==key&&"B"!==key||(xn=!xn),"s"!==key&&"S"!==key||!1!==Lt||saveCanvasAtCurrentTime(),"k"!==key&&"K"!==key||!1!==Lt||save4KCanvasAtCurrentTime(),"u"!==key&&"U"!==key||!1!==Lt||!1!==At||!1!==fn||!1!==Pt||On())}function On(){Lt=!0,wn=null,vn=null,submitButton=br("Submit",width/2-155*le,height/2+115*le,150*le,40*le,Fn),closeSettM ingButton=br("Close",width/2+5*le,height/2+115*le,150*le,40*le,Yn),vt=createInput(),vt.position(width/2-252.5*le,height/2-40*le),vt.size(500*le,25*le),vt.style("font-size","15px"),vt.value(Jt||""),zt=createInput(),zt.position(width/2-252.2*le,height/2+35*le),zt.size(500*le,25*le),zt.style("font-size","15px"),zt.value(Qt||"")}function Fn(){Vt=vt.value(),_t=zt.value(),submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide(),Lt=!1,yn=!0,Nn()}async function Nn(){[wn,vn,_]=await Promise.all([c(Vt),u(_t),O(1e3)]M ),yn=!1,wn&&vn?(n(Vt),i(_t),window.location.reload()):(Lt=!0,submitButton.show(),closeSettingButton.show(),vt.show(),zt.show())}function Bn(){Je.textFont("Trebuchet MS"),Je.noStroke(),pr(Je,600*le,200*le),Je.strokeWeight(1*le),Je.stroke(xt),Je.fill(xt),Je.textSize(50*le),Je.text("update()",width/2,height/2+2.5*le)}function Yn(){wn=null,vn=null,Lt=!1,submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide()}function Gn(){_n(),nn=Date.now(),pe=!1,me=!1,St=Wt.training.structure_gen,Rt=Wt.visual.birthYear,It=WtM .visual.lifeCycle,Ct=Wt.training.epoch_num,Tt=Wt.training.activation_func,Ft=Mr.findIndex((e=>e[0]==Wt.visual.hardwareAcceleration))+1,1==Ft?(Nt=30,fe=40):2==Ft?(Nt=15,fe=20):(Nt=2,fe=10);const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamM p=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),ae=100*le,ht=50*le,Oe=Sr.findIndex((e=>e[0]==Wt.visual.nodeShape))+1,dt=Er.findIndex((e=>e[0]==Wt.visual.nodeFill))+1,lt=_r.findIndex((e=>e[0]==Wt.visual.pattern))+1,de=Math.tanh(Math.log10(Xt.avgfeerate)),de=map(de,0,1,.2,.8),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);M for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].lengM th&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=minM (1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,at=.7,pt=[],xt=ft[ut][2],gt=ft[ut][ft[ut].length-1];for(let e=3;e<ft[ut].length-1;e++)pt.push(ft[ut][e]);mt=sr(xt,gt,pt,width),bt=[],wt=[],yt=width/(Ve-1);for(let e=0;e<Ve;e++)bt.push(hr(mt,yt*e/width)),wt.push(hr(mt,yt*e/width));wt.unshift(bt[0]),wt.push(bt[bt.length-1]),hn=0,cn=0,un=0,Yt=!0;const n={xLeft:ae/8,xRight:width-ae/8,yTop:ae/8,yBottom:height-ae/8},r=Ce.map((e=>e.length));jt=new R(bt,r,n,Oe,le)}function Hn(e,t){let n=Ce[e].length;return[e*weM +we/2+ae/2,height/2-(n-1)/2*ve+t*ve]}function $n(e,t){le=min(e,t)/1024,ae=100*le,ht=50*le,we=(e-ae)/Ve,ve=(t-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}xe=floor(De.length*de),Le=[],ke=[],ge=floor(map(de,.2,.8,15,2));for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,mt=srM (xt,gt,pt,e),bt=[],wt=[],yt=e/(Ve-1);for(let t=0;t<Ve;t++)bt.push(hr(mt,yt*t/e)),wt.push(hr(mt,yt*t/e));wt.unshift(bt[0]),wt.push(bt[bt.length-1])}function Xn(){const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$M rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=M 0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]M =Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le}function Wn(){jt.update();const e=4==Pe?0:Kt;jt.draw(Qe,ct,dt,e,le)}function Un(){if(!bn)return ar(),void et.image(je,0,0);if(4==Pe||5==Pe)return Wn(),void et.image(Qe,0,0);un>=Nt&&hn<Ve&&(hnM ++,un=0);for(let e=0;e<hn;e++)1==dt?it=ot=bt[e]:(it=ct,ot=bt[e]),Kn(e,it,ot,$e);un>=Nt&&cn<Ve-1&&(cn++,un=0);for(let e=0;e<cn;e++)Zn(e)}function qn(){et.background(ct),Ue.background(255),Ue.rectMode(CENTER),ne(Ue),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),Ue.stroke(st),Ue.strokeWeight(8*le),Ue.fill(ct),Qe.background(255),Qe.rectMode(CENTER),ne(Qe),Qe.strokeWeight(le),qe.background(255),qe.rectMode(CENTER),ne(qe),qe.textAlign(LEFT),$e.background(255),$e.rectMode(CENTER),ne($e),Xe.background(255),ne(Xe),Xe.strokM eWeight(Ne),We.background(255),We.rectMode(CENTER),ne(We),We.fill(st),We.stroke(st),We.strokeWeight(.1*le),er(lt),We.noStroke(),xn&&(We.rect(ae/16,height/2,ae/8,height),We.rect(width-ae/16,height/2,ae/8,height),We.rect(width/2,ae/16,width,ae/8),We.rect(width/2,height-ae/16,width,ae/8)),Ze.background(255),Ze.rectMode(CENTER),ne(Ze),Ze.textAlign(CENTER,CENTER),Ze.textStyle(BOLD),Ze.stroke(st),Ze.strokeWeight(8*le),Ze.fill(ct),je.background(255),je.rectMode(CENTER),ne(je),je.textAlign(CENTER,CENTER),je.textStyle(BOLD)M ,Ke.background(255),Ke.rectMode(CENTER),ne(Ke),Ke.textAlign(CENTER,CENTER),Ke.textStyle(BOLD),Ke.stroke(st),Ke.strokeWeight(8*le),Ke.fill(ct),Je.background(255),Je.rectMode(CENTER),ne(Je),Je.textAlign(CENTER,CENTER),Je.textStyle(BOLD),Je.stroke(st),Je.strokeWeight(8*le),Je.fill(ct),Un(),et.image(We,0,0),Pt&&An(),et.image(Xe,0,0),et.image($e,0,0),At&&(tr(),et.image(Ue,0,0)),fn&&(lr(),et.image(Ze,0,0)),Lt&&(or(),et.image(Ke,0,0)),Dt&&(ir(),et.image(qe,0,0)),yn&&(Bn(),et.image(Je,0,0))}function draw(){const e=Date.nowM ();bn&&(Ut.updateAge(new Date(e)),Xn()),qn(),image(et,0,0),zn||un++}function Zn(e){let t,n=Ce[e].length,r=Ce[e+1].length;for(let i=0;i<n;i++){const[n,o]=Hn(e,i);for(let a=0;a<r;a++){const[r,l]=Hn(e+1,a);t=map(min(Ce[e][i],Ce[e+1][a]),0,1,0,.5),ur(n,o,r,l,bt[e],bt[e+1],Xe,t)}}}function Kn(e,t,n,r){let i,o,a,l=Ce[e].length;for(let s=0;s<l;s++){const[l,h]=Hn(e,s);i=Ce[e][s],a=map(Be,1/30,1,3,10),o=map(Ce[e][s],0,1,2*a,0)*le,o<1.5*le&&(o=0),Qn(l,h,ze,Oe,t,n,o,i,r)}}function Jn(e,t,n,r,i){for(let o=0;o<Le[e].length;o++)M Qn(Le[e][o][0],Le[e][o][1],t,Oe,n,r,0,1,i)}function Qn(e,t,n,r,i,o,a,l,s){s.stroke(dr(o,map(l,0,1,.25,1))),s.fill(dr(i,map(l,0,1,.15,1))),s.strokeWeight(Fe),fr([a],s),3==dt&&s.fill(dr(i,0)),1==r?s.ellipse(e,t,n):2==r?s.rect(e,t,7*n/8,7*n/8):3==r&&(s.beginShape(),s.vertex(e-4*n/7,t),s.vertex(e,t-4*n/7),s.vertex(e+4*n/7,t),s.vertex(e,t+4*n/7),s.endShape(CLOSE))}function er(e){if(1==e);else if(2==e){We.strokeWeight(1*le);for(let e=ht/4;e<width+ht/4;e+=ht)for(let t=ht/4;t<height+ht/4;t+=ht)We.point(e,t)}else if(3==e){hM t=25*le;for(let e=ht/2;e<height+ht/2;e+=ht)We.line(0,e,width,e);for(let e=ht/2;e<width+ht/2;e+=ht)We.line(e,0,e,height)}}function tr(){Ue.textFont("Trebuchet MS"),Ue.textAlign(LEFT,CENTER),Ue.noStroke(),pr(Ue,800*le,500*le),Ue.noStroke(),Ue.fill(dr(st,.75)),Ue.rect(width/2,height/2-100*le,800*le,300*le,25*le,25*le,0,0),Ue.fill(st),Ue.rect(width/2-250*le,height/2-100*le,225*le,225*le),Ue.image(se.elt,width/2-357.5*le,height/2-207.5*le,215*le,215*le);let e=100*Zt[0][0];Ue.fill(ct),Ue.textSize(25*le),Ue.textStyle(NORMM AL),1==me&&(e>=0&&e<20?Ue.text("I have a feeling this image belongs to",width/2-100*le,height/2-170*le):e>=20&&e<40?Ue.text("I have a hunch this image belongs to",width/2-100*le,height/2-170*le):e>=40&&e<60?Ue.text("I think this image belongs to",width/2-100*le,height/2-170*le):e>=60&&e<80?Ue.text("I'm almost certain this image belongs to",width/2-100*le,height/2-170*le):Ue.text("I'm positive this image belongs to",width/2-100*le,height/2-170*le));let t=e.toFixed(2);"100.00"==t&&(t="100"),1==me&&Ue.text("I'm "+t+"%M confident that I'm right!",width/2-100*le,height/2-25*le),example=Zt.map((e=>e[1])),be=Ue.textWidth('"FIDENZAAAA"'),defaultPhrase=Ue.textWidth('"PERPENDICULAR INHABITATION"'),Ue.textStyle(BOLD);const n=me?example[0]:random(example);if(1===n.split(" ").length){let e=75*be/Ue.textWidth('"'+n+'"');e>75&&(e=75),Ue.textSize(e*le),Ue.text('"'+n+'"',width/2-100*le,height/2-90*le)}else nr(width/2-100*le,height/2-90*le,460*le,110*le,n,Ue);if(millis()-ye>1500&&(me=!0),C(tt,nt,st,ct,Pe,Mt),Ue.image(nt,width/2-370*le,height/2M +70*le,80*le,80*le),3==Pe){let e;e=map(Mt,50,60,.25,1.3),I(rt,e),Ue.image(rt,width/2-370*le,height/2+70*le,80*le,80*le)}let r,i;Ue.image(tt,width/2-370*le,height/2+70*le,80*le,80*le),Ue.fill(xt),Ue.textSize(40*le),Ue.text("INTELLIGENCE INFO",width/2-275*le,height/2+115*le),Ue.textSize(18*le),Ue.textStyle(NORMAL),Ue.circle(width/2-360*le,height/2+180*le,7.5*le),1==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s growing and getting smarter by the day.`:2==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years olM s stable and it has reached peak performance.`:3==Pe&&(r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s decaying and losing its luster.`),i=2==Pe?"The Perceptron remains stable for some time before entering the decay phase.":`Wait until ${new Date(an).toLocaleString("en-US")} for your Perceptron to reach its peak performance.`,Ue.text(r,width/2-350*le,height/2+180*le),Ue.circle(width/2-360*le,height/2+210*le,7.5*le),Ue.text(i,width/2-350*le,height/2+210*le),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BM OLD),gr(Ue,width/2-225*le,width/2+65*le,height/2+265*le,height/2+305*le,"SELECT ANOTHER IMAGE"),gr(Ue,width/2+75*le,width/2+225*le,height/2+265*le,height/2+305*le,"CLOSE")}function nr(e,t,n,r,i,o){let a=i.split(" "),l=75*be/o.textWidth('"'+i+'"'),s=0,h=[],c=[],u=[],f="",d="";if(l>=50)l>75&&(l=75),o.textSize(l*le),o.text('"'+i+'"',e,t);else if(l<50){if(l=50*defaultPhrase/o.textWidth('"'+i+'"'),l>30){if(l>50&&(l=50),[f,d]=rr(l,n,s,h,c,a,f,d,Ue),0==c.length)return o.textSize(l*le),void o.text('"'+i+'"',e,t);for(s=0,h=M [],c=[];o.textWidth(d)>n/le;)l=l*n/le/o.textWidth(d),f="",d="",[f,d]=rr(l,n,s,h,c,a,f,d,Ue)}else{l=30,o.textSize(l);for(let e=0;e<a.length;e++)s+=o.textWidth(" "+a[e]),s<=n/le?h.push(a[e]):s>n/le&&s<=n/le*2?c.push(a[e]):u.push(a[e]);for(let e=1;e<h.length;e++)f=f+" "+h[e];if(f='"'+h[0]+f,0==u.length){for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+c[c.length-1]+'"'}else if(1==c.length)d="... "+u[u.length-1]+'"';else{for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+"... "+u[u.length-1]+'"'}}o.textSize(l*le);let r=1.25*(oM .textDescent()+o.textAscent());o.text(f,e,t-r/2),o.text(d,e,t+r/2)}}function rr(e,t,n,r,i,o,a,l,s){s.textSize(e);for(let e=0;e<o.length;e++)(n+=s.textWidth(" "+o[e]))<=t/le?r.push(o[e]):i.push(o[e]);for(let e=1;e<r.length;e++)a=a+" "+r[e];if(a='"'+r[0]+a,0==i.length&&(a+='"',l=""),1==i.length)l=i[i.length-1]+'"';else{for(let e=0;e<i.length-1;e++)l=l+i[e]+" ";l=l+i[i.length-1]+'"'}return[a,l]}function ir(){const e=45*le;qe.textFont("Tahoma"),qe.stroke(st),qe.strokeWeight(2*le),qe.fill(ct),qe.rect(width/2,e/2+height-M 87.5*le,600*le,90*le),qe.fill(st),qe.rect(width/2-150*le,e+height-170*le,300*le,30*le),qe.fill(ct),qe.rect(width/2+150*le,e+height-170*le,300*le,30*le),qe.noStroke(),qe.fill(ct),qe.textSize(15*le),qe.textStyle(BOLD),qe.text("PERCEPTRON INFORMATION",width/2-285*le,e+height-165*le),qe.fill(xt),qe.text("ARTWORK NAME:",width/2+10*le,e+height-165*le),qe.textAlign(RIGHT),qe.textStyle(ITALIC),qe.text("Perceptron #"+Et,width/2+285*le,e+height-165*le);const[t,n]=It.split(" ");let r;"60 Years"===It?r="1 Year":"60 Months"===IM t?r="1 Month":"60 Weeks"===It?r="1 Week":"60 Days"===It?r="1 Day":"12 Hours"===It&&(r="12 Minutes"),data=[["AI MODEL NAME:",B(12*le,Ht,140*le)],["SCALE:","1:"+Te],["NUMBER OF CLASSES:",$t.length],["BIRTH YEAR:",Rt],["NUMBER OF REBIRTHS:",sn.toString()],["AGE:",`${Math.ceil(Mt)} Perceptron Years`],["ONE PERCEPTRON YEAR:",`${r}`],["STATE:",Ot[Pe]],["ACTIVE NEURONS:",`${round(ln*rn)} / ${ln}`],["NEXT STATE TIME:",vr(new Date(on))]],qe.fill(xt);const i=data.length/2;for(let t=0;t<data.length;++t){const n=t<i,r=n?width/M 2-285*le:width/2+10*le,o=n?width/2-10*le:width/2+285*le,a=e+height-(135-t%i*15)*le;qe.textStyle(BOLD),qe.textAlign(LEFT),qe.textSize(12*le),qe.text(data[t][0],r,a),qe.textStyle(ITALIC),qe.textAlign(RIGHT),qe.textSize(12*le),qe.text(data[t][1],o,a)}}function or(){Ke.textFont("Trebuchet MS"),Ke.noStroke(),pr(Ke,600*le,200*le),gr(Ke,width/2-155*le,width/2-5*le,height/2+115*le,height/2+155*le,"UPDATE"),gr(Ke,width/2+5*le,width/2+155*le,height/2+115*le,height/2+155*le,"CLOSE"),Ke.textAlign(LEFT),Ke.fill(xt),Ke.text("UPDM ATE BITCOIN FULL NODE ADDRESS",width/2-252.5*le,height/2-55*le),Ke.text("UPDATE MODEL ADDRESS",width/2-252.5*le,height/2+20*le),Ke.textAlign(RIGHT),Ke.textStyle(ITALIC),Ke.textSize(15*le),0==wn&&Ke.text("(*) Invalid Address",width/2+252.5*le,height/2-53*le),0==vn&&Ke.text("(*) Invalid Model",width/2+252.5*le,height/2+23*le)}function ar(){je.textFont("Trebuchet MS"),je.fill(st),je.textSize(50*le),je.stroke(st),je.strokeWeight(1*le),je.text("main()",width/2,height/2)}function lr(){un>=20&&1==dn&&(dn=!1,un=0),dn&&(Ze.M textFont("Trebuchet MS"),Ze.stroke(st),Ze.fill(ct),Ze.rect(width/2,height/2,600*le,150*le,25*le),Ze.fill(xt),Ze.textSize(75*le),Ze.noStroke(),1==Pe?Ze.text("GROWING",width/2,height/2+5*le):3==Pe?Ze.text("AGING",width/2,height/2+5*le):4==Pe?Ze.text("DEAD",width/2,height/2+5*le):5==Pe&&Ze.text("BIRTH",width/2,height/2+5*le)),un>=20&&0==dn&&(dn=!0,un=0,Bt++,3==Bt&&(fn=!1))}function sr(e,t,n,r){let i=[],o=r/(n.length+1),a=color(e),l=color(t);i.push(a);for(let e=0;e<n.length;e++){let t=color(n[e]);for(let e=1;e<=o;e++){M let n=lerpColor(a,t,e/o);i.push(n)}a=t}for(let e=1;e<o;e++){let t=lerpColor(a,l,e/o);i.push(t)}if(i.push(l),i.length>r)i.splice(r);else if(i.length<r){let e=i[i.length-1];for(;i.length<r;)i.push(e)}return i}function hr(e,t){let n=e.length,r=Math.floor(t*n);return r>=n&&(r=n-1),e[r]}function cr(e){e=e.replace("#","");var t=parseInt(e,16);return color(t>>16&255,t>>8&255,255&t)}function ur(e,t,n,r,i,o,a,l){var s=a.drawingContext.createLinearGradient(e,t,n,r);s.addColorStop(0,i),s.addColorStop(1,o),a.drawingContext.strM okeStyle=s,a.drawingContext.globalAlpha=l,a.line(e,t,n,r),a.drawingContext.globalAlpha=1}function fr(e,t){t.drawingContext.setLineDash(e)}function dr(e,t){let n=color(e),r=red(n),i=green(n),o=blue(n);return color(r,i,o,255*t)}function xr(e,t,n,r){return mouseX>e&&mouseX<t&&mouseY>n&&mouseY<r}function gr(e,t,n,r,i,o){e.strokeWeight(1*le),e.stroke(st);const[a,l]=xr(t,n,r,i)?[xt,ct]:[ct,xt];e.fill(a),e.push(),e.rectMode(CORNERS),e.rect(t,r,n,i,5*le),e.pop(),e.noStroke(),e.textSize(20*le),e.fill(l),e.text(o,(t+n)/2,(46M *r+54*i)/100)}function pr(e,t,n){e.fill(0,0,0,75),e.rect(width/2,height/2,width,height),e.stroke(st),e.fill(ct),e.rect(width/2,height/2,t,n,25*le)}function mr(e,t){resizeCanvas(e,t,!0),Xe.resizeCanvas(e,t,!0),$e.resizeCanvas(e,t,!0),We.resizeCanvas(e,t,!0),Ue.resizeCanvas(e,t,!0),qe.resizeCanvas(e,t,!0),Qe.resizeCanvas(e,t,!0),je.resizeCanvas(e,t,!0),Ze.resizeCanvas(e,t,!0),Ke.resizeCanvas(e,t,!0),Je.resizeCanvas(e,t,!0),et.resizeCanvas(e,t,!0)}function br(e,t,n,r,i,o){const a=J(e);return a.position(t,n),a.size(r,iM ),a.style("opacity","0"),a.mouseClicked(o),a}function yr(){return null!=vt&&vt?.isFocused()||null!=zt&&zt?.isFocused()}function wr(e,t,n,r){let i;if(e<=3){i=`Hey ${String.fromCodePoint(128075)}, I'm ${n}, ${t} years old. I can detect ${r.length} NFT collections: `;let e=0;for(let t=0;t<r.length;++t){const n=r[t];if(e+n.length>500){i+=", etc";break}t==r.length-1?i+=", and ":t>0&&(i+=", "),i+=n,e+=n.length}i+=". ",t<=5?i+="However, I am only a baby, so my recognition ability is not accurate. I'm in the state of GrowiM ng both looks and intelligence.":t<=13?i+="I am now a child. My recognition ability is becoming better, but still not very accurate. I'm in the state of Growing both looks and intelligence.":t<=25?i+="I have grown up to be a teen. My recognition ability almost reaches the peak, but I will still mess up sometimes. I'm in the state of Growing both looks and intelligence.":t<=50?i+="I finally reach adulthood. My recognition is fully functional now. I'm in the Stable state, where I am the most intelligent with all neurM ons activated.":t<=60&&(i+="I am now an old Perceptron, so my recognition ability is no longer the best. I'm in the Decaying state, meaning that my neurons are dying, and my intelligence is decreasing over time.")}else 4==e?i=`${n} is Dead. However, this is not the end to its story...`:5==e&&(i=`${n} is now in the Rebirth state, and is preparing to start a new life.`);return i}function vr(e){const t=e.getDate(),n=e.toLocaleString("en-US",{month:"long"}),r=e.getFullYear();let i=e.getHours().toString();1==i.length&&(M i="0"+i);let o=e.getMinutes().toString();return 1==o.length&&(o="0"+o),`${Y(t)} ${n} ${r} | ${i}:${o}`}saveCanvasAtCurrentTime=()=>{save(N())},save4KCanvasAtCurrentTime=()=>{const e=width,t=height,n=min(4096/min(e,t),1e4/max(e,t)),r=e*n,i=t*n;mr(r,i),zn=!0,$n(r,i),qn();let o="4K_"+N()+".png";saveCanvas(et,o),mr(e,t),$n(e,t),zn=!1};const zr=[["60 Years",3,365],["60 Months",40,30],["60 Weeks",37,7],["60 Days",20,1]],Vr=[["1943",1],["1951",1.5],["1957",2],["1969",2.5],["1970",3],["1980",3.5],["1982",4],["1986",4.5],["M 1988",5],["1997",5.5],["1998",6],["2002",6.5],["2009",7],["2012",7.5],["2014",8],["2015",8.5],["2016",9],["2023",15]],_r=[["Plain",20],["Dotted",40],["Squared",40]],Mr=[["Basic",30],["Standard",60],["Advanced",10]],Er=[["MNIST",70],["CIFAR",25],["IMAGENET",5]],Sr=[["Theano",60],["Torch",30],["TensorFlow",10]],Rr=[["Whitepaper",2],["Blackboard",2],["Blueprint",2],["Nak",74/14],["Jims",74/14],["Level 10",74/14],["Flips",74/14],["Level 14",74/14],["III",74/14],["XMB",74/14],["Info",74/14],["Adventure",74/14],["MarigolM d",74/14],["Phoenix",74/14],["Love",74/14],["Cachet",74/14],["Human",74/14],["Twilight",3],["Sunset",3],["Aurora",3],["Liminal Space",3],["D Vu",3],["Lucid Dream",3],["Parallel",1],["Multiverse",1]];function Ir(e){for(let e=0;e<100;++e)random(1);return{visual:{pattern:k(_r),hardwareAcceleration:k(Mr),nodeFill:k(Er),nodeShape:k(Sr),colorPalette:k(Rr),lifeCycle:k(zr),birthYear:k(Vr)},training:e}}function Cr(e){window.$generativeTraits={"Network Architecture":e.training.structure_gen,"Hidden Layers":e.training.n_M layers,"Max Neurons Per Hidden Layer":e.training.max_nodes,"Activation Function":e.training.activation_func,"Training Epochs":e.training.epoch_num,Dataset:e.visual.nodeFill,"Deep Learning Framework":e.visual.nodeShape,"Hardware Acceleration":e.visual.hardwareAcceleration,"Paper Pattern":e.visual.pattern,"Life Cycle":e.visual.lifeCycle,"Birth Year":e.visual.birthYear,"Color Palette":e.visual.colorPalette}} <script defer src="https://static.cloudflareinsights.com/beacon.min.js/v2b4487d741ca48dcbadcaf9M3 54e159fc61680799950996" integrity="sha512-D/jdE0CypeVxFadTejKGTzmwyV10c1pxZk/AqjJuZbaJwGMyNHY3q/mTPWqMUnFACfCTunhZUVcd4cV78dK1pQ==" data-cf-beacon='{"rayId":"7b481dcf1ca6543d","version":"2023.3.0","b":1,"token":"6c07c178c94442f695e7a0a2aaee641a","si":100}' crossorigin="anonymous"></script> {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "undead"}, {"trait_type": "Artifacts", "value": "undead staff"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "undead"}, {"trait_type": "Artifacts", "value": "sword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "golden armor"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "skull"}, {"trait_type": "Artifacts", "value": "dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "golden armor"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "bloody"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "pirate flag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "blue fire"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "lamp"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "fire"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "arrow wounds"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "eagle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "golden"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "eagle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "parrot"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "crown"}, {"trait_type": "Artifacts", "value": "bag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "zombie"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "cape"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "golden armor"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "lamp"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "tiger"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "fire"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "pauldrons"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "mage robes"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "golden"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "arrow wounds"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "moon"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "arrow wounds"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "broadsword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "whale"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "laser"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "badger"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "golden"}, {"trait_type": "Headgear", "value": "skull"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "tribal tattoo"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "sword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "badger"}, {"trait_type": "Artifacts", "value": "arrow wounds"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "moon"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "laser beams"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} text/plain;charset=utf-8 8{"p":"sns","op":"reg","name":"unitedinternational.sats"}h! {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "arrow wounds"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"JOMO","amt":"100"}h! {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "golden armor"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "bloody"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "axe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "whale"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "broadsword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "rainbow"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "shield"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "sword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "fire"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "pauldrons"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "broadsword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "golden"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "quiver"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "eagle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "honey pot"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "badger"}, {"trait_type": "Artifacts", "value": "pirate flag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "eagle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "rainbow"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "sword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "tribal tattoo"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "badger"}, {"trait_type": "Artifacts", "value": "wizard staff"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "bloody"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "pirate flag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "silver"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "golden"}, {"trait_type": "Headgear", "value": "undead"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "blue fire"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "badger"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "bloody"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "honey pot"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "sword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "golden"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "undead staff"}]} text/plain;charset=utf-8 {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "honey pot"}, {"trait_type": "Eyes", "value": "laser"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "lamp"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "honey pot"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "orc"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "parrot"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "bloody"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "lamp"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "axe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "lamp"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "honey pot"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "skull"}, {"trait_type": "Artifacts", "value": "dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "golden"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "none"}]} siTXtXML:com.adobe.xmp " id="W5M0MpCehiHzreSzNTczkc9d"?> <x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 5.6-c148 79.164036, 2019/08/13-01:06:57 "> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:xmpMM="http://ns.adobe.com/xap/1.0/mm/" xmlns:stRef="http://ns.adobe.com/xap/1.0/sType/ResourceRef#" xmlns:xmp="http://ns.adobe.com/xap/1.0/" xmpMM:OriginM alDocumentID="xmp.did:de767d66-9358-744d-a7b2-1b8c83fb4bcc" xmpMM:DocumentID="xmp.did:54157A44CBE211ED8B4ADE6DA02347CD" xmpMM:InstanceID="xmp.iid:54157A43CBE211ED8B4ADE6DA02347CD" xmp:CreatorTool="Adobe Photoshop 21.0 (Windows)"> <xmpMM:DerivedFrom stRef:instanceID="xmp.iid:00c94df4-2307-0849-b84e-099ef1d50d6e" stRef:documentID="xmp.did:de767d66-9358-744d-a7b2-1b8c83fb4bcc"/> </rdf:Description> </rdf:RDF> </x:xmpmeta> <?xpacket end="r"?> {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "rainbow"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "pirate flag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "golden"}, {"trait_type": "Headgear", "value": "undead"}, {"trait_type": "Artifacts", "value": "eagle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "tribal tattoo"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "axe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "golden armor"}, {"trait_type": "Mane", "value": "blue fire"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "lamp"}]} text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"rssc","amt":"1000"}h! {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "rainbow"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "broadsword"}]} text/plain;charset=utf-8 ({"p":"sns","op":"reg","name":" text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"JOMO","amt":"100"}h! {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "golden"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "axe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "tiger"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "cape"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "golden"}, {"trait_type": "Headgear", "value": "skull"}, {"trait_type": "Artifacts", "value": "cape"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "laser beams"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "poisoned dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "skull"}, {"trait_type": "Artifacts", "value": "eagle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "bloody"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "eagle"}]} text/plain;charset=utf-8 -{"p":"sns","op":"reg","name":"wangfilm.sats"}h! text/html;charset=utf-8 <meta charset="utf-8" /> position: relative; width: var(--width); height: var(--height); border: 1px solid blue; position: relative; <div id="upload"> <input id="inputUpload" type="file"> function e(e){"use strict";return new function e(t){let n="global"==t?window:this;n.canvas=document.createElement("canvas");let r=n.canvas.getContext("2d");n.width=100,n.height=100,n.canvas.width=n.width,n.canvas.height=n.height,"offscreen"!=t&&(document.body?document.body.appendChild(n.canvas):window.addEventListener("load",(function(){document.body.appendChild(n.canvas)}))),g(),n.MAGIC=161533525,n.RGB=0,n.HSV=1,n.HM SB=1,n.CHORD=0,n.PIE=1,n.OPEN=2,n.RADIUS=1,n.CORNER=2,n.CORNERS=3,n.ROUND="round",n.SQUARE="butt",n.PROJECT="square",n.MITER="miter",n.BEVEL="bevel",n.CLOSE=1,n.BLEND="source-over",n.REMOVE="destination-out",n.ADD="lighter",n.DARKEST="darken",n.LIGHTEST="lighten",n.DIFFERENCE="difference",n.SUBTRACT="subtract",n.EXCLUSION="exclusion",n.MULTIPLY="multiply",n.SCREEN="screen",n.REPLACE="copy",n.OVERLAY="overlay",n.HARD_LIGHT="hard-light",n.SOFT_LIGHT="soft-light",n.DODGE="color-dodge",n.BURN="color-burn",n.NORMAL="norM mal",n.ITALIC="italic",n.BOLD="bold",n.BOLDITALIC="italic bold",n.CENTER="center",n.LEFT="left",n.RIGHT="right",n.TOP="top",n.BOTTOM="bottom",n.BASELINE="alphabetic",n.LANDSCAPE="landscape",n.PORTRAIT="portrait",n.ALT=18,n.BACKSPACE=8,n.CONTROL=17,n.DELETE=46,n.DOWN_ARROW=40,n.ENTER=13,n.ESCAPE=27,n.LEFT_ARROW=37,n.OPTION=18,n.RETURN=13,n.RIGHT_ARROW=39,n.SHIFT=16,n.TAB=9,n.UP_ARROW=38,n.HALF_PI=Math.PI/2,n.PI=Math.PI,n.QUARTER_PI=Math.PI/4,n.TAU=2*Math.PI,n.TWO_PI=2*Math.PI,n.THRESHOLD=1,n.GRAY=2,n.OPAQUE=3,n.INVEM RT=4,n.POSTERIZE=5,n.DILATE=6,n.ERODE=7,n.BLUR=8,n.ARROW="default",n.CROSS="crosshair",n.HAND="pointer",n.MOVE="move",n.TEXT="text",n.VIDEO={video:!0,audio:!1},n.AUDIO={video:!1,audio:!0},n.SHR3=1,n.LCG=2,n.HARDWARE_FILTERS=!0,n.hint=function(e,t){n[e]=t},n.frameCount=0,n.mouseX=0,n.mouseY=0,n.pmouseX=0,n.pmouseY=0,n.mouseButton=null,n.keyIsPressed=!1,n.mouseIsPressed=!1,n.key=null,n.keyCode=null,n.pixels=null,n.accelerationX=0,n.accelerationY=0,n.accelerationZ=0,n.rotationX=0,n.rotationY=0,n.rotationZ=0,n.relRotatM ionX=0,n.relRotationY=0,n.relRotationZ=0,n.pAccelerationX=0,n.pAccelerationY=0,n.pAccelerationZ=0,n.pRotationX=0,n.pRotationY=0,n.pRotationZ=0,n.pRelRotationX=0,n.pRelRotationY=0,n.pRelRotationZ=0,n.touches=[],n._styleCache=[{colorMode:n.RGB,noStroke:!1,noFill:!1,ellipseMode:n.CENTER,rectMode:n.CORNER,curveDetail:20,curveAlpha:0,textFont:"sans-serif",textSize:12,textLeading:12,textStyle:"normal"}],n._style=n._styleCache[n._styleCache.length-1],n._noLoop=!1,n._pixelDensity=1,n._frameRate=null,n._tint=null;let i=nullM ,o=!0,a=[],l=null,s=0,h={},c=0,u=null,f=null,d=null;Object.defineProperty(n,"deviceOrientation",{get:function(){return 90==Math.abs(window.orientation)?n.LANDSCAPE:n.PORTRAIT}}),Object.defineProperty(n,"windowWidth",{get:function(){return window.innerWidth}}),Object.defineProperty(n,"windowHeight",{get:function(){return window.innerHeight}}),Object.defineProperty(n,"drawingContext",{get:function(){return r}}),n.createCanvas=function(e,t){return n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t,g(),n.canvas},nM .resizeCanvas=function(e,t){n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t},n.createGraphics=n.createImage=function(t,n){let r=new e("offscreen");return r.createCanvas(t,n),r.noLoop(),r},n.pixelDensity=function(e){return null==e||(n._pixelDensity=e,n.canvas.width=Math.ceil(n.width*e),n.canvas.height=Math.ceil(n.height*e),n.canvas.style.width=n.width+"px",n.canvas.style.height=n.height+"px",r.scale(n._pixelDensity,n._pixelDensity),g()),n._pixelDensity},n.map=function(e,t,n,r,i,o){let a=r+1*(e-t)/(n-t)*(i-r)M ;return o?r<i?Math.min(Math.max(a,r),i):Math.min(Math.max(a,i),r):a},n.lerp=function(e,t,n){return e*(1-n)+t*n},n.constrain=function(e,t,n){return Math.min(Math.max(e,t),n)},n.dist=function(){return 4==arguments.length?Math.hypot(arguments[0]-arguments[2],arguments[1]-arguments[3]):Math.hypot(arguments[0]-arguments[3],arguments[1]-arguments[4],arguments[2]-arguments[5])},n.norm=function(e,t,r){return n.map(e,t,r,0,1)},n.sq=function(e){return e*e},n.fract=function(e){return e-Math.floor(e)},n.degrees=function(e){retM urn 180*e/Math.PI},n.radians=function(e){return e*Math.PI/180},n.abs=Math.abs,n.ceil=Math.ceil,n.exp=Math.exp,n.floor=Math.floor,n.log=Math.log,n.mag=Math.hypot,n.max=Math.max,n.min=Math.min,n.round=Math.round,n.sqrt=Math.sqrt,n.sin=Math.sin,n.cos=Math.cos,n.tan=Math.tan,n.asin=Math.asin,n.acos=Math.acos,n.atan=Math.atan,n.atan2=Math.atan2,n.Vector=function(e,t,r){let i=this;i.x=e||0,i.y=t||0,i.z=r||0;let o=null,a=null;function l(e,t,n){return null!=e.x?e:null!=t?{x:e,y:t,z:n||0}:{x:e,y:e,z:e}}function s(){null==a&M &(a=i.x*i.x+i.y*i.y+i.z*i.z,o=Math.sqrt(a))}function h(){a=null,o=null}i.set=function(e,t,n){i.x=e||0,i.y=t||0,i.z=n||0},i.copy=function(){return new n.Vector(i.x,i.y,i.z)},i.add=function(){let e=l.apply(null,arguments);return i.x+=e.x,i.y+=e.y,i.z+=e.z,h(),i},i.rem=function(){let e=l.apply(null,arguments);return i.x%=e.x,i.y%=e.y,i.z%=e.z,h(),i},i.sub=function(){let e=l.apply(null,arguments);return i.x-=e.x,i.y-=e.y,i.z-=e.z,h(),i},i.mult=function(){let e=l.apply(null,arguments);return i.x*=e.x,i.y*=e.y,i.z*=e.z,hM (),i},i.div=function(){let e=l.apply(null,arguments);return i.x/=e.x,i.y/=e.y,i.z/=e.z,h(),i},i.mag=function(){return s(),o},i.magSq=function(){return s(),a},i.dot=function(){let e=l.apply(null,arguments);return i.x*e.x+i.y*e.y+i.z*e.z},i.dist=function(){let e=l.apply(null,arguments),t=i.x-e.x,n=i.y-e.y,r=i.z-e.z;return Math.sqrt(t*t+n*n+r*r)},i.cross=function(){let e=l.apply(null,arguments),t=i.y*e.z-i.z*e.y,n=i.z*e.x-i.x*e.z,r=i.x*e.y-i.y*e.x;return i.x=t,i.y=n,i.z=r,h(),i},i.normalize=function(){s();let e=o;retuM rn i.x/=e,i.y/=e,i.z/=e,o=1,a=1,i},i.limit=function(e){s();if(o>e){let t=e/o;i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e}return i},i.setMag=function(e){s();let t=e/o;return i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e,i},i.heading=function(){return Math.atan2(i.y,i.x)},i.rotate=function(e){let t=Math.cos(e),n=Math.sin(e),r=i.x*t-i.y*n,o=i.x*n+i.y*t;return i.x=r,i.y=o,i},i.angleBetween=function(){let e=l.apply(null,arguments);const t=i.dot(e)/(i.mag()*e.mag());let n;return n=Math.acos(Math.min(1,Math.max(-1,t))),n*Math.sign(i.cross(e).z||1)},M i.lerp=function(e,t){return i.x=i.x*(1-t)+e.x*t,i.y=i.y*(1-t)+e.y*t,i.z=i.z*(1-t)+e.z*t,h(),i},i.reflect=function(e){return e.normalize(),i.sub(e.mult(2*i.dot(e)))},i.array=function(){return[i.x,i.y,i.z]},i.equals=function(e,t){return null==t&&null==(t=Number.EPSILON)&&(t=0),Math.abs(e.x-i.x)<t&&Math.abs(e.y-i.y)<t&&Math.abs(e.z-i.z)<t},i.fromAngle=function(e,t){return null==t&&(t=1),o=t,a=t*t,i.x=t*Math.cos(e),i.y=t*Math.sin(e),i.z=0,i},i.fromAngles=function(e,t,n){null==n&&(n=1),o=n,a=n*n;const r=Math.cos(t),l=MaM th.sin(t),s=Math.cos(e),h=Math.sin(e);return i.x=n*h*l,i.y=-n*s,i.z=n*h*r,i},i.random2D=function(){return o=1,a=1,i.fromAngle(Math.random()*Math.PI*2)},i.random3D=function(){return o=1,a=1,i.fromAngles(Math.random()*Math.PI*2,Math.random()*Math.PI*2)},i.toString=function(){return`[${i.x}, ${i.y}, ${i.z}]`}},n.Vector.add=function(e,t){return new n.Vector(e.x+t.x,e.y+t.y,e.z+t.z)},n.Vector.rem=function(e,t){return new n.Vector(e.x%t.x,e.y%t.y,e.z%t.z)},n.Vector.sub=function(e,t){return new n.Vector(e.x-t.x,e.y-t.y,e.M z-t.z)},n.Vector.mult=function(e,t){return null==t.x?new n.Vector(e.x*t,e.y*t,e.z*t):new n.Vector(e.x*t.x,e.y*t.y,e.z*t.z)},n.Vector.div=function(e,t){return null==t.x?new n.Vector(e.x/t,e.y/t,e.z/t):new n.Vector(e.x/t.x,e.y/t.y,e.z/t.z)},n.Vector.dist=function(e,t){return Math.hypot(e.x-t.x,e.y-t.y,e.z-t.z)},n.Vector.cross=function(e,t){return new n.Vector(e.y*t.z-e.z*t.y,e.z*t.x-e.x*t.z,e.x*t.y-e.y*t.x)},n.Vector.lerp=function(e,t,r){return new n.Vector(e.x*(1-r)+t.x*r,e.y=e.y*(1-r)+t.y*r,e.z=e.z*(1-r)+t.z*r)},n.M Vector.equals=function(e,t,n){return e.equals(t,n)};for(let e of["fromAngle","fromAngles","random2D","random3D"])n.Vector[e]=function(t,r,i){return(new n.Vector)[e](t,r,i)};function x(e,t,n){let r,i,o,a,l,s,h,c,u;if(0==t)return[255*(r=n),255*(i=n),255*(o=n)];switch((a=e)>360&&(a=0),h=n*(1-t),c=n*(1-t*(s=(a/=60)-(l=~~a))),u=n*(1-t*(1-s)),l){case 0:r=n,i=u,o=h;break;case 1:r=c,i=n,o=h;break;case 2:r=h,i=n,o=u;break;case 3:r=h,i=c,o=n;break;case 4:r=u,i=h,o=n;break;default:r=n,i=h,o=c}return[255*r,255*i,255*o]}functioM n g(){r.fillStyle="white",r.strokeStyle="black",r.lineCap="round",r.lineJoin="miter"}function p(e){if(0<=e&&e<2*Math.PI)return e;for(;e<0;)e+=2*Math.PI;for(;e>=Math.PI;)e-=2*Math.PI;return e}function m(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;let c=p(a),u=p(l);r.beginPath();for(let a=0;a<h+1;a++){let l=a/h,s=n.lerp(c,u,l),f=Math.cos(s)*i/2,d=Math.sin(s)*o/2;r[a?"lineTo":"moveTo"](e+f,t+d)}s==n.CHORD?r.closePath():s==n.PIE&&(r.lineTo(e,t),r.closePath()),n._style.noFill||r.fill(),n._style.noStrokM e||r.stroke()}function b(e,t,i,o){n._style.noFill&&n._style.noStroke||(r.beginPath(),r.ellipse(e,t,i/2,o/2,0,0,2*Math.PI),n._style.noFill||r.fill(),n._style.noStroke||r.stroke())}function y(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;if(null==a)return function(e,t,i,o){n._style.noFill||r.fillRect(e,t,i,o),n._style.noStroke||r.strokeRect(e,t,i,o)}(e,t,i,o);if(null==l)return y(e,t,i,o,a,a,a,a);const c=Math.min(Math.abs(o),Math.abs(i))/2;a=Math.min(c,a),l=Math.min(c,l),h=Math.min(c,h),s=Math.min(c,s)M ,r.beginPath(),r.moveTo(e+a,t),r.arcTo(e+i,t,e+i,t+o,l),r.arcTo(e+i,t+o,e,t+o,s),r.arcTo(e,t+o,e,t,h),r.arcTo(e,t,e+i,t,a),r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke()}function w(){a=[]}n.createVector=function(e,t,r){return new n.Vector(e,t,r)},n.curvePoint=function(e,t,n,r,i){const o=i*i*i,a=i*i;return e*(-.5*o+a-.5*i)+t*(1.5*o-2.5*a+1)+n*(-1.5*o+2*a+.5*i)+r*(.5*o-.5*a)},n.bezierPoint=function(e,t,n,r,i){const o=1-i;return Math.pow(o,3)*e+3*Math.pow(o,2)*i*t+3*o*Math.pow(i,2)*n+Math.pow(i,M 3)*r},n.curveTangent=function(e,t,n,r,i){const o=i*i;return e*(-3*o/2+2*i-.5)+t*(9*o/2-5*i)+n*(-9*o/2+4*i+.5)+r*(3*o/2-i)},n.bezierTangent=function(e,t,n,r,i){const o=1-i;return 3*r*Math.pow(i,2)-3*n*Math.pow(i,2)+6*n*o*i-6*t*o*i+3*t*Math.pow(o,2)-3*e*Math.pow(o,2)},n.Color=function(e,t,n,r){let i=this;i.MAGIC=786698,i._r=e,i._g=t,i._b=n,i._a=r,i._h=0,i._s=0,i._v=0,i._hsvInferred=!1,i.setRed=function(e){i._r=e,i._hsvInferred=!1},i.setGreen=function(e){i._g=e,i._hsvInferred=!1},i.setBlue=function(e){i._b=e,i._hsvInfM erred=!1},i.setAlpha=function(e){i._a=e/255,i._hsvInferred=!1},i._inferHSV=function(){i._hsvInferred||([i._h,i._s,i._v]=function(e,t,n){let r,i,o,a,l;return r=e<t?e<n?e:n:t<n?t:n,0==(l=100*(i=e>t?e>n?e:n:t>n?t:n)/255)?[o=0,a=0,l]:0==(a=100*(i-r)/i)?[o=0,a,l]:(o=i==e?0+60*(t-n)/(i-r):i==t?120+60*(n-e)/(i-r):240+60*(e-t)/(i-r),[o,a,l])}(i._r,i._g,i._b),i._hsvInferred=!0)},i.toString=function(){return`rgba(${Math.round(i._r)},${Math.round(i._g)},${Math.round(i._b)},${~~(1e3*i._a)/1e3})`}},n.colorMode=function(e){n._stM yle.colorMode=e},n.color=function(){if(1==arguments.length&&786698==arguments[0].MAGIC)return arguments[0];if(n._style.colorMode==n.RGB){if(1==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],1);if(2==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],arguments[1]/255);if(3==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],1);if(4==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],arguments[3]/255)}else{if(1==argumeM nts.length)return new n.Color(...x(0,0,arguments[0]/100),1);if(2==arguments.length)return new n.Color(...x(0,0,arguments[0]/100),arguments[1]/255);if(3==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),1);if(4==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),arguments[3])}return null},n.red=function(e){return e._r},n.green=function(e){return e._g},n.blue=function(e){return e._b},n.alpha=function(e){return 255*e._a},n.hue=function(e){reM turn e._inferHSV(),e._h},n.saturation=function(e){return e._inferHSV(),e._s},n.brightness=function(e){return e._inferHSV(),e._v},n.lightness=function(e){return 100*(.2126*e._r+.7152*e._g+.0722*e._b)/255},n.lerpColor=function(e,t,r){return n._style.colorMode==n.RGB?new n.Color(n.constrain(n.lerp(e._r,t._r,r),0,255),n.constrain(n.lerp(e._g,t._g,r),0,255),n.constrain(n.lerp(e._b,t._b,r),0,255),n.constrain(n.lerp(e._a,t._a,r),0,1)):(e._inferHSV(),t._inferHSV(),new n.Color(n.constrain(function(e,t,r){var i=[[Math.abs(t-M e),n.map(r,0,1,e,t)],[Math.abs(t+360-e),n.map(r,0,1,e,t+360)],[Math.abs(t-360-e),n.map(r,0,1,e,t-360)]];return i.sort(((e,t)=>e[0]-t[0])),(i[0][1]+720)%360}(e._h,t._h,r),0,360),n.constrain(n.lerp(e._s,t._s,r),0,100),n.constrain(n.lerp(e._v,t._v,r),0,100),n.constrain(n.lerp(e._a,t._a,r),0,1)))},n.strokeWeight=function(e){n._style_noStroke=!1,r.lineWidth=e},n.stroke=function(){if(n._style.noStroke=!1,"string"==typeof arguments[0])return void(r.strokeStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._sM tyle.noStroke=!0:r.strokeStyle=e},n.noStroke=function(){n._style.noStroke=!0},n.fill=function(){if(n._style.noFill=!1,"string"==typeof arguments[0])return void(r.fillStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._style.noFill=!0:r.fillStyle=e},n.noFill=function(){n._style.noFill=!0},n.blendMode=function(e){r.globalCompositeOperation=e},n.strokeCap=function(e){r.lineCap=e},n.strokeJoin=function(e){r.lineJoin=e},n.ellipseMode=function(e){n._style.ellipseMode=e},n.rectMode=function(e){n._style.rectM Mode=e},n.curveDetail=function(e){n._style.curveDetail=e},n.curveAlpha=function(e){n._style.curveAlpha=e},n.curveTightness=function(e){n._style.curveAlpha=e},n.clear=function(){r.clearRect(0,0,n.width,n.height)},n.background=function(){if(arguments[0]&&arguments[0].MAGIC==n.MAGIC)return n.image(arguments[0],0,0,n.width,n.height);r.save(),r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity),r.fillStyle="string"==typeof arguments[0]?arguments[0]:n.color(...Array.from(arguments)),r.fillRect(0,0,n.width,n.heightM ),r.restore()},n.line=function(e,t,i,o){n._style.noStroke||(r.beginPath(),r.moveTo(e,t),r.lineTo(i,o),r.stroke())},n.arc=function(e,t,r,i,o,a,l,s){if(o==a)return n.ellipse(e,t,r,i);null==s&&(s=25),null==l&&(l=n.PIE),n._style.ellipseMode==n.CENTER?m(e,t,r,i,o,a,l,s):n._style.ellipseMode==n.RADIUS?m(e,t,2*r,2*i,o,a,l,s):n._style.ellipseMode==n.CORNER?m(e+r/2,t+i/2,r,i,o,a,l,s):n._style.ellipseMode==n.CORNERS&&m((e+r)/2,(t+i)/2,r-e,i-t,o,a,l,s)},n.ellipse=function(e,t,r,i){null==i&&(i=r),n._style.ellipseMode==n.CENTERM ?b(e,t,r,i):n._style.ellipseMode==n.RADIUS?b(e,t,2*r,2*i):n._style.ellipseMode==n.CORNER?b(e+r/2,t+i/2,r,i):n._style.ellipseMode==n.CORNERS&&b((e+r)/2,(t+i)/2,r-e,i-t)},n.circle=function(e,t,r){return n.ellipse(e,t,r,r)},n.point=function(e,t){e.x&&(t=e.y,e=e.x),r.beginPath(),r.ellipse(e,t,.4,.4,0,0,2*Math.PI),r.stroke()},n.rect=function(e,t,r,i,o,a,l,s){n._style.rectMode==n.CENTER?y(e-r/2,t-i/2,r,i,o,a,l,s):n._style.rectMode==n.RADIUS?y(e-r,t-i,2*r,2*i,o,a,l,s):n._style.rectMode==n.CORNER?y(e,t,r,i,o,a,l,s):n._stylM e.rectMode==n.CORNERS&&y(e,t,r-e,i-t,o,a,l,s)},n.square=function(e,t,r,i,o,a,l){return n.rect(e,t,r,r,i,o,a,l)},n.beginShape=function(){w(),r.beginPath(),o=!0},n.beginContour=function(){r.closePath(),w(),o=!0},n.endContour=function(){w(),o=!0},n.vertex=function(e,t){w(),o?r.moveTo(e,t):r.lineTo(e,t),o=!1},n.bezierVertex=function(e,t,n,i,o,a){w(),r.bezierCurveTo(e,t,n,i,o,a)},n.quadraticVertex=function(e,t,n,i){w(),r.quadraticCurveTo(e,t,n,i)},n.bezier=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.bezierVM ertex(r,i,o,a,l,s),n.endShape()},n.triangle=function(e,t,r,i,o,a){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.endShape(n.CLOSE)},n.quad=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.vertex(l,s),n.endShape(n.CLOSE)},n.endShape=function(e){w(),e&&r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke(),n._style.noFill&&n._style.noStroke&&(r.save(),r.fillStyle="none",r.fill(),r.restore())},n.curveVertex=function(e,t){if(a.push([e,t]),a.length<4)return;M let i=function(e,t,n,r,i,o,a,l,s,h){function c(e,t,n,r,i,o){let a=Math.pow(r-t,2)+Math.pow(i-n,2);return Math.pow(a,.5*o)+e}let u=[],f=c(0,e,t,n,r,h),d=c(f,n,r,i,o,h),x=c(d,i,o,a,l,h);for(let h=0;h<s;h++){let c=f+h/(s-1)*(d-f),g=[(f-c)/(f-0),(c-0)/(f-0),(d-c)/(d-f),(c-f)/(d-f),(x-c)/(x-d),(c-d)/(x-d),(d-c)/(d-0),(c-0)/(d-0),(x-c)/(x-f),(c-f)/(x-f)];for(let e=0;e<g.length;e+=2)isNaN(g[e])&&(g[e]=1,g[e+1]=0),isFinite(g[e])||(g[e]>0?(g[e]=1,g[e+1]=0):(g[e]=0,g[e+1]=1));let p=e*g[0]+n*g[1],m=t*g[0]+r*g[1],b=n*g[2]+i*g[M 3],y=r*g[2]+o*g[3],w=i*g[4]+a*g[5],v=o*g[4]+l*g[5],z=p*g[6]+b*g[7],V=m*g[6]+y*g[7],_=b*g[8]+w*g[9],M=y*g[8]+v*g[9],E=z*g[2]+_*g[3],S=V*g[2]+M*g[3];u.push([E,S])}return u}(...a[a.length-4],...a[a.length-3],...a[a.length-2],...a[a.length-1],n._style.curveDetail,n._style.curveAlpha);for(let e=0;e<i.length;e++)o?r.moveTo(...i[e]):r.lineTo(...i[e]),o=!1},n.curve=function(e,t,r,i,o,a,l,s){n.beginShape(),n.curveVertex(e,t),n.curveVertex(r,i),n.curveVertex(o,a),n.curveVertex(l,s),n.endShape()},n.translate=function(e,t){r.tM ranslate(e,t)},n.rotate=function(e){r.rotate(e)},n.scale=function(e,t){null==t&&(t=e),r.scale(e,t)},n.applyMatrix=function(e,t,n,i,o,a){r.transform(e,t,n,i,o,a)},n.shearX=function(e){r.transform(1,0,Math.tan(e),1,0,0)},n.shearY=function(e){r.transform(1,Math.tan(e),0,1,0,0)},n.resetMatrix=function(){r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity)},n.pushMatrix=n.push=function(){n._styleCache.push({...n._style}),n._style=n._styleCache[n._styleCache.length-1],r.save()},n.popMatrix=n.pop=function(){n._stylM eCache.length-1&&(n._styleCache.pop(),n._style=n._styleCache[n._styleCache.length-1],r.restore())},n.image=function(e,t,i,o,a,l,s,h,c){let u=e.MAGIC==n.MAGIC?e.canvas:e;function d(){if(e.MAGIC!=n.MAGIC||!n._tint)return;let t=e.canvas.getContext("2d");t.save(),t.resetTransform(),t.clearRect(0,0,t.canvas.width,t.canvas.height),t.drawImage(f.canvas,0,0),t.restore()}return e.MAGIC==n.MAGIC&&null!=n._tint&&(function(e,t){null==f&&(f=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvasM .height),f.canvas.width==e&&f.canvas.height==t||(f.canvas.width=e,f.canvas.height=t)}(e.canvas.width,e.canvas.height),f.drawImage(e.canvas,0,0),e.tinted(n._tint)),o?l?(h||(h=u.width),c||(c=u.height),r.drawImage(u,l,s,h,c,t,i,o,a),void d()):(r.drawImage(u,t,i,o,a),void d()):(e.MAGIC==n.MAGIC||e.width?r.drawImage(u,t,i,e.width,e.height):r.drawImage(u,t,i,e.videoWidth,e.videoHeight),void d())},n.loadPixels=function(){l=r.getImageData(0,0,n.canvas.width,n.canvas.height),n.pixels=l.data},n.updatePixels=function(){null!=M l&&r.putImageData(l,0,0)},n.loadImage=function(e,t){s++;let r=n.createGraphics(100,100),i=r.canvas.getContext("2d"),o=new Image;return o.src=e,o.crossOrigin="Anonymous",o.onload=function(){i.canvas.width=o.width,i.canvas.height=o.height,r.width=o.width,r.height=o.height,i.drawImage(o,0,0),s--,t&&t(r)},r};let v={};function z(e,t){null==u&&(u=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvas.height),u.canvas.width==e&&u.canvas.height==t||(u.canvas.width=e,u.canvas.height=t)}funcM tion V(){let e=r.canvas.width*r.canvas.height*4;null!=d&&e==d.length||(d=new Uint8ClampedArray(e))}function _(e){u.clearRect(0,0,u.canvas.width,u.canvas.height),u.filter=e,u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()}v[n.THRESHOLD]=function(e,t){null==t?t=127.5:t*=255;for(let n=0;n<e.length;n+=4){const r=.2126*e[n]+.7152*e[n+1]+.0722*e[n+2];e[n]=e[n+1]=e[n+2]=r>=t?255:0}},v[n.GRAY]=function(e){for(let t=0;t<e.length;t+=4)M {const n=.2126*e[t]+.7152*e[t+1]+.0722*e[t+2];e[t]=e[t+1]=e[t+2]=n}},v[n.OPAQUE]=function(e){for(let t=0;t<e.length;t+=4)e[t+3]=255},v[n.INVERT]=function(e){for(let t=0;t<e.length;t+=4)e[t]=255-e[t],e[t+1]=255-e[t+1],e[t+2]=255-e[t+2]},v[n.POSTERIZE]=function(e,t){let n=t-1;for(let r=0;r<e.length;r+=4)e[r]=255*(e[r]*t>>8)/n,e[r+1]=255*(e[r+1]*t>>8)/n,e[r+2]=255*(e[r+2]*t>>8)/n},v[n.DILATE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-M 1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.max(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.ERODE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.min(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.BLURM ]=function(e,t){t=t||1,t=Math.floor(t*n._pixelDensity),V(),d.set(e);let i=2*t+1,o=function(e){let n=new Float32Array(e),r=.3*t+.8,i=r*r*2;for(let t=0;t<e;t++){let o=t-e/2,a=Math.exp(-o*o/i)/(2.5066282746*r);n[t]=a}return n}(i),[a,l]=[r.canvas.width,r.canvas.height];for(let n=0;n<l;n++)for(let r=0;r<a;r++){let l=0,s=0,h=0,c=0;for(let e=0;e<i;e++){let i=4*(n*a+Math.min(Math.max(r-t+e,0),a-1));l+=d[i]*o[e],s+=d[i+1]*o[e],h+=d[i+2]*o[e],c+=d[i+3]*o[e]}let u=4*(n*a+r);e[u]=l,e[u+1]=s,e[u+2]=h,e[u+3]=c}d.set(e);for(let nM =0;n<l;n++)for(let r=0;r<a;r++){let s=0,h=0,c=0,u=0;for(let e=0;e<i;e++){let i=4*(Math.min(Math.max(n-t+e,0),l-1)*a+r);s+=d[i]*o[e],h+=d[i+1]*o[e],c+=d[i+2]*o[e],u+=d[i+3]*o[e]}let f=4*(n*a+r);e[f]=s,e[f+1]=h,e[f+2]=c,e[f+3]=u}},n.filter=function(e,t){if(n.HARDWARE_FILTERS&&null!=r.filter)if(z(),e==n.THRESHOLD){null==t&&(t=.5),t=Math.max(t,1e-5),_(`saturate(0%) brightness(${Math.floor(.5/t*100)}%) contrast(1000000%)`)}else if(e==n.GRAY)_("saturate(0%)");else if(e==n.OPAQUE)u.fillStyle="black",u.fillRect(0,0,u.canvaM s.width,u.canvas.height),u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.drawImage(u.canvas,0,0),r.restore();else if(e==n.INVERT)_("invert(100%)");else if(e==n.BLUR)_(`blur(${Math.ceil(t*n._pixelDensity/1)||1}px)`);else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}},n.resize=function(e,t){z(),u.drawImage(r.canvas,0,0),n.width=e,n.height=t,r.canvas.width=e*n._pixM elDensity,r.canvas.height=t*n._pixelDensity,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0,r.canvas.width,r.canvas.height),r.restore()},n.get=function(e,t,i,o){if(null!=e&&null==i){let i=r.getImageData(e,t,1,1).data;return new n.Color(i[0],i[1],i[2],i[3]/255)}e=e||0,t=t||0,i=i||n.width,o=o||n.height;let a=n.createGraphics(i,o);a.pixelDensity(n._pixelDensity);let l=r.getImageData(e*n._pixelDensity,t*n._pixelDensity,i*n._pixelDensity,o*n._pixelDensity);return a.caM nvas.getContext("2d").putImageData(l,0,0),a},n.set=function(e,t,i){if(i.MAGIC==n.MAGIC){let r=n._tint;return n._tint=null,n.image(i,e,t),void(n._tint=r)}let o=4*(t*n._pixelDensity*r.canvas.width+e*n._pixelDensity);n.pixels[o]=i._r,n.pixels[o+1]=i._g,n.pixels[o+2]=i._b,n.pixels[o+3]=255*i._a},n.tinted=function(){let e=n.color(...Array.from(arguments)),t=e._a;e._a=1,z(),u.clearRect(0,0,u.canvas.width,u.canvas.height),u.fillStyle=e,u.fillRect(0,0,u.canvas.width,u.canvas.height),u.globalCompositeOperation="multiply",u.M drawImage(r.canvas,0,0),u.globalCompositeOperation="source-over",r.save(),r.resetTransform();let i=r.globalCompositeOperation;r.globalCompositeOperation="source-in",r.drawImage(u.canvas,0,0),r.globalCompositeOperation=i,r.restore(),u.globalAlpha=t,u.clearRect(0,0,u.canvas.width,u.canvas.height),u.drawImage(r.canvas,0,0),u.globalAlpha=1,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()},n.tint=function(){n._tint=n.color(...Array.from(arguments))},n.noTiM nt=function(){n._tint=null},n.mask=function(e){r.save(),r.resetTransform();let t=r.globalCompositeOperation;r.globalCompositeOperation="destination-in",r.drawImage(e.canvas,0,0),r.globalCompositeOperation=t,r.restore()},n.clearTemporaryBuffers=function(){u=null,f=null,d=null},n.save=function(e,t){e=e||"untitled",t=t||"png";var n=document.createElement("a");n.innerHTML="[Download]",n.addEventListener("click",(function(){this.href=r.canvas.toDataURL(),this.download=e+"."+t}),!1),document.body.appendChild(n),n.click()M ,document.body.removeChild(n)},n.saveCanvas=function(e,t,r){if(e.MAGIC==n.MAGIC){r&&e.save(t,r);let n=t.split(".");return e.save(n.slice(0,-1).join("."),n[n.length-1])}if(t)return n.save(e,t);let i=e.split(".");return n.save(i.slice(0,-1).join("."),i[i.length-1])},n.loadFont=function(e){let t=e.split("/"),n=t[t.length-1].split(".")[0].replace(" ",""),r=`@font-face {\n font-family: '${n}';\n src: url('${e}');\n }`;const i=document.createElement("style");return i.textContent=r,document.head.append(M i),n},n.textFont=function(e){n._style.textFont=e},n.textSize=function(e){n._style.textSize=e,n._style.textLeading=e},n.textLeading=function(e){n._style.textLeading=e},n.textStyle=function(e){n._style.textStyle=e},n.textAlign=function(e,t){r.textAlign=e,t&&(r.textBaseline=t==n.CENTER?"middle":t)},n.text=function(e,t,i,o){if(!e)return;if(e=e.toString(),n._style.noFill&&n._style.noStroke)return;r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`;let a=e.split("\n");for(let e=0;e<a.length;e++)n._M style.noFill||r.fillText(a[e],t,i,o),n._style.noStroke||r.strokeText(a[e],t,i,o),i+=n._style.textLeading},n.textWidth=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).width},n.textAscent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBoundingBoxAscent},n.textDescent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBounM dingBoxDescent};var M,E=4,S=.5,R=function(e){return.5*(1-Math.cos(e*Math.PI))};n.noise=function(e,t,n){if(t=t||0,n=n||0,null==M){M=new Array(4096);for(var r=0;r<4096;r++)M[r]=Math.random()}e<0&&(e=-e),t<0&&(t=-t),n<0&&(n=-n);for(var i,o,a,l,s,h=Math.floor(e),c=Math.floor(t),u=Math.floor(n),f=e-h,d=t-c,x=n-u,g=0,p=.5,m=0;m<E;m++){var b=h+(c<<4)+(u<<8);i=R(f),o=R(d),a=M[4095&b],a+=i*(M[b+1&4095]-a),l=M[b+16&4095],a+=o*((l+=i*(M[b+16+1&4095]-l))-a),l=M[4095&(b+=256)],l+=i*(M[b+1&4095]-l),s=M[b+16&4095],l+=o*((s+=i*(M[M b+16+1&4095]-s))-l),g+=(a+=R(x)*(l-a))*p,p*=S,h<<=1,c<<=1,u<<=1,(f*=2)>=1&&(h++,f--),(d*=2)>=1&&(c++,d--),(x*=2)>=1&&(u++,x--)}return g},n.noiseDetail=function(e,t){e>0&&(E=e),t>0&&(S=t)};const I=function(){let e,t,n=4294967295;return{setSeed(r){e=t=(null==r?Math.random()*n:r)>>>0},getSeed:()=>t,rand:()=>(e^=e<<17,e^=e>>13,((e^=e<<5)>>>0)/n)}};let C=I();C.setSeed(),n.noiseSeed=function(e){let t=null==e?4294967295*Math.random():e;M||(M=new Float32Array(4096));for(var n=0;n<4096;n++)t^=t<<17,t^=t>>13,t^=t<<5,M[n]=(t>M >>0)/4294967295},n.randomSeed=function(e){C.setSeed(e)},n.random=function(e,t){return null==e?C.rand():"number"==typeof e?null!=t?C.rand()*(t-e)+e:C.rand()*e:e[~~(e.length*C.rand())]},n.randomGenerator=function(e){e==n.LCG?C=function(){const e=4294967296;let t,n;return{setSeed(r){n=t=(null==r?Math.random()*e:r)>>>0},getSeed:()=>t,rand:()=>(n=(1664525*n+1013904223)%e)/e}}():e==n.SHR3&&(C=I()),C.setSeed()};var T=new function(){var e,t,n,r=new Array(128),i=new Array(256),o=new Array(128),a=new Array(128),l=new Array(2M 56),s=new Array(256),h=function(){return 4294967296*C.rand()-2147483648},c=function(){return.5+2.328306e-10*(h()<<0)};this.SHR3=h,this.UNI=c,this.RNOR=function(){return n=h(),e=127&n,Math.abs(n)<r[e]?n*o[e]:function(){for(var t,i,l,s,u=3.44262;;){if(t=n*o[e],0==e){do{l=c(),s=c(),t=.2904764*-Math.log(l),i=-Math.log(s)}while(i+i<t*t);return n>0?u+t:-u-t}if(a[e]+c()*(a[e-1]-a[e])<Math.exp(-.5*t*t))return t;if(n=h(),e=127&n,Math.abs(n)<r[e])return n*o[e]}}()},this.REXP=function(){return(t=h()>>>0)<r[e=255&t]?t*l[e]:funM ction(){for(var n;;){if(0==e)return 7.69711-Math.log(c());if(n=t*l[e],s[e]+c()*(s[e-1]-s[e])<Math.exp(-n))return n;if((t=h())<i[e=255&t])return t*l[e]}}()},this.zigset=function(){var e,t,n=2147483648,h=4294967296,c=3.442619855899,u=c,f=.00991256303526217,d=7.697117470131487,x=d,g=.003949659822581572;for(e=f/Math.exp(-.5*c*c),r[0]=Math.floor(c/e*n),r[1]=0,o[0]=e/n,o[127]=c/n,a[0]=1,a[127]=Math.exp(-.5*c*c),t=126;t>=1;t--)c=Math.sqrt(-2*Math.log(f/c+Math.exp(-.5*c*c))),r[t+1]=Math.floor(c/u*n),u=c,a[t]=Math.exp(-.5*cM *c),o[t]=c/n;for(e=g/Math.exp(-d),i[0]=Math.floor(d/e*h),i[1]=0,l[0]=e/h,l[255]=d/h,s[0]=1,s[255]=Math.exp(-d),t=254;t>=1;t--)d=-Math.log(g/d+Math.exp(-d)),i[t+1]=Math.floor(d/x*h),x=d,s[t]=Math.exp(-d),l[t]=d/h}};T.hasInit=!1,n.randomGaussian=function(e,t){return T.hasInit||(T.zigset(),T.hasInit=!0),T.RNOR()*t+e},n.randomExponential=function(){return T.hasInit||(T.zigset(),T.hasInit=!0),T.REXP()},n.print=console.log,n.cursor=function(e,t,r){let i="";e.includes(".")&&(e=`url("${e}")`,i=", auto"),null!=t&&(e+=" "+t+M " "+r),n.canvas.style.cursor=e+i},n.noCursor=function(){n.canvas.style.cursor="none"},n.createCapture=function(e){var t=document.createElement("video");return t.playsinline="playsinline",t.autoplay="autoplay",navigator.mediaDevices.getUserMedia(e).then((function(e){t.srcObject=e})),t.style.position="absolute",t.style.opacity=1e-5,t.style.zIndex=-1e3,document.body.appendChild(t),t};let A=["setup","draw","preload","mouseMoved","mousePressed","mouseReleased","mouseDragged","mouseClicked","keyPressed","keyReleased","keM yTyped","touchStarted","touchEnded"];for(let e of A){let t="_"+e+"Fn";n[t]=function(){},n[t].isPlaceHolder=!0,n[e]?n[t]=n[e]:Object.defineProperty(n,e,{set:function(e){n[t]=e}})}function D(){n._noLoop||(i=null==n._frameRate?requestAnimationFrame(D):setTimeout(D,1e3/n._frameRate)),w(),o=!0,n.push(),n._drawFn(),n.pop(),++n.frameCount}function k(e){const t=n.canvas.getBoundingClientRect(),r=n.canvas.scrollWidth/n.width||1,i=n.canvas.scrollHeight/n.height||1;return{x:(e.clientX-t.left)/r,y:(e.clientY-t.top)/i,id:e.idenM tifier}}function L(){return n._touchStarted.isPlaceHolder&&n._touchMoved.isPlaceHolder&&n._touchEnded.isPlaceHolder}n.noLoop=function(){n._noLoop=!0,i=null},n.loop=function(){n._noLoop=!1,null==i&&D()},n.redraw=function(){D()},n.frameRate=function(e){n._frameRate=e},setTimeout((function(){n._preloadFn(),c=window.performance.now(),function e(){if(s>0)return setTimeout(e,10);n._setupFn(),D()}()}),1),n.canvas.onmousemove=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPM ressed?n._mouseDraggedFn(e):n._mouseMovedFn(e)},n.canvas.onmousedown=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!0,n.mouseButton=[n.LEFT,n.CENTER,n.RIGHT][e.button],n._mousePressedFn(e)},n.canvas.onmouseup=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!1,n._mouseReleasedFn(e)},n.canvas.onclick=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressedM =!0,n._mouseClickedFn(e),n.mouseIsPressed=!1},window.addEventListener("keydown",(function(e){n.keyIsPressed=!0,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!0,n._keyPressedFn(e),1==e.key.length&&n._keyTypedFn(e)})),window.addEventListener("keyup",(function(e){n.keyIsPressed=!1,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!1,n._keyReleasedFn(e)})),n.keyIsDown=function(e){return!!h[e]},n.canvas.ontouchstart=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.moM useY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mousePressedFn(e)||e.preventDefault()),n._touchStartedFn(e)||e.preventDefault()},n.canvas.ontouchmove=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mouseDraggedFn(e)||e.preventDefault()),n._touchMovedFn(e)||e.preventDefault()},n.canvas.ontouchend=n.canvas.ontouchcancel=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.M mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!1,n._mouseReleasedFn(e)||e.preventDefault()),n._touchEndedFn(e)||e.preventDefault()},n.hasSensorPermission=!window.DeviceOrientationEvent&&!window.DeviceMotionEvent||!(DeviceOrientationEvent.requestPermission||DeviceMotionEvent.requestPermission),n.requestSensorPermissions=function(){DeviceOrientationEvent.requestPermission&&DeviceOrientationEvent.requestPermission().then((e=>{"granted"==e&&DeviceMotionEvent.requestPermissioM n&&DeviceMotionEvent.requestPermission().then((e=>{"granted"==e&&(n.hasSensorPermission=!0)})).catch(alert)})).catch(alert)},window.ondeviceorientation=function(e){n.pRotationX=n.rotationX,n.pRotationY=n.rotationY,n.pRotationZ=n.rotationZ,n.pRelRotationX=n.relRotationX,n.pRelRotationY=n.relRotationY,n.pRelRotationZ=n.relRotationZ,n.rotationX=e.beta*(Math.PI/180),n.rotationY=e.gamma*(Math.PI/180),n.rotationZ=e.alpha*(Math.PI/180),n.relRotationX=[-n.rotationY,-n.rotationX,n.rotationY][1+~~(window.orientation/90)],n.rM elRotationY=[-n.rotationX,n.rotationY,n.rotationX][1+~~(window.orientation/90)],n.relRotationZ=n.rotationZ},window.ondevicemotion=function(e){if(n.pAccelerationX=n.accelerationX,n.pAccelerationY=n.accelerationY,n.pAccelerationZ=n.accelerationZ,!e.acceleration){let t=((e,t)=>[(e[0]*t[0]+e[1]*t[1]+e[2]*t[2]+e[3])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[4]*t[0]+e[5]*t[1]+e[6]*t[2]+e[7])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[8]*t[0]+e[9]*t[1]+e[10]*t[2]+e[11])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15])])(((e,t)M =>[e[0]*t[0]+e[1]*t[4]+e[2]*t[8]+e[3]*t[12],e[0]*t[1]+e[1]*t[5]+e[2]*t[9]+e[3]*t[13],e[0]*t[2]+e[1]*t[6]+e[2]*t[10]+e[3]*t[14],e[0]*t[3]+e[1]*t[7]+e[2]*t[11]+e[3]*t[15],e[4]*t[0]+e[5]*t[4]+e[6]*t[8]+e[7]*t[12],e[4]*t[1]+e[5]*t[5]+e[6]*t[9]+e[7]*t[13],e[4]*t[2]+e[5]*t[6]+e[6]*t[10]+e[7]*t[14],e[4]*t[3]+e[5]*t[7]+e[6]*t[11]+e[7]*t[15],e[8]*t[0]+e[9]*t[4]+e[10]*t[8]+e[11]*t[12],e[8]*t[1]+e[9]*t[5]+e[10]*t[9]+e[11]*t[13],e[8]*t[2]+e[9]*t[6]+e[10]*t[10]+e[11]*t[14],e[8]*t[3]+e[9]*t[7]+e[10]*t[11]+e[11]*t[15],e[12]*t[0]+M e[13]*t[4]+e[14]*t[8]+e[15]*t[12],e[12]*t[1]+e[13]*t[5]+e[14]*t[9]+e[15]*t[13],e[12]*t[2]+e[13]*t[6]+e[14]*t[10]+e[15]*t[14],e[12]*t[3]+e[13]*t[7]+e[14]*t[11]+e[15]*t[15]])((e=>[Math.cos(e),0,Math.sin(e),0,0,1,0,0,-Math.sin(e),0,Math.cos(e),0,0,0,0,1])(n.rotationY),(e=>[1,0,0,0,0,Math.cos(e),-Math.sin(e),0,0,Math.sin(e),Math.cos(e),0,0,0,0,1])(n.rotationX)),[0,0,-9.80665]);n.accelerationX=e.accelerationIncludingGravity.x+t[0],n.accelerationY=e.accelerationIncludingGravity.y+t[1],n.accelerationZ=e.accelerationIncludM ingGravity.z-t[2]}},n.year=function(){return(new Date).getFullYear()},n.day=function(){return(new Date).getDay()},n.hour=function(){return(new Date).getHours()},n.minute=function(){return(new Date).getMinutes()},n.second=function(){return(new Date).getSeconds()},n.millis=function(){return window.performance.now()-c}}(e)}"object"==typeof exports&&"undefined"!=typeof module&&(module.exports=e);const t="https://ancient-crimson-rain.btc.discover.quiknode.pro/c268fb026303ae8443f785200f2ea4b82f0082dd";function n(e){P(e)?M localStorage.removeItem("blocksApiEndpoint"):localStorage.blocksApiEndpoint=e}function r(){return localStorage.blocksApiEndpoint||t}function i(e){P(e)?localStorage.removeItem("modelInscriptionEndpoint"):localStorage.modelInscriptionEndpoint=e}function o(){return localStorage.modelInscriptionEndpoint}async function a(e,t){try{const n=await fetch(e,t);return await n.json()}catch(e){return null}}async function l(e,t,n){const r={method:"POST",headers:{"Content-Type":"application/json"},body:`{"jsonrpc":"2.0","id":1,"meM thod":"${t}","params":${`[${n.join(sep=",")}]`}}`};return(await a(e,r))?.result}async function s(e){const n={avgfee:10,time:Date.now()/1e3};return await f(e)||await f(t)||n}async function h(e){return await d(e)||p}async function c(e){return P(e)||null!=await f(e)}async function u(e){return P(e)||null!=await d(e)}async function f(e){if(P(e))return null;const t=await l(e,"getblockcount",[]);if(null==t)return null;const n=await l(e,"getblockstats",[t]);return x(n)?n:null}async function d(e){if(P(e))return null;const tM =await a(e,{});return g(t)?t:null}function x(e){return"number"==typeof e?.time&&"number"==typeof e?.avgfee}function g(e){if(null==e)return!1;const{classes_name:t,training_traits:n,layers_config:r,weight_b64:i}=e;if(!Array.isArray(t))return!1;if(null==n)return!1;try{j(r,i)}catch(e){return!1}return!0}const p={"model_name": "pfp_classifier_43", "layers_config": {"config": {"layers": [{"class_name": "InputLayer", "config": {"batch_input_shape": [null, 28, 28, 3]}}, {"class_name": "Rescaling", "config": {"scale": 0.0078M 4313725490196, "offset": -1}}, {"class_name": "Flatten"}, {"class_name": "Dense", "config": {"units": 14, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 19, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 8, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 4, "activation": "linear"}}]}}, "weight_b64": "fVCSPW7gXr1KgzW81fKwPGuc/jzAv+o8r8VEPaIctb0orkK7nYksPaf0Ub0oeAa9EsK7PNMgJL29egq9JRgRvcLmmr3qkwC9okgBPd1bKzy6Xa89xSguvac5nDxzl8y8rH8nvWQNELyhoEi9QhaLPenyWj1hM 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 PVXnDbz3CS+9oHYuPVpWqjvTaNI9xjbMPXJHFj2mkhq9jfTOPNaXGbzR7dS9jdOnvN1qhj3qZ8G8NdE8vGsi07xtDPE8lkDZvH0hRLz12sA8PIrfPNDBJ73bRSM9LsgCvAXiIr1b8I47C8hgPexPPj2D+WY95JtKPOP3AL5Ew7s8h1ACPT2Z1jyg/C48HSOMvBFzgz072BI8K/30vBwPJzx95Q294yGaPQcPWTvWP728QMJFPVOEF732CDk9CApYPYZqWz3MOl88GtWPPbeHar0Sn3O9R/HgvFj8uDrrCo89eHxOPSzSmrxmx2M971BBPN7rbTwzig49CD8NO9Gp3L37JBS9oUSFvGhiib0MAcW8qm4cPal0kryxO528JLxePeLbFr42Tcq8ys8Cu7F1Mj0OMaI9BuF/vGlzlz1U56o7jTGjvcExkbxX9dy8ITQMPeyjSr1MRsO9FxujPamSvbzrO7s9vaZvPcGGWDxpFge95mGQPaAEGD1hwzS9q9wTu/8E8jzHM 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 t7O8Ky6gvBTqMzyhqNu88HR0vNnZ3b3lLEu9KgJSvdcqhD2Yu/s8f0+HvaICQz2IBQm9xHEovbcygj33wHa8exiGPXbiN725uNS9BL3RPO5qOz1g6Io9fYH1u4ollbzJ/Wm9w2XWuwkXdby85ji9GB8evSVeZj1pFwq8ubMZvEcVlrscPS68Bt+dO4V9/TxQa1Y8FWoJvPj+5r3PnCG9KPggO+7YuDwyTw68bjXiPB0pH73CtB09aQo1PMaHub1/JOO89jzvvFhZAL2QliY9VBmFvTa4/jwJTFM9ODeivElI4jwN3Fw7bq0NPOHbPT2PAKW9dyezPVdw3by0O749XqBnPHLxGrvzcj89JsBLvQGxCL3yy4W9SJv5PKkTSj3JTI89r8hdPLma37oVQIk9ctARPbQIOT2a5ny7jQMJPXhwzL0NGyI9p6/2vHZbBzx9W9U8eucGvKRLBLu8cyg9+xTrOrzQkb03PyA836uKu7A9TjwkyI89SDYSvUcPbT2gpDy9c7LoM 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 PaN+fbwztDW8PeOePG0oczpEm2k8HK5rPFF8WD1E9dE8YoJQvRAV/LxQYi29EqUxPRxnAb2evls9rsH6PHn7PT3mTi086YFhPNb9Ab1aPDO9il/zvOfqPj2xzkM9+/MlvSHmgrwhLBO9lvdwvXXacTwdxkw8UvK5vOOCmjzBZwg9pUW+PNTotb3vGgC9xnPBvFhpdL1BX1w9R2jVvOH0lD3j+km9JYxZPTgIsLw4d+E8d2AaPegWIjpBMv485yjRuuBC8jy9aBk9iYwTPRX5oL1auHW9duO5PFIZjb04qHs9wQPHPElaOjy/C4c8YYGZvBaioryEcNe6KG4QvVFwzDwGhOC8B+GRO983UjycE7s7IWD3u9eUHrxCRww8CgaLPN+C8jwGlDK8kUrgvKWmt7tD/us7RZSWu0g/hzuEFeO7O+GRvO79g7vJdyC9WrUlPSAqYr0tI2M7v0SJu8Rn4rsTyBc94DsNPFjL3LwA3Vs96UGlPOYSib3Wz6+92dU3vA0aiL1JM 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 PXSsrTxRBdA8ZUInvV2w5rzZb9e808WNvGmRrzx2Hd083yf3O6fBRr2ZL3I9d8fsvEfxFLyAhmc9nSVjvSJetjx7mf+7cpVQPAoz8r2Q22y8g1Kju5pJ/jwWptk81wbCu9TRJD3lTbw8mqUPPS/ksT1H49s7WXOQPT9Ho7100xQ8/SaZvUUQRL2msEc9e6E7vVpLzDz9ZUw9Vdehu4ITjj2lD2w8hFTxPUZCxjzjQAi7hxPhvb7GRj2EJbK9h7acOuDOPDzn3io8lqrgOnEhSLyG/cG8ghCGPAYjrjxaCzc6nO6EOygbzLqcaZa8syEmPaIPC773a3S9BaGivGqw0bysdaU99BzWvPOjLL2nkC+8kU9wPTfLfj1rAAM9KhKBPWtcm71RGM279ibdvUl3ML2UF267HATtPF/LtT0ucYg9QZafPLIjAD0WI6g8dwsjPRNHJr1vVDq9AyblvWRefbvUjMG9RIO5vGEkAz2uB+s8T+vlu4mWsbwnh8Y8NLFZPFBNiT2uM 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 vEJz5D3Ca568jNqQPAJWMT0GZDg9kDEDPSGOFL18BLc9+jwDOwbu3LuzWHk9AaysvX10/DsTcac80b5BPJ2opLx4x5w8Z862vUvYJTyKAFO8wLE8PZo4Bz358ya9MGnFvLImaz3kpV+9qQdQvRxvCz3sI5M9niC8vbHcgz1+MwG90GouvZIjEz0JvVi88UMqPVTKvjxYkQi8EGjsPHndBDz2Go67ooocPd/QlDwxSUU8Y7hFPeUo7jxDGwO99BMlPb2p+DtzlmQ7zdERvUsBE71YQTQ7gkOJvBnZjzx39S88QLbpPJ9lLTz5/z69H4fFu8Tla7zVF4c9R+2SO7xsgT1OOPS8rK6rvPFOlTv3dWa9Ph4GvR/fTj2IYa49Xsatvamoaz0hT+m6EuCeu5GWirz9qSy9qVRLPTUmMbwJDEq9j7zNPHtgGb1sZZw8MMJPPboS6by4HGo8NEqZPLQKgTzEMZc8MASLPWn6r73VEi09EY7QPENHRrw0U3k9sL2KvTD3urxlM 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 PPjAvDwmv1A9ykWjPA8X0jwY85+7ZD4sPcnuvLzAWx293y4qPRAy4rxOyCw94eeMvdd2WDww9aW8hli0PGrzmLxc/Ea8+sdHvaTEOj1Q88Y9cD9suxe0AbsBk1y7SvQQvtBZ7ruDFx69VcHOvKNYprvu/y09gFsivbFOJL3Jzz69CY8bPWX+qzzxHsk6ztz8vHtIazxgire9mnBbvRhCsbzjGKY5PlyHvR70Cj29wqw7DMCNvPrelz2o4Aw7BGuUvDdUtbzkV5A8eMR1vJR4G71bFhw9/ZvivLZUM73Xt9y870WIPWxqGryckQ29mvgqvZt8xzzZysI9ydt+uxINQ71f+oo8LBbAvXN9vzzLEri883WPvL3Udj0kR2y87XaAvQHM2juahpy9vAM6vUaAVz3+XSU9QxZtPKmmPTybnca97IOxO8FYobxRf/i8qqfYvIxZA73JzXK6QL1tvZqJET2nFC48KfcCvEMLgD14qky91atcPfDtCr05x708KLd9PG9z1bwpM 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 s7U7WyccPYn3hD1iN2C9V75nu/BTU72rjgG8bAyhuwbrDrxR16K80lIlPV9ybryErge9RFqKPTv+oL2RGyE9SHPnvLUhozyu4289DpA2vBErMLyI1RM8IGmHvPQCQT2hLSO9x/iGPMeiOr19DY+9jvCxOUX3WTyRSgS8RdfIvHZdNr3B2hY98BpVvIrQ2ztqbMy89Y+PPF8haju8StM8auGpu3CGcr1d+ow8YOyxPGzsxrxNnx08VllTvEM10r1wBp+8P9bbuysWpbxRPQm97mQ7PaQ1N72F1MW86Hnlu9NdDr58zoI9k/7pOyWtOD1NU9A8INyGvU79Uz2P1uQ8Yx9tuzybeD2UdPI7UU0nPX0tJD1xJ5K9LzxVPBHMWT0QHIs9YySxPa+iUj1Ajik9hMgLPfPIID0jI5o6tJSyvMzQjrwIOhq8dDoJveb5k7wDovg8N7aTPHNlTbxJAWG8dz+YPZwxk70jnxI9FoinPE1S97tyrIk9Qt11PW0YBT02WEg8XWt9M 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 bfG8rWCkvUUUHb4ZzoE8Rj37PILSWTziG2m93D6IPX3z6zvPcas8FuuBvRK60bx13M28K/9CvLA1i7t4gKS9UtYcvhAjiz3OXMI9hQyuvMNIjTzgGbQ9xEfzuvnZpT2hNrg8Gu/SPBDETrwtqxA7Q+jovS/QC7yoyxy9u/Fnu5+hbj2cbR290D3DvIwQID3s8BI7iT2kPC9FmzzEjN881UmvvZ6ZwDqAF1i98pNcvWsVEL4AFZq7mURKPT0EIj3IhAW86l6DPU5HgD0K2zY9Ii3pvNtEA71t9bQ82EtPubnaGzw7FPi9AX/7vVnM/DwmLD09Ie9XPSbb7rzvhdc7aoxxPM8ngLzaxxe9ue33vL0dYb3XIBe9ZhVPveb3M72N6Ci9oP5BPSzGET0y2KO8bWm/vAmbOj09WsI8EF8evECnsT26N3A4Q7hhvYHO5Txmse88fC7IvbWozr099pe8lPRZPWDWCTxWZrI8bNe4vH8YfjwNBZc8VjjHvEIYpzxqVkq9S1xVM 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 iwy9blWvu8aOkj3yI9s80gSxvZ0/ST1d7UC93HFcumT3h7shG9A86M1FvWcUWryYKYO9GAA2PZzLZT2UHX095EhRPWUu9TxOx7e9eSsCPX3OT735C328yruVvEOJwT33z0280Y8sPT9qPT0FQC49HT0evYRP3Tx18aO8Ek/svJLcYD3wvle9o52cvRKl/rto25K89KOVPe9JKb3dC9i6CQ0vPUp14TykWq+9VTrVu/MqQTzQRk09EW5cvbUIZD2cYoS941lxvWylrjyEEuM7euAtvRqiGDzbHIC9QZoOvQTNpjwQ/Ya9evy1O4DzgDyy76i8hp4BPFx8p72489C8F9zMvKm54DtOSra9ahZcPYYUmT1E84c7OJUevXPB8zwkdxk9r9ZYPMKRALxQc3u9kHjxvY4q8Tu7Trq8+xqBPdvltrsTYGU9hJgbPIzikj0Jnzq9zLKgvf8tAz0+rQS9JQiFvc+qWD0dU5S9/O0hvWhSpztwFx49KaqdvdlxBr01ZD+9GYtKM 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 PbV+Zz1ocSw9qRH/veC1Lr0pfiu909GnPdGUjDwtm3a9TpjSvEd2Oj0UK0S6T9AyvPKjDTykRgo8dcl5PejBgD3sMKK9enQuPVH3WT0hL3+9louNPN8/Iz07V1Y9rR3RPIzRT76fN8G9Y6vtu9pIpj2LYEo7R3N2PbdHALxIcQy+SbGUvaS+zD2xJmQ8NeBeu0H42z0DyWs92pwkvo9/8r2dAJs92ni+vAfegjrvGA09zbIfPaxFUL5Wi0G+e36LPW6i8D0OlI88WwOPPU+8qTz5EWq+s5clvB0Dhj02Do08YG6hvRLyvD17T0W96AkFvm+8xL35Bac9S5OCPNNEpDzsmOm8Lg2GPb84ir2u1EG9Pb6kPMjYnjz+vBs9sgr+PCPoTj2smbC9irGKvV4M1719faE9Ojb7OyJ7nj0POtg8UXv7vQ1esb2lGMk8xf2YPGx1kLw4t7W5fow4Pf9WhL2p6Im9V9KzvbZL6D07i+08gskFParzST1LigO+fg8Zvb+GWjyjM L7e9TBxWvWt+aTy0YH47xyf9vdsTxr05TMO8vn9HvFcbkr3X21u+fblOPfQ32z36Zw09JLwtvWov5byyImg9Kk9Su1CdxT10SQc+q3PIPTnabL5F7de8rNykvZLj9L1WxSC88itdPGVzRL3FuT292N8BvY+xEj0hV3+9FTUcPhrYET4tQVs9J8c4vrNlL7xqiOG8OX42vWCeST0/Ajq9qEA7vCM3Nb2+JE29JcM8PSjIm72Y8WU9/iW4PcKYAT0uNui9m5L7PBDgg70Vqz29er4hvVCZ5z2hMk09IkJGvMEEBz5IAAM8o6HIvOVcML2XzPM9XL6LPZYue72w0FM9J/20vT5y/rwYU/i8fZCBvGwQH71DgHG9CS9uPasPKz1uQqS9w4RYvTFI2D26EPi7c8BdvS/qr7xx/869YaDeu19fm71bhPO8WkSlvDGZjb04YFc9NaFXvIUuNb3KNhw9pmHFPSVNG7xMNCk9wbbIPd5tk71TflO9yyPhvBPj9zyHU0G8iqAXM 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 ZkO9Kl7lPJ/ngbzBnSS9g+77PMY9nbx+CzC9rbxFPfK1jTxCqUO9B1JIvVVYnLzmjDi934z+vLSM/Dw124q8Pl/EvUTQMbyXAW29zwFvPe2sBj2Bq1a8+YOsPLIOhDyRUMm74ARrvfyLlrze6U+9XWUevXyMnT1HdD69mXmkvJkVET5yvyo9r3LXvYfzNTwNWy29hwgqvMaa6Dya+sS90NtwOBIGL7xR2jG9FbXbPFEcHLwP6VE7XYYsvPo34LuEUoi9tbzRPJwbYT1HDBc9fi+rOliTH72OhZK9siOpPCT1grySFC49im1wvTIXW71aHHQ8cXZHOrk+ILwVvs28d4UuvPRsPj1N8DU8TMJ2vdqqijsEmpc8oIxsuPHL1T1Dywo9sa7NvLJ+BT77uGs8QPmMvcINebwmpJs8Thi4vO1VwDyTGGO9RgMyvQgwID1NXZm9BbY0PkzaEz00BI082b9uPEKgWD0zXha+Jr9ivaICtD1IICg9zm5IvUZSpLseHOe9gn2fM PLfRGr0HpN89UAx3u8S6oDz8Vfe8hX+nPbkajrvPtHK9z8uqPa+zlDzLwr08Md3bvN4Jsj0YtDm9KJ+KvHo/bDx5b1i9Rr9svTt3sjxI4YC9vnQ7vQ2inTwQqb49Qxh4PfY+Jj1ByLq9Cu6nvUCHnzv2/o29livHPbthJz115rK9YEyZPd3m6zxpHhm+HeuBvfy5sz1G0IS8Uof0PCjeKL3DW/+6n1HqPFWkprv7xIw93RmQPeN0zL3cY5Q9l/Hru6WU2r3lRSa+qIU3PU2b9Txo15E8gID/PCE2YD3So0q8VvW1PWnDQr4b4ou93ukxPIlo7jsy5B29+O7EPWTKATpgWau9hHMnvohQuTwoifk8/i41vSivgjxsd9U9i7oovgUU0L2Ugtg9h+kIPQY6gL0mCFs91Hd/vc8pF745+xm+GZ3GPTVgnz3tHxe9lpMvPdG5oD348Bu+BFgNvX103DtIZ149nygvvUrQ6z2u7jW9L+QivbC+sr1ZcAw91wSJO0FRBT62M 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 UqE88KcUPedr671HKYu7Q5yGuz8KBL1C/Gw8lBaSPYDILDzI4Jk981SLPRr3EDuo2wq94XZUPZcqhz0CdvC8/Zi3PFycqbt0l4G9kSJJPSuljbxCTXa6PpW+vUzYhzyF8ps9dMg9PalXa7x+VYs8nSqLPZA6obwf7Sm8W6sevJtmoLzGkRg7f60WvQ9WS71pNWG84mEcvBeocD3mnM68thuVvd03QL18Jy895J8QPTj2lL3UmMA86GjkvGsZlTwxVrM82oS9PGNLKL1tcgI9KQtLvBIhzDzNHXK9Y2N3PCg1oj0tWK687ebeu+OwGDxFXee6sgQ4PXzuyLtm/BG8xy8hvKqKHj0AAie9lHxQPMk8Nr1XWlE9X6sfPb/JWbv10bU890qyvJ6bcD0R3kE92bX9u5HAwb2bRi89zmRjPVRBtr13mAy9+0IavQiAOT2R3IY9l1piPfJpCL3rWCU8dzh7vP/VvD2E4ls9SfuNPejwUD24WcM9rgmpvZ+ACz1M3pC9ROiiM 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 PQdzI72Bk5Q6HhJ4PURW7z2vmpA8q3/7u9GYyjuvPYq9QIljvaHx6D0K4aO9DunrPTe2Cj2TAas9L5S9vZzuir3g+245wviavU+ma71kYPe9gculPcKxpb3j5Eu9gN28PaadB74b3D49J5ZPPZK7dT2OYdK9cFUavrAPTzxhJpc9hJy2vdxuxL3oDUg9D1kEvGFwkLzOw8E9kEjXvNEABT7whA297jLbPE6yrT00+PU9g4iqPQITiD11BAE+RlcgvSq85L1Upc068knZPN6w+LxA/8o77NRBvMK41L1f7oy8Rf8cPlfftz2+7FY9ukaUvZewbj6Qt669yrdLvb7MOj4htdQ9Mkulva5cm71Sxvi8FYeTvcAEQj3Q4OE9S5HAPZB3hD2QtyQ9uO6vPZn2yr3D57G93PtYPumQwz1C8rK9Yt8rvdM0Aj5IucO7tmFvPbjP2Dzc6sA9IZ8ZPIyQXz3NKNs9rERnPYOZp70oAM68ULqDvECc+Dy5ypG9MTcivFH9Vbz0M 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 DI+9Q7epvbu4G7zGGDG9fIzHvMuO0Lojkwg9CACPPcj9lL19Mqu9PGrTPcb8Fr20iqO9oa3WPdrkHr3nrCi8Lx+4vCs9ML3ZbT8823L4vF21rTzUVpE9ueFevH1hqzwkXpM8l1GSvAWjSz2KRNc9wdLCvdMRML2byCk8XPQovTYP3b3j7pC9pHRoPWlNDT2RfqA8NlwpvbzYxz32Bp47wxp/PfkBrr3riSe+csdRvFzIgzxA4JK9AftmPYjIL71WuoM9jxxmvBaTfbuaUUK9N4u+Pev6Gj11zH69b7cHPlcbZ70B5bg8sX+DO+EB0bwV1R08uLOfvA/jAL1pRFM97PlAvbervTz8s989JBr3vVGYkb0TJzg9xKojPCPho7uarwG924pzutSoGbyeO4K9U14tvdoU3rtIoDe8HcFJPCbXFz0kJJO9bW2ePWhhaL2JwLA92QtfPLNiV71qHyc8ImYaPbn/5zxFsxc9DNKSPYL8pzsOP488qy0RPMQSgb0+9IK9inRPM vd1tvT0+KYQ9KXBLvf++obxl8Ru9B6yIPRD0/Lyb27Q9ADasupqbfz3OVpC9w1SuvZgsrL2TqgO8xLnZPBD/1jxUAEw8idQwvU10Ar17jhK828GKPClxyTtKRLC8Y2aRPXj+Ib37Fqy9Adg+PXieL70Yais7gMtwvSbpuzxSGDy9VPGXvK64eD0FTCG8HuXDPbARg70QpFC9GW8DPROfOzzWMxA85BtOPITfBj3xqdq8X2oOvaAIirwv7fm7dpjpPLGiHD3I+As+nOYsPf7PCz6PtUa9qWpiverNXr276zg8vlqjPPPslbyzqsW7RDeZPDVWJD2ckty8jjgKPek3LL2G+wq8ZPGLPKacPr2eCpg8qqGGPJI82r0brS09tQ8PPU7rOz0gJ8k8XLOfuzr08TvRqaa8aCqVu9vIabvbCsO8gGc0vbTuM7zFKQC9r9kGPOoaBz0MJSw9hFBlvW3gyryo7zw9ZCQ+PSrfgbqPpnI9J9TQvGZiczwbE729BDQovK0dvr2KM 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 PUQlhbzKrbU9rgFDPW1ddT0GBJi9H94KPSaSiL1ZfGG9LWDnPP/x5z3FR5i9t3FcPQe1aL2s1Yk9GWA0PKH5XT5VBCs9ZDnyPIVzyD1OKI89QaJOvLyqBT1FNdU9/pkxPGPmK74zKHo8xGlrPfD7QT35fI89QYz8PTHNT7wUV5k8y0IMPuGzyD10INY9bkT6vOWyOD5QFoQ9FeyvvSMjZz1LNSA9vw3buXAPRD1COVa8A6KoveaE/zz7n0s9YzgIPsgpgTw4ieS9B00nPl44yj1sOFC+qDpiPs/skTxqTYq9Bsw9vD+9Ej51Fn69i03wPAR7Kz3b7gc9qsIlvVOWKzyVf3I93e7bPaiYSzwPHbG9K1+XPSz12bzzh0Q93KyqPUTVP712yug9HLWpPGFtyT0WW4Q9DISRvaOLJD474AQ+3VyLOruOmjyocHQ9FY48vYx0+rtaqym8mMSDvcSOqj1Glb08i0sqPR2/Lj26eFy9w1QdPn6T1j0i34y9Hv8gPpvsdz2jM 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 PfpOzb2tmhE9sYK6PDCenb3IasO9vrTLPDLUebyumfa9WggcPWaKF7yNJxc811tKPS3MU71YL789oReSvdjg7Tzko5S9S/+Tvd1Gib1BBvI8rMQKPZB75b1SWvY72SGsvT9ZVz2llQE9ISy5PWNMWDwYeZC9YNOrvT3t6Tx72Ws9FYw0Pbe+oz05STS9qICPPFken7oML8C7E/fpvfLWQL3YQs69ls+Eve8Z3rwL6+C9nbbtvUftfb0sQv49wY2hPXfjhr2Y/h48dZawPCcp7TyqpmK95WSQvdgWhr3Y+5K8R+BTvQtZ6L3pEUG+Yb99PAYYAj3bcxs981sxvU7+D72Ypg28t4MzOpm3xryW3JK9tx3IPUcbkjqs6AA8A9yBvU42NDpd5nC9rDsCPo9P9TxhspW9gcIiu6+SI73f+jk9+L3Gvefdv7wVTMW8+/2+vFx49b16ko69DKzJveEKzr0Fp7U9tBZIPB8uir0od1I8e4FQPODSHD1n5Ae+d7lyvffwrDxzM 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 vBPRXDtHU+q8Wvk7uxGOHD0dtva8DDjdvWQdNz5ti/M9F2+dvdNtAD3HDjQ8NCWqvcbDET4KVfG9cTYOvkpXD74BMwi9j6DOvHgJED50i0W+fz80PiyMvT2NGGO9qZs/PWbTp7w+jwa+b0EIPifJGL4n/Ra+VJiSPUJpbLw9M3M9Yc+MPeEYw70w8UE91+dWPY1tQL1tnI49n1TlO49EJr7P9ac9uSVyvRHPC77gtDe8jqnnPQYYNz1n/O48MgadPBpaKz4jjoG9CEKrPJPazryf6w09xLWxvW2v3D0N43Q8ZZ1GvTHreLwyYG85rwCwPZMc0ryQmEY9AQmyPSf9J71ylmK9PgMeveaSuj2/xII89I3hvIQ00zrCPeM6KcxwPcJ0yz01qVk9/na+vSj1Iz2LFIQ9/oqHu7eJqTx2CQq9yT5kPY04pjySHza84znbO0drvj3QCd07j2hEPviQnj396WG99FBRPdXzEj5T08693ciYPH8GxT2oOGM9PjEaPK8wRjzuM 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 vFC/Wz0IU9m9qmaJvdWUYD16tdO9c7sNvs4m2Ltjsi+8tHMvPQYd0zxf4Yu91aRAPXWrn7xdTpW9cDuXPdYy2b1j7m69OTitPR38Gb08EHe98G7PPOldeTyYWVe8yDN9PV1nn72JZVu7m5NOPT44g73X24s9bgOwvY1JlLyD92M9yficvQeV2b326xA9F8bxvPvy/Lz4vUk9SI/PPaHqkr0CqEE9kUHvPO2QMr34Ym69CXWyPWX18T0jqL48iBAOPYg/Cb5WSzS9p9ubvSqOjztHpqw9NZZMveW/Qb30Hss7xewMvVRYJTy3Qlk9Q8SMO6H47Ly3MWS8quTdva30kDseElm9EKYivY8QlD3c3CC9tVM2PWbD+LyhvsA8JhepPOw/vjzy7GY9vRSlPQY9mD2H8Nm9ApxLPQMu6TnvuBo85POuPVlulrw5f6W9Wml6PASCKTu/57E9ph6OPdRbXz15g4W8SPqVvGNHgL3v19+8eiKyvKFewr0lIlg+WKygvROFx737M 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 fQQ9Ek8kPY1D170BJn69yzjAvbSk3L00iao9nYvMurcTG76gAyA9qyA0PoVx0j0m1IY9AWzXPbhQjj3nX7S9EIpxvHAi3j2Gn4M9zdWYvMRtLD1R0Sk+SynfOnekdL3rJW68v7WJPZ1Olb1CwIM9riIrPWmnlb08wmK9PBtwvPgRrbyUq7O9pP0xPG4hCD1HRgu+kL/4PYttmT3/QrE9GYYfvbQKmz0G/+u8u+e2vKIpX72qQ5+7si1yPAtaHLxMDoM8jSLVOz0cyr2aG6K9FqoqPuBElT0dmrS9F32MPTHAaj0obFu9ffrlvM6Pmj0PBei71qi9vSdobjzRD8A9vQSivSdFdztJmRa9r5NRPTO1bL3nmmi7pGw/vVo2RT0bovK60X4VvAtqjrxlbQ69t/3TO1oY2byy68m91k86PcfVALzBVOk83gyQPFShJTuOK6O9ZBTDvC/W3LvTOcO8+3dGPMp0pb1Tlag9ar+wvNY6q73+kg29za8jPqoAsztQmw+92IOYM 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 F209ljO/PCBFFT2Vt9E8G+d4vffMrz6Z3QA+oEbGuvxRJTyKy1I8xyMYvkqKFT4faYG9FZGevc23KL7OoTG+JbO0vVnMcj5wHTy+48NoPk+bKD7BtGY9I96qvXq6wzhyLo+933TxPTJcsr0iDAe+PiyhPSzKEr647zy9AkUXPkPxFL5gZCA+7U0CPT0pYj1YZ+S7eVc0PFdx1r1mBVk9VmXBvHMa1b1Afb28tu1/PWwWAD26Hww9ogtDvDqtrT40qkU9nR7RvVLHkjwvvvS7DouhvQqbrz3Hmx29xBJ0vXS2Bb4vnyK+f71RvR3eQj5Yz/O9jJRpPm9RAT4juNa7odGRO92ox71wqhS+UOQAPX4gx7zIbOC9DRzrPbmB77zylPU87uQbPmwaor19Kyg+0qDqvO/4gjzwHai6g14OvSmnU70jCx48PPjyPEHKKr5aIAE6eXb0PWbGcT3MR8E9kTs5vWTEgD5QeYQ8pp1BO3CeSLyaal09RHMOvq93Qj0x5Zk8OnE7M 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 yHM9d02tPW6xPTz4Ja89bf15PTX1h7wMkN68LLiWvWyeyTwoW268ZQocPaGx7bz9YB6+a5c9PI41mz3VB0m8Qn2eO/81NzyuE009aq3TvNGNbLn8M0y+8fCHPbUqyL2TUX+71SmEvSh7Prw+TWk9gH+KPdemaD3TDBi9ZmflvBesVz2vJ6w9OI0sPVW7Vr5FlY+8KvjgPMxFKr07xfC9dArVvZ91UrxECR8+iPASvNFj0rqSve88ZfehvLcbCT2bKe06DfMQvjSBQr1ewFA9Vq8wvQRdozyzDeu9OkR7PaC2DD4MdLS8ca+rvP0Y3jzhKpg8O48gPSdIYj36Aja+TqfMPXl79rz3f6m8YRqxvHOgiLx5Ci680I4UPnX+Kr00pF29GjUrPbZGpDxCbC09rJE7vdkBrr1tTKu9TtLhvFZVOb24wBK+XMObvR6FnL1uZVs+g4+Fve6e0L3cMqg8G8+SvDzZUj3pcMG8RyawvTOj5b07xZa89vK6vRBWBr5Jgje+RZKoM PfDFKj4Ze7e9AFuFvWOqkj34dSY9KukePHk4kTzkaZK9gQTYPM13Zbzg/Pa8ZGiivOZNqz0xc/Q9McvOPYaSSr25lqm9sN1wPO7tIb1JwlQ9BRFlu3AFQL3luBS+xpeRvZ1YIrxZztK9V5lfPXAmpLsLo/c9vMGVvd63grytIfk9G9gXvVd4tz2HvQW92ocavn1qjr0hcFa9+bF2PfRobr1DJTS9gkgtuly5Ej3Lxpu9EsJ0u7Qkhj226Za8eC5LPRa5kz0aqAy++f4XvTbt3L30P8a8gAeUPHCxET7xLZu8KrTVvDJTfL1rN0+9MoJMPY8JkDtIRY681Bo/vXALjL3ZSPm8IQ1AvDfh6jsbp029DyV4PThogj1/VhY6yLeJvEyEFz261tc8OMufvSO3qzvFJou9j0IavSstrL2ORNW8V0zbPDFcrrvJbaK98xtePewUSz2hAte8w7t8PPED+btrjL+8bbjAvBbGW70a06m8gGISO5PVqjxVO4I7M3mdPa6fdjyAM 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 PVuUpj1UYTs9PRZbveCOHLyuAfO7/t+EPTrT5zwzSck77rpyuw0k6bsdWDa9bD7gO+qTNL2UQ548+t7zu3oc7TxzjyC7m0HnvGSA+TwjkqY9eGGtvB30Xz21VpS9Iw82PFBvg73MzqI9LCu5uwi3dDw+Q4I9h4YtPIOZ6rwJRwq9V/SAPav+9zsHhH69EIgNPQSYBz03PFK9/Y1VPTWTkzxKUao9SJLCPE4LJT3EiKY8z9OzPB0l7bxEcTo8L8i+O7DuBL0+rIu9H4mCvPgXUj2VFLS9YFhCvFgxtjtoAsc8mDXoO10Z67wfMBy90h7qPKf5RrwJv/g8pj6bPO1cmzyohyO79TYxvGuZWb3YM3C9+O+ZPSibYzzQseW7gjy6PI8xwL18H9e817WfvDy/gD24/fY8GnmGPG9Uer25kwS9AppbPTX7kL1udyQ96w10Oo3OVj153Ds9IHTnO61jljxU66a8cKlgOPQmeT3xhEI8nIz1vOT4zjueYnu98hWmvGTqYT10M 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 mB6+c3OjPKfSdzzNGZe8+k7bvJoGqDweWQY9LFMdvaRYwj1lfE09bFqFvOKPYz321929lyc5vNvrEL7hG9o8k210PGbtkjz5Dym7+2BIPXxiQL1Xs+c81DwoPScSAL2SaE+71W6FPRUtob213Ci8U5tlvQracb0qQ6I8h9UgPZSM7ju2IVQ8Kmcsvc7wG73bHge8UipSPTdlxbyjWKO8KUyuvbJECj1iY8G9qdOuu5IDLb0FjZI8pOilPEIqeDzwwJa9eJIcvXLcjj2s+HI9zcJzvOYBpT0v/xu+uRojPe47I74WDXI85mP2vHrLgDuu1ms8ddRJPaVKkr2Em0g9Y/dHu7IBiTyzESy9zMy9PQSXS73keLM9Tr5rvIAMwjxUA3a8rbBbvfdIC73UX/A7S7cXvMMiRjwKBHo9HV+/PSYrurx0tHG8W0e/vYKVXLvgfdC9S3N9PdvH+jzUpIO8wJIzvZG+SD3R+4y9P0SpPFsMVj1uALE9BYKhvflyjz3ioOO9L7YlM 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 vCF87T3igrm9sShyvcvpKDxzYJ09yAfRu/9dBT3kYxg9lxzfO2uv37sBA2q9etQEvbbYHD1pjK88aUGoPAivcLx3vrC9pODSPZ1qN73gLVM8bRlXPJyIZjuFe468RK2DPWr22jwx1ny9a6XoPOy3mTtANCy9zW3zvHrlg7usVZG9CguWPHeO1zxxkUA9ccgVPKz5qzyZZSM83YWbPG44ATwiCpc8883KulKLjT3S7Yq8GJq/vAIfdbw4Phw9P0kpvbVw/zyLRv27UaocO+90yb2XyGG9ys6CvSy3Kz1VsxU7qAk7Pf5fmrwvv0C9IlHzPQIVD71KmyI92hRnvdyTzbx6+Kg7zQPVPOFbbb16SPO9bQ6VPDy+tTy7RVG9UEWeuUmmtrx+6I+91aRcPQ4f8Txgang8gL4ivCWRM7y0EYQ9ema3PBuBPb2HODe8+zsTvSYDOj1KrN88OEkzvWqqSb1mZPu5xwqovIzXk7ws9jy9/d8VPQkVhr1mC2K6J5CLvfMk1Dy9M 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 0YM9wlGGvNQ7Dz1Wn8k8WwOtvXDPPrpRkQ08uDs+PKDfjjt+Ibs4alPBOjUIrTxqG4s7l3YPPmzKBD2zN3m7+/zyOijvAr0v5ZC9/DmCOqcWoL0hwx478Dy0PKQ0pTsCFIq9pvWYPawsHD2ieJW7X1l0PQ+UXL3J+gs9VJv1OwI+g72JYk+8U+KDvZd6y7qx84k9tOz2POOf77yf9xG9HUj4u1IegjuEmGG8qgwuvbvthr0fu0a9otozvTHph732L9o7IcZGO2vBm7wrQZ+8t2NMPNXwXT1/ebE8SGacPfPMBjttdZw8qoURvS5lIDxjV269D6KCvOIfM70iwzO9JDoZPaT/gr3/TJ+7KqJtPbQf+TwHfJS8yof2uffU5rzhGm08zj5SvH46OjxbOI69jukfPBncGT39U2w99cy9u8x0yrzxBP68sfYiPSg+Or2BVGM9JbpyvcFpN72LRCQ9xMHyvO5c8rzKzS84xnfCO6oY+jzRDt+86L2xPc4f6LsTrHU9KnIgM PFkEfL1ItV+8c/ptvTrSKLyz+888blrfvB9fLr0g1MO8PKOCPVM09zyOJbO7ZWEUvWayiT3sB1W94fpIPXHgIr3fcne9kHIAvTy/Lr2JPBa9za+EPABKIjxEj6M9ZiBwvQ6U3bxkjBi9YRmLPag7/r1ByxQ9WIBGvUD04TyZRQm9MRxrvMAn7by3AAs89qvGvAuI/7yrDao8xjEKPQ/2Hr1eNCk9oMv/PGVhSL3wPFG7bVmNPLn5OTySbG+9ByK8vaeddj1fPFe7x1uiPZmwJD3vDtW6caZ9vN097DzDz6y9cgbEPAAll70meRA9oGhSvBAGWzy8qZq9dppFvVJjn7ynzds9jPsBOlmCoD0DhgS+iclUvGwOW71Alwa9Ww9fvYLwnzzjug89TEkZPPsehLzsuRc9OAXGOz9YMTwxaow7kZK/PcN7ID00WbM9f+lKvDZhOzpYsNW9YX8AvRYlVT1gCLG78pOsPD0ZvLy66Bw9eamsPbELrjxRzZm8rKjnu44Cgzy5M 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 Ssg++5gFvqp2BT30XIq+KIe0PoHUnr22bMI+Lj77PRJanb5sBFA+QnTRvZR4HT/fGIA9Q0nrPAOKDj416Jw+d2n1vil2Xj5Jpq4+1MKfvMC0Mj41zwi/t/DevmCY0T34Bq++4dQlvhWkcj1aQaM+eOXvPvbtCr/v2As+PE/bPsTFtb78mBQ95PVTPVED4T4p5is+PFNavQR+373XrRQ+Co/Nvq0N074tpi271ssUPpHxcz5Vqcw9f2WGPoQ0Qr2KzNk+nJHivGCQ773Aglu87oMnvo9DMz6DZZI+msyEvr58bT6qYLW+DZNzPit0+r6Xgjo+KZfWPjE75z4nNX8+CccKvvJm3z4+o5m+LNtQvoZc3701j9K+gyV+PtKklz6Gk6U9v4e8vSxzyr6WMO49aaxqvuAB473L5Xo+QjOKPilTkT5IVs69qYJXPUwwQT1Bgto+TaqaPlLVpj7Q8wQ/Xa60vivRczyVKE6+hLyLPmMaxr5aRIe+OQ2Lvjteoz7Eeac9wLHDM 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 yG++OPiLPp8gtb5bE8+9b+HTvmsA9D6QTiw9dS7KPgGwPr3Xq+C7o8OyvYUSKb5qEki+EtJfvrUhkr6Pw2e/qONAvxfDvT1Ss8w+edmNviFfyL1pgc8+OsdDv9K2lz69FUK+mC+IvIhEMD9ftfE+Pt1hv7NSJr1Fv+e+667tPiC/ob4amo++YtQev6kWyj4NdGo/KPNjvy2nwr7gHyo/9uB2v5oZeL8ZIKA9/c0hv+3EJz5Qlss+gMGrPO8wW77FiCq+", "training_traits": {"structure_gen": "Random", "n_layers": 3, "max_nodes": 19, "activation_func": "ReLU", "epoch_num": 5}, "classes_name": ["Cryptoadz", "Cryptopunks", "Moonbirds", "Nouns"]},m=25,b=50,y=59+11/12,w=59+11.5/12,v=60;function z(e,t){const n=MatM h.log(1-t)/Math.log(1-e);return e=>1-Math.pow(1-e,n)}class V{constructor(e,t,n){const{model:r,inputDim:i}=j(t,n);this.model=r,this.inputDim=i,this.iteration=0,this.stage=0;const o=new Date(parseInt(e.birthYear),0,1).getTime(),a=new Date(parseInt(e.birthYear)+1,0,1).getTime();this.birthDate=new Date(Math.floor((o+a)/2));const l=zr.filter((t=>t[0]==e.lifeCycle))[0][2];this.growSpeed=365/l,this.cycleLength=60*l*24*3600*1e3,this.growthFunc=z(.4,.8)}updateAge(e){const t=(e.getTime()-this.birthDate.getTime())/31536e6*thiM s.growSpeed;this.iteration=Math.floor(t/60);const n=t-60*this.iteration;let r;this.age=n;let i,o=0;if(n<25){let e=map(n,0,25,0,1);o=this.growthFunc(e),r=(25-n)/60,this.stage=1,this.stageRatio=map(n,0,25,0,1)}else n<50?(o=1,r=(50-n)/60,this.stage=2,this.stageRatio=map(n,25,50,0,1)):n<y?(o=map(n,50,y,1,0),r=(y-n)/60,this.stage=3,this.stageRatio=map(n,50,y,0,1)):n<w?(o=0,r=(w-n)/60,this.stage=4,this.stageRatio=map(n,y,w,0,1)):n<60&&(o=0,r=(60-n)/60,this.stage=5,this.stageRatio=map(n,w,60,0,1));n<50?i=map(n,0,50,0,780/M 880):n<w?i=map(n,50,w,780/880,800/880):n<60&&(i=map(n,w,60,800/880,1)),this.nextStateTimestamp=Math.round(e.getTime()+this.cycleLength*r),this.statePercentage=round(100*i);let a=(25-n)/60;a<0&&(a+=1),this.nextStableTimestamp=Math.round(e.getTime()+this.cycleLength*a),this.growth=o,this.model.updateNeurons(o,this.iteration)}getBrainStatus(){return{totalNeurons:this.model.getTotalNeurons(),neuronsLife:this.model.getNeuronsLife(),stage:this.stage,inputDim:this.inputDim,stageRatio:this.stageRatio,age:this.age,growth:thM is.growth,nextStateTimestamp:this.nextStateTimestamp,nextStableTimestamp:this.nextStableTimestamp,rebirthCount:max(this.iteration,0),statePercentage:this.statePercentage}}classifyImage(e){const t=new G(e,1,e.length);return this.model.forward(t).mat[0]}}class M{constructor(e,t,n,r,i){this.p=e,this.v=t,this.size=n,this.shape=i,this.col=r}getRadius(){return 1==Oe?1*this.size/2:2==Oe?7*this.size/16:3==Oe||4==Oe?4*this.size/7:0}update(){this.p.add(this.v)}draw(e,t,n,r){const i=this.p.x*r,o=this.p.y*r,a=this.size*r,{col:M l,shape:s}=this;let h,c;1==n?h=c=l:2==n?(h=dr(t,1),c=l):(h=dr(t,0),c=dr(l,1));e.stroke(dr(c,map(1,0,1,.25,1))),e.fill(dr(h,map(1,0,1,.15,1))),3==n&&e.fill(dr(h,0)),1==s?e.ellipse(i,o,a,a):2==s?e.rect(i,o,7*a/8,7*a/8):3==s&&(e.beginShape(),e.vertex(i-4*a/7,o),e.vertex(i,o-4*a/7),e.vertex(i+4*a/7,o),e.vertex(i,o+4*a/7),e.endShape(CLOSE))}}class E{constructor(e,t,n,r,i,o,a){this.center=e,this.len=t,this.angle=n,this.v=r,this.angV=i,this.c1=o,this.c2=a}getEndpoints(){const e=createVector(this.len/2*cos(this.angle),thisM .len/2*sin(this.angle));return[Vector.add(this.center,e),Vector.sub(this.center,e)]}update(){this.center.add(this.v),this.angle+=this.angV}draw(e,t){const[n,r]=this.getEndpoints(),i=n.x*t,o=n.y*t,a=r.x*t,l=r.y*t,s=this.c1,h=this.c2;var c=e.drawingContext.createLinearGradient(i,o,a,l);c.addColorStop(0,s),c.addColorStop(1,h),e.drawingContext.strokeStyle=c,e.drawingContext.globalAlpha=1,e.line(i,o,a,l),e.drawingContext.globalAlpha=1}}function S(e,t){const n=random(TAU),r=random(e,t);return createVector(r*cos(n),r*sin(M n))}class R{constructor(e,t,n,r,i){this.wall=n,this.maxR=i;const o=t.length;this.nodes=[];for(let a=0;a<o;++a){const o=[],l=.25*t[a];for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),l=S(.02*i,.05*i),s=random(10,25)*i;o.push(new M(t,l,s,e[a],r))}this.nodes.push(o)}const a=A(e);a.unshift(e[0]),a.push(e[e.length-1]),this.lines=[];for(let e=0;e<=o;++e){const r=[],l=(0==e?1:t[e-1])*(e==o?1:t[e])*1.5;for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTM op,n.yBottom)),o=random(5*i,10*i),l=random(TAU),s=S(.02*i,.05*i),h=random(2e-4,.001);r.push(new E(t,o,l,s,h,a[e],a[e+1]))}this.lines.push(r)}}reflectNode(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,{p:o,v:a}=e,l=e.getRadius();(o.x-l<t&&a.x<0||o.x+l>r&&a.x>0)&&(a.x=-a.x),(o.y-l<n&&a.y<0||o.y+l>i&&a.y>0)&&(a.y=-a.y)}reflectLine(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,[o,a]=e.getEndpoints(),l=e.v;(min(o.x,a.x)<t&&l.x<0||max(o.x,a.x)>r&&l.x>0)&&(l.x=-l.x),(min(o.y,a.y)<n&&l.y<0||max(o.y,a.y)>i&&M l.y>0)&&(l.y=-l.y)}update(){for(const e of this.lines)for(const t of e)t.update(),this.reflectLine(t);for(const e of this.nodes)for(const t of e)t.update(),this.reflectNode(t)}draw(e,t,n,r,i){const o=i/this.maxR;for(const t of this.lines){const n=t.length*r;for(let r=0;r<n;++r)t[r].draw(e,o)}for(const i of this.nodes){const a=i.length*r;for(let r=0;r<a;++r)i[r].draw(e,t,n,o)}}}function I(e,t){re(e),e.fill(0),e.rect(0,0,500,500),ie(e),e.noStroke(),e.fill(dr(cr("#000000"),.5)),e.push(),e.translate(250,250),e.scale(t)M ,e.translate(-250,-250),e.beginShape(),e.vertex(235.2,24.9),e.bezierVertex(215,24.6,185,11.4,164.8,11),e.bezierVertex(147.2,10.7,129.3,10.4,112.2,14.7),e.bezierVertex(95.1,19,78.5,28.5,69.6,43.8),e.bezierVertex(57.699,64.199,61.599,90.199,70.199,112.2),e.bezierVertex(78.799,134.2,91.6,154.6,97.199,177.5),e.bezierVertex(102.499,199.2,100.899,222.5,92.799,243.2),e.bezierVertex(83,268,64.6,288.3,48.9,310),e.bezierVertex(33.2,331.7,24.5,337.5,26.599,364.1),e.bezierVertex(28.2,384.1,61.399,404.2,75.7,418.3),e.bezierVertM ex(90,432.4,73.7,488.2,91.9,496.7),e.bezierVertex(124.2,511.6,159,472.5,194.3,468.1),e.bezierVertex(211.6,465.9,267.4,501.5,283.9,495.9),e.bezierVertex(340.7,476.7,298.599,428.9,355.4,409.7),e.bezierVertex(370.799,404.5,454.5,407.6,464.4,394.8),e.bezierVertex(478.599,376.3,474.7,349.3,464.299,328.4),e.bezierVertex(453.9,307.5,438.099,289.5,428.699,268.2),e.bezierVertex(412,230,419,182.6,446.1,150.9),e.bezierVertex(449.7,146.7,453.6,142.7,455.8,137.6),e.bezierVertex(459.4,129.299,457.5,119.6,454.8,111),e.bezierVerteM x(443.2,73.4,417.3,40.4,383.6,20.299),e.bezierVertex(358.1,5,343.2,-.4,313.5,0),e.bezierVertex(287.5,.4,261.6,25.4,235.2,24.9),e.endShape(),e.pop()}function C(e,t,n,r,i,o){let a,l,s;re(t),t.fill(0),t.rect(0,0,500,500),ie(t),t.noStroke(),t.fill(dr(n,.5)),1==i?(l=0,s=25,a=map(o,0,25,500,0)):a=0,t.rect(0,a,500,500),e.noStroke(),e.fill(r),e.rect(0,0,500,500),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,4M 53.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,19M 7.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,2M 1.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertexM (475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),e.fill(n),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertexM (119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100M .4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2M ,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),re(e),e.fill(r),e.beginShape(),e.vertex(184.3,473.2),e.bezierVertex(164,473.2,144.7,462.099,134,444.3),e.bezierVertex(131.7,440.5,129.1,438.5,125M ,437.1),e.bezierVertex(97.3,428.1,80.5,400.6,85.2,371.8),e.bezierVertex(86.3,365.1,85.8,364.1,79.9,361.2),e.bezierVertex(57.2,349.8,46.2,323.3,54.3,299.7),e.bezierVertex(54.7,298.599,55.1,297.7,55.5,296.9),e.bezierVertex(55.6,296.599,55.8,296.4,55.9,296.099),e.vertex(57.9,291.499),e.vertex(62.5,293.599),e.bezierVertex(64.9,294.7,67.3,295.799,69.5,296.9),e.bezierVertex(74.5,299.299,79.1,301.599,83.9,303.099),e.bezierVertex(89.8,304.9,96.5,305.499,102.7,305.9),e.bezierVertex(102.8,305.9,102.9,305.9,103,305.9),e.bezieM rVertex(106.6,305.9,108.9,302.799,109,299.799),e.bezierVertex(109.1,296.199,106.6,293.4,102.7,292.799),e.bezierVertex(101.3,292.599,99.9,292.4,98.4,292.299),e.bezierVertex(94.3,291.799,90.1,291.299,86,289.9),e.bezierVertex(68.9,284,56.5,270.2,52.7,252.799),e.bezierVertex(48.9,235.499,54.5,217.7,67.6,205.299),e.bezierVertex(71.9,201.299,72.7,198.1,70.8,192.399),e.bezierVertex(64.2,172.2,68.8,153.99,84.2,139.599),e.bezierVertex(94.2,130.199,105.5,125.399,117.8,125.399),e.bezierVertex(124.3,125.399,131.1,126.799,137.8M ,129.599),e.bezierVertex(157,137.399,167.9,152.799,169.4,173.99),e.vertex(169.4,174.399),e.bezierVertex(169.5,175.899,169.6,177.2,169.9,178.299),e.bezierVertex(170.7,181.2,173.2,183.2,176.1,183.2),e.bezierVertex(176.299,183.2,176.5,183.2,176.7,183.2),e.bezierVertex(180.1,182.899,182.6,180.299,182.7,177),e.bezierVertex(183.1,162,178.299,148.2,168.399,136.1),e.bezierVertex(158.2,123.5,144.899,115.8,128.799,113.199),e.bezierVertex(123.499,112.299,120.399,109.799,118.899,104.99),e.bezierVertex(113.899,89.699,120.699,72M .299,134.899,64.499),e.bezierVertex(139.99,61.699,145.799,60.199,151.7,60.199),e.bezierVertex(162.2,60.199,171.899,64.799,178.1,72.699),e.bezierVertex(179.6,74.6,180.799,76.6,181.9,78.499),e.vertex(182.2,79.099),e.bezierVertex(183.2,80.699,185.2,83.299,188.4,83.299),e.bezierVertex(189.5,83.299,190.6,82.99,191.7,82.399),e.bezierVertex(195.1,80.599,196,76.99,194,72.799),e.bezierVertex(190.1,64.799,184.1,58.499,175.6,53.299),e.bezierVertex(174.6,52.699,173.7,52.099,172.5,51.499),e.vertex(170.5,50.299),e.vertex(163,45.M 899),e.vertex(170.5,41.599),e.bezierVertex(182,34.99,193.1,30.799,204.4,28.599),e.bezierVertex(208.6,27.799,212.9,27.399,217.2,27.399),e.bezierVertex(217.6,27.399,217.9,27.399,218.3,27.399),e.bezierVertex(231.4,27.599,242.7,38.199,243,50.599),e.bezierVertex(243.4,64.899,243.3,78.99,243.2,93.799),e.bezierVertex(243.2,99.799,243.1,105.899,243.1,112.099),e.vertex(243.1,119.199),e.vertex(236.4,116.799),e.bezierVertex(235.7,116.499,235,116.299,234.4,115.99),e.bezierVertex(233.4,115.599,232.6,115.299,232,115.199),e.bezieM rVertex(230.6,114.899,229.2,114.599,227.8,114.299),e.bezierVertex(223.8,113.499,220.1,112.699,216.4,112.499),e.vertex(216.2,112.499),e.bezierVertex(212.5,112.499,210.7,115.599,210.6,118.599),e.bezierVertex(210.4,122.399,212.7,125.099,216.4,125.399),e.bezierVertex(230.1,126.399,238.9,133.099,242.3,145.199),e.bezierVertex(243.2,148.399,243.2,151.599,243.2,154.499),e.vertex(243.2,155.099),e.bezierVertex(243.2,254.199,243.2,330,243.2,400.599),e.bezierVertex(243.2,401.99,243.2,403.4,243.2,404.9),e.bezierVertex(243.3,411M .099,243.3,417.599,242.3,423.9),e.bezierVertex(238.1,449.2,219.6,467.799,194,472.5),e.bezierVertex(190.9,472.9,187.6,473.2,184.3,473.2),e.endShape(),e.beginShape(),e.vertex(315.8,473.1),e.bezierVertex(309.3,473.1,302.8,472,296.5,469.9),e.bezierVertex(270.4,461,253.8,434.9,257.1,407.9),e.bezierVertex(260,384,273.8,366.8,297,358.3),e.bezierVertex(297.7,358.1,298.3,357.8,299,357.6),e.bezierVertex(299.8,357.3,300.6,357.1,301.2,356.8),e.bezierVertex(304.3,355.4,306,351.8,304.9,348.7),e.bezierVertex(304,345.9,301.7,344.2M ,299,344.2),e.bezierVertex(298.6,344.2,298.1,344.2,297.6,344.3),e.bezierVertex(288.1,346.3,279,350.9,269.7,358.3),e.bezierVertex(268.9,358.9,268.1,359.6,267.2,360.4),e.vertex(265.5,361.8),e.vertex(258.5,367.6),e.vertex(257.4,358.6),e.bezierVertex(257.3,358,257.3,357.5,257.2,357.1),e.bezierVertex(257,356,256.9,354.9,256.9,353.7),e.bezierVertex(256.9,334.8,256.9,316,256.9,297.1),e.bezierVertex(256.9,260.3,256.9,222.3,256.8,185),e.bezierVertex(256.8,170.7,268.3,158.8,282.5,158.4),e.bezierVertex(284.8,158.3,286.7,157.6M ,287.9,156.2),e.bezierVertex(289.099,154.9,289.599,153.2,289.5,151.3),e.bezierVertex(289.3,147.5,286.7,145.1,282.7,145.1),e.bezierVertex(282.5,145.1,282.2,145.1,282,145.1),e.bezierVertex(278.8,145.3,275.5,146.1,272,146.9),e.bezierVertex(270.9,147.2,269.8,147.4,268.6,147.7),e.bezierVertex(267.9,147.9,267,148.2,265.8,148.7),e.bezierVertex(265.1,149,264.4,149.3,263.5,149.6),e.vertex(256.8,152),e.vertex(256.8,114.6),e.bezierVertex(256.8,95,256.8,75.4,256.8,55.9),e.bezierVertex(256.8,38,267.2,27.3,284.6,27.3),e.bezierVeM rtex(285.3,27.3,285.9,27.3,286.6,27.3),e.bezierVertex(299,27.9,318.7,34.5,329.6,41.9),e.vertex(336.1,46.3),e.vertex(324.4,53.3),e.bezierVertex(316.2,58.2,310.2,64.6,306,72.9),e.bezierVertex(304.2,76.4,305.1,78.5,306.1,80),e.bezierVertex(307.4,81.9,309.4,83,311.6,83),e.bezierVertex(313.7,83,315.7,81.9,317.1,80.1),e.bezierVertex(317.4,79.7,317.8,79,318.1,78.4),e.bezierVertex(318.4,77.9,318.7,77.3,319,76.8),e.bezierVertex(325.3,66.2,336.3,59.9,348.5,59.9),e.bezierVertex(353.2,59.9,357.8,60.8,362.1,62.7),e.bezierVertexM (377.6,69.3,386,86.7,381.7,103.2),e.bezierVertex(380.7,107.1,378.5,111.8,371.1,113.1),e.bezierVertex(342.7,118.1,322.2,139.1,317.8,167.8),e.bezierVertex(317.4,170.3,317.3,173.2,317.4,176.5),e.bezierVertex(317.5,180,320.1,182.8,323.5,183),e.bezierVertex(323.6,183,323.8,183,323.9,183),e.bezierVertex(327.1,183,329.8,180.6,330.3,177.2),e.bezierVertex(330.6,175.7,330.7,174,330.9,172.3),e.bezierVertex(331.1,169.8,331.4,167.3,332,164.7),e.bezierVertex(337.3,141.9,357.7,125.4,380.7,125.4),e.bezierVertex(382.5,125.4,384.3,1M 25.5,386.1,125.7),e.bezierVertex(412.8,128.9,432.6,150.9,432,176.9),e.bezierVertex(431.9,182.3,430.9,187.7,429.1,192.7),e.bezierVertex(427.2,197.9,428,201,432.3,205),e.bezierVertex(446.8,218.7,451.8,236,446.6,255),e.bezierVertex(441.4,274,428.3,286.5,408.7,291.3),e.bezierVertex(406.1,291.9,403.6,292.1,401.1,292.3),e.bezierVertex(400,292.4,398.9,292.5,397.9,292.6),e.bezierVertex(393.6,293.1,390.9,295.7,391,299.5),e.bezierVertex(391.1,303.4,394,305.8,398.5,305.8),e.bezierVertex(409.9,305.8,420.8,302.6,431.1,296.4),e.M bezierVertex(431.8,296,432.5,295.5,433.2,295.1),e.bezierVertex(433.8,294.7,434.5,294.3,435.2,293.9),e.bezierVertex(436,293.4,436.6,293.2,437.2,293.1),e.bezierVertex(437.4,293,437.7,292.9,438.1,292.8),e.vertex(442.5,291.4),e.vertex(444.2,295.7),e.bezierVertex(450.9,312.4,449.5,328.4,440,343.4),e.bezierVertex(435.3,350.8,428.7,356.7,420.2,361.1),e.bezierVertex(414.3,364.1,413.7,365.2,414.8,371.7),e.bezierVertex(419.5,400.2,403,427.6,375.6,436.9),e.bezierVertex(371,438.5,368.3,440.7,365.8,444.7),e.bezierVertex(355.2,4M 62.5,336.4,473.1,315.8,473.1),e.bezierVertex(315.8,473.1,315.8,473.1,315.8,473.1),e.endShape(),ie(e),e.fill(n),e.beginShape(),e.vertex(120.2,279.9),e.bezierVertex(117.9,279.9,112.4,279.299,112.2,273.599),e.bezierVertex(112,267.7,117.4,266.7,119.7,266.599),e.bezierVertex(133.1,265.799,143.1,259.499,149.3,247.899),e.bezierVertex(149.6,247.299,150.1,246.399,150.3,245.399),e.bezierVertex(150.6,244.299,150.5,243.299,150.5,242.7),e.bezierVertex(150.5,242.6,150.5,242.5,150.5,242.299),e.vertex(150.3,238.799),e.vertex(141.1M ,235.99),e.bezierVertex(114.6,227.799,95.6,202.499,95.9,175.799),e.bezierVertex(95.9,173.99,96.4,168.199,102.2,168.199),e.bezierVertex(102.6,168.199,103,168.199,103.4,168.299),e.bezierVertex(104.8,168.499,108.2,168.899,109.2,175.599),e.bezierVertex(109.3,176.599,109.5,177.599,109.6,178.499),e.bezierVertex(110.4,184.199,111.3,189.99,113.7,195.499),e.bezierVertex(121.9,213.99,139.5,225.499,159.7,225.499),e.bezierVertex(172.1,225.499,184.1,220.899,193.5,212.599),e.bezierVertex(194,212.199,194.4,211.799,194.8,211.399),M e.bezierVertex(195.1,211.099,195.5,210.799,195.8,210.399),e.bezierVertex(197.4,208.99,199.2,208.2,200.9,208.2),e.bezierVertex(202.5,208.2,204,208.899,205.3,210.1),e.bezierVertex(208,212.9,207.9,216.9,205,219.9),e.bezierVertex(196.5,228.6,186.3,234.3,174.7,236.8),e.bezierVertex(168.799,238.1,165.6,241,163.899,246.7),e.bezierVertex(158.3,265.9,139.9,279.7,120.2,279.9),e.vertex(120.2,279.9),e.endShape(),e.beginShape(),e.vertex(187.2,427.5),e.bezierVertex(183.799,427.5,181.299,425.3,180.799,422),e.bezierVertex(180.6,42M 0.8,180.499,419.5,180.399,418.1),e.bezierVertex(180.299,417,180.2,415.8,180.099,414.7),e.bezierVertex(177.199,390.5,156.699,371.3,132.399,370.2),e.bezierVertex(131.99,370.2,131.499,370.2,131.099,370.2),e.bezierVertex(130.699,370.2,130.299,370.2,129.799,370.2),e.bezierVertex(125.99,369.9,123.199,367.2,123.099,363.6),e.bezierVertex(122.99,360.2,125.799,357.3,129.599,356.9),e.bezierVertex(130.499,356.8,131.499,356.8,132.599,356.7),e.bezierVertex(133.199,356.7,133.799,356.7,134.399,356.6),e.vertex(138.299,356.4),e.vertM ex(139.1,352.6),e.bezierVertex(139.5,350.7,139.799,348.9,140.2,347),e.bezierVertex(140.899,343.4,141.5,340,142.399,336.8),e.bezierVertex(150.099,310.7,174.399,292,201.399,291.3),e.vertex(201.599,291.3),e.bezierVertex(203.699,291.3,206.299,292,208.299,293.2),e.bezierVertex(210.499,294.5,210.699,297.5,209.99,299.8),e.bezierVertex(209.499,301.5,208.199,303.9,203.299,304.7),e.bezierVertex(202.199,304.9,200.99,305,199.799,305.2),e.bezierVertex(194.499,305.9,188.99,306.599,183.799,308.9),e.bezierVertex(165.499,316.799,15M 5.199,331.299,152.99,352),e.bezierVertex(152.399,357.8,154.499,361.7,159.699,364.5),e.bezierVertex(178.199,374.4,189.399,390,193.099,410.9),e.bezierVertex(193.699,414.299,193.899,418,193.599,422),e.bezierVertex(193.399,425.2,190.899,427.5,187.399,427.5),e.vertex(187.2,427.5),e.endShape(),e.beginShape(),e.vertex(364.3,281.1),e.bezierVertex(346.3,280.6,332.9,272.8,323.5,257),e.bezierVertex(321.6,253.9,320.4,250.2,319.2,246.7),e.bezierVertex(317.7,242.2,315,239.799,310.5,238.799),e.bezierVertex(298.5,236.299,288,230.7M ,279.4,222.1),e.bezierVertex(276.7,219.4,274.9,215.299,278,211.9),e.bezierVertex(279.4,210.3,281,209.6,282.6,209.6),e.bezierVertex(284.4,209.6,286.4,210.6,288.3,212.5),e.bezierVertex(297.8,221.8,310.4,226.9,323.9,226.9),e.bezierVertex(340.2,226.9,355.1,219.3,364.8,206.2),e.bezierVertex(371,197.8,374.2,188.5,374.5,178.5),e.vertex(374.5,177.9),e.bezierVertex(374.5,177,374.5,176.1,374.7,175.4),e.bezierVertex(375.3,171.8,377.9,169.5,381.3,169.5),e.bezierVertex(381.4,169.5,381.5,169.5,381.7,169.5),e.bezierVertex(385.4,1M 69.7,388,172.4,388,176.1),e.bezierVertex(388.1,190.7,383.4,204,374.2,215.8),e.bezierVertex(365.8,226.5,354.7,233.9,341.2,237.9),e.bezierVertex(340,238.3,338.7,238.6,337.3,239.1),e.bezierVertex(335.9,239.6,335.1,240.4,334.7,240.9),e.bezierVertex(334.599,241,334.5,241.1,334.4,241.2),e.vertex(331.799,243.6),e.vertex(333.199,246.8),e.bezierVertex(338.199,258,346.799,264.9,358.699,267.3),e.bezierVertex(360.199,267.6,361.599,267.7,362.99,267.9),e.bezierVertex(363.599,268,364.299,268,364.899,268.1),e.bezierVertex(369.099,M 268.6,371.799,271.4,371.499,275),e.bezierVertex(371.199,278.6,368.299,281.2,364.399,281.2),e.vertex(364.3,281.1),e.endShape(),e.beginShape(),e.vertex(323.9,437),e.bezierVertex(323.7,437,323.5,437,323.299,437),e.bezierVertex(319.599,436.7,317.299,434.1,317.4,430.2),e.bezierVertex(317.9,406.099,328.299,388,349.5,375),e.bezierVertex(350.7,374.2,352,373.5,353.4,372.8),e.bezierVertex(354.099,372.4,354.7,372.1,355.299,371.7),e.vertex(357.499,370.5),e.vertex(357.799,368),e.bezierVertex(360.4,346.6,345.199,323.7,323.9,317)M ,e.bezierVertex(319.099,315.5,314.099,314.9,309.299,314.4),e.vertex(308.199,314.299),e.bezierVertex(305.99,314.099,300.799,312.9,300.899,307.299),e.bezierVertex(300.99,303.499,303.899,300.9,308.099,300.9),e.vertex(308.299,300.9),e.bezierVertex(327.099,301.299,343.099,308.7,355.699,322.9),e.bezierVertex(364.299,332.5,369.399,344.099,370.99,357.299),e.bezierVertex(371.099,358.4,371.299,359.4,371.499,360.499),e.bezierVertex(371.599,360.99,371.699,361.499,371.799,361.99),e.vertex(372.499,365.899),e.vertex(377.899,366.1M 99),e.bezierVertex(378.799,366.299,379.699,366.299,380.599,366.399),e.bezierVertex(385.099,366.699,387.899,369.399,387.799,373.299),e.bezierVertex(387.699,377.099,384.99,379.599,380.799,379.799),e.bezierVertex(369.799,380.199,359.99,383.299,351.899,389.299),e.bezierVertex(338.799,398.799,331.699,411.699,330.699,427.499),e.vertex(330.699,428.299),e.bezierVertex(330.599,429.199,330.599,430.099,330.499,430.799),e.bezierVertex(330,434.7,327.5,437,323.9,437),e.endShape()}function T(e){return e[0].map(((t,n)=>e.map((e=>eM [n]))))}function A(e){return e.map((e=>Array.isArray(e)?A(e):e))}function D(e,t){return floor(random(e,t))}function k(e){let t=0;for(const n of e)t+=n[1];let n=random(t),r=0;for(const t of e)if(r+=t[1],n<r)return t[0];return null}function L(e){for(let t=1;t<e.length;++t){let n=D(0,t),r=e[t];e[t]=e[n],e[n]=r}}function P(e){return null==e||""===e}function O(e){return new Promise((t=>setTimeout(t,e)))}function F(e,t,n){let r=0;for(let i=1;i<=1e3;++i)for(let o=1;o<=1e3;++o)if(e*o%(t*i)==0){let e=1*i/o;abs(e-n)<abs(r-n)M &&(r=e)}return r}function N(){let e=60*(new Date).getTimezoneOffset()*1e3;return new Date(Date.now()-e).toISOString().slice(0,-1)}function B(e,t,n){let r;if(push(),textSize(e),textWidth(t)<=n)r=t;else for(let e=0;e<t.length;++e){const i=t.slice(0,e+1)+"...";if(textWidth(i)>n){r=i;break}}return pop(),r}function Y(e){var t=e%10,n=e%100;return 1==t&&11!=n?e+"st":2==t&&12!=n?e+"nd":3==t&&13!=n?e+"rd":e+"th"}class G{constructor(e,t,n){this.n=t,this.m=n,this.mat=[];let r=0;for(let t=0;t<this.n;++t){this.mat.push([]);for(M let n=0;n<this.m;++n)this.mat[t].push(r<e.length?e[r]:0),r+=1}return this}copy(){return new G(this.mat.flat(),this.n,this.m)}}class H{static __linear=e=>e;static __relu=e=>Math.max(e,0);static __leaky_relu=e=>e>0?e:.2*e;static __sigmoid=e=>1/(1+Math.exp(-e));static __tanh=e=>Math.tanh(e);static __apply_unary_op(e,t){const n=e.copy();for(let e=0;e<n.n;++e)for(let r=0;r<n.m;++r)n.mat[e][r]=t(n.mat[e][r]);return n}static linear=e=>H.__apply_unary_op(e,H.__linear);static relu=e=>H.__apply_unary_op(e,H.__relu);static leM aky_relu=e=>H.__apply_unary_op(e,H.__leaky_relu);static sigmoid=e=>H.__apply_unary_op(e,H.__sigmoid);static tanh=e=>H.__apply_unary_op(e,H.__tanh);static __add=(e,t)=>e+t;static __mul=(e,t)=>e*t;static __apply_binary_op=(e,t,n)=>{"object"!=typeof t&&(t=new G([t],1,1));const r=e.copy();for(let e=0;e<r.n;++e)for(let i=0;i<r.m;++i)r.mat[e][i]=n(r.mat[e][i],t.mat[e%t.n][i%t.m]);return r};static mul=(e,t)=>H.__apply_binary_op(e,t,H.__mul);static add=(e,t)=>H.__apply_binary_op(e,t,H.__add);static matMul(e,t){const n=new M G([],e.n,t.m);for(let r=0;r<n.n;++r)for(let i=0;i<n.m;++i)for(let o=0;o<e.m;++o)n.mat[r][i]+=e.mat[r][o]*t.mat[o][i];return n}static softmax(e){const t=H.__apply_unary_op(e,(e=>Math.exp(e))),n=t.mat.flat().reduce(((e,t)=>e+t));for(let r=0;r<e.n;++r)for(let i=0;i<e.m;++i)t.mat[r][i]/=n;return t}}class ${constructor(e,t){this.scale=e,this.offset=t}forward(e){return H.add(H.mul(e,this.scale),this.offset)}}class X{constructor(){}forward(e){return e.map((e=>e.flat()))}}class W{constructor(e,t,n,r){this.out_dim=e,this.acM tivation=t,this.w=n,this.b=r}forward(e){const t=H.add(H.matMul(e,this.w),this.b);return null==this.activation?t:this.activation(t)}}class U{constructor(e,t,n){this.preprocessLayers=e,this.hiddenLayers=t,this.outputLayer=n,this.totalNeurons=this.hiddenLayers.map((e=>e.out_dim)),this.currentOrders=[],this.currentIteration=null}updateNeurons(e,t){if(t!=this.currentIteration){this.currentOrders=[];for(let e=0;e<this.totalNeurons.length;++e){randomSeed(100*(t+1)+e);const n=[];for(let t=0;t<this.totalNeurons[e];++t)n.pusM h(t);L(n),this.currentOrders.push(n)}this.currentIteration=t}const n=A(this.totalNeurons),r=n.reduce(((e,t)=>e+t))*(1-e);for(let e=0;e<r;++e){const t=n.map(((e,t)=>(e-1)/this.totalNeurons[t]));n[t.map(((e,t)=>[e,t])).reduce(((e,t)=>t[0]>e[0]?t:e))[1]]-=Math.min(r-e,1)}this.neuronsLife=[];for(let e=0;e<n.length;++e){const t=this.currentOrders[e],r=Array(this.totalNeurons[e]).fill(0);for(let i=0;i<n[e];++i)r[t[i]]=Math.min(n[e]-i,1);this.neuronsLife.push(r)}}getTotalNeurons(){return A(this.totalNeurons)}getNeuronsLifM e(){return A(this.neuronsLife)}forward(e){for(const t of this.preprocessLayers)e=t.forward(e);for(const[t,n]of this.hiddenLayers.entries()){e=n.forward(e);const r=new G(this.neuronsLife[t],1,e.m);e=H.mul(e,r)}return e=this.outputLayer.forward(e),H.softmax(e)}}function q(e){switch(e){case"relu":return H.relu;case"sigmoid":return H.sigmoid;case"tanh":return H.tanh;case"leaky_relu":return H.leaky_relu;default:return H.linear}}function j(e,t){const n=[],r=[],i=Z(t);let o=null,a=0,l=[];for(const t of e.config.layers)if(M "InputLayer"==t.class_name)o=t.config.batch_input_shape.slice(1),l=o;else if("Rescaling"==t.class_name)n.push(new $(t.config.scale,t.config.offset));else if("Flatten"==t.class_name)o=[o.reduce(((e,t)=>e*t))];else if("Dense"==t.class_name){const e=[t.config.units],n=o[0]*e[0],l=e[0],s=i.subarray(a,a+n);a+=n;const h=i.subarray(a,a+l);a+=l;const c=new G(s,o[0],e[0]),u=new G(h,1,e[0]),f=q(t.config.activation);r.push(new W(e[0],f,c,u)),o=e}const s=r.pop();return{model:new U(n,r,s),inputDim:l}}function Z(e){const t=windoM w.atob(e),n=t.length/Float32Array.BYTES_PER_ELEMENT,r=new DataView(new ArrayBuffer(Float32Array.BYTES_PER_ELEMENT)),i=new Float32Array(n);let o=0;for(let e=0;e<n;e++){o=4*e;for(let e=0;e<4;++e)r.setUint8(e,t.charCodeAt(o+e));i[e]=r.getFloat32(0,!0)}return i}class K{constructor(e){this.elt=e,this._events={},this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight}position(){if(0===arguments.length)return{x:this.elt.offsetLeft,y:this.elt.offsetTop};var e="absolute";return"static"!==arguments[2]&&"fixed"!==arM guments[2]&&"relative"!==arguments[2]&&"sticky"!==arguments[2]&&"initial"!==arguments[2]&&"inherit"!==arguments[2]||(e=arguments[2]),this.elt.style.position=e,this.elt.style.left=arguments[0]+"px",this.elt.style.top=arguments[1]+"px",this.x=arguments[0],this.y=arguments[1],this}show(){return this.elt.style.display="block",this}hide(){return this.elt.style.display="none",this}size(e,t){if(0===arguments.length)return{width:this.elt.offsetWidth,height:this.elt.offsetHeight};var n=e,r=t;if(n!==te||r!==te){if(n===te?n=tM *this.width/this.height:r===te&&(r=e*this.height/this.width),this.elt instanceof HTMLCanvasElement){var i,o={},a=this.elt.getContext("2d");for(i in a)o[i]=a[i];for(i in this.elt.setAttribute("width",n*this._pInst._pixelDensity),this.elt.setAttribute("height",r*this._pInst._pixelDensity),this.elt.style.width=n+"px",this.elt.style.height=r+"px",this._pInst.scale(this._pInst._pixelDensity,this._pInst._pixelDensity),o)this.elt.getContext("2d")[i]=o[i]}else this.elt.style.width=n+"px",this.elt.style.height=r+"px",this.eM lt.width=n,this.elt.height=r;this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight,this._pInst&&this._pInst._curElement&&this._pInst._curElement.elt===this.elt&&(this._pInst._setProperty("width",this.elt.offsetWidth),this._pInst._setProperty("height",this.elt.offsetHeight))}return this}style(e,t){if(t instanceof Color&&(t="rgba("+t.levels[0]+","+t.levels[1]+","+t.levels[2]+","+t.levels[3]/255+")"),void 0===t){if(-1===e.indexOf(":"))return window.getComputedStyle(this.elt).getPropertyValue(e);for(var n=eM .split(";"),r=0;r<n.length;r++){var i=n[r].split(":");i[0]&&i[1]&&(this.elt.style[i[0].trim()]=i[1].trim())}}else if(this.elt.style[e]=t,"width"===e||"height"===e||"left"===e||"top"===e){var o=window.getComputedStyle(this.elt).getPropertyValue(e).replace(/[^\d.]/g,"");this[e]=Math.round(parseFloat(o,10))}return this}value(){return arguments.length>0?(this.elt.value=arguments[0],this):"range"===this.elt.type?parseFloat(this.elt.value):this.elt.value}mouseClicked(e){return this._adjustListener("click",e,this),this}isM Focused(){return document.activeElement===this.elt}_adjustListener(e,t,n){return!1===t?this._detachListener(e,n):this._attachListener(e,t,n),this}_attachListener(e,t,n){n._events[e]&&this._detachListener(e,n);var r=t.bind(n);n.elt.addEventListener(e,r,!1),n._events[e]=r}_detachListener(e,t){var n=t._events[e];t.elt.removeEventListener(e,n,!1),t._events[e]=null}}function J(e,t){var n=document.createElement("button");return n.innerHTML=e,t&&(n.value=t),ee(n)}function Q(e){var t=arguments.length>1&&void 0!==arguments[M 1]&&arguments[1],n=function(t){var n=!0,r=!1,i=void 0;try{for(var o,a=t.target.files[Symbol.iterator]();!(n=(o=a.next()).done);n=!0){var l=o.value;File._load(l,e)}}catch(e){r=!0,i=e}finally{try{n||null==a.return||a.return()}finally{if(r)throw i}}};if(window.File&&window.FileReader&&window.FileList&&window.Blob){var r=document.createElement("input");return r.setAttribute("type","file"),t&&r.setAttribute("multiple",!0),r.addEventListener("change",n,!1),ee(r)}}function ee(e){return document.body.appendChild(e),new K(eM )}createImg=function(){var e,t=document.createElement("img"),n=arguments;return n.length>1&&"string"==typeof n[1]&&(t.alt=n[1]),n.length>2&&"string"==typeof n[2]&&(t.crossOrigin=n[2]),t.src=n[0],e=ee(t,this),t.addEventListener("load",(function(){e.width=t.offsetWidth||t.width,e.height=t.offsetHeight||t.height;var r=n[n.length-1];"function"==typeof r&&r(e)})),e},createInput=function(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:"",t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:"text",n=docM ument.createElement("input");return n.setAttribute("value",e),n.setAttribute("type",t),ee(n,this)};const te="auto";function ne(e){re(e);const t=e._rectMode;e.rectMode(CORNER),e.rect(0,0,e.width,e.height),e.rectMode(t),ie(e)}function re(e){e.push(),e.fill(255,255,255,255),e.blendMode(REMOVE)}function ie(e){e.blendMode(BLEND),e.pop()}File=function(e,t){this.file=e,this._pInst=t;var n=e.type.split("/");this.type=n[0],this.subtype=n[1],this.name=e.name,this.size=e.size,this.data=void 0},File._createLoader=function(e,t)M {var n=new FileReader;return n.onload=function(n){var r=new File(e);if("application/json"===r.file.type)r.data=JSON.parse(n.target.result);else if("text/xml"===r.file.type){var i=(new DOMParser).parseFromString(n.target.result,"text/xml");r.data=new XML(i.documentElement)}else r.data=n.target.result;t(r)},n},File._load=function(e,t){if(/^text\//.test(e.type)||"application/json"===e.type)File._createLoader(e,t).readAsText(e);else if(/^(video|audio)\//.test(e.type)){var n=new File(e);n.data=URL.createObjectURL(e),t(nM )}else File._createLoader(e,t).readAsDataURL(e)},XML=function(e){if(e)this.DOM=e;else{var t=document.implementation.createDocument(null,"doc");this.DOM=t.createElement("root")}},document.addEventListener("DOMContentLoaded",(function(){addEventListener("mousemove",(e=>{window.mouseX=e.pageX,window.mouseY=e.pageY}))})),new e("global");const oe="44";let ae,le,se,he,ce,ue,fe,de,xe,ge,pe,me,be,ye,we,ve,ze,Ve,_e,Me,Ee,Se,Re,Ie,Ce,Te,Ae,De,ke,Le,Pe,Oe,Fe,Ne,Be,Ye,Ge,He,$e,Xe,We,Ue,qe,je,Ze,Ke,Je,Qe,et,tt,nt,rt,it,ot,at,ltM ,st,ht,ct,ut,ft,dt,xt,gt,pt,mt,bt,yt,wt,vt,zt,Vt,_t,Mt,Et,St,Rt,It,Ct,Tt,At=!1,Dt=!1,kt=!0,Lt=!1,Pt=!1;const Ot=[" ","Growing","Stable","Decaying","Dead","Rebirth"];let Ft,Nt,Bt,Yt,Gt,Ht,$t,Xt,Wt,Ut,qt,jt,Zt,Kt,Jt,Qt,en,tn,nn,rn,on,an,ln,sn,hn=0,cn=0,un=0,fn=!1,dn=!0,xn=!0,gn=null,pn=null,mn=null,bn=!1,yn=!1,wn=null,vn=null,zn=!1;async function setup(){let e=windowWidth,t=windowHeight;createCanvas(e,t),et=createGraphics(e,t),Xe=createGraphics(e,t),$e=createGraphics(e,t),We=createGraphics(e,t),Ue=createGraphics(e,t)M ,qe=createGraphics(e,t),Qe=createGraphics(e,t),je=createGraphics(e,t),Ze=createGraphics(e,t),Ke=createGraphics(e,t),Je=createGraphics(e,t),tt=createGraphics(500,500),nt=createGraphics(500,500),rt=createGraphics(500,500),_n(),Mn(),Sn(),await En(),Gn(),Rn(),bn=!0}function _n(){Et=parseInt(oe),randomSeed(Et),noiseSeed(Et)}function Mn(){Wt=Ir(p.training_traits),Cr(Wt)}async function En(){let e;Jt=r(),Qt=o(),[Xt,e]=await Promise.all([s(Jt),h(Qt)]),Ut=new V(Wt.visual,e.layers_config,e.weight_b64),Ut.updateAge(new Date),_M n(),Wt.training=e.training_traits,Ht=e.model_name,$t=e.classes_name}function Sn(){le=min(width,height)/1024,ut=Rr.findIndex((e=>e[0]===Wt.visual.colorPalette)),ft=[["#ffffff","#231f20","#231f20"],["#231f20","#ffffff","#ffffff"],["#104da8","#ffffff","#ffffff"],["#722F1F","#FCE1B2","#FCE1B2"],["#e88120","#f9f2e5","#f9f2e5"],["#f6b941","#2E2E2E","#2E2E2E"],["#45daaa","#012221","#012221"],["#F1F1F1","#328DFE","#328DFE"],["#111822","#D3EB8D","#D3EB8D"],["#713FF9","#D6D5E6","#D6D5E6"],["#FBDA9D","#795106","#795106"],["#8M f5b62","#ead0d0","#ead0d0"],["#eae4cb","#508cac","#508cac"],["#ffc6cc","#cc313d","#cc313d"],["#60A900","#E0FE00","#E0FE00"],["#507DBE","#D0D1D3","#D0D1D3"],["#305848","#E8F2EE","#E8F2EE"],["#2a2634","#5b6988","#cb78a2","#5b6988"],["#590e29","#fd5e53","#fd5e53","#ffe373"],["#0a141d","#57d4e4","#328195","#2A9ECF","#0ab6a8","#57d4e4"],["#3a2d28","#d5c2ac","#df6338","#3d9895","#d5c2ac"],["#030706","#77c4d9","#77c4d9","#77c4d9","#ffffff","#ffffff","#e72020","#e72020"],["#3a4664","#92f5ff","#f9ff94","#eaa0a2","#55dde0"],M ["#fbfaff","#f04bb1","#f04bb1","#fac373","#82cef0","#8b31ce"],["#000000","#ffffff","#ff0002","#f26522","#fdff00","#00ff03","#01fffe","#0000ff","#ff00ff"]];for(let e=0;e<ft.length;++e)for(let t=0;t<ft[e].length;++t)ft[e][t]=cr(ft[e][t]);pt=[],ct=ft[ut][0],st=ft[ut][1]}function Rn(){gn=document.querySelector("#upload"),pn=document.querySelector("#inputUpload"),gn.addEventListener("dblclick",(()=>{if(!Lt&&!yn)if(In(Ie)&&cn==Ve-1)pn.click();else{if(4!=Pe&&5!=Pe&&(In(Ie)||cn!=Ve-1))return;fn=!0,dn=!0,Bt=0,un=0}})),pn.adM dEventListener("click",(()=>{pn.value=null,gn.style.display="block"})),pn.addEventListener("change",(()=>{const[e]=pn.files;e?(se=null,gn.style.display="none",Tn(URL.createObjectURL(e)),mn=e):gn.style.display="block"}))}function In(e){for(let t=0;t<e.length;++t){let n=0;for(let r=0;r<e[t].length;++r)e[t][r]>0&&++n;if(0==n)return!1}return!0}function Cn(){null!=se&&(un=0,Pt=!0,he=0,ue=0,drewLineAnim=!0,ce=(ae/2+we/2)/le,loadImage(se.elt.src,(e=>{const[t,n,r]=Gt,i=createGraphics(t,n);i.image(e,0,0,t,n),i.loadPixels();M const o=i.pixels.filter(((e,t)=>t%4!=3)),a=Ut.classifyImage(o);Zt=T([a,$t.map((e=>e.toUpperCase()))]).sort(((e,t)=>e[0]>t[0]?-1:1))})))}function Tn(e){se=createImg(e,""),se.hide(),Cn()}function An(){zn||(ce+=(width-ae-we)/tn/le),re(Xe),Xe.rect(ce*le,0,width,height),ie(Xe),un>=ge&&1==kt&&(kt=!1,un-=ge),kt&&(re($e),$e.strokeWeight(2*Fe),Jn(he,ze,ct,ct,$e),ie($e)),un>=ge&&0==kt&&(kt=!0,un-=ge,he+=1,he==en&&(++ue,he=0,ce=(ae/2+we/2)/le,1==ue&&(Pt=!1,Dn(),ye=millis())))}function Dn(){At=!0,pe=!1,me=!1,tryButton=br("Try M Again",width/2-225*le,height/2+265*le,290*le,40*le,kn),closeResultButton=br("Close",width/2+75*le,height/2+265*le,150*le,40*le,Ln)}function kn(){At=!1,tryButton.hide(),closeResultButton.hide(),pn.click()}function Ln(){Yt=!0,At=!1,Gn(),tryButton.hide(),closeResultButton.hide(),gn.style.display="block",se=null}function keyTyped(){bn&&!1===yn&&!1===yr()&&("i"!==key&&"I"!==key||(Dt=!Dt),"b"!==key&&"B"!==key||(xn=!xn),"s"!==key&&"S"!==key||!1!==Lt||saveCanvasAtCurrentTime(),"k"!==key&&"K"!==key||!1!==Lt||save4KCanvasAtCM urrentTime(),"u"!==key&&"U"!==key||!1!==Lt||!1!==At||!1!==fn||!1!==Pt||On())}function On(){Lt=!0,wn=null,vn=null,submitButton=br("Submit",width/2-155*le,height/2+115*le,150*le,40*le,Fn),closeSettingButton=br("Close",width/2+5*le,height/2+115*le,150*le,40*le,Yn),vt=createInput(),vt.position(width/2-252.5*le,height/2-40*le),vt.size(500*le,25*le),vt.style("font-size","15px"),vt.value(Jt||""),zt=createInput(),zt.position(width/2-252.2*le,height/2+35*le),zt.size(500*le,25*le),zt.style("font-size","15px"),zt.value(Qt||""M )}function Fn(){Vt=vt.value(),_t=zt.value(),submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide(),Lt=!1,yn=!0,Nn()}async function Nn(){[wn,vn,_]=await Promise.all([c(Vt),u(_t),O(1e3)]),yn=!1,wn&&vn?(n(Vt),i(_t),window.location.reload()):(Lt=!0,submitButton.show(),closeSettingButton.show(),vt.show(),zt.show())}function Bn(){Je.textFont("Trebuchet MS"),Je.noStroke(),pr(Je,600*le,200*le),Je.strokeWeight(1*le),Je.stroke(xt),Je.fill(xt),Je.textSize(50*le),Je.text("update()",width/2,height/2+2.5*le)}function M Yn(){wn=null,vn=null,Lt=!1,submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide()}function Gn(){_n(),nn=Date.now(),pe=!1,me=!1,St=Wt.training.structure_gen,Rt=Wt.visual.birthYear,It=Wt.visual.lifeCycle,Ct=Wt.training.epoch_num,Tt=Wt.training.activation_func,Ft=Mr.findIndex((e=>e[0]==Wt.visual.hardwareAcceleration))+1,1==Ft?(Nt=30,fe=40):2==Ft?(Nt=15,fe=20):(Nt=2,fe=10);const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStablM eTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),ae=100*le,ht=50*le,Oe=Sr.findIndex((e=>e[0]==Wt.visual.nodeShape))+1,dt=Er.findIndex((e=>e[0]==Wt.visual.nodeFill))+1,lt=_r.findIndex((e=>e[0]==Wt.visual.pattern))+1,de=Math.tanh(Math.log10(Xt.avgfeerate)),de=map(de,0,1,M .2,.8),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].puM sh(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=FM (tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,at=.7,pt=[],xt=ft[ut][2],gt=ft[ut][ft[ut].length-1];for(let e=3;e<ft[ut].length-1;e++)pt.push(ft[ut][e]);mt=sr(xt,gt,pt,width),bt=[],wt=[],yt=width/(Ve-1);for(let e=0;e<Ve;e++)bt.push(hr(mt,yt*e/width)),wt.push(hr(mt,yt*e/width));wt.unshift(bt[0]),wt.push(bt[bt.M length-1]),hn=0,cn=0,un=0,Yt=!0;const n={xLeft:ae/8,xRight:width-ae/8,yTop:ae/8,yBottom:height-ae/8},r=Ce.map((e=>e.length));jt=new R(bt,r,n,Oe,le)}function Hn(e,t){let n=Ce[e].length;return[e*we+we/2+ae/2,height/2-(n-1)/2*ve+t*ve]}function $n(e,t){le=min(e,t)/1024,ae=100*le,ht=50*le,we=(e-ae)/Ve,ve=(t-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}xe=floor(De.length*de),Le=[],ke=[],ge=floor(map(de,.2,.8,15,2));foM r(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,mt=sr(xt,gt,pt,e),bt=[],wt=[],yt=e/(Ve-1);for(let t=0;t<Ve;t++)bt.push(hr(mt,yt*t/e)),wt.push(hr(mt,yt*t/e));wt.unshift(bt[0]),wt.push(bt[bt.length-1])}function Xn(){const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.M $state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=M [];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.pushM (Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)M *le}function Wn(){jt.update();const e=4==Pe?0:Kt;jt.draw(Qe,ct,dt,e,le)}function Un(){if(!bn)return ar(),void et.image(je,0,0);if(4==Pe||5==Pe)return Wn(),void et.image(Qe,0,0);un>=Nt&&hn<Ve&&(hn++,un=0);for(let e=0;e<hn;e++)1==dt?it=ot=bt[e]:(it=ct,ot=bt[e]),Kn(e,it,ot,$e);un>=Nt&&cn<Ve-1&&(cn++,un=0);for(let e=0;e<cn;e++)Zn(e)}function qn(){et.background(ct),Ue.background(255),Ue.rectMode(CENTER),ne(Ue),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),Ue.stroke(st),Ue.strokeWeight(8*le),Ue.fill(ct),Qe.background(25M 5),Qe.rectMode(CENTER),ne(Qe),Qe.strokeWeight(le),qe.background(255),qe.rectMode(CENTER),ne(qe),qe.textAlign(LEFT),$e.background(255),$e.rectMode(CENTER),ne($e),Xe.background(255),ne(Xe),Xe.strokeWeight(Ne),We.background(255),We.rectMode(CENTER),ne(We),We.fill(st),We.stroke(st),We.strokeWeight(.1*le),er(lt),We.noStroke(),xn&&(We.rect(ae/16,height/2,ae/8,height),We.rect(width-ae/16,height/2,ae/8,height),We.rect(width/2,ae/16,width,ae/8),We.rect(width/2,height-ae/16,width,ae/8)),Ze.background(255),Ze.rectMode(CENTER)M ,ne(Ze),Ze.textAlign(CENTER,CENTER),Ze.textStyle(BOLD),Ze.stroke(st),Ze.strokeWeight(8*le),Ze.fill(ct),je.background(255),je.rectMode(CENTER),ne(je),je.textAlign(CENTER,CENTER),je.textStyle(BOLD),Ke.background(255),Ke.rectMode(CENTER),ne(Ke),Ke.textAlign(CENTER,CENTER),Ke.textStyle(BOLD),Ke.stroke(st),Ke.strokeWeight(8*le),Ke.fill(ct),Je.background(255),Je.rectMode(CENTER),ne(Je),Je.textAlign(CENTER,CENTER),Je.textStyle(BOLD),Je.stroke(st),Je.strokeWeight(8*le),Je.fill(ct),Un(),et.image(We,0,0),Pt&&An(),et.image(XeM ,0,0),et.image($e,0,0),At&&(tr(),et.image(Ue,0,0)),fn&&(lr(),et.image(Ze,0,0)),Lt&&(or(),et.image(Ke,0,0)),Dt&&(ir(),et.image(qe,0,0)),yn&&(Bn(),et.image(Je,0,0))}function draw(){const e=Date.now();bn&&(Ut.updateAge(new Date(e)),Xn()),qn(),image(et,0,0),zn||un++}function Zn(e){let t,n=Ce[e].length,r=Ce[e+1].length;for(let i=0;i<n;i++){const[n,o]=Hn(e,i);for(let a=0;a<r;a++){const[r,l]=Hn(e+1,a);t=map(min(Ce[e][i],Ce[e+1][a]),0,1,0,.5),ur(n,o,r,l,bt[e],bt[e+1],Xe,t)}}}function Kn(e,t,n,r){let i,o,a,l=Ce[e].length;foM r(let s=0;s<l;s++){const[l,h]=Hn(e,s);i=Ce[e][s],a=map(Be,1/30,1,3,10),o=map(Ce[e][s],0,1,2*a,0)*le,o<1.5*le&&(o=0),Qn(l,h,ze,Oe,t,n,o,i,r)}}function Jn(e,t,n,r,i){for(let o=0;o<Le[e].length;o++)Qn(Le[e][o][0],Le[e][o][1],t,Oe,n,r,0,1,i)}function Qn(e,t,n,r,i,o,a,l,s){s.stroke(dr(o,map(l,0,1,.25,1))),s.fill(dr(i,map(l,0,1,.15,1))),s.strokeWeight(Fe),fr([a],s),3==dt&&s.fill(dr(i,0)),1==r?s.ellipse(e,t,n):2==r?s.rect(e,t,7*n/8,7*n/8):3==r&&(s.beginShape(),s.vertex(e-4*n/7,t),s.vertex(e,t-4*n/7),s.vertex(e+4*n/7,t),s.M vertex(e,t+4*n/7),s.endShape(CLOSE))}function er(e){if(1==e);else if(2==e){We.strokeWeight(1*le);for(let e=ht/4;e<width+ht/4;e+=ht)for(let t=ht/4;t<height+ht/4;t+=ht)We.point(e,t)}else if(3==e){ht=25*le;for(let e=ht/2;e<height+ht/2;e+=ht)We.line(0,e,width,e);for(let e=ht/2;e<width+ht/2;e+=ht)We.line(e,0,e,height)}}function tr(){Ue.textFont("Trebuchet MS"),Ue.textAlign(LEFT,CENTER),Ue.noStroke(),pr(Ue,800*le,500*le),Ue.noStroke(),Ue.fill(dr(st,.75)),Ue.rect(width/2,height/2-100*le,800*le,300*le,25*le,25*le,0,0),Ue.fM ill(st),Ue.rect(width/2-250*le,height/2-100*le,225*le,225*le),Ue.image(se.elt,width/2-357.5*le,height/2-207.5*le,215*le,215*le);let e=100*Zt[0][0];Ue.fill(ct),Ue.textSize(25*le),Ue.textStyle(NORMAL),1==me&&(e>=0&&e<20?Ue.text("I have a feeling this image belongs to",width/2-100*le,height/2-170*le):e>=20&&e<40?Ue.text("I have a hunch this image belongs to",width/2-100*le,height/2-170*le):e>=40&&e<60?Ue.text("I think this image belongs to",width/2-100*le,height/2-170*le):e>=60&&e<80?Ue.text("I'm almost certain this iM mage belongs to",width/2-100*le,height/2-170*le):Ue.text("I'm positive this image belongs to",width/2-100*le,height/2-170*le));let t=e.toFixed(2);"100.00"==t&&(t="100"),1==me&&Ue.text("I'm "+t+"% confident that I'm right!",width/2-100*le,height/2-25*le),example=Zt.map((e=>e[1])),be=Ue.textWidth('"FIDENZAAAA"'),defaultPhrase=Ue.textWidth('"PERPENDICULAR INHABITATION"'),Ue.textStyle(BOLD);const n=me?example[0]:random(example);if(1===n.split(" ").length){let e=75*be/Ue.textWidth('"'+n+'"');e>75&&(e=75),Ue.textSize(e*lM e),Ue.text('"'+n+'"',width/2-100*le,height/2-90*le)}else nr(width/2-100*le,height/2-90*le,460*le,110*le,n,Ue);if(millis()-ye>1500&&(me=!0),C(tt,nt,st,ct,Pe,Mt),Ue.image(nt,width/2-370*le,height/2+70*le,80*le,80*le),3==Pe){let e;e=map(Mt,50,60,.25,1.3),I(rt,e),Ue.image(rt,width/2-370*le,height/2+70*le,80*le,80*le)}let r,i;Ue.image(tt,width/2-370*le,height/2+70*le,80*le,80*le),Ue.fill(xt),Ue.textSize(40*le),Ue.text("INTELLIGENCE INFO",width/2-275*le,height/2+115*le),Ue.textSize(18*le),Ue.textStyle(NORMAL),Ue.circle(wM idth/2-360*le,height/2+180*le,7.5*le),1==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s growing and getting smarter by the day.`:2==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s stable and it has reached peak performance.`:3==Pe&&(r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s decaying and losing its luster.`),i=2==Pe?"The Perceptron remains stable for some time before entering the decay phase.":`Wait until ${new Date(an).toLocaleString("en-US")} for your Perceptron to reach itsM peak performance.`,Ue.text(r,width/2-350*le,height/2+180*le),Ue.circle(width/2-360*le,height/2+210*le,7.5*le),Ue.text(i,width/2-350*le,height/2+210*le),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),gr(Ue,width/2-225*le,width/2+65*le,height/2+265*le,height/2+305*le,"SELECT ANOTHER IMAGE"),gr(Ue,width/2+75*le,width/2+225*le,height/2+265*le,height/2+305*le,"CLOSE")}function nr(e,t,n,r,i,o){let a=i.split(" "),l=75*be/o.textWidth('"'+i+'"'),s=0,h=[],c=[],u=[],f="",d="";if(l>=50)l>75&&(l=75),o.textSize(l*le),o.text('"'M +i+'"',e,t);else if(l<50){if(l=50*defaultPhrase/o.textWidth('"'+i+'"'),l>30){if(l>50&&(l=50),[f,d]=rr(l,n,s,h,c,a,f,d,Ue),0==c.length)return o.textSize(l*le),void o.text('"'+i+'"',e,t);for(s=0,h=[],c=[];o.textWidth(d)>n/le;)l=l*n/le/o.textWidth(d),f="",d="",[f,d]=rr(l,n,s,h,c,a,f,d,Ue)}else{l=30,o.textSize(l);for(let e=0;e<a.length;e++)s+=o.textWidth(" "+a[e]),s<=n/le?h.push(a[e]):s>n/le&&s<=n/le*2?c.push(a[e]):u.push(a[e]);for(let e=1;e<h.length;e++)f=f+" "+h[e];if(f='"'+h[0]+f,0==u.length){for(let e=0;e<c.length-M 1;e++)d=d+c[e]+" ";d=d+c[c.length-1]+'"'}else if(1==c.length)d="... "+u[u.length-1]+'"';else{for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+"... "+u[u.length-1]+'"'}}o.textSize(l*le);let r=1.25*(o.textDescent()+o.textAscent());o.text(f,e,t-r/2),o.text(d,e,t+r/2)}}function rr(e,t,n,r,i,o,a,l,s){s.textSize(e);for(let e=0;e<o.length;e++)(n+=s.textWidth(" "+o[e]))<=t/le?r.push(o[e]):i.push(o[e]);for(let e=1;e<r.length;e++)a=a+" "+r[e];if(a='"'+r[0]+a,0==i.length&&(a+='"',l=""),1==i.length)l=i[i.length-1]+'"';else{for(leM t e=0;e<i.length-1;e++)l=l+i[e]+" ";l=l+i[i.length-1]+'"'}return[a,l]}function ir(){const e=45*le;qe.textFont("Tahoma"),qe.stroke(st),qe.strokeWeight(2*le),qe.fill(ct),qe.rect(width/2,e/2+height-87.5*le,600*le,90*le),qe.fill(st),qe.rect(width/2-150*le,e+height-170*le,300*le,30*le),qe.fill(ct),qe.rect(width/2+150*le,e+height-170*le,300*le,30*le),qe.noStroke(),qe.fill(ct),qe.textSize(15*le),qe.textStyle(BOLD),qe.text("PERCEPTRON INFORMATION",width/2-285*le,e+height-165*le),qe.fill(xt),qe.text("ARTWORK NAME:",width/2+M 10*le,e+height-165*le),qe.textAlign(RIGHT),qe.textStyle(ITALIC),qe.text("Perceptron #"+Et,width/2+285*le,e+height-165*le);const[t,n]=It.split(" ");let r;"60 Years"===It?r="1 Year":"60 Months"===It?r="1 Month":"60 Weeks"===It?r="1 Week":"60 Days"===It?r="1 Day":"12 Hours"===It&&(r="12 Minutes"),data=[["AI MODEL NAME:",B(12*le,Ht,140*le)],["SCALE:","1:"+Te],["NUMBER OF CLASSES:",$t.length],["BIRTH YEAR:",Rt],["NUMBER OF REBIRTHS:",sn.toString()],["AGE:",`${Math.ceil(Mt)} Perceptron Years`],["ONE PERCEPTRON YEAR:",`${M r}`],["STATE:",Ot[Pe]],["ACTIVE NEURONS:",`${round(ln*rn)} / ${ln}`],["NEXT STATE TIME:",vr(new Date(on))]],qe.fill(xt);const i=data.length/2;for(let t=0;t<data.length;++t){const n=t<i,r=n?width/2-285*le:width/2+10*le,o=n?width/2-10*le:width/2+285*le,a=e+height-(135-t%i*15)*le;qe.textStyle(BOLD),qe.textAlign(LEFT),qe.textSize(12*le),qe.text(data[t][0],r,a),qe.textStyle(ITALIC),qe.textAlign(RIGHT),qe.textSize(12*le),qe.text(data[t][1],o,a)}}function or(){Ke.textFont("Trebuchet MS"),Ke.noStroke(),pr(Ke,600*le,200*le)M ,gr(Ke,width/2-155*le,width/2-5*le,height/2+115*le,height/2+155*le,"UPDATE"),gr(Ke,width/2+5*le,width/2+155*le,height/2+115*le,height/2+155*le,"CLOSE"),Ke.textAlign(LEFT),Ke.fill(xt),Ke.text("UPDATE BITCOIN FULL NODE ADDRESS",width/2-252.5*le,height/2-55*le),Ke.text("UPDATE MODEL ADDRESS",width/2-252.5*le,height/2+20*le),Ke.textAlign(RIGHT),Ke.textStyle(ITALIC),Ke.textSize(15*le),0==wn&&Ke.text("(*) Invalid Address",width/2+252.5*le,height/2-53*le),0==vn&&Ke.text("(*) Invalid Model",width/2+252.5*le,height/2+23*le)M }function ar(){je.textFont("Trebuchet MS"),je.fill(st),je.textSize(50*le),je.stroke(st),je.strokeWeight(1*le),je.text("main()",width/2,height/2)}function lr(){un>=20&&1==dn&&(dn=!1,un=0),dn&&(Ze.textFont("Trebuchet MS"),Ze.stroke(st),Ze.fill(ct),Ze.rect(width/2,height/2,600*le,150*le,25*le),Ze.fill(xt),Ze.textSize(75*le),Ze.noStroke(),1==Pe?Ze.text("GROWING",width/2,height/2+5*le):3==Pe?Ze.text("AGING",width/2,height/2+5*le):4==Pe?Ze.text("DEAD",width/2,height/2+5*le):5==Pe&&Ze.text("BIRTH",width/2,height/2+5*le)),M un>=20&&0==dn&&(dn=!0,un=0,Bt++,3==Bt&&(fn=!1))}function sr(e,t,n,r){let i=[],o=r/(n.length+1),a=color(e),l=color(t);i.push(a);for(let e=0;e<n.length;e++){let t=color(n[e]);for(let e=1;e<=o;e++){let n=lerpColor(a,t,e/o);i.push(n)}a=t}for(let e=1;e<o;e++){let t=lerpColor(a,l,e/o);i.push(t)}if(i.push(l),i.length>r)i.splice(r);else if(i.length<r){let e=i[i.length-1];for(;i.length<r;)i.push(e)}return i}function hr(e,t){let n=e.length,r=Math.floor(t*n);return r>=n&&(r=n-1),e[r]}function cr(e){e=e.replace("#","");var t=pM arseInt(e,16);return color(t>>16&255,t>>8&255,255&t)}function ur(e,t,n,r,i,o,a,l){var s=a.drawingContext.createLinearGradient(e,t,n,r);s.addColorStop(0,i),s.addColorStop(1,o),a.drawingContext.strokeStyle=s,a.drawingContext.globalAlpha=l,a.line(e,t,n,r),a.drawingContext.globalAlpha=1}function fr(e,t){t.drawingContext.setLineDash(e)}function dr(e,t){let n=color(e),r=red(n),i=green(n),o=blue(n);return color(r,i,o,255*t)}function xr(e,t,n,r){return mouseX>e&&mouseX<t&&mouseY>n&&mouseY<r}function gr(e,t,n,r,i,o){e.strokM eWeight(1*le),e.stroke(st);const[a,l]=xr(t,n,r,i)?[xt,ct]:[ct,xt];e.fill(a),e.push(),e.rectMode(CORNERS),e.rect(t,r,n,i,5*le),e.pop(),e.noStroke(),e.textSize(20*le),e.fill(l),e.text(o,(t+n)/2,(46*r+54*i)/100)}function pr(e,t,n){e.fill(0,0,0,75),e.rect(width/2,height/2,width,height),e.stroke(st),e.fill(ct),e.rect(width/2,height/2,t,n,25*le)}function mr(e,t){resizeCanvas(e,t,!0),Xe.resizeCanvas(e,t,!0),$e.resizeCanvas(e,t,!0),We.resizeCanvas(e,t,!0),Ue.resizeCanvas(e,t,!0),qe.resizeCanvas(e,t,!0),Qe.resizeCanvas(e,t,M !0),je.resizeCanvas(e,t,!0),Ze.resizeCanvas(e,t,!0),Ke.resizeCanvas(e,t,!0),Je.resizeCanvas(e,t,!0),et.resizeCanvas(e,t,!0)}function br(e,t,n,r,i,o){const a=J(e);return a.position(t,n),a.size(r,i),a.style("opacity","0"),a.mouseClicked(o),a}function yr(){return null!=vt&&vt?.isFocused()||null!=zt&&zt?.isFocused()}function wr(e,t,n,r){let i;if(e<=3){i=`Hey ${String.fromCodePoint(128075)}, I'm ${n}, ${t} years old. I can detect ${r.length} NFT collections: `;let e=0;for(let t=0;t<r.length;++t){const n=r[t];if(e+n.lengM th>500){i+=", etc";break}t==r.length-1?i+=", and ":t>0&&(i+=", "),i+=n,e+=n.length}i+=". ",t<=5?i+="However, I am only a baby, so my recognition ability is not accurate. I'm in the state of Growing both looks and intelligence.":t<=13?i+="I am now a child. My recognition ability is becoming better, but still not very accurate. I'm in the state of Growing both looks and intelligence.":t<=25?i+="I have grown up to be a teen. My recognition ability almost reaches the peak, but I will still mess up sometimes. I'm in theM state of Growing both looks and intelligence.":t<=50?i+="I finally reach adulthood. My recognition is fully functional now. I'm in the Stable state, where I am the most intelligent with all neurons activated.":t<=60&&(i+="I am now an old Perceptron, so my recognition ability is no longer the best. I'm in the Decaying state, meaning that my neurons are dying, and my intelligence is decreasing over time.")}else 4==e?i=`${n} is Dead. However, this is not the end to its story...`:5==e&&(i=`${n} is now in the Rebirth sM tate, and is preparing to start a new life.`);return i}function vr(e){const t=e.getDate(),n=e.toLocaleString("en-US",{month:"long"}),r=e.getFullYear();let i=e.getHours().toString();1==i.length&&(i="0"+i);let o=e.getMinutes().toString();return 1==o.length&&(o="0"+o),`${Y(t)} ${n} ${r} | ${i}:${o}`}saveCanvasAtCurrentTime=()=>{save(N())},save4KCanvasAtCurrentTime=()=>{const e=width,t=height,n=min(4096/min(e,t),1e4/max(e,t)),r=e*n,i=t*n;mr(r,i),zn=!0,$n(r,i),qn();let o="4K_"+N()+".png";saveCanvas(et,o),mr(e,t),$n(e,t)M ,zn=!1};const zr=[["60 Years",3,365],["60 Months",40,30],["60 Weeks",37,7],["60 Days",20,1]],Vr=[["1943",1],["1951",1.5],["1957",2],["1969",2.5],["1970",3],["1980",3.5],["1982",4],["1986",4.5],["1988",5],["1997",5.5],["1998",6],["2002",6.5],["2009",7],["2012",7.5],["2014",8],["2015",8.5],["2016",9],["2023",15]],_r=[["Plain",20],["Dotted",40],["Squared",40]],Mr=[["Basic",30],["Standard",60],["Advanced",10]],Er=[["MNIST",70],["CIFAR",25],["IMAGENET",5]],Sr=[["Theano",60],["Torch",30],["TensorFlow",10]],Rr=[["WhitepapM er",2],["Blackboard",2],["Blueprint",2],["Nak",74/14],["Jims",74/14],["Level 10",74/14],["Flips",74/14],["Level 14",74/14],["III",74/14],["XMB",74/14],["Info",74/14],["Adventure",74/14],["Marigold",74/14],["Phoenix",74/14],["Love",74/14],["Cachet",74/14],["Human",74/14],["Twilight",3],["Sunset",3],["Aurora",3],["Liminal Space",3],["D Vu",3],["Lucid Dream",3],["Parallel",1],["Multiverse",1]];function Ir(e){for(let e=0;e<100;++e)random(1);return{visual:{pattern:k(_r),hardwareAcceleration:k(Mr),nodeFill:k(Er),nodM eShape:k(Sr),colorPalette:k(Rr),lifeCycle:k(zr),birthYear:k(Vr)},training:e}}function Cr(e){window.$generativeTraits={"Network Architecture":e.training.structure_gen,"Hidden Layers":e.training.n_layers,"Max Neurons Per Hidden Layer":e.training.max_nodes,"Activation Function":e.training.activation_func,"Training Epochs":e.training.epoch_num,Dataset:e.visual.nodeFill,"Deep Learning Framework":e.visual.nodeShape,"Hardware Acceleration":e.visual.hardwareAcceleration,"Paper Pattern":e.visual.pattern,"Life Cycle":e.visuaM l.lifeCycle,"Birth Year":e.visual.birthYear,"Color Palette":e.visual.colorPalette}} <script defer src="https://static.cloudflareinsights.com/beacon.min.js/v2b4487d741ca48dcbadcaf954e159fc61680799950996" integrity="sha512-D/jdE0CypeVxFadTejKGTzmwyV10c1pxZk/AqjJuZbaJwGMyNHY3q/mTPWqMUnFACfCTunhZUVcd4cV78dK1pQ==" data-cf-beacon='{"rayId":"7b489311888ea1da","version":"2023.3.0","b":1,"token":"6c07c178c94442f695e7a0a2aaee641a","si":100}' crossorigin="anonymous"></script> {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "robot"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "golden"}, {"trait_type": "Headgear", "value": "skull"}, {"trait_type": "Artifacts", "value": "wizard staff"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "blue fire"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "arrow wounds"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "bag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "parrot"}]} text/plain;charset=utf-8 {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "cape"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "undead"}, {"trait_type": "Artifacts", "value": "dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "moon"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "honey pot"}, {"trait_type": "Eyes", "value": "laser"}, {"trait_type": "Headgear", "value": "crown"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "badger"}, {"trait_type": "Artifacts", "value": "pirate flag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "lamp"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "pauldrons"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "orc"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "pirate flag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "golden armor"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "shield"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "tribal tattoo"}, {"trait_type": "Mane", "value": "rainbow"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "axe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "blue fire"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "none"}]} text/plain;charset=utf-8 .{"p":"sns","op":"reg","name":"lucasfilm.sats"}h! {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "golden armor"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "pirate flag"}]} text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "skull"}, {"trait_type": "Artifacts", "value": "eagle"}]} text/plain;charset=utf-8 ({"p":"sns","op":"reg","name":" {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "tiger"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "shield"}]} text/plain;charset=utf-8 ({"p":"sns","op":"reg","name":" {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "sword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "fire sword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "golden"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "tribal tattoo"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "undead"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "pirate flag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "golden armor"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "badger"}, {"trait_type": "Artifacts", "value": "dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "noggles"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "parrot"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "ghostly companioM text/plain;charset=utf-8 -{"p":"sns","op":"reg","name":"fandango.sats"}h! {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "golden armor"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "skull"}, {"trait_type": "Artifacts", "value": "cape"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "blue fire"}, {"trait_type": "Claws", "value": "bloody"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "pirate flag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "blue fire"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "axe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "parrot"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "fire"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "skull"}, {"trait_type": "Artifacts", "value": "parrot"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "axe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "wizard staff"}]} text/html;charset=utf-8 <meta charset="utf-8" /> position: relative; width: var(--width); height: var(--height); border: 1px solid blue; position: relative; <div id="upload"> <input id="inputUpload" type="file"> function e(e){"use strict";return new function e(t){let n="global"==t?window:this;n.canvas=document.createElement("canvas");let r=n.canvas.getContext("2d");n.width=100,n.height=100,n.canvas.width=n.width,n.canvas.height=n.height,"offscreen"!=t&&(document.body?document.body.appendChild(n.canvas):window.addEventListener("load",(function(){document.body.appendChild(n.canvas)}))),g(),n.MAGIC=161533525,n.RGB=0,n.HSV=1,n.HM SB=1,n.CHORD=0,n.PIE=1,n.OPEN=2,n.RADIUS=1,n.CORNER=2,n.CORNERS=3,n.ROUND="round",n.SQUARE="butt",n.PROJECT="square",n.MITER="miter",n.BEVEL="bevel",n.CLOSE=1,n.BLEND="source-over",n.REMOVE="destination-out",n.ADD="lighter",n.DARKEST="darken",n.LIGHTEST="lighten",n.DIFFERENCE="difference",n.SUBTRACT="subtract",n.EXCLUSION="exclusion",n.MULTIPLY="multiply",n.SCREEN="screen",n.REPLACE="copy",n.OVERLAY="overlay",n.HARD_LIGHT="hard-light",n.SOFT_LIGHT="soft-light",n.DODGE="color-dodge",n.BURN="color-burn",n.NORMAL="norM mal",n.ITALIC="italic",n.BOLD="bold",n.BOLDITALIC="italic bold",n.CENTER="center",n.LEFT="left",n.RIGHT="right",n.TOP="top",n.BOTTOM="bottom",n.BASELINE="alphabetic",n.LANDSCAPE="landscape",n.PORTRAIT="portrait",n.ALT=18,n.BACKSPACE=8,n.CONTROL=17,n.DELETE=46,n.DOWN_ARROW=40,n.ENTER=13,n.ESCAPE=27,n.LEFT_ARROW=37,n.OPTION=18,n.RETURN=13,n.RIGHT_ARROW=39,n.SHIFT=16,n.TAB=9,n.UP_ARROW=38,n.HALF_PI=Math.PI/2,n.PI=Math.PI,n.QUARTER_PI=Math.PI/4,n.TAU=2*Math.PI,n.TWO_PI=2*Math.PI,n.THRESHOLD=1,n.GRAY=2,n.OPAQUE=3,n.INVEM RT=4,n.POSTERIZE=5,n.DILATE=6,n.ERODE=7,n.BLUR=8,n.ARROW="default",n.CROSS="crosshair",n.HAND="pointer",n.MOVE="move",n.TEXT="text",n.VIDEO={video:!0,audio:!1},n.AUDIO={video:!1,audio:!0},n.SHR3=1,n.LCG=2,n.HARDWARE_FILTERS=!0,n.hint=function(e,t){n[e]=t},n.frameCount=0,n.mouseX=0,n.mouseY=0,n.pmouseX=0,n.pmouseY=0,n.mouseButton=null,n.keyIsPressed=!1,n.mouseIsPressed=!1,n.key=null,n.keyCode=null,n.pixels=null,n.accelerationX=0,n.accelerationY=0,n.accelerationZ=0,n.rotationX=0,n.rotationY=0,n.rotationZ=0,n.relRotatM ionX=0,n.relRotationY=0,n.relRotationZ=0,n.pAccelerationX=0,n.pAccelerationY=0,n.pAccelerationZ=0,n.pRotationX=0,n.pRotationY=0,n.pRotationZ=0,n.pRelRotationX=0,n.pRelRotationY=0,n.pRelRotationZ=0,n.touches=[],n._styleCache=[{colorMode:n.RGB,noStroke:!1,noFill:!1,ellipseMode:n.CENTER,rectMode:n.CORNER,curveDetail:20,curveAlpha:0,textFont:"sans-serif",textSize:12,textLeading:12,textStyle:"normal"}],n._style=n._styleCache[n._styleCache.length-1],n._noLoop=!1,n._pixelDensity=1,n._frameRate=null,n._tint=null;let i=nullM ,o=!0,a=[],l=null,s=0,h={},c=0,u=null,f=null,d=null;Object.defineProperty(n,"deviceOrientation",{get:function(){return 90==Math.abs(window.orientation)?n.LANDSCAPE:n.PORTRAIT}}),Object.defineProperty(n,"windowWidth",{get:function(){return window.innerWidth}}),Object.defineProperty(n,"windowHeight",{get:function(){return window.innerHeight}}),Object.defineProperty(n,"drawingContext",{get:function(){return r}}),n.createCanvas=function(e,t){return n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t,g(),n.canvas},nM .resizeCanvas=function(e,t){n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t},n.createGraphics=n.createImage=function(t,n){let r=new e("offscreen");return r.createCanvas(t,n),r.noLoop(),r},n.pixelDensity=function(e){return null==e||(n._pixelDensity=e,n.canvas.width=Math.ceil(n.width*e),n.canvas.height=Math.ceil(n.height*e),n.canvas.style.width=n.width+"px",n.canvas.style.height=n.height+"px",r.scale(n._pixelDensity,n._pixelDensity),g()),n._pixelDensity},n.map=function(e,t,n,r,i,o){let a=r+1*(e-t)/(n-t)*(i-r)M ;return o?r<i?Math.min(Math.max(a,r),i):Math.min(Math.max(a,i),r):a},n.lerp=function(e,t,n){return e*(1-n)+t*n},n.constrain=function(e,t,n){return Math.min(Math.max(e,t),n)},n.dist=function(){return 4==arguments.length?Math.hypot(arguments[0]-arguments[2],arguments[1]-arguments[3]):Math.hypot(arguments[0]-arguments[3],arguments[1]-arguments[4],arguments[2]-arguments[5])},n.norm=function(e,t,r){return n.map(e,t,r,0,1)},n.sq=function(e){return e*e},n.fract=function(e){return e-Math.floor(e)},n.degrees=function(e){retM urn 180*e/Math.PI},n.radians=function(e){return e*Math.PI/180},n.abs=Math.abs,n.ceil=Math.ceil,n.exp=Math.exp,n.floor=Math.floor,n.log=Math.log,n.mag=Math.hypot,n.max=Math.max,n.min=Math.min,n.round=Math.round,n.sqrt=Math.sqrt,n.sin=Math.sin,n.cos=Math.cos,n.tan=Math.tan,n.asin=Math.asin,n.acos=Math.acos,n.atan=Math.atan,n.atan2=Math.atan2,n.Vector=function(e,t,r){let i=this;i.x=e||0,i.y=t||0,i.z=r||0;let o=null,a=null;function l(e,t,n){return null!=e.x?e:null!=t?{x:e,y:t,z:n||0}:{x:e,y:e,z:e}}function s(){null==a&M &(a=i.x*i.x+i.y*i.y+i.z*i.z,o=Math.sqrt(a))}function h(){a=null,o=null}i.set=function(e,t,n){i.x=e||0,i.y=t||0,i.z=n||0},i.copy=function(){return new n.Vector(i.x,i.y,i.z)},i.add=function(){let e=l.apply(null,arguments);return i.x+=e.x,i.y+=e.y,i.z+=e.z,h(),i},i.rem=function(){let e=l.apply(null,arguments);return i.x%=e.x,i.y%=e.y,i.z%=e.z,h(),i},i.sub=function(){let e=l.apply(null,arguments);return i.x-=e.x,i.y-=e.y,i.z-=e.z,h(),i},i.mult=function(){let e=l.apply(null,arguments);return i.x*=e.x,i.y*=e.y,i.z*=e.z,hM (),i},i.div=function(){let e=l.apply(null,arguments);return i.x/=e.x,i.y/=e.y,i.z/=e.z,h(),i},i.mag=function(){return s(),o},i.magSq=function(){return s(),a},i.dot=function(){let e=l.apply(null,arguments);return i.x*e.x+i.y*e.y+i.z*e.z},i.dist=function(){let e=l.apply(null,arguments),t=i.x-e.x,n=i.y-e.y,r=i.z-e.z;return Math.sqrt(t*t+n*n+r*r)},i.cross=function(){let e=l.apply(null,arguments),t=i.y*e.z-i.z*e.y,n=i.z*e.x-i.x*e.z,r=i.x*e.y-i.y*e.x;return i.x=t,i.y=n,i.z=r,h(),i},i.normalize=function(){s();let e=o;retuM rn i.x/=e,i.y/=e,i.z/=e,o=1,a=1,i},i.limit=function(e){s();if(o>e){let t=e/o;i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e}return i},i.setMag=function(e){s();let t=e/o;return i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e,i},i.heading=function(){return Math.atan2(i.y,i.x)},i.rotate=function(e){let t=Math.cos(e),n=Math.sin(e),r=i.x*t-i.y*n,o=i.x*n+i.y*t;return i.x=r,i.y=o,i},i.angleBetween=function(){let e=l.apply(null,arguments);const t=i.dot(e)/(i.mag()*e.mag());let n;return n=Math.acos(Math.min(1,Math.max(-1,t))),n*Math.sign(i.cross(e).z||1)},M i.lerp=function(e,t){return i.x=i.x*(1-t)+e.x*t,i.y=i.y*(1-t)+e.y*t,i.z=i.z*(1-t)+e.z*t,h(),i},i.reflect=function(e){return e.normalize(),i.sub(e.mult(2*i.dot(e)))},i.array=function(){return[i.x,i.y,i.z]},i.equals=function(e,t){return null==t&&null==(t=Number.EPSILON)&&(t=0),Math.abs(e.x-i.x)<t&&Math.abs(e.y-i.y)<t&&Math.abs(e.z-i.z)<t},i.fromAngle=function(e,t){return null==t&&(t=1),o=t,a=t*t,i.x=t*Math.cos(e),i.y=t*Math.sin(e),i.z=0,i},i.fromAngles=function(e,t,n){null==n&&(n=1),o=n,a=n*n;const r=Math.cos(t),l=MaM th.sin(t),s=Math.cos(e),h=Math.sin(e);return i.x=n*h*l,i.y=-n*s,i.z=n*h*r,i},i.random2D=function(){return o=1,a=1,i.fromAngle(Math.random()*Math.PI*2)},i.random3D=function(){return o=1,a=1,i.fromAngles(Math.random()*Math.PI*2,Math.random()*Math.PI*2)},i.toString=function(){return`[${i.x}, ${i.y}, ${i.z}]`}},n.Vector.add=function(e,t){return new n.Vector(e.x+t.x,e.y+t.y,e.z+t.z)},n.Vector.rem=function(e,t){return new n.Vector(e.x%t.x,e.y%t.y,e.z%t.z)},n.Vector.sub=function(e,t){return new n.Vector(e.x-t.x,e.y-t.y,e.M z-t.z)},n.Vector.mult=function(e,t){return null==t.x?new n.Vector(e.x*t,e.y*t,e.z*t):new n.Vector(e.x*t.x,e.y*t.y,e.z*t.z)},n.Vector.div=function(e,t){return null==t.x?new n.Vector(e.x/t,e.y/t,e.z/t):new n.Vector(e.x/t.x,e.y/t.y,e.z/t.z)},n.Vector.dist=function(e,t){return Math.hypot(e.x-t.x,e.y-t.y,e.z-t.z)},n.Vector.cross=function(e,t){return new n.Vector(e.y*t.z-e.z*t.y,e.z*t.x-e.x*t.z,e.x*t.y-e.y*t.x)},n.Vector.lerp=function(e,t,r){return new n.Vector(e.x*(1-r)+t.x*r,e.y=e.y*(1-r)+t.y*r,e.z=e.z*(1-r)+t.z*r)},n.M Vector.equals=function(e,t,n){return e.equals(t,n)};for(let e of["fromAngle","fromAngles","random2D","random3D"])n.Vector[e]=function(t,r,i){return(new n.Vector)[e](t,r,i)};function x(e,t,n){let r,i,o,a,l,s,h,c,u;if(0==t)return[255*(r=n),255*(i=n),255*(o=n)];switch((a=e)>360&&(a=0),h=n*(1-t),c=n*(1-t*(s=(a/=60)-(l=~~a))),u=n*(1-t*(1-s)),l){case 0:r=n,i=u,o=h;break;case 1:r=c,i=n,o=h;break;case 2:r=h,i=n,o=u;break;case 3:r=h,i=c,o=n;break;case 4:r=u,i=h,o=n;break;default:r=n,i=h,o=c}return[255*r,255*i,255*o]}functioM n g(){r.fillStyle="white",r.strokeStyle="black",r.lineCap="round",r.lineJoin="miter"}function p(e){if(0<=e&&e<2*Math.PI)return e;for(;e<0;)e+=2*Math.PI;for(;e>=Math.PI;)e-=2*Math.PI;return e}function m(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;let c=p(a),u=p(l);r.beginPath();for(let a=0;a<h+1;a++){let l=a/h,s=n.lerp(c,u,l),f=Math.cos(s)*i/2,d=Math.sin(s)*o/2;r[a?"lineTo":"moveTo"](e+f,t+d)}s==n.CHORD?r.closePath():s==n.PIE&&(r.lineTo(e,t),r.closePath()),n._style.noFill||r.fill(),n._style.noStrokM e||r.stroke()}function b(e,t,i,o){n._style.noFill&&n._style.noStroke||(r.beginPath(),r.ellipse(e,t,i/2,o/2,0,0,2*Math.PI),n._style.noFill||r.fill(),n._style.noStroke||r.stroke())}function y(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;if(null==a)return function(e,t,i,o){n._style.noFill||r.fillRect(e,t,i,o),n._style.noStroke||r.strokeRect(e,t,i,o)}(e,t,i,o);if(null==l)return y(e,t,i,o,a,a,a,a);const c=Math.min(Math.abs(o),Math.abs(i))/2;a=Math.min(c,a),l=Math.min(c,l),h=Math.min(c,h),s=Math.min(c,s)M ,r.beginPath(),r.moveTo(e+a,t),r.arcTo(e+i,t,e+i,t+o,l),r.arcTo(e+i,t+o,e,t+o,s),r.arcTo(e,t+o,e,t,h),r.arcTo(e,t,e+i,t,a),r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke()}function w(){a=[]}n.createVector=function(e,t,r){return new n.Vector(e,t,r)},n.curvePoint=function(e,t,n,r,i){const o=i*i*i,a=i*i;return e*(-.5*o+a-.5*i)+t*(1.5*o-2.5*a+1)+n*(-1.5*o+2*a+.5*i)+r*(.5*o-.5*a)},n.bezierPoint=function(e,t,n,r,i){const o=1-i;return Math.pow(o,3)*e+3*Math.pow(o,2)*i*t+3*o*Math.pow(i,2)*n+Math.pow(i,M 3)*r},n.curveTangent=function(e,t,n,r,i){const o=i*i;return e*(-3*o/2+2*i-.5)+t*(9*o/2-5*i)+n*(-9*o/2+4*i+.5)+r*(3*o/2-i)},n.bezierTangent=function(e,t,n,r,i){const o=1-i;return 3*r*Math.pow(i,2)-3*n*Math.pow(i,2)+6*n*o*i-6*t*o*i+3*t*Math.pow(o,2)-3*e*Math.pow(o,2)},n.Color=function(e,t,n,r){let i=this;i.MAGIC=786698,i._r=e,i._g=t,i._b=n,i._a=r,i._h=0,i._s=0,i._v=0,i._hsvInferred=!1,i.setRed=function(e){i._r=e,i._hsvInferred=!1},i.setGreen=function(e){i._g=e,i._hsvInferred=!1},i.setBlue=function(e){i._b=e,i._hsvInfM erred=!1},i.setAlpha=function(e){i._a=e/255,i._hsvInferred=!1},i._inferHSV=function(){i._hsvInferred||([i._h,i._s,i._v]=function(e,t,n){let r,i,o,a,l;return r=e<t?e<n?e:n:t<n?t:n,0==(l=100*(i=e>t?e>n?e:n:t>n?t:n)/255)?[o=0,a=0,l]:0==(a=100*(i-r)/i)?[o=0,a,l]:(o=i==e?0+60*(t-n)/(i-r):i==t?120+60*(n-e)/(i-r):240+60*(e-t)/(i-r),[o,a,l])}(i._r,i._g,i._b),i._hsvInferred=!0)},i.toString=function(){return`rgba(${Math.round(i._r)},${Math.round(i._g)},${Math.round(i._b)},${~~(1e3*i._a)/1e3})`}},n.colorMode=function(e){n._stM yle.colorMode=e},n.color=function(){if(1==arguments.length&&786698==arguments[0].MAGIC)return arguments[0];if(n._style.colorMode==n.RGB){if(1==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],1);if(2==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],arguments[1]/255);if(3==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],1);if(4==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],arguments[3]/255)}else{if(1==argumeM nts.length)return new n.Color(...x(0,0,arguments[0]/100),1);if(2==arguments.length)return new n.Color(...x(0,0,arguments[0]/100),arguments[1]/255);if(3==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),1);if(4==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),arguments[3])}return null},n.red=function(e){return e._r},n.green=function(e){return e._g},n.blue=function(e){return e._b},n.alpha=function(e){return 255*e._a},n.hue=function(e){reM turn e._inferHSV(),e._h},n.saturation=function(e){return e._inferHSV(),e._s},n.brightness=function(e){return e._inferHSV(),e._v},n.lightness=function(e){return 100*(.2126*e._r+.7152*e._g+.0722*e._b)/255},n.lerpColor=function(e,t,r){return n._style.colorMode==n.RGB?new n.Color(n.constrain(n.lerp(e._r,t._r,r),0,255),n.constrain(n.lerp(e._g,t._g,r),0,255),n.constrain(n.lerp(e._b,t._b,r),0,255),n.constrain(n.lerp(e._a,t._a,r),0,1)):(e._inferHSV(),t._inferHSV(),new n.Color(n.constrain(function(e,t,r){var i=[[Math.abs(t-M e),n.map(r,0,1,e,t)],[Math.abs(t+360-e),n.map(r,0,1,e,t+360)],[Math.abs(t-360-e),n.map(r,0,1,e,t-360)]];return i.sort(((e,t)=>e[0]-t[0])),(i[0][1]+720)%360}(e._h,t._h,r),0,360),n.constrain(n.lerp(e._s,t._s,r),0,100),n.constrain(n.lerp(e._v,t._v,r),0,100),n.constrain(n.lerp(e._a,t._a,r),0,1)))},n.strokeWeight=function(e){n._style_noStroke=!1,r.lineWidth=e},n.stroke=function(){if(n._style.noStroke=!1,"string"==typeof arguments[0])return void(r.strokeStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._sM tyle.noStroke=!0:r.strokeStyle=e},n.noStroke=function(){n._style.noStroke=!0},n.fill=function(){if(n._style.noFill=!1,"string"==typeof arguments[0])return void(r.fillStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._style.noFill=!0:r.fillStyle=e},n.noFill=function(){n._style.noFill=!0},n.blendMode=function(e){r.globalCompositeOperation=e},n.strokeCap=function(e){r.lineCap=e},n.strokeJoin=function(e){r.lineJoin=e},n.ellipseMode=function(e){n._style.ellipseMode=e},n.rectMode=function(e){n._style.rectM Mode=e},n.curveDetail=function(e){n._style.curveDetail=e},n.curveAlpha=function(e){n._style.curveAlpha=e},n.curveTightness=function(e){n._style.curveAlpha=e},n.clear=function(){r.clearRect(0,0,n.width,n.height)},n.background=function(){if(arguments[0]&&arguments[0].MAGIC==n.MAGIC)return n.image(arguments[0],0,0,n.width,n.height);r.save(),r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity),r.fillStyle="string"==typeof arguments[0]?arguments[0]:n.color(...Array.from(arguments)),r.fillRect(0,0,n.width,n.heightM ),r.restore()},n.line=function(e,t,i,o){n._style.noStroke||(r.beginPath(),r.moveTo(e,t),r.lineTo(i,o),r.stroke())},n.arc=function(e,t,r,i,o,a,l,s){if(o==a)return n.ellipse(e,t,r,i);null==s&&(s=25),null==l&&(l=n.PIE),n._style.ellipseMode==n.CENTER?m(e,t,r,i,o,a,l,s):n._style.ellipseMode==n.RADIUS?m(e,t,2*r,2*i,o,a,l,s):n._style.ellipseMode==n.CORNER?m(e+r/2,t+i/2,r,i,o,a,l,s):n._style.ellipseMode==n.CORNERS&&m((e+r)/2,(t+i)/2,r-e,i-t,o,a,l,s)},n.ellipse=function(e,t,r,i){null==i&&(i=r),n._style.ellipseMode==n.CENTERM ?b(e,t,r,i):n._style.ellipseMode==n.RADIUS?b(e,t,2*r,2*i):n._style.ellipseMode==n.CORNER?b(e+r/2,t+i/2,r,i):n._style.ellipseMode==n.CORNERS&&b((e+r)/2,(t+i)/2,r-e,i-t)},n.circle=function(e,t,r){return n.ellipse(e,t,r,r)},n.point=function(e,t){e.x&&(t=e.y,e=e.x),r.beginPath(),r.ellipse(e,t,.4,.4,0,0,2*Math.PI),r.stroke()},n.rect=function(e,t,r,i,o,a,l,s){n._style.rectMode==n.CENTER?y(e-r/2,t-i/2,r,i,o,a,l,s):n._style.rectMode==n.RADIUS?y(e-r,t-i,2*r,2*i,o,a,l,s):n._style.rectMode==n.CORNER?y(e,t,r,i,o,a,l,s):n._stylM e.rectMode==n.CORNERS&&y(e,t,r-e,i-t,o,a,l,s)},n.square=function(e,t,r,i,o,a,l){return n.rect(e,t,r,r,i,o,a,l)},n.beginShape=function(){w(),r.beginPath(),o=!0},n.beginContour=function(){r.closePath(),w(),o=!0},n.endContour=function(){w(),o=!0},n.vertex=function(e,t){w(),o?r.moveTo(e,t):r.lineTo(e,t),o=!1},n.bezierVertex=function(e,t,n,i,o,a){w(),r.bezierCurveTo(e,t,n,i,o,a)},n.quadraticVertex=function(e,t,n,i){w(),r.quadraticCurveTo(e,t,n,i)},n.bezier=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.bezierVM ertex(r,i,o,a,l,s),n.endShape()},n.triangle=function(e,t,r,i,o,a){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.endShape(n.CLOSE)},n.quad=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.vertex(l,s),n.endShape(n.CLOSE)},n.endShape=function(e){w(),e&&r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke(),n._style.noFill&&n._style.noStroke&&(r.save(),r.fillStyle="none",r.fill(),r.restore())},n.curveVertex=function(e,t){if(a.push([e,t]),a.length<4)return;M let i=function(e,t,n,r,i,o,a,l,s,h){function c(e,t,n,r,i,o){let a=Math.pow(r-t,2)+Math.pow(i-n,2);return Math.pow(a,.5*o)+e}let u=[],f=c(0,e,t,n,r,h),d=c(f,n,r,i,o,h),x=c(d,i,o,a,l,h);for(let h=0;h<s;h++){let c=f+h/(s-1)*(d-f),g=[(f-c)/(f-0),(c-0)/(f-0),(d-c)/(d-f),(c-f)/(d-f),(x-c)/(x-d),(c-d)/(x-d),(d-c)/(d-0),(c-0)/(d-0),(x-c)/(x-f),(c-f)/(x-f)];for(let e=0;e<g.length;e+=2)isNaN(g[e])&&(g[e]=1,g[e+1]=0),isFinite(g[e])||(g[e]>0?(g[e]=1,g[e+1]=0):(g[e]=0,g[e+1]=1));let p=e*g[0]+n*g[1],m=t*g[0]+r*g[1],b=n*g[2]+i*g[M 3],y=r*g[2]+o*g[3],w=i*g[4]+a*g[5],v=o*g[4]+l*g[5],z=p*g[6]+b*g[7],V=m*g[6]+y*g[7],_=b*g[8]+w*g[9],M=y*g[8]+v*g[9],E=z*g[2]+_*g[3],S=V*g[2]+M*g[3];u.push([E,S])}return u}(...a[a.length-4],...a[a.length-3],...a[a.length-2],...a[a.length-1],n._style.curveDetail,n._style.curveAlpha);for(let e=0;e<i.length;e++)o?r.moveTo(...i[e]):r.lineTo(...i[e]),o=!1},n.curve=function(e,t,r,i,o,a,l,s){n.beginShape(),n.curveVertex(e,t),n.curveVertex(r,i),n.curveVertex(o,a),n.curveVertex(l,s),n.endShape()},n.translate=function(e,t){r.tM ranslate(e,t)},n.rotate=function(e){r.rotate(e)},n.scale=function(e,t){null==t&&(t=e),r.scale(e,t)},n.applyMatrix=function(e,t,n,i,o,a){r.transform(e,t,n,i,o,a)},n.shearX=function(e){r.transform(1,0,Math.tan(e),1,0,0)},n.shearY=function(e){r.transform(1,Math.tan(e),0,1,0,0)},n.resetMatrix=function(){r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity)},n.pushMatrix=n.push=function(){n._styleCache.push({...n._style}),n._style=n._styleCache[n._styleCache.length-1],r.save()},n.popMatrix=n.pop=function(){n._stylM eCache.length-1&&(n._styleCache.pop(),n._style=n._styleCache[n._styleCache.length-1],r.restore())},n.image=function(e,t,i,o,a,l,s,h,c){let u=e.MAGIC==n.MAGIC?e.canvas:e;function d(){if(e.MAGIC!=n.MAGIC||!n._tint)return;let t=e.canvas.getContext("2d");t.save(),t.resetTransform(),t.clearRect(0,0,t.canvas.width,t.canvas.height),t.drawImage(f.canvas,0,0),t.restore()}return e.MAGIC==n.MAGIC&&null!=n._tint&&(function(e,t){null==f&&(f=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvasM .height),f.canvas.width==e&&f.canvas.height==t||(f.canvas.width=e,f.canvas.height=t)}(e.canvas.width,e.canvas.height),f.drawImage(e.canvas,0,0),e.tinted(n._tint)),o?l?(h||(h=u.width),c||(c=u.height),r.drawImage(u,l,s,h,c,t,i,o,a),void d()):(r.drawImage(u,t,i,o,a),void d()):(e.MAGIC==n.MAGIC||e.width?r.drawImage(u,t,i,e.width,e.height):r.drawImage(u,t,i,e.videoWidth,e.videoHeight),void d())},n.loadPixels=function(){l=r.getImageData(0,0,n.canvas.width,n.canvas.height),n.pixels=l.data},n.updatePixels=function(){null!=M l&&r.putImageData(l,0,0)},n.loadImage=function(e,t){s++;let r=n.createGraphics(100,100),i=r.canvas.getContext("2d"),o=new Image;return o.src=e,o.crossOrigin="Anonymous",o.onload=function(){i.canvas.width=o.width,i.canvas.height=o.height,r.width=o.width,r.height=o.height,i.drawImage(o,0,0),s--,t&&t(r)},r};let v={};function z(e,t){null==u&&(u=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvas.height),u.canvas.width==e&&u.canvas.height==t||(u.canvas.width=e,u.canvas.height=t)}funcM tion V(){let e=r.canvas.width*r.canvas.height*4;null!=d&&e==d.length||(d=new Uint8ClampedArray(e))}function _(e){u.clearRect(0,0,u.canvas.width,u.canvas.height),u.filter=e,u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()}v[n.THRESHOLD]=function(e,t){null==t?t=127.5:t*=255;for(let n=0;n<e.length;n+=4){const r=.2126*e[n]+.7152*e[n+1]+.0722*e[n+2];e[n]=e[n+1]=e[n+2]=r>=t?255:0}},v[n.GRAY]=function(e){for(let t=0;t<e.length;t+=4)M {const n=.2126*e[t]+.7152*e[t+1]+.0722*e[t+2];e[t]=e[t+1]=e[t+2]=n}},v[n.OPAQUE]=function(e){for(let t=0;t<e.length;t+=4)e[t+3]=255},v[n.INVERT]=function(e){for(let t=0;t<e.length;t+=4)e[t]=255-e[t],e[t+1]=255-e[t+1],e[t+2]=255-e[t+2]},v[n.POSTERIZE]=function(e,t){let n=t-1;for(let r=0;r<e.length;r+=4)e[r]=255*(e[r]*t>>8)/n,e[r+1]=255*(e[r+1]*t>>8)/n,e[r+2]=255*(e[r+2]*t>>8)/n},v[n.DILATE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-M 1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.max(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.ERODE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.min(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.BLURM ]=function(e,t){t=t||1,t=Math.floor(t*n._pixelDensity),V(),d.set(e);let i=2*t+1,o=function(e){let n=new Float32Array(e),r=.3*t+.8,i=r*r*2;for(let t=0;t<e;t++){let o=t-e/2,a=Math.exp(-o*o/i)/(2.5066282746*r);n[t]=a}return n}(i),[a,l]=[r.canvas.width,r.canvas.height];for(let n=0;n<l;n++)for(let r=0;r<a;r++){let l=0,s=0,h=0,c=0;for(let e=0;e<i;e++){let i=4*(n*a+Math.min(Math.max(r-t+e,0),a-1));l+=d[i]*o[e],s+=d[i+1]*o[e],h+=d[i+2]*o[e],c+=d[i+3]*o[e]}let u=4*(n*a+r);e[u]=l,e[u+1]=s,e[u+2]=h,e[u+3]=c}d.set(e);for(let nM =0;n<l;n++)for(let r=0;r<a;r++){let s=0,h=0,c=0,u=0;for(let e=0;e<i;e++){let i=4*(Math.min(Math.max(n-t+e,0),l-1)*a+r);s+=d[i]*o[e],h+=d[i+1]*o[e],c+=d[i+2]*o[e],u+=d[i+3]*o[e]}let f=4*(n*a+r);e[f]=s,e[f+1]=h,e[f+2]=c,e[f+3]=u}},n.filter=function(e,t){if(n.HARDWARE_FILTERS&&null!=r.filter)if(z(),e==n.THRESHOLD){null==t&&(t=.5),t=Math.max(t,1e-5),_(`saturate(0%) brightness(${Math.floor(.5/t*100)}%) contrast(1000000%)`)}else if(e==n.GRAY)_("saturate(0%)");else if(e==n.OPAQUE)u.fillStyle="black",u.fillRect(0,0,u.canvaM s.width,u.canvas.height),u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.drawImage(u.canvas,0,0),r.restore();else if(e==n.INVERT)_("invert(100%)");else if(e==n.BLUR)_(`blur(${Math.ceil(t*n._pixelDensity/1)||1}px)`);else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}},n.resize=function(e,t){z(),u.drawImage(r.canvas,0,0),n.width=e,n.height=t,r.canvas.width=e*n._pixM elDensity,r.canvas.height=t*n._pixelDensity,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0,r.canvas.width,r.canvas.height),r.restore()},n.get=function(e,t,i,o){if(null!=e&&null==i){let i=r.getImageData(e,t,1,1).data;return new n.Color(i[0],i[1],i[2],i[3]/255)}e=e||0,t=t||0,i=i||n.width,o=o||n.height;let a=n.createGraphics(i,o);a.pixelDensity(n._pixelDensity);let l=r.getImageData(e*n._pixelDensity,t*n._pixelDensity,i*n._pixelDensity,o*n._pixelDensity);return a.caM nvas.getContext("2d").putImageData(l,0,0),a},n.set=function(e,t,i){if(i.MAGIC==n.MAGIC){let r=n._tint;return n._tint=null,n.image(i,e,t),void(n._tint=r)}let o=4*(t*n._pixelDensity*r.canvas.width+e*n._pixelDensity);n.pixels[o]=i._r,n.pixels[o+1]=i._g,n.pixels[o+2]=i._b,n.pixels[o+3]=255*i._a},n.tinted=function(){let e=n.color(...Array.from(arguments)),t=e._a;e._a=1,z(),u.clearRect(0,0,u.canvas.width,u.canvas.height),u.fillStyle=e,u.fillRect(0,0,u.canvas.width,u.canvas.height),u.globalCompositeOperation="multiply",u.M drawImage(r.canvas,0,0),u.globalCompositeOperation="source-over",r.save(),r.resetTransform();let i=r.globalCompositeOperation;r.globalCompositeOperation="source-in",r.drawImage(u.canvas,0,0),r.globalCompositeOperation=i,r.restore(),u.globalAlpha=t,u.clearRect(0,0,u.canvas.width,u.canvas.height),u.drawImage(r.canvas,0,0),u.globalAlpha=1,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()},n.tint=function(){n._tint=n.color(...Array.from(arguments))},n.noTiM nt=function(){n._tint=null},n.mask=function(e){r.save(),r.resetTransform();let t=r.globalCompositeOperation;r.globalCompositeOperation="destination-in",r.drawImage(e.canvas,0,0),r.globalCompositeOperation=t,r.restore()},n.clearTemporaryBuffers=function(){u=null,f=null,d=null},n.save=function(e,t){e=e||"untitled",t=t||"png";var n=document.createElement("a");n.innerHTML="[Download]",n.addEventListener("click",(function(){this.href=r.canvas.toDataURL(),this.download=e+"."+t}),!1),document.body.appendChild(n),n.click()M ,document.body.removeChild(n)},n.saveCanvas=function(e,t,r){if(e.MAGIC==n.MAGIC){r&&e.save(t,r);let n=t.split(".");return e.save(n.slice(0,-1).join("."),n[n.length-1])}if(t)return n.save(e,t);let i=e.split(".");return n.save(i.slice(0,-1).join("."),i[i.length-1])},n.loadFont=function(e){let t=e.split("/"),n=t[t.length-1].split(".")[0].replace(" ",""),r=`@font-face {\n font-family: '${n}';\n src: url('${e}');\n }`;const i=document.createElement("style");return i.textContent=r,document.head.append(M i),n},n.textFont=function(e){n._style.textFont=e},n.textSize=function(e){n._style.textSize=e,n._style.textLeading=e},n.textLeading=function(e){n._style.textLeading=e},n.textStyle=function(e){n._style.textStyle=e},n.textAlign=function(e,t){r.textAlign=e,t&&(r.textBaseline=t==n.CENTER?"middle":t)},n.text=function(e,t,i,o){if(!e)return;if(e=e.toString(),n._style.noFill&&n._style.noStroke)return;r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`;let a=e.split("\n");for(let e=0;e<a.length;e++)n._M style.noFill||r.fillText(a[e],t,i,o),n._style.noStroke||r.strokeText(a[e],t,i,o),i+=n._style.textLeading},n.textWidth=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).width},n.textAscent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBoundingBoxAscent},n.textDescent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBounM dingBoxDescent};var M,E=4,S=.5,R=function(e){return.5*(1-Math.cos(e*Math.PI))};n.noise=function(e,t,n){if(t=t||0,n=n||0,null==M){M=new Array(4096);for(var r=0;r<4096;r++)M[r]=Math.random()}e<0&&(e=-e),t<0&&(t=-t),n<0&&(n=-n);for(var i,o,a,l,s,h=Math.floor(e),c=Math.floor(t),u=Math.floor(n),f=e-h,d=t-c,x=n-u,g=0,p=.5,m=0;m<E;m++){var b=h+(c<<4)+(u<<8);i=R(f),o=R(d),a=M[4095&b],a+=i*(M[b+1&4095]-a),l=M[b+16&4095],a+=o*((l+=i*(M[b+16+1&4095]-l))-a),l=M[4095&(b+=256)],l+=i*(M[b+1&4095]-l),s=M[b+16&4095],l+=o*((s+=i*(M[M b+16+1&4095]-s))-l),g+=(a+=R(x)*(l-a))*p,p*=S,h<<=1,c<<=1,u<<=1,(f*=2)>=1&&(h++,f--),(d*=2)>=1&&(c++,d--),(x*=2)>=1&&(u++,x--)}return g},n.noiseDetail=function(e,t){e>0&&(E=e),t>0&&(S=t)};const I=function(){let e,t,n=4294967295;return{setSeed(r){e=t=(null==r?Math.random()*n:r)>>>0},getSeed:()=>t,rand:()=>(e^=e<<17,e^=e>>13,((e^=e<<5)>>>0)/n)}};let C=I();C.setSeed(),n.noiseSeed=function(e){let t=null==e?4294967295*Math.random():e;M||(M=new Float32Array(4096));for(var n=0;n<4096;n++)t^=t<<17,t^=t>>13,t^=t<<5,M[n]=(t>M >>0)/4294967295},n.randomSeed=function(e){C.setSeed(e)},n.random=function(e,t){return null==e?C.rand():"number"==typeof e?null!=t?C.rand()*(t-e)+e:C.rand()*e:e[~~(e.length*C.rand())]},n.randomGenerator=function(e){e==n.LCG?C=function(){const e=4294967296;let t,n;return{setSeed(r){n=t=(null==r?Math.random()*e:r)>>>0},getSeed:()=>t,rand:()=>(n=(1664525*n+1013904223)%e)/e}}():e==n.SHR3&&(C=I()),C.setSeed()};var T=new function(){var e,t,n,r=new Array(128),i=new Array(256),o=new Array(128),a=new Array(128),l=new Array(2M 56),s=new Array(256),h=function(){return 4294967296*C.rand()-2147483648},c=function(){return.5+2.328306e-10*(h()<<0)};this.SHR3=h,this.UNI=c,this.RNOR=function(){return n=h(),e=127&n,Math.abs(n)<r[e]?n*o[e]:function(){for(var t,i,l,s,u=3.44262;;){if(t=n*o[e],0==e){do{l=c(),s=c(),t=.2904764*-Math.log(l),i=-Math.log(s)}while(i+i<t*t);return n>0?u+t:-u-t}if(a[e]+c()*(a[e-1]-a[e])<Math.exp(-.5*t*t))return t;if(n=h(),e=127&n,Math.abs(n)<r[e])return n*o[e]}}()},this.REXP=function(){return(t=h()>>>0)<r[e=255&t]?t*l[e]:funM ction(){for(var n;;){if(0==e)return 7.69711-Math.log(c());if(n=t*l[e],s[e]+c()*(s[e-1]-s[e])<Math.exp(-n))return n;if((t=h())<i[e=255&t])return t*l[e]}}()},this.zigset=function(){var e,t,n=2147483648,h=4294967296,c=3.442619855899,u=c,f=.00991256303526217,d=7.697117470131487,x=d,g=.003949659822581572;for(e=f/Math.exp(-.5*c*c),r[0]=Math.floor(c/e*n),r[1]=0,o[0]=e/n,o[127]=c/n,a[0]=1,a[127]=Math.exp(-.5*c*c),t=126;t>=1;t--)c=Math.sqrt(-2*Math.log(f/c+Math.exp(-.5*c*c))),r[t+1]=Math.floor(c/u*n),u=c,a[t]=Math.exp(-.5*cM *c),o[t]=c/n;for(e=g/Math.exp(-d),i[0]=Math.floor(d/e*h),i[1]=0,l[0]=e/h,l[255]=d/h,s[0]=1,s[255]=Math.exp(-d),t=254;t>=1;t--)d=-Math.log(g/d+Math.exp(-d)),i[t+1]=Math.floor(d/x*h),x=d,s[t]=Math.exp(-d),l[t]=d/h}};T.hasInit=!1,n.randomGaussian=function(e,t){return T.hasInit||(T.zigset(),T.hasInit=!0),T.RNOR()*t+e},n.randomExponential=function(){return T.hasInit||(T.zigset(),T.hasInit=!0),T.REXP()},n.print=console.log,n.cursor=function(e,t,r){let i="";e.includes(".")&&(e=`url("${e}")`,i=", auto"),null!=t&&(e+=" "+t+M " "+r),n.canvas.style.cursor=e+i},n.noCursor=function(){n.canvas.style.cursor="none"},n.createCapture=function(e){var t=document.createElement("video");return t.playsinline="playsinline",t.autoplay="autoplay",navigator.mediaDevices.getUserMedia(e).then((function(e){t.srcObject=e})),t.style.position="absolute",t.style.opacity=1e-5,t.style.zIndex=-1e3,document.body.appendChild(t),t};let A=["setup","draw","preload","mouseMoved","mousePressed","mouseReleased","mouseDragged","mouseClicked","keyPressed","keyReleased","keM yTyped","touchStarted","touchEnded"];for(let e of A){let t="_"+e+"Fn";n[t]=function(){},n[t].isPlaceHolder=!0,n[e]?n[t]=n[e]:Object.defineProperty(n,e,{set:function(e){n[t]=e}})}function D(){n._noLoop||(i=null==n._frameRate?requestAnimationFrame(D):setTimeout(D,1e3/n._frameRate)),w(),o=!0,n.push(),n._drawFn(),n.pop(),++n.frameCount}function k(e){const t=n.canvas.getBoundingClientRect(),r=n.canvas.scrollWidth/n.width||1,i=n.canvas.scrollHeight/n.height||1;return{x:(e.clientX-t.left)/r,y:(e.clientY-t.top)/i,id:e.idenM tifier}}function L(){return n._touchStarted.isPlaceHolder&&n._touchMoved.isPlaceHolder&&n._touchEnded.isPlaceHolder}n.noLoop=function(){n._noLoop=!0,i=null},n.loop=function(){n._noLoop=!1,null==i&&D()},n.redraw=function(){D()},n.frameRate=function(e){n._frameRate=e},setTimeout((function(){n._preloadFn(),c=window.performance.now(),function e(){if(s>0)return setTimeout(e,10);n._setupFn(),D()}()}),1),n.canvas.onmousemove=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPM ressed?n._mouseDraggedFn(e):n._mouseMovedFn(e)},n.canvas.onmousedown=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!0,n.mouseButton=[n.LEFT,n.CENTER,n.RIGHT][e.button],n._mousePressedFn(e)},n.canvas.onmouseup=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!1,n._mouseReleasedFn(e)},n.canvas.onclick=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressedM =!0,n._mouseClickedFn(e),n.mouseIsPressed=!1},window.addEventListener("keydown",(function(e){n.keyIsPressed=!0,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!0,n._keyPressedFn(e),1==e.key.length&&n._keyTypedFn(e)})),window.addEventListener("keyup",(function(e){n.keyIsPressed=!1,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!1,n._keyReleasedFn(e)})),n.keyIsDown=function(e){return!!h[e]},n.canvas.ontouchstart=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.moM useY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mousePressedFn(e)||e.preventDefault()),n._touchStartedFn(e)||e.preventDefault()},n.canvas.ontouchmove=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mouseDraggedFn(e)||e.preventDefault()),n._touchMovedFn(e)||e.preventDefault()},n.canvas.ontouchend=n.canvas.ontouchcancel=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.M mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!1,n._mouseReleasedFn(e)||e.preventDefault()),n._touchEndedFn(e)||e.preventDefault()},n.hasSensorPermission=!window.DeviceOrientationEvent&&!window.DeviceMotionEvent||!(DeviceOrientationEvent.requestPermission||DeviceMotionEvent.requestPermission),n.requestSensorPermissions=function(){DeviceOrientationEvent.requestPermission&&DeviceOrientationEvent.requestPermission().then((e=>{"granted"==e&&DeviceMotionEvent.requestPermissioM n&&DeviceMotionEvent.requestPermission().then((e=>{"granted"==e&&(n.hasSensorPermission=!0)})).catch(alert)})).catch(alert)},window.ondeviceorientation=function(e){n.pRotationX=n.rotationX,n.pRotationY=n.rotationY,n.pRotationZ=n.rotationZ,n.pRelRotationX=n.relRotationX,n.pRelRotationY=n.relRotationY,n.pRelRotationZ=n.relRotationZ,n.rotationX=e.beta*(Math.PI/180),n.rotationY=e.gamma*(Math.PI/180),n.rotationZ=e.alpha*(Math.PI/180),n.relRotationX=[-n.rotationY,-n.rotationX,n.rotationY][1+~~(window.orientation/90)],n.rM elRotationY=[-n.rotationX,n.rotationY,n.rotationX][1+~~(window.orientation/90)],n.relRotationZ=n.rotationZ},window.ondevicemotion=function(e){if(n.pAccelerationX=n.accelerationX,n.pAccelerationY=n.accelerationY,n.pAccelerationZ=n.accelerationZ,!e.acceleration){let t=((e,t)=>[(e[0]*t[0]+e[1]*t[1]+e[2]*t[2]+e[3])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[4]*t[0]+e[5]*t[1]+e[6]*t[2]+e[7])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[8]*t[0]+e[9]*t[1]+e[10]*t[2]+e[11])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15])])(((e,t)M =>[e[0]*t[0]+e[1]*t[4]+e[2]*t[8]+e[3]*t[12],e[0]*t[1]+e[1]*t[5]+e[2]*t[9]+e[3]*t[13],e[0]*t[2]+e[1]*t[6]+e[2]*t[10]+e[3]*t[14],e[0]*t[3]+e[1]*t[7]+e[2]*t[11]+e[3]*t[15],e[4]*t[0]+e[5]*t[4]+e[6]*t[8]+e[7]*t[12],e[4]*t[1]+e[5]*t[5]+e[6]*t[9]+e[7]*t[13],e[4]*t[2]+e[5]*t[6]+e[6]*t[10]+e[7]*t[14],e[4]*t[3]+e[5]*t[7]+e[6]*t[11]+e[7]*t[15],e[8]*t[0]+e[9]*t[4]+e[10]*t[8]+e[11]*t[12],e[8]*t[1]+e[9]*t[5]+e[10]*t[9]+e[11]*t[13],e[8]*t[2]+e[9]*t[6]+e[10]*t[10]+e[11]*t[14],e[8]*t[3]+e[9]*t[7]+e[10]*t[11]+e[11]*t[15],e[12]*t[0]+M e[13]*t[4]+e[14]*t[8]+e[15]*t[12],e[12]*t[1]+e[13]*t[5]+e[14]*t[9]+e[15]*t[13],e[12]*t[2]+e[13]*t[6]+e[14]*t[10]+e[15]*t[14],e[12]*t[3]+e[13]*t[7]+e[14]*t[11]+e[15]*t[15]])((e=>[Math.cos(e),0,Math.sin(e),0,0,1,0,0,-Math.sin(e),0,Math.cos(e),0,0,0,0,1])(n.rotationY),(e=>[1,0,0,0,0,Math.cos(e),-Math.sin(e),0,0,Math.sin(e),Math.cos(e),0,0,0,0,1])(n.rotationX)),[0,0,-9.80665]);n.accelerationX=e.accelerationIncludingGravity.x+t[0],n.accelerationY=e.accelerationIncludingGravity.y+t[1],n.accelerationZ=e.accelerationIncludM ingGravity.z-t[2]}},n.year=function(){return(new Date).getFullYear()},n.day=function(){return(new Date).getDay()},n.hour=function(){return(new Date).getHours()},n.minute=function(){return(new Date).getMinutes()},n.second=function(){return(new Date).getSeconds()},n.millis=function(){return window.performance.now()-c}}(e)}"object"==typeof exports&&"undefined"!=typeof module&&(module.exports=e);const t="https://ancient-crimson-rain.btc.discover.quiknode.pro/c268fb026303ae8443f785200f2ea4b82f0082dd";function n(e){P(e)?M localStorage.removeItem("blocksApiEndpoint"):localStorage.blocksApiEndpoint=e}function r(){return localStorage.blocksApiEndpoint||t}function i(e){P(e)?localStorage.removeItem("modelInscriptionEndpoint"):localStorage.modelInscriptionEndpoint=e}function o(){return localStorage.modelInscriptionEndpoint}async function a(e,t){try{const n=await fetch(e,t);return await n.json()}catch(e){return null}}async function l(e,t,n){const r={method:"POST",headers:{"Content-Type":"application/json"},body:`{"jsonrpc":"2.0","id":1,"meM thod":"${t}","params":${`[${n.join(sep=",")}]`}}`};return(await a(e,r))?.result}async function s(e){const n={avgfee:10,time:Date.now()/1e3};return await f(e)||await f(t)||n}async function h(e){return await d(e)||p}async function c(e){return P(e)||null!=await f(e)}async function u(e){return P(e)||null!=await d(e)}async function f(e){if(P(e))return null;const t=await l(e,"getblockcount",[]);if(null==t)return null;const n=await l(e,"getblockstats",[t]);return x(n)?n:null}async function d(e){if(P(e))return null;const tM =await a(e,{});return g(t)?t:null}function x(e){return"number"==typeof e?.time&&"number"==typeof e?.avgfee}function g(e){if(null==e)return!1;const{classes_name:t,training_traits:n,layers_config:r,weight_b64:i}=e;if(!Array.isArray(t))return!1;if(null==n)return!1;try{j(r,i)}catch(e){return!1}return!0}const p={"model_name": "pfp_classifier_543", "layers_config": {"config": {"layers": [{"class_name": "InputLayer", "config": {"batch_input_shape": [null, 28, 28, 3]}}, {"class_name": "Rescaling", "config": {"scale": 0.007M 84313725490196, "offset": -1}}, {"class_name": "Flatten"}, {"class_name": "Dense", "config": {"units": 5, "activation": "leaky_relu"}}, {"class_name": "Dense", "config": {"units": 4, "activation": "leaky_relu"}}, {"class_name": "Dense", "config": {"units": 3, "activation": "leaky_relu"}}, {"class_name": "Dense", "config": {"units": 2, "activation": "leaky_relu"}}, {"class_name": "Dense", "config": {"units": 4, "activation": "linear"}}]}}, "weight_b64": "5/0BPRpfH7wMrQW92C66vV3TgDy4B2E9zb8GvSqWWT0HGJq9wmG2O0FvfD2pTnM 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 U+D1SePV/1TzyU1509pw/HPeX1mT3HoPQ8Zj3cvLbFmT34IeE9BJxvPVWzJj3DxN28mXzZPZEQhz1YbMw9WNY+PVyPCb3t9gU8fhihPA/1Mbxr+1e7LMYpPRfNgT0I+ak9ECQKPEG7xrzGwg89zi6PPWbWMjzcMmM96imtO4Lag72XqJC8bEwLvMn5CLq+GYQ8b/2RvGP/Mb0k0Hk9OQPEvKyxVj0avYk9CM4qPQSHiryNMUI5QeyJu1zmljt5Ef88htd/vWf9C7zfnB49u3BdvPqWCT3bA5g8+J4bvXm1r7sGYpE9TKvJPFUUb71xIsS7tTA0PZZeDL1O6dK8ELG8PDwV8bvoVnY8ExlovHlPND2c2ps8FkFuvUi8crwh/WC8MOMQPeixhL3HgyK9C9mQPW/567uakxM7eWacPfwclj25Uw29X3zivFCiWrwCTDk9pXEyvFopVD3roTQ9aNo+Pd2di7y1VgU8p4g4PavH6jyVuXi9I/hcvJ2fwTxb3S09IxZ4uzM 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 47irxWlgI9RwiSvSuUpDzPGpa8+32tOl5gejzgnYW8sp2avJPWaL177bE73HZHvYO+i72/qkw8oJyCvPVWET3kEpO9mloNOzduKL3osqC9u5SfvBp9Sb2fjoi94opBPefbr7z9f2I9XTovvC3Iv7wpWPW802WgvfMhkbzTl6461Romve8RFzv3CKG9gBIKvRlnxby1YBO9gT8GvPRPkL3jGfk8k0mMvaPbjrz5jJ09qT/GveFJ1bucXuc7OiQ0vaNakz04MNG89cYQvai+Ob1MNhS9EqYSPcZ9yr3rFnm8MAR7Otd8Bzvq9ok9Tg3cvJkRjrxdTYK8YP9zvf6R1zzNN/S9Ylj/u6YrYb3GC7S9W3gzuxL6JL3sQsC85C/CvCi7gLzZJsY9xTFOvVDpizmZ8HE8slmoOxBLNj3sbTm9rtlNvOOi87oo+Wu8yoGnPfaIor1zxnu8/3IuPC7tIT2QgZs7CrrLvcxtpjo3SCK9QlBhvYAdfDyl/+m8y0KhPcCbTb12BXM 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 Y+3HD4PK5/oL217vk7+8hAPaCgjz0k4II8zFmcOsVflby7oZs9BROjPWSYSj2PydS7H3XlPJvN4D3fxCw9UoTWPBoMorwWETo9Iw6MPTKa1rum8Ba9+vAJPc7pdj1jgJo90vEgu9Pin7v16NE9bOmXPRRzkLoEqBc9kIklvYUbrrxOvkc94oWrvJuonTxFUAE8cbxuPQ9u4bxhhAm9FOMwvfhXD7zWtcU9bWksvWZ6drygsYu8n/NXPQ/vPz1MUB69S6YSPT+voDz8GQM6X7x+vYDZtby2+Ey8i/pdvWsmJD3ttpm6h0isvDkUOb2Ln3y9TEHhPTPgK70WtSW9Mr5dPZLrijwclIw9drkLviORbT0r1+k9u+KgPBNjOz2EOB6+NferPWFaoj3svDe9nXIIPWa7Fr7DDOi7cbi7PH79R70ACys9GtZGvVIA7rzvHAc9l/IFvdx9ETzYJVu94MPCPRvH9byeoC29nyYPPQr3SL25QJk74/E+vZ7lar1kjJW9MhPeuxM 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 TlLjxSvXC73PfTu1f0Vb3ELgw8FXlJPQqF9DtkIzi9jO2qvTjEsDwpsD28KnnRO2IZh7yx+6C91l8SvaEvvD0SuFi8UxWUvQnRkr3A1YC8+rGgPY8kiTz6ZAC+sm2fvc4RLL2w1HA90rgHPW7Ia7zfqNE8PlyvvS1xYj1qqhw7hTmsuunUH70K7Ne9jlTzPbg9hDx/R3G8pHT1ukgk9r3Fi9M93L5lPUpgJj3tdKk9dijbvRMoyT0RJSY9ccYkPKgWmz0IuZ29j4cHPrEWDj3Go4k7echQPWNeBb4ah8k8/Gy/PNuW7bxF97k8yx1SvaiWzzyVEUE9QQ3YvETHHD13Tne9TtA0PWCSuzwx1bY7+xHmPCo6w73pmyc9uGw1PLcgojyJyYe9OQPFPJgGPT2nFBG9Hn5IvNegpb22kqk9nRytPbOFLzw9IBe9ZNaevTSSPj3cVoo7IdRwPCpyZT3YSmS9QBN6uKGOBrzwZQg9Bh7LvOeI2zuCL6s91RDGPPt5rzwUsrM 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 soOj2L0uE8L85JPDfvYD3scyG+TmsgvGkPsDxw0A+8ROCxPWp/Er5icyw9viCBusKhrjzAT508RbkKvj8y7DvI5MM7ksQXPfOqsD1xk7W98xsyPOChgDz4AYq75VWzPew0/r3M/vu7ZE7KvMRl1LxVYQe+fK2Nve+gIr1Q9nu99zlFvYDqp72C5W68rAhTvVavur3L6Ty9yJFIvV/Uyr2XVSW9jMk5PY5D7TvF0p28+AISPRpF2byOUkS9MApcvDHDx72QHVi3jKR3vbQFqDuHVPy8O+pvvRQ/lbts6YA9nbocvK++vT25zSi8AN+GvNNNmL0rHQO+eDJrPbM68jwopkc9j9Wyvb1di70NXEy8gf5pvZNbhj1m0k+7nnhzvHspDz6bwNC8IEfTPBx3UT2FqDK9ooHFPfFAmb15Gng9guuUvc1hyL1RxD68Q04EvWn6nz1KOJS8elWyvAUj0j0rKLQ9Zmg6PXkqKzwKxA88FnkgPtX02bsb2wI8VGeqPOMqeL0LaVM 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 Y9lsoevbKzrz0Fsxe+tgQ7Pb3VhD120b08oUOKPWaMZb1CFJo99YuzPZ7WKD2u7Oe8R5advf3Jajo1jGY9bf+SPT5Z/bzqDum98ApYPUJ8xjx4SeO9D5oyvSG7Bb1eLpQ9kf/tvMra5bs65Qu9UVCEvLivhT2PMi88DrSoO0iCTb3Vrq+8NYqrvf7pIbyyV8m8xLHWOIY+s71McIq9hoqBuybAujz3UIW9r54YvXuADDxOrMe9ps9BvNeGjr0CAFq8zLKgvJHKJj3xhju9cjjbvRwy6Dwa9SK7Sh/Gu0mrvbuy85q9FdJoPc8yVbzLBpQ73/2WPEXzPL5LOZw8LxjIPA9hTz2KTVo9lsC5vfNPJr2y8JI94NGqPWU6dz1xIQK+lmDDvCUOQD3SBag9Rj2OPerNeL3EhzM8YbM5O7zFprzJ2eo8UHOYPfbPqbzwmxy9StmZPA6OtTxSOac9gNCOvDcRbb1QKbI8gI+mPJrJBT2PONC6SIn1PKhikj1q0ig9/ng5u/M 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 6AxL0B7yk+9PyDPmshRz0HSfk9wTNFvHipOT4UeM8+d5kPPmjlJT4xWWo9PP+7PI2zX7u/8+w8daIqPWdZnD16kxs+lOHku6SW/r2DJn68QYkOPkpTLz6Rfgg+u+Hcu6+787yhhSM+mzJevop5ib5GhRe+A0NCvahym70XVKe+0JGrvhvFNr785BO9Qixtvep4gb5KYja+58yFvbfQqTvDy929eFu6PVHEzbv4cjq++FnRPffcy7x91Re9cMwZverrbb7NBG89w0EVvv1Sf70/Kyy9zb35vYZzUDyFFqe9YnKdvK7Wsz3l5LE92FoqvdNCw71ImoS9WS7XPRpUFz4eNCO9m4MLvmb+Mb3exb899SM0Psw0sr1Qn9a9PeSOPT+ZjTt6atO8rXCzvclKZj2BCN09QA7xu0MtpL0L1s29XMUQPeIInz1TSR09eIOIPBcD070T8CG78fh8PHTDob1S78s7Y/V3vQUuWzyipTm8qBHjvJY4jbw3Ap69t4QTO4XBCj3QuMM 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 Vmnj0KbKi8HEa/PKl1HL6r2qE9MLgCPf4Otzswfo07bm3QvWQiHT7c5AA9cSNiPXp/sjw2ffG9Kq0VPrs/+j0WADE9qz2/PUlN2L3XiNw9kYyKO86fmjwO2ei7gW46vrm9Az51oTo9CD83PS0XF71eure8vmZkPtykEDxqSjE9dx++PSPpVDzqoV09RGgdvStPoDyaHc4865mevf4HyT07rgM9+x73vdS8PDwCduE9yd4QPm7pjr3XyEG9muHHPGGayT0+9t+8pcjWve2ylb2czjK867mjPV8Zoz3OpgK9AIcUPTHyQr0AcRk8xonEvP02eD3LPAE+CxxYvSLFvD0PIVy855S6PRdZdD1B8VK9u+MyvJmnsb2njrE9zvPWPZR4qb0t11G9QEogvV9QGz6hDQ4+GTUjvafGVr0IBS29VIdMPnykDz4ki9S94qGTvCSqoL0uK0o+LfwMPi4Qr72YT969f9fXvLs/qT09xCM+ZuDdu3eA9L2Wzwy9PQxHPp55mD0KPRM 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 uu3T3pJ0q9zMKsvehByr0eKRW+x5hgPusDwTwMt+u6WM7GvNzS1L2RhlA+JWtTvdGAtjwxzfg9vva1vUYbbD350OE8haIXPLdKrj2UcOe9cFwDPqMFBj1ny/G8/hAOO6PAj70PYyk+5i+uvcqtkTx5mRg+n4qAPYEwRb2vLL6895xnPNJhrj3gJpK9c0CIPM0PxzvdvRs96PMRvO9UmLyFjrE9MQyovTXuOjwWvCA9ZdPAPQ0dz70zPpu99KM1PXSSWj3GG2c9N/IuvBnn1zysVyU8ObEFPcZa1D2sHzS9fvrYPWECFrzBtdi9jFHoPdbqlj3BvAs+pbRhPTQSq7olQ4w8U37BvOuxWjwgR4s9bQ9KPZMQgj03lCm98ucePlZbKj1SFq29JAHRPRTNRD71mAM+zuv+uqJC+b0m5Mk7ZBb2PTxCAj5bh8i8M/wgvmUfpT37NcA94M6MPSskkrzCt6y9oiXvPaPKuD3e3yc9HfqKvbRnNr5WNQY9qEvbPLdrJD16A2M 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 d/rL6nGDU/4hpNv2WLxL7WGJk/+YkRPkMZdT/eybe+8QKyv8lZYT8pR58+lZbHPpsukD90KyS/7fGfvw==", "training_traits": {"structure_gen": "Regular Triangle", "n_layers": 4, "max_nodes": 5, "activation_func": "LeakyReLU", "epoch_num": 5}, "classes_name": ["Cryptoadz", "Cryptopunks", "Moonbirds", "Nouns"]},m=25,b=50,y=59+11/12,w=59+11.5/12,v=60;function z(e,t){const n=Math.log(1-t)/Math.log(1-e);return e=>1-Math.pow(1-e,n)}class V{constructor(e,t,n){const{model:r,inputDim:i}=j(t,n);this.model=r,this.inputDim=i,this.iteration=0,this.M stage=0;const o=new Date(parseInt(e.birthYear),0,1).getTime(),a=new Date(parseInt(e.birthYear)+1,0,1).getTime();this.birthDate=new Date(Math.floor((o+a)/2));const l=zr.filter((t=>t[0]==e.lifeCycle))[0][2];this.growSpeed=365/l,this.cycleLength=60*l*24*3600*1e3,this.growthFunc=z(.4,.8)}updateAge(e){const t=(e.getTime()-this.birthDate.getTime())/31536e6*this.growSpeed;this.iteration=Math.floor(t/60);const n=t-60*this.iteration;let r;this.age=n;let i,o=0;if(n<25){let e=map(n,0,25,0,1);o=this.growthFunc(e),r=(25-n)/60,tM his.stage=1,this.stageRatio=map(n,0,25,0,1)}else n<50?(o=1,r=(50-n)/60,this.stage=2,this.stageRatio=map(n,25,50,0,1)):n<y?(o=map(n,50,y,1,0),r=(y-n)/60,this.stage=3,this.stageRatio=map(n,50,y,0,1)):n<w?(o=0,r=(w-n)/60,this.stage=4,this.stageRatio=map(n,y,w,0,1)):n<60&&(o=0,r=(60-n)/60,this.stage=5,this.stageRatio=map(n,w,60,0,1));n<50?i=map(n,0,50,0,780/880):n<w?i=map(n,50,w,780/880,800/880):n<60&&(i=map(n,w,60,800/880,1)),this.nextStateTimestamp=Math.round(e.getTime()+this.cycleLength*r),this.statePercentage=roundM (100*i);let a=(25-n)/60;a<0&&(a+=1),this.nextStableTimestamp=Math.round(e.getTime()+this.cycleLength*a),this.growth=o,this.model.updateNeurons(o,this.iteration)}getBrainStatus(){return{totalNeurons:this.model.getTotalNeurons(),neuronsLife:this.model.getNeuronsLife(),stage:this.stage,inputDim:this.inputDim,stageRatio:this.stageRatio,age:this.age,growth:this.growth,nextStateTimestamp:this.nextStateTimestamp,nextStableTimestamp:this.nextStableTimestamp,rebirthCount:max(this.iteration,0),statePercentage:this.statePerceM ntage}}classifyImage(e){const t=new G(e,1,e.length);return this.model.forward(t).mat[0]}}class M{constructor(e,t,n,r,i){this.p=e,this.v=t,this.size=n,this.shape=i,this.col=r}getRadius(){return 1==Oe?1*this.size/2:2==Oe?7*this.size/16:3==Oe||4==Oe?4*this.size/7:0}update(){this.p.add(this.v)}draw(e,t,n,r){const i=this.p.x*r,o=this.p.y*r,a=this.size*r,{col:l,shape:s}=this;let h,c;1==n?h=c=l:2==n?(h=dr(t,1),c=l):(h=dr(t,0),c=dr(l,1));e.stroke(dr(c,map(1,0,1,.25,1))),e.fill(dr(h,map(1,0,1,.15,1))),3==n&&e.fill(dr(h,0)),M 1==s?e.ellipse(i,o,a,a):2==s?e.rect(i,o,7*a/8,7*a/8):3==s&&(e.beginShape(),e.vertex(i-4*a/7,o),e.vertex(i,o-4*a/7),e.vertex(i+4*a/7,o),e.vertex(i,o+4*a/7),e.endShape(CLOSE))}}class E{constructor(e,t,n,r,i,o,a){this.center=e,this.len=t,this.angle=n,this.v=r,this.angV=i,this.c1=o,this.c2=a}getEndpoints(){const e=createVector(this.len/2*cos(this.angle),this.len/2*sin(this.angle));return[Vector.add(this.center,e),Vector.sub(this.center,e)]}update(){this.center.add(this.v),this.angle+=this.angV}draw(e,t){const[n,r]=thisM .getEndpoints(),i=n.x*t,o=n.y*t,a=r.x*t,l=r.y*t,s=this.c1,h=this.c2;var c=e.drawingContext.createLinearGradient(i,o,a,l);c.addColorStop(0,s),c.addColorStop(1,h),e.drawingContext.strokeStyle=c,e.drawingContext.globalAlpha=1,e.line(i,o,a,l),e.drawingContext.globalAlpha=1}}function S(e,t){const n=random(TAU),r=random(e,t);return createVector(r*cos(n),r*sin(n))}class R{constructor(e,t,n,r,i){this.wall=n,this.maxR=i;const o=t.length;this.nodes=[];for(let a=0;a<o;++a){const o=[],l=.25*t[a];for(let t=0;t<l;++t){const t=crM eateVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),l=S(.02*i,.05*i),s=random(10,25)*i;o.push(new M(t,l,s,e[a],r))}this.nodes.push(o)}const a=A(e);a.unshift(e[0]),a.push(e[e.length-1]),this.lines=[];for(let e=0;e<=o;++e){const r=[],l=(0==e?1:t[e-1])*(e==o?1:t[e])*1.5;for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),o=random(5*i,10*i),l=random(TAU),s=S(.02*i,.05*i),h=random(2e-4,.001);r.push(new E(t,o,l,s,h,a[e],a[e+1]))}this.lines.push(r)}}reflectNode(e){const{xM Left:t,yTop:n,xRight:r,yBottom:i}=this.wall,{p:o,v:a}=e,l=e.getRadius();(o.x-l<t&&a.x<0||o.x+l>r&&a.x>0)&&(a.x=-a.x),(o.y-l<n&&a.y<0||o.y+l>i&&a.y>0)&&(a.y=-a.y)}reflectLine(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,[o,a]=e.getEndpoints(),l=e.v;(min(o.x,a.x)<t&&l.x<0||max(o.x,a.x)>r&&l.x>0)&&(l.x=-l.x),(min(o.y,a.y)<n&&l.y<0||max(o.y,a.y)>i&&l.y>0)&&(l.y=-l.y)}update(){for(const e of this.lines)for(const t of e)t.update(),this.reflectLine(t);for(const e of this.nodes)for(const t of e)t.update(),this.refM lectNode(t)}draw(e,t,n,r,i){const o=i/this.maxR;for(const t of this.lines){const n=t.length*r;for(let r=0;r<n;++r)t[r].draw(e,o)}for(const i of this.nodes){const a=i.length*r;for(let r=0;r<a;++r)i[r].draw(e,t,n,o)}}}function I(e,t){re(e),e.fill(0),e.rect(0,0,500,500),ie(e),e.noStroke(),e.fill(dr(cr("#000000"),.5)),e.push(),e.translate(250,250),e.scale(t),e.translate(-250,-250),e.beginShape(),e.vertex(235.2,24.9),e.bezierVertex(215,24.6,185,11.4,164.8,11),e.bezierVertex(147.2,10.7,129.3,10.4,112.2,14.7),e.bezierVertM ex(95.1,19,78.5,28.5,69.6,43.8),e.bezierVertex(57.699,64.199,61.599,90.199,70.199,112.2),e.bezierVertex(78.799,134.2,91.6,154.6,97.199,177.5),e.bezierVertex(102.499,199.2,100.899,222.5,92.799,243.2),e.bezierVertex(83,268,64.6,288.3,48.9,310),e.bezierVertex(33.2,331.7,24.5,337.5,26.599,364.1),e.bezierVertex(28.2,384.1,61.399,404.2,75.7,418.3),e.bezierVertex(90,432.4,73.7,488.2,91.9,496.7),e.bezierVertex(124.2,511.6,159,472.5,194.3,468.1),e.bezierVertex(211.6,465.9,267.4,501.5,283.9,495.9),e.bezierVertex(340.7,476.7,M 298.599,428.9,355.4,409.7),e.bezierVertex(370.799,404.5,454.5,407.6,464.4,394.8),e.bezierVertex(478.599,376.3,474.7,349.3,464.299,328.4),e.bezierVertex(453.9,307.5,438.099,289.5,428.699,268.2),e.bezierVertex(412,230,419,182.6,446.1,150.9),e.bezierVertex(449.7,146.7,453.6,142.7,455.8,137.6),e.bezierVertex(459.4,129.299,457.5,119.6,454.8,111),e.bezierVertex(443.2,73.4,417.3,40.4,383.6,20.299),e.bezierVertex(358.1,5,343.2,-.4,313.5,0),e.bezierVertex(287.5,.4,261.6,25.4,235.2,24.9),e.endShape(),e.pop()}function C(e,t,nM ,r,i,o){let a,l,s;re(t),t.fill(0),t.rect(0,0,500,500),ie(t),t.noStroke(),t.fill(dr(n,.5)),1==i?(l=0,s=25,a=map(o,0,25,500,0)):a=0,t.rect(0,a,500,500),e.noStroke(),e.fill(r),e.rect(0,0,500,500),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465M .1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVeM rtex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.beziM erVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),e.fill(n),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(4M 33.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3M ,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202M .7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.beM zierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),re(e),e.fill(r),e.beginShape(),e.vertex(184.3,473.2),e.bezierVertex(164,473.2,144.7,462.099,134,444.3),e.bezierVertex(131.7,440.5,129.1,438.5,125,437.1),e.bezierVertex(97.3,428.1,80.5,400.6,85.2,371.8),e.bezierVertex(86.3,365.1,85.8,364.1,79.9,361.2),e.bezierVertex(57.2,349.8,46.2,323.3,54.3,299.7),e.bezierVM ertex(54.7,298.599,55.1,297.7,55.5,296.9),e.bezierVertex(55.6,296.599,55.8,296.4,55.9,296.099),e.vertex(57.9,291.499),e.vertex(62.5,293.599),e.bezierVertex(64.9,294.7,67.3,295.799,69.5,296.9),e.bezierVertex(74.5,299.299,79.1,301.599,83.9,303.099),e.bezierVertex(89.8,304.9,96.5,305.499,102.7,305.9),e.bezierVertex(102.8,305.9,102.9,305.9,103,305.9),e.bezierVertex(106.6,305.9,108.9,302.799,109,299.799),e.bezierVertex(109.1,296.199,106.6,293.4,102.7,292.799),e.bezierVertex(101.3,292.599,99.9,292.4,98.4,292.299),e.bezieM rVertex(94.3,291.799,90.1,291.299,86,289.9),e.bezierVertex(68.9,284,56.5,270.2,52.7,252.799),e.bezierVertex(48.9,235.499,54.5,217.7,67.6,205.299),e.bezierVertex(71.9,201.299,72.7,198.1,70.8,192.399),e.bezierVertex(64.2,172.2,68.8,153.99,84.2,139.599),e.bezierVertex(94.2,130.199,105.5,125.399,117.8,125.399),e.bezierVertex(124.3,125.399,131.1,126.799,137.8,129.599),e.bezierVertex(157,137.399,167.9,152.799,169.4,173.99),e.vertex(169.4,174.399),e.bezierVertex(169.5,175.899,169.6,177.2,169.9,178.299),e.bezierVertex(170.M 7,181.2,173.2,183.2,176.1,183.2),e.bezierVertex(176.299,183.2,176.5,183.2,176.7,183.2),e.bezierVertex(180.1,182.899,182.6,180.299,182.7,177),e.bezierVertex(183.1,162,178.299,148.2,168.399,136.1),e.bezierVertex(158.2,123.5,144.899,115.8,128.799,113.199),e.bezierVertex(123.499,112.299,120.399,109.799,118.899,104.99),e.bezierVertex(113.899,89.699,120.699,72.299,134.899,64.499),e.bezierVertex(139.99,61.699,145.799,60.199,151.7,60.199),e.bezierVertex(162.2,60.199,171.899,64.799,178.1,72.699),e.bezierVertex(179.6,74.6,18M 0.799,76.6,181.9,78.499),e.vertex(182.2,79.099),e.bezierVertex(183.2,80.699,185.2,83.299,188.4,83.299),e.bezierVertex(189.5,83.299,190.6,82.99,191.7,82.399),e.bezierVertex(195.1,80.599,196,76.99,194,72.799),e.bezierVertex(190.1,64.799,184.1,58.499,175.6,53.299),e.bezierVertex(174.6,52.699,173.7,52.099,172.5,51.499),e.vertex(170.5,50.299),e.vertex(163,45.899),e.vertex(170.5,41.599),e.bezierVertex(182,34.99,193.1,30.799,204.4,28.599),e.bezierVertex(208.6,27.799,212.9,27.399,217.2,27.399),e.bezierVertex(217.6,27.399,2M 17.9,27.399,218.3,27.399),e.bezierVertex(231.4,27.599,242.7,38.199,243,50.599),e.bezierVertex(243.4,64.899,243.3,78.99,243.2,93.799),e.bezierVertex(243.2,99.799,243.1,105.899,243.1,112.099),e.vertex(243.1,119.199),e.vertex(236.4,116.799),e.bezierVertex(235.7,116.499,235,116.299,234.4,115.99),e.bezierVertex(233.4,115.599,232.6,115.299,232,115.199),e.bezierVertex(230.6,114.899,229.2,114.599,227.8,114.299),e.bezierVertex(223.8,113.499,220.1,112.699,216.4,112.499),e.vertex(216.2,112.499),e.bezierVertex(212.5,112.499,21M 0.7,115.599,210.6,118.599),e.bezierVertex(210.4,122.399,212.7,125.099,216.4,125.399),e.bezierVertex(230.1,126.399,238.9,133.099,242.3,145.199),e.bezierVertex(243.2,148.399,243.2,151.599,243.2,154.499),e.vertex(243.2,155.099),e.bezierVertex(243.2,254.199,243.2,330,243.2,400.599),e.bezierVertex(243.2,401.99,243.2,403.4,243.2,404.9),e.bezierVertex(243.3,411.099,243.3,417.599,242.3,423.9),e.bezierVertex(238.1,449.2,219.6,467.799,194,472.5),e.bezierVertex(190.9,472.9,187.6,473.2,184.3,473.2),e.endShape(),e.beginShape(),M e.vertex(315.8,473.1),e.bezierVertex(309.3,473.1,302.8,472,296.5,469.9),e.bezierVertex(270.4,461,253.8,434.9,257.1,407.9),e.bezierVertex(260,384,273.8,366.8,297,358.3),e.bezierVertex(297.7,358.1,298.3,357.8,299,357.6),e.bezierVertex(299.8,357.3,300.6,357.1,301.2,356.8),e.bezierVertex(304.3,355.4,306,351.8,304.9,348.7),e.bezierVertex(304,345.9,301.7,344.2,299,344.2),e.bezierVertex(298.6,344.2,298.1,344.2,297.6,344.3),e.bezierVertex(288.1,346.3,279,350.9,269.7,358.3),e.bezierVertex(268.9,358.9,268.1,359.6,267.2,360.4M ),e.vertex(265.5,361.8),e.vertex(258.5,367.6),e.vertex(257.4,358.6),e.bezierVertex(257.3,358,257.3,357.5,257.2,357.1),e.bezierVertex(257,356,256.9,354.9,256.9,353.7),e.bezierVertex(256.9,334.8,256.9,316,256.9,297.1),e.bezierVertex(256.9,260.3,256.9,222.3,256.8,185),e.bezierVertex(256.8,170.7,268.3,158.8,282.5,158.4),e.bezierVertex(284.8,158.3,286.7,157.6,287.9,156.2),e.bezierVertex(289.099,154.9,289.599,153.2,289.5,151.3),e.bezierVertex(289.3,147.5,286.7,145.1,282.7,145.1),e.bezierVertex(282.5,145.1,282.2,145.1,282M ,145.1),e.bezierVertex(278.8,145.3,275.5,146.1,272,146.9),e.bezierVertex(270.9,147.2,269.8,147.4,268.6,147.7),e.bezierVertex(267.9,147.9,267,148.2,265.8,148.7),e.bezierVertex(265.1,149,264.4,149.3,263.5,149.6),e.vertex(256.8,152),e.vertex(256.8,114.6),e.bezierVertex(256.8,95,256.8,75.4,256.8,55.9),e.bezierVertex(256.8,38,267.2,27.3,284.6,27.3),e.bezierVertex(285.3,27.3,285.9,27.3,286.6,27.3),e.bezierVertex(299,27.9,318.7,34.5,329.6,41.9),e.vertex(336.1,46.3),e.vertex(324.4,53.3),e.bezierVertex(316.2,58.2,310.2,64.6M ,306,72.9),e.bezierVertex(304.2,76.4,305.1,78.5,306.1,80),e.bezierVertex(307.4,81.9,309.4,83,311.6,83),e.bezierVertex(313.7,83,315.7,81.9,317.1,80.1),e.bezierVertex(317.4,79.7,317.8,79,318.1,78.4),e.bezierVertex(318.4,77.9,318.7,77.3,319,76.8),e.bezierVertex(325.3,66.2,336.3,59.9,348.5,59.9),e.bezierVertex(353.2,59.9,357.8,60.8,362.1,62.7),e.bezierVertex(377.6,69.3,386,86.7,381.7,103.2),e.bezierVertex(380.7,107.1,378.5,111.8,371.1,113.1),e.bezierVertex(342.7,118.1,322.2,139.1,317.8,167.8),e.bezierVertex(317.4,170.3M ,317.3,173.2,317.4,176.5),e.bezierVertex(317.5,180,320.1,182.8,323.5,183),e.bezierVertex(323.6,183,323.8,183,323.9,183),e.bezierVertex(327.1,183,329.8,180.6,330.3,177.2),e.bezierVertex(330.6,175.7,330.7,174,330.9,172.3),e.bezierVertex(331.1,169.8,331.4,167.3,332,164.7),e.bezierVertex(337.3,141.9,357.7,125.4,380.7,125.4),e.bezierVertex(382.5,125.4,384.3,125.5,386.1,125.7),e.bezierVertex(412.8,128.9,432.6,150.9,432,176.9),e.bezierVertex(431.9,182.3,430.9,187.7,429.1,192.7),e.bezierVertex(427.2,197.9,428,201,432.3,205M ),e.bezierVertex(446.8,218.7,451.8,236,446.6,255),e.bezierVertex(441.4,274,428.3,286.5,408.7,291.3),e.bezierVertex(406.1,291.9,403.6,292.1,401.1,292.3),e.bezierVertex(400,292.4,398.9,292.5,397.9,292.6),e.bezierVertex(393.6,293.1,390.9,295.7,391,299.5),e.bezierVertex(391.1,303.4,394,305.8,398.5,305.8),e.bezierVertex(409.9,305.8,420.8,302.6,431.1,296.4),e.bezierVertex(431.8,296,432.5,295.5,433.2,295.1),e.bezierVertex(433.8,294.7,434.5,294.3,435.2,293.9),e.bezierVertex(436,293.4,436.6,293.2,437.2,293.1),e.bezierVertexM (437.4,293,437.7,292.9,438.1,292.8),e.vertex(442.5,291.4),e.vertex(444.2,295.7),e.bezierVertex(450.9,312.4,449.5,328.4,440,343.4),e.bezierVertex(435.3,350.8,428.7,356.7,420.2,361.1),e.bezierVertex(414.3,364.1,413.7,365.2,414.8,371.7),e.bezierVertex(419.5,400.2,403,427.6,375.6,436.9),e.bezierVertex(371,438.5,368.3,440.7,365.8,444.7),e.bezierVertex(355.2,462.5,336.4,473.1,315.8,473.1),e.bezierVertex(315.8,473.1,315.8,473.1,315.8,473.1),e.endShape(),ie(e),e.fill(n),e.beginShape(),e.vertex(120.2,279.9),e.bezierVertex(1M 17.9,279.9,112.4,279.299,112.2,273.599),e.bezierVertex(112,267.7,117.4,266.7,119.7,266.599),e.bezierVertex(133.1,265.799,143.1,259.499,149.3,247.899),e.bezierVertex(149.6,247.299,150.1,246.399,150.3,245.399),e.bezierVertex(150.6,244.299,150.5,243.299,150.5,242.7),e.bezierVertex(150.5,242.6,150.5,242.5,150.5,242.299),e.vertex(150.3,238.799),e.vertex(141.1,235.99),e.bezierVertex(114.6,227.799,95.6,202.499,95.9,175.799),e.bezierVertex(95.9,173.99,96.4,168.199,102.2,168.199),e.bezierVertex(102.6,168.199,103,168.199,103M .4,168.299),e.bezierVertex(104.8,168.499,108.2,168.899,109.2,175.599),e.bezierVertex(109.3,176.599,109.5,177.599,109.6,178.499),e.bezierVertex(110.4,184.199,111.3,189.99,113.7,195.499),e.bezierVertex(121.9,213.99,139.5,225.499,159.7,225.499),e.bezierVertex(172.1,225.499,184.1,220.899,193.5,212.599),e.bezierVertex(194,212.199,194.4,211.799,194.8,211.399),e.bezierVertex(195.1,211.099,195.5,210.799,195.8,210.399),e.bezierVertex(197.4,208.99,199.2,208.2,200.9,208.2),e.bezierVertex(202.5,208.2,204,208.899,205.3,210.1),eM .bezierVertex(208,212.9,207.9,216.9,205,219.9),e.bezierVertex(196.5,228.6,186.3,234.3,174.7,236.8),e.bezierVertex(168.799,238.1,165.6,241,163.899,246.7),e.bezierVertex(158.3,265.9,139.9,279.7,120.2,279.9),e.vertex(120.2,279.9),e.endShape(),e.beginShape(),e.vertex(187.2,427.5),e.bezierVertex(183.799,427.5,181.299,425.3,180.799,422),e.bezierVertex(180.6,420.8,180.499,419.5,180.399,418.1),e.bezierVertex(180.299,417,180.2,415.8,180.099,414.7),e.bezierVertex(177.199,390.5,156.699,371.3,132.399,370.2),e.bezierVertex(131.M 99,370.2,131.499,370.2,131.099,370.2),e.bezierVertex(130.699,370.2,130.299,370.2,129.799,370.2),e.bezierVertex(125.99,369.9,123.199,367.2,123.099,363.6),e.bezierVertex(122.99,360.2,125.799,357.3,129.599,356.9),e.bezierVertex(130.499,356.8,131.499,356.8,132.599,356.7),e.bezierVertex(133.199,356.7,133.799,356.7,134.399,356.6),e.vertex(138.299,356.4),e.vertex(139.1,352.6),e.bezierVertex(139.5,350.7,139.799,348.9,140.2,347),e.bezierVertex(140.899,343.4,141.5,340,142.399,336.8),e.bezierVertex(150.099,310.7,174.399,292,2M 01.399,291.3),e.vertex(201.599,291.3),e.bezierVertex(203.699,291.3,206.299,292,208.299,293.2),e.bezierVertex(210.499,294.5,210.699,297.5,209.99,299.8),e.bezierVertex(209.499,301.5,208.199,303.9,203.299,304.7),e.bezierVertex(202.199,304.9,200.99,305,199.799,305.2),e.bezierVertex(194.499,305.9,188.99,306.599,183.799,308.9),e.bezierVertex(165.499,316.799,155.199,331.299,152.99,352),e.bezierVertex(152.399,357.8,154.499,361.7,159.699,364.5),e.bezierVertex(178.199,374.4,189.399,390,193.099,410.9),e.bezierVertex(193.699,4M 14.299,193.899,418,193.599,422),e.bezierVertex(193.399,425.2,190.899,427.5,187.399,427.5),e.vertex(187.2,427.5),e.endShape(),e.beginShape(),e.vertex(364.3,281.1),e.bezierVertex(346.3,280.6,332.9,272.8,323.5,257),e.bezierVertex(321.6,253.9,320.4,250.2,319.2,246.7),e.bezierVertex(317.7,242.2,315,239.799,310.5,238.799),e.bezierVertex(298.5,236.299,288,230.7,279.4,222.1),e.bezierVertex(276.7,219.4,274.9,215.299,278,211.9),e.bezierVertex(279.4,210.3,281,209.6,282.6,209.6),e.bezierVertex(284.4,209.6,286.4,210.6,288.3,212M .5),e.bezierVertex(297.8,221.8,310.4,226.9,323.9,226.9),e.bezierVertex(340.2,226.9,355.1,219.3,364.8,206.2),e.bezierVertex(371,197.8,374.2,188.5,374.5,178.5),e.vertex(374.5,177.9),e.bezierVertex(374.5,177,374.5,176.1,374.7,175.4),e.bezierVertex(375.3,171.8,377.9,169.5,381.3,169.5),e.bezierVertex(381.4,169.5,381.5,169.5,381.7,169.5),e.bezierVertex(385.4,169.7,388,172.4,388,176.1),e.bezierVertex(388.1,190.7,383.4,204,374.2,215.8),e.bezierVertex(365.8,226.5,354.7,233.9,341.2,237.9),e.bezierVertex(340,238.3,338.7,238.6M ,337.3,239.1),e.bezierVertex(335.9,239.6,335.1,240.4,334.7,240.9),e.bezierVertex(334.599,241,334.5,241.1,334.4,241.2),e.vertex(331.799,243.6),e.vertex(333.199,246.8),e.bezierVertex(338.199,258,346.799,264.9,358.699,267.3),e.bezierVertex(360.199,267.6,361.599,267.7,362.99,267.9),e.bezierVertex(363.599,268,364.299,268,364.899,268.1),e.bezierVertex(369.099,268.6,371.799,271.4,371.499,275),e.bezierVertex(371.199,278.6,368.299,281.2,364.399,281.2),e.vertex(364.3,281.1),e.endShape(),e.beginShape(),e.vertex(323.9,437),e.bM ezierVertex(323.7,437,323.5,437,323.299,437),e.bezierVertex(319.599,436.7,317.299,434.1,317.4,430.2),e.bezierVertex(317.9,406.099,328.299,388,349.5,375),e.bezierVertex(350.7,374.2,352,373.5,353.4,372.8),e.bezierVertex(354.099,372.4,354.7,372.1,355.299,371.7),e.vertex(357.499,370.5),e.vertex(357.799,368),e.bezierVertex(360.4,346.6,345.199,323.7,323.9,317),e.bezierVertex(319.099,315.5,314.099,314.9,309.299,314.4),e.vertex(308.199,314.299),e.bezierVertex(305.99,314.099,300.799,312.9,300.899,307.299),e.bezierVertex(300M .99,303.499,303.899,300.9,308.099,300.9),e.vertex(308.299,300.9),e.bezierVertex(327.099,301.299,343.099,308.7,355.699,322.9),e.bezierVertex(364.299,332.5,369.399,344.099,370.99,357.299),e.bezierVertex(371.099,358.4,371.299,359.4,371.499,360.499),e.bezierVertex(371.599,360.99,371.699,361.499,371.799,361.99),e.vertex(372.499,365.899),e.vertex(377.899,366.199),e.bezierVertex(378.799,366.299,379.699,366.299,380.599,366.399),e.bezierVertex(385.099,366.699,387.899,369.399,387.799,373.299),e.bezierVertex(387.699,377.099,3M 84.99,379.599,380.799,379.799),e.bezierVertex(369.799,380.199,359.99,383.299,351.899,389.299),e.bezierVertex(338.799,398.799,331.699,411.699,330.699,427.499),e.vertex(330.699,428.299),e.bezierVertex(330.599,429.199,330.599,430.099,330.499,430.799),e.bezierVertex(330,434.7,327.5,437,323.9,437),e.endShape()}function T(e){return e[0].map(((t,n)=>e.map((e=>e[n]))))}function A(e){return e.map((e=>Array.isArray(e)?A(e):e))}function D(e,t){return floor(random(e,t))}function k(e){let t=0;for(const n of e)t+=n[1];let n=randM om(t),r=0;for(const t of e)if(r+=t[1],n<r)return t[0];return null}function L(e){for(let t=1;t<e.length;++t){let n=D(0,t),r=e[t];e[t]=e[n],e[n]=r}}function P(e){return null==e||""===e}function O(e){return new Promise((t=>setTimeout(t,e)))}function F(e,t,n){let r=0;for(let i=1;i<=1e3;++i)for(let o=1;o<=1e3;++o)if(e*o%(t*i)==0){let e=1*i/o;abs(e-n)<abs(r-n)&&(r=e)}return r}function N(){let e=60*(new Date).getTimezoneOffset()*1e3;return new Date(Date.now()-e).toISOString().slice(0,-1)}function B(e,t,n){let r;if(push(),M textSize(e),textWidth(t)<=n)r=t;else for(let e=0;e<t.length;++e){const i=t.slice(0,e+1)+"...";if(textWidth(i)>n){r=i;break}}return pop(),r}function Y(e){var t=e%10,n=e%100;return 1==t&&11!=n?e+"st":2==t&&12!=n?e+"nd":3==t&&13!=n?e+"rd":e+"th"}class G{constructor(e,t,n){this.n=t,this.m=n,this.mat=[];let r=0;for(let t=0;t<this.n;++t){this.mat.push([]);for(let n=0;n<this.m;++n)this.mat[t].push(r<e.length?e[r]:0),r+=1}return this}copy(){return new G(this.mat.flat(),this.n,this.m)}}class H{static __linear=e=>e;static __M relu=e=>Math.max(e,0);static __leaky_relu=e=>e>0?e:.2*e;static __sigmoid=e=>1/(1+Math.exp(-e));static __tanh=e=>Math.tanh(e);static __apply_unary_op(e,t){const n=e.copy();for(let e=0;e<n.n;++e)for(let r=0;r<n.m;++r)n.mat[e][r]=t(n.mat[e][r]);return n}static linear=e=>H.__apply_unary_op(e,H.__linear);static relu=e=>H.__apply_unary_op(e,H.__relu);static leaky_relu=e=>H.__apply_unary_op(e,H.__leaky_relu);static sigmoid=e=>H.__apply_unary_op(e,H.__sigmoid);static tanh=e=>H.__apply_unary_op(e,H.__tanh);static __add=(e,tM )=>e+t;static __mul=(e,t)=>e*t;static __apply_binary_op=(e,t,n)=>{"object"!=typeof t&&(t=new G([t],1,1));const r=e.copy();for(let e=0;e<r.n;++e)for(let i=0;i<r.m;++i)r.mat[e][i]=n(r.mat[e][i],t.mat[e%t.n][i%t.m]);return r};static mul=(e,t)=>H.__apply_binary_op(e,t,H.__mul);static add=(e,t)=>H.__apply_binary_op(e,t,H.__add);static matMul(e,t){const n=new G([],e.n,t.m);for(let r=0;r<n.n;++r)for(let i=0;i<n.m;++i)for(let o=0;o<e.m;++o)n.mat[r][i]+=e.mat[r][o]*t.mat[o][i];return n}static softmax(e){const t=H.__apply_unM ary_op(e,(e=>Math.exp(e))),n=t.mat.flat().reduce(((e,t)=>e+t));for(let r=0;r<e.n;++r)for(let i=0;i<e.m;++i)t.mat[r][i]/=n;return t}}class ${constructor(e,t){this.scale=e,this.offset=t}forward(e){return H.add(H.mul(e,this.scale),this.offset)}}class X{constructor(){}forward(e){return e.map((e=>e.flat()))}}class W{constructor(e,t,n,r){this.out_dim=e,this.activation=t,this.w=n,this.b=r}forward(e){const t=H.add(H.matMul(e,this.w),this.b);return null==this.activation?t:this.activation(t)}}class U{constructor(e,t,n){this.M preprocessLayers=e,this.hiddenLayers=t,this.outputLayer=n,this.totalNeurons=this.hiddenLayers.map((e=>e.out_dim)),this.currentOrders=[],this.currentIteration=null}updateNeurons(e,t){if(t!=this.currentIteration){this.currentOrders=[];for(let e=0;e<this.totalNeurons.length;++e){randomSeed(100*(t+1)+e);const n=[];for(let t=0;t<this.totalNeurons[e];++t)n.push(t);L(n),this.currentOrders.push(n)}this.currentIteration=t}const n=A(this.totalNeurons),r=n.reduce(((e,t)=>e+t))*(1-e);for(let e=0;e<r;++e){const t=n.map(((e,t)=>M (e-1)/this.totalNeurons[t]));n[t.map(((e,t)=>[e,t])).reduce(((e,t)=>t[0]>e[0]?t:e))[1]]-=Math.min(r-e,1)}this.neuronsLife=[];for(let e=0;e<n.length;++e){const t=this.currentOrders[e],r=Array(this.totalNeurons[e]).fill(0);for(let i=0;i<n[e];++i)r[t[i]]=Math.min(n[e]-i,1);this.neuronsLife.push(r)}}getTotalNeurons(){return A(this.totalNeurons)}getNeuronsLife(){return A(this.neuronsLife)}forward(e){for(const t of this.preprocessLayers)e=t.forward(e);for(const[t,n]of this.hiddenLayers.entries()){e=n.forward(e);const r=nM ew G(this.neuronsLife[t],1,e.m);e=H.mul(e,r)}return e=this.outputLayer.forward(e),H.softmax(e)}}function q(e){switch(e){case"relu":return H.relu;case"sigmoid":return H.sigmoid;case"tanh":return H.tanh;case"leaky_relu":return H.leaky_relu;default:return H.linear}}function j(e,t){const n=[],r=[],i=Z(t);let o=null,a=0,l=[];for(const t of e.config.layers)if("InputLayer"==t.class_name)o=t.config.batch_input_shape.slice(1),l=o;else if("Rescaling"==t.class_name)n.push(new $(t.config.scale,t.config.offset));else if("FlatteM n"==t.class_name)o=[o.reduce(((e,t)=>e*t))];else if("Dense"==t.class_name){const e=[t.config.units],n=o[0]*e[0],l=e[0],s=i.subarray(a,a+n);a+=n;const h=i.subarray(a,a+l);a+=l;const c=new G(s,o[0],e[0]),u=new G(h,1,e[0]),f=q(t.config.activation);r.push(new W(e[0],f,c,u)),o=e}const s=r.pop();return{model:new U(n,r,s),inputDim:l}}function Z(e){const t=window.atob(e),n=t.length/Float32Array.BYTES_PER_ELEMENT,r=new DataView(new ArrayBuffer(Float32Array.BYTES_PER_ELEMENT)),i=new Float32Array(n);let o=0;for(let e=0;e<n;e+M +){o=4*e;for(let e=0;e<4;++e)r.setUint8(e,t.charCodeAt(o+e));i[e]=r.getFloat32(0,!0)}return i}class K{constructor(e){this.elt=e,this._events={},this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight}position(){if(0===arguments.length)return{x:this.elt.offsetLeft,y:this.elt.offsetTop};var e="absolute";return"static"!==arguments[2]&&"fixed"!==arguments[2]&&"relative"!==arguments[2]&&"sticky"!==arguments[2]&&"initial"!==arguments[2]&&"inherit"!==arguments[2]||(e=arguments[2]),this.elt.style.position=e,this.M elt.style.left=arguments[0]+"px",this.elt.style.top=arguments[1]+"px",this.x=arguments[0],this.y=arguments[1],this}show(){return this.elt.style.display="block",this}hide(){return this.elt.style.display="none",this}size(e,t){if(0===arguments.length)return{width:this.elt.offsetWidth,height:this.elt.offsetHeight};var n=e,r=t;if(n!==te||r!==te){if(n===te?n=t*this.width/this.height:r===te&&(r=e*this.height/this.width),this.elt instanceof HTMLCanvasElement){var i,o={},a=this.elt.getContext("2d");for(i in a)o[i]=a[i];for(M i in this.elt.setAttribute("width",n*this._pInst._pixelDensity),this.elt.setAttribute("height",r*this._pInst._pixelDensity),this.elt.style.width=n+"px",this.elt.style.height=r+"px",this._pInst.scale(this._pInst._pixelDensity,this._pInst._pixelDensity),o)this.elt.getContext("2d")[i]=o[i]}else this.elt.style.width=n+"px",this.elt.style.height=r+"px",this.elt.width=n,this.elt.height=r;this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight,this._pInst&&this._pInst._curElement&&this._pInst._curElement.elt===tM his.elt&&(this._pInst._setProperty("width",this.elt.offsetWidth),this._pInst._setProperty("height",this.elt.offsetHeight))}return this}style(e,t){if(t instanceof Color&&(t="rgba("+t.levels[0]+","+t.levels[1]+","+t.levels[2]+","+t.levels[3]/255+")"),void 0===t){if(-1===e.indexOf(":"))return window.getComputedStyle(this.elt).getPropertyValue(e);for(var n=e.split(";"),r=0;r<n.length;r++){var i=n[r].split(":");i[0]&&i[1]&&(this.elt.style[i[0].trim()]=i[1].trim())}}else if(this.elt.style[e]=t,"width"===e||"height"===e||M "left"===e||"top"===e){var o=window.getComputedStyle(this.elt).getPropertyValue(e).replace(/[^\d.]/g,"");this[e]=Math.round(parseFloat(o,10))}return this}value(){return arguments.length>0?(this.elt.value=arguments[0],this):"range"===this.elt.type?parseFloat(this.elt.value):this.elt.value}mouseClicked(e){return this._adjustListener("click",e,this),this}isFocused(){return document.activeElement===this.elt}_adjustListener(e,t,n){return!1===t?this._detachListener(e,n):this._attachListener(e,t,n),this}_attachListener(e,M t,n){n._events[e]&&this._detachListener(e,n);var r=t.bind(n);n.elt.addEventListener(e,r,!1),n._events[e]=r}_detachListener(e,t){var n=t._events[e];t.elt.removeEventListener(e,n,!1),t._events[e]=null}}function J(e,t){var n=document.createElement("button");return n.innerHTML=e,t&&(n.value=t),ee(n)}function Q(e){var t=arguments.length>1&&void 0!==arguments[1]&&arguments[1],n=function(t){var n=!0,r=!1,i=void 0;try{for(var o,a=t.target.files[Symbol.iterator]();!(n=(o=a.next()).done);n=!0){var l=o.value;File._load(l,e)}}M catch(e){r=!0,i=e}finally{try{n||null==a.return||a.return()}finally{if(r)throw i}}};if(window.File&&window.FileReader&&window.FileList&&window.Blob){var r=document.createElement("input");return r.setAttribute("type","file"),t&&r.setAttribute("multiple",!0),r.addEventListener("change",n,!1),ee(r)}}function ee(e){return document.body.appendChild(e),new K(e)}createImg=function(){var e,t=document.createElement("img"),n=arguments;return n.length>1&&"string"==typeof n[1]&&(t.alt=n[1]),n.length>2&&"string"==typeof n[2]&&(M t.crossOrigin=n[2]),t.src=n[0],e=ee(t,this),t.addEventListener("load",(function(){e.width=t.offsetWidth||t.width,e.height=t.offsetHeight||t.height;var r=n[n.length-1];"function"==typeof r&&r(e)})),e},createInput=function(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:"",t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:"text",n=document.createElement("input");return n.setAttribute("value",e),n.setAttribute("type",t),ee(n,this)};const te="auto";function ne(e){re(e);const t=e._rectMode;e.rectMoM de(CORNER),e.rect(0,0,e.width,e.height),e.rectMode(t),ie(e)}function re(e){e.push(),e.fill(255,255,255,255),e.blendMode(REMOVE)}function ie(e){e.blendMode(BLEND),e.pop()}File=function(e,t){this.file=e,this._pInst=t;var n=e.type.split("/");this.type=n[0],this.subtype=n[1],this.name=e.name,this.size=e.size,this.data=void 0},File._createLoader=function(e,t){var n=new FileReader;return n.onload=function(n){var r=new File(e);if("application/json"===r.file.type)r.data=JSON.parse(n.target.result);else if("text/xml"===r.fiM le.type){var i=(new DOMParser).parseFromString(n.target.result,"text/xml");r.data=new XML(i.documentElement)}else r.data=n.target.result;t(r)},n},File._load=function(e,t){if(/^text\//.test(e.type)||"application/json"===e.type)File._createLoader(e,t).readAsText(e);else if(/^(video|audio)\//.test(e.type)){var n=new File(e);n.data=URL.createObjectURL(e),t(n)}else File._createLoader(e,t).readAsDataURL(e)},XML=function(e){if(e)this.DOM=e;else{var t=document.implementation.createDocument(null,"doc");this.DOM=t.createElemM ent("root")}},document.addEventListener("DOMContentLoaded",(function(){addEventListener("mousemove",(e=>{window.mouseX=e.pageX,window.mouseY=e.pageY}))})),new e("global");const oe="544";let ae,le,se,he,ce,ue,fe,de,xe,ge,pe,me,be,ye,we,ve,ze,Ve,_e,Me,Ee,Se,Re,Ie,Ce,Te,Ae,De,ke,Le,Pe,Oe,Fe,Ne,Be,Ye,Ge,He,$e,Xe,We,Ue,qe,je,Ze,Ke,Je,Qe,et,tt,nt,rt,it,ot,at,lt,st,ht,ct,ut,ft,dt,xt,gt,pt,mt,bt,yt,wt,vt,zt,Vt,_t,Mt,Et,St,Rt,It,Ct,Tt,At=!1,Dt=!1,kt=!0,Lt=!1,Pt=!1;const Ot=[" ","Growing","Stable","Decaying","Dead","Rebirth"M ];let Ft,Nt,Bt,Yt,Gt,Ht,$t,Xt,Wt,Ut,qt,jt,Zt,Kt,Jt,Qt,en,tn,nn,rn,on,an,ln,sn,hn=0,cn=0,un=0,fn=!1,dn=!0,xn=!0,gn=null,pn=null,mn=null,bn=!1,yn=!1,wn=null,vn=null,zn=!1;async function setup(){let e=windowWidth,t=windowHeight;createCanvas(e,t),et=createGraphics(e,t),Xe=createGraphics(e,t),$e=createGraphics(e,t),We=createGraphics(e,t),Ue=createGraphics(e,t),qe=createGraphics(e,t),Qe=createGraphics(e,t),je=createGraphics(e,t),Ze=createGraphics(e,t),Ke=createGraphics(e,t),Je=createGraphics(e,t),tt=createGraphics(500,50M 0),nt=createGraphics(500,500),rt=createGraphics(500,500),_n(),Mn(),Sn(),await En(),Gn(),Rn(),bn=!0}function _n(){Et=parseInt(oe),randomSeed(Et),noiseSeed(Et)}function Mn(){Wt=Ir(p.training_traits),Cr(Wt)}async function En(){let e;Jt=r(),Qt=o(),[Xt,e]=await Promise.all([s(Jt),h(Qt)]),Ut=new V(Wt.visual,e.layers_config,e.weight_b64),Ut.updateAge(new Date),_n(),Wt.training=e.training_traits,Ht=e.model_name,$t=e.classes_name}function Sn(){le=min(width,height)/1024,ut=Rr.findIndex((e=>e[0]===Wt.visual.colorPalette)),ft=M [["#ffffff","#231f20","#231f20"],["#231f20","#ffffff","#ffffff"],["#104da8","#ffffff","#ffffff"],["#722F1F","#FCE1B2","#FCE1B2"],["#e88120","#f9f2e5","#f9f2e5"],["#f6b941","#2E2E2E","#2E2E2E"],["#45daaa","#012221","#012221"],["#F1F1F1","#328DFE","#328DFE"],["#111822","#D3EB8D","#D3EB8D"],["#713FF9","#D6D5E6","#D6D5E6"],["#FBDA9D","#795106","#795106"],["#8f5b62","#ead0d0","#ead0d0"],["#eae4cb","#508cac","#508cac"],["#ffc6cc","#cc313d","#cc313d"],["#60A900","#E0FE00","#E0FE00"],["#507DBE","#D0D1D3","#D0D1D3"],["#3058M 48","#E8F2EE","#E8F2EE"],["#2a2634","#5b6988","#cb78a2","#5b6988"],["#590e29","#fd5e53","#fd5e53","#ffe373"],["#0a141d","#57d4e4","#328195","#2A9ECF","#0ab6a8","#57d4e4"],["#3a2d28","#d5c2ac","#df6338","#3d9895","#d5c2ac"],["#030706","#77c4d9","#77c4d9","#77c4d9","#ffffff","#ffffff","#e72020","#e72020"],["#3a4664","#92f5ff","#f9ff94","#eaa0a2","#55dde0"],["#fbfaff","#f04bb1","#f04bb1","#fac373","#82cef0","#8b31ce"],["#000000","#ffffff","#ff0002","#f26522","#fdff00","#00ff03","#01fffe","#0000ff","#ff00ff"]];for(let M e=0;e<ft.length;++e)for(let t=0;t<ft[e].length;++t)ft[e][t]=cr(ft[e][t]);pt=[],ct=ft[ut][0],st=ft[ut][1]}function Rn(){gn=document.querySelector("#upload"),pn=document.querySelector("#inputUpload"),gn.addEventListener("dblclick",(()=>{if(!Lt&&!yn)if(In(Ie)&&cn==Ve-1)pn.click();else{if(4!=Pe&&5!=Pe&&(In(Ie)||cn!=Ve-1))return;fn=!0,dn=!0,Bt=0,un=0}})),pn.addEventListener("click",(()=>{pn.value=null,gn.style.display="block"})),pn.addEventListener("change",(()=>{const[e]=pn.files;e?(se=null,gn.style.display="none",Tn(UM RL.createObjectURL(e)),mn=e):gn.style.display="block"}))}function In(e){for(let t=0;t<e.length;++t){let n=0;for(let r=0;r<e[t].length;++r)e[t][r]>0&&++n;if(0==n)return!1}return!0}function Cn(){null!=se&&(un=0,Pt=!0,he=0,ue=0,drewLineAnim=!0,ce=(ae/2+we/2)/le,loadImage(se.elt.src,(e=>{const[t,n,r]=Gt,i=createGraphics(t,n);i.image(e,0,0,t,n),i.loadPixels();const o=i.pixels.filter(((e,t)=>t%4!=3)),a=Ut.classifyImage(o);Zt=T([a,$t.map((e=>e.toUpperCase()))]).sort(((e,t)=>e[0]>t[0]?-1:1))})))}function Tn(e){se=createImgM (e,""),se.hide(),Cn()}function An(){zn||(ce+=(width-ae-we)/tn/le),re(Xe),Xe.rect(ce*le,0,width,height),ie(Xe),un>=ge&&1==kt&&(kt=!1,un-=ge),kt&&(re($e),$e.strokeWeight(2*Fe),Jn(he,ze,ct,ct,$e),ie($e)),un>=ge&&0==kt&&(kt=!0,un-=ge,he+=1,he==en&&(++ue,he=0,ce=(ae/2+we/2)/le,1==ue&&(Pt=!1,Dn(),ye=millis())))}function Dn(){At=!0,pe=!1,me=!1,tryButton=br("Try Again",width/2-225*le,height/2+265*le,290*le,40*le,kn),closeResultButton=br("Close",width/2+75*le,height/2+265*le,150*le,40*le,Ln)}function kn(){At=!1,tryButton.hiM de(),closeResultButton.hide(),pn.click()}function Ln(){Yt=!0,At=!1,Gn(),tryButton.hide(),closeResultButton.hide(),gn.style.display="block",se=null}function keyTyped(){bn&&!1===yn&&!1===yr()&&("i"!==key&&"I"!==key||(Dt=!Dt),"b"!==key&&"B"!==key||(xn=!xn),"s"!==key&&"S"!==key||!1!==Lt||saveCanvasAtCurrentTime(),"k"!==key&&"K"!==key||!1!==Lt||save4KCanvasAtCurrentTime(),"u"!==key&&"U"!==key||!1!==Lt||!1!==At||!1!==fn||!1!==Pt||On())}function On(){Lt=!0,wn=null,vn=null,submitButton=br("Submit",width/2-155*le,height/2+1M 15*le,150*le,40*le,Fn),closeSettingButton=br("Close",width/2+5*le,height/2+115*le,150*le,40*le,Yn),vt=createInput(),vt.position(width/2-252.5*le,height/2-40*le),vt.size(500*le,25*le),vt.style("font-size","15px"),vt.value(Jt||""),zt=createInput(),zt.position(width/2-252.2*le,height/2+35*le),zt.size(500*le,25*le),zt.style("font-size","15px"),zt.value(Qt||"")}function Fn(){Vt=vt.value(),_t=zt.value(),submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide(),Lt=!1,yn=!0,Nn()}async function Nn(){[wn,vn,_]=await M Promise.all([c(Vt),u(_t),O(1e3)]),yn=!1,wn&&vn?(n(Vt),i(_t),window.location.reload()):(Lt=!0,submitButton.show(),closeSettingButton.show(),vt.show(),zt.show())}function Bn(){Je.textFont("Trebuchet MS"),Je.noStroke(),pr(Je,600*le,200*le),Je.strokeWeight(1*le),Je.stroke(xt),Je.fill(xt),Je.textSize(50*le),Je.text("update()",width/2,height/2+2.5*le)}function Yn(){wn=null,vn=null,Lt=!1,submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide()}function Gn(){_n(),nn=Date.now(),pe=!1,me=!1,St=Wt.training.structure_M gen,Rt=Wt.visual.birthYear,It=Wt.visual.lifeCycle,Ct=Wt.training.epoch_num,Tt=Wt.training.activation_func,Ft=Mr.findIndex((e=>e[0]==Wt.visual.hardwareAcceleration))+1,1==Ft?(Nt=30,fe=40):2==Ft?(Nt=15,fe=20):(Nt=2,fe=10);const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=M Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),ae=100*le,ht=50*le,Oe=Sr.findIndex((e=>e[0]==Wt.visual.nodeShape))+1,dt=Er.findIndex((e=>e[0]==Wt.visual.nodeFill))+1,lt=_r.findIndex((e=>e[0]==Wt.visual.pattern))+1,de=Math.tanh(Math.log10(Xt.avgfeerate)),de=map(de,0,1,.2,.8),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNM odes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let eM =0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,eM +1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,at=.7,pt=[],xt=ft[ut][2],gt=ft[ut][ft[ut].length-1];for(let e=3;e<ft[ut].length-1;e++)pt.push(ft[ut][e]);mt=sr(xt,gt,pt,width),bt=[],wt=[],yt=width/(Ve-1);for(let e=0;e<Ve;e++)bt.push(hr(mt,yt*e/width)),wt.push(hr(mt,yt*e/width));wt.unshift(bt[0]),wt.push(bt[bt.length-1]),hn=0,cn=0,un=0,Yt=!0;const n={xLeft:ae/8,xRight:width-ae/8,yTop:ae/8,yBottom:height-ae/8},r=Ce.map((e=>e.length));jt=new R(bt,r,n,Oe,le)}function Hn(e,tM ){let n=Ce[e].length;return[e*we+we/2+ae/2,height/2-(n-1)/2*ve+t*ve]}function $n(e,t){le=min(e,t)/1024,ae=100*le,ht=50*le,we=(e-ae)/Ve,ve=(t-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}xe=floor(De.length*de),Le=[],ke=[],ge=floor(map(de,.2,.8,15,2));for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*leM ,Ne=map(Be,1/30,1,1,10)*le,mt=sr(xt,gt,pt,e),bt=[],wt=[],yt=e/(Ve-1);for(let t=0;t<Ve;t++)bt.push(hr(mt,yt*t/e)),wt.push(hr(mt,yt*t/e));wt.unshift(bt[0]),wt.push(bt[bt.length-1])}function Xn(){const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimM estamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let M t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<M t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le}function Wn(){jt.update();const e=4==Pe?0:Kt;jt.draw(Qe,ct,dt,e,le)}function Un(){if(!bn)return ar(),void et.image(je,0,0);if(4==Pe||5==Pe)return Wn(),void et.M image(Qe,0,0);un>=Nt&&hn<Ve&&(hn++,un=0);for(let e=0;e<hn;e++)1==dt?it=ot=bt[e]:(it=ct,ot=bt[e]),Kn(e,it,ot,$e);un>=Nt&&cn<Ve-1&&(cn++,un=0);for(let e=0;e<cn;e++)Zn(e)}function qn(){et.background(ct),Ue.background(255),Ue.rectMode(CENTER),ne(Ue),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),Ue.stroke(st),Ue.strokeWeight(8*le),Ue.fill(ct),Qe.background(255),Qe.rectMode(CENTER),ne(Qe),Qe.strokeWeight(le),qe.background(255),qe.rectMode(CENTER),ne(qe),qe.textAlign(LEFT),$e.background(255),$e.rectMode(CENTER),ne($e),XeM .background(255),ne(Xe),Xe.strokeWeight(Ne),We.background(255),We.rectMode(CENTER),ne(We),We.fill(st),We.stroke(st),We.strokeWeight(.1*le),er(lt),We.noStroke(),xn&&(We.rect(ae/16,height/2,ae/8,height),We.rect(width-ae/16,height/2,ae/8,height),We.rect(width/2,ae/16,width,ae/8),We.rect(width/2,height-ae/16,width,ae/8)),Ze.background(255),Ze.rectMode(CENTER),ne(Ze),Ze.textAlign(CENTER,CENTER),Ze.textStyle(BOLD),Ze.stroke(st),Ze.strokeWeight(8*le),Ze.fill(ct),je.background(255),je.rectMode(CENTER),ne(je),je.textAlign(CM ENTER,CENTER),je.textStyle(BOLD),Ke.background(255),Ke.rectMode(CENTER),ne(Ke),Ke.textAlign(CENTER,CENTER),Ke.textStyle(BOLD),Ke.stroke(st),Ke.strokeWeight(8*le),Ke.fill(ct),Je.background(255),Je.rectMode(CENTER),ne(Je),Je.textAlign(CENTER,CENTER),Je.textStyle(BOLD),Je.stroke(st),Je.strokeWeight(8*le),Je.fill(ct),Un(),et.image(We,0,0),Pt&&An(),et.image(Xe,0,0),et.image($e,0,0),At&&(tr(),et.image(Ue,0,0)),fn&&(lr(),et.image(Ze,0,0)),Lt&&(or(),et.image(Ke,0,0)),Dt&&(ir(),et.image(qe,0,0)),yn&&(Bn(),et.image(Je,0,0))}M function draw(){const e=Date.now();bn&&(Ut.updateAge(new Date(e)),Xn()),qn(),image(et,0,0),zn||un++}function Zn(e){let t,n=Ce[e].length,r=Ce[e+1].length;for(let i=0;i<n;i++){const[n,o]=Hn(e,i);for(let a=0;a<r;a++){const[r,l]=Hn(e+1,a);t=map(min(Ce[e][i],Ce[e+1][a]),0,1,0,.5),ur(n,o,r,l,bt[e],bt[e+1],Xe,t)}}}function Kn(e,t,n,r){let i,o,a,l=Ce[e].length;for(let s=0;s<l;s++){const[l,h]=Hn(e,s);i=Ce[e][s],a=map(Be,1/30,1,3,10),o=map(Ce[e][s],0,1,2*a,0)*le,o<1.5*le&&(o=0),Qn(l,h,ze,Oe,t,n,o,i,r)}}function Jn(e,t,n,r,i)M {for(let o=0;o<Le[e].length;o++)Qn(Le[e][o][0],Le[e][o][1],t,Oe,n,r,0,1,i)}function Qn(e,t,n,r,i,o,a,l,s){s.stroke(dr(o,map(l,0,1,.25,1))),s.fill(dr(i,map(l,0,1,.15,1))),s.strokeWeight(Fe),fr([a],s),3==dt&&s.fill(dr(i,0)),1==r?s.ellipse(e,t,n):2==r?s.rect(e,t,7*n/8,7*n/8):3==r&&(s.beginShape(),s.vertex(e-4*n/7,t),s.vertex(e,t-4*n/7),s.vertex(e+4*n/7,t),s.vertex(e,t+4*n/7),s.endShape(CLOSE))}function er(e){if(1==e);else if(2==e){We.strokeWeight(1*le);for(let e=ht/4;e<width+ht/4;e+=ht)for(let t=ht/4;t<height+ht/4;t+=M ht)We.point(e,t)}else if(3==e){ht=25*le;for(let e=ht/2;e<height+ht/2;e+=ht)We.line(0,e,width,e);for(let e=ht/2;e<width+ht/2;e+=ht)We.line(e,0,e,height)}}function tr(){Ue.textFont("Trebuchet MS"),Ue.textAlign(LEFT,CENTER),Ue.noStroke(),pr(Ue,800*le,500*le),Ue.noStroke(),Ue.fill(dr(st,.75)),Ue.rect(width/2,height/2-100*le,800*le,300*le,25*le,25*le,0,0),Ue.fill(st),Ue.rect(width/2-250*le,height/2-100*le,225*le,225*le),Ue.image(se.elt,width/2-357.5*le,height/2-207.5*le,215*le,215*le);let e=100*Zt[0][0];Ue.fill(ct),Ue.tM extSize(25*le),Ue.textStyle(NORMAL),1==me&&(e>=0&&e<20?Ue.text("I have a feeling this image belongs to",width/2-100*le,height/2-170*le):e>=20&&e<40?Ue.text("I have a hunch this image belongs to",width/2-100*le,height/2-170*le):e>=40&&e<60?Ue.text("I think this image belongs to",width/2-100*le,height/2-170*le):e>=60&&e<80?Ue.text("I'm almost certain this image belongs to",width/2-100*le,height/2-170*le):Ue.text("I'm positive this image belongs to",width/2-100*le,height/2-170*le));let t=e.toFixed(2);"100.00"==t&&(t="M 100"),1==me&&Ue.text("I'm "+t+"% confident that I'm right!",width/2-100*le,height/2-25*le),example=Zt.map((e=>e[1])),be=Ue.textWidth('"FIDENZAAAA"'),defaultPhrase=Ue.textWidth('"PERPENDICULAR INHABITATION"'),Ue.textStyle(BOLD);const n=me?example[0]:random(example);if(1===n.split(" ").length){let e=75*be/Ue.textWidth('"'+n+'"');e>75&&(e=75),Ue.textSize(e*le),Ue.text('"'+n+'"',width/2-100*le,height/2-90*le)}else nr(width/2-100*le,height/2-90*le,460*le,110*le,n,Ue);if(millis()-ye>1500&&(me=!0),C(tt,nt,st,ct,Pe,Mt),Ue.M image(nt,width/2-370*le,height/2+70*le,80*le,80*le),3==Pe){let e;e=map(Mt,50,60,.25,1.3),I(rt,e),Ue.image(rt,width/2-370*le,height/2+70*le,80*le,80*le)}let r,i;Ue.image(tt,width/2-370*le,height/2+70*le,80*le,80*le),Ue.fill(xt),Ue.textSize(40*le),Ue.text("INTELLIGENCE INFO",width/2-275*le,height/2+115*le),Ue.textSize(18*le),Ue.textStyle(NORMAL),Ue.circle(width/2-360*le,height/2+180*le,7.5*le),1==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s growing and getting smarter by the day.`:2==Pe?r=`Your PerceptM ron is ${Math.ceil(Mt)} years old. It s stable and it has reached peak performance.`:3==Pe&&(r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s decaying and losing its luster.`),i=2==Pe?"The Perceptron remains stable for some time before entering the decay phase.":`Wait until ${new Date(an).toLocaleString("en-US")} for your Perceptron to reach its peak performance.`,Ue.text(r,width/2-350*le,height/2+180*le),Ue.circle(width/2-360*le,height/2+210*le,7.5*le),Ue.text(i,width/2-350*le,height/2+210*le),Ue.textAliM gn(CENTER,CENTER),Ue.textStyle(BOLD),gr(Ue,width/2-225*le,width/2+65*le,height/2+265*le,height/2+305*le,"SELECT ANOTHER IMAGE"),gr(Ue,width/2+75*le,width/2+225*le,height/2+265*le,height/2+305*le,"CLOSE")}function nr(e,t,n,r,i,o){let a=i.split(" "),l=75*be/o.textWidth('"'+i+'"'),s=0,h=[],c=[],u=[],f="",d="";if(l>=50)l>75&&(l=75),o.textSize(l*le),o.text('"'+i+'"',e,t);else if(l<50){if(l=50*defaultPhrase/o.textWidth('"'+i+'"'),l>30){if(l>50&&(l=50),[f,d]=rr(l,n,s,h,c,a,f,d,Ue),0==c.length)return o.textSize(l*le),void M o.text('"'+i+'"',e,t);for(s=0,h=[],c=[];o.textWidth(d)>n/le;)l=l*n/le/o.textWidth(d),f="",d="",[f,d]=rr(l,n,s,h,c,a,f,d,Ue)}else{l=30,o.textSize(l);for(let e=0;e<a.length;e++)s+=o.textWidth(" "+a[e]),s<=n/le?h.push(a[e]):s>n/le&&s<=n/le*2?c.push(a[e]):u.push(a[e]);for(let e=1;e<h.length;e++)f=f+" "+h[e];if(f='"'+h[0]+f,0==u.length){for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+c[c.length-1]+'"'}else if(1==c.length)d="... "+u[u.length-1]+'"';else{for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+"... "+u[u.length-1]+'"'M }}o.textSize(l*le);let r=1.25*(o.textDescent()+o.textAscent());o.text(f,e,t-r/2),o.text(d,e,t+r/2)}}function rr(e,t,n,r,i,o,a,l,s){s.textSize(e);for(let e=0;e<o.length;e++)(n+=s.textWidth(" "+o[e]))<=t/le?r.push(o[e]):i.push(o[e]);for(let e=1;e<r.length;e++)a=a+" "+r[e];if(a='"'+r[0]+a,0==i.length&&(a+='"',l=""),1==i.length)l=i[i.length-1]+'"';else{for(let e=0;e<i.length-1;e++)l=l+i[e]+" ";l=l+i[i.length-1]+'"'}return[a,l]}function ir(){const e=45*le;qe.textFont("Tahoma"),qe.stroke(st),qe.strokeWeight(2*le),qe.fillM (ct),qe.rect(width/2,e/2+height-87.5*le,600*le,90*le),qe.fill(st),qe.rect(width/2-150*le,e+height-170*le,300*le,30*le),qe.fill(ct),qe.rect(width/2+150*le,e+height-170*le,300*le,30*le),qe.noStroke(),qe.fill(ct),qe.textSize(15*le),qe.textStyle(BOLD),qe.text("PERCEPTRON INFORMATION",width/2-285*le,e+height-165*le),qe.fill(xt),qe.text("ARTWORK NAME:",width/2+10*le,e+height-165*le),qe.textAlign(RIGHT),qe.textStyle(ITALIC),qe.text("Perceptron #"+Et,width/2+285*le,e+height-165*le);const[t,n]=It.split(" ");let r;"60 Years"M ===It?r="1 Year":"60 Months"===It?r="1 Month":"60 Weeks"===It?r="1 Week":"60 Days"===It?r="1 Day":"12 Hours"===It&&(r="12 Minutes"),data=[["AI MODEL NAME:",B(12*le,Ht,140*le)],["SCALE:","1:"+Te],["NUMBER OF CLASSES:",$t.length],["BIRTH YEAR:",Rt],["NUMBER OF REBIRTHS:",sn.toString()],["AGE:",`${Math.ceil(Mt)} Perceptron Years`],["ONE PERCEPTRON YEAR:",`${r}`],["STATE:",Ot[Pe]],["ACTIVE NEURONS:",`${round(ln*rn)} / ${ln}`],["NEXT STATE TIME:",vr(new Date(on))]],qe.fill(xt);const i=data.length/2;for(let t=0;t<data.leM ngth;++t){const n=t<i,r=n?width/2-285*le:width/2+10*le,o=n?width/2-10*le:width/2+285*le,a=e+height-(135-t%i*15)*le;qe.textStyle(BOLD),qe.textAlign(LEFT),qe.textSize(12*le),qe.text(data[t][0],r,a),qe.textStyle(ITALIC),qe.textAlign(RIGHT),qe.textSize(12*le),qe.text(data[t][1],o,a)}}function or(){Ke.textFont("Trebuchet MS"),Ke.noStroke(),pr(Ke,600*le,200*le),gr(Ke,width/2-155*le,width/2-5*le,height/2+115*le,height/2+155*le,"UPDATE"),gr(Ke,width/2+5*le,width/2+155*le,height/2+115*le,height/2+155*le,"CLOSE"),Ke.textAligM n(LEFT),Ke.fill(xt),Ke.text("UPDATE BITCOIN FULL NODE ADDRESS",width/2-252.5*le,height/2-55*le),Ke.text("UPDATE MODEL ADDRESS",width/2-252.5*le,height/2+20*le),Ke.textAlign(RIGHT),Ke.textStyle(ITALIC),Ke.textSize(15*le),0==wn&&Ke.text("(*) Invalid Address",width/2+252.5*le,height/2-53*le),0==vn&&Ke.text("(*) Invalid Model",width/2+252.5*le,height/2+23*le)}function ar(){je.textFont("Trebuchet MS"),je.fill(st),je.textSize(50*le),je.stroke(st),je.strokeWeight(1*le),je.text("main()",width/2,height/2)}function lr(){un>=M 20&&1==dn&&(dn=!1,un=0),dn&&(Ze.textFont("Trebuchet MS"),Ze.stroke(st),Ze.fill(ct),Ze.rect(width/2,height/2,600*le,150*le,25*le),Ze.fill(xt),Ze.textSize(75*le),Ze.noStroke(),1==Pe?Ze.text("GROWING",width/2,height/2+5*le):3==Pe?Ze.text("AGING",width/2,height/2+5*le):4==Pe?Ze.text("DEAD",width/2,height/2+5*le):5==Pe&&Ze.text("BIRTH",width/2,height/2+5*le)),un>=20&&0==dn&&(dn=!0,un=0,Bt++,3==Bt&&(fn=!1))}function sr(e,t,n,r){let i=[],o=r/(n.length+1),a=color(e),l=color(t);i.push(a);for(let e=0;e<n.length;e++){let t=coM lor(n[e]);for(let e=1;e<=o;e++){let n=lerpColor(a,t,e/o);i.push(n)}a=t}for(let e=1;e<o;e++){let t=lerpColor(a,l,e/o);i.push(t)}if(i.push(l),i.length>r)i.splice(r);else if(i.length<r){let e=i[i.length-1];for(;i.length<r;)i.push(e)}return i}function hr(e,t){let n=e.length,r=Math.floor(t*n);return r>=n&&(r=n-1),e[r]}function cr(e){e=e.replace("#","");var t=parseInt(e,16);return color(t>>16&255,t>>8&255,255&t)}function ur(e,t,n,r,i,o,a,l){var s=a.drawingContext.createLinearGradient(e,t,n,r);s.addColorStop(0,i),s.addColM orStop(1,o),a.drawingContext.strokeStyle=s,a.drawingContext.globalAlpha=l,a.line(e,t,n,r),a.drawingContext.globalAlpha=1}function fr(e,t){t.drawingContext.setLineDash(e)}function dr(e,t){let n=color(e),r=red(n),i=green(n),o=blue(n);return color(r,i,o,255*t)}function xr(e,t,n,r){return mouseX>e&&mouseX<t&&mouseY>n&&mouseY<r}function gr(e,t,n,r,i,o){e.strokeWeight(1*le),e.stroke(st);const[a,l]=xr(t,n,r,i)?[xt,ct]:[ct,xt];e.fill(a),e.push(),e.rectMode(CORNERS),e.rect(t,r,n,i,5*le),e.pop(),e.noStroke(),e.textSize(20*leM ),e.fill(l),e.text(o,(t+n)/2,(46*r+54*i)/100)}function pr(e,t,n){e.fill(0,0,0,75),e.rect(width/2,height/2,width,height),e.stroke(st),e.fill(ct),e.rect(width/2,height/2,t,n,25*le)}function mr(e,t){resizeCanvas(e,t,!0),Xe.resizeCanvas(e,t,!0),$e.resizeCanvas(e,t,!0),We.resizeCanvas(e,t,!0),Ue.resizeCanvas(e,t,!0),qe.resizeCanvas(e,t,!0),Qe.resizeCanvas(e,t,!0),je.resizeCanvas(e,t,!0),Ze.resizeCanvas(e,t,!0),Ke.resizeCanvas(e,t,!0),Je.resizeCanvas(e,t,!0),et.resizeCanvas(e,t,!0)}function br(e,t,n,r,i,o){const a=J(e);rM eturn a.position(t,n),a.size(r,i),a.style("opacity","0"),a.mouseClicked(o),a}function yr(){return null!=vt&&vt?.isFocused()||null!=zt&&zt?.isFocused()}function wr(e,t,n,r){let i;if(e<=3){i=`Hey ${String.fromCodePoint(128075)}, I'm ${n}, ${t} years old. I can detect ${r.length} NFT collections: `;let e=0;for(let t=0;t<r.length;++t){const n=r[t];if(e+n.length>500){i+=", etc";break}t==r.length-1?i+=", and ":t>0&&(i+=", "),i+=n,e+=n.length}i+=". ",t<=5?i+="However, I am only a baby, so my recognition ability is not accM urate. I'm in the state of Growing both looks and intelligence.":t<=13?i+="I am now a child. My recognition ability is becoming better, but still not very accurate. I'm in the state of Growing both looks and intelligence.":t<=25?i+="I have grown up to be a teen. My recognition ability almost reaches the peak, but I will still mess up sometimes. I'm in the state of Growing both looks and intelligence.":t<=50?i+="I finally reach adulthood. My recognition is fully functional now. I'm in the Stable state, where I am thM e most intelligent with all neurons activated.":t<=60&&(i+="I am now an old Perceptron, so my recognition ability is no longer the best. I'm in the Decaying state, meaning that my neurons are dying, and my intelligence is decreasing over time.")}else 4==e?i=`${n} is Dead. However, this is not the end to its story...`:5==e&&(i=`${n} is now in the Rebirth state, and is preparing to start a new life.`);return i}function vr(e){const t=e.getDate(),n=e.toLocaleString("en-US",{month:"long"}),r=e.getFullYear();let i=e.getHM ours().toString();1==i.length&&(i="0"+i);let o=e.getMinutes().toString();return 1==o.length&&(o="0"+o),`${Y(t)} ${n} ${r} | ${i}:${o}`}saveCanvasAtCurrentTime=()=>{save(N())},save4KCanvasAtCurrentTime=()=>{const e=width,t=height,n=min(4096/min(e,t),1e4/max(e,t)),r=e*n,i=t*n;mr(r,i),zn=!0,$n(r,i),qn();let o="4K_"+N()+".png";saveCanvas(et,o),mr(e,t),$n(e,t),zn=!1};const zr=[["60 Years",3,365],["60 Months",40,30],["60 Weeks",37,7],["60 Days",20,1]],Vr=[["1943",1],["1951",1.5],["1957",2],["1969",2.5],["1970",3],["1980"M ,3.5],["1982",4],["1986",4.5],["1988",5],["1997",5.5],["1998",6],["2002",6.5],["2009",7],["2012",7.5],["2014",8],["2015",8.5],["2016",9],["2023",15]],_r=[["Plain",20],["Dotted",40],["Squared",40]],Mr=[["Basic",30],["Standard",60],["Advanced",10]],Er=[["MNIST",70],["CIFAR",25],["IMAGENET",5]],Sr=[["Theano",60],["Torch",30],["TensorFlow",10]],Rr=[["Whitepaper",2],["Blackboard",2],["Blueprint",2],["Nak",74/14],["Jims",74/14],["Level 10",74/14],["Flips",74/14],["Level 14",74/14],["III",74/14],["XMB",74/14],["Info",74/1M 4],["Adventure",74/14],["Marigold",74/14],["Phoenix",74/14],["Love",74/14],["Cachet",74/14],["Human",74/14],["Twilight",3],["Sunset",3],["Aurora",3],["Liminal Space",3],["D Vu",3],["Lucid Dream",3],["Parallel",1],["Multiverse",1]];function Ir(e){for(let e=0;e<100;++e)random(1);return{visual:{pattern:k(_r),hardwareAcceleration:k(Mr),nodeFill:k(Er),nodeShape:k(Sr),colorPalette:k(Rr),lifeCycle:k(zr),birthYear:k(Vr)},training:e}}function Cr(e){window.$generativeTraits={"Network Architecture":e.training.structure_gM en,"Hidden Layers":e.training.n_layers,"Max Neurons Per Hidden Layer":e.training.max_nodes,"Activation Function":e.training.activation_func,"Training Epochs":e.training.epoch_num,Dataset:e.visual.nodeFill,"Deep Learning Framework":e.visual.nodeShape,"Hardware Acceleration":e.visual.hardwareAcceleration,"Paper Pattern":e.visual.pattern,"Life Cycle":e.visual.lifeCycle,"Birth Year":e.visual.birthYear,"Color Palette":e.visual.colorPalette}} <script defer src="https://static.cloudflareinsights.com/beaconMS .min.js/v2b4487d741ca48dcbadcaf954e159fc61680799950996" integrity="sha512-D/jdE0CypeVxFadTejKGTzmwyV10c1pxZk/AqjJuZbaJwGMyNHY3q/mTPWqMUnFACfCTunhZUVcd4cV78dK1pQ==" data-cf-beacon='{"rayId":"7b481d87bc1b546d","version":"2023.3.0","b":1,"token":"6c07c178c94442f695e7a0a2aaee641a","si":100}' crossorigin="anonymous"></script> text/plain;charset=utf-8 text/plain;charset=utf-8 {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "laser"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "cape"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "bloody"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "tiger"}, {"trait_type": "Mane", "value": "fire"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "lamp"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "rainbow"}, {"trait_type": "Claws", "value": "honey pot"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "cape"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "golden"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "shield"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "blue fire"}, {"trait_type": "Claws", "value": "fire"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "pauldrons"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "cape"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "rainbow"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "laser"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "arrow wounds"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "golden armor"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "sword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "golden"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "dragon wings"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "pirate flag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "arrow wounds"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "pirate flag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "rainbow"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "blue fire"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "none"}]} text/plain;charset=utf-8 {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "fire"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "rainbow"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "laser"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "lightning bolt"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "pirate flag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "golden armor"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "moon"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "dagger"}]} text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "orc"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "skull"}, {"trait_type": "Artifacts", "value": "cape"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "tiger"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "bag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "honey pot"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "shield"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "laser"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "pauldrons"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "honey pot"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "orc"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "cape"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "sword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "axe"}]} 1d/SBICrypto.com Pool/ text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"wang","amt":"100000"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"pork","amt":"408"}h! <?xml version="1.0" encoding="UTF-8"?><svg id="gemimi" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" viewBox="0 0 1440 1440"><defs><style>.cls-1{fill:url(#linear-gradient);}.cls-2{fill:#fff;}.cls-3{fill:url(#linear-gradient-2);}</style><linearGradient id="linear-gradient" x1="120.22" y1="575.36" x2="1319.78" y2="1581.9" gradientTransform="translate(0 1438.63) scale(1 -1)" gradientUnits="userSpaceOnUse"><stop offset="0" stop-color="#6aba71"/><stop offset=".25" stop-color="#64c195"/><sM top offset=".5" stop-color="#8da07c"/><stop offset=".75" stop-color="#b7529a"/><stop offset="1" stop-color="#aa5457"/></linearGradient><linearGradient id="linear-gradient-2" y1="-4592.92" y2="-3586.38" gradientTransform="translate(0 5169.65)" xlink:href="#linear-gradient"/></defs><rect class="cls-1" width="1440" height="720"/><rect class="cls-3" y="720" width="1440" height="720"/><g><path class="cls-2" d="M413.81,894.41l-.15,.07c.07,.01,.15,.02,.22,.04-.02-.04-.05-.07-.07-.11Zm117.1,41.36h-.04l.09,.06s-.04-.04-.05-M .06Zm43.51-121.78c.8-1.24,2.26-1.46,3.5-2.13,2.59-1.17,4.93-2.62,7.24-4.11,.27-.17,.34-.53,.54-.86-16.76-10.39-14.43-4.32-3.92-14.28,.15-.15,.13-.4,.19-.6h0c.78,0,1.52,.05,2.24,.43,3.02,1.61,6.06,3.19,9.1,4.77l-.08-13.44c-.96-.41-1.56-1.06-2.84-1.06-2.86,3-4.94,6.91-8.42,9.27,.27-.86-.97-1.14-1.51-1.6-3.55-2.26-7.45-4.09-10.77-6.66,2.66-2.83,5.22-5.57,7.84-8.35,4.7,1.94,8.14,5.03,12.97,6.72,1.13-1.12,1.82-2.34,2.7-3.63l-.05-8.12c-2.76-1.4-5.58-3-8.25-4.47-.72,.08-1.06,.36-1.33,.76-1.81,2.65-3.76,5.51-5.74,7.99-.81,M .25-1.21-.08-1.6-.34-3.19-2.15-6.36-4.33-9.56-6.47-.7-.47-1.25-1.12-2.41-1.27-2.4,2.53-5.18,4.87-7.96,7.2-.79,.91,.83,1.48,1.36,2.02,3.78,2.63,7.52,5.22,11.34,7.82-2.35,3.1-6.56,4.5-9.53,6.83,.17,.71,.79,.98,1.28,1.3,3.7,2.49,7.61,4.76,11.21,7.39,1.27,1.39-10.5,4.96-11.01,6.56,3.61,2.57,7.54,4.81,11.29,7.19,.45,.28,.75,.6,.67,1.18-3.76,1.75-7.95,3.15-11.95,4.52-2.27,.86,1.46,2.14,2.14,2.82,2.46,1.51,4.92,3.01,7.38,4.51,.53,.32,1.13,.58,1.34,1.13-.34,.52-.94,.73-1.59,.9-3.96,1.07-7.91,2.14-11.86,3.21-.55,.23-2.38,.4M -1.57,1.28,3.41,2.29,6.93,4.47,10.42,6.65,.24,.15,.24,.54,.38,.88-5.74,1.54-11.48,2.55-17.3,3.47-.81,.11-.83,.77-.16,1.15,2.63,1.87,5.36,3.62,8.04,5.4,.73,.53,1.92,.79,1.91,1.83-.67,.69-1.69,.56-2.59,.69-5.83,.83-11.65,1.73-17.53,2.24-.35,.04-.62,.58-.4,.77,2.6,2.24,5.54,4.07,8.29,6.13,.54,.49,2.3,1.3,1.03,1.89-5.03,.87-10.17,.83-15.25,1.28-2.55,.17-5.1,.31-7.65,.49-.23,.01-.54,.15-.62,.3-.09,.16-.04,.45,.1,.58,2.66,2.32,5.51,4.43,8.25,6.66,2.35,1.81-.1,1.62-1.64,1.78-8.35,.49-16.69,.32-25.04,.37-.12,.01-.32,.07-.3M 4,.13-.06,.19-.17,.47-.06,.59,2.76,2.82,5.82,5.36,8.68,8.09,.28,.34,.26,.99-.39,.95-9.13-.13-18.32-.33-27.43-1.1-1.46-.17-2.95-.13-4.42-.17-1.13,.34-.06,1.29,.34,1.81,2.12,2.23,4.26,4.45,6.38,6.68,.34,.52,1.68,1.33,.77,1.84-10.18,.2-20.35-1.57-30.46-2.58-2.4-.28-4.79-.62-7.18-.91-.21-.02-.56,.1-.66,.24-.1,.15-.07,.44,.05,.6,2.57,3.28,5.19,6.53,7.72,9.85,.2,.26-.12,.75-.47,.72-1.48-.1-2.97-.14-4.42-.35-13.81-1.91-27.6-4.17-41.27-6.83,2.63,3.95,5.16,7.95,7.71,11.95,.11,.17,.15,.52,.03,.6-1.14,.68-2.55,.01-3.78-.1-12.M 08-2.2-24.02-4.83-35.87-7.7-4.38-.98-8.66-2.43-13.1-3.11-.46,.09-.28,.85-.18,1.15,1.9,3.68,3.83,7.35,5.73,11.04,.21,.52,.72,1.45-.13,1.64-21.12-4.39-41.69-11.04-62.13-17.4-.11,.41-.35,.74-.26,1,1.59,4.57,3.52,9.04,5.3,13.55,.12,.31,.23,.7-.18,.86-25.16-6.17-49.34-16.37-73.72-25.09-.29-.1-.86,.28-.81,.53,.05,.32,.09,.64,.18,.96,1.26,4.84,2.69,9.65,3.81,14.53,.04,.21,.04,.43,.06,.65,.02,.26-.57,.55-.9,.42-5.25-1.96-10.53-3.87-15.72-5.91-23.94-9.12-47.49-19.25-70.75-29.82-.51-.22-1.18,.08-1.14,.52,.14,1.5,.27,3,.46,4.M 5,.38,4.57,1.66,9.27,1.58,13.79-.9,.32-1.55-.2-2.21-.49-33.98-14.83-67.29-30.94-100.02-48.14-1.1-.42-3.36-2.23-3.28,.1,.18,6.76-.36,13.61,.26,20.32,28.67,14.48,57.92,27.76,87.57,40.34,5.84,2.46,11.71,4.87,17.57,7.29,.82,.34,1.61,.8,2.68,.67-.02-5.95-1.55-11.99-2.05-17.96-.1-.86,.29-1.3,1.43-.85,16.61,6.95,33.11,13.97,50.12,20.24,12.73,4.6,25.41,9.55,38.39,13.56,1.18,.09,.47-2.2,.27-2.87-1.12-4.32-2.27-8.63-3.39-12.96-.12-.46-.18-1.42,.55-1.27,17.64,5.92,35.05,12.26,53.03,17.39,6.94,2.05,13.94,4,20.91,5.98,.42,.14,1M .5,.38,1.63-.25-1.34-4.52-3.31-8.86-4.91-13.31-.21-.51-.51-1.49,.19-1.68,20.13,5.44,40.31,11.16,60.82,15.32,.68,.06,3.13,.9,2.88-.39-1.96-4.25-4.29-8.34-6.21-12.61-.1-1.25,2.28-.21,2.99-.18,12.2,2.68,24.41,5.32,36.83,7.32,18.34,2.28,17.11,6.49,7.25-10-.24-.67,1.07-.56,1.51-.48,14.4,2.47,28.87,4.3,43.47,5.54,.26,.02,.53,0,.8,0,.35,0,.71-.43,.54-.68-1.97-2.87-4.38-5.42-6.51-8.16-2.4-2.93-1.53-2.71,1.56-2.47,9.62,1.18,19.3,1.6,28.97,2.18,2.39,.03,4.87,.37,7.24,.05,.17-.05,.34-.37,.29-.51-2.06-2.82-4.87-5.14-7.19-7.78-M .41-.43-.75-.89-1.12-1.34-.02-1.12,1.88-.56,2.62-.67,10.1,.1,20.2,.66,30.3,.04,.36-.01,.59-.52,.34-.75-2.76-2.83-6.05-5.14-8.65-8.09-.19-.22,.14-.69,.5-.7,9.29-.17,18.57-.51,27.8-1.55,.1,0,.28-.39,.2-.53-2.29-2.45-5.3-4.27-7.84-6.49-.36-.45-1.8-1.18-1.01-1.76,2.26-.27,4.52-.55,6.8-.72,5.74-.53,11.51-.92,17.14-2.13,.13-.03,.28-.43,.19-.52-2.74-2.46-6.04-4.27-9.02-6.44-.4-.28-.82-.57-.75-1.14,6.39-1.48,13.19-1.87,19.6-3.43,.48-.12,1.44-.3,1.24-.94-2.74-2.29-6.05-3.93-9-5.95-.53-.33-1.1-.63-1.25-1.33,5.84-1.58,11.86-2M .67,17.66-4.39,.3-.11,.43-.67,.18-.82-3.04-2.01-6.27-3.73-9.37-5.62-.53-.31-1.13-.61-1.27-1.35,5-1.75,10.62-2.81,15.44-5.06,0-.68-.62-.96-1.16-1.26-3.33-2-6.98-3.6-10.11-5.88-.5-.88,1.55-1.13,2.12-1.5,3.54-1.52,7.37-2.55,10.73-4.44,.15-.1,.13-.37,.21-.66-4.01-2.34-8.22-4.41-12.15-6.94Zm18.92-12.83c-2.06,1.97-4.39,3.76-6.48,5.64,.12,.6,.52,.87,.99,1.1,1.85,.93,3.7,1.86,5.55,2.78l-.06-9.52Zm.1,16.6c-6.6,4.24-7.56,2.65,.04,6.69l-.04-6.69Zm.08,13.56c-1.68,.79-3.41,1.52-5.19,2.18-.72,.26-1.53,.45-2.03,1.24,2.27,1.46,4.7M 7,2.67,7.27,3.92l-.05-7.34Zm.33,53.42c-2.41,.65-4.85,1.28-7.25,1.95-.53,.15-.6,.67-.11,1.01,2.44,1.67,4.94,3.25,7.41,4.88l-.05-7.84Zm.13,20.02l-.06-10c-7.24,1.93-14.57,3.5-22,4.84-.94,.06-2.58,.57-1.46,1.48,2.25,1.88,4.62,3.61,6.92,5.44,.68,.44,1.94,1.55,.53,1.95-9.48,2.16-19.24,2.94-28.78,4.76-.08,.73,.44,1.1,.87,1.5,2.1,1.97,4.21,3.93,6.3,5.9,.43,.4,.94,.79,.94,1.39-4.3,1.46-9.27,1.37-13.8,2.02-6.83,.67-13.65,1.31-20.51,1.64-1.38,.44,.4,1.74,.78,2.37,2.38,2.58,4.79,5.15,7.2,7.72,2.4,.26,4.78-.31,7.16-.53,9.61-1.1M 3,19.27-1.84,28.66-4.08-.1-.34-.08-.69-.29-.9-2.5-2.77-5.65-4.88-7.87-7.89,10.12-2.08,20.28-3.43,30.23-6.09-.05-.29,.01-.55-.12-.69-2.37-2.25-5.06-4.16-7.57-6.27-.38-.31-.7-.63-.63-1.23,4.45-1.09,9-2.17,13.5-3.33Zm.99-32.35c-2.76-1.72-5.72-3.18-8.35-5.08-.9-.97,6.19-2.37,7.11-2.88l-.13-21.32c-3.48,1.18-6.96,2.36-10.45,3.54-.52,.17-.91,.41-1.07,.99,3.16,1.99,6.58,3.7,9.83,5.54,.43,.23,.84,.49,.94,1.05-5.85,2.28-12.12,3.42-18.15,5.21-.37,.12-.44,.58-.11,.78,3.2,1.97,6.46,3.88,9.64,5.87,.26,.17,.31,.54,.51,.91-6.94,2-M 14.02,3.04-21.07,4.54-1.49,.91,7.57,5.73,8.57,6.72,.42,.28,.85,.54,.86,1.04-.73,.52-1.69,.62-2.59,.76-7.21,1.33-14.53,2.2-21.84,3.16-1.28,.61,.46,1.44,.94,1.96,2.31,1.82,4.62,3.62,6.94,5.43,.39,.3,.74,.61,.67,1.1-2.46,.9-5.29,.79-7.89,1.18-6.92,.85-13.99,.96-20.88,1.67-.15,.11-.28,.46-.18,.55,2.01,1.88,4.08,3.71,6.07,5.61,.92,.88,2.33,1.49,2.6,2.76-1.18,1.03-2.77,.47-4.16,.65-9.65,.86-19.39,.57-29.07,.77-.37,.01-.72,.46-.53,.69,2.1,2.68,4.62,5.04,6.91,7.56,.4,.43,.74,.9,1.09,1.35,.31,1.2-3.74,.7-4.58,.85-11.59,.04-M 23.18-.45-34.71-1.3-1.4,.35,.27,1.72,.6,2.39,1.98,2.56,3.98,5.12,5.96,7.69,.28,.36,.54,.74,.17,1.28-15.39-.18-30.74-2.51-46.04-4.02-.86,.22-.23,1.13,.02,1.63,2.04,3.27,4.21,6.49,6.2,9.79,1.05,2.05-3.81,.63-4.75,.73-13.94-1.83-27.83-4-41.62-6.51-2.62-.46-5.24-.96-7.87-1.43-.35-.07-.82,.32-.72,.58,1.54,3.82,3.64,7.4,5.4,11.13,.29,.59,.5,1.22,.69,1.84,.03,.1-.3,.36-.49,.38-21.25-3.33-42.24-8.47-63.02-13.87-2.41-.68-1.88,.72-1.3,2.37,1.35,3.61,2.73,7.21,4.07,10.83,.1,.62,.79,1.74-.12,2.01-18.43-3.91-36.64-9.46-54.62-14M .85-6.41-1.98-12.74-4.11-19.12-6.14-.98-.31-1.9-.83-3.03-.71-.42,.5-.3,1.04-.17,1.56,1.1,5.08,2.88,10.08,3.57,15.21-.37,.84-2.84-.29-3.59-.39-15.65-4.96-31.18-10.14-46.54-15.64-14.09-4.82-27.75-10.7-41.65-15.64-.62-.07-.66,.56-.67,.97,.61,4.82,1.23,9.65,1.84,14.47,.15,1.17,.47,2.34,.13,3.51-37.08-12.51-73.52-29.42-109.11-45.47-.77-.32-1.44-.08-1.47,.52-.11,6.57,.04,13.14,.06,19.71-.04,.86,.5,1.4,1.41,1.79,1.18,.51,2.33,1.08,3.51,1.59,34.26,14.84,69.04,28.67,104.35,41.11,.97,.35,1.99,.62,3.01,.9,.3,.08,.57-.06,.58-.M 29-.05-6.12-1.56-12.21-1.89-18.31,0-.25,.6-.62,.87-.52,.99,.33,1.99,.65,2.96,1.01,29.09,10.86,58.98,20.48,88.96,29.08,2.01,.6,1.5-1.28,1.19-2.44-1.02-4.77-2.55-9.45-3.11-14.3-.01-.11,.41-.37,.56-.34,1.03,.21,2.06,.44,3.05,.74,24.51,7.32,49.35,14.26,74.52,19.17,1.05-.15,.29-1.6,.18-2.28-1.34-3.94-2.71-7.88-4.07-11.83-.69-1.69,.94-1.33,1.99-1.09,19.73,4.6,39.52,8.58,59.59,11.75,1.97,.11,5.96,1.61,3.76-2.03-1.59-3.64-3.64-7.14-4.91-10.91-.03-.13,.26-.43,.41-.44,.66-.03,1.34-.05,1.98,.04,17.21,2.71,34.48,5.16,51.86,6.5M 3,.39,.03,.79-.04,1.18-.1,.3-.05,.46-.25,.37-.49-.19-.51-.35-1.04-.65-1.51-1.92-3.21-4.09-6.27-5.86-9.57-.13-.24,.23-.73,.53-.72,10.21,.42,20.34,1.86,30.57,2.16,5.23,.38,10.51,.55,15.74,.41,.33-.02,.64-.48,.47-.73-2.29-3.19-4.73-6.27-7.09-9.4-.19-.26-.53-.6-.18-.88,.24-.19,.69-.35,1.02-.32,10.62,.61,21.29,.19,31.93,.23,2.02-.02,4.04-.16,6.05-.28,1.1-.07,1.44-.6,.85-1.28-2.13-2.5-4.46-4.88-6.68-7.3-.41-.51-1.45-1.54-.25-1.81,11.28-.3,22.58-.76,33.77-2.22,.02-.27,.15-.53,.04-.65-2.58-2.8-5.84-4.98-8.32-7.88-.19-.22,.M 1-.74,.45-.77,1.73-.15,3.48-.24,5.21-.45,7.71-1,15.45-1.72,23.1-3.09,1.94-.51-1.44-2.17-1.93-2.77-2.06-1.55-4.14-3.09-6.18-4.65-.25-.19-.32-.54-.53-.93,8.34-1.8,16.97-2.42,25.09-4.91,.23-.9-.85-1.24-1.42-1.76-2.36-1.61-4.75-3.19-7.1-4.8-.28-.19-.54-.51-.56-.78-.02-.34,.44-.51,.83-.6,3.1-.72,6.23-1.39,9.31-2.15,3.35-.82,6.67-1.71,10-2.57,.54-.14,.94-.39,1.19-.94-.45-.32-.91-.7-1.44-1.01Zm20.09-105.43c-.01,.05-.02,.1-.03,.15,.03,.01,.07,.03,.1,.04,.04-.05,.07-.09,.11-.14-.06-.02-.12-.03-.18-.05Zm7.28,16.21s-.03,.06-.M 04,.09c.02,0,.05,.02,.07,.02,.02-.03,.03-.06,.05-.09-.03-.01-.05-.02-.08-.02Zm6.44,15.51s-.02,.05-.03,.08c.04,0,.07,.03,.11,.04l-.08-.12Zm6.36,43.49s-.07-.03-.11-.04v1.93c1.04-.69,1.53-1.42,.11-1.89Zm.69-13.86c-.27-.16-.58-.31-.89-.43l.02,2.16c.39-.45,1.43-1.11,.87-1.73Z"/><path class="cls-2" d="M767.88,877.69c-.6,.82-1.22,1.64-1.83,2.45,1.84,2.23,3.62,4.38,5.39,6.52,.21,.25,.85,.27,1.07,.03,4.19-4.8,7.47-10.24,11.14-15.34,.18-.25,.87-.29,1.05-.07,1,1.27,2.01,2.54,2.98,3.83,.76,.66,1.28,3.09,2.55,2.28,3.55-4.75,6.3M 5-9.99,9.67-14.89,1.3-1.46,2.78,2.99,3.54,3.8l-.19,8.28c-2.4,3.61-4.77,7.22-7.17,10.83-.54,.68-.92,1.5-1.94,1.47-1.2-2.27-2.4-4.55-3.59-6.83-.22-.41-.56-.71-1.28-.84-3.61,4.89-6.97,9.93-10.85,14.68-.57,.5-1.23,1.88-2.13,1.5-1.03-1.23-1.45-2.78-2.32-4.11-.64-1.02-.67-2.34-2.18-2.95-1.19,.6-1.66,1.64-2.38,2.52-3.41,4.14-6.79,8.29-10.18,12.44-.37,.44-.71,.9-1.55,1.05-1.94-2.28-3.41-4.82-5.22-6.94-.09-.73,.36-1.01,.65-1.37,4.06-4.95,8.12-9.9,12.16-14.87,.71-.86,.66-1.19-.25-1.98-1.91-1.66-3.87-3.28-5.88-4.63-.92-.07-1.M 14,.38-1.41,.71-4.06,4.91-7.55,10.03-12.08,14.6-2.93-1.29-4.87-3.7-7.59-5.09-1-.01-1.29,.53-1.68,.93-4.69,4.52-8.84,9.72-13.9,13.8-2.02-1.13-6.33-4.13-7.79-5.41,4.67-4.74,9.26-9.55,13.95-14.25,.37-.34,1-.42,1.44-.15,2.53,1.52,4.87,3.08,7.49,4.5,4.36-4.36,8.25-9.07,11.9-13.93,1.03-1.3,1.38-1.37,2.78-.49,2.22,1.26,4.04,3.05,6.43,3.97,4.21-4.98,7.17-10.29,11.15-15.46,3.09,1.27,4.67,3.42,7.51,5.07,3.04-4.27,5.09-9.06,7.74-13.57,.79-1.3,1.2-2.59,2.82-1.23,1.53,1.21,3.04,2.45,4.56,3.67,1.29,1.05,1.67,.98,2.48-.49,1.87-3.M 56,3.59-7.2,5.39-10.79,.6-1.07,.84-2.39,1.89-3.13,.91,.28,1.31,.89,1.83,1.44l-.37,16.46c-.88,1.63-1.77,3.26-2.84,4.81-.33-.05-.66-.01-.8-.12-1.97-2.06-3.59-4.35-5.7-6.3-1.69,.78-1.98,2.73-3,4.15-2.36,3.72-4.18,7.83-6.92,11.29-.09,.09-.59,.08-.71-.02-2.11-1.72-3.78-4.21-6.28-5.33-3.43,3.99-6.24,9.23-9.55,13.5Z"/><path class="cls-2" d="M987.18,901.64s-.05,.02-.08,.03c-.01-.05-.03-.11-.04-.16l.12,.13Z"/><path class="cls-2" d="M961.06,978.63c.34-7.36,.31-14.73,.32-22.1,0-.54-.05-1.61-.82-1.54-4.22,2.18-8.01,5.09-12.06,M 7.58-3.11,2.43-1.97-1.85-2.07-3.61,.4-9.7,.03-19.39-.32-29.08-.03-.56-.1-1.6-.88-1.52-3.93,2.5-7.37,5.69-11.09,8.47-.53,.51-1.8,1.12-1.92-.09-.28-9.79-.43-19.63-1.33-29.37-.91-.87-1.96,.68-2.66,1.2-2.55,2.37-5.08,4.75-7.63,7.12-1.11,.97-2.32,2.04-2.38-.3-.55-7.1-1.07-14.19-1.65-21.28-.09-1.18-.4-2.34-.63-3.5-.01-.07-.16-.15-.27-.17-.69-.09-1.2,.85-1.7,1.23-2.93,3.07-5.57,6.42-8.7,9.3-.47,.27-.84-.35-.9-.76-.74-7.29-1.42-14.6-2.64-21.85-.97-1.34-2.52,1.73-3.23,2.37-2.18,2.7-4.24,5.52-6.5,8.17-.14,.15-.44,.29-.65,.28M -.18,0-.36-.22-.5-.37-.33-1.88-.48-3.86-.77-5.77-.6-4.4-1.15-8.79-2.06-13.14-.06-.3-.33-.57-.53-.85-.52-.09-1.01,.69-1.33,1-1.16,1.09-7.6,12.09-8.44,10.4-1.68-5.61-1.82-11.59-3.31-17.27-.44,.15-.94,.19-1.09,.39-2.59,3.75-5,7.63-7.54,11.42-.27,.41-.63,.69-1.35,.53-.8-4.67-1.87-9.33-2.89-13.97-.11-.51-.23-1.05-.91-1.33-.75,.36-.98,.99-1.33,1.57-2.17,3.58-4.35,7.16-6.53,10.74-.24,.4-.54,.75-1.31,.72-1.62-4.28-1.71-8.91-3.56-13.14-.82-.77-2.45,2.85-2.95,3.48l.28-12.5c.77,2.25,1.46,4.31,2.28,6.58,.42-.15,.93-.2,1.05-.4,M 1.02-1.76,1.97-3.54,2.96-5.31,1.37-2.45,2.74-4.9,4.15-7.34,.07-.12,.46-.14,.7-.16,.4,.13,.47,.75,.64,1.1,1.24,3.64,2.42,7.28,3.24,11,.11,.54,.27,1.06,.95,1.33,.78-.33,1-.98,1.34-1.55,1.94-3.32,3.86-6.64,5.79-9.96,.28-.48,.51-1,1.19-1.25,.77,.53,.89,1.28,1.06,2,.87,3.49,1.7,6.98,2.58,10.46,.26,1.05,.61,2.09,.94,3.13,.11,.13,.54,.14,.66,.03,2.56-3.18,4.41-6.91,6.71-10.29,.48-.63,.83-1.56,1.76-1.55,1.86,4.92,2.88,10.52,3.87,15.75,.1,.63,.4,1.24,.63,1.86,.03,.07,.18,.14,.28,.14,.74-.06,1.18-1.2,1.69-1.7,1.93-2.71,3.84-M 5.44,5.77-8.16,1.82-2.6,2.11-1.53,2.67,.93,1.16,5.96,2.29,11.91,3.45,17.98,.41-.07,.92-.03,1.07-.19,2.82-3.27,5.4-6.7,8.16-10.02,.19-.22,.73-.5,.92-.43,.3,.11,.56,.48,.62,.77,.37,1.59,.73,3.18,.97,4.78,.92,5.85,1.64,11.77,2.65,17.6,1.11,.21,1.53-.59,2.23-1.21,2.83-2.86,5.34-6.04,8.41-8.66,.24-.18,.58-.08,.65,.16,1.58,5.84,1.86,11.95,2.56,17.94,.25,2.68,.59,5.36,.91,8.04,.22,.58,.78,.91,1.43,.35,3.06-2.73,6.09-5.47,9.17-8.19,.55-.4,1.15-1.1,1.91-.7,1.43,7.65,1.63,15.68,2.39,23.48,.18,2.25,.34,4.51,.51,6.77,.71,.9,1.M 85-.33,2.54-.73,3.34-2.53,6.64-5.09,10.16-7.4,1.65-.48,1.29,2.8,1.49,3.81,.57,9.81,.95,19.59,1.06,29.4,.15,.75-.27,2.21,.83,2.16,4.11-1.86,7.78-4.62,11.73-6.82,.74-.27,2.03-1.53,2.64-.56,1.13,12.95,.46,25.95,.35,38.93-5.16-2.16-10.46-4.28-15.89-6.36Z"/><path class="cls-2" d="M973.86,1028.79c2.19,.98,4.36,1.97,6.49,2.96-2.06,.81-4.03,1.81-6.16,2.4-.16,.04-.57-.14-.61-.26-.33-1.68,.2-3.41,.28-5.1Z"/><path class="cls-2" d="M993.1,983.16c0,2.94,0,5.88-.06,8.82-4.52-2.05-9.16-4.08-13.91-6.08,4.18-1.85,8.21-4.61,12.91-4.M 88,1.19,.07,.96,1.31,1.06,2.14Z"/><path class="cls-2" d="M1042.99,839.47c.02,.06,.04,.11,.05,.17-.04-.02-.09-.03-.13-.05l.08-.12Z"/><path class="cls-2" d="M1086.34,834.06s.02-.01,.03-.01h0v.05l-.03-.04Z"/><path class="cls-2" d="M1211.58,762.84l-.02,.02-.03-.03h.05Z"/><path class="cls-2" d="M1387.33,896.54c-21.73-23.75-44.17-46.88-67.4-69.26-2.44-2.34-1.91,.44-1.72,2.14,.59,5.15,1.21,10.29,1.78,15.44,.02,.13-.26,.31-.44,.42-.56,.09-1.06-.64-1.48-.94-7.95-8.01-16.01-15.96-24.2-23.82-11.09-10.22-21.93-21.42-33.71-30.7M 8-.84,.35-.31,1.34-.27,2.01,.91,4.14,1.85,8.26,2.75,12.4,.09,1.31,1,2.98-.15,4.02l.14-.07s-.08,.14-.08,.15c-.02-.03-.04-.05-.06-.08h0c-16.09-16-33.64-30.38-50.92-45.31-.9,.89-.09,2.05,.15,3.05,1.81,5.28,3.62,10.57,5.43,15.85,.36,1.03,.79,2.02,.19,3.04-13.43-11.95-27.67-23.25-41.94-34.3-.57-.45-1.07-.99-1.96-1.08-.4,.52-.16,1.03,.05,1.54l7.32,17.79c.1,.45,.56,1.16,.25,1.52-.87,.33-1.5-.6-2.16-1-11.58-8.96-23.26-18.24-35.49-26.36-.17-.08-.53,.15-.49,.33,1.24,2.84,2.49,5.69,3.76,8.52,1.68,3.75,3.38,7.49,5.07,11.24,.18M ,.4,.32,.8-.09,1.27-10.35-7.22-20.55-14.67-31.16-21.55-.51-.27-1.1-.8-1.71-.74-.31,.11-.35,.29-.23,.53,1.37,2.69,2.76,5.38,4.08,8.09,1.94,4.01,3.84,8.04,5.74,12.06,.07,.15-.11,.38-.22,.56-8.26-4.74-16.1-10.8-24.5-15.71-2.16-1.13-5.87-4.32-3.16,.61,2.76,5.49,5.54,10.98,8.3,16.47,.35,.7,.64,1.42,.93,2.13,.02,.06-.11,.19-.21,.25-.7,.16-1.39-.58-2.01-.83-6.69-4.17-13.38-8.36-20.31-12.27-1.92-.94-3.87-2.46-2.11,.97,2.82,5.59,5.67,11.17,8.49,16.75,.36,1.14,1.8,2.53,.7,3.6-6.83-4.43-14.12-8.7-21.62-12.13-.46,.03-.23,.79-.M 15,1.06,2.98,6.1,5.98,12.18,8.97,18.27,.41,1.22,1.77,2.61,.81,3.84,.06-.07,.13-.15,.23-.26-.12,.16-.19,.24-.26,.34-.01,0-.01-.01-.02-.01h0c-5.29-3.63-11.31-6.17-16.98-9.18-.72-.32-2.73-1.58-2.56-.08,3.84,7.89,7.23,15.95,10.7,24,.17,.41,.27,.81-.2,1.26-5.95-2.82-11.49-6.45-17.52-9.13-.37-.17-.67,.29-.66,.56,3.51,9.37,7.54,18.59,11,27.99,.16,.41,.34,.82,.01,1.33-5.7-2.04-10.83-5.67-16.56-7.73-.2-.06-.53,.16-.51,.35,1.44,4.72,3.44,9.27,5.03,13.94,7.26,23.25,10.36,18.22-10.94,10.03,3.39,10.99,7.09,21.95,9.76,33.12-.37,M 1.29-2.49-.4-3.33-.54-3.35-1.39-6.69-2.79-10.05-4.16-.55-.22-1.12-.55-1.96-.3,2.11,9.71,4.77,19.39,6.91,29.12,.39,1.58,.66,3.18,.96,4.78,.1,.52,.21,1.06-.21,1.57-.86,.16-1.52-.29-2.22-.56-3.29-1.25-6.55-2.53-9.82-3.79-.72-.37-2.53-.93-2.49,.24,1.74,11.77,4.39,23.4,5.74,35.23,.11,.83,.4,1.69-.11,2.51-.73,.2-1.31-.11-1.92-.32-3.46-1.19-6.92-2.39-10.39-3.57-.77-.28-2.35-.72-2.28,.6,1.3,13.84,3.16,27.69,3.32,41.59-.61,.18-1.1,.42-1.61,.45-5.29,.36-11.65,1.78-14.02,1.54-.46-.75-.41-1.63-.44-2.49-.39-12.92-1.31-25.85-2.5M 7-38.71-.04-.42-.67-.76-1.17-.65-4.12,.99-8.21,2.04-12.31,3.11-1.79,.2-1.29-2.04-1.59-3.16-1.18-11.21-1.73-22.56-4.14-33.58-4.29,1.61-8.56,3.44-12.66,5.41-.75-.34-.81-.89-.89-1.42-.85-5.88-1.55-11.78-2.57-17.64-.63-3.63-1.27-7.25-1.93-10.88-.15-.62-.41-1.99-1.33-1.6-3.3,2.14-6.3,4.7-9.48,7.02-.64,.39-1.88,1.73-2.49,.77-1.37-8.67-3.4-17.23-5.17-25.82-.18-.46-.5-1.75-1.22-1.34-3.64,2.57-6.47,6.13-10.03,8.81-.89,.22-1.01-1.04-1.24-1.63-.66-2.86-1.25-5.73-1.95-8.58-1.09-4.44-2.24-8.86-3.39-13.29-.13-.42-.93-.55-1.22-.2M 9-3.06,2.96-5.52,6.43-8.61,9.35-.26,.25-.85-.06-.95-.25-1.77-6.42-3.49-12.83-5.43-19.21-.15-.51-.5-.99-.77-1.47-.4-.19-.93,.38-1.18,.6-2.46,3.21-4.71,6.55-7.28,9.68-.12,.14-.47,.15-.84,.26-2.06-6.12-3.54-12.39-6.08-18.34-.69-.15-1.04,.15-1.28,.53-1.71,2.69-3.39,5.39-5.1,8.08-1.33,1.78-2.01,3.98-3.14,.51-1.74-4.63-3.02-9.44-5.12-13.93-.05-.12-.42-.17-.65-.2-2.56,3.03-4.28,7.56-6.46,11.04-.22,.41-.56,.69-1.24,.62-2.04-4.75-3.21-9.6-6.22-14.01-1.87,1.04-5.88,13.8-7.5,12.29-1.7-3.4-3.21-6.84-5.21-10.15-.27-.49-.55-.98-M 1.14-1.3-.72,.39-.92,1.02-1.18,1.61-1.7,3.72-3.22,7.55-5.09,11.19-.71-.04-1.02-.35-1.26-.74-1.29-2.16-2.57-4.31-3.88-6.46l-.43,18.85c1.54-3.06,2.96-6.17,4.58-9.19,.2-.37,.87-.55,1.13-.1,1.9,3.57,3.11,7.3,4.51,11.04,.11,.26,.48,.44,.85,.78,9.52-16.02,5.98-18.82,12.73,.64,1.21,.03,1.44-1.05,2.02-1.84,1.71-3.04,3.39-6.1,5.08-9.15,.28-.49,.53-.99,1.21-1.23,.17,.16,.41,.3,.48,.48,1.94,5.04,3.45,10.17,4.88,15.27,.94,.22,1.2-.46,1.66-1.07,1.87-2.98,3.72-5.97,5.6-8.95,.41-.52,1.04-1.7,1.84-1.26,2.08,5.16,2.99,10.7,4.54,16.M 04,.52,1.92,1.08,2.62,2.38,.61,2.06-2.9,4.12-5.8,6.19-8.7,.37-.43,1-1.34,1.63-.87,2.27,6.72,3.16,13.81,5.29,20.52,.31,.25,1-.3,1.21-.51,2.26-2.68,4.47-5.38,6.73-8.06,.55-.48,1.37-1.87,2.2-1.4,2.11,6.72,3.25,13.76,4.41,20.68,.13,.95,.5,1.88,.78,2.81,.02,.06,.22,.13,.3,.11,.25-.06,.55-.11,.7-.26,2.53-2.52,5.02-5.06,7.55-7.58,1.47-1.22,2.49-2.96,3.16,.03,.92,5.55,2.27,11.05,2.84,16.64,.24,2.26,.57,4.5,.9,6.75,.1,.73,.11,1.51,.78,2.12,1.04-.11,1.67-.98,2.46-1.57,2.43-2.01,4.85-4.04,7.29-6.05,.66-.48,1.73-1.74,2.47-.81,M 1.03,3.95,1.36,8.11,2.01,12.15,.71,6.02,1.18,12.02,1.87,18.04,.03,.47,.64,.78,1.11,.55,3.89-2.45,7.62-5.12,11.47-7.66,1.74-.9,1.74,.36,1.83,1.73,1,10.73,2.15,21.48,2.52,32.24-.04,2.55,1.51,1.27,2.91,.64,3.4-1.88,7.28-3.5,11.27-4.19,.93,.13,.83,1.23,.97,1.92,.86,12.8,1.06,25.62,1.33,38.44,.05,.56,.7,.91,1.44,.76,4.32-.79,8.61-1.84,12.97-2.44,1.95-.24,1.27,1.93,1.45,3.1,.12,6.22,.17,12.44,.13,18.65,4.4,2.16,8.67,4.34,12.83,6.52l-9.87,18.83c4.01-.33,8.01-.68,12.02-1.02,.82-.08,1.71-.31,1.67-1.08,.37-14.85,.09-29.74-.6M -44.58,.02-.87-.32-2.52,1.1-2.28,4.47,1.38,8.85,3.12,13.23,4.79,.78,.29,1.38,.01,1.35-.64-.56-13.58-2.36-27.09-3.8-40.59-.43-2.25,1.21-1.46,2.54-.93,4.11,1.56,8.06,3.6,12.26,4.87,1.67,.32-.78-8.21-.71-9.61-1.08-7.49-2.37-14.95-3.93-22.39-.38-1.8-.71-3.62-1.03-5.43-.09-.51-.23-1.05,.24-1.52,.88-.11,1.55,.29,2.23,.6,3.74,1.72,7.47,3.46,11.2,5.17,.48,.16,1.34,.64,1.78,.36,.08-.31,.19-.63,.14-.93-1.05-5.86-2.47-11.67-3.88-17.49-1.37-5.59-2.82-11.18-4.22-16.78-.05-.24,.03-.74,.29-.84,5.43,1.74,10.28,5.16,15.62,7.26,1.14M ,.4-.23-3.19-.29-3.81-2.74-9.33-5.29-18.69-8.39-27.95-.17-.51-.18-1.05-.24-1.58-.01-.1,.08-.26,.17-.28,.23-.06,.55-.14,.72-.06,4.84,2.27,9.41,5.02,14.11,7.53,2.27,1.23,2.21,.61,1.63-1.55-3.09-9.37-6.22-18.73-9.71-28.01-1.1-2.79,1.26-1.26,2.56-.56,4.24,2.48,8.48,4.97,12.72,7.45,1.08,.54,2.19,1.72,3.45,1-.76-.78-.92-1.75-1.24-2.65-2.95-8.28-6.15-16.5-9.44-24.69-1.74-4.11-.28-2.78,2.44-1.33,5.72,3.41,11.07,7.32,16.92,10.49,.1-.18,.31-.37,.27-.5-.3-.94-.63-1.87-.99-2.79-3.05-7.8-6.22-15.58-9.64-23.29-.89-2.01,.03-1.76,M 1.51-.99,6.09,3.37,11.92,7.02,17.49,10.93,.8,.44,1.71,1.35,2.58,1.43,.12-.17,.3-.38,.24-.54-.29-.83-.62-1.65-.98-2.46-2.67-5.97-5.36-11.95-8.03-17.93-.36-.8-.71-1.62-1.01-2.44-.05-.15,.16-.37,.3-.53,.8,.11,1.6,.82,2.33,1.18,6.6,4.1,13.08,8.31,19.44,12.63,.71,.48,1.31,1.11,2.31,1.26,.5-.77-.27-1.63-.51-2.4-2.72-5.97-5.45-11.93-8.18-17.89-.32-.7-.63-1.42-.91-2.13-.02-.06,.13-.19,.24-.23,.1-.05,.29-.08,.37-.03,1.58,.99,3.21,1.93,4.73,2.99,7.2,5.03,14.36,10.09,21.54,15.14,.32,.27,1.06,.69,1.26,.11-.19-.62-.36-1.25-.63-M 1.85-2.66-5.98-5.35-11.96-8.02-17.93-.18-.68-.89-1.47-.28-2.07,.58-.11,1.15,.56,1.64,.81,9.41,6.62,18.57,13.45,27.5,20.48,.79,.49,1.43,1.51,2.47,1.38,.07-.01,.19-.18,.17-.26-.24-.72-.48-1.45-.78-2.17-2.36-5.6-4.74-11.21-7.1-16.82-.29-.87-1-1.73-.46-2.62,12.75,8.58,24.14,19.37,36.27,28.32,.14-.13,.35-.33,.31-.46-.2-.73-.45-1.46-.72-2.18-2.1-5.56-4.21-11.12-6.31-16.67-.28-.9-.98-1.88-.22-2.72,14.41,11.53,27.92,24,41.94,35.73,.06,.03,.29-.04,.29-.07,.04-.31,.13-.64,.04-.93-1.96-6.15-3.95-12.3-5.92-18.45-.16-.51-.2-1.0M 5-.27-1.58,0-.23,.31-.41,.53-.28,2.65,1.65,4.75,4.1,7.18,6.07,12.98,11.52,25.65,23.26,37.93,35.27,1.03,.99,2.05,1.99,3.11,2.97,.1,.09,.45,.04,.67,0-.77-6.56-3.06-13.36-4.45-19.95-.06-.48-.31-1.39,.53-1.1,20.02,17.78,38.21,37.94,57.04,56.41,.2-.12,.51-.28,.5-.41-.52-5.15-1.07-10.29-1.6-15.44-.1-.96-.14-1.93-.18-2.89,0-.06,.15-.14,.25-.17,.11-.04,.32-.07,.37-.02,.66,.53,1.34,1.05,1.91,1.63,6.11,6.3,12.22,12.6,18.27,18.93,15.71,16.06,30.25,33.22,45.51,49.33,.33,0,.53-.13,.52-.37,0-6.89-.03-13.78-.06-20.78Zm-293.02-121M .31s-.03-.02-.03-.04l.22-.12s-.18,.16-.19,.16Zm59.13-8.88s.08-.13,.12-.13c.11,.02,.2,.07,.31,.11-.11,.14-.26,.15-.43,.02Zm29.62,6.39s-.05,.01-.08,.01c.06-.05,.13-.09,.2-.15l.03,.03s-.1,.08-.15,.11Zm34.32,12.1s.03,0,.04-.01c0,.03,.02,.06,.03,.09-.03-.03-.05-.05-.07-.08Z"/><path class="cls-2" d="M803.51,611.25l.14,.17s.05-.07,.09-.1c-.08-.03-.15-.05-.23-.07Z"/><path class="cls-2" d="M808.43,646.45l.15-6.65c-3.05-.91-6.11-2.19-9.23-2.76-.78,.31-1.07,.81-1.31,1.3-1.14,2.3-2.27,4.6-3.37,6.91-.63,.97-.64,2.75-2.06,2.87-3M .73-.56-7.38-2.02-11.11-2.55-.83,.45-1.03,1.1-1.24,1.71-1.2,3.52-2.38,7.05-3.47,10.6,3.89,.77,7.66,1.9,11.69,2.54,2.03-3.92,2.67-7.85,4.85-11.69,3.95,.5,7.57,2.18,11.39,3.22,.21,.06,.31,.33,.53,.57-1.73,3.55-2.62,7.43-4.57,10.89-.37,.51-1.21,.12-1.83-.05-1.77-.5-3.53-1.03-5.31-1.5-1.27-.33-2.57-.6-3.86-.88-.5-.11-1.15,.21-1.27,.6-1.31,3.93-1.95,8.05-3.59,11.87,3.83,.36,7.49,1.67,11.24,2.46,.3,.08,.91-.17,1-.39,1.27-3.38,2.04-6.93,3.29-10.31,.33-.91,.94-1.12,2.17-.77,1.58,.44,3.88,1.23,5.46,1.74l.3-13.26c-.74-.41-2.M 36-.4-2.31-1.48,.62-1.72,1.68-3.32,2.46-4.99Z"/><path class="cls-2" d="M807.99,623.15c-.66,.66-1.24,1.38-1.81,2.04,.65,.88,1.75,1.02,2.7,1.4l.1-4.42c-.33,.32-.66,.65-.99,.98Z"/><path class="cls-2" d="M803.74,611.32c1.86,.53,3.67,1.14,5.45,1.78l.15-6.95c-1.93,1.67-4.03,3.24-5.6,5.17Z"/><path class="cls-2" d="M808.02,581.41c-2.56,1.37,.72,1.87,1.83,2.51l.08-3.71c-.64,.4-1.28,.8-1.91,1.2Z"/><path class="cls-2" d="M810.55,567.32c-11.87-5.88-11.84-3.47-.1-9.83l.23-10.11c-.1-.15-.1-.28,.01-.42l.24-10.65c-3.58,1.58-7.22,2M .76-10.52,4.91,2.61,2.26,6.1,3.58,8.74,5.63,0,.56-.41,.81-.88,1.03-5.56,2.65-10.86,5.6-16.05,8.69-1.5,.9-1.46,1.25,.2,2.06,2.47,1.29,5.16,2.29,7.51,3.78,.12,.09,.13,.46,0,.55-3.11,2.28-6.58,4.09-9.79,6.23-1.68,1.07-3.28,2.23-4.89,3.37-.38,.27-.78,.57-.52,1.15,2.91,1.2,5.96,2.43,8.88,3.67,.29,.13,.46,.44,.76,.73-4.36,3.36-8.9,6.55-13.01,10.12,.11,.57,.5,.82,1.01,1,2.46,.87,4.92,1.75,7.37,2.64,.51,.26,1.69,.46,1.54,1.18-3.42,3.33-7.35,6.28-10.56,9.75-.37,.39-.23,.88,.32,1.06,3.6,.92,7.05,2.63,10.74,3.03,3.87-3.26,7.5M 7-7.07,11.78-9.87,2.06,.33,3.94,1.41,5.93,2.07l.15-6.45c-1.74,1.19-3.47,2.37-5.21,3.56-.43,.29-.95,.55-1.46,.37-3.31-1.19-6.6-2.41-9.9-3.63-.31-.12-.4-.65-.13-.86,4.03-3.36,8.41-6.35,12.73-9.33-.06-.2-.04-.33-.11-.36-3.11-1.72-6.72-2.71-9.87-4.3-.09-.53,.19-.85,.64-1.13,2.55-1.59,5.07-3.21,7.65-4.77,2.04-1.24,4.13-2.43,6.21-3.64,.56-.21,1.02-.88,.35-1.23Z"/><path class="cls-2" d="M849.65,657.15s-.02,.01-.02,.02l-.06,.06s.1-.05,.13-.06c-.02,0-.03-.02-.05-.02Z"/><path class="cls-2" d="M850.86,603.02l-.08,3.67c1.14-.4M 4,2.45-.69,3.4-1.62-1.04-.76-2.16-1.43-3.32-2.05Z"/><path class="cls-2" d="M851.91,617.91c-.45-.27-.91-.54-1.37-.79l-.06,2.69c.61-.41,2.45-1.03,1.43-1.9Z"/><path class="cls-2" d="M853.24,632.27c-.94-.62-1.98-1.15-3.01-1.64l-.11,5.19c1.09-.99,2.28-1.91,3.27-2.99,.1-.11,0-.46-.15-.56Z"/><path class="cls-2" d="M854.15,552.12c-.7-.49-1.39-.97-2.1-1.45l-.07,2.86c.63-.32,3.03-.29,2.17-1.41Z"/><path class="cls-2" d="M856.61,647.53c-2.19-1.24-4.45-2.4-6.68-3.57l-.3,13.18s.01,0,.02,.01c2.45-2.62,4.62-5.48,6.95-8.2,.4-.42,.6M 2-1.1,0-1.42Z"/><path class="cls-2" d="M857.13,591.14c-1.97-1.1-3.96-2.18-5.93-3.28l-.16,7.32c2-.68,4.01-1.36,6.02-2.04,.61-.21,1.24-.38,1.53-.92-.31-.51-.91-.78-1.46-1.08Z"/><path class="cls-2" d="M885.35,472.92l-.16,.1c.06-.01,.13-.03,.19-.04l-.03-.06Z"/><path class="cls-2" d="M935.17,478.66c-.29-.6-.62-1.2-.98-1.77-5.96,1.3-11.87,2.55-17.73,3.73,6.13-.7,12.34-.79,18.48-1.38,.08-.19,.3-.43,.23-.58Z"/><path class="cls-2" d="M899.95,492.19c-1.94-2.42-3.87-4.85-5.79-7.28-12.75,2.33-25.26,4.39-37.53,6.18h0c9.06,10.79M ,10.14,7.19-3.48,11.01l-.24,10.6c6.43-1.79,13.27-2.52,19.66-4.42,.21-1.47-9.05-8.14-7.28-8.85,11.38-2.99,23.34-4.04,34.99-5.93,.21-.57-.04-.94-.33-1.31Z"/><path class="cls-2" d="M1030.85,456.11l-.1,.09s.1,.01,.15,.02c-.02-.04-.03-.07-.05-.11Z"/><path class="cls-2" d="M1095.46,449.73l.12,.03v-.12l-.12,.09Z"/><path class="cls-2" d="M1117.24,514.85c.02,.06,.04,.11,.06,.17l.1-.13c-.05-.01-.11-.03-.16-.04Z"/><path class="cls-2" d="M1177.17,467.11s0,.05,.02,.07c.02,0,.03,.01,.05,.01l-.07-.08Z"/><path class="cls-2" d="M11M 90.02,521.36s.03,.07,.04,.1l.14-.05c-.06-.02-.12-.03-.18-.05Z"/><path class="cls-2" d="M1387.26,543.4c.4-2.35-1.88-2.91-3.6-3.69-35.69-15.35-71.6-30.31-108.62-42.7-.96,.09-.65,1.23-.69,1.89,.36,3.32,.78,6.64,1.15,9.96,.24,2.25,.44,4.5,.65,6.76,.02,.24-.6,.57-.89,.47-30.89-11.4-62.19-21.91-94-30.84-1.34-6.03-2.45-12.11-4.07-18.07-26.79-7.31-54.23-12.51-81.61-17.42,.35,4.82,2.59,9.36,3.8,14.02,.47,1.58,.25,2.24-1.61,1.86-22.15-4.02-44.44-7.27-66.87-9.42,1.77,4.13,3.56,8.27,5.32,12.41,.23,.68,.74,1.74-.33,1.94-10.58-.M 84-21.12-2.2-31.73-2.8-8.07-.48-16.13-1.03-24.21-1.12-.55-.02-.94,.47-.73,.9,1.79,3.62,3.87,7.1,5.76,10.67,.53,.97,.19,1.3-1.25,1.3-15.69-.43-31.51-1.38-47.14,.07-.24,.5-.01,.89,.24,1.27,1.23,1.8,2.45,3.6,3.68,5.39,.84,1.23,1.72,2.44,2.51,3.68,.15,.23-.04,.59-.07,.97-13.62,.35-27.22,.92-40.72,2.63-.34,.06-.57,.55-.37,.79,1.03,1.27,2.05,2.53,3.1,3.79,1.34,1.61,2.7,3.21,4.04,4.82,.32,.39,.01,.9-.55,.96-11.45,1.44-23.29,1.84-34.43,4.74-.19,1.68,9.07,7.82,7.62,8.79-9.15,1.84-18.43,3.15-27.44,5.36-.86,.21-1.8,.27-2.45,.M 93,.08,.49,.49,.8,.89,1.1,2.45,2.12,5.24,3.93,7.5,6.25,.1,.12,0,.5-.09,.53-2.5,.74-5.09,1.2-7.61,1.82l-.23,10.11c5.99-1.72,12.43-2.21,18.36-4.05-.1-.7-.63-1.06-1.11-1.43-2.31-1.81-4.63-3.61-6.94-5.41-.4-.31-.69-.66-.42-1.23,9.49-2.29,19.69-3.37,29.34-4.82,.19-.68-.13-1.02-.48-1.35-2.4-2.45-5.31-4.51-7.4-7.22-.05-.62,.86-.79,1.35-.89,7.07-.86,14.14-1.61,21.23-2.24,3.21-.38,6.43-.52,9.66-.66,.72-.15,2.63,.15,2.53-.97-1.76-2.62-4.24-4.7-6.31-7.08-.41-.64-2.21-1.9-.8-2.33,13.12-1.53,26.35-1.05,39.53-1.48,.51-.03,.85-.6M ,.58-.99-2.22-3.2-4.71-6.24-6.75-9.56-.25-1.05,1.4-.79,2.04-.89,9.43,0,18.87,0,28.28,.55,5.77,.18,11.55,1.02,17.31,.82,.8-.4-.05-1.4-.27-1.98-1.81-3.24-3.74-6.43-5.51-9.7-.18-.38,.28-.91,.81-.89,18.81,.59,37.51,3.62,56.16,5.36-1.35-4.81-4.46-8.97-5.8-13.74,.77-.35,1.45-.29,2.11-.21,6.65,.84,13.28,1.75,19.89,2.78,14.54,2.27,28.95,4.98,43.32,7.85,.65,.06,1.76,.46,2.15-.22-.9-4.46-2.86-8.74-4.14-13.12-.27-.83-.85-2.01,.64-1.98,26.85,4.9,53.43,11.33,79.62,18.85,1.34,5.48,2.68,10.94,3.93,16.43,.1,.43,.09,.84-.42,1.26-25M .72-7.46-51.51-14.89-77.81-20.26-1.34,.02-.59,1.37-.46,2.12,1.38,4.28,3.09,8.46,4.3,12.78-.22,1.1-1.95,.32-2.72,.29-19.96-4.7-40.08-8.71-60.36-11.92-3.22-.4-3.8-.32-2.55,2.3,1.66,3.62,3.56,7.17,4.92,10.91,.04,.12-.28,.45-.41,.45-13.16-1.5-26.16-4.19-39.39-5.32-5.2-.61-10.39-1.22-15.63-1.4-1.33,.38,.13,1.76,.41,2.49,1.86,3.11,3.96,6.08,5.64,9.29,.13,.24-.28,.67-.65,.66-6.18-.23-12.29-1.16-18.48-1.46-9.14-.68-18.27-1.23-27.43-1.28-.79-.01-1.22,.55-.82,1.07,2.4,3.1,4.82,6.2,7.07,9.41,.25,.35-.23,.91-.76,.88-13.01-.34-M 26.16-.82-39.12,.22-1.92,1,9.05,9.18,7.05,10.08-7.61,.61-15.34,.39-22.96,1.14-3.65,.45-7.61,.18-11.08,1.38-.02,.86,.85,1.3,1.39,1.88,1.32,1.27,7.59,6.21,6.83,6.93-1.43,.79-3.11,.51-4.69,.69-2.27,.24-4.54,.43-6.81,.71-5.18,.64-10.37,1.32-15.55,2-.61,.19-2.84,.27-2.18,1.25,2.97,2.34,6.05,4.55,8.91,7.02,.1,.08-.02,.5-.12,.52-8.42,1.69-16.88,2.7-25.2,4.82,.18,.37,.22,.73,.46,.91,2.93,2.05,5.95,4.05,8.88,6.1,.26,.18,.08,.67-.28,.78-4.42,1.2-8.91,2.18-13.35,3.31l-.16,7.08c.86,.68,2.31,.9,2.53,2.14-.83,.26-1.72,.55-2.6,.8M 1l-.23,10.41c4.88-1.5,9.95-2.64,14.89-4.01-.09-.57-.44-.88-.88-1.14-1.74-1.02-3.48-2.03-5.21-3.06-1.46-1.09-3.55-1.58-4.39-3.23,6.67-1.91,13.49-3.18,20.36-4.27,.48-.09,1.46-.45,1.01-1.06-3.12-2.19-6.31-4.34-9.38-6.59-.25-.6,.7-.85,1.16-.96,7.61-1.42,15.31-2.39,23.03-3.36,.64-.1,.82-.59,.36-.95-2.58-2.05-5.17-4.08-7.75-6.13-2.17-1.64-.72-1.58,1.06-1.98,5.75-.54,11.47-1.3,17.26-1.56,3.08-.19,6.18-.28,9.25-.62,.27-.03,.45-.6,.25-.8-1.82-1.91-3.91-3.56-5.86-5.34-.81-.72-1.63-1.44-2.42-2.17-.27-.24-.48-.55-.21-.86,10.84M -1.72,22.27-.75,33.31-1.24,.3-.02,.62-.55,.44-.76-2.41-3.15-5.63-5.72-7.89-8.93-.04-.14,.18-.48,.34-.5,.78-.12,1.58-.23,2.37-.23,12.37-.11,24.72,.52,37.03,1.35,.29-.52,.08-.92-.19-1.28-1.11-1.48-2.24-2.95-3.37-4.41-1.2-1.56-2.43-3.1-3.61-4.67-.18-.24-.11-.61-.17-1.04,15.47,.28,30.84,2.37,46.18,4.13,1.33-.29,.18-1.48-.15-2.16-1.7-2.7-3.41-5.38-5.1-8.07-.41-.66-1.07-1.26-.93-2.08,1.45-.66,3.13-.06,4.65,.06,16.01,2.22,32.04,4.64,47.87,7.74,.79,.18,3.08,.81,2.72-.55-1.79-3.84-3.78-7.6-5.63-11.41-.19-.53-.79-1.41,.03-1.M 66,22.08,3.51,43.87,9.05,65.52,14.48-1.73-4.67-3.46-9.35-5.18-14.03-.22-.71-.5-1.29,.21-1.87,26.35,6.21,52.09,14.24,77.75,22.41-1.34-4.08-2.1-8.38-3.19-12.54-.33-1.37-.6-2.75-.86-4.13-.09-.45,.48-.87,.99-.74,28.24,8.43,55.75,18.57,83.1,29.23,2.55,.97,5.05,2.09,7.63,2.96,.85,.18,1.03-.38,.99-1.02-.66-5.79-1.6-11.55-2-17.36,.31-1.61,3.01,.27,3.99,.42,35.8,13.54,70.89,28.91,105.58,44.71,.32,.12,.88-.16,.91-.44,.32-6.33,.01-12.71,.1-19.05Z"/><path class="cls-2" d="M1095.46,449.73l.12,.03v-.12l-.12,.09Z"/><path class="cM ls-2" d="M146.84,783.15s-.04,.07-.04,.08h.02l.03-.09s0,.01-.01,.01Zm8.06,60.24s-.05-.02-.07-.03l.08,.09s-.01-.04-.01-.06Zm72.61-15.48h-.01v.03c.11,.02,.17,0,.18-.05-.06,.01-.11,.02-.17,.02Zm186.07,66.45s.05,.08,.08,.12l.15-.07c-.08-.02-.15-.03-.23-.05Zm68.05-41.28s-.01,.03-.02,.05l.08-.07s-.04,.01-.06,.02Zm6.45-94.41h-.05l.1,.06s-.04-.04-.05-.06Zm-.04-53.67s.05,.07,.07,.1c.02-.01,.05-.02,.07-.03l-.14-.07Zm104.97,43.31c-.78,1.81-1.58,3.62-2.37,5.43-.15,.39-.71,.81-1.1,.73-3.5-1.85-6.57-4.45-9.9-6.59-1.79-1.47-2.29-.M 75-3.25,.95-1.45,2.3-2.89,4.61-4.35,6.91-.23,.37-.98,.45-1.39,.18-4.08-2.7-7.64-6.1-11.72-8.82-2.78,2.3-4.04,5.35-6.79,7.7-.36,.33-.74,.6-1.51,.61-4.39-3.49-8.48-7.33-12.59-11.18,1.91-3.05,5.05-5.3,7.45-8.03,1.27-1.22,3.18,1.96,4.3,2.6,11.47,9.24,6.81,10.82,15.24-1.66,.74-.27,1.1,.08,1.46,.36,3.64,2.79,7.02,6.06,10.95,8.42,.7-.4,.96-.9,1.2-1.4,1.55-2.81,2.48-6.02,4.41-8.58,.36,.07,.56,.08,.84,.23,3.03,2.1,6.05,4.2,9.08,6.3l-.09-14.79c-1.71-1.07-3.01-2.72-4.96-3.37-.64,.28-.84,.79-1.03,1.3-1.19,2.97-2.11,6.05-3.64,8M .88-.81,.77-1.87-.48-2.57-.91-3.07-2.39-5.91-5.08-9.13-7.28-1.01-.25-1.24,1.21-1.72,1.82-1.1,2.08-2.18,4.17-3.29,6.24-.3,.58-.56,1.2-1.24,1.59-.76-.03-1.2-.46-1.64-.85-2.23-2.02-4.45-4.04-6.67-6.07-1.36-1.11-2.27-2.57-3.96-3.25-2.01,2.58-3.73,5.24-5.63,7.87-.37,.47-.98,1.3-1.67,1.06-3.95-3.24-7.17-7.27-10.82-10.83-.48-.43-1.06-1.27-1.81-.91-1.85,1.3-7.82,7.66-8.7,6.98-1.6-.87-2.41-2.27-3.48-3.48-3.05-3.41-5.81-7.03-8.94-10.35-.19-.19-.85-.23-1.11-.06-2.42,1.54-4.83,3.09-7.26,4.61-.95,.67-2.78,1.91-3.54,.38-4-5.31-8M .21-10.47-11.96-15.95-3.77,1.2-7.89,.9-11.87,1.48-.36,1.35,1.01,2.36,1.63,3.47,2.93,3.98,5.88,7.94,8.82,11.92,.4,.76,1.48,1.42,.99,2.33-3.83,.48-7.73,.54-11.59,.85-.35,.02-.63,.46-.45,.72,3.36,4.7,7.26,9.02,10.83,13.57,.25,.54,2.14,2.22,1.13,2.45-3,.67-6.13,.28-9.18,.43-1.08,.02-2.14,.06-3.22,.09-.3,0-.72,.51-.58,.7,4.23,5.39,9.01,10.34,13.46,15.56,4.18,.08,8.3-.43,12.42-.81,.56-.08,1.88-.3,1.49-1.1-3.77-4.21-7.63-8.35-11.42-12.53-1.54-1.82-1.66-2.2,.89-2.37,2.92-.38,5.85-.73,8.77-1.14,1.58-.23,1.68-.55,.69-1.69-3.M 64-4.11-7.1-8.39-10.63-12.58-.45-.53-.97-1.04-1.06-1.72,.35-.55,1.05-.63,1.68-.69,2.95-.29,5.83-.82,8.68-1.48,1.03-.24,1.52-.1,2.09,.55,.99,1.15,1.95,2.32,2.95,3.47,2.97,3.46,6.08,6.82,8.97,10.35,.75,1.49-8.97,2.76-10.32,3.48-.3,.09-.47,.61-.27,.84,1.01,1.14,1.98,2.3,3.04,3.42,2.6,2.75,5.21,5.49,7.89,8.19,2.39,2.43,1.72,2.23-1.31,3.01-2.91,.76-6.06,.96-8.95,1.73-.09,.93,.72,1.37,1.26,2.02,3.83,3.88,8.02,7.48,11.65,11.55,.15,.2,.03,.43-.27,.52-3.98,1.1-8.16,1.3-12.23,2.01-.88,.32,.03,1.19,.4,1.57,4.11,4,8.48,7.75,12M .43,11.89,.08,.09-.1,.47-.24,.5-17.62,3.37-18.91-2.29-3.95,11.89,.7,.91,4.41,2.88,1.89,3.57-5.07,.41-10.22,.46-15.29,.93-.13,.02-.32,.43-.24,.52,3.1,3.34,6.85,6.06,10.15,9.2,.35,.34,.44,.75,.18,.86-6.33,.89-12.89-.04-19.34-.24,.1,.42,.05,.78,.26,1,2.87,2.9,6.07,5.49,9.07,8.25,.39,.4,1.37,1.11,.56,1.52-6.84,.03-13.7-.72-20.46-1.65-1.21-.09-2.85-.33-1.34,1.24,2.58,2.48,5.18,4.96,7.77,7.44,.51,.49,.97,1.02,1.43,1.54,.06,.06,.02,.22-.04,.31-2.9,.54-6.13-.42-9.06-.69-5.57-.78-11.1-1.73-16.65-2.6-.29-.01-.87-.08-.96,.26,M .11,.29,.2,.63,.43,.86,2.55,2.64,5.15,5.26,7.71,7.9,.49,.5,.89,1.06,1.31,1.6,.07,.08,.08,.28,.02,.31-.56,.39-1.23,.14-1.85,.05-8.7-1.46-17.33-3.14-25.87-5.11-.95-.11-2.24-.63-3.11-.36-.07,.18-.17,.44-.07,.56,2.56,3.03,5.15,6.05,7.73,9.07,.45,.53,1.06,.99,1.13,1.69-.61,.37-1.24,.15-1.86,.02-9.63-2.06-19.15-4.39-28.53-7.07-2.11-.43-4.01-1.6-6.22-1.31,2.63,4.02,5.68,7.61,8.47,11.5,.2,.31-.43,.62-.62,.6-13.08-3.09-25.9-7.33-38.55-11.54-1.04-.2-2.45-1.19-3.34-.41,2.3,3.91,5.01,7.6,7.44,11.43,.17,.35,.52,.84,.35,1.19-.21M ,.11-.51,.27-.67,.22-15.54-4.91-31.02-10.35-46.03-16.54-.82-.25-1.68-.94-2.54-.5-.08,.02-.13,.19-.1,.27,.2,.51,.39,1.02,.65,1.51,1.89,3.58,3.78,7.14,5.68,10.71,.25,.48,.48,.97,.3,1.5-2.03,.16-3.93-1.17-5.85-1.74-17.64-6.6-34.7-14.6-51.72-21.85-.13,.17-.32,.38-.27,.55,1.35,4.08,3.17,8,4.72,12.01,.33,.81,.62,1.64,.94,2.46,.3,.55-.56,.77-.92,.65-21.9-9.46-43.41-20.05-64.26-31.12-.88-.33-1.78-1.26-2.76-.88-.09,.03-.17,.19-.15,.28,1.39,5.38,2.93,10.73,4.36,16.09,.23,.76-.68,.9-1.19,.57-21.19-10.61-42.14-21.96-62.54-33.8M 9-4.78-2.8-9.53-5.64-14.3-8.46-.52-.32-1.02-.7-1.76-.6-.48,1.6,.12,3.37,.21,5.03,.51,4.56,1.69,9.16,1.87,13.73-.61,.23-1.09,.06-1.53-.18-3.28-1.88-6.61-3.72-9.84-5.65-27.04-15.99-53.85-32.34-79.84-49.93-1.41-.78-3.52-3.06-3.47,.38,0,5.81,.03,11.62,.05,17.44,.07,.86-.09,1.85,.78,2.4,.73,.49,1.44,.98,2.18,1.44,29.69,18.88,60.26,36.56,91.32,53.31,.76,.42,1.6,.76,2.43,1.1,.11,.05,.57-.18,.57-.28-.1-5.61-1.46-11.11-2.15-16.67-.36-2.9,1.1-1.62,2.71-.86,25.9,14.28,52.13,28.58,79.26,40.4,.51-.47,.33-1,.19-1.5-1.28-5.16-3.2M 5-10.21-4.06-15.45-.03,0-.06-.01-.1-.02,.04,0,.07,0,.11,0,.05-.05,.09-.1,.14-.16,.03,.06,.04,.11,.03,.14,.97-.23,1.77,.4,2.61,.77,14.08,6.98,28.37,13.67,42.97,19.94,7.78,3.14,15.37,6.89,23.32,9.57,.85-.05,.46-1.05,.32-1.57-1.32-3.28-2.67-6.55-4.01-9.82-.42-1.02-.86-2.04-1.21-3.08-.09-.27,.01-.73,.25-.87,1.09-.22,2.23,.66,3.24,1,11.69,4.91,23.42,9.74,35.43,14.11,6,2.19,12.04,4.32,18.07,6.46,.6,.21,1.27,.29,1.92,.4,.08,.02,.3-.15,.28-.2-1.41-4.29-4.21-8.11-6.17-12.21-.18-.48-.6-1.02-.4-1.51,.12-.26,.35-.34,.65-.23,2.M 58,.91,5.17,1.81,7.75,2.73,12.66,4.55,25.53,8.65,38.6,12.36,1.65,.27,4.91,1.99,2.72-1.14-2.29-3.54-4.83-6.94-6.99-10.56-.08-.15,.08-.39,.18-.58,12.62,3.06,25.24,7.39,38.17,10.13,1.43,.29,2.84,.74,4.29,.9,.13-.01,.33-.03,.37-.09,.08-.15,.2-.39,.12-.5-2.08-2.77-4.19-5.52-6.28-8.29-.63-.82-1.23-1.67-1.79-2.52-.1-.22,.2-.73,.52-.66,8.44,1.71,16.74,4.06,25.28,5.57,3.53,.68,7.08,1.27,10.63,1.89,.17,.02,.5-.28,.38-.48-.42-1.43-10.56-10.8-8.49-10.81,9.33,1.41,18.67,3.24,28.09,4.41,1.02,.15,2.08,.35,3.13,.07,.16-.45-.1-.78-M .44-1.11-2.3-2.24-4.6-4.47-6.89-6.72-3.16-2.94-2.29-2.81,1.43-2.41,7.4,1.07,14.88,1.66,22.34,2.35,.87,.08,1.42-.06,1.35-.32-.07-.3-.18-.63-.42-.85-1.68-1.53-3.41-3.03-5.1-4.56-1.33-1.21-2.65-2.42-3.93-3.67-.2-.19-.16-.53-.21-.81,7.44-.21,14.99,.98,22.45,.67,.24-.12,.68-.41,.44-.69-2.82-2.66-5.94-4.99-8.88-7.52-.35-.4-1.33-1.05-1.26-1.55,.51-.64,1.43-.39,2.15-.43,5.78,.14,11.61,.17,17.35-.34,.67-.52-.37-1.15-.75-1.54-2.63-2.16-5.28-4.31-7.92-6.46-.6-.68-1.84-1.06-1.63-2.11,5.56-.7,11.27-.5,16.79-1.53,.35-.89-.69-1.2M 9-1.21-1.86-2.93-2.38-5.87-4.75-8.79-7.14-.4-.39-1.35-1.08-.69-1.57,4.47-.75,8.96-1.46,13.42-2.28,.79-.14,.94-.69,.34-1.22-4.36-3.85-9.04-7.32-13.22-11.38,.4-.28,.66-.59,1-.66,3.66-.68,7.3-1.44,10.9-2.38,.49-.12,.96-.33,1.17-.88-4.23-4.05-9.02-7.58-13.14-11.74-.21-.23-.03-.69,.32-.79,3.92-.99,7.79-2.68,11.76-3.26,4.08,3.12,11.98,9.75,13.61,11.44-.17,.44-.53,.73-1.05,.92-3.28,1.21-6.65,2.33-9.89,3.64-.64,.55,.37,1.17,.77,1.57,3.63,2.88,7.29,5.74,10.92,8.63,.55,.43,1.33,.74,1.41,1.68-3.97,1.64-8.31,2.76-12.51,4.08,.0M 2,.82,.72,1.21,1.29,1.64,2.86,2.13,5.74,4.25,8.61,6.37,.44,.46,2.12,1.26,1.63,1.93-15.8,5.28-20.79-.95-3.72,11.99,.32,.4,.02,.9-.46,.98-4.1,.62-8.2,1.25-12.36,1.56-.59,.16-4.88,.24-4.17,1.08,2.79,2.55,6.04,4.61,9,6.94,.58,.48,2.55,1.57,1,2.09-4.3,.27-8.6,.53-12.9,.77-.93,.3-7.99-.5-6.14,1.35,3.07,2.59,6.25,5.06,9.35,7.6,.17,.14,.29,.42,.23,.58-.05,.16-.36,.36-.58,.37-1.48,.12-2.95,.28-4.43,.26-6.05-.05-12.11-.33-18.16-.29-.06,.2-.24,.48-.14,.58,.64,.69,1.3,1.37,2.02,2,2.18,1.91,4.41,3.79,6.59,5.69,.39,.43,1.33,1.06M ,.63,1.59-7.6,.1-15.33-.64-22.92-1.35-1.33-.14-2.65-.41-3.96-.16-.31,.49,0,.84,.34,1.18,2.83,2.88,6.01,5.44,8.61,8.52-.13,1.32-6.77-.04-8.01-.05-5.19-.62-10.38-1.24-15.57-1.88-2.66-.29-5.29-.83-7.96-1.01-.13,0-.35,.06-.36,.12-.04,.19-.1,.46,.02,.59,2.89,3.25,5.95,6.37,8.73,9.7,.11,.13-.02,.37-.04,.67-11.92-1.41-23.8-3.64-35.49-6.12-.59-.07-1.4-.35-1.94-.07-.09,.17-.24,.42-.15,.54,2.65,3.49,5.41,6.94,8.08,10.43,.09,.13-.04,.38-.13,.56-.64,.34-1.97-.11-2.73-.16-8.22-1.66-16.43-3.36-24.53-5.38-5.01-1.25-9.99-2.58-14.9M 9-3.88-.51-.13-1.02-.27-1.65,.07,2.08,4.27,5.77,8.06,7.53,12.34-.64,.52-1.5,.18-2.22,.06-13.32-3.45-26.59-7.02-39.55-11.27-2.5-.82-5.01-1.59-7.51-2.39-.65-.35-2.76-.64-2,.61,2.25,4.26,4.61,8.47,6.79,12.76-.9,.6-1.77,.04-2.69-.16-17.11-5.24-33.91-11.05-50.39-17.46-2.19-.83-4.37-1.69-6.56-2.5-.44-.15-1.02-.09-1.09,.13-.06,.19-.17,.41-.1,.58,1.31,3.28,2.66,6.55,3.98,9.83,.54,1.33,1.04,2.67,1.53,4.01,.07,.18-.04,.4-.08,.59-.05,.21-.67,.3-1.09,.14-.98-.35-1.96-.72-2.93-1.09-23.64-8.4-44.91-18.55-67.22-27.6,.34,4.68,2.63M ,9.78,3.67,14.48,.2,.72,.47,1.45,.23,2.22-.26,.86-2.2-.36-2.78-.46-12.45-5.38-24.69-11.04-36.86-16.81-14.74-6.94-29.08-14.42-43.49-21.76-.47-.22-1.1,.12-1.06,.58,.14,1.4,.26,2.79,.45,4.18,.68,4.9,1.38,9.8,2.08,14.7,28.14,13.75,56.79,26.85,86.02,38.32,1.45,.17,.33-2.31,.26-3.1-1.19-4.43-2.51-8.81-3.63-13.25-.04-.19,.02-.46,.17-.6,.98-.5,2.24,.6,3.23,.85,22,9.36,44.67,17.94,67.48,25.64,1.44,.47,3.01,1.03,1.96-1.28-1.59-4.43-3.87-8.71-5.05-13.26-.02-.12,.33-.38,.51-.38,1.28-.04,2.3,.58,3.39,.97,18.89,6.31,38.25,13.81,M 57.87,17.64,.08-.68-.35-1.24-.66-1.82-1.56-2.98-3.15-5.95-4.73-8.93-.32-.91-2.4-3.24-.25-3.01,17.23,4.98,34.45,9.63,52.11,13.18-2.57-3.97-5.16-7.94-7.71-11.91-.14-.32-.48-1-.04-1.15,14.86,2.59,29.54,6.88,44.61,8.3,.13-.64-.27-1.07-.63-1.51-2.51-3.19-5.19-6.26-7.59-9.53-.07-.21,.24-.73,.57-.66,2.37,.37,4.74,.79,7.12,1.14,6.88,1.01,13.75,2.09,20.66,2.95,3.04,.37,6.1,.9,9.22,.81,.19-.01,.39-.21,.54-.35,.22-.4-.39-.8-.6-1.11-2.57-2.61-5.09-5.29-7.6-7.96-.32-.34-.6-.72-.46-1.24,10.48,.76,21.03,2.38,31.61,2.38,.61-.06,1.M 18-.43,.54-1.11-2.79-2.77-5.89-5.28-8.55-8.17-.1-.13,0-.38,.08-.57,8.89-.06,17.99,.91,26.98,.55,.45-.02,.9-.45,.62-.88-2.86-2.97-6.96-5.1-9.48-8.24,.14-.16,.32-.4,.5-.41,1.61-.06,3.23-.12,4.84-.11,5.93,.05,11.84-.36,17.74-.72,1.42-.44,.03-1.43-.63-1.88-2.78-2.31-6.05-4.19-8.53-6.82-.1-.87,1.2-.64,1.78-.76,6.03-.38,12.07-.67,18.03-1.67,1.37-.67-.89-1.58-1.36-2.12-2.53-1.78-5.07-3.54-7.58-5.33-1.23-.85-1.59-1.66,.22-1.85,5.31-.66,10.65-1.23,15.81-2.52,1.36-.73-1.03-1.53-1.49-2.06-2.86-1.96-5.74-3.91-8.61-5.87-.42-.28M -.72-.61-.56-1.09,4.87-1.13,9.85-2.01,14.58-3.68,.52-.59-.58-1.13-.99-1.49-2.97-2.02-5.96-4.03-8.93-6.06-.43-.4-1.82-1.05-1.29-1.69,4.11-1.59,8.49-2.59,12.55-4.3,.12-.96-.89-1.25-1.5-1.8-3.41-2.44-6.98-4.69-10.3-7.26-.98-1.02,1.91-1.46,2.5-1.93,2.69-1.22,5.43-2.38,7.89-3.89,.13-.09,.18-.46,.07-.56-3.65-3.06-7.68-5.7-11.47-8.61-.51-.55-2.12-1.24-1.14-2.04,2.72-1.37,5.42-2.81,8.08-4.28,1.66-.93,1.67-1.16,.33-2.17-3.94-2.9-7.65-6.06-11.5-9.08-.55-.44-.46-.96-.48-1.49,.45,.07,.75-.15,1.06-.36,2.78-1.83,5.25-3.99,7.81-5M .96,.96,.08,1.41,.67,1.97,1.1,3.29,2.54,6.55,5.09,9.84,7.63,.47,.37,.95,.78,1.87,.77,2.76-2.73,4.38-6.01,7.05-8.95,3.83,2.71,7.36,5.1,11.18,7.71,.45,.28,1.22,.75,1.71,.32,2.47-2.87,3.25-6.78,5.84-9.52,.95,.41,1.84,.86,2.7,1.33l-.05-8.32Zm-250.46,100.92c.06,.03,.14,.06,.21,.08-.22,.11-.28,.09-.21-.08Zm147.12-14.3s-.08,.01-.12,.02l.12-.12v.1Zm25.5-96.52c-.45-.37-.56-1.06-.03-1.4,2.74-1.91,5.48-3.81,8.22-5.71,.79-.55,1.33-.52,2,.18,3.97,4.2,8.16,8.2,12.1,12.42-2.89,2.62-6.66,5.35-9.54,6.93-4.73-3.5-8.64-8.27-12.75-12.M 42Zm24.1,25.99c-2.56,1.19-5.15,2.32-7.86,3.26-.78,.27-1.36,.23-1.83-.17-4.4-4.02-9.25-7.78-12.91-12.3,.23-.44,.78-.53,1.24-.68,2.98-.98,5.97-1.94,8.95-2.91,.68-.21,1.25-.1,1.79,.37,3.43,3.03,6.84,6.06,10.28,9.08,.91,.58,1.84,2.16,3.07,1.52-.83,.7-1.68,1.35-2.73,1.83Zm71.72-26.52s-.01,.03-.01,.04c.02,.01,.05,.02,.07,.03,0-.01,.01-.02,.01-.03-.02,0-.05-.03-.07-.04Zm8.11,17.54s-.01,.03-.01,.04c.03,.01,.07,.03,.1,.04,0-.01,.01-.03,.01-.04-.03-.02-.07-.03-.1-.04Zm6.5-25.12s0,.02-.01,.03c.03,.02,.05,.03,.08,.04,0-.01,.01M -.03,.01-.04-.03-.01-.05-.02-.08-.03Zm11.35,3.89s-.01-.09-.02-.14t-.02-.01c-.85-.28-1.7-.56-2.55-.84l.08,13.84h.01l.09,.03v-.02c.7-4.28,2.24-8.53,2.41-12.86Zm4.8-27.3c-2.66-.5-5.09-1.5-7.57-2.36l.09,14.5c1.36,.21,5,2.5,5.58,.6,.66-4.22,1.71-8.46,1.95-12.73-.02,0-.03-.01-.05-.01Z"/><path class="cls-2" d="M449.26,412.22s.05-.02,.07-.02c0-.01,0-.03,.01-.04l-.08,.06Zm14.24-264.12s.07-.03,.07-.06l-.07,.06Zm2.76,257.38c-1.55,.45-2.97,1.18-4.45,1.78,1.64,.75,3.3,1.5,4.97,2.25-.08-.96,1.01-4.15-.52-4.03Zm22.6-259.01l-.03,.M 12s.07-.01,.11-.01l-.08-.11Zm5.8,318.64c-.12,2.8-.22,5.59-.33,8.38-.03,.42,.18,1.12,.59,1.06,.24-.03,.54-.03,.71-.14,2.96-1.93,5.82-3.98,8.7-6.01-3.27-1.08-6.49-2.17-9.67-3.29Zm8.67-76.34c-.05-.12-.47-.29-.59-.24-.96,.39-1.91,.8-2.83,1.24-4.43,2-8.7,4.41-13.23,6.19-1.34,.05-.67-1.59-.67-2.42,.99-6.09,1.9-12.18,3.02-18.25,1.39-7.46,2.95-14.89,4.45-22.33,.55-2.76,1.15-5.52,1.72-8.28,0-1.6-2.3-.08-3.14,.07-4.66,1.69-9.32,3.38-13.99,5.06-.47,.17-1.01,.22-1.53,.3-.3,.05-.54-.1-.54-.36,2.06-15.22,6.29-30.15,9.66-45.16,.9M 8-4.67,2.71-9.2,3.35-13.94-.41-1.04-1.93-.22-2.76-.12-5.36,1.42-10.73,2.85-16.1,4.27-1.11,.29-2.51,.56-2.01-1.14,5.25-22.93,12.07-45.53,18.31-68.18,.04-.29-.41-.65-.76-.59-6.99,1.11-13.96,2.32-20.94,3.48-1.73,.05-.72-2-.6-2.98,7.25-26.49,16.19-52.65,24.68-78.8-7.53,.71-15.11,1.11-22.68,1.06-.88,.05-1.84-.12-2.59,.41-8.12,26.47-16.23,53.03-22.35,80.01,.09,.64,1,.72,1.54,.74,5.93,0,11.86,0,17.79,0,1.93-.19,2.81-.02,2.29,1.52-5.98,21.93-11.35,44.01-15.83,66.29-.04,.71-.46,2.14,.46,2.33,6.45,.59,12.63-1.89,18.84-3.11,1M .85-.17,.76,1.91,.71,2.91-3.46,15.23-6.54,30.54-9.29,45.91-.64,3.52-1.23,7.04-1.82,10.56-.11,.63-.28,1.28,.26,1.98,6.21-1.32,12.07-4.22,18.2-5.9,.32-.09,.87,.23,.83,.5-2.57,17.31-6.24,34.48-7.59,51.96,.47,1.1,1.89-.02,2.66-.24,3.88-1.73,7.75-3.48,11.62-5.22,1.04-.41,2.07-1.22,3.25-.92,.13,.03,.24,.38,.22,.57-.97,6.14-1.57,12.3-2.42,18.46,5.04,2.06,10.22,4.08,15.54,6.05,1.12-8.59,2.21-17.16,3.85-25.69,.35-2.64,1.28-5.37,1.01-8Zm10.27,36.21c-1.4-.03-2.41,1.03-3.59,1.63,1.12,.39,2.24,.77,3.37,1.16,.04-.93,.54-1.9,.22-M 2.79Zm78.11,114.53c-1.58,2.17-3.15,4.33-4.75,6.49-.1,.14-.45,.17-.7,.21-.05,.01-.19-.12-.22-.2-1.06-4.73-.82-9.67-1.18-14.49-.04-.63-.26-1.25-.42-1.88-.02-.09-.15-.21-.26-.23-.62,.04-1.17,.91-1.59,1.33-2.33,3.03-4.62,6.07-6.93,9.11-.63,.62-.99,1.85-2.05,1.68-.11,0-.27-.1-.29-.17-.9-6.17-.88-12.47-1.06-18.7-.4-1.32-1.84,.75-2.3,1.19-2.47,2.95-4.91,5.92-7.38,8.88-1.36,1.5-2.05,1.99-2.24-.51-.15-6.57-.27-13.14-.32-19.71,0-.5-.25-.83-.53-.74-.34,.12-.74,.25-.95,.47-2.86,3.13-5.69,6.28-8.55,9.41-.39,.43-.87,.81-1.33,1.2M -.13,.05-.57-.08-.64-.21-.74-7.46,.04-15.08-.07-22.6-.13-.85,.35-2.27-.62-2.65-.06-.04-.26,.02-.34,.08-14.28,12.75-12.13,16.75-11.53-4.56,.15-4.63,.29-9.25,.42-13.88-.4-1.11-1.81,.44-2.34,.8-14.33,12.14-11.52,12.59-10.59-5.61-4.72-1.39-9.35-2.82-13.91-4.28-.43,10.02-1.14,20.06-.64,30.06,.65,.31,1.08,.09,1.47-.23,2.82-2.33,5.63-4.65,8.44-6.97,.71-.44,3.29-3.34,3.73-1.8-.02,8.83-.33,17.66,.04,26.49,.03,.86,.08,1.72,.18,2.58,.08,.21,.59,.57,.87,.35,3.45-2.77,6.37-6.12,9.62-9.12,2.44-2.27,2.17-.53,2.27,1.71-.05,7.33,.2M 3,14.65,.79,21.96,.04,.57,.04,1.14,.7,1.32,.66-.13,1.13-.92,1.63-1.35,2.51-2.8,5.01-5.61,7.52-8.41,.49-.42,.99-1.19,1.64-1.31,.21,.1,.53,.24,.54,.38,.25,4.19,.44,8.39,.72,12.58,.2,2.91,.5,5.8,.78,8.7,.09,.34,.2,1.04,.65,1,.31-.18,.68-.34,.88-.58,2.27-2.81,4.51-5.63,6.76-8.44,.77-.69,1.42-2.34,2.55-2.2,.52,.05,.46,.74,.56,1.12,.54,6.01,.88,12.05,1.73,18.04,.24,.6,.71,.82,1.33,.08,3.02-3.75,5.42-8.12,8.84-11.51,.88-.19,.92,1.19,1.04,2.04,.03,3.46,.78,6.87,1.16,10.3,.17,1.49,.52,2.98,.8,4.47,.02,.08,.15,.21,.22,.21,.2M 5-.01,.61,0,.72-.12,2.75-3.52,5.04-7.36,7.62-11.01,1.73-2.7,2.29-.95,2.49,1.22,.55,4.05,.96,8.17,1.85,12.14,.71,.16,1.09-.05,1.37-.48,.64-.98,1.29-1.96,1.93-2.93l-.13-20.72Zm.25,39.06c-1.11-4.05-1.67-8.52-3.16-12.35-1.05-.01-1.35,1.17-1.9,1.86-1.95,3.19-3.87,6.4-5.82,9.59-.34,.57-.57,1.22-1.41,1.59-.23-.24-.62-.46-.69-.73-.99-4.23-2.1-8.45-2.69-12.73-.08-.53-.21-1.06-.35-1.59-.01-.06-.19-.16-.29-.15-.97-.12-1.26,.88-1.76,1.5-2.35,3.5-4.53,7.12-6.98,10.56-.11,.14-.48,.24-.69,.2-.18-.03-.4-.26-.43-.43-.56-2.98-1.11-5M .96-1.63-8.95-.67-2.76-.42-5.76-1.75-8.31-1.19,.69-1.65,1.65-2.4,2.68-2.19,2.97-4.15,6.09-6.48,8.94-.17,.11-.86,.17-.99-.14-1.59-6.43-2.01-13.01-3.12-19.51-.07-.13-.55-.22-.66-.14-3.28,3.31-5.77,7.29-8.84,10.79-.29,.34-.77,.5-.98,.33-.17-.14-.41-.31-.43-.48-.2-1.39-.33-2.79-.52-4.18-1.06-6.05-1.14-12.26-2.2-18.27-.72-.15-1.09,.15-1.41,.5-2.54,2.79-5.06,5.58-7.61,8.36-.58,.47-1.41,1.86-2.22,1.36-1.05-2.71-.68-5.78-1.09-8.63-.41-5.38-.81-10.75-1.23-16.12-.08-.57-.04-1.6-.87-1.47-3.18,2.38-5.83,5.36-8.8,7.99-.82,.6-1.M 52,1.8-2.62,1.85-.2-.04-.47-.26-.5-.42-.43-3.31-.21-6.67-.54-10-.66-6.55-.48-13.13-.77-19.69-.78-.91-2.04,.65-2.75,1.08-2.69,2.12-5.37,4.24-8.06,6.36-.84,.57-2.63,2.52-2.95,.49-.14-2.8-.24-5.6-.33-8.4-.26-7.65-.26-15.3,0-22.95-.03-.91,.39-2.86-1.1-2.49-3.79,2.2-7.35,4.73-11.05,7.05-.76,.37-2.22,1.83-2.77,.52-.18-8.15,.2-16.31,.39-24.46-11.27-4.29-21.96-8.76-32.07-13.33-.01,3.79-.2,7.6-.05,11.39,.06,.59,.41,1.11,1.13,1.09,3.97-.4,7.31-2.58,10.9-4.07,1.01-.23,3.88-2.58,4.22-.86-.25,12.6-.72,25.21,.05,37.8,.15,.77-.23M ,2.66,1.11,2.25,4.15-2.13,7.99-4.76,12.01-7.1,1.34-.77,2.32-1.05,2.22,.93,.14,11.17,.32,22.5,1.54,33.56,.61,.85,1.65-.12,2.27-.51,3.36-2.49,6.71-4.98,10.07-7.48,.66-.48,1.26-.25,1.45,.35,.32,4.08,.63,8.17,.94,12.25,.51,5.92,.61,11.87,1.84,17.7,.02,.09,.52,.26,.64,.2,3.89-2.65,6.98-6.32,10.74-9.17,.19-.15,.97,.07,1.02,.28,.09,.42,.21,.85,.26,1.27,1.09,8.22,1.23,16.67,3.17,24.73,.87,1.07,1.8-.69,2.5-1.19,2.28-2.41,4.53-4.82,6.8-7.23,.51-.54,1.56-1.9,2.18-.78,.57,3.74,1.1,7.48,1.69,11.22,.57,3.63,1.21,7.26,1.82,10.89,M .69,1.86,2.04-.15,2.7-.97,1.89-2.35,3.77-4.72,5.66-7.07,.71-.86,1.16-1.88,2.49-1.77,1.21,6.61,2.4,13.01,3.73,19.56,.43,1.39,1.45,.47,1.98-.27,2.56-3.42,4.71-7.11,7.52-10.31,.12-.1,.57-.08,.65,.09,1.86,5.82,2.18,11.98,4.39,17.71,.96-.12,1.26-.97,1.76-1.65,1.76-2.79,3.5-5.59,5.26-8.37,.51-.68,1.41-2.77,2.34-1.54,1.2,4.64,2.27,9.29,3.5,13.93,.15,.36,.34,.96,.74,1.09,.22,0,.57-.03,.64-.13,10.69-16.69,6.04-16.75,12.47,1.18,.7-.06,1.05-.36,1.27-.78,2.36-4.08,4.27-8.46,6.91-12.36l-.02-3.54Zm217.19-95.29s.04,.05,.06,.08c.0M 2,0,.04,0,.06-.02l-.12-.06Zm2.09,39.43c-1.84-1.42-4.33-3.05-6.1-4.74,1.78-1.48,4.19-1.84,6.27-2.81l.25-10.89c-4.75,1.85-9.45,3.78-14.01,5.93-.47,.22-.93,.43-1.51,.25-3.6-2.73-5.76-4.78-7.26-6.93,3.86-2.26,8.16-4,12.28-5.83-5.79,.53-11.53,.99-17.21,1.4,1.3,1.53,3.17,2.72,4.07,4.5-7.25,3.91-14.48,7.76-21.51,11.89-.65,.36-1.21,.88-2.29,.89-2.24-1.85-4.51-3.82-6.6-5.93-.34-.34-.26-.84,.2-1.13,5.24-3.48,10.81-6.49,16.31-9.57-7.28,.45-14.45,.8-21.53,1.06-.67,.43-1.36,.82-2.12,1.16-.41-.33-.76-.68-1.07-1.04-5.19,.17-10.33M ,.3-15.42,.37-3.54,2.46-6.8,5.18-10.26,7.67-.26,.18-.87,.09-1.03-.16-1.51-2.29-2.95-4.58-4.42-6.9-.26-.4-.92-.46-1.36-.13-6.05,4.54-11.26,9.85-16.86,14.81-.36,.32-1.13,.17-1.29-.24-.8-2.15-1.26-4.41-1.94-6.59-.08-.28-.25-.68-.51-.77-.86-.22-1.28,.63-1.86,1.04-4.56,4.39-9.22,8.72-13.48,13.31-.47,.5-.82,1.14-1.88,1.26-1.61-2.6-1.5-5.62-2.84-8.29-.65-.04-1.03,.24-1.35,.6-1.9,2.1-3.81,4.18-5.68,6.29-2.77,3.05-5.33,6.25-8.2,9.21-.13,.12-.5,.17-.71,.11-.61-.16-.68-.84-.83-1.35-.66-2.31-1.31-4.62-1.99-6.92-.05-.18-.29-.4-M .5-.46-.59-.09-1.07,.53-1.44,.92-4.63,4.95-8.35,10.64-12.95,15.58-1.34,.48-2.04-4.7-2.46-5.68-.45-1.25-.46-2.97-1.14-4.03-.25,.03-.59,.04-.73,.17-1.93,1.99-3.41,4.37-5.14,6.51l.1,16.42c2.31-3.22,4.6-6.45,6.9-9.67,.67-.77,1-1.76,2.19-1.84,.76,1.15,2.73,9.73,4.04,8.61,4.16-4.84,7.71-10.15,11.91-14.98,.53-.49,1.42-2.07,2.17-1.17,.76,1.95,1.52,3.9,2.25,5.86,.27,.72,.5,1.45,1.22,2,.87-.2,1.19-.83,1.64-1.35,3.65-4.27,7.3-8.54,10.95-12.8,.72-.61,1.33-1.98,2.38-1.95,.23,.06,.46,.26,.54,.44,1,2.31,1.55,4.92,3.02,6.98,.41,.2M ,.95-.33,1.23-.54,4.2-4.62,8.64-9.09,13.19-13.49,.59-.57,1.06-1.26,2.15-1.56,2.3,2.11,3.17,4.93,5.48,7.1,1.41-.24,2.18-1.45,3.18-2.33,4.28-4.17,8.83-8.14,13.61-11.94,.54-.44,.99-1.02,1.99-1.08,1.82,2.21,3.67,4.45,5.53,6.68,.24,.18,.47,.16,.85,.21,6.63-4.69,13-9.77,19.92-14.06,.43-.27,1.1-.18,1.41,.18,1.83,2.4,4.37,4.36,5.69,7.03-7.04,4.39-13.58,9.48-20.38,14.12-.88-.18-1.26-.63-1.67-1.04-1.67-1.69-3.31-3.4-4.97-5.09-.24-.25-.78-.29-1.08-.07-5.55,4.3-10.98,8.91-16.05,13.65-.49,.47-.89,1.07-1.85,1.21-2.57-1.69-3.4-4.M 6-5.96-6.35-.23-.63-3.12,2.5-5.31,4.65-3.17,3.22-6.32,6.44-9.49,9.65-.49,.49-.85,1.1-1.94,1.27-1.97-2.1-3.32-4.58-5.19-6.82-.83,.1-1.18,.55-1.54,.98-3.99,4.86-7.96,9.74-11.96,14.59-.44,.53-1.21,.46-1.55-.15-.87-1.58-1.7-3.17-2.55-4.75-.47-.59-.73-2.09-1.7-1.79-4.72,4.83-8.07,10.71-12.23,15.93-.17,.22-.89,.19-1.03-.05-.68-1.17-1.35-2.34-2-3.52-.66-1.18-1.28-2.36-1.93-3.55-1.01-.77-1.71,1.04-2.27,1.65-3.03,4.3-5.7,8.85-8.81,13.07-.18,.15-.79,.23-.96-.05-.32-.67-.63-1.35-.94-2.02l.03,5.33c.43-.45,.87-1.48,1.62-1.13,1.M 76,2.77,2.5,5.39,4.96,7.94,3.59-4.89,6.4-10.32,9.92-15.29,.53-.77,1.07-.5,1.51-.06,1.25,1.79,2.46,3.58,3.71,5.37,.29,.42,.95,1.03,1.48,.63,1.08-1.49,2.14-2.98,3.16-4.5,2.5-3.69,5.15-7.32,8-10.85,.31-.39,1.03-.39,1.34-.01,1.42,1.7,2.84,3.4,4.25,5.11,.3,.36,.68,.64,1.38,.72,4.03-4.79,7.97-9.7,11.98-14.51,.43-.52,.8-1.12,1.78-1.34,2.2,2.07,3.84,4.38,6.47,6.16,4.87-4.63,9.4-9.48,14.15-14.21,.5-.5,.94-1.07,1.93-1.19,2.15,1.86,4.35,3.75,6.52,5.66,.15,.13,.14,.38,.21,.6-4.76,4.63-9.31,9.47-13.95,14.23-.34,.34-.6,.7-.46,1.M 28,2.35,1.63,5.05,3.2,7.47,4.7,.98-.18,1.36-.78,1.84-1.27,4.22-4.47,8.58-8.87,13.04-13.18,0-.2,.06-.48-.08-.59-2.29-1.77-4.99-3.3-7.09-5.2,.05-.28,.01-.53,.14-.69,1.85-2.11,13.88-12.2,17.3-14.51,3.04,1.64,4.88,4.34,8.07,5.83,6.56-4.7,13.41-9.33,20.21-13.66,2.68,1.35,5.24,4.01,7.81,5.75,.78,.53,1.8-.04,2.53-.45,6.79-4,13.85-7.51,20.95-10.97,.5-.25,1.11-.19,1.48,.12,2.35,2.25,5.34,3.96,7.25,6.56-7.52,3.82-15.49,7.01-22.43,11.46,2.09,2.21,5.42,3.68,7.93,5.55,.44,.29,1,.27,1.51,.02,1.83-.91,3.67-1.8,5.48-2.74,3.73-1.94M ,7.66-3.61,11.55-5.32,1.59-.71,3.5-1.02,4.83-2.21,.27-.25,.29-.33-1.86-1.95Z"/><path class="cls-2" d="M510.8,220.18s-.02,.03-.03,.05c-.02,0-.03,.01-.05,.01l.08-.06Z"/><path class="cls-2" d="M547.46,404.29c-1.72,10.76-4.71,21.33-6.09,32.16-4.69-1.32-9.28-2.68-13.79-4.08,.87-5.86,2.37-11.64,2.71-17.56,0-.1-.47-.33-.58-.29-5.09,2.73-9.66,6.37-14.87,8.87-.11,.05-.56-.17-.56-.24,.46-4.18,.97-8.35,1.6-12.52,1.75-10.14,3.82-20.24,5.98-30.3,.11-.72-.15-1.2-.94-.94-2.5,.99-4.82,2.37-7.24,3.52-2.89,1.38-5.67,2.97-8.64,4.17-.M 29,.12-.88-.22-.83-.5,2.73-16.04,6.49-31.91,10.5-47.69,.05-.9,1.19-2.77-.32-2.76-6.02,2.09-11.78,4.88-17.85,6.76-.3,.07-.6-.08-.58-.33,.09-.96,.16-1.93,.39-2.87,1.67-6.97,3.3-13.96,5.09-20.92,2.8-11.18,6.07-22.3,9.23-33.42,.14-.52,.28-1.05-.32-1.58-5.58,1.41-11.15,3.11-16.71,4.65-1.03,.1-3.92,1.73-3.75-.23,6.36-22.81,12.96-45.65,20.88-67.96,7.44-1.42,14.85-3.01,22.3-4.34,.39-.06,.85,.27,.76,.55-2.33,6.52-4.7,13.02-7.02,19.55-5.06,15.44-11.12,30.84-14.97,46.53,.52,.62,1.47,.17,2.14,.05,6.04-1.79,12.07-3.67,18.11-5.3M 9,.82,.59,.32,1.39,.17,2.17-2.02,6.25-4.14,12.48-6.06,18.76-3.52,12.15-7.43,24.21-10.31,36.52-.05,.25,.59,.55,.91,.42,1.09-.41,2.19-.82,3.27-1.26,4.32-1.77,8.62-3.55,12.94-5.31,.58-.18,1.66-.71,2.04-.02-2.15,9.64-5.48,19.08-7.67,28.71-1.52,6.77-3.69,13.44-4.64,20.3-.03,.28,.58,.5,.93,.33,4.73-2.23,9.28-4.78,13.94-7.15,.67-.35,1.38-.64,2.09-.95,.39-.15,.59,.26,.72,.55-2.96,12.21-5.94,24.5-8.47,36.83-.38,1.8-.58,3.62-.85,5.44-.02,.09,.07,.27,.14,.28,.91,.26,1.65-.52,2.39-.89,3.49-2.21,6.97-4.42,10.46-6.62,.86-.32,2.7M 3-2.42,3.37-1Z"/><path class="cls-2" d="M555.97,432.23c-.39,2.6-.93,5.19-1.38,7.78-2.73-.7-5.44-1.42-8.11-2.15,2.78-2.07,5.51-4.16,8.31-6.21,.49-.23,1.33-.37,1.18,.58Z"/><path class="cls-2" d="M560.79,484.1c-3.69,2.88-6.84,6.57-10.34,9.72-.67,.53-1.22,1.37-2.2,1.06,.07-4.52,.65-9.03,.93-13.54,3.82,.95,7.69,1.87,11.61,2.76Z"/><path class="cls-2" d="M577.13,262.92s-.01,0-.02,.01c.01-.02,.01-.03,.02-.05v.04Z"/><path class="cls-2" d="M591.59,519.23c-2.02,2.47-3.92,5-6.06,7.38-.24,.28-.86-.04-.93-.22-.48-5.57-.02-11.2-.M 09-16.79,.01-.53-.1-1.06-.18-1.59-.01-.07-.18-.13-.29-.16-.5-.19-.85,.41-1.18,.67-2.5,2.94-4.98,5.89-7.47,8.83-.92,.89-1.47,2.42-2.92,2.22-.3-3.69-.2-11.65,.12-15.28,.18-2.04,.26-4.08,.38-6.12,.01-.27-.15-.46-.43-.44-1.18,.22-1.8,1.53-2.68,2.26-2.41,2.59-4.82,5.19-7.23,7.78-.6,.53-1.04,1.44-1.94,1.48-.92,.12-.35-2.66-.48-3.32,.24-7.24,.94-14.44,1.28-21.67,4.05,.92,8.16,1.82,12.33,2.68-.22,2.65-.41,5.3-.61,7.95,.04,.5,.8,.55,1.09,.27,2.23-2.22,4.33-4.56,6.5-6.83,1.65,.33,3.31,.65,4.98,.96-.31,4.85-.76,9.68-1.15,14.5M 3,.05,.48-.17,1.39,.59,1.36,2.15-1.35,4.28-4.57,6.24-6.46l.13,20.51Z"/><path class="cls-2" d="M596.7,427.88c-1.79,6.77-3.17,13.62-4.62,20.46-4.11-.77-8.16-1.58-12.16-2.43,.34-1.72,.49-3.47,.7-5.22,.01-.07-.12-.18-.22-.22-.11-.05-.32-.1-.38-.06-1.98,1.25-3.63,2.89-5.43,4.35-2.43-.53-4.84-1.07-7.23-1.63,1.75-7.78,3.34-15.57,4.8-23.41,.02-.12-.25-.3-.43-.42-.82,.01-1.54,.86-2.24,1.25-3.46,2.57-6.9,5.14-10.36,7.71-.63,.31-1.54,1.46-2.2,.8-.02-3.36,1.13-6.59,1.79-9.87,1.95-8.04,3.64-16.13,5.87-24.09,.11-.75,.9-2.55-.43-M 2.38-4.68,2.65-9.11,5.72-13.7,8.54-.62,.39-1.21,.87-2.17,.86,1.12-7.47,3.77-15.89,5.65-23.38,1.73-6.09,3.46-12.18,5.17-18.27-.01-1.59-2.23,.14-2.95,.38-4.06,2.13-8.1,4.27-12.16,6.4-.72,.29-2.55,1.7-2.7,.24,1.87-7.95,4.42-15.75,6.61-23.63,2.25-7.43,4.77-14.8,7.04-22.22,.21-.71,.7-1.43,.15-2.18-6.31,1.79-12.1,5.28-18.38,7.29-.41,.18-.69-.33-.68-.58,5.7-18.9,11.85-37.66,19.08-56.06l.25-.21c7.25-2.33,14.5-4.65,21.74-6.97-7.23,17.31-13.91,34.82-19.99,52.43-.28,.83-.5,1.67-.69,2.51-.02,.09,.41,.36,.54,.33,6.25-2.06,12.06M -5.37,18.33-7.36,.14-.03,.57,.24,.55,.33-.16,.74-.34,1.47-.62,2.19-5.45,14.2-10.29,28.53-14.81,42.94-.08,.51-.5,1.5-.16,1.87,.21,.08,.52,.19,.68,.12,5.51-2.63,10.74-5.79,16.22-8.5,.24-.05,.89-.06,.89,.33-.17,.73-.31,1.48-.55,2.2-3.73,10.88-7.04,21.87-10.27,32.89-.5,1.67-.93,3.36-1.36,5.05-.05,.18,.03,.48,.2,.58,.14,.09,.55,.06,.72-.04,4.74-2.8,9.29-5.87,13.95-8.81,.52-.33,1.02-.71,1.92-.57-.42,4.68-2.91,9.15-3.86,13.77-1.71,7.19-3.92,14.28-5.62,21.48,0,.25,.42,.66,.73,.46,.74-.46,1.49-.91,2.18-1.42,4.15-2.88,8.02-6M .17,12.36-8.78,1.85-.84-1.66,7.67-1.64,8.73-1.66,7.42-4.22,15.07-5.14,22.47,.93,.13,1.54-.7,2.23-1.16,3.5-2.84,6.98-5.69,10.49-8.52,.59-.34,2.31-2.19,2.31-.57Z"/><path class="cls-2" d="M597.34,493.03h-.05s-.02-.05-.03-.07l.08,.07Z"/><path class="cls-2" d="M605.56,443.57c-.28,2.35-1.05,4.61-1.52,6.92-2.14-.36-4.27-.73-6.37-1.11,2.38-2.07,4.63-4.26,7.11-6.21,.28-.22,.76,.2,.78,.4Z"/><path class="cls-2" d="M640.33,497.26c-2.76,2.72-4.71,6-4.04-.45,1.34,.15,2.69,.3,4.04,.45Z"/><path class="cls-2" d="M691.47,500.86c-4.9M 9,4.42-9.68,9.54-14.82,13.61-.22-.09-.55-.21-.58-.35-.41-2.24-.77-4.48-1.15-6.72-.33-3-1.24-2.07-2.88-.49-4.04,4.3-8.06,8.63-12.1,12.94-.79,.65-1.36,1.91-2.51,1.87-1.22-2.9-1.32-6.36-1.96-9.48-.57-1.38-1.81,.22-2.39,.88-4.04,4.7-8.14,9.36-12.11,14.12-.41,.44-1.11,1.45-1.71,1.04-.17-.15-.41-.31-.44-.49-.61-3.31-1.04-6.64-1.81-9.91-.91-1.53-3.21,2.65-3.97,3.29l-.09-15.67c1.33-1.28,3.24-4.55,3.34-1.09,.25,3.44,.37,6.89,.7,10.32,0,.58,.91,.44,1.19,.18,4.65-4.86,8.89-10.08,13.68-14.81,.63-.6,.96-1.57,2.3-1.51,.77,.61,.4M 4,1.41,.48,2.12,.32,1.25-.31,9.57,1.39,8.83,3.67-3.04,6.74-6.71,10.16-10.02,2.6,.19,5.22,.35,7.86,.51,.11,5.87,1.86,2.64,4.42,.25,4.29,.23,8.62,.43,13,.58Z"/><path class="cls-2" d="M704.01,501.22c-2.19,1.94-4.28,3.95-6.54,5.83-.14,.11-.52,.13-.73,.08-.22-.06-.49-.26-.52-.42-.38-1.9-.71-3.82-1.05-5.72,2.92,.1,5.87,.17,8.84,.23Z"/><path class="cls-2" d="M716.09,457.41c-.07,.87-.08,1.71-.23,2.54-1.45-.01-2.89-.02-4.32-.04,1.48-.86,2.74-2.61,4.55-2.5Z"/><path class="cls-2" d="M738.88,454.85c-.09,1.64-.2,3.29-.3,4.93-3.M 65,.08-7.28,.13-10.87,.16,3.4-2.22,6.68-4.67,10.2-6.7,1.1-.37,.98,.93,.97,1.61Z"/><path class="cls-2" d="M764.6,458.8c-6.54,.35-13,.62-19.36,.8,5.45-3.34,10.8-6.72,16.51-9.71,.7-.24,1.73-1.21,2.36-.46,.29,2.87-.27,5.79-.29,8.69-.02,.42,.33,.68,.78,.68Z"/><path class="cls-2" d="M809.27,483.34l-.12-.06s.04-.02,.06-.02c.02,.03,.04,.05,.06,.08Z"/><path class="cls-2" d="M870.74,441.98s-.07,.01-.1,.02c-.02-.03-.03-.07-.04-.1l.14,.08Z"/><path class="cls-2" d="M872.29,446.69c-27.76,4.67-54.23,8-79.47,10.15-.68-1.41-2.37-.0M 6-3.37,.29-8.37,.68-16.61,1.23-24.7,1.66,8.9-4.45,17.65-9.39,27.04-13.08,.55-.2,1.16,.07,1.14,.52-.09,1.62-.2,3.23-.29,4.84,.18,1.05-1.04,4.68,.85,4.16,10.89-4.21,21.66-8.78,32.89-12.36,1.82-.49,1.61,2.16,2.31,3.21,.75,1.84,1.51,3.68,2.31,5.51,.32,.75,.92,.94,1.92,.66,12.45-3.73,24.92-7.52,37.72-10.25,.55,1.56,1.11,3.12,1.65,4.69Z"/><path class="cls-2" d="M637.75,1092.25c.55,.13,1.06,.02,1.54-.19,3.79-1.63,7.59-3.24,11.37-4.9,5.67-2.48,11.16-5.2,16.67-7.9,.27-.09,1.23-.46,1.3,.02-2.6,5.81-6.35,11.13-9.39,16.75-.28,M .36,.26,.65,.6,.55,9.34-3.97,18.17-9.61,27.54-13.23,.11,.17,.3,.41,.23,.55-.5,.99-1.03,1.98-1.61,2.95-2.77,4.66-5.56,9.32-8.34,13.98-.34,.58-.61,1.18-.89,1.78-.03,.06,.1,.19,.2,.26,.33,.19,.75-.06,1.06-.17,4-1.99,8.03-3.93,11.98-5.99,4.06-2.12,8.02-4.35,12.04-6.52,.99-.52,2.52-1.12,1.5,.73-3.72,6.73-7.96,13.18-11.99,19.73-.12,.29-.33,1.01,.12,1.07,8.46-3.75,16.48-8.54,24.72-12.77,.59-.31,1.22-.43,1.86-.06l-.11-.03c-4.74,8.2-10.09,16.11-14.94,24.3-.13,.36,.58,.47,.74,.42,7.64-3.79,15.17-7.74,22.62-11.84,1.56-.74,3.5M 7-2.02,1.88,.86-4.72,7.97-9.91,15.75-15.07,23.55-2.57,3.81-2.51,4.16,1.72,2.01,7.33-3.42,14.51-7.73,21.93-10.69,.49,.74-.37,1.39-.67,2.05-6.44,10.42-13.69,20.45-20.45,30.76,0,.13,.37,.39,.53,.34,.75-.23,1.51-.43,2.22-.72,5-2.1,9.99-4.22,14.99-6.33,.58-.18,3.46-1.77,3.03-.31-4.38,6.82-9.11,13.42-13.7,20.11-3.28,4.7-6.67,9.34-10,14.01-.51,1.09-2.3,2.23-1.4,3.46,0-.23-.06-.32-.29-.36l.28,.3c6.75-2.43,13.49-4.86,20.25-7.27,.16-.06,.47,.11,.68,.21,.06,.03,.06,.2,.02,.28-.67,1.56-1.82,2.88-2.74,4.31-8.85,12.94-18.58,25.4M 1-27.86,38.19,.13,.94,2.14-.03,2.78-.07,6.35-1.76,12.62-3.81,19.02-5.38,.88,.17,.22,1.08-.06,1.56-2.84,3.91-5.69,7.82-8.55,11.72-8.45,11.52-17.24,22.87-26.3,34.09-.5,.62-1.16,1.2-1.16,2.01,.64,.35,1.32,.23,1.96,.1,2.35-.47,4.69-.97,7.04-1.44,4.3-.88,8.61-1.74,12.92-2.61,.46-.15,1.14-.21,1.49,.07,.11,.14,.05,.43-.07,.6-.58,.85-1.17,1.7-1.81,2.52-6.41,8.23-12.79,16.47-19.24,24.67-7.43,9.62-15.43,18.91-23.08,28.44-.08,.28,0,.76,.43,.7,2.4-.23,4.81-.45,7.21-.71,5.21-.52,10.4-1.27,15.61-1.69,1.32-.21,2.02,.37,.95,1.47-1M 7.51,21.6-34.69,43.52-53.74,63.85-8,.28-16.1,.05-24.12,.12-2.28-.09-3.49,.01-1.31-2.21,10.46-11.17,20.76-22.52,30.89-33.97,6.68-7.56,13.25-15.2,19.85-22.8,.86-1.21,2.31-2.13,2.45-3.67-7.67,.36-15.25,1.58-22.9,2.25-.49,0-2.21,.27-1.94-.48,15.33-17.94,31.61-35.31,45.79-54.05-.45-.06-.83-.19-1.15-.13-3.53,.67-7.06,1.39-10.59,2.07-3.92,.75-7.85,1.48-11.79,2.19-.11,.02-.47-.3-.43-.39,11.45-14.73,24.32-28.66,35.52-43.52,1.35-1.7,4.33-4.74-.07-3.42-6.12,1.66-12.23,3.34-18.34,5.01-.62,.17-1.26,.43-1.85,.03,10.25-13.85,22.0M 6-26.87,31.81-41.15-.31-.82-2.12,.2-2.78,.29-5.32,1.81-10.64,3.65-15.96,5.46-.86,.29-1.76,.5-2.66,.73-.08,.02-.24-.1-.32-.18-.29-.35,.42-1.05,.61-1.4,7.54-9.57,14.85-19.24,22.02-28.99,1.3-1.76,2.5-3.56,3.73-5.35,.28-.33-.21-.71-.57-.58-7.77,3.17-15.41,6.63-23.13,9.91-1.74,.65-3.8,1.55-1.77-1.07,6.97-9.71,14.42-19.11,20.97-29.1,.3-1.51-3.24,.82-3.84,.9-7.39,3.31-14.64,6.93-22.12,10.05-1.46,.06-.44-.86-.05-1.55,5.68-8.07,11.36-16.14,17.04-24.21,.26-.37,.49-.77,.64-1.17,.05-.14-.17-.35-.31-.6-8.91,3.96-17.46,8.67-26.4M 9,12.35-.14,.02-.47-.24-.4-.41,.55-.86,1.08-1.73,1.68-2.56,4.78-6.87,9.8-13.56,13.86-20.79-.34-.81-1.76,.16-2.33,.34-7.45,3.89-15.25,7.31-22.94,10.86-2.39,1.1-3.42,1.29-1.52-1.42,3.84-5.81,7.69-11.61,11.52-17.42,.3-.45,.79-.88,.59-1.46-.03-.09-.22-.23-.27-.21-.73,.26-1.48,.49-2.17,.82-8.61,4.24-17.49,7.98-26.01,12.35l.12-.05c-1.22-1.12,.78-2.65,1.29-3.75,3.03-4.3,5.86-8.67,8.57-13.1,.41-.67,.77-1.36,1.09-2.06,.07-.15-.14-.38-.24-.61-10.8,4.64-21.64,9.4-32.75,13.66l.02,.08c-.94-1.12,.67-2.21,1.17-3.19,2.93-4.11,5.88M -8.22,8.81-12.34,.46-.65,.9-1.32,1.29-2,.08-.14-.08-.37-.17-.55-11.55,3.8-22.96,8.96-34.66,12.88-1.55,.34-5.42,2.48-3.03-.79,2.88-4.26,5.77-8.51,8.65-12.78,.25-.37,.41-.79,.58-1.19,.03-.06-.09-.18-.17-.24-.52-.37-1.27,.14-1.83,.24-9.88,3.69-20.05,6.83-30.1,10.22-2.72,.92-5.44,1.88-8.34,2.41-.85-.2-.2-1.08,.08-1.57,2.88-4.25,5.92-8.42,8.59-12.8,.08-.13,0-.43-.14-.53-1.28-.41-2.85,.57-4.16,.79-12.21,3.68-24.51,7.17-36.97,10.3-.96,.17-1.83,.64-2.78,.07,2.48-4.67,5.95-8.83,8.29-13.57-.26-.78-1.81-.17-2.41-.11-14.79,3.5M 6-29.71,7.15-44.81,9.61-1.44-.14-.25-1.4,.05-2.08,2.06-3.51,4.26-6.95,6.26-10.49,.13-.29,.25-.71,.08-.92-.74-.67-2.12-.08-3.05-.03-10.74,2.07-21.61,3.58-32.48,5.08-5.45,.66-10.88,1.64-16.37,1.91-1.48-.24,.14-1.98,.37-2.75,1.68-3.05,3.4-6.09,5.08-9.15,.21-.5,.73-1.39,.03-1.69-3.72-.26-7.48,.57-11.21,.75-8.42,.87-16.9,1.28-25.34,1.87-6.44,.54-12.92,.5-19.36,.91-1.08,.12-3.39,.16-2.61-1.31,1.81-4.04,4.2-7.88,5.63-12.07,.07-.26-.33-.69-.67-.7-1.07-.04-2.14-.09-3.21-.09-21.4,.13-42.84-.14-64.19-1.77l.13,.12c1.82-4.49,3.M 64-8.98,5.46-13.48,.18-.48,.29-1.26-.37-1.4-6.49-.91-13.06-1.28-19.58-1.97-19.82-1.95-39.52-4.81-59.2-7.82l.09,.1c1.68-5.4,2.84-10.98,4.89-16.25l-.13,.07c26.58,4.42,53.27,8.92,80.17,10.99l-.15-.14c.13,.66-.12,1.27-.35,1.9-1.45,4.22-3.32,8.36-4.42,12.67,6.76,1.54,14,1.03,20.93,1.74,14.11,.77,28.26,1.12,42.4,1.17,1.21,.25,5.47-.79,4.53,1.44-1.38,3.15-2.83,6.27-4.2,9.42-1.46,2.98-1.32,2.98,2.53,2.95,8.36-.07,16.69-.49,25.02-.96,9.14-.43,18.26-1.19,27.35-2.02,4.51-.66,3.94,.04,2.55,2.84-1.52,3.11-3.26,6.13-4.76,9.25-.7M 8,1.55,1.86,1.04,2.79,.99,4-.47,8-.9,11.98-1.43,12.33-1.64,24.62-3.54,36.88-5.58,1.7-.04,.6,1.46,.23,2.25-1.88,3.56-4.07,6.99-5.76,10.65-.13,.29,.31,.6,.75,.52,4.32-.81,8.66-1.56,12.95-2.47,11.03-2.39,22.07-4.69,32.99-7.5,.22-.05,.5,.04,.74,.09,.66,.23-.13,1.3-.35,1.74-1.96,3.83-4.8,7.55-6.29,11.48,1.03,.62,2.27-.23,3.37-.34,10.15-2.54,20.13-5.46,30.09-8.44,3.14-.94,6.3-1.87,9.46-2.78,.18-.05,.47,.12,.69,.22,.17,.34-.17,.85-.31,1.2-2.24,3.8-4.57,7.56-6.85,11.34-.36,.6-.61,1.2-.12,1.81,.04-.22,.03-.34-.19-.43l.2,.38M c13.27-4.37,26.52-8.93,39.61-13.72,.2,.23,.5,.42,.46,.54-.17,.51-.37,1.03-.67,1.5-2.26,3.67-4.55,7.33-6.82,10.99-.36,.57-.66,1.17-.97,1.76-.03,.06,.05,.19,.12,.26,.46,.42,1.29-.1,1.83-.19,6.17-2.15,12.22-4.51,18.23-6.94,5.53-2.23,11.04-4.49,16.57-6.72,.46-.19,.99-.38,1.53,.11-2.81,4.89-6.01,9.6-9,14.39-.31,.48-.64,.95-.4,1.52-.4-.21-.68,.27-.28,.39,.29-.01,.39-.15,.3-.38Z"/><path class="cls-2" d="M1250.03,891.19c-.37,.86-.06,1.71,.15,2.55,1.39,5.48,2.82,10.96,4.22,16.44,.59,2.32,1.16,4.64,1.7,6.97,.04,.15-.18,.48-.M 27,.48-1.1-.12-1.63-1.38-2.42-2.04-10.13-10.76-20.2-21.56-30.39-32.25-1.33-1.22-4.93-5.82-3.48-.87,2.27,7.97,4.57,15.94,6.84,23.92,.09,.59,.48,1.38-.28,1.67-9.65-8.67-18.54-18.78-27.93-27.93-.97-.83-4.88-5.34-3.75-1.38,2.7,9.22,5.78,18.34,8.25,27.63,.02,.08-.12,.27-.18,.27-1.15,.03-1.72-1.22-2.55-1.83-8.66-8.03-16.8-16.72-25.74-24.39-.04-.02-.3,.09-.29,.13,.27,3.56,1.97,6.89,2.84,10.35,1.89,6.97,4.5,13.78,5.93,20.84-1.73-.53-2.55-1.87-3.87-2.95-6.4-5.83-12.79-11.66-19.21-17.48-1.73-1.32-3.21-2.97-2.27,.64,2.79,9.76M ,5.6,19.51,8.39,29.26,.04,.32,.16,.99-.22,1.14-.89-.03-1.9-1.33-2.67-1.83-5.87-5.05-11.73-10.1-17.61-15.15-1.07-.73-3.22-3.01-2.53-.02,3.08,10.59,5.7,21.25,8.43,31.9,.04,.38,.21,.94-.09,1.23-1.07,.1-1.8-.92-2.5-1.45-5.32-4.28-10.61-8.57-15.93-12.85-.55-.32-2.77-2.44-2.87-1.12,2.5,10.23,4.79,20.52,7.07,30.8,.4,1.8,.71,3.61,1.05,5.42,.02,.09-.08,.26-.17,.28-.67,.24-1.14-.21-1.63-.58-5.86-4.45-11.9-8.69-17.66-13.27-.02,.08-.03,.14-.05,.21l.1-.23c-.47,.58-.49,1.22-.37,1.87,.4,2.13,.81,4.25,1.22,6.38,1.73,9.15,3.49,18.2M 9,5.07,27.47,.38,3.6,1.69,6.25-2.65,2.89-4.42-2.99-8.84-5.98-13.28-8.96-.61-.35-1.67-1.28-2.27-.67,.02,5.26,1.48,10.47,2.03,15.7,1.11,8.88,2.41,17.75,3.12,26.67,.01,.13-.3,.29-.49,.41-.35,.11-.78-.17-1.08-.31-4.77-3.01-9.62-5.89-14.44-8.83-.61-.35-1.81-1.19-2.21-.22,.75,13.65,2.23,27.27,2.62,40.95,.09,1.83,.18,3.65,.26,5.48,.01,.27-.58,.55-.89,.42-5.5-2.65-10.89-5.57-16.37-8.27-.95-.31-1.04,.62-1.06,1.29-.04,16.47,.35,32.96-.4,49.41-.13,2.99-1.45,1.8-3.45,1.07-4.03-1.74-8.04-3.5-12.07-5.24-.93-.2-2.42-1.41-3.18-.47M -.92,13.97-2.01,27.94-3.4,41.88-.23,4.2-.81,8.37-1.38,12.54-.53,1.6,.43,5.9-2.18,4.87-5.57-1.9-11.14-3.89-16.81-5.48-.5-.12-1.18,.18-1.25,.56-.34,2.13-.66,4.27-1.02,6.4-2.6,16.78-5.67,33.51-9.01,50.17-.69,3.4-1.48,6.78-2.21,10.18-.11,.52-.25,1.07,.26,1.53,0,0,.06-.02,.06-.02-6.98-.58-13.76-3.02-20.65-4.31-1.22-.31-.87-1.35-.73-2.23,1.43-6.14,2.92-12.27,4.3-18.41,3.87-16.36,6.59-32.97,9.99-49.4,.61-.69,1.81-.04,2.57,.07,4.16,1.24,8.31,2.51,12.47,3.77,4,1.21,4.13,1.62,4.51-2.1,2.58-17.73,4.4-35.56,5.85-53.42,.12-1.28M ,.4-2.55,.62-3.82,.05-.26,.29-.38,.61-.31,5.23,1.51,10.16,3.96,15.28,5.8,1.57,.59,1.95,.44,2.06-.83,1.23-17.19,1.18-34.46,1.43-51.67,.76-1.23,2.76,.68,3.77,.83,4.07,1.91,8.12,3.83,12.18,5.75,.48,.23,.97,.34,1.59-.03-.06-15.7-1.64-31.37-2.37-47.04-.02-.3,.56-.55,.88-.39,5.23,2.59,10.26,5.56,15.41,8.3,.52,.2,1.32,.28,1.25-.62-1.3-11.15-2.28-22.35-4.01-33.44,.04-1.39-2.15-9.13-.49-8.92,5.38,2.68,10.32,6.21,15.47,9.29,.42,.28,.93,.62,1.42,.35,.46-.25,.33-.77,.28-1.19-.11-.86-.19-1.72-.33-2.57-1.49-9.19-3.2-18.35-5-27.4M 8-.35-1.81-.82-3.61-1.07-5.42-.14-1-.86-2.04,.01-3.06,1.27,.16,2.03,.96,2.92,1.56,4.23,2.84,8.41,5.73,12.61,8.6,.83,.43,1.59,1.43,2.61,1.17-1.43-10.43-4.8-20.97-6.97-31.42-.4-1.69-.83-3.38-1.2-5.08-.03-.13,.23-.32,.4-.44,.76-.03,1.6,.85,2.27,1.21,4.88,3.56,9.74,7.13,14.61,10.69,.72,.38,1.4,1.28,2.24,1.23,.1-.03,.24-.13,.24-.2-.02-.64,.03-1.29-.13-1.9-1.13-4.32-2.27-8.64-3.46-12.95-1.58-6.42-4.01-12.75-5.18-19.22,.16-.99,2.27,.92,2.72,1.14,6.11,4.69,12.02,9.64,18.23,14.19,.75,.34,.61-.71,.48-1.14-2.46-8.16-4.94-16.3M 2-7.37-24.49-.68-2.3-1.67-4.54-2.01-6.9-.01-.09,.1-.22,.19-.27,.09-.05,.28-.06,.36-.02,.72,.47,1.48,.91,2.12,1.45,6.15,5.13,12.29,10.28,18.43,15.42,.65,.54,1.31,1.08,1.99,1.6,.06,.05,.28,.02,.39-.02,.1-.05,.23-.17,.21-.25-.14-.74-.25-1.49-.48-2.22-2.76-8.54-5.55-17.09-8.33-25.63-.24-1.17-1.14-2.31-.77-3.48,1.34,.38,2.19,1.48,3.23,2.32,6.68,5.92,13.36,11.84,20.04,17.76,1.25,1.09,3.92,3.8,2.7,.04-2.99-9.18-6.24-18.38-9.09-27.59-.03-1.21,2.07,.9,2.34,1.07,5.8,5.39,11.6,10.78,17.38,16.18,3.15,2.95,6.26,5.92,9.4,8.87,.1M 7,.12,.88,.28,.91-.14-2.67-9.25-5.9-18.34-8.8-27.52-.72-2.43,1.26-.38,2.05,.3,10.5,9.83,20.47,20.04,30.67,30.04,.26,.24,.77-.12,.79-.32-2.17-8.56-5.17-16.93-7.63-25.42-.13-.41-.16-.84-.22-1.26,0-.07,.1-.2,.17-.21,12.48,10.89,23.59,23.86,35.21,35.69,.51,.34,2.73,3.34,3.14,2.3-1.32-7.75-4.16-15.34-6.02-23.03-.14-.53-.31-1.05-.42-1.58-.08-.41-.4-.99,.1-1.21,.64-.29,.86,.38,1.14,.68,14.45,14.93,28.08,30.59,42.33,45.68,.24,.14,.88,.16,.76-.31-1.63-7.97-3.37-15.92-5.17-23.86-.02-.09,.06-.28,.12-.29,.22-.02,.56-.05,.67,.0M 5,.77,.74,1.54,1.49,2.24,2.27,6.74,7.54,13.52,15.04,20.18,22.63,8.97,10.23,17.81,20.53,26.73,30.79,.28,.32,.93,.55,1.03,.38,.1-.17,.24-.37,.22-.55-.91-6.85-1.9-13.7-2.82-20.55-.3-2.98,1.51-.55,2.4,.37,18.22,21.16,36.13,42.55,53.85,64.1,.7,1,1.88,1.88,1.85,3.16-.02,6.57-.04,13.14-.09,19.71,0,.13-.32,.28-.51,.38-.64-.17-1.05-.95-1.52-1.4-16.37-20.18-32.83-40.23-49.74-60.09-.76-.66-1.52-2.3-2.63-2.22-.53,.37-.09,1.25-.09,1.79,.87,6.75,1.75,13.5,2.61,20.24,.02,.19-.11,.39-.2,.58-.08,.16-.73-.1-1.01-.41-2.83-3.27-5.57-6M .61-8.38-9.9-11.87-14-23.85-27.93-36.13-41.7-.77-.65-1.29-1.94-2.42-1.89-.31,.57,.11,1.82,.16,2.53,1.38,7.35,3.32,14.61,4.39,22-1.2,0-1.61-.99-2.37-1.7-9.42-10.51-18.81-21.02-28.25-31.52-3.3-3.67-6.71-7.29-10.07-10.92-.31-.33-.64-.7-1.29-.6,.05-.26-.01-.3-.19-.13l.27,.07Z"/><path class="cls-2" d="M322.27,493.7c.31-.51,.23-1.05,.13-1.58-.38-2.02-.73-4.05-1.16-6.07-1.48-7.01-2.77-14.04-3.91-21.09-.52-3.31-1.34-6.58-1.65-9.93-.13-1.33,1.01-1.06,1.61-.46,5.49,3.64,10.76,7.64,16.48,10.9,.1,.05,.58-.17,.58-.26,0-.96,.02-M 1.94-.15-2.89-.98-5.55-1.64-11.12-2.33-16.7-.78-7.64-2.63-15.53-2.52-23.1,1.03-.28,1.85,.66,2.72,1.07,4.29,2.61,8.58,5.22,12.87,7.83,.7,.32,1.61,1.21,2.36,.63-.32-14.93-2.48-30.1-2.61-45.14-.17-2.76,1.44-1.65,3.02-.8,4.81,2.32,9.41,5.17,14.36,7.18,1.04-.03,.67-1.49,.8-2.2,0-16.38-.37-32.76,.49-49.12,.02-2.38,1.9-1.08,3.25-.62,4.15,1.79,8.28,3.61,12.43,5.39,.78,.19,2.22,1.14,2.85,.41,1.15-14.49,2.08-29.04,3.58-43.52,.72-5.22,.85-10.61,2.03-15.72,.88-.77,2.31,.42,3.3,.51,5.14,1.51,10.13,3.74,15.37,4.83,.64,.04,.9-.71M ,.97-1.22,.76-4.7,1.49-9.4,2.27-14.1,2.17-13.81,4.75-27.53,7.51-41.23,.7-3.94,1.95-7.8,2.35-11.79,.01-.16-.27-.34-.42-.51l-.06,.02c6.36,.36,12.47,2.63,18.71,3.81,3.38,.8,3.33,.35,2.69,3.21-4.61,19.32-8.87,38.72-12.42,58.26-.65,2.96-.75,6.04-1.69,8.93-.54,.84-1.75,.18-2.52,.06-4.17-1.23-8.33-2.48-12.5-3.71-1.19-.13-3.52-1.75-4.2-.25-1.28,7.33-1.93,14.78-2.94,22.16-1.81,12.4-2.36,24.93-3.9,37.34-.04,.24-.68,.5-.97,.4-5.42-1.84-10.61-4.26-16.01-6.15-1.04-.17-1,1.01-1.07,1.72-.24,4.74-.5,9.47-.69,14.21-.36,11.31-.77,22M .62-.58,33.93,.03,3-.03,3.32-.58,3.34-1.46,.05-2.45-.78-3.58-1.29-3.75-1.7-7.43-3.49-11.15-5.24-.67-.19-1.94-1.13-2.32-.14,0,8.08,.44,16.16,.97,24.21,.47,7.42,.94,14.85,1.41,22.27-.12,1.89-2.46-.18-3.3-.41-4.5-2.33-8.81-5.04-13.42-7.14-.12-.04-.52,.16-.58,.3-.13,.29-.17,.63-.14,.94,1.24,11.06,2.25,22.12,4.01,33.12,.38,2.86,1.06,5.74,.97,8.62-.67,.21-1.14,.02-1.58-.25-4.18-2.55-8.35-5.11-12.52-7.66-1.08-.49-2.09-1.72-3.32-1.58-.18,.07-.36,.32-.35,.49,.11,2.38,.57,4.72,.97,7.06,1.19,6.5,2.4,12.99,3.6,19.49,.75,4.05,1M .49,8.09,2.2,12.14,.02,.13-.27,.31-.45,.44-5.27-2.49-10.72-7.18-15.84-10.38-.72-.33-1.78-1.66-2.4-.61,1.28,6.45,2.88,12.93,4.32,19.39,1.3,5.61,2.69,11.21,4.02,16.81,.03,.13-.21,.32-.36,.45-1.2-.06-2.16-1.27-3.18-1.86-4.77-3.5-9.53-7-14.29-10.49-.51-.25-1.04-.94-1.63-.82-.68,.37-.35,1.13-.26,1.74,.88,3.37,1.75,6.75,2.69,10.11,1.96,7.04,3.96,14.07,5.94,21.11,.15,.52,.29,1.05-.04,1.64-1.48-.29-2.5-1.51-3.7-2.33-5.19-4.08-10.38-8.16-15.57-12.24-.57-.44-1.05-1-2.1-1.06,2.55,10.48,6.12,20.75,9.27,31.09,.99,3.74-1.7,.74-3M .01-.15-6.24-5.22-12.46-10.45-18.7-15.67-.36-.3-.63-.71-1.24-.72-.1,0-.29,.09-.29,.14,.02,.53-.04,1.07,.11,1.58,1.13,3.66,2.28,7.31,3.47,10.96,1.91,5.83,3.86,11.65,5.79,17.48,.14,.41,.26,.82-.08,1.26-1.2-.37-2.03-1.33-2.96-2.1-6.42-5.67-12.83-11.35-19.24-17.03-1.25-.89-2.2-2.45-3.72-2.84-.22-.03-.38,.44-.26,.81,.36,1.15,.72,2.3,1.1,3.44,2.66,8.01,5.32,16.02,7.99,24.03,.17,.52,.44,1.02,.17,1.56-.59,.01-.99-.26-1.35-.58-1.79-1.61-3.61-3.2-5.36-4.84-6.02-5.66-12.01-11.35-18.03-17.02-1.31-1.23-2.65-2.44-4-3.64-.12-.11-M .45-.08-.69-.07-.36,.28,0,1.13,.08,1.55,2.74,8.44,5.49,16.88,8.24,25.31,.11,.58,.62,1.31-.09,1.67-.68-.07-1.21-.86-1.75-1.25-10.61-9.87-20.55-20.32-30.99-30.22-.9-.4-.42,.99-.34,1.43,2.43,7.95,4.88,15.89,7.31,23.84,.09,.53,.42,1.42,.14,1.85-1.15,0-1.77-1.2-2.59-1.84-10.78-10.76-21.33-21.68-31.71-32.69-1.4-1.28-2.24-2.97-4.13-3.65,1.84,8.77,4.81,17.28,6.92,26-.15,1.42-2.38-1.36-2.82-1.68-13.86-14.44-27.13-29.27-40.6-43.92-.12-.12-.47-.11-.72-.12-.04,0-.14,.19-.14,.28,.97,8.11,3.92,15.88,4.84,24.01-1.91-.53-2.73-2.34M -4.08-3.6-9.9-11.16-19.82-22.3-29.68-33.49-5.04-5.72-9.95-11.53-14.92-17.29-.55-.51-1.03-1.56-1.91-1.44-.34,.19-.32,.8-.26,1.16,.66,4.71,1.33,9.42,1.99,14.13,.31,2.25,.62,4.5,.89,6.75,.02,.14-.2,.42-.34,.43-.23,.03-.59-.05-.72-.18-.73-.77-1.43-1.56-2.12-2.36-6.54-7.64-13.16-15.25-19.61-22.95-11.25-13.42-22.4-26.9-33.59-40.35-.93-1.23-2.36-2.39-2.31-4.03,0-6.36,0-12.71,0-19.07,0-.44,.37-.82,.62-.66,3.21,2.78,5.49,6.67,8.36,9.85,14.33,17.6,28.83,35.12,43.62,52.48,.6,.71,1.29,1.36,1.96,2.03,.12,.09,.59-.03,.62-.21-.43M -5.7-1.28-11.36-2.01-17.02,0-1.12-1.77-7.48,.89-4.71,14.36,17.01,28.74,33.88,43.59,50.55,.96,.99,1.57,2.17,2.97,2.66-.8-7.27-2.99-14.46-4.28-21.71-.13-1.03-.61-2.15-.07-3.12,.14-.26,.4-.15,.91,.42,4.62,5.17,9.2,10.36,13.86,15.51,8.76,9.53,17.26,19.34,26.23,28.69,.28,.27,.72-.08,.76-.28-.58-2.43-1.17-4.86-1.79-7.29-1.45-5.7-2.92-11.39-4.37-17.09-.12-.45-.48-1.66,.31-1.64,11.76,11.72,22.88,24.26,34.54,36.17,.47,.49,.83,1.13,1.88,1.19-2.28-9.55-5.5-18.83-7.85-28.42,1.45,.23,1.86,1.2,2.84,2.05,8.34,8.46,16.67,16.93,25.M 02,25.38,1.33,1.35,2.78,2.63,4.19,3.93,.06,.06,.27,.05,.38,.02,.1-.03,.25-.15,.24-.21-.18-.84-.33-1.69-.58-2.52-2.5-8.27-5.02-16.53-7.52-24.79-.16-.52-.21-1.06-.29-1.6-.01-.09,.07-.26,.16-.28,1.03-.31,1.77,1.13,2.54,1.66,7.68,7.37,15.35,14.74,23.03,22.1,.92,.67,1.64,2.01,2.88,2.02,.05,0,.18-.19,.16-.28-.81-2.72-1.64-5.44-2.44-8.16-2.18-7.33-4.35-14.66-6.5-22-.06-.19,.06-.41,.1-.61,.92,.09,1.5,.65,2.09,1.27,3.88,3.58,7.74,7.18,11.66,10.74,3.47,3.16,7,6.27,10.51,9.39,.36,.25,.84,.73,1.32,.58,.1-.05,.2-.19,.18-.28-.51M -1.89-1.04-3.78-1.58-5.66-2.37-8.93-5.41-17.8-7.44-26.77,.31-.9,2.1,1.11,2.59,1.38,5.88,5.05,11.74,10.1,17.62,15.15,1,.85,3.63,3.23,2.82,.14-3.07-10.7-5.82-21.45-8.5-32.23-.31-1.03,.76-.89,1.32-.41,2.65,2.15,5.25,4.34,7.91,6.48,3.52,2.83,7.07,5.62,10.62,8.42,.37,.2,1.36,.95,1.54,.26-1.4-7.36-3.45-14.59-5.07-21.9-.93-4.02-1.77-8.06-2.62-12.09-.07-.76-.37-1.96-.08-2.53,.25-.03,.59-.09,.74,0,.93,.62,1.82,1.28,2.7,1.94,4.34,3.23,8.67,6.47,13.02,9.69,.93,.54,1.76,1.6,2.93,1.5,0,.22,.05,.23,.14,.04l-.22,.04Z"/><path clasM s="cls-2" d="M806.08,749.99c.11,4.26-1.22,8.52-1.92,12.68-.13,.63-.22,1.29-1.04,1.8-2.98-.81-5.84-2.15-8.83-2.95-.36-.11-.91,.1-.98,.36-.99,4-1.71,8.06-2.59,12.08-.15,1.06-.48,1.82-1.9,1.31-2.77-.75-5.46-1.93-8.29-2.35-.86,.95-.84,2.29-1.2,3.46-.65,2.97-1.26,5.95-1.92,8.92-.23,.65-.4,1.75-1.29,1.77-1.94,.11-8.92-3.4-9.61-1.24-1.04,4.54-2.69,9.05-3.36,13.61-3.57-.79-7.14-1.59-10.63-2.6,0-.01,0-.03,.02-.04,1.58-4.42,2.34-9.01,3.59-13.54,.09-.37,.76-.68,1.26-.61,2.62,.39,5.18,1.14,7.78,1.68,1.04,.24,1.63,0,1.8-.76,.9-M 4.25,1.79-8.48,2.71-12.74,.66-1.51,7.71,1.23,9.41,1.4,.31,.08,.95-.16,1.01-.37,1.38-4.33,1.5-9.06,2.87-13.34,.16-.15,.49-.34,.66-.29,2.93,.78,5.81,1.68,8.75,2.44,.84,.14,1.19-.67,1.33-1.33,.66-3.83,1.28-7.69,2.03-11.51,.1-.55,.87-.91,1.5-.72,2.99,.82,5.81,2.27,8.84,2.88Z"/><path class="cls-2" d="M811.68,722.48s-.01,.03-.01,.04l-.09-.08s.07,.03,.1,.04Z"/><path class="cls-2" d="M964.37,753.62s.01-.11,.01-.15h.14l-.15,.15Z"/><path class="cls-2" d="M1387.34,675.7c-.03-1.76-2.29-2.36-3.48-3.32-6.16-3.84-12.29-7.72-18.49M -11.52-21.25-13.11-42.81-25.52-64.79-37.54-2.89-1.58-5.81-3.13-8.72-4.69-.56-.3-1.11-.62-1.84-.49-.29,2.49,.64,5.14,.81,7.68,.29,3.62,1.45,7.29,1.18,10.9-.62,.74-2.59-.89-3.35-1.15-10.7-6.01-21.5-11.89-32.42-17.63-15.02-7.77-30.23-15.55-45.74-22.54-.21-.07-.85,.05-.82,.4,1.06,4.78,2.51,9.48,3.78,14.21,.17,.86,.92,2.93-.74,2.4-22.5-10.84-44.94-21.59-68.3-30.65-.64,.73-.18,1.42,.06,2.21,1.32,3.28,2.67,6.55,4.01,9.82,.35,.99,2.1,4.17,.14,3.63-18.64-7.93-37.45-15.41-56.7-21.94-3.19-1.02-1.22,1.25-.59,2.73,1.76,3.37,3.6M 1,6.71,5.34,10.11,.1,.27,.34,.67,.1,.89-.22,.08-.52,.22-.7,.16-4.56-1.58-9.12-3.18-13.67-4.79-11.08-3.94-22.41-7.38-33.8-10.67-.62-.18-1.28-.26-1.93-.36-.09-.02-.3,.12-.3,.19,.03,.3,.01,.65,.18,.91,2.34,3.93,5.62,7.65,7.46,11.73-.22,.1-.51,.28-.69,.23-2.54-.71-5.07-1.43-7.59-2.18-11.23-3.01-23.45-7.28-34.89-8.73-.3,.53,.63,1.22,.83,1.72,2.24,2.94,4.49,5.88,6.73,8.82,.27,.36,.44,.72,.25,1.13-.96,.21-1.83-.06-2.72-.29-11.05-2.77-22.26-5.34-33.55-7.09-.18,0-.74,.36-.53,.64,2.92,3.37,5.96,6.62,8.78,10.06,.06,.08,.07,.2M 7,0,.31-.63,.49-1.5,.2-2.22,.11-8.45-1.85-17.11-2.94-25.7-4.24-1.13-.08-2.47-.34-3.55-.08-.29,.93,.92,1.49,1.41,2.17,2.37,2.34,4.82,4.63,7.15,7.01,.18,.24,.62,.54,.4,.85-.15,.14-.37,.35-.54,.33-3.06-.32-6.14-.62-9.19-1.01-5.7-.6-11.48-1.41-17.2-1.47-.25,.5,.04,.84,.41,1.17,2.77,2.49,5.55,4.98,8.32,7.48,.29,.38,1.11,.84,.99,1.31-.65,.72-1.72,.23-2.57,.27-6.18-.45-12.36-.8-18.56-.88-.65,0-1.46-.2-1.85,.31-.45,.6,.35,.94,.76,1.32,2.79,2.33,5.62,4.64,8.39,6.99,1.68,1.45,.72,1.73-.98,1.65-5.89-.17-11.86-.27-17.7,.42-.4,M .26,.22,.84,.41,1.09,3.1,2.55,6.22,5.08,9.33,7.62,.36,.3,.88,.57,.75,1.05-.15,.58-.83,.44-1.31,.47-5.15,.41-10.49,.46-15.56,1.34-.24,.58,.07,.91,.47,1.22,3.43,2.89,7.1,5.52,10.37,8.59,.21,.2-.04,.74-.37,.79-1.98,.31-3.97,.6-5.94,.93-2.5,.42-4.99,.87-7.49,1.32-.61,.12-.84,.62-.45,.97,3.93,3.41,7.96,6.72,11.9,10.11,.54,.46,1.23,.86,1.38,1.62-1.08,1.29-14.01,2.08-12.7,4.04,4.24,3.74,8.57,7.42,12.7,11.28,.22,.2,.23,.54,.37,.89-3.98,1.15-8.02,1.98-11.69,3.63,3.71,4.23,8.28,7.7,12.28,11.69,.42,.39,.88,.79,.74,1.4-3.8,1.0M 4-7.46,2.93-11.36,3.45-4-3.6-8.11-7.15-12.16-10.71-.43-.37-.82-.85-1.69-.81-2.7,1.87-5.51,3.72-7.9,5.92-.4,.38-1.08,.89-1.65,.67-3.74-2.57-7.16-5.55-10.79-8.26-.65-.38-1.5-1.28-2.31-.94-2.46,2.27-4.08,5.32-6.2,7.91-.27,.36-.65,.69-.38,1.29,4.05,2.89,8,6.43,12.28,9.12,.66-.22,.93-.72,1.28-1.16,1.87-2.41,3.72-4.8,6.05-6.83,.94-.53,1.86,.64,2.57,1.13,3.73,3.29,7.36,6.58,11.12,9.85,3.76-1.71,6.18-4.83,9.84-6.59,1.17,.38,1.68,1.18,2.36,1.83,6.85,6.57,9.23,9.07,11.06,11.54-3.01,2.13-6.03,4.26-9.06,6.39-.43,.31-1.05,.27-1M .41-.09-3.63-3.76-7.31-7.46-11-11.17-.48-.48-.89-1.07-1.96-1.22-2.85,2.32-5.24,5.06-7.83,7.71-1.58-.28-2.36-1.63-3.54-2.55-2.61-2.33-5.22-4.65-7.84-6.97-.44-.39-.86-.82-1.78-.83-1.99,2.42-3.5,5.28-5.27,7.88-.36,.49-.88,1.41-1.63,1.08-3.79-2.7-7.34-5.69-11.03-8.52-.92-.52-1.39,.64-1.74,1.27-1.55,2.74-2.53,5.97-4.43,8.45-.91-.02-1.32-.49-1.82-.83-2.24-1.57-4.46-3.13-6.69-4.69l-.33,14.62c1.51,.86,2.38,2.38,4.27,2.54,1.94-3.3,2.53-7.21,4.54-10.46,.92,.02,1.38,.43,1.85,.81,2.82,2.31,5.7,4.56,8.46,6.94,1.23,1.04,1.88,1.2M 5,2.69-.55,1.53-2.8,2.69-6.01,4.83-8.39,1.12,.28,1.64,.95,2.25,1.5,2.84,2.59,5.65,5.21,8.47,7.81,.44,.4,.84,.84,1.72,.9,1.96-2.9,4.09-5.79,6.16-8.64,.29-.39,.98-.39,1.38-.04,3.74,3.64,7.28,7.48,10.93,11.21,.78,.82,.72,1.05-.04,2.01-2.2,2.47-4.2,5.94-6.58,8.05-.79-.06-1.13-.54-1.53-.97-3.61-3.47-6.53-7.76-10.6-10.65-2.47,2.96-3.83,6.67-6.21,9.7-1.02-.19-1.43-.78-1.94-1.27-2.7-2.55-5.39-5.1-8.09-7.65-.43-.41-.85-.84-1.56-.97-.59,.31-.86,.79-1.09,1.31-1.38,2.98-2.62,6.11-4.18,8.99-.76,.02-1.12-.28-1.49-.59-2.4-2.04-4.M 8-4.08-7.2-6.11-.82-.67-2.62-2.46-3.26-.87-1.2,3.31-2.31,6.64-3.55,9.93-.06,.17-.31,.26-.56,.26l-.05,2.17c.12-.79,.83-1.08,1.6-.44,3.26,2.51,6.03,5.6,9.39,7.93,.67-.41,.9-.91,1.1-1.43,1.27-3.04,2.16-6.29,3.73-9.2,.62-.47,1.47,.31,1.93,.69,2.67,2.57,5.3,5.17,7.95,7.75,.41,.4,.76,.88,1.67,.88,2-3.23,3.21-6.79,5.33-10.1,.42,.13,.9,.15,1.11,.35,3.24,3.12,6.09,6.57,9.14,9.87,.45,.41,1.04,1.3,1.74,.85,2.02-2.47,3.53-5.32,5.33-7.96,.31-.48,.61-.96,1.31-1.17,.8,.26,1.17,.86,1.6,1.39,3.24,3.89,6.44,7.92,9.73,11.76,.78-.05,1M .09-.39,1.4-.75,1.53-1.78,3.05-3.55,4.6-5.32,.84-.81,2.28-2.97,3.42-1.54,3.61,4.64,6.93,9.48,10.4,14.22,.29,.39,.6,.7,1.38,.73,1.53-1.22,3.09-2.56,4.8-3.77,1.48-1.04,2.47-2.58,4.59-2.98,1.37,1.08,2.04,2.5,2.9,3.82,2.65,4.11,5.25,8.25,7.88,12.38,.36,.56,.59,1.21,1.34,1.53,1.05-.11,1.67-.72,2.42-1.14,2.93-1.42,5.5-3.63,8.6-4.55,.01-.63-.47-1.12-.79-1.64-3.61-5.66-7.04-11.48-11.14-16.82-.19-.24-.76-.31-1.07-.13-2.83,1.65-5.64,3.32-8.47,4.96-.51,.29-.94,.78-1.67,.65-.69-.29-.94-.81-1.27-1.27-3.32-4.71-6.82-9.3-10.36-13M .85-.59-.77-1.18-.84-1.9-.26-2.7,2.09-5.22,4.4-8.03,6.34-.16,.09-.61,.07-.73-.04-4.17-4.42-7.9-9.24-11.89-13.81-.07-.08-.03-.21-.05-.41,2.38-2.66,5.15-5.12,8.23-7.37,.16-.12,.48-.1,.73-.15,.71,.17,1.01,.69,1.38,1.12,3.9,4.22,7.24,8.9,11.34,12.91,1.53-.06,2.18-1.16,3.23-1.77,2.32-1.28,4.44-2.87,6.82-4.01,1.15-.32,1.76,1.16,2.44,1.83,3.34,4.42,6.66,8.84,10,13.27,.34,.45,.57,.98,1.46,1.19,3.36-.24,6.87-.78,10.28-.83,.48,0,1.51-.2,1.37-.82-3.44-5.67-7.84-10.76-11.65-16.21-.3-.42-.02-.89,.55-.96,3.71-.58,7.5-.51,11.24-.M 81,.17-.02,.43-.36,.37-.48-3.58-5.36-8.12-10.13-12.06-15.26-.52-.65-.1-1.21,.95-1.29,3.89-.22,7.8,.02,11.69-.23,.33-.02,.61-.5,.43-.75-4.22-5.3-8.95-10.21-13.35-15.37l-.24-.15c-4.44,.02-8.85,.58-13.25,1.01-.56,.06-.83,.63-.51,1.01,3.46,3.87,7.02,7.64,10.51,11.47,.73,1.01,2.05,1.74,1.88,3.12-4.02,.61-8.09,.65-11.88,1.64-.29,.7,.22,1.1,.58,1.52,3.46,4.11,6.95,8.2,10.4,12.32,.52,.61,1.2,1.18,1.23,2.05-2.43,.87-5.21,.92-7.77,1.41-1.33,.15-2.53,.78-4.08,.64-3.65-4.03-7.21-8.27-10.79-12.37-.7-.92-1.82-1.56-1.88-2.8,3.09-M .98,6.15-1.6,9.28-2.36,.62-.15,1.29-.28,1.65-.95-3.78-4.46-8.02-8.6-12.06-12.85-.33-.35-.64-.7-.45-1.31,3.62-1.27,7.67-1.57,11.52-2.39,.34-.85-.57-1.36-1.04-1.97-3.88-3.86-7.91-7.59-11.71-11.53-.37-.77,1-.97,1.54-1.08,3.71-.54,7.42-1.07,11.07-1.59,.42-.45,.25-.83-.11-1.18-3.64-3.46-7.29-6.92-10.94-10.38-.6-.58-1.22-1.14-1.78-1.75-.11-.12,.02-.38,.05-.66,4.67-1.03,9.53-1.16,14.25-1.48,.46-.49,.31-.87-.07-1.22-4.08-3.73-8.11-7.53-12.28-11.16-.44-.46-1.24-1.21-.17-1.52,4.57-.27,9.13-.52,13.7-.79,2.72-.05,2.92-.31,.84-M 2.2-2.62-2.33-5.26-4.62-7.88-6.94-.45-.4-.83-.84-1.18-1.3-.06-.08,.19-.39,.38-.48,6.26-.42,12.64,.05,18.92,.4,.08-.27,.27-.52,.18-.64-.42-.54-.88-1.08-1.41-1.56-2.82-2.61-5.81-5.06-8.57-7.74-.13-.14-.17-.42-.09-.58,.08-.15,.38-.32,.59-.32,7,.09,13.94,.9,20.86,1.83,.34,.03,.9,.08,1.16-.1,.04-.2,.12-.47-.01-.59-2.8-2.76-5.63-5.5-8.44-8.25-.49-.48-1.54-.94-1.16-1.56,.52-.83,1.68-.29,2.52-.21,8.13,.67,16.09,2.66,24.18,3.4,.05-.82-.59-1.27-1.08-1.77-2.32-2.38-4.66-4.75-6.99-7.12-.33-.34-.66-.68-.97-1.03-.29-.33-.72-.71-M .4-1.1,.13-.16,.76-.14,1.14-.07,8.01,1.41,16.03,2.82,23.91,4.7,1.81,.43,3.64,.77,5.47,1.12,.15,.03,.4-.18,.56-.31,.06-.06,.06-.23,0-.3-1.73-2.06-3.46-4.11-5.19-6.16-1.21-1.43-2.42-2.85-3.6-4.29-.1-.19,.12-.72,.49-.63,10.66,2.12,21.21,4.88,31.6,7.85,1.33,.19,2.99,1.25,4.22,.6-2.36-4.12-6.13-7.66-8.34-11.72,.19-.11,.46-.29,.64-.25,1.31,.26,2.61,.52,3.88,.87,12.08,3.36,24,7.06,35.77,11.06,.73,.2,1.48,.73,2.19,.24-1.43-3.63-4.43-6.89-6.47-10.33-.44-.67-.84-1.35-1.21-2.04-.08-.15-.03-.45,.1-.55,.16-.11,.52-.15,.72-.09,1M 5.38,5,30.74,10.32,45.63,16.48,.83,.34,1.71,.61,2.58,.9,.16,.02,.48-.22,.46-.39-1.84-4.63-4.7-8.89-6.75-13.45-.42-1.42,3.46,.49,4.01,.57,18.39,6.76,36.09,15.38,53.86,22.65,.29-.08,.33-.31,.23-.55-1.09-2.77-2.17-5.54-3.26-8.31-.8-2.05-1.61-4.11-2.39-6.17-.06-.15,.12-.38,.24-.56,.03-.05,.25-.06,.36-.02,23.12,9.44,44.84,21.3,67.05,32.32,.81,.25,.53-.81,.49-1.24-1.42-5.15-2.93-10.27-4.19-15.46,0-.2,.53-.63,.81-.51,5.48,2.45,10.69,5.42,16.03,8.14,21.38,11,42.1,23.26,62.83,35.25,.14,.05,.59-.12,.61-.22,.08-.41,.12-.85,.0M 6-1.27-.65-4.49-1.34-8.98-1.99-13.47,.07-.96-1.09-4.33,.81-3.74,30.73,17.43,60.74,36.15,90.03,55.83,1.01,.5,1.78,1.64,2.97,1.38,.19-.08,.37-.32,.38-.49,.11-6.57,.03-13.14,.04-19.71Zm-368.62-88.28s.07-.03,.11-.04c0,.19-.03,.2-.11,.04Z"/><path class="cls-2" d="M660.77,307.26c-1.02-1.05,.27-2.26,.68-3.31,6.82-12.72,14.57-25.08,22.03-37.51-.42-.1-.84-.32-1.09-.23-2.57,.93-5.13,1.9-7.67,2.89-3.63,1.41-7.25,2.85-10.87,4.29-.35,.14-.8,.35-1.03,0-.15-.23-.1-.64,.05-.89,3.58-6.03,7.09-12.09,10.8-18.07,5.55-9.2,11.74-18.09,1M 7.11-27.4-1.33-.5-2.56,.39-3.87,.64-5.4,1.66-10.8,3.34-16.2,5-.61,.1-1.68,.69-1.95-.11,10.34-18.1,22.78-35.2,34.13-52.74,.23-1.07-2.94,.09-3.55,.04-6.25,1.32-12.48,2.67-18.73,3.99-.43,.11-1.04-.16-.88-.67,12.49-20.08,26.27-39.43,40.16-58.63,.46-.64,.83-1.34,1.2-2.02,.13-.24-.05-.45-.37-.47-.53-.03-1.07-.07-1.59-.01-6.94,.78-13.86,1.65-20.8,2.39-1.68,.37-2.61-.24-1.26-1.71,11.54-16.6,23.19-33.11,35.28-49.36,4.45-6.03,9.06-11.98,13.6-17.97,.21-.28,.47-.53,.63-.83,.6-1.22,2.02-1.31,3.37-1.27,7.41-.01,14.82-.03,22.24-.M 03,.66,0,1.33,.09,1.97,.21,.15,.03,.38,.39,.31,.51-17.37,22.13-35.49,43.81-51.64,66.73-.13,.21,.32,.69,.64,.67,.94-.04,1.89-.04,2.81-.14,6.81-.71,13.6-1.58,20.42-2.18,.21-.02,.54,.11,.64,.26,.1,.15,.08,.43-.03,.59-1.51,2.04-3.02,4.08-4.59,6.08-13.05,16.73-25.6,33.56-37.62,50.89-.27,.46-.95,1.38-.11,1.58,7.22-1.25,14.35-2.9,21.53-4.36,2.54-.38,.93,1.06,.2,2.2-3.46,4.74-6.94,9.48-10.4,14.22-8.13,11.59-16.97,23.01-23.97,35.06,.23,.08,.52,.21,.73,.16,1.53-.41,3.05-.85,4.56-1.3,4.92-1.47,9.83-2.94,14.75-4.41,.63-.09,1.6M 3-.7,2.06,.03-9.05,13.86-19.07,27.47-27.77,41.55-.45,.96-1.49,1.83-1.38,2.9,.03,.21,.6,.25,1.1,.06,5.72-2.18,11.44-4.33,17.17-6.48,.73-.27,1.5-.48,2.25-.7,.15-.02,.46,.27,.42,.43-7.76,12.42-16.29,24.43-23.73,37.06-1.75,2.93,.23,1.91,2.16,1,5.17-2.31,10.34-4.63,15.52-6.93,.45-.2,.99-.26,1.5-.35,.07-.01,.28,.15,.27,.21-.67,1.9-2.06,3.5-3.07,5.25-5.4,8.31-10.38,16.79-15.43,25.25-1.7,3.06-3.15,4.82,1.78,2.25,4.8-2.39,9.58-4.81,14.39-7.2,.44-.22,.97-.33,1.47-.46,.06-.02,.3,.15,.28,.2-1.7,4-4.58,7.51-6.62,11.36-3.34,5.76M -6.6,11.55-9.86,17.34-.15,.26-.05,.61-.03,.92,0,.06,.2,.17,.25,.15,7.11-3.51,13.83-7.88,20.81-11.68,1-.44,2.36-1.44,3.41-1.52,.1,.18,.27,.42,.2,.57-.46,.89-1,1.76-1.49,2.64-3.98,7.07-7.97,14.13-11.93,21.21-.26,.47-.7,.93-.51,1.5,.03,.08,.22,.19,.26,.18,8.45-4.23,16.26-9.65,24.61-14.09,.16,.26,.41,.47,.35,.59-.32,.7-.68,1.4-1.08,2.07-3.75,6.33-6.96,12.84-10.37,19.28-.21,.39-.44,.79,.04,1.3,7.88-4.63,15.87-9.21,23.95-13.65,1.96-1.01,1.74-.05,.98,1.43-3.26,5.9-6.67,11.72-9.63,17.78-.13,.25-.12,.47,.19,.54,1.37,.03,2.4M 8-1.22,3.71-1.74,5.91-3.39,11.82-6.79,17.75-10.15,1.42-.8,2.94-1.49,4.45-2.19,.12-.06,.44,.14,.73,.25-3.23,5.64-6,11.51-8.95,17.29-.11,.22,0,.4,.31,.49,8.94-4.02,17.43-9.5,26.45-13.59,.65-.22,1.22-.17,.88,.79-2.56,4.85-5.33,9.61-7.56,14.62-.09,1.73,3.25-.76,4.01-.95,6.73-3.37,13.45-6.77,20.36-9.91,1.4-.64,2.84-1.22,4.27-1.81,.3-.13,.54-.04,.66,.21-1.47,4.79-4.91,9.27-6.76,14.07-.06,.15,.14,.38,.27,.54,.83,.02,1.75-.56,2.54-.82,10.12-4.51,20.59-8.48,30.91-12.67,.93-.24,1.99-1,2.93-.48,.07,.03,.1,.2,.06,.27-.35,.7-.6M 9,1.4-1.07,2.08-1.79,3.25-3.6,6.49-5.39,9.75-.16,.47-.61,1.03-.38,1.51,.13,.24,.37,.33,.66,.23,1.36-.46,2.74-.89,4.08-1.39,10.51-3.89,21.05-7.71,31.81-11.15,1.13-.21,2.29-1.1,3.4-.46-1.97,4.34-4.65,8.45-6.58,12.8,.89,.61,1.74,.02,2.66-.17,13.66-4.28,27.49-8.43,41.48-11.74l-.07-.12c-2.13,3.8-4.09,7.69-6.08,11.56-.2,.58-.96,1.75,.02,1.9,15.7-3.68,31.45-7.15,47.38-10.16l-.09-.08c-1.61,3.68-3.54,7.21-5.35,10.79-.33,.84-1.66,2.59,.1,2.6,14.11-2.36,28.3-4.29,42.51-6.03,2.79-.34,5.61-.55,8.42-.78,.3-.02,.64,.19,1.05,.33-1M .21,3.07-2.69,5.89-4.07,8.87-2,4.21-2.07,3.85,3.5,3.56,10.85-1.02,21.73-1.5,32.61-1.9,6.73-.31,13.45-.59,20.18-.52,.62,.08,1.8-.16,1.96,.63-1.2,4.1-3.38,7.9-4.64,11.99-.17,1.6,3.73,.79,4.83,1.05,21.34,.64,42.78,1.17,63.98,3.77l-.13-.08c-1.69,4.73-2.86,9.71-4.85,14.29l.13-.09c-23.16-2.39-46.38-4.12-69.67-4.52l.11,.09c3.13-7.83,4.43-11.51,4.58-13.01,.01-.1-.08-.2-.16-.4-18.81-.34-37.67,.56-56.45,1.73-.66-.08-2.7,.41-2.64-.69,1.31-3.63,2.89-7.17,4.32-10.75,.56-1.86-4.5-.61-5.51-.71-15.34,1.55-30.6,3.66-45.82,6.05-.52,M .08-1.08-.38-.94-.77,1.24-3.32,2.86-6.5,4.26-9.75,1.37-2.83-1.53-1.57-3.12-1.44-13.43,2.7-26.87,5.32-40.15,8.66-.77,.03-3.02,1.03-3.09-.14,1.26-3.67,3.19-7.08,4.75-10.62,.37-1.32-.54-1.29-1.85-.9-12.84,3.44-25.75,7.01-38.29,11.22-.59,.2-1.28,.25-1.92,.35-.07,.01-.27-.16-.25-.23,.92-3.73,3.08-7.1,4.51-10.67,1.42-2.49-.84-1.58-2.25-1.13-5.44,1.87-10.92,3.68-16.31,5.63-6.13,2.22-12.2,4.55-18.3,6.84-.63,.29-2.07,.8-1.9-.36,1.56-3.56,3.34-7.04,4.97-10.58,.13-.63,1.06-1.67,0-1.9-11.54,3.97-22.74,9.28-33.92,14.08-.45-.46-M .42-.87-.24-1.29,1.68-4.09,3.51-8.12,5.09-12.25,.02-.07-.1-.19-.2-.26-.69-.23-1.76,.56-2.46,.77-7.89,3.73-15.53,7.76-23.19,11.78-1.28,.68-3.7,2.18-2.43-.63,1.85-4.38,4.05-8.63,5.66-13.09-.32-.76-1.46,.15-1.97,.31-5.11,2.8-10.24,5.59-15.3,8.44-3.26,1.61-6.06,4.15-9.45,5.34-.36-.47-.11-.87,.06-1.27,2.09-4.77,4.19-9.54,6.27-14.32,.85-2.51-2.72,.34-3.53,.68-6.56,3.96-13.12,7.92-19.67,11.88-.72,.37-1.53,1.16-2.36,1.05-.15-.07-.26-.4-.19-.56,2.34-5.53,5.11-10.88,7.64-16.33,.76-1.51,.53-1.99-1.08-1.17-7.47,4.2-14.43,8.95-M 21.6,13.58-.48,.31-1.02,.95-1.65,.54-.6-.39-.02-1.02,.19-1.49,2.44-5.36,4.75-10.76,7.51-16.02,.83-1.92,2.49-4.34-.93-2.22-6.13,3.87-12.25,7.76-18.37,11.64-1.05,.67-2.11,1.34-3.19,1.98-.14,.08-.47,0-.69-.05-.07-.01-.15-.19-.12-.27,.25-.61,.49-1.23,.79-1.83,3.19-6.52,6.39-13.03,9.58-19.54,.92-1.96,.68-2.39-1.27-1.24-5.18,3.27-10.35,6.56-15.52,9.84-1.9,1.2-3.79,2.41-5.71,3.6-.18,.07-.86,.03-.79-.34,3.65-9.07,9-17.47,13.08-26.39,.04-.15-.31-.41-.49-.33-.7,.32-1.42,.61-2.07,.99-5.04,2.88-10.01,5.86-15.06,8.71-1.47,.46-.M 23-1.64-.02-2.22,4.49-9.46,9.56-18.75,14.69-27.99,.16-.63-.18-1.03-1.08-.53-5.77,2.96-11.45,6.06-17.2,9.07-.15,.08-.48-.04-.71-.11-.29-.43,.28-1.04,.42-1.48,5.62-10.54,11.28-20.98,17.5-31.24,.49-1.01,2.46-3.34-.17-2.48-5.94,2.95-12.25,5.31-17.96,8.65h.05Z"/><path class="cls-2" d="M657.28,1058.23c8.98-4.12,17.66-8.8,26.41-13.35,.55-.29,1.07-.66,1.81-.44l-.09-.07c.34,.65,.03,1.26-.23,1.86-1.38,3.13-2.77,6.25-4.17,9.38-.51,1.2-1.31,2.32-1.2,3.67-.3,.04-.32,.08-.07,.14v-.2c.55,.16,1.02-.01,1.47-.27,2.09-1.17,4.18-2.34,M 6.29-3.48,5.67-3.07,11.33-6.15,16.68-9.57,.82-.53,1.89-1.2,2.8-.49l.06-.08c-.78,.64-.99,1.51-1.34,2.31-1.38,3.15-2.71,6.31-4.07,9.46-1.96,4.49-3.11,5.98,2.25,2.59,6.12-3.7,12.24-7.4,18.36-11.11,.98-.43,2.24-1.86,3.3-1.51,.26,.31,.13,.61,0,.91-2.35,5.16-4.87,10.26-7.28,15.4-.2,.67-.94,1.46-.29,2.05,.04,.05,.29,.04,.38-.01,8.21-4.6,15.88-9.97,23.89-14.88,.17,.26,.39,.45,.35,.58-.3,.82-.63,1.64-.99,2.45-2.48,5.57-5,11.14-7.85,16.6-.2,.38-.53,.75-.32,1.2,.04,.08,.22,.2,.26,.18,.47-.19,.98-.35,1.39-.61,6.65-4.21,13.29-8M .43,19.93-12.65,.84-.43,1.72-1.25,2.64-1.39,.62,.75-.46,1.87-.7,2.68-2.95,6.01-5.9,12.01-8.85,18.02-.39,.8-.73,1.61-1.07,2.43-.03,.08,.06,.2,.11,.29,.11,.21,.37,.3,.64,.13,3.11-1.88,6.24-3.75,9.3-5.68,4.33-2.73,8.61-5.52,12.93-8.27,.13-.08,.47,.01,.7,.06,.3,.3-.16,.83-.25,1.18-3.63,7.92-7.74,15.62-11.8,23.33-.36,.69-.66,1.4-.97,2.11-.03,.08,.04,.25,.11,.27,1.1,.31,2.06-.77,3.03-1.16,4.25-2.47,8.48-4.95,12.73-7.42,.75-.44,1.39-1.04,2.39-1.13l-.06-.09c.41,.88-.12,1.62-.5,2.42-4.09,8.61-8.57,17.09-13.29,25.49-.52,1.08M -1.51,2.04-1.41,3.29l-.12-.07c1.58,.05,2.83-1.06,4.2-1.69,4.13-2.21,8.25-4.43,12.38-6.63,.75-.28,1.6-.99,2.41-.88,.09,.07,.21,.2,.18,.27-.31,.71-.61,1.42-.97,2.11-5.43,10.28-11.03,20.5-17.09,30.56-.41,.67-.76,1.37-1.07,2.08-.07,.15,.1,.38,.22,.56,5.95-1.94,11.63-5.35,17.46-7.83,.58-.27,1.14-.58,1.86-.35l-.09-.06c.2,.56-.05,1.05-.33,1.55-4.01,7.06-7.95,14.14-12.05,21.16-3.19,5.46-6.6,10.84-9.9,16.26-.23,.38-.37,.8-.52,1.21-.02,.06,.11,.19,.21,.25,.83,.19,1.75-.44,2.57-.64,4.96-1.94,9.91-3.89,14.86-5.84,.95-.24,1.91-M 1.11,2.9-.64,.08,.03,.15,.19,.12,.26-.23,.5-.45,1.01-.73,1.5-8.29,15.12-18.76,29.66-27.1,44.62,.07,.08,.23,.2,.3,.18,.9-.21,1.81-.42,2.68-.69,5.4-1.66,10.8-3.34,16.2-5,.93-.2,1.79-.74,2.68-.11-10.61,18.11-22.71,35.48-34.36,52.94,.81,.47,1.46,.34,2.11,.2,6.37-1.37,12.73-2.77,19.1-4.14,.67-.1,2.3-.56,2.11,.48-9.1,14.78-19.09,28.96-29.05,43.24-3.64,5.16-7.38,10.27-11.06,15.41-.46,.65-.83,1.34-1.2,2.02-.25,.58,.8,.51,1.14,.53,6.94-.77,13.86-1.62,20.8-2.36,1.94,0,3.71-.53,1.91,1.96-16.21,23.36-32.68,46.57-50.21,69-8.32,M .47-16.69,.07-25.03,.19-.68,0-1.83,.05-1.97-.65,16.6-21.39,34.08-42.35,49.78-64.21,.68-.92,1.31-1.88,1.94-2.82,.17-.25-.21-.74-.53-.72-1.87,.12-3.74,.37-5.61,.56-4.8,.55-9.59,1.12-14.39,1.65-.86-.07-4.46,.89-3.99-.61,12.06-15.94,24.37-31.75,35.83-47.98,2.07-2.9,4.1-5.82,6.12-8.74,.32-.46,.55-.97,.75-1.48,.03-.08-.3-.37-.47-.37-6.8,1.15-13.54,2.84-20.32,4.17-.71,.03-1.67,.45-2.33,.12-.09-.18-.21-.43-.13-.56,.49-.76,1.03-1.51,1.58-2.25,11.62-16.01,23.47-31.86,33.9-48.46-.75-.5-1.48-.12-2.26,.08-6.55,1.74-13.08,4.4-19M .66,5.61-.64-.61,.38-1.38,.67-1.96,7.31-10.06,14.05-20.36,20.87-30.63,2.59-3.9,5.02-7.86,7.51-11.79,.15-.23,.05-.44-.23-.54-1.92-.01-3.67,1.27-5.5,1.8-4.89,1.77-9.71,3.79-14.66,5.39-.24,.04-.94-.12-.73-.46,8.27-12.7,16.96-25.14,24.33-38.27,.06-.13-.14-.37-.27-.53-.04-.05-.27-.04-.37,0-5.94,2.49-11.76,5.23-17.67,7.8-.45,.2-.99,.29-1.49,.4-.07,.01-.29-.15-.28-.21,.57-1.92,2.04-3.49,3.02-5.24,5.95-9.42,11.84-18.78,17.15-28.5,.01-.33-.37-.64-.76-.39-5.88,2.8-11.66,5.81-17.5,8.68-.32,.08-1.15,.42-1.35-.01,4.39-8.02,9.55M -15.66,13.85-23.68,.93-1.67,1.82-3.36,2.69-5.05,.27-.52,.16-1.06-.26-1.52,.07,.05,.13,.09,.2,.13-.22,.06-.24,0-.06-.17-7.03,4.98-15.08,8.67-22.5,13.12-2.84,1.46-2.09,.13-.96-1.71,4.14-7.37,8.27-14.73,12.4-22.1,.15-.4,.75-1.16,.41-1.48-.75-.31-1.36,.34-2,.64-6.4,3.76-12.8,7.53-19.21,11.29-.98,.57-1.96,1.14-2.98,1.67-.16,.08-.55,.05-.69-.05-.41-.72,.74-1.9,1.02-2.63,3.59-6.03,6.64-12.24,9.87-18.4,1.31-2.54-.57-1.62-1.93-.69-6.85,4.37-14.19,8.2-21.34,12.24-2.41,1.22-2.06,.19-1.09-1.64,3.13-5.71,6.48-11.33,9.32-17.18,.M 12-.25-.06-.59-.12-1.06-7.5,4.15-14.74,8.42-22.18,12.63-1.09,.62-2.26,1.17-3.4,1.75-.29,.14-.53,.09-.65-.11-.24-.49,.33-1.02,.48-1.5,2.62-5.07,5.25-10.14,7.87-15.22,.21-.4,.41-.8-.04-1.3-6.91,3.43-13.62,7.26-20.48,10.82-1.91,1.01-3.88,1.94-5.83,2.9-.46,.23-.91,.21-1.08,.03-.3-.32-.09-.61,.06-.89,1.58-2.97,3.2-5.93,4.76-8.91,.94-1.79,1.82-3.59,2.67-5.4,.12-.25-.08-.59-.13-.9-8.32,3.41-16.12,7.89-24.31,11.65-1.48,.6-3.08,1.57-4.63,1.82-.12-.17-.3-.39-.24-.54,2.08-4.45,4.44-8.78,6.63-13.18,.2-.4,.27-.83-.21-1.3-11.87,M 4.75-23.78,10.46-35.92,14.33-.1-.18-.27-.42-.2-.56,2-3.89,4.25-7.67,6.31-11.53,.31-.58,.46-1.22,.66-1.84,.02-.06-.16-.22-.26-.22-13.02,4.02-25.62,9.68-38.89,13.29-.19,.04-.47-.12-.67-.22-.18-.56,.55-1.52,.76-2.11,1.76-3.49,3.9-6.82,5.39-10.43,.06-.15-.14-.38-.27-.55-13.58,3.73-27.11,8.33-40.96,11.68-.76,.19-.75,.21-2-.14,2.11-3.83,4.02-7.75,5.98-11.64,.38-.75-.53-.87-1.06-.89-11.63,2.69-23.23,5.53-35,7.78-3.53,.62-7.03,1.67-10.62,1.88-1.19-.25-.03-1.55,.18-2.21,1.63-3.3,3.51-6.49,4.88-9.91,.18-.75-.86-.73-1.35-.66-M 9.64,1.55-19.27,3.17-28.96,4.38-4.52,.59-9.04,1.16-13.57,1.7-2.86,.15-5.86,1.04-8.68,.57-.17-.87,.38-1.53,.69-2.22,1.1-2.43,2.28-4.84,3.41-7.25,.41-1.15,2.2-3.35-.28-3.28-12.35,.86-24.7,1.8-37.08,2.13-6.06,.2-12.11,.6-18.18,.52-.8-.01-1.61-.06-2.4-.15-.16-.02-.41-.32-.38-.46,1.09-4.23,3.71-8.04,4.58-12.32,.05-.26-.11-.44-.42-.48-3.86-.47-7.79-.31-11.68-.44-18.92-.58-38-1.17-56.75-3.58l.15,.14c1.91-4.66,3.2-9.56,4.88-14.31l-.12,.09c23.14,2.58,46.4,3.98,69.68,4.52l-.11-.09c-1.54,4.12-3.08,8.25-4.61,12.37-.21,.56,.26,M 1.04,1.01,1.08,10.64,.2,21.29-.28,31.92-.56,8.47-.36,16.92-1.04,25.4-1.35,.37-.02,.81,.36,.75,.62-.98,3.81-2.92,7.37-4.23,11.09-.11,.28,.27,.69,.61,.7,16.96-1.07,33.81-3.92,50.62-6.36,.63-.09,1.06,.28,.89,.74-1.15,3.12-2.65,6.1-3.96,9.15-.29,.77-1.34,2.34,.16,2.4,14.94-2.45,29.74-5.92,44.47-9.4,.45-.03,1.17-.2,1.41,.19-1.22,3.98-3.51,7.65-5,11.56-.12,.28,.36,.61,.76,.52,8.74-2.04,17.32-4.73,25.93-7.18,5.06-1.45,9.98-3.28,15.04-4.69,1.16-.03,.58,1.14,.31,1.8-1.42,3.14-2.85,6.27-4.26,9.41-.08,.34-.53,1.34,.02,1.42,4.M 33-.91,8.5-2.71,12.7-4.07,8.61-2.93,17.04-6.73,25.69-9.29,.62,.51,.15,1.2-.07,1.79-1.62,3.42-3.25,6.84-4.89,10.26-.2,.41-.33,.82,.12,1.22,11.7-4.03,22.99-9.58,34.27-14.16,.11,.05,.24,.18,.23,.25-.15,.63-.26,1.28-.51,1.88-1.41,3.37-2.87,6.72-4.3,10.08-.26,.61-.52,1.23-.09,1.85-.07-.09-.14-.17-.2-.25l.2,.19Z"/><path class="cls-2" d="M555.62,1219.39c-.99-1.21,.96-2.1,1.6-2.98,7.4-7.4,14.81-14.8,22.21-22.2,.42-.58,1.48-1.05,1.14-1.84-.02-.06-.25-.13-.34-.1-11.26,3.15-22.38,6.82-33.6,10.15-.88,.27-1.78,.5-2.68,.71-.15,.M 03-.41-.17-.56-.29,6.26-7.42,13.83-14.29,20.52-21.53,.3-.45,2.03-1.94,.98-2.07-4.34,1.04-8.56,2.56-12.81,3.88-7.85,2.57-15.83,4.85-23.83,7.1-.63,.18-1.25,.4-1.91,.04,.05-.81,.8-1.33,1.36-1.91,5.72-6.37,12.2-12.27,17.55-18.9-.56-.28-1.09-.24-1.6-.09-3.04,.88-6.08,1.75-9.1,2.65-9.46,2.82-19.07,5.29-28.63,7.88-.57,.2-1.39,.33-1.91,.1-.7-.45,1.48-2.09,1.78-2.63,4.26-4.71,8.52-9.42,12.76-14.15,.61-.68,1.42-1.29,1.55-2.2-.78-.32-1.55,0-2.31,.18-11.2,3.09-22.59,5.7-33.9,8.5-2.3,.57-4.6,1.22-7.02,1.43-.2,.02-.45-.15-.63-.2M 7,0-.97,1.21-1.69,1.73-2.47,4.1-4.81,8.44-9.42,12.37-14.36,.2-1.29-3-.06-3.73-.03-14.45,2.97-28.85,6.51-43.43,8.67-1.12-.1,.51-1.67,.75-2.14,3.29-4.07,6.61-8.12,9.9-12.19,1.78-2.11,1.78-2.79-1.19-2.26-12.44,2.39-25.04,4.15-37.6,6.06-3.57,.54-7.17,.93-10.76,1.38-.25,.03-.72-.05-.74-.12-.22-.8,.4-1.41,.85-2.01,3.25-4.47,6.69-8.81,9.8-13.37,.16-.24-.21-.71-.56-.68-5.9,.35-11.73,1.31-17.6,1.93-13.24,1.27-26.49,2.51-39.77,3.36l.06,.11c2.63-4.5,5.53-8.83,8.38-13.21,2.08-3.14,1.69-3.19-2.22-3.03-20.4,.87-40.81,1.6-61.24,1M .27l.09,.1c2.32-5.29,5.41-10.25,7.79-15.52,.2-.4-.19-.92-.72-.95-2.01-.11-4.01-.28-6.02-.29-22.53-.46-45.03-2.07-67.48-4.03l.14,.11c2.14-5.86,4.22-11.74,6.44-17.58l-.11,.09c25.19,3.46,50.75,4.12,76.13,5.85l-.15-.09c-1.9,4.75-4.43,9.24-6.62,13.86-.29,.65-.91,1.68,.16,1.94,18.02,.81,36.11,.21,54.14-.29,3.23-.1,6.46-.23,9.69-.34,.71-.02,1.16,.58,.86,1.13-2.46,4.2-5.06,8.33-7.59,12.49-.52,.8-1.08,1.9,.57,1.86,13.42-.78,26.85-1.79,40.2-3.24,5.34-.53,10.67-1.33,16.03-1.56,.35,0,.79,.43,.65,.65-3.02,4.86-6.62,9.35-9.71,14M .16-.17,.26,.18,.7,.54,.66,2.27-.24,4.55-.42,6.79-.75,14.85-2,29.6-4.63,44.39-6.94,.35-.04,.76,.42,.59,.66-3.19,4.67-6.86,9-10.25,13.53-.41,.53-.92,1.04-.92,1.79,7.26-.63,14.43-2.7,21.62-3.97,8.07-1.69,16.18-3.3,24.13-5.34,.59-.07,1.4-.36,1.94-.09,.1,.16,.25,.4,.17,.53-.43,.67-.9,1.32-1.41,1.96-3.61,4.54-7.43,8.94-10.92,13.58-.06,.08-.09,.27-.03,.31,.73,.62,1.74,.04,2.57-.05,12.66-2.98,25.22-6.2,37.68-9.67,1.43-.22,2.9-1.18,4.31-.58-4.22,5.45-8.91,10.5-13.32,15.79-.45,.53-.84,1.08-1.24,1.64-.05,.07,0,.22,.06,.29,.7M 5,.34,1.87-.2,2.68-.3,13.02-3.22,25.81-7.97,38.65-11.08,.09,.16,.23,.41,.14,.52-.55,.74-1.13,1.46-1.75,2.16-4.35,4.93-8.71,9.85-13.06,14.78-.54,.61-1,1.27-1.47,1.91-.04,.06,0,.2,.05,.25,.63,.35,1.61-.13,2.28-.23,12.24-3.68,24.43-8.35,36.67-11.62,.29,.12,.2,.51-.35,1.12-5.98,6.96-12.51,13.47-18.56,20.36-.07,1.12,1.45,.3,2.06,.2,11.82-3.89,23.84-7.26,35.29-11.96l-.12,.07c.34,.37,.53,.77,.18,1.18-.76,.89-1.53,1.77-2.33,2.63-6.31,7.15-13.68,13.84-19.43,21.26,.07,.08,.25,.19,.33,.17,.89-.24,1.78-.48,2.64-.77,9.65-3.28,1M 9.29-6.57,28.93-9.85,1.09-.23,2.23-1.08,3.34-.65,.09,.52-.76,1.19-1.05,1.66-7.85,8.81-15.99,17.7-24.73,25.86,.3,0,.33,.04,.11,.12l-.03-.22c1.44,.79,3.09-.36,4.54-.67,8.33-2.76,16.65-5.54,24.97-8.31,.62-.21,1.2-.5,1.9-.17-7.52,9.73-16.62,18.51-25.08,27.66-.9,.93-1.73,1.9-2.58,2.87-.05,.06,0,.21,.07,.29,.07,.08,.23,.18,.31,.17,.78-.17,1.56-.33,2.31-.56,7.03-2.16,14.06-4.34,21.09-6.5,1.38-.42,2.77-.83,4.17-1.21,.15-.04,.41,.14,.58,.26,.05,.04,0,.23-.06,.3-10.07,11.44-20.92,22.19-31.46,33.21-1.87,2.01-1.86,2.37,.99,1.7M 1,7.29-1.9,14.58-3.82,21.87-5.73,1.34-.21,2.57-1.03,3.93-.57-7.36,8.35-15.49,16.02-23.29,23.98-5.46,5.71-11.72,10.95-16.8,16.89-.01,.63,1.63,.15,2.11,.09,8.22-1.68,16.46-3.28,24.73-4.75,1.07,.32,.42,.82-.13,1.42-2.86,2.86-5.7,5.73-8.59,8.57-9.11,8.96-18.39,17.76-27.68,26.55-3.57,3.37-7.21,6.69-10.81,10.03-.25,.33-.83,.67-.63,1.11,.52,.42,1.58,.11,2.25,.16,7.47-.45,15-1.72,22.46-1.67,.83,.58-.81,1.53-1.16,2.07-17.91,17.01-35.86,33.97-54.34,50.41-2.48,2.24-2.01,2.08-5.87,2.09-6.74,.01-13.47,.02-20.21,.02-2.4-.1-4.33,M .1-1.28-2.38,16.8-14.2,33.43-28.68,49.65-43.37,2.15-1.93,4.15-3.96,6.2-5.95,.21-.33-.3-.52-.54-.66-8.51,.91-17.07,1.93-25.6,2.78-.22,.02-.59-.07-.68-.2-.19-.79,.95-1.27,1.4-1.82,8.86-7.97,17.79-15.88,26.57-23.91,6.29-5.76,12.38-11.66,18.54-17.5,.46-.58,1.41-1.12,.99-1.92,0,.23,.08,.27,.28,.14l-.26-.05c-9.22,1.37-18.33,3.41-27.51,5.03-.88-.17-.68-.54-.11-1.1,13.42-12.44,27.78-24.76,39.62-38.08-.07-.08-.24-.18-.33-.16-.91,.17-1.83,.34-2.73,.56-8.88,2.13-17.71,4.48-26.61,6.49-.18,.04-.44-.12-.64-.22,0-.6,1.11-1.32,1.5M 1-1.83,11.31-10.7,22.99-20.99,33.63-32.35-1.62-.39-2.8,.4-4.31,.74-8.86,2.54-17.72,5.07-26.59,7.6-1.1,.28-2.38,.81-3.43,.12l.04,.03c10.14-8.99,19.5-18.92,29.36-28.24,.38-.46,1.23-.96,1.07-1.59-.11-.13-.49-.22-.69-.16-1.02,.27-2.02,.58-3.02,.88-7.02,2.16-14.03,4.33-21.06,6.47-3.41,1.21-7.22,1.72-10.44,3.32h.05Z"/><path class="cls-2" d="M376.96,212.56c-.59,.32-1.22,.43-1.91,.24-3.81-1.08-7.62-2.14-11.42-3.23-2.81-.68-5.53-1.9-8.39-2.25-.22,0-.57,.16-.63,.31-3.76,20.55-5.39,41.55-7.33,62.36-.06,2.49-1.66,1.24-3.14,.79M -5.27-2.16-10.54-4.34-15.81-6.5-.59-.23-1.68-.78-2.04-.01-1.63,18.12-1.7,36.38-2.24,54.57,.04,1.96-1.48,1.06-2.57,.51-4.35-2.35-8.7-4.72-13.04-7.08-1.1-.32-4.24-3.26-4.77-1.41-.21,16.36,.99,32.75,1.46,49.06-.97,.38-1.69-.33-2.48-.75-4.69-3.07-9.36-6.16-14.04-9.24-1.15-.57-2.24-1.94-3.56-1.9-.19,.06-.44,.3-.43,.45,.25,4.09,.48,8.17,.82,12.26,.77,9.13,1.75,18.26,2.64,27.38-.09,.94,.94,5-.21,4.93-.36-.1-.76-.18-1.03-.38-6-4.28-11.73-8.88-17.56-13.38-.48-.33-.91-1.01-1.64-.64-.62,.31-.3,.97-.28,1.48,.03,.65,.1,1.29,.19M ,1.93,1.43,12.55,3.63,25.04,5.16,37.56-1.12,.12-1.8-.79-2.63-1.36-5.58-4.68-11.14-9.37-16.72-14.05-.7-.42-2.6-2.8-2.99-1.15,1.64,12.44,4.59,24.77,6.22,37.19-2.11-.55-3.3-2.49-4.97-3.76-5.49-5.04-10.96-10.08-16.45-15.12-.78-.58-1.35-1.58-2.45-1.46,1.44,10.54,4.19,21.04,6.07,31.57,.19,.96,.34,1.92,.46,2.88,.02,.13-.28,.3-.47,.41-.94-.28-1.91-1.63-2.73-2.27-6.71-6.61-13.41-13.22-20.11-19.83-.88-.7-1.44-1.84-2.69-1.85,.85,7.37,3.03,14.65,4.38,21.98,.61,2.87,1.25,5.73,1.86,8.59,.11,.52,.24,1.06-.09,1.56-.03,.05-.29,.07-M .38,.03-1.95-1.11-3.27-3.11-4.91-4.63-6.84-7.21-13.68-14.42-20.52-21.63-.79-.64-1.37-1.91-2.48-1.96-.13,.01-.33,.31-.3,.46,.22,1.28,.47,2.56,.74,3.83,1.23,5.73,2.47,11.46,3.7,17.19,.55,2.55,1.1,5.09,1.62,7.64,.06,.28-.11,.6-.21,.89-.55,.19-1.34-.8-1.74-1.13-9.82-10.66-19.46-21.48-29.37-32.06-.12-.12-.48-.1-.74-.12-.03,0-.13,.19-.12,.28,1.36,9.1,3.48,18.08,5.22,27.11-.3,1.4-1.77-.61-2.18-1.04-11.39-12.38-21.85-25.95-33.44-37.95-1.08-.23-.21,2.39-.31,2.95,1.04,7.47,3.02,15.02,3.51,22.46-1.46-.35-2.11-1.82-3.09-2.82-1M 0.26-12.26-20.52-24.53-30.79-36.79-1.95-2.32-3.91-4.64-5.9-6.94-.1-.12-.48-.1-.73-.11-.45,.42-.18,1.27-.17,1.83,.68,6.22,1.37,12.44,2.04,18.67,.07,.64,.03,1.28,.02,1.93-.09,.36-.77,.17-.92,.07-14.72-17.71-28.96-35.82-43.51-53.67-.76-.96-1.73-1.94-1.56-3.24-.02-6.25-.05-12.5-.06-18.74,0-.3,.16-.61,.29-.9,.02-.05,.32-.11,.37-.07,13.69,15.93,26.51,32.72,39.95,48.91,.89,.84,1.61,2.54,2.94,2.5-.15-5.27-1.03-10.5-1.46-15.76-.23-2.25-.46-4.51-.67-6.76,.27-1.08,1-.43,1.51,.1,11.32,13.51,22.64,27.02,33.98,40.53,.6,.55,2.9,3M .82,3.2,2.29-1.06-8.42-2.96-16.94-3.56-25.32,1.02-.11,1.51,1,2.17,1.6,9.73,11.12,19.46,22.24,29.2,33.36,.48,.5,3.01,3.83,2.99,1.58-1.57-8.74-3.24-17.46-4.72-26.21-.07-.41,.07-.84,.13-1.25,0-.02,.3-.06,.38,0,9.92,9.99,19.11,20.86,28.81,31.13,.3,.32,.51,.76,1.13,.81,.09,0,.28-.1,.28-.16-.18-3.99-1.36-7.87-1.99-11.81-1.15-6.07-2.29-12.14-3.43-18.2-.24-1.15,.95-.8,1.33-.31,3.2,3.33,6.41,6.66,9.62,9.98,4.78,4.94,9.58,9.88,14.38,14.8,.58,.59,1.23,1.13,1.87,1.68,.12,.08,.58-.02,.63-.18-1.01-9.08-3.56-18.05-4.78-27.15-.31-M 1.81-.59-3.63-.84-5.45,.37-1.46,1.7,.35,2.36,.82,6.43,6.23,12.85,12.47,19.28,18.7,.85,.83,1.78,1.61,2.71,2.38,.11,.09,.49-.01,.87-.03-.91-8.79-3-17.47-4.18-26.24-.42-3.2-1.25-6.38-1.34-9.61,.44-.82,2.11,.99,2.64,1.33,5.49,4.89,10.95,9.8,16.43,14.7,2.8,2.21,5.28,5.88,4.09-.63-1.12-7.59-2.28-15.18-3.2-22.79-.34-4.38-1.59-8.8-1.39-13.16,.7-.63,1.83,.69,2.46,1.05,4.85,3.9,9.67,7.81,14.52,11.7,1.33,1.07,2.71,2.09,4.1,3.11,.13,.1,.49,.03,.73-.02,.08-.01,.18-.18,.17-.28-.22-2.47-.43-4.93-.68-7.4-.96-8.9-1.86-17.81-2.61-26M .73-.24-2.79-.41-5.59-.62-8.39-.03-.44,.21-.76,.49-.79,.45-.05,.75,.15,1.04,.35,3.85,2.69,7.69,5.41,11.56,8.09,2.34,1.62,4.72,3.21,7.1,4.79,.16,.11,.53,.13,.74,.06,.76-.35,.39-1.39,.46-2.06-.29-5.06-.79-10.1-.85-15.17-.38-9.58-.95-19.16-.99-28.75,.13-.88-.28-2.49,1.04-2.35,5.78,3.08,11.33,6.59,17.03,9.83,.86,.23,2.3,1.78,2.98,.68,.17-18.2,.43-36.4,1.1-54.59l-.14,.05c6.28,2.66,12.5,5.46,18.76,8.17,1.13,.35,3.11,1.59,3.06-.53,1.41-20.5,3.06-41,5.82-61.38l-.13,.12c6.79,2.07,13.6,4.07,20.4,6.1,.63,.19,1.27,.36,2.08,.01M ,2.87-19.84,6.37-39.63,10.07-59.34,.7-3.72,1.53-7.43,2.31-11.14,.2-.95,.71-1.2,2.01-1.04,5.96,.81,11.9,1.78,17.84,2.66,1.32,.2,2.63,.46,3.93,.73,.79,.33,.4,1.43,.35,2.09-3.26,14.48-6.46,28.99-9.21,43.56-1.82,9.13-3.38,18.29-4.97,27.45-.08,.43-.11,.85,.18,1.25h0Z"/><path class="cls-2" d="M1063.89,1226.8c5.16,.76,10.15,2.88,15.25,4.12,1.61,.13,7.1,3.06,7.29,.51,2.55-17.85,4.63-35.76,6.39-53.71,.46-2.96-.04-6.11,.96-8.96,.66-.62,1.77,.13,2.5,.31,5.28,2.16,10.54,4.33,15.82,6.49,1.08,.44,2.25,.95,2.43-.71,1.31-18.26,1.2M 5-36.6,2.11-54.87,1.07-.4,1.97,.4,2.92,.8,4.79,2.61,9.57,5.23,14.35,7.84,.75,.42,2.41,1.67,2.89,.52,.37-16.35-.91-32.78-1.37-49.07,.67-.64,1.68,.31,2.33,.6,5.63,3.69,11.22,7.41,16.85,11.1,.35,.22,1.04,.29,1.12,.12-.02-14.7-2.56-29.65-3.59-44.41,.42-1.61,2.45,.59,3.19,.97,4.97,3.8,9.92,7.61,14.88,11.41,.81,.46,1.54,1.42,2.48,1.5,.31-.02,.48-.16,.47-.43-.05-3.13-.54-6.23-.95-9.33-1.22-10.39-3.07-20.78-4.33-31.12,.99-.32,1.73,.71,2.49,1.19,5.67,4.76,11.33,9.53,17,14.29,.65,.54,1.35,1.05,2.04,1.55,.06,.05,.26,0,.38-.04M ,.1-.03,.25-.11,.25-.17,0-.64,.08-1.29-.03-1.92-.93-5.55-1.89-11.09-2.85-16.64-.96-6.29-2.46-12.59-3.21-18.85,1.25-.11,2.08,1.23,3.03,1.9,5.85,5.36,11.68,10.72,17.53,16.08,.99,.69,1.92,2.27,3.19,2.22,.3-.37,.11-1.07,.09-1.54-2.04-10.21-4.09-20.41-6.13-30.61-.02-.76-.64-1.92,.22-2.35,.07-.05,.3-.03,.36,.03,8.43,7.58,16.02,16.05,24.43,23.66,.11,.06,.59-.08,.63-.23,0-.64,.06-1.29-.07-1.92-2.01-9.77-4.12-19.54-6.23-29.29-.04-.2,.03-.42,.08-.63,.08-.18,.49-.22,.63-.13,5.32,4.89,10.02,10.42,15.09,15.57,3.91,4.12,7.82,8.2M 4,11.75,12.34,.22,.23,.63,.36,.96,.52,.34,.02,.39-.49,.36-.74-2.05-9.66-4.18-19.3-6.19-28.97,.23-1.47,1.79,.5,2.22,.94,9.13,10.01,18.25,20.02,27.39,30.03,1.43,1.42,3.06,3.8,2.51-.16-1.47-7.88-3.03-15.75-4.67-23.61-.1-.52-.04-1.06-.03-1.59,0-.07,.13-.16,.23-.19,.12-.03,.33-.05,.39,0,.67,.67,1.36,1.33,1.97,2.04,9.39,10.79,18.76,21.58,28.14,32.37,1.38,1.59,2.76,3.19,4.18,4.76,.19,.21,.67,.26,1.21,.46-1.02-7.64-2.43-14.98-3.68-22.55-.14-.85-.13-1.71-.18-2.57,0-.1,.1-.28,.14-.28,.24,0,.59,0,.71,.11,.75,.76,1.47,1.54,2.1M 4,2.34,11.45,13.7,22.9,27.41,34.35,41.11,.75,.89,1.53,1.77,2.34,2.63,.1,.11,.46,.09,.7,.08,.06,0,.17-.17,.17-.26-.32-6.89-1.18-13.74-1.83-20.61-.11-3,1.45-.75,2.41,.31,6.99,8.57,13.99,17.14,20.93,25.73,6.72,8.32,13.38,16.68,20.07,25.02,.75,1.09,2.01,2.05,2.06,3.44-.07,6.66,.32,13.39-.16,20.02-.09,.1-.54,.19-.67,.08-.71-.78-1.43-1.56-2.09-2.37-7.38-9.14-14.73-18.29-22.12-27.43-5.75-6.87-11.1-14.13-17.17-20.73-.12-.06-.58,.08-.62,.23-.03,.64-.1,1.29-.04,1.92,.68,6.76,1.41,13.51,1.92,20.28,0,.09-.1,.26-.17,.26-.7,.15-M 1.09-.32-1.49-.79-11.5-13.82-23.08-27.56-34.63-41.35-.52-.62-1.13-1.19-1.72-1.78-.13-.1-.57-.04-.65,.12,.72,8.31,2.67,16.64,3.45,25-.05,.56-.68,.54-1,.22-10.44-11.75-20.71-23.65-31.09-35.45-.59-.62-1.13-1.75-2.2-1.72,.2,5.34,1.93,11.06,2.72,16.51,.64,3.73,1.46,7.43,1.76,11.2,.03,.27-.17,.41-.48,.39-9.47-9.07-18-19.65-27.14-29.23-.91-.76-1.75-2.36-2.99-2.39-.32,.47-.03,1.32-.01,1.89,1.77,9.47,3.67,18.93,5.35,28.42,.01,.58-.73,.54-1.03,.26-8.07-8.2-15.99-16.53-24.01-24.78-4.75-5.23-2.48,.34-2.11,3.51,1.49,7.99,2.99,1M 5.97,4.47,23.96,.45,3,1.26,5.75-1.91,2.49-6.68-6.49-13.35-12.98-20.04-19.46-.68-.66-1.45-1.27-2.19-1.89-.14-.08-.58,.03-.66,.15,0,4.41,1.4,8.74,1.96,13.12,1.12,6.72,2.23,13.45,3.28,20.18,.15,.95,.48,1.91,.11,2.87-1.26-.02-2.03-1.28-2.99-1.97-5.57-4.98-11.13-9.97-16.71-14.94-.9-.8-1.87-1.54-2.82-2.3-.06-.05-.26-.02-.37,0-.11,.03-.27,.1-.28,.16-.06,.42-.16,.85-.1,1.27,.34,2.68,.72,5.35,1.1,8.03,1.34,9.84,2.98,19.66,3.81,29.56-.04,.46-.63,.86-1.05,.47-.87-.67-1.77-1.32-2.62-2.01-5.85-4.61-11.46-9.51-17.5-13.88-.29-.06M -.93-.03-.85,.4,.76,10.86,2.24,21.67,3.05,32.53,.29,3.33,.54,6.66,.79,10-.37,1.41-1.95-.09-2.63-.5-5.78-4.05-11.54-8.14-17.41-12.06-2.42-1.51-1.06,3.73-1.22,4.86,.82,14.29,1.64,28.63,1.67,42.94-.51,1.14-1.81-.11-2.54-.42-5.11-2.99-10.21-5.99-15.33-8.97-1.06-.59-1.92-1.35-3.24-.94-.21,18.23-.12,36.44-1.09,54.65l.14-.04c-6.28-2.65-12.49-5.45-18.74-8.17-1.79-.73-3.14-1.45-3.06,1.24-1.45,20.22-2.77,40.64-5.85,60.67l.11-.12c-6.81-2.02-13.6-4.07-20.4-6.1-1.43-.45-1.98-.03-2.15,1.43-1.8,14.03-4.47,27.96-6.71,41.93-1.56,9.M 58-4.1,19.14-5.44,28.69l.13-.1c-7.97-1.35-16.78-2.68-24.44-3.65,.22-4.7,1.97-9.3,2.78-13.96,1.19-5.39,2.4-10.78,3.5-16.19,2.92-14.95,5.86-29.89,8.28-44.93l-.14,.13Z"/><path class="cls-2" d="M1191.44,947.12c.49-.58,.5-1.22,.36-1.86-.33-1.48-.67-2.97-1.06-4.44-2.25-8.42-4.52-16.84-6.78-25.25-.09-.42-.28-1.51,.46-1.16,8.23,7.23,15.71,15.33,23.67,22.88,1.25,1.09,2.03,2.47,3.68,3.05-1.83-9.69-5.14-19.21-7.47-28.84-.14-.52-.18-1.05-.24-1.58,0-.08,.07-.22,.15-.24,.81,.05,1.66,1.18,2.3,1.67,5.88,6.03,11.76,12.06,17.61,18.1M 1,3.38,3.49,6.71,7.01,10.08,10.51,.1,.1,.45,.07,.68,.05,.28-.19,.07-.62,.01-.91-1.96-8.48-4.28-16.88-6.51-25.3-.21-.95-.54-1.94,0-2.83l-.05,.09c11.02,10.93,21.27,22.57,31.72,33.94,.91,.77,1.68,2.36,2.93,2.4-.04,.29,.03,.34,.22,.14l-.31-.07c.4-.86,.1-1.71-.09-2.55-1.69-7.19-3.42-14.38-5.13-21.57-.17-.73-.26-1.48-.37-2.22-.01-.1,.08-.29,.12-.29,.25,0,.6-.02,.72,.1,.93,.92,1.86,1.84,2.71,2.8,8.67,9.74,17.33,19.48,25.97,29.23,2.88,3.25,5.69,6.54,8.55,9.8,.47,.4,.98,1.28,1.63,1.31,.24-.2,.48-.44,.34-.75-1.43-7.34-2.87-1M 4.67-4.28-22.01-.77-4.35,1.5-1.14,2.89,.33,13.21,15.21,26.25,30.52,39.03,45.97,.74,.9,1.5,1.79,2.26,2.67,.4,.47,.8,.62,.95,.38,.11-.18,.29-.37,.27-.55-.46-5.81-1.26-11.58-1.96-17.37-.17-1.39-.38-2.78-.53-4.17-.02-.15,.19-.42,.34-.44,.23-.03,.59,.04,.72,.18,.72,.78,1.4,1.58,2.07,2.39,4.92,5.92,9.88,11.82,14.73,17.77,10.73,13.17,21.44,26.35,32.12,39.55,1.38,1.32,1.66,2.84,1.64,4.52-.18,6.02,.19,12.07-.16,18.08-.03,.14-.33,.27-.54,.36-.05,.02-.22-.08-.31-.14-15.99-18.66-30.47-39.54-47.3-57.22-.32,.22-.2,.84-.21,1.19,.M 74,7.06,1.88,14.13,2.27,21.21-.34,.03-.71,.14-.8,.06-.6-.57-1.19-1.16-1.71-1.78-6.13-7.34-12.21-14.71-18.37-22.04-6.38-7.6-12.83-15.16-19.26-22.73-.68-.8-1.38-1.59-2.11-2.36-.11-.12-.47-.11-.71-.12,.64,7.93,2.81,16.22,4.03,24.25,.05,.29-.1,.6-.19,.89-.27,.1-.82-.16-1.01-.37-11.2-12.79-22.38-25.59-33.58-38.38-.77-.88-1.6-1.73-2.44-2.57-.12-.12-.47-.09-.72-.14l-.03-.18,.13,.12c-.37,.97-.05,1.92,.16,2.86,1.78,8.15,3.67,16.22,5.3,24.42-1.14,.22-1.6-.85-2.34-1.47-6.47-7.11-12.9-14.25-19.4-21.35-3.49-3.81-7.08-7.55-10.64M -11.32-.39-.41-.71-.93-1.52-.88l.09-.06c.99,7.93,3.68,15.64,5.33,23.49,.41,1.69,.75,3.39,1.11,5.09,.1,.45-.11,.81-.39,.75-9.36-8.41-17.72-18.48-26.75-27.44-.79-.62-1.41-1.88-2.54-1.78-.05,0-.16,.19-.14,.29,2.17,10.09,4.73,20.09,7.07,30.14,.13,2.17-2.65-1.09-3.15-1.57-7.48-7.35-14.83-14.83-22.39-22.1-.43-.6-1.61-.68-1.28,.35,2.37,10.84,5.39,21.92,7.25,32.7-.91,.17-1.44-.74-2.08-1.21-4.02-3.77-8.02-7.56-12.05-11.32-2.8-2.62-5.63-5.22-8.46-7.83-.44-.39-.94-.91-1.59-.87-.12,.01-.3,.32-.27,.47,.27,1.38,.59,2.76,.88,4.14M ,2.08,9.87,4.29,19.72,6.16,29.63,.06,.62,.41,1.38-.34,1.72-.06,.04-.28,.02-.34-.03-.75-.62-1.5-1.24-2.23-1.87-6.29-5.29-12.22-11.05-18.74-16.05-.74-.16-.64,.69-.55,1.22,2.28,12.45,4.79,24.88,6.52,37.41-1.19,.32-2.23-1.09-3.2-1.67-4.78-3.8-9.53-7.61-14.31-11.42-.86-.68-1.76-1.33-2.67-1.97-.15-.1-.49-.06-.74-.03-.08,0-.2,.17-.19,.26,.74,7.52,2.34,14.94,3.16,22.46,.67,5.25,1.34,10.5,1.99,15.75,.12,.96,.09,1.93,.12,2.9,.03,.41-.68,.39-.87,.34-5.6-3.65-10.93-7.68-16.43-11.48-.83-.45-1.63-1.37-2.66-1.11,.46,8.07,1.7,16.3M 1,2.11,24.47,.55,6.98,1.31,13.96,1.49,20.97,0,.17-.18,.41-.37,.49-1.22,.17-2.25-1.08-3.31-1.56-4.36-2.71-8.72-5.43-13.09-8.13-1.01-.53-2.86-2.01-2.88,.17,.44,16.47,1.27,32.95,.91,49.43-.01,.28-.58,.58-.86,.45-5.59-2.52-10.97-5.47-16.47-8.17-3.22-1.88-2.47,.74-2.61,2.92-.47,17.87-1.29,35.78-2.88,53.58-.44,.82-1.74,.27-2.44,.03-3.87-1.52-7.73-3.06-11.6-4.57-2.1-.63-4.09-2.01-6.31-1.92-2.91,22.13-5.02,44.49-9.27,66.46l.14-.13c-7.2-2.18-14.57-4.29-21.94-5.82l.06,.09c4.81-21.94,7.7-44.32,10.76-66.58,.24-2.43,2.95-.66,4.M 31-.3,4.29,1.55,8.58,3.11,12.87,4.66,.81,.23,2.24,1.13,2.83,.23,1.18-6.69,1.37-13.51,2.08-20.26,.67-12.04,1.77-24.08,2.04-36.14,.1-.77-.16-2.23,1.06-2.04,5.87,2.27,11.38,5.37,17.19,7.78,1.14,.28,1.11-.81,1.18-1.58,.05-8.07,.45-16.15,.2-24.23-.26-8.29-.3-16.58-.42-24.87-.09-2.16,1.85-.76,2.89-.25,5.1,2.78,10.01,5.92,15.22,8.49,.56,.12,.9-.75,.83-1.21-.22-3.76-.47-7.53-.71-11.29-.48-6.12-.76-12.26-1.27-18.38-.25-5.25-1.5-10.51-1.35-15.75,1.21-.27,2.11,.75,3.11,1.26,4.26,2.81,8.51,5.63,12.77,8.44,.78,.36,2.9,2.45,3.25M ,.88-.62-6.98-1.51-13.95-2.48-20.89-.87-6.95-2.34-13.88-2.89-20.84,0-.09,.08-.25,.15-.25,.92-.23,1.63,.55,2.35,.98,5.46,4,10.89,8,16.27,12.1,.8,.35,1.36,.19,1.15-.92-2.06-12.84-4.87-25.6-6.91-38.41,1.54,.24,2.36,1.31,3.53,2.15,5.21,4.21,10.42,8.42,15.64,12.62,.54,.44,.98,1.07,1.95,1,.23-1.39-.44-3-.61-4.44-2.11-10.62-4.97-21.14-6.88-31.78,.37-.88,1.89,.76,2.37,1.03,5.67,4.9,11.32,9.82,16.99,14.72,1.07,.71,1.9,2.16,3.25,2.18v.14l-.1-.08c.34-.86,.06-1.72-.14-2.55-2.57-10.44-5.21-20.87-7.77-31.32,.03-.66,1.16-.22,1.4,M .11,7.89,7.2,15.93,14.26,23.34,21.83-.11-.24-.07-.29,.14-.13l-.28,.08Z"/><path class="cls-2" d="M171.16,461.61c10.66,11.81,21.24,23.67,32.27,35.16,.51,.38,1.44,1.01,1.21-.24-1.88-7.82-3.77-15.64-5.65-23.46-.38-1.58-.72-3.18-1.04-4.77-.03-.14,.19-.44,.31-.44,.79,0,1.21,.76,1.71,1.24,9.1,9.62,18.46,19.02,27.4,28.78,.01-.25,.07-.28,.17-.1l-.28,.03c1.05-1.03,.12-2.51-.01-3.74-1.99-9.4-4.99-18.84-6.47-28.22,.59,0,.97,.29,1.31,.63,2.27,2.28,4.52,4.56,6.81,6.82,5.68,5.61,11.39,11.2,17.08,16.81,.41,.4,.79,.84,1.53,.88-1.66M -11.04-5.5-22.18-7.25-33.37,.35-1.04,2.77,1.77,3.34,2.12,6.24,5.8,12.46,11.61,18.69,17.42,.64,.46,1.26,1.34,2.04,1.47,.25-.17,.57-.38,.43-.72-1.16-5.3-2.35-10.6-3.48-15.91-1.22-5.73-2.39-11.47-3.55-17.21-.58-3.85,1.1-1.65,2.81-.37,5.66,4.91,11.31,9.84,16.97,14.75,.64,.42,1.38,1.32,2.14,1.36,.16-.13,.38-.31,.36-.45-.53-2.98-1.11-5.96-1.65-8.95-1.66-9.83-3.88-19.62-5.02-29.51,1.6,.14,2.51,1.46,3.74,2.31,4.87,3.87,9.74,7.75,14.62,11.62,.8,.5,1.53,1.47,2.58,1.31,.06,0,.16-.18,.15-.28-.9-8.05-2.54-16.01-3.45-24.06-.6-5.M 36-1.51-10.7-1.9-16.08,0-.48-.41-1.13,.48-1.37,.58-.16,.96,.29,1.33,.55,4.54,3.21,9.06,6.45,13.6,9.66,1.54,.91,2.75,2.37,4.64,2.51-.83-10.12-1.9-20.21-2.73-30.34-.37-4.62-.65-9.25-.96-13.88,0-.57-.24-1.43,.32-1.8,.99-.29,1.85,.73,2.69,1.11,4.37,2.71,8.72,5.43,13.09,8.13,.82,.32,3.03,2.34,3.53,1.12,.13-5.69-.27-11.42-.45-17.11-.44-11.09-.63-22.19-.41-33.28,.01-.27,.62-.5,.94-.35,5.66,2.67,11.2,5.58,16.82,8.34,2.47,1.26,2.05-.33,2.18-2.18,.16-10.34,.77-20.67,1.33-31.01,.54-7.84,.69-15.74,1.73-23.54,.75-.93,2.28,.16,3M .21,.38,4.35,1.71,8.69,3.44,13.04,5.15,1.08,.42,2.14,.92,3.36,1.02,.19,.02,.54-.15,.6-.29,.16-.4,.25-.83,.3-1.26,2.58-21.86,4.79-43.93,9.24-65.47-.02,.32-.03,.69,.38,.82,1.23,.4,2.47,.77,3.73,1.11,5.17,1.39,10.35,2.75,15.52,4.14,.53,.14,1.03,.17,1.53-.04,0,.01-.07-.09-.07-.09-.75,7.59-2.86,15.1-3.82,22.7-.56,3.63-1.23,7.25-1.84,10.88-1.86,11.08-3.15,22.25-4.76,33.37-.23,2.58-3.25,.42-4.67,.16-4.79-1.71-9.58-3.44-14.37-5.16-1.6-.34-1.28,2.85-1.56,3.88-1.49,18.3-3.07,36.56-3.7,54.92-1.46,.21-2.48-.57-3.73-1.11-4.31-2M .01-8.61-4.02-12.91-6.02-.64-.29-1.95-1.04-2.41-.26-.77,16.67-.05,33.39,.06,50.07,.13,2.56-1.45,1.28-2.84,.66-4.52-2.54-9.01-5.11-13.52-7.66-1.31-.71-2.66-1.57-2.55,.74,.72,14.96,2.19,29.88,3.24,44.81-.57,.75-1.65-.29-2.26-.55-4.28-2.8-8.54-5.61-12.8-8.41-1.32-.74-2.34-2.02-3.96-2.02,.93,13.64,3.5,27.25,5.23,40.85,.01,.61,.35,1.86-.57,1.86-5.85-3.61-11.1-8.17-16.74-12.13-.71-.43-2.7-2.18-2.55-.28,1.37,8.11,2.72,16.23,4.31,24.3,.87,4.58,1.75,9.15,2.62,13.72-.33,1.49-3.12-1.43-3.79-1.8-5.54-4.4-10.95-8.94-16.55-13.26M -.2-.09-.9-.18-.91,.23,1.7,9.39,3.97,18.67,6.01,28,.51,2.54,1.39,5.04,1.63,7.63-.02,.21-.5,.61-.77,.42-.6-.43-1.21-.86-1.76-1.33-5.49-4.74-10.97-9.5-16.46-14.24-.91-.79-1.84-1.57-2.8-2.33-.13-.11-.48-.04-.88-.05,1.9,10.87,5.33,21.53,7.78,32.31,.98,3.38-1.76,.64-2.81-.27-6.44-5.95-12.85-11.9-19.29-17.85-.58-.36-1.99-2.28-2.54-1.47,1.55,9.25,4.85,18.3,6.95,27.49,.15,.8,1.86,4.59,.31,4.3-9.13-8.04-17.41-17.01-26.27-25.35-.14-.09-.88-.14-.84,.26,2.23,9.43,4.95,18.75,7.48,28.11,.06,.52,.45,1.54,.07,1.87-.24-.01-.57-.01-M .7-.13-9.27-9.03-18.16-18.47-27.01-27.82-.89-.72-1.53-2.11-2.78-2.12-.3,.55,.13,1.84,.21,2.51,2.06,8.74,4.93,17.41,6.59,26.18-.73-.07-1.06-.41-1.39-.76-2.62-2.74-5.28-5.45-7.84-8.22-7.37-7.97-14.7-15.96-22.05-23.94-1.16-1-2.15-2.92-3.6-3.35-1.01,.07,.47,3.77,.49,4.58,1.59,7.39,3.96,14.81,5.13,22.2-.22,0-.56,.08-.65-.01-.71-.64-1.42-1.29-2.04-1.99-11.84-13.36-23.76-26.64-35.51-40.08-.42-.33-.85-1.09-1.46-.93-.43,.15-.22,1.1-.22,1.47,1.49,7.85,3.14,15.54,4.5,23.43-1.63-.18-2.18-1.68-3.23-2.69-8.83-10.31-17.69-20.6-26M .49-30.92-4.47-5.25-8.83-10.56-13.26-15.84-.86-.78-1.4-2.19-2.7-2.21,.19,6.13,1.46,12.21,2.06,18.32,.59,4.84,.34,5.63-3.03,1.32-15.81-19.27-31.72-38.44-47.34-57.86-.85-1.04-1.23-2.09-1.22-3.33,.04-6.14,0-12.28-.01-18.42-.02-1.26,.95-.6,1.39-.2,14.57,18.15,29.33,36.13,43.99,54.2,1.14,1.14,1.84,2.94,3.52,3.33-.3-7.25-1.6-14.64-2.2-21.94-.04-.41-.04-.87,.79-.93,12.95,15.46,25.77,31.02,39,46.34,.76,.88,1.57,1.74,2.4,2.59,.11,.11,.45,.09,.68,.08,.05,0,.15-.19,.13-.29-1-6.09-2.12-12.15-3.19-18.22-.11-1.88-2.64-9.9,1.21-5M .06,8.31,9.55,16.61,19.1,24.94,28.64,3.16,3.62,6.39,7.2,9.62,10.79,.21,.24,.62,.37,.95,.53,.33,0,.35-.5,.32-.75-1.77-7.95-3.6-15.88-5.26-23.85-.24-1.15-.68-2.33,.06-3.49l-.16-.05Z"/><path class="cls-2" d="M745.07,937.02c-2.31-.08-4.64-.14-6.97-.2,1.64-1.44,3.23-2.95,4.92-4.35,.16-.13,.47-.16,.72-.18,.32-.02,.5,.14,.55,.39,.26,1.44,.52,2.89,.78,4.34Z"/><path class="cls-2" d="M802.31,915.76l-.2,9.02c-4.71,4.85-8.91,10.13-13.76,14.86-.61,.5-1.04,1.53-1.98,1.3-.48-.13-.44-.5-.46-.8-.06-.86-.08-1.72-.12-2.58-.2-2.46,.1-M 5.01-.58-7.39-.05-.15-.37-.25-.59-.33-2.96,2.09-6.13,6.16-8.98,8.77-3.08-.23-6.18-.43-9.31-.62-.07-3.12-1.61-1.48-2.94-.17-4.21-.23-8.46-.44-12.75-.6,4.08-3.75,8.2-7.46,11.95-11.43,.32-.26,.78-.76,1.22-.75,.23,.09,.57,.21,.6,.35,.55,2.76,.92,5.55,1.5,8.3,.11,.21,.62,.58,.92,.32,4.77-4.42,8.92-9.44,13.44-14.12,.88-.73,1.49-2.1,2.72-2.2,.06,0,.21,.13,.22,.21,.32,1.37,.65,2.75,.92,4.12,.35,1.81,.65,3.62,.99,5.43,.01,.08,.15,.15,.25,.2,.26,.15,.53,.13,.73-.07,.76-.75,1.56-1.48,2.24-2.27,3.44-3.99,6.83-8.01,10.25-12.01,M 3.5-4.57,3.05-.9,3.72,2.46Z"/><path class="cls-2" d="M906.19,1224.04c.06,0,.11-.02,.17-.03-.02,.05-.04,.11-.06,.16l-.11-.13Z"/><path class="cls-2" d="M945.14,1096.22c-.05,.02-.11,.04-.16,.06,.01-.06,.03-.13,.04-.19l.12,.13Z"/><path class="cls-2" d="M951.59,1293.34h-.18s.01-.05,.02-.07l.16,.07Z"/><path class="cls-2" d="M880.01,930.25c.63,2.44-.09,5.14-.02,7.67-.31,5.31-.43,10.62-1.08,15.9-3.99-.91-8.04-1.79-12.13-2.64-.05-2.22,.66-4.79,.24-6.88-.59-.3-1.26,.32-1.58,.7-1.56,1.66-3.12,3.31-4.68,4.97-2-.4-4.01-.79-6.04M -1.17,.32-4.3,.7-8.58,1.02-12.88-.05-2.38-1.01-1.46-2.12-.28-3,3.31-5.99,6.64-8.99,9.95-.33,.27-1.02,1.17-1.44,.8-.62-2.2,.1-4.65,.03-6.93,.03-3.79,.73-7.71,.26-11.44l.25-10.67c.11,2.26,.17,4.51,.09,6.77,.01,.34,.22,1.05,.67,.98,3.17-2.7,5.38-6.42,8.14-9.54,.74-.9,1.43-1.82,2.19-2.71,.1-.11,.49-.07,.74-.06,.09,0,.24,.12,.25,.19,.09,1.07,.22,2.14,.22,3.22-.02,4.3-.1,8.61-.13,12.92-.06,4.62,1.45,1.9,3.23,.02,2.5-2.94,4.97-5.89,7.47-8.83,.26-.21,.94-.7,1.28-.4,.1,.3,.21,.62,.21,.93,0,5.16,.25,10.33-.4,15.49-.04,2.38-1M .38,8.18,2.34,3.74,2.83-3.01,5.64-6.04,8.47-9.05,.35-.26,1.09-1.11,1.51-.77Z"/><path class="cls-2" d="M895.43,1000.67c-2.91,2.18-5.8,4.37-8.71,6.55-.58,.3-1.28,1.09-1.97,.94-.38-.28-.18-1.08-.17-1.51,.54-2.82,1.07-5.64,1.57-8.46,3.13,.81,6.23,1.64,9.28,2.48Z"/><path class="cls-2" d="M891.28,956.77c-3.37-.84-6.78-1.66-10.23-2.46,2.99-2.81,5.91-5.69,8.87-8.52,.65-.49,1.2-1.42,2.14-1.14,.22,.16,.2,.62,.2,.89-.32,3.75-.65,7.48-.98,11.23Z"/><path class="cls-2" d="M926.83,1293c-.17,.73-.9,2.02,.26,2.24,8.13-.29,16.19-1.6M 7,24.32-1.9-10.73,31.31-22.93,62.13-35.8,92.63-.37,.13-.62,.29-.86,.29-8.78-.02-17.51,.21-26.29,0-.35-1.36,.61-2.52,1.04-3.77,4.97-11.26,10.06-22.49,14.88-33.79,4.55-10.7,8.97-21.43,13.27-32.18,2.59-6.46,5.01-12.95,7.54-19.42,.59-1.32-.29-1.57-1.44-1.42-7.36,.67-14.71,1.39-22.07,2.04-1.91,.05-.55-1.97-.24-2.89,2.37-5.83,4.79-11.65,7.12-17.49,7.47-18.65,14.38-37.41,20.91-56.3,.29-.93,.18-1.63-1.72-1.25-7.12,1.42-14.26,2.84-21.39,4.22,7.94-22.07,16.25-44.29,22.4-66.85-.35-.89-2.08,0-2.79,.08-5.95,1.56-11.74,3.97-17.7M 7,5.11-.51-.63-.16-1.24,.03-1.86,2.12-6.57,4.27-13.12,6.32-19.7,3.06-9.82,5.8-19.69,8.61-29.56,.54-1.88,.98-3.79,1.42-5.7,.06-.27-.08-.72-.31-.84-.82-.25-1.83,.34-2.6,.63-5.06,2.03-10.05,4.18-15.12,6.15-1.4,.48-1.1-1.33-.8-2.11,4.4-14.74,8.12-29.61,11.68-44.55,.18-.74,.29-1.5,.42-2.24,.06-.32,.04-.66-.36-.82-.87-.15-1.7,.57-2.48,.89-4.79,2.35-9.36,5.18-14.3,7.23-1.69,.66,2.13-10.13,2.16-11.4,2.12-10.49,5.17-20.91,6.49-31.51-.23-.99-2.06,.59-2.57,.73-3.71,2.33-7.39,4.69-11.09,7.02-.63,.4-1.3,.75-1.97,1.11-.07,.04-.2M 7-.03-.37-.09-.1-.05-.21-.15-.21-.23-.01-.42-.05-.86,.03-1.27,1.98-10.84,4.71-21.54,6.12-32.47,4.69,1.32,9.3,2.69,13.81,4.1-.81,6.25-2.59,12.4-2.85,18.7,0,.1,.44,.33,.55,.29,4.54-2.11,8.56-5.21,12.9-7.71,.77-.4,1.51-1.08,2.44-.87-.45,7.45-2.14,14.98-3.36,22.41-1.13,7.14-3.38,14.57-4.06,21.64,.95,.07,1.58-.38,2.26-.71,4.82-2.35,9.55-4.9,14.44-7.12,1.34-.18,.68,1.63,.63,2.39-1.29,5.94-2.39,11.91-3.63,17.85-2.07,9.11-4.05,18.25-6.4,27.29-.05,.89-1.41,3.6,.15,3.4,6.32-2.22,12.45-4.97,18.8-7.14-3.78,16.48-7.79,32.85-12.M 58,49.11-.89,3.04-1.73,6.08-2.58,9.12-.12,.42-.18,.85,.36,1.3,6.08-1.46,12.14-3.35,18.2-4.98,.7-.13,2.09-.75,2.3,.27-4.53,17.51-9.83,34.85-15.31,52.11-1.42,5.13-3.8,10.09-4.79,15.31,.35,.86,1.78,.31,2.49,.32,6.51-1.22,13.1-2.43,19.59-3.57,.23,.26,.51,.43,.5,.59-.01,.53-.05,1.08-.22,1.59-1.94,5.82-3.61,11.69-5.56,17.51-6.58,19.44-13.35,38.8-20.55,58.04Z"/><path class="cls-2" d="M589.21,1154.29c-.11-.59,.35-1.01,.73-1.45,3.14-3.62,6.3-7.23,9.44-10.86,2.09-2.5,4.32-4.89,6.21-7.53,.18-.24,.14-.42-.13-.52-12.94,3.6-25.5M 2,9.24-38.66,12.68-1.12-.09,.19-1.29,.45-1.76,3.98-4.86,7.98-9.7,11.95-14.56,.51-.62,.92-1.3,1.36-1.96,.03-.05-.06-.18-.13-.23-.45-.28-1.02,.06-1.49,.15-2.24,.72-4.49,1.44-6.72,2.18-10.17,3.41-20.57,6.33-30.86,9.49-.73,.22-1.53,.32-2.3,.45-.07,.01-.27-.13-.27-.18,3.54-5.42,8.13-10.36,12-15.64,.36-.46,.64-.95,.29-1.49,0,.01,.14,.25,.14,.25l-.13-.16c-14.65,3.47-29.25,8.91-44.08,11.12-.07-.07-.13-.22-.08-.29,.35-.57,.68-1.15,1.09-1.69,2.95-3.86,5.91-7.71,8.86-11.56,.32-.57,1.24-1.43,1.12-2.02-.17-.13-.43-.33-.58-.3-1.M 95,.41-3.9,.84-5.83,1.3-13.14,3.19-26.45,5.84-39.78,8.48-.51,.1-1.05,.14-1.59,.15-.33,0-.56-.19-.45-.38,2.6-4.43,5.96-8.41,8.86-12.65,.46-.64,1.08-1.25,1.08-2.04-.46-.31-.98-.27-1.5-.18-3.95,.67-7.9,1.33-11.85,2.01-8.15,1.42-16.33,2.74-24.57,3.79-4.89,.38-9.8,1.95-14.68,1.72-.32-.62,.12-1.07,.41-1.52,2.21-3.45,4.44-6.89,6.65-10.33,.39-.84,2.26-2.66,.47-2.9-15.77,1.47-31.53,3.24-47.38,4-3.22,.12-6.43,.59-9.66,.5-1.25-.31-.13-1.5,.14-2.19,2.13-4.06,4.78-7.9,6.57-12.12-.12-.79-1.34-.54-1.94-.62-21.68,.64-43.35,.59-65.M 04,.04l.15,.09c2.43-5.2,4.86-10.4,7.29-15.59l-.11,.07c22.41,.6,44.88,.7,67.3,.63,.45,.66,.11,1.16-.14,1.64-1.55,2.98-3.12,5.95-4.68,8.93-.28,.98-2.77,3.75-.78,3.88,14.79-.46,29.54-1.62,44.27-2.88,4.41-.39,8.8-.97,13.22-1.27,.34-.03,.75,.42,.63,.67-2.23,4.42-5.14,8.49-7.47,12.86-.2,1.29,2.16,.57,2.91,.63,16.49-1.97,32.81-4.69,49.17-7.45,.2-.03,.47,.14,.67,.25,.13,.61-.68,1.48-.93,2.07-2.53,4.02-5.38,7.88-7.7,12.02,.89,.46,1.68,.26,2.46,.1,4.57-.91,9.13-1.86,13.7-2.76,9.67-1.91,19.19-4.23,28.76-6.42,.9-.21,1.82-.39,2M .74-.53,.16-.02,.4,.19,.55,.33,.12,.62-.75,1.45-1.05,2.04-2.33,3.27-4.68,6.54-7,9.81-1.53,2.28-2.71,3.44,1.12,2.55,6.52-1.71,13.02-3.45,19.55-5.14,6.02-1.56,11.91-3.39,17.85-5.12,1.3-.2,2.9-1.24,4.14-.72,.06,.03,.09,.2,.05,.28-.33,.58-.62,1.19-1.02,1.74-2.85,3.9-5.73,7.79-8.59,11.69-1.71,2.35-1.2,2.35,1.32,1.69,9.5-2.72,18.85-5.77,28.15-8.9,3.35-1.13,6.72-2.21,10.08-3.31,.3-.1,.57-.09,.69,.15,.27,.55-.23,1.01-.53,1.44-4.01,5.06-7.57,10.55-11.88,15.35,.16,.14,.21,.3,.43,.29l-.52-.31c2.13,.97,4.62-.91,6.74-1.36,10.97M -3.62,21.79-8.17,32.65-11.65,.9,.25-1.32,2.53-1.57,3.08-4.25,5.18-8.03,10.81-12.6,15.71,0,0,.17,.08,.17,.08l-.09-.15c1.01,.81,2.28,0,3.32-.34,10.58-4.02,21.25-7.9,31.6-12.3,.26-.09,1.22-.37,1.29,.06-3.97,6.79-9.14,12.97-13.93,19.27-2.39,3.06,5.41-1.06,6.25-1.19,6.49-2.63,12.89-5.39,19.21-8.27,1.23-.37,2.68-1.61,3.94-1.22,.21,.38-.45,1.05-.64,1.42-3.54,4.83-7.08,9.66-10.63,14.49-1.5,2.04-3.04,4.07-4.54,6.11-.53,.97-.25,1.33,1.21,.76,8.71-3.62,17.32-7.45,26.01-11.11,.39-.13,1.04,.11,.77,.64-4.35,6.1-9.11,11.95-13.62,M 17.95-1.76,2.29-3.56,4.57-5.31,6.87-.29,.48,.29,.82,.73,.67,8.07-3.16,16.14-6.46,24.01-9.99,.84-.26,2.08-1.04,2.89-.9,.09,.17,.23,.41,.15,.54-.5,.76-1.05,1.5-1.61,2.24-6.15,8.69-15.4,18.96-20.87,27.13,.07,.08,.23,.19,.3,.17,.75-.23,1.52-.44,2.24-.72,7.24-2.87,14.47-5.76,21.7-8.63,1.11-.27,2.19-1.31,3.3-.68-8.62,11.65-18.25,22.65-27.31,33.93,1.13,.67,2.59-.36,3.79-.63,7.13-2.54,14.25-5.11,21.38-7.65,.59-.13,1.3-.53,1.88-.26,.08,.05,.17,.19,.13,.24-.37,.57-.72,1.15-1.15,1.68-10.08,12.51-20.66,24.79-31.3,36.9-1.05,1.5M 6,.56,.96,1.5,.84,5.9-1.51,11.79-3.04,17.68-4.55,1.05-.14,2.49-.88,3.45-.6,.07,.05,.13,.18,.09,.24-.21,.39-.4,.8-.7,1.15-4.1,4.81-8.13,9.65-12.33,14.39-8.09,9.15-16.26,18.24-24.4,27.36-2.6,2.66-1.52,2.71,1.57,2.2,6.7-1.13,13.34-2.76,20.07-3.62,1.39,.17-.76,2.02-1.11,2.57-13.97,16.12-28.65,31.83-43.51,47.41-.51,.71-1.66,1.16-1.43,2.18,.9,.42,1.85,.18,2.75,.09,5.62-.55,11.22-1.14,16.84-1.69,1.46-.14,2.95-.19,4.42-.26,.33-.02,.51,.14,.51,.39-16.91,20.3-36.55,39.27-55.21,58.47-.61,.67-1.54,.86-2.48,.85-7.82,.04-15.63,.M 08-23.45,.11-.77,.01-1.87-.08-1.72-.85,18.36-18.02,37.14-35.65,54.89-54.27,.44-.6,1.39-1.12,1.1-1.94-1.34-.29-2.95,.05-4.36,.07-5.22,.46-10.43,1.03-15.64,1.53-1.34,.11-2.68,.17-4.02,.23-.33,.02-.51-.15-.5-.4,11.19-12.17,23.76-23.66,35.02-35.85,3.76-3.94,7.49-7.9,11.23-11.85,.56-.56,1.14-1.1,1.16-1.92-7.9,.6-15.72,2.92-23.66,3.76-1.2-.12,.96-1.88,1.21-2.31,13.04-13.6,26.3-26.93,38.41-41.16,.38-1.08-2.86,.26-3.4,.28-7.9,2.11-15.68,4.69-23.65,6.49-1.14-.12,.6-1.58,.86-2.03,4.58-4.93,9.26-9.8,13.75-14.78,5.83-6.46,11.5M 2-13.01,17.26-19.53,2.21-2.66-1.48-.92-2.72-.63-7.11,2.32-14.21,4.64-21.31,6.96-.87,.28-1.7,.67-2.7,.52l-.17-.14c.11-.3,.12-.66,.33-.9,3.73-4.23,7.51-8.42,11.21-12.66,5.01-5.74,9.97-11.51,14.95-17.27,.24-.39,.92-.98,.75-1.4-1.31-.4-2.75,.69-4.05,.98-6.99,2.53-13.98,5.06-20.97,7.59-1.15,.28-2.21,1.13-3.41,.69,2.48-3.51,5.58-6.57,8.27-9.92,4.9-6.17,10.52-11.91,14.98-18.35,.02-.04-.21-.22-.27-.21-.63,.14-1.28,.26-1.86,.49-8.61,3.35-17.15,6.82-25.88,9.87-.58,.11-1.35,.07-.67-.82,6.49-7.78,13.05-15.51,19.2-23.54,.26-.42M -.04-1.02-.63-.71-9.19,3.6-18.38,7.19-27.72,10.54-1.22,.44-2.49,.82-3.74,1.21-.14,.02-.5-.23-.44-.41,1.84-2.82,4.46-5.1,6.58-7.72,3.77-4.33,7.5-8.68,11.24-13.03,.38-.44,.68-.92,1.01-1.39,.04-.06,.01-.23-.04-.25-.23-.07-.49-.16-.73-.15-7.38,2.53-14.66,5.44-22.03,8.05-4.29,1.56-8.63,3.02-12.95,4.53-.62,.22-1.26,.38-1.94,.15l.09,.06Z"/><path class="cls-2" d="M609.5,986.85v.05s-.07,.03-.1,.04l.1-.09Z"/><path class="cls-2" d="M613.62,997.26s.04-.04,.06-.05c.03,.04,.05,.09,.07,.13h-.01s-.13-.09-.12-.08Z"/><path class="clM s-2" d="M697.99,978.32c-6.77,4.15-13.46,8.38-20.55,12.01-.31,.16-.9-.09-.91-.36-.49-1.62,1.38-9.45-.54-9.24-8.73,4.24-17.19,9.01-26.17,12.8-.45,.2-.91,.55-1.48,.3-.76-.33-.45-.93-.44-1.43,.02-.65,.12-1.29,.16-1.94-.19-1.21,.95-6.13-.61-6.09-2.4,.52-4.63,1.72-6.93,2.57-8.67,3.88-18.05,6.64-26.84,10.27-1.56-3.36-2.86-6.86-4.18-10.31,2.39-.87,4.76-1.77,7.17-2.62,10.34-1.22,20.48-2.26,30.43-3.11,.62,.88,.53,2.02,1.89,2.27,2.13-.88,4.47-1.96,6.6-2.95,7.36-.56,14.61-1.02,21.75-1.38,.36,.29,.86,.21,1.22-.06,6.56-.33,13.04M -.57,19.43-.73Z"/><path class="cls-2" d="M715.15,978.05c-4.23,2.77-8.31,5.97-12.79,8.36-1.52,.14-.05-6.86-.19-8.19,4.37-.1,8.7-.15,12.98-.17Z"/><path class="cls-2" d="M730.99,978.13c-1.88,1.32-3.59,2.89-5.64,3.94-.14,.06-.61-.1-.63-.19-.16-1.27,.23-2.53,.28-3.81,2.01,.01,4,.03,5.99,.06Z"/><path class="cls-2" d="M801.75,940.47v.55c-.16-.02-.32-.03-.47-.05,.15-.17,.31-.33,.47-.5Z"/><path class="cls-2" d="M817.7,956.29s-.01,0-.03-.02c.01,0,.02,.01,.03,.02Z"/><path class="cls-2" d="M835.46,996.84l.03-.03,.03,.03-.12,.0M 8s.04-.05,.06-.08Z"/><path class="cls-2" d="M844.14,988.97c-2.85,2.64-5.94,5.07-8.65,7.84-.48-.41-.59-.92-.47-1.46,.47-2.59,1.17-5.13,1.76-7.69,2.47,.42,4.93,.86,7.36,1.31Z"/><path class="cls-2" d="M906.3,1224.17c-.06,.01-.11,.02-.17,.03,.02-.05,.04-.11,.06-.16l.11,.13Z"/><path class="cls-2" d="M883.55,1226.61c-.66,1.54-.75,2.24,1.22,1.91,7.1-1.51,14.24-2.92,21.36-4.32-9.28,25.69-20.36,50.73-31.19,75.8,.69,.49,1.37,.41,2.01,.34,7.22-.74,14.42-1.53,21.63-2.27,.96-.09,1.32,.59,1,1.3-12.14,29.4-25.61,58.21-39.63,86.77M -8.94,.46-18.02,.3-26.97,.09-.28-.49-.25-.9-.03-1.32,1.07-2.09,2.11-4.19,3.22-6.27,13.17-25.48,26.6-50.91,37.7-77.25,.02-.14-.29-.45-.43-.44-1.74,.06-3.49,.1-5.21,.28-4.94,.51-9.87,1.1-14.8,1.64-1.3,.02-2.73,.46-3.94-.07-.17-.79,.29-1.46,.63-2.16,3.33-6.93,6.72-13.85,9.98-20.8,7.57-16.01,14.54-32.13,21.4-48.4,1.12-2.19-.04-2.35-1.95-1.84-6.11,1.3-12.22,2.61-18.34,3.91-1.71,.33-2.28,.21-1.49-1.7,2.95-6.7,5.99-13.37,8.84-20.1,5.71-13.66,11.65-27.21,16.41-41.19,.02-.1-.37-.39-.5-.36-.78,.14-1.56,.32-2.31,.56-5.25,1.67M -10.49,3.36-15.74,5.04-2.08,.68-2.73,.63-1.79-1.72,6.35-15.94,12.86-31.92,18.24-48.19,.44-1.35,.87-2.7,1.26-4.06,.03-.08-.38-.37-.51-.34-6.29,1.94-12.12,5.19-18.33,7.38-1.26,.06-.18-1.82-.03-2.47,4.02-10.38,7.63-20.86,11.08-31.37,1.27-3.85,2.5-7.71,3.72-11.57,.17-.52,.21-1.06,.29-1.59,.01-.09-.06-.25-.15-.28-.98-.47-1.89,.54-2.77,.84-4.15,2.21-8.29,4.43-12.43,6.64-.58,.22-2.25,1.51-2.56,.5,3.92-13.07,8.46-25.99,11.96-39.18,.74-2.58-.79-1.6-2.27-.68-4.57,2.83-8.97,5.93-13.67,8.56-1.84,.26,.65-4.79,.81-5.83,1.96-5.72M ,3.25-11.55,4.82-17.33,.99-3.69,2.03-7.36,3.03-11.04,.11-.42,.17-.85,.23-1.27,.01-.1-.07-.27-.15-.29-1.02-.3-1.74,.78-2.56,1.2-3.59,2.61-7.16,5.22-10.75,7.84-.67,.58-1.41,1.02-2.33,1.07-.33-1.13,.42-2.32,.63-3.46,1.86-6.07,3.17-12.23,4.69-18.35,.69-2.74,1.29-5.5,1.92-8.25,.09-.38,.42-.88-.25-1.09-.6-.18-.96,.3-1.31,.59-4.19,3.34-8.26,6.83-12.5,10.1-.22,.1-.87,.26-.9-.16,.09-.75,.12-1.51,.33-2.23,1.91-6.59,3.03-13.27,4.48-19.92,4.12,.78,8.19,1.6,12.19,2.45-.38,2.18-.74,4.37-1.11,6.55-.01,.09,.1,.27,.17,.28,.25,.02,.M 58,.07,.74-.04,2.31-1.65,4.35-3.61,6.55-5.41,2.08,.46,4.14,.93,6.18,1.41-1.57,8.2-3.61,16.34-5.05,24.57,.14,1.79,3.3-1.2,4-1.6,3.5-2.52,6.79-5.31,10.43-7.63,.16-.1,.5,0,.81,.02,.28,1.19-.06,2.35-.33,3.5-2.25,10.93-5.3,21.78-7.56,32.67,.34,.84,2.04-.63,2.59-.84,4.03-2.52,8.04-5.07,12.06-7.6,.52-.33,1.04-.7,1.93-.59-1.73,9.56-4.62,18.97-7.07,28.42-1.13,4.21-2.41,8.4-3.62,12.59-.04,.36-.26,.95,.06,1.23,.72,.09,1.51-.45,2.16-.7,3.72-1.94,7.43-3.9,11.14-5.86,1.38-.57,2.59-1.82,4.16-1.67,.46,.66-.09,1.72-.2,2.48-3.11,10.M 81-6.16,21.64-9.58,32.36-1.28,4.07-2.62,8.13-3.92,12.2-.1,.31-.1,.64-.14,.96-.04,.24,.57,.56,.88,.45,5.1-1.89,10.03-4.17,15.06-6.22,.83-.35,1.7-.63,2.56-.95,.31-.11,.54-.04,.65,.2,.19,.27,.1,.64,.04,.93-2.94,9.51-5.9,19.02-9.19,28.45-2.67,7.67-5.13,15.4-8.21,22.98-.42,1.01-.67,2.07-.99,3.12-.09,.31,.35,.68,.69,.61,5.98-1.54,11.8-3.63,17.74-5.36,1.45-.36,3.05-.95,2.2,1.29-7.01,20.77-14.81,41.25-23.12,61.55Z"/><path class="cls-2" d="M650.7,385.7c.75,.04,1.24-.36,1.75-.7,3.84-2.54,7.67-5.09,11.51-7.63,.76-.29,4.53-3.6M 8,4.17-1.58-3.39,7.77-7.25,15.49-9.77,23.56-.03,.25,.33,.4,.54,.27,6.77-4.32,13.14-9.24,19.77-13.77,.68-.48,1.27-1.12,2.3-1.17,.37,.56-.05,1.05-.25,1.54-2.05,5.01-4.11,10.02-6.17,15.03-.38,.92-.85,1.82-1.1,2.77-.18,.67-.99,1.32-.29,2.08,.92-.01,1.38-.61,1.97-1.02,6.51-4.52,13-9.05,19.51-13.57,.5-.26,1.09-.78,1.68-.73,.1,.05,.23,.19,.21,.26-.28,.82-.54,1.66-.9,2.46-2.2,5.39-4.71,10.75-6.04,16.34,.72,.06,1.13-.2,1.53-.47,1.83-1.27,3.67-2.54,5.49-3.81,5.63-3.66,10.71-8.1,16.66-11.22,.11,.22,.32,.42,.27,.57-1.87,5.4-4.M 37,10.6-6.12,16.03,.23,1.08,2.22-.56,2.77-.82,7.42-4.55,14.67-9.79,22.32-13.78,.65,.7-.34,1.89-.54,2.69-1.69,3.75-2.88,7.62-4.24,11.45-.15,.41-.25,.83,.21,1.3,8.02-4.61,15.59-9.89,23.9-14.24,.54-.3,1.08-.71,1.72-.43,.09,.02,.19,.19,.17,.27-.25,.84-.5,1.67-.81,2.5-1.08,3.52-3.09,6.89-3.53,10.54,.09,.96,2.74-.94,3.29-1.11,7.88-4.25,15.77-8.83,24-12.46,.18-.06,.57,.16,.57,.34-.3,.93-.61,1.86-.94,2.79-1.12,3.1-2.46,6.15-3.19,9.33-.02,.1,.31,.33,.51,.36,10.73-4.59,21.4-10.06,32.61-14.02,.52,.38,.47,.79,.31,1.2-1.16,2.98M -2.33,5.95-3.48,8.94-.24,.61-.38,1.25-.55,1.88-.02,.08,.05,.24,.14,.28,.21,.09,.51,.25,.67,.19,1.23-.44,2.43-.93,3.63-1.41,10.89-4.18,21.86-8.55,33.11-11.9,1.4,.05,.19,1.72,.04,2.45-1.09,2.77-2.2,5.54-3.29,8.31-.17,.42-.12,.84,.35,1.29,13.46-4.27,27.13-8.41,40.84-11.91,.69,.46,.56,.84,.32,1.48-1.09,2.77-2.2,5.54-3.28,8.31-.21,.7-.87,2.15,.37,2.14,12.97-2.92,25.91-5.93,39.02-8.25,.65-.13,1.31-.26,1.96-.38,3.29-.63,4.08-.68,4.21-.3,.4,1.14-.45,2.09-.79,3.1-.86,2.6-1.87,5.16-2.82,7.75-.16,.43,.35,.82,.95,.74,16.58-2.3M 5,33.19-4.85,49.92-5.8,.95,.21,.7,1.27,.46,1.95-1.4,3.43-2.09,7.3-3.96,10.47l.14-.12c-17.35,1.23-34.72,2.98-51.87,5.83l.13,.09c.98-3.78,2.67-7.46,3.2-11.31-.01-.15-.35-.42-.52-.42-.94,.04-1.89,.09-2.8,.25-13.83,2.35-27.44,5.3-41.05,8.48-1.93,.42,0-3.32,.16-4.5,.61-1.99,1.25-3.96,1.87-5.95,.13-.42-.44-.87-.95-.76-11.81,2.93-23.46,6.36-34.95,10.06-1.49,.48-3.03,.88-4.56,1.28-.12,.03-.52-.23-.51-.36,.31-3.24,1.96-6.25,2.83-9.38,1.15-2.93-2.51-.91-3.8-.59-10.94,3.85-21.8,7.85-32.51,12.27-.31,.12-.92-.22-.86-.47,.21-.95M ,.39-1.91,.67-2.85,.75-2.51,1.55-5.01,2.31-7.52,.06-.18-.06-.41-.12-.6-.17-.4-1.38,.06-1.82,.24-9.4,3.77-18.55,7.88-27.39,12.44-.92,.31-2.43,1.66-2.88,.5,.8-2.94,1.65-5.88,2.47-8.82,.29-1.11,1.2-3.64-.93-2.4-8.78,4.35-17.1,9.48-25.68,13.97-.36-.47-.24-.88-.12-1.29,1.06-3.78,2.26-7.52,3.17-11.34,.02-.08-.1-.26-.18-.27-.23-.04-.56-.1-.72-.01-7.09,4.03-13.95,8.39-20.73,12.9-.7,.31-3.48,2.7-3.75,1.51,.52-4.21,2.46-8.14,3.62-12.22,.85-2.17-1-.95-1.96-.41-6.9,4.48-13.95,8.82-20.5,13.65-.47,.44-1.1,.6-1.7,.78-.07-.29-.26-M .61-.18-.87,1.42-4.71,2.95-9.39,4.35-14.1-.2-1.09-2.17,.61-2.66,.9-5.88,4.28-11.74,8.58-17.61,12.86-.78,.43-1.66,1.44-2.53,1.49-.71-.37-.26-1.12-.16-1.71,1.36-4.83,3.05-9.6,4.82-14.34,.5-1.85-1.23-.71-1.91-.16-4.53,3.22-9.12,6.39-13.41,9.83-1.81,1.45-3.65,2.87-5.49,4.3-.48,.37-.91,.82-1.67,.84-.34-.38-.13-.78,0-1.19,1.9-5.61,3.81-11.22,5.7-16.83,.16-.51,.44-1.05-.09-1.44-.85,.09-1.78,1.06-2.53,1.51-5.54,4.25-11.07,8.52-16.6,12.78-.69,.41-1.37,1.26-2.17,1.34-.17-.11-.44-.3-.41-.41,.19-.85,.43-1.69,.69-2.52,1.66-5.33M ,3.58-10.6,5.64-15.84,.36-.92,.72-1.85,1.03-2.78,.05-.14-.16-.35-.29-.51-.03-.04-.28,0-.38,.06-5.42,3.32-10.23,7.96-15.66,11.08-.7-.37-.22-1.12-.08-1.69,2.73-7.66,5.53-15.29,8.43-22.91,.01-.16-.16-.34-.3-.49-.04-.04-.28,0-.38,.06-4.81,3.05-9.31,6.54-14,9.77-.54,.26-1.37,1.02-1.97,.85-.43-.35,.03-1.08,.1-1.54,3.32-8.53,6.55-17.08,10.25-25.52,.23-.65,.74-1.18,.14-1.82-5.9,3.2-11.01,7.2-16.77,10.62-.4-.6-.33-1.02-.15-1.43,1.37-3.26,2.74-6.53,4.13-9.79,2.96-6.93,5.94-13.85,8.9-20.77,.1-.38,.48-.92,.08-1.21-.7-.14-1.7,.M 66-2.37,.94-4.58,2.66-9.14,5.34-13.72,7.99-.42,.24-.94,.38-1.42,.54-.05,.02-.27-.12-.27-.17,1.62-5.33,4.33-10.38,6.48-15.56,2.95-6.47,6.03-12.91,9.04-19.36,.37-.8,.64-1.63,.94-2.46,.03-.07-.09-.21-.18-.28-.64-.21-1.47,.44-2.09,.64-5.26,2.62-10.42,5.4-15.73,7.92-.3,.15-.78-.27-.77-.49,5.87-14.27,13.1-28.09,20.04-41.92,.21-.41,.35-.8-.21-1.23-6.38,2.43-12.59,5.42-19.01,7.73-.38,.14-.62-.34-.6-.6,7.38-15.82,15.44-31.27,23.91-46.6,1.21-2.16,1.29-2.5,.78-2.64-1.17-.32-2.07,.29-3.03,.59-5.92,1.71-11.66,4.07-17.67,5.42-.5M 6-.11-.02-1.08,.09-1.44,9.49-19.03,20.15-37.47,30.69-55.98-1.66-.54-3.1,.24-4.74,.48-5.72,1.22-11.4,2.61-17.15,3.73-.38,.06-.82,.17-1.14-.1-.59-.64,.37-1.43,.58-2.06,5.94-10.73,12.02-21.42,18.3-32.02,6.25-10.62,12.85-21.09,19.15-31.71,.23-.9-1.19-.66-1.74-.64-5.74,.63-11.47,1.27-17.21,1.92-1.92,.05-3.78,1.01-5.66,.23,14.02-26.03,30.83-50.79,46.95-75.69,1.05-1.57,3.53-.77,5.17-.97,6.87,0,13.75-.02,20.62-.01,.64,.04,1.83-.12,1.93,.65-1.09,2.24-2.86,4.14-4.22,6.24-15.04,21.11-29.17,42.61-43.22,64.31-.49,.75-.88,1.55-1M .26,2.35-.05,.11,.19,.38,.38,.47,6.76-.24,13.59-1.52,20.38-2.09,.82,.08,3.99-.72,3.8,.52-13.54,20.85-27.64,41.47-39.85,63.08,.61,.31,1.14,.33,1.67,.21,2.34-.51,4.67-1.03,7.01-1.54,4.29-.93,8.58-1.86,12.87-2.78,.37-.08,.79-.04,1.18-.02,.35,.02,.5,.21,.38,.45-10.75,17.75-21.9,35.16-31.88,53.31-.27,.48-.37,1.02-.52,1.54-.01,.05,.19,.21,.28,.2,.52-.04,1.07-.05,1.55-.2,6.02-1.87,12.01-3.84,18.03-5.69,.48-.12,1.04-.5,1.48-.16,.64,.49-.07,.98-.27,1.44-.27,.61-.67,1.17-1.02,1.76-8.31,14.66-18.42,30.04-24.94,45.04,.69,.23,1M .51-.35,2.19-.51,5.89-2.37,11.73-4.86,17.65-7.15,.17,.28,.42,.51,.36,.64-.29,.71-.63,1.41-1.02,2.09-4.47,7.84-8.79,15.73-12.94,23.68-2.49,4.77-4.91,9.56-7.36,14.34-.25,.49-.54,.99,.15,1.56,5.59-2.47,11.04-5.32,16.57-7.94,.57-.28,1.19-.48,1.8-.71,.05-.02,.2,.08,.27,.14-4.86,11.74-12.96,24.09-17.69,36.28,.35,.82,1.72-.33,2.28-.51,4.64-2.59,9.26-5.2,13.9-7.79,.59-.22,1.47-.89,2.09-.68,.09,.06,.2,.19,.18,.26-.24,.61-.47,1.23-.78,1.83-4.76,9.15-8.83,18.51-13.12,27.8-.18,.64-.94,1.52-.4,2.09,1.09,.03,2.01-1.04,2.97-1.49,M 4.06-2.5,8.12-4.99,12.18-7.49,.58-.37,3.23-2.02,2.47-.13-4.18,8.24-7.81,16.73-11.58,25.15-.27,.6-.58,1.22-.15,1.86-.16-.09-.38-.12-.42,.07,.14,.14,.26,.08,.35-.15Z"/><path class="cls-2" d="M577.88,262.2s.03,.01,.05,.01h-.05Z"/><path class="cls-2" d="M638.22,415.16l-.02,.02-.03-.03h-.01s.14-.07,.14-.07l-.08,.08Z"/><path class="cls-2" d="M867.39,431s.01-.05,.02-.07c.02-.01,.04-.01,.06-.02l-.08,.09Z"/><path class="cls-2" d="M869.74,421.18c-.76,3.25-1.55,6.5-2.33,9.75-12.7,2.99-25.14,6.83-37.59,10.68-.56,.18-1.81,.61-2M .02-.22,0-2.79,.75-5.55,1.06-8.33,.33-1.75-1.02-1.23-2.1-.86-10.89,3.74-21.52,7.84-32.1,12.19-.68,.27-1.35-.14-1.26-.77,0-1.26,2.13-9.67,.59-9.31-9.01,3.13-17.65,7.82-26.06,12.22-.77,.42-1.6,.78-2.43,1.12-.13,.05-.61-.15-.63-.26-.32-3.11,.6-6.22,.87-9.31,.05-.41-.22-.81-.5-.76-5.43,2.21-10.52,5.63-15.6,8.51-3.14,1.82-6.13,3.98-9.44,5.5-.11,.05-.56-.16-.58-.27-.42-3.41,1.37-7.29,1.15-10.54-.88-.34-1.64,.45-2.37,.82-6.48,4.38-12.96,8.77-19.44,13.15-.72,.31-1.53,1.45-2.22,.77,.05-3.42,1-6.83,1.37-10.24,.34-1.8-1.15-1.M 04-1.98-.41-7.07,4.59-13.29,10.1-20.04,14.95-.01,.01-.02,.02-.03,.02-.77,.16-.71-.64-.67-1.16,.51-2.99,.63-6.01,1.38-8.97,.19-.73,.24-1.49,.34-2.23,.01-.09-.09-.27-.15-.28-1.05-.13-1.75,.84-2.55,1.36-4.42,3.54-8.83,7.08-13.25,10.62-1.75-.09-3.5-.18-5.23-.29,.5-3.01,1.15-6.02,1.52-9.05,.02-.18-.12-.46-.3-.53-.18-.08-.57-.03-.72,.08-3.56,2.79-6.82,5.92-10.25,8.85-2.69-.2-5.35-.41-8-.64,.32-2.49,1.16-4.96,1.14-7.47,0-.06-.13-.15-.23-.17-.12-.03-.31-.05-.38,0-2.96,2.05-5.47,4.63-8.22,6.93-3.2-.3-6.37-.63-9.51-.98,.52-2M .32,1.01-4.64,1.42-6.98,.02-.08-.07-.22-.17-.25-.65-.1-1.35,.74-1.86,1.07-1.98,1.8-3.94,3.6-5.91,5.4-1.99-.24-3.96-.48-5.92-.74,.81-3.71,1.61-7.42,2.42-11.13,.89-3.12-.16-2.9-2.13-1.08-3.43,3.04-6.83,6.1-10.26,9.14-.75,.58-2.79,2.6-2.29,.25,1.65-6.77,3.33-13.52,5.14-20.25,.13-.51,.05-1.06,.04-1.59,0-.04-.18-.1-.29-.11-.46-.06-.75,.2-1.02,.42-3.5,2.99-6.99,5.98-10.49,8.97-.74,.62-1.5,1.22-2.27,1.82-.27,.22-.76-.17-.77-.38,1.72-8.43,4.14-16.71,6.69-24.93,.16-.42,.12-.84-.26-1.12-.59-.09-1.15,.55-1.63,.83-3.78,2.93-7.M 54,5.86-11.3,8.79-.69,.44-1.26,1.32-2.19,1.12,1.65-9.13,5.02-18.56,7.85-27.61,.09-.66,1.15-3.13,0-2.8-4.4,2.75-8.45,5.99-12.7,8.96-.73,.39-1.82,1.42-2.61,1.39-.36-.3-.38-.72-.22-1.13,2.35-7.85,4.66-15.71,7.52-23.45,1.06-2.89,2.04-5.8,3.05-8.71,.08-.5,.53-1.1,.25-1.55-.2-.06-.51-.15-.64-.07-3.03,1.79-6.05,3.6-9.05,5.42-2.04,1.24-4.04,2.51-6.07,3.75-.39,.24-.81,.52-1.4,.34-.26-.55,.08-1.05,.24-1.56,2.68-8.56,5.63-17.06,8.77-25.52,1.34-3.62,2.74-7.21,4.1-10.82,.23-.6,.56-1.21,.35-1.87-.02-.09-.17-.23-.22-.22-.38,.08-.M 79,.14-1.1,.3-4.4,2.3-8.79,4.61-13.18,6.91-.9,.47-1.82,.92-2.75,1.36-.31,.16-.72-.28-.73-.52,1.86-6.63,4.69-13.02,7.06-19.53,3.09-7.91,6.33-15.78,9.51-23.66,.18-.78,.97-1.71,.36-2.42-5.69,1.65-11.19,4.75-16.8,6.91-.67,.14-1.89,.99-2.37,.2,4.47-13.73,10.75-27.06,16.47-40.48,1.68-3.75,3.36-7.5,5.03-11.25,.19-.4,.31-.82-.17-1.24-6.32,1.58-12.41,4.03-18.65,5.95-.6,.2-1.22,.39-1.89,.23-.34-.66-.01-1.26,.25-1.87,1.93-4.48,3.82-8.96,5.81-13.43,6.57-15.39,14.29-30.44,21.21-45.69,.04-.12-.27-.45-.4-.45-.8,.05-1.61,.1-2.37,.M 27-5.98,1.3-11.94,2.63-17.91,3.95-.67,.15-2.28,.61-1.98-.57,10.4-23.35,21.92-46.2,34.02-68.76,.28-.55,.85-1.11,.48-1.8-.78-.31-1.58-.13-2.38-.04-6.53,.74-13.06,1.49-19.6,2.23-.76-.04-2.62,.49-2.61-.65,8.95-18.7,18.79-36.91,28.75-55.13,4.45-7.97,8.88-15.93,13.35-23.89,.55-.97,.91-2.04,2.03-2.87,8.16-.27,16.39-.02,24.55-.1,3.32-.17,2.25,1.07,1,3.09-15.13,24.52-29.56,49.43-43.22,74.76-.91,1.24-.72,2.29,1.12,1.97,7.57-.57,15.19-2.33,22.75-2.16,.22,.62-.09,1.11-.36,1.6-1.53,2.63-3.11,5.25-4.6,7.9-10.92,19.4-21.63,38.84-M 31.36,58.81-.12,.29,.34,.62,.76,.53,7.16-1.53,14.29-3.09,21.44-4.62,1.58,0-.13,1.96-.32,2.67-9.85,18.69-19.81,37.45-28.26,56.69,.38,.67,1.45,.18,2.05,.04,6.13-1.93,12.22-4.01,18.38-5.85,1.4-.25,.6,1.38,.21,1.98-8.09,16.31-16.14,32.58-22.9,49.33,.38,.7,1.42,.11,1.99-.06,5.83-2.38,11.56-5.1,17.44-7.31,.53,.47,.37,.9,.19,1.3-6.29,13.7-12.53,27.51-18.01,41.48-1.28,3.13,.32,2.1,2.24,1.19,5.01-2.53,9.88-5.3,14.97-7.66,.19-.08,.83,.08,.77,.41-.25,.72-.47,1.46-.78,2.16-4.51,10.03-8.54,20.19-12.44,30.38-.71,1.85-1.27,3.74-1M .89,5.61-.03,.08,.06,.26,.14,.29,1.1,.3,2-.85,2.96-1.26,4.53-2.71,9.05-5.43,13.59-8.13,.13-.08,.45,0,.66,.06,.26,.19,.09,.64,.01,.92-3,7.82-6.04,15.63-9,23.46-.34,1.38-3.92,9.38-2.5,9.45,4.34-2.37,8.19-5.57,12.36-8.24,1.02-.7,2.1-1.34,3.16-2,.35-.19,.68,.23,.65,.5-2.23,6.78-4.83,13.44-7.16,20.19-.94,2.7-1.74,5.42-2.58,8.14-.09,.28,.03,.6,.05,.9,.97-.07,1.45-.63,2.03-1.07,4.13-3.09,8.25-6.19,12.39-9.28,.4-.23,.87-.71,1.36-.54,.09,.04,.22,.17,.2,.25-.18,.84-.31,1.69-.58,2.51-2.11,6.46-4.25,12.91-6.37,19.37-.37,1.14-.M 68,2.3-1.01,3.45-.02,.09,.05,.27,.12,.29,.65,.23,1.14-.2,1.62-.57,4.57-3.75,9.36-7.27,13.8-11.16,.02,.03,.05,.05,.06,.08h.01c.71,.81,.07,1.78-.11,2.66-1.94,6.6-3.89,13.2-5.81,19.8-.04,.14,.15,.34,.27,.49,.32,.04,.76-.25,1.03-.44,4.13-3.39,8.18-6.87,12.29-10.27,.66-.43,1.29-1.34,2.17-1.01,.09,.02,.17,.19,.16,.28-.14,.64-.25,1.28-.45,1.9-1.71,5.21-2.98,10.49-4.29,15.77-.05,.55-.28,1.71,.61,1.47,6.13-4.79,12-9.9,18.04-14.81,1.51-1.12,2.53-1.95,2.01,.75-1.18,4.53-2.4,9.05-3.58,13.58-.13,.52-.11,1.06-.14,1.59-.01,.09,.0M 8,.22,.17,.25,.8,.06,1.53-.88,2.19-1.26,3.85-3.17,7.65-6.37,11.51-9.53,1.98-1.62,4.05-3.16,6.09-4.73,.39-.3,.81-.56,1.48-.51,.02,2.63-1.41,5.21-1.88,7.83-.5,2.49-1.48,5.14-1.6,7.59,1.11,.23,1.91-.96,2.81-1.46,6.28-4.7,12.3-9.76,18.74-14.24,.26-.2,.79,.17,.8,.39-.89,4.35-1.9,8.69-2.81,13.04-.05,.4,.65,.39,.84,.32,6.8-5.06,13.67-10.07,20.87-14.76,.53-.27,1.12-.78,1.74-.69,.38,.28,.06,1.08,.05,1.5-.79,3.8-2.14,7.53-2.6,11.37,1.06,.02,1.6-.51,2.21-.91,4.35-2.9,8.68-5.81,13.04-8.69,2.39-1.58,4.85-3.09,7.28-4.62,.64-.36,M 1.33-.88,2.12-.65,.07,.02,.15,.2,.14,.29-.22,2.92-1.25,5.71-1.75,8.58-.17,.88-.93,1.78-.12,2.7,1.31-.08,2.13-.86,3.07-1.42,6.6-3.92,13.21-7.83,20.09-11.42,1.01-.4,2.03-1.4,3.14-1.23,.17,.07,.33,.35,.3,.52-.47,3.51-1.8,6.96-1.91,10.48,.84,.2,1.38-.16,1.93-.44,3.52-1.79,7.03-3.6,10.57-5.37,5.25-2.63,10.7-4.99,16.21-7.26,.66-.17,1.52-.84,2.16-.4,.88,.93-3.61,11.13-1.31,10.72,10.83-3.94,21.48-8.49,32.52-12.17,.89-.14,3.08-1.6,3.19-.02-.53,2.99-1.44,5.91-2.09,8.88-.07,.29-.03,.69,.17,.91,.72,.58,1.76-.23,2.57-.35,11.79-M 3.78,23.68-7.22,35.68-10.31,.56-.11,1.41-.37,1.69,.27,.07,.31,.04,.64-.03,.96Z"/><path class="cls-2" d="M516.24,1302.89c.91,.4,1.85,.16,2.75,0,2.63-.45,5.25-.94,7.87-1.44,6.02-1.16,12.03-2.33,18.05-3.49,.72-.07,1.59-.41,2.19,.14-13.96,13.66-29.89,26.26-44.77,39.36-2.86,2.42-4.31,3.58,.74,2.92,8.13-.87,16.23-2.1,24.39-2.69,.11,0,.33,.07,.34,.13,.04,.19,.11,.46-.01,.58-.77,.75-1.57,1.47-2.39,2.19-17.73,15.34-35.78,30.51-53.98,45.45-.98,.87-2.51,.75-3.78,.76-7.79-.14-15.62,.34-23.38-.2-1.05-.77,1.6-2.12,2.07-2.7,16.3-M 13.47,32.59-26.93,48.88-40.41,.35-.44,2.51-1.8,1.59-2.23-9.35,.38-18.63,2.28-28,2.66-.18,0-.41-.35-.32-.49,.68-.66,1.34-1.34,2.08-1.96,14.11-11.83,28.18-23.72,42.09-35.76,3.53-2.91-1.41-1.23-3.03-1.14-8.81,1.53-17.62,3.07-26.43,4.59-1.69-.37,1.47-2.2,1.94-2.8,12.08-10.67,24.92-20.89,36.24-32.07-.56-.41-1.19-.12-1.79,0-8.83,1.93-17.65,3.86-26.48,5.77-1.55,.34-3.14,.59-4.71,.86-.11,.02-.34-.04-.36-.1-.06-.17-.14-.42-.04-.53,10.65-10.26,22.91-19.55,32.99-30.2-12.26,2.45-23.65,5.87-35.97,8.23,.68-1.65,2.04-2.31,3.21-3.M 54,7.43-6.82,14.86-13.64,22.28-20.47,.92-1.01,2.37-1.74,2.66-3.12,.17-.03,.39-.05,.28-.25-.26-.02-.33,.09-.19,.31-.8-.29-1.58-.08-2.34,.11-3.7,.91-7.38,1.86-11.08,2.78-7.94,1.73-15.76,4.36-23.8,5.5l.06,.09c-.03-.2-.18-.47-.07-.59,.71-.78,1.44-1.55,2.22-2.29,6.64-6.38,13.29-12.74,19.93-19.12,.52-.5,1.03-1,1.49-1.53,.1-.11,0-.37-.08-.54-.76-.25-1.88,.25-2.69,.37-11.52,3.01-23.15,5.71-34.8,8.37-3.14,.77-2.07-.49-.53-1.95,6.26-6.35,12.8-12.45,18.91-18.94,.3-1.15-1.4-.44-1.99-.38-12.5,3.03-25.14,5.66-37.74,8.39-.82,.07-M 1.87,.59-2.55-.05-.07-.06-.07-.24-.01-.31,.53-.62,1.06-1.24,1.63-1.84,4.99-5.22,9.99-10.43,14.98-15.66,.32-.45,1.63-1.65,.61-1.79-14.38,2.75-28.71,5.79-43.21,8.19-.73,.06-1.6,.35-2.21-.17-.07-.05-.09-.23-.03-.31,4.78-5.92,10.3-11.25,15.08-17.17,.1-.22-.12-.75-.47-.69-10.72,1.63-21.34,3.61-32.11,5-5.58,.7-11.12,1.73-16.71,2.31-.26-.03-.74-.29-.57-.62,3.73-4.9,7.77-9.57,11.62-14.38,.32-.57,2.33-2.43,.96-2.64-4,.44-8,.91-11.99,1.35-14.11,1.4-28.3,3.38-42.44,3.86-.16-.75,.37-1.28,.76-1.83,2.44-3.47,4.89-6.94,7.34-10.41M ,.6-.84,1.23-1.67,1.76-2.54,.39-.65,1.38-1.31,.74-2.04-.46-.53-1.5-.24-2.28-.18-19.51,1.31-39.04,2.04-58.59,2.32-.46-1.31,.66-2.23,1.15-3.36,2.2-3.93,4.42-7.86,6.61-11.79,1.49-2.58-.23-1.98-2.17-2.14-22.51,.08-44.98-.98-67.45-2.01l.09,.1c2.43-6.07,4.86-12.13,7.29-18.2l-.12,.07c24.25,2,48.57,2.9,72.9,3.25l-.09-.1c-2.84,5.22-5.68,10.44-8.51,15.66-.42,.78-.06,1.18,1.12,1.17,20.85,.12,41.66-1.01,62.47-1.86l-.06-.11c-3.46,5.11-6.92,10.22-10.38,15.33-.3,.47-.49,1.2,.3,1.32,10.47-.6,20.89-1.64,31.32-2.68,7.89-.75,15.75-1.M 68,23.6-2.61,.34-.04,.78,.42,.65,.66-.17,.29-.31,.6-.51,.87-3.28,4.34-6.69,8.59-10.01,12.9-.49,.64-.93,1.31-1.37,1.97-.21,.4,.34,.46,.62,.56,16.87-1.79,33.57-5.37,50.34-7.41,.2,.64-.26,1.06-.62,1.48-4.36,5.18-8.88,10.25-13.17,15.49-.08,.22,.14,.72,.51,.66,1.85-.22,3.69-.62,5.52-.94,13.5-2.45,26.89-5.38,40.34-8.03,1.06,.2-.31,1.36-.59,1.82-4.28,4.7-8.58,9.39-12.86,14.09-.71,.78-1.39,1.58-2.07,2.38-.29,.35,.32,.55,.54,.55,13.44-2.62,26.67-6.03,39.94-9.2,1.02-.15,2.07-.69,3.08-.3,.05,.6-.49,.97-.89,1.38-5.86,6.33-12.1M 8,12.28-17.84,18.78,1.27,.34,2.26-.14,3.25-.37,4.9-1.18,9.77-2.42,14.63-3.68,7.59-2.16,15.44-3.72,22.88-6.28l-.02-.05c.86,1.14-.68,1.96-1.33,2.77-5.57,5.54-11.14,11.08-16.71,16.62-1.03,1.24-5.53,4.61-.98,3.38,11.98-3.24,24.05-6.18,35.93-9.73,1.38,.06-.89,1.99-1.25,2.43-6.86,6.8-13.74,13.6-20.81,20.2-1.24,1.26-4.29,3.67-.25,2.61,10.83-2.94,21.66-5.87,32.45-8.93,3.55-.99,1.25,.81,.04,2.15-6.14,5.86-12.3,11.71-18.47,17.55-.59,.93-10.64,8.92-8.22,8.72,11.07-2.62,22.01-5.69,33.01-8.59,3.22-.52-.59,2.19-1.3,3.01-10.02,9.M 16-20.04,18.32-30.06,27.48-.53,.49-1.05,.98-1.52,1.51-.1,.11,0,.36,.07,.53,.03,.06,.25,.13,.36,.1,3.11-.68,6.24-1.33,9.33-2.06,7.23-1.69,14.45-3.42,21.68-5.13,.4,0,1.2-.32,1.28,.14-12.14,12.22-25.76,23.14-38.51,34.8-.7,.62-1.67,1.12-1.84,2.06-.18,.23-.16,.26,.08,.09l-.19-.14Z"/><path class="cls-2" d="M1279.83,881.01c-9.33-9.29-17.97-19.35-27.59-28.59-5.31-5.29-10.7-10.51-16.06-15.76-.53-.46-1-1.15-1.81-1.02-.06,0-.19,.19-.17,.27,.74,2.73,1.47,5.46,2.25,8.19,1.19,4.19,2.41,8.38,3.62,12.57,.21,.73,.43,1.47,.2,2.23l.1M 2-.06c-1.32-.13-2.06-1.61-3.03-2.39-11.53-11.59-23.34-23.98-36.24-34.17-.15,.13-.36,.33-.33,.46,.29,1.05,.61,2.09,.95,3.13,2.02,6.14,4.06,12.28,6.07,18.42,.24,.72,.36,1.46,.52,2.2,.01,.06-.11,.19-.2,.21-.91-.15-1.56-1.18-2.29-1.71-5.69-5.47-11.28-11-17.08-16.39-4.4-4.08-9.06-7.97-13.62-11.94-.42-.37-.82-.82-1.62-.72-.24,.9,.33,1.69,.61,2.49,1.92,5.49,3.93,10.97,5.88,16.46,.88,2.48,1.67,4.98,2.48,7.47-.01,.23-.41,.35-.6,.19-9.04-7.91-17.69-16.26-26.88-24.12-.91-.79-1.87-1.55-2.83-2.29-.11-.08-.42-.03-.62,.01-.06,.01M -.13,.2-.1,.29,.3,.94,.61,1.87,.94,2.8,2.79,7.65,5.61,15.29,8.36,22.95,.33,.91,.9,1.81,.66,2.88-1.38-.35-2.18-1.49-3.25-2.32-6.83-5.81-13.65-11.62-20.49-17.43-.83-.7-1.74-1.34-2.63-1.99-.08-.06-.33-.08-.38-.04-.7,.54,0,1.38,.14,2.06,3.14,8.8,6.29,17.59,9.44,26.39,.18,.5,.53,.99,.14,1.53-1.12-.24-1.72-1.01-2.47-1.61-7-5.51-13.76-11.32-20.89-16.66-.19-.11-.89-.17-.88,.23,.76,2.29,1.54,4.57,2.33,6.86,2.47,7.16,4.96,14.32,7.42,21.48,.25,.72,.39,1.47,.56,2.21,.02,.09-.08,.26-.16,.28-.23,.04-.56,.09-.69,0-.91-.64-1.77-1.M 32-2.65-1.99-5.18-3.93-10.37-7.86-15.56-11.78-2.98-2.17-3.36-2.06-2.1,1.55,3,8.72,5.79,17.48,8.45,26.27,.32,1.05,.62,2.09,.89,3.15,.04,.15-.14,.34-.22,.52-1.02-.15-1.6-.79-2.29-1.28-4.43-3.15-8.85-6.32-13.28-9.46-1.19-.66-2.5-2.09-3.85-2.19-.39,.15-.41,.49-.34,.8,.15,.63,.3,1.27,.5,1.89,2.97,9.62,5.61,19.29,8.25,28.97,.48,2.29,1.19,3.95-1.72,1.89-4.37-2.88-8.72-5.77-13.1-8.64-1.01-.48-2.14-1.69-3.3-1.46-.07,.02-.13,.2-.11,.3,.54,2.22,1.05,4.44,1.64,6.65,2.38,9.9,5.2,19.85,6.75,29.82-.8,.13-1.31-.24-1.84-.57-4.61-2.M 81-9.18-5.69-13.88-8.37-1.67-.89-1.86-.11-1.64,1.48,2.13,10.62,4.17,21.26,5.93,31.95-.06,1.26,2.02,7.54-1,5.37-4.38-2.55-8.84-4.94-13.29-7.36-.55-.25-1.52-.88-2.01-.3,.63,9.55,2.74,19.02,3.46,28.59,.41,4.19,.81,8.38,1.18,12.57-.02,.64,.21,1.9-.75,1.85-5.2-2.19-10.07-5.12-15.33-7.17-.15-.05-.6,.11-.63,.22,.7,15.66,1.97,31.4,1.79,47.13,0,.29-.55,.56-.87,.46-4.51-1.6-8.81-3.74-13.26-5.49-.84-.32-2.67-1.24-2.95,.06-.58,17.55-.37,35.24-2.32,52.69-2.22,.08-4.22-1.27-6.33-1.84-3.2-1.13-6.41-2.26-9.63-3.35-.32-.11-.75,.01-M 1.14,.02l.04,.05c-.76-1.38-.23-2.95-.2-4.45,.21-2.79,.42-5.59,.63-8.38,1.11-13.21,1.8-26.44,2.19-39.69,.04-1.75,.14-2.73,2.55-1.73,3.91,1.44,7.8,2.92,11.71,4.37,1.46,.47,2.34,.65,2.4-1.23,.18-5.82-.1-11.63-.2-17.44,.05-9.37-.78-18.72-.95-28.08,.52-1.28,3.17,.62,4.13,.78,3.44,1.47,6.87,2.97,10.3,4.46,.48,.21,.96,.4,1.58,.12-.24-14.03-3.16-28.74-4.17-42.68,.63-.61,1.42-.04,2.08,.2,3.93,1.88,7.85,3.77,11.77,5.66,.68,.33,1.29,.8,2.24,.67,.08-3.91-1.26-7.89-1.72-11.81-1.2-7.26-2.5-14.51-3.91-21.73-.22-1.17-.49-2.34-.69-M 3.51-.14-.8-.75-1.61-.05-2.43,1.18-.03,1.98,.63,2.85,1.09,4.46,2.11,8.59,5.1,13.2,6.76,.45,0,.32-1.1,.3-1.42-.87-4.03-1.72-8.06-2.69-12.08-1.64-6.76-3.38-13.51-5.06-20.26-.08-.8-1.02-2.82,.33-2.76,5.05,2.58,9.81,5.7,14.74,8.49,.53,.31,1.03,.71,1.79,.51l-.02,.11-.08-.05c.33-.87,.02-1.71-.21-2.54-1.94-6.81-3.89-13.63-5.87-20.43-1.06-3.67-2.17-7.32-3.25-10.98-.02-.08,.06-.25,.14-.27,.76-.32,1.42,.28,2.05,.6,5.21,3.23,10.39,6.48,15.59,9.73,.18,.07,.88,.03,.83-.35-2.81-10.12-6.68-19.93-9.9-29.93-1.78-4.4,2.57-.57,4.07,.M 24,5.2,3.4,10.18,7.11,15.5,10.31,.35-.51,.22-.91,.07-1.32-3.38-9.64-6.91-19.23-10.51-28.8-.47-1.04,.26-1.31,1.37-.56,6.34,4.29,12.47,8.85,18.65,13.36,.59,.31,1.25,.99,1.93,.95,.39-.38-.16-1.35-.25-1.84-3.15-8.22-6.32-16.45-9.47-24.67-.87-2.48-2.11-4.38,1.42-1.97,7.44,5.59,14.86,11.22,22.2,16.91,0-.02,.04-.18,.04-.18l-.09,.26c.44-.75,.17-1.48-.12-2.2-1.08-2.77-2.15-5.55-3.27-8.32-1.96-4.81-3.97-9.61-5.91-14.42-.27-.67-.93-1.34-.43-2.12,.74,.04,1.22,.44,1.72,.79,1.91,1.36,3.82,2.72,5.71,4.1,6.17,4.5,12.36,8.99,18.12,M 13.84,.35,.3,.84,.49,1.28,.71,.05,.02,.29-.1,.29-.14-2.2-7.57-5.85-14.74-8.68-22.12-.17-.4-.34-.79,.02-1.18,1.2,.33,1.94,1.13,2.82,1.79,9.53,6.88,18.32,14.9,27.7,21.63,.15-.12,.37-.31,.33-.43-.29-.94-.6-1.88-.96-2.8-1.39-3.6-2.8-7.19-4.21-10.79-1.01-2.57-2.03-5.13-3.02-7.7-.1-.27-.01-.59-.01-.89,.81,.1,1.26,.53,1.72,.9,10.57,8.38,20.78,17.14,30.94,25.98,.85,.53,1.53,1.84,2.64,1.63,.07-.01,.16-.19,.14-.27-2.08-6.82-4.75-13.46-7.06-20.21-1.14-2.86,.99-1.16,2.17-.14,12.27,10.63,24.41,21.55,36.16,32.68,.51,.49,1.13,.9,M 1.71,1.33,.19,.13,.55,.04,.55-.22-1.5-7.11-4.17-14.01-6.09-21.04,.22-1.57,2.63,1.34,3.16,1.68,14.99,13.73,29.27,28.14,43.76,42.35,.06,.06,.29,.1,.34,.07,.17-.13,.44-.3,.42-.44-.07-.75-.18-1.5-.35-2.24-1.16-4.97-2.36-9.94-3.52-14.92-.24-1.79-1.69-5.74,1.36-2.62,17.96,17.72,35.36,36.12,52.5,54.54,1.53,.56,.58-2.14,.69-2.91-.7-5.57-1.52-11.13-2.24-16.7-.04-.29,.1-.6,.23-.89,.3-.42,1.64,.95,2.01,1.39,21.11,22.31,41.18,45.46,61.07,68.76,.89,1.03,1.3,2.06,1.29,3.3-.05,6.14-.02,12.28-.04,18.42,0,.29-.17,.58-.3,.86-.43,.53M -1.66-1.26-2.07-1.72-8.35-9.92-16.64-19.87-25.06-29.75-10.08-11.84-20.25-23.64-30.78-35.23-.71-.78-1.47-1.54-2.2-2.3-.19-.2-.45-.24-.72-.09-.09,.05-.21,.15-.2,.22,.06,1.07,.06,2.15,.21,3.21,.67,5.79,1.89,11.53,2.17,17.34,.02,.28-.14,.42-.49,.4-.77-.1-1.27-1.08-1.85-1.56-5.68-6.42-11.35-12.84-17.04-19.26-10.28-11.61-21.08-22.91-31.94-34.17-.43-.32-.92-1.02-1.52-.9-.1,.04-.21,.17-.2,.24,1.27,6.71,2.84,13.36,4.32,20.03,.18,.84,.42,1.7,.01,2.55l.03-.08Z"/><path class="cls-2" d="M257.76,597.97c1.93-.77,3.29,1.94,4.75,2.M 88,7.59,6.85,15.18,13.69,22.78,20.53,1.13,.89,2.08,2.16,3.53,2.54,.68-.66-.5-2.46-.7-3.34-2.79-7.64-5.59-15.27-8.37-22.92-1.44-4.03,.26-2.29,2.26-.64,7.01,5.96,14.02,11.92,21.04,17.87,.83,.7,1.71,1.37,2.61,2.02,.12,.08,.46,0,.68-.05,.07-.01,.14-.19,.11-.27-.41-1.25-.83-2.49-1.27-3.73-2.95-8.39-6.17-16.69-8.98-25.12-.09-.29-.26-.64,.2-.8,1.29,.14,2.42,1.79,3.55,2.49,5.98,4.81,11.96,9.62,17.96,14.41,.65,.52,1.2,1.18,2.33,1.33,.12-1.9-1.14-3.68-1.6-5.53-2.68-7.77-5.35-15.55-8.03-23.33-.29-.83-.67-1.64-.39-2.52l-.11,.0M 7c1.37,.01,2.29,1.39,3.42,2.05,5.96,4.33,11.57,9.16,17.77,13.15,.9,.32,.45-1.04,.36-1.49-3.43-10.28-6.83-20.57-9.82-30.98,.17-.73,1.16-.02,1.53,.18,5.92,4.39,12.33,8.28,17.96,12.98,.05-.05,.11-.11,.16-.16l-.22,.14c.98-.84,.34-2.05,.12-3.08-2.99-9.61-5.66-19.28-8.26-28.96-.23-.84-.37-1.7-.5-2.55-.02-.14,.23-.33,.39-.46,.74-.08,1.57,.88,2.26,1.2,4.58,3.01,9.15,6.02,13.74,9.02,.6,.39,1.17,.91,2.21,.78-1.03-6.07-3.07-12-4.35-18.03-1.3-6.2-3.13-12.58-4-18.73,.64-.25,1.2,.14,1.73,.45,4.46,2.81,9.01,5.48,13.55,8.17,.61,.3M 6,1.28,1.13,2.05,.7,.67-.38,.2-1.22,.09-1.84-.28-1.6-.65-3.19-.95-4.78-1.07-5.75-2.14-11.5-3.2-17.25-.67-5.1-2.44-10.2-2.28-15.35,.67-.74,1.92,.48,2.65,.72,4.22,2.31,8.43,4.64,12.66,6.94,.33,.11,1.12,.41,1.4,.11-.26-7.39-2-14.77-2.74-22.15-.65-6.95-1.67-13.92-1.84-20.89,1.29-.32,2.2,.63,3.34,1.04,3.8,1.84,7.6,3.68,11.41,5.52,.57,.27,1.15,.59,1.89,.33-.48-15.29-1.83-30.75-1.87-46.13,.02-.58,0-1.59,.81-1.56,4.8,1.56,9.32,3.87,14.02,5.71,3.36,1.54,2.28-2.04,2.52-4.06,.26-16.24,.48-32.58,2.15-48.73,.74-.72,2.04,.26,2.8M 9,.39,3.82,1.34,7.62,2.72,11.46,4.03,.83,.28,1.66,.77,2.68,.52,.01,0-.04-.05-.04-.05,.33,.36,.53,.76,.5,1.2-.23,3.55-.55,7.09-.81,10.64-1.09,13.43-1.83,26.87-2.22,40.34-.15,.83,.19,2.46-1.06,2.45-4.52-1.28-8.83-3.18-13.26-4.74-.61-.15-1.63-.63-2.1,0-.63,2.6-.23,5.38-.33,8.04,.03,12.93,.81,25.83,1.18,38.74,0,.25-.59,.56-.87,.45-1.21-.47-2.44-.91-3.63-1.41-3.33-1.42-6.64-2.86-9.96-4.29-.48-.21-.97-.35-1.54-.14,.34,14.16,2.83,28.33,4.25,42.45,.05,.4-.68,.73-1.17,.5-3.6-1.68-7.2-3.37-10.79-5.06-1.45-.6-2.64-1.66-4.26-1M .72,1.25,13.08,4.5,26.06,6.72,39.04-.04,.24-.47,.61-.78,.47-.94-.42-1.89-.82-2.79-1.3-3.59-1.91-7.16-3.84-10.73-5.76-.66-.36-1.29-.78-2.29-.81,1.41,10.01,4.36,19.92,6.74,29.83,.56,2.1,1.04,4.22,1.52,6.34,.03,.13-.23,.33-.4,.46-.59,.13-1.23-.42-1.76-.64-4.82-2.75-9.56-5.62-14.42-8.31-.29-.14-.76,.26-.78,.48,2.37,11.27,6.39,22.21,9.43,33.36-.16,1.16-2.49-.64-3.07-.89-4.77-2.99-9.54-5.97-14.29-8.99-.32-.2-.69-.39-1.07-.19-.15,.08-.21,.39-.17,.57,.2,.84,.42,1.69,.7,2.52,3,8.94,6.01,17.87,9,26.81,.24,.72,.39,1.46,.55,2.M 19,.02,.07-.12,.2-.22,.24-.99,.02-2.38-1.23-3.31-1.69-4.86-3.25-9.68-6.52-14.53-9.78-.52-.2-1.88-1.48-2.17-.61,.54,1.67,1.05,3.34,1.65,4.99,2.83,7.75,5.69,15.49,8.54,23.23,.13,.77,1.03,1.73,.29,2.35-.05,.04-.29,.02-.38-.04-6.59-4.14-12.68-9.02-19.07-13.46-.68-.49-1.23-1.16-2.25-1.26-.36,.41-.19,.82-.04,1.23,1.92,5.04,3.83,10.09,5.77,15.13,1.67,4.32,3.38,8.62,5.04,12.94,.05,.13-.16,.35-.3,.5-1.16-.24-2.15-1.3-3.14-1.94-6.32-4.85-12.63-9.7-18.96-14.54-.67-.51-1.21-1.17-2.21-1.32-.34,.56-.12,1.06,.08,1.58,3.2,8.23,6.4M 8,16.43,9.86,24.59,.03,.08-.03,.26-.1,.29-.74,.34-1.33-.32-1.93-.68-7.74-5.52-15.44-11.08-22.73-16.99-.67-.44-1.31-1.34-2.17-1.3-.56,.41-.04,1.26,.11,1.79,2.62,6.45,5.24,12.89,7.86,19.34,.21,.51,.38,1.03,.54,1.55,.03,.09-.06,.27-.14,.29-.77,.27-1.35-.4-1.93-.77-9.55-7.43-19.34-14.56-28.2-22.63-.06,.07-.11,.13-.15,.18l.21-.23c-1.02,1.01-.13,2.27,.21,3.38,2.32,5.95,4.65,11.89,6.96,17.84,.19,.68,.92,1.86-.4,1.54-11.76-8.88-22.65-18.71-33.81-28.11-.17-.09-.86-.14-.81,.27,1.98,6.6,4.61,13.01,6.84,19.54,.26,.72,.59,1.43,M .33,2.2l.11-.07c-1.34-.06-2.25-1.43-3.3-2.15-6.83-6.05-13.69-12.08-20.45-18.19-5.25-4.74-10.36-9.57-15.54-14.36-.34-.31-.63-.71-1.23-.75-.4-.03-.4,.44-.36,.71,1.88,6.25,3.76,12.51,5.66,18.75,.25,.84,.57,1.66,.38,2.53l.08-.06c-.61,.03-.98-.29-1.33-.61-14.43-13.12-28.47-26.75-42.07-40.53-.54-.36-3.92-4.45-4.2-3.04,1.42,6.47,3,12.91,4.52,19.36,.57,2.59-.79,1.75-2.07,.45-17.33-17.34-34.57-34.89-50.98-53.03-.6-.53-1.03-1.49-1.98-1.32-.06,0-.17,.18-.16,.28,.17,1.72,.3,3.43,.53,5.14,.65,4.82,1.35,9.63,2.02,14.45,0,.28,.05M ,.72-.32,.79-.61,.09-1.09-.58-1.52-.9-4.52-4.83-9.06-9.65-13.52-14.51-16.16-17.61-31.73-35.51-47.18-53.66-1.28-1.43-2.72-2.98-2.35-4.99-.05-6.23-.16-12.48-.17-18.71,.36-.06,.73-.2,.82-.12,.46,.37,.9,.78,1.27,1.21,6.24,7.42,12.42,14.87,18.7,22.26,12.7,14.97,25.48,29.91,38.81,44.53,.74,.62,1.2,1.73,2.34,1.49-.46-7.1-1.89-14.13-2.72-21.21,.46-1.57,2.15,1.12,2.67,1.56,5.13,5.81,10.26,11.61,15.39,17.42,11.26,12.09,22.32,25.48,34.65,36.36,.09-.04,.2-.15,.2-.23-.03-.64,0-1.29-.13-1.91-1.33-6.83-3.44-13.57-4.36-20.43,1.88,M .81,2.81,2.61,4.24,3.96,13.23,13.91,26.63,28.81,41.3,41.25,.06-.2,.23-.42,.18-.61-.59-2.21-1.18-4.42-1.81-6.62-1.31-5.4-3.55-10.69-4.35-16.15,1.89,.81,2.89,2.56,4.37,3.9,11.15,11.16,22.61,22.97,34.98,32.9,.1-.03,.26-.15,.25-.21-.16-.74-.29-1.48-.53-2.2-2.23-6.76-4.48-13.52-6.72-20.29-.07-.45-.44-1.22-.1-1.55,.22-.04,.56-.1,.66,0,.74,.62,1.45,1.27,2.14,1.93,9.82,9.53,19.64,19.04,30.22,27.8,.89,.69,1.89,1.1,1.34-.63-2.68-7.56-5.36-15.12-8.09-22.67-.29-.81-.34-1.72-1.16-2.37l-.02,.03Z"/><path class="cls-2" d="M138.15,M 1155.19c1.49-6.81,2.57-13.68,4.7-20.35l-.15,.11c15.17,2,30.38,3.66,45.61,5.06,10.96,1.06,22.02,1.32,32.95,2.72l-.09-.1c-2.03,4.9-4.08,9.8-6.1,14.7-.38,.91-.67,1.85-.95,2.78-.04,.13,.19,.43,.36,.47,22.24,1.54,44.62,1.24,66.91,1.56,.32,.52,.16,.92-.08,1.32-1.49,2.53-2.96,5.07-4.45,7.61-1.32,2.24-2.66,4.47-3.97,6.71-.26,.51-.88,1.32-.18,1.7,16.08,.32,32.28-1.03,48.37-1.86,3.22-.2,6.44-.43,9.67-.6,1.03-.04,1.34,.44,.79,1.24-3.39,4.79-6.97,9.46-10.42,14.21-.83,1.21-1.96,2.48,.47,2.3,17.22-1.24,34.55-3.64,51.62-5.11,.51,M .85-.71,1.53-1.09,2.23-4,4.73-8.01,9.45-12,14.18-.43,.51-1.08,.97-.82,1.74,12.23-.95,24.38-3.38,36.56-4.99,3.7-.57,7.38-1.21,11.07-1.81,.24-.04,.74,.05,.74,.1,.14,.83-.53,1.37-1.05,1.93-5.05,5.76-11.06,11.23-15.59,17.19,.57,.62,1.43,.15,2.15,.1,4.47-.76,8.94-1.56,13.42-2.3,9.83-1.56,19.44-3.75,29.23-5.39-.34,1.49-1.65,2.18-2.6,3.29-5.23,5.21-10.47,10.41-15.7,15.61-.45,.64-1.72,1.25-1.42,2.09,13.3-1.75,26.66-5.19,39.89-7.81,.51-.11,1.02-.32,1.64-.06-.64,1.57-2.34,2.52-3.47,3.78-6.01,5.67-12.02,11.33-18.03,17.01-.52,M .49-1,1.01-1.48,1.52-.07,.07-.08,.26-.02,.31,.6,.56,1.46,.17,2.17,.09,12.02-2.23,24.27-5.88,36.28-7.4-.38,1.57-2.12,2.4-3.16,3.57-7.22,6.54-14.45,13.07-21.67,19.61-.62,.56-1.2,1.16-1.78,1.75-.07,.07-.12,.26-.06,.3,.15,.12,.39,.29,.55,.26,11.4-2.07,22.67-4.7,33.95-7.19,.6-.12,1.25-.37,1.8,.02,.04,.02,0,.22-.08,.3-9.5,8.88-19.45,17.28-29.11,25.98-.73,.72-1.8,1.21-1.93,2.3,.93,.22,1.83,.05,2.74-.18,10.4-1.94,20.68-4.31,31.12-6.01-.59,1.55-2.06,2.25-3.2,3.39-10.74,9.7-23.56,19.18-33.45,29.2,.46,.37,1.66,.09,2.25,.08,9.M 65-1.36,19.22-3.58,28.92-4.38l-.05-.09c.03,.2,.18,.48,.07,.59-.76,.75-1.53,1.5-2.37,2.2-7.55,6.3-15.12,12.58-22.68,18.88-5.5,4.59-10.98,9.19-16.47,13.79-.29,.4-1.68,1.01-1.17,1.53,.17,.13,.46,.23,.69,.22,1.88-.13,3.76-.27,5.63-.46,5.88-.58,11.76-1.18,17.64-1.76,1.46-.15,2.93-.26,4.4-.37,.07,0,.18,.11,.21,.18,.04,.1,.09,.25,.03,.31-.68,.66-1.34,1.34-2.09,1.95-15.58,12.86-31.26,25.62-47.03,38.27-2.14,1.71-2.06,1.63-4.96,1.63-6.87,.01-13.75,.02-20.62,.02-3.63,.05-3.89-.42-.84-2.71,14.76-11.96,29.77-23.64,44.32-35.85,.M 13-.13,.07-.4,.05-.6-.65-.29-1.6-.09-2.33-.1-8.3,.73-16.59,1.56-24.88,2.32-1.18,.09-2.28-.05-.9-1.29,12.46-10.29,24.91-20.6,37.36-30.91,.48-.56,2.91-2.17,1.79-2.43-10.46,.94-20.88,3.59-31.36,4.24,.03-.24-.05-.51,.08-.64,.87-.82,1.78-1.61,2.7-2.39,9.61-8.15,19.23-16.3,28.84-24.45,1.04-1.01,2.38-1.71,2.94-3.08-9,1-17.91,3.11-26.88,4.5-1.01,0-9.91,2.41-6.69-.38,8.99-7.86,17.97-15.76,26.9-23.68,1.4-1.38,2.67-2.31-.39-1.89-10.21,1.95-20.42,3.92-30.62,5.9-.75,.08-4.38,1.11-4.28-.05,8.18-7.91,16.91-15.29,25.03-23.26,.22-.M 87-.62-.64-1.19-.51-11.72,2.46-23.6,4.37-35.4,6.56-.91,.01-2.29,.66-2.99-.05-.08-.16,.01-.44,.16-.59,.74-.77,1.51-1.52,2.28-2.26,5.77-5.55,11.55-11.1,17.32-16.65,.51-.49,.99-1.02,1.46-1.54,.07-.07,.09-.25,.03-.31-.34-.39-.86-.4-1.34-.29-10.25,1.8-20.5,3.63-30.76,5.4-3.42,.59-6.88,1.03-10.32,1.52-.17,.02-.42-.16-.58-.29-.07-.05-.06-.24,0-.31,.78-.88,1.55-1.76,2.37-2.61,4.86-5.03,9.74-10.05,14.59-15.08,.56-.58,1.32-1.1,1.33-2.06-10.47,1.08-20.83,3.25-31.33,4.4-5.17,.46-10.31,1.8-15.5,1.77,0-.28-.1-.54,.02-.69,.56-.73M ,1.17-1.45,1.78-2.15,3.78-4.32,7.58-8.64,11.36-12.97,.69-.79,1.34-1.61,1.99-2.43,.06-.07,.06-.24,0-.3-.15-.15-.37-.38-.54-.37-1.48,.1-2.96,.2-4.42,.39-10.64,1.39-21.35,2.34-32.02,3.49-4.55,.43-9.11,.75-13.67,1.09-1.95-.09,.22-2.02,.64-2.76,3.62-5.04,7.81-9.73,11.08-14.99,.05-.1-.22-.45-.35-.45-5.24-.11-10.45,.72-15.68,.96-12.63,.77-25.28,1.26-37.93,1.8-.83-.13-3.49,.54-3.41-.68,3.08-5.66,6.84-10.94,9.95-16.59,.19-1.16-1.78-.72-2.5-.85-4.45,.05-8.89,.14-13.34,.19-14.96,.21-29.91-.27-44.87-.55-1.21-.03-2.41-.14-3.62-M .21-.3-.02-.72-.49-.63-.71,.31-.82,.61-1.65,.96-2.46,1.93-4.92,4.5-9.65,6.06-14.69,.03-.15-.18-.38-.36-.48-2.05-.5-4.28-.39-6.39-.61-16.53-.77-33.02-2.06-49.49-3.62-5.21-.52-10.42-1.08-15.63-1.6-1.05-.1-2.13-.33-3.19,.01l.12,.1Z"/><path class="cls-2" d="M1009.12,190.08c12.91-2.58,25.93-4.91,38.93-7.08,1.98,.1-1.1,2.24-1.51,2.82-5.68,5.46-11.36,10.92-17.04,16.38-.85,.95-2.06,1.61-2.38,2.89,11.93-1.59,23.69-4.1,35.59-5.98,2.23-.38,4.5-.62,6.76-.89,.19-.02,.53,.13,.6,.27,.08,.97-1.46,1.87-2.02,2.67-5.29,5.57-10.8,10.9M 5-15.95,16.65-.3,1.52,7.01-.38,8.16-.35,11.63-1.79,23.27-3.53,34.96-4.92,1.17-.14,2.38-.44,3.58-.07l-.09-.07c.12,1.41-1.41,2.22-2.14,3.3-3.78,4.32-7.56,8.64-11.33,12.97-.54,.62-1.02,1.26-1.51,1.91-.15,.31,.38,.6,.61,.62,8.55-.65,17.06-1.9,25.6-2.69,8.41-.67,16.89-2.21,25.29-2.13,0,1.26-1.16,2.11-1.81,3.13-3.27,4.33-6.54,8.66-9.81,12.99-.41,.69-1.18,1.24-.8,2.1,19.13-1.24,38.05-2.36,57.27-2.98,.22,1.55-.92,2.46-1.57,3.73-2.72,4.56-5.65,9.02-8.23,13.66-.31,1.25,3.35,.66,4.16,.83,11.04,0,22.08-.1,33.12-.02,9.01,.14,18M .04,.24,27.04,.69,1.42,.37,.08,1.95-.1,2.84-2.04,5.01-4.36,9.92-6.25,14.98-.09,.26,.28,.67,.63,.69,2.95,.21,5.9,.47,8.85,.59,13.56,.66,27.08,1.8,40.6,3.04,7.22,.65,14.43,1.41,21.64,2.1,1.01-.02,2.21,.4,3.03-.31l-.02-.05c.15,.74,.3,1.46,.13,2.22-1.25,6.1-2.99,12.13-3.81,18.31l.11-.08c-17.4-1.82-34.76-4.14-52.22-5.53-9.05-.94-18.19-.99-27.2-2.25l.14,.09c2.26-5.41,4.57-10.81,6.84-16.21,.73-1.81-.08-1.85-1.67-1.94-21.78-1.09-43.6-1.27-65.4-1.33-.57-.91,.32-1.65,.67-2.48,2.75-4.79,5.74-9.47,8.34-14.34-.1-1.1-1.84-.69-2.M 63-.79-9.83,.32-19.66,.59-29.48,.99-8.87,.43-17.72,1.17-26.6,1.62-2.08-.15,.58-2.57,.94-3.41,2.8-3.81,5.62-7.6,8.42-11.4,.55-.74,1.05-1.5,1.52-2.27,.09-.15-.07-.39-.15-.69-14.44,.91-28.86,2.69-43.26,4.2-3.07,.33-6.14,.63-9.21,.93-.32,.03-.73-.48-.59-.7,.19-.29,.35-.58,.57-.85,4.02-4.86,8.16-9.63,12.22-14.46,1.76-2.25,1.58-2.29-1.23-2.09-11.94,1.6-23.88,3.25-35.79,5.1-3.3,.51-6.6,1.07-9.9,1.6-.1,.02-.3-.07-.33-.14-.08-.18-.19-.42-.1-.57,1.15-1.61,2.66-2.98,3.98-4.47,3.7-3.97,7.42-7.94,11.11-11.92,.56-.6,1.06-1.24,1.M 57-1.87,.06-.08,.07-.26,0-.31-.41-.33-.92-.3-1.4-.18-13.28,2.32-26.6,4.5-39.77,7.22-1.03,.21-2.11,.27-3.16,.38-.21,.02-.48-.27-.36-.46,5.48-5.92,11.42-11.43,17.07-17.2,.76-.76,1.52-1.51,2.24-2.29,.14-.15,.23-.54,.17-.57-.94-.52-2-.08-2.99,.06-11.94,2.2-23.81,4.6-35.61,7.23-3.07,.45-3.67,.45-.98-2,6.35-6.01,12.71-12.01,19.06-18.01,.7-.66,1.39-1.32,2.04-2,.11-.11,0-.37-.06-.55-.78-.29-1.87,.2-2.72,.27-11.96,2.3-23.91,5.61-35.88,7.4,.13-1.29,1.54-1.9,2.35-2.79,8.06-7.39,16.31-14.59,24.28-22.08,.49-1.17-1.3-.53-1.9-.5-M 10.32,2.05-20.59,4.24-30.81,6.6-2.75,.58-5.11,1.24-1.56-1.73,9.77-8.77,19.76-17.32,29.43-26.2,.29-1.01-2.9-.03-3.51-.03-9.01,1.79-18.02,3.59-27.04,5.38-4.72,1-3.52-.02-.68-2.46,10.39-8.9,20.78-17.79,31.17-26.69,.92-.79,1.83-1.58,2.7-2.4,.12-.11,.04-.38,0-.57-9.83,.66-19.82,3.04-29.68,4.41-2.76,.3-1.06-.91,0-1.95,12.99-10.95,26.1-21.78,39.16-32.67,.74-.62,1.38-1.31,2.04-1.97,.06-.06,.01-.22-.05-.31-9.47,.1-19.17,1.9-28.75,2.52-.28-.96,1.26-1.71,1.85-2.37,15.37-12.55,30.67-25.19,46.18-37.58,1.57-1.32,3.13-2.75,5.36-2M .39,7.55,0,15.09-.01,22.64-.01,3.48-.02,.72,1.55-.48,2.67-9.22,7.41-18.45,14.8-27.67,22.21-5.03,4.05-10.04,8.13-15.04,12.2-.57,.6-1.89,1.25-1.53,2.12,6.16-.21,12.3-1.16,18.45-1.62,3.21-.29,6.43-.51,9.64-.76,.34-.03,.52,.13,.5,.38-11.87,10.8-25.06,20.73-37.36,31.24-.93,.77-1.78,1.61-2.65,2.42-.24,.31,.34,.58,.55,.58,10.32-1.37,20.61-3.54,30.98-4.25-.03,.28,.05,.55-.09,.68-.78,.74-1.6,1.46-2.43,2.16-10.71,9.1-21.43,18.2-32.11,27.3,.29,.28,.38,.28,.23,.05-.04-.06-.22-.05-.34-.08,2.52,.76,5.3-.53,7.87-.72,8.82-1.41,17.M 56-3.38,26.44-4.4,.11-.01,.35,.07,.35,.12,.01,.2,.05,.46-.08,.59-9.24,8.29-18.63,16.41-27.92,24.64-.39,.46-1.29,1-1.32,1.56,.42,.32,.92,.28,1.41,.15,10.07-1.94,20.13-3.88,30.2-5.81,1.69-.32,3.41-.55,5.12-.81,.1-.02,.28,.07,.34,.15,.06,.08,.06,.24,0,.31-.46,.52-.91,1.05-1.43,1.53-7.24,6.66-14.49,13.31-21.74,19.97-.8,.88-2.15,1.56-1.64,2.67,.04-.32-.06-.4-.3-.26l.3,.19Z"/><path class="cls-2" d="M892.55,367.68c2.59-4.6,5.15-9.23,7.76-13.82-.68-.63-1.44-.2-2.21-.07-13.91,3.39-27.43,7.57-41.1,11.6-.2,.02-.87-.17-.68-.53M ,2.24-4.3,4.98-8.34,7.41-12.54,1.15-2.14-1.44-.91-2.47-.66-5.23,1.71-10.48,3.38-15.67,5.18-7.3,2.27-14.42,5.71-21.79,7.46-.28-.11-.36-.31-.22-.55,1.85-3.11,3.69-6.22,5.57-9.32,.88-1.45,1.85-2.87,2.77-4.31,.17-.27,.4-.61,.01-.85-.35-.23-.74-.04-1.1,.09-4.4,1.63-8.83,3.19-13.18,4.89-7.86,2.86-15.56,6.72-23.46,9.16-.59-.67,.26-1.39,.54-2.04,2.55-4.03,5.11-8.06,7.66-12.1,.24-.58,1.11-1.48,.88-2.04-.15-.24-.39-.3-.69-.18-4.17,1.75-8.37,3.45-12.49,5.26-5.19,2.29-10.3,4.68-15.3,7.23-.67,.34-1.43,.56-2.16,.82-.06,.02-.21-.M 08-.29-.15-.08-.07-.2-.2-.17-.26,.25-.61,.48-1.23,.82-1.81,2.56-4.39,5.14-8.77,7.7-13.16,1.96-3.3-.09-1.97-2.08-1.11-7.09,3.53-14.16,7.07-21.25,10.6-2.46,1.05-5.9,3.67-2.92-1.2,2.83-4.76,5.68-9.52,8.52-14.28,.52-.93,1.51-1.99,.55-2.98,.15,.13,.29,.26,.43,.39h.01l-.42-.39c-.31,.54-.87,.81-1.43,1.07-8.55,3.88-16.42,8.67-24.73,12.8-.09,.04-.33,.03-.35-.01-.1-.18-.27-.42-.19-.56,3.38-6.52,7.53-12.63,11.38-18.9,.33-.79,1.5-1.82,.98-2.64-.76-.09-1.71,.65-2.44,.92-7.44,3.88-14.86,7.77-22.26,11.73-.42,.22-.96,.65-1.39,.37-M .71-.46,0-.97,.24-1.43,4.59-7.81,9.75-15.31,14.28-23.16-.2-.8-1.43,.03-1.91,.17-6.89,3.56-13.81,7.06-20.59,10.82-2.67,1.44-3.33,1.67-3.4,1.27-.16-1.02,.65-1.79,1.16-2.63,4.47-7.48,9.35-14.79,14.2-22.11,3.14-4.35,2.79-4.62-1.93-2.18-6.99,3.44-13.89,7.06-20.92,10.4-1.78,.19,.02-1.75,.35-2.4,6.16-10.35,13.96-20.21,20.1-30.47-.17-.22-.42-.26-.71-.15-.97,.37-1.95,.72-2.9,1.11-4.53,1.9-9.05,3.82-13.57,5.72-1.21,.43-2.35,1.26-3.68,.89l.12,.03c6.15-10.43,13.75-20.24,20.75-30.29,1.68-2.33,3.27-4.7,4.88-7.05,.04-.06-.03-.19-M .09-.26-.08-.08-.24-.19-.31-.17-.76,.21-1.53,.4-2.27,.66-5.9,2.12-11.78,4.25-17.67,6.38-.83,.37-1.36,.13-.92-.92,.4-.67,.89-1.33,1.33-1.99,3.85-5.44,7.64-10.9,11.57-16.3,5.08-6.98,10.19-13.95,15.6-20.78,.71-.9,1.28-1.87,1.9-2.82,.04-.07-.01-.21-.08-.28-.08-.08-.24-.19-.32-.18-1.03,.22-2.07,.43-3.07,.72-5.07,1.45-10.13,2.92-15.2,4.38-1.01,.29-2.04,.56-3.06,.82-.32,.1-.64-.42-.58-.62,9.24-13.34,19.18-26.19,29.29-39.05,2.46-3.09,4.9-6.19,7.33-9.29,.1-.13,0-.39-.08-.57-.27-.24-.8-.13-1.15-.08-6.16,1.1-12.27,2.48-18.41,M 3.69-1.04,.21-2.1,.36-3.17,.5-.18,.02-.43-.17-.6-.3,12.55-17.88,27.1-34.95,41.11-52.14,.9-1.07,1.82-2.14,2.72-3.21,.3-.36,.54-.74,.4-1.21-.92-.3-1.85-.11-2.78,0-6.81,.75-13.61,1.52-20.41,2.27-.44,0-1.79,.18-1.55-.49,17.01-22.29,35.32-43.79,54.04-64.72,7.84-.29,15.65-.1,23.5-.19,.8,.13,3.66-.3,3.23,.89-9.18,10.29-18.82,20.21-27.84,30.56-8.48,9.59-17.02,19.14-25.18,28.9-.45,.54-.88,1.09-1.25,1.66-.06,.1,.17,.44,.34,.48,8.16-.2,16.27-2.08,24.44-2.09,.21,.99-.83,1.58-1.34,2.31-9.44,10.5-18.79,21.04-27.8,31.78-5.03,5.99M -10.01,12.01-14.99,18.03-.51,.62-1.21,1.18-1.28,1.97-.01,.15,.3,.48,.4,.46,6.97-1.17,13.87-2.65,20.81-3.99,.56-.08,2.72-.46,2.32,.33-12.28,15.46-25.68,30.19-37.5,45.99-1.06,1.33,.18,1.2,.97,1.1,6.37-1.74,12.73-3.5,19.1-5.25,.58-.07,1.36-.47,1.9-.19,.09,.17,.23,.41,.14,.53-.82,1.11-1.65,2.22-2.54,3.3-9.76,12.39-20.67,24.57-28.96,37.54,.07,.08,.22,.18,.3,.16,.76-.21,1.53-.41,2.27-.66,5.46-1.85,10.91-3.7,16.36-5.55,1.09-.33,2.33-.96,3.41-.29v-.04c-9.71,11.25-18.38,23.51-27.13,35.53-.09,.15,.05,.4,.13,.59,.02,.04,.23,.M 09,.31,.06,8.02-3.25,15.9-6.81,23.87-10.18,1.96-.8,3.05-1.05,1.31,1.25-5.79,7.89-11.61,15.78-17.38,23.68-1.29,1.76-2.44,3.59-3.63,5.4-.09,.13,.08,.38,.18,.56,1.18-.11,2.37-.98,3.52-1.39,7.01-3.21,14.01-6.43,21.03-9.63,.56-.25,1.21-.38,1.82-.55,.04,0,.23,.18,.21,.24-5.31,8.5-11.6,16.49-17.26,24.8-.52,.74-.88,1.58-1.77,2.13,0,0,.2,.09,.2,.09l-.12-.17c1.03,.8,2.21-.15,3.2-.57,6.66-3.18,13.31-6.35,19.97-9.53,1.53-.62,2.95-1.67,4.64-1.74l-.08-.06c.08,1.39-1.22,2.33-1.89,3.46-4.77,6.74-9.65,13.35-13.69,20.48,.31,.86,2.36M -.6,2.99-.78,8.12-3.89,16.29-8.25,24.79-11.34,.63,.11-.33,1.33-.47,1.69-3.77,5.71-7.55,11.41-11.33,17.12-.39,.77-1.25,1.47-1.02,2.37-.18,.01-.43,.01-.35,.24,.26,.05,.35-.05,.27-.3,1.59,.13,2.88-.97,4.3-1.53,7.94-3.65,15.67-7.72,23.83-10.89,.35-.09,.84,.2,.55,.57-3.78,5.69-7.77,11.33-11.17,17.19-.15,.26-.14,.59-.17,.88,0,.07,.19,.22,.25,.21,2.86-.75,5.47-2.3,8.21-3.41,7.62-3.45,15.48-6.52,23.38-9.55,.45-.09,1.05-.52,1.45-.15,.07,.07,.16,.2,.12,.26-.33,.58-.65,1.17-1.04,1.73-3.2,4.49-6.42,8.97-9.62,13.46-.4,.56-.7,1.M 16-1.02,1.74,.11,.53,.85,.42,1.25,.27,12.33-4.58,24.64-10.16,37.28-13.73,.62,.26-.33,1.3-.58,1.7-2.83,4.16-5.66,8.32-8.48,12.49-.17,.51-1.45,1.65-.7,1.98,12.37-3.76,24.7-8.51,37.25-12.24,1.24-.24,2.55-1.08,3.79-.63-11.29,18.87-15.91,16.75,7.36,10.31,8.97-2.43,18.07-5.34,27.17-7.06,.11,.04,.28,.16,.27,.2-.14,.41-.25,.83-.49,1.21-2.64,4.23-5.51,8.33-7.96,12.67,1.07,.6,2.07-.05,3.16-.21,14.81-3.39,29.8-7.26,44.81-9.4,.72,.23-.11,1.28-.35,1.71-1.93,3.2-3.87,6.4-5.78,9.6-.46,.76-1.09,1.48-1.04,2.39,.79,.37,1.58,.16,2.36M ,.03,3.55-.62,7.08-1.31,10.65-1.86,12.59-1.85,25.13-3.94,37.81-5.19,.9,0,2.53-.4,1.93,1.08-2.37,4.22-4.76,8.43-7.15,12.65l.08-.06c-8.06,1.62-16.8,1.91-25.01,3.31-9.84,1.14-19.46,3.23-29.28,4.45l.09,.08c2.17-3.92,4.28-7.88,6.53-11.76,.21-.41,.72-1.07,.52-1.49-.28-.17-.71-.36-1.02-.3-4.05,.73-8.12,1.43-12.14,2.26-11.81,2.46-23.59,5.02-35.21,7.99l.07,.12Z"/><path class="cls-2" d="M342.27,130.02c-3.54,23.39-7.76,46.69-10.31,70.21l.13-.12c-7.12-1.58-13.98-4.43-21.01-6.46-.61-.19-1.74-.64-2.08,.1-2.35,19.96-3.22,40.05-4.M 55,60.1l.14-.05c-6.97-3.26-13.86-6.7-20.88-9.84-.5-.21-1.06,.08-1.1,.58-.49,16.47-.85,32.96-.31,49.44,.13,3.28-.82,2.45-3.07,1.21-5.91-3.58-11.72-7.28-17.71-10.73-.23-.13-.72,.03-1.19,.06,.13,12.64,1.06,25.23,1.81,37.84,.16,2.69,.26,5.38,.36,8.07,0,.18-.17,.37-.27,.56-.59,.5-1.73-.62-2.32-.95-5.8-4.17-11.45-8.51-17.18-12.76-.58-.33-1.22-1.05-1.91-1.03-.25,.2-.6,.41-.52,.77,1.12,13.44,2.31,26.87,3.78,40.27-.02,2.7-2.85-.79-3.77-1.31-5.87-4.9-11.73-9.81-17.61-14.71-.51-.37-1.72-1.46-1.98-.33,.58,5.37,1.32,10.72,2.03,M 16.07,.93,7.07,1.82,14.14,2.81,21.2,.02,.41-.7,.36-.87,.28-7.77-6.8-15.16-14.02-22.8-20.97-2.46-2.08-.46,4.72-.56,5.73,1.3,9.53,3.15,18.99,4.4,28.52-.37,0-.73,.09-.85-.01-.83-.7-1.66-1.41-2.41-2.16-7.8-7.67-15.25-15.72-23.24-23.18-.15-.1-.57-.06-.59,.17,.24,1.92,.44,3.85,.75,5.77,1.33,8.22,2.77,16.43,4.08,24.66,.07,.47,.64,1.15-.2,1.36-.71,.18-1.05-.56-1.43-.97-6.44-6.91-12.86-13.83-19.29-20.75-2.49-2.68-4.97-5.36-7.48-8.04-.13-.14-.43-.18-.67-.24-.49,0-.35,1.07-.37,1.41,.79,6.33,2.08,12.6,2.94,18.91,1.9,10.74,1.83M ,10.3-5.12,2.33-8-9.06-16-18.13-24-27.19-.67-.59-1.12-1.73-2.1-1.79-.16,.02-.41,.29-.39,.43,.49,3.97,.99,7.93,1.52,11.89,.45,4.58,1.56,9.28,1.71,13.79-1.17,.02-1.85-1.45-2.65-2.17-11.3-12.87-21.8-26.74-33.48-39.12-1.06-.13-.3,2.83-.38,3.58,.42,6.43,1.46,12.91,1.56,19.32-.61,.63-1.21-.48-1.62-.86-12.59-15.42-25.18-30.85-37.76-46.28-.72-.86-1.56-1.78-1.46-2.93-.13-6.03-.08-12.06-.08-18.1,0-.53,.14-1.06,.25-1.58,.07-.12,.54-.21,.66-.12,12.13,14.03,23.68,28.57,35.68,42.71,.69,.63,1.13,1.77,2.24,1.53-.26-7.3-1.14-14.6-1M .6-21.9-.03-.41,.11-.83,.21-1.24,.01-.05,.28-.13,.36-.09,11.01,11.86,21.25,24.65,32.01,36.82,.52,.64,1.02,1.33,1.89,1.53,.3,.08,.48-.22,.41-.73-.34-2.79-.68-5.57-1.03-8.36-.72-5.57-1.45-11.13-1.98-16.72-.02-.17,.15-.37,.28-.53,.05-.05,.32-.07,.37-.03,.62,.56,1.28,1.1,1.83,1.71,4.57,5.07,9.1,10.16,13.68,15.22,4.42,4.89,8.89,9.75,13.34,14.62,.39,.44,1.01,1.29,1.75,1.02,.29-2.87-.72-5.77-.96-8.65-.9-6.2-1.73-12.41-2.55-18.62-.08-.77-.61-2.74,.82-2,8.54,8.71,16.88,17.62,25.4,26.36,.62,.54,1.14,1.4,2.08,1.32,.04,0,.15-.M 16,.14-.25-.14-1.18-.29-2.35-.45-3.53-1.21-9.61-3.12-19.2-3.83-28.85,1.21-.21,1.88,1.01,2.74,1.65,6.96,6.72,13.9,13.46,20.86,20.18,.73,.54,1.38,1.53,2.3,1.68,.29,0,.47-.14,.44-.41-.54-5.05-1.33-10.06-1.99-15.09-.81-6.75-1.58-13.51-2.34-20.27-.02-.15,.23-.4,.41-.45,1-.06,1.62,1.04,2.37,1.55,6.36,5.57,12.72,11.14,19.08,16.71,.77,.52,1.43,1.56,2.47,1.37,.08,0,.2-.14,.19-.22-.04-.97-.05-1.93-.15-2.9-1.16-12.21-2.94-24.49-3.41-36.71,.93-.27,1.59,.53,2.3,.98,6.04,4.61,12.08,9.23,18.12,13.85,1.25,.87,3.03,2.66,2.83-.23-.9M 4-14.28-2.08-28.59-2.43-42.88,1.16-.36,1.94,.46,2.88,.96,4.75,3.02,9.48,6.05,14.22,9.07,1.63,.84,3.1,2.36,4.92,2.66,.94-.15,.49-1.65,.59-2.35-.1-15.51-.57-31.02-.23-46.53,.03-2.72,3.03-.23,4.32,.25,5.25,2.63,10.5,5.26,15.76,7.88,.7,.25,1.8,1.05,2.45,.41,.98-17.71,1.59-35.52,2.83-53.25,.28-1.09-.26-3.83,1.47-3.51,6.48,2.13,12.95,4.26,19.43,6.38,1.43,.49,2.88,.94,2.99-1.09,1.69-16.65,3.83-33.25,6.03-49.84,.78-4.9,1.05-9.93,2.49-14.7l-.13,.09c5.91,.99,11.83,1.98,17.74,2.97,2.36,.26,4.73,1.12,7.1,.69l-.1-.1Z"/><path clM ass="cls-2" d="M1256.91,1041.89c1.6-.11,2.33,1.51,3.38,2.42,8.52,9.16,16.93,18.41,25.51,27.51,.35,.28,1.03,.21,.98-.38-.55-3.63-1.12-7.27-1.68-10.9-.86-5.66-1.79-11.32-2.6-16.99-.02-.13,.23-.4,.39-.41,1.2,.1,1.96,1.81,2.84,2.56,9.02,10.2,18.03,20.41,27.06,30.61,.75,.64,1.41,2.02,2.52,1.76-3.48-34.04-8.49-32.03,14.6-5.95,5.99,7.02,11.79,14.21,17.88,21.14,.22,.32,.75,.26,.91-.09,.06-.32,.13-.64,.11-.95-.5-6.88-1.14-13.75-1.68-20.63,.03-.33,.22-1.02,.68-.92,.38,.3,.78,.59,1.08,.94,2.38,2.87,4.74,5.76,7.1,8.64,9.86,12.M 09,19.73,24.17,29.57,36.27,2.29,2.82,2.05,2.02,2.07,5.71,.01,2.26,0,4.52,0,6.79-.01,3.55,.1,7.11-.06,10.66-.49,1.64-2.67-1.77-3.18-2.23-7.07-8.53-14.12-17.06-21.19-25.59-3.8-4.58-7.61-9.14-11.44-13.71-.48-.42-1.18-1.58-1.84-1.53-.42,0-.47,.43-.49,.75,.36,7,1.04,13.98,1.59,20.96,.03,.32-.04,.64-.1,.96-.06,.14-.52,.24-.65,.17-8.12-8.56-15.45-17.92-23.29-26.75-3.43-3.84-6.59-7.95-10.23-11.61-.13-.07-.57,.03-.64,.18,.18,7.15,1.75,14.36,2.41,21.52,.17,1.38,.15,2.78,.2,4.18,0,.06-.14,.15-.24,.19-.11,.04-.33,.09-.37,.05-.M 54-.47-1.11-.94-1.58-1.46-4.41-4.89-8.8-9.8-13.21-14.69-4.26-4.71-8.56-9.41-12.84-14.11-4.63-5.33-2.67-.04-2.35,3.29,1.15,7.8,2.32,15.59,3.07,23.44-.13,.93-1.38-.06-1.69-.44-8.34-8.74-16.72-17.44-25.09-26.15-.32-.33-.73-.61-1.12-.9-.51-.11-.53,.66-.54,1.01,.42,3.21,.87,6.42,1.32,9.63,.85,6.21,1.76,12.41,2.61,18.62,.14,1.07,.17,2.14,.23,3.21,0,.09-.1,.26-.15,.26-1.33,.05-2.1-1.55-3.12-2.26-6.96-6.72-13.9-13.45-20.86-20.17-.67-.57-1.18-1.37-2.21-1.21,.49,6.22,1.63,12.41,2.32,18.62,.71,5.57,1.38,11.14,2.05,16.72,.03,.M 29-.1,.6-.2,.89-.01,.04-.3,.09-.37,.05-.53-.31-1.09-.61-1.53-.99-5.01-4.37-9.98-8.76-14.99-13.12-2.18-1.9-4.41-3.77-6.65-5.63-.12-.1-.5-.04-.75,0-.25,.29-.13,.85-.14,1.24,.9,8.8,2.03,17.58,2.79,26.4,.32,3.54,.62,7.09,.91,10.64-.08,.56,.33,1.65-.53,1.68-.73-.03-1.31-.7-1.91-1.06-6.23-4.76-12.46-9.54-18.69-14.3-.47-.36-.88-.81-1.62-.85-1.24,.09-.11,5.37-.25,6.53,.84,12.47,1.73,24.94,2.05,37.43-.36,1.37-2.43-.44-3.12-.77-5.39-3.4-10.72-6.89-16.12-10.27-.98-.47-1.62-1.48-3.04-1.27-.68,.78-.32,1.65-.31,2.48-.03,15.71,1.M 01,31.48,.09,47.15-.03,.22-.7,.54-.93,.44-.94-.42-1.88-.83-2.79-1.28-5.99-2.87-11.79-6.14-17.89-8.78-.29-.12-.87,.17-.89,.44-.87,18.71-1.35,37.49-3.06,56.14-.05,.27-.61,.52-.94,.42-6.49-2.08-12.95-4.25-19.43-6.36-.85-.13-2.26-.99-2.85-.05-2.31,16.79-3.74,33.69-6.3,50.46-.61,4.39-1.21,8.78-1.83,13.16-.11,.75-.25,1.5-.95,2.08,0,0,.14-.08,.14-.08-7.67-1.61-15.52-2.62-23.25-4.05-1.54-.33-.71-2.1-.72-3.17,3.53-22.15,7.72-44.3,9.64-66.64l-.11,.12c7.14,1.57,14.01,4.43,21.06,6.46,.63,.14,1.66,.67,2.13,.02,2.3-19.99,3.22-40M .13,4.45-60.22l-.14,.04c6.59,3.14,13.17,6.29,19.76,9.43,.61,.23,1.5,.89,2.09,.33,1.33-16.42,.68-33.17,.6-49.7-.11-3.15,.69-2.68,3.01-1.35,3.75,2.28,7.48,4.59,11.22,6.88,2.14,1.31,4.28,2.61,6.46,3.88,.25,.14,.73,.02,1.24,.02-.16-15.42-1.62-30.78-2.21-46.18-.07-.59,.84-.51,1.16-.34,6.12,4.16,11.89,8.74,17.85,13.11,.78,.58,1.65,1.09,2.52,1.6,.09,.05,.57-.14,.6-.26,.11-5.56-.89-11.17-1.23-16.74-.77-7.83-1.66-15.66-2.41-23.5-.21-2.8,1.76-.73,2.85,.08,5.96,4.98,11.91,9.96,17.88,14.94,.78,.51,1.47,1.52,2.51,1.27-.45-7.57-M 1.94-15.21-2.77-22.8-.52-3.74-1.08-7.48-1.57-11.23-.15-1.17-.14-2.35-.19-3.53,0-.06,.14-.15,.24-.19,.6-.27,1.34,.74,1.83,1.05,6.95,6.44,13.89,12.89,20.84,19.33,.55,.47,1.04,1.11,1.86,.91-.66-8.49-2.56-17.09-3.7-25.61-.46-2.88-.94-5.76-1.39-8.65-.03-.18,.12-.38,.18-.57,1.05,.15,1.67,.89,2.35,1.6,7.28,7.34,14.56,14.68,21.85,22.01,.84,.66,1.43,1.88,2.63,1.78-1.04-10.57-3.4-21.13-4.91-31.69h-.09Z"/><path class="cls-2" d="M1074.53,313.27c-19.6,1.34-38.67,3.19-58.19,5.13-.36,0-.76-.41-.6-.65,.55-.86,1.08-1.73,1.67-2.58,2M .63-3.88,5.53-7.6,7.99-11.59,.2-1.25-3.05-.39-3.83-.44-6.36,.9-12.72,1.84-19.08,2.73-9.42,1.32-18.75,2.96-28.07,4.64-.53,.1-1.05,.12-1.53-.13,.04-.79,.66-1.39,1.15-2.02,2.81-3.67,5.64-7.34,8.45-11.01,.39-.72,2.66-2.67,.83-2.8-15.35,2.52-30.58,5.93-45.7,9.48-.51,.13-1.04,.24-1.53-.08,0-.81,.69-1.38,1.18-2,3.35-4.16,6.76-8.3,10.12-12.46,.3-.55,2.09-2.27,.94-2.37-13.6,2.96-27.04,6.58-40.41,10.19-.75,.1-3.98,1.42-3.69,.2,4.68-5.97,9.95-11.46,14.66-17.41-1.21-.59-2.55,.3-3.81,.47-8.43,2.24-16.74,4.75-25.06,7.25-4.16,1.2M 5-8.31,2.5-12.48,3.73-.18,.05-.46-.09-.68-.18,.26-1.16,1.52-2.04,2.24-3.01,4.74-5.5,9.8-10.74,14.33-16.4,.26-1.06-3.22,.45-3.79,.5-10.01,3.18-20.07,6.25-29.93,9.71-1.6,.56-3.25,1.02-4.9,1.49-.17,.05-.46-.11-.66-.21,4.96-6.6,11.32-12.6,16.93-18.84,1.59-1.82,3.99-3.87-.38-2.46-10.63,3.37-21.3,6.68-31.73,10.46-2.35,.72-5.09,2.14-1.9-1.33,6.71-7.52,14.17-14.59,20.54-22.33-.56-.31-1.06-.21-1.57-.04-5.21,1.75-10.44,3.48-15.64,5.25-5.57,1.9-11.13,3.84-16.69,5.74-.36,.07-1.16,.29-1.36-.08,2.81-4.11,6.63-7.56,9.95-11.34,4.4M 8-4.71,9.09-9.35,13.64-14.03,.65-.67,1.49-1.25,1.72-2.15-1.52-.29-3.05,.68-4.53,1-8.2,2.73-16.4,5.47-24.6,8.2-1.23,.27-3.11,1.16-1.48-.88,7.95-9.16,16.4-17.91,24.69-26.79,.8-.86,1.55-1.75,2.31-2.63,.06-.07,.07-.27,.03-.29-.23-.08-.52-.22-.71-.16-8.56,2.56-17.15,5.06-25.64,7.85-.61,.2-1.3,.32-1.69,.81h.04c-.35-.49-.52-1-.07-1.5,3.09-3.38,6.13-6.8,9.31-10.12,7.35-7.68,14.77-15.31,22.16-22.96,.36-.49,1.27-.89,.83-1.58-.78-.27-2.18,.38-3.06,.49-7.15,1.86-14.29,3.73-21.44,5.6-1.24,.25-2.64,.94-3.84,.24l.06,.03c13.14-13.M 08,26.01-26.48,39.39-39.35,2.97-2.8-1.61-1.14-3.03-1.02-7.06,1.4-14.11,2.81-21.17,4.21-3.73,.63-1.9-.81-.31-2.5,15.15-15.12,30.65-29.78,46.31-44.44,.34-1.2-1.82-.52-2.49-.62-6.3,.49-12.58,1.12-18.88,1.68-4.14,.35-4.43,.14-1.26-2.82,5.72-5.44,11.43-10.89,17.18-16.32,12.01-11.35,24.3-22.51,36.7-33.59,.94-.82,1.79-1.82,3.18-1.8,7.95-.03,15.9,.02,23.86,.03,1.57,.19,2.03,.37,.55,1.79-19,16.29-38.19,32.32-56.18,49.56-.12,.12-.02,.4,.03,.6,.01,.06,.21,.11,.33,.12,6.68-.19,13.35-1.41,20.02-2.01,1.47-.17,2.93-.39,4.4-.52,.5M 9-.05,1.4-.37,1.74,.3,.24,.46-.34,.77-.69,1.08-15.87,13.72-31.07,27.96-46.21,42.4-2.78,2.74,4.16,.44,5.15,.42,7.2-1.36,14.41-2.72,21.62-4.07,2.1-.05-.68,1.87-1.17,2.44-12.68,11.35-24.88,23.19-37.04,35.06-.49,.48-1.15,.9-1.14,1.62,.67,.26,1.3,.08,1.95-.08,5.4-1.35,10.79-2.69,16.19-4.03,3.47-.86,6.95-1.72,10.42-2.57,.62-.14,1.29-.32,1.87,.03-10.89,11.54-23.73,21.86-34.68,33.57-.91,1.72,2.55,0,3.22-.02,10.01-2.62,20.03-6.22,30.05-8.32,.08,.16,.2,.41,.11,.51-.72,.78-1.47,1.54-2.24,2.29-9.15,9.06-18.63,17.81-27.6,27.04-M .1,.12-.02,.35,.03,.52,.02,.05,.25,.11,.35,.09,10.62-3.07,21.16-6.4,31.75-9.56,.98-.13,2.4-1.06,3.26-.42,0,.59-.93,1.1-1.28,1.59-7.58,7.57-15.16,15.14-22.73,22.71-.37,.53-2.02,1.89-.93,2.02,6.76-1.65,13.3-4.11,19.98-6.04,5.15-1.58,10.34-3.1,15.51-4.63,.34-.1,.77-.05,1.15-.01,.72,.16-.74,1.47-1.08,1.83-6.82,7.18-14.25,13.99-20.53,21.57,.67,.39,1.23,.21,1.9,0,3.51-1.1,7.03-2.17,10.52-3.31,7.73-2.52,15.58-4.79,23.46-6.99,.89-.25,1.75-.58,2.73-.4l.1,.08c-.37,1.67-2.16,2.67-3.19,4-5.05,5.7-10.94,10.85-15.51,16.88-.01,.0M 3,.23,.2,.3,.18,1.02-.23,2.06-.45,3.06-.74,12.39-3.61,24.86-7.15,37.42-10.29,.63-.09,.95,.22,.55,.74-5.24,6.26-11.4,11.93-16.21,18.47-.02,.03,.2,.21,.28,.2,.64-.1,1.3-.2,1.92-.37,11.85-3.24,23.89-6.02,35.85-8.96,4.83-1.09,6.24-1.26,6.15-.93-.41,1.65-2.03,2.74-3.14,4.06-3.5,4.22-7.35,8.21-10.76,12.51-.81,1.45,1.45,.96,2.21,.75,14.16-3.16,28.37-6.08,42.66-8.7,.73-.07,1.59-.39,2.22,.13,.08,.05,.11,.23,.06,.3-.4,.56-.81,1.12-1.25,1.66-2.93,3.62-5.88,7.22-8.81,10.84-.77,1.19-2.2,2.17-2.27,3.61,10.78-1.17,21.58-3.68,32.4M 4-5,6.23-.83,12.45-1.94,18.72-2.5,.38-.02,.79,.39,.62,.63-3.36,4.81-6.93,9.48-10.37,14.24-.29,.3-.52,.86-.09,1.13,2.94,.25,5.87-.42,8.79-.69,16.27-1.9,32.63-3.37,48.99-4.3l-.08-.12c-3.55,5.37-6.81,10.99-10.53,16.23l.1-.05Z"/><path class="cls-2" d="M1005,333.95c-7.9,1.23-15.88,2.1-23.78,3.26-8.96,1.36-17.93,2.67-26.81,4.34-1.02,.11-2.12,.52-3.11,.09-.11-.69,.39-1.22,.76-1.79,2.36-3.61,4.72-7.22,7.09-10.83,.31-.48,.65-.94,.48-1.51,.05-.04,.11-.08,.16-.12-.25-.02-.27,.03-.05,.17-.93-.37-1.86-.1-2.76,.07-2.49,.46-4.96,M 1-7.45,1.48-12.69,2.13-25.23,6.02-37.76,7.96-.09-.17-.22-.4-.14-.53,.46-.78,.94-1.55,1.48-2.29,2.47-3.46,4.96-6.91,7.43-10.38,.27-.53,1.34-1.71,.35-1.89-1.94,.43-3.91,.82-5.82,1.33-7.16,1.88-14.33,3.76-21.46,5.72-5.49,1.45-10.82,3.36-16.34,4.68-.17,.02-.5-.2-.44-.39,3.16-5.42,7.67-10.04,10.84-15.45,.05-.17-.29-.43-.45-.4-.9,.23-1.79,.47-2.67,.72-12.18,3.47-24.04,7.6-36.01,11.49-.69,.25-1.54,.63-2.24,.38-.39-.19-.14-.56,.05-.82,3.88-5.44,8.1-10.65,12.04-16.05-1.02-.71-2.29,.23-3.38,.45-10.87,3.77-21.74,7.55-32.4,11.M 69-1.91,.56-4.98,2.24-2.4-1.14,4.24-5.5,8.56-10.94,12.76-16.48,.18-.24,.14-.42-.13-.52-8.97,2.61-17.75,6.74-26.64,9.89-2.67,1.03-5.28,2.14-7.93,3.21-.52,.21-1.04,.12-1.49-.17l-.1,.08c4.81-6.28,9.19-12.84,14.29-19.01,.36-.45,.8-.87,.61-1.46l.22-.1-.13,.18c-2.56,.01-4.88,1.76-7.32,2.49-7.6,2.84-14.88,6.74-22.39,9.41-.09-.18-.27-.44-.18-.57,2.31-3.28,4.6-6.57,6.99-9.81,2.8-3.8,5.68-7.56,8.52-11.34,.27-.36,.45-.77,.65-1.16,.03-.07-.06-.2-.14-.26-.07-.06-.24-.12-.31-.1-.98,.35-1.97,.69-2.91,1.09-8.19,3.48-16.35,7.04-24.M 56,10.49-.35,.19-.85-.02-.73-.4,5.81-8.32,12.34-16.14,18.45-24.25,1.59-2.23,.44-1.63-1.34-1.1-7.22,2.89-14.44,5.77-21.49,8.92-1.8,.67-6.28,3.37-3.18-.67,7.1-9.14,14.34-18.18,21.37-27.36,.06-.07,.06-.26,0-.28-1.08-.51-2.2,.48-3.26,.73-8.01,2.95-15.81,6.75-23.92,9.26l.07,.09c-.36-1.18,.84-1.92,1.41-2.83,7.48-9.53,15.02-19.03,23.02-28.29,.73-1.08,2.21-1.92,2.07-3.32,.22,.04,.47,.08,.41-.21-.27-.11-.38-.01-.33,.28-.69-.19-1.32,0-1.94,.21-5.76,2.05-11.55,4.06-17.28,6.2-6.89,2.49-7.87,2.72-7.72,2.29,9.18-12.92,20.39-24.6M 8,30.78-36.89,1.77-1.97,3.61-3.75-.67-2.54-6,1.55-12.01,3.11-18.01,4.66-.76,.2-1.53,.43-2.33,.09l.11,.05c-.06-.59,.37-1.01,.75-1.45,12.31-14.91,25.71-28.93,38.29-43.62,.27-.38-.4-.53-.63-.52-7.62,1.35-15.22,2.76-22.83,4.14-.12,.02-.33-.02-.37-.08-.4-.52,.14-.94,.45-1.35,11.46-13.07,23.07-26,35.2-38.66,3.28-3.42,6.52-6.86,9.76-10.31,.33-.51,1.56-1.38,.69-1.83-7.88,.17-15.77,1.45-23.65,1.98-1.53-.36,.28-1.69,.71-2.29,17.14-19.2,35.38-37.84,53.65-56.27,.71-.74,1.53-1.15,2.72-1.15,7.54-.2,15.09-.14,22.64-.13,2.29,.24,3M .97-.28,1.25,2.28-14.76,13.92-29.16,28.21-43.53,42.5-3.55,3.52-6.95,7.14-10.41,10.72-.48,.62-1.54,1.35-.25,1.72,7.36-.41,14.72-1.37,22.07-1.99,3.09-.21,1.75,.84,.36,2.35-6.14,6.14-12.39,12.22-18.43,18.42-8.94,9.18-17.74,18.44-26.59,27.67-.36,.41-.92,.8-.57,1.37,7.42-.52,15.01-2.51,22.45-3.65,.51-.09,1.02-.18,1.49,.1,.01,.72-.63,1.16-1.11,1.66-4.7,4.86-9.44,9.69-14.09,14.57-8.66,8.93-16.9,18.18-25.39,27.17,.1,.03,.19,.06,.27,.08l-.29-.13c1.85,.87,3.87-.52,5.73-.84,6.72-1.89,13.45-3.78,20.18-5.66,.5-.07,1.99-.6,1.99,M .15-10.35,11.92-21.63,23.27-31.74,35.38-.45,.52-1.08,.98-1.09,1.68,0,.07,.18,.22,.24,.21,8.82-2.32,17.37-5.76,26.16-8.31,.52-.17,1-.29,1.62,.07-8.66,10.16-17.76,19.96-26.28,30.16-.53,.62-.94,1.29-1.4,1.95-.04,.17,.32,.39,.47,.35,8.21-2.56,16.19-5.82,24.31-8.65,1.3-.32,2.81-1.43,4.11-.62l.09-.09c-3.59,3.53-6.7,7.5-9.97,11.3-4.41,5.26-8.79,10.54-13.18,15.82-.18,.31-.69,.81-.35,1.11,.08,.07,.25,.15,.33,.13,.99-.32,2-.62,2.96-1,7.84-3.07,15.64-6.2,23.62-9.02,2.6-.93,2.23-.19,.81,1.58-6.11,7.3-12.26,14.59-18.1,22.1-.3,.M 38-.44,.77-.15,1.19-.19-.16-.28-.15-.29,.03l.23-.11c9.71-3.14,19.11-7.48,28.9-10.71,.98-.35,1.98-.67,2.98-.96,.17-.05,.46,.12,.66,.22,.05,.03,.02,.23-.05,.3-.75,.89-1.51,1.78-2.28,2.66-5,5.74-10.01,11.48-15.01,17.23-.54,.62-1.04,1.25-1.51,1.91-.09,.13,.06,.38,.15,.56,.45,.16,1.01-.19,1.47-.3,7.09-2.61,14.2-5.19,21.28-7.83,4.64-1.73,9.33-3.34,14.11-4.81,.19-.06,.48,.09,.71,.18,.04,.01,.01,.2-.04,.29-3.6,4.73-7.85,9-11.64,13.58-1.68,1.95-3.27,3.95-4.89,5.93-.31,1.45,3.28-.48,3.98-.54,7.42-2.56,14.82-5.14,22.25-7.67,4M .09-1.39,8.22-2.69,12.34-4.01,.2-.06,.56-.04,.7,.07,.14,.11,.19,.42,.09,.56-.46,.65-.98,1.29-1.49,1.92-3.62,4.41-7.25,8.82-10.87,13.23-.59,.72-1.18,1.44-1.71,2.19-.09,.12,.05,.37,.14,.54,12.47-3.2,25.02-7.91,37.64-11.35,1.24-.21,2.55-1.11,3.78-.64-3.51,5.85-8.83,10.95-12.61,16.77,1.38,.49,2.58-.42,3.93-.64,12.97-3.58,25.93-7.21,39.12-10.27,.72-.17,1.23-.35,1.93,.13-3.44,4.77-7.12,9.37-10.65,14.07-.29,.47-1,1.33-.18,1.6,13.6-2.78,27.19-6.15,40.93-8.71,2.09-.19,4.65-1.41,6.65-.77,.08,.7-.44,1.21-.84,1.77-2.96,4.23-6.M 2,8.28-8.95,12.64-.06,.21,.27,.72,.59,.67,2.64-.42,5.28-.84,7.92-1.27,14.51-2.38,29.05-4.83,43.67-6.4,.34,0,.72,.44,.57,.69-3.01,4.83-6.13,9.59-9.24,14.35l.1-.06Z"/><path class="cls-2" d="M771.28,1312.01c-7.19,.82-14.39,1.65-21.58,2.46-.92,0-4.06,.69-3.89-.43,13.39-20.82,27.37-41.42,39.73-62.83,.14-.26-.22-.77-.53-.72-6.96,1.13-13.79,2.92-20.7,4.32-2.35,.51-2.08-.19-.98-1.9,11.01-17.46,21.88-34.91,31.66-53.04,.24-.36-.22-.66-.55-.63-6.44,1.84-12.77,4.02-19.18,5.98-.47,.15-1.03,.13-1.55,.16-.08,0-.27-.16-.26-.21,.12M -.41,.2-.85,.42-1.23,9.01-15.22,18.01-30.53,26.07-46.22,.37-1.72-3.55,.61-4.21,.71-4.56,1.86-9.11,3.73-13.67,5.59-.89,.26-1.73,.87-2.59,.21,7.28-12.94,14.34-26,20.91-39.19,.4-.79,.94-1.53,.68-2.44,.18,.02,.4,.04,.35-.18-.23-.08-.33,.01-.27,.25-.73-.2-1.28,.14-1.85,.41-5.68,2.52-11.15,5.99-16.99,7.94-.32-.1-.38-.28-.26-.53,2.69-5.16,5.43-10.31,8.05-15.5,3.07-6.08,6.04-12.2,9.05-18.31,.29-.6,.5-1.22,.73-1.84,.03-.08-.03-.24-.11-.27-.21-.09-.54-.24-.67-.17-1.02,.51-2.02,1.06-3.01,1.62-4.42,2.46-8.83,4.94-13.25,7.39-1.M 05,.41-1.64,.53-1.12-.89,4.89-9.55,9.24-19.29,13.65-28.99,.19-.58,.75-1.26,.11-1.74-.05-.05-.3-.05-.38,0-4.94,2.97-9.82,6.03-14.74,9.03-3.3,2.05-2.49,.35-1.31-1.99,3.78-7.48,7.1-15.1,10.39-22.73,.26-.61,.43-1.24,.62-1.87,.03-.09-.04-.25-.12-.28-.21-.07-.54-.19-.66-.11-5.29,3.3-10.41,6.82-15.61,10.24-2.45,1.16-.65-1.21-.33-2.35,3.07-7.32,6.91-14.46,8.94-22.06-1.29,.21-1.91,.97-2.7,1.52-5.97,4.19-11.92,8.4-17.88,12.6-.6,.31-1.27,1.02-1.98,.94-.11-.05-.25-.19-.23-.25,.29-.83,.59-1.65,.92-2.46,2.39-6.16,5.19-12.19,7.37M -18.43-.1-.9-1.69,.49-2.09,.66-6.6,4.6-13.19,9.2-19.79,13.8-.38,.28-1.11,.94-1.63,.42-.21-.67,.42-1.46,.61-2.14,2.18-4.86,3.94-9.83,5.77-14.78,.29-.6,.4-1.21,0-1.78-1.13,.05-2.23,1.23-3.21,1.78-6.55,4.47-12.84,9.3-19.61,13.44-.3,.14-.87-.15-.66-.52,1.92-5.38,4.52-10.56,6.09-16.04,0-.52-.94-.3-1.19-.09-7.82,5.11-15.95,9.82-23.59,15.17l.1-.06c-1.13-1.12,.3-2.7,.61-3.94,1.46-3.23,2.44-6.57,3.62-9.86,.14-.58,.49-1.35-.18-1.71-.07-.05-.3-.04-.39,0-1.18,.71-2.37,1.4-3.51,2.14-6.13,3.99-12.4,7.84-18.94,11.4-.99,.49-2.03,1M .43-3.19,.87h.09c1.63-4.43,3.27-8.86,4.89-13.3,.03-.08-.08-.21-.17-.28-.53-.2-1.26,.3-1.74,.49-7.4,4.32-15.18,8.18-22.81,12.22-.89,.47-1.86,.83-2.81,1.22-.19,.06-.53-.17-.52-.36,.99-3.7,2.56-7.23,3.78-10.86,.18-.48,.39-1.35,.11-1.55-.22-.06-.5-.13-.69-.07-1.68,.65-3.26,1.51-4.88,2.28-8.71,4.19-17.76,8.33-27,11.53-.19,0-.6-.23-.58-.31,.16-.73,.34-1.47,.61-2.18,1.1-2.88,2.24-5.75,3.34-8.63,.09-.35,.22-.99-.2-1.16-12.44,4.28-24.73,9.74-37.49,13.42-.11,.03-.55-.26-.52-.35,1.02-3.36,2.57-6.56,3.8-9.85,.21-.74,.79-1.77-.M 5-1.76-12.94,4.02-25.86,7.96-39,11.44-.53,.13-1.46,.29-1.72-.28,.75-3.4,2.51-6.58,3.63-9.88,.18-.45,.35-1.24-.25-1.4-7.07,1.15-13.98,3.14-20.99,4.61-7.78,1.72-15.66,3.17-23.53,4.54-.83,.13-1.34-.29-1.12-.91,1.18-3.3,2.45-6.59,3.54-9.92,.4-1.01-1.24-.95-1.98-.8-15.25,2.2-30.49,4.44-45.86,5.66-1.17,.11-2.39,.4-3.56-.12,.57-3.63,2.4-7.05,3.43-10.59,.15-.43,.09-.85-.3-1.2,0,0-.09,.06-.09,.06,17.08-1.97,33.93-3.11,51.13-5.96,1.53-.16,1.13,1.35,.84,2.25-.87,2.92-1.88,5.82-2.68,8.76,.69,.7,1.73,.3,2.6,.25,14.1-2.39,27.95-M 5.4,41.8-8.7,1.49-.13,.96,1.08,.7,1.93-.81,2.93-2.11,5.77-2.51,8.79-.02,.15,.26,.33,.47,.56,13.35-3.24,26.38-7.41,39.43-11.42,.49-.14,1.13,.3,1.03,.69-.92,3.37-2.29,6.62-3.15,10.01-.3,1.45,3.01-.22,3.63-.31,10.17-3.7,20.45-7.21,30.31-11.44,.82-.35,1.72-.59,2.58-.88,.3-.1,.82,.26,.77,.54-.77,3.51-2.04,6.9-2.98,10.37-.05,.17,.14,.4,.27,.58,10-3.11,19.56-8.24,28.88-12.77,1.37-.61,3.61-2.26,2.72,.6-.85,3.36-2.25,6.64-2.77,10.07,.16,.87,1.84-.3,2.32-.43,7.54-3.97,15.1-7.91,22.27-12.31,1.62-.8,3.18-2.21,2.49,.8-.9,3.15-1M .84,6.29-2.76,9.43-.05,.38-.29,.96,.03,1.24,.22,.07,.56,.18,.69,.11,7.28-3.96,14.12-8.58,21.05-13.09,4.99-3.53,3.52-1.04,2.47,2.92-.07,1.18-4.17,9.9-2.1,9.27,5.03-3.01,9.88-6.35,14.79-9.53,2.38-1.58,4.66-3.27,6.99-4.89,.52-.26,1.09-.81,1.7-.73,.38,.37,0,1.07-.05,1.54-1.17,3.76-2.38,7.51-3.54,11.27-.22,.72-.33,1.46-.47,2.2-.01,.07,.11,.19,.21,.22,.93,0,1.77-.98,2.58-1.41,6.51-4.67,12.87-9.55,19.46-14.1,.78-.23,.89,.88,.64,1.42-1.14,3.65-2.1,7.34-3.54,10.94-.57,1.43-1,2.9-1.47,4.36,.38,.81,1.37-.19,1.87-.44,7.01-4.73M ,13.43-9.97,20.14-14.94,.09-.06,.32-.1,.38-.06,.16,.12,.39,.31,.35,.43-.57,1.88-1.16,3.76-1.78,5.63-1.36,4.05-2.74,8.1-4.13,12.15-.14,.41-.27,.82,0,1.22,.72-.07,1.2-.45,1.69-.82,6.66-4.81,12.89-10.19,19.61-14.89,1.3-.41-.16,2.45-.21,3.08-1.89,6.28-4.4,12.42-6.62,18.63-.07,.42,.58,.35,.78,.27,4.38-2.77,8.36-6.1,12.58-9.09,1.15-.65,2.07-2.03,3.45-2.01l-.13-.05c.16,.77-.12,1.49-.39,2.21-2.65,7.12-4.99,14.31-7.9,21.36-.17,.58-.76,1.24-.12,1.72,.04,.04,.28,0,.37-.07,5.23-3.32,10.04-7.24,15.25-10.58,.21-.08,.86-.15,.83,.M 27-2.94,9.09-6.79,17.9-10.51,26.77-.2,.59-.77,1.22-.22,1.76,.02,.03,.28-.01,.37-.07,5.04-3.02,9.96-6.2,14.82-9.48,.51-.34,1-.74,1.75-.71,.35,.52,.1,1.02-.12,1.54-1.64,3.87-3.26,7.75-4.91,11.62-2.65,6.21-5.31,12.42-7.97,18.63-.17,.4-.42,.8-.07,1.23,.99-.06,1.66-.62,2.39-1.04,4.25-2.47,8.48-4.96,12.72-7.44,.86-.37,1.68-1.28,2.67-1.04-3.85,11.68-10.05,23.18-15.25,34.62-.43,1.17-1.48,2.1-.96,3.43,5.79-2.65,11.2-5.65,16.89-8.46,.44-.22,.98-.31,1.49-.44,.05-.01,.25,.15,.24,.21-5.56,14.13-12.74,27.64-19.58,41.3-.3,.58-.45M ,1.2-.64,1.81-.02,.05,.2,.22,.27,.21,6.42-1.93,12.41-5.21,18.73-7.51,2.27-.56-.13,2.69-.37,3.58-7.27,15.57-15.84,30.64-23.66,45.96,.28,.77,1.4,.21,1.98,.09,5.38-1.71,10.75-3.44,16.13-5.15,1.06-.18,2.44-1.11,3.37-.35-9.22,19.5-20.84,38.08-30.9,57.1,.21,.11,.49,.26,.69,.22,7.17-1.46,14.31-3.02,21.46-4.54,.84-.04,.81,.65,.58,1.2-12.18,22.2-25.24,44.04-38.6,65.77l.11-.06Z"/><path class="cls-2" d="M613.74,997.34c-.05,0-.1,0-.14-.01,.01-.02,.01-.05,.02-.07,0,0,.12,.07,.12,.08Z"/><path class="cls-2" d="M810.4,1039.06s.02-M .03,.03-.04c.01,.01,.01,.02,.02,.02l-.05,.02Z"/><path class="cls-2" d="M822.92,1306.27l.03-.06s.05-.01,.07-.01l-.1,.07Z"/><path class="cls-2" d="M834.45,1045.34c-.03-.08-.06-.15-.1-.23,.05,.02,.09,.1,.12,.24-.01,0-.01-.01-.02-.01Z"/><path class="cls-2" d="M861.27,1136.87c.73-1.85,1.43-3.7,2.11-5.56,.15-.4,.25-.83-.17-1.21-5.76,1.83-11.15,4.75-16.8,6.96-.68,.19-1.9,.99-2.37,.27,5.62-15.11,12.27-29.97,17.23-45.35-.38-1-1.54-.06-2.19,.2-4.39,2.3-8.77,4.62-13.16,6.92-2.15,1.14-3.58,1.97-2.27-1.32,4.46-12.4,9.83-25,12.8M 7-37.57-.9-.26-1.62,.53-2.36,.89-4.85,2.78-9.49,6.34-14.53,8.62-.13-.16-.33-.37-.28-.52,.35-1.15,.73-2.29,1.14-3.43,3.48-9.72,6.78-19.48,9.6-29.34,.12-.54,.58-1.55-.07-1.75-.26,.03-.57,.04-.75,.17-4.99,3.44-9.87,6.99-14.8,10.5,0,.02,.01,.04,.01,.06-.01-.02-.02-.05-.03-.07-.09-.06-.19-.11-.28-.16,.07-.07,.13-.09,.18-.07-.42-.88,.16-1.89,.36-2.8,2.39-7.17,4.61-14.38,6.55-21.64,.46-1.9,1.08-3.77,1.42-5.69,0-.1-.09-.27-.17-.28-.23-.03-.58-.08-.71,.02-3.99,3.06-7.94,6.13-11.92,9.19-.51,.27-2.43,2.09-2.71,1.23,1.66-7.62,M 4.6-15.02,6-22.7,.22-1.05,.4-2.11,.58-3.17,.01-.08-.1-.2-.19-.24-.11-.05-.32-.09-.38-.04-.6,.42-1.21,.85-1.75,1.31-3.4,2.92-6.78,5.84-10.18,8.76-.67,.46-1.28,1.32-2.2,1.12-.07,0-.17-.18-.16-.28,.05-.53,.06-1.07,.19-1.59,.89-3.37,1.82-6.73,2.7-10.1,.78-3.64,2.32-7.47,2.4-11.07-.91-.23-1.46,.69-2.1,1.14-3.42,3.05-6.82,6.1-10.25,9.14-.78,.58-1.41,1.55-2.51,1.42,.36-4.97,2.08-9.92,2.94-14.87-1.61-.22-3.24-.42-4.87-.62-1.28,.85-8.65,8.81-9.28,7.52,.18-2.8,1.29-5.61,1.68-8.42-2.75-.31-5.51-.6-8.3-.88-3.21,2.71-6.17,5.71-M 9.6,8.14-.11,.08-.44-.05-.75-.09,.43-2.97,1.01-5.91,1.45-8.88-2.23-.2-4.48-.38-6.75-.55-4.01,3.41-7.78,7.11-11.98,10.29-.12,.07-.59-.04-.65-.16,.04-4.6,1.8-9.09,2.11-13.69-.73-.2-1.12,.04-1.51,.35-.92,.74-1.85,1.49-2.77,2.23-5.59,4.66-11.55,8.94-16.93,13.83h-.01s-.04,.05-.07,.08l-.05-.14,.12,.06c-.97-.88-.4-2.28-.24-3.39,.74-2.74,.78-5.56,1.3-8.32,.09-.48,.18-1.21-.39-1.39-.22-.04-.56,.02-.72,.15-1.83,1.43-3.66,2.86-5.43,4.33-4.31,3.57-8.92,6.87-13.59,10.12-.68,.33-1.88,1.64-2.4,.53,.13-3.36,.94-6.62,1.44-9.93,0-.3M 5,.13-.97-.23-1.16-.63-.18-1.47,.59-2.01,.88-5.96,4.36-12.29,8.38-18.47,12.54-.71,.37-3.43,2.71-3.46,.79,.39-3.21,.95-6.41,1.4-9.61,.03-.15-.19-.4-.38-.46-1.12-.13-2.07,.94-3.03,1.38-6.32,3.85-12.62,7.72-19.24,11.23-1.12,.52-2.16,1.5-3.48,1.36-.49-.62-.03-1.72-.03-2.49,.24-2.35,.69-4.7,.77-7.06-.32-1.41-2.02-.09-2.79,.24-8.47,4.64-17.31,8.96-26.3,12.57-.33,.11-.82-.2-.77-.51,.33-2.13,.67-4.27,.98-6.4-.06-.87,1.04-3.6-.47-3.4-11.43,4.2-22.58,9.62-34.44,12.66-.08-.29-.27-.6-.23-.89,.55-3.15,.73-6.42,1.71-9.48-13,3.45M -25.73,8.24-39.07,10.98-1.02,.12-1.37-.8-1.5-1.59-1-2.93-1.19-6.08-2.97-8.7-14.12,2.57-28.16,5.91-42.5,7.76-2.14,.23-1.48,1.78-1.21,3.15,.56,2.65,1.19,5.29,1.68,7.96,.29,.79,1.24,.79,1.97,.6,5-.85,10.04-1.61,15-2.59,9.01-1.79,18.04-3.54,26.89-5.82,.99-.25,1.47,.12,1.29,1.03-.63,2.98-1.26,5.95-2.02,8.9-.13,.58,.49,.93,1.3,.74,12.88-3.03,25.28-7.43,37.99-10.85,2.19,.11-2.78,10.57-.75,10.51,7.48-2.17,14.83-5.14,22.09-7.88,4.09-1.65,8.18-3.29,12.28-4.92,.33-.13,.86-.21,1.13-.09,.24,.11,.38,.56,.32,.83-.61,2.97-1.43,5.9M 2-2.12,8.88-.2,.89,.59,1.19,1.35,.9,1.93-.76,3.85-1.55,5.75-2.36,6.9-2.95,13.52-6.26,20.07-9.67,1.66-.8,4.31-2.78,3.44,.82-.52,2.65-1.23,5.29-1.59,7.97-.04,.26,.18,.58,.4,.8,1.17,.1,2.37-1.03,3.46-1.45,6.78-3.53,13.23-7.43,19.72-11.28,1.52-.79,3.78-2.69,2.95,.83-.57,3.17-1.95,6.3-2,9.51,0,.06,.18,.17,.25,.15,.38-.07,.81-.11,1.1-.29,2.98-1.85,5.97-3.69,8.88-5.6,4.17-2.74,8.28-5.53,12.42-8.29,.59-.37,1.24-.99,2.04-.73,.11,3.1-1.42,6.12-1.93,9.19-.25,1.04-.37,2.11-.53,3.17-.01,.06,.14,.17,.24,.21,.6,.22,1.18-.45,1.7-.M 68,6.17-4.19,12.43-8.28,18.14-12.87,.97-.61,1.9-1.86,3.09-1.94,.16,.13,.39,.32,.36,.45-.95,4.35-1.93,8.69-2.89,13.03-.03,.14,.19,.32,.34,.45,.06,.05,.3,.04,.38-.02,.74-.47,1.49-.92,2.17-1.44,4.38-3.35,8.76-6.71,13.12-10.08,1.88-1.37,3.58-2.99,5.56-4.22,.09-.06,.29-.09,.37-.04,.18,.1,.47,.27,.46,.39-.47,4.69-3.19,10.92-3.45,15.13,2.23-.61,3.97-2.6,5.76-3.9,4.24-3.46,8.43-6.97,12.65-10.45,.93-.57,1.8-1.87,2.94-1.82-.63,5.47-2.65,10.73-3.88,16.11-.58,2.36,1.44,.79,2.28,.05,5.43-4.49,10.85-8.98,16.28-13.47,.59-.34,1.13M -1.19,1.83-1.13,.67,.33,.34,1.12,.27,1.69-1.37,5.38-2.61,10.77-4.41,16.07-.12,.58-.52,1.34,.18,1.69,.83-.02,1.73-1.12,2.44-1.56,3.63-3.03,7.24-6.08,10.87-9.11,.54-.46,1.01-1.04,1.93-1.07,.32,.4,.16,.8,.04,1.21-1.99,7.02-4.34,13.96-6.1,21.04-.03,.43,.64,.34,.84,.25,4.96-3.56,9.41-7.77,14.45-11.23,.18-.12,.57-.04,.58,.21-.32,1.26-.58,2.53-.98,3.77-2.1,6.45-4.24,12.89-6.35,19.34-.24,1.03-.93,2.21,.04,3.06,4.41-4.1,9.72-7.38,14.46-11.17,.27-.25,.69-.18,1.02-.12-1.94,9.09-6.04,18.1-9.02,27.06-.26,.72-.45,1.46-.65,2.2-.0M 2,.07,.1,.2,.21,.26,.57,.22,1.18-.42,1.68-.65,4.67-3.4,9.81-6.32,14.22-10.02l-.02,.18c.67,.63,.34,1.56,.13,2.32-1.12,3.21-2.21,6.43-3.42,9.62-2.41,6.39-4.9,12.75-7.35,19.13-.35,.92-.65,1.86-.95,2.8-.05,.36,.58,.43,.8,.38,5.4-2.93,10.48-6.45,15.85-9.46,.2-.07,.86-.07,.83,.32-4.1,12.75-9.66,25.14-14.94,37.49-.17,.41-.32,.83,.1,1.33,5.92-2.57,11.47-5.96,17.29-8.78,.21-.09,.57-.15,.75-.07,.16,.08,.26,.37,.24,.56-5.48,14.59-11.98,28.79-18.51,43.01-.84,2.1,1.14,1,2.15,.66,5.61-2.32,11.13-4.87,16.8-7.03,.36-.16,.67,.32,.6M 3,.57-6.94,16.71-14.77,33.01-22.93,49.3-1.63,3,.75,1.67,2.49,1.27,5.36-1.73,10.72-3.48,16.09-5.2,.6-.13,1.69-.61,2.08,.03-4.33,10.56-9.78,20.72-14.85,31.02-4.61,9.19-9.56,18.25-14.22,27.43-.34,.72,.5,.97,1.1,.79,6.38-1.29,12.72-2.79,19.09-4.15,.75-.16,1.62-.69,2.27-.2,.87,.65-.09,1.36-.35,2.01-10.94,22.01-22.9,43.52-35.06,64.89-.27,.48-.44,.99-.63,1.5-.09,.24,.09,.44,.42,.45,.67,.03,1.35,.06,2-.01,7.57-.85,15.14-1.79,22.72-2.53,12.48-23.41,24.54-47.14,35.3-71.28-.63-.61-1.31-.49-1.94-.35-3.24,.7-6.48,1.44-9.72,2.16M -3.24,.71-6.48,1.43-9.73,2.14-.53,.11-1.06,.11-1.63-.29,9.54-20.14,19.47-40.17,27.57-60.88,.02-.09-.39-.35-.53-.32-.77,.16-1.54,.35-2.28,.59-5.89,1.84-11.68,3.96-17.61,5.62-.4,.15-.68-.42-.63-.58,.29-.83,.63-1.64,1-2.45,6.54-14.47,12.77-29.02,18.52-43.7Zm-81.15-144.78h0Z"/><path class="cls-2" d="M378.87,529.22c.56-.16,1.04-.01,1.51,.21,4.55,1.9,8.89,4.8,13.7,5.88,.39-.7,.2-1.34,.08-1.97-.92-4.78-1.9-9.56-2.78-14.35-1.1-7.44-2.95-14.9-3.32-22.39,.02-.11,.43-.3,.59-.26,4.19,1.34,8.14,3.32,12.24,4.9,.71,.17,1.84,.99,2M .41,.26-.03-4.81-1.07-9.64-1.45-14.45-.95-8.89-1.83-17.8-2.27-26.73-.02-.42,.12-.84,.23-1.25,.01-.06,.25-.14,.35-.11,5.13,1.3,9.86,4.34,15.18,4.98l-.09-.08c.77,8.78,.97,17.64,1.92,26.42,.46,4.72,.97,9.43,1.48,14.15,.1,.96,.11,1.94,.66,2.84l.16-.13c-3.92,.15-7.86-2.3-11.67-3.25-.99-.34-1.97-.69-2.96-1.03-.29-.1-.84,.24-.83,.5,.75,8.47,2.28,16.88,3.78,25.28,.75,3.71,1.33,7.45,1.96,11.18,.24,1.53-.35,1.87-1.77,1.33-2.92-1.09-5.83-2.2-8.75-3.31-.92-.15-3.78-2.06-4.15-.87,.86,7.18,3.12,14.17,4.61,21.26,.95,4.64,2.68,9.1M 9,3.27,13.87-1,.17-1.67-.22-2.36-.5-3.35-1.37-6.68-2.78-10.02-4.17-.96-.29-1.91-1.06-2.93-.7,0,0,.15-.17,.15-.17-.31,.91,0,1.8,.26,2.68,2.75,10.09,6.04,20.06,9,30.12-.46,.62-1.51,.05-2.09-.14-4.35-1.93-8.67-3.92-13.01-5.86-.17-.07-.48,.05-.7,.13-.1,.03-.2,.19-.18,.27,.21,.84,.41,1.69,.67,2.52,2.66,8.34,5.76,16.58,8.79,24.83,2.12,4.92,.69,3.72-2.98,2.03-3.78-1.87-7.54-3.75-11.32-5.62-.53-.16-1.21-.68-1.76-.44-.09,.07-.2,.19-.18,.27,.29,.94,.56,1.88,.92,2.8,3.22,8.1,6.46,16.19,9.68,24.28,1.22,3.02,.17,2.37-2.08,1.36-M 3.82-2.02-7.63-4.04-11.42-6.09-3.74-2.02-4.3-2.25-4.35-1.89-.19,1.33,.67,2.46,1.16,3.67,2.84,7.07,6.06,14.03,9.39,20.96,.14,.29,.32,.59,.08,.9-.34,.42-1-.02-1.39-.1-6.1-3.07-12.42-5.87-18.09-9.65-.01,.25-.07,.28-.18,.09l.28-.03c-1.16,1.03,.25,2.48,.6,3.62,2.8,5.71,5.62,11.42,8.44,17.12,2.05,3.75-.24,2.24-2.42,1.11-5.53-2.88-10.9-5.96-16.2-9.1-.54-.19-2.75-1.83-2.89-.91,2.58,6.49,6.28,12.57,9.26,18.9,.4,.79,.72,1.61,1.06,2.42,.03,.08-.07,.2-.15,.28-.06,.06-.22,.13-.27,.11-.81-.38-1.64-.73-2.41-1.16-7.55-4.02-14.6-9.M 16-21.99-13.05-.68,.56,.06,1.38,.26,2.03,2.91,5.79,5.84,11.58,8.76,17.37,.3,.6,.59,1.2,.87,1.81,.03,.07-.05,.23-.11,.25-1.13,.3-2.05-.81-3.02-1.25-8.28-5.11-16.33-10.55-24.41-15.94-.31-.23-.99-.69-1.28-.18,.1,.52,.15,1.06,.38,1.54,2.92,6.15,5.92,12.27,9.05,18.32,.2,.4,.41,.8-.03,1.3-11.14-6.7-21.54-14.54-32.13-22.04-1.57-.39-.35,1.42-.12,2.13,2.74,6.19,5.75,12.27,8.33,18.52,.05,.39-.6,.37-.79,.3-4.74-3.1-9.22-6.63-13.8-9.95-7.18-5.37-14.43-10.69-21.36-16.27-.69-.45-1.31-1.27-2.22-1.13-.06,0-.18,.2-.15,.28,.28,.83,.M 55,1.66,.89,2.48,2.19,5.32,4.4,10.63,6.59,15.94,.16,.75,1.07,1.71,.4,2.35-9.6-6.29-18.46-14.22-27.44-21.37-5.13-4.27-10.21-8.59-15.31-12.89-.37-.31-.72-.66-1.3-.7-.08,0-.26,.08-.26,.13,1.62,6.52,4.39,12.84,6.41,19.29,.06,.47,.57,1.14,.25,1.55-.22,.04-.55,.11-.67,.02-.9-.65-1.79-1.31-2.63-2-9.96-8.19-19.65-16.58-29.14-25.11-6-5.39-11.91-10.85-17.87-16.27-.42-.39-.78-.88-1.72-.76,.93,6.06,2.89,12,3.68,18.07-.75,.11-1.14-.16-1.5-.49-13.66-12.25-27.17-24.79-40.26-37.53-5.81-5.66-11.51-11.39-17.25-17.11-.7-.61-1.19-.54-M 1.27,.2,.64,5.79,1.38,11.58,2.07,17.36,.04,.31-.04,.64-.1,.95-.07,.15-.5,.24-.64,.15-17.87-16.53-34.81-34.26-51.59-51.8-5.37-5.66-10.64-11.39-16.01-17.06-.95-1-1.39-2.02-1.38-3.27,.04-6.14,0-12.28,0-18.42,.27-1.41,1.56-.24,2.01,.4,18.57,20.64,37,41.16,56.55,60.99,2.49,2.54,4.99,5.08,7.52,7.6,.2,.2,.67,.22,1.08,.35-.08-6.31-1.34-12.47-1.83-18.75,0-.14,.29-.3,.48-.41,16.11,15.82,31.85,32.87,48.62,48.61,2.58,2.49,5.24,4.92,7.86,7.38,1.32,.93,.95-1.3,.75-1.97-1.3-6.26-3.66-12.72-4.3-18.93,.71-.05,1.3,.74,1.84,1.11,4.15M ,3.97,8.25,7.96,12.41,11.92,10.83,10.32,22,20.39,33.32,30.36,.55,.42,1.07,1.07,1.86,.94-1.35-6.29-4.03-12.73-5.87-19.06-.26-.82-.66-1.66-.17-2.52l-.06,.1c.73,.1,1.11,.57,1.56,.96,12.63,11.29,25.31,22.36,38.6,33.06,.61,.47,1.25,1.3,2.18,1.18,.32-.68-.17-1.27-.39-1.86-1.19-3.2-2.47-6.37-3.68-9.56-1.17-3.09-2.29-6.19-3.41-9.29-.07-.18,.06-.41,.1-.62,.93,.02,1.54,.54,2.18,1.13,2.81,2.32,5.61,4.65,8.45,6.95,8.55,6.62,16.69,14.05,25.84,19.92,.37-.45,.17-.84,0-1.24-2.15-4.99-4.3-9.97-6.41-14.96-.73-1.73-1.35-3.49-1.98-5.2M 4-.04-.12,.19-.33,.34-.47,9.91,6.89,19.42,14.94,29.66,21.81,.49,.32,1.29,1.18,1.94,.69-1.67-5.12-4.42-9.89-6.48-14.87-.95-2.12-1.83-4.27-2.71-6.41-.07-.17,.12-.4,.18-.6,.52,.05,.96,.23,1.36,.56,6.99,4.9,13.96,9.81,20.96,14.7,1.68,1.04,3.36,2.75,5.36,3.13,.08-.07,.18-.21,.15-.28-.32-.82-.63-1.64-1-2.44-2.72-5.96-5.46-11.92-8.18-17.89-.19-.65-.91-1.47-.29-2.05,7.41,4.18,14.64,9.52,22.02,14.04,.61,.32,1.24,.97,1.99,.64,.33-.33-.2-1.09-.31-1.51-3.11-7.22-6.75-14.25-9.45-21.63,0-.2,.5-.61,.78-.41,6.41,4.4,12.81,8.6,19.7M ,12.36,1.94,.97,1.7,.06,1.08-1.47-3.21-7.76-6.43-15.52-9.64-23.29-.2-.81-1.11-1.99-.69-2.75,.35-.21,.75-.03,1.04,.15,5.84,3.86,11.85,7.46,17.8,11.16,.33,.15,1.15,.55,1.35,.17-.02-.31-.03-.62-.14-.91-1.51-3.91-3.07-7.8-4.56-11.71-2-5.25-3.95-10.51-5.91-15.77-.08-.45-.49-1.22-.13-1.55,.21-.08,.53-.19,.67-.12,5.08,2.79,10,5.85,15.04,8.72,.75,.32,1.6,.97,2.43,.94,.43-.39-.12-1.33-.2-1.84-3.42-9.83-7.38-19.55-9.94-29.57,.11-.87,1.5,.12,1.95,.23,4.83,2.55,9.47,5.43,14.48,7.62,.27,.12,.61-.06,.59-.29-2.72-10.97-6.71-21.67M -9.38-32.67-.07-1.64,2.6,.29,3.26,.55,3.66,1.81,7.33,3.62,11.01,5.41,.52,.07,1.85,1.04,2.02,.2-1.21-6.98-3.5-13.92-5.02-20.89-.98-4.01-1.86-8.04-2.71-12.07-.2-.93-.57-1.9-.07-2.86l-.08,.08Z"/><path class="cls-2" d="M187.62,673.04c-.45,.45-.59,.97-.47,1.51,.42,1.91,.85,3.81,1.3,5.72,.84,3.6,1.69,7.19,2.52,10.79,.02,.09-.08,.27-.15,.28-1,.25-1.74-.81-2.51-1.28-13.39-10.92-26.78-21.85-39.64-33.18-6.43-5.66-12.82-11.35-19.23-17.03-.86-.56-1.54-1.82-2.67-1.64-.07,0-.18,.16-.18,.24,.14,5.82,1.35,11.57,2.03,17.35,.1,.77-.M 07,1.17-.45,1.06-26.11-21.17-50.35-45.1-74.35-68.36-.31-6.61-.11-13.18-.2-19.78,0-.41,.17-.83,.3-1.23,.02-.05,.29-.12,.37-.08,22.96,22.16,44.92,45.4,68.86,66.73,3.38,3.31,2.75,.61,2.5-2.27-.66-4.81-1.37-9.61-1.61-14.46-.02-.27,.18-.41,.51-.39,13.53,11.45,26,24.58,39.68,36.08,6.54,5.73,13.15,11.41,19.73,17.1,.7,.46,1.82,1.83,2.18,.65-1.12-4.98-2.27-9.95-3.39-14.93-.17-.73-.23-1.48-.32-2.23-.01-.09,.1-.28,.15-.28,1.36,.06,2.2,1.48,3.27,2.19,8.9,7.8,17.91,15.52,27.14,23.06,7.06,5.77,14.27,11.44,21.42,17.14,.49,.29,1.0M 4,.84,1.64,.76,.1-.05,.23-.19,.21-.26-.83-2.71-1.66-5.43-2.51-8.14-.82-2.61-1.66-5.22-2.45-7.83-.08-.25,.1-.55,.16-.83,.35,.14,.78,.22,1.04,.43,4.69,3.71,9.35,7.45,14.05,11.16,10.11,7.65,20.03,15.99,30.84,22.75,.35-.4,.22-.79,.04-1.2-2.18-4.98-4.35-9.96-6.51-14.94-.57-1.32-1.09-2.66-1.59-4-.04-.11,.18-.32,.33-.44,.05-.04,.28,0,.37,.06,12.51,8.98,24.98,18.22,38.03,26.57,.25,.16,.66,.49,.93,.17,.18-.2,.1-.63-.03-.9-2.65-5.41-5.33-10.82-8-16.22-.44-1.1-1.42-2.11-1.12-3.34,1.08,.15,1.68,.76,2.38,1.25,10.3,6.92,20.66,14M .09,31.56,20.15,.09-.31,.26-.54,.19-.7-.54-1.1-1.12-2.19-1.69-3.28-2.7-5.16-5.41-10.32-8.11-15.49-.21-.39-.36-.8,.1-1.18,8.58,4.84,16.69,10.55,25.53,15.25,.99,.56,2.01,1.07,3.03,1.59,.29,.15,.53,.07,.65-.16,.05-.09,.13-.21,.09-.28-.34-.7-.67-1.4-1.05-2.09-2.91-5.33-5.83-10.65-8.75-15.97-1.93-3.34,.65-1.69,2.3-.7,6.67,4.02,13.71,7.62,20.65,11.34,.55,.3,1.96,1.01,2.09,.54,.32-.75-.54-1.4-.78-2.07-2.88-5.1-5.77-10.2-8.64-15.3-.28-.72-2.53-3.86-.5-3.18,6.57,3.39,13.15,6.74,19.74,10.1,.65,.22,1.42,.81,2.11,.66,.09-.06,.M 22-.2,.19-.26-.27-.6-.55-1.21-.87-1.8-2.83-5.12-5.67-10.23-8.5-15.36-.47-1.38-2.47-3.15-1.15-4.49l-.12-.05c5.79,3.78,12.55,6.23,18.9,9.22,1.62,.27,.51-1.42,.15-2.12-2.96-5.66-5.93-11.31-8.87-16.98-1.31-2.84-2.13-3.88,1.53-2.23,4.89,2.03,9.67,4.31,14.63,6.18,2.11,.43-.1-2.48-.34-3.3-3.14-6.18-6.16-12.4-8.92-18.69-1.12-2.99,.71-1.62,2.37-1.03,3.81,1.59,7.5,3.46,11.38,4.89,.82,.25,1.69,1.01,2.52,.35,.64-.51-.11-1.2-.35-1.78-3.43-8.72-7.41-17.27-10.56-26.08,.05-.35,.38-.62,.8-.44,4.77,1.7,9.33,3.93,14.17,5.45,.45,.13,.M 98-.22,.82-.71-1.63-4.44-3.32-8.86-4.94-13.3-1.75-5.4-4.26-10.63-5.4-16.17-.03-.24,.28-.4,.57-.33,3.87,1.14,7.59,2.73,11.41,4.04,.76,.1,2.35,1.11,2.72,.05-2.62-9.68-6.11-19.17-8.57-28.87-.23-.84-.36-1.69-.52-2.54-.05-.24,.59-.57,.9-.47,4.21,1.44,8.46,2.78,12.69,4.15,.32,.1,.89-.22,.85-.47-2.04-8.66-4.24-17.3-6.14-26-.53-2.33-1.05-4.66-1.55-6.99-.11-.51-.21-1.04,.24-1.5,4.03,.86,7.78,2.38,11.77,3.41,.68,.2,2.18,.43,2.21-.57-1.4-8.86-2.95-17.7-4.34-26.56-.47-2.99-.76-6-1.11-9-.1-.86-.2-1.72,.13-2.56l-.16,.13c4.95-.24M ,9.87-1.51,14.66-2.6l-.14-.08c1.22,3.8,1.11,7.86,1.69,11.78,1.07,8.84,2.15,17.74,4.04,26.45l.07-.08c-4.44,1.22-8.83,2.56-13.4,3.45-.69,.13-1.05,.64-.92,1.24,2.27,11.22,4.63,22.48,7.76,33.53l.14-.13c-1.07,.32-2.14,.17-3.17-.09-2.95-.74-5.89-1.52-8.84-2.26-.61-.09-1.78-.42-2.11,.26,2.18,10.41,5.97,20.48,8.95,30.71-.41,.47-.9,.54-1.45,.4-3.32-.88-6.63-1.76-9.95-2.65-.74-.1-2.48-1.05-2.72,0,2.94,9.2,6.66,18.14,9.91,27.24,.28,.79,.85,2.13-.64,1.91-3.69-.98-7.31-2.16-10.96-3.26-.71-.21-2.55-.99-2.52,.23,3.09,8.27,6.55,16M .37,10.28,24.44,.36,.78,1.31,2.37-.31,2.19-4.23-.96-8.28-2.54-12.44-3.76-2.8-.87-2.05,.29-1.21,2.18,3.12,6.69,7.18,13.3,9.83,20.04-.81,.5-1.77-.07-2.59-.25-4.56-1.55-9.12-3.13-13.67-4.7-.18,.26-.44,.47-.39,.61,.25,.72,.52,1.44,.9,2.12,3.33,6.23,7.07,12.27,10.18,18.6-.29,.78-1.4,.17-1.97,.04-4.86-1.84-9.72-3.69-14.56-5.56-.74-.29-1.45-.57-2.28-.33,.02,0,.33-.04,.33-.04h-.3c3.42,5.86,6.85,11.71,10.27,17.56,2.32,3.62,2.06,3.95-1.92,2.26-5.11-2.18-10.21-4.37-15.32-6.55-1.33-.42-2.29-.92-1.4,1,1.95,3.31,3.91,6.62,5.9,9.M 91,1.64,2.71,3.33,5.41,4.97,8.12,.22,.49-.38,.81-.81,.65-7.65-2.82-14.61-6.95-22.03-10.07-.58,.81,.33,1.62,.63,2.39,2.91,5.09,5.98,10.12,9.19,15.1,.43,.66,.78,1.36,1.11,2.06,.05,.12-.2,.32-.37,.58-7.5-3.3-14.77-7.1-21.93-10.92-1.36-.61-2.57-1.72-4.12-1.81-.24-.02-.28,.5-.05,.89,3.49,5.83,7,11.64,10.49,17.47,.23,.41,.73,1.21-.03,1.28-10.42-4.42-19.87-10.93-29.84-15.88-.62,.78,.51,1.87,.8,2.67,2.74,4.8,5.5,9.59,8.25,14.39,.3,.81,1.49,1.84,.92,2.64-.02,.03-.25,.04-.33,0-10.02-5.26-19.69-11.33-29.27-17.23-1.58-1-3.18-1M .99-4.79-2.96-.15-.09-.57-.08-.66,0-.14,.14-.19,.42-.12,.59,.36,.81,.76,1.61,1.18,2.4,2.66,5.06,5.32,10.12,7.99,15.18,.26,.5,.6,.97,.18,1.55-14.24-7.67-27.14-17.67-40.79-26.34,0-.03,.03-.06,.04-.1-.47,.62-.24,1.25,.02,1.86,1.76,4.76,4.42,9.6,5.74,14.33-.23,.06-.57,.16-.69,.08-1.89-1.21-3.77-2.42-5.62-3.67-13.05-8.82-25.67-18.03-38.05-27.45-1.1-.7-4.44-3.88-3.27-.43,1.37,4.16,2.78,8.3,4.14,12.46,.27,.82,.39,1.67,.57,2.51-.01,.2-.45,.32-.61,.23-18.72-13.63-36.95-27.69-54.36-42.71,.06,.25,0,.29-.16,.11l.29-.05Z"/><patM h class="cls-2" d="M924.94,209.92c-.66-.26-1.33-.14-1.96,.01-2.05,.51-4.11,1.04-6.14,1.6-9.42,2.42-18.74,5.64-28.21,7.65-.51-.12,.43-1.1,.61-1.31,8.89-8.54,17.9-16.98,26.9-25.41,.4-.54,1.58-1.08,1.1-1.81-.55-.27-1.33,.14-1.92,.21-8.96,2.34-17.91,4.69-26.87,7.03-1.66,.43-3.33,.86-5.01,1.26-.18,.04-.44-.11-.64-.21,9.93-10.37,21.57-19.8,32.08-29.83,.71-.65,1.37-1.32,2.04-1.99,.28-.36-.36-.54-.6-.56-9.99,2.04-19.98,4.44-29.85,6.9-.64,.07-1.76,.46-2.3,.1,11.4-11.84,24.9-22.62,37.33-33.86,1.02-1.07,2.6-1.8,3.05-3.24-9.74M ,1.06-19.46,3.63-29.18,5.24-.59,.09-1.27,.34-1.75-.15-.07-.05-.06-.24,0-.31,15.26-14.51,32.61-27.58,47.65-42.05-.05-.13-.39-.29-.58-.27-3.87,.43-7.73,.88-11.6,1.33-5.33,.48-10.64,1.57-15.99,1.58-.02-.24-.15-.52-.03-.64,.75-.76,1.52-1.51,2.34-2.22,17.08-14.73,34.38-29.2,51.75-43.62,3.35-2.79,2.47-2.38,6.96-2.4,6.6-.04,13.21-.07,19.81-.09,.95,.13,2.26-.32,2.91,.52,.05,.07,0,.23-.07,.3-.61,.57-1.22,1.14-1.87,1.68-16.54,13.57-33.11,27.11-49.47,40.88-.67,.61-1.63,1.09-1.6,2.09,7.88-.2,15.99-1.69,23.93-2.33,1.54-.03,3.25M -.58,4.72-.28,.06,.08,.08,.25,.01,.31-.57,.59-1.11,1.2-1.75,1.74-8.44,7.12-16.91,14.2-25.32,21.33-5.73,4.86-11.4,9.77-17.09,14.66-.45,.48-1.26,.84-1.06,1.58,.52,.26,1.35,.07,1.95,.02,9.2-1.62,18.4-3.25,27.6-4.88,.51-.09,1.03-.17,1.52,.1-.03,.73-.75,1.12-1.28,1.58-5.21,4.51-10.47,8.99-15.65,13.52-6.82,5.96-13.59,11.96-20.38,17.95-.35,.44-1.38,1.02-1.24,1.57,.05,.08,.2,.18,.29,.17,1.05-.15,2.11-.28,3.13-.5,7.93-1.71,15.85-3.45,23.77-5.16,1.69-.36,3.4-.65,5.11-.94,.2-.03,.59,.08,.65,.2,.08,.16-.02,.44-.17,.59-.86,.83-M 1.76,1.63-2.66,2.43-8.44,7.55-16.89,15.1-25.32,22.65-1.52,1.36-2.98,2.78-4.45,4.18-.29,1.16,2.69-.04,3.3-.08,10.2-2.41,20.4-4.82,30.6-7.23,.41-.16,1.67-.11,1.38,.5-8.15,7.95-16.76,15.45-25.07,23.24-.84,.9-2.61,1.9-2.66,3.07,11.2-1.79,22.39-5.46,33.58-7.9,1.23-.14,2.59-.99,3.78-.49,.05,.02,.03,.23-.04,.3-.63,.69-1.25,1.39-1.94,2.05-6.47,6.21-12.95,12.41-19.42,18.61-.91,.96-2.05,1.66-2.51,2.94,1.41,.24,2.63-.29,3.96-.61,10.98-2.95,22.15-5.39,33.25-8.02,.84-.11,1.84-.58,2.62-.07,.07,.04,.07,.23,0,.3-.39,.44-.79,.87-1.M 21,1.29-5.92,5.87-11.84,11.74-17.75,17.62-3.15,3.09-1.31,2.42,1.7,1.76,12.9-2.97,25.87-6.17,38.95-8.36,.22-.02,.48,.26,.37,.46-5.3,5.88-10.93,11.47-16.35,17.23-.49,.51-.91,1.06-1.34,1.6-.06,.08-.06,.27,0,.31,.19,.11,.46,.26,.64,.23,3.14-.6,6.27-1.24,9.41-1.84,7.85-1.52,15.7-3.05,23.56-4.52,3.8-.71,7.64-1.3,11.46-1.93,.24-.04,.63,0,.74,.12,.25,.28,.07,.59-.17,.86-4.97,5.64-10.15,11.11-14.99,16.85-.22,.31,.36,.62,.55,.63,11.79-1.64,23.47-3.88,35.31-5.34,4.52-.54,8.99-1.51,13.53-1.78,.12,0,.34,.04,.36,.1,.07,.19,.17,.M 43,.07,.58-4.07,5.5-8.77,10.54-12.8,16.07-.11,1.21,2.21,.48,2.97,.56,17.07-2.01,34.17-3.83,51.32-5.02,.34-.03,.7,.42,.56,.68-.16,.3-.29,.61-.48,.89-3.7,5.25-7.36,10.52-11.04,15.78l-.04,.03c-18.78,1-37.44,3.36-56.14,5.23-.35,.02-.79-.44-.64-.67,.45-.66,.87-1.33,1.36-1.97,2.97-3.85,5.96-7.68,8.94-11.53,.34-.67,2.33-2.38,.92-2.65-11.3,1.15-22.55,3-33.76,4.83-5.4,.88-10.81,1.77-16.22,2.64-.18,.03-.44-.14-.63-.26-.07-.04-.06-.23,0-.31,.47-.65,.92-1.31,1.44-1.93,4.02-5.04,8.95-9.74,12.49-15-.19-.11-.45-.26-.64-.23-2.11,.M 35-4.21,.7-6.3,1.1-7.85,1.5-15.71,2.98-23.54,4.55-4.7,.94-9.35,2.02-14.02,3.03-.77,.17-1.55,.4-2.35,.05-.08-.72,.54-1.19,1.01-1.7,4.28-4.7,8.57-9.39,12.86-14.09,.7-.97,2.14-1.69,1.94-3.02,0,.01,.02,.25,.02,.25l-.02-.18c-13.95,2.71-27.73,6.19-41.51,9.52-.59,.07-1.37,.37-1.92,.09-.06-.07-.07-.22-.01-.29,.49-.63,.94-1.29,1.5-1.88,5.52-5.97,11.56-11.53,16.8-17.74,.06-.78-1.53-.16-1.98-.15-9.43,2.2-18.74,4.7-28.07,7.16-3.44,.91-6.9,1.79-10.35,2.67-1.24-.02,.9-1.81,1.16-2.23,5.82-5.79,11.65-11.57,17.48-17.36,.84-.84,1.66M -1.69,2.47-2.55,.06-.07,.05-.27-.01-.3-.19-.11-.45-.26-.63-.23-1.56,.34-3.11,.69-4.64,1.1-7.53,2.01-15.06,4.02-22.58,6.06-3.06,.83-6.08,1.74-9.12,2.61-.5,.14-1.02,.2-1.5-.16,.41-1.04,1.41-1.8,2.25-2.62,5.36-5.26,10.76-10.49,16.16-15.73,1.89-1.83,3.81-3.63,5.72-5.44,.35-.33,.68-.67,.61-1.14,.16-.05,.38-.07,.25-.27-.26,0-.31,.12-.16,.32Z"/><path class="cls-2" d="M1007.3,858.26c4.1,1.05,8.2,2.1,12.31,3.13,.5,.12,1.5,.22,1.72-.32-2.14-10.42-5.98-20.5-8.95-30.74,.44-.47,.94-.53,1.49-.39,3.96,1.04,7.9,2.15,11.86,3.15,.38M ,.09,.88-.24,.79-.52-.32-1.04-.61-2.09-.99-3.12-2.98-8.05-5.98-16.09-8.96-24.14-.19-.6-.73-1.91,.36-1.87,4.54,.86,8.77,2.88,13.3,3.7,.16,.01,.51-.26,.5-.4-2.75-8.23-6.51-16.18-10.02-24.19-1.59-3.17-1.07-3.04,2.06-2.23,4.04,1.14,7.95,2.79,12.06,3.64,.16,.02,.54-.26,.52-.34-1.99-5.3-5-10.21-7.41-15.34-.95-2.31-2.76-4.42-3.21-6.86,0-.23,.79-.26,1.51-.04,4.89,1.47,9.59,3.47,14.48,4.91,.33,.09,.63-.39,.59-.62-2.92-6.3-6.7-12.21-9.96-18.35-.23-.72-1.76-2.2-.9-2.6,1.05-.1,2.01,.37,2.97,.71,4,1.54,8,3.09,12,4.63,1.19,.39,2M .47,1.3,3.72,.67-.12,.06-.23,.11-.33,.16l.33-.13c-4.09-6.01-7.45-12.52-11.26-18.72-.34-.57-.83-1.11-.59-1.8l-.09,.06c.53-.2,1.05-.12,1.54,.09,3.71,1.53,7.43,3.04,11.12,4.6,2.26,.96,4.47,2,6.71,2.99,.77,.41,1.67,0,1-.86-3.71-6.22-7.43-12.43-11.15-18.64-.14-.24-.03-.43,.29-.52,6.31,1.95,12.32,5.34,18.25,8.17,2.2,.97,6.68,4.13,3.58-.76-3.29-5.43-6.57-10.86-9.9-16.26-.26-.43-.23-.86,.05-.86,1.2-.06,2.15,.68,3.2,1.12,7.9,3.41,15.19,8,22.89,11.47,.67-.66-.36-1.62-.63-2.32-3.24-5.78-7.21-11.23-10.03-17.2,.29-.38,1.06,.03,M 1.41,.14,2.51,1.26,5.03,2.51,7.49,3.83,6.83,3.66,13.55,7.41,20.15,11.36,3.04,1.6,.56-1.97,.04-2.95-2.69-4.7-5.39-9.4-8.07-14.1-2.46-3.92,1.37-1.38,3.03-.46,10.09,5.94,20.24,11.82,29.98,18.13,.51,.33,1.03,.75,1.69,.52,.07-.01,.16-.19,.12-.25-.57-1.21-1.13-2.42-1.75-3.61-2.68-5.17-5.37-10.34-8.05-15.51-.04-.07,0-.25,.06-.27,.22-.07,.54-.19,.69-.12,12.77,7.52,25.08,15.93,37.23,24.34,1.01,.69,1.87,1.56,3.22,1.88,.37-.41,.21-.8,.04-1.21-1.83-4.39-3.65-8.78-5.47-13.18-.18-.59-.74-1.23-.14-1.74,15.24,9.27,29.59,20.45,43.8M ,31.03,1.07,.82,2.2,1.58,3.32,2.35,.09,.06,.34,.1,.38,.06,.14-.13,.34-.33,.3-.46-5.63-19.72-10.68-21.18,8.32-7.06,13.1,9.94,25.91,20.11,38.42,30.53,.62,.36,3.56,3.37,3.7,1.83-1.08-5.65-2.52-11.23-3.79-16.83-.04-.16,.11-.48,.25-.51,14.37,10.18,27.8,22.63,41.28,33.99,6.96,6.15,13.89,12.33,20.84,18.49,.45,.4,.95,.76,1.45,1.11,.13,.06,.58-.08,.62-.26-.11-6.09-1.53-12.18-1.86-18.3,.34-.67,1.16,.02,1.53,.31,25.1,21.79,49.42,44.45,73.02,67.82,.19,6.6,.03,13.16,.07,19.76,0,.4-.17,.81-.3,1.2-.26,.32-.78-.04-1-.22-21.88-22.5M 2-44.47-44.62-67.63-65.99-1.38-1.07-3.28-3.54-2.99-.11,.7,5.57,1.46,11.13,1.88,16.72,.03,.43-.68,.35-.87,.27-17.28-16.47-35.08-32.57-53.18-48.24-2.36-2.07-4.79-4.08-7.21-6.11-.16-.13-.48-.15-.73-.19-.46-.1-.41,.67-.31,1.07,1.18,5.08,2.37,10.16,3.54,15.24,.06,.47,.25,1.18-.04,1.55-.26-.02-.6,0-.75-.13-17.34-14.51-34.19-30.2-52.66-43.21-.17,.12-.42,.31-.39,.43,.34,1.26,.7,2.52,1.1,3.77,1.13,3.55,2.29,7.09,3.4,10.64,.19,.61,.21,1.26,.29,1.9,0,.21-.45,.32-.6,.25-14.29-11.39-28.67-22.79-43.78-33.53-.48-.35-.87-.84-1.62-M .87-.1,0-.3,.11-.29,.15,2.14,6.78,5.75,13.14,8.14,19.87,.06,.41-.56,.37-.8,.33-12.76-8.91-25.25-18.97-38.74-26.8-.3,.07-.43,.24-.33,.46,.42,.91,.83,1.82,1.27,2.72,2.47,5.01,4.95,10.01,7.41,15.02,.3,.6,.55,1.21,.82,1.82,.11,.23,.03,.41-.27,.5-.12,.04-.31,.05-.39,0-1.97-1.3-3.94-2.61-5.89-3.93-9.05-5.87-17.94-12.38-27.57-17.39-.65-.41-.32,.42,.07-.09-.56,1.09,.41,2.02,.82,3,2.83,5.89,6.58,11.47,8.88,17.56-.32,.35-.97-.13-1.32-.27-4.99-3.1-9.92-6.26-14.96-9.32-3.75-2.28-7.61-4.43-11.43-6.63-.52-.3-1-.71-1.75-.63-.58,.M 69,.18,1.2,.4,1.76,.24,.61,.66,1.18,.98,1.77,2.7,4.92,5.4,9.84,8.09,14.76,.36,.87,1.23,1.69,.56,2.45-7.78-4.45-15.59-8.81-23.61-12.97-.57-.17-1.58-1.1-2.05-.48,2.26,5.51,6.91,12.31,9.8,17.94,.3,.82,1.35,1.86,.8,2.68-.81,0-1.63-.7-2.4-.99-6.64-3.21-13.01-7.05-19.81-9.89-1.02,.1,.09,1.35,.25,1.88,2.88,5.21,5.77,10.41,8.65,15.63,.5,1.42,2.36,3.06,1.16,4.51v-.03c-5.7-3.83-12.48-6.22-18.79-9.23-.2-.09-.48-.05-.73-.06-.23,0-.32,.54-.14,.89,2.4,4.55,4.84,9.08,7.2,13.64,1.23,2.38,2.35,4.79,3.5,7.19,.08,.35-.57,.47-.77,.45-M 5.33-2.23-10.54-4.76-15.96-6.82-.61-.25-1.27-.33-1.88,0,.22,.02,.37,.04,.46-.18l-.37,.18c3.57,7.3,7.29,14.54,10.54,21.99,.18,.4,.24,.83,.32,1.26,.02,.08-.09,.23-.18,.27-.98,.41-1.89-.5-2.81-.78-4.26-1.86-8.43-3.92-12.87-5.36-.4-.12-1.04,.2-.91,.68,3.51,9.24,8.05,18.22,11.04,27.61-.16,.88-2.16-.37-2.75-.45-3.74-1.48-7.46-2.99-11.2-4.45-.46-.18-1.03-.2-1.55-.26-.07,0-.25,.16-.24,.23,3.42,10.36,7.5,20.6,10.92,30.99l.08-.12c-4.44-1.82-8.96-3.44-13.51-5.01-.58-.15-1.8-.58-1.98,.25,2.68,9.84,6.22,19.56,8.77,29.44,.2,.71,M .54,1.45,.09,2.19-1.16,.48-1.97-.31-2.93-.54-.77-.18-1.47-.53-2.21-.77-2.61-.85-5.23-1.69-7.84-2.54-.71-.23-1.41-.02-1.24,.69,2.91,10.81,5.29,21.71,7.7,32.6,.12,.52,.22,1.06-.16,1.56-.7,.14-1.29-.15-1.88-.35-4.03-1.5-8.32-2.38-12.39-3.82-2.52-11.71-5.06-23.4-8-35.01l-.1,.1Z"/><path class="cls-2" d="M1190.06,521.46c30.44,10.44,60.33,21.99,89.85,34.62,.77,.28,1.55,.11,1.38-.87-.59-4.61-1.22-9.21-1.82-13.81-.18-1.37-.53-2.75-.16-4.15,35.67,13.35,70.11,30.06,104.3,46.65,4.31,2.16,3.66,1.4,3.69,5.33,.02,5.96,.07,11.86-.M 03,17.83-1.29,.43-2.18-.35-3.26-.87-26.06-13.81-52.7-26.86-79.85-39.26-6.67-3.04-13.39-6-20.09-9-.69-.31-1.37-.67-2.22-.51-.39,.9-.09,1.75,.02,2.6,.65,4.71,1.31,9.42,1.97,14.13,.14,.9,.31,2.57-1.14,2.06-13.21-5.82-26.24-11.91-39.63-17.45-15.01-6.33-30.28-12.24-45.65-18-.72-.21-2.02-.95-2.37-.02,.78,4.93,2.52,9.68,3.68,14.54,.1,.71,.54,1.55-.11,2.1-24.39-8.84-48.61-18.34-73.71-25.46-1.83,.03-.07,2.32,.11,3.24,1.36,3.49,2.73,6.99,4.08,10.48,.18,.55,.59,1.52-.28,1.62-20.46-6.04-40.7-12.73-61.64-17.36-2.03-.09-.06,2.18M ,.21,3.08,1.73,3.39,3.48,6.77,5.2,10.16,.2,.48-.43,.81-.85,.72-16.56-4.29-33.29-8.09-50.13-11.27-.76-.15-1.58-.34-2.35,.03-.17,.58,.21,1.03,.51,1.5,2.22,3.44,4.45,6.89,6.66,10.34,.06,.26-.12,.69-.5,.69-11.9-2.29-23.88-4.37-35.94-6.11-1.25,0-9.18-1.71-9.1-.31,1.95,3.26,4.68,6.02,6.95,9.06,.24,.42,.91,.97,.71,1.44-.16,.14-.39,.38-.55,.36-3.33-.4-6.64-.85-9.97-1.25-5.6-.66-11.18-1.41-16.82-1.78-15.86-1.12-12.56-1.85-3.32,8.59,.18,.25,.58,.9,.25,1.14-1.82,.34-3.75-.14-5.61-.16-8.96-.55-18.03-1.37-27.01-.97-.18,.1-.38,.M 42-.31,.51,2.7,3.01,5.91,5.58,8.81,8.41,.57,1.42-3.46,.6-4.35,.77-7.88,.07-15.98-.39-23.75,.67-.03,.2-.09,.48,.05,.6,.9,.8,1.82,1.58,2.77,2.35,2.09,1.68,4.21,3.34,6.27,5.04,.22,.18,.2,.55,.33,.94-8.04,.63-15.91,.65-23.81,1.84-1.27,.7,1.35,1.8,1.82,2.35,2.29,1.67,4.6,3.32,6.89,4.99,.4,.29,.8,.58,.8,1.08-.57,.51-1.41,.52-2.2,.61-2.4,.25-4.82,.45-7.21,.75-3.46,.44-6.9,.96-10.34,1.45-.4,.06-.85,.2-.85,.56,0,.27,.22,.62,.48,.8,1.75,1.18,3.55,2.31,5.3,3.5,1.44,.97,2.85,1.97,4.22,3.01,.21,.16,.12,.57,.17,.9-6.02,.99-11.97M ,1.9-17.64,3.54-.06,.57,.29,.86,.72,1.13,3.26,2.25,7.4,4.11,10.29,6.69,.1,.45-.35,.55-.68,.64-4.73,1.2-9.41,2.57-14.1,3.92-.52,.15-.59,.77-.12,1.06,2.77,1.72,5.55,3.41,8.31,5.14,.95,.59,1.85,1.24,2.74,1.9,.11,.08,.07,.41-.04,.55-4.07,1.64-8.39,2.91-12.4,4.67-.64,.27-1.3,.35-1.9,0-3.87-2.16-7.72-4.33-11.58-6.5-1.22-1.01,1.03-1.52,1.71-1.9,3.59-1.46,7.29-2.73,10.83-4.31,.16-.08,.17-.35,.28-.6-3.66-2.48-7.83-4.45-11.86-6.86,5.26-2.6,10.44-3.61,15.99-5.26-.16-.35-.18-.73-.44-.9-1.24-.83-2.53-1.61-3.82-2.39-2.05-1.23-4.M 13-2.42-6.16-3.67-.23-.14-.2-.55-.32-.89,5.93-1.7,11.91-2.97,17.82-4.28,.13-.57-.2-.88-.63-1.15-2.11-1.34-4.22-2.68-6.32-4.03-.95-.61-1.88-1.22-2.82-1.84-.4-.26-.58-.71-.37-.84,6.56-2.11,13.86-2.51,20.71-3.71,.39-.87-.55-1.18-1.31-1.83-2.55-1.76-5.11-3.51-7.67-5.26-.41-.28-.77-.6-.69-1.16,7.92-1.99,16.63-1.43,24.5-3.05,.08-.16,.04-.46-.11-.59-.81-.72-1.66-1.41-2.52-2.09-2.09-1.68-4.2-3.35-6.26-5.05-.22-.18-.19-.55-.32-.95,9.48-1.04,18.83-1.2,28.33-1.47,1.07-.45-.25-1.34-.66-1.8-10.45-9.55-10.97-7.65,3.24-8.09,6.87,M .16,13.74,.31,20.61,.46,.55-.04,1.51,.21,1.76-.39-.09-1.13-1.58-2.01-2.24-2.94-1.95-2.19-4.27-4.12-6.01-6.47-.1-.5,.58-.71,1.02-.65,12.78,.06,25.49,1.7,38.22,2.44,.12,0,.36-.36,.3-.48-2.15-3.41-5.04-6.35-7.49-9.56-.3-.37-.51-.75-.23-1.2,15.35,.63,30.6,3.48,45.82,5.51,1.54-.14-.99-2.69-1.36-3.57-1.67-2.58-3.34-5.16-4.99-7.75-.27-.41-.51-1.19,.1-1.36,18.12,2.04,35.97,6.88,53.74,9.86,.52-.52-.15-1.22-.35-1.76-1.66-3.29-3.33-6.59-4.99-9.88-.32-.79-1.49-2.31,.24-2.23,21.25,4.27,42.24,9.94,62.99,15.97,.53-.44,.52-.86,.37M -1.28-1.87-4.94-3.72-9.89-5.5-14.86l-.1,.13c26.09,6.73,51.2,15.77,76.61,24.13,.47-.63,.26-1.28,.1-1.9-1.18-5.28-3.23-10.46-3.81-15.84l-.14,.05Z"/><path class="cls-2" d="M1200.1,558.57c25.84,9.54,51.27,21.49,76.07,33.36,3.11,1.51,6.25,2.96,9.38,4.44,.26,.12,.91-.17,.93-.4-.05-5.67-1.43-11.36-2.03-17.02-.07-.72-.14-1.55,.95-1.31,34.6,16.22,68.74,33.5,101.77,52.6,.37,6.57,.05,13.16,.16,19.75,0,2.51-1.07,1.65-2.75,.73-30.91-18.53-62.66-35.92-94.93-52.14-.55-.28-1.18-.48-1.8-.66-.13-.04-.52,.17-.55,.31-.3,1.29,.04,2.57,M .23,3.85,.51,4.81,1.79,9.62,1.87,14.43-.63,.65-1.67-.26-2.35-.49-22.94-12.12-46.4-23.55-70.38-34.3-3.29-1.48-6.6-2.92-9.92-4.35-.55-.17-1.65-.74-2.01-.04,.82,5.47,3.13,10.66,4.04,16.13-.25,1.25-2.2-.16-2.93-.34-22.2-10.11-44.87-19.89-68.18-28.09-.12-.03-.54,.26-.51,.35,.23,.84,.48,1.68,.81,2.49,1.6,4.11,3.49,8.12,4.89,12.31,.03,.08-.06,.23-.15,.27-.22,.08-.52,.21-.69,.15-2.56-.95-5.12-1.92-7.66-2.91-16.99-6.49-34.25-12.79-51.93-17.83-.1-.02-.47,.29-.44,.41,1.8,4.54,4.73,8.64,6.72,13.12,.06,.15-.12,.37-.23,.54-.68,.M 19-1.56-.29-2.25-.43-9.07-3.03-18.24-5.87-27.51-8.48-7.01-1.78-14-4.13-21.11-5.42-.18,.02-.48,.29-.46,.4,1.95,4.27,5.31,7.89,7.44,12.08-.56,.4-1.07,.36-1.6,.23-4.22-1.1-8.45-2.19-12.67-3.3-8.83-2.32-17.83-4.16-26.83-6-.94-.06-2.17-.62-2.97,.04,1.96,3.42,5.17,6.55,7.51,9.88,.32,.42,1.02,.91,.47,1.39-.48,.41-1.28,.15-1.93,.02-1.31-.25-2.6-.56-3.9-.83-10.38-1.93-21.01-4.35-31.52-5.19-.17,.7,.28,1.21,.77,1.67,2.16,2.34,4.33,4.67,6.49,7.02,.42,.67,1.68,1.32,1.25,2.17-5.69-.29-11.67-1.6-17.46-2.15-4.71-.45-9.66-1.51-14.3M 2-1.1-.04,.2-.13,.46,0,.59,2.68,2.86,5.63,5.5,8.41,8.27,.34,.33,.64,.69,.35,1.21-8.82-.53-17.66-1.48-26.52-1.69-.21-.01-.53,.11-.64,.25-.11,.15-.11,.44,0,.58,2.24,2.34,4.91,4.29,7.31,6.47,.73,.63,1.41,1.3,2.06,1.98,.11,.12,.01,.39-.04,.58-7.49,.49-15.32-.66-22.89,.03-.28,.02-.51,.64-.31,.81,.84,.7,1.68,1.4,2.52,2.09,2.36,1.92,4.72,3.84,7.06,5.78,.16,.13,.25,.42,.18,.58-.07,.17-.36,.33-.59,.39-1.85,.29-3.77,.21-5.64,.29-4.56,.15-9.18,.2-13.67,.93-.22,.88,.84,1.24,1.38,1.77,2.84,2.15,5.69,4.28,8.54,6.42,.39,.3,.78,.6M ,.66,1.17-5.54,.87-11.43,1.21-16.97,2.17-.27,.58-.04,.92,.39,1.23,2.87,2.12,5.74,4.24,8.6,6.37,2.19,1.52,2.85,2.2-.37,2.63-4.02,.87-8.17,1.3-12.09,2.53-1.16,.67,.68,1.42,1.13,1.92,3.22,2.45,6.62,4.71,9.71,7.31,.23,.2,.23,.57,.32,.84-3.97,1.27-7.85,2.35-11.71,3.71-2.04,.93,.9,2.06,1.58,2.83,3.65,2.97,7.53,5.77,11.05,8.89-.23,.54-.64,.78-1.15,.95-3.08,1.07-6.22,2-9.22,3.28-2.68,.89,2.03,3.24,2.89,4.31,2.89,2.41,5.77,4.83,8.65,7.25,.38,.32,.63,.68,.48,1.1-3.22,1.4-6.41,2.79-9.61,4.17-.65,.28-1.25,.2-1.83-.25-3.84-3.03M -7.69-6.04-11.54-9.05-.47-.37-1.04-.7-1.04-1.39,2.9-1.99,6.45-3.4,9.56-5.26,.6-.61-.45-1.14-.86-1.54-3.56-2.64-7.13-5.26-10.7-7.89-.49-.36-1.08-.65-1.34-1.32,2.55-1.99,6.08-2.99,9.01-4.53,2.34-1.05,2.38-1.09,.27-2.62-3.54-2.71-7.58-4.77-10.83-7.82,4.21-1.96,8.79-2.94,12.98-4.49,.16-.57-.18-.89-.6-1.18-3.18-2.17-6.36-4.33-9.54-6.5-.6-.46-1.32-.69-1.39-1.55,4.83-1.62,9.91-2.63,14.96-3.65-.02-.28,.07-.55-.06-.68-2.92-2.45-6.3-4.37-9.41-6.59-.85-.51-2.32-1.54-.59-2.01,3.03-.52,6.06-1.02,9.1-1.48,2.25-.34,4.51-.6,6.77-.M 92,1.71-.52-.1-1.5-.83-2.08-2.32-1.64-4.65-3.27-6.98-4.91-.79-.67-2.1-.96-1.94-2.2,6.61-1.08,13.14-1.35,19.75-1.81,.32-.03,.61-.59,.4-.77-2.61-2.38-5.57-4.36-8.33-6.57-.48-.37-.92-.77-1.36-1.17-.08-.07-.14-.22-.1-.29,.12-.17,.28-.44,.45-.46,7.64-.71,15.33-.75,23-.82,.43,.02,.61-.42,.39-.72-2.66-2.48-5.64-4.62-8.42-6.97-1.01-.91-2.14-1.98,.25-1.92,6.06,.05,12.13-.08,18.18,.42,2.54,.21,5.1,.18,7.66,.26,.48,.05,.59-.39,.48-.7-2.81-2.92-5.79-5.68-8.71-8.49-.31-1.08,1.43-.66,2.07-.76,5.79,.11,11.55,.7,17.31,1.2,4.15,.39M ,8.28,.87,12.42,1.29,.2,.02,.54-.12,.62-.26,.09-.16,.04-.45-.09-.59-2.53-2.8-5.09-5.59-7.75-8.27-.4-.41-1.09-.88-.65-1.39,.39-.46,1.24-.27,1.89-.2,12,1.2,23.92,2.96,35.8,4.98,1.29-.13-.47-1.79-.77-2.3-2.11-2.63-4.23-5.25-6.33-7.88-.31-.47-1.04-1.3-.24-1.61,13.71,1.99,27.36,4.73,40.8,7.91,1.25,.13,2.64,.93,3.83,.39,.06-.03,.04-.22,0-.31-2.18-4.08-5.34-7.67-7.31-11.83-.03-.11,.31-.42,.44-.41,.93,.1,1.86,.21,2.76,.41,10.52,2.29,20.97,4.8,31.28,7.65,5.34,1.48,10.66,3.02,15.99,4.53,.5,.14,1.03,.23,1.55,.27,.13,0,.45-.31M ,.41-.42-1.66-3.91-3.97-7.53-5.87-11.33-.18-.6-1.3-1.98-.3-2.24,20.87,4.87,41.02,12.58,61.32,19.06,.56-1.36-.61-2.67-.96-3.99-1.34-3.71-3.26-7.3-4.27-11.09,.29-.86,1.76-.07,2.38,.02,9.39,3.26,18.76,6.54,28.04,9.99,13.8,5.14,27.36,10.67,40.83,16.33,.46,.2,.98,.32,1.48,.45,.32,.08,.56-.05,.54-.33-.64-4.93-2.54-9.67-3.67-14.52-.19-.72-.53-1.46-.01-2.19Z"/><path class="cls-2" d="M236.98,168.26c.96-.1,1.86,.03,2.74,.37,3.64,1.38,7.29,2.75,10.95,4.1,3.63,1.16,7.03,2.97,10.81,3.57,1.72-10.71,1.56-21.72,2.69-32.54,.72-8.14M ,1.57-16.28,2.28-24.43,.05-.53,.11-1.07-.37-1.53l-.05,.02c.89-.36,1.8-.32,2.74-.14,7.88,1.32,15.65,3.34,23.59,4.2l-.09-.08c-2.76,20.32-4.83,40.72-6.47,61.16-.11,2.65-1.77,1.48-3.49,1.05-4.68-1.65-9.35-3.33-14.03-4.98-2.13-.58-4.15-1.81-6.39-1.74-1.48,17.84-1.41,35.8-2.17,53.68-.9,1.26-6.12-2.42-7.55-2.88-4.19-2.16-8.37-4.33-12.56-6.49-.99-.39-1.86-1.17-2.99-.76-.16,14.83,.1,29.71,.65,44.54,.02,1.22,.42,3.95-1.73,2.47-6.88-4.49-13.66-9.13-20.58-13.57-.44-.37-.97,.03-1.11,.45,.18,13.76,1.73,27.52,2.44,41.27-1.1,.48-1M .82-.56-2.68-1.08-6.27-4.89-12.53-9.79-18.8-14.68-4.06-3.61-2.66,.59-2.64,3.36,.74,7.84,1.49,15.68,2.26,23.52,.27,2.9,.73,5.78,.78,8.69-.44,1.25-2.27-.94-2.87-1.3-6.58-5.85-13.15-11.7-19.73-17.55-.72-.64-1.48-1.24-2.27-1.82-.12-.09-.47,.03-.78,.06,.34,8.68,1.89,17.38,2.78,26.04,.28,2.36,.57,4.72,.82,7.08-.06,.19-.53,.58-.82,.36-.65-.54-1.32-1.07-1.9-1.65-7.21-7.11-14.4-14.24-21.62-21.35-.84-.83-1.77-1.6-2.68-2.39-.06-.05-.25-.02-.38,0-.11,.02-.29,.08-.3,.12-.03,.43-.08,.86-.03,1.28,.76,6.43,1.52,12.87,2.3,19.3,.34,M 2.79,.73,5.57,1.1,8.35,.11,.82,.02,1.09-.36,1.08-.63-.02-.92-.39-1.23-.72-8.69-9.2-17.38-18.4-26.07-27.59-.56-.59-1.22-1.13-1.86-1.68-.12-.07-.59,.04-.63,.19,.08,5.59,1.09,11.16,1.56,16.74,.33,3,.69,6.01,1.04,9.01,.14,1.11-1.01,.85-1.36,.29-4.3-4.83-8.6-9.65-12.89-14.48-5.46-6.15-10.9-12.31-16.36-18.45-.94-.88-2.98-3.72-2.81-.62,.39,5.16,.82,10.32,1.21,15.48-.09,1.17,1.08,7.69-.76,6.2-11.76-13.33-23.09-27.05-34.67-40.53-1.25-1.21-.94-2.82-1.05-4.35-.02-5.39-.03-10.77-.04-16.16,.04-.64-.08-1.41,.62-1.75,.05-.04,.29,M .03,.36,.1,11.51,12.07,21.88,25.22,33.44,37.23,.12,.08,.57-.03,.61-.2,.01-4.2-.42-8.39-.68-12.58-.2-3.44-.64-6.88-.63-10.33,.18-.6,.73-.85,1.35-.21,10.02,10.51,19.59,21.45,29.79,31.79,.55,.21,.8-.25,.76-.76-.47-5.05-.96-10.09-1.43-15.14-.29-3.11-.57-6.23-.84-9.35-.04-.43-.08-.86-.04-1.29,.07-.42,.7-.87,1.07-.43,8.37,8.12,16.5,16.49,24.79,24.7,1.06,.82,1.8,2.34,3.26,2.32-.76-10.3-2.17-20.6-2.96-30.88,1.15-.37,1.79,.65,2.61,1.24,3.89,3.58,7.76,7.17,11.64,10.75,3.62,3.34,7.23,6.68,10.86,10.01,.39,.26,1.1,1.07,1.57,.76M ,.15-.16,.34-.35,.32-.53-.12-1.72-.27-3.44-.44-5.16-.85-9.56-2.1-19.1-2.38-28.68,.17-.92,1.36-.17,1.78,.19,7.59,5.94,14.82,12.31,22.54,18.08,1.01,.21,.87-.69,.89-1.39-.33-6.89-.99-13.76-1.44-20.65-.31-5.27-.6-10.54-.9-15.82-.02-.43,0-.86,.11-1.28,.24-.3,1.04-.25,1.37,.04,6.82,4.55,13.54,9.22,20.33,13.81,1.72,1.14,2.79,1.9,2.63-.93-.42-13.89-1.16-27.78-1.14-41.68,0-.3,0-.71,.49-.76,.36-.04,.81,.02,1.11,.18,3.39,1.76,6.75,3.56,10.12,5.34,3.6,1.9,7.19,3.8,10.79,5.7,.5,.26,.98,.27,1.54-.08,.25-15.69,.18-31.42,.94-47.11M -.05-1.27,.36-2.67-.37-3.79h0Z"/><path class="cls-2" d="M1148.11,1317.93c.52-.78,.61-1.64,.71-2.5,.76-6.65,1.58-13.29,2.29-19.95,1.29-12.66,2.62-25.32,3.6-38.01,.2-.88,.04-2.44,1.36-2.31,5.52,1.61,10.85,3.8,16.29,5.65,1.48,.52,2.97,1.02,4.46,1.51,1.61,.52,1.97,.36,2.05-.89,.34-5.06,.63-10.11,.75-15.18,.6-11.19,.77-22.39,1-33.59,.03-1.18,.13-2.36,.2-3.54,.28-.8,1.44-.39,2-.15,6.17,3.06,12.24,6.28,18.36,9.42,.75,.24,2.15,1.41,2.7,.46,.42-13.11,0-26.28-.43-39.4-.11-2.37-.15-4.74-.19-7.11,0-.18,.17-.37,.27-.56,.11-.2,.M 71-.16,1.11,.08,6.64,4.18,13.08,8.66,19.63,12.97,.68,.28,1.59,1.36,2.3,.7,.4-6.31-.61-12.69-.77-19.02-.34-7.53-1.1-15.05-1.41-22.57,.91-.31,1.59,.5,2.29,.95,7.08,5.44,14.01,11.09,21.17,16.42,.19,.08,.91,.15,.92-.26-.23-3.11-.42-6.23-.71-9.34-.84-8.91-1.81-17.82-2.7-26.73,.01-.38-.14-.96,.26-1.15,.12-.04,.32-.08,.39-.03,.61,.42,1.24,.81,1.78,1.29,7.42,6.54,14.72,13.2,22.21,19.67,1.5,.86,.97-1.93,.94-2.7-.33-3.22-.68-6.44-1.04-9.66-.71-6.33-1.48-12.65-2.23-18.98,0-.71-.42-1.66,.42-2.04,.05-.04,.26,0,.32,.06,8.16,7.68M ,15.95,15.74,23.98,23.56,.82,.62,1.42,1.89,2.57,1.79,.06,0,.18-.15,.18-.23-.05-1.07-.06-2.15-.18-3.21-.79-7.08-1.74-14.15-2.62-21.22,.05-2.09-1.68-7.79,1.79-3.9,9.11,9.46,17.86,19.27,27.18,28.52,.11,.07,.59-.08,.61-.25-.05-1.5-.04-3.01-.19-4.5-.7-7.08-1.54-14.16-2.24-21.24,0-.24,.43-.68,.71-.57,10.15,10.59,19.51,21.96,29.39,32.83,.7,.79,1.46,1.54,2.23,2.28,.1,.1,.46,.05,.7,.02,.07,0,.17-.16,.18-.25,.01-6.56-.89-13.11-1.23-19.67,.04-.95-.33-2.37,0-3.17,.25,0,.62-.04,.74,.07,11.57,13.02,22.62,26.52,34.02,39.7,.69,.81M ,1.37,1.6,1.37,2.63-.03,6.57-.06,13.14-.09,19.7-.16,2.41-7.18-6.95-7.99-7.51-7.77-8.8-15.54-17.6-23.32-26.39-.7-.79-1.47-1.54-2.22-2.29-.12-.07-.59,.06-.64,.19-.12,6.86,.78,13.76,1.02,20.63,.28,4.19-.83,2.61-2.9,.5-8.6-9.25-17.19-18.5-25.79-27.75-.64-.69-1.33-1.35-1.99-2.03-.2-.21-.45-.3-.7-.12-.55,.44-.29,1.21-.29,1.82,.77,8.37,1.55,16.74,2.28,25.11-1,.34-1.53-.51-2.19-1.06-8.72-8.62-17.23-17.45-26.05-25.96-.39-.26-1.02-.13-1.03,.41,.89,9.77,2,19.53,2.79,29.31,0,.3-.25,1.04-.68,.96-1.31-.63-2.26-1.85-3.37-2.75-6.3M 5-5.86-12.69-11.74-19.04-17.6-.88-.81-1.84-1.57-2.77-2.34-.24-.23-.82,.15-.86,.31,.21,7.11,1.12,14.18,1.72,21.26,.33,3.98,.71,7.95,.92,11.93,0,2.45-2.15,.15-2.95-.45-6.14-4.99-12.28-9.99-18.43-14.97-.94-.76-1.93-1.49-2.94-2.2-.18-.08-.88-.09-.89,.3,.23,9.59,1.42,19.13,1.75,28.71,.01,3.32,.73,6.69,.41,9.99-.39,.48-1.28,.1-1.7-.2-6.78-4.61-13.54-9.22-20.33-13.81-.53-.26-1.04-.85-1.67-.74-.32,.03-.47,.17-.49,.43-.16,3.86,.13,7.75,.25,11.62,.42,10.65,.92,21.32,.63,31.97-.27,.74-1.5,.16-2.01-.12-6.51-3.45-13.02-6.9-19.5M 4-10.35-2.6-1.45-2.39-.26-2.45,2.03-.25,16.26,.01,32.54-1.08,48.78l.14-.06c-7.8-2.53-15.31-5.85-23.15-8.31-.49-.17-1.14,.17-1.17,.59-1.36,19.43-2.9,38.84-4.92,58.22l.12-.11c-8.74-.93-17.25-3.52-26-4.44l.08,.07Z"/><path class="cls-2" d="M802.86,891.83l-.38,16.6c-.3,.29-.87,.74-1.22,.3-.63-1.39-1.96-10.15-3.49-9.47-3.44,3.48-6.06,7.64-9.27,11.34-1.39,1.71-2.98,3.31-4.5,4.95-.96,.48-1.18-.84-1.4-1.48-.64-2.21-1.26-4.41-1.92-6.61-.3-.5-.94-.8-1.5-.17-4.25,4.71-8.41,9.5-12.65,14.22-.71,.67-1.24,1.64-2.34,1.65-1.25-2.7-1M .37-5.66-2.72-8.31-.8,.05-1.14,.37-1.46,.72-4,4.47-8.51,8.62-12.88,12.86-.86,.75-2.91,3.34-3.47,1.24-.58-2.22-1.21-4.42-1.93-6.6-.13-.43-.89-.54-1.29-.19-5.12,4.6-9.9,9.41-15.37,13.74-.78,.45-1.5,1.54-2.5,1.16-1.84-2.38-3.24-5.2-4.93-7.74,5.33-4.78,11-9.17,15.93-14.2,.77-.62,1.37-1.54,2.47-1.55,2.12,2.11,3.38,4.86,5.26,7.1,1.08-.24,1.47-.83,1.97-1.32,4.55-4.4,9-8.87,13.18-13.5,.39-.42,.73-.9,1.61-.87,1.59,2.23,1.86,4.94,3.22,7.22,.78,.5,1.5-.61,2.02-1.06,4.22-4.85,8.35-9.8,12.61-14.62,1.64-1.39,3.18,6.9,4.32,7.95,.M 85-.16,1.19-.63,1.57-1.07,4.32-4.95,7.98-10.24,12.05-15.31,.11-.11,.44-.13,.67-.14,.57,.28,.69,1.17,1,1.7,3.31,7.93,1.63,9.54,7.34,1.46Z"/><path class="cls-2" d="M945.02,1096.09s.11-.04,.16-.06c-.01,.06-.03,.13-.04,.19l-.12-.13Z"/><path class="cls-2" d="M977.4,1211.24s.01-.05,.02-.08h.06l-.08,.08Z"/><path class="cls-2" d="M927.29,1010.48c1.57,.53,3.14,1.07,4.69,1.62-.81,.3-4.92,3.46-5.19,2.21,.16-1.28,.32-2.55,.5-3.83Z"/><path class="cls-2" d="M932.16,941.31c.08,8.97-.05,17.93-.79,26.88-4.49-1.45-9.08-2.87-13.74-4.M 25,.38-4.24,.7-8.48,.51-12.74,0-.09-.53-.29-.64-.24-4.46,2.73-7.8,6.95-12.16,9.84-.12,.08-.67-.06-.68-.14-.11-.63-.19-1.28-.17-1.92,.25-5.92,.57-11.84,.79-17.76,.11-2.91,.08-5.82,.08-8.73,0-.17-.2-.35-.32-.53-.14-.21-.69-.1-1.03,.21-2.2,2.02-4.24,4.2-6.4,6.26-1.36,1.33-2.75,2.64-4.14,3.95-.25,.28-.8-.06-.88-.25-.36-7.95,.35-15.94,0-23.9-.02-.47,.31-1.22-.58-1.34-.72-.1-1.03,.58-1.4,1-2.69,2.96-5.35,5.94-8.04,8.91-.64,.58-1.11,1.44-2.13,1.15-.17-6.35-.21-12.69-.35-19.05-.02-.95,.09-1.93-.44-2.84-.52-.75-1.5,.74-1.92M ,1.07-2.47,2.96-4.91,5.93-7.38,8.88-.55,.43-1.11,1.75-1.91,1.36-.1-.06-.21-.16-.22-.24-.06-1.07-.17-2.14-.16-3.21,.07-5.07-.65-10.11-.85-15.17,.03-.41-.68-.89-1.01-.59-2.94,3.42-5.48,7.15-8.26,10.7-.54,.56-.89,1.55-1.81,1.46-.1,0-.28-.11-.3-.2-.65-2.83-.32-5.8-.62-8.68-.18-2.48-.46-4.94-.72-7.41-.02-.18-.22-.35-.34-.52-.13-.19-.7,.05-.98,.41-3.13,3.99-5.7,8.53-9.18,12.2l.46-20.39c9.61-14.87,6.63-11.69,9.31,3.03,.59,4.15,1.9,1.32,3.26-.51,2.13-3.12,4.25-6.24,6.37-9.36,.29-.44,.7-.61,1.39-.36,.84,5.42,1.82,10.87,2.06M ,16.34,0,.31,.52,.74,.72,.64,.22-.12,.47-.21,.63-.37,2-2.38,3.72-5,5.61-7.47,.96-1.3,1.88-2.62,2.89-3.89,.15-.19,.66-.2,1.12-.32,1.02,6.53,1.26,12.89,2.02,19.41,0,.14,.34,.28,.56,.37,.55-.04,.98-.74,1.37-1.09,2.62-3.26,5.23-6.53,7.84-9.8,.29-.36,.84-.61,.97-.45,.19,.25,.43,.52,.46,.8,3.34,24.33-3.22,28.21,11.55,11.78,.42-.4,1.2-1.22,1.8-.72,.93,7.91,1,15.93,1.03,23.88,.11,.74-.28,2.37,.95,1.98,3.66-3.08,6.88-6.63,10.37-9.9,.37-.36,.8-.54,1.47-.23,.62,9.75,.11,19.56,.27,29.33,.08,.19,.6,.54,.88,.3,4.06-2.9,7.66-6.41M ,11.69-9.36,1.16-.66,1.08,1.08,1.12,1.79Z"/><path class="cls-2" d="M945.82,973.05c-2.73-.96-5.49-1.9-8.29-2.84,2.3-1.6,4.59-3.21,6.9-4.82,.32-.29,1.02-.45,1.42-.19,.57,2.53-.11,5.26-.03,7.85Z"/><path class="cls-2" d="M993.68,1141.18c-3.98,23.58-10.58,46.73-16.26,69.98-7.64,.78-15.25,2.5-22.81,3.7-.7-.53-.49-1.16-.33-1.88,1.48-4.91,3.04-9.81,4.44-14.74,4.94-17.15,9.27-34.45,13.6-51.77,.12-.75,.43-1.78-.73-1.79-5.29,1.15-10.48,2.75-15.72,4.08-1.34,.18-4.94,2.13-4.33-.54,1.44-6.03,3-12.02,4.5-18.03,3.18-13.4,6.38-26.8M ,8.63-40.37,.03-.27-.53-.57-.87-.46-6.24,2.14-12.4,4.47-18.62,6.67,3.39-17.24,7.22-34.45,9.51-51.88-.35-1.16-1.88-.04-2.6,.18-3.94,1.87-7.86,3.76-11.79,5.64-.83,.22-2.88,1.87-3.3,.61,.38-4.19,1.44-8.32,2.06-12.49,1.23-7.42,2.06-14.88,3.04-22.33,5.36,2,10.57,4.04,15.64,6.12-.84,6.63-1.75,13.25-2.56,19.88,.17,1.7,4.34-1.06,5.37-1.31,3.78-1.65,7.49-3.47,11.31-5,.5-.19,1.19,.16,1.15,.58-.2,2.04-.35,4.09-.62,6.12-1.39,10.61-3.02,21.19-4.68,31.76-.61,4.69-2.2,9.35-2.24,14.06,.25,.8,1.87-.1,2.47-.16,4.95-1.7,9.86-3.47,14.M 83-5.13,2.5-.96,1.94,1.02,1.74,2.62-3.37,19.44-7.27,38.79-11.34,58.08-.04,.23,.54,.6,.84,.53,6.24-1.22,12.4-3.58,18.85-3.1,.23,0,.46,.2,.82,.37Z"/><path class="cls-2" d="M1072.64,698.95c-1.4,.77-2.71-.42-3.97-.94-6.16-2.88-12.31-5.78-18.49-8.64-1.21-.37-7.37-3.77-4.72-.23,3.3,4.94,6.61,9.87,9.9,14.81,.98,1.61,2.13,3.21-.79,1.96-5-2.12-9.97-4.27-14.99-6.36-1.91-.8-3.88-1.49-5.86-2.18-.28-.1-.72,.08-1.25,.16,3.95,5.97,7.9,11.8,11.85,17.75,.24,.37,.46,.78-.14,1.21-6.68-2.44-13.15-5.34-20.08-7.4-.19,.19-.5,.39-.46,.49,M .19,.51,.42,1.01,.73,1.48,3.18,4.87,6.38,9.72,9.57,14.59,.51,.94,1.42,1.8,1.35,2.92-.01,.25-.44,.27-1.07,.06-4.83-1.64-9.66-3.28-14.5-4.91-.99-.22-2.02-.9-3.01-.42,.09,1,.87,1.79,1.4,2.64,3.06,4.91,6.17,9.81,9.25,14.72,.42,.67,.79,1.37,1.12,2.07,.07,.14-.12,.38-.23,.55-.7,.18-1.55-.31-2.25-.45-4.23-1.41-8.55-2.6-12.9-3.74-.38-.1-.79-.26-1.12-.01-.53,.39-.06,.78,.13,1.14,.2,.4,.46,.78,.69,1.17,2.97,5.07,5.94,10.14,8.89,15.22,.56,.97,1.03,1.98,1.52,2.98,.04,.09,.03,.27-.04,.3-.97,.49-2.03-.21-3.03-.35-3.46-.88-6.92-1M .78-10.38-2.65-.63-.16-1.32-.25-1.94,.11,0,.89,.6,1.61,1.01,2.4,3.12,6.4,6.99,12.56,9.69,19.11,.02,.15-.31,.47-.43,.45-4.34-.67-8.62-1.7-12.93-2.53-1.85,0-.07,2.08,.18,2.92,3.63,7.51,6.89,15.12,9.87,22.83-.42,.46-.93,.5-1.47,.39-4.28-.97-8.58-1.88-12.93-2.5l.1,.06c-3.16-8.39-7.06-16.48-10.79-24.64-.1-.26,.29-.75,.59-.73,3.88,.22,7.75,.63,11.6,1.12,.54,.06,1.03-.42,.83-.84-3.1-6.46-6.77-12.65-10.13-18.98-.27-.59-1.16-1.69-.05-1.91,4.43,.03,8.67,1.5,13.04,1.81,.34-.02,.52-.2,.42-.43-3.01-6.16-7.05-11.82-10.46-17.77-.M 4-.66-1.03-1.27-.88-2.08,.62-.35,1.3-.24,1.94-.12,3.78,.74,7.63,1.31,11.33,2.3,.64,.17,1.3,.29,1.95-.09-2.91-5.93-7.36-11.22-10.83-16.89-.37-.76-1.31-1.46-.94-2.35l-.06,.09c4.6,.09,9.04,2.09,13.57,2.93,.67,.03,3.15,1.09,3.13,.09-3.75-6.23-8.35-11.99-12.33-18.08,.5-.45,1.02-.41,1.52-.28,5.6,1.52,11.19,3.06,16.75,4.72,1.52-.05-.2-1.69-.5-2.31-3.17-4.38-6.36-8.75-9.52-13.14-.6-.83-1.13-1.71-1.67-2.57-.03-.05,.05-.18,.12-.23,.53-.33,1.32,.06,1.9,.15,5.41,1.64,10.81,3.31,16.09,5.22,.85,.31,1.75,.53,2.64,.77,.12,.03,.52-M .24,.49-.39-3.71-6.04-8.44-11.46-12.35-17.39-.06-.08-.07-.28-.03-.3,.21-.09,.49-.23,.68-.19,7.23,2.24,14.35,4.95,21.37,7.65,.74,.41,3.36,1.32,1.95-.63-3.87-5.42-7.75-10.84-11.62-16.26-.31-.37,.2-.65,.54-.58,5.19,1.67,10.18,3.94,15.25,5.91,3.84,1.57,7.61,3.22,11.43,4.82,.15,.05,.94-.03,.79-.39-.62-1.34-1.63-2.47-2.44-3.71-2.88-4.14-5.76-8.28-8.65-12.42-.31-.39-.8-1.17-.15-1.39,3.36,.81,6.49,2.58,9.68,3.86,7.48,3.14,14.67,6.98,22.1,10,.46-.19-.04-1.12-.18-1.46-2.14-3.48-4.32-6.94-6.47-10.41-.36-.57-.66-1.17-.97-1.76-M .03-.06,.06-.19,.14-.25,.55-.29,1.26,.24,1.8,.39,5.18,2.52,10.4,4.98,15.51,7.59,6.13,3.13,12.15,6.4,18.22,9.6,.64,.21,1.4,.92,2.06,.69,.09-.07,.21-.2,.18-.27-.24-.61-.47-1.23-.79-1.82-1.75-3.27-3.52-6.52-5.28-9.78-2.43-3.91-.46-2.77,2.21-1.38,13.71,7.07,26.68,14.97,39.84,22.63,.1,.05,.36,.07,.38,.03,.11-.17,.29-.4,.22-.55-2.16-4.86-4.37-9.72-6.45-14.61,.33-.77,1.4,.09,1.92,.29,16.78,9.5,32.47,20.24,48.68,30.43,.17,.07,.53-.14,.48-.34-.29-.94-.58-1.88-.92-2.81-1.43-3.93-2.87-7.85-4.3-11.78-.18-.51-.38-1.03,.13-1.63,M 17.57,10.46,34.16,22.77,50.72,34.5,2.39,1.74,4.76,3.49,7.16,5.22,.12,.09,.47,.01,.7-.04,.5-.67-.13-1.73-.22-2.51-1.18-4.64-2.37-9.28-3.55-13.92-.34-1.55,1.11-.89,1.84-.32,2.12,1.5,4.25,2.99,6.34,4.51,18.33,13.32,36.62,27.01,54.1,41.27,1.89,1.53,3.82,3.04,5.75,4.54,.15,.12,.54,.15,.74,.07,.23-.14,.38-.55,.31-.83-.63-4.49-1.29-8.99-1.89-13.48-.17-1.58-1.29-6.16,1.65-3.68,26.66,20.93,52.78,42.49,78,65.1,.43,6.66,.06,13.37,.17,20.06-.18,1.21-.21,1.83-1.57,.74-3.28-3-6.54-6.02-9.8-9.03-20.71-19.14-42.18-37.93-64.17-55.9M 9-.5-.3-1.35-1.24-1.85-.56,.28,5.6,1.44,11.12,2.08,16.69,.05,.54,.42,1.98-.48,1.97-18.61-14.89-36.6-30.74-55.95-45.19-2.82-2.17-5.64-4.32-8.47-6.48-.48-.37-.97-.76-1.86-.66,.82,5.76,3.1,11.32,3.86,17.1-.04,.22-.48,.62-.77,.45-13.33-10.15-26.6-20.47-40.4-30.27-4.6-3.32-9.31-6.55-13.97-9.81-.61-.36-1.22-.97-2-.77-.07,.01-.16,.19-.14,.29,.09,.42,.19,.84,.33,1.25,1.64,4.77,3.3,9.54,4.93,14.32,.06,.19-.03,.41-.08,.62-.32,.36-1.25-.22-1.64-.54-9.02-6.34-18.04-12.63-27.19-18.83-6.18-4.17-12.57-8.12-18.88-12.16-.49-.21-1.1M 7-.76-1.71-.55-.09,.06-.2,.19-.18,.26,.32,.82,.65,1.64,1.01,2.45,1.7,3.86,3.42,7.71,5.1,11.57,.17,.38,.11,.83,.12,1.25,0,.05-.21,.16-.27,.14-3.49-1.6-6.51-4.16-9.84-6.11-9.67-6.2-19.54-12.2-29.65-17.93-.76-.43-1.6-.78-2.41-1.15-.05-.02-.22,.05-.28,.11-.08,.08-.17,.21-.14,.28,.31,.71,.63,1.42,.99,2.11,1.96,3.78,3.93,7.55,5.89,11.33,.21,.44,.58,1.33-.23,1.27-11.09-6.25-22.07-12.7-33.53-18.56-.78-.41-1.64-.71-2.48-1.04-.03-.01-.27,.16-.25,.21,1.67,4.12,4.65,7.73,6.8,11.65,1.49,2.28,2.6,4.81,4.36,6.9l-.07-.07c-1.42,.87M -2.86-.8-4.16-1.28-8.84-4.71-17.86-9.19-27.06-13.43-1.27-.33-.49,1.16-.08,1.64,3.82,5.64,7.15,11.68,11.27,17.09l.04-.04Z"/><path class="cls-2" d="M329.09,759.62c1.2-1.05-.46-2.45-.81-3.57-1.86-3.58-3.71-7.16-5.58-10.73-.21-.41-.34-.8,.08-1.27,10.94,6.27,21.86,12.56,33.17,18.4,.83,.3,2.35,1.57,3.12,1.06,.32-.78-.76-1.61-1.04-2.33-2.82-4.65-5.64-9.29-8.46-13.94-.34-.77-1.22-1.48-.97-2.36,.64-.54,2.27,.9,3.04,1.15,8.72,4.69,17.69,9.06,26.73,13.34,.44,.21,.87,.51,1.45,.37,.7-.04-.48-1.57-.65-1.98-3.56-5.42-7.19-10.8-10M .48-16.38-.46-1.49,2.46,.16,2.99,.41,8,3.55,15.64,7.79,23.87,10.81,.64-.73-.24-1.38-.59-2.06-3.36-5.03-6.74-10.05-10.09-15.09-.6-1.22-1.69-2.5,.58-1.71,6.6,2.99,13.33,5.66,20.08,8.3,.7,.22,1.48,.67,2.2,.24,.06-.03,.08-.2,.04-.27-.61-.95-1.24-1.9-1.86-2.85-3.33-5.04-6.66-10.08-9.97-15.13-.08-.13,.11-.39,.21-.57,6.87,1.95,13.51,5.66,20.52,7.21,.91-.33-.86-1.97-1.05-2.55-3.45-5.59-7.54-10.87-10.59-16.67,.45-.8,1.72,.12,2.42,.2,5.11,1.65,10.14,3.54,15.28,5.07,1.87,.2,.28-1.64-.13-2.38-3.48-5.45-7.01-10.89-10.28-16.47-.M 21-.36-.17-.82-.25-1.24l-.1,.05c.68-.26,1.31-.06,1.93,.13,3.27,.99,6.52,2.01,9.8,2.97,1.51,.44,3.07,.76,4.62,1.1,.09,.02,.45-.33,.4-.44-3.29-6.27-7.31-12.19-10.55-18.44-.2-.6-1.36-1.97-.38-2.19,4.17,.68,8.18,2.09,12.29,3.03,.92,.13,1.87,.5,2.68-.16-3.48-6.86-7.2-13.62-10.66-20.5-.2-.39-.43-.8,0-1.19,.33-.3,.75-.13,1.12-.06,4.03,.87,8.07,1.63,12.11,2.43,.88,.03,.81-.63,.54-1.19-3.92-8.06-7.53-16.26-10.7-24.58,.5-.42,1.02-.45,1.56-.34,4.28,.96,8.58,1.78,12.9,2.5l-.11-.06c2.87,8.48,7.08,16.44,10.72,24.67,.18,1.24-3.79M ,.38-4.67,.44-2-.2-3.99-.47-5.99-.7-.76-.09-1.7-.53-2.23,.11-.48,.58,.18,1.23,.49,1.81,3.35,6.34,6.84,12.62,10.12,19,.13,.26-.26,.69-.62,.65-4.28-.26-8.45-1.18-12.67-1.87-1.24,.07-.43,1.17-.15,1.79,3.17,5.48,6.41,10.93,9.81,16.28,.37,.78,2.03,2.51,.13,2.49-4.2-.61-8.43-1.41-12.54-2.43-3-.68-.86,1.63-.23,2.95,3.14,4.76,6.32,9.5,9.47,14.25,.21,.51,1.71,2.12,.65,2.21-5.01-.61-9.79-2.27-14.71-3.35-.48-.12-1.03-.06-1.55-.06-.07,0-.22,.16-.2,.22,2.43,4.6,5.9,8.67,8.73,13.06,1.05,1.5,2.14,2.99,3.2,4.49,.78,.85-.41,1.03-1.M 09,.87-21.55-5-21.6-10.22-7.48,9.83,.74,1.02,1.48,2.05,2.19,3.09,.11,.16,.13,.54,.09,.56-.36,.09-.78,.21-1.13,.14-5.55-1.55-10.98-3.55-16.48-5.27-.84-.21-4.79-2.1-3.13,.3,3.38,4.65,6.77,9.3,10.15,13.95,.61,.84,1.21,1.67,1.79,2.52,.16,.24,.07,.43-.22,.53-.62,.16-1.28-.24-1.88-.37-6.87-2.47-13.79-4.8-20.56-7.5-3.77-1.39,.02,2.52,.7,3.72,3.27,4.58,6.7,9.05,9.85,13.71-.29,.13-.56,.35-.7,.3-1.13-.34-2.25-.69-3.34-1.11-6.8-2.6-13.51-5.34-20.12-8.23-1.06-.46-2.15-.87-3.24-1.3-.47-.2-.68,.46-.61,.54,3.19,5.14,6.9,9.97,10.2M 9,14.98,.58,.9,1.67,1.94,.64,2.93h.03c-.39-.62-1.19-.83-1.88-1.13-9.92-4.29-19.75-8.75-29.52-13.35-.72,.55-.29,.89,.11,1.71,2.41,3.97,4.96,7.88,7.32,11.87,.08,.15-.08,.4-.17,.59-9.44-3.55-18.46-8.87-27.45-13.41-3.13-1.67-6.31-3.29-9.47-4.92-.09-.05-.34-.06-.36-.03-.11,.18-.3,.41-.24,.56,2.07,4.23,4.49,8.29,6.69,12.45,.14,.42,.67,1.15,.3,1.51-.07,.06-.25,.12-.31,.09-.93-.42-1.87-.83-2.76-1.3-13.88-6.97-26.81-15.32-40.23-22.64-.39,.58-.11,1.07,.12,1.58,1.96,4.35,4.04,8.67,5.92,13.05,.1,.27-.06,.6-.12,1.06-16.33-9.07-M 31.94-19.21-47.29-29.41-.82-.55-1.68-1.08-2.55-1.58-.13-.08-.44,0-.64,.07-.07,.02-.13,.2-.11,.29,1.57,5.24,3.87,10.28,5.44,15.52,.03,.17-.16,.37-.29,.53-.03,.04-.28,0-.38-.05-19.29-12.07-38.12-25.26-56.35-38.75-2.13-1.52-2.05-.62-1.72,1.41,1.17,4.64,2.38,9.28,3.58,13.91,.12,.52,.35,1.09-.26,1.38-18.61-12.23-36.55-26.45-54.16-40.12-19.54-15.21-14.02-15.36-12.05,7.73-.21,1.07-1.62-.11-2.09-.45-12.61-9.87-25.14-19.81-37.38-29.98-13.27-11.02-26.18-22.28-39.09-33.59-1.97-1.78-1.85-1.49-1.86-3.71,0-5.92-.05-11.85-.07-17.M 77,0-.41-.09-.86,.36-1.18,.44-.35,.96,.25,1.3,.46,8.25,7.54,16.45,15.11,24.76,22.61,15.73,14.18,31.77,27.91,48.17,41.4,.75,.62,1.56,1.18,2.36,1.75,.1,.05,.61-.07,.64-.22-.08-6.12-1.6-12.19-2.16-18.3-.08-.43,.53-.48,.83-.37,20.5,17.05,41.15,34.34,62.66,50.4,.78,.59,1.64,1.11,2.47,1.65,.29,.19,.74-.21,.73-.45-1.33-5.6-2.78-11.18-3.99-16.81-.03-.14,.23-.33,.39-.47,13.8,9.97,27.4,21.03,41.63,30.95,4.2,3.03,8.51,5.97,12.79,8.93,.6,.41,1.3,.73,1.97,1.07,.08,.04,.27,.02,.35-.03,.09-.06,.19-.2,.16-.28-.23-.84-.46-1.68-.75-M 2.5-1.45-4.15-2.92-8.29-4.37-12.43-.71-2.09,1.1-1.14,2-.43,4.86,3.41,9.67,6.86,14.57,10.24,10.42,7.14,20.96,14.32,31.93,20.83,.09,.05,.33,.06,.38,.02,.14-.15,.34-.35,.31-.5-1.74-4.77-4.08-9.34-6.04-14.03-.04-.35-.54-.95-.06-1.19,13.91,8.18,27.75,17.34,42.04,25.5,0,0,.15-.11,.15-.11l-.22,.06Z"/><polygon class="cls-2" points="431.53 461.93 431.53 462 431.44 462 431.53 461.93"/><polygon class="cls-2" points="433.83 504.59 433.97 504.59 433.97 504.68 433.83 504.59"/><path class="cls-2" d="M439.62,542.74v.07s-.05,.01-.0M 7,.02l.07-.09Z"/><path class="cls-2" d="M592.18,614.98c-.96-1.27-1.19-2.77-2.72-3.61-2.52,4.03-3.88,8.7-6.14,12.87-.72-.1-1.04-.44-1.26-.84-1.51-2.75-3.15-5.47-4.3-8.35-.32-.81-.83-1.57-1.27-2.35-.12-.1-.59-.12-.7,.02-2.57,3.86-3.78,8.43-6.45,12.2-1.22-.53-1.45-1.93-2-3.01-1.48-3.57-2.94-7.15-4.45-10.82-1.22,.03-1.48,1.18-2,2.03-1.58,2.85-3.15,5.71-4.74,8.57-1.54,2.68-1.81,.18-2.59-1.32-1.6-4.45-3.01-8.96-4.78-13.34-.05-.13-.36-.19-.54-.28-.65,.3-.88,.82-1.18,1.29-1.75,2.79-3.5,5.59-5.26,8.37-.4,.55-.92,1.64-1.71,1M .42-2.18-4.63-3.26-9.79-5.01-14.61-.45-.75-.61-3.98-1.68-3.69-3,3.03-5.3,7.02-8.13,10.32-.68,.46-1.23-.53-1.38-1.08-1.8-6.17-3.64-12.34-5.17-18.59-.08-.6-.67-1.55-1.37-1.1-2.77,3.03-5.51,6.13-8.3,9.14-.59,.59-1.19,.45-1.46-.15-.46-1.68-.91-3.36-1.32-5.06-1.3-5.39-2.56-10.78-3.86-16.17-.28-.65-.37-2.59-1.36-2.26-3.57,2.65-6.33,6.34-10.06,8.76-.77,.18-1.03-.79-1.19-1.35-1.6-7.21-3.05-14.43-4.4-21.68-.27-1.38-.51-2.76-.81-4.14-.54-.57-1.46,.18-1.96,.49-3.28,2.4-6.36,5.04-9.75,7.27-1.9,.56-1.6-3.23-1.96-4.31-1.95-8.8-2M .72-17.75-4.26-26.58-.08-.27-.66-.53-.94-.42-.23,.1-.5,.15-.71,.28-3.14,1.9-6.78,3.08-10.25,4.51-.41,.14-1.14,.25-1.42-.09-1.02-2.29-.96-4.87-1.4-7.3-1.42-9.17-1.88-18.46-2.98-27.67-.29-1.73-2.41-.76-3.55-.49-3.82,.83-7.55,2.31-11.44,2.73-.64-14.2-2.44-28.37-2.44-42.59,4.51-.36,8.85-1.58,13.29-2.4,.68-.19,2.22-.41,2.39,.44,.57,13.32,.33,26.74,1.63,40.02,.42,1.53,7.55-1.56,8.69-2.05,1.51-.71,2.93-1.53,4.39-2.31,.65-.34,1.35-.43,1.48-.19,.15,.28,.32,.58,.34,.87,.55,11.43,1.48,22.8,2.68,34.18,.67,1.75,3.01-.79,4-1.23,M 2.37-1.6,4.71-3.22,7.07-4.83,.95-.63,3.13-2.55,3.25-.29,.97,9.88,1.9,19.78,3.7,29.56,.07,.42,.88,.62,1.26,.32,3.45-2.71,6.81-5.51,10.19-8.3,.32-.29,1.06-.24,1.21,.21,.74,2.83,1,5.75,1.36,8.65,.57,5.58,1.94,11.08,2.84,16.63,.08,.52,.38,1.01,.56,1.47,.76,.02,1.12-.29,1.45-.63,2.99-2.91,5.75-6.03,8.88-8.79,.14-.12,.49-.07,.87-.12,1.91,7.87,2.57,16.06,5.09,23.78,.71-.01,1.08-.3,1.38-.67,2.65-3.12,5.16-6.33,7.92-9.36,.32-.3,1-.29,1.13,.23,1.74,6.71,2.7,13.65,5.02,20.23,.35-.07,.71-.06,.83-.2,2.72-3.13,4.85-6.71,7.34-10.M 02,.25-.35,.52-.73,1.17-.68,.64,.73,.75,1.59,.97,2.44,1.12,4.32,2.24,8.64,3.39,12.95,.23,.84,.55,1.67,.89,2.48,.12,.16,.77,.33,.96,.07,2.71-3.53,4.61-7.58,7.28-11.13,.1-.13,.46-.15,.71-.18,.43,.12,.42,.75,.58,1.1,1.36,4.39,2.7,8.78,4.07,13.17,.21,.45,.42,1.19,.91,1.38,1.12-.27,1.49-2.01,2.16-2.87,1.61-2.84,3.2-5.7,4.82-8.54,.23-.26,.71-.9,1.13-.6,2.2,4.21,3.04,9.15,4.97,13.53,1.2,.08,1.35-.96,1.95-1.85,1.67-3.17,3.32-6.36,4.97-9.54,.31-.59,.6-1.19,1.29-1.6,.72,.58,.91,1.33,1.16,2.05,.95,2.81,1.95,5.6,3.26,8.32,.39,M .61,.51,1.59,1.34,1.74,1.15-1.02,1.59-2.85,2.37-4.19l.06,9.73Z"/><path class="cls-2" d="M592.33,639.15c-.49-.57-1.05-1.72-1.89-1-1.74,3.91-3.17,7.99-4.64,11.97-.82,.15-1.21-.15-1.63-.72-1.86-2.62-3.7-5.26-5.56-7.88-.48-.49-.96-1.71-1.8-1.2-2.14,3.6-3.15,7.84-5.22,11.5-.2,.3-.78,.15-.96-.02-2.92-3.64-4.65-8.19-7.75-11.64-.63,.3-.89,.79-1.14,1.3-1.72,3.37-3.1,6.94-5.15,10.15-.73-.35-1.05-.81-1.33-1.31-1.95-3.43-3.9-6.86-5.86-10.28-.65-.85-.8-2.13-2.05-2.22-1.97,3.01-3.58,6.27-5.5,9.31-.29,.43-.31,1.18-1.23,1.07-.76-.M 1-.82-.78-1.11-1.23-2.81-4.73-4.67-9.91-7.34-14.62-.63,.05-.96,.38-1.23,.77-1.79,2.53-3.57,5.06-5.37,7.59-.39,.55-.68,1.18-1.48,1.49-.69-.24-.9-.74-1.11-1.24-1.35-3.16-2.73-6.31-4.03-9.48-.93-2.25-1.75-4.52-2.61-6.79-.2-.52-.42-1.03-.97-1.38-.23,.09-.52,.14-.66,.28-2.44,2.7-4.79,5.47-7.2,8.2-.32,.37-.72,.62-1.37,.65-2.32-4.71-3.85-9.85-5.82-14.74-.73-1.11-1.73-7.8-3.35-6.65-2.93,2.68-5.75,5.46-8.81,8-.78,.48-1.3-.36-1.54-.97-2.33-6.86-4.7-13.71-6.68-20.64-.27-.94-.62-1.86-.98-2.78-.04-.11-.49-.21-.67-.15-3.59,1.77-M 6.66,4.51-10.31,6.18-.66,.18-.96-.53-1.09-1.04-1.55-5.46-3.13-10.91-4.61-16.38-.98-3.58-1.73-7.19-2.65-10.77-.13-.43-.78-.72-1.25-.52-2.25,.96-4.49,1.95-6.76,2.89-1.31,.55-2.65,1.04-3.99,1.54-.44,.17-1.17-.14-1.27-.54-2.67-10.08-4.46-20.36-6.6-30.54-.17-.82-.1-1.66-.14-2.5,4.48-1.3,8.88-3.54,13.46-4.21,1.72,10.34,3.75,20.64,5.89,30.91,.13,.8,.43,1.77,1.52,1.35,3.72-1.52,7.03-3.6,10.59-5.31,1.01-.24,1.19,1.95,1.48,2.66,1.73,8.08,3.7,16.1,5.91,24.07,.05,.21,.17,.41,.26,.61,.08,.19,.86,.31,1.08,.16,2.83-1.9,5.27-4.3,7M .92-6.44,.79-.45,2.16-2.49,2.88-1.06,2.22,7.43,3.89,14.97,6.44,22.33,.23,.56,.49,1.5,1.27,1.31,3.14-2.32,5.52-5.57,8.35-8.25,.34-.35,.7-.65,1.4-.6,2.69,6.87,4.16,14.39,7.26,21.06,.7,.39,1.34-.47,1.75-.92,2.29-2.79,4.37-5.72,6.77-8.42,.16-.12,.83-.18,.98,.11,.42,1.02,.84,2.04,1.21,3.07,1.67,4.54,3.32,9.09,4.97,13.64,.23,.62,.41,1.25,1.1,1.66,.68-.22,.98-.7,1.29-1.18,1.75-2.68,3.49-5.35,5.26-8.01,.43-.5,.97-1.67,1.77-1.3,2.06,4.29,3.63,8.79,5.52,13.16,1.17,2.51,1.69,4.28,3.46,.77,1.46-2.67,2.91-5.33,4.39-7.99,.26-.46M ,.45-.99,1.27-1.23,2.52,4.31,4.55,8.97,7.04,13.34,.21,.36,.91,.52,1.17,.1,1.84-3.45,3.39-7.03,5.09-10.54,.19-.4,.47-.76,1.14-.91,2.62,3.7,4.21,7.97,7.14,11.48,.68-.06,.98-.36,1.16-.8,1.73-3.82,3.06-7.86,5.12-11.52,.8,.27,1.08,.76,1.38,1.23,2.07,2.87,3.62,6.15,6.03,8.74,1.22,.21,1.47-2.05,1.95-2.87l.04,6.14Z"/><path class="cls-2" d="M670,602.28l.06-.09s.05,.03,.08,.04l-.14,.05Z"/><path class="cls-2" d="M697.61,575.54c-.09,.33-.08,.67-.26,.93-3.24,4.59-6.45,9.23-9.75,13.78-.28,.34-.97,.48-1.43,.25-2.56-1.23-4.97-2.57M -7.63-3.65-3.5,4.94-5.34,10.32-8.48,15.34-2.54-1.32-4.99-2.95-7.63-4.08-.2-.05-.58,.06-.69,.19-2.18,3.61-3.57,7.67-5.44,11.45-.65,1.19-.84,2.63-2.02,3.43-3.11-1.13-4.94-3.3-8.14-4.36-2.01,4.12-3.44,8.39-5.18,12.61-.32,.8-.5,1.65-1.34,2.42-2.27-.91-4.01-2.41-5.96-3.78l-.05-7.07c1.51-3.27,2.6-6.75,4.46-9.85,.08-.11,.55-.18,.7-.1,2.14,1.23,3.95,2.92,5.94,4.35,.39,.3,.83,.56,1.59,.45,2.55-4.77,4.6-9.85,7.23-14.59,.26-.46,.86-.61,1.29-.33,1.43,.98,2.85,1.97,4.29,2.94,.87,.4,2.03,1.81,2.97,.96,2.7-5.01,5.58-10.04,8.09-15M .11-.58-1.17-2.02-1.68-3.05-2.5-1.23-.98-2.41-2.02-3.89-2.86-1.18,.56-1.52,1.67-2.14,2.69-1.95,3.55-3.88,7.1-5.83,10.65-.49,.63-.8,1.98-1.79,1.86-2.16-1.13-3.85-3.02-5.8-4.46-.39-.32-.79-.58-1.53-.51-2.99,4.78-5.02,10.17-7.76,15.07-.73,0-1.1-.28-1.42-.63-1.15-1.23-2.29-2.46-3.45-3.69l-.04-7.28c1.99-3.59,3.76-7.3,5.91-10.8,.23-.37,.97-.32,1.28,.08,1.45,2.13,3.37,3.88,5.09,5.81,.23,.24,.82,.18,1-.11,3.21-4.98,5.74-10.28,9.11-15.17,.47,.15,.93,.19,1.15,.39,1.8,1.59,3.3,3.49,5.29,4.86,1.29,.49,1.74-1.38,2.46-2.11,2.82-M 4.04,5.64-8.08,8.47-12.12,.32-.46,.62-.94,1.14-1,2.42,1.89,4.72,3.69,7.07,5.51,.2,.44-.2,.77-.46,1.13-3.35,4.8-6.73,9.57-10.05,14.38-.24,.39-.14,.88,.3,1.16,1.78,1.15,3.56,2.3,5.37,3.42,2,1.24,2.21,.46,3.4-1.13,2.89-4.02,5.76-8.04,8.64-12.05,.33-.46,.65-.94,1.38-1.08,2.65,1.16,5.02,2.9,7.59,4.31Z"/><path class="cls-2" d="M196.48,1198.45c19.59-.23,39.32,.32,58.96-.25,5.19-.09,5.05-.3,2.78,3.32-2.94,4.84-6.18,9.53-8.95,14.47-.23,1.29,2.14,.59,2.9,.74,3.1-.11,6.19-.21,9.29-.38,12.89-.76,25.82-1.27,38.67-2.42,1.31-.11,M 2.65-.35,4.06,.02-.14,1.37-1.38,2.28-2.11,3.4-3.34,4.3-6.69,8.59-10.03,12.89-.42,.55-.79,1.12-1.17,1.69-.13,.19,.34,.69,.64,.68,13.4-.68,26.76-2.38,40.1-3.8,2.66-.3,5.34-.52,8.01-.77,.43-.04,.48,.41,.42,.72-4.93,5.94-10.39,11.53-15.5,17.34-.46,.51-1.05,.99-.92,1.74,14.79-1.07,29.49-4.03,44.24-5.65,1.48,.34-.13,1.37-.78,2.2-5.29,5.31-10.6,10.6-15.89,15.91-.94,1.21-4.53,3.63-.68,3.11,12.98-1.81,25.91-3.96,38.84-6.08,.2,0,.74,.33,.49,.62-6.83,6.86-14.09,13.31-21.08,20.02-.45,.54-3.06,2.49-1.6,2.72,12.29-1.88,24.54-3.9M 9,36.81-5.96,.55-.08,1.04,.21,.55,.75-8.17,7.49-16.6,14.71-24.86,22.1-.81,.72-1.61,1.44-2.38,2.19-.12,.12-.06,.39-.02,.58,.83,.33,2.22-.08,3.15-.11,4.9-.73,9.79-1.47,14.68-2.24,5.62-.66,11.42-2.33,16.98-2.51,.13,.91-1.07,1.46-1.69,2.04-9.37,8.04-18.75,16.07-28.13,24.1-.73,.63-1.44,1.28-2.11,1.95-.12,.12,.01,.39,.04,.67,10.55-.81,20.9-3.02,31.46-3.85,0,.32,.11,.6-.02,.71-.87,.82-1.76,1.63-2.7,2.4-10.58,8.76-21.16,17.51-31.74,26.26-.84,.7-1.67,1.4-2.47,2.13-.14,.12-.17,.43-.08,.57,.7,.5,1.83,.14,2.66,.16,4.15-.36,8.3M -.73,12.45-1.09,4.28-.38,8.57-.76,12.85-1.14,.36-.03,.81-.13,.97,.25,.15,.35-.15,.62-.42,.85-.83,.7-1.68,1.4-2.53,2.09-13.61,10.89-27.14,21.9-40.81,32.73-.9,.78-2.27,.63-3.42,.66-7.14,0-14.28,.02-21.43,.02-5.03,.24-1.35-1.89,.44-3.41,5.6-4.51,11.21-9.02,16.8-13.53,5.78-4.67,11.54-9.36,17.31-14.04,1.75-1.48,4.74-3.28,.22-2.82-8.92,.76-17.73,1.29-26.68,1.94,.07-1.5,1.76-2.09,2.7-3.08,9.7-8.08,19.41-16.16,29.11-24.25,1.65-1.54,4.67-3.33,.11-2.83-9.2,1.06-18.39,2.14-27.59,3.15-.57,0-1.39,.16-1.87-.18-.06-.09-.13-.25-.0M 8-.31,.57-.59,1.13-1.19,1.76-1.74,8.47-7.39,16.94-14.76,25.41-22.15,.65-.71,3.52-2.74,.98-2.52-11.17,1.4-22.23,3.61-33.46,4.36-1.1-.07-.21-1.11,.21-1.46,7.18-6.57,14.39-13.12,21.56-19.7,.64-.78,4.21-3.36,1.45-3.03-7.96,1.09-15.92,2.19-23.89,3.27-4.39,.5-8.76,1.36-13.18,1.52-1.51-.16,.44-1.72,.86-2.23,5.77-5.69,11.56-11.37,17.33-17.05,2.45-2.42,2.89-3-1.09-2.57-12.89,1.79-25.77,3.51-38.74,4.64-.2-.01-.75-.35-.58-.65,.77-.88,1.54-1.77,2.34-2.63,4.73-5.11,9.48-10.2,14.21-15.31,.32-.5,1.21-1.1,1.07-1.65-.16-.14-.38-.37M -.55-.36-3.88,.38-7.75,.8-11.62,1.19-9.09,.92-18.17,1.87-27.27,2.68-2.14,.19-4.29,.34-6.43,.5-.41,.03-.8-.02-1.01-.34-.22-.34,.04-.62,.25-.88,4.59-5.95,9.7-11.56,13.94-17.76,.06-.1-.21-.47-.34-.47-4.17-.15-8.31,.42-12.47,.65-12.99,.88-26.06,2.03-39.07,2.11-.97-.52,.36-1.59,.55-2.26,3-4.7,6.03-9.39,9.03-14.08,.43-.67,.79-1.36,1.11-2.07,.06-.13-.18-.47-.35-.51-3.46-.36-7,.09-10.48,.05-15.88,.33-31.8,.8-47.67,.27-.79-.37-.06-1.41,.09-2.01,2.25-5.07,4.52-10.14,6.76-15.21,.26-.59,.77-1.16,.44-1.85l-.13,.07Z"/><path clasM s="cls-2" d="M1007.42,688.18c-.81,.29-1.58,.05-2.35-.13-4.13-.94-8.26-1.91-12.39-2.84-1.44-.16-2.91-.94-4.32-.41,3.83,6.01,9.39,11.13,12.99,17.3-.65,.29-1.16,.17-1.68,.05-4.52-1.04-9.1-1.9-13.73-2.55-.42-.05-1.77-.37-1.6,.32,3.41,5.29,7.47,10.17,11.13,15.3,.33,.67,1.48,1.54,1.03,2.29-.15,.13-.5,.19-.73,.16-4.35-.69-8.72-1.3-13.09-1.85-.77-.05-1.58,.4-.86,1.18,3.26,4.7,6.54,9.39,9.8,14.08,.55,1.04,3.37,3.9,.58,3.65-4.39-.49-8.78-1.02-13.2-1.28l.09,.07c-4.07-5.7-8.14-11.4-12.21-17.1-.33-.46-.77-.9-.32-1.56,4.23-.22,8M .54,.29,12.78,.43,.34,.02,.7-.45,.54-.69-3.37-4.96-7.33-9.53-10.94-14.33-.36-.69-1.64-1.46-1.13-2.27,.16-.2,.73-.29,1.1-.26,2.15,.13,4.3,.28,6.43,.49,2.27,.22,4.53,.52,6.8,.76,.22-.01,.77-.28,.58-.61-3.78-5.15-8.08-9.92-12.08-14.91-.37-.45-.8-.87-.61-1.56,5.44,.13,10.84,1.44,16.27,1.94,.45,.07,.51-.5,.39-.69-4.24-5.12-8.52-10.23-12.87-15.27-.09-.11,.05-.38,.14-.55,.04-.07,.23-.11,.36-.13,6.08,.47,12.18,2.35,18.14,2.77,.45-.52-.05-.96-.38-1.39-1.73-2.05-3.46-4.11-5.23-6.14-.53-1-8.37-8.49-6.35-8.45,7.17,.5,14.03,2.9M 3,21.02,4.22,1.3-.32-4.26-5.81-4.8-6.75-2.21-2.58-4.47-5.12-6.7-7.69-.45-.52-1.03-1.01-1.09-1.7,.59-.38,1.21-.18,1.84-.02,6.7,1.61,13.42,3.18,19.94,5.24,.99,.31,2.04,.51,3.07,.75,.1,.02,.26-.07,.35-.14,.06-.05,.1-.18,.06-.24-.3-.48-.59-.97-.95-1.41-2.12-2.62-4.27-5.23-6.41-7.84-.56-.87-1.89-1.67-1.83-2.75,.19-.4,.68-.18,1.05-.08,5.89,1.54,11.66,3.34,17.37,5.26,3.35,1.12,6.68,2.28,10.04,3.4,.21,.07,.56,.03,.74-.07,.13-.07,.2-.39,.11-.52-2.76-4.12-6.14-7.81-8.94-11.9,.74-.38,1.25-.18,1.95,.07,6.58,2.21,13.14,4.46,19.M 54,6.98,3.99,1.57,7.98,3.11,11.99,4.65,.18,.07,.55,0,.7-.11,.14-.11,.21-.41,.12-.55-.79-1.25-1.6-2.49-2.45-3.71-1.65-2.79-4.45-5.6-5.53-8.54,.13-.25,.37-.32,.67-.21,4.83,1.91,9.72,3.72,14.46,5.74,8.13,3.34,16.1,7.05,24.08,10.55,.16-.19,.44-.39,.4-.5-.24-.61-.51-1.22-.85-1.8-1.95-3.31-3.93-6.61-5.89-9.92-.29-.48-.51-.99-.73-1.5-.03-.07,.02-.24,.09-.26,.23-.07,.54-.19,.7-.12,2.27,.94,4.54,1.88,6.76,2.89,13.07,5.7,25.6,12.59,38.31,18.53,.14-.15,.36-.39,.3-.51-1.69-3.51-3.43-7.01-5.13-10.53-.58-1.2-1.09-2.42-1.62-3.63-M .02-.16,.32-.4,.5-.34,6.57,2.78,12.76,6.44,19.13,9.63,10.46,5.52,20.7,11.28,30.85,17.16,.87,.5,1.76,.99,2.67,1.45,.14,.07,.44-.03,.64-.1,.37-.41-.26-1.35-.32-1.85-1.65-4.32-3.31-8.64-4.95-12.97-.15-.39-.26-.81,.22-1.15,21.22,11,41.16,24.15,61.3,36.87,.58,.13,1.33,.43,1.23-.44-.36-1.48-.77-2.95-1.15-4.42-1.01-3.9-2.03-7.8-3.02-11.7-.03-.27,.19-.78,.58-.65,24.73,14.98,48.65,31.67,72.16,48.28,.13,.04,.56-.12,.62-.29,.06-.21,.12-.42,.09-.63-.58-4.17-1.19-8.34-1.76-12.52,.06-1.17-1.63-6.89,.75-5.24,28.99,19.99,57.33,40.M 95,84.58,63.1,.27,6.42,.04,12.89,.11,19.32-.08,.63,.22,1.35-.38,1.82-.74,.39-2.05-1.14-2.76-1.63-17.1-14.28-34.28-28.34-52.11-41.97-8.36-6.41-16.88-12.69-25.34-19.03-.71-.44-1.39-1.22-2.32-1.03-.3,.24-.2,.84-.2,1.2,.58,5.78,2.1,11.53,2.17,17.33,0,.09-.44,.23-.64,.21-1.13-.44-2.05-1.41-3.05-2.08-21.46-16.46-43.8-32.64-66.66-47.47-1.02-.26-.52,1.3-.5,1.83,1.14,4.43,2.32,8.85,3.49,13.27,.24,.73,.41,1.45,.11,2.19-.95-.03-1.64-.49-2.35-1.05-18.89-12.67-38.08-26.52-58.21-37.2-.16,.1-.24,.39-.19,.57,1.5,4.48,3.27,8.88,4.8M 6,13.33,.23,.62,.35,1.26,.51,1.89,.02,.41-.57,.37-.83,.33-16.62-10.2-33.45-20.74-50.96-29.6-.2-.09-.57,.09-.55,.29,2.01,4.82,4.44,9.47,6.6,14.22,.07,.22-.02,.76-.36,.73-13.81-7.06-27.12-14.94-41.22-21.56-1.16-.5-2.26-1.37-3.6-1.11,0,0,.18-.14,.18-.14l-.06,.1c.06,.31,.04,.66,.2,.94,2.5,4.36,5.03,8.71,7.55,13.07l.08-.02c-1.63,.7-3.16-.9-4.64-1.42-11.24-5.28-22.43-11.55-34.26-15.55-.37,0-.35,.41,.12,1.14,1.85,2.87,3.72,5.74,5.61,8.59,1.9,2.95,2.26,3.8,1.78,3.78-1.68-.07-2.88-1.01-4.26-1.6-8.52-3.69-17.06-7.36-25.85-10M .63-4.52-1.83-2.81-.03-1.06,2.58,2.17,3.22,4.81,6.18,6.69,9.57,0,.15-.38,.37-.53,.33-.74-.24-1.5-.46-2.21-.75-7.95-3.16-16.08-6.09-24.32-8.69-.48-.11-1.06-.46-1.48-.1-.45,.38,.03,.78,.3,1.12,.94,1.18,1.9,2.35,2.82,3.54,2.76,3.57,5.5,7.15,8.26,10.73,.35,.46,.76,.9,.51,1.48l.08-.06c-.69,.19-1.31,0-1.94-.2-4.23-1.36-8.45-2.75-12.69-4.07-3-.93-6.04-1.78-9.08-2.63-.3-.08-.71,.08-1.09,.14,3.75,5.79,8.86,10.71,12.66,16.49,.19,.39-.51,.47-.72,.45-5.58-1.54-11.15-3.09-16.74-4.59-1.14-.31-2.31-.55-3.48-.79-.19-.04-.46,.13-.6M 6,.24,.09,.79,1.42,1.99,1.9,2.77,3.39,4.25,6.79,8.5,10.18,12.75,.36,.45,.76,.89,.56,1.48l.09-.06Z"/><path class="cls-2" d="M1112.89,621.47c1.23-1.22-.36-2.66-.81-3.9-1.66-3.18-3.32-6.36-4.97-9.54-.2-.39-.28-.82-.38-1.24-.02-.08,.1-.2,.19-.27,17.96,6.57,35.43,15.51,52.52,23.84,1.26,.5,5.02,3.09,3.58-.21-1.59-4-3.2-8-4.79-12-.17-.68-.79-1.54-.08-2.06,21.77,9.52,42.49,21.43,63.27,32.88,.54,.17,2.51,1.56,2.64,.65-.6-4.94-2.56-9.67-3.69-14.51-.17-.62-.19-1.27-.26-1.91-.01-.09,.07-.26,.16-.28,.24-.05,.56-.14,.73-.05,17.3M 2,9.19,34.26,19.12,50.86,29.22,7.48,4.59,14.86,9.28,22.3,13.92,.95,.59,1.93,1.17,2.93,1.71,.11,.06,.62-.1,.65-.21,.01-5.97-1.55-11.99-2.12-17.97,.32-1.34,2.03,.13,2.73,.46,30.37,18.65,60.17,38.16,88.9,59.04,.34,6.57,.07,13.15,.17,19.73,0,.43-.06,.86-.12,1.28-.01,.08-.16,.18-.26,.2-.24,.03-.53,.09-.73,.01-8.98-6.24-17.53-13.1-26.47-19.45-18.59-13.43-37.46-26.38-56.69-38.98-1.24-.82-2.57-1.54-3.89-2.28-.09-.05-.58,.17-.58,.26,.17,5.71,1.5,11.34,2.16,17.01,.29,2.31-1.01,1.47-2.3,.65-23.15-15.76-46.6-30.69-70.96-44.92-M .75-.3-2.03-1.55-2.44-.43,.59,2.43,1.21,4.85,1.85,7.27,.81,3.05,1.65,6.1,2.44,9.16-.41,1.4-2.57-.67-3.38-.98-19.39-11.69-38.88-22.91-59.05-33.39-.67-.3-1.33-.88-2.11-.55-.1,.03-.22,.19-.2,.26,.27,.83,.54,1.67,.86,2.49,1.62,4.22,3.25,8.43,4.87,12.65,.03,.08-.03,.24-.11,.27-.22,.08-.52,.2-.69,.14-2.36-.98-4.5-2.35-6.76-3.52-15.43-8.25-31.18-16.28-47.37-23.46-.18,.25-.44,.44-.39,.58,.24,.72,.51,1.44,.86,2.14,1.65,3.3,3.34,6.58,5,9.88,.3,.6,.54,1.21,.79,1.83,.03,.08-.02,.25-.1,.27-.97,.42-1.9-.52-2.8-.81-14.24-6.71-28.M 65-13.46-43.58-19.03-.16-.05-.45,.12-.65,.23-.14,.53,.63,1.51,.87,2.07,1.95,3.19,3.93,6.37,5.88,9.57,.29,.48,.45,1,.64,1.51,.02,.05-.19,.23-.26,.22-4-.99-7.65-3.11-11.53-4.52-8.28-3.37-16.7-6.51-25.22-9.48-1.07-.23-2.22-1.14-3.32-.8-.15,.1-.27,.4-.19,.53,2.25,3.59,4.92,6.92,7.37,10.39,.21,.49,1.44,1.71,.39,1.84-10.84-3.45-21.42-7.6-32.48-10.63-.61-.09-1.31-.53-1.89-.22-.2,.11-.27,.36-.14,.54,3.18,3.66,6.02,7.84,9.4,11.23l-.06-.06c-1.37,.95-3.09-.17-4.53-.45-7.92-2.41-15.92-4.65-24.03-6.62-.61-.06-1.35-.44-1.92-.12-M .07,.06-.15,.18-.12,.24,.22,.38,.43,.79,.73,1.13,2.92,3.48,6.16,6.72,8.84,10.38-.63,.26-1.14,.18-1.67,.04-6.38-1.71-12.89-3.07-19.38-4.49-1.68-.28-3.35-.97-5.06-.76-.03,.64,.42,1.05,.82,1.47,3,3.31,6.27,6.41,9.08,9.88,.24,.36-.39,.56-.61,.56-6.98-1.07-13.89-2.9-20.96-3.14-1.18,.14,.93,1.87,1.2,2.32,3.55,3.79,7.11,7.57,10.67,11.36,.27,.41,1,.91,.86,1.4-.16,.13-.39,.32-.56,.3-1.73-.2-3.46-.4-5.17-.69-4.09-.69-8.24-1.07-12.38-1.47-.89-.16-1.47,.53-.69,1.19,3.38,3.62,6.76,7.25,10.13,10.88,.87,1.15,2.38,2.04,2.59,3.51-5M .18-.03-10.46-.99-15.71-1.04-.88-.15-1.43,.58-.66,1.23,3.92,4.23,7.81,8.5,11.66,12.78,1.06,1.21,1.56,2.07-.6,1.88-4.7-.43-9.4-.44-14.12-.25l-.24-.15c-3.7-4.24-7.74-8.28-11.82-12.29-.49-.67-3.01-2.24-1.32-2.79,4.01-.47,8.06-.35,12.09-.51,.61-.05,2.38,.16,2.03-.87-3.94-4.42-8.39-8.4-12.52-12.65-.21-.22-.64-.91-.32-1.12,.38-.1,.77-.23,1.16-.24,4.58-.07,9.16-.1,13.73,.15,1.61,.24,2.22-.6,.81-1.62-3.93-3.98-7.92-7.93-12.01-11.76-2.43-2.23,3.65-1.05,4.64-1.14,4.16,.3,8.34,.36,12.47,.89,2.79,.22,.69-1.45-.21-2.43-2.8-2.75M -5.63-5.49-8.42-8.25-.55-1.12,1.25-.73,1.88-.71,5.73,.66,11.47,1.27,17.13,2.25,.51,0,3.54,.57,3.15-.29-2.69-3.56-6.25-6.44-9.28-9.72-.91-1.24,1.16-.93,1.94-.82,7.79,1.14,15.49,2.74,23.19,4.31,.24,.05,.62,.04,.76-.08,.31-.26,.04-.57-.15-.81-2.6-3.04-5.43-5.9-8.11-8.86-2.32-2.37,.4-1.65,1.99-1.39,7.44,1.49,14.78,3.28,22.05,5.24,.99,.07,6.22,2.16,5.24,.35-2.47-3.23-5.18-6.29-7.74-9.46-.36-.44-.88-.83-.83-1.41,.48-.33,1.02-.24,1.51-.12,1.93,.48,3.84,.99,5.76,1.5,8.29,2.23,16.49,4.67,24.59,7.31,1.36,.38,2.45,1.06,3.93,.M 65-2.36-3.64-5.07-6.88-7.6-10.37-.26-.48-1.03-1.25-.81-1.72,.48-.42,1.65,.16,2.25,.24,12.56,3.89,24.94,8.11,37.06,12.79,4.41,1.91,1.02-2.11,.12-3.75-1.83-2.87-3.81-5.66-5.41-8.66-.19-.38,.51-.48,.71-.48,16.01,5.67,31.95,11.67,47.06,19.1,.06-.07,.11-.13,.17-.19l-.22,.18Z"/><path class="cls-2" d="M375.73,837.52c-.7,.2-1.31-.01-1.93-.24-4.64-1.73-9.3-3.42-13.91-5.19-9.6-3.68-19.06-7.57-28.37-11.69-1.06-.47-2.14-.91-3.23-1.32-.16-.06-.46,.08-.68,.16-.08,.03-.14,.19-.11,.27,.32,.71,.64,1.41,.99,2.11,1.93,3.79,3.87,7.57,M 5.78,11.36,.07,.14-.14,.38-.26,.55-19.01-6.89-37.22-16.52-55.38-25.11-.15-.06-.46,.06-.66,.14-.33,.33,.09,1.11,.18,1.53,1.65,4.1,3.31,8.19,4.96,12.29,.1,.44,.52,1.21,.18,1.53-.21,.08-.47,.18-.67,.14-1.48-.44-2.83-1.24-4.23-1.87-19.69-9.53-38.77-19.66-57.71-30.39-1.35-.59-4.25-2.87-3.32,.43,1.17,4.2,2.35,8.4,3.52,12.61,.08,.83,.85,2.11,.1,2.72-17.63-8.61-34.77-19.33-51.62-29.32-7.49-4.59-14.88-9.27-22.33-13.9-1.1-.49-2.12-1.77-3.39-1.44-.31,2.06,.39,4.06,.64,6.09,.39,4.15,1.54,8.32,1.58,12.45-.69,.21-1.16,0-1.59-.27M -16.39-9.9-32.57-20.24-48.43-30.75-13.25-8.83-26.35-17.8-39.19-27.02-.94-.79-2.52-1.38-2.6-2.74-.12-6.25-.02-12.5-.05-18.74-.13-2.89,2.13-.86,3.32,.01,27.44,20.62,55.51,40.46,84.62,59.1,.95,.58,1.24-.77,1-1.46-.74-5.57-1.53-11.13-2.3-16.7-.02-.19,.13-.56,.2-.56,20.31,12.19,40.11,26.47,61.08,38.54,3.98,2.4,8.01,4.75,12.03,7.11,.64,.37,1.22,.86,2.12,.79,.29-.53,.12-1.05-.03-1.58-1.17-4.2-2.34-8.41-3.48-12.61-.26-.94-.43-1.9-.61-2.85-.02-.09,.08-.22,.18-.28,.79-.12,1.69,.66,2.41,.95,7.15,4.23,14.24,8.52,21.44,12.69,12M .44,7.21,25.11,14.15,37.99,20.85,.78,.29,1.56,1.09,2.42,.66,.08-.03,.14-.19,.11-.28-.18-.63-.36-1.26-.6-1.87-1.61-4.11-3.23-8.21-4.85-12.32-.16-.4-.45-.8-.14-1.27,1.23-.14,2.83,1.19,4.01,1.67,16.28,8.83,33.08,17.26,50.07,24.93,.58,.14,1.42,.27,.93-.77-2.08-4.56-4.81-8.84-6.63-13.51,.32-.86,2.07,.4,2.68,.55,10.19,4.84,20.48,9.54,30.98,13.95,3.81,1.6,7.66,3.15,11.5,4.71,.53,.11,1.76,.81,2,.04-1.88-3.85-4.48-7.34-6.63-11.05-.35-.58-.61-1.19-.88-1.8,0-.14,.36-.4,.51-.38,12.74,4.88,25.27,10.18,38.26,14.56,.46,.16,1.01,.M 15,1.53,.2,.07,0,.25-.16,.24-.2-.17-.4-.31-.83-.57-1.19-2.45-3.69-5.58-7.11-7.71-10.96-.01-.17,.29-.42,.46-.42,2.05,.4,3.98,1.32,5.96,1.96,8.57,3.15,17.33,5.92,26.17,8.55,.73,.11,1.59,.58,2.28,.33,.09-.17,.22-.42,.13-.54-2.87-3.88-6.37-7.38-8.97-11.42,.58-.36,1.1-.27,1.61-.12,4.55,1.33,9.09,2.7,13.66,3.98,4.32,1.2,8.69,2.3,13.04,3.43,.47,.06,1.11,.26,1.55-.03,.06-.05,.1-.19,.06-.25-.39-.56-.75-1.14-1.2-1.66-2.46-2.83-4.94-5.65-7.41-8.47-.37-.42-.82-.82-.75-1.44,6.66,1.02,14.08,3.3,20.94,4.57,1.36,.18,3.44,.92,4.68,M .71,.09-.16,.23-.41,.14-.53-3.07-3.71-6.71-6.97-9.76-10.7-.11-.14-.04-.38,.01-.56,.01-.05,.24-.11,.36-.1,7.09,.91,14.17,3.11,21.37,3.11,.28-.98-.86-1.51-1.37-2.23-3.56-3.79-7.13-7.57-10.69-11.36-1.73-1.85-.9-1.92,1.11-1.62,5.54,.71,11.13,1.89,16.75,1.82,.83-.43-.17-1.11-.5-1.57-3.99-4.47-8.41-8.63-12.17-13.29-.11-.27-.02-.75,.41-.69,5.35,.31,10.7,1.41,16.06,1.07,.89-.52-.66-1.56-.99-2.13-3.81-4.43-8.22-8.45-11.69-13.14-.01-.17,.46-.63,.76-.53,4.96,.51,9.95,.34,14.93,.41l-.1-.06c4.4,4.76,8.98,9.41,13.67,13.99,1.68,1M .91-6.07,1.27-7.05,1.52-2.29,.08-4.57,.13-6.86,.2-1.48,.37,.74,1.96,1.14,2.56,3.78,3.79,7.57,7.56,11.36,11.34,.44,.71-.56,.9-1.07,.91-3.9,.02-7.81,.19-11.71-.05-3.37-.12-3.87-.08-3.78,.34,.22,1.01,1.18,1.63,1.92,2.36,3.48,3.43,6.99,6.83,10.49,10.25,.35,.42,1.27,1.11,.62,1.58-5.34,.02-10.76-.38-16.08-.9-.77-.05-3.76-.51-2.48,.99,3.18,3.21,6.49,6.32,9.71,9.5,.15,.14,.2,.43,.12,.6-.15,.19-.68,.35-.99,.28-5.74-.59-11.47-1.25-17.15-2.15-1.27-.1-2.73-.47-3.95-.25-.06,.19-.17,.46-.06,.59,2.8,3.53,6.82,6.5,9.37,10.02-.13,.M 15-.32,.38-.5,.39-2.53-.02-5.06-.6-7.55-.98-5.5-1.04-10.98-2.12-16.47-3.2-.51-.1-1-.34-1.5,.02,1.95,3.37,5.3,5.91,7.78,8.96,.55,.6,1.04,1.24,1.53,1.87,.06,.07,.02,.23-.05,.31-.94,.31-2.13-.15-3.12-.23-7.44-1.49-14.78-3.26-22.05-5.22-1.75-.27-3.64-1.42-5.38-.83,.3,0,.37-.08,.23-.23l-.13,.21c2.64,3.86,6,7.38,8.85,11.14,.06,.07,.03,.23-.03,.31-.65,.34-1.95-.12-2.69-.21-9.85-2.56-19.59-5.36-29.18-8.48-1.07-.28-2.26-1.01-3.37-.7-.45,.2-.17,.57,.01,.82,2.68,3.8,5.86,7.51,8.21,11.43-.59,.42-1.21,.12-1.82-.07-8.63-2.73-17.M 29-5.38-25.71-8.51-4.15-1.54-8.3-3.07-12.45-4.59-.46-.17-1.01-.57-1.45-.26-.66,.47,0,.98,.23,1.43,.35,.7,.83,1.35,1.26,2.02,1.9,2.96,3.95,5.85,5.69,8.9,.15,.26,.03,.62,.04,.93l.08-.07Z"/><path class="cls-2" d="M412.05,773.58c.69-.15,1.32,.03,1.95,.23,4.24,1.37,8.47,2.76,12.74,4.08,3.01,.93,6.06,1.77,9.11,2.62,.28,.08,.68-.1,1.22-.2-4.2-5.64-8.97-10.71-12.82-16.53-.03-.17,.3-.41,.47-.38,5.76,1.45,11.44,3.15,17.18,4.67,3.01,.51,5.56,2.01,2.29-1.95-3.4-4.26-6.83-8.52-10.23-12.78-.42-.53-1.01-1.03-.87-1.75l-.11,.05c.8-M .33,1.58-.08,2.34,.09,4.14,.93,8.26,1.89,12.4,2.82,1.39,.16,2.89,.91,4.25,.46,0-.69-.55-1.19-.98-1.73-3.87-5.23-8.53-10.04-11.86-15.6,.64-.28,1.15-.17,1.67-.05,4.78,1.1,9.62,2,14.53,2.65,.26,0,.91-.02,.85-.41-.33-.58-.64-1.17-1.04-1.71-3.65-5.02-7.51-9.9-11.04-15-.49-.6,0-1.13,.7-1,5.01,.74,10.02,1.52,15.03,2.27l-.04-.02c4.11,5.3,8.22,10.61,12.33,15.92,3.7,3.88-12.92-.19-14.32,.59-.08,.7,.45,1.21,.89,1.75,3.62,4.41,7.24,8.81,10.86,13.22,.44,.69,1.32,1.14,.93,2.07-22.1-1.73-20.42-6.68-5.46,11.88,.6,.7,1.17,1.43,1.73M ,2.16,.05,.07,0,.22-.08,.31-.06,.08-.2,.17-.3,.16-1.46-.13-2.94-.21-4.37-.44-4.08-.67-8.19-1.27-12.2-2.2-2.34-.28-2.45-.08-1.05,1.78,3.21,3.72,6.44,7.43,9.66,11.15,.69,.8,1.34,1.61,1.99,2.42,.18,.3-.36,.64-.56,.66-6.61-.72-13.09-2.48-19.49-4.05-1.74-.55-1.94-.04-.88,1.33,3.99,4.73,8.05,9.41,12.02,14.15,.11,.13,.1,.46-.02,.55-.16,.12-.51,.19-.74,.14-7.9-1.77-15.66-3.78-23.37-6.14-.69-.16-1.35,.26-.7,.87,2.97,3.72,5.98,7.42,9,11.1,.19,.23,.13,.42-.14,.52-3.41-.48-6.89-1.8-10.25-2.71-6.26-1.78-12.38-4.51-18.67-5.91-.3M ,0-.35,.46-.09,.84,2.69,3.93,6.24,7.58,8.59,11.6-.72,.46-1.48-.02-2.21-.22-10.08-3.32-19.94-7.03-29.69-10.93-.71-.24-1.42-.76-2.18-.39,1.76,4.04,5.19,7.75,7.59,11.62,.25,.36,.36,.78,.5,1.18,.02,.05-.19,.21-.28,.2-4.97-1.24-9.71-3.67-14.49-5.5-7.35-3.15-14.63-6.41-21.93-9.64-.81-.36-1.73-.62-2.22-1.33-.06,.07-.13,.13-.19,.2l.23-.18c-1.29,1.34,.69,2.85,1.19,4.14,1.84,3.23,3.89,6.37,5.62,9.66,.06,.17-.01,.46-.17,.57-15.64-5.66-30.38-14.19-45.4-21.41-.7,.57-.21,1.12,.03,1.77,1.82,3.71,3.67,7.41,5.48,11.12,.29,.59,.48,1M .22,.68,1.84,.02,.07-.12,.2-.22,.26-10.63-4.16-20.73-10.47-30.86-15.74-7.34-3.99-14.45-8.35-21.85-12.2-.37-.19-.68,.25-.68,.52,1.42,4.84,3.6,9.47,5.29,14.22,.09,.39,.39,.93,0,1.21-14.18-6.82-27.63-15.79-41.1-23.83-6.49-4.04-12.89-8.16-19.33-12.24-.63-.34-1.23-.98-2.01-.71,.62,5.55,3.27,11.33,4.06,17.03,0,.2-.43,.38-.6,.3-24.22-14.59-47.35-30.71-70.33-47.07-.62-.39-1.21-1.02-2.02-.79-.07,.01-.16,.18-.15,.27,.07,1.18,.09,2.36,.24,3.53,.53,3.96,1.09,7.92,1.67,11.88,.43,2.67,.43,3.05-.04,3.01-28.94-18.59-56.5-40.37-83.M 46-61.43-2.72-2.16-2.34-1.7-2.36-4.49,.06-6.13-.27-12.3,.05-18.4,.98-.44,1.79,.66,2.55,1.14,22.36,18.63,44.81,36.76,68.34,54.15,3.16,2.35,6.31,4.7,9.47,7.04,.58,.32,2.42,2.01,2.78,.87-.31-5.93-1.49-11.77-2.26-17.66-.09-1.94,2.33,.25,2.95,.68,21.83,16.44,44.35,33.51,67.69,47.88,.63-.34,.25-1.21,.17-1.77-.9-3.37-1.82-6.74-2.72-10.1-.35-1.78-1.3-3.55-.93-5.37,.77-.14,1.25,.28,1.75,.62,3.89,2.66,7.77,5.34,11.68,7.98,15.32,10,30.67,20.89,46.92,29.51,.1-.04,.23-.18,.21-.25-.12-.63-.2-1.27-.42-1.88-1.33-3.62-2.69-7.22-4.0M 4-10.83-.35-.93-.69-1.86-.98-2.8,0-.23,.37-.67,.71-.47,16.6,10.08,33.31,20.48,50.68,29.41,.21,.06,.83-.06,.8-.39-.12-.42-.23-.84-.42-1.23-1.81-3.83-3.63-7.65-5.44-11.48-.23-.5-.37-1.02-.52-1.54-.02-.08,.09-.21,.18-.28,.07-.05,.24-.09,.31-.06,.92,.43,1.87,.84,2.74,1.33,13.52,7.51,27.24,14.98,41.35,21.45,.15-.28,.38-.5,.31-.64-.44-.9-.92-1.79-1.42-2.67-1.98-3.53-3.98-7.06-5.95-10.61-.07-.13,.11-.38,.22-.55,.97-.06,1.92,.73,2.82,1.08,11.36,5.97,23.5,10.92,35.08,16.6,0,0,.03-.17,.03-.17l-.14,.12c1.09-.92-.15-2.02-.62-2M .93-1.92-2.95-3.87-5.9-5.79-8.85-.37-.57-.66-1.17-.98-1.76-.04-.07,.02-.25,.08-.26,.65-.3,1.21,.05,1.8,.3,6.04,2.58,12.06,5.21,18.14,7.73,19.83,7.84,13.67,6.14,4.72-7.9-.09-.13,.08-.38,.18-.56,.03-.05,.25-.08,.34-.05,8.29,3.08,16.47,6.3,25,8.93,.96,.18,2,.92,2.95,.44-3.33-5.41-8.04-10.41-11.84-15.66-.29-.38-.48-.76-.32-1.21l-.09,.08Z"/><path class="cls-2" d="M266.44,990.81v-.14s.09,.02,.13,.03l-.13,.11Z"/><path class="cls-2" d="M410.43,983.7s-.03-.07-.04-.1c.04,0,.09,0,.13,0l-.09,.09Z"/><path class="cls-2" d="M497.M 08,948.76h-.05s-.02-.03-.03-.05c.02,.01,.05,.03,.07,.04,.01,0,.01,.01,.01,.01Z"/><path class="cls-2" d="M504.92,960.34c-16.21,1.12-32.44,.18-48.62,.14-.16,.03-.38,.36-.33,.49,1.6,4.05,4.46,7.54,6.02,11.59-.13,1.17-4.79,.33-5.86,.47-7.85-.3-15.69-.65-23.52-1.23-9.12-.58-18.18-1.83-27.28-2.49-.89,.1-.71,1-.47,1.59,1.84,4.24,3.68,8.47,5.53,12.7-22.77-1.97-45.36-5.54-67.86-9.4-.91-.02-.8,.95-.64,1.55,1.32,4.28,2.8,8.5,3.81,12.87,.11,.43,.03,.85-.5,1.25-26.42-4-52.51-9.82-78.39-16.23-.62-.1-1.73-.5-2.1,.17,.14,1.28,.31,M 2.56,.55,3.83,.95,4.31,1.33,8.64,1.18,13.03-32.14-7.53-63.69-16.31-94.88-26.23-.71-.22-1.27,.14-1.29,.78-.12,5.77,.65,11.71-.16,17.41-1.03,.81-2.96-.31-4.07-.55-37.23-11.25-73.9-24.09-110.08-38.08-.73-.32-1.24-.77-1.22-1.52,.02-1.73-.01-3.45-.02-5.18,.06-5.03-.16-10.11,.1-15.14,.94-.46,1.81,.16,2.69,.43,35.81,14.47,71.63,28.14,108.55,40.06,1.04,.12,3.77,1.84,3.97,.09-.61-5.9-1.28-11.8-1.9-17.7-.05-.41,.6-.82,1.07-.68,30.46,10.4,61.22,19.93,92.53,27.96,.67,.22,2.22,.6,2.24-.4-.33-1.71-.66-3.41-1.03-5.1-.06-1.55-3.45M -11.72-1.51-11.46,25.1,6.65,50.31,12.95,75.9,17.84,1.44,.04,4.39,1.54,3.24-1.45-1.43-4.27-2.88-8.52-4.31-12.79-.21-.6,.34-1.09,1.06-.97,21.34,4.26,42.8,8.17,64.43,10.76,1.67,.15,2.04-.15,1.52-1.35-1.74-4.21-4-8.2-5.48-12.49,.5-.09,.9-.25,1.27-.2,5.85,.73,11.69,1.55,17.55,2.23,12.29,1.29,24.62,2.56,36.96,3.14,1.07,.08,1.31-.57,.9-1.27-1.93-3.32-3.9-6.61-5.75-9.98-1.41-2.48,4.33-1.06,5.55-1.22,14.2,1.21,28.5,1.3,42.76,1.15,2.61,3.86,5.54,7.54,7.89,11.58Z"/><path class="cls-2" d="M505.13,960.33l-.16,.1s-.04-.06-.05-.0M 9c.07,0,.14-.01,.21-.01Z"/><path class="cls-2" d="M1192.65,222.76c-18.63,.68-37.07,1.81-55.69,3.23-.13-1.59,1.21-2.37,1.98-3.58,3.41-4.39,6.83-8.78,10.23-13.18,.42-.55,.79-1.12,1.17-1.69,.14-.2-.35-.68-.67-.66-14.87,1.1-29.68,2.83-44.52,4.35-.67,.07-1.33,.2-1.99,.26-.74,.06-1.74,.54-2.16-.1-.39-.6,.49-1.16,.95-1.67,4.63-5.16,9.29-10.31,13.93-15.48,.34-.56,2.1-1.97,1.18-2.36-14.92,1.03-29.73,4.04-44.61,5.64-.21-1.1,1.07-1.74,1.67-2.54,5.29-5.31,10.6-10.61,15.89-15.91,.64-.85,2.18-1.67,1.95-2.79-12.6,1.28-25.18,3.51-M 37.65,5.66-5.12,.95-3.25-.36-.68-2.87,6.27-5.92,12.56-11.82,18.83-17.74,.61-.57,1.16-1.18,1.72-1.79,.07-.07,.07-.25,0-.31-.15-.13-.39-.32-.55-.3-2.91,.43-5.82,.87-8.72,1.34-8.44,1.39-16.87,2.8-25.31,4.18-1.04,.17-2.1,.44-3.18,.13l.08,.08c0-.2-.12-.47,0-.6,.65-.68,1.34-1.35,2.06-1.99,7.95-7.04,15.9-14.07,23.85-21.1,.63-.52,1.28-.97,1.34-1.83-11.34,1.1-22.76,3.34-34.07,5.03-1.55,.09-.59-.77,0-1.42,10.19-8.92,20.68-17.54,30.83-26.5,.76-1.36-2.35-.63-3.02-.65-6.91,.92-13.81,1.87-20.71,2.8-2.39,.32-4.78,.62-7.18,.9-.2,.M 02-.55-.11-.61-.24-.06-.92,1.47-1.59,2.04-2.25,10.58-8.76,21.16-17.51,31.74-26.27,3.65-2.97,5.33-3.99-.91-3.36-8.03,.68-16.07,1.37-24.11,1.98-.47,.03-.49-.52-.37-.7,4.02-3.52,8.29-6.77,12.42-10.17,9.79-7.86,19.6-15.72,29.4-23.58,2.63-2.11,2.11-1.87,5.62-1.87,7.75-.01,15.42,0,23.19,0,0,.4,.15,.79-.03,.96-.77,.74-1.63,1.43-2.48,2.12-11.37,9.19-22.75,18.38-34.12,27.58-.94,.76-1.82,1.58-2.69,2.4-.07,.06,.13,.4,.3,.5,9.45-.07,19.03-1.5,28.52-1.75,.02,.22,.15,.49,.03,.62-.57,.6-1.17,1.18-1.82,1.72-9.14,7.62-18.3,15.23-27M .44,22.85-1.68,1.4-3.32,2.82-4.95,4.26-.13,.12-.08,.4-.06,.59,.54,.26,1.35,.07,1.96,.07,6.26-.74,12.51-1.53,18.78-2.24,3.47-.39,6.95-.67,10.43-.98,.2-.02,.54,.11,.63,.25,.22,.84-1.13,1.46-1.61,2.06-3.83,3.33-7.67,6.66-11.49,9.99-5.01,4.37-10.01,8.74-15.01,13.11-.81,.56-1.27,1.54,.16,1.4,11.4-1.24,22.82-3.79,34.23-4.22,.5,.5-.93,1.43-1.29,1.85-5.96,5.42-11.93,10.84-17.87,16.27-1.86,1.7-3.66,3.45-5.46,5.19-.12,.12-.04,.39,.01,.58,.01,.06,.23,.1,.36,.11,10.38-.97,20.72-2.75,31.09-4.01,2.29-.17,4.84-1.05,7.06-.5,.07,.0M 9,.14,.25,.09,.31-.46,.53-.92,1.06-1.43,1.56-5.77,5.69-11.56,11.37-17.33,17.06-.76,.75-1.5,1.52-2.2,2.31-.12,.13-.02,.4-.02,.64,9.74-.57,19.38-2.67,29.12-3.53,4.27-.46,8.54-.91,12.82-1.34,.17-.02,.4,.18,.55,.31,.06,.06,.05,.23-.01,.31-.51,.63-1,1.27-1.56,1.88-4.65,5.02-9.31,10.03-13.96,15.06-.72,.77-1.36,1.59-1.99,2.41-.06,.08,.2,.47,.31,.47,8.31-.17,16.53-1.84,24.83-2.38,6.96-.63,13.92-1.24,20.89-1.86,.56-.05,1,.13,.95,.37-.19,1.24-1.38,2.07-2.06,3.08-3.71,4.62-7.42,9.25-11.12,13.88-.72,1.03-2.31,2.58,.14,2.4,16.8M 9-1.22,33.83-2.68,50.76-2.94,.54,.25,.21,1-.08,1.39-3.81,5.94-7.63,11.88-11.44,17.81l.1-.06Z"/><path class="cls-2" d="M971.86,453.64c-.07,.01-.13,.01-.2,.01,0-.04-.01-.09-.01-.13h.15l.06,.12Z"/><path class="cls-2" d="M1026.04,428.3s-.02,.07-.02,.11c-.04,0-.07-.01-.11-.01l.13-.1Z"/><path class="cls-2" d="M1030.71,456.1c-3.82-.16-7.62-.53-11.41-.87,3.32-.95,6.69-1.93,10.02-2.93,.48,1.26,.93,2.53,1.39,3.8Z"/><path class="cls-2" d="M1030.71,456.1c.05,0,.09,0,.14,0l-.1,.09s-.02-.07-.04-.1Z"/><path class="cls-2" d="M1093M .95,419.27v.1c-.05,0-.09,0-.14-.01l.14-.09Z"/><path class="cls-2" d="M1095.46,449.73s-.01-.07-.02-.1c.05,0,.09,.01,.14,.01l-.12,.09Z"/><path class="cls-2" d="M1271.78,456.82v-.08s.09,.01,.13,.02l-.13,.06Z"/><path class="cls-2" d="M1387.25,454.02c0,6.14,0,12.28-.01,18.42-.04,.74-.02,1.88-1.1,1.71-12.01-4.02-23.89-8.44-35.95-12.42-24.57-8.23-49.42-16.09-74.6-22.96-1.92-.46-1.56,2.12-1.96,3.28-.64,4.89-1.71,9.75-1.85,14.69-30.68-8.73-61.63-17.01-92.95-23.54-2.6-.35-3.86-1.34-3.79,2.1-.08,4.41,.27,8.84-.09,13.23-.41,.8M 3-1.76,.42-2.5,.33-3.11-.68-6.22-1.38-9.33-2.07-22.24-4.84-44.77-8.94-67.37-11.93-.87-.06-1.31,.62-1.23,1.33,.22,4.49,.13,8.98,.92,13.44-21.51-2.72-43.03-6.01-64.74-7.08l-4.22-14.11c20.64,1.3,41.29,2.71,61.79,5.46,1.32-.09,6.12,1.46,6-.48-.1-4.68-.21-9.36-.32-14.05,26.91,2.95,53.68,7.53,80.21,12.8,1.05,.04,1.16-.95,1.41-1.69,1.1-4.1,2.18-8.21,3.28-12.31,.41-1.51,.85-1.71,2.84-1.36,1.31,.24,2.62,.49,3.93,.75,29.5,5.65,58.6,12.67,87.56,20.46,.34,.08,.92-.15,.97-.39,.25-1.06,.55-2.11,.72-3.17,.66-4.17,1.27-8.34,1.92-1M 2.5,.21-.66,.22-1.8,1.11-1.89,36.81,9.24,73.52,19.99,109.19,32.58,.06,.52,.16,.95,.16,1.37Z"/><path class="cls-2" d="M138.69,233.83c.3-.5,.32-1.03,.29-1.58-.25-3.87-.51-7.74-.75-11.61-.36-5.91-.71-11.82-1.05-17.74-.24-3.14,1.52-1.37,3.05-.48,7.52,5.08,14.75,11.03,22.51,15.56,.26-.19,.61-.39,.55-.75-.37-12.24-1.26-24.55-1.11-36.77,.11-.44,.97-.37,1.34-.12,7.72,4.07,15.13,8.76,22.97,12.57,1.12,.11,.73-1.74,.87-2.47-.04-5.27-.14-10.55-.15-15.82,.07-8.38-.17-16.78,.16-25.15,1.09-.4,2.07,.23,3.1,.52,4.37,1.67,8.73,3.36,M 13.08,5.05,.85,.33,1.67,.71,2.52,1.03,5.07,1.93,6.02,2.2,6.25,1.78,.89-1.63,.48-3.38,.56-5.07,.44-14.84,.97-29.72,2.1-44.51,.05-.25,.55-.59,.87-.55,1.06,.13,2.13,.22,3.17,.42,7.14,1.47,14.38,2.6,21.46,4.31,.45,1.12,.19,2.14,.15,3.29-.45,6.34-.95,12.68-1.36,19.02-.99,11.01-.68,22.67-2.28,33.5h0c-.18-.27-.28-.67-.56-.78-2.29-.92-4.59-1.8-6.92-2.66-5.42-1.95-10.74-4.03-16.21-5.85-.94,.94-.66,2.25-.74,3.47-.21,14.53-.15,29.08-.38,43.61-.01,.25-.62,.56-.88,.44-.82-.37-1.66-.71-2.43-1.13-6.13-3.33-12.24-6.68-18.36-10.01-M .77-.24-2.41-1.72-2.98-.63,.34,11.51,.46,23.04,1.16,34.54,.14,2.03,.06,4.08,.05,6.12,0,.1-.46,.33-.58,.29-8.07-4.81-15.41-10.88-23.39-15.85-1.33-.42-1.01,1.02-1.08,1.84,.23,3.98,.4,7.96,.71,11.94,.47,7.1,.93,14.19,1.37,21.29,.02,.29-.18,.59-.32,.87-.03,.07-.3,.14-.36,.11-.53-.33-1.07-.65-1.53-1.03-5.65-4.62-11.27-9.26-16.93-13.88-2.07-1.69-3.96-3.52-6.32-4.98-.12-.07-.56,.03-.69,.15-.39,.95-.04,2.17-.07,3.2,.67,9.14,1.36,18.27,2.19,27.4-.11,2.2-2.12-.11-2.96-.83-7.97-7.3-15.89-14.65-23.84-21.96-.44-.61-1.61-.58-1.4M 8,.35,.41,7.75,1.2,15.47,1.75,23.21,.08,1.07,.07,2.15,.1,3.22,0,.28-.16,.42-.49,.4-9.66-8.58-18.42-18.56-27.77-27.62-.63-.52-1.12-1.44-2.07-1.25-.07,0-.19,.14-.19,.22,0,.86-.01,1.72,.04,2.57,.33,6.88,.96,13.76,1.15,20.65-.28,1.05-1.56-.24-1.95-.65-9.92-10.61-19.83-21.22-29.74-31.84-.88-.88-1.84-1.88-1.74-3.17,0-2.48-.06-4.95-.08-7.43-.02-3.45-.02-6.89,0-10.34-.11-3.62,1.65-1.62,3.14-.14,9.35,9.17,18.37,18.67,27.9,27.65,.83,.57,1.09-.56,1.04-1.18-.1-2.48-.22-4.95-.33-7.43-.2-4.52-.4-9.04-.59-13.56,.03-.63-.15-1.41,.M 58-1.7,.07-.04,.27-.03,.34,.03,9.46,7.98,18.09,16.87,27.44,24.99,.11,.1,.47,.04,.7,.01,.32-.23,.25-.84,.28-1.2-.36-8.92-1.46-17.85-1.56-26.76,.96-.44,1.57,.42,2.29,.88,7.63,6.24,15.24,12.49,22.86,18.73,.69,.48,1.3,1.28,2.24,1.14l.04,.13-.13-.06Z"/><path class="cls-2" d="M1203.01,1271.97c5.12,1.91,10.24,3.83,15.37,5.73,2.69,1,5.39,1.97,8.08,2.95,.92,.34,1.49,.02,1.51-.87,.38-14.54,.29-29.08,.32-43.63-.14-3.81,.66-2.85,3.38-1.57,6.35,3.45,12.69,6.91,19.03,10.38,.65,.31,1.27,1.04,2.1,.6,.74-.39,.38-1.18,.38-1.79-.05-6M .14-.45-12.28-.63-18.41-.01-6.89-.7-13.78-.74-20.66,.05-.33,.74-.35,.93-.28,7.61,4.89,14.89,10.28,22.39,15.35,.39,.27,.75,.62,1.34,.58,.38,0,.53-.46,.54-.75-.25-4.63-.5-9.25-.79-13.88-.41-6.56-.85-13.12-1.27-19.69,.08-.57-.29-1.63,.54-1.7,.92,.14,1.67,1.05,2.44,1.54,5.18,4.24,10.34,8.49,15.51,12.74,2.26,1.85,4.52,3.69,6.81,5.52,.12,.1,.48,.03,.71,0,.15-.08,.25-.4,.25-.58-.22-3.55-.43-7.1-.67-10.65-.58-6.44-1.05-12.9-1.56-19.35-.08-1.84,1.07-1.02,1.94-.22,8.51,7.79,16.9,15.68,25.5,23.37,.13,.11,.5,.07,.76,.06,.1-.06M ,.22-.43,.19-.59-.61-7.96-1.32-15.91-1.94-23.86-.14-2.75-.61-4.83,2.37-1.76,9.28,8.95,17.93,18.94,27.55,27.35,.2-.11,.5-.27,.5-.4-.09-3.12-.21-6.24-.35-9.36-.2-4.52-.42-9.04-.6-13.56,0-.14,.31-.3,.5-.41,10.57,10.18,20.34,21.73,30.61,32.4,1.16,1.01,1.81,2.3,1.6,3.85,0,5.82,0,11.64,0,17.45,0,.52,.11,1.07-.33,1.53-.07,.07-.31,.15-.36,.11-.5-.34-1.04-.66-1.44-1.06-3.57-3.51-7.14-7.02-10.68-10.55-5.47-5.47-10.91-10.95-16.38-16.43-.69-.54-1.17-1.4-2.19-1.07,.11,7.85,.73,15.7,.98,23.55,.01,.25-.16,.4-.49,.43-1.71-.43-2.84M -2.26-4.23-3.3-7.49-6.93-14.97-13.87-22.45-20.8-.6-.43-1.62-1.97-2.31-1.02,.09,9.14,1.32,18.27,1.5,27.42-.32,1.27-1.67,.03-2.22-.44-7.43-6.1-14.86-12.19-22.29-18.29-2.48-2.03-3.41-2.72-3.04,1.24,.44,9.81,1.89,19.93,1.42,29.61-.93,.26-1.61-.55-2.34-.96-7.27-5.15-14.51-10.32-21.82-15.4-.27-.19-.69-.25-1.05-.35-.1-.02-.33,.06-.34,.11-.1,.42-.22,.84-.21,1.27,.3,10.23,.74,20.46,1.09,30.69,.06,1.72,.03,3.44,.03,5.15,0,.24-.67,.53-.92,.42-.24-.1-.49-.18-.71-.3-7.01-3.81-13.94-7.74-20.91-11.62-3.25-1.94-2.59-.21-2.72,2.46,M .07,13.38,.42,26.75-.04,40.12-2.37,.15-4.46-1.37-6.7-2.01-5.1-1.95-10.2-3.91-15.3-5.86-.9-.17-2.55-1.37-3.11-.22-1.19,16.54-.63,33.3-2.63,49.75-8.64-.64-17.03-3.36-25.61-4.56l.08,.08c.79-18.57,2.79-37.09,3.24-55.69l-.14,.06Z"/><path class="cls-2" d="M670.91,824.6s-.03,.05-.04,.07l.09-.06s-.03,0-.05,0Zm21.26,37.39s-.02,.03-.04,.05l.08-.04s.01-.01,.02-.01h-.06Zm104-66.99s.07,.01,.1,.02c.02-.05,.03-.1,.05-.15l-.15,.13Zm7.96,3.76c-2.64-1.25-4.99-3-7.86-3.74-1.44,4.63-2.88,9.27-4.34,13.9-.25,.82-.94,1.06-1.79,.68-1.98-.M 91-3.96-1.82-5.95-2.72-.5-.21-1.35-.54-1.8-.09-2.27,4.5-3.23,9.61-5.49,14.12-.14,.28-.64,.39-1.01,.24-2.15-.9-4.29-1.79-6.47-2.63-1.61-.62-1.88-.51-2.52,.99-1.98,4.48-3.46,9.12-5.83,13.43-3.13-.9-5.84-2.33-8.99-3.12-2.87,4.3-4.71,9.18-7.18,13.73-.16,.31-.15,.61,.26,.81-3.63,.08-6.77-2.34-10.3-2.93-.04,0-.08-.01-.12-.02-.01,0-.02,.03-.02,.04-2.99,5.02-6.88,9.6-10.66,14.32-3.27-1.26-6.38-2.23-9.27-3.52,0-.87,.73-1.4,1.2-2.01,2.98-4.03,6.37-7.79,9.08-11.99,.01-.03,.03-.06,.05-.09-.02,0-.03-.01-.05-.01-3.27-.81-6.48-1.M 77-9.79-2.74,.33-1.85,1.53-3.27,2.28-4.83,1.52-3.05,3-6.12,4.37-9.24-2.6-.53-5.2-1.06-7.8-1.59-1.14-.2-3-.87-3.5,.44-2.04,4.03-3.94,8.25-6.26,12.11-.43,.07-.72,.18-.95,.13-3.26-.65-6.48-1.36-9.57-2.3-.04-.19-.12-.31-.08-.4,1.86-4.37,4.24-8.59,6.3-12.89-3.22-.7-6.46-1.4-9.69-2.1-1.75-.46-.5-2.02-.18-3.06,1.44-3.45,2.52-7.05,4.23-10.37-3.53-.61-7.06-1.23-10.6-1.84-.78-.13-1.31,.11-1.55,.69-1.1,2.76-2.19,5.52-3.3,8.27-.69,1.15-.78,3.36-2.49,3.35-3.55-.62-7.08-1.35-10.51-2.47,1.38-4.23,3.85-8.11,4.93-12.43,0-.03,.01-.0M 6,.02-.09-.02,0-.05-.01-.07,0-3.46-.75-6.91-1.48-10.36-2.25-.73-.16-1.06-.68-.87-1.24,1.15-3.51,2.29-7.02,3.47-10.53,.08-.27,.36-.51,.56-.76,.01-.02,.03-.03,.04-.05-2.47-.86-5.11-1.28-7.68-1.88-4.62-1.08-4.24-1.52-5.61,2.43-.87,2.46-1.87,4.92-2.84,7.37-.37,1.01-.13,1.44,1.02,1.74,2.68,.69,5.37,1.34,8.05,2.03,.7,.32,2.01,.3,2.16,1.18-1.12,3.95-3.35,7.46-4.87,11.31,3.42,1.74,7.63,1.94,11.15,3.31,.22,.64-.03,1.14-.3,1.63-1.39,2.56-2.77,5.12-4.15,7.68-.25,.88-1.8,2.18-.7,2.9,3.58,1.2,7.34,1.93,10.98,2.95,2.02-3.72,4.25M -7.35,5.93-11.19,.47-1.06,1.01-1.23,2.51-.93,3.19,.66,6.24,1.15,9.39,2.09-1.59,4.2-3.96,8-5.82,12.08-.18,.39,.12,.95,.58,1.07,2.97,.74,6.18,1.54,9.07,2.28,.33,.7-.02,1.17-.36,1.63-2.54,3.89-6.28,7.23-8.77,10.92,2.95,1.35,6.23,1.9,9.32,2.88,1.81,.65-1.13,2.55-1.63,3.38-2.81,2.88-5.65,5.75-8.46,8.62-.69,.71-.58,1.16,.36,1.51,3.04,.92,6.02,2.62,9.14,3.05,3.94-4.07,7.98-8.09,11.57-12.36,.2-.24,.62-.36,.96-.54,3.04,.96,6.1,1.79,8.89,2.93,.28,.53,.13,.93-.19,1.29-3.64,4.19-7.2,8.34-11.04,12.39,.26,.29,.42,.64,.73,.78,2.7M 6,1.22,5.51,2.15,8.18,3.64-4.27,5.02-9.61,9.01-14.2,13.67,1.74,1.42,5.25,3.34,8.63,4.74,.72-.12,1.08-.6,1.52-.99,4.6-4.08,8.91-8.35,12.84-12.8-.14-.52-.53-.8-1-1.03-2.26-1.16-4.68-2.1-6.81-3.45-.62-.68,.75-1.61,1.1-2.21,3.33-3.8,6.71-7.53,10-11.36,.48-.54,1.06-.7,1.73-.46,2.74,1.11,5.8,1.83,8.06,3.68-3.78,4.73-7.98,9.19-11.96,13.76-.32,.37-.21,.9,.24,1.14,2.34,1.28,4.67,2.55,7.01,3.82,.86,.54,1.61-.39,2.14-.96,3.97-4.54,7.88-9.03,11.85-13.58,2.98,1.18,5.27,3.05,8.16,4.41,4.11-4.8,7.37-10.25,11.19-15.27,2.2,.52,3.49M ,1.95,5.38,2.93,.86,.48,1.47,1.3,2.68,1.32,.79-.49,1.06-1.22,1.43-1.9,2.12-3.96,4.24-7.91,6.34-11.88,.27-.49,.45-1.02,1.09-1.31,2.53,.71,4.63,2.97,6.93,4.28,.31,.21,.82,.12,1.02-.16,2.67-4.73,4.77-9.85,7.21-14.72,.09-.18,0-.41,0-.83-2.25-1.47-4.64-3.02-7.24-4.35-.42-.22-1.14,0-1.34,.39-2.24,4.59-4.06,9.4-6.42,13.93-.24,.4-.91,.6-1.34,.37-2.01-1.09-4.01-2.18-6.01-3.28-.46-.25-.93-.41-1.64-.28-2.62,4.86-4.71,9.98-7.9,14.67-.4,0-.72,.08-.91-.01-2.41-1.18-4.8-2.38-7.19-3.58-.45-.22-.51-.62-.22-1.15,2.36-4.46,4.72-8.92,M 7.08-13.38,.21-.56,.92-.86,1.58-.62,2.54,.9,5.05,2.66,7.65,3.13,2.75-4.46,4.17-9.73,6.6-14.39,.13-.25,.75-.46,1.02-.34,2.61,1.14,5.14,2.26,7.68,3.58,.72-.5,1-1.09,1.23-1.7,1.69-4.37,3.14-8.91,5.02-13.19,.72-.15,1.18,.09,1.61,.32,2.25,1.16,4.37,2.58,6.7,3.57,.17,.06,.6-.08,.66-.2,1.92-3.99,2.95-8.29,4.42-12.45l.06-2.94c-.31-.04-.57-.17-.83-.3Zm-89.84,37.3c-3,4.1-6.28,8.02-9.39,12.05-.41,.52-1,.68-1.73,.45-2.88-.9-5.83-1.65-8.93-2.85,2.84-3.89,5.77-7.41,8.7-11.2,.61-.72,1.11-1.79,2.26-1.52,2.99,.63,5.96,1.3,8.83,2.23M ,.32,.11,.45,.54,.26,.84Zm38.34,13.2c-2.98,4.69-6.25,9.24-9.65,13.74-.39,.51-1.08,.65-1.72,.34-2.31-1.1-4.6-2.2-6.9-3.31-.42-.2-.52-.75-.23-1.14,1.54-2.02,3.12-4.01,4.59-6.06,2.29-2.74,3.57-6.27,6.44-8.46-.82,1.44,8.63,3.14,7.47,4.89Zm240.89,13.47l.13,.06v-.1s-.09,.03-.13,.04Zm7.28-62.69s.03,.04,.04,.06c.02,0,.04,0,.06,0l-.1-.07Zm6.49,58.19s0,.02,0,.03l.1-.09s-.07,.04-.11,.06Zm3.82-31.37c-3.31-8.91-6.13-18.16-10.27-26.76-1.3-.23-13.48-2.43-12.92-.59,3.18,8.92,6.92,17.62,9.72,26.65,.12,.4-.18,.86-.69,1.04-3.86,1.23-M 7.45,3.17-11.18,4.45-.82,0-.95-.87-1.2-1.47-1.87-5.28-3.7-10.57-5.61-15.85-1.05-2.89-2.24-5.75-3.37-8.62-.49-.9-1.71-.35-2.36,.08-2.88,1.77-5.73,3.56-8.6,5.36-.31,.18-.82,.05-.97-.25-3.15-6.97-5.76-14.17-9.09-21.06-.22-.47-.4-1.02-1.22-1.32-2.47,1.44-4.51,3.65-6.75,5.42-.87,.47-2.22,2.71-3.2,1.82-3.42-6.24-6.21-12.88-9.8-19.02-.75-.03-1.12,.26-1.43,.61-2.28,2.52-4.55,5.07-6.85,7.58-1.26,.76-1.65-1.34-2.27-2.05-2.77-4.65-5.18-9.53-8.2-14.03-1.02-.72-1.72,1.08-2.32,1.68-1.59,2.25-3.16,4.51-4.73,6.77-.27,.39-.6,.68-1.M 34,.71-2.71-4.15-5.42-8.4-8.12-12.56-.48-.59-1.08-2.14-2.01-1.45-1.89,2.65-3.22,5.68-4.91,8.48-1.08,2.04-1.54,1.8-2.81,.05-2.21-3.07-4.3-6.24-6.59-9.26-.38-.56-.88-1.16-1.58-1.33-.49-.11-.69,.27-.82,.56-1.37,2.92-2.71,5.85-4.07,8.78-.34,.61-.79,1.88-1.67,1.16-2.35-2.88-4.66-5.8-6.99-8.69-.87-1.08-1.72-2.27-2.57-.68-1.41,3.48-2.5,7.08-4.09,10.48-.79,.87-1.62-.69-2.18-1.17-1.96-2.19-3.9-4.39-5.86-6.58-.38-.44-.76-.9-1.59-1.08-1.84,2.99-2.3,6.78-3.64,10.03l-.09,4.14c2.6,2.71,4.73,5.86,7.42,8.5,.12,.11,.48,.05,.81,.08,M 6.56-16.35,2.72-14.53,13.45-1.69,.7-.17,1-.49,1.18-.92,1.17-2.76,2.32-5.51,3.51-8.26,.43-.64,.82-2.51,1.81-2.09,2.88,3.11,4.84,6.96,7.36,10.37,1.46,2.17,1.77,1.51,2.83-.45,1.24-2.38,2.45-4.77,3.7-7.16,.38-.55,.78-1.74,1.62-1.48,3.34,4.25,5.64,9.29,8.64,13.77,.75-.03,1.07-.32,1.32-.72,1.62-2.6,3.25-5.2,4.89-7.79,.43-.49,.93-1.71,1.74-1.25,3.54,5.17,5.87,10.92,9.19,16.27,3.01-2.74,4.88-6.3,7.71-9.22,.21-.24,.82-.18,1,.09,3.28,6.03,5.75,12.52,8.85,18.64,.71,.06,1.07-.22,1.41-.56,1.35-.99,7.66-8.96,8.71-7.33,3.25,6.65,M 5.73,13.67,8.51,20.52,.17,.42,.43,.77,1.15,.94,2.8-2.09,5.72-4.19,8.56-6.26,.42-.32,1.3-.71,1.75-.34,3.24,7.32,5.28,15.13,8.05,22.65,.28,.82,.62,1.64,.99,2.44,.05,.12,.5,.24,.68,.19,3.38-1.5,6.61-3.33,9.93-4.95,.46-.23,.95-.39,1.62-.25,3.16,9.88,6.48,19.92,8.39,30.06,4.53-1.53,9.17-2.79,13.64-4.46-2.47-9.83-5.72-19.47-8.63-29.18-.22-.71-.49-1.83,.65-1.82,3.87,.24,7.62,1.37,11.45,1.85,1.18-.13,.5-1.49,.35-2.22Z"/><path class="cls-2" d="M169.9,1258.03c.04-.86,0-1.73,.46-2.5,3.02-5.89,5.45-12.19,8.82-17.86l-.09,.06c17M -.83,34.21-.58,51.28-1.29,.9,.2,5.82-.82,4.89,.97-3.54,5.45-7.16,10.86-10.72,16.3-.34,.7-1.44,1.78-.22,2.19,12.9-.1,25.8-1.36,38.69-2.1,3.21-.1,6.44-.78,9.63-.49,.94,.41-.76,1.87-1.06,2.44-4.48,5.64-9.16,11.14-13.54,16.85-.18,.24,.14,.73,.47,.72,13.96-.55,27.84-2.36,41.73-3.78,3.62-.41,.91,1.49-.15,2.89-5.18,5.51-10.39,11.01-15.57,16.52-.27,.45-2,2-.84,2.1,13.28-.94,26.49-3,39.7-4.09-.25,1.41-1.68,2.15-2.58,3.19-6.58,6.42-13.26,12.74-19.78,19.22-.54,.65,.15,1,.81,.88,11.63-.97,23.17-2.82,34.79-3.91,1.38,.21-1.43,2.M 26-1.8,2.7-7.61,6.84-15.23,13.68-22.84,20.52-.62,.56-1.18,1.17-1.75,1.76-.07,.07-.08,.25-.01,.3,.16,.13,.38,.32,.56,.31,1.74-.15,3.48-.33,5.21-.5,7.09-.69,14.18-1.37,21.26-2.06,3.26-.26,8.77-2.01,3.16,2.39-9.18,7.88-18.44,15.71-27.6,23.62-.51,.44-1.5,.84-1.04,1.57,.32,.5,1.21,.26,1.84,.22,8.99-.41,17.98-1.6,26.97-1.65,.49,.38-.15,1-.53,1.29-12.28,10.02-24.38,20.24-36.77,30.14-8.15,.4-16.39,.05-24.56,.17-.57-.03-2.05,.11-2.13-.5,.21-1.12,1.58-1.68,2.33-2.51,6.37-5.41,12.76-10.82,19.13-16.23,3.6-3.06,7.2-6.12,10.8-9.M 18,.38-.32,.7-.65,.51-1.14-9.47,0-19.05,1.28-28.56,1.52-.68-.05-1.18-.25-.5-1.06,8.36-7.64,16.89-15.1,25.3-22.67,.47-.62,3.8-2.76,1.98-3.08-10.72,.88-21.39,2.15-32.14,2.66-.12,0-.33-.05-.35-.11-.06-.19-.16-.46-.05-.59,.54-.62,1.11-1.21,1.72-1.79,6.49-6.19,12.99-12.38,19.49-18.57,.69-.87,4.11-3.08,1.2-3.09-7.37,.49-14.72,1.37-22.08,2.01-4.42,.19-9.37,1.43-13.69,.97,.42-1.65,2.16-2.66,3.2-4,4.95-5.24,9.92-10.48,14.86-15.73,.56-.81,1.76-1.43,1.61-2.49-13.51,.92-27.03,2.62-40.6,3.21-1.14-.24-.4-.97,0-1.5,5.07-6.23,10.4M 4-12.25,15.35-18.61,.19-.26-.12-.74-.47-.73-5.65,.04-11.26,.76-16.9,1.09-9.27,.53-18.54,1.17-27.83,1.48-.73,.02-1.09-.55-.72-1.14,.85-1.34,1.71-2.69,2.6-4.02,2.48-3.7,4.97-7.4,7.45-11.1,1.02-1.9,3.85-4.25-.37-3.88-12.26,.38-24.51,.86-36.77,1.01-3.77,.04-7.55,.15-11.32,.24-.67,.01-1.35,.02-1.89,.42l.03,.02Z"/><path class="cls-2" d="M1262.17,202.07c-11.54,.6-23.17,.35-34.74,.71-6.06,.12-12.12,.37-18.18,.55-1.07,.03-2.15-.02-3.22-.09-.14,0-.4-.37-.34-.49,3.56-6.33,8.13-12.09,11.78-18.37,.14-.25-.22-.72-.54-.72-13.44,.M 4-26.87,1.48-40.3,2.34-2.68,.18-5.35,.55-8.05,.54-1.51-.28,.52-1.96,.86-2.62,4.23-5.25,8.47-10.5,12.7-15.75,.36-.44,.64-.93,.88-1.42,.05-.1-.24-.32-.42-.46-14.42,.88-28.9,2.52-43.31,3.87-1.14-.09,.65-1.68,.89-2.09,5.17-5.52,10.36-11.02,15.53-16.54,.72-.77,1.37-1.59,2.01-2.4,.06-.08-.14-.39-.31-.47-12.9,.93-25.93,2.54-38.79,4.18-2.48,.32-.45-1.45,.35-2.24,6.97-6.86,14.14-13.52,20.99-20.5,.21-.28-.31-.66-.5-.68-11.08,1.15-22.14,2.48-33.2,3.8-.86,.1-1.74,.64-2.6-.02,.03-.87,.93-1.28,1.53-1.82,7.87-7.09,15.76-14.17,23.M 63-21.26,.62-.56,1.15-1.18,1.7-1.78,.06-.06,0-.22-.06-.31-.61-.38-1.56-.12-2.27-.15-8.29,.82-16.57,1.64-24.86,2.48-2.89,.08-8.69,2.08-3.27-2.17,9.61-8.29,19.4-16.41,28.87-24.87,.11-.1,.01-.38-.04-.57-.26-.21-.77-.17-1.11-.19-8.6,.37-17.19,1.18-25.78,1.71-.64,.04-1.3-.05-1.95-.1-.05,0-.12-.21-.09-.3,11.83-10.78,24.86-20.68,37.25-30.96,8.2-.26,16.42-.04,24.63-.11,.73,.06,1.64-.18,2.12,.49,.05,.06,.02,.22-.04,.28-.59,.58-1.15,1.18-1.79,1.73-4.05,3.46-8.12,6.91-12.19,10.36-5.64,4.78-11.28,9.57-16.9,14.36-.85,.74-2.92,2M .37-.41,2.23,6.59-.37,13.17-.75,19.76-1.13,2.67-.05,5.38-.61,8.04-.38,1,.42-.97,1.78-1.35,2.28-8.73,7.93-17.69,15.62-26.28,23.69-.22,.3,.36,.64,.54,.66,10.88-.68,21.73-2.31,32.61-2.61-.12,.35-.11,.71-.33,.94-1.16,1.19-2.37,2.34-3.58,3.5-5.97,5.7-11.96,11.39-17.92,17.09-.69,.66-1.33,1.35-1.95,2.05-.1,.12,.05,.38,.11,.65,11.24-.67,22.45-2.23,33.69-3.05,5.43-.64,2.21,1.41,.31,3.69-5.52,5.98-11.34,11.72-16.68,17.86-.07,.31,.06,.74,.54,.68,11.79-.91,23.55-2.23,35.36-2.98,3.9-.09,7.65-1.77,3.09,3.19-4.02,4.85-8.05,9.69-1M 2.07,14.54-.59,.72-1.16,1.45-1.68,2.2-.11,.15,.02,.41,.04,.66,14.86-.42,29.77-2.23,44.69-2.53,1.38-.04,1.73,.37,1.13,1.33-.9,1.44-1.82,2.88-2.77,4.31-2.98,4.59-6.21,9.03-9.03,13.72-.22,1.06,1.45,.71,2.09,.79,4.04-.14,8.08-.3,12.12-.43,12.93-.35,25.86-.66,38.8-.82l-.12-.12c-3.15,6.75-6.32,13.48-9.72,20.12l.09-.06Z"/><path class="cls-2" d="M169.87,1258.01c-.57,.12-.87,.44-1.07,.86-1.78,3.72-3.56,7.44-5.34,11.16-1.06,2.21-2.12,4.42-3.17,6.64-.24,.45-.45,1.2,.21,1.37,15.47,.24,30.95-.88,46.42-1.35,2.19-.04,1.81,.42,.93M ,2.01-2.94,4.36-5.91,8.71-8.85,13.06-1.09,1.61-2.13,3.24-3.18,4.87-.25,.39,.2,.86,.8,.84,13.73-.31,27.41-1.57,41.12-2.25,.33-.01,.77,.47,.62,.67-.47,.65-.93,1.31-1.45,1.93-4.74,5.76-9.5,11.51-14.24,17.26-.41,.62-1.42,1.48-.14,1.81,2.82-.16,5.65-.29,8.47-.48,9.39-.62,18.78-1.31,28.17-2.03,.23,0,.73,.34,.6,.63-6.54,7.57-14.04,14.37-20.5,22.01-.04,.67,1,.61,1.48,.59,8.32-.59,16.64-1.18,24.96-1.78,1.28,.12,7.2-1.26,7.05,.15-5.52,5.92-11.73,11.23-17.5,16.92-9.71,9.4-9.82,7.73,3.25,7.36,6.05-.29,12.1-.62,18.15-.93,1.57-.M 09,1.12,.86,.19,1.63-8.82,7.85-17.63,15.72-26.43,23.59-1.14,.87-2.09,2.19-3.56,2.51-8.07,.19-16.17,.02-24.25,.07-.58-.04-1.89,.08-1.9-.69,8.02-8.61,17.05-16.34,25.27-24.77,.11-.11,.01-.39-.04-.58-.26-.23-.78-.18-1.12-.22-9.28,.45-18.57,.85-27.86,1-.2,0-.49-.18-.58-.33-.09-.16-.08-.45,.04-.59,2.39-2.61,4.77-5.21,7.21-7.79,4.14-4.38,8.32-8.74,12.48-13.11,.56-.59,2.23-2.01,.46-2.14-11.03,.28-22.03,1.46-33.05,1.7-.77-.33,0-1.15,.29-1.61,1.82-2.26,3.66-4.52,5.51-6.77,3.41-4.14,6.82-8.27,10.23-12.41,.36-.44,.83-.87,.43-1M .54-11.63,.14-23.33,1.38-34.98,1.77-.87-.11-4.49,.68-3.72-.93,4.24-6.63,8.93-12.99,13.09-19.66,.02-.8-1.28-.71-1.86-.71-3.23,.11-6.46,.22-9.69,.34-11.17,.49-22.34,.94-33.52,.98l.14,.11c2.93-6.11,5.86-12.22,8.79-18.33,.32-.76,1.36-2.24-.03-2.48-11.14-.25-22.28,0-33.43-.09-5.36-.12-10.75,.1-16.08-.39-1.05-.29-.43-1.57-.34-2.32,1.42-5.46,2.85-10.92,4.27-16.38,.16-.61,.46-1.26-.21-1.82l-.06,.02c1.12-.49,2.34-.42,3.55-.4,4.98,.08,9.96,.11,14.93,.25,13.01,.71,26.16-.26,39.1,.77,0,0-.03-.02-.03-.02Z"/><path class="cls-2" M d="M555.12,270.11c-7,1.83-13.79,4.34-20.78,6.2-.32,.09-.82-.29-.75-.56,6.68-20.92,14.95-41.42,23.13-61.84,.13-.81,1.53-2.6,.09-2.8-7.13,.88-14.05,3.09-21.18,4-1.41-.19-.12-2,0-2.82,8.89-23.82,18.88-47.2,29.24-70.46,.19-.82,1.38-2.28-.05-2.46-7.65,.34-15.2,1.79-22.85,2.16-2,0-.21-2.24,0-3.22,12.04-28.51,24.92-56.77,38.73-84.5,.33-.12,.57-.28,.82-.29,8.7,.03,17.46-.23,26.14,.01,.34,.53,.27,.95,.06,1.35-.86,1.7-1.71,3.4-2.6,5.08-13.61,25.67-26.43,51.46-38.34,77.78-.48,1.68,2.4,.9,3.36,.93,5.07-.55,10.14-1.12,15.21-1.6M 6,1.73-.18,3.48-.32,5.22-.46,.59-.05,.96,.39,.73,.87-11.5,23.85-22.85,47.72-32.65,72.24-.09,1.45,3.69-.15,4.58-.11,5.33-1.13,10.66-2.29,15.99-3.41,.61-.02,1.77-.44,2.09,.27-6.31,15.65-13.81,30.95-19.66,46.79-1.97,5.56-4.9,10.94-6.23,16.68l-.25,.21Z"/><path class="cls-2" d="M433.2,580.84s.01,.09,.02,.14c-.05,0-.11,0-.16-.02l.14-.12Z"/><path class="cls-2" d="M439.57,639.7s.04,.01,.06,.01c.02,.02,.03,.03,.04,.05l-.1-.06Z"/><path class="cls-2" d="M592.51,667.17c-.61,1.88-1.2,3.76-1.82,5.63-.23,.71-.34,1.47-1.03,2.03-.6M 1-.03-.96-.36-1.28-.71-1.88-2.1-3.75-4.21-5.64-6.31-.73-.56-1.65-2.62-2.69-1.69-1.75,3.56-2.61,7.52-4.45,11.04-.94,.82-1.77-1.01-2.4-1.55-1.83-2.26-3.64-4.53-5.45-6.79-.49-.57-1.31-2.05-2.04-1.79-.44,.13-.59,.41-.73,.71-1.53,3.2-2.85,6.52-4.53,9.66-1.18,1.21-2.26-1.47-2.99-2.15-2.13-3-4.23-6-6.34-9.01-.27-.38-.59-.68-1.27-.71-2.4,3.27-3.43,7.59-6.48,10.38-3.6-4.41-6.11-9.6-9.52-14.17-.83-.44-1.36,.76-1.83,1.25-1.72,2.43-3.43,4.88-5.13,7.32-.28,.39-.64,.65-1.36,.66-3.21-5.01-5.96-10.33-8.95-15.48-.61-1.5-1.66-1.15-2M .37-.04-2.23,2.51-4.32,5.31-6.91,7.44-.69-.18-.95-.56-1.15-.94-.91-1.68-1.84-3.35-2.68-5.05-2.44-4.44-4.01-9.32-6.87-13.47-1.43,.61-2.13,1.71-3.14,2.54-2.22,1.74-4,3.88-6.58,5.18-.84-.52-1.06-1.27-1.37-1.98-2.95-6.88-5.95-13.82-8.88-20.7-.89-.05-1.39,.31-1.91,.65-2.53,1.6-5.06,3.22-7.61,4.8-2.21,1.38-2.28,.01-3.1-1.76-2.23-6.09-4.44-12.19-6.64-18.29-.64-1.76-1.24-3.52-1.86-5.28-.44-.9-1.69-.43-2.39-.08-3.21,1.59-6.72,2.69-10.02,4.18-.64,.54-.07,1.47,.05,2.14,2.86,8.53,6.21,16.92,9.38,25.39,.55,1.88-11.47-.31-12.9-.M 51-.24-.35-.56-.68-.71-1.06-3.49-9.12-7.4-18.14-9.98-27.5,.3-.74,1.46-.31,2.07-.28,3.02,.53,6.03,1.08,9.04,1.61,.6,.06,1.85,.22,1.93-.59-2.74-10.34-6.84-20.41-8.76-30.91,3.58-.3,6.93-2.14,10.41-3.03,.86-.27,1.65-.76,2.95-.6,2.72,9.81,5.26,19.94,8.57,29.62,.86,.17,1.45-.1,2-.38,3.21-1.55,6.28-3.42,9.58-4.78,.65-.08,.95,.62,1.11,1.13,1.66,4.99,3.28,9.99,4.99,14.97,1.03,3.01,2.2,5.99,3.31,8.98,.16,.42,.89,.6,1.3,.32,3.06-2.08,6.1-4.19,8.99-6.49,.29-.22,.88-.14,1.02,.13,3.28,6.99,5.68,14.4,8.99,21.38,1.06,.07,1.59-.66,M 2.28-1.25,2.1-2.11,4.18-4.22,6.26-6.34,.35-.36,.73-.62,1.44-.59,2.93,5.95,5.41,12.14,8.43,18.07,.21,.42,.52,.73,1.25,.84,2.6-2.78,4.68-6.04,7.21-8.87,.14-.14,.47-.16,.71-.24,.75,.51,.93,1.26,1.29,1.93,2.58,4.6,4.84,9.41,7.64,13.88,.19,.28,.85,.36,1.02,.11,1.38-2.09,2.75-4.18,4.12-6.28,.75-.76,1.9-4.07,3.07-3.23,2.5,3.64,4.54,7.57,6.89,11.31,.52,.86,.92,1.81,1.92,2.43,.66-.26,.91-.75,1.17-1.24,1.37-2.69,2.75-5.38,4.13-8.07,.29-.57,.49-1.2,1.21-1.57,.67,.25,.91,.76,1.23,1.23,2.4,3.49,4.59,7.13,7.19,10.47,.96,1.01,1.7M 2-.77,1.96-1.52,1.34-3.04,2.59-6.11,3.98-9.14,.73-.85,1.48,.28,1.95,.83,10.47,14.14,6.22,10.33,12.5-2.94,.76-.01,1.09,.33,1.37,.68,1.92,2.31,3.68,4.74,5.8,6.89l.05,7.55Z"/><path class="cls-2" d="M630.58,655.17l-.18,.12c.01-.07,.01-.13,.01-.2,.06,.02,.11,.05,.17,.08Z"/><path class="cls-2" d="M670.14,602.23s-.01,.07-.01,.11c-.04-.02-.09-.04-.13-.06l.14-.05Z"/><path class="cls-2" d="M725.84,587.44s.05-.06,.08-.09c.01,0,.03,0,.04,0l-.12,.08Z"/><path class="cls-2" d="M737.93,573.79c-3.6,4.74-8.1,8.99-12.01,13.56-2.68-.9M 9-5.34-1.97-8.02-2.95-1.27-.47-1.72-.4-2.39,.42-3.42,4.39-7.28,8.5-9.8,13.36,2.77,1.42,6,1.94,8.86,3.13,.12,1.3-.79,2.25-1.25,3.39-1.75,3.72-3.71,7.38-5.16,11.18-.04-.01-.08-.02-.12-.04-3.21-1.11-6.63-1.52-9.65-3.09,1.85-4.59,4.23-9.02,6.43-13.47,.29-.6,.08-1.15-.54-1.38-2.44-.89-4.88-1.78-7.33-2.66-.68-.2-1.21,.26-1.49,.78-2.26,4.47-4.52,8.94-6.76,13.42-.08,.16,.01,.36,.05,.55,0,.03,.01,.05,.01,.08-2.92-1.09-5.85-2.18-8.78-3.26-.32-.12-.91,.04-1.04,.27-2.49,4.7-3.85,9.94-6.43,14.59-2.65-1.06-5.29-2.12-7.94-3.17-.4M 8-.19-1.14,.02-1.33,.43-1.68,3.94-2.95,8.05-4.49,12.05-.32,.89-.5,1.67-1.37,2.24-2.73-1.03-5.14-2.42-7.85-3.45-.29-.11-.89,.1-.98,.37-1.55,4.7-3.08,9.35-4.62,14.06-.51-.03-.97,.04-1.28-.1-2.45-1.11-4.8-2.37-7.19-3.59-1.15-.28-1.34,1.29-1.67,2.06v-3.19c.07,.04,.14,.08,.22,.12,.85-.31,1.02-.82,1.19-1.35,1.16-3.54,2.31-7.08,3.5-10.61,.28-.83,.67-1.63,1.08-2.42,.06-.13,.5-.27,.68-.22,2.37,.91,4.48,2.38,6.73,3.54,.46,.25,.95,.36,1.66,.23,7.86-18.72,2.28-15.59,14.51-10.9,2.42-4.72,5.04-10.47,6.77-15.43,2.78,1.21,5.41,2.7M 6,8.31,3.69,.19,.05,.58-.06,.69-.2,2.6-4.31,4.74-8.89,7.17-13.3,.27-.49,.57-.97,1.36-1.23,2.52,1.04,5.09,2.42,7.78,3.2,.21,.06,.6-.02,.73-.16,3.03-3.6,5.36-7.72,8.29-11.41,2.88-3.44,1.82-3.23,6.34-1.33,1.89,.69,3.55,1.72,5.59,1.94,4.19-4.42,7.87-9.33,12.27-13.52,.26-.15,.8-.18,1.13-.05,2.73,1.14,5.47,2.28,8.15,3.4,0,.21,.01,.32-.01,.42Z"/><path class="cls-2" d="M97.05,1321.32c-.26-.52-.21-1.05-.07-1.58,1.66-6.31,3.3-12.62,4.86-18.95,.52-1.7-1.99-1.36-3.12-1.45-3.63-.05-7.27-.14-10.9-.15-11.29-.13-22.61-.41-33.87-.9M 5-.68-.21-1.05-.89-.98-1.57,.02-6.35,.05-12.69,.09-19.04-.09-1.45,1.46-1.34,2.53-1.34,15.32,.78,30.65,1.17,45.97,1.63,1.39,.32,6.08-.65,5.63,1.55-.67,2.74-1.36,5.48-2.06,8.22-.88,3.48-1.77,6.95-2.64,10.43-.16,.42,.06,.99,.51,1.09,15.45,.66,30.94-.26,46.4-.02l-.14-.11c-2.89,6.51-6.08,12.89-9.19,19.3-.35,.78-1.04,1.9,.35,2.09,13.1,.2,26.13-.94,39.23-1.16,.35,1.33-.84,2.19-1.42,3.28-3.73,5.61-7.46,11.21-11.18,16.82-.27,.48-.94,1.33-.2,1.66,11.28,.18,22.59-.94,33.88-1.16,.63-.01,.99,.44,.69,.85-5.6,7.39-12.02,14.21-17.M 45,21.72-.02,.67,.99,.64,1.49,.64,9.29-.3,18.57-.61,27.86-.9,.39-.06,.7,.18,.98,.4,.21,.3-.21,.6-.38,.84-7.42,7.81-14.59,15.85-22.15,23.53-8.3,.48-16.68,.05-25,.2-3.79,.1-1.15-1.94-.07-3.45,4.78-5.99,9.57-11.98,14.35-17.96,.58-.71,2.19-2.35,.33-2.51-9.69,.12-19.39,.69-29.07,.55-.28-.02-.69-.51-.6-.71,.09-.2,.15-.42,.27-.61,4.22-6.62,8.53-13.2,12.83-19.78,.59-.91,.18-1.35-1.2-1.3-11.17,.34-22.34,.83-33.52,.93-1.39-.07-.7-1.34-.38-2.08,1.94-4.13,3.9-8.25,5.84-12.38,1-2.11,1.99-4.23,2.97-6.34,.2-.43-.18-.88-.75-.89-13M .58,.28-27.26,.19-40.79,.64-.01,0,.09,.05,.09,.05Z"/><path class="cls-2" d="M1344.66,118.75c-.19,.28-.49,.54-.56,.84-1.66,6.53-3.31,13.06-4.95,19.6-.14,.56,.34,1.01,1.12,1.08,14.93,.46,29.87,.5,44.79,1.11,1.75,.03,2.56,.05,2.49,2.09,0,6.13,0,12.27-.01,18.4-.05,.63,0,1.47-.79,1.63-5.76,.01-11.56-.5-17.32-.7-9.28-.29-18.56-.57-27.84-.85-2.8-.15-5.66,.12-8.38-.66l.14,.13c2.14-6.26,3.27-12.84,4.97-19.23,.11-.57,.38-1.51-.39-1.69-8.17-.55-16.37-.06-24.55-.1-6.05,.06-12.1,.15-18.14,.22-1.04-.07-3.73,.42-2.99-1.35,2.93-6.M 23,5.96-12.43,8.93-18.64,.47-.98,.12-1.37-1.23-1.38-13.16,.09-26.33,.53-39.46,1.37l.16,.11c3.68-7.1,8.9-13.53,13.09-20.38,.84-1.37,.42-1.84-1.13-1.81-11.08,.26-22.09,.76-33.16,1.31-.28-1.4,1.05-2.13,1.74-3.18,4.79-5.86,9.58-11.72,14.36-17.59,1.49-1.89,1.95-2.52-.96-2.43-9.02,.3-18.04,.59-27.07,.8-1.51-.21-.63-1.23,.09-1.92,7.15-7.46,13.99-15.13,21.15-22.58,8.93-.32,17.97-.22,26.9-.05,.31,.51,.12,.88-.18,1.27-3.03,3.82-6.04,7.65-9.08,11.47-2.39,3-4.81,5.98-7.2,8.97-.38,.52-1.36,1.6-.24,1.84,9.83-.09,19.66-.56,29.49-M .58,.99,.29,.56,1.02,.21,1.62-4.13,6.41-8.31,12.81-12.43,19.22-.88,1.5,.64,1.51,1.74,1.5,10.51-.31,21.01-.63,31.52-.8,1.94,0,2.36,.21,1.6,2.19-1.98,4.23-4,8.46-5.99,12.69-.9,1.91-1.75,3.84-2.62,5.76-.18,.4,.23,.94,.72,.97,13.86,.15,27.75-.63,41.61-.15l-.14-.12Z"/><path class="cls-2" d="M488.94,146.58c11-30.71,22.64-61.24,35.4-91.29,.17-.41,.31-.84,.59-1.19,.58-.69,1.66-.66,2.52-.66,7.68,0,15.37,0,23.05,0,.61-.04,1.9-.04,1.89,.72-4.98,11.98-10.58,23.72-15.59,35.66-7.46,17.5-14.67,35.07-21.37,52.85-.36,1.09-.04,1.49,M 1.22,1.4,1.88-.13,3.75-.29,5.63-.47,5.22-.5,10.43-1.02,15.64-1.53,.95-.14,2.42-.03,1.91,1.22-10.59,25.37-20.38,50.95-29.09,76.95l.08-.06c-6.93,1.29-13.86,2.59-20.79,3.86-.79,.03-2.51,.66-2.67-.47,2.7-8.99,5.59-17.91,8.62-26.82,5.62-16.84,11.55-33.58,17.88-50.18,.14-.64,.7-1.72-.15-2-1.34,.01-2.68,.01-4.01,.13-6.95,.53-13.87,1.5-20.84,1.76l.08,.11Z"/><path class="cls-2" d="M1271.78,456.81c37.9,11.66,75.35,24.51,112.26,38.83,1.08,.41,2.29,.69,3.1,1.66,.24,6.39,.05,12.86,.11,19.26-.06,.79,.14,2.22-1.1,1.97-22.58-8.99-M 45.03-18.03-68.01-26.24-14.84-5.35-29.77-10.66-44.91-15.38-.52-.15-1.19,.19-1.19,.57,.41,5.8,1.28,11.58,1.86,17.37,.02,.21,0,.43,0,.65,0,.25-.58,.64-.84,.55-31.46-10.83-63.55-20.68-95.91-28.95l.07,.08c-.82-5.6-2.66-11.29-1.74-16.95,.43-.66,1.47-.25,2.12-.18,29.7,6.83,59.04,15.19,88.03,24.3,1.85,.58,3.59,1.47,5.65,1.54,.49,.02,.51-.16,.36-4.97,.05-4.65-.68-9.62,.26-14.16l-.13,.06Z"/><path class="cls-2" d="M1001.34,1295.62c-.43-.72-.33-1.44-.11-2.2,.79-2.71,1.54-5.44,2.32-8.16,2.81-9.72,5.37-19.48,7.83-29.26,1.74-6.9M 4,3.48-13.88,5.14-20.83,1.36-5.69,2.61-11.39,3.91-17.09,.22-.95,.39-1.91,1.17-2.71,0,0-.06,.03-.05,.02,.48,.59,1.3,.7,2.05,.87,6.14,1.65,12.62,2.46,18.56,4.68l-.06-.09c-.45,6.23-2.27,12.34-3.38,18.5-4.09,18.79-8.3,37.52-13.13,56.15-.13,.99-1.07,2.52,.47,2.83,7.81,1.11,15.63,2.2,23.43,3.41l-.07-.09c-3.31,10.9-5.35,22.19-8.4,33.21-4.7,17.08-8.75,34.48-14.43,51.26-2.82,.26-16.49,.72-27.26,.03,8.33-28.47,17.65-56.76,24.94-85.56,.14-.53,.18-1.07,.25-1.6,.02-.46-.81-1-1.35-1-6.78-.89-13.55-1.78-20.33-2.67-.54-.07-1.07-.0M 5-1.5,.28v.02Z"/><path class="cls-2" d="M418.87,224.39c-.33-.54-.99-.67-1.62-.82-3.96-.92-7.93-1.82-11.89-2.74-2.23-.73-5.77-.93-7.25-2.24,5.17-24.77,10.5-49.52,16.86-74.03,.08-1.05,1.16-2.81-.47-3.14-6.5-.93-13-1.81-19.5-2.75-.92-.13-1.83-.36-2.72-.59-.2-.05-.43-.33-.43-.5,.84-6.32,2.86-12.49,4.25-18.73,5.56-21.74,11.27-43.51,17.86-64.96,.61-.64,1.79-.4,2.62-.49,7.41,0,14.83,0,22.24,.02,.84,0,2.46-.19,2.41,1-4.75,15.91-10.12,31.69-14.58,47.68-3.49,12.83-7.62,25.53-10.57,38.48-.16,1.04,1.47,1.23,2.31,1.33,4.38,.59,M 8.76,1.2,13.15,1.77,2.26,.29,4.53,.54,6.8,.78,.23,.02,.49-.14,.73-.21h0c.53,.56,.56,1.19,.37,1.83-3.91,13.36-7.53,26.81-10.92,40.28-2.12,8.42-4.31,16.82-6.03,25.3-.75,3.71-1.71,7.39-2.59,11.08-.15,.65-.51,1.22-1.1,1.7,0,0,.06-.01,.06-.01Z"/><path class="cls-2" d="M1287.14,363.02c-.97,5.98-2.15,11.93-3.26,17.89-.34,1.49-2.25,.69-3.29,.61-28.6-6-57.55-10.64-86.51-14.64l.15,.12c2.27-5.06,3.61-10.59,5.53-15.82,.47-1.77-3.38-1.3-4.48-1.66-3.07-.33-6.13-.64-9.2-.95-20.7-2.28-41.53-2.93-62.3-4.3l.15,.1c1.99-4.1,3.97-8.21,M 5.99-12.31,1.84-3.73,2.09-3.71-3.31-3.78-9.68-.15-19.36-.1-29.04-.05-10.35,.12-20.69,.64-31.04,.76-1.66-.34-.29-1.81,.11-2.67,2.63-4.35,5.3-8.68,7.91-13.05l-.1,.05c21.86-.81,43.72-1.72,65.6-1.27l-.09-.1c-1.75,4.63-4.6,8.95-6.72,13.47-.53,1.34-2.21,3.09,.67,3.08,24.21,.52,48.35,2.2,72.47,4.24l-.1-.11c-1.51,5.86-4.27,11.3-5.73,17.19,28.95,3.92,58.02,7.7,86.72,13.3l-.11-.1Z"/><path class="cls-2" d="M1096.34,280.31c19.3-1.43,38.66-2.02,58.01-2.49,.83,.14,4.47-.48,4.09,.81-2.39,4.7-5.14,9.22-7.66,13.85-.25,.73-1.55,2.15M -.37,2.54,23.27,.07,46.5,1.04,69.74,2.13l-.14-.09c-1.39,5.36-4.11,10.45-5.99,15.7-.29,.71-.65,1.41-.4,2.23,10.15,1.5,20.53,1.84,30.74,3.05,17.05,1.67,33.95,4.62,50.98,6.27l-.07-.09c-.22,.5-.53,.99-.64,1.5-1.09,5.99-2.75,11.92-3.43,17.95l.13-.05c-9.65-.58-19.25-3-28.9-4.16-18.66-2.73-37.43-4.72-56.18-6.83l.1,.11c2.04-5.7,4.9-11.45,6.2-17.22-23.96-2.93-48.44-2.85-72.62-3.56l.09,.1c2.85-5.22,5.7-10.44,8.55-15.66,.54-1.07-.6-1.27-1.49-1.22-20.73-.09-41.43,.84-62.13,1.92l.08,.12c3.76-5.62,7.51-11.24,11.27-16.87l.04-.03ZM "/><path class="cls-2" d="M1189.33,383.81c30.14,4.3,59.95,10.21,89.61,16.81,.72,.14,1.41-.21,1.51-.76,1.04-5.32,1.92-10.65,2.88-15.98,.34-1.99,1.77-1.33,3.25-1.1,33.63,7.05,66.61,15.51,99.38,24.94,1.16,.3,1.37,1.15,1.32,2.11,0,5.92,0,11.85,0,17.77,0,2.07-.27,2.56-3.01,1.74-10.45-3.15-20.89-6.34-31.4-9.39-23.4-6.81-47.12-13.01-70.99-18.59-1.14-.26-1.71,.07-1.88,1.1-.88,5.34-1.72,10.68-2.65,16.01-.13,.76-.76,1.08-1.75,.86-30.36-7.78-61.27-13.66-92.08-19.49l.17,.12c2.07-4.64,3.15-9.69,4.81-14.5,.19-.63,.37-1.24,.91-1.M 75l-.09,.09Z"/><path class="cls-2" d="M52.33,141.44c0-6.17-.02-12.66,0-18.89,.13-.85-.31-2.56,1.11-2.25,4.43,1.92,8.61,4.43,12.93,6.6,4.55,2.27,8.84,5.07,13.53,7.02,.14,.05,.59-.16,.61-.28,.13-.74,.24-1.49,.23-2.23-.09-7.22-.25-14.43-.3-21.65,0-.43,.05-.86,.08-1.29,.37-1.4,3.53,.54,4.51,.71,5.84,2.22,11.67,4.45,17.5,6.67,1.39,.27,5.46,2.94,5.36,.29,0-.65-.02-1.29-.02-1.94,0-9.05-.24-18.1-.04-27.15,.03-1.04,.52-1.36,1.76-1.11,4.44,.88,8.88,1.78,13.32,2.66,2.61,.52,5.23,1.02,7.83,1.56,4.25,.89,4.21,1.44,4.28-2.74,.26M -11.09,.33-22.19,.79-33.28,.03-1.31,1.65-1.34,2.69-1.3,8.07,.13,16.2-.23,24.24,.17,1.12,.36,.83,1.67,.86,2.58-.36,7.43-.78,14.85-1.1,22.28-.2,4.63-.26,9.26-.4,13.89-.31,1.36,.72,4.71-1.6,4.33-8.3-1.13-16.41-3.87-24.72-4.55-1.54,.09-.71,7.51-.95,9.06,0,7.97,0,15.94,0,23.91-.22,1.1,.65,3.9-1.29,3.38-8.01-3.04-15.9-6.4-23.94-9.37-2.04-.92-1.64,1.32-1.66,2.56-.19,9.25,.8,18.55,.4,27.76-.54,.52-1.51-.08-2.08-.35-5.77-3.18-11.51-6.38-17.29-9.55-2.33-1.28-4.73-2.47-7.11-3.69-.3-.16-.88,.09-.9,.39-.24,7.2,.27,14.43,.36,21.M 63,.06,3,0,3.4-.53,3.33-1.41-.2-2.19-1.15-3.19-1.82-7.65-5.12-15.27-10.25-22.91-15.38-.82-.55-1.75-1.01-2.37-1.99Z"/><path class="cls-2" d="M1305.47,1311.84c.95-.16,1.82,.09,2.67,.47,7.71,3.09,15.42,6.18,23.2,9.12,1.27,.47,1.41-.79,1.35-1.68-.1-8.83-.27-17.66-.45-26.49-.01-.64,.07-1.28,.12-1.93,.02-.24,.65-.54,.89-.42,1.03,.51,2.07,1.01,3.07,1.56,7.44,4.09,14.79,8.34,22.37,12.17,.45,.23,1.12-.1,1.12-.55,.09-8.17-.53-16.35-.52-24.51,.75-.37,1.24-.12,1.85,.28,8.73,6,17.72,11.65,26.3,17.84,.53,6.78,.06,13.73,.21,20.56M ,.02,.52-.21,1.28-.86,1.19-8.17-3.82-15.97-8.43-24.01-12.53-3.09-1.65-2.73-.79-2.8,2.1,.08,6.68,.18,13.36,.25,20.03,0,.85-.11,1.71-.24,2.56-.47,.62-1.48,.05-2.08-.11-8.07-2.95-15.99-6.3-24.16-8.96-.27-.09-.85,.27-.85,.52-.02,2.37-.05,4.73-.05,7.1,.03,7.32,.07,14.65,.1,21.97-.06,.72-.01,1.81-1,1.84-8.72-1.21-17.3-4.11-26.01-4.85-.75,11.35-.6,22.79-.98,34.17-.08,3.89,.08,3.71-4.66,3.71-6.6-.01-13.21-.02-19.81-.03-1.33,0-3.67,.26-3.42-1.69,.64-12.05,1.15-24.1,1.44-36.17,.05-1.61,.23-3.22,.35-4.82,.02-.22,.59-.62,.84-.M 6,7.37,1.01,14.63,2.92,21.96,4.26,3.07,.37,4.24,1.31,4.09-2.57-.19-11.18,.47-22.44-.23-33.58l-.03,.06Z"/><path class="cls-2" d="M161.33,138.68c-.15,13.24,.38,26.5,.36,39.72-.26,.31-1.03,.27-1.41,.02-5.86-3.01-11.47-6.43-17.24-9.59-1.99-1.11-4.02-2.17-6.05-3.23-2.19-.71-1.01,2.76-1.2,3.91,.33,9.15,.72,18.3,1.18,27.45,.15,1.97-.1,3.27-2.21,1.65-6.19-4.32-12.38-8.64-18.58-12.96-1.72-1.2-3.43-2.42-5.19-3.59-.23-.16-.72-.07-1.17-.11-.07,8.66,.87,17.24,1.22,25.89,.05,.86,0,1.72-.01,2.58-.02,.36-.73,.36-.9,.29-6.21-4.51-1M 1.91-9.67-17.94-14.42-2.83-2.3-5.7-4.58-8.57-6.85-1.85-1.02-1.21,1.73-1.24,2.77,.26,6.46,.53,12.92,.78,19.38-.06,.53,.11,1.52-.31,1.83-.23,.04-.58,.1-.71,0-9.05-7.73-17.63-16.03-26.56-23.91-1.34-1.32-3.42-2.54-3.19-4.63,.15-6.49-.22-12.99,.15-19.46,1.59-.29,2.55,1.25,3.75,2.01,7.8,6.26,15.59,12.52,23.39,18.77,.69,.44,1.3,1.32,2.22,1.07,.08-.01,.18-.16,.19-.24,.04-.86,.11-1.72,.09-2.57-.2-6.68-.42-13.35-.62-20.03,.06-.74-.31-2.31,.92-2.01,2.42,1.26,4.57,3.01,6.85,4.5,6.11,4.24,12.2,8.48,18.3,12.72,.43,.33,1.17,.8,1.M 73,.44,.1-.42,.22-.84,.21-1.26-.24-9.35-.92-18.72-.77-28.06,1.21-.42,2.17,.62,3.23,1.04,7.11,3.89,14.22,7.8,21.33,11.69,2.09,1.22,2.16,.48,2.17-1.58-.2-9.26-.42-18.52-.61-27.78-.09-4.58-.04-4.93,.6-4.95,2.15-.07,3.72,1.1,5.5,1.77,6.83,2.56,13.6,5.21,20.39,7.83l-.08-.08Z"/><path class="cls-2" d="M1305.5,1311.78c-.18-.92-1.32-.9-2.03-1.29-8.13-3.17-16.24-6.39-24.41-9.46l.08,.07c.38-13.13-.51-26.28-.18-39.4,.01-.25,.65-.53,.92-.39,2.24,1.2,4.49,2.38,6.7,3.6,5.2,2.88,10.38,5.79,15.58,8.67,.74,.28,2.13,1.36,2.66,.37,.03M -11.07-1.11-22.14-1.16-33.21,.99-.39,1.64,.38,2.43,.83,5.9,4.1,11.79,8.2,17.67,12.31,2.21,1.32,4.06,3.4,6.52,4.19,.1,.02,.32-.06,.35-.13,.58-9.47-1.03-19.13-1.04-28.65,1.25-.21,2.01,.92,2.95,1.51,5.57,4.54,11.1,9.1,16.69,13.62,2.65,2.14,5.37,4.23,8.06,6.34,.23,.18,.5,.15,.73-.03,.4-.36,.25-1.03,.31-1.52-.11-2.8-.25-5.6-.35-8.39-.17-4.52-.33-9.04-.47-13.56,.39-1.82,2.22,.47,2.95,1.02,8.72,7.92,17.45,15.84,26.17,23.77,1.33,1.03,.96,2.55,1.02,3.98,0,5.17,0,10.34,0,15.51,.34,4.94-1.76,2.26-4.11,.55-8.05-6.34-15.87-12.9M 7-24.04-19.15-1.18-.56-1.03,1.16-1.03,1.87,.18,5.06,.38,10.12,.55,15.18,.08,2.37,.09,4.74,.12,7.11-.14,.64-.61,.9-1.39,.39-7.81-5.27-15.52-10.67-23.25-16.05-.92-.56-1.77-1.51-2.93-1.51-.5,.03-.54,.44-.53,.74,.31,9.04,.65,18.08,.94,27.13,.01,2.23-1.25,1.49-2.64,.79-7.22-3.96-14.43-7.93-21.65-11.89-.85-.4-1.56-1.07-2.57-.68-.16,11.93,1.07,23.91,.37,35.83,0,.02,.02-.04,.02-.04Z"/><path class="cls-2" d="M804.53,817.99l-.32,14.35c-.82,1.22-1.3,5.49-3.43,3.79-2.12-1.64-4.23-3.29-6.36-4.95,1.43-5.05,3.88-9.86,5.7-14.81,.0M 8-.19,.29-.35,.45-.54,1.69,.18,2.63,1.39,3.96,2.16Z"/><path class="cls-2" d="M987.06,901.51s.07-.02,.1-.03c.01,.05,.01,.11,.02,.16l-.12-.13Z"/><path class="cls-2" d="M993.65,862.79s-.05,.02-.08,.04c-.02-.03-.03-.07-.05-.1l.13,.06Z"/><path class="cls-2" d="M1000.92,896.97s-.01,.09-.02,.14c-4.74,.99-9.15,2.93-13.74,4.37-1.28-10.69-3.6-21.25-5.81-31.78-.25-1.19-1.07-1.06-2.02-.62-3.43,1.6-6.74,3.52-10.14,5.16-.3-.19-.61-.29-.65-.43-.56-2.22-1.11-4.43-1.6-6.66-1.69-6.8-2.97-13.93-5.4-20.5-.68-.46-1.47,.21-2,.57-2.7,2.2M 5-5.38,4.53-8.06,6.8-.37,.31-.74,.6-1.35,.54-.62-.73-.75-1.59-.98-2.43-1.83-6.73-3.48-13.49-5.72-20.15-.21-.63-.36-1.27-1-1.72-.6,.03-.95,.34-1.28,.68-2.48,2.55-4.96,5.1-7.43,7.65-.34,.35-.71,.64-1.33,.63-3.01-6.76-3.99-14.41-7.38-21.06-.67-.46-1.28,.45-1.69,.87-2.29,2.79-4.36,5.73-6.78,8.41-.16,.13-.83,.21-1.01-.03-.42-1.02-.84-2.04-1.22-3.07-1.63-4.45-3.24-8.89-4.88-13.33-.26-.7-.42-1.45-1.12-2-.61,.08-.9,.45-1.15,.83-2.19,3.21-4.1,6.61-6.5,9.66-.23,.28-.75,.04-.88-.15-1.82-4.39-3.63-8.79-5.49-13.17-.34-.81-.8-1.M 59-1.26-2.36-.08-.12-.44-.16-.67-.19-.67,.29-.97,1.3-1.41,1.88-1.42,2.56-2.81,5.13-4.23,7.68-.41,.51-.85,1.76-1.67,1.29-2.22-3.89-4.09-7.95-6.19-11.91-.31-.59-.59-1.2-1.46-1.6-2.43,3.75-3.71,8.11-6.11,11.88-.84-.24-1.07-.75-1.34-1.22-1.98-3.29-3.72-6.73-5.92-9.9-.16-.23-.62-.32-1.08-.55-1.93,3.96-3.3,8.02-5.26,11.95-.27,.41-.95,.3-1.2-.05-2.02-2.9-3.92-5.89-5.93-8.81-.18-.25-.54-.43-.84-.61-.07-.05-.33-.03-.38,.03-1.42,2.29-2.09,5.01-3.2,7.47l.28-12.62c.79,.98,1.56,1.97,2.36,2.94,.11,.14,.46,.28,.63,.24,.22-.06,.46M -.27,.54-.45,1.81-3.88,2.87-8.09,4.71-11.96,.7,.02,1.08,.29,1.36,.68,1.61,2.24,3.22,4.48,4.83,6.72,.6,.84,1.17,1.69,1.77,2.53,.22,.31,.77,.09,.95-.09,1.88-3.51,3.13-7.34,4.78-10.96,.19-.44,.59-.72,.82-.59,1.18,.56,1.63,1.88,2.36,2.87,1.62,2.6,3.23,5.21,4.84,7.82,.29,.47,.56,.95,1.22,1.18,2.21-2.78,3.46-6.94,5.25-10.12,.24-.51,.51-.99,1.27-1.29,2.98,4.24,5.17,8.98,7.94,13.37,.15,.15,.77,.38,.98,.09,1.91-2.81,3.44-5.83,5.21-8.74,1.46-2.59,1.87-1.11,3.01,.64,2.41,4.45,4.47,9,6.61,13.53,.28,.46,.9,.32,1.18-.04,2.1-2.87M ,4.11-5.82,6.19-8.7,.27-.37,.56-.74,1.15-.86,.66,.4,.85,1.03,1.12,1.62,2.16,4.76,4.1,9.57,5.93,14.42,.39,.84,.57,3.01,1.95,2.75,2.71-2.6,4.97-5.61,7.5-8.39,.32-.37,.71-.62,1.39-.58,12.41,27.39,3.01,24.73,18.54,13.13,.75,.53,.93,1.16,1.14,1.78,2.75,7.6,4.97,15.38,7.52,23,.94,.13,1.41-.29,1.92-.62,2.54-1.61,5.06-3.22,7.6-4.82,.56-.29,1.48-.95,2.08-.51,3.37,9.35,5.28,19.16,7.97,28.72,1.79-.09,3.01-1.01,4.42-1.57,2.72-1.1,5.41-2.32,8.11-3.45,1.64,3.8,2.13,8.1,3.16,12.11,1.33,7.34,3.42,14.66,4.19,22.03Z"/><path class="cM ls-2" d="M1246.01,141.96c-9.51,.74-19.07,1-28.58,1.69-4.83,.21-9.66,.86-14.49,.82-1.22-.41,.59-1.79,.91-2.4,3.34-4.04,6.7-8.08,10.03-12.12,1.63-1.98,3.23-3.97,4.81-5.97,.19-.25,.35-.64,.24-.89-.22-.52-.88-.35-1.36-.31-7.38,.52-14.75,1.06-22.13,1.59-4.56,.27-9.11,.81-13.68,.87-.38,.04-.57-.46-.47-.71,5.94-6.71,12.34-13.04,18.45-19.61,.75-.9,1.84-1.54,1.92-2.79-10.51,.23-20.94,1.48-31.43,2.17-.65-.06-2.23,.38-2.32-.46,7.46-7.86,15.72-14.99,23.39-22.65,1.04-1.01,1.95-2.1-.3-2.04-9.28,.28-18.54,1.04-27.81,1.21-.4-.6,.0M 3-.98,.46-1.4,9.82-8.63,19.35-17.59,29.34-26.03,8.24-.33,16.6-.05,24.86-.14,.66,.05,2.3-.2,1.91,.89-7.86,7.98-16.15,15.57-24.16,23.42-.56,.65-1.6,1.25-.2,1.7,9.42-.33,18.83-.67,28.25-.92,1.43,.18,.32,1.39-.23,1.95-6.25,6.77-12.66,13.41-19,20.1-.34,.51-1.54,1.42-.65,1.82,1.34,0,2.69-.01,4.02-.09,9-.5,18-1.03,27-1.58,.89,.06,3.57-.54,2.62,1.09-4.99,6.29-10.18,12.43-15.24,18.66-.5,.84-1.65,1.52-1.43,2.57,1.33,.33,2.66,.08,3.99-.01,11.93-.76,23.91-1.64,35.88-1.66l-.16-.11c-5.04,7.01-9.71,14.27-14.58,21.4l.12-.05Z"/><paM th class="cls-2" d="M796.17,795c.02-.06,.04-.12,.05-.18,.03,.02,.07,.03,.1,.05l-.15,.13Z"/><path class="cls-2" d="M805.72,765.78l-.37,16.24c-1.26-.28-4.66-3.12-5.21-1.17-1.46,4.62-2.33,9.38-3.92,13.97-4.99-2.35-6.59-2.97-9.39-3.67-1.52,3.95-2.35,8.12-3.61,12.15-.24,.83-.39,1.69-1.25,2.43-3.08-.93-5.99-2.57-9.22-3.02,1.45-4.8,2.53-9.71,4.1-14.47,.09-.25,.66-.51,.96-.41,2.25,.71,4.49,1.44,6.73,2.15,1.53,.52,2.27,.69,2.71-1.12,.96-3.91,1.89-7.82,2.84-11.73,.19-.78,.89-1.13,1.73-.83,2.62,.95,5.37,1.95,7.92,2.99,.94-.46M ,.99-1.14,1.14-1.75,.65-2.74,1.24-5.5,1.86-8.26,.26-1.16,.54-2.32,.83-3.48,.26-.9,1.52-.33,2.15-.02Z"/><path class="cls-2" d="M964.52,753.47s.04,.05,.05,.07c-.07,.02-.13,.05-.2,.08l.15-.15Z"/><path class="cls-2" d="M977.5,752.9h-.05s-.03-.04-.04-.06l.09,.06Z"/><path class="cls-2" d="M988.27,774.2c-2.29,.1-4.57-.04-6.86,0-5.54,0-5.43-.47-3.31,3.77,3.26,6.69,6.46,13.39,9.03,20.29-.22,.25-.32,.48-.53,.58-3.7,1.68-7.24,3.95-11.06,5.27-.8-.34-.91-1.02-1.16-1.6-1.18-2.75-2.26-5.52-3.48-8.26-1.81-4.05-3.7-8.08-5.55-12.12-M .24-.51-.48-1.01-1.26-1.3-3.5,1.68-6.37,4.15-9.48,6.39-1.53,.86-1.77-1.38-2.4-2.26-2.38-4.57-4.75-9.14-7.16-13.7-.57-1.08-1.27-2.13-1.95-3.18-.08-.12-.52-.21-.7-.15-2.29,1.3-3.99,3.5-6.03,5.17-1,.83-1.71,2.09-3.07,2.37-3.92-5.34-6.55-11.42-10.42-16.8-.2-.28-.83-.36-1.03-.13-2.34,2.73-4.63,5.52-6.82,8.37-1.48,.89-2.37-2.19-3.23-3.05-2.3-3.4-4.61-6.81-6.93-10.21-.32-.48-.64-.96-1.52-1.12-9.87,13.96-3.24,12.52-16.86-2.81-.69,.21-1,.53-1.2,.95-1.33,2.7-2.67,5.4-4.01,8.1-.33,.61-.54,1.31-1.33,1.44-3.12-3-5.54-6.6-8.47-9M .81-.42-.4-1.08-1.29-1.72-.77-1.97,3.33-2.73,7.26-4.62,10.63-.96,.79-1.82-.97-2.5-1.5-2.44-2.39-4.49-5.26-7.22-7.33-.14-.08-.63-.03-.67,.05-.35,.7-.68,1.4-.92,2.13-.89,2.7-1.74,5.42-2.63,8.12-.81,2.96-2.69,.03-3.92-.95l.38-16.84c2.14,1.82,4.13,3.78,6.22,5.65,.21,.19,.7,.19,1.14,.29,1.26-3.47,2.39-6.85,3.62-10.31,.53-1.55,1.5-.99,2.36-.1,2.1,2.1,4.16,4.24,6.27,6.33,.75,.74,1.25,1.66,2.41,2.09,1.43-.57,1.27-1.81,1.73-2.76,1.26-2.58,2.17-5.34,3.54-7.84,.71-.03,1.12,.21,1.45,.58,1.58,1.74,3.19,3.47,4.75,5.22,1.51,1.65,M 2.79,3.47,4.43,5,.21,.2,.88,.11,1.03-.15,1.76-3.14,3.43-6.33,5.37-9.38,.16-.25,.82-.26,1.05,0,3.67,4.01,6.73,8.55,10.24,12.7,.69-.11,1.03-.4,1.3-.79,1.96-2.77,3.82-5.72,5.99-8.32,.73-.02,1.1,.25,1.38,.64,3.45,4.59,6.66,9.36,9.98,14.03,.2,.26,.82,.3,1.05,.06,2.73-2.52,4.88-5.56,8-7.66,.99,.24,1.37,1.23,1.93,1.97,2.95,4.71,5.88,9.44,8.81,14.16,.36,.57,.58,1.2,1.45,1.59,1.86-.84,8.99-7.82,10.3-6.53,3.55,5.6,6.38,11.62,9.67,17.39,.53,.66,.94,2.31,1.97,2.12,3.48-1.83,6.94-3.68,10.39-5.56,.32-.17,.43-.52,.28-.87-3.61-6.6M 9-7.26-13.45-11.2-19.94,4.11-1.15,8.63-.33,12.88-.64,3.84,5.95,6.95,12.31,10.42,18.46,.25,.77,1.71,2.52,.4,2.84Z"/><path class="cls-2" d="M695.81,884.63c-5.2,4.48-10.89,8.31-16.14,12.75,2.65,2.02,5.92,3.39,8.37,5.67-6.37,4.71-13.03,8.46-19.43,13-.45,.71,.53,1.13,.96,1.57,1.53,1.21,3.1,2.39,4.62,3.62,.54,.44,1.2,.84,1.43,1.64-3.93,3.06-8.89,5.16-13.18,7.79-3.24,2.07-6.94,3.28-10.06,5.54,.91,.92,1.83,1.84,2.75,2.77-3.65,.27-7.31,.56-11.01,.87,8.98-4.76,9.83-2.01,1.98-9.46-.38-.51-1.72-1.14-1.07-1.81,6.66-3.49,13.45-6M .74,19.82-10.54,.96-.61,2.06-.9,2.54-2.02-2.6-1.91-5.17-3.81-7.77-5.72,.93-1.27,2.4-1.73,3.68-2.57,5.14-2.96,9.95-6.25,14.79-9.52,.36-.25,.88-.49,.65-1.11-2.6-1.58-5.33-3.15-8.14-4.62-.19-.11-.51-.06-.89-.1-6.16,3.97-12.65,7.62-18.82,11.53-.12,.14-.12,.47,.01,.59,2.3,1.86,4.93,3.35,7.35,5.04,.48,.33,.48,.8-.03,1.08-6.62,3.82-13.53,7.11-20.47,10.35-.54,.26-1.19,.46-1.37,1.15,2.23,1.93,4.58,3.92,6.83,5.87,.52,.45,.42,1.05-.24,1.35-2.44,1.14-4.85,2.34-7.38,3.31l-.13-21.28c4.67-2.22,9.53-4.18,13.86-6.94,.8-1.06-6.72-4.M 69-7.82-5.64-.29-.17-.26-.66,.03-.85,6.2-3.59,12.4-7.29,18.7-10.69,3.34,1.02,6.37,3.21,9.54,4.63,.68,.06,1.03-.29,1.44-.56,5.65-3.59,10.59-7.99,15.94-11.73,2.88,.65,5.66,2.73,8.41,3.92,.48,.24,.59,.82,.25,1.12Z"/><path class="cls-2" d="M1271.91,182.14c2.73-7.07,6.55-13.84,9.65-20.8l-.07,.07c17.28-.01,34.6,.47,51.86,.01l-.14-.13c-.71,6.33-3.05,12.44-4.39,18.68-.19,.73-.25,1.49-.3,2.23-.01,.15,.25,.39,.46,.45,14.71,1.24,29.56,1.19,44.29,2.39,4.03,.25,8.05,.53,12.07,.8,.79,.08,2.01,.02,2.11,1.04,.16,6.45,0,12.91,.04,1M 9.37-.04,.58-.05,1.52-.78,1.63-21.32-1.03-42.62-3.68-63.97-3.86l.1,.09c1.53-6.1,3.07-12.2,4.59-18.31,.05-.88,.86-2.66-.43-2.9-18.39-.7-36.79-.69-55.19-.89l.12,.12Z"/><path class="cls-2" d="M976.39,1292.07c5.18,.62,10.37,1.25,15.55,1.87,3.1,.54,6.5,.36,9.39,1.68v-.02c-.6,.1-.88,.44-1.01,.88-.52,1.78-1.04,3.56-1.55,5.35-8.27,28.13-17.38,56.08-27.38,83.69-.39,.99-1.88,.78-2.79,.83-8.26-.1-16.48,.2-24.74-.15,6.32-19.51,14.76-38.71,21.08-58.29,3.91-11.31,7.57-22.66,11.35-34,.21-.63,.39-1.25,.2-1.91,0,0-.1,.06-.1,.06Z"/>M <path class="cls-2" d="M439.08,144.22c.41-.01,.86-.08,.97-.43,.53-1.67,1.03-3.34,1.52-5.01,8.58-28.57,17.51-57.17,28.03-85.12,8.76-.53,17.57-.01,26.36-.15,.25,0,.49,.14,.73,.21,.27,.55,.05,1.05-.15,1.57-2.01,5.24-4.07,10.48-6.01,15.74-9.6,25.48-18.63,51.2-27.02,77.06-.01,0,.08-.07,.06-.06-.38-.5-1.01-.65-1.68-.73-7.58-1.05-15.4-1.25-22.81-3.09Z"/><path class="cls-2" d="M164.64,1020.42c-36.95-9.62-73.85-19.97-109.74-32.76-.65-7.42-.2-18.46,.08-21.23,1.8-.34,3.52,.83,5.23,1.28,35.47,12.52,71.18,24.54,107.68,34.07l-.1M -.08c-1.18,6.27-1.91,12.61-3.27,18.85l.12-.12Z"/><path class="cls-2" d="M266.45,1007.52s.07,.01,.1,.02v.06l-.1-.08Z"/><path class="cls-2" d="M266.57,990.7v.13s-.09-.01-.13-.02l.13-.11Z"/><path class="cls-2" d="M347.32,1020.54v-.09s.08,0,.12,0l-.12,.09Z"/><path class="cls-2" d="M413.73,997.92s-.05-.03-.07-.04c0-.01-.01-.02-.01-.03l.08,.07Z"/><path class="cls-2" d="M414.03,1011.28c-19.69-1.18-39.35-2.47-58.91-5.01-2.39-.18-4.8-.8-7.2-.66-.22,.04-.51,.25-.54,.41-.41,4.78,.01,9.63-.06,14.43-27.12-2.76-54.1-7.37-80.77-1M 2.91,0-5.57-.12-11.14,.02-16.71,26.41,5.23,52.81,11.4,79.68,14.09,.77-.13,.65-1.08,.66-1.67-.17-3.44-.35-6.88-.53-10.32-.04-1-.43-2.74,1.15-2.58,20.65,3.14,41.45,5.57,62.31,6.93l4.19,14Z"/><path class="cls-2" d="M415.36,1011.41l-.13,.1s.02-.07,.03-.11c.03,0,.07,.01,.1,.01Z"/><path class="cls-2" d="M158.18,1057.92c-34.73-7.53-69.69-15.4-103.48-26.1-.46-6.71,.02-13.55-.1-20.29,0-.32,.13-.63,.2-.91,.56-.27,1.06-.15,1.57,0,2.77,.84,5.54,1.67,8.31,2.51,31.76,9.85,64.28,18.18,96.7,26.17l-.07-.09c-.51,6.33-2.25,12.55-3.25M ,18.83l.13-.11Z"/><path class="cls-2" d="M822.93,1306.26c8.25-.92,16.47-2.37,24.78-2.59,.89,.29-.05,1.69-.22,2.29-13.05,26.32-27.1,52.19-41.6,77.79-.49,.87-.8,1.84-1.92,2.55-8.15,.24-16.37,.04-24.53,.1-.68-.06-2.24,.2-2.25-.74,15.76-26.21,31.38-52.55,45.84-79.46l-.09,.07Z"/><path class="cls-2" d="M342.37,130.12c4.44-25.31,10.01-50.4,15.64-75.48,.24-1.53,1.96-1.22,3.17-1.27,7.27,0,14.55,0,21.83,0,.93,0,1.9-.11,2.81,.36-6.21,26.36-13.25,52.65-18.43,79.28-.23,1.29-1.75,1.25-2.77,1.01-5.68-.9-11.35-1.81-17.03-2.71-1.6-M .29-4.36-.39-5.22-1.2Z"/><path class="cls-2" d="M1073.79,1305.5c7.27,1.12,14.55,2.22,21.81,3.37,2.58,.33,2.62,.81,2.24,3.24-4.58,24.75-9.6,49.41-15.48,73.9-1.17,.52-2.35,.39-3.58,.41-6.87,0-13.75,0-20.62-.01-2.95-.1-3.58,.41-2.78-2.97,6.94-25.84,12.51-52,18.53-78.03,0,0-.12,.1-.12,.1Z"/><path class="cls-2" d="M154.84,843.36c.94,6.3,1.77,12.61,2.5,18.94-.23,.71-1.01,.55-1.59,.28-29.78-13.91-58.92-28.75-87.62-44.53-3.55-1.95-7.09-3.92-10.63-5.89-1.36-.84-3.39-1.47-3.05-3.42-.02-6.03-.03-12.06-.03-18.09,.06-.73,.02-1.M 96,1.15-1.55,6.71,3.74,13.21,7.82,19.92,11.6,26.03,15.01,52.55,29.21,79.42,42.75l-.08-.08Z"/><path class="cls-2" d="M1291.21,343.66c19.67,4.02,39.62,7.12,59.15,11.6,11.43,2.47,22.85,4.99,34.18,7.73,.9,.22,1.85,.33,2.64,1.05,.41,6.56,.03,13.26,.14,19.86,.09,2.43-1.57,1.37-3.13,1.14-32.05-8.44-64.42-15.72-97.05-22.03l.11,.1c1.5-6.46,1.94-13.24,4.09-19.5l-.13,.05Z"/><path class="cls-2" d="M151.08,1095.92c-32.28-4.74-64.34-11.96-96.08-19.4-.71-.64-.71-1.29-.71-1.94-.01-5.92,.02-11.85,.15-17.77-.03-2.97,1.3-1.99,3.43-1.M 59,31.24,8.07,62.66,15.29,94.41,21.35,.76,.17,2.07,.21,1.94,1.25-.36,2.13-.74,4.26-1.14,6.39-.47,2.56-1.03,5.1-1.43,7.67-.22,1.38-.92,2.72-.7,4.14l.12-.1Z"/><path class="cls-2" d="M476.1,686.24s.01,.02,.01,.03c-.05,.03-.11,.05-.16,.08l.15-.11Z"/><path class="cls-2" d="M488.04,705s.06,.01,.09,0c.02,.02,.03,.05,.05,.07l-.14-.07Z"/><path class="cls-2" d="M592.79,712.33c-.23-.25-.77-.31-1-.08-1.67,3.36-2.31,7.13-3.97,10.47-.13,.24-.81,.37-1.05,.18-3.06-2.39-6.05-4.87-8.96-7.44-1.24-1.06-1.7-.95-2.37,.57-1.35,2.97-2.52,M 6.16-4.25,8.93-.93,0-1.36-.44-1.79-.84-3.32-3.08-6.39-6.16-9.81-9.17-2.69,2.91-3.89,6.7-6.33,9.83-1.31-.43-1.97-1.4-2.88-2.3-2.76-2.92-5.49-5.85-8.26-8.77-.29-.31-.57-.72-1.35-.56-1.91,2.5-3.89,5.14-5.88,7.62-1.03,1.28-1.61,1.29-2.64,.15-3.4-3.86-6.62-7.86-9.93-11.79-.37-.45-.71-.91-1.55-1.1-2.94,2.27-5.63,4.82-8.7,6.94-.76-.1-1.13-.38-1.42-.77-4.1-4.91-7.42-10.36-11.59-15.2-3.34,1.71-6.34,3.68-9.57,5.54-.41,.25-.82,.5-1.36,.46-4.24-6.06-8.71-12.16-12.02-18.73,3.73-1.67,7.1-4.05,10.73-5.84,.93,.38,1.17,1.02,1.53,1.M 59,3.66,5.33,6.58,11.2,10.7,16.18,.65,.03,1.09-.23,1.48-.53,2.65-2.05,5.35-4.24,8.03-6.21,.92,.12,1.19,.62,1.52,1.08,2.83,3.91,5.66,7.82,8.5,11.73,1.23,1.42,2.18,4.13,4.11,1.67,2.03-2.27,4.08-4.53,6.04-6.85,.21-.24,.88-.3,1.06-.1,3.27,3.79,6.35,7.73,9.57,11.57,.43,.53,.8,1.13,1.68,1.43,1.43-.94,1.95-2.73,3.07-4.01,1.31-1.73,1.9-3.78,3.72-5.27-.12-1.38,8.24,8.67,10.04,10.29,.45,.45,1.3,1.23,1.87,.56,1.66-3.17,3.26-6.37,4.98-9.5,.14-.26,.8-.34,1.02-.13,3.4,3.01,6.3,6.58,9.95,9.29,.75,.2,1.11-.75,1.35-1.27,1.1-2.77,2.M 16-5.54,3.24-8.31,.17-.52,.55-1.2,1.2-.99,3.31,2.22,5.96,5.29,9.15,7.71,1.58,1.06,1.77-1.06,2.11-2.07l.03,4.04Z"/><path class="cls-2" d="M646.68,678.53s0,.04-.01,.06c-.68,4.68-1.19,9.53-2.68,14.03-3.43-.59-6.52-2.64-9.9-2.96l-.02-2.62c.75-3.53,1.45-7.23,2.17-10.79,.06-.73,.83-1.22,1.64-.94,2.91,1.05,5.8,2.12,8.7,3.18,.03,.02,.07,.03,.1,.04Z"/><path class="cls-2" d="M771.18,1312.07c7.2-.82,14.39-1.64,21.59-2.46,1.93-.16,4.6-.76,2.99,1.71-14.74,25.38-30.53,50.37-46.9,74.83-.47,.08-.98,.23-1.5,.23-8.5-.11-17.03,.29-25M .5-.14-.21-1.48,1.28-2.53,1.95-3.75,7.65-10.64,15.03-21.4,22.32-32.2,8.69-12.63,16.74-25.56,25.17-38.28l-.11,.06Z"/><path class="cls-2" d="M977.4,1211.23c6.65-.94,13.42-.27,20.13-.41,.64,.03,1.76,.09,1.85,.88-.13,.85-.2,1.72-.42,2.56-4.72,18.35-9.63,36.64-15.03,54.81-2.09,7.12-4.34,14.2-6.52,21.3-.19,.63-.31,1.27-1.03,1.7,0,0,.1-.06,.1-.06-8.36,.13-16.79-.02-25.06,1.26l.15,.07c9.39-27.15,17.98-54.61,25.89-82.18l-.08,.08Z"/><path class="cls-2" d="M1299.31,304.92c29.38,3.86,58.63,8.6,87.69,14.3,.15,.39,.36,.69,.36,.9M 9,0,6.56,0,13.12-.03,19.68-.02,1.89-2.19,.93-3.35,.82-24.8-5.07-49.53-10.16-74.6-13.97-4.68-.91-9.59-1.09-14.11-2.53l.07,.09c-.22-3.21,1.32-6.56,1.75-9.78,.54-2.63,1.04-5.27,1.54-7.9,.12-.64,.29-1.26,.79-1.79l-.11,.08Z"/><path class="cls-2" d="M142.84,1134.84c-28.64-3.11-57.14-8.26-85.46-13.49-1.55-.34-3.73-.32-3.4-2.39,.04-6.35-.03-12.7,.08-19.05,.05-.83,.61-1.2,1.55-1,3.13,.64,6.26,1.28,9.37,1.95,26.83,5.74,55.12,10.7,81.75,14.61-1.41,6.48-3.03,12.93-4.05,19.48l.15-.11Z"/><path class="cls-2" d="M476,659.09s-.03,.M 05-.05,.07l.05-.07Z"/><path class="cls-2" d="M592.68,695.77c-2.24-1.97-4.29-4.15-6.67-5.96-.11-.08-.61-.02-.66,.08-1.96,3.46-2.28,7.64-4.36,11.03-.79,.39-1.51-.67-2.06-1.1-2.75-2.64-5.18-5.58-8.1-8.03-.14-.1-.48,0-.81,0-1.38,3.13-2.72,6.31-4.14,9.43-.17,.39-.22,.89-.84,1-.85,.16-1.12-.46-1.52-.85-3.16-3.15-5.71-6.86-8.96-9.93-.87-.38-1.21,.88-1.62,1.41-1.3,2.36-2.58,4.73-3.89,7.09-.37,.62-.96,1.76-1.82,1.14-3.57-3.98-6.55-8.44-10.07-12.46-1.06-.63-1.66,1.16-2.25,1.78-1.4,1.97-2.77,3.94-4.18,5.9-1.24,1.7-1.86,1.16-2M .94-.28-2.47-3.46-4.92-6.92-7.36-10.39-.91-1.15-1.31-2.54-2.75-3.19-2.26,2.17-4.33,4.39-6.55,6.6-.66,.5-1.62,1.74-2.5,1.04-3.35-4.59-6.08-9.61-9.17-14.37-.74-1.07-1.05-2.29-2.27-2.97-3.11,2.16-5.79,4.6-9,6.61-.58,.38-1.2,.21-1.6-.4-3.65-6.54-7.65-13.07-10.6-19.81,3.68-2,6.72-4.63,10.12-6.84,1.03-.33,1.43,1.46,1.92,2.11,3.09,5.79,5.74,11.88,9.31,17.4,.75,.04,1.17-.24,1.54-.56,2.47-2.1,4.8-4.33,7.12-6.6,.24-.22,.66-.32,.98-.46,4,5.21,6.53,11.44,10.46,16.75,1.11,.9,2.39-1.62,3.16-2.28,1.59-2,3.14-4.02,4.71-6.03,.22-.2M 8,.77-.29,.99-.03,2.92,3.93,5.46,8.17,8.28,12.19,.68,.7,1.34,2.6,2.54,2,2.13-2.52,3.57-5.54,5.35-8.31,.28-.43,.42-1.14,1.19-1.09,.72,.04,.95,.7,1.29,1.16,.41,.55,.8,1.12,1.21,1.67,2.17,2.85,4.35,5.7,6.52,8.55,.35,.46,.7,.93,1.36,1.16,.59-.3,.86-.78,1.11-1.28,1.7-2.95,2.69-6.53,4.84-9.13,.52-.24,1.08,.62,1.43,.91,2.77,3.19,5.2,6.62,8.22,9.58,.13,.13,.46,.12,.7,.18,2.06-3.26,2.91-7.15,4.56-10.66,.18-.4,.94-.55,1.27-.27,2.98,2.85,5.4,6.39,8.72,8.84,.66,.2,.98-.5,1.13-1.03,1.15-3.43,2.29-6.86,3.43-10.29,.9-1.11,2.36,1.M 14,3.13,1.67l.1,17.33Z"/><path class="cls-2" d="M626.45,670.15s-.05-.03-.07-.04v-.03l.07,.07Z"/><path class="cls-2" d="M1048.73,359.22c1.68-4.25,4.15-8.16,6.19-12.25,.43-.99,1.53-2.48-.38-2.43-13.97,.67-27.93,1.46-41.85,2.75-4.68,.41-9.36,.84-14.02,1.4-.66,.07-1.33,.18-2.09-.18,2.27-5.09,5.7-9.69,8.44-14.56l-.1,.06c19.53-1.86,39.06-4.02,58.68-4.63,1.25,.33,.18,1.5-.12,2.2-2.13,4.06-4.76,7.92-6.57,12.13-.05,.13,.19,.46,.35,.48,5.36,.31,10.77-.14,16.14-.18,16.84-.57,33.68,.04,50.52,.34l-.15-.1c-2.25,5.23-4.49,10.64-7M .28,15.59l.1-.05c-22.66-.5-45.33-1.05-68.02-.67l.16,.08Z"/><path class="cls-2" d="M1148.03,1317.86c.33,.5,.27,1.04,.2,1.58-.41,3.1-.79,6.21-1.23,9.31-1.89,13.7-3.97,27.37-6.23,41.02-.85,5.12-1.71,10.24-2.57,15.36-.09,1.05-1.31,1.44-2.25,1.38-7.95,0-15.89-.01-23.84-.02-.64,0-1.89-.13-1.75-.9,3.65-19.35,7.57-38.66,10.66-58.12,.62-3.62,1.27-7.25,1.84-10.88,.16-1.04,.56-2.12-.04-3.17,0,0-.14,.08-.14,.09,7.9,.73,15.73,2.63,23.59,3.82,.64,.11,1.23,.4,1.84,.61l-.08-.07Z"/><path class="cls-2" d="M317.66,126.38c-8.46-1.47-1M 7.07-2.43-25.38-4.58l.09,.07c1.97-18.53,5.13-37,8.11-55.42,.62-3.73,1.22-7.46,1.85-11.19,.17-1.63,1.31-2.11,2.85-1.98,7.67,0,15.34,.02,23.01,.05,1.14,.06,2.4,.08,2.01,1.62-4.58,23.75-9.58,47.55-12.67,71.5l.13-.09Z"/><path class="cls-2" d="M410.52,983.61s.02,.07,.03,.1c-.04-.01-.08-.01-.12-.01l.09-.09Z"/><polygon class="cls-2" points="413.73 997.85 413.73 997.92 413.65 997.85 413.73 997.85"/><path class="cls-2" d="M505.13,960.33l.06,.09c-.07,.01-.15,.01-.22,.01l.16-.1Z"/><path class="cls-2" d="M548.1,956.57h-.05s-.0M 3-.04-.05-.06l.1,.06Z"/><path class="cls-2" d="M416.2,984.08c-1.68,.49-3.38,.99-5.06,1.49-.21-.62-.38-1.24-.59-1.86,1.89,.1,3.76,.23,5.65,.37Z"/><path class="cls-2" d="M510.06,960.21c-1.46,.31-2.92,.62-4.39,.95-.16-.25-.32-.49-.48-.74,1.63-.05,3.25-.12,4.87-.21Z"/><path class="cls-2" d="M548.1,956.57l-.1-.06s.03-.01,.05-.01c.02,.02,.03,.05,.05,.07Z"/><path class="cls-2" d="M594.07,919.72c-.63-.51-1.27-.99-1.86-1.53-.69-.62-1.78-1.03-1.81-2.06,1.15-.51,2.42-.75,3.64-1.11l.03,4.7Z"/><path class="cls-2" d="M577.48,941M .19c1.69,1.99,3.54,3.86,5.29,5.82-12.2,1.79-24.64,3.84-37.3,6.16-1.69-2.14-3.4-4.27-4.97-6.47-.06-.08-.01-.21-.01-.43,11.73-2.12,23.76-3.12,35.31-6.11,.35-1.48-9.07-8.21-7.29-8.91,8.52-2.06,17.19-3.55,25.6-5.88l.06,10.58c-5.37,1.4-10.76,2.7-16.17,3.97-.7,.17-.94,.77-.52,1.27Z"/><path class="cls-2" d="M639.48,898.84c-1.32,.73-2.69,1.4-4.09,1.97l-.03-5.55c.71,.69,5.81,2.68,4.12,3.58Z"/><path class="cls-2" d="M658.64,851.7c-3.53,3.01-7.33,5.71-10.98,8.58-.57,.44-1.29,.79-1.53,1.47,.32,.5,.97,.68,1.53,.91,2.4,.98,4.82,M 1.93,7.22,2.9,1.17,.47,1.19,.86,.13,1.64-3.99,2.95-8.27,5.51-12.56,8.13-.49,.46-2.31,1.03-1.83,1.79,2.7,2,6.36,2.73,8.96,4.79-.27,.68-1.02,.99-1.66,1.37-4.11,2.44-8.28,4.78-12.59,6.97l-.07-10.83c4.82-2.64,5.01-2.24-.03-4.68l-.04-6.56c3.2-2.22,7.14-3.67,9.83-6.48-3.31-1.76-6.94-2.73-10.25-4.43,1.23-1.87,3.6-2.68,5.32-4.06,2.92-1.94,5.4-4.18,8.3-6.17,3.43,1.16,6.75,2.31,10.01,3.57,.47,.18,.6,.77,.24,1.09Z"/><path class="cls-2" d="M1303,284.44c.53-.22,.72-.63,.81-1.05,1.34-5.71,2.7-11.41,3.93-17.14,.57-1.73,3.63-.6,5.M 04-.71,21.34,2.2,42.64,4.73,63.88,7.7,3.18,.44,6.36,.92,9.53,1.39,.69,.1,1.15,.55,1.19,1.13,.13,6.35,0,12.7,.03,19.06,0,.63,.16,1.3-.48,1.88-18.24-2.25-36.39-6-54.72-8.01-5.44-.72-10.89-1.43-16.34-2.11-3.32-.42-6.66-.79-9.99-1.18-1.08-.12-2.12-.31-2.9-1l.02,.05Z"/><path class="cls-2" d="M138.02,1155.09c-1.53,5.89-2.87,11.82-4.13,17.75-.28,1.74-1.05,1.73-2.61,1.63-25.75-2.29-51.37-5.63-76.94-9.36-.67-.87-.54-1.84-.57-2.86,.02-5.59,.06-11.18,.1-16.78-.11-2.93,1.14-2.14,3.37-2,16.62,2.67,33.22,5.43,49.93,7.54,8.89,1.1M 9,17.79,2.26,26.7,3.32,1.46,.17,2.95,.26,4.28,.85,0,0-.12-.1-.12-.1Z"/><path class="cls-2" d="M167.88,1001.77c.78-5.56,1.6-11.11,2.41-16.66,.11-.67,.3-1.48,1.22-1.33,31.21,9.08,62.97,17.28,95.03,23.81l-.1-.08c-.99,5.47-2.79,10.82-4.05,16.25l.13-.07c-31.84-6.17-63.67-12.94-94.74-22.01l.1,.08Z"/><path class="cls-2" d="M161.38,1039.29c1.58-6.15,2.49-12.57,3.26-18.87l-.12,.12c30.82,7.29,61.77,14.05,93.13,19.4l-.09-.1c-1.25,5.46-3.33,10.81-4.86,16.24l.14-.08c-30.8-3.61-61.25-10.51-91.53-16.8l.07,.09Z"/><path class="cls-M 2" d="M1199.82,1327.52c-1.65,14.47-2.68,28.99-4.52,43.44-.4,3.54-.76,7.08-1.17,10.62-.16,1.39-.41,2.77-.64,4.16-.07,.42-.58,.74-1.12,.78-7.81,.18-15.62,0-23.43,.03-.84-.13-2.46,.17-2.89-.65-.06-.53-.08-1.08,0-1.61,3.09-20.61,5.63-41.29,7.99-61.99l-.12,.11c8.64,1.81,17.46,3.08,26,5.19l-.08-.08Z"/><path class="cls-2" d="M266.08,117.79c-.16-.46-.58-.7-1.13-.8-7.33-1.37-14.66-2.79-21.98-4.21-.8-.15-1.89-.5-1.78-1.45,.73-11.08,1.85-22.13,3.11-33.17,.88-7.83,1.81-15.65,2.73-23.47,0-1.36,1.33-1.51,2.48-1.48,7.41,0,14.82,.M 02,22.23,.03,3.76-.19,2.85,1.04,2.64,3.95-1.78,13.16-3.8,26.29-5.36,39.48-.5,4.18-.99,8.36-1.47,12.54-.46,2.89-.06,5.92-1.51,8.6,0,0,.04-.01,.04-.01Z"/><path class="cls-2" d="M241.47,1089.6c-27.16-2.22-54.14-7.06-81-11.59-1.58-.27-3.14-.59-4.71-.9-.43-.08-.92-.63-.87-.98,.97-6.09,2.21-12.14,3.29-18.21l-.13,.11c29.52,5.69,59.17,11.1,89.08,14.87l-.1-.1c-1.53,5.69-3.86,11.25-5.67,16.89l.11-.09Z"/><path class="cls-2" d="M747.01,609.29c-3.24-.4-6.47-1.46-9.69-2.12-.32-.08-.55-.42-.85-.67,2.81-4.45,6.53-8.13,9.48-12.5-2.M 57-1.39-5.45-1.84-8.19-2.8-.53-.16-.93-.42-1.21-.92,3.11-4.13,7.04-7.92,10.71-11.65,.34-.34,.61-.71,.5-1.3-2.73-1.39-5.94-2.27-8.89-3.75,3.93-4.84,9.3-8.67,13.78-12.96-.08-.55-.43-.83-.92-1.07-2.52-1.24-5.03-2.51-7.54-3.76-.6-.03-.97,.28-1.31,.61-4.83,4.24-9.15,9-14.2,12.93-2.93-1.13-5.64-2.73-8.63-4.01-5.01,4.46-8.44,9.77-13.25,14.43-3.04-1.2-5.88-2.58-8.69-4.16,3.69-4.98,8.01-9.27,12.01-14,.86-.98,1.26-.97,2.65-.21,2.01,1.09,4.02,2.16,6.05,3.22,.72,.38,1.28,.31,1.76-.19,4.21-4.55,8.76-8.77,13.35-12.96,.48-.45,1.1M 6-.49,1.82-.14,2.37,1.23,4.69,2.54,7.09,3.73,1.24,.6,2.07-.55,2.97-1.16,4.89-3.87,10.01-7.48,14.76-11.49-.06-.2-.03-.49-.19-.59-2.73-1.6-5.2-3.67-8.11-4.93-6.27,3.92-11.66,9.16-17.54,13.58-2.31-1.15-6.22-3.48-7.78-4.65-.28-.21-.36-.66-.16-.88,5.36-4.86,10.88-9.69,16.93-13.89,3.15,1.36,5.54,3.72,8.55,5.47,6.73-4.4,13.18-8.97,20.08-13.05,2.12,1,5.38,3.33,8.5,6.07-6.31,4.15-12.98,7.88-19.16,12.31,.24,.37,.34,.72,.62,.89,2.43,1.53,5.09,2.76,7.4,4.47,.14,.11,.22,.46,.12,.54-4.79,3.65-9.88,6.99-14.44,10.81-.48,.55-2.13,1M .28-1.16,2.05,2.66,1.25,5.35,2.45,7.95,3.81,.26,.13,.31,.67,.08,.87-4.46,4.09-9.36,7.67-13.49,12.1,3.07,1.55,6.48,2.3,9.4,3.67,.09,.73-.43,1.1-.83,1.51-3.52,3.74-7.35,7.1-10.6,11.08,13.98,5.64,12.31-.8,.26,15.65Z"/><path class="cls-2" d="M809.28,679.78s-.03,.06-.03,.09c-.03-.02-.07-.03-.1-.04,.01-.02,.01-.05,.02-.07,.04,.01,.07,.01,.11,.02Z"/><path class="cls-2" d="M849.7,657.17s-.02,.08-.03,.11c-.01,0-.03-.01-.04-.02l-.06-.03s.1-.05,.13-.06Z"/><path class="cls-2" d="M868.1,684.06c-1.6,2.61-3.21,5.22-4.81,7.82-.57,M .92-1.09,.98-2.16,.23-3.35-2.35-6.65-4.8-10.17-6.88-1.34-.47-1.44,1.47-2.02,2.25l.09-3.59c.41,.26,.64,.27,1.23,.3,1.68-2.63,2.94-5.54,4.58-8.21,.97-1.58,1.33-1.66,2.93-.65,3.32,2.16,6.49,4.53,9.74,6.8,1.05,.75,1.12,1.06,.59,1.93Z"/><path class="cls-2" d="M884.49,665.31c-2.7,2.85-5.86,4.98-8.6,7.86-3.82-2.27-7.25-4.85-10.94-7.28-.6-.41-1.16-.91-2.2-1-2.79,2.69-4.25,6.12-6.92,9.05-2.24-1.11-4.37-2.32-6.5-3.48l.3-13.05s.03-.08,.04-.13c4.29,2.23,8.58,4.67,12.77,7,1.24-.49,1.59-1.36,2.24-2.01,1.95-2.12,3.76-4.21,5.92-6.M 15-.26-.31-.41-.64-.7-.81-4.02-2.5-8.22-4.76-12.14-7.41,1.92-2.26,4.3-4,6.77-5.67,.9-.62,2.06-1.07,2.48-2.2-3.9-2.77-8.64-4.61-12.43-7.49,2.71-2.15,3.82-2.77,11.63-6.48,.6-.06,.99,.21,1.42,.48,3.29,2.06,6.59,4.1,9.88,6.15,.73,.46,1.55,.86,1.97,1.66-3.7,1.98-7.74,3.5-11.22,5.6-.02,.57,.28,.88,.72,1.16,3.36,2.16,6.72,4.32,10.06,6.5,.7,.46,1.54,.84,1.92,1.68-2.67,1.71-5.66,3.27-8.13,5.23-1.75,1.37-1.75,1.44,.09,2.7,3.86,2.71,7.84,5.19,11.57,8.09Z"/><path class="cls-2" d="M150.95,1096.03c27.85,4.91,55.97,8.17,84.08,11.M 15-1.99,5.23-4.43,11.77-6.61,17.43l.12-.07c-27.37-1.76-54.62-5.35-81.8-9.06l.12,.11c1.46-6.53,2.32-13.23,4.21-19.65,0,0-.12,.1-.12,.1Z"/><path class="cls-2" d="M1313.16,244.77c-.19-1.62,.51-3.15,.85-4.71,1.23-5.09,2.27-10.28,3.87-15.27l-.08,.07c6.25-.6,12.58,.63,18.85,.92,16.06,1.15,32.08,2.61,48.09,4.27,1.21,.16,2.92,.16,2.72,1.72,.02,3.44,.02,6.88,.01,10.32,0,2.9-.02,5.8-.03,8.71,0,.53,.02,1.07-.52,1.54-12.5-.96-24.96-2.98-37.46-4.15-12.1-1.39-24.34-1.89-36.4-3.52l.1,.09Z"/><path class="cls-2" d="M123.43,1214.96cM -21.71-.31-43.77-3.21-65.45-5.06-1.66-.26-4.7,.18-4.42-2.17,0-1.94,.05-3.88,.06-5.81,.02-4.2,.03-8.4,.06-12.6,0-.63-.08-1.3,.69-1.86,22.35,2.55,44.74,5.25,67.19,6.94,1.74,.15,3.48,.28,5.22,.46,1.26,.13,1.59,.52,1.39,1.53-1.51,6.22-2.75,12.57-4.79,18.64l.08-.07Z"/><path class="cls-2" d="M1332.76,1370.74c.15-5.16-.05-10.35,.34-15.5,.63-1.09,2.6-.26,3.63-.24,7.2,1.38,14.35,2.96,21.56,4.26,2.69,.67,2.13-1.76,2.19-3.46,.02-7.43-.27-14.87-.04-22.29,.02-.42,.69-.74,1.18-.56,3.43,1.25,6.85,2.52,10.28,3.77,4.78,1.74,9.57,3.M 47,14.35,5.2,.96,.35,1.42,.92,1.41,1.77-.01,1.94,.01,3.88,.01,5.82,0,4.2,0,8.4,0,12.6-.13,.88,.34,2.42-1,2.43-8.19-1.1-16.26-3.02-24.39-4.48-1.15-.22-1.67,.15-1.72,1.19-.07,8.08-.01,16.16-.12,24.24,.11,1.74-1.71,1.68-3.1,1.65-7.28,0-14.56-.02-21.84-.03-1-.04-2.74,.14-2.83-1.18-.15-5.06,.07-10.12,.09-15.19h0Z"/><path class="cls-2" d="M1349.41,96.78c-12.27-.05-24.53,.75-36.79,.43,0-.35-.11-.7,.02-.97,2.92-6.36,5.9-12.7,8.77-19.08,1.32-2.41-1.29-1.85-2.81-1.94-8.35,.12-16.7,.25-25.05,.36-.82-.15-3,.37-2.92-.84,4.59-7.M 32,9.1-14.75,14.04-21.85,8.48-.33,16.97-.04,25.46-.13,2.83-.12,1.62,1.18,.99,2.91-2.56,5.78-5.13,11.56-7.7,17.34-1.1,1.99-.17,2.04,1.68,2.03,9.96-.16,19.95-.04,29.9-.35l-.13-.09c-.65,6.06-2.84,11.98-4.07,17.98-.42,1.47-.38,3.1-1.48,4.27l.1-.07Z"/><path class="cls-2" d="M740.58,623.02c-.18-.55,.07-1.04,.32-1.54,2.04-4.06,4.07-8.12,6.11-12.19l-.09,.06c3.48,1.08,7.19,1.81,10.65,2.68,.35-.18,.64-.26,.78-.42,3.09-3.53,6.17-7.06,9.24-10.6,.86-1.02-.91-1.4-1.68-1.61-2.57-.78-5.31-1.43-7.8-2.38-.33-.58,.07-.91,.37-1.22,3.2M 6-3.62,7.02-7.08,10.58-10.46-.14-.62-.64-.81-1.1-.97-2.85-1.03-5.68-1.92-8.51-3.06,.27-1.23,1.4-1.79,2.26-2.62,3.35-2.8,6.71-5.6,10.07-8.39,.46-.38,1-.73,.93-1.47-2.81-1.27-5.95-2.34-8.69-3.9-.16-.09-.25-.42-.17-.56,4.74-4.32,10.57-7.58,15.69-11.46-.01-.6-.34-.89-.82-1.14-1.92-1-3.84-2-5.74-3.01-.52-.41-1.94-.73-1.67-1.53,5.7-4.53,12.57-7.78,18.74-11.59,.37,.07,.68,.07,.87,.18,2.74,1.86,5.98,3.25,8.42,5.43-.34,.65-1.13,.9-1.78,1.27-5.42,3.2-11.02,6.14-16.34,9.49-.4,.28-.34,.83,.16,1.1,2.7,1.4,5.42,2.8,8.08,4.27,.59M ,.74-1.24,1.41-1.72,1.86-4.41,2.67-8.49,5.65-12.61,8.59-.49,.35-.99,.69-1.22,1.3,3.01,1.66,6.53,2.58,9.44,4.25-.13,.79-.83,1.16-1.41,1.59-3.66,2.71-7.23,5.49-10.55,8.46-1.85,1.58-.72,1.75,.94,2.38,2.34,.82,4.7,1.61,7.05,2.42,.66,.23,.79,.84,.29,1.32-3.62,3.57-7.52,6.69-10.89,10.52,3.34,1.22,6.51,2.09,9.86,3.16,.55,.17,.78,.71,.46,1.06-3.18,3.54-6.57,6.79-9.4,10.62,3.61,1.43,7.56,1.81,11,3.19,.22,.48,.04,.86-.18,1.26-1.37,2.46-2.73,4.92-4.08,7.38-.49,1.24-2.5,3.36-.16,3.84,3.47,.83,6.9,1.81,10.33,2.76l-.1-.11c-1.71,M 3.74-3.5,7.45-5.16,11.21-.33,.69-1.43,.63-2.11,.47-3.23-.84-6.57-1.19-9.7-2.38,.99-4.07,3.01-7.81,4.77-11.64,.28-1.16-1.93-1.09-2.68-1.45-2.85-.66-5.7-1.29-8.55-1.94,1.31-4.09,3.86-7.76,5.73-11.64,.19-.36-.13-.94-.59-1.06-3.06-.78-6.13-1.56-9.2-2.32-.72-.18-1.29,.07-1.6,.66-1.57,2.96-3.11,5.93-4.66,8.9-.67,.97-.75,2.7-2.2,2.79-3.4-.4-6.76-1.34-10.14-1.95l.16,.13Z"/><path class="cls-2" d="M189.3,102.26c-.68-.5-.54-1.39-.57-2.14,.18-4.31,.37-8.61,.57-12.92,.47-7.42,.87-14.85,1.33-22.27,.27-3.65,.41-7.33,.84-10.96,.27M -1.06,1.77-.92,2.65-.97,7.68,.01,15.37,.04,23.05,.07,.75-.05,1.6,.15,1.89,.87-.77,11.35-2.08,22.78-2.79,34.17-.43,5.7-.83,11.4-1.26,17.1-.05,.63,.02,1.31-.71,1.8-8.4-1.24-16.63-3.52-25.07-4.79-.02-.01,.06,.06,.06,.06Z"/><path class="cls-2" d="M1252.55,1337.94c-.5,.55-.56,1.2-.6,1.85-.11,1.94-.22,3.87-.28,5.81-.24,7.97-.81,15.92-1.4,23.88-.28,5.27-.65,10.54-1.05,15.81-.05,.53-.24,1.21-.85,1.33-8.04,.51-16.15,.02-24.22,.16-1.04,0-2.66,0-2.57-1.36,.53-9.04,1.67-18.04,2.34-27.07,.83-8.46,.78-17.07,2.06-25.45,8.95,1.16,M 17.78,3.61,26.7,5.16,0,0-.13-.1-.13-.1Z"/><path class="cls-2" d="M1244.37,241.5c22.97,.28,45.86,2.13,68.79,3.27l-.1-.09c-1.62,6.43-3.24,12.86-4.89,19.28-.46,1.77-4,.56-5.41,.72-2.68-.2-5.36-.43-8.03-.66-17.81-1.69-35.67-2.55-53.54-3.27-1.18-.29-5.49,.37-4.85-1.49,2.72-5.91,4.91-12.22,8.14-17.84l-.11,.07Z"/><path class="cls-2" d="M196.62,1198.39c-12.23-.58-24.49-.83-36.72-1.49-5.51-.27-11.02-.66-16.52-1.01-4.43-.29-8.86-.61-13.29-.92-1.35-.07-1.27-1.1-1.05-2.01,1.39-5.59,2.78-11.19,4.18-16.78,.14-.55,.47-1.15,1.15-1M .18,9.41,.32,18.76,1.47,28.15,2.04,13.95,1.17,27.95,1.44,41.91,2.35,.8,.21,.66,1.1,.36,1.67-2.38,5.38-4.77,10.75-7.16,16.13-.23,.51-.49,1-1.15,1.28-.01,0,.12-.06,.12-.06Z"/><path class="cls-2" d="M112.37,1257.38c-.33-.16-.66-.43-1-.45-2.82-.17-5.65-.29-8.47-.43-13.58-.64-27.17-1.23-40.75-2.07-1.88-.11-3.75-.32-5.63-.42-3.38-.19-3.39-.21-3.37-2.8,.05-5.6,.09-11.2,.14-16.8,.06-1.09-.2-2.62,1.45-2.54,3.36,.12,6.71,.44,10.06,.71,17.16,1.54,34.36,2.54,51.57,3.33,1.3,.08,1.76,.47,1.58,1.39-.57,2.88-1.37,5.71-2.09,8.56-.7M 8,3.06-1.57,6.12-2.32,9.18-.21,.86-.48,1.68-1.23,2.35,0,0,.06-.02,.06-.02Z"/><path class="cls-2" d="M1194.07,366.88c.24,.66-.03,1.27-.23,1.9-1.44,5.02-3.57,9.91-4.51,15.03l.09-.09c-26.35-3.7-52.84-6.69-79.4-8.33,2.15-5.21,4.59-10.31,6.56-15.59l-.1,.05c25.96,1.79,51.91,3.86,77.73,7.14l-.15-.12Z"/><path class="cls-2" d="M331.12,1064.38c-1.6,5.36-4.4,10.4-6.45,15.63l.11-.07c-25.97-1.78-51.94-3.66-77.75-7.14l.1,.1c1.94-5.62,3.42-11.42,5.7-16.91l-.14,.08c26,4.26,52.29,6.46,78.55,8.42l-.13-.12Z"/><path class="cls-2" d="MM 1183.54,399.84c.03,.42,.18,.87,.07,1.26-1.31,4.73-2.66,9.45-4.01,14.16-.54,1.84-4.35,.12-5.77,.09-24.88-4.32-49.97-8.24-75.16-10.29l.13,.08c1.87-4.99,3.43-10.1,5.55-15,26.57,2.32,53.03,5.89,79.36,9.81l-.17-.12Z"/><path class="cls-2" d="M1322.73,204.02c-1.51,6.97-3.58,13.84-4.93,20.84l.08-.07c-7.5-1.31-15.32-.86-22.92-1.44-13.06-.52-26.12-1.09-39.19-1.2-2.45-.09-2.84-.03-1.7-2.5,2.69-5.86,5.53-11.66,8.09-17.58l-.09,.06c20.21,.86,40.65,.1,60.75,1.98l-.1-.09Z"/><path class="cls-2" d="M179.17,1237.68c-19.76-.78-39.58-.M 45-59.33-1.69-1.3-.07-1.29-1.1-.94-2.02,1.47-6.34,3.54-12.57,4.51-19.01l-.08,.06c21.14,2.05,42.62,1.92,63.88,2.69,.31,.02,.73,.45,.63,.68-2.74,6.52-6.2,12.76-8.77,19.34l.09-.06Z"/><path class="cls-2" d="M436.03,360.73c-1.33-.36-2.67-.14-3.98,0-4,.41-8.03,.37-12.05,.48-.95,.03-1.88-.02-2.73-.44-.01,0,.04,.05,.03,.04,.2-.26,.56-.5,.61-.78,.79-4.79,1.03-9.65,1.62-14.47,1.77-15.12,3.79-30.24,6.47-45.22,.1-.54,.94-.84,1.53-.83,5.52-.12,11.04-.24,16.56-.35,.78-.05,2.22,.08,2.08,.98-1.95,12.39-4.57,24.68-6.42,37.09-1.11,7M .15-1.99,14.33-2.9,21.51-.1,.74-.16,1.51-.91,2.07l.09-.07Z"/><path class="cls-2" d="M1023.11,1078.99c-.96,1.08-.73,2.68-.99,4.03-.67,6.33-1.26,12.67-1.99,18.99-1.59,12.43-3.51,24.83-5.55,37.2-.18,1.29-1.97,.93-2.96,1-4.17,.09-8.35,.18-12.52,.26-1.19-.19-4.4,.72-4.67-.77,1.58-11.01,4.23-21.89,5.66-32.94,.74-4.81,1.49-9.61,2.18-14.43,.82-4.35,.65-8.88,2.01-13.11l-.11,.08c5.28-.63,10.61-.65,15.92-.79,1.07-.03,2.14-.04,3.06,.52,0,0-.04-.05-.04-.05Z"/><path class="cls-2" d="M161.4,138.76c-.07-13.73-.08-27.52,.64-41.24,.M 02-.41,.65-.78,1.12-.68,8.71,1.79,17.47,3.37,26.13,5.41,.01,0-.07-.06-.05-.05-.47,.28-.62,.67-.65,1.11-.14,2.25-.34,4.51-.41,6.76-.42,12.57-.57,25.15-1.02,37.72-.13,.76-1.37,.54-1.94,.24-7.93-3.17-16.06-5.96-23.89-9.35l.08,.08Z"/><path class="cls-2" d="M1192.55,222.83c19.87-.69,39.77-1,59.65-.56,.27,1.77-1.07,3.31-1.61,4.97-2.03,4.77-4.39,9.42-6.22,14.27l.11-.08c-20.85-.39-41.72-.07-62.58,.02-.77-.28-.14-1.15,.11-1.64,3.54-5.68,7.09-11.36,10.64-17.03l-.09,.06Z"/><path class="cls-2" d="M1279.05,1301.04c.32,13.68,.05M ,27.54-.41,41.24-.05,.45-.62,.79-1.11,.69-8.37-1.5-16.65-3.43-24.99-5.03,0,0,.13,.1,.13,.11-.58-.67-.42-1.44-.4-2.19,.13-4.74,.31-9.48,.43-14.21,.32-9.9,.3-19.82,.8-29.71,.19-.59,1.22-.41,1.7-.19,8.05,2.97,15.97,6.21,23.94,9.37l-.08-.07Z"/><path class="cls-2" d="M670.87,824.67c3.54,.66,6.93,1.71,10.38,2.59,.54,.14,.68,.58,.3,1.03-2.89,3.52-5.86,6.99-8.88,10.41-.31,.35-.1,.91,.41,1.07,2.52,.76,5.04,1.5,7.55,2.27,1.65,.51,2.16,.82,.79,2.24-2.72,2.95-5.59,5.8-8.63,8.55-.61,.56-1.37,1.06-1.49,1.96,3.18,1.29,6.63,2.21,9M .94,3.7-4.27,4.13-8.86,7.6-13.33,11.48-.23,.19-.19,.74,.06,.86,2.69,1.47,5.78,2.24,8.4,3.83,.35,.34,.08,.85-.28,1.11-4.87,3.78-10.07,7.14-15.07,10.76-.43,.3-1,.32-1.49,.07-2.87-1.67-6.19-2.71-8.76-4.76,5.05-3.7,10.84-6.92,15.65-10.95-.1-.55-.47-.82-.97-1.03-2.71-1.13-5.5-2.24-8.15-3.46,0-.29-.11-.56,.02-.68,.61-.57,1.24-1.13,1.92-1.64,3.44-2.58,6.79-5.24,9.95-8.04,.45-.4,.92-.79,.83-1.47-3.14-1.34-6.71-2.07-9.75-3.54-.03-.73,.53-1.08,.95-1.47,3.27-3.15,6.72-6.14,9.89-9.39,.47-.6-.41-.99-.87-1.16-3.15-.94-6.3-1.87-9M .37-2.78-.7,.03-.99,.42-1.32,.75-3.44,3.38-7.11,6.79-11.03,9.74-3.63-.6-6.98-2.44-10.51-3.52-.46-.17-.61-.82-.27-1.11,3.5-3.06,7.33-5.9,10.48-9.31-.36-.62-.98-.81-1.6-1.01-3.19-1.23-6.63-1.75-9.56-3.53,3.46-3.29,6.57-6.52,9.61-10.1l-.1,.04c3.7,.66,7.36,2.05,11.03,2.99,.34,.1,.61,.35,.98,.56-2.63,3.61-5.96,6.68-8.97,9.99-.32,.34-.12,.92,.38,1.07,3.14,.97,6.28,1.93,9.42,2.89,.46,.16,1.13,0,1.5-.19,3.7-3.33,6.89-7.18,10.06-10.9l-.09,.07Z"/><path class="cls-2" d="M1281.56,161.34c-16.21,.57-32.48,1.16-48.7,1.52-1.01-.35M ,.28-1.6,.53-2.19,4.2-6.24,8.45-12.45,12.62-18.7l-.12,.05c9-.16,17.99-.57,26.98-.93,5.36-.36,10.74-.37,16.11-.42,.65,0,1.33-.06,1.91,.28,.28,.56-.05,1.05-.28,1.54-3.04,6.31-5.89,12.71-9.13,18.92l.07-.07Z"/><path class="cls-2" d="M436.04,360.73l.02,.02s-.08,.04-.12,.06c.01-.01,.07-.06,.09-.08h.01Z"/><path class="cls-2" d="M449.34,412.16l-.08,.06v-.05s.05,0,.08,0Z"/><path class="cls-2" d="M455.28,358.64c-1.87,14.32-4.11,28.6-5.31,43-4.37-2.14-8.6-4.29-12.71-6.44l-4.62,8.82c.69-10.18,1.25-20.38,2.51-30.51,.4-3.75,.82-M 7.5,1.23-11.25,.06-.52,.13-1.06-.32-1.51,5.64-1.16,11.74-.49,17.26-2.36,.61-.19,1.76-.63,1.96,.25Z"/><path class="cls-2" d="M1004.16,1079.31v-.08s.07,0,.11,0c-.01,0-.11,.09-.11,.09Z"/><path class="cls-2" d="M1008.07,1032.63c-.77,15.58-2.74,31.06-3.91,46.6-5.26,.55-10.71,.31-15.83,1.74-.85,.06-2.28,.85-2.91,.09,1.47-14.75,4.21-29.53,5.21-44.4,4.15,2.04,8.19,4.1,12.11,6.15l5.33-10.18Z"/><path class="cls-2" d="M90.76,1343.29c-1.36-.59-2.89-.33-4.34-.4-9.57-.04-19.14-.05-28.71-.09-5.56-.19-4.99,.35-4.98-4.06,.13-5.81-.M 14-11.65,.29-17.44,.45-1.14,2.21-.59,3.2-.73,6.06,.11,12.12,.25,18.19,.33,7.54,.26,15.13-.22,22.63,.41,0,0-.09-.05-.08-.04-.58,.35-.73,.89-.86,1.4-1.97,6.85-3.06,14.01-5.45,20.7l.11-.08Z"/><path class="cls-2" d="M1349.31,96.84c12.37,.12,24.75-.14,37.12,.23,1.2,.1,1.16,1.22,1.18,2.1,0,6.02-.03,12.04-.05,18.07,.03,.73-.1,1.72-.95,1.89-13.97,.01-27.97-.55-41.95-.38l.15,.12c-.27-.51-.22-1.05-.09-1.58,1.42-6.85,4.06-13.57,4.7-20.52l-.1,.07Z"/><path class="cls-2" d="M987.92,363.09c20.25-1.6,40.49-3.31,60.81-3.87l-.16-.08M c-2.41,4.77-4.65,9.63-7.23,14.32-19.56,1.02-39.21,1.52-58.74,3.44-.78,.06-1.32-.44-1.05-1,2.07-4.32,4.27-8.59,6.44-12.87l-.08,.06Z"/><path class="cls-2" d="M80.48,79.91c-.47-8.03-.07-16.12-.19-24.17-.16-3.09,.55-2.98,3.42-2.95,6.99,0,13.99,0,20.98,.02,1.67,.05,3.55-.3,3.31,2.05-.16,9.88,.07,19.79-.32,29.66-.28,1-1.97,.6-2.78,.5-8.11-1.85-16.56-2.83-24.48-5.18l.08,.07Z"/><path class="cls-2" d="M415.26,463.87s.07,.02,.1,.03v.04l-.1-.07Z"/><path class="cls-2" d="M431.49,460.39c.01,.52-.03,1.04-.05,1.57-3.98,1.08-8.19,M 1.27-12.28,1.9-1.25,.15-2.53,.42-3.8,.04-.9-14.73-.8-29.46-.79-44.21,0-1.17-.1-2.35,.31-3.58,3.96-.88,8.03-.78,12.06-1.22l-8.92,17.01c4.32,2.27,8.77,4.53,13.36,6.78-.07,7.24-.09,14.47,.11,21.71Z"/><path class="cls-2" d="M431.44,462v-.04l.09-.03-.09,.07Z"/><path class="cls-2" d="M416.89,1024.97s.07,0,.1,0c0,.03,.01,.05,.01,.08l-.11-.09Z"/><path class="cls-2" d="M418.16,1025.04c-.39-.02-.78-.05-1.17-.06-.21-1.96-.42-3.93-.62-5.9l1.79,5.96Z"/><path class="cls-2" d="M474.41,1010.83s-.05,.01-.08,.01c-.03-.05-.05-.09-.07M -.14l.15,.13Z"/><path class="cls-2" d="M476.17,1022.61c.02,.52-.12,.98-.59,1.38h-.01c-6.1-.26-12.3,.67-18.44,.72-11.21,.55-22.42,.38-33.64,.44,17.34-5.18,34.38-9.82,50.96-14.05h.01c.96,3.72,1.42,7.67,1.71,11.51Z"/><path class="cls-2" d="M964.52,416.04s.02,.07,.02,.1c-.05,.01-.11,.01-.16,.02l.14-.12Z"/><path class="cls-2" d="M1010.73,414.57c-15.15,4.42-30,8.47-44.55,12.17-.53-3.53-.75-7.13-1.64-10.6,15.34-1.5,30.78-1.44,46.19-1.57Z"/><path class="cls-2" d="M1024.38,414.84h-.09s-.01-.06-.02-.09l.11,.09Z"/><path classM ="cls-2" d="M1025.24,424.3l-2.87-9.56c.64,.03,1.28,.07,1.92,.1,.59,3.11,.58,6.32,.95,9.46Z"/><path class="cls-2" d="M1026.04,428.3l-.13,.1s-.03-.06-.04-.09c.06-.01,.11-.01,.17-.01Z"/><path class="cls-2" d="M90.65,1343.37c2.41-1.01,5.32-.26,7.9-.52,7.51-.12,15.01-.26,22.52-.38,1.88-.03,3.75-.05,5.63-.04,1.15,0,1.87,.24,1.36,1.33-3.01,6.85-6.74,13.52-9.3,20.51l.13-.07c-.55,.39-1.23,.37-1.9,.39-9.55,.16-19.1,.44-28.65,.39-.72-.09-2.16,.16-2.27-.82,.91-7.06,3.83-13.87,4.7-20.88,0,0-.12,.09-.12,.09Z"/><path class="cls-2M " d="M80.4,79.84c-.27,8.28-.07,16.56-.05,24.85-.05,2.06,0,2.7-2.28,1.9-8.51-3.24-17.18-6.07-25.61-9.51-.35-6.57-.05-13.15-.14-19.73,0-.82-.1-2.05,1.01-2.14,9.12,1.01,18.04,3.85,27.15,4.7l-.08-.07Z"/><path class="cls-2" d="M118.76,1364.27c9.72,.64,19.64-.28,29.42-.17,2.04,.03,2.46,.28,1.21,2.14-4.29,6.7-8.59,13.4-12.9,20.09-.52,.91-1.85,.84-2.82,.86-8.18-.15-16.42,.43-24.57-.15-.54-.22-.43-.99-.25-1.43,3.08-6.88,6.18-13.76,9.29-20.63,.13-.28,.47-.51,.72-.77,.01,0-.12,.07-.12,.07Z"/><path class="cls-2" d="M85.23,1365M .49c-.62,4.99-2.25,9.88-3.29,14.81-.59,2.07-.83,4.3-1.68,6.28-.56,.68-1.67,.66-2.5,.68-7.52,0-15.05,0-22.57,0-1.45-.01-2.97,0-2.84-1.87,.03-6.23,.07-12.46,.11-18.68-.14-1.92,1.65-1.58,3.01-1.66,9-.02,18-.03,27-.02,.91,0,1.89-.19,2.75,.47Z"/><path class="cls-2" d="M1354.98,74.68c1.94-5.74,2.98-11.81,4.33-17.71,1.22-4.75,0-4.2,6.17-4.22,6.33-.02,12.66,0,19,0,1.26,.12,3.32-.4,3.15,1.51,0,6.25,0,12.49-.02,18.74-.05,.64-.04,1.52-.86,1.64-10.61,.2-21.29,.31-31.91-.04,0,0,.12,.09,.12,.09Z"/><path class="cls-2" d="M463.06,M 686.97c-4-6.21-7.22-12.95-10.93-19.35-.32-.59-.7-1.17-.44-1.84,3.12-.66,7.11-.02,10.4-.21,.52-.02,1.48,0,1.57-.64-1.64-4.45-4.1-8.6-5.97-12.96-1.47-3.22-2.81-6.49-4.2-9.74-.76-1.56,1.44-1.86,2.41-2.46,3.03-1.35,5.83-3.25,8.96-4.29,.73,.23,.76,.82,.96,1.28,3.23,7.55,6.23,15.1,10.12,22.39l.05-.07c-3.37,2.1-6.8,4.13-10.51,5.85-1.16,.4-.94,1.3-.45,2.17,3.68,6.38,7,13,10.91,19.24l.15-.11c-4.29,.92-8.76,.58-13.13,.67l.08,.06Z"/><path class="cls-2" d="M729.03,620.39c3.85,.86,7.73,1.61,11.55,2.63l-.16-.13c-2.15,3.91-3.58,8M .27-5.44,12.35-.12,.28-.01,.61-.01,1.01,3.67,.93,7.5,1.43,11.22,2.17-2.06,4.08-2.68,8.77-4.59,12.9-3.76,.15-7.18-.87-10.88-1.18,.7-4.36,2.44-8.54,3.39-12.86,.14-.55-.29-1.07-.98-1.2-3.15-.36-6.27-1.61-9.43-1.31-1.65,4.45-3.02,8.91-4.24,13.4-3.34,.1-6.6-.95-9.92-1.3-.47-.07-1.11,.29-1.21,.67-1.33,4.51-2.05,9.11-3.46,13.59-3.45-1.02-7.07-1.3-10.6-1.96,1.54-4.68,2.1-9.64,3.86-14.23,3.29,.03,6.3,1.26,9.58,1.34,.32,.01,.79-.22,.96-.45,1.29-3.46,2.26-7.1,3.46-10.62,.47-.9,.47-2.66,1.84-2.58,2.9,.44,5.79,.98,8.69,1.44,.71M ,.11,1.24-.21,1.48-.83,1.68-4.31,3.36-8.63,5.03-12.94l-.15,.08Z"/><path class="cls-2" d="M474.41,1010.71v.12l-.15-.13c.05,0,.1,.01,.15,.01Z"/><path class="cls-2" d="M525.35,1005.37c.05,1.25-3.56,1.12-4.55,1.42-15.03,1.68-30.1,3.53-45.23,4.03,16.53-4.18,32.67-7.91,48.43-11.21,.43,1.91,1.24,3.79,1.35,5.76Z"/><path class="cls-2" d="M716.81,930.4c-2.58,2.18-5.32,4.29-8.09,6.27-12.67,.15-25.66,.6-38.97,1.36,4.62-2.51,9.02-5.32,13.48-7.97,.66-.01,1,.34,1.29,.68,1.7,1.93,3.37,3.88,5.07,5.82,.47,.51,1.16,.49,1.69,.06,6.64-M 4.29,12.87-9.12,19.27-13.74,.4-.28,1.16-.25,1.43,.09,1.71,2.18,3.43,4.36,5.09,6.57,.14,.18-.03,.67-.26,.86Z"/><path class="cls-2" d="M867.39,431c14.89-3.8,30.16-6.89,45.39-9.04l-.13-.09c.91,3.89,1.68,7.79,2.55,11.7-14.99,2.24-29.82,5.03-44.59,8.34l.14,.07c-1.54-3.6-2.56-7.31-3.27-11.07l-.08,.09Z"/><path class="cls-2" d="M530.87,935.77c2.56,3.01,5.12,6.02,7.68,9.02,.31,.37,.5,.74,.32,1.26-6.06,1.23-12.47,1.17-18.63,1.88-7.74,.24-15.52,1.11-23.25,.77l.09,.06c-2.48-3.43-4.97-6.85-7.45-10.28-.38-.53,.03-1.08,.8-1.12,13M .52-.13,27.06-.18,40.53-1.54l-.09-.05Z"/><path class="cls-2" d="M787.43,729.58s-.01,.07-.02,.11c-.03,0-.05-.01-.08-.01l.1-.1Z"/><path class="cls-2" d="M806.74,720.84l-.33,14.34c-2.22-.81-4.47-1.49-6.71-2.22-.88-.28-1.51,.09-1.66,.9-.67,3.93-1.26,7.87-1.96,11.8-.09,.41-.7,.73-1.19,.59-2.52-.72-5.04-1.46-7.56-2.19-.64-.18-1.29-.3-1.99,.01-1.08,3.9-1.35,8.05-2.13,12.04-.12,.64-.44,1.44-1.25,1.4-3.41-.37-6.65-2.07-10.1-1.96,.04-.05,.07-.1,.09-.15,.63-.93,.67-1.95,.82-2.97,.53-3.73,1.08-7.45,1.61-11.18,.01-.01,.01-.02,.M 01-.03,.02,0,.05,0,.07,0,15.19,2.35,9.13,5.34,12.95-11.54,2.73,.27,5.32,1.32,7.98,1.96,1.13,.37,3.07,1,3.14-.53,.59-3.75,1.17-7.47,1.92-11.19,.74-1.79,4.84,.67,6.29,.91Z"/><path class="cls-2" d="M811.67,722.52s-.05-.02-.08-.03c0-.02-.01-.03-.01-.05l.09,.08Z"/><path class="cls-2" d="M704.24,914.84c-.27,.37-.41,.69-.68,.9-6.28,4.67-12.58,9.52-19.46,13.54-.34,.05-.81,.07-1.09-.19-2.06-2.09-4.75-3.8-6.44-6.14-.05-.52,.48-.74,.88-1,6.24-4.03,12.44-8.13,18.34-12.62,.41-.3,.4-.86-.01-1.15-2.28-1.66-4.69-3.19-6.88-4.97-.13M -.11-.15-.45-.03-.58,2.68-2.45,5.8-4.48,8.59-6.81,2.57-2.05,5.02-4.2,7.57-6.26,.83-.66,1.72-.06,2.45,.39,5.21,3.1,6.52,3.99,6.27,4.35-4.78,5.15-10.75,9.34-16.24,13.85-.37,.32-.38,.84,.02,1.16,2.26,1.82,4.58,3.55,6.71,5.53Z"/><path class="cls-2" d="M729.44,905.99c1.09-.32,1.6-.98,2.18-1.57,3.76-3.8,7.51-7.6,11.26-11.4,.75-.76,1.5-1.51,2.3-2.24,.12-.11,.47-.08,.72-.07,2.09,1.68,3.87,3.88,5.83,5.75,.34,.34,.3,.8-.08,1.18-4.84,4.9-9.68,9.8-14.53,14.69-.38,.37-1.03,.92-1.59,.61-1.68-1.46-2.84-3.39-4.33-5.03-1.28-1.5-1.6M 6-1.45-2.95-.25-5.03,4.78-10.48,9.32-15.97,13.7-.43,.33-1.11,.34-1.42,.02-1.98-2.03-3.94-4.07-5.89-6.08,.08-.25,.07-.51,.22-.63,5.85-4.58,11.31-9.62,16.96-14.27,.22-.07,.61-.1,.74,0,2.32,1.69,4.56,3.57,6.55,5.59Z"/><path class="cls-2" d="M609.37,986.89c-12.29,3.74-24.59,7.35-37.11,10.31-.74,.25-1.56,.18-2.14-.37-.84-1.75-1.36-3.73-2.08-5.56,13.83-2.33,27.34-4.32,40.53-5.99,.27,.54,.54,1.07,.8,1.61Z"/><path class="cls-2" d="M609.5,986.85l-.1,.09s-.02-.03-.03-.05c.04-.01,.09-.03,.13-.04Z"/><path class="cls-2" d="M725M .85,587.43c3.15,.89,6.23,1.92,9.27,3.02,.28,.16,.32,.29,.56,.59-3.14,4.17-6.85,8.44-9.85,12.69,.34,.57,.75,.82,1.28,.96,2.68,.69,5.38,1.3,8.03,2.1,.32,.09,.56,.54,.43,.8-2.17,4.27-4.35,8.54-6.53,12.8l.15-.08c-3.59-.2-7.01-1.88-10.59-1.84,1.26-4.57,3.81-8.68,6.05-12.9,.21-.37,.55-.74,.22-1.21-2.83-1.67-6.59-1.57-9.45-3.24,3.18-4.84,7.08-9.12,10.55-13.75l-.11,.08Z"/><path class="cls-2" d="M786.61,633.33c1.25-2.95,3.12-5.68,4.81-8.48,2.2-3.64,2.64-3.13-2.17-4.53-2.41-.87-5.27-1.04-7.44-2.36,1.82-3.18,7.12-8.03,9.75-10M .6,4.07,.95,8.29,2.3,12.08,4.05l-.14-.16c-8.54,8.26-8.64,8.37-9.43,10.36,13.94,5.46,13.28,.42,5.36,14.02-.43,.92-1.47,.84-2.29,.53-3.55-.98-7.1-1.96-10.64-2.94l.1,.11Z"/><path class="cls-2" d="M628.9,798.75s-.03,.05-.04,.07l-.08-.12s.08,.04,.12,.05Z"/><path class="cls-2" d="M634.59,814.27s-.03,.06-.05,.09l-.14-.09c.06,0,.13,.01,.19,0Z"/><path class="cls-2" d="M646.56,818.2s.03-.05,.05-.07c.02,.01,.04,.01,.06,.02l-.11,.05Z"/><path class="cls-2" d="M653.2,807.2c-1.83,3.8-4.13,7.38-6.59,10.93-4.02-1.22-7.95-2.87-12.02M -3.86,5.24-8.25,6.19-10.04,6.35-11.4-2.02-.68-4.12-1.38-6.17-2.01l-.07-12.83c.13-.08,.28-.15,.47-.19,3.03,.86,6.06,1.71,9.09,2.57,.88,.31,1.8,.4,2.44,1.13-1.21,3.64-3.17,7.04-4.79,10.52-.56,1.49,2.58,1.5,3.5,1.99,2.39,.7,4.79,1.39,7.18,2.09,.46,.13,.75,.69,.61,1.06Z"/><path class="cls-2" d="M626.46,670.12s-.01,.02-.01,.03l-.07-.07s.05,.02,.08,.04Z"/><path class="cls-2" d="M630.58,655.17c-.03,.06-.07,.11-.09,.17-.03-.02-.06-.03-.09-.05l.18-.12Z"/><path class="cls-2" d="M652.76,651.68c-.95,4-1.89,7.98-2.84,11.97,0,.0M 1-.01,.03-.01,.04-.02-.01-.05-.01-.07-.01-2.49-.63-4.83-1.74-7.24-2.58-.88-.38-2.52-1.22-2.99,.02-1.05,4.09-1.88,8.19-2.79,12.31-.21,1.36-1.9,.63-2.81,.19-.01,0-.01-.01-.02-.01l-.11-16.5c1.97,.8,3.85,2.28,6.06,2.31,1.2-4.61,2.45-9.21,3.75-13.8,.07-.26,.68-.53,.95-.42,2.9,1.1,5.74,2.29,8.48,3.54,.24,1.07-.13,2-.36,2.94Z"/><path class="cls-2" d="M788.86,715.32c.06,.02,.11,.03,.17,.05,0,.02,0,.04-.02,.06l-.15-.11Z"/><path class="cls-2" d="M807.37,693.01l-.31,13.81c-1.11-.35-2.23-.67-3.35-.99-.16-.05-.54,.12-.64,.26-1.M 31,3.85-1.15,8.17-2.61,11.99-.15,.22-.69,.45-1.01,.29-3.47-.99-6.95-2-10.42-3,1.49-4.25,1-8.77,2.78-12.95,13.66,2.51,10.22,6.84,13.48-7.99,.27-1.17,.73-2,2.08-1.42Z"/><path class="cls-2" d="M979,733.46c4.12,6.46,8.61,12.71,11.97,19.54,.1,.24-.1,.46-.39,.45-4.41,.06-8.76-.65-13.17-.62l.09,.06c-3.68-6.6-8.2-12.74-12-19.24,1.54-.72,3.15-.53,4.79-.59,2.94,.09,5.88,.13,8.8,.46l-.09-.07Z"/><path class="cls-2" d="M461.39,706.29c3.86,5.43,7.72,10.86,11.58,16.29,.39,.76,1.46,1.48,.92,2.35-4.69,.22-9.4-.38-14.09-.51l.04,.02cM -3.66-5.25-7.33-10.49-10.97-15.75-.31-.73-2.81-3.38-1.36-3.6,4.66,.24,9.28,1.08,13.97,1.25l-.09-.06Z"/><path class="cls-2" d="M461.47,706.35c-4.16-6.45-8.72-12.73-11.99-19.56,.05-.44,.75-.6,1.17-.56,4.15,.12,8.25,.74,12.41,.74l-.09-.06c3.5,6.29,7.62,12.37,11.6,18.45,1.91,2.43-11.82,.76-13.19,.94l.09,.06Z"/><path class="cls-2" d="M702.58,555.4c-4.47,4.82-8.53,9.93-12.65,14.92-.12,.11-.55,.13-.72,.05-2.45-1.31-4.8-3.13-7.02-4.59,0-.37-.1-.63,.01-.79,3.94-5.05,7.71-10.47,12.38-15.01,.43-.21,1.04-.03,1.4,.26,2.16,1.76,M 4.79,3.06,6.59,5.16Z"/><path class="cls-2" d="M692.13,862.03c2.13,1.15,4.56,1.84,6.79,2.84,.8,.36,1.82,.48,2.33,1.21-.03,.19,.02,.44-.11,.56-4.06,4.03-8.23,7.98-12.77,11.67-1.06,.86-1.38,.89-2.81,.25-2.24-.99-4.46-2-6.69-3.01-.46-.21-.88-.45-1.05-1,4.9-4.11,9.8-8.3,14.41-12.57,0,0-.1,.05-.1,.05Z"/><path class="cls-2" d="M788.86,715.32c.45,1.39,.03,2.77-.16,4.14-.38,3.41-1.2,6.79-1.37,10.22l.1-.1c-3.72-1.07-7.6-2.11-11.48-2.49,3.73-15.49-2.76-15.13,13.06-11.66l-.15-.11Z"/><path class="cls-2" d="M1228.38,910.98c-.05,M .07-.09,.19-.14,.19-.31,0-.28-.04,.09-.09,0-.01,.05-.1,.05-.1Z"/><path class="cls-2" d="M1279.81,881.08v-.2s.02,.17,0,.2Z"/><path class="cls-2" d="M433.09,751.59c-.28-.18-.27-.23,.03-.15-.04,.06-.09,.13-.13,.19l.1-.05Z"/><path class="cls-2" d="M1240.27,858.9s.12-.06,.12-.06c0,0-.12,.06-.12,.06Z"/><path class="cls-2" d="M393.07,779.89l.28-.25s-.13,.14-.24,.25h-.03Z"/><path class="cls-2" d="M481.61,853.12l.15,.02c-.08-.1-.05-.11-.15-.02Z"/><path class="cls-2" d="M248.66,642.99l.11,.06c0-.15,.02-.14-.11-.06Z"/><path cM lass="cls-2" d="M375.64,837.58l.27,.03c-.13,.19-.19,.16-.18-.09l-.08,.07Z"/><path class="cls-2" d="M1037.31,730.23l-.31-.14c.26-.16,.33-.1,.22,.19l.09-.06Z"/><path class="cls-2" d="M1086.38,834.09l-.3,.07c.09-.03,.19-.07,.29-.11,0,0,0,.04,0,.04Z"/><path class="cls-2" d="M1028.34,666.28c.29-.06,.4,.01,.33,.2-.21,.03-.27-.04-.25-.26l-.08,.06Z"/><path class="cls-2" d="M215.67,631.85l-.23,.11c.12,0,.17,.02,.23-.11Z"/><path class="cls-2" d="M835.41,996.91l-.03-.19c-.19,.08-.15,.11,.14,.11,0,0-.11,.08-.11,.08Z"/><path clM ass="cls-2" d="M1024.12,629.75l-.19,.07c.1-.08,.1-.19,.19-.07Z"/><path class="cls-2" d="M213.94,629.46s.07-.07,.08-.06-.08,.06-.08,.06Z"/><path class="cls-2" d="M998.52,718.5l-.17,.09c.11,.02,.11,0,.17-.09Z"/><path class="cls-2" d="M800.44,1026.36l-.16-.05s.14,.05,.16,.05Z"/><path class="cls-2" d="M1070.09,761.82c.09-.16,.18-.45,.28-.45,.35-.01,.34,.09-.02,.19-.09,.03-.15,.12-.24,.21l-.02,.05Z"/><path class="cls-2" d="M810.4,1039.05l-.17-.18c.07,.05,.14,.11,.21,.16,0,0-.05,.02-.05,.02Z"/><path class="cls-2" d="M146M .85,783.14l-.17,.11c.11,0,.12-.01,.17-.11Z"/><path class="cls-2" d="M1257,1041.9c.08-.04,.16-.08,.24-.13-.1,.04-.2,.08-.31,.12-.02,0,.08,0,.08,0Z"/><path class="cls-2" d="M686.57,1042.33c.13,0,.34-.03,.37,.02,.19,.24,.09,.25-.26-.02-.03,0-.12,0-.12,0Z"/><path class="cls-2" d="M708.45,1043.49l-.06-.12c.08,.05,.24,.03,.06,.12Z"/><path class="cls-2" d="M685.5,1044.44l.05-.26c.3,.13,.25,.19-.14,.19l.09,.07Z"/><path class="cls-2" d="M706.98,1045.42l-.11-.14c.13,.07,.22,.03,.11,.14Z"/><path class="cls-2" d="M1211.59,762.M 83l-.21,.18c.04-.06,.09-.11,.14-.18,.01,0,.07,0,.07,0Z"/><path class="cls-2" d="M1072.6,698.98l-.42,.2c.1-.04,.47-.27,.42-.2Z"/><path class="cls-2" d="M412.1,696.62l-.23-.12c.26-.09,.3-.03,.14,.18l.1-.05Z"/><path class="cls-2" d="M1092.71,695.04l-.14,.07c.06-.08,.04-.19,.14-.07Z"/><path class="cls-2" d="M775.96,1083.78l.27-.12c0,.2-.11,.22-.33,.04,0,0,.06,.08,.06,.08Z"/><path class="cls-2" d="M257.78,597.94l.51-.18c-.14,.03-.43,.2-.51,.18Z"/><path class="cls-2" d="M718.23,1098.91l-.37-.32c.24-.03,.18,.12,.24,.29,.0M 2,0,.13,.04,.13,.04Z"/><path class="cls-2" d="M1100.78,662.2c-.08,.07-.21,.21-.24,.2-.19-.08-.09-.16,.3-.22,.03,0-.06,.02-.06,.02Z"/><path class="cls-2" d="M624.22,1111.98c-.12-.1-.23-.2-.35-.3,.25,.02,.32,.12,.36,.35,0,.02-.01-.06-.01-.06Z"/><path class="cls-2" d="M646.13,1117.89v-.18c.1,.11,.19,.12,0,.18Z"/><path class="cls-2" d="M310.21,573.78l-.1-.06c0,.15-.03,.14,.1,.06Z"/><path class="cls-2" d="M780.14,1133.02v-.27c.35,.06,.31,.13-.09,.22l.09,.06Z"/><path class="cls-2" d="M589.12,1154.23l.04,.21c-.26,0-.25-.0M 5,.05-.15l-.1-.06Z"/><path class="cls-2" d="M605.07,1165.57v.14c-.15-.07-.15-.06,0-.14Z"/><path class="cls-2" d="M378.95,529.15l-.21,.04,.11-.13c0,.06,.01,.11,.02,.16l.08-.08Z"/><path class="cls-2" d="M1007.33,688.24l.31,.13c-.25,.17-.32,.11-.22-.18l-.09,.06Z"/><path class="cls-2" d="M523.46,1191.36l.23,.39c-.08-.13-.16-.26-.24-.42,0-.02,.01,.03,.01,.03Z"/><path class="cls-2" d="M597.34,492.98v.05l-.08-.07s.06,.01,.08,.02Z"/><path class="cls-2" d="M171.32,461.66l-.27,.08c.21,.14,.25,.09,.11-.13,0,0,.16,.05,.16,.05ZM "/><path class="cls-2" d="M412.14,773.5l-.16-.02c.08,.12,.06,.11,.16,.02Z"/><path class="cls-2" d="M555.57,1219.39l-.19-.22c.07,.07,.15,.14,.23,.21,0,0-.04,0-.04,0Z"/><path class="cls-2" d="M628.12,1219.02c.06,.7-1.41,.28-.17-.14l.17,.14Z"/><path class="cls-2" d="M638.3,415.07l-.04,.19c.24-.05,.2-.09-.1-.12,0,0,.14-.07,.14-.07Z"/><path class="cls-2" d="M560.31,1238.68l.46,.32c-.12-.09-.24-.18-.39-.27-.03,0-.07-.04-.07-.04Z"/><path class="cls-2" d="M476.02,1239.66l-.19,.13c-.01-.2,.07-.21,.25-.05,0,0-.06-.08-.06-.08M Z"/><path class="cls-2" d="M796.77,320.09v.21c.21-.02,.19-.07-.09-.13,0,0,.09-.08,.09-.08Z"/><path class="cls-2" d="M660.72,307.27l-.19-.21c.07,.07,.15,.14,.23,.2,0,0-.04,0-.04,0Z"/><path class="cls-2" d="M767.07,301.73l-.08-.06,.08,.06Z"/><path class="cls-2" d="M703.81,286.66c.07,.03,.21,.08,.21,.09-.09,.23-.11,.21-.08-.05-.01,0-.13-.04-.13-.04Z"/><path class="cls-2" d="M479.99,1310.06l.2-.09-.1,.15c-.05-.05-.1-.09-.15-.14,0,0,.05,.09,.05,.09Z"/><path class="cls-2" d="M755.9,264.86l-.26,.15c-.04-.2,.07-.23,.32-.07M ,0,0-.07-.08-.07-.08Z"/><path class="cls-2" d="M577.14,262.92c.65,.28,.66-.3,.79-.71l-.05-.02c-.4,.12-.77,.2-.74,.68v.04Z"/><path class="cls-2" d="M914.3,249.26c-.17-.36,.47-.5,.58-.18,0,.24-.19,.32-.48,.26l-.1-.08Z"/><path class="cls-2" d="M814.39,243.8l-.02-.22c-.23,.06-.2,.11,.1,.14,0,0-.09,.09-.09,.09Z"/><path class="cls-2" d="M753.96,241.18l-.35-.14c.09,.05,.29,.04,.35,.14Z"/><path class="cls-2" d="M816,219.41l-.32-.47c.16,.22,.25,.35,.35,.47,0,0-.03,0-.03,0Z"/><path class="cls-2" d="M1098.81,212.47v-.19c.22,.M 14,.19,.18-.09,.11l.09,.07Z"/><path class="cls-2" d="M765.37,204.6l.16,.16c-.25,.12-.27,.08-.05-.11,0,0-.11-.05-.11-.05Z"/><path class="cls-2" d="M819.94,189.58l.51,.23c-.19,.04-.25-.1-.42-.2-.03,0-.09-.03-.09-.03Z"/><path class="cls-2" d="M1036.44,164.59l-.08,.21c-.19-.18-.14-.23,.16-.13l-.08-.08Z"/><path class="cls-2" d="M370.46,678.14l-.14,.14c.04-.16-.04-.23,.14-.14Z"/><path class="cls-2" d="M615.24,767.03s-.07,.09-.11,.14c-.03,0-.07-.03-.1-.04,.01-.05,.02-.1,.03-.15,.06,.02,.12,.03,.18,.05Z"/><path class="cls-M 2" d="M619.2,755.46s-.01,.03-.01,.04c-.03-.01-.07-.03-.1-.04,0-.01,.01-.03,.01-.04,.03,.01,.07,.02,.1,.04Z"/><path class="cls-2" d="M627.26,771.52l-.11,.12s.04-.09,.06-.13c.02,.01,.03,.01,.05,.01Z"/><path class="cls-2" d="M643.33,763.24s.01-.06,.02-.09c.04,0,.09,.01,.13,.01l-.15,.08Z"/><path class="cls-2" d="M649.16,737.27s-.06,.09-.09,.14c-.02,0-.05-.01-.07-.02l.16-.12Z"/><path class="cls-2" d="M657.9,753.56s.01-.06,.02-.09c.03,0,.07,0,.1,.02l-.12,.07Z"/><path class="cls-2" d="M662.04,726.32s.02,.07,.02,.11c-.04-.M 01-.09-.03-.13-.04l.11-.07Z"/><path class="cls-2" d="M671.64,742.59s.01-.07,.02-.11c.04,.01,.07,.02,.11,.03l-.13,.08Z"/><path class="cls-2" d="M699.27,703.72c-1.11,4.12-.98,8.51-1.64,12.73-.08,.65-.55,1.02-1.28,.96-3.28-.15-6.3-.93-9.65-.73-1.27,4.37-.87,9.15-2.01,13.61-2.9-.44-5.8-.87-8.71-1.29-.87-.11-2.44-.33-2.56,.8-.59,4.22-1.18,8.45-1.76,12.68-2.81-.94-5.87-1.12-8.76-1.82-.74-.13-1.57-.27-2.28,.06-.13,.18-.33,.35-.36,.54-.79,4.07-1.57,8.14-2.34,12.21-3.43-.84-6.85-1.66-10.29-2.49-.55-.15-1.49,.02-1.64,.56-.88M ,3.87-1.76,7.74-2.64,11.61-3.03-.32-5.87-1.64-8.82-2.39l-.09-13.67s0-.06,.02-.09c3.27,1.49,6.96,2.11,10.41,3.2,.65,.18,1.35-.18,1.5-.72,1.07-3.98,1.09-8.28,2.7-12.07,3.29,1.2,6.81,1.79,10.3,2.47,.48,.09,.93-.24,1.02-.76,.72-4.22,1.48-8.45,1.67-12.69,3,.86,6.17,1.18,9.25,1.8,1.72,.35,2.14,.06,2.41-1.34,.42-4.02,1.43-8.1,1.16-12.13-.01-.02-.01-.04-.02-.06,3.17,.45,6.33,.93,9.51,1.34,1.59,.21,1.98-.04,2.16-1.22,.2-1.39,.34-2.78,.5-4.17,.26-2.35,.52-4.7,.8-7.05,.1-.85,.59-1.19,1.51-1.14,3.32,.35,6.62,.85,9.93,1.26Z"/><M path class="cls-2" d="M666.93,768.98c-4.1-.79-8.16-2.04-12.28-2.55l.09,.06c1.79-4.05,2.08-8.72,3.29-13l-.12,.07c15.95,2.19,10.53,5.53,13.87-11.06l-.13,.08c3.85-.11,7.55,1.25,11.4,1.17-.02,4.6-1.47,9.06-1.57,13.65-3.61,.05-7.12-.99-10.71-1.33-.46-.06-1.13,.32-1.23,.65-.97,4.1-1.81,8.24-2.74,12.35l.14-.09Z"/><path class="cls-2" d="M622.42,783.21s-.03,.06-.05,.09c-.02,0-.05-.01-.07-.02,.01-.03,.03-.06,.04-.09,.03,0,.05,.01,.08,.02Z"/><path class="cls-2" d="M627.26,771.52s0,.1-.01,.16c-.03-.01-.07-.03-.1-.04l.11-.12Z"/M ><path class="cls-2" d="M639.33,776.02c-1.31,3.36-2.65,6.72-3.98,10.08-.17,.35-.27,.73-.66,.92l-.08-12.78c1.53,.47,3.09,.9,4.67,1.28,.05,.18,.11,.36,.05,.5Z"/><path class="cls-2" d="M639.39,775.55s-.07-.02-.11-.03c0-.04,0-.09-.02-.13l.13,.16Z"/><path class="cls-2" d="M654.65,766.43c.28,.64,.12,1.28-.05,1.9-1.05,3.3-1.58,6.83-3,9.98-.11,.21-.73,.42-1.04,.34-3.82-.96-7.7-1.8-11.3-3.26l.13,.15c1.75-4.05,2.56-8.3,4.09-12.38l-.14,.08c3.68,1.45,7.74,1.76,11.4,3.25l-.09-.06Z"/><path class="cls-2" d="M675.9,783.82c-4.19-.0M 8-8.15-1.72-12.33-1.83,.65-4.39,2.07-8.75,3.35-13.01,3.37,.36,8.24,1.71,12.21,1.93-.48,.4-.71,.88-.84,1.42-.79,3.13-1.61,6.26-2.39,9.39-.18,.72-.45,1.45-.21,2.21l.21-.11Z"/><path class="cls-2" d="M1000.81,897c4.77-1.63,9.81-2.57,14.69-3.93,1.73,12.7,4.63,25.33,5.65,38.14,.02,.54-.47,1-1.18,1.13-4.2,.71-8.38,1.69-12.6,2.24-1.29,.02-1.19-1.45-1.43-2.34-.38-3.32-.68-6.65-1.07-9.97-.84-7.3-2.08-14.55-3.18-21.81-.18-1.17-.21-2.37-.88-3.46Z"/><path class="cls-2" d="M955.3,429.46c-13.18,3.23-26.11,6.17-38.79,8.84-.44-1.63M -.79-3.25-1.43-4.81,.04,0,.07,0,.11-.01,13.36-1.37,26.68-3.26,40.11-4.02Z"/><path class="cls-2" d="M727.47,663.7c2.82,.71,5.76,.87,8.65,1.25,1.99,.26,2.45,.28,2.87-1.68,.7-3.26,1.52-6.5,2.31-9.75,.19-.57,.38-1.46,1.12-1.53,3.73-.06,7.3,1.29,11.02,1.27-1.46,4.49-2.87,9.02-3.34,13.67l.11-.08c-3.55-.45-7.09-1.07-10.66-1.3-.44-.03-1.08,.37-1.16,.74-.27,1.26-.58,2.52-.8,3.78-.45,2.53-.85,5.07-1.26,7.61-.09,.53-.12,1.06,.2,1.56-3.55-.53-7.12-.98-10.68-1.42-1.03-.13-.92-1.14-.82-1.88,.83-4.12,1.18-8.33,2.54-12.33l-.11,.1ZM "/><path class="cls-2" d="M757.47,640.44c-3.8-.58-7.59-1.7-11.4-1.95,1.8-4.2,2.96-8.73,5.18-12.72,.11-.15,.45-.28,.67-.26,3.83,.15,7.46,1.72,11.27,1.92-2.5,4.02-3.57,8.8-5.72,13.02Z"/><path class="cls-2" d="M776.91,657.8c-1.04,4.34-2.68,8.6-3.34,13.01l.12-.08c-4.08-.67-8.13-1.62-12.26-1.94l.1,.13q2.58-10.93,3.8-13.08c3.89,.29,7.74,1.29,11.58,1.95Z"/><path class="cls-2" d="M753.33,653.34c1.26-4.35,3.27-8.57,4.05-13,3.52,.71,7.04,1.41,10.56,2.13,1.54,.34,.59,1.87,.31,2.82-.95,2.91-1.89,5.83-2.85,8.74-.18,.53-.45,1.11M -1.09,1.22-3.68-.21-7.4-1.12-10.98-1.91Z"/><path class="cls-2" d="M750.12,666.94c3.76,.76,7.83,.69,11.41,1.99l-.1-.13c-.74,4.33-1.83,8.61-2.31,12.97-3.83-.04-7.6-.94-11.43-1.25,.36-4.06,1.34-8.08,1.97-12.12,.09-.52,.37-1.03,.57-1.54l-.11,.08Z"/><path class="cls-2" d="M793.88,688.83c-.22,3.66-1.26,7.23-1.88,10.85-.27,.93-.35,2.37-1.75,2.09-3.11-.68-6.19-1.5-9.35-1.98-1.24-.03-1.27,1.46-1.46,2.35-.37,2.78-.71,5.57-1.09,8.35-.23,.77-.13,2.03-1.13,2.22-3.68-.32-7.35-1.34-11.02-1.92l.16,.11c1.6-4.16,.83-9.35,2.37-13.67,M 3.36,.65,6.73,1.3,10.09,1.95,.84,.12,1.26-.6,1.3-1.29,.93-3.86,1.01-7.94,2.46-11.64l-.1,.1c3.8,.81,7.56,1.84,11.39,2.48Z"/><path class="cls-2" d="M773.58,670.81c3.81,.84,7.61,1.68,11.42,2.52-.75,4.35-2.16,8.63-2.5,13.02l.1-.1c-4.1-.84-8.19-1.69-12.29-2.53,1.66-4.21,1.52-8.83,3.39-12.99l-.12,.08Z"/><path class="cls-2" d="M809.28,679.78s-.03,.06-.03,.09c-5.76,14.7,1.4,13.7-15.38,9.06-.04-.02-.08-.03-.12-.04,1.78-3.72,1.67-8.06,3.23-11.86,.1-.24,.67-.49,.97-.41,3.84,.85,7.47,2.38,11.33,3.16Z"/><path class="cls-2" d="MM 646.55,678.57c1.6-4.82,2.36-9.99,3.28-14.97,3.38,1.43,6.94,2.47,10.61,3.3l-.08-.06c-1.72,4.84-1.64,10.08-3.29,14.96l.12-.12c-3.56-.98-7.01-2.46-10.64-3.12Z"/><path class="cls-2" d="M653.2,710.13c-3.92-.84-7.71-1.98-11.5-3.13,1.57-4.3,1.35-9.09,2.73-13.44,.79-.29,1.41-.11,2.03,.07,2.76,.79,5.51,1.6,8.26,2.39l-.07-.08c.14,4.77-1.22,9.54-1.62,14.31l.16-.12Z"/><path class="cls-2" d="M654.73,696.02c1.29-4.63,1.84-9.55,2.46-14.32l-.12,.11c3.59,.6,7.16,1.47,10.62,2.59l-.08-.09c0,4.81-1.48,9.5-1.51,14.29-3.81-.89-7.63-1.78M -11.44-2.67l.07,.08Z"/><path class="cls-2" d="M649.17,737.27c-4.22-.41-8.19-2.19-12.33-3.11,1.66-3.72,1.59-8.02,2.59-11.96,.11-.57,.48-1.11,1.21-.99,14.82,3.75,8.7,4.93,12.57-11.08l-.16,.12c2.97,.66,5.95,1.32,8.92,1.98,1.09,.11,2.14,.85,1.8,2.04-.65,4.02-.57,8.24-1.83,12.12l.12-.07c-2.89-.15-5.65-1.11-8.47-1.66-.84-.15-2.34-.65-2.72,.41-.54,4.1-1.7,8.2-1.85,12.31l.16-.11Z"/><path class="cls-2" d="M725.01,838.22c2.57-3.99,4.24-8.51,6.4-12.73,.2-.56,.57-1.38-.1-1.75-3.05-1.1-6.37-1.49-9.52-2.31,1.54-4.63,3.83-9.17,4.M 96-13.85-.51-.6-1.35-.7-2.1-.85-1.82-.36-3.66-.64-5.48-1-.91-.25-2.65-.39-2.16-1.74,1.37-4.36,2.75-8.72,4.13-13.08l-.15,.12c3.48,.92,7.08,1.31,10.62,1.96l-.1-.1c-.72,4.15-2.48,8.1-3.63,12.16-.21,.78-.82,1.95,.35,2.27,2.94,.73,5.9,1.39,8.94,1.77,.88,0,1.1-1.12,1.4-1.74,1.11-4.17,3-8.25,3.57-12.51l-.18,.11c3.57,.51,7.1,1.66,10.69,1.82-1.31,4.8-2.95,9.56-4.09,14.39,0,.25,.31,.66,.59,.75,2.86,.75,5.79,2.2,8.79,2.19,2.29-4.67,3.36-9.86,5.14-14.75,3.18,1.31,6.54,2.16,9.8,3.26-1.92,4.95-3.19,10.01-5.37,14.87-14.08-3.65-6.M 86-5.63-15.29,11.21-.17,.37-.89,.63-1.33,.49-2.5-.77-5-1.55-7.51-2.27-.68-.22-1.31,0-1.95,.05,2.98-4.11,4.11-9.29,6.24-13.87,.15-.38,.35-.83-.27-1.42-2.01-.87-4.58-1.1-6.97-1.75-.8-.11-1.94-.51-2.63,.06-2.12,4.18-3.46,8.79-5.28,13.13-.06,.17,.08,.39,.13,.58,2.56,1.2,5.55,1.56,8.23,2.5,.28,.08,.4,.49,.6,.75,.26,.29,.19,.6,.05,.9-2.08,4.62-4.32,9.17-6.71,13.64-3.07-1.53-6.56-2.14-9.81-3.28Z"/><path class="cls-2" d="M758.98,767.7c-.1,4.56-1.79,9.1-2.5,13.64-.09,.4-.7,.77-1.18,.7-2.63-.43-5.24-.89-7.86-1.36-1.17-.18-1.M 76,.16-1.99,1.09-1.29,4.36-1.67,9.04-3.51,13.19l.18-.11c-3.54-.65-7.09-1.3-10.63-1.95l.1,.1c1.32-4.7,2.99-9.48,3.11-14.31,3.28,.36,6.54,.92,9.81,1.37,.78,.11,1.34-.2,1.46-.77,.97-4.49,1.93-8.99,2.5-13.55,3.49,.87,7.16,1.07,10.61,2.04l-.11-.09Z"/><path class="cls-2" d="M761.43,753.6c3.55-.02,7.2,.98,10.63,1.82-.11,4.27-1.28,8.44-1.91,12.65-.16,.98-.67,1.82-1.89,1.53-3.09-.62-6.15-1.43-9.27-1.9l.11,.09c1.29-4.67,1.63-9.53,2.46-14.29l-.12,.11Z"/><path class="cls-2" d="M1041.28,373.35c22.91,.41,45.94,.34,68.85,1.97-1.8M 7,4.66-3.75,9.33-5.6,14-.12,.29-.04,.63-.06,.95-22.75-1.75-45.54-2.5-68.35-2.76-.8-.3-.22-1.4-.06-1.99,1.73-4.05,3.81-7.98,5.22-12.16Z"/><path class="cls-2" d="M699.95,816.9c1.84-4.57,4.07-9.01,5.67-13.66,2.61,.47,5.22,.94,7.82,1.42,.83,.28,2.83,.25,2.69,1.43-1.16,3.64-2.68,7.16-4.01,10.75-.4,.7-.66,1.96-1.65,2-3.56-.34-6.94-1.53-10.52-1.93Z"/><path class="cls-2" d="M721.13,790.92c-3.86,.11-7.58-1.13-11.44-1.24l.09,.1c.58-4.33,2.03-8.58,2.93-12.87,.16-.6,.7-.93,1.41-.87,3.44,.29,6.88,.62,10.22,1.39-1.61,4.4-2.11,9.M 1-3.36,13.61l.15-.12Z"/><path class="cls-2" d="M705.72,803.34c-3.81-.65-7.62-1.3-11.42-1.95,1.32-4.57,3.22-9.02,4.14-13.67l-.12,.09c3.78,.85,7.72,1.01,11.45,1.98l-.09-.1c-1.32,4.55-2.63,9.11-3.97,13.66Z"/><path class="cls-2" d="M670.82,796.85c2.37-4.04,2.56-9.13,5.08-13.03l-.21,.11c3.04,.91,6.27,1.2,9.39,1.86,.56,.07,1.46,.2,1.83-.29,1.69-4.04,2.4-8.39,3.34-12.61,3.85,.23,7.57,1.12,11.43,1.26-1.06,4.57-1.99,9.16-3.36,13.66l.12-.09c-3.51-.08-6.86-1.01-10.34-1.35-.69-.08-1.28,.26-1.48,.84-.91,2.7-1.77,5.41-2.7,8.11-1M .43,4.14-.68,4.06-6.05,2.94-2.34-.49-4.7-.94-7.04-1.41Z"/><path class="cls-2" d="M702.5,630c-1.34,4.25-2.68,8.5-4.02,12.76-.15,.77-.49,1.71-1.49,1.61-2.75-.46-5.48-.97-8.22-1.48-.65-.11-1.3,.26-1.45,.84-1.19,4.5-2.22,9.04-3.55,13.51l.13-.08c-2.6-.56-5.2-1.11-7.79-1.67-.77-.16-1.54-.4-2.41-.11-1.86,4.25-1.77,9.15-3.22,13.55-.08,.24-.66,.5-.98,.42-3.02-.83-6.3-1.2-9.13-2.51l.08,.06c.01-.63-.08-1.27,.05-1.88,1.07-4.33,1.54-8.87,3.1-13.05,2.52,1.29,5.53,1.68,8.27,2.49,1.12,.28,1.71-.03,1.98-1.03,.95-3.8,1.89-7.59,2.92-M 11.37,.17-.62,.3-1.28,1.17-1.73,12.24,2.2,8.48,4.81,12.45-7.3,.45-1.46,.98-2.9,1.5-4.35,.17-.47,.69-.69,1.26-.56,3.12,.61,6.17,1.65,9.35,1.87Z"/><path class="cls-2" d="M672.46,621.58c3.15,1.33,6.35,2.54,9.81,3.25-1.55,4.66-3.06,9.32-4.61,13.98-.29,.84-.84,1.09-1.76,.82-2.77-.81-5.51-1.69-8.29-2.44,.97-5.34,3.93-10.31,4.85-15.62Z"/><path class="cls-2" d="M667.74,637.13c-1.91,4.09-2.59,8.71-3.94,13.03-.16,.61-.1,1.26-.14,1.9-3.28-.64-6.24-1.89-9.26-3.04-.49-.18-.71-.59-.58-1.08,.6-2.3,1.2-4.61,1.84-6.91,.52-1.88,1.08M -3.76,1.64-5.63,.24-.74,.67-1.75,1.66-1.41,2.93,1.05,5.86,2.1,8.79,3.15Z"/><path class="cls-2" d="M682.15,624.89c2.47-4.82,3.63-10.25,6.53-14.93,2.72,.91,5.44,1.81,8.16,2.72,.9,.28,1,.9,.72,1.59-1.71,4.18-3.41,8.36-5.13,12.53-.22,.53-.93,.83-1.61,.64-2.9-.84-5.78-1.69-8.68-2.54Z"/><path class="cls-2" d="M718.68,618.4c-2.46,4.14-3.29,9.1-5.58,13.32-.31,.35-.97,.4-1.44,.31-3.12-.57-6.27-1.08-9.29-1.96,2.17-4.64,3.75-9.55,5.69-14.29,3.53,.9,7.16,1.47,10.62,2.62Z"/><path class="cls-2" d="M774.48,741.3c-3-1.14-6.44-1.27M -9.61-2-.97-.17-1.55,.2-1.65,.95-.64,4.44-1.2,8.9-1.79,13.35l.12-.11c-3.42-1.05-7.05-1.22-10.57-1.86-.04-.53-.16-1.06-.11-1.59,.61-4.24,.57-8.62,1.8-12.74l-.1,.1c2.64,.38,5.27,.77,7.91,1.14,.86,.01,2.42,.58,2.83-.46,.75-4.02,1.1-8.09,1.61-12.13,.06-.75,1.07-.95,1.81-.8,3.12,.61,6.24,1.22,9.37,1.83-.42,4.78-1.56,9.55-1.62,14.33Z"/><path class="cls-2" d="M754.18,723.08c-.19,.62-.49,1.23-.56,1.86-.35,4.15-1.07,8.3-1.05,12.47l.1-.1c-3.85-.25-7.59-1.07-11.46-1.19,.54-4.78,.63-9.62,1.65-14.33,3.74,.74,7.56,1.12,11.39,1.3M 7l-.07-.09Z"/><path class="cls-2" d="M766.2,710.79c.54,1.64,.02,3.38-.07,5.06-.34,2.64-.52,5.32-1.05,7.93-.31,.9-1.54,.79-2.32,.67-2.86-.47-5.82-.53-8.59-1.38l.07,.09c-.35-4.13,.73-8.37,.95-12.53,.03-.42,.4-.91,.83-.97,3.48-.05,6.89,.82,10.33,1.23l-.16-.11Z"/><path class="cls-2" d="M694.41,659.09c-1.12,4.68-1.49,9.62-2.94,14.18-3.35,.3-6.35-.82-9.62-1.16-.86-.04-1.1,.75-1.21,1.41-.61,4.24-1.62,8.49-1.68,12.79l.12-.08c-3.85-.45-7.64-1.29-11.46-1.93l.08,.09c1.08-4.16,1.61-8.45,2.38-12.68,.3-1.77,.69-1.96,2.88-1.53,1.M 66,.06,7.56,2.47,8.13,.57,.9-4.54,1.86-9.07,2.81-13.6l-.13,.08c3.55,.61,7.05,1.5,10.64,1.86Z"/><path class="cls-2" d="M719.38,648.07c3.63,1.3,7.64,1.27,11.44,1.98-1.77,4.35-2.13,9.12-3.34,13.65l.11-.1c-3.85,.07-7.63-.83-11.44-1.29l.12,.09c.53-4.84,2.15-9.56,3.12-14.34Z"/><path class="cls-2" d="M678.95,686.32c3.3,.4,6.59,1.31,9.92,1.32,.22-.02,.56-.22,.6-.38,.29-1.27,.57-2.54,.77-3.82,.39-2.56,.71-5.13,1.08-7.7,.18-.92,.47-1.99,1.66-1.82,3.2,.34,6.41,.61,9.49,1.42l-.08-.09c.17,4.81-1.95,9.54-1.46,14.32-3.12-.7-6.35-M .85-9.52-1.34-.68-.08-1.72-.06-1.85,.78-.56,3.73-.98,7.48-1.51,11.21-.12,.58-.16,1.53-.9,1.62-3.61-.13-7.16-.77-10.72-1.28,.61-.62,.67-1.36,.76-2.1,.75-4.05,.44-8.35,1.88-12.22l-.12,.08Z"/><path class="cls-2" d="M704.82,661.04c3.87,.13,7.6,.99,11.45,1.37l-.12-.09c-.69,4.78-2.1,9.53-2.3,14.34-3.78-.66-7.6-1.12-11.46-1.4l.08,.09c.8-4.76,2.22-9.47,2.35-14.31Z"/><path class="cls-2" d="M742.94,721.87c-3.58-.32-7.15-.59-10.74-.77-.2-.01-.52,.19-.62,.35-1,4.32-1.01,8.92-1.7,13.33l.12-.07c-2.93-.12-5.86-.34-8.78-.63-.89-.0M 7-2.4-.23-2.51,.92-.33,2.98-.63,5.97-.97,8.95-.14,1.27-.02,2.58-.81,3.76l.11-.07c-15.69-.52-9.23-3.89-13.05,13.02l.11-.09c-3.81-.42-7.59-1.1-11.42-1.2,.6-4.26,1.15-8.53,1.83-12.78,.51-1.64,3.29-.52,4.61-.61,.8,.08,1.58,.25,2.38,.31,4.76,.36,4.61,.74,4.96-3.24,.38-3.41,.81-6.82,.87-10.26l-.12,.08c3.45,.22,6.9,.48,10.35,.72,.53,.04,1.08-.3,1.13-.7,.6-4.34,1.09-8.69,1.6-13.04l-.1,.09c2.79,.11,5.56,.35,8.34,.6,2.65,.17,2.89,.21,3.07-2.13,.18-3.82,.98-7.64,.8-11.46l-.14,.06c3.86-.34,7.59,.94,11.46,.63l-.14-.16c.67,4.79-M 1.14,9.59-.66,14.38Z"/><path class="cls-2" d="M747.8,680.43c-1.51,4.42-.89,9.34-2.58,13.65l.13-.08c-3.82-.37-7.66-.66-11.44-1.31l.11,.09c1.05-4.5,.85-9.31,2.35-13.65l11.43,1.3Z"/><path class="cls-2" d="M696.01,731.49c-.09,4.39-.48,8.88-1.44,13.15-.16,.45-.81,.64-1.28,.59-3.49-.26-6.94-.68-10.34-1.39,1.15-4.4,1.62-9.1,1.62-13.64,3.81,.45,7.59,1.16,11.43,1.3Z"/><path class="cls-2" d="M700.78,689.47c3.54,.43,7.13,.59,10.61,1.3-.06,3.98-.52,7.93-.98,11.88-.05,1-.38,1.92-1.64,1.79-3.23-.08-6.39-.83-9.61-.66,.26-4.75,.62M -9.65,1.62-14.31Z"/><path class="cls-2" d="M707.33,732.8c-3.81-.41-7.63-.82-11.44-1.23,.74-1.31,.65-2.72,.8-4.11,.31-2.89,.59-5.77,.9-8.66,.1-1.12,1.68-.93,2.56-.86,2.93,.31,5.87,.53,8.81,.7l-.1-.09c-.56,4.77-.49,9.65-1.65,14.33l.12-.08Z"/><path class="cls-2" d="M708.96,718.64c.29-4.29,.61-8.59,1.23-12.85,.09-.54,.69-.9,1.46-.85,2.01,.15,4.01,.3,6.01,.49,3.92,.38,3.72,.1,3.46,3.27-.34,3.75-.78,7.49-.92,11.25l.1-.09c-3.82-.36-7.66-.6-11.44-1.31l.1,.09Z"/><path class="cls-2" d="M732.41,706.96c-3.17-.86-6.6-.7-9.85-1.M 27-.51-.06-.9-.48-.88-.91,.1-1.7,.18-3.41,.34-5.11,.26-2.33,.44-4.69,.86-7,.06-.29,.78-.73,1.2-.7,3.32,.23,6.64,.5,9.95,.81l-.11-.09c-.1,4.78-.36,9.72-1.64,14.33l.14-.06Z"/><path class="cls-2" d="M711.24,690.87c.68-.97,.68-2.06,.83-3.13,.54-3.73,1.09-7.46,1.64-11.2,14.16,1.76,10.7-1.22,9.54,12.77-.15,.97-.27,2.32-1.62,2.2-3.48-.11-6.91-.89-10.4-.65Z"/><path class="cls-2" d="M666.01,698.53c3.48,.83,7.03,1.43,10.6,1.94-.14,4.8-.63,9.61-1.63,14.31-3.42-.78-7.08-1.09-10.39-2.21-.36-2.3-.27-3.17,1.42-14.04Z"/><path clasM s="cls-2" d="M692.8,759.3c-.88,4.54-1.81,9.08-2.44,13.67-3.72-.97-7.64-1.26-11.43-1.96,.36-4.6,1.5-9.15,2.45-13.67,3.56,1.33,7.68,1.19,11.42,1.96Z"/><path class="cls-2" d="M770.43,683.66c-.4,4.44-1.97,9.28-1.61,13.66-3.55-.52-7.08-1.16-10.66-1.45-.68-.06-1.25,.35-1.33,.95-.51,3.82-.83,7.67-1.51,11.47-.08,.42-.63,.75-1.15,.73-3.53-.33-7.22-.35-10.58-1.51l.14,.16c1.02-4.47,1.4-9.09,1.62-13.66l-.13,.08c3.59,.41,7.17,1.04,10.78,1.24,.36,0,.79-.15,.92-.51,1.02-4.27,1.32-8.77,2.08-13.11,3.52,1.13,7.72,1.55,11.42,1.96Z"/>M <path class="cls-2" d="M724.23,777.48c.88-4.77,1.16-9.63,2.54-14.29l-.12,.07c3.58,.2,7.12,.54,10.59,1.3l-.11-.08c.41,1.07,.08,2.14-.09,3.19-.73,3.7-.99,7.54-2.23,11.11-3.48-.69-6.98-1.29-10.59-1.3Z"/><path class="cls-2" d="M739.6,750.34c3.88,.05,7.61,1.02,11.47,1.19-.23,.5-.59,.98-.66,1.5-.63,4.27-1.21,8.54-1.81,12.81-3.81-.47-7.62-1-11.45-1.36l.11,.08c1.5-4.51,1.52-9.61,2.46-14.31l-.11,.1Z"/><path class="cls-2" d="M701.57,774.24c1.17-4.51,1.83-9.09,2.54-13.66l-.11,.09c3.83,.3,7.67,.61,11.43,1.3l-.11-.08c-.11,4.36-M 1.58,8.64-2.36,12.94-.4,1.16-2.18,.57-3.12,.57-2.76-.37-5.51-.77-8.26-1.16Z"/><path class="cls-2" d="M726.77,763.18c-3.82-.43-7.64-.86-11.46-1.3l.11,.08c.62-4.77,1.61-9.5,1.61-14.31l-.11,.07c3.8,.52,7.62,.91,11.43,1.31l-.1-.09c.12,4.78-1.21,9.54-1.61,14.31l.12-.07Z"/><path class="cls-2" d="M729.87,734.79l11.45,1.23c-.58,4.77-1.15,9.55-1.73,14.32l.11-.1-11.45-1.3,.1,.09c.86-4.75,1.2-9.54,1.63-14.32l-.12,.07Z"/></g></svg>h! text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/html;charset=utf-8 <meta charset="UTF-8"> <title>Zombie Pixels</title> height: 100%; background: black; display: flex; align-items: center; justify-content: center; border: 4px solid red; margin: 10px; position: relative; right: 10px; width: 300px; padding: 10px; background-color: rgba(0, 0, 0, 0.8); border-radius: 5px; text-align: center; color: white; #pause-button { display: 'block'; visibility: 'visible'; margin: 0px; width: 200px; justify-content: center; #restart-button { display: 'block'; margin: 0px; width: 200px; justify-content: center; <div id="controls"> 1>ZOMBIE PIXELS</h1> <h2>@BTC_RetroArcade</h2> <h3>How To Play:</h3> <p>Use the arrow keys to move the player.<br> Avoid the red zombie pixels!<br> Don't touch the edge! <button id="pause-button">Pause</button> <button id="restart-button">Restart Game</button> <canvas id="game-canvas" width="600" height="600"></canvas> // Created by Shane Masters 2023 for @BTC_RetroArcade the initial number of opposing team members let initialNumOpponents = 4; let maxOpponents = 40; // Create an array to hold the opposing team member objects const opponents = []; // Get the canvas and context const gamecanvas = document.getElementById("game-canvas"); const canvasctx = gamecanvas.getContext("2d"); let playerX = gamecanvas.width / 2; let playerY = gamecanvas.height / 2; // Set the player's radius const playerRadM const playerSize = playerRadius*2; // Set the size of the opposing team squares const opponentSize = 20; const pauseButton = document.getElementById("pause-button"); pauseButton.addEventListener("click", pauseGame); // Get the restart button element and add an event listener to it const restartButton = document.getElementById("restart-button"); restartButton.addEventListener("click", restartGame); let isPaused = false; nction initializePlayers() for (let index = 0; index < initialNumOpponents; index++) { addOpponent(); drawPlayer(playerX, playerY); // Set the player's speed const playerSpeed = 0.5; // Move the player with arrow keys function movePlayer(deltaTime) if(isPaused) return; // Calculate the distance to move based on player speed and deM const distance = playerSpeed * deltaTime; // Check for arrow key presses and move player accordingly if (keys.ArrowUp && playerY > 0) { playerY -= distance; if (keys.ArrowDown && playerY < gamecanvas.height) { playerY += distance; if (keys.ArrowLeft && playerX > 0) { playerX -= distance; if (keys.ArrowRight && playerX < gamecanvas.width) { playerX += distance; // Ensure player stays inside the canvas playerX = Math.max(0, Math.min(playerX, gamecanvas.width)); playerY = Math.max(0, Math.min(playerY, gamecanvas.height)); // Check if player is outside canvas and end game if true if (playerX === 0 || playerX === gamecanvas.width || playerY === 0 || playerY === gamecanvas.height) endGame(); // Set up keyboardM const keys = {}; document.addEventListener("keydown", e => { keys[e.code] = true; document.addEventListener("keyup", e => { keys[e.code] = false; // add an event listener to the game over condition document.addEventListener('gameOver', () => { // change the display property of the restart button to show it again restartButton.style.visibility = 'visible'; pauseButton.style.visibility = 'hidden';M // Define a custom game over event const gameOverEvent = new Event('gameOver'); function drawPlayer(positionX, positionY) // Get the canvas element and its context const canvas = document.getElementById("game-canvas"); const ctx = canvas.getContext("2d"); // Set the player's color to cyan ctx.fillStyle = "cyan"; // Draw the player circle ctx.beginPath(); ctx.arc(positioM nX, positionY, playerRadius, 0, 2 * Math.PI); ctx.fill(); function drawOpponents() const canvas = document.getElementById("game-canvas"); const ctx = canvas.getContext("2d"); // Draw the opposing team members as squares opponents.forEach(opponent => // Set the color of the opposing team members to red ctx.fillStyle = "white"; ctx.fillRect(opponent.x, opponent.y, opM ponentSize, opponentSize); function addOpponent() // Generate initial positions for the opposing team members const opponentX = Math.floor(Math.random() * (gamecanvas.width - opponentSize)); const opponentY = Math.floor(Math.random() * (gamecanvas.height - opponentSize)); if(opponents.length > maxOpponents) return; if(gameStarted == false) if(gameOver) return; if(isPaused) return; if(checkSpawningCollisions(opponentX, opponentY) == false) return; opponents.push({ x: opponentX, y: opponentY }); let lastUpdateTime = performance.now(); // get the current time in milliseconds let deltaTime = 0; function updateDeltM const currentTime = performance.now(); // get the current time in milliseconds deltaTime = currentTime - lastUpdateTime; // calculate the time difference lastUpdateTime = currentTime; // update the last update time // Set the time interval to add a new opponent const intervalTime = 5000; // 5 seconds // Start the interval timer to add opponents const opponentInterval = setInterval(addOpponent, intervalTime); function checkSpawningCollisions(newOpponentX, newOpponentY) const thresholdDistance = 20; // Check if the new opponent is too close to the player const dx = playerX - (newOpponentX + opponentSize / 2); const dy = playerY - (newOpponentY + opponentSize / 2); const distanceFromPlayer = Math.sqrt(dx * dx + dy * dy); if (distanceFromPlayer < playerSize / 2 + opponentSize / 2 + thresholdDistance) return falM return true; function checkCollisions() // Check if any opponent has collided with the player for (const opponent of opponents) const dx = playerX - (opponent.x + opponentSize / 2); const dy = playerY - (opponent.y + opponentSize / 2); const distance = Math.sqrt(dx * dx + dy * dy); if (distance < playerSize / 2 + opponentSize / 2) // The player has collided with an opponent, end the game endGame(); return; function displayGameOverMessage() // Get the canvas element and its context const canvas = document.getElementById("game-canvas"); const ctx = canvas.getContext("2d"); // Display the "Game Over" message ctx.font = "72px Arial"; ctx.fillStyle = "white"; ctx.textAlign = "center"; ctx.fillText("Game Over", gamecanvas.width / 2, gamecanvas.height / 2); if(gameScore > highScore) localStorage.setItem('zombiePixelsHighScore', gameScore); function endGame() // Set the game over flag to true gameOver = true; document.dispatchEvent(gameOverEvent); // Set the wait time and jitter range for the opposiM const waitTimeMin = 1000; // 1 second const waitTimeMax = 5000; // 3 seconds const jitterRange = 2; // 5 pixels // Set the speed of the opposing team members in pixels per second const opponentSpeed = 200; // Set the countdown time for the start of the game const countdownTime = 3000; // 3 seconds // Set a flag to indicate if the game has started let gameStarted = false; // Create a variable to store the time elapsedM since the start of the game let elapsedTime = 0; let lastplayerTime = 0; gameOver = false; // Create a game loop that updates the positions of the opposing team members function gameLoop() // Get the canvas element and its context const canvas = document.getElementById("game-canvas"); const ctx = canvas.getContext("2d"); // Clear the canvas ctx.clearRect(0, 0, canvas.width, canvas.height); // Check if the game has started if (!gameStarted) updateDeltaTime(); // If not, update the elapsed time elapsedTime += deltaTime; //Added here instead of below to remove the timer gameStarted = true; restartButton.style.visibility = 'hidden'; initializePlayers(); // Check if the countdown has finished if (elapsedTime >= counM // If so, set the flag to indicate that the game has started gameStarted = true; initializePlayers(); else // If not, draw the countdown on the canvas const countdown = Math.ceil((countdownTime - elapsedTime) / 1000); ctx.font = "72px Arial"; ctx.fillStyle = "white"; ctx.textM ctx.fillText(countdown, canvas.width / 2, canvas.height / 2); // Request the next frame of the game loop requestAnimationFrame(gameLoop); return; if(gameStarted) updateDeltaTime(); drawOpponents(); checkCollisions(); if(gameOver == false) if(!isPM moveOpponents(); movePlayer(deltaTime); // Update the game score and draw it in the top left of the canvas gameScore += deltaTime / 1000; displayGameOverMessage(); drawPlayer(playerX, playerY); ctx.font = "24px Arial"; ctx.fillStyle = "white"; ctx.baseline = 'top'; ctx.textAlign = 'left'; ctx.fillText(`Score: ${Math.floor(gameScore)}`, 10, 40); displayHighScore(); // Request the next frame of the game loop requestAnimationFrame(gameLoop); function moveOpponents() // Update the positions of the opposing team members opponents.forEach(opponent => // Check if the opponent is waiting if (!opponent.waitTime) // If not, set a new wait time and jitter value opponent.waitTime = Math.floor(Math.random() * (waitTimeMax - waitTimeMin)) + waitTimeMin; opponent.jitter = { x: Math.floor(Math.random() * (jitterRange * 2)) - jitterRange, y: Math.floor(Math.random() * (jitterRange * 2)) - jitterRange }; opponent.jitterTime = 0; else // If so, update the jitter valuM opponent.jitterTime += deltaTime; if (opponent.jitterTime >= 1000 / 60) { opponent.jitter.x = Math.floor(Math.random() * (jitterRange * 2)) - jitterRange; opponent.jitter.y = Math.floor(Math.random() * (jitterRange * 2)) - jitterRange; opponent.jitterTime = 0; } // Subtract the time elapsed since the last frame from the wait time opponent.waitTime -= deltaTime; if (opponent.waitTime <= 0) { // If the wait time has elapsed, reset it and calculate a new direction towards the player opponent.waitTime = 0; const dx = playerX - (opponent.x + opponentSize / 2); const dy = playerY - (opponent.y + opponentSize / 2); const distance = Math.sqrt(dx * dx + dy * dy); M opponent.dx = dx / distance * opponentSpeed; opponent.dy = dy / distance * opponentSpeed; } // Update the position of the opponent based on its direction and jitter value opponent.x += (opponent.dx || 0) * deltaTime / 1000 + opponent.jitter.x; opponent.y += (opponent.dy || 0) * deltaTime / 1000 + opponent.jitter.y; // Draw the opponent at its updated position //ctx.fillM Rect(opponent.x, opponent.y, opponentSize, opponentSize); function pauseGame() isPaused = !isPaused; const pauseButtonText = isPaused ? "Resume" : "Pause"; pauseButton.innerText = pauseButtonText; // Function to restart the game function restartGame() //Redisplay highscore highScore = localStorage.getItem('zombiePixelsHighScore') || 0; // Reset any necessary gaM pauseButton.style.visibility = 'visible'; restartButton.style.visibility = 'hidden'; playerX = gamecanvas.width / 2; playerY = gamecanvas.height / 2; gameScore = 0; opponents.length = 0; gameOver = false; initializePlayers(); function displayHighScore() // Get the canvas element and its context const canvas = document.getElementById("game-canvas"); const ctx = canvas.getContext("2d"); ctx.font = "24px Arial"; ctx.fillStyle = "cyan"; ctx.baseline = 'bottom'; ctx.textAlign = 'left'; ctx.fillText(`High Score: ${Math.floor(highScore)}`, 10, 20); // Start the game loop let lastFrameTime = Date.now(); let gameScore = 0; let highScore = localStorage.getItem('zombiePixelsHighScore') || 0; text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 6{"p":"brc-20","op":"mint","tick":"wack","amt":"13.37"}h! text/plain;charset=utf-8 6{"p":"brc-20","op":"mint","tick":"wack","amt":"13.37"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 @{"p":"brc-20","op":"deploy","tick":" ","max":"300","lim":"1"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"coin","amt":"1000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 7{"p":"brc-20","op":"mint","tick":"BRUH","amt":"100000"}h! text/plain;charset=utf-8 "name": "bcfx.sats" {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "tribal tattoo"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "eagle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "undead"}, {"trait_type": "Artifacts", "value": "bag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "arrow wounds"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "undead"}, {"trait_type": "Artifacts", "value": "axe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "mage robes"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "honey pot"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "axe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "bag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "undead"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "golden"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "axe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "pirate flag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "robot"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "bloody"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "pauldrons"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "honey pot"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "cape"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "wizard staff"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "blue fire"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "skull"}, {"trait_type": "Artifacts", "value": "undead staff"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "moon"}, {"trait_type": "Body", "value": "tribal tattoo"}, {"trait_type": "Mane", "value": "blue fire"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "frozen staff"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "bloody"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "lamp"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "rainbow"}, {"trait_type": "Claws", "value": "honey pot"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "wizard staff"}]} text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"rssc","amt":"1000"}h! {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "golden armor"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "broadsword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "arrow wounds"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "tribal tattoo"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "lamp"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "silver"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "pauldrons"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "eagle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "crown"}, {"trait_type": "Artifacts", "value": "pirate flag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "golden armor"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "skull"}, {"trait_type": "Artifacts", "value": "poisoned dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "golden armor"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "golden"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "dagger"}]} text/html;charset=utf-8 <meta charset="utf-8" /> position: relative; width: var(--width); height: var(--height); border: 1px solid blue; position: relative; <div id="upload"> <input id="inputUpload" type="file"> function e(e){"use strict";return new function e(t){let n="global"==t?window:this;n.canvas=document.createElement("canvas");let r=n.canvas.getContext("2d");n.width=100,n.height=100,n.canvas.width=n.width,n.canvas.height=n.height,"offscreen"!=t&&(document.body?document.body.appendChild(n.canvas):window.addEventListener("load",(function(){document.body.appendChild(n.canvas)}))),g(),n.MAGIC=161533525,n.RGB=0,n.HSV=1,n.HM SB=1,n.CHORD=0,n.PIE=1,n.OPEN=2,n.RADIUS=1,n.CORNER=2,n.CORNERS=3,n.ROUND="round",n.SQUARE="butt",n.PROJECT="square",n.MITER="miter",n.BEVEL="bevel",n.CLOSE=1,n.BLEND="source-over",n.REMOVE="destination-out",n.ADD="lighter",n.DARKEST="darken",n.LIGHTEST="lighten",n.DIFFERENCE="difference",n.SUBTRACT="subtract",n.EXCLUSION="exclusion",n.MULTIPLY="multiply",n.SCREEN="screen",n.REPLACE="copy",n.OVERLAY="overlay",n.HARD_LIGHT="hard-light",n.SOFT_LIGHT="soft-light",n.DODGE="color-dodge",n.BURN="color-burn",n.NORMAL="norM mal",n.ITALIC="italic",n.BOLD="bold",n.BOLDITALIC="italic bold",n.CENTER="center",n.LEFT="left",n.RIGHT="right",n.TOP="top",n.BOTTOM="bottom",n.BASELINE="alphabetic",n.LANDSCAPE="landscape",n.PORTRAIT="portrait",n.ALT=18,n.BACKSPACE=8,n.CONTROL=17,n.DELETE=46,n.DOWN_ARROW=40,n.ENTER=13,n.ESCAPE=27,n.LEFT_ARROW=37,n.OPTION=18,n.RETURN=13,n.RIGHT_ARROW=39,n.SHIFT=16,n.TAB=9,n.UP_ARROW=38,n.HALF_PI=Math.PI/2,n.PI=Math.PI,n.QUARTER_PI=Math.PI/4,n.TAU=2*Math.PI,n.TWO_PI=2*Math.PI,n.THRESHOLD=1,n.GRAY=2,n.OPAQUE=3,n.INVEM RT=4,n.POSTERIZE=5,n.DILATE=6,n.ERODE=7,n.BLUR=8,n.ARROW="default",n.CROSS="crosshair",n.HAND="pointer",n.MOVE="move",n.TEXT="text",n.VIDEO={video:!0,audio:!1},n.AUDIO={video:!1,audio:!0},n.SHR3=1,n.LCG=2,n.HARDWARE_FILTERS=!0,n.hint=function(e,t){n[e]=t},n.frameCount=0,n.mouseX=0,n.mouseY=0,n.pmouseX=0,n.pmouseY=0,n.mouseButton=null,n.keyIsPressed=!1,n.mouseIsPressed=!1,n.key=null,n.keyCode=null,n.pixels=null,n.accelerationX=0,n.accelerationY=0,n.accelerationZ=0,n.rotationX=0,n.rotationY=0,n.rotationZ=0,n.relRotatM ionX=0,n.relRotationY=0,n.relRotationZ=0,n.pAccelerationX=0,n.pAccelerationY=0,n.pAccelerationZ=0,n.pRotationX=0,n.pRotationY=0,n.pRotationZ=0,n.pRelRotationX=0,n.pRelRotationY=0,n.pRelRotationZ=0,n.touches=[],n._styleCache=[{colorMode:n.RGB,noStroke:!1,noFill:!1,ellipseMode:n.CENTER,rectMode:n.CORNER,curveDetail:20,curveAlpha:0,textFont:"sans-serif",textSize:12,textLeading:12,textStyle:"normal"}],n._style=n._styleCache[n._styleCache.length-1],n._noLoop=!1,n._pixelDensity=1,n._frameRate=null,n._tint=null;let i=nullM ,o=!0,a=[],l=null,s=0,h={},c=0,u=null,f=null,d=null;Object.defineProperty(n,"deviceOrientation",{get:function(){return 90==Math.abs(window.orientation)?n.LANDSCAPE:n.PORTRAIT}}),Object.defineProperty(n,"windowWidth",{get:function(){return window.innerWidth}}),Object.defineProperty(n,"windowHeight",{get:function(){return window.innerHeight}}),Object.defineProperty(n,"drawingContext",{get:function(){return r}}),n.createCanvas=function(e,t){return n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t,g(),n.canvas},nM .resizeCanvas=function(e,t){n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t},n.createGraphics=n.createImage=function(t,n){let r=new e("offscreen");return r.createCanvas(t,n),r.noLoop(),r},n.pixelDensity=function(e){return null==e||(n._pixelDensity=e,n.canvas.width=Math.ceil(n.width*e),n.canvas.height=Math.ceil(n.height*e),n.canvas.style.width=n.width+"px",n.canvas.style.height=n.height+"px",r.scale(n._pixelDensity,n._pixelDensity),g()),n._pixelDensity},n.map=function(e,t,n,r,i,o){let a=r+1*(e-t)/(n-t)*(i-r)M ;return o?r<i?Math.min(Math.max(a,r),i):Math.min(Math.max(a,i),r):a},n.lerp=function(e,t,n){return e*(1-n)+t*n},n.constrain=function(e,t,n){return Math.min(Math.max(e,t),n)},n.dist=function(){return 4==arguments.length?Math.hypot(arguments[0]-arguments[2],arguments[1]-arguments[3]):Math.hypot(arguments[0]-arguments[3],arguments[1]-arguments[4],arguments[2]-arguments[5])},n.norm=function(e,t,r){return n.map(e,t,r,0,1)},n.sq=function(e){return e*e},n.fract=function(e){return e-Math.floor(e)},n.degrees=function(e){retM urn 180*e/Math.PI},n.radians=function(e){return e*Math.PI/180},n.abs=Math.abs,n.ceil=Math.ceil,n.exp=Math.exp,n.floor=Math.floor,n.log=Math.log,n.mag=Math.hypot,n.max=Math.max,n.min=Math.min,n.round=Math.round,n.sqrt=Math.sqrt,n.sin=Math.sin,n.cos=Math.cos,n.tan=Math.tan,n.asin=Math.asin,n.acos=Math.acos,n.atan=Math.atan,n.atan2=Math.atan2,n.Vector=function(e,t,r){let i=this;i.x=e||0,i.y=t||0,i.z=r||0;let o=null,a=null;function l(e,t,n){return null!=e.x?e:null!=t?{x:e,y:t,z:n||0}:{x:e,y:e,z:e}}function s(){null==a&M &(a=i.x*i.x+i.y*i.y+i.z*i.z,o=Math.sqrt(a))}function h(){a=null,o=null}i.set=function(e,t,n){i.x=e||0,i.y=t||0,i.z=n||0},i.copy=function(){return new n.Vector(i.x,i.y,i.z)},i.add=function(){let e=l.apply(null,arguments);return i.x+=e.x,i.y+=e.y,i.z+=e.z,h(),i},i.rem=function(){let e=l.apply(null,arguments);return i.x%=e.x,i.y%=e.y,i.z%=e.z,h(),i},i.sub=function(){let e=l.apply(null,arguments);return i.x-=e.x,i.y-=e.y,i.z-=e.z,h(),i},i.mult=function(){let e=l.apply(null,arguments);return i.x*=e.x,i.y*=e.y,i.z*=e.z,hM (),i},i.div=function(){let e=l.apply(null,arguments);return i.x/=e.x,i.y/=e.y,i.z/=e.z,h(),i},i.mag=function(){return s(),o},i.magSq=function(){return s(),a},i.dot=function(){let e=l.apply(null,arguments);return i.x*e.x+i.y*e.y+i.z*e.z},i.dist=function(){let e=l.apply(null,arguments),t=i.x-e.x,n=i.y-e.y,r=i.z-e.z;return Math.sqrt(t*t+n*n+r*r)},i.cross=function(){let e=l.apply(null,arguments),t=i.y*e.z-i.z*e.y,n=i.z*e.x-i.x*e.z,r=i.x*e.y-i.y*e.x;return i.x=t,i.y=n,i.z=r,h(),i},i.normalize=function(){s();let e=o;retuM rn i.x/=e,i.y/=e,i.z/=e,o=1,a=1,i},i.limit=function(e){s();if(o>e){let t=e/o;i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e}return i},i.setMag=function(e){s();let t=e/o;return i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e,i},i.heading=function(){return Math.atan2(i.y,i.x)},i.rotate=function(e){let t=Math.cos(e),n=Math.sin(e),r=i.x*t-i.y*n,o=i.x*n+i.y*t;return i.x=r,i.y=o,i},i.angleBetween=function(){let e=l.apply(null,arguments);const t=i.dot(e)/(i.mag()*e.mag());let n;return n=Math.acos(Math.min(1,Math.max(-1,t))),n*Math.sign(i.cross(e).z||1)},M i.lerp=function(e,t){return i.x=i.x*(1-t)+e.x*t,i.y=i.y*(1-t)+e.y*t,i.z=i.z*(1-t)+e.z*t,h(),i},i.reflect=function(e){return e.normalize(),i.sub(e.mult(2*i.dot(e)))},i.array=function(){return[i.x,i.y,i.z]},i.equals=function(e,t){return null==t&&null==(t=Number.EPSILON)&&(t=0),Math.abs(e.x-i.x)<t&&Math.abs(e.y-i.y)<t&&Math.abs(e.z-i.z)<t},i.fromAngle=function(e,t){return null==t&&(t=1),o=t,a=t*t,i.x=t*Math.cos(e),i.y=t*Math.sin(e),i.z=0,i},i.fromAngles=function(e,t,n){null==n&&(n=1),o=n,a=n*n;const r=Math.cos(t),l=MaM th.sin(t),s=Math.cos(e),h=Math.sin(e);return i.x=n*h*l,i.y=-n*s,i.z=n*h*r,i},i.random2D=function(){return o=1,a=1,i.fromAngle(Math.random()*Math.PI*2)},i.random3D=function(){return o=1,a=1,i.fromAngles(Math.random()*Math.PI*2,Math.random()*Math.PI*2)},i.toString=function(){return`[${i.x}, ${i.y}, ${i.z}]`}},n.Vector.add=function(e,t){return new n.Vector(e.x+t.x,e.y+t.y,e.z+t.z)},n.Vector.rem=function(e,t){return new n.Vector(e.x%t.x,e.y%t.y,e.z%t.z)},n.Vector.sub=function(e,t){return new n.Vector(e.x-t.x,e.y-t.y,e.M z-t.z)},n.Vector.mult=function(e,t){return null==t.x?new n.Vector(e.x*t,e.y*t,e.z*t):new n.Vector(e.x*t.x,e.y*t.y,e.z*t.z)},n.Vector.div=function(e,t){return null==t.x?new n.Vector(e.x/t,e.y/t,e.z/t):new n.Vector(e.x/t.x,e.y/t.y,e.z/t.z)},n.Vector.dist=function(e,t){return Math.hypot(e.x-t.x,e.y-t.y,e.z-t.z)},n.Vector.cross=function(e,t){return new n.Vector(e.y*t.z-e.z*t.y,e.z*t.x-e.x*t.z,e.x*t.y-e.y*t.x)},n.Vector.lerp=function(e,t,r){return new n.Vector(e.x*(1-r)+t.x*r,e.y=e.y*(1-r)+t.y*r,e.z=e.z*(1-r)+t.z*r)},n.M Vector.equals=function(e,t,n){return e.equals(t,n)};for(let e of["fromAngle","fromAngles","random2D","random3D"])n.Vector[e]=function(t,r,i){return(new n.Vector)[e](t,r,i)};function x(e,t,n){let r,i,o,a,l,s,h,c,u;if(0==t)return[255*(r=n),255*(i=n),255*(o=n)];switch((a=e)>360&&(a=0),h=n*(1-t),c=n*(1-t*(s=(a/=60)-(l=~~a))),u=n*(1-t*(1-s)),l){case 0:r=n,i=u,o=h;break;case 1:r=c,i=n,o=h;break;case 2:r=h,i=n,o=u;break;case 3:r=h,i=c,o=n;break;case 4:r=u,i=h,o=n;break;default:r=n,i=h,o=c}return[255*r,255*i,255*o]}functioM n g(){r.fillStyle="white",r.strokeStyle="black",r.lineCap="round",r.lineJoin="miter"}function p(e){if(0<=e&&e<2*Math.PI)return e;for(;e<0;)e+=2*Math.PI;for(;e>=Math.PI;)e-=2*Math.PI;return e}function m(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;let c=p(a),u=p(l);r.beginPath();for(let a=0;a<h+1;a++){let l=a/h,s=n.lerp(c,u,l),f=Math.cos(s)*i/2,d=Math.sin(s)*o/2;r[a?"lineTo":"moveTo"](e+f,t+d)}s==n.CHORD?r.closePath():s==n.PIE&&(r.lineTo(e,t),r.closePath()),n._style.noFill||r.fill(),n._style.noStrokM e||r.stroke()}function b(e,t,i,o){n._style.noFill&&n._style.noStroke||(r.beginPath(),r.ellipse(e,t,i/2,o/2,0,0,2*Math.PI),n._style.noFill||r.fill(),n._style.noStroke||r.stroke())}function y(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;if(null==a)return function(e,t,i,o){n._style.noFill||r.fillRect(e,t,i,o),n._style.noStroke||r.strokeRect(e,t,i,o)}(e,t,i,o);if(null==l)return y(e,t,i,o,a,a,a,a);const c=Math.min(Math.abs(o),Math.abs(i))/2;a=Math.min(c,a),l=Math.min(c,l),h=Math.min(c,h),s=Math.min(c,s)M ,r.beginPath(),r.moveTo(e+a,t),r.arcTo(e+i,t,e+i,t+o,l),r.arcTo(e+i,t+o,e,t+o,s),r.arcTo(e,t+o,e,t,h),r.arcTo(e,t,e+i,t,a),r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke()}function w(){a=[]}n.createVector=function(e,t,r){return new n.Vector(e,t,r)},n.curvePoint=function(e,t,n,r,i){const o=i*i*i,a=i*i;return e*(-.5*o+a-.5*i)+t*(1.5*o-2.5*a+1)+n*(-1.5*o+2*a+.5*i)+r*(.5*o-.5*a)},n.bezierPoint=function(e,t,n,r,i){const o=1-i;return Math.pow(o,3)*e+3*Math.pow(o,2)*i*t+3*o*Math.pow(i,2)*n+Math.pow(i,M 3)*r},n.curveTangent=function(e,t,n,r,i){const o=i*i;return e*(-3*o/2+2*i-.5)+t*(9*o/2-5*i)+n*(-9*o/2+4*i+.5)+r*(3*o/2-i)},n.bezierTangent=function(e,t,n,r,i){const o=1-i;return 3*r*Math.pow(i,2)-3*n*Math.pow(i,2)+6*n*o*i-6*t*o*i+3*t*Math.pow(o,2)-3*e*Math.pow(o,2)},n.Color=function(e,t,n,r){let i=this;i.MAGIC=786698,i._r=e,i._g=t,i._b=n,i._a=r,i._h=0,i._s=0,i._v=0,i._hsvInferred=!1,i.setRed=function(e){i._r=e,i._hsvInferred=!1},i.setGreen=function(e){i._g=e,i._hsvInferred=!1},i.setBlue=function(e){i._b=e,i._hsvInfM erred=!1},i.setAlpha=function(e){i._a=e/255,i._hsvInferred=!1},i._inferHSV=function(){i._hsvInferred||([i._h,i._s,i._v]=function(e,t,n){let r,i,o,a,l;return r=e<t?e<n?e:n:t<n?t:n,0==(l=100*(i=e>t?e>n?e:n:t>n?t:n)/255)?[o=0,a=0,l]:0==(a=100*(i-r)/i)?[o=0,a,l]:(o=i==e?0+60*(t-n)/(i-r):i==t?120+60*(n-e)/(i-r):240+60*(e-t)/(i-r),[o,a,l])}(i._r,i._g,i._b),i._hsvInferred=!0)},i.toString=function(){return`rgba(${Math.round(i._r)},${Math.round(i._g)},${Math.round(i._b)},${~~(1e3*i._a)/1e3})`}},n.colorMode=function(e){n._stM yle.colorMode=e},n.color=function(){if(1==arguments.length&&786698==arguments[0].MAGIC)return arguments[0];if(n._style.colorMode==n.RGB){if(1==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],1);if(2==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],arguments[1]/255);if(3==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],1);if(4==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],arguments[3]/255)}else{if(1==argumeM nts.length)return new n.Color(...x(0,0,arguments[0]/100),1);if(2==arguments.length)return new n.Color(...x(0,0,arguments[0]/100),arguments[1]/255);if(3==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),1);if(4==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),arguments[3])}return null},n.red=function(e){return e._r},n.green=function(e){return e._g},n.blue=function(e){return e._b},n.alpha=function(e){return 255*e._a},n.hue=function(e){reM turn e._inferHSV(),e._h},n.saturation=function(e){return e._inferHSV(),e._s},n.brightness=function(e){return e._inferHSV(),e._v},n.lightness=function(e){return 100*(.2126*e._r+.7152*e._g+.0722*e._b)/255},n.lerpColor=function(e,t,r){return n._style.colorMode==n.RGB?new n.Color(n.constrain(n.lerp(e._r,t._r,r),0,255),n.constrain(n.lerp(e._g,t._g,r),0,255),n.constrain(n.lerp(e._b,t._b,r),0,255),n.constrain(n.lerp(e._a,t._a,r),0,1)):(e._inferHSV(),t._inferHSV(),new n.Color(n.constrain(function(e,t,r){var i=[[Math.abs(t-M e),n.map(r,0,1,e,t)],[Math.abs(t+360-e),n.map(r,0,1,e,t+360)],[Math.abs(t-360-e),n.map(r,0,1,e,t-360)]];return i.sort(((e,t)=>e[0]-t[0])),(i[0][1]+720)%360}(e._h,t._h,r),0,360),n.constrain(n.lerp(e._s,t._s,r),0,100),n.constrain(n.lerp(e._v,t._v,r),0,100),n.constrain(n.lerp(e._a,t._a,r),0,1)))},n.strokeWeight=function(e){n._style_noStroke=!1,r.lineWidth=e},n.stroke=function(){if(n._style.noStroke=!1,"string"==typeof arguments[0])return void(r.strokeStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._sM tyle.noStroke=!0:r.strokeStyle=e},n.noStroke=function(){n._style.noStroke=!0},n.fill=function(){if(n._style.noFill=!1,"string"==typeof arguments[0])return void(r.fillStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._style.noFill=!0:r.fillStyle=e},n.noFill=function(){n._style.noFill=!0},n.blendMode=function(e){r.globalCompositeOperation=e},n.strokeCap=function(e){r.lineCap=e},n.strokeJoin=function(e){r.lineJoin=e},n.ellipseMode=function(e){n._style.ellipseMode=e},n.rectMode=function(e){n._style.rectM Mode=e},n.curveDetail=function(e){n._style.curveDetail=e},n.curveAlpha=function(e){n._style.curveAlpha=e},n.curveTightness=function(e){n._style.curveAlpha=e},n.clear=function(){r.clearRect(0,0,n.width,n.height)},n.background=function(){if(arguments[0]&&arguments[0].MAGIC==n.MAGIC)return n.image(arguments[0],0,0,n.width,n.height);r.save(),r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity),r.fillStyle="string"==typeof arguments[0]?arguments[0]:n.color(...Array.from(arguments)),r.fillRect(0,0,n.width,n.heightM ),r.restore()},n.line=function(e,t,i,o){n._style.noStroke||(r.beginPath(),r.moveTo(e,t),r.lineTo(i,o),r.stroke())},n.arc=function(e,t,r,i,o,a,l,s){if(o==a)return n.ellipse(e,t,r,i);null==s&&(s=25),null==l&&(l=n.PIE),n._style.ellipseMode==n.CENTER?m(e,t,r,i,o,a,l,s):n._style.ellipseMode==n.RADIUS?m(e,t,2*r,2*i,o,a,l,s):n._style.ellipseMode==n.CORNER?m(e+r/2,t+i/2,r,i,o,a,l,s):n._style.ellipseMode==n.CORNERS&&m((e+r)/2,(t+i)/2,r-e,i-t,o,a,l,s)},n.ellipse=function(e,t,r,i){null==i&&(i=r),n._style.ellipseMode==n.CENTERM ?b(e,t,r,i):n._style.ellipseMode==n.RADIUS?b(e,t,2*r,2*i):n._style.ellipseMode==n.CORNER?b(e+r/2,t+i/2,r,i):n._style.ellipseMode==n.CORNERS&&b((e+r)/2,(t+i)/2,r-e,i-t)},n.circle=function(e,t,r){return n.ellipse(e,t,r,r)},n.point=function(e,t){e.x&&(t=e.y,e=e.x),r.beginPath(),r.ellipse(e,t,.4,.4,0,0,2*Math.PI),r.stroke()},n.rect=function(e,t,r,i,o,a,l,s){n._style.rectMode==n.CENTER?y(e-r/2,t-i/2,r,i,o,a,l,s):n._style.rectMode==n.RADIUS?y(e-r,t-i,2*r,2*i,o,a,l,s):n._style.rectMode==n.CORNER?y(e,t,r,i,o,a,l,s):n._stylM e.rectMode==n.CORNERS&&y(e,t,r-e,i-t,o,a,l,s)},n.square=function(e,t,r,i,o,a,l){return n.rect(e,t,r,r,i,o,a,l)},n.beginShape=function(){w(),r.beginPath(),o=!0},n.beginContour=function(){r.closePath(),w(),o=!0},n.endContour=function(){w(),o=!0},n.vertex=function(e,t){w(),o?r.moveTo(e,t):r.lineTo(e,t),o=!1},n.bezierVertex=function(e,t,n,i,o,a){w(),r.bezierCurveTo(e,t,n,i,o,a)},n.quadraticVertex=function(e,t,n,i){w(),r.quadraticCurveTo(e,t,n,i)},n.bezier=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.bezierVM ertex(r,i,o,a,l,s),n.endShape()},n.triangle=function(e,t,r,i,o,a){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.endShape(n.CLOSE)},n.quad=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.vertex(l,s),n.endShape(n.CLOSE)},n.endShape=function(e){w(),e&&r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke(),n._style.noFill&&n._style.noStroke&&(r.save(),r.fillStyle="none",r.fill(),r.restore())},n.curveVertex=function(e,t){if(a.push([e,t]),a.length<4)return;M let i=function(e,t,n,r,i,o,a,l,s,h){function c(e,t,n,r,i,o){let a=Math.pow(r-t,2)+Math.pow(i-n,2);return Math.pow(a,.5*o)+e}let u=[],f=c(0,e,t,n,r,h),d=c(f,n,r,i,o,h),x=c(d,i,o,a,l,h);for(let h=0;h<s;h++){let c=f+h/(s-1)*(d-f),g=[(f-c)/(f-0),(c-0)/(f-0),(d-c)/(d-f),(c-f)/(d-f),(x-c)/(x-d),(c-d)/(x-d),(d-c)/(d-0),(c-0)/(d-0),(x-c)/(x-f),(c-f)/(x-f)];for(let e=0;e<g.length;e+=2)isNaN(g[e])&&(g[e]=1,g[e+1]=0),isFinite(g[e])||(g[e]>0?(g[e]=1,g[e+1]=0):(g[e]=0,g[e+1]=1));let p=e*g[0]+n*g[1],m=t*g[0]+r*g[1],b=n*g[2]+i*g[M 3],y=r*g[2]+o*g[3],w=i*g[4]+a*g[5],v=o*g[4]+l*g[5],z=p*g[6]+b*g[7],V=m*g[6]+y*g[7],_=b*g[8]+w*g[9],M=y*g[8]+v*g[9],E=z*g[2]+_*g[3],S=V*g[2]+M*g[3];u.push([E,S])}return u}(...a[a.length-4],...a[a.length-3],...a[a.length-2],...a[a.length-1],n._style.curveDetail,n._style.curveAlpha);for(let e=0;e<i.length;e++)o?r.moveTo(...i[e]):r.lineTo(...i[e]),o=!1},n.curve=function(e,t,r,i,o,a,l,s){n.beginShape(),n.curveVertex(e,t),n.curveVertex(r,i),n.curveVertex(o,a),n.curveVertex(l,s),n.endShape()},n.translate=function(e,t){r.tM ranslate(e,t)},n.rotate=function(e){r.rotate(e)},n.scale=function(e,t){null==t&&(t=e),r.scale(e,t)},n.applyMatrix=function(e,t,n,i,o,a){r.transform(e,t,n,i,o,a)},n.shearX=function(e){r.transform(1,0,Math.tan(e),1,0,0)},n.shearY=function(e){r.transform(1,Math.tan(e),0,1,0,0)},n.resetMatrix=function(){r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity)},n.pushMatrix=n.push=function(){n._styleCache.push({...n._style}),n._style=n._styleCache[n._styleCache.length-1],r.save()},n.popMatrix=n.pop=function(){n._stylM eCache.length-1&&(n._styleCache.pop(),n._style=n._styleCache[n._styleCache.length-1],r.restore())},n.image=function(e,t,i,o,a,l,s,h,c){let u=e.MAGIC==n.MAGIC?e.canvas:e;function d(){if(e.MAGIC!=n.MAGIC||!n._tint)return;let t=e.canvas.getContext("2d");t.save(),t.resetTransform(),t.clearRect(0,0,t.canvas.width,t.canvas.height),t.drawImage(f.canvas,0,0),t.restore()}return e.MAGIC==n.MAGIC&&null!=n._tint&&(function(e,t){null==f&&(f=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvasM .height),f.canvas.width==e&&f.canvas.height==t||(f.canvas.width=e,f.canvas.height=t)}(e.canvas.width,e.canvas.height),f.drawImage(e.canvas,0,0),e.tinted(n._tint)),o?l?(h||(h=u.width),c||(c=u.height),r.drawImage(u,l,s,h,c,t,i,o,a),void d()):(r.drawImage(u,t,i,o,a),void d()):(e.MAGIC==n.MAGIC||e.width?r.drawImage(u,t,i,e.width,e.height):r.drawImage(u,t,i,e.videoWidth,e.videoHeight),void d())},n.loadPixels=function(){l=r.getImageData(0,0,n.canvas.width,n.canvas.height),n.pixels=l.data},n.updatePixels=function(){null!=M l&&r.putImageData(l,0,0)},n.loadImage=function(e,t){s++;let r=n.createGraphics(100,100),i=r.canvas.getContext("2d"),o=new Image;return o.src=e,o.crossOrigin="Anonymous",o.onload=function(){i.canvas.width=o.width,i.canvas.height=o.height,r.width=o.width,r.height=o.height,i.drawImage(o,0,0),s--,t&&t(r)},r};let v={};function z(e,t){null==u&&(u=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvas.height),u.canvas.width==e&&u.canvas.height==t||(u.canvas.width=e,u.canvas.height=t)}funcM tion V(){let e=r.canvas.width*r.canvas.height*4;null!=d&&e==d.length||(d=new Uint8ClampedArray(e))}function _(e){u.clearRect(0,0,u.canvas.width,u.canvas.height),u.filter=e,u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()}v[n.THRESHOLD]=function(e,t){null==t?t=127.5:t*=255;for(let n=0;n<e.length;n+=4){const r=.2126*e[n]+.7152*e[n+1]+.0722*e[n+2];e[n]=e[n+1]=e[n+2]=r>=t?255:0}},v[n.GRAY]=function(e){for(let t=0;t<e.length;t+=4)M {const n=.2126*e[t]+.7152*e[t+1]+.0722*e[t+2];e[t]=e[t+1]=e[t+2]=n}},v[n.OPAQUE]=function(e){for(let t=0;t<e.length;t+=4)e[t+3]=255},v[n.INVERT]=function(e){for(let t=0;t<e.length;t+=4)e[t]=255-e[t],e[t+1]=255-e[t+1],e[t+2]=255-e[t+2]},v[n.POSTERIZE]=function(e,t){let n=t-1;for(let r=0;r<e.length;r+=4)e[r]=255*(e[r]*t>>8)/n,e[r+1]=255*(e[r+1]*t>>8)/n,e[r+2]=255*(e[r+2]*t>>8)/n},v[n.DILATE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-M 1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.max(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.ERODE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.min(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.BLURM ]=function(e,t){t=t||1,t=Math.floor(t*n._pixelDensity),V(),d.set(e);let i=2*t+1,o=function(e){let n=new Float32Array(e),r=.3*t+.8,i=r*r*2;for(let t=0;t<e;t++){let o=t-e/2,a=Math.exp(-o*o/i)/(2.5066282746*r);n[t]=a}return n}(i),[a,l]=[r.canvas.width,r.canvas.height];for(let n=0;n<l;n++)for(let r=0;r<a;r++){let l=0,s=0,h=0,c=0;for(let e=0;e<i;e++){let i=4*(n*a+Math.min(Math.max(r-t+e,0),a-1));l+=d[i]*o[e],s+=d[i+1]*o[e],h+=d[i+2]*o[e],c+=d[i+3]*o[e]}let u=4*(n*a+r);e[u]=l,e[u+1]=s,e[u+2]=h,e[u+3]=c}d.set(e);for(let nM =0;n<l;n++)for(let r=0;r<a;r++){let s=0,h=0,c=0,u=0;for(let e=0;e<i;e++){let i=4*(Math.min(Math.max(n-t+e,0),l-1)*a+r);s+=d[i]*o[e],h+=d[i+1]*o[e],c+=d[i+2]*o[e],u+=d[i+3]*o[e]}let f=4*(n*a+r);e[f]=s,e[f+1]=h,e[f+2]=c,e[f+3]=u}},n.filter=function(e,t){if(n.HARDWARE_FILTERS&&null!=r.filter)if(z(),e==n.THRESHOLD){null==t&&(t=.5),t=Math.max(t,1e-5),_(`saturate(0%) brightness(${Math.floor(.5/t*100)}%) contrast(1000000%)`)}else if(e==n.GRAY)_("saturate(0%)");else if(e==n.OPAQUE)u.fillStyle="black",u.fillRect(0,0,u.canvaM s.width,u.canvas.height),u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.drawImage(u.canvas,0,0),r.restore();else if(e==n.INVERT)_("invert(100%)");else if(e==n.BLUR)_(`blur(${Math.ceil(t*n._pixelDensity/1)||1}px)`);else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}},n.resize=function(e,t){z(),u.drawImage(r.canvas,0,0),n.width=e,n.height=t,r.canvas.width=e*n._pixM elDensity,r.canvas.height=t*n._pixelDensity,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0,r.canvas.width,r.canvas.height),r.restore()},n.get=function(e,t,i,o){if(null!=e&&null==i){let i=r.getImageData(e,t,1,1).data;return new n.Color(i[0],i[1],i[2],i[3]/255)}e=e||0,t=t||0,i=i||n.width,o=o||n.height;let a=n.createGraphics(i,o);a.pixelDensity(n._pixelDensity);let l=r.getImageData(e*n._pixelDensity,t*n._pixelDensity,i*n._pixelDensity,o*n._pixelDensity);return a.caM nvas.getContext("2d").putImageData(l,0,0),a},n.set=function(e,t,i){if(i.MAGIC==n.MAGIC){let r=n._tint;return n._tint=null,n.image(i,e,t),void(n._tint=r)}let o=4*(t*n._pixelDensity*r.canvas.width+e*n._pixelDensity);n.pixels[o]=i._r,n.pixels[o+1]=i._g,n.pixels[o+2]=i._b,n.pixels[o+3]=255*i._a},n.tinted=function(){let e=n.color(...Array.from(arguments)),t=e._a;e._a=1,z(),u.clearRect(0,0,u.canvas.width,u.canvas.height),u.fillStyle=e,u.fillRect(0,0,u.canvas.width,u.canvas.height),u.globalCompositeOperation="multiply",u.M drawImage(r.canvas,0,0),u.globalCompositeOperation="source-over",r.save(),r.resetTransform();let i=r.globalCompositeOperation;r.globalCompositeOperation="source-in",r.drawImage(u.canvas,0,0),r.globalCompositeOperation=i,r.restore(),u.globalAlpha=t,u.clearRect(0,0,u.canvas.width,u.canvas.height),u.drawImage(r.canvas,0,0),u.globalAlpha=1,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()},n.tint=function(){n._tint=n.color(...Array.from(arguments))},n.noTiM nt=function(){n._tint=null},n.mask=function(e){r.save(),r.resetTransform();let t=r.globalCompositeOperation;r.globalCompositeOperation="destination-in",r.drawImage(e.canvas,0,0),r.globalCompositeOperation=t,r.restore()},n.clearTemporaryBuffers=function(){u=null,f=null,d=null},n.save=function(e,t){e=e||"untitled",t=t||"png";var n=document.createElement("a");n.innerHTML="[Download]",n.addEventListener("click",(function(){this.href=r.canvas.toDataURL(),this.download=e+"."+t}),!1),document.body.appendChild(n),n.click()M ,document.body.removeChild(n)},n.saveCanvas=function(e,t,r){if(e.MAGIC==n.MAGIC){r&&e.save(t,r);let n=t.split(".");return e.save(n.slice(0,-1).join("."),n[n.length-1])}if(t)return n.save(e,t);let i=e.split(".");return n.save(i.slice(0,-1).join("."),i[i.length-1])},n.loadFont=function(e){let t=e.split("/"),n=t[t.length-1].split(".")[0].replace(" ",""),r=`@font-face {\n font-family: '${n}';\n src: url('${e}');\n }`;const i=document.createElement("style");return i.textContent=r,document.head.append(M i),n},n.textFont=function(e){n._style.textFont=e},n.textSize=function(e){n._style.textSize=e,n._style.textLeading=e},n.textLeading=function(e){n._style.textLeading=e},n.textStyle=function(e){n._style.textStyle=e},n.textAlign=function(e,t){r.textAlign=e,t&&(r.textBaseline=t==n.CENTER?"middle":t)},n.text=function(e,t,i,o){if(!e)return;if(e=e.toString(),n._style.noFill&&n._style.noStroke)return;r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`;let a=e.split("\n");for(let e=0;e<a.length;e++)n._M style.noFill||r.fillText(a[e],t,i,o),n._style.noStroke||r.strokeText(a[e],t,i,o),i+=n._style.textLeading},n.textWidth=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).width},n.textAscent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBoundingBoxAscent},n.textDescent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBounM dingBoxDescent};var M,E=4,S=.5,R=function(e){return.5*(1-Math.cos(e*Math.PI))};n.noise=function(e,t,n){if(t=t||0,n=n||0,null==M){M=new Array(4096);for(var r=0;r<4096;r++)M[r]=Math.random()}e<0&&(e=-e),t<0&&(t=-t),n<0&&(n=-n);for(var i,o,a,l,s,h=Math.floor(e),c=Math.floor(t),u=Math.floor(n),f=e-h,d=t-c,x=n-u,g=0,p=.5,m=0;m<E;m++){var b=h+(c<<4)+(u<<8);i=R(f),o=R(d),a=M[4095&b],a+=i*(M[b+1&4095]-a),l=M[b+16&4095],a+=o*((l+=i*(M[b+16+1&4095]-l))-a),l=M[4095&(b+=256)],l+=i*(M[b+1&4095]-l),s=M[b+16&4095],l+=o*((s+=i*(M[M b+16+1&4095]-s))-l),g+=(a+=R(x)*(l-a))*p,p*=S,h<<=1,c<<=1,u<<=1,(f*=2)>=1&&(h++,f--),(d*=2)>=1&&(c++,d--),(x*=2)>=1&&(u++,x--)}return g},n.noiseDetail=function(e,t){e>0&&(E=e),t>0&&(S=t)};const I=function(){let e,t,n=4294967295;return{setSeed(r){e=t=(null==r?Math.random()*n:r)>>>0},getSeed:()=>t,rand:()=>(e^=e<<17,e^=e>>13,((e^=e<<5)>>>0)/n)}};let C=I();C.setSeed(),n.noiseSeed=function(e){let t=null==e?4294967295*Math.random():e;M||(M=new Float32Array(4096));for(var n=0;n<4096;n++)t^=t<<17,t^=t>>13,t^=t<<5,M[n]=(t>M >>0)/4294967295},n.randomSeed=function(e){C.setSeed(e)},n.random=function(e,t){return null==e?C.rand():"number"==typeof e?null!=t?C.rand()*(t-e)+e:C.rand()*e:e[~~(e.length*C.rand())]},n.randomGenerator=function(e){e==n.LCG?C=function(){const e=4294967296;let t,n;return{setSeed(r){n=t=(null==r?Math.random()*e:r)>>>0},getSeed:()=>t,rand:()=>(n=(1664525*n+1013904223)%e)/e}}():e==n.SHR3&&(C=I()),C.setSeed()};var T=new function(){var e,t,n,r=new Array(128),i=new Array(256),o=new Array(128),a=new Array(128),l=new Array(2M 56),s=new Array(256),h=function(){return 4294967296*C.rand()-2147483648},c=function(){return.5+2.328306e-10*(h()<<0)};this.SHR3=h,this.UNI=c,this.RNOR=function(){return n=h(),e=127&n,Math.abs(n)<r[e]?n*o[e]:function(){for(var t,i,l,s,u=3.44262;;){if(t=n*o[e],0==e){do{l=c(),s=c(),t=.2904764*-Math.log(l),i=-Math.log(s)}while(i+i<t*t);return n>0?u+t:-u-t}if(a[e]+c()*(a[e-1]-a[e])<Math.exp(-.5*t*t))return t;if(n=h(),e=127&n,Math.abs(n)<r[e])return n*o[e]}}()},this.REXP=function(){return(t=h()>>>0)<r[e=255&t]?t*l[e]:funM ction(){for(var n;;){if(0==e)return 7.69711-Math.log(c());if(n=t*l[e],s[e]+c()*(s[e-1]-s[e])<Math.exp(-n))return n;if((t=h())<i[e=255&t])return t*l[e]}}()},this.zigset=function(){var e,t,n=2147483648,h=4294967296,c=3.442619855899,u=c,f=.00991256303526217,d=7.697117470131487,x=d,g=.003949659822581572;for(e=f/Math.exp(-.5*c*c),r[0]=Math.floor(c/e*n),r[1]=0,o[0]=e/n,o[127]=c/n,a[0]=1,a[127]=Math.exp(-.5*c*c),t=126;t>=1;t--)c=Math.sqrt(-2*Math.log(f/c+Math.exp(-.5*c*c))),r[t+1]=Math.floor(c/u*n),u=c,a[t]=Math.exp(-.5*cM *c),o[t]=c/n;for(e=g/Math.exp(-d),i[0]=Math.floor(d/e*h),i[1]=0,l[0]=e/h,l[255]=d/h,s[0]=1,s[255]=Math.exp(-d),t=254;t>=1;t--)d=-Math.log(g/d+Math.exp(-d)),i[t+1]=Math.floor(d/x*h),x=d,s[t]=Math.exp(-d),l[t]=d/h}};T.hasInit=!1,n.randomGaussian=function(e,t){return T.hasInit||(T.zigset(),T.hasInit=!0),T.RNOR()*t+e},n.randomExponential=function(){return T.hasInit||(T.zigset(),T.hasInit=!0),T.REXP()},n.print=console.log,n.cursor=function(e,t,r){let i="";e.includes(".")&&(e=`url("${e}")`,i=", auto"),null!=t&&(e+=" "+t+M " "+r),n.canvas.style.cursor=e+i},n.noCursor=function(){n.canvas.style.cursor="none"},n.createCapture=function(e){var t=document.createElement("video");return t.playsinline="playsinline",t.autoplay="autoplay",navigator.mediaDevices.getUserMedia(e).then((function(e){t.srcObject=e})),t.style.position="absolute",t.style.opacity=1e-5,t.style.zIndex=-1e3,document.body.appendChild(t),t};let A=["setup","draw","preload","mouseMoved","mousePressed","mouseReleased","mouseDragged","mouseClicked","keyPressed","keyReleased","keM yTyped","touchStarted","touchEnded"];for(let e of A){let t="_"+e+"Fn";n[t]=function(){},n[t].isPlaceHolder=!0,n[e]?n[t]=n[e]:Object.defineProperty(n,e,{set:function(e){n[t]=e}})}function D(){n._noLoop||(i=null==n._frameRate?requestAnimationFrame(D):setTimeout(D,1e3/n._frameRate)),w(),o=!0,n.push(),n._drawFn(),n.pop(),++n.frameCount}function k(e){const t=n.canvas.getBoundingClientRect(),r=n.canvas.scrollWidth/n.width||1,i=n.canvas.scrollHeight/n.height||1;return{x:(e.clientX-t.left)/r,y:(e.clientY-t.top)/i,id:e.idenM tifier}}function L(){return n._touchStarted.isPlaceHolder&&n._touchMoved.isPlaceHolder&&n._touchEnded.isPlaceHolder}n.noLoop=function(){n._noLoop=!0,i=null},n.loop=function(){n._noLoop=!1,null==i&&D()},n.redraw=function(){D()},n.frameRate=function(e){n._frameRate=e},setTimeout((function(){n._preloadFn(),c=window.performance.now(),function e(){if(s>0)return setTimeout(e,10);n._setupFn(),D()}()}),1),n.canvas.onmousemove=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPM ressed?n._mouseDraggedFn(e):n._mouseMovedFn(e)},n.canvas.onmousedown=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!0,n.mouseButton=[n.LEFT,n.CENTER,n.RIGHT][e.button],n._mousePressedFn(e)},n.canvas.onmouseup=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!1,n._mouseReleasedFn(e)},n.canvas.onclick=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressedM =!0,n._mouseClickedFn(e),n.mouseIsPressed=!1},window.addEventListener("keydown",(function(e){n.keyIsPressed=!0,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!0,n._keyPressedFn(e),1==e.key.length&&n._keyTypedFn(e)})),window.addEventListener("keyup",(function(e){n.keyIsPressed=!1,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!1,n._keyReleasedFn(e)})),n.keyIsDown=function(e){return!!h[e]},n.canvas.ontouchstart=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.moM useY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mousePressedFn(e)||e.preventDefault()),n._touchStartedFn(e)||e.preventDefault()},n.canvas.ontouchmove=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mouseDraggedFn(e)||e.preventDefault()),n._touchMovedFn(e)||e.preventDefault()},n.canvas.ontouchend=n.canvas.ontouchcancel=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.M mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!1,n._mouseReleasedFn(e)||e.preventDefault()),n._touchEndedFn(e)||e.preventDefault()},n.hasSensorPermission=!window.DeviceOrientationEvent&&!window.DeviceMotionEvent||!(DeviceOrientationEvent.requestPermission||DeviceMotionEvent.requestPermission),n.requestSensorPermissions=function(){DeviceOrientationEvent.requestPermission&&DeviceOrientationEvent.requestPermission().then((e=>{"granted"==e&&DeviceMotionEvent.requestPermissioM n&&DeviceMotionEvent.requestPermission().then((e=>{"granted"==e&&(n.hasSensorPermission=!0)})).catch(alert)})).catch(alert)},window.ondeviceorientation=function(e){n.pRotationX=n.rotationX,n.pRotationY=n.rotationY,n.pRotationZ=n.rotationZ,n.pRelRotationX=n.relRotationX,n.pRelRotationY=n.relRotationY,n.pRelRotationZ=n.relRotationZ,n.rotationX=e.beta*(Math.PI/180),n.rotationY=e.gamma*(Math.PI/180),n.rotationZ=e.alpha*(Math.PI/180),n.relRotationX=[-n.rotationY,-n.rotationX,n.rotationY][1+~~(window.orientation/90)],n.rM elRotationY=[-n.rotationX,n.rotationY,n.rotationX][1+~~(window.orientation/90)],n.relRotationZ=n.rotationZ},window.ondevicemotion=function(e){if(n.pAccelerationX=n.accelerationX,n.pAccelerationY=n.accelerationY,n.pAccelerationZ=n.accelerationZ,!e.acceleration){let t=((e,t)=>[(e[0]*t[0]+e[1]*t[1]+e[2]*t[2]+e[3])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[4]*t[0]+e[5]*t[1]+e[6]*t[2]+e[7])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[8]*t[0]+e[9]*t[1]+e[10]*t[2]+e[11])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15])])(((e,t)M =>[e[0]*t[0]+e[1]*t[4]+e[2]*t[8]+e[3]*t[12],e[0]*t[1]+e[1]*t[5]+e[2]*t[9]+e[3]*t[13],e[0]*t[2]+e[1]*t[6]+e[2]*t[10]+e[3]*t[14],e[0]*t[3]+e[1]*t[7]+e[2]*t[11]+e[3]*t[15],e[4]*t[0]+e[5]*t[4]+e[6]*t[8]+e[7]*t[12],e[4]*t[1]+e[5]*t[5]+e[6]*t[9]+e[7]*t[13],e[4]*t[2]+e[5]*t[6]+e[6]*t[10]+e[7]*t[14],e[4]*t[3]+e[5]*t[7]+e[6]*t[11]+e[7]*t[15],e[8]*t[0]+e[9]*t[4]+e[10]*t[8]+e[11]*t[12],e[8]*t[1]+e[9]*t[5]+e[10]*t[9]+e[11]*t[13],e[8]*t[2]+e[9]*t[6]+e[10]*t[10]+e[11]*t[14],e[8]*t[3]+e[9]*t[7]+e[10]*t[11]+e[11]*t[15],e[12]*t[0]+M e[13]*t[4]+e[14]*t[8]+e[15]*t[12],e[12]*t[1]+e[13]*t[5]+e[14]*t[9]+e[15]*t[13],e[12]*t[2]+e[13]*t[6]+e[14]*t[10]+e[15]*t[14],e[12]*t[3]+e[13]*t[7]+e[14]*t[11]+e[15]*t[15]])((e=>[Math.cos(e),0,Math.sin(e),0,0,1,0,0,-Math.sin(e),0,Math.cos(e),0,0,0,0,1])(n.rotationY),(e=>[1,0,0,0,0,Math.cos(e),-Math.sin(e),0,0,Math.sin(e),Math.cos(e),0,0,0,0,1])(n.rotationX)),[0,0,-9.80665]);n.accelerationX=e.accelerationIncludingGravity.x+t[0],n.accelerationY=e.accelerationIncludingGravity.y+t[1],n.accelerationZ=e.accelerationIncludM ingGravity.z-t[2]}},n.year=function(){return(new Date).getFullYear()},n.day=function(){return(new Date).getDay()},n.hour=function(){return(new Date).getHours()},n.minute=function(){return(new Date).getMinutes()},n.second=function(){return(new Date).getSeconds()},n.millis=function(){return window.performance.now()-c}}(e)}"object"==typeof exports&&"undefined"!=typeof module&&(module.exports=e);const t="https://ancient-crimson-rain.btc.discover.quiknode.pro/c268fb026303ae8443f785200f2ea4b82f0082dd";function n(e){P(e)?M localStorage.removeItem("blocksApiEndpoint"):localStorage.blocksApiEndpoint=e}function r(){return localStorage.blocksApiEndpoint||t}function i(e){P(e)?localStorage.removeItem("modelInscriptionEndpoint"):localStorage.modelInscriptionEndpoint=e}function o(){return localStorage.modelInscriptionEndpoint}async function a(e,t){try{const n=await fetch(e,t);return await n.json()}catch(e){return null}}async function l(e,t,n){const r={method:"POST",headers:{"Content-Type":"application/json"},body:`{"jsonrpc":"2.0","id":1,"meM thod":"${t}","params":${`[${n.join(sep=",")}]`}}`};return(await a(e,r))?.result}async function s(e){const n={avgfee:10,time:Date.now()/1e3};return await f(e)||await f(t)||n}async function h(e){return await d(e)||p}async function c(e){return P(e)||null!=await f(e)}async function u(e){return P(e)||null!=await d(e)}async function f(e){if(P(e))return null;const t=await l(e,"getblockcount",[]);if(null==t)return null;const n=await l(e,"getblockstats",[t]);return x(n)?n:null}async function d(e){if(P(e))return null;const tM =await a(e,{});return g(t)?t:null}function x(e){return"number"==typeof e?.time&&"number"==typeof e?.avgfee}function g(e){if(null==e)return!1;const{classes_name:t,training_traits:n,layers_config:r,weight_b64:i}=e;if(!Array.isArray(t))return!1;if(null==n)return!1;try{j(r,i)}catch(e){return!1}return!0}const p={"model_name": "pfp_classifier_34", "layers_config": {"config": {"layers": [{"class_name": "InputLayer", "config": {"batch_input_shape": [null, 28, 28, 3]}}, {"class_name": "Rescaling", "config": {"scale": 0.0078M 4313725490196, "offset": -1}}, {"class_name": "Flatten"}, {"class_name": "Dense", "config": {"units": 5, "activation": "tanh"}}, {"class_name": "Dense", "config": {"units": 3, "activation": "tanh"}}, {"class_name": "Dense", "config": {"units": 5, "activation": "tanh"}}, {"class_name": "Dense", "config": {"units": 2, "activation": "tanh"}}, {"class_name": "Dense", "config": {"units": 4, "activation": "linear"}}]}}, "weight_b64": "HL9ovGB+QDzzxZs8Z201vZtZKb2tDI885TCcveK8nL0v10493sdEvQhKLD31vBo9s2n+PNxsNr0a44i9FnsFPPbM 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 8ISOmvZn2sTyEl8U9b44ZvCeoC7zpp2S9PhmLvYu70TxbYFA8lUc4PUbhIL00eIQ9wwKMvQOZrDwKF5k92kcGvev2FL0cQrs9k+43vdhs1zuR/Uo8yaGWum0WoDzFf1G8ol17OwQ+mzyYbAU+Y+/OvVTsJL3VVtg84bJXvS6v1LxZTno9SdJJO0yUH70JVs27x8MHOz/Wabwz54K9xMUNvcFWKLss8eY9IQh8vVGhKb0nKgU92kq6vahxqj2YhAc9HOfjOgqpGr0ic4q9dQXqPOwDiz0rjoC7mzGIPLJejb3LfhQ+K5fqvS55CL0J9B+8gUa4vYWwXD2TLEC8lXWcvbYUAzwm4tW8ZnKeOwOplj0p9ZG8pJyHvfqcBjvonsE9gu8Zvmynh70N+li9+dm7vch6kz08mvc7xCOyvBJZmr3ya8q94LzAuxUNKj16a9K8puW9PBgCVr1ssvw9Q6Ecvs6p0rw+Dyg9xZaSvZ+RRz3pZio9z1lCvKzfnr2Zl5i9nRoKvWTM 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 0Eb5gRKA6+a0DvmLk4rxK3689lJ3yvROhszrXUlm+SSkGvXRj8DxYbOG9ARTLPc7BHb60LAq9WwEEPWV1EbxTPGY8hJWfPR2O1r3etum8piS5vBH/Njssjia76cevvMm5jzxFQvq8/wGovE0WRLx7Viu82/EYvaOzjz0eDGq92YrxPYHE1Lv3fXi9zHuqPTZFbLw9mes9kSBsPI4CAT04QJs8z3uvvWKSxz2r4nQ8kUMEPCbwqr29E1O9qzXvvanL3z2vHyM9bfA7vajEVT10/te9wA7WPejDKT0KjEi9jTfMPBKGG71jLcs9E6kVvd4+jD10YM09CNVqPVs3HLzNrRO9He7FPayNPj3/GQE9HMJBvcV2JL10Ci27pdSKPP5TBLutqEO6VAaJvdUeFTx8wCA83DLqOj/0hL0oZqm9mIoCPlwfhTshk9C87vuivACzsbxJ/qI9Y8J5vTLhP71L+Y+8L9Z7uw0VM7yvebM8XmNevDvrgz2SDuw8e5+xumWkpz3oaSYM 9ht7GvNZUkjtOL+O8EFomvRJHkT0H8aU8ozeZvO7GrTsGXU28zC8HvYVTLT0xQoC8sisovOnUNL0Puue8mPnIvEbU1LscBw49EgwoPevyo7wgHtA8T0ICvf23yLzici69SvbcvHaWH7o1Cqw8MgcSvCWTYjwyl3G8+AulvGvmoTx4mrI72gQluSqZSj29Ooy9KcNovcRtlz0nfsi8FhaHu1uwILyuohY97uuSvTgXCr0HlQU8JHI3vfLO/Tzh1+k8XdCaOuKqlDxKbKC9fndfvZIEhz29Nwo9x9QivS4zqTzV5w8+0tqQvfslUz0hLJY7E8YDPCRnHz3A7Tc9omDPu2szkrw5VWc9gFNfvTBDXLxG/dQ9bhJZPAJS0jsTMMo91sMVvhGctT1fdhE9aa6pPI3TPLu09yW9xqEuPUMHtbvRjgy890sEvQiAuT3vBr89/SfQvHEoaj1y35m7zWOkvRT0wj2gEYc8ZdGsPSk1h72UlyC9n6fcPY6YvTxOqno96zcWvDOM 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 80xkJvSM+S73+RcA9ugbIO2lrWj0iGue9bl0UvQYsB73iRKI9rAFevJ/MCj1izwi9742svWdeaD2BSVk98USiPQ6kRb1ijGS8qGZoPbTjiDyEnKc88fxPvRQPFr3bQ0K9n/z1PMgmGD2E5sQ8IsoYvLs3lLyKjOW6fUxXvTEdND2cDXM9X7XMvRjlR73GBu28XAaVvCPFLz3YaBC9gNJBvbbuJr3WPFu82TbAPcfusL3PNd28ftB3vTlgtLwEmuQ8e6SnveopZDu1Rwq+7VrBPNw0i73jB+M81EZWvHRvlT3sttY6K68gPNosnj1FIVw9MMsAPjt0Nz1NFka9/0cMPZM3BD2TthQ+AuKivbiVRb2ODaS8pvkrPTo/u718ETW9qm75PEqvabySxec9NULivWgIbrubcww8yB1HvcbKKj3nSHm9Mp3nvTgCCL3Imc09FIluPXyt1b2yZg69JnwwvM37Aj7Js4M9l1DcvAnd1TzqrpC9+1OGPT2KUr3tSUG96xagPREM 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 9i2ZePeNooDrR6hq9T1CrPbtBBr0C9JQ9JlaEPfx2zzyuo429CpVjvfZMxz095G49F/QwvDm+h71Svbu9kpUPPmjkPT37xGc9+aVXvAAQGb34XtE9DHYwPVQoyDzpgIi992+gvB3qYj13cQk+dnQ4vTanO73620G7o/++PWrNy7s8i0g99+2DvVKWcD1XkaA9bKktvBXHzLxLszw9OCgQvSlBPj0ajGg9lriKvX/4qjymUhc9OKupPBeSM7xVjUk81C5XPe11eruITYA8oMnOvKjMaD3Uxyc6oBg1PbmSoT3qDeQ91LTPvX+QsD1+MZw9UMzpPOjwvrzKozc96FWzOl4fuD3WGD69Ll80PW9qnj0PNg28WR0ovchVUbyAHNM9RjlwvfJnhDwbu+48Hz/LPK9nIzvOl9K8lUIGPSN6yzk6wKI954rhvDUHbT3o7Yc9gIDhPDuNBTy/v2M9R4eHveWZpjwmTYy8gpAXPfKmOz0OVbU8dicAPL4VGD32ToA9DW4GvVSM 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 WoT06nwE+wQbuO9PUpb2GztI8TZ3rvEpepD2/GQg91i1+vSXCK7yUwJm8M25uPRYc7zkRq4k9WVXyvaZgoz0F7aQ91JVTPaVJqr1v/he9oGc0vdtnPD0Jgl68uNDqvNr7lL2MkJo7EBTUPeS/xjzcTVM7YvSLvS3onD2s3wY+vespPRAHv7uFlTm940SfvctKAj49DgE9RN+1PEWyrbzY33I93TB2PcAE9jwR3Ms9uFyHvVIBnTz0CZY93yycPP4gRz1eCTQ9wiaYvYsLnT2xmBs8uzwIPUN8iLzXMeM7LE+BPd9PXzxXO8Y9BGW6OxnvCzz1gUs8U+qGvCLWGD2wA4c8D+CEvZd0bj001AC9Uh/ZPdssHz3HOz08rDY4vLkStbybxKM9ocpbvIxZrLzAhSu2uB37vfBtnj1JuIs9MSdxvEA8UT3CVYG9rx6dPWKxdD2iGb07FZ+1vE8yEbzRQKs9ClSJPOARZLuOzdO7BqiqvHlO2jyYIso9MoOhvVDRsbyNTEOM 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 +7CIkPbKSTz9Jpsc/SuUFwBoxE8CbNso/eeO1v9zLhr9noQpAeYwAPq8jiL68NDc+V/GbvQ==", "training_traits": {"structure_gen": "Random", "n_layers": 4, "max_nodes": 5, "activation_func": "Tanh", "epoch_num": 5}, "classes_name": ["Cryptoadz", "Cryptopunks", "Moonbirds", "Nouns"]},m=25,b=50,y=59+11/12,w=59+11.5/12,v=60;function z(e,t){const n=Math.log(1-t)/Math.log(1-e);return e=>1-Math.pow(1-e,n)}class V{constructor(e,t,n){const{model:r,inputDim:i}=j(t,n);this.model=r,this.inputDim=i,this.iteration=0,this.stage=0;const o=new DateM (parseInt(e.birthYear),0,1).getTime(),a=new Date(parseInt(e.birthYear)+1,0,1).getTime();this.birthDate=new Date(Math.floor((o+a)/2));const l=zr.filter((t=>t[0]==e.lifeCycle))[0][2];this.growSpeed=365/l,this.cycleLength=60*l*24*3600*1e3,this.growthFunc=z(.4,.8)}updateAge(e){const t=(e.getTime()-this.birthDate.getTime())/31536e6*this.growSpeed;this.iteration=Math.floor(t/60);const n=t-60*this.iteration;let r;this.age=n;let i,o=0;if(n<25){let e=map(n,0,25,0,1);o=this.growthFunc(e),r=(25-n)/60,this.stage=1,this.stageRaM tio=map(n,0,25,0,1)}else n<50?(o=1,r=(50-n)/60,this.stage=2,this.stageRatio=map(n,25,50,0,1)):n<y?(o=map(n,50,y,1,0),r=(y-n)/60,this.stage=3,this.stageRatio=map(n,50,y,0,1)):n<w?(o=0,r=(w-n)/60,this.stage=4,this.stageRatio=map(n,y,w,0,1)):n<60&&(o=0,r=(60-n)/60,this.stage=5,this.stageRatio=map(n,w,60,0,1));n<50?i=map(n,0,50,0,780/880):n<w?i=map(n,50,w,780/880,800/880):n<60&&(i=map(n,w,60,800/880,1)),this.nextStateTimestamp=Math.round(e.getTime()+this.cycleLength*r),this.statePercentage=round(100*i);let a=(25-n)/60;M a<0&&(a+=1),this.nextStableTimestamp=Math.round(e.getTime()+this.cycleLength*a),this.growth=o,this.model.updateNeurons(o,this.iteration)}getBrainStatus(){return{totalNeurons:this.model.getTotalNeurons(),neuronsLife:this.model.getNeuronsLife(),stage:this.stage,inputDim:this.inputDim,stageRatio:this.stageRatio,age:this.age,growth:this.growth,nextStateTimestamp:this.nextStateTimestamp,nextStableTimestamp:this.nextStableTimestamp,rebirthCount:max(this.iteration,0),statePercentage:this.statePercentage}}classifyImage(e){M const t=new G(e,1,e.length);return this.model.forward(t).mat[0]}}class M{constructor(e,t,n,r,i){this.p=e,this.v=t,this.size=n,this.shape=i,this.col=r}getRadius(){return 1==Oe?1*this.size/2:2==Oe?7*this.size/16:3==Oe||4==Oe?4*this.size/7:0}update(){this.p.add(this.v)}draw(e,t,n,r){const i=this.p.x*r,o=this.p.y*r,a=this.size*r,{col:l,shape:s}=this;let h,c;1==n?h=c=l:2==n?(h=dr(t,1),c=l):(h=dr(t,0),c=dr(l,1));e.stroke(dr(c,map(1,0,1,.25,1))),e.fill(dr(h,map(1,0,1,.15,1))),3==n&&e.fill(dr(h,0)),1==s?e.ellipse(i,o,a,a):M 2==s?e.rect(i,o,7*a/8,7*a/8):3==s&&(e.beginShape(),e.vertex(i-4*a/7,o),e.vertex(i,o-4*a/7),e.vertex(i+4*a/7,o),e.vertex(i,o+4*a/7),e.endShape(CLOSE))}}class E{constructor(e,t,n,r,i,o,a){this.center=e,this.len=t,this.angle=n,this.v=r,this.angV=i,this.c1=o,this.c2=a}getEndpoints(){const e=createVector(this.len/2*cos(this.angle),this.len/2*sin(this.angle));return[Vector.add(this.center,e),Vector.sub(this.center,e)]}update(){this.center.add(this.v),this.angle+=this.angV}draw(e,t){const[n,r]=this.getEndpoints(),i=n.x*t,M o=n.y*t,a=r.x*t,l=r.y*t,s=this.c1,h=this.c2;var c=e.drawingContext.createLinearGradient(i,o,a,l);c.addColorStop(0,s),c.addColorStop(1,h),e.drawingContext.strokeStyle=c,e.drawingContext.globalAlpha=1,e.line(i,o,a,l),e.drawingContext.globalAlpha=1}}function S(e,t){const n=random(TAU),r=random(e,t);return createVector(r*cos(n),r*sin(n))}class R{constructor(e,t,n,r,i){this.wall=n,this.maxR=i;const o=t.length;this.nodes=[];for(let a=0;a<o;++a){const o=[],l=.25*t[a];for(let t=0;t<l;++t){const t=createVector(random(n.xLefM t,n.xRight),random(n.yTop,n.yBottom)),l=S(.02*i,.05*i),s=random(10,25)*i;o.push(new M(t,l,s,e[a],r))}this.nodes.push(o)}const a=A(e);a.unshift(e[0]),a.push(e[e.length-1]),this.lines=[];for(let e=0;e<=o;++e){const r=[],l=(0==e?1:t[e-1])*(e==o?1:t[e])*1.5;for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),o=random(5*i,10*i),l=random(TAU),s=S(.02*i,.05*i),h=random(2e-4,.001);r.push(new E(t,o,l,s,h,a[e],a[e+1]))}this.lines.push(r)}}reflectNode(e){const{xLeft:t,yTop:n,xRight:r,yM Bottom:i}=this.wall,{p:o,v:a}=e,l=e.getRadius();(o.x-l<t&&a.x<0||o.x+l>r&&a.x>0)&&(a.x=-a.x),(o.y-l<n&&a.y<0||o.y+l>i&&a.y>0)&&(a.y=-a.y)}reflectLine(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,[o,a]=e.getEndpoints(),l=e.v;(min(o.x,a.x)<t&&l.x<0||max(o.x,a.x)>r&&l.x>0)&&(l.x=-l.x),(min(o.y,a.y)<n&&l.y<0||max(o.y,a.y)>i&&l.y>0)&&(l.y=-l.y)}update(){for(const e of this.lines)for(const t of e)t.update(),this.reflectLine(t);for(const e of this.nodes)for(const t of e)t.update(),this.reflectNode(t)}draw(e,t,n,rM ,i){const o=i/this.maxR;for(const t of this.lines){const n=t.length*r;for(let r=0;r<n;++r)t[r].draw(e,o)}for(const i of this.nodes){const a=i.length*r;for(let r=0;r<a;++r)i[r].draw(e,t,n,o)}}}function I(e,t){re(e),e.fill(0),e.rect(0,0,500,500),ie(e),e.noStroke(),e.fill(dr(cr("#000000"),.5)),e.push(),e.translate(250,250),e.scale(t),e.translate(-250,-250),e.beginShape(),e.vertex(235.2,24.9),e.bezierVertex(215,24.6,185,11.4,164.8,11),e.bezierVertex(147.2,10.7,129.3,10.4,112.2,14.7),e.bezierVertex(95.1,19,78.5,28.5,69.M 6,43.8),e.bezierVertex(57.699,64.199,61.599,90.199,70.199,112.2),e.bezierVertex(78.799,134.2,91.6,154.6,97.199,177.5),e.bezierVertex(102.499,199.2,100.899,222.5,92.799,243.2),e.bezierVertex(83,268,64.6,288.3,48.9,310),e.bezierVertex(33.2,331.7,24.5,337.5,26.599,364.1),e.bezierVertex(28.2,384.1,61.399,404.2,75.7,418.3),e.bezierVertex(90,432.4,73.7,488.2,91.9,496.7),e.bezierVertex(124.2,511.6,159,472.5,194.3,468.1),e.bezierVertex(211.6,465.9,267.4,501.5,283.9,495.9),e.bezierVertex(340.7,476.7,298.599,428.9,355.4,409.M 7),e.bezierVertex(370.799,404.5,454.5,407.6,464.4,394.8),e.bezierVertex(478.599,376.3,474.7,349.3,464.299,328.4),e.bezierVertex(453.9,307.5,438.099,289.5,428.699,268.2),e.bezierVertex(412,230,419,182.6,446.1,150.9),e.bezierVertex(449.7,146.7,453.6,142.7,455.8,137.6),e.bezierVertex(459.4,129.299,457.5,119.6,454.8,111),e.bezierVertex(443.2,73.4,417.3,40.4,383.6,20.299),e.bezierVertex(358.1,5,343.2,-.4,313.5,0),e.bezierVertex(287.5,.4,261.6,25.4,235.2,24.9),e.endShape(),e.pop()}function C(e,t,n,r,i,o){let a,l,s;re(t),M t.fill(0),t.rect(0,0,500,500),ie(t),t.noStroke(),t.fill(dr(n,.5)),1==i?(l=0,s=25,a=map(o,0,25,500,0)):a=0,t.rect(0,a,500,500),e.noStroke(),e.fill(r),e.rect(0,0,500,500),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierM Vertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109M .9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82M .9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),e.fill(n),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,4M 30.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezM ierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8M .8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471M .6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),re(e),e.fill(r),e.beginShape(),e.vertex(184.3,473.2),e.bezierVertex(164,473.2,144.7,462.099,134,444.3),e.bezierVertex(131.7,440.5,129.1,438.5,125,437.1),e.bezierVertex(97.3,428.1,80.5,400.6,85.2,371.8),e.bezierVertex(86.3,365.1,85.8,364.1,79.9,361.2),e.bezierVertex(57.2,349.8,46.2,323.3,54.3,299.7),e.bezierVertex(54.7,298.599,55.1,M 297.7,55.5,296.9),e.bezierVertex(55.6,296.599,55.8,296.4,55.9,296.099),e.vertex(57.9,291.499),e.vertex(62.5,293.599),e.bezierVertex(64.9,294.7,67.3,295.799,69.5,296.9),e.bezierVertex(74.5,299.299,79.1,301.599,83.9,303.099),e.bezierVertex(89.8,304.9,96.5,305.499,102.7,305.9),e.bezierVertex(102.8,305.9,102.9,305.9,103,305.9),e.bezierVertex(106.6,305.9,108.9,302.799,109,299.799),e.bezierVertex(109.1,296.199,106.6,293.4,102.7,292.799),e.bezierVertex(101.3,292.599,99.9,292.4,98.4,292.299),e.bezierVertex(94.3,291.799,90.M 1,291.299,86,289.9),e.bezierVertex(68.9,284,56.5,270.2,52.7,252.799),e.bezierVertex(48.9,235.499,54.5,217.7,67.6,205.299),e.bezierVertex(71.9,201.299,72.7,198.1,70.8,192.399),e.bezierVertex(64.2,172.2,68.8,153.99,84.2,139.599),e.bezierVertex(94.2,130.199,105.5,125.399,117.8,125.399),e.bezierVertex(124.3,125.399,131.1,126.799,137.8,129.599),e.bezierVertex(157,137.399,167.9,152.799,169.4,173.99),e.vertex(169.4,174.399),e.bezierVertex(169.5,175.899,169.6,177.2,169.9,178.299),e.bezierVertex(170.7,181.2,173.2,183.2,176.M 1,183.2),e.bezierVertex(176.299,183.2,176.5,183.2,176.7,183.2),e.bezierVertex(180.1,182.899,182.6,180.299,182.7,177),e.bezierVertex(183.1,162,178.299,148.2,168.399,136.1),e.bezierVertex(158.2,123.5,144.899,115.8,128.799,113.199),e.bezierVertex(123.499,112.299,120.399,109.799,118.899,104.99),e.bezierVertex(113.899,89.699,120.699,72.299,134.899,64.499),e.bezierVertex(139.99,61.699,145.799,60.199,151.7,60.199),e.bezierVertex(162.2,60.199,171.899,64.799,178.1,72.699),e.bezierVertex(179.6,74.6,180.799,76.6,181.9,78.499)M ,e.vertex(182.2,79.099),e.bezierVertex(183.2,80.699,185.2,83.299,188.4,83.299),e.bezierVertex(189.5,83.299,190.6,82.99,191.7,82.399),e.bezierVertex(195.1,80.599,196,76.99,194,72.799),e.bezierVertex(190.1,64.799,184.1,58.499,175.6,53.299),e.bezierVertex(174.6,52.699,173.7,52.099,172.5,51.499),e.vertex(170.5,50.299),e.vertex(163,45.899),e.vertex(170.5,41.599),e.bezierVertex(182,34.99,193.1,30.799,204.4,28.599),e.bezierVertex(208.6,27.799,212.9,27.399,217.2,27.399),e.bezierVertex(217.6,27.399,217.9,27.399,218.3,27.399M ),e.bezierVertex(231.4,27.599,242.7,38.199,243,50.599),e.bezierVertex(243.4,64.899,243.3,78.99,243.2,93.799),e.bezierVertex(243.2,99.799,243.1,105.899,243.1,112.099),e.vertex(243.1,119.199),e.vertex(236.4,116.799),e.bezierVertex(235.7,116.499,235,116.299,234.4,115.99),e.bezierVertex(233.4,115.599,232.6,115.299,232,115.199),e.bezierVertex(230.6,114.899,229.2,114.599,227.8,114.299),e.bezierVertex(223.8,113.499,220.1,112.699,216.4,112.499),e.vertex(216.2,112.499),e.bezierVertex(212.5,112.499,210.7,115.599,210.6,118.59M 9),e.bezierVertex(210.4,122.399,212.7,125.099,216.4,125.399),e.bezierVertex(230.1,126.399,238.9,133.099,242.3,145.199),e.bezierVertex(243.2,148.399,243.2,151.599,243.2,154.499),e.vertex(243.2,155.099),e.bezierVertex(243.2,254.199,243.2,330,243.2,400.599),e.bezierVertex(243.2,401.99,243.2,403.4,243.2,404.9),e.bezierVertex(243.3,411.099,243.3,417.599,242.3,423.9),e.bezierVertex(238.1,449.2,219.6,467.799,194,472.5),e.bezierVertex(190.9,472.9,187.6,473.2,184.3,473.2),e.endShape(),e.beginShape(),e.vertex(315.8,473.1),e.M bezierVertex(309.3,473.1,302.8,472,296.5,469.9),e.bezierVertex(270.4,461,253.8,434.9,257.1,407.9),e.bezierVertex(260,384,273.8,366.8,297,358.3),e.bezierVertex(297.7,358.1,298.3,357.8,299,357.6),e.bezierVertex(299.8,357.3,300.6,357.1,301.2,356.8),e.bezierVertex(304.3,355.4,306,351.8,304.9,348.7),e.bezierVertex(304,345.9,301.7,344.2,299,344.2),e.bezierVertex(298.6,344.2,298.1,344.2,297.6,344.3),e.bezierVertex(288.1,346.3,279,350.9,269.7,358.3),e.bezierVertex(268.9,358.9,268.1,359.6,267.2,360.4),e.vertex(265.5,361.8),M e.vertex(258.5,367.6),e.vertex(257.4,358.6),e.bezierVertex(257.3,358,257.3,357.5,257.2,357.1),e.bezierVertex(257,356,256.9,354.9,256.9,353.7),e.bezierVertex(256.9,334.8,256.9,316,256.9,297.1),e.bezierVertex(256.9,260.3,256.9,222.3,256.8,185),e.bezierVertex(256.8,170.7,268.3,158.8,282.5,158.4),e.bezierVertex(284.8,158.3,286.7,157.6,287.9,156.2),e.bezierVertex(289.099,154.9,289.599,153.2,289.5,151.3),e.bezierVertex(289.3,147.5,286.7,145.1,282.7,145.1),e.bezierVertex(282.5,145.1,282.2,145.1,282,145.1),e.bezierVertex(2M 78.8,145.3,275.5,146.1,272,146.9),e.bezierVertex(270.9,147.2,269.8,147.4,268.6,147.7),e.bezierVertex(267.9,147.9,267,148.2,265.8,148.7),e.bezierVertex(265.1,149,264.4,149.3,263.5,149.6),e.vertex(256.8,152),e.vertex(256.8,114.6),e.bezierVertex(256.8,95,256.8,75.4,256.8,55.9),e.bezierVertex(256.8,38,267.2,27.3,284.6,27.3),e.bezierVertex(285.3,27.3,285.9,27.3,286.6,27.3),e.bezierVertex(299,27.9,318.7,34.5,329.6,41.9),e.vertex(336.1,46.3),e.vertex(324.4,53.3),e.bezierVertex(316.2,58.2,310.2,64.6,306,72.9),e.bezierVerteM x(304.2,76.4,305.1,78.5,306.1,80),e.bezierVertex(307.4,81.9,309.4,83,311.6,83),e.bezierVertex(313.7,83,315.7,81.9,317.1,80.1),e.bezierVertex(317.4,79.7,317.8,79,318.1,78.4),e.bezierVertex(318.4,77.9,318.7,77.3,319,76.8),e.bezierVertex(325.3,66.2,336.3,59.9,348.5,59.9),e.bezierVertex(353.2,59.9,357.8,60.8,362.1,62.7),e.bezierVertex(377.6,69.3,386,86.7,381.7,103.2),e.bezierVertex(380.7,107.1,378.5,111.8,371.1,113.1),e.bezierVertex(342.7,118.1,322.2,139.1,317.8,167.8),e.bezierVertex(317.4,170.3,317.3,173.2,317.4,176.5M ),e.bezierVertex(317.5,180,320.1,182.8,323.5,183),e.bezierVertex(323.6,183,323.8,183,323.9,183),e.bezierVertex(327.1,183,329.8,180.6,330.3,177.2),e.bezierVertex(330.6,175.7,330.7,174,330.9,172.3),e.bezierVertex(331.1,169.8,331.4,167.3,332,164.7),e.bezierVertex(337.3,141.9,357.7,125.4,380.7,125.4),e.bezierVertex(382.5,125.4,384.3,125.5,386.1,125.7),e.bezierVertex(412.8,128.9,432.6,150.9,432,176.9),e.bezierVertex(431.9,182.3,430.9,187.7,429.1,192.7),e.bezierVertex(427.2,197.9,428,201,432.3,205),e.bezierVertex(446.8,2M 18.7,451.8,236,446.6,255),e.bezierVertex(441.4,274,428.3,286.5,408.7,291.3),e.bezierVertex(406.1,291.9,403.6,292.1,401.1,292.3),e.bezierVertex(400,292.4,398.9,292.5,397.9,292.6),e.bezierVertex(393.6,293.1,390.9,295.7,391,299.5),e.bezierVertex(391.1,303.4,394,305.8,398.5,305.8),e.bezierVertex(409.9,305.8,420.8,302.6,431.1,296.4),e.bezierVertex(431.8,296,432.5,295.5,433.2,295.1),e.bezierVertex(433.8,294.7,434.5,294.3,435.2,293.9),e.bezierVertex(436,293.4,436.6,293.2,437.2,293.1),e.bezierVertex(437.4,293,437.7,292.9,4M 38.1,292.8),e.vertex(442.5,291.4),e.vertex(444.2,295.7),e.bezierVertex(450.9,312.4,449.5,328.4,440,343.4),e.bezierVertex(435.3,350.8,428.7,356.7,420.2,361.1),e.bezierVertex(414.3,364.1,413.7,365.2,414.8,371.7),e.bezierVertex(419.5,400.2,403,427.6,375.6,436.9),e.bezierVertex(371,438.5,368.3,440.7,365.8,444.7),e.bezierVertex(355.2,462.5,336.4,473.1,315.8,473.1),e.bezierVertex(315.8,473.1,315.8,473.1,315.8,473.1),e.endShape(),ie(e),e.fill(n),e.beginShape(),e.vertex(120.2,279.9),e.bezierVertex(117.9,279.9,112.4,279.299M ,112.2,273.599),e.bezierVertex(112,267.7,117.4,266.7,119.7,266.599),e.bezierVertex(133.1,265.799,143.1,259.499,149.3,247.899),e.bezierVertex(149.6,247.299,150.1,246.399,150.3,245.399),e.bezierVertex(150.6,244.299,150.5,243.299,150.5,242.7),e.bezierVertex(150.5,242.6,150.5,242.5,150.5,242.299),e.vertex(150.3,238.799),e.vertex(141.1,235.99),e.bezierVertex(114.6,227.799,95.6,202.499,95.9,175.799),e.bezierVertex(95.9,173.99,96.4,168.199,102.2,168.199),e.bezierVertex(102.6,168.199,103,168.199,103.4,168.299),e.bezierVertM ex(104.8,168.499,108.2,168.899,109.2,175.599),e.bezierVertex(109.3,176.599,109.5,177.599,109.6,178.499),e.bezierVertex(110.4,184.199,111.3,189.99,113.7,195.499),e.bezierVertex(121.9,213.99,139.5,225.499,159.7,225.499),e.bezierVertex(172.1,225.499,184.1,220.899,193.5,212.599),e.bezierVertex(194,212.199,194.4,211.799,194.8,211.399),e.bezierVertex(195.1,211.099,195.5,210.799,195.8,210.399),e.bezierVertex(197.4,208.99,199.2,208.2,200.9,208.2),e.bezierVertex(202.5,208.2,204,208.899,205.3,210.1),e.bezierVertex(208,212.9,M 207.9,216.9,205,219.9),e.bezierVertex(196.5,228.6,186.3,234.3,174.7,236.8),e.bezierVertex(168.799,238.1,165.6,241,163.899,246.7),e.bezierVertex(158.3,265.9,139.9,279.7,120.2,279.9),e.vertex(120.2,279.9),e.endShape(),e.beginShape(),e.vertex(187.2,427.5),e.bezierVertex(183.799,427.5,181.299,425.3,180.799,422),e.bezierVertex(180.6,420.8,180.499,419.5,180.399,418.1),e.bezierVertex(180.299,417,180.2,415.8,180.099,414.7),e.bezierVertex(177.199,390.5,156.699,371.3,132.399,370.2),e.bezierVertex(131.99,370.2,131.499,370.2,1M 31.099,370.2),e.bezierVertex(130.699,370.2,130.299,370.2,129.799,370.2),e.bezierVertex(125.99,369.9,123.199,367.2,123.099,363.6),e.bezierVertex(122.99,360.2,125.799,357.3,129.599,356.9),e.bezierVertex(130.499,356.8,131.499,356.8,132.599,356.7),e.bezierVertex(133.199,356.7,133.799,356.7,134.399,356.6),e.vertex(138.299,356.4),e.vertex(139.1,352.6),e.bezierVertex(139.5,350.7,139.799,348.9,140.2,347),e.bezierVertex(140.899,343.4,141.5,340,142.399,336.8),e.bezierVertex(150.099,310.7,174.399,292,201.399,291.3),e.vertex(2M 01.599,291.3),e.bezierVertex(203.699,291.3,206.299,292,208.299,293.2),e.bezierVertex(210.499,294.5,210.699,297.5,209.99,299.8),e.bezierVertex(209.499,301.5,208.199,303.9,203.299,304.7),e.bezierVertex(202.199,304.9,200.99,305,199.799,305.2),e.bezierVertex(194.499,305.9,188.99,306.599,183.799,308.9),e.bezierVertex(165.499,316.799,155.199,331.299,152.99,352),e.bezierVertex(152.399,357.8,154.499,361.7,159.699,364.5),e.bezierVertex(178.199,374.4,189.399,390,193.099,410.9),e.bezierVertex(193.699,414.299,193.899,418,193.5M 99,422),e.bezierVertex(193.399,425.2,190.899,427.5,187.399,427.5),e.vertex(187.2,427.5),e.endShape(),e.beginShape(),e.vertex(364.3,281.1),e.bezierVertex(346.3,280.6,332.9,272.8,323.5,257),e.bezierVertex(321.6,253.9,320.4,250.2,319.2,246.7),e.bezierVertex(317.7,242.2,315,239.799,310.5,238.799),e.bezierVertex(298.5,236.299,288,230.7,279.4,222.1),e.bezierVertex(276.7,219.4,274.9,215.299,278,211.9),e.bezierVertex(279.4,210.3,281,209.6,282.6,209.6),e.bezierVertex(284.4,209.6,286.4,210.6,288.3,212.5),e.bezierVertex(297.8M ,221.8,310.4,226.9,323.9,226.9),e.bezierVertex(340.2,226.9,355.1,219.3,364.8,206.2),e.bezierVertex(371,197.8,374.2,188.5,374.5,178.5),e.vertex(374.5,177.9),e.bezierVertex(374.5,177,374.5,176.1,374.7,175.4),e.bezierVertex(375.3,171.8,377.9,169.5,381.3,169.5),e.bezierVertex(381.4,169.5,381.5,169.5,381.7,169.5),e.bezierVertex(385.4,169.7,388,172.4,388,176.1),e.bezierVertex(388.1,190.7,383.4,204,374.2,215.8),e.bezierVertex(365.8,226.5,354.7,233.9,341.2,237.9),e.bezierVertex(340,238.3,338.7,238.6,337.3,239.1),e.bezierVeM rtex(335.9,239.6,335.1,240.4,334.7,240.9),e.bezierVertex(334.599,241,334.5,241.1,334.4,241.2),e.vertex(331.799,243.6),e.vertex(333.199,246.8),e.bezierVertex(338.199,258,346.799,264.9,358.699,267.3),e.bezierVertex(360.199,267.6,361.599,267.7,362.99,267.9),e.bezierVertex(363.599,268,364.299,268,364.899,268.1),e.bezierVertex(369.099,268.6,371.799,271.4,371.499,275),e.bezierVertex(371.199,278.6,368.299,281.2,364.399,281.2),e.vertex(364.3,281.1),e.endShape(),e.beginShape(),e.vertex(323.9,437),e.bezierVertex(323.7,437,32M 3.5,437,323.299,437),e.bezierVertex(319.599,436.7,317.299,434.1,317.4,430.2),e.bezierVertex(317.9,406.099,328.299,388,349.5,375),e.bezierVertex(350.7,374.2,352,373.5,353.4,372.8),e.bezierVertex(354.099,372.4,354.7,372.1,355.299,371.7),e.vertex(357.499,370.5),e.vertex(357.799,368),e.bezierVertex(360.4,346.6,345.199,323.7,323.9,317),e.bezierVertex(319.099,315.5,314.099,314.9,309.299,314.4),e.vertex(308.199,314.299),e.bezierVertex(305.99,314.099,300.799,312.9,300.899,307.299),e.bezierVertex(300.99,303.499,303.899,300.M 9,308.099,300.9),e.vertex(308.299,300.9),e.bezierVertex(327.099,301.299,343.099,308.7,355.699,322.9),e.bezierVertex(364.299,332.5,369.399,344.099,370.99,357.299),e.bezierVertex(371.099,358.4,371.299,359.4,371.499,360.499),e.bezierVertex(371.599,360.99,371.699,361.499,371.799,361.99),e.vertex(372.499,365.899),e.vertex(377.899,366.199),e.bezierVertex(378.799,366.299,379.699,366.299,380.599,366.399),e.bezierVertex(385.099,366.699,387.899,369.399,387.799,373.299),e.bezierVertex(387.699,377.099,384.99,379.599,380.799,37M 9.799),e.bezierVertex(369.799,380.199,359.99,383.299,351.899,389.299),e.bezierVertex(338.799,398.799,331.699,411.699,330.699,427.499),e.vertex(330.699,428.299),e.bezierVertex(330.599,429.199,330.599,430.099,330.499,430.799),e.bezierVertex(330,434.7,327.5,437,323.9,437),e.endShape()}function T(e){return e[0].map(((t,n)=>e.map((e=>e[n]))))}function A(e){return e.map((e=>Array.isArray(e)?A(e):e))}function D(e,t){return floor(random(e,t))}function k(e){let t=0;for(const n of e)t+=n[1];let n=random(t),r=0;for(const t ofM e)if(r+=t[1],n<r)return t[0];return null}function L(e){for(let t=1;t<e.length;++t){let n=D(0,t),r=e[t];e[t]=e[n],e[n]=r}}function P(e){return null==e||""===e}function O(e){return new Promise((t=>setTimeout(t,e)))}function F(e,t,n){let r=0;for(let i=1;i<=1e3;++i)for(let o=1;o<=1e3;++o)if(e*o%(t*i)==0){let e=1*i/o;abs(e-n)<abs(r-n)&&(r=e)}return r}function N(){let e=60*(new Date).getTimezoneOffset()*1e3;return new Date(Date.now()-e).toISOString().slice(0,-1)}function B(e,t,n){let r;if(push(),textSize(e),textWidth(t)M <=n)r=t;else for(let e=0;e<t.length;++e){const i=t.slice(0,e+1)+"...";if(textWidth(i)>n){r=i;break}}return pop(),r}function Y(e){var t=e%10,n=e%100;return 1==t&&11!=n?e+"st":2==t&&12!=n?e+"nd":3==t&&13!=n?e+"rd":e+"th"}class G{constructor(e,t,n){this.n=t,this.m=n,this.mat=[];let r=0;for(let t=0;t<this.n;++t){this.mat.push([]);for(let n=0;n<this.m;++n)this.mat[t].push(r<e.length?e[r]:0),r+=1}return this}copy(){return new G(this.mat.flat(),this.n,this.m)}}class H{static __linear=e=>e;static __relu=e=>Math.max(e,0);stM atic __leaky_relu=e=>e>0?e:.2*e;static __sigmoid=e=>1/(1+Math.exp(-e));static __tanh=e=>Math.tanh(e);static __apply_unary_op(e,t){const n=e.copy();for(let e=0;e<n.n;++e)for(let r=0;r<n.m;++r)n.mat[e][r]=t(n.mat[e][r]);return n}static linear=e=>H.__apply_unary_op(e,H.__linear);static relu=e=>H.__apply_unary_op(e,H.__relu);static leaky_relu=e=>H.__apply_unary_op(e,H.__leaky_relu);static sigmoid=e=>H.__apply_unary_op(e,H.__sigmoid);static tanh=e=>H.__apply_unary_op(e,H.__tanh);static __add=(e,t)=>e+t;static __mul=(e,tM )=>e*t;static __apply_binary_op=(e,t,n)=>{"object"!=typeof t&&(t=new G([t],1,1));const r=e.copy();for(let e=0;e<r.n;++e)for(let i=0;i<r.m;++i)r.mat[e][i]=n(r.mat[e][i],t.mat[e%t.n][i%t.m]);return r};static mul=(e,t)=>H.__apply_binary_op(e,t,H.__mul);static add=(e,t)=>H.__apply_binary_op(e,t,H.__add);static matMul(e,t){const n=new G([],e.n,t.m);for(let r=0;r<n.n;++r)for(let i=0;i<n.m;++i)for(let o=0;o<e.m;++o)n.mat[r][i]+=e.mat[r][o]*t.mat[o][i];return n}static softmax(e){const t=H.__apply_unary_op(e,(e=>Math.exp(e)M )),n=t.mat.flat().reduce(((e,t)=>e+t));for(let r=0;r<e.n;++r)for(let i=0;i<e.m;++i)t.mat[r][i]/=n;return t}}class ${constructor(e,t){this.scale=e,this.offset=t}forward(e){return H.add(H.mul(e,this.scale),this.offset)}}class X{constructor(){}forward(e){return e.map((e=>e.flat()))}}class W{constructor(e,t,n,r){this.out_dim=e,this.activation=t,this.w=n,this.b=r}forward(e){const t=H.add(H.matMul(e,this.w),this.b);return null==this.activation?t:this.activation(t)}}class U{constructor(e,t,n){this.preprocessLayers=e,this.M hiddenLayers=t,this.outputLayer=n,this.totalNeurons=this.hiddenLayers.map((e=>e.out_dim)),this.currentOrders=[],this.currentIteration=null}updateNeurons(e,t){if(t!=this.currentIteration){this.currentOrders=[];for(let e=0;e<this.totalNeurons.length;++e){randomSeed(100*(t+1)+e);const n=[];for(let t=0;t<this.totalNeurons[e];++t)n.push(t);L(n),this.currentOrders.push(n)}this.currentIteration=t}const n=A(this.totalNeurons),r=n.reduce(((e,t)=>e+t))*(1-e);for(let e=0;e<r;++e){const t=n.map(((e,t)=>(e-1)/this.totalNeurons[M t]));n[t.map(((e,t)=>[e,t])).reduce(((e,t)=>t[0]>e[0]?t:e))[1]]-=Math.min(r-e,1)}this.neuronsLife=[];for(let e=0;e<n.length;++e){const t=this.currentOrders[e],r=Array(this.totalNeurons[e]).fill(0);for(let i=0;i<n[e];++i)r[t[i]]=Math.min(n[e]-i,1);this.neuronsLife.push(r)}}getTotalNeurons(){return A(this.totalNeurons)}getNeuronsLife(){return A(this.neuronsLife)}forward(e){for(const t of this.preprocessLayers)e=t.forward(e);for(const[t,n]of this.hiddenLayers.entries()){e=n.forward(e);const r=new G(this.neuronsLife[t]M ,1,e.m);e=H.mul(e,r)}return e=this.outputLayer.forward(e),H.softmax(e)}}function q(e){switch(e){case"relu":return H.relu;case"sigmoid":return H.sigmoid;case"tanh":return H.tanh;case"leaky_relu":return H.leaky_relu;default:return H.linear}}function j(e,t){const n=[],r=[],i=Z(t);let o=null,a=0,l=[];for(const t of e.config.layers)if("InputLayer"==t.class_name)o=t.config.batch_input_shape.slice(1),l=o;else if("Rescaling"==t.class_name)n.push(new $(t.config.scale,t.config.offset));else if("Flatten"==t.class_name)o=[o.reM duce(((e,t)=>e*t))];else if("Dense"==t.class_name){const e=[t.config.units],n=o[0]*e[0],l=e[0],s=i.subarray(a,a+n);a+=n;const h=i.subarray(a,a+l);a+=l;const c=new G(s,o[0],e[0]),u=new G(h,1,e[0]),f=q(t.config.activation);r.push(new W(e[0],f,c,u)),o=e}const s=r.pop();return{model:new U(n,r,s),inputDim:l}}function Z(e){const t=window.atob(e),n=t.length/Float32Array.BYTES_PER_ELEMENT,r=new DataView(new ArrayBuffer(Float32Array.BYTES_PER_ELEMENT)),i=new Float32Array(n);let o=0;for(let e=0;e<n;e++){o=4*e;for(let e=0;e<4M ;++e)r.setUint8(e,t.charCodeAt(o+e));i[e]=r.getFloat32(0,!0)}return i}class K{constructor(e){this.elt=e,this._events={},this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight}position(){if(0===arguments.length)return{x:this.elt.offsetLeft,y:this.elt.offsetTop};var e="absolute";return"static"!==arguments[2]&&"fixed"!==arguments[2]&&"relative"!==arguments[2]&&"sticky"!==arguments[2]&&"initial"!==arguments[2]&&"inherit"!==arguments[2]||(e=arguments[2]),this.elt.style.position=e,this.elt.style.left=argumentsM [0]+"px",this.elt.style.top=arguments[1]+"px",this.x=arguments[0],this.y=arguments[1],this}show(){return this.elt.style.display="block",this}hide(){return this.elt.style.display="none",this}size(e,t){if(0===arguments.length)return{width:this.elt.offsetWidth,height:this.elt.offsetHeight};var n=e,r=t;if(n!==te||r!==te){if(n===te?n=t*this.width/this.height:r===te&&(r=e*this.height/this.width),this.elt instanceof HTMLCanvasElement){var i,o={},a=this.elt.getContext("2d");for(i in a)o[i]=a[i];for(i in this.elt.setAttribuM te("width",n*this._pInst._pixelDensity),this.elt.setAttribute("height",r*this._pInst._pixelDensity),this.elt.style.width=n+"px",this.elt.style.height=r+"px",this._pInst.scale(this._pInst._pixelDensity,this._pInst._pixelDensity),o)this.elt.getContext("2d")[i]=o[i]}else this.elt.style.width=n+"px",this.elt.style.height=r+"px",this.elt.width=n,this.elt.height=r;this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight,this._pInst&&this._pInst._curElement&&this._pInst._curElement.elt===this.elt&&(this._pInst._sM etProperty("width",this.elt.offsetWidth),this._pInst._setProperty("height",this.elt.offsetHeight))}return this}style(e,t){if(t instanceof Color&&(t="rgba("+t.levels[0]+","+t.levels[1]+","+t.levels[2]+","+t.levels[3]/255+")"),void 0===t){if(-1===e.indexOf(":"))return window.getComputedStyle(this.elt).getPropertyValue(e);for(var n=e.split(";"),r=0;r<n.length;r++){var i=n[r].split(":");i[0]&&i[1]&&(this.elt.style[i[0].trim()]=i[1].trim())}}else if(this.elt.style[e]=t,"width"===e||"height"===e||"left"===e||"top"===e){vM ar o=window.getComputedStyle(this.elt).getPropertyValue(e).replace(/[^\d.]/g,"");this[e]=Math.round(parseFloat(o,10))}return this}value(){return arguments.length>0?(this.elt.value=arguments[0],this):"range"===this.elt.type?parseFloat(this.elt.value):this.elt.value}mouseClicked(e){return this._adjustListener("click",e,this),this}isFocused(){return document.activeElement===this.elt}_adjustListener(e,t,n){return!1===t?this._detachListener(e,n):this._attachListener(e,t,n),this}_attachListener(e,t,n){n._events[e]&&this.M _detachListener(e,n);var r=t.bind(n);n.elt.addEventListener(e,r,!1),n._events[e]=r}_detachListener(e,t){var n=t._events[e];t.elt.removeEventListener(e,n,!1),t._events[e]=null}}function J(e,t){var n=document.createElement("button");return n.innerHTML=e,t&&(n.value=t),ee(n)}function Q(e){var t=arguments.length>1&&void 0!==arguments[1]&&arguments[1],n=function(t){var n=!0,r=!1,i=void 0;try{for(var o,a=t.target.files[Symbol.iterator]();!(n=(o=a.next()).done);n=!0){var l=o.value;File._load(l,e)}}catch(e){r=!0,i=e}finallM y{try{n||null==a.return||a.return()}finally{if(r)throw i}}};if(window.File&&window.FileReader&&window.FileList&&window.Blob){var r=document.createElement("input");return r.setAttribute("type","file"),t&&r.setAttribute("multiple",!0),r.addEventListener("change",n,!1),ee(r)}}function ee(e){return document.body.appendChild(e),new K(e)}createImg=function(){var e,t=document.createElement("img"),n=arguments;return n.length>1&&"string"==typeof n[1]&&(t.alt=n[1]),n.length>2&&"string"==typeof n[2]&&(t.crossOrigin=n[2]),t.srM c=n[0],e=ee(t,this),t.addEventListener("load",(function(){e.width=t.offsetWidth||t.width,e.height=t.offsetHeight||t.height;var r=n[n.length-1];"function"==typeof r&&r(e)})),e},createInput=function(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:"",t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:"text",n=document.createElement("input");return n.setAttribute("value",e),n.setAttribute("type",t),ee(n,this)};const te="auto";function ne(e){re(e);const t=e._rectMode;e.rectMode(CORNER),e.rect(0,0,e.M width,e.height),e.rectMode(t),ie(e)}function re(e){e.push(),e.fill(255,255,255,255),e.blendMode(REMOVE)}function ie(e){e.blendMode(BLEND),e.pop()}File=function(e,t){this.file=e,this._pInst=t;var n=e.type.split("/");this.type=n[0],this.subtype=n[1],this.name=e.name,this.size=e.size,this.data=void 0},File._createLoader=function(e,t){var n=new FileReader;return n.onload=function(n){var r=new File(e);if("application/json"===r.file.type)r.data=JSON.parse(n.target.result);else if("text/xml"===r.file.type){var i=(new DOMPM arser).parseFromString(n.target.result,"text/xml");r.data=new XML(i.documentElement)}else r.data=n.target.result;t(r)},n},File._load=function(e,t){if(/^text\//.test(e.type)||"application/json"===e.type)File._createLoader(e,t).readAsText(e);else if(/^(video|audio)\//.test(e.type)){var n=new File(e);n.data=URL.createObjectURL(e),t(n)}else File._createLoader(e,t).readAsDataURL(e)},XML=function(e){if(e)this.DOM=e;else{var t=document.implementation.createDocument(null,"doc");this.DOM=t.createElement("root")}},document.aM ddEventListener("DOMContentLoaded",(function(){addEventListener("mousemove",(e=>{window.mouseX=e.pageX,window.mouseY=e.pageY}))})),new e("global");const oe="35";let ae,le,se,he,ce,ue,fe,de,xe,ge,pe,me,be,ye,we,ve,ze,Ve,_e,Me,Ee,Se,Re,Ie,Ce,Te,Ae,De,ke,Le,Pe,Oe,Fe,Ne,Be,Ye,Ge,He,$e,Xe,We,Ue,qe,je,Ze,Ke,Je,Qe,et,tt,nt,rt,it,ot,at,lt,st,ht,ct,ut,ft,dt,xt,gt,pt,mt,bt,yt,wt,vt,zt,Vt,_t,Mt,Et,St,Rt,It,Ct,Tt,At=!1,Dt=!1,kt=!0,Lt=!1,Pt=!1;const Ot=[" ","Growing","Stable","Decaying","Dead","Rebirth"];let Ft,Nt,Bt,Yt,Gt,Ht,$M t,Xt,Wt,Ut,qt,jt,Zt,Kt,Jt,Qt,en,tn,nn,rn,on,an,ln,sn,hn=0,cn=0,un=0,fn=!1,dn=!0,xn=!0,gn=null,pn=null,mn=null,bn=!1,yn=!1,wn=null,vn=null,zn=!1;async function setup(){let e=windowWidth,t=windowHeight;createCanvas(e,t),et=createGraphics(e,t),Xe=createGraphics(e,t),$e=createGraphics(e,t),We=createGraphics(e,t),Ue=createGraphics(e,t),qe=createGraphics(e,t),Qe=createGraphics(e,t),je=createGraphics(e,t),Ze=createGraphics(e,t),Ke=createGraphics(e,t),Je=createGraphics(e,t),tt=createGraphics(500,500),nt=createGraphics(500,M 500),rt=createGraphics(500,500),_n(),Mn(),Sn(),await En(),Gn(),Rn(),bn=!0}function _n(){Et=parseInt(oe),randomSeed(Et),noiseSeed(Et)}function Mn(){Wt=Ir(p.training_traits),Cr(Wt)}async function En(){let e;Jt=r(),Qt=o(),[Xt,e]=await Promise.all([s(Jt),h(Qt)]),Ut=new V(Wt.visual,e.layers_config,e.weight_b64),Ut.updateAge(new Date),_n(),Wt.training=e.training_traits,Ht=e.model_name,$t=e.classes_name}function Sn(){le=min(width,height)/1024,ut=Rr.findIndex((e=>e[0]===Wt.visual.colorPalette)),ft=[["#ffffff","#231f20","#2M 31f20"],["#231f20","#ffffff","#ffffff"],["#104da8","#ffffff","#ffffff"],["#722F1F","#FCE1B2","#FCE1B2"],["#e88120","#f9f2e5","#f9f2e5"],["#f6b941","#2E2E2E","#2E2E2E"],["#45daaa","#012221","#012221"],["#F1F1F1","#328DFE","#328DFE"],["#111822","#D3EB8D","#D3EB8D"],["#713FF9","#D6D5E6","#D6D5E6"],["#FBDA9D","#795106","#795106"],["#8f5b62","#ead0d0","#ead0d0"],["#eae4cb","#508cac","#508cac"],["#ffc6cc","#cc313d","#cc313d"],["#60A900","#E0FE00","#E0FE00"],["#507DBE","#D0D1D3","#D0D1D3"],["#305848","#E8F2EE","#E8F2EE"],M ["#2a2634","#5b6988","#cb78a2","#5b6988"],["#590e29","#fd5e53","#fd5e53","#ffe373"],["#0a141d","#57d4e4","#328195","#2A9ECF","#0ab6a8","#57d4e4"],["#3a2d28","#d5c2ac","#df6338","#3d9895","#d5c2ac"],["#030706","#77c4d9","#77c4d9","#77c4d9","#ffffff","#ffffff","#e72020","#e72020"],["#3a4664","#92f5ff","#f9ff94","#eaa0a2","#55dde0"],["#fbfaff","#f04bb1","#f04bb1","#fac373","#82cef0","#8b31ce"],["#000000","#ffffff","#ff0002","#f26522","#fdff00","#00ff03","#01fffe","#0000ff","#ff00ff"]];for(let e=0;e<ft.length;++e)for(lM et t=0;t<ft[e].length;++t)ft[e][t]=cr(ft[e][t]);pt=[],ct=ft[ut][0],st=ft[ut][1]}function Rn(){gn=document.querySelector("#upload"),pn=document.querySelector("#inputUpload"),gn.addEventListener("dblclick",(()=>{if(!Lt&&!yn)if(In(Ie)&&cn==Ve-1)pn.click();else{if(4!=Pe&&5!=Pe&&(In(Ie)||cn!=Ve-1))return;fn=!0,dn=!0,Bt=0,un=0}})),pn.addEventListener("click",(()=>{pn.value=null,gn.style.display="block"})),pn.addEventListener("change",(()=>{const[e]=pn.files;e?(se=null,gn.style.display="none",Tn(URL.createObjectURL(e)),mnM =e):gn.style.display="block"}))}function In(e){for(let t=0;t<e.length;++t){let n=0;for(let r=0;r<e[t].length;++r)e[t][r]>0&&++n;if(0==n)return!1}return!0}function Cn(){null!=se&&(un=0,Pt=!0,he=0,ue=0,drewLineAnim=!0,ce=(ae/2+we/2)/le,loadImage(se.elt.src,(e=>{const[t,n,r]=Gt,i=createGraphics(t,n);i.image(e,0,0,t,n),i.loadPixels();const o=i.pixels.filter(((e,t)=>t%4!=3)),a=Ut.classifyImage(o);Zt=T([a,$t.map((e=>e.toUpperCase()))]).sort(((e,t)=>e[0]>t[0]?-1:1))})))}function Tn(e){se=createImg(e,""),se.hide(),Cn()}funM ction An(){zn||(ce+=(width-ae-we)/tn/le),re(Xe),Xe.rect(ce*le,0,width,height),ie(Xe),un>=ge&&1==kt&&(kt=!1,un-=ge),kt&&(re($e),$e.strokeWeight(2*Fe),Jn(he,ze,ct,ct,$e),ie($e)),un>=ge&&0==kt&&(kt=!0,un-=ge,he+=1,he==en&&(++ue,he=0,ce=(ae/2+we/2)/le,1==ue&&(Pt=!1,Dn(),ye=millis())))}function Dn(){At=!0,pe=!1,me=!1,tryButton=br("Try Again",width/2-225*le,height/2+265*le,290*le,40*le,kn),closeResultButton=br("Close",width/2+75*le,height/2+265*le,150*le,40*le,Ln)}function kn(){At=!1,tryButton.hide(),closeResultButton.hiM de(),pn.click()}function Ln(){Yt=!0,At=!1,Gn(),tryButton.hide(),closeResultButton.hide(),gn.style.display="block",se=null}function keyTyped(){bn&&!1===yn&&!1===yr()&&("i"!==key&&"I"!==key||(Dt=!Dt),"b"!==key&&"B"!==key||(xn=!xn),"s"!==key&&"S"!==key||!1!==Lt||saveCanvasAtCurrentTime(),"k"!==key&&"K"!==key||!1!==Lt||save4KCanvasAtCurrentTime(),"u"!==key&&"U"!==key||!1!==Lt||!1!==At||!1!==fn||!1!==Pt||On())}function On(){Lt=!0,wn=null,vn=null,submitButton=br("Submit",width/2-155*le,height/2+115*le,150*le,40*le,Fn),clM oseSettingButton=br("Close",width/2+5*le,height/2+115*le,150*le,40*le,Yn),vt=createInput(),vt.position(width/2-252.5*le,height/2-40*le),vt.size(500*le,25*le),vt.style("font-size","15px"),vt.value(Jt||""),zt=createInput(),zt.position(width/2-252.2*le,height/2+35*le),zt.size(500*le,25*le),zt.style("font-size","15px"),zt.value(Qt||"")}function Fn(){Vt=vt.value(),_t=zt.value(),submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide(),Lt=!1,yn=!0,Nn()}async function Nn(){[wn,vn,_]=await Promise.all([c(Vt),u(_t),M O(1e3)]),yn=!1,wn&&vn?(n(Vt),i(_t),window.location.reload()):(Lt=!0,submitButton.show(),closeSettingButton.show(),vt.show(),zt.show())}function Bn(){Je.textFont("Trebuchet MS"),Je.noStroke(),pr(Je,600*le,200*le),Je.strokeWeight(1*le),Je.stroke(xt),Je.fill(xt),Je.textSize(50*le),Je.text("update()",width/2,height/2+2.5*le)}function Yn(){wn=null,vn=null,Lt=!1,submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide()}function Gn(){_n(),nn=Date.now(),pe=!1,me=!1,St=Wt.training.structure_gen,Rt=Wt.visual.birthYeaM r,It=Wt.visual.lifeCycle,Ct=Wt.training.epoch_num,Tt=Wt.training.activation_func,Ft=Mr.findIndex((e=>e[0]==Wt.visual.hardwareAcceleration))+1,1==Ft?(Nt=30,fe=40):2==Ft?(Nt=15,fe=20):(Nt=2,fe=10);const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTM imestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),ae=100*le,ht=50*le,Oe=Sr.findIndex((e=>e[0]==Wt.visual.nodeShape))+1,dt=Er.findIndex((e=>e[0]==Wt.visual.nodeFill))+1,lt=_r.findIndex((e=>e[0]==Wt.visual.pattern))+1,de=Math.tanh(Math.log10(Xt.avgfeerate)),de=map(de,0,1,.2,.8),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.puM sh(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[M e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]M }Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,at=.7,pt=[],xt=ft[ut][2],gt=ft[ut][ft[ut].length-1];for(let e=3;e<ft[ut].length-1;e++)pt.push(ft[ut][e]);mt=sr(xt,gt,pt,width),bt=[],wt=[],yt=width/(Ve-1);for(let e=0;e<Ve;e++)bt.push(hr(mt,yt*e/width)),wt.push(hr(mt,yt*e/width));wt.unshift(bt[0]),wt.push(bt[bt.length-1]),hn=0,cn=0,un=0,Yt=!0;const n={xLeft:ae/8,xRight:width-ae/8,yTop:ae/8,yBottom:height-ae/8},r=Ce.map((e=>e.length));jt=new R(bt,r,n,Oe,le)}function Hn(e,t){let n=Ce[e].length;retuM rn[e*we+we/2+ae/2,height/2-(n-1)/2*ve+t*ve]}function $n(e,t){le=min(e,t)/1024,ae=100*le,ht=50*le,we=(e-ae)/Ve,ve=(t-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}xe=floor(De.length*de),Le=[],ke=[],ge=floor(map(de,.2,.8,15,2));for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*lM e,mt=sr(xt,gt,pt,e),bt=[],wt=[],yt=e/(Ve-1);for(let t=0;t<Ve;t++)bt.push(hr(mt,yt*t/e)),wt.push(hr(mt,yt*t/e));wt.unshift(bt[0]),wt.push(bt[bt.length-1])}function Xn(){const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),wM indow.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te)M {let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){conM st[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le}function Wn(){jt.update();const e=4==Pe?0:Kt;jt.draw(Qe,ct,dt,e,le)}function Un(){if(!bn)return ar(),void et.image(je,0,0);if(4==Pe||5==Pe)return Wn(),void et.image(Qe,0,0);un>=Nt&&hn<M Ve&&(hn++,un=0);for(let e=0;e<hn;e++)1==dt?it=ot=bt[e]:(it=ct,ot=bt[e]),Kn(e,it,ot,$e);un>=Nt&&cn<Ve-1&&(cn++,un=0);for(let e=0;e<cn;e++)Zn(e)}function qn(){et.background(ct),Ue.background(255),Ue.rectMode(CENTER),ne(Ue),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),Ue.stroke(st),Ue.strokeWeight(8*le),Ue.fill(ct),Qe.background(255),Qe.rectMode(CENTER),ne(Qe),Qe.strokeWeight(le),qe.background(255),qe.rectMode(CENTER),ne(qe),qe.textAlign(LEFT),$e.background(255),$e.rectMode(CENTER),ne($e),Xe.background(255),ne(Xe),XM e.strokeWeight(Ne),We.background(255),We.rectMode(CENTER),ne(We),We.fill(st),We.stroke(st),We.strokeWeight(.1*le),er(lt),We.noStroke(),xn&&(We.rect(ae/16,height/2,ae/8,height),We.rect(width-ae/16,height/2,ae/8,height),We.rect(width/2,ae/16,width,ae/8),We.rect(width/2,height-ae/16,width,ae/8)),Ze.background(255),Ze.rectMode(CENTER),ne(Ze),Ze.textAlign(CENTER,CENTER),Ze.textStyle(BOLD),Ze.stroke(st),Ze.strokeWeight(8*le),Ze.fill(ct),je.background(255),je.rectMode(CENTER),ne(je),je.textAlign(CENTER,CENTER),je.textStylM e(BOLD),Ke.background(255),Ke.rectMode(CENTER),ne(Ke),Ke.textAlign(CENTER,CENTER),Ke.textStyle(BOLD),Ke.stroke(st),Ke.strokeWeight(8*le),Ke.fill(ct),Je.background(255),Je.rectMode(CENTER),ne(Je),Je.textAlign(CENTER,CENTER),Je.textStyle(BOLD),Je.stroke(st),Je.strokeWeight(8*le),Je.fill(ct),Un(),et.image(We,0,0),Pt&&An(),et.image(Xe,0,0),et.image($e,0,0),At&&(tr(),et.image(Ue,0,0)),fn&&(lr(),et.image(Ze,0,0)),Lt&&(or(),et.image(Ke,0,0)),Dt&&(ir(),et.image(qe,0,0)),yn&&(Bn(),et.image(Je,0,0))}function draw(){const e=DM ate.now();bn&&(Ut.updateAge(new Date(e)),Xn()),qn(),image(et,0,0),zn||un++}function Zn(e){let t,n=Ce[e].length,r=Ce[e+1].length;for(let i=0;i<n;i++){const[n,o]=Hn(e,i);for(let a=0;a<r;a++){const[r,l]=Hn(e+1,a);t=map(min(Ce[e][i],Ce[e+1][a]),0,1,0,.5),ur(n,o,r,l,bt[e],bt[e+1],Xe,t)}}}function Kn(e,t,n,r){let i,o,a,l=Ce[e].length;for(let s=0;s<l;s++){const[l,h]=Hn(e,s);i=Ce[e][s],a=map(Be,1/30,1,3,10),o=map(Ce[e][s],0,1,2*a,0)*le,o<1.5*le&&(o=0),Qn(l,h,ze,Oe,t,n,o,i,r)}}function Jn(e,t,n,r,i){for(let o=0;o<Le[e].lengM th;o++)Qn(Le[e][o][0],Le[e][o][1],t,Oe,n,r,0,1,i)}function Qn(e,t,n,r,i,o,a,l,s){s.stroke(dr(o,map(l,0,1,.25,1))),s.fill(dr(i,map(l,0,1,.15,1))),s.strokeWeight(Fe),fr([a],s),3==dt&&s.fill(dr(i,0)),1==r?s.ellipse(e,t,n):2==r?s.rect(e,t,7*n/8,7*n/8):3==r&&(s.beginShape(),s.vertex(e-4*n/7,t),s.vertex(e,t-4*n/7),s.vertex(e+4*n/7,t),s.vertex(e,t+4*n/7),s.endShape(CLOSE))}function er(e){if(1==e);else if(2==e){We.strokeWeight(1*le);for(let e=ht/4;e<width+ht/4;e+=ht)for(let t=ht/4;t<height+ht/4;t+=ht)We.point(e,t)}else if(M 3==e){ht=25*le;for(let e=ht/2;e<height+ht/2;e+=ht)We.line(0,e,width,e);for(let e=ht/2;e<width+ht/2;e+=ht)We.line(e,0,e,height)}}function tr(){Ue.textFont("Trebuchet MS"),Ue.textAlign(LEFT,CENTER),Ue.noStroke(),pr(Ue,800*le,500*le),Ue.noStroke(),Ue.fill(dr(st,.75)),Ue.rect(width/2,height/2-100*le,800*le,300*le,25*le,25*le,0,0),Ue.fill(st),Ue.rect(width/2-250*le,height/2-100*le,225*le,225*le),Ue.image(se.elt,width/2-357.5*le,height/2-207.5*le,215*le,215*le);let e=100*Zt[0][0];Ue.fill(ct),Ue.textSize(25*le),Ue.textStyM le(NORMAL),1==me&&(e>=0&&e<20?Ue.text("I have a feeling this image belongs to",width/2-100*le,height/2-170*le):e>=20&&e<40?Ue.text("I have a hunch this image belongs to",width/2-100*le,height/2-170*le):e>=40&&e<60?Ue.text("I think this image belongs to",width/2-100*le,height/2-170*le):e>=60&&e<80?Ue.text("I'm almost certain this image belongs to",width/2-100*le,height/2-170*le):Ue.text("I'm positive this image belongs to",width/2-100*le,height/2-170*le));let t=e.toFixed(2);"100.00"==t&&(t="100"),1==me&&Ue.text("I'mM "+t+"% confident that I'm right!",width/2-100*le,height/2-25*le),example=Zt.map((e=>e[1])),be=Ue.textWidth('"FIDENZAAAA"'),defaultPhrase=Ue.textWidth('"PERPENDICULAR INHABITATION"'),Ue.textStyle(BOLD);const n=me?example[0]:random(example);if(1===n.split(" ").length){let e=75*be/Ue.textWidth('"'+n+'"');e>75&&(e=75),Ue.textSize(e*le),Ue.text('"'+n+'"',width/2-100*le,height/2-90*le)}else nr(width/2-100*le,height/2-90*le,460*le,110*le,n,Ue);if(millis()-ye>1500&&(me=!0),C(tt,nt,st,ct,Pe,Mt),Ue.image(nt,width/2-370*le,hM eight/2+70*le,80*le,80*le),3==Pe){let e;e=map(Mt,50,60,.25,1.3),I(rt,e),Ue.image(rt,width/2-370*le,height/2+70*le,80*le,80*le)}let r,i;Ue.image(tt,width/2-370*le,height/2+70*le,80*le,80*le),Ue.fill(xt),Ue.textSize(40*le),Ue.text("INTELLIGENCE INFO",width/2-275*le,height/2+115*le),Ue.textSize(18*le),Ue.textStyle(NORMAL),Ue.circle(width/2-360*le,height/2+180*le,7.5*le),1==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s growing and getting smarter by the day.`:2==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} yM s stable and it has reached peak performance.`:3==Pe&&(r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s decaying and losing its luster.`),i=2==Pe?"The Perceptron remains stable for some time before entering the decay phase.":`Wait until ${new Date(an).toLocaleString("en-US")} for your Perceptron to reach its peak performance.`,Ue.text(r,width/2-350*le,height/2+180*le),Ue.circle(width/2-360*le,height/2+210*le,7.5*le),Ue.text(i,width/2-350*le,height/2+210*le),Ue.textAlign(CENTER,CENTER),Ue.textM Style(BOLD),gr(Ue,width/2-225*le,width/2+65*le,height/2+265*le,height/2+305*le,"SELECT ANOTHER IMAGE"),gr(Ue,width/2+75*le,width/2+225*le,height/2+265*le,height/2+305*le,"CLOSE")}function nr(e,t,n,r,i,o){let a=i.split(" "),l=75*be/o.textWidth('"'+i+'"'),s=0,h=[],c=[],u=[],f="",d="";if(l>=50)l>75&&(l=75),o.textSize(l*le),o.text('"'+i+'"',e,t);else if(l<50){if(l=50*defaultPhrase/o.textWidth('"'+i+'"'),l>30){if(l>50&&(l=50),[f,d]=rr(l,n,s,h,c,a,f,d,Ue),0==c.length)return o.textSize(l*le),void o.text('"'+i+'"',e,t);forM (s=0,h=[],c=[];o.textWidth(d)>n/le;)l=l*n/le/o.textWidth(d),f="",d="",[f,d]=rr(l,n,s,h,c,a,f,d,Ue)}else{l=30,o.textSize(l);for(let e=0;e<a.length;e++)s+=o.textWidth(" "+a[e]),s<=n/le?h.push(a[e]):s>n/le&&s<=n/le*2?c.push(a[e]):u.push(a[e]);for(let e=1;e<h.length;e++)f=f+" "+h[e];if(f='"'+h[0]+f,0==u.length){for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+c[c.length-1]+'"'}else if(1==c.length)d="... "+u[u.length-1]+'"';else{for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+"... "+u[u.length-1]+'"'}}o.textSize(l*le);let r=M 1.25*(o.textDescent()+o.textAscent());o.text(f,e,t-r/2),o.text(d,e,t+r/2)}}function rr(e,t,n,r,i,o,a,l,s){s.textSize(e);for(let e=0;e<o.length;e++)(n+=s.textWidth(" "+o[e]))<=t/le?r.push(o[e]):i.push(o[e]);for(let e=1;e<r.length;e++)a=a+" "+r[e];if(a='"'+r[0]+a,0==i.length&&(a+='"',l=""),1==i.length)l=i[i.length-1]+'"';else{for(let e=0;e<i.length-1;e++)l=l+i[e]+" ";l=l+i[i.length-1]+'"'}return[a,l]}function ir(){const e=45*le;qe.textFont("Tahoma"),qe.stroke(st),qe.strokeWeight(2*le),qe.fill(ct),qe.rect(width/2,e/2+M height-87.5*le,600*le,90*le),qe.fill(st),qe.rect(width/2-150*le,e+height-170*le,300*le,30*le),qe.fill(ct),qe.rect(width/2+150*le,e+height-170*le,300*le,30*le),qe.noStroke(),qe.fill(ct),qe.textSize(15*le),qe.textStyle(BOLD),qe.text("PERCEPTRON INFORMATION",width/2-285*le,e+height-165*le),qe.fill(xt),qe.text("ARTWORK NAME:",width/2+10*le,e+height-165*le),qe.textAlign(RIGHT),qe.textStyle(ITALIC),qe.text("Perceptron #"+Et,width/2+285*le,e+height-165*le);const[t,n]=It.split(" ");let r;"60 Years"===It?r="1 Year":"60 MontM hs"===It?r="1 Month":"60 Weeks"===It?r="1 Week":"60 Days"===It?r="1 Day":"12 Hours"===It&&(r="12 Minutes"),data=[["AI MODEL NAME:",B(12*le,Ht,140*le)],["SCALE:","1:"+Te],["NUMBER OF CLASSES:",$t.length],["BIRTH YEAR:",Rt],["NUMBER OF REBIRTHS:",sn.toString()],["AGE:",`${Math.ceil(Mt)} Perceptron Years`],["ONE PERCEPTRON YEAR:",`${r}`],["STATE:",Ot[Pe]],["ACTIVE NEURONS:",`${round(ln*rn)} / ${ln}`],["NEXT STATE TIME:",vr(new Date(on))]],qe.fill(xt);const i=data.length/2;for(let t=0;t<data.length;++t){const n=t<i,r=nM ?width/2-285*le:width/2+10*le,o=n?width/2-10*le:width/2+285*le,a=e+height-(135-t%i*15)*le;qe.textStyle(BOLD),qe.textAlign(LEFT),qe.textSize(12*le),qe.text(data[t][0],r,a),qe.textStyle(ITALIC),qe.textAlign(RIGHT),qe.textSize(12*le),qe.text(data[t][1],o,a)}}function or(){Ke.textFont("Trebuchet MS"),Ke.noStroke(),pr(Ke,600*le,200*le),gr(Ke,width/2-155*le,width/2-5*le,height/2+115*le,height/2+155*le,"UPDATE"),gr(Ke,width/2+5*le,width/2+155*le,height/2+115*le,height/2+155*le,"CLOSE"),Ke.textAlign(LEFT),Ke.fill(xt),Ke.teM xt("UPDATE BITCOIN FULL NODE ADDRESS",width/2-252.5*le,height/2-55*le),Ke.text("UPDATE MODEL ADDRESS",width/2-252.5*le,height/2+20*le),Ke.textAlign(RIGHT),Ke.textStyle(ITALIC),Ke.textSize(15*le),0==wn&&Ke.text("(*) Invalid Address",width/2+252.5*le,height/2-53*le),0==vn&&Ke.text("(*) Invalid Model",width/2+252.5*le,height/2+23*le)}function ar(){je.textFont("Trebuchet MS"),je.fill(st),je.textSize(50*le),je.stroke(st),je.strokeWeight(1*le),je.text("main()",width/2,height/2)}function lr(){un>=20&&1==dn&&(dn=!1,un=0),dM n&&(Ze.textFont("Trebuchet MS"),Ze.stroke(st),Ze.fill(ct),Ze.rect(width/2,height/2,600*le,150*le,25*le),Ze.fill(xt),Ze.textSize(75*le),Ze.noStroke(),1==Pe?Ze.text("GROWING",width/2,height/2+5*le):3==Pe?Ze.text("AGING",width/2,height/2+5*le):4==Pe?Ze.text("DEAD",width/2,height/2+5*le):5==Pe&&Ze.text("BIRTH",width/2,height/2+5*le)),un>=20&&0==dn&&(dn=!0,un=0,Bt++,3==Bt&&(fn=!1))}function sr(e,t,n,r){let i=[],o=r/(n.length+1),a=color(e),l=color(t);i.push(a);for(let e=0;e<n.length;e++){let t=color(n[e]);for(let e=1;e<=M o;e++){let n=lerpColor(a,t,e/o);i.push(n)}a=t}for(let e=1;e<o;e++){let t=lerpColor(a,l,e/o);i.push(t)}if(i.push(l),i.length>r)i.splice(r);else if(i.length<r){let e=i[i.length-1];for(;i.length<r;)i.push(e)}return i}function hr(e,t){let n=e.length,r=Math.floor(t*n);return r>=n&&(r=n-1),e[r]}function cr(e){e=e.replace("#","");var t=parseInt(e,16);return color(t>>16&255,t>>8&255,255&t)}function ur(e,t,n,r,i,o,a,l){var s=a.drawingContext.createLinearGradient(e,t,n,r);s.addColorStop(0,i),s.addColorStop(1,o),a.drawingContM ext.strokeStyle=s,a.drawingContext.globalAlpha=l,a.line(e,t,n,r),a.drawingContext.globalAlpha=1}function fr(e,t){t.drawingContext.setLineDash(e)}function dr(e,t){let n=color(e),r=red(n),i=green(n),o=blue(n);return color(r,i,o,255*t)}function xr(e,t,n,r){return mouseX>e&&mouseX<t&&mouseY>n&&mouseY<r}function gr(e,t,n,r,i,o){e.strokeWeight(1*le),e.stroke(st);const[a,l]=xr(t,n,r,i)?[xt,ct]:[ct,xt];e.fill(a),e.push(),e.rectMode(CORNERS),e.rect(t,r,n,i,5*le),e.pop(),e.noStroke(),e.textSize(20*le),e.fill(l),e.text(o,(t+nM )/2,(46*r+54*i)/100)}function pr(e,t,n){e.fill(0,0,0,75),e.rect(width/2,height/2,width,height),e.stroke(st),e.fill(ct),e.rect(width/2,height/2,t,n,25*le)}function mr(e,t){resizeCanvas(e,t,!0),Xe.resizeCanvas(e,t,!0),$e.resizeCanvas(e,t,!0),We.resizeCanvas(e,t,!0),Ue.resizeCanvas(e,t,!0),qe.resizeCanvas(e,t,!0),Qe.resizeCanvas(e,t,!0),je.resizeCanvas(e,t,!0),Ze.resizeCanvas(e,t,!0),Ke.resizeCanvas(e,t,!0),Je.resizeCanvas(e,t,!0),et.resizeCanvas(e,t,!0)}function br(e,t,n,r,i,o){const a=J(e);return a.position(t,n),a.sM ize(r,i),a.style("opacity","0"),a.mouseClicked(o),a}function yr(){return null!=vt&&vt?.isFocused()||null!=zt&&zt?.isFocused()}function wr(e,t,n,r){let i;if(e<=3){i=`Hey ${String.fromCodePoint(128075)}, I'm ${n}, ${t} years old. I can detect ${r.length} NFT collections: `;let e=0;for(let t=0;t<r.length;++t){const n=r[t];if(e+n.length>500){i+=", etc";break}t==r.length-1?i+=", and ":t>0&&(i+=", "),i+=n,e+=n.length}i+=". ",t<=5?i+="However, I am only a baby, so my recognition ability is not accurate. I'm in the state oM f Growing both looks and intelligence.":t<=13?i+="I am now a child. My recognition ability is becoming better, but still not very accurate. I'm in the state of Growing both looks and intelligence.":t<=25?i+="I have grown up to be a teen. My recognition ability almost reaches the peak, but I will still mess up sometimes. I'm in the state of Growing both looks and intelligence.":t<=50?i+="I finally reach adulthood. My recognition is fully functional now. I'm in the Stable state, where I am the most intelligent with aM ll neurons activated.":t<=60&&(i+="I am now an old Perceptron, so my recognition ability is no longer the best. I'm in the Decaying state, meaning that my neurons are dying, and my intelligence is decreasing over time.")}else 4==e?i=`${n} is Dead. However, this is not the end to its story...`:5==e&&(i=`${n} is now in the Rebirth state, and is preparing to start a new life.`);return i}function vr(e){const t=e.getDate(),n=e.toLocaleString("en-US",{month:"long"}),r=e.getFullYear();let i=e.getHours().toString();1==i.leM ngth&&(i="0"+i);let o=e.getMinutes().toString();return 1==o.length&&(o="0"+o),`${Y(t)} ${n} ${r} | ${i}:${o}`}saveCanvasAtCurrentTime=()=>{save(N())},save4KCanvasAtCurrentTime=()=>{const e=width,t=height,n=min(4096/min(e,t),1e4/max(e,t)),r=e*n,i=t*n;mr(r,i),zn=!0,$n(r,i),qn();let o="4K_"+N()+".png";saveCanvas(et,o),mr(e,t),$n(e,t),zn=!1};const zr=[["60 Years",3,365],["60 Months",40,30],["60 Weeks",37,7],["60 Days",20,1]],Vr=[["1943",1],["1951",1.5],["1957",2],["1969",2.5],["1970",3],["1980",3.5],["1982",4],["1986",M 4.5],["1988",5],["1997",5.5],["1998",6],["2002",6.5],["2009",7],["2012",7.5],["2014",8],["2015",8.5],["2016",9],["2023",15]],_r=[["Plain",20],["Dotted",40],["Squared",40]],Mr=[["Basic",30],["Standard",60],["Advanced",10]],Er=[["MNIST",70],["CIFAR",25],["IMAGENET",5]],Sr=[["Theano",60],["Torch",30],["TensorFlow",10]],Rr=[["Whitepaper",2],["Blackboard",2],["Blueprint",2],["Nak",74/14],["Jims",74/14],["Level 10",74/14],["Flips",74/14],["Level 14",74/14],["III",74/14],["XMB",74/14],["Info",74/14],["Adventure",74/14],["M Marigold",74/14],["Phoenix",74/14],["Love",74/14],["Cachet",74/14],["Human",74/14],["Twilight",3],["Sunset",3],["Aurora",3],["Liminal Space",3],["D Vu",3],["Lucid Dream",3],["Parallel",1],["Multiverse",1]];function Ir(e){for(let e=0;e<100;++e)random(1);return{visual:{pattern:k(_r),hardwareAcceleration:k(Mr),nodeFill:k(Er),nodeShape:k(Sr),colorPalette:k(Rr),lifeCycle:k(zr),birthYear:k(Vr)},training:e}}function Cr(e){window.$generativeTraits={"Network Architecture":e.training.structure_gen,"Hidden Layers":e.traiM ning.n_layers,"Max Neurons Per Hidden Layer":e.training.max_nodes,"Activation Function":e.training.activation_func,"Training Epochs":e.training.epoch_num,Dataset:e.visual.nodeFill,"Deep Learning Framework":e.visual.nodeShape,"Hardware Acceleration":e.visual.hardwareAcceleration,"Paper Pattern":e.visual.pattern,"Life Cycle":e.visual.lifeCycle,"Birth Year":e.visual.birthYear,"Color Palette":e.visual.colorPalette}} <script defer src="https://static.cloudflareinsights.com/beacon.min.js/v2b4487d741ca48dcM: badcaf954e159fc61680799950996" integrity="sha512-D/jdE0CypeVxFadTejKGTzmwyV10c1pxZk/AqjJuZbaJwGMyNHY3q/mTPWqMUnFACfCTunhZUVcd4cV78dK1pQ==" data-cf-beacon='{"rayId":"7b48410cff6ea24d","version":"2023.3.0","b":1,"token":"6c07c178c94442f695e7a0a2aaee641a","si":100}' crossorigin="anonymous"></script> {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "rainbow"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "lamp"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "rainbow"}, {"trait_type": "Claws", "value": "bloody"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "pauldrons"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "sword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "golden"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "arrow wounds"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "golden"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "parrot"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "quiver"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "blue fire"}, {"trait_type": "Eyes", "value": "golden"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "axe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "pirate flag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "sword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "blue fire"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "poisoned dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "broadsword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "axe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "undead"}, {"trait_type": "Artifacts", "value": "arrow wounds"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "honey pot"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "shield"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "golden"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "shield"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "rainbow"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "bloody"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "poisoned dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "lamp"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "cape"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "moon"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "bloody"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "sword"}]} text/html;charset=utf-8 <meta charset="utf-8" /> position: relative; width: var(--width); height: var(--height); border: 1px solid blue; position: relative; <div id="upload"> <input id="inputUpload" type="file"> function e(e){"use strict";return new function e(t){let n="global"==t?window:this;n.canvas=document.createElement("canvas");let r=n.canvas.getContext("2d");n.width=100,n.height=100,n.canvas.width=n.width,n.canvas.height=n.height,"offscreen"!=t&&(document.body?document.body.appendChild(n.canvas):window.addEventListener("load",(function(){document.body.appendChild(n.canvas)}))),g(),n.MAGIC=161533525,n.RGB=0,n.HSV=1,n.HM SB=1,n.CHORD=0,n.PIE=1,n.OPEN=2,n.RADIUS=1,n.CORNER=2,n.CORNERS=3,n.ROUND="round",n.SQUARE="butt",n.PROJECT="square",n.MITER="miter",n.BEVEL="bevel",n.CLOSE=1,n.BLEND="source-over",n.REMOVE="destination-out",n.ADD="lighter",n.DARKEST="darken",n.LIGHTEST="lighten",n.DIFFERENCE="difference",n.SUBTRACT="subtract",n.EXCLUSION="exclusion",n.MULTIPLY="multiply",n.SCREEN="screen",n.REPLACE="copy",n.OVERLAY="overlay",n.HARD_LIGHT="hard-light",n.SOFT_LIGHT="soft-light",n.DODGE="color-dodge",n.BURN="color-burn",n.NORMAL="norM mal",n.ITALIC="italic",n.BOLD="bold",n.BOLDITALIC="italic bold",n.CENTER="center",n.LEFT="left",n.RIGHT="right",n.TOP="top",n.BOTTOM="bottom",n.BASELINE="alphabetic",n.LANDSCAPE="landscape",n.PORTRAIT="portrait",n.ALT=18,n.BACKSPACE=8,n.CONTROL=17,n.DELETE=46,n.DOWN_ARROW=40,n.ENTER=13,n.ESCAPE=27,n.LEFT_ARROW=37,n.OPTION=18,n.RETURN=13,n.RIGHT_ARROW=39,n.SHIFT=16,n.TAB=9,n.UP_ARROW=38,n.HALF_PI=Math.PI/2,n.PI=Math.PI,n.QUARTER_PI=Math.PI/4,n.TAU=2*Math.PI,n.TWO_PI=2*Math.PI,n.THRESHOLD=1,n.GRAY=2,n.OPAQUE=3,n.INVEM RT=4,n.POSTERIZE=5,n.DILATE=6,n.ERODE=7,n.BLUR=8,n.ARROW="default",n.CROSS="crosshair",n.HAND="pointer",n.MOVE="move",n.TEXT="text",n.VIDEO={video:!0,audio:!1},n.AUDIO={video:!1,audio:!0},n.SHR3=1,n.LCG=2,n.HARDWARE_FILTERS=!0,n.hint=function(e,t){n[e]=t},n.frameCount=0,n.mouseX=0,n.mouseY=0,n.pmouseX=0,n.pmouseY=0,n.mouseButton=null,n.keyIsPressed=!1,n.mouseIsPressed=!1,n.key=null,n.keyCode=null,n.pixels=null,n.accelerationX=0,n.accelerationY=0,n.accelerationZ=0,n.rotationX=0,n.rotationY=0,n.rotationZ=0,n.relRotatM ionX=0,n.relRotationY=0,n.relRotationZ=0,n.pAccelerationX=0,n.pAccelerationY=0,n.pAccelerationZ=0,n.pRotationX=0,n.pRotationY=0,n.pRotationZ=0,n.pRelRotationX=0,n.pRelRotationY=0,n.pRelRotationZ=0,n.touches=[],n._styleCache=[{colorMode:n.RGB,noStroke:!1,noFill:!1,ellipseMode:n.CENTER,rectMode:n.CORNER,curveDetail:20,curveAlpha:0,textFont:"sans-serif",textSize:12,textLeading:12,textStyle:"normal"}],n._style=n._styleCache[n._styleCache.length-1],n._noLoop=!1,n._pixelDensity=1,n._frameRate=null,n._tint=null;let i=nullM ,o=!0,a=[],l=null,s=0,h={},c=0,u=null,f=null,d=null;Object.defineProperty(n,"deviceOrientation",{get:function(){return 90==Math.abs(window.orientation)?n.LANDSCAPE:n.PORTRAIT}}),Object.defineProperty(n,"windowWidth",{get:function(){return window.innerWidth}}),Object.defineProperty(n,"windowHeight",{get:function(){return window.innerHeight}}),Object.defineProperty(n,"drawingContext",{get:function(){return r}}),n.createCanvas=function(e,t){return n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t,g(),n.canvas},nM .resizeCanvas=function(e,t){n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t},n.createGraphics=n.createImage=function(t,n){let r=new e("offscreen");return r.createCanvas(t,n),r.noLoop(),r},n.pixelDensity=function(e){return null==e||(n._pixelDensity=e,n.canvas.width=Math.ceil(n.width*e),n.canvas.height=Math.ceil(n.height*e),n.canvas.style.width=n.width+"px",n.canvas.style.height=n.height+"px",r.scale(n._pixelDensity,n._pixelDensity),g()),n._pixelDensity},n.map=function(e,t,n,r,i,o){let a=r+1*(e-t)/(n-t)*(i-r)M ;return o?r<i?Math.min(Math.max(a,r),i):Math.min(Math.max(a,i),r):a},n.lerp=function(e,t,n){return e*(1-n)+t*n},n.constrain=function(e,t,n){return Math.min(Math.max(e,t),n)},n.dist=function(){return 4==arguments.length?Math.hypot(arguments[0]-arguments[2],arguments[1]-arguments[3]):Math.hypot(arguments[0]-arguments[3],arguments[1]-arguments[4],arguments[2]-arguments[5])},n.norm=function(e,t,r){return n.map(e,t,r,0,1)},n.sq=function(e){return e*e},n.fract=function(e){return e-Math.floor(e)},n.degrees=function(e){retM urn 180*e/Math.PI},n.radians=function(e){return e*Math.PI/180},n.abs=Math.abs,n.ceil=Math.ceil,n.exp=Math.exp,n.floor=Math.floor,n.log=Math.log,n.mag=Math.hypot,n.max=Math.max,n.min=Math.min,n.round=Math.round,n.sqrt=Math.sqrt,n.sin=Math.sin,n.cos=Math.cos,n.tan=Math.tan,n.asin=Math.asin,n.acos=Math.acos,n.atan=Math.atan,n.atan2=Math.atan2,n.Vector=function(e,t,r){let i=this;i.x=e||0,i.y=t||0,i.z=r||0;let o=null,a=null;function l(e,t,n){return null!=e.x?e:null!=t?{x:e,y:t,z:n||0}:{x:e,y:e,z:e}}function s(){null==a&M &(a=i.x*i.x+i.y*i.y+i.z*i.z,o=Math.sqrt(a))}function h(){a=null,o=null}i.set=function(e,t,n){i.x=e||0,i.y=t||0,i.z=n||0},i.copy=function(){return new n.Vector(i.x,i.y,i.z)},i.add=function(){let e=l.apply(null,arguments);return i.x+=e.x,i.y+=e.y,i.z+=e.z,h(),i},i.rem=function(){let e=l.apply(null,arguments);return i.x%=e.x,i.y%=e.y,i.z%=e.z,h(),i},i.sub=function(){let e=l.apply(null,arguments);return i.x-=e.x,i.y-=e.y,i.z-=e.z,h(),i},i.mult=function(){let e=l.apply(null,arguments);return i.x*=e.x,i.y*=e.y,i.z*=e.z,hM (),i},i.div=function(){let e=l.apply(null,arguments);return i.x/=e.x,i.y/=e.y,i.z/=e.z,h(),i},i.mag=function(){return s(),o},i.magSq=function(){return s(),a},i.dot=function(){let e=l.apply(null,arguments);return i.x*e.x+i.y*e.y+i.z*e.z},i.dist=function(){let e=l.apply(null,arguments),t=i.x-e.x,n=i.y-e.y,r=i.z-e.z;return Math.sqrt(t*t+n*n+r*r)},i.cross=function(){let e=l.apply(null,arguments),t=i.y*e.z-i.z*e.y,n=i.z*e.x-i.x*e.z,r=i.x*e.y-i.y*e.x;return i.x=t,i.y=n,i.z=r,h(),i},i.normalize=function(){s();let e=o;retuM rn i.x/=e,i.y/=e,i.z/=e,o=1,a=1,i},i.limit=function(e){s();if(o>e){let t=e/o;i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e}return i},i.setMag=function(e){s();let t=e/o;return i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e,i},i.heading=function(){return Math.atan2(i.y,i.x)},i.rotate=function(e){let t=Math.cos(e),n=Math.sin(e),r=i.x*t-i.y*n,o=i.x*n+i.y*t;return i.x=r,i.y=o,i},i.angleBetween=function(){let e=l.apply(null,arguments);const t=i.dot(e)/(i.mag()*e.mag());let n;return n=Math.acos(Math.min(1,Math.max(-1,t))),n*Math.sign(i.cross(e).z||1)},M i.lerp=function(e,t){return i.x=i.x*(1-t)+e.x*t,i.y=i.y*(1-t)+e.y*t,i.z=i.z*(1-t)+e.z*t,h(),i},i.reflect=function(e){return e.normalize(),i.sub(e.mult(2*i.dot(e)))},i.array=function(){return[i.x,i.y,i.z]},i.equals=function(e,t){return null==t&&null==(t=Number.EPSILON)&&(t=0),Math.abs(e.x-i.x)<t&&Math.abs(e.y-i.y)<t&&Math.abs(e.z-i.z)<t},i.fromAngle=function(e,t){return null==t&&(t=1),o=t,a=t*t,i.x=t*Math.cos(e),i.y=t*Math.sin(e),i.z=0,i},i.fromAngles=function(e,t,n){null==n&&(n=1),o=n,a=n*n;const r=Math.cos(t),l=MaM th.sin(t),s=Math.cos(e),h=Math.sin(e);return i.x=n*h*l,i.y=-n*s,i.z=n*h*r,i},i.random2D=function(){return o=1,a=1,i.fromAngle(Math.random()*Math.PI*2)},i.random3D=function(){return o=1,a=1,i.fromAngles(Math.random()*Math.PI*2,Math.random()*Math.PI*2)},i.toString=function(){return`[${i.x}, ${i.y}, ${i.z}]`}},n.Vector.add=function(e,t){return new n.Vector(e.x+t.x,e.y+t.y,e.z+t.z)},n.Vector.rem=function(e,t){return new n.Vector(e.x%t.x,e.y%t.y,e.z%t.z)},n.Vector.sub=function(e,t){return new n.Vector(e.x-t.x,e.y-t.y,e.M z-t.z)},n.Vector.mult=function(e,t){return null==t.x?new n.Vector(e.x*t,e.y*t,e.z*t):new n.Vector(e.x*t.x,e.y*t.y,e.z*t.z)},n.Vector.div=function(e,t){return null==t.x?new n.Vector(e.x/t,e.y/t,e.z/t):new n.Vector(e.x/t.x,e.y/t.y,e.z/t.z)},n.Vector.dist=function(e,t){return Math.hypot(e.x-t.x,e.y-t.y,e.z-t.z)},n.Vector.cross=function(e,t){return new n.Vector(e.y*t.z-e.z*t.y,e.z*t.x-e.x*t.z,e.x*t.y-e.y*t.x)},n.Vector.lerp=function(e,t,r){return new n.Vector(e.x*(1-r)+t.x*r,e.y=e.y*(1-r)+t.y*r,e.z=e.z*(1-r)+t.z*r)},n.M Vector.equals=function(e,t,n){return e.equals(t,n)};for(let e of["fromAngle","fromAngles","random2D","random3D"])n.Vector[e]=function(t,r,i){return(new n.Vector)[e](t,r,i)};function x(e,t,n){let r,i,o,a,l,s,h,c,u;if(0==t)return[255*(r=n),255*(i=n),255*(o=n)];switch((a=e)>360&&(a=0),h=n*(1-t),c=n*(1-t*(s=(a/=60)-(l=~~a))),u=n*(1-t*(1-s)),l){case 0:r=n,i=u,o=h;break;case 1:r=c,i=n,o=h;break;case 2:r=h,i=n,o=u;break;case 3:r=h,i=c,o=n;break;case 4:r=u,i=h,o=n;break;default:r=n,i=h,o=c}return[255*r,255*i,255*o]}functioM n g(){r.fillStyle="white",r.strokeStyle="black",r.lineCap="round",r.lineJoin="miter"}function p(e){if(0<=e&&e<2*Math.PI)return e;for(;e<0;)e+=2*Math.PI;for(;e>=Math.PI;)e-=2*Math.PI;return e}function m(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;let c=p(a),u=p(l);r.beginPath();for(let a=0;a<h+1;a++){let l=a/h,s=n.lerp(c,u,l),f=Math.cos(s)*i/2,d=Math.sin(s)*o/2;r[a?"lineTo":"moveTo"](e+f,t+d)}s==n.CHORD?r.closePath():s==n.PIE&&(r.lineTo(e,t),r.closePath()),n._style.noFill||r.fill(),n._style.noStrokM e||r.stroke()}function b(e,t,i,o){n._style.noFill&&n._style.noStroke||(r.beginPath(),r.ellipse(e,t,i/2,o/2,0,0,2*Math.PI),n._style.noFill||r.fill(),n._style.noStroke||r.stroke())}function y(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;if(null==a)return function(e,t,i,o){n._style.noFill||r.fillRect(e,t,i,o),n._style.noStroke||r.strokeRect(e,t,i,o)}(e,t,i,o);if(null==l)return y(e,t,i,o,a,a,a,a);const c=Math.min(Math.abs(o),Math.abs(i))/2;a=Math.min(c,a),l=Math.min(c,l),h=Math.min(c,h),s=Math.min(c,s)M ,r.beginPath(),r.moveTo(e+a,t),r.arcTo(e+i,t,e+i,t+o,l),r.arcTo(e+i,t+o,e,t+o,s),r.arcTo(e,t+o,e,t,h),r.arcTo(e,t,e+i,t,a),r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke()}function w(){a=[]}n.createVector=function(e,t,r){return new n.Vector(e,t,r)},n.curvePoint=function(e,t,n,r,i){const o=i*i*i,a=i*i;return e*(-.5*o+a-.5*i)+t*(1.5*o-2.5*a+1)+n*(-1.5*o+2*a+.5*i)+r*(.5*o-.5*a)},n.bezierPoint=function(e,t,n,r,i){const o=1-i;return Math.pow(o,3)*e+3*Math.pow(o,2)*i*t+3*o*Math.pow(i,2)*n+Math.pow(i,M 3)*r},n.curveTangent=function(e,t,n,r,i){const o=i*i;return e*(-3*o/2+2*i-.5)+t*(9*o/2-5*i)+n*(-9*o/2+4*i+.5)+r*(3*o/2-i)},n.bezierTangent=function(e,t,n,r,i){const o=1-i;return 3*r*Math.pow(i,2)-3*n*Math.pow(i,2)+6*n*o*i-6*t*o*i+3*t*Math.pow(o,2)-3*e*Math.pow(o,2)},n.Color=function(e,t,n,r){let i=this;i.MAGIC=786698,i._r=e,i._g=t,i._b=n,i._a=r,i._h=0,i._s=0,i._v=0,i._hsvInferred=!1,i.setRed=function(e){i._r=e,i._hsvInferred=!1},i.setGreen=function(e){i._g=e,i._hsvInferred=!1},i.setBlue=function(e){i._b=e,i._hsvInfM erred=!1},i.setAlpha=function(e){i._a=e/255,i._hsvInferred=!1},i._inferHSV=function(){i._hsvInferred||([i._h,i._s,i._v]=function(e,t,n){let r,i,o,a,l;return r=e<t?e<n?e:n:t<n?t:n,0==(l=100*(i=e>t?e>n?e:n:t>n?t:n)/255)?[o=0,a=0,l]:0==(a=100*(i-r)/i)?[o=0,a,l]:(o=i==e?0+60*(t-n)/(i-r):i==t?120+60*(n-e)/(i-r):240+60*(e-t)/(i-r),[o,a,l])}(i._r,i._g,i._b),i._hsvInferred=!0)},i.toString=function(){return`rgba(${Math.round(i._r)},${Math.round(i._g)},${Math.round(i._b)},${~~(1e3*i._a)/1e3})`}},n.colorMode=function(e){n._stM yle.colorMode=e},n.color=function(){if(1==arguments.length&&786698==arguments[0].MAGIC)return arguments[0];if(n._style.colorMode==n.RGB){if(1==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],1);if(2==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],arguments[1]/255);if(3==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],1);if(4==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],arguments[3]/255)}else{if(1==argumeM nts.length)return new n.Color(...x(0,0,arguments[0]/100),1);if(2==arguments.length)return new n.Color(...x(0,0,arguments[0]/100),arguments[1]/255);if(3==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),1);if(4==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),arguments[3])}return null},n.red=function(e){return e._r},n.green=function(e){return e._g},n.blue=function(e){return e._b},n.alpha=function(e){return 255*e._a},n.hue=function(e){reM turn e._inferHSV(),e._h},n.saturation=function(e){return e._inferHSV(),e._s},n.brightness=function(e){return e._inferHSV(),e._v},n.lightness=function(e){return 100*(.2126*e._r+.7152*e._g+.0722*e._b)/255},n.lerpColor=function(e,t,r){return n._style.colorMode==n.RGB?new n.Color(n.constrain(n.lerp(e._r,t._r,r),0,255),n.constrain(n.lerp(e._g,t._g,r),0,255),n.constrain(n.lerp(e._b,t._b,r),0,255),n.constrain(n.lerp(e._a,t._a,r),0,1)):(e._inferHSV(),t._inferHSV(),new n.Color(n.constrain(function(e,t,r){var i=[[Math.abs(t-M e),n.map(r,0,1,e,t)],[Math.abs(t+360-e),n.map(r,0,1,e,t+360)],[Math.abs(t-360-e),n.map(r,0,1,e,t-360)]];return i.sort(((e,t)=>e[0]-t[0])),(i[0][1]+720)%360}(e._h,t._h,r),0,360),n.constrain(n.lerp(e._s,t._s,r),0,100),n.constrain(n.lerp(e._v,t._v,r),0,100),n.constrain(n.lerp(e._a,t._a,r),0,1)))},n.strokeWeight=function(e){n._style_noStroke=!1,r.lineWidth=e},n.stroke=function(){if(n._style.noStroke=!1,"string"==typeof arguments[0])return void(r.strokeStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._sM tyle.noStroke=!0:r.strokeStyle=e},n.noStroke=function(){n._style.noStroke=!0},n.fill=function(){if(n._style.noFill=!1,"string"==typeof arguments[0])return void(r.fillStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._style.noFill=!0:r.fillStyle=e},n.noFill=function(){n._style.noFill=!0},n.blendMode=function(e){r.globalCompositeOperation=e},n.strokeCap=function(e){r.lineCap=e},n.strokeJoin=function(e){r.lineJoin=e},n.ellipseMode=function(e){n._style.ellipseMode=e},n.rectMode=function(e){n._style.rectM Mode=e},n.curveDetail=function(e){n._style.curveDetail=e},n.curveAlpha=function(e){n._style.curveAlpha=e},n.curveTightness=function(e){n._style.curveAlpha=e},n.clear=function(){r.clearRect(0,0,n.width,n.height)},n.background=function(){if(arguments[0]&&arguments[0].MAGIC==n.MAGIC)return n.image(arguments[0],0,0,n.width,n.height);r.save(),r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity),r.fillStyle="string"==typeof arguments[0]?arguments[0]:n.color(...Array.from(arguments)),r.fillRect(0,0,n.width,n.heightM ),r.restore()},n.line=function(e,t,i,o){n._style.noStroke||(r.beginPath(),r.moveTo(e,t),r.lineTo(i,o),r.stroke())},n.arc=function(e,t,r,i,o,a,l,s){if(o==a)return n.ellipse(e,t,r,i);null==s&&(s=25),null==l&&(l=n.PIE),n._style.ellipseMode==n.CENTER?m(e,t,r,i,o,a,l,s):n._style.ellipseMode==n.RADIUS?m(e,t,2*r,2*i,o,a,l,s):n._style.ellipseMode==n.CORNER?m(e+r/2,t+i/2,r,i,o,a,l,s):n._style.ellipseMode==n.CORNERS&&m((e+r)/2,(t+i)/2,r-e,i-t,o,a,l,s)},n.ellipse=function(e,t,r,i){null==i&&(i=r),n._style.ellipseMode==n.CENTERM ?b(e,t,r,i):n._style.ellipseMode==n.RADIUS?b(e,t,2*r,2*i):n._style.ellipseMode==n.CORNER?b(e+r/2,t+i/2,r,i):n._style.ellipseMode==n.CORNERS&&b((e+r)/2,(t+i)/2,r-e,i-t)},n.circle=function(e,t,r){return n.ellipse(e,t,r,r)},n.point=function(e,t){e.x&&(t=e.y,e=e.x),r.beginPath(),r.ellipse(e,t,.4,.4,0,0,2*Math.PI),r.stroke()},n.rect=function(e,t,r,i,o,a,l,s){n._style.rectMode==n.CENTER?y(e-r/2,t-i/2,r,i,o,a,l,s):n._style.rectMode==n.RADIUS?y(e-r,t-i,2*r,2*i,o,a,l,s):n._style.rectMode==n.CORNER?y(e,t,r,i,o,a,l,s):n._stylM e.rectMode==n.CORNERS&&y(e,t,r-e,i-t,o,a,l,s)},n.square=function(e,t,r,i,o,a,l){return n.rect(e,t,r,r,i,o,a,l)},n.beginShape=function(){w(),r.beginPath(),o=!0},n.beginContour=function(){r.closePath(),w(),o=!0},n.endContour=function(){w(),o=!0},n.vertex=function(e,t){w(),o?r.moveTo(e,t):r.lineTo(e,t),o=!1},n.bezierVertex=function(e,t,n,i,o,a){w(),r.bezierCurveTo(e,t,n,i,o,a)},n.quadraticVertex=function(e,t,n,i){w(),r.quadraticCurveTo(e,t,n,i)},n.bezier=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.bezierVM ertex(r,i,o,a,l,s),n.endShape()},n.triangle=function(e,t,r,i,o,a){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.endShape(n.CLOSE)},n.quad=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.vertex(l,s),n.endShape(n.CLOSE)},n.endShape=function(e){w(),e&&r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke(),n._style.noFill&&n._style.noStroke&&(r.save(),r.fillStyle="none",r.fill(),r.restore())},n.curveVertex=function(e,t){if(a.push([e,t]),a.length<4)return;M let i=function(e,t,n,r,i,o,a,l,s,h){function c(e,t,n,r,i,o){let a=Math.pow(r-t,2)+Math.pow(i-n,2);return Math.pow(a,.5*o)+e}let u=[],f=c(0,e,t,n,r,h),d=c(f,n,r,i,o,h),x=c(d,i,o,a,l,h);for(let h=0;h<s;h++){let c=f+h/(s-1)*(d-f),g=[(f-c)/(f-0),(c-0)/(f-0),(d-c)/(d-f),(c-f)/(d-f),(x-c)/(x-d),(c-d)/(x-d),(d-c)/(d-0),(c-0)/(d-0),(x-c)/(x-f),(c-f)/(x-f)];for(let e=0;e<g.length;e+=2)isNaN(g[e])&&(g[e]=1,g[e+1]=0),isFinite(g[e])||(g[e]>0?(g[e]=1,g[e+1]=0):(g[e]=0,g[e+1]=1));let p=e*g[0]+n*g[1],m=t*g[0]+r*g[1],b=n*g[2]+i*g[M 3],y=r*g[2]+o*g[3],w=i*g[4]+a*g[5],v=o*g[4]+l*g[5],z=p*g[6]+b*g[7],V=m*g[6]+y*g[7],_=b*g[8]+w*g[9],M=y*g[8]+v*g[9],E=z*g[2]+_*g[3],S=V*g[2]+M*g[3];u.push([E,S])}return u}(...a[a.length-4],...a[a.length-3],...a[a.length-2],...a[a.length-1],n._style.curveDetail,n._style.curveAlpha);for(let e=0;e<i.length;e++)o?r.moveTo(...i[e]):r.lineTo(...i[e]),o=!1},n.curve=function(e,t,r,i,o,a,l,s){n.beginShape(),n.curveVertex(e,t),n.curveVertex(r,i),n.curveVertex(o,a),n.curveVertex(l,s),n.endShape()},n.translate=function(e,t){r.tM ranslate(e,t)},n.rotate=function(e){r.rotate(e)},n.scale=function(e,t){null==t&&(t=e),r.scale(e,t)},n.applyMatrix=function(e,t,n,i,o,a){r.transform(e,t,n,i,o,a)},n.shearX=function(e){r.transform(1,0,Math.tan(e),1,0,0)},n.shearY=function(e){r.transform(1,Math.tan(e),0,1,0,0)},n.resetMatrix=function(){r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity)},n.pushMatrix=n.push=function(){n._styleCache.push({...n._style}),n._style=n._styleCache[n._styleCache.length-1],r.save()},n.popMatrix=n.pop=function(){n._stylM eCache.length-1&&(n._styleCache.pop(),n._style=n._styleCache[n._styleCache.length-1],r.restore())},n.image=function(e,t,i,o,a,l,s,h,c){let u=e.MAGIC==n.MAGIC?e.canvas:e;function d(){if(e.MAGIC!=n.MAGIC||!n._tint)return;let t=e.canvas.getContext("2d");t.save(),t.resetTransform(),t.clearRect(0,0,t.canvas.width,t.canvas.height),t.drawImage(f.canvas,0,0),t.restore()}return e.MAGIC==n.MAGIC&&null!=n._tint&&(function(e,t){null==f&&(f=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvasM .height),f.canvas.width==e&&f.canvas.height==t||(f.canvas.width=e,f.canvas.height=t)}(e.canvas.width,e.canvas.height),f.drawImage(e.canvas,0,0),e.tinted(n._tint)),o?l?(h||(h=u.width),c||(c=u.height),r.drawImage(u,l,s,h,c,t,i,o,a),void d()):(r.drawImage(u,t,i,o,a),void d()):(e.MAGIC==n.MAGIC||e.width?r.drawImage(u,t,i,e.width,e.height):r.drawImage(u,t,i,e.videoWidth,e.videoHeight),void d())},n.loadPixels=function(){l=r.getImageData(0,0,n.canvas.width,n.canvas.height),n.pixels=l.data},n.updatePixels=function(){null!=M l&&r.putImageData(l,0,0)},n.loadImage=function(e,t){s++;let r=n.createGraphics(100,100),i=r.canvas.getContext("2d"),o=new Image;return o.src=e,o.crossOrigin="Anonymous",o.onload=function(){i.canvas.width=o.width,i.canvas.height=o.height,r.width=o.width,r.height=o.height,i.drawImage(o,0,0),s--,t&&t(r)},r};let v={};function z(e,t){null==u&&(u=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvas.height),u.canvas.width==e&&u.canvas.height==t||(u.canvas.width=e,u.canvas.height=t)}funcM tion V(){let e=r.canvas.width*r.canvas.height*4;null!=d&&e==d.length||(d=new Uint8ClampedArray(e))}function _(e){u.clearRect(0,0,u.canvas.width,u.canvas.height),u.filter=e,u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()}v[n.THRESHOLD]=function(e,t){null==t?t=127.5:t*=255;for(let n=0;n<e.length;n+=4){const r=.2126*e[n]+.7152*e[n+1]+.0722*e[n+2];e[n]=e[n+1]=e[n+2]=r>=t?255:0}},v[n.GRAY]=function(e){for(let t=0;t<e.length;t+=4)M {const n=.2126*e[t]+.7152*e[t+1]+.0722*e[t+2];e[t]=e[t+1]=e[t+2]=n}},v[n.OPAQUE]=function(e){for(let t=0;t<e.length;t+=4)e[t+3]=255},v[n.INVERT]=function(e){for(let t=0;t<e.length;t+=4)e[t]=255-e[t],e[t+1]=255-e[t+1],e[t+2]=255-e[t+2]},v[n.POSTERIZE]=function(e,t){let n=t-1;for(let r=0;r<e.length;r+=4)e[r]=255*(e[r]*t>>8)/n,e[r+1]=255*(e[r+1]*t>>8)/n,e[r+2]=255*(e[r+2]*t>>8)/n},v[n.DILATE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-M 1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.max(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.ERODE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.min(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.BLURM ]=function(e,t){t=t||1,t=Math.floor(t*n._pixelDensity),V(),d.set(e);let i=2*t+1,o=function(e){let n=new Float32Array(e),r=.3*t+.8,i=r*r*2;for(let t=0;t<e;t++){let o=t-e/2,a=Math.exp(-o*o/i)/(2.5066282746*r);n[t]=a}return n}(i),[a,l]=[r.canvas.width,r.canvas.height];for(let n=0;n<l;n++)for(let r=0;r<a;r++){let l=0,s=0,h=0,c=0;for(let e=0;e<i;e++){let i=4*(n*a+Math.min(Math.max(r-t+e,0),a-1));l+=d[i]*o[e],s+=d[i+1]*o[e],h+=d[i+2]*o[e],c+=d[i+3]*o[e]}let u=4*(n*a+r);e[u]=l,e[u+1]=s,e[u+2]=h,e[u+3]=c}d.set(e);for(let nM =0;n<l;n++)for(let r=0;r<a;r++){let s=0,h=0,c=0,u=0;for(let e=0;e<i;e++){let i=4*(Math.min(Math.max(n-t+e,0),l-1)*a+r);s+=d[i]*o[e],h+=d[i+1]*o[e],c+=d[i+2]*o[e],u+=d[i+3]*o[e]}let f=4*(n*a+r);e[f]=s,e[f+1]=h,e[f+2]=c,e[f+3]=u}},n.filter=function(e,t){if(n.HARDWARE_FILTERS&&null!=r.filter)if(z(),e==n.THRESHOLD){null==t&&(t=.5),t=Math.max(t,1e-5),_(`saturate(0%) brightness(${Math.floor(.5/t*100)}%) contrast(1000000%)`)}else if(e==n.GRAY)_("saturate(0%)");else if(e==n.OPAQUE)u.fillStyle="black",u.fillRect(0,0,u.canvaM s.width,u.canvas.height),u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.drawImage(u.canvas,0,0),r.restore();else if(e==n.INVERT)_("invert(100%)");else if(e==n.BLUR)_(`blur(${Math.ceil(t*n._pixelDensity/1)||1}px)`);else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}},n.resize=function(e,t){z(),u.drawImage(r.canvas,0,0),n.width=e,n.height=t,r.canvas.width=e*n._pixM elDensity,r.canvas.height=t*n._pixelDensity,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0,r.canvas.width,r.canvas.height),r.restore()},n.get=function(e,t,i,o){if(null!=e&&null==i){let i=r.getImageData(e,t,1,1).data;return new n.Color(i[0],i[1],i[2],i[3]/255)}e=e||0,t=t||0,i=i||n.width,o=o||n.height;let a=n.createGraphics(i,o);a.pixelDensity(n._pixelDensity);let l=r.getImageData(e*n._pixelDensity,t*n._pixelDensity,i*n._pixelDensity,o*n._pixelDensity);return a.caM nvas.getContext("2d").putImageData(l,0,0),a},n.set=function(e,t,i){if(i.MAGIC==n.MAGIC){let r=n._tint;return n._tint=null,n.image(i,e,t),void(n._tint=r)}let o=4*(t*n._pixelDensity*r.canvas.width+e*n._pixelDensity);n.pixels[o]=i._r,n.pixels[o+1]=i._g,n.pixels[o+2]=i._b,n.pixels[o+3]=255*i._a},n.tinted=function(){let e=n.color(...Array.from(arguments)),t=e._a;e._a=1,z(),u.clearRect(0,0,u.canvas.width,u.canvas.height),u.fillStyle=e,u.fillRect(0,0,u.canvas.width,u.canvas.height),u.globalCompositeOperation="multiply",u.M drawImage(r.canvas,0,0),u.globalCompositeOperation="source-over",r.save(),r.resetTransform();let i=r.globalCompositeOperation;r.globalCompositeOperation="source-in",r.drawImage(u.canvas,0,0),r.globalCompositeOperation=i,r.restore(),u.globalAlpha=t,u.clearRect(0,0,u.canvas.width,u.canvas.height),u.drawImage(r.canvas,0,0),u.globalAlpha=1,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()},n.tint=function(){n._tint=n.color(...Array.from(arguments))},n.noTiM nt=function(){n._tint=null},n.mask=function(e){r.save(),r.resetTransform();let t=r.globalCompositeOperation;r.globalCompositeOperation="destination-in",r.drawImage(e.canvas,0,0),r.globalCompositeOperation=t,r.restore()},n.clearTemporaryBuffers=function(){u=null,f=null,d=null},n.save=function(e,t){e=e||"untitled",t=t||"png";var n=document.createElement("a");n.innerHTML="[Download]",n.addEventListener("click",(function(){this.href=r.canvas.toDataURL(),this.download=e+"."+t}),!1),document.body.appendChild(n),n.click()M ,document.body.removeChild(n)},n.saveCanvas=function(e,t,r){if(e.MAGIC==n.MAGIC){r&&e.save(t,r);let n=t.split(".");return e.save(n.slice(0,-1).join("."),n[n.length-1])}if(t)return n.save(e,t);let i=e.split(".");return n.save(i.slice(0,-1).join("."),i[i.length-1])},n.loadFont=function(e){let t=e.split("/"),n=t[t.length-1].split(".")[0].replace(" ",""),r=`@font-face {\n font-family: '${n}';\n src: url('${e}');\n }`;const i=document.createElement("style");return i.textContent=r,document.head.append(M i),n},n.textFont=function(e){n._style.textFont=e},n.textSize=function(e){n._style.textSize=e,n._style.textLeading=e},n.textLeading=function(e){n._style.textLeading=e},n.textStyle=function(e){n._style.textStyle=e},n.textAlign=function(e,t){r.textAlign=e,t&&(r.textBaseline=t==n.CENTER?"middle":t)},n.text=function(e,t,i,o){if(!e)return;if(e=e.toString(),n._style.noFill&&n._style.noStroke)return;r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`;let a=e.split("\n");for(let e=0;e<a.length;e++)n._M style.noFill||r.fillText(a[e],t,i,o),n._style.noStroke||r.strokeText(a[e],t,i,o),i+=n._style.textLeading},n.textWidth=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).width},n.textAscent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBoundingBoxAscent},n.textDescent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBounM dingBoxDescent};var M,E=4,S=.5,R=function(e){return.5*(1-Math.cos(e*Math.PI))};n.noise=function(e,t,n){if(t=t||0,n=n||0,null==M){M=new Array(4096);for(var r=0;r<4096;r++)M[r]=Math.random()}e<0&&(e=-e),t<0&&(t=-t),n<0&&(n=-n);for(var i,o,a,l,s,h=Math.floor(e),c=Math.floor(t),u=Math.floor(n),f=e-h,d=t-c,x=n-u,g=0,p=.5,m=0;m<E;m++){var b=h+(c<<4)+(u<<8);i=R(f),o=R(d),a=M[4095&b],a+=i*(M[b+1&4095]-a),l=M[b+16&4095],a+=o*((l+=i*(M[b+16+1&4095]-l))-a),l=M[4095&(b+=256)],l+=i*(M[b+1&4095]-l),s=M[b+16&4095],l+=o*((s+=i*(M[M b+16+1&4095]-s))-l),g+=(a+=R(x)*(l-a))*p,p*=S,h<<=1,c<<=1,u<<=1,(f*=2)>=1&&(h++,f--),(d*=2)>=1&&(c++,d--),(x*=2)>=1&&(u++,x--)}return g},n.noiseDetail=function(e,t){e>0&&(E=e),t>0&&(S=t)};const I=function(){let e,t,n=4294967295;return{setSeed(r){e=t=(null==r?Math.random()*n:r)>>>0},getSeed:()=>t,rand:()=>(e^=e<<17,e^=e>>13,((e^=e<<5)>>>0)/n)}};let C=I();C.setSeed(),n.noiseSeed=function(e){let t=null==e?4294967295*Math.random():e;M||(M=new Float32Array(4096));for(var n=0;n<4096;n++)t^=t<<17,t^=t>>13,t^=t<<5,M[n]=(t>M >>0)/4294967295},n.randomSeed=function(e){C.setSeed(e)},n.random=function(e,t){return null==e?C.rand():"number"==typeof e?null!=t?C.rand()*(t-e)+e:C.rand()*e:e[~~(e.length*C.rand())]},n.randomGenerator=function(e){e==n.LCG?C=function(){const e=4294967296;let t,n;return{setSeed(r){n=t=(null==r?Math.random()*e:r)>>>0},getSeed:()=>t,rand:()=>(n=(1664525*n+1013904223)%e)/e}}():e==n.SHR3&&(C=I()),C.setSeed()};var T=new function(){var e,t,n,r=new Array(128),i=new Array(256),o=new Array(128),a=new Array(128),l=new Array(2M 56),s=new Array(256),h=function(){return 4294967296*C.rand()-2147483648},c=function(){return.5+2.328306e-10*(h()<<0)};this.SHR3=h,this.UNI=c,this.RNOR=function(){return n=h(),e=127&n,Math.abs(n)<r[e]?n*o[e]:function(){for(var t,i,l,s,u=3.44262;;){if(t=n*o[e],0==e){do{l=c(),s=c(),t=.2904764*-Math.log(l),i=-Math.log(s)}while(i+i<t*t);return n>0?u+t:-u-t}if(a[e]+c()*(a[e-1]-a[e])<Math.exp(-.5*t*t))return t;if(n=h(),e=127&n,Math.abs(n)<r[e])return n*o[e]}}()},this.REXP=function(){return(t=h()>>>0)<r[e=255&t]?t*l[e]:funM ction(){for(var n;;){if(0==e)return 7.69711-Math.log(c());if(n=t*l[e],s[e]+c()*(s[e-1]-s[e])<Math.exp(-n))return n;if((t=h())<i[e=255&t])return t*l[e]}}()},this.zigset=function(){var e,t,n=2147483648,h=4294967296,c=3.442619855899,u=c,f=.00991256303526217,d=7.697117470131487,x=d,g=.003949659822581572;for(e=f/Math.exp(-.5*c*c),r[0]=Math.floor(c/e*n),r[1]=0,o[0]=e/n,o[127]=c/n,a[0]=1,a[127]=Math.exp(-.5*c*c),t=126;t>=1;t--)c=Math.sqrt(-2*Math.log(f/c+Math.exp(-.5*c*c))),r[t+1]=Math.floor(c/u*n),u=c,a[t]=Math.exp(-.5*cM *c),o[t]=c/n;for(e=g/Math.exp(-d),i[0]=Math.floor(d/e*h),i[1]=0,l[0]=e/h,l[255]=d/h,s[0]=1,s[255]=Math.exp(-d),t=254;t>=1;t--)d=-Math.log(g/d+Math.exp(-d)),i[t+1]=Math.floor(d/x*h),x=d,s[t]=Math.exp(-d),l[t]=d/h}};T.hasInit=!1,n.randomGaussian=function(e,t){return T.hasInit||(T.zigset(),T.hasInit=!0),T.RNOR()*t+e},n.randomExponential=function(){return T.hasInit||(T.zigset(),T.hasInit=!0),T.REXP()},n.print=console.log,n.cursor=function(e,t,r){let i="";e.includes(".")&&(e=`url("${e}")`,i=", auto"),null!=t&&(e+=" "+t+M " "+r),n.canvas.style.cursor=e+i},n.noCursor=function(){n.canvas.style.cursor="none"},n.createCapture=function(e){var t=document.createElement("video");return t.playsinline="playsinline",t.autoplay="autoplay",navigator.mediaDevices.getUserMedia(e).then((function(e){t.srcObject=e})),t.style.position="absolute",t.style.opacity=1e-5,t.style.zIndex=-1e3,document.body.appendChild(t),t};let A=["setup","draw","preload","mouseMoved","mousePressed","mouseReleased","mouseDragged","mouseClicked","keyPressed","keyReleased","keM yTyped","touchStarted","touchEnded"];for(let e of A){let t="_"+e+"Fn";n[t]=function(){},n[t].isPlaceHolder=!0,n[e]?n[t]=n[e]:Object.defineProperty(n,e,{set:function(e){n[t]=e}})}function D(){n._noLoop||(i=null==n._frameRate?requestAnimationFrame(D):setTimeout(D,1e3/n._frameRate)),w(),o=!0,n.push(),n._drawFn(),n.pop(),++n.frameCount}function k(e){const t=n.canvas.getBoundingClientRect(),r=n.canvas.scrollWidth/n.width||1,i=n.canvas.scrollHeight/n.height||1;return{x:(e.clientX-t.left)/r,y:(e.clientY-t.top)/i,id:e.idenM tifier}}function L(){return n._touchStarted.isPlaceHolder&&n._touchMoved.isPlaceHolder&&n._touchEnded.isPlaceHolder}n.noLoop=function(){n._noLoop=!0,i=null},n.loop=function(){n._noLoop=!1,null==i&&D()},n.redraw=function(){D()},n.frameRate=function(e){n._frameRate=e},setTimeout((function(){n._preloadFn(),c=window.performance.now(),function e(){if(s>0)return setTimeout(e,10);n._setupFn(),D()}()}),1),n.canvas.onmousemove=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPM ressed?n._mouseDraggedFn(e):n._mouseMovedFn(e)},n.canvas.onmousedown=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!0,n.mouseButton=[n.LEFT,n.CENTER,n.RIGHT][e.button],n._mousePressedFn(e)},n.canvas.onmouseup=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!1,n._mouseReleasedFn(e)},n.canvas.onclick=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressedM =!0,n._mouseClickedFn(e),n.mouseIsPressed=!1},window.addEventListener("keydown",(function(e){n.keyIsPressed=!0,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!0,n._keyPressedFn(e),1==e.key.length&&n._keyTypedFn(e)})),window.addEventListener("keyup",(function(e){n.keyIsPressed=!1,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!1,n._keyReleasedFn(e)})),n.keyIsDown=function(e){return!!h[e]},n.canvas.ontouchstart=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.moM useY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mousePressedFn(e)||e.preventDefault()),n._touchStartedFn(e)||e.preventDefault()},n.canvas.ontouchmove=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mouseDraggedFn(e)||e.preventDefault()),n._touchMovedFn(e)||e.preventDefault()},n.canvas.ontouchend=n.canvas.ontouchcancel=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.M mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!1,n._mouseReleasedFn(e)||e.preventDefault()),n._touchEndedFn(e)||e.preventDefault()},n.hasSensorPermission=!window.DeviceOrientationEvent&&!window.DeviceMotionEvent||!(DeviceOrientationEvent.requestPermission||DeviceMotionEvent.requestPermission),n.requestSensorPermissions=function(){DeviceOrientationEvent.requestPermission&&DeviceOrientationEvent.requestPermission().then((e=>{"granted"==e&&DeviceMotionEvent.requestPermissioM n&&DeviceMotionEvent.requestPermission().then((e=>{"granted"==e&&(n.hasSensorPermission=!0)})).catch(alert)})).catch(alert)},window.ondeviceorientation=function(e){n.pRotationX=n.rotationX,n.pRotationY=n.rotationY,n.pRotationZ=n.rotationZ,n.pRelRotationX=n.relRotationX,n.pRelRotationY=n.relRotationY,n.pRelRotationZ=n.relRotationZ,n.rotationX=e.beta*(Math.PI/180),n.rotationY=e.gamma*(Math.PI/180),n.rotationZ=e.alpha*(Math.PI/180),n.relRotationX=[-n.rotationY,-n.rotationX,n.rotationY][1+~~(window.orientation/90)],n.rM elRotationY=[-n.rotationX,n.rotationY,n.rotationX][1+~~(window.orientation/90)],n.relRotationZ=n.rotationZ},window.ondevicemotion=function(e){if(n.pAccelerationX=n.accelerationX,n.pAccelerationY=n.accelerationY,n.pAccelerationZ=n.accelerationZ,!e.acceleration){let t=((e,t)=>[(e[0]*t[0]+e[1]*t[1]+e[2]*t[2]+e[3])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[4]*t[0]+e[5]*t[1]+e[6]*t[2]+e[7])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[8]*t[0]+e[9]*t[1]+e[10]*t[2]+e[11])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15])])(((e,t)M =>[e[0]*t[0]+e[1]*t[4]+e[2]*t[8]+e[3]*t[12],e[0]*t[1]+e[1]*t[5]+e[2]*t[9]+e[3]*t[13],e[0]*t[2]+e[1]*t[6]+e[2]*t[10]+e[3]*t[14],e[0]*t[3]+e[1]*t[7]+e[2]*t[11]+e[3]*t[15],e[4]*t[0]+e[5]*t[4]+e[6]*t[8]+e[7]*t[12],e[4]*t[1]+e[5]*t[5]+e[6]*t[9]+e[7]*t[13],e[4]*t[2]+e[5]*t[6]+e[6]*t[10]+e[7]*t[14],e[4]*t[3]+e[5]*t[7]+e[6]*t[11]+e[7]*t[15],e[8]*t[0]+e[9]*t[4]+e[10]*t[8]+e[11]*t[12],e[8]*t[1]+e[9]*t[5]+e[10]*t[9]+e[11]*t[13],e[8]*t[2]+e[9]*t[6]+e[10]*t[10]+e[11]*t[14],e[8]*t[3]+e[9]*t[7]+e[10]*t[11]+e[11]*t[15],e[12]*t[0]+M e[13]*t[4]+e[14]*t[8]+e[15]*t[12],e[12]*t[1]+e[13]*t[5]+e[14]*t[9]+e[15]*t[13],e[12]*t[2]+e[13]*t[6]+e[14]*t[10]+e[15]*t[14],e[12]*t[3]+e[13]*t[7]+e[14]*t[11]+e[15]*t[15]])((e=>[Math.cos(e),0,Math.sin(e),0,0,1,0,0,-Math.sin(e),0,Math.cos(e),0,0,0,0,1])(n.rotationY),(e=>[1,0,0,0,0,Math.cos(e),-Math.sin(e),0,0,Math.sin(e),Math.cos(e),0,0,0,0,1])(n.rotationX)),[0,0,-9.80665]);n.accelerationX=e.accelerationIncludingGravity.x+t[0],n.accelerationY=e.accelerationIncludingGravity.y+t[1],n.accelerationZ=e.accelerationIncludM ingGravity.z-t[2]}},n.year=function(){return(new Date).getFullYear()},n.day=function(){return(new Date).getDay()},n.hour=function(){return(new Date).getHours()},n.minute=function(){return(new Date).getMinutes()},n.second=function(){return(new Date).getSeconds()},n.millis=function(){return window.performance.now()-c}}(e)}"object"==typeof exports&&"undefined"!=typeof module&&(module.exports=e);const t="https://ancient-crimson-rain.btc.discover.quiknode.pro/c268fb026303ae8443f785200f2ea4b82f0082dd";function n(e){P(e)?M localStorage.removeItem("blocksApiEndpoint"):localStorage.blocksApiEndpoint=e}function r(){return localStorage.blocksApiEndpoint||t}function i(e){P(e)?localStorage.removeItem("modelInscriptionEndpoint"):localStorage.modelInscriptionEndpoint=e}function o(){return localStorage.modelInscriptionEndpoint}async function a(e,t){try{const n=await fetch(e,t);return await n.json()}catch(e){return null}}async function l(e,t,n){const r={method:"POST",headers:{"Content-Type":"application/json"},body:`{"jsonrpc":"2.0","id":1,"meM thod":"${t}","params":${`[${n.join(sep=",")}]`}}`};return(await a(e,r))?.result}async function s(e){const n={avgfee:10,time:Date.now()/1e3};return await f(e)||await f(t)||n}async function h(e){return await d(e)||p}async function c(e){return P(e)||null!=await f(e)}async function u(e){return P(e)||null!=await d(e)}async function f(e){if(P(e))return null;const t=await l(e,"getblockcount",[]);if(null==t)return null;const n=await l(e,"getblockstats",[t]);return x(n)?n:null}async function d(e){if(P(e))return null;const tM =await a(e,{});return g(t)?t:null}function x(e){return"number"==typeof e?.time&&"number"==typeof e?.avgfee}function g(e){if(null==e)return!1;const{classes_name:t,training_traits:n,layers_config:r,weight_b64:i}=e;if(!Array.isArray(t))return!1;if(null==n)return!1;try{j(r,i)}catch(e){return!1}return!0}const p={"model_name": "pfp_classifier_145", "layers_config": {"config": {"layers": [{"class_name": "InputLayer", "config": {"batch_input_shape": [null, 28, 28, 3]}}, {"class_name": "Rescaling", "config": {"scale": 0.007M 84313725490196, "offset": -1}}, {"class_name": "Flatten"}, {"class_name": "Dense", "config": {"units": 5, "activation": "leaky_relu"}}, {"class_name": "Dense", "config": {"units": 2, "activation": "leaky_relu"}}, {"class_name": "Dense", "config": {"units": 5, "activation": "leaky_relu"}}, {"class_name": "Dense", "config": {"units": 2, "activation": "leaky_relu"}}, {"class_name": "Dense", "config": {"units": 5, "activation": "leaky_relu"}}, {"class_name": "Dense", "config": {"units": 2, "activation": "leaky_relu"}},M {"class_name": "Dense", "config": {"units": 5, "activation": "leaky_relu"}}, {"class_name": "Dense", "config": {"units": 2, "activation": "leaky_relu"}}, {"class_name": "Dense", "config": {"units": 4, "activation": "linear"}}]}}, "weight_b64": "bzuqvIlhOr0HYnY8MHI5vXlfRT3Bxjm9+ZxaPchKFT5DBdc6cqiAvWfPHrwVNbC9r8C8vTwfJD1IzEY8KqI0O/qeXb0hywY9F8+iveKDVz3IKwU9LBv+PSbAoD3PZli8+ocJviOqYT1dexu8MqDsvRhlwz3gRjK8t9sePBGWCb10Nqw9IvfjvcjUWj0/V1E9xe0XPloUvz0ATnE9W/Gwvd23RT2yngi8vfmVvUqVhT2y9Y09hkI5OxEosrwPJ0A8BteYvT7JtD0WboM9KjM 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 yOPUkg5z2AwiY8kHcHvrhL3js3RXy9mgH1vSZTzz37OGk93D6ZPVvaib2UN528O6GGvaIl8zzwt0A9glkSPoupAj7mDec8P1+wvdOGfTxraja9nEfHvRVNyT2t5o89mD7pPDlKCD1FRnM9Nz8mvcsVlz2WNv08GwGnPRYHaT3/2bo9TLyuvR88g72dEu28pR2BvXzsDT4QNI09fTsUPfqTOTwXETq8Qu8JPfGWMTxTAQa8b5CwPTOcsT3lH0g96qrXvV9Ykb0QTYG8HPZXOvv2BD527ro9+WI4vVeekj2Vr4S5X8B+vOS7qztjq8q8TX+9PdsHhj0QFgo995nfvcX2F7uOTrU8y3DGOyBTjT2SGiM9qh8KO5tejTvj4ka95jzxPH4LWL2TFNI9+fezvJkaojtdqUO7j3OqvV0qF700DFO99S14PLV/XDxgFQy96/U0PfgOlr0S8Iu9W/oUvBq/tbwBIEc9wRxfu5MX473dFSG9EMnlvcxaKzyFZE69NQOuvALZhjM 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 1sPp48GXaHPd2ICb0jdJy9IMkOvbuoMb3L71I9YHixu2pba73BCpu94fymvastyjojUpa86T1UvZB/gjzQQ3y9/qpdPDA9oT1A2be9QYYGvTVYZr1E3Tg8pUwzPf5o1DzA7iC7dLB+u+VcuryYqXE9/8WQO6/ZcTvfxwO85aSKPS4ruz2twI697iGYvLZADrwLrYg6IdqjO2Dyhb1neDy9gK01vWwZhz0+Py+86+m8vMjfkb3MVsy99V9Zu/eIdz2Vdda9MpiRPXT5UL0HxlU9BXfUPBJzzr0wto28c0GHPNz76DzLFTo94sFmvXCoub1I0f693SqKPZAWIz1khMG9nrSsO8PeiLyhV8g881K3vHKycb0jFoK96w/zvJ+sGL2pKIA9aD4KvRVmJDzg7yO99P9uvfbp9z0a2CK91kmPPITFTLyYYho87RRoO56I4zzPrjC9ucffuxDKKb7Sj6w9ABzVPQFaaD3+Mx49sHpYvfRzmz3IZ2g8RtLqPbgzgT2j9Lq9hzM 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 GaPQHqOz3iSEA+NYDdPVagWb5phbA97qR7Pc+9/z3KrQY+36FwPXoZUL4K3Cq+LXUOviCwN75Imb89CRMBvp5JTb6pPXq9+cYqvlFrcDzZKKq9rsENvheI1b19qhO+z3TfvFXSDzyb2EG9fxFIO2Hho71yyr69YX6DPS3peDuZoSM8smWSPMg1l72xl+Y8QPnYvKMBrjsiWEu6MJhxPVG+pL13EW67eF3rvPczJTzVdt88UmYsvek/vzuH6c+9903evCP9Wj3f3zg95EEmuznkZL3uEva8Nf/LvfUdjLy+bZc9qr62PbRy0z2RWfe9OCdsPdREqD2TG4k9M+46vVStob1MSwA+iKyUPRIA+D2lJxs+b8uBvP2B/r0hzHk9L5ZXPAu6u7v8fLS8XZk8Pb2QBz6V/Ca8Uqf0vS4XTDt+ab69bnm8PDtgxz2bQCM9j+5oPctlDr5GEp49+v03vRzhlT3OiQg9qPUNPOPspT11rLA8T+ojvj+6NrxIXta94T/nvA1XrzM 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 upPaVSGz25W0e9veiUvUH6Nr1u7Ag9xoTBvWWswj0XLbc97yHZO7VgkLwiAc691IuSvdZqBD3u3lw9Ane6PPMfjL3SPES88FPKvWoRYjua+C29yw7XvfKAqD1Lei89HXm5PfkXPL1BruS9nnaBvbIh0TzzNDo9thf2PF/GKrzLEWS9KJylvRGQ0Dwc3gY7aN4evfoCezxkCpI83o9uPW1awjxVBaO98B2+vWHXWDz5zFU72pbzu+Mtf70PpJW9lPnTPUf1T7s2ZNM9VolXvGtlLr0tTiw8bv2OPQjEfrwqSRG+eCaovRJPVL31RHA878bWvbQWCb4SJQu+vLn0O1jdl7spMP+7EliDvFWEtr2ER7i8BJ6ouxROgT3/EI89C2ifPQS6YT11hqu9J9BiPcjjQD1fg1A6KMt3PVH7KL3kTmI9uD7LPTReyb0F1U07xFlqPTyIgj3uES+7+GkovPT8xjvyxso7uz2rvWEv/LyUlhO+zgGhvPbH3zwT1iy9kPYQPSh1oLM 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 2UM5e9eCVNvpv6BD7oTdk97IVZPnZrED4AgYa+N5wAPdU2Nj3fgCk+9qEGPgl/BL6UB3M9w5IoPbbxgbtEtx89xEIQvqepRT3RSnc8KTREPczviD2sAC2+aSoFPUkMGz14xC09PX95PZoq7b2muzs8S5kwPSH8vLwWFrc7WAu6PTDvCL7L5U++M2Yvvu8UM75Vfwa8Lz4Bvqc+y704z929Zi8OPJhgOT1pepG9In/QvJN8OL7faPS9dA7+PZOl3DvQ/Z29huOwvXtwKj0hWHc96M99vFyBT7140tC9x6iHPfIvNT0uQZc8ePNfvQMjjL28Gd28D3GbPWEYgb2rm2u9yvvvvPAr6DzRC589BlQcvZ78SL2gwqK7SNIlPF4OiDnUQ/M8O5JsvfHRhrwmdiU8FsBgvIhgij3+f4o93QI7PSvS2D1gLwe+p3e8PD/T9T3jQ/w9Q6iAPYtjO70gsAI9lu/mPZRGqj3Racs9nfIhOx3yjL1LGnY88DBrvV5gJzvp2G88v5M 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 Pfum6Mxb2+mGS9fv+lPI+9H7wOIpE8SiilvB3Mez19EqY9DSZovaO3ET0yNk09/yzBOzWIrj2eyLK95n6cvMy7Lz2cMFk9Wam2vMGnJr2oF488YFzqPWS1Fj3tDjo9jGJJPZjZqr1boC27KWGuvEKLALzcvZo9H0DHvZr7BT1AQt+8g0seviH5Nz19ZtC9/rStumbidLzJHYC8P4O4PXi13b2AjoO6dHUIvQKwErvOXDw9yTaUvS6bcT2xdbm7mQbbvWJL1LtS/Yq9YKd9vAaJDT0ZHKw80nKYO7XFjL12Wiu8tOuTvbUYYT0K6go70edKPZA6iD2fGh09gwURvgrKd73vUfa8EAR7ve7r0j2IcwU9MV1OvS27Bb1G+q09VqKQvS0lLz3O+7G8oY7+Pa6lAj5LgaI8O4KjvfK8F7w9jpG9xEiDvfSFqj0PNS89RGsEPccLNL2SeYq8x5IBvtLpMT2sFKW84iUfPStA8T0zlcs8xZUuvtSembyfEsm8POJIvYk0ATM 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 3X2jA8dJaXvYO1oztAa6i8pQ3zPPkvzTwqZ+28V0nHPduclD3ZRJs9UbF1vfaUJju43Rq97wu3vZr+wDz60dk8TwUMvHuMjz0ZtKw7c1hOPJflqz3LtcG86r/bPQ03Ij2k8ro9K3V1vFxFLr2kvP08ur20vcYxgj1NTXQ8J+95vagzmT2QWpm8UQT0PN+NKT27HRw6rl8aPku38TxoVAA9wU2/PGmllLxqZVA9/DGYvdmkwT0sSw09WuEFvV9aQj0NK0a9tMygu0NXozy20zK99Bz0PVThYT31JGo97hmovN2kI734fFI7cD+GvcZNzz06fgc8MNQ3vSmdlT2fHiE8M7hAvWpjoT2vzo+9/7awPayCpjz3W/g8yqmfvBVzS70xQEQ9qSu1veR8Yj3Mhg88q75ivMHOCz01OpY88uPOu5ypwz29bZy9ptXfPZU2hT0cnyM86lSBPM5QoDi4qPe8jD4SvoXEoT1Virg83hP3PKDmSDvLZwW9iHC8vBD4ET3fcfw8aYM 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 8ln7U+Ztp/v7lrpD5a3Y+/IhW7P8HTKL+t0No+BbEnv1KZKL+pREC/NhWpP0zAGb5F6ME+yim2PBd0ZL+R0hq/SCO7P4adWT+Eqlw+Y5RiP0M+q78=", "training_traits": {"structure_gen": "Zigzag", "n_layers": 8, "max_nodes": 5, "activation_func": "LeakyReLU", "epoch_num": 5}, "classes_name": ["Cryptoadz", "Cryptopunks", "Moonbirds", "Nouns"]},m=25,b=50,y=59+11/12,w=59+11.5/12,v=60;function z(e,t){const n=Math.log(1-t)/Math.log(1-e);return e=>1-Math.pow(1-e,n)}class V{constructor(e,t,n){const{model:r,inputDim:i}=j(t,n);this.model=r,this.inputDim=i,M this.iteration=0,this.stage=0;const o=new Date(parseInt(e.birthYear),0,1).getTime(),a=new Date(parseInt(e.birthYear)+1,0,1).getTime();this.birthDate=new Date(Math.floor((o+a)/2));const l=zr.filter((t=>t[0]==e.lifeCycle))[0][2];this.growSpeed=365/l,this.cycleLength=60*l*24*3600*1e3,this.growthFunc=z(.4,.8)}updateAge(e){const t=(e.getTime()-this.birthDate.getTime())/31536e6*this.growSpeed;this.iteration=Math.floor(t/60);const n=t-60*this.iteration;let r;this.age=n;let i,o=0;if(n<25){let e=map(n,0,25,0,1);o=this.growtM hFunc(e),r=(25-n)/60,this.stage=1,this.stageRatio=map(n,0,25,0,1)}else n<50?(o=1,r=(50-n)/60,this.stage=2,this.stageRatio=map(n,25,50,0,1)):n<y?(o=map(n,50,y,1,0),r=(y-n)/60,this.stage=3,this.stageRatio=map(n,50,y,0,1)):n<w?(o=0,r=(w-n)/60,this.stage=4,this.stageRatio=map(n,y,w,0,1)):n<60&&(o=0,r=(60-n)/60,this.stage=5,this.stageRatio=map(n,w,60,0,1));n<50?i=map(n,0,50,0,780/880):n<w?i=map(n,50,w,780/880,800/880):n<60&&(i=map(n,w,60,800/880,1)),this.nextStateTimestamp=Math.round(e.getTime()+this.cycleLength*r),thisM .statePercentage=round(100*i);let a=(25-n)/60;a<0&&(a+=1),this.nextStableTimestamp=Math.round(e.getTime()+this.cycleLength*a),this.growth=o,this.model.updateNeurons(o,this.iteration)}getBrainStatus(){return{totalNeurons:this.model.getTotalNeurons(),neuronsLife:this.model.getNeuronsLife(),stage:this.stage,inputDim:this.inputDim,stageRatio:this.stageRatio,age:this.age,growth:this.growth,nextStateTimestamp:this.nextStateTimestamp,nextStableTimestamp:this.nextStableTimestamp,rebirthCount:max(this.iteration,0),statePercM entage:this.statePercentage}}classifyImage(e){const t=new G(e,1,e.length);return this.model.forward(t).mat[0]}}class M{constructor(e,t,n,r,i){this.p=e,this.v=t,this.size=n,this.shape=i,this.col=r}getRadius(){return 1==Oe?1*this.size/2:2==Oe?7*this.size/16:3==Oe||4==Oe?4*this.size/7:0}update(){this.p.add(this.v)}draw(e,t,n,r){const i=this.p.x*r,o=this.p.y*r,a=this.size*r,{col:l,shape:s}=this;let h,c;1==n?h=c=l:2==n?(h=dr(t,1),c=l):(h=dr(t,0),c=dr(l,1));e.stroke(dr(c,map(1,0,1,.25,1))),e.fill(dr(h,map(1,0,1,.15,1))),M 3==n&&e.fill(dr(h,0)),1==s?e.ellipse(i,o,a,a):2==s?e.rect(i,o,7*a/8,7*a/8):3==s&&(e.beginShape(),e.vertex(i-4*a/7,o),e.vertex(i,o-4*a/7),e.vertex(i+4*a/7,o),e.vertex(i,o+4*a/7),e.endShape(CLOSE))}}class E{constructor(e,t,n,r,i,o,a){this.center=e,this.len=t,this.angle=n,this.v=r,this.angV=i,this.c1=o,this.c2=a}getEndpoints(){const e=createVector(this.len/2*cos(this.angle),this.len/2*sin(this.angle));return[Vector.add(this.center,e),Vector.sub(this.center,e)]}update(){this.center.add(this.v),this.angle+=this.angV}draM w(e,t){const[n,r]=this.getEndpoints(),i=n.x*t,o=n.y*t,a=r.x*t,l=r.y*t,s=this.c1,h=this.c2;var c=e.drawingContext.createLinearGradient(i,o,a,l);c.addColorStop(0,s),c.addColorStop(1,h),e.drawingContext.strokeStyle=c,e.drawingContext.globalAlpha=1,e.line(i,o,a,l),e.drawingContext.globalAlpha=1}}function S(e,t){const n=random(TAU),r=random(e,t);return createVector(r*cos(n),r*sin(n))}class R{constructor(e,t,n,r,i){this.wall=n,this.maxR=i;const o=t.length;this.nodes=[];for(let a=0;a<o;++a){const o=[],l=.25*t[a];for(let tM =0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),l=S(.02*i,.05*i),s=random(10,25)*i;o.push(new M(t,l,s,e[a],r))}this.nodes.push(o)}const a=A(e);a.unshift(e[0]),a.push(e[e.length-1]),this.lines=[];for(let e=0;e<=o;++e){const r=[],l=(0==e?1:t[e-1])*(e==o?1:t[e])*1.5;for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),o=random(5*i,10*i),l=random(TAU),s=S(.02*i,.05*i),h=random(2e-4,.001);r.push(new E(t,o,l,s,h,a[e],a[e+1]))}this.lines.push(r)}}M reflectNode(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,{p:o,v:a}=e,l=e.getRadius();(o.x-l<t&&a.x<0||o.x+l>r&&a.x>0)&&(a.x=-a.x),(o.y-l<n&&a.y<0||o.y+l>i&&a.y>0)&&(a.y=-a.y)}reflectLine(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,[o,a]=e.getEndpoints(),l=e.v;(min(o.x,a.x)<t&&l.x<0||max(o.x,a.x)>r&&l.x>0)&&(l.x=-l.x),(min(o.y,a.y)<n&&l.y<0||max(o.y,a.y)>i&&l.y>0)&&(l.y=-l.y)}update(){for(const e of this.lines)for(const t of e)t.update(),this.reflectLine(t);for(const e of this.nodes)for(const t ofM e)t.update(),this.reflectNode(t)}draw(e,t,n,r,i){const o=i/this.maxR;for(const t of this.lines){const n=t.length*r;for(let r=0;r<n;++r)t[r].draw(e,o)}for(const i of this.nodes){const a=i.length*r;for(let r=0;r<a;++r)i[r].draw(e,t,n,o)}}}function I(e,t){re(e),e.fill(0),e.rect(0,0,500,500),ie(e),e.noStroke(),e.fill(dr(cr("#000000"),.5)),e.push(),e.translate(250,250),e.scale(t),e.translate(-250,-250),e.beginShape(),e.vertex(235.2,24.9),e.bezierVertex(215,24.6,185,11.4,164.8,11),e.bezierVertex(147.2,10.7,129.3,10.4,11M 2.2,14.7),e.bezierVertex(95.1,19,78.5,28.5,69.6,43.8),e.bezierVertex(57.699,64.199,61.599,90.199,70.199,112.2),e.bezierVertex(78.799,134.2,91.6,154.6,97.199,177.5),e.bezierVertex(102.499,199.2,100.899,222.5,92.799,243.2),e.bezierVertex(83,268,64.6,288.3,48.9,310),e.bezierVertex(33.2,331.7,24.5,337.5,26.599,364.1),e.bezierVertex(28.2,384.1,61.399,404.2,75.7,418.3),e.bezierVertex(90,432.4,73.7,488.2,91.9,496.7),e.bezierVertex(124.2,511.6,159,472.5,194.3,468.1),e.bezierVertex(211.6,465.9,267.4,501.5,283.9,495.9),e.bezM ierVertex(340.7,476.7,298.599,428.9,355.4,409.7),e.bezierVertex(370.799,404.5,454.5,407.6,464.4,394.8),e.bezierVertex(478.599,376.3,474.7,349.3,464.299,328.4),e.bezierVertex(453.9,307.5,438.099,289.5,428.699,268.2),e.bezierVertex(412,230,419,182.6,446.1,150.9),e.bezierVertex(449.7,146.7,453.6,142.7,455.8,137.6),e.bezierVertex(459.4,129.299,457.5,119.6,454.8,111),e.bezierVertex(443.2,73.4,417.3,40.4,383.6,20.299),e.bezierVertex(358.1,5,343.2,-.4,313.5,0),e.bezierVertex(287.5,.4,261.6,25.4,235.2,24.9),e.endShape(),e.M pop()}function C(e,t,n,r,i,o){let a,l,s;re(t),t.fill(0),t.rect(0,0,500,500),ie(t),t.noStroke(),t.fill(dr(n,.5)),1==i?(l=0,s=25,a=map(o,0,25,500,0)):a=0,t.rect(0,a,500,500),e.noStroke(),e.fill(r),e.rect(0,0,500,500),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertexM (246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.M 8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,4M 5.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),e.fill(n),e.beginShape(),e.vertex(435.2,3M 73.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierM Vertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12M .1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,1M 95.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),re(e),e.fill(r),e.beginShape(),e.vertex(184.3,473.2),e.bezierVertex(164,473.2,144.7,462.099,134,444.3),e.bezierVertex(131.7,440.5,129.1,438.5,125,437.1),e.bezierVertex(97.3,428.1,80.5,400.6,85.2,371.8),e.bezierVertex(86.3,365.1,85.8,364.1,79.9,361.2),e.bezierVertex(57.2,349.8,46.2,323.3M ,54.3,299.7),e.bezierVertex(54.7,298.599,55.1,297.7,55.5,296.9),e.bezierVertex(55.6,296.599,55.8,296.4,55.9,296.099),e.vertex(57.9,291.499),e.vertex(62.5,293.599),e.bezierVertex(64.9,294.7,67.3,295.799,69.5,296.9),e.bezierVertex(74.5,299.299,79.1,301.599,83.9,303.099),e.bezierVertex(89.8,304.9,96.5,305.499,102.7,305.9),e.bezierVertex(102.8,305.9,102.9,305.9,103,305.9),e.bezierVertex(106.6,305.9,108.9,302.799,109,299.799),e.bezierVertex(109.1,296.199,106.6,293.4,102.7,292.799),e.bezierVertex(101.3,292.599,99.9,292.4M ,98.4,292.299),e.bezierVertex(94.3,291.799,90.1,291.299,86,289.9),e.bezierVertex(68.9,284,56.5,270.2,52.7,252.799),e.bezierVertex(48.9,235.499,54.5,217.7,67.6,205.299),e.bezierVertex(71.9,201.299,72.7,198.1,70.8,192.399),e.bezierVertex(64.2,172.2,68.8,153.99,84.2,139.599),e.bezierVertex(94.2,130.199,105.5,125.399,117.8,125.399),e.bezierVertex(124.3,125.399,131.1,126.799,137.8,129.599),e.bezierVertex(157,137.399,167.9,152.799,169.4,173.99),e.vertex(169.4,174.399),e.bezierVertex(169.5,175.899,169.6,177.2,169.9,178.29M 9),e.bezierVertex(170.7,181.2,173.2,183.2,176.1,183.2),e.bezierVertex(176.299,183.2,176.5,183.2,176.7,183.2),e.bezierVertex(180.1,182.899,182.6,180.299,182.7,177),e.bezierVertex(183.1,162,178.299,148.2,168.399,136.1),e.bezierVertex(158.2,123.5,144.899,115.8,128.799,113.199),e.bezierVertex(123.499,112.299,120.399,109.799,118.899,104.99),e.bezierVertex(113.899,89.699,120.699,72.299,134.899,64.499),e.bezierVertex(139.99,61.699,145.799,60.199,151.7,60.199),e.bezierVertex(162.2,60.199,171.899,64.799,178.1,72.699),e.beziM erVertex(179.6,74.6,180.799,76.6,181.9,78.499),e.vertex(182.2,79.099),e.bezierVertex(183.2,80.699,185.2,83.299,188.4,83.299),e.bezierVertex(189.5,83.299,190.6,82.99,191.7,82.399),e.bezierVertex(195.1,80.599,196,76.99,194,72.799),e.bezierVertex(190.1,64.799,184.1,58.499,175.6,53.299),e.bezierVertex(174.6,52.699,173.7,52.099,172.5,51.499),e.vertex(170.5,50.299),e.vertex(163,45.899),e.vertex(170.5,41.599),e.bezierVertex(182,34.99,193.1,30.799,204.4,28.599),e.bezierVertex(208.6,27.799,212.9,27.399,217.2,27.399),e.bezieM rVertex(217.6,27.399,217.9,27.399,218.3,27.399),e.bezierVertex(231.4,27.599,242.7,38.199,243,50.599),e.bezierVertex(243.4,64.899,243.3,78.99,243.2,93.799),e.bezierVertex(243.2,99.799,243.1,105.899,243.1,112.099),e.vertex(243.1,119.199),e.vertex(236.4,116.799),e.bezierVertex(235.7,116.499,235,116.299,234.4,115.99),e.bezierVertex(233.4,115.599,232.6,115.299,232,115.199),e.bezierVertex(230.6,114.899,229.2,114.599,227.8,114.299),e.bezierVertex(223.8,113.499,220.1,112.699,216.4,112.499),e.vertex(216.2,112.499),e.bezierVM ertex(212.5,112.499,210.7,115.599,210.6,118.599),e.bezierVertex(210.4,122.399,212.7,125.099,216.4,125.399),e.bezierVertex(230.1,126.399,238.9,133.099,242.3,145.199),e.bezierVertex(243.2,148.399,243.2,151.599,243.2,154.499),e.vertex(243.2,155.099),e.bezierVertex(243.2,254.199,243.2,330,243.2,400.599),e.bezierVertex(243.2,401.99,243.2,403.4,243.2,404.9),e.bezierVertex(243.3,411.099,243.3,417.599,242.3,423.9),e.bezierVertex(238.1,449.2,219.6,467.799,194,472.5),e.bezierVertex(190.9,472.9,187.6,473.2,184.3,473.2),e.endSM hape(),e.beginShape(),e.vertex(315.8,473.1),e.bezierVertex(309.3,473.1,302.8,472,296.5,469.9),e.bezierVertex(270.4,461,253.8,434.9,257.1,407.9),e.bezierVertex(260,384,273.8,366.8,297,358.3),e.bezierVertex(297.7,358.1,298.3,357.8,299,357.6),e.bezierVertex(299.8,357.3,300.6,357.1,301.2,356.8),e.bezierVertex(304.3,355.4,306,351.8,304.9,348.7),e.bezierVertex(304,345.9,301.7,344.2,299,344.2),e.bezierVertex(298.6,344.2,298.1,344.2,297.6,344.3),e.bezierVertex(288.1,346.3,279,350.9,269.7,358.3),e.bezierVertex(268.9,358.9,2M 68.1,359.6,267.2,360.4),e.vertex(265.5,361.8),e.vertex(258.5,367.6),e.vertex(257.4,358.6),e.bezierVertex(257.3,358,257.3,357.5,257.2,357.1),e.bezierVertex(257,356,256.9,354.9,256.9,353.7),e.bezierVertex(256.9,334.8,256.9,316,256.9,297.1),e.bezierVertex(256.9,260.3,256.9,222.3,256.8,185),e.bezierVertex(256.8,170.7,268.3,158.8,282.5,158.4),e.bezierVertex(284.8,158.3,286.7,157.6,287.9,156.2),e.bezierVertex(289.099,154.9,289.599,153.2,289.5,151.3),e.bezierVertex(289.3,147.5,286.7,145.1,282.7,145.1),e.bezierVertex(282.5M ,145.1,282.2,145.1,282,145.1),e.bezierVertex(278.8,145.3,275.5,146.1,272,146.9),e.bezierVertex(270.9,147.2,269.8,147.4,268.6,147.7),e.bezierVertex(267.9,147.9,267,148.2,265.8,148.7),e.bezierVertex(265.1,149,264.4,149.3,263.5,149.6),e.vertex(256.8,152),e.vertex(256.8,114.6),e.bezierVertex(256.8,95,256.8,75.4,256.8,55.9),e.bezierVertex(256.8,38,267.2,27.3,284.6,27.3),e.bezierVertex(285.3,27.3,285.9,27.3,286.6,27.3),e.bezierVertex(299,27.9,318.7,34.5,329.6,41.9),e.vertex(336.1,46.3),e.vertex(324.4,53.3),e.bezierVertexM (316.2,58.2,310.2,64.6,306,72.9),e.bezierVertex(304.2,76.4,305.1,78.5,306.1,80),e.bezierVertex(307.4,81.9,309.4,83,311.6,83),e.bezierVertex(313.7,83,315.7,81.9,317.1,80.1),e.bezierVertex(317.4,79.7,317.8,79,318.1,78.4),e.bezierVertex(318.4,77.9,318.7,77.3,319,76.8),e.bezierVertex(325.3,66.2,336.3,59.9,348.5,59.9),e.bezierVertex(353.2,59.9,357.8,60.8,362.1,62.7),e.bezierVertex(377.6,69.3,386,86.7,381.7,103.2),e.bezierVertex(380.7,107.1,378.5,111.8,371.1,113.1),e.bezierVertex(342.7,118.1,322.2,139.1,317.8,167.8),e.beM zierVertex(317.4,170.3,317.3,173.2,317.4,176.5),e.bezierVertex(317.5,180,320.1,182.8,323.5,183),e.bezierVertex(323.6,183,323.8,183,323.9,183),e.bezierVertex(327.1,183,329.8,180.6,330.3,177.2),e.bezierVertex(330.6,175.7,330.7,174,330.9,172.3),e.bezierVertex(331.1,169.8,331.4,167.3,332,164.7),e.bezierVertex(337.3,141.9,357.7,125.4,380.7,125.4),e.bezierVertex(382.5,125.4,384.3,125.5,386.1,125.7),e.bezierVertex(412.8,128.9,432.6,150.9,432,176.9),e.bezierVertex(431.9,182.3,430.9,187.7,429.1,192.7),e.bezierVertex(427.2,1M 97.9,428,201,432.3,205),e.bezierVertex(446.8,218.7,451.8,236,446.6,255),e.bezierVertex(441.4,274,428.3,286.5,408.7,291.3),e.bezierVertex(406.1,291.9,403.6,292.1,401.1,292.3),e.bezierVertex(400,292.4,398.9,292.5,397.9,292.6),e.bezierVertex(393.6,293.1,390.9,295.7,391,299.5),e.bezierVertex(391.1,303.4,394,305.8,398.5,305.8),e.bezierVertex(409.9,305.8,420.8,302.6,431.1,296.4),e.bezierVertex(431.8,296,432.5,295.5,433.2,295.1),e.bezierVertex(433.8,294.7,434.5,294.3,435.2,293.9),e.bezierVertex(436,293.4,436.6,293.2,437.2M ,293.1),e.bezierVertex(437.4,293,437.7,292.9,438.1,292.8),e.vertex(442.5,291.4),e.vertex(444.2,295.7),e.bezierVertex(450.9,312.4,449.5,328.4,440,343.4),e.bezierVertex(435.3,350.8,428.7,356.7,420.2,361.1),e.bezierVertex(414.3,364.1,413.7,365.2,414.8,371.7),e.bezierVertex(419.5,400.2,403,427.6,375.6,436.9),e.bezierVertex(371,438.5,368.3,440.7,365.8,444.7),e.bezierVertex(355.2,462.5,336.4,473.1,315.8,473.1),e.bezierVertex(315.8,473.1,315.8,473.1,315.8,473.1),e.endShape(),ie(e),e.fill(n),e.beginShape(),e.vertex(120.2,2M 79.9),e.bezierVertex(117.9,279.9,112.4,279.299,112.2,273.599),e.bezierVertex(112,267.7,117.4,266.7,119.7,266.599),e.bezierVertex(133.1,265.799,143.1,259.499,149.3,247.899),e.bezierVertex(149.6,247.299,150.1,246.399,150.3,245.399),e.bezierVertex(150.6,244.299,150.5,243.299,150.5,242.7),e.bezierVertex(150.5,242.6,150.5,242.5,150.5,242.299),e.vertex(150.3,238.799),e.vertex(141.1,235.99),e.bezierVertex(114.6,227.799,95.6,202.499,95.9,175.799),e.bezierVertex(95.9,173.99,96.4,168.199,102.2,168.199),e.bezierVertex(102.6,1M 68.199,103,168.199,103.4,168.299),e.bezierVertex(104.8,168.499,108.2,168.899,109.2,175.599),e.bezierVertex(109.3,176.599,109.5,177.599,109.6,178.499),e.bezierVertex(110.4,184.199,111.3,189.99,113.7,195.499),e.bezierVertex(121.9,213.99,139.5,225.499,159.7,225.499),e.bezierVertex(172.1,225.499,184.1,220.899,193.5,212.599),e.bezierVertex(194,212.199,194.4,211.799,194.8,211.399),e.bezierVertex(195.1,211.099,195.5,210.799,195.8,210.399),e.bezierVertex(197.4,208.99,199.2,208.2,200.9,208.2),e.bezierVertex(202.5,208.2,204,M 208.899,205.3,210.1),e.bezierVertex(208,212.9,207.9,216.9,205,219.9),e.bezierVertex(196.5,228.6,186.3,234.3,174.7,236.8),e.bezierVertex(168.799,238.1,165.6,241,163.899,246.7),e.bezierVertex(158.3,265.9,139.9,279.7,120.2,279.9),e.vertex(120.2,279.9),e.endShape(),e.beginShape(),e.vertex(187.2,427.5),e.bezierVertex(183.799,427.5,181.299,425.3,180.799,422),e.bezierVertex(180.6,420.8,180.499,419.5,180.399,418.1),e.bezierVertex(180.299,417,180.2,415.8,180.099,414.7),e.bezierVertex(177.199,390.5,156.699,371.3,132.399,370.M 2),e.bezierVertex(131.99,370.2,131.499,370.2,131.099,370.2),e.bezierVertex(130.699,370.2,130.299,370.2,129.799,370.2),e.bezierVertex(125.99,369.9,123.199,367.2,123.099,363.6),e.bezierVertex(122.99,360.2,125.799,357.3,129.599,356.9),e.bezierVertex(130.499,356.8,131.499,356.8,132.599,356.7),e.bezierVertex(133.199,356.7,133.799,356.7,134.399,356.6),e.vertex(138.299,356.4),e.vertex(139.1,352.6),e.bezierVertex(139.5,350.7,139.799,348.9,140.2,347),e.bezierVertex(140.899,343.4,141.5,340,142.399,336.8),e.bezierVertex(150.0M 99,310.7,174.399,292,201.399,291.3),e.vertex(201.599,291.3),e.bezierVertex(203.699,291.3,206.299,292,208.299,293.2),e.bezierVertex(210.499,294.5,210.699,297.5,209.99,299.8),e.bezierVertex(209.499,301.5,208.199,303.9,203.299,304.7),e.bezierVertex(202.199,304.9,200.99,305,199.799,305.2),e.bezierVertex(194.499,305.9,188.99,306.599,183.799,308.9),e.bezierVertex(165.499,316.799,155.199,331.299,152.99,352),e.bezierVertex(152.399,357.8,154.499,361.7,159.699,364.5),e.bezierVertex(178.199,374.4,189.399,390,193.099,410.9),e.M bezierVertex(193.699,414.299,193.899,418,193.599,422),e.bezierVertex(193.399,425.2,190.899,427.5,187.399,427.5),e.vertex(187.2,427.5),e.endShape(),e.beginShape(),e.vertex(364.3,281.1),e.bezierVertex(346.3,280.6,332.9,272.8,323.5,257),e.bezierVertex(321.6,253.9,320.4,250.2,319.2,246.7),e.bezierVertex(317.7,242.2,315,239.799,310.5,238.799),e.bezierVertex(298.5,236.299,288,230.7,279.4,222.1),e.bezierVertex(276.7,219.4,274.9,215.299,278,211.9),e.bezierVertex(279.4,210.3,281,209.6,282.6,209.6),e.bezierVertex(284.4,209.6M ,286.4,210.6,288.3,212.5),e.bezierVertex(297.8,221.8,310.4,226.9,323.9,226.9),e.bezierVertex(340.2,226.9,355.1,219.3,364.8,206.2),e.bezierVertex(371,197.8,374.2,188.5,374.5,178.5),e.vertex(374.5,177.9),e.bezierVertex(374.5,177,374.5,176.1,374.7,175.4),e.bezierVertex(375.3,171.8,377.9,169.5,381.3,169.5),e.bezierVertex(381.4,169.5,381.5,169.5,381.7,169.5),e.bezierVertex(385.4,169.7,388,172.4,388,176.1),e.bezierVertex(388.1,190.7,383.4,204,374.2,215.8),e.bezierVertex(365.8,226.5,354.7,233.9,341.2,237.9),e.bezierVertexM (340,238.3,338.7,238.6,337.3,239.1),e.bezierVertex(335.9,239.6,335.1,240.4,334.7,240.9),e.bezierVertex(334.599,241,334.5,241.1,334.4,241.2),e.vertex(331.799,243.6),e.vertex(333.199,246.8),e.bezierVertex(338.199,258,346.799,264.9,358.699,267.3),e.bezierVertex(360.199,267.6,361.599,267.7,362.99,267.9),e.bezierVertex(363.599,268,364.299,268,364.899,268.1),e.bezierVertex(369.099,268.6,371.799,271.4,371.499,275),e.bezierVertex(371.199,278.6,368.299,281.2,364.399,281.2),e.vertex(364.3,281.1),e.endShape(),e.beginShape(),eM .vertex(323.9,437),e.bezierVertex(323.7,437,323.5,437,323.299,437),e.bezierVertex(319.599,436.7,317.299,434.1,317.4,430.2),e.bezierVertex(317.9,406.099,328.299,388,349.5,375),e.bezierVertex(350.7,374.2,352,373.5,353.4,372.8),e.bezierVertex(354.099,372.4,354.7,372.1,355.299,371.7),e.vertex(357.499,370.5),e.vertex(357.799,368),e.bezierVertex(360.4,346.6,345.199,323.7,323.9,317),e.bezierVertex(319.099,315.5,314.099,314.9,309.299,314.4),e.vertex(308.199,314.299),e.bezierVertex(305.99,314.099,300.799,312.9,300.899,307.2M 99),e.bezierVertex(300.99,303.499,303.899,300.9,308.099,300.9),e.vertex(308.299,300.9),e.bezierVertex(327.099,301.299,343.099,308.7,355.699,322.9),e.bezierVertex(364.299,332.5,369.399,344.099,370.99,357.299),e.bezierVertex(371.099,358.4,371.299,359.4,371.499,360.499),e.bezierVertex(371.599,360.99,371.699,361.499,371.799,361.99),e.vertex(372.499,365.899),e.vertex(377.899,366.199),e.bezierVertex(378.799,366.299,379.699,366.299,380.599,366.399),e.bezierVertex(385.099,366.699,387.899,369.399,387.799,373.299),e.bezierVeM rtex(387.699,377.099,384.99,379.599,380.799,379.799),e.bezierVertex(369.799,380.199,359.99,383.299,351.899,389.299),e.bezierVertex(338.799,398.799,331.699,411.699,330.699,427.499),e.vertex(330.699,428.299),e.bezierVertex(330.599,429.199,330.599,430.099,330.499,430.799),e.bezierVertex(330,434.7,327.5,437,323.9,437),e.endShape()}function T(e){return e[0].map(((t,n)=>e.map((e=>e[n]))))}function A(e){return e.map((e=>Array.isArray(e)?A(e):e))}function D(e,t){return floor(random(e,t))}function k(e){let t=0;for(const n oM f e)t+=n[1];let n=random(t),r=0;for(const t of e)if(r+=t[1],n<r)return t[0];return null}function L(e){for(let t=1;t<e.length;++t){let n=D(0,t),r=e[t];e[t]=e[n],e[n]=r}}function P(e){return null==e||""===e}function O(e){return new Promise((t=>setTimeout(t,e)))}function F(e,t,n){let r=0;for(let i=1;i<=1e3;++i)for(let o=1;o<=1e3;++o)if(e*o%(t*i)==0){let e=1*i/o;abs(e-n)<abs(r-n)&&(r=e)}return r}function N(){let e=60*(new Date).getTimezoneOffset()*1e3;return new Date(Date.now()-e).toISOString().slice(0,-1)}function B(eM ,t,n){let r;if(push(),textSize(e),textWidth(t)<=n)r=t;else for(let e=0;e<t.length;++e){const i=t.slice(0,e+1)+"...";if(textWidth(i)>n){r=i;break}}return pop(),r}function Y(e){var t=e%10,n=e%100;return 1==t&&11!=n?e+"st":2==t&&12!=n?e+"nd":3==t&&13!=n?e+"rd":e+"th"}class G{constructor(e,t,n){this.n=t,this.m=n,this.mat=[];let r=0;for(let t=0;t<this.n;++t){this.mat.push([]);for(let n=0;n<this.m;++n)this.mat[t].push(r<e.length?e[r]:0),r+=1}return this}copy(){return new G(this.mat.flat(),this.n,this.m)}}class H{static _M _linear=e=>e;static __relu=e=>Math.max(e,0);static __leaky_relu=e=>e>0?e:.2*e;static __sigmoid=e=>1/(1+Math.exp(-e));static __tanh=e=>Math.tanh(e);static __apply_unary_op(e,t){const n=e.copy();for(let e=0;e<n.n;++e)for(let r=0;r<n.m;++r)n.mat[e][r]=t(n.mat[e][r]);return n}static linear=e=>H.__apply_unary_op(e,H.__linear);static relu=e=>H.__apply_unary_op(e,H.__relu);static leaky_relu=e=>H.__apply_unary_op(e,H.__leaky_relu);static sigmoid=e=>H.__apply_unary_op(e,H.__sigmoid);static tanh=e=>H.__apply_unary_op(e,H.__tM anh);static __add=(e,t)=>e+t;static __mul=(e,t)=>e*t;static __apply_binary_op=(e,t,n)=>{"object"!=typeof t&&(t=new G([t],1,1));const r=e.copy();for(let e=0;e<r.n;++e)for(let i=0;i<r.m;++i)r.mat[e][i]=n(r.mat[e][i],t.mat[e%t.n][i%t.m]);return r};static mul=(e,t)=>H.__apply_binary_op(e,t,H.__mul);static add=(e,t)=>H.__apply_binary_op(e,t,H.__add);static matMul(e,t){const n=new G([],e.n,t.m);for(let r=0;r<n.n;++r)for(let i=0;i<n.m;++i)for(let o=0;o<e.m;++o)n.mat[r][i]+=e.mat[r][o]*t.mat[o][i];return n}static softmax(eM ){const t=H.__apply_unary_op(e,(e=>Math.exp(e))),n=t.mat.flat().reduce(((e,t)=>e+t));for(let r=0;r<e.n;++r)for(let i=0;i<e.m;++i)t.mat[r][i]/=n;return t}}class ${constructor(e,t){this.scale=e,this.offset=t}forward(e){return H.add(H.mul(e,this.scale),this.offset)}}class X{constructor(){}forward(e){return e.map((e=>e.flat()))}}class W{constructor(e,t,n,r){this.out_dim=e,this.activation=t,this.w=n,this.b=r}forward(e){const t=H.add(H.matMul(e,this.w),this.b);return null==this.activation?t:this.activation(t)}}class U{coM nstructor(e,t,n){this.preprocessLayers=e,this.hiddenLayers=t,this.outputLayer=n,this.totalNeurons=this.hiddenLayers.map((e=>e.out_dim)),this.currentOrders=[],this.currentIteration=null}updateNeurons(e,t){if(t!=this.currentIteration){this.currentOrders=[];for(let e=0;e<this.totalNeurons.length;++e){randomSeed(100*(t+1)+e);const n=[];for(let t=0;t<this.totalNeurons[e];++t)n.push(t);L(n),this.currentOrders.push(n)}this.currentIteration=t}const n=A(this.totalNeurons),r=n.reduce(((e,t)=>e+t))*(1-e);for(let e=0;e<r;++e){M const t=n.map(((e,t)=>(e-1)/this.totalNeurons[t]));n[t.map(((e,t)=>[e,t])).reduce(((e,t)=>t[0]>e[0]?t:e))[1]]-=Math.min(r-e,1)}this.neuronsLife=[];for(let e=0;e<n.length;++e){const t=this.currentOrders[e],r=Array(this.totalNeurons[e]).fill(0);for(let i=0;i<n[e];++i)r[t[i]]=Math.min(n[e]-i,1);this.neuronsLife.push(r)}}getTotalNeurons(){return A(this.totalNeurons)}getNeuronsLife(){return A(this.neuronsLife)}forward(e){for(const t of this.preprocessLayers)e=t.forward(e);for(const[t,n]of this.hiddenLayers.entries()){e=M n.forward(e);const r=new G(this.neuronsLife[t],1,e.m);e=H.mul(e,r)}return e=this.outputLayer.forward(e),H.softmax(e)}}function q(e){switch(e){case"relu":return H.relu;case"sigmoid":return H.sigmoid;case"tanh":return H.tanh;case"leaky_relu":return H.leaky_relu;default:return H.linear}}function j(e,t){const n=[],r=[],i=Z(t);let o=null,a=0,l=[];for(const t of e.config.layers)if("InputLayer"==t.class_name)o=t.config.batch_input_shape.slice(1),l=o;else if("Rescaling"==t.class_name)n.push(new $(t.config.scale,t.config.ofM fset));else if("Flatten"==t.class_name)o=[o.reduce(((e,t)=>e*t))];else if("Dense"==t.class_name){const e=[t.config.units],n=o[0]*e[0],l=e[0],s=i.subarray(a,a+n);a+=n;const h=i.subarray(a,a+l);a+=l;const c=new G(s,o[0],e[0]),u=new G(h,1,e[0]),f=q(t.config.activation);r.push(new W(e[0],f,c,u)),o=e}const s=r.pop();return{model:new U(n,r,s),inputDim:l}}function Z(e){const t=window.atob(e),n=t.length/Float32Array.BYTES_PER_ELEMENT,r=new DataView(new ArrayBuffer(Float32Array.BYTES_PER_ELEMENT)),i=new Float32Array(n);let M o=0;for(let e=0;e<n;e++){o=4*e;for(let e=0;e<4;++e)r.setUint8(e,t.charCodeAt(o+e));i[e]=r.getFloat32(0,!0)}return i}class K{constructor(e){this.elt=e,this._events={},this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight}position(){if(0===arguments.length)return{x:this.elt.offsetLeft,y:this.elt.offsetTop};var e="absolute";return"static"!==arguments[2]&&"fixed"!==arguments[2]&&"relative"!==arguments[2]&&"sticky"!==arguments[2]&&"initial"!==arguments[2]&&"inherit"!==arguments[2]||(e=arguments[2]),this.elt.M style.position=e,this.elt.style.left=arguments[0]+"px",this.elt.style.top=arguments[1]+"px",this.x=arguments[0],this.y=arguments[1],this}show(){return this.elt.style.display="block",this}hide(){return this.elt.style.display="none",this}size(e,t){if(0===arguments.length)return{width:this.elt.offsetWidth,height:this.elt.offsetHeight};var n=e,r=t;if(n!==te||r!==te){if(n===te?n=t*this.width/this.height:r===te&&(r=e*this.height/this.width),this.elt instanceof HTMLCanvasElement){var i,o={},a=this.elt.getContext("2d");forM (i in a)o[i]=a[i];for(i in this.elt.setAttribute("width",n*this._pInst._pixelDensity),this.elt.setAttribute("height",r*this._pInst._pixelDensity),this.elt.style.width=n+"px",this.elt.style.height=r+"px",this._pInst.scale(this._pInst._pixelDensity,this._pInst._pixelDensity),o)this.elt.getContext("2d")[i]=o[i]}else this.elt.style.width=n+"px",this.elt.style.height=r+"px",this.elt.width=n,this.elt.height=r;this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight,this._pInst&&this._pInst._curElement&&this._pInM st._curElement.elt===this.elt&&(this._pInst._setProperty("width",this.elt.offsetWidth),this._pInst._setProperty("height",this.elt.offsetHeight))}return this}style(e,t){if(t instanceof Color&&(t="rgba("+t.levels[0]+","+t.levels[1]+","+t.levels[2]+","+t.levels[3]/255+")"),void 0===t){if(-1===e.indexOf(":"))return window.getComputedStyle(this.elt).getPropertyValue(e);for(var n=e.split(";"),r=0;r<n.length;r++){var i=n[r].split(":");i[0]&&i[1]&&(this.elt.style[i[0].trim()]=i[1].trim())}}else if(this.elt.style[e]=t,"widtM h"===e||"height"===e||"left"===e||"top"===e){var o=window.getComputedStyle(this.elt).getPropertyValue(e).replace(/[^\d.]/g,"");this[e]=Math.round(parseFloat(o,10))}return this}value(){return arguments.length>0?(this.elt.value=arguments[0],this):"range"===this.elt.type?parseFloat(this.elt.value):this.elt.value}mouseClicked(e){return this._adjustListener("click",e,this),this}isFocused(){return document.activeElement===this.elt}_adjustListener(e,t,n){return!1===t?this._detachListener(e,n):this._attachListener(e,t,n),tM his}_attachListener(e,t,n){n._events[e]&&this._detachListener(e,n);var r=t.bind(n);n.elt.addEventListener(e,r,!1),n._events[e]=r}_detachListener(e,t){var n=t._events[e];t.elt.removeEventListener(e,n,!1),t._events[e]=null}}function J(e,t){var n=document.createElement("button");return n.innerHTML=e,t&&(n.value=t),ee(n)}function Q(e){var t=arguments.length>1&&void 0!==arguments[1]&&arguments[1],n=function(t){var n=!0,r=!1,i=void 0;try{for(var o,a=t.target.files[Symbol.iterator]();!(n=(o=a.next()).done);n=!0){var l=o.vM alue;File._load(l,e)}}catch(e){r=!0,i=e}finally{try{n||null==a.return||a.return()}finally{if(r)throw i}}};if(window.File&&window.FileReader&&window.FileList&&window.Blob){var r=document.createElement("input");return r.setAttribute("type","file"),t&&r.setAttribute("multiple",!0),r.addEventListener("change",n,!1),ee(r)}}function ee(e){return document.body.appendChild(e),new K(e)}createImg=function(){var e,t=document.createElement("img"),n=arguments;return n.length>1&&"string"==typeof n[1]&&(t.alt=n[1]),n.length>2&&"sM tring"==typeof n[2]&&(t.crossOrigin=n[2]),t.src=n[0],e=ee(t,this),t.addEventListener("load",(function(){e.width=t.offsetWidth||t.width,e.height=t.offsetHeight||t.height;var r=n[n.length-1];"function"==typeof r&&r(e)})),e},createInput=function(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:"",t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:"text",n=document.createElement("input");return n.setAttribute("value",e),n.setAttribute("type",t),ee(n,this)};const te="auto";function ne(e){re(e);const M t=e._rectMode;e.rectMode(CORNER),e.rect(0,0,e.width,e.height),e.rectMode(t),ie(e)}function re(e){e.push(),e.fill(255,255,255,255),e.blendMode(REMOVE)}function ie(e){e.blendMode(BLEND),e.pop()}File=function(e,t){this.file=e,this._pInst=t;var n=e.type.split("/");this.type=n[0],this.subtype=n[1],this.name=e.name,this.size=e.size,this.data=void 0},File._createLoader=function(e,t){var n=new FileReader;return n.onload=function(n){var r=new File(e);if("application/json"===r.file.type)r.data=JSON.parse(n.target.result);elsM e if("text/xml"===r.file.type){var i=(new DOMParser).parseFromString(n.target.result,"text/xml");r.data=new XML(i.documentElement)}else r.data=n.target.result;t(r)},n},File._load=function(e,t){if(/^text\//.test(e.type)||"application/json"===e.type)File._createLoader(e,t).readAsText(e);else if(/^(video|audio)\//.test(e.type)){var n=new File(e);n.data=URL.createObjectURL(e),t(n)}else File._createLoader(e,t).readAsDataURL(e)},XML=function(e){if(e)this.DOM=e;else{var t=document.implementation.createDocument(null,"doc")M ;this.DOM=t.createElement("root")}},document.addEventListener("DOMContentLoaded",(function(){addEventListener("mousemove",(e=>{window.mouseX=e.pageX,window.mouseY=e.pageY}))})),new e("global");const oe="146";let ae,le,se,he,ce,ue,fe,de,xe,ge,pe,me,be,ye,we,ve,ze,Ve,_e,Me,Ee,Se,Re,Ie,Ce,Te,Ae,De,ke,Le,Pe,Oe,Fe,Ne,Be,Ye,Ge,He,$e,Xe,We,Ue,qe,je,Ze,Ke,Je,Qe,et,tt,nt,rt,it,ot,at,lt,st,ht,ct,ut,ft,dt,xt,gt,pt,mt,bt,yt,wt,vt,zt,Vt,_t,Mt,Et,St,Rt,It,Ct,Tt,At=!1,Dt=!1,kt=!0,Lt=!1,Pt=!1;const Ot=[" ","Growing","Stable","DecaM ying","Dead","Rebirth"];let Ft,Nt,Bt,Yt,Gt,Ht,$t,Xt,Wt,Ut,qt,jt,Zt,Kt,Jt,Qt,en,tn,nn,rn,on,an,ln,sn,hn=0,cn=0,un=0,fn=!1,dn=!0,xn=!0,gn=null,pn=null,mn=null,bn=!1,yn=!1,wn=null,vn=null,zn=!1;async function setup(){let e=windowWidth,t=windowHeight;createCanvas(e,t),et=createGraphics(e,t),Xe=createGraphics(e,t),$e=createGraphics(e,t),We=createGraphics(e,t),Ue=createGraphics(e,t),qe=createGraphics(e,t),Qe=createGraphics(e,t),je=createGraphics(e,t),Ze=createGraphics(e,t),Ke=createGraphics(e,t),Je=createGraphics(e,t),ttM =createGraphics(500,500),nt=createGraphics(500,500),rt=createGraphics(500,500),_n(),Mn(),Sn(),await En(),Gn(),Rn(),bn=!0}function _n(){Et=parseInt(oe),randomSeed(Et),noiseSeed(Et)}function Mn(){Wt=Ir(p.training_traits),Cr(Wt)}async function En(){let e;Jt=r(),Qt=o(),[Xt,e]=await Promise.all([s(Jt),h(Qt)]),Ut=new V(Wt.visual,e.layers_config,e.weight_b64),Ut.updateAge(new Date),_n(),Wt.training=e.training_traits,Ht=e.model_name,$t=e.classes_name}function Sn(){le=min(width,height)/1024,ut=Rr.findIndex((e=>e[0]===Wt.visM ual.colorPalette)),ft=[["#ffffff","#231f20","#231f20"],["#231f20","#ffffff","#ffffff"],["#104da8","#ffffff","#ffffff"],["#722F1F","#FCE1B2","#FCE1B2"],["#e88120","#f9f2e5","#f9f2e5"],["#f6b941","#2E2E2E","#2E2E2E"],["#45daaa","#012221","#012221"],["#F1F1F1","#328DFE","#328DFE"],["#111822","#D3EB8D","#D3EB8D"],["#713FF9","#D6D5E6","#D6D5E6"],["#FBDA9D","#795106","#795106"],["#8f5b62","#ead0d0","#ead0d0"],["#eae4cb","#508cac","#508cac"],["#ffc6cc","#cc313d","#cc313d"],["#60A900","#E0FE00","#E0FE00"],["#507DBE","#D0D1M D3","#D0D1D3"],["#305848","#E8F2EE","#E8F2EE"],["#2a2634","#5b6988","#cb78a2","#5b6988"],["#590e29","#fd5e53","#fd5e53","#ffe373"],["#0a141d","#57d4e4","#328195","#2A9ECF","#0ab6a8","#57d4e4"],["#3a2d28","#d5c2ac","#df6338","#3d9895","#d5c2ac"],["#030706","#77c4d9","#77c4d9","#77c4d9","#ffffff","#ffffff","#e72020","#e72020"],["#3a4664","#92f5ff","#f9ff94","#eaa0a2","#55dde0"],["#fbfaff","#f04bb1","#f04bb1","#fac373","#82cef0","#8b31ce"],["#000000","#ffffff","#ff0002","#f26522","#fdff00","#00ff03","#01fffe","#0000ffM ","#ff00ff"]];for(let e=0;e<ft.length;++e)for(let t=0;t<ft[e].length;++t)ft[e][t]=cr(ft[e][t]);pt=[],ct=ft[ut][0],st=ft[ut][1]}function Rn(){gn=document.querySelector("#upload"),pn=document.querySelector("#inputUpload"),gn.addEventListener("dblclick",(()=>{if(!Lt&&!yn)if(In(Ie)&&cn==Ve-1)pn.click();else{if(4!=Pe&&5!=Pe&&(In(Ie)||cn!=Ve-1))return;fn=!0,dn=!0,Bt=0,un=0}})),pn.addEventListener("click",(()=>{pn.value=null,gn.style.display="block"})),pn.addEventListener("change",(()=>{const[e]=pn.files;e?(se=null,gn.styM le.display="none",Tn(URL.createObjectURL(e)),mn=e):gn.style.display="block"}))}function In(e){for(let t=0;t<e.length;++t){let n=0;for(let r=0;r<e[t].length;++r)e[t][r]>0&&++n;if(0==n)return!1}return!0}function Cn(){null!=se&&(un=0,Pt=!0,he=0,ue=0,drewLineAnim=!0,ce=(ae/2+we/2)/le,loadImage(se.elt.src,(e=>{const[t,n,r]=Gt,i=createGraphics(t,n);i.image(e,0,0,t,n),i.loadPixels();const o=i.pixels.filter(((e,t)=>t%4!=3)),a=Ut.classifyImage(o);Zt=T([a,$t.map((e=>e.toUpperCase()))]).sort(((e,t)=>e[0]>t[0]?-1:1))})))}functM ion Tn(e){se=createImg(e,""),se.hide(),Cn()}function An(){zn||(ce+=(width-ae-we)/tn/le),re(Xe),Xe.rect(ce*le,0,width,height),ie(Xe),un>=ge&&1==kt&&(kt=!1,un-=ge),kt&&(re($e),$e.strokeWeight(2*Fe),Jn(he,ze,ct,ct,$e),ie($e)),un>=ge&&0==kt&&(kt=!0,un-=ge,he+=1,he==en&&(++ue,he=0,ce=(ae/2+we/2)/le,1==ue&&(Pt=!1,Dn(),ye=millis())))}function Dn(){At=!0,pe=!1,me=!1,tryButton=br("Try Again",width/2-225*le,height/2+265*le,290*le,40*le,kn),closeResultButton=br("Close",width/2+75*le,height/2+265*le,150*le,40*le,Ln)}function kM n(){At=!1,tryButton.hide(),closeResultButton.hide(),pn.click()}function Ln(){Yt=!0,At=!1,Gn(),tryButton.hide(),closeResultButton.hide(),gn.style.display="block",se=null}function keyTyped(){bn&&!1===yn&&!1===yr()&&("i"!==key&&"I"!==key||(Dt=!Dt),"b"!==key&&"B"!==key||(xn=!xn),"s"!==key&&"S"!==key||!1!==Lt||saveCanvasAtCurrentTime(),"k"!==key&&"K"!==key||!1!==Lt||save4KCanvasAtCurrentTime(),"u"!==key&&"U"!==key||!1!==Lt||!1!==At||!1!==fn||!1!==Pt||On())}function On(){Lt=!0,wn=null,vn=null,submitButton=br("Submit",widM th/2-155*le,height/2+115*le,150*le,40*le,Fn),closeSettingButton=br("Close",width/2+5*le,height/2+115*le,150*le,40*le,Yn),vt=createInput(),vt.position(width/2-252.5*le,height/2-40*le),vt.size(500*le,25*le),vt.style("font-size","15px"),vt.value(Jt||""),zt=createInput(),zt.position(width/2-252.2*le,height/2+35*le),zt.size(500*le,25*le),zt.style("font-size","15px"),zt.value(Qt||"")}function Fn(){Vt=vt.value(),_t=zt.value(),submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide(),Lt=!1,yn=!0,Nn()}async functionM Nn(){[wn,vn,_]=await Promise.all([c(Vt),u(_t),O(1e3)]),yn=!1,wn&&vn?(n(Vt),i(_t),window.location.reload()):(Lt=!0,submitButton.show(),closeSettingButton.show(),vt.show(),zt.show())}function Bn(){Je.textFont("Trebuchet MS"),Je.noStroke(),pr(Je,600*le,200*le),Je.strokeWeight(1*le),Je.stroke(xt),Je.fill(xt),Je.textSize(50*le),Je.text("update()",width/2,height/2+2.5*le)}function Yn(){wn=null,vn=null,Lt=!1,submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide()}function Gn(){_n(),nn=Date.now(),pe=!1,me=!1,St=M Wt.training.structure_gen,Rt=Wt.visual.birthYear,It=Wt.visual.lifeCycle,Ct=Wt.training.epoch_num,Tt=Wt.training.activation_func,Ft=Mr.findIndex((e=>e[0]==Wt.visual.hardwareAcceleration))+1,1==Ft?(Nt=30,fe=40):2==Ft?(Nt=15,fe=20):(Nt=2,fe=10);const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentM age,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),ae=100*le,ht=50*le,Oe=Sr.findIndex((e=>e[0]==Wt.visual.nodeShape))+1,dt=Er.findIndex((e=>e[0]==Wt.visual.nodeFill))+1,lt=_r.findIndex((e=>e[0]==Wt.visual.pattern))+1,de=Math.tanh(Math.log10(Xt.avgfeerate)),de=map(de,0,1,.2,.8),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1M );for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e]M [n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.lengthM );ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,at=.7,pt=[],xt=ft[ut][2],gt=ft[ut][ft[ut].length-1];for(let e=3;e<ft[ut].length-1;e++)pt.push(ft[ut][e]);mt=sr(xt,gt,pt,width),bt=[],wt=[],yt=width/(Ve-1);for(let e=0;e<Ve;e++)bt.push(hr(mt,yt*e/width)),wt.push(hr(mt,yt*e/width));wt.unshift(bt[0]),wt.push(bt[bt.length-1]),hn=0,cn=0,un=0,Yt=!0;const n={xLeft:ae/8,xRight:width-ae/8,yTop:ae/8,yBottom:height-ae/8},r=Ce.map((e=>e.length));jt=new R(bt,r,n,M Oe,le)}function Hn(e,t){let n=Ce[e].length;return[e*we+we/2+ae/2,height/2-(n-1)/2*ve+t*ve]}function $n(e,t){le=min(e,t)/1024,ae=100*le,ht=50*le,we=(e-ae)/Ve,ve=(t-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}xe=floor(De.length*de),Le=[],ke=[],ge=floor(map(de,.2,.8,15,2));for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),FeM =map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,mt=sr(xt,gt,pt,e),bt=[],wt=[],yt=e/(Ve-1);for(let t=0;t<Ve;t++)bt.push(hr(mt,yt*t/e)),wt.push(hr(mt,yt*t/e));wt.unshift(bt[0]),wt.push(bt[bt.length-1])}function Xn(){const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+M 1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;M e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e]M .length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le}function Wn(){jt.update();const e=4==Pe?0:Kt;jt.draw(Qe,ct,dt,e,le)}function Un(){if(!bn)return ar(),void et.image(je,0,0);if(4==Pe||5==PM e)return Wn(),void et.image(Qe,0,0);un>=Nt&&hn<Ve&&(hn++,un=0);for(let e=0;e<hn;e++)1==dt?it=ot=bt[e]:(it=ct,ot=bt[e]),Kn(e,it,ot,$e);un>=Nt&&cn<Ve-1&&(cn++,un=0);for(let e=0;e<cn;e++)Zn(e)}function qn(){et.background(ct),Ue.background(255),Ue.rectMode(CENTER),ne(Ue),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),Ue.stroke(st),Ue.strokeWeight(8*le),Ue.fill(ct),Qe.background(255),Qe.rectMode(CENTER),ne(Qe),Qe.strokeWeight(le),qe.background(255),qe.rectMode(CENTER),ne(qe),qe.textAlign(LEFT),$e.background(255),$e.rectM Mode(CENTER),ne($e),Xe.background(255),ne(Xe),Xe.strokeWeight(Ne),We.background(255),We.rectMode(CENTER),ne(We),We.fill(st),We.stroke(st),We.strokeWeight(.1*le),er(lt),We.noStroke(),xn&&(We.rect(ae/16,height/2,ae/8,height),We.rect(width-ae/16,height/2,ae/8,height),We.rect(width/2,ae/16,width,ae/8),We.rect(width/2,height-ae/16,width,ae/8)),Ze.background(255),Ze.rectMode(CENTER),ne(Ze),Ze.textAlign(CENTER,CENTER),Ze.textStyle(BOLD),Ze.stroke(st),Ze.strokeWeight(8*le),Ze.fill(ct),je.background(255),je.rectMode(CENTER)M ,ne(je),je.textAlign(CENTER,CENTER),je.textStyle(BOLD),Ke.background(255),Ke.rectMode(CENTER),ne(Ke),Ke.textAlign(CENTER,CENTER),Ke.textStyle(BOLD),Ke.stroke(st),Ke.strokeWeight(8*le),Ke.fill(ct),Je.background(255),Je.rectMode(CENTER),ne(Je),Je.textAlign(CENTER,CENTER),Je.textStyle(BOLD),Je.stroke(st),Je.strokeWeight(8*le),Je.fill(ct),Un(),et.image(We,0,0),Pt&&An(),et.image(Xe,0,0),et.image($e,0,0),At&&(tr(),et.image(Ue,0,0)),fn&&(lr(),et.image(Ze,0,0)),Lt&&(or(),et.image(Ke,0,0)),Dt&&(ir(),et.image(qe,0,0)),yn&&(BM n(),et.image(Je,0,0))}function draw(){const e=Date.now();bn&&(Ut.updateAge(new Date(e)),Xn()),qn(),image(et,0,0),zn||un++}function Zn(e){let t,n=Ce[e].length,r=Ce[e+1].length;for(let i=0;i<n;i++){const[n,o]=Hn(e,i);for(let a=0;a<r;a++){const[r,l]=Hn(e+1,a);t=map(min(Ce[e][i],Ce[e+1][a]),0,1,0,.5),ur(n,o,r,l,bt[e],bt[e+1],Xe,t)}}}function Kn(e,t,n,r){let i,o,a,l=Ce[e].length;for(let s=0;s<l;s++){const[l,h]=Hn(e,s);i=Ce[e][s],a=map(Be,1/30,1,3,10),o=map(Ce[e][s],0,1,2*a,0)*le,o<1.5*le&&(o=0),Qn(l,h,ze,Oe,t,n,o,i,r)}}M function Jn(e,t,n,r,i){for(let o=0;o<Le[e].length;o++)Qn(Le[e][o][0],Le[e][o][1],t,Oe,n,r,0,1,i)}function Qn(e,t,n,r,i,o,a,l,s){s.stroke(dr(o,map(l,0,1,.25,1))),s.fill(dr(i,map(l,0,1,.15,1))),s.strokeWeight(Fe),fr([a],s),3==dt&&s.fill(dr(i,0)),1==r?s.ellipse(e,t,n):2==r?s.rect(e,t,7*n/8,7*n/8):3==r&&(s.beginShape(),s.vertex(e-4*n/7,t),s.vertex(e,t-4*n/7),s.vertex(e+4*n/7,t),s.vertex(e,t+4*n/7),s.endShape(CLOSE))}function er(e){if(1==e);else if(2==e){We.strokeWeight(1*le);for(let e=ht/4;e<width+ht/4;e+=ht)for(let t=M ht/4;t<height+ht/4;t+=ht)We.point(e,t)}else if(3==e){ht=25*le;for(let e=ht/2;e<height+ht/2;e+=ht)We.line(0,e,width,e);for(let e=ht/2;e<width+ht/2;e+=ht)We.line(e,0,e,height)}}function tr(){Ue.textFont("Trebuchet MS"),Ue.textAlign(LEFT,CENTER),Ue.noStroke(),pr(Ue,800*le,500*le),Ue.noStroke(),Ue.fill(dr(st,.75)),Ue.rect(width/2,height/2-100*le,800*le,300*le,25*le,25*le,0,0),Ue.fill(st),Ue.rect(width/2-250*le,height/2-100*le,225*le,225*le),Ue.image(se.elt,width/2-357.5*le,height/2-207.5*le,215*le,215*le);let e=100*Zt[M 0][0];Ue.fill(ct),Ue.textSize(25*le),Ue.textStyle(NORMAL),1==me&&(e>=0&&e<20?Ue.text("I have a feeling this image belongs to",width/2-100*le,height/2-170*le):e>=20&&e<40?Ue.text("I have a hunch this image belongs to",width/2-100*le,height/2-170*le):e>=40&&e<60?Ue.text("I think this image belongs to",width/2-100*le,height/2-170*le):e>=60&&e<80?Ue.text("I'm almost certain this image belongs to",width/2-100*le,height/2-170*le):Ue.text("I'm positive this image belongs to",width/2-100*le,height/2-170*le));let t=e.toFixeM d(2);"100.00"==t&&(t="100"),1==me&&Ue.text("I'm "+t+"% confident that I'm right!",width/2-100*le,height/2-25*le),example=Zt.map((e=>e[1])),be=Ue.textWidth('"FIDENZAAAA"'),defaultPhrase=Ue.textWidth('"PERPENDICULAR INHABITATION"'),Ue.textStyle(BOLD);const n=me?example[0]:random(example);if(1===n.split(" ").length){let e=75*be/Ue.textWidth('"'+n+'"');e>75&&(e=75),Ue.textSize(e*le),Ue.text('"'+n+'"',width/2-100*le,height/2-90*le)}else nr(width/2-100*le,height/2-90*le,460*le,110*le,n,Ue);if(millis()-ye>1500&&(me=!0),C(M tt,nt,st,ct,Pe,Mt),Ue.image(nt,width/2-370*le,height/2+70*le,80*le,80*le),3==Pe){let e;e=map(Mt,50,60,.25,1.3),I(rt,e),Ue.image(rt,width/2-370*le,height/2+70*le,80*le,80*le)}let r,i;Ue.image(tt,width/2-370*le,height/2+70*le,80*le,80*le),Ue.fill(xt),Ue.textSize(40*le),Ue.text("INTELLIGENCE INFO",width/2-275*le,height/2+115*le),Ue.textSize(18*le),Ue.textStyle(NORMAL),Ue.circle(width/2-360*le,height/2+180*le,7.5*le),1==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s growing and getting smarter by the day.`M :2==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s stable and it has reached peak performance.`:3==Pe&&(r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s decaying and losing its luster.`),i=2==Pe?"The Perceptron remains stable for some time before entering the decay phase.":`Wait until ${new Date(an).toLocaleString("en-US")} for your Perceptron to reach its peak performance.`,Ue.text(r,width/2-350*le,height/2+180*le),Ue.circle(width/2-360*le,height/2+210*le,7.5*le),Ue.text(i,width/2-350*le,heighM t/2+210*le),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),gr(Ue,width/2-225*le,width/2+65*le,height/2+265*le,height/2+305*le,"SELECT ANOTHER IMAGE"),gr(Ue,width/2+75*le,width/2+225*le,height/2+265*le,height/2+305*le,"CLOSE")}function nr(e,t,n,r,i,o){let a=i.split(" "),l=75*be/o.textWidth('"'+i+'"'),s=0,h=[],c=[],u=[],f="",d="";if(l>=50)l>75&&(l=75),o.textSize(l*le),o.text('"'+i+'"',e,t);else if(l<50){if(l=50*defaultPhrase/o.textWidth('"'+i+'"'),l>30){if(l>50&&(l=50),[f,d]=rr(l,n,s,h,c,a,f,d,Ue),0==c.length)return M o.textSize(l*le),void o.text('"'+i+'"',e,t);for(s=0,h=[],c=[];o.textWidth(d)>n/le;)l=l*n/le/o.textWidth(d),f="",d="",[f,d]=rr(l,n,s,h,c,a,f,d,Ue)}else{l=30,o.textSize(l);for(let e=0;e<a.length;e++)s+=o.textWidth(" "+a[e]),s<=n/le?h.push(a[e]):s>n/le&&s<=n/le*2?c.push(a[e]):u.push(a[e]);for(let e=1;e<h.length;e++)f=f+" "+h[e];if(f='"'+h[0]+f,0==u.length){for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+c[c.length-1]+'"'}else if(1==c.length)d="... "+u[u.length-1]+'"';else{for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+".M .. "+u[u.length-1]+'"'}}o.textSize(l*le);let r=1.25*(o.textDescent()+o.textAscent());o.text(f,e,t-r/2),o.text(d,e,t+r/2)}}function rr(e,t,n,r,i,o,a,l,s){s.textSize(e);for(let e=0;e<o.length;e++)(n+=s.textWidth(" "+o[e]))<=t/le?r.push(o[e]):i.push(o[e]);for(let e=1;e<r.length;e++)a=a+" "+r[e];if(a='"'+r[0]+a,0==i.length&&(a+='"',l=""),1==i.length)l=i[i.length-1]+'"';else{for(let e=0;e<i.length-1;e++)l=l+i[e]+" ";l=l+i[i.length-1]+'"'}return[a,l]}function ir(){const e=45*le;qe.textFont("Tahoma"),qe.stroke(st),qe.stroM keWeight(2*le),qe.fill(ct),qe.rect(width/2,e/2+height-87.5*le,600*le,90*le),qe.fill(st),qe.rect(width/2-150*le,e+height-170*le,300*le,30*le),qe.fill(ct),qe.rect(width/2+150*le,e+height-170*le,300*le,30*le),qe.noStroke(),qe.fill(ct),qe.textSize(15*le),qe.textStyle(BOLD),qe.text("PERCEPTRON INFORMATION",width/2-285*le,e+height-165*le),qe.fill(xt),qe.text("ARTWORK NAME:",width/2+10*le,e+height-165*le),qe.textAlign(RIGHT),qe.textStyle(ITALIC),qe.text("Perceptron #"+Et,width/2+285*le,e+height-165*le);const[t,n]=It.splitM (" ");let r;"60 Years"===It?r="1 Year":"60 Months"===It?r="1 Month":"60 Weeks"===It?r="1 Week":"60 Days"===It?r="1 Day":"12 Hours"===It&&(r="12 Minutes"),data=[["AI MODEL NAME:",B(12*le,Ht,140*le)],["SCALE:","1:"+Te],["NUMBER OF CLASSES:",$t.length],["BIRTH YEAR:",Rt],["NUMBER OF REBIRTHS:",sn.toString()],["AGE:",`${Math.ceil(Mt)} Perceptron Years`],["ONE PERCEPTRON YEAR:",`${r}`],["STATE:",Ot[Pe]],["ACTIVE NEURONS:",`${round(ln*rn)} / ${ln}`],["NEXT STATE TIME:",vr(new Date(on))]],qe.fill(xt);const i=data.length/2M ;for(let t=0;t<data.length;++t){const n=t<i,r=n?width/2-285*le:width/2+10*le,o=n?width/2-10*le:width/2+285*le,a=e+height-(135-t%i*15)*le;qe.textStyle(BOLD),qe.textAlign(LEFT),qe.textSize(12*le),qe.text(data[t][0],r,a),qe.textStyle(ITALIC),qe.textAlign(RIGHT),qe.textSize(12*le),qe.text(data[t][1],o,a)}}function or(){Ke.textFont("Trebuchet MS"),Ke.noStroke(),pr(Ke,600*le,200*le),gr(Ke,width/2-155*le,width/2-5*le,height/2+115*le,height/2+155*le,"UPDATE"),gr(Ke,width/2+5*le,width/2+155*le,height/2+115*le,height/2+155*lM e,"CLOSE"),Ke.textAlign(LEFT),Ke.fill(xt),Ke.text("UPDATE BITCOIN FULL NODE ADDRESS",width/2-252.5*le,height/2-55*le),Ke.text("UPDATE MODEL ADDRESS",width/2-252.5*le,height/2+20*le),Ke.textAlign(RIGHT),Ke.textStyle(ITALIC),Ke.textSize(15*le),0==wn&&Ke.text("(*) Invalid Address",width/2+252.5*le,height/2-53*le),0==vn&&Ke.text("(*) Invalid Model",width/2+252.5*le,height/2+23*le)}function ar(){je.textFont("Trebuchet MS"),je.fill(st),je.textSize(50*le),je.stroke(st),je.strokeWeight(1*le),je.text("main()",width/2,heightM /2)}function lr(){un>=20&&1==dn&&(dn=!1,un=0),dn&&(Ze.textFont("Trebuchet MS"),Ze.stroke(st),Ze.fill(ct),Ze.rect(width/2,height/2,600*le,150*le,25*le),Ze.fill(xt),Ze.textSize(75*le),Ze.noStroke(),1==Pe?Ze.text("GROWING",width/2,height/2+5*le):3==Pe?Ze.text("AGING",width/2,height/2+5*le):4==Pe?Ze.text("DEAD",width/2,height/2+5*le):5==Pe&&Ze.text("BIRTH",width/2,height/2+5*le)),un>=20&&0==dn&&(dn=!0,un=0,Bt++,3==Bt&&(fn=!1))}function sr(e,t,n,r){let i=[],o=r/(n.length+1),a=color(e),l=color(t);i.push(a);for(let e=0;e<M n.length;e++){let t=color(n[e]);for(let e=1;e<=o;e++){let n=lerpColor(a,t,e/o);i.push(n)}a=t}for(let e=1;e<o;e++){let t=lerpColor(a,l,e/o);i.push(t)}if(i.push(l),i.length>r)i.splice(r);else if(i.length<r){let e=i[i.length-1];for(;i.length<r;)i.push(e)}return i}function hr(e,t){let n=e.length,r=Math.floor(t*n);return r>=n&&(r=n-1),e[r]}function cr(e){e=e.replace("#","");var t=parseInt(e,16);return color(t>>16&255,t>>8&255,255&t)}function ur(e,t,n,r,i,o,a,l){var s=a.drawingContext.createLinearGradient(e,t,n,r);s.addCM olorStop(0,i),s.addColorStop(1,o),a.drawingContext.strokeStyle=s,a.drawingContext.globalAlpha=l,a.line(e,t,n,r),a.drawingContext.globalAlpha=1}function fr(e,t){t.drawingContext.setLineDash(e)}function dr(e,t){let n=color(e),r=red(n),i=green(n),o=blue(n);return color(r,i,o,255*t)}function xr(e,t,n,r){return mouseX>e&&mouseX<t&&mouseY>n&&mouseY<r}function gr(e,t,n,r,i,o){e.strokeWeight(1*le),e.stroke(st);const[a,l]=xr(t,n,r,i)?[xt,ct]:[ct,xt];e.fill(a),e.push(),e.rectMode(CORNERS),e.rect(t,r,n,i,5*le),e.pop(),e.noStrM oke(),e.textSize(20*le),e.fill(l),e.text(o,(t+n)/2,(46*r+54*i)/100)}function pr(e,t,n){e.fill(0,0,0,75),e.rect(width/2,height/2,width,height),e.stroke(st),e.fill(ct),e.rect(width/2,height/2,t,n,25*le)}function mr(e,t){resizeCanvas(e,t,!0),Xe.resizeCanvas(e,t,!0),$e.resizeCanvas(e,t,!0),We.resizeCanvas(e,t,!0),Ue.resizeCanvas(e,t,!0),qe.resizeCanvas(e,t,!0),Qe.resizeCanvas(e,t,!0),je.resizeCanvas(e,t,!0),Ze.resizeCanvas(e,t,!0),Ke.resizeCanvas(e,t,!0),Je.resizeCanvas(e,t,!0),et.resizeCanvas(e,t,!0)}function br(e,t,nM ,r,i,o){const a=J(e);return a.position(t,n),a.size(r,i),a.style("opacity","0"),a.mouseClicked(o),a}function yr(){return null!=vt&&vt?.isFocused()||null!=zt&&zt?.isFocused()}function wr(e,t,n,r){let i;if(e<=3){i=`Hey ${String.fromCodePoint(128075)}, I'm ${n}, ${t} years old. I can detect ${r.length} NFT collections: `;let e=0;for(let t=0;t<r.length;++t){const n=r[t];if(e+n.length>500){i+=", etc";break}t==r.length-1?i+=", and ":t>0&&(i+=", "),i+=n,e+=n.length}i+=". ",t<=5?i+="However, I am only a baby, so my recognitM ion ability is not accurate. I'm in the state of Growing both looks and intelligence.":t<=13?i+="I am now a child. My recognition ability is becoming better, but still not very accurate. I'm in the state of Growing both looks and intelligence.":t<=25?i+="I have grown up to be a teen. My recognition ability almost reaches the peak, but I will still mess up sometimes. I'm in the state of Growing both looks and intelligence.":t<=50?i+="I finally reach adulthood. My recognition is fully functional now. I'm in the StablM e state, where I am the most intelligent with all neurons activated.":t<=60&&(i+="I am now an old Perceptron, so my recognition ability is no longer the best. I'm in the Decaying state, meaning that my neurons are dying, and my intelligence is decreasing over time.")}else 4==e?i=`${n} is Dead. However, this is not the end to its story...`:5==e&&(i=`${n} is now in the Rebirth state, and is preparing to start a new life.`);return i}function vr(e){const t=e.getDate(),n=e.toLocaleString("en-US",{month:"long"}),r=e.getFM ullYear();let i=e.getHours().toString();1==i.length&&(i="0"+i);let o=e.getMinutes().toString();return 1==o.length&&(o="0"+o),`${Y(t)} ${n} ${r} | ${i}:${o}`}saveCanvasAtCurrentTime=()=>{save(N())},save4KCanvasAtCurrentTime=()=>{const e=width,t=height,n=min(4096/min(e,t),1e4/max(e,t)),r=e*n,i=t*n;mr(r,i),zn=!0,$n(r,i),qn();let o="4K_"+N()+".png";saveCanvas(et,o),mr(e,t),$n(e,t),zn=!1};const zr=[["60 Years",3,365],["60 Months",40,30],["60 Weeks",37,7],["60 Days",20,1]],Vr=[["1943",1],["1951",1.5],["1957",2],["1969",2M .5],["1970",3],["1980",3.5],["1982",4],["1986",4.5],["1988",5],["1997",5.5],["1998",6],["2002",6.5],["2009",7],["2012",7.5],["2014",8],["2015",8.5],["2016",9],["2023",15]],_r=[["Plain",20],["Dotted",40],["Squared",40]],Mr=[["Basic",30],["Standard",60],["Advanced",10]],Er=[["MNIST",70],["CIFAR",25],["IMAGENET",5]],Sr=[["Theano",60],["Torch",30],["TensorFlow",10]],Rr=[["Whitepaper",2],["Blackboard",2],["Blueprint",2],["Nak",74/14],["Jims",74/14],["Level 10",74/14],["Flips",74/14],["Level 14",74/14],["III",74/14],["XMM B",74/14],["Info",74/14],["Adventure",74/14],["Marigold",74/14],["Phoenix",74/14],["Love",74/14],["Cachet",74/14],["Human",74/14],["Twilight",3],["Sunset",3],["Aurora",3],["Liminal Space",3],["D Vu",3],["Lucid Dream",3],["Parallel",1],["Multiverse",1]];function Ir(e){for(let e=0;e<100;++e)random(1);return{visual:{pattern:k(_r),hardwareAcceleration:k(Mr),nodeFill:k(Er),nodeShape:k(Sr),colorPalette:k(Rr),lifeCycle:k(zr),birthYear:k(Vr)},training:e}}function Cr(e){window.$generativeTraits={"Network Architecture":M e.training.structure_gen,"Hidden Layers":e.training.n_layers,"Max Neurons Per Hidden Layer":e.training.max_nodes,"Activation Function":e.training.activation_func,"Training Epochs":e.training.epoch_num,Dataset:e.visual.nodeFill,"Deep Learning Framework":e.visual.nodeShape,"Hardware Acceleration":e.visual.hardwareAcceleration,"Paper Pattern":e.visual.pattern,"Life Cycle":e.visual.lifeCycle,"Birth Year":e.visual.birthYear,"Color Palette":e.visual.colorPalette}} <script defer src="https://static.cloudflMi areinsights.com/beacon.min.js/v2b4487d741ca48dcbadcaf954e159fc61680799950996" integrity="sha512-D/jdE0CypeVxFadTejKGTzmwyV10c1pxZk/AqjJuZbaJwGMyNHY3q/mTPWqMUnFACfCTunhZUVcd4cV78dK1pQ==" data-cf-beacon='{"rayId":"7b481da42a115497","version":"2023.3.0","b":1,"token":"6c07c178c94442f695e7a0a2aaee641a","si":100}' crossorigin="anonymous"></script> {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "tribal tattoo"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "honey pot"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "skull"}, {"trait_type": "Artifacts", "value": "pirate flag"}]} text/plain;charset=utf-8 ,{"p":"sns","op":"reg","name":"aeindie.sats"}h! {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "honey pot"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "sword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "fire"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "bloody"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "skull"}, {"trait_type": "Artifacts", "value": "undead staff"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "moon"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "lamp"}]} text/plain;charset=utf-8 4{"p":"brc-20","op":"mint","tick":"JOMO","amt":"100"}h! {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "tiger"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "skull"}, {"trait_type": "Artifacts", "value": "cape"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "bloody"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "poisoned dagger"}]} text/html;charset=utf-8 <meta charset="utf-8" /> position: relative; width: var(--width); height: var(--height); border: 1px solid blue; position: relative; <div id="upload"> <input id="inputUpload" type="file"> function e(e){"use strict";return new function e(t){let n="global"==t?window:this;n.canvas=document.createElement("canvas");let r=n.canvas.getContext("2d");n.width=100,n.height=100,n.canvas.width=n.width,n.canvas.height=n.height,"offscreen"!=t&&(document.body?document.body.appendChild(n.canvas):window.addEventListener("load",(function(){document.body.appendChild(n.canvas)}))),g(),n.MAGIC=161533525,n.RGB=0,n.HSV=1,n.HM SB=1,n.CHORD=0,n.PIE=1,n.OPEN=2,n.RADIUS=1,n.CORNER=2,n.CORNERS=3,n.ROUND="round",n.SQUARE="butt",n.PROJECT="square",n.MITER="miter",n.BEVEL="bevel",n.CLOSE=1,n.BLEND="source-over",n.REMOVE="destination-out",n.ADD="lighter",n.DARKEST="darken",n.LIGHTEST="lighten",n.DIFFERENCE="difference",n.SUBTRACT="subtract",n.EXCLUSION="exclusion",n.MULTIPLY="multiply",n.SCREEN="screen",n.REPLACE="copy",n.OVERLAY="overlay",n.HARD_LIGHT="hard-light",n.SOFT_LIGHT="soft-light",n.DODGE="color-dodge",n.BURN="color-burn",n.NORMAL="norM mal",n.ITALIC="italic",n.BOLD="bold",n.BOLDITALIC="italic bold",n.CENTER="center",n.LEFT="left",n.RIGHT="right",n.TOP="top",n.BOTTOM="bottom",n.BASELINE="alphabetic",n.LANDSCAPE="landscape",n.PORTRAIT="portrait",n.ALT=18,n.BACKSPACE=8,n.CONTROL=17,n.DELETE=46,n.DOWN_ARROW=40,n.ENTER=13,n.ESCAPE=27,n.LEFT_ARROW=37,n.OPTION=18,n.RETURN=13,n.RIGHT_ARROW=39,n.SHIFT=16,n.TAB=9,n.UP_ARROW=38,n.HALF_PI=Math.PI/2,n.PI=Math.PI,n.QUARTER_PI=Math.PI/4,n.TAU=2*Math.PI,n.TWO_PI=2*Math.PI,n.THRESHOLD=1,n.GRAY=2,n.OPAQUE=3,n.INVEM RT=4,n.POSTERIZE=5,n.DILATE=6,n.ERODE=7,n.BLUR=8,n.ARROW="default",n.CROSS="crosshair",n.HAND="pointer",n.MOVE="move",n.TEXT="text",n.VIDEO={video:!0,audio:!1},n.AUDIO={video:!1,audio:!0},n.SHR3=1,n.LCG=2,n.HARDWARE_FILTERS=!0,n.hint=function(e,t){n[e]=t},n.frameCount=0,n.mouseX=0,n.mouseY=0,n.pmouseX=0,n.pmouseY=0,n.mouseButton=null,n.keyIsPressed=!1,n.mouseIsPressed=!1,n.key=null,n.keyCode=null,n.pixels=null,n.accelerationX=0,n.accelerationY=0,n.accelerationZ=0,n.rotationX=0,n.rotationY=0,n.rotationZ=0,n.relRotatM ionX=0,n.relRotationY=0,n.relRotationZ=0,n.pAccelerationX=0,n.pAccelerationY=0,n.pAccelerationZ=0,n.pRotationX=0,n.pRotationY=0,n.pRotationZ=0,n.pRelRotationX=0,n.pRelRotationY=0,n.pRelRotationZ=0,n.touches=[],n._styleCache=[{colorMode:n.RGB,noStroke:!1,noFill:!1,ellipseMode:n.CENTER,rectMode:n.CORNER,curveDetail:20,curveAlpha:0,textFont:"sans-serif",textSize:12,textLeading:12,textStyle:"normal"}],n._style=n._styleCache[n._styleCache.length-1],n._noLoop=!1,n._pixelDensity=1,n._frameRate=null,n._tint=null;let i=nullM ,o=!0,a=[],l=null,s=0,h={},c=0,u=null,f=null,d=null;Object.defineProperty(n,"deviceOrientation",{get:function(){return 90==Math.abs(window.orientation)?n.LANDSCAPE:n.PORTRAIT}}),Object.defineProperty(n,"windowWidth",{get:function(){return window.innerWidth}}),Object.defineProperty(n,"windowHeight",{get:function(){return window.innerHeight}}),Object.defineProperty(n,"drawingContext",{get:function(){return r}}),n.createCanvas=function(e,t){return n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t,g(),n.canvas},nM .resizeCanvas=function(e,t){n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t},n.createGraphics=n.createImage=function(t,n){let r=new e("offscreen");return r.createCanvas(t,n),r.noLoop(),r},n.pixelDensity=function(e){return null==e||(n._pixelDensity=e,n.canvas.width=Math.ceil(n.width*e),n.canvas.height=Math.ceil(n.height*e),n.canvas.style.width=n.width+"px",n.canvas.style.height=n.height+"px",r.scale(n._pixelDensity,n._pixelDensity),g()),n._pixelDensity},n.map=function(e,t,n,r,i,o){let a=r+1*(e-t)/(n-t)*(i-r)M ;return o?r<i?Math.min(Math.max(a,r),i):Math.min(Math.max(a,i),r):a},n.lerp=function(e,t,n){return e*(1-n)+t*n},n.constrain=function(e,t,n){return Math.min(Math.max(e,t),n)},n.dist=function(){return 4==arguments.length?Math.hypot(arguments[0]-arguments[2],arguments[1]-arguments[3]):Math.hypot(arguments[0]-arguments[3],arguments[1]-arguments[4],arguments[2]-arguments[5])},n.norm=function(e,t,r){return n.map(e,t,r,0,1)},n.sq=function(e){return e*e},n.fract=function(e){return e-Math.floor(e)},n.degrees=function(e){retM urn 180*e/Math.PI},n.radians=function(e){return e*Math.PI/180},n.abs=Math.abs,n.ceil=Math.ceil,n.exp=Math.exp,n.floor=Math.floor,n.log=Math.log,n.mag=Math.hypot,n.max=Math.max,n.min=Math.min,n.round=Math.round,n.sqrt=Math.sqrt,n.sin=Math.sin,n.cos=Math.cos,n.tan=Math.tan,n.asin=Math.asin,n.acos=Math.acos,n.atan=Math.atan,n.atan2=Math.atan2,n.Vector=function(e,t,r){let i=this;i.x=e||0,i.y=t||0,i.z=r||0;let o=null,a=null;function l(e,t,n){return null!=e.x?e:null!=t?{x:e,y:t,z:n||0}:{x:e,y:e,z:e}}function s(){null==a&M &(a=i.x*i.x+i.y*i.y+i.z*i.z,o=Math.sqrt(a))}function h(){a=null,o=null}i.set=function(e,t,n){i.x=e||0,i.y=t||0,i.z=n||0},i.copy=function(){return new n.Vector(i.x,i.y,i.z)},i.add=function(){let e=l.apply(null,arguments);return i.x+=e.x,i.y+=e.y,i.z+=e.z,h(),i},i.rem=function(){let e=l.apply(null,arguments);return i.x%=e.x,i.y%=e.y,i.z%=e.z,h(),i},i.sub=function(){let e=l.apply(null,arguments);return i.x-=e.x,i.y-=e.y,i.z-=e.z,h(),i},i.mult=function(){let e=l.apply(null,arguments);return i.x*=e.x,i.y*=e.y,i.z*=e.z,hM (),i},i.div=function(){let e=l.apply(null,arguments);return i.x/=e.x,i.y/=e.y,i.z/=e.z,h(),i},i.mag=function(){return s(),o},i.magSq=function(){return s(),a},i.dot=function(){let e=l.apply(null,arguments);return i.x*e.x+i.y*e.y+i.z*e.z},i.dist=function(){let e=l.apply(null,arguments),t=i.x-e.x,n=i.y-e.y,r=i.z-e.z;return Math.sqrt(t*t+n*n+r*r)},i.cross=function(){let e=l.apply(null,arguments),t=i.y*e.z-i.z*e.y,n=i.z*e.x-i.x*e.z,r=i.x*e.y-i.y*e.x;return i.x=t,i.y=n,i.z=r,h(),i},i.normalize=function(){s();let e=o;retuM rn i.x/=e,i.y/=e,i.z/=e,o=1,a=1,i},i.limit=function(e){s();if(o>e){let t=e/o;i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e}return i},i.setMag=function(e){s();let t=e/o;return i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e,i},i.heading=function(){return Math.atan2(i.y,i.x)},i.rotate=function(e){let t=Math.cos(e),n=Math.sin(e),r=i.x*t-i.y*n,o=i.x*n+i.y*t;return i.x=r,i.y=o,i},i.angleBetween=function(){let e=l.apply(null,arguments);const t=i.dot(e)/(i.mag()*e.mag());let n;return n=Math.acos(Math.min(1,Math.max(-1,t))),n*Math.sign(i.cross(e).z||1)},M i.lerp=function(e,t){return i.x=i.x*(1-t)+e.x*t,i.y=i.y*(1-t)+e.y*t,i.z=i.z*(1-t)+e.z*t,h(),i},i.reflect=function(e){return e.normalize(),i.sub(e.mult(2*i.dot(e)))},i.array=function(){return[i.x,i.y,i.z]},i.equals=function(e,t){return null==t&&null==(t=Number.EPSILON)&&(t=0),Math.abs(e.x-i.x)<t&&Math.abs(e.y-i.y)<t&&Math.abs(e.z-i.z)<t},i.fromAngle=function(e,t){return null==t&&(t=1),o=t,a=t*t,i.x=t*Math.cos(e),i.y=t*Math.sin(e),i.z=0,i},i.fromAngles=function(e,t,n){null==n&&(n=1),o=n,a=n*n;const r=Math.cos(t),l=MaM th.sin(t),s=Math.cos(e),h=Math.sin(e);return i.x=n*h*l,i.y=-n*s,i.z=n*h*r,i},i.random2D=function(){return o=1,a=1,i.fromAngle(Math.random()*Math.PI*2)},i.random3D=function(){return o=1,a=1,i.fromAngles(Math.random()*Math.PI*2,Math.random()*Math.PI*2)},i.toString=function(){return`[${i.x}, ${i.y}, ${i.z}]`}},n.Vector.add=function(e,t){return new n.Vector(e.x+t.x,e.y+t.y,e.z+t.z)},n.Vector.rem=function(e,t){return new n.Vector(e.x%t.x,e.y%t.y,e.z%t.z)},n.Vector.sub=function(e,t){return new n.Vector(e.x-t.x,e.y-t.y,e.M z-t.z)},n.Vector.mult=function(e,t){return null==t.x?new n.Vector(e.x*t,e.y*t,e.z*t):new n.Vector(e.x*t.x,e.y*t.y,e.z*t.z)},n.Vector.div=function(e,t){return null==t.x?new n.Vector(e.x/t,e.y/t,e.z/t):new n.Vector(e.x/t.x,e.y/t.y,e.z/t.z)},n.Vector.dist=function(e,t){return Math.hypot(e.x-t.x,e.y-t.y,e.z-t.z)},n.Vector.cross=function(e,t){return new n.Vector(e.y*t.z-e.z*t.y,e.z*t.x-e.x*t.z,e.x*t.y-e.y*t.x)},n.Vector.lerp=function(e,t,r){return new n.Vector(e.x*(1-r)+t.x*r,e.y=e.y*(1-r)+t.y*r,e.z=e.z*(1-r)+t.z*r)},n.M Vector.equals=function(e,t,n){return e.equals(t,n)};for(let e of["fromAngle","fromAngles","random2D","random3D"])n.Vector[e]=function(t,r,i){return(new n.Vector)[e](t,r,i)};function x(e,t,n){let r,i,o,a,l,s,h,c,u;if(0==t)return[255*(r=n),255*(i=n),255*(o=n)];switch((a=e)>360&&(a=0),h=n*(1-t),c=n*(1-t*(s=(a/=60)-(l=~~a))),u=n*(1-t*(1-s)),l){case 0:r=n,i=u,o=h;break;case 1:r=c,i=n,o=h;break;case 2:r=h,i=n,o=u;break;case 3:r=h,i=c,o=n;break;case 4:r=u,i=h,o=n;break;default:r=n,i=h,o=c}return[255*r,255*i,255*o]}functioM n g(){r.fillStyle="white",r.strokeStyle="black",r.lineCap="round",r.lineJoin="miter"}function p(e){if(0<=e&&e<2*Math.PI)return e;for(;e<0;)e+=2*Math.PI;for(;e>=Math.PI;)e-=2*Math.PI;return e}function m(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;let c=p(a),u=p(l);r.beginPath();for(let a=0;a<h+1;a++){let l=a/h,s=n.lerp(c,u,l),f=Math.cos(s)*i/2,d=Math.sin(s)*o/2;r[a?"lineTo":"moveTo"](e+f,t+d)}s==n.CHORD?r.closePath():s==n.PIE&&(r.lineTo(e,t),r.closePath()),n._style.noFill||r.fill(),n._style.noStrokM e||r.stroke()}function b(e,t,i,o){n._style.noFill&&n._style.noStroke||(r.beginPath(),r.ellipse(e,t,i/2,o/2,0,0,2*Math.PI),n._style.noFill||r.fill(),n._style.noStroke||r.stroke())}function y(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;if(null==a)return function(e,t,i,o){n._style.noFill||r.fillRect(e,t,i,o),n._style.noStroke||r.strokeRect(e,t,i,o)}(e,t,i,o);if(null==l)return y(e,t,i,o,a,a,a,a);const c=Math.min(Math.abs(o),Math.abs(i))/2;a=Math.min(c,a),l=Math.min(c,l),h=Math.min(c,h),s=Math.min(c,s)M ,r.beginPath(),r.moveTo(e+a,t),r.arcTo(e+i,t,e+i,t+o,l),r.arcTo(e+i,t+o,e,t+o,s),r.arcTo(e,t+o,e,t,h),r.arcTo(e,t,e+i,t,a),r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke()}function w(){a=[]}n.createVector=function(e,t,r){return new n.Vector(e,t,r)},n.curvePoint=function(e,t,n,r,i){const o=i*i*i,a=i*i;return e*(-.5*o+a-.5*i)+t*(1.5*o-2.5*a+1)+n*(-1.5*o+2*a+.5*i)+r*(.5*o-.5*a)},n.bezierPoint=function(e,t,n,r,i){const o=1-i;return Math.pow(o,3)*e+3*Math.pow(o,2)*i*t+3*o*Math.pow(i,2)*n+Math.pow(i,M 3)*r},n.curveTangent=function(e,t,n,r,i){const o=i*i;return e*(-3*o/2+2*i-.5)+t*(9*o/2-5*i)+n*(-9*o/2+4*i+.5)+r*(3*o/2-i)},n.bezierTangent=function(e,t,n,r,i){const o=1-i;return 3*r*Math.pow(i,2)-3*n*Math.pow(i,2)+6*n*o*i-6*t*o*i+3*t*Math.pow(o,2)-3*e*Math.pow(o,2)},n.Color=function(e,t,n,r){let i=this;i.MAGIC=786698,i._r=e,i._g=t,i._b=n,i._a=r,i._h=0,i._s=0,i._v=0,i._hsvInferred=!1,i.setRed=function(e){i._r=e,i._hsvInferred=!1},i.setGreen=function(e){i._g=e,i._hsvInferred=!1},i.setBlue=function(e){i._b=e,i._hsvInfM erred=!1},i.setAlpha=function(e){i._a=e/255,i._hsvInferred=!1},i._inferHSV=function(){i._hsvInferred||([i._h,i._s,i._v]=function(e,t,n){let r,i,o,a,l;return r=e<t?e<n?e:n:t<n?t:n,0==(l=100*(i=e>t?e>n?e:n:t>n?t:n)/255)?[o=0,a=0,l]:0==(a=100*(i-r)/i)?[o=0,a,l]:(o=i==e?0+60*(t-n)/(i-r):i==t?120+60*(n-e)/(i-r):240+60*(e-t)/(i-r),[o,a,l])}(i._r,i._g,i._b),i._hsvInferred=!0)},i.toString=function(){return`rgba(${Math.round(i._r)},${Math.round(i._g)},${Math.round(i._b)},${~~(1e3*i._a)/1e3})`}},n.colorMode=function(e){n._stM yle.colorMode=e},n.color=function(){if(1==arguments.length&&786698==arguments[0].MAGIC)return arguments[0];if(n._style.colorMode==n.RGB){if(1==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],1);if(2==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],arguments[1]/255);if(3==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],1);if(4==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],arguments[3]/255)}else{if(1==argumeM nts.length)return new n.Color(...x(0,0,arguments[0]/100),1);if(2==arguments.length)return new n.Color(...x(0,0,arguments[0]/100),arguments[1]/255);if(3==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),1);if(4==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),arguments[3])}return null},n.red=function(e){return e._r},n.green=function(e){return e._g},n.blue=function(e){return e._b},n.alpha=function(e){return 255*e._a},n.hue=function(e){reM turn e._inferHSV(),e._h},n.saturation=function(e){return e._inferHSV(),e._s},n.brightness=function(e){return e._inferHSV(),e._v},n.lightness=function(e){return 100*(.2126*e._r+.7152*e._g+.0722*e._b)/255},n.lerpColor=function(e,t,r){return n._style.colorMode==n.RGB?new n.Color(n.constrain(n.lerp(e._r,t._r,r),0,255),n.constrain(n.lerp(e._g,t._g,r),0,255),n.constrain(n.lerp(e._b,t._b,r),0,255),n.constrain(n.lerp(e._a,t._a,r),0,1)):(e._inferHSV(),t._inferHSV(),new n.Color(n.constrain(function(e,t,r){var i=[[Math.abs(t-M e),n.map(r,0,1,e,t)],[Math.abs(t+360-e),n.map(r,0,1,e,t+360)],[Math.abs(t-360-e),n.map(r,0,1,e,t-360)]];return i.sort(((e,t)=>e[0]-t[0])),(i[0][1]+720)%360}(e._h,t._h,r),0,360),n.constrain(n.lerp(e._s,t._s,r),0,100),n.constrain(n.lerp(e._v,t._v,r),0,100),n.constrain(n.lerp(e._a,t._a,r),0,1)))},n.strokeWeight=function(e){n._style_noStroke=!1,r.lineWidth=e},n.stroke=function(){if(n._style.noStroke=!1,"string"==typeof arguments[0])return void(r.strokeStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._sM tyle.noStroke=!0:r.strokeStyle=e},n.noStroke=function(){n._style.noStroke=!0},n.fill=function(){if(n._style.noFill=!1,"string"==typeof arguments[0])return void(r.fillStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._style.noFill=!0:r.fillStyle=e},n.noFill=function(){n._style.noFill=!0},n.blendMode=function(e){r.globalCompositeOperation=e},n.strokeCap=function(e){r.lineCap=e},n.strokeJoin=function(e){r.lineJoin=e},n.ellipseMode=function(e){n._style.ellipseMode=e},n.rectMode=function(e){n._style.rectM Mode=e},n.curveDetail=function(e){n._style.curveDetail=e},n.curveAlpha=function(e){n._style.curveAlpha=e},n.curveTightness=function(e){n._style.curveAlpha=e},n.clear=function(){r.clearRect(0,0,n.width,n.height)},n.background=function(){if(arguments[0]&&arguments[0].MAGIC==n.MAGIC)return n.image(arguments[0],0,0,n.width,n.height);r.save(),r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity),r.fillStyle="string"==typeof arguments[0]?arguments[0]:n.color(...Array.from(arguments)),r.fillRect(0,0,n.width,n.heightM ),r.restore()},n.line=function(e,t,i,o){n._style.noStroke||(r.beginPath(),r.moveTo(e,t),r.lineTo(i,o),r.stroke())},n.arc=function(e,t,r,i,o,a,l,s){if(o==a)return n.ellipse(e,t,r,i);null==s&&(s=25),null==l&&(l=n.PIE),n._style.ellipseMode==n.CENTER?m(e,t,r,i,o,a,l,s):n._style.ellipseMode==n.RADIUS?m(e,t,2*r,2*i,o,a,l,s):n._style.ellipseMode==n.CORNER?m(e+r/2,t+i/2,r,i,o,a,l,s):n._style.ellipseMode==n.CORNERS&&m((e+r)/2,(t+i)/2,r-e,i-t,o,a,l,s)},n.ellipse=function(e,t,r,i){null==i&&(i=r),n._style.ellipseMode==n.CENTERM ?b(e,t,r,i):n._style.ellipseMode==n.RADIUS?b(e,t,2*r,2*i):n._style.ellipseMode==n.CORNER?b(e+r/2,t+i/2,r,i):n._style.ellipseMode==n.CORNERS&&b((e+r)/2,(t+i)/2,r-e,i-t)},n.circle=function(e,t,r){return n.ellipse(e,t,r,r)},n.point=function(e,t){e.x&&(t=e.y,e=e.x),r.beginPath(),r.ellipse(e,t,.4,.4,0,0,2*Math.PI),r.stroke()},n.rect=function(e,t,r,i,o,a,l,s){n._style.rectMode==n.CENTER?y(e-r/2,t-i/2,r,i,o,a,l,s):n._style.rectMode==n.RADIUS?y(e-r,t-i,2*r,2*i,o,a,l,s):n._style.rectMode==n.CORNER?y(e,t,r,i,o,a,l,s):n._stylM e.rectMode==n.CORNERS&&y(e,t,r-e,i-t,o,a,l,s)},n.square=function(e,t,r,i,o,a,l){return n.rect(e,t,r,r,i,o,a,l)},n.beginShape=function(){w(),r.beginPath(),o=!0},n.beginContour=function(){r.closePath(),w(),o=!0},n.endContour=function(){w(),o=!0},n.vertex=function(e,t){w(),o?r.moveTo(e,t):r.lineTo(e,t),o=!1},n.bezierVertex=function(e,t,n,i,o,a){w(),r.bezierCurveTo(e,t,n,i,o,a)},n.quadraticVertex=function(e,t,n,i){w(),r.quadraticCurveTo(e,t,n,i)},n.bezier=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.bezierVM ertex(r,i,o,a,l,s),n.endShape()},n.triangle=function(e,t,r,i,o,a){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.endShape(n.CLOSE)},n.quad=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.vertex(l,s),n.endShape(n.CLOSE)},n.endShape=function(e){w(),e&&r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke(),n._style.noFill&&n._style.noStroke&&(r.save(),r.fillStyle="none",r.fill(),r.restore())},n.curveVertex=function(e,t){if(a.push([e,t]),a.length<4)return;M let i=function(e,t,n,r,i,o,a,l,s,h){function c(e,t,n,r,i,o){let a=Math.pow(r-t,2)+Math.pow(i-n,2);return Math.pow(a,.5*o)+e}let u=[],f=c(0,e,t,n,r,h),d=c(f,n,r,i,o,h),x=c(d,i,o,a,l,h);for(let h=0;h<s;h++){let c=f+h/(s-1)*(d-f),g=[(f-c)/(f-0),(c-0)/(f-0),(d-c)/(d-f),(c-f)/(d-f),(x-c)/(x-d),(c-d)/(x-d),(d-c)/(d-0),(c-0)/(d-0),(x-c)/(x-f),(c-f)/(x-f)];for(let e=0;e<g.length;e+=2)isNaN(g[e])&&(g[e]=1,g[e+1]=0),isFinite(g[e])||(g[e]>0?(g[e]=1,g[e+1]=0):(g[e]=0,g[e+1]=1));let p=e*g[0]+n*g[1],m=t*g[0]+r*g[1],b=n*g[2]+i*g[M 3],y=r*g[2]+o*g[3],w=i*g[4]+a*g[5],v=o*g[4]+l*g[5],z=p*g[6]+b*g[7],V=m*g[6]+y*g[7],_=b*g[8]+w*g[9],M=y*g[8]+v*g[9],E=z*g[2]+_*g[3],S=V*g[2]+M*g[3];u.push([E,S])}return u}(...a[a.length-4],...a[a.length-3],...a[a.length-2],...a[a.length-1],n._style.curveDetail,n._style.curveAlpha);for(let e=0;e<i.length;e++)o?r.moveTo(...i[e]):r.lineTo(...i[e]),o=!1},n.curve=function(e,t,r,i,o,a,l,s){n.beginShape(),n.curveVertex(e,t),n.curveVertex(r,i),n.curveVertex(o,a),n.curveVertex(l,s),n.endShape()},n.translate=function(e,t){r.tM ranslate(e,t)},n.rotate=function(e){r.rotate(e)},n.scale=function(e,t){null==t&&(t=e),r.scale(e,t)},n.applyMatrix=function(e,t,n,i,o,a){r.transform(e,t,n,i,o,a)},n.shearX=function(e){r.transform(1,0,Math.tan(e),1,0,0)},n.shearY=function(e){r.transform(1,Math.tan(e),0,1,0,0)},n.resetMatrix=function(){r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity)},n.pushMatrix=n.push=function(){n._styleCache.push({...n._style}),n._style=n._styleCache[n._styleCache.length-1],r.save()},n.popMatrix=n.pop=function(){n._stylM eCache.length-1&&(n._styleCache.pop(),n._style=n._styleCache[n._styleCache.length-1],r.restore())},n.image=function(e,t,i,o,a,l,s,h,c){let u=e.MAGIC==n.MAGIC?e.canvas:e;function d(){if(e.MAGIC!=n.MAGIC||!n._tint)return;let t=e.canvas.getContext("2d");t.save(),t.resetTransform(),t.clearRect(0,0,t.canvas.width,t.canvas.height),t.drawImage(f.canvas,0,0),t.restore()}return e.MAGIC==n.MAGIC&&null!=n._tint&&(function(e,t){null==f&&(f=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvasM .height),f.canvas.width==e&&f.canvas.height==t||(f.canvas.width=e,f.canvas.height=t)}(e.canvas.width,e.canvas.height),f.drawImage(e.canvas,0,0),e.tinted(n._tint)),o?l?(h||(h=u.width),c||(c=u.height),r.drawImage(u,l,s,h,c,t,i,o,a),void d()):(r.drawImage(u,t,i,o,a),void d()):(e.MAGIC==n.MAGIC||e.width?r.drawImage(u,t,i,e.width,e.height):r.drawImage(u,t,i,e.videoWidth,e.videoHeight),void d())},n.loadPixels=function(){l=r.getImageData(0,0,n.canvas.width,n.canvas.height),n.pixels=l.data},n.updatePixels=function(){null!=M l&&r.putImageData(l,0,0)},n.loadImage=function(e,t){s++;let r=n.createGraphics(100,100),i=r.canvas.getContext("2d"),o=new Image;return o.src=e,o.crossOrigin="Anonymous",o.onload=function(){i.canvas.width=o.width,i.canvas.height=o.height,r.width=o.width,r.height=o.height,i.drawImage(o,0,0),s--,t&&t(r)},r};let v={};function z(e,t){null==u&&(u=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvas.height),u.canvas.width==e&&u.canvas.height==t||(u.canvas.width=e,u.canvas.height=t)}funcM tion V(){let e=r.canvas.width*r.canvas.height*4;null!=d&&e==d.length||(d=new Uint8ClampedArray(e))}function _(e){u.clearRect(0,0,u.canvas.width,u.canvas.height),u.filter=e,u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()}v[n.THRESHOLD]=function(e,t){null==t?t=127.5:t*=255;for(let n=0;n<e.length;n+=4){const r=.2126*e[n]+.7152*e[n+1]+.0722*e[n+2];e[n]=e[n+1]=e[n+2]=r>=t?255:0}},v[n.GRAY]=function(e){for(let t=0;t<e.length;t+=4)M {const n=.2126*e[t]+.7152*e[t+1]+.0722*e[t+2];e[t]=e[t+1]=e[t+2]=n}},v[n.OPAQUE]=function(e){for(let t=0;t<e.length;t+=4)e[t+3]=255},v[n.INVERT]=function(e){for(let t=0;t<e.length;t+=4)e[t]=255-e[t],e[t+1]=255-e[t+1],e[t+2]=255-e[t+2]},v[n.POSTERIZE]=function(e,t){let n=t-1;for(let r=0;r<e.length;r+=4)e[r]=255*(e[r]*t>>8)/n,e[r+1]=255*(e[r+1]*t>>8)/n,e[r+2]=255*(e[r+2]*t>>8)/n},v[n.DILATE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-M 1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.max(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.ERODE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.min(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.BLURM ]=function(e,t){t=t||1,t=Math.floor(t*n._pixelDensity),V(),d.set(e);let i=2*t+1,o=function(e){let n=new Float32Array(e),r=.3*t+.8,i=r*r*2;for(let t=0;t<e;t++){let o=t-e/2,a=Math.exp(-o*o/i)/(2.5066282746*r);n[t]=a}return n}(i),[a,l]=[r.canvas.width,r.canvas.height];for(let n=0;n<l;n++)for(let r=0;r<a;r++){let l=0,s=0,h=0,c=0;for(let e=0;e<i;e++){let i=4*(n*a+Math.min(Math.max(r-t+e,0),a-1));l+=d[i]*o[e],s+=d[i+1]*o[e],h+=d[i+2]*o[e],c+=d[i+3]*o[e]}let u=4*(n*a+r);e[u]=l,e[u+1]=s,e[u+2]=h,e[u+3]=c}d.set(e);for(let nM =0;n<l;n++)for(let r=0;r<a;r++){let s=0,h=0,c=0,u=0;for(let e=0;e<i;e++){let i=4*(Math.min(Math.max(n-t+e,0),l-1)*a+r);s+=d[i]*o[e],h+=d[i+1]*o[e],c+=d[i+2]*o[e],u+=d[i+3]*o[e]}let f=4*(n*a+r);e[f]=s,e[f+1]=h,e[f+2]=c,e[f+3]=u}},n.filter=function(e,t){if(n.HARDWARE_FILTERS&&null!=r.filter)if(z(),e==n.THRESHOLD){null==t&&(t=.5),t=Math.max(t,1e-5),_(`saturate(0%) brightness(${Math.floor(.5/t*100)}%) contrast(1000000%)`)}else if(e==n.GRAY)_("saturate(0%)");else if(e==n.OPAQUE)u.fillStyle="black",u.fillRect(0,0,u.canvaM s.width,u.canvas.height),u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.drawImage(u.canvas,0,0),r.restore();else if(e==n.INVERT)_("invert(100%)");else if(e==n.BLUR)_(`blur(${Math.ceil(t*n._pixelDensity/1)||1}px)`);else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}},n.resize=function(e,t){z(),u.drawImage(r.canvas,0,0),n.width=e,n.height=t,r.canvas.width=e*n._pixM elDensity,r.canvas.height=t*n._pixelDensity,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0,r.canvas.width,r.canvas.height),r.restore()},n.get=function(e,t,i,o){if(null!=e&&null==i){let i=r.getImageData(e,t,1,1).data;return new n.Color(i[0],i[1],i[2],i[3]/255)}e=e||0,t=t||0,i=i||n.width,o=o||n.height;let a=n.createGraphics(i,o);a.pixelDensity(n._pixelDensity);let l=r.getImageData(e*n._pixelDensity,t*n._pixelDensity,i*n._pixelDensity,o*n._pixelDensity);return a.caM nvas.getContext("2d").putImageData(l,0,0),a},n.set=function(e,t,i){if(i.MAGIC==n.MAGIC){let r=n._tint;return n._tint=null,n.image(i,e,t),void(n._tint=r)}let o=4*(t*n._pixelDensity*r.canvas.width+e*n._pixelDensity);n.pixels[o]=i._r,n.pixels[o+1]=i._g,n.pixels[o+2]=i._b,n.pixels[o+3]=255*i._a},n.tinted=function(){let e=n.color(...Array.from(arguments)),t=e._a;e._a=1,z(),u.clearRect(0,0,u.canvas.width,u.canvas.height),u.fillStyle=e,u.fillRect(0,0,u.canvas.width,u.canvas.height),u.globalCompositeOperation="multiply",u.M drawImage(r.canvas,0,0),u.globalCompositeOperation="source-over",r.save(),r.resetTransform();let i=r.globalCompositeOperation;r.globalCompositeOperation="source-in",r.drawImage(u.canvas,0,0),r.globalCompositeOperation=i,r.restore(),u.globalAlpha=t,u.clearRect(0,0,u.canvas.width,u.canvas.height),u.drawImage(r.canvas,0,0),u.globalAlpha=1,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()},n.tint=function(){n._tint=n.color(...Array.from(arguments))},n.noTiM nt=function(){n._tint=null},n.mask=function(e){r.save(),r.resetTransform();let t=r.globalCompositeOperation;r.globalCompositeOperation="destination-in",r.drawImage(e.canvas,0,0),r.globalCompositeOperation=t,r.restore()},n.clearTemporaryBuffers=function(){u=null,f=null,d=null},n.save=function(e,t){e=e||"untitled",t=t||"png";var n=document.createElement("a");n.innerHTML="[Download]",n.addEventListener("click",(function(){this.href=r.canvas.toDataURL(),this.download=e+"."+t}),!1),document.body.appendChild(n),n.click()M ,document.body.removeChild(n)},n.saveCanvas=function(e,t,r){if(e.MAGIC==n.MAGIC){r&&e.save(t,r);let n=t.split(".");return e.save(n.slice(0,-1).join("."),n[n.length-1])}if(t)return n.save(e,t);let i=e.split(".");return n.save(i.slice(0,-1).join("."),i[i.length-1])},n.loadFont=function(e){let t=e.split("/"),n=t[t.length-1].split(".")[0].replace(" ",""),r=`@font-face {\n font-family: '${n}';\n src: url('${e}');\n }`;const i=document.createElement("style");return i.textContent=r,document.head.append(M i),n},n.textFont=function(e){n._style.textFont=e},n.textSize=function(e){n._style.textSize=e,n._style.textLeading=e},n.textLeading=function(e){n._style.textLeading=e},n.textStyle=function(e){n._style.textStyle=e},n.textAlign=function(e,t){r.textAlign=e,t&&(r.textBaseline=t==n.CENTER?"middle":t)},n.text=function(e,t,i,o){if(!e)return;if(e=e.toString(),n._style.noFill&&n._style.noStroke)return;r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`;let a=e.split("\n");for(let e=0;e<a.length;e++)n._M style.noFill||r.fillText(a[e],t,i,o),n._style.noStroke||r.strokeText(a[e],t,i,o),i+=n._style.textLeading},n.textWidth=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).width},n.textAscent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBoundingBoxAscent},n.textDescent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBounM dingBoxDescent};var M,E=4,S=.5,R=function(e){return.5*(1-Math.cos(e*Math.PI))};n.noise=function(e,t,n){if(t=t||0,n=n||0,null==M){M=new Array(4096);for(var r=0;r<4096;r++)M[r]=Math.random()}e<0&&(e=-e),t<0&&(t=-t),n<0&&(n=-n);for(var i,o,a,l,s,h=Math.floor(e),c=Math.floor(t),u=Math.floor(n),f=e-h,d=t-c,x=n-u,g=0,p=.5,m=0;m<E;m++){var b=h+(c<<4)+(u<<8);i=R(f),o=R(d),a=M[4095&b],a+=i*(M[b+1&4095]-a),l=M[b+16&4095],a+=o*((l+=i*(M[b+16+1&4095]-l))-a),l=M[4095&(b+=256)],l+=i*(M[b+1&4095]-l),s=M[b+16&4095],l+=o*((s+=i*(M[M b+16+1&4095]-s))-l),g+=(a+=R(x)*(l-a))*p,p*=S,h<<=1,c<<=1,u<<=1,(f*=2)>=1&&(h++,f--),(d*=2)>=1&&(c++,d--),(x*=2)>=1&&(u++,x--)}return g},n.noiseDetail=function(e,t){e>0&&(E=e),t>0&&(S=t)};const I=function(){let e,t,n=4294967295;return{setSeed(r){e=t=(null==r?Math.random()*n:r)>>>0},getSeed:()=>t,rand:()=>(e^=e<<17,e^=e>>13,((e^=e<<5)>>>0)/n)}};let C=I();C.setSeed(),n.noiseSeed=function(e){let t=null==e?4294967295*Math.random():e;M||(M=new Float32Array(4096));for(var n=0;n<4096;n++)t^=t<<17,t^=t>>13,t^=t<<5,M[n]=(t>M >>0)/4294967295},n.randomSeed=function(e){C.setSeed(e)},n.random=function(e,t){return null==e?C.rand():"number"==typeof e?null!=t?C.rand()*(t-e)+e:C.rand()*e:e[~~(e.length*C.rand())]},n.randomGenerator=function(e){e==n.LCG?C=function(){const e=4294967296;let t,n;return{setSeed(r){n=t=(null==r?Math.random()*e:r)>>>0},getSeed:()=>t,rand:()=>(n=(1664525*n+1013904223)%e)/e}}():e==n.SHR3&&(C=I()),C.setSeed()};var T=new function(){var e,t,n,r=new Array(128),i=new Array(256),o=new Array(128),a=new Array(128),l=new Array(2M 56),s=new Array(256),h=function(){return 4294967296*C.rand()-2147483648},c=function(){return.5+2.328306e-10*(h()<<0)};this.SHR3=h,this.UNI=c,this.RNOR=function(){return n=h(),e=127&n,Math.abs(n)<r[e]?n*o[e]:function(){for(var t,i,l,s,u=3.44262;;){if(t=n*o[e],0==e){do{l=c(),s=c(),t=.2904764*-Math.log(l),i=-Math.log(s)}while(i+i<t*t);return n>0?u+t:-u-t}if(a[e]+c()*(a[e-1]-a[e])<Math.exp(-.5*t*t))return t;if(n=h(),e=127&n,Math.abs(n)<r[e])return n*o[e]}}()},this.REXP=function(){return(t=h()>>>0)<r[e=255&t]?t*l[e]:funM ction(){for(var n;;){if(0==e)return 7.69711-Math.log(c());if(n=t*l[e],s[e]+c()*(s[e-1]-s[e])<Math.exp(-n))return n;if((t=h())<i[e=255&t])return t*l[e]}}()},this.zigset=function(){var e,t,n=2147483648,h=4294967296,c=3.442619855899,u=c,f=.00991256303526217,d=7.697117470131487,x=d,g=.003949659822581572;for(e=f/Math.exp(-.5*c*c),r[0]=Math.floor(c/e*n),r[1]=0,o[0]=e/n,o[127]=c/n,a[0]=1,a[127]=Math.exp(-.5*c*c),t=126;t>=1;t--)c=Math.sqrt(-2*Math.log(f/c+Math.exp(-.5*c*c))),r[t+1]=Math.floor(c/u*n),u=c,a[t]=Math.exp(-.5*cM *c),o[t]=c/n;for(e=g/Math.exp(-d),i[0]=Math.floor(d/e*h),i[1]=0,l[0]=e/h,l[255]=d/h,s[0]=1,s[255]=Math.exp(-d),t=254;t>=1;t--)d=-Math.log(g/d+Math.exp(-d)),i[t+1]=Math.floor(d/x*h),x=d,s[t]=Math.exp(-d),l[t]=d/h}};T.hasInit=!1,n.randomGaussian=function(e,t){return T.hasInit||(T.zigset(),T.hasInit=!0),T.RNOR()*t+e},n.randomExponential=function(){return T.hasInit||(T.zigset(),T.hasInit=!0),T.REXP()},n.print=console.log,n.cursor=function(e,t,r){let i="";e.includes(".")&&(e=`url("${e}")`,i=", auto"),null!=t&&(e+=" "+t+M " "+r),n.canvas.style.cursor=e+i},n.noCursor=function(){n.canvas.style.cursor="none"},n.createCapture=function(e){var t=document.createElement("video");return t.playsinline="playsinline",t.autoplay="autoplay",navigator.mediaDevices.getUserMedia(e).then((function(e){t.srcObject=e})),t.style.position="absolute",t.style.opacity=1e-5,t.style.zIndex=-1e3,document.body.appendChild(t),t};let A=["setup","draw","preload","mouseMoved","mousePressed","mouseReleased","mouseDragged","mouseClicked","keyPressed","keyReleased","keM yTyped","touchStarted","touchEnded"];for(let e of A){let t="_"+e+"Fn";n[t]=function(){},n[t].isPlaceHolder=!0,n[e]?n[t]=n[e]:Object.defineProperty(n,e,{set:function(e){n[t]=e}})}function D(){n._noLoop||(i=null==n._frameRate?requestAnimationFrame(D):setTimeout(D,1e3/n._frameRate)),w(),o=!0,n.push(),n._drawFn(),n.pop(),++n.frameCount}function k(e){const t=n.canvas.getBoundingClientRect(),r=n.canvas.scrollWidth/n.width||1,i=n.canvas.scrollHeight/n.height||1;return{x:(e.clientX-t.left)/r,y:(e.clientY-t.top)/i,id:e.idenM tifier}}function L(){return n._touchStarted.isPlaceHolder&&n._touchMoved.isPlaceHolder&&n._touchEnded.isPlaceHolder}n.noLoop=function(){n._noLoop=!0,i=null},n.loop=function(){n._noLoop=!1,null==i&&D()},n.redraw=function(){D()},n.frameRate=function(e){n._frameRate=e},setTimeout((function(){n._preloadFn(),c=window.performance.now(),function e(){if(s>0)return setTimeout(e,10);n._setupFn(),D()}()}),1),n.canvas.onmousemove=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPM ressed?n._mouseDraggedFn(e):n._mouseMovedFn(e)},n.canvas.onmousedown=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!0,n.mouseButton=[n.LEFT,n.CENTER,n.RIGHT][e.button],n._mousePressedFn(e)},n.canvas.onmouseup=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!1,n._mouseReleasedFn(e)},n.canvas.onclick=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressedM =!0,n._mouseClickedFn(e),n.mouseIsPressed=!1},window.addEventListener("keydown",(function(e){n.keyIsPressed=!0,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!0,n._keyPressedFn(e),1==e.key.length&&n._keyTypedFn(e)})),window.addEventListener("keyup",(function(e){n.keyIsPressed=!1,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!1,n._keyReleasedFn(e)})),n.keyIsDown=function(e){return!!h[e]},n.canvas.ontouchstart=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.moM useY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mousePressedFn(e)||e.preventDefault()),n._touchStartedFn(e)||e.preventDefault()},n.canvas.ontouchmove=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mouseDraggedFn(e)||e.preventDefault()),n._touchMovedFn(e)||e.preventDefault()},n.canvas.ontouchend=n.canvas.ontouchcancel=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.M mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!1,n._mouseReleasedFn(e)||e.preventDefault()),n._touchEndedFn(e)||e.preventDefault()},n.hasSensorPermission=!window.DeviceOrientationEvent&&!window.DeviceMotionEvent||!(DeviceOrientationEvent.requestPermission||DeviceMotionEvent.requestPermission),n.requestSensorPermissions=function(){DeviceOrientationEvent.requestPermission&&DeviceOrientationEvent.requestPermission().then((e=>{"granted"==e&&DeviceMotionEvent.requestPermissioM n&&DeviceMotionEvent.requestPermission().then((e=>{"granted"==e&&(n.hasSensorPermission=!0)})).catch(alert)})).catch(alert)},window.ondeviceorientation=function(e){n.pRotationX=n.rotationX,n.pRotationY=n.rotationY,n.pRotationZ=n.rotationZ,n.pRelRotationX=n.relRotationX,n.pRelRotationY=n.relRotationY,n.pRelRotationZ=n.relRotationZ,n.rotationX=e.beta*(Math.PI/180),n.rotationY=e.gamma*(Math.PI/180),n.rotationZ=e.alpha*(Math.PI/180),n.relRotationX=[-n.rotationY,-n.rotationX,n.rotationY][1+~~(window.orientation/90)],n.rM elRotationY=[-n.rotationX,n.rotationY,n.rotationX][1+~~(window.orientation/90)],n.relRotationZ=n.rotationZ},window.ondevicemotion=function(e){if(n.pAccelerationX=n.accelerationX,n.pAccelerationY=n.accelerationY,n.pAccelerationZ=n.accelerationZ,!e.acceleration){let t=((e,t)=>[(e[0]*t[0]+e[1]*t[1]+e[2]*t[2]+e[3])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[4]*t[0]+e[5]*t[1]+e[6]*t[2]+e[7])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[8]*t[0]+e[9]*t[1]+e[10]*t[2]+e[11])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15])])(((e,t)M =>[e[0]*t[0]+e[1]*t[4]+e[2]*t[8]+e[3]*t[12],e[0]*t[1]+e[1]*t[5]+e[2]*t[9]+e[3]*t[13],e[0]*t[2]+e[1]*t[6]+e[2]*t[10]+e[3]*t[14],e[0]*t[3]+e[1]*t[7]+e[2]*t[11]+e[3]*t[15],e[4]*t[0]+e[5]*t[4]+e[6]*t[8]+e[7]*t[12],e[4]*t[1]+e[5]*t[5]+e[6]*t[9]+e[7]*t[13],e[4]*t[2]+e[5]*t[6]+e[6]*t[10]+e[7]*t[14],e[4]*t[3]+e[5]*t[7]+e[6]*t[11]+e[7]*t[15],e[8]*t[0]+e[9]*t[4]+e[10]*t[8]+e[11]*t[12],e[8]*t[1]+e[9]*t[5]+e[10]*t[9]+e[11]*t[13],e[8]*t[2]+e[9]*t[6]+e[10]*t[10]+e[11]*t[14],e[8]*t[3]+e[9]*t[7]+e[10]*t[11]+e[11]*t[15],e[12]*t[0]+M e[13]*t[4]+e[14]*t[8]+e[15]*t[12],e[12]*t[1]+e[13]*t[5]+e[14]*t[9]+e[15]*t[13],e[12]*t[2]+e[13]*t[6]+e[14]*t[10]+e[15]*t[14],e[12]*t[3]+e[13]*t[7]+e[14]*t[11]+e[15]*t[15]])((e=>[Math.cos(e),0,Math.sin(e),0,0,1,0,0,-Math.sin(e),0,Math.cos(e),0,0,0,0,1])(n.rotationY),(e=>[1,0,0,0,0,Math.cos(e),-Math.sin(e),0,0,Math.sin(e),Math.cos(e),0,0,0,0,1])(n.rotationX)),[0,0,-9.80665]);n.accelerationX=e.accelerationIncludingGravity.x+t[0],n.accelerationY=e.accelerationIncludingGravity.y+t[1],n.accelerationZ=e.accelerationIncludM ingGravity.z-t[2]}},n.year=function(){return(new Date).getFullYear()},n.day=function(){return(new Date).getDay()},n.hour=function(){return(new Date).getHours()},n.minute=function(){return(new Date).getMinutes()},n.second=function(){return(new Date).getSeconds()},n.millis=function(){return window.performance.now()-c}}(e)}"object"==typeof exports&&"undefined"!=typeof module&&(module.exports=e);const t="https://ancient-crimson-rain.btc.discover.quiknode.pro/c268fb026303ae8443f785200f2ea4b82f0082dd";function n(e){P(e)?M localStorage.removeItem("blocksApiEndpoint"):localStorage.blocksApiEndpoint=e}function r(){return localStorage.blocksApiEndpoint||t}function i(e){P(e)?localStorage.removeItem("modelInscriptionEndpoint"):localStorage.modelInscriptionEndpoint=e}function o(){return localStorage.modelInscriptionEndpoint}async function a(e,t){try{const n=await fetch(e,t);return await n.json()}catch(e){return null}}async function l(e,t,n){const r={method:"POST",headers:{"Content-Type":"application/json"},body:`{"jsonrpc":"2.0","id":1,"meM thod":"${t}","params":${`[${n.join(sep=",")}]`}}`};return(await a(e,r))?.result}async function s(e){const n={avgfee:10,time:Date.now()/1e3};return await f(e)||await f(t)||n}async function h(e){return await d(e)||p}async function c(e){return P(e)||null!=await f(e)}async function u(e){return P(e)||null!=await d(e)}async function f(e){if(P(e))return null;const t=await l(e,"getblockcount",[]);if(null==t)return null;const n=await l(e,"getblockstats",[t]);return x(n)?n:null}async function d(e){if(P(e))return null;const tM =await a(e,{});return g(t)?t:null}function x(e){return"number"==typeof e?.time&&"number"==typeof e?.avgfee}function g(e){if(null==e)return!1;const{classes_name:t,training_traits:n,layers_config:r,weight_b64:i}=e;if(!Array.isArray(t))return!1;if(null==n)return!1;try{j(r,i)}catch(e){return!1}return!0}const p={"model_name": "pfp_classifier_470", "layers_config": {"config": {"layers": [{"class_name": "InputLayer", "config": {"batch_input_shape": [null, 28, 28, 3]}}, {"class_name": "Rescaling", "config": {"scale": 0.007M 84313725490196, "offset": -1}}, {"class_name": "Flatten"}, {"class_name": "Dense", "config": {"units": 20, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 17, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 14, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 3, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 4, "activation": "linear"}}]}}, "weight_b64": "8mpxOpqmH72wvak7SRpZu00V1LvkyX49/aKyOncTj7xz4CW9EaQQvbY2vbz9X4g9vEbAvHOgDr3vgju9ZldM 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 5KHg914psvR9vxLwuUhM9r00YvelYA7xdCgA93bKhu26fBj1FwY27GNqZvCU72Tv6Tgk9gCiQPRkydTzc8Ws8u5xyvHgL8zwk+lq9tqWnvbV+GL3N9h88nBeTPKdRu7wur3S8d3nsvGcbgjyWtGK8FgnJPEeitz3CZYO9ZSn8uzqHW70MuHE9Si2EO0qeUL0LFO8744BSPScZIrwjkeE8t1nuO9GNi7xMU2W9ej4CPVMjArxn/447w9h4vPSxE70LSBa9NyWOvBK1RL11sKo8K/hRPZEJWTwGSXG9dnFpPJad+LyH/ag8tRA3PZEzpz1l6cI8PnHGvaX0O7rNqQ897dIcPI2+Az1hvIA8gjL1u6NBv7t2VsW5wxH/vLIP47smELI8pKNKPQ3YET0IoMK8p0XxOlEwxjwzHhm9gADBvTO72Lx8pum78llFPK/Ts7yemXI9Iq7Du8/mPbyBWoK82YpBPETdtD3H66C9Yz8OuW6/ILyJbfo8BMBYu0EE1zuKJuY78sfM 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 54uS8psfwvGEiz7zlg0i8F0DdPGaY8jm4shE8n3h9PZVTJbxFIHA9G3jiuxxwiLoRcrO84pmIPYsWlzw7fBs9qnKUvPSHFTx0oQU9a/zpvOxv7r2Qjd09QodcvEJ71zxrZqE8MdtTPQhbI7xJtQA92l6vvN1npDut2G4952SkvRbUDLyoSIs9HjvzO5+2uTwpkFC8ZMCAvfiblbyxvSk9T7MUPMrxD712tMW8iavTvLOZdDxCxm28NolIvRlzXD06mRQ9FYkvvR/cgb3pMDE9QXYbvXIm7zxiZoQ9Ys+LPO0sJj1T20K9BS8tPc1kGT221I29Gcimu/UOEb3CVXo9ijbBvORcDTwUpTE8e97APafJurtDHkw90YoLvcWvPD3w3Sm9DPrFPfYZx7uxBYs9mlLYvNf0CbyWvcu8PXqmvHD5cL3MhZ89qe+NPdvQjTzP3pS6A3g2PEdCwDwSRZ487nxVvMMgbj1lelQ8rOyCvGu70TwOIpA9Rt4YvP3GYj2kIRg9w1tM 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 EvXGFWz038407AVQwvfDN9jxCaZK9fg8IvaXiVz0T75q9cYGpvSDJGr2qJMM7VL0YPUFhir3Zt069GhzBPQomI738PXc8HvFjPEQDGz3Y++e8CHfPPd/7gTxsKbE6uG4uvKROjT3v7Wi89L1tvfZIl70uSrg9rEglPRp3g7ssopQ79rGIPMCLST3tMpM6l31UvQZBdT2urbg8WMVXvQ5BrzrkV166/AL9POeMgz338x29ZuRfPDReYrz/cRe96RdmPBS2ib1pdSu9WoNhPQgFxLz9m8m8aqRMveWx7z2Uk6c8IuIBvmuykzx19lA8zPpbvGc5QjsVjKu8ozqUvFtpkDznRG69zpQ1vekhJj2shjC9sF+nvZl2PTzFgY68F5NYPXiIer2btLW83HeCPQMa2jsA3+o8Cb1TvKnTJTyN+4C9Kba4PfTbPLy0nmk9Gif1vMSNY7vlcRi8ojAnvJaAAL5CeAM9pMuAvPewC73USty8Vlw6vDkS6TzXgQw87k0SuKwQIjxM 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 ZvEhWEL1WuiG9fQJePWxY0byfJZ86afmUPF0GqT3RRUo97ZKkvM4JBj3XMRq8vTQiPbiLzjuRJeg8h/TbO5lgFj08DCI9nXgtPJQ6A73x2ni9RjoqPCS3uLw9MuO8zeuIvd3GFz1iiSK9O8SUvXPxvLzZ5EY9a6hwO8oQWz2H35q8j4wSvVeiIj3O+hm9FYfVPF/9pDzwuIy9QKGjvX99yLteQIA8EjD+unRvjL1zFJe9Sm63PJyWT7yAoeo86MPwvLPxybyeGyq9OP0iPXAuG7xRxLE8m/mRvC3JOT23s748IOHHvViFAr0EsY09udSGPeIpEjyQFXE8gb1lPfZXBT34+JA97aQsvT6sVT35Hxk914TUvA0dAL1BQZG80rsvOuf6mrz9sSy8uZduveX9CTxXVUe8g3s0uycthr2N5Du8c2pQPBwmoLxotam7Kjj4O7YA5D16N1i96/YoveomgLtrTdM84MAavZAETj0Cn+Y8hACmvFm3Aj0sXA69do9fvTHWrD3M 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 MO+HJbz1XOsS8Do5aPVZpabv7SQ89TOVnvc2RSz3bmlI9nCD6u2OFTbpLRdC879KQvJNuxbsraxQ9D2s0PMWrGL04yVc9iEGBPFZy97z1QIm9TDsYPeyPIb2LqCg98binvNd4kT2/eYC8beFfvUCOQL19qmo9WQDNuzmBUz0EcBs9zeohvLFcAL1i5YG9nhB9vevaIDyhv4K86QcjPAo7lrqoMxM91RvcvIASZr38y1a9tleuPQNa/7w7hre8y/cQvZXFBj07j0q94vOYPXVnDz2fDYU8SYlFvdQxsrzsfxE9JTUyvTkf2b0IS5g9BPZgPc/I3rykVTO93qQmPeOMVT06N207j1v/OgECZj0zZqE9/k2nvI/KD7ySSC+6xH5HPTKANTzhfyI78z/OPP0eLTzPcSg9AadVPGLiY7wl/UI7k2MQuwV0Nb2Egs079YoePWDG/jzZCae7PEvfvKOONr2oyVG8L9LkPG/FpjywkoI9NJ4OvZq0Hz17yoG9tjnbvHLrhj1M n6Vm9SXNKuxezgjzobVc9Ke6kuz0Fq7xjCJM86ZjrPKdY+LycqzM78JKUPCceEDsTf668rwSNPNJRhDwyIYo4xUeiPIu1VjtrJfi8reAkvahDRb3z3t89MHTqPJkalTz0ymC8ktyYPeLSND33Lg89l43bOl0PYDyhkTC7QsBlvYwVmbu5tIw7W+BRvPPJfzwJ6wu8h06GvDkjhrzhBEk9nLTmvIb/ijzF53I9vneiPNUaFzys4kc96e+3PNXffD0nrAQ9ymMMvUp6aL0Tlza8JW9NvFki/LyutT09udpyvBcbiL3gP4g85M3tvN9FvDzITkU8xUv5u8hzqbx+N1g9Hro9vdwsh70d0E+8g69FPJZjUjyLPP08BRUZPfbaYD3Tboo8Ce0tPdS6iT0RHoA94pHJu725rLxppV29PPWcvP2fs71Z9Y89Q4EdPYUr9zxDggG9kxbtPIo1cz1rO1g9b1wju4V4kTr/ep094WiDu5foXj1J3xu9v/ZhPBYtlLxDAu+8WTbM 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 KPQywfj1pRQM9DqQLvdZwnjsQxy899k6/Pa8cDz2lsDc9isUquoLtH7x9oBI9JYg4vWtGtbuWmaM9phHyvNATNrz97ay8EdibPDiLL72v0gC9T3HJO1/1jLuwYaW8c2xyvXc3Cz2CYTU9mHTnu744gT3MVJU9ViZhvc5Rdj3IXDA9sPQBvXqpW71535A8DhcZvUwfRD01UKy6Oq1VPdM55TvSn449tc6AvUmhkDyJekw9bmJSPCemjzvIVee8Uz0LvThPFT2G2oi8+C04PZjc3DxbWTG9jyvhvSrDET3Vc3y9ozyTvDLEYDxsqoE9hp7svFj8RLyyxBA9oRqdPDSbqLzf3rm87tG1PAKIAz2G6VQ9BIDePMMhrjz8uES9g04TvcfesDu5oCm6MzeJPP1q+rtz2K+8aJyiPN9QA71AeSC9kwv/u/h+uj0bVik9PkkgvbVPMb0Fzru81WDsvIglDbpUFRQ9nnuTvQSLPzvat1M7g+xZvIO+fryo1LI6BoskvX9gYbxM 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 gPRi9cpVjvcHlKTxqHPK8S1R2vFlnyTzsOTy830SZPGKTKT0WFxM7EqBavcCLYzy0J7M7D6h7PYtxPj1C2ZE8d81JPXYKB70Nqhi9OgOJvT//BL2QFjg9FKDzPPMyCb1lNsg8BL67PJ8mNz3+gJe8dsnevN3lvD3HIto89EqcvVfsJb3LWVi7cJZYPdI4CD11A4U8yV3CO2w9Yz2igBE7nZQ6vW4o+rxTx1m9y7JfPQ7BmjsmuFA8bIynPIJ74T3sEIU8OEpcvX2mpbzzXY88E7yivMx7fT2kRRg91Etdul3R5LzeAKQ8H2GsvKlxsT320uu7rriqvbfKBL0rRfk7z7roOxKnMbtCSU+96aInPcYvzLxH4Aw9DtI1PC9Ecz1S0L68bWKjPfsDWjxlmHE9TbU7PXDlwrzQNa073MTUvakh4b3wNUY99fmdPEKm9zwfAvg8c6WIvFx0AL2SpCc9thIzPWWhLDvWMEe8y5Seve3yQbysG+a7T/0MPTmMSD1AQlo9y2BM 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 sPDDWKD0Em/U6zrNsvCiAIT06yVE9CLIJPeYp87t11VW85F9lvduH+LzmGG682P0mvbjvkT3Rbp49bSUHPRXltTt3OuW96kv3PMmyvDwpZFY9x3yuvd1zRz2rGLy8kkMEvcSlkL1BBZg9mWquPB0scrtGDkG9ffx0vUvkHLvCC6e6Er89vOBTPDwV14g8fQUBPXLYgL2j+Fk9UTgKvPE3Oj1PZnu9io8fvap6N73LNEs89yLyu1veuLxQBge9Q5zuPJvsYbrxZrW8embqvLluHz03Qwm9SZc/vd+ZPT0ZHMG8EwB7vLb4RDzdJnE9iKX/vJDHvzzg3cG7cPK7vJ1iCTz2lIe7jLdnPcCalbwZ4x87yZQAvBAIEbxVR+c8vY7kPKcigD0cRRW8F32PvZmaALyrvtG9IclGPd3v0TxTU4a8FyuQvW9koz3mQCE9xyhLOxvYzjy90bG6mOFuPViJhz395cS7PV8SvOruzDxhg34972CXPFLWQj0SbY28neobvQaDabwM 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 jrom9f2tlvX7jgL0IhpE9T/uHPHFoqTvRa8+8qt3yPb5rzTzScbS8Mu7sO7h6y7zZzSq9+oG8PVxBuzf54dI8tx+iu/EEVT02b2w8vnFPvKRUAb3qfa89Ho64PER6eD1noty8g7ELPZktCr1G9688ZmqzPEKqej2Zg2c9pSKlvXZ1eL0rgRC83HoMPT+BSD2dKSS9ypWRu9V7Kj1MJSO8yVbIvBIQB7wk2ye9WVc6PbCZMrwx5oO8VhYfvXhj8D1tjLi8j0BzvUnlpb1VoiE9HhQKvA5h/7rrQ3Q9r+azPKOAdb0azoO9Njnxufg5sjpKp9G9XWfmvGHcybzA2n89I/cdPAvAcL2spgm9alQHPnA0orzfSK08ctaXPPi31DtACi+9p6vOPLON7jyBjhC8APnOOq8XMj33sj69YQybvSzGkr2/wyM9GypUvPiX3Dz5VdA8fB5vPOdHPTzZabk9WCmFu5B4gj2LpEE9AjCQvfZJmDyDsxI99nzfvBziMr3wS4c7DLqM 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 AvIMEwDxgyLc8b0rWO9PLfbzhI0i93PMjPHn/gzzlHcE8eorIvTRDrT1t9PC84yyPvSDgdr38nXQ9rqMYPMIZKT3Y0We8vOeEvfr/s7xl1EM8bSj0vIm/BD19ghe9nwCrO4XUm71WiEU9nT4IPHNsBTvDhIq9NRN3PQuVm706ZgU8NYiFvXjAiT3ETxK9PFDSPdUS/DwMKjw9qE1GO5RzWzxwH1u9ZUWTvWva2L2ZFm09LKAIO5VX4Tn31ZW8YudmPYUuHb0ch2882CUtPNDvZDzu2Xo7LmSXvY3t/Tspb9c867aAvFSbizyAEiM8g+tvvYJvwjuGtBe9P7GovNDaBbtcgxm9cNIfPcZovjtBbxS9P1JevUhcfD3wO727bIe1vbcGl7wrJoU89OAXPPM+G7wqude8BU7DvMZKK71qbQK5CYgYPb8Ehz2y8oK9rTGovaiabr0G1bY8AwhRPSK5o70ggIi9xoD/PQp6bL3VWJc87lJuvXnulDzq6Tm9OOgDPOKO0DxM 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 OvLuVsb1r1BQ9LyFVu70ZXz1UmKc9YATNPL5tRj2qFCG9kk0UvRPfoz2XMSC8bHw8vftEJr2ngza97J/FPfiKB734PTa9mdWivS45lLzkfGm8112UvCwHBr0aoU66xv6OPXP+rjxBYno9ulsSPUWnrb3ghD29AaTmvC75mrywmou6BvPavUX9Nr27pK092RkuvCCe+r0IuEY8tGm3vZMdCjw0C5O9uECzPTF4QbpNK5Y9VCeEPOReoT1pDVW8vywPvcMtOr16Apk9/iWDvQj3krz6Y4m93aMDPV57mzx5oSM8XIJlvfB9fL1QGL27YlDMvL62s73nbDG8YVPbO4NbBT1iMZs9NyP6PT2wkz1efvG6ud33vFrTkz1+aqE8Ah1mvbhVvL0Sd1C9xyxgPS1byr2PL7y9xdpMvWblSb14VaW71r2Ovckntb2CeVg7m/FlPfkamz29xru7vz1OPeUqOL2r/PW8tX+WPMVu3Tz0pMo8+7i6vcd/j7yySbY9YrsYvS0BWr3M 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 PuzzibL1VpIi75DdSPekgoD2R1u08cAOJNwE4GT0Ldtw8u4bLOldaib0yTaa9NoilPHQjwTx7US09/XaBPX9iu73ovJi7sIrsvD7ekLy/zlW9i0EsvZs187wWu6g9i+iGPQGoNT0Xr+c7qloovEiHmL0IyIg9gy+fvRSZo7zn7FU95H3BPFnyKD0YKYM9FYlgvVrHn7wzvTe8McOHvV+acLxdSo+9q19OPdNl2j3uOGS8xM8APUxzrj1C5nk9Wc99vW+e+Dy29eO9IFZJvcNtHb1IAbq83ec8PVOps719so+9Z06dvZkZwb2vIq09gJYFPSmQaL3Tauo7AJYqPXSFuD1Wlds9obU/vSTkg7xUMmQ8KVK0PA4COb0CV5y8YgiIPAGuXzuRdF892DdrPfRWK75D7C69KCoevYTIFT16PGe8nadwPQpHSDsMCxM8VvPPPYTPvDxca688oqpGPfmYDr0HPJw9rCgzve7XSj3FTBk93nsrO3Rs4zxW37I7CyP6u3HUVzzM 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 fu1v6xL1SDd+8K8IRvXjRQz3gBUU9Jwm9PEd6iz2d7YG8PZQnPlGlLT0kLRm9pwZxvLcktrz5iQA9GH33vHLugT3udoM9ReMHPetdLDx+aa48rsEJPVz/Gb1ODx49dvLKvMw4WzzCwKO7ojOUPeMQULtLjaw9ghnbvFhcgLw/dCi9yQPxvRZvH7pYccI8zoEBvVTa3j21RaW9B7PZPd3I0rxqjGM9efrwPD+aMD1jmka9HussPSh4Ab52bws+mx+jvVFr5D1FNhG72M7lvAVJpb2LuoO99at4vNsXgzsWEaO8XQLZvD0t/LyMEvo8EOw0PZecur33dDC9PsjcPFYviLwwLbs8MkbKvZVYjT27LD29Egy9Pdd5rTzy5hM7P7VaPLmuX73E3JM7XJ3UvWOkmT0sbhU9XMYvveZBoDyHnp09wN1TPS/5gL2CHjM9AA5BvXsiyT1F5iG9ezS8PVRwNb11uZo9g/5cvanH/jwocIC9pqUVvTxzmzuUgeg89vXuvNpLiT1M 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 vLGa8d4PTvUeeLr0HSB075VSXu0+n7jxqN4K9/sgvPZ+GWb2mt1Q8LU4NvXRLL71fnrC7p+MYPS0evTsiKRS9V7NGvCPTsbwU1gq9CER4vSnlCL0TCBQ9NdYgPSPnTTw+FX66l1YAvL9p2DvMl1w94CGIvYRSpLzUxZq8NLIMvbL3szyevyY9EeyBvIAgPT1m8Kg6vhVOvW+ibD0T4aa9bF0iPXE+Dr0eTiA91V29O0nEqz0L4vw7d5QCPU+NiLuBDia9f0LtvWbjOr1jab48zy7Juu+PLjx8A0S9Ey6svVkoizzRyYG9iT/HOwKCELs/Nw06tmKPvXP7gbwwSFQ95F4/vBBPmLyOxgA9BIoEPDP2hL3ElAa9LGyLPE6Ygj0Xkfs7+oeGvETF2jpFN+q8pCfrvGOcXr1+8FY9ZaWWvVE22bzkYwo9aWY5PcfLlzw8lzU94d0lPbohjbxvqqg9RCY1vTd8iT12LBM9GNAwvdmBcL3FkCe7VLuhu1r2B71Di1c9UlRM 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 YvYlvkD3iSu27bTohPPn5OLxgSc88qmkPvQRKBb7G5Aw92WPHPU5nQrwTcHY9x54TvKO1Ujyx4Qe9OvCTPL0RTr21JEU9+auFPQGlWL0Zh7g7ct8bPVS2wT0X+xA9ALNJvKGSEr24STu93ypavZEt67vfSuM9+IuivKqEGT0RpT69UArRPBFMZb3gS6O8SAgaPF9Rdj0quoK89p5vvOECCDys7hK9fbaZO4go1TsJ7+i8Q0+mPcfYob2Kcbi9vnboPMPdwTzGd3i9rh6XPd8thTxfwjg9P8Yevbpy0rsVfJs7zA6evGffErt33NW90FpSvfterz3tUWo8cEEOOwktAz3dnYe8J/qzvIur1b3tvys92TysPdh/Dr3ZJ0W8HuGMu4bhcrxIy7A8AbMcvTxwRr1FuzM9cabKvDzEa70Rgwa9coyIPV1gZj0pWuu6IhuYOyUzQbxglvW8JldovRZ0ij01zWI8AJm4uyyaXDwJG1o7p3XQPJFtIrwEkJS7pPHaPF70Tj3M 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 6PNgERj1QVio9K/eavIvzTr2Z2728Sn7OPVUrxj0dDmO8o0SfvYAENb0WPvO89tSOvTMUtT3uB609UXFEvOq0Rj2mvPw8KwstPUr1I7zVJii8C6eovEu36Du28X+8Da21vNw9QLyCV8I8cltJPN+NZbuLvp67ufM+PGA2wr0jpAM8qNutPcWXxb3fWXs9kuSRO4W9YT0Z/P88YHi6vEeilj168xM9KdvDvKsXujve1pa9B/X2vakKRD3QrkE9HPPsO0IJRbyXbo69deEivUbSX715g+c8IdiWvRPlJz38NfW8DSk8vE3IBjy9jSq9a/efvRHI3zz1Ki89QurJO2afezyRgzm9eWVAPcAlZD2K2BK8nKOMvX0wlr3v2fm8k8FjvbpKdD3y+WO9cDlGO1Olqr30JoQ9nr8rvazzorxwdRi9tt6dPeQAkDzexqs9d7AUvb/5tjzVF/E88/y6vUNp373MYzO8oceJvdTw97yb1Ic97ebpPH4P8L3be6I9an5WvR8Hmj1M 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 uW4U9P2P5PBNnDb2Kltc8JlHUPJo5Oj28qTc9D2pLPffhwTttqig9SdALPKkBoz1gk4s8kaHDvSaFjT0g/iE9rbwLvZDIij0mQ0K9zaYPPQBUqT0PSoY93v3pvDu+TT2r6CQ8mf5lvGSlMTytxRI931/GvKDLijyDqIG90TGDPesSL710i+U8JPdqvBaSs7zrvXi8JkoJPFhYEzw35So9/Tt7OrAyGbwoitg8CXS4vCOoObu8KEg9mD2IPIuMTr0fB5697nllPHXAhr0iVMW9NBc6vTsTjDwz3Te9qFXhPAGkgr1WKtC6/xvTPADuLL07ieG7WK/APOPIiLwCIbS7HpuYu00FLT3+H486pUQfPSPJIT3xCDS5Y+UWPbATsrwe5XO9i8MavDQ+Ebz0+Tu8fWTZveIB3T22xzY8Eb6sOqI8ej11Tli9oyiGuy2MojwJk4q80BixtvlllDywAwA9ty/ivKUO9DzZxFy9Ll2WPcc+aL3NwHc9LTd2PSLIG71qppq9OWjM 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 xFzK9Za8ku4qsAL04o5s9q6sYPVF/4TzqR3274ulePYNQrzzMd949v71VPQZnKb1K8Iq8WcylvPNFTr3BWBq9EWjsvG9S9TsJK+e9e03cvWN+JL6sxDM8NMEEvhPVzjxqGam99sPdPTiwWjxGVH89+MgFvO984DxZpys+8SwNvVKp/LxEOFS9G9V/vcqxob22EzK8a/DPPFd/DL4ohMq91xTKvTFsHjwsynG9FB7dPZFykr2SwAk+Dv0mPV4nUD1LvEm8jnTCurx+wj0hePu8rBQNvXQW/Tt50KW9ZMtDvbeTu7qMa1S81rITvimHp7uetbG9AtIePS+ddr0Hnx4+qSdAPFkzST1KSoC9A41EPRN2Sb0m8Aw928iovYcshLzJj4M9SMgZvS2buj1mwF28L766vAlPm715epk8fQWwPANbcb2VBGW9RTmyO8aNpb0hrWQ8cYz5vEtDOTlUd769AbTYu9HgyjqOlMS7fjBavTAfwD19FfW8ZKfMPIRzmLyggi29NeiM 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 nroO9DJervAbtOT2li1y9gd0jvY0RybyIVZo9fp4TPUfkHLzSSVG8zhxnvdxLND2Wynu9KwYAPaadwT2p7HW8rR1OvcnxGr1jbjs9/VqBPXBoBjyYNGq7ZIxHvFCj9bwH/dE8akIFvbYslT2T35U7pZofPUHQpjwHXrM8FnuJPDpcjrzPMxg9NA4HvWt91TwRjTc9OFb8PMQO3DxlOpQ8FrMDPaMI8Ltdlwy7XPAPvDiRNbyoK868QWPVvXck57thbRI999WXu4STNzxfpyE99yv0vBTvGL3/d8a7JTTeO1MlCL3CS488ew4YPf/IK71asaU8PNmrvNuF/TxD52g9TznevaeZoL0XCWs84pzoPCEk5jw7UIW9x1/mOtmI0zuAT7C9RjRePRUWUrziJTe8l89fvdsZBT0O9K49M6FivHMClTzLkgW8zIKZPGS4jbo/aFW9E1HjvCIH4TyqAC+95fvYuitB6zvFeDG9EDBoPV0dQr3BrhQ9qXKmvSiHLT148vw8DC6M 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 a2Vo76+X1vYCbpz3Gfda96m9SuyZ4+zu9FpM8Q7GBvf4SvDy1aou8Ns75PFTX5L2I4Es9bA34vbAHUzyhjL+9OjW6PRjwBL5oDu09DwL+PPh7db0lbIK9tIijPbiDg7wKWtK8KaqpvTNMjLt84He9R6vQvJwHLL1vCME8vnwYvS66pj2HK4a9TQIwve8WWL30xGG9uYjpukn5oLtXFDG+JDSwPYID9jxFcHi9EaPcOtz1DL56AgY8vpXIvSK8wj1Qjhq9RvuTPRaznzuIbCS8VuwuvfVJZ7stnXy9WbEvPcQSh7yyZsy8fkV5vTBZX75MXd09on70PekUnryJIYC930+mvAhL5jwh1I2839tSPS5vKTyJFWE9EFLYPfyh4r1suGo7pK0AvuTa37zMH509NqBzu2pGqr2f+iy9zR2FvdP6oDxJ/k09weyZvdJF4bwLMWq9BjBfvWK9hrpUqJU9S9o7PQm36jqzlx08g/iHPGI9Jzu6LO29vTY6PNbqdb0lEZW8jK6M 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 nPJCovr3c02m8vg0zPSwySLwspjW9mLoSPSVNeLu2kMc84c+WPU0URrxt68M7NzXJvWu0VjwrNJM8uR9dvTDdhD09Lz69Eg+HPD9goT3/k6Q9hJ2NvZDMCL0rGrq8Tvw8vRTUWTthfr67zaAJPW2lf71+yyY9tFTyPJsF+j16mEs92YoKPBXqGL15WJS81pYAvUopaL1Mhf+9ijm/vCejWjy8JTa+9AkHvrSHEL4ifoM9cdzjvGX1fb1YWli9Wom+PaIhprxrMrc9UN5QvO0jYbtt2KQ9uWhqvVGixr0Hhpi9/R7mvKYfzb3HvUE81GAavPgFV74L0lq9iOAKvV3i0j0ks+G92AOIPYJ1iL04kBE+yN9EPU31gD2X1JM8aSbovKQihz0T80K7ZunTvU6AjL10Ghq8GW7dvHltwzxuUpi7xZfKvTymY7wpccu9FszUPDCUvTwqhw4+E6K/O+8xtj0pA8S8cQ8KPfhFCLz3Yjs7SPiuvFUyy71OVTK9DBjqPMPyWj1M 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 LPPazNr0VPTG7OMN7PI9xZDzRPHU8RmHWPNVdpz0JAJY9quSovN4QO7z5gsE8fz1CPA3X9Lyyz/s8fHAxvfMdG7zlNRM7JPjkutQydTvISIw8UeoqvJS4EL0FAXO9/rPnu0ulmbvDVIg7xFWQvT2v1TyK35s96SIfPSXBLT3NNxy9UTNbvHhFw7zHVwW9gX3UPKxCDD1DW5q9Q4vBvRe4kD0x4Va9A0wpveJMtTxAsZa8BMfYvAweGD0hSIG7yWe3u2VvdD0H+UW7TissPS1UgzylSpq7VJypvMvscj2zADs98By4vdGyvzyDram8k6MEPSboYrsaqmM9I5cRO6Z/2zy8FAo85cE5PbCcej1Q2/k8KS5bvRvMirzbmQA8SzdKvTNcXbszBnI96MSGvP2kGjyq0lK8QxurO8pfMb2Sd+089kxYPUfmkrvX5nU9Os5IvG8XLbyXtWI9nSOwvc6Tib1y0mE9AyUsPUBvFb0P0Lu8foUkvb8Bcry9g4S9TsarPHKT1jxM 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 s2pM86AojPW7y1jyeXpQ9LgWnvIDZtz3pviK9rmgTvUbcQ7167vC8xceTvd6isLwuF/A7Zu+5PN3oa7hc98S6pieXvOKeVL1GxcI7Pc9/PAi0kz1gNyA9nC9lPBAuS73rILE89viWvbwbYT3wPP68Lr+avSr5dLvYWqa7AGN1O1kq1rxTHdE8ek1KvQ6el724Aq89lxs5vV5Oqz1pE0A8d9oVO3a2DDxMwq28w30zPJ2kUD1a44i98bJIPGb84Dr6QZU7+QvjvEFg0bxOud07L6wPvZHm8zykStS8qZEjvH1mPT2Anhm9dtecu3hKcrxkENc8bP0Pvb+ZkrxLmqO8yY5IvL4vKDsOWYK8shiXvP5ntLzCDxm8rzrmvJXimb3a/2A9eIosvV1VmDzZzPU8n5m6vZe/jrweiYQ80oLNOjI7Eb0FuU29ap4YPaRKM71HqI891jB9vZiw4jweJae9+t0evRklaT09cOy78Qu5vRJYgD0Zh3q7qQBHO7ikTb0Jdva5GgsM 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 2Na49QfcBPmVs8TzNYCK7QS58Pb6ZOD1G4v47Km05PQpqHb6rmWK8vgi9Owl5tT0DI5Y9a7gUvt/Zbb7Rg4E9cau8PW0DGr64zNG8vLWkPIrA5z3BvU89dOAYPAztcTy5I6I9h8MHPpoqzD25hh08iRcUPUZE/TwkBDM9gC7zPT+eYz1+ibu8/Gf0vURFnLyW5oc9bP0avrvObb1l8oQ8TrWCPQy1fjw5Yok8JVHyPN67Lr0PjTw9dnSXPdmBRjvBnbA9MZctPZG6sLxByke98yjtPbqNWD3TJCk9YQtaPZyQtroD59m9h3SUvRnO+L3v6rG9odrnvF7Ijj1FxSe+41sbviEL3L0I5JQ8chnIvT2v9bziPAq9+iTiPS9NO7wxOg8+O4kNvZMJCruaHSQ+2BwnvZG8A77OBbm8mSWUvQQ+NLtCAG49oDbEPQhIrL02orM7ywmhvSEYRz1WV1C9Bj3iPaLXU726/B4+WE8bPQse2z21yX88gImvPPBi5T1qpKs5roeM 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 FvaE9gYbqvPko0b0+m8M6mG0Dvf0X+zzYr6M8n41mPAooAr3AfC89O5W+vIxoCDz7lNE8HShJu6D6vD1UNVC9Ar+RvbB+ED1IOEI94qLLu+K9Kj2FNCy9eY7zPGw7Mb0JKIc9tMnTPOxPTr3Shxo95VlavO4flbtJPYc9pZNHvOn9NrxzkSu8GjjvvA2YcL2PVIe9kRDBvTPicD2awqe9h6vNPUfjrLxnV6C9/vpwvWl9pjvVH2894Gz1PKa3Mz0I+oG9jZRWvXRzBD1Uxic935gPvHFotrxdZps8Fj/IPH0YdzwhZ4u9VBoPPY9tqbyC4ps9e+SWPGRq7r12yR897KGGPHvA8DycqlE91qWquzc0ib2gpNQ841gYvV3uojskyvc6TCHhvLFXgT2jNuo8EYFgvT1eib3nMeI9VJ0DvfzQkz1lGom9ZEuEPYgAHr1w/oi8mhV/PRT9Ib0/34Q93aqbvZVt47yTqIU8V+wfPczbUT0kZmy9VFdmvYoWg72QdCC9OMzM 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 Z1/M5K1jqPdULgj3n5Nw7KglBvTYUsr2nFPS8AxBEPSjsCTyUZqG9hWzhvHL3eTw9OBY9y62yPDYedDzuPPq8Mx1Hvd4w+DxLjas8EEZ9Ou+D1T3Irm69xtbCPCLRHb7KV4a88IoavlrrR7pI26K9RQfHPAQcDLyVMEs9w3JtuwUHezzYkT69UwPmO8zNCb3n6oq9PdIAvbNlFzot1x09QKM9PYd69b1dZJQ9rjrIvYD+rrxp4um7qxFMvS9BNr4P2fw98+MNvdCTEDpEVVU9k+25uqQEib3TrGU9olyzvFBBrr05mwS+4LQOvC8Hgj0qA0g9OByNvTnEbj2OzGe90h9cO6OO1b1zlCw9fk9OPih4Eb0VTPq9pDrlPTepVj7RGm+9QtiUPaZy1L1HNeg92giLvORX6T0Ukfi9RGaKvdVMlLyGsJO9Sy0LvlvMCr0Ml106uyEkPZ5Mhr3G8U09bxPmO6sb5b10YC0+FJyyPZ2Zar1eAOe8OulzvXPG9z2Ls9I8AAhM 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 RPiUPmL1xoGy6rbu8vV79ij3v7Qq+qP1MO/gZfzywHJ890xqOPe56lj3DZ5g9k3n/O8kqjj07sJS9NnZDPXvrqbwGuBs90X8UvSUcyTz+5L88/KisvdoExb1AdQk+TMWJPMBsIr6/lg69H+ivPfgIET60YvA9Mm74vA+jvD0vW0g9oU0FPm2nDL20Ghk9t74nPreo6Tw1QR8+dU4OvVF4m73OgSq83a6uvD0kdT1Vk2c9qyzLveR1d7yVcEA9596SvOBrnz1dFKO8oyIEPLTwgj3iyoA8DjLbPSaPBz1nCTE+G7PWPLp9FT1pCmW9+vEIPs4vWTvY4rs8Ta5Ovd/IKT0Hi5e9Q2XyPIxKzb3UfNa8pSzBPTRJgj3oOjY94Q7DPGMMFTyzvQ696YnAvMz06jy9f808Kz10O7U1FDwh5go+sTRpvj2dWL3vIFA+YFIPPlqpdL7cg0S9UtUEPcVwMD6MAAA+ytnOPCACWj2ceRY9aasPPiniSD2V+p47GqRrPmwuiz0M 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 0vbUOTL0zHds8/pmRvMhDUj1dLSG9QSoHPREZXb049AG9tgLePA9HHr0Kjmo8VGFJvdSHbryBapM8IF4MPQPLET0xbMy96ELOPEkN7zxEz3i8eIVGvUX0oTxIua89sJ3PvNfLKTzatcU4XFqHvJI+AD19CtS7AhYVvaDOrrz+SpW8FItHvZpmZL2gEc675zFZvRBEE74vzj09hG6lPSIML709ZnQ9qJKYvajRLzzLPmE9LqqpPGm+Pj3vPiK9GWJgPdulFbySpuM7oLosvWq1CD62K0+9xmdVPKncuzxUQFw6PRWNvaihQL2WwGI9j6n9O976ED3A7LY8tM0XPegvmDwN5jA80EJXPSEm4Dzt2kw9eldTvX0vbj2VR8889hmAvSZ2mb1+wp89wTOQvC5oBL1/CAm8vJK1vRBXkT0Lu5271NhsO7S2iT1T/je86+MEvTbILryw7du6CDnmvDDUez3aOaQ9puWoPYTmgL1jvIs60fBIPT6uOz1oayQ8MClPvdGlwj1M X/zQ8DWOZPVQHJbz5ROM86lm2uxjI+bvjkj49DJ99vKXq/ruBsz089cQcPT7ZNDyQgTY9XL0jPasdiD0ky8s8WVxBvd4SqD2ROAs9JpOqPa1k3LwTmOu7fCuVvGFKoDzZ/r28HS0evMZkGL2uzn07CbScvbUdDL0Gr5K9pnI/PbAXGr0MdU897CmsvdI1YT17eN68BCqUPCYnWD0U9Ys9TQvoveyetj0kQKO9LTSTvSR9Ez2RyGi8Be4oPaTmpL0vZjg9gMr1uv2ZX7y7nsI9ogVePeTOTTyfYTI9Vn1PPMk1sj2EOGS74ge6Ow+GIj2+96y8UiNuPDaVCL2tscC8yfoFvdJ6V73kDp48DlmDPabKxL10oy09MV4GvTq7VzxZnA+9B8Q4PIGcyDwbre88yWPovHEYlD0qQ608aNLaPYIPDbzoX9+6y0qIvbbka7sIkuG72dOrvbaqIjzyYL48gdCNOsjvGbzQ3H69bI8aPL5vbLtU+aU9232WvRKu1D1uiLC8KdlM 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 ucm09MtL8PPLtnz3tM169BOLHOzWVNb1N8Pm7Gsxhvdmw0bwo34+9Utp2OzbxjrzURoK8qxwKvJ3Nwr1rODg9FCB/PCrNJrv03SG8WhuYPCDRzbw7m5c9f4SYvIyE5jw83nG9xRN0PQvF17zptx299kivuoBVqz19j+a7hTCxO674CT0RADe9mlc0vWmnbT0MqbM9crNMPF4XCju4boY5gCwuPIIqDjxY1mO9W9YSPdEMN708Exm9yRV7vYJT3rxO0xs9NnbVPDfjlrws4vI6Ht9cPaZEfjw5DmK802UgPbrl2bzTrKc9p6G/vRVUVbxTKRk9u7X0PDU+Br29sJK9vR2HvU7R/r0zeFm9M5eovXb5J73ZVbG9FoyRPcu2ub36cH69dVmmPZQ4aD1p/2s8sH+WvfXm8T3i7ri9pBdGvZ5pGb2b4e08/ZSSvVy3jb2uhNC9WPPIvQJOK729uNW8gwuVO6mWmj0EkiK9T2Zgvc31lDy0ajE9RW4EPPiuWjyrRAS88ZNM ePVpNGztZh8U8UNIEPO00gD170Fc8VIprvQIWATyipXu9oAa7vWSFATy5wYi8+vVwvE7yFz11qLw7sre6PNGZsD1CHTk9CjXUPcGmaDwerMa8g66IvDEz+Lv7Axm9xMRavVPBWDtcXYi971OivYCmmL0Jx0Y7rP7HvSxIxTyi6129eoqGPWr1471qTCI87uOXPYjQkTumjm09376xPESqv7xeuze978nPvbYRvrwy8zi9Zc9wPYNqBb6Yqpq9KLU/vTzrk7y8KJ29vtOXPdpojLxineo9OLTGvSY6kT086oA898ZoPJMMxj2QnJ28WOUiu9uwWr0meaC92MHqu+DVgTx3j0I7J9P4vfxVoL2amm29T1r0vOXxL72n6YQ9Kha4vcCGXT1AuJq9e31luhX0B7w/8wi9x66zPe1X/TsgG4s8JmDDPNFxw7pBilC8vjZouw4aj73ByZy97FCDvXHEPLxMa3u8wPS1vS5ai7sjLDC9F3q4vL5Uh72gjOi8bmPHPFm8IjwM dKDq8t123PfM+CT086AY9VkcBvl5xQb1pzog89nycu+JouzzX/XQ7jsoXPMtyxrtAZjC8beUMPS30oj0HA3s9IMC8vah/MLxrPj+8ebjSu9VKmT0zOo49oipUPAD2EztjARm965NCPattJD1DYQO9iHJdPE3EAL29Zhy7PWYJveaFBjuUzs+4xP3pvS6e7zz+jBK9uEEMvU3ZWDv8Xrq9XiyTPRABITx/NAQ809bWPLH3NLu5nZI9QZwyveYbLrzxZNm73P0SvH5NQj2OUTK92L1KvC+2jbwdbbo8PVNdvNi7irt5NEu8TroiPQSu9b1Xt5C88HLpPamQfbxjmpU8rSp5vLinP70hNV897ISJPZkZwDtbSLM83aM5PBTFuDxqkmW8v+YnPXPxmT2A1aC9LHOuvO3FwLxkSMI7ON6hvXOzAr2T8709jMDevA4e1DyAD8i7xzrQPJrEODwyAzg6mTmPPSmr/zxdQkk978J7vbfWbT321+i8qR5ZvQhFY73bsaU9F9sM 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 APYmNzL3dA7a8CkvbveoD5rys7LU9LUU7vfmbqb2GM2A+KOOFPStMR769rs68vzIDPTjd9j1cv0s9IohkPZHYXj1V2Tw+LPnEPbCppr0yxpW6KjUWPnnmgzws4fM9Hvv8OWM6Aj1/WDi93rJ/vSTHCT4iFcU9eLhLvuNgrryqSP28NCSNPUr77rngQ4s9QCWbvEPruz0eOgA+d8IWvKSskD26U2w+imYhPQzdfL230Ly9nLuvPO4IPT78hos9w63evcqmI74jafO8qi6QOztwMr6AdL+8/Y/dvUER/DwTnxW9pn+WPcERj7xgfxe+jW6dPNeIE74u4Ym9+zdxvXuFHb3cwSI94SkLvfz01zxunAg+pBJcvS3QhbxfycO91uuuvY+wsrx/L1g8ww04PS5BpbxYiFs+prjGPXDbRb1O67C7NIiBPadzmr3eBYE9l44RvXi/lLxS43g8lftXPayvDz5yGh49b6F4vUVgG70939y9CAS+vP429zzg+BK8rNmivRf2DT6M 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 QPuUV8b1Nk189hGYXvitnPryhtgS98TL6vY7RcL0ywVw+g/UdPUe2Bb6rrCe6wqNYPccNzT3mj7M9Biz/vDY5jz3vXlQ+WgtKPhCyiL1y8XE9KovOPTRuDj1/9G09g02dvQWtFL17+8E8ds50PdFEFj706SM7/4c1vWlkjTz4Uk69VXtwPdR2xD0qSm69EzqqPHSIBj6X6KE8x2tXPXU9Cj24GGA+F1CbPcUYer2WgEi9DJprPfAIrz1JZ8O9VkOXvbXLOL2+Er29Ud0QPO4VFr0SlzE93IcAPY7ZAL2EnzO9KgzwPUO70D2qHpy9l76IPdHaDL4vMwe48K62vFrubr1NGg89J9ZhvOQ4hb0nsX8+Eo7CPA/GtL3akyY9/mxYvXdXvj2gKaI92d2XvO626LzFKQE+VjrCPQC9Uj3rCos6wrC1PRZ1jbyehEk+OJCfvbJ6uzxkzf88hYQYPWyRKj7YMoQ9YteEvb6NSr2RH2q9JEthPWaBr7y5Xvo8t3rmvSwGbD3M 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 7G8+9Sxi6vT5RQb2m4Rk8GJImuzQonbqxfIs99cocuya3SDxNh5a9ldDGPcHqqjwUhoY7eNCjPBgWXz1IOVs9qwCqvPBVwLyzeRS9eCWuvd+Bgb32oV+8JtG5PIbIH72qO5M8rAchvS3fDT2dJiy9rCc3PSvIdr1kTCU84WaVvfJRhzya5ac99KO4PZKoODyV1d+8ljyZPJFoMbxjyI69hZHnvVU7nL2fDzM82BffOy5R6Tu61Dy7InKDPdLEJ73KuFe8Szxqvd34BT4Zsuy9dP2JvINdAz2oz4Q9Cp7ZvV8v1zxq16+8RPEaumLdF71dTb28H3BGPGj7Zz0BCH49lxwRvdws2zyOkZE9fhXaPDzFnr0Qax88vhWPPOnmXz1rLaK93ZoCPG+qeD1Xs008bAqwvRD1FTsC2gG9t+0GvdfITrylUJI78pJvPNSj6zx1NxM96gZCvQjbrTw250m8ZrsyvZCp6rxlQq08Ep3oPPvygTxD6Pw84z2YPGZVBT1VX7m9YZ2M 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 De286ymsVvXbQhzzrtBk9Vf4CvWI39zz3eGq60G5gvbZ2jjzVKK662C4dvWKKkjtqm5s8aPRDvYuf/7t0awA9GmajuuH3Ab4G1we9W8lEvdtoq7zQXgA9fyoMPY3Fu71nXaw8FIhHvDixTbk+Bhg9/krKPIuKV72jDMU8N1eSPFGm6Tv6QHw8RrB9vC7QgL2xkJU96VT2PK78Jbq44AE9djgbvFbMiL1NfRA9pCRXvWqRYzzNIXA7OEiFvMC25Twr4yQ9gr0GvR+lZr1Pd4I9OOQOvaecgTxkX7i8cZRkvVCetbyt03q9sQ48vcWJdjxbv6i85ftcvSJhorwQ28U8v/63vV+uFj2gnH684LGRvTctWLwHtVy8olfBvKySID39Xle9RqzGveD+qD1w1zc96BZEPMtMhL3AVGg97OMqvN3rizxQPQc+c8iaPXUFQb0wG489k1V7u+Cwuj2649m8CCenvUKW3T1IxKC7L3MGPepq6jwvtBg8mJFjvbzchbw66du5qPQM 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 d9oy8HkXBvTz9Ej2qxzy9lg6AvStUY70IxLu9KMgovf71cL01kke9J9cCvqi7Or1Njem8V6NbPCO6Nj5TKsE9u87QvS6uoz2N1ru9z5EQvbVm37yn+oG8Cy6SvYNjbj3gtnU9M8QUvVtoaT1zzpC9j/Hzup8r0ryAR1g9J5ikvcL3tb0PkwK9lr+8PYgkzjzUb8a9W/G2vPhNi72JKSg9BCgxPBrN+rztFjm9KInAPIClRD3PnGG9RrRJPYasC71RXQ4+W4cNPEnxHb5nUkk8SHbEPQaQy7y/bds9TewYvpp3gr3JjYW9O5plPbxqwrxQA2S8HVa2vYvxVz18jJg8xdmHvOcSSL2/ZQe+VJj+vGSID751+Vu9SSmJvYpmmbwc4yK9eioYPe4CNj7NEmE9Hc4BvntM1D1pC4+93HsZvbY2OzyT67G9eGghvaMlMDsWA/c8eEkkPDYnybyoQPG8qtshPQ5CKb1798c9DS7svZgMNL6Zxlg8FAX6Pav1qj27xVa9ZizM 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 Nj4S8ahpdPDOC3zyXjxA8ubdvvfjsmzxgiwq7a9uJvemHEz2X0Z48CweWvaVGZD22VS89Lzc+vC5jvT0im+c8oB0RPIl/FL5G6us92V0tPdcdbT27du66+gm/PRttW719C389X8iNvWy1DT0yli49QF0tPDQ6mL18gZe9E6mFPN+pQzlbJwA95ag9vaQXFTsE2aM9e38IvdD/zDxsauY8OHM7vF7Rd73oxoG8BH4ZvfVq3j1Tl8y8oHlovXUbAj2VzKg9KBVmvXZrsjxmjTY9j5O+O6jNqDxzxBu9Ti8HvIt5rDvq8U+9LxNivBiiTLyVIzO9RnolvXhY9bzKK208HrYqvYOcXrxAka27JVkUvdyWGz3Xnme8RBwzvfTVDr0IsT68NKqdvYspLTzpLxg9jwpovYBT3r1rY0Y9sby1PdthubzSu2o8HCNHPdnV5r3ab4k8qOG3vXTtxT3PAuA8kFg3PaBzrL0Yqea9pkH0PFQ46LyaIEE95+RHvRRlxrycDq8741kM 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 3Pe9d8Tz84o27sKjFu5sDlryQvYM80G2evaY0oD2PbYK8IZUgvR8PgLz2jJM9PYvZvbxdL71Wet48iVeBvWOGmjwGloK7iq6RPMYLUD3hhHM9agvYvTmGCz2hP886hCUGvTZS6LsqaCQ8mm2PvZB3kDziOum8M8fqvQpYdT0PG3y9fC2CvXeRyLxY80K84MepvOG/Jz19SY49YPVyOkjQyr2ej5Q96ZOEPatnt7xDSkw9IY1PPWcUwr0AGVA9jp8kvdTfnT3IcDi9u7SjPYPj2r12aRS9VM/hPIEjDb3eic28w+PtvJhACj3Nclg83XsNPfcyPTwWkBE9CpsDvf2FZDxuWRk967aKvRIDdT3zBQG9htmkPFdUHzxqM7E954jyvOczBLqtqNM85JBlOw7F2bwhqh89h04MPacqWT2psyW9NZjUvHqjRj0YK6m8BV1SvaNkb7xRs4A7Fd63PKp7ZbrmkVG9lxjovYeUpT3gVUC9DMC1vSY2KT13h1A9ozGxvVqvaD3M 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 mvdNyfzsxAl09eRxFvR8+5LoMgjy9LOi6vUEfBT0MAZ+8ji6mvUxFr73FFpU83oEuPJZnWj0kXg8+EGKTPeaoULxyIYQ91IMOvdGoAD3aSFW8Z+yivQcYxz11ZwC9XCkpPZxwUr0ZjXI9zpcgvcoXnjxvFuY8uSNtPc0OjrvUJQA9lw6JOyeKQzu2mQk8Nb3xu/CJnD2nW1g9tguVPKv4hj3GVAS+w9rGPZ/rfLzxbj09T0Dxu+2igr3DApU8TUJvvEO9mT06cVQ95bJDPYkwlrzsNI88MO9puzdQiTzm8K68CY1RvQC3aj1Ts5a7LRtTvQ05yrzvx+E8C4gwvc5ILD3cy+E88E+wvYyDGbol5CM9NvzFvM/VB73dbJQ9xcFiPK0GqztUrWw98JFePY5fy7wtMTY9zGNJPU9rGD0JkKW8J5yovUct3T1COvk6NNLaO6tKl7vbeK48JkXDu85LYz1F6zk9+jQ4PYJ2rbxo2AS887SBPSwvkLkgDWy7GpgjvcI9bz1M uHZM9Db4zPJDNrD2H8By+G5+lPevNAjo1E449ly2xPNuqxLws4AY9ZgKUPUg0qz0e72U9Enrdu0l1Ob2uBFe8qVMxvUOkJL38u7+6GCnJPIHVWjyvLQO8wffCvXK7Cr2AH0s9zqdDvYYV2T3PuLm8W12UvWwpPz3nEZI9Kik2vPEhvL2Y0uY88SFNPUWcTDyD3Ms9FlUnPQZ2kL22QeQ8XyMTvXZtrj2OUbu7POuIvU1jiD36Q7e9EpgxPD2TIb3L/kk9mBB7PPI7r7kY6xg9jaDHPHr5Gb12Sz69FPaoPB7hsbzFoWm9WRfoPMPmlj0WSXS6j6r1u5SEhT3Th9y9h0b8PWmSQr26aQG9+l+xvEEYLjyk2g09Z6U9PJRM7jl3IAy8OPi5vKmdy72MDHI9uOnFvMpGkr1Opkw9F3frOwlchT1c16W8xR8UvW+dBzyAcQI97ljTvcyL77tYmvW7lJK7vabfE71yyGy88jtPvQWsyrwSi/e7iUcvOxktUT11hoo96YgM 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 WPUaO1704x/O94pOkuztoib0qknO9fQJbPMcQZrzFLz67zHdfO1skSz0YFia8nGo5vT9Anb3ebQg9HYNIvG83g7zmQfW5JAFTPC+be7pTjbQ96rpzvR9WX71aTeG8LqAtvYX9rb1msS89m+MfvUCjvT3XXq+9p5zBvOqnXT0rjOu8w2ztvZkspz0//Wo89HAzvA2YyTwB1Gs94hlFPcGR5b2TjiY91B+RPUXX4Ds24sm8vVOyPS8By728xQW9gPAwvRdtMzmVch09oV0CuzVs3b12rrm9W13lPQSxsDsX0WE91NMKvXxxDT1tM2U9nSkrPbktLjuut7M7KUYbPBHhE71j7ls9BGxvu8noqj2KaC+9T+BpvS3zrjwJsXc8cdPCvRpCTL0gHMk9G/6pvFIyqrnGtnO8c+P5PPcnlT31ooM9cplfvbWfOL0y5407YFUTvCz/drwGEi69I9NbvVICKT0IGBg8wuZkvZigpT2kOka94d7KvQGfsj3XXuS8trEKvDT9kz0M GIhY9GmsQvePoyL2NkrM8AtbjPdRaJ7peRDC7qehtPZU/xb3lSA46XEeJvUiZAj1KOXI8PZyjOwZe971JxP67QzvjPbeUi72bpn89JK8PvfdLDz1VzD88x3GfPI0EXzzKC468LkMDPJRNh70tess8FwpZPBBnoz2Cdra99DUHvb4U5jwlsS49irOKvbzkur2zQe09vwQ7vKCkQD26O4Q8GQWRPNpXND1FOJy82ioIvBP5kTwIeOM8mTyLvY2HKj2FGiy8MTEcvdI0AT3jEeG8ubvivdlEiD0ILwi9sAu3vXt7TTyFZ/o8TgAbvSqDsz1aavQ8oAYEvUDyF74oz6s9R077PChE27xciNM87j+bPaAx3rwTUBG9vKQMvXZ7Prx2hBI9E2hwO3hQur1gDpW8MCL0PEdkRz2c08y8Xm+fPKb6s7wopZE90HtkPfh1DbxGvBc9OLw8Parorr3Mz/e8RrcWuyskGD15s5y9X5fYvKEl7zx4Ep49S1givYKg8bwr04s9/D4M +vfldO7tFSRo9UOwOPJtwqLzSSRK9HZGsvcnzEr2f6KG8UqhevBYkAb1JnTA8W4djvTRtgbo5dJS9ldwOvZGqUz1ygRe957NRveNOUrxd/mc9zF7nvBWqfj0zH9m81DQ/u5engr0CNQ49frYYPFf7FL0dHvm8trm5PaGEp71YQxY9zcz7vLovTD2iPDA8C2l3PWX5P71IQkm9432jPRLfVj0hit88KQSVvPKyyjzndRc9qz2LPBnIsL1oIR284slHPEA2iDxp7xg9UUABPU7Pij0K/cQ74HYEvClL9zsalaI9pEtfvbi/ib3104g9B/IhvKftSrzPS9q8nY28vARGjrw6SFe9KhdwvaoP1Duq0ae812EevW5qOLzERS69tJCPvZRQgD2Mksy9I1ZpO7kqMj6FIoc9OF4/O87Qszzl1gU8conlvJ/jGj1oO7w8GwQPvQgE4r0eRiK9d/SyvMnmVr0pegA8+hwAPcg3i722USq9iooHPWlJhrvHLz6789b7PWHySj2M 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 nvdW19j12mjG9894SvemmJD00YXE9AFcMvQQ3sTxyU/s80u+8O0zkjb1f4cc84KGiPVPAcLryDSI9e2ZUvNMx2DyRS0m8/LULPXOAgrxkdkw91f/sPbhuO70c/8o8ltu3u/xb1bxXvZY8oWUBvQ9sILwHJBw9/UcSPfn1c71wLQ27E2VxvQOpQ71UJtS7Kz+QPcQ2PL2SRcs8ySuKvTp8Vz3JFcY92fxbvVDRTT23cIo9SAubPJQjM73U2YA8L7EYvaTqL7z+EhO8DubuvTOlA75RwS+9MaYqu2OVVL3ji0C8haoevYKF0T11eo69FiVrvYgM7rqnS2k9OkQSvcXcJD3wdFK9OsBTvesoFT3g+ho9c6WLvbzcDL3Jq668HBagPCtpOTxlKPU97cunPcDAKjuCT4+8wdahOy0njz2HrcU8Kxn7OfXDCT2JVJq9ssfIPExxDb0Jiiw9L3bpvHJMNL2OVsO88NcfPb7Co72wIqW9JmJ0Pb1goTwJzaU8DtTHPLM9nLsM 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 qvecPQD3d1S89YBOwvNfBuD1x7+M7QH9JvNOQN71lGRS8JGX/OsAz17emiE69pSCsvP1ILT0nM7Y8SinvvM76Rj3U1Ra9FzH/vf1MKT1Nmv+7acRiPPa+PD3Kfi49mSrKvEJvNL0l34A9nSWJuxpN77xw1p88kNCOPUnhVL2YPg09JZYzPLXmXr1q5dM8y3uivB9ghL3vnbK9eMlbPRuEQL13k3k9dh/PPMbEuTy4GdQ9HQNOPZqBPj00wJu9wyRDPfu6mb29JmO8HNSSPEDcvz2g9Bk7DJQKvWfmST17OLg7hfwkvZmvwLsWxuQ8MrLzOwnxC71CIp489dI7vQmW/zudRgC8tRCkusMPLjwO8Ho9NOTlPATjLj2148G6KvinvHTF3Lu6vDc9XVpmvaYQRj2g47o8cug3vSw2lD1+Xjm9/eHgPKkHnzyf2049yXbKuoXcoryUjMc8p/QSvEi6KL27J2a6rT09PJX52rzlTtG7BN1ovYZhiby8sVG9w/rMPI+5wb3M 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 mHO88FbcaPQzyDL0HqlK9fkwhvbH1Lj0BlQI94LpPPZanojxWShg9MEAGvTORaD3cayq9ZWHOvFmUhr00mDC92ajSveNjlb1jdGm9WPXovA4AQr2Dpto9GwAyvcRetzyQ4yu8zPt6Pd7OL70u2eg7vc0dPQAv+jxqurs8kbMrvT3BmL1uvXg9TQ7dvdq8W70GHrW7+VmKPD7EBb2Oqg68NIUJPVdjaj2ckpm9YmSKPYTdLL3Hl4c9bfq6uwFhkD1K6qk9Tg+CPRbVEj36+qi7K7C3uu+4QTyM3dm8bjgzvcG31btx4Vy7VBK1vYA1k72xwbS8ScZOvNuylr27rmK8KTijva48Pj0b5RE8sbWvPEIbnT3y82A9mOT6vIGKmT25z185/YclvdtRory6Sdq7rOkfu+balDwozOC6kAA3vX/3BD2Vshs+6O9zPMQzv7zUaKG7tw5jPSpK2Dw9dtu72D1gvfL3ADzstpo8qjmAPelI3jvUr8k8SW5Qve/g9DuvJok9OA5M SPaIPMb15S4C8DEhyvU3H5zzUlai8MYTGPB4vKT3goaI9Rc2VvdJwzD0iHiw7UPDmPXQX/TsV1OS7ZZ0FPECVS7zKsI29FYsLvQT+Cj1zFkA9sowWveQ8Zb0+HpI70HMpPTbHqb0AGGe8oAyqvQGYoT0DtQQ8tm/Jtm+aDr1+6NI8ZSm4vTOEiD3rgS+9dMGxu/+Blrx9r1I7zuztPJelV72rANk8J2jyu2pV/DzoSqw9LqsNPekLKT2htsG8r7a0vH64gby+8408gkhpvUZInj1bTZU8fQ0yPMppKrx/2Gs79VBpvKAofT1NiyE9deisPHXThjxWOBW9mPi7uPQ+KTwp0VO86P6xO1TaKj2gbsc85iYBPInJvT2GHGy9DMBsPWBBUDqvGpk831wFvAmklLujWx49WN0CvJo3Rz0vpgE8bcU/PenIKL0tRXA9panuPNkf1bv6EEG8BJCuvcnDgT1EW5s8mBFPvBxsFL0/+6083oUgvH9htD1coAu8ey2jvY+GRz3M 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 ivSgrAL0yPKo9MEb4vPQV8z0UXyS9yWF+PRjr47zsGpY9hedqPQ451DwhfCi9Gl+PvN0Slz1QBf26wzT1OnqPVr1MoEi9MurRvUlCTj3E14S9y/sNvQCQQT0/Afg885CbvGyRvb22VT89N2k8PauR3zzLOhs+rWDTPYeVeby3hEE8CcSRPbxpqz1OB9E8r5PdvTpOTD2pUlu9HkeYPYr9Tr2e4QY9h4bzvJz7VrxC8fA9VywXPTcgrzuI6Bc92aEfPah74TzeBN446l0FPZN8iT164fQ88ZZnPSrUej1Vokq90XYgPF1WGL3qd7k8qneqvSBBP72wIp09QPuMOxQJ2z0rRKK8PEaePaILzbwmcCE8V7ZzvB5367xXOiE9+4hfvd02vz0wONq7X0E5vdHVn7wdqo68r4AEvUSsUT3p4tC9eyOmvRwqiTyGeYQ9DPc1PUPlqLzadMs9i0LIvBWLvz2ZpRw+t7O8PVSi+Tv+8k894B+0O7MfnT1XdzM9z8oTvk1CxLvM 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 7PX5xsr0gEOa9kWF8PYsCKT1+j5W8iTNXPSngoT1IxAE9jJSCvO4eFT6oCHu8R/WQvZ+v6bviOhY9eWqMvdUoET3+tkG8n2VIPehmVz2fdwU9AIe0vU27Gr7HwOm7e3qjPC0dXb3vLQ+82vJfvbc/kT1ju448t5QTPZm3jj0pWoc8Ml9fvXqawT3o0JG9BPSWu/G0yT0BUhw9tMsiva9zxb2J0g49+rejvb4FSDzY9CM97NeTPTZGkTxtR1c93DSiPcq30DwEWpE9MU5pvQ6isb1Iyz48HO6kPZpx3719+4w97YIGPW7HmLoaaJU9vUOVPewa5bxLrKO91dDmvJxpeTylxqe65D+VvJkXFz3eJ7c8AtUoPRyZCD6KbYk8Vrx2vet9MDvAzLI9yKmJvRVly7y/SxQ9ucIVPHqcDD1UzRo97wIKvqpAer1cH7Y7fa7qu68Lizz37Lg7to/uvHlpBT5H33S9IN9gvUdlIz3qj4e9rH+qu0WOzz0dZ2O8Vqiwvd3N+DyM 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 cgCk8REP1u5FRqD2dVBg9fh4IvV8zY72YbF49jb1cvbq3FbyS25A8QTE8PbcJE70ZM2A7D50zvVfK1LsMBzC9USaOu/4qRDyjWxU7rAKQvBM2sjz7wcs80u44Oz1euD2ob6o8foFMvSBuhz0dvCE92OnYvKeDBL3ZfR69ubRjvZtetLyfW5K9doWGvX8Pnr1AiFC8Y7CaPZ/30TuVrOq8V2hNPV0/rr0u9gm8YCJ0PX5akbubPGm9DoyuPRYVCr0p35I7fbiavSWR3LwKx3A8o9LHPbefvL06QqK9omWYPA8GAj2sLmS9ynvSOy8eCj3Anjw91zVJvZWkYzzdgos9ZCMNvV1hI717+Cw957aAvdquL71K0Ko8s8/pvLDWBD2D30Q8zc3ZvbdiG779J/a8mMQfPKfxtzuBn2u8mKG0vYIHij03hvy6fMmGPGB9xz22Akk9Xh8kvXxnLD16I4q8OAN9vGzWfjylmL48R+Z0vWr4g70x3XG9ZNOvvQkIzLuhzQk9FZEM 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 lzem+viqJvg8ZCz5U/qg9+UGQPq5p6z0qksq9bgHovS9xF77T6mS+15KLvm/2frzYkbE31BlyvvHZjj6FqMq+nvmEvrnBv763j4K+FnVmPlyzmr7uCAW+YcJnvjuxSD7k5Ju+89DdPSLi8710P+c+iWAxPZVHDr5MQbI9PIwOPgDEkD480KA+z+q6PuSccL6s/LY+eQ1ZvW5LQ76YUjm+m+sNvECbiz0YK3E+GAuhPrFQmr4/QN0+05kIPsZEMj6vvcG+blnSvl7htD6reNu9JC1YvtPfJT3Zjbq+NZZaPWOSx74ozKK+MaOvvh1yGj6GY2G+PgS0PluBgj5cF64+6K4pPmCPiT5GJK0+od3nPda6872lu5s+Zw2JPv4vDD4qwYe+KT9wPj1X9T290Rm8mF3UPovDf75XbVG+bh0XvtOBWj74epA+sDhOPriQhr6v5Q8+TSkGPqFJAT4lKZm+iNKrPY5Jcj5SQ+O++Ep6PpcIhr4yM4s+RUnSPAvTVD52B12+nHqM 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 obR0+nc4RPxbCNj9srFm+hb0XvwZmS77HNgk/O+TgPYweeT1IWHq+LaMFv7HDMT/gSA2/2MMLv2hA4D2dPLm+t1eZPu+rKD+OUaS9oOkivKG0ZT6oDNQ9fQ41PwuakL5iN1K/ZJWAvSjn/z4KpQY+T18vP0Vrdz8VH5Y+8EJaPuI+rr0EVsu/6IzJv2nDqj/v17E/", "training_traits": {"structure_gen": "Triangle", "n_layers": 4, "max_nodes": 20, "activation_func": "ReLU", "epoch_num": 6}, "classes_name": ["Cryptoadz", "Cryptopunks", "Moonbirds", "Nouns"]},m=25,b=50,y=59+11/12,w=59+11.5/12,v=60;function z(e,t){const n=Math.log(1-t)/Math.log(1-e);return e=>1-Math.pow(1-e,n)}class V{M constructor(e,t,n){const{model:r,inputDim:i}=j(t,n);this.model=r,this.inputDim=i,this.iteration=0,this.stage=0;const o=new Date(parseInt(e.birthYear),0,1).getTime(),a=new Date(parseInt(e.birthYear)+1,0,1).getTime();this.birthDate=new Date(Math.floor((o+a)/2));const l=zr.filter((t=>t[0]==e.lifeCycle))[0][2];this.growSpeed=365/l,this.cycleLength=60*l*24*3600*1e3,this.growthFunc=z(.4,.8)}updateAge(e){const t=(e.getTime()-this.birthDate.getTime())/31536e6*this.growSpeed;this.iteration=Math.floor(t/60);const n=t-60*thisM .iteration;let r;this.age=n;let i,o=0;if(n<25){let e=map(n,0,25,0,1);o=this.growthFunc(e),r=(25-n)/60,this.stage=1,this.stageRatio=map(n,0,25,0,1)}else n<50?(o=1,r=(50-n)/60,this.stage=2,this.stageRatio=map(n,25,50,0,1)):n<y?(o=map(n,50,y,1,0),r=(y-n)/60,this.stage=3,this.stageRatio=map(n,50,y,0,1)):n<w?(o=0,r=(w-n)/60,this.stage=4,this.stageRatio=map(n,y,w,0,1)):n<60&&(o=0,r=(60-n)/60,this.stage=5,this.stageRatio=map(n,w,60,0,1));n<50?i=map(n,0,50,0,780/880):n<w?i=map(n,50,w,780/880,800/880):n<60&&(i=map(n,w,60,80M 0/880,1)),this.nextStateTimestamp=Math.round(e.getTime()+this.cycleLength*r),this.statePercentage=round(100*i);let a=(25-n)/60;a<0&&(a+=1),this.nextStableTimestamp=Math.round(e.getTime()+this.cycleLength*a),this.growth=o,this.model.updateNeurons(o,this.iteration)}getBrainStatus(){return{totalNeurons:this.model.getTotalNeurons(),neuronsLife:this.model.getNeuronsLife(),stage:this.stage,inputDim:this.inputDim,stageRatio:this.stageRatio,age:this.age,growth:this.growth,nextStateTimestamp:this.nextStateTimestamp,nextStabM leTimestamp:this.nextStableTimestamp,rebirthCount:max(this.iteration,0),statePercentage:this.statePercentage}}classifyImage(e){const t=new G(e,1,e.length);return this.model.forward(t).mat[0]}}class M{constructor(e,t,n,r,i){this.p=e,this.v=t,this.size=n,this.shape=i,this.col=r}getRadius(){return 1==Oe?1*this.size/2:2==Oe?7*this.size/16:3==Oe||4==Oe?4*this.size/7:0}update(){this.p.add(this.v)}draw(e,t,n,r){const i=this.p.x*r,o=this.p.y*r,a=this.size*r,{col:l,shape:s}=this;let h,c;1==n?h=c=l:2==n?(h=dr(t,1),c=l):(h=drM (t,0),c=dr(l,1));e.stroke(dr(c,map(1,0,1,.25,1))),e.fill(dr(h,map(1,0,1,.15,1))),3==n&&e.fill(dr(h,0)),1==s?e.ellipse(i,o,a,a):2==s?e.rect(i,o,7*a/8,7*a/8):3==s&&(e.beginShape(),e.vertex(i-4*a/7,o),e.vertex(i,o-4*a/7),e.vertex(i+4*a/7,o),e.vertex(i,o+4*a/7),e.endShape(CLOSE))}}class E{constructor(e,t,n,r,i,o,a){this.center=e,this.len=t,this.angle=n,this.v=r,this.angV=i,this.c1=o,this.c2=a}getEndpoints(){const e=createVector(this.len/2*cos(this.angle),this.len/2*sin(this.angle));return[Vector.add(this.center,e),VectM or.sub(this.center,e)]}update(){this.center.add(this.v),this.angle+=this.angV}draw(e,t){const[n,r]=this.getEndpoints(),i=n.x*t,o=n.y*t,a=r.x*t,l=r.y*t,s=this.c1,h=this.c2;var c=e.drawingContext.createLinearGradient(i,o,a,l);c.addColorStop(0,s),c.addColorStop(1,h),e.drawingContext.strokeStyle=c,e.drawingContext.globalAlpha=1,e.line(i,o,a,l),e.drawingContext.globalAlpha=1}}function S(e,t){const n=random(TAU),r=random(e,t);return createVector(r*cos(n),r*sin(n))}class R{constructor(e,t,n,r,i){this.wall=n,this.maxR=i;coM nst o=t.length;this.nodes=[];for(let a=0;a<o;++a){const o=[],l=.25*t[a];for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),l=S(.02*i,.05*i),s=random(10,25)*i;o.push(new M(t,l,s,e[a],r))}this.nodes.push(o)}const a=A(e);a.unshift(e[0]),a.push(e[e.length-1]),this.lines=[];for(let e=0;e<=o;++e){const r=[],l=(0==e?1:t[e-1])*(e==o?1:t[e])*1.5;for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),o=random(5*i,10*i),l=random(TAU),s=S(.02*i,.05M *i),h=random(2e-4,.001);r.push(new E(t,o,l,s,h,a[e],a[e+1]))}this.lines.push(r)}}reflectNode(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,{p:o,v:a}=e,l=e.getRadius();(o.x-l<t&&a.x<0||o.x+l>r&&a.x>0)&&(a.x=-a.x),(o.y-l<n&&a.y<0||o.y+l>i&&a.y>0)&&(a.y=-a.y)}reflectLine(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,[o,a]=e.getEndpoints(),l=e.v;(min(o.x,a.x)<t&&l.x<0||max(o.x,a.x)>r&&l.x>0)&&(l.x=-l.x),(min(o.y,a.y)<n&&l.y<0||max(o.y,a.y)>i&&l.y>0)&&(l.y=-l.y)}update(){for(const e of this.lines)for(conM st t of e)t.update(),this.reflectLine(t);for(const e of this.nodes)for(const t of e)t.update(),this.reflectNode(t)}draw(e,t,n,r,i){const o=i/this.maxR;for(const t of this.lines){const n=t.length*r;for(let r=0;r<n;++r)t[r].draw(e,o)}for(const i of this.nodes){const a=i.length*r;for(let r=0;r<a;++r)i[r].draw(e,t,n,o)}}}function I(e,t){re(e),e.fill(0),e.rect(0,0,500,500),ie(e),e.noStroke(),e.fill(dr(cr("#000000"),.5)),e.push(),e.translate(250,250),e.scale(t),e.translate(-250,-250),e.beginShape(),e.vertex(235.2,24.9),eM .bezierVertex(215,24.6,185,11.4,164.8,11),e.bezierVertex(147.2,10.7,129.3,10.4,112.2,14.7),e.bezierVertex(95.1,19,78.5,28.5,69.6,43.8),e.bezierVertex(57.699,64.199,61.599,90.199,70.199,112.2),e.bezierVertex(78.799,134.2,91.6,154.6,97.199,177.5),e.bezierVertex(102.499,199.2,100.899,222.5,92.799,243.2),e.bezierVertex(83,268,64.6,288.3,48.9,310),e.bezierVertex(33.2,331.7,24.5,337.5,26.599,364.1),e.bezierVertex(28.2,384.1,61.399,404.2,75.7,418.3),e.bezierVertex(90,432.4,73.7,488.2,91.9,496.7),e.bezierVertex(124.2,511.6M ,159,472.5,194.3,468.1),e.bezierVertex(211.6,465.9,267.4,501.5,283.9,495.9),e.bezierVertex(340.7,476.7,298.599,428.9,355.4,409.7),e.bezierVertex(370.799,404.5,454.5,407.6,464.4,394.8),e.bezierVertex(478.599,376.3,474.7,349.3,464.299,328.4),e.bezierVertex(453.9,307.5,438.099,289.5,428.699,268.2),e.bezierVertex(412,230,419,182.6,446.1,150.9),e.bezierVertex(449.7,146.7,453.6,142.7,455.8,137.6),e.bezierVertex(459.4,129.299,457.5,119.6,454.8,111),e.bezierVertex(443.2,73.4,417.3,40.4,383.6,20.299),e.bezierVertex(358.1,5,M 343.2,-.4,313.5,0),e.bezierVertex(287.5,.4,261.6,25.4,235.2,24.9),e.endShape(),e.pop()}function C(e,t,n,r,i,o){let a,l,s;re(t),t.fill(0),t.rect(0,0,500,500),ie(t),t.noStroke(),t.fill(dr(n,.5)),1==i?(l=0,s=25,a=map(o,0,25,500,0)):a=0,t.rect(0,a,500,500),e.noStroke(),e.fill(r),e.rect(0,0,500,500),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.M 4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezieM rVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),eM .bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.M 1,435.1,373.8,435.2,373.8),e.endShape(),e.fill(n),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6M ,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVM ertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bM ezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),re(e),e.fill(r),e.beginShape(),e.vertex(184.3,473.2),e.bezierVertex(164,473.2,144.7,462.099,134,444.3),e.bezierVertex(131.7,440.5,129.1,438.5,125,437.1),e.bezierVertex(97.3,428.1,80.5,400.6,85.2,371.8),e.beM zierVertex(86.3,365.1,85.8,364.1,79.9,361.2),e.bezierVertex(57.2,349.8,46.2,323.3,54.3,299.7),e.bezierVertex(54.7,298.599,55.1,297.7,55.5,296.9),e.bezierVertex(55.6,296.599,55.8,296.4,55.9,296.099),e.vertex(57.9,291.499),e.vertex(62.5,293.599),e.bezierVertex(64.9,294.7,67.3,295.799,69.5,296.9),e.bezierVertex(74.5,299.299,79.1,301.599,83.9,303.099),e.bezierVertex(89.8,304.9,96.5,305.499,102.7,305.9),e.bezierVertex(102.8,305.9,102.9,305.9,103,305.9),e.bezierVertex(106.6,305.9,108.9,302.799,109,299.799),e.bezierVertexM (109.1,296.199,106.6,293.4,102.7,292.799),e.bezierVertex(101.3,292.599,99.9,292.4,98.4,292.299),e.bezierVertex(94.3,291.799,90.1,291.299,86,289.9),e.bezierVertex(68.9,284,56.5,270.2,52.7,252.799),e.bezierVertex(48.9,235.499,54.5,217.7,67.6,205.299),e.bezierVertex(71.9,201.299,72.7,198.1,70.8,192.399),e.bezierVertex(64.2,172.2,68.8,153.99,84.2,139.599),e.bezierVertex(94.2,130.199,105.5,125.399,117.8,125.399),e.bezierVertex(124.3,125.399,131.1,126.799,137.8,129.599),e.bezierVertex(157,137.399,167.9,152.799,169.4,173.M 99),e.vertex(169.4,174.399),e.bezierVertex(169.5,175.899,169.6,177.2,169.9,178.299),e.bezierVertex(170.7,181.2,173.2,183.2,176.1,183.2),e.bezierVertex(176.299,183.2,176.5,183.2,176.7,183.2),e.bezierVertex(180.1,182.899,182.6,180.299,182.7,177),e.bezierVertex(183.1,162,178.299,148.2,168.399,136.1),e.bezierVertex(158.2,123.5,144.899,115.8,128.799,113.199),e.bezierVertex(123.499,112.299,120.399,109.799,118.899,104.99),e.bezierVertex(113.899,89.699,120.699,72.299,134.899,64.499),e.bezierVertex(139.99,61.699,145.799,60.M 199,151.7,60.199),e.bezierVertex(162.2,60.199,171.899,64.799,178.1,72.699),e.bezierVertex(179.6,74.6,180.799,76.6,181.9,78.499),e.vertex(182.2,79.099),e.bezierVertex(183.2,80.699,185.2,83.299,188.4,83.299),e.bezierVertex(189.5,83.299,190.6,82.99,191.7,82.399),e.bezierVertex(195.1,80.599,196,76.99,194,72.799),e.bezierVertex(190.1,64.799,184.1,58.499,175.6,53.299),e.bezierVertex(174.6,52.699,173.7,52.099,172.5,51.499),e.vertex(170.5,50.299),e.vertex(163,45.899),e.vertex(170.5,41.599),e.bezierVertex(182,34.99,193.1,30M .799,204.4,28.599),e.bezierVertex(208.6,27.799,212.9,27.399,217.2,27.399),e.bezierVertex(217.6,27.399,217.9,27.399,218.3,27.399),e.bezierVertex(231.4,27.599,242.7,38.199,243,50.599),e.bezierVertex(243.4,64.899,243.3,78.99,243.2,93.799),e.bezierVertex(243.2,99.799,243.1,105.899,243.1,112.099),e.vertex(243.1,119.199),e.vertex(236.4,116.799),e.bezierVertex(235.7,116.499,235,116.299,234.4,115.99),e.bezierVertex(233.4,115.599,232.6,115.299,232,115.199),e.bezierVertex(230.6,114.899,229.2,114.599,227.8,114.299),e.bezierVeM rtex(223.8,113.499,220.1,112.699,216.4,112.499),e.vertex(216.2,112.499),e.bezierVertex(212.5,112.499,210.7,115.599,210.6,118.599),e.bezierVertex(210.4,122.399,212.7,125.099,216.4,125.399),e.bezierVertex(230.1,126.399,238.9,133.099,242.3,145.199),e.bezierVertex(243.2,148.399,243.2,151.599,243.2,154.499),e.vertex(243.2,155.099),e.bezierVertex(243.2,254.199,243.2,330,243.2,400.599),e.bezierVertex(243.2,401.99,243.2,403.4,243.2,404.9),e.bezierVertex(243.3,411.099,243.3,417.599,242.3,423.9),e.bezierVertex(238.1,449.2,21M 9.6,467.799,194,472.5),e.bezierVertex(190.9,472.9,187.6,473.2,184.3,473.2),e.endShape(),e.beginShape(),e.vertex(315.8,473.1),e.bezierVertex(309.3,473.1,302.8,472,296.5,469.9),e.bezierVertex(270.4,461,253.8,434.9,257.1,407.9),e.bezierVertex(260,384,273.8,366.8,297,358.3),e.bezierVertex(297.7,358.1,298.3,357.8,299,357.6),e.bezierVertex(299.8,357.3,300.6,357.1,301.2,356.8),e.bezierVertex(304.3,355.4,306,351.8,304.9,348.7),e.bezierVertex(304,345.9,301.7,344.2,299,344.2),e.bezierVertex(298.6,344.2,298.1,344.2,297.6,344.M 3),e.bezierVertex(288.1,346.3,279,350.9,269.7,358.3),e.bezierVertex(268.9,358.9,268.1,359.6,267.2,360.4),e.vertex(265.5,361.8),e.vertex(258.5,367.6),e.vertex(257.4,358.6),e.bezierVertex(257.3,358,257.3,357.5,257.2,357.1),e.bezierVertex(257,356,256.9,354.9,256.9,353.7),e.bezierVertex(256.9,334.8,256.9,316,256.9,297.1),e.bezierVertex(256.9,260.3,256.9,222.3,256.8,185),e.bezierVertex(256.8,170.7,268.3,158.8,282.5,158.4),e.bezierVertex(284.8,158.3,286.7,157.6,287.9,156.2),e.bezierVertex(289.099,154.9,289.599,153.2,289.M 5,151.3),e.bezierVertex(289.3,147.5,286.7,145.1,282.7,145.1),e.bezierVertex(282.5,145.1,282.2,145.1,282,145.1),e.bezierVertex(278.8,145.3,275.5,146.1,272,146.9),e.bezierVertex(270.9,147.2,269.8,147.4,268.6,147.7),e.bezierVertex(267.9,147.9,267,148.2,265.8,148.7),e.bezierVertex(265.1,149,264.4,149.3,263.5,149.6),e.vertex(256.8,152),e.vertex(256.8,114.6),e.bezierVertex(256.8,95,256.8,75.4,256.8,55.9),e.bezierVertex(256.8,38,267.2,27.3,284.6,27.3),e.bezierVertex(285.3,27.3,285.9,27.3,286.6,27.3),e.bezierVertex(299,27.M 9,318.7,34.5,329.6,41.9),e.vertex(336.1,46.3),e.vertex(324.4,53.3),e.bezierVertex(316.2,58.2,310.2,64.6,306,72.9),e.bezierVertex(304.2,76.4,305.1,78.5,306.1,80),e.bezierVertex(307.4,81.9,309.4,83,311.6,83),e.bezierVertex(313.7,83,315.7,81.9,317.1,80.1),e.bezierVertex(317.4,79.7,317.8,79,318.1,78.4),e.bezierVertex(318.4,77.9,318.7,77.3,319,76.8),e.bezierVertex(325.3,66.2,336.3,59.9,348.5,59.9),e.bezierVertex(353.2,59.9,357.8,60.8,362.1,62.7),e.bezierVertex(377.6,69.3,386,86.7,381.7,103.2),e.bezierVertex(380.7,107.1,M 378.5,111.8,371.1,113.1),e.bezierVertex(342.7,118.1,322.2,139.1,317.8,167.8),e.bezierVertex(317.4,170.3,317.3,173.2,317.4,176.5),e.bezierVertex(317.5,180,320.1,182.8,323.5,183),e.bezierVertex(323.6,183,323.8,183,323.9,183),e.bezierVertex(327.1,183,329.8,180.6,330.3,177.2),e.bezierVertex(330.6,175.7,330.7,174,330.9,172.3),e.bezierVertex(331.1,169.8,331.4,167.3,332,164.7),e.bezierVertex(337.3,141.9,357.7,125.4,380.7,125.4),e.bezierVertex(382.5,125.4,384.3,125.5,386.1,125.7),e.bezierVertex(412.8,128.9,432.6,150.9,432,M 176.9),e.bezierVertex(431.9,182.3,430.9,187.7,429.1,192.7),e.bezierVertex(427.2,197.9,428,201,432.3,205),e.bezierVertex(446.8,218.7,451.8,236,446.6,255),e.bezierVertex(441.4,274,428.3,286.5,408.7,291.3),e.bezierVertex(406.1,291.9,403.6,292.1,401.1,292.3),e.bezierVertex(400,292.4,398.9,292.5,397.9,292.6),e.bezierVertex(393.6,293.1,390.9,295.7,391,299.5),e.bezierVertex(391.1,303.4,394,305.8,398.5,305.8),e.bezierVertex(409.9,305.8,420.8,302.6,431.1,296.4),e.bezierVertex(431.8,296,432.5,295.5,433.2,295.1),e.bezierVerteM x(433.8,294.7,434.5,294.3,435.2,293.9),e.bezierVertex(436,293.4,436.6,293.2,437.2,293.1),e.bezierVertex(437.4,293,437.7,292.9,438.1,292.8),e.vertex(442.5,291.4),e.vertex(444.2,295.7),e.bezierVertex(450.9,312.4,449.5,328.4,440,343.4),e.bezierVertex(435.3,350.8,428.7,356.7,420.2,361.1),e.bezierVertex(414.3,364.1,413.7,365.2,414.8,371.7),e.bezierVertex(419.5,400.2,403,427.6,375.6,436.9),e.bezierVertex(371,438.5,368.3,440.7,365.8,444.7),e.bezierVertex(355.2,462.5,336.4,473.1,315.8,473.1),e.bezierVertex(315.8,473.1,315.M 8,473.1,315.8,473.1),e.endShape(),ie(e),e.fill(n),e.beginShape(),e.vertex(120.2,279.9),e.bezierVertex(117.9,279.9,112.4,279.299,112.2,273.599),e.bezierVertex(112,267.7,117.4,266.7,119.7,266.599),e.bezierVertex(133.1,265.799,143.1,259.499,149.3,247.899),e.bezierVertex(149.6,247.299,150.1,246.399,150.3,245.399),e.bezierVertex(150.6,244.299,150.5,243.299,150.5,242.7),e.bezierVertex(150.5,242.6,150.5,242.5,150.5,242.299),e.vertex(150.3,238.799),e.vertex(141.1,235.99),e.bezierVertex(114.6,227.799,95.6,202.499,95.9,175.7M 99),e.bezierVertex(95.9,173.99,96.4,168.199,102.2,168.199),e.bezierVertex(102.6,168.199,103,168.199,103.4,168.299),e.bezierVertex(104.8,168.499,108.2,168.899,109.2,175.599),e.bezierVertex(109.3,176.599,109.5,177.599,109.6,178.499),e.bezierVertex(110.4,184.199,111.3,189.99,113.7,195.499),e.bezierVertex(121.9,213.99,139.5,225.499,159.7,225.499),e.bezierVertex(172.1,225.499,184.1,220.899,193.5,212.599),e.bezierVertex(194,212.199,194.4,211.799,194.8,211.399),e.bezierVertex(195.1,211.099,195.5,210.799,195.8,210.399),e.bM ezierVertex(197.4,208.99,199.2,208.2,200.9,208.2),e.bezierVertex(202.5,208.2,204,208.899,205.3,210.1),e.bezierVertex(208,212.9,207.9,216.9,205,219.9),e.bezierVertex(196.5,228.6,186.3,234.3,174.7,236.8),e.bezierVertex(168.799,238.1,165.6,241,163.899,246.7),e.bezierVertex(158.3,265.9,139.9,279.7,120.2,279.9),e.vertex(120.2,279.9),e.endShape(),e.beginShape(),e.vertex(187.2,427.5),e.bezierVertex(183.799,427.5,181.299,425.3,180.799,422),e.bezierVertex(180.6,420.8,180.499,419.5,180.399,418.1),e.bezierVertex(180.299,417,1M 80.2,415.8,180.099,414.7),e.bezierVertex(177.199,390.5,156.699,371.3,132.399,370.2),e.bezierVertex(131.99,370.2,131.499,370.2,131.099,370.2),e.bezierVertex(130.699,370.2,130.299,370.2,129.799,370.2),e.bezierVertex(125.99,369.9,123.199,367.2,123.099,363.6),e.bezierVertex(122.99,360.2,125.799,357.3,129.599,356.9),e.bezierVertex(130.499,356.8,131.499,356.8,132.599,356.7),e.bezierVertex(133.199,356.7,133.799,356.7,134.399,356.6),e.vertex(138.299,356.4),e.vertex(139.1,352.6),e.bezierVertex(139.5,350.7,139.799,348.9,140.M 2,347),e.bezierVertex(140.899,343.4,141.5,340,142.399,336.8),e.bezierVertex(150.099,310.7,174.399,292,201.399,291.3),e.vertex(201.599,291.3),e.bezierVertex(203.699,291.3,206.299,292,208.299,293.2),e.bezierVertex(210.499,294.5,210.699,297.5,209.99,299.8),e.bezierVertex(209.499,301.5,208.199,303.9,203.299,304.7),e.bezierVertex(202.199,304.9,200.99,305,199.799,305.2),e.bezierVertex(194.499,305.9,188.99,306.599,183.799,308.9),e.bezierVertex(165.499,316.799,155.199,331.299,152.99,352),e.bezierVertex(152.399,357.8,154.49M 9,361.7,159.699,364.5),e.bezierVertex(178.199,374.4,189.399,390,193.099,410.9),e.bezierVertex(193.699,414.299,193.899,418,193.599,422),e.bezierVertex(193.399,425.2,190.899,427.5,187.399,427.5),e.vertex(187.2,427.5),e.endShape(),e.beginShape(),e.vertex(364.3,281.1),e.bezierVertex(346.3,280.6,332.9,272.8,323.5,257),e.bezierVertex(321.6,253.9,320.4,250.2,319.2,246.7),e.bezierVertex(317.7,242.2,315,239.799,310.5,238.799),e.bezierVertex(298.5,236.299,288,230.7,279.4,222.1),e.bezierVertex(276.7,219.4,274.9,215.299,278,21M 1.9),e.bezierVertex(279.4,210.3,281,209.6,282.6,209.6),e.bezierVertex(284.4,209.6,286.4,210.6,288.3,212.5),e.bezierVertex(297.8,221.8,310.4,226.9,323.9,226.9),e.bezierVertex(340.2,226.9,355.1,219.3,364.8,206.2),e.bezierVertex(371,197.8,374.2,188.5,374.5,178.5),e.vertex(374.5,177.9),e.bezierVertex(374.5,177,374.5,176.1,374.7,175.4),e.bezierVertex(375.3,171.8,377.9,169.5,381.3,169.5),e.bezierVertex(381.4,169.5,381.5,169.5,381.7,169.5),e.bezierVertex(385.4,169.7,388,172.4,388,176.1),e.bezierVertex(388.1,190.7,383.4,20M 4,374.2,215.8),e.bezierVertex(365.8,226.5,354.7,233.9,341.2,237.9),e.bezierVertex(340,238.3,338.7,238.6,337.3,239.1),e.bezierVertex(335.9,239.6,335.1,240.4,334.7,240.9),e.bezierVertex(334.599,241,334.5,241.1,334.4,241.2),e.vertex(331.799,243.6),e.vertex(333.199,246.8),e.bezierVertex(338.199,258,346.799,264.9,358.699,267.3),e.bezierVertex(360.199,267.6,361.599,267.7,362.99,267.9),e.bezierVertex(363.599,268,364.299,268,364.899,268.1),e.bezierVertex(369.099,268.6,371.799,271.4,371.499,275),e.bezierVertex(371.199,278.6M ,368.299,281.2,364.399,281.2),e.vertex(364.3,281.1),e.endShape(),e.beginShape(),e.vertex(323.9,437),e.bezierVertex(323.7,437,323.5,437,323.299,437),e.bezierVertex(319.599,436.7,317.299,434.1,317.4,430.2),e.bezierVertex(317.9,406.099,328.299,388,349.5,375),e.bezierVertex(350.7,374.2,352,373.5,353.4,372.8),e.bezierVertex(354.099,372.4,354.7,372.1,355.299,371.7),e.vertex(357.499,370.5),e.vertex(357.799,368),e.bezierVertex(360.4,346.6,345.199,323.7,323.9,317),e.bezierVertex(319.099,315.5,314.099,314.9,309.299,314.4),e.M vertex(308.199,314.299),e.bezierVertex(305.99,314.099,300.799,312.9,300.899,307.299),e.bezierVertex(300.99,303.499,303.899,300.9,308.099,300.9),e.vertex(308.299,300.9),e.bezierVertex(327.099,301.299,343.099,308.7,355.699,322.9),e.bezierVertex(364.299,332.5,369.399,344.099,370.99,357.299),e.bezierVertex(371.099,358.4,371.299,359.4,371.499,360.499),e.bezierVertex(371.599,360.99,371.699,361.499,371.799,361.99),e.vertex(372.499,365.899),e.vertex(377.899,366.199),e.bezierVertex(378.799,366.299,379.699,366.299,380.599,36M 6.399),e.bezierVertex(385.099,366.699,387.899,369.399,387.799,373.299),e.bezierVertex(387.699,377.099,384.99,379.599,380.799,379.799),e.bezierVertex(369.799,380.199,359.99,383.299,351.899,389.299),e.bezierVertex(338.799,398.799,331.699,411.699,330.699,427.499),e.vertex(330.699,428.299),e.bezierVertex(330.599,429.199,330.599,430.099,330.499,430.799),e.bezierVertex(330,434.7,327.5,437,323.9,437),e.endShape()}function T(e){return e[0].map(((t,n)=>e.map((e=>e[n]))))}function A(e){return e.map((e=>Array.isArray(e)?A(e):M e))}function D(e,t){return floor(random(e,t))}function k(e){let t=0;for(const n of e)t+=n[1];let n=random(t),r=0;for(const t of e)if(r+=t[1],n<r)return t[0];return null}function L(e){for(let t=1;t<e.length;++t){let n=D(0,t),r=e[t];e[t]=e[n],e[n]=r}}function P(e){return null==e||""===e}function O(e){return new Promise((t=>setTimeout(t,e)))}function F(e,t,n){let r=0;for(let i=1;i<=1e3;++i)for(let o=1;o<=1e3;++o)if(e*o%(t*i)==0){let e=1*i/o;abs(e-n)<abs(r-n)&&(r=e)}return r}function N(){let e=60*(new Date).getTimezoneM Offset()*1e3;return new Date(Date.now()-e).toISOString().slice(0,-1)}function B(e,t,n){let r;if(push(),textSize(e),textWidth(t)<=n)r=t;else for(let e=0;e<t.length;++e){const i=t.slice(0,e+1)+"...";if(textWidth(i)>n){r=i;break}}return pop(),r}function Y(e){var t=e%10,n=e%100;return 1==t&&11!=n?e+"st":2==t&&12!=n?e+"nd":3==t&&13!=n?e+"rd":e+"th"}class G{constructor(e,t,n){this.n=t,this.m=n,this.mat=[];let r=0;for(let t=0;t<this.n;++t){this.mat.push([]);for(let n=0;n<this.m;++n)this.mat[t].push(r<e.length?e[r]:0),r+=1M }return this}copy(){return new G(this.mat.flat(),this.n,this.m)}}class H{static __linear=e=>e;static __relu=e=>Math.max(e,0);static __leaky_relu=e=>e>0?e:.2*e;static __sigmoid=e=>1/(1+Math.exp(-e));static __tanh=e=>Math.tanh(e);static __apply_unary_op(e,t){const n=e.copy();for(let e=0;e<n.n;++e)for(let r=0;r<n.m;++r)n.mat[e][r]=t(n.mat[e][r]);return n}static linear=e=>H.__apply_unary_op(e,H.__linear);static relu=e=>H.__apply_unary_op(e,H.__relu);static leaky_relu=e=>H.__apply_unary_op(e,H.__leaky_relu);static sigmoM id=e=>H.__apply_unary_op(e,H.__sigmoid);static tanh=e=>H.__apply_unary_op(e,H.__tanh);static __add=(e,t)=>e+t;static __mul=(e,t)=>e*t;static __apply_binary_op=(e,t,n)=>{"object"!=typeof t&&(t=new G([t],1,1));const r=e.copy();for(let e=0;e<r.n;++e)for(let i=0;i<r.m;++i)r.mat[e][i]=n(r.mat[e][i],t.mat[e%t.n][i%t.m]);return r};static mul=(e,t)=>H.__apply_binary_op(e,t,H.__mul);static add=(e,t)=>H.__apply_binary_op(e,t,H.__add);static matMul(e,t){const n=new G([],e.n,t.m);for(let r=0;r<n.n;++r)for(let i=0;i<n.m;++i)forM (let o=0;o<e.m;++o)n.mat[r][i]+=e.mat[r][o]*t.mat[o][i];return n}static softmax(e){const t=H.__apply_unary_op(e,(e=>Math.exp(e))),n=t.mat.flat().reduce(((e,t)=>e+t));for(let r=0;r<e.n;++r)for(let i=0;i<e.m;++i)t.mat[r][i]/=n;return t}}class ${constructor(e,t){this.scale=e,this.offset=t}forward(e){return H.add(H.mul(e,this.scale),this.offset)}}class X{constructor(){}forward(e){return e.map((e=>e.flat()))}}class W{constructor(e,t,n,r){this.out_dim=e,this.activation=t,this.w=n,this.b=r}forward(e){const t=H.add(H.matMuM l(e,this.w),this.b);return null==this.activation?t:this.activation(t)}}class U{constructor(e,t,n){this.preprocessLayers=e,this.hiddenLayers=t,this.outputLayer=n,this.totalNeurons=this.hiddenLayers.map((e=>e.out_dim)),this.currentOrders=[],this.currentIteration=null}updateNeurons(e,t){if(t!=this.currentIteration){this.currentOrders=[];for(let e=0;e<this.totalNeurons.length;++e){randomSeed(100*(t+1)+e);const n=[];for(let t=0;t<this.totalNeurons[e];++t)n.push(t);L(n),this.currentOrders.push(n)}this.currentIteration=t}M const n=A(this.totalNeurons),r=n.reduce(((e,t)=>e+t))*(1-e);for(let e=0;e<r;++e){const t=n.map(((e,t)=>(e-1)/this.totalNeurons[t]));n[t.map(((e,t)=>[e,t])).reduce(((e,t)=>t[0]>e[0]?t:e))[1]]-=Math.min(r-e,1)}this.neuronsLife=[];for(let e=0;e<n.length;++e){const t=this.currentOrders[e],r=Array(this.totalNeurons[e]).fill(0);for(let i=0;i<n[e];++i)r[t[i]]=Math.min(n[e]-i,1);this.neuronsLife.push(r)}}getTotalNeurons(){return A(this.totalNeurons)}getNeuronsLife(){return A(this.neuronsLife)}forward(e){for(const t of thisM .preprocessLayers)e=t.forward(e);for(const[t,n]of this.hiddenLayers.entries()){e=n.forward(e);const r=new G(this.neuronsLife[t],1,e.m);e=H.mul(e,r)}return e=this.outputLayer.forward(e),H.softmax(e)}}function q(e){switch(e){case"relu":return H.relu;case"sigmoid":return H.sigmoid;case"tanh":return H.tanh;case"leaky_relu":return H.leaky_relu;default:return H.linear}}function j(e,t){const n=[],r=[],i=Z(t);let o=null,a=0,l=[];for(const t of e.config.layers)if("InputLayer"==t.class_name)o=t.config.batch_input_shape.sliceM (1),l=o;else if("Rescaling"==t.class_name)n.push(new $(t.config.scale,t.config.offset));else if("Flatten"==t.class_name)o=[o.reduce(((e,t)=>e*t))];else if("Dense"==t.class_name){const e=[t.config.units],n=o[0]*e[0],l=e[0],s=i.subarray(a,a+n);a+=n;const h=i.subarray(a,a+l);a+=l;const c=new G(s,o[0],e[0]),u=new G(h,1,e[0]),f=q(t.config.activation);r.push(new W(e[0],f,c,u)),o=e}const s=r.pop();return{model:new U(n,r,s),inputDim:l}}function Z(e){const t=window.atob(e),n=t.length/Float32Array.BYTES_PER_ELEMENT,r=new DatM aView(new ArrayBuffer(Float32Array.BYTES_PER_ELEMENT)),i=new Float32Array(n);let o=0;for(let e=0;e<n;e++){o=4*e;for(let e=0;e<4;++e)r.setUint8(e,t.charCodeAt(o+e));i[e]=r.getFloat32(0,!0)}return i}class K{constructor(e){this.elt=e,this._events={},this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight}position(){if(0===arguments.length)return{x:this.elt.offsetLeft,y:this.elt.offsetTop};var e="absolute";return"static"!==arguments[2]&&"fixed"!==arguments[2]&&"relative"!==arguments[2]&&"sticky"!==arguments[2M ]&&"initial"!==arguments[2]&&"inherit"!==arguments[2]||(e=arguments[2]),this.elt.style.position=e,this.elt.style.left=arguments[0]+"px",this.elt.style.top=arguments[1]+"px",this.x=arguments[0],this.y=arguments[1],this}show(){return this.elt.style.display="block",this}hide(){return this.elt.style.display="none",this}size(e,t){if(0===arguments.length)return{width:this.elt.offsetWidth,height:this.elt.offsetHeight};var n=e,r=t;if(n!==te||r!==te){if(n===te?n=t*this.width/this.height:r===te&&(r=e*this.height/this.width),M this.elt instanceof HTMLCanvasElement){var i,o={},a=this.elt.getContext("2d");for(i in a)o[i]=a[i];for(i in this.elt.setAttribute("width",n*this._pInst._pixelDensity),this.elt.setAttribute("height",r*this._pInst._pixelDensity),this.elt.style.width=n+"px",this.elt.style.height=r+"px",this._pInst.scale(this._pInst._pixelDensity,this._pInst._pixelDensity),o)this.elt.getContext("2d")[i]=o[i]}else this.elt.style.width=n+"px",this.elt.style.height=r+"px",this.elt.width=n,this.elt.height=r;this.width=this.elt.offsetWidth,M this.height=this.elt.offsetHeight,this._pInst&&this._pInst._curElement&&this._pInst._curElement.elt===this.elt&&(this._pInst._setProperty("width",this.elt.offsetWidth),this._pInst._setProperty("height",this.elt.offsetHeight))}return this}style(e,t){if(t instanceof Color&&(t="rgba("+t.levels[0]+","+t.levels[1]+","+t.levels[2]+","+t.levels[3]/255+")"),void 0===t){if(-1===e.indexOf(":"))return window.getComputedStyle(this.elt).getPropertyValue(e);for(var n=e.split(";"),r=0;r<n.length;r++){var i=n[r].split(":");i[0]&&iM [1]&&(this.elt.style[i[0].trim()]=i[1].trim())}}else if(this.elt.style[e]=t,"width"===e||"height"===e||"left"===e||"top"===e){var o=window.getComputedStyle(this.elt).getPropertyValue(e).replace(/[^\d.]/g,"");this[e]=Math.round(parseFloat(o,10))}return this}value(){return arguments.length>0?(this.elt.value=arguments[0],this):"range"===this.elt.type?parseFloat(this.elt.value):this.elt.value}mouseClicked(e){return this._adjustListener("click",e,this),this}isFocused(){return document.activeElement===this.elt}_adjustLisM tener(e,t,n){return!1===t?this._detachListener(e,n):this._attachListener(e,t,n),this}_attachListener(e,t,n){n._events[e]&&this._detachListener(e,n);var r=t.bind(n);n.elt.addEventListener(e,r,!1),n._events[e]=r}_detachListener(e,t){var n=t._events[e];t.elt.removeEventListener(e,n,!1),t._events[e]=null}}function J(e,t){var n=document.createElement("button");return n.innerHTML=e,t&&(n.value=t),ee(n)}function Q(e){var t=arguments.length>1&&void 0!==arguments[1]&&arguments[1],n=function(t){var n=!0,r=!1,i=void 0;try{forM (var o,a=t.target.files[Symbol.iterator]();!(n=(o=a.next()).done);n=!0){var l=o.value;File._load(l,e)}}catch(e){r=!0,i=e}finally{try{n||null==a.return||a.return()}finally{if(r)throw i}}};if(window.File&&window.FileReader&&window.FileList&&window.Blob){var r=document.createElement("input");return r.setAttribute("type","file"),t&&r.setAttribute("multiple",!0),r.addEventListener("change",n,!1),ee(r)}}function ee(e){return document.body.appendChild(e),new K(e)}createImg=function(){var e,t=document.createElement("img"),M n=arguments;return n.length>1&&"string"==typeof n[1]&&(t.alt=n[1]),n.length>2&&"string"==typeof n[2]&&(t.crossOrigin=n[2]),t.src=n[0],e=ee(t,this),t.addEventListener("load",(function(){e.width=t.offsetWidth||t.width,e.height=t.offsetHeight||t.height;var r=n[n.length-1];"function"==typeof r&&r(e)})),e},createInput=function(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:"",t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:"text",n=document.createElement("input");return n.setAttribute("value",e)M ,n.setAttribute("type",t),ee(n,this)};const te="auto";function ne(e){re(e);const t=e._rectMode;e.rectMode(CORNER),e.rect(0,0,e.width,e.height),e.rectMode(t),ie(e)}function re(e){e.push(),e.fill(255,255,255,255),e.blendMode(REMOVE)}function ie(e){e.blendMode(BLEND),e.pop()}File=function(e,t){this.file=e,this._pInst=t;var n=e.type.split("/");this.type=n[0],this.subtype=n[1],this.name=e.name,this.size=e.size,this.data=void 0},File._createLoader=function(e,t){var n=new FileReader;return n.onload=function(n){var r=new FM ile(e);if("application/json"===r.file.type)r.data=JSON.parse(n.target.result);else if("text/xml"===r.file.type){var i=(new DOMParser).parseFromString(n.target.result,"text/xml");r.data=new XML(i.documentElement)}else r.data=n.target.result;t(r)},n},File._load=function(e,t){if(/^text\//.test(e.type)||"application/json"===e.type)File._createLoader(e,t).readAsText(e);else if(/^(video|audio)\//.test(e.type)){var n=new File(e);n.data=URL.createObjectURL(e),t(n)}else File._createLoader(e,t).readAsDataURL(e)},XML=functionM (e){if(e)this.DOM=e;else{var t=document.implementation.createDocument(null,"doc");this.DOM=t.createElement("root")}},document.addEventListener("DOMContentLoaded",(function(){addEventListener("mousemove",(e=>{window.mouseX=e.pageX,window.mouseY=e.pageY}))})),new e("global");const oe="471";let ae,le,se,he,ce,ue,fe,de,xe,ge,pe,me,be,ye,we,ve,ze,Ve,_e,Me,Ee,Se,Re,Ie,Ce,Te,Ae,De,ke,Le,Pe,Oe,Fe,Ne,Be,Ye,Ge,He,$e,Xe,We,Ue,qe,je,Ze,Ke,Je,Qe,et,tt,nt,rt,it,ot,at,lt,st,ht,ct,ut,ft,dt,xt,gt,pt,mt,bt,yt,wt,vt,zt,Vt,_t,Mt,Et,StM ,Rt,It,Ct,Tt,At=!1,Dt=!1,kt=!0,Lt=!1,Pt=!1;const Ot=[" ","Growing","Stable","Decaying","Dead","Rebirth"];let Ft,Nt,Bt,Yt,Gt,Ht,$t,Xt,Wt,Ut,qt,jt,Zt,Kt,Jt,Qt,en,tn,nn,rn,on,an,ln,sn,hn=0,cn=0,un=0,fn=!1,dn=!0,xn=!0,gn=null,pn=null,mn=null,bn=!1,yn=!1,wn=null,vn=null,zn=!1;async function setup(){let e=windowWidth,t=windowHeight;createCanvas(e,t),et=createGraphics(e,t),Xe=createGraphics(e,t),$e=createGraphics(e,t),We=createGraphics(e,t),Ue=createGraphics(e,t),qe=createGraphics(e,t),Qe=createGraphics(e,t),je=createGrapM hics(e,t),Ze=createGraphics(e,t),Ke=createGraphics(e,t),Je=createGraphics(e,t),tt=createGraphics(500,500),nt=createGraphics(500,500),rt=createGraphics(500,500),_n(),Mn(),Sn(),await En(),Gn(),Rn(),bn=!0}function _n(){Et=parseInt(oe),randomSeed(Et),noiseSeed(Et)}function Mn(){Wt=Ir(p.training_traits),Cr(Wt)}async function En(){let e;Jt=r(),Qt=o(),[Xt,e]=await Promise.all([s(Jt),h(Qt)]),Ut=new V(Wt.visual,e.layers_config,e.weight_b64),Ut.updateAge(new Date),_n(),Wt.training=e.training_traits,Ht=e.model_name,$t=e.classM es_name}function Sn(){le=min(width,height)/1024,ut=Rr.findIndex((e=>e[0]===Wt.visual.colorPalette)),ft=[["#ffffff","#231f20","#231f20"],["#231f20","#ffffff","#ffffff"],["#104da8","#ffffff","#ffffff"],["#722F1F","#FCE1B2","#FCE1B2"],["#e88120","#f9f2e5","#f9f2e5"],["#f6b941","#2E2E2E","#2E2E2E"],["#45daaa","#012221","#012221"],["#F1F1F1","#328DFE","#328DFE"],["#111822","#D3EB8D","#D3EB8D"],["#713FF9","#D6D5E6","#D6D5E6"],["#FBDA9D","#795106","#795106"],["#8f5b62","#ead0d0","#ead0d0"],["#eae4cb","#508cac","#508cac"],M ["#ffc6cc","#cc313d","#cc313d"],["#60A900","#E0FE00","#E0FE00"],["#507DBE","#D0D1D3","#D0D1D3"],["#305848","#E8F2EE","#E8F2EE"],["#2a2634","#5b6988","#cb78a2","#5b6988"],["#590e29","#fd5e53","#fd5e53","#ffe373"],["#0a141d","#57d4e4","#328195","#2A9ECF","#0ab6a8","#57d4e4"],["#3a2d28","#d5c2ac","#df6338","#3d9895","#d5c2ac"],["#030706","#77c4d9","#77c4d9","#77c4d9","#ffffff","#ffffff","#e72020","#e72020"],["#3a4664","#92f5ff","#f9ff94","#eaa0a2","#55dde0"],["#fbfaff","#f04bb1","#f04bb1","#fac373","#82cef0","#8b31ce"M ],["#000000","#ffffff","#ff0002","#f26522","#fdff00","#00ff03","#01fffe","#0000ff","#ff00ff"]];for(let e=0;e<ft.length;++e)for(let t=0;t<ft[e].length;++t)ft[e][t]=cr(ft[e][t]);pt=[],ct=ft[ut][0],st=ft[ut][1]}function Rn(){gn=document.querySelector("#upload"),pn=document.querySelector("#inputUpload"),gn.addEventListener("dblclick",(()=>{if(!Lt&&!yn)if(In(Ie)&&cn==Ve-1)pn.click();else{if(4!=Pe&&5!=Pe&&(In(Ie)||cn!=Ve-1))return;fn=!0,dn=!0,Bt=0,un=0}})),pn.addEventListener("click",(()=>{pn.value=null,gn.style.display=M "block"})),pn.addEventListener("change",(()=>{const[e]=pn.files;e?(se=null,gn.style.display="none",Tn(URL.createObjectURL(e)),mn=e):gn.style.display="block"}))}function In(e){for(let t=0;t<e.length;++t){let n=0;for(let r=0;r<e[t].length;++r)e[t][r]>0&&++n;if(0==n)return!1}return!0}function Cn(){null!=se&&(un=0,Pt=!0,he=0,ue=0,drewLineAnim=!0,ce=(ae/2+we/2)/le,loadImage(se.elt.src,(e=>{const[t,n,r]=Gt,i=createGraphics(t,n);i.image(e,0,0,t,n),i.loadPixels();const o=i.pixels.filter(((e,t)=>t%4!=3)),a=Ut.classifyImage(M o);Zt=T([a,$t.map((e=>e.toUpperCase()))]).sort(((e,t)=>e[0]>t[0]?-1:1))})))}function Tn(e){se=createImg(e,""),se.hide(),Cn()}function An(){zn||(ce+=(width-ae-we)/tn/le),re(Xe),Xe.rect(ce*le,0,width,height),ie(Xe),un>=ge&&1==kt&&(kt=!1,un-=ge),kt&&(re($e),$e.strokeWeight(2*Fe),Jn(he,ze,ct,ct,$e),ie($e)),un>=ge&&0==kt&&(kt=!0,un-=ge,he+=1,he==en&&(++ue,he=0,ce=(ae/2+we/2)/le,1==ue&&(Pt=!1,Dn(),ye=millis())))}function Dn(){At=!0,pe=!1,me=!1,tryButton=br("Try Again",width/2-225*le,height/2+265*le,290*le,40*le,kn),closeM ResultButton=br("Close",width/2+75*le,height/2+265*le,150*le,40*le,Ln)}function kn(){At=!1,tryButton.hide(),closeResultButton.hide(),pn.click()}function Ln(){Yt=!0,At=!1,Gn(),tryButton.hide(),closeResultButton.hide(),gn.style.display="block",se=null}function keyTyped(){bn&&!1===yn&&!1===yr()&&("i"!==key&&"I"!==key||(Dt=!Dt),"b"!==key&&"B"!==key||(xn=!xn),"s"!==key&&"S"!==key||!1!==Lt||saveCanvasAtCurrentTime(),"k"!==key&&"K"!==key||!1!==Lt||save4KCanvasAtCurrentTime(),"u"!==key&&"U"!==key||!1!==Lt||!1!==At||!1!==fnM ||!1!==Pt||On())}function On(){Lt=!0,wn=null,vn=null,submitButton=br("Submit",width/2-155*le,height/2+115*le,150*le,40*le,Fn),closeSettingButton=br("Close",width/2+5*le,height/2+115*le,150*le,40*le,Yn),vt=createInput(),vt.position(width/2-252.5*le,height/2-40*le),vt.size(500*le,25*le),vt.style("font-size","15px"),vt.value(Jt||""),zt=createInput(),zt.position(width/2-252.2*le,height/2+35*le),zt.size(500*le,25*le),zt.style("font-size","15px"),zt.value(Qt||"")}function Fn(){Vt=vt.value(),_t=zt.value(),submitButton.hidM e(),closeSettingButton.hide(),vt.hide(),zt.hide(),Lt=!1,yn=!0,Nn()}async function Nn(){[wn,vn,_]=await Promise.all([c(Vt),u(_t),O(1e3)]),yn=!1,wn&&vn?(n(Vt),i(_t),window.location.reload()):(Lt=!0,submitButton.show(),closeSettingButton.show(),vt.show(),zt.show())}function Bn(){Je.textFont("Trebuchet MS"),Je.noStroke(),pr(Je,600*le,200*le),Je.strokeWeight(1*le),Je.stroke(xt),Je.fill(xt),Je.textSize(50*le),Je.text("update()",width/2,height/2+2.5*le)}function Yn(){wn=null,vn=null,Lt=!1,submitButton.hide(),closeSettingBM utton.hide(),vt.hide(),zt.hide()}function Gn(){_n(),nn=Date.now(),pe=!1,me=!1,St=Wt.training.structure_gen,Rt=Wt.visual.birthYear,It=Wt.visual.lifeCycle,Ct=Wt.training.epoch_num,Tt=Wt.training.activation_func,Ft=Mr.findIndex((e=>e[0]==Wt.visual.hardwareAcceleration))+1,1==Ft?(Nt=30,fe=40):2==Ft?(Nt=15,fe=20):(Nt=2,fe=10);const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(MM t),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),ae=100*le,ht=50*le,Oe=Sr.findIndex((e=>e[0]==Wt.visual.nodeShape))+1,dt=Er.findIndex((e=>e[0]==Wt.visual.nodeFill))+1,lt=_r.findIndex((e=>e[0]==Wt.visual.pattern))+1,de=Math.tanh(Math.log10(Xt.avgfeerate)),de=map(de,0,1,.2,.8),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],M Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;eM <Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],M ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,at=.7,pt=[],xt=ft[ut][2],gt=ft[ut][ft[ut].length-1];for(let e=3;e<ft[ut].length-1;e++)pt.push(ft[ut][e]);mt=sr(xt,gt,pt,width),bt=[],wt=[],yt=width/(Ve-1);for(let e=0;e<Ve;e++)bt.push(hr(mt,yt*e/width)),wt.push(hr(mt,yt*e/width));wt.unshift(bt[0]),wt.push(bt[bt.length-1]),hn=0,cn=0,un=0,Yt=!0;const n={xLeft:ae/8,xRight:wM idth-ae/8,yTop:ae/8,yBottom:height-ae/8},r=Ce.map((e=>e.length));jt=new R(bt,r,n,Oe,le)}function Hn(e,t){let n=Ce[e].length;return[e*we+we/2+ae/2,height/2-(n-1)/2*ve+t*ve]}function $n(e,t){le=min(e,t)/1024,ae=100*le,ht=50*le,we=(e-ae)/Ve,ve=(t-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}xe=floor(De.length*de),Le=[],ke=[],ge=floor(map(de,.2,.8,15,2));for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(randomM (1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,mt=sr(xt,gt,pt,e),bt=[],wt=[],yt=e/(Ve-1);for(let t=0;t<Ve;t++)bt.push(hr(mt,yt*t/e)),wt.push(hr(mt,yt*t/e));wt.unshift(bt[0]),wt.push(bt[bt.length-1])}function Xn(){const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`PerM ceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=mM ax(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,vM e=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le}function Wn(){jt.update();const e=4==Pe?0:Kt;jt.draw(Qe,M ct,dt,e,le)}function Un(){if(!bn)return ar(),void et.image(je,0,0);if(4==Pe||5==Pe)return Wn(),void et.image(Qe,0,0);un>=Nt&&hn<Ve&&(hn++,un=0);for(let e=0;e<hn;e++)1==dt?it=ot=bt[e]:(it=ct,ot=bt[e]),Kn(e,it,ot,$e);un>=Nt&&cn<Ve-1&&(cn++,un=0);for(let e=0;e<cn;e++)Zn(e)}function qn(){et.background(ct),Ue.background(255),Ue.rectMode(CENTER),ne(Ue),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),Ue.stroke(st),Ue.strokeWeight(8*le),Ue.fill(ct),Qe.background(255),Qe.rectMode(CENTER),ne(Qe),Qe.strokeWeight(le),qe.backgroM und(255),qe.rectMode(CENTER),ne(qe),qe.textAlign(LEFT),$e.background(255),$e.rectMode(CENTER),ne($e),Xe.background(255),ne(Xe),Xe.strokeWeight(Ne),We.background(255),We.rectMode(CENTER),ne(We),We.fill(st),We.stroke(st),We.strokeWeight(.1*le),er(lt),We.noStroke(),xn&&(We.rect(ae/16,height/2,ae/8,height),We.rect(width-ae/16,height/2,ae/8,height),We.rect(width/2,ae/16,width,ae/8),We.rect(width/2,height-ae/16,width,ae/8)),Ze.background(255),Ze.rectMode(CENTER),ne(Ze),Ze.textAlign(CENTER,CENTER),Ze.textStyle(BOLD),Ze.stM roke(st),Ze.strokeWeight(8*le),Ze.fill(ct),je.background(255),je.rectMode(CENTER),ne(je),je.textAlign(CENTER,CENTER),je.textStyle(BOLD),Ke.background(255),Ke.rectMode(CENTER),ne(Ke),Ke.textAlign(CENTER,CENTER),Ke.textStyle(BOLD),Ke.stroke(st),Ke.strokeWeight(8*le),Ke.fill(ct),Je.background(255),Je.rectMode(CENTER),ne(Je),Je.textAlign(CENTER,CENTER),Je.textStyle(BOLD),Je.stroke(st),Je.strokeWeight(8*le),Je.fill(ct),Un(),et.image(We,0,0),Pt&&An(),et.image(Xe,0,0),et.image($e,0,0),At&&(tr(),et.image(Ue,0,0)),fn&&(lr()M ,et.image(Ze,0,0)),Lt&&(or(),et.image(Ke,0,0)),Dt&&(ir(),et.image(qe,0,0)),yn&&(Bn(),et.image(Je,0,0))}function draw(){const e=Date.now();bn&&(Ut.updateAge(new Date(e)),Xn()),qn(),image(et,0,0),zn||un++}function Zn(e){let t,n=Ce[e].length,r=Ce[e+1].length;for(let i=0;i<n;i++){const[n,o]=Hn(e,i);for(let a=0;a<r;a++){const[r,l]=Hn(e+1,a);t=map(min(Ce[e][i],Ce[e+1][a]),0,1,0,.5),ur(n,o,r,l,bt[e],bt[e+1],Xe,t)}}}function Kn(e,t,n,r){let i,o,a,l=Ce[e].length;for(let s=0;s<l;s++){const[l,h]=Hn(e,s);i=Ce[e][s],a=map(Be,1/M 30,1,3,10),o=map(Ce[e][s],0,1,2*a,0)*le,o<1.5*le&&(o=0),Qn(l,h,ze,Oe,t,n,o,i,r)}}function Jn(e,t,n,r,i){for(let o=0;o<Le[e].length;o++)Qn(Le[e][o][0],Le[e][o][1],t,Oe,n,r,0,1,i)}function Qn(e,t,n,r,i,o,a,l,s){s.stroke(dr(o,map(l,0,1,.25,1))),s.fill(dr(i,map(l,0,1,.15,1))),s.strokeWeight(Fe),fr([a],s),3==dt&&s.fill(dr(i,0)),1==r?s.ellipse(e,t,n):2==r?s.rect(e,t,7*n/8,7*n/8):3==r&&(s.beginShape(),s.vertex(e-4*n/7,t),s.vertex(e,t-4*n/7),s.vertex(e+4*n/7,t),s.vertex(e,t+4*n/7),s.endShape(CLOSE))}function er(e){if(1==e)M ;else if(2==e){We.strokeWeight(1*le);for(let e=ht/4;e<width+ht/4;e+=ht)for(let t=ht/4;t<height+ht/4;t+=ht)We.point(e,t)}else if(3==e){ht=25*le;for(let e=ht/2;e<height+ht/2;e+=ht)We.line(0,e,width,e);for(let e=ht/2;e<width+ht/2;e+=ht)We.line(e,0,e,height)}}function tr(){Ue.textFont("Trebuchet MS"),Ue.textAlign(LEFT,CENTER),Ue.noStroke(),pr(Ue,800*le,500*le),Ue.noStroke(),Ue.fill(dr(st,.75)),Ue.rect(width/2,height/2-100*le,800*le,300*le,25*le,25*le,0,0),Ue.fill(st),Ue.rect(width/2-250*le,height/2-100*le,225*le,225*leM ),Ue.image(se.elt,width/2-357.5*le,height/2-207.5*le,215*le,215*le);let e=100*Zt[0][0];Ue.fill(ct),Ue.textSize(25*le),Ue.textStyle(NORMAL),1==me&&(e>=0&&e<20?Ue.text("I have a feeling this image belongs to",width/2-100*le,height/2-170*le):e>=20&&e<40?Ue.text("I have a hunch this image belongs to",width/2-100*le,height/2-170*le):e>=40&&e<60?Ue.text("I think this image belongs to",width/2-100*le,height/2-170*le):e>=60&&e<80?Ue.text("I'm almost certain this image belongs to",width/2-100*le,height/2-170*le):Ue.text("I'M m positive this image belongs to",width/2-100*le,height/2-170*le));let t=e.toFixed(2);"100.00"==t&&(t="100"),1==me&&Ue.text("I'm "+t+"% confident that I'm right!",width/2-100*le,height/2-25*le),example=Zt.map((e=>e[1])),be=Ue.textWidth('"FIDENZAAAA"'),defaultPhrase=Ue.textWidth('"PERPENDICULAR INHABITATION"'),Ue.textStyle(BOLD);const n=me?example[0]:random(example);if(1===n.split(" ").length){let e=75*be/Ue.textWidth('"'+n+'"');e>75&&(e=75),Ue.textSize(e*le),Ue.text('"'+n+'"',width/2-100*le,height/2-90*le)}else nr(M width/2-100*le,height/2-90*le,460*le,110*le,n,Ue);if(millis()-ye>1500&&(me=!0),C(tt,nt,st,ct,Pe,Mt),Ue.image(nt,width/2-370*le,height/2+70*le,80*le,80*le),3==Pe){let e;e=map(Mt,50,60,.25,1.3),I(rt,e),Ue.image(rt,width/2-370*le,height/2+70*le,80*le,80*le)}let r,i;Ue.image(tt,width/2-370*le,height/2+70*le,80*le,80*le),Ue.fill(xt),Ue.textSize(40*le),Ue.text("INTELLIGENCE INFO",width/2-275*le,height/2+115*le),Ue.textSize(18*le),Ue.textStyle(NORMAL),Ue.circle(width/2-360*le,height/2+180*le,7.5*le),1==Pe?r=`Your PerceptrM on is ${Math.ceil(Mt)} years old. It s growing and getting smarter by the day.`:2==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s stable and it has reached peak performance.`:3==Pe&&(r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s decaying and losing its luster.`),i=2==Pe?"The Perceptron remains stable for some time before entering the decay phase.":`Wait until ${new Date(an).toLocaleString("en-US")} for your Perceptron to reach its peak performance.`,Ue.text(r,width/2-350*le,height/2+180*leM ),Ue.circle(width/2-360*le,height/2+210*le,7.5*le),Ue.text(i,width/2-350*le,height/2+210*le),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),gr(Ue,width/2-225*le,width/2+65*le,height/2+265*le,height/2+305*le,"SELECT ANOTHER IMAGE"),gr(Ue,width/2+75*le,width/2+225*le,height/2+265*le,height/2+305*le,"CLOSE")}function nr(e,t,n,r,i,o){let a=i.split(" "),l=75*be/o.textWidth('"'+i+'"'),s=0,h=[],c=[],u=[],f="",d="";if(l>=50)l>75&&(l=75),o.textSize(l*le),o.text('"'+i+'"',e,t);else if(l<50){if(l=50*defaultPhrase/o.textWidth(M '"'+i+'"'),l>30){if(l>50&&(l=50),[f,d]=rr(l,n,s,h,c,a,f,d,Ue),0==c.length)return o.textSize(l*le),void o.text('"'+i+'"',e,t);for(s=0,h=[],c=[];o.textWidth(d)>n/le;)l=l*n/le/o.textWidth(d),f="",d="",[f,d]=rr(l,n,s,h,c,a,f,d,Ue)}else{l=30,o.textSize(l);for(let e=0;e<a.length;e++)s+=o.textWidth(" "+a[e]),s<=n/le?h.push(a[e]):s>n/le&&s<=n/le*2?c.push(a[e]):u.push(a[e]);for(let e=1;e<h.length;e++)f=f+" "+h[e];if(f='"'+h[0]+f,0==u.length){for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+c[c.length-1]+'"'}else if(1==c.lengthM )d="... "+u[u.length-1]+'"';else{for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+"... "+u[u.length-1]+'"'}}o.textSize(l*le);let r=1.25*(o.textDescent()+o.textAscent());o.text(f,e,t-r/2),o.text(d,e,t+r/2)}}function rr(e,t,n,r,i,o,a,l,s){s.textSize(e);for(let e=0;e<o.length;e++)(n+=s.textWidth(" "+o[e]))<=t/le?r.push(o[e]):i.push(o[e]);for(let e=1;e<r.length;e++)a=a+" "+r[e];if(a='"'+r[0]+a,0==i.length&&(a+='"',l=""),1==i.length)l=i[i.length-1]+'"';else{for(let e=0;e<i.length-1;e++)l=l+i[e]+" ";l=l+i[i.length-1]+'"'}reM turn[a,l]}function ir(){const e=45*le;qe.textFont("Tahoma"),qe.stroke(st),qe.strokeWeight(2*le),qe.fill(ct),qe.rect(width/2,e/2+height-87.5*le,600*le,90*le),qe.fill(st),qe.rect(width/2-150*le,e+height-170*le,300*le,30*le),qe.fill(ct),qe.rect(width/2+150*le,e+height-170*le,300*le,30*le),qe.noStroke(),qe.fill(ct),qe.textSize(15*le),qe.textStyle(BOLD),qe.text("PERCEPTRON INFORMATION",width/2-285*le,e+height-165*le),qe.fill(xt),qe.text("ARTWORK NAME:",width/2+10*le,e+height-165*le),qe.textAlign(RIGHT),qe.textStyle(ITALM IC),qe.text("Perceptron #"+Et,width/2+285*le,e+height-165*le);const[t,n]=It.split(" ");let r;"60 Years"===It?r="1 Year":"60 Months"===It?r="1 Month":"60 Weeks"===It?r="1 Week":"60 Days"===It?r="1 Day":"12 Hours"===It&&(r="12 Minutes"),data=[["AI MODEL NAME:",B(12*le,Ht,140*le)],["SCALE:","1:"+Te],["NUMBER OF CLASSES:",$t.length],["BIRTH YEAR:",Rt],["NUMBER OF REBIRTHS:",sn.toString()],["AGE:",`${Math.ceil(Mt)} Perceptron Years`],["ONE PERCEPTRON YEAR:",`${r}`],["STATE:",Ot[Pe]],["ACTIVE NEURONS:",`${round(ln*rn)} /M ${ln}`],["NEXT STATE TIME:",vr(new Date(on))]],qe.fill(xt);const i=data.length/2;for(let t=0;t<data.length;++t){const n=t<i,r=n?width/2-285*le:width/2+10*le,o=n?width/2-10*le:width/2+285*le,a=e+height-(135-t%i*15)*le;qe.textStyle(BOLD),qe.textAlign(LEFT),qe.textSize(12*le),qe.text(data[t][0],r,a),qe.textStyle(ITALIC),qe.textAlign(RIGHT),qe.textSize(12*le),qe.text(data[t][1],o,a)}}function or(){Ke.textFont("Trebuchet MS"),Ke.noStroke(),pr(Ke,600*le,200*le),gr(Ke,width/2-155*le,width/2-5*le,height/2+115*le,height/2+M 155*le,"UPDATE"),gr(Ke,width/2+5*le,width/2+155*le,height/2+115*le,height/2+155*le,"CLOSE"),Ke.textAlign(LEFT),Ke.fill(xt),Ke.text("UPDATE BITCOIN FULL NODE ADDRESS",width/2-252.5*le,height/2-55*le),Ke.text("UPDATE MODEL ADDRESS",width/2-252.5*le,height/2+20*le),Ke.textAlign(RIGHT),Ke.textStyle(ITALIC),Ke.textSize(15*le),0==wn&&Ke.text("(*) Invalid Address",width/2+252.5*le,height/2-53*le),0==vn&&Ke.text("(*) Invalid Model",width/2+252.5*le,height/2+23*le)}function ar(){je.textFont("Trebuchet MS"),je.fill(st),je.teM xtSize(50*le),je.stroke(st),je.strokeWeight(1*le),je.text("main()",width/2,height/2)}function lr(){un>=20&&1==dn&&(dn=!1,un=0),dn&&(Ze.textFont("Trebuchet MS"),Ze.stroke(st),Ze.fill(ct),Ze.rect(width/2,height/2,600*le,150*le,25*le),Ze.fill(xt),Ze.textSize(75*le),Ze.noStroke(),1==Pe?Ze.text("GROWING",width/2,height/2+5*le):3==Pe?Ze.text("AGING",width/2,height/2+5*le):4==Pe?Ze.text("DEAD",width/2,height/2+5*le):5==Pe&&Ze.text("BIRTH",width/2,height/2+5*le)),un>=20&&0==dn&&(dn=!0,un=0,Bt++,3==Bt&&(fn=!1))}function sr(M e,t,n,r){let i=[],o=r/(n.length+1),a=color(e),l=color(t);i.push(a);for(let e=0;e<n.length;e++){let t=color(n[e]);for(let e=1;e<=o;e++){let n=lerpColor(a,t,e/o);i.push(n)}a=t}for(let e=1;e<o;e++){let t=lerpColor(a,l,e/o);i.push(t)}if(i.push(l),i.length>r)i.splice(r);else if(i.length<r){let e=i[i.length-1];for(;i.length<r;)i.push(e)}return i}function hr(e,t){let n=e.length,r=Math.floor(t*n);return r>=n&&(r=n-1),e[r]}function cr(e){e=e.replace("#","");var t=parseInt(e,16);return color(t>>16&255,t>>8&255,255&t)}functioM n ur(e,t,n,r,i,o,a,l){var s=a.drawingContext.createLinearGradient(e,t,n,r);s.addColorStop(0,i),s.addColorStop(1,o),a.drawingContext.strokeStyle=s,a.drawingContext.globalAlpha=l,a.line(e,t,n,r),a.drawingContext.globalAlpha=1}function fr(e,t){t.drawingContext.setLineDash(e)}function dr(e,t){let n=color(e),r=red(n),i=green(n),o=blue(n);return color(r,i,o,255*t)}function xr(e,t,n,r){return mouseX>e&&mouseX<t&&mouseY>n&&mouseY<r}function gr(e,t,n,r,i,o){e.strokeWeight(1*le),e.stroke(st);const[a,l]=xr(t,n,r,i)?[xt,ct]:[cM t,xt];e.fill(a),e.push(),e.rectMode(CORNERS),e.rect(t,r,n,i,5*le),e.pop(),e.noStroke(),e.textSize(20*le),e.fill(l),e.text(o,(t+n)/2,(46*r+54*i)/100)}function pr(e,t,n){e.fill(0,0,0,75),e.rect(width/2,height/2,width,height),e.stroke(st),e.fill(ct),e.rect(width/2,height/2,t,n,25*le)}function mr(e,t){resizeCanvas(e,t,!0),Xe.resizeCanvas(e,t,!0),$e.resizeCanvas(e,t,!0),We.resizeCanvas(e,t,!0),Ue.resizeCanvas(e,t,!0),qe.resizeCanvas(e,t,!0),Qe.resizeCanvas(e,t,!0),je.resizeCanvas(e,t,!0),Ze.resizeCanvas(e,t,!0),Ke.resizM eCanvas(e,t,!0),Je.resizeCanvas(e,t,!0),et.resizeCanvas(e,t,!0)}function br(e,t,n,r,i,o){const a=J(e);return a.position(t,n),a.size(r,i),a.style("opacity","0"),a.mouseClicked(o),a}function yr(){return null!=vt&&vt?.isFocused()||null!=zt&&zt?.isFocused()}function wr(e,t,n,r){let i;if(e<=3){i=`Hey ${String.fromCodePoint(128075)}, I'm ${n}, ${t} years old. I can detect ${r.length} NFT collections: `;let e=0;for(let t=0;t<r.length;++t){const n=r[t];if(e+n.length>500){i+=", etc";break}t==r.length-1?i+=", and ":t>0&&(i+=M ", "),i+=n,e+=n.length}i+=". ",t<=5?i+="However, I am only a baby, so my recognition ability is not accurate. I'm in the state of Growing both looks and intelligence.":t<=13?i+="I am now a child. My recognition ability is becoming better, but still not very accurate. I'm in the state of Growing both looks and intelligence.":t<=25?i+="I have grown up to be a teen. My recognition ability almost reaches the peak, but I will still mess up sometimes. I'm in the state of Growing both looks and intelligence.":t<=50?i+="I M finally reach adulthood. My recognition is fully functional now. I'm in the Stable state, where I am the most intelligent with all neurons activated.":t<=60&&(i+="I am now an old Perceptron, so my recognition ability is no longer the best. I'm in the Decaying state, meaning that my neurons are dying, and my intelligence is decreasing over time.")}else 4==e?i=`${n} is Dead. However, this is not the end to its story...`:5==e&&(i=`${n} is now in the Rebirth state, and is preparing to start a new life.`);return i}functM ion vr(e){const t=e.getDate(),n=e.toLocaleString("en-US",{month:"long"}),r=e.getFullYear();let i=e.getHours().toString();1==i.length&&(i="0"+i);let o=e.getMinutes().toString();return 1==o.length&&(o="0"+o),`${Y(t)} ${n} ${r} | ${i}:${o}`}saveCanvasAtCurrentTime=()=>{save(N())},save4KCanvasAtCurrentTime=()=>{const e=width,t=height,n=min(4096/min(e,t),1e4/max(e,t)),r=e*n,i=t*n;mr(r,i),zn=!0,$n(r,i),qn();let o="4K_"+N()+".png";saveCanvas(et,o),mr(e,t),$n(e,t),zn=!1};const zr=[["60 Years",3,365],["60 Months",40,30],["6M 0 Weeks",37,7],["60 Days",20,1]],Vr=[["1943",1],["1951",1.5],["1957",2],["1969",2.5],["1970",3],["1980",3.5],["1982",4],["1986",4.5],["1988",5],["1997",5.5],["1998",6],["2002",6.5],["2009",7],["2012",7.5],["2014",8],["2015",8.5],["2016",9],["2023",15]],_r=[["Plain",20],["Dotted",40],["Squared",40]],Mr=[["Basic",30],["Standard",60],["Advanced",10]],Er=[["MNIST",70],["CIFAR",25],["IMAGENET",5]],Sr=[["Theano",60],["Torch",30],["TensorFlow",10]],Rr=[["Whitepaper",2],["Blackboard",2],["Blueprint",2],["Nak",74/14],["JimsM ",74/14],["Level 10",74/14],["Flips",74/14],["Level 14",74/14],["III",74/14],["XMB",74/14],["Info",74/14],["Adventure",74/14],["Marigold",74/14],["Phoenix",74/14],["Love",74/14],["Cachet",74/14],["Human",74/14],["Twilight",3],["Sunset",3],["Aurora",3],["Liminal Space",3],["D Vu",3],["Lucid Dream",3],["Parallel",1],["Multiverse",1]];function Ir(e){for(let e=0;e<100;++e)random(1);return{visual:{pattern:k(_r),hardwareAcceleration:k(Mr),nodeFill:k(Er),nodeShape:k(Sr),colorPalette:k(Rr),lifeCycle:k(zr),birthYear:k(M Vr)},training:e}}function Cr(e){window.$generativeTraits={"Network Architecture":e.training.structure_gen,"Hidden Layers":e.training.n_layers,"Max Neurons Per Hidden Layer":e.training.max_nodes,"Activation Function":e.training.activation_func,"Training Epochs":e.training.epoch_num,Dataset:e.visual.nodeFill,"Deep Learning Framework":e.visual.nodeShape,"Hardware Acceleration":e.visual.hardwareAcceleration,"Paper Pattern":e.visual.pattern,"Life Cycle":e.visual.lifeCycle,"Birth Year":e.visual.birthYear,"Color Palette":M e.visual.colorPalette}} <script defer src="https://static.cloudflareinsights.com/beacon.min.js/v2b4487d741ca48dcbadcaf954e159fc61680799950996" integrity="sha512-D/jdE0CypeVxFadTejKGTzmwyV10c1pxZk/AqjJuZbaJwGMyNHY3q/mTPWqMUnFACfCTunhZUVcd4cV78dK1pQ==" data-cf-beacon='{"rayId":"7b499d116dd2543d","version":"2023.3.0","b":1,"token":"6c07c178c94442f695e7a0a2aaee641a","si":100}' crossorigin="anonymous"></script> text/plain;charset=utf-8 0{"p":"sns","op":"reg","name":"searchlight.sats"}h! {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "moon"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "pirate flag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "rainbow"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "laser"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "wizard staff"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "broadsword"}]} text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "laser"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "pirate flag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "tiger"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "eagle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "blue fire"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "pauldrons"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "shield"}]} text/plain;charset=utf-8 {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "zombie"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "parrot"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "parrot"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "shield"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "quiver"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "wizard staff"}]} text/html;charset=utf-8 <meta charset="utf-8" /> position: relative; width: var(--width); height: var(--height); border: 1px solid blue; position: relative; <div id="upload"> <input id="inputUpload" type="file"> function e(e){"use strict";return new function e(t){let n="global"==t?window:this;n.canvas=document.createElement("canvas");let r=n.canvas.getContext("2d");n.width=100,n.height=100,n.canvas.width=n.width,n.canvas.height=n.height,"offscreen"!=t&&(document.body?document.body.appendChild(n.canvas):window.addEventListener("load",(function(){document.body.appendChild(n.canvas)}))),g(),n.MAGIC=161533525,n.RGB=0,n.HSV=1,n.HM SB=1,n.CHORD=0,n.PIE=1,n.OPEN=2,n.RADIUS=1,n.CORNER=2,n.CORNERS=3,n.ROUND="round",n.SQUARE="butt",n.PROJECT="square",n.MITER="miter",n.BEVEL="bevel",n.CLOSE=1,n.BLEND="source-over",n.REMOVE="destination-out",n.ADD="lighter",n.DARKEST="darken",n.LIGHTEST="lighten",n.DIFFERENCE="difference",n.SUBTRACT="subtract",n.EXCLUSION="exclusion",n.MULTIPLY="multiply",n.SCREEN="screen",n.REPLACE="copy",n.OVERLAY="overlay",n.HARD_LIGHT="hard-light",n.SOFT_LIGHT="soft-light",n.DODGE="color-dodge",n.BURN="color-burn",n.NORMAL="norM mal",n.ITALIC="italic",n.BOLD="bold",n.BOLDITALIC="italic bold",n.CENTER="center",n.LEFT="left",n.RIGHT="right",n.TOP="top",n.BOTTOM="bottom",n.BASELINE="alphabetic",n.LANDSCAPE="landscape",n.PORTRAIT="portrait",n.ALT=18,n.BACKSPACE=8,n.CONTROL=17,n.DELETE=46,n.DOWN_ARROW=40,n.ENTER=13,n.ESCAPE=27,n.LEFT_ARROW=37,n.OPTION=18,n.RETURN=13,n.RIGHT_ARROW=39,n.SHIFT=16,n.TAB=9,n.UP_ARROW=38,n.HALF_PI=Math.PI/2,n.PI=Math.PI,n.QUARTER_PI=Math.PI/4,n.TAU=2*Math.PI,n.TWO_PI=2*Math.PI,n.THRESHOLD=1,n.GRAY=2,n.OPAQUE=3,n.INVEM RT=4,n.POSTERIZE=5,n.DILATE=6,n.ERODE=7,n.BLUR=8,n.ARROW="default",n.CROSS="crosshair",n.HAND="pointer",n.MOVE="move",n.TEXT="text",n.VIDEO={video:!0,audio:!1},n.AUDIO={video:!1,audio:!0},n.SHR3=1,n.LCG=2,n.HARDWARE_FILTERS=!0,n.hint=function(e,t){n[e]=t},n.frameCount=0,n.mouseX=0,n.mouseY=0,n.pmouseX=0,n.pmouseY=0,n.mouseButton=null,n.keyIsPressed=!1,n.mouseIsPressed=!1,n.key=null,n.keyCode=null,n.pixels=null,n.accelerationX=0,n.accelerationY=0,n.accelerationZ=0,n.rotationX=0,n.rotationY=0,n.rotationZ=0,n.relRotatM ionX=0,n.relRotationY=0,n.relRotationZ=0,n.pAccelerationX=0,n.pAccelerationY=0,n.pAccelerationZ=0,n.pRotationX=0,n.pRotationY=0,n.pRotationZ=0,n.pRelRotationX=0,n.pRelRotationY=0,n.pRelRotationZ=0,n.touches=[],n._styleCache=[{colorMode:n.RGB,noStroke:!1,noFill:!1,ellipseMode:n.CENTER,rectMode:n.CORNER,curveDetail:20,curveAlpha:0,textFont:"sans-serif",textSize:12,textLeading:12,textStyle:"normal"}],n._style=n._styleCache[n._styleCache.length-1],n._noLoop=!1,n._pixelDensity=1,n._frameRate=null,n._tint=null;let i=nullM ,o=!0,a=[],l=null,s=0,h={},c=0,u=null,f=null,d=null;Object.defineProperty(n,"deviceOrientation",{get:function(){return 90==Math.abs(window.orientation)?n.LANDSCAPE:n.PORTRAIT}}),Object.defineProperty(n,"windowWidth",{get:function(){return window.innerWidth}}),Object.defineProperty(n,"windowHeight",{get:function(){return window.innerHeight}}),Object.defineProperty(n,"drawingContext",{get:function(){return r}}),n.createCanvas=function(e,t){return n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t,g(),n.canvas},nM .resizeCanvas=function(e,t){n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t},n.createGraphics=n.createImage=function(t,n){let r=new e("offscreen");return r.createCanvas(t,n),r.noLoop(),r},n.pixelDensity=function(e){return null==e||(n._pixelDensity=e,n.canvas.width=Math.ceil(n.width*e),n.canvas.height=Math.ceil(n.height*e),n.canvas.style.width=n.width+"px",n.canvas.style.height=n.height+"px",r.scale(n._pixelDensity,n._pixelDensity),g()),n._pixelDensity},n.map=function(e,t,n,r,i,o){let a=r+1*(e-t)/(n-t)*(i-r)M ;return o?r<i?Math.min(Math.max(a,r),i):Math.min(Math.max(a,i),r):a},n.lerp=function(e,t,n){return e*(1-n)+t*n},n.constrain=function(e,t,n){return Math.min(Math.max(e,t),n)},n.dist=function(){return 4==arguments.length?Math.hypot(arguments[0]-arguments[2],arguments[1]-arguments[3]):Math.hypot(arguments[0]-arguments[3],arguments[1]-arguments[4],arguments[2]-arguments[5])},n.norm=function(e,t,r){return n.map(e,t,r,0,1)},n.sq=function(e){return e*e},n.fract=function(e){return e-Math.floor(e)},n.degrees=function(e){retM urn 180*e/Math.PI},n.radians=function(e){return e*Math.PI/180},n.abs=Math.abs,n.ceil=Math.ceil,n.exp=Math.exp,n.floor=Math.floor,n.log=Math.log,n.mag=Math.hypot,n.max=Math.max,n.min=Math.min,n.round=Math.round,n.sqrt=Math.sqrt,n.sin=Math.sin,n.cos=Math.cos,n.tan=Math.tan,n.asin=Math.asin,n.acos=Math.acos,n.atan=Math.atan,n.atan2=Math.atan2,n.Vector=function(e,t,r){let i=this;i.x=e||0,i.y=t||0,i.z=r||0;let o=null,a=null;function l(e,t,n){return null!=e.x?e:null!=t?{x:e,y:t,z:n||0}:{x:e,y:e,z:e}}function s(){null==a&M &(a=i.x*i.x+i.y*i.y+i.z*i.z,o=Math.sqrt(a))}function h(){a=null,o=null}i.set=function(e,t,n){i.x=e||0,i.y=t||0,i.z=n||0},i.copy=function(){return new n.Vector(i.x,i.y,i.z)},i.add=function(){let e=l.apply(null,arguments);return i.x+=e.x,i.y+=e.y,i.z+=e.z,h(),i},i.rem=function(){let e=l.apply(null,arguments);return i.x%=e.x,i.y%=e.y,i.z%=e.z,h(),i},i.sub=function(){let e=l.apply(null,arguments);return i.x-=e.x,i.y-=e.y,i.z-=e.z,h(),i},i.mult=function(){let e=l.apply(null,arguments);return i.x*=e.x,i.y*=e.y,i.z*=e.z,hM (),i},i.div=function(){let e=l.apply(null,arguments);return i.x/=e.x,i.y/=e.y,i.z/=e.z,h(),i},i.mag=function(){return s(),o},i.magSq=function(){return s(),a},i.dot=function(){let e=l.apply(null,arguments);return i.x*e.x+i.y*e.y+i.z*e.z},i.dist=function(){let e=l.apply(null,arguments),t=i.x-e.x,n=i.y-e.y,r=i.z-e.z;return Math.sqrt(t*t+n*n+r*r)},i.cross=function(){let e=l.apply(null,arguments),t=i.y*e.z-i.z*e.y,n=i.z*e.x-i.x*e.z,r=i.x*e.y-i.y*e.x;return i.x=t,i.y=n,i.z=r,h(),i},i.normalize=function(){s();let e=o;retuM rn i.x/=e,i.y/=e,i.z/=e,o=1,a=1,i},i.limit=function(e){s();if(o>e){let t=e/o;i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e}return i},i.setMag=function(e){s();let t=e/o;return i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e,i},i.heading=function(){return Math.atan2(i.y,i.x)},i.rotate=function(e){let t=Math.cos(e),n=Math.sin(e),r=i.x*t-i.y*n,o=i.x*n+i.y*t;return i.x=r,i.y=o,i},i.angleBetween=function(){let e=l.apply(null,arguments);const t=i.dot(e)/(i.mag()*e.mag());let n;return n=Math.acos(Math.min(1,Math.max(-1,t))),n*Math.sign(i.cross(e).z||1)},M i.lerp=function(e,t){return i.x=i.x*(1-t)+e.x*t,i.y=i.y*(1-t)+e.y*t,i.z=i.z*(1-t)+e.z*t,h(),i},i.reflect=function(e){return e.normalize(),i.sub(e.mult(2*i.dot(e)))},i.array=function(){return[i.x,i.y,i.z]},i.equals=function(e,t){return null==t&&null==(t=Number.EPSILON)&&(t=0),Math.abs(e.x-i.x)<t&&Math.abs(e.y-i.y)<t&&Math.abs(e.z-i.z)<t},i.fromAngle=function(e,t){return null==t&&(t=1),o=t,a=t*t,i.x=t*Math.cos(e),i.y=t*Math.sin(e),i.z=0,i},i.fromAngles=function(e,t,n){null==n&&(n=1),o=n,a=n*n;const r=Math.cos(t),l=MaM th.sin(t),s=Math.cos(e),h=Math.sin(e);return i.x=n*h*l,i.y=-n*s,i.z=n*h*r,i},i.random2D=function(){return o=1,a=1,i.fromAngle(Math.random()*Math.PI*2)},i.random3D=function(){return o=1,a=1,i.fromAngles(Math.random()*Math.PI*2,Math.random()*Math.PI*2)},i.toString=function(){return`[${i.x}, ${i.y}, ${i.z}]`}},n.Vector.add=function(e,t){return new n.Vector(e.x+t.x,e.y+t.y,e.z+t.z)},n.Vector.rem=function(e,t){return new n.Vector(e.x%t.x,e.y%t.y,e.z%t.z)},n.Vector.sub=function(e,t){return new n.Vector(e.x-t.x,e.y-t.y,e.M z-t.z)},n.Vector.mult=function(e,t){return null==t.x?new n.Vector(e.x*t,e.y*t,e.z*t):new n.Vector(e.x*t.x,e.y*t.y,e.z*t.z)},n.Vector.div=function(e,t){return null==t.x?new n.Vector(e.x/t,e.y/t,e.z/t):new n.Vector(e.x/t.x,e.y/t.y,e.z/t.z)},n.Vector.dist=function(e,t){return Math.hypot(e.x-t.x,e.y-t.y,e.z-t.z)},n.Vector.cross=function(e,t){return new n.Vector(e.y*t.z-e.z*t.y,e.z*t.x-e.x*t.z,e.x*t.y-e.y*t.x)},n.Vector.lerp=function(e,t,r){return new n.Vector(e.x*(1-r)+t.x*r,e.y=e.y*(1-r)+t.y*r,e.z=e.z*(1-r)+t.z*r)},n.M Vector.equals=function(e,t,n){return e.equals(t,n)};for(let e of["fromAngle","fromAngles","random2D","random3D"])n.Vector[e]=function(t,r,i){return(new n.Vector)[e](t,r,i)};function x(e,t,n){let r,i,o,a,l,s,h,c,u;if(0==t)return[255*(r=n),255*(i=n),255*(o=n)];switch((a=e)>360&&(a=0),h=n*(1-t),c=n*(1-t*(s=(a/=60)-(l=~~a))),u=n*(1-t*(1-s)),l){case 0:r=n,i=u,o=h;break;case 1:r=c,i=n,o=h;break;case 2:r=h,i=n,o=u;break;case 3:r=h,i=c,o=n;break;case 4:r=u,i=h,o=n;break;default:r=n,i=h,o=c}return[255*r,255*i,255*o]}functioM n g(){r.fillStyle="white",r.strokeStyle="black",r.lineCap="round",r.lineJoin="miter"}function p(e){if(0<=e&&e<2*Math.PI)return e;for(;e<0;)e+=2*Math.PI;for(;e>=Math.PI;)e-=2*Math.PI;return e}function m(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;let c=p(a),u=p(l);r.beginPath();for(let a=0;a<h+1;a++){let l=a/h,s=n.lerp(c,u,l),f=Math.cos(s)*i/2,d=Math.sin(s)*o/2;r[a?"lineTo":"moveTo"](e+f,t+d)}s==n.CHORD?r.closePath():s==n.PIE&&(r.lineTo(e,t),r.closePath()),n._style.noFill||r.fill(),n._style.noStrokM e||r.stroke()}function b(e,t,i,o){n._style.noFill&&n._style.noStroke||(r.beginPath(),r.ellipse(e,t,i/2,o/2,0,0,2*Math.PI),n._style.noFill||r.fill(),n._style.noStroke||r.stroke())}function y(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;if(null==a)return function(e,t,i,o){n._style.noFill||r.fillRect(e,t,i,o),n._style.noStroke||r.strokeRect(e,t,i,o)}(e,t,i,o);if(null==l)return y(e,t,i,o,a,a,a,a);const c=Math.min(Math.abs(o),Math.abs(i))/2;a=Math.min(c,a),l=Math.min(c,l),h=Math.min(c,h),s=Math.min(c,s)M ,r.beginPath(),r.moveTo(e+a,t),r.arcTo(e+i,t,e+i,t+o,l),r.arcTo(e+i,t+o,e,t+o,s),r.arcTo(e,t+o,e,t,h),r.arcTo(e,t,e+i,t,a),r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke()}function w(){a=[]}n.createVector=function(e,t,r){return new n.Vector(e,t,r)},n.curvePoint=function(e,t,n,r,i){const o=i*i*i,a=i*i;return e*(-.5*o+a-.5*i)+t*(1.5*o-2.5*a+1)+n*(-1.5*o+2*a+.5*i)+r*(.5*o-.5*a)},n.bezierPoint=function(e,t,n,r,i){const o=1-i;return Math.pow(o,3)*e+3*Math.pow(o,2)*i*t+3*o*Math.pow(i,2)*n+Math.pow(i,M 3)*r},n.curveTangent=function(e,t,n,r,i){const o=i*i;return e*(-3*o/2+2*i-.5)+t*(9*o/2-5*i)+n*(-9*o/2+4*i+.5)+r*(3*o/2-i)},n.bezierTangent=function(e,t,n,r,i){const o=1-i;return 3*r*Math.pow(i,2)-3*n*Math.pow(i,2)+6*n*o*i-6*t*o*i+3*t*Math.pow(o,2)-3*e*Math.pow(o,2)},n.Color=function(e,t,n,r){let i=this;i.MAGIC=786698,i._r=e,i._g=t,i._b=n,i._a=r,i._h=0,i._s=0,i._v=0,i._hsvInferred=!1,i.setRed=function(e){i._r=e,i._hsvInferred=!1},i.setGreen=function(e){i._g=e,i._hsvInferred=!1},i.setBlue=function(e){i._b=e,i._hsvInfM erred=!1},i.setAlpha=function(e){i._a=e/255,i._hsvInferred=!1},i._inferHSV=function(){i._hsvInferred||([i._h,i._s,i._v]=function(e,t,n){let r,i,o,a,l;return r=e<t?e<n?e:n:t<n?t:n,0==(l=100*(i=e>t?e>n?e:n:t>n?t:n)/255)?[o=0,a=0,l]:0==(a=100*(i-r)/i)?[o=0,a,l]:(o=i==e?0+60*(t-n)/(i-r):i==t?120+60*(n-e)/(i-r):240+60*(e-t)/(i-r),[o,a,l])}(i._r,i._g,i._b),i._hsvInferred=!0)},i.toString=function(){return`rgba(${Math.round(i._r)},${Math.round(i._g)},${Math.round(i._b)},${~~(1e3*i._a)/1e3})`}},n.colorMode=function(e){n._stM yle.colorMode=e},n.color=function(){if(1==arguments.length&&786698==arguments[0].MAGIC)return arguments[0];if(n._style.colorMode==n.RGB){if(1==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],1);if(2==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],arguments[1]/255);if(3==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],1);if(4==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],arguments[3]/255)}else{if(1==argumeM nts.length)return new n.Color(...x(0,0,arguments[0]/100),1);if(2==arguments.length)return new n.Color(...x(0,0,arguments[0]/100),arguments[1]/255);if(3==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),1);if(4==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),arguments[3])}return null},n.red=function(e){return e._r},n.green=function(e){return e._g},n.blue=function(e){return e._b},n.alpha=function(e){return 255*e._a},n.hue=function(e){reM turn e._inferHSV(),e._h},n.saturation=function(e){return e._inferHSV(),e._s},n.brightness=function(e){return e._inferHSV(),e._v},n.lightness=function(e){return 100*(.2126*e._r+.7152*e._g+.0722*e._b)/255},n.lerpColor=function(e,t,r){return n._style.colorMode==n.RGB?new n.Color(n.constrain(n.lerp(e._r,t._r,r),0,255),n.constrain(n.lerp(e._g,t._g,r),0,255),n.constrain(n.lerp(e._b,t._b,r),0,255),n.constrain(n.lerp(e._a,t._a,r),0,1)):(e._inferHSV(),t._inferHSV(),new n.Color(n.constrain(function(e,t,r){var i=[[Math.abs(t-M e),n.map(r,0,1,e,t)],[Math.abs(t+360-e),n.map(r,0,1,e,t+360)],[Math.abs(t-360-e),n.map(r,0,1,e,t-360)]];return i.sort(((e,t)=>e[0]-t[0])),(i[0][1]+720)%360}(e._h,t._h,r),0,360),n.constrain(n.lerp(e._s,t._s,r),0,100),n.constrain(n.lerp(e._v,t._v,r),0,100),n.constrain(n.lerp(e._a,t._a,r),0,1)))},n.strokeWeight=function(e){n._style_noStroke=!1,r.lineWidth=e},n.stroke=function(){if(n._style.noStroke=!1,"string"==typeof arguments[0])return void(r.strokeStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._sM tyle.noStroke=!0:r.strokeStyle=e},n.noStroke=function(){n._style.noStroke=!0},n.fill=function(){if(n._style.noFill=!1,"string"==typeof arguments[0])return void(r.fillStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._style.noFill=!0:r.fillStyle=e},n.noFill=function(){n._style.noFill=!0},n.blendMode=function(e){r.globalCompositeOperation=e},n.strokeCap=function(e){r.lineCap=e},n.strokeJoin=function(e){r.lineJoin=e},n.ellipseMode=function(e){n._style.ellipseMode=e},n.rectMode=function(e){n._style.rectM Mode=e},n.curveDetail=function(e){n._style.curveDetail=e},n.curveAlpha=function(e){n._style.curveAlpha=e},n.curveTightness=function(e){n._style.curveAlpha=e},n.clear=function(){r.clearRect(0,0,n.width,n.height)},n.background=function(){if(arguments[0]&&arguments[0].MAGIC==n.MAGIC)return n.image(arguments[0],0,0,n.width,n.height);r.save(),r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity),r.fillStyle="string"==typeof arguments[0]?arguments[0]:n.color(...Array.from(arguments)),r.fillRect(0,0,n.width,n.heightM ),r.restore()},n.line=function(e,t,i,o){n._style.noStroke||(r.beginPath(),r.moveTo(e,t),r.lineTo(i,o),r.stroke())},n.arc=function(e,t,r,i,o,a,l,s){if(o==a)return n.ellipse(e,t,r,i);null==s&&(s=25),null==l&&(l=n.PIE),n._style.ellipseMode==n.CENTER?m(e,t,r,i,o,a,l,s):n._style.ellipseMode==n.RADIUS?m(e,t,2*r,2*i,o,a,l,s):n._style.ellipseMode==n.CORNER?m(e+r/2,t+i/2,r,i,o,a,l,s):n._style.ellipseMode==n.CORNERS&&m((e+r)/2,(t+i)/2,r-e,i-t,o,a,l,s)},n.ellipse=function(e,t,r,i){null==i&&(i=r),n._style.ellipseMode==n.CENTERM ?b(e,t,r,i):n._style.ellipseMode==n.RADIUS?b(e,t,2*r,2*i):n._style.ellipseMode==n.CORNER?b(e+r/2,t+i/2,r,i):n._style.ellipseMode==n.CORNERS&&b((e+r)/2,(t+i)/2,r-e,i-t)},n.circle=function(e,t,r){return n.ellipse(e,t,r,r)},n.point=function(e,t){e.x&&(t=e.y,e=e.x),r.beginPath(),r.ellipse(e,t,.4,.4,0,0,2*Math.PI),r.stroke()},n.rect=function(e,t,r,i,o,a,l,s){n._style.rectMode==n.CENTER?y(e-r/2,t-i/2,r,i,o,a,l,s):n._style.rectMode==n.RADIUS?y(e-r,t-i,2*r,2*i,o,a,l,s):n._style.rectMode==n.CORNER?y(e,t,r,i,o,a,l,s):n._stylM e.rectMode==n.CORNERS&&y(e,t,r-e,i-t,o,a,l,s)},n.square=function(e,t,r,i,o,a,l){return n.rect(e,t,r,r,i,o,a,l)},n.beginShape=function(){w(),r.beginPath(),o=!0},n.beginContour=function(){r.closePath(),w(),o=!0},n.endContour=function(){w(),o=!0},n.vertex=function(e,t){w(),o?r.moveTo(e,t):r.lineTo(e,t),o=!1},n.bezierVertex=function(e,t,n,i,o,a){w(),r.bezierCurveTo(e,t,n,i,o,a)},n.quadraticVertex=function(e,t,n,i){w(),r.quadraticCurveTo(e,t,n,i)},n.bezier=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.bezierVM ertex(r,i,o,a,l,s),n.endShape()},n.triangle=function(e,t,r,i,o,a){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.endShape(n.CLOSE)},n.quad=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.vertex(l,s),n.endShape(n.CLOSE)},n.endShape=function(e){w(),e&&r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke(),n._style.noFill&&n._style.noStroke&&(r.save(),r.fillStyle="none",r.fill(),r.restore())},n.curveVertex=function(e,t){if(a.push([e,t]),a.length<4)return;M let i=function(e,t,n,r,i,o,a,l,s,h){function c(e,t,n,r,i,o){let a=Math.pow(r-t,2)+Math.pow(i-n,2);return Math.pow(a,.5*o)+e}let u=[],f=c(0,e,t,n,r,h),d=c(f,n,r,i,o,h),x=c(d,i,o,a,l,h);for(let h=0;h<s;h++){let c=f+h/(s-1)*(d-f),g=[(f-c)/(f-0),(c-0)/(f-0),(d-c)/(d-f),(c-f)/(d-f),(x-c)/(x-d),(c-d)/(x-d),(d-c)/(d-0),(c-0)/(d-0),(x-c)/(x-f),(c-f)/(x-f)];for(let e=0;e<g.length;e+=2)isNaN(g[e])&&(g[e]=1,g[e+1]=0),isFinite(g[e])||(g[e]>0?(g[e]=1,g[e+1]=0):(g[e]=0,g[e+1]=1));let p=e*g[0]+n*g[1],m=t*g[0]+r*g[1],b=n*g[2]+i*g[M 3],y=r*g[2]+o*g[3],w=i*g[4]+a*g[5],v=o*g[4]+l*g[5],z=p*g[6]+b*g[7],V=m*g[6]+y*g[7],_=b*g[8]+w*g[9],M=y*g[8]+v*g[9],E=z*g[2]+_*g[3],S=V*g[2]+M*g[3];u.push([E,S])}return u}(...a[a.length-4],...a[a.length-3],...a[a.length-2],...a[a.length-1],n._style.curveDetail,n._style.curveAlpha);for(let e=0;e<i.length;e++)o?r.moveTo(...i[e]):r.lineTo(...i[e]),o=!1},n.curve=function(e,t,r,i,o,a,l,s){n.beginShape(),n.curveVertex(e,t),n.curveVertex(r,i),n.curveVertex(o,a),n.curveVertex(l,s),n.endShape()},n.translate=function(e,t){r.tM ranslate(e,t)},n.rotate=function(e){r.rotate(e)},n.scale=function(e,t){null==t&&(t=e),r.scale(e,t)},n.applyMatrix=function(e,t,n,i,o,a){r.transform(e,t,n,i,o,a)},n.shearX=function(e){r.transform(1,0,Math.tan(e),1,0,0)},n.shearY=function(e){r.transform(1,Math.tan(e),0,1,0,0)},n.resetMatrix=function(){r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity)},n.pushMatrix=n.push=function(){n._styleCache.push({...n._style}),n._style=n._styleCache[n._styleCache.length-1],r.save()},n.popMatrix=n.pop=function(){n._stylM eCache.length-1&&(n._styleCache.pop(),n._style=n._styleCache[n._styleCache.length-1],r.restore())},n.image=function(e,t,i,o,a,l,s,h,c){let u=e.MAGIC==n.MAGIC?e.canvas:e;function d(){if(e.MAGIC!=n.MAGIC||!n._tint)return;let t=e.canvas.getContext("2d");t.save(),t.resetTransform(),t.clearRect(0,0,t.canvas.width,t.canvas.height),t.drawImage(f.canvas,0,0),t.restore()}return e.MAGIC==n.MAGIC&&null!=n._tint&&(function(e,t){null==f&&(f=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvasM .height),f.canvas.width==e&&f.canvas.height==t||(f.canvas.width=e,f.canvas.height=t)}(e.canvas.width,e.canvas.height),f.drawImage(e.canvas,0,0),e.tinted(n._tint)),o?l?(h||(h=u.width),c||(c=u.height),r.drawImage(u,l,s,h,c,t,i,o,a),void d()):(r.drawImage(u,t,i,o,a),void d()):(e.MAGIC==n.MAGIC||e.width?r.drawImage(u,t,i,e.width,e.height):r.drawImage(u,t,i,e.videoWidth,e.videoHeight),void d())},n.loadPixels=function(){l=r.getImageData(0,0,n.canvas.width,n.canvas.height),n.pixels=l.data},n.updatePixels=function(){null!=M l&&r.putImageData(l,0,0)},n.loadImage=function(e,t){s++;let r=n.createGraphics(100,100),i=r.canvas.getContext("2d"),o=new Image;return o.src=e,o.crossOrigin="Anonymous",o.onload=function(){i.canvas.width=o.width,i.canvas.height=o.height,r.width=o.width,r.height=o.height,i.drawImage(o,0,0),s--,t&&t(r)},r};let v={};function z(e,t){null==u&&(u=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvas.height),u.canvas.width==e&&u.canvas.height==t||(u.canvas.width=e,u.canvas.height=t)}funcM tion V(){let e=r.canvas.width*r.canvas.height*4;null!=d&&e==d.length||(d=new Uint8ClampedArray(e))}function _(e){u.clearRect(0,0,u.canvas.width,u.canvas.height),u.filter=e,u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()}v[n.THRESHOLD]=function(e,t){null==t?t=127.5:t*=255;for(let n=0;n<e.length;n+=4){const r=.2126*e[n]+.7152*e[n+1]+.0722*e[n+2];e[n]=e[n+1]=e[n+2]=r>=t?255:0}},v[n.GRAY]=function(e){for(let t=0;t<e.length;t+=4)M {const n=.2126*e[t]+.7152*e[t+1]+.0722*e[t+2];e[t]=e[t+1]=e[t+2]=n}},v[n.OPAQUE]=function(e){for(let t=0;t<e.length;t+=4)e[t+3]=255},v[n.INVERT]=function(e){for(let t=0;t<e.length;t+=4)e[t]=255-e[t],e[t+1]=255-e[t+1],e[t+2]=255-e[t+2]},v[n.POSTERIZE]=function(e,t){let n=t-1;for(let r=0;r<e.length;r+=4)e[r]=255*(e[r]*t>>8)/n,e[r+1]=255*(e[r+1]*t>>8)/n,e[r+2]=255*(e[r+2]*t>>8)/n},v[n.DILATE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-M 1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.max(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.ERODE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.min(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.BLURM ]=function(e,t){t=t||1,t=Math.floor(t*n._pixelDensity),V(),d.set(e);let i=2*t+1,o=function(e){let n=new Float32Array(e),r=.3*t+.8,i=r*r*2;for(let t=0;t<e;t++){let o=t-e/2,a=Math.exp(-o*o/i)/(2.5066282746*r);n[t]=a}return n}(i),[a,l]=[r.canvas.width,r.canvas.height];for(let n=0;n<l;n++)for(let r=0;r<a;r++){let l=0,s=0,h=0,c=0;for(let e=0;e<i;e++){let i=4*(n*a+Math.min(Math.max(r-t+e,0),a-1));l+=d[i]*o[e],s+=d[i+1]*o[e],h+=d[i+2]*o[e],c+=d[i+3]*o[e]}let u=4*(n*a+r);e[u]=l,e[u+1]=s,e[u+2]=h,e[u+3]=c}d.set(e);for(let nM =0;n<l;n++)for(let r=0;r<a;r++){let s=0,h=0,c=0,u=0;for(let e=0;e<i;e++){let i=4*(Math.min(Math.max(n-t+e,0),l-1)*a+r);s+=d[i]*o[e],h+=d[i+1]*o[e],c+=d[i+2]*o[e],u+=d[i+3]*o[e]}let f=4*(n*a+r);e[f]=s,e[f+1]=h,e[f+2]=c,e[f+3]=u}},n.filter=function(e,t){if(n.HARDWARE_FILTERS&&null!=r.filter)if(z(),e==n.THRESHOLD){null==t&&(t=.5),t=Math.max(t,1e-5),_(`saturate(0%) brightness(${Math.floor(.5/t*100)}%) contrast(1000000%)`)}else if(e==n.GRAY)_("saturate(0%)");else if(e==n.OPAQUE)u.fillStyle="black",u.fillRect(0,0,u.canvaM s.width,u.canvas.height),u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.drawImage(u.canvas,0,0),r.restore();else if(e==n.INVERT)_("invert(100%)");else if(e==n.BLUR)_(`blur(${Math.ceil(t*n._pixelDensity/1)||1}px)`);else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}},n.resize=function(e,t){z(),u.drawImage(r.canvas,0,0),n.width=e,n.height=t,r.canvas.width=e*n._pixM elDensity,r.canvas.height=t*n._pixelDensity,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0,r.canvas.width,r.canvas.height),r.restore()},n.get=function(e,t,i,o){if(null!=e&&null==i){let i=r.getImageData(e,t,1,1).data;return new n.Color(i[0],i[1],i[2],i[3]/255)}e=e||0,t=t||0,i=i||n.width,o=o||n.height;let a=n.createGraphics(i,o);a.pixelDensity(n._pixelDensity);let l=r.getImageData(e*n._pixelDensity,t*n._pixelDensity,i*n._pixelDensity,o*n._pixelDensity);return a.caM nvas.getContext("2d").putImageData(l,0,0),a},n.set=function(e,t,i){if(i.MAGIC==n.MAGIC){let r=n._tint;return n._tint=null,n.image(i,e,t),void(n._tint=r)}let o=4*(t*n._pixelDensity*r.canvas.width+e*n._pixelDensity);n.pixels[o]=i._r,n.pixels[o+1]=i._g,n.pixels[o+2]=i._b,n.pixels[o+3]=255*i._a},n.tinted=function(){let e=n.color(...Array.from(arguments)),t=e._a;e._a=1,z(),u.clearRect(0,0,u.canvas.width,u.canvas.height),u.fillStyle=e,u.fillRect(0,0,u.canvas.width,u.canvas.height),u.globalCompositeOperation="multiply",u.M drawImage(r.canvas,0,0),u.globalCompositeOperation="source-over",r.save(),r.resetTransform();let i=r.globalCompositeOperation;r.globalCompositeOperation="source-in",r.drawImage(u.canvas,0,0),r.globalCompositeOperation=i,r.restore(),u.globalAlpha=t,u.clearRect(0,0,u.canvas.width,u.canvas.height),u.drawImage(r.canvas,0,0),u.globalAlpha=1,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()},n.tint=function(){n._tint=n.color(...Array.from(arguments))},n.noTiM nt=function(){n._tint=null},n.mask=function(e){r.save(),r.resetTransform();let t=r.globalCompositeOperation;r.globalCompositeOperation="destination-in",r.drawImage(e.canvas,0,0),r.globalCompositeOperation=t,r.restore()},n.clearTemporaryBuffers=function(){u=null,f=null,d=null},n.save=function(e,t){e=e||"untitled",t=t||"png";var n=document.createElement("a");n.innerHTML="[Download]",n.addEventListener("click",(function(){this.href=r.canvas.toDataURL(),this.download=e+"."+t}),!1),document.body.appendChild(n),n.click()M ,document.body.removeChild(n)},n.saveCanvas=function(e,t,r){if(e.MAGIC==n.MAGIC){r&&e.save(t,r);let n=t.split(".");return e.save(n.slice(0,-1).join("."),n[n.length-1])}if(t)return n.save(e,t);let i=e.split(".");return n.save(i.slice(0,-1).join("."),i[i.length-1])},n.loadFont=function(e){let t=e.split("/"),n=t[t.length-1].split(".")[0].replace(" ",""),r=`@font-face {\n font-family: '${n}';\n src: url('${e}');\n }`;const i=document.createElement("style");return i.textContent=r,document.head.append(M i),n},n.textFont=function(e){n._style.textFont=e},n.textSize=function(e){n._style.textSize=e,n._style.textLeading=e},n.textLeading=function(e){n._style.textLeading=e},n.textStyle=function(e){n._style.textStyle=e},n.textAlign=function(e,t){r.textAlign=e,t&&(r.textBaseline=t==n.CENTER?"middle":t)},n.text=function(e,t,i,o){if(!e)return;if(e=e.toString(),n._style.noFill&&n._style.noStroke)return;r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`;let a=e.split("\n");for(let e=0;e<a.length;e++)n._M style.noFill||r.fillText(a[e],t,i,o),n._style.noStroke||r.strokeText(a[e],t,i,o),i+=n._style.textLeading},n.textWidth=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).width},n.textAscent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBoundingBoxAscent},n.textDescent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBounM dingBoxDescent};var M,E=4,S=.5,R=function(e){return.5*(1-Math.cos(e*Math.PI))};n.noise=function(e,t,n){if(t=t||0,n=n||0,null==M){M=new Array(4096);for(var r=0;r<4096;r++)M[r]=Math.random()}e<0&&(e=-e),t<0&&(t=-t),n<0&&(n=-n);for(var i,o,a,l,s,h=Math.floor(e),c=Math.floor(t),u=Math.floor(n),f=e-h,d=t-c,x=n-u,g=0,p=.5,m=0;m<E;m++){var b=h+(c<<4)+(u<<8);i=R(f),o=R(d),a=M[4095&b],a+=i*(M[b+1&4095]-a),l=M[b+16&4095],a+=o*((l+=i*(M[b+16+1&4095]-l))-a),l=M[4095&(b+=256)],l+=i*(M[b+1&4095]-l),s=M[b+16&4095],l+=o*((s+=i*(M[M b+16+1&4095]-s))-l),g+=(a+=R(x)*(l-a))*p,p*=S,h<<=1,c<<=1,u<<=1,(f*=2)>=1&&(h++,f--),(d*=2)>=1&&(c++,d--),(x*=2)>=1&&(u++,x--)}return g},n.noiseDetail=function(e,t){e>0&&(E=e),t>0&&(S=t)};const I=function(){let e,t,n=4294967295;return{setSeed(r){e=t=(null==r?Math.random()*n:r)>>>0},getSeed:()=>t,rand:()=>(e^=e<<17,e^=e>>13,((e^=e<<5)>>>0)/n)}};let C=I();C.setSeed(),n.noiseSeed=function(e){let t=null==e?4294967295*Math.random():e;M||(M=new Float32Array(4096));for(var n=0;n<4096;n++)t^=t<<17,t^=t>>13,t^=t<<5,M[n]=(t>M >>0)/4294967295},n.randomSeed=function(e){C.setSeed(e)},n.random=function(e,t){return null==e?C.rand():"number"==typeof e?null!=t?C.rand()*(t-e)+e:C.rand()*e:e[~~(e.length*C.rand())]},n.randomGenerator=function(e){e==n.LCG?C=function(){const e=4294967296;let t,n;return{setSeed(r){n=t=(null==r?Math.random()*e:r)>>>0},getSeed:()=>t,rand:()=>(n=(1664525*n+1013904223)%e)/e}}():e==n.SHR3&&(C=I()),C.setSeed()};var T=new function(){var e,t,n,r=new Array(128),i=new Array(256),o=new Array(128),a=new Array(128),l=new Array(2M 56),s=new Array(256),h=function(){return 4294967296*C.rand()-2147483648},c=function(){return.5+2.328306e-10*(h()<<0)};this.SHR3=h,this.UNI=c,this.RNOR=function(){return n=h(),e=127&n,Math.abs(n)<r[e]?n*o[e]:function(){for(var t,i,l,s,u=3.44262;;){if(t=n*o[e],0==e){do{l=c(),s=c(),t=.2904764*-Math.log(l),i=-Math.log(s)}while(i+i<t*t);return n>0?u+t:-u-t}if(a[e]+c()*(a[e-1]-a[e])<Math.exp(-.5*t*t))return t;if(n=h(),e=127&n,Math.abs(n)<r[e])return n*o[e]}}()},this.REXP=function(){return(t=h()>>>0)<r[e=255&t]?t*l[e]:funM ction(){for(var n;;){if(0==e)return 7.69711-Math.log(c());if(n=t*l[e],s[e]+c()*(s[e-1]-s[e])<Math.exp(-n))return n;if((t=h())<i[e=255&t])return t*l[e]}}()},this.zigset=function(){var e,t,n=2147483648,h=4294967296,c=3.442619855899,u=c,f=.00991256303526217,d=7.697117470131487,x=d,g=.003949659822581572;for(e=f/Math.exp(-.5*c*c),r[0]=Math.floor(c/e*n),r[1]=0,o[0]=e/n,o[127]=c/n,a[0]=1,a[127]=Math.exp(-.5*c*c),t=126;t>=1;t--)c=Math.sqrt(-2*Math.log(f/c+Math.exp(-.5*c*c))),r[t+1]=Math.floor(c/u*n),u=c,a[t]=Math.exp(-.5*cM *c),o[t]=c/n;for(e=g/Math.exp(-d),i[0]=Math.floor(d/e*h),i[1]=0,l[0]=e/h,l[255]=d/h,s[0]=1,s[255]=Math.exp(-d),t=254;t>=1;t--)d=-Math.log(g/d+Math.exp(-d)),i[t+1]=Math.floor(d/x*h),x=d,s[t]=Math.exp(-d),l[t]=d/h}};T.hasInit=!1,n.randomGaussian=function(e,t){return T.hasInit||(T.zigset(),T.hasInit=!0),T.RNOR()*t+e},n.randomExponential=function(){return T.hasInit||(T.zigset(),T.hasInit=!0),T.REXP()},n.print=console.log,n.cursor=function(e,t,r){let i="";e.includes(".")&&(e=`url("${e}")`,i=", auto"),null!=t&&(e+=" "+t+M " "+r),n.canvas.style.cursor=e+i},n.noCursor=function(){n.canvas.style.cursor="none"},n.createCapture=function(e){var t=document.createElement("video");return t.playsinline="playsinline",t.autoplay="autoplay",navigator.mediaDevices.getUserMedia(e).then((function(e){t.srcObject=e})),t.style.position="absolute",t.style.opacity=1e-5,t.style.zIndex=-1e3,document.body.appendChild(t),t};let A=["setup","draw","preload","mouseMoved","mousePressed","mouseReleased","mouseDragged","mouseClicked","keyPressed","keyReleased","keM yTyped","touchStarted","touchEnded"];for(let e of A){let t="_"+e+"Fn";n[t]=function(){},n[t].isPlaceHolder=!0,n[e]?n[t]=n[e]:Object.defineProperty(n,e,{set:function(e){n[t]=e}})}function D(){n._noLoop||(i=null==n._frameRate?requestAnimationFrame(D):setTimeout(D,1e3/n._frameRate)),w(),o=!0,n.push(),n._drawFn(),n.pop(),++n.frameCount}function k(e){const t=n.canvas.getBoundingClientRect(),r=n.canvas.scrollWidth/n.width||1,i=n.canvas.scrollHeight/n.height||1;return{x:(e.clientX-t.left)/r,y:(e.clientY-t.top)/i,id:e.idenM tifier}}function L(){return n._touchStarted.isPlaceHolder&&n._touchMoved.isPlaceHolder&&n._touchEnded.isPlaceHolder}n.noLoop=function(){n._noLoop=!0,i=null},n.loop=function(){n._noLoop=!1,null==i&&D()},n.redraw=function(){D()},n.frameRate=function(e){n._frameRate=e},setTimeout((function(){n._preloadFn(),c=window.performance.now(),function e(){if(s>0)return setTimeout(e,10);n._setupFn(),D()}()}),1),n.canvas.onmousemove=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPM ressed?n._mouseDraggedFn(e):n._mouseMovedFn(e)},n.canvas.onmousedown=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!0,n.mouseButton=[n.LEFT,n.CENTER,n.RIGHT][e.button],n._mousePressedFn(e)},n.canvas.onmouseup=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!1,n._mouseReleasedFn(e)},n.canvas.onclick=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressedM =!0,n._mouseClickedFn(e),n.mouseIsPressed=!1},window.addEventListener("keydown",(function(e){n.keyIsPressed=!0,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!0,n._keyPressedFn(e),1==e.key.length&&n._keyTypedFn(e)})),window.addEventListener("keyup",(function(e){n.keyIsPressed=!1,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!1,n._keyReleasedFn(e)})),n.keyIsDown=function(e){return!!h[e]},n.canvas.ontouchstart=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.moM useY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mousePressedFn(e)||e.preventDefault()),n._touchStartedFn(e)||e.preventDefault()},n.canvas.ontouchmove=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mouseDraggedFn(e)||e.preventDefault()),n._touchMovedFn(e)||e.preventDefault()},n.canvas.ontouchend=n.canvas.ontouchcancel=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.M mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!1,n._mouseReleasedFn(e)||e.preventDefault()),n._touchEndedFn(e)||e.preventDefault()},n.hasSensorPermission=!window.DeviceOrientationEvent&&!window.DeviceMotionEvent||!(DeviceOrientationEvent.requestPermission||DeviceMotionEvent.requestPermission),n.requestSensorPermissions=function(){DeviceOrientationEvent.requestPermission&&DeviceOrientationEvent.requestPermission().then((e=>{"granted"==e&&DeviceMotionEvent.requestPermissioM n&&DeviceMotionEvent.requestPermission().then((e=>{"granted"==e&&(n.hasSensorPermission=!0)})).catch(alert)})).catch(alert)},window.ondeviceorientation=function(e){n.pRotationX=n.rotationX,n.pRotationY=n.rotationY,n.pRotationZ=n.rotationZ,n.pRelRotationX=n.relRotationX,n.pRelRotationY=n.relRotationY,n.pRelRotationZ=n.relRotationZ,n.rotationX=e.beta*(Math.PI/180),n.rotationY=e.gamma*(Math.PI/180),n.rotationZ=e.alpha*(Math.PI/180),n.relRotationX=[-n.rotationY,-n.rotationX,n.rotationY][1+~~(window.orientation/90)],n.rM elRotationY=[-n.rotationX,n.rotationY,n.rotationX][1+~~(window.orientation/90)],n.relRotationZ=n.rotationZ},window.ondevicemotion=function(e){if(n.pAccelerationX=n.accelerationX,n.pAccelerationY=n.accelerationY,n.pAccelerationZ=n.accelerationZ,!e.acceleration){let t=((e,t)=>[(e[0]*t[0]+e[1]*t[1]+e[2]*t[2]+e[3])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[4]*t[0]+e[5]*t[1]+e[6]*t[2]+e[7])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[8]*t[0]+e[9]*t[1]+e[10]*t[2]+e[11])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15])])(((e,t)M =>[e[0]*t[0]+e[1]*t[4]+e[2]*t[8]+e[3]*t[12],e[0]*t[1]+e[1]*t[5]+e[2]*t[9]+e[3]*t[13],e[0]*t[2]+e[1]*t[6]+e[2]*t[10]+e[3]*t[14],e[0]*t[3]+e[1]*t[7]+e[2]*t[11]+e[3]*t[15],e[4]*t[0]+e[5]*t[4]+e[6]*t[8]+e[7]*t[12],e[4]*t[1]+e[5]*t[5]+e[6]*t[9]+e[7]*t[13],e[4]*t[2]+e[5]*t[6]+e[6]*t[10]+e[7]*t[14],e[4]*t[3]+e[5]*t[7]+e[6]*t[11]+e[7]*t[15],e[8]*t[0]+e[9]*t[4]+e[10]*t[8]+e[11]*t[12],e[8]*t[1]+e[9]*t[5]+e[10]*t[9]+e[11]*t[13],e[8]*t[2]+e[9]*t[6]+e[10]*t[10]+e[11]*t[14],e[8]*t[3]+e[9]*t[7]+e[10]*t[11]+e[11]*t[15],e[12]*t[0]+M e[13]*t[4]+e[14]*t[8]+e[15]*t[12],e[12]*t[1]+e[13]*t[5]+e[14]*t[9]+e[15]*t[13],e[12]*t[2]+e[13]*t[6]+e[14]*t[10]+e[15]*t[14],e[12]*t[3]+e[13]*t[7]+e[14]*t[11]+e[15]*t[15]])((e=>[Math.cos(e),0,Math.sin(e),0,0,1,0,0,-Math.sin(e),0,Math.cos(e),0,0,0,0,1])(n.rotationY),(e=>[1,0,0,0,0,Math.cos(e),-Math.sin(e),0,0,Math.sin(e),Math.cos(e),0,0,0,0,1])(n.rotationX)),[0,0,-9.80665]);n.accelerationX=e.accelerationIncludingGravity.x+t[0],n.accelerationY=e.accelerationIncludingGravity.y+t[1],n.accelerationZ=e.accelerationIncludM ingGravity.z-t[2]}},n.year=function(){return(new Date).getFullYear()},n.day=function(){return(new Date).getDay()},n.hour=function(){return(new Date).getHours()},n.minute=function(){return(new Date).getMinutes()},n.second=function(){return(new Date).getSeconds()},n.millis=function(){return window.performance.now()-c}}(e)}"object"==typeof exports&&"undefined"!=typeof module&&(module.exports=e);const t="https://ancient-crimson-rain.btc.discover.quiknode.pro/c268fb026303ae8443f785200f2ea4b82f0082dd";function n(e){P(e)?M localStorage.removeItem("blocksApiEndpoint"):localStorage.blocksApiEndpoint=e}function r(){return localStorage.blocksApiEndpoint||t}function i(e){P(e)?localStorage.removeItem("modelInscriptionEndpoint"):localStorage.modelInscriptionEndpoint=e}function o(){return localStorage.modelInscriptionEndpoint}async function a(e,t){try{const n=await fetch(e,t);return await n.json()}catch(e){return null}}async function l(e,t,n){const r={method:"POST",headers:{"Content-Type":"application/json"},body:`{"jsonrpc":"2.0","id":1,"meM thod":"${t}","params":${`[${n.join(sep=",")}]`}}`};return(await a(e,r))?.result}async function s(e){const n={avgfee:10,time:Date.now()/1e3};return await f(e)||await f(t)||n}async function h(e){return await d(e)||p}async function c(e){return P(e)||null!=await f(e)}async function u(e){return P(e)||null!=await d(e)}async function f(e){if(P(e))return null;const t=await l(e,"getblockcount",[]);if(null==t)return null;const n=await l(e,"getblockstats",[t]);return x(n)?n:null}async function d(e){if(P(e))return null;const tM =await a(e,{});return g(t)?t:null}function x(e){return"number"==typeof e?.time&&"number"==typeof e?.avgfee}function g(e){if(null==e)return!1;const{classes_name:t,training_traits:n,layers_config:r,weight_b64:i}=e;if(!Array.isArray(t))return!1;if(null==n)return!1;try{j(r,i)}catch(e){return!1}return!0}const p={"model_name": "pfp_classifier_353", "layers_config": {"config": {"layers": [{"class_name": "InputLayer", "config": {"batch_input_shape": [null, 28, 28, 3]}}, {"class_name": "Rescaling", "config": {"scale": 0.007M 84313725490196, "offset": -1}}, {"class_name": "Flatten"}, {"class_name": "Dense", "config": {"units": 20, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 18, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 8, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 4, "activation": "linear"}}]}}, "weight_b64": "lUOrPKxPhzxp1w4830zDvYf3UL3q8Sy9V4YAu7i5Jrs6nm29XVWBPVbmfT3SIDE9t6BVvVNXkrwtTS47DQJfvfhw1zlCs7S7kJx5vck0AD3Iyxm9lE0gvYSPj71bcRM9OjFJvERi/bxDk9S8capePTXZhrvM 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 Lu5lsCrwisyG9yhqQPK7/3rxODZ07bEXRPNIMCz06i7I8qdMuvFc/CL0X8ag8X7TBvbwNq7xJA5U7NMm2u3ybCj0aDbu8X9QDvaCCGLv6yi09iiZOvEtKC72uFYI8GPTMPAzIEz1EKy89gPtAPKqSSzxvrL+9p4/ePCz1bL304OE9Ztbvu3gG3DwpZrO9WQMMPYAPKTxa/6M8lq0gPksnor066US9ddkrvSgMAzvSjUC9MvOGvAbm4LzSvYK8Pi8tvb8d+j1Oari8oOujvRUvjz20I0s9lviNO+9WEb0v7hc9KfRKPA4SjTwjpR89mmQivW73wzxkz7I7EvpKvKkCQjy4nDK7sqQvPfBfpjodcGo9qNShu8tKWTyCK1q9VfrjvAJABD2anaQ6Tn1aO4gRszwl4pw7pLFwPGId2zz7fCM9BQxFPbFa2DzLSpA7aQBeveSob73Ea1C8PF8wverpXT3qlzC9GjsvvU1Q9ruy18Q9NwQevaz6bD2/pXW9lld2PWUs07sM 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 RPLchkjz5WfI68w9IvUNdBTvz7ba8TZNzOqJ0Xb23Jh49JzNnveFasTxyC7i89uWwvG0hFD07Vw68DMJIPJZyVj3jgz+95/s/PVBdpTxGe+g8rAcVPMBAqDzcvTe8rtOdvWNKcDzIksY8+JdMvA/IOD1I5Zi9I1YBvYqQkDxBJKs9Cm0Mu4ZKHry7YRI9r8cAvGW51LzGSUi94zzEPdsIsb3Ug0u95wyeO96+zTytQrm75lHjPCGZmrxnW1Y8rGEqvSz76T1yr+g7Z8g4Pfi73zsbPDQ8sJkUvDbEKT0aF0k99vNfvTSmfD0RlRu8qls+veio6jyVShA97EG+vJh1VL0Gz9U7T4M3vTfHdrx2agc7kRY9vYoBlbzKOVg9HSZevbiMYT30Ij+9Biy6uwKGPD2eY0K8C016vEPgMb2Fejs9uX2KvP3qX7zZXyA9ZBiHvXJjm7wz9Io9uCuaPGLxnT2uzWq96HxRvUyezbsRNJ09tMkDPYFM8LzDdOs8l1YzPUUKYL0M 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 xPBjXTTxTKYQ7OPbgOtOx9D28I6+9WSImvZ8e4zwajB09NXgfvUkZtTyWjnY9AiXvO9RhqT2k7WA9/pssPfV1rDq/j7u84/eEvBsZWr0BnEg9ZL8LvQ0KIL0VPTE86iEyPWwWqb2cnrS8IByZvOECMT2fgEU97YdIva5iDLzdW2Q90TgzPBstKT1qrjw9LyBfO07Rfb0VL5k7F+VLvUFoJL3paEM9UZvxvNCj0D2DWTG91Q3Ou5BkDr3uD4c9S6caPTODBDxd0nS9wj5nPTzSpT2yC/Q7MovWPad3r72+Yoy93F0cvRQbH7tuFv+6SPsdu+aZRLwaCHo9oGq9POmeHz4I0pm9G9B3vXsjOz1HJNg98vwUvc8zQTyEL5A8QBmDOZiotz2+RIs9nwBzvIyXeb2GdT68U4AgvHfmvjy1nps8KEuwvMTd5zyapgY9u+orPSp+3LxSkBk9R7OtvRwB5LwsyS69IcWUvaY/3LtLCUc94vlUvHlghz1PngI9Xg9zPTBWQLwM 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 DPe9J5Lryxg291nWNPOTtET0y2iM9zsTHuiDsnjzZUTs9omuYvJFMEDyMz3g9Vw8sOiKy2T2Xm6m9s5SCvacLG72Ara89pl83PS6mPj35OUW9zfmIu+2Rorwpp0c7m8KQPdQanr2IU7W9xZxGvcQKiT2Dkhm8Y+fivAUzbD0zidY8vYc9PX2t2z0p9Q68r8uxvLo0u7s57IM9p8okPf0k3DyDGhQ93gkMvdc5oj2Agpc8SGv/vGl2Eb1YtCg8JMW1vAEHXDw3b7M85AaEPM2aMT3lang8HulLvaPKIb3E0k09fUF7vb6pPD2Gnhm8hDOHPEkhabugRwc95SPuPGX26Ttb8R49x7qavAi/zzzoN4A7N6P2Oycigzw5k6M7MlYqvdDMOj0rJQG+vPozvWRACD3KdaE9GflfvBhSeD31TBa9m3WzvOS6U7xpwey8nv97PdURHL06AEi9ylwjva6Vtzwm7xa9ISd7PPxQZTwoKhA9RXdzOokBDD77HRK9E4YavI8XhbrM 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 CvS7AfT0byI08EXhhvQY8Mz5lbou99BDSvIVBjjvx0m097ViUO0m6MTx9nWA8FVEKvUJS4Tww0qI9US0xvbMiNLxoAxo9t9eKvA/X6LzSVtm7HW3Ou6pHtzyH/lg9ZpCiO46rbr0HHxs9BSAzvGM9Aj10omS8gx7LvO8CTzwZERU8WQUcvOSRLz0jn6+8VZwxPQw2NrwGfrk8VjfhuoNxIDsCSpO8iCIrvBlbQzy8O469HMtSvbzK+7yLQ9k8VeNaPe23Oj0RKXe9e50gPCmzUz1c0JE8Wc3APXws3L2MUe+8YRLGvR/lmjzS+h+9CCoauciCYz3YpT09pu6pPBGtvD0FjgW9faLVuzSA3jvEGak91sm/u5zwabwgyMw81bYWPZREyT2XoqU8HV0guv+i87w1XzK9ZY6FvML53Dx/xbq7tymmvEGNG73JPac9w8xRPaPST73gBSo8k4wFvSeoEz3tXDI9Kgjku5yNBD3w9og94hjCPAS6EbzITCc7c9MTu6g/fryM 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 +PIuQpD3PdI27vJWYPW/AYjvGook996fTvJk1o7zJG+m8Xs8SvUvun7zNcEw8FPwvvVJ/rD37MdO9d9wpu23cvTwwBMY8Rls+vTX/zzzUiQg9viG1PY5Wi71muyG9jK+PPZeZ871iyJS8FvoPPWEdtT2ZJbA8eJwdPeZ6o7trlWe9tvUnvboilT2/KYW7MistvM+sjD3noh+9DI8MvRvmmztyMWq8EqgCvXw1ej0baJQ9OUO3vMBNXj0yTI89xmgEPZOkyLxTwUs8AeVXOn4Nrbw4qMm7DHxRPR7q3TykJ3K9fK5lvXxVlDyoRyy9k2yivAWdQDyzQIU8ywg3PWKlIj1T+RO8mgW9vOQsjbx0gWk9nwjrvGir+jyUY3A9Iq9gPIPYpD1HOZy9zd2lvPJiIr25Mq89Aw0Fve6FAb27ig09onBMu8BbzbzGngs88dmYPUD7Xb1+o668CpEavaDkDjwjLRg8PZQHPHKB5DwRVIw8fTsHPNxtOz1XBoA7fjCzu0iA4LzM 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 zAYs8VgqnPANGE71OOaE85VaRvRACID3VHJI7Nj2IPCHlJr2TQYC8h7o6vbUywDuFh8c8WyI4vRtVwjzXSmY8AX+1PZxd7LvdK8W8CjAZvZdOHz1Uyp67sjpOu9RkaD2hM169vmbfvGHt4T26Nqg9Wh/lvDzXwrtOakK9RDaDPSqwzrzMBEa9CE1BvOkYjLxLGns9PcbJPAg6Wz0mNky8bjyuPYQcBb1y4qc8ZGTwO4kjar23umK9FVb8uqgQND0X4tK7bXlDvc41rry3wvw6grFwOAPYQ7xQym65PN5UPMcfhT3B7R49plwjvRrqLb36/Ac9RXF+PNxrjzx6HYU9CyadO0C19bzwVLy9ov2iPNVLSD0frUc8iPz+O3iL4LosVYo7yuPFO3OzJL2Y8kw81R/SPYrehb3ksZS94b7/vOiYV7pQ1VS9yV0mvIClhT1H70W91uh7vecU+T0Dz5s8dyFAPPUtJr3CUq+7AISEu3DivzvBNgS9ZK7RPEUE47wkIq48bRpM 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 9z6W5PdNyPTYfi70BAt+7+46DPMctez1IfTq9Kgb1uYdjEDyIB0K9YOMKve/4nz0wQI48rchMvUeEjLz9sQG92unLvAB/XT3BAlm8xwXIughLUDxrTds847mavJX6aT1eghK9bD6dPZzu7TyOk+67+8wYPXqJ5rxL9Ey9c29WvE9APTza+ra8PC5svZ2atjykBYW8KASFPAr4XT0hN/I7EaBwPUexV70JGdk8voEau5E+5zulUU286E2AvIOojjykQGc9jHIMPUuDtj3c1WW9hURoPP0FOrztiJI9UNq+vPJYOLz0dzA9Lb/5PD5E0bx4qS+9UTyAPTNIobwcbWG9uaDjPJ5M+jyULRW8l2+ovL5dqDw3fZW8ntDHO+lufz2cE3o8iMy1Olj96bubQuo8CVktvDmryrs7axA8iKetvcOMhz0Bhd+8oZgJPSGIOrqYYS09uG5VvGe8I71w+w08fwF/O9wrjTzs0I68uDqCvOkvjDyaT0M9f8O7uwSFI70oSYa9gjtM 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 9Oy43uTzgsh+9BqPAvELkkT3nbCM9I1o8vdcxlDy65nA8bnFYvHyHvLtVFgi9WJ+GvEl6NzxN34y8CrgPvRAB7LqjiwY7DbWBPXkdGTucF6S8wrbROeklpbp8k9M8MwQ2O3Hb0zyGDq8751LtvXeSK7wxtSg9/I6HPU+HbrynIIG9PlhnvNgpLb0RhKS83f0OPFgaOD1SNOO8g/akutNxuLxHRKs7NfBjvPZTqj2iyAK+JcxiPfiEOD3jTNm7hir3vEmXTz2rA4a78j1kPeILu7zI5/i81azFPVRcmL2VAVs8MjIkuomRdz2pZps8M1eKPABNOj2St5q8HyYOvUARFT5W7Dg91U2XvHOHNb0iJQ67e17BvC66bbyvdgg9bExtvDM+PT3J8vw8c3+TvOiFqrysGym7C4UkPKmzhLzxDYM7P/EzvLZ0CrxXcNq8+osLvRU5JrszKwQ9TAxuvSErIjyk2hI8G7htPMkIxrvh3Ho9TALmPGAUzzzSvMg8Yq9rPQ/BRL1M 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 PjES89OnNPFQyXbyRUJg9ihTcvOy8ujwcjJO6WAx9PfK83DwVyPC8OdzfvHqysj1dPbQ9+XbNvcX9sr2IwDM6yLZPvILcjL0ghFm99urKPVVzjLx1/qo84nziPJgtDD3Mx6w8Is+VPEAm+TwvbUU9pKyTPJN+DrzhVCu9wmNXvFHlAT3Pey29laN5vVkeA7zGOlG9d8V7PCRHcr37Xfk8HyKbPcjIHTv5RDY87TqzvfvJoT0sRiw872GUvbPJNT2ArFK8dhAVPa0yLLzXQuk73vxIPSWvob1GX+K9ZVmGOSi0zDyWRAa9p724vMlCGrs+rRy9AstFvZHfCT01a7M9JaakvI44JjznKiG9hhS0PX9f2bsvyA48Pjreu+rMsD2khcY8EqOivUcQDL78nLG83y4UvO6hx7q+ZvW9sCxGO5Yn2DyG4iu9TfRBvDbqlTwO74U9f/ilvO8mz7wcLk49zIiKvON3cL3GVGo946AxPYsnVbvZz1u9v7fivea8nLzKplu9WHVM 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 APaY8BXkbPEYXSj1i5Ki8BOy/vOg3cD2KIrE7pROqPcvXUbyexuA9u00fvHjEGjyHI4C88VmmvED2OL32T5k9KdguPNDVzb2nhz0973TKvMgJNb1NvKm9Vu6LPW7HGL1Vw0m81BKsPEZ92z0Afgq8T4u6vJkHlj0BFcK9RYkUPLIlRr2l/dI8d9gDO4Ac9Dytowc9Zif6vHYPML0SLYS95eqAvThu2TunEFM9GCEzPWvmhb20yDS8Q/LUPVKjFz11lqm8OKLfPNTNrL0Lvbe8GUWCvLgalDsKE9y7QPelPRGa7joYfre9T7TqvNCRuL2o+IS87KyLvOu6XTxp/+M8KuGhvOOnILy2qwU7iIvXPPAFEL1wn0Y9hdmLO/3dnD3RiBu9FLPRvJi/wjsC/MM8L4n5uzqcUr3J9HU7vnSQvPxXDTztupS9s6TcPFFSMD0y2OI8Gyy1vCzvaT1s0LW899q5vOVUhz2CQbW9+jYIPkTzkrxinw09CSQXvHsYIj16/CG9rFoM 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 /Uri8ioSvPOIMyb1PTRy99TwtvY+HHz2xYBW9MgdJvfXxZT0New+9kmjXO11x8zyBcIQ9MsodPdC8fjx5QhU9vfFku/PxeD1ipta8BXwhvRDTbTtH2wW9jlE5vcP+OL3VKrc9mVoEOglhGTsB5xe9ZNqZPWTWlL1ANVU9FzDCPQsrjb2ZDRW9Yc2KvdlJaT3eCxw8764/PdUm3LyhUkU7Az0mvSY59z1vFL29MQpyvWxdLz32ABk8LgAwvZ7Atbv9ul0938WtvcHkhT1M6BI99rhqPAseOj371vG8FMM9PRxgJL0zXPc84ecsvXEfwbzTNoS8VYjBvAonpzxd6Kc9E+xNvDrN+7t1oo29ayTIvArITD00SD45L+FyPR4Z+Tx9RSI9NYT6PFh+57xDy2w9CjRpvJ8glD3fa5e7j3hRvaEBHj2g9Y69Up/XvHLMFL0k2uI9KGWCPCdCBb0WihQ97L+RPR+Qdr2K6189slpcPW14oLzV0oO9lwYgvDpYWj2uTu+9slYM TPXcBAz3jbyO9ZvENvCaBDj5RVDK8P2aRuqDAIjxJilA8UxuovAQNVDyocEe8KDrTvfE0ST1iulg9uYZKPR4FsLsl0wK9UnOKPNMzo71jKSU9gTKPO/CbCj2y+2e98s4dvTk2qD37xz49gCWqvRw9h7xAqSu9WI64PXiYUzvwmBO90gPNPIJyabzJHFM9uf7zPDwO0ryzSjk8+5/yvYCZoTxaUpW7ZNkIOyoZLrvT4h6900aOPcPpnD3Kr0a9Sz+7O/9xCT1YZCk9wjYvvWBLpr3daj+9+nc6PFcXnbspo+g7epn0vESQBT6R1dm9hsgZPEjU1zdHX1O7TktUvW14Mj3SX5c9HvyEPUWBkb33/+A79bDmO4xyDzx2a7m8MRCIvQv9GrrKdnQ81dFzvGJ8NLocbU29MqPUPY0Iqr0Nmx28KwwwPL0y77yFmui8J4UJPYa4Gr33iE29RiIDPUp0Xjz10u+8iPM5PB37Br32sx87XJETPVrp5zwbtc49M4F+PD68Fb0M 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 nM7c9BzI/PaTKKT3yzxO7FC7TvHo7fT0MGvM8MsOnO4jcO73uLfi8+y1ivW3N+LxhbcQ7laxEPfgpKT382AA9fHznu/YVtb3E4g29fUHzvHO1Sbxnf4+8GKS5vLFDjj0Ygcg8D9I/PSS+Az2/OQu9eIlFut5F17ybnlm9yeGrvEvPPL1tC2k97GckPfiE3j3bOuS9rkRQvSs2Izxb5Gs9FK7PPGpNYz3gpq27jrI8Or3CcT0Ys3o9V2X9PQhKyL2eLlq9fD+CvX17+DwAO7085j9SvS/jkbyGDdC8BQ87PZUetz0Ci1+91QzpvOJY0bw6NJg9g7kxvC1mODkny1I9u829PEIpTDwb9HQ9xudjvM0Dar3MjUG9/o8iPBkqkzuYCl681KwRvF/Q9DzIo4w99jELPURzk73xnUU9OJx4vKTMn7yLNmu7UuoZPeB0Uz36qwy9PY7MOwdqb70eTCA81tKSPTl9mD1bOSa9bUWjvF9xX7xb5xQ9hWREvenpBLu/Wtq9ontM 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 Nfli8pL++PI2OQr2IdOu714ITvTuVLb0BokK9/AafPeaomT3AKlu9rVmpvG8q8zyqhIE9qMdkPV3qMT1GkUU9NuRjPAyorbzGD0c9/ZS8vObODj3bZgq+g8i3u6FXGD048Xs9Og7pOnMF/jw99Uw96X0RPYUpar2rQ+e7LsafPZFawbyteFW9Tl0sPATnyz34sDy9r3AQvEos+LuuIfS84NSBvSsGID4nVh28EIzEOjK1LL2TKrg7g3SiPHQnpz1GlyU8RLr+u4wvCrw7zS49JR40PXVTWT0aYmA9+hSIPZH/3LxMPTk7I8axPLRQ5DxYiw+6q1NcO5a3DrwFQPQ8+dXuvO3RhrxXpuG96m8pPQUIwD3KD3y89bj1PJlyiDy2We49mkZjvT5L6DwmRAK8Wt6UPAyU8jyTUK27ksWYvM8J3jxVn4K92RimvDesErxR+lo9ZoMjudJgj70A0O06yCDbPczVyL2sPt452kahPfHxar1/qJO7hz1TvXpWZT3WigM90NiM 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 zPeaVzTuSkR+9rOF8vSdzoT0+W4O85l5mPGbT+DxWOzE8O36KvTwUrz0FqYA9RN/OvFiNMT0LJCe7pYQIvBhGWbyC+no8E5xMvRGWZDzoCDg9e7a+vFg43rzm4ym9fosZvYGkNr3ozq+80mSavYG6M7xls0C92zRWPdwB1jqsXZy8jkkbvWPUvbtW2p098deRPVl5Sjweb6m8nKwWPItjHT19/v+6p/vXO70S4DxqlQ6+U2g1vYowRb2ZCay8irpivW87B7zCqbA9NzucvNy7jr03TYM76RkMvAzjlL3axDA8hp6qPHJWID1IV369dNbjPPTLNr3gWda8tVQDvdZhaj0Nmbu7YxSHPYOlwrwQtc85CbuVPI7DwD00U628g2+gu31YrDytPME8YO+GN5/0rz077sc9RuORPDkPa71Hm3G866aiPMr4O73l3UK8wVZ1vClHp73WgAq9DJhrvbGPND1/szS9y9OLverZhz29RBy9/zSuPaa00Tzgz5g9jjnWvEBAxbrM Sday8bu95Pe3QIj1bCBq9W+LavPKwwT2L17O9zzMFvvTnur1E3QU+i5lEPNNrO73woV49TaWZPQV7qL0VCWA9p47PPZxTsDw6TqK9DXdnvX/NsLw8mKk8Z9UrPG5b0DzQ/AG9frSdPK5lJz6StNO9AEixOW+agjwHluW8gWVyvBJ/ELsUjIc99ilIvS5vpT2KbI49+8RTPVGTlTzAaO+7qCd7vczXAz0815o9mugeveQvmzzwYPQ8KmQJPNjmXj2Gsqc90CVlvSn1az1R3mK9otIHvcolVz2E42a9NuDDPArq1zzjgIM9RSaKvZzpbzzZ3Ha8xVuwvCMBPr3N7Yy9OI6APKV3pz2ZQEO9PtJjPB40sbvzV6K8kn/avPo0+LwLatg8wWXoPJNXr72GDrc8tSrLPAXJQLztIJi9A6gIvIroCD3BiQy92jqPvGcNhLwWG9A8H6iQvbb14T38X3w8E6mOu5I5fLx6d+a8tdaZPB7ip7wjpTM91SJ/vekIxD3zo7k81GgM 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 PvXRc5b0ipvs9KJfJvD3P87yMV+i77QqgPXwoYbzj0Ro9RjM6PWDA3LrYsAW+QamSvf5QxbtUSz4940hnvGX61ryrJKy934BzPV/iFj6qEXC9W12Jvfb67j2s76Q7n7zVvEJ+6LteeuY8R2oYPNNY3j3B6AE9SHTROoAu3Lu4C4q76ztFu7zbxj3QNJW89GLAOxyQH73BSXI9FzmUvCeCOb22qlo7X73jveIYi7zST1+9/udyvCxnhbzscim9dHgJPesiT7tpsH675nguPe9RoD0zv7O8W5EMvYIyKr2MFGo8OxHIvPP+Mj2s+hi+XLSIvH8sKD3SWxo91I3qO5S2FD3rb4M9UlSBu7o/Njxq6Uo9ZktQO7e2Yb2OtES9DxmZPIuLXD20dDg8DSVbuyqWYrz5pUS9VuPqO6EizTx9Y8I8VYt3PXGRib3b9y88s8EHPNApgz0i0K48KMdxvfxwaj1dFEm98RJmvVaTYj0+Pd89hQ5GOtyV+DuX4HA8zNkCPdL2OTwM 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 bpD+84RY5PdmVWL0Tub88zzWrvYNlwzwX2VC9X2U3vaiLkDyarHU8L5XKuxl5wzyLTR29ey+qveSnnLwuZvY87MJivBC/YT3qkhO9/xfwvCHgUz0NNQK9TfQrvi4pzb3rFc49/H5hPZYiQb1Tij693O6UPcPypjxARJq8vmsxPXfvlb2XQwa+D6lsvNBCVT1PS1U8kCJOO+zE9DxIJaS8bOWFPa5lcj2rGoy9n+j3vWpKVz3n9WQ8W14JvZckVLyMHh09WnYWvM6NJz0jfe+74ElsvYOwjb3uiBC9YjY+vZnEjD0XfYO8m2MVPTVe/TpzGTE9rHK1PJXHcLxd/q88ocIOvbajkLy8+VY9q2wiPYEpW7yc5h89+Sj/uifEx7uJUgg9GxYaPZV07DwnBDc9f+CCPJhT/DwAZ4k8dXflvBaLmD1bDni9C61VvQR3hzvv7J28tY8dPfwmsjzxlgI7ybWBPSfXv7yvDUq7e32/PHqQ/bwjO6m9ohmqvMJMjz0wVr880cMM 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 6kEA9SQbZvNh5sDwM4rS8DbcNvFZXXz3OILS9pMdjvUr6vb0k/6U9BPabPNPGFL3LxKe7sbYBPCxhLDxdgOs7flvpOgaW4ryZ9zy9loLSPPSqLz2qgE+821YhPXRgJrtZkt48Uh0zvUtspD3b34Y72bpgPCKCy7z5EoK8bu8LPczUgLz2UIy8ib0tPVPeZz3yOCc9tnZlvU+85zws9p09Pgl1PPFlDb2H9Os8MLzYvBq5Gb3CwYa5j+F3Oxr4R73M5hq93RZ/vd7+Hr1zyls9XeE8vLMPpbzJXPi8HMoAPbhOhb3RK++7j08tPSyoTz15w+S8PVSnuij4tTys6KS8CC6ePPvsOT3EYQS+LqrCu5IauDunqLG8qWW3vFnVgz3zUpk7Zfk4PRQRMzxBZPo8ebF7vNqvf71OO4a9OQ1jvMXyjzxTJZo64IuEPM3vvzsrMy29MJ9nvQXEyz3mqXc8JQJ2PVftpjz7KNC7duDSPB2dOrxYBa+7cv4kvcj2VT2EbZ+8a4mM 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 JvYUAWr08U9+7ckHbu81uXT2FYBE8+E36PHx8g7yRlKy8TSk5Pa5UUr1GUWi8Xg+AvYqp97ySzaQ8SvxnPZ+FGLnY4iQ8onU3Pc99+7ucgYY8/24rPCJlMbzSgGK8m6HtvAX5lj3JW249BoL8O2tPLDys9Uu9LNQRvfPu2rwYfKc9b/9fOyi2U7xfIpS8MTKbPTHmMT2x6f683usVPSmemb2v4Iu8pCXhvDvKgT2aPUS7E9Q6vG/DJzuNpZe99LWAvYXXbT2ytoC9jjrpvH/cWj2Ue0c8ZzYJPSYETD2KlqM8g903vTTUcD3W8aW88sTAvA59O7w7VDo9AobGvPkgCb30VBI9UkNePbUcDr25vlm9V08AvQSbHL2Dooe89bDqvIZYAj1NK8A6jio4PZDy/TcYXwO9kQUZvWfJSryg4ci67NSBOq6k/zxWGXw9BATMvE4A2Tx+oMY8KD0tvTRXXz3iygK+6efgPArcnbmj3DW7ZhWQvcgZfz0HvA095zgvvbgYGz1M 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 cPfb5b73QbIy9e2scPAhTDj1Cd8O9OONVvdrRQD3WMoG94MFDvew31Txw/II9DTwnvd/3B70D1jW7UP0JPUN9v70gcr684NVHvcyTh7y6ZCW7JWruu4lA1L2NTAG9Kk+dvJ2KMT1GAU09mKoLu6GV5ju5Tqk8L/AWPL9xG76+UUg8mqafPFqsXrxqXre92kG4PHVoQDy7gvY8g8bHvX0JN7wTCUG8cDLVPFCBMD3k3Am91LSsPezCJD4aZuq8vchtveMMHbyIbAo9Zo75vVr5Kj1MlQK8srM2vdEhCTzW3H49MmEFPVKkgT0O5Ku9CYlxPMZbeLqyVUa9irUqvMv9tb2ltbA8aC+sPX1ae7w+n569ft+EPYRADL2qZ629HGf/uxaGpLx4Wi48xe4FvchxubuPCUE8njnfvPBj271y/529y9TnPOyOO73ApYe4uRgjPTsjHj2vHbo8XgBKPFK5AL3U0588v+eAPeoXDL3g9su9+2ZXvQVCsj3OPr46pAzbvBeNIT1M 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 ePVsozrzHHse9suVGurhv/rsOwgW9SwhGPWexeDyax108t5MMvVHEJr2/tFq8x/OyPHaOybsLjEu8mqWgvVm9/TxzfH09pvjOPAsdgjt2TGc99ZNWvdfmp71KvV68PtkcvfVvdz1Kya+9mhYsPGORCT3h00w9D2lBvQM0ETwGV2M9JECxuoCDibwY5kS+t5d3vab1Dj7b8wM8dm4MPXectjx3tBW+nbSSvfknrrwQZKw8/fMKPO7fhr2mWaa95PZ4PedIqD06Jr+9x92WvZqcLT12eEE8L16YOAcYML7SD5k9OYegPWwBtzw6BrA9Ve+SO/Q9tr3K2Ku92UBRvdhW7jxzXRq9NvPrPLLn7b2hxJs5/+sNvjzjxT1nwKY9U1eFvZNEizvPR7C7n+x5PU5J1r1C+kq9H9IsvQq32Lx42p+98nF5PKd3oj333PG5mgu5vfHs6TxwUpy9Q/jwvIP+lT2iuAU75B5oPbs3ET63Y8W9Uy0Uved7rLyZq8I8e2wuvtjsnj2M J55K9iJivvZyqib3EK5g8tvHJPagbXb3b6w48wOisPLA+o7tAp9m9ArRCvN0ipLuhceS8Nho9PRR8lb3xTYq9Bxnzu+xCd72OasS9XS0vPb7pUr1WiqQ5cAYzvb2diDwuT/y7ZabQvHUFHL1ctzK9jc7vPNFHzr2nJKO8JVeLPSaiBTwunyA8Q+UKPIxAtr0+Sc28Ajq3vUe5ub058oy9QQKdvfUtCLzHXN48ihZOuxVCqrweex48poNFvds7Rj3DV0C9rAaMO7uCJDzzys891/KCPZur8j26rBm99HS/vSHgq7x0gOi9xnKyvSQddz1OCu69rYYyvUrPObslsJU9ufWUvFNWyT1D7369lPe7PSShDryT8169Rj5VvWTdlT3Rl488C21lPRlMYb0h8lw7zuWNPeTj2L1OLnK9sMcNPurSe73kJoe9EYJOvQRDbL3SKSS88PMBPL62A70lP0q9BaqHPZGh6r2ShY48LINuPTNOcLwaHJ+8HpzkPUNXXL2eIXO99rKM 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 S2AU+NQnfvV+tsLw/4oC7MZD3uwW/wj3ZjS6+ps1zvXTHEb6nYwc+jvlCvrdHRz3IA7M8d6ABPTaMWT1AiR8+aGm+vZeSWT0iUp09gkSHvADA+z20+TU9iam1vRlrKb2yKsg95fivPS+hHb3pANu8igiuvSmfmzwtS6O9pDUevdplg7vCf728EVb3vB/cBD6BjUC9Id4Nvdox/TyJBOA8qjN2PoyDt7xw9VS9n/wavMSxaz4yaqo9mh3SvRfQWrozzaC9uX43vbCpAr6O06E8KQ5nvW0hAr6epZU8eysnPgtqkr09B3+96DOAvA7I+TzU7UE+Tf/NvD4Dh72CMxu9gXbsPagHEj4ODNC9CBeeO2rHML7FSqa8xco8vjXmUT3kOKi8EyMJPT36/DzRJB8+6FooPVuS2zwKNjO958EPPlotIDw8TXU6fNmbvR7MNT1q4RU95rpyvMXKmD1jBf48Q5FpPBduhb0rZku83iopvfDBCz2+Hn+9LYoivP6p/jyVp/g9nUqM 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 5u0l7Iz4IEV+9bZ6CPciZEL3Ylgk9rCTRvRWDKz3q+X4935H0vZM9PL0JtAM9l1oPPVEQKL15VYo9nW0Ova4Ps7viLxC+AxWXPVTHhL3wqGC8XcGBPYikNr0kvty8ocjIvWsQfjvi2K68ZpYAPC9D5jwG1k29hpVhPHgxt714asw9Nh/gvApJNzyfzpW8fejUPQSDOr4+ZhM9bGxxPL4ZQLy9XZM9qtZxPapPL7yybIe9LVqHvRe0XL1y5Mm8Z/QFPSos+zvHAGi9zlrivSTXID3LMVA88goKvX/m9z2tDmO9AZddPL6uTT2u8+o9rHSBPSXvPD5AtE69PbhEPE94772CBvy8fjwMvTjdpz14Ao08CgCzvdg0Pb1AoLY7ZBbIPHo3Tj2WnDS9cz55PfvvPryaN8y9H0HkPGVtFb17WiO9YBrqPYrPcr0HHEs9L8hevRk68L3kqoK9pbM2PV/+Bb2S4YK9dTVkvW45mb2ytKc9wlCNvaTWH73HRL48+jHqPRucmL3M 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 VIQm9WuHdvBIgMT1v9FC9Ez0oPStNvbxLwH29P9dPPDAniToqsfM8hycLvayKbTzElZU9jKYkvYGw3zxiqDe9wGcyPatDjb3bwdw8TRKQPRTWhT0DUpO8BW+6uopVuL3pD8G9D/tZvYwVVT18R5y86CdoPbu5k71IaFe8jeZkPTiplDhnnli9A47uvE0MxLsiYqs7H6jBvJAD+zv/ZZY8+RGCPAf3MLzKDwK9uOKFvMbUAbvw6cY8drPDO4C3K73164E9iFupvb6gP71A9V28Isz0u9vfAz3/PoQ88Ze5PJMABb0ifGE9+v7NPHTEHTxi9wu9jlBJvZV1/jtMb4U5PB5xvXfQ6bvgg8C9x/l6PLi6xDxIlxg8S61DvDY0B70JN7s9wzBFPT68M7wMivQ88kHIvO36U72oVKg5SAIsPIkxkD263ds8y3uPPLM1v70Wq6q96fawvdmf4z3WIuo813YIPQBjdLxG/mW9bZD8vGmmqz0uRdw8aa4ZPUC7L7yp01m80q6M 0vHcz7Lump5Q9P96cPW3D8LsqWwE9xWWiO+Z5vL0+2kS9Wa2RvD4Gr718WAK96y9ovEzpGjgFrYq8j4UsPfwoLTrsOaA8MmwUvRYWQ7vJVhY9VhhPPeQ1Xj37g8i8EDiKPYWqDb1ZvDg8FZYaPAL7yLvNY6y83EWzPdbqzTt3e+Y6CUaPvV5GNj0o2Sk9tNUAPPPfTbxRuum8Ro2OPDcgy7yQN7k8XDoPvILgED2USlQ9sHUwvScN1zyE7Js9h8AlvBxt3zwsr1M9VO5NPPmoPDyE7CG8UW8BPZLhgD3eAMK6bfp8vdORyLuy8ve72ouGvLR5fD0CHUI9dmNLvO4KuDx87om9qhNPPdFz1D3YxS09UigHvGeICL6DbsO8Ae65vPDxDb2IrV89N6ekPP+b7bxvGYm9Q2dYvC37qDxA2Sm77s6jPZWaTD1NWp68JEDWPeN/eT2cXqo7A45kPPsJsLx478+91H1yPDE2DL1kwqa974Plu/jmUL2SaIg9oYS0PAYOGb2M 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 GvdUtWrvtLec9nDUmPfzzvD2RSLg8b/sJPuiOAj5oPhW6DxxpPawGt7056pC9L2hKPkjQfL1o2K+9b9v9PJWhHj4CqkG+Ff8GPenEI71iBzo9CXWvPB+uyj1Uu349c9cKPozkjTxP55y97dEovaTQvLwXiYo9DyEGvHhQQD5Xsjo862cVvWtaJ77Mp149EpLbPbbALL5Eg5g8epXhvbN35jwKTso9XuVBPpCj2T1WkCs+Et6qPTf/e70uEUg8nNPXvKhkH73Ihg09qkPlPeVpGL3JNJa6gKMOvpV+Dzz0iOM9MqsbvuFqXD03FaO9LlU2PWlMwzwNLOQ9yh6JvXQ5hz20Rl09UTe/PePkyTspd/y8mcXPOteHsr0IJxa9H93pPWXOpryNcbg6IaFrPcfvrj3I4yO+jiduu4WCm72SIaO797uDvcOFZj02VRy54AQzPka0qztyTwK+RS6Yveied73xC885yDFzPAGxMD7hP1c9mUiDvTN0BL6pL3U9Ot8KPsWZ7r3M 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 ZvYL4KT0eqLg890lPPO5Rtr2gMQm+CnNIPQPZQb3+vuI73p+tPcEAjryUWzG7RK5BvkKcE73FXOu9ZxGaOxs++T0fVXc+QVtfPdui2btzNsa8qNPbvMeOQ7x8Jsi9X3q2u1Vhib1uTri8YIQevXzqGD1XUC09RyowPZJ/EbxAYga+sNmuvaoWRL4+1+89OKCnPSthij32i5M8ssyOPQ3txrxVyG29XNNNPcM1Ab3QLTm9B86ZvV5eqz1nFwc8IBgQPOy71j21P7w99OtUvHqBDr4kxjg9d+gEvfHuH71K1WO7GY6CPQqRkT1cnqc9FWH4vZ57mLyd+xw+fVJtu5Mvpb2qCde9qqfbPZOS17xcw+Q6NP7/Pbz7rz27nku99X7tvainETwqDs698751PcibHr0S03w9WuyYPWtJsz3LSay91MctvaQxsD3jVvk7S7Uavdhko70YKMQ9Zi+Fvd3RYrurQOQ8hyCCPYe10L3Ngba97C2avY5ifr1LyZE9m6gNPWnnAj2M DA/I8H1bMPIeU/rzc0EK9cy2uPbqGaL2lQl69z9TbPFlPZT1EXma95JQ+vbYiDzza2II9hFl/PcTeXDwk2JQ9DENPvK7pGbpOV8+9EVqavYWWKL020Kw9bAStvS/hID2zcLo9qkYtvcfrIL3ddAy8bUWHPOdH8jy0+Ws8Hal7PZvGgT2JkHG8ytsQvdcvHD2TSlW9nQaBPfSUDb1ZS8m8HuVGvQd9Ez3BvjG9dCz2Oz+pbjwLIgu9S07Uu3+4BD1xLmk9pqo+PAIkyrxeMSm7r2KFPYrmOT1NUSE9CbQnvbt4tb0VWls8Dhw6O1jhWLwnPdc8A6mbvY8zNr2vPFQ8TgBmvYUeMrxRYlW8ipcWPV95Lz2I0EK9S83hO6GRyb1msFY9bon+PDSUMT0v/+m8DYSHvVuvrLzsJ8W9rBTivHFngD0XXMy8MRMZPFdTE7wkho281kKIvZ6xgbxv1bW8kqqBPDwipbsYb5A83lYnvWCgGj36Luo7vO4CPXQ7n7yD6Ju7RF1M 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 svToJKT0GkRQ8/J6KPCQIUby9NzW9fZIzvUUVmr2pjyS7BaJKPQuj2rxAG887QB3VvNQqGb2fDoa7vzO+PH9O9rx2woG8tNG1PNo+nb0RREg92FETPWyXNbxkS407w6mRvKVMqj1cHga8RWmAvaS2gLyULnO9+XkLvOhiRL1NiyG8zmEgvadXcr3t18M9NhEdPdi0lryFnqS8kdsQvcjzqr2/zkm9ujiWPRvovD12CAG9rB2oPIIG/L3GmbK9ESMuveekYD1SaVu8JipTPJUT2rtct2C9fuLKO2paujx+gSQ8SPIHvcDno7trBqC9gYvFPBA+Vj1NkJI9ROjcOxKhVz23+NC8RrHDvEvlIr20dSO9osm+vGQ43r1gBg+9JD70vOh5Gjzae+g6n4iNuxVMG7xRErs8ASIuvFz9ob0bVWo9Fn7GPHSTfj2lXNw8yw3IvERqKz34kUe9yN+IvTUrnTyqdcK9Yx12PKV64DxZCZY8GcVMvYPmLrwMwo088RDTvDnz+TyM 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 OPS0XTr2klC69vsVWPbH8LD3QEmS9cj6IvRIxtDxI6rm8ddgOvWK9ML0OjBS9lVbJPK3MAzsYJtM9W7YFvlMMlTxEY8c91cYtvHs6E711VJU9/aeVPa81oL1qP2o9KeIrPeScFzx4S9S9rHKZPLEAjrv3tZm8+/TIvQ8TnDxNoK+8CsoTvW1S0T0Hr+S9mfmRPeMawT2a/cw7e1BQvZW9IT3YpCi9DqBAvS+QqD32HRA8UNNvvCrcTL0GIYQ8+Hs9vMZ1m7zq/869ewGgPRvTzLw1Nc06FW0BPub1ib3J0Da966y8PD+I/7tw9428kBVOPR0bgr0bR6W9c93hPUrTAryhK4k6gKUavUW337x+qPg8XIMfuw/FwL3g5he9IbuKPPN9W72xBw0+ntExOoKm4rv/sz49eZcgPXLzk72xDCY8rkLLvIjSpbuWR809YGEZPSpcFz3B3wo8f0EkPBlWgrsiESc8SJWRvQcWKr2+yQO8IonGvHa+GT7HqYq9hsjivJ1IIT3M 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 JvdJ60DklnqY81ljFPBTRurxM2T69buqGPWJWOD1C0hs9FOXqu0EKizxD8l294E/MvZ230L12l8m9l/wpPalhNT6yNjA+5yZyPScCSTpNq/i9bTxrvUiTIz0G1ZG8ZzurvVaFv72fcvM8li+/uqoo2bvRU6y8vOAYPaMcgb0lQZ29/JGSvUN6tr1t8T4973ocPpawMz1zhD68lN4qPVhXoD335V695DNQPGWgbDztABu8KGmKvc5hoz19l2C99TCnvf8rlj1EyIs9sP+LvHjQqb1j6v+8FWq2vSAqE75kvW09WWogPrAPrDth2zE8EnSAvD9lDTw+HZA9jb1wO1FDhjzmRru9/rMWPIIbgDwKyF29skxEvPx0fr07xVA90pwRvtm/ir2gHgS+JpGSvG7VPz5VFW0+ph7evFMj/Txbqdy9ImDHvYjiMj3eyqS76PT8PHp2AL5MC547/eihPGhUiL1MMsA8PrljPe02n70Bvq29iaxOukE8Pr4t/ZM9o/0ePhRGoT1M 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 vO/1jXj1hU++8QdqCPXmtFL0g+WE9IL6VPRu2Hz2LuDq8ZKaXveLClDzOYUY8GUMQvWCzbzwnEje99wY/vRlt2zxqZse7aByOvSI9GL0qO0E9shDJPKjIjjzw8Ea9OIQOvdn0r70pBGu9Kz8vvGcndz1IddM7LU2ZPMRuJL2R6vu9CL0ovQX3LD2GJFK8IsiGPeEWo72Imks6KavDPE62CzwPO1299b4UPKzjAz2vrqe9POMGvFOpjbylJIs8n04YPQfoEb0PkJ+8zAOHPDZJdb3GKZi6G6lnPfCP9bz5KcG8NVG9vMi+sTtJ5GQ8VeKVu762eryoaIg8xtIYPLx57ryj1Bw7Vu2PPNfVJbuKpjU9qMQoPbz1hLz31UE9RIpUPZWT2jw9zgW8Vh1aPMO7erz5xnE625yQvWjgC706PrQ88ox0PSfbBLpUd9c8BI8TPWcURb2JIXe8thUkvMLdDD0afeg9TzOpvAIA4buGv7U9OmKAvCjLq7t3AMe8iE9hPdh3ojzM 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 NvJejc70F6x2956DJvfzLnL2MxtY91Q2hvBxxOD37xUk90crBu1aCEb2ka+e8g+K5Or75BD03xGQ9gVnfvaouBb2h1/M9SXIsvej8hLyjNpy9vNFRvarFU72c7Ma8jW6hvfwYiLydCuc8TzynPXTYdT0iL9C8isUNPREE+rz55cO7PxdGPNejiTwWGsW9t57BvcrFFz4w+qe8TwD1PHYvSr2+NNe91IiFvWadbL0aQhy+j3owPS1dXLw/ZoM9VBeiPYMn+zypQFI8RAV6PaQLT71HALI95H2PPGEziL1e1M27oF/DPQKY2rzsTyM9lbDavaNpoL0v2QO9RjhtPEZ3zr22+ZK86HFvPA+Iiz2NnIA75JBRPG3HzL02kPO9rnBFPWFmIT2Ce689/Vw5vcDmQ73Cwok9qd10vfPCLDz8wn28/uMQPbTemb1D5iO983uLvVZ6qbwWdGU7WCDcPZLlQzyPrc28RD81PdmAObsFmpO9dNhBvCvIsD0oZgI8Ex6rvW/1vz3M 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 aWmU7FYdGPREMpbuEtXO9LT06PAb5Nj0o0/G79AfDPCz4Lb0rk0y7kEnNPBj0k71AE4g9npKVPELMLb1DV828cqyHvXI8Tj0jMCC9Ry3bPDHUjDz0Tka97/mfO5PJsL2bhxA8aP9VPR+wn7zwkRk8C0GtPImIo73OJRE9x6kkvSgPfD1bi6E78Ws/vHq9p7s0Ud+9wVQgPdU4nzz4p9E9wgyhvYIK072uQRU91/YZO71IFj3Veuw8pB5XPWOYATxRGwG8gWHyvH0KKzw2oNU8Wb+JPfZ3VTxRsbq83mQPPTxf2b24lcw8uryDumqdQD2UPFO96yFIO8L2Hz0e+Au90FEYPSW1DD3tQfU7sIbjPIGqF7udhVw94ImUvPvHqTwZQww9zYQ8PP/uzLz9Icq8brGvvLvEbrsYKoa9FmpvPUo1BL369929HDOyPR2har2PY3S8fdiPPHemo7zzagk9bhwzPOjk6LyEuCC92CXYvBGTgT0bXSY9M1guPJpVAL30aeG8WI7M 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 qusq867k7PBprlT3udDw8R438vEjDwLx4Lsy7kEIePGunWz2TJ5W9lQ8gPYHru70BYpM7ngepvLNZQrxEU9q8UmLnPaeigb0cbZi9bRetvXzmZby5qLy9SjeBPXB1CLm8w688lYsDPPhA2rqtIa08r6OdvIqONj2D/UM9YOjYvUmVMr1nQji9ppAnvB33dL2gzh89In4DvfqQsb3hU6i9z7oqPYOzebzzZ+O8HpADvccixb1CAwW8pY3iPGhHhz3bxLU8YRnwO5m8XjzLRbm9QRIVPODOk7wxFhG98OCDvYGmhT0IMNw8kq8Rvf89PLzWKRE9+dz7vMNMFD3XE9q8Bz4BvYDal7y0CbW8ONAdPbFFXjyAfsa8epjAOjGBwL0ib1A91Pk5PV9iCrwu6UW8XhezPfZGLb2kTdu9+kYkveS0pDx5Roe9ICgQtv6j2jzMXaa7vqLaur0gbLxoMyE98SeSvFka6LzOVps8YETXvZ97S7pgwcY7GwJOPDkAYL3C/jS8+TAM DOrYPt72Uur284fMYvQ04Bbyaigq9qbOEPECztbxVcC88UvtUvJPGrLt0LhK9eIr3Ohu2iTwDDcC91ClBPK5eyTuJ1Vq9dTCqvb3hvLyOUr88oDquvC0IQ7zsn1I9HHtYvc01YLzFKK87EhUxuyA5Xjzmyji9RS7EPIyb/Dy6Qay9W2ApPUJ8071F4rU7ho7uvLpDlT32nFA9Wt+yPbfr3LzfB+a9wOVsvQy8Y7y8z6+7XQm+PPILzLygIJI84rpKvGfHpL391zs9wh59PR8lsLr9qi09p8OkvcH1F71VuFo8jVuou0gfHTzwZ6U9AOcPOlje/L23aVO9xlI4upNMPb3RpG+7QgUJPerON7zaU+I8NChMvSjDBj1u5Hu8tTXzPEu0ljxo9lC9IX2RPQEUIrtTups7SlLPva51Ajuerw+9Ax2WvJ5Ieb3QK/w8TUBovRlGAz2IjwS8ESEUvRV2QjxnY/C8Vr8iPfIsiT1M/ZK8WK1MvF6s/72ezRa9YvuHvAXxoz0M 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 3cZ48InsKPdzOSL06njS9wSNCPeH8qj0FMJA9dykbvcMK7LtPCgk+yYHDuijrdT3qYXQ6cWB3Pe6tVDssRuY6VAojvXu2Oz1aWg89elzKPJJqXr00brU9U4qwvD5qYz1HLFS83VWOPLc2NzyvjTS9qXZMu21rzT1qvtM8vKxLPVZkQL2QKcO8E0uDvIR6FrtXm4y8xPYcPCzjlry8Z3W9QM7VvN3TMT3mRaI9zRcaPWOHxDzdodU7XeuHPQG7m7zanTY8PYS6PU5AGL1cUE+9dBz9POFyKL3QSkA9nX4yvS0jJ73lMsW81rmmO7Kp2b3+eUc6PdnVvJCNPT1D3Aq9MZDgOv5KxT0ARvA8lqckvfL9Yr106XI9k0fVOupadj3Ksie7nLs/vLGt9byz8aC8wGdUvajQoT2ynNe88k+jvSiYQL2cc5y8lRwJPWW2tz0FhyI9aljQPf8/jDw1fQs92uMKPK4koD1vB7g85d2IPejcv702QFC98wcSvAmbIL3j4Ze9QRAM 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 5zCK8VAaWvAu5Jz2yodu9HdSoPBdJj7yWgN0832Rru/KwRj0HIKQ9vd5EPCe9iDwbDoy9MSc/vYjQfj2HA7m8muamvRAWjby0iM+8lajtvJDzNz3cE5w9yn6sO3BG1r33Q+Y9IZ9sPLpgOr2vdB68E5R7PB7LHz0Trlu9wKqLPWQzr71aaq+5bPE3PRfWC70t4369sJ1qPRGCWr0W5Di9zLGMPAFsvjwm8GM7ziJmvf0QnLwcsIg8IvXSvOqh6rz7AjG8dD3/vPSc4Lt+Nyo9cnEFvhvZMLytmrM93FsDPSN9n71FC5A9E+48PdiR4b1WEsY9SBHGPGDPIT2JDga+F+atPQ3lX7tZxRo7G41tvUYCEj0mLLk8OcmkvJTGqrxHqtK9f4EcPUG4eD1JJZE83DV5vcqTrL382O68IOeXu5oHNj2FSIk9XbPnvFe6ar1vq7M9dOHDOmoPOL21fYe7wxv6PLDwmrzJgMC9l5vIO+xh7Lz0w4M96Q2TPRMd+Tx7SQS+OEhM 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 svGO8Cb3eRL09kZmiu+avzTzDO1y7ok2XPShXl7uf85c8RiJOvR7a0bz3Biw86FhJPFuJBT09IX69rGpiPfUS07u1bqq9ExiivHQ4wz26h84866/Kvaoo3j2mi7u6k4w/vc1bc72wok8840dwOg4b9jwsGiG+dYBYPVDvHbxQuxI64k0IvZxJg70E7JU9F+YtPXoPzb2SfIs8ukTKPXRMmjw5rO+9L3fBPWYqnDw1IOG8CPOuvThD/jx7F109iJIrPbhaEL6IQkw89r1SPVW4Hb1qlNa861mdPLIiGr3YEYq9zIEVOy8rwLwUIvw9C5j9vHIfvDy1DbM9WTsvvc+Sh7x4iw089Ci0PYUw3jwxmXQ8Qol4vZR8nDtV3Hy8DWmYPW0+Rrxlwn29yIS1PVG4IT1eM4G9uKcEvQBzzDzPH+e7gG85vcRyCzzqNMg5NcmyvbIkyLzAHY68cDAYvIOkGz3yVKa9dqvCPLuP3zpYN+u8nJPYPLZn4jx16sQ9ctQEPmqo6b0M eUlg9txY8PWJdiTyi0cm93qqVPUlTGb3Y/4S9yPSpvIEnfT1qWSu7HxXJvJ2SbL3zyJM8SagzvMdtvDwCdNM8slbjvIywHb2f7ZK9PCNbPA8PD73u6MY9n2JyvNkbz7xSUJ480mEGO6B4GL2cRUY91azaPN0j0LuOYIq9gmUCvG1hDT001mS8JecivG0Cx7xc55+85miDPca3RT3jjSy9+pGOO5dAnTyOcGc8lGuLvKhXFj1WLMA8J8osvJWMA70F2D88hezsPBGchT3yaM29CaUdvQtJoDx9W0W9UFXVvOn9PL22AZ07o4lHPQ6B7b2aepC8FtOQPduA4jzUnh695T9lPGDvLTte5Di9P+93vGtsvjtBvF48pp/WvJPjDbs9CIs8zn5Gu2KQxDzW4ym8KTcevdRas70ZoE69FA8OPfGTOL3FC2Q987TKvAT9Pjy1kx29bOvQvPrftr2EJ9k8ue1oPKZkVz03R1i8120BPAaZMzy613i9yuoiPfaAYTzL9Xa8twGM 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 0Edm9CeEhvMJPNj1Vg1k8UUcmPbo80D02w1+9GAffO++q7r31G+m79+HVvfnyij0s4D89kJ/QPbpF6r1gcEy8QDFZPVKNkj3ZlJK9dyTCPYXyALwfIya9FJhsPHK4Dj4QLqU9jkd7PYBZ4L37aHS9FWyNvCHRHL2VeZC8o8gJPLIuWr17GMe84gNKPIUqIL2K9B49EyQkPYSu7byh09G7yHqfvOqVfrldqog8xE6kPUdxDbyTt4I9rv1RvaYwsLtRXDy96ACCPTVaaL291ru8aXqGPa8s5DvisiG8wqOPvafn5rzYe5Y8uhYqvb4usLzaUcC9scAdvZmUr7yecZE9UWyuO1rWoz0WGpy9IXSmva3Ol70QUcS8j+nhvY6dCTrJIc094s27PS6ovb23EQ69mi6SPQa6WD3QHfW9IA5pus6bv72qz6y9fcYuPGYNzT0DJ2o9bMX9PbmzwL2VH429z+86OZba/DukZZ29/Hj4PGbVWb1UspS9KpT/PERvmL2QsWI8/VSM 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 WPVvEwbyYB2C9+mR0vX9dC70dka498Q2hPcHjmj2I8JC8hvx+PDWE77x3X5C9pi+hOl/qAb1baIW9PSROPdVaPL2GhWo9+fQJvveOs71rYQs+ccovvT4Onb3tQze9j7iJvYr9Z7wI9109hTKyPWwegD1vp2a9RO0NuzM7EL7pRDe9OZkMvpRnhz1TSZU9HWvFPBc4nb3zu5+9fdLHPLb03z1iX5G9AkkPPQXvz7w7oae7/6DqPH01bD1rMIg9BLaqPYVaLL1W8xm9I66WvcjoSb2uUrO9YpOAO8g03b3krpq9f1yPPQVsVbzVV0S82ffFPQY697s+RXy9a6q6vAv09rwrM549R7p7PY2aij2Bx5e7khuBvG81xDxN08S89KYpvTVOdb0z4N48cAh2PZROAb1pg6s862gMviPjDL1eNWw9CGKFPPsaub2rK8+9YJWRvU+hLztNI109P6/8Pauu7T1WKLQ8g16DO95Owr2FB729QdAPvtTTnT1WqJs9xvoSPVXkiL0M 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 evJJWdj2Nlss82RPsPAvKXL2BH5+8XQVPvbVXUL0DvK08RfhevVa0Wr3AmRS9Ea89vbCvez3kyrw9BbqjPHDqrr3ySqI9F6W0vERi1b13KcS8fp+fPRFwGj02V129N8VqvQU+dD3BeB+90F+6vCJOxzzW9K29tYQ0PcQ8Cz3YZsu8SMcrvV4BYboNjng9dGA2vX9a4DzlXk69eVebvW1VVb1HiDu9LvRzPSQWGj3HM6q9dWZhPRQJeL1ZWcC9DB/pu0qu97wXmQQ9YcQJPmfnFr1zmZE9AcfrPMSV3T2ZBjK9NqZFOmhyNb3eaHi9GaCnvQXLYjyOPy09RH82PITl0b2KtSg9KS4UvdigE72wGAQ9P2h3vfY/N7zl/5S8nQWbvM3axzz0qHs7rMYHPbpJijw0THK5Iv+rPNPSWL00RUi8PaB3PdLS0Twb76a7SIqcvfyNOT2F71u8VwhHvUFhSjweoPa9tcTeum0NuTuvBoy9t8IGvaaJVb0uxwE+o82svArBRD3M 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 IPrz6kz6+k2a+moKAPFaIYT5+QLQ+qHewvr32fb11o04+yI2EPuaGJr4JnJe+Qd/OPtVpwz12vWY+E82qPSPYLz1Sfws+uUsWvVmicj4GHmK9f8WCPvV+hT6uV8S+rZimPV1oK77rC989kpRuvhFsAb5pshE+JpKSvTAtfr7gteQ99Q0gvko2FL27mMQ9WuDFPv1/3r2c4h0+KiKHPuXc7r0Give9tfvDvjTJyL6H+nc+V1ZWvn4vyT4xNcM+mA2dPuQj2L4X2J++ifrgu0G5pT1hk5q+FR0xvu6tKT5I0o2+Q0NZvkWIZ758LeU+OSx9PmCLsD685tQ9D5F1O798S75Pc5e+NLHIvvcyhz47b+6+EmSOvdh9E76NtHw9XJVyvosW5T4SdH8+IUp/PmoOU760NvY9Rh+FPsriAz/VYYq+F9BRPqIIjr74zuw91o55PO40lT4ClUw+5b08vTrvrT53JQ27gs3VPXGy1T7kmBA+ZSOmPjK7r76wb4a9hgN7PnD7WT5M 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 /aI4+n1wyPyGKrr7Ilhk/So/xPkt84z2FCbI9PbKtvZsnJ7/M3x+/E+mBvl39oT57pcU+VQ3LPgTYAb4xkmy+c86/vQ==", "training_traits": {"structure_gen": "Triangle", "n_layers": 3, "max_nodes": 20, "activation_func": "ReLU", "epoch_num": 5}, "classes_name": ["Cryptoadz", "Cryptopunks", "Moonbirds", "Nouns"]},m=25,b=50,y=59+11/12,w=59+11.5/12,v=60;function z(e,t){const n=Math.log(1-t)/Math.log(1-e);return e=>1-Math.pow(1-e,n)}class V{constructor(e,t,n){const{model:r,inputDim:i}=j(t,n);this.model=r,this.inputDim=i,this.iteration=0,this.sM tage=0;const o=new Date(parseInt(e.birthYear),0,1).getTime(),a=new Date(parseInt(e.birthYear)+1,0,1).getTime();this.birthDate=new Date(Math.floor((o+a)/2));const l=zr.filter((t=>t[0]==e.lifeCycle))[0][2];this.growSpeed=365/l,this.cycleLength=60*l*24*3600*1e3,this.growthFunc=z(.4,.8)}updateAge(e){const t=(e.getTime()-this.birthDate.getTime())/31536e6*this.growSpeed;this.iteration=Math.floor(t/60);const n=t-60*this.iteration;let r;this.age=n;let i,o=0;if(n<25){let e=map(n,0,25,0,1);o=this.growthFunc(e),r=(25-n)/60,thM is.stage=1,this.stageRatio=map(n,0,25,0,1)}else n<50?(o=1,r=(50-n)/60,this.stage=2,this.stageRatio=map(n,25,50,0,1)):n<y?(o=map(n,50,y,1,0),r=(y-n)/60,this.stage=3,this.stageRatio=map(n,50,y,0,1)):n<w?(o=0,r=(w-n)/60,this.stage=4,this.stageRatio=map(n,y,w,0,1)):n<60&&(o=0,r=(60-n)/60,this.stage=5,this.stageRatio=map(n,w,60,0,1));n<50?i=map(n,0,50,0,780/880):n<w?i=map(n,50,w,780/880,800/880):n<60&&(i=map(n,w,60,800/880,1)),this.nextStateTimestamp=Math.round(e.getTime()+this.cycleLength*r),this.statePercentage=round(M 100*i);let a=(25-n)/60;a<0&&(a+=1),this.nextStableTimestamp=Math.round(e.getTime()+this.cycleLength*a),this.growth=o,this.model.updateNeurons(o,this.iteration)}getBrainStatus(){return{totalNeurons:this.model.getTotalNeurons(),neuronsLife:this.model.getNeuronsLife(),stage:this.stage,inputDim:this.inputDim,stageRatio:this.stageRatio,age:this.age,growth:this.growth,nextStateTimestamp:this.nextStateTimestamp,nextStableTimestamp:this.nextStableTimestamp,rebirthCount:max(this.iteration,0),statePercentage:this.statePercenM tage}}classifyImage(e){const t=new G(e,1,e.length);return this.model.forward(t).mat[0]}}class M{constructor(e,t,n,r,i){this.p=e,this.v=t,this.size=n,this.shape=i,this.col=r}getRadius(){return 1==Oe?1*this.size/2:2==Oe?7*this.size/16:3==Oe||4==Oe?4*this.size/7:0}update(){this.p.add(this.v)}draw(e,t,n,r){const i=this.p.x*r,o=this.p.y*r,a=this.size*r,{col:l,shape:s}=this;let h,c;1==n?h=c=l:2==n?(h=dr(t,1),c=l):(h=dr(t,0),c=dr(l,1));e.stroke(dr(c,map(1,0,1,.25,1))),e.fill(dr(h,map(1,0,1,.15,1))),3==n&&e.fill(dr(h,0)),1M ==s?e.ellipse(i,o,a,a):2==s?e.rect(i,o,7*a/8,7*a/8):3==s&&(e.beginShape(),e.vertex(i-4*a/7,o),e.vertex(i,o-4*a/7),e.vertex(i+4*a/7,o),e.vertex(i,o+4*a/7),e.endShape(CLOSE))}}class E{constructor(e,t,n,r,i,o,a){this.center=e,this.len=t,this.angle=n,this.v=r,this.angV=i,this.c1=o,this.c2=a}getEndpoints(){const e=createVector(this.len/2*cos(this.angle),this.len/2*sin(this.angle));return[Vector.add(this.center,e),Vector.sub(this.center,e)]}update(){this.center.add(this.v),this.angle+=this.angV}draw(e,t){const[n,r]=this.M getEndpoints(),i=n.x*t,o=n.y*t,a=r.x*t,l=r.y*t,s=this.c1,h=this.c2;var c=e.drawingContext.createLinearGradient(i,o,a,l);c.addColorStop(0,s),c.addColorStop(1,h),e.drawingContext.strokeStyle=c,e.drawingContext.globalAlpha=1,e.line(i,o,a,l),e.drawingContext.globalAlpha=1}}function S(e,t){const n=random(TAU),r=random(e,t);return createVector(r*cos(n),r*sin(n))}class R{constructor(e,t,n,r,i){this.wall=n,this.maxR=i;const o=t.length;this.nodes=[];for(let a=0;a<o;++a){const o=[],l=.25*t[a];for(let t=0;t<l;++t){const t=creM ateVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),l=S(.02*i,.05*i),s=random(10,25)*i;o.push(new M(t,l,s,e[a],r))}this.nodes.push(o)}const a=A(e);a.unshift(e[0]),a.push(e[e.length-1]),this.lines=[];for(let e=0;e<=o;++e){const r=[],l=(0==e?1:t[e-1])*(e==o?1:t[e])*1.5;for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),o=random(5*i,10*i),l=random(TAU),s=S(.02*i,.05*i),h=random(2e-4,.001);r.push(new E(t,o,l,s,h,a[e],a[e+1]))}this.lines.push(r)}}reflectNode(e){const{xLM eft:t,yTop:n,xRight:r,yBottom:i}=this.wall,{p:o,v:a}=e,l=e.getRadius();(o.x-l<t&&a.x<0||o.x+l>r&&a.x>0)&&(a.x=-a.x),(o.y-l<n&&a.y<0||o.y+l>i&&a.y>0)&&(a.y=-a.y)}reflectLine(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,[o,a]=e.getEndpoints(),l=e.v;(min(o.x,a.x)<t&&l.x<0||max(o.x,a.x)>r&&l.x>0)&&(l.x=-l.x),(min(o.y,a.y)<n&&l.y<0||max(o.y,a.y)>i&&l.y>0)&&(l.y=-l.y)}update(){for(const e of this.lines)for(const t of e)t.update(),this.reflectLine(t);for(const e of this.nodes)for(const t of e)t.update(),this.reflM ectNode(t)}draw(e,t,n,r,i){const o=i/this.maxR;for(const t of this.lines){const n=t.length*r;for(let r=0;r<n;++r)t[r].draw(e,o)}for(const i of this.nodes){const a=i.length*r;for(let r=0;r<a;++r)i[r].draw(e,t,n,o)}}}function I(e,t){re(e),e.fill(0),e.rect(0,0,500,500),ie(e),e.noStroke(),e.fill(dr(cr("#000000"),.5)),e.push(),e.translate(250,250),e.scale(t),e.translate(-250,-250),e.beginShape(),e.vertex(235.2,24.9),e.bezierVertex(215,24.6,185,11.4,164.8,11),e.bezierVertex(147.2,10.7,129.3,10.4,112.2,14.7),e.bezierVerteM x(95.1,19,78.5,28.5,69.6,43.8),e.bezierVertex(57.699,64.199,61.599,90.199,70.199,112.2),e.bezierVertex(78.799,134.2,91.6,154.6,97.199,177.5),e.bezierVertex(102.499,199.2,100.899,222.5,92.799,243.2),e.bezierVertex(83,268,64.6,288.3,48.9,310),e.bezierVertex(33.2,331.7,24.5,337.5,26.599,364.1),e.bezierVertex(28.2,384.1,61.399,404.2,75.7,418.3),e.bezierVertex(90,432.4,73.7,488.2,91.9,496.7),e.bezierVertex(124.2,511.6,159,472.5,194.3,468.1),e.bezierVertex(211.6,465.9,267.4,501.5,283.9,495.9),e.bezierVertex(340.7,476.7,2M 98.599,428.9,355.4,409.7),e.bezierVertex(370.799,404.5,454.5,407.6,464.4,394.8),e.bezierVertex(478.599,376.3,474.7,349.3,464.299,328.4),e.bezierVertex(453.9,307.5,438.099,289.5,428.699,268.2),e.bezierVertex(412,230,419,182.6,446.1,150.9),e.bezierVertex(449.7,146.7,453.6,142.7,455.8,137.6),e.bezierVertex(459.4,129.299,457.5,119.6,454.8,111),e.bezierVertex(443.2,73.4,417.3,40.4,383.6,20.299),e.bezierVertex(358.1,5,343.2,-.4,313.5,0),e.bezierVertex(287.5,.4,261.6,25.4,235.2,24.9),e.endShape(),e.pop()}function C(e,t,n,M r,i,o){let a,l,s;re(t),t.fill(0),t.rect(0,0,500,500),ie(t),t.noStroke(),t.fill(dr(n,.5)),1==i?(l=0,s=25,a=map(o,0,25,500,0)):a=0,t.rect(0,a,500,500),e.noStroke(),e.fill(r),e.rect(0,0,500,500),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.M 1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVerM tex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezieM rVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),e.fill(n),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(43M 3.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,M 313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.M 7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezM ierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),re(e),e.fill(r),e.beginShape(),e.vertex(184.3,473.2),e.bezierVertex(164,473.2,144.7,462.099,134,444.3),e.bezierVertex(131.7,440.5,129.1,438.5,125,437.1),e.bezierVertex(97.3,428.1,80.5,400.6,85.2,371.8),e.bezierVertex(86.3,365.1,85.8,364.1,79.9,361.2),e.bezierVertex(57.2,349.8,46.2,323.3,54.3,299.7),e.bezierVeM rtex(54.7,298.599,55.1,297.7,55.5,296.9),e.bezierVertex(55.6,296.599,55.8,296.4,55.9,296.099),e.vertex(57.9,291.499),e.vertex(62.5,293.599),e.bezierVertex(64.9,294.7,67.3,295.799,69.5,296.9),e.bezierVertex(74.5,299.299,79.1,301.599,83.9,303.099),e.bezierVertex(89.8,304.9,96.5,305.499,102.7,305.9),e.bezierVertex(102.8,305.9,102.9,305.9,103,305.9),e.bezierVertex(106.6,305.9,108.9,302.799,109,299.799),e.bezierVertex(109.1,296.199,106.6,293.4,102.7,292.799),e.bezierVertex(101.3,292.599,99.9,292.4,98.4,292.299),e.bezierM Vertex(94.3,291.799,90.1,291.299,86,289.9),e.bezierVertex(68.9,284,56.5,270.2,52.7,252.799),e.bezierVertex(48.9,235.499,54.5,217.7,67.6,205.299),e.bezierVertex(71.9,201.299,72.7,198.1,70.8,192.399),e.bezierVertex(64.2,172.2,68.8,153.99,84.2,139.599),e.bezierVertex(94.2,130.199,105.5,125.399,117.8,125.399),e.bezierVertex(124.3,125.399,131.1,126.799,137.8,129.599),e.bezierVertex(157,137.399,167.9,152.799,169.4,173.99),e.vertex(169.4,174.399),e.bezierVertex(169.5,175.899,169.6,177.2,169.9,178.299),e.bezierVertex(170.7M ,181.2,173.2,183.2,176.1,183.2),e.bezierVertex(176.299,183.2,176.5,183.2,176.7,183.2),e.bezierVertex(180.1,182.899,182.6,180.299,182.7,177),e.bezierVertex(183.1,162,178.299,148.2,168.399,136.1),e.bezierVertex(158.2,123.5,144.899,115.8,128.799,113.199),e.bezierVertex(123.499,112.299,120.399,109.799,118.899,104.99),e.bezierVertex(113.899,89.699,120.699,72.299,134.899,64.499),e.bezierVertex(139.99,61.699,145.799,60.199,151.7,60.199),e.bezierVertex(162.2,60.199,171.899,64.799,178.1,72.699),e.bezierVertex(179.6,74.6,180M .799,76.6,181.9,78.499),e.vertex(182.2,79.099),e.bezierVertex(183.2,80.699,185.2,83.299,188.4,83.299),e.bezierVertex(189.5,83.299,190.6,82.99,191.7,82.399),e.bezierVertex(195.1,80.599,196,76.99,194,72.799),e.bezierVertex(190.1,64.799,184.1,58.499,175.6,53.299),e.bezierVertex(174.6,52.699,173.7,52.099,172.5,51.499),e.vertex(170.5,50.299),e.vertex(163,45.899),e.vertex(170.5,41.599),e.bezierVertex(182,34.99,193.1,30.799,204.4,28.599),e.bezierVertex(208.6,27.799,212.9,27.399,217.2,27.399),e.bezierVertex(217.6,27.399,21M 7.9,27.399,218.3,27.399),e.bezierVertex(231.4,27.599,242.7,38.199,243,50.599),e.bezierVertex(243.4,64.899,243.3,78.99,243.2,93.799),e.bezierVertex(243.2,99.799,243.1,105.899,243.1,112.099),e.vertex(243.1,119.199),e.vertex(236.4,116.799),e.bezierVertex(235.7,116.499,235,116.299,234.4,115.99),e.bezierVertex(233.4,115.599,232.6,115.299,232,115.199),e.bezierVertex(230.6,114.899,229.2,114.599,227.8,114.299),e.bezierVertex(223.8,113.499,220.1,112.699,216.4,112.499),e.vertex(216.2,112.499),e.bezierVertex(212.5,112.499,210M .7,115.599,210.6,118.599),e.bezierVertex(210.4,122.399,212.7,125.099,216.4,125.399),e.bezierVertex(230.1,126.399,238.9,133.099,242.3,145.199),e.bezierVertex(243.2,148.399,243.2,151.599,243.2,154.499),e.vertex(243.2,155.099),e.bezierVertex(243.2,254.199,243.2,330,243.2,400.599),e.bezierVertex(243.2,401.99,243.2,403.4,243.2,404.9),e.bezierVertex(243.3,411.099,243.3,417.599,242.3,423.9),e.bezierVertex(238.1,449.2,219.6,467.799,194,472.5),e.bezierVertex(190.9,472.9,187.6,473.2,184.3,473.2),e.endShape(),e.beginShape(),eM .vertex(315.8,473.1),e.bezierVertex(309.3,473.1,302.8,472,296.5,469.9),e.bezierVertex(270.4,461,253.8,434.9,257.1,407.9),e.bezierVertex(260,384,273.8,366.8,297,358.3),e.bezierVertex(297.7,358.1,298.3,357.8,299,357.6),e.bezierVertex(299.8,357.3,300.6,357.1,301.2,356.8),e.bezierVertex(304.3,355.4,306,351.8,304.9,348.7),e.bezierVertex(304,345.9,301.7,344.2,299,344.2),e.bezierVertex(298.6,344.2,298.1,344.2,297.6,344.3),e.bezierVertex(288.1,346.3,279,350.9,269.7,358.3),e.bezierVertex(268.9,358.9,268.1,359.6,267.2,360.4)M ,e.vertex(265.5,361.8),e.vertex(258.5,367.6),e.vertex(257.4,358.6),e.bezierVertex(257.3,358,257.3,357.5,257.2,357.1),e.bezierVertex(257,356,256.9,354.9,256.9,353.7),e.bezierVertex(256.9,334.8,256.9,316,256.9,297.1),e.bezierVertex(256.9,260.3,256.9,222.3,256.8,185),e.bezierVertex(256.8,170.7,268.3,158.8,282.5,158.4),e.bezierVertex(284.8,158.3,286.7,157.6,287.9,156.2),e.bezierVertex(289.099,154.9,289.599,153.2,289.5,151.3),e.bezierVertex(289.3,147.5,286.7,145.1,282.7,145.1),e.bezierVertex(282.5,145.1,282.2,145.1,282,M 145.1),e.bezierVertex(278.8,145.3,275.5,146.1,272,146.9),e.bezierVertex(270.9,147.2,269.8,147.4,268.6,147.7),e.bezierVertex(267.9,147.9,267,148.2,265.8,148.7),e.bezierVertex(265.1,149,264.4,149.3,263.5,149.6),e.vertex(256.8,152),e.vertex(256.8,114.6),e.bezierVertex(256.8,95,256.8,75.4,256.8,55.9),e.bezierVertex(256.8,38,267.2,27.3,284.6,27.3),e.bezierVertex(285.3,27.3,285.9,27.3,286.6,27.3),e.bezierVertex(299,27.9,318.7,34.5,329.6,41.9),e.vertex(336.1,46.3),e.vertex(324.4,53.3),e.bezierVertex(316.2,58.2,310.2,64.6,M 306,72.9),e.bezierVertex(304.2,76.4,305.1,78.5,306.1,80),e.bezierVertex(307.4,81.9,309.4,83,311.6,83),e.bezierVertex(313.7,83,315.7,81.9,317.1,80.1),e.bezierVertex(317.4,79.7,317.8,79,318.1,78.4),e.bezierVertex(318.4,77.9,318.7,77.3,319,76.8),e.bezierVertex(325.3,66.2,336.3,59.9,348.5,59.9),e.bezierVertex(353.2,59.9,357.8,60.8,362.1,62.7),e.bezierVertex(377.6,69.3,386,86.7,381.7,103.2),e.bezierVertex(380.7,107.1,378.5,111.8,371.1,113.1),e.bezierVertex(342.7,118.1,322.2,139.1,317.8,167.8),e.bezierVertex(317.4,170.3,M 317.3,173.2,317.4,176.5),e.bezierVertex(317.5,180,320.1,182.8,323.5,183),e.bezierVertex(323.6,183,323.8,183,323.9,183),e.bezierVertex(327.1,183,329.8,180.6,330.3,177.2),e.bezierVertex(330.6,175.7,330.7,174,330.9,172.3),e.bezierVertex(331.1,169.8,331.4,167.3,332,164.7),e.bezierVertex(337.3,141.9,357.7,125.4,380.7,125.4),e.bezierVertex(382.5,125.4,384.3,125.5,386.1,125.7),e.bezierVertex(412.8,128.9,432.6,150.9,432,176.9),e.bezierVertex(431.9,182.3,430.9,187.7,429.1,192.7),e.bezierVertex(427.2,197.9,428,201,432.3,205)M ,e.bezierVertex(446.8,218.7,451.8,236,446.6,255),e.bezierVertex(441.4,274,428.3,286.5,408.7,291.3),e.bezierVertex(406.1,291.9,403.6,292.1,401.1,292.3),e.bezierVertex(400,292.4,398.9,292.5,397.9,292.6),e.bezierVertex(393.6,293.1,390.9,295.7,391,299.5),e.bezierVertex(391.1,303.4,394,305.8,398.5,305.8),e.bezierVertex(409.9,305.8,420.8,302.6,431.1,296.4),e.bezierVertex(431.8,296,432.5,295.5,433.2,295.1),e.bezierVertex(433.8,294.7,434.5,294.3,435.2,293.9),e.bezierVertex(436,293.4,436.6,293.2,437.2,293.1),e.bezierVertex(M 437.4,293,437.7,292.9,438.1,292.8),e.vertex(442.5,291.4),e.vertex(444.2,295.7),e.bezierVertex(450.9,312.4,449.5,328.4,440,343.4),e.bezierVertex(435.3,350.8,428.7,356.7,420.2,361.1),e.bezierVertex(414.3,364.1,413.7,365.2,414.8,371.7),e.bezierVertex(419.5,400.2,403,427.6,375.6,436.9),e.bezierVertex(371,438.5,368.3,440.7,365.8,444.7),e.bezierVertex(355.2,462.5,336.4,473.1,315.8,473.1),e.bezierVertex(315.8,473.1,315.8,473.1,315.8,473.1),e.endShape(),ie(e),e.fill(n),e.beginShape(),e.vertex(120.2,279.9),e.bezierVertex(11M 7.9,279.9,112.4,279.299,112.2,273.599),e.bezierVertex(112,267.7,117.4,266.7,119.7,266.599),e.bezierVertex(133.1,265.799,143.1,259.499,149.3,247.899),e.bezierVertex(149.6,247.299,150.1,246.399,150.3,245.399),e.bezierVertex(150.6,244.299,150.5,243.299,150.5,242.7),e.bezierVertex(150.5,242.6,150.5,242.5,150.5,242.299),e.vertex(150.3,238.799),e.vertex(141.1,235.99),e.bezierVertex(114.6,227.799,95.6,202.499,95.9,175.799),e.bezierVertex(95.9,173.99,96.4,168.199,102.2,168.199),e.bezierVertex(102.6,168.199,103,168.199,103.M 4,168.299),e.bezierVertex(104.8,168.499,108.2,168.899,109.2,175.599),e.bezierVertex(109.3,176.599,109.5,177.599,109.6,178.499),e.bezierVertex(110.4,184.199,111.3,189.99,113.7,195.499),e.bezierVertex(121.9,213.99,139.5,225.499,159.7,225.499),e.bezierVertex(172.1,225.499,184.1,220.899,193.5,212.599),e.bezierVertex(194,212.199,194.4,211.799,194.8,211.399),e.bezierVertex(195.1,211.099,195.5,210.799,195.8,210.399),e.bezierVertex(197.4,208.99,199.2,208.2,200.9,208.2),e.bezierVertex(202.5,208.2,204,208.899,205.3,210.1),e.M bezierVertex(208,212.9,207.9,216.9,205,219.9),e.bezierVertex(196.5,228.6,186.3,234.3,174.7,236.8),e.bezierVertex(168.799,238.1,165.6,241,163.899,246.7),e.bezierVertex(158.3,265.9,139.9,279.7,120.2,279.9),e.vertex(120.2,279.9),e.endShape(),e.beginShape(),e.vertex(187.2,427.5),e.bezierVertex(183.799,427.5,181.299,425.3,180.799,422),e.bezierVertex(180.6,420.8,180.499,419.5,180.399,418.1),e.bezierVertex(180.299,417,180.2,415.8,180.099,414.7),e.bezierVertex(177.199,390.5,156.699,371.3,132.399,370.2),e.bezierVertex(131.9M 9,370.2,131.499,370.2,131.099,370.2),e.bezierVertex(130.699,370.2,130.299,370.2,129.799,370.2),e.bezierVertex(125.99,369.9,123.199,367.2,123.099,363.6),e.bezierVertex(122.99,360.2,125.799,357.3,129.599,356.9),e.bezierVertex(130.499,356.8,131.499,356.8,132.599,356.7),e.bezierVertex(133.199,356.7,133.799,356.7,134.399,356.6),e.vertex(138.299,356.4),e.vertex(139.1,352.6),e.bezierVertex(139.5,350.7,139.799,348.9,140.2,347),e.bezierVertex(140.899,343.4,141.5,340,142.399,336.8),e.bezierVertex(150.099,310.7,174.399,292,20M 1.399,291.3),e.vertex(201.599,291.3),e.bezierVertex(203.699,291.3,206.299,292,208.299,293.2),e.bezierVertex(210.499,294.5,210.699,297.5,209.99,299.8),e.bezierVertex(209.499,301.5,208.199,303.9,203.299,304.7),e.bezierVertex(202.199,304.9,200.99,305,199.799,305.2),e.bezierVertex(194.499,305.9,188.99,306.599,183.799,308.9),e.bezierVertex(165.499,316.799,155.199,331.299,152.99,352),e.bezierVertex(152.399,357.8,154.499,361.7,159.699,364.5),e.bezierVertex(178.199,374.4,189.399,390,193.099,410.9),e.bezierVertex(193.699,41M 4.299,193.899,418,193.599,422),e.bezierVertex(193.399,425.2,190.899,427.5,187.399,427.5),e.vertex(187.2,427.5),e.endShape(),e.beginShape(),e.vertex(364.3,281.1),e.bezierVertex(346.3,280.6,332.9,272.8,323.5,257),e.bezierVertex(321.6,253.9,320.4,250.2,319.2,246.7),e.bezierVertex(317.7,242.2,315,239.799,310.5,238.799),e.bezierVertex(298.5,236.299,288,230.7,279.4,222.1),e.bezierVertex(276.7,219.4,274.9,215.299,278,211.9),e.bezierVertex(279.4,210.3,281,209.6,282.6,209.6),e.bezierVertex(284.4,209.6,286.4,210.6,288.3,212.M 5),e.bezierVertex(297.8,221.8,310.4,226.9,323.9,226.9),e.bezierVertex(340.2,226.9,355.1,219.3,364.8,206.2),e.bezierVertex(371,197.8,374.2,188.5,374.5,178.5),e.vertex(374.5,177.9),e.bezierVertex(374.5,177,374.5,176.1,374.7,175.4),e.bezierVertex(375.3,171.8,377.9,169.5,381.3,169.5),e.bezierVertex(381.4,169.5,381.5,169.5,381.7,169.5),e.bezierVertex(385.4,169.7,388,172.4,388,176.1),e.bezierVertex(388.1,190.7,383.4,204,374.2,215.8),e.bezierVertex(365.8,226.5,354.7,233.9,341.2,237.9),e.bezierVertex(340,238.3,338.7,238.6,M 337.3,239.1),e.bezierVertex(335.9,239.6,335.1,240.4,334.7,240.9),e.bezierVertex(334.599,241,334.5,241.1,334.4,241.2),e.vertex(331.799,243.6),e.vertex(333.199,246.8),e.bezierVertex(338.199,258,346.799,264.9,358.699,267.3),e.bezierVertex(360.199,267.6,361.599,267.7,362.99,267.9),e.bezierVertex(363.599,268,364.299,268,364.899,268.1),e.bezierVertex(369.099,268.6,371.799,271.4,371.499,275),e.bezierVertex(371.199,278.6,368.299,281.2,364.399,281.2),e.vertex(364.3,281.1),e.endShape(),e.beginShape(),e.vertex(323.9,437),e.beM zierVertex(323.7,437,323.5,437,323.299,437),e.bezierVertex(319.599,436.7,317.299,434.1,317.4,430.2),e.bezierVertex(317.9,406.099,328.299,388,349.5,375),e.bezierVertex(350.7,374.2,352,373.5,353.4,372.8),e.bezierVertex(354.099,372.4,354.7,372.1,355.299,371.7),e.vertex(357.499,370.5),e.vertex(357.799,368),e.bezierVertex(360.4,346.6,345.199,323.7,323.9,317),e.bezierVertex(319.099,315.5,314.099,314.9,309.299,314.4),e.vertex(308.199,314.299),e.bezierVertex(305.99,314.099,300.799,312.9,300.899,307.299),e.bezierVertex(300.M 99,303.499,303.899,300.9,308.099,300.9),e.vertex(308.299,300.9),e.bezierVertex(327.099,301.299,343.099,308.7,355.699,322.9),e.bezierVertex(364.299,332.5,369.399,344.099,370.99,357.299),e.bezierVertex(371.099,358.4,371.299,359.4,371.499,360.499),e.bezierVertex(371.599,360.99,371.699,361.499,371.799,361.99),e.vertex(372.499,365.899),e.vertex(377.899,366.199),e.bezierVertex(378.799,366.299,379.699,366.299,380.599,366.399),e.bezierVertex(385.099,366.699,387.899,369.399,387.799,373.299),e.bezierVertex(387.699,377.099,38M 4.99,379.599,380.799,379.799),e.bezierVertex(369.799,380.199,359.99,383.299,351.899,389.299),e.bezierVertex(338.799,398.799,331.699,411.699,330.699,427.499),e.vertex(330.699,428.299),e.bezierVertex(330.599,429.199,330.599,430.099,330.499,430.799),e.bezierVertex(330,434.7,327.5,437,323.9,437),e.endShape()}function T(e){return e[0].map(((t,n)=>e.map((e=>e[n]))))}function A(e){return e.map((e=>Array.isArray(e)?A(e):e))}function D(e,t){return floor(random(e,t))}function k(e){let t=0;for(const n of e)t+=n[1];let n=randoM m(t),r=0;for(const t of e)if(r+=t[1],n<r)return t[0];return null}function L(e){for(let t=1;t<e.length;++t){let n=D(0,t),r=e[t];e[t]=e[n],e[n]=r}}function P(e){return null==e||""===e}function O(e){return new Promise((t=>setTimeout(t,e)))}function F(e,t,n){let r=0;for(let i=1;i<=1e3;++i)for(let o=1;o<=1e3;++o)if(e*o%(t*i)==0){let e=1*i/o;abs(e-n)<abs(r-n)&&(r=e)}return r}function N(){let e=60*(new Date).getTimezoneOffset()*1e3;return new Date(Date.now()-e).toISOString().slice(0,-1)}function B(e,t,n){let r;if(push(),tM extSize(e),textWidth(t)<=n)r=t;else for(let e=0;e<t.length;++e){const i=t.slice(0,e+1)+"...";if(textWidth(i)>n){r=i;break}}return pop(),r}function Y(e){var t=e%10,n=e%100;return 1==t&&11!=n?e+"st":2==t&&12!=n?e+"nd":3==t&&13!=n?e+"rd":e+"th"}class G{constructor(e,t,n){this.n=t,this.m=n,this.mat=[];let r=0;for(let t=0;t<this.n;++t){this.mat.push([]);for(let n=0;n<this.m;++n)this.mat[t].push(r<e.length?e[r]:0),r+=1}return this}copy(){return new G(this.mat.flat(),this.n,this.m)}}class H{static __linear=e=>e;static __rM elu=e=>Math.max(e,0);static __leaky_relu=e=>e>0?e:.2*e;static __sigmoid=e=>1/(1+Math.exp(-e));static __tanh=e=>Math.tanh(e);static __apply_unary_op(e,t){const n=e.copy();for(let e=0;e<n.n;++e)for(let r=0;r<n.m;++r)n.mat[e][r]=t(n.mat[e][r]);return n}static linear=e=>H.__apply_unary_op(e,H.__linear);static relu=e=>H.__apply_unary_op(e,H.__relu);static leaky_relu=e=>H.__apply_unary_op(e,H.__leaky_relu);static sigmoid=e=>H.__apply_unary_op(e,H.__sigmoid);static tanh=e=>H.__apply_unary_op(e,H.__tanh);static __add=(e,t)M =>e+t;static __mul=(e,t)=>e*t;static __apply_binary_op=(e,t,n)=>{"object"!=typeof t&&(t=new G([t],1,1));const r=e.copy();for(let e=0;e<r.n;++e)for(let i=0;i<r.m;++i)r.mat[e][i]=n(r.mat[e][i],t.mat[e%t.n][i%t.m]);return r};static mul=(e,t)=>H.__apply_binary_op(e,t,H.__mul);static add=(e,t)=>H.__apply_binary_op(e,t,H.__add);static matMul(e,t){const n=new G([],e.n,t.m);for(let r=0;r<n.n;++r)for(let i=0;i<n.m;++i)for(let o=0;o<e.m;++o)n.mat[r][i]+=e.mat[r][o]*t.mat[o][i];return n}static softmax(e){const t=H.__apply_unaM ry_op(e,(e=>Math.exp(e))),n=t.mat.flat().reduce(((e,t)=>e+t));for(let r=0;r<e.n;++r)for(let i=0;i<e.m;++i)t.mat[r][i]/=n;return t}}class ${constructor(e,t){this.scale=e,this.offset=t}forward(e){return H.add(H.mul(e,this.scale),this.offset)}}class X{constructor(){}forward(e){return e.map((e=>e.flat()))}}class W{constructor(e,t,n,r){this.out_dim=e,this.activation=t,this.w=n,this.b=r}forward(e){const t=H.add(H.matMul(e,this.w),this.b);return null==this.activation?t:this.activation(t)}}class U{constructor(e,t,n){this.pM reprocessLayers=e,this.hiddenLayers=t,this.outputLayer=n,this.totalNeurons=this.hiddenLayers.map((e=>e.out_dim)),this.currentOrders=[],this.currentIteration=null}updateNeurons(e,t){if(t!=this.currentIteration){this.currentOrders=[];for(let e=0;e<this.totalNeurons.length;++e){randomSeed(100*(t+1)+e);const n=[];for(let t=0;t<this.totalNeurons[e];++t)n.push(t);L(n),this.currentOrders.push(n)}this.currentIteration=t}const n=A(this.totalNeurons),r=n.reduce(((e,t)=>e+t))*(1-e);for(let e=0;e<r;++e){const t=n.map(((e,t)=>(M e-1)/this.totalNeurons[t]));n[t.map(((e,t)=>[e,t])).reduce(((e,t)=>t[0]>e[0]?t:e))[1]]-=Math.min(r-e,1)}this.neuronsLife=[];for(let e=0;e<n.length;++e){const t=this.currentOrders[e],r=Array(this.totalNeurons[e]).fill(0);for(let i=0;i<n[e];++i)r[t[i]]=Math.min(n[e]-i,1);this.neuronsLife.push(r)}}getTotalNeurons(){return A(this.totalNeurons)}getNeuronsLife(){return A(this.neuronsLife)}forward(e){for(const t of this.preprocessLayers)e=t.forward(e);for(const[t,n]of this.hiddenLayers.entries()){e=n.forward(e);const r=neM w G(this.neuronsLife[t],1,e.m);e=H.mul(e,r)}return e=this.outputLayer.forward(e),H.softmax(e)}}function q(e){switch(e){case"relu":return H.relu;case"sigmoid":return H.sigmoid;case"tanh":return H.tanh;case"leaky_relu":return H.leaky_relu;default:return H.linear}}function j(e,t){const n=[],r=[],i=Z(t);let o=null,a=0,l=[];for(const t of e.config.layers)if("InputLayer"==t.class_name)o=t.config.batch_input_shape.slice(1),l=o;else if("Rescaling"==t.class_name)n.push(new $(t.config.scale,t.config.offset));else if("FlattenM "==t.class_name)o=[o.reduce(((e,t)=>e*t))];else if("Dense"==t.class_name){const e=[t.config.units],n=o[0]*e[0],l=e[0],s=i.subarray(a,a+n);a+=n;const h=i.subarray(a,a+l);a+=l;const c=new G(s,o[0],e[0]),u=new G(h,1,e[0]),f=q(t.config.activation);r.push(new W(e[0],f,c,u)),o=e}const s=r.pop();return{model:new U(n,r,s),inputDim:l}}function Z(e){const t=window.atob(e),n=t.length/Float32Array.BYTES_PER_ELEMENT,r=new DataView(new ArrayBuffer(Float32Array.BYTES_PER_ELEMENT)),i=new Float32Array(n);let o=0;for(let e=0;e<n;e++M ){o=4*e;for(let e=0;e<4;++e)r.setUint8(e,t.charCodeAt(o+e));i[e]=r.getFloat32(0,!0)}return i}class K{constructor(e){this.elt=e,this._events={},this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight}position(){if(0===arguments.length)return{x:this.elt.offsetLeft,y:this.elt.offsetTop};var e="absolute";return"static"!==arguments[2]&&"fixed"!==arguments[2]&&"relative"!==arguments[2]&&"sticky"!==arguments[2]&&"initial"!==arguments[2]&&"inherit"!==arguments[2]||(e=arguments[2]),this.elt.style.position=e,this.eM lt.style.left=arguments[0]+"px",this.elt.style.top=arguments[1]+"px",this.x=arguments[0],this.y=arguments[1],this}show(){return this.elt.style.display="block",this}hide(){return this.elt.style.display="none",this}size(e,t){if(0===arguments.length)return{width:this.elt.offsetWidth,height:this.elt.offsetHeight};var n=e,r=t;if(n!==te||r!==te){if(n===te?n=t*this.width/this.height:r===te&&(r=e*this.height/this.width),this.elt instanceof HTMLCanvasElement){var i,o={},a=this.elt.getContext("2d");for(i in a)o[i]=a[i];for(iM in this.elt.setAttribute("width",n*this._pInst._pixelDensity),this.elt.setAttribute("height",r*this._pInst._pixelDensity),this.elt.style.width=n+"px",this.elt.style.height=r+"px",this._pInst.scale(this._pInst._pixelDensity,this._pInst._pixelDensity),o)this.elt.getContext("2d")[i]=o[i]}else this.elt.style.width=n+"px",this.elt.style.height=r+"px",this.elt.width=n,this.elt.height=r;this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight,this._pInst&&this._pInst._curElement&&this._pInst._curElement.elt===thM is.elt&&(this._pInst._setProperty("width",this.elt.offsetWidth),this._pInst._setProperty("height",this.elt.offsetHeight))}return this}style(e,t){if(t instanceof Color&&(t="rgba("+t.levels[0]+","+t.levels[1]+","+t.levels[2]+","+t.levels[3]/255+")"),void 0===t){if(-1===e.indexOf(":"))return window.getComputedStyle(this.elt).getPropertyValue(e);for(var n=e.split(";"),r=0;r<n.length;r++){var i=n[r].split(":");i[0]&&i[1]&&(this.elt.style[i[0].trim()]=i[1].trim())}}else if(this.elt.style[e]=t,"width"===e||"height"===e||"M left"===e||"top"===e){var o=window.getComputedStyle(this.elt).getPropertyValue(e).replace(/[^\d.]/g,"");this[e]=Math.round(parseFloat(o,10))}return this}value(){return arguments.length>0?(this.elt.value=arguments[0],this):"range"===this.elt.type?parseFloat(this.elt.value):this.elt.value}mouseClicked(e){return this._adjustListener("click",e,this),this}isFocused(){return document.activeElement===this.elt}_adjustListener(e,t,n){return!1===t?this._detachListener(e,n):this._attachListener(e,t,n),this}_attachListener(e,tM ,n){n._events[e]&&this._detachListener(e,n);var r=t.bind(n);n.elt.addEventListener(e,r,!1),n._events[e]=r}_detachListener(e,t){var n=t._events[e];t.elt.removeEventListener(e,n,!1),t._events[e]=null}}function J(e,t){var n=document.createElement("button");return n.innerHTML=e,t&&(n.value=t),ee(n)}function Q(e){var t=arguments.length>1&&void 0!==arguments[1]&&arguments[1],n=function(t){var n=!0,r=!1,i=void 0;try{for(var o,a=t.target.files[Symbol.iterator]();!(n=(o=a.next()).done);n=!0){var l=o.value;File._load(l,e)}}cM atch(e){r=!0,i=e}finally{try{n||null==a.return||a.return()}finally{if(r)throw i}}};if(window.File&&window.FileReader&&window.FileList&&window.Blob){var r=document.createElement("input");return r.setAttribute("type","file"),t&&r.setAttribute("multiple",!0),r.addEventListener("change",n,!1),ee(r)}}function ee(e){return document.body.appendChild(e),new K(e)}createImg=function(){var e,t=document.createElement("img"),n=arguments;return n.length>1&&"string"==typeof n[1]&&(t.alt=n[1]),n.length>2&&"string"==typeof n[2]&&(tM .crossOrigin=n[2]),t.src=n[0],e=ee(t,this),t.addEventListener("load",(function(){e.width=t.offsetWidth||t.width,e.height=t.offsetHeight||t.height;var r=n[n.length-1];"function"==typeof r&&r(e)})),e},createInput=function(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:"",t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:"text",n=document.createElement("input");return n.setAttribute("value",e),n.setAttribute("type",t),ee(n,this)};const te="auto";function ne(e){re(e);const t=e._rectMode;e.rectModM e(CORNER),e.rect(0,0,e.width,e.height),e.rectMode(t),ie(e)}function re(e){e.push(),e.fill(255,255,255,255),e.blendMode(REMOVE)}function ie(e){e.blendMode(BLEND),e.pop()}File=function(e,t){this.file=e,this._pInst=t;var n=e.type.split("/");this.type=n[0],this.subtype=n[1],this.name=e.name,this.size=e.size,this.data=void 0},File._createLoader=function(e,t){var n=new FileReader;return n.onload=function(n){var r=new File(e);if("application/json"===r.file.type)r.data=JSON.parse(n.target.result);else if("text/xml"===r.filM e.type){var i=(new DOMParser).parseFromString(n.target.result,"text/xml");r.data=new XML(i.documentElement)}else r.data=n.target.result;t(r)},n},File._load=function(e,t){if(/^text\//.test(e.type)||"application/json"===e.type)File._createLoader(e,t).readAsText(e);else if(/^(video|audio)\//.test(e.type)){var n=new File(e);n.data=URL.createObjectURL(e),t(n)}else File._createLoader(e,t).readAsDataURL(e)},XML=function(e){if(e)this.DOM=e;else{var t=document.implementation.createDocument(null,"doc");this.DOM=t.createElemeM nt("root")}},document.addEventListener("DOMContentLoaded",(function(){addEventListener("mousemove",(e=>{window.mouseX=e.pageX,window.mouseY=e.pageY}))})),new e("global");const oe="354";let ae,le,se,he,ce,ue,fe,de,xe,ge,pe,me,be,ye,we,ve,ze,Ve,_e,Me,Ee,Se,Re,Ie,Ce,Te,Ae,De,ke,Le,Pe,Oe,Fe,Ne,Be,Ye,Ge,He,$e,Xe,We,Ue,qe,je,Ze,Ke,Je,Qe,et,tt,nt,rt,it,ot,at,lt,st,ht,ct,ut,ft,dt,xt,gt,pt,mt,bt,yt,wt,vt,zt,Vt,_t,Mt,Et,St,Rt,It,Ct,Tt,At=!1,Dt=!1,kt=!0,Lt=!1,Pt=!1;const Ot=[" ","Growing","Stable","Decaying","Dead","Rebirth"]M ;let Ft,Nt,Bt,Yt,Gt,Ht,$t,Xt,Wt,Ut,qt,jt,Zt,Kt,Jt,Qt,en,tn,nn,rn,on,an,ln,sn,hn=0,cn=0,un=0,fn=!1,dn=!0,xn=!0,gn=null,pn=null,mn=null,bn=!1,yn=!1,wn=null,vn=null,zn=!1;async function setup(){let e=windowWidth,t=windowHeight;createCanvas(e,t),et=createGraphics(e,t),Xe=createGraphics(e,t),$e=createGraphics(e,t),We=createGraphics(e,t),Ue=createGraphics(e,t),qe=createGraphics(e,t),Qe=createGraphics(e,t),je=createGraphics(e,t),Ze=createGraphics(e,t),Ke=createGraphics(e,t),Je=createGraphics(e,t),tt=createGraphics(500,500M ),nt=createGraphics(500,500),rt=createGraphics(500,500),_n(),Mn(),Sn(),await En(),Gn(),Rn(),bn=!0}function _n(){Et=parseInt(oe),randomSeed(Et),noiseSeed(Et)}function Mn(){Wt=Ir(p.training_traits),Cr(Wt)}async function En(){let e;Jt=r(),Qt=o(),[Xt,e]=await Promise.all([s(Jt),h(Qt)]),Ut=new V(Wt.visual,e.layers_config,e.weight_b64),Ut.updateAge(new Date),_n(),Wt.training=e.training_traits,Ht=e.model_name,$t=e.classes_name}function Sn(){le=min(width,height)/1024,ut=Rr.findIndex((e=>e[0]===Wt.visual.colorPalette)),ft=[M ["#ffffff","#231f20","#231f20"],["#231f20","#ffffff","#ffffff"],["#104da8","#ffffff","#ffffff"],["#722F1F","#FCE1B2","#FCE1B2"],["#e88120","#f9f2e5","#f9f2e5"],["#f6b941","#2E2E2E","#2E2E2E"],["#45daaa","#012221","#012221"],["#F1F1F1","#328DFE","#328DFE"],["#111822","#D3EB8D","#D3EB8D"],["#713FF9","#D6D5E6","#D6D5E6"],["#FBDA9D","#795106","#795106"],["#8f5b62","#ead0d0","#ead0d0"],["#eae4cb","#508cac","#508cac"],["#ffc6cc","#cc313d","#cc313d"],["#60A900","#E0FE00","#E0FE00"],["#507DBE","#D0D1D3","#D0D1D3"],["#30584M 8","#E8F2EE","#E8F2EE"],["#2a2634","#5b6988","#cb78a2","#5b6988"],["#590e29","#fd5e53","#fd5e53","#ffe373"],["#0a141d","#57d4e4","#328195","#2A9ECF","#0ab6a8","#57d4e4"],["#3a2d28","#d5c2ac","#df6338","#3d9895","#d5c2ac"],["#030706","#77c4d9","#77c4d9","#77c4d9","#ffffff","#ffffff","#e72020","#e72020"],["#3a4664","#92f5ff","#f9ff94","#eaa0a2","#55dde0"],["#fbfaff","#f04bb1","#f04bb1","#fac373","#82cef0","#8b31ce"],["#000000","#ffffff","#ff0002","#f26522","#fdff00","#00ff03","#01fffe","#0000ff","#ff00ff"]];for(let eM =0;e<ft.length;++e)for(let t=0;t<ft[e].length;++t)ft[e][t]=cr(ft[e][t]);pt=[],ct=ft[ut][0],st=ft[ut][1]}function Rn(){gn=document.querySelector("#upload"),pn=document.querySelector("#inputUpload"),gn.addEventListener("dblclick",(()=>{if(!Lt&&!yn)if(In(Ie)&&cn==Ve-1)pn.click();else{if(4!=Pe&&5!=Pe&&(In(Ie)||cn!=Ve-1))return;fn=!0,dn=!0,Bt=0,un=0}})),pn.addEventListener("click",(()=>{pn.value=null,gn.style.display="block"})),pn.addEventListener("change",(()=>{const[e]=pn.files;e?(se=null,gn.style.display="none",Tn(URM L.createObjectURL(e)),mn=e):gn.style.display="block"}))}function In(e){for(let t=0;t<e.length;++t){let n=0;for(let r=0;r<e[t].length;++r)e[t][r]>0&&++n;if(0==n)return!1}return!0}function Cn(){null!=se&&(un=0,Pt=!0,he=0,ue=0,drewLineAnim=!0,ce=(ae/2+we/2)/le,loadImage(se.elt.src,(e=>{const[t,n,r]=Gt,i=createGraphics(t,n);i.image(e,0,0,t,n),i.loadPixels();const o=i.pixels.filter(((e,t)=>t%4!=3)),a=Ut.classifyImage(o);Zt=T([a,$t.map((e=>e.toUpperCase()))]).sort(((e,t)=>e[0]>t[0]?-1:1))})))}function Tn(e){se=createImg(M e,""),se.hide(),Cn()}function An(){zn||(ce+=(width-ae-we)/tn/le),re(Xe),Xe.rect(ce*le,0,width,height),ie(Xe),un>=ge&&1==kt&&(kt=!1,un-=ge),kt&&(re($e),$e.strokeWeight(2*Fe),Jn(he,ze,ct,ct,$e),ie($e)),un>=ge&&0==kt&&(kt=!0,un-=ge,he+=1,he==en&&(++ue,he=0,ce=(ae/2+we/2)/le,1==ue&&(Pt=!1,Dn(),ye=millis())))}function Dn(){At=!0,pe=!1,me=!1,tryButton=br("Try Again",width/2-225*le,height/2+265*le,290*le,40*le,kn),closeResultButton=br("Close",width/2+75*le,height/2+265*le,150*le,40*le,Ln)}function kn(){At=!1,tryButton.hidM e(),closeResultButton.hide(),pn.click()}function Ln(){Yt=!0,At=!1,Gn(),tryButton.hide(),closeResultButton.hide(),gn.style.display="block",se=null}function keyTyped(){bn&&!1===yn&&!1===yr()&&("i"!==key&&"I"!==key||(Dt=!Dt),"b"!==key&&"B"!==key||(xn=!xn),"s"!==key&&"S"!==key||!1!==Lt||saveCanvasAtCurrentTime(),"k"!==key&&"K"!==key||!1!==Lt||save4KCanvasAtCurrentTime(),"u"!==key&&"U"!==key||!1!==Lt||!1!==At||!1!==fn||!1!==Pt||On())}function On(){Lt=!0,wn=null,vn=null,submitButton=br("Submit",width/2-155*le,height/2+11M 5*le,150*le,40*le,Fn),closeSettingButton=br("Close",width/2+5*le,height/2+115*le,150*le,40*le,Yn),vt=createInput(),vt.position(width/2-252.5*le,height/2-40*le),vt.size(500*le,25*le),vt.style("font-size","15px"),vt.value(Jt||""),zt=createInput(),zt.position(width/2-252.2*le,height/2+35*le),zt.size(500*le,25*le),zt.style("font-size","15px"),zt.value(Qt||"")}function Fn(){Vt=vt.value(),_t=zt.value(),submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide(),Lt=!1,yn=!0,Nn()}async function Nn(){[wn,vn,_]=await PM romise.all([c(Vt),u(_t),O(1e3)]),yn=!1,wn&&vn?(n(Vt),i(_t),window.location.reload()):(Lt=!0,submitButton.show(),closeSettingButton.show(),vt.show(),zt.show())}function Bn(){Je.textFont("Trebuchet MS"),Je.noStroke(),pr(Je,600*le,200*le),Je.strokeWeight(1*le),Je.stroke(xt),Je.fill(xt),Je.textSize(50*le),Je.text("update()",width/2,height/2+2.5*le)}function Yn(){wn=null,vn=null,Lt=!1,submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide()}function Gn(){_n(),nn=Date.now(),pe=!1,me=!1,St=Wt.training.structure_gM en,Rt=Wt.visual.birthYear,It=Wt.visual.lifeCycle,Ct=Wt.training.epoch_num,Tt=Wt.training.activation_func,Ft=Mr.findIndex((e=>e[0]==Wt.visual.hardwareAcceleration))+1,1==Ft?(Nt=30,fe=40):2==Ft?(Nt=15,fe=20):(Nt=2,fe=10);const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=PM e%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),ae=100*le,ht=50*le,Oe=Sr.findIndex((e=>e[0]==Wt.visual.nodeShape))+1,dt=Er.findIndex((e=>e[0]==Wt.visual.nodeFill))+1,lt=_r.findIndex((e=>e[0]==Wt.visual.pattern))+1,de=Math.tanh(Math.log10(Xt.avgfeerate)),de=map(de,0,1,.2,.8),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNoM des;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=M 0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+M 1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,at=.7,pt=[],xt=ft[ut][2],gt=ft[ut][ft[ut].length-1];for(let e=3;e<ft[ut].length-1;e++)pt.push(ft[ut][e]);mt=sr(xt,gt,pt,width),bt=[],wt=[],yt=width/(Ve-1);for(let e=0;e<Ve;e++)bt.push(hr(mt,yt*e/width)),wt.push(hr(mt,yt*e/width));wt.unshift(bt[0]),wt.push(bt[bt.length-1]),hn=0,cn=0,un=0,Yt=!0;const n={xLeft:ae/8,xRight:width-ae/8,yTop:ae/8,yBottom:height-ae/8},r=Ce.map((e=>e.length));jt=new R(bt,r,n,Oe,le)}function Hn(e,t)M {let n=Ce[e].length;return[e*we+we/2+ae/2,height/2-(n-1)/2*ve+t*ve]}function $n(e,t){le=min(e,t)/1024,ae=100*le,ht=50*le,we=(e-ae)/Ve,ve=(t-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}xe=floor(De.length*de),Le=[],ke=[],ge=floor(map(de,.2,.8,15,2));for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,M Ne=map(Be,1/30,1,1,10)*le,mt=sr(xt,gt,pt,e),bt=[],wt=[],yt=e/(Ve-1);for(let t=0;t<Ve;t++)bt.push(hr(mt,yt*t/e)),wt.push(hr(mt,yt*t/e));wt.unshift(bt[0]),wt.push(bt[bt.length-1])}function Xn(){const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimeM stamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let tM =0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<tM ;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le}function Wn(){jt.update();const e=4==Pe?0:Kt;jt.draw(Qe,ct,dt,e,le)}function Un(){if(!bn)return ar(),void et.image(je,0,0);if(4==Pe||5==Pe)return Wn(),void et.iM mage(Qe,0,0);un>=Nt&&hn<Ve&&(hn++,un=0);for(let e=0;e<hn;e++)1==dt?it=ot=bt[e]:(it=ct,ot=bt[e]),Kn(e,it,ot,$e);un>=Nt&&cn<Ve-1&&(cn++,un=0);for(let e=0;e<cn;e++)Zn(e)}function qn(){et.background(ct),Ue.background(255),Ue.rectMode(CENTER),ne(Ue),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),Ue.stroke(st),Ue.strokeWeight(8*le),Ue.fill(ct),Qe.background(255),Qe.rectMode(CENTER),ne(Qe),Qe.strokeWeight(le),qe.background(255),qe.rectMode(CENTER),ne(qe),qe.textAlign(LEFT),$e.background(255),$e.rectMode(CENTER),ne($e),Xe.M background(255),ne(Xe),Xe.strokeWeight(Ne),We.background(255),We.rectMode(CENTER),ne(We),We.fill(st),We.stroke(st),We.strokeWeight(.1*le),er(lt),We.noStroke(),xn&&(We.rect(ae/16,height/2,ae/8,height),We.rect(width-ae/16,height/2,ae/8,height),We.rect(width/2,ae/16,width,ae/8),We.rect(width/2,height-ae/16,width,ae/8)),Ze.background(255),Ze.rectMode(CENTER),ne(Ze),Ze.textAlign(CENTER,CENTER),Ze.textStyle(BOLD),Ze.stroke(st),Ze.strokeWeight(8*le),Ze.fill(ct),je.background(255),je.rectMode(CENTER),ne(je),je.textAlign(CEM NTER,CENTER),je.textStyle(BOLD),Ke.background(255),Ke.rectMode(CENTER),ne(Ke),Ke.textAlign(CENTER,CENTER),Ke.textStyle(BOLD),Ke.stroke(st),Ke.strokeWeight(8*le),Ke.fill(ct),Je.background(255),Je.rectMode(CENTER),ne(Je),Je.textAlign(CENTER,CENTER),Je.textStyle(BOLD),Je.stroke(st),Je.strokeWeight(8*le),Je.fill(ct),Un(),et.image(We,0,0),Pt&&An(),et.image(Xe,0,0),et.image($e,0,0),At&&(tr(),et.image(Ue,0,0)),fn&&(lr(),et.image(Ze,0,0)),Lt&&(or(),et.image(Ke,0,0)),Dt&&(ir(),et.image(qe,0,0)),yn&&(Bn(),et.image(Je,0,0))}fM unction draw(){const e=Date.now();bn&&(Ut.updateAge(new Date(e)),Xn()),qn(),image(et,0,0),zn||un++}function Zn(e){let t,n=Ce[e].length,r=Ce[e+1].length;for(let i=0;i<n;i++){const[n,o]=Hn(e,i);for(let a=0;a<r;a++){const[r,l]=Hn(e+1,a);t=map(min(Ce[e][i],Ce[e+1][a]),0,1,0,.5),ur(n,o,r,l,bt[e],bt[e+1],Xe,t)}}}function Kn(e,t,n,r){let i,o,a,l=Ce[e].length;for(let s=0;s<l;s++){const[l,h]=Hn(e,s);i=Ce[e][s],a=map(Be,1/30,1,3,10),o=map(Ce[e][s],0,1,2*a,0)*le,o<1.5*le&&(o=0),Qn(l,h,ze,Oe,t,n,o,i,r)}}function Jn(e,t,n,r,i){M for(let o=0;o<Le[e].length;o++)Qn(Le[e][o][0],Le[e][o][1],t,Oe,n,r,0,1,i)}function Qn(e,t,n,r,i,o,a,l,s){s.stroke(dr(o,map(l,0,1,.25,1))),s.fill(dr(i,map(l,0,1,.15,1))),s.strokeWeight(Fe),fr([a],s),3==dt&&s.fill(dr(i,0)),1==r?s.ellipse(e,t,n):2==r?s.rect(e,t,7*n/8,7*n/8):3==r&&(s.beginShape(),s.vertex(e-4*n/7,t),s.vertex(e,t-4*n/7),s.vertex(e+4*n/7,t),s.vertex(e,t+4*n/7),s.endShape(CLOSE))}function er(e){if(1==e);else if(2==e){We.strokeWeight(1*le);for(let e=ht/4;e<width+ht/4;e+=ht)for(let t=ht/4;t<height+ht/4;t+=hM t)We.point(e,t)}else if(3==e){ht=25*le;for(let e=ht/2;e<height+ht/2;e+=ht)We.line(0,e,width,e);for(let e=ht/2;e<width+ht/2;e+=ht)We.line(e,0,e,height)}}function tr(){Ue.textFont("Trebuchet MS"),Ue.textAlign(LEFT,CENTER),Ue.noStroke(),pr(Ue,800*le,500*le),Ue.noStroke(),Ue.fill(dr(st,.75)),Ue.rect(width/2,height/2-100*le,800*le,300*le,25*le,25*le,0,0),Ue.fill(st),Ue.rect(width/2-250*le,height/2-100*le,225*le,225*le),Ue.image(se.elt,width/2-357.5*le,height/2-207.5*le,215*le,215*le);let e=100*Zt[0][0];Ue.fill(ct),Ue.teM xtSize(25*le),Ue.textStyle(NORMAL),1==me&&(e>=0&&e<20?Ue.text("I have a feeling this image belongs to",width/2-100*le,height/2-170*le):e>=20&&e<40?Ue.text("I have a hunch this image belongs to",width/2-100*le,height/2-170*le):e>=40&&e<60?Ue.text("I think this image belongs to",width/2-100*le,height/2-170*le):e>=60&&e<80?Ue.text("I'm almost certain this image belongs to",width/2-100*le,height/2-170*le):Ue.text("I'm positive this image belongs to",width/2-100*le,height/2-170*le));let t=e.toFixed(2);"100.00"==t&&(t="1M 00"),1==me&&Ue.text("I'm "+t+"% confident that I'm right!",width/2-100*le,height/2-25*le),example=Zt.map((e=>e[1])),be=Ue.textWidth('"FIDENZAAAA"'),defaultPhrase=Ue.textWidth('"PERPENDICULAR INHABITATION"'),Ue.textStyle(BOLD);const n=me?example[0]:random(example);if(1===n.split(" ").length){let e=75*be/Ue.textWidth('"'+n+'"');e>75&&(e=75),Ue.textSize(e*le),Ue.text('"'+n+'"',width/2-100*le,height/2-90*le)}else nr(width/2-100*le,height/2-90*le,460*le,110*le,n,Ue);if(millis()-ye>1500&&(me=!0),C(tt,nt,st,ct,Pe,Mt),Ue.iM mage(nt,width/2-370*le,height/2+70*le,80*le,80*le),3==Pe){let e;e=map(Mt,50,60,.25,1.3),I(rt,e),Ue.image(rt,width/2-370*le,height/2+70*le,80*le,80*le)}let r,i;Ue.image(tt,width/2-370*le,height/2+70*le,80*le,80*le),Ue.fill(xt),Ue.textSize(40*le),Ue.text("INTELLIGENCE INFO",width/2-275*le,height/2+115*le),Ue.textSize(18*le),Ue.textStyle(NORMAL),Ue.circle(width/2-360*le,height/2+180*le,7.5*le),1==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s growing and getting smarter by the day.`:2==Pe?r=`Your PerceptrM on is ${Math.ceil(Mt)} years old. It s stable and it has reached peak performance.`:3==Pe&&(r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s decaying and losing its luster.`),i=2==Pe?"The Perceptron remains stable for some time before entering the decay phase.":`Wait until ${new Date(an).toLocaleString("en-US")} for your Perceptron to reach its peak performance.`,Ue.text(r,width/2-350*le,height/2+180*le),Ue.circle(width/2-360*le,height/2+210*le,7.5*le),Ue.text(i,width/2-350*le,height/2+210*le),Ue.textAligM n(CENTER,CENTER),Ue.textStyle(BOLD),gr(Ue,width/2-225*le,width/2+65*le,height/2+265*le,height/2+305*le,"SELECT ANOTHER IMAGE"),gr(Ue,width/2+75*le,width/2+225*le,height/2+265*le,height/2+305*le,"CLOSE")}function nr(e,t,n,r,i,o){let a=i.split(" "),l=75*be/o.textWidth('"'+i+'"'),s=0,h=[],c=[],u=[],f="",d="";if(l>=50)l>75&&(l=75),o.textSize(l*le),o.text('"'+i+'"',e,t);else if(l<50){if(l=50*defaultPhrase/o.textWidth('"'+i+'"'),l>30){if(l>50&&(l=50),[f,d]=rr(l,n,s,h,c,a,f,d,Ue),0==c.length)return o.textSize(l*le),void oM .text('"'+i+'"',e,t);for(s=0,h=[],c=[];o.textWidth(d)>n/le;)l=l*n/le/o.textWidth(d),f="",d="",[f,d]=rr(l,n,s,h,c,a,f,d,Ue)}else{l=30,o.textSize(l);for(let e=0;e<a.length;e++)s+=o.textWidth(" "+a[e]),s<=n/le?h.push(a[e]):s>n/le&&s<=n/le*2?c.push(a[e]):u.push(a[e]);for(let e=1;e<h.length;e++)f=f+" "+h[e];if(f='"'+h[0]+f,0==u.length){for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+c[c.length-1]+'"'}else if(1==c.length)d="... "+u[u.length-1]+'"';else{for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+"... "+u[u.length-1]+'"'}M }o.textSize(l*le);let r=1.25*(o.textDescent()+o.textAscent());o.text(f,e,t-r/2),o.text(d,e,t+r/2)}}function rr(e,t,n,r,i,o,a,l,s){s.textSize(e);for(let e=0;e<o.length;e++)(n+=s.textWidth(" "+o[e]))<=t/le?r.push(o[e]):i.push(o[e]);for(let e=1;e<r.length;e++)a=a+" "+r[e];if(a='"'+r[0]+a,0==i.length&&(a+='"',l=""),1==i.length)l=i[i.length-1]+'"';else{for(let e=0;e<i.length-1;e++)l=l+i[e]+" ";l=l+i[i.length-1]+'"'}return[a,l]}function ir(){const e=45*le;qe.textFont("Tahoma"),qe.stroke(st),qe.strokeWeight(2*le),qe.fill(M ct),qe.rect(width/2,e/2+height-87.5*le,600*le,90*le),qe.fill(st),qe.rect(width/2-150*le,e+height-170*le,300*le,30*le),qe.fill(ct),qe.rect(width/2+150*le,e+height-170*le,300*le,30*le),qe.noStroke(),qe.fill(ct),qe.textSize(15*le),qe.textStyle(BOLD),qe.text("PERCEPTRON INFORMATION",width/2-285*le,e+height-165*le),qe.fill(xt),qe.text("ARTWORK NAME:",width/2+10*le,e+height-165*le),qe.textAlign(RIGHT),qe.textStyle(ITALIC),qe.text("Perceptron #"+Et,width/2+285*le,e+height-165*le);const[t,n]=It.split(" ");let r;"60 Years"=M ==It?r="1 Year":"60 Months"===It?r="1 Month":"60 Weeks"===It?r="1 Week":"60 Days"===It?r="1 Day":"12 Hours"===It&&(r="12 Minutes"),data=[["AI MODEL NAME:",B(12*le,Ht,140*le)],["SCALE:","1:"+Te],["NUMBER OF CLASSES:",$t.length],["BIRTH YEAR:",Rt],["NUMBER OF REBIRTHS:",sn.toString()],["AGE:",`${Math.ceil(Mt)} Perceptron Years`],["ONE PERCEPTRON YEAR:",`${r}`],["STATE:",Ot[Pe]],["ACTIVE NEURONS:",`${round(ln*rn)} / ${ln}`],["NEXT STATE TIME:",vr(new Date(on))]],qe.fill(xt);const i=data.length/2;for(let t=0;t<data.lenM gth;++t){const n=t<i,r=n?width/2-285*le:width/2+10*le,o=n?width/2-10*le:width/2+285*le,a=e+height-(135-t%i*15)*le;qe.textStyle(BOLD),qe.textAlign(LEFT),qe.textSize(12*le),qe.text(data[t][0],r,a),qe.textStyle(ITALIC),qe.textAlign(RIGHT),qe.textSize(12*le),qe.text(data[t][1],o,a)}}function or(){Ke.textFont("Trebuchet MS"),Ke.noStroke(),pr(Ke,600*le,200*le),gr(Ke,width/2-155*le,width/2-5*le,height/2+115*le,height/2+155*le,"UPDATE"),gr(Ke,width/2+5*le,width/2+155*le,height/2+115*le,height/2+155*le,"CLOSE"),Ke.textAlignM (LEFT),Ke.fill(xt),Ke.text("UPDATE BITCOIN FULL NODE ADDRESS",width/2-252.5*le,height/2-55*le),Ke.text("UPDATE MODEL ADDRESS",width/2-252.5*le,height/2+20*le),Ke.textAlign(RIGHT),Ke.textStyle(ITALIC),Ke.textSize(15*le),0==wn&&Ke.text("(*) Invalid Address",width/2+252.5*le,height/2-53*le),0==vn&&Ke.text("(*) Invalid Model",width/2+252.5*le,height/2+23*le)}function ar(){je.textFont("Trebuchet MS"),je.fill(st),je.textSize(50*le),je.stroke(st),je.strokeWeight(1*le),je.text("main()",width/2,height/2)}function lr(){un>=2M 0&&1==dn&&(dn=!1,un=0),dn&&(Ze.textFont("Trebuchet MS"),Ze.stroke(st),Ze.fill(ct),Ze.rect(width/2,height/2,600*le,150*le,25*le),Ze.fill(xt),Ze.textSize(75*le),Ze.noStroke(),1==Pe?Ze.text("GROWING",width/2,height/2+5*le):3==Pe?Ze.text("AGING",width/2,height/2+5*le):4==Pe?Ze.text("DEAD",width/2,height/2+5*le):5==Pe&&Ze.text("BIRTH",width/2,height/2+5*le)),un>=20&&0==dn&&(dn=!0,un=0,Bt++,3==Bt&&(fn=!1))}function sr(e,t,n,r){let i=[],o=r/(n.length+1),a=color(e),l=color(t);i.push(a);for(let e=0;e<n.length;e++){let t=colM or(n[e]);for(let e=1;e<=o;e++){let n=lerpColor(a,t,e/o);i.push(n)}a=t}for(let e=1;e<o;e++){let t=lerpColor(a,l,e/o);i.push(t)}if(i.push(l),i.length>r)i.splice(r);else if(i.length<r){let e=i[i.length-1];for(;i.length<r;)i.push(e)}return i}function hr(e,t){let n=e.length,r=Math.floor(t*n);return r>=n&&(r=n-1),e[r]}function cr(e){e=e.replace("#","");var t=parseInt(e,16);return color(t>>16&255,t>>8&255,255&t)}function ur(e,t,n,r,i,o,a,l){var s=a.drawingContext.createLinearGradient(e,t,n,r);s.addColorStop(0,i),s.addColoM rStop(1,o),a.drawingContext.strokeStyle=s,a.drawingContext.globalAlpha=l,a.line(e,t,n,r),a.drawingContext.globalAlpha=1}function fr(e,t){t.drawingContext.setLineDash(e)}function dr(e,t){let n=color(e),r=red(n),i=green(n),o=blue(n);return color(r,i,o,255*t)}function xr(e,t,n,r){return mouseX>e&&mouseX<t&&mouseY>n&&mouseY<r}function gr(e,t,n,r,i,o){e.strokeWeight(1*le),e.stroke(st);const[a,l]=xr(t,n,r,i)?[xt,ct]:[ct,xt];e.fill(a),e.push(),e.rectMode(CORNERS),e.rect(t,r,n,i,5*le),e.pop(),e.noStroke(),e.textSize(20*le)M ,e.fill(l),e.text(o,(t+n)/2,(46*r+54*i)/100)}function pr(e,t,n){e.fill(0,0,0,75),e.rect(width/2,height/2,width,height),e.stroke(st),e.fill(ct),e.rect(width/2,height/2,t,n,25*le)}function mr(e,t){resizeCanvas(e,t,!0),Xe.resizeCanvas(e,t,!0),$e.resizeCanvas(e,t,!0),We.resizeCanvas(e,t,!0),Ue.resizeCanvas(e,t,!0),qe.resizeCanvas(e,t,!0),Qe.resizeCanvas(e,t,!0),je.resizeCanvas(e,t,!0),Ze.resizeCanvas(e,t,!0),Ke.resizeCanvas(e,t,!0),Je.resizeCanvas(e,t,!0),et.resizeCanvas(e,t,!0)}function br(e,t,n,r,i,o){const a=J(e);reM turn a.position(t,n),a.size(r,i),a.style("opacity","0"),a.mouseClicked(o),a}function yr(){return null!=vt&&vt?.isFocused()||null!=zt&&zt?.isFocused()}function wr(e,t,n,r){let i;if(e<=3){i=`Hey ${String.fromCodePoint(128075)}, I'm ${n}, ${t} years old. I can detect ${r.length} NFT collections: `;let e=0;for(let t=0;t<r.length;++t){const n=r[t];if(e+n.length>500){i+=", etc";break}t==r.length-1?i+=", and ":t>0&&(i+=", "),i+=n,e+=n.length}i+=". ",t<=5?i+="However, I am only a baby, so my recognition ability is not accuM rate. I'm in the state of Growing both looks and intelligence.":t<=13?i+="I am now a child. My recognition ability is becoming better, but still not very accurate. I'm in the state of Growing both looks and intelligence.":t<=25?i+="I have grown up to be a teen. My recognition ability almost reaches the peak, but I will still mess up sometimes. I'm in the state of Growing both looks and intelligence.":t<=50?i+="I finally reach adulthood. My recognition is fully functional now. I'm in the Stable state, where I am theM most intelligent with all neurons activated.":t<=60&&(i+="I am now an old Perceptron, so my recognition ability is no longer the best. I'm in the Decaying state, meaning that my neurons are dying, and my intelligence is decreasing over time.")}else 4==e?i=`${n} is Dead. However, this is not the end to its story...`:5==e&&(i=`${n} is now in the Rebirth state, and is preparing to start a new life.`);return i}function vr(e){const t=e.getDate(),n=e.toLocaleString("en-US",{month:"long"}),r=e.getFullYear();let i=e.getHoM urs().toString();1==i.length&&(i="0"+i);let o=e.getMinutes().toString();return 1==o.length&&(o="0"+o),`${Y(t)} ${n} ${r} | ${i}:${o}`}saveCanvasAtCurrentTime=()=>{save(N())},save4KCanvasAtCurrentTime=()=>{const e=width,t=height,n=min(4096/min(e,t),1e4/max(e,t)),r=e*n,i=t*n;mr(r,i),zn=!0,$n(r,i),qn();let o="4K_"+N()+".png";saveCanvas(et,o),mr(e,t),$n(e,t),zn=!1};const zr=[["60 Years",3,365],["60 Months",40,30],["60 Weeks",37,7],["60 Days",20,1]],Vr=[["1943",1],["1951",1.5],["1957",2],["1969",2.5],["1970",3],["1980",M 3.5],["1982",4],["1986",4.5],["1988",5],["1997",5.5],["1998",6],["2002",6.5],["2009",7],["2012",7.5],["2014",8],["2015",8.5],["2016",9],["2023",15]],_r=[["Plain",20],["Dotted",40],["Squared",40]],Mr=[["Basic",30],["Standard",60],["Advanced",10]],Er=[["MNIST",70],["CIFAR",25],["IMAGENET",5]],Sr=[["Theano",60],["Torch",30],["TensorFlow",10]],Rr=[["Whitepaper",2],["Blackboard",2],["Blueprint",2],["Nak",74/14],["Jims",74/14],["Level 10",74/14],["Flips",74/14],["Level 14",74/14],["III",74/14],["XMB",74/14],["Info",74/14M ],["Adventure",74/14],["Marigold",74/14],["Phoenix",74/14],["Love",74/14],["Cachet",74/14],["Human",74/14],["Twilight",3],["Sunset",3],["Aurora",3],["Liminal Space",3],["D Vu",3],["Lucid Dream",3],["Parallel",1],["Multiverse",1]];function Ir(e){for(let e=0;e<100;++e)random(1);return{visual:{pattern:k(_r),hardwareAcceleration:k(Mr),nodeFill:k(Er),nodeShape:k(Sr),colorPalette:k(Rr),lifeCycle:k(zr),birthYear:k(Vr)},training:e}}function Cr(e){window.$generativeTraits={"Network Architecture":e.training.structure_geM n,"Hidden Layers":e.training.n_layers,"Max Neurons Per Hidden Layer":e.training.max_nodes,"Activation Function":e.training.activation_func,"Training Epochs":e.training.epoch_num,Dataset:e.visual.nodeFill,"Deep Learning Framework":e.visual.nodeShape,"Hardware Acceleration":e.visual.hardwareAcceleration,"Paper Pattern":e.visual.pattern,"Life Cycle":e.visual.lifeCycle,"Birth Year":e.visual.birthYear,"Color Palette":e.visual.colorPalette}} <script defer src="https://static.cloudflareinsights.com/beacon.MR min.js/v2b4487d741ca48dcbadcaf954e159fc61680799950996" integrity="sha512-D/jdE0CypeVxFadTejKGTzmwyV10c1pxZk/AqjJuZbaJwGMyNHY3q/mTPWqMUnFACfCTunhZUVcd4cV78dK1pQ==" data-cf-beacon='{"rayId":"7b481d6a7dd4cab4","version":"2023.3.0","b":1,"token":"6c07c178c94442f695e7a0a2aaee641a","si":100}' crossorigin="anonymous"></script> {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "ghostly companion"}]} text/html;charset=utf-8 <meta charset="utf-8" /> position: relative; width: var(--width); height: var(--height); border: 1px solid blue; position: relative; <div id="upload"> <input id="inputUpload" type="file"> function e(e){"use strict";return new function e(t){let n="global"==t?window:this;n.canvas=document.createElement("canvas");let r=n.canvas.getContext("2d");n.width=100,n.height=100,n.canvas.width=n.width,n.canvas.height=n.height,"offscreen"!=t&&(document.body?document.body.appendChild(n.canvas):window.addEventListener("load",(function(){document.body.appendChild(n.canvas)}))),g(),n.MAGIC=161533525,n.RGB=0,n.HSV=1,n.HM SB=1,n.CHORD=0,n.PIE=1,n.OPEN=2,n.RADIUS=1,n.CORNER=2,n.CORNERS=3,n.ROUND="round",n.SQUARE="butt",n.PROJECT="square",n.MITER="miter",n.BEVEL="bevel",n.CLOSE=1,n.BLEND="source-over",n.REMOVE="destination-out",n.ADD="lighter",n.DARKEST="darken",n.LIGHTEST="lighten",n.DIFFERENCE="difference",n.SUBTRACT="subtract",n.EXCLUSION="exclusion",n.MULTIPLY="multiply",n.SCREEN="screen",n.REPLACE="copy",n.OVERLAY="overlay",n.HARD_LIGHT="hard-light",n.SOFT_LIGHT="soft-light",n.DODGE="color-dodge",n.BURN="color-burn",n.NORMAL="norM mal",n.ITALIC="italic",n.BOLD="bold",n.BOLDITALIC="italic bold",n.CENTER="center",n.LEFT="left",n.RIGHT="right",n.TOP="top",n.BOTTOM="bottom",n.BASELINE="alphabetic",n.LANDSCAPE="landscape",n.PORTRAIT="portrait",n.ALT=18,n.BACKSPACE=8,n.CONTROL=17,n.DELETE=46,n.DOWN_ARROW=40,n.ENTER=13,n.ESCAPE=27,n.LEFT_ARROW=37,n.OPTION=18,n.RETURN=13,n.RIGHT_ARROW=39,n.SHIFT=16,n.TAB=9,n.UP_ARROW=38,n.HALF_PI=Math.PI/2,n.PI=Math.PI,n.QUARTER_PI=Math.PI/4,n.TAU=2*Math.PI,n.TWO_PI=2*Math.PI,n.THRESHOLD=1,n.GRAY=2,n.OPAQUE=3,n.INVEM RT=4,n.POSTERIZE=5,n.DILATE=6,n.ERODE=7,n.BLUR=8,n.ARROW="default",n.CROSS="crosshair",n.HAND="pointer",n.MOVE="move",n.TEXT="text",n.VIDEO={video:!0,audio:!1},n.AUDIO={video:!1,audio:!0},n.SHR3=1,n.LCG=2,n.HARDWARE_FILTERS=!0,n.hint=function(e,t){n[e]=t},n.frameCount=0,n.mouseX=0,n.mouseY=0,n.pmouseX=0,n.pmouseY=0,n.mouseButton=null,n.keyIsPressed=!1,n.mouseIsPressed=!1,n.key=null,n.keyCode=null,n.pixels=null,n.accelerationX=0,n.accelerationY=0,n.accelerationZ=0,n.rotationX=0,n.rotationY=0,n.rotationZ=0,n.relRotatM ionX=0,n.relRotationY=0,n.relRotationZ=0,n.pAccelerationX=0,n.pAccelerationY=0,n.pAccelerationZ=0,n.pRotationX=0,n.pRotationY=0,n.pRotationZ=0,n.pRelRotationX=0,n.pRelRotationY=0,n.pRelRotationZ=0,n.touches=[],n._styleCache=[{colorMode:n.RGB,noStroke:!1,noFill:!1,ellipseMode:n.CENTER,rectMode:n.CORNER,curveDetail:20,curveAlpha:0,textFont:"sans-serif",textSize:12,textLeading:12,textStyle:"normal"}],n._style=n._styleCache[n._styleCache.length-1],n._noLoop=!1,n._pixelDensity=1,n._frameRate=null,n._tint=null;let i=nullM ,o=!0,a=[],l=null,s=0,h={},c=0,u=null,f=null,d=null;Object.defineProperty(n,"deviceOrientation",{get:function(){return 90==Math.abs(window.orientation)?n.LANDSCAPE:n.PORTRAIT}}),Object.defineProperty(n,"windowWidth",{get:function(){return window.innerWidth}}),Object.defineProperty(n,"windowHeight",{get:function(){return window.innerHeight}}),Object.defineProperty(n,"drawingContext",{get:function(){return r}}),n.createCanvas=function(e,t){return n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t,g(),n.canvas},nM .resizeCanvas=function(e,t){n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t},n.createGraphics=n.createImage=function(t,n){let r=new e("offscreen");return r.createCanvas(t,n),r.noLoop(),r},n.pixelDensity=function(e){return null==e||(n._pixelDensity=e,n.canvas.width=Math.ceil(n.width*e),n.canvas.height=Math.ceil(n.height*e),n.canvas.style.width=n.width+"px",n.canvas.style.height=n.height+"px",r.scale(n._pixelDensity,n._pixelDensity),g()),n._pixelDensity},n.map=function(e,t,n,r,i,o){let a=r+1*(e-t)/(n-t)*(i-r)M ;return o?r<i?Math.min(Math.max(a,r),i):Math.min(Math.max(a,i),r):a},n.lerp=function(e,t,n){return e*(1-n)+t*n},n.constrain=function(e,t,n){return Math.min(Math.max(e,t),n)},n.dist=function(){return 4==arguments.length?Math.hypot(arguments[0]-arguments[2],arguments[1]-arguments[3]):Math.hypot(arguments[0]-arguments[3],arguments[1]-arguments[4],arguments[2]-arguments[5])},n.norm=function(e,t,r){return n.map(e,t,r,0,1)},n.sq=function(e){return e*e},n.fract=function(e){return e-Math.floor(e)},n.degrees=function(e){retM urn 180*e/Math.PI},n.radians=function(e){return e*Math.PI/180},n.abs=Math.abs,n.ceil=Math.ceil,n.exp=Math.exp,n.floor=Math.floor,n.log=Math.log,n.mag=Math.hypot,n.max=Math.max,n.min=Math.min,n.round=Math.round,n.sqrt=Math.sqrt,n.sin=Math.sin,n.cos=Math.cos,n.tan=Math.tan,n.asin=Math.asin,n.acos=Math.acos,n.atan=Math.atan,n.atan2=Math.atan2,n.Vector=function(e,t,r){let i=this;i.x=e||0,i.y=t||0,i.z=r||0;let o=null,a=null;function l(e,t,n){return null!=e.x?e:null!=t?{x:e,y:t,z:n||0}:{x:e,y:e,z:e}}function s(){null==a&M &(a=i.x*i.x+i.y*i.y+i.z*i.z,o=Math.sqrt(a))}function h(){a=null,o=null}i.set=function(e,t,n){i.x=e||0,i.y=t||0,i.z=n||0},i.copy=function(){return new n.Vector(i.x,i.y,i.z)},i.add=function(){let e=l.apply(null,arguments);return i.x+=e.x,i.y+=e.y,i.z+=e.z,h(),i},i.rem=function(){let e=l.apply(null,arguments);return i.x%=e.x,i.y%=e.y,i.z%=e.z,h(),i},i.sub=function(){let e=l.apply(null,arguments);return i.x-=e.x,i.y-=e.y,i.z-=e.z,h(),i},i.mult=function(){let e=l.apply(null,arguments);return i.x*=e.x,i.y*=e.y,i.z*=e.z,hM (),i},i.div=function(){let e=l.apply(null,arguments);return i.x/=e.x,i.y/=e.y,i.z/=e.z,h(),i},i.mag=function(){return s(),o},i.magSq=function(){return s(),a},i.dot=function(){let e=l.apply(null,arguments);return i.x*e.x+i.y*e.y+i.z*e.z},i.dist=function(){let e=l.apply(null,arguments),t=i.x-e.x,n=i.y-e.y,r=i.z-e.z;return Math.sqrt(t*t+n*n+r*r)},i.cross=function(){let e=l.apply(null,arguments),t=i.y*e.z-i.z*e.y,n=i.z*e.x-i.x*e.z,r=i.x*e.y-i.y*e.x;return i.x=t,i.y=n,i.z=r,h(),i},i.normalize=function(){s();let e=o;retuM rn i.x/=e,i.y/=e,i.z/=e,o=1,a=1,i},i.limit=function(e){s();if(o>e){let t=e/o;i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e}return i},i.setMag=function(e){s();let t=e/o;return i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e,i},i.heading=function(){return Math.atan2(i.y,i.x)},i.rotate=function(e){let t=Math.cos(e),n=Math.sin(e),r=i.x*t-i.y*n,o=i.x*n+i.y*t;return i.x=r,i.y=o,i},i.angleBetween=function(){let e=l.apply(null,arguments);const t=i.dot(e)/(i.mag()*e.mag());let n;return n=Math.acos(Math.min(1,Math.max(-1,t))),n*Math.sign(i.cross(e).z||1)},M i.lerp=function(e,t){return i.x=i.x*(1-t)+e.x*t,i.y=i.y*(1-t)+e.y*t,i.z=i.z*(1-t)+e.z*t,h(),i},i.reflect=function(e){return e.normalize(),i.sub(e.mult(2*i.dot(e)))},i.array=function(){return[i.x,i.y,i.z]},i.equals=function(e,t){return null==t&&null==(t=Number.EPSILON)&&(t=0),Math.abs(e.x-i.x)<t&&Math.abs(e.y-i.y)<t&&Math.abs(e.z-i.z)<t},i.fromAngle=function(e,t){return null==t&&(t=1),o=t,a=t*t,i.x=t*Math.cos(e),i.y=t*Math.sin(e),i.z=0,i},i.fromAngles=function(e,t,n){null==n&&(n=1),o=n,a=n*n;const r=Math.cos(t),l=MaM th.sin(t),s=Math.cos(e),h=Math.sin(e);return i.x=n*h*l,i.y=-n*s,i.z=n*h*r,i},i.random2D=function(){return o=1,a=1,i.fromAngle(Math.random()*Math.PI*2)},i.random3D=function(){return o=1,a=1,i.fromAngles(Math.random()*Math.PI*2,Math.random()*Math.PI*2)},i.toString=function(){return`[${i.x}, ${i.y}, ${i.z}]`}},n.Vector.add=function(e,t){return new n.Vector(e.x+t.x,e.y+t.y,e.z+t.z)},n.Vector.rem=function(e,t){return new n.Vector(e.x%t.x,e.y%t.y,e.z%t.z)},n.Vector.sub=function(e,t){return new n.Vector(e.x-t.x,e.y-t.y,e.M z-t.z)},n.Vector.mult=function(e,t){return null==t.x?new n.Vector(e.x*t,e.y*t,e.z*t):new n.Vector(e.x*t.x,e.y*t.y,e.z*t.z)},n.Vector.div=function(e,t){return null==t.x?new n.Vector(e.x/t,e.y/t,e.z/t):new n.Vector(e.x/t.x,e.y/t.y,e.z/t.z)},n.Vector.dist=function(e,t){return Math.hypot(e.x-t.x,e.y-t.y,e.z-t.z)},n.Vector.cross=function(e,t){return new n.Vector(e.y*t.z-e.z*t.y,e.z*t.x-e.x*t.z,e.x*t.y-e.y*t.x)},n.Vector.lerp=function(e,t,r){return new n.Vector(e.x*(1-r)+t.x*r,e.y=e.y*(1-r)+t.y*r,e.z=e.z*(1-r)+t.z*r)},n.M Vector.equals=function(e,t,n){return e.equals(t,n)};for(let e of["fromAngle","fromAngles","random2D","random3D"])n.Vector[e]=function(t,r,i){return(new n.Vector)[e](t,r,i)};function x(e,t,n){let r,i,o,a,l,s,h,c,u;if(0==t)return[255*(r=n),255*(i=n),255*(o=n)];switch((a=e)>360&&(a=0),h=n*(1-t),c=n*(1-t*(s=(a/=60)-(l=~~a))),u=n*(1-t*(1-s)),l){case 0:r=n,i=u,o=h;break;case 1:r=c,i=n,o=h;break;case 2:r=h,i=n,o=u;break;case 3:r=h,i=c,o=n;break;case 4:r=u,i=h,o=n;break;default:r=n,i=h,o=c}return[255*r,255*i,255*o]}functioM n g(){r.fillStyle="white",r.strokeStyle="black",r.lineCap="round",r.lineJoin="miter"}function p(e){if(0<=e&&e<2*Math.PI)return e;for(;e<0;)e+=2*Math.PI;for(;e>=Math.PI;)e-=2*Math.PI;return e}function m(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;let c=p(a),u=p(l);r.beginPath();for(let a=0;a<h+1;a++){let l=a/h,s=n.lerp(c,u,l),f=Math.cos(s)*i/2,d=Math.sin(s)*o/2;r[a?"lineTo":"moveTo"](e+f,t+d)}s==n.CHORD?r.closePath():s==n.PIE&&(r.lineTo(e,t),r.closePath()),n._style.noFill||r.fill(),n._style.noStrokM e||r.stroke()}function b(e,t,i,o){n._style.noFill&&n._style.noStroke||(r.beginPath(),r.ellipse(e,t,i/2,o/2,0,0,2*Math.PI),n._style.noFill||r.fill(),n._style.noStroke||r.stroke())}function y(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;if(null==a)return function(e,t,i,o){n._style.noFill||r.fillRect(e,t,i,o),n._style.noStroke||r.strokeRect(e,t,i,o)}(e,t,i,o);if(null==l)return y(e,t,i,o,a,a,a,a);const c=Math.min(Math.abs(o),Math.abs(i))/2;a=Math.min(c,a),l=Math.min(c,l),h=Math.min(c,h),s=Math.min(c,s)M ,r.beginPath(),r.moveTo(e+a,t),r.arcTo(e+i,t,e+i,t+o,l),r.arcTo(e+i,t+o,e,t+o,s),r.arcTo(e,t+o,e,t,h),r.arcTo(e,t,e+i,t,a),r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke()}function w(){a=[]}n.createVector=function(e,t,r){return new n.Vector(e,t,r)},n.curvePoint=function(e,t,n,r,i){const o=i*i*i,a=i*i;return e*(-.5*o+a-.5*i)+t*(1.5*o-2.5*a+1)+n*(-1.5*o+2*a+.5*i)+r*(.5*o-.5*a)},n.bezierPoint=function(e,t,n,r,i){const o=1-i;return Math.pow(o,3)*e+3*Math.pow(o,2)*i*t+3*o*Math.pow(i,2)*n+Math.pow(i,M 3)*r},n.curveTangent=function(e,t,n,r,i){const o=i*i;return e*(-3*o/2+2*i-.5)+t*(9*o/2-5*i)+n*(-9*o/2+4*i+.5)+r*(3*o/2-i)},n.bezierTangent=function(e,t,n,r,i){const o=1-i;return 3*r*Math.pow(i,2)-3*n*Math.pow(i,2)+6*n*o*i-6*t*o*i+3*t*Math.pow(o,2)-3*e*Math.pow(o,2)},n.Color=function(e,t,n,r){let i=this;i.MAGIC=786698,i._r=e,i._g=t,i._b=n,i._a=r,i._h=0,i._s=0,i._v=0,i._hsvInferred=!1,i.setRed=function(e){i._r=e,i._hsvInferred=!1},i.setGreen=function(e){i._g=e,i._hsvInferred=!1},i.setBlue=function(e){i._b=e,i._hsvInfM erred=!1},i.setAlpha=function(e){i._a=e/255,i._hsvInferred=!1},i._inferHSV=function(){i._hsvInferred||([i._h,i._s,i._v]=function(e,t,n){let r,i,o,a,l;return r=e<t?e<n?e:n:t<n?t:n,0==(l=100*(i=e>t?e>n?e:n:t>n?t:n)/255)?[o=0,a=0,l]:0==(a=100*(i-r)/i)?[o=0,a,l]:(o=i==e?0+60*(t-n)/(i-r):i==t?120+60*(n-e)/(i-r):240+60*(e-t)/(i-r),[o,a,l])}(i._r,i._g,i._b),i._hsvInferred=!0)},i.toString=function(){return`rgba(${Math.round(i._r)},${Math.round(i._g)},${Math.round(i._b)},${~~(1e3*i._a)/1e3})`}},n.colorMode=function(e){n._stM yle.colorMode=e},n.color=function(){if(1==arguments.length&&786698==arguments[0].MAGIC)return arguments[0];if(n._style.colorMode==n.RGB){if(1==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],1);if(2==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],arguments[1]/255);if(3==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],1);if(4==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],arguments[3]/255)}else{if(1==argumeM nts.length)return new n.Color(...x(0,0,arguments[0]/100),1);if(2==arguments.length)return new n.Color(...x(0,0,arguments[0]/100),arguments[1]/255);if(3==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),1);if(4==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),arguments[3])}return null},n.red=function(e){return e._r},n.green=function(e){return e._g},n.blue=function(e){return e._b},n.alpha=function(e){return 255*e._a},n.hue=function(e){reM turn e._inferHSV(),e._h},n.saturation=function(e){return e._inferHSV(),e._s},n.brightness=function(e){return e._inferHSV(),e._v},n.lightness=function(e){return 100*(.2126*e._r+.7152*e._g+.0722*e._b)/255},n.lerpColor=function(e,t,r){return n._style.colorMode==n.RGB?new n.Color(n.constrain(n.lerp(e._r,t._r,r),0,255),n.constrain(n.lerp(e._g,t._g,r),0,255),n.constrain(n.lerp(e._b,t._b,r),0,255),n.constrain(n.lerp(e._a,t._a,r),0,1)):(e._inferHSV(),t._inferHSV(),new n.Color(n.constrain(function(e,t,r){var i=[[Math.abs(t-M e),n.map(r,0,1,e,t)],[Math.abs(t+360-e),n.map(r,0,1,e,t+360)],[Math.abs(t-360-e),n.map(r,0,1,e,t-360)]];return i.sort(((e,t)=>e[0]-t[0])),(i[0][1]+720)%360}(e._h,t._h,r),0,360),n.constrain(n.lerp(e._s,t._s,r),0,100),n.constrain(n.lerp(e._v,t._v,r),0,100),n.constrain(n.lerp(e._a,t._a,r),0,1)))},n.strokeWeight=function(e){n._style_noStroke=!1,r.lineWidth=e},n.stroke=function(){if(n._style.noStroke=!1,"string"==typeof arguments[0])return void(r.strokeStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._sM tyle.noStroke=!0:r.strokeStyle=e},n.noStroke=function(){n._style.noStroke=!0},n.fill=function(){if(n._style.noFill=!1,"string"==typeof arguments[0])return void(r.fillStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._style.noFill=!0:r.fillStyle=e},n.noFill=function(){n._style.noFill=!0},n.blendMode=function(e){r.globalCompositeOperation=e},n.strokeCap=function(e){r.lineCap=e},n.strokeJoin=function(e){r.lineJoin=e},n.ellipseMode=function(e){n._style.ellipseMode=e},n.rectMode=function(e){n._style.rectM Mode=e},n.curveDetail=function(e){n._style.curveDetail=e},n.curveAlpha=function(e){n._style.curveAlpha=e},n.curveTightness=function(e){n._style.curveAlpha=e},n.clear=function(){r.clearRect(0,0,n.width,n.height)},n.background=function(){if(arguments[0]&&arguments[0].MAGIC==n.MAGIC)return n.image(arguments[0],0,0,n.width,n.height);r.save(),r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity),r.fillStyle="string"==typeof arguments[0]?arguments[0]:n.color(...Array.from(arguments)),r.fillRect(0,0,n.width,n.heightM ),r.restore()},n.line=function(e,t,i,o){n._style.noStroke||(r.beginPath(),r.moveTo(e,t),r.lineTo(i,o),r.stroke())},n.arc=function(e,t,r,i,o,a,l,s){if(o==a)return n.ellipse(e,t,r,i);null==s&&(s=25),null==l&&(l=n.PIE),n._style.ellipseMode==n.CENTER?m(e,t,r,i,o,a,l,s):n._style.ellipseMode==n.RADIUS?m(e,t,2*r,2*i,o,a,l,s):n._style.ellipseMode==n.CORNER?m(e+r/2,t+i/2,r,i,o,a,l,s):n._style.ellipseMode==n.CORNERS&&m((e+r)/2,(t+i)/2,r-e,i-t,o,a,l,s)},n.ellipse=function(e,t,r,i){null==i&&(i=r),n._style.ellipseMode==n.CENTERM ?b(e,t,r,i):n._style.ellipseMode==n.RADIUS?b(e,t,2*r,2*i):n._style.ellipseMode==n.CORNER?b(e+r/2,t+i/2,r,i):n._style.ellipseMode==n.CORNERS&&b((e+r)/2,(t+i)/2,r-e,i-t)},n.circle=function(e,t,r){return n.ellipse(e,t,r,r)},n.point=function(e,t){e.x&&(t=e.y,e=e.x),r.beginPath(),r.ellipse(e,t,.4,.4,0,0,2*Math.PI),r.stroke()},n.rect=function(e,t,r,i,o,a,l,s){n._style.rectMode==n.CENTER?y(e-r/2,t-i/2,r,i,o,a,l,s):n._style.rectMode==n.RADIUS?y(e-r,t-i,2*r,2*i,o,a,l,s):n._style.rectMode==n.CORNER?y(e,t,r,i,o,a,l,s):n._stylM e.rectMode==n.CORNERS&&y(e,t,r-e,i-t,o,a,l,s)},n.square=function(e,t,r,i,o,a,l){return n.rect(e,t,r,r,i,o,a,l)},n.beginShape=function(){w(),r.beginPath(),o=!0},n.beginContour=function(){r.closePath(),w(),o=!0},n.endContour=function(){w(),o=!0},n.vertex=function(e,t){w(),o?r.moveTo(e,t):r.lineTo(e,t),o=!1},n.bezierVertex=function(e,t,n,i,o,a){w(),r.bezierCurveTo(e,t,n,i,o,a)},n.quadraticVertex=function(e,t,n,i){w(),r.quadraticCurveTo(e,t,n,i)},n.bezier=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.bezierVM ertex(r,i,o,a,l,s),n.endShape()},n.triangle=function(e,t,r,i,o,a){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.endShape(n.CLOSE)},n.quad=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.vertex(l,s),n.endShape(n.CLOSE)},n.endShape=function(e){w(),e&&r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke(),n._style.noFill&&n._style.noStroke&&(r.save(),r.fillStyle="none",r.fill(),r.restore())},n.curveVertex=function(e,t){if(a.push([e,t]),a.length<4)return;M let i=function(e,t,n,r,i,o,a,l,s,h){function c(e,t,n,r,i,o){let a=Math.pow(r-t,2)+Math.pow(i-n,2);return Math.pow(a,.5*o)+e}let u=[],f=c(0,e,t,n,r,h),d=c(f,n,r,i,o,h),x=c(d,i,o,a,l,h);for(let h=0;h<s;h++){let c=f+h/(s-1)*(d-f),g=[(f-c)/(f-0),(c-0)/(f-0),(d-c)/(d-f),(c-f)/(d-f),(x-c)/(x-d),(c-d)/(x-d),(d-c)/(d-0),(c-0)/(d-0),(x-c)/(x-f),(c-f)/(x-f)];for(let e=0;e<g.length;e+=2)isNaN(g[e])&&(g[e]=1,g[e+1]=0),isFinite(g[e])||(g[e]>0?(g[e]=1,g[e+1]=0):(g[e]=0,g[e+1]=1));let p=e*g[0]+n*g[1],m=t*g[0]+r*g[1],b=n*g[2]+i*g[M 3],y=r*g[2]+o*g[3],w=i*g[4]+a*g[5],v=o*g[4]+l*g[5],z=p*g[6]+b*g[7],V=m*g[6]+y*g[7],_=b*g[8]+w*g[9],M=y*g[8]+v*g[9],E=z*g[2]+_*g[3],S=V*g[2]+M*g[3];u.push([E,S])}return u}(...a[a.length-4],...a[a.length-3],...a[a.length-2],...a[a.length-1],n._style.curveDetail,n._style.curveAlpha);for(let e=0;e<i.length;e++)o?r.moveTo(...i[e]):r.lineTo(...i[e]),o=!1},n.curve=function(e,t,r,i,o,a,l,s){n.beginShape(),n.curveVertex(e,t),n.curveVertex(r,i),n.curveVertex(o,a),n.curveVertex(l,s),n.endShape()},n.translate=function(e,t){r.tM ranslate(e,t)},n.rotate=function(e){r.rotate(e)},n.scale=function(e,t){null==t&&(t=e),r.scale(e,t)},n.applyMatrix=function(e,t,n,i,o,a){r.transform(e,t,n,i,o,a)},n.shearX=function(e){r.transform(1,0,Math.tan(e),1,0,0)},n.shearY=function(e){r.transform(1,Math.tan(e),0,1,0,0)},n.resetMatrix=function(){r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity)},n.pushMatrix=n.push=function(){n._styleCache.push({...n._style}),n._style=n._styleCache[n._styleCache.length-1],r.save()},n.popMatrix=n.pop=function(){n._stylM eCache.length-1&&(n._styleCache.pop(),n._style=n._styleCache[n._styleCache.length-1],r.restore())},n.image=function(e,t,i,o,a,l,s,h,c){let u=e.MAGIC==n.MAGIC?e.canvas:e;function d(){if(e.MAGIC!=n.MAGIC||!n._tint)return;let t=e.canvas.getContext("2d");t.save(),t.resetTransform(),t.clearRect(0,0,t.canvas.width,t.canvas.height),t.drawImage(f.canvas,0,0),t.restore()}return e.MAGIC==n.MAGIC&&null!=n._tint&&(function(e,t){null==f&&(f=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvasM .height),f.canvas.width==e&&f.canvas.height==t||(f.canvas.width=e,f.canvas.height=t)}(e.canvas.width,e.canvas.height),f.drawImage(e.canvas,0,0),e.tinted(n._tint)),o?l?(h||(h=u.width),c||(c=u.height),r.drawImage(u,l,s,h,c,t,i,o,a),void d()):(r.drawImage(u,t,i,o,a),void d()):(e.MAGIC==n.MAGIC||e.width?r.drawImage(u,t,i,e.width,e.height):r.drawImage(u,t,i,e.videoWidth,e.videoHeight),void d())},n.loadPixels=function(){l=r.getImageData(0,0,n.canvas.width,n.canvas.height),n.pixels=l.data},n.updatePixels=function(){null!=M l&&r.putImageData(l,0,0)},n.loadImage=function(e,t){s++;let r=n.createGraphics(100,100),i=r.canvas.getContext("2d"),o=new Image;return o.src=e,o.crossOrigin="Anonymous",o.onload=function(){i.canvas.width=o.width,i.canvas.height=o.height,r.width=o.width,r.height=o.height,i.drawImage(o,0,0),s--,t&&t(r)},r};let v={};function z(e,t){null==u&&(u=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvas.height),u.canvas.width==e&&u.canvas.height==t||(u.canvas.width=e,u.canvas.height=t)}funcM tion V(){let e=r.canvas.width*r.canvas.height*4;null!=d&&e==d.length||(d=new Uint8ClampedArray(e))}function _(e){u.clearRect(0,0,u.canvas.width,u.canvas.height),u.filter=e,u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()}v[n.THRESHOLD]=function(e,t){null==t?t=127.5:t*=255;for(let n=0;n<e.length;n+=4){const r=.2126*e[n]+.7152*e[n+1]+.0722*e[n+2];e[n]=e[n+1]=e[n+2]=r>=t?255:0}},v[n.GRAY]=function(e){for(let t=0;t<e.length;t+=4)M {const n=.2126*e[t]+.7152*e[t+1]+.0722*e[t+2];e[t]=e[t+1]=e[t+2]=n}},v[n.OPAQUE]=function(e){for(let t=0;t<e.length;t+=4)e[t+3]=255},v[n.INVERT]=function(e){for(let t=0;t<e.length;t+=4)e[t]=255-e[t],e[t+1]=255-e[t+1],e[t+2]=255-e[t+2]},v[n.POSTERIZE]=function(e,t){let n=t-1;for(let r=0;r<e.length;r+=4)e[r]=255*(e[r]*t>>8)/n,e[r+1]=255*(e[r+1]*t>>8)/n,e[r+2]=255*(e[r+2]*t>>8)/n},v[n.DILATE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-M 1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.max(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.ERODE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.min(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.BLURM ]=function(e,t){t=t||1,t=Math.floor(t*n._pixelDensity),V(),d.set(e);let i=2*t+1,o=function(e){let n=new Float32Array(e),r=.3*t+.8,i=r*r*2;for(let t=0;t<e;t++){let o=t-e/2,a=Math.exp(-o*o/i)/(2.5066282746*r);n[t]=a}return n}(i),[a,l]=[r.canvas.width,r.canvas.height];for(let n=0;n<l;n++)for(let r=0;r<a;r++){let l=0,s=0,h=0,c=0;for(let e=0;e<i;e++){let i=4*(n*a+Math.min(Math.max(r-t+e,0),a-1));l+=d[i]*o[e],s+=d[i+1]*o[e],h+=d[i+2]*o[e],c+=d[i+3]*o[e]}let u=4*(n*a+r);e[u]=l,e[u+1]=s,e[u+2]=h,e[u+3]=c}d.set(e);for(let nM =0;n<l;n++)for(let r=0;r<a;r++){let s=0,h=0,c=0,u=0;for(let e=0;e<i;e++){let i=4*(Math.min(Math.max(n-t+e,0),l-1)*a+r);s+=d[i]*o[e],h+=d[i+1]*o[e],c+=d[i+2]*o[e],u+=d[i+3]*o[e]}let f=4*(n*a+r);e[f]=s,e[f+1]=h,e[f+2]=c,e[f+3]=u}},n.filter=function(e,t){if(n.HARDWARE_FILTERS&&null!=r.filter)if(z(),e==n.THRESHOLD){null==t&&(t=.5),t=Math.max(t,1e-5),_(`saturate(0%) brightness(${Math.floor(.5/t*100)}%) contrast(1000000%)`)}else if(e==n.GRAY)_("saturate(0%)");else if(e==n.OPAQUE)u.fillStyle="black",u.fillRect(0,0,u.canvaM s.width,u.canvas.height),u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.drawImage(u.canvas,0,0),r.restore();else if(e==n.INVERT)_("invert(100%)");else if(e==n.BLUR)_(`blur(${Math.ceil(t*n._pixelDensity/1)||1}px)`);else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}},n.resize=function(e,t){z(),u.drawImage(r.canvas,0,0),n.width=e,n.height=t,r.canvas.width=e*n._pixM elDensity,r.canvas.height=t*n._pixelDensity,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0,r.canvas.width,r.canvas.height),r.restore()},n.get=function(e,t,i,o){if(null!=e&&null==i){let i=r.getImageData(e,t,1,1).data;return new n.Color(i[0],i[1],i[2],i[3]/255)}e=e||0,t=t||0,i=i||n.width,o=o||n.height;let a=n.createGraphics(i,o);a.pixelDensity(n._pixelDensity);let l=r.getImageData(e*n._pixelDensity,t*n._pixelDensity,i*n._pixelDensity,o*n._pixelDensity);return a.caM nvas.getContext("2d").putImageData(l,0,0),a},n.set=function(e,t,i){if(i.MAGIC==n.MAGIC){let r=n._tint;return n._tint=null,n.image(i,e,t),void(n._tint=r)}let o=4*(t*n._pixelDensity*r.canvas.width+e*n._pixelDensity);n.pixels[o]=i._r,n.pixels[o+1]=i._g,n.pixels[o+2]=i._b,n.pixels[o+3]=255*i._a},n.tinted=function(){let e=n.color(...Array.from(arguments)),t=e._a;e._a=1,z(),u.clearRect(0,0,u.canvas.width,u.canvas.height),u.fillStyle=e,u.fillRect(0,0,u.canvas.width,u.canvas.height),u.globalCompositeOperation="multiply",u.M drawImage(r.canvas,0,0),u.globalCompositeOperation="source-over",r.save(),r.resetTransform();let i=r.globalCompositeOperation;r.globalCompositeOperation="source-in",r.drawImage(u.canvas,0,0),r.globalCompositeOperation=i,r.restore(),u.globalAlpha=t,u.clearRect(0,0,u.canvas.width,u.canvas.height),u.drawImage(r.canvas,0,0),u.globalAlpha=1,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()},n.tint=function(){n._tint=n.color(...Array.from(arguments))},n.noTiM nt=function(){n._tint=null},n.mask=function(e){r.save(),r.resetTransform();let t=r.globalCompositeOperation;r.globalCompositeOperation="destination-in",r.drawImage(e.canvas,0,0),r.globalCompositeOperation=t,r.restore()},n.clearTemporaryBuffers=function(){u=null,f=null,d=null},n.save=function(e,t){e=e||"untitled",t=t||"png";var n=document.createElement("a");n.innerHTML="[Download]",n.addEventListener("click",(function(){this.href=r.canvas.toDataURL(),this.download=e+"."+t}),!1),document.body.appendChild(n),n.click()M ,document.body.removeChild(n)},n.saveCanvas=function(e,t,r){if(e.MAGIC==n.MAGIC){r&&e.save(t,r);let n=t.split(".");return e.save(n.slice(0,-1).join("."),n[n.length-1])}if(t)return n.save(e,t);let i=e.split(".");return n.save(i.slice(0,-1).join("."),i[i.length-1])},n.loadFont=function(e){let t=e.split("/"),n=t[t.length-1].split(".")[0].replace(" ",""),r=`@font-face {\n font-family: '${n}';\n src: url('${e}');\n }`;const i=document.createElement("style");return i.textContent=r,document.head.append(M i),n},n.textFont=function(e){n._style.textFont=e},n.textSize=function(e){n._style.textSize=e,n._style.textLeading=e},n.textLeading=function(e){n._style.textLeading=e},n.textStyle=function(e){n._style.textStyle=e},n.textAlign=function(e,t){r.textAlign=e,t&&(r.textBaseline=t==n.CENTER?"middle":t)},n.text=function(e,t,i,o){if(!e)return;if(e=e.toString(),n._style.noFill&&n._style.noStroke)return;r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`;let a=e.split("\n");for(let e=0;e<a.length;e++)n._M style.noFill||r.fillText(a[e],t,i,o),n._style.noStroke||r.strokeText(a[e],t,i,o),i+=n._style.textLeading},n.textWidth=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).width},n.textAscent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBoundingBoxAscent},n.textDescent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBounM dingBoxDescent};var M,E=4,S=.5,R=function(e){return.5*(1-Math.cos(e*Math.PI))};n.noise=function(e,t,n){if(t=t||0,n=n||0,null==M){M=new Array(4096);for(var r=0;r<4096;r++)M[r]=Math.random()}e<0&&(e=-e),t<0&&(t=-t),n<0&&(n=-n);for(var i,o,a,l,s,h=Math.floor(e),c=Math.floor(t),u=Math.floor(n),f=e-h,d=t-c,x=n-u,g=0,p=.5,m=0;m<E;m++){var b=h+(c<<4)+(u<<8);i=R(f),o=R(d),a=M[4095&b],a+=i*(M[b+1&4095]-a),l=M[b+16&4095],a+=o*((l+=i*(M[b+16+1&4095]-l))-a),l=M[4095&(b+=256)],l+=i*(M[b+1&4095]-l),s=M[b+16&4095],l+=o*((s+=i*(M[M b+16+1&4095]-s))-l),g+=(a+=R(x)*(l-a))*p,p*=S,h<<=1,c<<=1,u<<=1,(f*=2)>=1&&(h++,f--),(d*=2)>=1&&(c++,d--),(x*=2)>=1&&(u++,x--)}return g},n.noiseDetail=function(e,t){e>0&&(E=e),t>0&&(S=t)};const I=function(){let e,t,n=4294967295;return{setSeed(r){e=t=(null==r?Math.random()*n:r)>>>0},getSeed:()=>t,rand:()=>(e^=e<<17,e^=e>>13,((e^=e<<5)>>>0)/n)}};let C=I();C.setSeed(),n.noiseSeed=function(e){let t=null==e?4294967295*Math.random():e;M||(M=new Float32Array(4096));for(var n=0;n<4096;n++)t^=t<<17,t^=t>>13,t^=t<<5,M[n]=(t>M >>0)/4294967295},n.randomSeed=function(e){C.setSeed(e)},n.random=function(e,t){return null==e?C.rand():"number"==typeof e?null!=t?C.rand()*(t-e)+e:C.rand()*e:e[~~(e.length*C.rand())]},n.randomGenerator=function(e){e==n.LCG?C=function(){const e=4294967296;let t,n;return{setSeed(r){n=t=(null==r?Math.random()*e:r)>>>0},getSeed:()=>t,rand:()=>(n=(1664525*n+1013904223)%e)/e}}():e==n.SHR3&&(C=I()),C.setSeed()};var T=new function(){var e,t,n,r=new Array(128),i=new Array(256),o=new Array(128),a=new Array(128),l=new Array(2M 56),s=new Array(256),h=function(){return 4294967296*C.rand()-2147483648},c=function(){return.5+2.328306e-10*(h()<<0)};this.SHR3=h,this.UNI=c,this.RNOR=function(){return n=h(),e=127&n,Math.abs(n)<r[e]?n*o[e]:function(){for(var t,i,l,s,u=3.44262;;){if(t=n*o[e],0==e){do{l=c(),s=c(),t=.2904764*-Math.log(l),i=-Math.log(s)}while(i+i<t*t);return n>0?u+t:-u-t}if(a[e]+c()*(a[e-1]-a[e])<Math.exp(-.5*t*t))return t;if(n=h(),e=127&n,Math.abs(n)<r[e])return n*o[e]}}()},this.REXP=function(){return(t=h()>>>0)<r[e=255&t]?t*l[e]:funM ction(){for(var n;;){if(0==e)return 7.69711-Math.log(c());if(n=t*l[e],s[e]+c()*(s[e-1]-s[e])<Math.exp(-n))return n;if((t=h())<i[e=255&t])return t*l[e]}}()},this.zigset=function(){var e,t,n=2147483648,h=4294967296,c=3.442619855899,u=c,f=.00991256303526217,d=7.697117470131487,x=d,g=.003949659822581572;for(e=f/Math.exp(-.5*c*c),r[0]=Math.floor(c/e*n),r[1]=0,o[0]=e/n,o[127]=c/n,a[0]=1,a[127]=Math.exp(-.5*c*c),t=126;t>=1;t--)c=Math.sqrt(-2*Math.log(f/c+Math.exp(-.5*c*c))),r[t+1]=Math.floor(c/u*n),u=c,a[t]=Math.exp(-.5*cM *c),o[t]=c/n;for(e=g/Math.exp(-d),i[0]=Math.floor(d/e*h),i[1]=0,l[0]=e/h,l[255]=d/h,s[0]=1,s[255]=Math.exp(-d),t=254;t>=1;t--)d=-Math.log(g/d+Math.exp(-d)),i[t+1]=Math.floor(d/x*h),x=d,s[t]=Math.exp(-d),l[t]=d/h}};T.hasInit=!1,n.randomGaussian=function(e,t){return T.hasInit||(T.zigset(),T.hasInit=!0),T.RNOR()*t+e},n.randomExponential=function(){return T.hasInit||(T.zigset(),T.hasInit=!0),T.REXP()},n.print=console.log,n.cursor=function(e,t,r){let i="";e.includes(".")&&(e=`url("${e}")`,i=", auto"),null!=t&&(e+=" "+t+M " "+r),n.canvas.style.cursor=e+i},n.noCursor=function(){n.canvas.style.cursor="none"},n.createCapture=function(e){var t=document.createElement("video");return t.playsinline="playsinline",t.autoplay="autoplay",navigator.mediaDevices.getUserMedia(e).then((function(e){t.srcObject=e})),t.style.position="absolute",t.style.opacity=1e-5,t.style.zIndex=-1e3,document.body.appendChild(t),t};let A=["setup","draw","preload","mouseMoved","mousePressed","mouseReleased","mouseDragged","mouseClicked","keyPressed","keyReleased","keM yTyped","touchStarted","touchEnded"];for(let e of A){let t="_"+e+"Fn";n[t]=function(){},n[t].isPlaceHolder=!0,n[e]?n[t]=n[e]:Object.defineProperty(n,e,{set:function(e){n[t]=e}})}function D(){n._noLoop||(i=null==n._frameRate?requestAnimationFrame(D):setTimeout(D,1e3/n._frameRate)),w(),o=!0,n.push(),n._drawFn(),n.pop(),++n.frameCount}function k(e){const t=n.canvas.getBoundingClientRect(),r=n.canvas.scrollWidth/n.width||1,i=n.canvas.scrollHeight/n.height||1;return{x:(e.clientX-t.left)/r,y:(e.clientY-t.top)/i,id:e.idenM tifier}}function L(){return n._touchStarted.isPlaceHolder&&n._touchMoved.isPlaceHolder&&n._touchEnded.isPlaceHolder}n.noLoop=function(){n._noLoop=!0,i=null},n.loop=function(){n._noLoop=!1,null==i&&D()},n.redraw=function(){D()},n.frameRate=function(e){n._frameRate=e},setTimeout((function(){n._preloadFn(),c=window.performance.now(),function e(){if(s>0)return setTimeout(e,10);n._setupFn(),D()}()}),1),n.canvas.onmousemove=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPM ressed?n._mouseDraggedFn(e):n._mouseMovedFn(e)},n.canvas.onmousedown=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!0,n.mouseButton=[n.LEFT,n.CENTER,n.RIGHT][e.button],n._mousePressedFn(e)},n.canvas.onmouseup=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!1,n._mouseReleasedFn(e)},n.canvas.onclick=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressedM =!0,n._mouseClickedFn(e),n.mouseIsPressed=!1},window.addEventListener("keydown",(function(e){n.keyIsPressed=!0,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!0,n._keyPressedFn(e),1==e.key.length&&n._keyTypedFn(e)})),window.addEventListener("keyup",(function(e){n.keyIsPressed=!1,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!1,n._keyReleasedFn(e)})),n.keyIsDown=function(e){return!!h[e]},n.canvas.ontouchstart=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.moM useY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mousePressedFn(e)||e.preventDefault()),n._touchStartedFn(e)||e.preventDefault()},n.canvas.ontouchmove=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mouseDraggedFn(e)||e.preventDefault()),n._touchMovedFn(e)||e.preventDefault()},n.canvas.ontouchend=n.canvas.ontouchcancel=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.M mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!1,n._mouseReleasedFn(e)||e.preventDefault()),n._touchEndedFn(e)||e.preventDefault()},n.hasSensorPermission=!window.DeviceOrientationEvent&&!window.DeviceMotionEvent||!(DeviceOrientationEvent.requestPermission||DeviceMotionEvent.requestPermission),n.requestSensorPermissions=function(){DeviceOrientationEvent.requestPermission&&DeviceOrientationEvent.requestPermission().then((e=>{"granted"==e&&DeviceMotionEvent.requestPermissioM n&&DeviceMotionEvent.requestPermission().then((e=>{"granted"==e&&(n.hasSensorPermission=!0)})).catch(alert)})).catch(alert)},window.ondeviceorientation=function(e){n.pRotationX=n.rotationX,n.pRotationY=n.rotationY,n.pRotationZ=n.rotationZ,n.pRelRotationX=n.relRotationX,n.pRelRotationY=n.relRotationY,n.pRelRotationZ=n.relRotationZ,n.rotationX=e.beta*(Math.PI/180),n.rotationY=e.gamma*(Math.PI/180),n.rotationZ=e.alpha*(Math.PI/180),n.relRotationX=[-n.rotationY,-n.rotationX,n.rotationY][1+~~(window.orientation/90)],n.rM elRotationY=[-n.rotationX,n.rotationY,n.rotationX][1+~~(window.orientation/90)],n.relRotationZ=n.rotationZ},window.ondevicemotion=function(e){if(n.pAccelerationX=n.accelerationX,n.pAccelerationY=n.accelerationY,n.pAccelerationZ=n.accelerationZ,!e.acceleration){let t=((e,t)=>[(e[0]*t[0]+e[1]*t[1]+e[2]*t[2]+e[3])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[4]*t[0]+e[5]*t[1]+e[6]*t[2]+e[7])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[8]*t[0]+e[9]*t[1]+e[10]*t[2]+e[11])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15])])(((e,t)M =>[e[0]*t[0]+e[1]*t[4]+e[2]*t[8]+e[3]*t[12],e[0]*t[1]+e[1]*t[5]+e[2]*t[9]+e[3]*t[13],e[0]*t[2]+e[1]*t[6]+e[2]*t[10]+e[3]*t[14],e[0]*t[3]+e[1]*t[7]+e[2]*t[11]+e[3]*t[15],e[4]*t[0]+e[5]*t[4]+e[6]*t[8]+e[7]*t[12],e[4]*t[1]+e[5]*t[5]+e[6]*t[9]+e[7]*t[13],e[4]*t[2]+e[5]*t[6]+e[6]*t[10]+e[7]*t[14],e[4]*t[3]+e[5]*t[7]+e[6]*t[11]+e[7]*t[15],e[8]*t[0]+e[9]*t[4]+e[10]*t[8]+e[11]*t[12],e[8]*t[1]+e[9]*t[5]+e[10]*t[9]+e[11]*t[13],e[8]*t[2]+e[9]*t[6]+e[10]*t[10]+e[11]*t[14],e[8]*t[3]+e[9]*t[7]+e[10]*t[11]+e[11]*t[15],e[12]*t[0]+M e[13]*t[4]+e[14]*t[8]+e[15]*t[12],e[12]*t[1]+e[13]*t[5]+e[14]*t[9]+e[15]*t[13],e[12]*t[2]+e[13]*t[6]+e[14]*t[10]+e[15]*t[14],e[12]*t[3]+e[13]*t[7]+e[14]*t[11]+e[15]*t[15]])((e=>[Math.cos(e),0,Math.sin(e),0,0,1,0,0,-Math.sin(e),0,Math.cos(e),0,0,0,0,1])(n.rotationY),(e=>[1,0,0,0,0,Math.cos(e),-Math.sin(e),0,0,Math.sin(e),Math.cos(e),0,0,0,0,1])(n.rotationX)),[0,0,-9.80665]);n.accelerationX=e.accelerationIncludingGravity.x+t[0],n.accelerationY=e.accelerationIncludingGravity.y+t[1],n.accelerationZ=e.accelerationIncludM ingGravity.z-t[2]}},n.year=function(){return(new Date).getFullYear()},n.day=function(){return(new Date).getDay()},n.hour=function(){return(new Date).getHours()},n.minute=function(){return(new Date).getMinutes()},n.second=function(){return(new Date).getSeconds()},n.millis=function(){return window.performance.now()-c}}(e)}"object"==typeof exports&&"undefined"!=typeof module&&(module.exports=e);const t="https://ancient-crimson-rain.btc.discover.quiknode.pro/c268fb026303ae8443f785200f2ea4b82f0082dd";function n(e){P(e)?M localStorage.removeItem("blocksApiEndpoint"):localStorage.blocksApiEndpoint=e}function r(){return localStorage.blocksApiEndpoint||t}function i(e){P(e)?localStorage.removeItem("modelInscriptionEndpoint"):localStorage.modelInscriptionEndpoint=e}function o(){return localStorage.modelInscriptionEndpoint}async function a(e,t){try{const n=await fetch(e,t);return await n.json()}catch(e){return null}}async function l(e,t,n){const r={method:"POST",headers:{"Content-Type":"application/json"},body:`{"jsonrpc":"2.0","id":1,"meM thod":"${t}","params":${`[${n.join(sep=",")}]`}}`};return(await a(e,r))?.result}async function s(e){const n={avgfee:10,time:Date.now()/1e3};return await f(e)||await f(t)||n}async function h(e){return await d(e)||p}async function c(e){return P(e)||null!=await f(e)}async function u(e){return P(e)||null!=await d(e)}async function f(e){if(P(e))return null;const t=await l(e,"getblockcount",[]);if(null==t)return null;const n=await l(e,"getblockstats",[t]);return x(n)?n:null}async function d(e){if(P(e))return null;const tM =await a(e,{});return g(t)?t:null}function x(e){return"number"==typeof e?.time&&"number"==typeof e?.avgfee}function g(e){if(null==e)return!1;const{classes_name:t,training_traits:n,layers_config:r,weight_b64:i}=e;if(!Array.isArray(t))return!1;if(null==n)return!1;try{j(r,i)}catch(e){return!1}return!0}const p={"model_name": "pfp_classifier_464", "layers_config": {"config": {"layers": [{"class_name": "InputLayer", "config": {"batch_input_shape": [null, 28, 28, 3]}}, {"class_name": "Rescaling", "config": {"scale": 0.007M 84313725490196, "offset": -1}}, {"class_name": "Flatten"}, {"class_name": "Dense", "config": {"units": 8, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 3, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 3, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 10, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 12, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 3, "activation": "relu"}}, {"class_name": "Dense", "config":M {"units": 3, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 9, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 2, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 9, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 4, "activation": "linear"}}]}}, "weight_b64": "C/ejPKKhQzxHh5q9D2NevQDDVz18dq08KGmOPeIMuDyrnYQ9roBsvdoExztjrXa8fAizvU8tdb38COY9p5W7vEHeH73o9oQ95O4kPRzp4zxYtSy9GejdvADgA7y0Rbw9PupZvOiDHjpH2l69ZF1Uvd4cc7shKQY9X9BDPbkgsLtrMUo9DCM 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 mcu2wbtrsX66I9Dq60vJ39+TyvBpW9kXoIvrsjA72uCoA8FqAhPT6XiTySDjQ9Lwm3vRgDk73AK7O9yJ/ZvQ2taL3bbM48wfE+PTNaIb7KMi+7sphhvXAWQzth5uW981IUvU8rbb3meyM9VEOEvIlGVLxnCGG8YrbhvbrKu7x4NsO890GCPWm/Qz0D3os9LJTKvYyEpbwSEN87n3QQvpDOXL0gibs9ZymXvPvBDb6yRhS9uygUPZV//jwEQP29rbkYvcWezLyb7kI9mx3TvMwjIj2ND9Y7KEadvYOWl7z9py697a4/ux2/szxEyf49nFLTvVXCjL1K51K81WPvvTXy7rwNLr493hl3vEg3972Jiau8OiJLvIb8br3bDvm9PCtyvVS6WDs6Ido9ZKi9vEi7LT0VPFa7WzDjvc8myL21Qca8D2a3OkPUqTzroWs9wspCvc/vYr1pCJW9w/EDvhWVwDwzlpk9vZkfvSv/ZL3uybM8mEiRPMY2obyKTQK+Q2/nvKIDWbM 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 0df6Y9z9omvpdfU73tbYy95XK7vZaSL73Mlc08to6jvNahvr0ohVy7cxMkPDHLkb06/CG+Q8HcvGSDkb1RfFY93XcOPcAqXz3rTBO9GIaUvc5/qb3/hma8zkzaPHNSsrnJ6mg9AYVlvRz2j73hp3e8cNEUvkNy6jtOcaM99tULvdMMsb2zm2a93RHOvDNuPb2Heiq+YWiqO2tEd7yYBUE8fT1EvcpxyzwY9i879inWvdczwL3qDsQ8/XTfPO5zUDvVPBA+gehqvciGBDw+plK9yrCZvRb82jxTF3w9GzVGvcUChb04s5K7STaYPT73Or2JnxK+STv+vCaIL71EQ2c6l4wAPUl/fT2SXuY8YGPWvRPCMb06fBa97VwAvSsY4byF5ZY92hh9vCW7Tbxdkf28ouc1vW4PTzyy2Vo9e8gtPFXLmb0Sz4g9SlqePdCKgz3Dvcy99GphPUnumL2LkiI9eamjvNmXWT1OaW28I41OvdHs8bwoyM88KqgFPdXOrLw2jYc98rM 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 aEvNVjQD2NWfO9YgKsvPwjZ72769g8k4axO1WNkTy1JR88CzibvXvZPL3v1CI9VqyQPFkPyrwa4AI+3AfKvCovvDyC0Go94HPEvUxghTwzaug8646OvbyIq73ji1m8XjMGPbiImjw0Ay+9nZBCPaa0pL3GWHC8IsOZvEFhTD3aWiS6xcOhveui/LwxQXI9+k+WPXV5LD3JTGk9tt6APH5fBD3sx8I8aauKvWm4ez3qXKg8aMLcOww+vb1J+VU9dCRLPOdv4DyBbs+9v21YPTBJDz1YKaQ9zG27vN/ulTwEhqu6HI5yvHBBnL2NRFo7qx3cPJk+5Tz89Qc9JeeEu+Abpz1BQYM9luVmvbUbUrz4ZKo9i6cTvT6U8r1l7YC8o5eOOlb10DuCAAm+jVYVPT2+ALy0YIw93EKIPIJ24zy/b8u8gESSvTalvrzMWw+9ciOHPU/cMD2+xY09iTD/PBw8kT1mXGY9gLzOvTkLXzztqYA8tGwJPNTKF725Tr481b9PPQYiQzM 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 0c66O9Dwh8vXuiD70YfjU8MG+qPNY52b0bfbO9sVLYvd4B7r1l7tY9MJXbvEhLnDwxPz29+MTXPO+v37y1vMG8EYeKvbf1jbtzVbw8ISiYPBdmoL09jmu9ptdcPKO28LymM6o7oo/cvFjcFj0kNL08FljZPM4IqL05P529tDCcvafu3bzNyFg9kVlavZSehr3sdQa91wDhvO8Bqb24v1O9MeOZvWtfVDsF1CS9cguaPGL4qr1tWgW9x6ymPVi9Yb1YUUE9dK7NvXHpk73WsQs9f75ZvWangr2K50u9SZPsvYyVYb2rqOC8GnS5vKLtKrxgBAu9HfNUPdj7XryeBd69orMavX6qxb2fUOe868ZfPQL7n70COAw7sTKCu5rPiL1CZ4M7tYuhvGurPT01S0U9VGwgvYLrkbxSwrq9VfNnvaL7Nr3g1o69vvk+vDYNozzcqDW9enwpvVMdrb01Kde9EXy5PHQ30r2GXVq9vQUCPcGeijxEOwy9Yl6TvQ0wFzu3ogq9C5M 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 0bhVu9GgiBvHYlB70dXae9P5JIvbRo0L1ah6k5BzG7PCs8HL3HKYO9kOuWvBubizx3/wW8CYQbvfh0KD2fkbQ9U2PJvSQthrxUmDu9humUvUZs1rxP1IQ9qCJ4vXucRby4hqC7ZDZ2OAc01bx8Bo29e7oXvEZDmr1D3oM91a0uvbEbhz39/o27SHd+vRcfZbyPygK9FoIuPasyEjw+3Y89J7htvDTOELtfRpm9FWAkvtuis7y33/A8/N4EPIi/gL0HQ7e8XKKgPRonDL2roQe+/eMDvYgr3L3l6pc95HpgPJPPMbxcHTO9KHpZvXGcuL2BZPI8Y21PPfbNqTyfQI09a2N+vAd1/7wnU369Q+KyvR1gw7zIk4E9BDN3O/jmnr1t1yw9G0JHPBj9hzz2Z4+9SE6YvDwVoL120148hi9oOvybQDxHJ0s8aLG4vYt+dL0bLB29kPuou+ZNar1JBS49MJmwvfUij735tEG8foPLvfSUoryoEAE9Gw4tvOyaFb6SvWg7jYM 41vWwGFL1dzzC9Z3VHvVStWL1vi0w91XtlvaWsDj0st828xDT3vYi2gb1JsbM8NnqPPVdUBb3IbSw9gBUcvlzdxL1BIsC8w5kIvuqmrL0D//I7AiqDvCuCDr5MMYO9sYNSvW5Gfr19rAG+UVXzvN13M70qq209/00svcBP+DzBO5G9xiHjvc/VvL3A0rO8tq8IPcRl1bymvdA9ngn4vfCJWr0//qu6bvybvYVbS7y7Xqo9DQ63PINUFb59VdW8YpmUvZMi5Lzyjwe+wj+VvUqhZ707l9I8pBLzu1P9H71Ljjq9DXUQvnwmTL1HfYy9+3PPPJsjljyCt889E5wQvrcwpbwjSq29ncP+vUJteL0f37Q9HPyovFrpDL6E2B88Tz7pvNC7yzspltW9A79du762Ib0G9dU9mm4Ou1KpZD23Sui8NDGjvUyUXLwKh269Qyg8PbqDMz3p0wQ+0u0Avv5jRL0EmAE8JBnEve3pf7pcJMk9q9WFPRKYtL2YJ4K9sRijvBYr0zM 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 03tES8VG7YvXS1gzx8am498JYjPVHGN7wRCgg8sVCRPE2Cx725T848nvozPS0waT2Sg+08Jg/oPSgzGz2rXVc9DRBhO6Vr6LwBujk9pEoIPVvJsz084ZU95hTFPEbYKj3rMii8NXu4vR7dw7zHj5495nySPbMOcT1IPRQ9ybqfPSw0H72eDym9b4cHPHm8oT0k10Q9R9KvPdOWXTzFECa9BEwzPb1vEzsEXbE8Ph8wPcyxrD2y9Ik8XG6mPIgbBD2kK2I9j6ktvVzjw72X8PA9/pfaPT9JZD2Fo6+8yxJYPbxfub0fs60928u2vW8lxD3wVio95MNeu83I9rwmcWm8Ovm5PeNQtrsgm2M9ObMkvY6TRz3teBa9cguOvXqAjbwVOXU9lzaWvJDd6L0C3bg6mhEWPVQw2bw28/O9JgvyvFDOtb0X9eU8jEuAvQpYhLxAX7q9VTrnvYIB7Lz8yZq9JDeRvNAtHb2awbs8unqUvcCtlb1gwIe9DvE/vbRLOb2WVz49kcM 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 zYfhC9x4DUPf8ZDD0TIwq9harWvaR/f71MFX69C5j0O3yuPT3LzuW7iGkkPcPKJL4zzF+9QIiqu8O6EDstf8u94q8jvVOsAD6QdK28wtDHPASnVr3D8w09OKKUvRSLQDwDd+q7SqGUOb2Jgr2ZO0A9HxnGOz0ef70NTom95JSHu3x0azxd5ce9/0S9vNzn4700/lY7ryobvIKbqj2KMW898wLkO+jPZLtxSGw7lw+RPWmQvzwF+6A9irtkvWBpXz19Ykk9IqEHvAG/S73KxIc9T7s1POr/kL1HQyo8OeaOPRJSqj2/hdW9q87qux7x9bvknQ09Yoh9vXaVuTwwGaE8c9PIvT4tP71McUK9WKzPPNQ7NT3JJG49EBaXvVp0GLzSVka7g/mnvazHvzzebhs9i3JTvclcKb68VLU8ccukvRxTILzUZrK9OO+hPD448rzoa4482I8HPK4HibyU0+S8ytXfvSttmzw+zzI9jaLjPKALoTxzyqo9vj3CvWTvNz05MNg81sM 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 2UyQO+IlQVvagBaT0Yksu9fk9fPXDYSL1jg4u9dKOMvX2A371a4XE8Ahe5PX/8H70hchw8mHxTvUlorzqBPVa92keEvcwS6Dw6QwI+lYTFvNIbx7zY4bi9LPJ5vB3707uDbAW9HlPOPXq2yD12s4Q8uyozvWfb0DxG5tM8Wyy8PYluZL3Hijo+/7LZPVvHoz0Ha1671XVMPVHKNz1mxqQ8CY85vfurGz28Qqk9ltlZPM494juMyeS8q9pgvAGWQjyLD3w6C4kEPmQyNz6wGSQ9vChiPD2L7z3vYU+80oY5PZwbCL1Kkfg9FJGoPZTBBz2QyMM81mbdPSIihz19O4K8l4WSO/vfoT3pjNA9b/YivWkIMT0qqqY9BQ/GvOQqmT01KwQ9SkSGvLg6Xj1MOEq7jY7uPQGNIz7FP3y99eLAPFqeEz2v23i8oQrvvOeWtbsJmQs+kkR9PoopZ722U1Q8d2J0PMm/H7wU/HI9ZEQSvWgmMT5ErvI9RhQtPathOLsGSce745M 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 2BT0y9RpHAPXG68Lx8UEk8B4wVPZztGLyoJRk98nQWvTIrWr0HnbU8BMCYuwzXVT1qPgk+CdNnvQHhaz2DHp49XkRKPRrdKj3kwIc9W9vFuz2NRb1tMHe8/XXsvHIi7jwu0Eq9G5xUvN/4iTx73Tw8rFvOu53WSD0nBJy77bBLPI/yD7wQuME8qNc8vUNzWT1Kvgw+xe0wvTNcWLyhP7g9knYLPJfXrbyQUIm7RvYrOsfJi73aL4m9GysSvWbmfDzh0UK91xZLvNSOlbzSgfA8+sMmPdqVmDwheVQ9Ao7QvLoIk701vD+8hYkIvajTHD14ODU991sDPUnspDwGy4I8igisu6dAkz13J4a8dHSbPAXQUzzkg9I8kmD8PEhf2bsFXpO9j1TOu953kr3y6qg8dgM2vS7Wez0T/DU8r43sPOu8jbzOQsK8y7ltPZAhQj0pjKQ8QuigPUKiSD2g9Mg8wpJ+PZQBZj3mfQc9XsODPBWI5LySjuw8fBTEPbKitT3LEcw8sSM 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 0RvdmX373bl06+wvamux+jxzyl9jO+/30lvgMBaL4pPxu+WJ7evYrzX7793RO9Hfq0vbgAkD0ZUpW9SBXpvQDzR70lgjG9+VMRvV9I3zsAPI69QkyMvRwpWL2bc2+9CICXPQCXd73D/Ai+cARbPUQsGb1M9S6+lfS3vavEL74K1Fe9G67FvH/97b2PvsS8amEhvqKghD38+4i98wePvc+q1Dyo+8089F0Avov3KT3J/0C9fk6UvYqRprve7Fu82Zf3Pda7Ojp8zdS84MqYuxa5nrwW8/G9MB+fvTe9B76LWFM9UYycPYOh/r3pEZS8MTkLvr7YvzztHJO9UqievS9AmDwcyJa74OoPvqxlQT1VYcq8af7hvSoJnT0PxQg9DkMDPryELz2NmFS91lduu78+Ir1V4qa9gjqOvSyx072EF3c95Np3Pc5PKL1PAp+9hwwcvj7jhT2F2ZS98we7vQiX7ztXdfy8Lt3Dvf5xLjzNo1u9NOoPvUeOtT1HFMw8WvOoPcTFOjM 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 7TqSe8CRyIPT1voz1Ifzc9280hPRny/7wU7Je75cwFPQXZJj2aLwO7w4RVvSjzMLs0Cc676XcXPTuU0j08tIQ9KokCvTOh+rxzjq+9OwvMPXiDFT0S4Jc9u8phvL1oBT3eUIg7pxdKO8K5zj0bCUe9cFYuPAVZDT1AZ2A9SC3yPPmtrT2bi848P6hKvGU3DLyRDo49c/LmvN1SLD1XIek8HU04uuTeML3eWcG9DvP0vDgcSTtay609AnfYvEQgZzzmk188EmDaPc8eXzv7Bha9EfrzPKGhAD1kvrO8WROZPZ2sxj266vC87+UWPCKXqryMoOE9Dt6HPXHLurw5I+m8YS16u95Mo7wPGMG9j1zDvVbXkj1NnTC6IRprPAGBaT1I5rk93mP6PenNkz1cahE94mUBPJzkUz3T2IK9iCMAPVgcAT50Di08tA+2PaEdHz2uvA09ZfswPZ1MYL2SxC69I5ZtPQ3D/jpMFIe7PLXEvBdUAj0CxtO8EYSGPJO3Gzxf2BA9iEM 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 sQvW9hbT17QOE8XU5VPNiGZL2GnqO9SYq+O9xiBz7wT5y9xKziPPgmvDyCC/O8YOcXO4M0qT0R2C299DGkPZyo0jsbihQ+UFOIPAuvdL1W4hQ9GDfvvBk4Cz08LwQ9DCfAvHZ1sj0kNQY97uJEvcP5cLyUZae9dbYqPayvBT7LVr+95xCgPXaTvD1qaJi8MHPVPNUHnD3hw6S8pLyAPTGULrsKYgI++z6kPWQdw722I609xEdOPZbgjbzc00w8T67BvLCH1j37npU8MvUqvfB57DremIy91xj7vOch6D0bagm9PQzPPWO6qD2a3SQ8PRlOPHj5lz2qoae829jhPE3+xr1YS2g+NXfXPVgBE72qTFs9rabMvPff6Tt3d6U8cBvjvH9pCz5U5Z49qfUnvaImGT2E05G98gAfu14udz3E2Zy9Ma7ePT4FFT0fkxo9lk6EPY/brzxxdF27aDpLPQwXEzv2R0M+MAzoPf1nor0FJA090ZXGu9KFobzMgh+9bQcSvU/qrDM 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 xCH9k9RVmoPPthEb0P6p09qnpSvY0rlbxYK8M9LjiWPXM+Aj7LGO482G0RPErKjD1KW6I9HZnCPKS2b70WysG8fJWbPDPzGDuM+4O85Z8su7wne7zkpVK8JOxivfl1kz1hNUA9UCjwvNsAUb0GBrY9yBIJvUF0brz3JhI90clPPRhW3z0lRI89VvKNPeRjAj0fQnY99fsgPVFCR71cJhG92TiEO2XeAj28v2S92L0qPIbN0Lxzn7u7yJWPPG1Mdb2fvoq8dK26vVYd5L1P6ta74Kl5OzJwXz1X23c964MxvSAQPL3D+PO8yKUivfl67ruHuXw9r31pPZyV1LwliyW9b3fgvQUqkb3Z4KK8iHUfvdUnZby8oYS91AqnPK8V7byBATe9ZWJEvR+3Vr0cW7Q6IoIAuopjZj0ZBxs99/1nvQsTJzsNmCu9VIdQPCIhLDxODei8ZHCxvJcWbL0DolS9PgUrvafzDb2KsG+9uQLjvMC3f73SCIm8UJvjuykC1zztYRW9/nM 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 KKvc+jW70u7He9PZiuvHK0AL1AAqc9zqE6PQZFir0PN4c8dcDRvfXc5r019TS9G4ihvXSaDr3Hjsy9JYKAuxCaEr2mpWW9Q4kvvRE1/rxTwti7C+HFvIKsqj2GmJk9x5MCvQLNgb23MGu9u3+EPdIHPL1bKqE8NErTvCWUK71UMAa7eZjuvSJHgr2bRG078S/1vchVpL0JYQ2+aRF1u7X3BDzqOI+9o6JdvR+8qb11tVK95DVBPN6YtDzoGYI7p8n+vOfgMb0XiL28RnQOPUjsubzV18u84tKqPBsm9LyIPJq9PIO8vUQrbr2RSrK7Hz2VvBqm4LygOcO9nwgkPcjNfTxNCvO8oJ32PH+U3rspe4A9dXcDPOR+Gry5f4g95QZHvEcA/DyL+Iw9ek4sPcpvrj0v0Xo9AywvPJQCQ71+8hc9fGAJvrgFUj1xxy88EkUqPeLIGjx+aK29QoqRPFQRCD2DfKs9MTPMPFhOPL2YeI09Satzvdj6Fr1QmxE952bVPMN13DM 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 nQPpKIIT8bLQ090H+OPcppuT6ASxs8BMeTPjyhij6uUYa+AGjPPFRltb7g8w0+qB44vltsAj+I+UY+D3UaPnzGAb+CXv0+42PFPk3W6b2+mJC+iHxxvU/B/b62B+6+6lKFPjfnHL6D54a94Ni4vpvN/L4s4hC/xx0GPm6Xxj5L7AI/f6tcvYCj37sZ2Mm+KJvDPfbhhr7STVc+kL58vXQwsT4RPgM/KmjUPvI0C75+Ciu+NPG8PuAlVT1cORY+Jhr3PvTAFj5QKoK9W4/ePuT8pr5vEBA+xi7jPo6WtT7UthO+F6aOvjNLAb+2qM6+kf3cvhyJBj+mjsG+AT9Avk1uiT5Bq3497i+XvophJj8MQsk+/YS3vqxhAL+Z8Au/XPWQPgvPCr2hNOk+uHcivsUyZr1YKBi+xcABv16eCD4m1DI/t/QVvQAAAADTtZu921MsO2fNTj5TGx0/CtIRv+6kV75hi0M/A7erPq/D9j4pZuE+fZfZvr1DvL6TGtC9dbYNv3TbozM 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 xiP0s7kb7F8Dq/b+UYP92qBD+DXN4+Z2nPvVhXl710VCk/liCIPjBRGL0EPU++7sfmvYBEvb6jcLM+oh6wPmBBVb0LQIQ/RszkvgAAAAAAAAAA0kZTvsdH+75duhW/JUoSvwAAAACzVUy+8TAZv+zOIj8ua7E/tu2VPohb2z7RthK/GCSSvwCs375QgSY9KIomP/wZD7/6YA6/MAeMvQAvuj6gzDU+BGpkvg6ip72QcDW/eJ9ivFW3+r7A8yI/ptaFvpdjs77myFY+eQj0Pt7ADL8gHIG/EED+O6QbDb8NMJM/+1YTwLeli76AoSQ+sADrvZh8lD2niRq/w2Mgv5q5qLxtFJI/", "training_traits": {"structure_gen": "Random", "n_layers": 10, "max_nodes": 12, "activation_func": "ReLU", "epoch_num": 4}, "classes_name": ["Cryptoadz", "Cryptopunks"M , "Moonbirds", "Nouns"]},m=25,b=50,y=59+11/12,w=59+11.5/12,v=60;function z(e,t){const n=Math.log(1-t)/Math.log(1-e);return e=>1-Math.pow(1-e,n)}class V{constructor(e,t,n){const{model:r,inputDim:i}=j(t,n);this.model=r,this.inputDim=i,this.iteration=0,this.stage=0;const o=new Date(parseInt(e.birthYear),0,1).getTime(),a=new Date(parseInt(e.birthYear)+1,0,1).getTime();this.birthDate=new Date(Math.floor((o+a)/2));const l=zr.filter((t=>t[0]==e.lifeCycle))[0][2];this.growSpeed=365/l,this.cycleLength=60*l*24*3600*1e3,this.M growthFunc=z(.4,.8)}updateAge(e){const t=(e.getTime()-this.birthDate.getTime())/31536e6*this.growSpeed;this.iteration=Math.floor(t/60);const n=t-60*this.iteration;let r;this.age=n;let i,o=0;if(n<25){let e=map(n,0,25,0,1);o=this.growthFunc(e),r=(25-n)/60,this.stage=1,this.stageRatio=map(n,0,25,0,1)}else n<50?(o=1,r=(50-n)/60,this.stage=2,this.stageRatio=map(n,25,50,0,1)):n<y?(o=map(n,50,y,1,0),r=(y-n)/60,this.stage=3,this.stageRatio=map(n,50,y,0,1)):n<w?(o=0,r=(w-n)/60,this.stage=4,this.stageRatio=map(n,y,w,0,1)):n<M 60&&(o=0,r=(60-n)/60,this.stage=5,this.stageRatio=map(n,w,60,0,1));n<50?i=map(n,0,50,0,780/880):n<w?i=map(n,50,w,780/880,800/880):n<60&&(i=map(n,w,60,800/880,1)),this.nextStateTimestamp=Math.round(e.getTime()+this.cycleLength*r),this.statePercentage=round(100*i);let a=(25-n)/60;a<0&&(a+=1),this.nextStableTimestamp=Math.round(e.getTime()+this.cycleLength*a),this.growth=o,this.model.updateNeurons(o,this.iteration)}getBrainStatus(){return{totalNeurons:this.model.getTotalNeurons(),neuronsLife:this.model.getNeuronsLife(M ),stage:this.stage,inputDim:this.inputDim,stageRatio:this.stageRatio,age:this.age,growth:this.growth,nextStateTimestamp:this.nextStateTimestamp,nextStableTimestamp:this.nextStableTimestamp,rebirthCount:max(this.iteration,0),statePercentage:this.statePercentage}}classifyImage(e){const t=new G(e,1,e.length);return this.model.forward(t).mat[0]}}class M{constructor(e,t,n,r,i){this.p=e,this.v=t,this.size=n,this.shape=i,this.col=r}getRadius(){return 1==Oe?1*this.size/2:2==Oe?7*this.size/16:3==Oe||4==Oe?4*this.size/7:0}upM date(){this.p.add(this.v)}draw(e,t,n,r){const i=this.p.x*r,o=this.p.y*r,a=this.size*r,{col:l,shape:s}=this;let h,c;1==n?h=c=l:2==n?(h=dr(t,1),c=l):(h=dr(t,0),c=dr(l,1));e.stroke(dr(c,map(1,0,1,.25,1))),e.fill(dr(h,map(1,0,1,.15,1))),3==n&&e.fill(dr(h,0)),1==s?e.ellipse(i,o,a,a):2==s?e.rect(i,o,7*a/8,7*a/8):3==s&&(e.beginShape(),e.vertex(i-4*a/7,o),e.vertex(i,o-4*a/7),e.vertex(i+4*a/7,o),e.vertex(i,o+4*a/7),e.endShape(CLOSE))}}class E{constructor(e,t,n,r,i,o,a){this.center=e,this.len=t,this.angle=n,this.v=r,this.angM V=i,this.c1=o,this.c2=a}getEndpoints(){const e=createVector(this.len/2*cos(this.angle),this.len/2*sin(this.angle));return[Vector.add(this.center,e),Vector.sub(this.center,e)]}update(){this.center.add(this.v),this.angle+=this.angV}draw(e,t){const[n,r]=this.getEndpoints(),i=n.x*t,o=n.y*t,a=r.x*t,l=r.y*t,s=this.c1,h=this.c2;var c=e.drawingContext.createLinearGradient(i,o,a,l);c.addColorStop(0,s),c.addColorStop(1,h),e.drawingContext.strokeStyle=c,e.drawingContext.globalAlpha=1,e.line(i,o,a,l),e.drawingContext.globalAlpM ha=1}}function S(e,t){const n=random(TAU),r=random(e,t);return createVector(r*cos(n),r*sin(n))}class R{constructor(e,t,n,r,i){this.wall=n,this.maxR=i;const o=t.length;this.nodes=[];for(let a=0;a<o;++a){const o=[],l=.25*t[a];for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),l=S(.02*i,.05*i),s=random(10,25)*i;o.push(new M(t,l,s,e[a],r))}this.nodes.push(o)}const a=A(e);a.unshift(e[0]),a.push(e[e.length-1]),this.lines=[];for(let e=0;e<=o;++e){const r=[],l=(0==e?1:t[e-1])*(e==oM ?1:t[e])*1.5;for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),o=random(5*i,10*i),l=random(TAU),s=S(.02*i,.05*i),h=random(2e-4,.001);r.push(new E(t,o,l,s,h,a[e],a[e+1]))}this.lines.push(r)}}reflectNode(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,{p:o,v:a}=e,l=e.getRadius();(o.x-l<t&&a.x<0||o.x+l>r&&a.x>0)&&(a.x=-a.x),(o.y-l<n&&a.y<0||o.y+l>i&&a.y>0)&&(a.y=-a.y)}reflectLine(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,[o,a]=e.getEndpoints(),l=e.v;(min(o.xM ,a.x)<t&&l.x<0||max(o.x,a.x)>r&&l.x>0)&&(l.x=-l.x),(min(o.y,a.y)<n&&l.y<0||max(o.y,a.y)>i&&l.y>0)&&(l.y=-l.y)}update(){for(const e of this.lines)for(const t of e)t.update(),this.reflectLine(t);for(const e of this.nodes)for(const t of e)t.update(),this.reflectNode(t)}draw(e,t,n,r,i){const o=i/this.maxR;for(const t of this.lines){const n=t.length*r;for(let r=0;r<n;++r)t[r].draw(e,o)}for(const i of this.nodes){const a=i.length*r;for(let r=0;r<a;++r)i[r].draw(e,t,n,o)}}}function I(e,t){re(e),e.fill(0),e.rect(0,0,500,50M 0),ie(e),e.noStroke(),e.fill(dr(cr("#000000"),.5)),e.push(),e.translate(250,250),e.scale(t),e.translate(-250,-250),e.beginShape(),e.vertex(235.2,24.9),e.bezierVertex(215,24.6,185,11.4,164.8,11),e.bezierVertex(147.2,10.7,129.3,10.4,112.2,14.7),e.bezierVertex(95.1,19,78.5,28.5,69.6,43.8),e.bezierVertex(57.699,64.199,61.599,90.199,70.199,112.2),e.bezierVertex(78.799,134.2,91.6,154.6,97.199,177.5),e.bezierVertex(102.499,199.2,100.899,222.5,92.799,243.2),e.bezierVertex(83,268,64.6,288.3,48.9,310),e.bezierVertex(33.2,331M .7,24.5,337.5,26.599,364.1),e.bezierVertex(28.2,384.1,61.399,404.2,75.7,418.3),e.bezierVertex(90,432.4,73.7,488.2,91.9,496.7),e.bezierVertex(124.2,511.6,159,472.5,194.3,468.1),e.bezierVertex(211.6,465.9,267.4,501.5,283.9,495.9),e.bezierVertex(340.7,476.7,298.599,428.9,355.4,409.7),e.bezierVertex(370.799,404.5,454.5,407.6,464.4,394.8),e.bezierVertex(478.599,376.3,474.7,349.3,464.299,328.4),e.bezierVertex(453.9,307.5,438.099,289.5,428.699,268.2),e.bezierVertex(412,230,419,182.6,446.1,150.9),e.bezierVertex(449.7,146.7M ,453.6,142.7,455.8,137.6),e.bezierVertex(459.4,129.299,457.5,119.6,454.8,111),e.bezierVertex(443.2,73.4,417.3,40.4,383.6,20.299),e.bezierVertex(358.1,5,343.2,-.4,313.5,0),e.bezierVertex(287.5,.4,261.6,25.4,235.2,24.9),e.endShape(),e.pop()}function C(e,t,n,r,i,o){let a,l,s;re(t),t.fill(0),t.rect(0,0,500,500),ie(t),t.noStroke(),t.fill(dr(n,.5)),1==i?(l=0,s=25,a=map(o,0,25,500,0)):a=0,t.rect(0,a,500,500),e.noStroke(),e.fill(r),e.rect(0,0,500,500),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,39M 3.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),M e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,22M 3.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.M 5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),e.fill(n),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,M 242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),eM .bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.M 5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),re(e),e.fill(r),e.beginShape(),e.vertex(184.3,473.2),eM .bezierVertex(164,473.2,144.7,462.099,134,444.3),e.bezierVertex(131.7,440.5,129.1,438.5,125,437.1),e.bezierVertex(97.3,428.1,80.5,400.6,85.2,371.8),e.bezierVertex(86.3,365.1,85.8,364.1,79.9,361.2),e.bezierVertex(57.2,349.8,46.2,323.3,54.3,299.7),e.bezierVertex(54.7,298.599,55.1,297.7,55.5,296.9),e.bezierVertex(55.6,296.599,55.8,296.4,55.9,296.099),e.vertex(57.9,291.499),e.vertex(62.5,293.599),e.bezierVertex(64.9,294.7,67.3,295.799,69.5,296.9),e.bezierVertex(74.5,299.299,79.1,301.599,83.9,303.099),e.bezierVertex(89.M 8,304.9,96.5,305.499,102.7,305.9),e.bezierVertex(102.8,305.9,102.9,305.9,103,305.9),e.bezierVertex(106.6,305.9,108.9,302.799,109,299.799),e.bezierVertex(109.1,296.199,106.6,293.4,102.7,292.799),e.bezierVertex(101.3,292.599,99.9,292.4,98.4,292.299),e.bezierVertex(94.3,291.799,90.1,291.299,86,289.9),e.bezierVertex(68.9,284,56.5,270.2,52.7,252.799),e.bezierVertex(48.9,235.499,54.5,217.7,67.6,205.299),e.bezierVertex(71.9,201.299,72.7,198.1,70.8,192.399),e.bezierVertex(64.2,172.2,68.8,153.99,84.2,139.599),e.bezierVertexM (94.2,130.199,105.5,125.399,117.8,125.399),e.bezierVertex(124.3,125.399,131.1,126.799,137.8,129.599),e.bezierVertex(157,137.399,167.9,152.799,169.4,173.99),e.vertex(169.4,174.399),e.bezierVertex(169.5,175.899,169.6,177.2,169.9,178.299),e.bezierVertex(170.7,181.2,173.2,183.2,176.1,183.2),e.bezierVertex(176.299,183.2,176.5,183.2,176.7,183.2),e.bezierVertex(180.1,182.899,182.6,180.299,182.7,177),e.bezierVertex(183.1,162,178.299,148.2,168.399,136.1),e.bezierVertex(158.2,123.5,144.899,115.8,128.799,113.199),e.bezierVertM ex(123.499,112.299,120.399,109.799,118.899,104.99),e.bezierVertex(113.899,89.699,120.699,72.299,134.899,64.499),e.bezierVertex(139.99,61.699,145.799,60.199,151.7,60.199),e.bezierVertex(162.2,60.199,171.899,64.799,178.1,72.699),e.bezierVertex(179.6,74.6,180.799,76.6,181.9,78.499),e.vertex(182.2,79.099),e.bezierVertex(183.2,80.699,185.2,83.299,188.4,83.299),e.bezierVertex(189.5,83.299,190.6,82.99,191.7,82.399),e.bezierVertex(195.1,80.599,196,76.99,194,72.799),e.bezierVertex(190.1,64.799,184.1,58.499,175.6,53.299),e.bM ezierVertex(174.6,52.699,173.7,52.099,172.5,51.499),e.vertex(170.5,50.299),e.vertex(163,45.899),e.vertex(170.5,41.599),e.bezierVertex(182,34.99,193.1,30.799,204.4,28.599),e.bezierVertex(208.6,27.799,212.9,27.399,217.2,27.399),e.bezierVertex(217.6,27.399,217.9,27.399,218.3,27.399),e.bezierVertex(231.4,27.599,242.7,38.199,243,50.599),e.bezierVertex(243.4,64.899,243.3,78.99,243.2,93.799),e.bezierVertex(243.2,99.799,243.1,105.899,243.1,112.099),e.vertex(243.1,119.199),e.vertex(236.4,116.799),e.bezierVertex(235.7,116.49M 9,235,116.299,234.4,115.99),e.bezierVertex(233.4,115.599,232.6,115.299,232,115.199),e.bezierVertex(230.6,114.899,229.2,114.599,227.8,114.299),e.bezierVertex(223.8,113.499,220.1,112.699,216.4,112.499),e.vertex(216.2,112.499),e.bezierVertex(212.5,112.499,210.7,115.599,210.6,118.599),e.bezierVertex(210.4,122.399,212.7,125.099,216.4,125.399),e.bezierVertex(230.1,126.399,238.9,133.099,242.3,145.199),e.bezierVertex(243.2,148.399,243.2,151.599,243.2,154.499),e.vertex(243.2,155.099),e.bezierVertex(243.2,254.199,243.2,330,2M 43.2,400.599),e.bezierVertex(243.2,401.99,243.2,403.4,243.2,404.9),e.bezierVertex(243.3,411.099,243.3,417.599,242.3,423.9),e.bezierVertex(238.1,449.2,219.6,467.799,194,472.5),e.bezierVertex(190.9,472.9,187.6,473.2,184.3,473.2),e.endShape(),e.beginShape(),e.vertex(315.8,473.1),e.bezierVertex(309.3,473.1,302.8,472,296.5,469.9),e.bezierVertex(270.4,461,253.8,434.9,257.1,407.9),e.bezierVertex(260,384,273.8,366.8,297,358.3),e.bezierVertex(297.7,358.1,298.3,357.8,299,357.6),e.bezierVertex(299.8,357.3,300.6,357.1,301.2,35M 6.8),e.bezierVertex(304.3,355.4,306,351.8,304.9,348.7),e.bezierVertex(304,345.9,301.7,344.2,299,344.2),e.bezierVertex(298.6,344.2,298.1,344.2,297.6,344.3),e.bezierVertex(288.1,346.3,279,350.9,269.7,358.3),e.bezierVertex(268.9,358.9,268.1,359.6,267.2,360.4),e.vertex(265.5,361.8),e.vertex(258.5,367.6),e.vertex(257.4,358.6),e.bezierVertex(257.3,358,257.3,357.5,257.2,357.1),e.bezierVertex(257,356,256.9,354.9,256.9,353.7),e.bezierVertex(256.9,334.8,256.9,316,256.9,297.1),e.bezierVertex(256.9,260.3,256.9,222.3,256.8,185)M ,e.bezierVertex(256.8,170.7,268.3,158.8,282.5,158.4),e.bezierVertex(284.8,158.3,286.7,157.6,287.9,156.2),e.bezierVertex(289.099,154.9,289.599,153.2,289.5,151.3),e.bezierVertex(289.3,147.5,286.7,145.1,282.7,145.1),e.bezierVertex(282.5,145.1,282.2,145.1,282,145.1),e.bezierVertex(278.8,145.3,275.5,146.1,272,146.9),e.bezierVertex(270.9,147.2,269.8,147.4,268.6,147.7),e.bezierVertex(267.9,147.9,267,148.2,265.8,148.7),e.bezierVertex(265.1,149,264.4,149.3,263.5,149.6),e.vertex(256.8,152),e.vertex(256.8,114.6),e.bezierVerteM x(256.8,95,256.8,75.4,256.8,55.9),e.bezierVertex(256.8,38,267.2,27.3,284.6,27.3),e.bezierVertex(285.3,27.3,285.9,27.3,286.6,27.3),e.bezierVertex(299,27.9,318.7,34.5,329.6,41.9),e.vertex(336.1,46.3),e.vertex(324.4,53.3),e.bezierVertex(316.2,58.2,310.2,64.6,306,72.9),e.bezierVertex(304.2,76.4,305.1,78.5,306.1,80),e.bezierVertex(307.4,81.9,309.4,83,311.6,83),e.bezierVertex(313.7,83,315.7,81.9,317.1,80.1),e.bezierVertex(317.4,79.7,317.8,79,318.1,78.4),e.bezierVertex(318.4,77.9,318.7,77.3,319,76.8),e.bezierVertex(325.3,M 66.2,336.3,59.9,348.5,59.9),e.bezierVertex(353.2,59.9,357.8,60.8,362.1,62.7),e.bezierVertex(377.6,69.3,386,86.7,381.7,103.2),e.bezierVertex(380.7,107.1,378.5,111.8,371.1,113.1),e.bezierVertex(342.7,118.1,322.2,139.1,317.8,167.8),e.bezierVertex(317.4,170.3,317.3,173.2,317.4,176.5),e.bezierVertex(317.5,180,320.1,182.8,323.5,183),e.bezierVertex(323.6,183,323.8,183,323.9,183),e.bezierVertex(327.1,183,329.8,180.6,330.3,177.2),e.bezierVertex(330.6,175.7,330.7,174,330.9,172.3),e.bezierVertex(331.1,169.8,331.4,167.3,332,16M 4.7),e.bezierVertex(337.3,141.9,357.7,125.4,380.7,125.4),e.bezierVertex(382.5,125.4,384.3,125.5,386.1,125.7),e.bezierVertex(412.8,128.9,432.6,150.9,432,176.9),e.bezierVertex(431.9,182.3,430.9,187.7,429.1,192.7),e.bezierVertex(427.2,197.9,428,201,432.3,205),e.bezierVertex(446.8,218.7,451.8,236,446.6,255),e.bezierVertex(441.4,274,428.3,286.5,408.7,291.3),e.bezierVertex(406.1,291.9,403.6,292.1,401.1,292.3),e.bezierVertex(400,292.4,398.9,292.5,397.9,292.6),e.bezierVertex(393.6,293.1,390.9,295.7,391,299.5),e.bezierVerteM x(391.1,303.4,394,305.8,398.5,305.8),e.bezierVertex(409.9,305.8,420.8,302.6,431.1,296.4),e.bezierVertex(431.8,296,432.5,295.5,433.2,295.1),e.bezierVertex(433.8,294.7,434.5,294.3,435.2,293.9),e.bezierVertex(436,293.4,436.6,293.2,437.2,293.1),e.bezierVertex(437.4,293,437.7,292.9,438.1,292.8),e.vertex(442.5,291.4),e.vertex(444.2,295.7),e.bezierVertex(450.9,312.4,449.5,328.4,440,343.4),e.bezierVertex(435.3,350.8,428.7,356.7,420.2,361.1),e.bezierVertex(414.3,364.1,413.7,365.2,414.8,371.7),e.bezierVertex(419.5,400.2,403,M 427.6,375.6,436.9),e.bezierVertex(371,438.5,368.3,440.7,365.8,444.7),e.bezierVertex(355.2,462.5,336.4,473.1,315.8,473.1),e.bezierVertex(315.8,473.1,315.8,473.1,315.8,473.1),e.endShape(),ie(e),e.fill(n),e.beginShape(),e.vertex(120.2,279.9),e.bezierVertex(117.9,279.9,112.4,279.299,112.2,273.599),e.bezierVertex(112,267.7,117.4,266.7,119.7,266.599),e.bezierVertex(133.1,265.799,143.1,259.499,149.3,247.899),e.bezierVertex(149.6,247.299,150.1,246.399,150.3,245.399),e.bezierVertex(150.6,244.299,150.5,243.299,150.5,242.7),eM .bezierVertex(150.5,242.6,150.5,242.5,150.5,242.299),e.vertex(150.3,238.799),e.vertex(141.1,235.99),e.bezierVertex(114.6,227.799,95.6,202.499,95.9,175.799),e.bezierVertex(95.9,173.99,96.4,168.199,102.2,168.199),e.bezierVertex(102.6,168.199,103,168.199,103.4,168.299),e.bezierVertex(104.8,168.499,108.2,168.899,109.2,175.599),e.bezierVertex(109.3,176.599,109.5,177.599,109.6,178.499),e.bezierVertex(110.4,184.199,111.3,189.99,113.7,195.499),e.bezierVertex(121.9,213.99,139.5,225.499,159.7,225.499),e.bezierVertex(172.1,22M 5.499,184.1,220.899,193.5,212.599),e.bezierVertex(194,212.199,194.4,211.799,194.8,211.399),e.bezierVertex(195.1,211.099,195.5,210.799,195.8,210.399),e.bezierVertex(197.4,208.99,199.2,208.2,200.9,208.2),e.bezierVertex(202.5,208.2,204,208.899,205.3,210.1),e.bezierVertex(208,212.9,207.9,216.9,205,219.9),e.bezierVertex(196.5,228.6,186.3,234.3,174.7,236.8),e.bezierVertex(168.799,238.1,165.6,241,163.899,246.7),e.bezierVertex(158.3,265.9,139.9,279.7,120.2,279.9),e.vertex(120.2,279.9),e.endShape(),e.beginShape(),e.vertex(1M 87.2,427.5),e.bezierVertex(183.799,427.5,181.299,425.3,180.799,422),e.bezierVertex(180.6,420.8,180.499,419.5,180.399,418.1),e.bezierVertex(180.299,417,180.2,415.8,180.099,414.7),e.bezierVertex(177.199,390.5,156.699,371.3,132.399,370.2),e.bezierVertex(131.99,370.2,131.499,370.2,131.099,370.2),e.bezierVertex(130.699,370.2,130.299,370.2,129.799,370.2),e.bezierVertex(125.99,369.9,123.199,367.2,123.099,363.6),e.bezierVertex(122.99,360.2,125.799,357.3,129.599,356.9),e.bezierVertex(130.499,356.8,131.499,356.8,132.599,356.M 7),e.bezierVertex(133.199,356.7,133.799,356.7,134.399,356.6),e.vertex(138.299,356.4),e.vertex(139.1,352.6),e.bezierVertex(139.5,350.7,139.799,348.9,140.2,347),e.bezierVertex(140.899,343.4,141.5,340,142.399,336.8),e.bezierVertex(150.099,310.7,174.399,292,201.399,291.3),e.vertex(201.599,291.3),e.bezierVertex(203.699,291.3,206.299,292,208.299,293.2),e.bezierVertex(210.499,294.5,210.699,297.5,209.99,299.8),e.bezierVertex(209.499,301.5,208.199,303.9,203.299,304.7),e.bezierVertex(202.199,304.9,200.99,305,199.799,305.2),eM .bezierVertex(194.499,305.9,188.99,306.599,183.799,308.9),e.bezierVertex(165.499,316.799,155.199,331.299,152.99,352),e.bezierVertex(152.399,357.8,154.499,361.7,159.699,364.5),e.bezierVertex(178.199,374.4,189.399,390,193.099,410.9),e.bezierVertex(193.699,414.299,193.899,418,193.599,422),e.bezierVertex(193.399,425.2,190.899,427.5,187.399,427.5),e.vertex(187.2,427.5),e.endShape(),e.beginShape(),e.vertex(364.3,281.1),e.bezierVertex(346.3,280.6,332.9,272.8,323.5,257),e.bezierVertex(321.6,253.9,320.4,250.2,319.2,246.7),eM .bezierVertex(317.7,242.2,315,239.799,310.5,238.799),e.bezierVertex(298.5,236.299,288,230.7,279.4,222.1),e.bezierVertex(276.7,219.4,274.9,215.299,278,211.9),e.bezierVertex(279.4,210.3,281,209.6,282.6,209.6),e.bezierVertex(284.4,209.6,286.4,210.6,288.3,212.5),e.bezierVertex(297.8,221.8,310.4,226.9,323.9,226.9),e.bezierVertex(340.2,226.9,355.1,219.3,364.8,206.2),e.bezierVertex(371,197.8,374.2,188.5,374.5,178.5),e.vertex(374.5,177.9),e.bezierVertex(374.5,177,374.5,176.1,374.7,175.4),e.bezierVertex(375.3,171.8,377.9,16M 9.5,381.3,169.5),e.bezierVertex(381.4,169.5,381.5,169.5,381.7,169.5),e.bezierVertex(385.4,169.7,388,172.4,388,176.1),e.bezierVertex(388.1,190.7,383.4,204,374.2,215.8),e.bezierVertex(365.8,226.5,354.7,233.9,341.2,237.9),e.bezierVertex(340,238.3,338.7,238.6,337.3,239.1),e.bezierVertex(335.9,239.6,335.1,240.4,334.7,240.9),e.bezierVertex(334.599,241,334.5,241.1,334.4,241.2),e.vertex(331.799,243.6),e.vertex(333.199,246.8),e.bezierVertex(338.199,258,346.799,264.9,358.699,267.3),e.bezierVertex(360.199,267.6,361.599,267.7,M 362.99,267.9),e.bezierVertex(363.599,268,364.299,268,364.899,268.1),e.bezierVertex(369.099,268.6,371.799,271.4,371.499,275),e.bezierVertex(371.199,278.6,368.299,281.2,364.399,281.2),e.vertex(364.3,281.1),e.endShape(),e.beginShape(),e.vertex(323.9,437),e.bezierVertex(323.7,437,323.5,437,323.299,437),e.bezierVertex(319.599,436.7,317.299,434.1,317.4,430.2),e.bezierVertex(317.9,406.099,328.299,388,349.5,375),e.bezierVertex(350.7,374.2,352,373.5,353.4,372.8),e.bezierVertex(354.099,372.4,354.7,372.1,355.299,371.7),e.vertM ex(357.499,370.5),e.vertex(357.799,368),e.bezierVertex(360.4,346.6,345.199,323.7,323.9,317),e.bezierVertex(319.099,315.5,314.099,314.9,309.299,314.4),e.vertex(308.199,314.299),e.bezierVertex(305.99,314.099,300.799,312.9,300.899,307.299),e.bezierVertex(300.99,303.499,303.899,300.9,308.099,300.9),e.vertex(308.299,300.9),e.bezierVertex(327.099,301.299,343.099,308.7,355.699,322.9),e.bezierVertex(364.299,332.5,369.399,344.099,370.99,357.299),e.bezierVertex(371.099,358.4,371.299,359.4,371.499,360.499),e.bezierVertex(371.M 599,360.99,371.699,361.499,371.799,361.99),e.vertex(372.499,365.899),e.vertex(377.899,366.199),e.bezierVertex(378.799,366.299,379.699,366.299,380.599,366.399),e.bezierVertex(385.099,366.699,387.899,369.399,387.799,373.299),e.bezierVertex(387.699,377.099,384.99,379.599,380.799,379.799),e.bezierVertex(369.799,380.199,359.99,383.299,351.899,389.299),e.bezierVertex(338.799,398.799,331.699,411.699,330.699,427.499),e.vertex(330.699,428.299),e.bezierVertex(330.599,429.199,330.599,430.099,330.499,430.799),e.bezierVertex(33M 0,434.7,327.5,437,323.9,437),e.endShape()}function T(e){return e[0].map(((t,n)=>e.map((e=>e[n]))))}function A(e){return e.map((e=>Array.isArray(e)?A(e):e))}function D(e,t){return floor(random(e,t))}function k(e){let t=0;for(const n of e)t+=n[1];let n=random(t),r=0;for(const t of e)if(r+=t[1],n<r)return t[0];return null}function L(e){for(let t=1;t<e.length;++t){let n=D(0,t),r=e[t];e[t]=e[n],e[n]=r}}function P(e){return null==e||""===e}function O(e){return new Promise((t=>setTimeout(t,e)))}function F(e,t,n){let r=0;fM or(let i=1;i<=1e3;++i)for(let o=1;o<=1e3;++o)if(e*o%(t*i)==0){let e=1*i/o;abs(e-n)<abs(r-n)&&(r=e)}return r}function N(){let e=60*(new Date).getTimezoneOffset()*1e3;return new Date(Date.now()-e).toISOString().slice(0,-1)}function B(e,t,n){let r;if(push(),textSize(e),textWidth(t)<=n)r=t;else for(let e=0;e<t.length;++e){const i=t.slice(0,e+1)+"...";if(textWidth(i)>n){r=i;break}}return pop(),r}function Y(e){var t=e%10,n=e%100;return 1==t&&11!=n?e+"st":2==t&&12!=n?e+"nd":3==t&&13!=n?e+"rd":e+"th"}class G{constructor(e,M t,n){this.n=t,this.m=n,this.mat=[];let r=0;for(let t=0;t<this.n;++t){this.mat.push([]);for(let n=0;n<this.m;++n)this.mat[t].push(r<e.length?e[r]:0),r+=1}return this}copy(){return new G(this.mat.flat(),this.n,this.m)}}class H{static __linear=e=>e;static __relu=e=>Math.max(e,0);static __leaky_relu=e=>e>0?e:.2*e;static __sigmoid=e=>1/(1+Math.exp(-e));static __tanh=e=>Math.tanh(e);static __apply_unary_op(e,t){const n=e.copy();for(let e=0;e<n.n;++e)for(let r=0;r<n.m;++r)n.mat[e][r]=t(n.mat[e][r]);return n}static linear=M e=>H.__apply_unary_op(e,H.__linear);static relu=e=>H.__apply_unary_op(e,H.__relu);static leaky_relu=e=>H.__apply_unary_op(e,H.__leaky_relu);static sigmoid=e=>H.__apply_unary_op(e,H.__sigmoid);static tanh=e=>H.__apply_unary_op(e,H.__tanh);static __add=(e,t)=>e+t;static __mul=(e,t)=>e*t;static __apply_binary_op=(e,t,n)=>{"object"!=typeof t&&(t=new G([t],1,1));const r=e.copy();for(let e=0;e<r.n;++e)for(let i=0;i<r.m;++i)r.mat[e][i]=n(r.mat[e][i],t.mat[e%t.n][i%t.m]);return r};static mul=(e,t)=>H.__apply_binary_op(e,t,M H.__mul);static add=(e,t)=>H.__apply_binary_op(e,t,H.__add);static matMul(e,t){const n=new G([],e.n,t.m);for(let r=0;r<n.n;++r)for(let i=0;i<n.m;++i)for(let o=0;o<e.m;++o)n.mat[r][i]+=e.mat[r][o]*t.mat[o][i];return n}static softmax(e){const t=H.__apply_unary_op(e,(e=>Math.exp(e))),n=t.mat.flat().reduce(((e,t)=>e+t));for(let r=0;r<e.n;++r)for(let i=0;i<e.m;++i)t.mat[r][i]/=n;return t}}class ${constructor(e,t){this.scale=e,this.offset=t}forward(e){return H.add(H.mul(e,this.scale),this.offset)}}class X{constructor(){}M forward(e){return e.map((e=>e.flat()))}}class W{constructor(e,t,n,r){this.out_dim=e,this.activation=t,this.w=n,this.b=r}forward(e){const t=H.add(H.matMul(e,this.w),this.b);return null==this.activation?t:this.activation(t)}}class U{constructor(e,t,n){this.preprocessLayers=e,this.hiddenLayers=t,this.outputLayer=n,this.totalNeurons=this.hiddenLayers.map((e=>e.out_dim)),this.currentOrders=[],this.currentIteration=null}updateNeurons(e,t){if(t!=this.currentIteration){this.currentOrders=[];for(let e=0;e<this.totalNeurons.M length;++e){randomSeed(100*(t+1)+e);const n=[];for(let t=0;t<this.totalNeurons[e];++t)n.push(t);L(n),this.currentOrders.push(n)}this.currentIteration=t}const n=A(this.totalNeurons),r=n.reduce(((e,t)=>e+t))*(1-e);for(let e=0;e<r;++e){const t=n.map(((e,t)=>(e-1)/this.totalNeurons[t]));n[t.map(((e,t)=>[e,t])).reduce(((e,t)=>t[0]>e[0]?t:e))[1]]-=Math.min(r-e,1)}this.neuronsLife=[];for(let e=0;e<n.length;++e){const t=this.currentOrders[e],r=Array(this.totalNeurons[e]).fill(0);for(let i=0;i<n[e];++i)r[t[i]]=Math.min(n[e]M -i,1);this.neuronsLife.push(r)}}getTotalNeurons(){return A(this.totalNeurons)}getNeuronsLife(){return A(this.neuronsLife)}forward(e){for(const t of this.preprocessLayers)e=t.forward(e);for(const[t,n]of this.hiddenLayers.entries()){e=n.forward(e);const r=new G(this.neuronsLife[t],1,e.m);e=H.mul(e,r)}return e=this.outputLayer.forward(e),H.softmax(e)}}function q(e){switch(e){case"relu":return H.relu;case"sigmoid":return H.sigmoid;case"tanh":return H.tanh;case"leaky_relu":return H.leaky_relu;default:return H.linear}}fuM nction j(e,t){const n=[],r=[],i=Z(t);let o=null,a=0,l=[];for(const t of e.config.layers)if("InputLayer"==t.class_name)o=t.config.batch_input_shape.slice(1),l=o;else if("Rescaling"==t.class_name)n.push(new $(t.config.scale,t.config.offset));else if("Flatten"==t.class_name)o=[o.reduce(((e,t)=>e*t))];else if("Dense"==t.class_name){const e=[t.config.units],n=o[0]*e[0],l=e[0],s=i.subarray(a,a+n);a+=n;const h=i.subarray(a,a+l);a+=l;const c=new G(s,o[0],e[0]),u=new G(h,1,e[0]),f=q(t.config.activation);r.push(new W(e[0],f,M c,u)),o=e}const s=r.pop();return{model:new U(n,r,s),inputDim:l}}function Z(e){const t=window.atob(e),n=t.length/Float32Array.BYTES_PER_ELEMENT,r=new DataView(new ArrayBuffer(Float32Array.BYTES_PER_ELEMENT)),i=new Float32Array(n);let o=0;for(let e=0;e<n;e++){o=4*e;for(let e=0;e<4;++e)r.setUint8(e,t.charCodeAt(o+e));i[e]=r.getFloat32(0,!0)}return i}class K{constructor(e){this.elt=e,this._events={},this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight}position(){if(0===arguments.length)return{x:this.elt.ofM fsetLeft,y:this.elt.offsetTop};var e="absolute";return"static"!==arguments[2]&&"fixed"!==arguments[2]&&"relative"!==arguments[2]&&"sticky"!==arguments[2]&&"initial"!==arguments[2]&&"inherit"!==arguments[2]||(e=arguments[2]),this.elt.style.position=e,this.elt.style.left=arguments[0]+"px",this.elt.style.top=arguments[1]+"px",this.x=arguments[0],this.y=arguments[1],this}show(){return this.elt.style.display="block",this}hide(){return this.elt.style.display="none",this}size(e,t){if(0===arguments.length)return{width:thisM .elt.offsetWidth,height:this.elt.offsetHeight};var n=e,r=t;if(n!==te||r!==te){if(n===te?n=t*this.width/this.height:r===te&&(r=e*this.height/this.width),this.elt instanceof HTMLCanvasElement){var i,o={},a=this.elt.getContext("2d");for(i in a)o[i]=a[i];for(i in this.elt.setAttribute("width",n*this._pInst._pixelDensity),this.elt.setAttribute("height",r*this._pInst._pixelDensity),this.elt.style.width=n+"px",this.elt.style.height=r+"px",this._pInst.scale(this._pInst._pixelDensity,this._pInst._pixelDensity),o)this.elt.geM tContext("2d")[i]=o[i]}else this.elt.style.width=n+"px",this.elt.style.height=r+"px",this.elt.width=n,this.elt.height=r;this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight,this._pInst&&this._pInst._curElement&&this._pInst._curElement.elt===this.elt&&(this._pInst._setProperty("width",this.elt.offsetWidth),this._pInst._setProperty("height",this.elt.offsetHeight))}return this}style(e,t){if(t instanceof Color&&(t="rgba("+t.levels[0]+","+t.levels[1]+","+t.levels[2]+","+t.levels[3]/255+")"),void 0===t){if(-M 1===e.indexOf(":"))return window.getComputedStyle(this.elt).getPropertyValue(e);for(var n=e.split(";"),r=0;r<n.length;r++){var i=n[r].split(":");i[0]&&i[1]&&(this.elt.style[i[0].trim()]=i[1].trim())}}else if(this.elt.style[e]=t,"width"===e||"height"===e||"left"===e||"top"===e){var o=window.getComputedStyle(this.elt).getPropertyValue(e).replace(/[^\d.]/g,"");this[e]=Math.round(parseFloat(o,10))}return this}value(){return arguments.length>0?(this.elt.value=arguments[0],this):"range"===this.elt.type?parseFloat(this.elM t.value):this.elt.value}mouseClicked(e){return this._adjustListener("click",e,this),this}isFocused(){return document.activeElement===this.elt}_adjustListener(e,t,n){return!1===t?this._detachListener(e,n):this._attachListener(e,t,n),this}_attachListener(e,t,n){n._events[e]&&this._detachListener(e,n);var r=t.bind(n);n.elt.addEventListener(e,r,!1),n._events[e]=r}_detachListener(e,t){var n=t._events[e];t.elt.removeEventListener(e,n,!1),t._events[e]=null}}function J(e,t){var n=document.createElement("button");return n.iM nnerHTML=e,t&&(n.value=t),ee(n)}function Q(e){var t=arguments.length>1&&void 0!==arguments[1]&&arguments[1],n=function(t){var n=!0,r=!1,i=void 0;try{for(var o,a=t.target.files[Symbol.iterator]();!(n=(o=a.next()).done);n=!0){var l=o.value;File._load(l,e)}}catch(e){r=!0,i=e}finally{try{n||null==a.return||a.return()}finally{if(r)throw i}}};if(window.File&&window.FileReader&&window.FileList&&window.Blob){var r=document.createElement("input");return r.setAttribute("type","file"),t&&r.setAttribute("multiple",!0),r.addEveM ntListener("change",n,!1),ee(r)}}function ee(e){return document.body.appendChild(e),new K(e)}createImg=function(){var e,t=document.createElement("img"),n=arguments;return n.length>1&&"string"==typeof n[1]&&(t.alt=n[1]),n.length>2&&"string"==typeof n[2]&&(t.crossOrigin=n[2]),t.src=n[0],e=ee(t,this),t.addEventListener("load",(function(){e.width=t.offsetWidth||t.width,e.height=t.offsetHeight||t.height;var r=n[n.length-1];"function"==typeof r&&r(e)})),e},createInput=function(){var e=arguments.length>0&&void 0!==argumenM ts[0]?arguments[0]:"",t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:"text",n=document.createElement("input");return n.setAttribute("value",e),n.setAttribute("type",t),ee(n,this)};const te="auto";function ne(e){re(e);const t=e._rectMode;e.rectMode(CORNER),e.rect(0,0,e.width,e.height),e.rectMode(t),ie(e)}function re(e){e.push(),e.fill(255,255,255,255),e.blendMode(REMOVE)}function ie(e){e.blendMode(BLEND),e.pop()}File=function(e,t){this.file=e,this._pInst=t;var n=e.type.split("/");this.type=n[0],this.subtypM e=n[1],this.name=e.name,this.size=e.size,this.data=void 0},File._createLoader=function(e,t){var n=new FileReader;return n.onload=function(n){var r=new File(e);if("application/json"===r.file.type)r.data=JSON.parse(n.target.result);else if("text/xml"===r.file.type){var i=(new DOMParser).parseFromString(n.target.result,"text/xml");r.data=new XML(i.documentElement)}else r.data=n.target.result;t(r)},n},File._load=function(e,t){if(/^text\//.test(e.type)||"application/json"===e.type)File._createLoader(e,t).readAsText(e);eM lse if(/^(video|audio)\//.test(e.type)){var n=new File(e);n.data=URL.createObjectURL(e),t(n)}else File._createLoader(e,t).readAsDataURL(e)},XML=function(e){if(e)this.DOM=e;else{var t=document.implementation.createDocument(null,"doc");this.DOM=t.createElement("root")}},document.addEventListener("DOMContentLoaded",(function(){addEventListener("mousemove",(e=>{window.mouseX=e.pageX,window.mouseY=e.pageY}))})),new e("global");const oe="465";let ae,le,se,he,ce,ue,fe,de,xe,ge,pe,me,be,ye,we,ve,ze,Ve,_e,Me,Ee,Se,Re,Ie,Ce,M Te,Ae,De,ke,Le,Pe,Oe,Fe,Ne,Be,Ye,Ge,He,$e,Xe,We,Ue,qe,je,Ze,Ke,Je,Qe,et,tt,nt,rt,it,ot,at,lt,st,ht,ct,ut,ft,dt,xt,gt,pt,mt,bt,yt,wt,vt,zt,Vt,_t,Mt,Et,St,Rt,It,Ct,Tt,At=!1,Dt=!1,kt=!0,Lt=!1,Pt=!1;const Ot=[" ","Growing","Stable","Decaying","Dead","Rebirth"];let Ft,Nt,Bt,Yt,Gt,Ht,$t,Xt,Wt,Ut,qt,jt,Zt,Kt,Jt,Qt,en,tn,nn,rn,on,an,ln,sn,hn=0,cn=0,un=0,fn=!1,dn=!0,xn=!0,gn=null,pn=null,mn=null,bn=!1,yn=!1,wn=null,vn=null,zn=!1;async function setup(){let e=windowWidth,t=windowHeight;createCanvas(e,t),et=createGraphics(e,t)M ,Xe=createGraphics(e,t),$e=createGraphics(e,t),We=createGraphics(e,t),Ue=createGraphics(e,t),qe=createGraphics(e,t),Qe=createGraphics(e,t),je=createGraphics(e,t),Ze=createGraphics(e,t),Ke=createGraphics(e,t),Je=createGraphics(e,t),tt=createGraphics(500,500),nt=createGraphics(500,500),rt=createGraphics(500,500),_n(),Mn(),Sn(),await En(),Gn(),Rn(),bn=!0}function _n(){Et=parseInt(oe),randomSeed(Et),noiseSeed(Et)}function Mn(){Wt=Ir(p.training_traits),Cr(Wt)}async function En(){let e;Jt=r(),Qt=o(),[Xt,e]=await Promise.M all([s(Jt),h(Qt)]),Ut=new V(Wt.visual,e.layers_config,e.weight_b64),Ut.updateAge(new Date),_n(),Wt.training=e.training_traits,Ht=e.model_name,$t=e.classes_name}function Sn(){le=min(width,height)/1024,ut=Rr.findIndex((e=>e[0]===Wt.visual.colorPalette)),ft=[["#ffffff","#231f20","#231f20"],["#231f20","#ffffff","#ffffff"],["#104da8","#ffffff","#ffffff"],["#722F1F","#FCE1B2","#FCE1B2"],["#e88120","#f9f2e5","#f9f2e5"],["#f6b941","#2E2E2E","#2E2E2E"],["#45daaa","#012221","#012221"],["#F1F1F1","#328DFE","#328DFE"],["#11182M 2","#D3EB8D","#D3EB8D"],["#713FF9","#D6D5E6","#D6D5E6"],["#FBDA9D","#795106","#795106"],["#8f5b62","#ead0d0","#ead0d0"],["#eae4cb","#508cac","#508cac"],["#ffc6cc","#cc313d","#cc313d"],["#60A900","#E0FE00","#E0FE00"],["#507DBE","#D0D1D3","#D0D1D3"],["#305848","#E8F2EE","#E8F2EE"],["#2a2634","#5b6988","#cb78a2","#5b6988"],["#590e29","#fd5e53","#fd5e53","#ffe373"],["#0a141d","#57d4e4","#328195","#2A9ECF","#0ab6a8","#57d4e4"],["#3a2d28","#d5c2ac","#df6338","#3d9895","#d5c2ac"],["#030706","#77c4d9","#77c4d9","#77c4d9","M #ffffff","#ffffff","#e72020","#e72020"],["#3a4664","#92f5ff","#f9ff94","#eaa0a2","#55dde0"],["#fbfaff","#f04bb1","#f04bb1","#fac373","#82cef0","#8b31ce"],["#000000","#ffffff","#ff0002","#f26522","#fdff00","#00ff03","#01fffe","#0000ff","#ff00ff"]];for(let e=0;e<ft.length;++e)for(let t=0;t<ft[e].length;++t)ft[e][t]=cr(ft[e][t]);pt=[],ct=ft[ut][0],st=ft[ut][1]}function Rn(){gn=document.querySelector("#upload"),pn=document.querySelector("#inputUpload"),gn.addEventListener("dblclick",(()=>{if(!Lt&&!yn)if(In(Ie)&&cn==Ve-M 1)pn.click();else{if(4!=Pe&&5!=Pe&&(In(Ie)||cn!=Ve-1))return;fn=!0,dn=!0,Bt=0,un=0}})),pn.addEventListener("click",(()=>{pn.value=null,gn.style.display="block"})),pn.addEventListener("change",(()=>{const[e]=pn.files;e?(se=null,gn.style.display="none",Tn(URL.createObjectURL(e)),mn=e):gn.style.display="block"}))}function In(e){for(let t=0;t<e.length;++t){let n=0;for(let r=0;r<e[t].length;++r)e[t][r]>0&&++n;if(0==n)return!1}return!0}function Cn(){null!=se&&(un=0,Pt=!0,he=0,ue=0,drewLineAnim=!0,ce=(ae/2+we/2)/le,loadImM age(se.elt.src,(e=>{const[t,n,r]=Gt,i=createGraphics(t,n);i.image(e,0,0,t,n),i.loadPixels();const o=i.pixels.filter(((e,t)=>t%4!=3)),a=Ut.classifyImage(o);Zt=T([a,$t.map((e=>e.toUpperCase()))]).sort(((e,t)=>e[0]>t[0]?-1:1))})))}function Tn(e){se=createImg(e,""),se.hide(),Cn()}function An(){zn||(ce+=(width-ae-we)/tn/le),re(Xe),Xe.rect(ce*le,0,width,height),ie(Xe),un>=ge&&1==kt&&(kt=!1,un-=ge),kt&&(re($e),$e.strokeWeight(2*Fe),Jn(he,ze,ct,ct,$e),ie($e)),un>=ge&&0==kt&&(kt=!0,un-=ge,he+=1,he==en&&(++ue,he=0,ce=(ae/2+wM e/2)/le,1==ue&&(Pt=!1,Dn(),ye=millis())))}function Dn(){At=!0,pe=!1,me=!1,tryButton=br("Try Again",width/2-225*le,height/2+265*le,290*le,40*le,kn),closeResultButton=br("Close",width/2+75*le,height/2+265*le,150*le,40*le,Ln)}function kn(){At=!1,tryButton.hide(),closeResultButton.hide(),pn.click()}function Ln(){Yt=!0,At=!1,Gn(),tryButton.hide(),closeResultButton.hide(),gn.style.display="block",se=null}function keyTyped(){bn&&!1===yn&&!1===yr()&&("i"!==key&&"I"!==key||(Dt=!Dt),"b"!==key&&"B"!==key||(xn=!xn),"s"!==key&&M "S"!==key||!1!==Lt||saveCanvasAtCurrentTime(),"k"!==key&&"K"!==key||!1!==Lt||save4KCanvasAtCurrentTime(),"u"!==key&&"U"!==key||!1!==Lt||!1!==At||!1!==fn||!1!==Pt||On())}function On(){Lt=!0,wn=null,vn=null,submitButton=br("Submit",width/2-155*le,height/2+115*le,150*le,40*le,Fn),closeSettingButton=br("Close",width/2+5*le,height/2+115*le,150*le,40*le,Yn),vt=createInput(),vt.position(width/2-252.5*le,height/2-40*le),vt.size(500*le,25*le),vt.style("font-size","15px"),vt.value(Jt||""),zt=createInput(),zt.position(width/2M -252.2*le,height/2+35*le),zt.size(500*le,25*le),zt.style("font-size","15px"),zt.value(Qt||"")}function Fn(){Vt=vt.value(),_t=zt.value(),submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide(),Lt=!1,yn=!0,Nn()}async function Nn(){[wn,vn,_]=await Promise.all([c(Vt),u(_t),O(1e3)]),yn=!1,wn&&vn?(n(Vt),i(_t),window.location.reload()):(Lt=!0,submitButton.show(),closeSettingButton.show(),vt.show(),zt.show())}function Bn(){Je.textFont("Trebuchet MS"),Je.noStroke(),pr(Je,600*le,200*le),Je.strokeWeight(1*le),Je.strM oke(xt),Je.fill(xt),Je.textSize(50*le),Je.text("update()",width/2,height/2+2.5*le)}function Yn(){wn=null,vn=null,Lt=!1,submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide()}function Gn(){_n(),nn=Date.now(),pe=!1,me=!1,St=Wt.training.structure_gen,Rt=Wt.visual.birthYear,It=Wt.visual.lifeCycle,Ct=Wt.training.epoch_num,Tt=Wt.training.activation_func,Ft=Mr.findIndex((e=>e[0]==Wt.visual.hardwareAcceleration))+1,1==Ft?(Nt=30,fe=40):2==Ft?(Nt=15,fe=20):(Nt=2,fe=10);const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=M e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),ae=100*le,ht=50*le,Oe=Sr.findIndex((e=>e[0]==Wt.visual.nodeShape))+1,dt=Er.findIndex((e=>e[0]==Wt.visual.nodeFill))+1,lt=_r.findM Index((e=>e[0]==Wt.visual.pattern))+1,de=Math.tanh(Math.log10(Xt.avgfeerate)),de=map(de,0,1,.2,.8),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e]M .length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1=M =Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,at=.7,pt=[],xt=ft[ut][2],gt=ft[ut][ft[ut].length-1];for(let e=3;e<ft[ut].length-1;e++)pt.push(ft[ut][e]);mt=sr(xt,gt,pt,width),bt=[],wt=[],yt=width/(Ve-1);for(let e=0;e<VM e;e++)bt.push(hr(mt,yt*e/width)),wt.push(hr(mt,yt*e/width));wt.unshift(bt[0]),wt.push(bt[bt.length-1]),hn=0,cn=0,un=0,Yt=!0;const n={xLeft:ae/8,xRight:width-ae/8,yTop:ae/8,yBottom:height-ae/8},r=Ce.map((e=>e.length));jt=new R(bt,r,n,Oe,le)}function Hn(e,t){let n=Ce[e].length;return[e*we+we/2+ae/2,height/2-(n-1)/2*ve+t*ve]}function $n(e,t){le=min(e,t)/1024,ae=100*le,ht=50*le,we=(e-ae)/Ve,ve=(t-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,rM ]=Hn(e,n);De.push([t,r])}}xe=floor(De.length*de),Le=[],ke=[],ge=floor(map(de,.2,.8,15,2));for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,mt=sr(xt,gt,pt,e),bt=[],wt=[],yt=e/(Ve-1);for(let t=0;t<Ve;t++)bt.push(hr(mt,yt*t/e)),wt.push(hr(mt,yt*t/e));wt.unshift(bt[0]),wt.push(bt[bt.length-1])}function Xn(){const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=M e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputM Nodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let M e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,M e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le}function Wn(){jt.update();const e=4==Pe?0:Kt;jt.draw(Qe,ct,dt,e,le)}function Un(){if(!bn)return ar(),void et.image(je,0,0);if(4==Pe||5==Pe)return Wn(),void et.image(Qe,0,0);un>=Nt&&hn<Ve&&(hn++,un=0);for(let e=0;e<hn;e++)1==dt?it=ot=bt[e]:(it=ct,ot=bt[e]),Kn(e,it,ot,$e);un>=Nt&&cn<Ve-1&&(cn++,un=0);for(let e=0;e<cn;e++)Zn(e)}function qn(){et.background(ct),Ue.background(255),Ue.rectMode(CENTER),ne(Ue),Ue.textAlign(CENTERM ,CENTER),Ue.textStyle(BOLD),Ue.stroke(st),Ue.strokeWeight(8*le),Ue.fill(ct),Qe.background(255),Qe.rectMode(CENTER),ne(Qe),Qe.strokeWeight(le),qe.background(255),qe.rectMode(CENTER),ne(qe),qe.textAlign(LEFT),$e.background(255),$e.rectMode(CENTER),ne($e),Xe.background(255),ne(Xe),Xe.strokeWeight(Ne),We.background(255),We.rectMode(CENTER),ne(We),We.fill(st),We.stroke(st),We.strokeWeight(.1*le),er(lt),We.noStroke(),xn&&(We.rect(ae/16,height/2,ae/8,height),We.rect(width-ae/16,height/2,ae/8,height),We.rect(width/2,ae/16,M width,ae/8),We.rect(width/2,height-ae/16,width,ae/8)),Ze.background(255),Ze.rectMode(CENTER),ne(Ze),Ze.textAlign(CENTER,CENTER),Ze.textStyle(BOLD),Ze.stroke(st),Ze.strokeWeight(8*le),Ze.fill(ct),je.background(255),je.rectMode(CENTER),ne(je),je.textAlign(CENTER,CENTER),je.textStyle(BOLD),Ke.background(255),Ke.rectMode(CENTER),ne(Ke),Ke.textAlign(CENTER,CENTER),Ke.textStyle(BOLD),Ke.stroke(st),Ke.strokeWeight(8*le),Ke.fill(ct),Je.background(255),Je.rectMode(CENTER),ne(Je),Je.textAlign(CENTER,CENTER),Je.textStyle(BOLDM ),Je.stroke(st),Je.strokeWeight(8*le),Je.fill(ct),Un(),et.image(We,0,0),Pt&&An(),et.image(Xe,0,0),et.image($e,0,0),At&&(tr(),et.image(Ue,0,0)),fn&&(lr(),et.image(Ze,0,0)),Lt&&(or(),et.image(Ke,0,0)),Dt&&(ir(),et.image(qe,0,0)),yn&&(Bn(),et.image(Je,0,0))}function draw(){const e=Date.now();bn&&(Ut.updateAge(new Date(e)),Xn()),qn(),image(et,0,0),zn||un++}function Zn(e){let t,n=Ce[e].length,r=Ce[e+1].length;for(let i=0;i<n;i++){const[n,o]=Hn(e,i);for(let a=0;a<r;a++){const[r,l]=Hn(e+1,a);t=map(min(Ce[e][i],Ce[e+1][a])M ,0,1,0,.5),ur(n,o,r,l,bt[e],bt[e+1],Xe,t)}}}function Kn(e,t,n,r){let i,o,a,l=Ce[e].length;for(let s=0;s<l;s++){const[l,h]=Hn(e,s);i=Ce[e][s],a=map(Be,1/30,1,3,10),o=map(Ce[e][s],0,1,2*a,0)*le,o<1.5*le&&(o=0),Qn(l,h,ze,Oe,t,n,o,i,r)}}function Jn(e,t,n,r,i){for(let o=0;o<Le[e].length;o++)Qn(Le[e][o][0],Le[e][o][1],t,Oe,n,r,0,1,i)}function Qn(e,t,n,r,i,o,a,l,s){s.stroke(dr(o,map(l,0,1,.25,1))),s.fill(dr(i,map(l,0,1,.15,1))),s.strokeWeight(Fe),fr([a],s),3==dt&&s.fill(dr(i,0)),1==r?s.ellipse(e,t,n):2==r?s.rect(e,t,7*n/8M ,7*n/8):3==r&&(s.beginShape(),s.vertex(e-4*n/7,t),s.vertex(e,t-4*n/7),s.vertex(e+4*n/7,t),s.vertex(e,t+4*n/7),s.endShape(CLOSE))}function er(e){if(1==e);else if(2==e){We.strokeWeight(1*le);for(let e=ht/4;e<width+ht/4;e+=ht)for(let t=ht/4;t<height+ht/4;t+=ht)We.point(e,t)}else if(3==e){ht=25*le;for(let e=ht/2;e<height+ht/2;e+=ht)We.line(0,e,width,e);for(let e=ht/2;e<width+ht/2;e+=ht)We.line(e,0,e,height)}}function tr(){Ue.textFont("Trebuchet MS"),Ue.textAlign(LEFT,CENTER),Ue.noStroke(),pr(Ue,800*le,500*le),Ue.noStroM ke(),Ue.fill(dr(st,.75)),Ue.rect(width/2,height/2-100*le,800*le,300*le,25*le,25*le,0,0),Ue.fill(st),Ue.rect(width/2-250*le,height/2-100*le,225*le,225*le),Ue.image(se.elt,width/2-357.5*le,height/2-207.5*le,215*le,215*le);let e=100*Zt[0][0];Ue.fill(ct),Ue.textSize(25*le),Ue.textStyle(NORMAL),1==me&&(e>=0&&e<20?Ue.text("I have a feeling this image belongs to",width/2-100*le,height/2-170*le):e>=20&&e<40?Ue.text("I have a hunch this image belongs to",width/2-100*le,height/2-170*le):e>=40&&e<60?Ue.text("I think this imagM e belongs to",width/2-100*le,height/2-170*le):e>=60&&e<80?Ue.text("I'm almost certain this image belongs to",width/2-100*le,height/2-170*le):Ue.text("I'm positive this image belongs to",width/2-100*le,height/2-170*le));let t=e.toFixed(2);"100.00"==t&&(t="100"),1==me&&Ue.text("I'm "+t+"% confident that I'm right!",width/2-100*le,height/2-25*le),example=Zt.map((e=>e[1])),be=Ue.textWidth('"FIDENZAAAA"'),defaultPhrase=Ue.textWidth('"PERPENDICULAR INHABITATION"'),Ue.textStyle(BOLD);const n=me?example[0]:random(example);M if(1===n.split(" ").length){let e=75*be/Ue.textWidth('"'+n+'"');e>75&&(e=75),Ue.textSize(e*le),Ue.text('"'+n+'"',width/2-100*le,height/2-90*le)}else nr(width/2-100*le,height/2-90*le,460*le,110*le,n,Ue);if(millis()-ye>1500&&(me=!0),C(tt,nt,st,ct,Pe,Mt),Ue.image(nt,width/2-370*le,height/2+70*le,80*le,80*le),3==Pe){let e;e=map(Mt,50,60,.25,1.3),I(rt,e),Ue.image(rt,width/2-370*le,height/2+70*le,80*le,80*le)}let r,i;Ue.image(tt,width/2-370*le,height/2+70*le,80*le,80*le),Ue.fill(xt),Ue.textSize(40*le),Ue.text("INTELLIGENM CE INFO",width/2-275*le,height/2+115*le),Ue.textSize(18*le),Ue.textStyle(NORMAL),Ue.circle(width/2-360*le,height/2+180*le,7.5*le),1==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s growing and getting smarter by the day.`:2==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s stable and it has reached peak performance.`:3==Pe&&(r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s decaying and losing its luster.`),i=2==Pe?"The Perceptron remains stable for some time before entering the decay M phase.":`Wait until ${new Date(an).toLocaleString("en-US")} for your Perceptron to reach its peak performance.`,Ue.text(r,width/2-350*le,height/2+180*le),Ue.circle(width/2-360*le,height/2+210*le,7.5*le),Ue.text(i,width/2-350*le,height/2+210*le),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),gr(Ue,width/2-225*le,width/2+65*le,height/2+265*le,height/2+305*le,"SELECT ANOTHER IMAGE"),gr(Ue,width/2+75*le,width/2+225*le,height/2+265*le,height/2+305*le,"CLOSE")}function nr(e,t,n,r,i,o){let a=i.split(" "),l=75*be/o.textWidM th('"'+i+'"'),s=0,h=[],c=[],u=[],f="",d="";if(l>=50)l>75&&(l=75),o.textSize(l*le),o.text('"'+i+'"',e,t);else if(l<50){if(l=50*defaultPhrase/o.textWidth('"'+i+'"'),l>30){if(l>50&&(l=50),[f,d]=rr(l,n,s,h,c,a,f,d,Ue),0==c.length)return o.textSize(l*le),void o.text('"'+i+'"',e,t);for(s=0,h=[],c=[];o.textWidth(d)>n/le;)l=l*n/le/o.textWidth(d),f="",d="",[f,d]=rr(l,n,s,h,c,a,f,d,Ue)}else{l=30,o.textSize(l);for(let e=0;e<a.length;e++)s+=o.textWidth(" "+a[e]),s<=n/le?h.push(a[e]):s>n/le&&s<=n/le*2?c.push(a[e]):u.push(a[e]);M for(let e=1;e<h.length;e++)f=f+" "+h[e];if(f='"'+h[0]+f,0==u.length){for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+c[c.length-1]+'"'}else if(1==c.length)d="... "+u[u.length-1]+'"';else{for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+"... "+u[u.length-1]+'"'}}o.textSize(l*le);let r=1.25*(o.textDescent()+o.textAscent());o.text(f,e,t-r/2),o.text(d,e,t+r/2)}}function rr(e,t,n,r,i,o,a,l,s){s.textSize(e);for(let e=0;e<o.length;e++)(n+=s.textWidth(" "+o[e]))<=t/le?r.push(o[e]):i.push(o[e]);for(let e=1;e<r.length;e++)a=a+" "M +r[e];if(a='"'+r[0]+a,0==i.length&&(a+='"',l=""),1==i.length)l=i[i.length-1]+'"';else{for(let e=0;e<i.length-1;e++)l=l+i[e]+" ";l=l+i[i.length-1]+'"'}return[a,l]}function ir(){const e=45*le;qe.textFont("Tahoma"),qe.stroke(st),qe.strokeWeight(2*le),qe.fill(ct),qe.rect(width/2,e/2+height-87.5*le,600*le,90*le),qe.fill(st),qe.rect(width/2-150*le,e+height-170*le,300*le,30*le),qe.fill(ct),qe.rect(width/2+150*le,e+height-170*le,300*le,30*le),qe.noStroke(),qe.fill(ct),qe.textSize(15*le),qe.textStyle(BOLD),qe.text("PERCEPTRM ON INFORMATION",width/2-285*le,e+height-165*le),qe.fill(xt),qe.text("ARTWORK NAME:",width/2+10*le,e+height-165*le),qe.textAlign(RIGHT),qe.textStyle(ITALIC),qe.text("Perceptron #"+Et,width/2+285*le,e+height-165*le);const[t,n]=It.split(" ");let r;"60 Years"===It?r="1 Year":"60 Months"===It?r="1 Month":"60 Weeks"===It?r="1 Week":"60 Days"===It?r="1 Day":"12 Hours"===It&&(r="12 Minutes"),data=[["AI MODEL NAME:",B(12*le,Ht,140*le)],["SCALE:","1:"+Te],["NUMBER OF CLASSES:",$t.length],["BIRTH YEAR:",Rt],["NUMBER OF REBIRTM HS:",sn.toString()],["AGE:",`${Math.ceil(Mt)} Perceptron Years`],["ONE PERCEPTRON YEAR:",`${r}`],["STATE:",Ot[Pe]],["ACTIVE NEURONS:",`${round(ln*rn)} / ${ln}`],["NEXT STATE TIME:",vr(new Date(on))]],qe.fill(xt);const i=data.length/2;for(let t=0;t<data.length;++t){const n=t<i,r=n?width/2-285*le:width/2+10*le,o=n?width/2-10*le:width/2+285*le,a=e+height-(135-t%i*15)*le;qe.textStyle(BOLD),qe.textAlign(LEFT),qe.textSize(12*le),qe.text(data[t][0],r,a),qe.textStyle(ITALIC),qe.textAlign(RIGHT),qe.textSize(12*le),qe.text(dM ata[t][1],o,a)}}function or(){Ke.textFont("Trebuchet MS"),Ke.noStroke(),pr(Ke,600*le,200*le),gr(Ke,width/2-155*le,width/2-5*le,height/2+115*le,height/2+155*le,"UPDATE"),gr(Ke,width/2+5*le,width/2+155*le,height/2+115*le,height/2+155*le,"CLOSE"),Ke.textAlign(LEFT),Ke.fill(xt),Ke.text("UPDATE BITCOIN FULL NODE ADDRESS",width/2-252.5*le,height/2-55*le),Ke.text("UPDATE MODEL ADDRESS",width/2-252.5*le,height/2+20*le),Ke.textAlign(RIGHT),Ke.textStyle(ITALIC),Ke.textSize(15*le),0==wn&&Ke.text("(*) Invalid Address",width/2+M 252.5*le,height/2-53*le),0==vn&&Ke.text("(*) Invalid Model",width/2+252.5*le,height/2+23*le)}function ar(){je.textFont("Trebuchet MS"),je.fill(st),je.textSize(50*le),je.stroke(st),je.strokeWeight(1*le),je.text("main()",width/2,height/2)}function lr(){un>=20&&1==dn&&(dn=!1,un=0),dn&&(Ze.textFont("Trebuchet MS"),Ze.stroke(st),Ze.fill(ct),Ze.rect(width/2,height/2,600*le,150*le,25*le),Ze.fill(xt),Ze.textSize(75*le),Ze.noStroke(),1==Pe?Ze.text("GROWING",width/2,height/2+5*le):3==Pe?Ze.text("AGING",width/2,height/2+5*le)M :4==Pe?Ze.text("DEAD",width/2,height/2+5*le):5==Pe&&Ze.text("BIRTH",width/2,height/2+5*le)),un>=20&&0==dn&&(dn=!0,un=0,Bt++,3==Bt&&(fn=!1))}function sr(e,t,n,r){let i=[],o=r/(n.length+1),a=color(e),l=color(t);i.push(a);for(let e=0;e<n.length;e++){let t=color(n[e]);for(let e=1;e<=o;e++){let n=lerpColor(a,t,e/o);i.push(n)}a=t}for(let e=1;e<o;e++){let t=lerpColor(a,l,e/o);i.push(t)}if(i.push(l),i.length>r)i.splice(r);else if(i.length<r){let e=i[i.length-1];for(;i.length<r;)i.push(e)}return i}function hr(e,t){let n=e.lM ength,r=Math.floor(t*n);return r>=n&&(r=n-1),e[r]}function cr(e){e=e.replace("#","");var t=parseInt(e,16);return color(t>>16&255,t>>8&255,255&t)}function ur(e,t,n,r,i,o,a,l){var s=a.drawingContext.createLinearGradient(e,t,n,r);s.addColorStop(0,i),s.addColorStop(1,o),a.drawingContext.strokeStyle=s,a.drawingContext.globalAlpha=l,a.line(e,t,n,r),a.drawingContext.globalAlpha=1}function fr(e,t){t.drawingContext.setLineDash(e)}function dr(e,t){let n=color(e),r=red(n),i=green(n),o=blue(n);return color(r,i,o,255*t)}functioM n xr(e,t,n,r){return mouseX>e&&mouseX<t&&mouseY>n&&mouseY<r}function gr(e,t,n,r,i,o){e.strokeWeight(1*le),e.stroke(st);const[a,l]=xr(t,n,r,i)?[xt,ct]:[ct,xt];e.fill(a),e.push(),e.rectMode(CORNERS),e.rect(t,r,n,i,5*le),e.pop(),e.noStroke(),e.textSize(20*le),e.fill(l),e.text(o,(t+n)/2,(46*r+54*i)/100)}function pr(e,t,n){e.fill(0,0,0,75),e.rect(width/2,height/2,width,height),e.stroke(st),e.fill(ct),e.rect(width/2,height/2,t,n,25*le)}function mr(e,t){resizeCanvas(e,t,!0),Xe.resizeCanvas(e,t,!0),$e.resizeCanvas(e,t,!0),M We.resizeCanvas(e,t,!0),Ue.resizeCanvas(e,t,!0),qe.resizeCanvas(e,t,!0),Qe.resizeCanvas(e,t,!0),je.resizeCanvas(e,t,!0),Ze.resizeCanvas(e,t,!0),Ke.resizeCanvas(e,t,!0),Je.resizeCanvas(e,t,!0),et.resizeCanvas(e,t,!0)}function br(e,t,n,r,i,o){const a=J(e);return a.position(t,n),a.size(r,i),a.style("opacity","0"),a.mouseClicked(o),a}function yr(){return null!=vt&&vt?.isFocused()||null!=zt&&zt?.isFocused()}function wr(e,t,n,r){let i;if(e<=3){i=`Hey ${String.fromCodePoint(128075)}, I'm ${n}, ${t} years old. I can detectM ${r.length} NFT collections: `;let e=0;for(let t=0;t<r.length;++t){const n=r[t];if(e+n.length>500){i+=", etc";break}t==r.length-1?i+=", and ":t>0&&(i+=", "),i+=n,e+=n.length}i+=". ",t<=5?i+="However, I am only a baby, so my recognition ability is not accurate. I'm in the state of Growing both looks and intelligence.":t<=13?i+="I am now a child. My recognition ability is becoming better, but still not very accurate. I'm in the state of Growing both looks and intelligence.":t<=25?i+="I have grown up to be a teen. MyM recognition ability almost reaches the peak, but I will still mess up sometimes. I'm in the state of Growing both looks and intelligence.":t<=50?i+="I finally reach adulthood. My recognition is fully functional now. I'm in the Stable state, where I am the most intelligent with all neurons activated.":t<=60&&(i+="I am now an old Perceptron, so my recognition ability is no longer the best. I'm in the Decaying state, meaning that my neurons are dying, and my intelligence is decreasing over time.")}else 4==e?i=`${n} iM s Dead. However, this is not the end to its story...`:5==e&&(i=`${n} is now in the Rebirth state, and is preparing to start a new life.`);return i}function vr(e){const t=e.getDate(),n=e.toLocaleString("en-US",{month:"long"}),r=e.getFullYear();let i=e.getHours().toString();1==i.length&&(i="0"+i);let o=e.getMinutes().toString();return 1==o.length&&(o="0"+o),`${Y(t)} ${n} ${r} | ${i}:${o}`}saveCanvasAtCurrentTime=()=>{save(N())},save4KCanvasAtCurrentTime=()=>{const e=width,t=height,n=min(4096/min(e,t),1e4/max(e,t)),r=M e*n,i=t*n;mr(r,i),zn=!0,$n(r,i),qn();let o="4K_"+N()+".png";saveCanvas(et,o),mr(e,t),$n(e,t),zn=!1};const zr=[["60 Years",3,365],["60 Months",40,30],["60 Weeks",37,7],["60 Days",20,1]],Vr=[["1943",1],["1951",1.5],["1957",2],["1969",2.5],["1970",3],["1980",3.5],["1982",4],["1986",4.5],["1988",5],["1997",5.5],["1998",6],["2002",6.5],["2009",7],["2012",7.5],["2014",8],["2015",8.5],["2016",9],["2023",15]],_r=[["Plain",20],["Dotted",40],["Squared",40]],Mr=[["Basic",30],["Standard",60],["Advanced",10]],Er=[["MNIST",70],[M "CIFAR",25],["IMAGENET",5]],Sr=[["Theano",60],["Torch",30],["TensorFlow",10]],Rr=[["Whitepaper",2],["Blackboard",2],["Blueprint",2],["Nak",74/14],["Jims",74/14],["Level 10",74/14],["Flips",74/14],["Level 14",74/14],["III",74/14],["XMB",74/14],["Info",74/14],["Adventure",74/14],["Marigold",74/14],["Phoenix",74/14],["Love",74/14],["Cachet",74/14],["Human",74/14],["Twilight",3],["Sunset",3],["Aurora",3],["Liminal Space",3],["D Vu",3],["Lucid Dream",3],["Parallel",1],["Multiverse",1]];function Ir(e){for(let e=0;e<M 100;++e)random(1);return{visual:{pattern:k(_r),hardwareAcceleration:k(Mr),nodeFill:k(Er),nodeShape:k(Sr),colorPalette:k(Rr),lifeCycle:k(zr),birthYear:k(Vr)},training:e}}function Cr(e){window.$generativeTraits={"Network Architecture":e.training.structure_gen,"Hidden Layers":e.training.n_layers,"Max Neurons Per Hidden Layer":e.training.max_nodes,"Activation Function":e.training.activation_func,"Training Epochs":e.training.epoch_num,Dataset:e.visual.nodeFill,"Deep Learning Framework":e.visual.nodeShape,"Hardware AccelM eration":e.visual.hardwareAcceleration,"Paper Pattern":e.visual.pattern,"Life Cycle":e.visual.lifeCycle,"Birth Year":e.visual.birthYear,"Color Palette":e.visual.colorPalette}} <script defer src="https://static.cloudflareinsights.com/beacon.min.js/v2b4487d741ca48dcbadcaf954e159fc61680799950996" integrity="sha512-D/jdE0CypeVxFadTejKGTzmwyV10c1pxZk/AqjJuZbaJwGMyNHY3q/mTPWqMUnFACfCTunhZUVcd4cV78dK1pQ==" data-cf-beacon='{"rayId":"7b481dc80a1aa1e7","version":"2023.3.0","b":1,"token":"6c07c178c94442f695e7aJ0a2aaee641a","si":100}' crossorigin="anonymous"></script> text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "undead staff"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "honey pot"}, {"trait_type": "Eyes", "value": "golden"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "bag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "blue fire"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "shield"}]} text/plain;charset=utf-8 {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "lightning bolt"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "bloody"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "pauldrons"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "tiger"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "wizard staff"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "badger"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "golden"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "undead staff"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "poisoned dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "moon"}, {"trait_type": "Body", "value": "robot"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "badger"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "fire"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "axe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "wizard staff"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "golden"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "quiver"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "golden armor"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "wizard staff"}]} text/plain;charset=utf-8 ({"p":"sns","op":"reg","name":" {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "wizard sM {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "bloody"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "bag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "pirate flag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "axe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "golden armor"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "honey pot"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "zombie"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "dagger"}]} text/plain;charset=utf-8 ({"p":"sns","op":"reg","name":" {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "undead"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "laser beams"}, {"trait_type": "Headgear", "value": "crown"}, {"trait_type": "Artifacts", "value": "dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "robot"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "broadsword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "moon"}, {"trait_type": "Body", "value": "silver"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "blue fire"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "eagle"}]} text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "golden"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "wizard staff"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "rainbow"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "undead"}, {"trait_type": "Artifacts", "value": "arrow wounds"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "wizard stafM {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "cape"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "moon"}, {"trait_type": "Body", "value": "tiger"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "sword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "mage robes"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "blue fire"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "frozen staff"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "tribal tattoo"}, {"trait_type": "Mane", "value": "fire"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "laser"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "arrow wounds"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "rainbow"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "shield"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "undead"}, {"trait_type": "Artifacts", "value": "poisoned dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "tribal tattoo"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "fire"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "undead"}, {"trait_type": "Artifacts", "value": "parrot"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "wizard staff"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "axe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "honey pot"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "bag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "moon"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "golden"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "arrow wounds"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "moon"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "axe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "rainbow"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "orc"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "pauldrons"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "moon"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "whale"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "orc"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "honey pot"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "bag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "axe"}]} text/plain;charset=utf-8 H{"p":"brc-20","op":"deploy","tick":"ANON","max":"11051605","lim":"2009"}h! text/html;charset=utf-8 <meta charset="utf-8" /> position: relative; width: var(--width); height: var(--height); border: 1px solid blue; position: relative; <div id="upload"> <input id="inputUpload" type="file"> function e(e){"use strict";return new function e(t){let n="global"==t?window:this;n.canvas=document.createElement("canvas");let r=n.canvas.getContext("2d");n.width=100,n.height=100,n.canvas.width=n.width,n.canvas.height=n.height,"offscreen"!=t&&(document.body?document.body.appendChild(n.canvas):window.addEventListener("load",(function(){document.body.appendChild(n.canvas)}))),g(),n.MAGIC=161533525,n.RGB=0,n.HSV=1,n.HM SB=1,n.CHORD=0,n.PIE=1,n.OPEN=2,n.RADIUS=1,n.CORNER=2,n.CORNERS=3,n.ROUND="round",n.SQUARE="butt",n.PROJECT="square",n.MITER="miter",n.BEVEL="bevel",n.CLOSE=1,n.BLEND="source-over",n.REMOVE="destination-out",n.ADD="lighter",n.DARKEST="darken",n.LIGHTEST="lighten",n.DIFFERENCE="difference",n.SUBTRACT="subtract",n.EXCLUSION="exclusion",n.MULTIPLY="multiply",n.SCREEN="screen",n.REPLACE="copy",n.OVERLAY="overlay",n.HARD_LIGHT="hard-light",n.SOFT_LIGHT="soft-light",n.DODGE="color-dodge",n.BURN="color-burn",n.NORMAL="norM mal",n.ITALIC="italic",n.BOLD="bold",n.BOLDITALIC="italic bold",n.CENTER="center",n.LEFT="left",n.RIGHT="right",n.TOP="top",n.BOTTOM="bottom",n.BASELINE="alphabetic",n.LANDSCAPE="landscape",n.PORTRAIT="portrait",n.ALT=18,n.BACKSPACE=8,n.CONTROL=17,n.DELETE=46,n.DOWN_ARROW=40,n.ENTER=13,n.ESCAPE=27,n.LEFT_ARROW=37,n.OPTION=18,n.RETURN=13,n.RIGHT_ARROW=39,n.SHIFT=16,n.TAB=9,n.UP_ARROW=38,n.HALF_PI=Math.PI/2,n.PI=Math.PI,n.QUARTER_PI=Math.PI/4,n.TAU=2*Math.PI,n.TWO_PI=2*Math.PI,n.THRESHOLD=1,n.GRAY=2,n.OPAQUE=3,n.INVEM RT=4,n.POSTERIZE=5,n.DILATE=6,n.ERODE=7,n.BLUR=8,n.ARROW="default",n.CROSS="crosshair",n.HAND="pointer",n.MOVE="move",n.TEXT="text",n.VIDEO={video:!0,audio:!1},n.AUDIO={video:!1,audio:!0},n.SHR3=1,n.LCG=2,n.HARDWARE_FILTERS=!0,n.hint=function(e,t){n[e]=t},n.frameCount=0,n.mouseX=0,n.mouseY=0,n.pmouseX=0,n.pmouseY=0,n.mouseButton=null,n.keyIsPressed=!1,n.mouseIsPressed=!1,n.key=null,n.keyCode=null,n.pixels=null,n.accelerationX=0,n.accelerationY=0,n.accelerationZ=0,n.rotationX=0,n.rotationY=0,n.rotationZ=0,n.relRotatM ionX=0,n.relRotationY=0,n.relRotationZ=0,n.pAccelerationX=0,n.pAccelerationY=0,n.pAccelerationZ=0,n.pRotationX=0,n.pRotationY=0,n.pRotationZ=0,n.pRelRotationX=0,n.pRelRotationY=0,n.pRelRotationZ=0,n.touches=[],n._styleCache=[{colorMode:n.RGB,noStroke:!1,noFill:!1,ellipseMode:n.CENTER,rectMode:n.CORNER,curveDetail:20,curveAlpha:0,textFont:"sans-serif",textSize:12,textLeading:12,textStyle:"normal"}],n._style=n._styleCache[n._styleCache.length-1],n._noLoop=!1,n._pixelDensity=1,n._frameRate=null,n._tint=null;let i=nullM ,o=!0,a=[],l=null,s=0,h={},c=0,u=null,f=null,d=null;Object.defineProperty(n,"deviceOrientation",{get:function(){return 90==Math.abs(window.orientation)?n.LANDSCAPE:n.PORTRAIT}}),Object.defineProperty(n,"windowWidth",{get:function(){return window.innerWidth}}),Object.defineProperty(n,"windowHeight",{get:function(){return window.innerHeight}}),Object.defineProperty(n,"drawingContext",{get:function(){return r}}),n.createCanvas=function(e,t){return n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t,g(),n.canvas},nM .resizeCanvas=function(e,t){n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t},n.createGraphics=n.createImage=function(t,n){let r=new e("offscreen");return r.createCanvas(t,n),r.noLoop(),r},n.pixelDensity=function(e){return null==e||(n._pixelDensity=e,n.canvas.width=Math.ceil(n.width*e),n.canvas.height=Math.ceil(n.height*e),n.canvas.style.width=n.width+"px",n.canvas.style.height=n.height+"px",r.scale(n._pixelDensity,n._pixelDensity),g()),n._pixelDensity},n.map=function(e,t,n,r,i,o){let a=r+1*(e-t)/(n-t)*(i-r)M ;return o?r<i?Math.min(Math.max(a,r),i):Math.min(Math.max(a,i),r):a},n.lerp=function(e,t,n){return e*(1-n)+t*n},n.constrain=function(e,t,n){return Math.min(Math.max(e,t),n)},n.dist=function(){return 4==arguments.length?Math.hypot(arguments[0]-arguments[2],arguments[1]-arguments[3]):Math.hypot(arguments[0]-arguments[3],arguments[1]-arguments[4],arguments[2]-arguments[5])},n.norm=function(e,t,r){return n.map(e,t,r,0,1)},n.sq=function(e){return e*e},n.fract=function(e){return e-Math.floor(e)},n.degrees=function(e){retM urn 180*e/Math.PI},n.radians=function(e){return e*Math.PI/180},n.abs=Math.abs,n.ceil=Math.ceil,n.exp=Math.exp,n.floor=Math.floor,n.log=Math.log,n.mag=Math.hypot,n.max=Math.max,n.min=Math.min,n.round=Math.round,n.sqrt=Math.sqrt,n.sin=Math.sin,n.cos=Math.cos,n.tan=Math.tan,n.asin=Math.asin,n.acos=Math.acos,n.atan=Math.atan,n.atan2=Math.atan2,n.Vector=function(e,t,r){let i=this;i.x=e||0,i.y=t||0,i.z=r||0;let o=null,a=null;function l(e,t,n){return null!=e.x?e:null!=t?{x:e,y:t,z:n||0}:{x:e,y:e,z:e}}function s(){null==a&M &(a=i.x*i.x+i.y*i.y+i.z*i.z,o=Math.sqrt(a))}function h(){a=null,o=null}i.set=function(e,t,n){i.x=e||0,i.y=t||0,i.z=n||0},i.copy=function(){return new n.Vector(i.x,i.y,i.z)},i.add=function(){let e=l.apply(null,arguments);return i.x+=e.x,i.y+=e.y,i.z+=e.z,h(),i},i.rem=function(){let e=l.apply(null,arguments);return i.x%=e.x,i.y%=e.y,i.z%=e.z,h(),i},i.sub=function(){let e=l.apply(null,arguments);return i.x-=e.x,i.y-=e.y,i.z-=e.z,h(),i},i.mult=function(){let e=l.apply(null,arguments);return i.x*=e.x,i.y*=e.y,i.z*=e.z,hM (),i},i.div=function(){let e=l.apply(null,arguments);return i.x/=e.x,i.y/=e.y,i.z/=e.z,h(),i},i.mag=function(){return s(),o},i.magSq=function(){return s(),a},i.dot=function(){let e=l.apply(null,arguments);return i.x*e.x+i.y*e.y+i.z*e.z},i.dist=function(){let e=l.apply(null,arguments),t=i.x-e.x,n=i.y-e.y,r=i.z-e.z;return Math.sqrt(t*t+n*n+r*r)},i.cross=function(){let e=l.apply(null,arguments),t=i.y*e.z-i.z*e.y,n=i.z*e.x-i.x*e.z,r=i.x*e.y-i.y*e.x;return i.x=t,i.y=n,i.z=r,h(),i},i.normalize=function(){s();let e=o;retuM rn i.x/=e,i.y/=e,i.z/=e,o=1,a=1,i},i.limit=function(e){s();if(o>e){let t=e/o;i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e}return i},i.setMag=function(e){s();let t=e/o;return i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e,i},i.heading=function(){return Math.atan2(i.y,i.x)},i.rotate=function(e){let t=Math.cos(e),n=Math.sin(e),r=i.x*t-i.y*n,o=i.x*n+i.y*t;return i.x=r,i.y=o,i},i.angleBetween=function(){let e=l.apply(null,arguments);const t=i.dot(e)/(i.mag()*e.mag());let n;return n=Math.acos(Math.min(1,Math.max(-1,t))),n*Math.sign(i.cross(e).z||1)},M i.lerp=function(e,t){return i.x=i.x*(1-t)+e.x*t,i.y=i.y*(1-t)+e.y*t,i.z=i.z*(1-t)+e.z*t,h(),i},i.reflect=function(e){return e.normalize(),i.sub(e.mult(2*i.dot(e)))},i.array=function(){return[i.x,i.y,i.z]},i.equals=function(e,t){return null==t&&null==(t=Number.EPSILON)&&(t=0),Math.abs(e.x-i.x)<t&&Math.abs(e.y-i.y)<t&&Math.abs(e.z-i.z)<t},i.fromAngle=function(e,t){return null==t&&(t=1),o=t,a=t*t,i.x=t*Math.cos(e),i.y=t*Math.sin(e),i.z=0,i},i.fromAngles=function(e,t,n){null==n&&(n=1),o=n,a=n*n;const r=Math.cos(t),l=MaM th.sin(t),s=Math.cos(e),h=Math.sin(e);return i.x=n*h*l,i.y=-n*s,i.z=n*h*r,i},i.random2D=function(){return o=1,a=1,i.fromAngle(Math.random()*Math.PI*2)},i.random3D=function(){return o=1,a=1,i.fromAngles(Math.random()*Math.PI*2,Math.random()*Math.PI*2)},i.toString=function(){return`[${i.x}, ${i.y}, ${i.z}]`}},n.Vector.add=function(e,t){return new n.Vector(e.x+t.x,e.y+t.y,e.z+t.z)},n.Vector.rem=function(e,t){return new n.Vector(e.x%t.x,e.y%t.y,e.z%t.z)},n.Vector.sub=function(e,t){return new n.Vector(e.x-t.x,e.y-t.y,e.M z-t.z)},n.Vector.mult=function(e,t){return null==t.x?new n.Vector(e.x*t,e.y*t,e.z*t):new n.Vector(e.x*t.x,e.y*t.y,e.z*t.z)},n.Vector.div=function(e,t){return null==t.x?new n.Vector(e.x/t,e.y/t,e.z/t):new n.Vector(e.x/t.x,e.y/t.y,e.z/t.z)},n.Vector.dist=function(e,t){return Math.hypot(e.x-t.x,e.y-t.y,e.z-t.z)},n.Vector.cross=function(e,t){return new n.Vector(e.y*t.z-e.z*t.y,e.z*t.x-e.x*t.z,e.x*t.y-e.y*t.x)},n.Vector.lerp=function(e,t,r){return new n.Vector(e.x*(1-r)+t.x*r,e.y=e.y*(1-r)+t.y*r,e.z=e.z*(1-r)+t.z*r)},n.M Vector.equals=function(e,t,n){return e.equals(t,n)};for(let e of["fromAngle","fromAngles","random2D","random3D"])n.Vector[e]=function(t,r,i){return(new n.Vector)[e](t,r,i)};function x(e,t,n){let r,i,o,a,l,s,h,c,u;if(0==t)return[255*(r=n),255*(i=n),255*(o=n)];switch((a=e)>360&&(a=0),h=n*(1-t),c=n*(1-t*(s=(a/=60)-(l=~~a))),u=n*(1-t*(1-s)),l){case 0:r=n,i=u,o=h;break;case 1:r=c,i=n,o=h;break;case 2:r=h,i=n,o=u;break;case 3:r=h,i=c,o=n;break;case 4:r=u,i=h,o=n;break;default:r=n,i=h,o=c}return[255*r,255*i,255*o]}functioM n g(){r.fillStyle="white",r.strokeStyle="black",r.lineCap="round",r.lineJoin="miter"}function p(e){if(0<=e&&e<2*Math.PI)return e;for(;e<0;)e+=2*Math.PI;for(;e>=Math.PI;)e-=2*Math.PI;return e}function m(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;let c=p(a),u=p(l);r.beginPath();for(let a=0;a<h+1;a++){let l=a/h,s=n.lerp(c,u,l),f=Math.cos(s)*i/2,d=Math.sin(s)*o/2;r[a?"lineTo":"moveTo"](e+f,t+d)}s==n.CHORD?r.closePath():s==n.PIE&&(r.lineTo(e,t),r.closePath()),n._style.noFill||r.fill(),n._style.noStrokM e||r.stroke()}function b(e,t,i,o){n._style.noFill&&n._style.noStroke||(r.beginPath(),r.ellipse(e,t,i/2,o/2,0,0,2*Math.PI),n._style.noFill||r.fill(),n._style.noStroke||r.stroke())}function y(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;if(null==a)return function(e,t,i,o){n._style.noFill||r.fillRect(e,t,i,o),n._style.noStroke||r.strokeRect(e,t,i,o)}(e,t,i,o);if(null==l)return y(e,t,i,o,a,a,a,a);const c=Math.min(Math.abs(o),Math.abs(i))/2;a=Math.min(c,a),l=Math.min(c,l),h=Math.min(c,h),s=Math.min(c,s)M ,r.beginPath(),r.moveTo(e+a,t),r.arcTo(e+i,t,e+i,t+o,l),r.arcTo(e+i,t+o,e,t+o,s),r.arcTo(e,t+o,e,t,h),r.arcTo(e,t,e+i,t,a),r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke()}function w(){a=[]}n.createVector=function(e,t,r){return new n.Vector(e,t,r)},n.curvePoint=function(e,t,n,r,i){const o=i*i*i,a=i*i;return e*(-.5*o+a-.5*i)+t*(1.5*o-2.5*a+1)+n*(-1.5*o+2*a+.5*i)+r*(.5*o-.5*a)},n.bezierPoint=function(e,t,n,r,i){const o=1-i;return Math.pow(o,3)*e+3*Math.pow(o,2)*i*t+3*o*Math.pow(i,2)*n+Math.pow(i,M 3)*r},n.curveTangent=function(e,t,n,r,i){const o=i*i;return e*(-3*o/2+2*i-.5)+t*(9*o/2-5*i)+n*(-9*o/2+4*i+.5)+r*(3*o/2-i)},n.bezierTangent=function(e,t,n,r,i){const o=1-i;return 3*r*Math.pow(i,2)-3*n*Math.pow(i,2)+6*n*o*i-6*t*o*i+3*t*Math.pow(o,2)-3*e*Math.pow(o,2)},n.Color=function(e,t,n,r){let i=this;i.MAGIC=786698,i._r=e,i._g=t,i._b=n,i._a=r,i._h=0,i._s=0,i._v=0,i._hsvInferred=!1,i.setRed=function(e){i._r=e,i._hsvInferred=!1},i.setGreen=function(e){i._g=e,i._hsvInferred=!1},i.setBlue=function(e){i._b=e,i._hsvInfM erred=!1},i.setAlpha=function(e){i._a=e/255,i._hsvInferred=!1},i._inferHSV=function(){i._hsvInferred||([i._h,i._s,i._v]=function(e,t,n){let r,i,o,a,l;return r=e<t?e<n?e:n:t<n?t:n,0==(l=100*(i=e>t?e>n?e:n:t>n?t:n)/255)?[o=0,a=0,l]:0==(a=100*(i-r)/i)?[o=0,a,l]:(o=i==e?0+60*(t-n)/(i-r):i==t?120+60*(n-e)/(i-r):240+60*(e-t)/(i-r),[o,a,l])}(i._r,i._g,i._b),i._hsvInferred=!0)},i.toString=function(){return`rgba(${Math.round(i._r)},${Math.round(i._g)},${Math.round(i._b)},${~~(1e3*i._a)/1e3})`}},n.colorMode=function(e){n._stM yle.colorMode=e},n.color=function(){if(1==arguments.length&&786698==arguments[0].MAGIC)return arguments[0];if(n._style.colorMode==n.RGB){if(1==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],1);if(2==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],arguments[1]/255);if(3==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],1);if(4==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],arguments[3]/255)}else{if(1==argumeM nts.length)return new n.Color(...x(0,0,arguments[0]/100),1);if(2==arguments.length)return new n.Color(...x(0,0,arguments[0]/100),arguments[1]/255);if(3==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),1);if(4==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),arguments[3])}return null},n.red=function(e){return e._r},n.green=function(e){return e._g},n.blue=function(e){return e._b},n.alpha=function(e){return 255*e._a},n.hue=function(e){reM turn e._inferHSV(),e._h},n.saturation=function(e){return e._inferHSV(),e._s},n.brightness=function(e){return e._inferHSV(),e._v},n.lightness=function(e){return 100*(.2126*e._r+.7152*e._g+.0722*e._b)/255},n.lerpColor=function(e,t,r){return n._style.colorMode==n.RGB?new n.Color(n.constrain(n.lerp(e._r,t._r,r),0,255),n.constrain(n.lerp(e._g,t._g,r),0,255),n.constrain(n.lerp(e._b,t._b,r),0,255),n.constrain(n.lerp(e._a,t._a,r),0,1)):(e._inferHSV(),t._inferHSV(),new n.Color(n.constrain(function(e,t,r){var i=[[Math.abs(t-M e),n.map(r,0,1,e,t)],[Math.abs(t+360-e),n.map(r,0,1,e,t+360)],[Math.abs(t-360-e),n.map(r,0,1,e,t-360)]];return i.sort(((e,t)=>e[0]-t[0])),(i[0][1]+720)%360}(e._h,t._h,r),0,360),n.constrain(n.lerp(e._s,t._s,r),0,100),n.constrain(n.lerp(e._v,t._v,r),0,100),n.constrain(n.lerp(e._a,t._a,r),0,1)))},n.strokeWeight=function(e){n._style_noStroke=!1,r.lineWidth=e},n.stroke=function(){if(n._style.noStroke=!1,"string"==typeof arguments[0])return void(r.strokeStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._sM tyle.noStroke=!0:r.strokeStyle=e},n.noStroke=function(){n._style.noStroke=!0},n.fill=function(){if(n._style.noFill=!1,"string"==typeof arguments[0])return void(r.fillStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._style.noFill=!0:r.fillStyle=e},n.noFill=function(){n._style.noFill=!0},n.blendMode=function(e){r.globalCompositeOperation=e},n.strokeCap=function(e){r.lineCap=e},n.strokeJoin=function(e){r.lineJoin=e},n.ellipseMode=function(e){n._style.ellipseMode=e},n.rectMode=function(e){n._style.rectM Mode=e},n.curveDetail=function(e){n._style.curveDetail=e},n.curveAlpha=function(e){n._style.curveAlpha=e},n.curveTightness=function(e){n._style.curveAlpha=e},n.clear=function(){r.clearRect(0,0,n.width,n.height)},n.background=function(){if(arguments[0]&&arguments[0].MAGIC==n.MAGIC)return n.image(arguments[0],0,0,n.width,n.height);r.save(),r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity),r.fillStyle="string"==typeof arguments[0]?arguments[0]:n.color(...Array.from(arguments)),r.fillRect(0,0,n.width,n.heightM ),r.restore()},n.line=function(e,t,i,o){n._style.noStroke||(r.beginPath(),r.moveTo(e,t),r.lineTo(i,o),r.stroke())},n.arc=function(e,t,r,i,o,a,l,s){if(o==a)return n.ellipse(e,t,r,i);null==s&&(s=25),null==l&&(l=n.PIE),n._style.ellipseMode==n.CENTER?m(e,t,r,i,o,a,l,s):n._style.ellipseMode==n.RADIUS?m(e,t,2*r,2*i,o,a,l,s):n._style.ellipseMode==n.CORNER?m(e+r/2,t+i/2,r,i,o,a,l,s):n._style.ellipseMode==n.CORNERS&&m((e+r)/2,(t+i)/2,r-e,i-t,o,a,l,s)},n.ellipse=function(e,t,r,i){null==i&&(i=r),n._style.ellipseMode==n.CENTERM ?b(e,t,r,i):n._style.ellipseMode==n.RADIUS?b(e,t,2*r,2*i):n._style.ellipseMode==n.CORNER?b(e+r/2,t+i/2,r,i):n._style.ellipseMode==n.CORNERS&&b((e+r)/2,(t+i)/2,r-e,i-t)},n.circle=function(e,t,r){return n.ellipse(e,t,r,r)},n.point=function(e,t){e.x&&(t=e.y,e=e.x),r.beginPath(),r.ellipse(e,t,.4,.4,0,0,2*Math.PI),r.stroke()},n.rect=function(e,t,r,i,o,a,l,s){n._style.rectMode==n.CENTER?y(e-r/2,t-i/2,r,i,o,a,l,s):n._style.rectMode==n.RADIUS?y(e-r,t-i,2*r,2*i,o,a,l,s):n._style.rectMode==n.CORNER?y(e,t,r,i,o,a,l,s):n._stylM e.rectMode==n.CORNERS&&y(e,t,r-e,i-t,o,a,l,s)},n.square=function(e,t,r,i,o,a,l){return n.rect(e,t,r,r,i,o,a,l)},n.beginShape=function(){w(),r.beginPath(),o=!0},n.beginContour=function(){r.closePath(),w(),o=!0},n.endContour=function(){w(),o=!0},n.vertex=function(e,t){w(),o?r.moveTo(e,t):r.lineTo(e,t),o=!1},n.bezierVertex=function(e,t,n,i,o,a){w(),r.bezierCurveTo(e,t,n,i,o,a)},n.quadraticVertex=function(e,t,n,i){w(),r.quadraticCurveTo(e,t,n,i)},n.bezier=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.bezierVM ertex(r,i,o,a,l,s),n.endShape()},n.triangle=function(e,t,r,i,o,a){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.endShape(n.CLOSE)},n.quad=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.vertex(l,s),n.endShape(n.CLOSE)},n.endShape=function(e){w(),e&&r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke(),n._style.noFill&&n._style.noStroke&&(r.save(),r.fillStyle="none",r.fill(),r.restore())},n.curveVertex=function(e,t){if(a.push([e,t]),a.length<4)return;M let i=function(e,t,n,r,i,o,a,l,s,h){function c(e,t,n,r,i,o){let a=Math.pow(r-t,2)+Math.pow(i-n,2);return Math.pow(a,.5*o)+e}let u=[],f=c(0,e,t,n,r,h),d=c(f,n,r,i,o,h),x=c(d,i,o,a,l,h);for(let h=0;h<s;h++){let c=f+h/(s-1)*(d-f),g=[(f-c)/(f-0),(c-0)/(f-0),(d-c)/(d-f),(c-f)/(d-f),(x-c)/(x-d),(c-d)/(x-d),(d-c)/(d-0),(c-0)/(d-0),(x-c)/(x-f),(c-f)/(x-f)];for(let e=0;e<g.length;e+=2)isNaN(g[e])&&(g[e]=1,g[e+1]=0),isFinite(g[e])||(g[e]>0?(g[e]=1,g[e+1]=0):(g[e]=0,g[e+1]=1));let p=e*g[0]+n*g[1],m=t*g[0]+r*g[1],b=n*g[2]+i*g[M 3],y=r*g[2]+o*g[3],w=i*g[4]+a*g[5],v=o*g[4]+l*g[5],z=p*g[6]+b*g[7],V=m*g[6]+y*g[7],_=b*g[8]+w*g[9],M=y*g[8]+v*g[9],E=z*g[2]+_*g[3],S=V*g[2]+M*g[3];u.push([E,S])}return u}(...a[a.length-4],...a[a.length-3],...a[a.length-2],...a[a.length-1],n._style.curveDetail,n._style.curveAlpha);for(let e=0;e<i.length;e++)o?r.moveTo(...i[e]):r.lineTo(...i[e]),o=!1},n.curve=function(e,t,r,i,o,a,l,s){n.beginShape(),n.curveVertex(e,t),n.curveVertex(r,i),n.curveVertex(o,a),n.curveVertex(l,s),n.endShape()},n.translate=function(e,t){r.tM ranslate(e,t)},n.rotate=function(e){r.rotate(e)},n.scale=function(e,t){null==t&&(t=e),r.scale(e,t)},n.applyMatrix=function(e,t,n,i,o,a){r.transform(e,t,n,i,o,a)},n.shearX=function(e){r.transform(1,0,Math.tan(e),1,0,0)},n.shearY=function(e){r.transform(1,Math.tan(e),0,1,0,0)},n.resetMatrix=function(){r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity)},n.pushMatrix=n.push=function(){n._styleCache.push({...n._style}),n._style=n._styleCache[n._styleCache.length-1],r.save()},n.popMatrix=n.pop=function(){n._stylM eCache.length-1&&(n._styleCache.pop(),n._style=n._styleCache[n._styleCache.length-1],r.restore())},n.image=function(e,t,i,o,a,l,s,h,c){let u=e.MAGIC==n.MAGIC?e.canvas:e;function d(){if(e.MAGIC!=n.MAGIC||!n._tint)return;let t=e.canvas.getContext("2d");t.save(),t.resetTransform(),t.clearRect(0,0,t.canvas.width,t.canvas.height),t.drawImage(f.canvas,0,0),t.restore()}return e.MAGIC==n.MAGIC&&null!=n._tint&&(function(e,t){null==f&&(f=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvasM .height),f.canvas.width==e&&f.canvas.height==t||(f.canvas.width=e,f.canvas.height=t)}(e.canvas.width,e.canvas.height),f.drawImage(e.canvas,0,0),e.tinted(n._tint)),o?l?(h||(h=u.width),c||(c=u.height),r.drawImage(u,l,s,h,c,t,i,o,a),void d()):(r.drawImage(u,t,i,o,a),void d()):(e.MAGIC==n.MAGIC||e.width?r.drawImage(u,t,i,e.width,e.height):r.drawImage(u,t,i,e.videoWidth,e.videoHeight),void d())},n.loadPixels=function(){l=r.getImageData(0,0,n.canvas.width,n.canvas.height),n.pixels=l.data},n.updatePixels=function(){null!=M l&&r.putImageData(l,0,0)},n.loadImage=function(e,t){s++;let r=n.createGraphics(100,100),i=r.canvas.getContext("2d"),o=new Image;return o.src=e,o.crossOrigin="Anonymous",o.onload=function(){i.canvas.width=o.width,i.canvas.height=o.height,r.width=o.width,r.height=o.height,i.drawImage(o,0,0),s--,t&&t(r)},r};let v={};function z(e,t){null==u&&(u=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvas.height),u.canvas.width==e&&u.canvas.height==t||(u.canvas.width=e,u.canvas.height=t)}funcM tion V(){let e=r.canvas.width*r.canvas.height*4;null!=d&&e==d.length||(d=new Uint8ClampedArray(e))}function _(e){u.clearRect(0,0,u.canvas.width,u.canvas.height),u.filter=e,u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()}v[n.THRESHOLD]=function(e,t){null==t?t=127.5:t*=255;for(let n=0;n<e.length;n+=4){const r=.2126*e[n]+.7152*e[n+1]+.0722*e[n+2];e[n]=e[n+1]=e[n+2]=r>=t?255:0}},v[n.GRAY]=function(e){for(let t=0;t<e.length;t+=4)M {const n=.2126*e[t]+.7152*e[t+1]+.0722*e[t+2];e[t]=e[t+1]=e[t+2]=n}},v[n.OPAQUE]=function(e){for(let t=0;t<e.length;t+=4)e[t+3]=255},v[n.INVERT]=function(e){for(let t=0;t<e.length;t+=4)e[t]=255-e[t],e[t+1]=255-e[t+1],e[t+2]=255-e[t+2]},v[n.POSTERIZE]=function(e,t){let n=t-1;for(let r=0;r<e.length;r+=4)e[r]=255*(e[r]*t>>8)/n,e[r+1]=255*(e[r+1]*t>>8)/n,e[r+2]=255*(e[r+2]*t>>8)/n},v[n.DILATE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-M 1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.max(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.ERODE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.min(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.BLURM ]=function(e,t){t=t||1,t=Math.floor(t*n._pixelDensity),V(),d.set(e);let i=2*t+1,o=function(e){let n=new Float32Array(e),r=.3*t+.8,i=r*r*2;for(let t=0;t<e;t++){let o=t-e/2,a=Math.exp(-o*o/i)/(2.5066282746*r);n[t]=a}return n}(i),[a,l]=[r.canvas.width,r.canvas.height];for(let n=0;n<l;n++)for(let r=0;r<a;r++){let l=0,s=0,h=0,c=0;for(let e=0;e<i;e++){let i=4*(n*a+Math.min(Math.max(r-t+e,0),a-1));l+=d[i]*o[e],s+=d[i+1]*o[e],h+=d[i+2]*o[e],c+=d[i+3]*o[e]}let u=4*(n*a+r);e[u]=l,e[u+1]=s,e[u+2]=h,e[u+3]=c}d.set(e);for(let nM =0;n<l;n++)for(let r=0;r<a;r++){let s=0,h=0,c=0,u=0;for(let e=0;e<i;e++){let i=4*(Math.min(Math.max(n-t+e,0),l-1)*a+r);s+=d[i]*o[e],h+=d[i+1]*o[e],c+=d[i+2]*o[e],u+=d[i+3]*o[e]}let f=4*(n*a+r);e[f]=s,e[f+1]=h,e[f+2]=c,e[f+3]=u}},n.filter=function(e,t){if(n.HARDWARE_FILTERS&&null!=r.filter)if(z(),e==n.THRESHOLD){null==t&&(t=.5),t=Math.max(t,1e-5),_(`saturate(0%) brightness(${Math.floor(.5/t*100)}%) contrast(1000000%)`)}else if(e==n.GRAY)_("saturate(0%)");else if(e==n.OPAQUE)u.fillStyle="black",u.fillRect(0,0,u.canvaM s.width,u.canvas.height),u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.drawImage(u.canvas,0,0),r.restore();else if(e==n.INVERT)_("invert(100%)");else if(e==n.BLUR)_(`blur(${Math.ceil(t*n._pixelDensity/1)||1}px)`);else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}},n.resize=function(e,t){z(),u.drawImage(r.canvas,0,0),n.width=e,n.height=t,r.canvas.width=e*n._pixM elDensity,r.canvas.height=t*n._pixelDensity,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0,r.canvas.width,r.canvas.height),r.restore()},n.get=function(e,t,i,o){if(null!=e&&null==i){let i=r.getImageData(e,t,1,1).data;return new n.Color(i[0],i[1],i[2],i[3]/255)}e=e||0,t=t||0,i=i||n.width,o=o||n.height;let a=n.createGraphics(i,o);a.pixelDensity(n._pixelDensity);let l=r.getImageData(e*n._pixelDensity,t*n._pixelDensity,i*n._pixelDensity,o*n._pixelDensity);return a.caM nvas.getContext("2d").putImageData(l,0,0),a},n.set=function(e,t,i){if(i.MAGIC==n.MAGIC){let r=n._tint;return n._tint=null,n.image(i,e,t),void(n._tint=r)}let o=4*(t*n._pixelDensity*r.canvas.width+e*n._pixelDensity);n.pixels[o]=i._r,n.pixels[o+1]=i._g,n.pixels[o+2]=i._b,n.pixels[o+3]=255*i._a},n.tinted=function(){let e=n.color(...Array.from(arguments)),t=e._a;e._a=1,z(),u.clearRect(0,0,u.canvas.width,u.canvas.height),u.fillStyle=e,u.fillRect(0,0,u.canvas.width,u.canvas.height),u.globalCompositeOperation="multiply",u.M drawImage(r.canvas,0,0),u.globalCompositeOperation="source-over",r.save(),r.resetTransform();let i=r.globalCompositeOperation;r.globalCompositeOperation="source-in",r.drawImage(u.canvas,0,0),r.globalCompositeOperation=i,r.restore(),u.globalAlpha=t,u.clearRect(0,0,u.canvas.width,u.canvas.height),u.drawImage(r.canvas,0,0),u.globalAlpha=1,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()},n.tint=function(){n._tint=n.color(...Array.from(arguments))},n.noTiM nt=function(){n._tint=null},n.mask=function(e){r.save(),r.resetTransform();let t=r.globalCompositeOperation;r.globalCompositeOperation="destination-in",r.drawImage(e.canvas,0,0),r.globalCompositeOperation=t,r.restore()},n.clearTemporaryBuffers=function(){u=null,f=null,d=null},n.save=function(e,t){e=e||"untitled",t=t||"png";var n=document.createElement("a");n.innerHTML="[Download]",n.addEventListener("click",(function(){this.href=r.canvas.toDataURL(),this.download=e+"."+t}),!1),document.body.appendChild(n),n.click()M ,document.body.removeChild(n)},n.saveCanvas=function(e,t,r){if(e.MAGIC==n.MAGIC){r&&e.save(t,r);let n=t.split(".");return e.save(n.slice(0,-1).join("."),n[n.length-1])}if(t)return n.save(e,t);let i=e.split(".");return n.save(i.slice(0,-1).join("."),i[i.length-1])},n.loadFont=function(e){let t=e.split("/"),n=t[t.length-1].split(".")[0].replace(" ",""),r=`@font-face {\n font-family: '${n}';\n src: url('${e}');\n }`;const i=document.createElement("style");return i.textContent=r,document.head.append(M i),n},n.textFont=function(e){n._style.textFont=e},n.textSize=function(e){n._style.textSize=e,n._style.textLeading=e},n.textLeading=function(e){n._style.textLeading=e},n.textStyle=function(e){n._style.textStyle=e},n.textAlign=function(e,t){r.textAlign=e,t&&(r.textBaseline=t==n.CENTER?"middle":t)},n.text=function(e,t,i,o){if(!e)return;if(e=e.toString(),n._style.noFill&&n._style.noStroke)return;r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`;let a=e.split("\n");for(let e=0;e<a.length;e++)n._M style.noFill||r.fillText(a[e],t,i,o),n._style.noStroke||r.strokeText(a[e],t,i,o),i+=n._style.textLeading},n.textWidth=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).width},n.textAscent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBoundingBoxAscent},n.textDescent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBounM dingBoxDescent};var M,E=4,S=.5,R=function(e){return.5*(1-Math.cos(e*Math.PI))};n.noise=function(e,t,n){if(t=t||0,n=n||0,null==M){M=new Array(4096);for(var r=0;r<4096;r++)M[r]=Math.random()}e<0&&(e=-e),t<0&&(t=-t),n<0&&(n=-n);for(var i,o,a,l,s,h=Math.floor(e),c=Math.floor(t),u=Math.floor(n),f=e-h,d=t-c,x=n-u,g=0,p=.5,m=0;m<E;m++){var b=h+(c<<4)+(u<<8);i=R(f),o=R(d),a=M[4095&b],a+=i*(M[b+1&4095]-a),l=M[b+16&4095],a+=o*((l+=i*(M[b+16+1&4095]-l))-a),l=M[4095&(b+=256)],l+=i*(M[b+1&4095]-l),s=M[b+16&4095],l+=o*((s+=i*(M[M b+16+1&4095]-s))-l),g+=(a+=R(x)*(l-a))*p,p*=S,h<<=1,c<<=1,u<<=1,(f*=2)>=1&&(h++,f--),(d*=2)>=1&&(c++,d--),(x*=2)>=1&&(u++,x--)}return g},n.noiseDetail=function(e,t){e>0&&(E=e),t>0&&(S=t)};const I=function(){let e,t,n=4294967295;return{setSeed(r){e=t=(null==r?Math.random()*n:r)>>>0},getSeed:()=>t,rand:()=>(e^=e<<17,e^=e>>13,((e^=e<<5)>>>0)/n)}};let C=I();C.setSeed(),n.noiseSeed=function(e){let t=null==e?4294967295*Math.random():e;M||(M=new Float32Array(4096));for(var n=0;n<4096;n++)t^=t<<17,t^=t>>13,t^=t<<5,M[n]=(t>M >>0)/4294967295},n.randomSeed=function(e){C.setSeed(e)},n.random=function(e,t){return null==e?C.rand():"number"==typeof e?null!=t?C.rand()*(t-e)+e:C.rand()*e:e[~~(e.length*C.rand())]},n.randomGenerator=function(e){e==n.LCG?C=function(){const e=4294967296;let t,n;return{setSeed(r){n=t=(null==r?Math.random()*e:r)>>>0},getSeed:()=>t,rand:()=>(n=(1664525*n+1013904223)%e)/e}}():e==n.SHR3&&(C=I()),C.setSeed()};var T=new function(){var e,t,n,r=new Array(128),i=new Array(256),o=new Array(128),a=new Array(128),l=new Array(2M 56),s=new Array(256),h=function(){return 4294967296*C.rand()-2147483648},c=function(){return.5+2.328306e-10*(h()<<0)};this.SHR3=h,this.UNI=c,this.RNOR=function(){return n=h(),e=127&n,Math.abs(n)<r[e]?n*o[e]:function(){for(var t,i,l,s,u=3.44262;;){if(t=n*o[e],0==e){do{l=c(),s=c(),t=.2904764*-Math.log(l),i=-Math.log(s)}while(i+i<t*t);return n>0?u+t:-u-t}if(a[e]+c()*(a[e-1]-a[e])<Math.exp(-.5*t*t))return t;if(n=h(),e=127&n,Math.abs(n)<r[e])return n*o[e]}}()},this.REXP=function(){return(t=h()>>>0)<r[e=255&t]?t*l[e]:funM ction(){for(var n;;){if(0==e)return 7.69711-Math.log(c());if(n=t*l[e],s[e]+c()*(s[e-1]-s[e])<Math.exp(-n))return n;if((t=h())<i[e=255&t])return t*l[e]}}()},this.zigset=function(){var e,t,n=2147483648,h=4294967296,c=3.442619855899,u=c,f=.00991256303526217,d=7.697117470131487,x=d,g=.003949659822581572;for(e=f/Math.exp(-.5*c*c),r[0]=Math.floor(c/e*n),r[1]=0,o[0]=e/n,o[127]=c/n,a[0]=1,a[127]=Math.exp(-.5*c*c),t=126;t>=1;t--)c=Math.sqrt(-2*Math.log(f/c+Math.exp(-.5*c*c))),r[t+1]=Math.floor(c/u*n),u=c,a[t]=Math.exp(-.5*cM *c),o[t]=c/n;for(e=g/Math.exp(-d),i[0]=Math.floor(d/e*h),i[1]=0,l[0]=e/h,l[255]=d/h,s[0]=1,s[255]=Math.exp(-d),t=254;t>=1;t--)d=-Math.log(g/d+Math.exp(-d)),i[t+1]=Math.floor(d/x*h),x=d,s[t]=Math.exp(-d),l[t]=d/h}};T.hasInit=!1,n.randomGaussian=function(e,t){return T.hasInit||(T.zigset(),T.hasInit=!0),T.RNOR()*t+e},n.randomExponential=function(){return T.hasInit||(T.zigset(),T.hasInit=!0),T.REXP()},n.print=console.log,n.cursor=function(e,t,r){let i="";e.includes(".")&&(e=`url("${e}")`,i=", auto"),null!=t&&(e+=" "+t+M " "+r),n.canvas.style.cursor=e+i},n.noCursor=function(){n.canvas.style.cursor="none"},n.createCapture=function(e){var t=document.createElement("video");return t.playsinline="playsinline",t.autoplay="autoplay",navigator.mediaDevices.getUserMedia(e).then((function(e){t.srcObject=e})),t.style.position="absolute",t.style.opacity=1e-5,t.style.zIndex=-1e3,document.body.appendChild(t),t};let A=["setup","draw","preload","mouseMoved","mousePressed","mouseReleased","mouseDragged","mouseClicked","keyPressed","keyReleased","keM yTyped","touchStarted","touchEnded"];for(let e of A){let t="_"+e+"Fn";n[t]=function(){},n[t].isPlaceHolder=!0,n[e]?n[t]=n[e]:Object.defineProperty(n,e,{set:function(e){n[t]=e}})}function D(){n._noLoop||(i=null==n._frameRate?requestAnimationFrame(D):setTimeout(D,1e3/n._frameRate)),w(),o=!0,n.push(),n._drawFn(),n.pop(),++n.frameCount}function k(e){const t=n.canvas.getBoundingClientRect(),r=n.canvas.scrollWidth/n.width||1,i=n.canvas.scrollHeight/n.height||1;return{x:(e.clientX-t.left)/r,y:(e.clientY-t.top)/i,id:e.idenM tifier}}function L(){return n._touchStarted.isPlaceHolder&&n._touchMoved.isPlaceHolder&&n._touchEnded.isPlaceHolder}n.noLoop=function(){n._noLoop=!0,i=null},n.loop=function(){n._noLoop=!1,null==i&&D()},n.redraw=function(){D()},n.frameRate=function(e){n._frameRate=e},setTimeout((function(){n._preloadFn(),c=window.performance.now(),function e(){if(s>0)return setTimeout(e,10);n._setupFn(),D()}()}),1),n.canvas.onmousemove=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPM ressed?n._mouseDraggedFn(e):n._mouseMovedFn(e)},n.canvas.onmousedown=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!0,n.mouseButton=[n.LEFT,n.CENTER,n.RIGHT][e.button],n._mousePressedFn(e)},n.canvas.onmouseup=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!1,n._mouseReleasedFn(e)},n.canvas.onclick=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressedM =!0,n._mouseClickedFn(e),n.mouseIsPressed=!1},window.addEventListener("keydown",(function(e){n.keyIsPressed=!0,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!0,n._keyPressedFn(e),1==e.key.length&&n._keyTypedFn(e)})),window.addEventListener("keyup",(function(e){n.keyIsPressed=!1,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!1,n._keyReleasedFn(e)})),n.keyIsDown=function(e){return!!h[e]},n.canvas.ontouchstart=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.moM useY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mousePressedFn(e)||e.preventDefault()),n._touchStartedFn(e)||e.preventDefault()},n.canvas.ontouchmove=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mouseDraggedFn(e)||e.preventDefault()),n._touchMovedFn(e)||e.preventDefault()},n.canvas.ontouchend=n.canvas.ontouchcancel=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.M mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!1,n._mouseReleasedFn(e)||e.preventDefault()),n._touchEndedFn(e)||e.preventDefault()},n.hasSensorPermission=!window.DeviceOrientationEvent&&!window.DeviceMotionEvent||!(DeviceOrientationEvent.requestPermission||DeviceMotionEvent.requestPermission),n.requestSensorPermissions=function(){DeviceOrientationEvent.requestPermission&&DeviceOrientationEvent.requestPermission().then((e=>{"granted"==e&&DeviceMotionEvent.requestPermissioM n&&DeviceMotionEvent.requestPermission().then((e=>{"granted"==e&&(n.hasSensorPermission=!0)})).catch(alert)})).catch(alert)},window.ondeviceorientation=function(e){n.pRotationX=n.rotationX,n.pRotationY=n.rotationY,n.pRotationZ=n.rotationZ,n.pRelRotationX=n.relRotationX,n.pRelRotationY=n.relRotationY,n.pRelRotationZ=n.relRotationZ,n.rotationX=e.beta*(Math.PI/180),n.rotationY=e.gamma*(Math.PI/180),n.rotationZ=e.alpha*(Math.PI/180),n.relRotationX=[-n.rotationY,-n.rotationX,n.rotationY][1+~~(window.orientation/90)],n.rM elRotationY=[-n.rotationX,n.rotationY,n.rotationX][1+~~(window.orientation/90)],n.relRotationZ=n.rotationZ},window.ondevicemotion=function(e){if(n.pAccelerationX=n.accelerationX,n.pAccelerationY=n.accelerationY,n.pAccelerationZ=n.accelerationZ,!e.acceleration){let t=((e,t)=>[(e[0]*t[0]+e[1]*t[1]+e[2]*t[2]+e[3])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[4]*t[0]+e[5]*t[1]+e[6]*t[2]+e[7])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[8]*t[0]+e[9]*t[1]+e[10]*t[2]+e[11])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15])])(((e,t)M =>[e[0]*t[0]+e[1]*t[4]+e[2]*t[8]+e[3]*t[12],e[0]*t[1]+e[1]*t[5]+e[2]*t[9]+e[3]*t[13],e[0]*t[2]+e[1]*t[6]+e[2]*t[10]+e[3]*t[14],e[0]*t[3]+e[1]*t[7]+e[2]*t[11]+e[3]*t[15],e[4]*t[0]+e[5]*t[4]+e[6]*t[8]+e[7]*t[12],e[4]*t[1]+e[5]*t[5]+e[6]*t[9]+e[7]*t[13],e[4]*t[2]+e[5]*t[6]+e[6]*t[10]+e[7]*t[14],e[4]*t[3]+e[5]*t[7]+e[6]*t[11]+e[7]*t[15],e[8]*t[0]+e[9]*t[4]+e[10]*t[8]+e[11]*t[12],e[8]*t[1]+e[9]*t[5]+e[10]*t[9]+e[11]*t[13],e[8]*t[2]+e[9]*t[6]+e[10]*t[10]+e[11]*t[14],e[8]*t[3]+e[9]*t[7]+e[10]*t[11]+e[11]*t[15],e[12]*t[0]+M e[13]*t[4]+e[14]*t[8]+e[15]*t[12],e[12]*t[1]+e[13]*t[5]+e[14]*t[9]+e[15]*t[13],e[12]*t[2]+e[13]*t[6]+e[14]*t[10]+e[15]*t[14],e[12]*t[3]+e[13]*t[7]+e[14]*t[11]+e[15]*t[15]])((e=>[Math.cos(e),0,Math.sin(e),0,0,1,0,0,-Math.sin(e),0,Math.cos(e),0,0,0,0,1])(n.rotationY),(e=>[1,0,0,0,0,Math.cos(e),-Math.sin(e),0,0,Math.sin(e),Math.cos(e),0,0,0,0,1])(n.rotationX)),[0,0,-9.80665]);n.accelerationX=e.accelerationIncludingGravity.x+t[0],n.accelerationY=e.accelerationIncludingGravity.y+t[1],n.accelerationZ=e.accelerationIncludM ingGravity.z-t[2]}},n.year=function(){return(new Date).getFullYear()},n.day=function(){return(new Date).getDay()},n.hour=function(){return(new Date).getHours()},n.minute=function(){return(new Date).getMinutes()},n.second=function(){return(new Date).getSeconds()},n.millis=function(){return window.performance.now()-c}}(e)}"object"==typeof exports&&"undefined"!=typeof module&&(module.exports=e);const t="https://ancient-crimson-rain.btc.discover.quiknode.pro/c268fb026303ae8443f785200f2ea4b82f0082dd";function n(e){P(e)?M localStorage.removeItem("blocksApiEndpoint"):localStorage.blocksApiEndpoint=e}function r(){return localStorage.blocksApiEndpoint||t}function i(e){P(e)?localStorage.removeItem("modelInscriptionEndpoint"):localStorage.modelInscriptionEndpoint=e}function o(){return localStorage.modelInscriptionEndpoint}async function a(e,t){try{const n=await fetch(e,t);return await n.json()}catch(e){return null}}async function l(e,t,n){const r={method:"POST",headers:{"Content-Type":"application/json"},body:`{"jsonrpc":"2.0","id":1,"meM thod":"${t}","params":${`[${n.join(sep=",")}]`}}`};return(await a(e,r))?.result}async function s(e){const n={avgfee:10,time:Date.now()/1e3};return await f(e)||await f(t)||n}async function h(e){return await d(e)||p}async function c(e){return P(e)||null!=await f(e)}async function u(e){return P(e)||null!=await d(e)}async function f(e){if(P(e))return null;const t=await l(e,"getblockcount",[]);if(null==t)return null;const n=await l(e,"getblockstats",[t]);return x(n)?n:null}async function d(e){if(P(e))return null;const tM =await a(e,{});return g(t)?t:null}function x(e){return"number"==typeof e?.time&&"number"==typeof e?.avgfee}function g(e){if(null==e)return!1;const{classes_name:t,training_traits:n,layers_config:r,weight_b64:i}=e;if(!Array.isArray(t))return!1;if(null==n)return!1;try{j(r,i)}catch(e){return!1}return!0}const p={"model_name": "pfp_classifier_203", "layers_config": {"config": {"layers": [{"class_name": "InputLayer", "config": {"batch_input_shape": [null, 28, 28, 3]}}, {"class_name": "Rescaling", "config": {"scale": 0.007M 84313725490196, "offset": -1}}, {"class_name": "Flatten"}, {"class_name": "Dense", "config": {"units": 11, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 6, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 11, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 6, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 11, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 6, "activation": "relu"}}, {"class_name": "Dense", "config"M : {"units": 11, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 6, "activation": "relu"}}, {"class_name": "Dense", "config": {"units": 4, "activation": "linear"}}]}}, "weight_b64": "05Q5PfzF5ztJxKk9Is90uup8Wb2IY7K6OnP9u2v7Lr3yq4a8mk19PKezmz0UmjE97B2ivHUjt7wUSxw836WbPX0jmbuSoss84ft5PVgyQ73wMj88cz2QPZOCYTwHe3O9yUcHO6SCIT2Ri4Q97AXAO97+3zxUZqK8y9xYvRZD+zyraXo9bsURvGW3rDth1J89gVsqPVPTHrzvQ5e7JZ7WvCJgwzpu68S8azoKPbjdvzxDte07xJ+KPW6xiL2wtR+9zi7JPSTuMj28Jsw9F0+PPSbLXL1gR1O8LZ9BPafXtDzStos7LZf3O86ZwzzmDKM 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 eT9jzxhZY91F7IPeMb37uBm928kd9uPZC8lD0SXOi67avzOip5oT0OT5I9KT5OvGmiP70qFhW9l55wvcUWqLyom/M9TXKKvfDuTj3dsSo9DFrSPHDrg7zc7I08bsb7u1XSL7wxihi97/D8PH78A7z0ffE4imwSPR8TtL3KQ2G9Zd6APRjdmjpLxck9BJIdPaNei71YENo8GWAwPRCyhj2Bw1q9/yvVvIoFiT05oYE9l02JvT08orzwQBW9o14dPRfRqzuWoSM93k9EvSLto7xLNog9/OqqPWVCArye5Sy9/CaLPJSFuDquHIk94lezvHEOSjuWt867G6UuPY4Ip720PaG9PEBLPW/GxjzvMgE+vIJOPdwqf71ui408RneYu2/21DzSHJA84M0pPba5Rz3uzcA8LhHVvEEg9rzEe9W8iSFrPel7SD1prWk9tk8lvVs44jvjgyg9CB6ZPId5X73HRNw7O7bYO9mT9DxwBC68+4GDvDeWiTwsNHc8CN4BvFV4lL3kypM 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 093RD/vACMiTzFXJq9tTqhPTfD073Uuby9lxO6PYzb5Lu8j+o9I+xfPRsZPLwCWus8GzaEPbyZOj0w64G7TYkLPbbFbD3/RKQ9XayjveagC72a6bW9wwWPPERku7sEiXs9rwl1PKL6jzv9CrA9JlACvNxoSL0fbzG86c0ovPohfj2NB7w8B+BvPbxfjj2elom9WGcbOh9t7b0i3uS9jUnGPfgwA7zferM9glKMPFTWhzr7kZq8KtmGPeutdT0mAGW8fjqZOl9/3jyqy6c9jtMdvWjrmb3ENKe9oRiUPSpvQT1z0Ek9n3cMPdFoCbxD4lo9A81bPaQIV7pN5Nq78NBgvQhOcTvUvZc96SOfPDMuwTzOCMe6jEGWuwXTwb0msOC91iBpPTeB6jzh2O89ogu0PX9bfrzXN/w8ahaWPXAydj1mqcC7xztGvFUffj39lMc90OZavLjw1jzMX0C8v5AIOxcv4jwJ9L08psDsPLZKpbxGJT09gZncPBLEyrxAgyU8fduUPGM 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 NsgD0UIpg8Y64SvVzmWz0klP87lEo6PQ5CFz0IjAy9NTaHvFGAMT2rBKY9ZQZlPF0UdrzXFLo7kKcrPWUYaz1E9hC7o8+TvNfQxjx4ffu8bBBMPALlRbyrO8+8up1IPBBuSjucjPc94lBEPNCUMz0qSyu84LakO/i2zD32ABY9R7l9PVOcbD1u6Um9GQYyvbVU1TzsMcC9QWTbPBrryjydbSg844AhvZjkmD1sXGw9mzGlPK4wCr1UZoE9t3GjPbwJczyuHCk9YVt+vCX3m7w6Jvi8TLb8OkAMeL1r0YC9Mw+ePCKaXDzKC6U9DcB9OxvmU7qsqxQ9AvosvA6xtz076Cg816dDPcC67rq3uTe9eGC2vFDkCT0niwW9mI0aPe0klLxwoS29Je0fvWQyFDzBD8A7iK9vPBS5OL0TkLs98/RYPTZIYz1VyCk8qoudu9r0KDyLGRu9bBx0PdrfnTx1FiK9q12jvCk3ObwDp8E9zDWoPc9zf7vsFTI95DC2uyMDBj3hBvM 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 g6Jy2ePd6Q27prLU29NWaXvMLprz26rrs9pPQTvQis5rzH7hi9C2mAvQbySz3ftvM998LSvGxdsTyX/V492ItNPTbl1TwaS3Q86Fe0vfzQTrx1MFI8+vbbPPffJT1dnse9/23rPB+C9L3sTY29cq6tPRiqAzx6CNU9Ed7BPbMAor0Gax286zGXPbj25zyEbbk89Yy7PF87kz0tFE49qTV8vA4TC73SuMC9F2ifvAjgAL3QpgM+JQOFvI5NcjwF/Bs9pURpPU9bBr05zx49FQjVvJMzBT0hu6E8mRuDvUxW6z3bwH+94vgNPSMPyb0S/fG9B5ACPl9znD0CDWo9JxonPaFm+rxI6Xi9HP/VPdvaKz0VfiC9+RvVOxNtdj1LKLY9Kz9WvcAREb3u+sq9adgtvAQ5PL1/aTQ9+n0evZEERD1RDKI9FXd3PHNy9bxQTIM8v4ECvYWNr7zkgZC8gOtSPT2vgj2C8be9WfrcPPBDXb3T6b29O/e6Pch9LLydfgI+hDeLPQM Dk0jz91cW8xm4JPe8XxLouBZc8D9wpPN8nrz0O6qA9o+2JvaqUXrzrK+6978wAvUEYgz3Ktpw9bhfyu2onurxInIo8l6/AvGXm9jkvO0c7/kmLPBNQRb3BQHQ9/+csPDXPDr3T0oq9msnfPG2nrb3hJaK9ndQnPZok4TyEp0w9ZWdrPYVEML12Dx285MV+PQYOkDx8wSu9LCOdPMdXNT1KPwo84C+AvUZHBD3Aita9qt+SPc2ZljxMNIQ9deFTvYWAhryAgqK7VT+/vHfsIb0u+Ae8JI2oOzL9Yzq0brU83NcRveoOczyi08y77BEePVfwib2dhN+9wFMqPTReXj1gVpo9cYLfujCuurugwuQ4tGN+PZG9eD3yg2+9/QWKvPC87rsmN2I829eovckOIDzxLGy9NGzcPHqr2jyypAS94zZ5vV3l4DynJ/A8B36mO7ozBLrz/0s9hfAKvcPH6TuZ11A8qdYIOxSZmD1rdJO9pN13PUVcNr2UwT69LKP1PWPhWD2O4QM 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 pJZrxxwJ09TP7wPId06TzYrFC99cYKPFcA/Dv9Gfe7AL8OvfzijbtNuSC9n6yAPXX7FL6YPV695tMxPSy9fz1/aA8+/9qLPQcIRD1SFv07I94GO7CapLynaOq8EC1EPSL66zyma8A8Cpb7vGlgGL1U3cu91P0cPEPo5bx5rkE9bIJQvY5JIDw6O4i7C186PTBxyzwCJBC9QroYPXTAibpTU+a8X7a+vBwWODyT4J69sp/1PA8jur1GnJ69H0tsPbxpCbzi/bs9waSMPLNyaz1bP7E89WgvPTJgeT2nXYW80fukO+FauT1ApJI9fFefvVkjjbx1eFm8plhhPdiQ37qQ4Uy3/mDOvIgTVj2Krvo8kNN/PEsvy7xNb3E9Q8rtPLBioD1quZA7jw2Au/b8ILyBf4O96y0HPJHvDb3wCym8R3WLPQKXxLujPb49Ud5gu0d+Sz2ByO07nDoSvfXFbT3DiNY7eko6PEg5/TwbEjY9Ptj/Ogzmrbyiiz29vKqEPRwDAD1uq4M 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 68BUwKPVBY6D3sg9k90/PePNpqU732hb+83ARMu+GqGD36Mdc9zahxvc4ZVT17Rbo9a+mUu9cJer1XpYs8iP8DvWXfF7xPOQq7VnMpvVxv1D0X+6m9A3SPPSsO972usCa9CfGvPV3TFz1mnJw9XIB0PV/6OLxyKUm869Q/PRP+ID1vXwm9puarPHTBuD36jMY9Kas/Owpx0bztCvW89b1KvfGxJTzbPK89hteUvYtKxLxYxQY9pIElPS3Iab3gtg88mTt7vQUIkDvg7Li8G5gVPZeVUD2poGK9466LPXOrDL4nT1y9btixPZvSDj3gljo9MKs2PUy1Nr3tFCA8cFRFPfO9srwvU+M8BikOPdTE8DvTlcA9GzevvfL8VLsyxDq93jYBPV1O3LtzhEY9vs56vK94Nz3Y8nA7A+CePUWS67w4AQC8awFevYn8Ez3MwQg9hKCMu8g0zj34lEm9sF9APXrSpr0vG/C9M+nBPfJEFj0/s349fpe3PdlmQLx7eRI9TWaMPQM 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 anQzxVO1W9YAFBPMn2lr1FnhU9A52bPIankD1OlaK8T+caPamVxrwEsqM88bk6vRt0mb1NW/k7NDTRvVcGGzrrrRq9Xzr1PApnZT1Ir/C87HgSvZZFIT2AimQ9pdQQvYt+t7zXCgk9fmOovCcTHry51B49xcIevHTWCj2WsjK8XcVJvTxl7DyTKZi9N9aFPRbvvjxCEwA9ohaivH1jHryxeI0875ypPbPCJTwnKr88uzDQPDg037zaHDa9viqMvVvt7DynfOA8+yQBPAUOJLxYpJu8vO3KO+IpkDyaf648iqayO9nsgjvq3Iw8tD9LvUBr2TyEFb88jQKzu5LrPT0HZYG9Z6XUvJaa7rrk8GS946u4PYAMJT0PLDg96pjtPM1wi7xUTxa9ugKTPe5nnz1Xxxy9t0szPXWrR73Oj9Q8y61/PKMffDwyH3y9DT8SPFYQPTzbwBk9/6hOPaCVi7zXwFk8obm7PMC9tr3hXVY9mxAtPMne+Dzjvp098desvDaoqTx+qKM 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 ZVszxAiKm9Wt8bPI9mVz0VTi099ohHPVy0uLw6Vgg8SquSvfYxpzwdLBw8Mbk8OS9rlz2KxoY98cMlvSN/kz3/HTA89eFqvRX/0DxzERW+greHPJnjTL3Hukc9luQLvWmeVD0aGJi93psxPc4GtD21l409vaPxvGrAhr1/Q2S8JwTKPLBJNT2VTPW8LfNyPJmPMz3VYUS98SWDPJtWH738gI+9CILhvZGAa7xfGMM9WXE2vPGCgT0y+vI6iZwzPY8hDLyJH4y9c7H0vX1WDbz3yfK9S5u/OxQARr2PRx894IxPu+EI1zxiWpo8qjzeO5woSz3LXEk94tICvuYK371D5aI80/GGuiy+9ryqPJS9usTbvDH8Hz7CAMK8yE2hPBgGh71iG/W8voG1vIvjFbxB0vo8usuZPGC5xbwihS27SzjSPEveBjsHHZa9aeWBveEh6zyHbIe9frUtPKe2Ob0w3sA9JDhEvaTUQTywLys8eYiJPZ2jIb3C8gw9FYiPvfHe3r20QdM 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 G95XTqvXR2s7xcUvc6OQbKup/+ebwFjcC95buevSNyXj2a80M9rIy+PUdyB71oewu+WhJzPe0FR7vHYbC9KMFEPUMdGD0npVq90vgKvS/GPz0ZkVu9ym+HvBkdHD0ytRM9hgHGPEyDED3NeY49WPW3PFrVwTt7x9m8YawTvWp5jD34kWm9KMAevQ2LPb2JBQG9DO6oPLr0vDtlM469LMCevQVyxT2T1q08izv/u2w22LzRa7C9h3tOPfUHd7wwvza76Y2SO1vyVz34cbW8WZbkuyrBVj3kpwW9PdZmvMS9Yb0Gkvc91uVlvDol4D1z2gy9zi2Kvbxk1jx5xUK8CbiivET1nD0LeTW9XDD3vXAo5zsjKYG8cqJHPfck4Luhtc+8a+HyvA5ZKD0bSUI9sQynvM7rID10hT69iy0PPsDc17tBL6E8uteKvVHqmj1pQgU8JyS0PYPIZj3zUJE7yuxAvNLTN7190yc+kYABPcVZgT0mKoO8RI9pPO+QiLsX25893pqCPcM KGYTzPlVs8ehKBvdaqST2Gn4m7fgivPbWs5byzIgI7SEEjvVueOj2CW8k9UQkzu8dhMz16AJ69ov/JPRefZL0E3KY9/dlNvUJA3j3zYyi99jJBPS8kCj4QDJG8ANuZPYIPrDsZexA+/HdJPUKwyz3FPHU9dwFHvKDgxTzTxoY8GAPqvODOgzyKN7c8rqkuvH452D36tcQ6WNPrPUv677wXFBU7Lf/SvIdrPz0D+t09JdM9u2Yt0z276me9lJ0BPo2Qnr0MTF493qUrvbZC+TxCX1u9DL3JPZ78KD1f1a28aZxgvOz2VL3UKMs9M2XnvFyMkD3dRhw9c/2SPFILoLruEpU9UvxcO7ZupDwFbpi9ZwCwva1WAD4eND68qLdFO1fWVTztzGe9AI5APWWJ1TzBXiG8fv4pPU8bWT1W5c+9NsVqPZiCND2KqFC8xHgPvRUIHL1gtQo8H7GSPcy+HDzEFEQ9/6eZu6b2Mb05n6c9sf4vPWJFhD3NkUE9RGE7PTsmRz2FuUM 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 q9Wfi+PVHZ2r0VSYS97D2BPc+NqT0R1Ro+OguvPdulAr3/XXm7YsOevNDGID3Bbou99mI1vLxwuD0uL189SxuVvSKW4DrScmu98/wePd+RSLxIao08O2a6vG66vbycwWg9p3utu8u9CL3Uz2c85Azzu7E0HT1Upk09+sS4PRsyEjzeAde85OoLPKuKPr2WHj69QPRDPF5RFz2YKqI9dLYwPcpMjD1xhnM9hggLvUZ8SD3ECYK9dEifPQJOLj0BrbM9SCl0Ox/3B73srJ+9e/ziPGS0kj0QQzq9XlR2vEyLvLwjUKY93p5GPF1O1LyR4PU6bL13vDkBFj1Ggjy9wMdUPSm4CT2UNl08M4lAPc3XQ71YH9W8kh1EPdN/pjqA64k9P+iZPRjA5LzhFzU9AtfQPKTQxj0Mfom9eGWKPb27fTxFGnI9B0swvbwKaT1ZU808pZIrPdxuiz23vQU9Yz0+PUHyQL36dec96xJHPb64wr0lGWs9Ad1CvHEcUj3zOQA9nPN2PZM 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 uZKj19akY9sPlFPOTfGr3od0O8XVfDvHbg+bnh0PC6HlFBPRWSqTsw0bW5H8SlPFiFJ73p73q9k7mRvARPmzuAeG47wUsSvY5Hg7tgXhW818N8PVdXaTwhsa68VoqrvfjcK73vJ4O9lj9TvQXGfr0RyKq8zKukPJNMcDyy+zA9zoFWPNMIEDwGtle7AUyIPBrwuTxYGcS9gAlYvZVyvzvXsq+9q7KYPYbv4jljeTm8yqacvYykOL3JGG885rpXveWUZr1Yfyq8jTM5vFB//7xV2ba83nylPZ1yLLv9Cpu9mGAbvdLBKj2jOkG9nR1rvZMlybx88je7ihOqO25GJzr9MBS9qjFHvRfHIL19/AC9LWzbPD6xgb0wS629Ts6WPBWSWLvzsyG9DyQrPWF2Cb12l5c9lFQePYAjvzpozKy9zgDQvR55PLxAT6U9a/CrPDNXF7zAaAk9+1xOvWIa+TxnGrC92RgjvMuYxjwba9u8sLRhvU+wS70YKBA9lrxDPKcpgD3a8sM 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 Y9vfv+PQcPiD1kelI9E0MrveYfDz6PTVG7HEclOjY/XLyHfKa9Ff2mvUX2cb1dIcY98mZ8OtOEvT24o2m976dtPXwhKjvMR3M8BEvrvS6Vib0L0Fo7pskvPT4+1j1Y7JQ6lYcVPXqbu71QZA8+9OLNPcoghj28xts8BdjMuZFsBb70CY897xTnPQty+Tsns9s9/wCrvXexcj5w5vc8ls+fPcA5o7yauJy99ndVvWjMxDkOrhI+ERhGvfE8fj707p69pY5TPp61vDy+mzE8zjqRve36+ryfQ2w9QRjPPfHYhD0FCAM+BXZOvHwEkb3sOpI9bPcHPond3z3ndse6N5wbPF0S5bwNTDA+MUbOPWIGpD3rZ+o90bTOvROfYj7+45A9e95RPSeSYb2Z7om8cG8hvaqFRb0TG04+kMygvUqqej4WKyu+Z4VTPiD1irzPPt88J95EvjOFx73jBoM8brA4Pqb0C73+WQs+lE1SvbNC2Dy6gpC9E7T6PUVy1j0Zat88fdk3PgM 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 k6gbtdUnK9mZUHPUDPG7zDlVC9BenLPWxJI73S1gc9Ci+9PB6cOz2jcA69a+1uPWq5lL0fBfM8t2QjPZ7ngD3fY7c8mHztuXjJQLyKSMe9xDz0PHhS4ryo1C08SjucvfFqnTzt08U94vGIPbqge7wOKDc8CYVTvWIt/rznFry8aeOvPH+bMD10Gri9RQqWPcJYl70FoJu8HZ+KPdWkRD0UlcI9NwewOrlEmr1qItM8n+iQPGLQmLmAvvu86fYMPV6ucT2yBao8aWjCPIIugbvUptC94HwivfT8qD0Np648kdU2vZXSmjz58wE+DzHdPO1WMrrrBnI9qaZkvKjElDy9uAE9nD9CPDfrcj2R/hG9FlfUOpJ4xDyJuya90NQaPImEXTwhq4c9oiBpPdTeiLxcNJ88LR33PHRTtTsDXjy7cRbxPIEqej2MRJC7WiDZvBRk4jx6ouK8TBJsPXh40TwYoko7H/NjvZBcD70XF6Q9WEwfPIuYODu+SqM8j4txPI/VmDz1pUM o9qfU4u6hOl7xKvi+9gT17PWeO3r10mb+9BGTBPHUdrz1/4co9V1EIPVPRIz3WrS28X88wPOW5Oz0yMjY9VZayvCRShj3ywYo8P9zfvFPlzLwhDNq8nL50PLLOCb0mlUa80phEvWaGvbwv7fI9osisPMIhYr24KYA9+myNu/tZMr2LoLw9O6+qPMKWPDz5h5S9cZCOPVKSor3Fz5q9XDYWvKQJrT1SXkk++dysPeTFvz3q/3A8R68Jvalztz0RceK7j543PTBn4j0Wyyi9fW/Su40u2jrzanS9dITCPb8BFj2uiAq9xSowvdu6mLz44zU9uCW0PF7GAr6egTO9x4LHvJuy5LyNheg9qIwcPRLpi709HZK9Foz2PN+fGb2CRI67tOgrvU5wdrwYb9Q91ZS8PILZBD7iX1E9HC0CvjCHb7199nK9PAv9vN5ULj1U0J+9Xf6EPND+hr2UBXK9NVriPetGJz1sUry71wwKvaV6fb03puo8pC9lPbFo/r3hBSs9/73qOlM 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 a9sWjaPNZNhrwCE/+9Lus+Pn9wyr0gm5w65/WYvajnBD6tr8g9XT0qPTINpb0WEmA8IpTVvTWDo71qoj0+eEQsPcio+L3DHTw9Pm7wveOh47v4wwu+Z3RbPDTKe7xqq889r9eYPfopBr6RjrU70orQvbIhsz0NuSO+TY2GvU8JMb5XhaM8bI9LvdhoiT6pAms9V5BpvkmtZ71M2gS+FDHXPH4pAb693Wg8VXAdvgp6iLxVjcq8tvfWPSi0qT0dsGK+DWUBvbF50T2W8ka+6VyXvDrLXT1AhJw7J0oPvSVzwr35z5y8gN3TvQeqNb2a/ay8hSNFPRXns70YQCO9nXt5vGiONzvq98i9oY6CvSfX6z3kXwm+pTrbvbo4VruTYZ68TZg5vccONTvs6qy9zwE6O8z12rwuTCy9FSpSvVtglzuRkvi9ZaQcPiRhqzyZdsa8SptiPWMhyzvF+cI8UgcnPUJ6tLwkoE28jLievKAGZb1rnyo9gIpXPJKvlrwoQBo9dXKZvVM frnLyATEU95X+qPYBDoLu7db48TS5BvYB2Aj7PlUI9sGMxvWqrRT0FY6u9xeaQPTxLtD0+UDA7aotivdnLWj0Uh5m81NxIPU5SsbwmlMQ84xYuPN/hZTziwJU9h3ZIPRNU5T1QyQq+Q4mkPAjSbD3FdMY9315iPXtM1D0E2m49EbqKPKQX87w8Cb88fNflPQUh9b0fJSU8zYQLPZMjjDw3olE9n0m5PTlIkzsPhIm9fBp0PAVWhD3gwWY9QI/Lvd3uNDw6RZo9dWYePI2KUr1X/oM8sumJPFuSSj2gQQU9TIjtvA1hLzysiZO6jhRsPZRb3Dy3Vau9cK0evZO0yj30CKk9iVe7PGl6Cr1JN3Q7xh2YPJwxWTtkrRk9xviZvFAgs7029da8lPaLPIG7bD1/hbU8klNCvcRuHr3qZMO6nR9YvfnmgLvC7vq7gf2JvcvuW719bT49oWaEPHUBBj3Wsee86ILROxdQCL3AI2s96SlfPS/HrbwAtU29Rm9qPQtSobxyhMM 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 Ejqb2NUHY9V+eOvBUCYj366bE8zXKdvbQzeLxxnoQ9B+r1vFsBoz0WqIQ7wFpFvQcX5DxPuSm9vIQbPXlO8rxUy+o81tIfvaCr2Dw54jO9o5mnO3ExKT2z3yq91NMpPVuKi7wdK2q7Lc/8PCcQAT3Psx+8FAUaPY8Nh7t2nI+9ifioPG1OTTxXtmw99RotvESmxrygdW48oKRIPKjSJr0K4q88H6KVu9D/cb2ISGu9wImRu8yroz30RVo9DT58PTXHT72P29U9JxLpvJZqIDwPQgE9xW8QvpFFIr1n8+88jryHPEQFj73hIys8eaiBvE6+ez076QQ90TCxPfjyvz0XXJa8BjSvvU7wjLwH/Bc9oFUNvlb4mD1wuYS9sSc9PjeUd70Ar5C8v2cEPTNtnb3KLiq9VgnqPJljqT34BIu902+xPQbIq7wpAmw+cNCVvXozET0YKJ25lIwPvbumyry+Awc9MuK/vX8jMDxHpau9+XULuxLtoLyEFbg9Uq26OIACPj2v4LM 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 eudz2u1IK9h7S9PaMT+DvFyaE7WPiLO/+di70cjE09unbGvPxhbzz7F5A9VLWnuv/hlr29FDQ9ZgokPXrLcL2jfhK95LqEvIwh7TyZm909EJs1veyWLT0o+kq7dvuGvV5ykb2Ye3K8LXJ3vKHQgT1kLPa8PMabuwhrrr0ChLW9H2JXPfZy/by31b28Gdrku4eIiry7Z/e81o1zPRsPirxy03i8QkE2vXG+kbwx2Se80fELPaxFursl+y+9cvFYvD2RH73yFw+9JewNvT/QQj2tpp08LZMYvbWf8LtaEZe8+vemPPyjsr26atO7QC2fvVABjj3JZcS9Ax4tPYZSz72XExi9YLVTPUkLyL1v/wq9/BdNPTFxUb1HIyW9GzugPIkpFb2f0fW6gyW4vBe3Dzw02yo9qjJbvGTsQbyomae8fJRBvZyvt7uWvMa4ufVQvTMLoD2rvaY9I4YDu2ffnzzoBsw6EyZnPETqO72B7t882eQTvMfQsTwt7Tm88g3hvFZWAb2nIaM 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 K8F4AJPFI8fbyMVce8EXBrvRaLCr0lF369QsNtPcnQobyXUxU+sunMOpxovr3ZAKY9vTvSPS590Ts7xEu8E6bXPbcxDL6rDAs9+ttjveUc1D0q6Zc8C1gtvtHKij13uK88fv+bvGbZjD34GSY+qOpOvnscujzYh/U8adz7PXMB6Ty9hyW+jEqrPcpKNT2srjK9oY/vPGQokT1uoUC+brGxvb8b+TwMslA91jTzPXN1ub11d+Y9Y1mtvOByi70GVyy9zH+1uh+wOjxKbwW9fTTfPT66Cj1JGiU+08UZvtBWQD56L8M8r1bavWUwQD0Aguy93GlwPDtsvr25AOA9r8Kcve+M+j3KETm9W0MnPk/xZzxfybG9lyNGveQ5mb2Rnq083awFvugG/j3UqKS9IWn2PYlKJryR2wE+neukvJ7WEb2Lf8O9PiuAvZ15OD5n3hS+0/0hPsYYT732bBo+YkHrPfxK8D2wPe69KnmpvVmm3L3OdNy9V5NaPgC4Dr5kyCI+CrENvpM 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 48/g8jvaaiGb2WX389ucD3vUgaGLiPWVE9nFe6vOYTsj1K0tY9JMCRPeXLyT0RgGQ9RKVFPVTOYD1H3to8hmUEvUAIrz1nYF286Xe0PbNwKT7hNUK7VjgZPuerwb0Rmus8aLFxPS8Fkj3qQ2S9+pGfPdQwar0dDJ67PFg7PmXm3jsChgM+dmMGvrvxKT2UObU9NtGBPcpMhL2WIS88LW00vvmmg733okM+LR0fvQ43iD0JN5g8uq5ivFxGLTy8SDE9301XvV32Yrw+rgU93vkwvCg9ED6OW5y9anD0PcZBqb0RWmU9PmkmPc2DuD0RssK9K8nou8epNzzE0IO8+Gf/PSFctr3s9IQ9hVoPvgakIT2eQ6I90KFWPcFAx710ypS9ZBnLvZ2nsb1YlR4+Wy/cvLI7Yr0YjDi8A0rovR2l2rwonNm947VDvZN6vLzup889BMSdPccwh70d/gm9S72DvXMaFT2h7oq9ai1gvcasGb5utze9DAfqvOZ/7D3eSgg9F5R4vSM 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 hclz11xh47oWBgva6elLzmD1w8Ohb7vI5efrxBpLA7+OfguwPloD367uk82oOoPRICeT3zrXq90bkQvhx0bD3REEY8eaCIurCZo73CSk091va0PB2uEr2tWQI9L88WvXRDA7zolue9IKeCPbOSh72hX3C8gIjrPL536DsJiNs7elvtvMquj71bbEC9BtgXPRKEdL0FpKw8cPlAvbnDBTv3nX+9D25GPLMs67u92ZE8MM1gvO2xAbzx9o89+8fNvYcOjj30kwO9+HadPMW/Bj0+3Cq7XqE3vWvXhb0y8wa9Q7+kvIQH5jw/Rp+93kCsPfKnRb1NyGq8rKUqu+Bevryph4Y97Qh8vcbQTj33kWy9awZqvQI3673qGBY8KqEQvZgJND2bu3+9iGwdvVaz/DzJ2wq9CKz+u/NUvbxJLpI7dL8IvYdLbL12v5E9ErZiPL7GrLyeOHy9vi1ZPUkzID0RNt88GMCZvBBMKTv7m2c7hVKRPFRirTyrXLS9Mc6cOvZ+hTzJzbM 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 c957bFvKWPGz7Bzrk891VwvqVkoD2Ohei7+UOdvQfjMD6cYO09pVODvjA7Rb0AFdS88Y0oPWwHeDx9zFe+z7bjPHaPQD0Zq2K9Gx8dPpGS2j3c/DG+InlHvaylWjw3XCC99lO2PbpAD72gbow9fFIqvUY7LL1Sswg8ZX5+vbRbPb0ZPea9jH9CPXwTKDut/EI9r6QJvhZtxz3mgQK9c05nvb0n0T0dXSG9ZKWpvd0uvL2pVKw9PLGAveT+6D1735i9KEw8PYZW0TlHV/e8wjaAvSXPVr06Hss5lRZ1vXZGRD00AJ68FKSdPQnN/zzH2fo9BAX3vB8pwzz3LHC9HSOmvae1ND6e1Zy9COeMPZg8vbww1+072Q/WPdqHHj1xQUi94WbKPMjDCL6NkWW9jPInPplcpTy4S9o9dgvFvdwqhTwFCRU+AKsyvDr6u71HIWG9MlwxvgH/or0pW0U+V8DwvebPDD16MAS9MO5kPbeB2zwnGJI9tg/bvdgsGj2t/Z29RBw4vYM 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 +7GC8FPY6eaj2lNJ499wtKPVJtaD1RSVA9jcKMvcXvB7yxP7G8ImVVO6M1nrxmTB29sUixPeTMWbxEUWY9Hv1kPEEmzzxt8JU6x9FqPeUecbsB56Y8q6odvSrcJz1gulY9i9JXuv2inj3QnBY654X9u+VSiDxpxVM9T5RSPVzRmbzMCQ69bfHmOtobl72GxZW7ySU8PefZm7yYDiO9G8qePXwECjzrZsM8WN2jvGHnDD1yNSo8HbzrPOwDJz3nZtM8CVe5vToBxDwplHO8IcIuvdqRbr0vCkg7X7kPvb2Gij27LDm82duHPKzcOzuNojG9msoFvuUHLjzROKk89unkO0QFMj2TeEo9Q/scvUvAfb0E4nm91BIZvSe6XT2GEbi9q1LSPJkoXrwwotQ8BAPOO7ZUujzpXu48GN2svL1NmTy4qWy9c+F2PYt9jL1lYVQ9Ms8WPDmUzTwsw5O9kLBjvGVIUD0yKdo6igrWu/RsUL1u4yo9tTssvXX5hby0f3K9edumPLM 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 z4Jj33t5e9t+fsPRaGv7xZWzA97HyrvPK8Kb2IZJi8AsvDuvKsYz1L8eA7o5CIvDuU2TuNLwU8H6bTvOSUQj3gHRA8V2CNvXpE1Tyzk4q9MiZRPGtbC75TLQC9CjuDvdkVHD1Vnl89VsdHPa0N2r3qMBC8PU0NPc+pJL0h7Q69LlwSvbz5cD1bPf08dUhpPe/FrjtbXra8BowKPYNeSD1ptH+83+rcvHwmhL1dt1s9Rt3EPJZ5Q72uYnk8BNCKvQ85qj3bi8k823jEPKtYDb3HS+68GGwbPGWDIL1bxu87aRQQPYXDhz088RG9FEy6PGa8c735EAg9QjWwPEHGUD3BVKK8QCzPPbGL9ryJX0Y9aUoEvcxs6b005G68oAqePGuXTT1ZbgU9G4ODPc3xoL1aCtE9TcqVvSaVArsRQq+7fViSvUW7TD3TEG48YWWWO+YjoT2Ij2S9898IvlCEtTxFq7c8kjPbvMH6DL3W4bM6kRaNO6xoCj0E62083fxgPTGn+7wqFtM 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 M9APvOvVN7Er1gaZ+8b5Bavd/RKb1NwzG97H+YvULIWT0Gqls8JKsHPTI3w7y2yLk95TBNPTwbvL37Sa88ZQ3ZvDolpry7qKe883ljvDD9hbv0Iis8jYUrvHeVSj3tTo09eQ28vZABPjzwnjm9Vm2hvCoxfLw+88G9WX6HuxTK4TxiRby7gViCPdPV1by0Cim9tOZivWJO7jt45o+92Ql/PSPahD1J70+8OmXyvBia87seAuO8UDf0unm3I72i4KY8pYhaPOOfNLt/C8M9Kk+wPEH6Gz3J1Ze9BJfJunGyJztLu3i8oBWIPYknrr0bpG89h/SJve1qljxExry92UI+vatbHjyvXoQ9BJFzvFxF47yhFQU9EkMAvnMdWjzFFPq9ss+GPVcDdD0z2UW9wbtivQwZk717Rli8PKlvvf3dpTt6JYq9W+8bvFlwTb0XPKk9Jg9GvPTm4jz0C9i98TBevSazDr27DiC9d9AmPdrQ6b2C5RG9X1IuvRRD7byR0rW9aPbOO3M 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 RJGD1bCZ88NXRFPW6BkL1xZaU9DD1CPTGtar2XdmQ9Ya3YvNK9Jb0Fo4G9kH1APacc0LtV3Lu8wAfwvbyjTT39aKC7mxFrvfExKTwYCU29oadfvHWafrzyAqk7G3hbPWbozLmMhU49Z8mPPd75ELsaAIs8eA2iPBoOxrx4ilW59MWIvbyhhz1neAe9EsWsPHeFOb1AGAU9SkRUvIb6qr3UvE28nIqju2o8Jr3OGce9lzoevQCaXL0Loii9umpJPesTAz1TgHK95fcfvu8Tbz3tf6e953j0PRMgwj28Y4881qsSvZP2erwtu/O8/O8wvQk73zz0KE48irURPLzJ/byIGYc9uitPvSxuozxyZjm7h/lQO7N6nL2OBu28AWgPPYfEvr0jM0u80peivZVcgT1lmH+9ejlCvbUcA73CYQ08ismhvXmVybyYp/C7BlqDvQHzvjz+wwq+dnCgPTIl+T3QSUM9IqF5vYnZUbzqQRe+XFGgvFHG1T3FZ4i9UEUjPTMJsr2wIpM 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 8RqjxPUyK9jV1UPbjq07z9IPo9S/FjPdMZJT0vM2W9INNkvfcpEb3r8WU9Z2kkPAsUz7oFPMM8MeTrO4XIyDs+PIc97PMSvWZsYr3Drga9KOF5PfWcf7wjgJ881GJEvQWeND0Yxvq7S6SuPQUQAz1xUEQ9ZiwvvW66Sj3tdZE87SiQPJjHED2tpLW9CD+oPDAJXD1S0v89vmR4vG+k5jz0Pp28RsH1PKbMSj2cgtQ8BdkEvBRzuL1PWEc8u8JDPZCz6j3g9l89fPcSPNoZCr1oKmI9L6rEPd7csTruIp098NEBvgLo0rwDoSo9pRkgPchUQz1y5dI9+3MIvMdZGLsk1A88QTXHPEu1hj23x/e8DO9aOrXvcT2Gloc9NsvvO2+Jdbx9Ehe9H6zzPXiaeL0BQts8svC5u0BKDb5Htfm7CNiAPCU94TwHZ/q6h9GuvDOCFb1LRPo9/U8iPca7LD0Zmuo8ja46vr1AHb1RU809S34+PAKsojwLcrY9TxglvVlpMD0bO6M 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 O8AOJSvVjee72h6yq8MHaMPXf+1rvjEQs+kvoCvfw+1j3fnz27t/1Ovbg/0L0RL5u9qeO8vTCyFz1Vc+g8aHwmvXKWmD2B53C9HGpYPT3plL3S1Wu9ZoSOvbeRN71p3Qq9PRA8vGSD5TzkKfm8BoKHPblSYL3ubdk9x5UUu8k2xzubMrK9F9kYvVbOhL0H/48954zOPKgalL23IQE+zemHvbMyCj7pNQQ8u3iYPOi2l714oza4zMvzux9u3brBvsW7dq3pvL0ixz0MCPO92l8gu0xF2b09yoK8Fj58vTDxfr1KatG8aNH+uzxPrTx55kO9v6SdPd5jAr2Gy3w9U34xvYkKoLySDn29fPs8vMlu6by3+D89+ph9PJutS72wMwc9CB8HvYLiwj2Oy6I8QRC0vWxQgr0V5QS7mIQwvZ8ao7viQT87kPxSvaEvWjxfB6e9/TwPPWnrM70yAfm8uuCpvY1BqL03AqC9ADOUvWPdwD1U39C9Mm6rPUWd4DzLay09oVRKvSM 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 I8oWegPPjpYT3coDG8BR+cPGG8AL2fBWA7QZjDvKyPUL0PjTy9GGd/vMpnML0dNBm9BncuvDl4cj3rLhC893StvQ4GLj30dZy7lPoDvT7pYL7m+W49tKg/vePZC71Z+Ai+XybsvHXb6jvqIJA886HeOntoJb2DzJq9PlIUvVC1v7zDZuq8v7NZPduvIrvd3Zo6hPvlPEL5+Lv5lBE9EyRwvSTpJTvsHSS8uBiGvXjR67xNQl+9ZZQivBVDNj29MK07oWqRPDjTGb2yZl68ha/iPPuiA71rxay7kGTGu4zVIDthzw+8Mf/rO4CAn7011sc7BZYpPaporrwPTKC8UVZsvSXvHr1mM7u7HPkyPO21KrxgU5q8heR7u3MrY7yk2Ae9VxF8vTu+kj0c01e8O0shPPrTz7wbUjw9tSWQvZpCPT3bilW9SRcgvSjxF7z1QS+93fTxPFlawb39Vq488+EdvbmT4jy2t569ZWYwPITfAb6bb7c5c7dvPDvc8L1eBby8dHc0vdM 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 K9c8rPPcAalL1aKby70jcyvX4xbL14sLY7pv/wPBxLPD3o/rm9A1yXPb1iqTyTTOs8P33JPGiyvjvSz+U6dwGzO/s7zbzoNUA8saabPUJAOr14/QQ+UgSKvYloTz2XB/i8agKoPGsNVD0of1o9KxumvPxiBD1TZ4M9MV1ZvYV7KTwpcpm8jYAIPbMy+7x9xD69LHYkvfway7w7GIm7haq0PcF7oLzEbki8zSvmvESeqzxfaIY96ia6OzRmiT0K5LA8qEBmPSG9ej2A6Zy7S4T8PJZfGb2x8dQ9yNeAvW1gmrygSD474mSpuw4tXrzGV3894AWgvC0Plj07vHY9wS6UvXSzhDtmzHm62dkdPRNbnjsHgem8PmqMPECx0Lzsg+27ltd0PQxMwrvezM+8Tt18vRSaqTzy4ZO9RKyiPVjHGLsV+8y8irP3PJWNa72UIfk8F3bdvNAJXbnR1Aa9qjkfPcSLob1TYhq9S0yMvWMDej22uRm7HbXHvIJ9qj3CP4e8FR+lvQM 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 13gL2InfY8JfO/vN8A1jyayni9iWFbvc5hxT2xWfg9PlRoPOoEVD0Kra89kvTevWnzAD3qNc08GzUqPcdZ0Dr2Xoe94uxmPQoBzDzJdgC9t2WmPOEKEz1oXpK9wVGLPGCa0bz4oNM9tneoPBI0pT23Npc8CiSAPShkwDyuC4E9GFhjPUMRm71Gb1Q9LOlaveQDOz0EPVu9ibOhvHX1kT0SFIo9fREOvdhndj1qeKM9qPUUvjHYKD1froY8k6PRPB0bqb31eya9RvmCvAGmK71zXae8LKe2PZNNgTzx0fW8SMYBu5Cfzbx0fmM9b+kdvHuMKrvVie88UNSLPBbFDr0pKrA9YH0jPQALB742n4486H+AvJZRdD3k5YE65CdGvcgVmz0LoSQ9UoYru2ce1D2DYac9LrK/vXpJiD1FVAM96mDmPL7KfL01vYS9+J8rPM58IL2iA5S8PMYlPU5vkTz/U7C9+gyGvV/Vq7w5Xl07vgmUPXEIQTpEMvU8uGApvbtTmb0TPIM 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 IgVruyzue95qKNPYF+grzXMLo9ZHLNPKVJojyUVBm9tDNBPYSmeD1rjYg9SToyPZd03r3NbcA91Y7Svfj3GT3oSLS96UxpvY9Qh7wn+Yg9xeIhvVtITz2tUaI9hDQxvlBuHzuKVNi9bma5PXnRib1srsw705fuPJp4zrvbcv27WGT8Pey91z2/EPS9+IA/PZn+Mr15OHo9Rn90vaIMej28dQo9O8yWPZ5CpTzHGjY9BBDhPGVuo70Jx8Y9Dwy6vYntTTw0NE+9El2OvbEzobw8S/M9+90fPXnsgD1/7Fo9ZTYWvj6xEzxSqMO7Or+APUjItL3Do62841U9veAew7xjkY68WsOSPTrb6zyLUpm971FuPbxHKb261I89GS/EOsAp1bzUFg891FgmPSb9ozyZhTk9Sjw1vEjFkL2KReQ9zjGhvC4F37yHlAO9J0CKvU8+lj1BFLM8fED6vDPkjz1SyMY9gC1FvWeekj3vc5+9vOcSPbbHLDulZIw8K0WuuzDcM71dpnM 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 Q+IPJEvm8mxT7cVsw+4xt2vqn+I70r4rS9HbCCPkXRtT7lQZm+TBH7Pbv4X76KQso9IrfhvlQnAz9Iizm99oCXvmLgCD61n448MKdSPiNHWj68AvS+RzISP/eVBj+rBAI/I3ukvQZIhD7Nync9bxPwvSMomD2x+lI+1C5uPMXRyr1xVd08ZNXYPYwTOL7Z0X68Ay0Zve3tUr6mW5w+KTVIPsDeIj+N7mK+EK+HvgKsqj3cQmC+qQQhPkEeub0PLEo/G99mPkHizb1Upbe+kWHWPr0j4L6Gswa/0Z6vvQBgEj6y18a++DkhPnp/Bj8Izi8+5bYIP/fy7j7gurS9NWCiPqjlNj88Dse+N8CxvuvZ9z62Tc6+2LFkvhtU6L7VE5i+aBmovrN1CT8yeLe+WmBgPqEHYj14qas+fjEXP7dY8r5uhY6+PqYMv1BxwL7m4QM/spLHPhrnr77erEy+Tj2fvga2mb7kDx0/DVk+Ps/aCL9GeBG/i6XkPtIPnTs6Ti4/xyfrPqM 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 S+hg4RP7zbYz71nic+kOLkPraYCT8TxCA/JPgAP7NsbL5Qsxs/nQgXvoWDfj5ZGMW+p4M1vlD1JT7hv7c+J1GZPU9gm74f5xK/WgrdPsSZJT/AuLW91pvCvBCSgz0P1oK+0QBRv/QMVb49+y+/eoLJvWUzpD5nsYs+TcaZvecbp777l3C+SdFbv5mC7b7h51E+AqBoPxASBr9/kea9NQIavuHfWr8ELxA/DPUKv2aOXb6eNkc+", "training_traits": {"structure_gen": "Zigzag", "n_layers": 8, "max_nodes": 11, "activation_func": "ReLU", "epoch_num": 4}, "classes_name": ["Cryptoadz", "Cryptopunks", "Moonbirds", "Nouns"]},m=25,b=50,y=59+11/12,w=59+11.5/12,v=60;function z(e,t){const n=Math.log(1-t)/Math.loM g(1-e);return e=>1-Math.pow(1-e,n)}class V{constructor(e,t,n){const{model:r,inputDim:i}=j(t,n);this.model=r,this.inputDim=i,this.iteration=0,this.stage=0;const o=new Date(parseInt(e.birthYear),0,1).getTime(),a=new Date(parseInt(e.birthYear)+1,0,1).getTime();this.birthDate=new Date(Math.floor((o+a)/2));const l=zr.filter((t=>t[0]==e.lifeCycle))[0][2];this.growSpeed=365/l,this.cycleLength=60*l*24*3600*1e3,this.growthFunc=z(.4,.8)}updateAge(e){const t=(e.getTime()-this.birthDate.getTime())/31536e6*this.growSpeed;this.iM teration=Math.floor(t/60);const n=t-60*this.iteration;let r;this.age=n;let i,o=0;if(n<25){let e=map(n,0,25,0,1);o=this.growthFunc(e),r=(25-n)/60,this.stage=1,this.stageRatio=map(n,0,25,0,1)}else n<50?(o=1,r=(50-n)/60,this.stage=2,this.stageRatio=map(n,25,50,0,1)):n<y?(o=map(n,50,y,1,0),r=(y-n)/60,this.stage=3,this.stageRatio=map(n,50,y,0,1)):n<w?(o=0,r=(w-n)/60,this.stage=4,this.stageRatio=map(n,y,w,0,1)):n<60&&(o=0,r=(60-n)/60,this.stage=5,this.stageRatio=map(n,w,60,0,1));n<50?i=map(n,0,50,0,780/880):n<w?i=map(n,5M 0,w,780/880,800/880):n<60&&(i=map(n,w,60,800/880,1)),this.nextStateTimestamp=Math.round(e.getTime()+this.cycleLength*r),this.statePercentage=round(100*i);let a=(25-n)/60;a<0&&(a+=1),this.nextStableTimestamp=Math.round(e.getTime()+this.cycleLength*a),this.growth=o,this.model.updateNeurons(o,this.iteration)}getBrainStatus(){return{totalNeurons:this.model.getTotalNeurons(),neuronsLife:this.model.getNeuronsLife(),stage:this.stage,inputDim:this.inputDim,stageRatio:this.stageRatio,age:this.age,growth:this.growth,nextStatM eTimestamp:this.nextStateTimestamp,nextStableTimestamp:this.nextStableTimestamp,rebirthCount:max(this.iteration,0),statePercentage:this.statePercentage}}classifyImage(e){const t=new G(e,1,e.length);return this.model.forward(t).mat[0]}}class M{constructor(e,t,n,r,i){this.p=e,this.v=t,this.size=n,this.shape=i,this.col=r}getRadius(){return 1==Oe?1*this.size/2:2==Oe?7*this.size/16:3==Oe||4==Oe?4*this.size/7:0}update(){this.p.add(this.v)}draw(e,t,n,r){const i=this.p.x*r,o=this.p.y*r,a=this.size*r,{col:l,shape:s}=this;leM t h,c;1==n?h=c=l:2==n?(h=dr(t,1),c=l):(h=dr(t,0),c=dr(l,1));e.stroke(dr(c,map(1,0,1,.25,1))),e.fill(dr(h,map(1,0,1,.15,1))),3==n&&e.fill(dr(h,0)),1==s?e.ellipse(i,o,a,a):2==s?e.rect(i,o,7*a/8,7*a/8):3==s&&(e.beginShape(),e.vertex(i-4*a/7,o),e.vertex(i,o-4*a/7),e.vertex(i+4*a/7,o),e.vertex(i,o+4*a/7),e.endShape(CLOSE))}}class E{constructor(e,t,n,r,i,o,a){this.center=e,this.len=t,this.angle=n,this.v=r,this.angV=i,this.c1=o,this.c2=a}getEndpoints(){const e=createVector(this.len/2*cos(this.angle),this.len/2*sin(this.anM gle));return[Vector.add(this.center,e),Vector.sub(this.center,e)]}update(){this.center.add(this.v),this.angle+=this.angV}draw(e,t){const[n,r]=this.getEndpoints(),i=n.x*t,o=n.y*t,a=r.x*t,l=r.y*t,s=this.c1,h=this.c2;var c=e.drawingContext.createLinearGradient(i,o,a,l);c.addColorStop(0,s),c.addColorStop(1,h),e.drawingContext.strokeStyle=c,e.drawingContext.globalAlpha=1,e.line(i,o,a,l),e.drawingContext.globalAlpha=1}}function S(e,t){const n=random(TAU),r=random(e,t);return createVector(r*cos(n),r*sin(n))}class R{constrM uctor(e,t,n,r,i){this.wall=n,this.maxR=i;const o=t.length;this.nodes=[];for(let a=0;a<o;++a){const o=[],l=.25*t[a];for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),l=S(.02*i,.05*i),s=random(10,25)*i;o.push(new M(t,l,s,e[a],r))}this.nodes.push(o)}const a=A(e);a.unshift(e[0]),a.push(e[e.length-1]),this.lines=[];for(let e=0;e<=o;++e){const r=[],l=(0==e?1:t[e-1])*(e==o?1:t[e])*1.5;for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),o=rM andom(5*i,10*i),l=random(TAU),s=S(.02*i,.05*i),h=random(2e-4,.001);r.push(new E(t,o,l,s,h,a[e],a[e+1]))}this.lines.push(r)}}reflectNode(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,{p:o,v:a}=e,l=e.getRadius();(o.x-l<t&&a.x<0||o.x+l>r&&a.x>0)&&(a.x=-a.x),(o.y-l<n&&a.y<0||o.y+l>i&&a.y>0)&&(a.y=-a.y)}reflectLine(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,[o,a]=e.getEndpoints(),l=e.v;(min(o.x,a.x)<t&&l.x<0||max(o.x,a.x)>r&&l.x>0)&&(l.x=-l.x),(min(o.y,a.y)<n&&l.y<0||max(o.y,a.y)>i&&l.y>0)&&(l.y=-l.y)M }update(){for(const e of this.lines)for(const t of e)t.update(),this.reflectLine(t);for(const e of this.nodes)for(const t of e)t.update(),this.reflectNode(t)}draw(e,t,n,r,i){const o=i/this.maxR;for(const t of this.lines){const n=t.length*r;for(let r=0;r<n;++r)t[r].draw(e,o)}for(const i of this.nodes){const a=i.length*r;for(let r=0;r<a;++r)i[r].draw(e,t,n,o)}}}function I(e,t){re(e),e.fill(0),e.rect(0,0,500,500),ie(e),e.noStroke(),e.fill(dr(cr("#000000"),.5)),e.push(),e.translate(250,250),e.scale(t),e.translate(-250,M -250),e.beginShape(),e.vertex(235.2,24.9),e.bezierVertex(215,24.6,185,11.4,164.8,11),e.bezierVertex(147.2,10.7,129.3,10.4,112.2,14.7),e.bezierVertex(95.1,19,78.5,28.5,69.6,43.8),e.bezierVertex(57.699,64.199,61.599,90.199,70.199,112.2),e.bezierVertex(78.799,134.2,91.6,154.6,97.199,177.5),e.bezierVertex(102.499,199.2,100.899,222.5,92.799,243.2),e.bezierVertex(83,268,64.6,288.3,48.9,310),e.bezierVertex(33.2,331.7,24.5,337.5,26.599,364.1),e.bezierVertex(28.2,384.1,61.399,404.2,75.7,418.3),e.bezierVertex(90,432.4,73.7,4M 88.2,91.9,496.7),e.bezierVertex(124.2,511.6,159,472.5,194.3,468.1),e.bezierVertex(211.6,465.9,267.4,501.5,283.9,495.9),e.bezierVertex(340.7,476.7,298.599,428.9,355.4,409.7),e.bezierVertex(370.799,404.5,454.5,407.6,464.4,394.8),e.bezierVertex(478.599,376.3,474.7,349.3,464.299,328.4),e.bezierVertex(453.9,307.5,438.099,289.5,428.699,268.2),e.bezierVertex(412,230,419,182.6,446.1,150.9),e.bezierVertex(449.7,146.7,453.6,142.7,455.8,137.6),e.bezierVertex(459.4,129.299,457.5,119.6,454.8,111),e.bezierVertex(443.2,73.4,417.3M ,40.4,383.6,20.299),e.bezierVertex(358.1,5,343.2,-.4,313.5,0),e.bezierVertex(287.5,.4,261.6,25.4,235.2,24.9),e.endShape(),e.pop()}function C(e,t,n,r,i,o){let a,l,s;re(t),t.fill(0),t.rect(0,0,500,500),ie(t),t.noStroke(),t.fill(dr(n,.5)),1==i?(l=0,s=25,a=map(o,0,25,500,0)):a=0,t.rect(0,a,500,500),e.noStroke(),e.fill(r),e.rect(0,0,500,500),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379M ,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVerteM x(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.M bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5M ,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),e.fill(n),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,4M 53.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertexM (96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVeM rtex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),re(e),e.fill(r),e.beginShape(),e.vertex(184.3,473.2),e.bezierVertex(164,473.2,144.7,462.099,134,444.3),e.bezierVertex(131.7,440.5,129.1,438.5,125,437.1),e.bezierVeM rtex(97.3,428.1,80.5,400.6,85.2,371.8),e.bezierVertex(86.3,365.1,85.8,364.1,79.9,361.2),e.bezierVertex(57.2,349.8,46.2,323.3,54.3,299.7),e.bezierVertex(54.7,298.599,55.1,297.7,55.5,296.9),e.bezierVertex(55.6,296.599,55.8,296.4,55.9,296.099),e.vertex(57.9,291.499),e.vertex(62.5,293.599),e.bezierVertex(64.9,294.7,67.3,295.799,69.5,296.9),e.bezierVertex(74.5,299.299,79.1,301.599,83.9,303.099),e.bezierVertex(89.8,304.9,96.5,305.499,102.7,305.9),e.bezierVertex(102.8,305.9,102.9,305.9,103,305.9),e.bezierVertex(106.6,305.M 9,108.9,302.799,109,299.799),e.bezierVertex(109.1,296.199,106.6,293.4,102.7,292.799),e.bezierVertex(101.3,292.599,99.9,292.4,98.4,292.299),e.bezierVertex(94.3,291.799,90.1,291.299,86,289.9),e.bezierVertex(68.9,284,56.5,270.2,52.7,252.799),e.bezierVertex(48.9,235.499,54.5,217.7,67.6,205.299),e.bezierVertex(71.9,201.299,72.7,198.1,70.8,192.399),e.bezierVertex(64.2,172.2,68.8,153.99,84.2,139.599),e.bezierVertex(94.2,130.199,105.5,125.399,117.8,125.399),e.bezierVertex(124.3,125.399,131.1,126.799,137.8,129.599),e.bezierM Vertex(157,137.399,167.9,152.799,169.4,173.99),e.vertex(169.4,174.399),e.bezierVertex(169.5,175.899,169.6,177.2,169.9,178.299),e.bezierVertex(170.7,181.2,173.2,183.2,176.1,183.2),e.bezierVertex(176.299,183.2,176.5,183.2,176.7,183.2),e.bezierVertex(180.1,182.899,182.6,180.299,182.7,177),e.bezierVertex(183.1,162,178.299,148.2,168.399,136.1),e.bezierVertex(158.2,123.5,144.899,115.8,128.799,113.199),e.bezierVertex(123.499,112.299,120.399,109.799,118.899,104.99),e.bezierVertex(113.899,89.699,120.699,72.299,134.899,64.49M 9),e.bezierVertex(139.99,61.699,145.799,60.199,151.7,60.199),e.bezierVertex(162.2,60.199,171.899,64.799,178.1,72.699),e.bezierVertex(179.6,74.6,180.799,76.6,181.9,78.499),e.vertex(182.2,79.099),e.bezierVertex(183.2,80.699,185.2,83.299,188.4,83.299),e.bezierVertex(189.5,83.299,190.6,82.99,191.7,82.399),e.bezierVertex(195.1,80.599,196,76.99,194,72.799),e.bezierVertex(190.1,64.799,184.1,58.499,175.6,53.299),e.bezierVertex(174.6,52.699,173.7,52.099,172.5,51.499),e.vertex(170.5,50.299),e.vertex(163,45.899),e.vertex(170.M 5,41.599),e.bezierVertex(182,34.99,193.1,30.799,204.4,28.599),e.bezierVertex(208.6,27.799,212.9,27.399,217.2,27.399),e.bezierVertex(217.6,27.399,217.9,27.399,218.3,27.399),e.bezierVertex(231.4,27.599,242.7,38.199,243,50.599),e.bezierVertex(243.4,64.899,243.3,78.99,243.2,93.799),e.bezierVertex(243.2,99.799,243.1,105.899,243.1,112.099),e.vertex(243.1,119.199),e.vertex(236.4,116.799),e.bezierVertex(235.7,116.499,235,116.299,234.4,115.99),e.bezierVertex(233.4,115.599,232.6,115.299,232,115.199),e.bezierVertex(230.6,114.M 899,229.2,114.599,227.8,114.299),e.bezierVertex(223.8,113.499,220.1,112.699,216.4,112.499),e.vertex(216.2,112.499),e.bezierVertex(212.5,112.499,210.7,115.599,210.6,118.599),e.bezierVertex(210.4,122.399,212.7,125.099,216.4,125.399),e.bezierVertex(230.1,126.399,238.9,133.099,242.3,145.199),e.bezierVertex(243.2,148.399,243.2,151.599,243.2,154.499),e.vertex(243.2,155.099),e.bezierVertex(243.2,254.199,243.2,330,243.2,400.599),e.bezierVertex(243.2,401.99,243.2,403.4,243.2,404.9),e.bezierVertex(243.3,411.099,243.3,417.599M ,242.3,423.9),e.bezierVertex(238.1,449.2,219.6,467.799,194,472.5),e.bezierVertex(190.9,472.9,187.6,473.2,184.3,473.2),e.endShape(),e.beginShape(),e.vertex(315.8,473.1),e.bezierVertex(309.3,473.1,302.8,472,296.5,469.9),e.bezierVertex(270.4,461,253.8,434.9,257.1,407.9),e.bezierVertex(260,384,273.8,366.8,297,358.3),e.bezierVertex(297.7,358.1,298.3,357.8,299,357.6),e.bezierVertex(299.8,357.3,300.6,357.1,301.2,356.8),e.bezierVertex(304.3,355.4,306,351.8,304.9,348.7),e.bezierVertex(304,345.9,301.7,344.2,299,344.2),e.beziM erVertex(298.6,344.2,298.1,344.2,297.6,344.3),e.bezierVertex(288.1,346.3,279,350.9,269.7,358.3),e.bezierVertex(268.9,358.9,268.1,359.6,267.2,360.4),e.vertex(265.5,361.8),e.vertex(258.5,367.6),e.vertex(257.4,358.6),e.bezierVertex(257.3,358,257.3,357.5,257.2,357.1),e.bezierVertex(257,356,256.9,354.9,256.9,353.7),e.bezierVertex(256.9,334.8,256.9,316,256.9,297.1),e.bezierVertex(256.9,260.3,256.9,222.3,256.8,185),e.bezierVertex(256.8,170.7,268.3,158.8,282.5,158.4),e.bezierVertex(284.8,158.3,286.7,157.6,287.9,156.2),e.beM zierVertex(289.099,154.9,289.599,153.2,289.5,151.3),e.bezierVertex(289.3,147.5,286.7,145.1,282.7,145.1),e.bezierVertex(282.5,145.1,282.2,145.1,282,145.1),e.bezierVertex(278.8,145.3,275.5,146.1,272,146.9),e.bezierVertex(270.9,147.2,269.8,147.4,268.6,147.7),e.bezierVertex(267.9,147.9,267,148.2,265.8,148.7),e.bezierVertex(265.1,149,264.4,149.3,263.5,149.6),e.vertex(256.8,152),e.vertex(256.8,114.6),e.bezierVertex(256.8,95,256.8,75.4,256.8,55.9),e.bezierVertex(256.8,38,267.2,27.3,284.6,27.3),e.bezierVertex(285.3,27.3,28M 5.9,27.3,286.6,27.3),e.bezierVertex(299,27.9,318.7,34.5,329.6,41.9),e.vertex(336.1,46.3),e.vertex(324.4,53.3),e.bezierVertex(316.2,58.2,310.2,64.6,306,72.9),e.bezierVertex(304.2,76.4,305.1,78.5,306.1,80),e.bezierVertex(307.4,81.9,309.4,83,311.6,83),e.bezierVertex(313.7,83,315.7,81.9,317.1,80.1),e.bezierVertex(317.4,79.7,317.8,79,318.1,78.4),e.bezierVertex(318.4,77.9,318.7,77.3,319,76.8),e.bezierVertex(325.3,66.2,336.3,59.9,348.5,59.9),e.bezierVertex(353.2,59.9,357.8,60.8,362.1,62.7),e.bezierVertex(377.6,69.3,386,86M .7,381.7,103.2),e.bezierVertex(380.7,107.1,378.5,111.8,371.1,113.1),e.bezierVertex(342.7,118.1,322.2,139.1,317.8,167.8),e.bezierVertex(317.4,170.3,317.3,173.2,317.4,176.5),e.bezierVertex(317.5,180,320.1,182.8,323.5,183),e.bezierVertex(323.6,183,323.8,183,323.9,183),e.bezierVertex(327.1,183,329.8,180.6,330.3,177.2),e.bezierVertex(330.6,175.7,330.7,174,330.9,172.3),e.bezierVertex(331.1,169.8,331.4,167.3,332,164.7),e.bezierVertex(337.3,141.9,357.7,125.4,380.7,125.4),e.bezierVertex(382.5,125.4,384.3,125.5,386.1,125.7),M e.bezierVertex(412.8,128.9,432.6,150.9,432,176.9),e.bezierVertex(431.9,182.3,430.9,187.7,429.1,192.7),e.bezierVertex(427.2,197.9,428,201,432.3,205),e.bezierVertex(446.8,218.7,451.8,236,446.6,255),e.bezierVertex(441.4,274,428.3,286.5,408.7,291.3),e.bezierVertex(406.1,291.9,403.6,292.1,401.1,292.3),e.bezierVertex(400,292.4,398.9,292.5,397.9,292.6),e.bezierVertex(393.6,293.1,390.9,295.7,391,299.5),e.bezierVertex(391.1,303.4,394,305.8,398.5,305.8),e.bezierVertex(409.9,305.8,420.8,302.6,431.1,296.4),e.bezierVertex(431.8M ,296,432.5,295.5,433.2,295.1),e.bezierVertex(433.8,294.7,434.5,294.3,435.2,293.9),e.bezierVertex(436,293.4,436.6,293.2,437.2,293.1),e.bezierVertex(437.4,293,437.7,292.9,438.1,292.8),e.vertex(442.5,291.4),e.vertex(444.2,295.7),e.bezierVertex(450.9,312.4,449.5,328.4,440,343.4),e.bezierVertex(435.3,350.8,428.7,356.7,420.2,361.1),e.bezierVertex(414.3,364.1,413.7,365.2,414.8,371.7),e.bezierVertex(419.5,400.2,403,427.6,375.6,436.9),e.bezierVertex(371,438.5,368.3,440.7,365.8,444.7),e.bezierVertex(355.2,462.5,336.4,473.1,3M 15.8,473.1),e.bezierVertex(315.8,473.1,315.8,473.1,315.8,473.1),e.endShape(),ie(e),e.fill(n),e.beginShape(),e.vertex(120.2,279.9),e.bezierVertex(117.9,279.9,112.4,279.299,112.2,273.599),e.bezierVertex(112,267.7,117.4,266.7,119.7,266.599),e.bezierVertex(133.1,265.799,143.1,259.499,149.3,247.899),e.bezierVertex(149.6,247.299,150.1,246.399,150.3,245.399),e.bezierVertex(150.6,244.299,150.5,243.299,150.5,242.7),e.bezierVertex(150.5,242.6,150.5,242.5,150.5,242.299),e.vertex(150.3,238.799),e.vertex(141.1,235.99),e.bezierVM ertex(114.6,227.799,95.6,202.499,95.9,175.799),e.bezierVertex(95.9,173.99,96.4,168.199,102.2,168.199),e.bezierVertex(102.6,168.199,103,168.199,103.4,168.299),e.bezierVertex(104.8,168.499,108.2,168.899,109.2,175.599),e.bezierVertex(109.3,176.599,109.5,177.599,109.6,178.499),e.bezierVertex(110.4,184.199,111.3,189.99,113.7,195.499),e.bezierVertex(121.9,213.99,139.5,225.499,159.7,225.499),e.bezierVertex(172.1,225.499,184.1,220.899,193.5,212.599),e.bezierVertex(194,212.199,194.4,211.799,194.8,211.399),e.bezierVertex(195M .1,211.099,195.5,210.799,195.8,210.399),e.bezierVertex(197.4,208.99,199.2,208.2,200.9,208.2),e.bezierVertex(202.5,208.2,204,208.899,205.3,210.1),e.bezierVertex(208,212.9,207.9,216.9,205,219.9),e.bezierVertex(196.5,228.6,186.3,234.3,174.7,236.8),e.bezierVertex(168.799,238.1,165.6,241,163.899,246.7),e.bezierVertex(158.3,265.9,139.9,279.7,120.2,279.9),e.vertex(120.2,279.9),e.endShape(),e.beginShape(),e.vertex(187.2,427.5),e.bezierVertex(183.799,427.5,181.299,425.3,180.799,422),e.bezierVertex(180.6,420.8,180.499,419.5,M 180.399,418.1),e.bezierVertex(180.299,417,180.2,415.8,180.099,414.7),e.bezierVertex(177.199,390.5,156.699,371.3,132.399,370.2),e.bezierVertex(131.99,370.2,131.499,370.2,131.099,370.2),e.bezierVertex(130.699,370.2,130.299,370.2,129.799,370.2),e.bezierVertex(125.99,369.9,123.199,367.2,123.099,363.6),e.bezierVertex(122.99,360.2,125.799,357.3,129.599,356.9),e.bezierVertex(130.499,356.8,131.499,356.8,132.599,356.7),e.bezierVertex(133.199,356.7,133.799,356.7,134.399,356.6),e.vertex(138.299,356.4),e.vertex(139.1,352.6),e.M bezierVertex(139.5,350.7,139.799,348.9,140.2,347),e.bezierVertex(140.899,343.4,141.5,340,142.399,336.8),e.bezierVertex(150.099,310.7,174.399,292,201.399,291.3),e.vertex(201.599,291.3),e.bezierVertex(203.699,291.3,206.299,292,208.299,293.2),e.bezierVertex(210.499,294.5,210.699,297.5,209.99,299.8),e.bezierVertex(209.499,301.5,208.199,303.9,203.299,304.7),e.bezierVertex(202.199,304.9,200.99,305,199.799,305.2),e.bezierVertex(194.499,305.9,188.99,306.599,183.799,308.9),e.bezierVertex(165.499,316.799,155.199,331.299,152.M 99,352),e.bezierVertex(152.399,357.8,154.499,361.7,159.699,364.5),e.bezierVertex(178.199,374.4,189.399,390,193.099,410.9),e.bezierVertex(193.699,414.299,193.899,418,193.599,422),e.bezierVertex(193.399,425.2,190.899,427.5,187.399,427.5),e.vertex(187.2,427.5),e.endShape(),e.beginShape(),e.vertex(364.3,281.1),e.bezierVertex(346.3,280.6,332.9,272.8,323.5,257),e.bezierVertex(321.6,253.9,320.4,250.2,319.2,246.7),e.bezierVertex(317.7,242.2,315,239.799,310.5,238.799),e.bezierVertex(298.5,236.299,288,230.7,279.4,222.1),e.beM zierVertex(276.7,219.4,274.9,215.299,278,211.9),e.bezierVertex(279.4,210.3,281,209.6,282.6,209.6),e.bezierVertex(284.4,209.6,286.4,210.6,288.3,212.5),e.bezierVertex(297.8,221.8,310.4,226.9,323.9,226.9),e.bezierVertex(340.2,226.9,355.1,219.3,364.8,206.2),e.bezierVertex(371,197.8,374.2,188.5,374.5,178.5),e.vertex(374.5,177.9),e.bezierVertex(374.5,177,374.5,176.1,374.7,175.4),e.bezierVertex(375.3,171.8,377.9,169.5,381.3,169.5),e.bezierVertex(381.4,169.5,381.5,169.5,381.7,169.5),e.bezierVertex(385.4,169.7,388,172.4,388M ,176.1),e.bezierVertex(388.1,190.7,383.4,204,374.2,215.8),e.bezierVertex(365.8,226.5,354.7,233.9,341.2,237.9),e.bezierVertex(340,238.3,338.7,238.6,337.3,239.1),e.bezierVertex(335.9,239.6,335.1,240.4,334.7,240.9),e.bezierVertex(334.599,241,334.5,241.1,334.4,241.2),e.vertex(331.799,243.6),e.vertex(333.199,246.8),e.bezierVertex(338.199,258,346.799,264.9,358.699,267.3),e.bezierVertex(360.199,267.6,361.599,267.7,362.99,267.9),e.bezierVertex(363.599,268,364.299,268,364.899,268.1),e.bezierVertex(369.099,268.6,371.799,271.M 4,371.499,275),e.bezierVertex(371.199,278.6,368.299,281.2,364.399,281.2),e.vertex(364.3,281.1),e.endShape(),e.beginShape(),e.vertex(323.9,437),e.bezierVertex(323.7,437,323.5,437,323.299,437),e.bezierVertex(319.599,436.7,317.299,434.1,317.4,430.2),e.bezierVertex(317.9,406.099,328.299,388,349.5,375),e.bezierVertex(350.7,374.2,352,373.5,353.4,372.8),e.bezierVertex(354.099,372.4,354.7,372.1,355.299,371.7),e.vertex(357.499,370.5),e.vertex(357.799,368),e.bezierVertex(360.4,346.6,345.199,323.7,323.9,317),e.bezierVertex(31M 9.099,315.5,314.099,314.9,309.299,314.4),e.vertex(308.199,314.299),e.bezierVertex(305.99,314.099,300.799,312.9,300.899,307.299),e.bezierVertex(300.99,303.499,303.899,300.9,308.099,300.9),e.vertex(308.299,300.9),e.bezierVertex(327.099,301.299,343.099,308.7,355.699,322.9),e.bezierVertex(364.299,332.5,369.399,344.099,370.99,357.299),e.bezierVertex(371.099,358.4,371.299,359.4,371.499,360.499),e.bezierVertex(371.599,360.99,371.699,361.499,371.799,361.99),e.vertex(372.499,365.899),e.vertex(377.899,366.199),e.bezierVertexM (378.799,366.299,379.699,366.299,380.599,366.399),e.bezierVertex(385.099,366.699,387.899,369.399,387.799,373.299),e.bezierVertex(387.699,377.099,384.99,379.599,380.799,379.799),e.bezierVertex(369.799,380.199,359.99,383.299,351.899,389.299),e.bezierVertex(338.799,398.799,331.699,411.699,330.699,427.499),e.vertex(330.699,428.299),e.bezierVertex(330.599,429.199,330.599,430.099,330.499,430.799),e.bezierVertex(330,434.7,327.5,437,323.9,437),e.endShape()}function T(e){return e[0].map(((t,n)=>e.map((e=>e[n]))))}function AM (e){return e.map((e=>Array.isArray(e)?A(e):e))}function D(e,t){return floor(random(e,t))}function k(e){let t=0;for(const n of e)t+=n[1];let n=random(t),r=0;for(const t of e)if(r+=t[1],n<r)return t[0];return null}function L(e){for(let t=1;t<e.length;++t){let n=D(0,t),r=e[t];e[t]=e[n],e[n]=r}}function P(e){return null==e||""===e}function O(e){return new Promise((t=>setTimeout(t,e)))}function F(e,t,n){let r=0;for(let i=1;i<=1e3;++i)for(let o=1;o<=1e3;++o)if(e*o%(t*i)==0){let e=1*i/o;abs(e-n)<abs(r-n)&&(r=e)}return r}fM unction N(){let e=60*(new Date).getTimezoneOffset()*1e3;return new Date(Date.now()-e).toISOString().slice(0,-1)}function B(e,t,n){let r;if(push(),textSize(e),textWidth(t)<=n)r=t;else for(let e=0;e<t.length;++e){const i=t.slice(0,e+1)+"...";if(textWidth(i)>n){r=i;break}}return pop(),r}function Y(e){var t=e%10,n=e%100;return 1==t&&11!=n?e+"st":2==t&&12!=n?e+"nd":3==t&&13!=n?e+"rd":e+"th"}class G{constructor(e,t,n){this.n=t,this.m=n,this.mat=[];let r=0;for(let t=0;t<this.n;++t){this.mat.push([]);for(let n=0;n<this.m;+M +n)this.mat[t].push(r<e.length?e[r]:0),r+=1}return this}copy(){return new G(this.mat.flat(),this.n,this.m)}}class H{static __linear=e=>e;static __relu=e=>Math.max(e,0);static __leaky_relu=e=>e>0?e:.2*e;static __sigmoid=e=>1/(1+Math.exp(-e));static __tanh=e=>Math.tanh(e);static __apply_unary_op(e,t){const n=e.copy();for(let e=0;e<n.n;++e)for(let r=0;r<n.m;++r)n.mat[e][r]=t(n.mat[e][r]);return n}static linear=e=>H.__apply_unary_op(e,H.__linear);static relu=e=>H.__apply_unary_op(e,H.__relu);static leaky_relu=e=>H.__apM ply_unary_op(e,H.__leaky_relu);static sigmoid=e=>H.__apply_unary_op(e,H.__sigmoid);static tanh=e=>H.__apply_unary_op(e,H.__tanh);static __add=(e,t)=>e+t;static __mul=(e,t)=>e*t;static __apply_binary_op=(e,t,n)=>{"object"!=typeof t&&(t=new G([t],1,1));const r=e.copy();for(let e=0;e<r.n;++e)for(let i=0;i<r.m;++i)r.mat[e][i]=n(r.mat[e][i],t.mat[e%t.n][i%t.m]);return r};static mul=(e,t)=>H.__apply_binary_op(e,t,H.__mul);static add=(e,t)=>H.__apply_binary_op(e,t,H.__add);static matMul(e,t){const n=new G([],e.n,t.m);for(M let r=0;r<n.n;++r)for(let i=0;i<n.m;++i)for(let o=0;o<e.m;++o)n.mat[r][i]+=e.mat[r][o]*t.mat[o][i];return n}static softmax(e){const t=H.__apply_unary_op(e,(e=>Math.exp(e))),n=t.mat.flat().reduce(((e,t)=>e+t));for(let r=0;r<e.n;++r)for(let i=0;i<e.m;++i)t.mat[r][i]/=n;return t}}class ${constructor(e,t){this.scale=e,this.offset=t}forward(e){return H.add(H.mul(e,this.scale),this.offset)}}class X{constructor(){}forward(e){return e.map((e=>e.flat()))}}class W{constructor(e,t,n,r){this.out_dim=e,this.activation=t,this.w=M n,this.b=r}forward(e){const t=H.add(H.matMul(e,this.w),this.b);return null==this.activation?t:this.activation(t)}}class U{constructor(e,t,n){this.preprocessLayers=e,this.hiddenLayers=t,this.outputLayer=n,this.totalNeurons=this.hiddenLayers.map((e=>e.out_dim)),this.currentOrders=[],this.currentIteration=null}updateNeurons(e,t){if(t!=this.currentIteration){this.currentOrders=[];for(let e=0;e<this.totalNeurons.length;++e){randomSeed(100*(t+1)+e);const n=[];for(let t=0;t<this.totalNeurons[e];++t)n.push(t);L(n),this.curM rentOrders.push(n)}this.currentIteration=t}const n=A(this.totalNeurons),r=n.reduce(((e,t)=>e+t))*(1-e);for(let e=0;e<r;++e){const t=n.map(((e,t)=>(e-1)/this.totalNeurons[t]));n[t.map(((e,t)=>[e,t])).reduce(((e,t)=>t[0]>e[0]?t:e))[1]]-=Math.min(r-e,1)}this.neuronsLife=[];for(let e=0;e<n.length;++e){const t=this.currentOrders[e],r=Array(this.totalNeurons[e]).fill(0);for(let i=0;i<n[e];++i)r[t[i]]=Math.min(n[e]-i,1);this.neuronsLife.push(r)}}getTotalNeurons(){return A(this.totalNeurons)}getNeuronsLife(){return A(this.M neuronsLife)}forward(e){for(const t of this.preprocessLayers)e=t.forward(e);for(const[t,n]of this.hiddenLayers.entries()){e=n.forward(e);const r=new G(this.neuronsLife[t],1,e.m);e=H.mul(e,r)}return e=this.outputLayer.forward(e),H.softmax(e)}}function q(e){switch(e){case"relu":return H.relu;case"sigmoid":return H.sigmoid;case"tanh":return H.tanh;case"leaky_relu":return H.leaky_relu;default:return H.linear}}function j(e,t){const n=[],r=[],i=Z(t);let o=null,a=0,l=[];for(const t of e.config.layers)if("InputLayer"==t.clM ass_name)o=t.config.batch_input_shape.slice(1),l=o;else if("Rescaling"==t.class_name)n.push(new $(t.config.scale,t.config.offset));else if("Flatten"==t.class_name)o=[o.reduce(((e,t)=>e*t))];else if("Dense"==t.class_name){const e=[t.config.units],n=o[0]*e[0],l=e[0],s=i.subarray(a,a+n);a+=n;const h=i.subarray(a,a+l);a+=l;const c=new G(s,o[0],e[0]),u=new G(h,1,e[0]),f=q(t.config.activation);r.push(new W(e[0],f,c,u)),o=e}const s=r.pop();return{model:new U(n,r,s),inputDim:l}}function Z(e){const t=window.atob(e),n=t.lengM th/Float32Array.BYTES_PER_ELEMENT,r=new DataView(new ArrayBuffer(Float32Array.BYTES_PER_ELEMENT)),i=new Float32Array(n);let o=0;for(let e=0;e<n;e++){o=4*e;for(let e=0;e<4;++e)r.setUint8(e,t.charCodeAt(o+e));i[e]=r.getFloat32(0,!0)}return i}class K{constructor(e){this.elt=e,this._events={},this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight}position(){if(0===arguments.length)return{x:this.elt.offsetLeft,y:this.elt.offsetTop};var e="absolute";return"static"!==arguments[2]&&"fixed"!==arguments[2]&&"relatM ive"!==arguments[2]&&"sticky"!==arguments[2]&&"initial"!==arguments[2]&&"inherit"!==arguments[2]||(e=arguments[2]),this.elt.style.position=e,this.elt.style.left=arguments[0]+"px",this.elt.style.top=arguments[1]+"px",this.x=arguments[0],this.y=arguments[1],this}show(){return this.elt.style.display="block",this}hide(){return this.elt.style.display="none",this}size(e,t){if(0===arguments.length)return{width:this.elt.offsetWidth,height:this.elt.offsetHeight};var n=e,r=t;if(n!==te||r!==te){if(n===te?n=t*this.width/this.hM eight:r===te&&(r=e*this.height/this.width),this.elt instanceof HTMLCanvasElement){var i,o={},a=this.elt.getContext("2d");for(i in a)o[i]=a[i];for(i in this.elt.setAttribute("width",n*this._pInst._pixelDensity),this.elt.setAttribute("height",r*this._pInst._pixelDensity),this.elt.style.width=n+"px",this.elt.style.height=r+"px",this._pInst.scale(this._pInst._pixelDensity,this._pInst._pixelDensity),o)this.elt.getContext("2d")[i]=o[i]}else this.elt.style.width=n+"px",this.elt.style.height=r+"px",this.elt.width=n,this.elM t.height=r;this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight,this._pInst&&this._pInst._curElement&&this._pInst._curElement.elt===this.elt&&(this._pInst._setProperty("width",this.elt.offsetWidth),this._pInst._setProperty("height",this.elt.offsetHeight))}return this}style(e,t){if(t instanceof Color&&(t="rgba("+t.levels[0]+","+t.levels[1]+","+t.levels[2]+","+t.levels[3]/255+")"),void 0===t){if(-1===e.indexOf(":"))return window.getComputedStyle(this.elt).getPropertyValue(e);for(var n=e.split(";"),r=0;r<M n.length;r++){var i=n[r].split(":");i[0]&&i[1]&&(this.elt.style[i[0].trim()]=i[1].trim())}}else if(this.elt.style[e]=t,"width"===e||"height"===e||"left"===e||"top"===e){var o=window.getComputedStyle(this.elt).getPropertyValue(e).replace(/[^\d.]/g,"");this[e]=Math.round(parseFloat(o,10))}return this}value(){return arguments.length>0?(this.elt.value=arguments[0],this):"range"===this.elt.type?parseFloat(this.elt.value):this.elt.value}mouseClicked(e){return this._adjustListener("click",e,this),this}isFocused(){return dM ocument.activeElement===this.elt}_adjustListener(e,t,n){return!1===t?this._detachListener(e,n):this._attachListener(e,t,n),this}_attachListener(e,t,n){n._events[e]&&this._detachListener(e,n);var r=t.bind(n);n.elt.addEventListener(e,r,!1),n._events[e]=r}_detachListener(e,t){var n=t._events[e];t.elt.removeEventListener(e,n,!1),t._events[e]=null}}function J(e,t){var n=document.createElement("button");return n.innerHTML=e,t&&(n.value=t),ee(n)}function Q(e){var t=arguments.length>1&&void 0!==arguments[1]&&arguments[1],nM =function(t){var n=!0,r=!1,i=void 0;try{for(var o,a=t.target.files[Symbol.iterator]();!(n=(o=a.next()).done);n=!0){var l=o.value;File._load(l,e)}}catch(e){r=!0,i=e}finally{try{n||null==a.return||a.return()}finally{if(r)throw i}}};if(window.File&&window.FileReader&&window.FileList&&window.Blob){var r=document.createElement("input");return r.setAttribute("type","file"),t&&r.setAttribute("multiple",!0),r.addEventListener("change",n,!1),ee(r)}}function ee(e){return document.body.appendChild(e),new K(e)}createImg=functiM on(){var e,t=document.createElement("img"),n=arguments;return n.length>1&&"string"==typeof n[1]&&(t.alt=n[1]),n.length>2&&"string"==typeof n[2]&&(t.crossOrigin=n[2]),t.src=n[0],e=ee(t,this),t.addEventListener("load",(function(){e.width=t.offsetWidth||t.width,e.height=t.offsetHeight||t.height;var r=n[n.length-1];"function"==typeof r&&r(e)})),e},createInput=function(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:"",t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:"text",n=document.createElemenM t("input");return n.setAttribute("value",e),n.setAttribute("type",t),ee(n,this)};const te="auto";function ne(e){re(e);const t=e._rectMode;e.rectMode(CORNER),e.rect(0,0,e.width,e.height),e.rectMode(t),ie(e)}function re(e){e.push(),e.fill(255,255,255,255),e.blendMode(REMOVE)}function ie(e){e.blendMode(BLEND),e.pop()}File=function(e,t){this.file=e,this._pInst=t;var n=e.type.split("/");this.type=n[0],this.subtype=n[1],this.name=e.name,this.size=e.size,this.data=void 0},File._createLoader=function(e,t){var n=new FileReaM der;return n.onload=function(n){var r=new File(e);if("application/json"===r.file.type)r.data=JSON.parse(n.target.result);else if("text/xml"===r.file.type){var i=(new DOMParser).parseFromString(n.target.result,"text/xml");r.data=new XML(i.documentElement)}else r.data=n.target.result;t(r)},n},File._load=function(e,t){if(/^text\//.test(e.type)||"application/json"===e.type)File._createLoader(e,t).readAsText(e);else if(/^(video|audio)\//.test(e.type)){var n=new File(e);n.data=URL.createObjectURL(e),t(n)}else File._creatM eLoader(e,t).readAsDataURL(e)},XML=function(e){if(e)this.DOM=e;else{var t=document.implementation.createDocument(null,"doc");this.DOM=t.createElement("root")}},document.addEventListener("DOMContentLoaded",(function(){addEventListener("mousemove",(e=>{window.mouseX=e.pageX,window.mouseY=e.pageY}))})),new e("global");const oe="204";let ae,le,se,he,ce,ue,fe,de,xe,ge,pe,me,be,ye,we,ve,ze,Ve,_e,Me,Ee,Se,Re,Ie,Ce,Te,Ae,De,ke,Le,Pe,Oe,Fe,Ne,Be,Ye,Ge,He,$e,Xe,We,Ue,qe,je,Ze,Ke,Je,Qe,et,tt,nt,rt,it,ot,at,lt,st,ht,ct,ut,ft,dM t,xt,gt,pt,mt,bt,yt,wt,vt,zt,Vt,_t,Mt,Et,St,Rt,It,Ct,Tt,At=!1,Dt=!1,kt=!0,Lt=!1,Pt=!1;const Ot=[" ","Growing","Stable","Decaying","Dead","Rebirth"];let Ft,Nt,Bt,Yt,Gt,Ht,$t,Xt,Wt,Ut,qt,jt,Zt,Kt,Jt,Qt,en,tn,nn,rn,on,an,ln,sn,hn=0,cn=0,un=0,fn=!1,dn=!0,xn=!0,gn=null,pn=null,mn=null,bn=!1,yn=!1,wn=null,vn=null,zn=!1;async function setup(){let e=windowWidth,t=windowHeight;createCanvas(e,t),et=createGraphics(e,t),Xe=createGraphics(e,t),$e=createGraphics(e,t),We=createGraphics(e,t),Ue=createGraphics(e,t),qe=createGraphicM s(e,t),Qe=createGraphics(e,t),je=createGraphics(e,t),Ze=createGraphics(e,t),Ke=createGraphics(e,t),Je=createGraphics(e,t),tt=createGraphics(500,500),nt=createGraphics(500,500),rt=createGraphics(500,500),_n(),Mn(),Sn(),await En(),Gn(),Rn(),bn=!0}function _n(){Et=parseInt(oe),randomSeed(Et),noiseSeed(Et)}function Mn(){Wt=Ir(p.training_traits),Cr(Wt)}async function En(){let e;Jt=r(),Qt=o(),[Xt,e]=await Promise.all([s(Jt),h(Qt)]),Ut=new V(Wt.visual,e.layers_config,e.weight_b64),Ut.updateAge(new Date),_n(),Wt.training=eM .training_traits,Ht=e.model_name,$t=e.classes_name}function Sn(){le=min(width,height)/1024,ut=Rr.findIndex((e=>e[0]===Wt.visual.colorPalette)),ft=[["#ffffff","#231f20","#231f20"],["#231f20","#ffffff","#ffffff"],["#104da8","#ffffff","#ffffff"],["#722F1F","#FCE1B2","#FCE1B2"],["#e88120","#f9f2e5","#f9f2e5"],["#f6b941","#2E2E2E","#2E2E2E"],["#45daaa","#012221","#012221"],["#F1F1F1","#328DFE","#328DFE"],["#111822","#D3EB8D","#D3EB8D"],["#713FF9","#D6D5E6","#D6D5E6"],["#FBDA9D","#795106","#795106"],["#8f5b62","#ead0d0",M "#ead0d0"],["#eae4cb","#508cac","#508cac"],["#ffc6cc","#cc313d","#cc313d"],["#60A900","#E0FE00","#E0FE00"],["#507DBE","#D0D1D3","#D0D1D3"],["#305848","#E8F2EE","#E8F2EE"],["#2a2634","#5b6988","#cb78a2","#5b6988"],["#590e29","#fd5e53","#fd5e53","#ffe373"],["#0a141d","#57d4e4","#328195","#2A9ECF","#0ab6a8","#57d4e4"],["#3a2d28","#d5c2ac","#df6338","#3d9895","#d5c2ac"],["#030706","#77c4d9","#77c4d9","#77c4d9","#ffffff","#ffffff","#e72020","#e72020"],["#3a4664","#92f5ff","#f9ff94","#eaa0a2","#55dde0"],["#fbfaff","#f04bM b1","#f04bb1","#fac373","#82cef0","#8b31ce"],["#000000","#ffffff","#ff0002","#f26522","#fdff00","#00ff03","#01fffe","#0000ff","#ff00ff"]];for(let e=0;e<ft.length;++e)for(let t=0;t<ft[e].length;++t)ft[e][t]=cr(ft[e][t]);pt=[],ct=ft[ut][0],st=ft[ut][1]}function Rn(){gn=document.querySelector("#upload"),pn=document.querySelector("#inputUpload"),gn.addEventListener("dblclick",(()=>{if(!Lt&&!yn)if(In(Ie)&&cn==Ve-1)pn.click();else{if(4!=Pe&&5!=Pe&&(In(Ie)||cn!=Ve-1))return;fn=!0,dn=!0,Bt=0,un=0}})),pn.addEventListener("cM lick",(()=>{pn.value=null,gn.style.display="block"})),pn.addEventListener("change",(()=>{const[e]=pn.files;e?(se=null,gn.style.display="none",Tn(URL.createObjectURL(e)),mn=e):gn.style.display="block"}))}function In(e){for(let t=0;t<e.length;++t){let n=0;for(let r=0;r<e[t].length;++r)e[t][r]>0&&++n;if(0==n)return!1}return!0}function Cn(){null!=se&&(un=0,Pt=!0,he=0,ue=0,drewLineAnim=!0,ce=(ae/2+we/2)/le,loadImage(se.elt.src,(e=>{const[t,n,r]=Gt,i=createGraphics(t,n);i.image(e,0,0,t,n),i.loadPixels();const o=i.pixels.M filter(((e,t)=>t%4!=3)),a=Ut.classifyImage(o);Zt=T([a,$t.map((e=>e.toUpperCase()))]).sort(((e,t)=>e[0]>t[0]?-1:1))})))}function Tn(e){se=createImg(e,""),se.hide(),Cn()}function An(){zn||(ce+=(width-ae-we)/tn/le),re(Xe),Xe.rect(ce*le,0,width,height),ie(Xe),un>=ge&&1==kt&&(kt=!1,un-=ge),kt&&(re($e),$e.strokeWeight(2*Fe),Jn(he,ze,ct,ct,$e),ie($e)),un>=ge&&0==kt&&(kt=!0,un-=ge,he+=1,he==en&&(++ue,he=0,ce=(ae/2+we/2)/le,1==ue&&(Pt=!1,Dn(),ye=millis())))}function Dn(){At=!0,pe=!1,me=!1,tryButton=br("Try Again",width/2-22M 5*le,height/2+265*le,290*le,40*le,kn),closeResultButton=br("Close",width/2+75*le,height/2+265*le,150*le,40*le,Ln)}function kn(){At=!1,tryButton.hide(),closeResultButton.hide(),pn.click()}function Ln(){Yt=!0,At=!1,Gn(),tryButton.hide(),closeResultButton.hide(),gn.style.display="block",se=null}function keyTyped(){bn&&!1===yn&&!1===yr()&&("i"!==key&&"I"!==key||(Dt=!Dt),"b"!==key&&"B"!==key||(xn=!xn),"s"!==key&&"S"!==key||!1!==Lt||saveCanvasAtCurrentTime(),"k"!==key&&"K"!==key||!1!==Lt||save4KCanvasAtCurrentTime(),"u"!M ==key&&"U"!==key||!1!==Lt||!1!==At||!1!==fn||!1!==Pt||On())}function On(){Lt=!0,wn=null,vn=null,submitButton=br("Submit",width/2-155*le,height/2+115*le,150*le,40*le,Fn),closeSettingButton=br("Close",width/2+5*le,height/2+115*le,150*le,40*le,Yn),vt=createInput(),vt.position(width/2-252.5*le,height/2-40*le),vt.size(500*le,25*le),vt.style("font-size","15px"),vt.value(Jt||""),zt=createInput(),zt.position(width/2-252.2*le,height/2+35*le),zt.size(500*le,25*le),zt.style("font-size","15px"),zt.value(Qt||"")}function Fn(){VM t=vt.value(),_t=zt.value(),submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide(),Lt=!1,yn=!0,Nn()}async function Nn(){[wn,vn,_]=await Promise.all([c(Vt),u(_t),O(1e3)]),yn=!1,wn&&vn?(n(Vt),i(_t),window.location.reload()):(Lt=!0,submitButton.show(),closeSettingButton.show(),vt.show(),zt.show())}function Bn(){Je.textFont("Trebuchet MS"),Je.noStroke(),pr(Je,600*le,200*le),Je.strokeWeight(1*le),Je.stroke(xt),Je.fill(xt),Je.textSize(50*le),Je.text("update()",width/2,height/2+2.5*le)}function Yn(){wn=null,vn=nM ull,Lt=!1,submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide()}function Gn(){_n(),nn=Date.now(),pe=!1,me=!1,St=Wt.training.structure_gen,Rt=Wt.visual.birthYear,It=Wt.visual.lifeCycle,Ct=Wt.training.epoch_num,Tt=Wt.training.activation_func,Ft=Mr.findIndex((e=>e[0]==Wt.visual.hardwareAcceleration))+1,1==Ft?(Nt=30,fe=40):2==Ft?(Nt=15,fe=20):(Nt=2,fe=10);const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.aM ge,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),ae=100*le,ht=50*le,Oe=Sr.findIndex((e=>e[0]==Wt.visual.nodeShape))+1,dt=Er.findIndex((e=>e[0]==Wt.visual.nodeFill))+1,lt=_r.findIndex((e=>e[0]==Wt.visual.pattern))+1,de=Math.tanh(Math.log10(Xt.avgfeerate)),de=map(de,0,1,.2,.8),inputNodesM =1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else CM e=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=rouM nd(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,at=.7,pt=[],xt=ft[ut][2],gt=ft[ut][ft[ut].length-1];for(let e=3;e<ft[ut].length-1;e++)pt.push(ft[ut][e]);mt=sr(xt,gt,pt,width),bt=[],wt=[],yt=width/(Ve-1);for(let e=0;e<Ve;e++)bt.push(hr(mt,yt*e/width)),wt.push(hr(mt,yt*e/width));wt.unshift(bt[0]),wt.push(bt[bt.length-1]),hn=0,cM n=0,un=0,Yt=!0;const n={xLeft:ae/8,xRight:width-ae/8,yTop:ae/8,yBottom:height-ae/8},r=Ce.map((e=>e.length));jt=new R(bt,r,n,Oe,le)}function Hn(e,t){let n=Ce[e].length;return[e*we+we/2+ae/2,height/2-(n-1)/2*ve+t*ve]}function $n(e,t){le=min(e,t)/1024,ae=100*le,ht=50*le,we=(e-ae)/Ve,ve=(t-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}xe=floor(De.length*de),Le=[],ke=[],ge=floor(map(de,.2,.8,15,2));for(let e=0;e<en;e+M +){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,mt=sr(xt,gt,pt,e),bt=[],wt=[],yt=e/(Ve-1);for(let t=0;t<Ve;t++)bt.push(hr(mt,yt*t/e)),wt.push(hr(mt,yt*t/e));wt.unshift(bt[0]),wt.push(bt[bt.length-1])}function Xn(){const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,window.$state=Pe,window.M $age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<M Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_eM =max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le}function Wn()M {jt.update();const e=4==Pe?0:Kt;jt.draw(Qe,ct,dt,e,le)}function Un(){if(!bn)return ar(),void et.image(je,0,0);if(4==Pe||5==Pe)return Wn(),void et.image(Qe,0,0);un>=Nt&&hn<Ve&&(hn++,un=0);for(let e=0;e<hn;e++)1==dt?it=ot=bt[e]:(it=ct,ot=bt[e]),Kn(e,it,ot,$e);un>=Nt&&cn<Ve-1&&(cn++,un=0);for(let e=0;e<cn;e++)Zn(e)}function qn(){et.background(ct),Ue.background(255),Ue.rectMode(CENTER),ne(Ue),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),Ue.stroke(st),Ue.strokeWeight(8*le),Ue.fill(ct),Qe.background(255),Qe.rectMode(CEM NTER),ne(Qe),Qe.strokeWeight(le),qe.background(255),qe.rectMode(CENTER),ne(qe),qe.textAlign(LEFT),$e.background(255),$e.rectMode(CENTER),ne($e),Xe.background(255),ne(Xe),Xe.strokeWeight(Ne),We.background(255),We.rectMode(CENTER),ne(We),We.fill(st),We.stroke(st),We.strokeWeight(.1*le),er(lt),We.noStroke(),xn&&(We.rect(ae/16,height/2,ae/8,height),We.rect(width-ae/16,height/2,ae/8,height),We.rect(width/2,ae/16,width,ae/8),We.rect(width/2,height-ae/16,width,ae/8)),Ze.background(255),Ze.rectMode(CENTER),ne(Ze),Ze.textAlM ign(CENTER,CENTER),Ze.textStyle(BOLD),Ze.stroke(st),Ze.strokeWeight(8*le),Ze.fill(ct),je.background(255),je.rectMode(CENTER),ne(je),je.textAlign(CENTER,CENTER),je.textStyle(BOLD),Ke.background(255),Ke.rectMode(CENTER),ne(Ke),Ke.textAlign(CENTER,CENTER),Ke.textStyle(BOLD),Ke.stroke(st),Ke.strokeWeight(8*le),Ke.fill(ct),Je.background(255),Je.rectMode(CENTER),ne(Je),Je.textAlign(CENTER,CENTER),Je.textStyle(BOLD),Je.stroke(st),Je.strokeWeight(8*le),Je.fill(ct),Un(),et.image(We,0,0),Pt&&An(),et.image(Xe,0,0),et.image($eM ,0,0),At&&(tr(),et.image(Ue,0,0)),fn&&(lr(),et.image(Ze,0,0)),Lt&&(or(),et.image(Ke,0,0)),Dt&&(ir(),et.image(qe,0,0)),yn&&(Bn(),et.image(Je,0,0))}function draw(){const e=Date.now();bn&&(Ut.updateAge(new Date(e)),Xn()),qn(),image(et,0,0),zn||un++}function Zn(e){let t,n=Ce[e].length,r=Ce[e+1].length;for(let i=0;i<n;i++){const[n,o]=Hn(e,i);for(let a=0;a<r;a++){const[r,l]=Hn(e+1,a);t=map(min(Ce[e][i],Ce[e+1][a]),0,1,0,.5),ur(n,o,r,l,bt[e],bt[e+1],Xe,t)}}}function Kn(e,t,n,r){let i,o,a,l=Ce[e].length;for(let s=0;s<l;s++M ){const[l,h]=Hn(e,s);i=Ce[e][s],a=map(Be,1/30,1,3,10),o=map(Ce[e][s],0,1,2*a,0)*le,o<1.5*le&&(o=0),Qn(l,h,ze,Oe,t,n,o,i,r)}}function Jn(e,t,n,r,i){for(let o=0;o<Le[e].length;o++)Qn(Le[e][o][0],Le[e][o][1],t,Oe,n,r,0,1,i)}function Qn(e,t,n,r,i,o,a,l,s){s.stroke(dr(o,map(l,0,1,.25,1))),s.fill(dr(i,map(l,0,1,.15,1))),s.strokeWeight(Fe),fr([a],s),3==dt&&s.fill(dr(i,0)),1==r?s.ellipse(e,t,n):2==r?s.rect(e,t,7*n/8,7*n/8):3==r&&(s.beginShape(),s.vertex(e-4*n/7,t),s.vertex(e,t-4*n/7),s.vertex(e+4*n/7,t),s.vertex(e,t+4*n/7)M ,s.endShape(CLOSE))}function er(e){if(1==e);else if(2==e){We.strokeWeight(1*le);for(let e=ht/4;e<width+ht/4;e+=ht)for(let t=ht/4;t<height+ht/4;t+=ht)We.point(e,t)}else if(3==e){ht=25*le;for(let e=ht/2;e<height+ht/2;e+=ht)We.line(0,e,width,e);for(let e=ht/2;e<width+ht/2;e+=ht)We.line(e,0,e,height)}}function tr(){Ue.textFont("Trebuchet MS"),Ue.textAlign(LEFT,CENTER),Ue.noStroke(),pr(Ue,800*le,500*le),Ue.noStroke(),Ue.fill(dr(st,.75)),Ue.rect(width/2,height/2-100*le,800*le,300*le,25*le,25*le,0,0),Ue.fill(st),Ue.rect(wM idth/2-250*le,height/2-100*le,225*le,225*le),Ue.image(se.elt,width/2-357.5*le,height/2-207.5*le,215*le,215*le);let e=100*Zt[0][0];Ue.fill(ct),Ue.textSize(25*le),Ue.textStyle(NORMAL),1==me&&(e>=0&&e<20?Ue.text("I have a feeling this image belongs to",width/2-100*le,height/2-170*le):e>=20&&e<40?Ue.text("I have a hunch this image belongs to",width/2-100*le,height/2-170*le):e>=40&&e<60?Ue.text("I think this image belongs to",width/2-100*le,height/2-170*le):e>=60&&e<80?Ue.text("I'm almost certain this image belongs to",M width/2-100*le,height/2-170*le):Ue.text("I'm positive this image belongs to",width/2-100*le,height/2-170*le));let t=e.toFixed(2);"100.00"==t&&(t="100"),1==me&&Ue.text("I'm "+t+"% confident that I'm right!",width/2-100*le,height/2-25*le),example=Zt.map((e=>e[1])),be=Ue.textWidth('"FIDENZAAAA"'),defaultPhrase=Ue.textWidth('"PERPENDICULAR INHABITATION"'),Ue.textStyle(BOLD);const n=me?example[0]:random(example);if(1===n.split(" ").length){let e=75*be/Ue.textWidth('"'+n+'"');e>75&&(e=75),Ue.textSize(e*le),Ue.text('"'+n+M '"',width/2-100*le,height/2-90*le)}else nr(width/2-100*le,height/2-90*le,460*le,110*le,n,Ue);if(millis()-ye>1500&&(me=!0),C(tt,nt,st,ct,Pe,Mt),Ue.image(nt,width/2-370*le,height/2+70*le,80*le,80*le),3==Pe){let e;e=map(Mt,50,60,.25,1.3),I(rt,e),Ue.image(rt,width/2-370*le,height/2+70*le,80*le,80*le)}let r,i;Ue.image(tt,width/2-370*le,height/2+70*le,80*le,80*le),Ue.fill(xt),Ue.textSize(40*le),Ue.text("INTELLIGENCE INFO",width/2-275*le,height/2+115*le),Ue.textSize(18*le),Ue.textStyle(NORMAL),Ue.circle(width/2-360*le,heiM ght/2+180*le,7.5*le),1==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s growing and getting smarter by the day.`:2==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s stable and it has reached peak performance.`:3==Pe&&(r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s decaying and losing its luster.`),i=2==Pe?"The Perceptron remains stable for some time before entering the decay phase.":`Wait until ${new Date(an).toLocaleString("en-US")} for your Perceptron to reach its peak performanceM .`,Ue.text(r,width/2-350*le,height/2+180*le),Ue.circle(width/2-360*le,height/2+210*le,7.5*le),Ue.text(i,width/2-350*le,height/2+210*le),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),gr(Ue,width/2-225*le,width/2+65*le,height/2+265*le,height/2+305*le,"SELECT ANOTHER IMAGE"),gr(Ue,width/2+75*le,width/2+225*le,height/2+265*le,height/2+305*le,"CLOSE")}function nr(e,t,n,r,i,o){let a=i.split(" "),l=75*be/o.textWidth('"'+i+'"'),s=0,h=[],c=[],u=[],f="",d="";if(l>=50)l>75&&(l=75),o.textSize(l*le),o.text('"'+i+'"',e,t);else M if(l<50){if(l=50*defaultPhrase/o.textWidth('"'+i+'"'),l>30){if(l>50&&(l=50),[f,d]=rr(l,n,s,h,c,a,f,d,Ue),0==c.length)return o.textSize(l*le),void o.text('"'+i+'"',e,t);for(s=0,h=[],c=[];o.textWidth(d)>n/le;)l=l*n/le/o.textWidth(d),f="",d="",[f,d]=rr(l,n,s,h,c,a,f,d,Ue)}else{l=30,o.textSize(l);for(let e=0;e<a.length;e++)s+=o.textWidth(" "+a[e]),s<=n/le?h.push(a[e]):s>n/le&&s<=n/le*2?c.push(a[e]):u.push(a[e]);for(let e=1;e<h.length;e++)f=f+" "+h[e];if(f='"'+h[0]+f,0==u.length){for(let e=0;e<c.length-1;e++)d=d+c[e]+" M ";d=d+c[c.length-1]+'"'}else if(1==c.length)d="... "+u[u.length-1]+'"';else{for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+"... "+u[u.length-1]+'"'}}o.textSize(l*le);let r=1.25*(o.textDescent()+o.textAscent());o.text(f,e,t-r/2),o.text(d,e,t+r/2)}}function rr(e,t,n,r,i,o,a,l,s){s.textSize(e);for(let e=0;e<o.length;e++)(n+=s.textWidth(" "+o[e]))<=t/le?r.push(o[e]):i.push(o[e]);for(let e=1;e<r.length;e++)a=a+" "+r[e];if(a='"'+r[0]+a,0==i.length&&(a+='"',l=""),1==i.length)l=i[i.length-1]+'"';else{for(let e=0;e<i.length-M 1;e++)l=l+i[e]+" ";l=l+i[i.length-1]+'"'}return[a,l]}function ir(){const e=45*le;qe.textFont("Tahoma"),qe.stroke(st),qe.strokeWeight(2*le),qe.fill(ct),qe.rect(width/2,e/2+height-87.5*le,600*le,90*le),qe.fill(st),qe.rect(width/2-150*le,e+height-170*le,300*le,30*le),qe.fill(ct),qe.rect(width/2+150*le,e+height-170*le,300*le,30*le),qe.noStroke(),qe.fill(ct),qe.textSize(15*le),qe.textStyle(BOLD),qe.text("PERCEPTRON INFORMATION",width/2-285*le,e+height-165*le),qe.fill(xt),qe.text("ARTWORK NAME:",width/2+10*le,e+height-16M 5*le),qe.textAlign(RIGHT),qe.textStyle(ITALIC),qe.text("Perceptron #"+Et,width/2+285*le,e+height-165*le);const[t,n]=It.split(" ");let r;"60 Years"===It?r="1 Year":"60 Months"===It?r="1 Month":"60 Weeks"===It?r="1 Week":"60 Days"===It?r="1 Day":"12 Hours"===It&&(r="12 Minutes"),data=[["AI MODEL NAME:",B(12*le,Ht,140*le)],["SCALE:","1:"+Te],["NUMBER OF CLASSES:",$t.length],["BIRTH YEAR:",Rt],["NUMBER OF REBIRTHS:",sn.toString()],["AGE:",`${Math.ceil(Mt)} Perceptron Years`],["ONE PERCEPTRON YEAR:",`${r}`],["STATE:",OtM [Pe]],["ACTIVE NEURONS:",`${round(ln*rn)} / ${ln}`],["NEXT STATE TIME:",vr(new Date(on))]],qe.fill(xt);const i=data.length/2;for(let t=0;t<data.length;++t){const n=t<i,r=n?width/2-285*le:width/2+10*le,o=n?width/2-10*le:width/2+285*le,a=e+height-(135-t%i*15)*le;qe.textStyle(BOLD),qe.textAlign(LEFT),qe.textSize(12*le),qe.text(data[t][0],r,a),qe.textStyle(ITALIC),qe.textAlign(RIGHT),qe.textSize(12*le),qe.text(data[t][1],o,a)}}function or(){Ke.textFont("Trebuchet MS"),Ke.noStroke(),pr(Ke,600*le,200*le),gr(Ke,width/2-15M 5*le,width/2-5*le,height/2+115*le,height/2+155*le,"UPDATE"),gr(Ke,width/2+5*le,width/2+155*le,height/2+115*le,height/2+155*le,"CLOSE"),Ke.textAlign(LEFT),Ke.fill(xt),Ke.text("UPDATE BITCOIN FULL NODE ADDRESS",width/2-252.5*le,height/2-55*le),Ke.text("UPDATE MODEL ADDRESS",width/2-252.5*le,height/2+20*le),Ke.textAlign(RIGHT),Ke.textStyle(ITALIC),Ke.textSize(15*le),0==wn&&Ke.text("(*) Invalid Address",width/2+252.5*le,height/2-53*le),0==vn&&Ke.text("(*) Invalid Model",width/2+252.5*le,height/2+23*le)}function ar(){jeM .textFont("Trebuchet MS"),je.fill(st),je.textSize(50*le),je.stroke(st),je.strokeWeight(1*le),je.text("main()",width/2,height/2)}function lr(){un>=20&&1==dn&&(dn=!1,un=0),dn&&(Ze.textFont("Trebuchet MS"),Ze.stroke(st),Ze.fill(ct),Ze.rect(width/2,height/2,600*le,150*le,25*le),Ze.fill(xt),Ze.textSize(75*le),Ze.noStroke(),1==Pe?Ze.text("GROWING",width/2,height/2+5*le):3==Pe?Ze.text("AGING",width/2,height/2+5*le):4==Pe?Ze.text("DEAD",width/2,height/2+5*le):5==Pe&&Ze.text("BIRTH",width/2,height/2+5*le)),un>=20&&0==dn&&(dM n=!0,un=0,Bt++,3==Bt&&(fn=!1))}function sr(e,t,n,r){let i=[],o=r/(n.length+1),a=color(e),l=color(t);i.push(a);for(let e=0;e<n.length;e++){let t=color(n[e]);for(let e=1;e<=o;e++){let n=lerpColor(a,t,e/o);i.push(n)}a=t}for(let e=1;e<o;e++){let t=lerpColor(a,l,e/o);i.push(t)}if(i.push(l),i.length>r)i.splice(r);else if(i.length<r){let e=i[i.length-1];for(;i.length<r;)i.push(e)}return i}function hr(e,t){let n=e.length,r=Math.floor(t*n);return r>=n&&(r=n-1),e[r]}function cr(e){e=e.replace("#","");var t=parseInt(e,16);retM urn color(t>>16&255,t>>8&255,255&t)}function ur(e,t,n,r,i,o,a,l){var s=a.drawingContext.createLinearGradient(e,t,n,r);s.addColorStop(0,i),s.addColorStop(1,o),a.drawingContext.strokeStyle=s,a.drawingContext.globalAlpha=l,a.line(e,t,n,r),a.drawingContext.globalAlpha=1}function fr(e,t){t.drawingContext.setLineDash(e)}function dr(e,t){let n=color(e),r=red(n),i=green(n),o=blue(n);return color(r,i,o,255*t)}function xr(e,t,n,r){return mouseX>e&&mouseX<t&&mouseY>n&&mouseY<r}function gr(e,t,n,r,i,o){e.strokeWeight(1*le),e.sM troke(st);const[a,l]=xr(t,n,r,i)?[xt,ct]:[ct,xt];e.fill(a),e.push(),e.rectMode(CORNERS),e.rect(t,r,n,i,5*le),e.pop(),e.noStroke(),e.textSize(20*le),e.fill(l),e.text(o,(t+n)/2,(46*r+54*i)/100)}function pr(e,t,n){e.fill(0,0,0,75),e.rect(width/2,height/2,width,height),e.stroke(st),e.fill(ct),e.rect(width/2,height/2,t,n,25*le)}function mr(e,t){resizeCanvas(e,t,!0),Xe.resizeCanvas(e,t,!0),$e.resizeCanvas(e,t,!0),We.resizeCanvas(e,t,!0),Ue.resizeCanvas(e,t,!0),qe.resizeCanvas(e,t,!0),Qe.resizeCanvas(e,t,!0),je.resizeCanvM as(e,t,!0),Ze.resizeCanvas(e,t,!0),Ke.resizeCanvas(e,t,!0),Je.resizeCanvas(e,t,!0),et.resizeCanvas(e,t,!0)}function br(e,t,n,r,i,o){const a=J(e);return a.position(t,n),a.size(r,i),a.style("opacity","0"),a.mouseClicked(o),a}function yr(){return null!=vt&&vt?.isFocused()||null!=zt&&zt?.isFocused()}function wr(e,t,n,r){let i;if(e<=3){i=`Hey ${String.fromCodePoint(128075)}, I'm ${n}, ${t} years old. I can detect ${r.length} NFT collections: `;let e=0;for(let t=0;t<r.length;++t){const n=r[t];if(e+n.length>500){i+=", etcM ";break}t==r.length-1?i+=", and ":t>0&&(i+=", "),i+=n,e+=n.length}i+=". ",t<=5?i+="However, I am only a baby, so my recognition ability is not accurate. I'm in the state of Growing both looks and intelligence.":t<=13?i+="I am now a child. My recognition ability is becoming better, but still not very accurate. I'm in the state of Growing both looks and intelligence.":t<=25?i+="I have grown up to be a teen. My recognition ability almost reaches the peak, but I will still mess up sometimes. I'm in the state of GrowingM both looks and intelligence.":t<=50?i+="I finally reach adulthood. My recognition is fully functional now. I'm in the Stable state, where I am the most intelligent with all neurons activated.":t<=60&&(i+="I am now an old Perceptron, so my recognition ability is no longer the best. I'm in the Decaying state, meaning that my neurons are dying, and my intelligence is decreasing over time.")}else 4==e?i=`${n} is Dead. However, this is not the end to its story...`:5==e&&(i=`${n} is now in the Rebirth state, and is prepM aring to start a new life.`);return i}function vr(e){const t=e.getDate(),n=e.toLocaleString("en-US",{month:"long"}),r=e.getFullYear();let i=e.getHours().toString();1==i.length&&(i="0"+i);let o=e.getMinutes().toString();return 1==o.length&&(o="0"+o),`${Y(t)} ${n} ${r} | ${i}:${o}`}saveCanvasAtCurrentTime=()=>{save(N())},save4KCanvasAtCurrentTime=()=>{const e=width,t=height,n=min(4096/min(e,t),1e4/max(e,t)),r=e*n,i=t*n;mr(r,i),zn=!0,$n(r,i),qn();let o="4K_"+N()+".png";saveCanvas(et,o),mr(e,t),$n(e,t),zn=!1};const zr=M [["60 Years",3,365],["60 Months",40,30],["60 Weeks",37,7],["60 Days",20,1]],Vr=[["1943",1],["1951",1.5],["1957",2],["1969",2.5],["1970",3],["1980",3.5],["1982",4],["1986",4.5],["1988",5],["1997",5.5],["1998",6],["2002",6.5],["2009",7],["2012",7.5],["2014",8],["2015",8.5],["2016",9],["2023",15]],_r=[["Plain",20],["Dotted",40],["Squared",40]],Mr=[["Basic",30],["Standard",60],["Advanced",10]],Er=[["MNIST",70],["CIFAR",25],["IMAGENET",5]],Sr=[["Theano",60],["Torch",30],["TensorFlow",10]],Rr=[["Whitepaper",2],["BlackboaM rd",2],["Blueprint",2],["Nak",74/14],["Jims",74/14],["Level 10",74/14],["Flips",74/14],["Level 14",74/14],["III",74/14],["XMB",74/14],["Info",74/14],["Adventure",74/14],["Marigold",74/14],["Phoenix",74/14],["Love",74/14],["Cachet",74/14],["Human",74/14],["Twilight",3],["Sunset",3],["Aurora",3],["Liminal Space",3],["D Vu",3],["Lucid Dream",3],["Parallel",1],["Multiverse",1]];function Ir(e){for(let e=0;e<100;++e)random(1);return{visual:{pattern:k(_r),hardwareAcceleration:k(Mr),nodeFill:k(Er),nodeShape:k(Sr),coloM rPalette:k(Rr),lifeCycle:k(zr),birthYear:k(Vr)},training:e}}function Cr(e){window.$generativeTraits={"Network Architecture":e.training.structure_gen,"Hidden Layers":e.training.n_layers,"Max Neurons Per Hidden Layer":e.training.max_nodes,"Activation Function":e.training.activation_func,"Training Epochs":e.training.epoch_num,Dataset:e.visual.nodeFill,"Deep Learning Framework":e.visual.nodeShape,"Hardware Acceleration":e.visual.hardwareAcceleration,"Paper Pattern":e.visual.pattern,"Life Cycle":e.visual.lifeCycle,"BirtM h Year":e.visual.birthYear,"Color Palette":e.visual.colorPalette}} <script defer src="https://static.cloudflareinsights.com/beacon.min.js/v2b4487d741ca48dcbadcaf954e159fc61680799950996" integrity="sha512-D/jdE0CypeVxFadTejKGTzmwyV10c1pxZk/AqjJuZbaJwGMyNHY3q/mTPWqMUnFACfCTunhZUVcd4cV78dK1pQ==" data-cf-beacon='{"rayId":"7b48a73d7a41a217","version":"2023.3.0","b":1,"token":"6c07c178c94442f695e7a0a2aaee641a","si":100}' crossorigin="anonymous"></script> {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "pauldrons"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "silver"}, {"trait_type": "Mane", "value": "fire"}, {"trait_type": "Claws", "value": "fire"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "shield"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "wizard staff"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "fire"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "cape"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "broadsword"}]} text/plain;charset=utf-8 2{"p":"brc-20","op":"mint","tick":"<10K","amt":"1"}h! {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "bag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "pauldrons"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "orc"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "bag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "poisoned dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "none"}]} text/plain;charset=utf-8 {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "orc"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "badger"}, {"trait_type": "Artifacts", "value": "arrow wounds"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "blue fire"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "noggles"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "whale"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "golden"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "moon"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "golden armor"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "none"}]} text/plain;charset=utf-8 {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "badger"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "shield"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "robot"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "bloody"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "skull"}, {"trait_type": "Artifacts", "value": "dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "dagger"}]} text/html;charset=utf-8 <meta charset="utf-8" /> position: relative; width: var(--width); height: var(--height); border: 1px solid blue; position: relative; <div id="upload"> <input id="inputUpload" type="file"> function e(e){"use strict";return new function e(t){let n="global"==t?window:this;n.canvas=document.createElement("canvas");let r=n.canvas.getContext("2d");n.width=100,n.height=100,n.canvas.width=n.width,n.canvas.height=n.height,"offscreen"!=t&&(document.body?document.body.appendChild(n.canvas):window.addEventListener("load",(function(){document.body.appendChild(n.canvas)}))),g(),n.MAGIC=161533525,n.RGB=0,n.HSV=1,n.HM SB=1,n.CHORD=0,n.PIE=1,n.OPEN=2,n.RADIUS=1,n.CORNER=2,n.CORNERS=3,n.ROUND="round",n.SQUARE="butt",n.PROJECT="square",n.MITER="miter",n.BEVEL="bevel",n.CLOSE=1,n.BLEND="source-over",n.REMOVE="destination-out",n.ADD="lighter",n.DARKEST="darken",n.LIGHTEST="lighten",n.DIFFERENCE="difference",n.SUBTRACT="subtract",n.EXCLUSION="exclusion",n.MULTIPLY="multiply",n.SCREEN="screen",n.REPLACE="copy",n.OVERLAY="overlay",n.HARD_LIGHT="hard-light",n.SOFT_LIGHT="soft-light",n.DODGE="color-dodge",n.BURN="color-burn",n.NORMAL="norM mal",n.ITALIC="italic",n.BOLD="bold",n.BOLDITALIC="italic bold",n.CENTER="center",n.LEFT="left",n.RIGHT="right",n.TOP="top",n.BOTTOM="bottom",n.BASELINE="alphabetic",n.LANDSCAPE="landscape",n.PORTRAIT="portrait",n.ALT=18,n.BACKSPACE=8,n.CONTROL=17,n.DELETE=46,n.DOWN_ARROW=40,n.ENTER=13,n.ESCAPE=27,n.LEFT_ARROW=37,n.OPTION=18,n.RETURN=13,n.RIGHT_ARROW=39,n.SHIFT=16,n.TAB=9,n.UP_ARROW=38,n.HALF_PI=Math.PI/2,n.PI=Math.PI,n.QUARTER_PI=Math.PI/4,n.TAU=2*Math.PI,n.TWO_PI=2*Math.PI,n.THRESHOLD=1,n.GRAY=2,n.OPAQUE=3,n.INVEM RT=4,n.POSTERIZE=5,n.DILATE=6,n.ERODE=7,n.BLUR=8,n.ARROW="default",n.CROSS="crosshair",n.HAND="pointer",n.MOVE="move",n.TEXT="text",n.VIDEO={video:!0,audio:!1},n.AUDIO={video:!1,audio:!0},n.SHR3=1,n.LCG=2,n.HARDWARE_FILTERS=!0,n.hint=function(e,t){n[e]=t},n.frameCount=0,n.mouseX=0,n.mouseY=0,n.pmouseX=0,n.pmouseY=0,n.mouseButton=null,n.keyIsPressed=!1,n.mouseIsPressed=!1,n.key=null,n.keyCode=null,n.pixels=null,n.accelerationX=0,n.accelerationY=0,n.accelerationZ=0,n.rotationX=0,n.rotationY=0,n.rotationZ=0,n.relRotatM ionX=0,n.relRotationY=0,n.relRotationZ=0,n.pAccelerationX=0,n.pAccelerationY=0,n.pAccelerationZ=0,n.pRotationX=0,n.pRotationY=0,n.pRotationZ=0,n.pRelRotationX=0,n.pRelRotationY=0,n.pRelRotationZ=0,n.touches=[],n._styleCache=[{colorMode:n.RGB,noStroke:!1,noFill:!1,ellipseMode:n.CENTER,rectMode:n.CORNER,curveDetail:20,curveAlpha:0,textFont:"sans-serif",textSize:12,textLeading:12,textStyle:"normal"}],n._style=n._styleCache[n._styleCache.length-1],n._noLoop=!1,n._pixelDensity=1,n._frameRate=null,n._tint=null;let i=nullM ,o=!0,a=[],l=null,s=0,h={},c=0,u=null,f=null,d=null;Object.defineProperty(n,"deviceOrientation",{get:function(){return 90==Math.abs(window.orientation)?n.LANDSCAPE:n.PORTRAIT}}),Object.defineProperty(n,"windowWidth",{get:function(){return window.innerWidth}}),Object.defineProperty(n,"windowHeight",{get:function(){return window.innerHeight}}),Object.defineProperty(n,"drawingContext",{get:function(){return r}}),n.createCanvas=function(e,t){return n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t,g(),n.canvas},nM .resizeCanvas=function(e,t){n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t},n.createGraphics=n.createImage=function(t,n){let r=new e("offscreen");return r.createCanvas(t,n),r.noLoop(),r},n.pixelDensity=function(e){return null==e||(n._pixelDensity=e,n.canvas.width=Math.ceil(n.width*e),n.canvas.height=Math.ceil(n.height*e),n.canvas.style.width=n.width+"px",n.canvas.style.height=n.height+"px",r.scale(n._pixelDensity,n._pixelDensity),g()),n._pixelDensity},n.map=function(e,t,n,r,i,o){let a=r+1*(e-t)/(n-t)*(i-r)M ;return o?r<i?Math.min(Math.max(a,r),i):Math.min(Math.max(a,i),r):a},n.lerp=function(e,t,n){return e*(1-n)+t*n},n.constrain=function(e,t,n){return Math.min(Math.max(e,t),n)},n.dist=function(){return 4==arguments.length?Math.hypot(arguments[0]-arguments[2],arguments[1]-arguments[3]):Math.hypot(arguments[0]-arguments[3],arguments[1]-arguments[4],arguments[2]-arguments[5])},n.norm=function(e,t,r){return n.map(e,t,r,0,1)},n.sq=function(e){return e*e},n.fract=function(e){return e-Math.floor(e)},n.degrees=function(e){retM urn 180*e/Math.PI},n.radians=function(e){return e*Math.PI/180},n.abs=Math.abs,n.ceil=Math.ceil,n.exp=Math.exp,n.floor=Math.floor,n.log=Math.log,n.mag=Math.hypot,n.max=Math.max,n.min=Math.min,n.round=Math.round,n.sqrt=Math.sqrt,n.sin=Math.sin,n.cos=Math.cos,n.tan=Math.tan,n.asin=Math.asin,n.acos=Math.acos,n.atan=Math.atan,n.atan2=Math.atan2,n.Vector=function(e,t,r){let i=this;i.x=e||0,i.y=t||0,i.z=r||0;let o=null,a=null;function l(e,t,n){return null!=e.x?e:null!=t?{x:e,y:t,z:n||0}:{x:e,y:e,z:e}}function s(){null==a&M &(a=i.x*i.x+i.y*i.y+i.z*i.z,o=Math.sqrt(a))}function h(){a=null,o=null}i.set=function(e,t,n){i.x=e||0,i.y=t||0,i.z=n||0},i.copy=function(){return new n.Vector(i.x,i.y,i.z)},i.add=function(){let e=l.apply(null,arguments);return i.x+=e.x,i.y+=e.y,i.z+=e.z,h(),i},i.rem=function(){let e=l.apply(null,arguments);return i.x%=e.x,i.y%=e.y,i.z%=e.z,h(),i},i.sub=function(){let e=l.apply(null,arguments);return i.x-=e.x,i.y-=e.y,i.z-=e.z,h(),i},i.mult=function(){let e=l.apply(null,arguments);return i.x*=e.x,i.y*=e.y,i.z*=e.z,hM (),i},i.div=function(){let e=l.apply(null,arguments);return i.x/=e.x,i.y/=e.y,i.z/=e.z,h(),i},i.mag=function(){return s(),o},i.magSq=function(){return s(),a},i.dot=function(){let e=l.apply(null,arguments);return i.x*e.x+i.y*e.y+i.z*e.z},i.dist=function(){let e=l.apply(null,arguments),t=i.x-e.x,n=i.y-e.y,r=i.z-e.z;return Math.sqrt(t*t+n*n+r*r)},i.cross=function(){let e=l.apply(null,arguments),t=i.y*e.z-i.z*e.y,n=i.z*e.x-i.x*e.z,r=i.x*e.y-i.y*e.x;return i.x=t,i.y=n,i.z=r,h(),i},i.normalize=function(){s();let e=o;retuM rn i.x/=e,i.y/=e,i.z/=e,o=1,a=1,i},i.limit=function(e){s();if(o>e){let t=e/o;i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e}return i},i.setMag=function(e){s();let t=e/o;return i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e,i},i.heading=function(){return Math.atan2(i.y,i.x)},i.rotate=function(e){let t=Math.cos(e),n=Math.sin(e),r=i.x*t-i.y*n,o=i.x*n+i.y*t;return i.x=r,i.y=o,i},i.angleBetween=function(){let e=l.apply(null,arguments);const t=i.dot(e)/(i.mag()*e.mag());let n;return n=Math.acos(Math.min(1,Math.max(-1,t))),n*Math.sign(i.cross(e).z||1)},M i.lerp=function(e,t){return i.x=i.x*(1-t)+e.x*t,i.y=i.y*(1-t)+e.y*t,i.z=i.z*(1-t)+e.z*t,h(),i},i.reflect=function(e){return e.normalize(),i.sub(e.mult(2*i.dot(e)))},i.array=function(){return[i.x,i.y,i.z]},i.equals=function(e,t){return null==t&&null==(t=Number.EPSILON)&&(t=0),Math.abs(e.x-i.x)<t&&Math.abs(e.y-i.y)<t&&Math.abs(e.z-i.z)<t},i.fromAngle=function(e,t){return null==t&&(t=1),o=t,a=t*t,i.x=t*Math.cos(e),i.y=t*Math.sin(e),i.z=0,i},i.fromAngles=function(e,t,n){null==n&&(n=1),o=n,a=n*n;const r=Math.cos(t),l=MaM th.sin(t),s=Math.cos(e),h=Math.sin(e);return i.x=n*h*l,i.y=-n*s,i.z=n*h*r,i},i.random2D=function(){return o=1,a=1,i.fromAngle(Math.random()*Math.PI*2)},i.random3D=function(){return o=1,a=1,i.fromAngles(Math.random()*Math.PI*2,Math.random()*Math.PI*2)},i.toString=function(){return`[${i.x}, ${i.y}, ${i.z}]`}},n.Vector.add=function(e,t){return new n.Vector(e.x+t.x,e.y+t.y,e.z+t.z)},n.Vector.rem=function(e,t){return new n.Vector(e.x%t.x,e.y%t.y,e.z%t.z)},n.Vector.sub=function(e,t){return new n.Vector(e.x-t.x,e.y-t.y,e.M z-t.z)},n.Vector.mult=function(e,t){return null==t.x?new n.Vector(e.x*t,e.y*t,e.z*t):new n.Vector(e.x*t.x,e.y*t.y,e.z*t.z)},n.Vector.div=function(e,t){return null==t.x?new n.Vector(e.x/t,e.y/t,e.z/t):new n.Vector(e.x/t.x,e.y/t.y,e.z/t.z)},n.Vector.dist=function(e,t){return Math.hypot(e.x-t.x,e.y-t.y,e.z-t.z)},n.Vector.cross=function(e,t){return new n.Vector(e.y*t.z-e.z*t.y,e.z*t.x-e.x*t.z,e.x*t.y-e.y*t.x)},n.Vector.lerp=function(e,t,r){return new n.Vector(e.x*(1-r)+t.x*r,e.y=e.y*(1-r)+t.y*r,e.z=e.z*(1-r)+t.z*r)},n.M Vector.equals=function(e,t,n){return e.equals(t,n)};for(let e of["fromAngle","fromAngles","random2D","random3D"])n.Vector[e]=function(t,r,i){return(new n.Vector)[e](t,r,i)};function x(e,t,n){let r,i,o,a,l,s,h,c,u;if(0==t)return[255*(r=n),255*(i=n),255*(o=n)];switch((a=e)>360&&(a=0),h=n*(1-t),c=n*(1-t*(s=(a/=60)-(l=~~a))),u=n*(1-t*(1-s)),l){case 0:r=n,i=u,o=h;break;case 1:r=c,i=n,o=h;break;case 2:r=h,i=n,o=u;break;case 3:r=h,i=c,o=n;break;case 4:r=u,i=h,o=n;break;default:r=n,i=h,o=c}return[255*r,255*i,255*o]}functioM n g(){r.fillStyle="white",r.strokeStyle="black",r.lineCap="round",r.lineJoin="miter"}function p(e){if(0<=e&&e<2*Math.PI)return e;for(;e<0;)e+=2*Math.PI;for(;e>=Math.PI;)e-=2*Math.PI;return e}function m(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;let c=p(a),u=p(l);r.beginPath();for(let a=0;a<h+1;a++){let l=a/h,s=n.lerp(c,u,l),f=Math.cos(s)*i/2,d=Math.sin(s)*o/2;r[a?"lineTo":"moveTo"](e+f,t+d)}s==n.CHORD?r.closePath():s==n.PIE&&(r.lineTo(e,t),r.closePath()),n._style.noFill||r.fill(),n._style.noStrokM e||r.stroke()}function b(e,t,i,o){n._style.noFill&&n._style.noStroke||(r.beginPath(),r.ellipse(e,t,i/2,o/2,0,0,2*Math.PI),n._style.noFill||r.fill(),n._style.noStroke||r.stroke())}function y(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;if(null==a)return function(e,t,i,o){n._style.noFill||r.fillRect(e,t,i,o),n._style.noStroke||r.strokeRect(e,t,i,o)}(e,t,i,o);if(null==l)return y(e,t,i,o,a,a,a,a);const c=Math.min(Math.abs(o),Math.abs(i))/2;a=Math.min(c,a),l=Math.min(c,l),h=Math.min(c,h),s=Math.min(c,s)M ,r.beginPath(),r.moveTo(e+a,t),r.arcTo(e+i,t,e+i,t+o,l),r.arcTo(e+i,t+o,e,t+o,s),r.arcTo(e,t+o,e,t,h),r.arcTo(e,t,e+i,t,a),r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke()}function w(){a=[]}n.createVector=function(e,t,r){return new n.Vector(e,t,r)},n.curvePoint=function(e,t,n,r,i){const o=i*i*i,a=i*i;return e*(-.5*o+a-.5*i)+t*(1.5*o-2.5*a+1)+n*(-1.5*o+2*a+.5*i)+r*(.5*o-.5*a)},n.bezierPoint=function(e,t,n,r,i){const o=1-i;return Math.pow(o,3)*e+3*Math.pow(o,2)*i*t+3*o*Math.pow(i,2)*n+Math.pow(i,M 3)*r},n.curveTangent=function(e,t,n,r,i){const o=i*i;return e*(-3*o/2+2*i-.5)+t*(9*o/2-5*i)+n*(-9*o/2+4*i+.5)+r*(3*o/2-i)},n.bezierTangent=function(e,t,n,r,i){const o=1-i;return 3*r*Math.pow(i,2)-3*n*Math.pow(i,2)+6*n*o*i-6*t*o*i+3*t*Math.pow(o,2)-3*e*Math.pow(o,2)},n.Color=function(e,t,n,r){let i=this;i.MAGIC=786698,i._r=e,i._g=t,i._b=n,i._a=r,i._h=0,i._s=0,i._v=0,i._hsvInferred=!1,i.setRed=function(e){i._r=e,i._hsvInferred=!1},i.setGreen=function(e){i._g=e,i._hsvInferred=!1},i.setBlue=function(e){i._b=e,i._hsvInfM erred=!1},i.setAlpha=function(e){i._a=e/255,i._hsvInferred=!1},i._inferHSV=function(){i._hsvInferred||([i._h,i._s,i._v]=function(e,t,n){let r,i,o,a,l;return r=e<t?e<n?e:n:t<n?t:n,0==(l=100*(i=e>t?e>n?e:n:t>n?t:n)/255)?[o=0,a=0,l]:0==(a=100*(i-r)/i)?[o=0,a,l]:(o=i==e?0+60*(t-n)/(i-r):i==t?120+60*(n-e)/(i-r):240+60*(e-t)/(i-r),[o,a,l])}(i._r,i._g,i._b),i._hsvInferred=!0)},i.toString=function(){return`rgba(${Math.round(i._r)},${Math.round(i._g)},${Math.round(i._b)},${~~(1e3*i._a)/1e3})`}},n.colorMode=function(e){n._stM yle.colorMode=e},n.color=function(){if(1==arguments.length&&786698==arguments[0].MAGIC)return arguments[0];if(n._style.colorMode==n.RGB){if(1==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],1);if(2==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],arguments[1]/255);if(3==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],1);if(4==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],arguments[3]/255)}else{if(1==argumeM nts.length)return new n.Color(...x(0,0,arguments[0]/100),1);if(2==arguments.length)return new n.Color(...x(0,0,arguments[0]/100),arguments[1]/255);if(3==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),1);if(4==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),arguments[3])}return null},n.red=function(e){return e._r},n.green=function(e){return e._g},n.blue=function(e){return e._b},n.alpha=function(e){return 255*e._a},n.hue=function(e){reM turn e._inferHSV(),e._h},n.saturation=function(e){return e._inferHSV(),e._s},n.brightness=function(e){return e._inferHSV(),e._v},n.lightness=function(e){return 100*(.2126*e._r+.7152*e._g+.0722*e._b)/255},n.lerpColor=function(e,t,r){return n._style.colorMode==n.RGB?new n.Color(n.constrain(n.lerp(e._r,t._r,r),0,255),n.constrain(n.lerp(e._g,t._g,r),0,255),n.constrain(n.lerp(e._b,t._b,r),0,255),n.constrain(n.lerp(e._a,t._a,r),0,1)):(e._inferHSV(),t._inferHSV(),new n.Color(n.constrain(function(e,t,r){var i=[[Math.abs(t-M e),n.map(r,0,1,e,t)],[Math.abs(t+360-e),n.map(r,0,1,e,t+360)],[Math.abs(t-360-e),n.map(r,0,1,e,t-360)]];return i.sort(((e,t)=>e[0]-t[0])),(i[0][1]+720)%360}(e._h,t._h,r),0,360),n.constrain(n.lerp(e._s,t._s,r),0,100),n.constrain(n.lerp(e._v,t._v,r),0,100),n.constrain(n.lerp(e._a,t._a,r),0,1)))},n.strokeWeight=function(e){n._style_noStroke=!1,r.lineWidth=e},n.stroke=function(){if(n._style.noStroke=!1,"string"==typeof arguments[0])return void(r.strokeStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._sM tyle.noStroke=!0:r.strokeStyle=e},n.noStroke=function(){n._style.noStroke=!0},n.fill=function(){if(n._style.noFill=!1,"string"==typeof arguments[0])return void(r.fillStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._style.noFill=!0:r.fillStyle=e},n.noFill=function(){n._style.noFill=!0},n.blendMode=function(e){r.globalCompositeOperation=e},n.strokeCap=function(e){r.lineCap=e},n.strokeJoin=function(e){r.lineJoin=e},n.ellipseMode=function(e){n._style.ellipseMode=e},n.rectMode=function(e){n._style.rectM Mode=e},n.curveDetail=function(e){n._style.curveDetail=e},n.curveAlpha=function(e){n._style.curveAlpha=e},n.curveTightness=function(e){n._style.curveAlpha=e},n.clear=function(){r.clearRect(0,0,n.width,n.height)},n.background=function(){if(arguments[0]&&arguments[0].MAGIC==n.MAGIC)return n.image(arguments[0],0,0,n.width,n.height);r.save(),r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity),r.fillStyle="string"==typeof arguments[0]?arguments[0]:n.color(...Array.from(arguments)),r.fillRect(0,0,n.width,n.heightM ),r.restore()},n.line=function(e,t,i,o){n._style.noStroke||(r.beginPath(),r.moveTo(e,t),r.lineTo(i,o),r.stroke())},n.arc=function(e,t,r,i,o,a,l,s){if(o==a)return n.ellipse(e,t,r,i);null==s&&(s=25),null==l&&(l=n.PIE),n._style.ellipseMode==n.CENTER?m(e,t,r,i,o,a,l,s):n._style.ellipseMode==n.RADIUS?m(e,t,2*r,2*i,o,a,l,s):n._style.ellipseMode==n.CORNER?m(e+r/2,t+i/2,r,i,o,a,l,s):n._style.ellipseMode==n.CORNERS&&m((e+r)/2,(t+i)/2,r-e,i-t,o,a,l,s)},n.ellipse=function(e,t,r,i){null==i&&(i=r),n._style.ellipseMode==n.CENTERM ?b(e,t,r,i):n._style.ellipseMode==n.RADIUS?b(e,t,2*r,2*i):n._style.ellipseMode==n.CORNER?b(e+r/2,t+i/2,r,i):n._style.ellipseMode==n.CORNERS&&b((e+r)/2,(t+i)/2,r-e,i-t)},n.circle=function(e,t,r){return n.ellipse(e,t,r,r)},n.point=function(e,t){e.x&&(t=e.y,e=e.x),r.beginPath(),r.ellipse(e,t,.4,.4,0,0,2*Math.PI),r.stroke()},n.rect=function(e,t,r,i,o,a,l,s){n._style.rectMode==n.CENTER?y(e-r/2,t-i/2,r,i,o,a,l,s):n._style.rectMode==n.RADIUS?y(e-r,t-i,2*r,2*i,o,a,l,s):n._style.rectMode==n.CORNER?y(e,t,r,i,o,a,l,s):n._stylM e.rectMode==n.CORNERS&&y(e,t,r-e,i-t,o,a,l,s)},n.square=function(e,t,r,i,o,a,l){return n.rect(e,t,r,r,i,o,a,l)},n.beginShape=function(){w(),r.beginPath(),o=!0},n.beginContour=function(){r.closePath(),w(),o=!0},n.endContour=function(){w(),o=!0},n.vertex=function(e,t){w(),o?r.moveTo(e,t):r.lineTo(e,t),o=!1},n.bezierVertex=function(e,t,n,i,o,a){w(),r.bezierCurveTo(e,t,n,i,o,a)},n.quadraticVertex=function(e,t,n,i){w(),r.quadraticCurveTo(e,t,n,i)},n.bezier=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.bezierVM ertex(r,i,o,a,l,s),n.endShape()},n.triangle=function(e,t,r,i,o,a){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.endShape(n.CLOSE)},n.quad=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.vertex(l,s),n.endShape(n.CLOSE)},n.endShape=function(e){w(),e&&r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke(),n._style.noFill&&n._style.noStroke&&(r.save(),r.fillStyle="none",r.fill(),r.restore())},n.curveVertex=function(e,t){if(a.push([e,t]),a.length<4)return;M let i=function(e,t,n,r,i,o,a,l,s,h){function c(e,t,n,r,i,o){let a=Math.pow(r-t,2)+Math.pow(i-n,2);return Math.pow(a,.5*o)+e}let u=[],f=c(0,e,t,n,r,h),d=c(f,n,r,i,o,h),x=c(d,i,o,a,l,h);for(let h=0;h<s;h++){let c=f+h/(s-1)*(d-f),g=[(f-c)/(f-0),(c-0)/(f-0),(d-c)/(d-f),(c-f)/(d-f),(x-c)/(x-d),(c-d)/(x-d),(d-c)/(d-0),(c-0)/(d-0),(x-c)/(x-f),(c-f)/(x-f)];for(let e=0;e<g.length;e+=2)isNaN(g[e])&&(g[e]=1,g[e+1]=0),isFinite(g[e])||(g[e]>0?(g[e]=1,g[e+1]=0):(g[e]=0,g[e+1]=1));let p=e*g[0]+n*g[1],m=t*g[0]+r*g[1],b=n*g[2]+i*g[M 3],y=r*g[2]+o*g[3],w=i*g[4]+a*g[5],v=o*g[4]+l*g[5],z=p*g[6]+b*g[7],V=m*g[6]+y*g[7],_=b*g[8]+w*g[9],M=y*g[8]+v*g[9],E=z*g[2]+_*g[3],S=V*g[2]+M*g[3];u.push([E,S])}return u}(...a[a.length-4],...a[a.length-3],...a[a.length-2],...a[a.length-1],n._style.curveDetail,n._style.curveAlpha);for(let e=0;e<i.length;e++)o?r.moveTo(...i[e]):r.lineTo(...i[e]),o=!1},n.curve=function(e,t,r,i,o,a,l,s){n.beginShape(),n.curveVertex(e,t),n.curveVertex(r,i),n.curveVertex(o,a),n.curveVertex(l,s),n.endShape()},n.translate=function(e,t){r.tM ranslate(e,t)},n.rotate=function(e){r.rotate(e)},n.scale=function(e,t){null==t&&(t=e),r.scale(e,t)},n.applyMatrix=function(e,t,n,i,o,a){r.transform(e,t,n,i,o,a)},n.shearX=function(e){r.transform(1,0,Math.tan(e),1,0,0)},n.shearY=function(e){r.transform(1,Math.tan(e),0,1,0,0)},n.resetMatrix=function(){r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity)},n.pushMatrix=n.push=function(){n._styleCache.push({...n._style}),n._style=n._styleCache[n._styleCache.length-1],r.save()},n.popMatrix=n.pop=function(){n._stylM eCache.length-1&&(n._styleCache.pop(),n._style=n._styleCache[n._styleCache.length-1],r.restore())},n.image=function(e,t,i,o,a,l,s,h,c){let u=e.MAGIC==n.MAGIC?e.canvas:e;function d(){if(e.MAGIC!=n.MAGIC||!n._tint)return;let t=e.canvas.getContext("2d");t.save(),t.resetTransform(),t.clearRect(0,0,t.canvas.width,t.canvas.height),t.drawImage(f.canvas,0,0),t.restore()}return e.MAGIC==n.MAGIC&&null!=n._tint&&(function(e,t){null==f&&(f=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvasM .height),f.canvas.width==e&&f.canvas.height==t||(f.canvas.width=e,f.canvas.height=t)}(e.canvas.width,e.canvas.height),f.drawImage(e.canvas,0,0),e.tinted(n._tint)),o?l?(h||(h=u.width),c||(c=u.height),r.drawImage(u,l,s,h,c,t,i,o,a),void d()):(r.drawImage(u,t,i,o,a),void d()):(e.MAGIC==n.MAGIC||e.width?r.drawImage(u,t,i,e.width,e.height):r.drawImage(u,t,i,e.videoWidth,e.videoHeight),void d())},n.loadPixels=function(){l=r.getImageData(0,0,n.canvas.width,n.canvas.height),n.pixels=l.data},n.updatePixels=function(){null!=M l&&r.putImageData(l,0,0)},n.loadImage=function(e,t){s++;let r=n.createGraphics(100,100),i=r.canvas.getContext("2d"),o=new Image;return o.src=e,o.crossOrigin="Anonymous",o.onload=function(){i.canvas.width=o.width,i.canvas.height=o.height,r.width=o.width,r.height=o.height,i.drawImage(o,0,0),s--,t&&t(r)},r};let v={};function z(e,t){null==u&&(u=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvas.height),u.canvas.width==e&&u.canvas.height==t||(u.canvas.width=e,u.canvas.height=t)}funcM tion V(){let e=r.canvas.width*r.canvas.height*4;null!=d&&e==d.length||(d=new Uint8ClampedArray(e))}function _(e){u.clearRect(0,0,u.canvas.width,u.canvas.height),u.filter=e,u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()}v[n.THRESHOLD]=function(e,t){null==t?t=127.5:t*=255;for(let n=0;n<e.length;n+=4){const r=.2126*e[n]+.7152*e[n+1]+.0722*e[n+2];e[n]=e[n+1]=e[n+2]=r>=t?255:0}},v[n.GRAY]=function(e){for(let t=0;t<e.length;t+=4)M {const n=.2126*e[t]+.7152*e[t+1]+.0722*e[t+2];e[t]=e[t+1]=e[t+2]=n}},v[n.OPAQUE]=function(e){for(let t=0;t<e.length;t+=4)e[t+3]=255},v[n.INVERT]=function(e){for(let t=0;t<e.length;t+=4)e[t]=255-e[t],e[t+1]=255-e[t+1],e[t+2]=255-e[t+2]},v[n.POSTERIZE]=function(e,t){let n=t-1;for(let r=0;r<e.length;r+=4)e[r]=255*(e[r]*t>>8)/n,e[r+1]=255*(e[r+1]*t>>8)/n,e[r+2]=255*(e[r+2]*t>>8)/n},v[n.DILATE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-M 1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.max(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.ERODE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.min(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.BLURM ]=function(e,t){t=t||1,t=Math.floor(t*n._pixelDensity),V(),d.set(e);let i=2*t+1,o=function(e){let n=new Float32Array(e),r=.3*t+.8,i=r*r*2;for(let t=0;t<e;t++){let o=t-e/2,a=Math.exp(-o*o/i)/(2.5066282746*r);n[t]=a}return n}(i),[a,l]=[r.canvas.width,r.canvas.height];for(let n=0;n<l;n++)for(let r=0;r<a;r++){let l=0,s=0,h=0,c=0;for(let e=0;e<i;e++){let i=4*(n*a+Math.min(Math.max(r-t+e,0),a-1));l+=d[i]*o[e],s+=d[i+1]*o[e],h+=d[i+2]*o[e],c+=d[i+3]*o[e]}let u=4*(n*a+r);e[u]=l,e[u+1]=s,e[u+2]=h,e[u+3]=c}d.set(e);for(let nM =0;n<l;n++)for(let r=0;r<a;r++){let s=0,h=0,c=0,u=0;for(let e=0;e<i;e++){let i=4*(Math.min(Math.max(n-t+e,0),l-1)*a+r);s+=d[i]*o[e],h+=d[i+1]*o[e],c+=d[i+2]*o[e],u+=d[i+3]*o[e]}let f=4*(n*a+r);e[f]=s,e[f+1]=h,e[f+2]=c,e[f+3]=u}},n.filter=function(e,t){if(n.HARDWARE_FILTERS&&null!=r.filter)if(z(),e==n.THRESHOLD){null==t&&(t=.5),t=Math.max(t,1e-5),_(`saturate(0%) brightness(${Math.floor(.5/t*100)}%) contrast(1000000%)`)}else if(e==n.GRAY)_("saturate(0%)");else if(e==n.OPAQUE)u.fillStyle="black",u.fillRect(0,0,u.canvaM s.width,u.canvas.height),u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.drawImage(u.canvas,0,0),r.restore();else if(e==n.INVERT)_("invert(100%)");else if(e==n.BLUR)_(`blur(${Math.ceil(t*n._pixelDensity/1)||1}px)`);else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}},n.resize=function(e,t){z(),u.drawImage(r.canvas,0,0),n.width=e,n.height=t,r.canvas.width=e*n._pixM elDensity,r.canvas.height=t*n._pixelDensity,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0,r.canvas.width,r.canvas.height),r.restore()},n.get=function(e,t,i,o){if(null!=e&&null==i){let i=r.getImageData(e,t,1,1).data;return new n.Color(i[0],i[1],i[2],i[3]/255)}e=e||0,t=t||0,i=i||n.width,o=o||n.height;let a=n.createGraphics(i,o);a.pixelDensity(n._pixelDensity);let l=r.getImageData(e*n._pixelDensity,t*n._pixelDensity,i*n._pixelDensity,o*n._pixelDensity);return a.caM nvas.getContext("2d").putImageData(l,0,0),a},n.set=function(e,t,i){if(i.MAGIC==n.MAGIC){let r=n._tint;return n._tint=null,n.image(i,e,t),void(n._tint=r)}let o=4*(t*n._pixelDensity*r.canvas.width+e*n._pixelDensity);n.pixels[o]=i._r,n.pixels[o+1]=i._g,n.pixels[o+2]=i._b,n.pixels[o+3]=255*i._a},n.tinted=function(){let e=n.color(...Array.from(arguments)),t=e._a;e._a=1,z(),u.clearRect(0,0,u.canvas.width,u.canvas.height),u.fillStyle=e,u.fillRect(0,0,u.canvas.width,u.canvas.height),u.globalCompositeOperation="multiply",u.M drawImage(r.canvas,0,0),u.globalCompositeOperation="source-over",r.save(),r.resetTransform();let i=r.globalCompositeOperation;r.globalCompositeOperation="source-in",r.drawImage(u.canvas,0,0),r.globalCompositeOperation=i,r.restore(),u.globalAlpha=t,u.clearRect(0,0,u.canvas.width,u.canvas.height),u.drawImage(r.canvas,0,0),u.globalAlpha=1,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()},n.tint=function(){n._tint=n.color(...Array.from(arguments))},n.noTiM nt=function(){n._tint=null},n.mask=function(e){r.save(),r.resetTransform();let t=r.globalCompositeOperation;r.globalCompositeOperation="destination-in",r.drawImage(e.canvas,0,0),r.globalCompositeOperation=t,r.restore()},n.clearTemporaryBuffers=function(){u=null,f=null,d=null},n.save=function(e,t){e=e||"untitled",t=t||"png";var n=document.createElement("a");n.innerHTML="[Download]",n.addEventListener("click",(function(){this.href=r.canvas.toDataURL(),this.download=e+"."+t}),!1),document.body.appendChild(n),n.click()M ,document.body.removeChild(n)},n.saveCanvas=function(e,t,r){if(e.MAGIC==n.MAGIC){r&&e.save(t,r);let n=t.split(".");return e.save(n.slice(0,-1).join("."),n[n.length-1])}if(t)return n.save(e,t);let i=e.split(".");return n.save(i.slice(0,-1).join("."),i[i.length-1])},n.loadFont=function(e){let t=e.split("/"),n=t[t.length-1].split(".")[0].replace(" ",""),r=`@font-face {\n font-family: '${n}';\n src: url('${e}');\n }`;const i=document.createElement("style");return i.textContent=r,document.head.append(M i),n},n.textFont=function(e){n._style.textFont=e},n.textSize=function(e){n._style.textSize=e,n._style.textLeading=e},n.textLeading=function(e){n._style.textLeading=e},n.textStyle=function(e){n._style.textStyle=e},n.textAlign=function(e,t){r.textAlign=e,t&&(r.textBaseline=t==n.CENTER?"middle":t)},n.text=function(e,t,i,o){if(!e)return;if(e=e.toString(),n._style.noFill&&n._style.noStroke)return;r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`;let a=e.split("\n");for(let e=0;e<a.length;e++)n._M style.noFill||r.fillText(a[e],t,i,o),n._style.noStroke||r.strokeText(a[e],t,i,o),i+=n._style.textLeading},n.textWidth=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).width},n.textAscent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBoundingBoxAscent},n.textDescent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBounM dingBoxDescent};var M,E=4,S=.5,R=function(e){return.5*(1-Math.cos(e*Math.PI))};n.noise=function(e,t,n){if(t=t||0,n=n||0,null==M){M=new Array(4096);for(var r=0;r<4096;r++)M[r]=Math.random()}e<0&&(e=-e),t<0&&(t=-t),n<0&&(n=-n);for(var i,o,a,l,s,h=Math.floor(e),c=Math.floor(t),u=Math.floor(n),f=e-h,d=t-c,x=n-u,g=0,p=.5,m=0;m<E;m++){var b=h+(c<<4)+(u<<8);i=R(f),o=R(d),a=M[4095&b],a+=i*(M[b+1&4095]-a),l=M[b+16&4095],a+=o*((l+=i*(M[b+16+1&4095]-l))-a),l=M[4095&(b+=256)],l+=i*(M[b+1&4095]-l),s=M[b+16&4095],l+=o*((s+=i*(M[M b+16+1&4095]-s))-l),g+=(a+=R(x)*(l-a))*p,p*=S,h<<=1,c<<=1,u<<=1,(f*=2)>=1&&(h++,f--),(d*=2)>=1&&(c++,d--),(x*=2)>=1&&(u++,x--)}return g},n.noiseDetail=function(e,t){e>0&&(E=e),t>0&&(S=t)};const I=function(){let e,t,n=4294967295;return{setSeed(r){e=t=(null==r?Math.random()*n:r)>>>0},getSeed:()=>t,rand:()=>(e^=e<<17,e^=e>>13,((e^=e<<5)>>>0)/n)}};let C=I();C.setSeed(),n.noiseSeed=function(e){let t=null==e?4294967295*Math.random():e;M||(M=new Float32Array(4096));for(var n=0;n<4096;n++)t^=t<<17,t^=t>>13,t^=t<<5,M[n]=(t>M >>0)/4294967295},n.randomSeed=function(e){C.setSeed(e)},n.random=function(e,t){return null==e?C.rand():"number"==typeof e?null!=t?C.rand()*(t-e)+e:C.rand()*e:e[~~(e.length*C.rand())]},n.randomGenerator=function(e){e==n.LCG?C=function(){const e=4294967296;let t,n;return{setSeed(r){n=t=(null==r?Math.random()*e:r)>>>0},getSeed:()=>t,rand:()=>(n=(1664525*n+1013904223)%e)/e}}():e==n.SHR3&&(C=I()),C.setSeed()};var T=new function(){var e,t,n,r=new Array(128),i=new Array(256),o=new Array(128),a=new Array(128),l=new Array(2M 56),s=new Array(256),h=function(){return 4294967296*C.rand()-2147483648},c=function(){return.5+2.328306e-10*(h()<<0)};this.SHR3=h,this.UNI=c,this.RNOR=function(){return n=h(),e=127&n,Math.abs(n)<r[e]?n*o[e]:function(){for(var t,i,l,s,u=3.44262;;){if(t=n*o[e],0==e){do{l=c(),s=c(),t=.2904764*-Math.log(l),i=-Math.log(s)}while(i+i<t*t);return n>0?u+t:-u-t}if(a[e]+c()*(a[e-1]-a[e])<Math.exp(-.5*t*t))return t;if(n=h(),e=127&n,Math.abs(n)<r[e])return n*o[e]}}()},this.REXP=function(){return(t=h()>>>0)<r[e=255&t]?t*l[e]:funM ction(){for(var n;;){if(0==e)return 7.69711-Math.log(c());if(n=t*l[e],s[e]+c()*(s[e-1]-s[e])<Math.exp(-n))return n;if((t=h())<i[e=255&t])return t*l[e]}}()},this.zigset=function(){var e,t,n=2147483648,h=4294967296,c=3.442619855899,u=c,f=.00991256303526217,d=7.697117470131487,x=d,g=.003949659822581572;for(e=f/Math.exp(-.5*c*c),r[0]=Math.floor(c/e*n),r[1]=0,o[0]=e/n,o[127]=c/n,a[0]=1,a[127]=Math.exp(-.5*c*c),t=126;t>=1;t--)c=Math.sqrt(-2*Math.log(f/c+Math.exp(-.5*c*c))),r[t+1]=Math.floor(c/u*n),u=c,a[t]=Math.exp(-.5*cM *c),o[t]=c/n;for(e=g/Math.exp(-d),i[0]=Math.floor(d/e*h),i[1]=0,l[0]=e/h,l[255]=d/h,s[0]=1,s[255]=Math.exp(-d),t=254;t>=1;t--)d=-Math.log(g/d+Math.exp(-d)),i[t+1]=Math.floor(d/x*h),x=d,s[t]=Math.exp(-d),l[t]=d/h}};T.hasInit=!1,n.randomGaussian=function(e,t){return T.hasInit||(T.zigset(),T.hasInit=!0),T.RNOR()*t+e},n.randomExponential=function(){return T.hasInit||(T.zigset(),T.hasInit=!0),T.REXP()},n.print=console.log,n.cursor=function(e,t,r){let i="";e.includes(".")&&(e=`url("${e}")`,i=", auto"),null!=t&&(e+=" "+t+M " "+r),n.canvas.style.cursor=e+i},n.noCursor=function(){n.canvas.style.cursor="none"},n.createCapture=function(e){var t=document.createElement("video");return t.playsinline="playsinline",t.autoplay="autoplay",navigator.mediaDevices.getUserMedia(e).then((function(e){t.srcObject=e})),t.style.position="absolute",t.style.opacity=1e-5,t.style.zIndex=-1e3,document.body.appendChild(t),t};let A=["setup","draw","preload","mouseMoved","mousePressed","mouseReleased","mouseDragged","mouseClicked","keyPressed","keyReleased","keM yTyped","touchStarted","touchEnded"];for(let e of A){let t="_"+e+"Fn";n[t]=function(){},n[t].isPlaceHolder=!0,n[e]?n[t]=n[e]:Object.defineProperty(n,e,{set:function(e){n[t]=e}})}function D(){n._noLoop||(i=null==n._frameRate?requestAnimationFrame(D):setTimeout(D,1e3/n._frameRate)),w(),o=!0,n.push(),n._drawFn(),n.pop(),++n.frameCount}function k(e){const t=n.canvas.getBoundingClientRect(),r=n.canvas.scrollWidth/n.width||1,i=n.canvas.scrollHeight/n.height||1;return{x:(e.clientX-t.left)/r,y:(e.clientY-t.top)/i,id:e.idenM tifier}}function L(){return n._touchStarted.isPlaceHolder&&n._touchMoved.isPlaceHolder&&n._touchEnded.isPlaceHolder}n.noLoop=function(){n._noLoop=!0,i=null},n.loop=function(){n._noLoop=!1,null==i&&D()},n.redraw=function(){D()},n.frameRate=function(e){n._frameRate=e},setTimeout((function(){n._preloadFn(),c=window.performance.now(),function e(){if(s>0)return setTimeout(e,10);n._setupFn(),D()}()}),1),n.canvas.onmousemove=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPM ressed?n._mouseDraggedFn(e):n._mouseMovedFn(e)},n.canvas.onmousedown=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!0,n.mouseButton=[n.LEFT,n.CENTER,n.RIGHT][e.button],n._mousePressedFn(e)},n.canvas.onmouseup=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!1,n._mouseReleasedFn(e)},n.canvas.onclick=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressedM =!0,n._mouseClickedFn(e),n.mouseIsPressed=!1},window.addEventListener("keydown",(function(e){n.keyIsPressed=!0,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!0,n._keyPressedFn(e),1==e.key.length&&n._keyTypedFn(e)})),window.addEventListener("keyup",(function(e){n.keyIsPressed=!1,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!1,n._keyReleasedFn(e)})),n.keyIsDown=function(e){return!!h[e]},n.canvas.ontouchstart=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.moM useY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mousePressedFn(e)||e.preventDefault()),n._touchStartedFn(e)||e.preventDefault()},n.canvas.ontouchmove=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mouseDraggedFn(e)||e.preventDefault()),n._touchMovedFn(e)||e.preventDefault()},n.canvas.ontouchend=n.canvas.ontouchcancel=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.M mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!1,n._mouseReleasedFn(e)||e.preventDefault()),n._touchEndedFn(e)||e.preventDefault()},n.hasSensorPermission=!window.DeviceOrientationEvent&&!window.DeviceMotionEvent||!(DeviceOrientationEvent.requestPermission||DeviceMotionEvent.requestPermission),n.requestSensorPermissions=function(){DeviceOrientationEvent.requestPermission&&DeviceOrientationEvent.requestPermission().then((e=>{"granted"==e&&DeviceMotionEvent.requestPermissioM n&&DeviceMotionEvent.requestPermission().then((e=>{"granted"==e&&(n.hasSensorPermission=!0)})).catch(alert)})).catch(alert)},window.ondeviceorientation=function(e){n.pRotationX=n.rotationX,n.pRotationY=n.rotationY,n.pRotationZ=n.rotationZ,n.pRelRotationX=n.relRotationX,n.pRelRotationY=n.relRotationY,n.pRelRotationZ=n.relRotationZ,n.rotationX=e.beta*(Math.PI/180),n.rotationY=e.gamma*(Math.PI/180),n.rotationZ=e.alpha*(Math.PI/180),n.relRotationX=[-n.rotationY,-n.rotationX,n.rotationY][1+~~(window.orientation/90)],n.rM elRotationY=[-n.rotationX,n.rotationY,n.rotationX][1+~~(window.orientation/90)],n.relRotationZ=n.rotationZ},window.ondevicemotion=function(e){if(n.pAccelerationX=n.accelerationX,n.pAccelerationY=n.accelerationY,n.pAccelerationZ=n.accelerationZ,!e.acceleration){let t=((e,t)=>[(e[0]*t[0]+e[1]*t[1]+e[2]*t[2]+e[3])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[4]*t[0]+e[5]*t[1]+e[6]*t[2]+e[7])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[8]*t[0]+e[9]*t[1]+e[10]*t[2]+e[11])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15])])(((e,t)M =>[e[0]*t[0]+e[1]*t[4]+e[2]*t[8]+e[3]*t[12],e[0]*t[1]+e[1]*t[5]+e[2]*t[9]+e[3]*t[13],e[0]*t[2]+e[1]*t[6]+e[2]*t[10]+e[3]*t[14],e[0]*t[3]+e[1]*t[7]+e[2]*t[11]+e[3]*t[15],e[4]*t[0]+e[5]*t[4]+e[6]*t[8]+e[7]*t[12],e[4]*t[1]+e[5]*t[5]+e[6]*t[9]+e[7]*t[13],e[4]*t[2]+e[5]*t[6]+e[6]*t[10]+e[7]*t[14],e[4]*t[3]+e[5]*t[7]+e[6]*t[11]+e[7]*t[15],e[8]*t[0]+e[9]*t[4]+e[10]*t[8]+e[11]*t[12],e[8]*t[1]+e[9]*t[5]+e[10]*t[9]+e[11]*t[13],e[8]*t[2]+e[9]*t[6]+e[10]*t[10]+e[11]*t[14],e[8]*t[3]+e[9]*t[7]+e[10]*t[11]+e[11]*t[15],e[12]*t[0]+M e[13]*t[4]+e[14]*t[8]+e[15]*t[12],e[12]*t[1]+e[13]*t[5]+e[14]*t[9]+e[15]*t[13],e[12]*t[2]+e[13]*t[6]+e[14]*t[10]+e[15]*t[14],e[12]*t[3]+e[13]*t[7]+e[14]*t[11]+e[15]*t[15]])((e=>[Math.cos(e),0,Math.sin(e),0,0,1,0,0,-Math.sin(e),0,Math.cos(e),0,0,0,0,1])(n.rotationY),(e=>[1,0,0,0,0,Math.cos(e),-Math.sin(e),0,0,Math.sin(e),Math.cos(e),0,0,0,0,1])(n.rotationX)),[0,0,-9.80665]);n.accelerationX=e.accelerationIncludingGravity.x+t[0],n.accelerationY=e.accelerationIncludingGravity.y+t[1],n.accelerationZ=e.accelerationIncludM ingGravity.z-t[2]}},n.year=function(){return(new Date).getFullYear()},n.day=function(){return(new Date).getDay()},n.hour=function(){return(new Date).getHours()},n.minute=function(){return(new Date).getMinutes()},n.second=function(){return(new Date).getSeconds()},n.millis=function(){return window.performance.now()-c}}(e)}"object"==typeof exports&&"undefined"!=typeof module&&(module.exports=e);const t="https://ancient-crimson-rain.btc.discover.quiknode.pro/c268fb026303ae8443f785200f2ea4b82f0082dd";function n(e){P(e)?M localStorage.removeItem("blocksApiEndpoint"):localStorage.blocksApiEndpoint=e}function r(){return localStorage.blocksApiEndpoint||t}function i(e){P(e)?localStorage.removeItem("modelInscriptionEndpoint"):localStorage.modelInscriptionEndpoint=e}function o(){return localStorage.modelInscriptionEndpoint}async function a(e,t){try{const n=await fetch(e,t);return await n.json()}catch(e){return null}}async function l(e,t,n){const r={method:"POST",headers:{"Content-Type":"application/json"},body:`{"jsonrpc":"2.0","id":1,"meM thod":"${t}","params":${`[${n.join(sep=",")}]`}}`};return(await a(e,r))?.result}async function s(e){const n={avgfee:10,time:Date.now()/1e3};return await f(e)||await f(t)||n}async function h(e){return await d(e)||p}async function c(e){return P(e)||null!=await f(e)}async function u(e){return P(e)||null!=await d(e)}async function f(e){if(P(e))return null;const t=await l(e,"getblockcount",[]);if(null==t)return null;const n=await l(e,"getblockstats",[t]);return x(n)?n:null}async function d(e){if(P(e))return null;const tM =await a(e,{});return g(t)?t:null}function x(e){return"number"==typeof e?.time&&"number"==typeof e?.avgfee}function g(e){if(null==e)return!1;const{classes_name:t,training_traits:n,layers_config:r,weight_b64:i}=e;if(!Array.isArray(t))return!1;if(null==n)return!1;try{j(r,i)}catch(e){return!1}return!0}const p={"model_name": "pfp_classifier_364", "layers_config": {"config": {"layers": [{"class_name": "InputLayer", "config": {"batch_input_shape": [null, 28, 28, 3]}}, {"class_name": "Rescaling", "config": {"scale": 0.007M 84313725490196, "offset": -1}}, {"class_name": "Flatten"}, {"class_name": "Dense", "config": {"units": 5, "activation": "leaky_relu"}}, {"class_name": "Dense", "config": {"units": 2, "activation": "leaky_relu"}}, {"class_name": "Dense", "config": {"units": 4, "activation": "linear"}}]}}, "weight_b64": "hxSIvHK0hz1304W9sXdgvbcAVz0+8ba7nUf0vazJNb0yvIg9xa5FPYhujT1w+tE5OKgQPjrXVL3TCQa9PyhHParthD2UOoq9XiGMu+IuXT1GtSA8Zu2LvfcURr0hp4a8IL7GPXcXRz19WSA9uWWXPX2+XL3mFOm8l1kivdlmmjyYk+i9WzF5vSoHnzxsu6c7jcsRvonYK71s/dk8oSirPflmM 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 IJHJvERU6DvatTY9RCBevn2JdbxAWUc92OSdPWn4oD24tFi9vc+vPfFiFr2q5TK9DsiPu2o3Vz2rka69Gh+7vAk1AD3gRbM7VadcvuBlhjyp+E48IO/TPSAr+bha1Si9szQhPg7dyLw106a9qxukPcSz7jx1Rau9JpmCvUYiyDvFxKs9KIhTvkDlNT17pHE9OHuSPTYMfD1F/N+6R0vnPTTlv7wM80G9HzvqPLkP5jyvqHK9Wo7BOWVNJr3tU7k93W8Kvj8CD72dU2E8fI2gPaG/SD0A7kq9BSGlPWGnw7tk98S9KioDPE9/uzwmY6G9ey7zOn353Lzkqzk8JSYDvjuaiLtR9U89z5n6Pe4QgD211Go7b2XdPUaOKr0OWFa9QJ5hPREzpzzs4am9jDlCvQR3BrzNU4g8KtU1vm5jZ73Vj0M9RKuZPaofPzliMJ47A14LPo/2O72rRqu9lFcNPJp8yjwg3tq8JVBNvdG6Jr04ZN28ukbAvScTM73K52o9VR2yPej4M 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 pDoGUZo9kkc+PeBdnzuDHxS9HzmhO0kn3DyKiA++r0FTvSWRgL3xYoi9ihifvWKR2L2QpEk9eB4UvCr5VrzWtKc9isuuPKrNx7yOjCG9spwFvJeykj12sQ++VO3NvF9Yjr2QSZA8nUZEvY36Z73KEhE9IrCLPRz3Br1Cyag9FX29OzBA7bxjtdS8evE/vQEy2zzcw5y93L6OvIXVmbyYMso85EQvvfMMTr30o5U9BhHxPF3q9Lx2Ybs8q5HcPS2nEj1im6q9psSYvXIUkT2ruqK9ww6XvLCqn7zBFnq9h0K3vTW6ib32nrI8n01kPYmnpTx8r5c9MiVRPfytPrxr58y9jO4NPBHlaD3QAwq+vGMMvN2hgrulaoO9M5wNvhFZYL1SgiA9zDrHPYKDtzsTx349SIJoPQzAT7wa74S9MBAmvWmpXboyIMO9ln4ouzriZ72+C7Y8z/ocvvVYX72IQzo9LBsMPK1MwLvRT4m8F2GBPAL0GTyeheG9IMbaO69ZcT1MOe69M 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 Ij1Gh429UccaPotazb0kuKS9NG+qPa2qMzxO55m9eOXFvYNT3DztZqM95n07vp8Hk7w9G2i6CGc5PeJbMjw9Xkm8Z3fNPfudbr3h/i29fhQYPQCDET1xZKe9ykTnvSXh1jzw3qg7GkJfvji/tLzvdtQ8ZhVmPQF/gT23ca69erPhPUFOXL2m36u99wQivDIogz3v5sC9vAmVvcsBxTzTsaU9CkQTvhyWdL3M4/678tY8PVyO5jvnv5m9VZMCPlynM71t91K9827SO39ujz3/Kom827b9vH1EMTyrXNK8gs0qvkKi2LrlKe28H9mJPZAmWj3KmQS99YgNPpTrkr04tT29auLDu/Xtgj07nhm9GE4mOklYMr1i7EC8Ufi8vZIOKL2Y1rc90GVxPVsT6bzBwk49I17LPYWS7TwAGXA4RMOAOyeDSz0DJAa9/KyNveY0Ob0rN/u8KnIwvkXuyrwnn+q8a+2ZPRULzzxnkQS9K6UIPi0+r7zLVJO9iHYkOjavOzym/9q8M 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 gPEyvOzW1bwG+5g8i64mvmIYvb3MDju9DVfSu5flkLxQl829Uah5vX4Bsz2j9qu8EHrFOuiP171cg7m81uAVPSWEOb1rPRQ9vjervcCJCL3/IYa987yRPPGQSDzp9pi9GTdFvR6H8ruVE1O8ZVAhPZLpub3ahpi7ciNfPJkwI728XSw9mU+ovRitdb1BvA69HZwivH6Kqrv6owO+7E8JvXd/Gz00RrO8/feTPM6cwr17wua8eL03vDD7s7wuUO49DMD8vX8oWb3ljMC8QsmqvAJnwD0zBwG+7N0WvAIbLL35aDS93RSPPf26uL11d0C9aJuavB1TID39HsE995f1ve66pLsoBQ08+YKBPDxmdD2WwY+9piVaPVlDMz0iwI08Z+MVPDSOAjxXMJ2858DkPTEihTzi8wA9iYmrvBVLDL37UEw9vXCNPetwQD3ulZy8oWZjPW4Mbz3Dw+48V7ULPd3xBD1VOZ88tFLBPQVBvzuG4f48Slq5vXHPVr3g9to88lrVPOHVM 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 IjyJFJM8OUjcPDm/AD7xhcC7NPqYPSc0yj0hkes9rFIJPn7XnT0OhM687XtxPayFRD0FldY8MzkEvVeiy722vAk9K+BSvRnHlT3LxSC869CNPJ41Mz1ONfA9xNzzPSb1DT1WdaK7DU8UPt2YOj2I8Q09XDgiPYnicL3LwNg9efI8Pd6YFT7n5y08wMDgPDmn9zzYJIs762u6PZAWdz23QB+9oPidPcG4zDy2ecE7LkACPVnP1L2ALqQ7tpu7vfdWVD2NZ648SkqgvTJIob0ZO8S8cMHtvKnxMDzS5Vm99FLcvGGCWbqYZxa91BJuvCd9uLzPjTa9jwMOvR+2xjz8TZG9kqXOPJJq+ru5esO8mC1qPW1tib3YVQU9T/IMvcHXajtAskw9aHIpvMuZUD0t8xW7UBSJPbwo1zt7bYQ8g/ctuzXITD12K/A7MZ9wPWfKB734WGI8SaKRvVBcXjs3Nps7BtebPUWNYTxIi1M8FjwNPdKTtT3zkX+9UF5EPdZfaT2hHgq8M y+lYO0a+Mz2Tnu48oU/+vcfTrLvTm8u8eatbPUKHmz2PRvG7cNBqPUlsjrxduiw8S+9SPa0fEj2z4aG9G84Vvf3xhj1Gbb497NeTvXLCA71NiDG89VG/PfZ2jz1u34Q8EYdpPU2UKjz1Nw69gVbePBOR1jypEkq9JNlQPDS8h7xI59I9swugvX164rvc2CI6rkiSPb48CT3GDuM89BAHPojYyLtdoJK8BHsEPZs/xDuVAKm9oh7evDbREr3+qXg9XVzQvdicb7y26ny8sD3IPYBXgTsJsdE8ryHSPbwQEjthCwW9PQkzPHKokjzDJmm9JNGUvWZ1KL0fOXg82Wo+vlSmK719e9e8ZGVKPSnemburdsy8N5G/PQ8k371UIsO8mX1dPQSpizw9DNa99QlQvTUnOr1DDEQ9A7xlvu8Ltbw3hLy8iBHsPRlnmTp7KC+94XqXPfm/Cr6TTrq9DQIFPTD23TkjZLy9jJeivUMdHzxhuQ88tt1CvllJgDv+iB08KM6FPQPPM 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 VL22MDG94JSxvOOitj0lj+88jvkoPfxsLrzNm8S86v7ZO4tgrzwQqo89yWyWPVc8jLz1VLq9qy4nPC2JxT0AUR49fnM3PRbXBL2POWc97pgzPRFbUb1bxoK9+wM6PFnz3jsggxY9rsCNPSJ+p736l7S9O9VFPFMe5j3Lmcm9fcChvYJIbr3WcVI91HidvBc4OLz5T4C8xnKPPRpkjrzh3Wg8HgZuPCULh71/k7y9stUWPTrw3D1a4/G9bzRYvfTAV71bHEQ9kfyjPBy28jwWsRk8whUUPvsTUz2W3wq8hcoWPlW/H73aDwk8DQb1u/hhxz0ZiZu9qSqxvXkSRby7kIE97cm6PNIOCD3oP1Y9J7PuPc2LiLyuNZU9OPUwPgshRLyw7YK8KxGiPUMOKz2t0/G8+J+JPQ4OKL0ffjk9PdmxPLCcGL4DTSO9zqhjOuv/g71U8lK7KYSZPD+CT73Qra+9n5C9vFNBjT2O/KS9JKNsvVEJB7xG/eQ8OYUPvcmXiL4W7dS9M 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 JZdVPXhN7zz0iZU9f4kCPh3InT2YYOU90H8cPWla+z2ReB49xHmvPYjNoT0MBX49PRYIPhvH2z25lwI+SbM4PppmhDzABxA+kAE2Pj9PeT7sWYk+bkKAPV+fJz10LFM+Xu5/PjZSgj6r/ZQ9OqsrPtbYGT7+k4Q+ePIgPoIa5Ts+ToM9wN8BPrM3gj6GPV8+G3L+PAujZ7yZ/iY+/Zo2PnT3nz7e5fk8u5THPQs6vz1FWJ893m5UPXGuJjzld3W8MsHqPYCLDT3IXDQ+r8ITvOEiEb7Wrsw98bySPdFbAj4cevy8mikmPWH/vruHVHe7m5BAPJ475rwBq7O9NsHOu1VfOrybT2m9+QWSvCHhO71p9k29LKyGPF3Uibw7Q9S8c92WvayDNr4VQky+LGOBvj7F7r1JQ6C9+dlLvsGCXb5n1lu+0WvGvSQ1qL1MBEO+ypUYvoawSb64m/O9cvxMvCGr6TytX0g9npq6Pbatbj0RfJg8F2SVPaC3mjqt2du8lCNVu4z4M 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 iDzD9JY9YfzFPbIyw7zr1Fa9Ge7cPOcnAz7aJ1S9c5g+u8mVND2dTBO95EmnvFBzir0CYVc99NkpPKHQlT3dOZQ9S4niPU0EyjyT7106WJ26velGQj2Utxy+WjI1vVeAhb14wSW9Uuw1vZwd172zVAy8VbAsO3l7kTzXeOw9sFd3PRd2XrmteBS9JXYcPSdEsL15gdm9e504vUylvb1AGDC9lgTtvSjNgL2lJ6W99d5tvU05fjwBEcS8caqvvWF2fb098wu9u7pEvLGtaT1sgMG7esYYO9YiTDtNbkw81Ej/PZgDfD1BMHw9vypbPZve8rzRp589Krq8Okngvj2UVbM8fBdxvMc9Db7fiZK8ZrRNvYPX8bvMj5C9M6NbvcRkKL20qTq9dwLkvYlZiLs6M9K9ky3UvdMrQT2cIAa9F1OnvaHcDj4zzao9QtL5PZAvnD1WPFS9+5kePmQWgzz7saw9yYCHu78m6Dy37Xg9WWZPOxCPfzzE0cw8BLCFvXY9iz1xVGy9M 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 az4qjFo84RdrPnyUxzxwI8Y9+soovTHoOz3I34M8vYufvMsHab1UvcI7978hPQOaPz062LK8aOIGPbXE+T3kR8K8Hxi8PREmgLw/L7o8kW0LPpSSAD7e+0o+oCwaPsYX+T3gdAQ+8hb5PQVhfT6qaBg+bjgEPjUF8D2Meek93jiIPg/D8D26JrE9wAzPOp0g+L2mvEG9p1mdvUw4hbxYsie9NDYivuoeJr7FNku+4o9lvVRrgbrS24K+SRA1vhdS/73rluu9Z0yVPaadjbxaAJ88mlAIvlbsJT1VSMc91fbdvW98nr38x0O+6dNDvUB2OT3kP4O+Riu4vXqjSr4HeIK9Z6gDO6RFIT5bR0M+/05IPr2SwT0XcpS9Pd8xPj0IeD5vMow+nCqEvFVGOL0S88M9hxsZPsxCEj4vqpg872ZKu3qxXb7Jyyi8efyRvYBW+b2o8yW8ZdSGvZdcOj09Nr+8oDexvT6oNr2uvtq8zfXUPCNtwT3F6le9V0WWvUVgKz3TT5q9M 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 M75abjE91x8xvWRQET0QMOg7hkR8vfaXhbzaIyK956a1vfhSGb11cd+9fsyzvY/+Dr5jkmC+B1QBvnL1/L2TS8i9OzstvpWhT75pRgO+TWh3vYzzFr4KaLG9WcFNvp8yxL2gDU49KbNcvl4+PL6KjpC+m9YVvhUI9T2Kbom+WWuivYWWhb75fUa9PZ6wPcveyj1SoPg9QmQ4vUseCD5p+0g+qKP4PEq95T3eIi29LaruPbztPD4qLoi9wHadPTqbyr1uY4k96xuVPd7ikz2e3oS8s+govWDTSD0zS3c9Gg3nPAYUKT2mM3e9cwiLPOB+uztz0GW9/fKMPeiWcL3c/F89WtSoPCNqRTwFv/k8586sPI7wnT1WOlc9o+JUPGqjBz6EUvC83miZPaX3lD2zxGm9U/y7Pem+x7xUkMI9usOnPU0kF73wMmQ8SmAmvQLporq9tds9YCbEvTYqMLzgHTO+Y6DnO2B+zD0jWES+cqLYvB3pML47lA89kKIHPeCKiL3+zy49M 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 nTwWzrk823HGPapLU7zkQ1096HenvekAoD3XCwm9EcgWuyrALT3Ustm8bDI6vSQGUjtXfUc8r86fvP8zSr3rw3M8o4Y3PZL99Txq+ui7BgpTvY0Byry1jrm9xVE4vYAVH713ZUC8jTR3vUgAib2MLby9xQk7PR1VcTwOY8C8vL3VPQBj7rxr0wq7uiGHPH9eXT3lDt68QJlmveN/AT34dr08KtjmvS/217sAFTC8eHaCPSJzozz+MsS8I4lzPd/tebvqj7K89noLvGF62T0RDQC9HbRgPaWRZz1iOpm9MOxKvTmnIT1K2p89kuSfPecRgDwaMKs9sYKaPdJvkLxN1FS9Le0jvX1Ytj0qENa86JVfPRUWZb3fHya+aWmBvSLhTj00RxA+npR2PZ4e4r02cvg9zCopPnGe7j2J4VY8n/+evOt02D1H9IM8ytPnufLrl7rw+Xu8A7BRvb77Kr3Gg0c9nlXsPH91gLxERUq95Zs6PbbCfb3icLi9444APQTyFj1iF6Q8M 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 7DuAips9VhVXvYtH8L2j1CA9vzI4PINZQT1xjLC9Cj2IvbvQNr32Olg9gW7QvKZSnbzzW9a8sT2cPHBsmzx7oPs9pJwFuzyrAL3MkGo8DKtVPeoGKT4CQaU9K5ciPREMPzxGVV09g25IPZVrODxQuT48WcyaPTlXPjv9KRI9yGNxPUkThDyMwQg9Wymyvd8nnT1BLrm7TTQxvTrod71toJ28WgpwvHaiIDzsRve8IvjfPNm9ub3c1fM8jqibPQzpYrvY14Q8Hp+hvF+gVr3dRaI8spTJvSP/sLyLlhG9F/8DvqMDHb24/s29DoQYuiVCRj06+4G9I8J2Pb4Mor2DFeS5bAfTPFwBi73NpJ28zMXcvV7JJb0bVoe8A4M9vkXanrvY1zu8DL3KPMkf4LwYJ7o80NuVPZqCHbqpPSm91UPyPDVnkTyvvgq925BPvf+vKj0vP/m8OBv3vWGjdDxT0cM9WhWFPbC9trvVfE89CjzEPXdrRD0/OjC9U7qoveuq0z2MlG69M 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 MN/NvQ9kQL2XzVe8trkVvn9yJ7zMr569TI1vu8q787vQZoO93c8FPX3c5bzvbKQ8yaiqPVLEIL3Z57c8h8s2vYeh5rsHLRg9Lg42vtIrGD3xoGu9iZd/PQgxPz1IPn+94BAQPNxkb7tf48+8JmR+POQrkj3vVSK8T6Y/PYs0Jj3aY/U73Z6HvDfoV7qsVbo9FF6zPZaJk7wDTJK85euHPWgmBL0d3xw9oI0PvGLz3j0QMUO9Je2FPGMG8TxlYqW9MaCJvCROZT22vh0+WclCPV27K7uUe/E9FxWRPSoFJz2BSiU7lK97vVFl0z1z5788jCcuO4hpO72/PBW9086kvZbrLz0QBgc+PeKTPZupCr2VdWk95WygPQ6BKD2h8ra8iQ6UuyD9tz2d2428LAIuPFokkD1M10U8gXPHvPp4C7zb+dU9sCKLPXgjkLgfeVq9HKJUPVASULym4Wq9AeIgvcIgtj2uxEI9zxxnPPpwBjzYVpO9DoKHvLfZwDy/l0Q9BG6qu5FsM 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 Aj1ryKW9Im8UvR5Nk700nJe9orpZugJCAT3R0c08QMAKOy8v1Lzmvk48OS9VvWkmRj0ZfJY9rrdBvWPiOj02Oxm9kE5wPVN3hrz5q1O9r9yyO99XkD3Prgk9ECYtPX04SLxGjGu7cBxEPZiLSz0Qsxk8sw8FPdZ7FL3P5Z08MkOlPRC/Az22V668vIQkvXOeTz2gDoe867qwPJRtaLxeOaS8viziPC16wDufMuI9K/0evKL/sLxpHNY8Eg+EPRyqxLxDJSu9jY2VvJ+vfD0GFYQ9QxZiPQxQnLoDGvM7D4qMPL3ONj2FuY89WwATPXCehL1lR908En4lPeI7H7oYjg69LLEavJbBuD3crlc8cRuBu9Osk7uAXZ25rShMvMh7vTy14cw9N6QNPZgreDovdRw96OFVPYDwqT08wxG9Bo1ZvCvPiD37aCS8uFMlPVH+eD2Sq0C7+cO6vGfQ2zuMAw4+ccwqPf0szLyPcoA9wwyHPTouaDxK1Yq7+3uWvMrcSb3oIzi6M 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 kr3R8Q49OR2RPYA657vfoM28gYOpvQ9kND5SFEc9MvA7PLiMjz1j/7a9IzarPZivADw4GQS7SmIRuyPAzbwclIk9CCEXPDEdE73liz+9Iulkvi/BJ74Ddb68jxPrvCga3b5lqqQ/3ljEPjFQAT40cbm/gKntPQTx/r4ySmC+33ysv+q+Qj8FTpC/f1ncvuvqiD52lgy/vj2EPuGXNz83UYS/UuzcvhDiS7//dPE+/lXAP37KkT9WElq/MSJav0ZgIb0=", "training_traits": {"structure_gen": "Triangle", "n_layers": 2, "max_nodes": 5, "activation_func": "LeakyReLU", "epoch_num": 4}, "classes_name": ["Cryptoadz", "Cryptopunks", "Moonbirds", "Nouns"]},m=25,b=50,y=59+11/12,w=59+11.5/12,v=60;function z(e,t){constM n=Math.log(1-t)/Math.log(1-e);return e=>1-Math.pow(1-e,n)}class V{constructor(e,t,n){const{model:r,inputDim:i}=j(t,n);this.model=r,this.inputDim=i,this.iteration=0,this.stage=0;const o=new Date(parseInt(e.birthYear),0,1).getTime(),a=new Date(parseInt(e.birthYear)+1,0,1).getTime();this.birthDate=new Date(Math.floor((o+a)/2));const l=zr.filter((t=>t[0]==e.lifeCycle))[0][2];this.growSpeed=365/l,this.cycleLength=60*l*24*3600*1e3,this.growthFunc=z(.4,.8)}updateAge(e){const t=(e.getTime()-this.birthDate.getTime())/31536M e6*this.growSpeed;this.iteration=Math.floor(t/60);const n=t-60*this.iteration;let r;this.age=n;let i,o=0;if(n<25){let e=map(n,0,25,0,1);o=this.growthFunc(e),r=(25-n)/60,this.stage=1,this.stageRatio=map(n,0,25,0,1)}else n<50?(o=1,r=(50-n)/60,this.stage=2,this.stageRatio=map(n,25,50,0,1)):n<y?(o=map(n,50,y,1,0),r=(y-n)/60,this.stage=3,this.stageRatio=map(n,50,y,0,1)):n<w?(o=0,r=(w-n)/60,this.stage=4,this.stageRatio=map(n,y,w,0,1)):n<60&&(o=0,r=(60-n)/60,this.stage=5,this.stageRatio=map(n,w,60,0,1));n<50?i=map(n,0,50,M 0,780/880):n<w?i=map(n,50,w,780/880,800/880):n<60&&(i=map(n,w,60,800/880,1)),this.nextStateTimestamp=Math.round(e.getTime()+this.cycleLength*r),this.statePercentage=round(100*i);let a=(25-n)/60;a<0&&(a+=1),this.nextStableTimestamp=Math.round(e.getTime()+this.cycleLength*a),this.growth=o,this.model.updateNeurons(o,this.iteration)}getBrainStatus(){return{totalNeurons:this.model.getTotalNeurons(),neuronsLife:this.model.getNeuronsLife(),stage:this.stage,inputDim:this.inputDim,stageRatio:this.stageRatio,age:this.age,groM wth:this.growth,nextStateTimestamp:this.nextStateTimestamp,nextStableTimestamp:this.nextStableTimestamp,rebirthCount:max(this.iteration,0),statePercentage:this.statePercentage}}classifyImage(e){const t=new G(e,1,e.length);return this.model.forward(t).mat[0]}}class M{constructor(e,t,n,r,i){this.p=e,this.v=t,this.size=n,this.shape=i,this.col=r}getRadius(){return 1==Oe?1*this.size/2:2==Oe?7*this.size/16:3==Oe||4==Oe?4*this.size/7:0}update(){this.p.add(this.v)}draw(e,t,n,r){const i=this.p.x*r,o=this.p.y*r,a=this.size*rM ,{col:l,shape:s}=this;let h,c;1==n?h=c=l:2==n?(h=dr(t,1),c=l):(h=dr(t,0),c=dr(l,1));e.stroke(dr(c,map(1,0,1,.25,1))),e.fill(dr(h,map(1,0,1,.15,1))),3==n&&e.fill(dr(h,0)),1==s?e.ellipse(i,o,a,a):2==s?e.rect(i,o,7*a/8,7*a/8):3==s&&(e.beginShape(),e.vertex(i-4*a/7,o),e.vertex(i,o-4*a/7),e.vertex(i+4*a/7,o),e.vertex(i,o+4*a/7),e.endShape(CLOSE))}}class E{constructor(e,t,n,r,i,o,a){this.center=e,this.len=t,this.angle=n,this.v=r,this.angV=i,this.c1=o,this.c2=a}getEndpoints(){const e=createVector(this.len/2*cos(this.angleM ),this.len/2*sin(this.angle));return[Vector.add(this.center,e),Vector.sub(this.center,e)]}update(){this.center.add(this.v),this.angle+=this.angV}draw(e,t){const[n,r]=this.getEndpoints(),i=n.x*t,o=n.y*t,a=r.x*t,l=r.y*t,s=this.c1,h=this.c2;var c=e.drawingContext.createLinearGradient(i,o,a,l);c.addColorStop(0,s),c.addColorStop(1,h),e.drawingContext.strokeStyle=c,e.drawingContext.globalAlpha=1,e.line(i,o,a,l),e.drawingContext.globalAlpha=1}}function S(e,t){const n=random(TAU),r=random(e,t);return createVector(r*cos(n),M r*sin(n))}class R{constructor(e,t,n,r,i){this.wall=n,this.maxR=i;const o=t.length;this.nodes=[];for(let a=0;a<o;++a){const o=[],l=.25*t[a];for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),l=S(.02*i,.05*i),s=random(10,25)*i;o.push(new M(t,l,s,e[a],r))}this.nodes.push(o)}const a=A(e);a.unshift(e[0]),a.push(e[e.length-1]),this.lines=[];for(let e=0;e<=o;++e){const r=[],l=(0==e?1:t[e-1])*(e==o?1:t[e])*1.5;for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),randoM m(n.yTop,n.yBottom)),o=random(5*i,10*i),l=random(TAU),s=S(.02*i,.05*i),h=random(2e-4,.001);r.push(new E(t,o,l,s,h,a[e],a[e+1]))}this.lines.push(r)}}reflectNode(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,{p:o,v:a}=e,l=e.getRadius();(o.x-l<t&&a.x<0||o.x+l>r&&a.x>0)&&(a.x=-a.x),(o.y-l<n&&a.y<0||o.y+l>i&&a.y>0)&&(a.y=-a.y)}reflectLine(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,[o,a]=e.getEndpoints(),l=e.v;(min(o.x,a.x)<t&&l.x<0||max(o.x,a.x)>r&&l.x>0)&&(l.x=-l.x),(min(o.y,a.y)<n&&l.y<0||max(o.y,a.M y)>i&&l.y>0)&&(l.y=-l.y)}update(){for(const e of this.lines)for(const t of e)t.update(),this.reflectLine(t);for(const e of this.nodes)for(const t of e)t.update(),this.reflectNode(t)}draw(e,t,n,r,i){const o=i/this.maxR;for(const t of this.lines){const n=t.length*r;for(let r=0;r<n;++r)t[r].draw(e,o)}for(const i of this.nodes){const a=i.length*r;for(let r=0;r<a;++r)i[r].draw(e,t,n,o)}}}function I(e,t){re(e),e.fill(0),e.rect(0,0,500,500),ie(e),e.noStroke(),e.fill(dr(cr("#000000"),.5)),e.push(),e.translate(250,250),e.scM ale(t),e.translate(-250,-250),e.beginShape(),e.vertex(235.2,24.9),e.bezierVertex(215,24.6,185,11.4,164.8,11),e.bezierVertex(147.2,10.7,129.3,10.4,112.2,14.7),e.bezierVertex(95.1,19,78.5,28.5,69.6,43.8),e.bezierVertex(57.699,64.199,61.599,90.199,70.199,112.2),e.bezierVertex(78.799,134.2,91.6,154.6,97.199,177.5),e.bezierVertex(102.499,199.2,100.899,222.5,92.799,243.2),e.bezierVertex(83,268,64.6,288.3,48.9,310),e.bezierVertex(33.2,331.7,24.5,337.5,26.599,364.1),e.bezierVertex(28.2,384.1,61.399,404.2,75.7,418.3),e.beziM erVertex(90,432.4,73.7,488.2,91.9,496.7),e.bezierVertex(124.2,511.6,159,472.5,194.3,468.1),e.bezierVertex(211.6,465.9,267.4,501.5,283.9,495.9),e.bezierVertex(340.7,476.7,298.599,428.9,355.4,409.7),e.bezierVertex(370.799,404.5,454.5,407.6,464.4,394.8),e.bezierVertex(478.599,376.3,474.7,349.3,464.299,328.4),e.bezierVertex(453.9,307.5,438.099,289.5,428.699,268.2),e.bezierVertex(412,230,419,182.6,446.1,150.9),e.bezierVertex(449.7,146.7,453.6,142.7,455.8,137.6),e.bezierVertex(459.4,129.299,457.5,119.6,454.8,111),e.bezieM rVertex(443.2,73.4,417.3,40.4,383.6,20.299),e.bezierVertex(358.1,5,343.2,-.4,313.5,0),e.bezierVertex(287.5,.4,261.6,25.4,235.2,24.9),e.endShape(),e.pop()}function C(e,t,n,r,i,o){let a,l,s;re(t),t.fill(0),t.rect(0,0,500,500),ie(t),t.noStroke(),t.fill(dr(n,.5)),1==i?(l=0,s=25,a=map(o,0,25,500,0)):a=0,t.rect(0,a,500,500),e.noStroke(),e.fill(r),e.rect(0,0,500,500),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(3M 83.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,4M 9.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,2M 51.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierM Vertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),e.fill(n),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierM Vertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99M .4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3M ,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),re(e),e.fill(r),e.beginShape(),e.vertex(184.3,473.2),e.bezierVertex(164,473.2,144.7,462.099,134,444.3),e.bezierVertex(131.7,440.5,129.1,438M .5,125,437.1),e.bezierVertex(97.3,428.1,80.5,400.6,85.2,371.8),e.bezierVertex(86.3,365.1,85.8,364.1,79.9,361.2),e.bezierVertex(57.2,349.8,46.2,323.3,54.3,299.7),e.bezierVertex(54.7,298.599,55.1,297.7,55.5,296.9),e.bezierVertex(55.6,296.599,55.8,296.4,55.9,296.099),e.vertex(57.9,291.499),e.vertex(62.5,293.599),e.bezierVertex(64.9,294.7,67.3,295.799,69.5,296.9),e.bezierVertex(74.5,299.299,79.1,301.599,83.9,303.099),e.bezierVertex(89.8,304.9,96.5,305.499,102.7,305.9),e.bezierVertex(102.8,305.9,102.9,305.9,103,305.9),eM .bezierVertex(106.6,305.9,108.9,302.799,109,299.799),e.bezierVertex(109.1,296.199,106.6,293.4,102.7,292.799),e.bezierVertex(101.3,292.599,99.9,292.4,98.4,292.299),e.bezierVertex(94.3,291.799,90.1,291.299,86,289.9),e.bezierVertex(68.9,284,56.5,270.2,52.7,252.799),e.bezierVertex(48.9,235.499,54.5,217.7,67.6,205.299),e.bezierVertex(71.9,201.299,72.7,198.1,70.8,192.399),e.bezierVertex(64.2,172.2,68.8,153.99,84.2,139.599),e.bezierVertex(94.2,130.199,105.5,125.399,117.8,125.399),e.bezierVertex(124.3,125.399,131.1,126.799M ,137.8,129.599),e.bezierVertex(157,137.399,167.9,152.799,169.4,173.99),e.vertex(169.4,174.399),e.bezierVertex(169.5,175.899,169.6,177.2,169.9,178.299),e.bezierVertex(170.7,181.2,173.2,183.2,176.1,183.2),e.bezierVertex(176.299,183.2,176.5,183.2,176.7,183.2),e.bezierVertex(180.1,182.899,182.6,180.299,182.7,177),e.bezierVertex(183.1,162,178.299,148.2,168.399,136.1),e.bezierVertex(158.2,123.5,144.899,115.8,128.799,113.199),e.bezierVertex(123.499,112.299,120.399,109.799,118.899,104.99),e.bezierVertex(113.899,89.699,120.M 699,72.299,134.899,64.499),e.bezierVertex(139.99,61.699,145.799,60.199,151.7,60.199),e.bezierVertex(162.2,60.199,171.899,64.799,178.1,72.699),e.bezierVertex(179.6,74.6,180.799,76.6,181.9,78.499),e.vertex(182.2,79.099),e.bezierVertex(183.2,80.699,185.2,83.299,188.4,83.299),e.bezierVertex(189.5,83.299,190.6,82.99,191.7,82.399),e.bezierVertex(195.1,80.599,196,76.99,194,72.799),e.bezierVertex(190.1,64.799,184.1,58.499,175.6,53.299),e.bezierVertex(174.6,52.699,173.7,52.099,172.5,51.499),e.vertex(170.5,50.299),e.vertex(1M 63,45.899),e.vertex(170.5,41.599),e.bezierVertex(182,34.99,193.1,30.799,204.4,28.599),e.bezierVertex(208.6,27.799,212.9,27.399,217.2,27.399),e.bezierVertex(217.6,27.399,217.9,27.399,218.3,27.399),e.bezierVertex(231.4,27.599,242.7,38.199,243,50.599),e.bezierVertex(243.4,64.899,243.3,78.99,243.2,93.799),e.bezierVertex(243.2,99.799,243.1,105.899,243.1,112.099),e.vertex(243.1,119.199),e.vertex(236.4,116.799),e.bezierVertex(235.7,116.499,235,116.299,234.4,115.99),e.bezierVertex(233.4,115.599,232.6,115.299,232,115.199),eM .bezierVertex(230.6,114.899,229.2,114.599,227.8,114.299),e.bezierVertex(223.8,113.499,220.1,112.699,216.4,112.499),e.vertex(216.2,112.499),e.bezierVertex(212.5,112.499,210.7,115.599,210.6,118.599),e.bezierVertex(210.4,122.399,212.7,125.099,216.4,125.399),e.bezierVertex(230.1,126.399,238.9,133.099,242.3,145.199),e.bezierVertex(243.2,148.399,243.2,151.599,243.2,154.499),e.vertex(243.2,155.099),e.bezierVertex(243.2,254.199,243.2,330,243.2,400.599),e.bezierVertex(243.2,401.99,243.2,403.4,243.2,404.9),e.bezierVertex(243M .3,411.099,243.3,417.599,242.3,423.9),e.bezierVertex(238.1,449.2,219.6,467.799,194,472.5),e.bezierVertex(190.9,472.9,187.6,473.2,184.3,473.2),e.endShape(),e.beginShape(),e.vertex(315.8,473.1),e.bezierVertex(309.3,473.1,302.8,472,296.5,469.9),e.bezierVertex(270.4,461,253.8,434.9,257.1,407.9),e.bezierVertex(260,384,273.8,366.8,297,358.3),e.bezierVertex(297.7,358.1,298.3,357.8,299,357.6),e.bezierVertex(299.8,357.3,300.6,357.1,301.2,356.8),e.bezierVertex(304.3,355.4,306,351.8,304.9,348.7),e.bezierVertex(304,345.9,301.7M ,344.2,299,344.2),e.bezierVertex(298.6,344.2,298.1,344.2,297.6,344.3),e.bezierVertex(288.1,346.3,279,350.9,269.7,358.3),e.bezierVertex(268.9,358.9,268.1,359.6,267.2,360.4),e.vertex(265.5,361.8),e.vertex(258.5,367.6),e.vertex(257.4,358.6),e.bezierVertex(257.3,358,257.3,357.5,257.2,357.1),e.bezierVertex(257,356,256.9,354.9,256.9,353.7),e.bezierVertex(256.9,334.8,256.9,316,256.9,297.1),e.bezierVertex(256.9,260.3,256.9,222.3,256.8,185),e.bezierVertex(256.8,170.7,268.3,158.8,282.5,158.4),e.bezierVertex(284.8,158.3,286.7M ,157.6,287.9,156.2),e.bezierVertex(289.099,154.9,289.599,153.2,289.5,151.3),e.bezierVertex(289.3,147.5,286.7,145.1,282.7,145.1),e.bezierVertex(282.5,145.1,282.2,145.1,282,145.1),e.bezierVertex(278.8,145.3,275.5,146.1,272,146.9),e.bezierVertex(270.9,147.2,269.8,147.4,268.6,147.7),e.bezierVertex(267.9,147.9,267,148.2,265.8,148.7),e.bezierVertex(265.1,149,264.4,149.3,263.5,149.6),e.vertex(256.8,152),e.vertex(256.8,114.6),e.bezierVertex(256.8,95,256.8,75.4,256.8,55.9),e.bezierVertex(256.8,38,267.2,27.3,284.6,27.3),e.beM zierVertex(285.3,27.3,285.9,27.3,286.6,27.3),e.bezierVertex(299,27.9,318.7,34.5,329.6,41.9),e.vertex(336.1,46.3),e.vertex(324.4,53.3),e.bezierVertex(316.2,58.2,310.2,64.6,306,72.9),e.bezierVertex(304.2,76.4,305.1,78.5,306.1,80),e.bezierVertex(307.4,81.9,309.4,83,311.6,83),e.bezierVertex(313.7,83,315.7,81.9,317.1,80.1),e.bezierVertex(317.4,79.7,317.8,79,318.1,78.4),e.bezierVertex(318.4,77.9,318.7,77.3,319,76.8),e.bezierVertex(325.3,66.2,336.3,59.9,348.5,59.9),e.bezierVertex(353.2,59.9,357.8,60.8,362.1,62.7),e.bezierM Vertex(377.6,69.3,386,86.7,381.7,103.2),e.bezierVertex(380.7,107.1,378.5,111.8,371.1,113.1),e.bezierVertex(342.7,118.1,322.2,139.1,317.8,167.8),e.bezierVertex(317.4,170.3,317.3,173.2,317.4,176.5),e.bezierVertex(317.5,180,320.1,182.8,323.5,183),e.bezierVertex(323.6,183,323.8,183,323.9,183),e.bezierVertex(327.1,183,329.8,180.6,330.3,177.2),e.bezierVertex(330.6,175.7,330.7,174,330.9,172.3),e.bezierVertex(331.1,169.8,331.4,167.3,332,164.7),e.bezierVertex(337.3,141.9,357.7,125.4,380.7,125.4),e.bezierVertex(382.5,125.4,3M 84.3,125.5,386.1,125.7),e.bezierVertex(412.8,128.9,432.6,150.9,432,176.9),e.bezierVertex(431.9,182.3,430.9,187.7,429.1,192.7),e.bezierVertex(427.2,197.9,428,201,432.3,205),e.bezierVertex(446.8,218.7,451.8,236,446.6,255),e.bezierVertex(441.4,274,428.3,286.5,408.7,291.3),e.bezierVertex(406.1,291.9,403.6,292.1,401.1,292.3),e.bezierVertex(400,292.4,398.9,292.5,397.9,292.6),e.bezierVertex(393.6,293.1,390.9,295.7,391,299.5),e.bezierVertex(391.1,303.4,394,305.8,398.5,305.8),e.bezierVertex(409.9,305.8,420.8,302.6,431.1,296M .4),e.bezierVertex(431.8,296,432.5,295.5,433.2,295.1),e.bezierVertex(433.8,294.7,434.5,294.3,435.2,293.9),e.bezierVertex(436,293.4,436.6,293.2,437.2,293.1),e.bezierVertex(437.4,293,437.7,292.9,438.1,292.8),e.vertex(442.5,291.4),e.vertex(444.2,295.7),e.bezierVertex(450.9,312.4,449.5,328.4,440,343.4),e.bezierVertex(435.3,350.8,428.7,356.7,420.2,361.1),e.bezierVertex(414.3,364.1,413.7,365.2,414.8,371.7),e.bezierVertex(419.5,400.2,403,427.6,375.6,436.9),e.bezierVertex(371,438.5,368.3,440.7,365.8,444.7),e.bezierVertex(3M 55.2,462.5,336.4,473.1,315.8,473.1),e.bezierVertex(315.8,473.1,315.8,473.1,315.8,473.1),e.endShape(),ie(e),e.fill(n),e.beginShape(),e.vertex(120.2,279.9),e.bezierVertex(117.9,279.9,112.4,279.299,112.2,273.599),e.bezierVertex(112,267.7,117.4,266.7,119.7,266.599),e.bezierVertex(133.1,265.799,143.1,259.499,149.3,247.899),e.bezierVertex(149.6,247.299,150.1,246.399,150.3,245.399),e.bezierVertex(150.6,244.299,150.5,243.299,150.5,242.7),e.bezierVertex(150.5,242.6,150.5,242.5,150.5,242.299),e.vertex(150.3,238.799),e.vertexM (141.1,235.99),e.bezierVertex(114.6,227.799,95.6,202.499,95.9,175.799),e.bezierVertex(95.9,173.99,96.4,168.199,102.2,168.199),e.bezierVertex(102.6,168.199,103,168.199,103.4,168.299),e.bezierVertex(104.8,168.499,108.2,168.899,109.2,175.599),e.bezierVertex(109.3,176.599,109.5,177.599,109.6,178.499),e.bezierVertex(110.4,184.199,111.3,189.99,113.7,195.499),e.bezierVertex(121.9,213.99,139.5,225.499,159.7,225.499),e.bezierVertex(172.1,225.499,184.1,220.899,193.5,212.599),e.bezierVertex(194,212.199,194.4,211.799,194.8,211M .399),e.bezierVertex(195.1,211.099,195.5,210.799,195.8,210.399),e.bezierVertex(197.4,208.99,199.2,208.2,200.9,208.2),e.bezierVertex(202.5,208.2,204,208.899,205.3,210.1),e.bezierVertex(208,212.9,207.9,216.9,205,219.9),e.bezierVertex(196.5,228.6,186.3,234.3,174.7,236.8),e.bezierVertex(168.799,238.1,165.6,241,163.899,246.7),e.bezierVertex(158.3,265.9,139.9,279.7,120.2,279.9),e.vertex(120.2,279.9),e.endShape(),e.beginShape(),e.vertex(187.2,427.5),e.bezierVertex(183.799,427.5,181.299,425.3,180.799,422),e.bezierVertex(18M 0.6,420.8,180.499,419.5,180.399,418.1),e.bezierVertex(180.299,417,180.2,415.8,180.099,414.7),e.bezierVertex(177.199,390.5,156.699,371.3,132.399,370.2),e.bezierVertex(131.99,370.2,131.499,370.2,131.099,370.2),e.bezierVertex(130.699,370.2,130.299,370.2,129.799,370.2),e.bezierVertex(125.99,369.9,123.199,367.2,123.099,363.6),e.bezierVertex(122.99,360.2,125.799,357.3,129.599,356.9),e.bezierVertex(130.499,356.8,131.499,356.8,132.599,356.7),e.bezierVertex(133.199,356.7,133.799,356.7,134.399,356.6),e.vertex(138.299,356.4),M e.vertex(139.1,352.6),e.bezierVertex(139.5,350.7,139.799,348.9,140.2,347),e.bezierVertex(140.899,343.4,141.5,340,142.399,336.8),e.bezierVertex(150.099,310.7,174.399,292,201.399,291.3),e.vertex(201.599,291.3),e.bezierVertex(203.699,291.3,206.299,292,208.299,293.2),e.bezierVertex(210.499,294.5,210.699,297.5,209.99,299.8),e.bezierVertex(209.499,301.5,208.199,303.9,203.299,304.7),e.bezierVertex(202.199,304.9,200.99,305,199.799,305.2),e.bezierVertex(194.499,305.9,188.99,306.599,183.799,308.9),e.bezierVertex(165.499,316.M 799,155.199,331.299,152.99,352),e.bezierVertex(152.399,357.8,154.499,361.7,159.699,364.5),e.bezierVertex(178.199,374.4,189.399,390,193.099,410.9),e.bezierVertex(193.699,414.299,193.899,418,193.599,422),e.bezierVertex(193.399,425.2,190.899,427.5,187.399,427.5),e.vertex(187.2,427.5),e.endShape(),e.beginShape(),e.vertex(364.3,281.1),e.bezierVertex(346.3,280.6,332.9,272.8,323.5,257),e.bezierVertex(321.6,253.9,320.4,250.2,319.2,246.7),e.bezierVertex(317.7,242.2,315,239.799,310.5,238.799),e.bezierVertex(298.5,236.299,288M ,230.7,279.4,222.1),e.bezierVertex(276.7,219.4,274.9,215.299,278,211.9),e.bezierVertex(279.4,210.3,281,209.6,282.6,209.6),e.bezierVertex(284.4,209.6,286.4,210.6,288.3,212.5),e.bezierVertex(297.8,221.8,310.4,226.9,323.9,226.9),e.bezierVertex(340.2,226.9,355.1,219.3,364.8,206.2),e.bezierVertex(371,197.8,374.2,188.5,374.5,178.5),e.vertex(374.5,177.9),e.bezierVertex(374.5,177,374.5,176.1,374.7,175.4),e.bezierVertex(375.3,171.8,377.9,169.5,381.3,169.5),e.bezierVertex(381.4,169.5,381.5,169.5,381.7,169.5),e.bezierVertex(3M 85.4,169.7,388,172.4,388,176.1),e.bezierVertex(388.1,190.7,383.4,204,374.2,215.8),e.bezierVertex(365.8,226.5,354.7,233.9,341.2,237.9),e.bezierVertex(340,238.3,338.7,238.6,337.3,239.1),e.bezierVertex(335.9,239.6,335.1,240.4,334.7,240.9),e.bezierVertex(334.599,241,334.5,241.1,334.4,241.2),e.vertex(331.799,243.6),e.vertex(333.199,246.8),e.bezierVertex(338.199,258,346.799,264.9,358.699,267.3),e.bezierVertex(360.199,267.6,361.599,267.7,362.99,267.9),e.bezierVertex(363.599,268,364.299,268,364.899,268.1),e.bezierVertex(36M 9.099,268.6,371.799,271.4,371.499,275),e.bezierVertex(371.199,278.6,368.299,281.2,364.399,281.2),e.vertex(364.3,281.1),e.endShape(),e.beginShape(),e.vertex(323.9,437),e.bezierVertex(323.7,437,323.5,437,323.299,437),e.bezierVertex(319.599,436.7,317.299,434.1,317.4,430.2),e.bezierVertex(317.9,406.099,328.299,388,349.5,375),e.bezierVertex(350.7,374.2,352,373.5,353.4,372.8),e.bezierVertex(354.099,372.4,354.7,372.1,355.299,371.7),e.vertex(357.499,370.5),e.vertex(357.799,368),e.bezierVertex(360.4,346.6,345.199,323.7,323.M 9,317),e.bezierVertex(319.099,315.5,314.099,314.9,309.299,314.4),e.vertex(308.199,314.299),e.bezierVertex(305.99,314.099,300.799,312.9,300.899,307.299),e.bezierVertex(300.99,303.499,303.899,300.9,308.099,300.9),e.vertex(308.299,300.9),e.bezierVertex(327.099,301.299,343.099,308.7,355.699,322.9),e.bezierVertex(364.299,332.5,369.399,344.099,370.99,357.299),e.bezierVertex(371.099,358.4,371.299,359.4,371.499,360.499),e.bezierVertex(371.599,360.99,371.699,361.499,371.799,361.99),e.vertex(372.499,365.899),e.vertex(377.899M ,366.199),e.bezierVertex(378.799,366.299,379.699,366.299,380.599,366.399),e.bezierVertex(385.099,366.699,387.899,369.399,387.799,373.299),e.bezierVertex(387.699,377.099,384.99,379.599,380.799,379.799),e.bezierVertex(369.799,380.199,359.99,383.299,351.899,389.299),e.bezierVertex(338.799,398.799,331.699,411.699,330.699,427.499),e.vertex(330.699,428.299),e.bezierVertex(330.599,429.199,330.599,430.099,330.499,430.799),e.bezierVertex(330,434.7,327.5,437,323.9,437),e.endShape()}function T(e){return e[0].map(((t,n)=>e.mapM ((e=>e[n]))))}function A(e){return e.map((e=>Array.isArray(e)?A(e):e))}function D(e,t){return floor(random(e,t))}function k(e){let t=0;for(const n of e)t+=n[1];let n=random(t),r=0;for(const t of e)if(r+=t[1],n<r)return t[0];return null}function L(e){for(let t=1;t<e.length;++t){let n=D(0,t),r=e[t];e[t]=e[n],e[n]=r}}function P(e){return null==e||""===e}function O(e){return new Promise((t=>setTimeout(t,e)))}function F(e,t,n){let r=0;for(let i=1;i<=1e3;++i)for(let o=1;o<=1e3;++o)if(e*o%(t*i)==0){let e=1*i/o;abs(e-n)<abM s(r-n)&&(r=e)}return r}function N(){let e=60*(new Date).getTimezoneOffset()*1e3;return new Date(Date.now()-e).toISOString().slice(0,-1)}function B(e,t,n){let r;if(push(),textSize(e),textWidth(t)<=n)r=t;else for(let e=0;e<t.length;++e){const i=t.slice(0,e+1)+"...";if(textWidth(i)>n){r=i;break}}return pop(),r}function Y(e){var t=e%10,n=e%100;return 1==t&&11!=n?e+"st":2==t&&12!=n?e+"nd":3==t&&13!=n?e+"rd":e+"th"}class G{constructor(e,t,n){this.n=t,this.m=n,this.mat=[];let r=0;for(let t=0;t<this.n;++t){this.mat.push([]M );for(let n=0;n<this.m;++n)this.mat[t].push(r<e.length?e[r]:0),r+=1}return this}copy(){return new G(this.mat.flat(),this.n,this.m)}}class H{static __linear=e=>e;static __relu=e=>Math.max(e,0);static __leaky_relu=e=>e>0?e:.2*e;static __sigmoid=e=>1/(1+Math.exp(-e));static __tanh=e=>Math.tanh(e);static __apply_unary_op(e,t){const n=e.copy();for(let e=0;e<n.n;++e)for(let r=0;r<n.m;++r)n.mat[e][r]=t(n.mat[e][r]);return n}static linear=e=>H.__apply_unary_op(e,H.__linear);static relu=e=>H.__apply_unary_op(e,H.__relu);staM tic leaky_relu=e=>H.__apply_unary_op(e,H.__leaky_relu);static sigmoid=e=>H.__apply_unary_op(e,H.__sigmoid);static tanh=e=>H.__apply_unary_op(e,H.__tanh);static __add=(e,t)=>e+t;static __mul=(e,t)=>e*t;static __apply_binary_op=(e,t,n)=>{"object"!=typeof t&&(t=new G([t],1,1));const r=e.copy();for(let e=0;e<r.n;++e)for(let i=0;i<r.m;++i)r.mat[e][i]=n(r.mat[e][i],t.mat[e%t.n][i%t.m]);return r};static mul=(e,t)=>H.__apply_binary_op(e,t,H.__mul);static add=(e,t)=>H.__apply_binary_op(e,t,H.__add);static matMul(e,t){const M n=new G([],e.n,t.m);for(let r=0;r<n.n;++r)for(let i=0;i<n.m;++i)for(let o=0;o<e.m;++o)n.mat[r][i]+=e.mat[r][o]*t.mat[o][i];return n}static softmax(e){const t=H.__apply_unary_op(e,(e=>Math.exp(e))),n=t.mat.flat().reduce(((e,t)=>e+t));for(let r=0;r<e.n;++r)for(let i=0;i<e.m;++i)t.mat[r][i]/=n;return t}}class ${constructor(e,t){this.scale=e,this.offset=t}forward(e){return H.add(H.mul(e,this.scale),this.offset)}}class X{constructor(){}forward(e){return e.map((e=>e.flat()))}}class W{constructor(e,t,n,r){this.out_dim=e,tM his.activation=t,this.w=n,this.b=r}forward(e){const t=H.add(H.matMul(e,this.w),this.b);return null==this.activation?t:this.activation(t)}}class U{constructor(e,t,n){this.preprocessLayers=e,this.hiddenLayers=t,this.outputLayer=n,this.totalNeurons=this.hiddenLayers.map((e=>e.out_dim)),this.currentOrders=[],this.currentIteration=null}updateNeurons(e,t){if(t!=this.currentIteration){this.currentOrders=[];for(let e=0;e<this.totalNeurons.length;++e){randomSeed(100*(t+1)+e);const n=[];for(let t=0;t<this.totalNeurons[e];++tM )n.push(t);L(n),this.currentOrders.push(n)}this.currentIteration=t}const n=A(this.totalNeurons),r=n.reduce(((e,t)=>e+t))*(1-e);for(let e=0;e<r;++e){const t=n.map(((e,t)=>(e-1)/this.totalNeurons[t]));n[t.map(((e,t)=>[e,t])).reduce(((e,t)=>t[0]>e[0]?t:e))[1]]-=Math.min(r-e,1)}this.neuronsLife=[];for(let e=0;e<n.length;++e){const t=this.currentOrders[e],r=Array(this.totalNeurons[e]).fill(0);for(let i=0;i<n[e];++i)r[t[i]]=Math.min(n[e]-i,1);this.neuronsLife.push(r)}}getTotalNeurons(){return A(this.totalNeurons)}getNeurM onsLife(){return A(this.neuronsLife)}forward(e){for(const t of this.preprocessLayers)e=t.forward(e);for(const[t,n]of this.hiddenLayers.entries()){e=n.forward(e);const r=new G(this.neuronsLife[t],1,e.m);e=H.mul(e,r)}return e=this.outputLayer.forward(e),H.softmax(e)}}function q(e){switch(e){case"relu":return H.relu;case"sigmoid":return H.sigmoid;case"tanh":return H.tanh;case"leaky_relu":return H.leaky_relu;default:return H.linear}}function j(e,t){const n=[],r=[],i=Z(t);let o=null,a=0,l=[];for(const t of e.config.layeM rs)if("InputLayer"==t.class_name)o=t.config.batch_input_shape.slice(1),l=o;else if("Rescaling"==t.class_name)n.push(new $(t.config.scale,t.config.offset));else if("Flatten"==t.class_name)o=[o.reduce(((e,t)=>e*t))];else if("Dense"==t.class_name){const e=[t.config.units],n=o[0]*e[0],l=e[0],s=i.subarray(a,a+n);a+=n;const h=i.subarray(a,a+l);a+=l;const c=new G(s,o[0],e[0]),u=new G(h,1,e[0]),f=q(t.config.activation);r.push(new W(e[0],f,c,u)),o=e}const s=r.pop();return{model:new U(n,r,s),inputDim:l}}function Z(e){const tM =window.atob(e),n=t.length/Float32Array.BYTES_PER_ELEMENT,r=new DataView(new ArrayBuffer(Float32Array.BYTES_PER_ELEMENT)),i=new Float32Array(n);let o=0;for(let e=0;e<n;e++){o=4*e;for(let e=0;e<4;++e)r.setUint8(e,t.charCodeAt(o+e));i[e]=r.getFloat32(0,!0)}return i}class K{constructor(e){this.elt=e,this._events={},this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight}position(){if(0===arguments.length)return{x:this.elt.offsetLeft,y:this.elt.offsetTop};var e="absolute";return"static"!==arguments[2]&&"fixedM "!==arguments[2]&&"relative"!==arguments[2]&&"sticky"!==arguments[2]&&"initial"!==arguments[2]&&"inherit"!==arguments[2]||(e=arguments[2]),this.elt.style.position=e,this.elt.style.left=arguments[0]+"px",this.elt.style.top=arguments[1]+"px",this.x=arguments[0],this.y=arguments[1],this}show(){return this.elt.style.display="block",this}hide(){return this.elt.style.display="none",this}size(e,t){if(0===arguments.length)return{width:this.elt.offsetWidth,height:this.elt.offsetHeight};var n=e,r=t;if(n!==te||r!==te){if(n===M te?n=t*this.width/this.height:r===te&&(r=e*this.height/this.width),this.elt instanceof HTMLCanvasElement){var i,o={},a=this.elt.getContext("2d");for(i in a)o[i]=a[i];for(i in this.elt.setAttribute("width",n*this._pInst._pixelDensity),this.elt.setAttribute("height",r*this._pInst._pixelDensity),this.elt.style.width=n+"px",this.elt.style.height=r+"px",this._pInst.scale(this._pInst._pixelDensity,this._pInst._pixelDensity),o)this.elt.getContext("2d")[i]=o[i]}else this.elt.style.width=n+"px",this.elt.style.height=r+"px",M this.elt.width=n,this.elt.height=r;this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight,this._pInst&&this._pInst._curElement&&this._pInst._curElement.elt===this.elt&&(this._pInst._setProperty("width",this.elt.offsetWidth),this._pInst._setProperty("height",this.elt.offsetHeight))}return this}style(e,t){if(t instanceof Color&&(t="rgba("+t.levels[0]+","+t.levels[1]+","+t.levels[2]+","+t.levels[3]/255+")"),void 0===t){if(-1===e.indexOf(":"))return window.getComputedStyle(this.elt).getPropertyValue(e);for(vM ar n=e.split(";"),r=0;r<n.length;r++){var i=n[r].split(":");i[0]&&i[1]&&(this.elt.style[i[0].trim()]=i[1].trim())}}else if(this.elt.style[e]=t,"width"===e||"height"===e||"left"===e||"top"===e){var o=window.getComputedStyle(this.elt).getPropertyValue(e).replace(/[^\d.]/g,"");this[e]=Math.round(parseFloat(o,10))}return this}value(){return arguments.length>0?(this.elt.value=arguments[0],this):"range"===this.elt.type?parseFloat(this.elt.value):this.elt.value}mouseClicked(e){return this._adjustListener("click",e,this),tM his}isFocused(){return document.activeElement===this.elt}_adjustListener(e,t,n){return!1===t?this._detachListener(e,n):this._attachListener(e,t,n),this}_attachListener(e,t,n){n._events[e]&&this._detachListener(e,n);var r=t.bind(n);n.elt.addEventListener(e,r,!1),n._events[e]=r}_detachListener(e,t){var n=t._events[e];t.elt.removeEventListener(e,n,!1),t._events[e]=null}}function J(e,t){var n=document.createElement("button");return n.innerHTML=e,t&&(n.value=t),ee(n)}function Q(e){var t=arguments.length>1&&void 0!==arguM ments[1]&&arguments[1],n=function(t){var n=!0,r=!1,i=void 0;try{for(var o,a=t.target.files[Symbol.iterator]();!(n=(o=a.next()).done);n=!0){var l=o.value;File._load(l,e)}}catch(e){r=!0,i=e}finally{try{n||null==a.return||a.return()}finally{if(r)throw i}}};if(window.File&&window.FileReader&&window.FileList&&window.Blob){var r=document.createElement("input");return r.setAttribute("type","file"),t&&r.setAttribute("multiple",!0),r.addEventListener("change",n,!1),ee(r)}}function ee(e){return document.body.appendChild(e),nM ew K(e)}createImg=function(){var e,t=document.createElement("img"),n=arguments;return n.length>1&&"string"==typeof n[1]&&(t.alt=n[1]),n.length>2&&"string"==typeof n[2]&&(t.crossOrigin=n[2]),t.src=n[0],e=ee(t,this),t.addEventListener("load",(function(){e.width=t.offsetWidth||t.width,e.height=t.offsetHeight||t.height;var r=n[n.length-1];"function"==typeof r&&r(e)})),e},createInput=function(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:"",t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:"text"M ,n=document.createElement("input");return n.setAttribute("value",e),n.setAttribute("type",t),ee(n,this)};const te="auto";function ne(e){re(e);const t=e._rectMode;e.rectMode(CORNER),e.rect(0,0,e.width,e.height),e.rectMode(t),ie(e)}function re(e){e.push(),e.fill(255,255,255,255),e.blendMode(REMOVE)}function ie(e){e.blendMode(BLEND),e.pop()}File=function(e,t){this.file=e,this._pInst=t;var n=e.type.split("/");this.type=n[0],this.subtype=n[1],this.name=e.name,this.size=e.size,this.data=void 0},File._createLoader=functioM n(e,t){var n=new FileReader;return n.onload=function(n){var r=new File(e);if("application/json"===r.file.type)r.data=JSON.parse(n.target.result);else if("text/xml"===r.file.type){var i=(new DOMParser).parseFromString(n.target.result,"text/xml");r.data=new XML(i.documentElement)}else r.data=n.target.result;t(r)},n},File._load=function(e,t){if(/^text\//.test(e.type)||"application/json"===e.type)File._createLoader(e,t).readAsText(e);else if(/^(video|audio)\//.test(e.type)){var n=new File(e);n.data=URL.createObjectURL(M e),t(n)}else File._createLoader(e,t).readAsDataURL(e)},XML=function(e){if(e)this.DOM=e;else{var t=document.implementation.createDocument(null,"doc");this.DOM=t.createElement("root")}},document.addEventListener("DOMContentLoaded",(function(){addEventListener("mousemove",(e=>{window.mouseX=e.pageX,window.mouseY=e.pageY}))})),new e("global");const oe="365";let ae,le,se,he,ce,ue,fe,de,xe,ge,pe,me,be,ye,we,ve,ze,Ve,_e,Me,Ee,Se,Re,Ie,Ce,Te,Ae,De,ke,Le,Pe,Oe,Fe,Ne,Be,Ye,Ge,He,$e,Xe,We,Ue,qe,je,Ze,Ke,Je,Qe,et,tt,nt,rt,it,oM t,at,lt,st,ht,ct,ut,ft,dt,xt,gt,pt,mt,bt,yt,wt,vt,zt,Vt,_t,Mt,Et,St,Rt,It,Ct,Tt,At=!1,Dt=!1,kt=!0,Lt=!1,Pt=!1;const Ot=[" ","Growing","Stable","Decaying","Dead","Rebirth"];let Ft,Nt,Bt,Yt,Gt,Ht,$t,Xt,Wt,Ut,qt,jt,Zt,Kt,Jt,Qt,en,tn,nn,rn,on,an,ln,sn,hn=0,cn=0,un=0,fn=!1,dn=!0,xn=!0,gn=null,pn=null,mn=null,bn=!1,yn=!1,wn=null,vn=null,zn=!1;async function setup(){let e=windowWidth,t=windowHeight;createCanvas(e,t),et=createGraphics(e,t),Xe=createGraphics(e,t),$e=createGraphics(e,t),We=createGraphics(e,t),Ue=createGraphiM cs(e,t),qe=createGraphics(e,t),Qe=createGraphics(e,t),je=createGraphics(e,t),Ze=createGraphics(e,t),Ke=createGraphics(e,t),Je=createGraphics(e,t),tt=createGraphics(500,500),nt=createGraphics(500,500),rt=createGraphics(500,500),_n(),Mn(),Sn(),await En(),Gn(),Rn(),bn=!0}function _n(){Et=parseInt(oe),randomSeed(Et),noiseSeed(Et)}function Mn(){Wt=Ir(p.training_traits),Cr(Wt)}async function En(){let e;Jt=r(),Qt=o(),[Xt,e]=await Promise.all([s(Jt),h(Qt)]),Ut=new V(Wt.visual,e.layers_config,e.weight_b64),Ut.updateAge(new M Date),_n(),Wt.training=e.training_traits,Ht=e.model_name,$t=e.classes_name}function Sn(){le=min(width,height)/1024,ut=Rr.findIndex((e=>e[0]===Wt.visual.colorPalette)),ft=[["#ffffff","#231f20","#231f20"],["#231f20","#ffffff","#ffffff"],["#104da8","#ffffff","#ffffff"],["#722F1F","#FCE1B2","#FCE1B2"],["#e88120","#f9f2e5","#f9f2e5"],["#f6b941","#2E2E2E","#2E2E2E"],["#45daaa","#012221","#012221"],["#F1F1F1","#328DFE","#328DFE"],["#111822","#D3EB8D","#D3EB8D"],["#713FF9","#D6D5E6","#D6D5E6"],["#FBDA9D","#795106","#795106M "],["#8f5b62","#ead0d0","#ead0d0"],["#eae4cb","#508cac","#508cac"],["#ffc6cc","#cc313d","#cc313d"],["#60A900","#E0FE00","#E0FE00"],["#507DBE","#D0D1D3","#D0D1D3"],["#305848","#E8F2EE","#E8F2EE"],["#2a2634","#5b6988","#cb78a2","#5b6988"],["#590e29","#fd5e53","#fd5e53","#ffe373"],["#0a141d","#57d4e4","#328195","#2A9ECF","#0ab6a8","#57d4e4"],["#3a2d28","#d5c2ac","#df6338","#3d9895","#d5c2ac"],["#030706","#77c4d9","#77c4d9","#77c4d9","#ffffff","#ffffff","#e72020","#e72020"],["#3a4664","#92f5ff","#f9ff94","#eaa0a2","#55M dde0"],["#fbfaff","#f04bb1","#f04bb1","#fac373","#82cef0","#8b31ce"],["#000000","#ffffff","#ff0002","#f26522","#fdff00","#00ff03","#01fffe","#0000ff","#ff00ff"]];for(let e=0;e<ft.length;++e)for(let t=0;t<ft[e].length;++t)ft[e][t]=cr(ft[e][t]);pt=[],ct=ft[ut][0],st=ft[ut][1]}function Rn(){gn=document.querySelector("#upload"),pn=document.querySelector("#inputUpload"),gn.addEventListener("dblclick",(()=>{if(!Lt&&!yn)if(In(Ie)&&cn==Ve-1)pn.click();else{if(4!=Pe&&5!=Pe&&(In(Ie)||cn!=Ve-1))return;fn=!0,dn=!0,Bt=0,un=0}})M ),pn.addEventListener("click",(()=>{pn.value=null,gn.style.display="block"})),pn.addEventListener("change",(()=>{const[e]=pn.files;e?(se=null,gn.style.display="none",Tn(URL.createObjectURL(e)),mn=e):gn.style.display="block"}))}function In(e){for(let t=0;t<e.length;++t){let n=0;for(let r=0;r<e[t].length;++r)e[t][r]>0&&++n;if(0==n)return!1}return!0}function Cn(){null!=se&&(un=0,Pt=!0,he=0,ue=0,drewLineAnim=!0,ce=(ae/2+we/2)/le,loadImage(se.elt.src,(e=>{const[t,n,r]=Gt,i=createGraphics(t,n);i.image(e,0,0,t,n),i.loadPiM xels();const o=i.pixels.filter(((e,t)=>t%4!=3)),a=Ut.classifyImage(o);Zt=T([a,$t.map((e=>e.toUpperCase()))]).sort(((e,t)=>e[0]>t[0]?-1:1))})))}function Tn(e){se=createImg(e,""),se.hide(),Cn()}function An(){zn||(ce+=(width-ae-we)/tn/le),re(Xe),Xe.rect(ce*le,0,width,height),ie(Xe),un>=ge&&1==kt&&(kt=!1,un-=ge),kt&&(re($e),$e.strokeWeight(2*Fe),Jn(he,ze,ct,ct,$e),ie($e)),un>=ge&&0==kt&&(kt=!0,un-=ge,he+=1,he==en&&(++ue,he=0,ce=(ae/2+we/2)/le,1==ue&&(Pt=!1,Dn(),ye=millis())))}function Dn(){At=!0,pe=!1,me=!1,tryButton=bM r("Try Again",width/2-225*le,height/2+265*le,290*le,40*le,kn),closeResultButton=br("Close",width/2+75*le,height/2+265*le,150*le,40*le,Ln)}function kn(){At=!1,tryButton.hide(),closeResultButton.hide(),pn.click()}function Ln(){Yt=!0,At=!1,Gn(),tryButton.hide(),closeResultButton.hide(),gn.style.display="block",se=null}function keyTyped(){bn&&!1===yn&&!1===yr()&&("i"!==key&&"I"!==key||(Dt=!Dt),"b"!==key&&"B"!==key||(xn=!xn),"s"!==key&&"S"!==key||!1!==Lt||saveCanvasAtCurrentTime(),"k"!==key&&"K"!==key||!1!==Lt||save4KCaM nvasAtCurrentTime(),"u"!==key&&"U"!==key||!1!==Lt||!1!==At||!1!==fn||!1!==Pt||On())}function On(){Lt=!0,wn=null,vn=null,submitButton=br("Submit",width/2-155*le,height/2+115*le,150*le,40*le,Fn),closeSettingButton=br("Close",width/2+5*le,height/2+115*le,150*le,40*le,Yn),vt=createInput(),vt.position(width/2-252.5*le,height/2-40*le),vt.size(500*le,25*le),vt.style("font-size","15px"),vt.value(Jt||""),zt=createInput(),zt.position(width/2-252.2*le,height/2+35*le),zt.size(500*le,25*le),zt.style("font-size","15px"),zt.valueM (Qt||"")}function Fn(){Vt=vt.value(),_t=zt.value(),submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide(),Lt=!1,yn=!0,Nn()}async function Nn(){[wn,vn,_]=await Promise.all([c(Vt),u(_t),O(1e3)]),yn=!1,wn&&vn?(n(Vt),i(_t),window.location.reload()):(Lt=!0,submitButton.show(),closeSettingButton.show(),vt.show(),zt.show())}function Bn(){Je.textFont("Trebuchet MS"),Je.noStroke(),pr(Je,600*le,200*le),Je.strokeWeight(1*le),Je.stroke(xt),Je.fill(xt),Je.textSize(50*le),Je.text("update()",width/2,height/2+2.5*le)}fuM nction Yn(){wn=null,vn=null,Lt=!1,submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide()}function Gn(){_n(),nn=Date.now(),pe=!1,me=!1,St=Wt.training.structure_gen,Rt=Wt.visual.birthYear,It=Wt.visual.lifeCycle,Ct=Wt.training.epoch_num,Tt=Wt.training.activation_func,Ft=Mr.findIndex((e=>e[0]==Wt.visual.hardwareAcceleration))+1,1==Ft?(Nt=30,fe=40):2==Ft?(Nt=15,fe=20):(Nt=2,fe=10);const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.neM xtStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),ae=100*le,ht=50*le,Oe=Sr.findIndex((e=>e[0]==Wt.visual.nodeShape))+1,dt=Er.findIndex((e=>e[0]==Wt.visual.nodeFill))+1,lt=_r.findIndex((e=>e[0]==Wt.visual.pattern))+1,de=Math.tanh(Math.log10(Xt.avgfeerate)),de=map(M de,0,1,.2,.8),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;CM e[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,M 2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,at=.7,pt=[],xt=ft[ut][2],gt=ft[ut][ft[ut].length-1];for(let e=3;e<ft[ut].length-1;e++)pt.push(ft[ut][e]);mt=sr(xt,gt,pt,width),bt=[],wt=[],yt=width/(Ve-1);for(let e=0;e<Ve;e++)bt.push(hr(mt,yt*e/width)),wt.push(hr(mt,yt*e/width));wt.unshift(bt[0]),wt.pushM (bt[bt.length-1]),hn=0,cn=0,un=0,Yt=!0;const n={xLeft:ae/8,xRight:width-ae/8,yTop:ae/8,yBottom:height-ae/8},r=Ce.map((e=>e.length));jt=new R(bt,r,n,Oe,le)}function Hn(e,t){let n=Ce[e].length;return[e*we+we/2+ae/2,height/2-(n-1)/2*ve+t*ve]}function $n(e,t){le=min(e,t)/1024,ae=100*le,ht=50*le,we=(e-ae)/Ve,ve=(t-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}xe=floor(De.length*de),Le=[],ke=[],ge=floor(map(de,.2,.8,15M ,2));for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,mt=sr(xt,gt,pt,e),bt=[],wt=[],yt=e/(Ve-1);for(let t=0;t<Ve;t++)bt.push(hr(mt,yt*t/e)),wt.push(hr(mt,yt*t/e));wt.unshift(bt[0]),wt.push(bt[bt.length-1])}function Xn(){const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.age,M window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:AeM *=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)M Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,M 1,1,10)*le}function Wn(){jt.update();const e=4==Pe?0:Kt;jt.draw(Qe,ct,dt,e,le)}function Un(){if(!bn)return ar(),void et.image(je,0,0);if(4==Pe||5==Pe)return Wn(),void et.image(Qe,0,0);un>=Nt&&hn<Ve&&(hn++,un=0);for(let e=0;e<hn;e++)1==dt?it=ot=bt[e]:(it=ct,ot=bt[e]),Kn(e,it,ot,$e);un>=Nt&&cn<Ve-1&&(cn++,un=0);for(let e=0;e<cn;e++)Zn(e)}function qn(){et.background(ct),Ue.background(255),Ue.rectMode(CENTER),ne(Ue),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),Ue.stroke(st),Ue.strokeWeight(8*le),Ue.fill(ct),Qe.backgrM ound(255),Qe.rectMode(CENTER),ne(Qe),Qe.strokeWeight(le),qe.background(255),qe.rectMode(CENTER),ne(qe),qe.textAlign(LEFT),$e.background(255),$e.rectMode(CENTER),ne($e),Xe.background(255),ne(Xe),Xe.strokeWeight(Ne),We.background(255),We.rectMode(CENTER),ne(We),We.fill(st),We.stroke(st),We.strokeWeight(.1*le),er(lt),We.noStroke(),xn&&(We.rect(ae/16,height/2,ae/8,height),We.rect(width-ae/16,height/2,ae/8,height),We.rect(width/2,ae/16,width,ae/8),We.rect(width/2,height-ae/16,width,ae/8)),Ze.background(255),Ze.rectMode(M CENTER),ne(Ze),Ze.textAlign(CENTER,CENTER),Ze.textStyle(BOLD),Ze.stroke(st),Ze.strokeWeight(8*le),Ze.fill(ct),je.background(255),je.rectMode(CENTER),ne(je),je.textAlign(CENTER,CENTER),je.textStyle(BOLD),Ke.background(255),Ke.rectMode(CENTER),ne(Ke),Ke.textAlign(CENTER,CENTER),Ke.textStyle(BOLD),Ke.stroke(st),Ke.strokeWeight(8*le),Ke.fill(ct),Je.background(255),Je.rectMode(CENTER),ne(Je),Je.textAlign(CENTER,CENTER),Je.textStyle(BOLD),Je.stroke(st),Je.strokeWeight(8*le),Je.fill(ct),Un(),et.image(We,0,0),Pt&&An(),et.iM mage(Xe,0,0),et.image($e,0,0),At&&(tr(),et.image(Ue,0,0)),fn&&(lr(),et.image(Ze,0,0)),Lt&&(or(),et.image(Ke,0,0)),Dt&&(ir(),et.image(qe,0,0)),yn&&(Bn(),et.image(Je,0,0))}function draw(){const e=Date.now();bn&&(Ut.updateAge(new Date(e)),Xn()),qn(),image(et,0,0),zn||un++}function Zn(e){let t,n=Ce[e].length,r=Ce[e+1].length;for(let i=0;i<n;i++){const[n,o]=Hn(e,i);for(let a=0;a<r;a++){const[r,l]=Hn(e+1,a);t=map(min(Ce[e][i],Ce[e+1][a]),0,1,0,.5),ur(n,o,r,l,bt[e],bt[e+1],Xe,t)}}}function Kn(e,t,n,r){let i,o,a,l=Ce[e].leM ngth;for(let s=0;s<l;s++){const[l,h]=Hn(e,s);i=Ce[e][s],a=map(Be,1/30,1,3,10),o=map(Ce[e][s],0,1,2*a,0)*le,o<1.5*le&&(o=0),Qn(l,h,ze,Oe,t,n,o,i,r)}}function Jn(e,t,n,r,i){for(let o=0;o<Le[e].length;o++)Qn(Le[e][o][0],Le[e][o][1],t,Oe,n,r,0,1,i)}function Qn(e,t,n,r,i,o,a,l,s){s.stroke(dr(o,map(l,0,1,.25,1))),s.fill(dr(i,map(l,0,1,.15,1))),s.strokeWeight(Fe),fr([a],s),3==dt&&s.fill(dr(i,0)),1==r?s.ellipse(e,t,n):2==r?s.rect(e,t,7*n/8,7*n/8):3==r&&(s.beginShape(),s.vertex(e-4*n/7,t),s.vertex(e,t-4*n/7),s.vertex(e+4*n/M 7,t),s.vertex(e,t+4*n/7),s.endShape(CLOSE))}function er(e){if(1==e);else if(2==e){We.strokeWeight(1*le);for(let e=ht/4;e<width+ht/4;e+=ht)for(let t=ht/4;t<height+ht/4;t+=ht)We.point(e,t)}else if(3==e){ht=25*le;for(let e=ht/2;e<height+ht/2;e+=ht)We.line(0,e,width,e);for(let e=ht/2;e<width+ht/2;e+=ht)We.line(e,0,e,height)}}function tr(){Ue.textFont("Trebuchet MS"),Ue.textAlign(LEFT,CENTER),Ue.noStroke(),pr(Ue,800*le,500*le),Ue.noStroke(),Ue.fill(dr(st,.75)),Ue.rect(width/2,height/2-100*le,800*le,300*le,25*le,25*le,0,M 0),Ue.fill(st),Ue.rect(width/2-250*le,height/2-100*le,225*le,225*le),Ue.image(se.elt,width/2-357.5*le,height/2-207.5*le,215*le,215*le);let e=100*Zt[0][0];Ue.fill(ct),Ue.textSize(25*le),Ue.textStyle(NORMAL),1==me&&(e>=0&&e<20?Ue.text("I have a feeling this image belongs to",width/2-100*le,height/2-170*le):e>=20&&e<40?Ue.text("I have a hunch this image belongs to",width/2-100*le,height/2-170*le):e>=40&&e<60?Ue.text("I think this image belongs to",width/2-100*le,height/2-170*le):e>=60&&e<80?Ue.text("I'm almost certainM this image belongs to",width/2-100*le,height/2-170*le):Ue.text("I'm positive this image belongs to",width/2-100*le,height/2-170*le));let t=e.toFixed(2);"100.00"==t&&(t="100"),1==me&&Ue.text("I'm "+t+"% confident that I'm right!",width/2-100*le,height/2-25*le),example=Zt.map((e=>e[1])),be=Ue.textWidth('"FIDENZAAAA"'),defaultPhrase=Ue.textWidth('"PERPENDICULAR INHABITATION"'),Ue.textStyle(BOLD);const n=me?example[0]:random(example);if(1===n.split(" ").length){let e=75*be/Ue.textWidth('"'+n+'"');e>75&&(e=75),Ue.textSM ize(e*le),Ue.text('"'+n+'"',width/2-100*le,height/2-90*le)}else nr(width/2-100*le,height/2-90*le,460*le,110*le,n,Ue);if(millis()-ye>1500&&(me=!0),C(tt,nt,st,ct,Pe,Mt),Ue.image(nt,width/2-370*le,height/2+70*le,80*le,80*le),3==Pe){let e;e=map(Mt,50,60,.25,1.3),I(rt,e),Ue.image(rt,width/2-370*le,height/2+70*le,80*le,80*le)}let r,i;Ue.image(tt,width/2-370*le,height/2+70*le,80*le,80*le),Ue.fill(xt),Ue.textSize(40*le),Ue.text("INTELLIGENCE INFO",width/2-275*le,height/2+115*le),Ue.textSize(18*le),Ue.textStyle(NORMAL),Ue.cM ircle(width/2-360*le,height/2+180*le,7.5*le),1==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s growing and getting smarter by the day.`:2==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s stable and it has reached peak performance.`:3==Pe&&(r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s decaying and losing its luster.`),i=2==Pe?"The Perceptron remains stable for some time before entering the decay phase.":`Wait until ${new Date(an).toLocaleString("en-US")} for your Perceptron to reM ach its peak performance.`,Ue.text(r,width/2-350*le,height/2+180*le),Ue.circle(width/2-360*le,height/2+210*le,7.5*le),Ue.text(i,width/2-350*le,height/2+210*le),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),gr(Ue,width/2-225*le,width/2+65*le,height/2+265*le,height/2+305*le,"SELECT ANOTHER IMAGE"),gr(Ue,width/2+75*le,width/2+225*le,height/2+265*le,height/2+305*le,"CLOSE")}function nr(e,t,n,r,i,o){let a=i.split(" "),l=75*be/o.textWidth('"'+i+'"'),s=0,h=[],c=[],u=[],f="",d="";if(l>=50)l>75&&(l=75),o.textSize(l*le),o.tM ext('"'+i+'"',e,t);else if(l<50){if(l=50*defaultPhrase/o.textWidth('"'+i+'"'),l>30){if(l>50&&(l=50),[f,d]=rr(l,n,s,h,c,a,f,d,Ue),0==c.length)return o.textSize(l*le),void o.text('"'+i+'"',e,t);for(s=0,h=[],c=[];o.textWidth(d)>n/le;)l=l*n/le/o.textWidth(d),f="",d="",[f,d]=rr(l,n,s,h,c,a,f,d,Ue)}else{l=30,o.textSize(l);for(let e=0;e<a.length;e++)s+=o.textWidth(" "+a[e]),s<=n/le?h.push(a[e]):s>n/le&&s<=n/le*2?c.push(a[e]):u.push(a[e]);for(let e=1;e<h.length;e++)f=f+" "+h[e];if(f='"'+h[0]+f,0==u.length){for(let e=0;e<c.M length-1;e++)d=d+c[e]+" ";d=d+c[c.length-1]+'"'}else if(1==c.length)d="... "+u[u.length-1]+'"';else{for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+"... "+u[u.length-1]+'"'}}o.textSize(l*le);let r=1.25*(o.textDescent()+o.textAscent());o.text(f,e,t-r/2),o.text(d,e,t+r/2)}}function rr(e,t,n,r,i,o,a,l,s){s.textSize(e);for(let e=0;e<o.length;e++)(n+=s.textWidth(" "+o[e]))<=t/le?r.push(o[e]):i.push(o[e]);for(let e=1;e<r.length;e++)a=a+" "+r[e];if(a='"'+r[0]+a,0==i.length&&(a+='"',l=""),1==i.length)l=i[i.length-1]+'"';elseM {for(let e=0;e<i.length-1;e++)l=l+i[e]+" ";l=l+i[i.length-1]+'"'}return[a,l]}function ir(){const e=45*le;qe.textFont("Tahoma"),qe.stroke(st),qe.strokeWeight(2*le),qe.fill(ct),qe.rect(width/2,e/2+height-87.5*le,600*le,90*le),qe.fill(st),qe.rect(width/2-150*le,e+height-170*le,300*le,30*le),qe.fill(ct),qe.rect(width/2+150*le,e+height-170*le,300*le,30*le),qe.noStroke(),qe.fill(ct),qe.textSize(15*le),qe.textStyle(BOLD),qe.text("PERCEPTRON INFORMATION",width/2-285*le,e+height-165*le),qe.fill(xt),qe.text("ARTWORK NAME:",wM idth/2+10*le,e+height-165*le),qe.textAlign(RIGHT),qe.textStyle(ITALIC),qe.text("Perceptron #"+Et,width/2+285*le,e+height-165*le);const[t,n]=It.split(" ");let r;"60 Years"===It?r="1 Year":"60 Months"===It?r="1 Month":"60 Weeks"===It?r="1 Week":"60 Days"===It?r="1 Day":"12 Hours"===It&&(r="12 Minutes"),data=[["AI MODEL NAME:",B(12*le,Ht,140*le)],["SCALE:","1:"+Te],["NUMBER OF CLASSES:",$t.length],["BIRTH YEAR:",Rt],["NUMBER OF REBIRTHS:",sn.toString()],["AGE:",`${Math.ceil(Mt)} Perceptron Years`],["ONE PERCEPTRON YEAM R:",`${r}`],["STATE:",Ot[Pe]],["ACTIVE NEURONS:",`${round(ln*rn)} / ${ln}`],["NEXT STATE TIME:",vr(new Date(on))]],qe.fill(xt);const i=data.length/2;for(let t=0;t<data.length;++t){const n=t<i,r=n?width/2-285*le:width/2+10*le,o=n?width/2-10*le:width/2+285*le,a=e+height-(135-t%i*15)*le;qe.textStyle(BOLD),qe.textAlign(LEFT),qe.textSize(12*le),qe.text(data[t][0],r,a),qe.textStyle(ITALIC),qe.textAlign(RIGHT),qe.textSize(12*le),qe.text(data[t][1],o,a)}}function or(){Ke.textFont("Trebuchet MS"),Ke.noStroke(),pr(Ke,600*le,M 200*le),gr(Ke,width/2-155*le,width/2-5*le,height/2+115*le,height/2+155*le,"UPDATE"),gr(Ke,width/2+5*le,width/2+155*le,height/2+115*le,height/2+155*le,"CLOSE"),Ke.textAlign(LEFT),Ke.fill(xt),Ke.text("UPDATE BITCOIN FULL NODE ADDRESS",width/2-252.5*le,height/2-55*le),Ke.text("UPDATE MODEL ADDRESS",width/2-252.5*le,height/2+20*le),Ke.textAlign(RIGHT),Ke.textStyle(ITALIC),Ke.textSize(15*le),0==wn&&Ke.text("(*) Invalid Address",width/2+252.5*le,height/2-53*le),0==vn&&Ke.text("(*) Invalid Model",width/2+252.5*le,height/2M +23*le)}function ar(){je.textFont("Trebuchet MS"),je.fill(st),je.textSize(50*le),je.stroke(st),je.strokeWeight(1*le),je.text("main()",width/2,height/2)}function lr(){un>=20&&1==dn&&(dn=!1,un=0),dn&&(Ze.textFont("Trebuchet MS"),Ze.stroke(st),Ze.fill(ct),Ze.rect(width/2,height/2,600*le,150*le,25*le),Ze.fill(xt),Ze.textSize(75*le),Ze.noStroke(),1==Pe?Ze.text("GROWING",width/2,height/2+5*le):3==Pe?Ze.text("AGING",width/2,height/2+5*le):4==Pe?Ze.text("DEAD",width/2,height/2+5*le):5==Pe&&Ze.text("BIRTH",width/2,height/2+M 5*le)),un>=20&&0==dn&&(dn=!0,un=0,Bt++,3==Bt&&(fn=!1))}function sr(e,t,n,r){let i=[],o=r/(n.length+1),a=color(e),l=color(t);i.push(a);for(let e=0;e<n.length;e++){let t=color(n[e]);for(let e=1;e<=o;e++){let n=lerpColor(a,t,e/o);i.push(n)}a=t}for(let e=1;e<o;e++){let t=lerpColor(a,l,e/o);i.push(t)}if(i.push(l),i.length>r)i.splice(r);else if(i.length<r){let e=i[i.length-1];for(;i.length<r;)i.push(e)}return i}function hr(e,t){let n=e.length,r=Math.floor(t*n);return r>=n&&(r=n-1),e[r]}function cr(e){e=e.replace("#","");M var t=parseInt(e,16);return color(t>>16&255,t>>8&255,255&t)}function ur(e,t,n,r,i,o,a,l){var s=a.drawingContext.createLinearGradient(e,t,n,r);s.addColorStop(0,i),s.addColorStop(1,o),a.drawingContext.strokeStyle=s,a.drawingContext.globalAlpha=l,a.line(e,t,n,r),a.drawingContext.globalAlpha=1}function fr(e,t){t.drawingContext.setLineDash(e)}function dr(e,t){let n=color(e),r=red(n),i=green(n),o=blue(n);return color(r,i,o,255*t)}function xr(e,t,n,r){return mouseX>e&&mouseX<t&&mouseY>n&&mouseY<r}function gr(e,t,n,r,i,o){M e.strokeWeight(1*le),e.stroke(st);const[a,l]=xr(t,n,r,i)?[xt,ct]:[ct,xt];e.fill(a),e.push(),e.rectMode(CORNERS),e.rect(t,r,n,i,5*le),e.pop(),e.noStroke(),e.textSize(20*le),e.fill(l),e.text(o,(t+n)/2,(46*r+54*i)/100)}function pr(e,t,n){e.fill(0,0,0,75),e.rect(width/2,height/2,width,height),e.stroke(st),e.fill(ct),e.rect(width/2,height/2,t,n,25*le)}function mr(e,t){resizeCanvas(e,t,!0),Xe.resizeCanvas(e,t,!0),$e.resizeCanvas(e,t,!0),We.resizeCanvas(e,t,!0),Ue.resizeCanvas(e,t,!0),qe.resizeCanvas(e,t,!0),Qe.resizeCanvM as(e,t,!0),je.resizeCanvas(e,t,!0),Ze.resizeCanvas(e,t,!0),Ke.resizeCanvas(e,t,!0),Je.resizeCanvas(e,t,!0),et.resizeCanvas(e,t,!0)}function br(e,t,n,r,i,o){const a=J(e);return a.position(t,n),a.size(r,i),a.style("opacity","0"),a.mouseClicked(o),a}function yr(){return null!=vt&&vt?.isFocused()||null!=zt&&zt?.isFocused()}function wr(e,t,n,r){let i;if(e<=3){i=`Hey ${String.fromCodePoint(128075)}, I'm ${n}, ${t} years old. I can detect ${r.length} NFT collections: `;let e=0;for(let t=0;t<r.length;++t){const n=r[t];if(eM +n.length>500){i+=", etc";break}t==r.length-1?i+=", and ":t>0&&(i+=", "),i+=n,e+=n.length}i+=". ",t<=5?i+="However, I am only a baby, so my recognition ability is not accurate. I'm in the state of Growing both looks and intelligence.":t<=13?i+="I am now a child. My recognition ability is becoming better, but still not very accurate. I'm in the state of Growing both looks and intelligence.":t<=25?i+="I have grown up to be a teen. My recognition ability almost reaches the peak, but I will still mess up sometimes. I'mM in the state of Growing both looks and intelligence.":t<=50?i+="I finally reach adulthood. My recognition is fully functional now. I'm in the Stable state, where I am the most intelligent with all neurons activated.":t<=60&&(i+="I am now an old Perceptron, so my recognition ability is no longer the best. I'm in the Decaying state, meaning that my neurons are dying, and my intelligence is decreasing over time.")}else 4==e?i=`${n} is Dead. However, this is not the end to its story...`:5==e&&(i=`${n} is now in the ReM birth state, and is preparing to start a new life.`);return i}function vr(e){const t=e.getDate(),n=e.toLocaleString("en-US",{month:"long"}),r=e.getFullYear();let i=e.getHours().toString();1==i.length&&(i="0"+i);let o=e.getMinutes().toString();return 1==o.length&&(o="0"+o),`${Y(t)} ${n} ${r} | ${i}:${o}`}saveCanvasAtCurrentTime=()=>{save(N())},save4KCanvasAtCurrentTime=()=>{const e=width,t=height,n=min(4096/min(e,t),1e4/max(e,t)),r=e*n,i=t*n;mr(r,i),zn=!0,$n(r,i),qn();let o="4K_"+N()+".png";saveCanvas(et,o),mr(e,t),M $n(e,t),zn=!1};const zr=[["60 Years",3,365],["60 Months",40,30],["60 Weeks",37,7],["60 Days",20,1]],Vr=[["1943",1],["1951",1.5],["1957",2],["1969",2.5],["1970",3],["1980",3.5],["1982",4],["1986",4.5],["1988",5],["1997",5.5],["1998",6],["2002",6.5],["2009",7],["2012",7.5],["2014",8],["2015",8.5],["2016",9],["2023",15]],_r=[["Plain",20],["Dotted",40],["Squared",40]],Mr=[["Basic",30],["Standard",60],["Advanced",10]],Er=[["MNIST",70],["CIFAR",25],["IMAGENET",5]],Sr=[["Theano",60],["Torch",30],["TensorFlow",10]],Rr=[["WM hitepaper",2],["Blackboard",2],["Blueprint",2],["Nak",74/14],["Jims",74/14],["Level 10",74/14],["Flips",74/14],["Level 14",74/14],["III",74/14],["XMB",74/14],["Info",74/14],["Adventure",74/14],["Marigold",74/14],["Phoenix",74/14],["Love",74/14],["Cachet",74/14],["Human",74/14],["Twilight",3],["Sunset",3],["Aurora",3],["Liminal Space",3],["D Vu",3],["Lucid Dream",3],["Parallel",1],["Multiverse",1]];function Ir(e){for(let e=0;e<100;++e)random(1);return{visual:{pattern:k(_r),hardwareAcceleration:k(Mr),nodeFill:k(M Er),nodeShape:k(Sr),colorPalette:k(Rr),lifeCycle:k(zr),birthYear:k(Vr)},training:e}}function Cr(e){window.$generativeTraits={"Network Architecture":e.training.structure_gen,"Hidden Layers":e.training.n_layers,"Max Neurons Per Hidden Layer":e.training.max_nodes,"Activation Function":e.training.activation_func,"Training Epochs":e.training.epoch_num,Dataset:e.visual.nodeFill,"Deep Learning Framework":e.visual.nodeShape,"Hardware Acceleration":e.visual.hardwareAcceleration,"Paper Pattern":e.visual.pattern,"Life Cycle":M e.visual.lifeCycle,"Birth Year":e.visual.birthYear,"Color Palette":e.visual.colorPalette}} <script defer src="https://static.cloudflareinsights.com/beacon.min.js/v2b4487d741ca48dcbadcaf954e159fc61680799950996" integrity="sha512-D/jdE0CypeVxFadTejKGTzmwyV10c1pxZk/AqjJuZbaJwGMyNHY3q/mTPWqMUnFACfCTunhZUVcd4cV78dK1pQ==" data-cf-beacon='{"rayId":"7b481de51c9ba1f3","version":"2023.3.0","b":1,"token":"6c07c178c94442f695e7a0a2aaee641a","si":100}' crossorigin="anonymous"></script> {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "pauldrons"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "carrot"}, {"trait_type": "Mane", "value": "blue fire"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} text/html;charset=utf-8 <meta charset="utf-8" /> position: relative; width: var(--width); height: var(--height); border: 1px solid blue; position: relative; <div id="upload"> <input id="inputUpload" type="file"> function e(e){"use strict";return new function e(t){let n="global"==t?window:this;n.canvas=document.createElement("canvas");let r=n.canvas.getContext("2d");n.width=100,n.height=100,n.canvas.width=n.width,n.canvas.height=n.height,"offscreen"!=t&&(document.body?document.body.appendChild(n.canvas):window.addEventListener("load",(function(){document.body.appendChild(n.canvas)}))),g(),n.MAGIC=161533525,n.RGB=0,n.HSV=1,n.HM SB=1,n.CHORD=0,n.PIE=1,n.OPEN=2,n.RADIUS=1,n.CORNER=2,n.CORNERS=3,n.ROUND="round",n.SQUARE="butt",n.PROJECT="square",n.MITER="miter",n.BEVEL="bevel",n.CLOSE=1,n.BLEND="source-over",n.REMOVE="destination-out",n.ADD="lighter",n.DARKEST="darken",n.LIGHTEST="lighten",n.DIFFERENCE="difference",n.SUBTRACT="subtract",n.EXCLUSION="exclusion",n.MULTIPLY="multiply",n.SCREEN="screen",n.REPLACE="copy",n.OVERLAY="overlay",n.HARD_LIGHT="hard-light",n.SOFT_LIGHT="soft-light",n.DODGE="color-dodge",n.BURN="color-burn",n.NORMAL="norM mal",n.ITALIC="italic",n.BOLD="bold",n.BOLDITALIC="italic bold",n.CENTER="center",n.LEFT="left",n.RIGHT="right",n.TOP="top",n.BOTTOM="bottom",n.BASELINE="alphabetic",n.LANDSCAPE="landscape",n.PORTRAIT="portrait",n.ALT=18,n.BACKSPACE=8,n.CONTROL=17,n.DELETE=46,n.DOWN_ARROW=40,n.ENTER=13,n.ESCAPE=27,n.LEFT_ARROW=37,n.OPTION=18,n.RETURN=13,n.RIGHT_ARROW=39,n.SHIFT=16,n.TAB=9,n.UP_ARROW=38,n.HALF_PI=Math.PI/2,n.PI=Math.PI,n.QUARTER_PI=Math.PI/4,n.TAU=2*Math.PI,n.TWO_PI=2*Math.PI,n.THRESHOLD=1,n.GRAY=2,n.OPAQUE=3,n.INVEM RT=4,n.POSTERIZE=5,n.DILATE=6,n.ERODE=7,n.BLUR=8,n.ARROW="default",n.CROSS="crosshair",n.HAND="pointer",n.MOVE="move",n.TEXT="text",n.VIDEO={video:!0,audio:!1},n.AUDIO={video:!1,audio:!0},n.SHR3=1,n.LCG=2,n.HARDWARE_FILTERS=!0,n.hint=function(e,t){n[e]=t},n.frameCount=0,n.mouseX=0,n.mouseY=0,n.pmouseX=0,n.pmouseY=0,n.mouseButton=null,n.keyIsPressed=!1,n.mouseIsPressed=!1,n.key=null,n.keyCode=null,n.pixels=null,n.accelerationX=0,n.accelerationY=0,n.accelerationZ=0,n.rotationX=0,n.rotationY=0,n.rotationZ=0,n.relRotatM ionX=0,n.relRotationY=0,n.relRotationZ=0,n.pAccelerationX=0,n.pAccelerationY=0,n.pAccelerationZ=0,n.pRotationX=0,n.pRotationY=0,n.pRotationZ=0,n.pRelRotationX=0,n.pRelRotationY=0,n.pRelRotationZ=0,n.touches=[],n._styleCache=[{colorMode:n.RGB,noStroke:!1,noFill:!1,ellipseMode:n.CENTER,rectMode:n.CORNER,curveDetail:20,curveAlpha:0,textFont:"sans-serif",textSize:12,textLeading:12,textStyle:"normal"}],n._style=n._styleCache[n._styleCache.length-1],n._noLoop=!1,n._pixelDensity=1,n._frameRate=null,n._tint=null;let i=nullM ,o=!0,a=[],l=null,s=0,h={},c=0,u=null,f=null,d=null;Object.defineProperty(n,"deviceOrientation",{get:function(){return 90==Math.abs(window.orientation)?n.LANDSCAPE:n.PORTRAIT}}),Object.defineProperty(n,"windowWidth",{get:function(){return window.innerWidth}}),Object.defineProperty(n,"windowHeight",{get:function(){return window.innerHeight}}),Object.defineProperty(n,"drawingContext",{get:function(){return r}}),n.createCanvas=function(e,t){return n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t,g(),n.canvas},nM .resizeCanvas=function(e,t){n.width=e,n.height=t,n.canvas.width=e,n.canvas.height=t},n.createGraphics=n.createImage=function(t,n){let r=new e("offscreen");return r.createCanvas(t,n),r.noLoop(),r},n.pixelDensity=function(e){return null==e||(n._pixelDensity=e,n.canvas.width=Math.ceil(n.width*e),n.canvas.height=Math.ceil(n.height*e),n.canvas.style.width=n.width+"px",n.canvas.style.height=n.height+"px",r.scale(n._pixelDensity,n._pixelDensity),g()),n._pixelDensity},n.map=function(e,t,n,r,i,o){let a=r+1*(e-t)/(n-t)*(i-r)M ;return o?r<i?Math.min(Math.max(a,r),i):Math.min(Math.max(a,i),r):a},n.lerp=function(e,t,n){return e*(1-n)+t*n},n.constrain=function(e,t,n){return Math.min(Math.max(e,t),n)},n.dist=function(){return 4==arguments.length?Math.hypot(arguments[0]-arguments[2],arguments[1]-arguments[3]):Math.hypot(arguments[0]-arguments[3],arguments[1]-arguments[4],arguments[2]-arguments[5])},n.norm=function(e,t,r){return n.map(e,t,r,0,1)},n.sq=function(e){return e*e},n.fract=function(e){return e-Math.floor(e)},n.degrees=function(e){retM urn 180*e/Math.PI},n.radians=function(e){return e*Math.PI/180},n.abs=Math.abs,n.ceil=Math.ceil,n.exp=Math.exp,n.floor=Math.floor,n.log=Math.log,n.mag=Math.hypot,n.max=Math.max,n.min=Math.min,n.round=Math.round,n.sqrt=Math.sqrt,n.sin=Math.sin,n.cos=Math.cos,n.tan=Math.tan,n.asin=Math.asin,n.acos=Math.acos,n.atan=Math.atan,n.atan2=Math.atan2,n.Vector=function(e,t,r){let i=this;i.x=e||0,i.y=t||0,i.z=r||0;let o=null,a=null;function l(e,t,n){return null!=e.x?e:null!=t?{x:e,y:t,z:n||0}:{x:e,y:e,z:e}}function s(){null==a&M &(a=i.x*i.x+i.y*i.y+i.z*i.z,o=Math.sqrt(a))}function h(){a=null,o=null}i.set=function(e,t,n){i.x=e||0,i.y=t||0,i.z=n||0},i.copy=function(){return new n.Vector(i.x,i.y,i.z)},i.add=function(){let e=l.apply(null,arguments);return i.x+=e.x,i.y+=e.y,i.z+=e.z,h(),i},i.rem=function(){let e=l.apply(null,arguments);return i.x%=e.x,i.y%=e.y,i.z%=e.z,h(),i},i.sub=function(){let e=l.apply(null,arguments);return i.x-=e.x,i.y-=e.y,i.z-=e.z,h(),i},i.mult=function(){let e=l.apply(null,arguments);return i.x*=e.x,i.y*=e.y,i.z*=e.z,hM (),i},i.div=function(){let e=l.apply(null,arguments);return i.x/=e.x,i.y/=e.y,i.z/=e.z,h(),i},i.mag=function(){return s(),o},i.magSq=function(){return s(),a},i.dot=function(){let e=l.apply(null,arguments);return i.x*e.x+i.y*e.y+i.z*e.z},i.dist=function(){let e=l.apply(null,arguments),t=i.x-e.x,n=i.y-e.y,r=i.z-e.z;return Math.sqrt(t*t+n*n+r*r)},i.cross=function(){let e=l.apply(null,arguments),t=i.y*e.z-i.z*e.y,n=i.z*e.x-i.x*e.z,r=i.x*e.y-i.y*e.x;return i.x=t,i.y=n,i.z=r,h(),i},i.normalize=function(){s();let e=o;retuM rn i.x/=e,i.y/=e,i.z/=e,o=1,a=1,i},i.limit=function(e){s();if(o>e){let t=e/o;i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e}return i},i.setMag=function(e){s();let t=e/o;return i.x*=t,i.y*=t,i.z*=t,o=e,a=e*e,i},i.heading=function(){return Math.atan2(i.y,i.x)},i.rotate=function(e){let t=Math.cos(e),n=Math.sin(e),r=i.x*t-i.y*n,o=i.x*n+i.y*t;return i.x=r,i.y=o,i},i.angleBetween=function(){let e=l.apply(null,arguments);const t=i.dot(e)/(i.mag()*e.mag());let n;return n=Math.acos(Math.min(1,Math.max(-1,t))),n*Math.sign(i.cross(e).z||1)},M i.lerp=function(e,t){return i.x=i.x*(1-t)+e.x*t,i.y=i.y*(1-t)+e.y*t,i.z=i.z*(1-t)+e.z*t,h(),i},i.reflect=function(e){return e.normalize(),i.sub(e.mult(2*i.dot(e)))},i.array=function(){return[i.x,i.y,i.z]},i.equals=function(e,t){return null==t&&null==(t=Number.EPSILON)&&(t=0),Math.abs(e.x-i.x)<t&&Math.abs(e.y-i.y)<t&&Math.abs(e.z-i.z)<t},i.fromAngle=function(e,t){return null==t&&(t=1),o=t,a=t*t,i.x=t*Math.cos(e),i.y=t*Math.sin(e),i.z=0,i},i.fromAngles=function(e,t,n){null==n&&(n=1),o=n,a=n*n;const r=Math.cos(t),l=MaM th.sin(t),s=Math.cos(e),h=Math.sin(e);return i.x=n*h*l,i.y=-n*s,i.z=n*h*r,i},i.random2D=function(){return o=1,a=1,i.fromAngle(Math.random()*Math.PI*2)},i.random3D=function(){return o=1,a=1,i.fromAngles(Math.random()*Math.PI*2,Math.random()*Math.PI*2)},i.toString=function(){return`[${i.x}, ${i.y}, ${i.z}]`}},n.Vector.add=function(e,t){return new n.Vector(e.x+t.x,e.y+t.y,e.z+t.z)},n.Vector.rem=function(e,t){return new n.Vector(e.x%t.x,e.y%t.y,e.z%t.z)},n.Vector.sub=function(e,t){return new n.Vector(e.x-t.x,e.y-t.y,e.M z-t.z)},n.Vector.mult=function(e,t){return null==t.x?new n.Vector(e.x*t,e.y*t,e.z*t):new n.Vector(e.x*t.x,e.y*t.y,e.z*t.z)},n.Vector.div=function(e,t){return null==t.x?new n.Vector(e.x/t,e.y/t,e.z/t):new n.Vector(e.x/t.x,e.y/t.y,e.z/t.z)},n.Vector.dist=function(e,t){return Math.hypot(e.x-t.x,e.y-t.y,e.z-t.z)},n.Vector.cross=function(e,t){return new n.Vector(e.y*t.z-e.z*t.y,e.z*t.x-e.x*t.z,e.x*t.y-e.y*t.x)},n.Vector.lerp=function(e,t,r){return new n.Vector(e.x*(1-r)+t.x*r,e.y=e.y*(1-r)+t.y*r,e.z=e.z*(1-r)+t.z*r)},n.M Vector.equals=function(e,t,n){return e.equals(t,n)};for(let e of["fromAngle","fromAngles","random2D","random3D"])n.Vector[e]=function(t,r,i){return(new n.Vector)[e](t,r,i)};function x(e,t,n){let r,i,o,a,l,s,h,c,u;if(0==t)return[255*(r=n),255*(i=n),255*(o=n)];switch((a=e)>360&&(a=0),h=n*(1-t),c=n*(1-t*(s=(a/=60)-(l=~~a))),u=n*(1-t*(1-s)),l){case 0:r=n,i=u,o=h;break;case 1:r=c,i=n,o=h;break;case 2:r=h,i=n,o=u;break;case 3:r=h,i=c,o=n;break;case 4:r=u,i=h,o=n;break;default:r=n,i=h,o=c}return[255*r,255*i,255*o]}functioM n g(){r.fillStyle="white",r.strokeStyle="black",r.lineCap="round",r.lineJoin="miter"}function p(e){if(0<=e&&e<2*Math.PI)return e;for(;e<0;)e+=2*Math.PI;for(;e>=Math.PI;)e-=2*Math.PI;return e}function m(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;let c=p(a),u=p(l);r.beginPath();for(let a=0;a<h+1;a++){let l=a/h,s=n.lerp(c,u,l),f=Math.cos(s)*i/2,d=Math.sin(s)*o/2;r[a?"lineTo":"moveTo"](e+f,t+d)}s==n.CHORD?r.closePath():s==n.PIE&&(r.lineTo(e,t),r.closePath()),n._style.noFill||r.fill(),n._style.noStrokM e||r.stroke()}function b(e,t,i,o){n._style.noFill&&n._style.noStroke||(r.beginPath(),r.ellipse(e,t,i/2,o/2,0,0,2*Math.PI),n._style.noFill||r.fill(),n._style.noStroke||r.stroke())}function y(e,t,i,o,a,l,s,h){if(n._style.noFill&&n._style.noStroke)return;if(null==a)return function(e,t,i,o){n._style.noFill||r.fillRect(e,t,i,o),n._style.noStroke||r.strokeRect(e,t,i,o)}(e,t,i,o);if(null==l)return y(e,t,i,o,a,a,a,a);const c=Math.min(Math.abs(o),Math.abs(i))/2;a=Math.min(c,a),l=Math.min(c,l),h=Math.min(c,h),s=Math.min(c,s)M ,r.beginPath(),r.moveTo(e+a,t),r.arcTo(e+i,t,e+i,t+o,l),r.arcTo(e+i,t+o,e,t+o,s),r.arcTo(e,t+o,e,t,h),r.arcTo(e,t,e+i,t,a),r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke()}function w(){a=[]}n.createVector=function(e,t,r){return new n.Vector(e,t,r)},n.curvePoint=function(e,t,n,r,i){const o=i*i*i,a=i*i;return e*(-.5*o+a-.5*i)+t*(1.5*o-2.5*a+1)+n*(-1.5*o+2*a+.5*i)+r*(.5*o-.5*a)},n.bezierPoint=function(e,t,n,r,i){const o=1-i;return Math.pow(o,3)*e+3*Math.pow(o,2)*i*t+3*o*Math.pow(i,2)*n+Math.pow(i,M 3)*r},n.curveTangent=function(e,t,n,r,i){const o=i*i;return e*(-3*o/2+2*i-.5)+t*(9*o/2-5*i)+n*(-9*o/2+4*i+.5)+r*(3*o/2-i)},n.bezierTangent=function(e,t,n,r,i){const o=1-i;return 3*r*Math.pow(i,2)-3*n*Math.pow(i,2)+6*n*o*i-6*t*o*i+3*t*Math.pow(o,2)-3*e*Math.pow(o,2)},n.Color=function(e,t,n,r){let i=this;i.MAGIC=786698,i._r=e,i._g=t,i._b=n,i._a=r,i._h=0,i._s=0,i._v=0,i._hsvInferred=!1,i.setRed=function(e){i._r=e,i._hsvInferred=!1},i.setGreen=function(e){i._g=e,i._hsvInferred=!1},i.setBlue=function(e){i._b=e,i._hsvInfM erred=!1},i.setAlpha=function(e){i._a=e/255,i._hsvInferred=!1},i._inferHSV=function(){i._hsvInferred||([i._h,i._s,i._v]=function(e,t,n){let r,i,o,a,l;return r=e<t?e<n?e:n:t<n?t:n,0==(l=100*(i=e>t?e>n?e:n:t>n?t:n)/255)?[o=0,a=0,l]:0==(a=100*(i-r)/i)?[o=0,a,l]:(o=i==e?0+60*(t-n)/(i-r):i==t?120+60*(n-e)/(i-r):240+60*(e-t)/(i-r),[o,a,l])}(i._r,i._g,i._b),i._hsvInferred=!0)},i.toString=function(){return`rgba(${Math.round(i._r)},${Math.round(i._g)},${Math.round(i._b)},${~~(1e3*i._a)/1e3})`}},n.colorMode=function(e){n._stM yle.colorMode=e},n.color=function(){if(1==arguments.length&&786698==arguments[0].MAGIC)return arguments[0];if(n._style.colorMode==n.RGB){if(1==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],1);if(2==arguments.length)return new n.Color(arguments[0],arguments[0],arguments[0],arguments[1]/255);if(3==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],1);if(4==arguments.length)return new n.Color(arguments[0],arguments[1],arguments[2],arguments[3]/255)}else{if(1==argumeM nts.length)return new n.Color(...x(0,0,arguments[0]/100),1);if(2==arguments.length)return new n.Color(...x(0,0,arguments[0]/100),arguments[1]/255);if(3==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),1);if(4==arguments.length)return new n.Color(...x(arguments[0],arguments[1]/100,arguments[2]/100),arguments[3])}return null},n.red=function(e){return e._r},n.green=function(e){return e._g},n.blue=function(e){return e._b},n.alpha=function(e){return 255*e._a},n.hue=function(e){reM turn e._inferHSV(),e._h},n.saturation=function(e){return e._inferHSV(),e._s},n.brightness=function(e){return e._inferHSV(),e._v},n.lightness=function(e){return 100*(.2126*e._r+.7152*e._g+.0722*e._b)/255},n.lerpColor=function(e,t,r){return n._style.colorMode==n.RGB?new n.Color(n.constrain(n.lerp(e._r,t._r,r),0,255),n.constrain(n.lerp(e._g,t._g,r),0,255),n.constrain(n.lerp(e._b,t._b,r),0,255),n.constrain(n.lerp(e._a,t._a,r),0,1)):(e._inferHSV(),t._inferHSV(),new n.Color(n.constrain(function(e,t,r){var i=[[Math.abs(t-M e),n.map(r,0,1,e,t)],[Math.abs(t+360-e),n.map(r,0,1,e,t+360)],[Math.abs(t-360-e),n.map(r,0,1,e,t-360)]];return i.sort(((e,t)=>e[0]-t[0])),(i[0][1]+720)%360}(e._h,t._h,r),0,360),n.constrain(n.lerp(e._s,t._s,r),0,100),n.constrain(n.lerp(e._v,t._v,r),0,100),n.constrain(n.lerp(e._a,t._a,r),0,1)))},n.strokeWeight=function(e){n._style_noStroke=!1,r.lineWidth=e},n.stroke=function(){if(n._style.noStroke=!1,"string"==typeof arguments[0])return void(r.strokeStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._sM tyle.noStroke=!0:r.strokeStyle=e},n.noStroke=function(){n._style.noStroke=!0},n.fill=function(){if(n._style.noFill=!1,"string"==typeof arguments[0])return void(r.fillStyle=arguments[0]);let e=n.color.apply(null,arguments);e._a<=0?n._style.noFill=!0:r.fillStyle=e},n.noFill=function(){n._style.noFill=!0},n.blendMode=function(e){r.globalCompositeOperation=e},n.strokeCap=function(e){r.lineCap=e},n.strokeJoin=function(e){r.lineJoin=e},n.ellipseMode=function(e){n._style.ellipseMode=e},n.rectMode=function(e){n._style.rectM Mode=e},n.curveDetail=function(e){n._style.curveDetail=e},n.curveAlpha=function(e){n._style.curveAlpha=e},n.curveTightness=function(e){n._style.curveAlpha=e},n.clear=function(){r.clearRect(0,0,n.width,n.height)},n.background=function(){if(arguments[0]&&arguments[0].MAGIC==n.MAGIC)return n.image(arguments[0],0,0,n.width,n.height);r.save(),r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity),r.fillStyle="string"==typeof arguments[0]?arguments[0]:n.color(...Array.from(arguments)),r.fillRect(0,0,n.width,n.heightM ),r.restore()},n.line=function(e,t,i,o){n._style.noStroke||(r.beginPath(),r.moveTo(e,t),r.lineTo(i,o),r.stroke())},n.arc=function(e,t,r,i,o,a,l,s){if(o==a)return n.ellipse(e,t,r,i);null==s&&(s=25),null==l&&(l=n.PIE),n._style.ellipseMode==n.CENTER?m(e,t,r,i,o,a,l,s):n._style.ellipseMode==n.RADIUS?m(e,t,2*r,2*i,o,a,l,s):n._style.ellipseMode==n.CORNER?m(e+r/2,t+i/2,r,i,o,a,l,s):n._style.ellipseMode==n.CORNERS&&m((e+r)/2,(t+i)/2,r-e,i-t,o,a,l,s)},n.ellipse=function(e,t,r,i){null==i&&(i=r),n._style.ellipseMode==n.CENTERM ?b(e,t,r,i):n._style.ellipseMode==n.RADIUS?b(e,t,2*r,2*i):n._style.ellipseMode==n.CORNER?b(e+r/2,t+i/2,r,i):n._style.ellipseMode==n.CORNERS&&b((e+r)/2,(t+i)/2,r-e,i-t)},n.circle=function(e,t,r){return n.ellipse(e,t,r,r)},n.point=function(e,t){e.x&&(t=e.y,e=e.x),r.beginPath(),r.ellipse(e,t,.4,.4,0,0,2*Math.PI),r.stroke()},n.rect=function(e,t,r,i,o,a,l,s){n._style.rectMode==n.CENTER?y(e-r/2,t-i/2,r,i,o,a,l,s):n._style.rectMode==n.RADIUS?y(e-r,t-i,2*r,2*i,o,a,l,s):n._style.rectMode==n.CORNER?y(e,t,r,i,o,a,l,s):n._stylM e.rectMode==n.CORNERS&&y(e,t,r-e,i-t,o,a,l,s)},n.square=function(e,t,r,i,o,a,l){return n.rect(e,t,r,r,i,o,a,l)},n.beginShape=function(){w(),r.beginPath(),o=!0},n.beginContour=function(){r.closePath(),w(),o=!0},n.endContour=function(){w(),o=!0},n.vertex=function(e,t){w(),o?r.moveTo(e,t):r.lineTo(e,t),o=!1},n.bezierVertex=function(e,t,n,i,o,a){w(),r.bezierCurveTo(e,t,n,i,o,a)},n.quadraticVertex=function(e,t,n,i){w(),r.quadraticCurveTo(e,t,n,i)},n.bezier=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.bezierVM ertex(r,i,o,a,l,s),n.endShape()},n.triangle=function(e,t,r,i,o,a){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.endShape(n.CLOSE)},n.quad=function(e,t,r,i,o,a,l,s){n.beginShape(),n.vertex(e,t),n.vertex(r,i),n.vertex(o,a),n.vertex(l,s),n.endShape(n.CLOSE)},n.endShape=function(e){w(),e&&r.closePath(),n._style.noFill||r.fill(),n._style.noStroke||r.stroke(),n._style.noFill&&n._style.noStroke&&(r.save(),r.fillStyle="none",r.fill(),r.restore())},n.curveVertex=function(e,t){if(a.push([e,t]),a.length<4)return;M let i=function(e,t,n,r,i,o,a,l,s,h){function c(e,t,n,r,i,o){let a=Math.pow(r-t,2)+Math.pow(i-n,2);return Math.pow(a,.5*o)+e}let u=[],f=c(0,e,t,n,r,h),d=c(f,n,r,i,o,h),x=c(d,i,o,a,l,h);for(let h=0;h<s;h++){let c=f+h/(s-1)*(d-f),g=[(f-c)/(f-0),(c-0)/(f-0),(d-c)/(d-f),(c-f)/(d-f),(x-c)/(x-d),(c-d)/(x-d),(d-c)/(d-0),(c-0)/(d-0),(x-c)/(x-f),(c-f)/(x-f)];for(let e=0;e<g.length;e+=2)isNaN(g[e])&&(g[e]=1,g[e+1]=0),isFinite(g[e])||(g[e]>0?(g[e]=1,g[e+1]=0):(g[e]=0,g[e+1]=1));let p=e*g[0]+n*g[1],m=t*g[0]+r*g[1],b=n*g[2]+i*g[M 3],y=r*g[2]+o*g[3],w=i*g[4]+a*g[5],v=o*g[4]+l*g[5],z=p*g[6]+b*g[7],V=m*g[6]+y*g[7],_=b*g[8]+w*g[9],M=y*g[8]+v*g[9],E=z*g[2]+_*g[3],S=V*g[2]+M*g[3];u.push([E,S])}return u}(...a[a.length-4],...a[a.length-3],...a[a.length-2],...a[a.length-1],n._style.curveDetail,n._style.curveAlpha);for(let e=0;e<i.length;e++)o?r.moveTo(...i[e]):r.lineTo(...i[e]),o=!1},n.curve=function(e,t,r,i,o,a,l,s){n.beginShape(),n.curveVertex(e,t),n.curveVertex(r,i),n.curveVertex(o,a),n.curveVertex(l,s),n.endShape()},n.translate=function(e,t){r.tM ranslate(e,t)},n.rotate=function(e){r.rotate(e)},n.scale=function(e,t){null==t&&(t=e),r.scale(e,t)},n.applyMatrix=function(e,t,n,i,o,a){r.transform(e,t,n,i,o,a)},n.shearX=function(e){r.transform(1,0,Math.tan(e),1,0,0)},n.shearY=function(e){r.transform(1,Math.tan(e),0,1,0,0)},n.resetMatrix=function(){r.resetTransform(),r.scale(n._pixelDensity,n._pixelDensity)},n.pushMatrix=n.push=function(){n._styleCache.push({...n._style}),n._style=n._styleCache[n._styleCache.length-1],r.save()},n.popMatrix=n.pop=function(){n._stylM eCache.length-1&&(n._styleCache.pop(),n._style=n._styleCache[n._styleCache.length-1],r.restore())},n.image=function(e,t,i,o,a,l,s,h,c){let u=e.MAGIC==n.MAGIC?e.canvas:e;function d(){if(e.MAGIC!=n.MAGIC||!n._tint)return;let t=e.canvas.getContext("2d");t.save(),t.resetTransform(),t.clearRect(0,0,t.canvas.width,t.canvas.height),t.drawImage(f.canvas,0,0),t.restore()}return e.MAGIC==n.MAGIC&&null!=n._tint&&(function(e,t){null==f&&(f=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvasM .height),f.canvas.width==e&&f.canvas.height==t||(f.canvas.width=e,f.canvas.height=t)}(e.canvas.width,e.canvas.height),f.drawImage(e.canvas,0,0),e.tinted(n._tint)),o?l?(h||(h=u.width),c||(c=u.height),r.drawImage(u,l,s,h,c,t,i,o,a),void d()):(r.drawImage(u,t,i,o,a),void d()):(e.MAGIC==n.MAGIC||e.width?r.drawImage(u,t,i,e.width,e.height):r.drawImage(u,t,i,e.videoWidth,e.videoHeight),void d())},n.loadPixels=function(){l=r.getImageData(0,0,n.canvas.width,n.canvas.height),n.pixels=l.data},n.updatePixels=function(){null!=M l&&r.putImageData(l,0,0)},n.loadImage=function(e,t){s++;let r=n.createGraphics(100,100),i=r.canvas.getContext("2d"),o=new Image;return o.src=e,o.crossOrigin="Anonymous",o.onload=function(){i.canvas.width=o.width,i.canvas.height=o.height,r.width=o.width,r.height=o.height,i.drawImage(o,0,0),s--,t&&t(r)},r};let v={};function z(e,t){null==u&&(u=document.createElement("canvas").getContext("2d")),null==e&&(e=r.canvas.width,t=r.canvas.height),u.canvas.width==e&&u.canvas.height==t||(u.canvas.width=e,u.canvas.height=t)}funcM tion V(){let e=r.canvas.width*r.canvas.height*4;null!=d&&e==d.length||(d=new Uint8ClampedArray(e))}function _(e){u.clearRect(0,0,u.canvas.width,u.canvas.height),u.filter=e,u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()}v[n.THRESHOLD]=function(e,t){null==t?t=127.5:t*=255;for(let n=0;n<e.length;n+=4){const r=.2126*e[n]+.7152*e[n+1]+.0722*e[n+2];e[n]=e[n+1]=e[n+2]=r>=t?255:0}},v[n.GRAY]=function(e){for(let t=0;t<e.length;t+=4)M {const n=.2126*e[t]+.7152*e[t+1]+.0722*e[t+2];e[t]=e[t+1]=e[t+2]=n}},v[n.OPAQUE]=function(e){for(let t=0;t<e.length;t+=4)e[t+3]=255},v[n.INVERT]=function(e){for(let t=0;t<e.length;t+=4)e[t]=255-e[t],e[t+1]=255-e[t+1],e[t+2]=255-e[t+2]},v[n.POSTERIZE]=function(e,t){let n=t-1;for(let r=0;r<e.length;r+=4)e[r]=255*(e[r]*t>>8)/n,e[r+1]=255*(e[r+1]*t>>8)/n,e[r+2]=255*(e[r+2]*t>>8)/n},v[n.DILATE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-M 1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.max(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.ERODE]=function(e){V(),d.set(e);let[t,n]=[r.canvas.width,r.canvas.height];for(let r=0;r<n;r++)for(let i=0;i<t;i++){let o=4*Math.max(i-1,0),a=4*Math.min(i+1,t-1),l=4*Math.max(r-1,0)*t,s=4*Math.min(r+1,n-1)*t,h=4*r*t,c=4*i;for(let t=0;t<4;t++){let n=t+l,r=t+s,i=t+h;e[h+c+t]=Math.min(d[n+c],d[i+o],d[i+c],d[i+a],d[r+c])}}},v[n.BLURM ]=function(e,t){t=t||1,t=Math.floor(t*n._pixelDensity),V(),d.set(e);let i=2*t+1,o=function(e){let n=new Float32Array(e),r=.3*t+.8,i=r*r*2;for(let t=0;t<e;t++){let o=t-e/2,a=Math.exp(-o*o/i)/(2.5066282746*r);n[t]=a}return n}(i),[a,l]=[r.canvas.width,r.canvas.height];for(let n=0;n<l;n++)for(let r=0;r<a;r++){let l=0,s=0,h=0,c=0;for(let e=0;e<i;e++){let i=4*(n*a+Math.min(Math.max(r-t+e,0),a-1));l+=d[i]*o[e],s+=d[i+1]*o[e],h+=d[i+2]*o[e],c+=d[i+3]*o[e]}let u=4*(n*a+r);e[u]=l,e[u+1]=s,e[u+2]=h,e[u+3]=c}d.set(e);for(let nM =0;n<l;n++)for(let r=0;r<a;r++){let s=0,h=0,c=0,u=0;for(let e=0;e<i;e++){let i=4*(Math.min(Math.max(n-t+e,0),l-1)*a+r);s+=d[i]*o[e],h+=d[i+1]*o[e],c+=d[i+2]*o[e],u+=d[i+3]*o[e]}let f=4*(n*a+r);e[f]=s,e[f+1]=h,e[f+2]=c,e[f+3]=u}},n.filter=function(e,t){if(n.HARDWARE_FILTERS&&null!=r.filter)if(z(),e==n.THRESHOLD){null==t&&(t=.5),t=Math.max(t,1e-5),_(`saturate(0%) brightness(${Math.floor(.5/t*100)}%) contrast(1000000%)`)}else if(e==n.GRAY)_("saturate(0%)");else if(e==n.OPAQUE)u.fillStyle="black",u.fillRect(0,0,u.canvaM s.width,u.canvas.height),u.drawImage(r.canvas,0,0),r.save(),r.resetTransform(),r.drawImage(u.canvas,0,0),r.restore();else if(e==n.INVERT)_("invert(100%)");else if(e==n.BLUR)_(`blur(${Math.ceil(t*n._pixelDensity/1)||1}px)`);else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}else{let n=r.getImageData(0,0,r.canvas.width,r.canvas.height);v[e](n.data,t),r.putImageData(n,0,0)}},n.resize=function(e,t){z(),u.drawImage(r.canvas,0,0),n.width=e,n.height=t,r.canvas.width=e*n._pixM elDensity,r.canvas.height=t*n._pixelDensity,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0,r.canvas.width,r.canvas.height),r.restore()},n.get=function(e,t,i,o){if(null!=e&&null==i){let i=r.getImageData(e,t,1,1).data;return new n.Color(i[0],i[1],i[2],i[3]/255)}e=e||0,t=t||0,i=i||n.width,o=o||n.height;let a=n.createGraphics(i,o);a.pixelDensity(n._pixelDensity);let l=r.getImageData(e*n._pixelDensity,t*n._pixelDensity,i*n._pixelDensity,o*n._pixelDensity);return a.caM nvas.getContext("2d").putImageData(l,0,0),a},n.set=function(e,t,i){if(i.MAGIC==n.MAGIC){let r=n._tint;return n._tint=null,n.image(i,e,t),void(n._tint=r)}let o=4*(t*n._pixelDensity*r.canvas.width+e*n._pixelDensity);n.pixels[o]=i._r,n.pixels[o+1]=i._g,n.pixels[o+2]=i._b,n.pixels[o+3]=255*i._a},n.tinted=function(){let e=n.color(...Array.from(arguments)),t=e._a;e._a=1,z(),u.clearRect(0,0,u.canvas.width,u.canvas.height),u.fillStyle=e,u.fillRect(0,0,u.canvas.width,u.canvas.height),u.globalCompositeOperation="multiply",u.M drawImage(r.canvas,0,0),u.globalCompositeOperation="source-over",r.save(),r.resetTransform();let i=r.globalCompositeOperation;r.globalCompositeOperation="source-in",r.drawImage(u.canvas,0,0),r.globalCompositeOperation=i,r.restore(),u.globalAlpha=t,u.clearRect(0,0,u.canvas.width,u.canvas.height),u.drawImage(r.canvas,0,0),u.globalAlpha=1,r.save(),r.resetTransform(),r.clearRect(0,0,r.canvas.width,r.canvas.height),r.drawImage(u.canvas,0,0),r.restore()},n.tint=function(){n._tint=n.color(...Array.from(arguments))},n.noTiM nt=function(){n._tint=null},n.mask=function(e){r.save(),r.resetTransform();let t=r.globalCompositeOperation;r.globalCompositeOperation="destination-in",r.drawImage(e.canvas,0,0),r.globalCompositeOperation=t,r.restore()},n.clearTemporaryBuffers=function(){u=null,f=null,d=null},n.save=function(e,t){e=e||"untitled",t=t||"png";var n=document.createElement("a");n.innerHTML="[Download]",n.addEventListener("click",(function(){this.href=r.canvas.toDataURL(),this.download=e+"."+t}),!1),document.body.appendChild(n),n.click()M ,document.body.removeChild(n)},n.saveCanvas=function(e,t,r){if(e.MAGIC==n.MAGIC){r&&e.save(t,r);let n=t.split(".");return e.save(n.slice(0,-1).join("."),n[n.length-1])}if(t)return n.save(e,t);let i=e.split(".");return n.save(i.slice(0,-1).join("."),i[i.length-1])},n.loadFont=function(e){let t=e.split("/"),n=t[t.length-1].split(".")[0].replace(" ",""),r=`@font-face {\n font-family: '${n}';\n src: url('${e}');\n }`;const i=document.createElement("style");return i.textContent=r,document.head.append(M i),n},n.textFont=function(e){n._style.textFont=e},n.textSize=function(e){n._style.textSize=e,n._style.textLeading=e},n.textLeading=function(e){n._style.textLeading=e},n.textStyle=function(e){n._style.textStyle=e},n.textAlign=function(e,t){r.textAlign=e,t&&(r.textBaseline=t==n.CENTER?"middle":t)},n.text=function(e,t,i,o){if(!e)return;if(e=e.toString(),n._style.noFill&&n._style.noStroke)return;r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`;let a=e.split("\n");for(let e=0;e<a.length;e++)n._M style.noFill||r.fillText(a[e],t,i,o),n._style.noStroke||r.strokeText(a[e],t,i,o),i+=n._style.textLeading},n.textWidth=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).width},n.textAscent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBoundingBoxAscent},n.textDescent=function(e){return r.font=`${n._style.textStyle} ${n._style.textSize}px ${n._style.textFont}`,r.measureText(e).actualBounM dingBoxDescent};var M,E=4,S=.5,R=function(e){return.5*(1-Math.cos(e*Math.PI))};n.noise=function(e,t,n){if(t=t||0,n=n||0,null==M){M=new Array(4096);for(var r=0;r<4096;r++)M[r]=Math.random()}e<0&&(e=-e),t<0&&(t=-t),n<0&&(n=-n);for(var i,o,a,l,s,h=Math.floor(e),c=Math.floor(t),u=Math.floor(n),f=e-h,d=t-c,x=n-u,g=0,p=.5,m=0;m<E;m++){var b=h+(c<<4)+(u<<8);i=R(f),o=R(d),a=M[4095&b],a+=i*(M[b+1&4095]-a),l=M[b+16&4095],a+=o*((l+=i*(M[b+16+1&4095]-l))-a),l=M[4095&(b+=256)],l+=i*(M[b+1&4095]-l),s=M[b+16&4095],l+=o*((s+=i*(M[M b+16+1&4095]-s))-l),g+=(a+=R(x)*(l-a))*p,p*=S,h<<=1,c<<=1,u<<=1,(f*=2)>=1&&(h++,f--),(d*=2)>=1&&(c++,d--),(x*=2)>=1&&(u++,x--)}return g},n.noiseDetail=function(e,t){e>0&&(E=e),t>0&&(S=t)};const I=function(){let e,t,n=4294967295;return{setSeed(r){e=t=(null==r?Math.random()*n:r)>>>0},getSeed:()=>t,rand:()=>(e^=e<<17,e^=e>>13,((e^=e<<5)>>>0)/n)}};let C=I();C.setSeed(),n.noiseSeed=function(e){let t=null==e?4294967295*Math.random():e;M||(M=new Float32Array(4096));for(var n=0;n<4096;n++)t^=t<<17,t^=t>>13,t^=t<<5,M[n]=(t>M >>0)/4294967295},n.randomSeed=function(e){C.setSeed(e)},n.random=function(e,t){return null==e?C.rand():"number"==typeof e?null!=t?C.rand()*(t-e)+e:C.rand()*e:e[~~(e.length*C.rand())]},n.randomGenerator=function(e){e==n.LCG?C=function(){const e=4294967296;let t,n;return{setSeed(r){n=t=(null==r?Math.random()*e:r)>>>0},getSeed:()=>t,rand:()=>(n=(1664525*n+1013904223)%e)/e}}():e==n.SHR3&&(C=I()),C.setSeed()};var T=new function(){var e,t,n,r=new Array(128),i=new Array(256),o=new Array(128),a=new Array(128),l=new Array(2M 56),s=new Array(256),h=function(){return 4294967296*C.rand()-2147483648},c=function(){return.5+2.328306e-10*(h()<<0)};this.SHR3=h,this.UNI=c,this.RNOR=function(){return n=h(),e=127&n,Math.abs(n)<r[e]?n*o[e]:function(){for(var t,i,l,s,u=3.44262;;){if(t=n*o[e],0==e){do{l=c(),s=c(),t=.2904764*-Math.log(l),i=-Math.log(s)}while(i+i<t*t);return n>0?u+t:-u-t}if(a[e]+c()*(a[e-1]-a[e])<Math.exp(-.5*t*t))return t;if(n=h(),e=127&n,Math.abs(n)<r[e])return n*o[e]}}()},this.REXP=function(){return(t=h()>>>0)<r[e=255&t]?t*l[e]:funM ction(){for(var n;;){if(0==e)return 7.69711-Math.log(c());if(n=t*l[e],s[e]+c()*(s[e-1]-s[e])<Math.exp(-n))return n;if((t=h())<i[e=255&t])return t*l[e]}}()},this.zigset=function(){var e,t,n=2147483648,h=4294967296,c=3.442619855899,u=c,f=.00991256303526217,d=7.697117470131487,x=d,g=.003949659822581572;for(e=f/Math.exp(-.5*c*c),r[0]=Math.floor(c/e*n),r[1]=0,o[0]=e/n,o[127]=c/n,a[0]=1,a[127]=Math.exp(-.5*c*c),t=126;t>=1;t--)c=Math.sqrt(-2*Math.log(f/c+Math.exp(-.5*c*c))),r[t+1]=Math.floor(c/u*n),u=c,a[t]=Math.exp(-.5*cM *c),o[t]=c/n;for(e=g/Math.exp(-d),i[0]=Math.floor(d/e*h),i[1]=0,l[0]=e/h,l[255]=d/h,s[0]=1,s[255]=Math.exp(-d),t=254;t>=1;t--)d=-Math.log(g/d+Math.exp(-d)),i[t+1]=Math.floor(d/x*h),x=d,s[t]=Math.exp(-d),l[t]=d/h}};T.hasInit=!1,n.randomGaussian=function(e,t){return T.hasInit||(T.zigset(),T.hasInit=!0),T.RNOR()*t+e},n.randomExponential=function(){return T.hasInit||(T.zigset(),T.hasInit=!0),T.REXP()},n.print=console.log,n.cursor=function(e,t,r){let i="";e.includes(".")&&(e=`url("${e}")`,i=", auto"),null!=t&&(e+=" "+t+M " "+r),n.canvas.style.cursor=e+i},n.noCursor=function(){n.canvas.style.cursor="none"},n.createCapture=function(e){var t=document.createElement("video");return t.playsinline="playsinline",t.autoplay="autoplay",navigator.mediaDevices.getUserMedia(e).then((function(e){t.srcObject=e})),t.style.position="absolute",t.style.opacity=1e-5,t.style.zIndex=-1e3,document.body.appendChild(t),t};let A=["setup","draw","preload","mouseMoved","mousePressed","mouseReleased","mouseDragged","mouseClicked","keyPressed","keyReleased","keM yTyped","touchStarted","touchEnded"];for(let e of A){let t="_"+e+"Fn";n[t]=function(){},n[t].isPlaceHolder=!0,n[e]?n[t]=n[e]:Object.defineProperty(n,e,{set:function(e){n[t]=e}})}function D(){n._noLoop||(i=null==n._frameRate?requestAnimationFrame(D):setTimeout(D,1e3/n._frameRate)),w(),o=!0,n.push(),n._drawFn(),n.pop(),++n.frameCount}function k(e){const t=n.canvas.getBoundingClientRect(),r=n.canvas.scrollWidth/n.width||1,i=n.canvas.scrollHeight/n.height||1;return{x:(e.clientX-t.left)/r,y:(e.clientY-t.top)/i,id:e.idenM tifier}}function L(){return n._touchStarted.isPlaceHolder&&n._touchMoved.isPlaceHolder&&n._touchEnded.isPlaceHolder}n.noLoop=function(){n._noLoop=!0,i=null},n.loop=function(){n._noLoop=!1,null==i&&D()},n.redraw=function(){D()},n.frameRate=function(e){n._frameRate=e},setTimeout((function(){n._preloadFn(),c=window.performance.now(),function e(){if(s>0)return setTimeout(e,10);n._setupFn(),D()}()}),1),n.canvas.onmousemove=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPM ressed?n._mouseDraggedFn(e):n._mouseMovedFn(e)},n.canvas.onmousedown=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!0,n.mouseButton=[n.LEFT,n.CENTER,n.RIGHT][e.button],n._mousePressedFn(e)},n.canvas.onmouseup=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressed=!1,n._mouseReleasedFn(e)},n.canvas.onclick=function(e){n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=e.offsetX,n.mouseY=e.offsetY,n.mouseIsPressedM =!0,n._mouseClickedFn(e),n.mouseIsPressed=!1},window.addEventListener("keydown",(function(e){n.keyIsPressed=!0,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!0,n._keyPressedFn(e),1==e.key.length&&n._keyTypedFn(e)})),window.addEventListener("keyup",(function(e){n.keyIsPressed=!1,n.key=e.key,n.keyCode=e.keyCode,h[n.keyCode]=!1,n._keyReleasedFn(e)})),n.keyIsDown=function(e){return!!h[e]},n.canvas.ontouchstart=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.moM useY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mousePressedFn(e)||e.preventDefault()),n._touchStartedFn(e)||e.preventDefault()},n.canvas.ontouchmove=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!0,n.mouseButton=n.LEFT,n._mouseDraggedFn(e)||e.preventDefault()),n._touchMovedFn(e)||e.preventDefault()},n.canvas.ontouchend=n.canvas.ontouchcancel=function(e){n.touches=e.touches.map(k),L()&&(n.pmouseX=n.M mouseX,n.pmouseY=n.mouseY,n.mouseX=n.touches[0].x,n.mouseY=n.touches[0].y,n.mouseIsPressed=!1,n._mouseReleasedFn(e)||e.preventDefault()),n._touchEndedFn(e)||e.preventDefault()},n.hasSensorPermission=!window.DeviceOrientationEvent&&!window.DeviceMotionEvent||!(DeviceOrientationEvent.requestPermission||DeviceMotionEvent.requestPermission),n.requestSensorPermissions=function(){DeviceOrientationEvent.requestPermission&&DeviceOrientationEvent.requestPermission().then((e=>{"granted"==e&&DeviceMotionEvent.requestPermissioM n&&DeviceMotionEvent.requestPermission().then((e=>{"granted"==e&&(n.hasSensorPermission=!0)})).catch(alert)})).catch(alert)},window.ondeviceorientation=function(e){n.pRotationX=n.rotationX,n.pRotationY=n.rotationY,n.pRotationZ=n.rotationZ,n.pRelRotationX=n.relRotationX,n.pRelRotationY=n.relRotationY,n.pRelRotationZ=n.relRotationZ,n.rotationX=e.beta*(Math.PI/180),n.rotationY=e.gamma*(Math.PI/180),n.rotationZ=e.alpha*(Math.PI/180),n.relRotationX=[-n.rotationY,-n.rotationX,n.rotationY][1+~~(window.orientation/90)],n.rM elRotationY=[-n.rotationX,n.rotationY,n.rotationX][1+~~(window.orientation/90)],n.relRotationZ=n.rotationZ},window.ondevicemotion=function(e){if(n.pAccelerationX=n.accelerationX,n.pAccelerationY=n.accelerationY,n.pAccelerationZ=n.accelerationZ,!e.acceleration){let t=((e,t)=>[(e[0]*t[0]+e[1]*t[1]+e[2]*t[2]+e[3])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[4]*t[0]+e[5]*t[1]+e[6]*t[2]+e[7])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15]),(e[8]*t[0]+e[9]*t[1]+e[10]*t[2]+e[11])/(e[12]*t[0]+e[13]*t[1]+e[14]*t[2]+e[15])])(((e,t)M =>[e[0]*t[0]+e[1]*t[4]+e[2]*t[8]+e[3]*t[12],e[0]*t[1]+e[1]*t[5]+e[2]*t[9]+e[3]*t[13],e[0]*t[2]+e[1]*t[6]+e[2]*t[10]+e[3]*t[14],e[0]*t[3]+e[1]*t[7]+e[2]*t[11]+e[3]*t[15],e[4]*t[0]+e[5]*t[4]+e[6]*t[8]+e[7]*t[12],e[4]*t[1]+e[5]*t[5]+e[6]*t[9]+e[7]*t[13],e[4]*t[2]+e[5]*t[6]+e[6]*t[10]+e[7]*t[14],e[4]*t[3]+e[5]*t[7]+e[6]*t[11]+e[7]*t[15],e[8]*t[0]+e[9]*t[4]+e[10]*t[8]+e[11]*t[12],e[8]*t[1]+e[9]*t[5]+e[10]*t[9]+e[11]*t[13],e[8]*t[2]+e[9]*t[6]+e[10]*t[10]+e[11]*t[14],e[8]*t[3]+e[9]*t[7]+e[10]*t[11]+e[11]*t[15],e[12]*t[0]+M e[13]*t[4]+e[14]*t[8]+e[15]*t[12],e[12]*t[1]+e[13]*t[5]+e[14]*t[9]+e[15]*t[13],e[12]*t[2]+e[13]*t[6]+e[14]*t[10]+e[15]*t[14],e[12]*t[3]+e[13]*t[7]+e[14]*t[11]+e[15]*t[15]])((e=>[Math.cos(e),0,Math.sin(e),0,0,1,0,0,-Math.sin(e),0,Math.cos(e),0,0,0,0,1])(n.rotationY),(e=>[1,0,0,0,0,Math.cos(e),-Math.sin(e),0,0,Math.sin(e),Math.cos(e),0,0,0,0,1])(n.rotationX)),[0,0,-9.80665]);n.accelerationX=e.accelerationIncludingGravity.x+t[0],n.accelerationY=e.accelerationIncludingGravity.y+t[1],n.accelerationZ=e.accelerationIncludM ingGravity.z-t[2]}},n.year=function(){return(new Date).getFullYear()},n.day=function(){return(new Date).getDay()},n.hour=function(){return(new Date).getHours()},n.minute=function(){return(new Date).getMinutes()},n.second=function(){return(new Date).getSeconds()},n.millis=function(){return window.performance.now()-c}}(e)}"object"==typeof exports&&"undefined"!=typeof module&&(module.exports=e);const t="https://ancient-crimson-rain.btc.discover.quiknode.pro/c268fb026303ae8443f785200f2ea4b82f0082dd";function n(e){P(e)?M localStorage.removeItem("blocksApiEndpoint"):localStorage.blocksApiEndpoint=e}function r(){return localStorage.blocksApiEndpoint||t}function i(e){P(e)?localStorage.removeItem("modelInscriptionEndpoint"):localStorage.modelInscriptionEndpoint=e}function o(){return localStorage.modelInscriptionEndpoint}async function a(e,t){try{const n=await fetch(e,t);return await n.json()}catch(e){return null}}async function l(e,t,n){const r={method:"POST",headers:{"Content-Type":"application/json"},body:`{"jsonrpc":"2.0","id":1,"meM thod":"${t}","params":${`[${n.join(sep=",")}]`}}`};return(await a(e,r))?.result}async function s(e){const n={avgfee:10,time:Date.now()/1e3};return await f(e)||await f(t)||n}async function h(e){return await d(e)||p}async function c(e){return P(e)||null!=await f(e)}async function u(e){return P(e)||null!=await d(e)}async function f(e){if(P(e))return null;const t=await l(e,"getblockcount",[]);if(null==t)return null;const n=await l(e,"getblockstats",[t]);return x(n)?n:null}async function d(e){if(P(e))return null;const tM =await a(e,{});return g(t)?t:null}function x(e){return"number"==typeof e?.time&&"number"==typeof e?.avgfee}function g(e){if(null==e)return!1;const{classes_name:t,training_traits:n,layers_config:r,weight_b64:i}=e;if(!Array.isArray(t))return!1;if(null==n)return!1;try{j(r,i)}catch(e){return!1}return!0}const p={"model_name": "pfp_classifier_243", "layers_config": {"config": {"layers": [{"class_name": "InputLayer", "config": {"batch_input_shape": [null, 28, 28, 3]}}, {"class_name": "Rescaling", "config": {"scale": 0.007M 84313725490196, "offset": -1}}, {"class_name": "Flatten"}, {"class_name": "Dense", "config": {"units": 3, "activation": "sigmoid"}}, {"class_name": "Dense", "config": {"units": 6, "activation": "sigmoid"}}, {"class_name": "Dense", "config": {"units": 4, "activation": "linear"}}]}}, "weight_b64": "LuGivHn5rzzqDWq9c9O6Oxu8pTxKmpi9UTbKvV3pVz3L/uO8raDGvUmcUj0uTDa9dmmHvCQSUz0fcl69XoXFva4ym7peHzU8KeL9vc77Dz2QWeM8MpEBvgVxVz1/zJM8Fi3vvcyDhz3RzAw9zySCO7T7aDxkxxs9g+ukuzbWFz167Us811/IvfUxSz2hZLY8LdqDvRPLuD11fnu9ZLEtvRgFpj1/1uM 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 psiD2oUrW8nZuQPA1ngToKrPU8HHScPdVgkbw+IEa9777Ru/i52bw4dG29yB8ZPfEnOL2CB7q9TgutPJ40MDyTdVy93oESve9fvDy3+vC9oSmiO52an73nw4e8dbJ4PYZhpjzRc3y9qhlnvObS9Tx/WOi9qdyMPQXHI71Vjpi9hiIjPYtb/zusf+a9erFPvUF1kTygyKi9YGPLPTBp0L0BS8A8J2BQPQzrgb1zBkM77/wOPJ/UM73xa0a8NWTkPZ68LL0PewE9rJ4OPbmD1r1oyQ68zWEUPV/fa713Lsa8sk3+vPq8UbwfyNM8/fMwvTJAdb3sQoM7c6QHvii+cjzTqoU9yZ16vaOttTwizAE92kiwvUgfkDyqN7u7bbSjvUUhhzxWbbU9JHO1vTnO3D02PAS8LOw6vq4BpD0rhpC8o5EivgohtT3JWLk9pEupvUbqzj3TaJe8HxgZvt6A5j3x5km863r1vchL/T2FFmg9dNnDvRjRJT7+QEm9JN/WvRn5QT21f6M 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 0PYL1AKCq9r13VvYv7BD0qx1y9Pq64vHrEm7xLXoy9JJuzvQ1+Yz1mOrK8FHAEvrWEYT36f/28n8M3vfVrkD14t2g7ouWdvRaIuj01q4U8L2ZMPZwJ/rxyNIC84NZKPfjghry3BKI76QxEPfID9bx/NBi9N5EaPvmSsr1h11i9pF3rPR97pL09oBe+17yNPbOUIL39IgO9T33oPXA9lL3Buqe9BNEBPsOLlb2abAC+uDkEPe8pK70+uf69KU+KPYKwcL3FAhq+FztCPcehkLyY3xW+eUo5PVBXar0wmga+x6moPGVB/zqpnIu9XNuvPU3JqbwRuOe93sMPPOAYMr0wEMq9vl03PYD5m7sxRRS8LlbfPcEmIr2RzhC+WRcuO2OC2rqmh5i9le+BPSYcZjxwRpC9YeSBO0ZcRD2fl0O9BVzEvanPtDwRmFK9nxffPZVTtrzMcHy91aKRPbnIhb1w9Ky8GffUuw27FjwdAiO9YYCePTnLXL2t1hm9wmWXPQsZVb3e8hM 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 Y8PW2evCClz73PRAI+rwOavKjTtbzEUO4946mHvZPYKD6A1qm+S3AVvjMprT4CKcC+gvdVvvKXpT5cicC+axWhvcCVhj39XIg9wDrvvd42aj5abZk7k9/+vU+JdT7oVIQ8pxnPPQBP073Hxow+yTEVPbgVT75Z2oM+T4GTPd7IgL7zz2A+XRQrPtHDY73IzJS+2T0jPktBd72l45a9YlX4PXUsDL5kVo28Qj0OvpviPj5nwyQ+hDWTuoKLdD1fvOY9Ot1cPQ9lgj0RYFa8bwLAvYj7Pz6yPBQ9WfvuvauIiD71oUc8NiARviAaFD4sTpq91J8GPt5Pfr5ISOQ9RAUgvbZsIb5J/Ik92T2Pven7UL5qSTw8OXD1PSoN2LsyTEK9v1KoPQWdrb25Kaw8gokUPcxgA77ymju9RqgmvfvmJT3AwyS9JbTVvSwrDj63rEI8ibMyvculYz3R4Z08JEFYPBuyNzykMTi8y5cOPczWGj0KAj07RdzhPPV2gb3Vtsi8jWwXPuM 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 S8JXSqPFpySb382Hq9wtN7vUrH+Tw6pPu8cpoAvmK0Jz4iJe67VaUQvhkn3zzbLZe8rI0DPil/izwPeco8pKbrvKYHmT02ZYo83ImrvfIpojtDS2c9QA00Pp7Lhb2vBYK9uqufPTGE/7z+1lS8OebsPOscWrxZhqe9tVqNvkOGRD6qtNw8XBV8vp5glj0lfRg+3XZxvi0RqD1xZLo9rXOFPt/ae717USS+bkYrPgnAnDuCK4E9x4hiPpUYbrxUmiC8iQY8vXCIaj2Rttg9ge+Wvd/lKTwQYyo+Z+34Pad2sbwM4sw9cFE7vZD1lL1vU3Q+TLjZvKSTHT1rEX49suu6PUqL3b1/ZKO9X9HSvRCh0D01o9e9e0htvojOpj5RSJO+MdAYvtv7kD4C0qm+dtJCPsMDhr4uSkw++0d4PcS8Cb6fPog+jr/ovJd6sryHREI+qC8yPwCuM79vnX4+CbEwP5/9F78wlG4+hXi4PgUFwr711Ys+077KPdmBdb5qsG2+8nY+vsM Y+Db7lTGa+5WDYPV1Eur7ZN6K9QZv3vYvptby249u9YBjJvgOALz5Vm1e+Fm+uvbYJrr0z10e+EFwJvpY1YL40xKY+TiMEPn/oA7+cqpk+gSdPPgRQ8L6fUhQ+5gatvZOrM71+Pwm9fnyFvDCmNr1LEbC+WCI2viJSwj28Saa+g7QLPqJ9gzzySTm+XxtwPp4ahTxOeLy+3MM2vJO2AT4ZaJu+9QU3vSLopTvfm+E+mB3wPaAyHL53Juk+UDeGO0EgGL3Masc+8H5VPsNhHb4txnm+aiIMPvggDr4Kazq9sEw4PoqPib0ifjC9MOOAvlaTaD5ARjE94nlIvgypkT4F+oU9Py6ZvSPegj4ZXhe9g8YKvo9KDj7F8T+9F/4uvi0kYj4yvCS9MLpbvp1zXT7NX7K97quvPTogCr46KP09KcbFvXQ07L0V6Nc9FrXjvffKJ75iT5u8uCkpPRwVfLtclC+9MBjCPDgj8715ZH080+I7PX1T/70Y6Wm90CvrPEx4LTw1rvM 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 hGm756TIE9OBQKPlgaTL66/0Q+3nANPRmcAr6dqSM+7B+DvQfRCb70zVQ+828wvfV4uL1V1NU+7gkYvWg7CL1u2pc+bSLBPp7F571FFcG+q6CNPg/yK74c6Wu9BapyPleIab11gyC+SxIpvoMmbD5Gr6E+BlpxvoTtOz7FRKE+RCAKvmZdFT5ZWTM9PmaaPXftvz0Nsmq+w1RhPnCeuz0q7Lm+3lMAPUZecz0EFqe9As3jPDiuR70NXyc9Riz7vAso4rznvz29OZ/ZvdVaG724uji7BQqrvdSzeL2LnAg+3AWLvRYSsr1+5a09SweDvWdfU755Q2C9CCb/PJZ7vD04fE49lL8GvnEkqz00lYE8tGcqvscwuT2jkSE+JQEgPU62eT34gTW+EiUeverAHz4MiLy98CvOvfWSAj657bk9WoWSPr/w4r3zDNS96EmcPiNCzb2MrAm9dkh4PnSGtb1/cey7r+ryPXS3iLxdzWg9iqdKPXsJzrx+loY9KbxKPZUPPL1Kp0M 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 PPGb7w8wG/6SYovl8wVD1cpkG9P9oHvttMDj0Vrpi+mSiTPvsBIb6OGbq+qAI0vfaGvrwMMi29EZFlvVxNg7pmmYC+dWWXPjjYN748hri+vro6vS8PjL3IXK+8XIuIPTpQ470ijp6+chOcPkZ5hL77YO2+/3w2vCy/Ur1FjBe9aan4PS/3Jr7nx1a+hYGSPr5jiL7TDZK+J88Qvacm273kuyy9jDP4PdQmYr4EKoU9X8MuPmblp77z2vK8rhikPI+84r0lMQU9rouWvTKTfL2Nr+I9In+Mu0AR/r0uGoU9wqO2PebQ673lA52950ImvrjqQT1jE9Y9FYiqvYqpGju4zDU6oHgKPv04ubv0CNu9Bx2ZvcIhPj0ZG4I9n+cMvmxa2z1C0ms9N/wevepHgD2xXeA8lgjuPREjIb3CEle+SBjgvCUPAj3L1e296LG8vd7sHT0Kl588o2J9PXKMz70eA4i+r6VOPZvwOL2MlGS+E47uPHgWm7ypTQe+EK2pPWoHUr7enZM 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 m/dxRDQNYHUcBHajC+0qI4QO6In7+zH05A4+QqwIw7Yz8yrxRA9s5YwE4gjEDBIzpAfXLBvy+MIUDikULAwHatvsrYS7+FChO/3WxTPm2+gr/+kVs9wh7Yv+hkpr9REuY9TrAtQB3HB0DLV9c/kqEhwBQtEMDx6yA/w+UEQBJoCMDFkZE/O+CNPzGyTsDN+yJAjbwZwMZqzL4fZTxA4vLSv1MvkD6LbMy/b0mwvyjKEj/XxxFA1yGxvvrFLb+GT58/2KT4vg==", "training_traits": {"structure_gen": "Random", "n_layers": 2, "max_nodes": 6, "activation_func": "Sigmoid", "epoch_num": 11}, "classes_name": ["Cryptoadz", "Cryptopunks", "Moonbirds", "Nouns"]},m=25,b=50,y=59+11/12,w=59+11.5/12,v=60;function z(e,t){coM nst n=Math.log(1-t)/Math.log(1-e);return e=>1-Math.pow(1-e,n)}class V{constructor(e,t,n){const{model:r,inputDim:i}=j(t,n);this.model=r,this.inputDim=i,this.iteration=0,this.stage=0;const o=new Date(parseInt(e.birthYear),0,1).getTime(),a=new Date(parseInt(e.birthYear)+1,0,1).getTime();this.birthDate=new Date(Math.floor((o+a)/2));const l=zr.filter((t=>t[0]==e.lifeCycle))[0][2];this.growSpeed=365/l,this.cycleLength=60*l*24*3600*1e3,this.growthFunc=z(.4,.8)}updateAge(e){const t=(e.getTime()-this.birthDate.getTime())/31M 536e6*this.growSpeed;this.iteration=Math.floor(t/60);const n=t-60*this.iteration;let r;this.age=n;let i,o=0;if(n<25){let e=map(n,0,25,0,1);o=this.growthFunc(e),r=(25-n)/60,this.stage=1,this.stageRatio=map(n,0,25,0,1)}else n<50?(o=1,r=(50-n)/60,this.stage=2,this.stageRatio=map(n,25,50,0,1)):n<y?(o=map(n,50,y,1,0),r=(y-n)/60,this.stage=3,this.stageRatio=map(n,50,y,0,1)):n<w?(o=0,r=(w-n)/60,this.stage=4,this.stageRatio=map(n,y,w,0,1)):n<60&&(o=0,r=(60-n)/60,this.stage=5,this.stageRatio=map(n,w,60,0,1));n<50?i=map(n,0,M 50,0,780/880):n<w?i=map(n,50,w,780/880,800/880):n<60&&(i=map(n,w,60,800/880,1)),this.nextStateTimestamp=Math.round(e.getTime()+this.cycleLength*r),this.statePercentage=round(100*i);let a=(25-n)/60;a<0&&(a+=1),this.nextStableTimestamp=Math.round(e.getTime()+this.cycleLength*a),this.growth=o,this.model.updateNeurons(o,this.iteration)}getBrainStatus(){return{totalNeurons:this.model.getTotalNeurons(),neuronsLife:this.model.getNeuronsLife(),stage:this.stage,inputDim:this.inputDim,stageRatio:this.stageRatio,age:this.age,M growth:this.growth,nextStateTimestamp:this.nextStateTimestamp,nextStableTimestamp:this.nextStableTimestamp,rebirthCount:max(this.iteration,0),statePercentage:this.statePercentage}}classifyImage(e){const t=new G(e,1,e.length);return this.model.forward(t).mat[0]}}class M{constructor(e,t,n,r,i){this.p=e,this.v=t,this.size=n,this.shape=i,this.col=r}getRadius(){return 1==Oe?1*this.size/2:2==Oe?7*this.size/16:3==Oe||4==Oe?4*this.size/7:0}update(){this.p.add(this.v)}draw(e,t,n,r){const i=this.p.x*r,o=this.p.y*r,a=this.sizM e*r,{col:l,shape:s}=this;let h,c;1==n?h=c=l:2==n?(h=dr(t,1),c=l):(h=dr(t,0),c=dr(l,1));e.stroke(dr(c,map(1,0,1,.25,1))),e.fill(dr(h,map(1,0,1,.15,1))),3==n&&e.fill(dr(h,0)),1==s?e.ellipse(i,o,a,a):2==s?e.rect(i,o,7*a/8,7*a/8):3==s&&(e.beginShape(),e.vertex(i-4*a/7,o),e.vertex(i,o-4*a/7),e.vertex(i+4*a/7,o),e.vertex(i,o+4*a/7),e.endShape(CLOSE))}}class E{constructor(e,t,n,r,i,o,a){this.center=e,this.len=t,this.angle=n,this.v=r,this.angV=i,this.c1=o,this.c2=a}getEndpoints(){const e=createVector(this.len/2*cos(this.anM gle),this.len/2*sin(this.angle));return[Vector.add(this.center,e),Vector.sub(this.center,e)]}update(){this.center.add(this.v),this.angle+=this.angV}draw(e,t){const[n,r]=this.getEndpoints(),i=n.x*t,o=n.y*t,a=r.x*t,l=r.y*t,s=this.c1,h=this.c2;var c=e.drawingContext.createLinearGradient(i,o,a,l);c.addColorStop(0,s),c.addColorStop(1,h),e.drawingContext.strokeStyle=c,e.drawingContext.globalAlpha=1,e.line(i,o,a,l),e.drawingContext.globalAlpha=1}}function S(e,t){const n=random(TAU),r=random(e,t);return createVector(r*cos(M n),r*sin(n))}class R{constructor(e,t,n,r,i){this.wall=n,this.maxR=i;const o=t.length;this.nodes=[];for(let a=0;a<o;++a){const o=[],l=.25*t[a];for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),random(n.yTop,n.yBottom)),l=S(.02*i,.05*i),s=random(10,25)*i;o.push(new M(t,l,s,e[a],r))}this.nodes.push(o)}const a=A(e);a.unshift(e[0]),a.push(e[e.length-1]),this.lines=[];for(let e=0;e<=o;++e){const r=[],l=(0==e?1:t[e-1])*(e==o?1:t[e])*1.5;for(let t=0;t<l;++t){const t=createVector(random(n.xLeft,n.xRight),raM ndom(n.yTop,n.yBottom)),o=random(5*i,10*i),l=random(TAU),s=S(.02*i,.05*i),h=random(2e-4,.001);r.push(new E(t,o,l,s,h,a[e],a[e+1]))}this.lines.push(r)}}reflectNode(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,{p:o,v:a}=e,l=e.getRadius();(o.x-l<t&&a.x<0||o.x+l>r&&a.x>0)&&(a.x=-a.x),(o.y-l<n&&a.y<0||o.y+l>i&&a.y>0)&&(a.y=-a.y)}reflectLine(e){const{xLeft:t,yTop:n,xRight:r,yBottom:i}=this.wall,[o,a]=e.getEndpoints(),l=e.v;(min(o.x,a.x)<t&&l.x<0||max(o.x,a.x)>r&&l.x>0)&&(l.x=-l.x),(min(o.y,a.y)<n&&l.y<0||max(o.yM ,a.y)>i&&l.y>0)&&(l.y=-l.y)}update(){for(const e of this.lines)for(const t of e)t.update(),this.reflectLine(t);for(const e of this.nodes)for(const t of e)t.update(),this.reflectNode(t)}draw(e,t,n,r,i){const o=i/this.maxR;for(const t of this.lines){const n=t.length*r;for(let r=0;r<n;++r)t[r].draw(e,o)}for(const i of this.nodes){const a=i.length*r;for(let r=0;r<a;++r)i[r].draw(e,t,n,o)}}}function I(e,t){re(e),e.fill(0),e.rect(0,0,500,500),ie(e),e.noStroke(),e.fill(dr(cr("#000000"),.5)),e.push(),e.translate(250,250),eM .scale(t),e.translate(-250,-250),e.beginShape(),e.vertex(235.2,24.9),e.bezierVertex(215,24.6,185,11.4,164.8,11),e.bezierVertex(147.2,10.7,129.3,10.4,112.2,14.7),e.bezierVertex(95.1,19,78.5,28.5,69.6,43.8),e.bezierVertex(57.699,64.199,61.599,90.199,70.199,112.2),e.bezierVertex(78.799,134.2,91.6,154.6,97.199,177.5),e.bezierVertex(102.499,199.2,100.899,222.5,92.799,243.2),e.bezierVertex(83,268,64.6,288.3,48.9,310),e.bezierVertex(33.2,331.7,24.5,337.5,26.599,364.1),e.bezierVertex(28.2,384.1,61.399,404.2,75.7,418.3),e.bM ezierVertex(90,432.4,73.7,488.2,91.9,496.7),e.bezierVertex(124.2,511.6,159,472.5,194.3,468.1),e.bezierVertex(211.6,465.9,267.4,501.5,283.9,495.9),e.bezierVertex(340.7,476.7,298.599,428.9,355.4,409.7),e.bezierVertex(370.799,404.5,454.5,407.6,464.4,394.8),e.bezierVertex(478.599,376.3,474.7,349.3,464.299,328.4),e.bezierVertex(453.9,307.5,438.099,289.5,428.699,268.2),e.bezierVertex(412,230,419,182.6,446.1,150.9),e.bezierVertex(449.7,146.7,453.6,142.7,455.8,137.6),e.bezierVertex(459.4,129.299,457.5,119.6,454.8,111),e.beM zierVertex(443.2,73.4,417.3,40.4,383.6,20.299),e.bezierVertex(358.1,5,343.2,-.4,313.5,0),e.bezierVertex(287.5,.4,261.6,25.4,235.2,24.9),e.endShape(),e.pop()}function C(e,t,n,r,i,o){let a,l,s;re(t),t.fill(0),t.rect(0,0,500,500),ie(t),t.noStroke(),t.fill(dr(n,.5)),1==i?(l=0,s=25,a=map(o,0,25,500,0)):a=0,t.rect(0,a,500,500),e.noStroke(),e.fill(r),e.rect(0,0,500,500),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVerteM x(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.M 6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.M 7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,107.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezM ierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),e.fill(n),e.beginShape(),e.vertex(435.2,373.8),e.bezierVertex(433.7,384.1,433.3,393.7,430.8,402.7),e.bezierVertex(424.1,426.3,408.9,442.9,386.3,452.5),e.bezierVertex(383.2,453.8,381,455.5,379,458.3),e.bezierVertex(348.6,501.7,285,502.4,253.5,459.8),e.bezierVertex(252.5,458.4,251.4,457.1,250.3,455.6),e.bezierVertex(246.2,460.3,242.7,465.1,238.5,469.1),e.bezierVertex(203.8,502.8,148.8,497.4,120.7,457.8),e.bezM ierVertex(119.3,455.8,117,453.9,114.7,452.9),e.bezierVertex(84.9,440.6,66.2,412.9,66.4,380.7),e.bezierVertex(66.4,376.3,65.3,373.7,61.7,371.1),e.bezierVertex(33.5,350.4,25.3,313.2,41.8,282.4),e.bezierVertex(43.2,279.9,43.6,278,42.1,275.1),e.bezierVertex(28.2,247.7,30.4,221.6,49.6,197.3),e.bezierVertex(51.7,194.6,51.7,192.3,51.2,189.4),e.bezierVertex(46.8,164.8,53.5,143.7,71.1,126.1),e.bezierVertex(77.699,119.6,85.399,114.8,94,111.5),e.bezierVertex(96.1,110.7,98.3,109.9,100.7,109),e.bezierVertex(100.2,106,99.8,103.2M ,99.4,100.4),e.bezierVertex(96.6,79.7,107.1,58.7,125.2,48.2),e.bezierVertex(129.4,45.8,133.4,43.2,137.3,40.3),e.bezierVertex(154.2,28,172.3,18,192.5,12.1),e.bezierVertex(202.7,9.1,213.1,7.2,223.8,8.8),e.bezierVertex(233.8,10.3,242.4,14.9,249.7,22.4),e.bezierVertex(250.7,21.7,251.6,21.2,252.3,20.5),e.bezierVertex(263.8,9.9,277.5,6.8,292.6,9),e.bezierVertex(316.9,12.6,338.1,23.5,358.1,37.1),e.bezierVertex(364.3,41.3,370.5,45.5,376.9,49.5),e.bezierVertex(395,61,404.3,82.9,400,104.5),e.bezierVertex(399.7,105.9,399.5,10M 7.3,399.2,108.9),e.bezierVertex(402.7,110.3,406,111.4,409.3,112.9),e.bezierVertex(438.5,125.8,455.1,157.3,449,188.7),e.bezierVertex(448.3,192.4,448.6,195.2,451.3,198.4),e.bezierVertex(469,219.5,471.6,249.7,458.1,274.9),e.bezierVertex(456.7,277.5,456.5,279.4,458,282.2),e.bezierVertex(475.1,314.2,466.5,351.1,437,372.3),e.bezierVertex(436.2,373.1,435.1,373.8,435.2,373.8),e.endShape(),re(e),e.fill(r),e.beginShape(),e.vertex(184.3,473.2),e.bezierVertex(164,473.2,144.7,462.099,134,444.3),e.bezierVertex(131.7,440.5,129.1,M 438.5,125,437.1),e.bezierVertex(97.3,428.1,80.5,400.6,85.2,371.8),e.bezierVertex(86.3,365.1,85.8,364.1,79.9,361.2),e.bezierVertex(57.2,349.8,46.2,323.3,54.3,299.7),e.bezierVertex(54.7,298.599,55.1,297.7,55.5,296.9),e.bezierVertex(55.6,296.599,55.8,296.4,55.9,296.099),e.vertex(57.9,291.499),e.vertex(62.5,293.599),e.bezierVertex(64.9,294.7,67.3,295.799,69.5,296.9),e.bezierVertex(74.5,299.299,79.1,301.599,83.9,303.099),e.bezierVertex(89.8,304.9,96.5,305.499,102.7,305.9),e.bezierVertex(102.8,305.9,102.9,305.9,103,305.9M ),e.bezierVertex(106.6,305.9,108.9,302.799,109,299.799),e.bezierVertex(109.1,296.199,106.6,293.4,102.7,292.799),e.bezierVertex(101.3,292.599,99.9,292.4,98.4,292.299),e.bezierVertex(94.3,291.799,90.1,291.299,86,289.9),e.bezierVertex(68.9,284,56.5,270.2,52.7,252.799),e.bezierVertex(48.9,235.499,54.5,217.7,67.6,205.299),e.bezierVertex(71.9,201.299,72.7,198.1,70.8,192.399),e.bezierVertex(64.2,172.2,68.8,153.99,84.2,139.599),e.bezierVertex(94.2,130.199,105.5,125.399,117.8,125.399),e.bezierVertex(124.3,125.399,131.1,126.M 799,137.8,129.599),e.bezierVertex(157,137.399,167.9,152.799,169.4,173.99),e.vertex(169.4,174.399),e.bezierVertex(169.5,175.899,169.6,177.2,169.9,178.299),e.bezierVertex(170.7,181.2,173.2,183.2,176.1,183.2),e.bezierVertex(176.299,183.2,176.5,183.2,176.7,183.2),e.bezierVertex(180.1,182.899,182.6,180.299,182.7,177),e.bezierVertex(183.1,162,178.299,148.2,168.399,136.1),e.bezierVertex(158.2,123.5,144.899,115.8,128.799,113.199),e.bezierVertex(123.499,112.299,120.399,109.799,118.899,104.99),e.bezierVertex(113.899,89.699,1M 20.699,72.299,134.899,64.499),e.bezierVertex(139.99,61.699,145.799,60.199,151.7,60.199),e.bezierVertex(162.2,60.199,171.899,64.799,178.1,72.699),e.bezierVertex(179.6,74.6,180.799,76.6,181.9,78.499),e.vertex(182.2,79.099),e.bezierVertex(183.2,80.699,185.2,83.299,188.4,83.299),e.bezierVertex(189.5,83.299,190.6,82.99,191.7,82.399),e.bezierVertex(195.1,80.599,196,76.99,194,72.799),e.bezierVertex(190.1,64.799,184.1,58.499,175.6,53.299),e.bezierVertex(174.6,52.699,173.7,52.099,172.5,51.499),e.vertex(170.5,50.299),e.verteM x(163,45.899),e.vertex(170.5,41.599),e.bezierVertex(182,34.99,193.1,30.799,204.4,28.599),e.bezierVertex(208.6,27.799,212.9,27.399,217.2,27.399),e.bezierVertex(217.6,27.399,217.9,27.399,218.3,27.399),e.bezierVertex(231.4,27.599,242.7,38.199,243,50.599),e.bezierVertex(243.4,64.899,243.3,78.99,243.2,93.799),e.bezierVertex(243.2,99.799,243.1,105.899,243.1,112.099),e.vertex(243.1,119.199),e.vertex(236.4,116.799),e.bezierVertex(235.7,116.499,235,116.299,234.4,115.99),e.bezierVertex(233.4,115.599,232.6,115.299,232,115.199M ),e.bezierVertex(230.6,114.899,229.2,114.599,227.8,114.299),e.bezierVertex(223.8,113.499,220.1,112.699,216.4,112.499),e.vertex(216.2,112.499),e.bezierVertex(212.5,112.499,210.7,115.599,210.6,118.599),e.bezierVertex(210.4,122.399,212.7,125.099,216.4,125.399),e.bezierVertex(230.1,126.399,238.9,133.099,242.3,145.199),e.bezierVertex(243.2,148.399,243.2,151.599,243.2,154.499),e.vertex(243.2,155.099),e.bezierVertex(243.2,254.199,243.2,330,243.2,400.599),e.bezierVertex(243.2,401.99,243.2,403.4,243.2,404.9),e.bezierVertex(M 243.3,411.099,243.3,417.599,242.3,423.9),e.bezierVertex(238.1,449.2,219.6,467.799,194,472.5),e.bezierVertex(190.9,472.9,187.6,473.2,184.3,473.2),e.endShape(),e.beginShape(),e.vertex(315.8,473.1),e.bezierVertex(309.3,473.1,302.8,472,296.5,469.9),e.bezierVertex(270.4,461,253.8,434.9,257.1,407.9),e.bezierVertex(260,384,273.8,366.8,297,358.3),e.bezierVertex(297.7,358.1,298.3,357.8,299,357.6),e.bezierVertex(299.8,357.3,300.6,357.1,301.2,356.8),e.bezierVertex(304.3,355.4,306,351.8,304.9,348.7),e.bezierVertex(304,345.9,30M 1.7,344.2,299,344.2),e.bezierVertex(298.6,344.2,298.1,344.2,297.6,344.3),e.bezierVertex(288.1,346.3,279,350.9,269.7,358.3),e.bezierVertex(268.9,358.9,268.1,359.6,267.2,360.4),e.vertex(265.5,361.8),e.vertex(258.5,367.6),e.vertex(257.4,358.6),e.bezierVertex(257.3,358,257.3,357.5,257.2,357.1),e.bezierVertex(257,356,256.9,354.9,256.9,353.7),e.bezierVertex(256.9,334.8,256.9,316,256.9,297.1),e.bezierVertex(256.9,260.3,256.9,222.3,256.8,185),e.bezierVertex(256.8,170.7,268.3,158.8,282.5,158.4),e.bezierVertex(284.8,158.3,28M 6.7,157.6,287.9,156.2),e.bezierVertex(289.099,154.9,289.599,153.2,289.5,151.3),e.bezierVertex(289.3,147.5,286.7,145.1,282.7,145.1),e.bezierVertex(282.5,145.1,282.2,145.1,282,145.1),e.bezierVertex(278.8,145.3,275.5,146.1,272,146.9),e.bezierVertex(270.9,147.2,269.8,147.4,268.6,147.7),e.bezierVertex(267.9,147.9,267,148.2,265.8,148.7),e.bezierVertex(265.1,149,264.4,149.3,263.5,149.6),e.vertex(256.8,152),e.vertex(256.8,114.6),e.bezierVertex(256.8,95,256.8,75.4,256.8,55.9),e.bezierVertex(256.8,38,267.2,27.3,284.6,27.3),eM .bezierVertex(285.3,27.3,285.9,27.3,286.6,27.3),e.bezierVertex(299,27.9,318.7,34.5,329.6,41.9),e.vertex(336.1,46.3),e.vertex(324.4,53.3),e.bezierVertex(316.2,58.2,310.2,64.6,306,72.9),e.bezierVertex(304.2,76.4,305.1,78.5,306.1,80),e.bezierVertex(307.4,81.9,309.4,83,311.6,83),e.bezierVertex(313.7,83,315.7,81.9,317.1,80.1),e.bezierVertex(317.4,79.7,317.8,79,318.1,78.4),e.bezierVertex(318.4,77.9,318.7,77.3,319,76.8),e.bezierVertex(325.3,66.2,336.3,59.9,348.5,59.9),e.bezierVertex(353.2,59.9,357.8,60.8,362.1,62.7),e.bezM ierVertex(377.6,69.3,386,86.7,381.7,103.2),e.bezierVertex(380.7,107.1,378.5,111.8,371.1,113.1),e.bezierVertex(342.7,118.1,322.2,139.1,317.8,167.8),e.bezierVertex(317.4,170.3,317.3,173.2,317.4,176.5),e.bezierVertex(317.5,180,320.1,182.8,323.5,183),e.bezierVertex(323.6,183,323.8,183,323.9,183),e.bezierVertex(327.1,183,329.8,180.6,330.3,177.2),e.bezierVertex(330.6,175.7,330.7,174,330.9,172.3),e.bezierVertex(331.1,169.8,331.4,167.3,332,164.7),e.bezierVertex(337.3,141.9,357.7,125.4,380.7,125.4),e.bezierVertex(382.5,125.M 4,384.3,125.5,386.1,125.7),e.bezierVertex(412.8,128.9,432.6,150.9,432,176.9),e.bezierVertex(431.9,182.3,430.9,187.7,429.1,192.7),e.bezierVertex(427.2,197.9,428,201,432.3,205),e.bezierVertex(446.8,218.7,451.8,236,446.6,255),e.bezierVertex(441.4,274,428.3,286.5,408.7,291.3),e.bezierVertex(406.1,291.9,403.6,292.1,401.1,292.3),e.bezierVertex(400,292.4,398.9,292.5,397.9,292.6),e.bezierVertex(393.6,293.1,390.9,295.7,391,299.5),e.bezierVertex(391.1,303.4,394,305.8,398.5,305.8),e.bezierVertex(409.9,305.8,420.8,302.6,431.1,M 296.4),e.bezierVertex(431.8,296,432.5,295.5,433.2,295.1),e.bezierVertex(433.8,294.7,434.5,294.3,435.2,293.9),e.bezierVertex(436,293.4,436.6,293.2,437.2,293.1),e.bezierVertex(437.4,293,437.7,292.9,438.1,292.8),e.vertex(442.5,291.4),e.vertex(444.2,295.7),e.bezierVertex(450.9,312.4,449.5,328.4,440,343.4),e.bezierVertex(435.3,350.8,428.7,356.7,420.2,361.1),e.bezierVertex(414.3,364.1,413.7,365.2,414.8,371.7),e.bezierVertex(419.5,400.2,403,427.6,375.6,436.9),e.bezierVertex(371,438.5,368.3,440.7,365.8,444.7),e.bezierVerteM x(355.2,462.5,336.4,473.1,315.8,473.1),e.bezierVertex(315.8,473.1,315.8,473.1,315.8,473.1),e.endShape(),ie(e),e.fill(n),e.beginShape(),e.vertex(120.2,279.9),e.bezierVertex(117.9,279.9,112.4,279.299,112.2,273.599),e.bezierVertex(112,267.7,117.4,266.7,119.7,266.599),e.bezierVertex(133.1,265.799,143.1,259.499,149.3,247.899),e.bezierVertex(149.6,247.299,150.1,246.399,150.3,245.399),e.bezierVertex(150.6,244.299,150.5,243.299,150.5,242.7),e.bezierVertex(150.5,242.6,150.5,242.5,150.5,242.299),e.vertex(150.3,238.799),e.verM tex(141.1,235.99),e.bezierVertex(114.6,227.799,95.6,202.499,95.9,175.799),e.bezierVertex(95.9,173.99,96.4,168.199,102.2,168.199),e.bezierVertex(102.6,168.199,103,168.199,103.4,168.299),e.bezierVertex(104.8,168.499,108.2,168.899,109.2,175.599),e.bezierVertex(109.3,176.599,109.5,177.599,109.6,178.499),e.bezierVertex(110.4,184.199,111.3,189.99,113.7,195.499),e.bezierVertex(121.9,213.99,139.5,225.499,159.7,225.499),e.bezierVertex(172.1,225.499,184.1,220.899,193.5,212.599),e.bezierVertex(194,212.199,194.4,211.799,194.8,M 211.399),e.bezierVertex(195.1,211.099,195.5,210.799,195.8,210.399),e.bezierVertex(197.4,208.99,199.2,208.2,200.9,208.2),e.bezierVertex(202.5,208.2,204,208.899,205.3,210.1),e.bezierVertex(208,212.9,207.9,216.9,205,219.9),e.bezierVertex(196.5,228.6,186.3,234.3,174.7,236.8),e.bezierVertex(168.799,238.1,165.6,241,163.899,246.7),e.bezierVertex(158.3,265.9,139.9,279.7,120.2,279.9),e.vertex(120.2,279.9),e.endShape(),e.beginShape(),e.vertex(187.2,427.5),e.bezierVertex(183.799,427.5,181.299,425.3,180.799,422),e.bezierVertexM (180.6,420.8,180.499,419.5,180.399,418.1),e.bezierVertex(180.299,417,180.2,415.8,180.099,414.7),e.bezierVertex(177.199,390.5,156.699,371.3,132.399,370.2),e.bezierVertex(131.99,370.2,131.499,370.2,131.099,370.2),e.bezierVertex(130.699,370.2,130.299,370.2,129.799,370.2),e.bezierVertex(125.99,369.9,123.199,367.2,123.099,363.6),e.bezierVertex(122.99,360.2,125.799,357.3,129.599,356.9),e.bezierVertex(130.499,356.8,131.499,356.8,132.599,356.7),e.bezierVertex(133.199,356.7,133.799,356.7,134.399,356.6),e.vertex(138.299,356.M 4),e.vertex(139.1,352.6),e.bezierVertex(139.5,350.7,139.799,348.9,140.2,347),e.bezierVertex(140.899,343.4,141.5,340,142.399,336.8),e.bezierVertex(150.099,310.7,174.399,292,201.399,291.3),e.vertex(201.599,291.3),e.bezierVertex(203.699,291.3,206.299,292,208.299,293.2),e.bezierVertex(210.499,294.5,210.699,297.5,209.99,299.8),e.bezierVertex(209.499,301.5,208.199,303.9,203.299,304.7),e.bezierVertex(202.199,304.9,200.99,305,199.799,305.2),e.bezierVertex(194.499,305.9,188.99,306.599,183.799,308.9),e.bezierVertex(165.499,3M 16.799,155.199,331.299,152.99,352),e.bezierVertex(152.399,357.8,154.499,361.7,159.699,364.5),e.bezierVertex(178.199,374.4,189.399,390,193.099,410.9),e.bezierVertex(193.699,414.299,193.899,418,193.599,422),e.bezierVertex(193.399,425.2,190.899,427.5,187.399,427.5),e.vertex(187.2,427.5),e.endShape(),e.beginShape(),e.vertex(364.3,281.1),e.bezierVertex(346.3,280.6,332.9,272.8,323.5,257),e.bezierVertex(321.6,253.9,320.4,250.2,319.2,246.7),e.bezierVertex(317.7,242.2,315,239.799,310.5,238.799),e.bezierVertex(298.5,236.299,M 288,230.7,279.4,222.1),e.bezierVertex(276.7,219.4,274.9,215.299,278,211.9),e.bezierVertex(279.4,210.3,281,209.6,282.6,209.6),e.bezierVertex(284.4,209.6,286.4,210.6,288.3,212.5),e.bezierVertex(297.8,221.8,310.4,226.9,323.9,226.9),e.bezierVertex(340.2,226.9,355.1,219.3,364.8,206.2),e.bezierVertex(371,197.8,374.2,188.5,374.5,178.5),e.vertex(374.5,177.9),e.bezierVertex(374.5,177,374.5,176.1,374.7,175.4),e.bezierVertex(375.3,171.8,377.9,169.5,381.3,169.5),e.bezierVertex(381.4,169.5,381.5,169.5,381.7,169.5),e.bezierVerteM x(385.4,169.7,388,172.4,388,176.1),e.bezierVertex(388.1,190.7,383.4,204,374.2,215.8),e.bezierVertex(365.8,226.5,354.7,233.9,341.2,237.9),e.bezierVertex(340,238.3,338.7,238.6,337.3,239.1),e.bezierVertex(335.9,239.6,335.1,240.4,334.7,240.9),e.bezierVertex(334.599,241,334.5,241.1,334.4,241.2),e.vertex(331.799,243.6),e.vertex(333.199,246.8),e.bezierVertex(338.199,258,346.799,264.9,358.699,267.3),e.bezierVertex(360.199,267.6,361.599,267.7,362.99,267.9),e.bezierVertex(363.599,268,364.299,268,364.899,268.1),e.bezierVertexM (369.099,268.6,371.799,271.4,371.499,275),e.bezierVertex(371.199,278.6,368.299,281.2,364.399,281.2),e.vertex(364.3,281.1),e.endShape(),e.beginShape(),e.vertex(323.9,437),e.bezierVertex(323.7,437,323.5,437,323.299,437),e.bezierVertex(319.599,436.7,317.299,434.1,317.4,430.2),e.bezierVertex(317.9,406.099,328.299,388,349.5,375),e.bezierVertex(350.7,374.2,352,373.5,353.4,372.8),e.bezierVertex(354.099,372.4,354.7,372.1,355.299,371.7),e.vertex(357.499,370.5),e.vertex(357.799,368),e.bezierVertex(360.4,346.6,345.199,323.7,3M 23.9,317),e.bezierVertex(319.099,315.5,314.099,314.9,309.299,314.4),e.vertex(308.199,314.299),e.bezierVertex(305.99,314.099,300.799,312.9,300.899,307.299),e.bezierVertex(300.99,303.499,303.899,300.9,308.099,300.9),e.vertex(308.299,300.9),e.bezierVertex(327.099,301.299,343.099,308.7,355.699,322.9),e.bezierVertex(364.299,332.5,369.399,344.099,370.99,357.299),e.bezierVertex(371.099,358.4,371.299,359.4,371.499,360.499),e.bezierVertex(371.599,360.99,371.699,361.499,371.799,361.99),e.vertex(372.499,365.899),e.vertex(377.M 899,366.199),e.bezierVertex(378.799,366.299,379.699,366.299,380.599,366.399),e.bezierVertex(385.099,366.699,387.899,369.399,387.799,373.299),e.bezierVertex(387.699,377.099,384.99,379.599,380.799,379.799),e.bezierVertex(369.799,380.199,359.99,383.299,351.899,389.299),e.bezierVertex(338.799,398.799,331.699,411.699,330.699,427.499),e.vertex(330.699,428.299),e.bezierVertex(330.599,429.199,330.599,430.099,330.499,430.799),e.bezierVertex(330,434.7,327.5,437,323.9,437),e.endShape()}function T(e){return e[0].map(((t,n)=>e.M map((e=>e[n]))))}function A(e){return e.map((e=>Array.isArray(e)?A(e):e))}function D(e,t){return floor(random(e,t))}function k(e){let t=0;for(const n of e)t+=n[1];let n=random(t),r=0;for(const t of e)if(r+=t[1],n<r)return t[0];return null}function L(e){for(let t=1;t<e.length;++t){let n=D(0,t),r=e[t];e[t]=e[n],e[n]=r}}function P(e){return null==e||""===e}function O(e){return new Promise((t=>setTimeout(t,e)))}function F(e,t,n){let r=0;for(let i=1;i<=1e3;++i)for(let o=1;o<=1e3;++o)if(e*o%(t*i)==0){let e=1*i/o;abs(e-n)M <abs(r-n)&&(r=e)}return r}function N(){let e=60*(new Date).getTimezoneOffset()*1e3;return new Date(Date.now()-e).toISOString().slice(0,-1)}function B(e,t,n){let r;if(push(),textSize(e),textWidth(t)<=n)r=t;else for(let e=0;e<t.length;++e){const i=t.slice(0,e+1)+"...";if(textWidth(i)>n){r=i;break}}return pop(),r}function Y(e){var t=e%10,n=e%100;return 1==t&&11!=n?e+"st":2==t&&12!=n?e+"nd":3==t&&13!=n?e+"rd":e+"th"}class G{constructor(e,t,n){this.n=t,this.m=n,this.mat=[];let r=0;for(let t=0;t<this.n;++t){this.mat.pushM ([]);for(let n=0;n<this.m;++n)this.mat[t].push(r<e.length?e[r]:0),r+=1}return this}copy(){return new G(this.mat.flat(),this.n,this.m)}}class H{static __linear=e=>e;static __relu=e=>Math.max(e,0);static __leaky_relu=e=>e>0?e:.2*e;static __sigmoid=e=>1/(1+Math.exp(-e));static __tanh=e=>Math.tanh(e);static __apply_unary_op(e,t){const n=e.copy();for(let e=0;e<n.n;++e)for(let r=0;r<n.m;++r)n.mat[e][r]=t(n.mat[e][r]);return n}static linear=e=>H.__apply_unary_op(e,H.__linear);static relu=e=>H.__apply_unary_op(e,H.__relu);M static leaky_relu=e=>H.__apply_unary_op(e,H.__leaky_relu);static sigmoid=e=>H.__apply_unary_op(e,H.__sigmoid);static tanh=e=>H.__apply_unary_op(e,H.__tanh);static __add=(e,t)=>e+t;static __mul=(e,t)=>e*t;static __apply_binary_op=(e,t,n)=>{"object"!=typeof t&&(t=new G([t],1,1));const r=e.copy();for(let e=0;e<r.n;++e)for(let i=0;i<r.m;++i)r.mat[e][i]=n(r.mat[e][i],t.mat[e%t.n][i%t.m]);return r};static mul=(e,t)=>H.__apply_binary_op(e,t,H.__mul);static add=(e,t)=>H.__apply_binary_op(e,t,H.__add);static matMul(e,t){conM st n=new G([],e.n,t.m);for(let r=0;r<n.n;++r)for(let i=0;i<n.m;++i)for(let o=0;o<e.m;++o)n.mat[r][i]+=e.mat[r][o]*t.mat[o][i];return n}static softmax(e){const t=H.__apply_unary_op(e,(e=>Math.exp(e))),n=t.mat.flat().reduce(((e,t)=>e+t));for(let r=0;r<e.n;++r)for(let i=0;i<e.m;++i)t.mat[r][i]/=n;return t}}class ${constructor(e,t){this.scale=e,this.offset=t}forward(e){return H.add(H.mul(e,this.scale),this.offset)}}class X{constructor(){}forward(e){return e.map((e=>e.flat()))}}class W{constructor(e,t,n,r){this.out_dim=M e,this.activation=t,this.w=n,this.b=r}forward(e){const t=H.add(H.matMul(e,this.w),this.b);return null==this.activation?t:this.activation(t)}}class U{constructor(e,t,n){this.preprocessLayers=e,this.hiddenLayers=t,this.outputLayer=n,this.totalNeurons=this.hiddenLayers.map((e=>e.out_dim)),this.currentOrders=[],this.currentIteration=null}updateNeurons(e,t){if(t!=this.currentIteration){this.currentOrders=[];for(let e=0;e<this.totalNeurons.length;++e){randomSeed(100*(t+1)+e);const n=[];for(let t=0;t<this.totalNeurons[e];M ++t)n.push(t);L(n),this.currentOrders.push(n)}this.currentIteration=t}const n=A(this.totalNeurons),r=n.reduce(((e,t)=>e+t))*(1-e);for(let e=0;e<r;++e){const t=n.map(((e,t)=>(e-1)/this.totalNeurons[t]));n[t.map(((e,t)=>[e,t])).reduce(((e,t)=>t[0]>e[0]?t:e))[1]]-=Math.min(r-e,1)}this.neuronsLife=[];for(let e=0;e<n.length;++e){const t=this.currentOrders[e],r=Array(this.totalNeurons[e]).fill(0);for(let i=0;i<n[e];++i)r[t[i]]=Math.min(n[e]-i,1);this.neuronsLife.push(r)}}getTotalNeurons(){return A(this.totalNeurons)}getNM euronsLife(){return A(this.neuronsLife)}forward(e){for(const t of this.preprocessLayers)e=t.forward(e);for(const[t,n]of this.hiddenLayers.entries()){e=n.forward(e);const r=new G(this.neuronsLife[t],1,e.m);e=H.mul(e,r)}return e=this.outputLayer.forward(e),H.softmax(e)}}function q(e){switch(e){case"relu":return H.relu;case"sigmoid":return H.sigmoid;case"tanh":return H.tanh;case"leaky_relu":return H.leaky_relu;default:return H.linear}}function j(e,t){const n=[],r=[],i=Z(t);let o=null,a=0,l=[];for(const t of e.config.lM ayers)if("InputLayer"==t.class_name)o=t.config.batch_input_shape.slice(1),l=o;else if("Rescaling"==t.class_name)n.push(new $(t.config.scale,t.config.offset));else if("Flatten"==t.class_name)o=[o.reduce(((e,t)=>e*t))];else if("Dense"==t.class_name){const e=[t.config.units],n=o[0]*e[0],l=e[0],s=i.subarray(a,a+n);a+=n;const h=i.subarray(a,a+l);a+=l;const c=new G(s,o[0],e[0]),u=new G(h,1,e[0]),f=q(t.config.activation);r.push(new W(e[0],f,c,u)),o=e}const s=r.pop();return{model:new U(n,r,s),inputDim:l}}function Z(e){consM t t=window.atob(e),n=t.length/Float32Array.BYTES_PER_ELEMENT,r=new DataView(new ArrayBuffer(Float32Array.BYTES_PER_ELEMENT)),i=new Float32Array(n);let o=0;for(let e=0;e<n;e++){o=4*e;for(let e=0;e<4;++e)r.setUint8(e,t.charCodeAt(o+e));i[e]=r.getFloat32(0,!0)}return i}class K{constructor(e){this.elt=e,this._events={},this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight}position(){if(0===arguments.length)return{x:this.elt.offsetLeft,y:this.elt.offsetTop};var e="absolute";return"static"!==arguments[2]&&"fiM xed"!==arguments[2]&&"relative"!==arguments[2]&&"sticky"!==arguments[2]&&"initial"!==arguments[2]&&"inherit"!==arguments[2]||(e=arguments[2]),this.elt.style.position=e,this.elt.style.left=arguments[0]+"px",this.elt.style.top=arguments[1]+"px",this.x=arguments[0],this.y=arguments[1],this}show(){return this.elt.style.display="block",this}hide(){return this.elt.style.display="none",this}size(e,t){if(0===arguments.length)return{width:this.elt.offsetWidth,height:this.elt.offsetHeight};var n=e,r=t;if(n!==te||r!==te){if(nM ===te?n=t*this.width/this.height:r===te&&(r=e*this.height/this.width),this.elt instanceof HTMLCanvasElement){var i,o={},a=this.elt.getContext("2d");for(i in a)o[i]=a[i];for(i in this.elt.setAttribute("width",n*this._pInst._pixelDensity),this.elt.setAttribute("height",r*this._pInst._pixelDensity),this.elt.style.width=n+"px",this.elt.style.height=r+"px",this._pInst.scale(this._pInst._pixelDensity,this._pInst._pixelDensity),o)this.elt.getContext("2d")[i]=o[i]}else this.elt.style.width=n+"px",this.elt.style.height=r+"pM x",this.elt.width=n,this.elt.height=r;this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight,this._pInst&&this._pInst._curElement&&this._pInst._curElement.elt===this.elt&&(this._pInst._setProperty("width",this.elt.offsetWidth),this._pInst._setProperty("height",this.elt.offsetHeight))}return this}style(e,t){if(t instanceof Color&&(t="rgba("+t.levels[0]+","+t.levels[1]+","+t.levels[2]+","+t.levels[3]/255+")"),void 0===t){if(-1===e.indexOf(":"))return window.getComputedStyle(this.elt).getPropertyValue(e);foM r(var n=e.split(";"),r=0;r<n.length;r++){var i=n[r].split(":");i[0]&&i[1]&&(this.elt.style[i[0].trim()]=i[1].trim())}}else if(this.elt.style[e]=t,"width"===e||"height"===e||"left"===e||"top"===e){var o=window.getComputedStyle(this.elt).getPropertyValue(e).replace(/[^\d.]/g,"");this[e]=Math.round(parseFloat(o,10))}return this}value(){return arguments.length>0?(this.elt.value=arguments[0],this):"range"===this.elt.type?parseFloat(this.elt.value):this.elt.value}mouseClicked(e){return this._adjustListener("click",e,thisM ),this}isFocused(){return document.activeElement===this.elt}_adjustListener(e,t,n){return!1===t?this._detachListener(e,n):this._attachListener(e,t,n),this}_attachListener(e,t,n){n._events[e]&&this._detachListener(e,n);var r=t.bind(n);n.elt.addEventListener(e,r,!1),n._events[e]=r}_detachListener(e,t){var n=t._events[e];t.elt.removeEventListener(e,n,!1),t._events[e]=null}}function J(e,t){var n=document.createElement("button");return n.innerHTML=e,t&&(n.value=t),ee(n)}function Q(e){var t=arguments.length>1&&void 0!==aM rguments[1]&&arguments[1],n=function(t){var n=!0,r=!1,i=void 0;try{for(var o,a=t.target.files[Symbol.iterator]();!(n=(o=a.next()).done);n=!0){var l=o.value;File._load(l,e)}}catch(e){r=!0,i=e}finally{try{n||null==a.return||a.return()}finally{if(r)throw i}}};if(window.File&&window.FileReader&&window.FileList&&window.Blob){var r=document.createElement("input");return r.setAttribute("type","file"),t&&r.setAttribute("multiple",!0),r.addEventListener("change",n,!1),ee(r)}}function ee(e){return document.body.appendChild(eM ),new K(e)}createImg=function(){var e,t=document.createElement("img"),n=arguments;return n.length>1&&"string"==typeof n[1]&&(t.alt=n[1]),n.length>2&&"string"==typeof n[2]&&(t.crossOrigin=n[2]),t.src=n[0],e=ee(t,this),t.addEventListener("load",(function(){e.width=t.offsetWidth||t.width,e.height=t.offsetHeight||t.height;var r=n[n.length-1];"function"==typeof r&&r(e)})),e},createInput=function(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:"",t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:"teM xt",n=document.createElement("input");return n.setAttribute("value",e),n.setAttribute("type",t),ee(n,this)};const te="auto";function ne(e){re(e);const t=e._rectMode;e.rectMode(CORNER),e.rect(0,0,e.width,e.height),e.rectMode(t),ie(e)}function re(e){e.push(),e.fill(255,255,255,255),e.blendMode(REMOVE)}function ie(e){e.blendMode(BLEND),e.pop()}File=function(e,t){this.file=e,this._pInst=t;var n=e.type.split("/");this.type=n[0],this.subtype=n[1],this.name=e.name,this.size=e.size,this.data=void 0},File._createLoader=funcM tion(e,t){var n=new FileReader;return n.onload=function(n){var r=new File(e);if("application/json"===r.file.type)r.data=JSON.parse(n.target.result);else if("text/xml"===r.file.type){var i=(new DOMParser).parseFromString(n.target.result,"text/xml");r.data=new XML(i.documentElement)}else r.data=n.target.result;t(r)},n},File._load=function(e,t){if(/^text\//.test(e.type)||"application/json"===e.type)File._createLoader(e,t).readAsText(e);else if(/^(video|audio)\//.test(e.type)){var n=new File(e);n.data=URL.createObjectUM RL(e),t(n)}else File._createLoader(e,t).readAsDataURL(e)},XML=function(e){if(e)this.DOM=e;else{var t=document.implementation.createDocument(null,"doc");this.DOM=t.createElement("root")}},document.addEventListener("DOMContentLoaded",(function(){addEventListener("mousemove",(e=>{window.mouseX=e.pageX,window.mouseY=e.pageY}))})),new e("global");const oe="244";let ae,le,se,he,ce,ue,fe,de,xe,ge,pe,me,be,ye,we,ve,ze,Ve,_e,Me,Ee,Se,Re,Ie,Ce,Te,Ae,De,ke,Le,Pe,Oe,Fe,Ne,Be,Ye,Ge,He,$e,Xe,We,Ue,qe,je,Ze,Ke,Je,Qe,et,tt,nt,rt,iM t,ot,at,lt,st,ht,ct,ut,ft,dt,xt,gt,pt,mt,bt,yt,wt,vt,zt,Vt,_t,Mt,Et,St,Rt,It,Ct,Tt,At=!1,Dt=!1,kt=!0,Lt=!1,Pt=!1;const Ot=[" ","Growing","Stable","Decaying","Dead","Rebirth"];let Ft,Nt,Bt,Yt,Gt,Ht,$t,Xt,Wt,Ut,qt,jt,Zt,Kt,Jt,Qt,en,tn,nn,rn,on,an,ln,sn,hn=0,cn=0,un=0,fn=!1,dn=!0,xn=!0,gn=null,pn=null,mn=null,bn=!1,yn=!1,wn=null,vn=null,zn=!1;async function setup(){let e=windowWidth,t=windowHeight;createCanvas(e,t),et=createGraphics(e,t),Xe=createGraphics(e,t),$e=createGraphics(e,t),We=createGraphics(e,t),Ue=createGraM phics(e,t),qe=createGraphics(e,t),Qe=createGraphics(e,t),je=createGraphics(e,t),Ze=createGraphics(e,t),Ke=createGraphics(e,t),Je=createGraphics(e,t),tt=createGraphics(500,500),nt=createGraphics(500,500),rt=createGraphics(500,500),_n(),Mn(),Sn(),await En(),Gn(),Rn(),bn=!0}function _n(){Et=parseInt(oe),randomSeed(Et),noiseSeed(Et)}function Mn(){Wt=Ir(p.training_traits),Cr(Wt)}async function En(){let e;Jt=r(),Qt=o(),[Xt,e]=await Promise.all([s(Jt),h(Qt)]),Ut=new V(Wt.visual,e.layers_config,e.weight_b64),Ut.updateAge(nM ew Date),_n(),Wt.training=e.training_traits,Ht=e.model_name,$t=e.classes_name}function Sn(){le=min(width,height)/1024,ut=Rr.findIndex((e=>e[0]===Wt.visual.colorPalette)),ft=[["#ffffff","#231f20","#231f20"],["#231f20","#ffffff","#ffffff"],["#104da8","#ffffff","#ffffff"],["#722F1F","#FCE1B2","#FCE1B2"],["#e88120","#f9f2e5","#f9f2e5"],["#f6b941","#2E2E2E","#2E2E2E"],["#45daaa","#012221","#012221"],["#F1F1F1","#328DFE","#328DFE"],["#111822","#D3EB8D","#D3EB8D"],["#713FF9","#D6D5E6","#D6D5E6"],["#FBDA9D","#795106","#795M 106"],["#8f5b62","#ead0d0","#ead0d0"],["#eae4cb","#508cac","#508cac"],["#ffc6cc","#cc313d","#cc313d"],["#60A900","#E0FE00","#E0FE00"],["#507DBE","#D0D1D3","#D0D1D3"],["#305848","#E8F2EE","#E8F2EE"],["#2a2634","#5b6988","#cb78a2","#5b6988"],["#590e29","#fd5e53","#fd5e53","#ffe373"],["#0a141d","#57d4e4","#328195","#2A9ECF","#0ab6a8","#57d4e4"],["#3a2d28","#d5c2ac","#df6338","#3d9895","#d5c2ac"],["#030706","#77c4d9","#77c4d9","#77c4d9","#ffffff","#ffffff","#e72020","#e72020"],["#3a4664","#92f5ff","#f9ff94","#eaa0a2","M #55dde0"],["#fbfaff","#f04bb1","#f04bb1","#fac373","#82cef0","#8b31ce"],["#000000","#ffffff","#ff0002","#f26522","#fdff00","#00ff03","#01fffe","#0000ff","#ff00ff"]];for(let e=0;e<ft.length;++e)for(let t=0;t<ft[e].length;++t)ft[e][t]=cr(ft[e][t]);pt=[],ct=ft[ut][0],st=ft[ut][1]}function Rn(){gn=document.querySelector("#upload"),pn=document.querySelector("#inputUpload"),gn.addEventListener("dblclick",(()=>{if(!Lt&&!yn)if(In(Ie)&&cn==Ve-1)pn.click();else{if(4!=Pe&&5!=Pe&&(In(Ie)||cn!=Ve-1))return;fn=!0,dn=!0,Bt=0,un=0M }})),pn.addEventListener("click",(()=>{pn.value=null,gn.style.display="block"})),pn.addEventListener("change",(()=>{const[e]=pn.files;e?(se=null,gn.style.display="none",Tn(URL.createObjectURL(e)),mn=e):gn.style.display="block"}))}function In(e){for(let t=0;t<e.length;++t){let n=0;for(let r=0;r<e[t].length;++r)e[t][r]>0&&++n;if(0==n)return!1}return!0}function Cn(){null!=se&&(un=0,Pt=!0,he=0,ue=0,drewLineAnim=!0,ce=(ae/2+we/2)/le,loadImage(se.elt.src,(e=>{const[t,n,r]=Gt,i=createGraphics(t,n);i.image(e,0,0,t,n),i.loaM dPixels();const o=i.pixels.filter(((e,t)=>t%4!=3)),a=Ut.classifyImage(o);Zt=T([a,$t.map((e=>e.toUpperCase()))]).sort(((e,t)=>e[0]>t[0]?-1:1))})))}function Tn(e){se=createImg(e,""),se.hide(),Cn()}function An(){zn||(ce+=(width-ae-we)/tn/le),re(Xe),Xe.rect(ce*le,0,width,height),ie(Xe),un>=ge&&1==kt&&(kt=!1,un-=ge),kt&&(re($e),$e.strokeWeight(2*Fe),Jn(he,ze,ct,ct,$e),ie($e)),un>=ge&&0==kt&&(kt=!0,un-=ge,he+=1,he==en&&(++ue,he=0,ce=(ae/2+we/2)/le,1==ue&&(Pt=!1,Dn(),ye=millis())))}function Dn(){At=!0,pe=!1,me=!1,tryButtoM n=br("Try Again",width/2-225*le,height/2+265*le,290*le,40*le,kn),closeResultButton=br("Close",width/2+75*le,height/2+265*le,150*le,40*le,Ln)}function kn(){At=!1,tryButton.hide(),closeResultButton.hide(),pn.click()}function Ln(){Yt=!0,At=!1,Gn(),tryButton.hide(),closeResultButton.hide(),gn.style.display="block",se=null}function keyTyped(){bn&&!1===yn&&!1===yr()&&("i"!==key&&"I"!==key||(Dt=!Dt),"b"!==key&&"B"!==key||(xn=!xn),"s"!==key&&"S"!==key||!1!==Lt||saveCanvasAtCurrentTime(),"k"!==key&&"K"!==key||!1!==Lt||save4M KCanvasAtCurrentTime(),"u"!==key&&"U"!==key||!1!==Lt||!1!==At||!1!==fn||!1!==Pt||On())}function On(){Lt=!0,wn=null,vn=null,submitButton=br("Submit",width/2-155*le,height/2+115*le,150*le,40*le,Fn),closeSettingButton=br("Close",width/2+5*le,height/2+115*le,150*le,40*le,Yn),vt=createInput(),vt.position(width/2-252.5*le,height/2-40*le),vt.size(500*le,25*le),vt.style("font-size","15px"),vt.value(Jt||""),zt=createInput(),zt.position(width/2-252.2*le,height/2+35*le),zt.size(500*le,25*le),zt.style("font-size","15px"),zt.vaM lue(Qt||"")}function Fn(){Vt=vt.value(),_t=zt.value(),submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide(),Lt=!1,yn=!0,Nn()}async function Nn(){[wn,vn,_]=await Promise.all([c(Vt),u(_t),O(1e3)]),yn=!1,wn&&vn?(n(Vt),i(_t),window.location.reload()):(Lt=!0,submitButton.show(),closeSettingButton.show(),vt.show(),zt.show())}function Bn(){Je.textFont("Trebuchet MS"),Je.noStroke(),pr(Je,600*le,200*le),Je.strokeWeight(1*le),Je.stroke(xt),Je.fill(xt),Je.textSize(50*le),Je.text("update()",width/2,height/2+2.5*le)M }function Yn(){wn=null,vn=null,Lt=!1,submitButton.hide(),closeSettingButton.hide(),vt.hide(),zt.hide()}function Gn(){_n(),nn=Date.now(),pe=!1,me=!1,St=Wt.training.structure_gen,Rt=Wt.visual.birthYear,It=Wt.visual.lifeCycle,Ct=Wt.training.epoch_num,Tt=Wt.training.activation_func,Ft=Mr.findIndex((e=>e[0]==Wt.visual.hardwareAcceleration))+1,1==Ft?(Nt=30,fe=40):2==Ft?(Nt=15,fe=20):(Nt=2,fe=10);const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=eM .nextStableTimestamp,Mt=e.age,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),ae=100*le,ht=50*le,Oe=Sr.findIndex((e=>e[0]==Wt.visual.nodeShape))+1,dt=Er.findIndex((e=>e[0]==Wt.visual.nodeFill))+1,lt=_r.findIndex((e=>e[0]==Wt.visual.pattern))+1,de=Math.tanh(Math.log10(Xt.avgfeerate)),de=mM ap(de,0,1,.2,.8),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0:Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/M r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;e++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,M 15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,at=.7,pt=[],xt=ft[ut][2],gt=ft[ut][ft[ut].length-1];for(let e=3;e<ft[ut].length-1;e++)pt.push(ft[ut][e]);mt=sr(xt,gt,pt,width),bt=[],wt=[],yt=width/(Ve-1);for(let e=0;e<Ve;e++)bt.push(hr(mt,yt*e/width)),wt.push(hr(mt,yt*e/width));wt.unshift(bt[0]),wt.pM ush(bt[bt.length-1]),hn=0,cn=0,un=0,Yt=!0;const n={xLeft:ae/8,xRight:width-ae/8,yTop:ae/8,yBottom:height-ae/8},r=Ce.map((e=>e.length));jt=new R(bt,r,n,Oe,le)}function Hn(e,t){let n=Ce[e].length;return[e*we+we/2+ae/2,height/2-(n-1)/2*ve+t*ve]}function $n(e,t){le=min(e,t)/1024,ae=100*le,ht=50*le,we=(e-ae)/Ve,ve=(t-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}xe=floor(De.length*de),Le=[],ke=[],ge=floor(map(de,.2,.8M ,15,2));for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/30,1,1,10)*le,mt=sr(xt,gt,pt,e),bt=[],wt=[],yt=e/(Ve-1);for(let t=0;t<Ve;t++)bt.push(hr(mt,yt*t/e)),wt.push(hr(mt,yt*t/e));wt.unshift(bt[0]),wt.push(bt[bt.length-1])}function Xn(){const e=Ut.getBrainStatus();Gt=e.inputDim,Kt=e.stageRatio,Pe=e.stage,rn=e.growth,sn=e.rebirthCount,on=e.nextStateTimestamp,an=e.nextStableTimestamp,Mt=e.aM ge,window.$state=Pe,window.$age=Math.ceil(Mt),window.$artworkName=`Perceptron #${Et}`,window.$statePercentage=e.statePercentage,window.$nextState=Pe%5+1,window.$nextStateTimestamp=vr(new Date(on)),window.$rebirthCount=sn,window.$introText=wr(Pe,Math.ceil(Mt),`Perceptron #${Et}`,$t),inputNodes=1,Ye=1,Ge=[],He=[],Ie=e.neuronsLife,Ce=[],Ae=1,ln=Ie.map((e=>e.length)).reduce(((e,t)=>e+t));for(let e=0;e<Ye;e++)Ge.push(1);for(let e=0;e<inputNodes;e++)He.push(1);Ie.push(Ge);for(let e=0;e<Ie.length;e++)Ie[e].length>30?Ae*=0M :Ae*=1;Se=[];for(let e=0;e<Ie.length;e++)Se.push(Ie[e].length);if(Ee=max(...Se),Te=ceil(Ee/30),Re=max(...Se.slice(0,-1)),0==Ae)for(let e=0;e<Ie.length;e++){Ce[e]=[];for(let t=0;t<Ie[e].length;t+=Te){let n=0,r=min(Ie[e].length-t,Te);for(let i=0;i<r;i++)n+=Ie[e][t+i]/r;Ce[e].push(n),n=0}}else Ce=Ie;if(Ce.unshift(He),1==Pe){for(let e=0;e<Ce.length;e++){let t=[];for(let n=0;n<Ce[e].length;n++)0!=Ce[e][n]&&t.push(Ce[e][n]);Ce[e]=t}for(let e=0;e<Ce.length;e++)0==Ce[e].length&&Ce[e].push(0)}Me=[];for(let e=0;e<Ce.length;eM ++)Me.push(Ce[e].length);_e=max(...Me),Ve=Ce.length,we=(width-ae)/Ve,ve=(height-2*ae)/_e,ze=min(we,ve)/2,De=[];for(let e=0;e<Ce.length;e++){let t=Ce[e].length;for(let n=0;n<t;n++)if(1==Ce[e][n]){const[t,r]=Hn(e,n);De.push([t,r])}}tn=2*(Ve-1)*fe;const t=map(de,.2,.8,15,2);ge=F(tn/2,1,t),en=round(tn/(2*ge)),xe=floor(De.length*de),Le=[],ke=[];for(let e=0;e<en;e++){for(let e=0;e<xe;e++){let e=floor(random(1)*De.length);ke.push(De.slice(e,e+1)[0])}Le.push(ke),ke=[]}Be=min(1/Ve,1/_e),Fe=map(Be,1/30,1,2,4)*le,Ne=map(Be,1/M 30,1,1,10)*le}function Wn(){jt.update();const e=4==Pe?0:Kt;jt.draw(Qe,ct,dt,e,le)}function Un(){if(!bn)return ar(),void et.image(je,0,0);if(4==Pe||5==Pe)return Wn(),void et.image(Qe,0,0);un>=Nt&&hn<Ve&&(hn++,un=0);for(let e=0;e<hn;e++)1==dt?it=ot=bt[e]:(it=ct,ot=bt[e]),Kn(e,it,ot,$e);un>=Nt&&cn<Ve-1&&(cn++,un=0);for(let e=0;e<cn;e++)Zn(e)}function qn(){et.background(ct),Ue.background(255),Ue.rectMode(CENTER),ne(Ue),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),Ue.stroke(st),Ue.strokeWeight(8*le),Ue.fill(ct),Qe.bacM kground(255),Qe.rectMode(CENTER),ne(Qe),Qe.strokeWeight(le),qe.background(255),qe.rectMode(CENTER),ne(qe),qe.textAlign(LEFT),$e.background(255),$e.rectMode(CENTER),ne($e),Xe.background(255),ne(Xe),Xe.strokeWeight(Ne),We.background(255),We.rectMode(CENTER),ne(We),We.fill(st),We.stroke(st),We.strokeWeight(.1*le),er(lt),We.noStroke(),xn&&(We.rect(ae/16,height/2,ae/8,height),We.rect(width-ae/16,height/2,ae/8,height),We.rect(width/2,ae/16,width,ae/8),We.rect(width/2,height-ae/16,width,ae/8)),Ze.background(255),Ze.rectMoM de(CENTER),ne(Ze),Ze.textAlign(CENTER,CENTER),Ze.textStyle(BOLD),Ze.stroke(st),Ze.strokeWeight(8*le),Ze.fill(ct),je.background(255),je.rectMode(CENTER),ne(je),je.textAlign(CENTER,CENTER),je.textStyle(BOLD),Ke.background(255),Ke.rectMode(CENTER),ne(Ke),Ke.textAlign(CENTER,CENTER),Ke.textStyle(BOLD),Ke.stroke(st),Ke.strokeWeight(8*le),Ke.fill(ct),Je.background(255),Je.rectMode(CENTER),ne(Je),Je.textAlign(CENTER,CENTER),Je.textStyle(BOLD),Je.stroke(st),Je.strokeWeight(8*le),Je.fill(ct),Un(),et.image(We,0,0),Pt&&An(),eM t.image(Xe,0,0),et.image($e,0,0),At&&(tr(),et.image(Ue,0,0)),fn&&(lr(),et.image(Ze,0,0)),Lt&&(or(),et.image(Ke,0,0)),Dt&&(ir(),et.image(qe,0,0)),yn&&(Bn(),et.image(Je,0,0))}function draw(){const e=Date.now();bn&&(Ut.updateAge(new Date(e)),Xn()),qn(),image(et,0,0),zn||un++}function Zn(e){let t,n=Ce[e].length,r=Ce[e+1].length;for(let i=0;i<n;i++){const[n,o]=Hn(e,i);for(let a=0;a<r;a++){const[r,l]=Hn(e+1,a);t=map(min(Ce[e][i],Ce[e+1][a]),0,1,0,.5),ur(n,o,r,l,bt[e],bt[e+1],Xe,t)}}}function Kn(e,t,n,r){let i,o,a,l=Ce[e]M .length;for(let s=0;s<l;s++){const[l,h]=Hn(e,s);i=Ce[e][s],a=map(Be,1/30,1,3,10),o=map(Ce[e][s],0,1,2*a,0)*le,o<1.5*le&&(o=0),Qn(l,h,ze,Oe,t,n,o,i,r)}}function Jn(e,t,n,r,i){for(let o=0;o<Le[e].length;o++)Qn(Le[e][o][0],Le[e][o][1],t,Oe,n,r,0,1,i)}function Qn(e,t,n,r,i,o,a,l,s){s.stroke(dr(o,map(l,0,1,.25,1))),s.fill(dr(i,map(l,0,1,.15,1))),s.strokeWeight(Fe),fr([a],s),3==dt&&s.fill(dr(i,0)),1==r?s.ellipse(e,t,n):2==r?s.rect(e,t,7*n/8,7*n/8):3==r&&(s.beginShape(),s.vertex(e-4*n/7,t),s.vertex(e,t-4*n/7),s.vertex(e+4M *n/7,t),s.vertex(e,t+4*n/7),s.endShape(CLOSE))}function er(e){if(1==e);else if(2==e){We.strokeWeight(1*le);for(let e=ht/4;e<width+ht/4;e+=ht)for(let t=ht/4;t<height+ht/4;t+=ht)We.point(e,t)}else if(3==e){ht=25*le;for(let e=ht/2;e<height+ht/2;e+=ht)We.line(0,e,width,e);for(let e=ht/2;e<width+ht/2;e+=ht)We.line(e,0,e,height)}}function tr(){Ue.textFont("Trebuchet MS"),Ue.textAlign(LEFT,CENTER),Ue.noStroke(),pr(Ue,800*le,500*le),Ue.noStroke(),Ue.fill(dr(st,.75)),Ue.rect(width/2,height/2-100*le,800*le,300*le,25*le,25*leM ,0,0),Ue.fill(st),Ue.rect(width/2-250*le,height/2-100*le,225*le,225*le),Ue.image(se.elt,width/2-357.5*le,height/2-207.5*le,215*le,215*le);let e=100*Zt[0][0];Ue.fill(ct),Ue.textSize(25*le),Ue.textStyle(NORMAL),1==me&&(e>=0&&e<20?Ue.text("I have a feeling this image belongs to",width/2-100*le,height/2-170*le):e>=20&&e<40?Ue.text("I have a hunch this image belongs to",width/2-100*le,height/2-170*le):e>=40&&e<60?Ue.text("I think this image belongs to",width/2-100*le,height/2-170*le):e>=60&&e<80?Ue.text("I'm almost certM ain this image belongs to",width/2-100*le,height/2-170*le):Ue.text("I'm positive this image belongs to",width/2-100*le,height/2-170*le));let t=e.toFixed(2);"100.00"==t&&(t="100"),1==me&&Ue.text("I'm "+t+"% confident that I'm right!",width/2-100*le,height/2-25*le),example=Zt.map((e=>e[1])),be=Ue.textWidth('"FIDENZAAAA"'),defaultPhrase=Ue.textWidth('"PERPENDICULAR INHABITATION"'),Ue.textStyle(BOLD);const n=me?example[0]:random(example);if(1===n.split(" ").length){let e=75*be/Ue.textWidth('"'+n+'"');e>75&&(e=75),Ue.teM xtSize(e*le),Ue.text('"'+n+'"',width/2-100*le,height/2-90*le)}else nr(width/2-100*le,height/2-90*le,460*le,110*le,n,Ue);if(millis()-ye>1500&&(me=!0),C(tt,nt,st,ct,Pe,Mt),Ue.image(nt,width/2-370*le,height/2+70*le,80*le,80*le),3==Pe){let e;e=map(Mt,50,60,.25,1.3),I(rt,e),Ue.image(rt,width/2-370*le,height/2+70*le,80*le,80*le)}let r,i;Ue.image(tt,width/2-370*le,height/2+70*le,80*le,80*le),Ue.fill(xt),Ue.textSize(40*le),Ue.text("INTELLIGENCE INFO",width/2-275*le,height/2+115*le),Ue.textSize(18*le),Ue.textStyle(NORMAL),UM e.circle(width/2-360*le,height/2+180*le,7.5*le),1==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s growing and getting smarter by the day.`:2==Pe?r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s stable and it has reached peak performance.`:3==Pe&&(r=`Your Perceptron is ${Math.ceil(Mt)} years old. It s decaying and losing its luster.`),i=2==Pe?"The Perceptron remains stable for some time before entering the decay phase.":`Wait until ${new Date(an).toLocaleString("en-US")} for your Perceptron toM reach its peak performance.`,Ue.text(r,width/2-350*le,height/2+180*le),Ue.circle(width/2-360*le,height/2+210*le,7.5*le),Ue.text(i,width/2-350*le,height/2+210*le),Ue.textAlign(CENTER,CENTER),Ue.textStyle(BOLD),gr(Ue,width/2-225*le,width/2+65*le,height/2+265*le,height/2+305*le,"SELECT ANOTHER IMAGE"),gr(Ue,width/2+75*le,width/2+225*le,height/2+265*le,height/2+305*le,"CLOSE")}function nr(e,t,n,r,i,o){let a=i.split(" "),l=75*be/o.textWidth('"'+i+'"'),s=0,h=[],c=[],u=[],f="",d="";if(l>=50)l>75&&(l=75),o.textSize(l*le),M o.text('"'+i+'"',e,t);else if(l<50){if(l=50*defaultPhrase/o.textWidth('"'+i+'"'),l>30){if(l>50&&(l=50),[f,d]=rr(l,n,s,h,c,a,f,d,Ue),0==c.length)return o.textSize(l*le),void o.text('"'+i+'"',e,t);for(s=0,h=[],c=[];o.textWidth(d)>n/le;)l=l*n/le/o.textWidth(d),f="",d="",[f,d]=rr(l,n,s,h,c,a,f,d,Ue)}else{l=30,o.textSize(l);for(let e=0;e<a.length;e++)s+=o.textWidth(" "+a[e]),s<=n/le?h.push(a[e]):s>n/le&&s<=n/le*2?c.push(a[e]):u.push(a[e]);for(let e=1;e<h.length;e++)f=f+" "+h[e];if(f='"'+h[0]+f,0==u.length){for(let e=0;eM <c.length-1;e++)d=d+c[e]+" ";d=d+c[c.length-1]+'"'}else if(1==c.length)d="... "+u[u.length-1]+'"';else{for(let e=0;e<c.length-1;e++)d=d+c[e]+" ";d=d+"... "+u[u.length-1]+'"'}}o.textSize(l*le);let r=1.25*(o.textDescent()+o.textAscent());o.text(f,e,t-r/2),o.text(d,e,t+r/2)}}function rr(e,t,n,r,i,o,a,l,s){s.textSize(e);for(let e=0;e<o.length;e++)(n+=s.textWidth(" "+o[e]))<=t/le?r.push(o[e]):i.push(o[e]);for(let e=1;e<r.length;e++)a=a+" "+r[e];if(a='"'+r[0]+a,0==i.length&&(a+='"',l=""),1==i.length)l=i[i.length-1]+'"';eM lse{for(let e=0;e<i.length-1;e++)l=l+i[e]+" ";l=l+i[i.length-1]+'"'}return[a,l]}function ir(){const e=45*le;qe.textFont("Tahoma"),qe.stroke(st),qe.strokeWeight(2*le),qe.fill(ct),qe.rect(width/2,e/2+height-87.5*le,600*le,90*le),qe.fill(st),qe.rect(width/2-150*le,e+height-170*le,300*le,30*le),qe.fill(ct),qe.rect(width/2+150*le,e+height-170*le,300*le,30*le),qe.noStroke(),qe.fill(ct),qe.textSize(15*le),qe.textStyle(BOLD),qe.text("PERCEPTRON INFORMATION",width/2-285*le,e+height-165*le),qe.fill(xt),qe.text("ARTWORK NAME:M ",width/2+10*le,e+height-165*le),qe.textAlign(RIGHT),qe.textStyle(ITALIC),qe.text("Perceptron #"+Et,width/2+285*le,e+height-165*le);const[t,n]=It.split(" ");let r;"60 Years"===It?r="1 Year":"60 Months"===It?r="1 Month":"60 Weeks"===It?r="1 Week":"60 Days"===It?r="1 Day":"12 Hours"===It&&(r="12 Minutes"),data=[["AI MODEL NAME:",B(12*le,Ht,140*le)],["SCALE:","1:"+Te],["NUMBER OF CLASSES:",$t.length],["BIRTH YEAR:",Rt],["NUMBER OF REBIRTHS:",sn.toString()],["AGE:",`${Math.ceil(Mt)} Perceptron Years`],["ONE PERCEPTRON M YEAR:",`${r}`],["STATE:",Ot[Pe]],["ACTIVE NEURONS:",`${round(ln*rn)} / ${ln}`],["NEXT STATE TIME:",vr(new Date(on))]],qe.fill(xt);const i=data.length/2;for(let t=0;t<data.length;++t){const n=t<i,r=n?width/2-285*le:width/2+10*le,o=n?width/2-10*le:width/2+285*le,a=e+height-(135-t%i*15)*le;qe.textStyle(BOLD),qe.textAlign(LEFT),qe.textSize(12*le),qe.text(data[t][0],r,a),qe.textStyle(ITALIC),qe.textAlign(RIGHT),qe.textSize(12*le),qe.text(data[t][1],o,a)}}function or(){Ke.textFont("Trebuchet MS"),Ke.noStroke(),pr(Ke,600*M le,200*le),gr(Ke,width/2-155*le,width/2-5*le,height/2+115*le,height/2+155*le,"UPDATE"),gr(Ke,width/2+5*le,width/2+155*le,height/2+115*le,height/2+155*le,"CLOSE"),Ke.textAlign(LEFT),Ke.fill(xt),Ke.text("UPDATE BITCOIN FULL NODE ADDRESS",width/2-252.5*le,height/2-55*le),Ke.text("UPDATE MODEL ADDRESS",width/2-252.5*le,height/2+20*le),Ke.textAlign(RIGHT),Ke.textStyle(ITALIC),Ke.textSize(15*le),0==wn&&Ke.text("(*) Invalid Address",width/2+252.5*le,height/2-53*le),0==vn&&Ke.text("(*) Invalid Model",width/2+252.5*le,heighM t/2+23*le)}function ar(){je.textFont("Trebuchet MS"),je.fill(st),je.textSize(50*le),je.stroke(st),je.strokeWeight(1*le),je.text("main()",width/2,height/2)}function lr(){un>=20&&1==dn&&(dn=!1,un=0),dn&&(Ze.textFont("Trebuchet MS"),Ze.stroke(st),Ze.fill(ct),Ze.rect(width/2,height/2,600*le,150*le,25*le),Ze.fill(xt),Ze.textSize(75*le),Ze.noStroke(),1==Pe?Ze.text("GROWING",width/2,height/2+5*le):3==Pe?Ze.text("AGING",width/2,height/2+5*le):4==Pe?Ze.text("DEAD",width/2,height/2+5*le):5==Pe&&Ze.text("BIRTH",width/2,heightM /2+5*le)),un>=20&&0==dn&&(dn=!0,un=0,Bt++,3==Bt&&(fn=!1))}function sr(e,t,n,r){let i=[],o=r/(n.length+1),a=color(e),l=color(t);i.push(a);for(let e=0;e<n.length;e++){let t=color(n[e]);for(let e=1;e<=o;e++){let n=lerpColor(a,t,e/o);i.push(n)}a=t}for(let e=1;e<o;e++){let t=lerpColor(a,l,e/o);i.push(t)}if(i.push(l),i.length>r)i.splice(r);else if(i.length<r){let e=i[i.length-1];for(;i.length<r;)i.push(e)}return i}function hr(e,t){let n=e.length,r=Math.floor(t*n);return r>=n&&(r=n-1),e[r]}function cr(e){e=e.replace("#","M ");var t=parseInt(e,16);return color(t>>16&255,t>>8&255,255&t)}function ur(e,t,n,r,i,o,a,l){var s=a.drawingContext.createLinearGradient(e,t,n,r);s.addColorStop(0,i),s.addColorStop(1,o),a.drawingContext.strokeStyle=s,a.drawingContext.globalAlpha=l,a.line(e,t,n,r),a.drawingContext.globalAlpha=1}function fr(e,t){t.drawingContext.setLineDash(e)}function dr(e,t){let n=color(e),r=red(n),i=green(n),o=blue(n);return color(r,i,o,255*t)}function xr(e,t,n,r){return mouseX>e&&mouseX<t&&mouseY>n&&mouseY<r}function gr(e,t,n,r,i,M o){e.strokeWeight(1*le),e.stroke(st);const[a,l]=xr(t,n,r,i)?[xt,ct]:[ct,xt];e.fill(a),e.push(),e.rectMode(CORNERS),e.rect(t,r,n,i,5*le),e.pop(),e.noStroke(),e.textSize(20*le),e.fill(l),e.text(o,(t+n)/2,(46*r+54*i)/100)}function pr(e,t,n){e.fill(0,0,0,75),e.rect(width/2,height/2,width,height),e.stroke(st),e.fill(ct),e.rect(width/2,height/2,t,n,25*le)}function mr(e,t){resizeCanvas(e,t,!0),Xe.resizeCanvas(e,t,!0),$e.resizeCanvas(e,t,!0),We.resizeCanvas(e,t,!0),Ue.resizeCanvas(e,t,!0),qe.resizeCanvas(e,t,!0),Qe.resizeCM anvas(e,t,!0),je.resizeCanvas(e,t,!0),Ze.resizeCanvas(e,t,!0),Ke.resizeCanvas(e,t,!0),Je.resizeCanvas(e,t,!0),et.resizeCanvas(e,t,!0)}function br(e,t,n,r,i,o){const a=J(e);return a.position(t,n),a.size(r,i),a.style("opacity","0"),a.mouseClicked(o),a}function yr(){return null!=vt&&vt?.isFocused()||null!=zt&&zt?.isFocused()}function wr(e,t,n,r){let i;if(e<=3){i=`Hey ${String.fromCodePoint(128075)}, I'm ${n}, ${t} years old. I can detect ${r.length} NFT collections: `;let e=0;for(let t=0;t<r.length;++t){const n=r[t];iM f(e+n.length>500){i+=", etc";break}t==r.length-1?i+=", and ":t>0&&(i+=", "),i+=n,e+=n.length}i+=". ",t<=5?i+="However, I am only a baby, so my recognition ability is not accurate. I'm in the state of Growing both looks and intelligence.":t<=13?i+="I am now a child. My recognition ability is becoming better, but still not very accurate. I'm in the state of Growing both looks and intelligence.":t<=25?i+="I have grown up to be a teen. My recognition ability almost reaches the peak, but I will still mess up sometimes. M I'm in the state of Growing both looks and intelligence.":t<=50?i+="I finally reach adulthood. My recognition is fully functional now. I'm in the Stable state, where I am the most intelligent with all neurons activated.":t<=60&&(i+="I am now an old Perceptron, so my recognition ability is no longer the best. I'm in the Decaying state, meaning that my neurons are dying, and my intelligence is decreasing over time.")}else 4==e?i=`${n} is Dead. However, this is not the end to its story...`:5==e&&(i=`${n} is now in theM Rebirth state, and is preparing to start a new life.`);return i}function vr(e){const t=e.getDate(),n=e.toLocaleString("en-US",{month:"long"}),r=e.getFullYear();let i=e.getHours().toString();1==i.length&&(i="0"+i);let o=e.getMinutes().toString();return 1==o.length&&(o="0"+o),`${Y(t)} ${n} ${r} | ${i}:${o}`}saveCanvasAtCurrentTime=()=>{save(N())},save4KCanvasAtCurrentTime=()=>{const e=width,t=height,n=min(4096/min(e,t),1e4/max(e,t)),r=e*n,i=t*n;mr(r,i),zn=!0,$n(r,i),qn();let o="4K_"+N()+".png";saveCanvas(et,o),mr(e,M t),$n(e,t),zn=!1};const zr=[["60 Years",3,365],["60 Months",40,30],["60 Weeks",37,7],["60 Days",20,1]],Vr=[["1943",1],["1951",1.5],["1957",2],["1969",2.5],["1970",3],["1980",3.5],["1982",4],["1986",4.5],["1988",5],["1997",5.5],["1998",6],["2002",6.5],["2009",7],["2012",7.5],["2014",8],["2015",8.5],["2016",9],["2023",15]],_r=[["Plain",20],["Dotted",40],["Squared",40]],Mr=[["Basic",30],["Standard",60],["Advanced",10]],Er=[["MNIST",70],["CIFAR",25],["IMAGENET",5]],Sr=[["Theano",60],["Torch",30],["TensorFlow",10]],Rr=[M ["Whitepaper",2],["Blackboard",2],["Blueprint",2],["Nak",74/14],["Jims",74/14],["Level 10",74/14],["Flips",74/14],["Level 14",74/14],["III",74/14],["XMB",74/14],["Info",74/14],["Adventure",74/14],["Marigold",74/14],["Phoenix",74/14],["Love",74/14],["Cachet",74/14],["Human",74/14],["Twilight",3],["Sunset",3],["Aurora",3],["Liminal Space",3],["D Vu",3],["Lucid Dream",3],["Parallel",1],["Multiverse",1]];function Ir(e){for(let e=0;e<100;++e)random(1);return{visual:{pattern:k(_r),hardwareAcceleration:k(Mr),nodeFillM :k(Er),nodeShape:k(Sr),colorPalette:k(Rr),lifeCycle:k(zr),birthYear:k(Vr)},training:e}}function Cr(e){window.$generativeTraits={"Network Architecture":e.training.structure_gen,"Hidden Layers":e.training.n_layers,"Max Neurons Per Hidden Layer":e.training.max_nodes,"Activation Function":e.training.activation_func,"Training Epochs":e.training.epoch_num,Dataset:e.visual.nodeFill,"Deep Learning Framework":e.visual.nodeShape,"Hardware Acceleration":e.visual.hardwareAcceleration,"Paper Pattern":e.visual.pattern,"Life CyclM e":e.visual.lifeCycle,"Birth Year":e.visual.birthYear,"Color Palette":e.visual.colorPalette}} <script defer src="https://static.cloudflareinsights.com/beacon.min.js/v2b4487d741ca48dcbadcaf954e159fc61680799950996" integrity="sha512-D/jdE0CypeVxFadTejKGTzmwyV10c1pxZk/AqjJuZbaJwGMyNHY3q/mTPWqMUnFACfCTunhZUVcd4cV78dK1pQ==" data-cf-beacon='{"rayId":"7b481d547ebca1e1","version":"2023.3.0","b":1,"token":"6c07c178c94442f695e7a0a2aaee641a","si":100}' crossorigin="anonymous"></script> {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "tiger"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "parrot"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "blue fire"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "sword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "fire"}, {"trait_type": "Eyes", "value": "golden"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "quiver"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "orc"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "tribal tattoo"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "skull"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "golden"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "axe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "cape"}]} text/plain;charset=utf-8 {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "bag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "blue"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "sword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "zombie"}, {"trait_type": "Mane", "value": "fire"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "skull"}, {"trait_type": "Artifacts", "value": "cape"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "golden"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":"rssc","amt":"1000"}h! text/plain;charset=utf-8 "name": "abit.sats" {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "silver"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "badger"}, {"trait_type": "Artifacts", "value": "axe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "lamp"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "lamp"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "rainbow"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "robot"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "eagle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "blue fire"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "ghostly companion"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} text/plain;charset=utf-8 {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "robot"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "golden"}, {"trait_type": "Headgear", "value": "skull"}, {"trait_type": "Artifacts", "value": "shield"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "moon"}, {"trait_type": "Body", "value": "golden armor"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "pauldrons"}]} text/plain;charset=utf-8 5{"p":"brc-20","op":"mint","tick":" wtf","amt":"1000"}h! {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "bull horns"}, {"trait_type": "Artifacts", "value": "ghostly companion"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "golden"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "tribal tattoo"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "bag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "golden armor"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "eagle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "honey pot"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "skull"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "rainbow"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "golden"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "orc"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "golden"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "tribal tattoo"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "tribal tattoo"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "pirate flag"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "moon"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "blue fire"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "thief hood"}, {"trait_type": "Artifacts", "value": "eagle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "blue fire"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "sword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "golden tribal tattoo"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "pauldrons"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "crown"}, {"trait_type": "Artifacts", "value": "sword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "bloody"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "parrot"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "orc"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "undead"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "zombie"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "shield"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "undead"}, {"trait_type": "Artifacts", "value": "cape"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "whale"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "blonde"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "noggles"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "hobo bindle"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "green"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "greenish"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "broadsword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "pickaxe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "armor"}, {"trait_type": "Mane", "value": "grey"}, {"trait_type": "Claws", "value": "bloody"}, {"trait_type": "Eyes", "value": "green"}, {"trait_type": "Headgear", "value": "crown"}, {"trait_type": "Artifacts", "value": "poisoned dagger"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "blue"}, {"trait_type": "Mane", "value": "rainbow"}, {"trait_type": "Claws", "value": "bloody"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "wizard hat"}, {"trait_type": "Artifacts", "value": "fire sword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "BTC whitepaper"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "mohawk"}, {"trait_type": "Artifacts", "value": "pauldrons"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "blue"}, {"trait_type": "Body", "value": "black"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "quiver"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "mage robes"}, {"trait_type": "Mane", "value": "toxic green"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "white"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "axe"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "sword"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "pink"}, {"trait_type": "Body", "value": "dark blue"}, {"trait_type": "Mane", "value": "black"}, {"trait_type": "Claws", "value": "long claws"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "unicorn"}, {"trait_type": "Artifacts", "value": "none"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "purple"}, {"trait_type": "Body", "value": "brown"}, {"trait_type": "Mane", "value": "white"}, {"trait_type": "Claws", "value": "wrapped"}, {"trait_type": "Eyes", "value": "red"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "parrot"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "yellow"}, {"trait_type": "Body", "value": "white"}, {"trait_type": "Mane", "value": "fire"}, {"trait_type": "Claws", "value": "regular"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "dark wizard hat"}, {"trait_type": "Artifacts", "value": "wizard staff"}]} {"name": "Honey Badgers", "description": "Honey Badgers is a generative 10k PFP collection inscribed on the Bitcoin Blockchain through Ordinals. It is an experiment to see if a native NFT community can emerge and thrive on the native Bitcoin ecosystem. The project doesn\u2019t have a roadmap and its solely purpose is to deliver high quality pixelated art and a fun place to hang out with friends. The collection is Bitcoin themed with the M honey badger meme being the center of it, but also has many other traits related to crypto and specifically the Bitcoin culture.", "creator": "Honey Badgers Team", "attributes": [{"trait_type": "Background", "value": "red"}, {"trait_type": "Body", "value": "zombie"}, {"trait_type": "Mane", "value": "whale"}, {"trait_type": "Claws", "value": "bloody"}, {"trait_type": "Eyes", "value": "regular"}, {"trait_type": "Headgear", "value": "none"}, {"trait_type": "Artifacts", "value": "none"}]} text/plain;charset=utf-8 /ViaBTC/Mined by unp570/, JjH=:BNB.BUSD-BD1:bnb136a3p64ugfnx233ate4vqg6a5uxa733aqkkeq8:24830863368::0 Aj?=:ETH.ETH:0x46CBdf0b4b5C704f7EB852f21aDBDE9FEee1Ff84:5005109::0 KjISWAPTX:0x08a1bbaba71745ba17951fed2f17674cb39d9c4d94fca944c63ea181a497046a Aj?=:ETH.ETH:0x5f32843BfDa08C87BBD32A65F816E3c8A92Ce04F:2172564::0 Bj@=:BNB.BNB:bnb1c48eg622z27l67wfmffl7pqq4n05qw7xj0m363:17567014::0 Bj@=:ETH.ETH:0xe54119f9CbD77e97802Aa1470b35cDB2a1D04b17:11087982::0 text/plain;charset=utf-8 LS{"p":"orditalk.org","op":"post","content":"Gm ","attached_inscription_id":"474255"}h! FjDOUT:6632DB3587922C6D1AC8AE92806B859D9F82E503CC463C21FD9207122506D019 FjDOUT:DD1A5CB4522BF78D1F9E5F73C5806D15E6DEF215DA4AF8676F0B991AB49E561E text/plain;charset=utf-8 La{"p":"orditalk.org","op":"create_user","name":"Chedin","profile_picture_inscription_id":"474255"}h! FjDOUT:BC7D56470557C1B43FD7C87353850D4C3A85F49839D402D0BE4E6C9D2E17CD21 FjDOUT:5BB1C787DE4B3E8795C51E0261677B955BBCFEE35EB9F5F27D40147D4CAFFD13 FjDOUT:A55F0B3BF60FD08F0E920E564C8A4DD037FE17A7A2CCBCFC19933F3D4623A645 text/plain;charset=utf-8 3{"p":"brc-20","op":"mint","tick":"pork","amt":"25"}h! text/plain;charset=utf-8 3{"p":"brc-20","op":"mint","tick":"pork","amt":"25"}h! text/plain;charset=utf-8 3{"p":"brc-20","op":"mint","tick":"pork","amt":"25"}h! text/plain;charset=utf-8 3{"p":"brc-20","op":"mint","tick":"pork","amt":"25"}h! text/plain;charset=utf-8 3{"p":"brc-20","op":"mint","tick":"pork","amt":"25"}h! text/plain;charset=utf-8 3{"p":"brc-20","op":"mint","tick":"pork","amt":"25"}h! text/plain;charset=utf-8 3{"p":"brc-20","op":"mint","tick":"pork","amt":"25"}h! text/plain;charset=utf-8 3{"p":"brc-20","op":"mint","tick":"pork","amt":"25"}h! text/plain;charset=utf-8 3{"p":"brc-20","op":"mint","tick":"pork","amt":"25"}h! text/plain;charset=utf-8 3{"p":"brc-20","op":"mint","tick":"pork","amt":"25"}h! text/plain;charset=utf-8 3{"p":"brc-20","op":"mint","tick":"pork","amt":"25"}h! text/plain;charset=utf-8 3{"p":"brc-20","op":"mint","tick":"pork","amt":"25"}h! text/plain;charset=utf-8 3{"p":"brc-20","op":"mint","tick":"pork","amt":"25"}h! text/plain;charset=utf-8 3{"p":"brc-20","op":"mint","tick":"pork","amt":"25"}h! text/plain;charset=utf-8 3{"p":"brc-20","op":"mint","tick":"pork","amt":"25"}h! text/plain;charset=utf-8 3{"p":"brc-20","op":"mint","tick":"pork","amt":"25"}h! text/plain;charset=utf-8 3{"p":"brc-20","op":"mint","tick":"pork","amt":"25"}h! text/plain;charset=utf-8 3{"p":"brc-20","op":"mint","tick":"pork","amt":"25"}h! text/plain;charset=utf-8 3{"p":"brc-20","op":"mint","tick":"pork","amt":"25"}h! text/plain;charset=utf-8 3{"p":"brc-20","op":"mint","tick":"pork","amt":"25"}h! text/plain;charset=utf-8 3{"p":"brc-20","op":"mint","tick":"pork","amt":"25"}h! text/plain;charset=utf-8 3{"p":"brc-20","op":"mint","tick":"pork","amt":"25"}h! text/plain;charset=utf-8 3{"p":"brc-20","op":"mint","tick":"pork","amt":"25"}h! text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 text/plain;charset=utf-8 <?xml version="1.0" encoding="UTF-8"?><svg id="taurus" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" viewBox="0 0 1440 1440"><defs><style>.cls-1{fill:url(#linear-gradient);}.cls-2{fill:#fff;}.cls-3{fill:url(#linear-gradient-2);}</style><linearGradient id="linear-gradient" x1="120.22" y1="576.73" x2="1319.78" y2="1583.27" gradientTransform="translate(0 1440) scale(1 -1)" gradientUnits="userSpaceOnUse"><stop offset="0" stop-color="#6aba71"/><stop offset=".25" stop-color="#64c195"/><stoM p offset=".5" stop-color="#8da07c"/><stop offset=".75" stop-color="#b7529a"/><stop offset="1" stop-color="#aa5457"/></linearGradient><linearGradient id="linear-gradient-2" x1="120.22" y1="-4592.92" x2="1319.78" y2="-3586.38" gradientTransform="translate(0 5169.65)" xlink:href="#linear-gradient"/></defs><rect class="cls-1" width="1440" height="720"/><rect class="cls-3" y="720" width="1440" height="720"/><g><path class="cls-2" d="M413.81,894.41l-.15,.07c.07,.01,.15,.02,.22,.04-.02-.04-.05-.07-.07-.11Zm95.17-19.52c-.7M 2,.05-1.65-.1-2.28,.2-.06,.19-.17,.46-.06,.59,1.03,1.13,2.24,2.15,3.36,3.19-.36-1.32-.7-2.65-1.02-3.98Zm-14.93,21.46c-2.23-2.26-.7-2.07,1.5-2.02,6.44,.12,12.88,.27,19.32,.33-1.15-3.29-2.23-6.61-3.23-9.98-8.04-.23-16.12-.32-24.14-1.07-1.45-.17-2.95-.12-4.42-.17-.3-.01-.65,.51-.49,.72,2.46,3.28,5.8,5.87,8.32,9.11,0,.66-1,.63-1.52,.63-9.82-.31-19.54-1.6-29.28-2.7-2.4-.28-4.79-.62-7.18-.91-.21-.03-.56,.1-.66,.24-.1,.15-.07,.44,.05,.59,1.57,2.01,3.17,4.01,4.75,6.01,1,1.28,1.98,2.56,2.97,3.84,.2,.27-.12,.76-.47,.73-15.34M -1.41-30.56-4.43-45.69-7.18,2.63,3.95,5.16,7.95,7.71,11.94,.11,.17,.15,.53,.04,.6-1.15,.7-2.56,.02-3.79-.09-12.08-2.21-24.01-4.84-35.87-7.71-4.38-.98-8.65-2.42-13.1-3.11-.46,.08-.28,.86-.18,1.15,1.9,3.69,3.83,7.36,5.73,11.04,.21,.54,.73,1.45-.13,1.64-21.13-4.38-41.7-11.04-62.13-17.39-.11,.4-.35,.73-.26,.99,1.6,4.58,3.52,9.04,5.3,13.56,.12,.3,.23,.69-.18,.86-25.16-6.17-49.34-16.37-73.72-25.1-.29-.09-.86,.29-.81,.54,.05,.32,.1,.64,.18,.95,1.26,4.86,2.7,9.66,3.81,14.54,.05,.21,.04,.43,.06,.64,.02,.26-.57,.55-.9,.43-5.M 25-1.97-10.52-3.88-15.72-5.92-23.93-9.11-47.49-19.26-70.75-29.81-.51-.22-1.18,.08-1.14,.51,.14,1.51,.27,3.01,.47,4.51,.37,4.57,1.65,9.27,1.57,13.79-.9,.32-1.55-.2-2.2-.49-33.99-14.86-67.3-30.93-100.03-48.15-1.1-.4-3.36-2.24-3.28,.1,.18,6.76-.36,13.61,.26,20.32,28.67,14.49,57.92,27.76,87.57,40.35,5.84,2.45,11.71,4.87,17.57,7.29,.82,.34,1.61,.8,2.68,.66-.02-5.95-1.55-11.98-2.05-17.96-.1-.86,.29-1.3,1.43-.84,2.17,.86,4.3,1.79,6.44,2.69,25.77,11.02,52.1,21,78.69,30.1,2.85,.74,4.97,2.47,3.65-1.86-1.12-4.32-2.26-8.64-3.3M 9-12.96-.14-.46-.16-1.43,.55-1.27,17.64,5.9,35.05,12.26,53.03,17.39,6.94,2.05,13.94,3.99,20.91,5.97,.47,.14,1.46,.39,1.64-.24-1.36-4.53-3.32-8.87-4.91-13.31-.98-2.51,1.05-1.5,2.51-1.2,19.24,5.68,38.8,10.67,58.49,14.83,.79,.08,3.06,.91,2.88-.38-1.94-4.26-4.31-8.33-6.2-12.61-.05-1.29,2.22-.19,2.98-.19,16.72,3.73,33.67,7.12,50.69,9.5,.35,.03,.77-.4,.61-.65-1.87-2.98-3.76-5.95-5.63-8.93-.55-1.23-3.16-3.64-.08-3.07,14.41,2.46,28.87,4.29,43.47,5.54,.26,.02,.53,0,.8,0,.35,0,.71-.43,.54-.68-2.41-3.55-5.55-6.55-7.91-10.13-.M 17-.23,.21-.67,.56-.65,.8,.04,1.61,.07,2.41,.15,12,1.19,24.16,2.34,36.21,2.23,.16-.05,.33-.37,.28-.52-2.07-2.81-4.87-5.14-7.19-7.77Zm23.76,25.2c-1.61-1.86-3.53-3.47-4.89-5.52-.17-.24,.18-.68,.54-.7,3.25-.14,6.51-.19,9.76-.29-1.58-3.38-3.09-6.8-4.51-10.27-5,.08-10,.01-15,.15-.37,.01-.72,.45-.53,.69,2.11,2.67,4.62,5.03,6.91,7.55,.4,.43,.74,.9,1.1,1.36,.28,1.21-3.73,.68-4.59,.85-11.59,.03-23.17-.45-34.7-1.3-1.42,.33,.26,1.72,.59,2.38,1.98,2.57,3.98,5.13,5.96,7.69,.28,.37,.54,.74,.18,1.28-15.39-.18-30.75-2.51-46.05-4.0M 2-.84,.22-.23,1.14,.02,1.63,2.04,3.28,4.22,6.48,6.2,9.8,1.05,2.05-3.81,.61-4.75,.73-13.94-1.83-27.82-4.01-41.62-6.51-2.62-.47-5.24-.96-7.86-1.44-.36-.06-.83,.33-.73,.59,1.7,4.46,4.51,8.47,6.09,12.97-.22,.56-1.18,.4-1.69,.32-20.83-3.74-41.42-8.37-61.82-13.81-2.41-.7-1.87,.72-1.3,2.37,1.35,3.61,2.73,7.21,4.08,10.82,.08,.62,.79,1.76-.13,2.01-18.43-3.9-36.64-9.46-54.62-14.84-6.41-1.98-12.74-4.11-19.12-6.14-.97-.31-1.9-.84-3.03-.72-.42,.51-.3,1.04-.17,1.57,1.09,5.08,2.89,10.07,3.57,15.2-.36,.83-2.84-.28-3.59-.38-15.65-4M .97-31.18-10.14-46.54-15.65-14.07-4.83-27.74-10.68-41.64-15.64-.63-.06-.66,.55-.68,.98,.61,4.82,1.24,9.64,1.84,14.46,.15,1.17,.47,2.34,.13,3.51-37.08-12.49-73.52-29.42-109.11-45.46-.76-.32-1.44-.09-1.47,.51-.03,.43-.05,.86-.05,1.3,.03,5.7,.06,11.41,.09,17.12,.02,1.29-.15,2.56,1.43,3.09,1.18,.51,2.33,1.08,3.51,1.59,34.27,14.82,69.03,28.68,104.35,41.1,.98,.35,2,.63,3.01,.9,.31,.09,.57-.05,.58-.28-.09-5.91-1.35-11.78-1.9-17.67-.03-.22,0-.43,0-.65,.01-.25,.6-.61,.87-.52,21.61,7.79,43.24,15.52,65.43,22.21,8.8,2.67,17.65M ,5.31,26.49,7.89,2.01,.6,1.5-1.27,1.19-2.45-.9-3.8-1.82-7.61-2.7-11.42-.88-4.19-.39-3.36,3.2-2.47,24.51,7.31,49.35,14.25,74.52,19.17,1.06-.16,.28-1.61,.18-2.28-1.29-4.28-3.22-8.45-4.21-12.78,.4-.69,1.5-.21,2.13-.15,5.84,1.3,11.66,2.65,17.5,3.92,14.96,3.14,30.07,6.13,45.29,8.22,1.87,.23,1.08-1.47,.56-2.41-1.58-3.66-3.64-7.14-4.91-10.91-.03-.13,.26-.44,.41-.44,.66-.04,1.34-.06,1.99,.04,4.76,.71,9.51,1.48,14.28,2.18,12.86,1.68,25.8,3.79,38.75,4.24,.3-.04,.46-.24,.37-.49-1.65-3.94-4.61-7.24-6.5-11.07-.13-.24,.22-.73,.5M 2-.72,1.21,.03,2.42,.02,3.62,.11,8.97,.84,17.93,1.66,26.95,2.04,5.23,.4,10.51,.53,15.74,.42,.33-.02,.64-.49,.47-.73-.6-.84-1.21-1.68-1.83-2.51-1.75-2.3-3.52-4.59-5.26-6.9-.83-.78,.12-1.19,.84-1.2,10.63,.61,21.29,.21,31.93,.23,2.02-.02,4.04-.16,6.05-.28,1.1-.07,1.44-.59,.85-1.28-.84-.97-1.7-1.94-2.58-2.89Zm13.11,14.22h-.05l.09,.05s-.03-.03-.04-.05Zm-2.47-10.41c-.96,.31-6.62-.32-6.01,1.06,2.55,3.34,5.67,6.22,8.48,9.35,1.16,.16,2.31,.03,3.46-.1-2.07-3.37-4.05-6.81-5.93-10.31Zm100.34-126.66s-.02,.05-.03,.08c.04,0,.07,.M 03,.11,.04l-.08-.12Zm5.61,15.56h-.01l.15,.1-.14-.1Zm-5.61-15.56s-.02,.05-.03,.08c.04,0,.07,.03,.11,.04l-.08-.12Zm0,0s-.02,.05-.03,.08c.04,0,.07,.03,.11,.04l-.08-.12Zm0,0s-.02,.05-.03,.08c.04,0,.07,.03,.11,.04l-.08-.12Zm0,0s-.02,.05-.03,.08c.04,0,.07,.03,.11,.04l-.08-.12Zm0,0s-.02,.05-.03,.08c.04,0,.07,.03,.11,.04l-.08-.12Zm0,0s-.02,.05-.03,.08c.04,0,.07,.03,.11,.04l-.08-.12Zm0,0s-.02,.05-.03,.08c.04,0,.07,.03,.11,.04l-.08-.12Zm0,0s-.02,.05-.03,.08c.04,0,.07,.03,.11,.04l-.08-.12Zm6.36,43.48c-15-5.62-10.01-2.34-.08-1M 2.22,1.48-1.35,1.07-1.67-.63-2.26-3-1.2-6.21-2.02-9.09-3.46-.15-.1-.24-.44-.15-.57,2.92-3.25,6.15-6.24,9.19-9.4-1.45-1.27-13.03-3.76-11.98-5.3,2.05-3.41,4.76-6.56,6.35-10.19-3.83-1.44-7.74-2.7-11.51-4.24-.48-.22-.69-.69-.46-1.09,1.97-3.38,3.9-6.75,5.63-10.25-.02-.01-.05-.01-.07-.02h-.01c-4.09-1.25-7.87-3.01-11.75-4.63-.4-.16-.61-.74-.42-1.13,1.82-3.4,2.85-7.27,5.07-10.4-4.49-1.14-8.23-3.93-12.68-5.02-2.05,3.28-3.25,6.84-5.52,10.1-4.34-1.57-8.11-4.16-12.14-6.23-.71,.07-1.06,.36-1.33,.76-1.8,2.65-3.76,5.52-5.74,7.98-M .81,.25-1.21-.08-1.59-.34-3.2-2.15-6.37-4.32-9.57-6.46-.7-.47-1.25-1.12-2.41-1.27-2.4,2.53-5.18,4.86-7.95,7.2-.8,.91,.82,1.47,1.35,2.02,3.78,2.63,7.53,5.21,11.34,7.82-2.34,3.09-6.55,4.5-9.52,6.82,.16,.72,.78,.98,1.27,1.3,3.7,2.51,7.61,4.75,11.21,7.4,1.24,1.41-10.48,4.93-11.01,6.56,3.6,2.56,7.55,4.8,11.3,7.18,.44,.28,.74,.61,.66,1.18-3.76,1.77-7.94,3.14-11.95,4.53-2.26,.84,1.46,2.15,2.14,2.81,2.46,1.51,4.92,3.01,7.39,4.52,.52,.32,1.12,.58,1.34,1.12-.35,.52-.95,.73-1.6,.91-3.96,1.06-7.91,2.13-11.86,3.2-.55,.24-2.37,.M 4-1.57,1.29,3.41,2.28,6.93,4.47,10.42,6.64,.24,.16,.25,.55,.38,.88-5.73,1.55-11.48,2.56-17.3,3.47-.81,.11-.83,.77-.16,1.15,2.62,1.86,5.36,3.64,8.04,5.4,.73,.54,1.92,.8,1.91,1.83-.67,.69-1.69,.57-2.59,.7-3.54,.5-7.09,1.01-10.64,1.48,.48,2.75,1.04,5.48,1.66,8.17,.26,.2,.51,.41,.77,.62,.24,.2-.09,.74-.45,.76,.77,3.23,1.62,6.43,2.57,9.58,3.25-.39,6.54-.67,9.72-1.42,.77-.57-1.04-1.49-1.46-1.91-2.44-1.7-4.91-3.37-7.37-5.05-.4-.28-.81-.57-.75-1.15,6.4-1.46,13.19-1.88,19.6-3.43,.48-.13,1.45-.29,1.24-.94-2.73-2.29-6.05-3.92M -9-5.95-.53-.33-1.1-.63-1.25-1.33,5.84-1.57,11.86-2.67,17.66-4.39,.3-.11,.43-.66,.18-.82-3.04-2-6.25-3.72-9.37-5.61-.52-.32-1.13-.61-1.26-1.35,4.98-1.76,10.62-2.81,15.43-5.07,0-.68-.62-.95-1.16-1.26-3.33-2.01-6.98-3.6-10.11-5.88-.5-.86,1.57-1.12,2.12-1.49,3.54-1.53,7.37-2.54,10.73-4.45,.15-.09,.13-.37,.21-.65-4-2.33-8.22-4.43-12.15-6.94,.8-1.24,2.26-1.46,3.5-2.13,2.59-1.18,4.94-2.62,7.24-4.11,.27-.17,.34-.54,.54-.87-16.78-10.37-14.41-4.32-3.91-14.28,.14-.14,.12-.4,.18-.6h0c.78,.01,1.52,.05,2.24,.43,3.74,2.09,7.71,3M .85,11.37,6.07-2.04,3.28-5.92,5.58-8.72,8.29,.12,.61,.53,.87,.99,1.11,2.4,1.2,4.79,2.4,7.19,3.6,.7,.61,4.5,1.43,3.21,2.61-12.09,10.11-15.28,4.4,1.29,13.35,.07,.61-.27,.91-.73,1.17-3.35,1.82-6.79,3.51-10.47,4.86-.73,.27-1.54,.45-2.03,1.24,3.61,2.34,7.84,4.04,11.7,6.29-.83,1.1-2.12,1.24-3.33,1.73-3.84,1.31-7.68,2.62-11.53,3.91-.52,.18-.91,.42-1.07,1,3.16,1.96,6.57,3.69,9.83,5.53,.43,.24,.85,.49,.95,1.05-5.84,2.29-12.13,3.42-18.16,5.22-.36,.11-.44,.57-.11,.77,3.2,1.98,6.45,3.88,9.64,5.87,.26,.17,.31,.55,.51,.92-6.94,1M .99-14.02,3.04-21.07,4.53-1.45,.96,7.55,5.71,8.58,6.73,.41,.27,.85,.53,.85,1.04-.73,.51-1.69,.61-2.59,.76-5.31,.87-10.62,1.8-16,2.42,2.33,6.41,5.01,12.62,8.03,18.63,.75-.28,7.16-.5,5.53-1.81-2.74-2.25-5.67-4.3-8.47-6.47-.25-.19-.31-.53-.53-.93,8.35-1.77,16.97-2.44,25.09-4.9,.23-.91-.85-1.24-1.42-1.77-2.36-1.6-4.75-3.18-7.1-4.79-.28-.19-.54-.51-.56-.78-.02-.35,.45-.51,.83-.6,3.11-.72,6.23-1.39,9.31-2.15,3.35-.82,6.67-1.72,10-2.58,.54-.14,.95-.38,1.19-.93-3.04-2.29-6.72-3.81-9.78-6.1-.12-.09-.13-.47-.04-.51,6.12-2.39M ,12.6-3.68,18.69-6.19-2.7-2.47-6.71-3.71-9.9-5.6-.48-.24-.8-.56-.95-1.1,1.56-.73,17.14-5.68,15.46-7.13-3.05-1.63-6.2-3.04-9.29-4.56-.59-.28-1.15-.57-1.41-1.13,4.18-2.18,8.43-4.23,12.11-6.93,.61-.47,1.37-.85,2.15-.52,3.24,1.32,6.48,2.64,9.72,3.96,1.14,.41,.88,1.16,0,1.71-3.74,2.6-7.8,4.99-11.48,7.57,.14,.53,.52,.8,1.01,1.02,2.37,1.03,4.72,2.07,7.09,3.1q3.06,1.34,.14,3.02c-4.09,2.47-8.7,4.36-13.11,6.3,.02,.55,.39,.82,.84,1.04,3.28,1.66,6.41,3.14,9.67,4.92-5.7,3.39-12.47,4.61-18.61,7.07-.51,.19-.56,.77-.08,1.05,2.4,1.M 39,4.82,2.77,7.21,4.16,3.55,1.96,1.65,1.99-.97,2.95-5.99,1.97-12.17,3.49-18.28,5.16-.53,.15-.59,.68-.11,1.01,2.65,1.84,5.42,3.55,8.11,5.34,.42,.27,.82,.56,.82,1.08-7.74,2.78-16.14,3.99-24.29,5.61-1.07,.21-1.35,.77-.67,1.36,2.25,1.87,4.62,3.61,6.92,5.43,.68,.47,1.96,1.53,.53,1.95-3.44,.75-6.89,1.44-10.38,1.92,1.84,3.16,3.77,6.26,5.79,9.28,5.19-1,10.37-2.1,15.48-3.38-.04-.3,.01-.55-.12-.69-2.36-2.26-5.06-4.17-7.57-6.27-.38-.31-.7-.64-.63-1.23,8.45-2.09,17.24-4.08,25.53-6.72,.14-.54-.1-.89-.54-1.18-1.06-.98-9.15-5.24-M 8.2-6.18,5.59-1.88,11.31-3.43,16.84-5.42,1.82-.77,3.85-.95,5.33-2.33-3.16-2.12-6.68-3.65-9.77-5.71,.16-.55,.56-.8,1.08-.97,5.91-2.05,11.67-4.21,17.05-7.29,1.68-1.37-8.81-4.43-9.31-6,5.11-2.93,10.47-5.47,15.19-9.07-3.03-1.62-6.13-2.75-9.25-4.15-.49-.21-.86-.5-1.03-1.02,3.63-2.53,7.35-5.02,11.01-7.53,.94-.62,2.65-1.74,.74-2.34Zm-42.47-58.69c-.68-.33-1.27-.82-2.29-.79-2.86,3-4.93,6.92-8.42,9.27,.27-.87-.97-1.13-1.51-1.6-3.55-2.25-7.45-4.1-10.77-6.65,2.66-2.84,5.22-5.57,7.84-8.35,4.71,1.94,8.14,5.02,12.98,6.72,2.47-2.7M 6,4.1-6.05,6.28-9.02,.41-.46,1.32-.17,1.82,.07,3.59,1.72,7.3,3.16,10.79,5.09-1.24,3.45-3.68,6.43-5.41,9.69-.75,1.17-2.15-.06-3.08-.37-2.75-1.35-5.48-2.72-8.23-4.06Zm7.05,29.95c1.35-2.12,3.78-3.51,5.53-5.34,.6-.87,4.54-3.29,2.67-4.07-3.85-1.8-7.78-3.38-11.52-5.41,1.56-3.15,4.27-5.69,6.29-8.62,.77-.99,1.07-1.08,2.23-.59,3.55,1.63,7.4,2.9,10.81,4.78,.08,.19,.2,.33,.15,.39-1.98,3.3-4.18,6.53-6.48,9.61,.33,.57,.9,.84,1.51,1.08,2.64,1.07,5.28,2.14,7.92,3.21,.64,.44,2.95,.67,2.37,1.74-2.63,3.19-5.89,5.87-8.99,8.61-.39,0-.M 71,.07-.91-.02-3.81-1.86-8.04-3.11-11.58-5.37Zm12.71,19.79c-3.34-1.5-6.51-2.91-9.66-4.34-.57-.34-2.42-.93-1.53-1.73,3.44-2.41,6.8-4.88,10-7.49,.39-.32,.92-.44,1.48-.22,3.48,1.38,6.97,2.77,10.44,4.17,.31,.13,.51,.45,.75,.66-2.3,2.31-7.07,6.03-11.48,8.95Zm16.35-34.53s-.02,.05-.03,.08c.04,0,.07,.03,.11,.04l-.08-.12Zm0,0s-.02,.05-.03,.08c.04,0,.07,.03,.11,.04l-.08-.12Zm0,0s-.02,.05-.03,.08c.04,0,.07,.03,.11,.04l-.08-.12Zm0,0s-.02,.05-.03,.08c.04,0,.07,.03,.11,.04l-.08-.12Zm0,0s-.02,.05-.03,.08c.04,0,.07,.03,.11,.04l-.0M 8-.12Zm0,0s-.02,.05-.03,.08c.04,0,.07,.03,.11,.04l-.08-.12Zm0,0s-.02,.05-.03,.08c.04,0,.07,.03,.11,.04l-.08-.12Zm0,0s-.02,.05-.03,.08c.04,0,.07,.03,.11,.04l-.08-.12Zm0,0s-.02,.05-.03,.08c.04,0,.07,.03,.11,.04l-.08-.12Z"/><path class="cls-2" d="M893.58,831.05c-.09,2.34-.24,4.67-.44,6.99-.75-1.88-.91-4.66-2.92-1.63-1.88,2.98-3.73,5.98-5.6,8.96-.46,.6-.72,1.28-1.66,1.07-1.43-5.11-2.94-10.24-4.88-15.28-.07-.18-.31-.31-.48-.47-.67,.24-.93,.74-1.2,1.23-1.7,3.05-3.38,6.1-5.09,9.15-.58,.79-.82,1.87-2.02,1.84-6.78-19.61-3.2M 1-16.56-12.73-.65-1.43-.99-1.41-2.71-2.09-4.18-.91-2.6-1.98-5.15-3.27-7.64-.07-.14-.38-.31-.53-.28-.23,.04-.51,.21-.6,.38-2.14,4.05-4.06,8.22-6.11,12.3-.21,.43-.53,.72-1.25,.65-1.54-3.16-2.92-6.49-4.67-9.58-.17-.26-.58-.42-1-.71-2.49,4.72-4.5,9.5-7.14,14.19-1.82-.86-2.08-3.23-3.23-4.79-.64-.92-2.06-4.26-3.43-3.92-2.4,4.3-4.45,8.78-6.72,13.14-1.2,2.33-1.58,1-2.61-.47-1.11-1.85-2.44-3.6-3.89-5.29-.43-.53-1.27-.31-1.5,.26-2.52,4.76-4.69,9.69-7.68,14.19-.33-.04-.66,0-.8-.12-1.98-2.06-3.58-4.35-5.7-6.3-1.69,.8-1.97,2.73M -3,4.15-2.37,3.72-4.16,7.85-6.92,11.29-.09,.1-.59,.09-.71-.02-2.11-1.72-3.79-4.2-6.28-5.33-4.16,5.07-7.25,10.83-11.38,15.96,1.84,2.23,3.62,4.37,5.39,6.51,.21,.25,.85,.28,1.07,.04,4.18-4.81,7.47-10.23,11.14-15.35,.18-.24,.87-.29,1.05-.06,1.57,1.98,3.18,3.95,4.51,6.09,1.03,.75,1.72-1,2.27-1.64,2.84-4.4,5.56-8.86,8.42-13.24,.28-.42,.99-.4,1.26,.05,1.47,2.3,2.82,4.62,4.05,7.04,1.2,1.24,2.39-2.16,3.04-2.9,1.97-3.43,3.91-6.86,5.85-10.3,.33-.57,.55-1.2,1.34-1.68,1.76,1.73,2.26,4.33,3.42,6.47,.37,.8,.74,1.61,1.12,2.41,.03,M .08,.2,.17,.27,.16,1.11-.14,1.39-1.46,1.99-2.24,1.94-3.43,3.86-6.88,5.8-10.31,.56-.74,.82-1.9,1.96-1.8,1.4,2.9,2.4,5.92,3.52,8.9,.26,.44,.45,1.19,1.01,1.31,.68-.22,1-1.27,1.42-1.82,2.3-3.99,4.19-8.21,6.71-12.06,.68,.19,.93,.55,1.07,.96,1.27,3.69,2.45,7.27,3.78,10.98,.42-.15,.93-.2,1.05-.4,1.02-1.75,1.97-3.53,2.96-5.3,1.37-2.46,2.75-4.91,4.15-7.35,.07-.11,.46-.13,.71-.15,.4,.13,.47,.76,.63,1.1,1.24,3.63,2.42,7.28,3.24,10.99,.12,.54,.27,1.06,.95,1.34,.78-.34,1-.98,1.34-1.55,1.94-3.32,3.86-6.64,5.79-9.96,.28-.49,.51-1M ,1.19-1.26,.77,.53,.89,1.29,1.07,2.01,1.17,4.52,2.07,9.13,3.51,13.58,.68,.47,1.18-.6,1.55-1.02,1.95-3.08,3.87-6.16,5.82-9.24,.48-.61,.83-1.57,1.77-1.54,.05,0,.19,.12,.21,.2,.33,1.16,.68,2.31,.97,3.47,.99,4.01,2.08,8.01,2.68,12.08,.1,.63,.41,1.24,.63,1.85,.09,.15,.38,.19,.56,.12-.22,.86-.45,1.71-.69,2.56-.04-.05-.07-.09-.11-.14-.44-.12-1.05,.69-1.33,.99-1.17,1.12-7.6,12.08-8.44,10.41-1.68-5.62-1.82-11.59-3.31-17.27-.44,.14-.93,.18-1.09,.39-2.6,3.76-5,7.62-7.54,11.42-.27,.41-.63,.68-1.35,.53-.8-4.67-1.87-9.34-2.89-13M .98-.11-.51-.23-1.05-.91-1.33-.75,.36-.98,1-1.33,1.57-2.17,3.58-4.34,7.17-6.53,10.75-.24,.39-.54,.75-1.31,.72-1.62-4.29-1.71-8.92-3.56-13.15-.74-.61-1.59,1.47-2.02,1.94-2.05,3.4-4.06,6.81-6.1,10.2-.28,.46-.51,.99-1.24,1.16-.67-.46-.76-1.12-.93-1.75-.58-1.41-2.08-10.44-3.6-9.79-2.76,3.44-4.61,7.53-7,11.24-.29,.48-.54,.99-.91,1.44-.4,.48-.43,1.4-1.44,1.25-.69-.1-.67-.85-.85-1.36-1.22-2.82-1.68-6.42-3.55-8.81-.79,.48-1.07,1.09-1.41,1.68-2.15,3.59-4.3,7.18-6.48,10.77-.47,.77-1.04,1.5-1.58,2.24-.06,.08-.26,.18-.34,.15-.M 21-.07-.48-.17-.55-.32-1.61-2.78-2.2-6.15-4.22-8.65-1.04,.6-1.35,1.46-1.85,2.21-2.6,3.89-5.16,7.81-7.75,11.7-.54,.67-.91,1.52-1.94,1.47-1.19-2.26-2.4-4.54-3.59-6.82-.22-.42-.56-.72-1.28-.85-3.6,4.89-6.96,9.94-10.85,14.69-.55,.49-1.27,1.9-2.12,1.49-1.04-1.22-1.45-2.78-2.32-4.11-.65-1.01-.68-2.34-2.19-2.94-1.19,.6-1.66,1.64-2.38,2.52-3.41,4.13-6.79,8.28-10.18,12.43-.37,.45-.71,.91-1.55,1.06-1.94-2.28-3.41-4.82-5.22-6.95-.09-.72,.36-1.01,.65-1.36,4.06-4.95,8.12-9.91,12.16-14.87,.71-.87,.66-1.2-.24-1.98-1.92-1.66-3.88-M 3.28-5.89-4.64-.92-.06-1.14,.38-1.4,.71-4.06,4.93-7.56,10.03-12.09,14.61-2.92-1.29-4.87-3.71-7.59-5.1-.99,0-1.29,.53-1.68,.93-4.69,4.53-8.83,9.72-13.9,13.81-2.02-1.13-6.33-4.13-7.79-5.41,4.67-4.74,9.24-9.56,13.95-14.25,.37-.34,1-.42,1.45-.15,2.52,1.52,4.88,3.06,7.48,4.5,4.37-4.36,8.24-9.07,11.9-13.93,1.04-1.31,1.39-1.37,2.78-.49,2.22,1.25,4.04,3.05,6.43,3.96,4.21-4.97,7.18-10.29,11.15-15.46,3.08,1.29,4.67,3.42,7.51,5.08,3.04-4.28,5.09-9.05,7.74-13.58,.79-1.31,1.2-2.58,2.83-1.23,1.52,1.22,3.03,2.45,4.55,3.68,1.29,1.M 04,1.67,.97,2.48-.49,1.87-3.56,3.59-7.2,5.39-10.8,.6-1.07,.84-2.38,1.89-3.12,.86,.25,1.27,.84,1.75,1.34,1.56,1.62,3.09,3.26,4.64,4.88,.89,.56,1.36-.69,1.68-1.32,1.02-2.22,2.03-4.44,3.04-6.67,.86-1.92,1.72-3.85,2.59-5.77,.19-.43,.98-.56,1.3-.23,1.86,1.94,3.41,4.14,5.12,6.19,.28,.35,.55,.73,1.17,.74,.59-.47,.83-1.09,1.09-1.7,1.53-3.56,3.06-7.12,4.6-10.68,.31-.66,.7-1.89,1.63-1.24,2.23,2.63,3.82,5.81,6.19,8.25,.72-.28,.92-.8,1.13-1.28,1.42-3.26,2.8-6.52,4.22-9.77,.31-.71,.67-1.4,1.07-2.08,.04-.07,.57-.09,.65,0,2.38,2.M 62,3.79,5.92,5.72,8.87,.23,.39,.54,.7,1.25,.74,1.87-3.64,3.39-7.46,5.09-11.19,.26-.59,.46-1.22,1.18-1.6,.59,.32,.87,.8,1.15,1.3,1.99,3.29,3.49,6.74,5.2,10.14,1.64,1.5,5.62-11.23,7.5-12.28,3.01,4.41,4.18,9.25,6.22,14.01,.68,.07,1.02-.21,1.25-.63,1.63-2.95,3.25-5.91,4.89-8.86,.38-.68,.82-1.34,1.24-2.01,.2-.3,.85-.11,.98,.04,2.36,4.97,3.57,10.4,5.76,15.44,.87,1.09,1.49-.81,2.06-1.39Z"/><path class="cls-2" d="M987.18,901.63s-.05,.02-.08,.03c-.02-.05-.03-.1-.04-.15l.12,.12Z"/><path class="cls-2" d="M990.88,1027.86s.02-.M 02,.03-.04h.02s-.03,.02-.05,.04Z"/><path class="cls-2" d="M993.11,983.15c.02,13.16-.52,26.29-1.25,39.42-.29,1.62,.15,3.97-.95,5.25-5.87,1.35-11,4.55-16.72,6.32-.84,.06-.74-.94-.73-1.52,.46-4.73,1-9.45,1.46-14.17,.46-10.1,1.71-20.21,1.66-30.32-.01-.27-.61-.5-.92-.35-4.64,2.13-9.07,4.65-13.61,6.96-.45,.23-.92,.46-1.61,.09,.13-12.75,1.29-25.53,.94-38.3-.02-.56-.03-1.6-.82-1.54-4.23,2.17-8.01,5.09-12.06,7.58-3.05,2.42-2-1.86-2.06-3.62,.39-9.7,.03-19.39-.33-29.08-.05-.56-.09-1.6-.88-1.51-3.92,2.5-7.37,5.68-11.09,8.47-.3M 8,.3-.75,.61-1.33,.62-.38,.01-.55-.42-.59-.72-.03-1.4,0-2.8-.06-4.2-.28-7.65-.62-15.29-.98-22.93-.04-.75-.17-1.49-.28-2.24-.02-.08-.18-.18-.3-.2-.23-.03-.58-.1-.71,0-3.78,3-6.88,6.75-10.75,9.63-.86,.23-.85-.83-.92-1.41-.18-2.35-.36-4.7-.54-7.05,3.98-9.2,7.32-18.72,9.97-28.48,1.15,5.46,1.58,11.07,2.18,16.59,.25,2.69,.59,5.37,.91,8.05,.02,.18,.24,.35,.38,.51,.18,.22,.69,.14,1.05-.17,3.07-2.71,6.09-5.47,9.17-8.18,.54-.41,1.15-1.1,1.91-.71,.09,.03,.15,.19,.16,.29,1.07,7.7,1.6,15.45,2.23,23.19,.18,2.26,.34,4.52,.51,6.77M ,.71,.92,1.84-.33,2.54-.73,3.34-2.53,6.65-5.09,10.16-7.39,.87-.33,1.13,.57,1.24,1.23,.61,6.22,.72,12.48,1.02,18.73,1.01,21.18-3.31,17.05,14.54,7.71,1.11-.36,1.03,.88,1.12,1.59,.59,11.09,.63,22.19,.19,33.28-.08,1.83-.03,3.66,.01,5.49,0,.11,.4,.33,.58,.32,4.9-1.48,9.17-5.21,14.49-5.4,1.18,.05,.97,1.32,1.07,2.13Z"/><path class="cls-2" d="M1042.99,839.46c.02,.06,.04,.11,.05,.17-.04-.02-.09-.03-.13-.05l.08-.12Z"/><path class="cls-2" d="M1086.38,834.09l-.03-.03s0-.01,.02-.01v.04Z"/><path class="cls-2" d="M1211.58,762.83sM -.02,.02-.02,.03c0-.01-.01-.01-.01-.01l-.02-.02h.05Z"/><path class="cls-2" d="M1387.34,896.54c-21.73-23.74-44.18-46.89-67.41-69.26-2.45-2.35-1.9,.42-1.72,2.14,.6,5.14,1.21,10.29,1.79,15.43,.01,.14-.27,.31-.45,.43-.57,.06-1.06-.63-1.48-.94-7.95-8.02-16.01-15.96-24.2-23.82-11.09-10.23-21.93-21.41-33.71-30.79-.84,.36-.3,1.35-.27,2.02,.91,4.13,1.85,8.26,2.75,12.39,.08,1.31,1.01,2.99-.15,4.02-16.1-15.99-33.65-30.38-50.93-45.3-.91,.89-.09,2.05,.15,3.05,1.81,5.28,3.62,10.56,5.43,15.84,.36,1.03,.79,2.02,.19,3.04-13.44-11.9M 5-27.68-23.25-41.94-34.3-.57-.44-1.07-.99-1.96-1.07-.4,.52-.16,1.02,.05,1.53,2.45,5.93,4.89,11.86,7.32,17.79,.19,.7,.9,1.81-.4,1.58-8.26-6.28-16.49-12.7-24.92-18.89-3.54-2.65-7.16-5.22-10.76-7.82-.46-.23-1.12-.86-1.64-.64-.09,.06-.2,.2-.17,.27,2.88,6.6,5.87,13.18,8.83,19.75,.19,.41,.32,.8-.09,1.27-10.36-7.23-20.54-14.65-31.16-21.55-.51-.26-1.1-.8-1.71-.74-.31,.11-.35,.3-.23,.54,3.45,6.63,6.65,13.38,9.82,20.15,.07,.15-.11,.38-.21,.56-.69-.02-1.37-.68-1.98-.99-8.62-5.66-17.32-12.11-26.47-16.81-.53,.84,.51,1.86,.78,2.M 7,2.76,5.49,5.54,10.98,8.3,16.47,.35,.7,.64,1.42,.93,2.13,0,.17-.39,.37-.56,.29-8.29-4.44-16.02-10.63-24.66-14.28-.09,.07-.2,.2-.17,.28,.23,.61,.45,1.23,.75,1.82,2.82,5.59,5.67,11.17,8.5,16.76,.35,1.14,1.8,2.52,.69,3.59-6.83-4.43-14.11-8.67-21.62-12.13-.44,.04-.24,.8-.15,1.07,2.98,6.09,5.98,12.18,8.97,18.27,.41,1.21,1.77,2.6,.81,3.84,.09-.1,.19-.23,.37-.44-.21,.27-.3,.39-.4,.52-5.28-3.64-11.32-6.18-17-9.2-.73-.32-2.74-1.58-2.56-.07,3.83,7.88,7.24,15.94,10.7,23.99,.17,.41,.27,.82-.2,1.27-5.95-2.83-11.5-6.44-17.52-9.M 14-.38-.16-.67,.29-.66,.57,3.52,9.37,7.54,18.59,11,27.99,.16,.4,.34,.82,.01,1.32-5.7-2.03-10.82-5.68-16.56-7.72-.19-.06-.52,.15-.51,.34,1.43,4.73,3.44,9.27,5.03,13.94,7.26,23.21,10.36,18.25-10.94,10.03,3.39,10.99,7.09,21.94,9.76,33.12-.32,1.29-2.51-.38-3.33-.54-3.35-1.39-6.68-2.79-10.05-4.16-.55-.22-1.12-.55-1.96-.29,2.12,9.72,4.78,19.39,6.91,29.11,.39,1.59,.66,3.19,.96,4.79,.1,.52,.22,1.06-.2,1.56-.86,.17-1.53-.29-2.23-.56-3.29-1.24-6.55-2.52-9.82-3.79-.73-.36-2.53-.92-2.49,.25,1.76,11.76,4.38,23.4,5.74,35.22,.11,M .84,.4,1.7-.11,2.52-.73,.19-1.31-.12-1.92-.33-3.46-1.19-6.92-2.39-10.39-3.57-.78-.26-2.35-.73-2.28,.61,1.3,13.83,3.16,27.69,3.32,41.58-.61,.18-1.1,.43-1.61,.46-5.29,.36-11.65,1.78-14.02,1.53-.44-.75-.42-1.64-.43-2.49-.41-12.92-1.31-25.84-2.58-38.71-.04-.41-.67-.76-1.17-.64-4.12,.97-8.21,2.04-12.31,3.1-1.79,.21-1.28-2.04-1.59-3.15-1.17-11.21-1.73-22.55-4.14-33.59-4.29,1.63-8.56,3.45-12.66,5.42-.75-.35-.81-.89-.89-1.42-1.44-9.95-2.57-20-4.9-29.77-.66-1.07-1.78,.3-2.48,.66-3.17,2.33-6.19,4.85-9.46,7.04-.29,.2-.91,.03-M .96-.26-1.37-8.68-3.4-17.22-5.17-25.83-.09-.41-.34-.8-.55-1.19-.58-.74-1.6,.65-2.14,.94-2.89,2.54-5.53,5.36-8.56,7.72-.11,.07-.59-.01-.64-.1-1.99-6.05-2.87-12.49-4.7-18.62-1.08,10.06-2.85,19.95-5.29,29.6,3.09-2.95,5.86-6.23,9.2-8.93,.08-.07,.58,.03,.63,.13,.25,.49,.51,1.01,.6,1.53,.92,5.55,2.27,11.05,2.84,16.64,.24,2.25,.58,4.5,.9,6.75,.11,.73,.11,1.51,.78,2.11,1.04-.1,1.67-.99,2.46-1.56,2.43-2.02,4.85-4.04,7.29-6.06,.64-.48,1.75-1.72,2.47-.81,2.32,9.98,2.57,20.39,3.99,30.5,.68,1.12,3.24-1.38,4.13-1.78,2.78-1.88,5.M 54-3.77,8.34-5.64,.27-.18,.72-.29,1.08-.28,.88,.11,.61,1.39,.76,2.01,.98,10.74,2.14,21.46,2.52,32.25-.07,2.55,1.53,1.26,2.9,.63,3.4-1.88,7.3-3.5,11.27-4.18,.92,.13,.84,1.23,.97,1.92,.71,11.62,1.12,23.24,1.23,34.88,.26,1.42-.83,4.66,1.55,4.32,4.32-.79,8.6-1.85,12.96-2.44,1.95-.25,1.27,1.93,1.45,3.1,.43,14.53-.12,29.09-.29,43.61,.37,.69,1.47,.47,2.14,.49,4.42-.36,8.84-.75,13.26-1.13,.8-.09,1.73-.29,1.67-1.07,.06-1.51,.13-3.01,.13-4.52,0-7.11,.01-14.22-.06-21.33-.1-6.25-.44-12.49-.67-18.74-.22-2.52,.43-2.63,2.61-1.84,M 3.19,1.16,6.37,2.33,9.55,3.5,1.01,.27,3.29,1.87,3.53,.21-.58-13.58-2.37-27.08-3.81-40.59-.46-2.24,1.25-1.44,2.54-.93,3.6,1.48,7.18,2.97,10.78,4.44,.46,.19,.97,.32,1.48,.43,.32,.07,.56-.08,.56-.32,.04-3.13-.91-6.18-1.27-9.28-1.07-7.49-2.37-14.96-3.93-22.39-.38-1.81-.7-3.62-1.02-5.43-.09-.52-.24-1.06,.23-1.53,.88-.11,1.55,.29,2.24,.61,3.74,1.71,7.46,3.45,11.2,5.16,.48,.16,1.35,.66,1.78,.36,.07-.3,.18-.62,.13-.92-1.05-5.86-2.46-11.68-3.88-17.49-1.37-5.6-2.82-11.19-4.22-16.78-.04-.24,.02-.76,.29-.84,5.43,1.7,10.27,5.18M ,15.62,7.25,1.15,.41-.23-3.19-.29-3.8-2.74-9.33-5.28-18.69-8.39-27.95-.17-.51-.18-1.06-.24-1.59-.01-.09,.08-.26,.17-.28,.23-.05,.55-.13,.72-.05,4.84,2.27,9.4,5.02,14.12,7.53,2.28,1.22,2.19,.6,1.62-1.56-3.09-9.36-6.22-18.72-9.71-28-1.1-2.8,1.27-1.27,2.56-.56,4.24,2.47,8.48,4.96,12.72,7.44,1.07,.54,2.21,1.74,3.46,1.01-.75-.77-.92-1.75-1.25-2.65-2.95-8.28-6.15-16.5-9.43-24.7-1.76-4.11-.28-2.77,2.43-1.33,5.74,3.41,11.06,7.34,16.92,10.49,.1-.18,.31-.36,.27-.5-.3-.93-.62-1.86-.99-2.79-3.05-7.8-6.22-15.57-9.64-23.28-.89-2M ,.02-1.78,1.51-1,6.1,3.37,11.92,7.03,17.49,10.94,.82,.44,1.67,1.33,2.59,1.43,.11-.17,.29-.39,.23-.54-.29-.83-.62-1.65-.98-2.46-2.67-5.98-5.36-11.95-8.03-17.93-.36-.81-.71-1.62-1-2.45-.06-.14,.15-.36,.29-.52,7.54,3.92,14.64,9.19,21.78,13.81,.7,.48,1.3,1.11,2.3,1.25,.51-.77-.27-1.62-.51-2.4-2.72-5.96-5.45-11.92-8.18-17.88-.32-.71-.62-1.42-.91-2.14-.02-.05,.13-.18,.24-.23,.1-.04,.29-.07,.37-.03,1.58,.99,3.22,1.94,4.73,2.99,7.2,5.03,14.36,10.09,21.54,15.14,.32,.27,1.05,.7,1.26,.12-.19-.62-.36-1.26-.62-1.86-2.67-5.98-5.M 36-11.95-8.03-17.93-.18-.67-.89-1.46-.28-2.07,.59-.11,1.14,.57,1.64,.82,9.41,6.62,18.57,13.44,27.5,20.47,.79,.49,1.43,1.53,2.47,1.38,.07,0,.19-.18,.17-.25-2.37-6.43-5.3-12.64-7.88-18.99-.3-.87-1-1.74-.46-2.63,12.74,8.59,24.15,19.35,36.27,28.33,.14-.14,.35-.33,.31-.47-.2-.73-.44-1.46-.72-2.18-2.1-5.56-4.21-11.11-6.31-16.67-.28-.88-.98-1.87-.22-2.71,14.41,11.52,27.92,24.01,41.94,35.72,.06,.03,.29-.03,.29-.06,.04-.31,.13-.64,.04-.93-1.96-6.15-3.95-12.3-5.91-18.45-.17-.51-.21-1.05-.28-1.58-.01-.09,.07-.23,.17-.28,.08-.M 05,.27-.05,.36-.01,2.64,1.65,4.76,4.1,7.18,6.07,12.98,11.53,25.65,23.27,37.94,35.27,1.02,1,2.04,2,3.1,2.97,.1,.09,.45,.04,.67,.01-.76-6.58-3.05-13.34-4.45-19.95-.06-.47-.31-1.4,.54-1.1,20.01,17.79,38.21,37.96,57.04,56.4,.19-.11,.5-.28,.49-.4-.52-5.15-1.07-10.3-1.6-15.45-.1-.96-.14-1.92-.18-2.88,0-.06,.15-.15,.25-.18,.12-.03,.32-.07,.38-.02,.65,.54,1.33,1.05,1.9,1.64,6.11,6.3,12.22,12.59,18.27,18.92,15.7,16.07,30.25,33.22,45.51,49.34,.33,0,.53-.14,.53-.38-.02-6.88-.04-13.77-.06-20.77Zm-293.02-121.31s-.03-.02-.04-.04M l.22-.13-.18,.17Zm59.12-8.88s.09-.14,.12-.14c.11,.03,.21,.08,.31,.11-.11,.15-.25,.16-.43,.03Zm29.62,6.39s-.05,0-.08,.01c.07-.05,.13-.1,.2-.15l.03,.03c-.05,.03-.1,.07-.15,.11Zm34.32,12.1s.03-.01,.05-.01c0,.02,.01,.05,.02,.08-.02-.02-.04-.05-.07-.07Zm45.17,23.4s-.04-.05-.05-.07l.13-.07-.08,.14Z"/><path class="cls-2" d="M1030.85,456.1l-.1,.1c.05,.01,.1,.01,.15,.02-.02-.04-.03-.08-.05-.12Z"/><path class="cls-2" d="M1095.46,449.73l.12,.03v-.12l-.12,.09Z"/><path class="cls-2" d="M875.35,508.09c-.49,.08-.92,.37-1.33,.54,.M 48,1.79,2.47,2.71,3.63,4.06,.4-1.7,.81-3.42,1.22-5.17-1.17,.19-2.35,.38-3.52,.57Z"/><path class="cls-2" d="M865.3,499.42c5.31-1.58,10.91-2.17,16.38-3.2,1.01-3.86,2.12-7.79,3.38-11.77-9.43,1.52-18.72,3.4-27.97,5.61-.53,.12-.78,.68-.46,1.04,1.24,1.41,2.48,2.81,3.74,4.21,1.02,1.14,2.06,2.26,3.07,3.4,.24,.27,.1,.69-.25,.81-9.88,2.82-20.11,4.6-29.79,8.04-.28,.12-.4,.64-.17,.85,.86,1.09,8.53,6.59,7.22,7.32-8.51,2.96-17.35,5.12-25.55,8.74-1.58,1.11,8.02,5.64,7.94,7.1-.84,.76-2.06,1-3.15,1.39-6.58,2.54-13.23,4.7-19.28,8.26M ,2.61,2.26,6.1,3.58,8.74,5.63,0,.56-.41,.81-.88,1.03-5.56,2.64-10.86,5.6-16.05,8.69-1.5,.89-1.46,1.24,.2,2.06,2.48,1.28,5.16,2.29,7.51,3.77,.12,.1,.13,.46,0,.56-3.11,2.28-6.58,4.1-9.79,6.22-1.68,1.08-3.28,2.24-4.89,3.38-.38,.26-.78,.56-.52,1.15,2.92,1.19,5.96,2.42,8.88,3.67,.29,.12,.47,.43,.76,.73-4.35,3.35-8.91,6.54-13.01,10.12,.11,.56,.51,.81,1.01,.99,2.46,.88,4.92,1.75,7.37,2.64,.51,.27,1.68,.47,1.54,1.18-3.42,3.33-7.35,6.29-10.56,9.76-.37,.38-.23,.88,.32,1.05,2.26,.71,4.52,1.41,6.78,2.1,2.24-.43,4.45-.9,6.64-1.M 43,3-2.5,5.81-5.42,9.1-7.51,2.5,.49,4.82,1.75,7.23,2.58,5.87-2.18,11.49-4.77,16.88-7.85-2.72-1.34-5.55-2.46-8.32-3.7-.49-.21-.89-.48-1.05-1.02,4.52-3.1,9.89-5.27,14.98-7.47,.46-.2,.5-.82,.04-1.06-2.83-1.45-5.69-2.89-8.54-4.31-1.42-.73-1.46-1.21-.07-1.79,1.91-.79,3.83-1.59,5.8-2.28,3.69-1.3,7.46-2.47,11.16-3.76,.56-.2,.71-.73,.28-1.01-2.44-1.55-5.03-2.9-7.51-4.36-2.93-1.63-1.92-1.79,.61-2.65,5.24-1.71,10.6-3.15,15.98-4.54,4.71-1.15,3.93-1.12,.36-3.56-1.96-1.31-3.94-2.6-5.9-3.92-.64-.44-.47-.88,.39-1.15,6.11-1.75,12.M 33-3.08,18.62-4.29,2.01-.44,4.21-.49,6.06-1.41-.09-.66-.62-1.06-1.1-1.42-2.32-1.81-4.64-3.61-6.95-5.42-.4-.31-.68-.66-.42-1.22,3.71-.95,7.56-1.61,11.43-2.22,.95-3.44,1.86-7.12,2.73-10.73-7.44,1.17-14.77,2.68-22.06,4.33-.88,.2-1.83,.29-2.44,.92,.09,.6,.66,.93,1.13,1.3,2.08,1.69,4.18,3.36,6.26,5.05,.39,.4,1.38,.96,.9,1.54-8.57,2.16-17.29,3.95-25.59,6.81-.06,.54,.29,.84,.71,1.12,1.87,1.23,3.75,2.46,5.61,3.7,.53,.54,3.46,1.79,2.34,2.54-6.91,2.09-13.83,4.2-20.57,6.68-1.32,.5-1.45,.96-.4,1.58,1.85,1.08,3.73,2.13,5.59,3.1M 9,.55,.54,4.11,1.73,2.84,2.52-4.82,1.88-9.7,3.69-14.45,5.75-.88,.6-5.36,1.93-2.87,3.04,2.81,1.47,5.77,2.72,8.48,4.38,.45,.73-.8,1-1.26,1.33-4.32,2.2-8.44,4.63-12.46,7.17-.53,.29-1.51,1.03-.61,1.45,3.11,1.43,6.4,2.63,9.44,4.2,.11,.58-.37,.82-.73,1.17-3.89,2.67-7.79,5.32-11.68,7.97-.43,.3-.95,.55-1.46,.37-3.31-1.18-6.6-2.41-9.89-3.63-.32-.11-.4-.65-.14-.86,4.03-3.35,8.41-6.35,12.73-9.33-.06-.19-.04-.32-.11-.36-3.11-1.71-6.72-2.7-9.87-4.3-.09-.52,.2-.85,.64-1.13,2.55-1.59,5.07-3.2,7.65-4.77,2.14-1.3,4.34-2.54,6.52-3.8M 1,.48-.29,.51-.82,.04-1.05-2.9-1.58-6.13-2.64-8.91-4.41-.13-.1-.2-.44-.1-.52,4.54-2.98,9.5-5.28,14.61-7.46,.67-.45,4.21-1.29,3.24-2.27-1.96-1.35-4.11-2.43-6.18-3.63-3.63-2.02-3.44-1.95,.44-3.45,6.34-2.43,12.76-4.62,19.2-6.92-.59-1.65-2.8-2.32-4.08-3.47-1.46-1.2-3.46-2-4.5-3.58,.66-.68,1.6-.83,2.45-1.11,6.47-2.15,13.06-4.03,19.69-5.83,.74-.4,4.42-.63,3.66-1.79-1.99-1.78-4.09-3.42-6.14-5.13-2.31-1.91-2.56-2.19,.79-3.03,9.12-2.57,18.67-4.05,27.85-6.45,.19-1.49-9.07-8.13-7.27-8.85Z"/><path class="cls-2" d="M885.38,472.M 98c.59,1.3,1.53,2.38,2.38,3.53,.52-1.43,1.07-2.87,1.65-4.31-1.35,.25-2.69,.5-4.03,.78Z"/><path class="cls-2" d="M928.19,467.74c-.06,.01-.12,.01-.18,.02l.03,.09c.07,0,.14,0,.21-.02l-.06-.09Z"/><path class="cls-2" d="M935.17,478.66c-.47-1-1.07-1.96-1.69-2.89-.73,1.2-1.39,2.49-2.03,3.75,1.16-.11,2.35-.02,3.49-.28,.09-.2,.3-.43,.23-.58Z"/><path class="cls-2" d="M1030.85,456.1l-.1,.1c.05,.01,.1,.01,.15,.02-.02-.04-.03-.08-.05-.12Z"/><path class="cls-2" d="M1095.46,449.73l.12,.03v-.12l-.12,.09Z"/><path class="cls-2" d="MM 1387.26,543.4c.4-2.35-1.88-2.91-3.6-3.69-35.69-15.36-71.58-30.32-108.62-42.71-.94,.1-.65,1.23-.69,1.89,.36,3.32,.78,6.64,1.15,9.97,.24,2.25,.44,4.5,.65,6.75,.02,.25-.6,.58-.88,.48-30.88-11.41-62.2-21.91-94.01-30.84-1.34-6.02-2.43-12.11-4.07-18.07-26.79-7.31-54.23-12.52-81.61-17.42,.35,4.81,2.6,9.36,3.8,14.01,.47,1.6,.25,2.24-1.61,1.87-22.15-4.02-44.44-7.28-66.87-9.42,1.77,4.14,3.56,8.27,5.32,12.4,.23,.7,.74,1.73-.33,1.95-10.58-.86-21.12-2.21-31.73-2.8-8.07-.48-16.13-1.04-24.21-1.13-.55,0-.94,.47-.73,.9,1.79,3.62,3.M 87,7.11,5.76,10.67,.53,.98,.19,1.31-1.25,1.3-15.69-.4-31.51-1.4-47.14,.08-.24,.5,0,.89,.25,1.27,1.22,1.79,2.44,3.59,3.67,5.38,.84,1.23,1.72,2.44,2.51,3.69,.15,.23-.03,.59-.07,.96-5.55,.2-11.01,.24-16.54,.59-1.31,3.68-2.49,7.5-3.59,11.46,8.49-.45,17.01-.31,25.51-.49,.81-.16,3.54,.42,3-1.09-2.23-3.19-4.71-6.25-6.75-9.55-.25-1.05,1.4-.79,2.04-.89,15.23-.39,30.42,.94,45.59,1.36,.8-.39-.05-1.4-.26-1.97-1.67-2.94-3.37-5.87-5.05-8.81-.44-.67-.92-1.65,.34-1.78,18.82,.57,37.5,3.62,56.16,5.35-1.36-4.82-4.45-8.97-5.8-13.73,.7M 7-.36,1.45-.3,2.11-.21,6.65,.84,13.28,1.74,19.89,2.77,14.54,2.27,28.95,4.99,43.32,7.86,.64,.06,1.77,.45,2.15-.22-.89-4.46-2.86-8.73-4.14-13.13-.27-.82-.85-2.02,.64-1.97,26.85,4.89,53.43,11.33,79.62,18.84,1.34,5.46,2.69,10.94,3.93,16.43,.1,.43,.1,.85-.42,1.27-25.71-7.46-51.51-14.89-77.81-20.26-1.34,.02-.59,1.36-.46,2.12,1.38,4.27,3.09,8.46,4.3,12.77-.21,1.11-1.95,.33-2.72,.29-19.96-4.69-40.06-8.7-60.35-11.92-3.23-.4-3.81-.31-2.56,2.31,1.35,2.81,2.66,5.64,3.96,8.46,1.59,3.43,1.16,3.02-2.23,2.65-12.19-1.85-24.33-3.89-M 36.61-5.07-5.2-.62-10.4-1.22-15.63-1.4-.3-.02-.69,.48-.57,.71,2,3.8,4.64,7.25,6.62,11.06,.13,.25-.28,.68-.65,.66-1.61-.08-3.23-.11-4.83-.28-13.65-1.33-27.36-2.31-41.08-2.45-.79-.02-1.22,.55-.82,1.07,2.41,3.1,4.82,6.2,7.07,9.41,.25,.35-.23,.91-.76,.88-12.38-.55-24.79-.37-37.18-.1-.65,.01-1.31,.16-1.94,.32-.15,.04-.35,.38-.28,.51,1.99,3.38,5.61,5.69,7.63,9.04,.06,.14-.13,.46-.3,.53-3.31,.55-6.78,.19-10.13,.39-.81,3.47-1.65,6.97-2.55,10.46,6.9-.31,13.8-.08,20.7-.23,.66-.07,2.31,.23,2.05-.84-2.41-3.14-5.64-5.72-7.89-8.M 93-.04-.14,.18-.47,.34-.49,.78-.13,1.58-.24,2.38-.24,12.37-.1,24.71,.52,37.02,1.36,.29-.53,.08-.92-.19-1.29-1.11-1.47-2.23-2.94-3.37-4.41-1.2-1.55-2.43-3.1-3.61-4.67-.18-.24-.11-.6-.17-1.03,15.47,.27,30.84,2.37,46.18,4.12,1.33-.29,.18-1.46-.15-2.16-1.69-2.69-3.41-5.37-5.1-8.07-.41-.66-1.07-1.25-.93-2.07,1.47-.68,3.12-.06,4.65,.05,16.01,2.23,32.04,4.64,47.87,7.74,.8,.17,3.08,.82,2.72-.54-1.78-3.85-3.77-7.6-5.63-11.42-.2-.53-.79-1.41,.03-1.66,22.09,3.52,43.86,9.05,65.52,14.49-1.73-4.68-3.46-9.36-5.18-14.03-.21-.72-.5M 1-1.3,.21-1.87,26.35,6.19,52.08,14.24,77.75,22.41-1.34-4.09-2.09-8.38-3.19-12.54-.33-1.37-.6-2.75-.86-4.13-.09-.45,.49-.87,1-.74,28.25,8.43,55.74,18.57,83.1,29.23,2.55,.97,5.03,2.09,7.62,2.95,.85,.18,1.03-.38,.99-1.01-.66-5.78-1.6-11.56-2-17.36,.3-1.62,3.01,.26,3.99,.42,35.81,13.52,70.88,28.93,105.59,44.7,.31,.12,.87-.16,.9-.44,.32-6.33,.01-12.7,.1-19.04Z"/><path class="cls-2" d="M1095.46,449.73l.12,.03v-.12l-.12,.09Z"/><path class="cls-2" d="M1030.85,456.1l-.1,.1c.05,.01,.1,.01,.15,.02-.02-.04-.03-.08-.05-.12Z"/><M path class="cls-2" d="M1190.02,521.36s.03,.07,.04,.1l.14-.05c-.06-.02-.12-.04-.18-.05Z"/><path class="cls-2" d="M1177.17,467.11s.01,.05,.02,.07c.02,0,.03,.01,.05,.01l-.07-.08Z"/><path class="cls-2" d="M1117.24,514.85c.02,.06,.04,.11,.06,.17l.1-.13s-.11-.03-.16-.04Z"/><path class="cls-2" d="M1095.46,449.73l.12,.03v-.12l-.12,.09Z"/><path class="cls-2" d="M1030.85,456.1l-.1,.1c.05,.01,.1,.01,.15,.02-.02-.04-.03-.08-.05-.12Z"/><path class="cls-2" d="M912.31,544.44l-.02-.02c-.07,.27-.15,.55-.23,.83,.28-.04,.45-.6,.25-.8M 1Z"/><path class="cls-2" d="M885.35,472.92l-.15,.1c.06-.01,.12-.03,.18-.04l-.03-.06Z"/><path class="cls-2" d="M859.61,551.79c-1.16,.24-2.31,.54-3.57,.83,.18,.38,.22,.74,.46,.91,1.98,1.43,4.06,2.74,6.05,4.16,1.32-2.33,2.52-4.73,3.62-7.2-2.19,.41-4.38,.85-6.56,1.3Z"/><path class="cls-2" d="M846.2,565.07c-.64,.16-1.25,.39-1.97,.61,.1,.32,.07,.72,.3,.87,2.68,1.7,5.46,3.31,8.2,4.93,2.7-3.06,5.26-6.39,7.44-9.82-4.66,1.14-9.32,2.27-13.97,3.41Z"/><path class="cls-2" d="M856.61,647.53c-3.76-2.12-7.62-4.04-11.44-6.07-.3-.16-M .44-.64-.25-.85,2.56-2.85,5.82-5.03,8.47-7.78,.1-.12,0-.47-.15-.57-2.15-1.35-4.54-2.36-6.8-3.52-4.59,2.54-9.28,4.85-14.15,6.77,3.15,1.61,6.48,2.95,9.67,4.48,.64,.43,1.76,.62,1.87,1.48-.79,1.31-1.95,2.5-2.87,3.76,3.97,2.72,7.85,5.56,11.63,8.53,1.38-1.7,2.86-3.35,4.21-5.09,.32-.41,.26-.89-.19-1.14Z"/><path class="cls-2" d="M836.94,578.33c-.63,.19-1.23,.39-1.48,1.06,1.72,1.21,3.82,2.11,5.72,3.17,3.22-2.58,6.27-5.39,9.13-8.43-4.46,1.41-8.91,2.8-13.37,4.2Z"/><path class="cls-2" d="M828.18,637.14c.36,.21,.73,.43,1.09,.65M ,.34-.5,.69-.99,1.04-1.49-.71,.28-1.42,.56-2.13,.84Z"/><path class="cls-2" d="M787.98,663.06c-1.16,3.45-1.67,7.03-3.15,10.38,3.82,.37,7.48,1.68,11.23,2.47,.3,.07,.91-.17,1-.39,.89-2.32,1.5-4.72,2.23-7.1-3.7-1.92-7.47-3.7-11.31-5.36Z"/><path class="cls-2" d="M776.82,657.78l-.03,.09s.07,.01,.1,.02c0-.03,.01-.06,.02-.09-.03-.01-.06-.01-.09-.02Z"/><path class="cls-2" d="M146.8,783.23h.02s.02-.05,.02-.08c-.01,.02-.02,.05-.04,.08Zm8.1,60.16l-.06-.03,.07,.08s0-.03-.01-.05Zm72.61-15.48h-.01v.02c.11,.02,.18,0,.18-.04-.06,.0M 1-.12,.02-.17,.02Zm186.07,66.45s.05,.08,.08,.12l.15-.07c-.08-.02-.15-.03-.23-.05Zm68.05-41.29s-.01,.03-.02,.05l.08-.07s-.04,.01-.06,.02Zm6.46-94.41h-.05l.1,.06s-.04-.04-.05-.06Zm-.05-53.66s.05,.07,.07,.1c.02-.02,.05-.03,.07-.04l-.14-.06Zm5.86,134.46c-1.33-1.21-2.65-2.43-3.93-3.67-.19-.19-.16-.53-.2-.81,4.39-.32,8.82,.51,13.24,.46-.19-3.05-.3-6.1-.35-9.14-.21-.16-.24-.42,0-.55-.07-3.61-.01-7.24,.12-10.83-4.3,.01-8.38-.31-12.7-.53,.1,.41,.06,.78,.26,1,2.87,2.89,6.07,5.48,9.08,8.24,.37,.41,1.37,1.12,.55,1.52-6.84,.05-M 13.71-.72-20.46-1.65-1.2-.09-2.84-.32-1.34,1.24,2.58,2.49,5.18,4.96,7.77,7.45,.51,.49,.97,1.01,1.43,1.53,.06,.07,.02,.23-.04,.32-2.91,.52-6.12-.42-9.06-.7-5.57-.78-11.1-1.73-16.65-2.6-.28-.01-.86-.07-.96,.26,.11,.3,.2,.63,.43,.87,2.56,2.64,5.15,5.25,7.71,7.89,.49,.51,.89,1.07,1.32,1.61,.06,.08,.07,.28,.01,.31-.57,.38-1.24,.14-1.85,.04-8.7-1.45-17.33-3.14-25.87-5.11-.91-.1-2.32-.65-3.11-.35-.07,.18-.17,.43-.07,.55,2.56,3.04,5.15,6.05,7.73,9.08,.45,.53,1.06,.99,1.14,1.68-.62,.38-1.25,.16-1.87,.03-9.62-2.06-19.15-4.4-M 28.53-7.07-2.11-.43-4.01-1.59-6.22-1.32,2.47,4.15,6.23,7.72,8.45,11.81-.18,.13-.44,.33-.6,.3-1.56-.34-3.12-.67-4.64-1.09-11.45-3.19-22.77-6.64-33.91-10.45-1.01-.21-2.51-1.19-3.34-.41,2.31,3.91,5.01,7.6,7.44,11.43,.17,.34,.53,.84,.35,1.19-.21,.1-.51,.27-.67,.21-15.54-4.9-31.02-10.35-46.03-16.53-.82-.26-1.67-.94-2.54-.51-.33,.4,.43,1.33,.56,1.79,1.88,3.57,3.78,7.14,5.67,10.7,.25,.49,.49,.97,.3,1.51-2.04,.15-3.93-1.18-5.85-1.74-17.63-6.62-34.69-14.58-51.72-21.86-.13,.17-.31,.39-.27,.55,1.34,4.08,3.18,8,4.72,12.01,.33,M .82,.62,1.65,.95,2.47,.29,.55-.55,.76-.93,.65-21.89-9.48-43.41-20.06-64.25-31.13-.89-.34-1.78-1.25-2.77-.87-.09,.03-.17,.19-.15,.27,1.39,5.38,2.93,10.72,4.36,16.09,.23,.75-.68,.91-1.18,.57-21.2-10.59-42.14-21.96-62.55-33.89-4.78-2.8-9.53-5.64-14.3-8.46-.53-.31-1.02-.69-1.76-.59-.48,1.6,.11,3.36,.21,5.02,.51,4.58,1.69,9.17,1.87,13.74-.61,.23-1.09,.06-1.52-.19-3.29-1.88-6.61-3.71-9.85-5.65-27.04-15.97-53.85-32.34-79.84-49.93-1.4-.78-3.51-3.04-3.47,.38,0,5.81,.03,11.63,.05,17.44,.07,.87-.09,1.85,.78,2.41,.73,.48,1.44,M .97,2.18,1.44,29.7,18.87,60.26,36.56,91.32,53.3,.76,.42,1.6,.77,2.43,1.11,.11,.04,.57-.19,.57-.28-.1-5.6-1.47-11.11-2.15-16.67-.36-2.9,1.1-1.62,2.71-.86,25.9,14.26,52.12,28.6,79.26,40.39,.51-.46,.33-1,.19-1.5-1.28-5.15-3.26-10.22-4.06-15.45-.03,.01-.06,0-.1-.01,.04,0,.07,0,.11-.01,.05-.06,.09-.11,.14-.16,.03,.06,.05,.1,.03,.14,.96-.23,1.79,.4,2.61,.77,14.08,6.97,28.38,13.67,42.97,19.94,7.77,3.14,15.38,6.87,23.32,9.57,.87-.06,.46-1.05,.32-1.57-1.7-4.31-3.58-8.57-5.22-12.91-.08-.26,.02-.73,.25-.86,1.09-.24,2.23,.66,3M .24,1,11.69,4.9,23.42,9.73,35.43,14.11,6,2.19,12.04,4.32,18.07,6.45,.6,.21,1.27,.29,1.92,.41,.08,.01,.3-.15,.28-.21-1.41-4.29-4.22-8.12-6.17-12.21-.18-.48-.6-1.02-.4-1.51,.12-.25,.35-.33,.65-.23,2.59,.91,5.18,1.81,7.75,2.74,12.66,4.54,25.54,8.64,38.6,12.36,1.67,.26,4.91,2.01,2.72-1.15-2.3-3.53-4.83-6.94-6.99-10.56-.08-.14,.08-.39,.18-.57,12.62,3.04,25.24,7.4,38.18,10.13,1.43,.29,2.84,.73,4.28,.9,.13-.01,.34-.03,.37-.09,.08-.16,.2-.39,.12-.51-2.08-2.77-4.19-5.52-6.28-8.28-.63-.83-1.23-1.67-1.79-2.53-.1-.22,.2-.71,.5M 2-.66,8.43,1.74,16.74,4.06,25.28,5.57,3.53,.68,7.08,1.28,10.63,1.9,.17,0,.5-.28,.38-.48-.43-1.48-10.53-10.75-8.49-10.82,9.33,1.43,18.67,3.24,28.09,4.41,1.02,.16,2.08,.36,3.13,.07,.17-.44-.1-.77-.44-1.1-2.3-2.24-4.6-4.48-6.89-6.73-.68-.66-1.32-1.35-1.97-2.03-.2-.31,.39-.58,.59-.6,8.38,.84,16.73,1.95,25.16,2.57,4.34,.59-3.58-4.8-4.18-5.72Zm-151.35,9.77c.06,.02,.14,.05,.21,.07-.22,.12-.28,.09-.21-.07Zm147.12-14.31s-.08,.01-.11,.02l.11-.11v.09Zm11.65-31.05c-.6,.15-2.35-.2-2.22,.7,1.15,1.42,2.66,2.56,4.02,3.78,.1-1.54,.M 22-3.07,.36-4.6-.72,.04-1.44,.08-2.16,.12Zm2.51,41.61c-.68,0-1.35,.01-2.02,.01-.06,.21-.24,.48-.14,.59,.78,.84,1.61,1.68,2.5,2.41-.13-1.01-.24-2.01-.34-3.01Zm-1.12-56.26c-1.33,.61,1.63,2.55,2.11,3.15,.15-1.12,.32-2.23,.51-3.34-.87,.07-1.74,.12-2.62,.19Zm-7.01,75.31c3.7,.14,7.4,.32,11.09,.49-.65-3.22-1.22-6.48-1.71-9.76-7.03-.08-14.07-1.3-21.05-1.42-.3,.5,0,.85,.34,1.18,2.83,2.88,6.02,5.45,8.61,8.53-.15,1.31-6.75-.05-8-.05-5.2-.62-10.39-1.24-15.58-1.88-2.66-.28-5.29-.85-7.96-1.01-.13,0-.35,.06-.36,.11-.04,.2-.1,.46,M .02,.6,2.89,3.23,5.95,6.36,8.73,9.69,.11,.13-.01,.38-.04,.67-11.92-1.38-23.8-3.64-35.49-6.12-.58-.04-1.41-.36-1.94-.06-.09,.16-.24,.42-.15,.53,2.66,3.5,5.41,6.95,8.08,10.43,.09,.13-.04,.39-.13,.57-.75,.32-1.91-.11-2.73-.17-8.22-1.65-16.43-3.35-24.53-5.38-5.01-1.25-9.99-2.57-14.98-3.87-.52-.14-1.03-.27-1.66,.07,1.93,3.56,4.39,6.85,6.54,10.28,.27,.59,1.16,1.5,.99,2.06-.64,.52-1.5,.17-2.22,.05-13.32-3.45-26.59-7.02-39.55-11.26-1.12-.11-11.09-4.42-9.51-1.79,2.25,4.25,4.61,8.47,6.79,12.76-.9,.62-1.77,.04-2.69-.15-17.11-M 5.24-33.91-11.05-50.39-17.46-2.18-.84-4.36-1.7-6.56-2.5-.44-.16-1.02-.09-1.08,.12-.06,.19-.18,.42-.11,.59,1.32,3.28,2.66,6.55,3.98,9.83,.54,1.33,1.04,2.67,1.53,4.01,.07,.17-.04,.39-.08,.58-.92,.73-2.93-.73-4.02-.94-22.25-8.28-43.86-17.31-65.22-27.12-.57-.26-1.14-.58-2-.48,.41,4.89,2.6,9.65,3.67,14.47,.2,.73,.47,1.46,.23,2.22-.24,.88-2.19-.35-2.78-.46-12.44-5.38-24.69-11.03-36.85-16.8-14.74-6.94-29.09-14.42-43.5-21.77-.47-.22-1.1,.12-1.06,.59,.14,1.39,.26,2.79,.45,4.18,.68,4.9,1.39,9.81,2.08,14.7,28.14,13.76,56.78,2M 6.82,86.02,38.32,1.46,.13,.33-2.29,.26-3.11-1.17-4.41-2.52-8.81-3.62-13.25-.05-.18,.01-.46,.16-.59,.98-.52,2.24,.6,3.23,.85,22,9.36,44.68,17.91,67.48,25.64,.7,.17,2.07,.89,2.35-.04-1.51-4.92-4.17-9.52-5.44-14.5-.02-.12,.33-.38,.52-.39,1.27-.04,2.29,.59,3.38,.98,18.89,6.31,38.27,13.8,57.87,17.63,.08-.67-.35-1.23-.66-1.82-1.56-2.98-3.15-5.95-4.72-8.92-.21-.72-1.81-2.46-.99-2.95,17.52,4.29,34.92,9.76,52.84,13.12-2.57-3.97-5.15-7.94-7.71-11.92-.14-.29-.48-1.02-.04-1.14,14.87,2.57,29.55,6.89,44.62,8.29,.12-.63-.28-1.07-M .64-1.51-2.52-3.18-5.2-6.26-7.59-9.53-.07-.2,.24-.73,.57-.66,2.37,.38,4.74,.8,7.12,1.15,6.88,1.01,13.75,2.09,20.66,2.94,3.05,.38,6.1,.91,9.22,.81,.19,0,.39-.2,.54-.34,.23-.4-.38-.79-.6-1.12-2.57-2.62-5.09-5.29-7.6-7.95-.31-.35-.6-.72-.46-1.25,7.81,.55,15.67,1.67,23.54,2.11,2.82,.02,6.06,.61,8.76,.03,.53-.44-.57-1.25-.92-1.61-2.28-2.13-4.56-4.26-6.82-6.39-.4-.47-1.27-.9-.88-1.6,.03-.07,.23-.14,.35-.14Zm8.4-90.84c-1.58,.57,2.78,3.55,3.29,4.3,.35-1.65,.72-3.3,1.12-4.93-1.47,.21-2.94,.42-4.41,.63Zm8.53-17.82c-2.91,.74-M 6.06,.96-8.95,1.73,.03,.29-.03,.54,.1,.7,2.07,2.44,4.56,4.51,6.8,6.8,.89-3.18,1.85-6.32,2.89-9.44-.25,.06-.54,.13-.84,.21Zm2.51-18.87c2.69-1.86,5.37-3.73,8.06-5.6,.26-.57,.53-1.13,.8-1.7-4.04-3.72-7.12-8.25-10.81-12.31-.63-.61-1.26-1.83-2.32-1.34-3.25,1.84-6.12,4.41-9.61,5.77-.68,0-.92-.42-1.19-.77-4-5.3-8.2-10.48-11.96-15.95-3.77,1.19-7.89,.89-11.87,1.48-.35,1.35,1.01,2.35,1.63,3.46,2.93,3.98,5.88,7.95,8.82,11.92,.41,.75,1.49,1.44,.99,2.34-3.83,.46-7.73,.55-11.59,.84-.35,.02-.63,.47-.45,.73,3.37,4.69,7.26,9.02,10.M 83,13.57,.25,.53,2.13,2.2,1.14,2.45-3,.66-6.14,.27-9.19,.43-1.07,0-2.14,.06-3.21,.09-.31,.01-.73,.51-.59,.69,4.23,5.39,9.02,10.35,13.47,15.56,4.17,.09,8.29-.43,12.42-.8,.56-.08,1.87-.3,1.48-1.1-3.76-4.22-7.63-8.34-11.42-12.54-1.54-1.81-1.65-2.21,.89-2.36,2.92-.38,5.85-.73,8.77-1.15,1.58-.23,1.68-.54,.69-1.69-3.64-4.11-7.09-8.38-10.63-12.58-.45-.53-.97-1.03-1.06-1.71,.35-.56,1.06-.64,1.68-.7,2.95-.28,5.83-.82,8.68-1.48,1.03-.23,1.53-.1,2.09,.55,3.87,4.7,8.05,9.13,11.93,13.83,.68,1.51-8.93,2.74-10.33,3.47-.3,.1-.47,.M 61-.27,.84,1.01,1.15,1.98,2.31,3.04,3.42,2.71,2.88,5.47,5.74,8.25,8.57,1.3-3.8,2.72-7.56,4.24-11.27-1.14-1.17-2.27-2.36-3.37-3.55-.46-.37-.56-1.06-.03-1.41Zm32.42,105.95c-.81-.67-1.65-1.32-2.53-1.91,.1,.98,.21,1.96,.34,2.95,.63-.21,2.65,.04,2.19-1.04Zm6.45-69.83c-.71-.53-1.44-1.05-2.14-1.59-.58,1.86-1.13,3.74-1.65,5.63,1.16-.61,2.32-1.23,3.46-1.87,1.66-.92,1.67-1.15,.33-2.17Zm.59,58.01c-3.43-2.49-7.03-4.81-10.52-7.23,.01,3.24,.13,6.5,.33,9.78,1.18-.4,11.38-1.1,10.19-2.55Zm2.62-13.41c-15.21-10.52-12.53-5.94,2.33-12.M 05,.13-.98-.88-1.25-1.5-1.81-2.94-2.05-5.9-4.09-8.85-6.13-.48-.5-2.28-1.21-1.42-1.97,3.49-1.56,7.13-3.03,10.36-4.98,.14-.08,.18-.45,.08-.56-3.02-2.55-6.36-4.74-9.51-7.16-2.01,8.51-3.4,17.24-4.1,26.11,.77,.56,.99,1.02-.1,1.3-.29,4.08-.44,8.18-.44,12.31,4.74-1.07,9.55-1.96,14.14-3.57,.52-.61-.57-1.13-.99-1.49Zm84.54-110.84c-14.15-3.49-9.51-6.98-13.04,8.75-.02,.6-.64,1.11-1.28,.89-3.02-1.16-6.06-2.3-9.02-3.59-1.15-.38-1.45,.96-1.63,1.77-.63,2.75-1.22,5.51-1.86,8.26-.17,.72-.23,1.5-1.01,2.03-.89,.07-1.54-.37-2.21-.7-2.M 65-1.28-5.27-2.6-7.9-3.91-.32-.16-.87-.01-1,.27-1.41,3.31-1.98,6.93-3.27,10.3-.19,.55-1,.72-1.6,.32-2.9-1.89-5.61-4.02-8.37-6.08-.49-.36-.92-.8-1.64-.89-.65,.28-.84,.79-1.04,1.31-1.19,2.97-2.12,6.05-3.64,8.88-.12,.23-.8,.32-1.06,.14-3.26-2.25-6.16-4.98-9.28-7.4-2.23,3.37-4.34,6.82-6.34,10.34,3.62,2.75,6.97,6.02,10.87,8.34,.7-.4,.96-.89,1.2-1.4,1.55-2.8,2.48-6.03,4.41-8.57,.37,.07,.57,.07,.84,.23,3.65,2.52,7.29,5.06,10.94,7.59-.99,3.34-2.88,6.65-4.19,9.98-.09,.19-.25,.39-.44,.53-.68,.52-1.41-.18-2-.5-2.86-1.96-5.71-M 3.93-8.56-5.9-1.78-1.46-2.29-.75-3.25,.95-1.45,2.3-2.89,4.61-4.34,6.91-.24,.37-.99,.46-1.4,.19-3.38-2.31-6.51-4.96-9.75-7.45-1.76,3.7-3.4,7.47-4.9,11.3,2.24,1.73,4.47,3.47,6.71,5.2,.48,.36,.95,.77,1.87,.77,2.76-2.75,4.39-6,7.05-8.96,3.83,2.72,7.36,5.09,11.18,7.71,.45,.3,1.22,.75,1.71,.32,2.48-2.86,3.25-6.78,5.84-9.51,4.34,1.94,7.65,4.32,12.1,6.05,2-3.63,2.83-7.35,4.57-10.76,.39-.02,.69-.12,.87-.04,3.77,1.64,7.54,3.29,11.3,4.94,0-.01,.01-.03,.01-.04,1.04-3.86,2.26-7.67,3.31-11.53,.55-1.43,4.42,1.01,5.67,1.16,2.1,.69M ,4.24,1.33,6.36,1.99v-.02c.67-4.33,2.31-8.63,2.39-13-.01,0-.02-.01-.03-.01-3.74-1.24-7.49-2.49-11.23-3.72,.79-3.67,1.56-7.35,2.34-11.02,.12-1.07,.45-2.32,1.86-1.79,2.83,.97,5.66,1.98,8.51,2.86,.78,.24,1.47-.32,1.54-1.06,.58-4.15,1.67-8.24,1.87-12.42-.01,0-.03,0-.04-.01Zm-34.01,41.17c-.26,.68-.61,1.76-1.56,1.52-3.95-1.64-7.73-3.69-11.32-5.82,1.39-3.61,2.86-7.32,4.18-10.93,.72-.22,1.2-.04,1.64,.18,3.39,1.74,6.79,3.4,10.29,4.92-1.08,3.38-2.15,6.76-3.23,10.13Zm17.01-13.36c-.55,2.4-1.17,4.8-1.77,7.19-.13,.53-.94,.84-1.5M 6,.6-3.53-1.41-7.17-2.67-10.37-4.57,1.21-4.01,1.74-8.24,3.45-12.07,2.37,.73,8.06,3.04,11.08,4.49-.27,1.46-.5,2.91-.83,4.36Z"/><path class="cls-2" d="M831.23,506.67c-2.08-1.98-4.18-3.95-6.25-5.94-.85-.82-1.37-.89-2.43-.54-8.44,3.01-16.86,6.28-24.9,10-.47,.22-.93,.43-1.51,.26-3.6-2.74-5.76-4.79-7.25-6.94,8.53-4.8,17.92-7.87,26.8-12.04-2.03-2.85-4.47-5.38-6.48-8.12-9.56,3.5-18.56,8.01-27.71,12.32-.68-.12-1.07-.39-1.37-.76-1.45-1.82-2.89-3.64-4.36-5.45-.45-.47-1.02-1.28-1.77-1.09-8.28,3.88-15.68,9.09-23.52,13.58-2.66-2M .27-3.71-5.23-6.14-7.57-1.12,.18-1.73,.79-2.41,1.28-6.21,4.3-12.24,8.78-18.2,13.29-.26,.18-.87,.09-1.03-.16-.87-1.33-1.74-2.67-2.6-4.01-.87-.9-1.58-4.03-3.18-3.02-6.05,4.54-11.27,9.85-16.86,14.82-.35,.31-1.13,.16-1.29-.24-.79-2.15-1.25-4.4-1.93-6.6-.3-1.19-1.23-.87-1.84-.21-4.76,4.51-9.58,9.05-14.02,13.79-.47,.51-.82,1.14-1.88,1.26-1.61-2.6-1.5-5.62-2.84-8.28-.65-.05-1.03,.23-1.35,.6-1.9,2.09-3.81,4.18-5.68,6.29-2.77,3.04-5.34,6.25-8.2,9.21-.13,.12-.5,.16-.71,.11-.61-.17-.68-.85-.82-1.36-.66-2.3-1.32-4.61-2-6.91-.0M 5-.19-.28-.41-.5-.47-.6-.08-1.07,.53-1.44,.93-4.11,4.61-7.89,9.49-11.7,14.33-.49,.45-1.1,1.62-1.88,1.17-1.62-3.02-1.71-6.62-2.97-9.63-.93-.02-1.36,.87-1.9,1.47-2.8,3.68-5.59,7.36-8.38,11.05-.65,.72-1,1.71-2.06,1.9-1.55-2.9-1.32-6.31-2.12-9.45-.12-.62-.13-1.29-.78-1.78-.75,.13-1.02,.65-1.35,1.11-2.48,3.45-4.95,6.92-7.43,10.37-.59,.63-1.26,2.08-2.04,2.32-.78-.15-.81-.96-.95-1.58-.7-3.71-.62-7.59-1.85-11.18-1.19,.04-1.57,1.31-2.29,2.07-2.33,3.28-4.63,6.57-6.95,9.84-.56,.61-.9,1.55-1.91,1.32-1.07-4.54-1.16-9.2-1.7-13.8M 1-.05-.47-.33-.81-.59-.7-.84,.28-1.3,.94-1.77,1.62-2.7,3.59-5.3,7.25-7.98,10.86-.1,.13-.45,.16-.7,.2-.35-.17-.39-.79-.48-1.13-.6-4.5-.68-9.02-.92-13.55-.38-2.4-.52-2.86-2.27-.79-2.79,3.55-5.36,7.26-8.26,10.72-.11,.11-.48,.08-.72,.08-.48-.08-.39-.76-.49-1.13-.55-5.91-.77-11.82-.86-17.75-.4-2.29-6.11,6.19-7,6.86,1.59,5.96,3.37,11.57,5.55,16.87,.56-.62,1.48-2.53,2.46-1.83,.77,3.21,.56,6.59,1.26,9.84,.01,0,0,.01,.01,.02,.97,1.85,2.02,3.66,3.15,5.44,11.64-17.45,7.32-12.19,10.85,3.78,.71,.16,1.1-.05,1.37-.47,2.26-3.43,4.M 51-6.87,6.78-10.29,1.15-1.66,2.3-3.58,2.87-.28,.38,3.44,1.26,6.82,1.96,10.22,.1,.29,.26,.72,.59,.79,.23,0,.58,0,.67-.1,.44-.54,.82-1.11,1.19-1.68,2.16-3.35,4.3-6.71,6.47-10.05,.62-.75,.95-1.78,2.1-1.84,.99,3.57,1.86,7.17,2.83,10.73,.07,.26,.49,.46,.74,.68,.91-.48,1.18-1.23,1.62-1.89,2.38-3.62,4.76-7.24,7.15-10.86,.41-.47,.8-1.29,1.43-1.47,.23,.06,.58,.15,.62,.28,.39,1.14,.72,2.29,1.08,3.44,.62,1.98,1.24,3.96,1.9,5.94,.03,.11,.4,.18,.63,.22,3.61-3.83,6.32-8.79,9.61-13.01,.66-.77,1.01-1.76,2.19-1.84,.76,1.18,2.69,9.7M ,4.04,8.62,4.15-4.85,7.72-10.15,11.9-14.99,.54-.48,1.42-2.07,2.17-1.16,.76,1.95,1.52,3.9,2.25,5.85,.27,.73,.5,1.46,1.22,2.01,.87-.2,1.19-.83,1.64-1.36,3.65-4.26,7.3-8.53,10.96-12.79,.73-.63,1.3-1.99,2.38-1.95,.22,.05,.46,.25,.54,.43,.97,2.32,1.55,4.93,3.01,6.98,.38,.22,.96-.33,1.23-.54,4.2-4.62,8.65-9.09,13.2-13.49,.58-.57,1.05-1.26,2.14-1.55,2.3,2.1,3.17,4.93,5.48,7.09,1.41-.23,2.18-1.46,3.18-2.32,4.28-4.17,8.83-8.14,13.61-11.95,.54-.43,.99-1.01,1.99-1.07,1.82,2.21,3.67,4.45,5.53,6.68,.24,.18,.47,.15,.85,.21,6.62-M 4.69,13-9.77,19.92-14.06,.43-.28,1.1-.19,1.42,.18,1.81,2.38,4.37,4.35,5.68,7.03-7.04,4.38-13.59,9.46-20.38,14.12-.88-.18-1.26-.64-1.67-1.05-1.66-1.69-3.31-3.39-4.97-5.09-.24-.25-.77-.28-1.07-.06-5.57,4.28-10.98,8.91-16.05,13.65-.5,.47-.9,1.06-1.86,1.21-2.57-1.69-3.4-4.61-5.96-6.36-.38-.22-.64,.01-4.05,3.39-.42,.42-.85,.84-1.26,1.26-3.17,3.22-6.32,6.45-9.49,9.66-.48,.49-.85,1.1-1.94,1.26-1.97-2.09-3.32-4.58-5.18-6.81-.84,.09-1.19,.54-1.54,.98-3.33,4.05-6.65,8.1-9.97,12.16-.9,.76-2.25,4.01-3.55,2.27-1.21-2.16-2.24-4.M 4-3.59-6.49-.79-.4-1.42,.74-1.91,1.19-3.94,4.77-7.24,9.84-10.98,14.69-.17,.22-.89,.19-1.03-.04-1.36-2.34-2.65-4.7-3.93-7.07-.14-.25-.83-.25-1.02,0-3.29,4.4-6.17,9.07-9.21,13.64-.4,.52-.69,1.3-1.5,1.22-.11,0-.27-.1-.31-.19-.9-1.91-1.78-3.82-2.67-5.73-.42-.9-.53-1.91-1.45-2.72-1.4,.58-1.88,2.22-2.74,3.37-1.88,3.1-3.73,6.21-5.6,9.31-.52,.64-.76,1.89-1.7,1.97-.23-.05-.5-.24-.57-.41-1.12-2.65-2.22-5.31-2.92-8.06-.16-.63-.3-1.27-.95-1.73-.99,.36-1.36,1.51-1.96,2.31-2.17,3.59-4.31,7.18-6.48,10.77-.33,.45-.86,1.4-1.54,.96-M 5.44-15.24-1.26-15.72-11.87,1.03,2.72,2.43,5.58,4.68,8.57,6.78,1.2-1.79,1.7-4.04,3.37-5.47,.1,.03,.27,.03,.3,.09,1.96,3.31,2.55,7,4.43,10.31,.85-.12,1.1-.61,1.37-1.1,2.15-3.83,4.3-7.66,6.47-11.49,1.88-3.29,2.12-1.61,3.26,.82,1.05,1.96,1.54,4.26,3.04,5.94,.95,.38,1.31-1.15,1.79-1.71,11.17-18.46,5.73-14.75,13.52-5.12,3.61-4.88,6.38-10.33,9.92-15.28,.54-.79,1.06-.5,1.52-.06,1.24,1.78,2.46,3.58,3.7,5.36,.3,.43,.96,1.03,1.48,.63,1.08-1.48,2.14-2.98,3.16-4.49,2.5-3.69,5.15-7.32,8-10.85,.32-.39,1.03-.39,1.34-.02,1.42,1.7,M 2.84,3.41,4.25,5.11,.31,.37,.68,.65,1.38,.73,4.01-4.8,7.98-9.69,11.98-14.51,.43-.53,.8-1.13,1.78-1.35,2.22,2.08,3.83,4.37,6.48,6.16,4.86-4.64,9.4-9.48,14.15-14.21,.49-.49,.93-1.07,1.92-1.19,2.15,1.87,4.35,3.76,6.52,5.66,.15,.13,.14,.38,.21,.6-4.75,4.63-9.31,9.49-13.95,14.23-.34,.35-.6,.71-.46,1.28,2.34,1.63,5.04,3.2,7.47,4.7,.98-.17,1.36-.77,1.84-1.27,4.23-4.47,8.58-8.87,13.04-13.17,0-.2,.06-.48-.08-.59-2.29-1.79-4.99-3.29-7.09-5.21,.05-.27,.01-.53,.15-.68,1.84-2.11,13.87-12.2,17.29-14.52,3.04,1.64,4.87,4.35,8.07,5M .83,6.56-4.7,13.42-9.32,20.21-13.66,.98,.24,1.4,.83,1.98,1.27,1.94,1.5,3.88,2.99,5.83,4.48,.78,.54,1.8-.04,2.53-.45,6.79-3.99,13.86-7.51,20.96-10.97,.49-.24,1.1-.18,1.47,.13,2.36,2.24,5.34,3.95,7.25,6.55-7.52,3.82-15.49,7.01-22.42,11.46,2.03,2.19,5.44,3.71,7.92,5.56,.45,.29,1.01,.27,1.51,.02,5.62-2.83,11.2-5.62,17.03-8.06,1.63-.72,3.54-1.05,4.83-2.22,1.39-.01-6.76-5.26-7.96-6.68,.95-.97,2.2-1.19,3.39-1.71,7.03-2.73,14.06-5.45,21.35-7.71,.73-.23,1.53-.39,1.94-1.07-.19-.26-.34-.57-.59-.81Zm-44.07-2.5c-7.14,3.47-13.83M ,7.45-20.65,11.3-.65,.37-1.21,.88-2.29,.9-2.24-1.86-4.51-3.83-6.59-5.94-.34-.34-.27-.84,.19-1.13,2.11-1.33,4.18-2.71,6.37-3.96,4.92-2.82,9.9-5.58,14.86-8.35,.68-.34,1.35-.85,2.15-.6,2.28,2.02,4.34,4.4,6.54,6.55,.15,.16,.18,.4,.28,.65-.28,.18-.54,.42-.86,.58Zm21.99-20.89s.03,.05,.06,.07c.02,0,.04,0,.06-.02l-.12-.05Zm-218.39,90.11c-.7-2.31-.97-5.08-1.96-7.18-.25,.04-.6,.05-.71,.19-1,1.21-1.71,2.57-2.54,3.89,1.88,2.16,3.85,4.22,5.92,6.17-.24-1.02-.46-2.05-.71-3.07Zm-48.71,7.6c.31,.9,.25,4.29,1.85,2.92-.64-.97-1.26-1.9M 4-1.85-2.92Zm-14.88-33.92c-.6,.69-1.24,1.3-1.97,1.89-.1,.08-.61,0-.65-.09-1.03-2.73-.69-5.78-1.09-8.64,0-.07-.77-10.3-.79-10.36-.56-2.35-1.09-4.7-1.59-7.04-3.03,2.39-5.65,5.23-8.52,7.81-.79,.55-2.23,2.73-3.12,1.43-.53-9.34-1.26-18.72-1.18-28.09-.08-.49,.11-1.59-.36-1.82-.24-.03-.58-.1-.74,0-3.38,2.41-6.54,5.12-9.84,7.65-.75,.42-1.6,1.69-2.53,1.32-.25-.18-.41-.54-.42-.83-.14-2.8-.23-5.6-.33-8.4-.37-8.3-.07-16.59,0-24.88-.53-1.47-2.21,.2-3.02,.6-3.04,1.96-6.07,3.93-9.11,5.9-.73,.36-1.47,1.22-2.35,.99-.2-.07-.42-.3-.4M 2-.47-.04-2.15-.09-4.31-.05-6.46,.21-9.66,.37-19.32,.92-28.97-1.55-.76-3.14-1.46-4.78-2.09l-8.28,4.32c-.8,.24-2.47,1.65-3.05,.65-.19-2.82,.09-5.62,.23-8.44-5.31-1.28-10.88-2.08-16.55-2.39-.09,5.66-.31,11.32-.17,16.98,.33,3.34,10.15-2.36,12.04-2.98,1.01-.23,3.85-2.57,4.22-.87-.02,2.05-.01,4.09-.1,6.14-.46,10.56-.39,21.11,.14,31.66,.15,.78-.24,2.66,1.11,2.26,4.14-2.14,7.99-4.76,12.01-7.11,.54-.28,1.53-.92,2.05-.34,.57,11,.32,23.99,1.71,34.84,.62,.83,1.65-.13,2.27-.52,2.57-1.9,5.14-3.8,7.7-5.71,1.01-.49,3.04-3.16,3.82M -1.42,.32,4.09,.63,8.17,.94,12.26,.51,5.91,.6,11.87,1.85,17.69,.56,.55,1.4-.25,1.87-.6,3.18-2.78,6.2-5.72,9.5-8.36,.19-.16,.97,.06,1.02,.28,.09,.42,.21,.84,.26,1.27,.62,5.79,1.21,11.59,1.86,17.38,.39,1.35,.51,8.49,2.24,7.63,2.97-2.73,5.57-5.82,8.37-8.71,.52-.52,1.55-1.9,2.18-.78,1.17,7.47,2.11,15.03,3.64,22.42,.9,1.34,1.93-.61,2.57-1.27,1.4-1.74,2.79-3.49,4.18-5.23-3.18-6.88-5.65-13.76-7.68-20.5Zm-18.55-68.83c-.31,7.24-.53,14.53-.22,21.76,.66,.3,1.08,.08,1.48-.24,1.61-1.33,3.22-2.66,4.83-3.99-1.71-6.19-3.67-12.04-6M .09-17.53Zm-5.29-89.47c-.05-.13-.47-.29-.59-.24-.96,.38-1.91,.79-2.83,1.23-4.43,2.02-8.7,4.39-13.23,6.2-1.34,.05-.67-1.6-.67-2.43,.99-6.08,1.9-12.18,3.02-18.25,1.39-7.45,2.95-14.89,4.45-22.33,.55-2.76,1.15-5.52,1.72-8.28,0-1.61-2.31-.07-3.14,.08-4.66,1.68-9.31,3.38-13.98,5.05-.51,.12-2,.67-2.08-.06,2.07-15.22,6.29-30.15,9.66-45.16,.98-4.66,2.72-9.2,3.35-13.94-.42-1.05-1.94-.2-2.76-.12-5.36,1.42-10.73,2.86-16.09,4.27-1.11,.31-2.53,.56-2.02-1.14,5.27-22.91,12.06-45.53,18.31-68.17,.04-.3-.41-.65-.76-.6-6.98,1.13-13.96M ,2.33-20.94,3.49-1.73,.03-.72-2-.6-2.98,7.24-26.51,16.21-52.63,24.67-78.8-7.54,.69-15.1,1.11-22.67,1.05-.88,.06-1.86-.13-2.59,.42-8.11,26.47-16.23,53.03-22.35,80.01,.09,.63,1.02,.72,1.54,.74,5.93,0,11.86,0,17.79-.01,1.93-.16,2.81-.02,2.29,1.52-5.98,21.93-11.33,44.02-15.83,66.29-.04,.73-.46,2.13,.47,2.34,6.44,.57,12.63-1.87,18.83-3.12,1.85-.16,.76,1.91,.71,2.92-3.46,15.23-6.54,30.54-9.29,45.9-.64,3.52-1.23,7.04-1.82,10.56-.11,.63-.28,1.29,.26,1.99,6.22-1.34,12.06-4.23,18.2-5.91,.32-.08,.87,.24,.83,.51-2.46,16.55-5.9M 2,32.96-7.4,49.65,1.61,.31,3.22,.64,4.82,1.01,3.1-1.38,6.18-2.77,9.27-4.17,1.05-.39,2.07-1.23,3.25-.91,.13,.03,.25,.38,.22,.57-.39,2.59-.75,5.18-1.07,7.77,5.31,1.77,10.53,3.91,15.57,6.46,.74-5.15,1.43-10.3,2.47-15.42,.35-2.63,1.28-5.36,1.01-7.99Zm-8.37,69.83c-.29,4.96-.42,9.92-.63,14.88-.02,1,.49,1.28,1.3,.92,2.73-1.77,5.37-3.65,8.02-5.53-2.47-3.84-5.38-7.25-8.69-10.27Zm-6.1-312.14s-.02,.09-.04,.13c.04,0,.08-.01,.12-.01l-.08-.12Zm-25.35,1.63s.03-.02,.05-.03t.01-.02l-.06,.05Zm-14.24,264.13s.03-.01,.05-.02c.01-.02,.0M 1-.03,.02-.05l-.07,.07Z"/><path class="cls-2" d="M510.8,220.17s-.02,.03-.03,.05c-.02,0-.03,.01-.05,.01l.08-.06Z"/><path class="cls-2" d="M597.34,493.02h-.05s-.02-.05-.03-.07l.08,.07Z"/><path class="cls-2" d="M809.15,483.28s.05-.02,.07-.03c.01,.03,.03,.05,.05,.08l-.12-.05Z"/><path class="cls-2" d="M870.74,441.97s-.07,.02-.11,.02l-.03-.09,.14,.07Z"/><path class="cls-2" d="M885.2,473.02s-.04-.05-.05-.07c.07-.01,.13-.02,.2-.03l-.15,.1Z"/><path class="cls-2" d="M902.6,447.3c-2.82,3.91-5.42,8.15-7.64,12.58-4.84,.83-9.68,M 1.62-14.46,2.67-.85,.21-1.1,.56-.83,1.19,1.4,3.22,3.26,6.28,5.48,9.21-12.17,1.97-24.04,4.78-35.9,7.92-.48,.16-.75,.73-.46,1.08,2.16,2.64,4.41,5.36,6.58,8-.46,.61-1.12,.77-1.74,.94-2.16,.58-4.34,1.13-6.51,1.71-7.75,2.04-15.34,4.47-22.87,6.96-.34-.15-.64-.2-.79-.35-2.18-2.19-4.34-4.38-6.5-6.58-.34-.35-.54-.73-.27-1.3,9.88-3.81,20.53-7,30.7-10.09,.17-.45,.04-.65-.15-1.01-1.8-2.64-3.61-5.27-5.4-7.87-2.17,.15-4.78,.87-11.04,3.05-7.19,2.58-14.55,4.89-21.58,7.84-1.92-2.7-3.85-5.36-5.87-7.99-.22-.31-.68-.41-1.05-.3-8.8,3.3M 6-17.27,7.54-25.56,11.73-.65,.34-1.23,.8-2.21,.84-1.65-1.54-2.66-3.69-3.98-5.51-.7-.88-1.25-2.97-2.71-2.16-8,4.03-15.29,9.14-22.92,13.62-.72-.11-1.01-.45-1.25-.85-1.09-1.86-2.17-3.71-3.26-5.56-.34-.56-.55-1.19-1.25-1.58-.87,.09-1.42,.59-2.02,1.02-5.03,3.57-10.16,7.08-14.86,10.94-1.45,1.01-2.53,2.48-4.36,2.84-1.2-2.72-1.15-5.57-1.94-8.28-.95-.21-1.61,.57-2.32,1.04-5.75,4.4-10.76,9.34-16.19,13.99-.34,.25-1.11,.08-1.25-.33-.51-2.54-.92-5.11-1.37-7.66-.03-.15-.35-.28-.57-.37-.36-.02-.73,.28-1,.49-4.64,4.33-9.28,8.67-13M .92,13.01-.78,.73-1.55,1.47-2.34,2.2-.25,.24-.87-.07-.95-.27-.54-2.75-.87-5.56-1.47-8.3-.05-.16-.35-.29-.57-.4-.77,.12-1.4,1.02-1.99,1.49-4.04,4.31-8.06,8.63-12.1,12.94-.79,.66-1.36,1.9-2.51,1.88-.06,0-.18-.14-.2-.23-.84-3.04-1.24-6.15-1.76-9.25-.03-.18-.23-.34-.39-.49-.68-.36-1.53,.9-2,1.36-3.29,3.81-6.58,7.62-9.86,11.44-1,1.15-1.92,2.36-2.96,3.47-.31,.33-.79,.46-1,.26-.17-.16-.41-.32-.44-.5-.4-2.23-.76-4.48-1.15-6.72-.19-1.06-.41-2.12-.66-3.18-.04-.15-.31-.37-.48-.38-1.04,.21-1.57,1.45-2.27,2.14-2.75,3.45-5.48,6.M 91-8.23,10.37-.48,.43-.88,1.3-1.58,1.32-.41,.01-.45-.41-.56-.71-1.05-3.72-.34-8.42-1.64-11.78-1.02,.03-1.44,1.13-2.08,1.77-2.71,3.47-5.39,6.96-8.1,10.43-.35,.44-.79,.84-1.22,1.25-.05,.05-.35,.02-.37-.03-.16-.28-.36-.57-.38-.86-.23-3.88-.42-7.75-.64-11.62-.21-1.26,.09-2.87-1.54-1.41-3.33,4.03-6.3,8.35-9.74,12.26-.26,.18-.91,.19-.9-.21-2.51-16.31,3.86-23.37-10.14-5.66-.62,.58-1.19,1.76-1.96,1.96-.22-.08-.57-.21-.58-.33-.11-1.07-.21-2.15-.21-3.22,.02-4.53,.09-9.05,.12-13.57,.01-.54-.1-1.07-.18-1.6,0-.06-.17-.13-.29-.1M 6-.52-.18-.84,.41-1.17,.68-2.5,2.94-4.99,5.89-7.48,8.83-.61,.71-1.2,1.44-1.88,2.1-.16,.15-.68,.08-1.04,.11-1.71-22.73,6.39-29.37-9.84-11.79-.63,.57-1.14,1.62-2.14,1.46-.09-.45-.19-.86-.29-1.31,.06-7.88,.91-15.74,1.31-23.6-.72-1.4-4.79,3.76-5.77,4.39-1.54-5.94-3.34-11.98-5.61-18.14,.11-1.35,.22-2.68,.31-4.03,.01-.09-.07-.25-.14-.27-.69-.23-1.06,.23-1.57,.59-2.48-6.27-5.51-12.89-9.11-18.7,.27-1.53,.44-3.07,.64-4.61,.01-.09-.1-.26-.17-.27-1.1-.2-1.87,.86-2.75,1.36-2.97-4.35-6.25-8.38-9.79-12.08,.88-5.92,2.4-11.77,2.74M -17.75,0-.1-.47-.34-.58-.29-4.52,2.5-8.76,5.49-13.23,8.09-.65-.5-1.31-1-1.97-1.49,.82-8.15,2.4-16.18,3.88-24.23,1.14-5.52,2.31-11.04,3.47-16.56,.05-.28,.01-.74-.18-.92-.7-.3-1.53,.32-2.18,.57-4.34,2.18-8.66,4.37-13.03,6.5-.63,.28-1.97,1.11-2.26,.09,2.79-16.8,6.97-33.35,10.99-49.91-.28-1.38-3.2,.56-4.1,.69-4.87,1.8-9.59,4.04-14.56,5.54-.3,.07-.6-.09-.57-.34,3.22-17.18,8.15-34.06,12.92-50.9,.62-2.1,1.2-4.2,1.78-6.3,.15-.52,.28-1.06-.32-1.59-5.58,1.41-11.15,3.12-16.71,4.65-1.03,.11-3.92,1.74-3.75-.23,6.36-22.81,12.97-M 45.66,20.88-67.96,7.44-1.42,14.86-3.01,22.31-4.34,.39-.05,.84,.28,.75,.56-2.32,6.51-4.71,13.02-7.02,19.54-5.05,15.45-11.12,30.84-14.97,46.53,.51,.64,1.48,.17,2.14,.06,6.04-1.78,12.06-3.67,18.12-5.4,.8,.59,.32,1.4,.16,2.17-2.02,6.26-4.14,12.49-6.06,18.76-3.25,10.78-6.36,21.57-9.38,32.4-.37,1.36-.63,2.75-.93,4.13-.05,.24,.59,.54,.91,.42,5.46-2.08,10.79-4.39,16.21-6.57,2.25-.84,2.28-.2,1.75,1.89-4.45,15.58-9.05,31.2-12.02,47.1-.03,.28,.58,.5,.93,.33,4.73-2.25,9.28-4.78,13.94-7.16,.78-.29,1.65-1,2.48-.92,.2,.25,.43,.52M ,.31,.85-.37,1.48-.75,2.95-1.11,4.43-2.69,10.64-5.08,21.34-7.33,32.08-.39,1.79-.59,3.62-.86,5.43-.02,.09,.07,.27,.14,.29,.92,.25,1.65-.52,2.39-.9,3.49-2.2,6.97-4.41,10.46-6.62,.96-.45,1.85-1.56,2.98-1.46,.44,.17,.46,.72,.31,1.11-2.01,12.14-5.64,24.09-6.49,36.37,.67,.15,1.1-.07,1.51-.38,4.13-3.1,8.23-6.21,12.39-9.27,.49-.22,1.33-.38,1.18,.58-1.68,9.16-3.25,18.31-4.45,27.54-.03,.88-1.05,4.19,.36,4.11,4.01-2.94,7.61-6.4,11.46-9.55,.64-.47,2.34-1.96,2.17-.17-1.46,9.16-3.11,18.34-3.57,27.61,1.02,.21,1.5-.62,2.19-1.17,3.M 21-3.05,6.4-6.11,9.61-9.16,.35-.24,1.17-.96,1.59-.65,.6,3.74-.96,8-1.12,11.84-.41,4.08-.69,8.17-1,12.25,.66,1.6,2.63-1.52,3.32-2.02,2.91-2.96,5.56-6.15,8.63-8.95,.12-.1,.47-.04,.71-.02,.28,6.48-.87,13.33-1.24,19.92-.01,.66-.04,1.71,.95,1.28,3.62-3.71,6.96-7.65,10.48-11.45,.3-.33,.62-.68,1.23-.62,.34,.6,.21,1.21,.18,1.84-.14,5.48-.8,11-.62,16.46,.75,.99,1.47-.42,2.11-1.01,3.3-3.66,6.23-7.66,9.77-11.08,.11-.08,.61,.05,.67,.15,.07,.54,.17,1.07,.16,1.6-.04,4.63-.53,9.26-.13,13.88,.01,.14,.33,.28,.53,.38,4.11-3.58,7.15-M 8.65,11.06-12.59,1.61-1.43,1.31,1.19,1.31,2.1,.06,3.66,.11,7.32,.19,10.99,0,.17,.22,.35,.34,.52,.55,.43,1.36-.61,1.73-1.05,3.48-4.1,6.93-8.25,10.62-12.19,.11-.12,.46-.12,.7-.13,.37,.31,.29,1.05,.38,1.52,.19,2.9,.36,5.81,.55,8.71,.19,.6-.22,1.99,.66,2.01,1.01-.09,1.46-1.18,2.14-1.77,2.68-2.97,5.35-5.95,8.05-8.9,1.35-1.48,2.72-2.95,4.18-4.37,.62-.6,.95-1.57,2.29-1.5,.78,.61,.44,1.4,.48,2.11,.34,2.87-.19,5.9,.76,8.65,.47,.91,1.79-.88,2.27-1.19,4.35-4.4,8.67-8.81,13.01-13.2,.59-.59,1.25-1.13,1.92-1.66,.1-.07,.64,.03,.6M 6,.11,.74,3.04,.63,6.22,1.03,9.32,.38,1.08,1.32,.52,1.94-.17,3.25-3.45,6.87-6.65,10.42-9.89,1.87-1.7,3.8-3.35,5.75-4.99,.21-.18,.68-.17,1.13-.27,.58,3.11,.63,6.05,1.17,9.08,.03,.19,.88,.36,1.06,.21,6.21-5.06,11.89-10.7,18.45-15.36,.26-.2,.92,0,.96,.29,.38,2.77,.36,5.63,1.03,8.34,.73,1.06,2.85-1.35,3.66-1.77,5.58-4.34,11.47-8.59,17.49-12.45,.24-.14,.95,.1,.98,.33,.39,2.56,.53,5.14,.75,7.72,.58,1.26,2.06-.14,2.82-.58,7.01-4.31,13.83-9.13,21.35-12.74,.75-.13,1.1,.8,1.43,1.3,1.15,2.07,2.29,4.14,3.44,6.2,.22,.4,.53,.74,M 1.32,.85,8.84-4.58,17.82-9.35,27.23-12.98,.26-.1,.92,.1,1.06,.32,1.56,2.5,3.07,5.03,4.63,7.53,.18,.26,.56,.43,.9,.69,10.58-4.29,21.49-7.88,32.32-11.79,.21-.17,.34-.62,.2-.89-1.41-2.9-2.77-5.82-4.38-8.74-11.67,3.21-22.55,8.23-33.92,12.26-2.15-2.67-3.2-5.64-4.75-8.58-.19-.37-.92-.59-1.36-.39-8.26,3.52-16.18,7.66-24.1,11.82-.82,.23-2.73,1.94-3.31,.79-.15-2.79-.09-5.6-.42-8.38-.01-.12-.46-.31-.63-.27-8.2,3.78-15.59,9.19-23.4,13.73-.25,.15-.94-.07-.99-.31-.45-2.11-.21-4.3-.34-6.44,0-.65-.05-1.29-.06-1.94,0-.26-.14-.43-.M 47-.43-1.02-.02-1.79,.85-2.62,1.31-6.4,4.29-12.59,8.79-18.73,13.3-.3,.21-.94,.06-.97-.23-.39-2.99-.11-6.02-.14-9.02,0-.25-.18-.39-.5-.42-.51-.03-.97,.33-1.36,.58-5.38,4.02-10.52,8.3-15.62,12.65-.65,.54-1.27,1.12-1.95,1.64-.44,.35-.81,.96-1.62,.66-.6-.22-.41-.75-.42-1.15-.02-2.78,.13-5.61-.03-8.39-.04-.26-.37-.7-.69-.65-6.32,4.51-12.07,10.17-17.79,15.38-.3,.33-1.04,.76-1.3,.5-1.39-.75,.86-12.74-1.57-10.95-6.01,5.04-11.06,11.45-17.17,16.19-.33,.02-.53-.12-.53-.39-.03-2.47-.07-4.95-.08-7.42-.01-1.4,.07-2.79,.06-4.19,0M -.13-.33-.27-.53-.37-5.53,4.15-10.14,9.81-15,14.71-.64,.68-1.37,1.31-2.07,1.95-.06,.06-.24,.05-.36,.03-.12-.02-.31-.07-.32-.13-.08-.43-.19-.86-.17-1.28,.18-4.09,.47-8.17,.55-12.26,.01-.08-.12-.22-.19-.22-.96-.18-1.41,.74-2.03,1.28-3.15,3.37-6.28,6.74-9.42,10.11-.62,.5-1.13,1.4-1.9,1.58-.21-.09-.54-.23-.54-.35,.01-1.4,.04-2.8,.12-4.19,.03-3.7,.78-7.66,.48-11.24-.23-.03-.59-.08-.69,.02-4.12,4.07-7.98,8.35-11.78,12.69-.76-.27-.87-.66-.83-1.36,.08-5.73,1.19-11.38,1.63-17.07-.99-.2-1.5,.62-2.14,1.18-3,3.18-5.98,6.38-8.9M 8,9.56-.49,.51-1.05,.97-1.6,1.44-.05,.05-.26,.01-.37-.02-.1-.04-.25-.13-.25-.19-.01-.86-.07-1.72,.02-2.57,.66-5.25,.99-10.56,1.99-15.75,.98-4.54-1.67-1.43-3.23,.05-2.72,2.67-5.41,5.36-8.13,8.04-.55,.38-1.39,1.64-2.03,.9,.05-1.18,.02-2.37,.2-3.53,.92-6.1,1.9-12.18,2.85-18.27,.35-2.58-.45-2.12-2.03-.82-2.99,2.77-5.96,5.56-8.95,8.34-.61,.57-1.29,1.09-1.96,1.62-.05,.04-.25-.03-.37-.07-.1-.04-.25-.11-.26-.18-.25-1.4-.02-2.8,.23-4.18,1.12-6.07,2.32-12.13,3.44-18.2,.29-1.59,.43-3.2,.62-4.8-.5-.82-1.58,.48-2.11,.78-3.97,3.M 19-7.62,6.8-11.82,9.71-.13,.08-.57,0-.59-.2,1.37-10.51,4.34-20.78,6.06-31.25,.03-.12-.25-.31-.43-.42-.81,0-1.54,.87-2.24,1.25-3.46,2.56-6.9,5.14-10.35,7.71-.63,.3-1.23,1.13-1.96,.96-.1-.03-.25-.11-.25-.17-.03-3.36,1.14-6.58,1.8-9.87,1.51-6.45,3.03-12.91,4.57-19.36,.06-1.31,2.86-7.5,.86-7.11-4.67,2.68-9.12,5.73-13.7,8.54-.62,.4-1.21,.88-2.17,.86,1.21-7.82,3.7-15.62,5.66-23.38,1.72-6.08,3.45-12.17,5.16-18.26,.01-1.6-2.25,.14-2.95,.38-4.05,2.12-8.1,4.26-12.15,6.39-.73,.31-2.56,1.72-2.71,.24,1.87-7.95,4.43-15.75,6.61-2M 3.62,2.25-7.43,4.77-14.8,7.04-22.23,.22-.71,.7-1.42,.16-2.17-6.31,1.78-12.1,5.27-18.39,7.29-.4,.16-.7-.35-.67-.58,5.67-18.91,11.84-37.65,19.07-56.06l.25-.22c7.26-2.32,14.5-4.65,21.75-6.97-7.25,17.31-13.92,34.82-20,52.44-.28,.82-.5,1.67-.69,2.51-.02,.08,.42,.36,.54,.32,6.26-2.04,12.05-5.39,18.34-7.35,.14-.03,.56,.24,.54,.33-.16,.73-.34,1.47-.62,2.18-5.45,14.2-10.29,28.54-14.81,42.94-.16,.52-.22,1.06-.3,1.59-.02,.09,.05,.26,.14,.29,.21,.07,.52,.18,.69,.11,5.51-2.63,10.73-5.8,16.21-8.49,.24-.07,.88-.06,.89,.32-.17,.74M -.31,1.48-.55,2.21-3.72,10.88-7.04,21.88-10.27,32.89-.5,1.67-.93,3.36-1.36,5.04-.05,.19,.03,.48,.2,.58,.14,.1,.55,.07,.72-.03,4.74-2.8,9.29-5.89,13.95-8.81,.52-.33,1.03-.71,1.92-.58-.41,4.69-2.91,9.14-3.86,13.78-1.5,5.9-3.02,11.81-4.71,17.68-.36,1.26-.64,2.53-.91,3.8-.03,.14,.19,.33,.34,.46,.8,.05,1.84-1.03,2.57-1.42,3.6-2.61,7.17-5.23,10.76-7.84,.43-.23,1.91-1.5,2.17-.72-1.81,7.99-4.29,15.97-6.04,24.02-.53,2.22-.98,4.45-1.46,6.67-.02,.09,.09,.28,.15,.29,.93,.12,1.54-.7,2.23-1.17,3.5-2.84,6.98-5.69,10.49-8.52,.55-.M 45,1.19-.84,1.8-1.25,.06-.03,.32,.03,.35,.08,.09,.19,.2,.42,.16,.61-.59,2.42-1.27,4.84-1.8,7.28-1.24,6.36-3.05,12.7-3.87,19.1,.24,1.75,10.69-8.84,12.07-9.71,.62-.41,1.3-1.41,2.04-1.42,.17,.12,.44,.3,.42,.44-.14,.96-.28,1.93-.53,2.87-1.63,6.12-2.61,12.28-3.6,18.5-.09,.49-.3,1.79,.4,1.68,.24-.08,.54-.11,.69-.25,4-3.78,7.86-7.7,11.96-11.37,.15-.09,.9-.19,.86,.24-.47,2.78-.91,5.55-1.45,8.31-.75,3.83-1.34,7.68-1.83,11.53-.05,.35,.39,.66,.69,.5,4.65-3.72,8.27-8.67,13.01-12.25,.08-.05,.37-.02,.38,.01,.08,.3,.21,.62,.17,.9M 2-.63,4.5-1.29,8.99-1.93,13.48-.31,2.26-.94,5.32,1.99,2.1,2.94-2.94,5.88-5.9,8.83-8.83,.76-.75,1.57-1.47,2.4-2.18,.13-.1,.47-.07,.72-.06,.48,3.48-.89,7.8-1.13,11.46-.14,1.17-.09,2.36-.12,3.54,0,.25,.17,.4,.5,.41,1.08-.34,1.86-1.54,2.74-2.25,4.87-4.85,9.69-9.94,15.18-14.24,.14-.07,.56-.02,.65,.13,.07,.21,.15,.43,.1,.63-.8,3.95-.67,7.95-1.22,11.91-.09,.41,.13,.8,.29,1.17,.83,.38,1.97-1.24,2.65-1.73,4.57-4.24,9.15-8.48,13.73-12.71,.9-.61,1.79-2.1,2.97-1.87,.06,.01,.13,.18,.13,.27-.17,3.66-.6,7.3-.89,10.95-.08,.43,.16,M 1.15,.58,1.04,.23-.07,.52-.1,.68-.23,5.94-5,11.84-10.06,17.91-14.92,.36-.29,.85-.49,1.29-.71,.09-.04,.36,.01,.38,.05,.39,3.23-.66,6.62-.79,9.91-.22,3.25,2.6-.1,3.74-.78,5.12-4.28,10.38-8.46,15.93-12.39,.79-.52,1.41-1.19,2.48-1.01-.3,3.35-.8,6.64-.69,9.99,.37,1.45,1.85,.04,2.59-.48,6.36-4.78,13.07-9.46,19.91-13.67,.32-.18,.89,.03,.91,.32,.16,2.68-.28,5.37-.35,8.06-.36,1.49,.73,1.92,1.86,.96,7.15-4.28,14.01-8.79,21.42-12.7,.68-.22,1.75-1.21,2.36-.45,.29,2.87-.27,5.8-.29,8.68-.03,.61,.73,.88,1.42,.52,8.65-4.6,17.35-9.M 23,26.55-12.92,.55-.21,1.16,.07,1.14,.52-.09,1.61-.2,3.23-.29,4.84,.18,1.02-1.03,4.71,.85,4.15,9.83-3.75,19.44-7.91,29.54-11.23,1.11-.37,2.23-.75,3.35-1.12,.56-.19,1.13,0,1.29,.42,.98,2.82,2.14,5.55,3.33,8.3,.32,.74,.92,.93,1.92,.65,12.45-3.74,24.92-7.49,37.71-10.25,.8,2.24,1.6,4.49,2.38,6.74,1.52,4.36,1.99,3.57-3.41,4.86-10.31,2.48-20.56,5.08-30.6,8.18-2.74,.84-2.76,.83-1.51,2.95,1.2,2.04,2.44,4.07,3.67,6.1,.55,1.31,1.96,.76,3.01,.46,10.92-3.21,21.95-5.88,33.13-8.17,.53-.13,1.38-.33,1.45-.94-.92-3.26-3.03-6.14-3.9M 9-9.4,8.94-2.8,18.56-3.74,27.84-5.47Z"/><path class="cls-2" d="M918.48,445.2c-.05,.01-.09,.02-.14,.03,0-.03-.02-.06-.02-.09,.05-.01,.09,0,.14,0,.01,.02,.01,.04,.02,.06Z"/><path class="cls-2" d="M637.75,1092.25c.55,.13,1.06,.02,1.54-.19,3.79-1.63,7.59-3.24,11.37-4.9,5.67-2.48,11.16-5.2,16.67-7.9,.27-.09,1.23-.46,1.3,.02-2.6,5.81-6.35,11.13-9.39,16.75-.28,.36,.26,.65,.6,.55,9.34-3.97,18.17-9.61,27.54-13.23,.11,.17,.3,.41,.23,.55-.5,.99-1.03,1.98-1.61,2.95-2.77,4.66-5.56,9.32-8.34,13.98-.34,.58-.61,1.18-.89,1.78-.03,.M 06,.1,.19,.2,.26,.33,.19,.75-.06,1.06-.17,4-1.99,8.03-3.93,11.98-5.99,4.06-2.12,8.02-4.35,12.04-6.52,.99-.52,2.52-1.12,1.5,.73-3.72,6.73-7.96,13.18-11.99,19.73-.12,.29-.33,1.01,.12,1.07,8.46-3.75,16.48-8.54,24.72-12.77,.59-.31,1.22-.43,1.86-.06l-.11-.03c-4.74,8.2-10.09,16.11-14.94,24.3-.13,.36,.58,.47,.74,.42,7.64-3.79,15.17-7.74,22.62-11.84,1.56-.74,3.57-2.02,1.88,.86-4.72,7.97-9.91,15.75-15.07,23.55-2.57,3.81-2.51,4.16,1.72,2.01,7.33-3.42,14.51-7.73,21.93-10.69,.49,.74-.37,1.39-.67,2.05-6.44,10.42-13.69,20.45-20.M 45,30.76,0,.13,.37,.39,.53,.34,.75-.23,1.51-.43,2.22-.72,5-2.1,9.99-4.22,14.99-6.33,.58-.18,3.46-1.77,3.03-.31-4.38,6.82-9.11,13.42-13.7,20.11-3.28,4.7-6.67,9.34-10,14.01-.51,1.09-2.3,2.23-1.4,3.46,0-.23-.06-.32-.29-.36l.28,.3c6.75-2.43,13.49-4.86,20.25-7.27,.16-.06,.47,.11,.68,.21,.06,.03,.06,.2,.02,.28-.67,1.56-1.82,2.88-2.74,4.31-8.85,12.94-18.58,25.41-27.86,38.19,.13,.94,2.14-.03,2.78-.07,6.35-1.76,12.62-3.81,19.02-5.38,.88,.17,.22,1.08-.06,1.56-2.84,3.91-5.69,7.82-8.55,11.72-8.45,11.52-17.24,22.87-26.3,34.09-.M 5,.62-1.16,1.2-1.16,2.01,.64,.35,1.32,.23,1.96,.1,2.35-.47,4.69-.97,7.04-1.44,4.3-.88,8.61-1.74,12.92-2.61,.46-.15,1.14-.21,1.49,.07,.11,.14,.05,.43-.07,.6-.58,.85-1.17,1.7-1.81,2.52-6.41,8.23-12.79,16.47-19.24,24.67-7.43,9.62-15.43,18.91-23.08,28.44-.08,.28,0,.76,.43,.7,2.4-.23,4.81-.45,7.21-.71,5.21-.52,10.4-1.27,15.61-1.69,1.32-.21,2.02,.37,.95,1.47-17.51,21.6-34.69,43.52-53.74,63.85-8,.28-16.1,.05-24.12,.12-2.28-.09-3.49,.01-1.31-2.21,10.46-11.17,20.76-22.52,30.89-33.97,6.68-7.56,13.25-15.2,19.85-22.8,.86-1.21,M 2.31-2.13,2.45-3.67-7.67,.36-15.25,1.58-22.9,2.25-.49,0-2.21,.27-1.94-.48,15.33-17.94,31.61-35.31,45.79-54.05-.45-.06-.83-.19-1.15-.13-3.53,.67-7.06,1.39-10.59,2.07-3.92,.75-7.85,1.48-11.79,2.19-.11,.02-.47-.3-.43-.39,11.45-14.73,24.32-28.66,35.52-43.52,1.35-1.7,4.33-4.74-.07-3.42-6.12,1.66-12.23,3.34-18.34,5.01-.62,.17-1.26,.43-1.85,.03,10.25-13.85,22.06-26.87,31.81-41.15-.31-.82-2.12,.2-2.78,.29-5.32,1.81-10.64,3.65-15.96,5.46-.86,.29-1.76,.5-2.66,.73-.08,.02-.24-.1-.32-.18-.29-.35,.42-1.05,.61-1.4,7.54-9.57,14.8M 5-19.24,22.02-28.99,1.3-1.76,2.5-3.56,3.73-5.35,.28-.33-.21-.71-.57-.58-7.77,3.17-15.41,6.63-23.13,9.91-1.74,.65-3.8,1.55-1.77-1.07,6.97-9.71,14.42-19.11,20.97-29.1,.3-1.51-3.24,.82-3.84,.9-7.39,3.31-14.64,6.93-22.12,10.05-1.46,.06-.44-.86-.05-1.55,5.68-8.07,11.36-16.14,17.04-24.21,.26-.37,.49-.77,.64-1.17,.05-.14-.17-.35-.31-.6-8.91,3.96-17.46,8.67-26.49,12.35-.14,.02-.47-.24-.4-.41,.55-.86,1.08-1.73,1.68-2.56,4.78-6.87,9.8-13.56,13.86-20.79-.34-.81-1.76,.16-2.33,.34-7.45,3.89-15.25,7.31-22.94,10.86-2.39,1.1-3.42,M 1.29-1.52-1.42,3.84-5.81,7.69-11.61,11.52-17.42,.3-.45,.79-.88,.59-1.46-.03-.09-.22-.23-.27-.21-.73,.26-1.48,.49-2.17,.82-8.61,4.24-17.49,7.98-26.01,12.35l.12-.05c-1.22-1.12,.78-2.65,1.29-3.75,3.03-4.3,5.86-8.67,8.57-13.1,.41-.67,.77-1.36,1.09-2.06,.07-.15-.14-.38-.24-.61-10.8,4.64-21.64,9.4-32.75,13.66l.02,.08c-.94-1.12,.67-2.21,1.17-3.19,2.93-4.11,5.88-8.22,8.81-12.34,.46-.65,.9-1.32,1.29-2,.08-.14-.08-.37-.17-.55-11.55,3.8-22.96,8.96-34.66,12.88-1.55,.34-5.42,2.48-3.03-.79,2.88-4.26,5.77-8.51,8.65-12.78,.25-.37,M .41-.79,.58-1.19,.03-.06-.09-.18-.17-.24-.52-.37-1.27,.14-1.83,.24-9.88,3.69-20.05,6.83-30.1,10.22-2.72,.92-5.44,1.88-8.34,2.41-.85-.2-.2-1.08,.08-1.57,2.88-4.25,5.92-8.42,8.59-12.8,.08-.13,0-.43-.14-.53-1.28-.41-2.85,.57-4.16,.79-12.21,3.68-24.51,7.17-36.97,10.3-.96,.17-1.83,.64-2.78,.07,2.48-4.67,5.95-8.83,8.29-13.57-.26-.78-1.81-.17-2.41-.11-14.79,3.56-29.71,7.15-44.81,9.61-1.44-.14-.25-1.4,.05-2.08,2.06-3.51,4.26-6.95,6.26-10.49,.13-.29,.25-.71,.08-.92-.74-.67-2.12-.08-3.05-.03-10.74,2.07-21.61,3.58-32.48,5.08-M 5.45,.66-10.88,1.64-16.37,1.91-1.48-.24,.14-1.98,.37-2.75,1.68-3.05,3.4-6.09,5.08-9.15,.21-.5,.73-1.39,.03-1.69-3.72-.26-7.48,.57-11.21,.75-8.42,.87-16.9,1.28-25.34,1.87-6.44,.54-12.92,.5-19.36,.91-1.08,.12-3.39,.16-2.61-1.31,1.81-4.04,4.2-7.88,5.63-12.07,.07-.26-.33-.69-.67-.7-1.07-.04-2.14-.09-3.21-.09-21.4,.13-42.84-.14-64.19-1.77l.13,.12c1.82-4.49,3.64-8.98,5.46-13.48,.18-.48,.29-1.26-.37-1.4-6.49-.91-13.06-1.28-19.58-1.97-19.82-1.95-39.52-4.81-59.2-7.82l.09,.1c1.68-5.4,2.84-10.98,4.89-16.25l-.13,.07c26.58,4.42M ,53.27,8.92,80.17,10.99l-.15-.14c.13,.66-.12,1.27-.35,1.9-1.45,4.22-3.32,8.36-4.42,12.67,6.76,1.54,14,1.03,20.93,1.74,14.11,.77,28.26,1.12,42.4,1.17,1.21,.25,5.47-.79,4.53,1.44-1.38,3.15-2.83,6.27-4.2,9.42-1.46,2.98-1.32,2.98,2.53,2.95,8.36-.07,16.69-.49,25.02-.96,9.14-.43,18.26-1.19,27.35-2.02,4.51-.66,3.94,.04,2.55,2.84-1.52,3.11-3.26,6.13-4.76,9.25-.78,1.55,1.86,1.04,2.79,.99,4-.47,8-.9,11.98-1.43,12.33-1.64,24.62-3.54,36.88-5.58,1.7-.04,.6,1.46,.23,2.25-1.88,3.56-4.07,6.99-5.76,10.65-.13,.29,.31,.6,.75,.52,4.32M -.81,8.66-1.56,12.95-2.47,11.03-2.39,22.07-4.69,32.99-7.5,.22-.05,.5,.04,.74,.09,.66,.23-.13,1.3-.35,1.74-1.96,3.83-4.8,7.55-6.29,11.48,1.03,.62,2.27-.23,3.37-.34,10.15-2.54,20.13-5.46,30.09-8.44,3.14-.94,6.3-1.87,9.46-2.78,.18-.05,.47,.12,.69,.22,.17,.34-.17,.85-.31,1.2-2.24,3.8-4.57,7.56-6.85,11.34-.36,.6-.61,1.2-.12,1.81,.04-.22,.03-.34-.19-.43l.2,.38c13.27-4.37,26.52-8.93,39.61-13.72,.2,.23,.5,.42,.46,.54-.17,.51-.37,1.03-.67,1.5-2.26,3.67-4.55,7.33-6.82,10.99-.36,.57-.66,1.17-.97,1.76-.03,.06,.05,.19,.12,.26,.M 46,.42,1.29-.1,1.83-.19,6.17-2.15,12.22-4.51,18.23-6.94,5.53-2.23,11.04-4.49,16.57-6.72,.46-.19,.99-.38,1.53,.11-2.81,4.89-6.01,9.6-9,14.39-.31,.48-.64,.95-.4,1.52-.4-.21-.68,.27-.28,.39,.29-.01,.39-.15,.3-.38Z"/><path class="cls-2" d="M1250.03,891.19c-.37,.86-.06,1.71,.15,2.55,1.39,5.48,2.82,10.96,4.22,16.44,.59,2.32,1.16,4.64,1.7,6.97,.04,.15-.18,.48-.27,.48-1.1-.12-1.63-1.38-2.42-2.04-10.13-10.76-20.2-21.56-30.39-32.25-1.33-1.22-4.93-5.82-3.48-.87,2.27,7.97,4.57,15.94,6.84,23.92,.09,.59,.48,1.38-.28,1.67-9.65-8.M 67-18.54-18.78-27.93-27.93-.97-.83-4.88-5.34-3.75-1.38,2.7,9.22,5.78,18.34,8.25,27.63,.02,.08-.12,.27-.18,.27-1.15,.03-1.72-1.22-2.55-1.83-8.66-8.03-16.8-16.72-25.74-24.39-.04-.02-.3,.09-.29,.13,.27,3.56,1.97,6.89,2.84,10.35,1.89,6.97,4.5,13.78,5.93,20.84-1.73-.53-2.55-1.87-3.87-2.95-6.4-5.83-12.79-11.66-19.21-17.48-1.73-1.32-3.21-2.97-2.27,.64,2.79,9.76,5.6,19.51,8.39,29.26,.04,.32,.16,.99-.22,1.14-.89-.03-1.9-1.33-2.67-1.83-5.87-5.05-11.73-10.1-17.61-15.15-1.07-.73-3.22-3.01-2.53-.02,3.08,10.59,5.7,21.25,8.43,31.M 9,.04,.38,.21,.94-.09,1.23-1.07,.1-1.8-.92-2.5-1.45-5.32-4.28-10.61-8.57-15.93-12.85-.55-.32-2.77-2.44-2.87-1.12,2.5,10.23,4.79,20.52,7.07,30.8,.4,1.8,.71,3.61,1.05,5.42,.02,.09-.08,.26-.17,.28-.67,.24-1.14-.21-1.63-.58-5.86-4.45-11.9-8.69-17.66-13.27-.02,.08-.03,.14-.05,.21l.1-.23c-.47,.58-.49,1.22-.37,1.87,.4,2.13,.81,4.25,1.22,6.38,1.73,9.15,3.49,18.29,5.07,27.47,.38,3.6,1.69,6.25-2.65,2.89-4.42-2.99-8.84-5.98-13.28-8.96-.61-.35-1.67-1.28-2.27-.67,.02,5.26,1.48,10.47,2.03,15.7,1.11,8.88,2.41,17.75,3.12,26.67,.01M ,.13-.3,.29-.49,.41-.35,.11-.78-.17-1.08-.31-4.77-3.01-9.62-5.89-14.44-8.83-.61-.35-1.81-1.19-2.21-.22,.75,13.65,2.23,27.27,2.62,40.95,.09,1.83,.18,3.65,.26,5.48,.01,.27-.58,.55-.89,.42-5.5-2.65-10.89-5.57-16.37-8.27-.95-.31-1.04,.62-1.06,1.29-.04,16.47,.35,32.96-.4,49.41-.13,2.99-1.45,1.8-3.45,1.07-4.03-1.74-8.04-3.5-12.07-5.24-.93-.2-2.42-1.41-3.18-.47-.92,13.97-2.01,27.94-3.4,41.88-.23,4.2-.81,8.37-1.38,12.54-.53,1.6,.43,5.9-2.18,4.87-5.57-1.9-11.14-3.89-16.81-5.48-.5-.12-1.18,.18-1.25,.56-.34,2.13-.66,4.27-1.02M ,6.4-2.6,16.78-5.67,33.51-9.01,50.17-.69,3.4-1.48,6.78-2.21,10.18-.11,.52-.25,1.07,.26,1.53,0,0,.06-.02,.06-.02-6.98-.58-13.76-3.02-20.65-4.31-1.22-.31-.87-1.35-.73-2.23,1.43-6.14,2.92-12.27,4.3-18.41,3.87-16.36,6.59-32.97,9.99-49.4,.61-.69,1.81-.04,2.57,.07,4.16,1.24,8.31,2.51,12.47,3.77,4,1.21,4.13,1.62,4.51-2.1,2.58-17.73,4.4-35.56,5.85-53.42,.12-1.28,.4-2.55,.62-3.82,.05-.26,.29-.38,.61-.31,5.23,1.51,10.16,3.96,15.28,5.8,1.57,.59,1.95,.44,2.06-.83,1.23-17.19,1.18-34.46,1.43-51.67,.76-1.23,2.76,.68,3.77,.83,4.07M ,1.91,8.12,3.83,12.18,5.75,.48,.23,.97,.34,1.59-.03-.06-15.7-1.64-31.37-2.37-47.04-.02-.3,.56-.55,.88-.39,5.23,2.59,10.26,5.56,15.41,8.3,.52,.2,1.32,.28,1.25-.62-1.3-11.15-2.28-22.35-4.01-33.44,.04-1.39-2.15-9.13-.49-8.92,5.38,2.68,10.32,6.21,15.47,9.29,.42,.28,.93,.62,1.42,.35,.46-.25,.33-.77,.28-1.19-.11-.86-.19-1.72-.33-2.57-1.49-9.19-3.2-18.35-5-27.48-.35-1.81-.82-3.61-1.07-5.42-.14-1-.86-2.04,.01-3.06,1.27,.16,2.03,.96,2.92,1.56,4.23,2.84,8.41,5.73,12.61,8.6,.83,.43,1.59,1.43,2.61,1.17-1.43-10.43-4.8-20.97-6.9M 7-31.42-.4-1.69-.83-3.38-1.2-5.08-.03-.13,.23-.32,.4-.44,.76-.03,1.6,.85,2.27,1.21,4.88,3.56,9.74,7.13,14.61,10.69,.72,.38,1.4,1.28,2.24,1.23,.1-.03,.24-.13,.24-.2-.02-.64,.03-1.29-.13-1.9-1.13-4.32-2.27-8.64-3.46-12.95-1.58-6.42-4.01-12.75-5.18-19.22,.16-.99,2.27,.92,2.72,1.14,6.11,4.69,12.02,9.64,18.23,14.19,.75,.34,.61-.71,.48-1.14-2.46-8.16-4.94-16.32-7.37-24.49-.68-2.3-1.67-4.54-2.01-6.9-.01-.09,.1-.22,.19-.27,.09-.05,.28-.06,.36-.02,.72,.47,1.48,.91,2.12,1.45,6.15,5.13,12.29,10.28,18.43,15.42,.65,.54,1.31,1.0M 8,1.99,1.6,.06,.05,.28,.02,.39-.02,.1-.05,.23-.17,.21-.25-.14-.74-.25-1.49-.48-2.22-2.76-8.54-5.55-17.09-8.33-25.63-.24-1.17-1.14-2.31-.77-3.48,1.34,.38,2.19,1.48,3.23,2.32,6.68,5.92,13.36,11.84,20.04,17.76,1.25,1.09,3.92,3.8,2.7,.04-2.99-9.18-6.24-18.38-9.09-27.59-.03-1.21,2.07,.9,2.34,1.07,5.8,5.39,11.6,10.78,17.38,16.18,3.15,2.95,6.26,5.92,9.4,8.87,.17,.12,.88,.28,.91-.14-2.67-9.25-5.9-18.34-8.8-27.52-.72-2.43,1.26-.38,2.05,.3,10.5,9.83,20.47,20.04,30.67,30.04,.26,.24,.77-.12,.79-.32-2.17-8.56-5.17-16.93-7.63-25M .42-.13-.41-.16-.84-.22-1.26,0-.07,.1-.2,.17-.21,12.48,10.89,23.59,23.86,35.21,35.69,.51,.34,2.73,3.34,3.14,2.3-1.32-7.75-4.16-15.34-6.02-23.03-.14-.53-.31-1.05-.42-1.58-.08-.41-.4-.99,.1-1.21,.64-.29,.86,.38,1.14,.68,14.45,14.93,28.08,30.59,42.33,45.68,.24,.14,.88,.16,.76-.31-1.63-7.97-3.37-15.92-5.17-23.86-.02-.09,.06-.28,.12-.29,.22-.02,.56-.05,.67,.05,.77,.74,1.54,1.49,2.24,2.27,6.74,7.54,13.52,15.04,20.18,22.63,8.97,10.23,17.81,20.53,26.73,30.79,.28,.32,.93,.55,1.03,.38,.1-.17,.24-.37,.22-.55-.91-6.85-1.9-13.7M -2.82-20.55-.3-2.98,1.51-.55,2.4,.37,18.22,21.16,36.13,42.55,53.85,64.1,.7,1,1.88,1.88,1.85,3.16-.02,6.57-.04,13.14-.09,19.71,0,.13-.32,.28-.51,.38-.64-.17-1.05-.95-1.52-1.4-16.37-20.18-32.83-40.23-49.74-60.09-.76-.66-1.52-2.3-2.63-2.22-.53,.37-.09,1.25-.09,1.79,.87,6.75,1.75,13.5,2.61,20.24,.02,.19-.11,.39-.2,.58-.08,.16-.73-.1-1.01-.41-2.83-3.27-5.57-6.61-8.38-9.9-11.87-14-23.85-27.93-36.13-41.7-.77-.65-1.29-1.94-2.42-1.89-.31,.57,.11,1.82,.16,2.53,1.38,7.35,3.32,14.61,4.39,22-1.2,0-1.61-.99-2.37-1.7-9.42-10.51-1M 8.81-21.02-28.25-31.52-3.3-3.67-6.71-7.29-10.07-10.92-.31-.33-.64-.7-1.29-.6,.05-.26-.01-.3-.19-.13l.27,.07Z"/><path class="cls-2" d="M322.27,493.7c.31-.51,.23-1.05,.13-1.58-.38-2.02-.73-4.05-1.16-6.07-1.48-7.01-2.77-14.04-3.91-21.09-.52-3.31-1.34-6.58-1.65-9.93-.13-1.33,1.01-1.06,1.61-.46,5.49,3.64,10.76,7.64,16.48,10.9,.1,.05,.58-.17,.58-.26,0-.96,.02-1.94-.15-2.89-.98-5.55-1.64-11.12-2.33-16.7-.78-7.64-2.63-15.53-2.52-23.1,1.03-.28,1.85,.66,2.72,1.07,4.29,2.61,8.58,5.22,12.87,7.83,.7,.32,1.61,1.21,2.36,.63-.32-1M 4.93-2.48-30.1-2.61-45.14-.17-2.76,1.44-1.65,3.02-.8,4.81,2.32,9.41,5.17,14.36,7.18,1.04-.03,.67-1.49,.8-2.2,0-16.38-.37-32.76,.49-49.12,.02-2.38,1.9-1.08,3.25-.62,4.15,1.79,8.28,3.61,12.43,5.39,.78,.19,2.22,1.14,2.85,.41,1.15-14.49,2.08-29.04,3.58-43.52,.72-5.22,.85-10.61,2.03-15.72,.88-.77,2.31,.42,3.3,.51,5.14,1.51,10.13,3.74,15.37,4.83,.64,.04,.9-.71,.97-1.22,.76-4.7,1.49-9.4,2.27-14.1,2.17-13.81,4.75-27.53,7.51-41.23,.7-3.94,1.95-7.8,2.35-11.79,.01-.16-.27-.34-.42-.51l-.06,.02c6.36,.36,12.47,2.63,18.71,3.81,3.M 38,.8,3.33,.35,2.69,3.21-4.61,19.32-8.87,38.72-12.42,58.26-.65,2.96-.75,6.04-1.69,8.93-.54,.84-1.75,.18-2.52,.06-4.17-1.23-8.33-2.48-12.5-3.71-1.19-.13-3.52-1.75-4.2-.25-1.28,7.33-1.93,14.78-2.94,22.16-1.81,12.4-2.36,24.93-3.9,37.34-.04,.24-.68,.5-.97,.4-5.42-1.84-10.61-4.26-16.01-6.15-1.04-.17-1,1.01-1.07,1.72-.24,4.74-.5,9.47-.69,14.21-.36,11.31-.77,22.62-.58,33.93,.03,3-.03,3.32-.58,3.34-1.46,.05-2.45-.78-3.58-1.29-3.75-1.7-7.43-3.49-11.15-5.24-.67-.19-1.94-1.13-2.32-.14,0,8.08,.44,16.16,.97,24.21,.47,7.42,.94,1M 4.85,1.41,22.27-.12,1.89-2.46-.18-3.3-.41-4.5-2.33-8.81-5.04-13.42-7.14-.12-.04-.52,.16-.58,.3-.13,.29-.17,.63-.14,.94,1.24,11.06,2.25,22.12,4.01,33.12,.38,2.86,1.06,5.74,.97,8.62-.67,.21-1.14,.02-1.58-.25-4.18-2.55-8.35-5.11-12.52-7.66-1.08-.49-2.09-1.72-3.32-1.58-.18,.07-.36,.32-.35,.49,.11,2.38,.57,4.72,.97,7.06,1.19,6.5,2.4,12.99,3.6,19.49,.75,4.05,1.49,8.09,2.2,12.14,.02,.13-.27,.31-.45,.44-5.27-2.49-10.72-7.18-15.84-10.38-.72-.33-1.78-1.66-2.4-.61,1.28,6.45,2.88,12.93,4.32,19.39,1.3,5.61,2.69,11.21,4.02,16.81M ,.03,.13-.21,.32-.36,.45-1.2-.06-2.16-1.27-3.18-1.86-4.77-3.5-9.53-7-14.29-10.49-.51-.25-1.04-.94-1.63-.82-.68,.37-.35,1.13-.26,1.74,.88,3.37,1.75,6.75,2.69,10.11,1.96,7.04,3.96,14.07,5.94,21.11,.15,.52,.29,1.05-.04,1.64-1.48-.29-2.5-1.51-3.7-2.33-5.19-4.08-10.38-8.16-15.57-12.24-.57-.44-1.05-1-2.1-1.06,2.55,10.48,6.12,20.75,9.27,31.09,.99,3.74-1.7,.74-3.01-.15-6.24-5.22-12.46-10.45-18.7-15.67-.36-.3-.63-.71-1.24-.72-.1,0-.29,.09-.29,.14,.02,.53-.04,1.07,.11,1.58,1.13,3.66,2.28,7.31,3.47,10.96,1.91,5.83,3.86,11.65,M 5.79,17.48,.14,.41,.26,.82-.08,1.26-1.2-.37-2.03-1.33-2.96-2.1-6.42-5.67-12.83-11.35-19.24-17.03-1.25-.89-2.2-2.45-3.72-2.84-.22-.03-.38,.44-.26,.81,.36,1.15,.72,2.3,1.1,3.44,2.66,8.01,5.32,16.02,7.99,24.03,.17,.52,.44,1.02,.17,1.56-.59,.01-.99-.26-1.35-.58-1.79-1.61-3.61-3.2-5.36-4.84-6.02-5.66-12.01-11.35-18.03-17.02-1.31-1.23-2.65-2.44-4-3.64-.12-.11-.45-.08-.69-.07-.36,.28,0,1.13,.08,1.55,2.74,8.44,5.49,16.88,8.24,25.31,.11,.58,.62,1.31-.09,1.67-.68-.07-1.21-.86-1.75-1.25-10.61-9.87-20.55-20.32-30.99-30.22-.9-.M 4-.42,.99-.34,1.43,2.43,7.95,4.88,15.89,7.31,23.84,.09,.53,.42,1.42,.14,1.85-1.15,0-1.77-1.2-2.59-1.84-10.78-10.76-21.33-21.68-31.71-32.69-1.4-1.28-2.24-2.97-4.13-3.65,1.84,8.77,4.81,17.28,6.92,26-.15,1.42-2.38-1.36-2.82-1.68-13.86-14.44-27.13-29.27-40.6-43.92-.12-.12-.47-.11-.72-.12-.04,0-.14,.19-.14,.28,.97,8.11,3.92,15.88,4.84,24.01-1.91-.53-2.73-2.34-4.08-3.6-9.9-11.16-19.82-22.3-29.68-33.49-5.04-5.72-9.95-11.53-14.92-17.29-.55-.51-1.03-1.56-1.91-1.44-.34,.19-.32,.8-.26,1.16,.66,4.71,1.33,9.42,1.99,14.13,.31,2.M 25,.62,4.5,.89,6.75,.02,.14-.2,.42-.34,.43-.23,.03-.59-.05-.72-.18-.73-.77-1.43-1.56-2.12-2.36-6.54-7.64-13.16-15.25-19.61-22.95-11.25-13.42-22.4-26.9-33.59-40.35-.93-1.23-2.36-2.39-2.31-4.03,0-6.36,0-12.71,0-19.07,0-.44,.37-.82,.62-.66,3.21,2.78,5.49,6.67,8.36,9.85,14.33,17.6,28.83,35.12,43.62,52.48,.6,.71,1.29,1.36,1.96,2.03,.12,.09,.59-.03,.62-.21-.43-5.7-1.28-11.36-2.01-17.02,0-1.12-1.77-7.48,.89-4.71,14.36,17.01,28.74,33.88,43.59,50.55,.96,.99,1.57,2.17,2.97,2.66-.8-7.27-2.99-14.46-4.28-21.71-.13-1.03-.61-2.15M -.07-3.12,.14-.26,.4-.15,.91,.42,4.62,5.17,9.2,10.36,13.86,15.51,8.76,9.53,17.26,19.34,26.23,28.69,.28,.27,.72-.08,.76-.28-.58-2.43-1.17-4.86-1.79-7.29-1.45-5.7-2.92-11.39-4.37-17.09-.12-.45-.48-1.66,.31-1.64,11.76,11.72,22.88,24.26,34.54,36.17,.47,.49,.83,1.13,1.88,1.19-2.28-9.55-5.5-18.83-7.85-28.42,1.45,.23,1.86,1.2,2.84,2.05,8.34,8.46,16.67,16.93,25.02,25.38,1.33,1.35,2.78,2.63,4.19,3.93,.06,.06,.27,.05,.38,.02,.1-.03,.25-.15,.24-.21-.18-.84-.33-1.69-.58-2.52-2.5-8.27-5.02-16.53-7.52-24.79-.16-.52-.21-1.06-.29-M 1.6-.01-.09,.07-.26,.16-.28,1.03-.31,1.77,1.13,2.54,1.66,7.68,7.37,15.35,14.74,23.03,22.1,.92,.67,1.64,2.01,2.88,2.02,.05,0,.18-.19,.16-.28-.81-2.72-1.64-5.44-2.44-8.16-2.18-7.33-4.35-14.66-6.5-22-.06-.19,.06-.41,.1-.61,.92,.09,1.5,.65,2.09,1.27,3.88,3.58,7.74,7.18,11.66,10.74,3.47,3.16,7,6.27,10.51,9.39,.36,.25,.84,.73,1.32,.58,.1-.05,.2-.19,.18-.28-.51-1.89-1.04-3.78-1.58-5.66-2.37-8.93-5.41-17.8-7.44-26.77,.31-.9,2.1,1.11,2.59,1.38,5.88,5.05,11.74,10.1,17.62,15.15,1,.85,3.63,3.23,2.82,.14-3.07-10.7-5.82-21.45-8.M 5-32.23-.31-1.03,.76-.89,1.32-.41,2.65,2.15,5.25,4.34,7.91,6.48,3.52,2.83,7.07,5.62,10.62,8.42,.37,.2,1.36,.95,1.54,.26-1.4-7.36-3.45-14.59-5.07-21.9-.93-4.02-1.77-8.06-2.62-12.09-.07-.76-.37-1.96-.08-2.53,.25-.03,.59-.09,.74,0,.93,.62,1.82,1.28,2.7,1.94,4.34,3.23,8.67,6.47,13.02,9.69,.93,.54,1.76,1.6,2.93,1.5,0,.22,.05,.23,.14,.04l-.22,.04Z"/><path class="cls-2" d="M811.67,722.52l-.09-.09s.07,.03,.1,.04c0,.02-.01,.03-.01,.05Z"/><path class="cls-2" d="M853.94,712.51c-.34,.95-.71,1.87-1.3,2.72-.9,.04-1.35-.38-1.84-.M 74-2.48-1.83-4.94-3.66-7.43-5.48-.73-.43-1.45-1.14-2.37-.9-1.84,3.7-1.87,7.55-3.87,11.25-3.6-1.17-6.61-3.43-10.17-4.67-.44-.16-1.15,.15-1.25,.55-.4,1.58-.78,3.17-1.16,4.75-.71,2.11-.74,4.94-1.99,6.71-3.72-1.01-7.23-2.9-10.88-4.23,.87-4.01,1.72-8.03,2.57-12.04,.12-.58,.8-.81,1.55-.52,2.76,1.09,5.51,2.26,8.26,3.4,1.4,.55,1.9,.55,2.24-.74,.76-2.95,1.59-5.89,2.38-8.83,.17-.64,.32-1.27,1.11-1.81,3.7,1.33,7.02,3.68,10.72,4.95,.21,.03,.57-.11,.66-.25,.93-1.84,1.46-3.86,2.23-5.77,3.68,3.72,7.2,7.61,10.54,11.65Z"/><path claM ss="cls-2" d="M864.29,726.38c-.81,.04-.91,1.07-1.24,1.63-1.01,2.57-1.99,5.14-2.97,7.71-.2,.53-.43,1.03-1.1,1.43-3.36-2.33-6.14-5.42-9.39-7.93-.63-.52-1.32-.44-1.52,.17-1.15,3.61-2.28,7.31-3.41,10.9-.75,.09-1.19-.12-1.58-.44-1.9-1.53-3.79-3.06-5.72-4.57-.97-.53-2.71-2.75-3.68-1.32-.97,3.45-1.73,6.96-2.64,10.45-.15,.66-.43,1.53-1.32,1.24-2.86-1.42-5.64-2.98-8.59-4.23-.29-.12-.73-.02-1.12-.02-1.32,4.16-1.66,8.61-3.05,12.74-.09,.13-.47,.24-.67,.2-2.61-.75-5-2.12-7.53-3.08-2.1-1.01-2.48,.07-2.74,1.83-.62,3.19-1.23,6.38-M 1.86,9.57-.13,.63-.22,1.3-1.03,1.8-2.98-.79-5.84-2.15-8.84-2.95-.36-.1-.91,.1-.98,.36-.98,4-1.7,8.06-2.59,12.09-.15,1.05-.48,1.82-1.9,1.31-2.76-.76-5.46-1.94-8.29-2.36-.2,.26-.41,.43-.47,.62-1.08,3.88-1.74,7.84-2.65,11.76-.23,.64-.4,1.77-1.29,1.77-1.97,.12-8.87-3.41-9.61-1.23-1.03,4.54-2.69,9.04-3.36,13.6-3.57-.78-7.14-1.58-10.63-2.6,.01-.01,.01-.03,.02-.04,1.59-4.4,2.34-9.02,3.59-13.53,.48-1.66,7.42,.96,9.05,1.07,1.03,.23,1.63-.02,1.79-.77,.91-4.24,1.8-8.5,2.71-12.73,.61-1.51,7.75,1.23,9.41,1.4,.31,.08,.95-.16,1.0M 1-.38,1.38-4.33,1.5-9.06,2.87-13.33,.16-.15,.49-.34,.66-.3,2.93,.8,5.81,1.69,8.75,2.44,.87,.13,1.18-.67,1.33-1.32,.67-3.84,1.28-7.69,2.03-11.51,.1-.56,.87-.92,1.51-.72,2.89,.85,5.66,2.07,8.56,2.87,.32,.09,.8-.17,.86-.49,.84-4.15,1.37-8.36,2.55-12.42,.07-.24,.67-.45,.99-.35,2.58,.87,5.03,2.06,7.54,3.09,.81,.37,2.25,1.02,2.54-.24,.63-2.97,1.24-5.95,1.9-8.92,.39-.91,.28-3.16,1.68-2.89,3.03,1.36,6.01,2.83,8.98,4.33,.47,.22,1.17-.01,1.28-.42,.96-3.58,1.96-7.15,2.96-10.71,.4-.95,1.66-.26,2.22,.24,2.16,1.63,4.3,3.26,6.45,M 4.89,.84,.38,1.94,2,2.84,1.15,1.23-3.3,2.35-6.62,3.55-9.93,.27-.76,1.04-.86,1.82-.27,3.16,2.41,6.02,5.19,9.15,7.62,.4,.57,.79,1.14,1.17,1.72Z"/><path class="cls-2" d="M964.38,753.47c-3.1,.91-5.67,3.14-8.6,4.55-.75,.42-1.37,1.03-2.42,1.14-.75-.32-.98-.97-1.34-1.54-2.62-4.12-5.22-8.26-7.88-12.38-.85-1.32-1.53-2.74-2.9-3.82-2.12,.4-3.11,1.94-4.59,2.98-1.71,1.21-3.26,2.56-4.8,3.78-.78-.03-1.09-.34-1.37-.73-2.83-3.92-5.66-7.84-8.5-11.75-2.45-3.35-2.66-4.14-5.65-.56-2.48-5.52-5.17-10.91-8.08-16.15,3.59,4.12,6.94,8.45,10.M 7,12.42,.12,.1,.57,.13,.73,.03,2.82-1.92,5.32-4.26,8.03-6.34,.72-.58,1.31-.5,1.9,.26,3.55,4.57,7.03,9.13,10.36,13.86,.33,.46,.58,.97,1.27,1.26,.73,.13,1.16-.35,1.67-.65,2.84-1.64,5.64-3.3,8.47-4.96,.31-.18,.88-.1,1.07,.13,4.11,5.34,7.52,11.16,11.14,16.82,.33,.52,.81,1.03,.79,1.65Z"/><path class="cls-2" d="M964.38,753.47s.09,0,.14,0l-.15,.15s.01-.09,.01-.14Z"/><path class="cls-2" d="M1387.34,675.7c-.02-1.77-2.28-2.37-3.48-3.32-6.16-3.85-12.29-7.72-18.49-11.52-21.25-13.12-42.8-25.53-64.79-37.55-2.89-1.58-5.81-3.12-8.M 72-4.68-.55-.3-1.1-.63-1.84-.49-.29,2.48,.64,5.14,.81,7.67,.29,3.62,1.45,7.29,1.18,10.91-.59,.74-2.61-.89-3.35-1.16-10.69-6-21.5-11.88-32.42-17.62-15.02-7.79-30.24-15.54-45.74-22.55-.21-.06-.85,.06-.82,.41,1.07,4.78,2.5,9.47,3.78,14.2,.17,.86,.93,2.94-.74,2.4-22.5-10.82-44.93-21.61-68.3-30.64-.65,.72-.17,1.42,.06,2.21,1.32,3.27,2.68,6.55,4.01,9.82,.34,.98,2.1,4.16,.14,3.63-18.64-7.94-37.44-15.41-56.7-21.94-3.18-1.04-1.23,1.26-.59,2.72,1.76,3.39,3.62,6.72,5.34,10.12,.11,.25,.32,.67,.11,.88-.23,.09-.53,.23-.71,.17-4.M 56-1.59-9.12-3.18-13.67-4.8-11.08-3.93-22.41-7.37-33.8-10.67-.62-.18-1.28-.26-1.93-.36-.08,0-.3,.13-.3,.19,.03,.31,.01,.65,.18,.91,2.34,3.93,5.63,7.65,7.46,11.73-.22,.11-.51,.28-.69,.23-2.54-.7-5.07-1.43-7.59-2.18-10.22-3.03-20.55-5.83-31.03-8.26-1.15-.26-2.34-.42-3.52-.61-.1-.02-.27,.07-.34,.15-.29,.53,.63,1.22,.83,1.71,2.24,2.95,4.49,5.89,6.73,8.83,.27,.36,.44,.73,.25,1.14-.96,.2-1.83-.08-2.72-.3-11.04-2.77-22.26-5.36-33.55-7.09-.18,0-.74,.36-.53,.64,2.92,3.35,5.96,6.62,8.78,10.05,.06,.08,.08,.27,0,.31-.63,.49-1.M 51,.21-2.22,.11-8.45-1.85-17.11-2.93-25.7-4.23-1.12-.08-2.48-.34-3.55-.08-.29,.93,.92,1.49,1.41,2.17,2.38,2.34,4.81,4.63,7.16,7,.17,.24,.62,.54,.39,.85-.15,.14-.37,.35-.53,.34-3.07-.32-6.14-.62-9.2-1.02-5.7-.6-11.48-1.39-17.2-1.47-.25,.51,.04,.84,.41,1.17,2.78,2.5,5.55,4.99,8.32,7.49,.29,.37,1.1,.83,.99,1.3-.64,.72-1.72,.24-2.57,.28-6.18-.46-12.36-.79-18.56-.89-.64,0-1.46-.2-1.85,.31-.45,.6,.35,.95,.76,1.32,2.78,2.35,5.62,4.63,8.4,6.99,1.66,1.47,.71,1.73-.99,1.65-5.39-.3-10.77,0-16.16,.17-1.04,.17-2.45,0-1.12,1.34,M 3.09,2.55,6.21,5.08,9.32,7.63,.36,.29,.88,.56,.75,1.05-.15,.57-.83,.44-1.31,.47-5.14,.4-10.49,.47-15.56,1.33-.24,.58,.08,.91,.47,1.23,2.93,2.37,5.87,4.74,8.8,7.13,.47,.56,2.5,1.64,1.2,2.25-1.98,.31-3.96,.59-5.94,.92-2.5,.43-4.99,.88-7.49,1.33-.61,.11-.84,.61-.45,.96,3.92,3.42,7.96,6.73,11.9,10.12,.55,.46,1.23,.86,1.38,1.61-1.07,1.3-14.01,2.09-12.7,4.04,4.24,3.75,8.57,7.42,12.7,11.28,.22,.21,.23,.55,.37,.89-3.98,1.15-8.02,1.98-11.69,3.63,3.7,4.24,8.28,7.69,12.28,11.69,.42,.4,.89,.8,.74,1.41-3.74,1.01-7.58,2.96-11.36M ,3.44-3.99-3.59-8.11-7.14-12.16-10.7-.43-.38-.82-.85-1.69-.81-2.69,1.87-5.51,3.71-7.9,5.92-.4,.35-1.08,.9-1.65,.66-3.73-2.56-7.16-5.54-10.79-8.25-.76-.49-1.89-1.6-2.71-.64,3.83,3.99,7.49,8.12,11,12.4,.76-.82,1.62-1.58,2.43-2.37,.2-.19,.87-.17,1.12,.01,4.38,3.45,8.31,7.35,12.57,10.97,3.76-1.73,6.17-4.81,9.84-6.6,1.17,.39,1.68,1.19,2.36,1.84,6.85,6.57,9.23,9.06,11.06,11.54-3.01,2.12-6.03,4.26-9.06,6.39-.43,.3-1.05,.26-1.41-.1-3.64-3.75-7.3-7.46-11-11.16-.48-.48-.89-1.07-1.96-1.23-1.87,1.53-3.54,3.22-5.2,4.96,3.58,5.1M 7,6.94,10.51,10.05,16.01,2.35-2.6,5.07-5.02,8.09-7.22,.17-.12,.48-.1,.73-.15,.72,.17,1.01,.68,1.38,1.11,3.91,4.23,7.24,8.91,11.34,12.91,1.53-.06,2.18-1.15,3.23-1.77,2.32-1.28,4.44-2.86,6.82-4,1.15-.33,1.76,1.15,2.44,1.82,3.34,4.42,6.67,8.85,10,13.27,.34,.45,.57,.99,1.46,1.2,3.36-.24,6.87-.78,10.28-.84,.5,.02,1.52-.2,1.37-.82-3.45-5.66-7.84-10.76-11.65-16.2-.3-.42-.02-.9,.55-.97,3.72-.56,7.49-.52,11.24-.8,.17-.03,.43-.37,.37-.48-3.57-5.37-8.12-10.13-12.06-15.26-.52-.66-.1-1.22,.95-1.29,3.9-.23,7.8,.04,11.7-.24,.32,0M ,.6-.5,.42-.74-4.22-5.31-8.95-10.22-13.35-15.37l-.24-.15c-4.44,.02-8.84,.57-13.25,1-.56,.06-.82,.64-.5,1.02,3.45,3.86,7.01,7.64,10.5,11.47,.73,.99,2.05,1.74,1.88,3.11-4.01,.62-8.09,.65-11.88,1.65-.29,.69,.22,1.09,.58,1.52,3.46,4.1,6.95,8.2,10.41,12.31,.51,.61,1.19,1.18,1.23,2.06-2.43,.86-5.22,.92-7.77,1.41-1.33,.14-2.53,.77-4.09,.63-3.65-4.03-7.2-8.27-10.79-12.37-.7-.92-1.81-1.55-1.88-2.79,3.08-.98,6.17-1.59,9.28-2.37,.62-.15,1.29-.27,1.65-.95-3.78-4.45-8.03-8.6-12.06-12.85-.33-.34-.64-.69-.45-1.3,3.62-1.27,7.67-1.M 57,11.52-2.39,.34-.85-.57-1.37-1.04-1.97-3.87-3.86-7.92-7.58-11.7-11.53-.38-.78,.99-.98,1.53-1.09,3.71-.54,7.42-1.06,11.07-1.58,.42-.45,.25-.84-.11-1.18-3.64-3.47-7.29-6.92-10.94-10.39-.6-.57-1.22-1.14-1.78-1.74-.11-.12,.02-.39,.05-.67,4.67-1.02,9.53-1.15,14.25-1.47,.46-.49,.31-.88-.07-1.23-4.08-3.72-8.12-7.51-12.27-11.16-.46-.44-1.24-1.21-.18-1.51,4.57-.27,9.13-.53,13.7-.79,2.73-.06,2.93-.31,.84-2.21-2.61-2.32-5.26-4.62-7.88-6.94-.45-.39-.83-.84-1.17-1.3-.06-.07,.18-.38,.37-.48,6.27-.41,12.64,.05,18.92,.4,.09-.27,M .27-.52,.19-.63-.43-.55-.88-1.09-1.41-1.56-2.83-2.61-5.82-5.06-8.58-7.74-.13-.14-.17-.43-.09-.59,.08-.15,.38-.31,.59-.31,4.59-.03,9.13,.53,13.68,.92,2.77,.07,5.64,1.12,8.35,.8,.03-.19,.11-.47-.02-.59-2.8-2.76-5.63-5.49-8.44-8.24-.49-.48-1.54-.94-1.16-1.56,.52-.83,1.68-.29,2.53-.21,8.12,.64,16.08,2.68,24.17,3.39,.05-.82-.59-1.27-1.08-1.77-2.31-2.38-4.66-4.74-6.99-7.11-.33-.34-.66-.68-.97-1.03-.29-.34-.72-.72-.4-1.11,.13-.16,.77-.13,1.14-.07,8.01,1.42,16.04,2.82,23.91,4.7,1.81,.43,3.64,.78,5.48,1.13,.15,.03,.39-.18,.M 55-.31,.06-.06,.06-.24,0-.31-1.72-2.06-3.46-4.11-5.19-6.16-1.21-1.42-2.42-2.84-3.6-4.28-.1-.22,.13-.72,.49-.64,10.66,2.14,21.21,4.88,31.6,7.85,1.35,.21,2.96,1.25,4.23,.6-2.37-4.1-6.15-7.68-8.34-11.71,.18-.12,.46-.29,.64-.26,1.3,.27,2.6,.53,3.87,.88,12.09,3.35,24,7.05,35.78,11.06,.71,.19,1.48,.72,2.18,.23-1.43-3.62-4.43-6.89-6.46-10.33-.45-.66-.85-1.35-1.22-2.04-.08-.15-.03-.45,.1-.54,.16-.11,.52-.16,.72-.09,15.37,5,30.74,10.31,45.63,16.47,.83,.35,1.72,.61,2.58,.9,.15,.04,.5-.23,.46-.38-1.84-4.63-4.7-8.89-6.75-13.46M -.39-1.41,3.45,.5,4.01,.58,18.39,6.75,36.09,15.37,53.86,22.65,.29-.09,.33-.31,.24-.55-1.1-2.77-2.18-5.54-3.27-8.32-.8-2.05-1.61-4.1-2.39-6.16-.06-.16,.13-.39,.24-.57,.03-.04,.26-.05,.36-.02,23.13,9.44,44.83,21.32,67.05,32.32,.82,.27,.53-.81,.49-1.24-1.42-5.15-2.93-10.27-4.19-15.46,0-.19,.53-.64,.81-.5,5.48,2.43,10.69,5.42,16.03,8.13,21.39,11.01,42.09,23.26,62.83,35.25,.14,.05,.59-.11,.61-.21,.08-.42,.12-.86,.06-1.28-.65-4.49-1.34-8.98-1.99-13.47,.07-.94-1.09-4.35,.81-3.73,30.74,17.42,60.74,36.14,90.03,55.83,1.02,.4M 9,1.79,1.66,2.97,1.37,.19-.08,.38-.31,.38-.48,.11-6.57,.04-13.14,.04-19.71Zm-368.62-88.28s.08-.03,.12-.05c0,.19-.04,.21-.12,.05Z"/><path class="cls-2" d="M660.75,307.25s.01,0,.01-.01t.01,.02h-.05s.02,0,.03-.01Z"/><path class="cls-2" d="M892.54,367.68c-.05,.01-.11,.03-.16,.04,.03-.05,.06-.11,.09-.16l.07,.12Z"/><path class="cls-2" d="M933.79,370.86s-.09,.02-.13,.04c.01-.04,.03-.08,.05-.12l.08,.08Z"/><path class="cls-2" d="M1024.42,414.74s-.03,.07-.04,.1l-.1-.1h.14Z"/><path class="cls-2" d="M1093.82,419.36s.04-.07,.06M -.1c.02,.01,.05,.01,.07,.01l-.13,.09Z"/><path class="cls-2" d="M1098.65,405.13c-1.66,4.68-2.86,9.56-4.77,14.13-13.71-1.43-27.44-2.52-41.19-3.46-8.12-3.57-16.67-6.33-25.46-8.27,1.06-3.3,1.98-4.85,1.58-6.09-15.84-.33-31.75,.37-47.58,1.18-1.39-.22-12.06,1.51-11.5-.14,1.3-3.64,2.89-7.17,4.32-10.75,.62-1.84-4.55-.63-5.52-.71-15.35,1.55-30.59,3.66-45.82,6.05-.52,.08-1.08-.38-.94-.77,1.24-3.32,2.86-6.5,4.27-9.75,1.35-2.84-1.52-1.57-3.12-1.44-13.44,2.7-26.87,5.33-40.15,8.66-.79,.02-2.97,1.05-3.1-.14,1.27-3.67,3.18-7.09,4.7M 6-10.62,.35-1.34-.54-1.27-1.86-.91-12.83,3.45-25.74,7.01-38.28,11.22-.6,.2-1.28,.25-1.92,.35-.07,.01-.27-.16-.26-.23,.91-3.73,3.08-7.1,4.52-10.66,1.41-2.5-.83-1.58-2.26-1.13-5.44,1.86-10.91,3.68-16.31,5.63-6.13,2.21-12.2,4.55-18.29,6.83-.64,.29-2.07,.81-1.9-.35,1.55-3.57,3.34-7.05,4.97-10.58,.12-.63,1.06-1.68,0-1.9-11.54,3.96-22.74,9.28-33.92,14.08-.45-.46-.42-.87-.24-1.29,1.69-4.09,3.51-8.12,5.09-12.25,.03-.07-.1-.19-.19-.26-.69-.23-1.76,.56-2.46,.77-7.89,3.73-15.54,7.76-23.2,11.78-1.27,.67-3.7,2.18-2.42-.63,1.84-M 4.37,4.05-8.63,5.66-13.09-.32-.77-1.47,.14-1.97,.31-5.11,2.8-10.24,5.58-15.31,8.44-3.25,1.6-6.06,4.15-9.45,5.34-.36-.48-.11-.87,.06-1.27,2.01-5.1,4.86-10.02,6.39-15.23,0-.04-.19-.15-.27-.14-1.25,.24-2.26,1.15-3.37,1.73-7.11,4.25-14.16,8.63-21.31,12.82-2.26,.93,.5-3.32,.68-4.1,2-4.23,4.02-8.45,6.03-12.68,.76-1.5,.55-1.99-1.08-1.17-7.46,4.21-14.42,8.95-21.6,13.58-.47,.31-1.01,.95-1.65,.54-.6-.39-.02-1.02,.2-1.49,2.43-5.36,4.75-10.76,7.5-16.02,.47-.89,.82-1.82,1.2-2.73,.03-.07-.07-.21-.16-.28-.05-.06-.22-.1-.28-.07-.5M 7,.27-1.17,.52-1.69,.85-7.21,4.52-14.32,9.16-21.56,13.62-.14,.09-.47,0-.69-.04-.07-.02-.15-.19-.12-.27,3.24-7.22,6.96-14.22,10.36-21.37,.94-1.96,.68-2.39-1.26-1.24-7.09,4.47-14.13,9-21.23,13.44-.17,.08-.85,.02-.79-.34,2.97-7.32,6.98-14.22,10.61-21.29,.88-1.68,1.66-3.4,2.47-5.1,.03-.07-.09-.21-.19-.28-.7-.12-1.7,.66-2.37,.94-5.04,2.89-10.01,5.85-15.06,8.71-1.47,.46-.23-1.65-.02-2.23,4.1-8.54,8.53-16.98,13.24-25.32,.36-.83,2.88-4.24,.37-3.19-5.77,2.95-11.46,6.06-17.2,9.06-.15,.08-.48-.04-.71-.11-.14-.1-.1-.41,0-.57,5M .93-11.64,12.47-22.89,19.07-34.21,.37-.77-.9-.64-1.31-.41-5.93,2.94-12.21,5.31-17.92,8.62-1.02-1.04,.29-2.24,.69-3.28,6.82-12.73,14.57-25.07,22.03-37.51-.43-.1-.85-.32-1.09-.23-2.58,.93-5.13,1.89-7.67,2.88-3.64,1.42-7.25,2.86-10.87,4.29-.36,.14-.8,.34-1.03,0-.15-.23-.1-.64,.05-.89,3.57-6.03,7.09-12.09,10.8-18.07,5.55-9.2,11.74-18.09,17.11-27.39-1.33-.51-2.56,.39-3.87,.64-5.4,1.66-10.8,3.33-16.2,4.99-.62,.11-1.68,.69-1.95-.11,10.35-18.09,22.78-35.19,34.12-52.74,.25-1.06-2.94,.09-3.55,.04-6.24,1.32-12.48,2.67-18.73,3M .99-.43,.12-1.04-.16-.88-.67,12.48-20.09,26.28-39.44,40.16-58.64,.46-.64,.83-1.33,1.2-2.02,.13-.24-.06-.45-.37-.47-.53-.02-1.08-.07-1.6-.01-6.93,.79-13.86,1.63-20.79,2.4-1.67,.36-2.62-.24-1.26-1.71,11.54-16.61,23.2-33.11,35.27-49.37,4.46-6.02,9.06-11.97,13.6-17.96,.21-.28,.47-.53,.63-.83,.6-1.23,2.02-1.31,3.37-1.26,7.41-.02,14.82-.04,22.24-.04,.66,0,1.33,.1,1.97,.21,.15,.03,.38,.4,.31,.51-17.37,22.13-35.49,43.82-51.64,66.74-.13,.21,.32,.68,.65,.67,.94-.04,1.88-.04,2.81-.14,6.81-.7,13.6-1.59,20.42-2.17,.21-.02,.55,.M 11,.65,.25,.1,.15,.08,.44-.03,.59-1.52,2.04-3.02,4.08-4.6,6.09-13.05,16.72-25.59,33.56-37.62,50.88-.26,.46-.95,1.38-.11,1.58,7.23-1.24,14.35-2.9,21.53-4.36,2.54-.38,.92,1.06,.2,2.2-3.46,4.74-6.93,9.48-10.4,14.22-8.13,11.59-16.97,23.01-23.97,35.06,.23,.08,.53,.21,.73,.15,1.53-.41,3.05-.84,4.56-1.29,4.92-1.47,9.83-2.95,14.75-4.41,.64-.1,1.63-.71,2.06,.02-9.06,13.87-19.07,27.48-27.78,41.55-.44,.95-1.48,1.83-1.38,2.9,.03,.21,.61,.25,1.1,.06,5.72-2.17,11.43-4.32,17.17-6.48,.6-.08,2.53-1.23,2.67-.27-7.78,12.42-16.28,24.4M 3-23.73,37.06-1.75,2.93,.22,1.92,2.16,1,5.17-2.31,10.34-4.63,15.52-6.93,.45-.19,.99-.25,1.5-.35,.07-.01,.28,.15,.27,.21-.67,1.9-2.07,3.5-3.08,5.24-5.4,8.32-10.38,16.8-15.42,25.25-1.71,3.06-3.15,4.81,1.78,2.25,4.8-2.39,9.58-4.8,14.39-7.19,.43-.22,.96-.33,1.46-.46,.07-.02,.3,.15,.28,.2-1.7,4.01-4.58,7.52-6.62,11.36-3.34,5.76-6.59,11.56-9.86,17.35-.15,.25-.05,.61-.03,.91,0,.06,.2,.17,.25,.16,7.1-3.52,13.82-7.88,20.81-11.69,.96-.42,2.42-1.48,3.41-1.52,.09,.18,.27,.42,.19,.56-.46,.9-.99,1.77-1.49,2.65-3.98,7.06-7.97,14.M 13-11.92,21.21-.26,.46-.7,.92-.51,1.49,.03,.08,.22,.2,.26,.18,8.44-4.24,16.26-9.64,24.61-14.1,.16,.27,.4,.48,.35,.6-.32,.7-.68,1.4-1.09,2.07-3.74,6.33-6.96,12.84-10.37,19.28-.21,.4-.44,.8,.04,1.31,7.88-4.63,15.87-9.22,23.95-13.65,1.97-1.01,1.73-.04,.97,1.43-3.26,5.88-6.67,11.72-9.63,17.77-.13,.25-.11,.47,.19,.55,1.37,.02,2.49-1.22,3.71-1.74,5.92-3.39,11.82-6.79,17.75-10.15,1.42-.81,2.95-1.49,4.45-2.2,.12-.06,.44,.14,.73,.25-3.21,5.64-6.01,11.51-8.95,17.29-.11,.22,.01,.4,.31,.49,8.95-4.03,17.43-9.5,26.45-13.59,.65-.M 23,1.22-.17,.88,.78-2.56,4.85-5.32,9.62-7.56,14.62-.08,1.73,3.25-.76,4.01-.95,6.74-3.37,13.45-6.77,20.36-9.91,1.4-.64,2.84-1.22,4.27-1.82,.3-.12,.54-.04,.66,.21-1.46,4.79-4.92,9.28-6.76,14.07-.06,.15,.14,.38,.27,.55,.84,.02,1.75-.55,2.55-.82,10.12-4.51,20.58-8.48,30.91-12.68,.92-.24,1.99-.99,2.92-.48-1.48,4.1-4.41,8.07-6.4,12.1-.15,.47-.62,1.03-.38,1.51,.14,.24,.37,.33,.67,.23,1.36-.46,2.73-.89,4.07-1.39,10.51-3.89,21.05-7.71,31.81-11.15,1.13-.21,2.29-1.1,3.4-.46-1.97,4.34-4.65,8.45-6.58,12.8,.9,.6,1.74,.03,2.66-.1M 8,13.6-4.26,27.38-8.4,41.31-11.69-2.09,3.75-4.02,7.59-5.99,11.4-.2,.58-.96,1.75,.02,1.9,15.66-3.64,31.35-7.16,47.25-10.12-1.62,3.63-3.51,7.13-5.3,10.67-.33,.85-1.66,2.58,.1,2.6,14.11-2.37,28.3-4.29,42.51-6.03,2.79-.34,5.6-.55,8.41-.78,.3-.02,.64,.19,1.05,.33-1.21,3.07-2.69,5.89-4.06,8.87-2.01,4.21-2.07,3.85,3.5,3.56,10.84-1.02,21.73-1.51,32.61-1.9,6.72-.31,13.44-.58,20.18-.52,.64,.09,1.8-.16,1.96,.64-1.19,4.1-3.37,7.9-4.64,11.99-.17,1.6,3.73,.79,4.83,1.05,21.3,.64,42.68,1.16,63.84,3.75Z"/><path class="cls-2" d="M10M 98.8,405.15c-.05-.01-.1-.01-.15-.02,0-.02,.01-.05,.02-.07l.13,.09Z"/><path class="cls-2" d="M657.28,1058.23c8.98-4.12,17.66-8.8,26.41-13.35,.55-.29,1.07-.66,1.81-.44l-.09-.07c.34,.65,.03,1.26-.23,1.86-1.38,3.13-2.77,6.25-4.17,9.38-.51,1.2-1.31,2.32-1.2,3.67-.3,.04-.32,.08-.07,.14v-.2c.55,.16,1.02-.01,1.47-.27,2.09-1.17,4.18-2.34,6.29-3.48,5.67-3.07,11.33-6.15,16.68-9.57,.82-.53,1.89-1.2,2.8-.49l.06-.08c-.78,.64-.99,1.51-1.34,2.31-1.38,3.15-2.71,6.31-4.07,9.46-1.96,4.49-3.11,5.98,2.25,2.59,6.12-3.7,12.24-7.4,18.36-1M 1.11,.98-.43,2.24-1.86,3.3-1.51,.26,.31,.13,.61,0,.91-2.35,5.16-4.87,10.26-7.28,15.4-.2,.67-.94,1.46-.29,2.05,.04,.05,.29,.04,.38-.01,8.21-4.6,15.88-9.97,23.89-14.88,.17,.26,.39,.45,.35,.58-.3,.82-.63,1.64-.99,2.45-2.48,5.57-5,11.14-7.85,16.6-.2,.38-.53,.75-.32,1.2,.04,.08,.22,.2,.26,.18,.47-.19,.98-.35,1.39-.61,6.65-4.21,13.29-8.43,19.93-12.65,.84-.43,1.72-1.25,2.64-1.39,.62,.75-.46,1.87-.7,2.68-2.95,6.01-5.9,12.01-8.85,18.02-.39,.8-.73,1.61-1.07,2.43-.03,.08,.06,.2,.11,.29,.11,.21,.37,.3,.64,.13,3.11-1.88,6.24-3.M 75,9.3-5.68,4.33-2.73,8.61-5.52,12.93-8.27,.13-.08,.47,.01,.7,.06,.3,.3-.16,.83-.25,1.18-3.63,7.92-7.74,15.62-11.8,23.33-.36,.69-.66,1.4-.97,2.11-.03,.08,.04,.25,.11,.27,1.1,.31,2.06-.77,3.03-1.16,4.25-2.47,8.48-4.95,12.73-7.42,.75-.44,1.39-1.04,2.39-1.13l-.06-.09c.41,.88-.12,1.62-.5,2.42-4.09,8.61-8.57,17.09-13.29,25.49-.52,1.08-1.51,2.04-1.41,3.29l-.12-.07c1.58,.05,2.83-1.06,4.2-1.69,4.13-2.21,8.25-4.43,12.38-6.63,.75-.28,1.6-.99,2.41-.88,.09,.07,.21,.2,.18,.27-.31,.71-.61,1.42-.97,2.11-5.43,10.28-11.03,20.5-17.0M 9,30.56-.41,.67-.76,1.37-1.07,2.08-.07,.15,.1,.38,.22,.56,5.95-1.94,11.63-5.35,17.46-7.83,.58-.27,1.14-.58,1.86-.35l-.09-.06c.2,.56-.05,1.05-.33,1.55-4.01,7.06-7.95,14.14-12.05,21.16-3.19,5.46-6.6,10.84-9.9,16.26-.23,.38-.37,.8-.52,1.21-.02,.06,.11,.19,.21,.25,.83,.19,1.75-.44,2.57-.64,4.96-1.94,9.91-3.89,14.86-5.84,.95-.24,1.91-1.11,2.9-.64,.08,.03,.15,.19,.12,.26-.23,.5-.45,1.01-.73,1.5-8.29,15.12-18.76,29.66-27.1,44.62,.07,.08,.23,.2,.3,.18,.9-.21,1.81-.42,2.68-.69,5.4-1.66,10.8-3.34,16.2-5,.93-.2,1.79-.74,2.68-M .11-10.61,18.11-22.71,35.48-34.36,52.94,.81,.47,1.46,.34,2.11,.2,6.37-1.37,12.73-2.77,19.1-4.14,.67-.1,2.3-.56,2.11,.48-9.1,14.78-19.09,28.96-29.05,43.24-3.64,5.16-7.38,10.27-11.06,15.41-.46,.65-.83,1.34-1.2,2.02-.25,.58,.8,.51,1.14,.53,6.94-.77,13.86-1.62,20.8-2.36,1.94,0,3.71-.53,1.91,1.96-16.21,23.36-32.68,46.57-50.21,69-8.32,.47-16.69,.07-25.03,.19-.68,0-1.83,.05-1.97-.65,16.6-21.39,34.08-42.35,49.78-64.21,.68-.92,1.31-1.88,1.94-2.82,.17-.25-.21-.74-.53-.72-1.87,.12-3.74,.37-5.61,.56-4.8,.55-9.59,1.12-14.39,1.6M 5-.86-.07-4.46,.89-3.99-.61,12.06-15.94,24.37-31.75,35.83-47.98,2.07-2.9,4.1-5.82,6.12-8.74,.32-.46,.55-.97,.75-1.48,.03-.08-.3-.37-.47-.37-6.8,1.15-13.54,2.84-20.32,4.17-.71,.03-1.67,.45-2.33,.12-.09-.18-.21-.43-.13-.56,.49-.76,1.03-1.51,1.58-2.25,11.62-16.01,23.47-31.86,33.9-48.46-.75-.5-1.48-.12-2.26,.08-6.55,1.74-13.08,4.4-19.66,5.61-.64-.61,.38-1.38,.67-1.96,7.31-10.06,14.05-20.36,20.87-30.63,2.59-3.9,5.02-7.86,7.51-11.79,.15-.23,.05-.44-.23-.54-1.92-.01-3.67,1.27-5.5,1.8-4.89,1.77-9.71,3.79-14.66,5.39-.24,.04M -.94-.12-.73-.46,8.27-12.7,16.96-25.14,24.33-38.27,.06-.13-.14-.37-.27-.53-.04-.05-.27-.04-.37,0-5.94,2.49-11.76,5.23-17.67,7.8-.45,.2-.99,.29-1.49,.4-.07,.01-.29-.15-.28-.21,.57-1.92,2.04-3.49,3.02-5.24,5.95-9.42,11.84-18.78,17.15-28.5,.01-.33-.37-.64-.76-.39-5.88,2.8-11.66,5.81-17.5,8.68-.32,.08-1.15,.42-1.35-.01,4.39-8.02,9.55-15.66,13.85-23.68,.93-1.67,1.82-3.36,2.69-5.05,.27-.52,.16-1.06-.26-1.52,.07,.05,.13,.09,.2,.13-.22,.06-.24,0-.06-.17-7.03,4.98-15.08,8.67-22.5,13.12-2.84,1.46-2.09,.13-.96-1.71,4.14-7.37,M 8.27-14.73,12.4-22.1,.15-.4,.75-1.16,.41-1.48-.75-.31-1.36,.34-2,.64-6.4,3.76-12.8,7.53-19.21,11.29-.98,.57-1.96,1.14-2.98,1.67-.16,.08-.55,.05-.69-.05-.41-.72,.74-1.9,1.02-2.63,3.59-6.03,6.64-12.24,9.87-18.4,1.31-2.54-.57-1.62-1.93-.69-6.85,4.37-14.19,8.2-21.34,12.24-2.41,1.22-2.06,.19-1.09-1.64,3.13-5.71,6.48-11.33,9.32-17.18,.12-.25-.06-.59-.12-1.06-7.5,4.15-14.74,8.42-22.18,12.63-1.09,.62-2.26,1.17-3.4,1.75-.29,.14-.53,.09-.65-.11-.24-.49,.33-1.02,.48-1.5,2.62-5.07,5.25-10.14,7.87-15.22,.21-.4,.41-.8-.04-1.3-6.M 91,3.43-13.62,7.26-20.48,10.82-1.91,1.01-3.88,1.94-5.83,2.9-.46,.23-.91,.21-1.08,.03-.3-.32-.09-.61,.06-.89,1.58-2.97,3.2-5.93,4.76-8.91,.94-1.79,1.82-3.59,2.67-5.4,.12-.25-.08-.59-.13-.9-8.32,3.41-16.12,7.89-24.31,11.65-1.48,.6-3.08,1.57-4.63,1.82-.12-.17-.3-.39-.24-.54,2.08-4.45,4.44-8.78,6.63-13.18,.2-.4,.27-.83-.21-1.3-11.87,4.75-23.78,10.46-35.92,14.33-.1-.18-.27-.42-.2-.56,2-3.89,4.25-7.67,6.31-11.53,.31-.58,.46-1.22,.66-1.84,.02-.06-.16-.22-.26-.22-13.02,4.02-25.62,9.68-38.89,13.29-.19,.04-.47-.12-.67-.22-.1M 8-.56,.55-1.52,.76-2.11,1.76-3.49,3.9-6.82,5.39-10.43,.06-.15-.14-.38-.27-.55-13.58,3.73-27.11,8.33-40.96,11.68-.76,.19-.75,.21-2-.14,2.11-3.83,4.02-7.75,5.98-11.64,.38-.75-.53-.87-1.06-.89-11.63,2.69-23.23,5.53-35,7.78-3.53,.62-7.03,1.67-10.62,1.88-1.19-.25-.03-1.55,.18-2.21,1.63-3.3,3.51-6.49,4.88-9.91,.18-.75-.86-.73-1.35-.66-9.64,1.55-19.27,3.17-28.96,4.38-4.52,.59-9.04,1.16-13.57,1.7-2.86,.15-5.86,1.04-8.68,.57-.17-.87,.38-1.53,.69-2.22,1.1-2.43,2.28-4.84,3.41-7.25,.41-1.15,2.2-3.35-.28-3.28-12.35,.86-24.7,1.8M -37.08,2.13-6.06,.2-12.11,.6-18.18,.52-.8-.01-1.61-.06-2.4-.15-.16-.02-.41-.32-.38-.46,1.09-4.23,3.71-8.04,4.58-12.32,.05-.26-.11-.44-.42-.48-3.86-.47-7.79-.31-11.68-.44-18.92-.58-38-1.17-56.75-3.58l.15,.14c1.91-4.66,3.2-9.56,4.88-14.31l-.12,.09c23.14,2.58,46.4,3.98,69.68,4.52l-.11-.09c-1.54,4.12-3.08,8.25-4.61,12.37-.21,.56,.26,1.04,1.01,1.08,10.64,.2,21.29-.28,31.92-.56,8.47-.36,16.92-1.04,25.4-1.35,.37-.02,.81,.36,.75,.62-.98,3.81-2.92,7.37-4.23,11.09-.11,.28,.27,.69,.61,.7,16.96-1.07,33.81-3.92,50.62-6.36,.63-.M 09,1.06,.28,.89,.74-1.15,3.12-2.65,6.1-3.96,9.15-.29,.77-1.34,2.34,.16,2.4,14.94-2.45,29.74-5.92,44.47-9.4,.45-.03,1.17-.2,1.41,.19-1.22,3.98-3.51,7.65-5,11.56-.12,.28,.36,.61,.76,.52,8.74-2.04,17.32-4.73,25.93-7.18,5.06-1.45,9.98-3.28,15.04-4.69,1.16-.03,.58,1.14,.31,1.8-1.42,3.14-2.85,6.27-4.26,9.41-.08,.34-.53,1.34,.02,1.42,4.33-.91,8.5-2.71,12.7-4.07,8.61-2.93,17.04-6.73,25.69-9.29,.62,.51,.15,1.2-.07,1.79-1.62,3.42-3.25,6.84-4.89,10.26-.2,.41-.33,.82,.12,1.22,11.7-4.03,22.99-9.58,34.27-14.16,.11,.05,.24,.18,.2M 3,.25-.15,.63-.26,1.28-.51,1.88-1.41,3.37-2.87,6.72-4.3,10.08-.26,.61-.52,1.23-.09,1.85-.07-.09-.14-.17-.2-.25l.2,.19Z"/><path class="cls-2" d="M555.62,1219.39c-.99-1.21,.96-2.1,1.6-2.98,7.4-7.4,14.81-14.8,22.21-22.2,.42-.58,1.48-1.05,1.14-1.84-.02-.06-.25-.13-.34-.1-11.26,3.15-22.38,6.82-33.6,10.15-.88,.27-1.78,.5-2.68,.71-.15,.03-.41-.17-.56-.29,6.26-7.42,13.83-14.29,20.52-21.53,.3-.45,2.03-1.94,.98-2.07-4.34,1.04-8.56,2.56-12.81,3.88-7.85,2.57-15.83,4.85-23.83,7.1-.63,.18-1.25,.4-1.91,.04,.05-.81,.8-1.33,1.36-1.M 91,5.72-6.37,12.2-12.27,17.55-18.9-.56-.28-1.09-.24-1.6-.09-3.04,.88-6.08,1.75-9.1,2.65-9.46,2.82-19.07,5.29-28.63,7.88-.57,.2-1.39,.33-1.91,.1-.7-.45,1.48-2.09,1.78-2.63,4.26-4.71,8.52-9.42,12.76-14.15,.61-.68,1.42-1.29,1.55-2.2-.78-.32-1.55,0-2.31,.18-11.2,3.09-22.59,5.7-33.9,8.5-2.3,.57-4.6,1.22-7.02,1.43-.2,.02-.45-.15-.63-.27,0-.97,1.21-1.69,1.73-2.47,4.1-4.81,8.44-9.42,12.37-14.36,.2-1.29-3-.06-3.73-.03-14.45,2.97-28.85,6.51-43.43,8.67-1.12-.1,.51-1.67,.75-2.14,3.29-4.07,6.61-8.12,9.9-12.19,1.78-2.11,1.78-2.7M 9-1.19-2.26-12.44,2.39-25.04,4.15-37.6,6.06-3.57,.54-7.17,.93-10.76,1.38-.25,.03-.72-.05-.74-.12-.22-.8,.4-1.41,.85-2.01,3.25-4.47,6.69-8.81,9.8-13.37,.16-.24-.21-.71-.56-.68-5.9,.35-11.73,1.31-17.6,1.93-13.24,1.27-26.49,2.51-39.77,3.36l.06,.11c2.63-4.5,5.53-8.83,8.38-13.21,2.08-3.14,1.69-3.19-2.22-3.03-20.4,.87-40.81,1.6-61.24,1.27l.09,.1c2.32-5.29,5.41-10.25,7.79-15.52,.2-.4-.19-.92-.72-.95-2.01-.11-4.01-.28-6.02-.29-22.53-.46-45.03-2.07-67.48-4.03l.14,.11c2.14-5.86,4.22-11.74,6.44-17.58l-.11,.09c25.19,3.46,50.75M ,4.12,76.13,5.85l-.15-.09c-1.9,4.75-4.43,9.24-6.62,13.86-.29,.65-.91,1.68,.16,1.94,18.02,.81,36.11,.21,54.14-.29,3.23-.1,6.46-.23,9.69-.34,.71-.02,1.16,.58,.86,1.13-2.46,4.2-5.06,8.33-7.59,12.49-.52,.8-1.08,1.9,.57,1.86,13.42-.78,26.85-1.79,40.2-3.24,5.34-.53,10.67-1.33,16.03-1.56,.35,0,.79,.43,.65,.65-3.02,4.86-6.62,9.35-9.71,14.16-.17,.26,.18,.7,.54,.66,2.27-.24,4.55-.42,6.79-.75,14.85-2,29.6-4.63,44.39-6.94,.35-.04,.76,.42,.59,.66-3.19,4.67-6.86,9-10.25,13.53-.41,.53-.92,1.04-.92,1.79,7.26-.63,14.43-2.7,21.62-3.M 97,8.07-1.69,16.18-3.3,24.13-5.34,.59-.07,1.4-.36,1.94-.09,.1,.16,.25,.4,.17,.53-.43,.67-.9,1.32-1.41,1.96-3.61,4.54-7.43,8.94-10.92,13.58-.06,.08-.09,.27-.03,.31,.73,.62,1.74,.04,2.57-.05,12.66-2.98,25.22-6.2,37.68-9.67,1.43-.22,2.9-1.18,4.31-.58-4.22,5.45-8.91,10.5-13.32,15.79-.45,.53-.84,1.08-1.24,1.64-.05,.07,0,.22,.06,.29,.75,.34,1.87-.2,2.68-.3,13.02-3.22,25.81-7.97,38.65-11.08,.09,.16,.23,.41,.14,.52-.55,.74-1.13,1.46-1.75,2.16-4.35,4.93-8.71,9.85-13.06,14.78-.54,.61-1,1.27-1.47,1.91-.04,.06,0,.2,.05,.25,.63M ,.35,1.61-.13,2.28-.23,12.24-3.68,24.43-8.35,36.67-11.62,.29,.12,.2,.51-.35,1.12-5.98,6.96-12.51,13.47-18.56,20.36-.07,1.12,1.45,.3,2.06,.2,11.82-3.89,23.84-7.26,35.29-11.96l-.12,.07c.34,.37,.53,.77,.18,1.18-.76,.89-1.53,1.77-2.33,2.63-6.31,7.15-13.68,13.84-19.43,21.26,.07,.08,.25,.19,.33,.17,.89-.24,1.78-.48,2.64-.77,9.65-3.28,19.29-6.57,28.93-9.85,1.09-.23,2.23-1.08,3.34-.65,.09,.52-.76,1.19-1.05,1.66-7.85,8.81-15.99,17.7-24.73,25.86,.3,0,.33,.04,.11,.12l-.03-.22c1.44,.79,3.09-.36,4.54-.67,8.33-2.76,16.65-5.54,24M .97-8.31,.62-.21,1.2-.5,1.9-.17-7.52,9.73-16.62,18.51-25.08,27.66-.9,.93-1.73,1.9-2.58,2.87-.05,.06,0,.21,.07,.29,.07,.08,.23,.18,.31,.17,.78-.17,1.56-.33,2.31-.56,7.03-2.16,14.06-4.34,21.09-6.5,1.38-.42,2.77-.83,4.17-1.21,.15-.04,.41,.14,.58,.26,.05,.04,0,.23-.06,.3-10.07,11.44-20.92,22.19-31.46,33.21-1.87,2.01-1.86,2.37,.99,1.71,7.29-1.9,14.58-3.82,21.87-5.73,1.34-.21,2.57-1.03,3.93-.57-7.36,8.35-15.49,16.02-23.29,23.98-5.46,5.71-11.72,10.95-16.8,16.89-.01,.63,1.63,.15,2.11,.09,8.22-1.68,16.46-3.28,24.73-4.75,1.0M 7,.32,.42,.82-.13,1.42-2.86,2.86-5.7,5.73-8.59,8.57-9.11,8.96-18.39,17.76-27.68,26.55-3.57,3.37-7.21,6.69-10.81,10.03-.25,.33-.83,.67-.63,1.11,.52,.42,1.58,.11,2.25,.16,7.47-.45,15-1.72,22.46-1.67,.83,.58-.81,1.53-1.16,2.07-17.91,17.01-35.86,33.97-54.34,50.41-2.48,2.24-2.01,2.08-5.87,2.09-6.74,.01-13.47,.02-20.21,.02-2.4-.1-4.33,.1-1.28-2.38,16.8-14.2,33.43-28.68,49.65-43.37,2.15-1.93,4.15-3.96,6.2-5.95,.21-.33-.3-.52-.54-.66-8.51,.91-17.07,1.93-25.6,2.78-.22,.02-.59-.07-.68-.2-.19-.79,.95-1.27,1.4-1.82,8.86-7.97,1M 7.79-15.88,26.57-23.91,6.29-5.76,12.38-11.66,18.54-17.5,.46-.58,1.41-1.12,.99-1.92,0,.23,.08,.27,.28,.14l-.26-.05c-9.22,1.37-18.33,3.41-27.51,5.03-.88-.17-.68-.54-.11-1.1,13.42-12.44,27.78-24.76,39.62-38.08-.07-.08-.24-.18-.33-.16-.91,.17-1.83,.34-2.73,.56-8.88,2.13-17.71,4.48-26.61,6.49-.18,.04-.44-.12-.64-.22,0-.6,1.11-1.32,1.51-1.83,11.31-10.7,22.99-20.99,33.63-32.35-1.62-.39-2.8,.4-4.31,.74-8.86,2.54-17.72,5.07-26.59,7.6-1.1,.28-2.38,.81-3.43,.12l.04,.03c10.14-8.99,19.5-18.92,29.36-28.24,.38-.46,1.23-.96,1.07-1M .59-.11-.13-.49-.22-.69-.16-1.02,.27-2.02,.58-3.02,.88-7.02,2.16-14.03,4.33-21.06,6.47-3.41,1.21-7.22,1.72-10.44,3.32h.05Z"/><path class="cls-2" d="M376.96,212.56c-.59,.32-1.22,.43-1.91,.24-3.81-1.08-7.62-2.14-11.42-3.23-2.81-.68-5.53-1.9-8.39-2.25-.22,0-.57,.16-.63,.31-3.76,20.55-5.39,41.55-7.33,62.36-.06,2.49-1.66,1.24-3.14,.79-5.27-2.16-10.54-4.34-15.81-6.5-.59-.23-1.68-.78-2.04-.01-1.63,18.12-1.7,36.38-2.24,54.57,.04,1.96-1.48,1.06-2.57,.51-4.35-2.35-8.7-4.72-13.04-7.08-1.1-.32-4.24-3.26-4.77-1.41-.21,16.36,.99M ,32.75,1.46,49.06-.97,.38-1.69-.33-2.48-.75-4.69-3.07-9.36-6.16-14.04-9.24-1.15-.57-2.24-1.94-3.56-1.9-.19,.06-.44,.3-.43,.45,.25,4.09,.48,8.17,.82,12.26,.77,9.13,1.75,18.26,2.64,27.38-.09,.94,.94,5-.21,4.93-.36-.1-.76-.18-1.03-.38-6-4.28-11.73-8.88-17.56-13.38-.48-.33-.91-1.01-1.64-.64-.62,.31-.3,.97-.28,1.48,.03,.65,.1,1.29,.19,1.93,1.43,12.55,3.63,25.04,5.16,37.56-1.12,.12-1.8-.79-2.63-1.36-5.58-4.68-11.14-9.37-16.72-14.05-.7-.42-2.6-2.8-2.99-1.15,1.64,12.44,4.59,24.77,6.22,37.19-2.11-.55-3.3-2.49-4.97-3.76-5.49M -5.04-10.96-10.08-16.45-15.12-.78-.58-1.35-1.58-2.45-1.46,1.44,10.54,4.19,21.04,6.07,31.57,.19,.96,.34,1.92,.46,2.88,.02,.13-.28,.3-.47,.41-.94-.28-1.91-1.63-2.73-2.27-6.71-6.61-13.41-13.22-20.11-19.83-.88-.7-1.44-1.84-2.69-1.85,.85,7.37,3.03,14.65,4.38,21.98,.61,2.87,1.25,5.73,1.86,8.59,.11,.52,.24,1.06-.09,1.56-.03,.05-.29,.07-.38,.03-1.95-1.11-3.27-3.11-4.91-4.63-6.84-7.21-13.68-14.42-20.52-21.63-.79-.64-1.37-1.91-2.48-1.96-.13,.01-.33,.31-.3,.46,.22,1.28,.47,2.56,.74,3.83,1.23,5.73,2.47,11.46,3.7,17.19,.55,2.55M ,1.1,5.09,1.62,7.64,.06,.28-.11,.6-.21,.89-.55,.19-1.34-.8-1.74-1.13-9.82-10.66-19.46-21.48-29.37-32.06-.12-.12-.48-.1-.74-.12-.03,0-.13,.19-.12,.28,1.36,9.1,3.48,18.08,5.22,27.11-.3,1.4-1.77-.61-2.18-1.04-11.39-12.38-21.85-25.95-33.44-37.95-1.08-.23-.21,2.39-.31,2.95,1.04,7.47,3.02,15.02,3.51,22.46-1.46-.35-2.11-1.82-3.09-2.82-10.26-12.26-20.52-24.53-30.79-36.79-1.95-2.32-3.91-4.64-5.9-6.94-.1-.12-.48-.1-.73-.11-.45,.42-.18,1.27-.17,1.83,.68,6.22,1.37,12.44,2.04,18.67,.07,.64,.03,1.28,.02,1.93-.09,.36-.77,.17-.92,M .07-14.72-17.71-28.96-35.82-43.51-53.67-.76-.96-1.73-1.94-1.56-3.24-.02-6.25-.05-12.5-.06-18.74,0-.3,.16-.61,.29-.9,.02-.05,.32-.11,.37-.07,13.69,15.93,26.51,32.72,39.95,48.91,.89,.84,1.61,2.54,2.94,2.5-.15-5.27-1.03-10.5-1.46-15.76-.23-2.25-.46-4.51-.67-6.76,.27-1.08,1-.43,1.51,.1,11.32,13.51,22.64,27.02,33.98,40.53,.6,.55,2.9,3.82,3.2,2.29-1.06-8.42-2.96-16.94-3.56-25.32,1.02-.11,1.51,1,2.17,1.6,9.73,11.12,19.46,22.24,29.2,33.36,.48,.5,3.01,3.83,2.99,1.58-1.57-8.74-3.24-17.46-4.72-26.21-.07-.41,.07-.84,.13-1.25,0M -.02,.3-.06,.38,0,9.92,9.99,19.11,20.86,28.81,31.13,.3,.32,.51,.76,1.13,.81,.09,0,.28-.1,.28-.16-.18-3.99-1.36-7.87-1.99-11.81-1.15-6.07-2.29-12.14-3.43-18.2-.24-1.15,.95-.8,1.33-.31,3.2,3.33,6.41,6.66,9.62,9.98,4.78,4.94,9.58,9.88,14.38,14.8,.58,.59,1.23,1.13,1.87,1.68,.12,.08,.58-.02,.63-.18-1.01-9.08-3.56-18.05-4.78-27.15-.31-1.81-.59-3.63-.84-5.45,.37-1.46,1.7,.35,2.36,.82,6.43,6.23,12.85,12.47,19.28,18.7,.85,.83,1.78,1.61,2.71,2.38,.11,.09,.49-.01,.87-.03-.91-8.79-3-17.47-4.18-26.24-.42-3.2-1.25-6.38-1.34-9.61M ,.44-.82,2.11,.99,2.64,1.33,5.49,4.89,10.95,9.8,16.43,14.7,2.8,2.21,5.28,5.88,4.09-.63-1.12-7.59-2.28-15.18-3.2-22.79-.34-4.38-1.59-8.8-1.39-13.16,.7-.63,1.83,.69,2.46,1.05,4.85,3.9,9.67,7.81,14.52,11.7,1.33,1.07,2.71,2.09,4.1,3.11,.13,.1,.49,.03,.73-.02,.08-.01,.18-.18,.17-.28-.22-2.47-.43-4.93-.68-7.4-.96-8.9-1.86-17.81-2.61-26.73-.24-2.79-.41-5.59-.62-8.39-.03-.44,.21-.76,.49-.79,.45-.05,.75,.15,1.04,.35,3.85,2.69,7.69,5.41,11.56,8.09,2.34,1.62,4.72,3.21,7.1,4.79,.16,.11,.53,.13,.74,.06,.76-.35,.39-1.39,.46-2.06M -.29-5.06-.79-10.1-.85-15.17-.38-9.58-.95-19.16-.99-28.75,.13-.88-.28-2.49,1.04-2.35,5.78,3.08,11.33,6.59,17.03,9.83,.86,.23,2.3,1.78,2.98,.68,.17-18.2,.43-36.4,1.1-54.59l-.14,.05c6.28,2.66,12.5,5.46,18.76,8.17,1.13,.35,3.11,1.59,3.06-.53,1.41-20.5,3.06-41,5.82-61.38l-.13,.12c6.79,2.07,13.6,4.07,20.4,6.1,.63,.19,1.27,.36,2.08,.01,2.87-19.84,6.37-39.63,10.07-59.34,.7-3.72,1.53-7.43,2.31-11.14,.2-.95,.71-1.2,2.01-1.04,5.96,.81,11.9,1.78,17.84,2.66,1.32,.2,2.63,.46,3.93,.73,.79,.33,.4,1.43,.35,2.09-3.26,14.48-6.46,28.M 99-9.21,43.56-1.82,9.13-3.38,18.29-4.97,27.45-.08,.43-.11,.85,.18,1.25h0Z"/><path class="cls-2" d="M1063.89,1226.8c5.16,.76,10.15,2.88,15.25,4.12,1.61,.13,7.1,3.06,7.29,.51,2.55-17.85,4.63-35.76,6.39-53.71,.46-2.96-.04-6.11,.96-8.96,.66-.62,1.77,.13,2.5,.31,5.28,2.16,10.54,4.33,15.82,6.49,1.08,.44,2.25,.95,2.43-.71,1.31-18.26,1.25-36.6,2.11-54.87,1.07-.4,1.97,.4,2.92,.8,4.79,2.61,9.57,5.23,14.35,7.84,.75,.42,2.41,1.67,2.89,.52,.37-16.35-.91-32.78-1.37-49.07,.67-.64,1.68,.31,2.33,.6,5.63,3.69,11.22,7.41,16.85,11.1,.M 35,.22,1.04,.29,1.12,.12-.02-14.7-2.56-29.65-3.59-44.41,.42-1.61,2.45,.59,3.19,.97,4.97,3.8,9.92,7.61,14.88,11.41,.81,.46,1.54,1.42,2.48,1.5,.31-.02,.48-.16,.47-.43-.05-3.13-.54-6.23-.95-9.33-1.22-10.39-3.07-20.78-4.33-31.12,.99-.32,1.73,.71,2.49,1.19,5.67,4.76,11.33,9.53,17,14.29,.65,.54,1.35,1.05,2.04,1.55,.06,.05,.26,0,.38-.04,.1-.03,.25-.11,.25-.17,0-.64,.08-1.29-.03-1.92-.93-5.55-1.89-11.09-2.85-16.64-.96-6.29-2.46-12.59-3.21-18.85,1.25-.11,2.08,1.23,3.03,1.9,5.85,5.36,11.68,10.72,17.53,16.08,.99,.69,1.92,2.27M ,3.19,2.22,.3-.37,.11-1.07,.09-1.54-2.04-10.21-4.09-20.41-6.13-30.61-.02-.76-.64-1.92,.22-2.35,.07-.05,.3-.03,.36,.03,8.43,7.58,16.02,16.05,24.43,23.66,.11,.06,.59-.08,.63-.23,0-.64,.06-1.29-.07-1.92-2.01-9.77-4.12-19.54-6.23-29.29-.04-.2,.03-.42,.08-.63,.08-.18,.49-.22,.63-.13,5.32,4.89,10.02,10.42,15.09,15.57,3.91,4.12,7.82,8.24,11.75,12.34,.22,.23,.63,.36,.96,.52,.34,.02,.39-.49,.36-.74-2.05-9.66-4.18-19.3-6.19-28.97,.23-1.47,1.79,.5,2.22,.94,9.13,10.01,18.25,20.02,27.39,30.03,1.43,1.42,3.06,3.8,2.51-.16-1.47-7.M 88-3.03-15.75-4.67-23.61-.1-.52-.04-1.06-.03-1.59,0-.07,.13-.16,.23-.19,.12-.03,.33-.05,.39,0,.67,.67,1.36,1.33,1.97,2.04,9.39,10.79,18.76,21.58,28.14,32.37,1.38,1.59,2.76,3.19,4.18,4.76,.19,.21,.67,.26,1.21,.46-1.02-7.64-2.43-14.98-3.68-22.55-.14-.85-.13-1.71-.18-2.57,0-.1,.1-.28,.14-.28,.24,0,.59,0,.71,.11,.75,.76,1.47,1.54,2.14,2.34,11.45,13.7,22.9,27.41,34.35,41.11,.75,.89,1.53,1.77,2.34,2.63,.1,.11,.46,.09,.7,.08,.06,0,.17-.17,.17-.26-.32-6.89-1.18-13.74-1.83-20.61-.11-3,1.45-.75,2.41,.31,6.99,8.57,13.99,17.14M ,20.93,25.73,6.72,8.32,13.38,16.68,20.07,25.02,.75,1.09,2.01,2.05,2.06,3.44-.07,6.66,.32,13.39-.16,20.02-.09,.1-.54,.19-.67,.08-.71-.78-1.43-1.56-2.09-2.37-7.38-9.14-14.73-18.29-22.12-27.43-5.75-6.87-11.1-14.13-17.17-20.73-.12-.06-.58,.08-.62,.23-.03,.64-.1,1.29-.04,1.92,.68,6.76,1.41,13.51,1.92,20.28,0,.09-.1,.26-.17,.26-.7,.15-1.09-.32-1.49-.79-11.5-13.82-23.08-27.56-34.63-41.35-.52-.62-1.13-1.19-1.72-1.78-.13-.1-.57-.04-.65,.12,.72,8.31,2.67,16.64,3.45,25-.05,.56-.68,.54-1,.22-10.44-11.75-20.71-23.65-31.09-35.45M -.59-.62-1.13-1.75-2.2-1.72,.2,5.34,1.93,11.06,2.72,16.51,.64,3.73,1.46,7.43,1.76,11.2,.03,.27-.17,.41-.48,.39-9.47-9.07-18-19.65-27.14-29.23-.91-.76-1.75-2.36-2.99-2.39-.32,.47-.03,1.32-.01,1.89,1.77,9.47,3.67,18.93,5.35,28.42,.01,.58-.73,.54-1.03,.26-8.07-8.2-15.99-16.53-24.01-24.78-4.75-5.23-2.48,.34-2.11,3.51,1.49,7.99,2.99,15.97,4.47,23.96,.45,3,1.26,5.75-1.91,2.49-6.68-6.49-13.35-12.98-20.04-19.46-.68-.66-1.45-1.27-2.19-1.89-.14-.08-.58,.03-.66,.15,0,4.41,1.4,8.74,1.96,13.12,1.12,6.72,2.23,13.45,3.28,20.18,.1M 5,.95,.48,1.91,.11,2.87-1.26-.02-2.03-1.28-2.99-1.97-5.57-4.98-11.13-9.97-16.71-14.94-.9-.8-1.87-1.54-2.82-2.3-.06-.05-.26-.02-.37,0-.11,.03-.27,.1-.28,.16-.06,.42-.16,.85-.1,1.27,.34,2.68,.72,5.35,1.1,8.03,1.34,9.84,2.98,19.66,3.81,29.56-.04,.46-.63,.86-1.05,.47-.87-.67-1.77-1.32-2.62-2.01-5.85-4.61-11.46-9.51-17.5-13.88-.29-.06-.93-.03-.85,.4,.76,10.86,2.24,21.67,3.05,32.53,.29,3.33,.54,6.66,.79,10-.37,1.41-1.95-.09-2.63-.5-5.78-4.05-11.54-8.14-17.41-12.06-2.42-1.51-1.06,3.73-1.22,4.86,.82,14.29,1.64,28.63,1.67,4M 2.94-.51,1.14-1.81-.11-2.54-.42-5.11-2.99-10.21-5.99-15.33-8.97-1.06-.59-1.92-1.35-3.24-.94-.21,18.23-.12,36.44-1.09,54.65l.14-.04c-6.28-2.65-12.49-5.45-18.74-8.17-1.79-.73-3.14-1.45-3.06,1.24-1.45,20.22-2.77,40.64-5.85,60.67l.11-.12c-6.81-2.02-13.6-4.07-20.4-6.1-1.43-.45-1.98-.03-2.15,1.43-1.8,14.03-4.47,27.96-6.71,41.93-1.56,9.58-4.1,19.14-5.44,28.69l.13-.1c-7.97-1.35-16.78-2.68-24.44-3.65,.22-4.7,1.97-9.3,2.78-13.96,1.19-5.39,2.4-10.78,3.5-16.19,2.92-14.95,5.86-29.89,8.28-44.93l-.14,.13Z"/><path class="cls-2" d=M "M1191.44,947.12c.49-.58,.5-1.22,.36-1.86-.33-1.48-.67-2.97-1.06-4.44-2.25-8.42-4.52-16.84-6.78-25.25-.09-.42-.28-1.51,.46-1.16,8.23,7.23,15.71,15.33,23.67,22.88,1.25,1.09,2.03,2.47,3.68,3.05-1.83-9.69-5.14-19.21-7.47-28.84-.14-.52-.18-1.05-.24-1.58,0-.08,.07-.22,.15-.24,.81,.05,1.66,1.18,2.3,1.67,5.88,6.03,11.76,12.06,17.61,18.11,3.38,3.49,6.71,7.01,10.08,10.51,.1,.1,.45,.07,.68,.05,.28-.19,.07-.62,.01-.91-1.96-8.48-4.28-16.88-6.51-25.3-.21-.95-.54-1.94,0-2.83l-.05,.09c11.02,10.93,21.27,22.57,31.72,33.94,.91,.77,1M .68,2.36,2.93,2.4-.04,.29,.03,.34,.22,.14l-.31-.07c.4-.86,.1-1.71-.09-2.55-1.69-7.19-3.42-14.38-5.13-21.57-.17-.73-.26-1.48-.37-2.22-.01-.1,.08-.29,.12-.29,.25,0,.6-.02,.72,.1,.93,.92,1.86,1.84,2.71,2.8,8.67,9.74,17.33,19.48,25.97,29.23,2.88,3.25,5.69,6.54,8.55,9.8,.47,.4,.98,1.28,1.63,1.31,.24-.2,.48-.44,.34-.75-1.43-7.34-2.87-14.67-4.28-22.01-.77-4.35,1.5-1.14,2.89,.33,13.21,15.21,26.25,30.52,39.03,45.97,.74,.9,1.5,1.79,2.26,2.67,.4,.47,.8,.62,.95,.38,.11-.18,.29-.37,.27-.55-.46-5.81-1.26-11.58-1.96-17.37-.17-1.3M 9-.38-2.78-.53-4.17-.02-.15,.19-.42,.34-.44,.23-.03,.59,.04,.72,.18,.72,.78,1.4,1.58,2.07,2.39,4.92,5.92,9.88,11.82,14.73,17.77,10.73,13.17,21.44,26.35,32.12,39.55,1.38,1.32,1.66,2.84,1.64,4.52-.18,6.02,.19,12.07-.16,18.08-.03,.14-.33,.27-.54,.36-.05,.02-.22-.08-.31-.14-15.99-18.66-30.47-39.54-47.3-57.22-.32,.22-.2,.84-.21,1.19,.74,7.06,1.88,14.13,2.27,21.21-.34,.03-.71,.14-.8,.06-.6-.57-1.19-1.16-1.71-1.78-6.13-7.34-12.21-14.71-18.37-22.04-6.38-7.6-12.83-15.16-19.26-22.73-.68-.8-1.38-1.59-2.11-2.36-.11-.12-.47-.11M -.71-.12,.64,7.93,2.81,16.22,4.03,24.25,.05,.29-.1,.6-.19,.89-.27,.1-.82-.16-1.01-.37-11.2-12.79-22.38-25.59-33.58-38.38-.77-.88-1.6-1.73-2.44-2.57-.12-.12-.47-.09-.72-.14l-.03-.18,.13,.12c-.37,.97-.05,1.92,.16,2.86,1.78,8.15,3.67,16.22,5.3,24.42-1.14,.22-1.6-.85-2.34-1.47-6.47-7.11-12.9-14.25-19.4-21.35-3.49-3.81-7.08-7.55-10.64-11.32-.39-.41-.71-.93-1.52-.88l.09-.06c.99,7.93,3.68,15.64,5.33,23.49,.41,1.69,.75,3.39,1.11,5.09,.1,.45-.11,.81-.39,.75-9.36-8.41-17.72-18.48-26.75-27.44-.79-.62-1.41-1.88-2.54-1.78-.05,0M -.16,.19-.14,.29,2.17,10.09,4.73,20.09,7.07,30.14,.13,2.17-2.65-1.09-3.15-1.57-7.48-7.35-14.83-14.83-22.39-22.1-.43-.6-1.61-.68-1.28,.35,2.37,10.84,5.39,21.92,7.25,32.7-.91,.17-1.44-.74-2.08-1.21-4.02-3.77-8.02-7.56-12.05-11.32-2.8-2.62-5.63-5.22-8.46-7.83-.44-.39-.94-.91-1.59-.87-.12,.01-.3,.32-.27,.47,.27,1.38,.59,2.76,.88,4.14,2.08,9.87,4.29,19.72,6.16,29.63,.06,.62,.41,1.38-.34,1.72-.06,.04-.28,.02-.34-.03-.75-.62-1.5-1.24-2.23-1.87-6.29-5.29-12.22-11.05-18.74-16.05-.74-.16-.64,.69-.55,1.22,2.28,12.45,4.79,24.8M 8,6.52,37.41-1.19,.32-2.23-1.09-3.2-1.67-4.78-3.8-9.53-7.61-14.31-11.42-.86-.68-1.76-1.33-2.67-1.97-.15-.1-.49-.06-.74-.03-.08,0-.2,.17-.19,.26,.74,7.52,2.34,14.94,3.16,22.46,.67,5.25,1.34,10.5,1.99,15.75,.12,.96,.09,1.93,.12,2.9,.03,.41-.68,.39-.87,.34-5.6-3.65-10.93-7.68-16.43-11.48-.83-.45-1.63-1.37-2.66-1.11,.46,8.07,1.7,16.31,2.11,24.47,.55,6.98,1.31,13.96,1.49,20.97,0,.17-.18,.41-.37,.49-1.22,.17-2.25-1.08-3.31-1.56-4.36-2.71-8.72-5.43-13.09-8.13-1.01-.53-2.86-2.01-2.88,.17,.44,16.47,1.27,32.95,.91,49.43-.01,M .28-.58,.58-.86,.45-5.59-2.52-10.97-5.47-16.47-8.17-3.22-1.88-2.47,.74-2.61,2.92-.47,17.87-1.29,35.78-2.88,53.58-.44,.82-1.74,.27-2.44,.03-3.87-1.52-7.73-3.06-11.6-4.57-2.1-.63-4.09-2.01-6.31-1.92-2.91,22.13-5.02,44.49-9.27,66.46l.14-.13c-7.2-2.18-14.57-4.29-21.94-5.82l.06,.09c4.81-21.94,7.7-44.32,10.76-66.58,.24-2.43,2.95-.66,4.31-.3,4.29,1.55,8.58,3.11,12.87,4.66,.81,.23,2.24,1.13,2.83,.23,1.18-6.69,1.37-13.51,2.08-20.26,.67-12.04,1.77-24.08,2.04-36.14,.1-.77-.16-2.23,1.06-2.04,5.87,2.27,11.38,5.37,17.19,7.78,1.1M 4,.28,1.11-.81,1.18-1.58,.05-8.07,.45-16.15,.2-24.23-.26-8.29-.3-16.58-.42-24.87-.09-2.16,1.85-.76,2.89-.25,5.1,2.78,10.01,5.92,15.22,8.49,.56,.12,.9-.75,.83-1.21-.22-3.76-.47-7.53-.71-11.29-.48-6.12-.76-12.26-1.27-18.38-.25-5.25-1.5-10.51-1.35-15.75,1.21-.27,2.11,.75,3.11,1.26,4.26,2.81,8.51,5.63,12.77,8.44,.78,.36,2.9,2.45,3.25,.88-.62-6.98-1.51-13.95-2.48-20.89-.87-6.95-2.34-13.88-2.89-20.84,0-.09,.08-.25,.15-.25,.92-.23,1.63,.55,2.35,.98,5.46,4,10.89,8,16.27,12.1,.8,.35,1.36,.19,1.15-.92-2.06-12.84-4.87-25.6-6.M 91-38.41,1.54,.24,2.36,1.31,3.53,2.15,5.21,4.21,10.42,8.42,15.64,12.62,.54,.44,.98,1.07,1.95,1,.23-1.39-.44-3-.61-4.44-2.11-10.62-4.97-21.14-6.88-31.78,.37-.88,1.89,.76,2.37,1.03,5.67,4.9,11.32,9.82,16.99,14.72,1.07,.71,1.9,2.16,3.25,2.18v.14l-.1-.08c.34-.86,.06-1.72-.14-2.55-2.57-10.44-5.21-20.87-7.77-31.32,.03-.66,1.16-.22,1.4,.11,7.89,7.2,15.93,14.26,23.34,21.83-.11-.24-.07-.29,.14-.13l-.28,.08Z"/><path class="cls-2" d="M171.16,461.61c10.66,11.81,21.24,23.67,32.27,35.16,.51,.38,1.44,1.01,1.21-.24-1.88-7.82-3.77-M 15.64-5.65-23.46-.38-1.58-.72-3.18-1.04-4.77-.03-.14,.19-.44,.31-.44,.79,0,1.21,.76,1.71,1.24,9.1,9.62,18.46,19.02,27.4,28.78,.01-.25,.07-.28,.17-.1l-.28,.03c1.05-1.03,.12-2.51-.01-3.74-1.99-9.4-4.99-18.84-6.47-28.22,.59,0,.97,.29,1.31,.63,2.27,2.28,4.52,4.56,6.81,6.82,5.68,5.61,11.39,11.2,17.08,16.81,.41,.4,.79,.84,1.53,.88-1.66-11.04-5.5-22.18-7.25-33.37,.35-1.04,2.77,1.77,3.34,2.12,6.24,5.8,12.46,11.61,18.69,17.42,.64,.46,1.26,1.34,2.04,1.47,.25-.17,.57-.38,.43-.72-1.16-5.3-2.35-10.6-3.48-15.91-1.22-5.73-2.39-11M .47-3.55-17.21-.58-3.85,1.1-1.65,2.81-.37,5.66,4.91,11.31,9.84,16.97,14.75,.64,.42,1.38,1.32,2.14,1.36,.16-.13,.38-.31,.36-.45-.53-2.98-1.11-5.96-1.65-8.95-1.66-9.83-3.88-19.62-5.02-29.51,1.6,.14,2.51,1.46,3.74,2.31,4.87,3.87,9.74,7.75,14.62,11.62,.8,.5,1.53,1.47,2.58,1.31,.06,0,.16-.18,.15-.28-.9-8.05-2.54-16.01-3.45-24.06-.6-5.36-1.51-10.7-1.9-16.08,0-.48-.41-1.13,.48-1.37,.58-.16,.96,.29,1.33,.55,4.54,3.21,9.06,6.45,13.6,9.66,1.54,.91,2.75,2.37,4.64,2.51-.83-10.12-1.9-20.21-2.73-30.34-.37-4.62-.65-9.25-.96-13.88M ,0-.57-.24-1.43,.32-1.8,.99-.29,1.85,.73,2.69,1.11,4.37,2.71,8.72,5.43,13.09,8.13,.82,.32,3.03,2.34,3.53,1.12,.13-5.69-.27-11.42-.45-17.11-.44-11.09-.63-22.19-.41-33.28,.01-.27,.62-.5,.94-.35,5.66,2.67,11.2,5.58,16.82,8.34,2.47,1.26,2.05-.33,2.18-2.18,.16-10.34,.77-20.67,1.33-31.01,.54-7.84,.69-15.74,1.73-23.54,.75-.93,2.28,.16,3.21,.38,4.35,1.71,8.69,3.44,13.04,5.15,1.08,.42,2.14,.92,3.36,1.02,.19,.02,.54-.15,.6-.29,.16-.4,.25-.83,.3-1.26,2.58-21.86,4.79-43.93,9.24-65.47-.02,.32-.03,.69,.38,.82,1.23,.4,2.47,.77,3.M 73,1.11,5.17,1.39,10.35,2.75,15.52,4.14,.53,.14,1.03,.17,1.53-.04,0,.01-.07-.09-.07-.09-.75,7.59-2.86,15.1-3.82,22.7-.56,3.63-1.23,7.25-1.84,10.88-1.86,11.08-3.15,22.25-4.76,33.37-.23,2.58-3.25,.42-4.67,.16-4.79-1.71-9.58-3.44-14.37-5.16-1.6-.34-1.28,2.85-1.56,3.88-1.49,18.3-3.07,36.56-3.7,54.92-1.46,.21-2.48-.57-3.73-1.11-4.31-2.01-8.61-4.02-12.91-6.02-.64-.29-1.95-1.04-2.41-.26-.77,16.67-.05,33.39,.06,50.07,.13,2.56-1.45,1.28-2.84,.66-4.52-2.54-9.01-5.11-13.52-7.66-1.31-.71-2.66-1.57-2.55,.74,.72,14.96,2.19,29.88M ,3.24,44.81-.57,.75-1.65-.29-2.26-.55-4.28-2.8-8.54-5.61-12.8-8.41-1.32-.74-2.34-2.02-3.96-2.02,.93,13.64,3.5,27.25,5.23,40.85,.01,.61,.35,1.86-.57,1.86-5.85-3.61-11.1-8.17-16.74-12.13-.71-.43-2.7-2.18-2.55-.28,1.37,8.11,2.72,16.23,4.31,24.3,.87,4.58,1.75,9.15,2.62,13.72-.33,1.49-3.12-1.43-3.79-1.8-5.54-4.4-10.95-8.94-16.55-13.26-.2-.09-.9-.18-.91,.23,1.7,9.39,3.97,18.67,6.01,28,.51,2.54,1.39,5.04,1.63,7.63-.02,.21-.5,.61-.77,.42-.6-.43-1.21-.86-1.76-1.33-5.49-4.74-10.97-9.5-16.46-14.24-.91-.79-1.84-1.57-2.8-2.33-.M 13-.11-.48-.04-.88-.05,1.9,10.87,5.33,21.53,7.78,32.31,.98,3.38-1.76,.64-2.81-.27-6.44-5.95-12.85-11.9-19.29-17.85-.58-.36-1.99-2.28-2.54-1.47,1.55,9.25,4.85,18.3,6.95,27.49,.15,.8,1.86,4.59,.31,4.3-9.13-8.04-17.41-17.01-26.27-25.35-.14-.09-.88-.14-.84,.26,2.23,9.43,4.95,18.75,7.48,28.11,.06,.52,.45,1.54,.07,1.87-.24-.01-.57-.01-.7-.13-9.27-9.03-18.16-18.47-27.01-27.82-.89-.72-1.53-2.11-2.78-2.12-.3,.55,.13,1.84,.21,2.51,2.06,8.74,4.93,17.41,6.59,26.18-.73-.07-1.06-.41-1.39-.76-2.62-2.74-5.28-5.45-7.84-8.22-7.37-7.M 97-14.7-15.96-22.05-23.94-1.16-1-2.15-2.92-3.6-3.35-1.01,.07,.47,3.77,.49,4.58,1.59,7.39,3.96,14.81,5.13,22.2-.22,0-.56,.08-.65-.01-.71-.64-1.42-1.29-2.04-1.99-11.84-13.36-23.76-26.64-35.51-40.08-.42-.33-.85-1.09-1.46-.93-.43,.15-.22,1.1-.22,1.47,1.49,7.85,3.14,15.54,4.5,23.43-1.63-.18-2.18-1.68-3.23-2.69-8.83-10.31-17.69-20.6-26.49-30.92-4.47-5.25-8.83-10.56-13.26-15.84-.86-.78-1.4-2.19-2.7-2.21,.19,6.13,1.46,12.21,2.06,18.32,.59,4.84,.34,5.63-3.03,1.32-15.81-19.27-31.72-38.44-47.34-57.86-.85-1.04-1.23-2.09-1.22-3M .33,.04-6.14,0-12.28-.01-18.42-.02-1.26,.95-.6,1.39-.2,14.57,18.15,29.33,36.13,43.99,54.2,1.14,1.14,1.84,2.94,3.52,3.33-.3-7.25-1.6-14.64-2.2-21.94-.04-.41-.04-.87,.79-.93,12.95,15.46,25.77,31.02,39,46.34,.76,.88,1.57,1.74,2.4,2.59,.11,.11,.45,.09,.68,.08,.05,0,.15-.19,.13-.29-1-6.09-2.12-12.15-3.19-18.22-.11-1.88-2.64-9.9,1.21-5.06,8.31,9.55,16.61,19.1,24.94,28.64,3.16,3.62,6.39,7.2,9.62,10.79,.21,.24,.62,.37,.95,.53,.33,0,.35-.5,.32-.75-1.77-7.95-3.6-15.88-5.26-23.85-.24-1.15-.68-2.33,.06-3.49l-.16-.05Z"/><path cM lass="cls-2" d="M671.72,960.32s.01,.01,.01,.02l-.09,.06,.08-.08Z"/><path class="cls-2" d="M856.06,931.34c-4.06,5.13-8.41,10.02-13.03,14.66-.11-5.19,.51-10.46,.63-15.68,.03-.75-.06-1.5-.12-2.25-.01-.06-.2-.13-.32-.16-.11-.03-.3-.07-.35-.02-.45,.38-.94,.75-1.31,1.18-2.91,3.37-5.79,6.76-8.7,10.12-1.03,.93-1.79,2.08-2.01-.12-.1-4.86,.88-10.08-.07-14.76-.85-.41-1.52,1.19-2.12,1.65-2.62,3.13-5.21,6.28-7.84,9.41-.63,.59-1.27,1.59-2.08,1.88-.2-.1-.51-.23-.53-.37-.28-3.96-.11-7.97-.23-11.94,0-.54-.09-1.07-.17-1.61-.01-.07-.M 16-.18-.25-.19-.25-.01-.63-.04-.73,.07-.66,.68-1.26,1.39-1.87,2.1-3.28,3.67-6.23,7.63-9.71,11.12-.19,.1-.84,.24-.91-.15-.41-3.96-.55-7.96-.92-11.9-1.01-.29-1.48,.59-2.11,1.17-4.6,5.08-9.06,10.24-13.91,15.08-.27,.28-.61,.42-1.03,.31-.48-.13-.44-.5-.46-.8-.06-.86-.08-1.73-.11-2.59-.31-1.57,.41-7.41-1.18-7.71-4.85,3.96-10.35,10.48-15.16,15.03-.64,.51-1.84,2.29-2.42,.83-.26-2.69-.49-5.37-.74-8.06-.08-.58-.09-1.62-.93-1.45-5.25,4.45-10,9.58-15.37,14.08-.79,.5-2.33,2.72-3.1,1.3-.4-2.89-.49-5.83-1.06-8.68-.15-.27-.82-.27-M 1-.18-5.66,4.57-10.74,9.65-16.58,14.12-.8,.43-2.01,2-2.78,.92-.27-2.68-.53-5.36-.89-8.03-.07-.47-.77-.71-1.17-.42-6.21,4.81-12.57,9.43-19.14,13.91-.55,.41-1.05,.71-1.83,.63-.74-2.69-.5-5.57-1.02-8.31-.04-.28-.68-.47-.98-.3-7.44,4.41-14.54,9.36-22.17,13.49-.42,.23-.86,.49-1.5,.35-1.67-2.89-3.35-5.81-5.05-8.73,8.31-4.36,15.88-9.56,23.88-14.17,.62-.23,1.13,.41,1.42,.87,1.29,2.13,2.55,4.28,3.81,6.42,.72,1.02,1.87-.02,2.61-.48,4.86-3.42,9.74-6.8,14.28-10.49,1.04-.85,2.09-1.68,3.17-2.5,.45-.35,.9-.94,1.63-.66,.63,.24,.68M ,.89,.78,1.42,.42,2.23,.83,4.46,1.25,6.77,.41-.05,.91,.01,1.13-.16,5.56-4.14,10.52-8.9,15.69-13.47,.65-.48,2.19-2.48,2.91-1.22,.44,2.45,.9,4.9,1.25,7.35,.75,1.8,2.45-.47,3.28-1.12,4.66-4.33,9.46-8.55,13.77-13.12,.32-.27,.78-.75,1.23-.75,.22,.09,.56,.21,.59,.36,.55,2.75,.91,5.55,1.5,8.29,.05,.17,.34,.31,.56,.42,.82-.19,1.55-1.25,2.2-1.78,3.88-4.14,7.73-8.29,11.6-12.43,.89-.73,1.48-2.1,2.72-2.2,.06,0,.21,.12,.23,.21,.77,3.15,1.33,6.36,1.9,9.55,.02,.07,.15,.15,.25,.2,.26,.14,.53,.13,.73-.07,.76-.75,1.56-1.48,2.24-2.28M ,3.44-3.99,6.84-8,10.25-12,.92-.94,2.6-3.76,3.18-.98,.56,3.08,.79,6.24,1.68,9.26,.05,.14,.33,.26,.53,.34,.68-.02,1.33-1.16,1.82-1.61,2.82-3.55,5.61-7.1,8.43-10.65,.43-.54,.94-1.04,1.43-1.54,.13-.1,.58-.06,.67,.08,1.1,3.88,.99,7.9,1.5,11.86,0,.19,.23,.38,.39,.54,.58,.08,1.23-.89,1.62-1.25,3-3.83,5.96-7.68,8.96-11.52,.19-.24,.57-.39,.88-.55,.08-.04,.36,.02,.37,.07,.77,3.89,.51,7.96,.88,11.91,.05,.75,.16,1.49,.26,2.24,.01,.06,.2,.12,.31,.15,.61,.11,.98-.62,1.38-.96,2.51-3.19,5-6.4,7.5-9.59,.76-.63,2.04-3.56,2.83-1.83,M .36,4.94,.76,9.9,.61,14.85,.07,.32,.19,1.05,.67,.97,.39-.27,.83-.53,1.1-.86,3.12-3.77,6.15-7.59,9.23-11.38,.1-.11,.49-.08,.74-.07,.09,0,.24,.12,.25,.19,.09,1.08,.22,2.15,.22,3.22,.08,5.05-.35,10.12,.03,15.15Z"/><path class="cls-2" d="M906.2,1224.04c.05,0,.11-.02,.16-.03-.02,.05-.04,.1-.06,.15l-.1-.12Z"/><path class="cls-2" d="M945.14,1096.22c-.05,.02-.1,.04-.15,.05,.01-.06,.03-.12,.04-.18l.11,.13Z"/><path class="cls-2" d="M951.59,1293.34h-.17s.01-.05,.02-.07l.15,.07Z"/><path class="cls-2" d="M926.83,1293c-.17,.72-.M 9,2.03,.26,2.23,8.13-.26,16.19-1.68,24.33-1.89-10.75,31.3-22.93,62.14-35.81,92.63-.37,.13-.61,.29-.86,.29-8.77-.02-17.51,.21-26.29,0-.35-1.37,.61-2.51,1.05-3.78,4.96-11.26,10.05-22.49,14.87-33.79,4.55-10.69,8.97-21.42,13.28-32.18,2.58-6.46,5-12.95,7.53-19.42,.6-1.33-.3-1.54-1.44-1.42-7.36,.67-14.71,1.4-22.07,2.05-1.9,.06-.56-1.97-.24-2.89,2.38-5.83,4.79-11.65,7.12-17.49,7.48-18.65,14.38-37.42,20.91-56.31,.3-.93,.18-1.62-1.72-1.24-7.12,1.41-14.25,2.83-21.39,4.22,7.94-22.07,16.25-44.28,22.4-66.85-.34-.89-2.09,0-2.79,M .07-5.95,1.57-11.74,3.97-17.76,5.11-.51-.63-.17-1.24,.03-1.86,2.11-6.56,4.26-13.12,6.31-19.7,3.06-9.81,5.8-19.69,8.61-29.55,.54-1.89,.98-3.8,1.42-5.7,.06-.27-.07-.73-.31-.84-.82-.26-1.82,.35-2.6,.62-5.05,2.04-10.05,4.18-15.12,6.16-.22,.08-.69,.11-.75,.03-.53-.66-.26-1.42-.05-2.15,4.41-14.74,8.13-29.6,11.68-44.55,.09-.92,1.25-3.64-.68-2.99-4.83,2.29-9.48,4.93-14.27,7.34-.48,.18-2.23,1.27-2.3,.39,2.52-10.88,5.22-21.74,7.47-32.69,.58-3.29,1.62-6.56,1.72-9.89-.2-.94-2.08,.54-2.58,.72-4.39,2.67-8.57,5.64-13.06,8.13-.16,M .05-.57-.12-.58-.32,1.03-8.55,3.4-16.99,4.9-25.49,.53-3.84,1.45-7.68,1.51-11.55-.71-.6-1.6,.48-2.24,.79-4.1,2.93-7.9,6.28-12.18,8.94-.17,.1-.57-.04-.58-.26,.88-7.69,2.86-15.31,3.69-23.04,.32-2.98,1.07-5.96,.91-8.98,0-.06-.16-.14-.27-.17-.72-.16-1.29,.72-1.87,1.04-3.14,2.67-6.26,5.35-9.39,8.02-.56,.34-2.51,2.52-2.71,.88,.72-5.14,1.56-10.27,2.28-15.41,5.1-5.46,9.9-11.18,14.4-17.14-.54,6.61-.97,13.21-1.6,19.8,.36,1.27,2.03-.58,2.59-.94,2.86-2.44,5.71-4.88,8.57-7.32,.77-.5,1.43-1.54,2.46-1.35,.08,.01,.19,.15,.19,.23-.0M 6,1.39-.09,2.79-.21,4.18-.92,7.94-1.29,15.91-2.78,23.79-.3,1.49-.38,2.99-.55,4.49-.01,.4,.69,.37,.88,.29,4.52-3.02,8.81-6.33,13.26-9.46,.37-.14,1.02-.13,1,.52-.68,7.3-1.67,14.59-2.84,21.84-.76,5.12-2.16,10.18-2.31,15.36,.54,.72,1.66-.23,2.27-.48,3.74-2.3,7.45-4.62,11.18-6.93,.77-.4,1.5-1.08,2.44-.88-.44,7.44-2.13,14.98-3.35,22.42-1.13,5.96-2.42,11.9-3.55,17.85-.16,1.26-.85,2.52-.51,3.78,.94,.07,1.57-.37,2.25-.71,4.82-2.35,9.55-4.9,14.44-7.12,1.36-.16,.67,1.63,.63,2.4-1.29,5.94-2.39,11.9-3.63,17.84-2.08,9.11-4.04,18M .27-6.4,27.29-.05,.9-1.4,3.6,.15,3.41,6.34-2.24,12.45-4.98,18.81-7.15-3.8,16.48-7.8,32.85-12.59,49.11-.89,3.04-1.73,6.09-2.58,9.13-.12,.42-.17,.85,.36,1.3,6.09-1.48,12.14-3.35,18.2-4.98,.7-.14,2.09-.74,2.3,.26-4.53,17.51-9.83,34.85-15.31,52.12-1.42,5.14-3.81,10.08-4.79,15.31,.36,.84,1.78,.32,2.49,.31,6.51-1.21,13.11-2.43,19.59-3.57,.23,.26,.51,.43,.51,.6-.02,.53-.06,1.07-.22,1.58-1.96,5.82-3.61,11.7-5.57,17.51-6.58,19.45-13.35,38.8-20.55,58.05Z"/><path class="cls-2" d="M589.21,1154.29c-.11-.59,.35-1.01,.73-1.45,3.1M 4-3.62,6.3-7.23,9.44-10.86,2.09-2.5,4.32-4.89,6.21-7.53,.18-.24,.14-.42-.13-.52-12.94,3.6-25.52,9.24-38.66,12.68-1.12-.09,.19-1.29,.45-1.76,3.98-4.86,7.98-9.7,11.95-14.56,.51-.62,.92-1.3,1.36-1.96,.03-.05-.06-.18-.13-.23-.45-.28-1.02,.06-1.49,.15-2.24,.72-4.49,1.44-6.72,2.18-10.17,3.41-20.57,6.33-30.86,9.49-.73,.22-1.53,.32-2.3,.45-.07,.01-.27-.13-.27-.18,3.54-5.42,8.13-10.36,12-15.64,.36-.46,.64-.95,.29-1.49,0,.01,.14,.25,.14,.25l-.13-.16c-14.65,3.47-29.25,8.91-44.08,11.12-.07-.07-.13-.22-.08-.29,.35-.57,.68-1.15,M 1.09-1.69,2.95-3.86,5.91-7.71,8.86-11.56,.32-.57,1.24-1.43,1.12-2.02-.17-.13-.43-.33-.58-.3-1.95,.41-3.9,.84-5.83,1.3-13.14,3.19-26.45,5.84-39.78,8.48-.51,.1-1.05,.14-1.59,.15-.33,0-.56-.19-.45-.38,2.6-4.43,5.96-8.41,8.86-12.65,.46-.64,1.08-1.25,1.08-2.04-.46-.31-.98-.27-1.5-.18-3.95,.67-7.9,1.33-11.85,2.01-8.15,1.42-16.33,2.74-24.57,3.79-4.89,.38-9.8,1.95-14.68,1.72-.32-.62,.12-1.07,.41-1.52,2.21-3.45,4.44-6.89,6.65-10.33,.39-.84,2.26-2.66,.47-2.9-15.77,1.47-31.53,3.24-47.38,4-3.22,.12-6.43,.59-9.66,.5-1.25-.31-.1M 3-1.5,.14-2.19,2.13-4.06,4.78-7.9,6.57-12.12-.12-.79-1.34-.54-1.94-.62-21.68,.64-43.35,.59-65.04,.04l.15,.09c2.43-5.2,4.86-10.4,7.29-15.59l-.11,.07c22.41,.6,44.88,.7,67.3,.63,.45,.66,.11,1.16-.14,1.64-1.55,2.98-3.12,5.95-4.68,8.93-.28,.98-2.77,3.75-.78,3.88,14.79-.46,29.54-1.62,44.27-2.88,4.41-.39,8.8-.97,13.22-1.27,.34-.03,.75,.42,.63,.67-2.23,4.42-5.14,8.49-7.47,12.86-.2,1.29,2.16,.57,2.91,.63,16.49-1.97,32.81-4.69,49.17-7.45,.2-.03,.47,.14,.67,.25,.13,.61-.68,1.48-.93,2.07-2.53,4.02-5.38,7.88-7.7,12.02,.89,.46,1M .68,.26,2.46,.1,4.57-.91,9.13-1.86,13.7-2.76,9.67-1.91,19.19-4.23,28.76-6.42,.9-.21,1.82-.39,2.74-.53,.16-.02,.4,.19,.55,.33,.12,.62-.75,1.45-1.05,2.04-2.33,3.27-4.68,6.54-7,9.81-1.53,2.28-2.71,3.44,1.12,2.55,6.52-1.71,13.02-3.45,19.55-5.14,6.02-1.56,11.91-3.39,17.85-5.12,1.3-.2,2.9-1.24,4.14-.72,.06,.03,.09,.2,.05,.28-.33,.58-.62,1.19-1.02,1.74-2.85,3.9-5.73,7.79-8.59,11.69-1.71,2.35-1.2,2.35,1.32,1.69,9.5-2.72,18.85-5.77,28.15-8.9,3.35-1.13,6.72-2.21,10.08-3.31,.3-.1,.57-.09,.69,.15,.27,.55-.23,1.01-.53,1.44-4.01M ,5.06-7.57,10.55-11.88,15.35,.16,.14,.21,.3,.43,.29l-.52-.31c2.13,.97,4.62-.91,6.74-1.36,10.97-3.62,21.79-8.17,32.65-11.65,.9,.25-1.32,2.53-1.57,3.08-4.25,5.18-8.03,10.81-12.6,15.71,0,0,.17,.08,.17,.08l-.09-.15c1.01,.81,2.28,0,3.32-.34,10.58-4.02,21.25-7.9,31.6-12.3,.26-.09,1.22-.37,1.29,.06-3.97,6.79-9.14,12.97-13.93,19.27-2.39,3.06,5.41-1.06,6.25-1.19,6.49-2.63,12.89-5.39,19.21-8.27,1.23-.37,2.68-1.61,3.94-1.22,.21,.38-.45,1.05-.64,1.42-3.54,4.83-7.08,9.66-10.63,14.49-1.5,2.04-3.04,4.07-4.54,6.11-.53,.97-.25,1.33M ,1.21,.76,8.71-3.62,17.32-7.45,26.01-11.11,.39-.13,1.04,.11,.77,.64-4.35,6.1-9.11,11.95-13.62,17.95-1.76,2.29-3.56,4.57-5.31,6.87-.29,.48,.29,.82,.73,.67,8.07-3.16,16.14-6.46,24.01-9.99,.84-.26,2.08-1.04,2.89-.9,.09,.17,.23,.41,.15,.54-.5,.76-1.05,1.5-1.61,2.24-6.15,8.69-15.4,18.96-20.87,27.13,.07,.08,.23,.19,.3,.17,.75-.23,1.52-.44,2.24-.72,7.24-2.87,14.47-5.76,21.7-8.63,1.11-.27,2.19-1.31,3.3-.68-8.62,11.65-18.25,22.65-27.31,33.93,1.13,.67,2.59-.36,3.79-.63,7.13-2.54,14.25-5.11,21.38-7.65,.59-.13,1.3-.53,1.88-.26M ,.08,.05,.17,.19,.13,.24-.37,.57-.72,1.15-1.15,1.68-10.08,12.51-20.66,24.79-31.3,36.9-1.05,1.56,.56,.96,1.5,.84,5.9-1.51,11.79-3.04,17.68-4.55,1.05-.14,2.49-.88,3.45-.6,.07,.05,.13,.18,.09,.24-.21,.39-.4,.8-.7,1.15-4.1,4.81-8.13,9.65-12.33,14.39-8.09,9.15-16.26,18.24-24.4,27.36-2.6,2.66-1.52,2.71,1.57,2.2,6.7-1.13,13.34-2.76,20.07-3.62,1.39,.17-.76,2.02-1.11,2.57-13.97,16.12-28.65,31.83-43.51,47.41-.51,.71-1.66,1.16-1.43,2.18,.9,.42,1.85,.18,2.75,.09,5.62-.55,11.22-1.14,16.84-1.69,1.46-.14,2.95-.19,4.42-.26,.33-.02M ,.51,.14,.51,.39-16.91,20.3-36.55,39.27-55.21,58.47-.61,.67-1.54,.86-2.48,.85-7.82,.04-15.63,.08-23.45,.11-.77,.01-1.87-.08-1.72-.85,18.36-18.02,37.14-35.65,54.89-54.27,.44-.6,1.39-1.12,1.1-1.94-1.34-.29-2.95,.05-4.36,.07-5.22,.46-10.43,1.03-15.64,1.53-1.34,.11-2.68,.17-4.02,.23-.33,.02-.51-.15-.5-.4,11.19-12.17,23.76-23.66,35.02-35.85,3.76-3.94,7.49-7.9,11.23-11.85,.56-.56,1.14-1.1,1.16-1.92-7.9,.6-15.72,2.92-23.66,3.76-1.2-.12,.96-1.88,1.21-2.31,13.04-13.6,26.3-26.93,38.41-41.16,.38-1.08-2.86,.26-3.4,.28-7.9,2.11M -15.68,4.69-23.65,6.49-1.14-.12,.6-1.58,.86-2.03,4.58-4.93,9.26-9.8,13.75-14.78,5.83-6.46,11.52-13.01,17.26-19.53,2.21-2.66-1.48-.92-2.72-.63-7.11,2.32-14.21,4.64-21.31,6.96-.87,.28-1.7,.67-2.7,.52l-.17-.14c.11-.3,.12-.66,.33-.9,3.73-4.23,7.51-8.42,11.21-12.66,5.01-5.74,9.97-11.51,14.95-17.27,.24-.39,.92-.98,.75-1.4-1.31-.4-2.75,.69-4.05,.98-6.99,2.53-13.98,5.06-20.97,7.59-1.15,.28-2.21,1.13-3.41,.69,2.48-3.51,5.58-6.57,8.27-9.92,4.9-6.17,10.52-11.91,14.98-18.35,.02-.04-.21-.22-.27-.21-.63,.14-1.28,.26-1.86,.49-8.6M 1,3.35-17.15,6.82-25.88,9.87-.58,.11-1.35,.07-.67-.82,6.49-7.78,13.05-15.51,19.2-23.54,.26-.42-.04-1.02-.63-.71-9.19,3.6-18.38,7.19-27.72,10.54-1.22,.44-2.49,.82-3.74,1.21-.14,.02-.5-.23-.44-.41,1.84-2.82,4.46-5.1,6.58-7.72,3.77-4.33,7.5-8.68,11.24-13.03,.38-.44,.68-.92,1.01-1.39,.04-.06,.01-.23-.04-.25-.23-.07-.49-.16-.73-.15-7.38,2.53-14.66,5.44-22.03,8.05-4.29,1.56-8.63,3.02-12.95,4.53-.62,.22-1.26,.38-1.94,.15l.09,.06Z"/><path class="cls-2" d="M643.47,973.96s-.06,.03-.09,.04c-.01-.03-.02-.06-.04-.09l.13,.05Z"/>M <path class="cls-2" d="M647.72,982.37c-3.81-1.71-7.55-3.54-11.22-5.51,2.3-.94,4.6-1.89,6.88-2.86,1.44,2.79,2.88,5.59,4.34,8.37Z"/><path class="cls-2" d="M830.24,943.42c-.55-.45-1.12,.15-1.53,.55-3.63,4.12-7.61,8.02-11.03,12.28-.53-.52-.61-1.14-.57-1.79,.26-4.84,.78-9.67,.69-14.52-.63-.53-1.3,.39-1.76,.77-3.87,3.98-7.37,8.33-11.48,12.07-.3,.15-.91,.05-.86-.34-.07-2.26,.31-4.51,.4-6.77,.09-2.05,.11-4.09,.13-6.14,0-.17-.22-.35-.38-.5-.19-.18-.68-.02-1.01,.3-3.04,3.16-5.97,6.39-9.07,9.51-2.25,2.28-4.65,4.47-6.98,6.69-.M 25,.29-.81,.18-.92-.17,0-3.87,.54-7.75,.01-11.61-.02-.16-.26-.38-.46-.43-.97-.03-1.55,1.1-2.25,1.62-4.88,4.75-9.61,9.63-14.63,14.22-.5,.49-1.61,.71-1.47-.31-.08-3.34,.12-6.68-.16-10.01-.02-.15-.33-.29-.54-.4-.77,.13-1.38,1.02-2.02,1.46-5.62,4.74-10.87,10.03-16.68,14.49-.86,.15-.83-.86-.88-1.45-.03-2.89,.11-5.81-.03-8.69-.98-.46-1.58,.41-2.29,.88-3.54,2.97-7.02,5.97-10.59,8.9-2.26,1.85-4.64,3.6-6.98,5.39-.27,.2-.66,.49-1.03,.2-.24-.2-.42-.55-.41-.83,.03-2.48,.12-4.95,.15-7.43-.14-2.67-1.96-.79-3.16-.03-5.34,4.12-10.M 96,7.98-16.6,11.83-.96,.49-1.77,1.6-2.93,1.53-.52-.11-.49-.47-.5-.77-.03-2.16-.04-4.31-.08-6.46,.02-2.8-.85-2.17-2.73-1.04-7.09,4.3-13.97,8.94-21.34,12.78-.45,.25-1.15-.05-1.17-.5-.11-2.69-.17-5.38-.48-8.05-.02-.25-.66-.5-.93-.36-8.56,4.47-17.11,9.1-26.11,12.89,4.01,1.73,8.09,3.32,12.23,4.75,4.78-2.32,9.34-5.02,14.18-7.2,1.89-.24,.07,7.63,.54,9.23,0,.28,.61,.53,.91,.36,7.76-3.95,15.05-8.66,22.46-13.18,.84-.56,2.34-1.47,2.33,.26-.09,2.9-.72,5.81-.45,8.7,.5,.7,1.4-.09,1.94-.36,6.67-4.39,13.21-8.79,19.5-13.59,.45-.36,M 1.5-.97,1.89-.25,.35,3.34-.35,6.66-.39,9.98,.59,.51,1.41-.25,1.94-.56,4.69-3.4,9.3-6.88,13.66-10.55,1.48-1.25,2.98-2.49,4.49-3.72,.38-.26,.81-.65,1.32-.63,1.04-.07,.28,2.57,.38,3.28-.25,2.58-.54,5.15-.8,7.72-.02,.43,.65,.38,.87,.32,6.27-4.78,12.13-10.11,18.24-15.1,.6-.55,1.61-1.38,1.86-.12-.26,3.87-.79,7.72-.89,11.6,.05,.1,.57,.22,.67,.15,.59-.43,1.22-.84,1.74-1.32,4.94-4.56,9.86-9.13,14.8-13.69,.81-.61,1.37-1.64,2.56-1.34-.37,4.5-.52,9.02-1.29,13.5-.02,.13,.22,.31,.39,.44,.68,0,1.26-.8,1.81-1.15,5-4.38,9.62-9.01,1M 4.2-13.67,.55-.42,2.29-2.7,2.73-1.4,.07,3.67-.66,7.29-1.09,10.93-.16,1.28-.28,2.57-.41,3.85-.02,.27,.15,.42,.46,.42,.71-.01,1.22-.8,1.74-1.2,3.38-3.36,6.73-6.73,10.11-10.09,.53-.38,1.03-1.2,1.75-1.18,.51,.03,.39,.72,.41,1.07-.41,3.14-.81,6.28-1.29,9.41,4.86-3.19,9.53-6.62,14.02-10.26,.5-5.03,1.7-10.13,1.14-15.17Zm-12.59,12.88s-.04-.07-.04-.09c.02,0,.04,.04,.06,.05-.01,.01-.01,.03-.02,.04Z"/><path class="cls-2" d="M906.3,1224.16c-.05,.01-.11,.02-.16,.03l.06-.15,.1,.12Z"/><path class="cls-2" d="M883.55,1226.6c-.64,1.M 56-.8,2.23,1.22,1.91,7.11-1.51,14.24-2.9,21.37-4.32-9.29,25.69-20.37,50.72-31.19,75.8,.68,.49,1.36,.41,2,.35,7.22-.75,14.42-1.53,21.63-2.28,.97-.08,1.31,.61,1,1.31-12.13,29.38-25.61,58.22-39.63,86.76-8.94,.46-18.02,.31-26.97,.09-.28-.49-.25-.9-.03-1.31,1.07-2.09,2.11-4.2,3.22-6.28,13.19-25.48,26.59-50.9,37.7-77.24,.02-.14-.29-.45-.43-.45-1.74,.07-3.49,.1-5.21,.28-4.94,.52-9.87,1.11-14.8,1.64-1.3,.03-2.73,.47-3.94-.06-.17-.79,.29-1.47,.63-2.17,3.33-6.93,6.72-13.84,9.98-20.8,7.56-15.99,14.54-32.13,21.4-48.39,1.11-2.1M 8-.03-2.36-1.95-1.84-6.11,1.3-12.22,2.6-18.33,3.9-1.7,.33-2.29,.23-1.5-1.69,2.95-6.7,5.99-13.38,8.84-20.1,5.7-13.66,11.65-27.21,16.41-41.19,.02-.1-.37-.39-.5-.37-.78,.15-1.56,.33-2.31,.56-5.76,1.78-11.46,3.8-17.26,5.45-1.29,.01-.45-1.42-.27-2.12,3.09-7.8,6.27-15.57,9.26-23.39,3.64-9.58,7.29-19.1,10.24-28.86-.44-.76-1.73,.04-2.37,.19-5.51,2.24-10.9,4.75-16.47,6.84-1.25,.13-.18-1.84-.03-2.46,4.02-10.39,7.63-20.86,11.08-31.38,1.27-3.85,2.5-7.71,3.72-11.56,.13-.73,.47-1.48,.14-1.88-.98-.45-1.87,.53-2.77,.85-4.14,2.21-8M .29,4.42-12.43,6.63-.59,.22-2.23,1.51-2.56,.51,3.93-13.08,8.46-25.99,11.96-39.19,.74-2.58-.78-1.58-2.27-.68-4.57,2.85-8.98,5.92-13.67,8.57-1.83,.25,.65-4.8,.81-5.84,1.96-5.71,3.25-11.54,4.82-17.33,1-3.68,2.03-7.36,3.03-11.03,.12-.42,.17-.85,.23-1.28,0-.09-.07-.27-.15-.28-1-.3-1.75,.78-2.56,1.19-3.58,2.61-7.16,5.23-10.74,7.84-.68,.58-1.41,1.02-2.34,1.08-.33-1.13,.42-2.33,.63-3.47,1.86-6.06,3.17-12.22,4.7-18.34,.68-2.75,1.29-5.5,1.91-8.25,.09-.38,.42-.89-.25-1.09-.6-.19-.95,.29-1.31,.58-3.69,2.99-7.37,5.99-11.05,8.99M -.69,.48-1.25,1.32-2.18,1.21-.06,0-.18-.17-.17-.26,.09-.74,.12-1.5,.34-2.23,1.23-4.21,2.11-8.47,2.97-12.73,5.21-3.82,10.23-7.87,15.05-12.14-.89,4.64-1.69,9.29-2.46,13.96-.02,.08,.09,.27,.16,.27,1.05,.2,1.7-.86,2.49-1.36,3.14-2.67,6.28-5.34,9.42-8,.78-.49,1.44-1.56,2.47-1.32,.07,.01,.16,.19,.15,.28-.38,2.35-.71,4.71-1.19,7.04-1.55,7.97-3.52,15.9-4.92,23.9,.14,1.78,3.3-1.2,4-1.61,3.5-2.52,6.79-5.31,10.43-7.63,.16-.09,.5,.01,.81,.02,.28,1.19-.06,2.35-.33,3.51-2.25,10.92-5.3,21.78-7.56,32.67,.38,.81,2.02-.64,2.59-.84,4M .03-2.53,8.04-5.07,12.06-7.61,.52-.33,1.04-.7,1.93-.59-1.73,9.57-4.62,18.97-7.07,28.43-1.13,4.21-2.41,8.39-3.62,12.59-.05,.37-.26,.94,.06,1.23,.72,.07,1.5-.44,2.16-.7,3.72-1.94,7.43-3.91,11.15-5.86,1.36-.57,2.59-1.83,4.15-1.68,.47,.65-.09,1.74-.2,2.48-3.12,10.82-6.15,21.64-9.58,32.37-1.28,4.07-2.62,8.13-3.92,12.2-.1,.3-.1,.63-.14,.95-.04,.25,.57,.57,.88,.46,5.09-1.89,10.03-4.18,15.06-6.22,.83-.35,1.7-.64,2.56-.95,.31-.11,.54-.04,.65,.19,.18,.29,.11,.62,.04,.94-2.94,9.5-5.9,19.01-9.19,28.45-2.67,7.67-5.13,15.39-8.21M ,22.97-.42,1.02-.67,2.08-.99,3.12-.09,.31,.35,.69,.69,.61,5.98-1.53,11.8-3.63,17.74-5.36,1.46-.36,3.07-.93,2.2,1.3-7,20.76-14.8,41.25-23.12,61.54Z"/><path class="cls-2" d="M912.65,421.86c.06-.01,.11-.02,.17-.03-.02,.04-.03,.08-.04,.12l-.13-.09Z"/><path class="cls-2" d="M964.53,416.03l-.15,.12,.09-.12h.06Z"/><path class="cls-2" d="M968.57,404.41c-.1-1.63-7.33,0-8.71-.05-14.04,1.11-27.95,3.18-41.89,5.17-.6,.08-1.1-.31-.95-.74,.94-2.58,1.96-5.15,2.82-7.75,.33-1.01,1.19-1.96,.78-3.09-.13-.39-.92-.34-4.21,.29-.65,.13-1.M 31,.26-1.96,.38-13.11,2.32-26.04,5.34-39.02,8.25-1.26,.03-.54-1.45-.37-2.13,1.08-2.78,2.2-5.54,3.29-8.31,.26-.65,.35-1.01-.32-1.48-13.72,3.51-27.38,7.64-40.84,11.91-.47-.44-.52-.86-.35-1.28,1.09-2.77,2.2-5.54,3.29-8.31,.17-.73,1.35-2.43-.04-2.45-11.26,3.34-22.23,7.72-33.11,11.9-1.21,.48-2.41,.96-3.64,1.41-.16,.05-.46-.1-.67-.19-.09-.04-.16-.2-.14-.28,.17-.63,.31-1.27,.55-1.88,1.15-2.98,2.32-5.96,3.48-8.94,.16-.41,.2-.82-.31-1.2-11.21,3.95-21.89,9.43-32.61,14.02-1.59,.05,2.4-8.38,2.68-9.69,.33-.93,.64-1.86,.94-2.79,M 0-.18-.38-.39-.57-.34-8.22,3.65-16.13,8.21-24,12.47-.63,.2-3.14,2.05-3.29,1.11,.45-3.66,2.46-7.02,3.53-10.55,.31-.82,.56-1.66,.81-2.49,.03-.08-.08-.25-.16-.27-.65-.28-1.19,.13-1.73,.43-8.31,4.35-15.88,9.62-23.9,14.24-.46-.47-.36-.9-.21-1.31,1.36-3.82,2.55-7.69,4.24-11.44,.21-.8,1.18-2.01,.54-2.69-.03-.04-.29-.02-.38,.04-7.42,4.41-14.67,9.09-21.93,13.74-.86,.39-1.63,1.36-2.65,1.11-.07-.02-.15-.2-.12-.29,1.43-4.5,3.44-8.82,5.08-13.25,.37-.93,.72-1.85,1.03-2.78,.05-.15-.16-.35-.27-.57-5.95,3.12-11.03,7.56-16.66,11.22-M 1.83,1.27-3.66,2.54-5.49,3.81-.4,.28-.81,.54-1.54,.48,1.34-5.58,3.83-10.96,6.04-16.34,.37-.8,.62-1.64,.91-2.46,.02-.07-.11-.22-.21-.27-.59-.04-1.18,.48-1.68,.74-6.5,4.52-13,9.05-19.51,13.57-.59,.41-1.05,1-1.97,1.02-.7-.76,.11-1.41,.29-2.08,.25-.95,.72-1.85,1.1-2.77,2.06-5.01,4.12-10.02,6.17-15.03,.2-.49,.62-.98,.25-1.54-1.04,.05-1.62,.69-2.3,1.17-6.64,4.53-13,9.46-19.78,13.77-1.97,.9,3.88-11.46,4.22-12.59,1.61-3.76,3.35-7.5,5.01-11.25,.08-.18,0-.41-.05-.62-.04-.17-.59-.09-.99,.16-1.05,.68-2.1,1.36-3.13,2.04-3.84,2.M 54-7.67,5.09-11.51,7.63-.51,.34-.99,.73-1.73,.7-.36-.62-.06-1.21,.19-1.78,2.53-5.68,5.05-11.37,7.63-17.03,1.25-2.73,2.63-5.42,3.95-8.13,.24-.48,.18-.91-.08-.88-.91,.05-1.65,.55-2.39,1.01-4.81,2.95-9.6,5.92-14.42,8.86-.43,.24-1.04,.22-.92-.43,4.27-9.9,8.8-19.65,13.72-29.33,.31-.6,.54-1.22,.78-1.83,.03-.07-.08-.2-.17-.26-.63-.22-1.49,.45-2.09,.68-4.64,2.59-9.27,5.19-13.91,7.79-.57,.18-1.94,1.34-2.28,.5,4.86-11.61,11.09-22.64,16.85-33.89,.37-.69,.67-1.4,.98-2.11,.03-.07-.06-.2-.14-.28-.06-.07-.21-.16-.26-.14-.61,.22-1M .24,.43-1.81,.71-5.52,2.61-10.98,5.46-16.56,7.93-.69-.57-.4-1.07-.15-1.56,2.45-4.78,4.87-9.57,7.36-14.34,4.15-7.95,8.47-15.84,12.94-23.68,.38-.68,.72-1.38,1.02-2.09,.05-.14-.19-.36-.36-.65-5.92,2.29-11.76,4.78-17.65,7.15-.69,.18-1.49,.72-2.19,.51,6.54-15.02,16.62-30.36,24.95-45.04,.34-.58,.75-1.15,1.02-1.75,.2-.46,.91-.95,.27-1.44-.44-.34-1,.04-1.48,.16-6.03,1.86-12.01,3.82-18.03,5.7-1.92,.35-2.21,.47-1.32-1.54,9.98-18.15,21.13-35.57,31.88-53.31,.22-.72-1.17-.44-1.56-.43-4.3,.91-8.58,1.84-12.87,2.77-2.34,.51-4.67,1M .04-7.01,1.55-.53,.11-1.06,.09-1.67-.22,12.21-21.61,26.32-42.23,39.85-63.08,.24-1.21-3.02-.46-3.8-.52-6.78,.56-13.62,1.85-20.37,2.09-.19-.09-.44-.36-.39-.47,.38-.8,.78-1.59,1.27-2.35,14.05-21.69,28.19-43.2,43.22-64.31,1.36-2.1,3.13-4,4.22-6.24-.1-.81-1.32-.57-1.93-.65-6.87,0-13.75,.01-20.62,.02-1.64,.17-4.13-.59-5.18,.97-16.11,24.9-32.94,49.66-46.95,75.69,1.88,.78,3.74-.18,5.66-.22,5.73-.65,11.47-1.29,17.21-1.92,.57-.05,1.95-.24,1.74,.64-6.3,10.62-12.89,21.08-19.14,31.71-6.28,10.6-12.36,21.29-18.3,32.02-.22,.65-1.1M 6,1.41-.58,2.06,.92,.47,2.11-.18,3.1-.27,5.06-1.11,10.12-2.24,15.18-3.35,1.64-.25,3.07-1.04,4.74-.48-10.55,18.49-21.19,36.95-30.69,55.97-.11,.36-.63,1.34-.08,1.45,6-1.37,11.75-3.71,17.66-5.43,.96-.3,1.86-.91,3.03-.59,.51,.14,.43,.48-.78,2.64-8.46,15.32-16.53,30.79-23.91,46.6,0,.25,.22,.76,.6,.6,6.43-2.29,12.64-5.3,19.01-7.73,.56,.44,.42,.83,.21,1.24-6.95,13.83-14.16,27.65-20.04,41.92,0,.22,.47,.64,.77,.48,5.31-2.52,10.47-5.3,15.73-7.92,.64-.21,1.41-.82,2.09-.64,.09,.08,.21,.21,.18,.28-.29,.82-.56,1.66-.94,2.46-3,6.M 45-6.09,12.89-9.04,19.36-2.15,5.19-4.85,10.23-6.48,15.56,0,.05,.21,.19,.27,.17,.48-.17,1-.3,1.42-.55,4.58-2.65,9.14-5.33,13.72-7.99,.69-.27,1.64-1.08,2.37-.93,.42,.29,0,.82-.08,1.2-2.96,6.93-5.94,13.85-8.9,20.78-1.4,3.26-2.76,6.52-4.13,9.79-.18,.41-.24,.83,.15,1.43,5.77-3.42,10.87-7.43,16.78-10.62,.6,.64,.08,1.17-.14,1.82-3.7,8.43-6.93,16.99-10.26,25.52-.13,.46-.64,1.69,.23,1.58,5.49-3.12,10.23-7.4,15.64-10.67,.36-.23,.65,.15,.68,.43-2.9,7.62-5.69,15.25-8.43,22.92-.13,.57-.61,1.31,.08,1.69,5.44-3.12,10.23-7.77,15.6M 6-11.08,.1-.06,.35-.1,.38-.06,.13,.15,.33,.36,.29,.5-.31,.94-.67,1.86-1.03,2.79-2.06,5.24-3.98,10.51-5.64,15.83-.26,.84-.5,1.68-.69,2.53-.03,.11,.24,.3,.41,.41,.8-.07,1.48-.93,2.17-1.34,5.54-4.26,11.06-8.52,16.6-12.78,.8-.47,1.61-1.39,2.53-1.51,.52,.4,.26,.94,.09,1.45-1.9,5.61-3.8,11.22-5.7,16.83-.14,.4-.34,.81-.01,1.19,.77-.02,1.2-.47,1.68-.84,1.84-1.42,3.68-2.84,5.48-4.29,4.29-3.44,8.88-6.61,13.41-9.83,.69-.54,2.4-1.7,1.92,.16-1.77,4.75-3.46,9.51-4.82,14.34-.1,.6-.54,1.34,.16,1.71,.83-.02,1.78-1.08,2.53-1.49,5.88M -4.28,11.74-8.58,17.62-12.86,.8-.43,1.55-1.43,2.54-1.19,.07,.02,.14,.2,.12,.29-1.41,4.71-2.93,9.4-4.35,14.1-.08,.27,.11,.59,.17,.88,.62-.19,1.23-.35,1.71-.78,6.55-4.83,13.6-9.17,20.5-13.65,.95-.53,2.82-1.77,1.96,.41-1.16,4.08-3.1,8.01-3.62,12.22,.28,1.21,3.06-1.22,3.75-1.51,6.78-4.51,13.63-8.86,20.73-12.9,.16-.09,.48-.03,.72,0,.08,.02,.2,.19,.18,.28-.92,3.81-2.12,7.56-3.18,11.33-.12,.42-.23,.82,.12,1.29,8.58-4.46,16.89-9.62,25.68-13.96,2.14-1.25,1.21,1.32,.93,2.4-.82,2.94-1.66,5.88-2.47,8.82-.03,.13,.24,.33,.41,.46M ,.84,.05,1.69-.67,2.47-.96,8.84-4.55,18-8.67,27.4-12.44,.42-.17,1.65-.64,1.81-.24,.06,.2,.18,.42,.12,.6-.76,2.51-1.56,5.02-2.31,7.53-.28,.94-.46,1.9-.67,2.85-.06,.26,.55,.59,.85,.48,10.7-4.43,21.57-8.41,32.51-12.27,1.31-.31,4.95-2.35,3.81,.59-.88,3.13-2.53,6.14-2.83,9.38,0,.13,.39,.39,.51,.36,1.53-.4,3.07-.79,4.56-1.28,11.48-3.71,23.14-7.12,34.94-10.06,.51-.1,1.08,.34,.95,.76-.62,1.98-1.26,3.96-1.87,5.95-.38,1.25-.72,2.51-1.06,3.77-.12,.48,.35,.85,.9,.73,13.62-3.17,27.21-6.13,41.05-8.48,.91-.15,1.86-.21,2.8-.25,.17M ,0,.51,.27,.52,.42-.52,3.8-2.21,7.46-3.17,11.19,7.41-1.35,14.91-2.14,22.39-3.09,10.26-5.6,21.41-9.52,32.71-11.84h.01c.25-.82,.66-1.63,.64-2.49Zm-318.22-18.56c0-.13,.19-.21,.33-.11-.09,.2-.2,.24-.33,.11Z"/><path class="cls-2" d="M638.16,415.14c.86,.8,.21,1.85,0,2.78-1.94,6.6-3.88,13.2-5.8,19.8-.04,.14,.15,.34,.27,.49,.32,.05,.76-.25,1.03-.43,4.12-3.4,8.18-6.86,12.29-10.28,.66-.42,1.29-1.34,2.17-1.01,.08,.02,.17,.19,.15,.28-.13,.63-.24,1.28-.45,1.9-1.71,5.21-2.98,10.49-4.29,15.77-.08,.74-.22,1.69,.6,1.47,6.14-4.78,12M -9.9,18.05-14.8,1.5-1.14,2.52-1.95,2,.74-1.18,4.53-2.4,9.05-3.58,13.58-.13,.52-.12,1.06-.15,1.59,0,.08,.08,.21,.17,.25,.8,.05,1.53-.87,2.19-1.26,3.84-3.17,7.65-6.37,11.51-9.53,1.98-1.62,4.05-3.16,6.08-4.73,.39-.3,.82-.56,1.48-.51,.03,2.63-1.4,5.21-1.88,7.83-.62,2.42-1.14,4.86-1.69,7.29-.02,.1,.04,.29,.1,.3,1.11,.25,1.91-.97,2.8-1.46,6.28-4.7,12.31-9.75,18.74-14.24,.28-.2,.79,.18,.8,.39-.89,4.35-1.89,8.69-2.81,13.04-.05,.4,.66,.4,.84,.32,6.8-5.07,13.66-10.07,20.87-14.77,.52-.26,1.12-.78,1.74-.68,.4,.29,.06,1.07,.05,M 1.5-.79,3.8-2.14,7.52-2.6,11.36,1.06,.02,1.6-.51,2.21-.91,4.35-2.89,8.68-5.81,13.04-8.69,2.39-1.57,4.84-3.09,7.28-4.62,.64-.35,1.33-.89,2.12-.64,.08,.02,.15,.19,.14,.29-.23,2.91-1.25,5.71-1.75,8.58-.17,.88-.93,1.78-.12,2.7,1.31-.08,2.13-.86,3.08-1.42,6.6-3.92,13.2-7.83,20.08-11.42,1.01-.38,2.03-1.39,3.14-1.23,.17,.08,.33,.36,.3,.52-.46,3.51-1.8,6.96-1.91,10.48,.84,.2,1.38-.16,1.93-.44,3.53-1.79,7.03-3.61,10.57-5.37,5.26-2.63,10.7-4.99,16.21-7.26,.67-.16,1.52-.84,2.17-.4,.16,.12,.23,.4,.18,.59-.74,2.84-1.51,5.68-2.1M 1,8.55-.19,1.74,.15,1.82,1.76,1.32,10.31-4.27,20.76-8.19,31.37-11.9,.88-.15,3.08-1.59,3.19-.02-.54,2.99-1.44,5.91-2.09,8.88-.23,1.18,.73,1.3,1.6,.91,12.58-3.84,25.15-8.02,38.01-10.79,.63,.12,.6,.86,.47,1.36-.77,3.28-1.56,6.55-2.35,9.82l.08-.09c-12.72,3-25.19,6.84-37.65,10.7-.62,.16-1.75,.61-2.01-.22-.11-3.11,1.12-6.19,1.03-9.28-.51-.66-1.43-.05-2.08,.09-10.89,3.74-21.51,7.84-32.1,12.19-.68,.27-1.35-.14-1.26-.77,.41-2.99,1.11-5.95,1.13-8.97,0-.26-.21-.4-.55-.34-3.1,.78-5.97,2.46-8.93,3.66-6.74,2.94-13.01,6.55-19.56,M 9.68-1.78,.28,.28-8.13,.24-9.57,.03-.92-.68-.83-1.24-.62-7.77,4.06-15.14,8.53-22.59,13.05-.62,.23-1.69,1.25-2.28,.55-.23-3.44,.93-6.83,1.29-10.25,.01-.09-.06-.26-.15-.29-.87-.34-1.66,.44-2.37,.82-6.49,4.38-12.96,8.77-19.44,13.15-.94,.58-2.52,1.98-2.26-.17,.46-3.1,.95-6.2,1.41-9.3,.3-1.79-1.12-1.05-1.99-.41-5.07,3.55-10.13,7.1-14.8,10.99-.98,.5-6.49,6.36-5.93,2.82,.47-3.75,1.09-7.47,1.72-11.2,.01-.09-.09-.27-.15-.27-1.04-.14-1.74,.85-2.54,1.35-5.52,4.42-11.03,8.85-16.55,13.27-.64,.37-1.43,1.41-2.16,1.28-.36-.07-.39-M .51-.38-.8,.69-4.16,1.58-8.29,2.13-12.47,.04-.55-.64-.7-1.02-.45-5.63,4.57-10.91,9.54-16.41,14.26-.84,.55-1.57,1.83-2.66,1.72-.66-.57-.07-1.99-.07-2.78,.67-3.84,1.38-7.67,2.05-11.51,.37-2.51-1.87-.17-2.69,.4-4.98,4.38-10.05,8.71-14.75,13.29-.63,.52-1.16,1.37-2.03,1.45-.32,.02-.5-.12-.47-.4,.49-5.7,1.97-11.28,3-16.91,.05-.27-.39-.35-.56-.24-4.42,3.32-8.2,7.42-12.38,11.04-.57,.38-1.08,1.19-1.78,1.19-.23-.2-.5-.45-.38-.77,1.22-5.62,2.44-11.24,3.66-16.86,.1-.7,.73-1.9,0-2.42-.12-.04-.32-.06-.39,0-.59,.43-1.2,.86-1.74,1M .34-3.43,3.04-6.83,6.1-10.25,9.14-.67,.44-1.29,1.31-2.13,1.36-.09-.01-.22-.1-.22-.16,.69-4.8,2.3-9.5,3.35-14.25-.01-1.08,3.88-10.86,.57-8.23-3.5,2.98-6.99,5.98-10.5,8.96-.73,.63-1.5,1.23-2.27,1.83-.07,.06-.3,.09-.37,.04-.17-.12-.44-.31-.41-.43,1.72-8.43,4.14-16.71,6.69-24.93,.21-.46,0-1.35-.64-1.1-4.86,3.31-9.25,7.26-14.02,10.69-.15,.1-.48,.05-.71,.02-.08,0-.2-.19-.17-.27,1.36-5.05,2.66-10.11,4.13-15.14,1.19-4.09,2.6-8.13,3.89-12.2,.26-.83,.4-1.68,.57-2.52,.02-.08-.09-.21-.19-.26-.1-.05-.31-.08-.39-.03-.94,.6-1.9,1M .18-2.8,1.83-4.07,2.81-7.89,5.96-12.13,8.52-.63,.25-.84-.68-.6-1.12,2.35-7.85,4.66-15.71,7.51-23.45,1.07-2.89,2.04-5.8,3.05-8.7,.03-.52,.57-1.1,.25-1.55-.2-.06-.51-.15-.64-.08-3.03,1.79-6.05,3.6-9.05,5.42-2.04,1.24-4.04,2.51-6.08,3.75-.39,.24-.81,.52-1.4,.34-.26-.55,.08-1.05,.24-1.56,2.68-8.56,5.63-17.07,8.77-25.53,1.34-3.61,2.74-7.21,4.1-10.81,.23-.61,.56-1.21,.35-1.88-.03-.08-.17-.22-.22-.21-.38,.08-.79,.13-1.1,.3-4.4,2.29-8.78,4.61-13.18,6.91-.9,.47-1.82,.92-2.75,1.36-.32,.14-.72-.28-.73-.52,1.86-6.64,4.7-13.02,M 7.05-19.53,3.1-7.91,6.34-15.78,9.51-23.66,.18-.79,.98-1.7,.36-2.42-5.69,1.67-11.18,4.75-16.8,6.91-.65,.15-1.92,.99-2.36,.21,4.46-13.74,10.75-27.06,16.46-40.48,1.68-3.75,3.36-7.5,5.04-11.25,.18-.41,.31-.83-.17-1.25-6.32,1.58-12.41,4.04-18.65,5.95-.63,.21-1.25,.4-1.95,.22l.05,.02c-.33-.66-.01-1.27,.25-1.87,1.93-4.48,3.82-8.97,5.81-13.43,6.58-15.41,14.28-30.43,21.21-45.69,.04-.13-.27-.46-.4-.45-.79,.05-1.61,.1-2.37,.26-5.97,1.3-11.94,2.63-17.91,3.95-.67,.16-2.27,.61-1.98-.57,10.4-23.34,21.92-46.19,34.01-68.76,.29-.55,M .86-1.11,.48-1.8-.78-.31-1.58-.13-2.38-.04-6.53,.74-13.07,1.49-19.6,2.23-.75-.04-2.64,.48-2.61-.64,8.94-18.7,18.78-36.91,28.75-55.14,4.44-7.96,8.88-15.93,13.35-23.89,.54-.97,.9-2.04,2.03-2.87,8.15-.27,16.38-.03,24.55-.1,3.32-.18,2.25,1.06,.99,3.08-15.12,24.52-29.56,49.43-43.22,74.76-.91,1.26-.73,2.29,1.12,1.98,7.48-.57,15.31-2.36,22.74-2.16,.23,.62-.08,1.11-.36,1.59-1.52,2.64-3.11,5.26-4.6,7.91-10.93,19.39-21.62,38.84-31.36,58.8-.12,.29,.34,.62,.76,.53,7.15-1.53,14.29-3.08,21.44-4.62,1.6,0-.12,1.96-.32,2.68-9.85,18M .68-19.81,37.44-28.25,56.69,.37,.67,1.45,.17,2.05,.04,6.14-1.93,12.22-4.02,18.38-5.85,1.39-.26,.59,1.38,.21,1.98-8.09,16.31-16.16,32.58-22.9,49.33,.37,.69,1.42,.11,1.98-.07,5.83-2.37,11.56-5.1,17.45-7.31,.52,.48,.37,.91,.19,1.3-6.3,13.7-12.54,27.51-18.01,41.48-.19,.7-.81,1.5-.22,2.13,.03,.04,.27,.04,.37,0,4.78-2.12,9.28-4.78,13.95-7.11,1.02-.53,2.06-1.02,3.12-1.49,.14-.06,.44,.05,.64,.13,.08,.03,.16,.2,.13,.28-.24,.72-.46,1.46-.78,2.16-4.51,10.03-8.54,20.19-12.44,30.38-.71,1.85-1.27,3.73-1.89,5.6-.03,.09,.06,.26,.1M 4,.29,1.11,.31,2-.85,2.96-1.26,4.53-2.71,9.05-5.43,13.59-8.13,.19-.07,.83-.04,.8,.34-2.77,8.1-6.19,16.04-9.13,24.1-.33,1.39-3.92,9.4-2.5,9.45,4.35-2.35,8.2-5.57,12.37-8.24,1.02-.7,2.1-1.34,3.16-1.99,.37-.2,.67,.24,.65,.5-2.24,6.78-4.84,13.45-7.17,20.19-.94,2.69-1.74,5.42-2.58,8.14-.09,.28,.03,.6,.05,.9,.97-.07,1.45-.63,2.03-1.07,4.13-3.09,8.26-6.19,12.39-9.28,.4-.22,.86-.71,1.36-.54,.1,.04,.22,.17,.21,.25-.18,.84-.32,1.69-.58,2.52-2.11,6.46-4.25,12.91-6.36,19.36-.37,1.14-.68,2.3-1.01,3.46-.02,.09,.05,.27,.12,.28,.6M 4,.24,1.15-.21,1.61-.56,4.61-3.79,9.46-7.31,13.91-11.26l-.14,.06Z"/><path class="cls-2" d="M516.24,1302.89c.91,.4,1.85,.16,2.75,0,2.63-.45,5.25-.94,7.87-1.44,6.02-1.16,12.03-2.33,18.05-3.49,.72-.07,1.59-.41,2.19,.14-13.96,13.66-29.89,26.26-44.77,39.36-2.86,2.42-4.31,3.58,.74,2.92,8.13-.87,16.23-2.1,24.39-2.69,.11,0,.33,.07,.34,.13,.04,.19,.11,.46-.01,.58-.77,.75-1.57,1.47-2.39,2.19-17.73,15.34-35.78,30.51-53.98,45.45-.98,.87-2.51,.75-3.78,.76-7.79-.14-15.62,.34-23.38-.2-1.05-.77,1.6-2.12,2.07-2.7,16.3-13.47,32.59-2M 6.93,48.88-40.41,.35-.44,2.51-1.8,1.59-2.23-9.35,.38-18.63,2.28-28,2.66-.18,0-.41-.35-.32-.49,.68-.66,1.34-1.34,2.08-1.96,14.11-11.83,28.18-23.72,42.09-35.76,3.53-2.91-1.41-1.23-3.03-1.14-8.81,1.53-17.62,3.07-26.43,4.59-1.69-.37,1.47-2.2,1.94-2.8,12.08-10.67,24.92-20.89,36.24-32.07-.56-.41-1.19-.12-1.79,0-8.83,1.93-17.65,3.86-26.48,5.77-1.55,.34-3.14,.59-4.71,.86-.11,.02-.34-.04-.36-.1-.06-.17-.14-.42-.04-.53,10.65-10.26,22.91-19.55,32.99-30.2-12.26,2.45-23.65,5.87-35.97,8.23,.68-1.65,2.04-2.31,3.21-3.54,7.43-6.82,M 14.86-13.64,22.28-20.47,.92-1.01,2.37-1.74,2.66-3.12,.17-.03,.39-.05,.28-.25-.26-.02-.33,.09-.19,.31-.8-.29-1.58-.08-2.34,.11-3.7,.91-7.38,1.86-11.08,2.78-7.94,1.73-15.76,4.36-23.8,5.5l.06,.09c-.03-.2-.18-.47-.07-.59,.71-.78,1.44-1.55,2.22-2.29,6.64-6.38,13.29-12.74,19.93-19.12,.52-.5,1.03-1,1.49-1.53,.1-.11,0-.37-.08-.54-.76-.25-1.88,.25-2.69,.37-11.52,3.01-23.15,5.71-34.8,8.37-3.14,.77-2.07-.49-.53-1.95,6.26-6.35,12.8-12.45,18.91-18.94,.3-1.15-1.4-.44-1.99-.38-12.5,3.03-25.14,5.66-37.74,8.39-.82,.07-1.87,.59-2.55M -.05-.07-.06-.07-.24-.01-.31,.53-.62,1.06-1.24,1.63-1.84,4.99-5.22,9.99-10.43,14.98-15.66,.32-.45,1.63-1.65,.61-1.79-14.38,2.75-28.71,5.79-43.21,8.19-.73,.06-1.6,.35-2.21-.17-.07-.05-.09-.23-.03-.31,4.78-5.92,10.3-11.25,15.08-17.17,.1-.22-.12-.75-.47-.69-10.72,1.63-21.34,3.61-32.11,5-5.58,.7-11.12,1.73-16.71,2.31-.26-.03-.74-.29-.57-.62,3.73-4.9,7.77-9.57,11.62-14.38,.32-.57,2.33-2.43,.96-2.64-4,.44-8,.91-11.99,1.35-14.11,1.4-28.3,3.38-42.44,3.86-.16-.75,.37-1.28,.76-1.83,2.44-3.47,4.89-6.94,7.34-10.41,.6-.84,1.23-M 1.67,1.76-2.54,.39-.65,1.38-1.31,.74-2.04-.46-.53-1.5-.24-2.28-.18-19.51,1.31-39.04,2.04-58.59,2.32-.46-1.31,.66-2.23,1.15-3.36,2.2-3.93,4.42-7.86,6.61-11.79,1.49-2.58-.23-1.98-2.17-2.14-22.51,.08-44.98-.98-67.45-2.01l.09,.1c2.43-6.07,4.86-12.13,7.29-18.2l-.12,.07c24.25,2,48.57,2.9,72.9,3.25l-.09-.1c-2.84,5.22-5.68,10.44-8.51,15.66-.42,.78-.06,1.18,1.12,1.17,20.85,.12,41.66-1.01,62.47-1.86l-.06-.11c-3.46,5.11-6.92,10.22-10.38,15.33-.3,.47-.49,1.2,.3,1.32,10.47-.6,20.89-1.64,31.32-2.68,7.89-.75,15.75-1.68,23.6-2.61,M .34-.04,.78,.42,.65,.66-.17,.29-.31,.6-.51,.87-3.28,4.34-6.69,8.59-10.01,12.9-.49,.64-.93,1.31-1.37,1.97-.21,.4,.34,.46,.62,.56,16.87-1.79,33.57-5.37,50.34-7.41,.2,.64-.26,1.06-.62,1.48-4.36,5.18-8.88,10.25-13.17,15.49-.08,.22,.14,.72,.51,.66,1.85-.22,3.69-.62,5.52-.94,13.5-2.45,26.89-5.38,40.34-8.03,1.06,.2-.31,1.36-.59,1.82-4.28,4.7-8.58,9.39-12.86,14.09-.71,.78-1.39,1.58-2.07,2.38-.29,.35,.32,.55,.54,.55,13.44-2.62,26.67-6.03,39.94-9.2,1.02-.15,2.07-.69,3.08-.3,.05,.6-.49,.97-.89,1.38-5.86,6.33-12.18,12.28-17.84M ,18.78,1.27,.34,2.26-.14,3.25-.37,4.9-1.18,9.77-2.42,14.63-3.68,7.59-2.16,15.44-3.72,22.88-6.28l-.02-.05c.86,1.14-.68,1.96-1.33,2.77-5.57,5.54-11.14,11.08-16.71,16.62-1.03,1.24-5.53,4.61-.98,3.38,11.98-3.24,24.05-6.18,35.93-9.73,1.38,.06-.89,1.99-1.25,2.43-6.86,6.8-13.74,13.6-20.81,20.2-1.24,1.26-4.29,3.67-.25,2.61,10.83-2.94,21.66-5.87,32.45-8.93,3.55-.99,1.25,.81,.04,2.15-6.14,5.86-12.3,11.71-18.47,17.55-.59,.93-10.64,8.92-8.22,8.72,11.07-2.62,22.01-5.69,33.01-8.59,3.22-.52-.59,2.19-1.3,3.01-10.02,9.16-20.04,18.3M 2-30.06,27.48-.53,.49-1.05,.98-1.52,1.51-.1,.11,0,.36,.07,.53,.03,.06,.25,.13,.36,.1,3.11-.68,6.24-1.33,9.33-2.06,7.23-1.69,14.45-3.42,21.68-5.13,.4,0,1.2-.32,1.28,.14-12.14,12.22-25.76,23.14-38.51,34.8-.7,.62-1.67,1.12-1.84,2.06-.18,.23-.16,.26,.08,.09l-.19-.14Z"/><path class="cls-2" d="M1279.83,881.01c-9.33-9.29-17.97-19.35-27.59-28.59-5.31-5.29-10.7-10.51-16.06-15.76-.53-.46-1-1.15-1.81-1.02-.06,0-.19,.19-.17,.27,.74,2.73,1.47,5.46,2.25,8.19,1.19,4.19,2.41,8.38,3.62,12.57,.21,.73,.43,1.47,.2,2.23l.12-.06c-1.32-.M 13-2.06-1.61-3.03-2.39-11.53-11.59-23.34-23.98-36.24-34.17-.15,.13-.36,.33-.33,.46,.29,1.05,.61,2.09,.95,3.13,2.02,6.14,4.06,12.28,6.07,18.42,.24,.72,.36,1.46,.52,2.2,.01,.06-.11,.19-.2,.21-.91-.15-1.56-1.18-2.29-1.71-5.69-5.47-11.28-11-17.08-16.39-4.4-4.08-9.06-7.97-13.62-11.94-.42-.37-.82-.82-1.62-.72-.24,.9,.33,1.69,.61,2.49,1.92,5.49,3.93,10.97,5.88,16.46,.88,2.48,1.67,4.98,2.48,7.47-.01,.23-.41,.35-.6,.19-9.04-7.91-17.69-16.26-26.88-24.12-.91-.79-1.87-1.55-2.83-2.29-.11-.08-.42-.03-.62,.01-.06,.01-.13,.2-.1,.2M 9,.3,.94,.61,1.87,.94,2.8,2.79,7.65,5.61,15.29,8.36,22.95,.33,.91,.9,1.81,.66,2.88-1.38-.35-2.18-1.49-3.25-2.32-6.83-5.81-13.65-11.62-20.49-17.43-.83-.7-1.74-1.34-2.63-1.99-.08-.06-.33-.08-.38-.04-.7,.54,0,1.38,.14,2.06,3.14,8.8,6.29,17.59,9.44,26.39,.18,.5,.53,.99,.14,1.53-1.12-.24-1.72-1.01-2.47-1.61-7-5.51-13.76-11.32-20.89-16.66-.19-.11-.89-.17-.88,.23,.76,2.29,1.54,4.57,2.33,6.86,2.47,7.16,4.96,14.32,7.42,21.48,.25,.72,.39,1.47,.56,2.21,.02,.09-.08,.26-.16,.28-.23,.04-.56,.09-.69,0-.91-.64-1.77-1.32-2.65-1.99-M 5.18-3.93-10.37-7.86-15.56-11.78-2.98-2.17-3.36-2.06-2.1,1.55,3,8.72,5.79,17.48,8.45,26.27,.32,1.05,.62,2.09,.89,3.15,.04,.15-.14,.34-.22,.52-1.02-.15-1.6-.79-2.29-1.28-4.43-3.15-8.85-6.32-13.28-9.46-1.19-.66-2.5-2.09-3.85-2.19-.39,.15-.41,.49-.34,.8,.15,.63,.3,1.27,.5,1.89,2.97,9.62,5.61,19.29,8.25,28.97,.48,2.29,1.19,3.95-1.72,1.89-4.37-2.88-8.72-5.77-13.1-8.64-1.01-.48-2.14-1.69-3.3-1.46-.07,.02-.13,.2-.11,.3,.54,2.22,1.05,4.44,1.64,6.65,2.38,9.9,5.2,19.85,6.75,29.82-.8,.13-1.31-.24-1.84-.57-4.61-2.81-9.18-5.69-M 13.88-8.37-1.67-.89-1.86-.11-1.64,1.48,2.13,10.62,4.17,21.26,5.93,31.95-.06,1.26,2.02,7.54-1,5.37-4.38-2.55-8.84-4.94-13.29-7.36-.55-.25-1.52-.88-2.01-.3,.63,9.55,2.74,19.02,3.46,28.59,.41,4.19,.81,8.38,1.18,12.57-.02,.64,.21,1.9-.75,1.85-5.2-2.19-10.07-5.12-15.33-7.17-.15-.05-.6,.11-.63,.22,.7,15.66,1.97,31.4,1.79,47.13,0,.29-.55,.56-.87,.46-4.51-1.6-8.81-3.74-13.26-5.49-.84-.32-2.67-1.24-2.95,.06-.58,17.55-.37,35.24-2.32,52.69-2.22,.08-4.22-1.27-6.33-1.84-3.2-1.13-6.41-2.26-9.63-3.35-.32-.11-.75,.01-1.14,.02l.04,M .05c-.76-1.38-.23-2.95-.2-4.45,.21-2.79,.42-5.59,.63-8.38,1.11-13.21,1.8-26.44,2.19-39.69,.04-1.75,.14-2.73,2.55-1.73,3.91,1.44,7.8,2.92,11.71,4.37,1.46,.47,2.34,.65,2.4-1.23,.18-5.82-.1-11.63-.2-17.44,.05-9.37-.78-18.72-.95-28.08,.52-1.28,3.17,.62,4.13,.78,3.44,1.47,6.87,2.97,10.3,4.46,.48,.21,.96,.4,1.58,.12-.24-14.03-3.16-28.74-4.17-42.68,.63-.61,1.42-.04,2.08,.2,3.93,1.88,7.85,3.77,11.77,5.66,.68,.33,1.29,.8,2.24,.67,.08-3.91-1.26-7.89-1.72-11.81-1.2-7.26-2.5-14.51-3.91-21.73-.22-1.17-.49-2.34-.69-3.51-.14-.8-.M 75-1.61-.05-2.43,1.18-.03,1.98,.63,2.85,1.09,4.46,2.11,8.59,5.1,13.2,6.76,.45,0,.32-1.1,.3-1.42-.87-4.03-1.72-8.06-2.69-12.08-1.64-6.76-3.38-13.51-5.06-20.26-.08-.8-1.02-2.82,.33-2.76,5.05,2.58,9.81,5.7,14.74,8.49,.53,.31,1.03,.71,1.79,.51l-.02,.11-.08-.05c.33-.87,.02-1.71-.21-2.54-1.94-6.81-3.89-13.63-5.87-20.43-1.06-3.67-2.17-7.32-3.25-10.98-.02-.08,.06-.25,.14-.27,.76-.32,1.42,.28,2.05,.6,5.21,3.23,10.39,6.48,15.59,9.73,.18,.07,.88,.03,.83-.35-2.81-10.12-6.68-19.93-9.9-29.93-1.78-4.4,2.57-.57,4.07,.24,5.2,3.4,10M .18,7.11,15.5,10.31,.35-.51,.22-.91,.07-1.32-3.38-9.64-6.91-19.23-10.51-28.8-.47-1.04,.26-1.31,1.37-.56,6.34,4.29,12.47,8.85,18.65,13.36,.59,.31,1.25,.99,1.93,.95,.39-.38-.16-1.35-.25-1.84-3.15-8.22-6.32-16.45-9.47-24.67-.87-2.48-2.11-4.38,1.42-1.97,7.44,5.59,14.86,11.22,22.2,16.91,0-.02,.04-.18,.04-.18l-.09,.26c.44-.75,.17-1.48-.12-2.2-1.08-2.77-2.15-5.55-3.27-8.32-1.96-4.81-3.97-9.61-5.91-14.42-.27-.67-.93-1.34-.43-2.12,.74,.04,1.22,.44,1.72,.79,1.91,1.36,3.82,2.72,5.71,4.1,6.17,4.5,12.36,8.99,18.12,13.84,.35,.3,M .84,.49,1.28,.71,.05,.02,.29-.1,.29-.14-2.2-7.57-5.85-14.74-8.68-22.12-.17-.4-.34-.79,.02-1.18,1.2,.33,1.94,1.13,2.82,1.79,9.53,6.88,18.32,14.9,27.7,21.63,.15-.12,.37-.31,.33-.43-.29-.94-.6-1.88-.96-2.8-1.39-3.6-2.8-7.19-4.21-10.79-1.01-2.57-2.03-5.13-3.02-7.7-.1-.27-.01-.59-.01-.89,.81,.1,1.26,.53,1.72,.9,10.57,8.38,20.78,17.14,30.94,25.98,.85,.53,1.53,1.84,2.64,1.63,.07-.01,.16-.19,.14-.27-2.08-6.82-4.75-13.46-7.06-20.21-1.14-2.86,.99-1.16,2.17-.14,12.27,10.63,24.41,21.55,36.16,32.68,.51,.49,1.13,.9,1.71,1.33,.19M ,.13,.55,.04,.55-.22-1.5-7.11-4.17-14.01-6.09-21.04,.22-1.57,2.63,1.34,3.16,1.68,14.99,13.73,29.27,28.14,43.76,42.35,.06,.06,.29,.1,.34,.07,.17-.13,.44-.3,.42-.44-.07-.75-.18-1.5-.35-2.24-1.16-4.97-2.36-9.94-3.52-14.92-.24-1.79-1.69-5.74,1.36-2.62,17.96,17.72,35.36,36.12,52.5,54.54,1.53,.56,.58-2.14,.69-2.91-.7-5.57-1.52-11.13-2.24-16.7-.04-.29,.1-.6,.23-.89,.3-.42,1.64,.95,2.01,1.39,21.11,22.31,41.18,45.46,61.07,68.76,.89,1.03,1.3,2.06,1.29,3.3-.05,6.14-.02,12.28-.04,18.42,0,.29-.17,.58-.3,.86-.43,.53-1.66-1.26-2.M 07-1.72-8.35-9.92-16.64-19.87-25.06-29.75-10.08-11.84-20.25-23.64-30.78-35.23-.71-.78-1.47-1.54-2.2-2.3-.19-.2-.45-.24-.72-.09-.09,.05-.21,.15-.2,.22,.06,1.07,.06,2.15,.21,3.21,.67,5.79,1.89,11.53,2.17,17.34,.02,.28-.14,.42-.49,.4-.77-.1-1.27-1.08-1.85-1.56-5.68-6.42-11.35-12.84-17.04-19.26-10.28-11.61-21.08-22.91-31.94-34.17-.43-.32-.92-1.02-1.52-.9-.1,.04-.21,.17-.2,.24,1.27,6.71,2.84,13.36,4.32,20.03,.18,.84,.42,1.7,.01,2.55l.03-.08Z"/><path class="cls-2" d="M213.93,629.46s.01-.04,.01-.06h.07l-.08,.06Z"/><path cM lass="cls-2" d="M248.66,642.99s.02-.05,.02-.07c.03-.01,.06,0,.09,0l-.11,.07Z"/><path class="cls-2" d="M257.79,597.95s.01,.01,.01,.01h-.02s-.01,0-.02,0h.01s.01-.03,.01-.03h.01Z"/><path class="cls-2" d="M310.2,573.78s-.01,.05-.02,.07h-.08l.1-.07Z"/><path class="cls-2" d="M392.98,407.55c-4.12,1.5-8.14,3.2-12.05,5.1-.07-2.72-.1-5.43-.15-8.14,.03-.6-.01-1.59,.81-1.57,3.91,1.22,7.58,3.12,11.39,4.61Z"/><path class="cls-2" d="M399.18,454.51c-.07-1.51-.16-3.02-.24-4.54-.32,.16-.63,.31-.94,.47l-16.93-33.55c.3,7.5,.65,14.99,1M .02,22.49,0,3.74,.93,7.56,.56,11.25-.75,.26-1.33-.06-1.89-.33-3.81-1.84-7.61-3.68-11.41-5.52-1.13-.42-2.05-1.36-3.34-1.04,.17,6.96,1.2,13.94,1.84,20.89,.76,7.39,2.48,14.76,2.75,22.15-.29,.28-1.09,0-1.4-.11-4.23-2.31-8.44-4.63-12.67-6.95-.73-.25-2.01-1.44-2.65-.71-.16,5.14,1.62,10.25,2.28,15.34,1.06,5.75,2.12,11.5,3.2,17.25,.3,1.6,.67,3.19,.94,4.78,.11,.63,.58,1.46-.09,1.84-.76,.44-1.43-.34-2.05-.7-4.54-2.69-9.09-5.36-13.55-8.17-.52-.31-1.09-.68-1.72-.45,.86,6.15,2.7,12.53,4,18.73,1.28,6.04,3.32,11.96,4.35,18.03-1.0M 4,.13-1.6-.38-2.21-.77-5.37-3.26-10.52-7.41-16-10.23-.17,.14-.41,.32-.39,.46,.12,.86,.27,1.71,.5,2.55,2.6,9.68,5.26,19.35,8.25,28.96,.23,1.03,.85,2.21-.08,3.07,.06-.04,.12-.09,.18-.12-.05,.05-.1,.1-.16,.15-.01-.01-.02-.02-.02-.03h0c-5.64-4.66-12.02-8.56-17.93-12.94-.38-.22-1.36-.89-1.54-.18,2.99,10.4,6.39,20.71,9.82,30.97,.88,2.96-1.41,.78-2.56,.11-5.2-3.91-10.38-7.84-15.57-11.76-1.11-.65-2.01-1.98-3.34-2.05-.24,.85,.14,1.65,.41,2.45,2.68,7.78,5.35,15.56,8.03,23.33,.46,1.85,1.71,3.63,1.6,5.53-1.13-.15-1.68-.81-2.33M -1.33-6-4.8-11.98-9.6-17.96-14.41-.64-.41-4.35-4.13-3.75-1.68,2.82,8.43,6.03,16.74,8.99,25.12,.44,1.24,.86,2.49,1.27,3.73,.03,.08-.04,.26-.11,.27-.22,.05-.56,.14-.67,.05-.9-.65-1.78-1.31-2.61-2.01-7.02-5.95-14.02-11.92-21.04-17.87-1.94-1.61-3.72-3.43-2.26,.64,3.05,8.36,6.09,16.74,9.18,25.08,.18,.5,.09,1.23-.11,1.17-1.45-.38-2.41-1.66-3.53-2.54-7.6-6.84-15.19-13.69-22.78-20.53-1.45-.94-2.81-3.63-4.71-2.89,.8,.65,.85,1.56,1.14,2.35,2.73,7.55,5.41,15.11,8.09,22.67,.5,1.6-.28,1.44-1.34,.63-10.58-8.76-20.39-18.27-30.22-M 27.8-.69-.66-1.39-1.31-2.13-1.93-.11-.09-.45-.03-.66,.01-.36,.29,.04,1.14,.09,1.55,2.24,6.76,4.49,13.52,6.72,20.29,.24,.72,.37,1.46,.53,2.2,.01,.06-.14,.18-.25,.21-12.37-9.95-23.83-21.73-34.98-32.9-1.48-1.34-2.46-3.08-4.37-3.9,.79,5.46,3.04,10.75,4.35,16.15,.63,2.2,1.23,4.41,1.81,6.62,.05,.19-.11,.41-.17,.61-14.68-12.43-28.07-27.35-41.31-41.25-1.44-1.35-2.35-3.15-4.24-3.96,.94,6.87,3.04,13.61,4.37,20.43,.14,.63,.1,1.28,.13,1.92,0,.07-.11,.19-.2,.23-12.34-10.89-23.39-24.27-34.66-36.37-5.13-5.8-10.26-11.61-15.39-17.4M 1-.65-.61-2.18-3.07-2.67-1.57,.83,7.08,2.26,14.12,2.72,21.21-1.14,.25-1.61-.88-2.34-1.5-13.34-14.62-26.11-29.55-38.82-44.53-6.27-7.4-12.46-14.84-18.69-22.26-.37-.44-.81-.85-1.27-1.22-.1-.07-.46,.06-.82,.12,.02,6.23,.12,12.48,.17,18.71-.35,2.03,1.05,3.54,2.35,4.99,15.46,18.14,31.02,36.05,47.18,53.66,4.46,4.86,9.01,9.68,13.53,14.51,.41,.32,.9,.99,1.51,.9,.37-.06,.32-.51,.32-.79-.66-4.82-1.36-9.63-2.01-14.45-.23-1.71-.37-3.42-.53-5.14-.01-.09,.1-.27,.16-.28,.95-.17,1.38,.79,1.98,1.32,16.41,18.14,33.66,35.7,50.98,53.03M ,.99,.99,2.74,2.41,2.07-.45-1.52-6.44-3.11-12.88-4.52-19.35-.02-.09,.1-.29,.14-.29,.24,.01,.57,0,.7,.12,1.14,1.05,2.28,2.11,3.36,3.21,13.6,13.78,27.64,27.41,42.07,40.53,.34,.31,.69,.62,1.26,.61,.17-.85-.14-1.66-.39-2.47-1.89-6.25-3.78-12.5-5.65-18.75-.05-.26-.04-.75,.35-.71,.61,.04,.89,.44,1.23,.75,5.18,4.79,10.29,9.62,15.54,14.36,6.76,6.11,13.62,12.14,20.45,18.19,1.03,.7,1.92,2.01,3.21,2.15,.22-.74-.1-1.43-.35-2.13-2.23-6.53-4.87-12.94-6.84-19.54-.05-.41,.64-.35,.81-.27,11.16,9.4,22.04,19.24,33.81,28.11,1.29,.31,.M 62-.83,.4-1.54-2.32-5.95-4.64-11.89-6.96-17.84-.32-1.06-1.21-2.32-.26-3.31-.06,.05-.11,.11-.16,.17,.04-.05,.09-.11,.15-.18,8.86,8.06,18.65,15.2,28.2,22.62,.59,.38,1.16,1.04,1.94,.78,.91,.38-8.24-20.7-8.26-21.18-.15-.53-.68-1.38-.11-1.79,.86-.03,1.51,.86,2.17,1.3,7.28,5.92,14.98,11.48,22.72,17,.59,.36,1.19,1.01,1.93,.68,.08-.03,.14-.21,.1-.29-3.37-8.17-6.66-16.36-9.86-24.59-.2-.51-.43-1.02-.08-1.57,1,.15,1.54,.81,2.21,1.32,6.32,4.84,12.64,9.69,18.96,14.53,.98,.65,1.97,1.71,3.13,1.95,.14-.15,.36-.37,.3-.5-1.66-4.32-3M .37-8.63-5.04-12.94-1.94-5.04-3.85-10.09-5.77-15.13-.16-.41-.32-.83,.04-1.24,1.02,.11,1.56,.78,2.25,1.27,5.52,3.95,11.01,7.92,16.53,11.87,.85,.47,2.02,1.55,2.93,1.62,.73-.54-.17-1.64-.29-2.34-2.85-7.75-5.71-15.49-8.54-23.23-.6-1.65-1.12-3.32-1.65-4.99-.01-.2,.35-.4,.54-.29,5.58,3.25,10.73,7.19,16.16,10.68,2.07,1.08,4.55,3.63,2.97-.74-2.99-8.94-6-17.88-9-26.81-.28-.83-.5-1.68-.7-2.52-.05-.19,.01-.5,.16-.58,.38-.19,.75-.01,1.07,.2,4.76,3,9.52,6,14.3,8.98,.59,.27,2.91,2.04,3.06,.9-3.03-11.15-7.06-22.08-9.43-33.36,.03-M .23,.49-.62,.78-.49,4.85,2.69,9.6,5.56,14.42,8.31,.54,.2,1.17,.79,1.76,.64,.17-.13,.43-.32,.4-.45-.48-2.12-.96-4.24-1.52-6.34-2.38-9.91-5.33-19.82-6.74-29.83,1,.03,1.63,.45,2.29,.81,3.57,1.92,7.14,3.85,10.73,5.76,.9,.48,1.85,.88,2.79,1.3,.31,.13,.75-.23,.78-.47-2.19-12.99-5.48-25.96-6.71-39.04,1.62,.05,2.82,1.12,4.26,1.71,3.59,1.7,7.19,3.38,10.79,5.07,.49,.22,1.22-.1,1.17-.5-1.42-14.13-3.89-28.29-4.25-42.46,.58-.21,1.06-.07,1.55,.14,4.52,1.93,8.98,3.99,13.58,5.71,.27,.1,.87-.21,.87-.46,.01-.96,.05-1.93,.01-2.9Z"/><M path class="cls-2" d="M417.76,361.95c-.92,13.19-2.2,26.36-2.6,39.57-5.79,1.07-11.5,2.5-17.06,4.28,.27-16.65,.46-33.39,2.17-49.94,.68-.73,2.07,.25,2.89,.39,3.83,1.34,7.62,2.72,11.46,4.03,.83,.28,1.66,.77,2.68,.52,.31,.35,.49,.73,.46,1.15Z"/><path class="cls-2" d="M138.15,1155.19c1.49-6.81,2.57-13.68,4.7-20.35l-.15,.11c15.17,2,30.38,3.66,45.61,5.06,10.96,1.06,22.02,1.32,32.95,2.72l-.09-.1c-2.03,4.9-4.08,9.8-6.1,14.7-.38,.91-.67,1.85-.95,2.78-.04,.13,.19,.43,.36,.47,22.24,1.54,44.62,1.24,66.91,1.56,.32,.52,.16,.92-.08M ,1.32-1.49,2.53-2.96,5.07-4.45,7.61-1.32,2.24-2.66,4.47-3.97,6.71-.26,.51-.88,1.32-.18,1.7,16.08,.32,32.28-1.03,48.37-1.86,3.22-.2,6.44-.43,9.67-.6,1.03-.04,1.34,.44,.79,1.24-3.39,4.79-6.97,9.46-10.42,14.21-.83,1.21-1.96,2.48,.47,2.3,17.22-1.24,34.55-3.64,51.62-5.11,.51,.85-.71,1.53-1.09,2.23-4,4.73-8.01,9.45-12,14.18-.43,.51-1.08,.97-.82,1.74,12.23-.95,24.38-3.38,36.56-4.99,3.7-.57,7.38-1.21,11.07-1.81,.24-.04,.74,.05,.74,.1,.14,.83-.53,1.37-1.05,1.93-5.05,5.76-11.06,11.23-15.59,17.19,.57,.62,1.43,.15,2.15,.1,4.47M -.76,8.94-1.56,13.42-2.3,9.83-1.56,19.44-3.75,29.23-5.39-.34,1.49-1.65,2.18-2.6,3.29-5.23,5.21-10.47,10.41-15.7,15.61-.45,.64-1.72,1.25-1.42,2.09,13.3-1.75,26.66-5.19,39.89-7.81,.51-.11,1.02-.32,1.64-.06-.64,1.57-2.34,2.52-3.47,3.78-6.01,5.67-12.02,11.33-18.03,17.01-.52,.49-1,1.01-1.48,1.52-.07,.07-.08,.26-.02,.31,.6,.56,1.46,.17,2.17,.09,12.02-2.23,24.27-5.88,36.28-7.4-.38,1.57-2.12,2.4-3.16,3.57-7.22,6.54-14.45,13.07-21.67,19.61-.62,.56-1.2,1.16-1.78,1.75-.07,.07-.12,.26-.06,.3,.15,.12,.39,.29,.55,.26,11.4-2.07,2M 2.67-4.7,33.95-7.19,.6-.12,1.25-.37,1.8,.02,.04,.02,0,.22-.08,.3-9.5,8.88-19.45,17.28-29.11,25.98-.73,.72-1.8,1.21-1.93,2.3,.93,.22,1.83,.05,2.74-.18,10.4-1.94,20.68-4.31,31.12-6.01-.59,1.55-2.06,2.25-3.2,3.39-10.74,9.7-23.56,19.18-33.45,29.2,.46,.37,1.66,.09,2.25,.08,9.65-1.36,19.22-3.58,28.92-4.38l-.05-.09c.03,.2,.18,.48,.07,.59-.76,.75-1.53,1.5-2.37,2.2-7.55,6.3-15.12,12.58-22.68,18.88-5.5,4.59-10.98,9.19-16.47,13.79-.29,.4-1.68,1.01-1.17,1.53,.17,.13,.46,.23,.69,.22,1.88-.13,3.76-.27,5.63-.46,5.88-.58,11.76-1.1M 8,17.64-1.76,1.46-.15,2.93-.26,4.4-.37,.07,0,.18,.11,.21,.18,.04,.1,.09,.25,.03,.31-.68,.66-1.34,1.34-2.09,1.95-15.58,12.86-31.26,25.62-47.03,38.27-2.14,1.71-2.06,1.63-4.96,1.63-6.87,.01-13.75,.02-20.62,.02-3.63,.05-3.89-.42-.84-2.71,14.76-11.96,29.77-23.64,44.32-35.85,.13-.13,.07-.4,.05-.6-.65-.29-1.6-.09-2.33-.1-8.3,.73-16.59,1.56-24.88,2.32-1.18,.09-2.28-.05-.9-1.29,12.46-10.29,24.91-20.6,37.36-30.91,.48-.56,2.91-2.17,1.79-2.43-10.46,.94-20.88,3.59-31.36,4.24,.03-.24-.05-.51,.08-.64,.87-.82,1.78-1.61,2.7-2.39,9.M 61-8.15,19.23-16.3,28.84-24.45,1.04-1.01,2.38-1.71,2.94-3.08-9,1-17.91,3.11-26.88,4.5-1.01,0-9.91,2.41-6.69-.38,8.99-7.86,17.97-15.76,26.9-23.68,1.4-1.38,2.67-2.31-.39-1.89-10.21,1.95-20.42,3.92-30.62,5.9-.75,.08-4.38,1.11-4.28-.05,8.18-7.91,16.91-15.29,25.03-23.26,.22-.87-.62-.64-1.19-.51-11.72,2.46-23.6,4.37-35.4,6.56-.91,.01-2.29,.66-2.99-.05-.08-.16,.01-.44,.16-.59,.74-.77,1.51-1.52,2.28-2.26,5.77-5.55,11.55-11.1,17.32-16.65,.51-.49,.99-1.02,1.46-1.54,.07-.07,.09-.25,.03-.31-.34-.39-.86-.4-1.34-.29-10.25,1.8-20M .5,3.63-30.76,5.4-3.42,.59-6.88,1.03-10.32,1.52-.17,.02-.42-.16-.58-.29-.07-.05-.06-.24,0-.31,.78-.88,1.55-1.76,2.37-2.61,4.86-5.03,9.74-10.05,14.59-15.08,.56-.58,1.32-1.1,1.33-2.06-10.47,1.08-20.83,3.25-31.33,4.4-5.17,.46-10.31,1.8-15.5,1.77,0-.28-.1-.54,.02-.69,.56-.73,1.17-1.45,1.78-2.15,3.78-4.32,7.58-8.64,11.36-12.97,.69-.79,1.34-1.61,1.99-2.43,.06-.07,.06-.24,0-.3-.15-.15-.37-.38-.54-.37-1.48,.1-2.96,.2-4.42,.39-10.64,1.39-21.35,2.34-32.02,3.49-4.55,.43-9.11,.75-13.67,1.09-1.95-.09,.22-2.02,.64-2.76,3.62-5.04M ,7.81-9.73,11.08-14.99,.05-.1-.22-.45-.35-.45-5.24-.11-10.45,.72-15.68,.96-12.63,.77-25.28,1.26-37.93,1.8-.83-.13-3.49,.54-3.41-.68,3.08-5.66,6.84-10.94,9.95-16.59,.19-1.16-1.78-.72-2.5-.85-4.45,.05-8.89,.14-13.34,.19-14.96,.21-29.91-.27-44.87-.55-1.21-.03-2.41-.14-3.62-.21-.3-.02-.72-.49-.63-.71,.31-.82,.61-1.65,.96-2.46,1.93-4.92,4.5-9.65,6.06-14.69,.03-.15-.18-.38-.36-.48-2.05-.5-4.28-.39-6.39-.61-16.53-.77-33.02-2.06-49.49-3.62-5.21-.52-10.42-1.08-15.63-1.6-1.05-.1-2.13-.33-3.19,.01l.12,.1Z"/><path class="cls-2M " d="M1009.12,190.08c12.91-2.58,25.93-4.91,38.93-7.08,1.98,.1-1.1,2.24-1.51,2.82-5.68,5.46-11.36,10.92-17.04,16.38-.85,.95-2.06,1.61-2.38,2.89,11.93-1.59,23.69-4.1,35.59-5.98,2.23-.38,4.5-.62,6.76-.89,.19-.02,.53,.13,.6,.27,.08,.97-1.46,1.87-2.02,2.67-5.29,5.57-10.8,10.95-15.95,16.65-.3,1.52,7.01-.38,8.16-.35,11.63-1.79,23.27-3.53,34.96-4.92,1.17-.14,2.38-.44,3.58-.07l-.09-.07c.12,1.41-1.41,2.22-2.14,3.3-3.78,4.32-7.56,8.64-11.33,12.97-.54,.62-1.02,1.26-1.51,1.91-.15,.31,.38,.6,.61,.62,8.55-.65,17.06-1.9,25.6-2.69,M 8.41-.67,16.89-2.21,25.29-2.13,0,1.26-1.16,2.11-1.81,3.13-3.27,4.33-6.54,8.66-9.81,12.99-.41,.69-1.18,1.24-.8,2.1,19.13-1.24,38.05-2.36,57.27-2.98,.22,1.55-.92,2.46-1.57,3.73-2.72,4.56-5.65,9.02-8.23,13.66-.31,1.25,3.35,.66,4.16,.83,11.04,0,22.08-.1,33.12-.02,9.01,.14,18.04,.24,27.04,.69,1.42,.37,.08,1.95-.1,2.84-2.04,5.01-4.36,9.92-6.25,14.98-.09,.26,.28,.67,.63,.69,2.95,.21,5.9,.47,8.85,.59,13.56,.66,27.08,1.8,40.6,3.04,7.22,.65,14.43,1.41,21.64,2.1,1.01-.02,2.21,.4,3.03-.31l-.02-.05c.15,.74,.3,1.46,.13,2.22-1.25M ,6.1-2.99,12.13-3.81,18.31l.11-.08c-17.4-1.82-34.76-4.14-52.22-5.53-9.05-.94-18.19-.99-27.2-2.25l.14,.09c2.26-5.41,4.57-10.81,6.84-16.21,.73-1.81-.08-1.85-1.67-1.94-21.78-1.09-43.6-1.27-65.4-1.33-.57-.91,.32-1.65,.67-2.48,2.75-4.79,5.74-9.47,8.34-14.34-.1-1.1-1.84-.69-2.63-.79-9.83,.32-19.66,.59-29.48,.99-8.87,.43-17.72,1.17-26.6,1.62-2.08-.15,.58-2.57,.94-3.41,2.8-3.81,5.62-7.6,8.42-11.4,.55-.74,1.05-1.5,1.52-2.27,.09-.15-.07-.39-.15-.69-14.44,.91-28.86,2.69-43.26,4.2-3.07,.33-6.14,.63-9.21,.93-.32,.03-.73-.48-.59M -.7,.19-.29,.35-.58,.57-.85,4.02-4.86,8.16-9.63,12.22-14.46,1.76-2.25,1.58-2.29-1.23-2.09-11.94,1.6-23.88,3.25-35.79,5.1-3.3,.51-6.6,1.07-9.9,1.6-.1,.02-.3-.07-.33-.14-.08-.18-.19-.42-.1-.57,1.15-1.61,2.66-2.98,3.98-4.47,3.7-3.97,7.42-7.94,11.11-11.92,.56-.6,1.06-1.24,1.57-1.87,.06-.08,.07-.26,0-.31-.41-.33-.92-.3-1.4-.18-13.28,2.32-26.6,4.5-39.77,7.22-1.03,.21-2.11,.27-3.16,.38-.21,.02-.48-.27-.36-.46,5.48-5.92,11.42-11.43,17.07-17.2,.76-.76,1.52-1.51,2.24-2.29,.14-.15,.23-.54,.17-.57-.94-.52-2-.08-2.99,.06-11.94,M 2.2-23.81,4.6-35.61,7.23-3.07,.45-3.67,.45-.98-2,6.35-6.01,12.71-12.01,19.06-18.01,.7-.66,1.39-1.32,2.04-2,.11-.11,0-.37-.06-.55-.78-.29-1.87,.2-2.72,.27-11.96,2.3-23.91,5.61-35.88,7.4,.13-1.29,1.54-1.9,2.35-2.79,8.06-7.39,16.31-14.59,24.28-22.08,.49-1.17-1.3-.53-1.9-.5-10.32,2.05-20.59,4.24-30.81,6.6-2.75,.58-5.11,1.24-1.56-1.73,9.77-8.77,19.76-17.32,29.43-26.2,.29-1.01-2.9-.03-3.51-.03-9.01,1.79-18.02,3.59-27.04,5.38-4.72,1-3.52-.02-.68-2.46,10.39-8.9,20.78-17.79,31.17-26.69,.92-.79,1.83-1.58,2.7-2.4,.12-.11,.04-M .38,0-.57-9.83,.66-19.82,3.04-29.68,4.41-2.76,.3-1.06-.91,0-1.95,12.99-10.95,26.1-21.78,39.16-32.67,.74-.62,1.38-1.31,2.04-1.97,.06-.06,.01-.22-.05-.31-9.47,.1-19.17,1.9-28.75,2.52-.28-.96,1.26-1.71,1.85-2.37,15.37-12.55,30.67-25.19,46.18-37.58,1.57-1.32,3.13-2.75,5.36-2.39,7.55,0,15.09-.01,22.64-.01,3.48-.02,.72,1.55-.48,2.67-9.22,7.41-18.45,14.8-27.67,22.21-5.03,4.05-10.04,8.13-15.04,12.2-.57,.6-1.89,1.25-1.53,2.12,6.16-.21,12.3-1.16,18.45-1.62,3.21-.29,6.43-.51,9.64-.76,.34-.03,.52,.13,.5,.38-11.87,10.8-25.06,20M .73-37.36,31.24-.93,.77-1.78,1.61-2.65,2.42-.24,.31,.34,.58,.55,.58,10.32-1.37,20.61-3.54,30.98-4.25-.03,.28,.05,.55-.09,.68-.78,.74-1.6,1.46-2.43,2.16-10.71,9.1-21.43,18.2-32.11,27.3,.29,.28,.38,.28,.23,.05-.04-.06-.22-.05-.34-.08,2.52,.76,5.3-.53,7.87-.72,8.82-1.41,17.56-3.38,26.44-4.4,.11-.01,.35,.07,.35,.12,.01,.2,.05,.46-.08,.59-9.24,8.29-18.63,16.41-27.92,24.64-.39,.46-1.29,1-1.32,1.56,.42,.32,.92,.28,1.41,.15,10.07-1.94,20.13-3.88,30.2-5.81,1.69-.32,3.41-.55,5.12-.81,.1-.02,.28,.07,.34,.15,.06,.08,.06,.24,0,M .31-.46,.52-.91,1.05-1.43,1.53-7.24,6.66-14.49,13.31-21.74,19.97-.8,.88-2.15,1.56-1.64,2.67,.04-.32-.06-.4-.3-.26l.3,.19Z"/><path class="cls-2" d="M892.55,367.68c2.59-4.6,5.15-9.23,7.76-13.82-.68-.63-1.44-.2-2.21-.07-13.91,3.39-27.43,7.57-41.1,11.6-.2,.02-.87-.17-.68-.53,2.24-4.3,4.98-8.34,7.41-12.54,1.15-2.14-1.44-.91-2.47-.66-5.23,1.71-10.48,3.38-15.67,5.18-7.3,2.27-14.42,5.71-21.79,7.46-.28-.11-.36-.31-.22-.55,1.85-3.11,3.69-6.22,5.57-9.32,.88-1.45,1.85-2.87,2.77-4.31,.17-.27,.4-.61,.01-.85-.35-.23-.74-.04-1.1,.M 09-4.4,1.63-8.83,3.19-13.18,4.89-7.86,2.86-15.56,6.72-23.46,9.16-.59-.67,.26-1.39,.54-2.04,2.55-4.03,5.11-8.06,7.66-12.1,.24-.58,1.11-1.48,.88-2.04-.15-.24-.39-.3-.69-.18-4.17,1.75-8.37,3.45-12.49,5.26-5.19,2.29-10.3,4.68-15.3,7.23-.67,.34-1.43,.56-2.16,.82-.06,.02-.21-.08-.29-.15-.08-.07-.2-.2-.17-.26,.25-.61,.48-1.23,.82-1.81,2.56-4.39,5.14-8.77,7.7-13.16,1.96-3.3-.09-1.97-2.08-1.11-7.09,3.53-14.16,7.07-21.25,10.6-2.46,1.05-5.9,3.67-2.92-1.2,2.83-4.76,5.68-9.52,8.52-14.28,.52-.93,1.51-1.99,.55-2.98,.15,.13,.29,.2M 6,.43,.39h.01l-.42-.39c-.31,.54-.87,.81-1.43,1.07-8.55,3.88-16.42,8.67-24.73,12.8-.09,.04-.33,.03-.35-.01-.1-.18-.27-.42-.19-.56,3.38-6.52,7.53-12.63,11.38-18.9,.33-.79,1.5-1.82,.98-2.64-.76-.09-1.71,.65-2.44,.92-7.44,3.88-14.86,7.77-22.26,11.73-.42,.22-.96,.65-1.39,.37-.71-.46,0-.97,.24-1.43,4.59-7.81,9.75-15.31,14.28-23.16-.2-.8-1.43,.03-1.91,.17-6.89,3.56-13.81,7.06-20.59,10.82-2.67,1.44-3.33,1.67-3.4,1.27-.16-1.02,.65-1.79,1.16-2.63,4.47-7.48,9.35-14.79,14.2-22.11,3.14-4.35,2.79-4.62-1.93-2.18-6.99,3.44-13.89,7M .06-20.92,10.4-1.78,.19,.02-1.75,.35-2.4,6.16-10.35,13.96-20.21,20.1-30.47-.17-.22-.42-.26-.71-.15-.97,.37-1.95,.72-2.9,1.11-4.53,1.9-9.05,3.82-13.57,5.72-1.21,.43-2.35,1.26-3.68,.89l.12,.03c6.15-10.43,13.75-20.24,20.75-30.29,1.68-2.33,3.27-4.7,4.88-7.05,.04-.06-.03-.19-.09-.26-.08-.08-.24-.19-.31-.17-.76,.21-1.53,.4-2.27,.66-5.9,2.12-11.78,4.25-17.67,6.38-.83,.37-1.36,.13-.92-.92,.4-.67,.89-1.33,1.33-1.99,3.85-5.44,7.64-10.9,11.57-16.3,5.08-6.98,10.19-13.95,15.6-20.78,.71-.9,1.28-1.87,1.9-2.82,.04-.07-.01-.21-.08-M .28-.08-.08-.24-.19-.32-.18-1.03,.22-2.07,.43-3.07,.72-5.07,1.45-10.13,2.92-15.2,4.38-1.01,.29-2.04,.56-3.06,.82-.32,.1-.64-.42-.58-.62,9.24-13.34,19.18-26.19,29.29-39.05,2.46-3.09,4.9-6.19,7.33-9.29,.1-.13,0-.39-.08-.57-.27-.24-.8-.13-1.15-.08-6.16,1.1-12.27,2.48-18.41,3.69-1.04,.21-2.1,.36-3.17,.5-.18,.02-.43-.17-.6-.3,12.55-17.88,27.1-34.95,41.11-52.14,.9-1.07,1.82-2.14,2.72-3.21,.3-.36,.54-.74,.4-1.21-.92-.3-1.85-.11-2.78,0-6.81,.75-13.61,1.52-20.41,2.27-.44,0-1.79,.18-1.55-.49,17.01-22.29,35.32-43.79,54.04-64.M 72,7.84-.29,15.65-.1,23.5-.19,.8,.13,3.66-.3,3.23,.89-9.18,10.29-18.82,20.21-27.84,30.56-8.48,9.59-17.02,19.14-25.18,28.9-.45,.54-.88,1.09-1.25,1.66-.06,.1,.17,.44,.34,.48,8.16-.2,16.27-2.08,24.44-2.09,.21,.99-.83,1.58-1.34,2.31-9.44,10.5-18.79,21.04-27.8,31.78-5.03,5.99-10.01,12.01-14.99,18.03-.51,.62-1.21,1.18-1.28,1.97-.01,.15,.3,.48,.4,.46,6.97-1.17,13.87-2.65,20.81-3.99,.56-.08,2.72-.46,2.32,.33-12.28,15.46-25.68,30.19-37.5,45.99-1.06,1.33,.18,1.2,.97,1.1,6.37-1.74,12.73-3.5,19.1-5.25,.58-.07,1.36-.47,1.9-.19,M .09,.17,.23,.41,.14,.53-.82,1.11-1.65,2.22-2.54,3.3-9.76,12.39-20.67,24.57-28.96,37.54,.07,.08,.22,.18,.3,.16,.76-.21,1.53-.41,2.27-.66,5.46-1.85,10.91-3.7,16.36-5.55,1.09-.33,2.33-.96,3.41-.29v-.04c-9.71,11.25-18.38,23.51-27.13,35.53-.09,.15,.05,.4,.13,.59,.02,.04,.23,.09,.31,.06,8.02-3.25,15.9-6.81,23.87-10.18,1.96-.8,3.05-1.05,1.31,1.25-5.79,7.89-11.61,15.78-17.38,23.68-1.29,1.76-2.44,3.59-3.63,5.4-.09,.13,.08,.38,.18,.56,1.18-.11,2.37-.98,3.52-1.39,7.01-3.21,14.01-6.43,21.03-9.63,.56-.25,1.21-.38,1.82-.55,.04,0M ,.23,.18,.21,.24-5.31,8.5-11.6,16.49-17.26,24.8-.52,.74-.88,1.58-1.77,2.13,0,0,.2,.09,.2,.09l-.12-.17c1.03,.8,2.21-.15,3.2-.57,6.66-3.18,13.31-6.35,19.97-9.53,1.53-.62,2.95-1.67,4.64-1.74l-.08-.06c.08,1.39-1.22,2.33-1.89,3.46-4.77,6.74-9.65,13.35-13.69,20.48,.31,.86,2.36-.6,2.99-.78,8.12-3.89,16.29-8.25,24.79-11.34,.63,.11-.33,1.33-.47,1.69-3.77,5.71-7.55,11.41-11.33,17.12-.39,.77-1.25,1.47-1.02,2.37-.18,.01-.43,.01-.35,.24,.26,.05,.35-.05,.27-.3,1.59,.13,2.88-.97,4.3-1.53,7.94-3.65,15.67-7.72,23.83-10.89,.35-.09,.M 84,.2,.55,.57-3.78,5.69-7.77,11.33-11.17,17.19-.15,.26-.14,.59-.17,.88,0,.07,.19,.22,.25,.21,2.86-.75,5.47-2.3,8.21-3.41,7.62-3.45,15.48-6.52,23.38-9.55,.45-.09,1.05-.52,1.45-.15,.07,.07,.16,.2,.12,.26-.33,.58-.65,1.17-1.04,1.73-3.2,4.49-6.42,8.97-9.62,13.46-.4,.56-.7,1.16-1.02,1.74,.11,.53,.85,.42,1.25,.27,12.33-4.58,24.64-10.16,37.28-13.73,.62,.26-.33,1.3-.58,1.7-2.83,4.16-5.66,8.32-8.48,12.49-.17,.51-1.45,1.65-.7,1.98,12.37-3.76,24.7-8.51,37.25-12.24,1.24-.24,2.55-1.08,3.79-.63-11.29,18.87-15.91,16.75,7.36,10.31M ,8.97-2.43,18.07-5.34,27.17-7.06,.11,.04,.28,.16,.27,.2-.14,.41-.25,.83-.49,1.21-2.64,4.23-5.51,8.33-7.96,12.67,1.07,.6,2.07-.05,3.16-.21,14.81-3.39,29.8-7.26,44.81-9.4,.72,.23-.11,1.28-.35,1.71-1.93,3.2-3.87,6.4-5.78,9.6-.46,.76-1.09,1.48-1.04,2.39,.79,.37,1.58,.16,2.36,.03,3.55-.62,7.08-1.31,10.65-1.86,12.59-1.85,25.13-3.94,37.81-5.19,.9,0,2.53-.4,1.93,1.08-2.37,4.22-4.76,8.43-7.15,12.65l.08-.06c-8.06,1.62-16.8,1.91-25.01,3.31-9.84,1.14-19.46,3.23-29.28,4.45l.09,.08c2.17-3.92,4.28-7.88,6.53-11.76,.21-.41,.72-1.07M ,.52-1.49-.28-.17-.71-.36-1.02-.3-4.05,.73-8.12,1.43-12.14,2.26-11.81,2.46-23.59,5.02-35.21,7.99l.07,.12Z"/><path class="cls-2" d="M342.27,130.02c-3.54,23.39-7.76,46.69-10.31,70.21l.13-.12c-7.12-1.58-13.98-4.43-21.01-6.46-.61-.19-1.74-.64-2.08,.1-2.35,19.96-3.22,40.05-4.55,60.1l.14-.05c-6.97-3.26-13.86-6.7-20.88-9.84-.5-.21-1.06,.08-1.1,.58-.49,16.47-.85,32.96-.31,49.44,.13,3.28-.82,2.45-3.07,1.21-5.91-3.58-11.72-7.28-17.71-10.73-.23-.13-.72,.03-1.19,.06,.13,12.64,1.06,25.23,1.81,37.84,.16,2.69,.26,5.38,.36,8.07,0,M .18-.17,.37-.27,.56-.59,.5-1.73-.62-2.32-.95-5.8-4.17-11.45-8.51-17.18-12.76-.58-.33-1.22-1.05-1.91-1.03-.25,.2-.6,.41-.52,.77,1.12,13.44,2.31,26.87,3.78,40.27-.02,2.7-2.85-.79-3.77-1.31-5.87-4.9-11.73-9.81-17.61-14.71-.51-.37-1.72-1.46-1.98-.33,.58,5.37,1.32,10.72,2.03,16.07,.93,7.07,1.82,14.14,2.81,21.2,.02,.41-.7,.36-.87,.28-7.77-6.8-15.16-14.02-22.8-20.97-2.46-2.08-.46,4.72-.56,5.73,1.3,9.53,3.15,18.99,4.4,28.52-.37,0-.73,.09-.85-.01-.83-.7-1.66-1.41-2.41-2.16-7.8-7.67-15.25-15.72-23.24-23.18-.15-.1-.57-.06-.59M ,.17,.24,1.92,.44,3.85,.75,5.77,1.33,8.22,2.77,16.43,4.08,24.66,.07,.47,.64,1.15-.2,1.36-.71,.18-1.05-.56-1.43-.97-6.44-6.91-12.86-13.83-19.29-20.75-2.49-2.68-4.97-5.36-7.48-8.04-.13-.14-.43-.18-.67-.24-.49,0-.35,1.07-.37,1.41,.79,6.33,2.08,12.6,2.94,18.91,1.9,10.74,1.83,10.3-5.12,2.33-8-9.06-16-18.13-24-27.19-.67-.59-1.12-1.73-2.1-1.79-.16,.02-.41,.29-.39,.43,.49,3.97,.99,7.93,1.52,11.89,.45,4.58,1.56,9.28,1.71,13.79-1.17,.02-1.85-1.45-2.65-2.17-11.3-12.87-21.8-26.74-33.48-39.12-1.06-.13-.3,2.83-.38,3.58,.42,6.43,M 1.46,12.91,1.56,19.32-.61,.63-1.21-.48-1.62-.86-12.59-15.42-25.18-30.85-37.76-46.28-.72-.86-1.56-1.78-1.46-2.93-.13-6.03-.08-12.06-.08-18.1,0-.53,.14-1.06,.25-1.58,.07-.12,.54-.21,.66-.12,12.13,14.03,23.68,28.57,35.68,42.71,.69,.63,1.13,1.77,2.24,1.53-.26-7.3-1.14-14.6-1.6-21.9-.03-.41,.11-.83,.21-1.24,.01-.05,.28-.13,.36-.09,11.01,11.86,21.25,24.65,32.01,36.82,.52,.64,1.02,1.33,1.89,1.53,.3,.08,.48-.22,.41-.73-.34-2.79-.68-5.57-1.03-8.36-.72-5.57-1.45-11.13-1.98-16.72-.02-.17,.15-.37,.28-.53,.05-.05,.32-.07,.37-.0M 3,.62,.56,1.28,1.1,1.83,1.71,4.57,5.07,9.1,10.16,13.68,15.22,4.42,4.89,8.89,9.75,13.34,14.62,.39,.44,1.01,1.29,1.75,1.02,.29-2.87-.72-5.77-.96-8.65-.9-6.2-1.73-12.41-2.55-18.62-.08-.77-.61-2.74,.82-2,8.54,8.71,16.88,17.62,25.4,26.36,.62,.54,1.14,1.4,2.08,1.32,.04,0,.15-.16,.14-.25-.14-1.18-.29-2.35-.45-3.53-1.21-9.61-3.12-19.2-3.83-28.85,1.21-.21,1.88,1.01,2.74,1.65,6.96,6.72,13.9,13.46,20.86,20.18,.73,.54,1.38,1.53,2.3,1.68,.29,0,.47-.14,.44-.41-.54-5.05-1.33-10.06-1.99-15.09-.81-6.75-1.58-13.51-2.34-20.27-.02-.15M ,.23-.4,.41-.45,1-.06,1.62,1.04,2.37,1.55,6.36,5.57,12.72,11.14,19.08,16.71,.77,.52,1.43,1.56,2.47,1.37,.08,0,.2-.14,.19-.22-.04-.97-.05-1.93-.15-2.9-1.16-12.21-2.94-24.49-3.41-36.71,.93-.27,1.59,.53,2.3,.98,6.04,4.61,12.08,9.23,18.12,13.85,1.25,.87,3.03,2.66,2.83-.23-.94-14.28-2.08-28.59-2.43-42.88,1.16-.36,1.94,.46,2.88,.96,4.75,3.02,9.48,6.05,14.22,9.07,1.63,.84,3.1,2.36,4.92,2.66,.94-.15,.49-1.65,.59-2.35-.1-15.51-.57-31.02-.23-46.53,.03-2.72,3.03-.23,4.32,.25,5.25,2.63,10.5,5.26,15.76,7.88,.7,.25,1.8,1.05,2.45M ,.41,.98-17.71,1.59-35.52,2.83-53.25,.28-1.09-.26-3.83,1.47-3.51,6.48,2.13,12.95,4.26,19.43,6.38,1.43,.49,2.88,.94,2.99-1.09,1.69-16.65,3.83-33.25,6.03-49.84,.78-4.9,1.05-9.93,2.49-14.7l-.13,.09c5.91,.99,11.83,1.98,17.74,2.97,2.36,.26,4.73,1.12,7.1,.69l-.1-.1Z"/><path class="cls-2" d="M1256.91,1041.89c1.6-.11,2.33,1.51,3.38,2.42,8.52,9.16,16.93,18.41,25.51,27.51,.35,.28,1.03,.21,.98-.38-.55-3.63-1.12-7.27-1.68-10.9-.86-5.66-1.79-11.32-2.6-16.99-.02-.13,.23-.4,.39-.41,1.2,.1,1.96,1.81,2.84,2.56,9.02,10.2,18.03,20.41M ,27.06,30.61,.75,.64,1.41,2.02,2.52,1.76-3.48-34.04-8.49-32.03,14.6-5.95,5.99,7.02,11.79,14.21,17.88,21.14,.22,.32,.75,.26,.91-.09,.06-.32,.13-.64,.11-.95-.5-6.88-1.14-13.75-1.68-20.63,.03-.33,.22-1.02,.68-.92,.38,.3,.78,.59,1.08,.94,2.38,2.87,4.74,5.76,7.1,8.64,9.86,12.09,19.73,24.17,29.57,36.27,2.29,2.82,2.05,2.02,2.07,5.71,.01,2.26,0,4.52,0,6.79-.01,3.55,.1,7.11-.06,10.66-.49,1.64-2.67-1.77-3.18-2.23-7.07-8.53-14.12-17.06-21.19-25.59-3.8-4.58-7.61-9.14-11.44-13.71-.48-.42-1.18-1.58-1.84-1.53-.42,0-.47,.43-.49,.7M 5,.36,7,1.04,13.98,1.59,20.96,.03,.32-.04,.64-.1,.96-.06,.14-.52,.24-.65,.17-8.12-8.56-15.45-17.92-23.29-26.75-3.43-3.84-6.59-7.95-10.23-11.61-.13-.07-.57,.03-.64,.18,.18,7.15,1.75,14.36,2.41,21.52,.17,1.38,.15,2.78,.2,4.18,0,.06-.14,.15-.24,.19-.11,.04-.33,.09-.37,.05-.54-.47-1.11-.94-1.58-1.46-4.41-4.89-8.8-9.8-13.21-14.69-4.26-4.71-8.56-9.41-12.84-14.11-4.63-5.33-2.67-.04-2.35,3.29,1.15,7.8,2.32,15.59,3.07,23.44-.13,.93-1.38-.06-1.69-.44-8.34-8.74-16.72-17.44-25.09-26.15-.32-.33-.73-.61-1.12-.9-.51-.11-.53,.66-.M 54,1.01,.42,3.21,.87,6.42,1.32,9.63,.85,6.21,1.76,12.41,2.61,18.62,.14,1.07,.17,2.14,.23,3.21,0,.09-.1,.26-.15,.26-1.33,.05-2.1-1.55-3.12-2.26-6.96-6.72-13.9-13.45-20.86-20.17-.67-.57-1.18-1.37-2.21-1.21,.49,6.22,1.63,12.41,2.32,18.62,.71,5.57,1.38,11.14,2.05,16.72,.03,.29-.1,.6-.2,.89-.01,.04-.3,.09-.37,.05-.53-.31-1.09-.61-1.53-.99-5.01-4.37-9.98-8.76-14.99-13.12-2.18-1.9-4.41-3.77-6.65-5.63-.12-.1-.5-.04-.75,0-.25,.29-.13,.85-.14,1.24,.9,8.8,2.03,17.58,2.79,26.4,.32,3.54,.62,7.09,.91,10.64-.08,.56,.33,1.65-.53,1M .68-.73-.03-1.31-.7-1.91-1.06-6.23-4.76-12.46-9.54-18.69-14.3-.47-.36-.88-.81-1.62-.85-1.24,.09-.11,5.37-.25,6.53,.84,12.47,1.73,24.94,2.05,37.43-.36,1.37-2.43-.44-3.12-.77-5.39-3.4-10.72-6.89-16.12-10.27-.98-.47-1.62-1.48-3.04-1.27-.68,.78-.32,1.65-.31,2.48-.03,15.71,1.01,31.48,.09,47.15-.03,.22-.7,.54-.93,.44-.94-.42-1.88-.83-2.79-1.28-5.99-2.87-11.79-6.14-17.89-8.78-.29-.12-.87,.17-.89,.44-.87,18.71-1.35,37.49-3.06,56.14-.05,.27-.61,.52-.94,.42-6.49-2.08-12.95-4.25-19.43-6.36-.85-.13-2.26-.99-2.85-.05-2.31,16.79M -3.74,33.69-6.3,50.46-.61,4.39-1.21,8.78-1.83,13.16-.11,.75-.25,1.5-.95,2.08,0,0,.14-.08,.14-.08-7.67-1.61-15.52-2.62-23.25-4.05-1.54-.33-.71-2.1-.72-3.17,3.53-22.15,7.72-44.3,9.64-66.64l-.11,.12c7.14,1.57,14.01,4.43,21.06,6.46,.63,.14,1.66,.67,2.13,.02,2.3-19.99,3.22-40.13,4.45-60.22l-.14,.04c6.59,3.14,13.17,6.29,19.76,9.43,.61,.23,1.5,.89,2.09,.33,1.33-16.42,.68-33.17,.6-49.7-.11-3.15,.69-2.68,3.01-1.35,3.75,2.28,7.48,4.59,11.22,6.88,2.14,1.31,4.28,2.61,6.46,3.88,.25,.14,.73,.02,1.24,.02-.16-15.42-1.62-30.78-2.21M -46.18-.07-.59,.84-.51,1.16-.34,6.12,4.16,11.89,8.74,17.85,13.11,.78,.58,1.65,1.09,2.52,1.6,.09,.05,.57-.14,.6-.26,.11-5.56-.89-11.17-1.23-16.74-.77-7.83-1.66-15.66-2.41-23.5-.21-2.8,1.76-.73,2.85,.08,5.96,4.98,11.91,9.96,17.88,14.94,.78,.51,1.47,1.52,2.51,1.27-.45-7.57-1.94-15.21-2.77-22.8-.52-3.74-1.08-7.48-1.57-11.23-.15-1.17-.14-2.35-.19-3.53,0-.06,.14-.15,.24-.19,.6-.27,1.34,.74,1.83,1.05,6.95,6.44,13.89,12.89,20.84,19.33,.55,.47,1.04,1.11,1.86,.91-.66-8.49-2.56-17.09-3.7-25.61-.46-2.88-.94-5.76-1.39-8.65-.03-M .18,.12-.38,.18-.57,1.05,.15,1.67,.89,2.35,1.6,7.28,7.34,14.56,14.68,21.85,22.01,.84,.66,1.43,1.88,2.63,1.78-1.04-10.57-3.4-21.13-4.91-31.69h-.09Z"/><path class="cls-2" d="M1074.53,313.27c-19.6,1.34-38.67,3.19-58.19,5.13-.36,0-.76-.41-.6-.65,.55-.86,1.08-1.73,1.67-2.58,2.63-3.88,5.53-7.6,7.99-11.59,.2-1.25-3.05-.39-3.83-.44-6.36,.9-12.72,1.84-19.08,2.73-9.42,1.32-18.75,2.96-28.07,4.64-.53,.1-1.05,.12-1.53-.13,.04-.79,.66-1.39,1.15-2.02,2.81-3.67,5.64-7.34,8.45-11.01,.39-.72,2.66-2.67,.83-2.8-15.35,2.52-30.58,5.93-4M 5.7,9.48-.51,.13-1.04,.24-1.53-.08,0-.81,.69-1.38,1.18-2,3.35-4.16,6.76-8.3,10.12-12.46,.3-.55,2.09-2.27,.94-2.37-13.6,2.96-27.04,6.58-40.41,10.19-.75,.1-3.98,1.42-3.69,.2,4.68-5.97,9.95-11.46,14.66-17.41-1.21-.59-2.55,.3-3.81,.47-8.43,2.24-16.74,4.75-25.06,7.25-4.16,1.25-8.31,2.5-12.48,3.73-.18,.05-.46-.09-.68-.18,.26-1.16,1.52-2.04,2.24-3.01,4.74-5.5,9.8-10.74,14.33-16.4,.26-1.06-3.22,.45-3.79,.5-10.01,3.18-20.07,6.25-29.93,9.71-1.6,.56-3.25,1.02-4.9,1.49-.17,.05-.46-.11-.66-.21,4.96-6.6,11.32-12.6,16.93-18.84,1.M 59-1.82,3.99-3.87-.38-2.46-10.63,3.37-21.3,6.68-31.73,10.46-2.35,.72-5.09,2.14-1.9-1.33,6.71-7.52,14.17-14.59,20.54-22.33-.56-.31-1.06-.21-1.57-.04-5.21,1.75-10.44,3.48-15.64,5.25-5.57,1.9-11.13,3.84-16.69,5.74-.36,.07-1.16,.29-1.36-.08,2.81-4.11,6.63-7.56,9.95-11.34,4.48-4.71,9.09-9.35,13.64-14.03,.65-.67,1.49-1.25,1.72-2.15-1.52-.29-3.05,.68-4.53,1-8.2,2.73-16.4,5.47-24.6,8.2-1.23,.27-3.11,1.16-1.48-.88,7.95-9.16,16.4-17.91,24.69-26.79,.8-.86,1.55-1.75,2.31-2.63,.06-.07,.07-.27,.03-.29-.23-.08-.52-.22-.71-.16-8.5M 6,2.56-17.15,5.06-25.64,7.85-.61,.2-1.3,.32-1.69,.81h.04c-.35-.49-.52-1-.07-1.5,3.09-3.38,6.13-6.8,9.31-10.12,7.35-7.68,14.77-15.31,22.16-22.96,.36-.49,1.27-.89,.83-1.58-.78-.27-2.18,.38-3.06,.49-7.15,1.86-14.29,3.73-21.44,5.6-1.24,.25-2.64,.94-3.84,.24l.06,.03c13.14-13.08,26.01-26.48,39.39-39.35,2.97-2.8-1.61-1.14-3.03-1.02-7.06,1.4-14.11,2.81-21.17,4.21-3.73,.63-1.9-.81-.31-2.5,15.15-15.12,30.65-29.78,46.31-44.44,.34-1.2-1.82-.52-2.49-.62-6.3,.49-12.58,1.12-18.88,1.68-4.14,.35-4.43,.14-1.26-2.82,5.72-5.44,11.43-1M 0.89,17.18-16.32,12.01-11.35,24.3-22.51,36.7-33.59,.94-.82,1.79-1.82,3.18-1.8,7.95-.03,15.9,.02,23.86,.03,1.57,.19,2.03,.37,.55,1.79-19,16.29-38.19,32.32-56.18,49.56-.12,.12-.02,.4,.03,.6,.01,.06,.21,.11,.33,.12,6.68-.19,13.35-1.41,20.02-2.01,1.47-.17,2.93-.39,4.4-.52,.59-.05,1.4-.37,1.74,.3,.24,.46-.34,.77-.69,1.08-15.87,13.72-31.07,27.96-46.21,42.4-2.78,2.74,4.16,.44,5.15,.42,7.2-1.36,14.41-2.72,21.62-4.07,2.1-.05-.68,1.87-1.17,2.44-12.68,11.35-24.88,23.19-37.04,35.06-.49,.48-1.15,.9-1.14,1.62,.67,.26,1.3,.08,1.9M 5-.08,5.4-1.35,10.79-2.69,16.19-4.03,3.47-.86,6.95-1.72,10.42-2.57,.62-.14,1.29-.32,1.87,.03-10.89,11.54-23.73,21.86-34.68,33.57-.91,1.72,2.55,0,3.22-.02,10.01-2.62,20.03-6.22,30.05-8.32,.08,.16,.2,.41,.11,.51-.72,.78-1.47,1.54-2.24,2.29-9.15,9.06-18.63,17.81-27.6,27.04-.1,.12-.02,.35,.03,.52,.02,.05,.25,.11,.35,.09,10.62-3.07,21.16-6.4,31.75-9.56,.98-.13,2.4-1.06,3.26-.42,0,.59-.93,1.1-1.28,1.59-7.58,7.57-15.16,15.14-22.73,22.71-.37,.53-2.02,1.89-.93,2.02,6.76-1.65,13.3-4.11,19.98-6.04,5.15-1.58,10.34-3.1,15.51-4.M 63,.34-.1,.77-.05,1.15-.01,.72,.16-.74,1.47-1.08,1.83-6.82,7.18-14.25,13.99-20.53,21.57,.67,.39,1.23,.21,1.9,0,3.51-1.1,7.03-2.17,10.52-3.31,7.73-2.52,15.58-4.79,23.46-6.99,.89-.25,1.75-.58,2.73-.4l.1,.08c-.37,1.67-2.16,2.67-3.19,4-5.05,5.7-10.94,10.85-15.51,16.88-.01,.03,.23,.2,.3,.18,1.02-.23,2.06-.45,3.06-.74,12.39-3.61,24.86-7.15,37.42-10.29,.63-.09,.95,.22,.55,.74-5.24,6.26-11.4,11.93-16.21,18.47-.02,.03,.2,.21,.28,.2,.64-.1,1.3-.2,1.92-.37,11.85-3.24,23.89-6.02,35.85-8.96,4.83-1.09,6.24-1.26,6.15-.93-.41,1.65M -2.03,2.74-3.14,4.06-3.5,4.22-7.35,8.21-10.76,12.51-.81,1.45,1.45,.96,2.21,.75,14.16-3.16,28.37-6.08,42.66-8.7,.73-.07,1.59-.39,2.22,.13,.08,.05,.11,.23,.06,.3-.4,.56-.81,1.12-1.25,1.66-2.93,3.62-5.88,7.22-8.81,10.84-.77,1.19-2.2,2.17-2.27,3.61,10.78-1.17,21.58-3.68,32.44-5,6.23-.83,12.45-1.94,18.72-2.5,.38-.02,.79,.39,.62,.63-3.36,4.81-6.93,9.48-10.37,14.24-.29,.3-.52,.86-.09,1.13,2.94,.25,5.87-.42,8.79-.69,16.27-1.9,32.63-3.37,48.99-4.3l-.08-.12c-3.55,5.37-6.81,10.99-10.53,16.23l.1-.05Z"/><path class="cls-2" d="MM 1005,333.95c-7.9,1.23-15.88,2.1-23.78,3.26-8.96,1.36-17.93,2.67-26.81,4.34-1.02,.11-2.12,.52-3.11,.09-.11-.69,.39-1.22,.76-1.79,2.36-3.61,4.72-7.22,7.09-10.83,.31-.48,.65-.94,.48-1.51,.05-.04,.11-.08,.16-.12-.25-.02-.27,.03-.05,.17-.93-.37-1.86-.1-2.76,.07-2.49,.46-4.96,1-7.45,1.48-12.69,2.13-25.23,6.02-37.76,7.96-.09-.17-.22-.4-.14-.53,.46-.78,.94-1.55,1.48-2.29,2.47-3.46,4.96-6.91,7.43-10.38,.27-.53,1.34-1.71,.35-1.89-1.94,.43-3.91,.82-5.82,1.33-7.16,1.88-14.33,3.76-21.46,5.72-5.49,1.45-10.82,3.36-16.34,4.68-.17,M .02-.5-.2-.44-.39,3.16-5.42,7.67-10.04,10.84-15.45,.05-.17-.29-.43-.45-.4-.9,.23-1.79,.47-2.67,.72-12.18,3.47-24.04,7.6-36.01,11.49-.69,.25-1.54,.63-2.24,.38-.39-.19-.14-.56,.05-.82,3.88-5.44,8.1-10.65,12.04-16.05-1.02-.71-2.29,.23-3.38,.45-10.87,3.77-21.74,7.55-32.4,11.69-1.91,.56-4.98,2.24-2.4-1.14,4.24-5.5,8.56-10.94,12.76-16.48,.18-.24,.14-.42-.13-.52-8.97,2.61-17.75,6.74-26.64,9.89-2.67,1.03-5.28,2.14-7.93,3.21-.52,.21-1.04,.12-1.49-.17l-.1,.08c4.81-6.28,9.19-12.84,14.29-19.01,.36-.45,.8-.87,.61-1.46l.22-.1-.1M 3,.18c-2.56,.01-4.88,1.76-7.32,2.49-7.6,2.84-14.88,6.74-22.39,9.41-.09-.18-.27-.44-.18-.57,2.31-3.28,4.6-6.57,6.99-9.81,2.8-3.8,5.68-7.56,8.52-11.34,.27-.36,.45-.77,.65-1.16,.03-.07-.06-.2-.14-.26-.07-.06-.24-.12-.31-.1-.98,.35-1.97,.69-2.91,1.09-8.19,3.48-16.35,7.04-24.56,10.49-.35,.19-.85-.02-.73-.4,5.81-8.32,12.34-16.14,18.45-24.25,1.59-2.23,.44-1.63-1.34-1.1-7.22,2.89-14.44,5.77-21.49,8.92-1.8,.67-6.28,3.37-3.18-.67,7.1-9.14,14.34-18.18,21.37-27.36,.06-.07,.06-.26,0-.28-1.08-.51-2.2,.48-3.26,.73-8.01,2.95-15.81M ,6.75-23.92,9.26l.07,.09c-.36-1.18,.84-1.92,1.41-2.83,7.48-9.53,15.02-19.03,23.02-28.29,.73-1.08,2.21-1.92,2.07-3.32,.22,.04,.47,.08,.41-.21-.27-.11-.38-.01-.33,.28-.69-.19-1.32,0-1.94,.21-5.76,2.05-11.55,4.06-17.28,6.2-6.89,2.49-7.87,2.72-7.72,2.29,9.18-12.92,20.39-24.68,30.78-36.89,1.77-1.97,3.61-3.75-.67-2.54-6,1.55-12.01,3.11-18.01,4.66-.76,.2-1.53,.43-2.33,.09l.11,.05c-.06-.59,.37-1.01,.75-1.45,12.31-14.91,25.71-28.93,38.29-43.62,.27-.38-.4-.53-.63-.52-7.62,1.35-15.22,2.76-22.83,4.14-.12,.02-.33-.02-.37-.08-.4M -.52,.14-.94,.45-1.35,11.46-13.07,23.07-26,35.2-38.66,3.28-3.42,6.52-6.86,9.76-10.31,.33-.51,1.56-1.38,.69-1.83-7.88,.17-15.77,1.45-23.65,1.98-1.53-.36,.28-1.69,.71-2.29,17.14-19.2,35.38-37.84,53.65-56.27,.71-.74,1.53-1.15,2.72-1.15,7.54-.2,15.09-.14,22.64-.13,2.29,.24,3.97-.28,1.25,2.28-14.76,13.92-29.16,28.21-43.53,42.5-3.55,3.52-6.95,7.14-10.41,10.72-.48,.62-1.54,1.35-.25,1.72,7.36-.41,14.72-1.37,22.07-1.99,3.09-.21,1.75,.84,.36,2.35-6.14,6.14-12.39,12.22-18.43,18.42-8.94,9.18-17.74,18.44-26.59,27.67-.36,.41-.92M ,.8-.57,1.37,7.42-.52,15.01-2.51,22.45-3.65,.51-.09,1.02-.18,1.49,.1,.01,.72-.63,1.16-1.11,1.66-4.7,4.86-9.44,9.69-14.09,14.57-8.66,8.93-16.9,18.18-25.39,27.17,.1,.03,.19,.06,.27,.08l-.29-.13c1.85,.87,3.87-.52,5.73-.84,6.72-1.89,13.45-3.78,20.18-5.66,.5-.07,1.99-.6,1.99,.15-10.35,11.92-21.63,23.27-31.74,35.38-.45,.52-1.08,.98-1.09,1.68,0,.07,.18,.22,.24,.21,8.82-2.32,17.37-5.76,26.16-8.31,.52-.17,1-.29,1.62,.07-8.66,10.16-17.76,19.96-26.28,30.16-.53,.62-.94,1.29-1.4,1.95-.04,.17,.32,.39,.47,.35,8.21-2.56,16.19-5.82M ,24.31-8.65,1.3-.32,2.81-1.43,4.11-.62l.09-.09c-3.59,3.53-6.7,7.5-9.97,11.3-4.41,5.26-8.79,10.54-13.18,15.82-.18,.31-.69,.81-.35,1.11,.08,.07,.25,.15,.33,.13,.99-.32,2-.62,2.96-1,7.84-3.07,15.64-6.2,23.62-9.02,2.6-.93,2.23-.19,.81,1.58-6.11,7.3-12.26,14.59-18.1,22.1-.3,.38-.44,.77-.15,1.19-.19-.16-.28-.15-.29,.03l.23-.11c9.71-3.14,19.11-7.48,28.9-10.71,.98-.35,1.98-.67,2.98-.96,.17-.05,.46,.12,.66,.22,.05,.03,.02,.23-.05,.3-.75,.89-1.51,1.78-2.28,2.66-5,5.74-10.01,11.48-15.01,17.23-.54,.62-1.04,1.25-1.51,1.91-.09,.M 13,.06,.38,.15,.56,.45,.16,1.01-.19,1.47-.3,7.09-2.61,14.2-5.19,21.28-7.83,4.64-1.73,9.33-3.34,14.11-4.81,.19-.06,.48,.09,.71,.18,.04,.01,.01,.2-.04,.29-3.6,4.73-7.85,9-11.64,13.58-1.68,1.95-3.27,3.95-4.89,5.93-.31,1.45,3.28-.48,3.98-.54,7.42-2.56,14.82-5.14,22.25-7.67,4.09-1.39,8.22-2.69,12.34-4.01,.2-.06,.56-.04,.7,.07,.14,.11,.19,.42,.09,.56-.46,.65-.98,1.29-1.49,1.92-3.62,4.41-7.25,8.82-10.87,13.23-.59,.72-1.18,1.44-1.71,2.19-.09,.12,.05,.37,.14,.54,12.47-3.2,25.02-7.91,37.64-11.35,1.24-.21,2.55-1.11,3.78-.64-3M .51,5.85-8.83,10.95-12.61,16.77,1.38,.49,2.58-.42,3.93-.64,12.97-3.58,25.93-7.21,39.12-10.27,.72-.17,1.23-.35,1.93,.13-3.44,4.77-7.12,9.37-10.65,14.07-.29,.47-1,1.33-.18,1.6,13.6-2.78,27.19-6.15,40.93-8.71,2.09-.19,4.65-1.41,6.65-.77,.08,.7-.44,1.21-.84,1.77-2.96,4.23-6.2,8.28-8.95,12.64-.06,.21,.27,.72,.59,.67,2.64-.42,5.28-.84,7.92-1.27,14.51-2.38,29.05-4.83,43.67-6.4,.34,0,.72,.44,.57,.69-3.01,4.83-6.13,9.59-9.24,14.35l.1-.06Z"/><path class="cls-2" d="M475.58,1023.99s.02,.02,.02,.03c-.03,0-.06,.01-.09,.01,0,0,.0M 1,0,.01-.01,.02,0,.03-.03,.05-.02h.01Z"/><path class="cls-2" d="M662.93,1031.59c-9.08,4.41-18.46,8.73-28.1,12.07-.19,0-.6-.23-.58-.31,.92-3.72,2.69-7.2,3.96-10.81,.54-2.07-1.43-.79-2.44-.5-11.57,4.56-23.3,9.13-35.26,12.76-.11,.04-.54-.25-.52-.34,1.02-3.36,2.57-6.56,3.81-9.85,.89-2.23-.37-1.85-2.02-1.36-12.38,4.05-24.87,7.62-37.48,11.04-1.46,.34-2.11,.02-1.46-1.55,1.09-3.19,2.77-6.29,3.55-9.56-.02-.17-.31-.47-.43-.45-.8,.07-1.6,.18-2.37,.35-12.69,2.94-25.36,5.87-38.2,8.12-1.27,.02-5.46,1.67-5.07-.23,1.18-3.31,2.46-6M .59,3.54-9.93,.39-1-1.24-.95-1.98-.8-15.25,2.21-30.5,4.44-45.86,5.66-1.17,.1-2.4,.4-3.57-.12,.57-3.63,2.4-7.05,3.43-10.59,.15-.42,.09-.83-.28-1.17,17-1.93,34.11-3.13,51.02-5.94,1.53-.17,1.14,1.35,.84,2.25-.87,2.92-1.87,5.82-2.68,8.76,.69,.69,1.73,.3,2.6,.25,14.1-2.39,27.95-5.41,41.81-8.7,1.49-.12,.96,1.08,.7,1.93-.81,2.93-2.11,5.77-2.51,8.79-.02,.16,.26,.33,.47,.57,13.35-3.26,26.37-7.41,39.43-11.42,.49-.14,1.13,.3,1.02,.69-.9,3.38-2.29,6.62-3.14,10.02-.14,1.46,2.89-.23,3.63-.31,8.42-3.06,16.92-6,25.19-9.33,2.31,.99M ,4.64,1.94,7,2.85-.51,1.69-1.01,3.38-1.5,5.06-.05,.17,.14,.4,.26,.58,2.8-.38,5.55-2.13,8.24-3.07,4.91,1.71,9.9,3.24,14.95,4.59Z"/><path class="cls-2" d="M678.79,1035.21c-3.98,2.1-7.99,4.16-11.96,6.26-.89,.47-1.87,.83-2.81,1.22-.08,.04-.25-.02-.33-.08-.1-.07-.21-.19-.19-.27,.87-3.32,2.27-6.48,3.37-9.73,3.93,.98,7.91,1.84,11.92,2.6Z"/><path class="cls-2" d="M696.29,1037.77c-2.15,1.27-4.32,2.5-6.53,3.7-.86,.39-1.73,1.22-2.74,1h0c-.08-.02-.16-.04-.24-.07-.01,0-.02,0-.03-.01-.06-.01-.12-.04-.18-.06,0,0,.05,.01,.09,.01h0M c.68-1.84,1.35-3.67,2.02-5.5,2.53,.35,5.06,.66,7.61,.93Z"/><polygon class="cls-2" points="708.53 1043.43 708.53 1043.42 708.54 1043.43 708.53 1043.43"/><path class="cls-2" d="M715.36,1038.91c-2.26,1.52-4.72,2.8-6.83,4.51-.35-.34-.56-.74-.41-1.17,.38-1.19,.85-2.37,1.37-3.51,1.95,.09,3.91,.14,5.87,.17Z"/><path class="cls-2" d="M738.06,1038.08c-3.53,2.24-6.85,5.33-10.66,6.89-.29-.11-.35-.29-.26-.52,.74-1.92,1.5-3.85,2.26-5.77,2.88-.14,5.76-.34,8.66-.6Z"/><path class="cls-2" d="M766.68,1033.63c-7.05,4.63-13.84,9.65-20.M 8,14.4-.39,.27-.75,.65-1.37,.6-.18-.03-.39-.28-.35-.46,1.44-3.78,3.16-7.48,4.49-11.28,6.11-.85,12.12-1.94,18.03-3.26Z"/><path class="cls-2" d="M771.18,1312.07s.02-.03,.03-.05c.02,0,.05-.01,.07-.01l-.1,.06Z"/><path class="cls-2" d="M800.44,1026.36h-.12s0-.03,0-.04l.13,.04Z"/><path class="cls-2" d="M821.24,1148.14c-5.85,1.58-12.11,5.01-17.95,7.18-.46,.19-1.01,.26-1.52,.36-.07,.02-.29-.15-.28-.21,6.48-14.48,14.61-28.31,20.22-43.11,0-.07-.18-.21-.24-.21-6.41,2.35-12.05,6.22-18.38,8.9-.51-1.33,.52-2.26,.96-3.43,5.2-11.4M 4,11.39-22.94,15.25-34.62-1-.25-1.82,.67-2.68,1.04-4.24,2.48-8.46,4.97-12.71,7.44-.74,.43-1.4,.99-2.39,1.04-.36-.42-.11-.82,.06-1.22,2.66-6.21,5.32-12.42,7.97-18.63,1.65-3.88,3.27-7.75,4.91-11.63,.22-.51,.46-1.01,.12-1.53-.75-.03-1.24,.37-1.75,.71-4.87,3.27-9.79,6.46-14.82,9.47-.1,.06-.36,.1-.38,.07-.54-.55,.02-1.18,.22-1.76,3.72-8.87,7.56-17.69,10.51-26.77,.04-.43-.62-.35-.83-.27-5.22,3.33-10.02,7.27-15.25,10.58-.1,.06-.34,.1-.38,.07-.64-.48-.05-1.14,.12-1.72,2.91-7.05,5.25-14.24,7.9-21.36,.27-.71,.55-1.42,.4-2.17M -1.32,.07-2.22,1.38-3.33,2.01-3.57,2.63-7.12,5.27-10.69,7.89-.81,.44-1.56,1.37-2.56,1.22-.06-.01-.14-.2-.11-.29,.99-3.11,2.36-6.11,3.42-9.19-6.31,2.08-12.76,3.88-19.34,5.39-1.85,6.3-5.02,12.39-7.32,18.61-.33,.82-.63,1.64-.92,2.47-.02,.06,.12,.2,.23,.25,.71,.08,1.37-.64,1.98-.94,5.96-4.2,11.91-8.41,17.88-12.6,.79-.55,1.41-1.31,2.7-1.52-2.03,7.6-5.86,14.74-8.94,22.07-.32,1.12-2.12,3.52,.33,2.34,5.21-3.42,10.32-6.94,15.61-10.24,.16-.07,.86,.04,.78,.4-.19,.62-.36,1.25-.62,1.86-3.29,7.63-6.61,15.25-10.39,22.73-1.18,2.35M -2.01,4.03,1.31,1.99,4.92-3,9.79-6.06,14.74-9.03,.08-.05,.33-.05,.38,0,.64,.47,.09,1.16-.11,1.73-4.42,9.71-8.76,19.45-13.65,29-.48,1.34,0,1.33,1.12,.88,4.43-2.45,8.84-4.92,13.26-7.39,.99-.55,1.99-1.1,3.01-1.61,.13-.07,.46,.08,.67,.17,.08,.03,.14,.19,.11,.27-.23,.62-.44,1.24-.73,1.84-5.51,11.36-11.17,22.64-17.09,33.81-.29,1.37,2.24-.2,2.76-.34,4.84-2.35,9.66-4.71,14.48-7.07,.56-.26,1.09-.59,1.79-.42,.23,.9-.31,1.61-.69,2.39-6.59,13.19-13.64,26.25-20.92,39.19,.87,.65,1.71,.04,2.59-.21,4.57-1.86,9.12-3.73,13.68-5.59,.M 96-.35,4.59-2.26,4.2-.71-8.05,15.7-17.06,30.99-26.07,46.22-.22,.38-.31,.81-.42,1.23-.02,.05,.17,.21,.26,.21,.52-.03,1.07-.01,1.54-.16,6.41-1.96,12.74-4.14,19.18-5.98,.33-.02,.81,.25,.56,.63-9.8,18.12-20.65,35.58-31.66,53.04-.97,1.53-1.53,2.46,.98,1.9,6.91-1.41,13.74-3.2,20.7-4.33,.3-.04,.67,.46,.53,.72-12.36,21.41-26.34,42.02-39.73,62.83-.14,.25,.29,.66,.67,.64,1.07-.06,2.15-.09,3.22-.2,7.18-.81,14.34-1.63,21.51-2.45,13.33-21.72,26.41-43.53,38.56-65.72,.23-.53,.28-1.25-.57-1.2-7.15,1.51-14.29,3.07-21.46,4.54-.2,.04M -.48-.12-.69-.22,10.05-19.04,21.68-37.6,30.9-57.11-.96-.75-2.29,.16-3.37,.36-5.38,1.71-10.75,3.43-16.13,5.14-.59,.12-1.7,.68-1.98-.09,7.81-15.32,16.39-30.4,23.66-45.96,.43-.91,.85-1.82,1.26-2.73,.17-.39,.08-.88-.15-.89Zm-19.87-25.55c-.07,.02-.15,.02-.23,0-.1-.31,.44-.27,.23,0Z"/><path class="cls-2" d="M609.24,1009.08c-12.2,3.79-24.32,7.57-36.77,10.66-.82,.2-1.44-.15-1.31-.74,.76-2.95,1.39-5.92,2.02-8.89,.18-.92-.3-1.28-1.28-1.03-8.86,2.27-17.89,4.03-26.9,5.81-4.96,.99-9.99,1.74-15,2.6-.68,.19-1.73,.15-1.96-.61-.6-3M .2-1.41-6.35-1.99-9.55-.14-.9,.3-1.35,1.52-1.55,14.34-1.89,28.37-5.17,42.49-7.77,1.78,2.62,1.97,5.77,2.97,8.7,.14,.78,.48,1.73,1.5,1.59,7.95-1.65,15.73-4.05,23.46-6.32,3.67,2.48,7.42,4.85,11.25,7.1Z"/><path class="cls-2" d="M621.08,1015.56c-3.8,1.21-7.51,2.94-11.38,3.85-.19,0-.56-.22-.56-.33,.27-3.06,1.55-5.95,1.84-8.99,3.31,1.91,6.68,3.73,10.1,5.47Z"/><path class="cls-2" d="M701.31,988.58c-.38,2.64-.84,5.28-1.19,7.92-3.77-.4-7.51-.93-11.22-1.57,3.02-1.79,6-3.61,8.99-5.43,.86-.33,2.85-2.35,3.42-.92Z"/><path class="M cls-2" d="M783.14,974.12c-.05-.05-.28-.03-.34,.03-.75,.61-1.5,1.23-2.22,1.86-4.9,4.3-9.78,8.61-14.69,12.91-.63,.55-1.34,1.05-2.03,1.56-.06,.05-.26,.01-.38-.02-.1-.03-.27-.1-.27-.15-.02-.53-.08-1.07,.01-1.6,.63-4.02,1.71-8.03,2.1-12.08-.73-.21-1.12,.03-1.51,.35-6.51,5.41-13.4,10.44-19.7,16.05-.99-.88-.4-2.27-.25-3.38,.74-2.75,.78-5.56,1.3-8.33,.21-.84-.08-1.82-1.11-1.24-6.24,4.99-12.33,9.95-19.02,14.45-3.09,2.32-2.38,.02-2.14-2.36,.36-2.34,.79-4.69,1.18-7.03,.04-.49,.12-1.37-.62-1.21-6.49,4.16-12.77,8.75-19.32,12.96M ,11.83,.98,23.63,.79,35.51-.64,.86-.65,3.63-3.12,2.89-.36,13.7-1.84,26.81-5.23,39.19-9.95,.69-3.77,1.24-7.56,1.82-11.35,.03-.15-.23-.33-.4-.47Zm-39.11,18.99l-.05-.13,.12,.06-.07,.07Z"/><path class="cls-2" d="M800.99,973.65c-.02,1.24-.07,2.48-.32,3.7-3.22,1.71-6.51,3.31-9.86,4.81,3.3-2.81,6.25-5.91,9.55-8.67,.14-.08,.58,0,.63,.16Z"/><path class="cls-2" d="M807.64,1020.02c-1.07,.55-6.96,6.67-5.55,2.39,1.86-.77,3.71-1.56,5.55-2.39Z"/><path class="cls-2" d="M810.4,1039.05s.02-.03,.03-.04c.01,.01,.01,.02,.02,.02l-.05,.0M 2Z"/><path class="cls-2" d="M822.93,1306.26l.03-.06s.04-.01,.06-.01l-.09,.07Z"/><path class="cls-2" d="M834.46,1045.34c-.03-.07-.07-.14-.1-.22,.05,.02,.08,.1,.1,.22Z"/><path class="cls-2" d="M842.75,1180.57c-.36,.81-.71,1.62-1,2.44-.05,.16,.15,.38,.28,.56,.03,.05,.24,.05,.35,.02,5.93-1.65,11.73-3.78,17.61-5.61,2.12-.58,3.57-1.44,2.27,1.6-8.54,19.9-17.55,39.51-27.03,59.01,.58,.4,1.1,.4,1.63,.28,3.25-.71,6.49-1.42,9.73-2.14,3.24-.72,6.48-1.45,9.72-2.16,.63-.14,1.31-.25,1.94,.36-10.76,24.14-22.83,47.86-35.29,71.27-7.5M 9,.76-15.15,1.68-22.73,2.53-1.89-.04-3.23,.67-1.79-1.94,12.17-21.37,24.11-42.88,35.06-64.88,.26-.65,1.22-1.36,.35-2.02-.65-.48-1.52,.04-2.27,.21-6.37,1.35-12.7,2.86-19.09,4.14-.58,.16-1.46-.02-1.1-.79,4.67-9.17,9.61-18.24,14.22-27.42,5.08-10.31,10.52-20.47,14.85-31.03-.4-.64-1.49-.15-2.08-.03-5.37,1.73-10.72,3.48-16.09,5.21-1.74,.39-4.13,1.73-2.48-1.28,8.15-16.29,15.99-32.58,22.92-49.3,.06-.14-.13-.37-.26-.54-.04-.05-.27-.06-.37-.02-5.67,2.16-11.19,4.71-16.8,7.02-1.05,.38-3,1.42-2.14-.66,6.52-14.21,13.03-28.42,18.5M -43.01,.02-.19-.08-.48-.24-.55-.18-.09-.54-.03-.75,.07-5.82,2.82-11.37,6.18-17.29,8.78-.42-.51-.27-.92-.1-1.33,5.29-12.35,10.84-24.74,14.94-37.49,.04-.39-.63-.39-.83-.32-5.37,3-10.44,6.53-15.85,9.45-.21,.06-.85-.02-.8-.38,.3-.93,.6-1.87,.95-2.79,2.45-6.38,4.94-12.75,7.35-19.13,1.21-3.19,2.3-6.41,3.42-9.62,.21-.79,.56-1.68-.12-2.33v-.18c-4.39,3.72-9.53,6.62-14.21,10.03-.5,.23-1.1,.87-1.68,.64-.1-.05-.23-.18-.21-.26,.2-.73,.4-1.47,.65-2.19,2.98-8.96,7.09-17.97,9.02-27.07-.32-.05-.75-.12-1.02,.12-4.75,3.79-10.03,7.08-M 14.46,11.17-.96-.85-.28-2.03-.04-3.05,2.2-6.81,4.54-13.59,6.67-20.43,5.15-2.61,10.17-5.42,15.05-8.42-5.19,21.9-10.92,23.26,9.69,7.61,.13-.11,.48-.05,.71-.03,.08,.01,.18,.19,.17,.28-.34,1.92-.96,3.8-1.42,5.69-1.94,7.26-4.16,14.47-6.54,21.65-.2,.91-.8,1.92-.36,2.81-.05-.04-.12-.02-.19,.05,.1,.06,.19,.12,.29,.17,.01,.02,.01,.04,.02,.06,0-.02-.01-.04-.01-.05,2.91-2.08,5.82-4.17,8.73-6.24,2.16-1.29,4.53-3.73,6.82-4.44,.64,.18,.21,1.26,.07,1.75-2.82,9.87-6.12,19.63-9.6,29.35-1.61,4.53-1.87,4.87,2.48,2.23,4.31-2.57,8.47-5M .39,12.85-7.83,.22-.08,.88-.06,.85,.32-3.75,12.6-8.34,24.93-13.02,37.29-.15,.72-.99,1.84-.18,2.33,5.34-2.07,10.39-5.42,15.61-7.94,.65-.26,1.8-1.19,2.19-.2-.43,1.47-.85,2.94-1.39,4.38-5,13.75-10.65,27.33-15.84,40.98,.5,.75,1.7-.14,2.37-.28,5.65-2.19,11.04-5.15,16.8-6.95,.42,.37,.32,.8,.17,1.2-6.26,16.65-13.29,32.96-20.63,49.27Z"/><path class="cls-2" d="M378.87,529.22c.56-.16,1.04-.01,1.51,.21,4.55,1.9,8.89,4.8,13.7,5.88,.39-.7,.2-1.34,.08-1.97-.92-4.78-1.9-9.56-2.78-14.35-1.1-7.44-2.95-14.9-3.32-22.39,.02-.11,.43-.3M ,.59-.26,4.19,1.34,8.14,3.32,12.24,4.9,.71,.17,1.84,.99,2.41,.26-.03-4.81-1.07-9.64-1.45-14.45-.95-8.89-1.83-17.8-2.27-26.73-.02-.42,.12-.84,.23-1.25,.01-.06,.25-.14,.35-.11,5.13,1.3,9.86,4.34,15.18,4.98l-.09-.08c.77,8.78,.97,17.64,1.92,26.42,.46,4.72,.97,9.43,1.48,14.15,.1,.96,.11,1.94,.66,2.84l.16-.13c-3.92,.15-7.86-2.3-11.67-3.25-.99-.34-1.97-.69-2.96-1.03-.29-.1-.84,.24-.83,.5,.75,8.47,2.28,16.88,3.78,25.28,.75,3.71,1.33,7.45,1.96,11.18,.24,1.53-.35,1.87-1.77,1.33-2.92-1.09-5.83-2.2-8.75-3.31-.92-.15-3.78-2.06-M 4.15-.87,.86,7.18,3.12,14.17,4.61,21.26,.95,4.64,2.68,9.19,3.27,13.87-1,.17-1.67-.22-2.36-.5-3.35-1.37-6.68-2.78-10.02-4.17-.96-.29-1.91-1.06-2.93-.7,0,0,.15-.17,.15-.17-.31,.91,0,1.8,.26,2.68,2.75,10.09,6.04,20.06,9,30.12-.46,.62-1.51,.05-2.09-.14-4.35-1.93-8.67-3.92-13.01-5.86-.17-.07-.48,.05-.7,.13-.1,.03-.2,.19-.18,.27,.21,.84,.41,1.69,.67,2.52,2.66,8.34,5.76,16.58,8.79,24.83,2.12,4.92,.69,3.72-2.98,2.03-3.78-1.87-7.54-3.75-11.32-5.62-.53-.16-1.21-.68-1.76-.44-.09,.07-.2,.19-.18,.27,.29,.94,.56,1.88,.92,2.8,3.2M 2,8.1,6.46,16.19,9.68,24.28,1.22,3.02,.17,2.37-2.08,1.36-3.82-2.02-7.63-4.04-11.42-6.09-3.74-2.02-4.3-2.25-4.35-1.89-.19,1.33,.67,2.46,1.16,3.67,2.84,7.07,6.06,14.03,9.39,20.96,.14,.29,.32,.59,.08,.9-.34,.42-1-.02-1.39-.1-6.1-3.07-12.42-5.87-18.09-9.65-.01,.25-.07,.28-.18,.09l.28-.03c-1.16,1.03,.25,2.48,.6,3.62,2.8,5.71,5.62,11.42,8.44,17.12,2.05,3.75-.24,2.24-2.42,1.11-5.53-2.88-10.9-5.96-16.2-9.1-.54-.19-2.75-1.83-2.89-.91,2.58,6.49,6.28,12.57,9.26,18.9,.4,.79,.72,1.61,1.06,2.42,.03,.08-.07,.2-.15,.28-.06,.06-.22M ,.13-.27,.11-.81-.38-1.64-.73-2.41-1.16-7.55-4.02-14.6-9.16-21.99-13.05-.68,.56,.06,1.38,.26,2.03,2.91,5.79,5.84,11.58,8.76,17.37,.3,.6,.59,1.2,.87,1.81,.03,.07-.05,.23-.11,.25-1.13,.3-2.05-.81-3.02-1.25-8.28-5.11-16.33-10.55-24.41-15.94-.31-.23-.99-.69-1.28-.18,.1,.52,.15,1.06,.38,1.54,2.92,6.15,5.92,12.27,9.05,18.32,.2,.4,.41,.8-.03,1.3-11.14-6.7-21.54-14.54-32.13-22.04-1.57-.39-.35,1.42-.12,2.13,2.74,6.19,5.75,12.27,8.33,18.52,.05,.39-.6,.37-.79,.3-4.74-3.1-9.22-6.63-13.8-9.95-7.18-5.37-14.43-10.69-21.36-16.27-.M 69-.45-1.31-1.27-2.22-1.13-.06,0-.18,.2-.15,.28,.28,.83,.55,1.66,.89,2.48,2.19,5.32,4.4,10.63,6.59,15.94,.16,.75,1.07,1.71,.4,2.35-9.6-6.29-18.46-14.22-27.44-21.37-5.13-4.27-10.21-8.59-15.31-12.89-.37-.31-.72-.66-1.3-.7-.08,0-.26,.08-.26,.13,1.62,6.52,4.39,12.84,6.41,19.29,.06,.47,.57,1.14,.25,1.55-.22,.04-.55,.11-.67,.02-.9-.65-1.79-1.31-2.63-2-9.96-8.19-19.65-16.58-29.14-25.11-6-5.39-11.91-10.85-17.87-16.27-.42-.39-.78-.88-1.72-.76,.93,6.06,2.89,12,3.68,18.07-.75,.11-1.14-.16-1.5-.49-13.66-12.25-27.17-24.79-40.26M -37.53-5.81-5.66-11.51-11.39-17.25-17.11-.7-.61-1.19-.54-1.27,.2,.64,5.79,1.38,11.58,2.07,17.36,.04,.31-.04,.64-.1,.95-.07,.15-.5,.24-.64,.15-17.87-16.53-34.81-34.26-51.59-51.8-5.37-5.66-10.64-11.39-16.01-17.06-.95-1-1.39-2.02-1.38-3.27,.04-6.14,0-12.28,0-18.42,.27-1.41,1.56-.24,2.01,.4,18.57,20.64,37,41.16,56.55,60.99,2.49,2.54,4.99,5.08,7.52,7.6,.2,.2,.67,.22,1.08,.35-.08-6.31-1.34-12.47-1.83-18.75,0-.14,.29-.3,.48-.41,16.11,15.82,31.85,32.87,48.62,48.61,2.58,2.49,5.24,4.92,7.86,7.38,1.32,.93,.95-1.3,.75-1.97-1.3M -6.26-3.66-12.72-4.3-18.93,.71-.05,1.3,.74,1.84,1.11,4.15,3.97,8.25,7.96,12.41,11.92,10.83,10.32,22,20.39,33.32,30.36,.55,.42,1.07,1.07,1.86,.94-1.35-6.29-4.03-12.73-5.87-19.06-.26-.82-.66-1.66-.17-2.52l-.06,.1c.73,.1,1.11,.57,1.56,.96,12.63,11.29,25.31,22.36,38.6,33.06,.61,.47,1.25,1.3,2.18,1.18,.32-.68-.17-1.27-.39-1.86-1.19-3.2-2.47-6.37-3.68-9.56-1.17-3.09-2.29-6.19-3.41-9.29-.07-.18,.06-.41,.1-.62,.93,.02,1.54,.54,2.18,1.13,2.81,2.32,5.61,4.65,8.45,6.95,8.55,6.62,16.69,14.05,25.84,19.92,.37-.45,.17-.84,0-1.24-M 2.15-4.99-4.3-9.97-6.41-14.96-.73-1.73-1.35-3.49-1.98-5.24-.04-.12,.19-.33,.34-.47,9.91,6.89,19.42,14.94,29.66,21.81,.49,.32,1.29,1.18,1.94,.69-1.67-5.12-4.42-9.89-6.48-14.87-.95-2.12-1.83-4.27-2.71-6.41-.07-.17,.12-.4,.18-.6,.52,.05,.96,.23,1.36,.56,6.99,4.9,13.96,9.81,20.96,14.7,1.68,1.04,3.36,2.75,5.36,3.13,.08-.07,.18-.21,.15-.28-.32-.82-.63-1.64-1-2.44-2.72-5.96-5.46-11.92-8.18-17.89-.19-.65-.91-1.47-.29-2.05,7.41,4.18,14.64,9.52,22.02,14.04,.61,.32,1.24,.97,1.99,.64,.33-.33-.2-1.09-.31-1.51-3.11-7.22-6.75-14.M 25-9.45-21.63,0-.2,.5-.61,.78-.41,6.41,4.4,12.81,8.6,19.7,12.36,1.94,.97,1.7,.06,1.08-1.47-3.21-7.76-6.43-15.52-9.64-23.29-.2-.81-1.11-1.99-.69-2.75,.35-.21,.75-.03,1.04,.15,5.84,3.86,11.85,7.46,17.8,11.16,.33,.15,1.15,.55,1.35,.17-.02-.31-.03-.62-.14-.91-1.51-3.91-3.07-7.8-4.56-11.71-2-5.25-3.95-10.51-5.91-15.77-.08-.45-.49-1.22-.13-1.55,.21-.08,.53-.19,.67-.12,5.08,2.79,10,5.85,15.04,8.72,.75,.32,1.6,.97,2.43,.94,.43-.39-.12-1.33-.2-1.84-3.42-9.83-7.38-19.55-9.94-29.57,.11-.87,1.5,.12,1.95,.23,4.83,2.55,9.47,5.43M ,14.48,7.62,.27,.12,.61-.06,.59-.29-2.72-10.97-6.71-21.67-9.38-32.67-.07-1.64,2.6,.29,3.26,.55,3.66,1.81,7.33,3.62,11.01,5.41,.52,.07,1.85,1.04,2.02,.2-1.21-6.98-3.5-13.92-5.02-20.89-.98-4.01-1.86-8.04-2.71-12.07-.2-.93-.57-1.9-.07-2.86l-.08,.08Z"/><path class="cls-2" d="M187.62,673.04c-.45,.45-.59,.97-.47,1.51,.42,1.91,.85,3.81,1.3,5.72,.84,3.6,1.69,7.19,2.52,10.79,.02,.09-.08,.27-.15,.28-1,.25-1.74-.81-2.51-1.28-13.39-10.92-26.78-21.85-39.64-33.18-6.43-5.66-12.82-11.35-19.23-17.03-.86-.56-1.54-1.82-2.67-1.64-.07,M 0-.18,.16-.18,.24,.14,5.82,1.35,11.57,2.03,17.35,.1,.77-.07,1.17-.45,1.06-26.11-21.17-50.35-45.1-74.35-68.36-.31-6.61-.11-13.18-.2-19.78,0-.41,.17-.83,.3-1.23,.02-.05,.29-.12,.37-.08,22.96,22.16,44.92,45.4,68.86,66.73,3.38,3.31,2.75,.61,2.5-2.27-.66-4.81-1.37-9.61-1.61-14.46-.02-.27,.18-.41,.51-.39,13.53,11.45,26,24.58,39.68,36.08,6.54,5.73,13.15,11.41,19.73,17.1,.7,.46,1.82,1.83,2.18,.65-1.12-4.98-2.27-9.95-3.39-14.93-.17-.73-.23-1.48-.32-2.23-.01-.09,.1-.28,.15-.28,1.36,.06,2.2,1.48,3.27,2.19,8.9,7.8,17.91,15.52,M 27.14,23.06,7.06,5.77,14.27,11.44,21.42,17.14,.49,.29,1.04,.84,1.64,.76,.1-.05,.23-.19,.21-.26-.83-2.71-1.66-5.43-2.51-8.14-.82-2.61-1.66-5.22-2.45-7.83-.08-.25,.1-.55,.16-.83,.35,.14,.78,.22,1.04,.43,4.69,3.71,9.35,7.45,14.05,11.16,10.11,7.65,20.03,15.99,30.84,22.75,.35-.4,.22-.79,.04-1.2-2.18-4.98-4.35-9.96-6.51-14.94-.57-1.32-1.09-2.66-1.59-4-.04-.11,.18-.32,.33-.44,.05-.04,.28,0,.37,.06,12.51,8.98,24.98,18.22,38.03,26.57,.25,.16,.66,.49,.93,.17,.18-.2,.1-.63-.03-.9-2.65-5.41-5.33-10.82-8-16.22-.44-1.1-1.42-2.11M -1.12-3.34,1.08,.15,1.68,.76,2.38,1.25,10.3,6.92,20.66,14.09,31.56,20.15,.09-.31,.26-.54,.19-.7-.54-1.1-1.12-2.19-1.69-3.28-2.7-5.16-5.41-10.32-8.11-15.49-.21-.39-.36-.8,.1-1.18,8.58,4.84,16.69,10.55,25.53,15.25,.99,.56,2.01,1.07,3.03,1.59,.29,.15,.53,.07,.65-.16,.05-.09,.13-.21,.09-.28-.34-.7-.67-1.4-1.05-2.09-2.91-5.33-5.83-10.65-8.75-15.97-1.93-3.34,.65-1.69,2.3-.7,6.67,4.02,13.71,7.62,20.65,11.34,.55,.3,1.96,1.01,2.09,.54,.32-.75-.54-1.4-.78-2.07-2.88-5.1-5.77-10.2-8.64-15.3-.28-.72-2.53-3.86-.5-3.18,6.57,3.39,M 13.15,6.74,19.74,10.1,.65,.22,1.42,.81,2.11,.66,.09-.06,.22-.2,.19-.26-.27-.6-.55-1.21-.87-1.8-2.83-5.12-5.67-10.23-8.5-15.36-.47-1.38-2.47-3.15-1.15-4.49l-.12-.05c5.79,3.78,12.55,6.23,18.9,9.22,1.62,.27,.51-1.42,.15-2.12-2.96-5.66-5.93-11.31-8.87-16.98-1.31-2.84-2.13-3.88,1.53-2.23,4.89,2.03,9.67,4.31,14.63,6.18,2.11,.43-.1-2.48-.34-3.3-3.14-6.18-6.16-12.4-8.92-18.69-1.12-2.99,.71-1.62,2.37-1.03,3.81,1.59,7.5,3.46,11.38,4.89,.82,.25,1.69,1.01,2.52,.35,.64-.51-.11-1.2-.35-1.78-3.43-8.72-7.41-17.27-10.56-26.08,.05-.M 35,.38-.62,.8-.44,4.77,1.7,9.33,3.93,14.17,5.45,.45,.13,.98-.22,.82-.71-1.63-4.44-3.32-8.86-4.94-13.3-1.75-5.4-4.26-10.63-5.4-16.17-.03-.24,.28-.4,.57-.33,3.87,1.14,7.59,2.73,11.41,4.04,.76,.1,2.35,1.11,2.72,.05-2.62-9.68-6.11-19.17-8.57-28.87-.23-.84-.36-1.69-.52-2.54-.05-.24,.59-.57,.9-.47,4.21,1.44,8.46,2.78,12.69,4.15,.32,.1,.89-.22,.85-.47-2.04-8.66-4.24-17.3-6.14-26-.53-2.33-1.05-4.66-1.55-6.99-.11-.51-.21-1.04,.24-1.5,4.03,.86,7.78,2.38,11.77,3.41,.68,.2,2.18,.43,2.21-.57-1.4-8.86-2.95-17.7-4.34-26.56-.47-2.M 99-.76-6-1.11-9-.1-.86-.2-1.72,.13-2.56l-.16,.13c4.95-.24,9.87-1.51,14.66-2.6l-.14-.08c1.22,3.8,1.11,7.86,1.69,11.78,1.07,8.84,2.15,17.74,4.04,26.45l.07-.08c-4.44,1.22-8.83,2.56-13.4,3.45-.69,.13-1.05,.64-.92,1.24,2.27,11.22,4.63,22.48,7.76,33.53l.14-.13c-1.07,.32-2.14,.17-3.17-.09-2.95-.74-5.89-1.52-8.84-2.26-.61-.09-1.78-.42-2.11,.26,2.18,10.41,5.97,20.48,8.95,30.71-.41,.47-.9,.54-1.45,.4-3.32-.88-6.63-1.76-9.95-2.65-.74-.1-2.48-1.05-2.72,0,2.94,9.2,6.66,18.14,9.91,27.24,.28,.79,.85,2.13-.64,1.91-3.69-.98-7.31-2.M 16-10.96-3.26-.71-.21-2.55-.99-2.52,.23,3.09,8.27,6.55,16.37,10.28,24.44,.36,.78,1.31,2.37-.31,2.19-4.23-.96-8.28-2.54-12.44-3.76-2.8-.87-2.05,.29-1.21,2.18,3.12,6.69,7.18,13.3,9.83,20.04-.81,.5-1.77-.07-2.59-.25-4.56-1.55-9.12-3.13-13.67-4.7-.18,.26-.44,.47-.39,.61,.25,.72,.52,1.44,.9,2.12,3.33,6.23,7.07,12.27,10.18,18.6-.29,.78-1.4,.17-1.97,.04-4.86-1.84-9.72-3.69-14.56-5.56-.74-.29-1.45-.57-2.28-.33,.02,0,.33-.04,.33-.04h-.3c3.42,5.86,6.85,11.71,10.27,17.56,2.32,3.62,2.06,3.95-1.92,2.26-5.11-2.18-10.21-4.37-15.3M 2-6.55-1.33-.42-2.29-.92-1.4,1,1.95,3.31,3.91,6.62,5.9,9.91,1.64,2.71,3.33,5.41,4.97,8.12,.22,.49-.38,.81-.81,.65-7.65-2.82-14.61-6.95-22.03-10.07-.58,.81,.33,1.62,.63,2.39,2.91,5.09,5.98,10.12,9.19,15.1,.43,.66,.78,1.36,1.11,2.06,.05,.12-.2,.32-.37,.58-7.5-3.3-14.77-7.1-21.93-10.92-1.36-.61-2.57-1.72-4.12-1.81-.24-.02-.28,.5-.05,.89,3.49,5.83,7,11.64,10.49,17.47,.23,.41,.73,1.21-.03,1.28-10.42-4.42-19.87-10.93-29.84-15.88-.62,.78,.51,1.87,.8,2.67,2.74,4.8,5.5,9.59,8.25,14.39,.3,.81,1.49,1.84,.92,2.64-.02,.03-.25,.M 04-.33,0-10.02-5.26-19.69-11.33-29.27-17.23-1.58-1-3.18-1.99-4.79-2.96-.15-.09-.57-.08-.66,0-.14,.14-.19,.42-.12,.59,.36,.81,.76,1.61,1.18,2.4,2.66,5.06,5.32,10.12,7.99,15.18,.26,.5,.6,.97,.18,1.55-14.24-7.67-27.14-17.67-40.79-26.34,0-.03,.03-.06,.04-.1-.47,.62-.24,1.25,.02,1.86,1.76,4.76,4.42,9.6,5.74,14.33-.23,.06-.57,.16-.69,.08-1.89-1.21-3.77-2.42-5.62-3.67-13.05-8.82-25.67-18.03-38.05-27.45-1.1-.7-4.44-3.88-3.27-.43,1.37,4.16,2.78,8.3,4.14,12.46,.27,.82,.39,1.67,.57,2.51-.01,.2-.45,.32-.61,.23-18.72-13.63-36.9M 5-27.69-54.36-42.71,.06,.25,0,.29-.16,.11l.29-.05Z"/><path class="cls-2" d="M924.94,209.92c-.66-.26-1.33-.14-1.96,.01-2.05,.51-4.11,1.04-6.14,1.6-9.42,2.42-18.74,5.64-28.21,7.65-.51-.12,.43-1.1,.61-1.31,8.89-8.54,17.9-16.98,26.9-25.41,.4-.54,1.58-1.08,1.1-1.81-.55-.27-1.33,.14-1.92,.21-8.96,2.34-17.91,4.69-26.87,7.03-1.66,.43-3.33,.86-5.01,1.26-.18,.04-.44-.11-.64-.21,9.93-10.37,21.57-19.8,32.08-29.83,.71-.65,1.37-1.32,2.04-1.99,.28-.36-.36-.54-.6-.56-9.99,2.04-19.98,4.44-29.85,6.9-.64,.07-1.76,.46-2.3,.1,11.4-11.8M 4,24.9-22.62,37.33-33.86,1.02-1.07,2.6-1.8,3.05-3.24-9.74,1.06-19.46,3.63-29.18,5.24-.59,.09-1.27,.34-1.75-.15-.07-.05-.06-.24,0-.31,15.26-14.51,32.61-27.58,47.65-42.05-.05-.13-.39-.29-.58-.27-3.87,.43-7.73,.88-11.6,1.33-5.33,.48-10.64,1.57-15.99,1.58-.02-.24-.15-.52-.03-.64,.75-.76,1.52-1.51,2.34-2.22,17.08-14.73,34.38-29.2,51.75-43.62,3.35-2.79,2.47-2.38,6.96-2.4,6.6-.04,13.21-.07,19.81-.09,.95,.13,2.26-.32,2.91,.52,.05,.07,0,.23-.07,.3-.61,.57-1.22,1.14-1.87,1.68-16.54,13.57-33.11,27.11-49.47,40.88-.67,.61-1.63,M 1.09-1.6,2.09,7.88-.2,15.99-1.69,23.93-2.33,1.54-.03,3.25-.58,4.72-.28,.06,.08,.08,.25,.01,.31-.57,.59-1.11,1.2-1.75,1.74-8.44,7.12-16.91,14.2-25.32,21.33-5.73,4.86-11.4,9.77-17.09,14.66-.45,.48-1.26,.84-1.06,1.58,.52,.26,1.35,.07,1.95,.02,9.2-1.62,18.4-3.25,27.6-4.88,.51-.09,1.03-.17,1.52,.1-.03,.73-.75,1.12-1.28,1.58-5.21,4.51-10.47,8.99-15.65,13.52-6.82,5.96-13.59,11.96-20.38,17.95-.35,.44-1.38,1.02-1.24,1.57,.05,.08,.2,.18,.29,.17,1.05-.15,2.11-.28,3.13-.5,7.93-1.71,15.85-3.45,23.77-5.16,1.69-.36,3.4-.65,5.11-.M 94,.2-.03,.59,.08,.65,.2,.08,.16-.02,.44-.17,.59-.86,.83-1.76,1.63-2.66,2.43-8.44,7.55-16.89,15.1-25.32,22.65-1.52,1.36-2.98,2.78-4.45,4.18-.29,1.16,2.69-.04,3.3-.08,10.2-2.41,20.4-4.82,30.6-7.23,.41-.16,1.67-.11,1.38,.5-8.15,7.95-16.76,15.45-25.07,23.24-.84,.9-2.61,1.9-2.66,3.07,11.2-1.79,22.39-5.46,33.58-7.9,1.23-.14,2.59-.99,3.78-.49,.05,.02,.03,.23-.04,.3-.63,.69-1.25,1.39-1.94,2.05-6.47,6.21-12.95,12.41-19.42,18.61-.91,.96-2.05,1.66-2.51,2.94,1.41,.24,2.63-.29,3.96-.61,10.98-2.95,22.15-5.39,33.25-8.02,.84-.11,M 1.84-.58,2.62-.07,.07,.04,.07,.23,0,.3-.39,.44-.79,.87-1.21,1.29-5.92,5.87-11.84,11.74-17.75,17.62-3.15,3.09-1.31,2.42,1.7,1.76,12.9-2.97,25.87-6.17,38.95-8.36,.22-.02,.48,.26,.37,.46-5.3,5.88-10.93,11.47-16.35,17.23-.49,.51-.91,1.06-1.34,1.6-.06,.08-.06,.27,0,.31,.19,.11,.46,.26,.64,.23,3.14-.6,6.27-1.24,9.41-1.84,7.85-1.52,15.7-3.05,23.56-4.52,3.8-.71,7.64-1.3,11.46-1.93,.24-.04,.63,0,.74,.12,.25,.28,.07,.59-.17,.86-4.97,5.64-10.15,11.11-14.99,16.85-.22,.31,.36,.62,.55,.63,11.79-1.64,23.47-3.88,35.31-5.34,4.52-.5M 4,8.99-1.51,13.53-1.78,.12,0,.34,.04,.36,.1,.07,.19,.17,.43,.07,.58-4.07,5.5-8.77,10.54-12.8,16.07-.11,1.21,2.21,.48,2.97,.56,17.07-2.01,34.17-3.83,51.32-5.02,.34-.03,.7,.42,.56,.68-.16,.3-.29,.61-.48,.89-3.7,5.25-7.36,10.52-11.04,15.78l-.04,.03c-18.78,1-37.44,3.36-56.14,5.23-.35,.02-.79-.44-.64-.67,.45-.66,.87-1.33,1.36-1.97,2.97-3.85,5.96-7.68,8.94-11.53,.34-.67,2.33-2.38,.92-2.65-11.3,1.15-22.55,3-33.76,4.83-5.4,.88-10.81,1.77-16.22,2.64-.18,.03-.44-.14-.63-.26-.07-.04-.06-.23,0-.31,.47-.65,.92-1.31,1.44-1.93,4.M 02-5.04,8.95-9.74,12.49-15-.19-.11-.45-.26-.64-.23-2.11,.35-4.21,.7-6.3,1.1-7.85,1.5-15.71,2.98-23.54,4.55-4.7,.94-9.35,2.02-14.02,3.03-.77,.17-1.55,.4-2.35,.05-.08-.72,.54-1.19,1.01-1.7,4.28-4.7,8.57-9.39,12.86-14.09,.7-.97,2.14-1.69,1.94-3.02,0,.01,.02,.25,.02,.25l-.02-.18c-13.95,2.71-27.73,6.19-41.51,9.52-.59,.07-1.37,.37-1.92,.09-.06-.07-.07-.22-.01-.29,.49-.63,.94-1.29,1.5-1.88,5.52-5.97,11.56-11.53,16.8-17.74,.06-.78-1.53-.16-1.98-.15-9.43,2.2-18.74,4.7-28.07,7.16-3.44,.91-6.9,1.79-10.35,2.67-1.24-.02,.9-1.81M ,1.16-2.23,5.82-5.79,11.65-11.57,17.48-17.36,.84-.84,1.66-1.69,2.47-2.55,.06-.07,.05-.27-.01-.3-.19-.11-.45-.26-.63-.23-1.56,.34-3.11,.69-4.64,1.1-7.53,2.01-15.06,4.02-22.58,6.06-3.06,.83-6.08,1.74-9.12,2.61-.5,.14-1.02,.2-1.5-.16,.41-1.04,1.41-1.8,2.25-2.62,5.36-5.26,10.76-10.49,16.16-15.73,1.89-1.83,3.81-3.63,5.72-5.44,.35-.33,.68-.67,.61-1.14,.16-.05,.38-.07,.25-.27-.26,0-.31,.12-.16,.32Z"/><path class="cls-2" d="M1007.3,858.26c4.1,1.05,8.2,2.1,12.31,3.13,.5,.12,1.5,.22,1.72-.32-2.14-10.42-5.98-20.5-8.95-30.74,.M 44-.47,.94-.53,1.49-.39,3.96,1.04,7.9,2.15,11.86,3.15,.38,.09,.88-.24,.79-.52-.32-1.04-.61-2.09-.99-3.12-2.98-8.05-5.98-16.09-8.96-24.14-.19-.6-.73-1.91,.36-1.87,4.54,.86,8.77,2.88,13.3,3.7,.16,.01,.51-.26,.5-.4-2.75-8.23-6.51-16.18-10.02-24.19-1.59-3.17-1.07-3.04,2.06-2.23,4.04,1.14,7.95,2.79,12.06,3.64,.16,.02,.54-.26,.52-.34-1.99-5.3-5-10.21-7.41-15.34-.95-2.31-2.76-4.42-3.21-6.86,0-.23,.79-.26,1.51-.04,4.89,1.47,9.59,3.47,14.48,4.91,.33,.09,.63-.39,.59-.62-2.92-6.3-6.7-12.21-9.96-18.35-.23-.72-1.76-2.2-.9-2.6,1M .05-.1,2.01,.37,2.97,.71,4,1.54,8,3.09,12,4.63,1.19,.39,2.47,1.3,3.72,.67-.12,.06-.23,.11-.33,.16l.33-.13c-4.09-6.01-7.45-12.52-11.26-18.72-.34-.57-.83-1.11-.59-1.8l-.09,.06c.53-.2,1.05-.12,1.54,.09,3.71,1.53,7.43,3.04,11.12,4.6,2.26,.96,4.47,2,6.71,2.99,.77,.41,1.67,0,1-.86-3.71-6.22-7.43-12.43-11.15-18.64-.14-.24-.03-.43,.29-.52,6.31,1.95,12.32,5.34,18.25,8.17,2.2,.97,6.68,4.13,3.58-.76-3.29-5.43-6.57-10.86-9.9-16.26-.26-.43-.23-.86,.05-.86,1.2-.06,2.15,.68,3.2,1.12,7.9,3.41,15.19,8,22.89,11.47,.67-.66-.36-1.62-.M 63-2.32-3.24-5.78-7.21-11.23-10.03-17.2,.29-.38,1.06,.03,1.41,.14,2.51,1.26,5.03,2.51,7.49,3.83,6.83,3.66,13.55,7.41,20.15,11.36,3.04,1.6,.56-1.97,.04-2.95-2.69-4.7-5.39-9.4-8.07-14.1-2.46-3.92,1.37-1.38,3.03-.46,10.09,5.94,20.24,11.82,29.98,18.13,.51,.33,1.03,.75,1.69,.52,.07-.01,.16-.19,.12-.25-.57-1.21-1.13-2.42-1.75-3.61-2.68-5.17-5.37-10.34-8.05-15.51-.04-.07,0-.25,.06-.27,.22-.07,.54-.19,.69-.12,12.77,7.52,25.08,15.93,37.23,24.34,1.01,.69,1.87,1.56,3.22,1.88,.37-.41,.21-.8,.04-1.21-1.83-4.39-3.65-8.78-5.47-13M .18-.18-.59-.74-1.23-.14-1.74,15.24,9.27,29.59,20.45,43.8,31.03,1.07,.82,2.2,1.58,3.32,2.35,.09,.06,.34,.1,.38,.06,.14-.13,.34-.33,.3-.46-5.63-19.72-10.68-21.18,8.32-7.06,13.1,9.94,25.91,20.11,38.42,30.53,.62,.36,3.56,3.37,3.7,1.83-1.08-5.65-2.52-11.23-3.79-16.83-.04-.16,.11-.48,.25-.51,14.37,10.18,27.8,22.63,41.28,33.99,6.96,6.15,13.89,12.33,20.84,18.49,.45,.4,.95,.76,1.45,1.11,.13,.06,.58-.08,.62-.26-.11-6.09-1.53-12.18-1.86-18.3,.34-.67,1.16,.02,1.53,.31,25.1,21.79,49.42,44.45,73.02,67.82,.19,6.6,.03,13.16,.07,1M 9.76,0,.4-.17,.81-.3,1.2-.26,.32-.78-.04-1-.22-21.88-22.52-44.47-44.62-67.63-65.99-1.38-1.07-3.28-3.54-2.99-.11,.7,5.57,1.46,11.13,1.88,16.72,.03,.43-.68,.35-.87,.27-17.28-16.47-35.08-32.57-53.18-48.24-2.36-2.07-4.79-4.08-7.21-6.11-.16-.13-.48-.15-.73-.19-.46-.1-.41,.67-.31,1.07,1.18,5.08,2.37,10.16,3.54,15.24,.06,.47,.25,1.18-.04,1.55-.26-.02-.6,0-.75-.13-17.34-14.51-34.19-30.2-52.66-43.21-.17,.12-.42,.31-.39,.43,.34,1.26,.7,2.52,1.1,3.77,1.13,3.55,2.29,7.09,3.4,10.64,.19,.61,.21,1.26,.29,1.9,0,.21-.45,.32-.6,.25-M 14.29-11.39-28.67-22.79-43.78-33.53-.48-.35-.87-.84-1.62-.87-.1,0-.3,.11-.29,.15,2.14,6.78,5.75,13.14,8.14,19.87,.06,.41-.56,.37-.8,.33-12.76-8.91-25.25-18.97-38.74-26.8-.3,.07-.43,.24-.33,.46,.42,.91,.83,1.82,1.27,2.72,2.47,5.01,4.95,10.01,7.41,15.02,.3,.6,.55,1.21,.82,1.82,.11,.23,.03,.41-.27,.5-.12,.04-.31,.05-.39,0-1.97-1.3-3.94-2.61-5.89-3.93-9.05-5.87-17.94-12.38-27.57-17.39-.65-.41-.32,.42,.07-.09-.56,1.09,.41,2.02,.82,3,2.83,5.89,6.58,11.47,8.88,17.56-.32,.35-.97-.13-1.32-.27-4.99-3.1-9.92-6.26-14.96-9.32-3M .75-2.28-7.61-4.43-11.43-6.63-.52-.3-1-.71-1.75-.63-.58,.69,.18,1.2,.4,1.76,.24,.61,.66,1.18,.98,1.77,2.7,4.92,5.4,9.84,8.09,14.76,.36,.87,1.23,1.69,.56,2.45-7.78-4.45-15.59-8.81-23.61-12.97-.57-.17-1.58-1.1-2.05-.48,2.26,5.51,6.91,12.31,9.8,17.94,.3,.82,1.35,1.86,.8,2.68-.81,0-1.63-.7-2.4-.99-6.64-3.21-13.01-7.05-19.81-9.89-1.02,.1,.09,1.35,.25,1.88,2.88,5.21,5.77,10.41,8.65,15.63,.5,1.42,2.36,3.06,1.16,4.51v-.03c-5.7-3.83-12.48-6.22-18.79-9.23-.2-.09-.48-.05-.73-.06-.23,0-.32,.54-.14,.89,2.4,4.55,4.84,9.08,7.2,13M .64,1.23,2.38,2.35,4.79,3.5,7.19,.08,.35-.57,.47-.77,.45-5.33-2.23-10.54-4.76-15.96-6.82-.61-.25-1.27-.33-1.88,0,.22,.02,.37,.04,.46-.18l-.37,.18c3.57,7.3,7.29,14.54,10.54,21.99,.18,.4,.24,.83,.32,1.26,.02,.08-.09,.23-.18,.27-.98,.41-1.89-.5-2.81-.78-4.26-1.86-8.43-3.92-12.87-5.36-.4-.12-1.04,.2-.91,.68,3.51,9.24,8.05,18.22,11.04,27.61-.16,.88-2.16-.37-2.75-.45-3.74-1.48-7.46-2.99-11.2-4.45-.46-.18-1.03-.2-1.55-.26-.07,0-.25,.16-.24,.23,3.42,10.36,7.5,20.6,10.92,30.99l.08-.12c-4.44-1.82-8.96-3.44-13.51-5.01-.58-.15M -1.8-.58-1.98,.25,2.68,9.84,6.22,19.56,8.77,29.44,.2,.71,.54,1.45,.09,2.19-1.16,.48-1.97-.31-2.93-.54-.77-.18-1.47-.53-2.21-.77-2.61-.85-5.23-1.69-7.84-2.54-.71-.23-1.41-.02-1.24,.69,2.91,10.81,5.29,21.71,7.7,32.6,.12,.52,.22,1.06-.16,1.56-.7,.14-1.29-.15-1.88-.35-4.03-1.5-8.32-2.38-12.39-3.82-2.52-11.71-5.06-23.4-8-35.01l-.1,.1Z"/><path class="cls-2" d="M880.11,620.81c-4.07,1.65-8.4,2.9-12.4,4.67-.64,.27-1.29,.35-1.9,0-2.47-1.37-4.92-2.75-7.38-4.13,3.67-2.52,7.25-5.22,10.7-8.12,3.65,2.33,7.52,4.45,11.02,7.02,.12,.M 09,.08,.42-.04,.55Z"/><path class="cls-2" d="M884,607.61c.1,.45-.35,.54-.68,.64-4.14,1.04-8.25,2.24-12.35,3.42,2.74-2.38,5.4-4.88,7.97-7.51,1.6,1.17,3.79,1.95,5.06,3.45Z"/><path class="cls-2" d="M890.63,596.25c-1.77,.29-3.54,.58-5.29,.87,.96-1.13,1.9-2.28,2.82-3.45,.78,.54,1.54,1.1,2.3,1.67,.21,.16,.11,.57,.17,.91Z"/><path class="cls-2" d="M901.05,584.67c-1.99,1.09-4.89,.66-7.14,1.1,1.03-1.54,2.01-3.09,2.94-4.64,1.13,.82,2.27,1.64,3.4,2.46,.4,.29,.8,.58,.8,1.08Z"/><path class="cls-2" d="M1117.4,514.89c.02,.06,.04,.M 11,.06,.17-.05-.01-.11-.03-.16-.04l.1-.13Z"/><path class="cls-2" d="M1190.2,521.41v.1c-.05-.02-.09-.03-.14-.05l.14-.05Z"/><path class="cls-2" d="M1387.31,603.78c0,1.07-.03,2.15-.05,3.29-1.29,.43-2.17-.36-3.25-.87-26.06-13.81-52.7-26.87-79.85-39.26-6.67-3.05-13.39-6.01-20.09-9-.69-.31-1.37-.67-2.22-.51-.39,.9-.1,1.75,.02,2.6,.65,4.71,1.32,9.42,1.97,14.13,.14,.9,.31,2.57-1.14,2.06-13.21-5.81-26.24-11.92-39.64-17.46-15.01-6.33-30.28-12.24-45.64-18-.72-.21-2.02-.95-2.37-.02,.78,4.93,2.52,9.68,3.68,14.54,.1,.7,.54,1.55-M .11,2.1-24.39-8.85-48.61-18.33-73.71-25.47-1.84,.03-.06,2.32,.11,3.25,1.36,3.49,2.73,6.98,4.08,10.48,.18,.55,.59,1.52-.28,1.62-20.47-6.06-40.69-12.72-61.64-17.36-2.02-.11-.05,2.19,.22,3.07,1.73,3.39,3.48,6.77,5.2,10.17,.19,.48-.43,.81-.85,.72-16.56-4.3-33.28-8.09-50.14-11.27-.76-.15-1.57-.34-2.35,.03-.16,.58,.21,1.03,.51,1.5,2.23,3.44,4.46,6.88,6.66,10.34,.07,.26-.12,.68-.5,.69-11.9-2.3-23.88-4.38-35.93-6.11-1.25,0-9.16-1.72-9.1-.31,1.94,3.26,4.69,6.01,6.95,9.06,.25,.44,.89,.95,.71,1.44-.16,.14-.39,.38-.55,.36-3.32M -.4-6.64-.86-9.97-1.25-5.6-.66-11.18-1.4-16.82-1.78-15.87-1.1-12.55-1.86-3.32,8.59,.18,.26,.59,.89,.25,1.13-1.82,.36-3.75-.14-5.6-.16-8.97-.55-18.04-1.37-27.01-.97-.18,.1-.39,.42-.32,.51,2.71,3.01,5.91,5.57,8.82,8.41,.54,1.42-3.47,.6-4.36,.76-7.88,.07-15.98-.39-23.75,.67-.02,.2-.08,.48,.05,.6,.9,.8,1.82,1.58,2.77,2.34,2.09,1.69,4.21,3.35,6.27,5.04,.23,.18,.21,.56,.33,.94-5.21,.31-10.15,.6-15.26,.98,3.57-6.69,6.38-13.41,8.72-20.05,4.12-.21,8.25-.38,12.38-.34,2.12,.02,2.77-.34,.95-1.9-10.44-9.55-10.99-7.65,3.24-8.1,6M .87,.17,13.74,.31,20.61,.47,.55-.05,1.51,.2,1.76-.39-.09-1.12-1.58-2.02-2.24-2.94-1.95-2.19-4.26-4.13-6.01-6.48-.1-.49,.58-.71,1.02-.65,2.83,.08,5.67,.11,8.49,.27,9.94,.33,19.82,1.7,29.73,2.17,.12,0,.36-.36,.3-.47-2.14-3.42-5.05-6.36-7.49-9.57-.3-.37-.51-.74-.23-1.19,15.35,.62,30.61,3.48,45.83,5.51,1.54-.15-1-2.71-1.36-3.57-1.67-2.58-3.34-5.16-4.99-7.75-.28-.41-.51-1.19,.1-1.36,18.12,2.01,37.02,7.12,53.74,9.86,.52-.52-.16-1.22-.35-1.75-1.66-3.3-3.33-6.59-4.99-9.89-.33-.78-1.5-2.3,.24-2.22,21.25,4.28,42.23,9.93,62.9M 9,15.97,.53-.44,.52-.86,.36-1.28-1.84-4.88-3.68-9.78-5.43-14.69,26.05,6.71,51.09,15.75,76.46,24.08,.47-.63,.26-1.27,.09-1.9-1.18-5.23-3.17-10.41-3.81-15.73,30.4,10.42,60.22,21.97,89.71,34.57,.77,.29,1.54,.1,1.37-.87-.59-4.6-1.21-9.21-1.82-13.81-.18-1.37-.52-2.75-.16-4.15,35.66,13.34,70.11,30.06,104.3,46.66,4.32,2.16,3.66,1.4,3.69,5.33,.05,4.84,.02,9.69,.02,14.54Z"/><path class="cls-2" d="M1200.1,558.57c25.84,9.54,51.27,21.49,76.07,33.36,3.11,1.51,6.25,2.96,9.38,4.44,.26,.12,.91-.17,.93-.4-.05-5.67-1.43-11.36-2.03-1M 7.02-.07-.72-.14-1.55,.95-1.31,34.6,16.22,68.74,33.5,101.77,52.6,.37,6.57,.05,13.16,.16,19.75,0,2.51-1.07,1.65-2.75,.73-30.91-18.53-62.66-35.92-94.93-52.14-.55-.28-1.18-.48-1.8-.66-.13-.04-.52,.17-.55,.31-.3,1.29,.04,2.57,.23,3.85,.51,4.81,1.79,9.62,1.87,14.43-.63,.65-1.67-.26-2.35-.49-22.94-12.12-46.4-23.55-70.38-34.3-3.29-1.48-6.6-2.92-9.92-4.35-.55-.17-1.65-.74-2.01-.04,.82,5.47,3.13,10.66,4.04,16.13-.25,1.25-2.2-.16-2.93-.34-22.2-10.11-44.87-19.89-68.18-28.09-.12-.03-.54,.26-.51,.35,.23,.84,.48,1.68,.81,2.49,1.M 6,4.11,3.49,8.12,4.89,12.31,.03,.08-.06,.23-.15,.27-.22,.08-.52,.21-.69,.15-2.56-.95-5.12-1.92-7.66-2.91-16.99-6.49-34.25-12.79-51.93-17.83-.1-.02-.47,.29-.44,.41,1.8,4.54,4.73,8.64,6.72,13.12,.06,.15-.12,.37-.23,.54-.68,.19-1.56-.29-2.25-.43-9.07-3.03-18.24-5.87-27.51-8.48-7.01-1.78-14-4.13-21.11-5.42-.18,.02-.48,.29-.46,.4,1.95,4.27,5.31,7.89,7.44,12.08-.56,.4-1.07,.36-1.6,.23-4.22-1.1-8.45-2.19-12.67-3.3-8.83-2.32-17.83-4.16-26.83-6-.94-.06-2.17-.62-2.97,.04,1.96,3.42,5.17,6.55,7.51,9.88,.32,.42,1.02,.91,.47,1.3M 9-.48,.41-1.28,.15-1.93,.02-1.31-.25-2.6-.56-3.9-.83-10.38-1.93-21.01-4.35-31.52-5.19-.17,.7,.28,1.21,.77,1.67,2.16,2.34,4.33,4.67,6.49,7.02,.42,.67,1.68,1.32,1.25,2.17-5.69-.29-11.67-1.6-17.46-2.15-4.71-.45-9.66-1.51-14.32-1.1-.04,.2-.13,.46,0,.59,2.68,2.86,5.63,5.5,8.41,8.27,.34,.33,.64,.69,.35,1.21-8.82-.53-17.66-1.48-26.52-1.69-.21-.01-.53,.11-.64,.25-.11,.15-.11,.44,0,.58,2.24,2.34,4.91,4.29,7.31,6.47,.73,.63,1.41,1.3,2.06,1.98,.11,.12,.01,.39-.04,.58-7.49,.49-15.32-.66-22.89,.03-.28,.02-.51,.64-.31,.81,.84,.7M ,1.68,1.4,2.52,2.09,2.36,1.92,4.72,3.84,7.06,5.78,.16,.13,.25,.42,.18,.58-.07,.17-.36,.33-.59,.39-1.85,.29-3.77,.21-5.64,.29-4.56,.15-9.18,.2-13.67,.93-.22,.88,.84,1.24,1.38,1.77,2.84,2.15,5.69,4.28,8.54,6.42,.39,.3,.78,.6,.66,1.17-5.54,.87-11.43,1.21-16.97,2.17-.27,.58-.04,.92,.39,1.23,2.87,2.12,5.74,4.24,8.6,6.37,2.19,1.52,2.85,2.2-.37,2.63-4.02,.87-8.17,1.3-12.09,2.53-1.16,.67,.68,1.42,1.13,1.92,3.22,2.45,6.62,4.71,9.71,7.31,.23,.2,.23,.57,.32,.84-3.97,1.27-7.85,2.35-11.71,3.71-2.04,.93,.9,2.06,1.58,2.83,3.65,2.M 97,7.53,5.77,11.05,8.89-.23,.54-.64,.78-1.15,.95-3.08,1.07-6.22,2-9.22,3.28-2.68,.89,2.03,3.24,2.89,4.31,2.89,2.41,5.77,4.83,8.65,7.25,.38,.32,.63,.68,.48,1.1-3.22,1.4-6.41,2.79-9.61,4.17-.65,.28-1.25,.2-1.83-.25-3.84-3.03-7.69-6.04-11.54-9.05-.47-.37-1.04-.7-1.04-1.39,2.9-1.99,6.45-3.4,9.56-5.26,.6-.61-.45-1.14-.86-1.54-3.56-2.64-7.13-5.26-10.7-7.89-.49-.36-1.08-.65-1.34-1.32,2.55-1.99,6.08-2.99,9.01-4.53,2.34-1.05,2.38-1.09,.27-2.62-3.54-2.71-7.58-4.77-10.83-7.82,4.21-1.96,8.79-2.94,12.98-4.49,.16-.57-.18-.89-.6-M 1.18-3.18-2.17-6.36-4.33-9.54-6.5-.6-.46-1.32-.69-1.39-1.55,4.83-1.62,9.91-2.63,14.96-3.65-.02-.28,.07-.55-.06-.68-2.92-2.45-6.3-4.37-9.41-6.59-.85-.51-2.32-1.54-.59-2.01,3.03-.52,6.06-1.02,9.1-1.48,2.25-.34,4.51-.6,6.77-.92,1.71-.52-.1-1.5-.83-2.08-2.32-1.64-4.65-3.27-6.98-4.91-.79-.67-2.1-.96-1.94-2.2,6.61-1.08,13.14-1.35,19.75-1.81,.32-.03,.61-.59,.4-.77-2.61-2.38-5.57-4.36-8.33-6.57-.48-.37-.92-.77-1.36-1.17-.08-.07-.14-.22-.1-.29,.12-.17,.28-.44,.45-.46,7.64-.71,15.33-.75,23-.82,.43,.02,.61-.42,.39-.72-2.66-2.M 48-5.64-4.62-8.42-6.97-1.01-.91-2.14-1.98,.25-1.92,6.06,.05,12.13-.08,18.18,.42,2.54,.21,5.1,.18,7.66,.26,.48,.05,.59-.39,.48-.7-2.81-2.92-5.79-5.68-8.71-8.49-.31-1.08,1.43-.66,2.07-.76,5.79,.11,11.55,.7,17.31,1.2,4.15,.39,8.28,.87,12.42,1.29,.2,.02,.54-.12,.62-.26,.09-.16,.04-.45-.09-.59-2.53-2.8-5.09-5.59-7.75-8.27-.4-.41-1.09-.88-.65-1.39,.39-.46,1.24-.27,1.89-.2,12,1.2,23.92,2.96,35.8,4.98,1.29-.13-.47-1.79-.77-2.3-2.11-2.63-4.23-5.25-6.33-7.88-.31-.47-1.04-1.3-.24-1.61,13.71,1.99,27.36,4.73,40.8,7.91,1.25,.13,M 2.64,.93,3.83,.39,.06-.03,.04-.22,0-.31-2.18-4.08-5.34-7.67-7.31-11.83-.03-.11,.31-.42,.44-.41,.93,.1,1.86,.21,2.76,.41,10.52,2.29,20.97,4.8,31.28,7.65,5.34,1.48,10.66,3.02,15.99,4.53,.5,.14,1.03,.23,1.55,.27,.13,0,.45-.31,.41-.42-1.66-3.91-3.97-7.53-5.87-11.33-.18-.6-1.3-1.98-.3-2.24,20.87,4.87,41.02,12.58,61.32,19.06,.56-1.36-.61-2.67-.96-3.99-1.34-3.71-3.26-7.3-4.27-11.09,.29-.86,1.76-.07,2.38,.02,9.39,3.26,18.76,6.54,28.04,9.99,13.8,5.14,27.36,10.67,40.83,16.33,.46,.2,.98,.32,1.48,.45,.32,.08,.56-.05,.54-.33-.6M 4-4.93-2.54-9.67-3.67-14.52-.19-.72-.53-1.46-.01-2.19Z"/><path class="cls-2" d="M236.98,168.26c.96-.1,1.86,.03,2.74,.37,3.64,1.38,7.29,2.75,10.95,4.1,3.63,1.16,7.03,2.97,10.81,3.57,1.72-10.71,1.56-21.72,2.69-32.54,.72-8.14,1.57-16.28,2.28-24.43,.05-.53,.11-1.07-.37-1.53l-.05,.02c.89-.36,1.8-.32,2.74-.14,7.88,1.32,15.65,3.34,23.59,4.2l-.09-.08c-2.76,20.32-4.83,40.72-6.47,61.16-.11,2.65-1.77,1.48-3.49,1.05-4.68-1.65-9.35-3.33-14.03-4.98-2.13-.58-4.15-1.81-6.39-1.74-1.48,17.84-1.41,35.8-2.17,53.68-.9,1.26-6.12-2.42-7.M 55-2.88-4.19-2.16-8.37-4.33-12.56-6.49-.99-.39-1.86-1.17-2.99-.76-.16,14.83,.1,29.71,.65,44.54,.02,1.22,.42,3.95-1.73,2.47-6.88-4.49-13.66-9.13-20.58-13.57-.44-.37-.97,.03-1.11,.45,.18,13.76,1.73,27.52,2.44,41.27-1.1,.48-1.82-.56-2.68-1.08-6.27-4.89-12.53-9.79-18.8-14.68-4.06-3.61-2.66,.59-2.64,3.36,.74,7.84,1.49,15.68,2.26,23.52,.27,2.9,.73,5.78,.78,8.69-.44,1.25-2.27-.94-2.87-1.3-6.58-5.85-13.15-11.7-19.73-17.55-.72-.64-1.48-1.24-2.27-1.82-.12-.09-.47,.03-.78,.06,.34,8.68,1.89,17.38,2.78,26.04,.28,2.36,.57,4.72,.M 82,7.08-.06,.19-.53,.58-.82,.36-.65-.54-1.32-1.07-1.9-1.65-7.21-7.11-14.4-14.24-21.62-21.35-.84-.83-1.77-1.6-2.68-2.39-.06-.05-.25-.02-.38,0-.11,.02-.29,.08-.3,.12-.03,.43-.08,.86-.03,1.28,.76,6.43,1.52,12.87,2.3,19.3,.34,2.79,.73,5.57,1.1,8.35,.11,.82,.02,1.09-.36,1.08-.63-.02-.92-.39-1.23-.72-8.69-9.2-17.38-18.4-26.07-27.59-.56-.59-1.22-1.13-1.86-1.68-.12-.07-.59,.04-.63,.19,.08,5.59,1.09,11.16,1.56,16.74,.33,3,.69,6.01,1.04,9.01,.14,1.11-1.01,.85-1.36,.29-4.3-4.83-8.6-9.65-12.89-14.48-5.46-6.15-10.9-12.31-16.36-M 18.45-.94-.88-2.98-3.72-2.81-.62,.39,5.16,.82,10.32,1.21,15.48-.09,1.17,1.08,7.69-.76,6.2-11.76-13.33-23.09-27.05-34.67-40.53-1.25-1.21-.94-2.82-1.05-4.35-.02-5.39-.03-10.77-.04-16.16,.04-.64-.08-1.41,.62-1.75,.05-.04,.29,.03,.36,.1,11.51,12.07,21.88,25.22,33.44,37.23,.12,.08,.57-.03,.61-.2,.01-4.2-.42-8.39-.68-12.58-.2-3.44-.64-6.88-.63-10.33,.18-.6,.73-.85,1.35-.21,10.02,10.51,19.59,21.45,29.79,31.79,.55,.21,.8-.25,.76-.76-.47-5.05-.96-10.09-1.43-15.14-.29-3.11-.57-6.23-.84-9.35-.04-.43-.08-.86-.04-1.29,.07-.42,.M 7-.87,1.07-.43,8.37,8.12,16.5,16.49,24.79,24.7,1.06,.82,1.8,2.34,3.26,2.32-.76-10.3-2.17-20.6-2.96-30.88,1.15-.37,1.79,.65,2.61,1.24,3.89,3.58,7.76,7.17,11.64,10.75,3.62,3.34,7.23,6.68,10.86,10.01,.39,.26,1.1,1.07,1.57,.76,.15-.16,.34-.35,.32-.53-.12-1.72-.27-3.44-.44-5.16-.85-9.56-2.1-19.1-2.38-28.68,.17-.92,1.36-.17,1.78,.19,7.59,5.94,14.82,12.31,22.54,18.08,1.01,.21,.87-.69,.89-1.39-.33-6.89-.99-13.76-1.44-20.65-.31-5.27-.6-10.54-.9-15.82-.02-.43,0-.86,.11-1.28,.24-.3,1.04-.25,1.37,.04,6.82,4.55,13.54,9.22,20.33M ,13.81,1.72,1.14,2.79,1.9,2.63-.93-.42-13.89-1.16-27.78-1.14-41.68,0-.3,0-.71,.49-.76,.36-.04,.81,.02,1.11,.18,3.39,1.76,6.75,3.56,10.12,5.34,3.6,1.9,7.19,3.8,10.79,5.7,.5,.26,.98,.27,1.54-.08,.25-15.69,.18-31.42,.94-47.11-.05-1.27,.36-2.67-.37-3.79h0Z"/><path class="cls-2" d="M1148.11,1317.93c.52-.78,.61-1.64,.71-2.5,.76-6.65,1.58-13.29,2.29-19.95,1.29-12.66,2.62-25.32,3.6-38.01,.2-.88,.04-2.44,1.36-2.31,5.52,1.61,10.85,3.8,16.29,5.65,1.48,.52,2.97,1.02,4.46,1.51,1.61,.52,1.97,.36,2.05-.89,.34-5.06,.63-10.11,.75-1M 5.18,.6-11.19,.77-22.39,1-33.59,.03-1.18,.13-2.36,.2-3.54,.28-.8,1.44-.39,2-.15,6.17,3.06,12.24,6.28,18.36,9.42,.75,.24,2.15,1.41,2.7,.46,.42-13.11,0-26.28-.43-39.4-.11-2.37-.15-4.74-.19-7.11,0-.18,.17-.37,.27-.56,.11-.2,.71-.16,1.11,.08,6.64,4.18,13.08,8.66,19.63,12.97,.68,.28,1.59,1.36,2.3,.7,.4-6.31-.61-12.69-.77-19.02-.34-7.53-1.1-15.05-1.41-22.57,.91-.31,1.59,.5,2.29,.95,7.08,5.44,14.01,11.09,21.17,16.42,.19,.08,.91,.15,.92-.26-.23-3.11-.42-6.23-.71-9.34-.84-8.91-1.81-17.82-2.7-26.73,.01-.38-.14-.96,.26-1.15,.M 12-.04,.32-.08,.39-.03,.61,.42,1.24,.81,1.78,1.29,7.42,6.54,14.72,13.2,22.21,19.67,1.5,.86,.97-1.93,.94-2.7-.33-3.22-.68-6.44-1.04-9.66-.71-6.33-1.48-12.65-2.23-18.98,0-.71-.42-1.66,.42-2.04,.05-.04,.26,0,.32,.06,8.16,7.68,15.95,15.74,23.98,23.56,.82,.62,1.42,1.89,2.57,1.79,.06,0,.18-.15,.18-.23-.05-1.07-.06-2.15-.18-3.21-.79-7.08-1.74-14.15-2.62-21.22,.05-2.09-1.68-7.79,1.79-3.9,9.11,9.46,17.86,19.27,27.18,28.52,.11,.07,.59-.08,.61-.25-.05-1.5-.04-3.01-.19-4.5-.7-7.08-1.54-14.16-2.24-21.24,0-.24,.43-.68,.71-.57,10M .15,10.59,19.51,21.96,29.39,32.83,.7,.79,1.46,1.54,2.23,2.28,.1,.1,.46,.05,.7,.02,.07,0,.17-.16,.18-.25,.01-6.56-.89-13.11-1.23-19.67,.04-.95-.33-2.37,0-3.17,.25,0,.62-.04,.74,.07,11.57,13.02,22.62,26.52,34.02,39.7,.69,.81,1.37,1.6,1.37,2.63-.03,6.57-.06,13.14-.09,19.7-.16,2.41-7.18-6.95-7.99-7.51-7.77-8.8-15.54-17.6-23.32-26.39-.7-.79-1.47-1.54-2.22-2.29-.12-.07-.59,.06-.64,.19-.12,6.86,.78,13.76,1.02,20.63,.28,4.19-.83,2.61-2.9,.5-8.6-9.25-17.19-18.5-25.79-27.75-.64-.69-1.33-1.35-1.99-2.03-.2-.21-.45-.3-.7-.12-.5M 5,.44-.29,1.21-.29,1.82,.77,8.37,1.55,16.74,2.28,25.11-1,.34-1.53-.51-2.19-1.06-8.72-8.62-17.23-17.45-26.05-25.96-.39-.26-1.02-.13-1.03,.41,.89,9.77,2,19.53,2.79,29.31,0,.3-.25,1.04-.68,.96-1.31-.63-2.26-1.85-3.37-2.75-6.35-5.86-12.69-11.74-19.04-17.6-.88-.81-1.84-1.57-2.77-2.34-.24-.23-.82,.15-.86,.31,.21,7.11,1.12,14.18,1.72,21.26,.33,3.98,.71,7.95,.92,11.93,0,2.45-2.15,.15-2.95-.45-6.14-4.99-12.28-9.99-18.43-14.97-.94-.76-1.93-1.49-2.94-2.2-.18-.08-.88-.09-.89,.3,.23,9.59,1.42,19.13,1.75,28.71,.01,3.32,.73,6.69,M .41,9.99-.39,.48-1.28,.1-1.7-.2-6.78-4.61-13.54-9.22-20.33-13.81-.53-.26-1.04-.85-1.67-.74-.32,.03-.47,.17-.49,.43-.16,3.86,.13,7.75,.25,11.62,.42,10.65,.92,21.32,.63,31.97-.27,.74-1.5,.16-2.01-.12-6.51-3.45-13.02-6.9-19.54-10.35-2.6-1.45-2.39-.26-2.45,2.03-.25,16.26,.01,32.54-1.08,48.78l.14-.06c-7.8-2.53-15.31-5.85-23.15-8.31-.49-.17-1.14,.17-1.17,.59-1.36,19.43-2.9,38.84-4.92,58.22l.12-.11c-8.74-.93-17.25-3.52-26-4.44l.08,.07Z"/><path class="cls-2" d="M878.95,893.47c-3.16,7.15-6.8,14.07-10.88,20.7,.07-5.24-.64-10M .44-.86-15.67,.03-.36-.38-.53-.65-.69-.72,.13-1.19,1.18-1.71,1.69-2.31,3.03-4.6,6.08-6.91,9.11-.54,.57-.88,1.54-1.81,1.47-.1,0-.28-.12-.3-.2-.65-2.84-.32-5.8-.62-8.69-.18-2.47-.46-4.94-.72-7.41-.52-1.48-1.64,.33-2.13,1.01-2.94,3.66-5.19,8-8.58,11.24-.05,.04-.36-.02-.37-.07-.13-.51-.29-1.03-.34-1.55-.48-4.31-.57-8.95-1.79-13.09-.94-.07-1.3,.89-1.82,1.48-2.32,3.28-4.63,6.57-6.95,9.85-.67,.67-1.09,2.1-2.18,2.01-.09,0-.23-.14-.25-.23-.19-.74-.41-1.47-.51-2.22-.49-1.37-.67-11.4-2.46-10.18-3.14,4.12-6.04,8.4-9.08,12.59-.M 33,.46-.63,.96-1.34,1.14-.57-.37-.69-.9-.78-1.44-.65-3.36-.9-6.7-2.05-9.96-1.62,.55-2.07,2.16-3.12,3.34-2.66,3.49-5.33,6.99-8.01,10.47-.31,.29-.71,.83-1.21,.71-1.43-2.68-1.48-6.63-3.08-9.56-.87-.45-1.59,.96-2.14,1.45-4.01,5.02-7.77,10.18-12.3,14.78-.96,.45-1.18-.82-1.39-1.49-.65-2.2-1.27-4.4-1.93-6.6-.05-.18-.31-.32-.49-.47-.22-.18-.69-.05-1.01,.29-.83,.84-1.55,1.75-2.35,2.63-3.43,3.87-6.85,7.74-10.3,11.59-.71,.67-1.23,1.64-2.34,1.65-1.25-2.7-1.37-5.66-2.71-8.3-.81,.05-1.15,.36-1.46,.71-4.01,4.47-8.52,8.63-12.89,12M .86-.85,.75-2.93,3.36-3.46,1.24-.6-2.21-1.22-4.42-1.93-6.59-1.02-1.35-2.54,1.19-3.43,1.75-4.9,4.39-9.52,9.26-15.04,13.05-.21,.07-.82-.05-.97-.33-1.55-2.49-3.1-4.99-4.66-7.51,5.34-4.76,11-9.18,15.93-14.2,.77-.63,1.38-1.52,2.47-1.55,2.12,2.13,3.38,4.85,5.26,7.11,1.08-.25,1.48-.84,1.97-1.32,4.55-4.41,9-8.87,13.18-13.5,.39-.43,.73-.9,1.61-.88,1.59,2.23,1.85,4.94,3.22,7.22,.78,.52,1.5-.62,2.02-1.05,4.22-4.86,8.36-9.8,12.61-14.63,1.65-1.37,3.18,6.9,4.32,7.95,.85-.16,1.19-.62,1.57-1.07,3.75-4.35,7.11-8.89,10.53-13.4,.6-.5M 8,1.53-2.69,2.48-1.85,1.32,2.67,2.15,5.54,3.3,8.29,.02,.06,.55,.11,.64,.02,3.98-4.46,6.93-9.75,10.66-14.44,.15-.17,.67-.15,1.13-.24,1.01,3.32,2,6.54,2.98,9.75,1.19,.16,1.56-.93,2.19-1.67,2.4-3.62,4.77-7.24,7.14-10.87,.37-.57,.65-1.18,1.34-1.57,.59,.14,.81,.52,.91,.93,.95,3.47,1.55,7.02,2.85,10.39,.02,.05,.2,.09,.3,.09,.78-.17,1.33-1.41,1.85-2.01,2.17-3.34,4.31-6.7,6.47-10.05,.49-.59,.75-1.63,1.69-1.51,.1,0,.26,.12,.29,.2,1.24,3.7,1.52,7.66,2.37,11.46,.13,.36,.2,1.02,.65,1.1,.23-.01,.58-.02,.68-.13,2.95-3.94,5.43-8.M 18,8.2-12.24,.24-.26,.79-.83,1.19-.58,1.53,4.66,1.2,9.88,2.59,14.63,.12,.31,.81,.22,.95,.1,.65-.82,1.26-1.66,1.84-2.51,2.13-3.11,4.25-6.24,6.37-9.36,.3-.43,.7-.6,1.39-.35,.86,5.4,1.81,10.86,2.06,16.33,.01,.31,.52,.74,.72,.64,.22-.11,.47-.21,.63-.36,2-2.38,3.72-5,5.61-7.48,.96-1.3,1.88-2.61,2.89-3.89,.15-.19,.67-.19,1.12-.31,.58,3.5,.86,6.81,1.14,10.25Z"/><path class="cls-2" d="M945.03,1096.09c.05-.02,.1-.04,.15-.05-.02,.06-.03,.12-.04,.18l-.11-.13Z"/><path class="cls-2" d="M977.4,1211.23s.01-.05,.02-.07h.06l-.08,.0M 7Z"/><path class="cls-2" d="M993.69,1141.18c-4.01,23.58-10.58,46.75-16.27,69.98-7.64,.76-15.24,2.51-22.81,3.69-.7-.53-.5-1.16-.32-1.87,1.47-4.92,3.03-9.81,4.43-14.74,4.94-17.16,9.27-34.46,13.6-51.77,.13-.76,.42-1.78-.73-1.8-5.29,1.17-10.48,2.76-15.72,4.08-1.34,.19-4.93,2.13-4.32-.54,1.42-6.03,3-12.02,4.49-18.03,3.18-13.39,6.39-26.81,8.64-40.37,.03-.27-.54-.56-.88-.45-6.24,2.14-12.41,4.45-18.62,6.68,3.39-17.25,7.2-34.46,9.52-51.89-.36-1.16-1.88-.03-2.61,.17-4.77,2.23-9.44,4.64-14.26,6.74-.29,.13-.84-.2-.82-.49,.71-6M .45,2.34-12.77,3.07-19.22,1.09-8.25,2.18-16.48,3.11-24.75-.37-1.29-2.07,.16-2.77,.47-3.79,2.25-7.56,4.51-11.35,6.75-.5,.19-2.1,1.37-2.28,.48,1.5-9.93,2.49-19.9,3.45-29.9,.28-2.78,.52-5.57,.76-8.36,.08-.42-.53-.51-.84-.44-4.54,2.79-8.67,6.17-13.15,9.05-.14,.1-.49,.02-.74-.02-.36-.22-.27-.82-.25-1.19,.74-8.81,1.53-17.62,2.13-26.44,.09-1.93,.02-3.87-.01-5.81-.67-.62-1.64,.37-2.21,.74-3.57,2.91-6.82,6.2-10.59,8.87-.12,.07-.67-.07-.68-.15-.31-9.33,1-18.71,.71-28.08,.9-1.52,1.78-3.05,2.64-4.6,2.92-2.82,5.81-5.66,8.72-8.4M 9,.37-.36,.8-.55,1.48-.23,.41,8.68,.4,17.41,.17,26.1-.03,1.07,.03,2.15,.1,3.22,.06,.2,.6,.55,.87,.31,3.27-2.35,6.23-5.06,9.37-7.58,.84-.42,2.5-2.66,3.29-1.6,.78,11.28-.67,22.61-.66,33.88,.98,.55,2.14-.69,3.03-1.17,3.36-2.33,6.7-4.69,10.05-7.02,.32-.31,1.02-.46,1.42-.19,.12,.3,.25,.62,.24,.93-.28,6.14-.37,12.29-.92,18.41-.33,4.62-.65,9.24-.99,13.87-.1,2.01-.92,4.07-.51,6.08,.59,.21,1.07,.03,1.51-.22,2.31-1.31,4.6-2.64,6.92-3.93,2.21-1.24,4.44-2.44,6.66-3.65,.27-.15,.92,.1,.95,.34,.15,6.85-1.14,13.76-1.55,20.62-.74,8M .06-2.05,16.06-2.98,24.1-.05,.41,.65,.76,1.13,.56,4.72-2.06,9.41-4.2,14.11-6.3,.72-.34,2.38-1.16,2.59,.02-.19,2.04-.34,4.08-.61,6.12-1.41,10.61-3.02,21.18-4.69,31.76,.04,1.69-3.65,15.13-1.66,14.37,5.68-1.5,11.1-3.85,16.72-5.6,1.67-.52,2.08-.23,1.9,1.33-3.24,19.89-7.4,39.64-11.5,59.36-.04,.24,.54,.6,.84,.54,6.24-1.23,12.4-3.58,18.85-3.11,.23,0,.46,.2,.83,.38Z"/><path class="cls-2" d="M1072.64,698.95c-1.4,.77-2.71-.42-3.97-.94-6.16-2.88-12.31-5.78-18.49-8.64-1.21-.37-7.37-3.77-4.72-.23,3.3,4.94,6.61,9.87,9.9,14.81,.9M 8,1.61,2.13,3.21-.79,1.96-5-2.12-9.97-4.27-14.99-6.36-1.91-.8-3.88-1.49-5.86-2.18-.28-.1-.72,.08-1.25,.16,3.95,5.97,7.9,11.8,11.85,17.75,.24,.37,.46,.78-.14,1.21-6.68-2.44-13.15-5.34-20.08-7.4-.19,.19-.5,.39-.46,.49,.19,.51,.42,1.01,.73,1.48,3.18,4.87,6.38,9.72,9.57,14.59,.51,.94,1.42,1.8,1.35,2.92-.01,.25-.44,.27-1.07,.06-4.83-1.64-9.66-3.28-14.5-4.91-.99-.22-2.02-.9-3.01-.42,.09,1,.87,1.79,1.4,2.64,3.06,4.91,6.17,9.81,9.25,14.72,.42,.67,.79,1.37,1.12,2.07,.07,.14-.12,.38-.23,.55-.7,.18-1.55-.31-2.25-.45-4.23-1.41M -8.55-2.6-12.9-3.74-.38-.1-.79-.26-1.12-.01-.53,.39-.06,.78,.13,1.14,.2,.4,.46,.78,.69,1.17,2.97,5.07,5.94,10.14,8.89,15.22,.56,.97,1.03,1.98,1.52,2.98,.04,.09,.03,.27-.04,.3-.97,.49-2.03-.21-3.03-.35-3.46-.88-6.92-1.78-10.38-2.65-.63-.16-1.32-.25-1.94,.11,0,.89,.6,1.61,1.01,2.4,3.12,6.4,6.99,12.56,9.69,19.11,.02,.15-.31,.47-.43,.45-4.34-.67-8.62-1.7-12.93-2.53-1.85,0-.07,2.08,.18,2.92,3.63,7.51,6.89,15.12,9.87,22.83-.42,.46-.93,.5-1.47,.39-4.28-.97-8.58-1.88-12.93-2.5l.1,.06c-3.16-8.39-7.06-16.48-10.79-24.64-.1-.2M 6,.29-.75,.59-.73,3.88,.22,7.75,.63,11.6,1.12,.54,.06,1.03-.42,.83-.84-3.1-6.46-6.77-12.65-10.13-18.98-.27-.59-1.16-1.69-.05-1.91,4.43,.03,8.67,1.5,13.04,1.81,.34-.02,.52-.2,.42-.43-3.01-6.16-7.05-11.82-10.46-17.77-.4-.66-1.03-1.27-.88-2.08,.62-.35,1.3-.24,1.94-.12,3.78,.74,7.63,1.31,11.33,2.3,.64,.17,1.3,.29,1.95-.09-2.91-5.93-7.36-11.22-10.83-16.89-.37-.76-1.31-1.46-.94-2.35l-.06,.09c4.6,.09,9.04,2.09,13.57,2.93,.67,.03,3.15,1.09,3.13,.09-3.75-6.23-8.35-11.99-12.33-18.08,.5-.45,1.02-.41,1.52-.28,5.6,1.52,11.19,3.M 06,16.75,4.72,1.52-.05-.2-1.69-.5-2.31-3.17-4.38-6.36-8.75-9.52-13.14-.6-.83-1.13-1.71-1.67-2.57-.03-.05,.05-.18,.12-.23,.53-.33,1.32,.06,1.9,.15,5.41,1.64,10.81,3.31,16.09,5.22,.85,.31,1.75,.53,2.64,.77,.12,.03,.52-.24,.49-.39-3.71-6.04-8.44-11.46-12.35-17.39-.06-.08-.07-.28-.03-.3,.21-.09,.49-.23,.68-.19,7.23,2.24,14.35,4.95,21.37,7.65,.74,.41,3.36,1.32,1.95-.63-3.87-5.42-7.75-10.84-11.62-16.26-.31-.37,.2-.65,.54-.58,5.19,1.67,10.18,3.94,15.25,5.91,3.84,1.57,7.61,3.22,11.43,4.82,.15,.05,.94-.03,.79-.39-.62-1.34-1M .63-2.47-2.44-3.71-2.88-4.14-5.76-8.28-8.65-12.42-.31-.39-.8-1.17-.15-1.39,3.36,.81,6.49,2.58,9.68,3.86,7.48,3.14,14.67,6.98,22.1,10,.46-.19-.04-1.12-.18-1.46-2.14-3.48-4.32-6.94-6.47-10.41-.36-.57-.66-1.17-.97-1.76-.03-.06,.06-.19,.14-.25,.55-.29,1.26,.24,1.8,.39,5.18,2.52,10.4,4.98,15.51,7.59,6.13,3.13,12.15,6.4,18.22,9.6,.64,.21,1.4,.92,2.06,.69,.09-.07,.21-.2,.18-.27-.24-.61-.47-1.23-.79-1.82-1.75-3.27-3.52-6.52-5.28-9.78-2.43-3.91-.46-2.77,2.21-1.38,13.71,7.07,26.68,14.97,39.84,22.63,.1,.05,.36,.07,.38,.03,.11M -.17,.29-.4,.22-.55-2.16-4.86-4.37-9.72-6.45-14.61,.33-.77,1.4,.09,1.92,.29,16.78,9.5,32.47,20.24,48.68,30.43,.17,.07,.53-.14,.48-.34-.29-.94-.58-1.88-.92-2.81-1.43-3.93-2.87-7.85-4.3-11.78-.18-.51-.38-1.03,.13-1.63,17.57,10.46,34.16,22.77,50.72,34.5,2.39,1.74,4.76,3.49,7.16,5.22,.12,.09,.47,.01,.7-.04,.5-.67-.13-1.73-.22-2.51-1.18-4.64-2.37-9.28-3.55-13.92-.34-1.55,1.11-.89,1.84-.32,2.12,1.5,4.25,2.99,6.34,4.51,18.33,13.32,36.62,27.01,54.1,41.27,1.89,1.53,3.82,3.04,5.75,4.54,.15,.12,.54,.15,.74,.07,.23-.14,.38-.55M ,.31-.83-.63-4.49-1.29-8.99-1.89-13.48-.17-1.58-1.29-6.16,1.65-3.68,26.66,20.93,52.78,42.49,78,65.1,.43,6.66,.06,13.37,.17,20.06-.18,1.21-.21,1.83-1.57,.74-3.28-3-6.54-6.02-9.8-9.03-20.71-19.14-42.18-37.93-64.17-55.99-.5-.3-1.35-1.24-1.85-.56,.28,5.6,1.44,11.12,2.08,16.69,.05,.54,.42,1.98-.48,1.97-18.61-14.89-36.6-30.74-55.95-45.19-2.82-2.17-5.64-4.32-8.47-6.48-.48-.37-.97-.76-1.86-.66,.82,5.76,3.1,11.32,3.86,17.1-.04,.22-.48,.62-.77,.45-13.33-10.15-26.6-20.47-40.4-30.27-4.6-3.32-9.31-6.55-13.97-9.81-.61-.36-1.22-.M 97-2-.77-.07,.01-.16,.19-.14,.29,.09,.42,.19,.84,.33,1.25,1.64,4.77,3.3,9.54,4.93,14.32,.06,.19-.03,.41-.08,.62-.32,.36-1.25-.22-1.64-.54-9.02-6.34-18.04-12.63-27.19-18.83-6.18-4.17-12.57-8.12-18.88-12.16-.49-.21-1.17-.76-1.71-.55-.09,.06-.2,.19-.18,.26,.32,.82,.65,1.64,1.01,2.45,1.7,3.86,3.42,7.71,5.1,11.57,.17,.38,.11,.83,.12,1.25,0,.05-.21,.16-.27,.14-3.49-1.6-6.51-4.16-9.84-6.11-9.67-6.2-19.54-12.2-29.65-17.93-.76-.43-1.6-.78-2.41-1.15-.05-.02-.22,.05-.28,.11-.08,.08-.17,.21-.14,.28,.31,.71,.63,1.42,.99,2.11,1.M 96,3.78,3.93,7.55,5.89,11.33,.21,.44,.58,1.33-.23,1.27-11.09-6.25-22.07-12.7-33.53-18.56-.78-.41-1.64-.71-2.48-1.04-.03-.01-.27,.16-.25,.21,1.67,4.12,4.65,7.73,6.8,11.65,1.49,2.28,2.6,4.81,4.36,6.9l-.07-.07c-1.42,.87-2.86-.8-4.16-1.28-8.84-4.71-17.86-9.19-27.06-13.43-1.27-.33-.49,1.16-.08,1.64,3.82,5.64,7.15,11.68,11.27,17.09l.04-.04Z"/><path class="cls-2" d="M329.09,759.62c1.2-1.05-.46-2.45-.81-3.57-1.86-3.58-3.71-7.16-5.58-10.73-.21-.41-.34-.8,.08-1.27,10.94,6.27,21.86,12.56,33.17,18.4,.83,.3,2.35,1.57,3.12,1.06,M .32-.78-.76-1.61-1.04-2.33-2.82-4.65-5.64-9.29-8.46-13.94-.34-.77-1.22-1.48-.97-2.36,.64-.54,2.27,.9,3.04,1.15,8.72,4.69,17.69,9.06,26.73,13.34,.44,.21,.87,.51,1.45,.37,.7-.04-.48-1.57-.65-1.98-3.56-5.42-7.19-10.8-10.48-16.38-.46-1.49,2.46,.16,2.99,.41,8,3.55,15.64,7.79,23.87,10.81,.64-.73-.24-1.38-.59-2.06-3.36-5.03-6.74-10.05-10.09-15.09-.6-1.22-1.69-2.5,.58-1.71,6.6,2.99,13.33,5.66,20.08,8.3,.7,.22,1.48,.67,2.2,.24,.06-.03,.08-.2,.04-.27-.61-.95-1.24-1.9-1.86-2.85-3.33-5.04-6.66-10.08-9.97-15.13-.08-.13,.11-.39,M .21-.57,6.87,1.95,13.51,5.66,20.52,7.21,.91-.33-.86-1.97-1.05-2.55-3.45-5.59-7.54-10.87-10.59-16.67,.45-.8,1.72,.12,2.42,.2,5.11,1.65,10.14,3.54,15.28,5.07,1.87,.2,.28-1.64-.13-2.38-3.48-5.45-7.01-10.89-10.28-16.47-.21-.36-.17-.82-.25-1.24l-.1,.05c.68-.26,1.31-.06,1.93,.13,3.27,.99,6.52,2.01,9.8,2.97,1.51,.44,3.07,.76,4.62,1.1,.09,.02,.45-.33,.4-.44-3.29-6.27-7.31-12.19-10.55-18.44-.2-.6-1.36-1.97-.38-2.19,4.17,.68,8.18,2.09,12.29,3.03,.92,.13,1.87,.5,2.68-.16-3.48-6.86-7.2-13.62-10.66-20.5-.2-.39-.43-.8,0-1.19,.33M -.3,.75-.13,1.12-.06,4.03,.87,8.07,1.63,12.11,2.43,.88,.03,.81-.63,.54-1.19-3.92-8.06-7.53-16.26-10.7-24.58,.5-.42,1.02-.45,1.56-.34,4.28,.96,8.58,1.78,12.9,2.5l-.11-.06c2.87,8.48,7.08,16.44,10.72,24.67,.18,1.24-3.79,.38-4.67,.44-2-.2-3.99-.47-5.99-.7-.76-.09-1.7-.53-2.23,.11-.48,.58,.18,1.23,.49,1.81,3.35,6.34,6.84,12.62,10.12,19,.13,.26-.26,.69-.62,.65-4.28-.26-8.45-1.18-12.67-1.87-1.24,.07-.43,1.17-.15,1.79,3.17,5.48,6.41,10.93,9.81,16.28,.37,.78,2.03,2.51,.13,2.49-4.2-.61-8.43-1.41-12.54-2.43-3-.68-.86,1.63-.23M ,2.95,3.14,4.76,6.32,9.5,9.47,14.25,.21,.51,1.71,2.12,.65,2.21-5.01-.61-9.79-2.27-14.71-3.35-.48-.12-1.03-.06-1.55-.06-.07,0-.22,.16-.2,.22,2.43,4.6,5.9,8.67,8.73,13.06,1.05,1.5,2.14,2.99,3.2,4.49,.78,.85-.41,1.03-1.09,.87-21.55-5-21.6-10.22-7.48,9.83,.74,1.02,1.48,2.05,2.19,3.09,.11,.16,.13,.54,.09,.56-.36,.09-.78,.21-1.13,.14-5.55-1.55-10.98-3.55-16.48-5.27-.84-.21-4.79-2.1-3.13,.3,3.38,4.65,6.77,9.3,10.15,13.95,.61,.84,1.21,1.67,1.79,2.52,.16,.24,.07,.43-.22,.53-.62,.16-1.28-.24-1.88-.37-6.87-2.47-13.79-4.8-20.5M 6-7.5-3.77-1.39,.02,2.52,.7,3.72,3.27,4.58,6.7,9.05,9.85,13.71-.29,.13-.56,.35-.7,.3-1.13-.34-2.25-.69-3.34-1.11-6.8-2.6-13.51-5.34-20.12-8.23-1.06-.46-2.15-.87-3.24-1.3-.47-.2-.68,.46-.61,.54,3.19,5.14,6.9,9.97,10.29,14.98,.58,.9,1.67,1.94,.64,2.93h.03c-.39-.62-1.19-.83-1.88-1.13-9.92-4.29-19.75-8.75-29.52-13.35-.72,.55-.29,.89,.11,1.71,2.41,3.97,4.96,7.88,7.32,11.87,.08,.15-.08,.4-.17,.59-9.44-3.55-18.46-8.87-27.45-13.41-3.13-1.67-6.31-3.29-9.47-4.92-.09-.05-.34-.06-.36-.03-.11,.18-.3,.41-.24,.56,2.07,4.23,4.49,8M .29,6.69,12.45,.14,.42,.67,1.15,.3,1.51-.07,.06-.25,.12-.31,.09-.93-.42-1.87-.83-2.76-1.3-13.88-6.97-26.81-15.32-40.23-22.64-.39,.58-.11,1.07,.12,1.58,1.96,4.35,4.04,8.67,5.92,13.05,.1,.27-.06,.6-.12,1.06-16.33-9.07-31.94-19.21-47.29-29.41-.82-.55-1.68-1.08-2.55-1.58-.13-.08-.44,0-.64,.07-.07,.02-.13,.2-.11,.29,1.57,5.24,3.87,10.28,5.44,15.52,.03,.17-.16,.37-.29,.53-.03,.04-.28,0-.38-.05-19.29-12.07-38.12-25.26-56.35-38.75-2.13-1.52-2.05-.62-1.72,1.41,1.17,4.64,2.38,9.28,3.58,13.91,.12,.52,.35,1.09-.26,1.38-18.61-1M 2.23-36.55-26.45-54.16-40.12-19.54-15.21-14.02-15.36-12.05,7.73-.21,1.07-1.62-.11-2.09-.45-12.61-9.87-25.14-19.81-37.38-29.98-13.27-11.02-26.18-22.28-39.09-33.59-1.97-1.78-1.85-1.49-1.86-3.71,0-5.92-.05-11.85-.07-17.77,0-.41-.09-.86,.36-1.18,.44-.35,.96,.25,1.3,.46,8.25,7.54,16.45,15.11,24.76,22.61,15.73,14.18,31.77,27.91,48.17,41.4,.75,.62,1.56,1.18,2.36,1.75,.1,.05,.61-.07,.64-.22-.08-6.12-1.6-12.19-2.16-18.3-.08-.43,.53-.48,.83-.37,20.5,17.05,41.15,34.34,62.66,50.4,.78,.59,1.64,1.11,2.47,1.65,.29,.19,.74-.21,.73M -.45-1.33-5.6-2.78-11.18-3.99-16.81-.03-.14,.23-.33,.39-.47,13.8,9.97,27.4,21.03,41.63,30.95,4.2,3.03,8.51,5.97,12.79,8.93,.6,.41,1.3,.73,1.97,1.07,.08,.04,.27,.02,.35-.03,.09-.06,.19-.2,.16-.28-.23-.84-.46-1.68-.75-2.5-1.45-4.15-2.92-8.29-4.37-12.43-.71-2.09,1.1-1.14,2-.43,4.86,3.41,9.67,6.86,14.57,10.24,10.42,7.14,20.96,14.32,31.93,20.83,.09,.05,.33,.06,.38,.02,.14-.15,.34-.35,.31-.5-1.74-4.77-4.08-9.34-6.04-14.03-.04-.35-.54-.95-.06-1.19,13.91,8.18,27.75,17.34,42.04,25.5,0,0,.15-.11,.15-.11l-.22,.06Z"/><polygon M class="cls-2" points="431.53 461.92 431.53 462 431.44 462 431.53 461.92"/><polygon class="cls-2" points="433.83 504.59 433.98 504.59 433.98 504.67 433.83 504.59"/><path class="cls-2" d="M439.62,542.74v.06s-.05,.01-.07,.02l.07-.08Z"/><path class="cls-2" d="M670,602.28s.04-.07,.07-.1c.03,.01,.05,.03,.08,.04l-.15,.06Z"/><path class="cls-2" d="M574.01,615.95c-1.67,2.97-2.63,6.21-4.67,8.97-1.23-.54-1.44-1.93-1.99-3.02-1.49-3.57-2.95-7.14-4.46-10.82-1.22,.04-1.47,1.19-2,2.04-1.58,2.85-3.15,5.71-4.74,8.56-1.53,2.68-1.82,.M 19-2.58-1.32-1.62-4.44-3.01-8.95-4.79-13.34-.05-.13-.36-.19-.54-.27-.64,.3-.88,.81-1.18,1.29-1.75,2.79-3.5,5.58-5.26,8.37-.38,.54-.93,1.62-1.7,1.42-2.46-5.57-3.97-11.63-5.84-17.44-.17-.42-.21-1.04-.86-.86-2.98,3.02-5.3,7.01-8.13,10.31-.26,.3-.74,.03-.93-.18-2.35-6.3-3.87-12.98-5.62-19.49-.14-.56-.34-1.11-1-1.21-.1-.03-.3,.04-.36,.11-2.78,3.05-5.51,6.12-8.31,9.15-.6,.57-1.19,.45-1.46-.15-.46-1.69-.91-3.37-1.32-5.06-1.29-5.39-2.56-10.78-3.86-16.17-.17-.74-.43-1.46-.71-2.18-.03-.08-.52-.16-.65-.08-3.57,2.65-6.34,6.33-M 10.06,8.76-.77,.18-1.03-.8-1.19-1.35-1.6-7.21-3.04-14.42-4.4-21.68-.26-1.38-.51-2.77-.81-4.14-.54-.57-1.46,.16-1.96,.49-3.27,2.4-6.36,5.04-9.75,7.27-1.9,.56-1.6-3.23-1.96-4.31-1.95-8.8-2.72-17.75-4.26-26.58-.07-.28-.66-.54-.94-.42-.23,.09-.5,.15-.71,.27-3.14,1.91-6.78,3.08-10.25,4.51-.4,.17-1.14,.24-1.42-.08-1.02-2.3-.96-4.86-1.4-7.3-1.41-9.18-1.89-18.47-2.97-27.68-.3-1.74-2.42-.74-3.56-.49-3.82,.83-7.55,2.31-11.43,2.74-.67-14.19-2.42-28.37-2.45-42.59,4.51-.38,8.85-1.58,13.29-2.41,.69-.19,2.21-.4,2.4,.45,.54,13.33,M .34,26.74,1.62,40.02,.46,1.53,7.53-1.56,8.7-2.06,1.5-.71,2.92-1.53,4.39-2.3,.64-.34,1.34-.44,1.47-.19,.15,.27,.32,.57,.34,.86,.55,11.43,1.47,22.81,2.68,34.18,.67,1.76,3.01-.77,4.01-1.22,2.36-1.61,4.7-3.23,7.06-4.83,.95-.62,3.14-2.56,3.25-.29,.97,9.88,1.9,19.78,3.7,29.56,.07,.42,.88,.62,1.26,.31,3.46-2.71,6.8-5.51,10.2-8.29,.31-.29,1.04-.23,1.21,.2,1.53,8.41,2.39,16.91,4.19,25.29,.08,.51,.38,1.01,.56,1.47,.77,.02,1.12-.3,1.45-.63,2.99-2.91,5.74-6.04,8.88-8.79,.14-.12,.49-.08,.87-.13,1.91,7.86,2.56,16.07,5.09,23.78,.M 71-.01,1.08-.3,1.38-.67,2.65-3.12,5.18-6.32,7.92-9.36,.32-.3,1-.29,1.13,.23,1.74,6.72,2.7,13.65,5.02,20.24,.35-.08,.71-.07,.83-.2,2.71-3.14,4.85-6.71,7.34-10.02,.25-.35,.52-.73,1.18-.68,.63,.72,.74,1.59,.96,2.43,1.46,5.13,2.41,10.43,4.28,15.44,.12,.14,.77,.34,.96,.06,1.82-2.3,3.18-4.91,4.78-7.35,2.24,2.59,4.57,5.07,6.97,7.45,.61,1.48,1.3,6.56,3.06,2.93,3.23,3.01,6.59,5.83,10.05,8.47Z"/><path class="cls-2" d="M583.99,622.93c-.23,.45-.46,.88-.67,1.31-1.74-.42-1.82-2.33-2.77-3.56,1.14,.77,2.28,1.52,3.44,2.25Z"/><path M class="cls-2" d="M603.84,633.57c-1.1,3-2.15,6.1-3.21,9.12h-.01c-1.17,.76-2.32,1.53-3.47,2.32-1.99-2.24-3.79-4.63-5.68-6.94-.17-.21-.94-.16-1.03,.07-1.73,3.92-3.18,7.99-4.64,11.98-.83,.14-1.19-.17-1.63-.73-1.86-2.62-3.7-5.25-5.56-7.87-.47-.48-.96-1.72-1.8-1.2-2.15,3.59-3.15,7.83-5.22,11.49-.19,.31-.78,.14-.96,0-2.9-3.6-4.68-8.27-7.75-11.64-.63,.3-.89,.78-1.13,1.29-1.73,3.4-3.12,6.93-5.15,10.16-.74-.35-1.06-.82-1.34-1.31-1.95-3.43-3.9-6.86-5.86-10.29-.65-.83-.81-2.13-2.05-2.21-1.98,3.01-3.57,6.26-5.49,9.31-.3,.42-.32M ,1.18-1.23,1.06-.77-.09-.83-.77-1.12-1.23-2.8-4.71-4.67-9.91-7.34-14.61-.63,.05-.96,.38-1.23,.76-1.79,2.53-3.57,5.07-5.37,7.59-.39,.56-.68,1.19-1.47,1.49-.69-.23-.91-.74-1.12-1.24-1.35-3.15-2.73-6.3-4.03-9.47-.93-2.25-1.75-4.53-2.61-6.8-.2-.52-.41-1.02-.97-1.38-.22,.1-.52,.14-.66,.29-2.44,2.7-4.78,5.47-7.19,8.2-.33,.36-.72,.62-1.38,.65-2.32-4.72-3.85-9.85-5.82-14.74-.72-1.11-1.71-7.8-3.35-6.65-2.93,2.67-5.74,5.46-8.81,8-.79,.48-1.29-.36-1.54-.98-2.33-6.85-4.7-13.7-6.68-20.63-.27-.94-.62-1.87-.98-2.79-.04-.1-.48-.2-M .67-.15-3.6,1.78-6.65,4.5-10.31,6.19-.66,.16-.95-.53-1.09-1.04-1.54-5.46-3.13-10.91-4.61-16.38-.98-3.58-1.73-7.19-2.65-10.78-.13-.43-.77-.71-1.24-.51-2.26,.96-4.5,1.94-6.77,2.89-1.31,.54-2.65,1.04-3.99,1.54-.44,.16-1.16-.15-1.26-.54-2.69-10.07-4.46-20.36-6.61-30.55-.16-.82-.09-1.67-.14-2.5,4.49-1.3,8.88-3.54,13.46-4.21,1.72,10.34,3.74,20.64,5.89,30.91,.13,.8,.42,1.77,1.52,1.36,3.72-1.54,7.04-3.59,10.59-5.32,.16-.05,.62,.07,.66,.17,.32,.82,.63,1.65,.82,2.49,1.73,8.08,3.71,16.1,5.91,24.08,.06,.21,.18,.4,.26,.61,.08,.M 18,.86,.3,1.08,.15,2.83-1.89,5.27-4.3,7.92-6.43,.79-.45,2.15-2.5,2.88-1.07,2.22,7.45,3.89,14.96,6.44,22.34,.23,.53,.5,1.5,1.27,1.31,3.13-2.33,5.53-5.56,8.35-8.25,.34-.36,.7-.65,1.4-.6,2.71,6.87,4.15,14.37,7.26,21.05,.69,.4,1.34-.47,1.75-.91,2.29-2.79,4.37-5.74,6.77-8.42,.16-.12,.84-.19,.98,.11,.42,1.02,.84,2.03,1.21,3.06,1.67,4.55,3.32,9.1,4.97,13.64,.23,.62,.41,1.25,1.1,1.67,.68-.23,.98-.71,1.3-1.19,1.74-2.67,3.48-5.34,5.25-8.01,.43-.49,.97-1.68,1.77-1.29,2.06,4.29,3.63,8.78,5.52,13.15,1.18,2.52,1.69,4.29,3.46,.77M ,1.47-2.66,2.91-5.33,4.39-7.98,.26-.47,.45-1,1.27-1.23,2.52,4.31,4.55,8.96,7.04,13.34,.21,.36,.91,.52,1.17,.09,1.84-3.45,3.39-7.02,5.09-10.54,.19-.39,.47-.75,1.14-.9,2.63,3.68,4.21,7.98,7.14,11.47,.68-.05,.98-.35,1.16-.79,1.73-3.84,3.06-7.86,5.12-11.53,.8,.28,1.08,.76,1.38,1.24,2.07,2.85,3.62,6.16,6.03,8.73,1.35,.55,2.9-5.91,3.64-7.1,3.22,1.73,6.53,3.31,9.86,4.8Z"/><path class="cls-2" d="M610.78,636.45c-.69,.4-1.37,.79-2.05,1.2-.97-1.08-1.93-2.16-2.9-3.23,1.65,.7,3.29,1.37,4.95,2.03Z"/><path class="cls-2" d="M697.6M 1,575.53c-.09,.33-.08,.68-.26,.94-3.24,4.59-6.45,9.22-9.75,13.77-.27,.34-.96,.48-1.43,.26-2.56-1.24-4.97-2.57-7.63-3.66-3.49,4.93-5.34,10.32-8.47,15.34-10.4-5.49-7.1-6.28-12.22,4.16-3.33-.5-6.62-1.11-9.87-1.83,1.86-3.75,3.53-7.59,5.55-11.26,.26-.46,.86-.61,1.29-.32,2.06,1.39,4.05,2.88,6.22,4.11,1.09,.42,1.42-1,1.89-1.68,2.31-4.58,5.07-9.04,7.24-13.65-.58-1.17-2.02-1.68-3.05-2.5-1.23-.98-2.41-2.02-3.89-2.85-1.18,.55-1.52,1.67-2.14,2.69-1.95,3.54-3.88,7.1-5.83,10.65-.49,.62-.8,1.98-1.79,1.86-2.15-1.15-3.85-3.03-5.8-4M .46-.39-.32-.79-.58-1.52-.52-3.01,4.79-5.02,10.15-7.76,15.08-.74,0-1.11-.29-1.43-.63-1.85-1.84-3.39-3.99-5.46-5.58-.12-.08-.62,.01-.68,.11-.66,1.16-1.32,2.31-1.84,3.52-3.09-1.12-6.1-2.35-9.04-3.7,1.36-2.7,2.72-5.4,4.08-8.09,.21-.41,.52-.74,1.24-.9,.9,.97,5.12,9.17,6.42,7.08,2.23-4.28,4.53-8.52,6.81-12.77,1.28-2.49,1.74-2.06,3.19,.03,1.34,1.48,2.7,2.95,4.07,4.41,.23,.25,.82,.18,1-.1,3.22-4.98,5.74-10.27,9.11-15.18,.47,.15,.93,.19,1.15,.4,1.8,1.58,3.3,3.48,5.29,4.86,1.29,.49,1.74-1.39,2.46-2.11,2.83-4.04,5.64-8.09,8.M 47-12.13,.32-.45,.62-.94,1.14-.99,2.42,1.88,4.73,3.68,7.07,5.51,.2,.43-.2,.76-.46,1.13-3.34,4.8-6.72,9.57-10.05,14.38-.24,.38-.13,.88,.3,1.16,1.78,1.15,3.57,2.3,5.37,3.42,2.01,1.24,2.21,.46,3.4-1.14,2.89-4.01,5.76-8.03,8.64-12.05,.33-.45,.65-.94,1.38-1.07,2.65,1.15,5.01,2.9,7.59,4.3Z"/><path class="cls-2" d="M196.48,1198.45c19.59-.23,39.32,.32,58.96-.25,5.19-.09,5.05-.3,2.78,3.32-2.94,4.84-6.18,9.53-8.95,14.47-.23,1.29,2.14,.59,2.9,.74,3.1-.11,6.19-.21,9.29-.38,12.89-.76,25.82-1.27,38.67-2.42,1.31-.11,2.65-.35,4.06M ,.02-.14,1.37-1.38,2.28-2.11,3.4-3.34,4.3-6.69,8.59-10.03,12.89-.42,.55-.79,1.12-1.17,1.69-.13,.19,.34,.69,.64,.68,13.4-.68,26.76-2.38,40.1-3.8,2.66-.3,5.34-.52,8.01-.77,.43-.04,.48,.41,.42,.72-4.93,5.94-10.39,11.53-15.5,17.34-.46,.51-1.05,.99-.92,1.74,14.79-1.07,29.49-4.03,44.24-5.65,1.48,.34-.13,1.37-.78,2.2-5.29,5.31-10.6,10.6-15.89,15.91-.94,1.21-4.53,3.63-.68,3.11,12.98-1.81,25.91-3.96,38.84-6.08,.2,0,.74,.33,.49,.62-6.83,6.86-14.09,13.31-21.08,20.02-.45,.54-3.06,2.49-1.6,2.72,12.29-1.88,24.54-3.99,36.81-5.96,M .55-.08,1.04,.21,.55,.75-8.17,7.49-16.6,14.71-24.86,22.1-.81,.72-1.61,1.44-2.38,2.19-.12,.12-.06,.39-.02,.58,.83,.33,2.22-.08,3.15-.11,4.9-.73,9.79-1.47,14.68-2.24,5.62-.66,11.42-2.33,16.98-2.51,.13,.91-1.07,1.46-1.69,2.04-9.37,8.04-18.75,16.07-28.13,24.1-.73,.63-1.44,1.28-2.11,1.95-.12,.12,.01,.39,.04,.67,10.55-.81,20.9-3.02,31.46-3.85,0,.32,.11,.6-.02,.71-.87,.82-1.76,1.63-2.7,2.4-10.58,8.76-21.16,17.51-31.74,26.26-.84,.7-1.67,1.4-2.47,2.13-.14,.12-.17,.43-.08,.57,.7,.5,1.83,.14,2.66,.16,4.15-.36,8.3-.73,12.45-1.M 09,4.28-.38,8.57-.76,12.85-1.14,.36-.03,.81-.13,.97,.25,.15,.35-.15,.62-.42,.85-.83,.7-1.68,1.4-2.53,2.09-13.61,10.89-27.14,21.9-40.81,32.73-.9,.78-2.27,.63-3.42,.66-7.14,0-14.28,.02-21.43,.02-5.03,.24-1.35-1.89,.44-3.41,5.6-4.51,11.21-9.02,16.8-13.53,5.78-4.67,11.54-9.36,17.31-14.04,1.75-1.48,4.74-3.28,.22-2.82-8.92,.76-17.73,1.29-26.68,1.94,.07-1.5,1.76-2.09,2.7-3.08,9.7-8.08,19.41-16.16,29.11-24.25,1.65-1.54,4.67-3.33,.11-2.83-9.2,1.06-18.39,2.14-27.59,3.15-.57,0-1.39,.16-1.87-.18-.06-.09-.13-.25-.08-.31,.57-.59M ,1.13-1.19,1.76-1.74,8.47-7.39,16.94-14.76,25.41-22.15,.65-.71,3.52-2.74,.98-2.52-11.17,1.4-22.23,3.61-33.46,4.36-1.1-.07-.21-1.11,.21-1.46,7.18-6.57,14.39-13.12,21.56-19.7,.64-.78,4.21-3.36,1.45-3.03-7.96,1.09-15.92,2.19-23.89,3.27-4.39,.5-8.76,1.36-13.18,1.52-1.51-.16,.44-1.72,.86-2.23,5.77-5.69,11.56-11.37,17.33-17.05,2.45-2.42,2.89-3-1.09-2.57-12.89,1.79-25.77,3.51-38.74,4.64-.2-.01-.75-.35-.58-.65,.77-.88,1.54-1.77,2.34-2.63,4.73-5.11,9.48-10.2,14.21-15.31,.32-.5,1.21-1.1,1.07-1.65-.16-.14-.38-.37-.55-.36-3.88M ,.38-7.75,.8-11.62,1.19-9.09,.92-18.17,1.87-27.27,2.68-2.14,.19-4.29,.34-6.43,.5-.41,.03-.8-.02-1.01-.34-.22-.34,.04-.62,.25-.88,4.59-5.95,9.7-11.56,13.94-17.76,.06-.1-.21-.47-.34-.47-4.17-.15-8.31,.42-12.47,.65-12.99,.88-26.06,2.03-39.07,2.11-.97-.52,.36-1.59,.55-2.26,3-4.7,6.03-9.39,9.03-14.08,.43-.67,.79-1.36,1.11-2.07,.06-.13-.18-.47-.35-.51-3.46-.36-7,.09-10.48,.05-15.88,.33-31.8,.8-47.67,.27-.79-.37-.06-1.41,.09-2.01,2.25-5.07,4.52-10.14,6.76-15.21,.26-.59,.77-1.16,.44-1.85l-.13,.07Z"/><path class="cls-2" d="M M1007.42,688.18c-.81,.29-1.58,.05-2.35-.13-4.13-.94-8.26-1.91-12.39-2.84-1.44-.16-2.91-.94-4.32-.41,3.83,6.01,9.39,11.13,12.99,17.3-.65,.29-1.16,.17-1.68,.05-4.52-1.04-9.1-1.9-13.73-2.55-.42-.05-1.77-.37-1.6,.32,3.41,5.29,7.47,10.17,11.13,15.3,.33,.67,1.48,1.54,1.03,2.29-.15,.13-.5,.19-.73,.16-4.35-.69-8.72-1.3-13.09-1.85-.77-.05-1.58,.4-.86,1.18,3.26,4.7,6.54,9.39,9.8,14.08,.55,1.04,3.37,3.9,.58,3.65-4.39-.49-8.78-1.02-13.2-1.28l.09,.07c-4.07-5.7-8.14-11.4-12.21-17.1-.33-.46-.77-.9-.32-1.56,4.23-.22,8.54,.29,12.78M ,.43,.34,.02,.7-.45,.54-.69-3.37-4.96-7.33-9.53-10.94-14.33-.36-.69-1.64-1.46-1.13-2.27,.16-.2,.73-.29,1.1-.26,2.15,.13,4.3,.28,6.43,.49,2.27,.22,4.53,.52,6.8,.76,.22-.01,.77-.28,.58-.61-3.78-5.15-8.08-9.92-12.08-14.91-.37-.45-.8-.87-.61-1.56,5.44,.13,10.84,1.44,16.27,1.94,.45,.07,.51-.5,.39-.69-4.24-5.12-8.52-10.23-12.87-15.27-.09-.11,.05-.38,.14-.55,.04-.07,.23-.11,.36-.13,6.08,.47,12.18,2.35,18.14,2.77,.45-.52-.05-.96-.38-1.39-1.73-2.05-3.46-4.11-5.23-6.14-.53-1-8.37-8.49-6.35-8.45,7.17,.5,14.03,2.93,21.02,4.22,M 1.3-.32-4.26-5.81-4.8-6.75-2.21-2.58-4.47-5.12-6.7-7.69-.45-.52-1.03-1.01-1.09-1.7,.59-.38,1.21-.18,1.84-.02,6.7,1.61,13.42,3.18,19.94,5.24,.99,.31,2.04,.51,3.07,.75,.1,.02,.26-.07,.35-.14,.06-.05,.1-.18,.06-.24-.3-.48-.59-.97-.95-1.41-2.12-2.62-4.27-5.23-6.41-7.84-.56-.87-1.89-1.67-1.83-2.75,.19-.4,.68-.18,1.05-.08,5.89,1.54,11.66,3.34,17.37,5.26,3.35,1.12,6.68,2.28,10.04,3.4,.21,.07,.56,.03,.74-.07,.13-.07,.2-.39,.11-.52-2.76-4.12-6.14-7.81-8.94-11.9,.74-.38,1.25-.18,1.95,.07,6.58,2.21,13.14,4.46,19.54,6.98,3.99,M 1.57,7.98,3.11,11.99,4.65,.18,.07,.55,0,.7-.11,.14-.11,.21-.41,.12-.55-.79-1.25-1.6-2.49-2.45-3.71-1.65-2.79-4.45-5.6-5.53-8.54,.13-.25,.37-.32,.67-.21,4.83,1.91,9.72,3.72,14.46,5.74,8.13,3.34,16.1,7.05,24.08,10.55,.16-.19,.44-.39,.4-.5-.24-.61-.51-1.22-.85-1.8-1.95-3.31-3.93-6.61-5.89-9.92-.29-.48-.51-.99-.73-1.5-.03-.07,.02-.24,.09-.26,.23-.07,.54-.19,.7-.12,2.27,.94,4.54,1.88,6.76,2.89,13.07,5.7,25.6,12.59,38.31,18.53,.14-.15,.36-.39,.3-.51-1.69-3.51-3.43-7.01-5.13-10.53-.58-1.2-1.09-2.42-1.62-3.63-.02-.16,.32-.M 4,.5-.34,6.57,2.78,12.76,6.44,19.13,9.63,10.46,5.52,20.7,11.28,30.85,17.16,.87,.5,1.76,.99,2.67,1.45,.14,.07,.44-.03,.64-.1,.37-.41-.26-1.35-.32-1.85-1.65-4.32-3.31-8.64-4.95-12.97-.15-.39-.26-.81,.22-1.15,21.22,11,41.16,24.15,61.3,36.87,.58,.13,1.33,.43,1.23-.44-.36-1.48-.77-2.95-1.15-4.42-1.01-3.9-2.03-7.8-3.02-11.7-.03-.27,.19-.78,.58-.65,24.73,14.98,48.65,31.67,72.16,48.28,.13,.04,.56-.12,.62-.29,.06-.21,.12-.42,.09-.63-.58-4.17-1.19-8.34-1.76-12.52,.06-1.17-1.63-6.89,.75-5.24,28.99,19.99,57.33,40.95,84.58,63.1M ,.27,6.42,.04,12.89,.11,19.32-.08,.63,.22,1.35-.38,1.82-.74,.39-2.05-1.14-2.76-1.63-17.1-14.28-34.28-28.34-52.11-41.97-8.36-6.41-16.88-12.69-25.34-19.03-.71-.44-1.39-1.22-2.32-1.03-.3,.24-.2,.84-.2,1.2,.58,5.78,2.1,11.53,2.17,17.33,0,.09-.44,.23-.64,.21-1.13-.44-2.05-1.41-3.05-2.08-21.46-16.46-43.8-32.64-66.66-47.47-1.02-.26-.52,1.3-.5,1.83,1.14,4.43,2.32,8.85,3.49,13.27,.24,.73,.41,1.45,.11,2.19-.95-.03-1.64-.49-2.35-1.05-18.89-12.67-38.08-26.52-58.21-37.2-.16,.1-.24,.39-.19,.57,1.5,4.48,3.27,8.88,4.86,13.33,.23,.M 62,.35,1.26,.51,1.89,.02,.41-.57,.37-.83,.33-16.62-10.2-33.45-20.74-50.96-29.6-.2-.09-.57,.09-.55,.29,2.01,4.82,4.44,9.47,6.6,14.22,.07,.22-.02,.76-.36,.73-13.81-7.06-27.12-14.94-41.22-21.56-1.16-.5-2.26-1.37-3.6-1.11,0,0,.18-.14,.18-.14l-.06,.1c.06,.31,.04,.66,.2,.94,2.5,4.36,5.03,8.71,7.55,13.07l.08-.02c-1.63,.7-3.16-.9-4.64-1.42-11.24-5.28-22.43-11.55-34.26-15.55-.37,0-.35,.41,.12,1.14,1.85,2.87,3.72,5.74,5.61,8.59,1.9,2.95,2.26,3.8,1.78,3.78-1.68-.07-2.88-1.01-4.26-1.6-8.52-3.69-17.06-7.36-25.85-10.63-4.52-1.83M -2.81-.03-1.06,2.58,2.17,3.22,4.81,6.18,6.69,9.57,0,.15-.38,.37-.53,.33-.74-.24-1.5-.46-2.21-.75-7.95-3.16-16.08-6.09-24.32-8.69-.48-.11-1.06-.46-1.48-.1-.45,.38,.03,.78,.3,1.12,.94,1.18,1.9,2.35,2.82,3.54,2.76,3.57,5.5,7.15,8.26,10.73,.35,.46,.76,.9,.51,1.48l.08-.06c-.69,.19-1.31,0-1.94-.2-4.23-1.36-8.45-2.75-12.69-4.07-3-.93-6.04-1.78-9.08-2.63-.3-.08-.71,.08-1.09,.14,3.75,5.79,8.86,10.71,12.66,16.49,.19,.39-.51,.47-.72,.45-5.58-1.54-11.15-3.09-16.74-4.59-1.14-.31-2.31-.55-3.48-.79-.19-.04-.46,.13-.66,.24,.09,.79M ,1.42,1.99,1.9,2.77,3.39,4.25,6.79,8.5,10.18,12.75,.36,.45,.76,.89,.56,1.48l.09-.06Z"/><path class="cls-2" d="M1112.89,621.47c1.23-1.22-.36-2.66-.81-3.9-1.66-3.18-3.32-6.36-4.97-9.54-.2-.39-.28-.82-.38-1.24-.02-.08,.1-.2,.19-.27,17.96,6.57,35.43,15.51,52.52,23.84,1.26,.5,5.02,3.09,3.58-.21-1.59-4-3.2-8-4.79-12-.17-.68-.79-1.54-.08-2.06,21.77,9.52,42.49,21.43,63.27,32.88,.54,.17,2.51,1.56,2.64,.65-.6-4.94-2.56-9.67-3.69-14.51-.17-.62-.19-1.27-.26-1.91-.01-.09,.07-.26,.16-.28,.24-.05,.56-.14,.73-.05,17.32,9.19,34.26,M 19.12,50.86,29.22,7.48,4.59,14.86,9.28,22.3,13.92,.95,.59,1.93,1.17,2.93,1.71,.11,.06,.62-.1,.65-.21,.01-5.97-1.55-11.99-2.12-17.97,.32-1.34,2.03,.13,2.73,.46,30.37,18.65,60.17,38.16,88.9,59.04,.34,6.57,.07,13.15,.17,19.73,0,.43-.06,.86-.12,1.28-.01,.08-.16,.18-.26,.2-.24,.03-.53,.09-.73,.01-8.98-6.24-17.53-13.1-26.47-19.45-18.59-13.43-37.46-26.38-56.69-38.98-1.24-.82-2.57-1.54-3.89-2.28-.09-.05-.58,.17-.58,.26,.17,5.71,1.5,11.34,2.16,17.01,.29,2.31-1.01,1.47-2.3,.65-23.15-15.76-46.6-30.69-70.96-44.92-.75-.3-2.03-1M .55-2.44-.43,.59,2.43,1.21,4.85,1.85,7.27,.81,3.05,1.65,6.1,2.44,9.16-.41,1.4-2.57-.67-3.38-.98-19.39-11.69-38.88-22.91-59.05-33.39-.67-.3-1.33-.88-2.11-.55-.1,.03-.22,.19-.2,.26,.27,.83,.54,1.67,.86,2.49,1.62,4.22,3.25,8.43,4.87,12.65,.03,.08-.03,.24-.11,.27-.22,.08-.52,.2-.69,.14-2.36-.98-4.5-2.35-6.76-3.52-15.43-8.25-31.18-16.28-47.37-23.46-.18,.25-.44,.44-.39,.58,.24,.72,.51,1.44,.86,2.14,1.65,3.3,3.34,6.58,5,9.88,.3,.6,.54,1.21,.79,1.83,.03,.08-.02,.25-.1,.27-.97,.42-1.9-.52-2.8-.81-14.24-6.71-28.65-13.46-43.5M 8-19.03-.16-.05-.45,.12-.65,.23-.14,.53,.63,1.51,.87,2.07,1.95,3.19,3.93,6.37,5.88,9.57,.29,.48,.45,1,.64,1.51,.02,.05-.19,.23-.26,.22-4-.99-7.65-3.11-11.53-4.52-8.28-3.37-16.7-6.51-25.22-9.48-1.07-.23-2.22-1.14-3.32-.8-.15,.1-.27,.4-.19,.53,2.25,3.59,4.92,6.92,7.37,10.39,.21,.49,1.44,1.71,.39,1.84-10.84-3.45-21.42-7.6-32.48-10.63-.61-.09-1.31-.53-1.89-.22-.2,.11-.27,.36-.14,.54,3.18,3.66,6.02,7.84,9.4,11.23l-.06-.06c-1.37,.95-3.09-.17-4.53-.45-7.92-2.41-15.92-4.65-24.03-6.62-.61-.06-1.35-.44-1.92-.12-.07,.06-.15,.M 18-.12,.24,.22,.38,.43,.79,.73,1.13,2.92,3.48,6.16,6.72,8.84,10.38-.63,.26-1.14,.18-1.67,.04-6.38-1.71-12.89-3.07-19.38-4.49-1.68-.28-3.35-.97-5.06-.76-.03,.64,.42,1.05,.82,1.47,3,3.31,6.27,6.41,9.08,9.88,.24,.36-.39,.56-.61,.56-6.98-1.07-13.89-2.9-20.96-3.14-1.18,.14,.93,1.87,1.2,2.32,3.55,3.79,7.11,7.57,10.67,11.36,.27,.41,1,.91,.86,1.4-.16,.13-.39,.32-.56,.3-1.73-.2-3.46-.4-5.17-.69-4.09-.69-8.24-1.07-12.38-1.47-.89-.16-1.47,.53-.69,1.19,3.38,3.62,6.76,7.25,10.13,10.88,.87,1.15,2.38,2.04,2.59,3.51-5.18-.03-10.46M -.99-15.71-1.04-.88-.15-1.43,.58-.66,1.23,3.92,4.23,7.81,8.5,11.66,12.78,1.06,1.21,1.56,2.07-.6,1.88-4.7-.43-9.4-.44-14.12-.25l-.24-.15c-3.7-4.24-7.74-8.28-11.82-12.29-.49-.67-3.01-2.24-1.32-2.79,4.01-.47,8.06-.35,12.09-.51,.61-.05,2.38,.16,2.03-.87-3.94-4.42-8.39-8.4-12.52-12.65-.21-.22-.64-.91-.32-1.12,.38-.1,.77-.23,1.16-.24,4.58-.07,9.16-.1,13.73,.15,1.61,.24,2.22-.6,.81-1.62-3.93-3.98-7.92-7.93-12.01-11.76-2.43-2.23,3.65-1.05,4.64-1.14,4.16,.3,8.34,.36,12.47,.89,2.79,.22,.69-1.45-.21-2.43-2.8-2.75-5.63-5.49-8.M 42-8.25-.55-1.12,1.25-.73,1.88-.71,5.73,.66,11.47,1.27,17.13,2.25,.51,0,3.54,.57,3.15-.29-2.69-3.56-6.25-6.44-9.28-9.72-.91-1.24,1.16-.93,1.94-.82,7.79,1.14,15.49,2.74,23.19,4.31,.24,.05,.62,.04,.76-.08,.31-.26,.04-.57-.15-.81-2.6-3.04-5.43-5.9-8.11-8.86-2.32-2.37,.4-1.65,1.99-1.39,7.44,1.49,14.78,3.28,22.05,5.24,.99,.07,6.22,2.16,5.24,.35-2.47-3.23-5.18-6.29-7.74-9.46-.36-.44-.88-.83-.83-1.41,.48-.33,1.02-.24,1.51-.12,1.93,.48,3.84,.99,5.76,1.5,8.29,2.23,16.49,4.67,24.59,7.31,1.36,.38,2.45,1.06,3.93,.65-2.36-3.64-M 5.07-6.88-7.6-10.37-.26-.48-1.03-1.25-.81-1.72,.48-.42,1.65,.16,2.25,.24,12.56,3.89,24.94,8.11,37.06,12.79,4.41,1.91,1.02-2.11,.12-3.75-1.83-2.87-3.81-5.66-5.41-8.66-.19-.38,.51-.48,.71-.48,16.01,5.67,31.95,11.67,47.06,19.1,.06-.07,.11-.13,.17-.19l-.22,.18Z"/><path class="cls-2" d="M375.73,837.52c-.7,.2-1.31-.01-1.93-.24-4.64-1.73-9.3-3.42-13.91-5.19-9.6-3.68-19.06-7.57-28.37-11.69-1.06-.47-2.14-.91-3.23-1.32-.16-.06-.46,.08-.68,.16-.08,.03-.14,.19-.11,.27,.32,.71,.64,1.41,.99,2.11,1.93,3.79,3.87,7.57,5.78,11.36,.0M 7,.14-.14,.38-.26,.55-19.01-6.89-37.22-16.52-55.38-25.11-.15-.06-.46,.06-.66,.14-.33,.33,.09,1.11,.18,1.53,1.65,4.1,3.31,8.19,4.96,12.29,.1,.44,.52,1.21,.18,1.53-.21,.08-.47,.18-.67,.14-1.48-.44-2.83-1.24-4.23-1.87-19.69-9.53-38.77-19.66-57.71-30.39-1.35-.59-4.25-2.87-3.32,.43,1.17,4.2,2.35,8.4,3.52,12.61,.08,.83,.85,2.11,.1,2.72-17.63-8.61-34.77-19.33-51.62-29.32-7.49-4.59-14.88-9.27-22.33-13.9-1.1-.49-2.12-1.77-3.39-1.44-.31,2.06,.39,4.06,.64,6.09,.39,4.15,1.54,8.32,1.58,12.45-.69,.21-1.16,0-1.59-.27-16.39-9.9-32M .57-20.24-48.43-30.75-13.25-8.83-26.35-17.8-39.19-27.02-.94-.79-2.52-1.38-2.6-2.74-.12-6.25-.02-12.5-.05-18.74-.13-2.89,2.13-.86,3.32,.01,27.44,20.62,55.51,40.46,84.62,59.1,.95,.58,1.24-.77,1-1.46-.74-5.57-1.53-11.13-2.3-16.7-.02-.19,.13-.56,.2-.56,20.31,12.19,40.11,26.47,61.08,38.54,3.98,2.4,8.01,4.75,12.03,7.11,.64,.37,1.22,.86,2.12,.79,.29-.53,.12-1.05-.03-1.58-1.17-4.2-2.34-8.41-3.48-12.61-.26-.94-.43-1.9-.61-2.85-.02-.09,.08-.22,.18-.28,.79-.12,1.69,.66,2.41,.95,7.15,4.23,14.24,8.52,21.44,12.69,12.44,7.21,25.1M 1,14.15,37.99,20.85,.78,.29,1.56,1.09,2.42,.66,.08-.03,.14-.19,.11-.28-.18-.63-.36-1.26-.6-1.87-1.61-4.11-3.23-8.21-4.85-12.32-.16-.4-.45-.8-.14-1.27,1.23-.14,2.83,1.19,4.01,1.67,16.28,8.83,33.08,17.26,50.07,24.93,.58,.14,1.42,.27,.93-.77-2.08-4.56-4.81-8.84-6.63-13.51,.32-.86,2.07,.4,2.68,.55,10.19,4.84,20.48,9.54,30.98,13.95,3.81,1.6,7.66,3.15,11.5,4.71,.53,.11,1.76,.81,2,.04-1.88-3.85-4.48-7.34-6.63-11.05-.35-.58-.61-1.19-.88-1.8,0-.14,.36-.4,.51-.38,12.74,4.88,25.27,10.18,38.26,14.56,.46,.16,1.01,.15,1.53,.2,.0M 7,0,.25-.16,.24-.2-.17-.4-.31-.83-.57-1.19-2.45-3.69-5.58-7.11-7.71-10.96-.01-.17,.29-.42,.46-.42,2.05,.4,3.98,1.32,5.96,1.96,8.57,3.15,17.33,5.92,26.17,8.55,.73,.11,1.59,.58,2.28,.33,.09-.17,.22-.42,.13-.54-2.87-3.88-6.37-7.38-8.97-11.42,.58-.36,1.1-.27,1.61-.12,4.55,1.33,9.09,2.7,13.66,3.98,4.32,1.2,8.69,2.3,13.04,3.43,.47,.06,1.11,.26,1.55-.03,.06-.05,.1-.19,.06-.25-.39-.56-.75-1.14-1.2-1.66-2.46-2.83-4.94-5.65-7.41-8.47-.37-.42-.82-.82-.75-1.44,6.66,1.02,14.08,3.3,20.94,4.57,1.36,.18,3.44,.92,4.68,.71,.09-.16,.M 23-.41,.14-.53-3.07-3.71-6.71-6.97-9.76-10.7-.11-.14-.04-.38,.01-.56,.01-.05,.24-.11,.36-.1,7.09,.91,14.17,3.11,21.37,3.11,.28-.98-.86-1.51-1.37-2.23-3.56-3.79-7.13-7.57-10.69-11.36-1.73-1.85-.9-1.92,1.11-1.62,5.54,.71,11.13,1.89,16.75,1.82,.83-.43-.17-1.11-.5-1.57-3.99-4.47-8.41-8.63-12.17-13.29-.11-.27-.02-.75,.41-.69,5.35,.31,10.7,1.41,16.06,1.07,.89-.52-.66-1.56-.99-2.13-3.81-4.43-8.22-8.45-11.69-13.14-.01-.17,.46-.63,.76-.53,4.96,.51,9.95,.34,14.93,.41l-.1-.06c4.4,4.76,8.98,9.41,13.67,13.99,1.68,1.91-6.07,1.27M -7.05,1.52-2.29,.08-4.57,.13-6.86,.2-1.48,.37,.74,1.96,1.14,2.56,3.78,3.79,7.57,7.56,11.36,11.34,.44,.71-.56,.9-1.07,.91-3.9,.02-7.81,.19-11.71-.05-3.37-.12-3.87-.08-3.78,.34,.22,1.01,1.18,1.63,1.92,2.36,3.48,3.43,6.99,6.83,10.49,10.25,.35,.42,1.27,1.11,.62,1.58-5.34,.02-10.76-.38-16.08-.9-.77-.05-3.76-.51-2.48,.99,3.18,3.21,6.49,6.32,9.71,9.5,.15,.14,.2,.43,.12,.6-.15,.19-.68,.35-.99,.28-5.74-.59-11.47-1.25-17.15-2.15-1.27-.1-2.73-.47-3.95-.25-.06,.19-.17,.46-.06,.59,2.8,3.53,6.82,6.5,9.37,10.02-.13,.15-.32,.38-.5M ,.39-2.53-.02-5.06-.6-7.55-.98-5.5-1.04-10.98-2.12-16.47-3.2-.51-.1-1-.34-1.5,.02,1.95,3.37,5.3,5.91,7.78,8.96,.55,.6,1.04,1.24,1.53,1.87,.06,.07,.02,.23-.05,.31-.94,.31-2.13-.15-3.12-.23-7.44-1.49-14.78-3.26-22.05-5.22-1.75-.27-3.64-1.42-5.38-.83,.3,0,.37-.08,.23-.23l-.13,.21c2.64,3.86,6,7.38,8.85,11.14,.06,.07,.03,.23-.03,.31-.65,.34-1.95-.12-2.69-.21-9.85-2.56-19.59-5.36-29.18-8.48-1.07-.28-2.26-1.01-3.37-.7-.45,.2-.17,.57,.01,.82,2.68,3.8,5.86,7.51,8.21,11.43-.59,.42-1.21,.12-1.82-.07-8.63-2.73-17.29-5.38-25.71M -8.51-4.15-1.54-8.3-3.07-12.45-4.59-.46-.17-1.01-.57-1.45-.26-.66,.47,0,.98,.23,1.43,.35,.7,.83,1.35,1.26,2.02,1.9,2.96,3.95,5.85,5.69,8.9,.15,.26,.03,.62,.04,.93l.08-.07Z"/><path class="cls-2" d="M412.05,773.58c.69-.15,1.32,.03,1.95,.23,4.24,1.37,8.47,2.76,12.74,4.08,3.01,.93,6.06,1.77,9.11,2.62,.28,.08,.68-.1,1.22-.2-4.2-5.64-8.97-10.71-12.82-16.53-.03-.17,.3-.41,.47-.38,5.76,1.45,11.44,3.15,17.18,4.67,3.01,.51,5.56,2.01,2.29-1.95-3.4-4.26-6.83-8.52-10.23-12.78-.42-.53-1.01-1.03-.87-1.75l-.11,.05c.8-.33,1.58-.08,M 2.34,.09,4.14,.93,8.26,1.89,12.4,2.82,1.39,.16,2.89,.91,4.25,.46,0-.69-.55-1.19-.98-1.73-3.87-5.23-8.53-10.04-11.86-15.6,.64-.28,1.15-.17,1.67-.05,4.78,1.1,9.62,2,14.53,2.65,.26,0,.91-.02,.85-.41-.33-.58-.64-1.17-1.04-1.71-3.65-5.02-7.51-9.9-11.04-15-.49-.6,0-1.13,.7-1,5.01,.74,10.02,1.52,15.03,2.27l-.04-.02c4.11,5.3,8.22,10.61,12.33,15.92,3.7,3.88-12.92-.19-14.32,.59-.08,.7,.45,1.21,.89,1.75,3.62,4.41,7.24,8.81,10.86,13.22,.44,.69,1.32,1.14,.93,2.07-22.1-1.73-20.42-6.68-5.46,11.88,.6,.7,1.17,1.43,1.73,2.16,.05,.07M ,0,.22-.08,.31-.06,.08-.2,.17-.3,.16-1.46-.13-2.94-.21-4.37-.44-4.08-.67-8.19-1.27-12.2-2.2-2.34-.28-2.45-.08-1.05,1.78,3.21,3.72,6.44,7.43,9.66,11.15,.69,.8,1.34,1.61,1.99,2.42,.18,.3-.36,.64-.56,.66-6.61-.72-13.09-2.48-19.49-4.05-1.74-.55-1.94-.04-.88,1.33,3.99,4.73,8.05,9.41,12.02,14.15,.11,.13,.1,.46-.02,.55-.16,.12-.51,.19-.74,.14-7.9-1.77-15.66-3.78-23.37-6.14-.69-.16-1.35,.26-.7,.87,2.97,3.72,5.98,7.42,9,11.1,.19,.23,.13,.42-.14,.52-3.41-.48-6.89-1.8-10.25-2.71-6.26-1.78-12.38-4.51-18.67-5.91-.3,0-.35,.46-.0M 9,.84,2.69,3.93,6.24,7.58,8.59,11.6-.72,.46-1.48-.02-2.21-.22-10.08-3.32-19.94-7.03-29.69-10.93-.71-.24-1.42-.76-2.18-.39,1.76,4.04,5.19,7.75,7.59,11.62,.25,.36,.36,.78,.5,1.18,.02,.05-.19,.21-.28,.2-4.97-1.24-9.71-3.67-14.49-5.5-7.35-3.15-14.63-6.41-21.93-9.64-.81-.36-1.73-.62-2.22-1.33-.06,.07-.13,.13-.19,.2l.23-.18c-1.29,1.34,.69,2.85,1.19,4.14,1.84,3.23,3.89,6.37,5.62,9.66,.06,.17-.01,.46-.17,.57-15.64-5.66-30.38-14.19-45.4-21.41-.7,.57-.21,1.12,.03,1.77,1.82,3.71,3.67,7.41,5.48,11.12,.29,.59,.48,1.22,.68,1.84,M .02,.07-.12,.2-.22,.26-10.63-4.16-20.73-10.47-30.86-15.74-7.34-3.99-14.45-8.35-21.85-12.2-.37-.19-.68,.25-.68,.52,1.42,4.84,3.6,9.47,5.29,14.22,.09,.39,.39,.93,0,1.21-14.18-6.82-27.63-15.79-41.1-23.83-6.49-4.04-12.89-8.16-19.33-12.24-.63-.34-1.23-.98-2.01-.71,.62,5.55,3.27,11.33,4.06,17.03,0,.2-.43,.38-.6,.3-24.22-14.59-47.35-30.71-70.33-47.07-.62-.39-1.21-1.02-2.02-.79-.07,.01-.16,.18-.15,.27,.07,1.18,.09,2.36,.24,3.53,.53,3.96,1.09,7.92,1.67,11.88,.43,2.67,.43,3.05-.04,3.01-28.94-18.59-56.5-40.37-83.46-61.43-2.72M -2.16-2.34-1.7-2.36-4.49,.06-6.13-.27-12.3,.05-18.4,.98-.44,1.79,.66,2.55,1.14,22.36,18.63,44.81,36.76,68.34,54.15,3.16,2.35,6.31,4.7,9.47,7.04,.58,.32,2.42,2.01,2.78,.87-.31-5.93-1.49-11.77-2.26-17.66-.09-1.94,2.33,.25,2.95,.68,21.83,16.44,44.35,33.51,67.69,47.88,.63-.34,.25-1.21,.17-1.77-.9-3.37-1.82-6.74-2.72-10.1-.35-1.78-1.3-3.55-.93-5.37,.77-.14,1.25,.28,1.75,.62,3.89,2.66,7.77,5.34,11.68,7.98,15.32,10,30.67,20.89,46.92,29.51,.1-.04,.23-.18,.21-.25-.12-.63-.2-1.27-.42-1.88-1.33-3.62-2.69-7.22-4.04-10.83-.35-.M 93-.69-1.86-.98-2.8,0-.23,.37-.67,.71-.47,16.6,10.08,33.31,20.48,50.68,29.41,.21,.06,.83-.06,.8-.39-.12-.42-.23-.84-.42-1.23-1.81-3.83-3.63-7.65-5.44-11.48-.23-.5-.37-1.02-.52-1.54-.02-.08,.09-.21,.18-.28,.07-.05,.24-.09,.31-.06,.92,.43,1.87,.84,2.74,1.33,13.52,7.51,27.24,14.98,41.35,21.45,.15-.28,.38-.5,.31-.64-.44-.9-.92-1.79-1.42-2.67-1.98-3.53-3.98-7.06-5.95-10.61-.07-.13,.11-.38,.22-.55,.97-.06,1.92,.73,2.82,1.08,11.36,5.97,23.5,10.92,35.08,16.6,0,0,.03-.17,.03-.17l-.14,.12c1.09-.92-.15-2.02-.62-2.93-1.92-2.95M -3.87-5.9-5.79-8.85-.37-.57-.66-1.17-.98-1.76-.04-.07,.02-.25,.08-.26,.65-.3,1.21,.05,1.8,.3,6.04,2.58,12.06,5.21,18.14,7.73,19.83,7.84,13.67,6.14,4.72-7.9-.09-.13,.08-.38,.18-.56,.03-.05,.25-.08,.34-.05,8.29,3.08,16.47,6.3,25,8.93,.96,.18,2,.92,2.95,.44-3.33-5.41-8.04-10.41-11.84-15.66-.29-.38-.48-.76-.32-1.21l-.09,.08Z"/><path class="cls-2" d="M496.99,948.69c2.65,3.91,5.62,7.63,7.98,11.73l.16-.1c-16.27,1.16-32.58,.19-48.83,.15-.16,.03-.38,.36-.33,.5,1.61,4.03,4.46,7.53,6.03,11.59-.12,.86-1.71,.5-2.36,.59-9.01-.32M -18.03-.69-27.02-1.35-9.13-.57-18.19-1.83-27.28-2.49-.9,.1-.71,1-.47,1.59,1.85,4.27,3.71,8.53,5.57,12.8l.1-.09c-22.82-1.96-45.44-5.55-67.99-9.4-.91-.03-.8,.94-.64,1.54,1.32,4.28,2.8,8.51,3.81,12.87,.11,.43,.03,.85-.51,1.25-26.41-4-52.51-9.82-78.38-16.23-.63-.09-1.73-.5-2.11,.17,.15,1.28,.31,2.56,.55,3.83,.97,4.36,1.34,8.73,1.18,13.18l.13-.12c-32.19-7.52-63.78-16.33-95.01-26.26-1.3-.38-1.37,.86-1.3,1.75-.03,5.45,.62,11.06-.15,16.44-1.09,.81-2.92-.31-4.07-.55-37.23-11.25-73.91-24.1-110.08-38.08-.74-.32-1.24-.77-1.23-M 1.53,.03-1.72-.01-3.45-.01-5.17,.06-5.04-.17-10.12,.1-15.15,.94-.45,1.81,.16,2.69,.44,35.81,14.47,71.63,28.14,108.55,40.06,1.04,.12,3.77,1.84,3.98,.09-.62-5.9-1.28-11.8-1.91-17.7-.04-.41,.61-.82,1.07-.68,30.47,10.39,61.22,19.93,92.54,27.96,.66,.22,2.22,.6,2.23-.41-.33-1.7-.66-3.4-1.03-5.09-.07-1.54-3.45-11.73-1.51-11.46,25.1,6.65,50.32,12.95,75.9,17.83,.91,.18,1.85,.29,2.78,.42,1.07,0,.64-1.22,.47-1.87-1.43-4.26-2.88-8.52-4.32-12.78-.21-.61,.34-1.1,1.06-.97,21.34,4.25,42.79,8.17,64.43,10.75,1.67,.15,2.04-.15,1.52-1M .34-1.72-4.21-4-8.2-5.48-12.5,.51-.08,.91-.24,1.27-.2,5.85,.74,11.69,1.55,17.56,2.23,12.3,1.29,24.63,2.56,36.96,3.13,1.07,.08,1.31-.56,.89-1.27-1.93-3.32-3.9-6.62-5.75-9.97-1.4-2.48,4.33-1.06,5.55-1.22,14.22,1.21,28.53,1.3,42.81,1.15l-.09-.06Z"/><path class="cls-2" d="M1192.65,222.76c-18.63,.68-37.07,1.81-55.69,3.23-.13-1.59,1.21-2.37,1.98-3.58,3.41-4.39,6.83-8.78,10.23-13.18,.42-.55,.79-1.12,1.17-1.69,.14-.2-.35-.68-.67-.66-14.87,1.1-29.68,2.83-44.52,4.35-.67,.07-1.33,.2-1.99,.26-.74,.06-1.74,.54-2.16-.1-.39-.6,.4M 9-1.16,.95-1.67,4.63-5.16,9.29-10.31,13.93-15.48,.34-.56,2.1-1.97,1.18-2.36-14.92,1.03-29.73,4.04-44.61,5.64-.21-1.1,1.07-1.74,1.67-2.54,5.29-5.31,10.6-10.61,15.89-15.91,.64-.85,2.18-1.67,1.95-2.79-12.6,1.28-25.18,3.51-37.65,5.66-5.12,.95-3.25-.36-.68-2.87,6.27-5.92,12.56-11.82,18.83-17.74,.61-.57,1.16-1.18,1.72-1.79,.07-.07,.07-.25,0-.31-.15-.13-.39-.32-.55-.3-2.91,.43-5.82,.87-8.72,1.34-8.44,1.39-16.87,2.8-25.31,4.18-1.04,.17-2.1,.44-3.18,.13l.08,.08c0-.2-.12-.47,0-.6,.65-.68,1.34-1.35,2.06-1.99,7.95-7.04,15.9-14M .07,23.85-21.1,.63-.52,1.28-.97,1.34-1.83-11.34,1.1-22.76,3.34-34.07,5.03-1.55,.09-.59-.77,0-1.42,10.19-8.92,20.68-17.54,30.83-26.5,.76-1.36-2.35-.63-3.02-.65-6.91,.92-13.81,1.87-20.71,2.8-2.39,.32-4.78,.62-7.18,.9-.2,.02-.55-.11-.61-.24-.06-.92,1.47-1.59,2.04-2.25,10.58-8.76,21.16-17.51,31.74-26.27,3.65-2.97,5.33-3.99-.91-3.36-8.03,.68-16.07,1.37-24.11,1.98-.47,.03-.49-.52-.37-.7,4.02-3.52,8.29-6.77,12.42-10.17,9.79-7.86,19.6-15.72,29.4-23.58,2.63-2.11,2.11-1.87,5.62-1.87,7.75-.01,15.42,0,23.19,0,0,.4,.15,.79-.03,M .96-.77,.74-1.63,1.43-2.48,2.12-11.37,9.19-22.75,18.38-34.12,27.58-.94,.76-1.82,1.58-2.69,2.4-.07,.06,.13,.4,.3,.5,9.45-.07,19.03-1.5,28.52-1.75,.02,.22,.15,.49,.03,.62-.57,.6-1.17,1.18-1.82,1.72-9.14,7.62-18.3,15.23-27.44,22.85-1.68,1.4-3.32,2.82-4.95,4.26-.13,.12-.08,.4-.06,.59,.54,.26,1.35,.07,1.96,.07,6.26-.74,12.51-1.53,18.78-2.24,3.47-.39,6.95-.67,10.43-.98,.2-.02,.54,.11,.63,.25,.22,.84-1.13,1.46-1.61,2.06-3.83,3.33-7.67,6.66-11.49,9.99-5.01,4.37-10.01,8.74-15.01,13.11-.81,.56-1.27,1.54,.16,1.4,11.4-1.24,22.M 82-3.79,34.23-4.22,.5,.5-.93,1.43-1.29,1.85-5.96,5.42-11.93,10.84-17.87,16.27-1.86,1.7-3.66,3.45-5.46,5.19-.12,.12-.04,.39,.01,.58,.01,.06,.23,.1,.36,.11,10.38-.97,20.72-2.75,31.09-4.01,2.29-.17,4.84-1.05,7.06-.5,.07,.09,.14,.25,.09,.31-.46,.53-.92,1.06-1.43,1.56-5.77,5.69-11.56,11.37-17.33,17.06-.76,.75-1.5,1.52-2.2,2.31-.12,.13-.02,.4-.02,.64,9.74-.57,19.38-2.67,29.12-3.53,4.27-.46,8.54-.91,12.82-1.34,.17-.02,.4,.18,.55,.31,.06,.06,.05,.23-.01,.31-.51,.63-1,1.27-1.56,1.88-4.65,5.02-9.31,10.03-13.96,15.06-.72,.77-M 1.36,1.59-1.99,2.41-.06,.08,.2,.47,.31,.47,8.31-.17,16.53-1.84,24.83-2.38,6.96-.63,13.92-1.24,20.89-1.86,.56-.05,1,.13,.95,.37-.19,1.24-1.38,2.07-2.06,3.08-3.71,4.62-7.42,9.25-11.12,13.88-.72,1.03-2.31,2.58,.14,2.4,16.89-1.22,33.83-2.68,50.76-2.94,.54,.25,.21,1-.08,1.39-3.81,5.94-7.63,11.88-11.44,17.81l.1-.06Z"/><path class="cls-2" d="M1026.04,428.3s-.02,.07-.02,.11c-.04,0-.07,0-.11,0l.13-.1Z"/><path class="cls-2" d="M1030.71,456.09c-19.64-1.37-39.33-2.94-59.04-2.45-.03-1.64-.57-3.21-.92-4.81,18.37-5.18,40.16-4.06,M 58.09,2.12h.01c.58,1.72,1.26,3.42,1.86,5.14Z"/><path class="cls-2" d="M1030.71,456.09c.05,0,.09,0,.14,0l-.1,.1s-.03-.07-.04-.11Z"/><path class="cls-2" d="M1093.95,419.27v.1s-.09-.01-.13-.01l.13-.09Z"/><path class="cls-2" d="M1095.46,449.73s-.01-.07-.02-.1c.05,0,.09,.01,.14,.01l-.12,.09Z"/><path class="cls-2" d="M1271.78,456.81v-.08s.09,.02,.13,.03l-.13,.05Z"/><path class="cls-2" d="M1387.25,454.02c.01,6.14,0,12.28-.01,18.42-.04,.72-.01,1.88-1.09,1.7-12.02-4.01-23.89-8.43-35.96-12.41-24.56-8.24-49.41-16.11-74.6-22.9M 6-1.93-.47-1.55,2.12-1.95,3.28-.66,4.89-1.72,9.74-1.86,14.68-30.67-8.72-61.63-16.99-92.95-23.54-2.59-.34-3.87-1.33-3.79,2.11-.07,4.41,.28,8.83-.09,13.23-.41,.81-1.75,.42-2.5,.33-3.11-.68-6.22-1.39-9.33-2.08-22.25-4.84-44.76-8.94-67.37-11.92-.86-.07-1.31,.62-1.23,1.33,.22,4.49,.13,8.98,.92,13.44-15.82-1.99-31.63-4.41-47.56-5.77l7.1-13.46c12.74,1,25.41,2.54,38.08,4,.71,.07,1.23-.35,1.22-.98-.11-4.69-.22-9.37-.33-14.05,26.91,2.93,53.69,7.53,80.21,12.79,1.05,.06,1.15-.94,1.41-1.68,1.1-4.11,2.18-8.21,3.28-12.32,.41-1.5,M .85-1.7,2.84-1.35,1.31,.23,2.62,.48,3.93,.74,29.51,5.65,58.59,12.68,87.56,20.46,.34,.08,.92-.14,.97-.39,.26-1.05,.56-2.1,.72-3.16,.66-4.17,1.27-8.34,1.92-12.51,.22-.65,.22-1.81,1.11-1.88,36.82,9.22,73.52,20,109.19,32.58,.06,.52,.16,.94,.16,1.37Z"/><path class="cls-2" d="M138.69,233.83c.3-.5,.32-1.03,.29-1.58-.25-3.87-.51-7.74-.75-11.61-.36-5.91-.71-11.82-1.05-17.74-.24-3.14,1.52-1.37,3.05-.48,7.52,5.08,14.75,11.03,22.51,15.56,.26-.19,.61-.39,.55-.75-.37-12.24-1.26-24.55-1.11-36.77,.11-.44,.97-.37,1.34-.12,7.72,4.07M ,15.13,8.76,22.97,12.57,1.12,.11,.73-1.74,.87-2.47-.04-5.27-.14-10.55-.15-15.82,.07-8.38-.17-16.78,.16-25.15,1.09-.4,2.07,.23,3.1,.52,4.37,1.67,8.73,3.36,13.08,5.05,.85,.33,1.67,.71,2.52,1.03,5.07,1.93,6.02,2.2,6.25,1.78,.89-1.63,.48-3.38,.56-5.07,.44-14.84,.97-29.72,2.1-44.51,.05-.25,.55-.59,.87-.55,1.06,.13,2.13,.22,3.17,.42,7.14,1.47,14.38,2.6,21.46,4.31,.45,1.12,.19,2.14,.15,3.29-.45,6.34-.95,12.68-1.36,19.02-.99,11.01-.68,22.67-2.28,33.5h0c-.18-.27-.28-.67-.56-.78-2.29-.92-4.59-1.8-6.92-2.66-5.42-1.95-10.74-4.M 03-16.21-5.85-.94,.94-.66,2.25-.74,3.47-.21,14.53-.15,29.08-.38,43.61-.01,.25-.62,.56-.88,.44-.82-.37-1.66-.71-2.43-1.13-6.13-3.33-12.24-6.68-18.36-10.01-.77-.24-2.41-1.72-2.98-.63,.34,11.51,.46,23.04,1.16,34.54,.14,2.03,.06,4.08,.05,6.12,0,.1-.46,.33-.58,.29-8.07-4.81-15.41-10.88-23.39-15.85-1.33-.42-1.01,1.02-1.08,1.84,.23,3.98,.4,7.96,.71,11.94,.47,7.1,.93,14.19,1.37,21.29,.02,.29-.18,.59-.32,.87-.03,.07-.3,.14-.36,.11-.53-.33-1.07-.65-1.53-1.03-5.65-4.62-11.27-9.26-16.93-13.88-2.07-1.69-3.96-3.52-6.32-4.98-.12-M .07-.56,.03-.69,.15-.39,.95-.04,2.17-.07,3.2,.67,9.14,1.36,18.27,2.19,27.4-.11,2.2-2.12-.11-2.96-.83-7.97-7.3-15.89-14.65-23.84-21.96-.44-.61-1.61-.58-1.48,.35,.41,7.75,1.2,15.47,1.75,23.21,.08,1.07,.07,2.15,.1,3.22,0,.28-.16,.42-.49,.4-9.66-8.58-18.42-18.56-27.77-27.62-.63-.52-1.12-1.44-2.07-1.25-.07,0-.19,.14-.19,.22,0,.86-.01,1.72,.04,2.57,.33,6.88,.96,13.76,1.15,20.65-.28,1.05-1.56-.24-1.95-.65-9.92-10.61-19.83-21.22-29.74-31.84-.88-.88-1.84-1.88-1.74-3.17,0-2.48-.06-4.95-.08-7.43-.02-3.45-.02-6.89,0-10.34-.11-M 3.62,1.65-1.62,3.14-.14,9.35,9.17,18.37,18.67,27.9,27.65,.83,.57,1.09-.56,1.04-1.18-.1-2.48-.22-4.95-.33-7.43-.2-4.52-.4-9.04-.59-13.56,.03-.63-.15-1.41,.58-1.7,.07-.04,.27-.03,.34,.03,9.46,7.98,18.09,16.87,27.44,24.99,.11,.1,.47,.04,.7,.01,.32-.23,.25-.84,.28-1.2-.36-8.92-1.46-17.85-1.56-26.76,.96-.44,1.57,.42,2.29,.88,7.63,6.24,15.24,12.49,22.86,18.73,.69,.48,1.3,1.28,2.24,1.14l.04,.13-.13-.06Z"/><path class="cls-2" d="M1203.01,1271.97c5.12,1.91,10.24,3.83,15.37,5.73,2.69,1,5.39,1.97,8.08,2.95,.92,.34,1.49,.02,1.M 51-.87,.38-14.54,.29-29.08,.32-43.63-.14-3.81,.66-2.85,3.38-1.57,6.35,3.45,12.69,6.91,19.03,10.38,.65,.31,1.27,1.04,2.1,.6,.74-.39,.38-1.18,.38-1.79-.05-6.14-.45-12.28-.63-18.41-.01-6.89-.7-13.78-.74-20.66,.05-.33,.74-.35,.93-.28,7.61,4.89,14.89,10.28,22.39,15.35,.39,.27,.75,.62,1.34,.58,.38,0,.53-.46,.54-.75-.25-4.63-.5-9.25-.79-13.88-.41-6.56-.85-13.12-1.27-19.69,.08-.57-.29-1.63,.54-1.7,.92,.14,1.67,1.05,2.44,1.54,5.18,4.24,10.34,8.49,15.51,12.74,2.26,1.85,4.52,3.69,6.81,5.52,.12,.1,.48,.03,.71,0,.15-.08,.25-.4,M .25-.58-.22-3.55-.43-7.1-.67-10.65-.58-6.44-1.05-12.9-1.56-19.35-.08-1.84,1.07-1.02,1.94-.22,8.51,7.79,16.9,15.68,25.5,23.37,.13,.11,.5,.07,.76,.06,.1-.06,.22-.43,.19-.59-.61-7.96-1.32-15.91-1.94-23.86-.14-2.75-.61-4.83,2.37-1.76,9.28,8.95,17.93,18.94,27.55,27.35,.2-.11,.5-.27,.5-.4-.09-3.12-.21-6.24-.35-9.36-.2-4.52-.42-9.04-.6-13.56,0-.14,.31-.3,.5-.41,10.57,10.18,20.34,21.73,30.61,32.4,1.16,1.01,1.81,2.3,1.6,3.85,0,5.82,0,11.64,0,17.45,0,.52,.11,1.07-.33,1.53-.07,.07-.31,.15-.36,.11-.5-.34-1.04-.66-1.44-1.06-3.5M 7-3.51-7.14-7.02-10.68-10.55-5.47-5.47-10.91-10.95-16.38-16.43-.69-.54-1.17-1.4-2.19-1.07,.11,7.85,.73,15.7,.98,23.55,.01,.25-.16,.4-.49,.43-1.71-.43-2.84-2.26-4.23-3.3-7.49-6.93-14.97-13.87-22.45-20.8-.6-.43-1.62-1.97-2.31-1.02,.09,9.14,1.32,18.27,1.5,27.42-.32,1.27-1.67,.03-2.22-.44-7.43-6.1-14.86-12.19-22.29-18.29-2.48-2.03-3.41-2.72-3.04,1.24,.44,9.81,1.89,19.93,1.42,29.61-.93,.26-1.61-.55-2.34-.96-7.27-5.15-14.51-10.32-21.82-15.4-.27-.19-.69-.25-1.05-.35-.1-.02-.33,.06-.34,.11-.1,.42-.22,.84-.21,1.27,.3,10.23,M .74,20.46,1.09,30.69,.06,1.72,.03,3.44,.03,5.15,0,.24-.67,.53-.92,.42-.24-.1-.49-.18-.71-.3-7.01-3.81-13.94-7.74-20.91-11.62-3.25-1.94-2.59-.21-2.72,2.46,.07,13.38,.42,26.75-.04,40.12-2.37,.15-4.46-1.37-6.7-2.01-5.1-1.95-10.2-3.91-15.3-5.86-.9-.17-2.55-1.37-3.11-.22-1.19,16.54-.63,33.3-2.63,49.75-8.64-.64-17.03-3.36-25.61-4.56l.08,.08c.79-18.57,2.79-37.09,3.24-55.69l-.14,.06Z"/><path class="cls-2" d="M1011.12,826.86c-3.33-8.9-6.11-18.19-10.29-26.77-1.32-.23-13.44-2.43-12.91-.58,3.19,8.92,6.91,17.61,9.72,26.64,.12,.M 41-.18,.86-.69,1.04-3.86,1.24-7.44,3.16-11.18,4.46-.82,0-.95-.88-1.2-1.47-1.87-5.29-3.7-10.58-5.61-15.85-1.05-2.89-2.24-5.75-3.37-8.63-.49-.89-1.7-.33-2.36,.08-2.88,1.77-5.73,3.58-8.6,5.36-.3,.19-.82,.05-.97-.25-3.15-6.97-5.76-14.15-9.09-21.06-.22-.47-.39-1.01-1.22-1.31-2.48,1.44-4.5,3.64-6.75,5.41-.87,.47-2.22,2.7-3.19,1.83-3.43-6.25-6.23-12.87-9.8-19.02-1.61,0-1.99,1.48-3.02,2.36,1.81,8.63,3.13,17.62,3.85,26.45,1.79-.46,8.22-9.58,9.58-7.87,3.25,6.67,5.73,13.66,8.51,20.53,.17,.42,.43,.76,1.15,.94,2.8-2.1,5.72-4.2,M 8.56-6.26,.41-.31,1.3-.72,1.75-.35,3.24,7.33,5.28,15.13,8.05,22.65,.28,.83,.62,1.64,.99,2.45,.05,.12,.5,.24,.68,.18,3.39-1.49,6.61-3.32,9.93-4.94,.46-.24,.95-.39,1.62-.26,3.16,9.87,6.47,19.93,8.39,30.07,4.53-1.53,9.18-2.78,13.64-4.47-2.47-9.84-5.72-19.46-8.63-29.18-.22-.71-.48-1.81,.65-1.82,3.86,.23,7.6,1.39,11.45,1.85,1.17-.11,.51-1.5,.36-2.21Zm-3.83,31.36s.01,.03,.01,.04l.1-.1s-.07,.04-.11,.06Zm-6.49-58.18s.02,.03,.03,.05c.02,0,.05,0,.07,0l-.1-.06Zm-7.28,62.69l.13,.05v-.09s-.09,.03-.13,.04Zm-109.4-96.61c-1.19-1.3M 8-1.95-3.43-3.68-4.19-.49-.1-.69,.27-.82,.56-1.37,2.93-2.71,5.86-4.07,8.79-.32,.6-.81,1.9-1.66,1.15-2.61-3.12-5.06-6.37-7.68-9.49-.53-.6-.95-.82-1.21-.61-.27,.22-.57,.46-.68,.74-1.41,3.47-2.5,7.08-4.09,10.47-.79,.87-1.61-.7-2.18-1.16-1.96-2.2-3.9-4.39-5.85-6.59-.39-.43-.77-.89-1.6-1.08-1.07,1.28-1.25,3-1.81,4.53-.85,2.6-1.72,5.19-2.56,7.73-.77,.08-1.17-.17-1.51-.53-2.34-2.39-4.56-4.86-7.12-7.03-1.17-.54-1.31,1.33-1.65,2.05-.89,3.04-1.74,6.08-2.64,9.12-.17,.6-.26,1.26-1.02,1.65-.74-.11-1.09-.6-1.53-1-1.69-1.53-3.38-M 3.07-5.08-4.6-.58-.61-2.01-1.54-2.42-.42-1.13,4.21-2.37,8.4-3.6,12.59-.14,.48-.73,.66-1.23,.37-2.82-1.41-5.02-3.44-8.12-4.34-.51,.46-.68,1.08-.86,1.69-1.15,4.13-2.33,8.43-3.66,12.47-.74,.2-1.21,0-1.66-.23-2.63-1.27-4.98-3-7.86-3.75-1.44,4.64-2.88,9.27-4.33,13.91-.26,.81-.95,1.05-1.79,.67-1.99-.9-3.96-1.82-5.95-2.71-.52-.22-1.34-.54-1.81-.09-2.28,4.51-3.23,9.6-5.49,14.12-.14,.27-.63,.39-1.01,.23-2.15-.89-4.29-1.78-6.47-2.62-1.61-.62-1.88-.51-2.52,.98-1.98,4.48-3.46,9.13-5.83,13.43-3.12-.9-5.84-2.32-8.99-3.11-2.88,4.M 29-4.71,9.19-7.18,13.73-.15,.31-.15,.6,.26,.81-3.66,.06-6.84-2.39-10.42-2.95-.01,.01-.02,.03-.02,.04-2.99,5.02-6.88,9.59-10.66,14.31-3.27-1.26-6.38-2.22-9.27-3.51,0-.88,.73-1.4,1.2-2.01,3-4.05,6.41-7.84,9.13-12.08-.02,0-.04,0-.06-.02-3.27-.81-6.47-1.77-9.78-2.73,.33-1.85,1.53-3.28,2.28-4.84,1.52-3.03,3-6.13,4.37-9.23-2.6-.53-5.2-1.07-7.8-1.59-1.13-.21-2.99-.87-3.5,.43-2.04,4.05-3.94,8.24-6.26,12.12-.43,.06-.72,.17-.95,.12-3.25-.64-6.48-1.36-9.56-2.29-.05-.2-.13-.32-.09-.4,1.86-4.37,4.24-8.6,6.3-12.9-3.22-.7-6.46-1.M 39-9.68-2.1-1.78-.45-.5-2.01-.19-3.06,1.44-3.44,2.51-7.05,4.23-10.36-3.53-.61-7.06-1.23-10.59-1.84-.79-.14-1.32,.1-1.56,.69-1.1,2.75-2.19,5.51-3.3,8.27-.69,1.14-.77,3.37-2.48,3.34-3.55-.62-7.09-1.32-10.51-2.47,1.36-4.27,3.91-8.16,4.94-12.52-.02,0-.04-.01-.06-.01-3.46-.75-6.92-1.48-10.37-2.24-.73-.16-1.06-.69-.87-1.24,1.15-3.52,2.29-7.03,3.47-10.53,.1-.3,.4-.55,.6-.82-2.47-.86-5.11-1.28-7.68-1.88-4.62-1.07-4.24-1.51-5.61,2.43-.87,2.48-1.86,4.94-2.84,7.38-.37,1.01-.13,1.44,1.02,1.74,2.68,.68,5.38,1.34,8.06,2.03,.69,.M 3,2,.29,2.15,1.17-1.12,3.95-3.35,7.46-4.87,11.31,3.41,1.75,7.63,1.95,11.15,3.31,.22,.65-.03,1.14-.3,1.64-1.38,2.55-2.77,5.11-4.15,7.67-.25,.87-1.79,2.19-.7,2.9,3.58,1.23,7.34,1.93,10.98,2.95,2.02-3.71,4.25-7.36,5.93-11.18,.47-1.06,1.01-1.23,2.51-.93,3.19,.64,6.23,1.15,9.39,2.09-1.59,4.19-3.94,8-5.82,12.07-.18,.39,.12,.95,.58,1.07,2.98,.76,6.17,1.54,9.07,2.28,.34,.71-.02,1.17-.36,1.64-2.54,3.88-6.14,7.07-8.77,10.91,2.94,1.37,6.22,1.91,9.32,2.88,1.81,.65-1.13,2.57-1.63,3.39-2.81,2.88-5.65,5.74-8.46,8.62-.69,.7-.58,1.M 16,.36,1.5,3.04,.92,6.02,2.61,9.14,3.06,3.94-4.08,7.98-8.08,11.58-12.37,.19-.23,.61-.35,.95-.54,3.04,.97,6.1,1.8,8.89,2.94,.28,.53,.13,.92-.19,1.29-3.64,4.19-7.2,8.35-11.04,12.39,.26,.29,.42,.64,.73,.77,2.76,1.23,5.51,2.16,8.18,3.65-4.27,5.03-9.61,9-14.2,13.67,1.74,1.42,5.26,3.34,8.63,4.74,.72-.12,1.08-.61,1.52-1,4.6-4.08,8.91-8.34,12.84-12.79-.14-.53-.52-.81-1-1.04-2.25-1.17-4.69-2.08-6.81-3.45-.62-.67,.75-1.6,1.1-2.21,3.33-3.78,6.72-7.53,10-11.36,.48-.53,1.06-.69,1.73-.46,2.74,1.11,5.8,1.83,8.06,3.68-3.79,4.74-7.M 97,9.2-11.96,13.77-.32,.36-.21,.89,.24,1.14,2.34,1.27,4.68,2.54,7.01,3.81,.86,.56,1.61-.39,2.14-.95,3.98-4.54,7.87-9.05,11.86-13.58,2.97,1.17,5.26,3.05,8.15,4.41,4.1-4.81,7.36-10.26,11.2-15.27,2.19,.51,3.49,1.95,5.37,2.93,.86,.48,1.47,1.29,2.68,1.32,.8-.49,1.06-1.23,1.43-1.91,2.12-3.95,4.24-7.91,6.34-11.87,.27-.5,.45-1.02,1.09-1.32,2.5,.7,4.66,3,6.93,4.29,.31,.21,.82,.12,1.02-.16,2.67-4.74,4.77-9.85,7.21-14.72,.09-.18,0-.42,0-.83-2.25-1.47-4.64-3.02-7.24-4.36-.42-.21-1.14,0-1.34,.4-2.25,4.58-4.05,9.4-6.42,13.92-.24M ,.41-.91,.6-1.34,.37-2.01-1.09-4.01-2.18-6.01-3.27-.46-.25-.93-.42-1.64-.29-2.62,4.86-4.71,9.99-7.9,14.68-.39,0-.72,.08-.91,0-2.41-1.18-4.8-2.38-7.19-3.58-.45-.23-.51-.62-.22-1.16,2.36-4.46,4.72-8.92,7.08-13.38,.21-.56,.93-.86,1.58-.61,2.58,.91,4.97,2.63,7.65,3.12,2.76-4.45,4.17-9.73,6.61-14.38,.13-.25,.74-.47,1.01-.35,2.61,1.13,5.14,2.27,7.68,3.58,.72-.5,1-1.08,1.23-1.69,1.69-4.38,3.14-8.91,5.02-13.19,.72-.15,1.18,.08,1.61,.31,2.26,1.16,4.37,2.59,6.71,3.58,.16,.05,.59-.08,.65-.21,2.08-4.37,3.2-9.1,4.81-13.65,.2-.6M ,.92-.81,1.57-.43,2.39,1.37,4.7,2.89,7.11,4.23,.15,.08,.62-.01,.67-.11,2.05-4.39,2.96-9.14,4.55-13.78,.43,.04,.94-.04,1.12,.12,1.91,1.67,3.75,3.39,5.62,5.08,.89,.8,1.99,2.05,2.6,.22,1.42-4.01,2.2-8.3,4-12.14,.66-.48,1.36,.35,1.81,.75,1.8,1.88,3.57,3.78,5.36,5.67,.4,.42,.72,.92,1.65,.99,1.85-4.11,2.83-8.45,4.44-12.6,.66-.21,1.08,0,1.4,.37,2.39,2.72,4.53,5.66,7.1,8.22,.12,.11,.48,.06,.81,.08,6.56-16.32,2.73-14.54,13.45-1.68,.71-.18,1.01-.5,1.19-.93,1.16-2.75,2.32-5.5,3.5-8.25,.43-.65,.81-2.51,1.81-2.09,3.32,3.49,5.27M ,8.08,8.47,11.68,.09,.08,.59,.06,.65-.03,1.53-2.25,2.57-4.76,3.86-7.14-1.14-4.38-2.45-8.68-3.91-12.9Zm-169.83,69.94c-3.01,4.09-6.27,8.02-9.38,12.04-.42,.53-1,.68-1.74,.45-2.87-.9-5.83-1.64-8.93-2.84,2.84-3.9,5.77-7.42,8.7-11.21,.6-.71,1.12-1.79,2.26-1.51,2.99,.62,5.96,1.29,8.83,2.23,.32,.1,.45,.53,.26,.84Zm38.34,13.19c-2.98,4.69-6.25,9.25-9.65,13.75-.38,.51-1.07,.64-1.72,.33-2.3-1.09-4.6-2.2-6.9-3.31-.42-.2-.52-.75-.22-1.14,1.53-2.02,3.11-4.01,4.58-6.05,2.3-2.75,3.57-6.27,6.44-8.46-.84,1.41,8.65,3.15,7.47,4.88Zm43.M 54-54.26s.07,.01,.1,.02c.02-.05,.03-.1,.05-.15l-.15,.13Zm-104,67l-.03,.03s.07-.02,.09-.03h.01s-.05-.01-.07,0Zm-21.26-37.4s-.03,.05-.04,.08l.09-.07s-.03,0-.05,0Z"/><path class="cls-2" d="M169.9,1258.03c.04-.86,0-1.73,.46-2.5,3.02-5.89,5.45-12.19,8.82-17.86l-.09,.06c17-.83,34.21-.58,51.28-1.29,.9,.2,5.82-.82,4.89,.97-3.54,5.45-7.16,10.86-10.72,16.3-.34,.7-1.44,1.78-.22,2.19,12.9-.1,25.8-1.36,38.69-2.1,3.21-.1,6.44-.78,9.63-.49,.94,.41-.76,1.87-1.06,2.44-4.48,5.64-9.16,11.14-13.54,16.85-.18,.24,.14,.73,.47,.72,13.96-.M 55,27.84-2.36,41.73-3.78,3.62-.41,.91,1.49-.15,2.89-5.18,5.51-10.39,11.01-15.57,16.52-.27,.45-2,2-.84,2.1,13.28-.94,26.49-3,39.7-4.09-.25,1.41-1.68,2.15-2.58,3.19-6.58,6.42-13.26,12.74-19.78,19.22-.54,.65,.15,1,.81,.88,11.63-.97,23.17-2.82,34.79-3.91,1.38,.21-1.43,2.26-1.8,2.7-7.61,6.84-15.23,13.68-22.84,20.52-.62,.56-1.18,1.17-1.75,1.76-.07,.07-.08,.25-.01,.3,.16,.13,.38,.32,.56,.31,1.74-.15,3.48-.33,5.21-.5,7.09-.69,14.18-1.37,21.26-2.06,3.26-.26,8.77-2.01,3.16,2.39-9.18,7.88-18.44,15.71-27.6,23.62-.51,.44-1.5,.8M 4-1.04,1.57,.32,.5,1.21,.26,1.84,.22,8.99-.41,17.98-1.6,26.97-1.65,.49,.38-.15,1-.53,1.29-12.28,10.02-24.38,20.24-36.77,30.14-8.15,.4-16.39,.05-24.56,.17-.57-.03-2.05,.11-2.13-.5,.21-1.12,1.58-1.68,2.33-2.51,6.37-5.41,12.76-10.82,19.13-16.23,3.6-3.06,7.2-6.12,10.8-9.18,.38-.32,.7-.65,.51-1.14-9.47,0-19.05,1.28-28.56,1.52-.68-.05-1.18-.25-.5-1.06,8.36-7.64,16.89-15.1,25.3-22.67,.47-.62,3.8-2.76,1.98-3.08-10.72,.88-21.39,2.15-32.14,2.66-.12,0-.33-.05-.35-.11-.06-.19-.16-.46-.05-.59,.54-.62,1.11-1.21,1.72-1.79,6.49-6.M 19,12.99-12.38,19.49-18.57,.69-.87,4.11-3.08,1.2-3.09-7.37,.49-14.72,1.37-22.08,2.01-4.42,.19-9.37,1.43-13.69,.97,.42-1.65,2.16-2.66,3.2-4,4.95-5.24,9.92-10.48,14.86-15.73,.56-.81,1.76-1.43,1.61-2.49-13.51,.92-27.03,2.62-40.6,3.21-1.14-.24-.4-.97,0-1.5,5.07-6.23,10.44-12.25,15.35-18.61,.19-.26-.12-.74-.47-.73-5.65,.04-11.26,.76-16.9,1.09-9.27,.53-18.54,1.17-27.83,1.48-.73,.02-1.09-.55-.72-1.14,.85-1.34,1.71-2.69,2.6-4.02,2.48-3.7,4.97-7.4,7.45-11.1,1.02-1.9,3.85-4.25-.37-3.88-12.26,.38-24.51,.86-36.77,1.01-3.77,.04M -7.55,.15-11.32,.24-.67,.01-1.35,.02-1.89,.42l.03,.02Z"/><path class="cls-2" d="M1262.17,202.07c-11.54,.6-23.17,.35-34.74,.71-6.06,.12-12.12,.37-18.18,.55-1.07,.03-2.15-.02-3.22-.09-.14,0-.4-.37-.34-.49,3.56-6.33,8.13-12.09,11.78-18.37,.14-.25-.22-.72-.54-.72-13.44,.4-26.87,1.48-40.3,2.34-2.68,.18-5.35,.55-8.05,.54-1.51-.28,.52-1.96,.86-2.62,4.23-5.25,8.47-10.5,12.7-15.75,.36-.44,.64-.93,.88-1.42,.05-.1-.24-.32-.42-.46-14.42,.88-28.9,2.52-43.31,3.87-1.14-.09,.65-1.68,.89-2.09,5.17-5.52,10.36-11.02,15.53-16.54,.72-.M 77,1.37-1.59,2.01-2.4,.06-.08-.14-.39-.31-.47-12.9,.93-25.93,2.54-38.79,4.18-2.48,.32-.45-1.45,.35-2.24,6.97-6.86,14.14-13.52,20.99-20.5,.21-.28-.31-.66-.5-.68-11.08,1.15-22.14,2.48-33.2,3.8-.86,.1-1.74,.64-2.6-.02,.03-.87,.93-1.28,1.53-1.82,7.87-7.09,15.76-14.17,23.63-21.26,.62-.56,1.15-1.18,1.7-1.78,.06-.06,0-.22-.06-.31-.61-.38-1.56-.12-2.27-.15-8.29,.82-16.57,1.64-24.86,2.48-2.89,.08-8.69,2.08-3.27-2.17,9.61-8.29,19.4-16.41,28.87-24.87,.11-.1,.01-.38-.04-.57-.26-.21-.77-.17-1.11-.19-8.6,.37-17.19,1.18-25.78,1.7M 1-.64,.04-1.3-.05-1.95-.1-.05,0-.12-.21-.09-.3,11.83-10.78,24.86-20.68,37.25-30.96,8.2-.26,16.42-.04,24.63-.11,.73,.06,1.64-.18,2.12,.49,.05,.06,.02,.22-.04,.28-.59,.58-1.15,1.18-1.79,1.73-4.05,3.46-8.12,6.91-12.19,10.36-5.64,4.78-11.28,9.57-16.9,14.36-.85,.74-2.92,2.37-.41,2.23,6.59-.37,13.17-.75,19.76-1.13,2.67-.05,5.38-.61,8.04-.38,1,.42-.97,1.78-1.35,2.28-8.73,7.93-17.69,15.62-26.28,23.69-.22,.3,.36,.64,.54,.66,10.88-.68,21.73-2.31,32.61-2.61-.12,.35-.11,.71-.33,.94-1.16,1.19-2.37,2.34-3.58,3.5-5.97,5.7-11.96,1M 1.39-17.92,17.09-.69,.66-1.33,1.35-1.95,2.05-.1,.12,.05,.38,.11,.65,11.24-.67,22.45-2.23,33.69-3.05,5.43-.64,2.21,1.41,.31,3.69-5.52,5.98-11.34,11.72-16.68,17.86-.07,.31,.06,.74,.54,.68,11.79-.91,23.55-2.23,35.36-2.98,3.9-.09,7.65-1.77,3.09,3.19-4.02,4.85-8.05,9.69-12.07,14.54-.59,.72-1.16,1.45-1.68,2.2-.11,.15,.02,.41,.04,.66,14.86-.42,29.77-2.23,44.69-2.53,1.38-.04,1.73,.37,1.13,1.33-.9,1.44-1.82,2.88-2.77,4.31-2.98,4.59-6.21,9.03-9.03,13.72-.22,1.06,1.45,.71,2.09,.79,4.04-.14,8.08-.3,12.12-.43,12.93-.35,25.86-.6M 6,38.8-.82l-.12-.12c-3.15,6.75-6.32,13.48-9.72,20.12l.09-.06Z"/><path class="cls-2" d="M169.87,1258.01c-.57,.12-.87,.44-1.07,.86-1.78,3.72-3.56,7.44-5.34,11.16-1.06,2.21-2.12,4.42-3.17,6.64-.24,.45-.45,1.2,.21,1.37,15.47,.24,30.95-.88,46.42-1.35,2.19-.04,1.81,.42,.93,2.01-2.94,4.36-5.91,8.71-8.85,13.06-1.09,1.61-2.13,3.24-3.18,4.87-.25,.39,.2,.86,.8,.84,13.73-.31,27.41-1.57,41.12-2.25,.33-.01,.77,.47,.62,.67-.47,.65-.93,1.31-1.45,1.93-4.74,5.76-9.5,11.51-14.24,17.26-.41,.62-1.42,1.48-.14,1.81,2.82-.16,5.65-.29,8.47M -.48,9.39-.62,18.78-1.31,28.17-2.03,.23,0,.73,.34,.6,.63-6.54,7.57-14.04,14.37-20.5,22.01-.04,.67,1,.61,1.48,.59,8.32-.59,16.64-1.18,24.96-1.78,1.28,.12,7.2-1.26,7.05,.15-5.52,5.92-11.73,11.23-17.5,16.92-9.71,9.4-9.82,7.73,3.25,7.36,6.05-.29,12.1-.62,18.15-.93,1.57-.09,1.12,.86,.19,1.63-8.82,7.85-17.63,15.72-26.43,23.59-1.14,.87-2.09,2.19-3.56,2.51-8.07,.19-16.17,.02-24.25,.07-.58-.04-1.89,.08-1.9-.69,8.02-8.61,17.05-16.34,25.27-24.77,.11-.11,.01-.39-.04-.58-.26-.23-.78-.18-1.12-.22-9.28,.45-18.57,.85-27.86,1-.2,0-M .49-.18-.58-.33-.09-.16-.08-.45,.04-.59,2.39-2.61,4.77-5.21,7.21-7.79,4.14-4.38,8.32-8.74,12.48-13.11,.56-.59,2.23-2.01,.46-2.14-11.03,.28-22.03,1.46-33.05,1.7-.77-.33,0-1.15,.29-1.61,1.82-2.26,3.66-4.52,5.51-6.77,3.41-4.14,6.82-8.27,10.23-12.41,.36-.44,.83-.87,.43-1.54-11.63,.14-23.33,1.38-34.98,1.77-.87-.11-4.49,.68-3.72-.93,4.24-6.63,8.93-12.99,13.09-19.66,.02-.8-1.28-.71-1.86-.71-3.23,.11-6.46,.22-9.69,.34-11.17,.49-22.34,.94-33.52,.98l.14,.11c2.93-6.11,5.86-12.22,8.79-18.33,.32-.76,1.36-2.24-.03-2.48-11.14-.25M -22.28,0-33.43-.09-5.36-.12-10.75,.1-16.08-.39-1.05-.29-.43-1.57-.34-2.32,1.42-5.46,2.85-10.92,4.27-16.38,.16-.61,.46-1.26-.21-1.82l-.06,.02c1.12-.49,2.34-.42,3.55-.4,4.98,.08,9.96,.11,14.93,.25,13.01,.71,26.16-.26,39.1,.77,0,0-.03-.02-.03-.02Z"/><path class="cls-2" d="M555.12,270.11c-7,1.83-13.79,4.34-20.78,6.2-.32,.09-.82-.29-.75-.56,6.68-20.92,14.95-41.42,23.13-61.84,.13-.81,1.53-2.6,.09-2.8-7.13,.88-14.05,3.09-21.18,4-1.41-.19-.12-2,0-2.82,8.89-23.82,18.88-47.2,29.24-70.46,.19-.82,1.38-2.28-.05-2.46-7.65,.34-15M .2,1.79-22.85,2.16-2,0-.21-2.24,0-3.22,12.04-28.51,24.92-56.77,38.73-84.5,.33-.12,.57-.28,.82-.29,8.7,.03,17.46-.23,26.14,.01,.34,.53,.27,.95,.06,1.35-.86,1.7-1.71,3.4-2.6,5.08-13.61,25.67-26.43,51.46-38.34,77.78-.48,1.68,2.4,.9,3.36,.93,5.07-.55,10.14-1.12,15.21-1.66,1.73-.18,3.48-.32,5.22-.46,.59-.05,.96,.39,.73,.87-11.5,23.85-22.85,47.72-32.65,72.24-.09,1.45,3.69-.15,4.58-.11,5.33-1.13,10.66-2.29,15.99-3.41,.61-.02,1.77-.44,2.09,.27-6.31,15.65-13.81,30.95-19.66,46.79-1.97,5.56-4.9,10.94-6.23,16.68l-.25,.21Z"/><pM ath class="cls-2" d="M433.2,580.83s.01,.1,.02,.15c-.05,0-.11-.01-.16-.02l.14-.13Z"/><path class="cls-2" d="M439.57,639.7s.05,.01,.07,.01c.02,.02,.03,.03,.04,.05l-.11-.06Z"/><path class="cls-2" d="M670.15,602.22s-.01,.08-.02,.12c-.04-.02-.09-.04-.13-.06l.15-.06Z"/><path class="cls-2" d="M725.85,587.43s.05-.05,.07-.08c.01,0,.03,.01,.04,.01l-.11,.07Z"/><path class="cls-2" d="M576.96,660.56c-3.12,2.7-6.16,5.5-9.11,8.38-.52-.58-1.37-2.19-2.14-1.91-.44,.12-.59,.4-.72,.7-1.19,2.56-2.36,5.12-3.54,7.69-.68,.73-1.36,1.46-2.0M 3,2.2-3.11-3.5-5.51-7.62-8.3-11.38-.27-.39-.59-.69-1.27-.71-2.4,3.28-3.44,7.59-6.48,10.38-3.59-4.41-6.11-9.61-9.52-14.17-.82-.46-1.36,.76-1.83,1.24-1.72,2.44-3.43,4.88-5.13,7.33-.27,.39-.64,.65-1.36,.65-13.73-21.42-5.88-19.44-18.23-8.07-.69-.19-.94-.56-1.15-.94-.91-1.68-1.84-3.36-2.68-5.06-2.44-4.42-4.01-9.31-6.87-13.46-1.43,.61-2.13,1.7-3.14,2.54-2.21,1.74-4.01,3.88-6.58,5.18-.84-.53-1.06-1.27-1.37-1.98-2.95-6.9-5.95-13.82-8.88-20.71-.89-.05-1.39,.32-1.91,.65-2.53,1.61-5.06,3.22-7.61,4.81-2.23,1.36-2.27,.03-3.09-1M .76-2.23-6.1-4.45-12.2-6.65-18.3-.64-1.75-1.23-3.52-1.86-5.28-.45-.89-1.69-.42-2.39-.07-3.21,1.59-6.71,2.7-10.02,4.17-.64,.55-.07,1.47,.05,2.15,2.87,8.53,6.2,16.93,9.39,25.38,.5,1.9-11.44-.31-12.9-.5-.25-.35-.57-.69-.72-1.06-3.49-9.13-7.4-18.15-9.98-27.51,.52-1.71,13.13,2.98,13.04,.75-2.75-10.35-6.83-20.42-8.76-30.91,3.58-.3,6.93-2.14,10.41-3.03,.86-.28,1.65-.76,2.95-.61,2.72,9.82,5.26,19.95,8.57,29.63,.86,.16,1.45-.1,2.01-.39,3.2-1.55,6.28-3.4,9.57-4.78,.64-.08,.96,.62,1.11,1.13,1.66,4.99,3.28,9.99,4.99,14.97,1.03M ,3.01,2.2,5.99,3.31,8.98,.16,.42,.9,.61,1.31,.32,3.06-2.08,6.1-4.18,8.98-6.49,.29-.22,.88-.13,1.02,.14,3.28,6.98,5.67,14.4,8.99,21.37,1.05,.08,1.59-.64,2.28-1.25,2.1-2.1,4.18-4.22,6.26-6.34,.35-.35,.74-.61,1.44-.59,2.94,5.95,5.4,12.16,8.44,18.08,.2,.42,.51,.73,1.25,.83,2.58-2.78,4.67-6.03,7.2-8.86,.14-.14,.47-.17,.71-.25,3.31,4.62,5.68,10.96,8.93,15.81,.19,.29,.85,.36,1.02,.11,1.38-2.09,2.75-4.18,4.12-6.27,.69-1.05,1.36-2.1,2.05-3.15,.16-.25,.87-.3,1.02-.08,2.51,3.64,4.54,7.57,6.89,11.31,.53,.86,.92,1.81,1.92,2.43,M .66-.26,.92-.75,1.17-1.24,1.37-2.69,2.75-5.38,4.13-8.07,.3-.58,.5-1.21,1.22-1.58,.66,.25,.9,.76,1.22,1.24,1.9,2.84,3.81,5.69,5.73,8.53,.6,.71,1.15,1.97,2.05,2.27,.86-.32,1.09-1.09,1.37-1.85,1.34-3.05,2.59-6.12,3.98-9.14,.13-.27,.81-.41,1.01-.21,1.89,2.05,3.38,4.41,5.11,6.61Z"/><path class="cls-2" d="M586.61,652.66c-.8,.6-1.59,1.22-2.38,1.86,.29-.85,.7-1.69,1.06-2.48,.72,0,1.05,.29,1.32,.62Z"/><path class="cls-2" d="M737.94,573.78c-3.62,4.76-8.11,9-12.02,13.57-2.68-.99-5.34-1.98-8.02-2.96-1.27-.46-1.72-.4-2.38,.42-3M .43,4.39-7.3,8.51-9.81,13.37,2.77,1.41,6,1.93,8.86,3.13-.12,2.18-1.77,3.99-2.52,6.03l-11.16-.1c4.47-10.75,7.55-7.75-3.93-12-.68-.2-1.22,.25-1.5,.77-1.87,3.71-3.75,7.42-5.61,11.13l-9.19-.09c-.5-.22-1.28-.49-1.69-.01l-10.64-.1c.56-1.54,1.55-2.97,1.8-4.6,2.79,1.21,5.41,2.77,8.31,3.68,.19,.06,.58-.06,.7-.19,2.58-4.32,4.74-8.89,7.17-13.3,.26-.5,.56-.97,1.35-1.24,2.53,1.07,5.1,2.41,7.79,3.21,.2,.06,.59-.03,.72-.16,3.04-3.61,5.35-7.73,8.29-11.41,2.89-3.45,1.82-3.23,6.34-1.33,1.89,.68,3.55,1.72,5.59,1.94,4.18-4.43,7.88-9.3M 2,12.27-13.53,.26-.14,.8-.19,1.13-.05,2.74,1.14,5.47,2.29,8.15,3.41,0,.21,.01,.31,0,.41Z"/><path class="cls-2" d="M97.05,1321.32c-.26-.52-.21-1.05-.07-1.58,1.66-6.31,3.3-12.62,4.86-18.95,.52-1.7-1.99-1.36-3.12-1.45-3.63-.05-7.27-.14-10.9-.15-11.29-.13-22.61-.41-33.87-.95-.68-.21-1.05-.89-.98-1.57,.02-6.35,.05-12.69,.09-19.04-.09-1.45,1.46-1.34,2.53-1.34,15.32,.78,30.65,1.17,45.97,1.63,1.39,.32,6.08-.65,5.63,1.55-.67,2.74-1.36,5.48-2.06,8.22-.88,3.48-1.77,6.95-2.64,10.43-.16,.42,.06,.99,.51,1.09,15.45,.66,30.94-.26,M 46.4-.02l-.14-.11c-2.89,6.51-6.08,12.89-9.19,19.3-.35,.78-1.04,1.9,.35,2.09,13.1,.2,26.13-.94,39.23-1.16,.35,1.33-.84,2.19-1.42,3.28-3.73,5.61-7.46,11.21-11.18,16.82-.27,.48-.94,1.33-.2,1.66,11.28,.18,22.59-.94,33.88-1.16,.63-.01,.99,.44,.69,.85-5.6,7.39-12.02,14.21-17.45,21.72-.02,.67,.99,.64,1.49,.64,9.29-.3,18.57-.61,27.86-.9,.39-.06,.7,.18,.98,.4,.21,.3-.21,.6-.38,.84-7.42,7.81-14.59,15.85-22.15,23.53-8.3,.48-16.68,.05-25,.2-3.79,.1-1.15-1.94-.07-3.45,4.78-5.99,9.57-11.98,14.35-17.96,.58-.71,2.19-2.35,.33-2.51-M 9.69,.12-19.39,.69-29.07,.55-.28-.02-.69-.51-.6-.71,.09-.2,.15-.42,.27-.61,4.22-6.62,8.53-13.2,12.83-19.78,.59-.91,.18-1.35-1.2-1.3-11.17,.34-22.34,.83-33.52,.93-1.39-.07-.7-1.34-.38-2.08,1.94-4.13,3.9-8.25,5.84-12.38,1-2.11,1.99-4.23,2.97-6.34,.2-.43-.18-.88-.75-.89-13.58,.28-27.26,.19-40.79,.64-.01,0,.09,.05,.09,.05Z"/><path class="cls-2" d="M1344.66,118.75c-.19,.28-.49,.54-.56,.84-1.66,6.53-3.31,13.06-4.95,19.6-.14,.56,.34,1.01,1.12,1.08,14.93,.46,29.87,.5,44.79,1.11,1.75,.03,2.56,.05,2.49,2.09,0,6.13,0,12.27-.0M 1,18.4-.05,.63,0,1.47-.79,1.63-5.76,.01-11.56-.5-17.32-.7-9.28-.29-18.56-.57-27.84-.85-2.8-.15-5.66,.12-8.38-.66l.14,.13c2.14-6.26,3.27-12.84,4.97-19.23,.11-.57,.38-1.51-.39-1.69-8.17-.55-16.37-.06-24.55-.1-6.05,.06-12.1,.15-18.14,.22-1.04-.07-3.73,.42-2.99-1.35,2.93-6.23,5.96-12.43,8.93-18.64,.47-.98,.12-1.37-1.23-1.38-13.16,.09-26.33,.53-39.46,1.37l.16,.11c3.68-7.1,8.9-13.53,13.09-20.38,.84-1.37,.42-1.84-1.13-1.81-11.08,.26-22.09,.76-33.16,1.31-.28-1.4,1.05-2.13,1.74-3.18,4.79-5.86,9.58-11.72,14.36-17.59,1.49-1.8M 9,1.95-2.52-.96-2.43-9.02,.3-18.04,.59-27.07,.8-1.51-.21-.63-1.23,.09-1.92,7.15-7.46,13.99-15.13,21.15-22.58,8.93-.32,17.97-.22,26.9-.05,.31,.51,.12,.88-.18,1.27-3.03,3.82-6.04,7.65-9.08,11.47-2.39,3-4.81,5.98-7.2,8.97-.38,.52-1.36,1.6-.24,1.84,9.83-.09,19.66-.56,29.49-.58,.99,.29,.56,1.02,.21,1.62-4.13,6.41-8.31,12.81-12.43,19.22-.88,1.5,.64,1.51,1.74,1.5,10.51-.31,21.01-.63,31.52-.8,1.94,0,2.36,.21,1.6,2.19-1.98,4.23-4,8.46-5.99,12.69-.9,1.91-1.75,3.84-2.62,5.76-.18,.4,.23,.94,.72,.97,13.86,.15,27.75-.63,41.61-.1M 5l-.14-.12Z"/><path class="cls-2" d="M488.94,146.58c11-30.71,22.64-61.24,35.4-91.29,.17-.41,.31-.84,.59-1.19,.58-.69,1.66-.66,2.52-.66,7.68,0,15.37,0,23.05,0,.61-.04,1.9-.04,1.89,.72-4.98,11.98-10.58,23.72-15.59,35.66-7.46,17.5-14.67,35.07-21.37,52.85-.36,1.09-.04,1.49,1.22,1.4,1.88-.13,3.75-.29,5.63-.47,5.22-.5,10.43-1.02,15.64-1.53,.95-.14,2.42-.03,1.91,1.22-10.59,25.37-20.38,50.95-29.09,76.95l.08-.06c-6.93,1.29-13.86,2.59-20.79,3.86-.79,.03-2.51,.66-2.67-.47,2.7-8.99,5.59-17.91,8.62-26.82,5.62-16.84,11.55-33.58,M 17.88-50.18,.14-.64,.7-1.72-.15-2-1.34,.01-2.68,.01-4.01,.13-6.95,.53-13.87,1.5-20.84,1.76l.08,.11Z"/><path class="cls-2" d="M1271.78,456.81c37.9,11.66,75.35,24.51,112.26,38.83,1.08,.41,2.29,.69,3.1,1.66,.24,6.39,.05,12.86,.11,19.26-.06,.79,.14,2.22-1.1,1.97-22.58-8.99-45.03-18.03-68.01-26.24-14.84-5.35-29.77-10.66-44.91-15.38-.52-.15-1.19,.19-1.19,.57,.41,5.8,1.28,11.58,1.86,17.37,.02,.21,0,.43,0,.65,0,.25-.58,.64-.84,.55-31.46-10.83-63.55-20.68-95.91-28.95l.07,.08c-.82-5.6-2.66-11.29-1.74-16.95,.43-.66,1.47-.25,2M .12-.18,29.7,6.83,59.04,15.19,88.03,24.3,1.85,.58,3.59,1.47,5.65,1.54,.49,.02,.51-.16,.36-4.97,.05-4.65-.68-9.62,.26-14.16l-.13,.06Z"/><path class="cls-2" d="M1001.34,1295.62c-.43-.72-.33-1.44-.11-2.2,.79-2.71,1.54-5.44,2.32-8.16,2.81-9.72,5.37-19.48,7.83-29.26,1.74-6.94,3.48-13.88,5.14-20.83,1.36-5.69,2.61-11.39,3.91-17.09,.22-.95,.39-1.91,1.17-2.71,0,0-.06,.03-.05,.02,.48,.59,1.3,.7,2.05,.87,6.14,1.65,12.62,2.46,18.56,4.68l-.06-.09c-.45,6.23-2.27,12.34-3.38,18.5-4.09,18.79-8.3,37.52-13.13,56.15-.13,.99-1.07,2.52,M .47,2.83,7.81,1.11,15.63,2.2,23.43,3.41l-.07-.09c-3.31,10.9-5.35,22.19-8.4,33.21-4.7,17.08-8.75,34.48-14.43,51.26-2.82,.26-16.49,.72-27.26,.03,8.33-28.47,17.65-56.76,24.94-85.56,.14-.53,.18-1.07,.25-1.6,.02-.46-.81-1-1.35-1-6.78-.89-13.55-1.78-20.33-2.67-.54-.07-1.07-.05-1.5,.28v.02Z"/><path class="cls-2" d="M418.87,224.39c-.33-.54-.99-.67-1.62-.82-3.96-.92-7.93-1.82-11.89-2.74-2.23-.73-5.77-.93-7.25-2.24,5.17-24.77,10.5-49.52,16.86-74.03,.08-1.05,1.16-2.81-.47-3.14-6.5-.93-13-1.81-19.5-2.75-.92-.13-1.83-.36-2.72-.M 59-.2-.05-.43-.33-.43-.5,.84-6.32,2.86-12.49,4.25-18.73,5.56-21.74,11.27-43.51,17.86-64.96,.61-.64,1.79-.4,2.62-.49,7.41,0,14.83,0,22.24,.02,.84,0,2.46-.19,2.41,1-4.75,15.91-10.12,31.69-14.58,47.68-3.49,12.83-7.62,25.53-10.57,38.48-.16,1.04,1.47,1.23,2.31,1.33,4.38,.59,8.76,1.2,13.15,1.77,2.26,.29,4.53,.54,6.8,.78,.23,.02,.49-.14,.73-.21h0c.53,.56,.56,1.19,.37,1.83-3.91,13.36-7.53,26.81-10.92,40.28-2.12,8.42-4.31,16.82-6.03,25.3-.75,3.71-1.71,7.39-2.59,11.08-.15,.65-.51,1.22-1.1,1.7,0,0,.06-.01,.06-.01Z"/><path claM ss="cls-2" d="M1287.14,363.02c-.97,5.98-2.15,11.93-3.26,17.89-.34,1.49-2.25,.69-3.29,.61-28.6-6-57.55-10.64-86.51-14.64l.15,.12c2.27-5.06,3.61-10.59,5.53-15.82,.47-1.77-3.38-1.3-4.48-1.66-3.07-.33-6.13-.64-9.2-.95-20.7-2.28-41.53-2.93-62.3-4.3l.15,.1c1.99-4.1,3.97-8.21,5.99-12.31,1.84-3.73,2.09-3.71-3.31-3.78-9.68-.15-19.36-.1-29.04-.05-10.35,.12-20.69,.64-31.04,.76-1.66-.34-.29-1.81,.11-2.67,2.63-4.35,5.3-8.68,7.91-13.05l-.1,.05c21.86-.81,43.72-1.72,65.6-1.27l-.09-.1c-1.75,4.63-4.6,8.95-6.72,13.47-.53,1.34-2.21,3.M 09,.67,3.08,24.21,.52,48.35,2.2,72.47,4.24l-.1-.11c-1.51,5.86-4.27,11.3-5.73,17.19,28.95,3.92,58.02,7.7,86.72,13.3l-.11-.1Z"/><path class="cls-2" d="M1096.34,280.31c19.3-1.43,38.66-2.02,58.01-2.49,.83,.14,4.47-.48,4.09,.81-2.39,4.7-5.14,9.22-7.66,13.85-.25,.73-1.55,2.15-.37,2.54,23.27,.07,46.5,1.04,69.74,2.13l-.14-.09c-1.39,5.36-4.11,10.45-5.99,15.7-.29,.71-.65,1.41-.4,2.23,10.15,1.5,20.53,1.84,30.74,3.05,17.05,1.67,33.95,4.62,50.98,6.27l-.07-.09c-.22,.5-.53,.99-.64,1.5-1.09,5.99-2.75,11.92-3.43,17.95l.13-.05c-9.65M -.58-19.25-3-28.9-4.16-18.66-2.73-37.43-4.72-56.18-6.83l.1,.11c2.04-5.7,4.9-11.45,6.2-17.22-23.96-2.93-48.44-2.85-72.62-3.56l.09,.1c2.85-5.22,5.7-10.44,8.55-15.66,.54-1.07-.6-1.27-1.49-1.22-20.73-.09-41.43,.84-62.13,1.92l.08,.12c3.76-5.62,7.51-11.24,11.27-16.87l.04-.03Z"/><path class="cls-2" d="M1189.33,383.81c30.14,4.3,59.95,10.21,89.61,16.81,.72,.14,1.41-.21,1.51-.76,1.04-5.32,1.92-10.65,2.88-15.98,.34-1.99,1.77-1.33,3.25-1.1,33.63,7.05,66.61,15.51,99.38,24.94,1.16,.3,1.37,1.15,1.32,2.11,0,5.92,0,11.85,0,17.77,0,M 2.07-.27,2.56-3.01,1.74-10.45-3.15-20.89-6.34-31.4-9.39-23.4-6.81-47.12-13.01-70.99-18.59-1.14-.26-1.71,.07-1.88,1.1-.88,5.34-1.72,10.68-2.65,16.01-.13,.76-.76,1.08-1.75,.86-30.36-7.78-61.27-13.66-92.08-19.49l.17,.12c2.07-4.64,3.15-9.69,4.81-14.5,.19-.63,.37-1.24,.91-1.75l-.09,.09Z"/><path class="cls-2" d="M52.33,141.44c0-6.17-.02-12.66,0-18.89,.13-.85-.31-2.56,1.11-2.25,4.43,1.92,8.61,4.43,12.93,6.6,4.55,2.27,8.84,5.07,13.53,7.02,.14,.05,.59-.16,.61-.28,.13-.74,.24-1.49,.23-2.23-.09-7.22-.25-14.43-.3-21.65,0-.43,.M 05-.86,.08-1.29,.37-1.4,3.53,.54,4.51,.71,5.84,2.22,11.67,4.45,17.5,6.67,1.39,.27,5.46,2.94,5.36,.29,0-.65-.02-1.29-.02-1.94,0-9.05-.24-18.1-.04-27.15,.03-1.04,.52-1.36,1.76-1.11,4.44,.88,8.88,1.78,13.32,2.66,2.61,.52,5.23,1.02,7.83,1.56,4.25,.89,4.21,1.44,4.28-2.74,.26-11.09,.33-22.19,.79-33.28,.03-1.31,1.65-1.34,2.69-1.3,8.07,.13,16.2-.23,24.24,.17,1.12,.36,.83,1.67,.86,2.58-.36,7.43-.78,14.85-1.1,22.28-.2,4.63-.26,9.26-.4,13.89-.31,1.36,.72,4.71-1.6,4.33-8.3-1.13-16.41-3.87-24.72-4.55-1.54,.09-.71,7.51-.95,9.06,M 0,7.97,0,15.94,0,23.91-.22,1.1,.65,3.9-1.29,3.38-8.01-3.04-15.9-6.4-23.94-9.37-2.04-.92-1.64,1.32-1.66,2.56-.19,9.25,.8,18.55,.4,27.76-.54,.52-1.51-.08-2.08-.35-5.77-3.18-11.51-6.38-17.29-9.55-2.33-1.28-4.73-2.47-7.11-3.69-.3-.16-.88,.09-.9,.39-.24,7.2,.27,14.43,.36,21.63,.06,3,0,3.4-.53,3.33-1.41-.2-2.19-1.15-3.19-1.82-7.65-5.12-15.27-10.25-22.91-15.38-.82-.55-1.75-1.01-2.37-1.99Z"/><path class="cls-2" d="M1305.47,1311.84c.95-.16,1.82,.09,2.67,.47,7.71,3.09,15.42,6.18,23.2,9.12,1.27,.47,1.41-.79,1.35-1.68-.1-8.83-M .27-17.66-.45-26.49-.01-.64,.07-1.28,.12-1.93,.02-.24,.65-.54,.89-.42,1.03,.51,2.07,1.01,3.07,1.56,7.44,4.09,14.79,8.34,22.37,12.17,.45,.23,1.12-.1,1.12-.55,.09-8.17-.53-16.35-.52-24.51,.75-.37,1.24-.12,1.85,.28,8.73,6,17.72,11.65,26.3,17.84,.53,6.78,.06,13.73,.21,20.56,.02,.52-.21,1.28-.86,1.19-8.17-3.82-15.97-8.43-24.01-12.53-3.09-1.65-2.73-.79-2.8,2.1,.08,6.68,.18,13.36,.25,20.03,0,.85-.11,1.71-.24,2.56-.47,.62-1.48,.05-2.08-.11-8.07-2.95-15.99-6.3-24.16-8.96-.27-.09-.85,.27-.85,.52-.02,2.37-.05,4.73-.05,7.1,.03M ,7.32,.07,14.65,.1,21.97-.06,.72-.01,1.81-1,1.84-8.72-1.21-17.3-4.11-26.01-4.85-.75,11.35-.6,22.79-.98,34.17-.08,3.89,.08,3.71-4.66,3.71-6.6-.01-13.21-.02-19.81-.03-1.33,0-3.67,.26-3.42-1.69,.64-12.05,1.15-24.1,1.44-36.17,.05-1.61,.23-3.22,.35-4.82,.02-.22,.59-.62,.84-.6,7.37,1.01,14.63,2.92,21.96,4.26,3.07,.37,4.24,1.31,4.09-2.57-.19-11.18,.47-22.44-.23-33.58l-.03,.06Z"/><path class="cls-2" d="M161.33,138.68c-.15,13.24,.38,26.5,.36,39.72-.26,.31-1.03,.27-1.41,.02-5.86-3.01-11.47-6.43-17.24-9.59-1.99-1.11-4.02-2.17M -6.05-3.23-2.19-.71-1.01,2.76-1.2,3.91,.33,9.15,.72,18.3,1.18,27.45,.15,1.97-.1,3.27-2.21,1.65-6.19-4.32-12.38-8.64-18.58-12.96-1.72-1.2-3.43-2.42-5.19-3.59-.23-.16-.72-.07-1.17-.11-.07,8.66,.87,17.24,1.22,25.89,.05,.86,0,1.72-.01,2.58-.02,.36-.73,.36-.9,.29-6.21-4.51-11.91-9.67-17.94-14.42-2.83-2.3-5.7-4.58-8.57-6.85-1.85-1.02-1.21,1.73-1.24,2.77,.26,6.46,.53,12.92,.78,19.38-.06,.53,.11,1.52-.31,1.83-.23,.04-.58,.1-.71,0-9.05-7.73-17.63-16.03-26.56-23.91-1.34-1.32-3.42-2.54-3.19-4.63,.15-6.49-.22-12.99,.15-19.46,1M .59-.29,2.55,1.25,3.75,2.01,7.8,6.26,15.59,12.52,23.39,18.77,.69,.44,1.3,1.32,2.22,1.07,.08-.01,.18-.16,.19-.24,.04-.86,.11-1.72,.09-2.57-.2-6.68-.42-13.35-.62-20.03,.06-.74-.31-2.31,.92-2.01,2.42,1.26,4.57,3.01,6.85,4.5,6.11,4.24,12.2,8.48,18.3,12.72,.43,.33,1.17,.8,1.73,.44,.1-.42,.22-.84,.21-1.26-.24-9.35-.92-18.72-.77-28.06,1.21-.42,2.17,.62,3.23,1.04,7.11,3.89,14.22,7.8,21.33,11.69,2.09,1.22,2.16,.48,2.17-1.58-.2-9.26-.42-18.52-.61-27.78-.09-4.58-.04-4.93,.6-4.95,2.15-.07,3.72,1.1,5.5,1.77,6.83,2.56,13.6,5.21,M 20.39,7.83l-.08-.08Z"/><path class="cls-2" d="M1305.5,1311.78c-.18-.92-1.32-.9-2.03-1.29-8.13-3.17-16.24-6.39-24.41-9.46l.08,.07c.38-13.13-.51-26.28-.18-39.4,.01-.25,.65-.53,.92-.39,2.24,1.2,4.49,2.38,6.7,3.6,5.2,2.88,10.38,5.79,15.58,8.67,.74,.28,2.13,1.36,2.66,.37,.03-11.07-1.11-22.14-1.16-33.21,.99-.39,1.64,.38,2.43,.83,5.9,4.1,11.79,8.2,17.67,12.31,2.21,1.32,4.06,3.4,6.52,4.19,.1,.02,.32-.06,.35-.13,.58-9.47-1.03-19.13-1.04-28.65,1.25-.21,2.01,.92,2.95,1.51,5.57,4.54,11.1,9.1,16.69,13.62,2.65,2.14,5.37,4.23,8.0M 6,6.34,.23,.18,.5,.15,.73-.03,.4-.36,.25-1.03,.31-1.52-.11-2.8-.25-5.6-.35-8.39-.17-4.52-.33-9.04-.47-13.56,.39-1.82,2.22,.47,2.95,1.02,8.72,7.92,17.45,15.84,26.17,23.77,1.33,1.03,.96,2.55,1.02,3.98,0,5.17,0,10.34,0,15.51,.34,4.94-1.76,2.26-4.11,.55-8.05-6.34-15.87-12.97-24.04-19.15-1.18-.56-1.03,1.16-1.03,1.87,.18,5.06,.38,10.12,.55,15.18,.08,2.37,.09,4.74,.12,7.11-.14,.64-.61,.9-1.39,.39-7.81-5.27-15.52-10.67-23.25-16.05-.92-.56-1.77-1.51-2.93-1.51-.5,.03-.54,.44-.53,.74,.31,9.04,.65,18.08,.94,27.13,.01,2.23-1.25M ,1.49-2.64,.79-7.22-3.96-14.43-7.93-21.65-11.89-.85-.4-1.56-1.07-2.57-.68-.16,11.93,1.07,23.91,.37,35.83,0,.02,.02-.04,.02-.04Z"/><path class="cls-2" d="M892.62,803.66c-.2-.04-.45-.06-.57,.13-2.42,3.42-3.79,7.47-6.36,10.77-.86,.24-1.1-.99-1.47-1.54-1.79-3.48-3.57-6.97-5.36-10.45-.3-.6-.59-1.21-1.46-1.61-2.42,3.75-3.72,8.11-6.11,11.88-.84-.23-1.06-.74-1.34-1.21-1.98-3.3-3.72-6.73-5.92-9.91-.16-.22-.62-.32-1.08-.54-1.92,3.97-3.31,8.02-5.26,11.95-1.2,1.14-2.23-1.9-2.93-2.6-1.71-2.18-2.88-5.18-5.04-6.88-.49-.15-.73,.55M -.92,.87-1.63,3.88-3,7.84-4.78,11.66-.07,.14-.36,.33-.52,.32-.23-.03-.52-.19-.64-.35-1.3-1.76-2.56-3.54-3.87-5.3-.69-.61-2.23-3.7-3.17-2.62-1.94,3.96-3.24,8.22-4.97,12.27-.16,.41-.4,.79-.98,.93-.77-.3-1.09-.91-1.53-1.44-1.49-1.8-2.98-3.59-4.47-5.38-.32-.37-.71-.64-1.47-.57-1.73,4.25-3.45,8.56-5.16,12.83-.21,.52-.43,1.02-1.11,1.3-2.35-1.7-4.15-4.26-6.36-6.2-1.35-.88-1.6,1.2-2.05,2.02-1.72,3.97-3.25,8.01-5.1,11.92-.38,.77-1.02,.85-1.84,.22-2.12-1.64-4.23-3.3-6.36-4.96,1.43-5.05,3.88-9.85,5.7-14.8,.08-.2,.29-.36,.45-.M 55,1.18,.05,1.85,.79,2.67,1.3,1.99,1.09,3.19,2.71,5.49,3.39,2.18-3.73,3.54-9.21,5.26-13.37,.26-1.56,1.62-1.24,2.32-.26,1.95,1.77,3.61,3.83,5.7,5.43,.14,.1,.46,.03,.83,.05,1.68-4.16,3.01-8.47,4.51-12.7,.27-1,1.07-1.23,1.82-.39,2.08,2.25,4.09,4.54,6.21,6.76,.21,.23,.91,.14,1.01-.12,1.65-4.23,3.03-8.44,4.59-12.79,.46,.1,.98,.08,1.14,.26,2.32,2.63,4.46,5.37,6.66,8.09,.11,.14,.46,.28,.63,.24,.22-.05,.46-.26,.54-.45,1.82-3.88,2.87-8.09,4.71-11.95,.71,.02,1.08,.28,1.36,.67,1.61,2.24,3.22,4.48,4.83,6.73,.6,.84,1.17,1.69,1.M 77,2.53,.23,.3,.77,.08,.95-.1,1.88-3.51,3.14-7.33,4.78-10.96,.19-.43,.59-.72,.83-.59,1.17,.58,1.63,1.88,2.35,2.88,1.62,2.6,3.23,5.2,4.84,7.81,.29,.48,.57,.95,1.22,1.18,.62-.47,.88-1.08,1.17-1.68,1.35-2.82,2.72-5.62,4.08-8.43,.24-.51,.51-1,1.28-1.3,3.14,4.21,5.06,9.49,8.25,13.54,.09,.69,.17,1.38,.25,2.07Z"/><path class="cls-2" d="M987.06,901.51s.07-.02,.1-.03c.01,.05,.01,.1,.02,.15l-.12-.12Z"/><path class="cls-2" d="M993.65,862.78s-.06,.03-.09,.04c-.01-.03-.03-.06-.04-.09l.13,.05Z"/><path class="cls-2" d="M1000.92,8M 96.97s-.01,.09-.02,.13c-.01,0-.02,0-.03,.01-4.74,1.01-9.12,2.91-13.71,4.37-1.29-10.7-3.59-21.24-5.81-31.78-.25-1.19-1.07-1.06-2.02-.63-3.42,1.61-6.72,3.52-10.14,5.16-.3-.19-.61-.29-.65-.43-.55-2.21-1.11-4.43-1.6-6.65-1.7-6.8-2.94-13.95-5.4-20.5-.68-.47-1.47,.2-2,.56-2.7,2.26-5.38,4.53-8.06,6.81-.37,.31-.74,.59-1.35,.53-.62-.72-.75-1.59-.98-2.43-1.82-6.73-3.48-13.49-5.72-20.15-.21-.62-.36-1.26-1-1.72-.6,.03-.95,.34-1.28,.68-2.14,2.2-4.29,4.41-6.42,6.62,.65-9.87,.61-19.77-.12-29.7,11.85,26.75,2.9,23.86,18.2,12.44,.75M ,.53,.93,1.17,1.14,1.79,2.76,7.6,4.98,15.39,7.52,23,.94,.12,1.41-.3,1.93-.63,2.53-1.6,5.05-3.22,7.6-4.81,.54-.29,1.47-.96,2.07-.51,3.38,9.35,5.28,19.16,7.97,28.71,1.79-.08,3.01-1,4.42-1.56,2.72-1.12,5.4-2.32,8.1-3.46,1.66,3.81,2.13,8.1,3.17,12.12,1.33,7.33,3.43,14.66,4.19,22.03Z"/><path class="cls-2" d="M1246.01,141.96c-9.51,.74-19.07,1-28.58,1.69-4.83,.21-9.66,.86-14.49,.82-1.22-.41,.59-1.79,.91-2.4,3.34-4.04,6.7-8.08,10.03-12.12,1.63-1.98,3.23-3.97,4.81-5.97,.19-.25,.35-.64,.24-.89-.22-.52-.88-.35-1.36-.31-7.38,.M 52-14.75,1.06-22.13,1.59-4.56,.27-9.11,.81-13.68,.87-.38,.04-.57-.46-.47-.71,5.94-6.71,12.34-13.04,18.45-19.61,.75-.9,1.84-1.54,1.92-2.79-10.51,.23-20.94,1.48-31.43,2.17-.65-.06-2.23,.38-2.32-.46,7.46-7.86,15.72-14.99,23.39-22.65,1.04-1.01,1.95-2.1-.3-2.04-9.28,.28-18.54,1.04-27.81,1.21-.4-.6,.03-.98,.46-1.4,9.82-8.63,19.35-17.59,29.34-26.03,8.24-.33,16.6-.05,24.86-.14,.66,.05,2.3-.2,1.91,.89-7.86,7.98-16.15,15.57-24.16,23.42-.56,.65-1.6,1.25-.2,1.7,9.42-.33,18.83-.67,28.25-.92,1.43,.18,.32,1.39-.23,1.95-6.25,6.77-M 12.66,13.41-19,20.1-.34,.51-1.54,1.42-.65,1.82,1.34,0,2.69-.01,4.02-.09,9-.5,18-1.03,27-1.58,.89,.06,3.57-.54,2.62,1.09-4.99,6.29-10.18,12.43-15.24,18.66-.5,.84-1.65,1.52-1.43,2.57,1.33,.33,2.66,.08,3.99-.01,11.93-.76,23.91-1.64,35.88-1.66l-.16-.11c-5.04,7.01-9.71,14.27-14.58,21.4l.12-.05Z"/><path class="cls-2" d="M796.17,794.99c.02-.06,.04-.12,.05-.18,.03,.02,.07,.03,.1,.05l-.15,.13Z"/><path class="cls-2" d="M881.33,758.66c-.35,.63-.56,1.39-1.38,1.54-3.11-3.01-5.55-6.61-8.47-9.82-.42-.39-1.07-1.28-1.72-.76-1.97,3.M 32-2.72,7.26-4.62,10.63-.97,.79-1.81-.99-2.5-1.5-9.93-10.44-6.86-9.82-11.43,2.97-.23,.52-.51,1.49-1.27,1.3-2.65-1.85-4.72-4.41-7.15-6.54-.52-.31-1.57-1.66-2.13-.95-1.82,3.71-2.08,8.05-3.7,11.85-1.1,.98-2.35-1.17-3.3-1.68-1.77-1.47-3.53-2.96-5.33-4.41-.23-.18-.71-.15-1.14-.24-1.53,4.41-2.08,8.92-3.63,13.2-1.92,.58-9.05-5.78-9.97-3.86-1.05,4-2.05,8-3.03,12.02-.14,.51-.28,1.05-.91,1.4-13.22-4.84-7.17-7.76-13.43,11-4.99-2.35-6.59-2.97-9.38-3.67-1.54,3.95-2.35,8.12-3.62,12.16-.23,.82-.39,1.68-1.25,2.43-3.07-.94-5.99-2.5M 9-9.22-3.02,1.44-4.81,2.54-9.7,4.1-14.47,.09-.26,.66-.52,.96-.42,2.25,.72,4.49,1.44,6.74,2.16,1.52,.52,2.26,.67,2.7-1.12,.96-3.91,1.89-7.82,2.84-11.73,.19-.79,.89-1.13,1.73-.83,2.62,.94,5.36,1.96,7.92,2.98,.94-.45,1-1.14,1.14-1.74,.93-3.91,1.71-7.85,2.69-11.75,.12-.44,.7-.63,1.26-.4,2.63,1.07,5.18,2.29,7.78,3.41,.3,.13,.74,.02,1.13,.02,1.38-4.25,1.81-8.76,3.17-13.02,.07-.21,.78-.42,1.04-.32,2.71,1.1,5.21,2.66,7.82,3.98,.91,.48,1.59,.3,1.79-.49,.37-1.48,.71-2.96,1.07-4.44,.56-2.32,1.11-4.65,1.68-6.97,.15-.64,.85-.77M ,1.51-.31,2.46,1.81,4.72,3.85,7.09,5.75,.46,.38,.86,.84,1.76,.87,1.68-3.65,2.23-7.73,3.56-11.51,.14-.38,.97-.56,1.32-.26,1.38,1.18,2.76,2.36,4.1,3.57,1.43,1.29,2.79,2.63,4.23,3.91,.22,.19,.7,.18,1.14,.29,1.26-3.47,2.4-6.86,3.62-10.32,.55-1.56,1.49-.98,2.37-.1,2.09,2.11,4.15,4.24,6.27,6.34,.74,.73,1.24,1.65,2.4,2.09,1.43-.58,1.27-1.82,1.73-2.77,.64-1.31,1.2-2.65,1.76-3.99,3.03,5.66,5.76,11.51,8.16,17.54Z"/><path class="cls-2" d="M964.52,753.46s.04,.05,.05,.07c-.07,.02-.13,.05-.2,.08l.15-.15Z"/><path class="cls-2" d=M "M977.5,752.9h-.04s-.04-.05-.05-.07l.09,.07Z"/><path class="cls-2" d="M988.27,774.2c-2.29,.1-4.57-.04-6.86-.02-5.54,0-5.43-.47-3.31,3.78,3.26,6.67,6.46,13.38,9.03,20.28-.22,.25-.32,.48-.53,.58-3.7,1.69-7.24,3.95-11.06,5.28-.8-.35-.91-1.03-1.16-1.61-1.18-2.74-2.26-5.52-3.48-8.25-1.8-4.06-3.7-8.08-5.55-12.12-.24-.52-.48-1.01-1.26-1.31-3.49,1.69-6.38,4.16-9.48,6.4-1.53,.84-1.76-1.38-2.4-2.26-2.38-4.57-4.75-9.14-7.16-13.7-.57-1.09-1.26-2.14-1.95-3.18-.08-.12-.52-.22-.7-.16-2.28,1.33-4,3.5-6.03,5.17-1,.84-1.72,2.09-3.07M ,2.38-2.37-3-3.81-6.38-5.9-9.55-.96-3.49-2.01-6.95-3.14-10.36,2.29-2.1,4.05-4.65,6.72-6.34,.97,.23,1.37,1.24,1.92,1.96,2.95,4.72,5.89,9.44,8.82,14.17,.35,.56,.57,1.2,1.44,1.58,1.87-.84,8.96-7.81,10.3-6.53,3.54,5.61,6.39,11.62,9.67,17.39,.51,.65,.97,2.34,1.97,2.12,3.48-1.83,6.94-3.68,10.39-5.55,.32-.18,.43-.53,.28-.87-3.6-6.7-7.27-13.45-11.2-19.95,4.13-1.12,8.63-.34,12.89-.63,3.82,5.95,6.95,12.31,10.42,18.46,.24,.79,1.71,2.48,.39,2.84Z"/><path class="cls-2" d="M566.29,975.97c-1.25,.31-2.51,.57-3.8,.64-.38,.02-.78-.1M 2-.98-.45-1.55-3.06-3.42-6.04-5.2-9.05,.24-.33,.56-.54,.96-.67,2.9,3.27,5.92,6.44,9.02,9.53Z"/><path class="cls-2" d="M637.65,964.94s-.02-.03-.03-.04c.05-.03,.1-.05,.15-.07l-.12,.11Z"/><path class="cls-2" d="M659.11,944.03s0-.03,0-.05c.02-.01,.03-.01,.05-.02h0s-.03,.07-.04,.07Z"/><path class="cls-2" d="M695.56,883.5c-2.74-1.18-5.54-3.25-8.41-3.92-5.36,3.75-10.29,8.15-15.94,11.73-.4,.27-.76,.62-1.44,.57-3.15-1.43-6.2-3.61-9.53-4.63-6.31,3.37-12.52,7.1-18.71,10.69-.28,.19-.32,.67-.03,.85,2.6,1.69,5.43,3.11,7.84,5.05,M .38,.71-.75,1.09-1.23,1.41-6.61,3.54-13.61,6.51-20.61,9.52-.13,.09-.13,.42-.03,.58,2.32,2.28,5.42,3.78,7.71,6.12,.26,.63-.64,.87-1.1,1.08-8.07,3.21-16.26,6.29-24.6,8.97-.52,.18-.71,.74-.38,1.07,2.18,2.19,4.48,4.3,6.67,6.48,.21,.23,.17,.6,.26,.95-6.71,2.55-13.62,4.56-20.59,6.49,2.94,2.92,5.98,5.74,9.13,8.45,6.78-2.13,13.43-4.52,20.09-6.89,2.38,2.56,4.48,5.26,6.7,8.01-5.38,2.94-11.4,4.46-17.15,6.62,3.45,2.57,6.99,5.02,10.62,7.33,4.33-1.59,8.6-3.25,12.79-5.13-1.82-2.73-4.02-5.26-5.61-8.12-.07-.17,.02-.48,.18-.58,9.08-M 3.98,18.05-8.03,26.91-12.22-.08-.4-.03-.87-.29-1.17-2.03-2.27-4.3-4.43-6.43-6.61,3.13-2.25,6.82-3.45,10.06-5.54,4.29-2.62,9.25-4.72,13.18-7.78-.23-.8-.88-1.21-1.43-1.65-1.52-1.22-3.09-2.41-4.62-3.62-.44-.44-1.39-.86-.96-1.57,6.41-4.54,13.05-8.29,19.43-12.99-2.45-2.29-5.72-3.66-8.37-5.68,4.64-3.85,9.49-7.36,14.21-11.1,.62-.73,3.1-1.78,1.68-2.77Zm-17.47,14.71c-4.84,3.26-9.65,6.55-14.79,9.52-1.28,.84-2.75,1.3-3.68,2.56,2.6,1.92,5.17,3.81,7.77,5.73-.47,1.11-1.58,1.42-2.54,2.01-6.37,3.81-13.15,7.06-19.82,10.54-.65,.68,.M 71,1.3,1.07,1.82,1.74,1.64,3.49,3.27,5.22,4.92,.39,.37,.3,.88-.16,1.12-8.52,4.43-17.58,7.98-26.53,11.55-2.5-2.62-4.99-5.26-7.57-7.99,8.55-3.77,17.53-6.49,25.91-10.65,.66-.31,.76-.9,.24-1.36-2.24-1.94-4.59-3.93-6.82-5.87,.17-.69,.82-.89,1.36-1.15,6.94-3.23,13.85-6.53,20.47-10.35,.51-.28,.51-.75,.03-1.07-2.42-1.71-5.06-3.17-7.34-5.05-.13-.11-.14-.44-.02-.58,6.17-3.93,12.67-7.55,18.82-11.54,.38,.04,.7,0,.9,.1,2.81,1.48,5.54,3.05,8.13,4.62,.23,.63-.29,.87-.65,1.12Z"/><path class="cls-2" d="M1271.91,182.14c2.73-7.07,6.5M 5-13.84,9.65-20.8l-.07,.07c17.28-.01,34.6,.47,51.86,.01l-.14-.13c-.71,6.33-3.05,12.44-4.39,18.68-.19,.73-.25,1.49-.3,2.23-.01,.15,.25,.39,.46,.45,14.71,1.24,29.56,1.19,44.29,2.39,4.03,.25,8.05,.53,12.07,.8,.79,.08,2.01,.02,2.11,1.04,.16,6.45,0,12.91,.04,19.37-.04,.58-.05,1.52-.78,1.63-21.32-1.03-42.62-3.68-63.97-3.86l.1,.09c1.53-6.1,3.07-12.2,4.59-18.31,.05-.88,.86-2.66-.43-2.9-18.39-.7-36.79-.69-55.19-.89l.12,.12Z"/><path class="cls-2" d="M976.39,1292.07c5.18,.62,10.37,1.25,15.55,1.87,3.1,.54,6.5,.36,9.39,1.68v-.0M 2c-.6,.1-.88,.44-1.01,.88-.52,1.78-1.04,3.56-1.55,5.35-8.27,28.13-17.38,56.08-27.38,83.69-.39,.99-1.88,.78-2.79,.83-8.26-.1-16.48,.2-24.74-.15,6.32-19.51,14.76-38.71,21.08-58.29,3.91-11.31,7.57-22.66,11.35-34,.21-.63,.39-1.25,.2-1.91,0,0-.1,.06-.1,.06Z"/><path class="cls-2" d="M439.08,144.22c.41-.01,.86-.08,.97-.43,.53-1.67,1.03-3.34,1.52-5.01,8.58-28.57,17.51-57.17,28.03-85.12,8.76-.53,17.57-.01,26.36-.15,.25,0,.49,.14,.73,.21,.27,.55,.05,1.05-.15,1.57-2.01,5.24-4.07,10.48-6.01,15.74-9.6,25.48-18.63,51.2-27.02,77.M 06-.01,0,.08-.07,.06-.06-.38-.5-1.01-.65-1.68-.73-7.58-1.05-15.4-1.25-22.81-3.09Z"/><path class="cls-2" d="M164.64,1020.42c-36.95-9.62-73.85-19.97-109.74-32.76-.65-7.42-.2-18.46,.08-21.23,1.8-.34,3.52,.83,5.23,1.28,35.47,12.52,71.18,24.54,107.68,34.07l-.1-.08c-1.18,6.27-1.91,12.61-3.27,18.85l.12-.12Z"/><path class="cls-2" d="M266.55,1007.6c.02-5.64-.13-11.27,.02-16.91l-.13,.12c26.46,5.22,52.9,11.41,79.82,14.11,.77-.13,.64-1.09,.66-1.67-.17-3.44-.35-6.88-.53-10.32-.04-1-.42-2.74,1.15-2.58,17.2,2.68,34.51,4.64,51.85,M 6.2,4.02,.3,8.04,.56,12.06,.84,.8,.06,1.62,.1,2.29,.53l-.08-.07c1.03,3.27,1.1,6.77,1.62,10.15,.14,1.16,.36,2.34-.04,3.51l.13-.1c-20.12-1.34-40.24-2.48-60.24-5.14-2.39-.18-4.8-.8-7.2-.65-.22,.04-.51,.25-.54,.41-.42,4.81,.01,9.68-.07,14.51l.12-.09c-27.2-2.72-54.25-7.39-80.99-12.93l.1,.08Z"/><path class="cls-2" d="M158.18,1057.92c-34.73-7.53-69.69-15.4-103.48-26.1-.46-6.71,.02-13.55-.1-20.29,0-.32,.13-.63,.2-.91,.56-.27,1.06-.15,1.57,0,2.77,.84,5.54,1.67,8.31,2.51,31.76,9.85,64.28,18.18,96.7,26.17l-.07-.09c-.51,6.33-2M .25,12.55-3.25,18.83l.13-.11Z"/><path class="cls-2" d="M822.93,1306.26c8.25-.92,16.47-2.37,24.78-2.59,.89,.29-.05,1.69-.22,2.29-13.05,26.32-27.1,52.19-41.6,77.79-.49,.87-.8,1.84-1.92,2.55-8.15,.24-16.37,.04-24.53,.1-.68-.06-2.24,.2-2.25-.74,15.76-26.21,31.38-52.55,45.84-79.46l-.09,.07Z"/><path class="cls-2" d="M342.37,130.12c4.44-25.31,10.01-50.4,15.64-75.48,.24-1.53,1.96-1.22,3.17-1.27,7.27,0,14.55,0,21.83,0,.93,0,1.9-.11,2.81,.36-6.21,26.36-13.25,52.65-18.43,79.28-.23,1.29-1.75,1.25-2.77,1.01-5.68-.9-11.35-1.81-1M 7.03-2.71-1.6-.29-4.36-.39-5.22-1.2Z"/><path class="cls-2" d="M1073.79,1305.5c7.27,1.12,14.55,2.22,21.81,3.37,2.58,.33,2.62,.81,2.24,3.24-4.58,24.75-9.6,49.41-15.48,73.9-1.17,.52-2.35,.39-3.58,.41-6.87,0-13.75,0-20.62-.01-2.95-.1-3.58,.41-2.78-2.97,6.94-25.84,12.51-52,18.53-78.03,0,0-.12,.1-.12,.1Z"/><path class="cls-2" d="M154.84,843.36c.94,6.3,1.77,12.61,2.5,18.94-.23,.71-1.01,.55-1.59,.28-29.78-13.91-58.92-28.75-87.62-44.53-3.55-1.95-7.09-3.92-10.63-5.89-1.36-.84-3.39-1.47-3.05-3.42-.02-6.03-.03-12.06-.03-18.09,M .06-.73,.02-1.96,1.15-1.55,6.71,3.74,13.21,7.82,19.92,11.6,26.03,15.01,52.55,29.21,79.42,42.75l-.08-.08Z"/><path class="cls-2" d="M1291.21,343.66c19.67,4.02,39.62,7.12,59.15,11.6,11.43,2.47,22.85,4.99,34.18,7.73,.9,.22,1.85,.33,2.64,1.05,.41,6.56,.03,13.26,.14,19.86,.09,2.43-1.57,1.37-3.13,1.14-32.05-8.44-64.42-15.72-97.05-22.03l.11,.1c1.5-6.46,1.94-13.24,4.09-19.5l-.13,.05Z"/><path class="cls-2" d="M151.08,1095.92c-32.28-4.74-64.34-11.96-96.08-19.4-.71-.64-.71-1.29-.71-1.94-.01-5.92,.02-11.85,.15-17.77-.03-2.97,1.M 3-1.99,3.43-1.59,31.24,8.07,62.66,15.29,94.41,21.35,.76,.17,2.07,.21,1.94,1.25-.36,2.13-.74,4.26-1.14,6.39-.47,2.56-1.03,5.1-1.43,7.67-.22,1.38-.92,2.72-.7,4.14l.12-.1Z"/><path class="cls-2" d="M476.1,686.23s.01,.02,.01,.03c-.05,.03-.11,.05-.16,.08l.15-.11Z"/><path class="cls-2" d="M488.04,705s.07,.01,.1,.01c.02,.02,.03,.03,.04,.05l-.14-.06Z"/><path class="cls-2" d="M536.63,707.2c-2.34,3.62-4.56,7.31-6.66,11.08-2.56-3.05-5.1-6.09-7.65-9.15-.37-.45-.71-.92-1.55-1.1-2.94,2.26-5.63,4.82-8.7,6.93-.76-.09-1.13-.38-1.42-M .76-4.1-4.92-7.41-10.37-11.59-15.2-3.34,1.72-6.34,3.68-9.57,5.54-.41,.24-.81,.49-1.35,.47-4.24-6.07-8.72-12.16-12.03-18.75,3.72-1.66,7.1-4.04,10.73-5.84,.93,.39,1.17,1.03,1.53,1.6,3.66,5.32,6.59,11.2,10.7,16.18,.65,.02,1.09-.23,1.48-.53,2.66-2.05,5.35-4.24,8.03-6.22,.92,.13,1.19,.62,1.52,1.09,3.41,4.63,6.66,9.38,10.19,13.92,.7,1.01,1.76,.26,2.42-.52,2.02-2.27,4.07-4.53,6.04-6.85,.21-.24,.88-.31,1.06-.1,2.35,2.67,4.54,5.48,6.82,8.21Z"/><path class="cls-2" d="M646.68,678.52s0,.05-.01,.07c-.68,4.69-1.19,9.52-2.68,14.0M 2-3.26-.71-6.18-2.12-9.37-3.02-1.77-.6-2.05,6.98-2.57,8.38-.28,1.49-.6,2.97-.9,4.46-.09,.43-.7,.64-1.25,.43-3.07-1.02-5.91-2.71-9.02-3.55-.21-.02-.6,.14-.64,.26-1.18,4.09-1.67,8.26-2.98,12.34-1.55,0-2.54-.83-3.69-1.34-2.38-.96-4.36-2.6-6.87-3.25-.16,.1-.31,.14-.33,.21-1.57,3.68-1.9,7.82-3.46,11.49-.75,.18-1.19-.07-1.57-.36-3-2.15-5.78-4.58-8.9-6.55-.13-.07-.6,.03-.65,.14-.34,.69-.66,1.4-.91,2.12-.88,2.49-1.72,4.98-2.59,7.46-.23,.63-.71,1.47-1.51,1.07-2.3-1.85-4.62-3.63-6.81-5.58,2.48-3.24,5.07-6.38,7.77-9.43,1,.61,M 3.5,3.97,4.47,2.22,1.13-3.49,2.01-7.07,3.34-10.5h.01c.04-.19,.15-.32,.36-.38h.01c.74-.21,1.26,.58,1.84,.91,2.5,1.97,4.88,4.06,7.52,5.86,.4,.28,1.11,.07,1.23-.39,1.16-3.85,1.82-7.82,3.09-11.62,.18-.06,.32-.14,.4-.12,3.58,1.02,6.15,3.43,9.79,4.5,.24-.23,.63-.45,.7-.71,.4-1.69,.72-3.39,1.1-5.09,.52-2.32,1.08-4.65,1.65-6.97,.04-.15,.33-.26,.61-.46,1.93,.61,3.74,1.62,5.63,2.38,4.69,2.07,4.08,1.69,4.97-2.35,2.86-12.96-.33-10.83,12.12-6.69,.03,.02,.07,.03,.1,.04Z"/><path class="cls-2" d="M771.18,1312.07c7.2-.82,14.39-1.64M ,21.59-2.46,1.93-.16,4.6-.76,2.99,1.71-14.74,25.38-30.53,50.37-46.9,74.83-.47,.08-.98,.23-1.5,.23-8.5-.11-17.03,.29-25.5-.14-.21-1.48,1.28-2.53,1.95-3.75,7.65-10.64,15.03-21.4,22.32-32.2,8.69-12.63,16.74-25.56,25.17-38.28l-.11,.06Z"/><path class="cls-2" d="M977.4,1211.23c6.65-.94,13.42-.27,20.13-.41,.64,.03,1.76,.09,1.85,.88-.13,.85-.2,1.72-.42,2.56-4.72,18.35-9.63,36.64-15.03,54.81-2.09,7.12-4.34,14.2-6.52,21.3-.19,.63-.31,1.27-1.03,1.7,0,0,.1-.06,.1-.06-8.36,.13-16.79-.02-25.06,1.26l.15,.07c9.39-27.15,17.98-54.61M ,25.89-82.18l-.08,.08Z"/><path class="cls-2" d="M1299.31,304.92c29.38,3.86,58.63,8.6,87.69,14.3,.15,.39,.36,.69,.36,.99,0,6.56,0,13.12-.03,19.68-.02,1.89-2.19,.93-3.35,.82-24.8-5.07-49.53-10.16-74.6-13.97-4.68-.91-9.59-1.09-14.11-2.53l.07,.09c-.22-3.21,1.32-6.56,1.75-9.78,.54-2.63,1.04-5.27,1.54-7.9,.12-.64,.29-1.26,.79-1.79l-.11,.08Z"/><path class="cls-2" d="M142.84,1134.84c-28.64-3.11-57.14-8.26-85.46-13.49-1.55-.34-3.72-.32-3.4-2.39,.04-6.35-.03-12.7,.08-19.05,.05-.83,.61-1.2,1.55-1,3.13,.64,6.26,1.28,9.37,1.95,M 27.06,5.87,54.49,10.42,81.87,14.73l-.12-.11c-1.41,6.48-3.03,12.93-4.05,19.48l.15-.11Z"/><path class="cls-2" d="M476,659.09v.03s-.03,.02-.05,.03l.05-.06Z"/><path class="cls-2" d="M551.31,686.97c-2.63,3.2-5.16,6.49-7.59,9.84-2.21-2.73-4.25-5.57-6.56-8.21-1.07-.62-1.66,1.17-2.25,1.79-1.4,1.96-2.77,3.94-4.18,5.9-.39,.47-1.02,1.34-1.73,.99-3.28-3.53-5.67-7.83-8.57-11.67-.9-1.14-1.32-2.53-2.75-3.19-2.26,2.18-4.33,4.41-6.55,6.6-.66,.51-1.61,1.74-2.5,1.04-3.35-4.58-6.07-9.61-9.17-14.36-.74-1.06-1.05-2.3-2.27-2.97-3.09,2.15M -5.8,4.59-8.99,6.6-.59,.39-1.21,.22-1.6-.4-3.67-6.52-7.67-13.08-10.6-19.81,3.66-2,6.71-4.6,10.11-6.84,1.07-.3,1.4,1.45,1.92,2.11,3.1,5.8,5.73,11.9,9.32,17.41,.75,.03,1.17-.25,1.53-.56,2.47-2.12,4.82-4.32,7.12-6.61,.24-.22,.66-.31,.98-.46,4.01,5.21,6.53,11.44,10.46,16.75,1.11,.92,2.4-1.61,3.16-2.28,1.6-1.99,3.14-4.01,4.71-6.02,.22-.28,.77-.29,.99-.04,2.93,3.94,5.46,8.18,8.28,12.19,.68,.7,1.34,2.6,2.54,2.01,9.16-12.49,3.56-12.73,14.19,.19Z"/><path class="cls-2" d="M611.49,685.56c-.52,2.23-1.11,4.44-1.71,6.66-1.01,1.1M 5-3.08-1.44-4.02-2,1.87-1.59,3.78-3.14,5.73-4.66Z"/><path class="cls-2" d="M625.22,675.91c-.55,2.29-1,4.59-1.54,6.88-.13,.5-.22,1.06-.89,1.35-2.13-.41-3.82-1.84-5.76-2.71,2.67-1.91,5.4-3.75,8.19-5.52Z"/><path class="cls-2" d="M626.45,670.14s-.05-.03-.07-.04v-.02l.07,.06Z"/><path class="cls-2" d="M1048.73,359.22c1.68-4.25,4.15-8.16,6.19-12.25,.43-.99,1.53-2.48-.38-2.43-13.97,.67-27.93,1.46-41.85,2.75-4.68,.41-9.36,.84-14.02,1.4-.66,.07-1.33,.18-2.09-.18,2.27-5.09,5.7-9.69,8.44-14.56l-.1,.06c19.53-1.86,39.06-4.02,58.M 68-4.63,1.25,.33,.18,1.5-.12,2.2-2.13,4.06-4.76,7.92-6.57,12.13-.05,.13,.19,.46,.35,.48,5.36,.31,10.77-.14,16.14-.18,16.84-.57,33.68,.04,50.52,.34l-.15-.1c-2.25,5.23-4.49,10.64-7.28,15.59l.1-.05c-22.66-.5-45.33-1.05-68.02-.67l.16,.08Z"/><path class="cls-2" d="M1148.03,1317.86c.33,.5,.27,1.04,.2,1.58-.41,3.1-.79,6.21-1.23,9.31-1.89,13.7-3.97,27.37-6.23,41.02-.85,5.12-1.71,10.24-2.57,15.36-.09,1.05-1.31,1.44-2.25,1.38-7.95,0-15.89-.01-23.84-.02-.64,0-1.89-.13-1.75-.9,3.65-19.35,7.57-38.66,10.66-58.12,.62-3.62,1.27-7.M 25,1.84-10.88,.16-1.04,.56-2.12-.04-3.17,0,0-.14,.08-.14,.09,7.9,.73,15.73,2.63,23.59,3.82,.64,.11,1.23,.4,1.84,.61l-.08-.07Z"/><path class="cls-2" d="M317.66,126.38c-8.46-1.47-17.07-2.43-25.38-4.58l.09,.07c1.97-18.53,5.13-37,8.11-55.42,.62-3.73,1.22-7.46,1.85-11.19,.17-1.63,1.31-2.11,2.85-1.98,7.67,0,15.34,.02,23.01,.05,1.14,.06,2.4,.08,2.01,1.62-4.58,23.75-9.58,47.55-12.67,71.5l.13-.09Z"/><path class="cls-2" d="M504.97,960.42c14.45-.49,28.79-2.27,43.13-3.85l-.1-.06c2.16,2.84,4.32,5.69,6.47,8.53,.34,.45,.75,.9,.61M ,1.52-13.01,3.05-26.67,3.83-39.98,5.3-2.11,.24-2.19,.38-1.2,2.03,1.85,3.13,4.07,6.28,4.85,9.85l.14-.14c-16.4,1.35-32.76,2.44-49.22,2.82-.02,3.27,1.37,6.37,1.95,9.58,.2,.84,.48,1.68,.25,2.56l.1-.09c-19.45,.84-38.88-.06-58.32-.62l.08,.07c.13-4.94-1.52-9.65-3.21-14.31l-.1,.09c18.87,1.43,37.79,2.72,56.74,2.54,3.37,.2-.09-3.8-.51-5.26-1.06-2.09-2.14-4.17-3.22-6.26-.21-.41-.31-.81-.08-1.24,16.21-.48,32.53,.13,48.74-1.57-.04-.39,.04-.74-.11-1-2.17-3.59-4.58-7.06-6.85-10.59l-.16,.1Z"/><path class="cls-2" d="M548,956.5s.03,M 0,.04-.01c.02,.03,.04,.05,.06,.08l-.1-.06h0Z"/><path class="cls-2" d="M548.81,956.36c-.26,.05-.51,.09-.77,.13-2.45-3.3-5.17-6.47-7.54-9.8-.06-.08-.01-.21-.01-.43l.72-.15c2.43,3.5,4.97,6.92,7.6,10.25Z"/><path class="cls-2" d="M658.64,851.69c-3.52,3.02-7.33,5.71-10.97,8.58-.58,.44-1.3,.79-1.54,1.47,.32,.51,.97,.68,1.53,.92,2.4,.98,4.82,1.92,7.22,2.9,1.17,.47,1.19,.85,.13,1.64-4,2.93-8.27,5.52-12.56,8.12-.5,.45-2.32,1.04-1.83,1.8,2.7,1.98,6.35,2.74,8.96,4.78-.27,.69-1.02,1-1.65,1.38-4.76,2.82-9.62,5.53-14.67,8.02-.52,M .39-2.04,.67-1.72,1.49,2.47,1.88,5.32,3.28,7.95,4.95,.46,.28,.45,.85,0,1.09-6.68,3.39-13.73,6.05-20.76,8.63-.49,.18-.91,.42-.98,1.01,2.67,2.21,6.05,3.82,8.5,6.44-8.37,3.68-17.25,6.07-26,8.89-.3,.1-.43,.62-.19,.84,1.89,1.68,3.79,3.35,5.67,5.04,.7,.63,1.62,1.14,1.93,2.01-.41,.47-1.02,.67-1.66,.88-6.15,2-12.48,3.56-18.81,5.15-2.54-2.89-4.98-5.87-7.33-8.94,6.28-1.47,12.61-2.75,18.72-4.73-.22-1.02-1.19-1.51-1.87-2.14-1.42-1.31-3.04-2.46-4.49-3.72-.68-.62-1.78-1.03-1.81-2.07,8.27-2.54,16.75-4.55,24.88-7.46,1.03-.38,1.2-.M 89,.43-1.44-2.12-1.49-4.26-2.97-6.38-4.46-.5-.36-.97-.74-1.45-1.12-.88-.91,2.95-1.57,3.55-1.97,5.3-1.86,10.67-3.58,15.79-5.76,.83-.35,1.63-.74,2.4-1.16,.14-.08,.2-.46,.09-.57-2.47-1.89-5.42-3.17-8.08-4.8-.46-.26-.76-.57-.72-1.15,5.71-2.42,11.5-5.1,16.83-8.16,.46-.33,1.58-.77,1.16-1.43-2.87-1.62-5.94-2.96-8.9-4.42-.31-.15-.31-.66-.02-.85,4.02-2.54,8.15-4.93,12.2-7.43,1.03-.7,2.17-1.16,2.84-2.25-3.29-1.76-6.96-2.73-10.24-4.42,.5-1.12,1.67-1.54,2.54-2.19,.89-.65,1.86-1.24,2.77-1.88,2.93-1.9,5.4-4.19,8.3-6.16,3.43,1.16M ,6.75,2.3,10.01,3.56,.47,.18,.6,.77,.24,1.09Z"/><path class="cls-2" d="M1303,284.44c.53-.22,.72-.63,.81-1.05,1.34-5.71,2.7-11.41,3.93-17.14,.57-1.73,3.63-.6,5.04-.71,21.34,2.2,42.64,4.73,63.88,7.7,3.18,.44,6.36,.92,9.53,1.39,.69,.1,1.15,.55,1.19,1.13,.13,6.35,0,12.7,.03,19.06,0,.63,.16,1.3-.48,1.88-18.24-2.25-36.39-6-54.72-8.01-5.44-.72-10.89-1.43-16.34-2.11-3.32-.42-6.66-.79-9.99-1.18-1.08-.12-2.12-.31-2.9-1l.02,.05Z"/><path class="cls-2" d="M138.02,1155.09c-1.53,5.89-2.87,11.82-4.13,17.75-.28,1.74-1.05,1.73-2.61,M 1.63-25.75-2.29-51.37-5.63-76.94-9.36-.67-.87-.54-1.84-.57-2.86,.02-5.59,.06-11.18,.1-16.78-.11-2.93,1.14-2.14,3.37-2,16.62,2.67,33.22,5.43,49.93,7.54,8.89,1.19,17.79,2.26,26.7,3.32,1.46,.17,2.95,.26,4.28,.85,0,0-.12-.1-.12-.1Z"/><path class="cls-2" d="M167.88,1001.77c.78-5.56,1.6-11.11,2.41-16.66,.11-.67,.3-1.48,1.22-1.33,31.21,9.08,62.97,17.28,95.03,23.81l-.1-.08c-.99,5.47-2.79,10.82-4.05,16.25l.13-.07c-31.84-6.17-63.67-12.94-94.74-22.01l.1,.08Z"/><path class="cls-2" d="M161.38,1039.29c1.58-6.15,2.49-12.57,3.26-1M 8.87l-.12,.12c30.82,7.29,61.77,14.05,93.13,19.4l-.09-.1c-1.25,5.46-3.33,10.81-4.86,16.24l.14-.08c-30.8-3.61-61.25-10.51-91.53-16.8l.07,.09Z"/><path class="cls-2" d="M1199.82,1327.52c-1.65,14.47-2.68,28.99-4.52,43.44-.4,3.54-.76,7.08-1.17,10.62-.16,1.39-.41,2.77-.64,4.16-.07,.42-.58,.74-1.12,.78-7.81,.18-15.62,0-23.43,.03-.84-.13-2.46,.17-2.89-.65-.06-.53-.08-1.08,0-1.61,3.09-20.61,5.63-41.29,7.99-61.99l-.12,.11c8.64,1.81,17.46,3.08,26,5.19l-.08-.08Z"/><path class="cls-2" d="M266.08,117.79c-.16-.46-.58-.7-1.13-.8-7.M 33-1.37-14.66-2.79-21.98-4.21-.8-.15-1.89-.5-1.78-1.45,.73-11.08,1.85-22.13,3.11-33.17,.88-7.83,1.81-15.65,2.73-23.47,0-1.36,1.33-1.51,2.48-1.48,7.41,0,14.82,.02,22.23,.03,3.76-.19,2.85,1.04,2.64,3.95-1.78,13.16-3.8,26.29-5.36,39.48-.5,4.18-.99,8.36-1.47,12.54-.46,2.89-.06,5.92-1.51,8.6,0,0,.04-.01,.04-.01Z"/><path class="cls-2" d="M241.47,1089.6c-27.16-2.22-54.14-7.06-81-11.59-1.58-.27-3.14-.59-4.71-.9-.43-.08-.92-.63-.87-.98,.97-6.09,2.21-12.14,3.29-18.21l-.13,.11c29.52,5.69,59.17,11.1,89.08,14.87l-.1-.1c-1.53,5.M 69-3.86,11.25-5.67,16.89l.11-.09Z"/><path class="cls-2" d="M780.87,529.52c-6.32,4.13-12.98,7.89-19.16,12.3,.25,.37,.34,.73,.62,.89,2.42,1.53,5.09,2.77,7.4,4.47,.14,.12,.22,.46,.12,.55-4.8,3.65-9.87,6.99-14.44,10.81-.49,.55-2.13,1.28-1.16,2.05,2.66,1.26,5.35,2.45,7.95,3.81,.26,.13,.31,.67,.08,.87-4.47,4.1-9.36,7.68-13.49,12.11,3.07,1.54,6.48,2.3,9.4,3.67,.09,.73-.43,1.1-.83,1.51-3.52,3.74-7.35,7.09-10.61,11.08,14.16,5.53,11.79-.19,1.57,14.03l-9.21-.09c-.97-.26-1.95-.23-2.64-1.09,2.81-4.45,6.54-8.14,9.48-12.5-2.57-1.M 39-5.45-1.84-8.19-2.8-.53-.16-.93-.42-1.21-.92,3.12-4.13,7.04-7.92,10.71-11.65,.34-.34,.61-.71,.5-1.3-2.73-1.4-5.94-2.27-8.89-3.75,3.92-4.84,9.3-8.67,13.77-12.96-.08-.55-.43-.83-.91-1.07-2.53-1.24-5.03-2.51-7.54-3.76-.6-.03-.97,.28-1.31,.6-4.83,4.24-9.16,8.99-14.2,12.94-2.94-1.14-5.65-2.73-8.63-4.01-5.02,4.46-8.43,9.77-13.25,14.43-3.04-1.21-5.88-2.59-8.68-4.16,3.67-5,8.01-9.27,12.01-14,.86-.97,1.25-.96,2.65-.21,2.01,1.09,4.02,2.16,6.05,3.22,.73,.38,1.28,.31,1.77-.19,4.2-4.55,8.75-8.77,13.34-12.96,.49-.45,1.17-.49,1M .82-.15,2.38,1.24,4.68,2.56,7.09,3.73,1.22,.59,2.08-.54,2.97-1.15,4.89-3.86,10-7.48,14.76-11.49-.06-.2-.03-.49-.19-.59-2.72-1.61-5.19-3.67-8.1-4.93-6.27,3.91-11.66,9.17-17.54,13.58-2.31-1.14-6.21-3.48-7.78-4.64-.28-.21-.36-.67-.16-.88,5.36-4.86,10.88-9.7,16.93-13.89,3.15,1.36,5.55,3.72,8.55,5.47,6.73-4.4,13.18-8.97,20.08-13.05,2.12,1,5.38,3.32,8.5,6.07Z"/><path class="cls-2" d="M817.23,696.61l.09,.03s0,.02,0,.03l-.08-.06Z"/><path class="cls-2" d="M832.74,690.95c-5.25,14.94-.71,10.13-15.42,5.69,1.68-3.97,2.01-8.48,4M .05-12.26-4.03-1.63-8.15-3.03-12.22-4.55,.53-1.64,1.05-3.28,1.58-4.93,3.78,2.33,7.48,4.81,11.07,7.42-.25,.69-.65,1.31-.32,2.05,2.3,.94,4.59,1.93,6.87,2.95,1.48,1.18,2.94,2.39,4.39,3.63Z"/><path class="cls-2" d="M884.5,665.3c-2.73,2.85-5.86,4.98-8.61,7.87-1.74-1.02-3.18-2-4.8-3.12-2.36-2.33-4.77-4.6-7.23-6.81,2.14-2.5,4.31-4.88,6.74-7.13-.26-.31-.41-.63-.7-.81-4.02-2.5-8.23-4.75-12.14-7.41,1.92-2.26,4.3-3.99,6.77-5.67,.9-.61,2.06-1.06,2.48-2.2-3.9-2.77-8.64-4.61-12.43-7.49,2.71-2.15,3.82-2.77,11.63-6.47,.6-.07,.99,.M 2,1.42,.47,3.29,2.06,6.6,4.1,9.88,6.16,.73,.45,1.55,.85,1.97,1.66-3.7,1.97-7.74,3.49-11.22,5.59-.02,.57,.28,.89,.72,1.17,3.36,2.16,6.72,4.32,10.06,6.5,.7,.46,1.54,.83,1.92,1.68-2.68,1.7-5.66,3.26-8.13,5.23-1.75,1.37-1.75,1.43,.09,2.69,3.88,2.71,7.83,5.2,11.58,8.09Z"/><path class="cls-2" d="M150.95,1096.03c27.85,4.91,55.97,8.17,84.08,11.15-1.99,5.23-4.43,11.77-6.61,17.43l.12-.07c-27.37-1.76-54.62-5.35-81.8-9.06l.12,.11c1.46-6.53,2.32-13.23,4.21-19.65,0,0-.12,.1-.12,.1Z"/><path class="cls-2" d="M1313.16,244.77c-.19-1M .62,.51-3.15,.85-4.71,1.23-5.09,2.27-10.28,3.87-15.27l-.08,.07c6.25-.6,12.58,.63,18.85,.92,16.06,1.15,32.08,2.61,48.09,4.27,1.21,.16,2.92,.16,2.72,1.72,.02,3.44,.02,6.88,.01,10.32,0,2.9-.02,5.8-.03,8.71,0,.53,.02,1.07-.52,1.54-12.5-.96-24.96-2.98-37.46-4.15-12.1-1.39-24.34-1.89-36.4-3.52l.1,.09Z"/><path class="cls-2" d="M123.43,1214.96c-21.71-.31-43.77-3.21-65.45-5.06-1.66-.26-4.7,.18-4.42-2.17,0-1.94,.05-3.88,.06-5.81,.02-4.2,.03-8.4,.06-12.6,0-.63-.08-1.3,.69-1.86,22.35,2.55,44.74,5.25,67.19,6.94,1.74,.15,3.48,.2M 8,5.22,.46,1.26,.13,1.59,.52,1.39,1.53-1.51,6.22-2.75,12.57-4.79,18.64l.08-.07Z"/><path class="cls-2" d="M1332.76,1370.74c.15-5.16-.05-10.35,.34-15.5,.63-1.09,2.6-.26,3.63-.24,7.2,1.38,14.35,2.96,21.56,4.26,2.69,.67,2.13-1.76,2.19-3.46,.02-7.43-.27-14.87-.04-22.29,.02-.42,.69-.74,1.18-.56,3.43,1.25,6.85,2.52,10.28,3.77,4.78,1.74,9.57,3.47,14.35,5.2,.96,.35,1.42,.92,1.41,1.77-.01,1.94,.01,3.88,.01,5.82,0,4.2,0,8.4,0,12.6-.13,.88,.34,2.42-1,2.43-8.19-1.1-16.26-3.02-24.39-4.48-1.15-.22-1.67,.15-1.72,1.19-.07,8.08-.01,M 16.16-.12,24.24,.11,1.74-1.71,1.68-3.1,1.65-7.28,0-14.56-.02-21.84-.03-1-.04-2.74,.14-2.83-1.18-.15-5.06,.07-10.12,.09-15.19h0Z"/><path class="cls-2" d="M1349.41,96.78c-12.27-.05-24.53,.75-36.79,.43,0-.35-.11-.7,.02-.97,2.92-6.36,5.9-12.7,8.77-19.08,1.32-2.41-1.29-1.85-2.81-1.94-8.35,.12-16.7,.25-25.05,.36-.82-.15-3,.37-2.92-.84,4.59-7.32,9.1-14.75,14.04-21.85,8.48-.33,16.97-.04,25.46-.13,2.83-.12,1.62,1.18,.99,2.91-2.56,5.78-5.13,11.56-7.7,17.34-1.1,1.99-.17,2.04,1.68,2.03,9.96-.16,19.95-.04,29.9-.35l-.13-.09c-.65M ,6.06-2.84,11.98-4.07,17.98-.42,1.47-.38,3.1-1.48,4.27l.1-.07Z"/><path class="cls-2" d="M799.32,541.24c-.34,.65-1.12,.9-1.77,1.27-5.42,3.21-11.03,6.13-16.34,9.49-.4,.28-.34,.83,.16,1.09,2.71,1.41,5.42,2.8,8.08,4.28,.58,.74-1.23,1.41-1.72,1.85-4.41,2.68-8.49,5.65-12.61,8.59-.48,.35-.98,.69-1.22,1.3,3.01,1.66,6.53,2.58,9.44,4.25-.13,.79-.83,1.17-1.41,1.6-3.66,2.71-7.23,5.49-10.55,8.46-1.85,1.58-.72,1.74,.94,2.38,2.34,.81,4.7,1.6,7.05,2.41,.66,.23,.79,.85,.29,1.32-3.61,3.58-7.52,6.7-10.89,10.53,3.35,1.21,6.52,2.09,9.8M 6,3.16,.56,.18,.78,.72,.46,1.06-1.09,1.17-2.18,2.33-3.25,3.52-.29,.04-.59,.08-.88,.11l-13.28-.12c8.99-10.41,7.91-6.48-3.58-10.76-.33-.59,.08-.91,.37-1.23,3.26-3.62,7.02-7.08,10.58-10.46-.14-.62-.64-.81-1.1-.97-2.86-1.04-5.69-1.92-8.52-3.06,.29-1.23,1.4-1.79,2.27-2.62,3.35-2.8,6.71-5.6,10.07-8.39,.46-.38,1-.73,.93-1.47-2.81-1.26-5.95-2.33-8.69-3.9-.15-.09-.25-.41-.17-.56,4.75-4.31,10.56-7.58,15.69-11.46-.01-.6-.34-.9-.82-1.14-1.92-1-3.83-2-5.74-3.01-.52-.42-1.95-.74-1.67-1.54,5.71-4.53,12.57-7.78,18.74-11.59,.37,.08M ,.68,.07,.87,.18,2.74,1.86,5.98,3.26,8.41,5.43Z"/><path class="cls-2" d="M189.3,102.26c-.68-.5-.54-1.39-.57-2.14,.18-4.31,.37-8.61,.57-12.92,.47-7.42,.87-14.85,1.33-22.27,.27-3.65,.41-7.33,.84-10.96,.27-1.06,1.77-.92,2.65-.97,7.68,.01,15.37,.04,23.05,.07,.75-.05,1.6,.15,1.89,.87-.77,11.35-2.08,22.78-2.79,34.17-.43,5.7-.83,11.4-1.26,17.1-.05,.63,.02,1.31-.71,1.8-8.4-1.24-16.63-3.52-25.07-4.79-.02-.01,.06,.06,.06,.06Z"/><path class="cls-2" d="M1252.55,1337.94c-.5,.55-.56,1.2-.6,1.85-.11,1.94-.22,3.87-.28,5.81-.24,7.9M 7-.81,15.92-1.4,23.88-.28,5.27-.65,10.54-1.05,15.81-.05,.53-.24,1.21-.85,1.33-8.04,.51-16.15,.02-24.22,.16-1.04,0-2.66,0-2.57-1.36,.53-9.04,1.67-18.04,2.34-27.07,.83-8.46,.78-17.07,2.06-25.45,8.95,1.16,17.78,3.61,26.7,5.16,0,0-.13-.1-.13-.1Z"/><path class="cls-2" d="M1244.37,241.5c22.97,.28,45.86,2.13,68.79,3.27l-.1-.09c-1.62,6.43-3.24,12.86-4.89,19.28-.46,1.77-4,.56-5.41,.72-2.68-.2-5.36-.43-8.03-.66-17.81-1.69-35.67-2.55-53.54-3.27-1.18-.29-5.49,.37-4.85-1.49,2.72-5.91,4.91-12.22,8.14-17.84l-.11,.07Z"/><path clasM s="cls-2" d="M196.62,1198.39c-12.23-.58-24.49-.83-36.72-1.49-5.51-.27-11.02-.66-16.52-1.01-4.43-.29-8.86-.61-13.29-.92-1.35-.07-1.27-1.1-1.05-2.01,1.39-5.59,2.78-11.19,4.18-16.78,.14-.55,.47-1.15,1.15-1.18,9.41,.32,18.76,1.47,28.15,2.04,13.95,1.17,27.95,1.44,41.91,2.35,.8,.21,.66,1.1,.36,1.67-2.38,5.38-4.77,10.75-7.16,16.13-.23,.51-.49,1-1.15,1.28-.01,0,.12-.06,.12-.06Z"/><path class="cls-2" d="M112.37,1257.38c-.33-.16-.66-.43-1-.45-2.82-.17-5.65-.29-8.47-.43-13.58-.64-27.17-1.23-40.75-2.07-1.88-.11-3.75-.32-5.63-.M 42-3.38-.19-3.39-.21-3.37-2.8,.05-5.6,.09-11.2,.14-16.8,.06-1.09-.2-2.62,1.45-2.54,3.36,.12,6.71,.44,10.06,.71,17.16,1.54,34.36,2.54,51.57,3.33,1.3,.08,1.76,.47,1.58,1.39-.57,2.88-1.37,5.71-2.09,8.56-.78,3.06-1.57,6.12-2.32,9.18-.21,.86-.48,1.68-1.23,2.35,0,0,.06-.02,.06-.02Z"/><path class="cls-2" d="M1194.07,366.88c.24,.66-.03,1.27-.23,1.9-1.44,5.02-3.57,9.91-4.51,15.03l.09-.09c-26.35-3.7-52.84-6.69-79.4-8.33,2.15-5.21,4.59-10.31,6.56-15.59l-.1,.05c25.96,1.79,51.91,3.86,77.73,7.14l-.15-.12Z"/><path class="cls-2" dM ="M331.12,1064.38c-1.6,5.36-4.4,10.4-6.45,15.63l.11-.07c-25.97-1.78-51.94-3.66-77.75-7.14l.1,.1c1.94-5.62,3.42-11.42,5.7-16.91l-.14,.08c26,4.26,52.29,6.46,78.55,8.42l-.13-.12Z"/><path class="cls-2" d="M1183.54,399.84c.03,.42,.18,.87,.07,1.26-1.31,4.73-2.66,9.45-4.01,14.16-.54,1.84-4.35,.12-5.77,.09-24.88-4.32-49.97-8.24-75.16-10.29l.13,.08c1.87-4.99,3.43-10.1,5.55-15,26.57,2.32,53.03,5.89,79.36,9.81l-.17-.12Z"/><path class="cls-2" d="M1322.73,204.02c-1.51,6.97-3.58,13.84-4.93,20.84l.08-.07c-7.5-1.31-15.32-.86-22.92M -1.44-13.06-.52-26.12-1.09-39.19-1.2-2.45-.09-2.84-.03-1.7-2.5,2.69-5.86,5.53-11.66,8.09-17.58l-.09,.06c20.21,.86,40.65,.1,60.75,1.98l-.1-.09Z"/><path class="cls-2" d="M179.17,1237.68c-19.76-.78-39.58-.45-59.33-1.69-1.3-.07-1.29-1.1-.94-2.02,1.47-6.34,3.54-12.57,4.51-19.01l-.08,.06c21.14,2.05,42.62,1.92,63.88,2.69,.31,.02,.73,.45,.63,.68-2.74,6.52-6.2,12.76-8.77,19.34l.09-.06Z"/><path class="cls-2" d="M436.03,360.73c-1.33-.36-2.67-.14-3.98,0-4,.41-8.03,.37-12.05,.48-.95,.03-1.88-.02-2.73-.44-.01,0,.04,.05,.03,.04,.M 2-.26,.56-.5,.61-.78,.79-4.79,1.03-9.65,1.62-14.47,1.77-15.12,3.79-30.24,6.47-45.22,.1-.54,.94-.84,1.53-.83,5.52-.12,11.04-.24,16.56-.35,.78-.05,2.22,.08,2.08,.98-1.95,12.39-4.57,24.68-6.42,37.09-1.11,7.15-1.99,14.33-2.9,21.51-.1,.74-.16,1.51-.91,2.07l.09-.07Z"/><path class="cls-2" d="M1023.11,1078.99c-.96,1.08-.73,2.68-.99,4.03-.67,6.33-1.26,12.67-1.99,18.99-1.59,12.43-3.51,24.83-5.55,37.2-.18,1.29-1.97,.93-2.96,1-4.17,.09-8.35,.18-12.52,.26-1.19-.19-4.4,.72-4.67-.77,1.58-11.01,4.23-21.89,5.66-32.94,.74-4.81,1.49-M 9.61,2.18-14.43,.82-4.35,.65-8.88,2.01-13.11l-.11,.08c5.28-.63,10.61-.65,15.92-.79,1.07-.03,2.14-.04,3.06,.52,0,0-.04-.05-.04-.05Z"/><path class="cls-2" d="M161.4,138.76c-.07-13.73-.08-27.52,.64-41.24,.02-.41,.65-.78,1.12-.68,8.71,1.79,17.47,3.37,26.13,5.41,.01,0-.07-.06-.05-.05-.47,.28-.62,.67-.65,1.11-.14,2.25-.34,4.51-.41,6.76-.42,12.57-.57,25.15-1.02,37.72-.13,.76-1.37,.54-1.94,.24-7.93-3.17-16.06-5.96-23.89-9.35l.08,.08Z"/><path class="cls-2" d="M1192.55,222.83c19.87-.69,39.77-1,59.65-.56,.27,1.77-1.07,3.31-1.M 61,4.97-2.03,4.77-4.39,9.42-6.22,14.27l.11-.08c-20.85-.39-41.72-.07-62.58,.02-.77-.28-.14-1.15,.11-1.64,3.54-5.68,7.09-11.36,10.64-17.03l-.09,.06Z"/><path class="cls-2" d="M1279.05,1301.04c.32,13.68,.05,27.54-.41,41.24-.05,.45-.62,.79-1.11,.69-8.37-1.5-16.65-3.43-24.99-5.03,0,0,.13,.1,.13,.11-.58-.67-.42-1.44-.4-2.19,.13-4.74,.31-9.48,.43-14.21,.32-9.9,.3-19.82,.8-29.71,.19-.59,1.22-.41,1.7-.19,8.05,2.97,15.97,6.21,23.94,9.37l-.08-.07Z"/><path class="cls-2" d="M670.87,824.67c3.54,.66,6.93,1.71,10.38,2.59,.54,.14,.6M 8,.58,.3,1.03-2.89,3.52-5.86,6.99-8.88,10.41-.31,.35-.1,.91,.41,1.07,2.52,.76,5.04,1.5,7.55,2.27,1.65,.51,2.16,.82,.79,2.24-2.72,2.95-5.59,5.8-8.63,8.55-.61,.56-1.37,1.06-1.49,1.96,3.18,1.29,6.63,2.21,9.94,3.7-4.27,4.13-8.86,7.6-13.33,11.48-.23,.19-.19,.74,.06,.86,2.69,1.47,5.78,2.24,8.4,3.83,.35,.34,.08,.85-.28,1.11-4.87,3.78-10.07,7.14-15.07,10.76-.43,.3-1,.32-1.49,.07-2.87-1.67-6.19-2.71-8.76-4.76,5.05-3.7,10.84-6.92,15.65-10.95-.1-.55-.47-.82-.97-1.03-2.71-1.13-5.5-2.24-8.15-3.46,0-.29-.11-.56,.02-.68,.61-.57,1M .24-1.13,1.92-1.64,3.44-2.58,6.79-5.24,9.95-8.04,.45-.4,.92-.79,.83-1.47-3.14-1.34-6.71-2.07-9.75-3.54-.03-.73,.53-1.08,.95-1.47,3.27-3.15,6.72-6.14,9.89-9.39,.47-.6-.41-.99-.87-1.16-3.15-.94-6.3-1.87-9.37-2.78-.7,.03-.99,.42-1.32,.75-3.44,3.38-7.11,6.79-11.03,9.74-3.63-.6-6.98-2.44-10.51-3.52-.46-.17-.61-.82-.27-1.11,3.5-3.06,7.33-5.9,10.48-9.31-.36-.62-.98-.81-1.6-1.01-3.19-1.23-6.63-1.75-9.56-3.53,3.46-3.29,6.57-6.52,9.61-10.1l-.1,.04c3.7,.66,7.36,2.05,11.03,2.99,.34,.1,.61,.35,.98,.56-2.63,3.61-5.96,6.68-8.97,9M .99-.32,.34-.12,.92,.38,1.07,3.14,.97,6.28,1.93,9.42,2.89,.46,.16,1.13,0,1.5-.19,3.7-3.33,6.89-7.18,10.06-10.9l-.09,.07Z"/><path class="cls-2" d="M1281.56,161.34c-16.21,.57-32.48,1.16-48.7,1.52-1.01-.35,.28-1.6,.53-2.19,4.2-6.24,8.45-12.45,12.62-18.7l-.12,.05c9-.16,17.99-.57,26.98-.93,5.36-.36,10.74-.37,16.11-.42,.65,0,1.33-.06,1.91,.28,.28,.56-.05,1.05-.28,1.54-3.04,6.31-5.89,12.71-9.13,18.92l.07-.07Z"/><path class="cls-2" d="M436.04,360.72l.02,.02s-.07,.04-.1,.05l.03-.03s.03-.03,.04-.03h.01Z"/><path class="cls-2"M d="M449.34,412.15l-.07,.07v-.06s.05,0,.07,0Z"/><path class="cls-2" d="M455.28,358.63c-1.74,13.55-3.91,27.05-5.09,40.67-5.74-.33-11.5-.33-17.24,.04,.6-8.63,1.12-17.25,2.2-25.84,.41-3.75,.82-7.5,1.23-11.25,.06-.52,.13-1.05-.32-1.51,5.64-1.13,11.76-.5,17.26-2.35,.6-.19,1.75-.62,1.96,.24Z"/><path class="cls-2" d="M990.83,1027.9c5.44-1.18,11.06-1.89,16.61-2.23,.96,.13,.82,1.2,.84,1.92-.54,17.3-2.84,34.49-4.12,51.72l.11-.08c-5.3,.55-10.79,.31-15.94,1.75-1.13,.14-3.35,1.2-2.99-.86,1.98-14.1,4.04-28.19,5.19-42.38,.26-2.79M ,.5-5.58,.75-8.37,.05-.54,.05-1.08-.33-1.55l-.12,.09Z"/><path class="cls-2" d="M90.76,1343.29c-1.36-.59-2.89-.33-4.34-.4-9.57-.04-19.14-.05-28.71-.09-5.56-.19-4.99,.35-4.98-4.06,.13-5.81-.14-11.65,.29-17.44,.45-1.14,2.21-.59,3.2-.73,6.06,.11,12.12,.25,18.19,.33,7.54,.26,15.13-.22,22.63,.41,0,0-.09-.05-.08-.04-.58,.35-.73,.89-.86,1.4-1.97,6.85-3.06,14.01-5.45,20.7l.11-.08Z"/><path class="cls-2" d="M1349.31,96.84c12.37,.12,24.75-.14,37.12,.23,1.2,.1,1.16,1.22,1.18,2.1,0,6.02-.03,12.04-.05,18.07,.03,.73-.1,1.72-.95,1.M 89-13.97,.01-27.97-.55-41.95-.38l.15,.12c-.27-.51-.22-1.05-.09-1.58,1.42-6.85,4.06-13.57,4.7-20.52l-.1,.07Z"/><path class="cls-2" d="M987.92,363.09c20.25-1.6,40.49-3.31,60.81-3.87l-.16-.08c-2.41,4.77-4.65,9.63-7.23,14.32-19.56,1.02-39.21,1.52-58.74,3.44-.78,.06-1.32-.44-1.05-1,2.07-4.32,4.27-8.59,6.44-12.87l-.08,.06Z"/><path class="cls-2" d="M80.48,79.91c-.47-8.03-.07-16.12-.19-24.17-.16-3.09,.55-2.98,3.42-2.95,6.99,0,13.99,0,20.98,.02,1.67,.05,3.55-.3,3.31,2.05-.16,9.88,.07,19.79-.32,29.66-.28,1-1.97,.6-2.78,.5-8.M 11-1.85-16.56-2.83-24.48-5.18l.08,.07Z"/><path class="cls-2" d="M415.26,463.86s.07,.02,.1,.03v.05l-.1-.08Z"/><path class="cls-2" d="M431.49,460.38c.01,.52-.03,1.05-.05,1.57-3.98,1.08-8.19,1.27-12.28,1.9-1.24,.16-2.53,.42-3.8,.04-.24-6.59-.74-13.18-.75-19.77,5.38-1.46,11.02-2.51,16.75-3.1-.05,6.45-.05,12.91,.13,19.36Z"/><path class="cls-2" d="M431.44,462v-.05l.09-.03-.09,.08Z"/><path class="cls-2" d="M474.26,1010.7c1.27,3.76,1.53,7.95,1.91,11.91,.02,.55-.14,1.04-.67,1.43,0,0,.09-.06,.08-.05-6.1-.28-12.31,.67-18.45,.M 72-13.4,.48-26.84,.64-40.24,.26l.11,.09c-.7-4.54-.54-9.19-1.63-13.65l-.13,.1c19.71-.05,39.52,1,59.18-.67l-.15-.13Z"/><path class="cls-2" d="M964.55,416.13c-.06,.01-.11,.01-.17,.02l.15-.12s.02,.07,.02,.1Z"/><path class="cls-2" d="M1024.38,414.84h-.08s-.01-.07-.02-.1l.1,.1Z"/><path class="cls-2" d="M1026.04,428.3l-.13,.1s-.03-.06-.04-.09c.06-.01,.11-.01,.17-.01Z"/><path class="cls-2" d="M90.65,1343.37c2.41-1.01,5.32-.26,7.9-.52,7.51-.12,15.01-.26,22.52-.38,1.88-.03,3.75-.05,5.63-.04,1.15,0,1.87,.24,1.36,1.33-3.01,6.8M 5-6.74,13.52-9.3,20.51l.13-.07c-.55,.39-1.23,.37-1.9,.39-9.55,.16-19.1,.44-28.65,.39-.72-.09-2.16,.16-2.27-.82,.91-7.06,3.83-13.87,4.7-20.88,0,0-.12,.09-.12,.09Z"/><path class="cls-2" d="M80.4,79.84c-.27,8.28-.07,16.56-.05,24.85-.05,2.06,0,2.7-2.28,1.9-8.51-3.24-17.18-6.07-25.61-9.51-.35-6.57-.05-13.15-.14-19.73,0-.82-.1-2.05,1.01-2.14,9.12,1.01,18.04,3.85,27.15,4.7l-.08-.07Z"/><path class="cls-2" d="M118.76,1364.27c9.72,.64,19.64-.28,29.42-.17,2.04,.03,2.46,.28,1.21,2.14-4.29,6.7-8.59,13.4-12.9,20.09-.52,.91-1.85,M .84-2.82,.86-8.18-.15-16.42,.43-24.57-.15-.54-.22-.43-.99-.25-1.43,3.08-6.88,6.18-13.76,9.29-20.63,.13-.28,.47-.51,.72-.77,.01,0-.12,.07-.12,.07Z"/><path class="cls-2" d="M85.23,1365.49c-.62,4.99-2.25,9.88-3.29,14.81-.59,2.07-.83,4.3-1.68,6.28-.56,.68-1.67,.66-2.5,.68-7.52,0-15.05,0-22.57,0-1.45-.01-2.97,0-2.84-1.87,.03-6.23,.07-12.46,.11-18.68-.14-1.92,1.65-1.58,3.01-1.66,9-.02,18-.03,27-.02,.91,0,1.89-.19,2.75,.47Z"/><path class="cls-2" d="M1354.98,74.68c1.94-5.74,2.98-11.81,4.33-17.71,1.22-4.75,0-4.2,6.17-4.22,6M .33-.02,12.66,0,19,0,1.26,.12,3.32-.4,3.15,1.51,0,6.25,0,12.49-.02,18.74-.05,.64-.04,1.52-.86,1.64-10.61,.2-21.29,.31-31.91-.04,0,0,.12,.09,.12,.09Z"/><path class="cls-2" d="M463.06,686.97c-4-6.21-7.22-12.95-10.93-19.35-.32-.59-.7-1.17-.44-1.84,3.12-.66,7.11-.02,10.4-.21,.52-.02,1.48,0,1.57-.64-1.64-4.45-4.1-8.6-5.97-12.96-1.47-3.22-2.81-6.49-4.2-9.74-.76-1.56,1.44-1.86,2.41-2.46,3.03-1.35,5.83-3.25,8.96-4.29,.73,.23,.76,.82,.96,1.28,3.23,7.55,6.23,15.1,10.12,22.39l.05-.07c-3.37,2.1-6.8,4.13-10.51,5.85-1.16,.4-.94,M 1.3-.45,2.17,3.68,6.38,7,13,10.91,19.24l.15-.11c-4.29,.92-8.76,.58-13.13,.67l.08,.06Z"/><path class="cls-2" d="M707.91,649.21c-1.2,3.94-1.74,7.99-3.03,11.91-.02-.01-.04-.01-.06-.02-3.42-1-7.03-1.29-10.54-1.93,.89-2.93,1.57-5.91,2.31-8.88,3.79-.49,7.56-.85,11.32-1.08Z"/><path class="cls-2" d="M719.48,648.11s-.01,.03-.01,.05c-.04,0-.07,.01-.11,.01,0-.03,.01-.07,.02-.1,.03,.01,.07,.02,.1,.04Z"/><path class="cls-2" d="M742.06,650.38c-.13,.34-.32,.66-.46,.94-3.75,.16-7.14-.86-10.83-1.17-.02-.01-.03-.01-.05-.01,.03-.3,.0M 5-.6,.08-.89,3.78,.25,7.54,.63,11.26,1.13Z"/><path class="cls-2" d="M522.87,994.6c.38,3.67,2.1,7.11,2.48,10.77,.06,1.23-3.57,1.13-4.55,1.42-15.46,1.59-30.99,3.92-46.54,3.91l.15,.13c.05-2.71-.72-5.33-1.29-7.97-.32-1.47-.31-3.01-1.16-4.4l-.1,.09c17.09-.57,34.11-2.07,51.11-3.89l-.11-.07Z"/><path class="cls-2" d="M659.11,944.03c8.06-4.65,16.33-9.07,24.12-13.97,.66,0,1,.34,1.29,.68,1.7,1.94,3.37,3.89,5.06,5.82,.23,.21,.67,.48,1.01,.39,2.09-1.08,4-2.56,5.94-3.86,4.4-3.17,8.75-6.37,13.12-9.56,.61-.51,1.64-1.27,2.32-.57,1.M 72,2.18,3.44,4.36,5.1,6.57,.14,.19-.03,.67-.26,.86-5.9,4.98-12.37,9.27-18.62,13.82-.58,.41-1.13,.88-2,1.04-2.3-2.54-3.44-5.38-6.15-7.61-7.82,4.51-15.33,9.53-23.37,13.64-.77-.03-1.12-.31-1.42-.69-1.59-1.99-3.2-3.98-4.79-5.97-.31-.38-.69-.65-1.28-.68-.02,.02-.07,.08-.07,.08Z"/><path class="cls-2" d="M867.47,430.9s.01,.05,.01,.07l-.09,.03,.08-.1Z"/><path class="cls-2" d="M870.6,441.9s.07-.01,.1-.02c.01,.03,.03,.06,.04,.09l-.14-.07Z"/><path class="cls-2" d="M912.78,421.95s-.07,.01-.11,0c-.01-.03-.01-.06-.02-.09l.13,.09M Z"/><path class="cls-2" d="M915.2,433.56c-14.96,2.22-29.76,5.02-44.5,8.32-1.51-3.55-2.51-7.2-3.22-10.91,14.83-3.79,30.03-6.82,45.19-9.02,.91,3.83,1.63,7.68,2.52,11.52,0,.03,0,.06,.01,.09Z"/><path class="cls-2" d="M518.75,983.74c9.05-1.64,18.28-2.33,27.33-3.97,4.34-.7,8.64-1.58,12.96-2.36,.94-.08,2.26-.62,2.89,.33,1.32,2.81,2.64,5.62,3.94,8.44,.25,.54-.17,1.07-.87,1.23-13.95,2.94-27.98,5.29-42.13,7.19l.11,.07c-.21-.27-.51-.53-.61-.82-1.17-3.41-2.31-6.83-3.47-10.25l-.14,.14Z"/><path class="cls-2" d="M530.87,935.77c2.M 56,3.01,5.12,6.02,7.68,9.02,.31,.37,.5,.74,.32,1.26-6.06,1.23-12.47,1.17-18.63,1.88-7.74,.24-15.52,1.11-23.25,.77l.09,.06c-2.48-3.43-4.97-6.85-7.45-10.28-.38-.53,.03-1.08,.8-1.12,13.52-.13,27.06-.18,40.53-1.54l-.09-.05Z"/><path class="cls-2" d="M787.33,729.68c2.76,.25,5.37,1.32,8.06,1.96,1.13,.39,3.06,1,3.14-.53,.59-3.74,1.18-7.47,1.92-11.18,.56-1.44,2.73-.19,3.8,.06,2.48,.84,4.94,1.69,7.41,2.53l-.09-.09c0,3.19-1.15,6.36-1.59,9.54-.37,1.28-.29,2.86-1.23,3.87-3.19-.73-5.93-2.02-9.06-2.89-.88-.28-1.51,.09-1.66,.9-.67M ,3.93-1.26,7.87-1.96,11.8-.09,.41-.7,.73-1.19,.59-2.52-.72-5.04-1.46-7.56-2.19-.64-.18-1.29-.3-1.99,0-1.09,3.9-1.34,8.06-2.13,12.05-.12,.65-.44,1.44-1.25,1.4-3.41-.37-6.65-2.07-10.09-1.96,.71-.96,.75-2.05,.9-3.11,.53-3.74,1.08-7.47,1.62-11.21,15.3,2.35,9.2,5.41,13.04-11.64l-.1,.1Z"/><path class="cls-2" d="M704.24,914.84c-.27,.37-.41,.69-.68,.9-6.28,4.67-12.58,9.52-19.46,13.54-.34,.05-.81,.07-1.09-.19-2.06-2.09-4.75-3.8-6.44-6.14-.05-.52,.48-.74,.88-1,6.24-4.03,12.44-8.13,18.34-12.62,.41-.3,.4-.86-.01-1.15-2.28-1.66M -4.69-3.19-6.88-4.97-.13-.11-.15-.45-.03-.58,2.68-2.45,5.8-4.48,8.59-6.81,2.57-2.05,5.02-4.2,7.57-6.26,.83-.66,1.72-.06,2.45,.39,5.21,3.1,6.52,3.99,6.27,4.35-4.78,5.15-10.75,9.34-16.24,13.85-.37,.32-.38,.84,.02,1.16,2.26,1.82,4.58,3.55,6.71,5.53Z"/><path class="cls-2" d="M729.44,905.99c1.09-.32,1.6-.98,2.18-1.57,3.76-3.8,7.51-7.6,11.26-11.4,.75-.76,1.5-1.51,2.3-2.24,.12-.11,.47-.08,.72-.07,2.09,1.68,3.87,3.88,5.83,5.75,.34,.34,.3,.8-.08,1.18-4.84,4.9-9.68,9.8-14.53,14.69-.38,.37-1.03,.92-1.59,.61-1.68-1.46-2.84-3.3M 9-4.33-5.03-1.28-1.5-1.66-1.45-2.95-.25-5.03,4.78-10.48,9.32-15.97,13.7-.43,.33-1.11,.34-1.42,.02-1.98-2.03-3.94-4.07-5.89-6.08,.08-.25,.07-.51,.22-.63,5.85-4.58,11.31-9.62,16.96-14.27,.22-.07,.61-.1,.74,0,2.32,1.69,4.56,3.57,6.55,5.59Z"/><path class="cls-2" d="M586.4,993.61c-5.09,1.22-10.18,2.86-15.32,3.71-.57-.13-1.14-.48-1.25-1.09-.92-2.97-2.46-5.87-2.98-8.92,2.84-1.29,5.99-1.57,8.97-2.44,3.43,3.03,6.96,5.95,10.58,8.74Z"/><path class="cls-2" d="M725.96,587.36s-.04,.05-.07,.08c-.01,0-.03-.01-.04-.01l.11-.07Z"/><pM ath class="cls-2" d="M735.57,607.55l-11.96-.11c.34-.63,.68-1.26,1.03-1.88,.21-.37,.55-.74,.22-1.21-2.83-1.67-6.58-1.57-9.45-3.24,3.15-4.81,7.03-9.07,10.48-13.67,3.13,.9,6.19,1.91,9.23,3.01,.27,.16,.31,.29,.56,.59-3.14,4.18-6.85,8.44-9.85,12.69,.34,.57,.75,.82,1.28,.96,1.91,.48,3.84,.96,5.75,1.45,.78,.37,2.81,.29,2.71,1.41Z"/><path class="cls-2" d="M646.67,818.15c-4.1-1.21-8.11-3.01-12.27-3.89l.14,.1q5.96-9.54,6.4-11.49c-4-1.43-8.28-2.49-12.16-4.17l.08,.12c1.91-3.17,3.47-6.49,5.13-9.79,.24-.47,.42-1.03,1.18-1.19,3.0M 3,.85,6.06,1.7,9.09,2.57,.88,.31,1.8,.39,2.44,1.13-.88,2.92-2.54,5.62-3.75,8.43-.25,.95-1.93,2.51-.56,3.18,3.39,1.03,6.8,1.98,10.2,2.98,.81,.27,.7,1.11,.39,1.68-2,3.51-3.98,7.03-6.41,10.38l.1-.04Z"/><path class="cls-2" d="M637.65,964.94c9.69-3.75,18.76-8.35,27.89-12.88,.27-.05,.81,.09,1.01,.36,1.48,1.76,3.94,5.63,5.08,7.98l.09-.08c-9.13,4.89-18.51,10.01-28.39,13.59l.14,.05c-2.17-2.86-3.79-6.09-5.7-9.12l-.12,.11Z"/><path class="cls-2" d="M626.46,670.12s-.01,.01-.01,.02l-.07-.06s.05,.02,.08,.04Z"/><path class="cls-2"M d="M637.87,668.63c-1.48,6.31-.25,6.81-6.69,3.67,2.2-1.27,4.43-2.49,6.69-3.67Z"/><path class="cls-2" d="M650.12,662.84c-.07,.27-.13,.54-.19,.81-.01,0-.01,.02-.01,.03-.37-.09-.77-.14-1.11-.27,.43-.2,.87-.38,1.31-.57Z"/><path class="cls-2" d="M817.23,696.61c-.34,3.9-1.81,7.8-2.56,11.69-.1,.41-.76,.71-1.24,.56-3.23-1.06-6.44-2.13-9.71-3.04-.64-.07-.89,.67-.97,1.17-.59,3.18-1.15,6.37-1.74,9.55-.22,.71-.27,1.69-1.16,1.87-3.67-.87-7.32-2.11-10.98-3.1l.15,.11c1.5-4.26,1.01-8.8,2.8-13.01,3.59,.48,6.83,1.96,10.36,2.64,.26,.M 05,.83-.27,.92-.51,1-3.29,1.41-6.76,2.21-10.12,.2-.72,.45-1.77,1.45-1.6,3.65,1.05,7.25,2.21,10.57,3.84l-.08-.06Z"/><path class="cls-2" d="M979,733.46c4.12,6.46,8.61,12.71,11.97,19.54,.1,.24-.1,.46-.39,.45-4.41,.06-8.76-.65-13.17-.62l.09,.06c-3.68-6.6-8.2-12.74-12-19.24,1.54-.72,3.15-.53,4.79-.59,2.94,.09,5.88,.13,8.8,.46l-.09-.07Z"/><path class="cls-2" d="M461.39,706.29c3.86,5.43,7.72,10.86,11.58,16.29,.39,.76,1.46,1.48,.92,2.35-4.69,.22-9.4-.38-14.09-.51l.04,.02c-3.66-5.25-7.33-10.49-10.97-15.75-.31-.73-2.81-3.38-M 1.36-3.6,4.66,.24,9.28,1.08,13.97,1.25l-.09-.06Z"/><path class="cls-2" d="M461.47,706.35c-4.16-6.45-8.72-12.73-11.99-19.56,.05-.44,.75-.6,1.17-.56,4.15,.12,8.25,.74,12.41,.74l-.09-.06c3.5,6.29,7.62,12.37,11.6,18.45,1.91,2.43-11.82,.76-13.19,.94l.09,.06Z"/><path class="cls-2" d="M702.58,555.4c-4.47,4.82-8.53,9.93-12.65,14.92-.12,.11-.55,.13-.72,.05-2.45-1.31-4.8-3.13-7.02-4.59,0-.37-.1-.63,.01-.79,3.94-5.05,7.71-10.47,12.38-15.01,.43-.21,1.04-.03,1.4,.26,2.16,1.76,4.79,3.06,6.59,5.16Z"/><path class="cls-2" d="M692.1M 3,862.03c2.13,1.15,4.56,1.84,6.79,2.84,.8,.36,1.82,.48,2.33,1.21-.03,.19,.02,.44-.11,.56-4.06,4.03-8.23,7.98-12.77,11.67-1.06,.86-1.38,.89-2.81,.25-2.24-.99-4.46-2-6.69-3.01-.46-.21-.88-.45-1.05-1,4.9-4.11,9.8-8.3,14.41-12.57,0,0-.1,.05-.1,.05Z"/><path class="cls-2" d="M788.86,715.32c.45,1.39,.03,2.77-.16,4.14-.38,3.41-1.2,6.79-1.37,10.22l.1-.1c-3.72-1.07-7.6-2.11-11.48-2.49,3.73-15.49-2.76-15.13,13.06-11.66l-.15-.11Z"/><path class="cls-2" d="M1228.38,910.98c-.05,.07-.09,.19-.14,.19-.31,0-.28-.04,.09-.09,0-.01,.05-M .1,.05-.1Z"/><path class="cls-2" d="M1279.81,881.08v-.2s.02,.17,0,.2Z"/><path class="cls-2" d="M433.09,751.59c-.28-.18-.27-.23,.03-.15-.04,.06-.09,.13-.13,.19l.1-.05Z"/><path class="cls-2" d="M1240.27,858.9s.12-.06,.12-.06c0,0-.12,.06-.12,.06Z"/><path class="cls-2" d="M393.07,779.89l.28-.25s-.13,.14-.24,.25h-.03Z"/><path class="cls-2" d="M481.61,853.12l.15,.02c-.08-.1-.05-.11-.15-.02Z"/><path class="cls-2" d="M248.66,642.99l.11,.06c0-.15,.02-.14-.11-.06Z"/><path class="cls-2" d="M375.64,837.58l.27,.03c-.13,.19-.19,M .16-.18-.09l-.08,.07Z"/><path class="cls-2" d="M1037.31,730.23l-.31-.14c.26-.16,.33-.1,.22,.19l.09-.06Z"/><path class="cls-2" d="M1086.38,834.09l-.3,.07c.09-.03,.19-.07,.29-.11,0,0,0,.04,0,.04Z"/><path class="cls-2" d="M1028.34,666.28c.29-.06,.4,.01,.33,.2-.21,.03-.27-.04-.25-.26l-.08,.06Z"/><path class="cls-2" d="M215.67,631.85l-.23,.11c.12,0,.17,.02,.23-.11Z"/><path class="cls-2" d="M1024.12,629.75l-.19,.07c.1-.08,.1-.19,.19-.07Z"/><path class="cls-2" d="M213.94,629.46s.07-.07,.08-.06-.08,.06-.08,.06Z"/><path claM ss="cls-2" d="M998.52,718.5l-.17,.09c.11,.02,.11,0,.17-.09Z"/><path class="cls-2" d="M800.44,1026.36l-.16-.05s.14,.05,.16,.05Z"/><path class="cls-2" d="M1070.09,761.82c.09-.16,.18-.45,.28-.45,.35-.01,.34,.09-.02,.19-.09,.03-.15,.12-.24,.21l-.02,.05Z"/><path class="cls-2" d="M810.4,1039.05l-.17-.18c.07,.05,.14,.11,.21,.16,0,0-.05,.02-.05,.02Z"/><path class="cls-2" d="M146.85,783.14l-.17,.11c.11,0,.12-.01,.17-.11Z"/><path class="cls-2" d="M1257,1041.9c.08-.04,.16-.08,.24-.13-.1,.04-.2,.08-.31,.12-.02,0,.08,0,.08,0Z"/M ><path class="cls-2" d="M686.57,1042.33c.13,0,.34-.03,.37,.02,.19,.24,.09,.25-.26-.02-.03,0-.12,0-.12,0Z"/><path class="cls-2" d="M708.45,1043.49l-.06-.12c.08,.05,.24,.03,.06,.12Z"/><path class="cls-2" d="M685.5,1044.44l.05-.26c.3,.13,.25,.19-.14,.19l.09,.07Z"/><path class="cls-2" d="M706.98,1045.42l-.11-.14c.13,.07,.22,.03,.11,.14Z"/><path class="cls-2" d="M1211.59,762.83l-.21,.18c.04-.06,.09-.11,.14-.18,.01,0,.07,0,.07,0Z"/><path class="cls-2" d="M1072.6,698.98l-.42,.2c.1-.04,.47-.27,.42-.2Z"/><path class="cls-2"M d="M412.1,696.62l-.23-.12c.26-.09,.3-.03,.14,.18l.1-.05Z"/><path class="cls-2" d="M1092.71,695.04l-.14,.07c.06-.08,.04-.19,.14-.07Z"/><path class="cls-2" d="M775.96,1083.78l.27-.12c0,.2-.11,.22-.33,.04,0,0,.06,.08,.06,.08Z"/><path class="cls-2" d="M257.78,597.94l.51-.18c-.14,.03-.43,.2-.51,.18Z"/><path class="cls-2" d="M718.23,1098.91l-.37-.32c.24-.03,.18,.12,.24,.29,.02,0,.13,.04,.13,.04Z"/><path class="cls-2" d="M1100.78,662.2c-.08,.07-.21,.21-.24,.2-.19-.08-.09-.16,.3-.22,.03,0-.06,.02-.06,.02Z"/><path class="cM ls-2" d="M624.22,1111.98c-.12-.1-.23-.2-.35-.3,.25,.02,.32,.12,.36,.35,0,.02-.01-.06-.01-.06Z"/><path class="cls-2" d="M646.13,1117.89v-.18c.1,.11,.19,.12,0,.18Z"/><path class="cls-2" d="M310.21,573.78l-.1-.06c0,.15-.03,.14,.1,.06Z"/><path class="cls-2" d="M780.14,1133.02v-.27c.35,.06,.31,.13-.09,.22l.09,.06Z"/><path class="cls-2" d="M589.12,1154.23l.04,.21c-.26,0-.25-.05,.05-.15l-.1-.06Z"/><path class="cls-2" d="M605.07,1165.57v.14c-.15-.07-.15-.06,0-.14Z"/><path class="cls-2" d="M378.95,529.15l-.21,.04,.11-.13c0,M .06,.01,.11,.02,.16l.08-.08Z"/><path class="cls-2" d="M1007.33,688.24l.31,.13c-.25,.17-.32,.11-.22-.18l-.09,.06Z"/><path class="cls-2" d="M523.46,1191.36l.23,.39c-.08-.13-.16-.26-.24-.42,0-.02,.01,.03,.01,.03Z"/><path class="cls-2" d="M597.35,493.02v-.16c.18,.12,.15,.15-.08,.09l.08,.07Z"/><path class="cls-2" d="M171.32,461.66l-.27,.08c.21,.14,.25,.09,.11-.13,0,0,.16,.05,.16,.05Z"/><path class="cls-2" d="M412.14,773.5l-.16-.02c.08,.12,.06,.11,.16,.02Z"/><path class="cls-2" d="M555.57,1219.39l-.19-.22c.07,.07,.15,.14M ,.23,.21,0,0-.04,0-.04,0Z"/><path class="cls-2" d="M628.12,1219.02c.06,.7-1.41,.28-.17-.14l.17,.14Z"/><path class="cls-2" d="M638.3,415.07l-.04,.19c.24-.05,.2-.09-.1-.12,0,0,.14-.07,.14-.07Z"/><path class="cls-2" d="M560.31,1238.68l.46,.32c-.12-.09-.24-.18-.39-.27-.03,0-.07-.04-.07-.04Z"/><path class="cls-2" d="M476.02,1239.66l-.19,.13c-.01-.2,.07-.21,.25-.05,0,0-.06-.08-.06-.08Z"/><path class="cls-2" d="M796.77,320.09v.21c.21-.02,.19-.07-.09-.13,0,0,.09-.08,.09-.08Z"/><path class="cls-2" d="M660.72,307.27l-.19-.21M c.07,.07,.15,.14,.23,.2,0,0-.04,0-.04,0Z"/><path class="cls-2" d="M767.07,301.73l-.08-.06,.08,.06Z"/><path class="cls-2" d="M703.81,286.66c.07,.03,.21,.08,.21,.09-.09,.23-.11,.21-.08-.05-.01,0-.13-.04-.13-.04Z"/><path class="cls-2" d="M479.99,1310.06l.2-.09-.1,.15c-.05-.05-.1-.09-.15-.14,0,0,.05,.09,.05,.09Z"/><path class="cls-2" d="M755.9,264.86l-.26,.15c-.04-.2,.07-.23,.32-.07,0,0-.07-.08-.07-.08Z"/><path class="cls-2" d="M577.14,262.92c.65,.28,.66-.3,.79-.71l-.05-.02c-.4,.12-.77,.2-.74,.68v.04Z"/><path class="clM s-2" d="M914.3,249.26c-.17-.36,.47-.5,.58-.18,0,.24-.19,.32-.48,.26l-.1-.08Z"/><path class="cls-2" d="M814.39,243.8l-.02-.22c-.23,.06-.2,.11,.1,.14,0,0-.09,.09-.09,.09Z"/><path class="cls-2" d="M753.96,241.18l-.35-.14c.09,.05,.29,.04,.35,.14Z"/><path class="cls-2" d="M816,219.41l-.32-.47c.16,.22,.25,.35,.35,.47,0,0-.03,0-.03,0Z"/><path class="cls-2" d="M1098.81,212.47v-.19c.22,.14,.19,.18-.09,.11l.09,.07Z"/><path class="cls-2" d="M765.37,204.6l.16,.16c-.25,.12-.27,.08-.05-.11,0,0-.11-.05-.11-.05Z"/><path class="clsM -2" d="M819.94,189.58l.51,.23c-.19,.04-.25-.1-.42-.2-.03,0-.09-.03-.09-.03Z"/><path class="cls-2" d="M1036.44,164.59l-.08,.21c-.19-.18-.14-.23,.16-.13l-.08-.08Z"/><path class="cls-2" d="M370.46,678.14l-.14,.14c.04-.16-.04-.23,.14-.14Z"/><path class="cls-2" d="M634.46,747c3.26,1.49,6.97,2.11,10.41,3.2,.65,.18,1.35-.18,1.5-.72,1.13-4.01,1.04-8.42,2.8-12.2l-.16,.11c3.31,1.22,6.85,1.81,10.37,2.49,.49,.09,.93-.24,1.03-.76,.69-4.24,1.54-8.52,1.65-12.79l-.12,.07c3.04,.89,6.26,1.21,9.38,1.84,1.72,.35,2.14,.06,2.41-1.34,.42M -4.01,1.48-8.19,1.14-12.19,3.17,.45,6.33,.93,9.51,1.34,1.59,.21,1.98-.04,2.16-1.22,.2-1.38,.34-2.78,.5-4.17,.27-2.35,.52-4.7,.8-7.05,.1-.85,.59-1.19,1.51-1.13,3.32,.34,6.62,.86,9.93,1.26-1.11,4.12-.98,8.5-1.64,12.72-.07,.66-.55,1.02-1.27,.96-3.29-.15-6.3-.93-9.65-.73-1.28,4.37-.86,9.15-2.02,13.61-2.9-.44-5.8-.87-8.7-1.29-.88-.11-2.43-.32-2.56,.8-.6,4.26-1.19,8.52-1.78,12.79l.13-.08c-2.84-.97-5.94-1.13-8.86-1.84-.74-.14-1.57-.28-2.29,.05-.12,.18-.32,.35-.36,.54-.8,4.1-1.58,8.2-2.36,12.31l.12-.07c-3.46-.84-6.92-1.67-M 10.39-2.51-.55-.15-1.5,.01-1.64,.56-.89,3.9-1.77,7.8-2.66,11.7l.14-.08c-3.94-.48-7.8-2.29-11.65-3.15-.7,.24-.94,.62-1.08,1.05-1.15,3.56-2.06,7.14-3.6,10.58l.12-.12c-4.24-.99-8.13-2.97-12.23-4.4,1.03-3.99,3.05-7.73,4.07-11.71,3.92,1.31,7.7,2.99,11.72,4.01,2.09-3.77,2.62-8.29,3.65-12.42Z"/><path class="cls-2" d="M666.93,768.98c-4.1-.79-8.16-2.04-12.28-2.55l.09,.06c1.79-4.05,2.08-8.72,3.29-13l-.12,.07c15.95,2.19,10.53,5.53,13.87-11.06l-.13,.08c3.85-.11,7.55,1.25,11.4,1.17-.02,4.6-1.47,9.06-1.57,13.65-3.61,.05-7.12-.99M -10.71-1.33-.46-.06-1.13,.32-1.23,.65-.97,4.1-1.81,8.24-2.74,12.35l.14-.09Z"/><path class="cls-2" d="M622.3,783.28c1.58-3.93,3.79-7.74,4.97-11.76l-.12,.12c3.97,1.52,8.01,2.9,12.24,3.91l-.13-.15c.03,.21,.15,.44,.07,.63-1.31,3.36-2.65,6.72-3.98,10.08-.2,.68-.84,1.27-1.64,1.07-3.86-1.14-7.62-2.57-11.42-3.89Z"/><path class="cls-2" d="M654.65,766.43c.28,.64,.12,1.28-.05,1.9-1.05,3.3-1.58,6.83-3,9.98-.11,.21-.73,.42-1.04,.34-3.82-.96-7.7-1.8-11.3-3.26l.13,.15c1.75-4.05,2.56-8.3,4.09-12.38l-.14,.08c3.68,1.45,7.74,1.76,11.M 4,3.25l-.09-.06Z"/><path class="cls-2" d="M675.9,783.82c-4.19-.08-8.15-1.72-12.33-1.83,.65-4.39,2.07-8.75,3.35-13.01,3.37,.36,8.24,1.71,12.21,1.93-.48,.4-.71,.88-.84,1.42-.79,3.13-1.61,6.26-2.39,9.39-.18,.72-.45,1.45-.21,2.21l.21-.11Z"/><path class="cls-2" d="M1000.81,897c4.77-1.63,9.81-2.57,14.69-3.93,1.73,12.7,4.63,25.33,5.65,38.14,.02,.54-.47,1-1.18,1.13-4.2,.71-8.38,1.69-12.6,2.24-1.29,.02-1.19-1.45-1.43-2.34-.38-3.32-.68-6.65-1.07-9.97-.84-7.3-2.08-14.55-3.18-21.81-.18-1.17-.21-2.37-.88-3.46Z"/><path class="clM s-2" d="M928.25,467.83c-.07,.01-.14,.01-.21,.02l-.03-.09c.06-.01,.12-.01,.18-.02l.06,.09Z"/><path class="cls-2" d="M976.88,466.49c-12.34,.04-24.69-.19-37.01,.51,4.88-5.43,10.85-9.77,17.76-13.21,4.72-.17,9.45-.24,14.18-.27,2.02,3.98,4.02,7.98,6.03,11.98,.29,.59-.08,.98-.96,.99Z"/><path class="cls-2" d="M915.2,433.56s-.06,.01-.09,.01l-.03-.09s.07,0,.11-.01c0,.03,0,.06,.01,.09Z"/><path class="cls-2" d="M918.48,445.2c-.05,.01-.09,.02-.14,.03,0-.03-.02-.06-.02-.09,.05-.01,.09,0,.14,0,.01,.02,.01,.04,.02,.06Z"/><path claM ss="cls-2" d="M727.47,663.7c2.82,.71,5.76,.87,8.65,1.25,1.99,.26,2.45,.28,2.87-1.68,.7-3.26,1.52-6.5,2.31-9.75,.19-.57,.38-1.46,1.12-1.53,3.73-.06,7.3,1.29,11.02,1.27-1.46,4.49-2.87,9.02-3.34,13.67l.11-.08c-3.55-.45-7.09-1.07-10.66-1.3-.44-.03-1.08,.37-1.16,.74-.27,1.26-.58,2.52-.8,3.78-.45,2.53-.85,5.07-1.26,7.61-.09,.53-.12,1.06,.2,1.56-3.55-.53-7.12-.98-10.68-1.42-1.03-.13-.92-1.14-.82-1.88,.83-4.12,1.18-8.33,2.54-12.33l-.11,.1Z"/><path class="cls-2" d="M761.43,668.79s.09,.01,.13,.01l-.03,.12-.1-.13Z"/><path claM ss="cls-2" d="M773.58,670.81s0-.07,0-.1c.03,0,.07,0,.1,.02l-.11,.08Z"/><path class="cls-2" d="M776.68,658.65c-.96,4.03-2.5,7.97-3.09,12.06-4-.65-7.97-1.58-12.03-1.91q2.55-10.81,3.77-12.95c3.93,.14,7.67,1.53,11.35,2.8Z"/><path class="cls-2" d="M776.91,657.8s-.02,.06-.02,.09c-.03-.01-.07-.01-.1-.02l.03-.09s.06,0,.09,.02Z"/><path class="cls-2" d="M764.88,654.99c-.36,.29-.9,.36-1.36,.29-3.38-.57-6.79-1.06-10.09-1.92-.03,0-.07-.01-.1-.02,0-.02,.02-.05,.02-.07,.11-.32,.21-.63,.32-.95,3.78,.77,7.52,1.66,11.21,2.67Z"/><patM h class="cls-2" d="M750.12,666.94c3.76,.76,7.83,.69,11.41,1.99l-.1-.13c-.74,4.33-1.83,8.61-2.31,12.97-3.83-.04-7.6-.94-11.43-1.25,.36-4.06,1.34-8.08,1.97-12.12,.09-.52,.37-1.03,.57-1.54l-.11,.08Z"/><path class="cls-2" d="M793.88,688.83c-.22,3.66-1.26,7.23-1.88,10.85-.27,.93-.35,2.37-1.75,2.09-3.11-.68-6.19-1.5-9.35-1.98-1.24-.03-1.27,1.46-1.46,2.35-.37,2.78-.71,5.57-1.09,8.35-.23,.77-.13,2.03-1.13,2.22-3.68-.32-7.35-1.34-11.02-1.92l.16,.11c1.6-4.16,.83-9.35,2.37-13.67,3.36,.65,6.73,1.3,10.09,1.95,.84,.12,1.26-.6,1.M 3-1.29,.93-3.86,1.01-7.94,2.46-11.64l-.1,.1c3.8,.81,7.56,1.84,11.39,2.48Z"/><path class="cls-2" d="M773.58,670.81c3.81,.84,7.61,1.68,11.42,2.52-.75,4.35-2.16,8.63-2.5,13.02l.1-.1c-4.1-.84-8.19-1.69-12.29-2.53,1.66-4.21,1.52-8.83,3.39-12.99l-.12,.08Z"/><path class="cls-2" d="M809.28,679.77c-5.82,14.87,1.42,13.79-15.52,9.11,1.77-3.73,1.67-8.06,3.23-11.86,.09-.24,.66-.49,.97-.41,3.86,.86,7.43,2.37,11.33,3.16Z"/><path class="cls-2" d="M646.55,678.57c1.6-4.82,2.36-9.99,3.28-14.97,3.38,1.43,6.94,2.47,10.61,3.3l-.08-.06c-M 1.72,4.84-1.64,10.08-3.29,14.96l.12-.12c-3.56-.98-7.01-2.46-10.64-3.12Z"/><path class="cls-2" d="M653.2,710.13c-3.92-.84-7.71-1.98-11.5-3.13,1.57-4.3,1.35-9.09,2.73-13.44,.79-.29,1.41-.11,2.03,.07,2.76,.79,5.51,1.6,8.26,2.39l-.07-.08c.14,4.77-1.22,9.54-1.62,14.31l.16-.12Z"/><path class="cls-2" d="M654.73,696.02c1.29-4.63,1.84-9.55,2.46-14.32l-.12,.11c3.59,.6,7.16,1.47,10.62,2.59l-.08-.09c0,4.81-1.48,9.5-1.51,14.29-3.81-.89-7.63-1.78-11.44-2.67l.07,.08Z"/><path class="cls-2" d="M649.17,737.27c-4.22-.41-8.19-2.19-12.M 33-3.11,1.66-3.72,1.59-8.02,2.59-11.96,.11-.57,.48-1.11,1.21-.99,14.82,3.75,8.7,4.93,12.57-11.08l-.16,.12c2.97,.66,5.95,1.32,8.92,1.98,1.09,.11,2.14,.85,1.8,2.04-.65,4.02-.57,8.24-1.83,12.12l.12-.07c-2.89-.15-5.65-1.11-8.47-1.66-.84-.15-2.34-.65-2.72,.41-.54,4.1-1.7,8.2-1.85,12.31l.16-.11Z"/><path class="cls-2" d="