Muitas vezes acreditamos que os computadores são mais eficientes que os humanos. Afinal, os computadores podem completar uma equação matemática complexa em um momento e também podem lembrar o nome daquele ator que continuamos esquecendo.
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7ivKZ3PPc0ukm7VpEs9MBOiBLFBZnN5itEUAjrj4YhdprzJQ7aXZ440YswzVvPC4jfQRqWD+fUF6ZDiwGlZFebuJ1cicuozUzEWQUB7p8bLPUqE3plzFugppSY2AvezrGV4WZwC+CjMiY1mazJaiGy2XsdL1esZhlooSLNt3nuPLpv816BzYyZbc7m9pO3yM9TDF+gJi8xc7s8K5eUV7ifn+kswV2NBJlZtr6Un8h6yRXmu3w0M6f5XqW5fiCewAzyovVkDx7PsBoQe43LF2OjH9sbXsFsCIVG9r6PFx4reYpsbeGnCF2+HpPW7XjS6x6VXg010EcUySonKugkkCSQJJAkkZJIEkgSSBZgEQz6Tz/pahBPqKaxzAdBW9Vd3l7aEakwCPkYq3ULOrOlqbWd4FeVjd5tLRBbqWX+e/eD7yHRlNEAXDel21RqCbV1nTajsguT3kaXKeJdyXA3Mmm1z+i9MyUkTYNCYX1afGU9NqK8ubvjl+eW9LpryDPrY1xuxnFIoh4paHeSQc/oc7PVV5W1Xd5ytJE6C3Yw0vz/oFcn5ySu3KSo1dSgupAkkCSQJJGSSBJIEkg5JAkkZdSIc7Hn/AFaTAHcXnyk+ylquUJ1bTTG8aNMgcwWpCHzrBGRxKipgWYkiyq5cqty6Rejz39cXulz+hE6ZTax0Mo0GNU1SI7w05yXqnp5u8KilczSephDIToc5hadCt1M4mqazdZa3YcAzFMg5SeBOZ5yrOyLghR20ufEyhkm7eR3GjvSS6WGmrRVg7QOHi56fR8xvSdAqWpJGpJAkqBcqMkkCSQJJBySguZywlDseqvbBkvQE6PPcS9KfjdWVFXhVHHT7KPRnzMtr6aZKDVakOOuWzpFUbDjdWhWctYLMEPcLacKJFjVknd5z2aMymxjTczvLbkc/r8u6W7HKPtn3lEuhnKHO7XJ0VMDYx1BKBFd3KrGmFZgagmUkxdbHCAr7ivMtUwLMm7vMVaqQJJESSBdSAeAuXqsxmsyNSSBJVhJIElQLlRlyoO5nIbgowma0GYSxj1u2ZvWgxZNNj0YgBatgDdFRvOWtC2lhPoA0z5CvVU3z5o3hXolBajsaAcAYONnTDexrvN7fMtPpZ51E9XfJO5eYUNObLCbOQ8Vc+HQDl9rlu0qNOnGussfIQQ6CNVW+dWVMq2uHWT51kmBqJ4vUmpJAkkZJcRJIEkgSSBJIEkoJdQLlZDUxQEzmBdVAJeLb1B5Auc2FUTTBaJY8Xu2YvegHopGA0yUahHSoRM6QEytbQuRgolzH3KHvVE0LYKgS5V9csCgqvj3Vne2A4ECMvHmwCoKXIqzUjy0YJKTzCJax6LPNdznpMptY6F5vRVjTlrto9MGNy9tOr4JNcoDiONbmdIqXpGJqgqSBJIF1IFyoFyoFyoEkgSSBMzIXUoJdUzVVAur0PEJYCssZjWrDN7tvFk2AdMEBbbZgSK6UaRXCJKFdMjnk6OhImYoWN5yItBwI+V8VLOFcOWgrjpFXyC1a2g1SuquO9oJRiBV04lyBJKFmS3EIPbZSrlUuP819ZdJpJrIZxes9eRz+pzdBAew6LovcNpyPl9Pn43JNSaLGELCdWAFayEkgSSBJIEkoLlQLqUFzFBeZbeb3oB2SBm9WzM3YYve2xWfYL7aKCZHTAiV0iFCuHBAnRKkgZmks7zkRKDlo2QDpM4VHUtjVE05hPLTY1cU2cL5YfAs1WxzLdDvIhXWo7D5mxKS6JkmkVneE6uoRNZtmyCKJroJOrJttJmIcIA+WinL7XLd8dV9LZC0GoG12BwwzNiYYSIhhaDCsyguVAupAkzkCUOgJmW3iyWA96sM3dszetBiy7bBpkoKEcKhIrpATK4cESdIyXNO7EBLVEkoOGj5XHUtZUzSbEATGMK4sZGvihga+WGGLDRsijC0KqslYphIPTrebovOdUQDebx2IddpNLJBpTUidYJkMS7U5vWm8s5bQU4SLBkyZzPosJt5XvmdRJacXm9rk6COSYhsYlJCkgXMwWqzQag8gXObCqJYD1ux5u7ZU1YZhNjFZygrtsrEyOlQkV04Ik6R0cs/RsSpt0lqDw5NkA2mcKjqGxqDpN4TxSaGrhjUTurbELNXvI9VUzWWXmssmaojUxA1MWGpUb1vGjTV4hV1VCFMznrbSbKYx6p1JIiVojQiMGmV9moM7HipYpTTzbc57qy6DaDmLZCWZ68bk9vlVXLGcLLzBI3nEFed2A7JAxrUCpqwze9AOzbGDTJWKEcKhIrhgSL0WEco/U2JE58pXY8uS0DDTGFh1LeE8UnRACxgSoqlsauGM4WwNjK9NmyKNm0Hb2LMVWmtAgyZzQXm6FWbyolVJi5UHcqxkvNvWSoFyUMN51jFsrNFgl5q7lQRWgSVvC1EM0vGG0tLzbyuQhttBuY6L3NeiXiBLjsjy+1zHfEV6CVsWd0LM1aMXrQDsugDpggK7cICZXCoTK+yHLL1ypcxhyhDLjIi5FhyfCw3LY1B0nBp4acGqNtkaw6TWVbduraTHvAqFvOaHqqgXKoerzbrd51W15qh3KtF3UHKqCrGsrOpIRdS2TVaL1UjupLSkkAGs6mNOKPmigjgKrdHStcgglXlKVKIkqE62PYmGk2SH3ua8s+iwozjpfM6qC04vP7HP0tKMWxfTRElCOEQmV1lLml6x0uQ10aEueZEShYEbK46lrCg3LeEx0O4SzTaEETDDWGJrK1DYpfRprFZDZBHehUnUkYkozkqBJUZcrVOam60lTA5dWlNVZUrUHit0885LHI4SnOL1oM3qPbMuyMTVJSXZSeh75pL0UOmaLKdZNMBdBpixdCuVBSVBStW1ndQkx1zktuoOLLotoOZthc+M9eYn0sVfM11GBchjq6SRYLknUFgk+QDpM4Vw02NQdJwSuKbA1sNMjXG2xgGRnwLLtmLlegxHAKXVpXrNhKqIIws1emU2FnNVI8pJAklsm6I7lEA6qS1ld1ZVyrHd1bqSRqTVU6ySkY1dDkrKmTNqblRO9VbtEknHLfRkV6BJCCnJpeKkpSpBVUhGtyOpJG9mkWbDkhi65JmmNyZahNIVVSEVUjMYkcjFJU4FJSHiSkMcjMSStMYkKxiRmakTlSO4WR3teRupJMy5HObkDbcl6LryGdSQzkkFJIMhZK2gJCJcii7kKlyBqpHUkjNySruSF5qRTjMk5Z1JMy5C9XI7/8QAKxAAAwACAQMEAgIDAQEBAQAAAAECAxESBBAhEyAwMSJAMkEFFCMzUEIV/9oACAEBAAEFAu+v2dH1AjGjqPxihMxsxPayfwv7yfFLGbN/BxFJKGu32n2TESUxUtbk1JV6KybTHRv4NGvhXbiNdtm/1kjHhqz/AFshkxUhyJHTzu+qf/R9oMH8cv8AGjI/jnyqXu120RG3/rJChp3ookvvJiW009pduQ32r9TZvtTG/wBdIwRyusgrray0qyRNY+J0q0ZHt0xGIxfwyfyyFfHDPscCg4HA4nE0JHTr8rt8nkpmxi+77IRFOXf2Njo5G/13Q38iNfGkf+eMx+b3+WL8sEw3V6x47GSYkR4m/wD0ysr40SKTiaNCg4FSJGCdGTzWjQ5NGvDkU9pMfnHf3X6WjRo0aNGvnQl4fwowr8rrbMQjBfE/GRzFGXE5bkmTBPl+Jp/hfy413Yie1rtNrV4/yWI9IrGPGcB4ziOSUY63FfdDXt0a+bX6SF9V8KI/8n2XjHJ00GbJuuZjyzU1he+GngXjM/xzfxr5EhPQrOZsTEzYxyyJ81KEhIqSkOXpDkcnExw0V9sf7L+WEP6+FD/HGyVt091Jg84bGJk5GjHezGtLK0jI9lD+KUPwbNmxKhJo9SUeuerTJ8mNI0J96SE0zXlQjJAplK72UMf/AMaJLNfAiFure6F9EnSV5zLVV2kgx/xz/dFv44Q5OCN40eqPJT9kkiyaXMx15G9DKWmjkctj+qGV+ps2bNmzfywhLw5OJSH7kY/5vt/+CTp3q+qX512hEmP+HUfyor36FDNSjnCPVZyb76NGjRoQmbORNEP8arbitlLaXZleFQxoa/Q37NmzZv5sfdlP4I8D7L+IjG/Ob8sVIS8yY5214XUfdD908S6aTpv2pCg17+RvZJjpOb8Pnpp8lfhyzRa/Fo4jgqSl/wDExmzYxoa9qJRl+32n6EQR+XTUiZJRinSM1ebodI2caZwZwRopHP8AHukTApSTe/iiyTIm0zBk068r6ceVf1oSGikWhr54k4eKn9KCqJffiODgaNdsf88n8n2k4tixsmEjpmZVqtmL7X1kepyssxtdnSPUR6jOT9soiBIp7ejRo0P34bFqptFPR0+X1YtG/D899lDKka+WUQtDY1sqf0Ej6TeyEOjmKzkN9tGjGvyyS+XpnBE6Q8ko9UVtnTv8+pXkxPyvrN9ZC+zb+CUY5NFGjRo0aGh+7A/+y/G7RkRhyell+1jRxGih0ch9mhz8ejHI/A2Sx+Rya+VCGJG9DfdPskxLtDnlWZbeZjumJ+XPnRCMP3nW5aJMT2rW5yotDRo0aNGjXZESY5Pt5a4RGqnRo0NDGP24f/XIKeWPLI589JfiUV4HWykUhm+7RUjXwJEyfRT7I320OTj8crtobG+8Ts4onSd25PUpnlmuMvtoSJQoFJH3l/8ANiRhXi3qb8jkcDg4HprGcpR4pcT02TjZjxkSY/KzxuOkzem9GjQyihj9nTflksxvWLJj5CxOqn08JGXnOdvUMZSGhmzkcuzkcmu+jiKDiIbH7F20cfiSEuzrvo0Lwu1eYQkWvLk0KSYJg/ok/li4kyStLN9M0cdjgWPTzR+fpkYz00cDiSiSfw6ip5LPg84epvCY8uPL2ZRQx9m9D21hj04iXdUvG+Ly50iqOmzcLtbT/GoopFIaH22KhGhwcDgcDRsbEU/ahC+JIXgdG++hIUlffaH415mSZ5JwOCYJgYjiJGJjnyl2yGjRo47JRSOIl212RJ1WLZisrGqWfGyY25zZ4P8AbH1OMrPjHlkdtiV246dI4o1yOlfPK/Jm8LIyrOR0eb1cfURtRWhPapFIaNGjQjkJ92Mb7IfuQjfwJH0OvYhISNaT7w/OiEQvNSOSYK+9GhGifZRrv/T+v6aJ0NGi1rtJ9mXFo9Vy1kjIf663wHigzYkk+SNZGLDmow4XjNFVGMXqdTUSsWNP8upZkHJwMFPFk8XGWeF4qGUNDQxs2bJo2b7V2Q/ckI2VXvSNjfsQkSiUZvEv2R5UIkZoSP7nzOjQhC7v2P62SV2b/DZX0SLtm6fZqprFkYqPxHMjiCnjkrqMaK6tHrZchg6OqcRGJVQ7PGTFYpNGjo8unmjlK/Goe1SGMftT7J90P2pdtjo2cDj7d+1CJRKJR1I/ZiZie571/H/84bTfvfsrMsmZPxiexnAa/HgyzYn22bGlR6KOBU0ZZyGRZDjYsNsx9DmZh6bHiGyixs6YyYHyrG0NFDrT6fL62LqMenjo+1SKQx+1D9j9zob7vSKodGzfvQiSUSdVP4v2RWq6evPZD8yZ+WOsGeM8/A/B1HVczp4e6Z0j5ponsjL9iI8p/exMT7fZ5Nnk5nI32osZD4tZqJSyTkjRYzpM3o5bXKWuFYqKRSKQ/au8j9uxv23fxokkkk6jJCjZTfsxXruhG9ZKlXN4rxXi/wAgY82PJ7auZMnXY5KvN1LxYlIlwWbJ5wx6WHfmvpsVMoYiH+L8j8Gzkcjl59RHJ0OrRtZF9NUbKoqu2iTfpTd7Mj79Bm5x1GPah6Je1SKQ0P2yNEjGa7Nm/dXxokkky5PTi6dUvql474mYK5Y+yZ1OJ2sXUbNTkM3TVv03tf7EnrdUh9R1JWbKzabnFksw9M5TcwsvU8jo+n4Dfa1s0aH2RjGPts2bNmx1p03NV+WHZ6g77JDX4wnvqf40y++O3juKnLiyzwrFR9q0Uho0a7z2XbQxv4H8SESSI6iuVMjtX32l6fTVq+yEzqelWU9TJhrD1iZ/ys9GWehRfScxdBjQsOKCuow4zL1zYvUz103SLENm+3PQrQ/JS0MRFLX2UkP2aNFCSvHE/wDDL4GIlELzeMj8Yy3sofs6DNwvLHKV+Lx1spFIaNexH9LtTG/00SiUSjI9TQ0L7LXsxUJ7XZCMuGMyy/420ceowi6vMhddZ/v0V1uVlZstE4cuQxf45mLFGKaY3232XbIMRK2N6TY++jRoaMPi1rjkxptwPUjzs9bIPNlPVyHqWcjwcTia7dJm9bF1EaeOj7VIpDXsQhDKNfpIRKIQloyeXSOJx7UvHfE/PTVuOyEheB0b2PFjo/1cB/q4T/Twno457f3TG/dK8V9iIL++6EJdmhz5xVou/OS9j+BNolzQ4HJgyPDlerhrjWKikUhjH2RJsb7aHP6KJRCIQ5/GkNHEcmhlrz2X3016vvLH9Pvs2cvDo2IYzRM7HpGtoT2qnXaZ2b4jpM0jXdGxUcdlrj2yXyGx/FjyFYypOiymeNqGQ9qkUhjNCRvRVGzYqPstD+dEkIlCRa032ZT8syL2Yn4x1yjvBXt2bEN9kkzjodJJsgfbf4f2/E+x9kIRJdc6utjH8nT3tXB5msdrLjyzwrFQ/KpDRxNaHQ2b9kMv6fzIRJBIjMijkOimb2n9d8b/AC6SvHbR9J9te1dtCRY+yKW5NnI2bNiEho0aEiUZHxi/xxtaTH8mCuOap41kk6fJ6WTLHKV+Lx1saGiimP3T9/1f38qESQSIyLcWWNjZD7X99+nrVdpRXbRSGaNdkI12oZolFMftQheBvtoSEZK3nzjv/vQx/Gv5dQvD8rIjpMvOOojTx0S9zRRQ/dIvrJ9/KiSSCRdsq85EV2X2WvZgMT5Qkuz0fRs+05OJo0eEJ77a7aOMnEatHJGjQ0aEiEfY5FJSEIb11udbjqdzlVc5fyYPOfN/5r6yE28eTxlxtcaxWMpFIaH7Z+19ZPv5USSQSLtnXnIiu6+n9d8T0+mryjfhvumKuz0PJtxj+FyqHjqCLVGjRKLZs2zek34XbrN4urjVxmx7mW8bVKl8fTT/AN8r8a0shR0ObVZ8eyXp43tUikUhofsRH1kXzIRJJBPbKtzkRaH2jta89pMNaEN+1G/DdZ6mVC+O8XIg4n0UM2Kx+Rduuxepg6TNxeSVlnPjcuTl8Kls+6wRwmfzumZGUf30+T1sWWONY60fapFIaGvYiPrJ8yESSQT2flZEZEPtP2WvBMikxmB7j2aEjLunKUr5XIhlDNmxMl+O3XdN6V9N1bTqZzTn6Xzq5ajZ6dGvYvLjp0Zq2YMHASdvxrJRbGJHS16eS45Tx08dFIpFIa9iI+svzokkgkXbMvORFd19P6S84MXOlgk9JKsS0zXZLt9KPE4/MfL/AH/bKH3RP199qU3PV9LWGsHUVjePPGab6dM4OB/WVVvybZps6fHxGroiJg4Hqciq0rop9oRjkwP8c0dk+SpFIaGPvjZkH8yJRCJJYu2ZeMiLQ+0duPnpFomtN6ZK0vb1D1j6nx02P/z+Xf55K0/tUPuiXtSOjZ4azdBFFYsvT3j66pI6rFZwih4pHhR6KOCR4Q8mNH+zo45MptTN2VQ2Ly8XTZWY+n0KJkyXOqZjoZSKQx94ZflP5pRIhMkntS2siMiH2n+SRxMamJ+6XkbJft6r+HVeem6a/wDp8jfFYW3XVV+eP/yofdEvRzZs5HI5FcaV9JjovoaPRz4z1+pk/wBzMf7WU9bIzWSiOnpkzGMrIVYsWXIT0FsnosEHqYMRXWyf7VM9VsqxVsmtPHW1SKRSGu6YntWvkRMn0bNksgnvlXnKiuyMflKSf/NaF4nZD8+zOtxi/wCnTvcrDlnNHx9Rn55cJv1ep+lQ/ZvtsWzyjY7PUPUPUOaP+Z/zOUoeQ3dC6fLQukhH/DEX12NF9fbKzZL7IVHMdHIT2sdaf8lSKRSH3hleU18SJnvs2QyGT3yoyotDJXnCRJUixmS+I78xZNbW++SeWOMnDJ1OIjLfT5cHVRmXwVSldV1u10uN7zV6OHp402UP2KWcB5MMD6yTDlnOqTl5Dmcz1D1BU6JwZqJ6M4YMZXV4pL69l9Tks8v37N9orT5cXgzLdIpFIY+yNlL4pR9Gx0bESyGQxPta3ORFockox+DGz1dDyyZknFUY784L7Lv1UcKwZuJ1XR8yleJ4f8hcmPrcVk5Iru2kX1OGDL/kkh5rzVhwu61PTY22qwR6cNjY+zqZH1UIfU5KHVUbNmO3F+M+LKh/cdNnsj/HULpumxD6rBjL/wAgX1WWh1T+eXyR0+X1cdIpFIftY/fKPobG+6JIZDJF2ySXA4OBKMa82imdPe3lw8X9PE9Pts2NKl1mGsFdL17grHi6iM3+PaKxZIOVIWbIh5so7pnlkdNkt4Og0XkxdOnmTrp8L22UyssovqCs1s2RGz0MjS6Rn+tGrlxR0XUcLyrA36/T4y+vZfV5aHTf6aemzDbx5GUikNDXZD7te2UJaGxv2IkggkXbIho4nESI8GT+OX7WzEuWGp08a2sb3HbZspTc9T/j6l4cvp1i6ts54chXS4qH0GM//nQLoMSFgxSX1ODEZ/8AIVRjnJmvpulWJNjYzL4rTZxMcrfLMlizOjPlvHkxZeZ1OPnPbl43+vLMCXrfZSKRSGhru17kiUNjftRJBJBPal4cleOyIlay/VyKSLczwix4tGJ6vvs2bMmDFlMn+OGurxk9Vlk/3qH12QfV5mcsmRx0mezF/joRKnHOxsb7ZZ3JX307SbyJJX/0zXzydKvLOox8K/axUYm8daKkqSpGvY0P2TIxv3wQSR4SrvTGtzxZPly9j/i5JxbdRxIrTr+Lf5fa9mzZs2NSz0sQ+m6dnoYELSNmzZvvzxyV1eMZU7J+u2HpmyZUozSqiv2pfnFbyxrw0VJUlIa9jntomBrRQ/fJBIv4IXbJ9qtFZHtZGYmPyKR+FWQUSx/ijC9x79mzZs5HM5Gx5JRXUwiuqorLbPIhPaMEan05OKRtFdRCK6pnSP1JzrWX9TZs8mhISMNOXjyK0NFSXJSGu6EiZEiyh+zRo0SQYxvUoXbJ9UUyWY3tqTfnLl4jvYsjRvZ/eF6ye3ZyOZzOTPI6lD6iEV1bHmujb9yri8S5U8sQV1SH1FsdNmzZOW4G9v8AR2b7aNexEGNkVvs0XJUlIa7JikS7ZK9qQpOJxEiUST/CRCH9WWL7wCZv/pkln9oRRsV7nkcjbPPd1KH1EIrqx57o238TJp6GbN/pbN9tGjXu0JEkEifakVJUjQ+3Idmy+2jgKTiTOzg0cBzrsmY34JF2yrzaFJy0Ysvnjt5a8V9yu1k15w+VpIdSPKkV1MldUVnujdM1/wDA2bN9tGvdo0cTicBQTJMk9k+1IqSpHJxORsn6oSFIpR+ByhHqI9U9TzzTFxZryvAiRdsy8UjRxbIxvlPhX92TQ7KYq1b6nSrqis9s3TNGv2Nm379m+2jRr3aNHE4igUCgUCkSEIUs49mMY/ZP1RImNjo5nM5nM5k0KjYiSe1Lc0f22YKTV0kqLOWjmOijRr9jZv3L62b7aNGvdo0cTiKBQKBQKDiaOIoYsZwRpdtjY2NjY2cu8/VdlQ6H7pZLExMlki7ZF5opmK9VdaOe1Rk+9mx/rbNnn4dGjXu0aNHEUCgUCgUHE4ikWNixHBGl22bNmzkOh0NjY2N95+q+JCYmSyCRdsqKKF91e3H3SMq7L7/v9R/Bo18GjRxOIoFAoFApOIoFiYsSOKXfZs2cjkcjkcjkch0OhsbH3gv40IkgkXa1uaLG9dsGt5tav6F2SNGh/ov2aNfBo0cTiKBQKBQKDiKRYmLEKJXfZs2cjkcjkcjkcjkcjkcjkbG/bBfyIkgkkXbIiyuyYr2qZX3/AESJDQ/n2b7aNfBo0cTiKBQKBQcRSLGxYRY5R4XfZs2cjkcjkch0cjkcjkcjZs38EF/IiCCSRdsq82ixmya7X9v7EJjY/j2b7aNGvfo0cTiKBQKBQKBSLGxYWLEjSXfZs2cjkOjkcjkcjkch0cjZs2b7bN/BBfyIhCJET2yL8bRaGMX2V3TNm/g2bN9tGvfo0aOJwFAoFAoOIoFhYsKFKXfZs2cjkcjkcjkOjkcjkbNmzZs322b+Ofuvr44RIhEskQ/q0ZEX3n6v4tm+2jRr36NHE4igUCgUCkUCxMWEUSu+zZs5HI5HIdHI5HI5HIbNmzZv9Nff9P4NGiZJXZGySRdsi85EZEPtBf37dm+2jRr36NHE4nAUCgUCgUCxMWEWOUaS7bNmzZyORyORyORyORyORyNmzf66P6fu0KRQcTXbZyEyCRdsq8ZDIPtP2/s2bN9tGvfo0aOIpFAoFAoFIsbYsDFilGku2zZs5HI5HIdDo5Do5HI5HI5HI2b9u/1Uf17VIp77OQ6N9pZLJZIh+VaMiK7t9tGjXv0aOJxFAoFAoFIsbFgYsKFMrvs2bORyHRyORyORVDo5HI5HI2bN+7Zs3+qj+vZJ9Ds5nM5GxHI2SSySRdsi85EWh/Do0aOJxFAoFApFBOGmLALHK77NmzkcjkcjkOh0cjkcjZVHI2bN/wDwUf0/ZJVe7ZsRJJJIu2VGRGRD92jRxOIoFAoFAoJw0xdOLFKPC7bNmzkcjkcjmczkcjkch0cjZs34p/8AxUJeK7o/p/AhEkkMntXmbRkRS7aNHE4nEUCgUCknG2Lp2LDKFKXbZs2cjkcjmczkOh0OjkcjkcjY2b7If1XyP9lE/V90h/ChEkkEi7WjIipOJxFAoFBxFDJwULAhRK77NmzkcjkcjkOjkcjkbGxs2bNm/bJX0/1tfOiPq5NEof0/hQiSSCRdsiKQ5OBxFBOGmLpxYpR9dtmzZyORyOQ6HRyORyORyNnI2MfwyWP4n+3CI+qRUiWin8aESSST2v6ZwbFgYsMoSS7bNmzkcjkcjmOzmcjkOjkbNmzZvtsQ/hkv4V2f7SIJGMofxoRJJJIu0/fxPu/lQx+5CJ+r+FD/AGv/xAAlEQACAwACAwACAgMBAAAAAAAAAQIQERIgITAxQEETUQMiMmH/2gAIAQMBAT8BwzDRLou2mm0kfsf0XVmdJuoDJLqlem928Pphppoqd6On0R+xXnTkbUhISGO0Z1TNNGacjkMQ3aIiH0dO9P0RpGVKm600bNOQ5HIfml1fTejXVUurp0hj+EL5HI3s+qMEurXTDKwY+iJCd4YMy4jH8I+jDDBxHbqLrOjvRdHeGCOOmYbb66IkRMPBtrz3cc6RYn6UZS7KnenLox/SJIXZL0PwxvTKixO30QkYYZ3bHI5GiH0aGIf0zpvobNwleESL64KJls28MpslIciNRHS8011fVM2tNHv6NUfL8sWt6yRHB4RY1hFidYYLq6wy2Nkqj8pXH5WDVJW+mm35GcR9Ph9pMQqwfR1pyNpjHUfloZD5nTKlP9IlLPHferVql4JITIsVJj6MbG6VsZFdENC8G6aajTUN/wBCXfDDLbuKpoQ/AmJ2xW6wzo6iuzVb+BhxRhhl/BraixDraY3bt0u0RjRhhhno3olnoYiSEJiv4yVYabbpdk+z6rrpFeReh19qLFI00kPu6QurPqMMrTDLwcP6PnWIv67sk8eUiSpMTqXoYxC6tkHTZolndmdEM3r/ACa8RJqPlkdk+TEMRJCIiJG9VbpdHSNpLX6H10TrcNqWM5qP/KOLl5lfJGjW1ETrOqMMJKl0brRVH76H5ZvmkNGXteLc0jlJ/DhJ/RQSuSEREYMY1SEPwSdJ26eVGkf+j6abvgnLgiKxVp5fw4P9nBVlcj/Zn8f9iil6EyLrCQ6SNwb0YxMVbTVJ2mJ3h4Gzj510onw0jhJZeeuVRYqa0aMPg6ZIiLo7V6cjkaaaac0j/G9Gqihr35UZGmjNJPpMRGmrbMF005HM1s4yP40KKRERyRyN/AapSFI8iRIchvaYiIqZu0lUn5NPLFCR/GhRS7b+JJVF3Mw4sadoVMQlfAUUvzNNG6VtaJZeDiYRpoz83TTTTkba6u2MQhq1+Pppppppt4YceuDV4SpXn4mmmmnI28MpK0YYKmIdslUfxNNNORyNtIUTiYYZ0SrKQ0Z0bGMiL36aaacjemGGEYmVhg0YYJdEK3cjBiF69NNNNNNrCMTicTDKSEusrVaaLto6dIXbTTTTTb4mHESMIofRCHI0TNGx0q20MTp3hg0MQq05HI5HI5G1hgkcRIcTOkuiQ3l7eHESwbtIiMXVDJDEL0q1SHa+1LoifdDGK//EACQRAAICAgIDAQEBAQEBAAAAAAABAhEQEiAhAzAxQUAiURMy/9oACAECAQE/AbLLLNjYv00fZGp5V0eH4PjLjQpI+4TzRRJ+tcqKKNSjU1FGxxRF0Q7dmx5meMo1KzR8LLEyT/ydUbYS7xF/gzsooooooo1NTU15oT4WN9FljW0inETTJdyohErgkUSiKJJCJU0b9G2FiP31WWWWUUUUUUURiUUUUNFGpHqVFEooirkRxRRWHJIfliPzDm3h9jjhHbO/hFUN8aNSivXJikWWWWX2WWPqVlkmeP8A+hFmw/LFD87/AAc5POxubCmJ2V2NCNjY2yhYssssvFllllllj7Z8NzbhZZN9G3R5JHjX6S8rQ/PNlzZq+DkWXlOhSsroQvuFwssvN+urKNR9G45mzx+EPh5EeP4S5SxZfCL7IuzWi+xCWL5MiivW2OT5KRAk+iHSN8UUa4ZKOELKIlOX0pJlieKxfCssvhXGTwssc7ZFl4b6P0i8WWPLRqalCRRD6Tv8EpEiD4alC4v1PjL4MUhSxKRYhDeaKzRWIoa6sTTw32fCL9iXNjysNEo2OLQmbHbIwEIoSFmihIrEXiS/4P5j6iLFxZZfrfBYY1iispcP3OxZY2MhEsXbJvEWNEXxYuFc2x82ampRRXL9Hj4fRobR/wCjLZbLyu0LoTzIS9NYY3yjhoWKzfGsPDJS5pi6JIixM2Pubplll8mPkvuPvG8Xhlieaw/RFi/4fBMXCXpY+USSEij4WS8iRuORYvI0R81/T6fMO+Fc4DH2iLFiiiaEuijXnLlGBNZZ5J10ucHizpjWHm+FCVDExkWIRRMj89LGLPjXZJu+hvossY/+84sWX8KKGsLovKWHldCYmWSfRGRZfNjFmKoR9Hmvzn8RD5hiZedTU1NSsUdDeYsTz8eLK5MeY/SR/oglRL6ViUf0pSHFrKi2KFfRf6Ys9FosssvHRsbPkhPLzfKhoYii+jxsl/l2NYoaHEstFo3/AOGrf0UcN4aZ5FJHjlss360LFcUMvESYyIiRBkmn0O0PNDgf+ZoalYpkuiy0eSd9Ig6YvcmReKKGXisUyKJkhfSNEl1iEDXsk+NGpSLRuWxk3+CgxeIUEvc1hMixFFMjEoUBRo6xNEsRY02jXX6J9EpMsRWNkblvlX8TxFikbZjjo6KGSGREybbdDH2amxs/7kIrKlQ3eUWMkIgz9Ghqv6rLzRRQkL1MeIyENfpJ/wA1l4oo1NTUo1NTU1NfSxjEIb/kvNGpqKJqampqalFFeyhiPz+Gy8UampqalCQkVxvjZfDYso1GS99l4oo1NSiiuVlllllllll8WVhSHLDGL02XiijU1KK9t/xMYhcbzRqalFFemiiiiijU1NTU1NSiiiyTFIv0SWbLxRqampqUUUUUUUUUampqUUV674SEL0S9S4r+j//EADUQAAECAwUHBAEDAwUAAAAAAAEAEQIhMRASICIwAzJAQVBRcWBhgZETI0KhM3CxUmJygOH/2gAIAQEABj8C43zghhwnoc1SyXU5BbqErRiPDss0XoCdE0Mgq2CMCwxdsTcRM6T9Wb90VgsIsuiuLxw7o6Wbqs+SewnsLXot7ET34e62nd6rHb5sc0Ft3aLLMKdoHD1xPhfqoh7zsZSpYRgkU0U1Lg6KZAVXUgqqdkypYaYG6oLXtZHhZxLussICrrt1wcFOJSClJV1XsbrV604IYtaaDUUzwN2x0/WW7WxashZW11dxT05qSey6eeBuqBG0+FSyqu6DGytteE8J7fcVTp+qhG0qqkLBoz02GqPfA/LnYeq1oqKirifg4okCOeoE6BtuH46nSya9zhY4BpZ5lbgW7i/hRQq5HTUJ5MggnhTLuU49IRwHmZJwr0KaKcKyRfGi7SU/nBlsumhsbqbcFPRvhTqnC3Vlqmd/KzbP6XP6VSualDY8aB7KcoUYhuQyCbCx3oU46vd4OeFxZNXoVMKiyrcUtmuymVJZy57BXRIIQw2NgEQTih6uShwYwvAu2hIJhJPE4HdNCLSeYw/iPxY3VSjBzGpdFBYbW0JhStofpc1zW6SqCHynrF3wkKWBwr3PmnHSnxNgNkO1grCnhrzGi5X49j9p1dUcXJ5cBRU0s2Ce6a9LuxHEDhMHMUsvbMpttD8hZIwcOaIBfp5ysxl2ClMr3X4oJxGqEFj62Wz3THQ98P44qw0TjpLnEy8YL8G8ExlF/le6cKYIWWOJb38KcX8LNtj9qpiKlC3lZipfau7L7X5I68rXGJ9JxRCLnjkg9cIjh5IRCh6g3fDeglEmi5Jj/KmGWWJbyzLkuSksqaZ9lejmcUsDKWi3MJk2I4/xxUi6gCgcOeFPsy6/cFOfwt0LcUv8LeUoYin2kTeFkhbUbRmpWzWULeX9SL7W/F9qqninvCqfp7dtCcAW6t1bilANJzrzTqWjJNQ2iLlzUufTx78JKxtaac6t2One38UXwn6eDwMuC/2jXunlY4qE/wB9EfTMPUofKu2Md02N02E4p6r65h7BBRQfWsEIrbpqE46cNOakMNFIkL/UmMjq7QJ0NoE41YPOARBOOfTm0ruyDp4y50ZhPAXHZe+mI+6ZGE8qKScaj9kBg/FFQ0TjpoOiwlAE0Oo4qmOKeB+cKuGoor0KvAeQspU9GSuhOrxpgkn58+neMf44flMKDWfTvwbpTRVTw1UpFNFjZZpr8WyHlXoqphRMKDC/I1tbpDKWg6O0POaB78TdiDhOJw91NTmss1RUXNVtvEF1M3R7LKE8RYK5sqcymGK6U/ST4sfQIHhDXGNsDFPsy3suYX6kP0t8fKp9Kq5LlZVTiWSFPGWCYYJLdbysxsn0kRWti+ET2YqOA+RquUSe6hhCh8ajRB1KSkyle+Fvn5X7fpftVV+4p4sqlW3LAVnjAWbN5Uro8LKLK2NY3Rp8rJaFw8spQNI4Feh+RqDYw05olRxcocoTaU8e6FuQqQFmWElTYLPESv2hSmsoUypnE9j9FCmmGMhXzuxSi9ijEOdVI/8Aq7RdtF4iwV3Z07p/3RK7DOIyCEHacXnQmVVZYUxkUxxSBKo3lZ4/pcvlSWUKqmdS6efR3FrYTGzwR7yGyjieE7sSeFTTRTHupyUogbZlTjHwv04ftPGVRXoqr8u03zuw9lPeMzhzFSmsslOIm0RBAitsoD8r9SNvCzT8lZf4WUKqmddrJ7w6MYYqFe1gOFjRSe4Vc2s4e6eFisqoqqUS3yqrmqLMror2V454+XYL8u1rywSCrZRShksx+lzTGy7FQp4yFkhHwFlhW8pnhHQI6I9rHQuxBwVe2E4eymYofcKd2P8A4qbP74aLeHgJtnlCaEGIp45xf4wNa7OnEgrsRTCKS9045cWyhvUUujuvZN3x54Z90+yjU3I+1uBbp+1K8Fvlc4v5W5d8yT7WK97BNAABhvNS0PY9hi5Wex4tivY9CbFJPpThC3IV/SClsofpSDY5lXaqVjELeTQBynjkmHHbo6LJTTgqtjduAmVJSVVM4H7qgUrKrKEb0yiPfi3hK9+hspYfOpMqSkqquP2UysoXZTNuUsp8bPoB76IOOZskLJnTZ/QslNPyTY5mzkqqVkz6DnZRSFs+Ea8pD01JTqpf9LZ9Tn/cKnp+ap6fn6fop+n6KdlPTtLJqnp6imVT09RTPp+inZIenaWTKp6eoplU9PUU7JD+1X//xAApEAADAAICAgEEAgMBAQEAAAAAAREQITFBIFFhMHGBkaGxQMHR8OHx/9oACAEBAAE/IRoSENIpfClKXLf0oJYSU55kEKNIaH0hjYbfDZNof0ZMXs1GW8IeWhV4DNRkBY8jiNs26G1nZ6NTRo0eoqckGwNn5zB/QIQ0haYdIZeCxSl8F9NLCw3MXuEU3URHDB/JVvgcT2cxIX0fBzwPMJhZTjGCbzBImEFQxSE/a+B5U0hWWpoQfo5jFzhQOUQ2D0PQqUYfJPGiZS4flSiwcLwSZo2XwQliE80sCULg2x7fB8JDyK/2NibqvDJBG+YcjaOhdbwPs5CRBtfZQ0pz8J57hqMDcXAsbnFu+5odemhJKPLIMTYuIccaao9Lwg3G28wmIQXjCEIQhCENRR4X0yEw/NLE/wCefCGzV/Jsz+T7L2RSQz3M5GOYhuQkUNa62KNs5ExCEITw0ZusCQcEMsPNWPpoWqdlFjTVjvDcjhHIRqaKLsmkmINb8IQhCEIQhCEJ9BhBseFm/RhMPyWCXXBKMe3Y2NH7wc40tNdbM4Xf5NwNhsLqPZk/sg9YyEITEIQhBLeJIeC7EGtYUozfuXZuYF8MO0SihyOICm9xNhMEIQmSEJiCRCEFiEwhCEHhYf0EcxBy+gsNWfZDY/Lf+DkWZFucFU/WpnEPmQmkkJ0QgadtbeD+kljQEDQkUKw3wtOp+DU1WfEj3CWuCYkaXwRtOkOqxYf015Ji80y/GCzRmof0Fg/sNmDFp2K9BpHM040bGw6piI0mP5EekbyV9DGbf1CjEgYoTMb4Y/tMF2/2D/8AvK+n2EbbCiWtkLaBTYfByjmQaTr0dWh3hFU4L30JR9Dng2aUpfpUpRMpSlKQmHieSEqasrQ/JCAKjGaunPAmMbHuiK+cEcxeDhHLGwbKXF8UsNkNPEjppm0Byblb5wjkOag27PcL+hLw2wj6G6UR3BoyvJozfB/SebilKJ/QAfhPFCKsmLYQyeVhxYsXL7lGLv5I17EJvFzOA5BjkPyTPhDfwdSOyMfWQfObE8XRQhihtJ9+IgrlYBox7VEE/LghREx4pfBMo3ilKXClG/ELh/RQjmdDGxNl8EITZuEhsf0sOQRiZyCREgWCOXHmPwpqr/gdnMcgMuUsLOYSmTxrXDE/ZHDBYbR7xa06FpThi7ELZuz1cCrBpJsfjSlxc0pREY/CiKMv0aPs1Qzshowa8VGkNI8BsfwhnMY2l6N4ylWbwbiFNhKeJT5GLpQ9wh7ZK4SOo+B9K/OUsNCq/QZ9nohB+NKSc/c02wg/A5Ho7h9xNAm5nJg/MPARMVyT+lfGgwgyeC+ohSRVi4Iho8DDfFIX9p/OyXRLjMd+I5ihW+jKyJpsmhYmYGGnJXpjU+BHlRpeqx9SSG8Vvl5RXAtI+1eAYQYx5o6Tv+g0r8ogNG1fqHWEjk/x6GDLMXuNCfg8UvlRkWFAgP69mJhRgQjngSsQaZAwzi7GPvHyYl9USBRaP+IGvYfHD9zNR+0TYpINUKznyMcm/NFCopihdX5heHvTIY/DU9aMbV1n3q7NIKWXDItOmXeCaGIDLlKkhrDxfJVheDbhRJjck+ogsQ1xNULlE2MK2PE+SI2DTsWIzOoqOwjkj5hDTh8CxUikkbDVmtKBty78joLi4zhfQ/s00cmkmKzi5nh4Ws9bOaDvgCDeFbvIaDYm3EIXFIbBEEtYYDHiZhRiBaZmEbRrgbfUGIJSKYhRvgj0dAPVEaZ7yX2Lymxf+ZoQayFtfq+BqcaJ8kJIbOE2biNFBjUXzqduJDWiU6XR0PyDsipzob+ihVtYJDQ+G/5HyUqj3n4foXpgwongGMbhfSoHrQ3XFI0Oi00Jzo7K5pIKRBDTFPAxCYJsCRDGgevNHELA/FlzZkEVLFaQQQQWyxi/iExXR9TA8SmFzjyjbYuzpXRyNpBG4ibzkWNE1oqzxi6KPAkXQk9EMX6lT7j3IjaR+DWb/mQsqG/2GhBBBcGL5CLM1OJeyb25CH8uIWpXCObwUUivsuxdXr+zK6GdgtqeByDEwwajvBYgoIRphfA/BhxhecEi4iw3eEhZIwbGy0GsYt75XHhipKs2WuBGnR9lxglp9+G92MoIOBMVdGIDTYthrLeufhj3r73yfxJFtqn2claX8M3aPxE/d+Q1ylDH/Af4Tfg/2gycT/RuSv0bmJJcELkaPLITi/uMZKE5kSZsKN/9D+Ue8izxsd40WSEohkRFg2DlmiH8VmceUJh0mK4QmbeyNtjeIHZp45obmbcXEg+q6xSamj+IsFtZUYSEhoLUJcBGeyHCRL+QvgLGJI1UV9AtsK5qx8Ao39oxzJVqmy7/AOjtH6OeSUqOrYvQ2zfesJk0fH6OGJfyaw6imNbKOhLle0JqbED6Lg4RaqJgQNMuiBujmWiYQbQ/BLI0yQhCEwOEVyhPGF8spxpjQxobvFCVLtiUe8idC+K0QRC3cRsbUQ4ZqNF20a29Egw+hxqMcnJ8GidY1aJa2OvQ30IdHLNHDnvf3G1SH6EZbHbkgUvb944sr4qC7PYSPQ3rp7Nb2O6DXYFzvKxPZAbqGhNZwhMCUHGJhMajSQ8XBvxL4Ec0vHrghbEyiNHGHyPfwQhBCw8GsqLf97Iuyj7Md1TjhMZKiXrKsSmdfFMSfQpcHUR0yVbX6DZz/AdxfZIktq/sQUqu2BhjcPavTHnnQxjRAYclkadQtfRpfnEUzvyiieL6EEzlnWEIQSLMjSkmOmS4eViouJCpoPDeI3vfaKUYSJC5a97PjVNe0WJPyFlFKUbwyRsSS7Y93vT017+wtbrSNUP5Y5Dyj8D9g24xuOcHDC2ON0jQLNKN/lhTD7ZqzOcjaI410MXJ9C2ezWnI/CsJ6vgdE6X4OINeDHKIJsTQ0ISIOMDY2XG4bvgsPKQogoogz7D4GFGV4TjKF9CdVWGHNr5L8kOD5T5RURNcNEv/ACvsIr8Bd+Kuqfll5I/g0ich9okaBfkNAtuOfyTX9Hspc/cbhp7BrZRyPXkk4ifiCBBYdUYvUMjnKLQOL/I2+AZumdYW2Mo+D7tv4Nx4HjeX9xYiu3438g1iCOGFBdCCDcwsNjw8NvxWGTCzKKJe+xmfWNaLeJSF3phPEtsnHCjT3p8CP16GoUNEtSfi/eiU5fkpdJX8H4gf+0A1U3sbq/NOHlOWH1ffJnjvwf8AeK7GIuCCd9Fo5jwXTDvcGfZT5H34vXBqHRKfsX1obJpj+Rce3iig3oozX5TMeOSxjjRR9Vxha2eCTwQmLWhRoYZLC3h4Y8c/FeKCiimqo2XSwbUGJMpJvHC5bFcn2L2azb9HyjaqfwE0Vld9H/3Z6wyU6cOWQT86CTjSmkIrUfQjR6V0sbDdEHVUoiXYe28iBOJQh98H4GF0TF9gwqBmWz2C2P0QsLuY49Jnbm7Xwy0M4smnhOw0THPJ0TLeTyyE80L4F6vti4Nce7wZEcoUs4a8SFp6faLCa+npjc4Hq33Bbn9R8T9M4AkNO2H/APEDriX1syMV8u3lrg2MK6G3PA3zY0DDEhBFv6LoReszgcBynJuG534FOBfcfW6+yGuQa5qH3H3G74G/wP1GGOD8Af8Ao0kkxPf4JNDw2zdCHERsYmXh5hPNCC51SbzhhmaLB85jBY74LBjE7YWnLZ/oiNmPXpCX1fwJRa4E7A1axPkSIQSFegPXHh8UXdGMmXV0NVcYIUjtNCqXS9jdNFi/oA2L8nDJdYPtgJ7QtTVJUx0z25BfATYuhxhqZDxNTDZfpwSE8BaNg2CGs0qFIZNEZ8G0yhEheCiY8aGgnkNHS3sTDsCcWyKYKrcG8iD+JKxbYj2hs4Yw0LkYTiZwNFq5EJQnELW+MxjH5r1v6dkO+69kTVTjf/JrBNmn7yCiCsmT4H3CiEcGy+T8FhIUXNaC4hBNDqEMOi+H6R8nrKYw6uGNlEEhzwJzATsyAFGTH7Eae8Ko5YlwGJvPQg0NguG2Da9cIfBjH9Gnsf8AQRyhpLWyoU/fSemPr0RZyF4HgSKjFKJm8SnmPzvghYKKKLhvGo4x1EBaHp5kKs/dYgqNfMJqkGGPCeCVw3eBd0bF8jFDKGGFgsTGOWYue2cTtkhZmP6VD04ZbbjrD9hF/GKd1dEkzuma/Fw9nT6RYQvN6x8Cmmc6MJMk46eneyCRBU4Cr0JUNVEyQUQQejYQQk64RZfGDpvKCbGXIqxpM5YlPViv5Zqbt9JPwBjH9DqeywEwO2/96wlNiLdiCiCj8eWFMJieSyvEHwaqhFlkMeLjVfBtQsu1p5FOzS/JyxsQ8n2oP9L2zfb/AENOyL0iPSG7lf0cZ+QE+mk+dM3RfzG6HiLA7RKmS4GwStiiFk7WiSp7moWv83xgxjH9BEgw1K/xFOtvlezV3pNDnrEt8IkGvI1ExCeSysjjDjiOd7xLseHqC0NR5im977GHOA2UauCvI98oSLwP3h79EX/oa+iqini0EMeg8a0yDi0aidotFR3MUP0FEO3d9fYkLewpdk+V7P4EDGP6L2nKbiv8DPvj/ZJOzGafxYEIQgu8O4aIQhPprDjDCN76ySYfUxDBCulPpHTjFQYyCQhpT4Q1vo2/ZOkX1FdP+4zftWHA2eChlYEbWopc4sIu5D0N/s/B2nQ8VA1dgxXxn2HsY/KjHBxdrFubl7YvoBqb94uQqkejQlbcdKNquGOYfJ47EIQXYg5jxCEH9JYcYcQtUb2sC4aLjmCVeS5Qgp86DGQSFgOi6Xl6Qkrn1RFnHJwFuDYLIV0LY7sDU6YtM+XyV2Gp2n9bNQfsYmtMaeqNl14JoPbE42+wu/QC/wDzI4ADT7szblBqvhBX9Q2kdjxoGs8hgg8vD+ghhvCNib/OJdjw9QS4SUIY+1/Juj8kNDEwJDad6Ddn/gG/KPqoT2RxHg2LFFLYmkEh4oOUbQt49BLtz2cE/JCWuk9D1mG22oy7aT8DnsfKxcJNnMboj9bPL9iCCtBG3gQVdYsdTsoUKehwdITjPvPlEUTNJxGKUpR4eVleGNMDiK340flENBQ3dG57OCEJYo0OGkJkK69nWlgmK6U+qhK49aPvYTi8rwx8yRyNgi6kpp9Mu3fbg7oe0OJT50YnSg/Swewvy2OsGvb8Eev0PgD7kEdp8IadL5Ythi+O0i+YVwRt/BLdp+BP/SSGhF0xJ1cEWLVcgvgm8HnhvFH4rKWNIPgfBFFHLgXDxMSoeT8GqQXRIhp0WU8Ec79MzUf/ANB99vvr6q28CO4y/wCB3aRs7GS8PhOUGUEEGiCfJu3Z7dhvWH3HFf4R7aDd1+g+u/CF0/xCiiT+Thl9mfOVOaC9vRv/AIlbNxTfMln2iCeqHX0doU7OV/BoPKhE1iDxM34vxWEwKBBGjzLE2wrsZyEizUInr+BAigaN8+IQiD4ejf5UYRt8H9Cyzf6H9Rbbyri76F/ZoXB+QiQnSyvKDeCNwmxrhYyEVjbuUhpuf1kX/gdFfZHyi/ggjnCfk3n8CjXpM/k4mOgDnk2+Q0ICwWydRGQehmkp4AIPIoSeHh+KyrCmoryTCxquDcJiJqFWh7SJaFchChzhLRBeCYiF8taJegcouEkn+zukv0grKr33/X0WdRHbK2tufY2VXivSEr/cxsje+cHGweJRvoldZ05v42Kc7+4wq+Eewc0zfcMo4+Eevwhba/gLo372Fsa/Y9IOScbIi8bkpqnwxfYD9Xw8AFEGOcCg1B5fgsdgeBuP42yKHgZuNyGRwnRo9W0dca1QWr/dFGEJnowlXXyLf9kJemKTv9ESjUJLf/Ts5Y3+dn9t2U2hfdnJL9jVW+Q7MudC89/SE0ZX/n4REHV6o3t7XNNjhlHB2xxhKfzkMcF9IeBtCOk009NF6pU4vL3oObT8EogsMSiR+A4+xL7HMpPf1ti5RWn8o/YDwAUaFycrCCDw8ouxaZ1sQ42RfDo2PB8Jyx6AxMemIYNHY+q5EeU1MQQcV1uUXduB9ChU6uyK6Q+0U2Wm3+6F2n5EUahrn9pyTCT4kxIUjknSV+r/AGypP/Bh3A/B9YNJ3FGou9/gtvY+XQkyevY9XEW0z+40FTZX+s/kGH98BwkL5Z3JfYf1jH/hbhG2h9sBr2LVfFYaHEHoauBjxCrJPHVg2R89lxsNMezQqfUzQbtH8Xjm1DOHggXlaxRBBpS5SY3W/dQ/eK/8NCPRPt9/pibkPRI8AxxP0fZOYn6F/D8iebfuF5fyPko0OREl/Hk71NFOD4SG622eoXs/gAWhxyn2bqgrrENAbD08WGz7L/jT24Zv2K6OJWq8lYgixINDxChFeFXCw5YObCYsPYJRcHKZ1TSL4laPSOO1SuLQcxw8UQQQ4l+DkYn+gxLIntQaB/gqNG1v4L3+wn/o6z/KQ+Yd+Rx7J7LbhvsInKukPNGx8XyMcx6q/nCET2uAb+ANtG5SB/5SqKRUydK+IhBCWNCEEsTRYn4IXgYW2UEzo6C5eUdk0LFMRoUF2ot0fwaLGiOuUbM2rNZeUzga4fhRBBY+Tv3Q2c/qGlYoBQxX2IZZZZbpPbHwETUKHqI5PaDEKdLXaNP/ALG3amdwbW+wQ+EY9Kb6Emv8momuuBajkvkUovNJEzksQWYGH8kPsYfYmjHHwkFLvA5acPZOxs0CeyAQ0iaEXKHouTL0bxyITxviLT2NC3wht25i33ge4w5dh1yGjTXQuyxdZBv932E9pCSe0j3B/CNpfkYt94sl/wDioxrFPliMSvAzetBryoTgTGuQmsH34qLEwjuEVU0CQ+KFt+G5CG9sShsLgi40iKa3CMutPGoajUYZsXs5g33oY4w7oNnOFyj7SRv2OMIbQca/wOWGMMvNwdVq/wDBqGpZtlCEIJYtGsEU5DXlkj0QxoRdYGPEzi8VDNt9xh8FroWXB9IaKGtNGtV7K5FLqHocxMFpV0J9wMtxk6GvbHDhBHF7Gl3THhFL9BySUbGz857+rSca2VihCEIJZCmuPUxrxa1xCwK0csbCwULkhuxrGwTgyjdGJ7GGxNzcITrG8BqXkcaKgmN0MbCFb1NJj4ghHunrn3FPc9M7YYT5iSX1U3zRtvl/4MY0RvFCEIQggggivEMR7R78SdljbBzKPEgthNNR/cXAr7iRxopL2b0dTRuNQ0kaBhhxFKxsriEJQt7buhqzwQsFyAIXwLpCf+hwrHy2fNiT/BXHlSSnBv2LwqJG5tiyoQhCCCKC84oqCO6OwQcePPCxcxt5uGR4Fg3FY4wwiwIcCfI9GiYGyp3HaG2Bqmz5Mj1/irjLQvpG32TFKMGg/UrZTxQhCEIIIoLyiogigx0N70JXIkcJFH5CreCxcyxmvC1eXhDvEofKDiYEbuGXSiA5pis6L/Gao+KKxM0uYyhFGEIQgsCK8gqIoNfQx0ewSxI4RcGGWX9AHUsXPzeEPPBRsXx3C4s2qxDWBq5NdwlD2zIQn+E3RrFKXEeCEIQhCEEEUF5RRQY+EPc6EOWLrGlwXBllhhhlll+NEbCOBy8nlCwcYcYcRYFFNiF2RRuiibFrD5NU2LAiyn+DyLjeCEITEITBFBeUVEfSh3oT2OkNLhFwYZYYZZZZZZZZYYeA2PCOByH4vwQmMNiw2D2iDYpzxEbvZQWHhV7EJklH9WrGyNixQhMQhBBFBeMUR+Ef6PYz5AS4EUuDLLDDLLxWWWWGHnXDH41H4vxWHLBhhxHM94k3gxumFqH8Ah8s4/o0kZrZQihCZhMEUF5RU+Ec4R3NCPOxcYUuDLxPAZZZZZeAw/DLkuGPCxyF15PxXhrDjCKV4V5DRHjlfXgIst+cY0yN4oQmIQmCKKC8Qoi18Id50KcjhhwXKywyy8bwmGGGWWXkXJSiYsvxEpa2MWGPxWFJixsHwSwcmBB4aqcPvmlL4VDNm3gsUzCEwRQXlBFj4Q/0e8dIaXCLgwywyy8VlllB4LLDwUbGylKXwQsvxmV3hZeJgsWAhsXHxRPxEflDaLxpIzWysUJmEJgigivEIehDo94+UFwEi+BZYZZZZZZZZeBY2LhlGxsuKUpSlEUpSly2y4mLMFkiKgRr4pcRShNCijHhevhpjRHikITMJgiivIiHwnHDuIc5sXGQuRlhh+FrxWWWWGHhQTExsuDZSjwylKUomIpS5uORS3vwRQUJJFQ0GmG2J+/ApsFqs0gxOOjDb8NMwhMEUF5RRc4DvOhflThUKUYZZYeKyyyslZZYYZeKlEUTHkXwY/JC+hyxfPglYohDOzbI72PQWw2Jx85NmExCEIQhMEUUF4wFj4R6QLwW0uC4MssMssvNWXiWpuGGWGKUvgsUvm/JC81jkJHliiFmJvwomwYYccccR2ZBfCEwRQXjAPgOAxjrqJcCSLgwywwyywwyyy8BhlYG4pfoIWG8rxY/CCX0FjlipvK7G4GvhS4Qw4w+BhC08JJlQQXjAeGY7hI57ZwYXIywwyww/CKyy/EinPDy+ihCG+lCEIQSIQhMzCOeFNjEiSH+gsjDjD4dG5+CF4QEXuA1yoL9hx6HBcGGWGWWXisvG81fhlGLnC7NfoqRBIbwvGEITCEIJEH4rKZzFxmNhoG8oTxDjDjiNxfORY+FlFe7CS4JIuDLLDDLzVlllhh4kWxbysMQsX+gSEhIbC+hCEGiEF5rKKMSCptIvKpcQgsHGHHGExbYlOuHuSRzWzhxFwYZYYZZeAwy8Bhll5lEGooxYpRsTEcRx+aEHpDZWVm+MJilL4Lw8zhhyx5+Lwsr6CzoRXpeTGMY8GPB5Yxj8/DyPDlg5D8kLHiPC8F4LKHhjHhYQsf/2gAMAwEAAgADAAAAEDjskNe+ffwf14oc/gotU8JeHQlxWK3VlC3fLsv524Lg8fdq5xdMwfDH1+BOcmmcP1dGU5mU18AWU+ZHVe0m7S8zcgy+Jj2OkkJnq1rpjuzD3L49ms4uX4yaOpRbi27nkSzLshS3iBw7XzJt4GRN5GihIduPna+fDx3Q2Fgs/mmbmu9tKbP42PsQ/NqpJ+fa2fQD+RPJcocef+kSMNHFgNNQdfTJrVRwzYFniEhj46zjc6arLM+m/mkXOldFH6BCTHyVaBUF96jl+QtuQqadorqX06uQyHlOuYaRzLpkHBPAXe1kdckEwrwc6OYns+Yv8fIgnNFg362Kxu1vENMe/A3RrFngYrFofnSGu1+zKQjZxvqjAREWQitt/Ezm97ieIK2YmT6AtKrLf0zP2kDzbxt1sFlJ5M52u+i59JVyNknhii0tYBhIu21MOHZb50j7HhjAlf8AydP97EnAjsh97RqTgWEKsdlWYsYECR4fmechi+oeFHKy/LER+rJ5ay3fGG2I66/NlBya4h45YAR7IyF43HUFO5lc3zWlYdP9pbp/24zRGab1YB5cdoBItzhmK2WjlLiyj0yFIC3saSjtlBvW5eqU3hUTGsYv0z/kaO5JwEtdJqzjLwCJa5rpVsUzmirYPleSNmwTnEtMNODIhEOoYtkQbQTDwy2JI8OdKRggnO2Joi2Oe2b0PGyzihPKJqPT4fVBPuJcZmJBMRj8GiXpJ4kq7tlZFwKigVQV4wOfn8OJm3o8s3OpirWtzjVHYNbOL2jKydHKmO6vsylk6CP/ADQsfexA0/PzQAhxv5rUAyZs4WmCTY8Oc3baSvN2UA2B4Fx+c3SJFVzIETyz65wsQE6rviUuv0D9EXaryy6//q5ALzybhM4xXckvXSjss0Vl2oaMbPk2dxaVVmHk+lxCq085Fa28zUkWhSoZK16mTZ3PnaZ/QocQuY00nuEw1bT8LUnlNp2BBE7Ugk7wZdG/OLX7IrjwxiwyCkCs2Cax7piJh21lhcEX22CWHH0rYgXN13tF3o+/bUqyCCCAAEdTHV2K5+gPCPCANwMn56EftSeK0I8ALvMeZpIHbI9UeiCABBCC1HKF8ev9RaIsvghBrW/CRGHm7oskwuM9Z99Fi/LKwCONx9y2xyJjp4Olm5c6kB86LKeVpEB7KudgDiFNsQCCHTyRwbDPNICpLG/L0PMU7KvKj31i7TcTfFYpqYjTAx2GcyCCCCGkGzDL4EX5yw/pcCg2Vnp35IQyJ1mdTKfNfpaeTTa+a+eOOKyyyGlVIO1/UP3LI3u1hN+97a2ZifVir8scvEM/upyZn42CSCGOS7EoWwT41h53NZfaqwdU7Ewk4P4YEZEt1RXi7e4vxd7ZfOa/XEuiN/Axjn9RaLOEMatxfiTMgMVctDW3w9x+HUYEuy56dJlV9qIdaa87xS8S9WLUp62+7z44CKw+gvQ/uW15atKiyQXLWFQEkfjCJDfi8SZsdMQV5mo5bxoNRQaSyrW2Lj2BCBCf6ahGKQd7oEg1rA1R0RfYeWgYJP8AkRYXffK8WPTXmej/AH17NUIEhT7z8twQUIOeXwL0+jyEwLoAvJKr81Giqap/IcMxPPFs3NnI2oodvL2GpsoH9FJJLkXVxRAf34Ph0xi8aE5syd3/AEn6n0ggeidccj8i+/CCBCie+gDgCdjfeeeDC8+eDeA9A8CffDdi8DiB/8QAIREBAQEAAwEBAQEBAQEBAAAAAQARECExQSBRYTBAcYH/2gAIAQMBAT8QW2PV/JI+3RbDsJ42GWczcJN0RO0PUHXIQiEvUNlYrLOGkRx7b3kN1gJJ/ORIS94W6gEz1E7sHXBbYinuGSy95a5eo7nm3gj1bbk9uGz3hyZF5kzgDAiW2bCKBlGIhnic4NXgQ7l3weAhZx3CDZwR1qGsOEtiAZK2SPZnWBg8FY+WwLy3vBZY2iB2xuzhs7a3ZLkw8tyfUs8DO3g+ENI5LOQc4ru0uS75A2SEIMtm8e5bG7CyIs4AskjtwSxzfLLvi/kkDncnXAxd21JJ1eJ68R6mWNjnYXOkEtnqGxpxGMxMi2XCzO8vd6X2G2d2cCCdJgvTYXQ4ZvsY6u7svkvl/q0SOFhAzznbZB9vZOs6dMv4JIJe5eHgcFy7XyTvnIR13dnZSAO5JOzIVs/vHriXeQ74bbbbLeRxk8bbLrlqDniXHh0OMjdvIsifqdXS2ZYYhznOzavHAJbFsI9x7u2IOTpbbwPYexvOHkScdfsu+7zyFSdEs4Du8nIDkeuRKtk4F8/AHfvhfOGw1Z1wZ8gyDuDDgmcl0ZbDGH/ZRdrrmjX/AAnLXWx+pY6tOrZvK7s0cbyD8GIDJCXqXAr7HOHSe5hEnVhZwJPv5dOXcP8AcF9g3Ut7yB4xG3QjRzjXLt3KPOFlLdLcNl6lyh3+DscVqm73aMnDQtH6WDPsuGRvCdTa8NJbWLqkiGtmmS1jfTkFbYS7t6t4fB2cnyZ8N3Y5ffElbfYn+o/pI/vAn+ITu9gtvklnBFiCPL58fJHjbuWkNc+MuS7tcLk7b3OIMmWVm2B+C9OPs46Ng/Lo8t+3sW/gnyWGHuF94Mfyx/LFj849WS7OBy6gV4Ds+bZQy6TyWH6XWQ/A6mJZnDHfC5wHZI/n/DPfsPjL5ZOzzjG+wBYPIyKxg29Xe3vgcvGTLLrk9Q7OcMsszgWSBPBNplFn9MtL/bxIjlhwFJ/V2kyJeA65vs/2C6Rrg9XaH9sQWSH0gYisZd46j26t7eD+XhYEO7o5bdw5x6Qy6s62bZIOGEZy4Ym/ndWQZYTqyb++3TMyRISWN27I1wnCgawfZgI0P/w4DSWlgynK8xkl22fZclszGHuccvq22PBbqLOt/TdZtvZMY6d8PTDiW0/tixbBlCtII6kPtjerJZjLOJNLxZhw+zw7TcL7eY4ereWItJvKPEtt/PQJ2g+fgab/AC7LUu2fxYfycOA+RHqXuQBx9fwHEIZfSeAsi2vHiHjzHvA6sOpljb8w+nG28FrEH+jex68EXyWnqw7INODh7I+Wf4Rr1eMfpNJMeY9mDHjltIE0F04ltucExu6P5xNspfwun0kPjf8A1ZMDqP6DLtpAcOloszyTfbNn/DODHXC9tgHJAGz1nl7MzJtlhAkJLSbYhMcWsQezbHucGLY2xP8A0ST+zPLGNRMRtujhlIRzWcdkl97s/t/GNdw6llts2JEeYtPWPpeASy/pkJfyW+y/8css4STi1Hj2nXH4gGSY8PUsZSTOLDYMgkETQ8CV71H2dvELPwe8Nt/GfjP2yScHjNF/ZNtjiSJ7M+5z5CAd8QZathdW8I/8mfneNkTwn3icH6hj5PshLvjMo4inUO2f+LLP1sxrWsaq2Qht7l7tl1HcEYZPuXBnUEP++WWfnZE1rXgZtkcsMhl7n2NcWEEwR0z4SP8Aiz8ZZZ+NkcWtZ3tbLXBO+ALIbeJ7Svt0l1xyCHXB9lEez+M/OWWWfjSa1rGN3buZ4CNY8wuuCeI7tIiS28Xa6spRzn4yyz8aSJrWs7ys7ZFKcQoExocDF2QdRZw9292zs4C3SN0ZRxllln42RNa1rdNi2ttJ/BBb2RLZrZLy3Yy9cjhyWJlmKe4X2fA/GyJrWtbrBsplxw3vDHrjOO11g8jitxksuRVtwndsO3qWFt7baeFJ3aOIdzlDJmMY8kNtc05OZIjtgwl1bbbxZLWFYg3vB3ygsui9XngeTM+/ier1wZmZnyP1HDzfOR8/E95iI94I/C9R7F//xAAgEQEBAQADAQEBAQEBAQAAAAABABEQITFBIFEwYXGB/9oACAECAQE/EMcM8WMXazvGQWWZ2xi+xExP5wInRStg2COAQWQQfWWdS4txyxZepDLt5BLHydfYOBG6m22G9k3fOWRCtYU4tGspzItD8nrWaBDC7cOvGzqZttB3atlNAWT8vXgBplpGnkqu36h2/DOS22w8NmeNieS6GEaVjwP/ALes7LxJ22Nusksm8eZV5g43qM6h3hEjjCWN5PnO2222w/kDkbtxXBdHFpS6oT1uhHWAsnl1LZDJyRJsQBeox/O5Phetb33FHUgQSl6CDOmE9cC22wbDjhblkcGcZAWEZd2cB0k2YveNa8Z5ulWe7lnBB7ewyPF6je+2yTl/tBCsGSR2LrdreBsMtJxPGxmxDiPw7hYU1DL1HkxJ7C6Pl26SZllB+ryL6Y01Y64XDWd4EHhVpeqQ8A2O2tiC3OK5m22l6h3nbbbbYYM7nTbMCR9ScyXOpT1tjuLbobLUQ7sss4JvhLwINvGFAZLGz8rv7w4F0t38BfyWBPfTlbbbeBveMCQZsPDZKHtt5LpLzXZZK4wDYy7WCer3sj2TpKURDvbfpAPgmpA8zqxLFpb/ACBb1xvBU2WRwLbb5Sy7lh2WdzcG4dJdscy7GDIZyxthP8ktLG+R/wAcg+IJmXmIe4fbXqG2zZ6Q43kfhm3UFsstvCz14Zdic0NlbFpDmR3n1xBtN6m7Tcs4EC7LPD5CcEou3am28E2b2TBZLLbYey222QcO9cN2stjIOAKW7PCw7YbBjfdgy7hxk3jo8JWTN3wiZAf9SztL3s+lm4y3g4HJdzwbNvDZByspt4WMQvtP/ZgLog323g6tSHYMi4926T8Q3y2N4N7unWQOWt/5CdTYOWTbxyy7gtlknDLON4XgU8sPW2yLvLLZFO+FmcnbZ3e9pZ5Br3KCEnRCnHCW9YLxtvsI2Xgnq2IssBIsIRjOWFlnGfkN3h5XWcYdy6upDYBH9kxr7D3kmOk9eQbI53CJDOyfLd/Xwbs2+hfPgYD6jCcYWE8jZbY/GNkkfgXWS5Dpd2zB12IuvUpzIsuF/wCziW2mxH62L+kmraH46x2WWcMciMex+M73JIx/Vj44/wDsy2Ztf28Ji6TQdQgjXuQhcvtmdTiPy+Rul6rByUH+g6YX2OGDZzt4AzhX/QW7bbyTHUOwCGEDgbZs9QOcuzhZp2TdHbcnvAg6sTqw/TH8DaTqIvqKxT3t+jgW2XjdppcJqSL7AmLSDb+UuSsbvJ650uk6M59tiLZOZRBrnC9LZqGPDHpSY4/o3SDiDrh142Dy3bBkcNRAFi+X/babXy14+HANtsbPJtu3lt3hwXhdTqMGZdxZ6cEu7Eg/7wGNl4BB2gdvhG+SRj1v5XfkEwN09bB4Sn+CG2GxMzXbuOpeO3OGl07nU1LWHxiTZJ4OHZbPbT5ZfJ+BHbmRkGQE4yvJPd6v/UiMtW/5KUd3azJJLLp3KJvUOroQZNhLoYWfCtOX9QybO7Thn+RmCQW0dQMgIhD32/yzhLc4dYZ1asEaZmY/IrIvYEJZNO45vwtDWc9mKIeM4CsPWz8lfJb1jsniXB9gOiDP3llllnH0ts21kTqUuy7SPsAtF18uiE+3ZYK7I3q0Smwkf8WB6yP/AGX8Jb1tt/HvbLD/AAyyyyzlhjDY8RSPYEp9tpcJ1F+wjPuT5aIT66kdJARg6JT7/pn4yyyyyzjbbbZZdghC1DD3JF4BLJF3hdHgcdWkitX/AHyyyyznZbeTWxYpTijgIO7LLyLbbxGerCX27O0S9f55xllllnO2zGawmKQ4CkITXALO5tlhtiUIcfE71/llllllnG2y8NbFikOCUpwAg8CJZBkyQSWWXnDDe7Y32zjOcssss523hq7YpCEIfirCzjSxKQlpacTtLbLIjUaukCF4wzZZZZZZZ+NscO2IUhClxBwQ2/gNXatWuGuDjbT1EOoC3t4jllllnO2OGraYpCFJkEcLbbES228N4yyyzgCcOMsng5EfybLM1sWKQhTiyONtiRsYhSs3zEOccLxkxLb2NW8hZZJwHTDkmVdsQhCHLOA1PE073iBlizAgWWXXAQFkllucNhi88PH4OXg+zERER+RyfOSfPwRMxERyzyX/xAApEAEAAgICAgIBBAMBAQEAAAABABEhMRBBUWFxgZEgobHBMNHh8PFA/9oACAEBAAE/EAxMktZ5ZUE1G7C2BLDiw8FwcRHhYS5cvP6DhjixirFejARUzRvLMLCMrMsqisZjVeI6+KO1Kqx5hH9AQ1CYiYqTql5LWXFmKEJdGylEz26mZxiZiUjiItM1S1niIGZgmhAR0djC+szauZg3r0stjDtjcJG3w0xy8zqvnKhLgwqUeQlS+LhCEBBZQRnKUyo+CIsLYOGnIsuGoLYkqJE/QbhriyMsbFYW44Ries1EWogx6zyZTxswJm4jsEyvmfZLNzLlJtDUSHAkEqXHCBUxLCKm5uC4M+oKtQi9BRytQrQC9LY2mYFSEytFNTZNqgrieE6TCbWqCXFg3NpCYjENowpYUu5haZd4DcOLqPDIIXENxOLlwYQQ5FJuNYCELEWXcLQKlx4BAy5UHAnBhI8hKljLoGCAr6IVyHp/nzEQtobTKtxTZCYuoaTDAg122oibKrMjFYFmfI5c3TfkTOHpjVSsypXBMSpXJuU0hwZcER1B1qL0jPUXWo61MMJwYpXvqXRFVLQsEVtXMbTGkM5gqXQoQRWSNSYOgR55XMsbdTpTeMrMrkrgyKhrgYFxlcVBy8FCRQghUxk4ECMWLUWENQhBcwXGkYIkrMSBAgS5miIAYAX30EzweJRfxMS0p/eVS26QVmLKUU8iNbAsPZFapaXiHm4bfU9/KzJRygQ4HgYSJAjQmNATJBdQukOhB6So1KnUpaqA15F8RhgWtQsgxqMNS+iLqjXglBZA2SzaKhDQtwCwAxqixUSV+kTntYcBJBeMslOJJBBLPAtYMRYsYZUNwgQIMksipY8HhhCCCVetz+or+Vczz30j5cTOTq4xSLiQceSNuzCYFjkTTHNJUMR8fEPwBiI25df7lpDaxyhBwJyssEOwhVysgqO4zFYQWAvUAcaYz1VEwQEsdQwgQaJ4EAUzYqD0nSIoyRmGmGLk88O1jnzn6JIZSPAOQJUBM48ogh1HLBwo8VxWYECCGxKI2RIkSJHMCBBDkmA7cn3wKrMy9Oj0/wCwWJh6sjcViwwEQ2l1yu3qLtYayktpXhKhLSVnZluaH7I7eLuBL/SxMyzEzWw0lLLEdwbuX9krGY4T0xDYUeVqA2L1lBX0c3iNoL4IGjcbULlpxMRNShkniIPiGWCIh+W5cgxcZcoIi5iYgkE4eFxFz+gQg1L4FxUSVwG4ZQKjwqBmBKYQIEDMQIsUdsqJGJKlZhBBqUv/AOGoptMVXP8AiCk0R6Eh1Cg9xhiDCqM9DF8ZS6fcyUqyXHRUTB1EytZgxZjBlwZcuXL4qpqY1w80Wotn7+0qZYD3A+WHQnT9ihSYHoQna57ZQA8ENT80JWR9zGxBL37lO6xEboRVo3BMHzmRJUHBqB2Wal6HqXFHwLLmHA4LlRu4kIBxeZfIThlYcDDDwJwDhUCBKgQS8VKrJA3RBPUpgxKzElSuLoaulz8RG+3HoizF3w19TJMxLmOJYm0oKYswKJVH7OZhApmTwMELCLlwhEUIxmonWfLG79cbhuN7iWgPNZnVTwYii0r5WDFHhAAZimG8MLcwFLH2zbJkwH0XLADPcucY6mqt1pmsVTUPw+IOfPTxFbTcQG4E4uGLFgwZcGCRCUl5l8L5HiYQkghhhOTuBGKlQhBBKKFIlcQEC0UuLi+GEVfC/wARZYsx/j/wzaZCZcrSWhMG5mhomtYMKn7GKFQx2+DLlwYRukfibAPkyvseDMsZ07Y/AHqb7X1dTLBMEwTNqUg4pK3ZGFRcQdxQ5ZkF2xUzVUQrTweyEnk1Lc1CVPvhQU3swXcS51ka1TGLGCBg5l44HiXyMvFvDi2hyM4uIosYTriv0FGUgkOAEvUOYty5c3hj0FOpe2tS64uY/wAv9otTORwumGDugZkZfFIR8CCB0cJYZv4MqY8yg7iV9d0E/eMSAVg0z9zB4DAWOxWsRhkrthSXfufGAHiMcxuG4H3AYAwRlnwywkvwZ35iKywljLs5WvMUuwsi9FKAe50jEUV0rUdZ4UYNS5YjtwYbhBzGCGbjFxYwwxZYAXFXAy4wowoxcvMuXLlwYMIUMpkYL3E4IxWGiHFY4GCIZtahi9HVe+5ki5mRej+/BYSpJgOWUsVMolfMpCGDICLojIsaALLu7+CXaY+JkqD3Bi/rIb2Dyw6a81FQEOD7mbRby1LhLmM1iIjEpffiEacBwNEEtf8AmeHUGWxY941HUWLUw0TaDb4dRkLxMD1KKRJlBBM30/6hpTMsD6l/3SEDY5YdwB1FQZcAOIyRncNcLBjFl8Fi8VmKzEE0iQscXFilxjx3yw4ILZUjKFDEIuDtFOIvIgwXUF4lEJJ8IPzoZWY1Xn+xNwPqLbY+2UFvwJozR2wGqAYjQt4wAA6iLXca2Z2AvNg3CxaB3E8F9Ny+WPRRGFe8czbo+MR3B+WCQYbiIllWS9aDuJqwwE8DExpPzDtUwMoPUw+ZTuLyRdRYwlXsLz3C2kxVmmZqTOCiZIAsWUe/P3M4GRuFccNIym8w1mMq1uGGVVIAUipxK5UvPBi4s3HhTIYrAuoLHyCFGMIahEicBFg/oOICTQqRYTuPkgpl4K3L8UEMVM+oRxaSx6Mpls+iNZ+xhQGXU81fS5fyva1HCgHgl1TcOqQaTcDCQOKnRMQuYMtwphio6/aM7hM8a4zZeJaMSmOTmWdUXSZLqGFQ4f8AmjBqvUt5l79RXqWLlihFzuVOdnusiO8pp+JhcSu6Jn79wP8AkpUErE8Szshk8zNRB7gLcqsInaXFLLW5kQjqKrqIcnhcHEYcMpRSkGkiMWYYwmbBH6S51NQjGXLjLhzYwLo6olrbKkRXuWgu+BYotm7E+Yq2fmBGiGsAFA3qNRpX0ROPcLcbyXowRNrZeWF3c3wjLqKJiI/wz1lwrBM52QAepQiLbiJEvUtBeIKKIo6mLLUlyYniQAHKtPzX9QHFgfVxK+UGE2EaGZUXM0x6mD9alQc6l5wynzFqUE/F6iPejt7p+MSoS5NR7ntT48QxLtirUDtjAK31PDGsxhhZzCJDKaFELoiLMEErPCpUIcJSMQkLsRcytJh3ASw1LdQDqaYsZ3wwYMuG5dSy2iEZZQiI9yoNg79PEdJfmOgbeYSmG1j+yAir6S4r3QNV4hJ1wyl9YlbKFteX+phASCRwj2SYx6iqj04Z5crEsb7galzO4iDqG0KtBDiO1V9nzC0VvZZRQ1izHdoahCCFKNQwYgMKtb5F/uMcZ+YTMGyRKTt/qAgoRyJNpgihiHUHmFv5lu2WozFX5lBXARkjSX3bOwElWN2LT8szSsdh1BJVnK9RkqnYYGIfhwnh8QZBUu7j7vEBUl14laxFE7TysJ7ijCMEY6jE34Ceox1L9nEgYJVwRhBRLguWmoF6izF4SXFDKXDMQIBxyJgoYpQiyWwSO3PCsHxCvMuRBepmMRwjI1G8R71EXUemIYWlBGbGzz7It5ZQIAGREbaTAxKhKQO5flDKJGgeppE+Y4rI2Rt9cQuSC9dDK9c0j2BBkAioDEV7SWdf/RKUvIRlBu3tcLCt0/sf6hugcpofXDiTjS3qUXT8wd3B8TBO3wbnzwEHxCOAeT34iNnB/YwEGCiNALl5hINWU3LZVv5gii5/AYTOcYilKziXo7l41Fy1K7lcsQHcJKeYPSX6I2aj9kDYh1IgYjOozlmCoreDipJgIERFl8MeNojEWoDbOgjLctZcy6pqmbUyA64LpdvPUE/gyysTGnY/6ld4mXUsTEwoAlrhRwe2CdvPsgD2NSpnqUCNDDBExwJZINa4ypTPmUxxBx7l2jbMmpZ1Z3KCigj4JUrwTedIxTAKevDDDESh0fPzGFK9wbj2xhr+4F+TMWEJKX1k/O5Uo722H7w+0np0/Eexk95hfFOEcpD3RN6z1h+8WPRvf3BSa/F7ilIXLFbEb+zb+P5ijsmJhasuZaZuMIIu3bN6jLHPQzwgziPSsIM5IDeJv4Gl7gHKguPhngqYymJC+A2sf0bwYJhCO5cIGIkSEF2XVcImXEUsILrjvrEvrENEdS5vfAsxd4Y0XvcJqEioIVSzSZDEC4jzCsLAg/EzlZbJURMrTLRMe9wKjLbZk4csosbMz6Rcpd2bhDK7jP2EmED6REvY5m8WCDJkKRmKXxfEIW135lETympV2/I7hcH9JdV29Qp4wVhQWQ8ECryPKi1IO8H8Q7U9a1L2lfcCpewfmDWHIdDyw4sOXtdrBLnFwW6guBGIY2S3LKvzBFWLIfUVBSZS2ZgGnhBgOoUeGK8z2R9mGowZRYkygjuXJKKRW81wZiCiIEwUMCECjwCgbYGKMotsJlNUsmcmuUo8zH5xYuZQHTAsdxCsSqrIRnOZVYrpoh2irqYByL4Ag5Wn+YAzWXHUFzLCnUFSwcgZlDrHUQjNkVtIrgkKagOZK3ktrhZDKgZSyARMjEi/K5+pbgV04YABv2YZ/ehFtH9zqn0kYyiKYCeyWoh+4W86DiXUAqZuTO98EtLEPJTzKbzM0PcSODQ3mCsqA2qo2QSTXOWzp7IGBgRFsGBaZvily8vN48KoohcwWRVmDLNK7RZlW8CCbYMEZbpl3cpanm4xExAEYdi8XBbNMumUxDoxEnQhdxlxmwckI+zD8yoiWO2KwdofvNM7vUUjQBHtd/mVm0BcNVHLimXBUCu44ddLHHmlyuAnx8fvcFsoY7hBW25qGJ6oBL6mYmOyK3D2hbuejPs1G7T6bhiIYAbl9RF3U8J/qAYZ9o/qOUMvaWZ/hX+CItlyugea3/Er+Bt/gmCPTHLiKluqGpqXRssiq6iF3EtWwbElkj6oP6YlF7xERmNAfubpVfOJwMFGX0ZRmKQhVSLYQQcEBhGo73G8ZfQgi1EUVLQbBily4LhzL64cxMZK0GtywZis0wTbADOGZK4H2EKwzl1Rtoqz6zANorB8QIOX+EMIEEyuT/XuVA4EEvEYPBrUoJfR/SZ6e46GlJ+Xt/qUAABb4JoGfxD/ALLbBPSIKRmgy7mhafERiFSplNRqWx58S2BxE88YpE7GAKMCKBacaZSsv9StFj8RphEqZ9yyLZFhgZgzTUewTz7lID8swAxS1WZSwcwwdy5K6Px4fqOQtZaNRy8C4lgJhlhZN3J5okOGGVFYy2K5zQZmGAIQiseZIwtsRRcftLlwcxQ5BNUyTVwZiaIOirA3PGTxEYttYMoE6jKsq2ACWJYwczMcd8Ydb39QQgCkgdWWik9RiMxiv+YHWL0fg54Lly2K/NhEEF+kZflmFhb/AHE9yoEuHx9EAC1gDUZNcBX7IAyI2ztZZSJ5hlbMl7WVkLexZjh0cviJtlQlQ3K2VG4e0O0VuK3U8wxuAbI7WjuYUdaKCt0EsbqBrcIHMBJcpk1KyyKQDaxNCo/iHSOWY2ptxtyWT/5xLAM7fmOJsbgkXbLRxNmOOngqECmZ0nZK3gLczZgCeKIswRRi4tcvk4HIE3Icw64NEurmYI4VG8yi9JcPZHcOMypYjlt8dRlTwIyz+xIVqHGB8HhjVCV5UHbMZEq/ueNEtY/JCND01fhmXP8AA/1Aqp+aH9SieSA/hLxYfL/eIlj+T8SguFtYRMIvQEQuHF9vxKHBr2D298agsz0UHxH8JjRWyGo3hlbHXXmAsKvxEMWGHmiHJSJ1X3AoFy5kUixSXnMaBbYkCn2vmGXAyqEdDA3RWsRbhDK9PUCndYVWURm3DsVe+TsZlS0PD2fTHYZOZWgsKh3MjibcfoASQqQl9pQywhF3xlzhiMOD+gVvipUCCEeAmSZpp46utBcc2tIZY11DYksiHFi9zImgfPUSEoZohgNnQf8AcFbkpw/ZAj6Mv5nwMpf5EMwfqKNb8wIH9qjF/ezL8l2qiOAIeJWJTolotDkgNI5HP+1m6XMRYjkPU0rW0vWTVMoAhnWH0N3eILBsqmYy32gqNuXC3UEkSosB6li9wCW6goN2bgLgSG1GcGIllOViY/igz/UURLUruNDFSpaUd6/+bhdpCN8SMKy4Zfc3YmaVvC04dGGYGYlZTIiqOWBEiR4pKhthwVAhL4IJZUyTTjgwlg9q74il4cRK4owncMxnE+pqbSSoE6RVKdkFDj4GUAPX/wABm1s+QleOnxL/ABB8982P4jXR/CfvLwvNNP7l+KOy/wCiEsr3gflhDaDmPvqafDKz8jNwMtd8SjiWNxLxOots2ToDgI+iXBV48ortwq2WPEyXUNtQkiQVYGFYDSNNw5pj2KfxB8FnTcsD3GTMLA6oP6mDSeLVG3kNlqnmY9BmlH4xLWsp8y4uj8RjqIdSlCWJkSCIxMPz4+0wPh8SkLhn27m7E244KpjFlRjplMVUjjHHUaSokwjBKlRghJUJUqJBngzku6mmCFURKPRqXuo71GM1qFyywIKRDiwbhluuXHwxIMwagmIlugTBRCKIPCXN1HyUgNoHxcuxT8sPWT5h78QhlQPAKhWvMUQ0RlZZ4HwnwlTcJi0cYisu8zODU64WtwvIloVipvCLmVlIFRyqZUSdQMv1XTuao5t3HnL7e2Zq7h7iFR7j8x+ZsmmZVfXmA4Ou37nUdIoTpI5Aba8KBwFYu7iNFFwcC9QEs7m6VwxRcxkSoXAMFd8B1JTkIyi8DCy+GEeCECMZpmJekuSacRqWzMwMvgXqB0jA2EsoQjkdMJa4b/ev3iQj1LRNPmJUG7lhblrikGoZENteSMe5iHctY6zAjsMSbahLBqYkK9zAGTZDDdRVadLMlSnsm0+AeZ1odww5u2HOJ6GONJANxVwDAW1Ky7NUsDUC6jWjGvc1F5CKbwdEZvMyPEyJpUGI7jcf0UMiwn8viAtx0nuInEzsyyPZ3/aXhZ7imOE3CvNib+Ku4tx1qDmxJuW6YtdwZ3O1HFuEVPMt8wZfBNOCqgzaGSZJkJlIOIVEBo9z1MyphN8YQvmLMsoncOGQDTpAN9nz3Kg0xJlRiWBGpg4iQzjjYxjmUq3iGl+Yuk6+mNxQCUhp8xLmWFVsxGIKjAYmTMdAMxFChXqKuWDLtg3WuNBueWK5ZBW3UJxjTfb5lFilqDx3EO8RWvbN5vvE+E2VEiX54f0Ms2Ae/wDiMKcMeZuA6YPww/cBKQMmOGYAu6b4zHKIJ1I63EXkUYlC4FkxhcXDi5ceBqXwUFzITMTRMRBiVAdmZmZcmHczsyoZdENgw4pjplhNf9pUIZASqJVtwbWmRGDPHaDXBZSowzmEsBOomlEihaykZXEDU78zFSNcMbrKHyEV2rKJ7IlYo1iIvUwzDCZCYIAho6P7irPsl7bq2DYXBWvuWvWp7xM+o7juMfPPXDXgA9w4Yw3J2lF4mcaXLpdMJcZDEQYFQxbhl8E3AFqNmJWKLLlwZUJ+1gsjKlQ4vEYsuLEvMUfEwZJ0mhNJpmcpjYlMTzLJZb+Y5lq+Yb4Yx0ytHavg4h2lkSwTGNBbCS1PgihDZwPAK5rmOaJ4Zkcwr2QnUOAIQJBzDbUXwispeG8BEgWjNQlRxCAJjRJlMSkhkOGT3Y/1DQdWQ8RfYMZmzWJu2SykBl8zevxNpv5jw456l8JutfmCMZAllj3KFliZOs76H+pgL8SjFgK2G5VcZubZkhjwS48Yb+srUrgkICMY/oE68VqPUeSYiPEB12VMFaZUsFPC+ecTqXVdTuENksnezg+whcbZYYDEOHaNpsVqoPbMGsOo5k3EOo46hlLGwHuE2n0CA/6VRORb7bj/AMyK7b6n7wSkSMc+LfzMU50P3IN6paxFhSPZPRPTO9lrggCrYLGEx6OjEDDAAHyzRwPgib7VTPDSmFsybjyYSd1mnlDWeiXfnRcwmWZ5E1iPDz3DAuziALO9/wCWTKzZs/gdkVwLZR26vErQXGkhizIzbN+JmeCqVmBiVmHD5h/bM/gk24BH9A4ODiyTRNExksOFNehNsrUOZ38S7SyPUuSEJvG8TNnBp8kUZtDMRbue2bTcklwCMr4EJdQNr1F9H31jZa8/sQaKJcWLmX+j1kNmSWCti8//AH+ZSALCeZd1D1mYFzWQ9QpaMscPaGwEZIMsF6mGJUe2Pk0kqKoW/K1HsF3yfU2kXo/6jVbO1sgzVZgpaxCjEqPcSOYx5rHTL6t1EouXZGoeD/79p3m7LjIbT14fcuywyxivpgXXPU3Tbib5m4d4cFRmXKrzNonG2BDghuOPJNUzk0zBFNQzGNxKFlTGZXjmJMz5gwWwQc7ihbQwEWxyTElRy0ISPuJZaC1Y2Ku714Pf8QAUv39vNy/8GvD76+X+5jNMWd/cLdRp3uPLEdRrBpJbIMdykGHWYcYqGrg3NpjZ2f39SmIlpdO4GJXV2PhlNot16fJBtnaXn/svBc8jD/qLJETqptc28x3HcYxmaKC16CZKXgXzADp/waIrYM+YSW87PjqWLHaiUlAidMoYr+Z5+46LJcJi4hDPc2Ym7E9PA8ZOHwRSgIn6AIwJVQ4Ibii1NEyk0zBHiCh2SjwGVrKmJLZ04nUuo6iUS2ooahbwu1H4dSzxLcWjiVgjYfc/PR/yF3BQH+Q4kBYb9kd+8zIam+CHiTGY6BI4biBSWPUoslxfhTwNFtH/AHKbimTsncEKgWFf/NMxz80Zyx5Mx6lCbPERvsYibiNN4+YRmWoDMtXX0JUWgdPfiOiD8YBEg5ZeEdny+JtzLFljLhM3NB68/Uv5my15ipGmElu5txNuOHNwpUKjowmO6LMuEUHlqXBhmdQ3HXFojVJ1jol0NS8VjKbcSlQ5mm/Ev3qXBK0JEIaO4izdolfSWgs8FQKTRr7npmSEp4xA1UQmhA0xU+AYPx/MtltF/l/yHG9PiyWN9prDuHPBIxahdRMHxUE2w3w6SOySsj8GDFM6bICBiz1fJ1H7LpZjymr0mIJRiaJl73lFh/lin++MZZ8DG+OPVe2YcW21r/zxNozt7YyjH5aiqXwjR6gTAEvvMuOZdiWD5g0xKxs7vUAsMM9WkDLphm2b5UwVFXGlJdSO7zJCGpHOOMUORFjgizLLEalNSoJomqLEq66ltyhYKYze9Qs1HMrcel6EVEoW6ZU0KXGiZisFUweMrUW+4t+odzUQLYf9f3GqbV66tCAL2ftcf5CKORtW/FwGr4QR+yd4csEMcVGHJdeY0Q2S9gz3xmFqQsYpZ+arXw9S1UPIlj8MOYXu/wCDL8B5D86hIVPID9p2E9MyT9gYsv8AbzzT9BNo33PpSGYdQ/b/AGjRuAHv4IKEB9vtmVmKrmWMPL3Qtl6eaf8ADcUEV8H+2BApO1gsWzqFfWtMrW8O4dDIzfN/GY3cGYC5sQo4MwQYwoMZcIoMJcxVFgkhzXLpoTWXN4mtUrWVMZ6A4ltNTGahFtphUFhoLqLoIaNAlytkq4kCay4f/UI/1O4LfSBiqaLcewLD4f5lcVKlcV+pZ6O1iMZb/wAfc7GUfH/iJX2Q/md53m3FDLFx1DOy4nme6YNxB4UFxRWPWyAt+NamqO7s/iVdR0j/ACRDD9qYTkPgzdFfUWrQPhBDyjnOf+ZkKb3vAexcVt50U/LHAF2Nv9Qygm8J+Coo0J0j+JlB7MG4A9Spb/mEG0wbJDWHTDvuQsm/E2zbN3FriCoYyMSmMuovE3HUuHAiKS/KSpRxGdyszFqaHPSNzZKVBma6g0XUBpUzwstuoEH3qKjZcXGDgkEDeHEGLBnWARyX+EqVU2RuxMfxTHfZ2XS4I+klGAYTfiZUqVK/wArRUu6z+IzUoK+2X8FQSS/TFY/uOhBBFHyGnHEoRSz9pwlVYXLVuXctSruB5gPM2AvyTYP6xZYD8YWlvyBxma+7D8zKsvK38EqkHZf/AE/ebQTvf5bgKIvctwj8XEnDerme0fcZoRu0StxU3ALZG4O5dwROTMvRaTfib5TcrhqdxRC4NkZOSwysxeDgFZqUlDRMssT2jqZiYiYyOEsM2jKFMksgkKaJFLVOpkYKdOIOpa3EbHcAt5IJrszMpdHEYUi3h6/eV2wB8eBfnUE3dYF46Hx/EToCVb9B9e4UavIrfl2SpUqVKlcVN2PEojl3CTD/AKEqLrA/kPr+vmOq4Qbe3+4TzD7y0f8AvE2cDzFwJUCzW0+YGsh81GqT+skuD8NgPBM2/chBZNPklI3FKrgzuC8y0eu5Mv7SlW126/bc+QQFH5YNbU7LfvMwA0aRlh+zmWVEehojtpPNn5lByMGQUUxtMidTFG8rXqHKLhbzN83zfK14BmVJwEbJa4u464LwTeXosRQTLlghFLczypJTWZbWZYEVyhR0cTO4jXqUy4AVLSLNIJSsC8mAWWFoEcwMSp3HvP8AxmHEfATLFVbdQTomdx0eBicaGadfH+pksFj/AKeoTR2Kefof3cKLV1g/JAb+MNwR0jxYBzsCCK8dK37SwvPN/R/uGDRhaPg0S1jO+j5fUKuClDK6CZ4B7Nnn3LSrdjz4+pum6WspfUCv5Zj6dK6JhPR8v5lx8ZggaFkWxVKOSXAhhWz0+IgdRSMGaLoMspFZ6f7yiDd2n5a/iEa13Z+2pQ+poIIiwz2ty/sj1hElRfuI7L8sANAf5ciYse4AI0mGAQuk+fc34m/EyuOWdCEVTDBdRy4Kix5i8ZRCxCR9k8bFe4pkmuU1mNiWhFibQ9zBVLloiXAy1Rysajd2ooXMUg1ChqRtGGVLEyVKl1TFG0OfiHk1zRQPJaTsl5Gr6j4fcE0mLLH+yGCbjN+SM263gs/2S8VT2zAVp1CYF6aguQfObz/LLMHqrYWpXyW/iFVqvY0v+iVBbpMvvo+44+IvxO33N+5e17Pv+OIBK0ELba8EtAz2xtsDwqI3F1fcGBLzpZ5hAUXNoRVoLZdjql/pCxbHcwYBUEq12gq6r4vzUd3PgF/e5m+FpbLYSeMY+SPluZbVlhqLF/zofVKk1ssrbaHSUtKsupumZ490pZ0QWXUoSqKbSswhAxCvlYy5i3Bij1MxLtTCpiIrITrNwV1C8TwoRG2i0l8+DHcsldxbTGQ1W23UINLOpof3C+pdQrxe+EvyhWM7lE2/F5P3lUZqel8JhgENeJ9834uWSTut/TmG3VH0/wAy1/8AP6irv8H/AHExGHgf3LVcHlj/AFGOI6bfggNjfN+DqX8RavXtXBET3AD8Xl9z2T2Q2NJUbdbHHxNyQpEeocPKxbC/EMD31r/CAgdQKWWrbqSn4Y0mItHTMjarPjxDYeItZuFItuvM2ijCsWXwx/yVyncsWf0MCw3BdX1MOE7G5sxN+OOlmSCGXdylZFKmXEErPFFUMlJSUS5YsIGKKOxMQmYmoiVbCfJEMPKWJGzKVEDVcs1owHuJnWoI5mTdKqAcAyTu4qMbh3bPgXfJMZcKcWPhKVK6K/Lv7jDOMmFPv/5K14Kv5jH7wH5G37JiB/RDX7jDE+9EXfwv4kpS90KRkvPbT8bip23/ACO39oM66NcXslnHS4iqjIRAS78RUrtepfkYUfKLapO4MTQTjqGLlTCu2eERT3KBSq91gljlFnG8S5cuPF/575qmIAfDPJTLIVTI5JbeJuxKlxK3UasEsl+SKOY8CqYlGWYg4nbHgijiFIjEWowK11EXgl0cwi50w0UdCREyPlM4K7l6DDEsHKumIipkCfhAANepdl2ai8vF1FKIsYgmhFkSVBhT9AhG0H0sTbV+syJfVn8MdEKawZSAjFET2z2z3T3RdIjrCZtqeW412KgLZBOLhpqk0y5U6hArFAdQPWYmPZWdmDABMZzKUC78y8YpkxGrCNfouXL/APxWEdakugmwwVKKV0l2VgrEsJjcTfiVriVS6eKzaELCZRl1LqalCglBLGMTkjzKDMQzEipupVLAhqZ3zO0VGqAYAjcd5ZBakqottX8RiM89S31FSSh4XT1CLv0DqZqlfmX7Za+uowwkqXLYScPziTuCgbVx2B+ZtgIBZ/mWNFS1CizpX7ie1fcIayrgjY7PEoXP8wUddR1U33evrLeA8BX8QfJDso/mBpW7Jk/M0FFsW0hpKQs0fEBkILUWXL/wX+q+LlhuIdx8RnUxDYIJMQLvuKk7PD8wiA7Tz8cIpqXXibcRRcSl1KeGQpllS11DDEACy1EHFSoN1DwQTqVuIMEKqYlFjeZdHg4Vo6ioZUrKdROtuFzj6CWBwG4CEP7ke/UCtqyZwpq3mWI47fPUSJEjRuIdkD3A9wSJ1OmMVzSgim/cPwt6l0BDjYHzUftvqNd5+eFy4qRj0dtwbeuVBjw1Ga/E3AppWiY4IMYTwt8AncSLiUowOxFVe2LxfFy5f+JDaQWsxbRUvzQThCdQ4Tplg6jlI0kok+XmWEuHEtHEyuJT1wC0RQbILEijWgx23DEzBuiKtpAeoK6hTqUupqiSgZfWcJkmIiue2CWhKglSmxm9RHsASwia5LlOZBYS2C4FiC4wzAmI2chl0dLfmH1OhFT2oxoIvJYTf2Ev7W9RlhE6iPmopaQA2rAGiMX+knVhigE0NRV5lWRLhjgViuqI2uUwxrjpL/x3EG0iHuL6I+dBNw8mCdQk9IQRawUa42Bl0DHgmE/LLCWDib8TM4jF4i3ESHiQqwx1iVxg9JdshnUpdTAtX3De0x0sprUoMSpQTsY5aqg3qaZihkmsYcxVEMxBTPxKOnyg8+Iu+4JU0dyqAcyggQZdZ+I1loPUIsv2zTp+jEN/lWy3yXgxOsfuWAMPWIxafmA7LNAHF/4SLhlWgtmyWUfq7uXLl/ouXFqJdx8SL9z2ILtgmyEkkEjnoivUR6jeIz1M+pSmJQGIaoixAGtIQYhN4gN4mzEtXE9cRdy+zHc7eCoqyXiojFqY2SztVcWtXzd1MApl2XHMXKQhRxWIyCL5g/kQa7tZezTLiLEpCemAriK6IzQlrUXMILpQCMx5mLcI3ArDKTUsC47ixYFGH+IRcz5Uw6B6jmf7ZltYDRK/RUr/ABOmaubly4gMpEtWx1FQo2pYrB4uXEtsS1mI1ifNFdsB3AHUJJIJGxWLHeo71F8T1T0QQ1BOoJ1K+ooAyyllUD23EBRqPcrmAhMwkuPPDthgltXCoB0QVllfMr5g+YG9wsZmYRzFQrnzCpe5ak0zBHqVL1K1KjQW0SstR6xK6rFpfEQ0fUHyoLIVUwa3LDcK41g+ZnsYBFfrP8nTNXChtg+7in9kXdT4le8/MwRhgKW1Bdxeke0w3IeTBOoSQQSPxE8RGN4jPUR6nonqnogFYhnU8ZGepoU/UwcBN8WJ2JlYHB7Ju46YXnh5il5wdhDMoabi3MI6ibgxQDVxMTTmH5l9TBHgmypXPcyMpaNT4QGHSVViYC9S0ZdnzBjuKG4qPteKlSv898XOylqq6Ow1PZWAHUuMMLPqWdS3HU8rAOoEhBBBxBxfEd6iPUR6nomjEHxCOofRMAL8Tun3KAUE7RZT02d1KxBBO4HmD5heYPmbsz2z3zfmLe+N+PfHf6COpvCLUsTGRlxGUl1R0TRBmcJuY2FLgMazuLfmjE3jZNSl1XUvMqBi+QhaDi4n/wCC5q8pQl8GPlLXzBPUH2wfEOIgggkcWeiJ4jvUXxPRPRPTBKxD6I0C/iZIfadp/E1xfmFFAPiJIiBPbA8z2z3yrue6e6e6eye+e+X3xk2inbHcqVKhFGE24qZCa5qmM4nPciYmbIj0L3LuTEFRrMaFLDqGD1DTPEPpyiHqWVLTUr6lMf8AHf6XxX4zAXUE7YPiFYcVQggkU9EZ6jeIj1PRPVNGIB1CKxFds8DPcN/TPIPmAFAfEZRKYPmB5h+Z7p757Z7575757p7J7Z7o73wXx3CbRxvm0P0PPAQ3FiZpqmYjwTXMBFZBYPZKV7i5hSGxiZjkgS5TEoJLn3K9suHMBqBUAJVc7R/Vcv8ASltiei4pqW8zyQBCCCAhBBKxXqO9R3qemaMT0QTqGdRHUUNON1E3haCUZERMYog+Z7Z757p7p7p7Z757Z7pb3PZF8xhUbxY+LCVmLqZoMysQlZlYhzA4Nwm8epkJiHBomAilfoTbK1MJTGvfcW58rYroawjzK6gBBSXxZl8X+pBtiHuL0VHtMEnkYBohBAQIQSX6ieIniM9RHqeiaMT0QDqeCNm/iKrGN+jWEoETEkDzB8xHmYNzLue6e6e6e6e6e+e2e6e2Nu4+8faMsZEIXgJXCo6MstEzwECJibcXO4RZhtJmFmIcGclgRz3QmBmZhpeD5Mg2XBiukPPmDKJSbl5uXxeblxaiW2PiR71fHAE7YMCQgOBA4J4Heo71G8T0z0T0QDqF0SqtgBSnuZKz0TTn3BBgCMso8z2z3T3T3z2x9ph3Mu5757Z7p74swbjruMPKeFhOSYgiTuGo6EzEqgQcjmBEgQhViKQCRalZLBMBFiWXkSukfOJUsOYy6RU/pOpcw51iy4ltg9FxTWJ8zBu4BvMAaIQEDgQNg4r1Heo71PRPTPRB8QfExizxMgFIfU8q+YGsIywPmCQTuF5nvnvntnvnvmXct7nsmfcR7i+eFhnHMseBli4RYMzSXLs5JDUVCZRkRg4YbgTKC8RHqZCyCTiBUMpnJrivhc4w5h0yhYKYkwQ+Ic3LiTbEPcToqPaWCbgO2AdQpAgQggcExPEbxGep6p6Z6IPiAdRHa/Ur6QTwhK6y0CxvqJjDL7Svue+e6b8z3z3z3z3z3z3T3zLue+NpdxMkdMeRsL+gEYEJfLrHiWDMWEnawcHjKKxnqacQTqHFCU7R6jLHcSpHQWzVFKHxmVMrKl4VHuXD6ihuC7j4kV7lnmCdsFAnUICBCCSEi+I71FaxF8T0T0wPE01+ybw/EVSEdsU1M+pQjCZRA8z2z3TPuUdz2z3z2z3z3T3T3xfM9kU9yzht4t4GpdGGFcYo/oBwmSPEY24XB4XFjwWQkOBcamIIzPHSmC7gHcCsMu4tjiWlTNc0TXFYT40mBJtlawSi8IpxE3XBO4AgDRCKgcCB+IKJGxiM9RHqeieiUViD4lTc/Uqkh9zLovUM/OSUNYjIT2QfMLzC8z2z3z3z2zDuVLme2e6e6e+eye2J5j7TOWjhFXE8GUXhiii83LuCax4IuJcuDNcvgdcXwhssJUMV5lvMV7ijcW7+EAoUHglsaZomua4sEMkpUwuJUsyRIm9T4foBBIokV6jvUd6npmnE9ME6jlK/BKK6PcLT9RNMF9wooB8RlgPMHzB8z3T3z3z3z2z2zPueyZu5u3M7M90XzFieY8y5cGKDMSNmLBzB4uLxWXLi8CCGIsvMzwctMsgVAxjJgC2V4I67ly5cX5nlQTMxwZSa5rmIilwTaMpWUsSJK4F4NisbxGeojWJ6ZpxA8S5wn6lHYHljbI9Eo7T9wyvjCMog+YPmB5lfc90989090989s9kfzPfMm5l3L2YSq8xcYWXxcuXwIMzRwDF5LiLmXwECJCZcAcJKgYiQ4BBjLoqcccWiYaIpUYsYYGKaJmmua5omIjxKx4zLBmZmRi7hAvER6jvUv6npnpgeJpoiud9RtIMrM3NEvqIIw1nsheYPme6e6eye6e+eye2e+eye2PtG/cfzL3vi7EVQs53w8XLiwgguCuO7hKhOoxOKuKvnIP0mMBEhA8NMN/WUObSxmRZe1FIsYkSIw4DJHU1TRNMwEeJVoe5SEtvEa9RfiO9T0T0zRiH4ioM/UoUD7mdZeCUGcduYIKAD1ExEHzB8wzuF5nvnvnvm3M989sb9y83GzFO4vmK8xfmCl4+ALSWiLDFlixZcvmuAmqV6i2wSoECBiOUZZJ2j+iJSCXnhmplKg8Dsyz6RLWowxGGVSxZbfFSpRHgMMWTitTRMpMZMUU2emZ2Je6m2oZWJjEfqUdUPLDKQPRPJHuBV8QRMYDzB8wPMrNz3z3T2z2z3z3T3S/ueyL5ir3Le5YYiR4BWEECGbTaGUlRWx5qVKlnDhuURb4EqBCECV+gYIwQAixYy8QY8epfFBlZADidEgWMvaI55uMkiMyOBzFM01TVNcwzFMI6hRczv1MoZ+ZlQv3AK+giY0gkEheZ7Z75757p7J7pb3L+57J7J7eP2R94wywylxjMEIRrzzyQVaWsf6jcOpYwwseDgReASw4DxWZUeBjDLI3Lg3wvjaDCa5owHSaP6Rm0OBr9BsTrOs0JrNJtDme+HidxjHm2N8xvmN8xvmN8sb5ifMb5lt7ivOuLyw520Oeptw0cO2bcv6GpytocCEd82HA1Dc24P6A7msd8hP//Z)
Conhecido como não-localidade, estímulos elétricos passados ??entre eletrodos vizinhos também podem afetar eletrodos não vizinhos. Crédito: Mario Rojas / UC San Diego
Muitas vezes acreditamos que os computadores são mais eficientes que os humanos. Afinal, os computadores podem completar uma equação matemática complexa em um momento e também podem lembrar o nome daquele ator que continuamos esquecendo. No entanto, o cérebro humano pode processar camadas complicadas de informações com rapidez, precisão e quase sem entrada de energia: reconhecer um rosto depois de vê-lo apenas uma vez ou saber instantaneamente a diferença entre uma montanha e o oceano.
Essas tarefas humanas simples exigem processamento enorme e entrada de energia de computadores e, mesmo assim, com graus variados de precisão.
Criando computadores semelhantes ao cérebro com requisitos mínimos de energia revolucionaria quase todos os aspectos da vida moderna. Materiais Quânticos para Computação Neuromórfica com Eficiência Energética (Q-MEEN-C) - um consórcio nacional liderado pela Universidade da Califórnia em San Diego - está na vanguarda desta pesquisa.
Alex Frañó, professor assistente de física da UC San Diego, é codiretor do Q-MEEN-C e pensa no trabalho do centro em fases. Na primeira fase, ele trabalhou em estreita colaboração com o presidente emérito da Universidade da Califórnia e o professor de física Robert Dynes, bem como o professor de engenharia da Rutgers, Shriram Ramanathan. Juntas, suas equipes conseguiram encontrar maneiras de criar ou imitar as propriedades de um único elemento cerebral (como um neurônio ou sinapse) em um material quântico.
Agora, na fase dois, uma nova pesquisa do Q-MEEN-C, publicada em Nano Letters , mostra que estímulos elétricos passados ??entre eletrodos vizinhos também podem afetar eletrodos não vizinhos. Conhecida como não-localidade, essa descoberta é um marco crucial na jornada em direção a novos tipos de dispositivos que imitam funções cerebrais conhecidas como computação neuromórfica.
“No cérebro, entende-se que essas interações não locais são nominais – elas acontecem com frequência e com esforço mínimo”, afirmou Frañó, um dos coautores do artigo. “É uma parte crucial de como o cérebro funciona, mas comportamentos semelhantes replicados em materiais sintéticos são escassos”.
Como muitos projetos de pesquisa que estão dando frutos, a ideia de testar se a não localidade em materiais quânticos era possível surgiu durante a pandemia. Os espaços físicos do laboratório foram fechados, então a equipe executou cálculos em matrizes que continham vários dispositivos para imitar os múltiplos neurônios e sinapses no cérebro. Ao executar esses testes, eles descobriram que a não-localidade era teoricamente possível.
Quando os laboratórios reabriram, eles refinaram ainda mais essa ideia e recrutaram o professor associado da Escola de Engenharia Jacobs da UC San Diego, Duygu Kuzum, cujo trabalho em engenharia elétrica e de computação os ajudou a transformar uma simulação em um dispositivo real.
Isso envolveu a obtenção de uma fina película de niquelato - uma cerâmica de "material quântico" que exibe propriedades eletrônicas ricas - inserindo íons de hidrogênio e, em seguida, colocando um condutor de metal no topo. Um fio é preso ao metal para que um sinal elétrico possa ser enviado ao niquelato. O sinal faz com que os átomos de hidrogênio semelhantes a gel se movam para uma determinada configuração e, quando o sinal é removido, a nova configuração permanece.
"É basicamente assim que uma memória se parece", afirmou Frañó. "O dispositivo lembra que você perturbou o material. Agora você pode ajustar para onde esses íons vão para criar caminhos que são mais condutivos e mais fáceis para a eletricidade fluir."
Tradicionalmente, a criação de redes que transportam eletricidade suficiente para alimentar algo como um laptop requer circuitos complicados com pontos de conexão contínuos, o que é ineficiente e caro. O conceito de design do Q-MEEN-C é muito mais simples porque o comportamento não local no experimento significa que todos os fios em um circuito não precisam ser conectados uns aos outros. Pense em uma teia de aranha, onde o movimento em uma parte pode ser sentido em toda a teia.
Isso é análogo a como o cérebro aprende: não de maneira linear, mas em camadas complexas. Cada pedaço de aprendizado cria conexões em múltiplas áreas do cérebro, permitindo-nos diferenciar não apenas árvores de cachorros, mas um carvalho de uma palmeira ou um golden retriever de um poodle.
Até o momento, esses padrões de reconhecimento que o cérebro executa tão bem só podem ser simuladas por meio de software de computador. Programas de IA como ChatGPT e Bard usam algoritmos complexos para imitar atividades baseadas no cérebro, como pensar e escrever. E eles fazem isso muito bem. Mas sem hardware correspondentemente avançado para suportá-lo, em algum momento o software atingirá seu limite.
Frañó está ansioso por uma revolução de hardware paralela à que está acontecendo atualmente com o software e mostrando que é possível reproduzir comportamento não local em um material sintético, deixando os cientistas um passo mais perto. A próxima etapa envolverá a criação de matrizes mais complexas com mais eletrodos em configurações mais elaboradas.
"Este é um passo muito importante em nossas tentativas de entender e simular as funções cerebrais", disse Dynes, que também é co-autor. "Mostrar um sistema que possui interações não locais nos leva mais longe na direção de como nossos cérebros pensam. Nossos cérebros são, é claro, muito mais complicados do que isso, mas um sistema físico capaz de aprender deve ser altamente interativo e isso é um primeiro passo necessário. Agora podemos pensar em uma coerência de maior alcance no espaço e no tempo."
"É amplamente aceito que, para que essa tecnologia realmente exploda, precisamos encontrar maneiras de melhorar o hardware - uma máquina física que possa executar a tarefa em conjunto com o software", afirmou Frañó. "A próxima fase será aquela em que criamos máquinas eficientes cujas propriedades físicas são as que estão fazendo o aprendizado. Isso nos dará um novo paradigma no mundo da inteligência artificial."
Mais informações: Ravindra Singh Bisht et al, Spatial Interactions in Hydrogenated Perovskite Nickelate Synaptic Networks, Nano Letters (2023). DOI: 10.1021/acs.nanolett.3c02076
Informações do periódico: Nano Letters