Made this in like 10 minutes lool ----- Also, if you didn't notice,,, the flower colors are the block colors!!!data:image/png;base64,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Made this in like 10 minutes lool ----- Also, if you didn't notice,,, the flower colors are the block colors!!!

Accepts any number of scripts as inputs. Launches a separate thread for each of them, so they are done in parallel, then waits for them all to complete. This doesn't change how the Snap! scheduler works; the threads are not truly asynchronous. And there is no increase in speed. Rather, the point of this block is to allow starting synchronized but independent scripts.

pt:executa _ em paralelo e espera ca:executa en paral·lel _ i espera each scripttest

Accepts any number of scripts as inputs. Launches a separate thread for each of them, so they are done in parallel, then continues with the current script while they all run. This doesn't change how the Snap! scheduler works; the threads are not truly asynchronous. And there is no increase in speed. Rather, the point of this block is to allow starting synchronized but independent scripts.

pt:executa _ em paralelo ca:executa en paral·lel _

de:animiere Setter _ Getter _ Delta _ über _ Sek. beschleunigt _ ca:modifica setter _ i getter _ amb delta _ en _ segons de forma _ pt:anima com modificador _ e inspector _ de _ em _ s de forma _ 501

de:Grad _ ca:graus de _ radians pt:_ radianos em graus 0.5

de:Fehler _ pt:assinala o erro _

de:gleite _ in _ Sek. beschleunigt: _ ca:llisca _ en _ segons de forma _ fr:glisser _ en _ sec. accélérer _ pt:desliza _ em _ s de forma _ 501linearlinear quadratic={ quadratic-in quadratic-out quadratic-in-out } cubic={ cubic-in cubic-out cubic-in-out } quart={ quart-in quart-out quart-in-out } sinusoidal={ sine-in sine-out sine-in-out } elasticend time1000deltaXdeltaY

de:animiere _ um _ in _ Sek. beschleunigt: _ ca:modifica _ amb _ en _ segons de forma _ pt:anima _ de _ em _ s de forma _ x positionx position y position direction size ghost effect color effect saturation effect brightness effect fisheye effect whirl effect pixelate effect mosaic effect negative effect tempo volume balance501linearlinear quadratic={ quadratic-in quadratic-out quadratic-in-out } cubic={ cubic-in cubic-out cubic-in-out } quart={ quart-in quart-out quart-in-out } sinusoidal={ sine-in sine-out sine-in-out } elasticy positiondirectionsizetempovolumebalance1

de:Beschleunigung _ ca:de forma _ pt:a forma _ linearlinear quadratic={ quadratic-in quadratic-out quadratic-in-out } cubic={ cubic-in cubic-out cubic-in-out } quart={ quart-in quart-out quart-in-out } sinusoidal={ sine-in sine-out sine-in-out } elasticquadratic-inquadratic-outquadratic-in-outcubic-incubic-outcubic-in-outquart-inquart-outquart-in-outsine-insine-outsine-in-outelastic

unknown easing function ""

de:für _ = _ bis _ _ in _ Sek. beschleunigt: _ _ ca:per _ = _ fins _ _ en _ segons de forma _ _ pt:para _ de _ a _ _ em _ s de forma _ _ 01001linearlinear quadratic={ quadratic-in quadratic-out quadratic-in-out } cubic={ cubic-in cubic-out cubic-in-out } quart={ quart-in quart-out quart-in-out } sinusoidal={ sine-in sine-out sine-in-out } elastic

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cEQwLJEqABJ0uK6zIisL5i6Pi48P1UAjM1IcqsetNNRqIYTAIWExCGnH3AmSvnWZyW6VxKgAbs0sGq0lZtWL9WAhcC6K+KJuoggWwSSGgYO/j06k+zWYO53UGABuyOOSrXRU1l4HIBeTFk6wvU+SEB7xAQvnjp7OX86cM7E0+7Uxpw2ugY2BaBunD5RQbELwEMJSES8CoBWTBg28DvvtXTq/2z7+QI0ICT48RVnRCIVATOFUJeIYEAYZEACQBG77GNg45/Kjs3GBKwKwjQgF0xRvuaWPeYfkoigZsADLdPBSuTgJoEEv2Piw2ecXcXNdVRld0EaMB2T8DB9Wsr9FukwK8A+BzcBqWTQFYJxPSfy0Tg0tN1v3g8q4WY3HEEaMCOG5kagmvC+jMCOEkNNVRBAuoSkPl90DT9Q1PgX4J+cb66Sqks1wRowLkm7vB68rXphbXrVn8EiJEOb4XySSBnBOIDZ6Nl1E0QAs8GigVPZ8sZebUL0YDVno9S6mrDQ48HfM9IfuWs1FwoxgEEfF3ROP0TQMszTfjXgWJxiwNUU2KWCdCAswzYLekjlYE/Q8qL3dIP+yCBXBNI9DsGzePu2VFWw3eDReKpXGtgPbUI0IDVmoeSaiJhvRpAuZLiKIoEnEJA5CE65QUY3Xb8qyR9OCTUR3zkFPnUaT0BGrD1TF2VsbZSXy0lhriqKYc3k0gUIp4ogGHk7biY0uLI8zXD54s6vDP3yzeKJiI6oWJHoxLR/DyUDu0jNrq/c3bYFgEaMPdFuwRqwvp/BDCViHJPYOOmYdi0WceWrUOxbftANDYOQFOTH80tfXYb776qTCMu6LIJXbs2oFu3OvToXoNePVejT+9qFPVZlvsmWLENAgLRgx+C4T9815+tCfoFT43z6F6hAXt08J21XVOh3ycEftLZOv65NQTWfz0e674+GF/Xj0PDhlEwDGuPEta0GPzFn6NvySL07/sR+vX92BrhzJIyAaPHCEQnP7dn3JKgXxyYciIGOJ4ADdjxI7S+AfNdvZDYebeI9fmZcQeBmsjhWBuZhkjtFLTEcntscJf8rSg94C0MKl2AgaX/4UhyTCB6yCMwivf6cmlh0C92XxbnWA7L2USABmwTeFXL1oUDYwzIT3i6VXYmtHlLOVauPh6r1xyDaHNRdoqkmLWwYCOGDnkJ5UOfR+9eK1OM5vJ0CCT6HYfmcXftG3pZ0C/+kE4+xjiTAA3YmXPLmuqasL5RAH2yVsCjidetn4Dl1d9tvepV+WNeDYf0J9G/3wcqy3S8NtmlGE1Hvr9XHxKoD/lFX8c3xwaSJkADThqV+xdGwvqXfKmCtXNet/4QfLnsDNStP9TaxFnONqDf+xgxrAL9+7UeochPFghEJ/0LRq8xe2cWeDRYLP4rC+WYUkECNGAFh2KHpJpweVhAzLajthtrbtlahiVf/AhfrZ3h6PYGD3oNY0Y+hF49Vzm6DxXFJ/qfgOaxd+xrwC3xBMaO6CuWqqiZmqwlQAO2lqcjs9U9PkQ34nlfAOBr0yyY4JIvfozPvviRBZnUSTF65EMYM/JBdQS5QElbX0ObbUng3ZBfHOaCFtlCJwRowNwiiIT1NwBMI4rMCHxdPxYfL/45Nm5y56uRi/osxfixd6JvyeLMQDF6N4GmaW9BFvTfj4gEfhLyiweIyt0EaMDunm+n3dXO00+UBp4BwL3QKa32F3y+9Af49LNzM8jgnNADR/8No4b/3TmCFVYaHzQHLSN/15bCtUG/GKywdEqzgAD/o2sBRCeniITLP+erBdOfYCzWHe99dAXW1hyZfhIHRg4a+AYmHnwr8vO3O1C9OpJlQT80TXu7TUFS4q5Qifi5OmqpxGoCNGCriTooXySs/zeAPzlIslJSN24K4Z0PrsGWLWVK6cqVmF69VuGwCTeiqM/yXJV0ZZ3Go1e019e2oF/k9oQWVxJWtykasLqzybqy2ko9IiUOyHohFxaorTsMb713PeLxri7sLvmW8vKaMGXi9ThgwDvJB3HlXgSiE8Iwitp+TI2/Bbt7s9CA3T3fdrurCQduF5AXebT9jNpe89VMvP3+tRnlcFvw5EN/gyGD57utrZz0Ext2FWJD2zl2XeL1YIlw9rNsOaHozCI0YGfOLWPVkbC+FUCPjBN5LMGqNcfi3Q+u8ljXybU7acJNKBvyYnKLuWo3gXjpqWgZfSu/hvbgnqABe3DotZX6dVLieg+2nlHLa9bOxNvv8cq3I4iTJ/4GQwbxSjiVjWZ+/Wx+Dd3uR8N3g0XiqVRycq0zCNCAnTEnS1VGwvqnAPY5A8/SEq5LVrtuEhYsvM11fWWjoWlTL8cB/d/NRmpX5pRdB6HpcPNR/HY+EvODJWKWK5v3eFM0YI9tgCXzRvUoTkQ3Q0DzWOtpt7tpcwCvLrgD5iNH/HROwHw06ahpF6FP73bv7u08iZdW5PVA44xFHXXMu6Fduh9owC4dbHttRcL6zQCu9FjbabcbTxRi/ut3wzRhfpInYJrvzOkXIs8XTT7IqyuFhsZZHT/KJYEpIb9o+4Fhr3JzQd80YBcMMZUWasP6cgkEU4nx8tq337sOa9Ye5WUEafc+ZNCrmDzxhrTjvRTYegWc18E9kRJPBkvEKV5i4oVeacBemPLOHuueCPQzWuQ6D7WcUatfLp+DRZ9ekFEOrwePO/AejAh1cIOR1wHt7L95/ANIlHR4mtqmoF8UEZe7CNCA3TXPDrupqQjcIYTk0XZJzLxhw0i88vq9Sazkks4IzJp+PvzF5su2+GmPQMvI3yI+6MyOAMWDfpFPgu4iQAN21zw77CZSqa+DRD8PtZx2q/PfuAv1DbxRPG2AewSW+Jdg5pE/syKVa3MkcQWMRxcj/4YZIu5aCB5sjAbskaHvfOcvb0tNYt5fLDsTi5f8NImVXJIsgbFj/oKRw+Ymu9xz66JTX4HRrbzDvn0aZpQXidc9B8fFDdOAXTzcPVuLVJT/FkJc45F2025z+/YD8NxLcyEln9JKG2IbgUIYOPGYM9G9e62VaV2Tq4MXMuzuUQMu0/3iD65pmo3wHbBe2QORsG6+wPX7Xuk33T7f+/DXWLn6uHTDGdcBgfKhL2DiIeZTcPzsTUCg8eiqTqFIiUdCJeKsThdygWMI8ArYMaPKTGgkrJtH7UzLLIu7oxs2jMYrr9/t7iZt7m7W9AvhL/7MZhWKldfy0Tjzy2RELQz6xeHJLOQaZxCgATtjThmrjIR189/w4RkncnGChe/8Fmsj/P8o2RzxoNIFmHrY/2SzhPNyd34S1q6eVgX9ouMfip3XvacV04A9Mv5IWF8PoK9H2k25zYYNo/DK6/ekHMeA1AnMmn4B/MWfpx7o0gjZpS+ajkzqfcpbg37Ry6UYPNkWDdgjY4+E9UYA3n57fAezfveDq7FqzTEe2Q32tlk25CVMmvA7e0UoVN28+9m8CzqJjxH0C18S67jEIQRowA4ZVKYyI2E9AfAFDG1xbGzsh2deeCxTxIxPgcDJx52Gbt3ML2X4MXqPQ3TiE0mBCPoF/5udFClnLOIwnTGnjFR+8JdDupX23rg9oyQuDv7sy7Ow5POzXdyheq2NGfUARo94WD1hNiiKD/o+Wkb+JpnKvAJOhpKD1tCAHTSsdKWuqwhMSQi5MN14t8f9+6W/Y+u2wW5vU6n+evb4Cicc8wOlNNklJplDOHZqiwb9gj8j2TWoLNSlAWcBqmop6yoD5xpS/lU1XSroWV9/EF5b8GcVpHhOw4xpl6BfySee63uvhn3d0HjUp8ky4AsZkiXlkHU0YIcMKhOZNXP1M4QGngPYBsSPF1+EZVWnZoKXsWkSGBZ8HOPH3pFmtDvCjKJDEZ2Q3NuiJFAT8otB7uicXZgEaMAe2Ad1FWWTDKEl9ZyDB3Ds1eJzL1Zg2/ZSr7WtRL89ukdw4rFnKKHFLhFJvAVpT2mfB/1itF1aWdd6AjRg65kql3HtwwP9WkFBvXLCbBa0aXMAL85/wGYV3i5/7Myz0ae3R98RInxonLUslQ3Ak7BSoeWAtTRgBwzJComRsC6tyOOmHMuqTsPHi/l6ZDtnOn7snRgW9OYjYEa3oYhOfTVp/FLiX6ES8Z2kA7hQeQI0YOVHZI3ASFg33yPKh/j3wMmjJ63ZW5lk8fLRlPFBZ6Bl5I3J4xP4S7BYnJ98AFeqToAGrPqELNLHk7D2B/n0v/+JpmiJRYSZJh0CXQvr8a0TvpdOqONjooc9DaNn8j/pSuC6kF8k9cCw4+F4pAEasEcGHakM1ENKv0fa7bTNxqZ+eOZ5b3712SmcHC84+fjT0K2rt07Fkl1K0HTku6mSnhr0i7dSDeJ6dQnQgNWdjaXKasL6agEMsTSpg5PV1h2GBW/d6uAO3CN92pQrcMAAb92kHwtcgph+cfJDFIgFi0WX5AO40gkEaMBOmJIFGmvD+iIJjLUglStSLF0+G598eqErenF6EwcdeDeGhyqd3kbS+mVBfzRNS/lCdmnQL0YkXYQLHUGABuyIMWUuMhIufw0Q0zPP5I4MH37yC1RVf9sdzTi8i6D+Lxxy0B8d3kXy8mOhKxArOy/5APPABoG7AsWCt+ynRE39xTRg9WdkicJIpX4+JPjC250033zrFkTqJlvClkkyI1A64G0cMeXKzJI4JFoWDkTTEQtSVpvQcNDwIrEo5UAGKE2ABqz0eKwVx2eBv+H50qt/w8ZNw6wFzGxpESjqswzHHHVuWrFOC2oZfi3iQ85KSbYEtof8okdKQVzsCAI0YEeMyRqRtZV6REocYE02Z2cx3/9rvgeYH/sJmO8FNt8P7PaP7DoETYe/lk6bHwb9YkI6gYxRmwANWO35WKqutrK8UkpxuqVJHZrsiWf+jVisu0PVu0t2fv52nHLyCe5qqo1uWkbdhPjA2Sn3KQRuCRSLX6ccyADlCdCAlR+RdQL5VqRvWD721HwYRp51cJkpbQKaFsdp35mZdrwTAo3uOqJTXk5LqvQhGOojPHpgdlrIHBNEA3bMqKwRWlsZiEkpPe88lU+8YQ1QZrGEwOxTjrQkj5JJhA/NY+9Aot+x6chbF/SLAekEMkZ9AjRg9WdkqcLasL5cAkFLkzowGQ1YraG52YBjgYsR0y9JC7jQcF2giMdPpgXPAUE0YAcMyUqJkXDgEUD+0MqcTszFr6DVmZqbv4KODzgJLQf+OV3YNUG/GJRuMOPUJ0ADVn9Gliqseyz4bSNhPGVpUgcme+KZ5xCL8ckOFUaXn78Np5x8ogpSLNVg9B6P6MTH088pcUWwRNyWfgJGqk6ABqz6hLKgLxLWawF4+nelZ1+oxPZGTyPIws5KL2X3bnU46bjU7w5Or1qOovK6o3HG4rSLCYHVgWJRlnYCBjqCAA3YEWOyVmSkMnANpPyttVmdle3l1/6KDRuHO0u0S9UWFy3F0TNSO5pRdRTRI/4DozD9R+41DRfrReIO1fukvswI0IAz4+fY6Eil/hUkPPv70n/evgk1tVMdOz83CR94wEIcPvkq17TUPO7udO943sFAYkWwRHj+RknXbIgOGqEBe2HKbfRYUxH4lRDy9x5tHx8tugTLV5zi1faV6jsUeAIHj0v7RiWlejEfNTINOMPPeUG/+FuGORjuAAI0YAcMKVsSI2F9JQBP/s60rOpUfLz4omyhZd4UCIwfeweGBTO4WSmFWtlcmuh/Quvzvhl++NrBDAE6KZwG7KRpWay1trL8Z1KKOy1O64h0desOxRsL/+AIrW4XeeTUX2FA//cd3Was7KeIhS7PtIeE0HB6oEg8kWkixjuDAA3YGXPKmkqvHswRjfrxr3/zv3NZ21gpJP72CaegsLAhhQiVlgq0jL4F8dJTMxYlJW4NlQhvvJcxY1ruSEADdscc0+6irlI/25C4P+0EDg7ko0j2D8/RjyBpBYgeOg9GrzEZg5QCz4aKxckZJ2ICRxGgATtqXNkRG6ko/wJCjMhOdnWzvv3etViz1t0vAVCX/g5lQwbNx+SJv1Fd5n76ZBc/mo58zxrdAl8Ei8Uoa5Ixi5MI0ICdNK1zNRuIAAAclUlEQVQsaV03t3xsQhPvAijMUgkl01ZVfwcffnKpktq8IuqQg/6EoO6sg9mMHiFEJ79gyYiEQEIvQg8hRNSShEziKAI0YEeNK3tiIxWBayC8dTjHlq1D8PzLj2YPKjN3SuD4o3+IXj3XdLpOiQUiH/F+x6JlrIWPTAmcECwWzyvRH0XknAANOOfI1S1YEy5/QUCk9c40dbvqWNnzLz+MLVs9+SSW7SPr1XMVjj/6LNt1dC5AwCg6FC2jb4PRdXDny5NdIXF7sESk95qkZGtwndIEaMBKjyf34iKV+mpIDMl9ZXsqLlryU3y57Ex7inu86ohhczFuzF+UpmB0DyI27AokSo6yVKcEVob8Qrc0KZM5jgAN2HEjy77gSFhvBtAl+5Xsr9CwYRReef0e+4V4UMGs6RfAX/y5kp3Lgr6Il52H2JCzLdcnBNYEisVQyxMzoeMI0IAdN7LsC14THhzIQ35V9iupUeHF+fdj02YevZvLafTpXYVjZ/4klyWTq+XrhljpaYiNuDa59amvWhj0i8NTD2OEGwnQgN04VQt6qq0I/I8U0nnPh6TR+5fL52DRpxekEcmQdAmMO/AejAiF0w23Pk5oSPQ9Bs3j7rI+986M0sD9ob7inKwVYGLHEaABO25kuRMcCZe/BojpuatoT6Xmlt546tmn7Snu0arfOelbKOiyWanujZ4j0XzwI5Bdiq3WlRACPw8Ui3utTsx8ziZAA3b2/LKuPlJZfhWk+F3WC9lc4IOPf4kVK79lswpvlA+UP40J4/9XyWbjA09Hy6ibrdS2CTEcERwglliZlLncQYAG7I45ZrWLtX/XZ2p5eCWrRWxOvnmLjhdeedBmFd4of9ysH6N3r2plm20ZeSPig87IXJ/E0mCJ906YyxycdzLQgL0z64w6XTe3vH+8oE+NiG32ZZRI4eB3P7gaq9Yco7BC50srG/ISJk1Q+wsVmd8bzYc8CqPn6HSBxyHwRLBYzE43AeO8QYAG7I05W9Llmk0yoP3n5GXats81SxIqloRXwdkfiOpXv7sIJPxHoPngh1IHIvGR9OGcUJH4OPVgRniNAA3YaxPPsN/lDfLsrh+ffZ9W/4Yr985Hiy7B8hWnZEiJ4W0RCAWewMHjLDzGMcuYY+U/Qyz4i2Sr1EmBG0PFInu3USerhOscQ8CV/xF1DH2HCl1eL+8u+OKqC/IijwHScGgXbcs274h+7sW5iMV6uKovu5vJz9+GE489U7k7nzvj0nzQvUj0Pbr9ZRLNUuLvfLyoM5L887YI0IC5L9IiUFUvX9M2vTe9y9LfQNv6RVo5VA3iW5Ksn4wT33pkUjCPomw+5BHIgv5tQXlTAmeG/GKt9cSY0QsEaMBemHKWeqxqkCsBlOXVhJFffSdEtDZLlXKfdsHC21C7blLuC7uw4gH938W0qZc7tjPzjmjzzug9PssNgeuGFYsKxzZF4UoQoAErMQbniqhqkFsBtH5fm7/8NuSvrQDiW5zb0E7l5qsKX5z/IAwjz/G92NmApsVx7MwfO+eVg23B0vIRnfQMzPcAmx8BfBmP4cThA4S6z1LZOXTWTpoADThpVFzYHoGqhtYfgnfvpS6fXoq89c8DRszR0KpXnYT3P7rM0T3YLf7Qg38PvexZu2VkXD8+9CdoGXbV7jwSmBfy8zGjjMF6PAEN2OMbwKr2qxpkAsDux5O0aA3yl1wG35bFQKLJqjI5z8MTstJHrvKJV6l2ZT4bbF4Fy64D9wy9LOgXf0g1F9eTwC4CNGDuBcsIVDXIegD+fRPmrXkIebVPQdv2pSOvil9dcDu+rh9nGScvJOpbsghHTbvYVa3G9IsQC/z3nlfBcWiYFSoSb7iqUTaTMwI04Jyh9kahFQ3yPQkc2l63+dV/hq/ueWiN1UDrRbP6n8bGfnh1wR3Y3jhAfbEKKOzerQ5HTbsI3bqtV0CNdRJk4QGIHvYMZH7Rnknf7laMWaVCNFpXiZm8QoAG7JVJ57DP5Q0yLICOj+Fr2YD8lXch7+v5O+6elvEcKky9VMOGUXj9P39CPF6YerCHIvLyoph++KXwF3/uyq5joSsQKztv395uD/rFJa5smE1llQANOKt4vZu8ql7eDoGLkiGQv/Je5Ff9Ppmltq6pW3co3ljIn/w6GsKRU3+FAf3ft3VO2SxudA+0XgVDK9irjCbwQ71Y/D2btZnbfQRowO6bqTIdraiXvzaP59vz5qy2xHV9YxJEi/nzsfqfSN1kvPnWLeoLtUHhEVOuROmAt22onNuSLSNuQHzwD/YtujYhcfTwEvFlbtWwmpMJ0ICdPD0HaK+ql2cJgbsl0K0tuebX0PlVf3RAJ99INK+EF757I7+O3onE/Np56qRrXH3lu+cGNXqPR3Ti423t2SeDfsGDxB31b7O9YmnA9vL3RPUlS2SPrqUIQ+I4Cez1OsOub06FiNY5joP5m/Db713n+RuzzBuuJk+8wbW/+ba9MQWapr0NWdB3/z8WOCFYLJ533IamYFsI0IBtwe7Nosvq5SQNuAsCh5gE8lffj/xlNzkWhnl39DsfXOPZR5TMR40Om3Cj6+52TmZDNo+7G4l+x7a19ImgX3wvmRxcQwI0YO6BnBMwv5aGwPVd35xWJqI1Oa9vdUEvHtbhpkM20tkPsbKfIhZq+3xr4cOsQB8xP528jPEWARqwt+atTLc1Yf1CYV4Nu+RjHlv54SeXuv7saPNsZ/PNRm44XjKTrWcUTUJ0wtz2UoSDfnFGJvkZ6w0CNGBvzFm5LiMVehUEAsoJy0CQ+QKHTxb/3LVvUTLfanTQ2Dud/WKFDOa7V6hWgMajFgOi7Zd1GAkcOayfWGBVOeZxJwEasDvnqnRXNWH9xwJ4QGmRGYgz3ye8+LNzEYu1viTK8Z/8/G0YO/pvCOpPOb4XKxtonjAXiaJ2Xlkp8EiwWJxlZT3mch8BGrD7Zqp8R5EK/QsIjFBeaAYCm1t647MvfoTlK5z9VEoo8ARGj3wIBV02Z0DDnaGx4C8RK7+w3eYkMDnkF++4s3t2ZQUBGrAVFJkjJQKRsG6eO7nX40gpJXDQ4s1bdHy57AysWnOMg1QDZUNewohhFejdi6+8bW9wiZLpaB5/f0dzvS/oF+c6avAUm1MCNOCc4maxtRWBH2lCPug1EqYRL1/xXaxY+S2lWzfvbg4FnqTxJjElmdcTTTM+6XClBAaH/GJtEum4xIMEaMAeHLqdLUcq9ccgcaqdGuysbX41vXL18Vi95mhs2hy0U8ru2n16V2HokJdRPvR5ftWc4kQaZy1t90YsM5UATg34xT9TTMvlHiFAA/bIoFVpMxLWVwIoU0WPnTrM07TWRo5ApHYKtmzNLZJePVeh9IC3MKj0TY+dYmXtxBuP+hTwtXnK6q5Cvw/6RdsPDFsrhdkcSIAG7MChOVlybVhvkUC+k3vIhnbzEab1Xx+Mr+vHomHDaMuPuDSPjPQXf4a+JYvRr+9HfJTIoiE2Tf8QMr9PR9neDPrFNIvKMY3LCNCAXTZQldupfSw4XSaM11TWqIq2aNSPTZt1bNk6FNu2D0RjY380RUvQ3NwbLbEeSCQKdx/6YR6O4fNF0SV/GwoKNqNrYT26dVuHHt1r0KvnavTpXY3CwgZVWnOVjqZp77R9JvQ3XbZsakbRhFLR6KrG2YwlBGjAlmBkkmQIRML6vQB+msxariEBJxBoOmIBZOHADqUawDHD/OJlJ/RDjbklQAPOLW9PV4tU6p9BYpSnIbB5VxFomvoKZLfyDnsSwPUBv7jBVY2zGUsI0IAtwcgkyRCIhPUmAIXJrOUaEnACgejk52H0GNaZAb8c8AtnPQjuBPgu0EgDdsEQndCCnIcutYbe7ASt1EgCyRKITvoXjF5jOlwugW0hv+iZbE6u8w4BGrB3Zm1rp9X/KB9a6BOrbBXB4iRgMYHoxMdg9D6406xSw8GhIvFxpwu5wFMEaMCeGrd9zdbOK58oDfGufQpYmQSsJ9DhCxn2LCdwQrBYPG+9AmZ0MgEasJOn5yDta8OhkzQknnGQZEolgU4JNB35DmSXvp2uk8DskF/M63QhF3iKAA3YU+O2r1m3v4LQPrKsbBcBmd8bTdM/Sqq8BM4J+UWHb25IKhEXuYoADdhV41S3mdrKwK+klL9XVyGVkUBqBIze4xGd+HhSQRK4NOQX/5fUYi7yDAEasGdGbW+jNXP1m4WGK+1VweokYB2BeOmpaBl9a3IJNfxPsEjcmNxirvIKARqwVyZtc5+RSv0eSJxvswyWJwHLCMRClyNWluTBbhK3BUvEFZYVZyJXEKABu2KM6jdRG9YrJDBHfaVUSALJEWgedxcS/Y5LarGUuCdUIi5MajEXeYYADdgzo7a30Uil/hwkTrBXBauTgHUEooc9C6PnyKQSSom/h0rED5NazEWeIUAD9syo7W20tlJ/VkqcaK8KVicBiwgIHxpnfNLZu4C/KSbwVLBYfNei6kzjEgI0YJcMUvU2asL6DQK4VnWd1EcCyRAwugcRnfJiMkt3rZkf9ItZqQRwrfsJ0IDdP2MlOqx7TJ9pJPCKEmIoggQyJBAvPQUto1N4qk7gkWCxOCvDsgx3GQEasMsGqnI7kbAuVdZHbSSQLIHmg/6KRN+ZyS6HlLgqVCJuTjqACz1BgAbsiTGr0WQkrDcC6KqGGqoggfQImDdemTdgpfJJSJwyvEQ8mUoM17qfAA3Y/TNWpsPasL5SAmXKCKIQEkiDQCxwKWL6z1OK9EmMLC8RX6YUxMWuJ0ADdv2I1WkwEi5/DRDT1VFEJSSQOgHz5ivzJqxUPkG/4H9rUwHmkbXcFB4ZtApt1oT1uwVwgQpaqIEE0iFgHrxhHsCRykcCX4b8IrkHhlNJzLWOJ0ADdvwIndNATYV+thDgG2GcMzIq3YdA84H/h8SAk1PiIoAnA35xSkpBXOwJAjRgT4xZjSbXhAcH8pBfpYYaqiCB1AjIbkPRNPlFQMtPKVAI3BwoFlelFMTFniBAA/bEmNVpsjZcXiMhStVRRCUkkBwB88UL5gsYUv5InBUsEY+kHMcA1xOgAbt+xGo1GAnr9wJI8hUyammnGg8T0AoRnTgPRs/RKUMwJEYNKxFfpBzIANcToAG7fsRqNVg9t7x/oSZqAPjUUkY1JNA+AfOxI/Pxo5Q/Eh8GS8SElOMY4AkCNGBPjFmtJiNh/WMAB6mlimpIoG0CRo9haD50HmRez5QRSeDSkF/8X8qBDPAEARqwJ8asVpNr55b9t6Zpf1JLFdWQQNsEWkbfhnjp99LCIwSGBorFmrSCGeR6AjRg149YzQYjYX0LgNQvKdRsh6pcSiDRdxaaD/pLet0JPB8sFnwHdnr0PBFFA/bEmNVrsjasPyOBk9RTRkUk8A2B6KFhGH0OTQuJBM4J+QWfe0+LnjeCaMDemLNyXa6tDMzQpHxVOWEURAI7CcSHno2WYVeny8PwFWBgeQ9Rl24CxrmfAA3Y/TNWtsNIpb4aEkOUFUhhniUguw5C1LzxqqB/ugwqg34xJ91gxnmDAA3YG3NWssu6sH6lAfAdqUpOx9uiWkZcj/jgH6YNQWr4r1CReDTtBAz0BAEasCfGrG6TtWF9iQRSP91A3ZaozOEEYuUXIhb8ZSZdfBVrwviRg0RDJkkY634CNGD3z1jpDnf+FvwKAE1poU4V5+sKJJqcqj7numNDz0Vs2JWZ1ZW4JFgibs8sCaO9QIAG7IUpK94j74jOzoA25PdH4fS30O2V4YCMZ6eIi7LGh5yFluHXZtaRwOvBYjEjsySM9goBGrBXJq14n3wu2NoBtUDD3AOuxOljftKauOsbkyBa6q0t4qJs8UFnomXkbzPuSAicFCgWz2WciAk8QYAG7Ikxq99kbaV+i5S4Qn2lzlB4d2I4tui/wMXDZu0WXPj2cdC2LXdGAzlUGS89DS2jb8m4ogDuD/jFORknYgLPEKABe2bU6jcaCQdWAFJXX6naCj+SfpzUMhMXDzP/+saATdWFH8yBtvF9tRvIobr4Ad9Gy5g/WlFxoyExlW89sgKld3LQgL0za+U7rZ1XfiqkmCcluC/TnNZm2QUjW77TGt2WAZv/vGDRBfCtfynNCu4JS/Q/Ac1j77CkISlxdahE3GRJMibxDAH+h84zo3ZGo5Fw+WuAmO4Mteqp1JtPQRR5HRpwqwkvvgi+df9Wr4EcKYoFf4VY+QVWVfsgWoupY8aIFqsSMo83CNCAvTFnR3UZCevmd6R8h2qKU7s5PhZ3JEbsjmrvCnjXAi+asNFrDGLBy5DwH54i3Q6Xzwn6RaWVCZnLGwRowN6Ys+O6jITLPwfESMcJt0nwB9KPb7XM3Kt6ZwZsLs5ffhvyV98HyIRNynNX1rzTORa6DDKvl3VFJW4LlgjePGgdUU9logF7atzOajYS1lcCKHOW6tyr3SS7YNTO3333rJ6MAZvrtc2ftJqwb93zuRefg4qyi7/1qjc+8DSrq90X9ItzrU7KfN4hQAP2zqwd2WltWK+VwABHis+B6FWyB6a0tP3K2WQNeKfMrXl1T/fMW3UftK2f5UB5bkokSma0XvUaPYZbXfCJoF98z+qkzOctAjRgb83bkd1GwvoGAEWOFJ9F0e/LEny75ah2K6RkwAK/S8Txok9EF+Svug95q++DiG/NovrsppaFAxAfeDpi+iXWF+JpV9Yz9WhGGrBHB++0tmvC+kYB9HGa7mzpfdYYjPNikztMn4IBfxX0i9bXQlZvlEMNA6u0bctaTTgv8s9stZCVvLLrYMQHzm41X/OrZ6s/QmBxoFiMszov83mTAA3Ym3N3ZNeRsL4eQF9HirdQ9D+NobgoNqnTjMkasDRwQ6ivuH5XwrVbpD8aw2IApb7611ufGfatfxEitqnTmnYtMLrrSOwyXitvstqjIQnUhPxikF09sq77CNCA3TdTV3dUGy4PS4jZrm6yg+YqDB2/jCX3hFa6BmyWXy5lgdiIFyDR+ky2aGnYacQvwdewQBn85m+7u654Yb75KXufpqBfdMteemb2IgEasBen7vCe6+aVzTYMLezwNlKW/1AiiKviBycdl4kB7yqyokHeL4Gz9yyqbVmy+6pY216VtB7rFgoYvQ9CvPSU1q+aIXYcPJLFz2dBvxiTxfxM7VECNGCPDt7pba/+csEP8r644lHRvM7prXSqfxvy8UAihFviqXmAFQZsiqtukH82gIvbEupb/3KrGWtbFkHbXg1AdtpPygu0glbDTfQ+CEbvcTB6HwxZkLNfIq4N+kXmr0lKuWkGeIEADdgLU3Zpjys2yDu7fPDDn/k2vOXSDgVWFo7CEZtHw0ijQ6sM2CxdtUH+DhJXdSTDvGtabK+G1li98+8rIRpXQtu+EjCak+5A5vWE0eeQ3X8l+hySi6vcvfUJxADMCBaLhUkL50ISSJEADThFYFyuFoEV9fLv+Utv+H7eV49m5+rLpnZl1yFoGXY1/rQJuH3Z/LRUWGnArVfCG+QPzJcOSOCb8y6TVCaa1kBE6wCtC6DlA6ILpPn3tv539r9S7lC1lPhHcz4uHtNbmI+/8UMCWSNAA84aWibOFYEVG+TTvprHT86v+l+IZvNGaQd/fF0RM49MHLbjYvP2Za8oY8CtV8J1sh/ycbX5siUHU25XupS4MlQibnVjb+xJPQI0YPVmQkVpEKiql69BYHre2grkrXkY2nbnvXg+UTwZzePuBfJ67CagmgHvErbsa3miprUacccPI6cxS1tCBKo04Bd6sXjGlvos6kkCNGBPjt2dTa9okO9J4FCzO23jO8hfcTt8mz4EZFzdhrV8mG/oiQ/+EeIDTtpPp6oGbAqVUuZV1eMaaLhaYOc7ENUl3bYygSpp4MG8QjxQ3kPUOU0+9TqbAA3Y2fOj+n0ILG+Qnwlg1O5/3FKPLktvRF79q0B8uzK8ZNdBiPc/HrHQ5eb/XWhXl8oGvEv08gY5WRO4WkqcqAzgToRIYJHQ8EA8jgdH9BXOPXPTKcCps00CNGBuDNcRWNEgqyVQvm9j5qv3fF+/DK2pJqW7ci0DlNcT5tfMsbLzYPQen1RaJxjwbiOulz/UBL4lgW8B6JJUg7lftFACDwaL8YAQIgvPTOW+IVZ0LgEasHNnR+UdEKhqkOZRige2t8T8ijqv7llomz6E1vQVkGjKAk8B+ApgdA+2HhgRH/T9lGs4yYB3Nbe0Xg7MEzh1pxG3/7aIlGmkHyCBlwTwQNAvKtPPwkgSsJYADdhansymEIGqBvk37DjFqf3veHfq1aK18EUeh6/hTYhtyyFkDDDM344TgOzkKVyhAb7uMAr6wnx8yOgxAkbRIUgUH77jMZsMPk404D3bXVondS0PszWB0yVwUAYoUgqVwAYBvCOAdw3g3ZBfvJhSAi4mgRwQoAHnADJL2EegeoM8WUr8NfN3ChvQouuA5nqIWH3r2cjmxyieDKNwYNYadLoB7wlmZb0cYQjMbn2OWGK4EBguAUvOVxZArRR4FwbehoaFPEAja1uSiS0kQAO2ECZTqUtgeb2cLwSU+Do0FUpuMuC2+q5qkIMNYIQmMRwahgvZasrmQR+lAMybo8y/tph/F8BWueufiR3/GxJVwsBCva9YmgpXriUBFQjQgFWYAjXkhMCyenmNBlwFgay+NsfKZtxuwFayYi4ScBoBGrDTJka9GRH4fL0M5fvwtEjjOMWMCqcZTANOExzDSMABBGjADhgSJVpPYMUGeaUEzoWEbn126zLSgK1jyUwkoBoBGrBqE6GenBKobpDm4zKXS+CQZO6Wzqk4Bc+CznX/rEcCbiZAA3bzdNlb0gSqtsoxIoabpYFZEChMOjDLC3kFnGXATE8CNhKgAdsIn6XVJFDVIO8FcCoAv40KpQCW//zDf0Ser10yPR0dVr+OMB0NjCEBEmifAA2Yu4ME2iGwYoM8yZD4rgAOw46jLXNx9/RmAbwiDdwc7Cs+xINXXg8N16UzJBpwOtQYQwK5I0ADzh1rVnI4gaUb5TifgR9A4ChptB4k0T3dliTQogEbJLBWSCw1BD7SJN4MlIj398pJA04XMeNIQHkCNGDlR0SBqhL4ICK79c7HeZpA1wTQTRMoFOYzxuZvyBKFhkShJlAAiQIIxAwDizUNC/UivCSEaEmqLxpwUpi4iAScSIAG7MSpUbN3CNCAvTNrduo5AjRgz42cDTuKAA3YUeOiWBJIhQANOBVaXEsCuSZAA841cdYjgZwRoAHnDDULkUAaBGjAaUBjCAk4gwAN2BlzokqvEqABe3Xy7NsDBGjAHhgyW3QwARqwg4dH6STQMQEaMHcICahMgAas8nSojQQyIkADzggfg0kgywRowFkGzPQkYB8BGrB97FmZBDonQAPunBFXkIBDCdCAHTo4yvYIARqwRwbNNr1IgAbsxamzZ+cQoAE7Z1ZUSgIpEqABpwiMy0kgpwRowDnFzWIkkEsCNOBc0mYtEkiVAA04VWJcTwKOIUADdsyoKNSTBGjAnhw7m/YGARqwN+bMLp1KgAbs1MlRNwl0SoAG3CkiLiABGwnQgG2Ez9IkkF0CNODs8mV2EsiMAA04M36MJgGFCdCAFR4OpZEAaMDcBCTgWgI0YNeOlo25ggAN2BVjZBMk0BYBGjD3BQmoTIAGrPJ0qI0EMiJAA84IH4NJIMsEaMBZBsz0JGAfARqwfexZmQQ6J0AD7pwRV5CAQwnQgB06OMr2CAEasEcGzTa9SIAG7MWps2fnEKABO2dWVEoCKRKgAacIjMtJIKcEaMA5xc1iJJBLAjTgXNJmLRJIlQANOFViXE8CjiHw/39+qzsiJ93EAAAAAElFTkSuQmCC5267139422670