data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAKAAAAB4CAYAAAB1ovlvAAAAAXNSR0IArs4c6QAAH7BJREFUeF7t3QeUXVXVB/D9ZpJMAoFAEnoHRZqAQgAVUZSWIE0wYBcxFkQBQVBUFDuKFbErCopRERAIRVEQRUTARrHSpIQWQiQhZJKZ963fSU54ebyXV2ZmvW+Se1lvMeXec/bZ+7//u5xzJ6WTTz65HMu5yuVy+LhKpVL65MvP+/v7Y/78+fHkk0/GwoULY9SoUbHaaqtFT0/PMvcub456v+vt7Y1FixalcYw7YsSIpbK0Oh5ZjWPMuXPnJlnJOHbs2Bg5cmTb41bLMZgyV49daYuurq5WVfD/8v5SPQAC1oIFC+KJJ55IRrN4hho3btxScM2ZMyeeeuqp2GSTTWKDDTZIP583b17ce++9cf/99ycgMnAlaBtpwbzAbBxKHj16dAIhWYxvTEBs9TLe448/nuTfbLPNYsyYMel7svrd+PHj01ztXEMlM1nova+vL+n5f//7X9IFvZB/9dVXT7poRb/NrM962Nz/sw2aea76HnJl8soEVvl9+lk1AC1s0qRJsc0227QzZ0vPYKKrrroqHnjggbRQC3700UcT0F7wghckpnrooYfS90AOLDfeeGOsv/76seqqq9acyxj5QwHd3d2JoTnLnnvumRzqpz/9aQI5p9l///2Tsn/1q1/FhhtumBym0ZWZaLBkXt58dDB79uzYcsstY4sttljqkH7217/+NelonXXWSeQw0Au46QfY4cD66IYDrLLKKulDn42uVqJN6dhjjy3nSdZYY41485vfnDwqD9Lq//916u6xy/o9jWSMnhGleOgtV6V5KPLyyy9PYRETvehFL4qvfOUr8Yc//CEt3jVhwoR44xvfGFtvvXVcdNFF8axnPSspKH/cg8kAjfyYIbM4AL7qVa+KK6+8Mn7yk58kNs0XpRp3p512ip///OcJ6OZkUJ/MtpmFzEHOHBEGInMlczE+O+Rog42NDRCTJ0+OP//5zzF9+vSYNWtWkut5z3testU//vGP+Ne//pVYPYflZhgxO1G+1/wzZ85Men3uc5+bxvUzevfh+MiA8zcCeyvRpnTUUUeVDQrZWI+BB3KN//Z+sXrP0/nJ2NPvifKch2LeJ3d5xrB3v/6ypT/7xS9+EXfeeWfssssu8YlPfCL+/e9/PyMvAwZKp+wbbrghMSOlk52y5InAix3vu+++WGuttZYCCGgvvvjipYCuFMa4Rx11VLr/wQcfTOMaD7tgAuM98sgjiQG23377FPpcwNCuzIwonQA0IBNezc/YLsaWxhxyyCExY8aMJDtwVl4TJ05MuuLA0gm6sBYy+9QKzxzJfJzSGumO3jz/whe+MD1zxhlnJP25jPmc5zwnjj322LjrrrvijjvuiI033ngZ22SSaifalM4+++zy73//+zThxz72saXrY0hKsmjM+PDDDydBfZ//z1AUiHUs4D//+U+sd+5BywBw1JT3x6g93hZz37fpMwD4z6kXLv3Z5z//+WTc8847L/72t7/V9QEKOv3001PYoUiyAIHwvPfee8ePf/zjuPbaaxMbkh9YGfX666+vCb48kXV85CMfSaxjrGc/+9kpJP/mN7+Ju+++O3bdddfYdNNN44ILLkhshDnI++IXv7hlmenNPFiFXgHp5S9/eWIgrG9s82FjrPyjH/2oruxsI1qQkaMAg3HYU77LWXJEk3ZwpI022iiBKjsv/WVGBz7OUH2JTJ/85CcDVjJ4AZhTArvnRZZWo01p7NixZcYipIXsuOOO6evPfe5ziebRO0+Xp/nwzHXXXTcZ3u+hnlGuu+669NzG0w9bBoBjjvx+LLzpx7HolqfZLi/u1kN+sjTUH3TQQQk0lFSdqFYrw4KBSr7oa3K87nWvSw7ESwGPguVMwvCf/vSnxGw5nNdDt7Xkyh7Qt9122zj44IOTg5nvs5/9bDJOLsYYsB2Z6U6OK7T+8Y9/jH333Te+9KUvxS233LK0yDA/QJm7kdzyQ3bzPNDRJZaS1gAIkOZ8er/99ks55fnnn590BVgvfelLY7311ks259T1Lk6PKP7+978nHKgVjD+QaFPq7u4uE37q1KlJ+bvttttAInBsedHrYrVRT7dq6g9WipunnJN+bUHYBfiEGywoEW7mwiZHHHFEYuJvfOMbSZHvf//7E3thF05Bcb/73e/iO9/5TlJ+sxeAAaHx3va2tyUjbrfddnH00UenXAkDtCOz+cnFSd773vcmZhHaAG6fffZJgATA22+/PYVekaWVy7MKLumKgkuKhRUBTdF32WWXJQbmvNIAlwhWHeJrzUm/MPLKV75yUKJNqoIB8LbbbkvKxBiZPbIAjcrpdn/PoNdcc01SNgBRAsMyxEc/+tGUA1WPXa0UAPzwhz8cl1xySQpDX/ziFxMTcKbNN988gUQ+iQXWXnvt+MAHPpBYKxdey2Nbc7/kJS9Jof1DH/pQvOIVr4jXv/71ibWwUrsy59xKvou53/3udyfGMgdgCInkBg55+RVXXJEKEOGt2YvswCyvow/VvZAuSmB6a3nta1+bfp7D9je/+c2UFtRjXHaCjfe85z3x8Y9/fFCiTenMM88s8w6VD9ZhfIzE+3391a9+NTEILxTyGoUDC//MZz6TACGXQ9GUCSjmILy8hmHlZc9//vPTQozPa80BHLwTA/Be1atEm4Nk9siJLxAYc4899kjy33zzzYn9MMqll16a7sdeuZ8m/2EATPjb3/42hSlMmSteDkjRQOoSsk444YRBlTnLLgQrMoQ1jmG9QiKgcE5rA3YsjMF9OJK0SKhslKrI/84666z4/ve/n3JMbCod+eAHP5jSqGyfvJkgpNKzZ3I1Xgn4oYg2pVNOOaVswaopQOR1J554Ylo8MKHcXGFSkIQYMwmZlJTzC+zjPtf73ve+lCtJro0HGH4nweb1FAN0Cp2vf/3rKX+kBIBnCCDPOxV+zgF8b26OQVEAq4/HWbCHjzl5NPDy9NxuMS6PlcPmefyfHMZmFM9bb26s//KXv0zAB1ghcTBk5hRbbbVV3HTTTamKByzOYWwRiL60PwCGA7iXPvxOUZSrXLLrWwKUrxVaigugoldODJxyzR/84Afx7W9/O/U7AUjuptrmdCLEX/7ylzQGBwZ2+eQ///nP5KT//e9/k5zGZD+YOPXUUwc12pSmT59eFu6AK19AJeGmMMIyqgUSlIC5828xfgekjAhMwqiQpe+mGhVSFTGUIZy4H8CAF+ABJQPX/JxBJWYccriXQs3PYI899lhKerM8FOf3ZAIWTMYBKLHyAnbGNC/F5i1D4RnrkJGzULyvsS2FCzkAMlCZOS1QZBAJs3QLPBzHuujq+OOPX8q+5Ods73jHOxLrWZ+L3oAV4Dim5zG670UceZ8IZL5TTjklgdq88lfsriDbYYcd0u98zfGAEQ5EEHJlwElbOLuo5Wv6VqEPVrQpTZs2rXz22WcvAwICHXrooSn8yAl4AEUwBo+wGMoCPJ7KiIR2YRpKOOywwxLgeKCFE1qVxRDCKgXIbQCp8qIg4YK3UoZQYCyJrwJl5513XlpUvOxlL4vvfve7KY8EwDXXXDMpmGNUhyc/Ny9jCV++f8Mb3pDWpdVy5JFHpuTcOIxqDVKGwZJZxDA28AME3ZqX7uhVJf+1r30t6bvyIociiBNYJ31zbo5kHE7KFqpfrGZ87SG6Mj4W3WuvvVK0EBmsn6PJ97BoZZ4vHaDr3F6RcxqPU3NYEUw0yXocjGhTKpVK5Vq5RN7G4vm5R0QRhM85g8SYQEKUn1OGhWIRP+eRGI4h5ZIW085loYCm/yaEq0KBT2vkzDPPbJgL1ZsTo37rW99KLQkOhBFcAOFrudJgyozlhPqTTz45FRW//vWvky7zzg3g17ry9lfOv6UNWmaenzJlytI+oLGBKBOGnh0AihhIxvhsAYga/9VVL/sZz5pFEHpXIEmvMKzINtjRRr9kuadhKj3kne98Z+oxSYZ5mFzGxTsxBYXkAwjyL2FCH0s40wJpVMDUAwqFaTBTJE9817velRgLe8jV2r0AUMvnnHPOSewJcC7bctoM8p3BkvmYY45JOSl2Irv2Sz3ANVoPfQAwoAHN29/+9qVtK0zKTnqz9C/6qK4rtx8bjV/5ex0S6YsPEA9mtEnFWCsAZPgDDjggUbt+EkrOl59PmzYtgUTul5uUQrAQoYBops9USznY9Ic//GFKxoV9uRxvxAyU0u5FRrsq5557bsptTjrppJT/Mdpb3/rWlI+1C5JKmUUFhZ2xGVT7Q55amfu2sgZhGQDlkZwfuHOHQLiUyyECOzqiBrZr98KgBx54YAL4YEeblgCIeeR3Fiw342mnnXZayrdc+cwepWINeeLhhx+eFC5XAaB2AWgurQqgFwLMoakK3CrVdi7g/cIXvpCKKn0yuahE3Jq0R4BT+GkXgJUyM16uaIFb09/Y7eoDoKUO2F8awgYKwCyrtWFJebwQz8HavaQjr371q1OnYiiiTdMMyDhyJQDAcqoyXobeLbLW5fe8RhvAAhr1reopSc70mte8JlXGQqbeoXDvgEG7oUV+A7wKEobTBbAOfTAAlLMquNq9ssyKhltvvTXlUeaQo4kQmLue3hrN+Za3vCVVxoAnDRIVtG6kRi4syF52QqyHztq5kApnUf0qegY72nD6pgGYQ5QcgFdgDdWqfEZyXeviibaZhAuhoN2LwoUYIVhlLVEW7pvdrqs1LyNhZ3mUCxtqStujdWSLMdt1GONVynzcccelnFluqW8pHWmXWY39qU99KoFCI5kNtEisxYkVoMGQjphJA+Tm1Z2GZu0gL+b4dlPkyYMZbWBIMdk0APNOAaNrKQCA8GUbDDBqXRagp2dnBAO0y1Z5bK0Z7GQbCQMMxIiV8ur3UbCPsOVUzD333NOsnRreJ5/US9P2EeIz6Bs+WOcGwMpH/9mBXgFFgSj9Ef6BXs4u72zn0qZyNE9+ORTRRu/VjkvTAMyL4GFOiAChPKweAwKsxFso0DgVBii+XdCY1+kW4NOQ1Sbg+e3mUXk9ciWGEooBXO/LjgnWHujYZKYnUUC6oIUkjZGODMZFXg6u3WIbk1NibSkK4ABnu/oGQECWqw52tLFfj73purTXXns11YbJCrMlBHjyGB6C9mu1KoBFN15PSbWGUeQ8Qkc7F8Xa45WX8XjJvO8rX37KPTUFUD5WZa56J4Xzjo6cVn7pe6BOoaFUSr2vZk4X11sPGTiLHFDvThLv8IFQnw98tqMLz0hvNJitjYxSI/qmD60erRlHvESndnJN4+RT14MdbRRFOih0XrrkkkvKFgFEuS2AvWq9dYURsJntG1Wdvhlw1brymTe9OiEDG8qr8rsmPCyfxMhvqVFqPkBZOSZD5jfvNIx5vAVovOp15YOV1uBnxgVSYd+z7vGpBlM+FAAcWO/LX/5yyjXlJ1jEtqB1uNzbrszGVyz87Gc/SwdYsZU8LZ9YrmxGmysf+c8N6mpbkIXOtFncm/fvrdkzdGgOYdm62mFBc7CdXqkuxmBGG7sxcKBdVDrjjDPKlGzf14QWgeFs7VQn4b4XsizItpGqrplEXehxjEnrQGNa/BfGba+pEjVN5WGqOpUbEFT2yMyR90ttHzlFw2gAm99P0Bszj/wNywIopgEia7Jbo39Zydb56BMnwhS5qMlbTwyZwa3dMVCZzQ0sxs2vC1hD3nNmFOu2HUcW9wNSvReBjMUGdokqC0EgpGOFiZ0P+sggpje6wnDGZw/6zSebs+NnnctdtaRU2tkZ3TPQaEPHOiilJ554oowKtUuETVWa8MbgNrUrDUYp9hvz65jNhA+FiByIUi2S0QHM6RuKsf8qP+KtQG2fE1M6SpXBnY9SebZWOKFwOwKKHSDh9XYxGFqYxjzCCJBRaDNOU2kI7AuAxh9MmfN2p0a9cAmAciO7Rhr7QpV0QHFUeViE/GwGdPlVzWpbGDu/MpHfIGRfoKVjgBIhhG1kg6V1OjIgM8i03eTucFD5HslAo431KpBKvb29ZQyk70URcjasJFchOO9rNw/KR5/kixjWIh1GcH4Py1KgPU09RZcTNWSw7aPCpsDKq9Lr/JwSfLSE5GvCPNCZS5jGfFdffXUylrkpHfNUMwrHwkL5BXUFia/dZwzjK1Rqyay9xLCtyAxA+UUq8gn39E3vn/70p5MeFG9YPLedrL2d96Fz+kBPxhX6FSjSKSkHxhVmtZ4UlIoa+suXeXM0ynpjFyTFyQcabUo33nhjGeoZADgIpXLzNRrHWvkYkcncK1QCCoX43r28KL8KSWgLxhrGNYbDnzkMaHUI5XnxEnW7GlhSDpdzwkoW8jVvBCTJMTZUTQKL+ynWOGSVA+rDkU2bKOdyOaxVjptZ3faYUx6Uj3nMQ26MD4T2hq3FuhhsoDIbn2MYj0NyDLJgGQYGTEULcIsY1c6IFKxbWMTydM4Oxshv7VWHU06lL2id+eApPcrr2VS45kgOkVSDnZzZIW3t6UZg6epog8xEG4VXM9GmNHXq1LIGKfTrpkuWgYDSTWqhPJPyba0Jk5TiNUaL/t73vpfYJp+CYTRAkd/ZQ/Qc8AGLcIFhKQAAUbAyX1iwJ8uoWdGZ7bIHA5qP+wFAviqJdV/OYTgMAzAKNtTwlUAzUK0rK9/6tRoo/cILL0wHPcmhUiUrx8m5JtbGhgOVmV45INk5atazniH9OkVEdxw7M32ORJ5hH8CxUwE0CkM6xGyeya+Tkt08AIc02CWHfk13OjBXPlrF1pVpV05/zOX+VLmWSulET61ok9/yc84RYTWKNqUjjjiirLnrAXEZW1S+eEwAk2MdFyAxrhYMhpFDMIp8wgeIVGcWqvIEEODUTVcEoHoKdmVj5vc5GLseUBQKwhH2BA4gz++3OimTmYAnCw8+knPOVO9FavPLbxxscB9ZGUKFb78bE2o75T/ZweiDLbO0IIOR7A5AmBsDskmt9AdAMA/HkiMCXD4ZlF/3JLMwngFIXy5OBqSAIYSyCYfLL/pnh892MJedFAxtdwUBIRK5vbEro40mO5nYIhNYo2hTOvzww8vYT7ebAoSGykUzih4eI0nmfa/PxKgmsbcJtEI3L1QM5L/rQkBjehbINSAxFI+Xs1GcCkuxAwD1chxhCZ1Tak6ozS+8Yjh7zRbueQzr+DkjClGZXWoBG4DJwRj5JLSqE6tYD8Xz4qyPoZA5V5ZkMQ99chxyiya1LiFZUcJWHJ6ejfOmN70p2cC2Yn4dojqNQSiciLMLo9aZU616OhIJyCVEYzhzwIHNAGM5J9putEl/GUH7QlyX+1WDAGB4m6KAsXPfjbBYCX0TSqUGBNXsqaoWsrCinMY9jO17LJV7dZRQ78pN5Vy9MpYQ49yb4gnQPM/75UEUpZrMR/TrDlzxC2Nbn3c0GNiORQZ1vm0oZM7gpmPMy9noBEDqFX9CKrvkNAURkB+jAUI+tlarl+s+gLKHjBzkaiJUrXutmxPSKcYDcvIJxboWOhn5dHu70aZ09NFHpxfTGRQjVV8QTjmAxSCZgSgArXtjzPFuygCCyhYHqpfUq7oUGeha7oTWeQ/WM0Z+U60ZoLgnh00KEb4xMMeRn0gXyIq5qpPx5Y3PqAAovXB0jJNg88pQNBQyG5/uMLy0RkdgeWlDrTWwj54fhxYN8l8qq5fOiBLeStSdWN69ns8n4vNYSEeEkDo4FAGIqut2o03pwAMPLOe/PlWdMAIThfh4hwMAs6egYYriAfIVX1c/n5ujhKXg/DdoMIxiB0Byb6pZ8JFJQq3KBT5hKjsOsJPVTgZQ1mvg1ppLPotJgED4rnaKoZKZLBzVmjinXIsjN9v6og+MJ/zqn4oOtXZ98poBhe3yjtPy7q3WEzCKaAoQ1S4wSqEGEm1KkyZNSiG41p8l45kqWKFt9913X5qM53ClLwZImCK/YV+ZcwAdJspgxbIu39vR8KJSTpSbBaAQAGi8nSdnpyCralyCTK56+VO9eSgzb8nV+vNvQyFzloWj0gfHUWi10u8DXswtz7b+RuwpnIogckwFVitzcUIRSz6vmMzdgYFEm9Khhx5argcCjICmtT1ytUZpAKkB6zlCYYtqj83vAQuTlJKLG+CVQFOEfdEMymYBCAjpIOOSVwkz0Miazyqar15OU2sens2RRAKGAerK9QyVzFkWFaxmtwJIrtXKBbxyOWkH2Zf3vHVgd47LSd3bLNOSKeeCooW8X+gfaLQpHX/88WkvuNYFRHp1aLoynBEAM2IKHlvrL4sKBcp7XqbTnz0tV09YU8OzFQXk8Jv/WlXl8/mgRDN/v656rZxIOJcPiQbV+hgqmclhTV4O54gKvVYcx/NSDl0KZFD5NwLr5X/SJXpDKq2kKHSgYBHpEBDQs/FAo03ppJNOKi8PBBRUzQY8Vj9QGV/vlIlKy5v2jgxVFzcWYPGtKhvLqdaNl/+WXaWiq2Vthkk8w5MxvTBmPfWMN1Qy5z/D0egPP1bLRY9YX0FIz42iifvki6rten9htp7O6F4XQ8TRE2Zb7DfQaFP3b0TXEwQrmhyj2UGo5UW8JR8D0tppheWWBxr5nZMwmty1KvZmAFd9D1mFJCzIMK06RaM5h0LmPCcG0r9lB+zdSM+cjf3yMbBGslf+XtrjtQLVsygjFRqMaNMWACWxFry8RD9v57RC840Uwgu1jFrNXRqNK3znP5nR6N5Wfz9UMpMjV7RC72DquXqNgMvmckDOnw9tNAJ8rXGqo03LADRoboC2KkCrxqt1fzthdjDmHcgYQyWzcfNBkYHI1+hZc+Q/Ytpq6K4cu1a0aQuAjQQufl9ooJ4GqqNNAcACKx3VQAHAjqq/mLwAYIGBjmqgAGBH1V9MXgCwwEBHNVAAsKPqLyYvAFhgoKMaKADYUfUXkxcALDDQUQ0UAOyo+ovJCwAWGOioBgoAdlT9xeQFAAsMdFQDBQA7qv5i8gKABQY6qoECgB1VfzF5AcACAx3VQAHAjqq/mLwAYIGBjmqgAGBH1V9MXgCwwEBHNVAAsKPqLyYvAFhgoKMaKADYUfUXkxcALDDQUQ0UAOyo+ovJCwAWGOioBgoAdlT9xeQFAAsMdFQDBQA7qv5i8gKABQY6qoECgB1VfzF5AcACAx3VQAHAjqq/mLwAYIGBjmqgAGBH1V9MXgCwwEBHNVAAsKPqLyYvAFhgoKMaKADYUfUXkxcALDDQUQ0UAOyo+ovJCwAWGOioBgoAdlD9/iXN2bPnxKJFfdHdXUr/+qh//HvZfwSynCQslxd/+vvLMX/+/HjwwUdi5MiuWGWVnvScf0i61X9vuINLXzp1AcAOWMG/PumfPr3++r/GAzMXRl//qtHdNT8mTlw1xo9fL7q7RywGnf/6y9FfHhXl/rGxcGFX9PX5J2ufjNlz+mLhwpnRVb4lenp6Yuedd4xJkyYN+r93PNTqKQA41BquMb5/ufzqq/8Qt956e/R37Rgx8tCI/llRisej1LVaRAkAMZ9Pf5RjQkTXOhExMiIWRrm/LyLGRvTNiOidHqWuTWOLzcbG5Mm7LvffcO7AUhtOWQCwoYoG/4ZZs2bH5ZffFvfPfCyi/GDE6A9HjNg3Ip5aArLSEvAtmbs0OqJrbER0Lf55wub/Iua9OqIErwfERuveHlP2WyvGjVt18AUewhELAA6hcusNPXPmIzHjsgdi1tzdInovjCitETH2/Iiu1Ws8Aow+wJevcsTCKyPmvSli9PFRGrFVbDDxqth/nxGxxhpjOrCi9qcsANi+7tp+8v77H4oZVz4as+cdEtF/b8RTZ0as8pWInsOXgK3B0OX5EfOmRSy6PmLsORHxeKw/YUbsv3dXjB+PKYfPVQCwA7Z6GoBTI7q2i5g/bTHwxl4S0bVuI/RF9F4e8eRrInqOiug5MaL/T7H++BkxZe9STJiwWgdW1P6UBQDb113bTy4DwJH7LA6n84+JGHVkxCqfjojlhNHynIh5B0f0Pxix6qURXRMi+q4rANi2NVbCB5cF4OTFgHvquIjeCyJ6jo7omRbRtWFV3kdRvRG950Q8eULEmNMiRh0TUZobsagA4EoIo/aX/AwAdk1cnAsu+Mji8Nq1Q8Tod0Z0bx8Rq0REd0Q8GtF7cUTvWRFdm0Wsel5ESWvm8QKA7Zti5XyyJgCpojw7YuGFEQvOiuh/JKJr7cUVsv5f/8OLPyN3jeg5JWLE85corwDgyomiAay6LgDTmAsjyndELLomov9vEWW9wqciShMjug+I6H5xRNeaFdVyAcABmGLlfHT5AGxVJwUAW9XYSn9/AcCnIVC0YTrgDgUACwB2AHZPTzk0ALw0puzdHRMmFDshHTXucJg8AfCKh2P2k1MjRk2OKK3dpthOJTwWsfDa2GDCZbH/vqNjzTWLwwhtKnPleWzmzIdjxmV3x6y5r4joOTiia+MlvT6HDpq9gK83ov/OKC2YERutc21MmbxRjBtXbMU1q8GV9r45c+bElb+4Oe6+b7MojzwoYsTzIkrjlux8NAPCJWcF9Qp7r4nuvsti263nxZ577pROVA+nqyhCOmCtRYsWxe23/yNuuOHumDN30+gvbRNhNyQWn4Ru7upLjenu8k0xcfzM2H337WPzzTerOs7f3EidvKsAYIe0772OO+64K+6888F4Yu7I6Osf1QIDEro/RnT3xppr9MWWW24Ym2yySYwY0QqAO7TwqmkLAHbQDn19fTFv3rxYsKA3+vr6W5aku7srxowZHWPGjInubvvFw+8qADj8bLZCSVwAcIUy5/BbTAHA4WezFUriAoArlDmH32IKAA4/m61QEhcAXKHMOfwWUwBw+NlshZK4AOAKZc7ht5gCgMPPZiuUxAUAVyhzDr/FFAAcfjZboSQuALhCmXP4LaYA4PCz2QolcQHAFcqcw28x/wfXt2swzIuhPAAAAABJRU5ErkJggg==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 _
501de:Grad _
ca:graus de _ radians
pt:_ radianos em graus
0.5de: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 time1000deltaXdeltaYde: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 positiondirectionsizetempovolumebalance112de: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-outelasticunknown 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
}
elasticde:fange _ _
ca:agafa _ _
es:atrapar _ _
fr:attrape _ _
pt:captura _ _
contde:wirf _
ca:llança _
es:lanzar _
fr:lance _
pt:lança _
catchtagde:fange _ _
ca:agafa _ _
es:atrapar _ _
fr:attrape _ _
pt:captura _ _
contde:wirf _ _
ca:llança _ _
es:lanzar _ _
fr:lance _ _
pt:lança _ _
catchtagThis is a breakpoint block, to be used in debugging.
The Boolean input specifies the condition under which
the program should pause. (Use True for an unconditional breakpoint.) The intent is that the script should have
SHOW VARIABLE blocks for the process's local variables.
After the pause, this block automatically hides all temporary variables.de:falls _ dann _ und pause $pause-1-255-220-0
ca:si _ fes _ i atura-ho tot $pause-1-255-220-0
es:si _ haz _ y páralo todo $pause-1-255-220-0
fr:si _ faire _ et mettre tout en pause $pause-1-255-220-0
pt:se _ , então _ e faz pausa em tudo $pause-1-255-220-0
This block does nothing.
Use it when you are calling a reporter
for its side effect and don't care about
its return value.de:ignoriere _
ca:ignora _
es:ignorar _
fr:ignore _
pt:ignora _
Call f(f(f(...(f(x))))) n times where the three input slots are n, f, and x from left to right. The # variable can be used inside f to represent how many times f has been called.pt:o resultado de _ invocações em cascata de _ com argumento inicial _ _
ca:en cascada _ vegades _ _ _
Call f(f(f(...(f(x))))) until condition is true, where the three input slots are condition, f, and x from left to right. The # variable can be used inside f or condition to indicate how many times f has been called.pt:o resultado da invocação em cascata até que _ de _ com argumento inicial _ _
ca:en cascada fins _ _ _ _
Returns the function x↦f(g(x)) where f and g are the two inputs.pt:a composição de _ com _
ca:composa _ _
Like the built-in REPEAT UNTIL block, except that the ending condition is not tested until the script has been run the first time. So the script is run at least once.pt:repete _ até que _ $loop-0.7
ca:repeteix _ fins _
Run the script repeatedly, as long as the given condition is true. Runs the script at least once before testing the condition.pt:repete _ enquanto _ $loop-0.7
ca:repeteix _ mentre _
Runs the script repeatedly, as long as the condition is true. Tests the condition before the first time the script is run. Like the built in REPEAT UNTIL except that in this block the condition must be true, not false.pt:enquanto _ , repete _ $loop-0.7
Runs the script the specified number of times, like the built-in REPEAT block, but this one provides the # variable that can be used inside the script. Try
REPEAT (200)
MOVE (#) STEPS
RIGHT 92
with the pen down.pt:repete _ vezes _ _ $loop-0.7
ca:repeteix _ _ _
The primitive FOR block uses an implicit step of ±1 depending on which of the starting and ending values is larger. This version allows you to provide an explicit step value. If the sign of the step input is incompatible with the ordering of the starting and ending values, the script will not be run at all.pt:para _ de _ com passo _ a _ _ $loop-0.7
ca:per _ = _ incrementant _ fins _ _
1110Provides LOOP as a function of one input that runs
the body of the LET with A set to the function input,
so the body can run itself recursively.
See COPY block in Variables for an example of use.pt:tendo _ o valor inicial _ , executa _ definido como _
ca:fes que _ sigui _ al _ _
new 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