{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.10.14","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kaggle":{"accelerator":"nvidiaTeslaT4","dataSources":[{"sourceId":51753,"databundleVersionId":5692552,"sourceType":"competition"},{"sourceId":123164466,"sourceType":"kernelVersion"}],"dockerImageVersionId":30786,"isInternetEnabled":true,"language":"python","sourceType":"notebook","isGpuEnabled":true}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"markdown","source":"# Introduction\n## imports","metadata":{}},{"cell_type":"code","source":"import os\nimport random\n\nimport numpy as np\nimport time\nimport matplotlib.pyplot as plt\n\nimport tensorflow as tf\nfrom tensorflow import keras\nfrom tensorflow.keras.models import Sequential\nfrom tensorflow.keras import layers\nfrom tensorflow.keras import callbacks\nfrom tensorflow.keras.preprocessing.image import ImageDataGenerator\nfrom tensorflow.keras import backend as K","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-11-19T16:35:04.46151Z","iopub.execute_input":"2024-11-19T16:35:04.461884Z","iopub.status.idle":"2024-11-19T16:35:15.45354Z","shell.execute_reply.started":"2024-11-19T16:35:04.461849Z","shell.execute_reply":"2024-11-19T16:35:15.452655Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"## Data Processing","metadata":{}},{"cell_type":"code","source":"class CFG:\n    base_dir = \"/kaggle/input/google-research-identify-contrails-reduce-global-warming/\"\n\n    train_path = os.path.join(base_dir, \"train\")\n    validation_path = os.path.join(base_dir, \"validation\")\n    test_path = os.path.join(base_dir, \"test\")","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-11-19T16:35:15.45491Z","iopub.execute_input":"2024-11-19T16:35:15.455342Z","iopub.status.idle":"2024-11-19T16:35:15.459659Z","shell.execute_reply.started":"2024-11-19T16:35:15.455316Z","shell.execute_reply":"2024-11-19T16:35:15.458866Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"def get_record_ids(path, observation_number):\n    record_ids = os.listdir(path)\n    \n    sample_record_ids = random.sample(record_ids, observation_number)\n\n    return sample_record_ids","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-11-19T16:35:15.460788Z","iopub.execute_input":"2024-11-19T16:35:15.461125Z","iopub.status.idle":"2024-11-19T16:35:15.47155Z","shell.execute_reply.started":"2024-11-19T16:35:15.461089Z","shell.execute_reply":"2024-11-19T16:35:15.470687Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"Ash color = [page 7](https://eumetrain.org/sites/default/files/2020-05/RGB_recipes.pdf)\n[https://user.eumetsat.int/resources/user-guides/ash-rgb-quick-guide](https://user.eumetsat.int/resources/user-guides/ash-rgb-quick-guide)","metadata":{},"attachments":{"7648f877-135e-4498-a33e-5af1b9b9ab9a.png":{"image/png":"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"},"0283cea4-687a-43d4-a4c0-d0d789e1b97f.png":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAA2oAAAHPCAYAAAAiZSl/AAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAP+lSURBVHhe7N0HXFVlHwfw3x1sQYaIgAMn7ol7z9S0nJmVmStnbq3c5kwzNfXV3DtNc5bmXrm3iXvgQAEVRDbce5/3uXBBxkURwS7y+346yT3r3nOecZ7/Gc9RCAlERERERERkMpSGf4mIiIiIiMhEMFAjIiIiIiIyMQzUiIiIiIiITAwDNSIiIiIiIhPDQI2IiIiIiMjEMFAjIiIiIiIyMQzUiIiIiIiITAwDNSIiIiIiIhPDQI2IiIiIiMjEMFAjIiIiIiIyMQzUiIiIiIiITAwDNSIiIiIiIhPDQI2IiIiIiMjEMFAjIiIiIiIyMQzUiIiIiIiITAwDNSIiIiIiIhPDQI2IiIiIiMjEMFAjIiIiIiIyMQzUiIiIiIiITAwDNSIiIiIiIhPDQI2IiIiIiMjEMFAjIiIiIiIyMQzUiIiIiIiITAwDNSIiIiIiIhPDQI2IiIiIiMjEMFAjIiIiIiIyMQzUiIiIiIiITAwDNSIiIiIiIhPDQI2IiIiIiMjEMFAjIiIiIiIyMQohGf4mIqKsLMwPd3yDEWOo1RUWjijg4QyLuI8ZLzoI930CEBH7fQqYO+RFwdzWsZMygjbYF7f9QpHaQUqhUEFtbg4rW0c4OeSAeTpOPepCfHDqwCGc9r4N32chiNSqYW2fG/mLlUf1+rVRLo+lYc6UXvn7FAqolGqozCxgndMJuewtoTJMIiIiSgsGakRE7wUNzo6qhOqTL70M1KzrY+blPRhQMHNCBO21KahZdgROxug/qVCw3x5cnVM/gwJDHfznf4D8ffYi2jAmdTIosnRE/lKV0eiTb/Bd/+YolHp8FUv35CQWjx+JaSsP4E6IzmiwpTBzQpmWfTF+yrdoVSx5APoGv0+hhFnO/ChXtxV6fPsdulV3YdBGRESvxVsfiYjeB5FHsXLdlYQgTU9E/INVK71lCPe+E9BGPsPds39j0XcfoVrzH3E6zDApBR0Cj01Dy4q10WvePtxOJUjTEzHPcGnTBLSr8QHGHgqUS6aT0CHmuQ/ObJ2FXg1qofPqO9AaJhEREaWGgRoR0XsgZM8K/OGTLCQTMbi4djlORBk+ZwdCiycHx+LrKadgbLPDzv6Edi2/x46HMYkCNAVU1s7w8CyDsiULIpeVUo6JJ4PAZ0cx6bOvseZ+ukO1BCLyFn77phfm32KoRkREr8ZAjYgoy3uGbSu24rGRtr/m9u9YtjvE8CkrU6P416tx6MgRHDEMhw8fwsEDe7F91Y/oVtkJqvjoSkTh3+ULsT/S8Dle+AlM7jEWBwPjAy4FzFzroP+iw7gbEIC71y7hovcd+D/2xqYxTZHfLGGF0D7agrFT9iHUMCalZL/v8GEcPnQQB/b+hfVzB6NRXrOE4E/3/CCWr72aDa50EhHR2+AzakREWZzuwQI0L9UHu0L01bkC5nlcYfvkEZ7FBm5KOLZZgWsbvoDzq07NRfnhwr7dOHz+Bh4+C0U0LGDnnA/FKtZFk4ZlkFttmC+R1J5RUwdewe7Nf+LEjQBEWbmieM0P8XGD4nB4owezkj8DZoZK487ixNgyMiRKSRewFp+W7oQNTwxBmJkXJlw4gVEl479Uh/sLPkTZPn8jOPaop4A6bxv8uncNunoae6pOBnszmqHO8AN4blil0vkLbLizCm1y6D+92e8L3tYFpdosh68hTZw7b8b95R/hNY/SERFRNsYrakREWZoWN39bjUOhhnNuCls0Hj0bnxWMDxd0CNq1HOtTvW1Piwc7RqGJZyFU/LAzBoyahOkzZ2P2zGmYMOIbdGpWHoWKf4TJh568/hktEYmrq3qiWrGy+LD7t/hh2gz8OH4ounxQBkWr9cWGu5l3DUnpVA5lCiSOBKMQEZ7oPKT2OlYv348X8aOUufDRlLn4ymiQpmeBMn3HoXMRK9h7VESDdj0wfPjHKJzOOxZt3PPCKeGIq4SDoyMPwERE9Eo8ThARZWWaS1i99hSiDAGI0r4hPm3fEl+080y4siPCj2Dl6itGb7ULP/EDWn8yGXvuRRjvVEPoEHZ7O0a37oDZ3q8KtASC9gzGh90W4cwzbdJ1CQ2enZmP7t3m4Ho6A53X0T06hpOJnvtSqF2R1/3lIU7nuwd7L758Lk3p0gJftc7z6oOgZR38eD4Qz+6exb4NCzFlaDuUy2mY9iY0D/Dn/N9x1bD7FGoPfPCRF8zjPhIRERnFQI2IKAuLOroC67zjAxAlnJp2RAtnC1T8rD3KxT9jJaJxfvUKnErRj3wgNk+fg/NhhqVti6F5n7H4ae58/G/WBPT7sBhyGI4SuqBDmDrhDzyL+2iEDs9vXMNjcw806D4aP82eibE9asM90XNeL/5ZipXn03tVTSDk/hns27sXe+OHXTvx5+Z1WDZzGFo3Gowd8fcoQgHras3QJPfLQ1z0v5dwLTo+TFPAvGw1VLUxfHwFC2vLNB4otbi7abgMktujvWFo17YNWn3YAF6FS6Hd0htxPXIqLFC08zR8X4c3PRIR0avxGTUioiwrFNu7FUfrpb4yTJBUbuiy+TqWtswh44YbmF6vHL79JzIuiFPlRbdtV7G4eewDVnGij2Fo2bqYcV0fPKng3uNP3FrY9OVzU7rHWNOxCvocUCCPe17kL/kppizrDy/DpaCkz6jprxQVRtdNx7CwZW5DcBOJY8Mqou5Pho4zFJZovsgXf3VzjJ36am/yHrWkFDaV8P2ug5hU8+W2Pl/yIfJ032HoCVIJly5b4LO0ZdJnxHSPcGTNZlxICPiSk/uoTie0KWcr/07H71M6ovpgGVhPaYH8xh5kIyIiSoRX1IiIsqpn27Fq6+O4IE1S5f0IHRsaghNVEXT4tBas4y9oaR9hy/LtSa+IKa1hbZkwAx6t7YePek/G8r8v4nG4HKV0xefrHyA44D6unz+GPWteBmnGqEt/jn7N4oM0PUtUrOmFnPEjhBbBgUEJvzfjKWBT+EOM3bwdExIFafqgKiIyKuG2R/18atXLXhgTaG5h4/iB6N+/fyrDIMzen/o1xdfSBeHk/75B99FbcPdNo08iIsp2GKgREWVJOvhuXIm/E7qaV6NQ689Qx9rwUVbvedt2RAO7+HBEh8C/l+P3xJ2KqEugScOCSLhDMuw29iwYiS7NKiCvU2541vgI3UbMwZbz/mm4aiSDpOJlUCzZlSKFnS1yJIqIoqMzIUJRmMG90SDM3XwWt6/8ibGNXZMd3JTIkcMGyoTfoUNYSEgGB4xK2HvWRbNmzQxDU3zQuCHq16qCMgUdYRH73QK6cB/s+bEDmvbbhoDX9s5CRETZGQM1IqKsSHsLa1cfRHxnj1BYwTZgByaMGoVRhmHM3H+hcXzZE6IIPYQVq68lClAsUGPEPAyqlDPZwUAGFJFPcOP4diyd0h9tvArBs/EwbLzxqjdny2AoZ04k74FfoVJDnShQS//d9mYoO2wf7ty9Be9Tu7H0u6bwiIt+5Epj8OjQ79h2+QWUqdxSaF6gANwSNlIgzOcW7qeI1FSwypEDdnZ2CUMOC1XKK29GqVC44xxs27EDO2KHnfh7917sP3ISl+48xu1dI1DLwfADRDRuLv8eP5/mZTUiIkodAzUioixI8+9qrD2Z6HY+EYJza6di0qRJiYZZ2Jm4S3wRhbOrVyBxfKB0aoQfD57E5qnd0bikE8yNRCVCFw6fvTPwecvB2PXcMNIIMzMjUVLaopw0MbNxRj6PwihZuTG6TNmO/YvaIZ8hChQxvtg9thVaTTxh9KXUFmUro1yiS3uaywdx0C/ZJS3zmph6IQjBwcGG4RmODC9t9L1ob8Yc7o3HYspXRV72xBlzE3t33TB8IiIiSomBGhFRlhOF4yvW4XJsN4JvRnNjHZbtDzN8MrDxxEffLsJubz888t6HNTNH4uu29VHWPUeiq2EC0TdX439b3uIZrQylRsHPF2BJL8+XwaXuOY5P7IzhfwcixV2F9o3QvJZtQtwowg9h0a/nDJ2LvAsqODs7JIpbdQh6air7koiITBEDNSKirCZ0L1ZsuJPwXjSFyg5uhYugSBHjQyEXm5eVvfYhNi//E4H6P59dxZEdG7Hy15mYNPo7zP8nAk4lGuCzgRPx68b9uPjwMS7OagbH+IVFBO7ffWD0fWz/CaUjGk9ZjMHlrF4GYDE3sfibkdgVZBgRT+mKtt1bwS3+3kwRhfMzumHwdkOPmcaEXMXRiwEpg770iLqKLTu9E+07JXK75TH8TURElBIDNSKiLCbwz5XY+jg+vFDAstY4HLl+EzdvGh+u/z3k5TvVZNjxdOdybPDVQdxZhT6t2qNzr8EYNXEavh0+E6eT3DdojVzOtjAzfIJCAXsHB9M6cOSoiVHzBqBcQu+VAjG3l2Dw+AMIMYyJ59ByNL5v+PL3i/BLmP9JTTQdsgj7r8f3RqlF8O1/sG5aTzQoXRXfbHvZq+arCQR578SaVauwKtGwctli/O/H4ehYsyFG/ROacKuqwqwkGn1Q2PCJiIgoJQZqRERZie4RNq78G8/iL/MobFH/8w7wSN6LRyLqMl+iUw3Ll1edQg5i5eobUFTsgb4JgYtAyInxaFiuHj6Vgduwof3RvU0NVOy6Af6G71LY1MBHzfOa3IHDpsYozOlfxtCzoiRicH3BIEw5rn/HQCKqIui16H/4rJD5y30ReQ97f/4aDUvkglUOBzjksIJj0dro+O1CHLgfkRBY6SksPVCqWE7Dp+Q0uLPhW3z15Zf4MtHQuavcx99Nx7qzAdAkrEwFl4+HoXe5t3/6jYiI3l8M1IiIshDtnd+w+kBIQgChdGyCz9u4vboyVxVEx86NE73PLAqnV6/EOVEQPebPxWdFLOICF6FDyJ1DWP/rTPw0Yw6WbD4J38i4b1KocqHB+FnoXewVEeF/xga1Rs/BN6UM2yGJqEv4ZeAMnE/2EJoq/6dYsmctvqnmnKQ3Sv22x4Q9x/OwGOgSR2d6CjO4VOmGOfv/wdwPHQwj00mhhEOVIVg+r2OiXiiJiIhS4mGCiCjL0ODyqjU4ERUfSaiQp8UXaOlk+JgqJfK0/gotcydEaoi5+huWHQyHyuMzLD+0Az9+4YU8CZekEpGBRQ6PBvhm2X5sGVwOlobRJidHHYyZ0wclEnoWEQg7/RMGzb1i+PySeaG2mH3oAg4sGISPyueB1csXrCWigLmTJ+p+Mgiztl/C9eOL0be6c5oPmgq531RqM5hbWMHGzh653AujXL12GDDzb5w99CM+SEgLIiIi4xQi/S+1ISKi94jm2XWcPHYWVx88RUikDhb2rihYuipqeXnA9r2NK7QIuXcJZ85dxq3HQQjTWsDBxRXu+YujolcxOPLuRCIi+o8wUCMiIiIiIjIxvPeCiIiIiIjIxDBQIyIiIiIiMjEM1IiIiIiIiEwMAzUiIiIiIiITw0CNiIiIiIjIxDBQIyIiIiIiMjEM1IiIiIiIiEwMAzUiIiIiIiITw0CNiIiIiIjIxDBQIyIiIiIiMjEM1IiIiIiIiEwMAzUiIiIiIiITw0CNiIiIiIjIxDBQIyIiIiIiMjEM1IiIiIiIiEwMAzUiIiIiIiITw0CNiIiIiIjIxDBQIyIiIiIiMjEM1IiIiIiIiEwMAzUiIiIiIiITw0CNiIiIiIjIxDBQIyIiIiIiMjEM1IiIiIiIiEwMAzUiIiIiIiITw0CNiIiIiIjIxDBQIyIiIiIiMjEM1IiIiIiIiEwMAzUiIiIiIiITw0CNiIiIiIjIxDBQIyIiIiIiMjEM1IiIiIiIiEwMAzUiIiIiIiITw0CNiIiIiIjIxDBQIyIiIiIiMjEM1IiIiIiIiEwMAzUiIiIiIiITw0CNiIiIiIjIxDBQIyIiIiIiMjEM1IiIiIiIiEwMAzUiIiIiIiITw0CNiIiIiIjIxDBQIyIiIiIiMjEM1IiIiIiIiEwMAzUiIiIiIiITw0CNiIiIiIjIxDBQIyIiIiIiMjEM1IiIiIiIiEwMAzUiIiIiIiITw0CNiIiIiIjIxDBQIyIiIiIiMjEM1IiIiIiIiEwMAzUiIiIiIiITw0CNiIiIiIjIxDBQIyIiIiIiMjEKIRn+NgkKhcLwFxERERERZWcmFqq8UyYZqGXnBKGMwXxE2Q3zPBHR22Ndalqye3rw1kciIiIiIiITw0CNiIiIiIjIxPDWxwyiCXmEOz7+CBNWcMpXCPkdzA1T6L+QbS6Va0Lw6I4P/MMErJzyoVB+BzDnZU+8XYeI6O29dV2qDYP/vXvwC4oArHMhX8F8cLTkdZH04q2PlH5R93Hwf4PQ2isfHBzywrNsRVQsVwIezg5wrfARBi48jgCtYd63osG/M1qidPFSaDTxJKINYym7isL9g//DoNZeyOfggLyeZVGxYjmU8HCGg2sFfDRwIY4byXja2wvQvkxxlKw1EgejDCOzGc2/M9CydHGUajQRJ1mQKDvReGPWx6VRvHhxI0MJlChZGmUrVEHtxm3QddhMbPEOhs6wKBG9Tgiubf8JvVtUQj57e7gWLoXyXl4oX7IgcuXMjeL1O2Pc+kt4zkJFb4hX1NIp6sZvGNCxLxafD4JWxruWjh4oVsgFNrKwPrp5Hfefx0AozJD3w2nYvHYgvGwNC6ZLNE59XxE1p15Dvn57cHVOfVgYppBx7+0ZmKgb+G1AR/RdfB5BMhZTWjrCo1ghuNjIw8Sjm7h+/zlihAJmeT/EtM1rMTBRxtNemYhq5UfjnGMXbPFZipaWhgnZSPSp71Gx5lRcy9cPe67OQf33qCDxihq9kuYMRlWsgUn/xhhGvJrCqhg6LfkbSzsWhMowjig7eOO69PlJzOz6OUZtuY1wuZjCLCfcixRBPgczRD9/hNs3H+B5jH6CJQq1nY2tq75G6Wx4/E0vXlGjN6Z79Ad6Ne+Mheeew7zQRxj/xyU88r+Ni6eO4dipf+Hz+Db2zWiHYpYaPPxrOD7pvxn+PItCb0v3CH/0ao7OC8/huXkhfDT+D1x65I/bF0/h2LFT+NfnMW7vm4F2xSyhefgXhn/SH5uZ8YgoCTPUnHAaPvfu4V6S4Q6uXzqKrQuGoqmHbEVG3MDqbwZixQPWIUSpirqMWe0/xNDNtxFhVRQfj/kd53yf4sGVMzh29DjOeN+Dv+8FbBz3MYpYRuHOH9+gw8hDCDUsTvQ6DNTelC4Am4YPwKrbGqiLdsGaw5swpnUpOCQ+5WiZD/UH/4a/ZjaDsyIGPmtGYPrxbHqvGWUQHQI2DceAVbehURdFlzWHsWlMa5RKmvGQr/5g/PbXTDRzViDGZw1GTD8O5jwiekkB85yuyJc/P/InGQqiWJka+KjndGzfOQl1bRXQBe7Gqk0PeAskkVFaXJ3TB6P3PYOwLI2+f/yDTePbo7yz2jA9jrlzWbQd+wd2z24h24TRuLpwIpb7sFRR2vDWxzekvTIFtSqOxAmNG77ccAkrWjsaphihOY8xlati4r8WKP/9HpyYUC1ZRw9aBN04igNH/8X9IA0scxVEuTr1UdXDNlkE/bpbH9O6Hh0eH1yKlcefwc6rI75unD/ZLS1hOL9uHv72UaJYy4FoW0pf2ejgf2Q5lv/zDAWa9UX7fLewY8tB3NW6oEy9pqhbLKdJRvvv3aVy7RVMqVURI09o4PblBlxa0Rqp5zwNzo+pjKoT/4VF+e+x58QEVJMZL/mtj82jbuHonkO4eP85YF8YlRs1QbX81oZ1pBT+6DyOHDmLm75BiBAWsHcrBq969VDBNek9HLpnx7BqySH452uCPh0rwTr4Fg7vPoTLD0OgdJLf07AhKrsn/Z70LJOYLvQeTu0/hAt3nyHK3BEe5euiQVUP2CbLnLz1kbKthFsfFaj/yx3s/cY99bpbexvT6pTAt8d0KJjK7faZWR+8pEPI7aPYdfA87oeYwblodTRpXB7OIYZ1utRFt0414JRsQ9JaHxAZk+a6NHQHepT8CIsfKlF62EGc/LEGUj9KSbJNONqrKiZddUbHFZew5lMnw4R44Xh0/giOnL0J36AICAt7uBXzQr16FZC0WOnw7NgqLDkUgPyyXfZpeQsEXt6LnUevwS/CCvkqNkTzOoWRwzB31KPT+Hv3KdwNUsCxWE188EE5uCSKJePLaED+Zuj7aXlYBF7G3p1Hcc0vAlb5KqJh8zoo/HJlOP33bpy6GwSFYzHU/OADlEu8ssTCH+H8kSM4e9MXQRECFvZuKOZVD/UquOJN7vzM9sc2ufEmxQR/UiIacXVyVWEm84zKo4/YF2kYnSqtCLhyWnj7p5wxyucvMaZlMWGnUsRuc/ygUDuKcp/NEseeaQ1z6kWJk9+VEmqoRMF++0XitWXUemJpH4m5Dc0FFJai1aoww8gYcW5UWWEGc9Fw5EzxSUELoTB8h8q9q9geYpjNxOh/3/tEc3WyqGom01jlIfq8PuMJbcAVcdrbP0kaa7wnCC8zCKXLZ2LWkp7CK5c6IS1j84yFu2g0dp8ISJxlJK3fQfHjJ2WFo/77E80fu4y5m6g9aLPw0RhmluK/x7zBDHFwZQ9RyUGV4nsajtkr/BN9T3qWiRMkTs3rLCom2xYo1MKpfCcx92SQYb44USe/E6XUMu8W7Cf2v343Zin67SZKVcxpMbKMmcwn5qL+Lw/l0ekVIg+LgUXVcl4zUW70eXkUeOld1AexwrzFyq+9RK4k36MUtsU/FXPWjYxdp5nXBOGd6LvetD4gMkafZ9IidPOXIrdS5mGbRmLu/VeWKAPZJrx6XtwOSpJpJa3wO/ij+KSsY2z78mV+1w8KYe5WWwza7CNboPE0wnuCV2y7rPHPe8W8jiWEnTJROVFYiPwtZ4vzoU/FkaktRUHLxNOUwr7iN2Kr78vfm1BGG/8s9s7rKErYKROVH4WwyN9SzD4fKp4emSpaFrRMMk1pX1F8s9U3aX2i9RMHf/xElHU0S1oO9YPCXLjVHiQ2J64kXkO/XHZmcltv2gnyXKxqnUNmPIWwb/ebeGEY+6a0jzaJbkX1AY9CWBVoIHpO+J9YsXq5+GXMl6JaHn3GVgo7r5HicMIXGA+wMmo9CV4ZqMnKwsJC2BRrJUbMWyaWzPhWDJx7Sq7RNL1vBfv5qtYih6zAFfbtxG/pzHjxlbFCZSbMVLKyrNZJjJy9VKxa/osY0bakrOhlJapyF19tTdSYifEWM+rbC6VMf5uizUX/KfPFirVrxYr5U0T/lp7CVr+M0lm0W+2fUFHHf48qt7twM7cU+ep1Fz/MWyFWLf1ZDPu4eNwyqgKi+18vNyQ9y8jDpDg5oaaw1x8orQuKhj1/EPNWrBYrF0wR/ZoVFTnkeKV9LTHpVHxeZqBG2VhaAzXtM3F0fB3hoC9XZsXF0KOJavl3VB/oj0UbvvSQjVaFUNmXFe2/nyWWrVomZn3XTpS1VwmVTQ5hLZdLGqi9eX1AZEza6tIocWRQMdmekvmwxo/iVtrjjhRivGeI+vZK2fayEUWb9xdT5q8Qa9euEPOn9BctPW1leZN517mdWJ1wNiM+UFMJJ5dcwsy6kGjcZ7L4dcUK8b9RrUUxaxmYKaxE6TpVRS4zF1Htq3GyLKwUCyd2FZWd9CdKVCJvtz8T2rAJZdTJRc5vLQo17iMm/7pCrPjfKNG6mHVcG7N0HVE1l5lwqfaVGCfL78qFE0XXyk5Cpb9wkbeb+DOh+MYI7xn148qhTVHRvP8UMX/FWrF2xXwxpX9L4Wkrt1O2TZ3brTZy4tU4BmomxqQTRHNVTKqiP9CpRclvT6QzSAkVe3oXFCqZ8S1L9xU7/JLm1Jg7q8WnBdRCoTAXFcacMZzJNBZgZdR6EnlloCYLnWU1Mely4nOrpuv9KtgacXVSldg0UJf8VpxIZ3QcXxlDpn++T9eKe4kPLNqHYslHjvKAoBQuX20TEYbREbt7ifwqeZDI3VosT37GUOsv1n2aJ3YZx883JSyT+HsKdNogEp24i/2exS0dYpdx7frnWy0Tc3mKqC4PSAqr8mLwvqfJzugFisPfVRLWsqFnU3eGuG7YVgZqlG0lBGpqUaBxbzFkyJCkw+ABotdXbUX9krLhpz+rLxuNZfrvSHKF/V3VBxEH+4uialm2bauLcScSn5wRIuT0JFFH36iV+T1xoJae+oDImLTVpUFiWUur2BPiub/ampB331yE2N0rv2zLyfW0Xi5SFqt14tM8Mr8rHcXnmxJKlSFQk+VK5SE6b3qcKL9HimPDSsQGkFDaibrTLiVq62mF/+q2IpcMolSFvhEHDBMSl1GPzpvE40S/IfLYMFFCHjP1wZVd3WniUqLjptZ/tWibS/42VSHxTfzKInaLXvlV8rtzi9bL7ycth/rvX/epyKM/aeL4uUjYnNfI7sc23rH9JkQEImN7ZlDAytomfc9mhe/Hms33oFW6oP0PE9HMJela1AU74qeRTWCHaPz722ocT+1dTxm1njegLvcR2hZP5V5kykQCEXEZDwora9i8bak1K4Mu37aHbHC9pHRHi2ZeUEOHoAf3EWR4zlnj+gGG/TAK308diU/zJftiZS7Urlkydpmw4GCk6PTbrDQ6DWoFt8SLKV3RpFH52GWePXyAF8mfp07zMhpc+G0tzoQrkKvVCIxu4JS0PCodUHv4YDS3VyDs2HpsuJEhLzQkeg9ocG/PfMyYMSPp8PNsLFj+Bw5cDYatZxP0/d9e7NN3iJWoYL2b+iASB1b9gTsaJfJ//gOGVU36bpscXkMxpXtRuUxirA/oHdOFIDhUK4/OCuSwtZP/Tynq3z8wc/p0TDcy/Lz+vKHnRw1cPxiGH0Z9j6kjP0XKYlUbNUvK3K4LQ3BwyldrqD07oPeHeRLldwtUqFoh9nlMhV1jfN2jTKLnS5Vw8vJCEXns1z31h3/yYqD2RIfeH0IGUgksKlRFhbiVofHXPVAm0cOqSicveMWtDP7xK9O44oNhP2DU91Mx8tN8ydrJSuSqXRNxmxMMI5tDRiTdh/RqCmtYWen/EIiMCJeHljenuXMe/z7TyQZ3FTSsZ28Ym5gSro0boqzMyJp7F3HhifFvyaj1pJ0CNoWKokDS3kfonVDAOi7jQURGIPwtk1JhXQyliiVt5ujlsLeDhf6G8qhIROrPYenHlW6FfiMmYGKXSgmVvTbMHzdO7cH6+RMx7vdriK2etRp5uElKYVkUpTyTf48Sjg45odIf1aKjUvRImeZldIE4e+Zm3HfeWIeBXbqgS/Jh0Abc1i+juY6LlyL1cxKRDHGKtR+Pn3/+OXaYMW0CBrevhNxmCijUuVFr+BZcurwLc3tVSxKk6b2T+kBzAyfPB0CryIEqdasZ6ZzBHJXq10LuxL+N9QG9a0pLWMoyoxcVYTw/hZ9cgu+HD8dwI8P3vx42nBDNgdKt+mHEhInoUimhVCHM/wZO7VmP+RPH4fdrcUGQVpOiVMG8WGmUStpLHfQNVX1nHSq3IiicrAApcsh2rP5nyzKaPE5TmBdD6ZQrg1XcylAk5cpk2yR2ZdDEryxHabTqNwITJnbBy80Jg/+NU9izfj4mjvsdcZsjl0m+OWQUA7U3oXJHATdLWTR0eHz/QYoDUVronj2NLZxK+9xwSaV7IGXuPMilrwDECwTFX9pIJqPWk3ZKWFvbGD1rRJlNBfcCbrCUO1/3+D4evGXlprCUFbWxkq+IT12hv8/hpeAr2DK9H9rVr4ii7vawtnOFZ9Um+LTPOCz+53GqJywUVjmMXv1TKGWDUP+HSPY9UpqX0QXA/6n+bKYOT85uworly7E8+bBiC84Hyl8nIhH8PFy/FBHJuty9djcMGDQIg+QweNgozPj9JC5s+QblLJ7gn2nt8UG/bXicWsHO7PpA6w+/ALkWZU7kcjbTj0lB5ZIHTolPGrI+oHfOFnnzOcrSpMOzB/cQbCTjW5Rrj6HffotvE4bh6Nkgr9EXyAdf2YLp/dqhfsWicLe3hp2rJ6o2+RR9xi3GP6kWRoUsf7bJri6/pDAzh0WKMhd/nE9JYW0H29RXBvOUK0tlbcG4smU6+rWrj4pF3WEv1+vqWRVNPu2DcYv/Sb1uIaOMVJuUOitU8ioVe5vGi/OncOm1txPKg8b6vmjUqjtGzNuPB/qzCLLgqGXOFtExiE7eSo0XHYno2DMOspDpW+fGvO16jC6jgfYVBSihHU/vnFUlL+jflqB7cR6nXp/xoHuyHn0btUL3EfOwPzbjJZb2hNQ92oyeNaqgzfB52HT4GoKtC6N68w7oMXQC5q3fj8OT68F4U0pKT4ZJ6zIKFdSxRztz1P7hGC5fvvyK4TwWdXjFazSIsj0VXJvPwG9TG8NJEQ7vhZ3x+azLSF7TvJv6QJZtfWNRyGNb/KX9ZHTR0YhJPIn1Ab1z5qhUpRysFALR+i71QwyjE7Gu3AUTp07F1IRhMgY1zpus4a3Do809UaNKGwyftwmHrwXDunB1NO/QA0MnzMP6/YcxuV6qpQoqVQY241Wqtw8KdI+wuWcNVGkzHPM2Hca1YGsUrt4cHXoMxYR567H/8GS8YnPICAZqb0SFwi2aoqyZApqbW/D7qdfcPqHzw9bVa3Fg61L8su06lPI4pS5QAO4qBXTPb+Dq/eQN6DjRV67gplbfaY8b8ucxfq9h+tajjC3U+sNldHTym84k3VM8eZZa1Ef/JVXhFmha1gwKzU1s+f0UXp3zdPDbuhprD2zF0l+24bo+46VLGHaNG4AlV8JhWboH1l72h9/Nszi4/TcsnD4KfT6pDUdNiCHmT3l1LFOpZJ5211/d1sL3SRSKlCqFUqkOJZDf3ng5IqJ4ahTvvQBTmztDqXuOg2O/xk8XE4dq76g+MCuEwvn13WQ9w51bAbI2Syn89i08SnzYY31A75wSuT9sjbp2sh329C8sWuuT4lbCNAnbhXEDluBKuCVK91iLy/5+uHn2ILb/thDTR/XBJ7UdoQkxlKbYfjVMW9iucRiw5ArCLUujx9rL8Pe7ibMHt+O3hdMxqs8nqO2oQRbaHJPAQO0NqUt2Rrf6drEN5iXf/YSzYYYJKejwZOd4TNsVDJ0yN1p0aQdXubeVLvVQt7RaLn8W61aeNdLgfo59KzbjjkYBK6+6qJ7abY3pWo8Ctrb6txbqEOT7MMWleq3Pfhy+yZuGTZK6JDp3qw87hQY3l3yHn1LPeNA92Ynx03bJ9JUHkhZd0E6f8dJDcwenzvrJg48ZqnYfhU9KJHuBuvYB9h24GnsLsNBq03UrcPrZonb9yrBSaHFv02Js098qlYzGeypq2tvBpUgLzPJmviZ6LVVBdJn1A5o4KiFCT2LawHm4Gl903lV9oMyLxo3Kym+JwclNG3AreetX54tNvx9EaJJGHusDeveU7h0xuFNRmInn2DO+D+Zffs3Je1kqQkKT3naruXMKZ/1kJjeriu6jPkEJfccdiWgf7MOB2EIooNWaer7V4M6ps4jbnO4Y9UmJZC+Z1+LBvgNxdYrQ6h+TozRIZwsuG1N5oMvkIagq450Xx8ajZcvvsP5SYLIzKaG4un4QWnZajJsxCjjU/x5j2znH7Wx1KXTv3wLOimhcnNEJXRecTehhT39v/pFpnfD1srvQqvOjQ//PkD+1FErXelQoUKk83FQCEftnY9yf9xNubQm/sx0ju0zGPxE8xWGaVPCQ6TMkLuNhfMuW+G79JQQma8SEXl2PQS07YfHNGCgc6uP7se1SdAiQZkpnuOY2l+G9Bt57duBm4ouwodexceinGHswLO7MeXQkIlO2jTKREgU+H4iOBdTQPVqHfh3GYue9lz8wymczBn85GSeCQxHuWgeNU3RiQETGqAp3x88j6yCnUofgw5MwdMmduOPbO6sP1CjZbQBa5lYg/J+J+PLb7fCJ/y7NI+z7oRO+/yso2ZU21gf0X7BF/fH/Q78y1hD+f2NQ4yYYsPQYfFPEa1o8v/onZnSvixbT/oU8OkNlZhH7bJnS2RW5zRX6MwnYs+Nmkg62Qq9vxNBPx+JgWFy7LDoy0ugVZtOhhLNrbsRtzh7sSFpJ4PrGofh07EHEbU40It9toyHrMnTTbzJM8CcZoRF313UVJWzi3vauUNmJglWaiNZfdBVdP28l6hZ3MrxdXiFylOsjtjxM/mKMx2LH0CrCQf8meYVK2OYtLapUryxK5LEWSv1LjdUuov6ko+Lla4dTef/ZG69Hirksfq6vf2+NnK60EW4lvUSVCoWEo5lCqN2ail7tiwm10feoqYR79x0p371morJGPnpzmrvrRNcSNkLWg7FpblewimjS+gvRtevnolXd4sJJpmNsnsxRTvTZkvSltvHvSlG6dBHbjLy/JGxde2Er841ZrenituE9Q4E7+wpPC33+UgpbD/ldH7cSLRpWFoXt1TJ/5RbVPq4j3FUQ6lLfiZOG97u99ntWtxbW8nvM684U9ww/MD3L6AX9M0k0yCN/i36bLXKJopWqi+qViolc+t8sy5+5R1ux+OrLF8/xPWqUbaX1hdd6kefE+Cr6F93KMpmnjVhpOIa9q/pA/74l381fi5L6B4AUCmGZ21N46Y9trvpjm43wLFNYyMagMKsySVxJ9E60N60PiIx507pUc3+bGFrDWbad4tp9Zo7FRI0PWovPunQVndp9KGqXzC0sZT6OPTYr7USJDj+JQ4/jM26g2NnXU1jIZRVKW+Eh25Ift2ohGlYuLOzVsl2Wu5r4uI67UEEtSn130vD+3vj3qCmFS5eX7z2NF/FXN+GqlOWj3GhxPtmrb7UPfxH1zeV32bQRawzNvFeW0Yi/RDdXpYBZOTE65crEL/X17961EW3iVxa4U/T1tJBlUCGUth6iSpOPRasWDUXlwvZy/6hF7mofizruKgF1KfFdfCXxGtn92Jbec+3ZnAoeHRbhn4OLMaBpcdgrQ3D31G5sXr0US9dswaFrgRA5PdFs8HL8c2gePnZPtpuVedBs+n6c2jYVPZqWR65IH1w4440AtQdqffo9Fh08j90jasBYp/tJpGc96lIYtGk/lg9vi6qFrBB8619cfWSGMh0nYsvRDehSmE95mjKVRwcs+ucgFg9oiuL2SoTcPYXdm1dj6dI12HLoGgJFTng2G4zl/xzCvI/d3/qSuUPTWdizfSq61CsO26CLOLBjF/65Fo68TYdg0aELOLS8H+o4KKG9uQd/X3/39zHY1xyBHaf2YM6A1qhWQI0A7zM4c9kP6gLV0WbIrzhwYj26FU/e3TARvZJFBQyd2R9lZOtR57cVI7/fDP3dhO+uPlDCrdV8HD7wKwa0rIg82oe4dO4anjvWRM+5e7B7WFl5FJbMLWK7IY/H+oD+C6p8LTH90EXs/99AtCyXG6qgmzi2azPWLluKVRv/wpErT6C1K4Bq7b/Dkn+u4cK6IaiT0P+AA5rO2oPtU7ugXnFbBF08gB27/sG18LxoOmQRDl04hOX96sBBqcXNPX/jPzjMvhmHppi1ZzumdqmH4rZBuHhgB3bJbQ7P2xRDFh3ChUPL0a+OA5Tam9jz93XDQvQqCn20ZvjbJCgUCn3obPiUNUQ9uY7z57xx1/8FopTWcMpfClWqlIJL4iMIvVNZMR+9sagnuH7+HLzv+uNFlBLWTvlRqkoVlGLGy5ayRZ4ngg5+//sABfrug+qjZXi8tTNyGqYQZYS3q0u1CLn/L85dvIEHgRGAtSPy5C2GCpU84cRzBOmS3Y9tDNTovcR8RNkN8zy9HzTwntkOnf+IRoWvpmF+99LJ3hMVgm1diqPN8gAUHXYYF6dVB9u/lJFYl5qW7J4evPWRiIiITIQa7q7muHN8J5ZNmoo/7iV+RYAGD7Z9i1HrH0NnVgQtWlVikEZE7zVeUaP3EvMRZTfM8/TeCD+JcfWbYMKpECjsPFC5ViUUzCkQdOccjp3xwQthh0rDNmH35AZw5OlmymCsS01Ldk8PBmr0XmI+ouyGeZ7eJ7qgM1g+YTx+Wbcfl/3CoZVZW6GygVu5xvhs4DiM6FTu9R1uEaUD61LTwkDNxLaeBYQyAvMRZTfM8/R+0iDE/xGehAE5crshdw6+A40yF+tS08JAzcS2ngWEMgLzEWU3zPNERG+Pdalpye7pwbu7iYiIiIiITAwDNSIiIiIiIhPDQI3ov6B7jjtnT+KCT4hhRCaIDsTdy2dx9uJV3AuMMoyMEx14F5fPnsXFq/cQGKUzjCVjQu9dxMkztxHE3URERETvEAO1DKC9PhdtShdHyVojcTBpe5jICC18VnZFzeqdsPi2YdRr6J6sRdeyxVGi0kDDGEl7Gwval0HxktXx7b7EGS8a11f3gJd7HhQu4wWv8iVRuIJhuejrWN3DC+55CqOMlxfKlyyMCgP3x00joxT3VuCrmtXRSSaW1jCOiIiIKLMxUMsAIuop7t24juu3HiOEz5/Sa+gerMbgb7dD02IkRtS3NYx9DU0Q7l+XeezGQ8MIvSg89ZHjrt/E40QZT+e7DIP6LsHZpxpYupZC1eqVUb5+df0U+C4bhL5LzuKpxhKupaqieuXyqF+9VNyCZJRNrW8xppUSu0YMwFIfhmpERET0bjBQI3qngvDX+LHY9rw0eo/sCLe3KYEKN7QYOR8Lf52JrhXMDCOB6AuncSFUQOX+JdZ6X8aJY6dwZvmX+im4cPoCQoUK7l+uhfflEzh26gyWf+katyAZp3RB+5F9USHsb4wfswVPeAskERERvQMM1IjeIc3l+Zi09gFsGvZGzwrmhrHppLRH+Vbd0KN7J9QroDKMBHRhoQgXcnKhMihnZxgZS4ew0HAIWewLlSmHJJPoldSlv0bfprZ4/PsUzLukMYwlIiIiyjx8j1oG0Fwah6pe43HBsQu2+CzFB8/PYtffx3E72AzOxaqhUcNycHlFm1wXeg+n9h/ChbvPEGXuCI/yddGgqgdsXxFGhz86jyNHzuKmbxAihAXs3YrBq149VHC1NMwRR/fsGFYtOYSA/M3Q99PysAi8jL07j+KaXwSs8lVEw+Z1UDiHYeaoRzj9926cuhsEhWMx1PzgA5RzyZovFzXNfBSGv78uiRZLwtB61XVs+MzJMD6ZMB8c23sEl+7JdMhdBvWb1UWR8Plo4tEP+83bQheyMW4+3TMcW7UEhx5boHSbfvgw1ymsWnwQ9y//jsmrL0BT6GMM61oVtmpXVCwncPHcQ1z+fTJWX9Cg0MfD0LWqLdTu9dH9i2pwjM9rulDcO7Ufhy7cxbMoczh6lEfdBlXhkTwz6vxxZPly/POsAJr1bY98t3Zgy8G70LqUQb2mdVEsZ6L507xOw/b450OTPh1RyToYtw7vxqHLDxGidELhyg3RsLI7rA2zpxB+Hyf2/YN/7/ohVJ0LhSrWRaNqBWBjmJyUDqH3TmH/oQu4+ywK5o4eKF+3Aap62KZ69ur5H1+g+CfroO68CVeXfoQ03rT6zvDdP0REb491qWnJ9ukhN96kmOBPeq2Yi2NFRTMIpctn4uf5nURJO2XsdsQNCmGZr4EYvtVHxBjmfylInJrXWVTMpRaKhPnloFALp/KdxNyTQYb5XtL6HRQ/flJWOJopEn1H3KAwdxO1B20WPhrDzJLGe4Lwkr/NvPHPYu+8jqKE/G0vv0shLPK3FLPPh4qnR6aKlgUtk0xT2lcU32z1FVrDurIS/TaYnMB1okMuuf/tW4tVgYZxSYSIi4u7i6p5zJOkgzp3TTFk2RhR31ymcY62hnkljbeY4GUmoHQSnTZHCM2ViaKKTOu45RINZlXFoAGVhVny8XIwqzZFXDPkl6BT80TnirmEWtaJL+eR3+9UXnSae1Lm1kRizolRZeV3mzcUI2d+IgpaxOdHlXDvut0w0xuuM357zBuIGQdXih6VHIQq8XIKC+HecIzY658sR2ofi32T24myTmbJypGZyF21t1hzLdIwo0HQKTGvc0WRS520DCnUTqJ8p7nCSLGL83y96OCoFEqH1mJlgOmVCv02EBHR22Fdalqye3qY3NZnxQSJD9QUanNhrjYTzpU7iTFzl4uVi6aKvg0LCEvZ2FRYVxAjjoYaltALFScn1BT2Sv20gqJhzx/EvBWrxcoFU0S/ZkVFDjleaV9LTDoVZphfivEWM+rbC6Vs6NoUbS76T5kvVqxdK1bMnyL6t/QUtnIZKJ1Fu9X+CcFVfKCmcnIRucysRaHGfcTkX1eIFf8bJVoXs5YNW4WwKl1HVM1lJlyqfSXGzVshVi6cKLpWdoptJKvydhN/vjCsLAsxxXz0YuNnIpdSBu6N5gnfFO18rbi/uoPIK4MHhcpJVPxslPhl+Sqx9OfhonWpnEJlbiHM9fnoFYGaiHgoLh49IvZPaiRyyHnNKg4Umw4fEUeOXhS3bl0UR4/sF5Ma5ZBpbiYqDtwkDh85Io5efCjkkiL05ARR014pgxtrUbBhT/GDzAerVy4QU/o1E0VzyPFKe1Fr0imRkBvjAzWFubCwsBHFWo0Q85YtETO+HSjmnoqKneWN1xm/Parcwt3NXFjmqye6/zBPrFi1VPw87GNR3FZ/AkQlCnT/S7zMki/E4e8qChv9vrHIK+p0GyfmLl8plsj91ra0LCsKhTD37Cd2xwdfoSfFhJpxZci6YEPRU7/+1SvFgin9RLOiOeR4pbCvNUkkLnYJtH5iYTNZZpQOot1ao5H2f4qNCyKit8e61LQwUDMxWTlQg2zkOTf9RVzWt3zjaR6K3zsVFGrZYMzR4Bdxx3D1IubyFFHdWjbKrcqLwfueJr1qpQ2Ujc9KwlouY1N3hrhuWCZidy+RXyUDuNytxfL7ya8q+It1n+aJbWg6fr4ptvGtFx+o6Ru4Hp03iceJFos8NkyUUMf9bru608SlRBcetP6rRdtcsmGsKiS+OZDsikQWYHr5KEoc7F9YqKEWJYYfl5+SCdsv+hVSy+Alp6g9+ZwM4xMJOiJGeNnEXi16ZaBmELb+E2EnAxfzOj+Lu0mySZhY/4mdXI+5qPPz3Zd5LuaymFJdBiAKK1F+8D7xNGlmFIGHvxOV9HnVpq6YEZ8Z4wM1GfBYVpskLie/XJyedcZvj9xOVYFOYkOSaFYrHi5uKRz0JzBcu4o/DZuruTJV1LCS6zErJL7ccF8Y1hQnaL8YUMJM/gYb0WjuPbmGGHF5SvXYcmVVfrDYl/RHyWJ3WHxXSf+bbUTdGdeTritWjDgzsqwwk2UpX689wtRKBRsXRERvj3Wpacnu6ZHa4xiUDgqzCug7rTdKJX5MTOWOtj8MRG0rIOyf9dh4V9+9twYXfluLM+EK5Go1AqMbOCV9LkbpgNrDB6O5vQJhx9Zjw424LsE1rh9g2A+j8P3Ukfg0X7KkU+ZC7ZolodZ3GBEcjBjD6ARqT3To/SHyJFrMokJVVNA/J6SwQ+Ove6CMhWGCpHTyglcRFaB7Cn9/dkn+1nTPcNn7AbQKNQoWLYbkjyxGHV2Prfc0Mrt0wIgBFZI+V2VfC9+P+QRuL/sLyVCaC79h7ZlwKHK1wojRDeCUNDPCofZwDG5uD0XYMazfcMMwPp4a5T5qi+LJHmV8u3WaoXSnQWiVpEtMJVybNEJ5+T26Zw/x4IW+60UNrm7YgNMRgHW9IZjYJh+S7CL7OhgybRJGTJiMLhXlHtdcwG9rzyBckQutRoxGg6Q/Sha72hg+uDnsFWE4tn4DDMUuETWKFCsIc4UW/lcu4TF7fyQiIqJMlLSlQm9F5VEHDT1Tdr6hzFsbNYuoIWK8cfZ8lGxpBuLsmZuymSndWIeBXbqgS/Jh0AbcVsjpmuu4eClSPydylG6FfiMmYGKXSoiPqbRh/rhxag/Wz5+Icb9fi3shr1YTt+5EFObFULpU8vDAClb6oFLlhiKFk3XRoMgBayv9D9BCwzjt7Wnu4/4jHYTCHi55kneHoYXP2Yvw0ypgWaEGqhnpLSNHrbqoZKlPj4ymQ+DZM7gZlxmxbqCRvNhlEDbEZUZcv3hJP+NLChsUKlogaYD01uu0RNFSnjIsSkrp6ICcKv0y0YiKfb93GM6fvybXoIZnjdpwTVGbqZCvxTBMHNkfn1XPA/mjcCbuR8liN9DIb+qCQRtuI/ZXXb8IQ7FLwtLFBQ7ye3SPHuBB8kJGRERElIEYqGUghVNu5DZ21UOZC85OsvknIvA8MEy28gLg/1QLIRu0T85uworly7E8+bBiC84H6uQykQh+Hm5YkRR8BVum90O7+hVR1N0e1nau8KzaBJ/2GYfF/zyWazROYW0H29Q6cFSYwdwiZVbQN1gpg4gQvAjT3ylojRw5ku9ZLZ4+CZT5QQHbXE5I2m+ngbULXOwzo7jqEOD/FFr503RPzmLTCiN5cfkKbDkfKOcUiAx+bljOQGkNa5vk2/OW61RYIYeNkW1VKKGI/Sr9LdvyH10QngbGxO43x9zOr63MdAH+eBr3o3B20wojv2k5Vmw5j7hiF4zExS6ewtYW1vI36MJkevKKGhEREWUiBmoZSROT8pZDPRGNqGh9I10JS/0lLIUK6tiAzhy1fziGy5cvv2I4j0UdHGNXo3u0GT1rVEGb4fOw6fA1BFsXRvXmHdBj6ATMW78fhyfXw8vXHiejUjGx/1NKKGODDB10+iAjCaUMlM1iA+PoqOi4USnIsD7FchlBAVVcZoR57R9wzGgefDmcX9Qhdt6XFLG/O6nMWKcxKn22jqWJSW2/vaRQqeOu/JnXxg/HjP+WhOH8IhiKXVK6uOhMIRMzLj2JiIiIMgfb7hlI++ge7hmL1KKu4Zr+2TRVXhQsaBF7q2F+d0vZGNXC90kUipQqhVKpDiWQ317fvAzDrnEDsORKOCxL98Day/7wu3kWB7f/hoXTR6HPJ7XhqAmRzXk9YfiXTIbKDvb65wFFGEJeJE8dNTwKFYCZQoeQ29dxz8itprpAH9zXX+rJcCq45XeH/q5Kre8TRBUxlgdfDiXy2xuWe5XMWKcRSifkc9e/90yLe7fuGD1JEnV4Etq3+Ry9ZhzA8zz54R73o/AkqojR35IwlMiP2GKXjAh5gVCZfIocOZGTgRoRERFlIgZqGUjnvxeb9yW7jQs6+G9fjZ3+Oqhc6qCRvlMD2KJ2/cqwUsgG5qbF2BaQsgGu8Z6KmvZ2cCnSArO8NXLEHZw66yebpGao2n0UPimR7MW82gfYd+Bq7LNpQqtN8Ywa/cfUBeGRVwWFLhiPfJ/LXJGUY4PGqCKDCM25DVijf44xCS18NmzE8ajMCb9ta9dHZSsFtPc2YfG2gBS/TWZGTK1pDzuXImgxy9sw8tUyY50pWaJa3aqwkeXowd8bcTTUMDpBKA7+thibN6/Hjpsa2OSsjfqVraDQ3sOmxduQsthp4D21JuztXFCkxSzoi11yYb6PEKhTQJm3IAqmdisxERERUQZgoJaRtPexok9XzD0T3xDXwv/wFHQatAF+uhyo0qc/Pojtzk+JAp8PRMcCaugerUO/DmOx897LxnmUz2YM/nIyTgSHIty1DhrrOyhROsM1tzlkUx7ee3bgZuK2fOh1bBz6KcYeDIu7khYdicgUjVD6b9mibLlCUMk8cevKlRRXf1QeX2Lgp/mgirmAGZ17Y9WV+KgjGg92jESncQdjr+RkBmWBzzGwYwGodY+wrl8HjN15DwnZK8oHmwd/icknghEa7oo6jT0NE14tM9aZkhKu7fvhMxkxaW8vRu+ei3Ex2DAJkbi1fhCGrLgHnWU5dOlRF5bKAvh8YEcUUOvwaF0/dBi7Ey+LXRR8Ng/Gl5NPIDg0HK51GiNlv0DRuHLlFjRCBY+y5ZL1ZElERESUsdjUyEDqovVQS/kn+lcviELlq6Jq2QIo0mA09viZoUjHeVg+tOzLnuwcW+Kn1eNR30WBJwcn4kPPvCjmVQM1vDyRt3hbzDkXCrVHG8xaNBCl9Asp86D9gK9QzELgyY6+qFy8Kj5o1RotG1VBkXyl8cncu/BsWQfuKkD3xB9+vKRmYsxRrk51uKi08D17KuXtjUpHtPxpGYZVzonIK8vQubwHinpVR5WSBWS6TsMpdV7k1fdikSn0370a4+u7QPHkICZ+KPNgMS/UqOEFz7zF0XbOOYSqPdBm1iIMjM2MaZEZ6zQiZzNMXTEW9Zy1uLn2a3gVKIBy1Wqgsmd+lO64GFdiXNBo0mIMrxTX46ljy5+wenx9uCie4ODED+VvKQavGjXgJctf8bZzcC5UDY82s7BoYKkUvU5CBp2nz96DVumE6nUrpHjFAhEREVFGYqCWgRROTTBn7yaMa+sJ5f1/ceFmGBzKfohv5u/HPyu/RLFkLTv7miOw49QezBnQGtUKqBHgfQZnLvtBXaA62gz5FQdOrEe34i8Xcmg6C3u2T0WXesVhG3QRB3bswj/XwpG36RAsOnQBh5b3Qx0HJbQ39+Dv64zUTI1l3dZomkcFzaX92Oef8pKn0rEBJu8/gc2Tu6BeUUs89T4H7wBrlG3zPdbu+QmNbDPxoSj7mhix4xT2zBmA1tUKQB3gjTNnLsNPXQDV2wzBrwdOYH234m8WnGTGOo2wrzUKO07uwE+9mqGcYzjunD+Df/3NUbRBN0zdfhzbByd+L509ao7YgVN75mBA62oooA6A95kzuOynRoHqbTDk1wM4sb4bEhW7BLon+7DvfAwULk3RumGSN90RERERZTiF/q3Xhr9NgkKh0L+C3PCJKH1MMx9F4sjgcmgwyxcN5l3Hzt7uPFOSZejgt+RjePb4G7n77cHFX+rByOvu/lOsO4mI3h7rUtOS3dOD7USid8YSNXr1RE2bCBxeswY3+CLxrEN7F+tW70eoVVX06F3b5II0IiIiev8wUCN6h1TFemDkFx7QnFyCX48aeaMymaSo0wux+GgU8n02Aj1LGOm3n4iIiCiDMVAjeqds0XD0BLR2voPl09bgPnvnNH36niunLcF1h48wfkxT5DSMJiIiIspMfEaN3kumnY90uL+6A2p0PYvmW85hYfN0vvCZ3omQvf1QqfkfKPXrcWzs4gFTvZ7GupOI6O2xLjUt2T09TDJQIyIiIiIiYqBmQngmgzIC8xFlN8zzxDyQtTH9TAPTwbRk9/TgM2pEREREREQmhoEaERERERGRiWGgRkREREREZGIYqBEREREREZkYBmrvgvcsoHRxoLiRoUQJOa0sUKU20KYrMHMLEPwOXq6lewJ0ld9bohLwV6RhJCXRurRMI7mP1gQYRhhovIGP9dOMpGdxmZ4l5bQKVYDGbYBhM2X6BxsWfJ0o4KeWQFmZD568Ig+EXAdmDwVa1AXKy99XuQ7wxRDgTzk+Pf7dAHzdSq6nPOAl8+Hnw4B9dw0TM5sWuPpLXPko2wUISLTdmVVuLvwElJHLrpVl4FUycr9E+wKLRsg0k2lVvhxQvRHQZ4r8jueGGSgz6B5vRO/qJVGiylDsksWL3ichuP7XbAzt1AJ1ZRktW74y6jT/AkNm/YnroYZZKJNEYe/waihZvCRqjzqkP3KlIhRnZrZDpRLF5aHRC5/MOiNTjd6lKHm8aymPd11fd7wj0yVMjAn+pLd3eqQQZnK79Nv22kEhRLEvhbijMSycSbSPhGhoLoQihxBrwwwj3x8Zko/KmckVyX00x9cwwiDmtBBl9NOSp10qg1UxuY/vGBZ+hcMjhMgh09+8oRCPtIaRydxcKURxmWb69SpUQtjZC2Eh/439LMd/tUqIKMO8ryXz2PpuQljL79TnOwtb+VvVcj1yXSonIcYclPnEMGumiRHi/Oi48mHeQAjfRF+YGeXm+WEhvPT7T6brXFkGjMrg/fLiuCxreeKWj08zM2Xc77aWeWPVLcOMb+e9rDvfhvaeWNXOTajkflHYdxQb3r9qLoVskweiboqVXxaX1SXkNiuEytJO2NtZCJXhc46SX4lV19NcEZqMrJN+EWLT545CCaXI0/VP+cmYEHH6pyYij0ohoLQTFfpvF76Z3KzJKO9NOZLHuxHyeKeQx7uGqR7vTF92P7bxitq7ZFYTOO0D3LuXdLhzHTi6FRjaFLCU891YDQxcoX8vMpk0M2DC6ZTpee8OcOkosGAo4CETNOIG8M1A4EFqCSrHH50MtPsRCNXXSamIvgR06g1cCwdqDgLOPQaCg+TgCyztCeSU41f0AqZfNCzwGjf+B/RcJtfrBkzaDQS+AF7IdS38SubDQGByV2B3Wq8GZqKMKjeBMk3atAPOvuZ0e4buF5kmY+Vy+/2BfC3jrsjp0+zZFWCY3K5ImTf6dAOuag3zU8bQ4u6ybzBk0yP9NVt6r0Tj0vRO6L3qGsKdamLQ2nN4HByMIDn4nliKnpVyIvzKCvTqPB0XNYZF6B0LxZkZbdHy2z3wEzlRZchG7JzZAm4qw2TKdDp5vJssj3c/yuPdK1oVlBUYAjaTYYI/6e3FXxkwry/Ew1edio8RYka9uDPvlvJfn0y8nMEraq/32itqctovDw0jU3F1hhC2CrmfLYWY5WMYmYg2QK7/MzmPUgilHPRpn9oVtd09hVDJ6Xk6COGXfLpGiPlN9adehPDoI0SkYXSqZJr39pDboBKi0x+GcfFkPpxeR/4W+bvrz4xddeZJwxW1ty438vPxOUKUtJXz6Pez/kpZalfUMni/RO4Uwl2uS+UuxOYgw0gDrcwPjfRX92ReGnPeMDL93su6M51irs0VHzgphdrBSdjLMsEralmFVvjumC4GDxgsfvr7kfEL1xG7Rc/8KgFlHtHhN78U82juzhdN7ZWyCHuIPvteWxGalKyTfq+6opb4SpqjqDn6gHj6qurbBGXtcqQVAfJ495k83inl8U4pj3fgFbUsjVfUTIoa+LhZ7D+I0V8xiIkbnYQOuHcCWLkAmDkbWLEV8HndXd9hwDE534JfgF/XATdM4CpJdlH0Y6CMTFAh0/LWHcNIg4AdQO2yQP/fAFV5YP4oWZ8apqWgAY7IdNfKIluvHeCSvOiqgJaGvPPoKvDsNZdjo44Bfz2Qi+UDvvrQMDKeXEmXroCt/PPYJpnfTP2axCvKjS4A+LY2UKc/cF3uo+7zgUap7uSM3y/hvsBTOZ+qCFDRzjDSQOkKVMov/5DT7/rEjaO3F+2NX3qPwp4XRdB9Si948ix+FqLDkxNrMWf2HPx24qnRi+Oaa0dw4rEWypz10K6lS4oH7VX5W6JZBVlWtY9w1fuZYSy9Gy+vpPkjF+r/sB1//lAPTmxpvgOytMjj3Q55vCsrj3e/yeNdeXm8G/Wq4x1lCSw+pubRY9mol/8qZaPOIVkL4/lp2XisDBSpAXTuDQweKD+3ksFAQeDLeXK6Yb7ELi0BqslGYi05X+8BQK+OQKliwPBdseWaMpnmEfAkNkFlejrEjYv39BxwXgZgHScD52SA0FGmY6pkw2OADA6O7wNG1jWMSyZIZoDYr7IELF5TtO+cAmRjB9YVgMoWhpGJ2FcBisvvjL4InAg3jDRhqZUb8RQ4cB4oLfP9drm/F8p/jWxugozeL9buQC75e7S3gAvJTqjoAoGrMn/o84a7W9w4ektRuDCjJ8YfikCJfgswqV4OKAxT6P2gLjEAm84cx74tI1HXyjAyMV0Qnr+QlYFCCUurVxV2yliJgjRFHjT58S9sHVkD9oaplNlknpfHu3PyeKeRx7vJ8nh3TB7vCrIIZHkM1ExJoGysj1ohG/eyaVG4MVBSNgjjhckGZIsmwArZ6MzXAPhBBmarVwJT+gEFo4BV/YGWssGfuO34YA3wYS/g1BOgwmfAL8uBpT/L+ZyBWT2Bo8au2FGG0TfEfxwF3JbBmFlhoGlJwwQDt/YyUJMN+DXfyTRMQ23qVEgG3fVk0CHTL4VImR82xOWdUtWAnIbRqbl7J/ZCDlw9jAcu+itK7uay4o+QwcsDw0gT9apyo5AB0K+yzJyRZaHZqwJhg4zeLxb1ge4y6NPJgGzI18BJQw+i0fLztK7AjmAZWNYBOleKG09vJfzUZHw96TiiywzA/B/qv7YYUBZk4YRCZauhXp3ScDbSgok8vRobLmmgUJdCtWrMAe9GoiBN6Y4WM3fijyGVY28+oHdFHv/k8a69PN7dkse77+TxjjHa+4GB2rukk43AScOBoUOTDgN7A+1k8OUpG+GHgwCb0sDPcr6EK9ayoT9nIHBMNurKDwJO7wZG9wE+7wR8N0c2/nYAlSzjOqRYcMOwjIzYpo0BHuqAWhPkemVD9ZvOQBe5/KZ/gG/LAjH6SxCUfnLfbp+UMj2HyLTq0g4o4wmMOywb9TZAbxkgV0t2C4K9nO6ZQQ2JozKN53rLiloGcd90i7sN8FUCZRCpT347Rxl8xI1KSq7APof8V84UJPPkfynd5UZS2gMV5H5Oa02X4ftFHipHb5O/XwblgZuA6nmB3K4y6JaB4Ii9QNkvZB76HShu9MvoTYQexYSe03FWlMeQ+WNQW59MZMK08r/nuH/VG97e8cNV+ARGxRbBqEAfXE0YL4er9/H8dXeBBMs88M1ceMco4NziG3RLfNKGMocIx7n4jkO0+pRTw9HNBcYudlJmkgc5ebzzlMe7nGzZv18Mz6qZDBP8SW8vrd2MmzkK0aSvEMcDDAsaxHdeoXQW4vdkHRLEW9MuriOJKhPjOjmI3C1EPn0nBvmE2GnkKfqQbXGdHLAzkdS9bff8CjlP8SZCzD8e25/Fa71YJoSFXO5V3fMbc+EXIdz03cfL7/t0Tdo6uVjcPO431pqeyvyRQvTKL+eReaTvfsO4zJCGzkSS79fkQ2rlxqgXQrS0kMul0plIZuwXn+1CfFxS/k6FLKOWMq3chbDV5x/5OU8V+TtOpC1/vMZ7WXem2XOxf1ApYaG0EVXGnkro3EBzbYqoJvMQOxMxRbK8BiwQH8g6T/+7XztYNBOLAg2LGhN6QfzyoZtQKxTCLP+nYs29tFSEpkW/nVlDfGciCmHtnlfkUimEwrKwqO7lFvuKBFWeVmJpZr9iKBNlnXR4nRdimTzesTORrI1x97ukLgaM/xn4WT/MACYMBirlBhQKIHctYMslYNdcoFqyW9sCzwI3Df0Mr9NfremScthwO2769Yuxd8HBRy7jpwUsK8j1WcdNSyyH/D79VTh6C2qg/XhDesph2gT5uRJgJtNTLdN1+Bbg8i6gV7VMunati7uK2lTmo8fyY5MfgcWfpXIlKBml4Qdp9ff5pUKjnya3RfUfX+1Jb7lJj4zeL0F/y/RpB2y7CTQYC9x4Cvg+lOP9gNXfANFngP7NgBlpfKUCGRW0awR6zb0K82oj8Ov3lWPf1kCmzkz+54yiFSqhUqWXQyl3G1m6lLBxL5VkfKUKRZArlQtksV2Rt2qKwTtkRZinCX7cshif5edV6swnEC7rs2fmnuiyfA8O/jkPX3qoofPbhiHdf4F3tGE2Iko/Q8BmMkzwJ729V3UzrnkkRP/yIrZrcetSQmw1ctbj3/Fpu7KgHyyaxJ6oFP8MFkItP+fpqj/5ZUSkED3ceUXtVdLVPb9GiL/6C2GjkPvWWoheW9N+teSNrqjJ9FvXUwg7fZf+8ne0mS9EqGFSWvzeIS7PVRgTe1ErJZlpvnCU2yi3c6Tc3leJ/FuIQjIfWcvtTTLYC/G/ZPsuhXR2z5+WcmPUa66oZeR+0eeF6bXk+mReKDko9quTktu04Yu4Vy44tpXlNq0Zxbj3su6MFSmzl7XMUskG+2Yye2mF1n+r6FbITChz1hHTLiV9yTGvqGU1MeLCmAqy2JuJSuMuGS+CyUTeXCd6lreLvbpjXrCNmH/xTSpC05J10i/+iposWzalxNcb7xluQNCKZzt6iWJmCgHZtqgy5oT+hSdZzvtTl/KK2vuAV9T+aypXYMZvQGMnINwb6Pw5cDnZaSiV4TSieW3g2GU5/RXD+UWAo35ei9iT/oiOil3UKJ0+/1PGUgHNZwBTG8v9Hw4s7AzMkumSkXTPgEktgE4LgVA74Jv1wPpegI1helq4usX+VAT4xXWekZwuGPDXvxhaZqI8r+mRUMgVRMhtDTcyaDIpj6Wl3KRHRu4XRMjyekHuH1l+23SK69Y/CVn9tpT5w11+YfBx4Aw79zFOyOwVLrNT8iEyNnsFbV2A1XdjIGKuYt5HnihYsGDCUKTRdFzQ34wQsh39SslxRepi3Ame5n8/6PDsyCS0qNsJCy+Ewq7SN1h/YD16lX2TipDejhLO7Sdjdtv8hhs5lHBsNgXz+5SABUJx+sduGLnPWHfURJRWDNRMgbo4sGAqYruwen4Q+PonGWAZpum55QcsZcNQ6wtEFQFKlUp9KCHn1deYHoXibsELuW38fU/6Hgnvy4EygWyY914gAzZnuZ/lQWrs18DFDGoc6mQAMfQDYMxeGSvItJ65G5jdKvYr34inzCvmMn88vSmDEiNP6GuuAXfkeH1AVFIGQ69iXhlY8xewY0eyYRvwUS7DTJngdeUmPTJyv+h/TKQh+MqZSqcxKrkOB/n7dWGyrBqLDEkmiMxeO2SWSjZsmyqzlxI6nUwPGbCJ8Ce45+MDn8TDw0BE6qdpQ+EfO+4hAvUjKIvTwW/nUHzQYgz2PlYg/8czsXvfbLQq8KYVIb0tpTIuRHvJHg0m/oqB5axke+UK5vUYhM1+RupSIkoTBmqmomAX4IcmMkVkI+LkNGDeVcMEybY2UFlWetp7wGLZ+E1R52mAqTUBOxegxazYj3BsAFSxlH+fk43o83GzJeazATj+iqtt9HZUBYFZP8h0kEUs9CQwcF5curwV2Zif1FYGZmcBq9IyXWVw0l8GSenhKPNUeXMZS8j8sUsGf8ld3CUDefmDHWoAlV7Tya9SBqT1mwLNmiUbZEBZIJM7CH5VuUmPjNwv+kucHnnkvzIAO3UqblRyT2XZvCvXp8or503WKygZKGX2aiazVLLhgyqx2cv5qw3wDQhAgJHB7+QYeJkBCvu2WP5QjvM/gym1MjlPUqYLOzkJbT+bjbMhVijdfQ0ObuyPyuyJ33TkqIUxC4ahkqwCY+6uQt8+K+HD81BE6cJAzWSogO4/A3Xk0UZ/e9WkocAdQ82mLCAb+h0BtYzQ1vUDxu7Uv9fVQP6xeTAw+YQMCMLl8o3jrq6oPOQyn8p/Y4AZnYFVV+Jm13uwA+g0Ts7PM8uZqnB3YGQdmX4y3Q5PApbcMUxIp2MTZb44Llud7sD87UA7mcZp4XMBOCHzx2VfwwhJVQT4op784wXw42jgUaLoP/JfYMRCeYSVebJ919e/k+0/9Ypykx7p3S8hPjJQlPv45GW8fJehDAg+bQ2YyXK2bQLwl77Hl0Q094Dvpshl5d9lZQBekVcD0sXCFk7OznA2MuTKaWW42GwOGwc5zskBNtzNJkwJ18bfYOLkiejXKI/xBkr4MUz8ehKOByvg3nY+ts9vBw+mqcmxrjoCi0bUgJ1Ci8dbh6D73CtvfcMDUXbEQM2UqEsAP8ugy1oBPPsbGLb25dWzlj8B4+vLRvoTYOKHQN5iQI0agGdeoO0cGXTJI1WbWTI4K2VYQCatfplhlWUDUwZpncsDRb2AKiXlMi2BU3L+vEZ6g6QMJPdxXxlEeMn9rH+ubNwwwDdRw/9N6AKAnxbIuFw2+sVTYEBFwNHR+ODSCLgRH6zIQP5nGQRUry7zwKJEV/Vk/ugiA7+aMtq4tUxObwiMnSGDk+EyX8l8ti8Q8PgcGNXAML8Je1W5eWPp3C9nZTrXlPu4dme5XKJLp7VGAX1KA9GyDLaRadZ+ADDjF1mG5e+tVgVYeUsGfFWBOTLAZGOTsj0lctfqguHfD8dXNZ2NNFB0CNj4ExZc1r9rTeDprgGo6Owoqz1jgwsa/Rz/XlF69yxQfuivGFvPHkpdIPaP7ooppxLOYhFRGjFQMzUVZIOtfxkZkMmW5taRwGbZQI9lD4zYAeyRQVnrarJRJ8efOQP4ydZd9TbArweA9d30J45fUspG++T9ch2TgXpFgafegLdcrqycf+0eoFGK3g0oo1lUAGb2l//KIMJvK/D95vQFEfpu3E+8iPtbJ4Mv/cuWUx1CjHeEkZylDNw3yd/UWgb9Dw8BP8i899104IL8nso9gL9+BdyySBWRarlJh4zcL0onGUTuBaZ1BOxksL5RBmlDZbA2eiZwLhioKsvsnp0yCGRZJHq9aJw5fAIv9HWo0CEqJEhWeakPIRG83+4/ZV4KAxZMQmMnJUTIKUztNgr72bcI0RtR6Lt+NPxtEhQKfd/YvCWP3g7z0ZuQrZ7bJ4Czt4EoS6BENcArn2FadpbB+yXSTwbbJ4EHsqVi7giUlesrkQHvfjNgnifmgayN6WcamA6mJbunBwM1ei8xH1F2wzxPzANZG9PPNDAdTEt2Tw/e+khERERERGRiGKgRERERERGZGAZqREREREREJsYkn1EjIiIiIiLKzs+osTMRei8xH1F2wzxPzANZG9PPNDAdTEt2Tw/e+khERERERGRiGKgRERERERGZGN76mNFEJPzDn8AvJhpQ2SKfdS44qhgPv2u8dYGyG+Z5Yh7I2ph+poHpYFqye3owUMsQEbjmtwuzfY7gz6c+8NXqEL8FCoUtijlWwqcFP8ZANw/Ys6+UdyIz8tEvJ/vjf6EKVC82Hkvy2Se6HK2F9+0f0cHHFxrDmMQUck6VQg1rMzvkzVEQtfM0QNc8+ZHzdXlBexc/nZ6FlRZtsa98HTinNn/MPWy48xfWPLkDnxjA1tIN1VwaoU+BsiioMsyTZjHwfXYA8+6dwj8vniEY5nC2LoSG7k3R263Af5R/tdCG7ES70ztxFZ4YXbMfPreI2/uaF9vR9szfuG40qeWeV6hgobJBLitXlHesgq8KVEYpM2MnTjJiu7W46/cXVj4Pg84wJnXmKOveCm1t3ziBUsXGRUq6xxvRt80YHNQ2x6wjP+EDC8OE91T2yQM6BB1bjjm77slSZ5zCuhw6DGmDEmrDiCwg66RfFPYOr4v+217Aqd187J1YF8aLVijOzPwKPRdeRhhyoGzPBVgy0Au2hqmm6n0qR1EXfkK7Tivh/P0+LP3M2TA2a8nuxzYGam8r5gZmnp+JUY/9EC4/KhTWcLdxRT4zFaI1gbgd+hTPYzfHDIXcumNrxSYonXFtM0pFZuSjMQfaYcILBRqU+RV7CjkmCdTOXB2MGjfuy+Z+WpijWL6++LtCHRRMNQAIw5ErY9H85m1E5+oBnxrN4WpkXm34P+h5fA6WhkbLT2rkUCsRoYmWAaMSTo7t8EfVDqhrntYruhE4cWMKWl/7F35y16mUVrBVROOFViubRfI35+2NHRXqoXBaV5dhtNAEr4fXoQ24iDKY03gc+lkZArWgNah4ZCP+TWNSW9nUw5Lq/dDRJnEhzKjtjsG+i33wgc/TVBuPL9ngs8pLscbN3PD57WX3g1kKuvtY3aE6vtr4CDr7jvjddy3aWRumvaeyTx6QgULvomi64EGqZU3p+Dk2+q5Ga0vDiCwg66RfJDZ/4Y52a54jd9dtuLvkQ6TczTJIm9EWLb/dI+tVW1TotwZ//twCblmg/fPelKPgIxjZqDmmnIlGg7k+2NvX1TAha8nuxzYGam9Dew+zTo7GkCchECpXfFTkc4wrWA3lLV7WRNFRPth+9zd8d/MUbunUKFl4LE6WLo0chumUOTIjH6UlUINjRxyrVB+5DVPiaXXheBxyDZt9/sDcgCfyMGeLj8r/jM0FciVaj4EIwdGb09Hm6r8IkB/NUwvUhC/mHB+OgU8i4Zq7I5aXa4lG1moEBO3Ht+eXYEVIDAoWGIlz5Ssip2GRVwl/uhQVj23HDeRCixL9Ma9QGeRTRuD649/R7cJWHI2xQN1S07CvSD6822NtGgI1FMeE2oPwpUWynSSiERzli2OP/sbUu+fho1PAKU8fnK/SCPkMs2bcdmvh4/831qR6RU2Le/5/YVlQGFRWtbGi1gB0tM64PZndD2ZJaWXjsQ2qfb0NATIxFAzU3i/au5hR3xNDj+ZA9S4D0KxAyrMoCusyaD+gFTx5RS0TvC5QSxyk5USVIb9j29TGcHntyS7T8D6UI13gUUxt30a2WwKgFeZoyEAty8oixcYUaXH17q8YrQ/SlPnRt/JkbCpeM0mQpmdu4YG2xYdjdxkvOEODqz4bsDz89TdGUdakUNrA1coZ+a2TDgVzFEAN1w8wveoYTHKyhAIh2P3gOB4kq3t0Udcx9+wINJNB2lM5V6oX3KTwJ3/i5yfhUFjWxi+V2skgTX/ziQq5HRpjUeVPUVulw92Hm7Es7PXXd/RXgw4/PIpbQgm3vN2xsqgMVvRZWWEFT7dOWFO8DHLIg/OxB//gX5PMvmrktMyVYr/nt3FHGccq6Fl6JHaWKCXDY4HAgIPYFBG/ERm53Sp4uHyIkZ6fYLSRYZCzDhdehEGoCuM7r94ZGqRRUprrC9D72z8RmNMJ9jzKZSE6PNr5E4YMHIIZux6ncsJDirqES9e0UKjL49OxozF6dMph1JCsFaS9PxIHaQ6oOXIzdmShIC3r0+HJibnoVLsZRh94CiGDHMraWHTSS3MBP9++LqskFUoV6o0fXRI/s5ScCgXzd0RPO9kw0z3A8cBQw3j5MfIKlt7ciOkP7yJcvMAlv7345fZurH/ii+AkjXgdQsOvY9v9vzH71nbMv38Sx8MjUj+QxUrrMjo8C9yPaTc247fnEbGfg0MvY8O9vzDz9k6s9LsJX2MPX9GbU7riY5cCMqyQIUKEH+4kJIYOAf4rUPvASPT3fQRVzsaY71kOqd8YF4Njj8/ggcx1+fI0wIfJZlTbNkBXZytAew2bHj/B60O1KPhGvJDzKVEkZyHYGcbGUcLVvjDyy/peG+kPnyx5YkuFoq6VUEZug9A9wa2E4PUdbXfMOQw/txnntFao5fkNRjnKtKHMEe2NX3qPwp4XRdB9Si94Mh7OQvSNzLWYM3sOfjvx1MixKo7mzkV4P9dBVaA8KjICMCEvgzR/5EL9H7bjzx/qwYlJ9A7I0qILwI5va6Nsnf747boK5bvPx6hGGXd7Pf03WHzSKezJP9gWqYNCVQq9ChXDa++oUXqgv9d03Gq2CGvyvmwO6iIvYPbVNRh17xgWnhmGKifnYcDl+fj02BgM9tcHTVLMTfzv3DAU3PsdPj7/KwZ6L0Wf81NRc29PVDq7A6eMPRj1RssI+D/ZgVFX12Lx09tYdWE4Cu4bjU8uLMbgywvR+eRwFN43BmOfPE/1wElppcOjyBexnc0o1TZwSDjZJfD0+WWcF/nRscQInKvdBx2tX3E6WPjh1PMgGWCYo4JjUSMPctugikNeGRBqcDHwRuzzk69mAXcrOxnO6HDrxV2EGMbG0SEw5CEeyR+ttHCCWxY9QaeJDMQT/R8KazgkPLf3LrY7CsdurMASGRxaO7TGnMIFXhGA09uJwoUZPTH+UARK9FuASfVyvPKqNGVNEZcu4aZGAevSFVGahclEJArSFHnQ5Me/sHVkDdgbplJmkwcq8RTnDpyHpnRHTN5+DscWdkTB97wDpeyAgVq6xOD8sxsIlH+p7cqjqWVadqMSzrYFUcjM+OndmGdb8J2/Gs2Kfo1l5b/Ct4XaolduK9m6vIGJJ8bhmwd3EG5VBj2Lf40VFQdgQYnmaGodg0sPF+ODExtxOvEVr/QsE0uHy7d/RvcHz1Euf0fMqzAAS0u1wsc5LBET+S8mnV+Dv9PWWwYZJRv+gZsw6oGfDJ9UKOxcESUTso4Cbm69cb7RT1hTrNLre2vUBeBOpAybFY7wMBrQqZDPyjE2IIiI8Etxi2VKZqhfoDEqqGQg+WAZvr57I/bZHn1ef/R0M7peO4tgGfzVKVAflbJgraGLvoYfrx7AbbkfzGzKoWlCb4uZv92aF39i2N37iFHkxdclW6Ica91ME35qMr6edBzRZQZg/g/10/RsJmU10bhy8QrChRru9v74tVcLVC1ZAM72DnApVAlNe0zDjtuvPzVFGSlRkKZ0R4uZO/HHkMom37vj+0Uh/3ND+1/P49aZNfiuWcFUeuKkrIZNhnSJxq1Qfc9uCjjkcId7BpyyFUKBCsW+xYaSzfBVgY8xtUxzVFZq4X1nKaYEhsPC7iNsrzsOCzyb4ct89dCzWA/8WWc0huc0Q3DgRgzz8TXc3paeZeLpEBCpRoeK07Cvwifok78euhTpjE01uuFDMwW0EWfxxzN974KUGl3YaUzyXoahl5MOAy/+gnZHB8Dzn3U4HCNgY9sUPxctlujKihL2toXgabTreCNECAKj9dGXFRxTWUZtZhPbaY2ICUPQawM1wMKhPbZV/Rztc4Ri06VvkXdnZ7ju/BIeR1djr84DX5Qeid8L5ZUhoCnyx/YbK1Ls9yH/LkCXU6NRZt8ojHumfz4sP3qXbo1qiXZZpm63CMYfN/7ECa0CufK0xTCnLNQFXVYTehQTek7HWVEeQ+aPQW322GTi5NFH+xz3r3rD2zt+uAqfwKjYOw6iAn1wNWG8HK7ex/PYkyjBuPSvj1w6BleXDcX3S//BI+GAvO62iH54HrsWf4ePqjXB6P1P5BGNMp0Ix7n4Z9K0+pRTw9HNRR6Z6N2SBzWlPTwreCInW/bvFSZneogIBMe+K02BHGpro7fWRL04jpk3N2O6keFn3zt4+ZSagcIDH7m6xz67lEB3F789vIVw2KFVsU/QIFk360rzkhhepBLs9bdW+R7DDX0dmZ5lEjGzq4dBrol7NJTLWJZHo5z6ZmoIHkaE8+D3CpqIi5h/extmJBtm+xzAH08fIljtjiYFe2Jvza5oZngXWLroNDIF9cxhmUoEoVCaxZ5RE7oYxMZ0r6N7hrPPbuJyZIRsBCmgUqgSghONJhDXX9zFrRgTTX3xBHt8Uu73n+/swvLHl3E1xgqezs3wvxo/YKZLzqQVXyZutzZkD2Y+fg6hyIduRWsafcUCZYRgHBjTEzMvKeE1bAFGVbcxjCfTFSj/W4+vK5RG6dLxQ1m0mnsFGhmEXf7lI5RNGC+HCr2wMVguFvUvLl6NlmXKDPk/nIQd133x4OoFnPe+j8c3/sKYhi7As6OY0qk/fvfj0SpzCbzYPRgf66+kmRVCdS83KDU+WN23N1bcTXoamIjS5y1aitmYPEBYGhpcUVrjV5jCg/bi+ysrMdzI8L2Pd4orHApVHhRN1gucLuY2zhg6PbjhuwRdzv2SYhjk6xcbKGpCfXBJzpqeZRKzzJEPnslzhSIHHNTK2GWiZYBAqVPb1MD4Ul3wc+zwJSYUroFK5iq575TI7dgaW+rPxq6yTVHtbYI0PYV+jXo6xJ7ENEZoY6+YKhT6F27HjUpdKP6+/APaXT+Fm6oyGFt1Hp42X4qHzVbDr95AfJNTgzP3F6PZqa24aIptH/0tH57x+/0rTCv+EdrnzAkzOUltXgLDq87C5Rpfo5djsiAtU7c7Bsfu7cdZuZxNrg/Qy17/aygzBO0agV5zr8K82gj8+n1lI+90ItMjy4OZM4pWqIRKlV4OpdxtYutLG/dSScZXqlAEufRnMi2qYcyukzi08yD2bxyBpgVfBuWWHs0wdv18dMqrgvbxZvyy/IZhCmUOgXDfh3hm7okuy/fg4J/z8KWHGjq/bRjS/Rd48wYcorfGQC1drJDXylbuPB2eRTxJ1jtjHAu7GhhapDW+TRhaoWcup1Rvn1KqzZH8HLAu6jmexq77Bc4+PoDlD1IOK/zuxj4rJ3TheK4P1NKxzEsKWKksjWQKedg0NPRF7E0plBqlVUl0K/wRBhXRD60xqvQwnKz/Pb6xM8OTwM1of3xRbCc0b01hCZvYhIpGeLJgO57QxkDfHY1CZfXazm60oXsx6Z4vohV50a/ScIzN42rIjyo45qyLmVV64zNLBYKebcIEX/1pbeN0UbvR8q8OsPkz7UOOv2fhj1S2Ie0cUbtAC8N+/xjDZND2e92fsaWQByyir2La6fHo9zgwxdXgjNpuozSXseaxPzRyjU3y1Ux4bxu9qSgUtrWBjU2ywaE55j/SQRewDcP6LMIt61oYvWAoyvPBjCzCXv7XBnOOn8GZM/HDCazpVgxqWf6K9/gNJxLGy+H4L2gV+9CTNXIXq4Q6H9RAYSMRudKpGT5r7gaViMalEycNYymzKGxKoceqXVjYoSDMXT7CT/O6o6iZQNCBMeg66WQaOrIioldhoJYualRy8Ii9Bzs6+AqOGLnIZO3QEBNLfYmpCcMXGOTs9IodnrIVp4i/BUtRAj/Uno3L9V8x1OuDDubpWyYxvnIj46ksK2GGVyc0NlMgPGQ3Op/djstvG6spHeCmvyonguEXZWxlOgTLoF1/i63Cwv61PRZGBF3DBbkatW11dDLSdbzSsjI653GUeSscx5/eMoxNSQlz2JnbwtHsTQarzOkFUeGI5qWGYKqzLRTaB1h4biZmvUjaG05GbbcxUUGn8HeEDkqz8mif/HZLegMCEeHhCE8xREIjgKCtC7D6bgxEzFXM+8gTBQsWTBiKNJqOC/r6OWQ7+pWS44rUxbgTPM3/flPB1S23LG8CMS9eGMZR5lDCuf1kzG6bP67dIT87NpuC+X1KwEIefU7/2A0j9z2PnUJE6cO2Q7ookdulGuqqZXM4+gwWPQyIvcUso6ksc8FdX/uJQDzRuaKUXf7UB1tn2MvGeHqWocyntm2KBaUqwVk2Hp4/XYevb93FWzUXle4oZaOW4f0L3AwJNvLcoBbXQv3leCVcc+SD02vSOVobg9gQRm2NnEbnVcLJPIf8vw5hGsNrI4yxqIc1jRfjwQdpH+437ImWcUf5jKfMi97lOqG5uQI6zWWMvZD0FsYM2+4UYnAh4DJ85V+2ubzQJFMi0ezCHGv+2oEdO5IN26bio1wyZXQyQWXAJsKf4J6PD3wSDw8DEamfpg2Ff+y4hwjUj6AsS3N1C34aPxLDJv6B20YPvDo8exok/6+ApZOzYRxlFqUyeeVtjwYTf8XAclZA1BXM6zEIm/msIFG6MVBLJ6VVbQzO5wYzhGPP9V8x/8Xrmt06hGjjun9IM3VJ1Lc3l4ebJ9h07xQCUrQvtPC+8R3s//oKRU5sh7e+LkzPMvQO6F963hU/5NY3+iNx8uYSzAt5m/A+B2rnKiibsBqce3IefsnTWeeDXU+exN52VyNX4dd202tjkxt55L/akJvG38snXuB8sP42PiXyynmzEpVNA8wqXh6O8u/QoM0YeOeB3I44mbbdIgjHgvxkaVOjglNJvkvorShRv2kzNGuWbPigCgrIjO381Qb4BgQgwMjgd3IMvMwAhX1bLH8ox/mfwZRavDcyK9M9PYSFEydjxqTZ2OJjpA6NOo+d++9Dq7BEpVpVDSPpncpRC2MWDEMlGyDm7ir07bMSxpKKiF6PgVq6WaF+8Z7oZ2cOEXUOg46Nw4B71+CbojLS4nnIacw4PxItbt6LPXuvUpgl7d0xNYrc+LxwbRRQ6PDo4SJ0uHYW9xLWHwOfR0vx5c0bCNZEwdWpXFwnIOlZht4NhSu6l26HOmr91Z0rmHR5L+6k++S+CkXc66KezEgvAjZhtF/i56+i8e+d1VgoA0GVdU10dUn89GMEfIJv4ETgDVyOeHniwMKxFlrbqCBiTmHC1TN4nOR3aXHv0SpMCYiQNYYH2roVNozPKlQoXKALRjpZywovHIdvLI99+bReurc7JgAXAq/L/XgPvsb619HexXm5/4UiF8rldGBFm5ksbOHk7AxnI0OunFaGutYcNg5ynJMDbNJU+dJ/QwnXxt9g4uSJ6Ncoj9FyY16lPT4uKqPvyGOY9f1a3E1c/nTPcGhcf/zvigYq19bo3bGAYQK9a9ZVR2DRiBqwU2jxeOsQdJ975e3uIiHKpth+eAtK87KYXm0ohjjYAVFX8cuF71FwV1/UPDYVn5+fiy9PT0Sd/d3gun8yht6/iQBhhRJuX+Hvio3T3E23Y54uWF28DFwUwTh4YyI8d/eB1+Hv4LW3G4qf3oFzGhU8XLthUeH8CcFfepahd0Nt2xw/Fy4Cawg8C1iHYQ+fJQqw3ozSuiEmFi2BnMIPy858i4bnf8OMW5sw/PR3qO99CYEKZ3xesj0aJE5k7W38fOp7VD8yAp3vPU64sgRVCYwq2wylVRpc8fkRFQ9Nw4BrW/HLrd8x+PS3qHL2AG4Ja1Qt2gND7TPrPsVMpMyHvqU/gpf86bqY8xjnfQS++qAsndsdFbwVbY98h+r//IJFhqAvMW3UI9yJ0X9BbhTLkQX3F9F/Qonctbpg+PfD8VVNZ+MNFItqGD7ja5Sw0uHhxm6oXvNzfDt1NmZPG4GuDSqh2Y+nEGpZHF3nTUfb3Gzi/HcsUH7orxhbzx5KXSD2j+6KKafYtQjRm2It9pZUVpUxvdZM7C/bAi3tckIV8wjHnpzE2vv7sOrRWRwJCYZW7Yxqbm2wpPZcXKj8Meqk9uIro2xQs9honKrRAwNcPVFABl/ez2/hcpQKBRyqYUi5CThRuRGKJ0nJ9CxD74YZKhTpiv52+ufLnmPrlVXYbLQzkLQwh1fRb7G1ZFUUUz7Dofu/Y6j3Kkx/dBcvzIuiR4XR+NU96TvxUqeEU+4u2FutMzraWeFZ8HH8cn05Bnj/hpmPbiPYvBi6lRuPncWLI7bjtSzIwr4VZhYqIJsPAn6PV+P7x89lkJw5262Neo4n8l+lmQPc0voScyJKAyWcm83G7q3j0bq4DZ6dXotp3w/EwG+nYNlhX1iUaIMftu7G/FZubOD818xLYcCCSWjspIQIOYWp3UZhP/sWIXojCiEZ/jYJCoUCJvaT3oAWIeH3ce6FLx5ER8sozhZ5rNxQwd4dsp6idyhr56M3p4t5jBPPbuN2tAaWFnlRzakI8qX7cmk0/F7cwMkXT/FcqOFoXQDVHPLB+b3Pw1l7u7NbnqeUsl0e0IXi/rmjOH3dD2FKO7gVq4Ialdxf+zoSU8UybBqYDqYlu6cHAzV6LzEfUXbDPE/MA1kb0880MB1MS3ZPD17nISIiIiIiMjEM1IiIiIiIiEwMAzUiIiIiIiITw0CNiIiIiIjIxJhkZyJERERERETZuTMR9vpI7yXmI8pumOeJeSBrY/qZBqaDacnu6cFbH4mIiIiIiEwMAzUiIiIiIiITw0CNiIiIiIjIxPAZtUylw95tF9D/skb+lZR+O83MVMhlbw2vos7oWtUJxS0NE/W0oZix9CoWPTPHFx3LYFQBxtRvInve0yyg9fdFu+WPcFVhh9G9PfG5bVznPJrHD9F25SNc18Z+TErOolQqYRGbH61QvlAufCXzYymr13fsE+X7AO1W+8O5UVksrWRuGJtS8KMnmHPEH3t9I/FcqOCa2w4tqrqhWzErJM72aaKJwpHTvlhy+QUuP5dly8wMhdwd0KGmG9q6qbPt2aesn+dDcP2vpVi0bg9OX3uIoBgz2Lt5onKTT/F19xbwzGGY7VV0j7GxbxuMOahF81lH8NMHFoYJiYXi2vYFmLfyb5y5/RTRlk7wKNcQ7bp2xyeVc0NlmCsrMuU8EHptOxbMW4m/z9zG02hLOHmUQ8N2XdH9k8rI/YqdHvzvBsyZswZ7z/vIusMWrp7V0KJrH3RrWDCVuiPrpm/WKcNR2Du8LvpvewGndvOxd2JdGCtp+rQ4M/Mr9Fx4GWHIgbI9F2DJQC/YGqaaqvep/RB14Se067QSzt/vw9LPnA1js5bs2Z57iYFaptJh8+rjaHc2ZaCWnE1uFyz62hMdnQyNY80LfD/jPKb6W6Jf78qYU5SB2pvIngVbQOPrA6+f7+Oiwh5zRpdFv5yGQO3+XVScfR//vi4jGlg5u2BJz0T50ZiI5xg5/19MeSDQoE1V7K1t7FAtcO/8DTT7zQ9XYwCVSgUbpRYh8m8o1KjRuBS2f2APh7Rm78gXmLr0MsbcjIF+FZYWKqhjtAjTb5eZFb74pAyWellBHTtz9pKl83z0Lazq0RJ9Vl1DqFBAZWkLW/MohIREQSs/5yjZGfM3/4oviqV+MkBf395f3QHVv9qIRzp7dPzdF2vbWRumGWjvYWOflui6+F+EyPWaWeeEtS4ULyI0Mv+4oN6o37FxVB04ZtHq1jTzgBb3NvZBy66L8W+IgMLMGjmtdQh9EQENzOBSbxR+3zgKdVLsdLnc7z3RrMtSXA2XdYdFDll3RCAkUqaV0gk1Rv6B7WPrJq07snj6Zp0yHInNX7ij3ZrnyN11G+4u+dBI0CyDtBlt0fLbPfCTAXaFfmvw588t4JYFzoS8N+2H4CMY2ag5ppyJRoO5Ptjb19UwIWvJnu25l7Lo4SjryV2hOG6NqYp7hsFnVBVcGVoe2z7Ji0ayMR0e4I8+Gx/DJ40NaaJ0UdphwqCX+TBhGFUZl/qXwoL6DvCQUU7EE398s9kPD1LJj7qwYExedgU/yhleVX1qAx6h++9+uKY1R9PmZXFnci0ET6mOk5+4oKSZBsf2Xsf312UjKk20OPz3tdggDfZO+LFPVQRNleubVBkb69vBUROB1RuvY7Z/9q3Qs6ZoXJreCb1lkBbuVBOD1p7D4+BgBMnB98RS9KyUE+FXVqBX5+m4+Iqsor27DN8M2YRHxq4ax9Lixvwe6CEb8WH21TF4/WU8CQ7C8xe+OLW4i8yPATg4oTOG73xumJ8ygvbGfPToIYO0MHtUH7wel5/ItH3+Ar6nFqNLSTMEHJyAzsN3Ivle1974H7r3XIZr0W5oOmk37gS+QLBMq5MLv0JJy0Acm9wV3+8ONsytx/Q1HYmDtJyoMmQjds7MGkHa+0IXeBST27TDj2dDX3mMJtPHQO0dUZqp4e5gifyGoYCTFUq450TL6oWx6dM88FAAwTf9sTGQRYoykUKJnHYWCfkwYXCyRpmCudDzozLY+WHO2FtTAq/7Y9Pz5PlR4ImPLzrN+RejZcAkXnl3pBYHDj3AgUjArWIRrG7sgPz6CyIqc1Su7okNH+SEjS4Sq/f74XZaTlBogrH6QgRiFOb4rE1xDC9qGXsWV2lpjTYtSmC8/qpz1AusPheGtIZ+ZAIiD+F/C08jTJEH7ef8gZ86lodz7IUzC7hU6YJ5G6egib0CYacXY+HhqNhFUtBcx4Le3+LPwJxwsk/lsBZ9EovmHpABgT2aTlmH6e1LIqe+4ajODa9u87GwjydUmnv4Y+mOFEEDpd/JRXNxQO5Q+6ZTsG56e5SM2+nI7dUN8xf2gadKg3t/LMWOJDs9HAdm/SyXU8Ct4y9YPaIR8usvjsq0qtx9ETaMqw0b7V2snrYMt+MDc6aviUgcpDmg5sjN2DG1MVzY2nxHdHhyYi461W6G0QeeymP0Kw/SlAWw6JgA24I5UU6tf6FfDB69eEWgpovCweP3MWXfI+wJMjJfVAjW7buPqfufGEYko9Pins9TrDz6EDMPPcKKf4PhE8nAkBJToGhpR5SRNYPQRuHWs0T5QxeNHdsvoOycW/gtAChfrShGFXvFQUDzAn9ciYJWYYGPKzvByTA6jgIlquZBQwvZJLv7FFvScoIiOgq+ofJfpRXK5012alZpDq+8llDJQPJhYCQDtSxEc+0ITjzWQpmzHtq1dElxUFLlb4lmFWQFqX2Eq97PDGMTi4b3L70xas8LFOk+Bb08jZ+214UEw7pETVQo1QpftMuf7HssUKZUUagUAmGP7sE/1aty9KaCrUugZoVSaPVFO+RPlrgWZUqhqEoBEfYI9xLv9Khj+OOvB9Cq8uHjrz5MVneoUaJLVzS0lXXHsU3Yci9uOaavKXgZpPkjF+r/sB1//lAPTskLNWUCnfwvADu+rY2ydfrjt+sqlO8+H6Mavep2ccoKWHxMgDYoEg/lgUNhZoWSuV7R8JWB2q7DdzFCHsC2PU3ZsNVFvsDinXL6Tn/DmJee3/fFVzNPoMhsb3TeeBuDt9zEV0svoOiEs/jyyAueYaQEmuBoxIb6ChUcrBPnxxicuxkKjWtuTO5RCcc65EbBVzwMpn32AudeyNWY26JG8haanpUtqrjIRpo2FMcMja1XMreAu75DCV0ELvkmm1+nwRX/qNhnQV1ymrNiy0LUJQZg05nj2LdlJOpaGUYmptPfvibrO4USllYpn4OMujADPccfQkSJflgwqR5ypFKFKp2aYfzmgzh3aRk6OhpGJgjBiVPe0Aol7DyK8BatDNRs/GYcPHcJy1LudIScOAVvrYDSzgNFEu107Z1TOCeDd4V1BdSobOTZV/sqqFJcDRF9EcdOhMeOYvr+1xIFaYo8aPLjX9g6sgbsDVMps8k6UjzFuQPnoSndEZO3n8OxhR1R0HgvL5SFsD3zn9Lh2aMnGLHhIc7pFChZLS862GX8Zeqwe/fQYv4trHioQ76irvihrSdWf1YUU2o5oqAmDKs2X0LLPS8Qd7ij7Ez/7NmPO/xjb0U0y+WApjKQeskC7T+phFuDS+C7Elap9PL1kuZZJB7KY4fKzgIFjAV0SksUyKmAQpaDB89SuaUtMbU9ulfLARsRjTVbb+B/96LjrpxponBw/3WMviqDNyt79KhsC55DzEIsnFCobDXUq1MazkaOSJGnV2PDJQ0U6lKoVi2nYaxB+ClM/noSjkeXwYD5P6B+sslpEfX4BFZ92wZdF9+FNkdF9B3Y0uR7pcvyoh7jxKpv0abrYtzV5kDFvgPRMtFO19y9E3vyUuXqgQLGKhpVPhRwN4dCRODBnQeGkcYxfd+FREGa0h0tZu7EH0Mqcz+/U/JYrXBD+1/P49aZNfiuWcHXHqMpa2Cg9o48vXAdRccdR75Eg8v3/8Bl+hVM91GgRr0S2N7CIeMrNm0Y5my+j2ORSpSvWxqnexXD6Fp58HllN3zXtjROfp0PldRaHN17BwsC0nD7GWVtsmGzfc8dDN16O8kwZPMNdFl2EWWmXMS4OxoIcxv0bpUP1RIHWEo1PPNaI2caaw1NuAb6O3QVlmap9LKmQE4rlfy/QLCc9/WUqNKkNLZ+6AzP8CfoN+sEHEcdQ+6RJ9HgryBEueXGjO4l8U2S4JKytOCjmPDNXHjHKODc4ht0K5k4Q4bi6ISemH5WoPyQ+RhTOy3997+kvT4LTd3sYJu3Br6ctg/+Lk0wfut2jK36xi+MoLTSXsespm6ws82LGl9Owz5/FzQZvxXbx1ZN0mugJjAwru6wc4Sj0atfauS0zxFXdwQFGcYlxfR9R0Q4zsU/k6bVtyHUcHRzgbGL45SZ5EFWaQ/PCp5pPkZT1sDkfEc00TF4GBydZAiIFNDfwCV0MfjX2x/Lr2f8szUa3wCsfaCDwsYJIz5wSHavuAIOhfNhsGz8KKJfYP1FXlN77+misOfYQ8w4mHT4+fBjLL/0HFcjVPD0dMP/epfFzBJvdwthtEYXeysi1MpU3ncEWMpp+rAqWpuW3kTkfM9DcfheGB5Gyg9yQbVKgbhnpQVCgvW3REYgOG2rIlMXdhFzPv8E086FQ53/E8yc9QXcE2XI4ANj0HPmJSi9hmHBqOqwMYxPK83967gdaYPcue1gLvNQjO8B/G/kOKzyZj2YaTT3cf12JGxy54Zd3E7Hgf+NxLhV3knu6IiOioJO3+a3jOswKCUFLC0sYgO16Khow7ikmL7vgsCL3YPxsf5KmlkhVPdyg1Ljg9V9e2PF3TTczk5Er8VA7R1x8SoJ/8k1ERQ/TKoBvzGVcbqXJ8aUsYL2yTNMWP4vhqa5q/K0EAh8GIKbsQ3XCKzbfA1d1iYfbmPD07h5r/uG6f+g95nSCu2bFsbPH+uHQpjWLC/a5zWDmZykzmGH4d28cLlXUfTyePvnvJSxAZQkW1yp5WpNbGsMUKWlZ6rwQAz+1RsTLkfAumgBbB9RE4Hjq8tyVR3nP3dHBW0Ilm3+F60PhsJ4042yitiupVs1xeAdj4E8TfDjlsX4LH+iSytBuzCi11xcNa+GEb9+j8rpuEhiUXcWvAMf4+HjZ/C/9BsGVbdFwImF6PHRAPz5jNF+prCoi1negXj88DGe+V/Cb4OqwzbgBBb2+AgD/nwWd2JH0r+AP5ZWm3rdodEHAorYdzMaw/R9FwTCfR/imbknuizfg4N/zsOXHmro/LZhSPdf4M2KmOitMVB7RxTywGNnpYZ9/GBtBhcHa3h55sH4r8pihv6qliYcC3c/TltX5WkUEBITe9VOFxaKTaf9sdzIsMU37oXckfoXidL7TWGB2lXdMaheXjnkw7AmhfH7oErYUtsGFqEvMG35JfS7HNcpx9sys1DF3f6i0SG1zkUjYvTvYVPAWs77agK3TtzDkgABtYsb1n7lgQ9zGZZRmqGcV2FsaZ8beWWz7si+e9gQmsoXksmLurUefRo2x+i9/lB6tMacv//AoAqJrpfpArBtWB8sumWNWqMXYGj5dD6JYW5heJZRBfvSHfDTxtlo46JAzN21mL3ON3YKZTRzWBgeIFXZl0aHnzZidhsXKGLuYu3sdfA1VDxmOWxgpT93ExmeSt0hEBEZEVd32CZ7qXk8pu87obAphR6rdmFhh4Iwd/kIP83rjqJmAkEHxqDrpJN89p3oLTFQMwVKS3QonxP6w02k7wucTkO8ZPTYpRMpGtgqw2UN80IeODbcC5dfMZzvkDt2XspmlBZo/nFJTPVUywZTOBauuYZZj98+VFPbmcd2DqELjcZjYxlWp4FfiDY2zzrLeV9Nh5M+oYiSDbOSZV1QI8UVFAVcSudBy5xyzogXOPCAgVrWo8OzI5PQom4nLLwQCrtK32D9gfXoVTbZTY1BW7Fg9V3EiBhcnfcRPAsWRMH4oUgjTL+gr0BDsL1fKTmuCOqOOxG33GsoXT9Guzp2UIgoXDl/2TCWMpXSFR+3qwM7hUDUlfO4HBM3Wu3qBmeVzBEBfnhs7A46XTD8/ENljlHAOY+bYeSrMX0zgxLO7Sdjdtv8MhyO++zYbArm9ykBC4Ti9I/dMHIf+5QmehsM1ExEfEClb7VqUmtjKhSGW8R0iDYSzOnCYpD4tVf6xqubg0XsPf7a4GhEOduglGvqQwmHV/S1Tu83lTV6ty+E5rJNrIt8jrHrH+DiW15gNc9tg6L6xlZoBK6HGMnUunBc02dYhTmKu+hvvnwVHcJjROwJCltLGVDGjUxKoYaT/nUCQotQvh8wi9HBb+dQfNBiDPY+ViD/xzOxe99stDLWXahO/+yjTF8Rjif3fODjk3h4iEB92uvzgH/cOP179fQ0F1dgSLcOaN1vFYw/PqOGpZWZzFsCOvH2Jyoozooh3dChdT+sSuWZJbWlFcz0xVZ/otFQbM09S6GouQK6pzdxPcBIWmiu4dodOV7liuIl496yxvT9byiVye+GsEeDib9iYDkryOgb83oMwmY/7m+i9GKgZhJisPvaC0TIv9QymCqdWrykUMFWf+FBaOD7PO52xZcEfG4GG55He8m2kD0qyzawNvApFl+OTraMpA3D1Nn/wG70SbQ4xGfUsjOVUx7MauYAR9loCr3/AAP/CXu7zm2sc6Kuu1yZNkTm75R5L/pRIPYHyUrI2g71872uKlKhkKN57Autr94PQbBhbGL623sv6AM/pQUKGu9mkkxU2MlJaPvZbJwNsULp7mtwcGN/VE6tq33nr7DBNwABAUYGv5MY4yUrPIU92i5/KMf548yUWnHLxdzEnlW/Y+uypdhq7L19Uefwz6kg6BRmKFaqpGEkva2be1bh963LsHTrvdjb8JOKwrl/TiFIp4BZsVIoGX++xrE26paXB7voc9i9yy9l3XFxF/bf10DpUAP1KxlufWX6mo4ctTBmwTBUspHJcncV+vZZCR/jcToRvQZbM/+xyBchWP/nFXxzLhpaGYjVq+aCMslPUMVTWqKSu76xqsP+wz74Myj+8KXFnct30WVvcGywl5jSMTcGVrSAWkRj3R9XMPZqpDw0GmgisXnrNUyWB7XQaHPUKZbKvf6UTShQuFphjCykglJocXjPHSwx8mL1NFNaoYOXPexk/ty93wfbghOtKyYU8/56jCsyC3uUc0WzxH05R0biwr0XOHEvDL4JD6MrUbNiLhSWNVbg5XsY5Z3sOTptJDb+eR+7ZOa2cHPGJ3mNXnMjUxR+DBP170ILVsC97Xxsn98OHq+8uG8BWydnODsbGXLlhJVhWXMbBznOCQ42cSPU5dujfTlLIOIfzBz1O+4nbjjqnuHQD4Ox8IZs/Ds1xVcdChgm0Ntq374cLOWR6Z+Zo/B70p2OZ4d+wOCFN6BROqHpVx1QIP7YpyqCDl/Uk3XHC+z+cTS2PUpU2iP/xbwRC3ElRgWP9l3RzBDQM31Ni3XVEVg0ogbsFFo83joE3edeYSdPROnAQO0dCTh7FW4jjsIx8fD9EdiNO4dP9z3HI50CHmULY04NK8O93sYoUa9WXtSRjdpIv8doPfUkSv18DhUnnkDxJQ9wJ78r2jsbZk1ghpYfl8D4omZQhAZj4sJTyDvpLGrMOgvPcafQ9kgoQpUWaNPaEwNd2bjN9lQ26NsqL/QXJXThgRi3LSDhAf83p0CBKgUxvKAK2qd++HTWRfTY+QAz993Gp7MvYphsNKkcXDC1iX2SrtWjHj5A29nnUf2Xa1iUKFC0LFgAv9SygZU2HAuWnUWV5bfww4GHmLn7Fj6ZdQ5fnI6E1tIW37bJiwqpFyIyKToEbPwJCy5HQX9j69NdA1DR2RGOjsYGFzT6+YZhuXRQl8PAWcNQ2VaH++u+QvU6nTFi2i+Y/eMIdGlQEc2mnESIuhA6zp6FLxO/B4DeSrmBszCssi1099fhq+p10HnENPwy+0eM6NIAFZtNwckQNQp1nI1ZX7onapAoUaDLRAyvmRPaW8vwafWG6DF2Bmb+OByf1qiPYfsCofL4HFNHNXhZdzB9TYwFyg/9FWPr2UOpC8T+0V0x5RS7FiF6U6yt3hGdVougCE2SITgasLG1QiVPF4z+rDxOfekKz9c0MNWuebGpb3EML2uLQmYa3HoUjkdKG3RsXhpHv8qDwsaWt8qJEV9XxJ427mhdwBLq0DCceRAGP6UlqpfJi1/7VsT6ataGHrIou7PImw8z69jIwyzgd/kuvv/XyC2zaWVmi++6lsaUMlawCA7G4t13MPjPh1jvq4VTflcs+boY2udM4wkCpRk++LgsdrZ0RjlLDc5d9MXYbbcxeKcvNjzUIFeBPLHvfxtf8JWXY8ikROPM4RN4oc9gQoeokCAEBaU+hES83f1TtjXHYceOn/CZrD+fHF+JKd8OwMDvpmD54UewKNkGP2w7jOWfebziZBm9MduaGLdjB376rCxsnxzHyinfYsDA7zBl+WE8siiJNj9sw+Hln8Ej+U639MJ3m7ZiSutisHh4CIt/GIrB303H+gsv4FS5B5b89SvauyVtwjB9TYx5KQxYMAmNnZQQIacwtdso7GffIkRvRCEkw98mQaFQwMR+EmVBzEemRiD46QsceRCJZxolXFxsUTu/5Ru/pDhBTDT+vfcC3kEaxKjV8HCzQ1UX82x9soF5/k2Ew/f8MZy44oswpR3ci1dF9QpusT3vZmWmngfCfc/j2Ikr8A1Tws69OKpWrwC31+50HYJvn8CRs7fxLMoSLiWqobZXvtfUHVkzfVmGTQPTwbRk9/RgoEbvJeYjym6Y54l5IGtj+pkGpoNpye7pwVsfiYiIiIiITAwDNSIiIiIiIhPDQI2IiIiIiMjEmOQzakRERERERNn5GTWTC9SIiIiIiIiyO976SEREREREZGIYqBEREREREZkYBmpEREREREQmhoEaERERERGRiWGgRkREREREZGIYqBEREREREZkYBmpEREREREQmhoEaERERERGRiWGgRkREREREZGIYqBEREREREZkYBmpEREREREQmhoEaERERERGRiWGgRkREREREZGIYqBEREREREZkYBmpEREREREQmhoEaERERERGRiWGgRkREREREZGIYqBEREREREZkYBmpEREREREQmhoEaERERERGRiWGgRkREREREZGIYqBEREREREZkYBmpEREREREQmhoEaERERERGRiWGgRkREREREZGIYqBEREREREZkYBmpEREREREQmhoEaERERERGRiWGgRkREREREZGIYqBEREREREZkYBmpEREREREQmhoEaERERERGRiWGgRkREREREZGIYqBEREREREZkYBmpEREREREQmhoEaERERERGRiWGgRkREREREZGIYqBEREREREZkYBmpEREREREQmhoEaERERERGRiWGgRkREREREZGIYqBER/Z+9M4GLqnr7+G82ZhBZXBAQQURCEXADTMtdNMVXDXdNc80008RcWtRcSjPLzErrr1kuqYGgAaKJJgouoAWipBQKllsqboiAzPC8584MMBs6F4bCvN/PZ0rOnDn3nOc825k5514BAQEBAQEBgRqGsFATEBAQEBAQEBAQEBCoYQgLNQEBAQEBAQEBAQEBgRqGsFATEBAQEBAQEBAQEBCoYQgLNQEBAQEBAQEBAQEBgRqGsFATEBAQEBAQEBAQEBCoYQgLNQEBAQEBAQEBAQEBgRqGsFATEBAQEBAQEBAQEBCoYQgLNQEBAQEBAQEBAQEBgRqGsFATEBAQEBAQEBAQEBCoYQgLNQEBAQEBAQEBAQEBgRqGsFATEBAQEBAQEBAQEBCoYYiIof33E4QKf8aswGcHrrF/mYekSX+8Na076mT+gCXrjqPA7yW8Pz4QVtr3/3nycT/fBrVttH/yRZmBbYvXI6WoFV7+YCzaSLXlFaE8hU0LvkOqKACffjBKW/hvosTZH5Zg3fEC+L30PsYH/nszUdNRnuWns6rMCLz/9VHks/ofsfp84Xs9i6I8ix+WrMPxAj+89P54/OfVosbZ5T+IMNdVpAQ3DqzGhzF/wbXvHMzo6QQxi4iZEe/j66P5Rn5VmROLpfNWYueJi7gHG7gO+BC7PwqBdQXlttrPCQgYUtUYU62YsjNVJiLe/xpH8/3w6UfjNWX/EiU3DmD1hzH4y7Uv5szoCSezfi6p2K6rhfz7yLepzbyBlqfNV9c0uIXak0cRJb/lS2xtwi0yzXrJOnxIfyiJCuMmkqtERIoXN1O+trV/mttpG2lGd28a8X0VelAQTeOcxCSqPYi2mtNMfgSNcBCRuO5L2oJ/m0KKm+hKEpGCXtz8b83EkwFfnS2Mn0xu2vqV4V+1kcI4mugqIZHiRXoq1KLG2eU/iDDXVURJ55a1JxlkFLgkg/3FUUjxk92M/WpxGi0JsiYRi4UiWS1ycLAj79cPUGFF5dqPCQiYoqoxploxZWeF8TTZTeNr/m2U55ZRexnLSQOXUIbGaM2gAru2OLcpbeMM6u49gvTS06fNV9cwntCtj1bwmbAOe+PjEV/22oft09pABhFqdVuA3XrvxWPvZ8PRSKL9+L9KEZLXvIvPD15CIbeEFBCwMFKPXnhtzlzMGuinLREQEHg6kMKj12uYM3cWBvqVf+1dcvUQfj5VAFH9/vg68zZu376LzM+7Q1ZBuVz7OQEBUzxxMUbqgV6vzcHcWQO1BU8apu3a4hQlY827n+PgpUL1LxwCNYMn9oyarVcH9AgORnDZqwc6eNqxZRogqd8CXfXeC0b3oMZQaD4qIPCfRuIVireWLsOS0a21JQICAk8HEniFvoWly5ZgdOvy/fCUdw95LPOSeLVHZ/fyRK+icgGBR/HExRiJF0LfWoplS0ZrC540TNu1wNOBZCFD++8nHMLd4xvx+U8XIfUdjFlD/CDTvqOLKisGq7eloqBZKOYOb4rLSTuxbftOxB1KxcUH9vDwdISCW+0ZUYSrqXsRGR6FmPgkpF24BZmTBxra8jAaZQbCl36OyIQjSL9axAqKcTUjFffd26NZXc2aWXnrHBJjd2JXbBz27k/EybOXUWjbCO71rfVX1crf8eOq7Ugr9sGg2YPgmhmHrZsjEJeYjkvFdeHeuK7+OIp/Q+TKCGSI/PHeXONvlYqupmJvZDiiYuKRlHYBt2RO8Ghoi0q5BGUuMg5EITxiF/YkJONMzh1IHN0NZKVCVsxqbEstQLPQuRje9DKSdm7D9p1xOJR6EQ/sPeDpqFAvvI148CeOx+5AxM5Y7D+ShuzbMjh5NERZ86oc7F61Epv2/gGrVm3gbl3eiirrR3yyagt+Si+GV5AX7MuEWoIr+7/Ax9/uxeU67dHSRdOYMjcDB6LCEbFrDxKSzyDnjgSO7jrXehwW6Ivv/T28dFZ1PlrdbvyVeuja0llbWooS19PisCNyF2L3HkZq9j1YN/SEs025dlXeRh6P8noa4nZEMv3ei8Op2bhn3RCezjbluq3KQszqbUgtaIbQucPR9HISdm7bjp1xh5B68QHsPTzhaPLiStw6l4jYnWxccXuxP/Ekzl4uhG0jd9S31rEc1e/YteIzbDstgm+AOygnEVHbwrFrbyLSLxfDwb0x6ukJk2d9HcyyqUfYZZV1z5DH2Y0aJTKjPsJn2zMg9WsBStmC9Vv34ZdLKjTw9EAdHrm8MNfmz7U5qHLTERfOrhF7EKmXS+Dk6QZVyrdYe+AqnLtPxsTOjuozauejP8GqLfG4Uq8jWja4gYNrV+Cb2MNIOpmNPFaDbmXi2NHzuJgejcg4g/LjuXB+zheOpWIsuorUvZEIj4pBfFIaLtyqgs6Y1ZYKv+9agc+2nYbINwDulIPEqG0I37UXiemXUezgjsb1KogLZvi2Mszqixaz4hkPlLdwLjEWO3fFIm7vfiSePIvLhbZo5F4fuuqrzIzCR59tR4bUDy0oBVvWb8W+Xy5B1cATHjqGaInYrcwIx9LPt+PnS3Zo16qhUe5UcmU/vvh4A+LOiZlteEBxoYIYY46stHnQ9kQDXeMoyUXi/5ZjXcw5SNj8e9jozrSZdm/KzlTnEf3JKmyJv4LuXVtqytQokZtxAFHhEdi1JwHJZ3JwR+II9wrlxzMPVOUiPS6c6VksDqZeRomTJ9xUKfh27QFcde6OyRM764+/Qgzs2pl9qAr+yhQaHYhEwpF0aNLTq8hIvQ/39s1Qt6SyvtoCebMAW978Z1DRxU+7kBVEZDtke4Vna0rP38h7hNHifh7E8mb1GTb1SyQjp84L6Odclba2BtX1Q7RsgBcxn1Fel71ENk2p/9JDdF2/esVo907rtgGJG02OL2QXuUb7F4WQp41YfV5At45IUofaTo2iP3WvU3pGzaYXhb3bjVxkOu2ycdQPmko/nC/WVmZUdD5CdZ0OLRtAXjYG/RLZUNP+S+mQ2YPTUHRuI43xtSOxoazkjajn4gQqF23pGTU59QhbTP08NOckyurLnKjzgp916nMUUdaOmdTFVW4gIxHZePalRfuvMi3guE1bh9QhsbgejYi4py7RoKQ/lj9HMtY3kU0Irftbp3HVFfqqtw27biAtOcNtHC+icxvHkK+d4Xww3WnUkxYn5Gqv9Tiq3he+OlvR+YHii9E0t4c7WYt155rphJ0vjV5/usxmKmMjj6X4IkXP7UHu1vryFIntyHf0ejpdfnHNXnh5Dwpb3I88rPX7KnPqTAt+1pe96tp+WhTiSTZ649LUl9RpS1Oj/iyvr21fFjCHNnzQm9zlhu13ovm67fOtz8HHpkzapaV0rxRz7YajgKLHOZFY1pbGvdGDGjA9UNeVuNDoqNvaOo9BmGsec20OefTrl8PJx57JSqc/Nt7DaP7EgEefUStOp4UBMv2+sZfYIYSGtjFRXmck7Sjg2lHR9UPLaIAX80N6ddh1m/anpYeu68jhcTrDpy1tXJAF0JwNH1Bvd32d5eJCp/mGccF838avL3zimTmo6Nr+RRTiaWPUHkQSqtN2KkXpBPmC6HHkJJZR23FvUI8GpXMvIZfRUSyqMCwYu1VX1lFfOyavBiMp4o62sAwlZa3oRAqRlJq9eYR5EzZLJmKM2bLSsYMota7poDxHy9ozveRin84BLl52b8rOTJ1RKzpHG8f4kp1hmywnadRzMSUYTC7fPDDv1y9puI89s0Xdut40bP5ECrDEGbXK+KtHkB8xghwMxiZxm0xcelopX22pvFmAntKFmka5rNyCaebaaDqamkZJkctooBcLCiwR9Zl9VO2M1BT+Sks72jPno6Amfd6i9XuOU3p6CsVvWkCh3rVY8uFAnZefKq//SFjSnX+LoidwCxRrGvDtTbqfX0BFTGEvbxrEnDLrU+MQmrdxHyWnn6HTKftpy6KB1KwWMwqJB722X8eraRdqasWXNKDnX19LcclpdHL/d/RWz0ZsAcACT9BCOlF6KtxkklBIvy7tSPbsuoomfeit9XvoeHo6pcRvogWh3lRLJCaHzsvplHmDY8PLotU97Fh/nKjLmxtob3I6ZaQfp91rp1C7OixpkzWnWUdKO6QNyJzxiqzILXgmrY0+SqlpSRS5bCB5MacjkvnQ7KOlF1fRzd2TyduKlcs9qPfcb2hP8ik6dTSGvpzWmVykrNw2iBYcu6+u+/c3/ciWBb/Gr+1nV9Ki+pvW962tCXjiBvTyLh0tubWFBjL5yFrNo1/Z+laZtZp6sMAlcepCb27Yy+Yjg9KP76a1U9pRHSYvWfNZVDaUR1L1vvDVWZMLtYLjND+AJSesrmu3mfTV7mOU9msiRa4YTa3s2dxYtaA3D2v6wNtGHksBHZ8fwBw2G5NrN5r51W46lvYrJUauoNGtONuyohZvHtbYrDYgqPXayo2CZ66l6KOplJYUScsGepGca8NnNpWrxWXaNIgliayNxiHzaOO+ZEo/c5pS9m+hRQObMR1mwcbjNSozHW37YmsbslE0phfmrGd6eopSD/1AS0K9WDLC2vd/h5JLv+PgW5+vTZmwS8vpHgcfu+HQJt1sXGKZG4UsiaJjJ4/SjxtjKMOsCRfmms9cPx62sNg1njzYPIntW9GYT3bSkTRmi1FMni05ebL5e+TNRFRUXJBP904u0CSH7d+n0/fuUz6LO4Umy4vU7RT+upQ6cn5B0YT6vLWe9hxPp/SUeNq0IJS8WTwSO3Sm5WUDe7TO8GtLGxfE1mRjo6DGL8yh9XuT6VTqIfphSSh5Kdh4Zf70Tvkk8PNtfPrCK549HtXlTTSI+3LVqjGFzNtI+1h7Z06n0P4ti2hgM5ZLsEWYB4sRpeqrWaix8bLFmlvIEoo6dpKO/riRYtSGaOHYTTdpy6C66i8Uh22/pS3TojxLS9tbsfG2onlcQGIYxRg+suK7UONr92Yt1Njic3UPsmNx2anLm7SB6Vh6Rjod372WprSrw64lo+azjjApa+GZB6qu76LxHlJWbk+txnxCO4+kMb8WRStGt1TPmYj12VILNfP91WNQFlL+rWiawNoUWQ+gb28yf1BQxDwIg6+vtmjeLPDULtREiiBamKbvZPNiJ1Aj9p7s2aV0Vm1AKrqyoT85iMVUL2QtZRkovCpnPfWrLyZx/SG09aa28LEU0t5JjZjB1aLQLeW9XNlFwZycB03ao/urC0cB7Z/iwRY0Mmq/7Jw2GDNKF2rMefnPOkR6nyo4SQvbccbgyJxurqbMhPNSXdlA/R1Y/+uF0FrjwdH6fvWZ465PQ8wd3P0tFMqCnfSZGXRYzwKVlLk6lPwDutGUrTllCYVmocacPVtQ6k9FHsVOYDJiY3526VlN/eJ0WhzIgoW4Lr3wRSbp97aAfl3SgWozZ2Hb80vKYZ5FdelLCmZ9kfm/SydLK+dF0ihHCdVu+gzTASl5a78d5Li/awwLilJqrl2A3N8SygKAlJ6ZcVjfmSgzaXWoPwV0m0Jbc8zzslXtCz+dZfWNFmoquvbdAKbHbPHefgml6jWhpAtfBLOAJSbHlyKZ5Plf73Gorn1HA5ieiWza0xL9i5PywhcUzH2T6/gSRWourgkIzMEHLUwrD5QcebE0oRF7T/YsLdVeXHlhJXVhyZvEYxIZm85+muLB1W9Py86VCqe0fTkFGrUfQ+O596pQn7dNmbBLS+oeX7vhytRJN1iiN+BbusbzW09hrrWYOdePRfkbS1zlLDY0pGFbr2iSJi2qK9tpBNcnM+76WHxmsWZBpr37cSkmy1VXaEN/B3XSHrI2y0BnVJSzvh/VZzGx/pCtLL3neITO8G6rPC7IA43jQsx47j3dWMjDt/HtC6949jhYX1Z2YckzW4xN2qMfrxkF+6eQB+dX2y+jUnXULNS4Xz9Z0mxgiBaP3Yw7kaPY9cRUZ9AW0mYNaopPczoiIqt275ctLIxiDB9Z8Vyo8bZ7sxZq92lLKMuRpM/QDP0OMze7mkL9A6jblK2kcbN880Al/basPVu8SKjhsK10xcAeto/QfEFtqYWa2f7NHAr30iTmd0W1QkknPdW5ljm+ujry5qcbs3bH/heR+vXDYD/9e1vVCmiL5pwF5f6NG+oHtN1FfPRB9t+66D1hNJoabKsVNx6KEV3tQLcOIu7wA21p5ZgWcx5nT+7B4p6GT6+RoZGbs/pcR2FBAfczhx4ieSdMmt5R/5k3ijZ4dUJnWFMuDsQe0hYaczc+GgfvAnV7T8Bo48Fh6IiusKNbOBh3WFv4GKTOcHYUQ3VhG+bNXYf4jOvgtjpzB2G9p0Uh/eTPWDOiMftLFyn8+g2G/lTUQkDb5qweIffvG+CmQpUThz2nHkLsEorp47wN9o8r0GbqdPSpI8L9I7HYd7MEYufe6B1gBWXmIST8qXnaXtHJBBy9LUPQhFfRzkaF7KOJ0LxVhOP7EnCTjblX3wD1c8Okzs5wFKtwYds8zF0Xj4zrmpFA4o1pUek4+fMajGhs3m1Eq9qXUszTWVM8wKE9h3CPbNDtlVfRWq8JCZqM3YBjZ7Lx+4aBqK0t5aj89fR5cGgPDt0j2HR7Ba/qXxySJmOx4dgZZP++AQP1L45+g/307z5XKwBtNRfH39qLS5pMQ8z5szi5ZzGMTacR3Li9/ChEQYGB5Uj9MWCIYfv+8GvKtX8Pd+4YDM7M+pawKUvqHl+7KUcCv46dUZ9nhBDmWktl/KcJSi7tw0+pbP5c+2NiqEv5+T4GN6evDW3K6yySWdyNR7RmYJgw2rB9MRoPHYGudoRbB+OgH/ZM6Eyl25LCf8AQo7jg79dUHRfu3bmjjgu8fBvfvlQqnlUE68u0GJw/exJ7Fvc0ekadrJEbNOpbAEP1lfh1RGcDQ6wO3bN/YST6NRTh7oFIxN4o9QVKnIlgY1Uq0GHYCDSraLAWlZU+lbb7RyKFs7MjxKoL2DZvLtbFZ6DczU5DVPpJ/LxmBDRulmceWHIJ+35KxUOxK/pPDIWLvtEi9LWhRm1UCb7+rSqY5av/ubz5aUHf+p8ixE6ucDXwGmK5FWTcXjSVCkrO5pXnkXm+EFRyE98Pqg2RSGTwssPIHXfY+/fwZ851TSOVRGrbEM1ae0GWlYToLV/h40Vz8drLL6Jbaw8ELUhGMatTUmLsiCSN/NDS6ImJYtRt4YNGkhLczc7SlhmixPnM8yikEtz8fhBqG41NBLuRO3CHvX/vzxztZx6DvAveeKcvGoqv4/CqSejl7wpH90CEjHsbqyNPaA6oGiGGk6urgQMXQ27FPWiBoFIp1YtTZVYW/mSxQ9KsNdqYun2nXSu0Yo6JHl7E+Wwlq9gYfXq1hLQ4DQcP5qKEjTcz4Qj+ErVA5z4haO8nhfL0ESTeYZ99mIp9By8DLj0Q8qxmaSTv8gbe6dsQ4uuHsWpSL/i7OsI9MATj3l6NyBNXtUHITKrYl1LM0llTqP5CVnY+SiRu8Glhry3UwcYNLVq4w0H/cpW/nh4q/JWVjfwSCdx8WsD46jZwa9EC7sYXh6vxxWGluThUZReXwrZhM7T2kiErKRpbvvoYi+a+hpdf7IbWHkFYkKy2HBiZjtjZuH1Yw1qtW6x93TULh1n1LWNTltQ93nZTikgGRxcnnomVMNd85/pxFGf9jmw2fklTH/gYiI17TI1/y2Zqe7QkyvOZOF9IKLn5PQbVNh6XyG4kdtxh79/7EznXdYRnQmcq3RaLAc5GcYHNgmYSWFzQ1uXh23j3pVLx7BFIbdGQ2aGXLAtJ0Vvw1ceLMPe1l/Fit9bwCFoAjfqWGHwZK4LM0QVOeoKoJt2z6Y5RAz0gvvszdsTcYJbEUKYiPCoDSptOGDbEo2J/YGlZ6VFJu38kcnR54x30bSjG9cOrMKmXP1wd3REYMg5vr47ECd0O880Di7PwO/OlJGkKH2OjhZV/SzSzpNHy9W9VwRxf/Q/mzU8LT+lCjSmLzErv1wqTlBSigHvYmcQJQYPGYOzYsRW8RiPY21QWZD5FWREI69oErj6dMGD0FMxeuALropJxrXYA+nZyN/j2Twcrhf63G1rEcoUmgCt1ki89SlBYwD0rQwKnoEEYY3JcmtfoYG/tZx6HFM0mMSeX8A3mj+2FVi5yPLj0C/Z89yHeGPwsmvoMwKcpedq6WpjhyqweOxOgood4yKZCpLCGwqTWyiFXC0IJpfoLJAm8+/RCc+kDpBxMwgPVFSQc/g3U6Dl09WmKrp2egeTBCSQeK4Tyj3gcyCpBgx590bF0GqXNMIkFmIRv5mNsr1ZwkT/ApV/24LsP38DgZ5kDHvApDIdSMVXsixozddYUVIRCLu6IrKAwLTwTVOF6ehCKNBdnqqow2+GIWNJnhlowipAVEYauTVzh02kARk+ZjYUr1iEq+RpqB/RFJ3fTliMSSSEzdVvYUgyCvnn1LWRTFtQ9/nZTCpt7K77JhDDXpl7m+09jiMlTPX8ylgyZEKjMxsak/68KJYUF6md8SpyCMGiM6TGpX6ODoR/2jHWm0m2xuCA1Z9J4+Db+falEPHsURVmICOuKJq4+6DRgNKbMXogV66KQfK02Avp2QgXqy2RqxSxKl+rSPTk6jBwMb8k9JERG42+W4D88EY6oc0rYdx+Bga6Pkq+lZMUdx9H+s4zK2f3jkDabhMgTCfhm/lj0auUC+YNL+GXPd/jwjcF4tqkPBnyaAnWP+eaBVIgijdFCbtpoYWNBo+Xr36qCWb76H8ybnxrUGyD/E/C76yO3t9qozq111EcOkjR5nX7mNuEqM2hJoIz5wyY0VV1gCUyfUZvfxppEIgV5hsymLyIO0InMa3RfvbVYSRlLAtV39mo572T5vnrtGTVJwwkUZ6JrBdFj1QeRa/3fBk2B0b7t0nYl1GTqz/p7ji1GAV09tY82rwijUD8H9WFzRful2n3Z2rMIBmcpSrm1rg/Jub69rulbUWIYeUu5fd2LSX1TRkOKEinMW6rek720dE92URLNZGUSj6l04NoWGmgvoXojIzTnsPZOokYS7hxYEp37uBPJxfVphPHtrsopuEqn9m2mFWGh5MedwWH9br80Q/umGVShL7x0lmF0fkB1kT7tYsX02I1e3WdippXn6eD2KNqXnK0+O8H3eo+m1C4l5PbqPhN6pqTzB7dT1L5kytZcXL0XnjtLYKwWt2hdH7naHl/XXrwweT61sRax+p4UMvsLijhwgjKv3dechSi1X1lLmld6OPBR7av+prW9mJykzWjWEe25BV71K2FT5pxbqoLu8beb0htDONCwcKMJeAzCXD+SSpxRK055m/y4M2RtF1J6mfMvRUV/f9WL5CLLnlFTZiyhQFYmaTLVTBuvWGf4t/WouMDGu7YX0y8pNZulPdPLw7fd5t0XQx4Vzx5HISXPb0PW3Gc8Q2j2FxF04EQmXdME+TI5yVrOKzvHXHozEYdh4QZ+uBpjd/Epeq+tjES1e9NXlwvo0BteJGXxaGjpWXctJm9YpccjZFWwg0ZyNxhxGE5GLqY4hd721T+jxtvuzTqjZkzB1VO0b/MKCgv1U595FCmYT+T6wDcP5Mbgx/WpLS00NlrmSr6iXnKRxc6ome3fzOExZ9TM8tXVkjc/3Zj7pefTicQTgW2cIFH9hfhdx2G0m7bkL4TPGoIRE2djU/pDbeHjYU6L/Vf3a46HiDxdALHbGKyJ+AhTB3dHoLcTbNS/MOfh9JlscF92m9r6qLqRjCSja+fjyN7DyCUpWrRrpy0zRALPwDZwkqjwV/wuHDceHP4Kn4UhIyZi9qZ0bdmjUWVGYtHrYzFm+WGtrBRwbtkTo2atxI5976ObjI309wyc43Yq8MTKNwgtbcVQZuxDXJbxnuuiU3HYn62CxKkl2pae37EKRJ8ersDlQ4jbeADJ9+UI6tIRtdhb8vbd0MGuBOcPhmPd7pMotuuMkO6lW2dUyIxchNfHjsHy0j3UCme07DkKs1buwL73u0HG5uz3jHOa98yh0n2xAGJnBLR2h1R1DUcTTrOe66NM24Dpoweh7/RtuGws2ioihnNAa7hLVbh2NAGnjS+ODdNHY1Df6djG++IPkRYVidMFYriNWYOIj6ZicPdAeDvZMO1m5J3GGaYTnC7z2xZTWSxhU5bVvUrZTaUR5roc/v7TFNIW7RFYn83f2QPYd8FQZneRkJCGYguPV+IZiDZOEqj+iscu44GxsBeOWUNGYOLsTXhc2LNkWybh4duuNebXF4vGs4dpiIo8jQKxG8asicBHUweje6A3nDRBnqnvGWjU13DroymqUfekvhgxNAhW+UexOyYOO2JzUOLUFyND6mormIaXrETWsLZm/y+4g9v56spllOSewqmLuruAqsnuVZmIXPQ6xo5ZXnY2UuHcEj1HzcLKHfvwvqbDyOA6zDcPlLZA+8D6ECvP4sC+C+rcTZe7CQlIs7TRWgwx92N21X6Fq6a8+WlGWKg9EgW6TXgZvnIV/lg3FTN2ZOucD8nH6a+nYeaqSITH5EDSwNyf30WwknO/+6lw68ZN5l44xOB2jNCD67h2R3dDcSGytoXhvV23WD3Cw6KH2vo6FP+GNTPeR2Ju6TtK/BUzB2HfZqPEvgcmjGquLTdG0W0CXvaVQ/XHOkydsQPZ5YND/umvMW3mKkSGxyBH0kBb+mhEiqtI2rgJWz58D5+d1N3moMLlxGP4g3ksqWczeFdmp0KdEEwY0hiSwqNY/iobb9lhZzbiy3F4e8oXOKOUwXf0eHQt+zVdjg59uqOB6iw2fRqLa2J/dFI/FJZh2wXdguQskK/DmiNFsOkYgp4O6g8xRFBcTcLGTVvw4XufQX8ol5F47A82Iik8m/HcVlKpvlgCK3QYMxKtFEpkrJmJpUmcPmnJP40189chQ2mDjsMG4Zmq5uomsOowBiNbKdhiYQ1mLk3CrfKL4/Sa+ViXoWRjHoZBvC8uhpyzJWYbD65fg77pZGFb2HvYxV2MHqLooe6b1UfVbcrCulcpu6k8wlxrqIz/NIlNL7wyugVkhUewfOonSOHOsap5iJyIWZgfpT1LZEkU3TDhZV/IVX9g3dQZ2KE/MHw9bSZWRYYjJkeCx4Y9S7ZlEh6+zYZfXywaz8RyyDVBHtev3dGbs8KsbQh7b5faVuhhEcxR3+rTPQmeGTYcz1vfR8LKedh1kdCo/wjjm3gYwEtW0ubw8WT/KD6O7RvPsCxHS9F5RLy1AvvzdVcJ1WT3IgWuJm3Epi0f4r3PTmq2OGpRXU7EMU2H0UzdYb55oA16vTIaLWSFOLJ8Kj4pN1o8zInArPlR0HHDNQuRlVpPSXULN/RuLsWH6sibn3K0v6z9B6iGrY9q8ihlRU/N84bEtcm9XR8aPDSUgts0JAXTZ5G8KY36Plu77cQcVJT9aVfNZ21cyS8omBYcLKSPuziQmPW9VuNONOzV6TR98svUL6gR1ZLYUfOgFupbnTYY8yOV3c22dOujkz+1dJGSlVMr6jlwCL3Y1ZscuL6yfo3YqHML4gq23eSlrKCe7PMikZhqu7ejPoOHUmhwG2qoEKlv+9p01PeUbfbg8ihxXiDZirlbu7tQ6+BQGj5yKPXv7E11ZKxP1j40Jbb0gaL8tj5yqG7up7ef5Z5xIiJZPR/q9uJQGtKvI3k5SFj/peQcvIJSuL2EutwJp+H1NM+bk3q/SeW7AJR09oNnScbKIapFPddc0vZLS14izQu0Vc+JwqU1BYcOp5FD+1Nn7zrqZ9RZ+0yhWL5PbKxkX6q89VHNfUr5qAc5cbohcyS/7qE0bEhfetaNe/iqhBoEryy7FbZltz5quJ/yEfVw4vRMRo5+3Sl02BDq+6yb+gGmkgbBtLL84ry2wxWf+Zi6OHCPqahFjTsNo1enT6fJL/ejoEa1SGLXnIJacLfjbkBjftRaTrVuh9PAy6ZM2aWFdY+f3VRl66MGYa55zLU53DtCi55n86fWh7b0ArvGgM7PkL1ETA716pDUwlsf1eSl0IqeLqxt1t/a7tSuz2AaGhpMbRoqSMT6IW86ir4vG9hjdIZXWzy3Pqox37fx6wufePY4iunMx11YHGdt1WpMnYa9StOnT6aX+wVRo1oSsmseRC242+03GEOl6lvx1kcNlo3dOqiu0LoQOyYPFo/Ut68vFV45xjGGj6xUdHnzYHJmnxeJbcnz+X40eGBvCuDsuE4H+r9ODUiss/WRt92bsjMTWx/zEudRoC3XroJcWgdT6PCRNLR/Z/KuI2MytSafKbE6D2XmmwfeoyOLnqc6Wnm0fYHp2YDO9Iy9hMQO9agOa6dGbn1UZdOnXTW2YOPqR0HBC4ilp4++lglfzV9eAo9CWKjpUmESWkg58StpckgAedSzISupjGwcPSlowHRak3iVv7LdOU6fDmlFzrU0ycxzy/8g1fUkWv1KD/J1sVO3X6tuY2rT+xVaHvMH5V38gnpwzyjxmkYHS1dq2oWa1GcOHTz1Pc3s40cutlZkZetCvj0n0aqEK/r9ekSSUJgTTysnh1CARz2ysZKSzMaRPIMG0PQ1iXSV7+BUuZSy/k0K7eBNznZykkrlZOfsTc8NDKOvjvyt0yf+CzU1eWcpavEY6u7nSg7WMpLbO5PXs6EU9uVBumTSH92kjS/aM8cjJuex0XpzXnR0FjWXco60C628YDxQVW4KrX8zlDp4O5OdXEpSuR05ez9HA8O+oiN/8551RuX6YpmFGkcBnd+9jMb38CdXBwXJZDbUwLsjjVy4kzJL9YpRHQs1joLzu2nZ+B7k7+pAChmzoQbe1HHkQtqpf3GeAUFF15NW0ys9fMnFzoqkslpUt3Eb6v3Kcor5I48uftFD/Uwyr2kHNdX/geSdw2ybqsAuLa57ZttN1RdqHMJcmz/XZpH3G+1YOJI6qvVBTrYN/aj3tG/oyP8GUu3qWKhxFOZQ/MrJFBLgQfVsOHnbkKNnEA2YvoYS9QZmhs6Y3VZlFmoc5vk2NWb3hWF2PDMD1XVKWv0K9fB1ITtOT2rVpcZtetMry2Poj7yL9EUP7rleXjRNG+Qft1DjsGjs1uH65oFUly0yZL5vU4rxMSvTMYaXrPIofcscCg1qQnWsrcjawZ0C+s+izek3NWf4dR94zdfuzVyoce3mpqynN0M7kLezHcmlUpLbOZP3cwMp7KsjZOxm+eaBefTbjoU0sqNGHnLbhuTXexp9c+R/NLB2DV2oMe4c/5SGtHKmWuovPp6j5Zxj4O2rOSycNz/FiLj/qH9aExAQEBAQEBAQEBAQEKgRCGfUBAQEBAQEBAQEBAQEahjCQk1AQEBAQEBAQEBAQKCGISzUBAQEBAQEBAQEBAQEahjCQk1AQEBAQEBAQEBAQKCGISzUBAQEBAQEBAQEBAQEahjCQk1AQEBAQEBAQEBAQKCGISzUBAQEBAQEBAQEBAQEahjCQk1AQEBAQEBAQEBAQKCGITzw+rGU4MaB1fgw5i+49p2DGT2dhNXtf5SSGwew+sMY/OXaF3Nm9IRTpSZaiYxti7E+pQitXv4AY9tIteUVocSpTQvwXaoIAeMXYZT/4+r/1/gPjF+ZgW2L1yOlqBVe/mAsHjvlAhWgwp8xK/DZgWvsX+YhadIfb03rDseSs/hhyTocL/DDS++PR6CVtoLAU4FlfHf1oTy1CQu+S4UoYDw+GOWvLX1KUNYw21SewqYF3yFVFIBPPxilLayYfycv+IdQ5iB26Tys3HkCF+8BNq4D8MGnQfj1+6PI93sJH40P1Fa0MPn3kW9TGzbaPwUeA7dQE3gUSjq3rD3JIKPAJRnsL4H/Kspzy6i9DCQLXEIZlZ7oAooe50RiUW0atDVfW/Yo8ilihAOJxHXppagCbdnTxH9g/AXRNM5JTKLag8isKReogCJKfsuXWArDfXlo1kvW4UP6g7PVwjia6CohkeJF2izMwVOHZXx39ZEfMYIcRGKq+1KUtuQpoqbZZn4EjXAQkbjuS9qCR/Pv5AX/BMWUtiSIrEXMl4pkVMvBgey8X6c9uyeTm0REihc3a+tZktuUtnEGdfceQd8LftpshB+HBAQEBARqAFbwmbAOe+PjEV/22oft09pABhFqdVuA3XrvxWPvZ8PRSKL9uICAgICAeZRcxaGfT6FAVB/9v87E7du3cTfzc/T07oXX5szFrIF+2ooWpCgZa979HAcvFaq/aRMwD2GhJiAgICBQI7D16oAewcEILnv1QAdPO7ZMAyT1W6Cr3nvB6B7UGArNRwUEBAQEzIXycC+PLZckXmjf2R2lO1IlXqF4a+kyLBndWlsi8G8jWcjQ/vsJQ4nMqI/w2fYMSP1agFK2YP3WffjlkgoNPD1Qp1Triq4idW8kwqNiEJ+Uhgu3ZHDyaAjbCrYIq3LTERcejqjYg0i9XAInTzeoUr7F2gNX4dx9MiZ2dqye1e3Da/gldju27YhFwi/ZuG/nDs96N/DT6k+wOTEP7u2boS67sDIzCh99th0ZUj+0oBRsWb8V+365BFUDT3iUDZobdir2RrJxxMQjKe0Cbsmc4NHQFhXtjDarvup37FrxGbadFsE3wB2Uk4iobeHYtTcR6ZeL4eDeGPUUXEplAZS3cC4xFjt3xSJu734knjyLy4W2aOReH9Y6E6D6fRdWfLYNp0W+CHAn5CRGYVv4LuxNTMflYge4N64Hk11S5SI9LpzpRSwOpl5GiZMn3FQp+HbtAVx17o7JEzvDsVITrcTvP67C9rRi+AyajUGumYjbuhkRcUxGl4pRl8morl6HivFb5EpEZIjgP/RNDPRhEldmIHzp59iemAvn53z1+1GSi8T/Lce6mHOQ+AbAw8ZgcDz1nT9KXE+Lw47IXYjdexip2fdg3dATzjYmhPXgTxyP3YGInbHYfyQN2bdN9cXE+HUxqw0lMsKX4vPtich1fg6++gJDbuL/sHxdDM5JmI542LCk30zfYS7K3/Hjqu1IK/bBoNmD4JoZh62bIxDHdPBScV2mg3VN6yCDn50qcetcImJ3MtnH7cX+xJM4e7kQto3cUV/fKPTstOT8zwjfEo7o+GPIvG0D92ecoZ6ukrvIPBCO73+IxoET55Fv74GmjtbqRZEuytwMHIgKR8SuPUhIPoOcOxI4ultSpx4F4e7xjfj8p4uQ+g7GrCF+kGnf0UOVhZjV25Ba0Ayhc4ej6eUk7Ny2HTvjDiH14gPYe3jCsYJJ4OsrzUOF33etwGfbTkPE7NS95Dx+Dt+C8Oh4HMu8DRv3Z7Q2U4K7mQcQ/v0PiD5wAufz7eHR1BHWprrK07aVt84hMXYndsXGYe/+RJw8exmFto3gXt/aOIYpc5FxIArhEbuwJyEZZ3LuQOLojoZ6jVeTnfH1WdXhu0t97s+XYNeuFRoaKlnJFez/4mNsiDsHsa7fNTNOFf8WiZURGRD5D8XcgT7qMmVGOJZ+vh2Juc54zlc/ryjJTcT/lq9DzDkJs2EP6Lv5IlxN3YvI8CjExCch7cItyJw8DOaqnOq0X7ParoJtPvjzOGJ3RGBn7H4cScvGbVO2yTdeFv+GyJURyBD54725A7UVtdSYvEAHi8f0Evx9cC1WfBOLw0knkZ0HiOkWMo8dV9t183ux+GTVFsRfqYeuLZ3Vn3h83qlEbsYBRIVHYNeeBCSfycEdiSPcdeZKo++RSDiSjqtFrKD4KjJS75fltgKPQLsF8glEu+dX1pbGvdGDGkhEmnMLEhcaHXWbva+i64eW0QAvG2LqX3amgbt/ik3T/rT00HVWQ5c8+vXL4eRjL9Gpz+p6D6P5EwOq9Yxafvo6GtXCjsTcXmHttUUyF+r69oc03ltKErfJFF+oqVsQPY6cxDJqO+4N6tGgtK8SchkdRdyoSXWdDi0bQF42WnmUvkQ21LT/Ujp0XX/UvOpr95rLAubQhg96k7tc9zMikjl1ovk/5xrIlS8qurZ/EYV42ujJQ9MnCdVpO5Wi/iy/QmHcRHKVyChgzgb6oLc7yXU/I5KRU6f59HOuwUz/+iUN97Enia68bbxp2PyJFGCxveg21CvsXermItPTJ1n9IJr6w3kq1tY2eUZLZw+90bEt5Tla1l5GkAXSEr1O8tV3/hRfjKa5PdzJWqw/72I7Xxq9/jQbSSlFlLVjJnVxlRv3xbMvLdp/VacvFZ1Rs0QbHKbOmD7Od/Ck9IyaTS8Ke7cbuch05MN0sH7QVPrhfPmMq+Fpp6pr+2lRiCfZ6Mmee4lIUqctTY36s1weZXYaRmve6WrQHyk5Ba+gE5cP0ZJgV5Lp+Rw3evHr35jkSymicxvHkK8dG1vp59UvEckb9aTFCVW1dXNQ0cVPu5AVu6btkO06OmZA6TkYeQ8KW9yPPKx15cT5ps60wNA38fWVvCikuImuJJEFUNiad6irgR+QOgXTihOX6dCSYHI10Be3F7+m38ongcHTtlXXaP+iEPK0MZw3NseSOtR2ahTpuFAqOreRxvjqxx91XXkj6rk4gcrdp6XtjL/PqjbfrbpC6/rasbE1oJERd7SF5SizVlAnBZu3Zm/SEfXc8ItTps6o6ZYZu3nT56JU1w/RsgFexNYbetcU2TSl/ksPkb7KVqf98mi7MrZZlEU7ZnYhV70cg72YbXr2XUT7r+rU5hsvKzijVrPyAo7qiunFlL6Qy2l122QvcR0auaOACuONz6g9Mu8sOkcbx/iSnWFsEsmpUc/FlKB1IBp913mfvXRzW4GKefIXaiJmcCzBCFkSRcdOHqUfN8ZQBnOkhb8upY72zIkomlCft9bTnuPplJ4ST5sWhJJ3LfYZh860/FRpNGQGsWs8eUhZuX0rGvPJTjqSlkZJUStodEt79TVE1bVQy91Nr3oxoxXbku+ID2lHYhqlHd1FK8e3JQexhKTMYIwXaqw/zGjcQpZQ1LGTdPTHjRTDDZolB78u7Uj27H1Fkz701vo9dDw9nVLiN9GCUG+qxYKCQ+flVDZsvvW1DldsbUM2isb0wpz1tDf5FKUe+oGWhHqRgslJ5v8OJRvkpHxQXd5Eg7ik16oxhczbSPuS0+nM6RTav2URDWxWi82DhDxe218W2DQLNTFZ29iQovELNGf9Xko+lUqHflhCoV4KErHEx/+d5DIHqLq+i8Z7SJn87KnVmE9o5xEm76QoWjG6pVoOIuZILOKQ1Y5KQg2ef53WxiVT2sn99N1bPakRS8pENkG08ESpd7LMQo2fvleCguM0P4AFDCZP124z6avdxyjt10SKXDGaWnHXtWpBbx7m0mgV3dw9mbyt2DjlHtR77je0h+nIqaMx9OW0zuTCbExkG0QLjt3XtGsy+bNEG6U8IoGswHfwRrtQ4wKPSNKAnn99LcUlp9HJ/d/RWz0bscUQC6xBC6lsyvnaneoybRrE9deKGofMo437kin9zGlK2b+FFg1sxuqzgOfxGu0vNwptYqQgea1n6MX3NtOBk6coOXo5DWjMdJ8lC66N6pOD/yj6KDKJ0lITafu8YGrIfI3YcTj9cEvTjDJrNfWwY/7HqQu9uYHZVXoGpR/fTWuntKM6rO+y5rPoSLUHWX4LNfUcWLlR8My1FH00ldl2JC0b6EVyzjf5zKajlfV9vNEu1FiyopDXomdefI82HzhJp5KjafmAxiTldMK1EdV38KdRH0VSUloqJW6fR8EN2byJHWl46SQw+Mayy5sGqWOEVeMQmrdxH5u3M3Q6ZT9tWTSQmrH6kHjQa6XKosyi1T3YAkXiRF3e3MD8eTplpB+n3WunULs67Jqy5jSrbJIta2d8fVZ1++6bWwZRXbGY6g3bTuXS51DS2aXtyYr5vlbzflXHEr5xyiILtcJfaWlHLh9RUJM+b9H6PccpPT2F4jctoFBvdk2xA3Vefqrsi5bqtF9ebfO1TdVN2j3Zm8mbLfo8etPcb/awmH6KjsZ8SdM6u6htxzZoAZW7/6ov1GpeXsDfPvigKi6g/HsnaUEAJ5v29P7pe3Q/P5+K2PgqXqixPhrlnQ8oa3UPsmNjcuryJm3Yy2JTRjod372WprSrw3RVRs1nHWHekKEspPxb0TSBi03WA+jbm/cpv6CIeSyBx/HkL9TAAuqAb+ma7myrrtCG/g4kFtejkLVZRt9S5KzvR/WZQ64/ZCvd5IqUvzFjlrNg1ZCGbb2ipziqK9tphNrJVMdCjQWA5c+zBY6EGg79ni7pXZg5q0lezCnpf+ugMRgwI2WKrjdorq8bqL+DmMT1QmhtlsFqSZVD6/vVZzKpT0O2qkfNu36Zw2XJR+DCNI3xlZIXQ+O595jRLztXWSkp6cLKLmp5eEzaQ/e0paUU7J9CHhLmMNsvo9JLaBZqLADIA2lhml6PWJfGq98rr6+k31gyIefkPWwrXTHQme0jWGLFHKllHDJLlPxn0SG9QRTQyYXt1EmgI0sGctVlFlio8dV33qjo2ncDyIE5apv2SyhVT8xszr4IZo6ajemlSMorTqfFgVbq8bzwRaZBXwro1yUdqDYXaHt+STlq+ZsYvyXaKOMRCaQp31EZShdqbCHlP+uQvt4WnKSF7bgkypGGbdfMOF+7U15YSV0ULCnymER7jI2CpngY2J2OnbZbkq4jPxVlr+zMEiBmL/a96MsLOkpeqlfSZ2jGYU3wv78llOmqlJ6ZcVjnVzaGMpNWh/pTQLcptDWn0oZiJjwXaiyJDTLyTbE0oREno2dp6VlNf3n7Pt5oF2qs3/J2Syhd5xKq7JXU2YotmET21OvLC1qd5CjVVR2Z845lF2hlFwWLZR40yVhZaP8UD9YnGbVfdk5z3ftbKJQlfdJnZpB22rUoKXN1KPkHdKMpW3O0fbSgnfH2Wf+A774TSaOYHYvrDKItGlPVUHyaFrOEVmTVjt5XN84/TlV9oaaiKxv6Mx/MFpIha8lYZddTv/qs7/WHUKnKVqf98mqbp20Wpy+mQGYf4rov0BeZBgMt+JWWdKjNFk621PPLHE1ZlRdqNTAvqPaYzig+o9ZryDrQh+pb52qoeKFmKu+8T1tCWXzTiRulKDNXU6h/AHWbspXK1KxwL01i8y2qFUpbKnTmAob8B3aGSuDXsTPq647kbjyiD94F6vbGhNFNDc4aiNF46Ah0tSPcOhiHww+Akkv78FPqQ4hd+2NiqIveXnGxSyheG2rYhoVQ/Ym43SdQJPHE0NcHw1XvwvXwQtg4tK3gwhK/juisN2hu2NHQDHsCRjc1+KC4MYaO6Ao7uoWDcYfVRXzrlyH1x4AhfpBr/1RTyx9+TTl3dg937pj7FCRDJGgyLQbnz57EnsU9YastLUXWyA3O3JALC1DAfT+ng9R/AIb46fWIdckPmi7dgbpLJZew76dUPBS7ov/EULjoTzRCXxsKQzFUGpEcnSZNR0e9QSjQ5tUJ6GxNyD0Qi0P52uKqwlPf+fMAh/Ycwj2yQbdXXkVrPTGzORu7AcfOZOP3DQNhnROHPaeYLTG7mT7O26AvbPxTp6NPHRHuH4nFvpsl2nJ9VBZowzxM+I4qIJJ3wqTpHfX1VtEGr07oDGvKxYHYQ+oivnYnaTINMefP4uSexehpbBRw0xgFCoyMogV69/PRkZ8Yzk2bwEHEPhbQD6GNmXGUInFDY1e2HCrJw727GplKnZ3hKFbhwrZ5mLsuHhnXuYMFDIk3pkWl4+TPazBCt42agNQP/QYb+qYAtG3OOYJc/H1D45sq7ft4I0WL3v2ge/RS7NwUTTSTgH6hjZkWliKBW2NXWIlKkHfvLtSzwNe2JU0wLeY8zp7cg8XGyoJGbs7q+FZYUKDee8QmGc6OYqgubMO8uesQn3EdmlmWwHtaFNJP/ow1I3T7WBmqHqP/Ed9t/wJG9msI0d0DiIy9oZE/Q3kmAlHpSig6DMOIZpwkKh+nKs9dxEcfZP+ti94TRhuNVdx4KEZ0tQPdOog4rZOvTvutVNtm2aYKOXF7cOqhGC6h0zHO22CgzJ9Ond4HdUT3cSR2n7awitTEvKDaY3rlMM47pXB2doRYdQHb5s3FuvgMlKvCNGY3J/HzmhGoaWHiSUNX4k8mIhkcXZz0AonyfCbOFxJKbn6PQbVFEIkMXnYjseMOe//en8i5XoLirN+RrSRImvrAx+hGAlbwb9kMMhZXLY7yHM6eZ86JOTd/f+M7GEg8WsHPZBYpgszRBU56yq/E+czzKKQS3Px+EGobjpm97EbuwB32/r0/cypRXwexM1xdDS3PGtbq26+poKpK7iy1RcNmreEly0JS9BZ89fEizH3tZbzYrTU8ghYguZjVKSnRJBk6iJ1dYdwla80d4VQqTdAtzsLv2UqQpCl8jCcaVv4t0cxSEy1pBL+Wxg9HF9dtAZ9GEpTczUbWtcouaPXhq++8Uf2FrOx8lLBk3qeFvbZQBxs3tGjhDgcmUmVWFv5kl5CwOWxj6nZ8dq3Qiq2e6eFFnGdzYQpLtGEWJnxHVZA08kNLo6ehilG3hQ8aSUpwNzuL/V0Zu5PCtmEztPaSISspGlu++hiL5r6Gl1/shtYeQVigMQqUGBmFE0vMDTIMiYT1SAR5PUfYG3RVKuXuoMDtstD8Le/yBt7p2xDi64exalIv+Ls6wj0wBOPeXo3IE1e1CX0Ng43ZyDeJ5bDi7JqYb2J+vkq+jzdiOLHEXX8WJJAw2Yvk9eBoPAnqm6WQdhIqY9tS24Zo1toLsqwkRG/5Ch8vmovXXn4R3Vp7IGhBMjQutGyS8cY7fdFQfB2HV01CL39XOLoHImTc21gdeUJz6L+qWCBG/zO+2wbdRw2Eh/guft4RgxtqcSqRGh6FDKUNOg0bAo/SQVQyTlUa5Xlkni8EldzE94NqG8tLZIeRO+6w9+/hz5zr6o9Up/1Wqm0zbTMr60/mzSRMh9to4rcBdq1aoamE8PDieW1JFamBeUG1x/RKYSrvlKPLG++gb0Mxrh9ehUm9/OHq6I7AkHF4e3UkTljEgQgY6ssTiBWsrPSNqKSwgAVhZhNOQRg0ZizGjq3gNToY3swTUGERHrL6IhlzGiYkIrOx0f8WyFJQIQrVHWVjMHUrMxFbaBiMrRQrKytmNrqUoLCAezaFBE5BgzDG1Hi1r9HB3pWoX45IxJIJU/0tpSrRqSgLEWFd0cTVB50GjMaU2QuxYl0Ukq/VRkDfTnA3+c0Wc1wsyXxsl5i8izQTDbnpiYaNxSbaCgpTbbHApFA7fSWUlVpjlCfSpfDVd95QEZiJMLmxMSke7TKo6KHGlhRMd01WlUOulgsbfwXrVEu0oUtp0muMse+oElYKk35CLFdovuhRT3hl7K4IWRFh6NrEFT6dBmD0lNlYuGIdopKvoXZAX3QybRTMThXaL0+M4YL9Y5E2wySWrCd8Mx9je7WCi/wBLv2yB999+AYGP8uSmgGfIiVPW7eGIGK2zVzjY6i87+MNk7Oi4kkw8OHGVMa2i7IiENa1CVx9OmHA6CmYvXAF1kUl41rtAPTt5G6waJSi2SSWUCV8g/lje6GVixwPLv2CPd99iDcGP4umPgPwqZmTzMfOeI/rH/Ld8g4jMdhbgnsJkYj+myXAD08gPOoclPbdMWKga3nCVKk4xQMmSz1plhSiQCMwBA0aY1pW6tdoBJcqQnXabyXaNs82ic3zQ/Zfjd2Ydv/M/3P/NyuAGsdLI2pgXlDtMb2SGOednCpMYovzBHwzfyx6tXKB/MEl/LLnO3z4xmA829QHAz5NQQ0LE08ezLk+oWj3/IocaFi4/mZXZcYSCpSBJE2m0s/6x5ZMUpzyNvlx+8HbLtQ7S6BBRX9/1Yvkomo4o1aUSGHeUoKsI32se16klHtbabC96ZuJOAwLNzivoaSMJYEkg4SaTP1Zfx+4SfjWZ2j3mosUL9Jmw/3Fqr9pbS8rYlZLszS3xaoEhZQ8vw1Zi0Sk8Ayh2V9E0IETmXTtvkY2pfMqazmPTmrnSXNGTbOf2rhLa6mXFUjabJbmTl3FKfS2H7cnuy0tNJ5oVv8r6iUXWWYvuqQhTYgzIdWCaBrLHUKv9X+0QX1i3cS5j4IdNJI7yO8wnAxUWzMGX/0993z1nTeqi/RpFza3Ejd6dZ+JCyjP08HtUbQvOZtuJoaRt5Tbz7+YzpiSYZnOt6el6gMcxuMv4t1GAe0YyR1cdqDhxgKjlLd9TZ+dMeE7KoX2jJqk4QQyPeVj1TZb6/82sL/4211h8nxqYy1idudJIbO/oIgDJyjz2n3NWJQZtCSQ04eWNK/cKCq004LY8eTM+mI39AcDe8mn8GHcPDjRuGjDgx5aCq7SqX2baUVYKPk5MP0UKaj90gztm9UFz7s+mvJNdIvW9ZEz/W1Cr6sNpBK+jzelNxNR0IvGk0DjnZn87IbSDwZv5YcPU59bchoXzbS0ErZdmEzz21ir58YzZDZ9EXGATmReI40LLR23jFrOO2lw7qWUArp6ah9tXhFGoX4OzEaYb22/VOsPLWdnvMf1j/hujmI69V5bkolqU++vLlPBoTfISyqm+kNLzxRz8I9Tps6oFewYqb7xhsNww1jODfdt8uXaKB1PqZ0zHZ5aWSdfnfb7qLZ52WYRJYZ5k5TTo8VntHqkT1l8YHqphme8NDqjVgPzgmqP6Ry8z6iZyjuNKbh6ivZtXkFhoX7qc+0iBYvTpYITzqhVCpNfWDzpSDwD0cZJAtVf8dh13HgDb8lf4Zg1ZAQmzt6E9IeAtEV7BNYXQ3n2APZdMPyK/i4SEtJQ/LhvZSqDlT+eC3CAWHkaBw9ch+EP2HmHD+D4fXMvLIFnYBs4SVT4K34XjIddgr/CZ2HIiImYvSmd/c23/j/AwzRERZ5GgdgNY9ZE4KOpg9E90BtONprf2vNOn0E2Nz2V3VIibYH2gfWZvM/iwL4LMJrphASkWWqiVTeQnJQOpl565B/Zi8O5bD3boh3aGR5uKEVkze3aBAru4LbBObaS3FM4dVH/m0S++s4bsTMCWrtDqrqGowmnjcakTNuA6aMHoe/0bbjRPAgtbZktZexDXJbxz11Fp+Kwn02ixKkl2lawcd3Kl28bIiYvtcBwx1hgOHXqIsz57rWqqG4kI8lIwPk4svcwclnq0aJdO/Y3X7t7iLSoSJwuEMNtzBpEfDQVg7sHwtvJhrXEyDuNMxqjMN76WCVUyIxchNfHjsHy0kMQCme07DkKs1buwL73u0HG+vZ7xjnNe08UNdD3VQBf236YFoXI0wUQu43BmoiPMHVwdwR6O0HjQvNw+ky22u+Vbn1UZUZi0etjMWb5YWhaV8C5ZU+MmrUSO/a9j24y1ubvGTjHbeWzoJ3x9ln/mO+WwnfEUARZ5ePo7hjE7YhFTokT+o4MQV1tDUvFKRGTpcbN32ZeQpcS5J46BT03L/FEYBsnSFR/IX7Xce1c6VDyF8JnDcGIibOxSS2w6rTf6mzbCr5BLWErViJjXxyM3X8RTsXtZ/KVwKllW00Rz3hpRA3MC6o9plsKVSYiF72OsWOWl52VUzi3RM9Rs7Byxz68r3EgyNA4EIaY20jA/dApwIP/5EINim6Y8LIv5Ko/sG7qDOzI1tknm38aX0+biVWR4YjJkaABt0XBphdeGd0CssIjWD71E6Tc0VTlkqSciFmYH1V+sLgcFYoe5CP/QZGRYZuPPfpMGgkv6T389P4b+O5suUEq/9yFWXO/x2UejSu6TcDLvnKo/liHqTN2QH/YX2PazFWIDI9BjqSBuoxv/WpHLIec2yJDD3D92h09mRdmbUPYe7twixXSwyI8NJ4QM7BBr1dGo4WsEEeWT8Un5RONhzkRmDU/SnsuwRIU47c1M/B+Ym7ZOJR/xWBO2LfILrFHjwmj0Lyi7THS5vDxZG8WH8f2jWdQqC1G0XlEvLUC+/MNvBxffeeNFTqMGYlWChY818zE0qRb5XPD2l8zf536DEfHYYPwTP0QTBjSGJLCo1j+6vtI1BGo8nIc3p7yBc4oZfAdPR5dK9qyUYdvG1I09/Fk/y3G8e0bcaZcYDgf8RZW7M//Z+JC8W9YM4P1N7dsxvFXzByEfZuNEvsemDCqubqUn92JIZdz200ID65fw51yUXBGgW1h72GXxihQVDmjqAARFFeTsHHTFnz43mc4qbt3RXUZicf+YH5PCs9mOlsDVUV4kJ+PB4X/xLK4atQ431cRPG1bLJdD40Kv45q+siBrWxje28XZLuFh0UO1DYsUV5G0cRO2fPgePtOfZFxOPIY/WPyRejaD5p4OFrQz3j7rn/PdkmeGYfjz1rifsBLzdl0ENeqPEbo3ZrFQnJI294HGzW/HxnJhMjcfgbdW7Ie+m1eg24SX4StX4Y91UzFjR7bOObB8nP56GmauikR4TA4kaoFVwn7Npjrb5tz/BAxpLEHh0eV49f1EnXlV4nLc25jyxRkoZb4YPb6rpphvvDSiBuYF1R7TLYRIgatJG7Fpy4d477OTelscVZcTcUzjQNCs9KYwIiu17ZDqFm5U6UZgTxmaH9aeRB6zfSkvhVb01DxzQ1zbndr1GUxDQ4OpTUMFibhbJjcdRd9n6/yOfe8ILXq+jvr2qQqXtvTC4KE0oPMzZC8Rk0O9Oqwd/a2Pmlsss7hk1ZlWZlfh/t6qm7RvRiv1AyxFNu70bMhgGtK/Ez3jICUrVzdykoAk7lPM2PqoIS9lBfV04Z6VJKba7u2oDxtHaHAbaqjgbgctp6ajvifdYfOqX+1bH4vpzMddyEHMZFGrMXUa9ipNnz6ZXu4XRI1qSciueRC14G6p3WAM/ajdncVr66Oae3Rk0fNUh7uGwoXavsD0YkBnesZeQmKHelRHaqktDk7k35Lpn5UTteo5kIa82JW82ZyKOJmO2Khze2VTt7xW0eXNg8mZjYt7vp7n8/1o8MDeFNCoFknqdKD/69SAxLpbOTj46jtv7lPKRz3IiXuGmcyR/LqH0rAhfelZN+6BrxJqELySSp+OoLq5n95+ltsixWRZz4e6vTiUhvTrSF4OTHdEUnIOXkEpeZq6psfPtw1W//JmGuzMvScmW8/nqd/ggdQ7oBHVktShDv/XiRqI/4Gtj07+1JLZkpVTK+o5cAi92NWbHDh5yZvSiI36t1jmY3fFZz6mLkzvIapFjTsNo1enT6fJL/ejIE4f7JpTUAvuNs4NaEy5UVhm62NeIs0LtNX6xNYUHDqcRg7tT52966ifDWftM4VidZ6we/N/vUnOQoosYLG2xBJUx9ZHDXx9JT8ss/VRDR/bLj5DH3dh+sDKazXuRMNenU7TJ79M/YI4W7Cj5kEt1Ld4bzDmR237eZQ4L5Bstf6wdXAoDR85lPp39qY63LOdrH1oSmz5g3Utame8fVZ1++5SVHRlXQjZcd+OaB+VoL/7jH+cMrX1kQmTNg92ZjrCxm/rSc/3G0wDeweo26jT4f+oUwOxwXjyKGVFT81zJMW1yb1dHxo8NJSC2zQkBZc/MD8z6vvs8u2CPO2XF3za5m2bKrq5/216ltvOyPKuej7d6MWhQ6hfRy9y4GKi1JmCV6QwaZTCM14a3Z6fo6blBYzqjukW2vqYlziPAm25+KQgl9bBFDp8JA3t35m868jYuKzJZ0ps+YPYVdn0aVdN/21c/SgoeAEd1DcuARP8dxdqHIU5FL9yMoUEeFA9GyuSymzI0TOIBkxfQ4lXTSh43m+0Y+FI6ujtTHZyOdk29KPe076hI/8bSLWra6HGofybjqx5jXq3ciUHhYwUdTyp/cj3Ke7XzzULDa/yZ9yYs1e4MCeeVk4OoQCPemRjJSWZjSN5Bg2g6WsSydSwza5f7Qs1huo6Ja1+hXr4upAd15dadalxm970yvIY+iPvIn3Rg3tmhxdNO6iJgPwXahx59NuOhTSyozc528lJbtuQ/HpPo2+O/I8G1raQQ5b60JyDp+j7mX3Iz8WWrKxsycW3J01alUBX9Nqu6NlEeZS+ZQ6FBjWhOtZWZO3gTgH9Z9Hm9Ju0d1Ijkhgu1Dj46jtvCuj87mU0voc/uTooSMbab+DdkUYu3EmZul3nyDtLUYvHUHc/ptPWMpLbO5PXs6EU9uVBuqQ3FxWNn2F2Gxry0rfQnNAgalLHmqysHcg9oD/N2pxON/dOokaS6l+oSX3m0MFT39PMPn7kYmtFVrYu5NtzEq1KuFKePOlgvp2q6HrSanqlhy+52HHzWovqNm5DvV9ZTjF/5NHFL3qon2nkNe2gprqlFmoMVW4KrX8zlDqofaKUpHI7cvZ+jgaGfUVH/tYf1ZO2UOPg6yvNx4ILNQ4etq26nkSrX+lBvi52ZCWVUa26jalN71doecwflHfxC+rBPTfNaxppXSg3yZSy/k0K7aDxh1KpnOycvem5gWH01ZG/jXTXonbG22dVp+/W4fpmGliXJZ8yX3o7xfjcEt84ZXKhxpGXTlvmhFJQkzpkbWVNDu4B1H/WZkq/qTnLYzyeQsqJX0mTQwLIo56Nen5tHD0paMB0WpN41Wiu+NgvX8xuu5K2mXc2ihaP6U5+rg5kLZOTvbMXPRsaRl8evKT/7DY1POKlyYUaR03KC7RUZ0y32Bk1FeWmrKc3QzuQt7MdyaVSkts5k/dzAynsqyNkqGZ3jn9KQ1o5Uy31l77P0XKdawuYRsT9R/vjmgBPSq5+iV7NdmHg7z/hNfWDUyyLKusjdG4xFydaLUHa8XloYfpIj4CAgICAgICAgIDAf4z/5hm1f4QSXI7bi9NubdG2bmXFWISEWQHw9O+Gd+Lva8tKKcGNpKM4qxLDvrmv8MBAAQEBAQEBAQEBgacIYaFWWXJ34r01+Zi0ehbaPfbZIBUhg4+fG27/dghfvDMPUb/f1x4wfYA/93+Ise/G4o64MQa9FAwbdbmAgICAgICAgICAwNOAsPXx36boDNYMDUFYzF8oFslh71gPiqJbuHG3ECVSF3R/LxwR73ZEHW11AQEBAQEBAQEBAYH/PsJCrSZQkou0yA3YHHccZ/+6jYcyBzTyaY+Ql8ZhUICj5nlJAgICAgICAgICAgJPDcJCTUBAQEBAQEBAQEBAoIYhnFETEBAQEBAQEBAQEBCoYQgLNQEBAQEBAQEBAQEBgRqGsFATEBAQEBAQEBAQEBCoYQhn1EyhPIVNC75DqigAn34wSl2kyozA+18fRb7fS/hofKC6TJmxDYvXp6Co1cv4YGwbSNWl/zD595FvU7t6bt9fcgMHVn+ImL9c0XfODPR0quS6vjr7qIcSGdsWY31KEVq9/AHGtqnKjKiQGfE+vj6aD7+X3sf4wMo8g0GJsz8swbrjBbzbyL+fD5vaT+NDGfJxP98GT+XQLcBTqTeqPxGz4jMcuKbSFjwOCZr0fwtvdHeE8uwPWLLuOAqYX3+f+fVKP2nln0R5Fj8sWYfjBX546f3xqJRreqJQ4tSmBfguVYSA8Yswyv9fibQ1hMrHlCeTapx7U/mNKhMR73+No/l++PSj8dqKDGUOYpfOw8qdJ3DxHmDjOgAf7v4IIdYVlNtqPycgYAm4hZqAAfkRNMJBROK6L2kLiArjJ5ObRESKFzdrS4gKoseRk1hEtQdtpXxt2T/HbUrbOIO6e4+g76vr4spztKy9jCALpCUZSm0hH/6BPupRQNHjnEgsqk2Dtlb1goUUP9mNJCIFvbi5sm0VUtxEV35t3E6jjTO6k/eI7/8Fnfp3uZ22kWZ096YR/4yy/Ld4ivWGipLpLV8p94WjmS8ZdfjwD/VHC+MmkqvWrz8xciuMo4muEhIpXqRKu6YninyKGOFAInFdeimqQFv2tFKJmPJEU41zbyq/KYynyW4a2yqnmNKWBJG1iPkOkYxqOTiQnffrdKCwonLtxwQELISw9dFMpB698NqcuZg10E9b8i9TlIw1736Og5cK1dlHjeRJ6GOFSOHR6zXMmTsLA/3+uW8ti5LX4N3PD+JS4ZMnsapRhOQ17+Lzg5fw1A3dAjy9esOw8sGEdXsRHx9f/tq3HdPayABRLXRbsFv/vfi9+Gx4I+2HBQQEBLRIPdDrtTmYO2ugtoBRchWHfj6FAlF99P86E7dv38bdzM/RXVZBuVz7OQEBCyEs1MxE4hWKt5Yuw5LRrbUlAv9tJPAKfQtLly3B6NZP81YbAYGaji28OvRAcHBw+atHB3jaidh7EtRv0VX/veDuCGqs0HxUQEBAoBSJF0LfWoplS0ZrCxiUh3t5pH6vfWf38u3RFZULCFgYyUKG9t9PLsrrSIvbgchdsdh7OBXZ96zR0NMZNkbLUCVunUtE7M5diI3bi/2JJ3H2ciFsG7mjvrVO5eLfELkyAhkif7w3V/PNiup8ND5ZtQXxV+qha0tndZny9x+xansain0GYfYgV2TGbcXmiDgkpl9CcV13NK6rAJcqlKLMjMJHn21HhtQPLSgFW9Zvxb5fLkHVwBMedbRmrryFc4mx2MnGErd3PxJPnsXlQls0cq+P0i4qM8Kx9PNIJBxJx9UiVlB8FRmp9+Hevhnq6gyj6Goq9kaGIyomHklpF3BL5gSPhrYVnKVTITc9DuHhUYg9mIrLJU7wdFMh5du1OHDVGd0nT0RnR/PX9eb18QH+PB6LHRE7Ebv/CNKyb0Pm5IGGtpVdGCnx+4+rsD2tGD6DZmOQaybitm5GRFwi0i8Vo657Y9RV6M0IMqM+wmfbMyD1awFK2YL1W/fhl0sqNPB0w629n2DVlnhcqdcRLZ31x/7w2i+I3b4NO2IT8Ev2fdi5e6LejZ+w+pPNSMxzR/tmdSFmMs2KWY1tqQVoFjoXw5teRtLObdi+Mw6HUi/igb0HPB1LdUSJjPCl+DwyAUfSr0Ijsgyk3ufaskfWrhX4bNtpiHwD4E45SIzahvBde5muXUaxA9O1evq6Vk4RrqbuRSSb15j4JKRduPUIGSuRm3EAUeER2LUnAclncnBH4gh3UzqjzEXGgSiER+zCnoRknMm5A4mje+XmTpmB8KWfIzLhCNI1yoKrGam4794ezXQU2ix9Vv2OXSs+w7bTIvgGuKPk/M8I3xKO6PhjyLxtA/dntH6h5C4yD4Tj+x+iceDEeeSzuWjqaF0uw9J2UlVoFtgI+b/swuYtkfjp+G+4VFgHTZrUrTAwm9VPZSaiPvoM2zOk8GtBSNmyHlv3/YJLqgbw9KhT1rby1jkkxu7Ertg47N2fiJNnL6PQthHc61trv2V7lN7URYnaDrcjMdcZz/k66n0zV5KbiP8tX4eYcxImKw/YsMGb5aOqS6csCd3F8Y2f46eLUvgOnoUhfjLtG/qosmKwelsqCpqFYu7wprictBPbtu9E3KFUXHxgDw9PR+i5jDL4yIAnj4tnqizErN6G1IJmCJ07HE0vJ2Hntu3YGXcIqRcfwN7DE44mO21m/GN+63de/oZvfR2KriJ1byTCo2IQn5SGC7dkcPJoCH0xFuO3yJWIyBDBf+ibGOhT/qYyNwMHosIRsWsPEpLPIOeOBI7uhp+vDObFJvPshQePzWX4xBR9Hu9LOJ6cueeHmfmN6jyiP1mFLfFX0L2rH/4+uBYrvonF4aSTyM4DxHQLmceO4vzFdERHxhmUH0eu83PwLcuTzPQRZsaCysQ/yklE1LZw7NrLcqDLxXBgOVA90w7NDN0rh09uWX02+hSh3QL5hFJMF6PnUg93axJz+4TV5w+4/cJisvMdTetPl+/hVl3bT4tCPMlGLCqvp36JSFKnLU2N+pNU2rp8z6jZ9Aqjd7u5kEynDyJZfQqa+gOdL9ZWZmjqy6jtuDeoRwMJMXNhdSXkMjqKbrOrX9u/iEI8bfTHwr1EEqrTdipF/anpYX7ECHIwqCNxm0zxpXujVdfp0LIB5GVjMFaRDTXtv5QOXS8bqYa8X+nL4T5kz8anW9d72HyaGFC5M2qP62NR1g6a2cWV5AZ1RDae1HfRfrpq0EXzKD2jZkO9wt6lbi4yrYy5l4hk9YNo6g/nmdaUoq0va0vj3uhBDUrHL3Gh0VHXKjijlk/p60ZRCzuxftsuXentD8eTt1RCbpPjSTPM0vMEcuoRtpj6eVjrfIbTESfqvOBnylWPVbsXX+d9Tjc0bWnbkQXQnA0fUG93uVE7neaXtlOO6vohWjbAi1gCrtMmJ+Om1H/pIdJTg6JztHGML9kZ2gfre6OeiylBp/GicxtpjK+dkZ6K5I2o5+IEo348Fq296bYFiRtNLlUWPvqsPb8jCwijNe90JReZrk5LySl4BZ24fIiWBLsa2Ksbvfj1b1SkbaasHb/X6bN3OlEDqW47MmrQfhpFXNAxbg4+/SyIpnFOYpK1HUdv9GjAdERTV+IymqJus/dV12j/ohDytNHVM81LJKlDbadGkcYdPEpvSu1QTHVfimLaro/y3DJqLwPJApdQqXk/2kdVn05ZHNVF+rSLFbuWLQ3ZXvFZntIzavIeYbS4n4fmvElZP2Xk1HkB/WzQT14y4IWZ8az0jJq8B4Ut7kce1rryZb7IqTMt+Dm3PJ4xeMU/3v6mMv5JRdcPLaMBXjYGusviadP+tPTQdZ3+mDqnVETnNo4hXz0/rPm8vFFPWpygP34+8IlNj7MX8zE3l+ETU7SY7Us4noS55wmf/EbvjFoxpS8MIJleH9lL7EAhQ9uYKK9DI3do+sjLRzw2FlQm/s2hDR/0Jne5oW/oRPMNfAOfPJpXX6rRRp82nuiFWsHx+RTAFEYkc6VuM7+i3cfS6NfESFoxuhXZs4Bk1eJNOszpmOoybRrEJfBW1DhkHm3cl0zpZ05Tyv4ttGhgM6rFlFPi8RrtL/UDvBZqGsWTNHieXl8bR8lpJ2n/d29Rz0ZskcCUN2jhCebKdOuz/jLH7hayhKKOnaSjP26kmIwi1sVNNIgZq8iqMYXM20j7ktPpzOkU2r9lEQ1sVospuoQ8XtuvSbaUhZR/K5omcMHaegB9e/M+5RewNrj32NV+XdpRPX5Fkz701vo9dDw9nVLiN9GCUG82VjE5dF5Op0ozUmZ4u8Z7kJSV27caQ5/sPEJpaUkUtWI0tbRn/RExg6zMzUQe0UfVzd002duKtS0nj95z6Zs9yXTq1FGK+XIadXaRsnJbClpwjO5rWuKBduGldhwSavD867Q2LpnSTu6n797qSY1Y0i6yCaKFJ8pmRLuwY3PNEvWQJVF07ORR+nFjDGUUmb6ZSO7uV8mLtSO29aURH+6gxLQ0OrprJY1v60BiiZTVN7FQU/fHityCZ9La6KOUyuQbuWwgeTEnKpL50OyjmslQFubTregJ6sTResC3dPN+PhUUcRLTtiO2JhsbBTV+YQ6t38tklnqIflgSSl4Krh1/eidZZ+FQ+Cst7WjPxqagJn3eovV7jlN6egrFb1pAod5Mn1iw6bz8lHZhoqSs1T3IjvXdqcubtIG1nZ6RTsd3r6Up7eqwNmTUfNYRzZiUWbS6hx0L8E7U5c0NtJfpaUb6cdq9dgq1q8P0RdacZh0pla+5KKkw/xZFT+ASEGsa8O1Nup9fQOqh89XnsiRWQfJaz9CL722mAydPUXL0chrQmNMtG3JtVJ8c/EfRR5FJlJaaSNvnBVNDJnOx43D64ZZBO1ZykstcqNvb2+nEn9fpasYe+mQY5zNEVCtgASWXDZVnP7XBWcTKZW4htCTqGJ08+iNtjMlgc6Kiy5sGqX2FVeMQmrdxHyWnn6HTKftpy6KB1KwWs0mJB72mdVgV601lF2qmfVS16VR1wGuhpvHhVm7BNHNtNB1NTaOkyGU00IslnayfPrOPasfE4CUDfpgdz7S6ySU9Iis3Cp65lqKPplJaUiQtG+jFFhgsIfOZTVq3wj/+8fY3/P1T4a9LqSMXXxRNqM9b62nP8XRKT4mnTQtCyZvpt9ihMy0vMxbjZF2ZtZp62LG469SF3tywl9lHBqUf301rp7SjOkxWsuaziLcbYvCNTY+0Fx6YPfelsjYzprAR8fIlT8Lc84JvfmNwMxFVcQHl3ztJC9QLuvb0/ul7LDYx/1pouryIa4avj3hkLKhc/BNb25CNojG9MGc9i9GnKPXQD7Qk1IsUnG/wf4d0UwU+usenL9Vlo08jT+5CTXWNvhvAkmOWeLVfkspUSAflBfoimCWTYkd6KTKP/bmSujCHIfGYRHvuaeuUUrCfpniwoMeMbdk5rbHyXKiJrPxp1iH9hgtOLqR2nNNxHEbbc7Vl2vpiB7ZwuaZJpDQo6cLKLsyI2GJs0h4y7uIU8mDJhKz9MirtIhXupUmNmEOpFUpbdPIQ1ZUN1N9BTOJ6IbQ2S8caOVQ5tL5ffRKL69OQrTfVRcrfWLLGnLuk4TDaekW3Tyq6sn2EJompzEKNw2Qfiyl9cSBZccnjC19QpkEXC35dQh1qM6dh25O+zNHtjzmULtSYc/GfRfpTUkAnF7ZTOxPHYdtJMyWl9ZmDYQmu3pQwjTJaqCnP0vLnFWyR0pCGfn9JuzDWwAX4SV4skOv8msG1oQmqTG+CFlKanpLmUeyERuw9GT279CzTAA2FeydRI6ZntUK3sBBVSnk78kDjdmLGc+/JqP2yc9p22Nxt6E8OYjHVC1lLxmqwnvrVZzpSfwhp1OA+bQllAUT6DM04XBY+1CgzV1OofwB1m7KVcrjG72+hUKbX0mdmkH5VJWWuDiX/gG40ZWtO2XjMp5D2TmLyENWiUB2F5qvPZUksS7TaLUln2laKirJXdmZ6x+zVvhd9eUGnh6V3/9Idf1k7VuQ/K5FJWYfis/RJV86/1KVBWzTX5d1PbXDmvp0d8O01PV3i/NfKLpyeedAkY4dF+6d4GMx3RXpT2YWaKR9VjTpVHfBcqIkUQbRQ37AoL3YCkymTz7NL6ay6n3xlwAMe8axcNxUUtDBNv25eLE1gPheyZ2mpptP84x9vf8OzvuoKbejPxiquRyFrs3RslENFOev7UX0m4/pDtpJGjMbJ+v0tocyXS+mZGYf1F8XKTFod6k8B3abQVt7KxT82VWwvPOAz9zqyNium8PYlNX/u+cA7vzF118fiM7RYvSDrQB/+oa3HYbK8Ej7iEbGgKvEv0Mg3xNB47j1dW+ehe3z7Uj02+nRiYvfpE8KDQ9hz6B7IphteebU19G60I2mCsRuO4Uz279gwsDb7cxpizp/FyT2L0dPw+RayRnBTnz8qREEB9yUlX0SQd5qE6R31G1a0eRUTOluDcg8g9lC+tlSDxK8jOtfXFb0ETabF4PzZk9izuCeMu+gGTRcL8Lgu3o2PxsG7QN3eEzC6qcEmYHFjDB3RFXZ0CwfjDrOCElza9xNSH4rh2n8iQl10+ySGS+hrGGrYRlVR5SBuzyk8FLsgdPo4eBs0r2gzFdP71IHo/hHE7rupLeWJSI5Ok6ZDf0oUaPPqBHS2JuQeiIX+lEjg17Ez9KbEBKo/47D7RBEknkPx+mBXvfM+4novIGxc2wrO3Ujh128w/PSUtBYC2jZnV2b9+fsGzHsClBT+A4YYtePv11Tdzr07d7Tt3EV89EH237roPWE0jNVgKEZ0tQPdOoi4ww9YiRTOzo4Qqy5g27y5WBefgevcYSeGxHsaotJP4uc1I9BYwlV1hrOjGKoL2zBv7jrEZ1xXn4viZOg9LQrpJ3/GmhGN2V+WgZ8+6yBtgd79fHTmQwznpk3gIGL2FNAPoerBaJG4obGrFUQlebh3t0RbqEEk74hXpj+H2tq/1UibY+y47rClO0iIS1AXVbqfEj907FxfT5c4/zUt5jzOntyDxcYOC43cnNX1CwsK2KxXD8Y+qhp1qgYg9euHwfqGhVoBbdGc++ki92/cUBsWXxnwgEc8K0Pqh36D/fTr1gpAW02n8bem01WIf+b6m1LMrH83HtEaY8GE0U11bJRDjMZDR6CrHeHWwThUJEapszMcxSpc2DYPc9fFI6NcuTAtKh0nf16DEXyVqwqxydheeFCZuWdSMyumVNqX1Ny5N59/Ib+pio8wEQsqH//8MWCIoW/wh19Tzjfcw5072tnjoXt8+1ItNvqUUknP8u+j+isL2fklLMfyQQt7baEONm4t0MLdQXsQUwrbhs3Q2kuGrKRobPnqYyya+xpefrEbWnsEYUFyMatTgpJKZT0SNPJrCSdDSYrrooVPI0hK7iI765q2kEMEmaMLnAz1U2qLhs1aw0uWhaToLfjq40WY+9rLeLFba3gELYCmiyUGztQQJc5nnkchleDm94NQWySCyOBlN3IH7rD37/2Zw+oXI+v3bChJgqY+PsY3R7DyR8tmMtMHgSuLMgtZf7JkWMLmo42pO6/ZoVUr5tzpIS6ez9aW8UTSCH4tnYyUW1y3BXwaSVByNxtZug/HFcng6OLEZvLRKM+dxXn2MYm3P/yNhCWBRyu/ChZ7Yji5uhq0L4bcipMtQaVSPmZeS2GLDaN2AGtrjRxVKu0iQ3kemecLQSU38f2g2kY6IBLZYeSOO+z9e/gz5zr7gBxd3ngHfRuKcf3wKkzq5Q9XR3cEhozD26sjcUJ9gw8t8i54452+aCi+jsOrJqGXvysc3QMRMu5trI48oblxjMXgq886iJ1YEmIQTCQSJkER5PUcYW8wT1Ipd7MJboeB5u9SJG4t0drIuIHazZqhkYRdNzuL/VX5fopkjnAxcgacO2iIZq29IMtKQvSWr/Dxorl47eUX0a21B4IWJDPL5dxBpRyWGZjwUdWpUzUAsZMrXA2mQSy3gow7XKFSMR/JCnjLwHz4xTMtTMddjTsNK02noVJ3mqOy8c9Mf1OGefWV5zNxvpBQcvN7DKptKEP2shuJHXfY+/f+RM51w2tokHd5A+/0bQjx9cNYNakX/F0d4R4YgnFvr0bkCc1NdXhT6dhUQUw3k0rNPZO1uTGlcr6k5s69+fwb+U3lfYRxLKhK/HM29g2whmY6mG/QitZ83ePfl2qx0acUk2nlkwAVFaonWmSlgOKxoyhCVkQYujZxhU+nARg9ZTYWrliHqORrqB3QF53cq/atipVC73sILcxpKjROQKlUaoq0WFlZGTuHoixEhHVFE1cfdBowGlNmL8SKdVFIvlYbAX07wbwulqCwgHtmmQROQYMwZuxYjK3gNTrYm9UnFBY9ZP9lgYYlJcZilMHGxtTYqgAV4eFDFhRECuY0TE+cXK65plKp/52d+VjB9JTIoeCSGOZ09KfEis3J4901FRYyR8XiOJs/U/eQEzEvaLIZ5sRk7DNVhrUjlZm+e50GbbAtKUSBuqNOCBo0xuT8a16jEeytCaTSZpOY80zAN/PHolcrF8gfXMIve77Dh28MxrNNfTDg0xTkaWqi2SSWaCd8g/lje6GVixwPLv2CPd99iDcGP8sC4gB8mqKpWXX46nM5IrV+af8wgAsq5iJS2JTdbVUXMUuIpFwzxQ/ZfyrfT6Z4JnWmKCsCYV2bwNWnEwaMnoLZC1dgXVQyrtUOQN9O7gbfRFcSbuu79p+GGPmoatWpfxuWaMjYPGj/qpBKyMBc+MUzDSKRjFMfM6hk/DPX35RiZv2SwgKNH3UKwqAxpuSnfY0ORoVilDbDpMgTSPhmPsb2agUX+QNc+mUPvvvwDQx+til8BnwK3m6oCrHJZEw3k8rMPSdrc2NKpXxJTZ57s/kX8puq+AijWFCV+CeFOdNnvu5Voi/VYaNPK+oNkE8gqoufUhcr7k6Cr9I+vY21GpTnD9L2qH2UnH2PCpPnUxtrEYkUnhQy+wuKOHCCMq/d1+7hzqAlgdw+45Y076R23y2vM2oSajghTn9vr5oCih7LHeCuRf+3QXOHAk19ETkMC9c7R8Lt806e34asRax9zxCa/UUEHTiRSdfua/bvKjOWUCB3lqTlPCrtounzX0rKWBJIMkioydSfTfTJkGJKeduP1ZdR24W653m0qP6mr3rJSWTJM2pFiRTmLVXvC198xlSbRZQY5k3MzVD7pee0ZeaiPXMmaUgT4kyMviCaxnKHdmv9H2mmpPRmIg40LNzwHIvxGbWixDDylrJ56Pgx6R5xKuXe1sFkb+pmIrrn3HS4ta4Pybm5er18rh55Rs1kOyr6e20vsoKUms06otkLXqrTkiY09efHa4EpCq6eon2bV1BYqB85MJ0VKdrTUpM6UEBXT+2jzSvCKNSP2+vOdLj90rIzT+Zj6owaX31maPfoc2cMDEVVEDuenNlY7Ib+YGB/+RQ+jDsH4UTjorXnILTtSFxfoT2mVCl2ArmwtqxD1rG/KtHP0gPkDsPIWPWSaX4ba2KLTfIMmU1fRBygE5nXSOMOSq8lo5bzTpbZbEVn1Ap2jFQf3HYYbuhzmPWnvE2+FdxMxMhH/aM6ZQF43vWR8+tGtW6toz5yFmOavE7qIVtABhXBJ549SsdZp2ldH7m6j69r+8g7/vH1Nzzrl8YzSZOpGrk+FjPOKRVcpVP7NtOKsFDyc+BuzKBg8SND+6aZVCI2VRzTzYfX3D9S1iZiCm9f8gTOfYVUIr+p6hm1yviICmOBZeMfN961vZhPlDajWUc0s2e+7t3m3xdDLGGjTynmfn9T4xA7B6C1uxSqa0eRcJr7VlsXJdI2TMfoQX0xfVs2fomKxOkCMdzGrEHER1MxuHsgvJ1soP5hOO80zmRz345VduujCjeSk5Bu2IX8I9h7OBckbYF27Qz3hhvwMA1RkadRIHbDmDUR+GjqYHQP9IaTjean67zTZ6Dpou7WRzH3JVbZNyMaJPAMbAMniQp/xe/CcaM93iX4K3wWhoyYiNmb0tnfUrRoH4j6YiXOHtiHC4Y/YN1NQEJasf4leGGij1a+CGppC7EyA/visgz2uTOKTiFufzZUEie0bNtYW8gT1Q0kJ6XDeEr24nAu81Mt2uFxU2IKK//nEOAghvL0QRww2paRh8MHjuN+5YWlQSxSfzNbpWYknghs4wSJ6i/E7zoOYzX4C+GzhmDExNnYxCmuKhORi17H2DHLy84FKJxboueoWVi5Yx/e7yZjOvo7Ms4Vs6qRWPT6WIxZfljbrgLOLXti1KyV2LHvfWiqZoBV5Q1b5LH/6o6crz5bHtXfR3Aw1VCTHiB532HcYCmb/3PPsb8t28+HaVGIPF0AsdsYrIn4CFMHd0egtxM07iAPp88w+2D/0tuuVIHeiKytYc3+X3DnNvRPypYg99QpXNT/sb9iqlGnnhj4yoAH5sezy8Y+85E8RFq1xj/+SDwD0cZJAtVf8dhlbCxMjOGYNWQEJs7eZBxX1aiQGbkIr48dg+XlyoWWPUdh1sod2Pd+N8jYuH/POKd5z1z+idhkguqb+0r6kmqk6nPPh+rOb0xgUR9R/fHPfN27hsa8+lJNNvqU8sQu1GDVAWNGtoKCOdU1M5ci6VZ54px/eg3mr8uA0qYjhg1qhlpyblsC4cH1a7ijm18XZmFb2HvYxX2WHqLooWHybR7Fv63BjPcTkVv6ceVfiJkThm+zS2DfYwJGNX/MRiWxHHLuN296gOvX7jCVL6cwaxvC3tsFTReLUNZFkZX6M6S6hRs3yz+h6DYBL/vKofpjHabO2IFsnY3A+ae/xrSZqxAZHoMcSQN1mU2vVzC6hQyFR5Zj6icpuKMuZTzMQcSs+Yi6odsbnpjsYx2ETBiCxpJCHF3+Kt5PvFE+XuVlxL09BV+cUULmOxrju1Z270Mxflszg7WdW9a28q8YzAn7Ftkl9ugxYRQeNyUmse+DSSO9IL33E95/4zucLXNWSvy5axbmfs8/kBoispLDSkRQ3boBnWnliQLdJrwMX7kKf6ybihk7stXbGzTk4/TX0zBzVSTCY3IgacAEIVLgatJGbNryId777KTedjTV5UQc+4ONSuqJZt5SVvUqkjZuwpYP38NnJ/Vq4nLiMWiqNjM6iP94RLDi7JRUuHXjZtm88dVni6M8h69nLmEL/NIeqXB1zzsI+yYLJQ49MWFUc3WpJfsplnM6wLmD67im77CQtS0M7+26xeRDeFj0sExOFemNtLkPPNlcFB/fjo1nCrWlLOc8H4G3VuxHvtlZSvXpVCmqogfIz3+AQqXumGsSPGXAB7Pj2TOaBZbZiCGv5vjHG0U3THjZF3LVH1g3dQZ26BsLvp42E6siwxGTI4FpMYqguJqEjZu24MP3PoO+G7qMxGN/MCuVwrOZwTbjx/JPxCYTVNvcV86XVCtVnnt+VGt+YxLL+ohqj388dM+GV1+qy0afUrS/rD2Z3E+hj3o4kZR7NoSjH3UPHUZD+j5LbtyDHSUNKHil5vakxWc+pi4OYoKoFjXuNIxenT6dJr/cj4Ia1SKJXXMKasHdLrYBjflR+9M6z62PTv4tyUVqRU6tetLAIS9SV28HdZ/kTUfQRp3bmFa8TaKYznzchRzEIFGtxtRp2Ks0ffpkerlfEDWqJSG75kHUgrstaoMxVNpFUmXTp10VJGKprY2rHwUFL6CD2t+j81JWUE/1M1/EVNu9HfUZPJRCg9tQQwXL5ERyajrqe8rW+QX/3pFF9HwdTj4Kcmn7Ag0eOoA6P2NPErED1avD2qns1seK+qi6Sfvffla9JUskq0c+3V6koUP6UUcvB5IwuUmdg2lFit4N0c2kdOujE/m3dCGplRO16jmQhrzYlbwdOHmwsY/YqHPLXH5bHzlUN/fRjFbcgzrZmNyfpZDBQ6h/p2fIgc2/q5sTSSAh9ymV3/qoyv6UuqrnyYZc/YIoeMFB9h7f7SgceZSyoifTSyZjcW1yb9eHzWsoBbdpSAqWtYnkTWnU99ma7U9c7cR5FGir1YHWwRQ6fCQN7d+ZvOtwzwO0Jp8psdqHdOZR4rxAsuV0VeFCrYNDafjIodS/szfV4Z5TZ+1DU2J1H1hqLirK/rSrpm82ruQXFEwLtArNS58tvPVRJKlPTvWlZNWgJQUPZNft5kN1uXFaedDQ7/RvL82rn4/a+lh8hj7uwnwS07FajTvRsFen0/TJL1O/oEZUS2JHzYNaqG//3GDMj0yDNZjWG+6Ny7R5sLParsS2nvR8v8E0sHeA2q/U6fB/1KmB2Lytj2qqS6c4btL/esvZslFGAYvPaMuqQHVsfVTDTwa8MDOe8d36yDv+8fY3lfBPeSm0oifz0Zxe1nandn0G09DQYGrTUBMv5E1H0fdlxmJi+1teIs0LtFXbiMKlNQWHDqeRQ/tTZ+86JGNtWvtMoVi9h++aCc/YZImtj2rMnftHytpETOHtS56AuecJr/ymyrfn5+DpIx4VCxiWin+mtj6qMVv3ePalumz0KeTJXqhxFJyn3cvGUw9/V3JQyEhm04C8O46khTszy5IYzmFcT1pNr/TwJRc7K5LKalHdxm2o9yvLKeaPPLr4RQ/18x68ph3UVOe1UJOSz5yDdOr7mdTHz4VsrazI1sWXek5aRQlXdI33MU5ddZ2SVr9CPXxdyM5KSrJadalxm970yvIY+iPvIn3Rg3smkRdNO1g+qjvHP6UhrZypFucQZM/Rch1nUZgTTysnh1CARz2y4dqzcSTPoAE0fU0iXdXvlpq833bQwpEdydvZjuRyW2ro15umfXOE/jewtr4j40nFfcyjs1GLaUx3P3J1sCaZ3J6cvZ6l0LAv6eAlHSfCC+3CS+pDcw6eou9n9iE/F1uysrIlF9+eNGlVAulPCf+FGofy7yO05rXe1MrVgRQyBdXxbE8j34+jXz/XBCWvsueG8Ayqau7Q8U+HUCvnWhrH+dxy+kNZiWCoppBy4lfS5JAA8qhnQ1ZSGdk4elLQgOm0JvGqQTKpotyU9fRmaB+NfXIAAEf4SURBVAeNDkilJLdzJu/nBlLYV0fob93KqlxKWf8mhXbwJmc7OUmlcrJz9qbnBobRV0f+rlySynHnOH06pBU51+ICgYyeW/6H9g0e+mzphRpr538nt9KbIX7kUltO1nXdqc3/MfkdvmJynGb38zHBWXU9iVa/0oN8XezU81arbmNq0/sVWh7zB+Vd/IJ6cM+y85pG5e7AlN5o38pLpy1zQimoSR2ytrImB/cA6j9rM6Xf1JwhNX+hxlFNOvXELNQ4+MiAJ+bEM54LNW4eeMW/R/otCyXrHIU5FL9yMoUEeFA9G65fNuToGUQDpq+hRD1jMZ2sq3JTaP2bodTB25ns5FKSyu3I2fs5Ghj2FR3RVy6emB+bLLZQ4zArl+EfU/j5kidj7vlidn5jkYUaBw8f8ZhYwGGJ+FfhQo3DLN3TwCe3rD4bfboQcf/R/rgmICBQaVTI+qgzWsw9gVZL0nB8Xgve21QEahBFe/BK0374JrcfNuXuxKha2nIBAQEBAQEBgX+IJ/eMmoDAP01RAmYFeMK/2zuIv68tK6XkBpKOnoVKbI/mvpZ74LOAgICAgICAgMDTibBQExAwF5kP/Nxu47dDX+CdeVH4/b724O2DP7H/w7F4N/YOxI0H4aVgG025gICAgICAgICAQCURFmoCAuYidsKI9z/A/zUqwi+fDYZP/XpwdnVBnXqe6PXuPtxo0B0LNy1D70rc+l9AQEBAQEBAQEBAF+GMmoAAT0py0xC5YTPijp/FX7cfQubQCD7tQ/DSuEEIcBQ2Pf4nUF3EwU0xyChsgp6v9EUzC9wqWkBAQEBAQECAD8JCTUBAQEBAQEBAQEBAoIYhbH0UEBAQEBAQEBAQEBCoYQgLNQEBAQEBAQEBAQEBgRqGsFATEBAQEBAQEBAQEBCoYTwdCzXlWfzw3kyEzdmAkw+1Zf8mylPY9E4Ywt7doi14NCU3DmDVmzPw5sp4/K29I7wlUGZsw4KwMMz9LhVKbVmNJf8+8rX/5FCe/QHvzQzDnA0nUROm9ElAkBlHCW4cWIU3Z7yJlfF/s7+eZJQ4tekdhIW9iy2ntRasykTEIo2vezIxMaYnAQP/VD3k434lL/Kv2n7JDRxY9SZmvLkS8ZYMYDUaFTIjFmFm2BxsMEo6DOdRibM/vFdBXVM8qu1/A4Px1LR8yxTKDGxbwHKwud8htapuxhI+t9Iyq7xPEHiC4G4m8p+nMI4mukpIpHiRNudry/5N8iNohIOIxHVf0hY8GuW5ZdReBpIFLqEMpbbQAhREjyMnsYhqD9pKNUEsprlNaRtnUHfvEfS9TicL4yaSq0REihc31+C+1ywEmXEo6dyy9iSDjAKXZLC/nmTyKWKEA4nEdemlqAJNUWE8TXbT+LonExNjqtGY9k+W5nbaRprR3ZtGVPIi/6rtK8/RsvYygiyQllgygNVoCil+shtJRAp6USfpMD2PhRQ30dWobsWYbvvfwOR4alq+ZYqCaBrnJCZR7UG0tap9tITPrYTMquoTBJ4chK2PAjWbomSsefdzHLxUCOH2pAICj0HqgV6vzcHcWQO1BQLVyj/in4qQvOZdfH7wEgoFJ/iEIIVHr9cwZ+4sDPSz0pZZah5Ntf1vIOilmn/F5wqyf5oQFmoCAgIC/xUkXgh9aymWLRmtLRAQEPjnkcAr9C0sXbYEo1tb+iGM1dm2AG8EnytQzUgWMrT/fjJR5iLjQBTCI3ZhT0IyzuTcgcTRHQ1tdRyYKgsxq7chtaAZQucOR9PLSdi5bTt2xh1C6sUHsPfwhKNCpK2sz4M/jyN2RwR2xu7HkbRs3JY5waOhLfTcozID4Us/x/bEXDg/5wtH3eVvSS4S/7cc62LOQeIbAA8bdp3i3xC5MgIZIn+8N9fgWxhVLtLjwhEeFYuDqZdR4uQJN1UKvl17AFedu2PyxM767VcB5e8/YtX2NBT7DMLsQa7IjNuKzRFxSEy/hOK67mhcVwHTUinC1dS9iAyPQkx8EtIu3ILMyUNf5hZAmRGOpZ9HIuFIOq4WsYLiq8hIvQ/39s1gdz4Gq7eloqBZKOYOb4rLSTuxbftOxB1KxcUH9vDwdITpKTWv76rfd2HFZ9twWuSLAHdCTmIUtoXvwt7EdFwudoB743oVtG8Biq4idW8k04EYxCel4cItGZw8GkK/iyr8vmsFPtt2GiKmV+6Ug8SobQjftZfN32UUO7D5q6c/f6qsSspMeQvnEmOxc1cs4vbuR+LJs7hcaItG7vVhraOLlZeZEtfT4rAjchdi9x5GavY9WDf0hLONCUU3SzblqHLTERcejqjYg0i9XAInTzeoUr7F2gNX4dx9MiZ2dnyCv60qxm+RKxGRIYL/0Dcx0IcJQXUe0Z+swpb4K+jetaWmmup37FrxGbadFsE3wB2Uk4iobeHYtTcR6ZeL4eDeGPUqUOaiq6nYG8nkFxOPpLQLuGXK/5WhxK1ziYjdyeYxbi/2J57E2cuFsG3kjvq6iqLMRNRHn2F7hhR+LQgpW9Zj675fcEnVAJ4etZGlNyYRzv/4CVZt2Yff4IPAJrWNfNL9lO/wwVdROFXUFEHP2FtsPpW5GTgQFY6IXXuQkHwGOXckcHQv17VH+qc/ovDRZ9uRIfVDC0rBlvVbse+XS1A18IRHnfJfQR4rX21siUw4gnTNRXA1IxX33dujWd3ykSqvpyFuRyR2xe7F4dRs3LNuCE9nmzJZVNr2eft6FXLT4xDO6sceTMXlEid4uqmQ8u1aHLjqjO6TJ6KzpQJYNaLK2Y1VKzdh7x9WaNXGHdZlslEhS62PPyG92AtBXjr6VnIF+7/4GN/uvYw67X3xII6rF48r9TqiZf2zj5jHEmTFrMa21AI0C52L4U0vI2nnNmzfGYdDqRfxwN4Dno66vlyF89E6bTuzHlTBxivFo/TS7nyl8y1+/qYKKH/Hj6u2I63YB4NmD4JrZhy2bo5AHItVl4rrslhVV98eHuWz3G5hr6HPLeMhrv0Si+3bdiA24Rdk37eDu2c93PhpNT7ZnIi8Ujvmk6M+Svb2Wf+Ir3+cb9SFT12BCtBugXwiKTq3kcb42pFYpN51UvYSyRtRz8UJlKvSVizd/yvvQWGL+5GHtUinvohkTp1pwc+5VFpdTVEW7ZjZhVzlunXZS2RDnn0X0f6rOrV1zpwZHaswtT+/gjNqeb9+ScN97EmiMx6RjTcNmz+RAqrxjJpNrzB6t5sLyXSvK6tPQVN/oPPF2spaVNcP0bIBXsTWm2V1Nf1sSv2XHqLrekKsGvkRI8jB4DoSt8kUX8hNqebMhbxHGC3u50EskJbXE8nIqfMC+rlMATTw6bumfRkFzNlAH/R2J7lh+53mG7VfdVR0/dAyGuBlQ8yV6vSRzVHT/rT00HUdHdWea5AF0JwNH1Bvd7neZ0QyJ+o0/+dyG2Dwl5mKru1fRCGeNkY2BpGE6rSdSlF/6vSoEjIrvhhNc3u4kzXTw/L2mW3Y+dLo9ad1ztPwkQ1HHv365XDysWd2r1vXexjNnxjwdJ1R0/o/WcAc2vBBb3LX82mc/+tE8w39n+o6HVo2gLxsjP1f0/5L6ZCBoauu7adFIZ5kozeP3EtEkjptaWrUn+Xta8+HyNqOozd6NCjzdxKX0RR123hMt8NHkCNr17rbKsrWvywjl7YOrktiiStNiL2vLasqRXRu4xjytRMb6Zq8UU9anKCR1aP8k8a3yqjtuDeoR4NSHZSQy+gous1dwlz5amOFXh2JG03mLsJRfJGi5/Ygd2v9vorEduQ7ej2d1hpQdftLNXm/0pfDfcieXae8bRvyHjafJgY8YWfUbm+lIXXEJK43giLuacs4lH/Q8udkTNbMl4Sso791ZKC68hX1ZvPJxekzSoNzZI+cx9IzanLqEbaY+nlY688l8+WdF+j6chNn1Cpj41XhUeOpTL7F099UmdIzaja9KOzdbuQi07kus4f6QVPpB93k51E+61oFZ9Ty02ndqBZkp+sTWdsuXd+mD8d7k1TXjvnIzAzZV5+vN883auBTV+BRPLkLNWUWre5hRyKJE3V5cwPtTU6njPTjtHvtFGrHHKxI1pxmHdE3Ak5JRFZuFDxzLUUfTaW0pEhaNtCLJZRMgX1m09EiTXVS3aTdk73JipXLPXrT3G/2UPKpU3Q05kua1tmFpKzcNmgBHSvNC3QWXpVdqKmu76LxHlIWYO2p1ZhPaOeRNNa/KFoxuiXZM0MXMcdQPQs1jeFIGjxPr6+No+S0k7T/u7eoZyMWjJihBi08wcKClsJfaWlHe5a0K6hJn7do/Z7jlJ6eQvGbFlCody3WdwfqvPwUM08LwYJd/q1omsA5MOsB9O3N+5RfUKQ2bk3ioem7lVswzVwbTUdT0ygpchkN9GKLFuYQfWYfLe8Lz75r2heTtY0NKRq/QHPW72U6kEqHflhCoV4Kdfv+7ySTwTq2ShT+upQ62jPdVTShPm+tpz3H0yk9JZ42LQgl71pMXxw60/JTZT3UBHexNdnYKKjxC3No/d5kOpV6iH5YEkpeCqYzMn96J7m8h3xlprq8iQZxwcyqMYXM20j7mI2dOZ1C+7csooHNmMxY4unx2n4qVXneMis4TvMD2MKLlbt2m0lf7T5Gab8mUuSK0dSKk4NVC3rzsCYR4ScbtqjbNZ48pKzcvhWN+WQnHUlj44xaQaNbcjrAZPMULtTE1jZko2hML8xZz/zlKUo99AMtCfUiBef//N+hclUppF+XdlT7HUWTPvTW+j10PD2dUuI30YJQb6olEpND5+VULu7LtGmQE5OrFTUOmUcb9yVT+pnTlLJ/Cy0a2IzVZwmNx2u0v1RRSpMk1o7MLYSWRB2jk0d/pI0xGUz3TIwpL0bjAxSd6eMs/RlT/f0dDWC+VK/9KqLMWk097FibTl3ozQ1Mh9MzKP34blo7pR3VYTKRNZ9F6tDyCP9U+iWYiC3W3EKWUNSxk3T0x40Uk8EJjY98lVSYf4uiJ3CJvDUN+PYm3c8voCJ1hlNAx+cHsIUU65NrN5r51W46lvYrJUYyPW/F6bkVtXjzsPrLjur2l1yyt2u8B4uNYrJvNYY+2XmE0tKSKIrZckvOblkfn6iFmupv+qafLcsvGtNr+8siICteT31raxJacYOXaZd2ncRxa8tAtnCXUat5vzIfZ7iYetQ8an05l8SyOXMLnklro49SKpNf5LKB5MWSbZHMh2aXJSgVL9TMt/Gq8ojx8M23+PobS6D1Qeo+ShrQ86+vpbjkNDq5/zt6q2cjkrE+2gQtpBOlU/8on2XyZiK5tPtVL9aOmGx9R9CHOxKZPRylXSvHU1sHMUmkrL6JhZp5Mnu87KvL15vtG3nWFXg0T+5C7f4WCmUJmvSZGXRYz4CVlLk6lPwDutGUrTnsL0apETDHFrQwjammDnmxNKERe0/2LC09qwkixemLKdCKW0i9QF9kGni2gl9pSYfazGBtqeeXOZqyKi/UlPTbsvbMGCXUcNhWuqJ23lpUV2j7CI0Tr66FmsjKn2Yd0v3akL13ciG14xJgx2G0PZcrUdGVDf3JQSymeiFrKctALKqc9dSvvpjE9YfQ1pvaQktQuJcmsfkR1QqlLTpBsTTxECmCaGGavrXnxU6gRuw92bNLSTOl/Pte1r480Lj9mPHq92Ttl9E5S80Hm+cN/R1ILK5HIWuzDBaAKspZ34/qs/7XH7KVNF0sDe4ikgcuJP0u5lHMeO49GbVfdk5jAwx+MlPShZVdmGNni7FJe0hfO5h+7J9CHgYy4CczFV37bgCbExYQ2y+hVL3q7NpfBJMdCxKOL0VSHl/ZKH9jNseST0lDGrb1CqtRjurKdhqhDohP30INIjkFGvm/GBrPvSdrT8u0E6m6soH6s2RCXC+E1hobC63vV5/NRX0aojUW5YWV1EXBLZYm0R5jRaEpHvrtlyVJLNkf8O01vfkxOSa2IDkwtQlLSuT03Ifl+szN/ZV1IUxPpOQ9M6l80VBF7m8JZQmKlJ6ZcVi/TWUmrQ71p4BuU2hrjrYXFfinUt8qdmALuGv6I+QrX3YR2jupERt/LQrVuYjqGrdIZcmjTXtaom9AbE6+oGCWJIkdX6LIPB3brCZ/qfxtGbVnCwpJw2G0VT+A0ZXtI9TXfqIWaqzfl74MZnogI/93T5b5nLzIUeQoqU1Nn2H+VepNbx4p1ZD7tGuME4mlzbULKlN3ZjQ9j1x5qS9XsMWBoS+PncA+w/zVs0vPanW/4oWauTZuGSoYD898i789WIBSH8QWxv6zDunHt4KTtLAd92WEIw3TJD+P9lkmfK7y7HJ6nvOJDYfS95f07eHm7knkJWWLfVMLNTNl9njZV4+v5+MbeflRgUdS8zeLV4TUGc6OYqgubMO8uesQn3Ed3G5d7qCt97QopJ/8GWtGNGZ/6SD1Q7/BfpBr/1RTKwBtm3PLoFz8fUPFClTIiduDUw/FcAmdjnHeBhtpFW0wdXof1BHdx5HYfdrCKlJyCft+SsVDsSv6TwyFi+6siF0Q+tpQNK22/bwiyDtNwvSOttq/NSjavIoJna2ZWA4g9hD3oI67iI8+yP5bF70njDbqj7jxUIzoage6dRBxhx9oS6sfqV8/DPbTm1E2pW2hmdK/oZ7SKvRd6j8AQwzb9/dDU679e3dwR92+Bbgbj+iDd4G6vTFhdFODfeFiNB46Al3tCLcOxkG/i1L4DxgC/S7Wgr9fU6b7hHt37jCN1sc8mUnQZFoMzp89iT2Le0JfO9gyp5EbuKMRKCxAAfc9oA7myewBDu05hHtkg26vvIrWetXZtcduwLEz2fh9w0DU5imbkkv78FPqQ4hd+2NiqIvemSWxSyheG2rYxlOC1B8Dhhj6P3/4aSYGd7TKfDc+GhpxT8BoY2PB0BFdYUe3cDDusLpI0mQaYs6fxck9i9HTWFHgplEUFBgqisQPHTvX15sf0yjQceQgeEke4mTUDmSWKnTJZewMP4Q8aXMMGv4sLHX/O6mzMxzFKlzYNg9z18Uj47omskDijWlR6Tj58xqMaMxkZgYSv47oXF9/hHzlWxEPDu3BoXsEm26v4FV9A2JzMhYbjp1B9u8bMLC2tpBRPf6yBJf2/YRUFjNd+09EqH4AY3H0NQw1bKTGI4Zz794IsFIi81AC/lTLpQgnE47itiwIE15tBxtVNo4m/qnxr0XHsS/hJpNNL/QNqKwmSuHXb7CRLw9o21zty3P/vmHky40w08b/EczKtyxnD5VBJO+ESdM76sc3luO9OqEzrFkfD8Qe0hZqMctnqfBn3G6cKJLAc+jrGOyqbw/1XgjDuLYV2IOZMnss1eTr+fhGS/rRp53Hx8iairwL3ninLxqKr+Pwqkno5e8KR/dAhIx7G6sjT2gOdxsidoKrq4FiiOWwknE7aFVQKblEQomsrD9Z6JGgWes2LEUwxq5VK5Z0Eh5ePK8tqSLFWfg9WwmSNIWPj7GTt/JviWZcH6sFCRr5tYSToSaI66KFTyNISu4iO+saE8t5ZJ4vBJXcxPeDakMkEhm87DByxx32/j38mXNd20j1I3ZyhfGUWkEzpSpoprTyfRc7G7cPa2uNXrD2LfX4VuX5TJwvJJTc/B6Dahv2j73sRmLHHfb+vT+Rc133qiyhcHVls6iPtbVGc1Uq4x6aJTMOqS0aNmsNL1kWkqK34KuPF2Huay/jxW6t4RG0AMnFrE5JCbefSg+zZKb6C1nZ+SiRuMGnhT1Xoo+NG1q0cIcDMwe+sinO+h3ZbBCSpj4wNicr+Ldsph6r5XiAUxErsWLFCvNeH69GTOa/8DBnsbOx/4M1NKrC/J96YpQ4n3kehVSCm98PQm1DWbOX3cgduMPev/dnDvcBhhS2DZuhtZcMWUnR2PLVx1g09zW8/GI3tPYIwgKNoqDEQFFEMke4OBn2xzRW7V7CUD8pilN3YsdvGtmpLkYiIukBpC0HY0Qbyy0E5F3ewDt9G0J8/TBWTeoFf1dHuAeGYNzbqxF54qr2C0FzEEHm6AL9IVZGvqZQ4a+sbOSXSODm0wLGFmQDtxYt4M4ZkA7V4y+LkfV7NvusBE19fIwXzFb+aNlMZnQTmCqhPIfozz42sq1PNhzCFQs5ZUnjPujVkulc2kEczGWNKjORcOQviFp0Rp+Q9vCTKnH6SCLusLoPU/fh4GXApUcInjUO4WYihpORLxdDbsXJjpjrZDmCtrRCzLLxfwgz8y3L2EPlkDTyQ0vj5Ad1W/igkaQEd7OztGUazPNZSpw7e55JWwJvf39je5B4oJVfBYs9s2RmBtXk6/n4Rsv5UYEnd6HGkoNmkyJxIuEbzB/bC61c5Hhw6Rfs+e5DvDH4WRYwBuDTlDxtXQ0ikQxWj3WihKKHD9l/RVAwrTYpILlc802F0pxki9teqv1nRVAhuyarxPontzJxRZkNbPS+GrEsVgpTjbMAodAEVyU3zpJCFHAP7JA4IWjQGIwdO7aC12gEe2sWCdUPcyYyq8d/k17pvrP2pTLItH+Zwky3+VhKCguYw+S6GIRBY0z1TfsaHQz9LooglfHpoZky4yjKQkRYVzRx9UGnAaMxZfZCrFgXheRrtRHQtxPcTebGZsqMilDIeWqRFRSKR7shvrIh1rDGnFiAM2lONvrfNFaVkjwc/d/bmDNnjpmv+dhy6qH2w/8cIpEUj1eVEhQWcM8Ek8ApaBDGmJKz9jU62Fv9Me6XhqyIMHRt4gqfTgMwespsLFyxDlHJ11A7oC86mVYU5niYHpqbvUv9MWJoW8iU6di54wxLMVQ4v2MHjhVaIWjIcLSw3DqNXasZJkWeQMI38zG2Vyu4yB/g0i978N2Hb2Dws03hM+BTGISWCrFiY9QfYmXkawoWpzQGxPx3BXHKiOryl8RsWRMzZWzRZ9wXGWwsHcAepmLTPGPbeuujWORY6jsQiTf69GoO6YMUHEx6ANWVBBz+jdDoua7wadoVnZ6R4MGJRKaDSvwRfwBZJQ3Qo29Hk1/umgXz5bLHJyiPxDwb/2cwL9+ylD1UEiuFyVgglis0X+YZ5nhm+SxmD4WaMVmxRbYxIrZgMvQLGsyT2eOpNl/Pxzda0I8+7Zjn32ssUrg8Nw6Lv/0JaZdv4lLaPmxeEYZQP3sU5cTgnTe+wG+8f+kXo169Ouy/Jbh+5QpLB4xRsfLrXCJYt56mQMwCIHOyVKKC0vAbK8pD3n3tvytC2gAN6kmY3dzEtWvGUabk/i3cKtD+YXEId27e0titHkpcu3oTKuY4HJ0bsKBVF3XtOddSC+2mfo1vv/22gtd6zO/rrGmipvAE9F1Sty40XWyHqV+b6pv2tX4++qq3klU3RUj5YCjGfHYYNxv2wewvInDgRCau3rmLq2eTEDm/Oxy1kaZSX9KK2Zw4sAZKbuG6qe0cqgtI+GEn4lNy8ICnbKQNGkBjTtdgbE4luH/rFixqTuI6CFkShejoaDNfP2BOp0qnc9WMBHXr2quTiFrtpuJrU3LWvtbP76v+RFHKBxg65jMcvtkQfWZ/gYgDJ5B59Q7uXj2LpMj56F4lRSlFAu9hw/GcQomMnTtwqvAPREadwENFBwwZ6sXetTBSFzw3bjG+/SkNl29eQtq+zVgRFgo/+yLkxLyDN774TVuRL/zlaxoxa8eBtVOCW9dNbYlT4ULCD9gZn4IcvskQb38pRYMG9djISnDz2jUWOQwouY9blg5g0iboMmwURo3Sf700oC0aWEwZpPDv0xNNxLdw5OcU3Ew8hF+L7dGhSyDkVq3QraMzRDeP4fAv57E3/gxUdbuibxcb7WcFzMNS9lA56M5N3DKxeFVeu4qbKu4X8crkA2I4OtaDmIpx4+/rJmzzIf6+fqdq7tAiVFL2fHxjtfnRp4sndqGmyozEotfHYszyw9Ac2VHAuWVPjJq1Ejv2vY9uMmYOv2fgHLfrhhdW8A1qCVsxSwj2xSHLyMqKcCpuP7JVEji1bKspEllzO7uAgju4zR3n0qEk9xROXXzMV3zSFmgfWB9i5Vkc2HfByLDvJiQgrbi6vgpT4UZyEtINv+DPP4K9h3NBrG/t2tkym/ZEYBsnSFR/IX7Xca3MdSj5C+GzhmDExNnYZNRYVRCzRTD7X1WG/6/13XwknoFo4ySB6q947Dpu1EPWxXDMGjICE2dvMp6r6uBhGqIiT6NA7IYxayLw0dTB6B7oDScbTRaUd/oMswH2DxNbH81C7IyA1u6Qqq7haMJpFrr0UaZtwPTRg9B3+jZca8xPNtIW7RFYXwzl2QPYd8HImpCQkAbLmpMVGrfvi379+pn3+r/eCNA7x1OTkMAzsA2cJCr8Fb8LxuIuwV/hszBkxETM3pTO/n6ItKhInC4Qw23MGkR8NBWDuwfC28mGtcTIO40zGkUx2vrIF4nHEAzvUhvKc7uxc89O7P61GDadh2GIRc85qJAZuQivjx2D5aWHQRXOaNlzFGat3IF973eDjI3594xzmvd4+ye+8tUgNrqIGM4BreEuVeHa0QScNjYgbJg+GoP6Tse2y0ZB7NHw9pdStGgfiPosZp49sA/GJpeAhLTiKrlwI6zaY9r6Tdi8ebPe67vlI+BlQXWwCuyDHq7A5UNx2HggGfflQejSsRZ7R4723TrAruQ8Doavw+6TxbDrHILuJnZx62I8j082VR9P5ezBUqhuJCPJKKDm48jew8glptft2mnL+GAF/+cC4MDs4fTBA9A7qcCRdxgHjt+vshb887Ln4xv5+lGBR/HELtREiqtI2rgJWz58D5+d1P3KUIXLicfwBwsWUs9mMLwXiDnUCZmgDv6FR5fj1fcTcaPM0JS4HPc2pnxxBkqZL0aP76opljaHjye7UPFxbN94BoWaUramO4+It1Zgf/7jjMkGvV4ZjRayQhxZPhWfpHC73jU8zInArPlROn2wPMW/rcEMNk5uG74a5V+ImROGb7NLYN9jAkY154SoQLcJL8NXrsIf66Zixo5snT3G+Tj99TTMXBWJ8JgcSBpYcB+SyApyKxFIdQs3blZWCP9S3/mg6IYJL/tCrvoD66bOwI5snR3c+afx9bSZWBUZjpgcCf6RLorlarmDHuD6Nf1v/wqztiHsvV24xQrpYREeVmparNBhzEi04n4hWTMTS5NulV+DjXfN/HXIUNqg47BBeMaGp2xseuGV0S0gKzyC5VM/Qbk5PUROxCzMj7qhNx4BfRTdJuBlXzlUf6zD1Bk7oC/urzFt5ipEhscgR9KAlYghl3PbeAgPrl/DHX1Fwbaw97BLoygoqpyilMPdWGlEMOxVGYhc/D1+Udqh+zCDmy9VGREUV5OwcdMWfPjeZ9APLZeReOwPFmGk8Gym3QpUCf/ET74cIlhxMiYVbt24Waa7Vh3GYGQrBZQZazBzaZLaHjUwn7ZmPtZlKGHTcRgGPcN35cLfX9r0egWjW8hQeGQ5pn6Soj63peZhDiJmzUdUdQaw6kTeAX26N4Dq7CZ8GnsNYv9OZQ/stu3SDUFyJdLWrcGRIuarQnrCQf1ORZiexycXy4yHvz1YkOLfsGbG+0gsT37wV8wchH2bjRL7Hpgwqrm2nB/2fSZhpJcU9356H298d7b8yw7ln9g1ay6+5/vliRH/huz5+EaeflTg0XC3fnwyyaPEeYFkK+ZuOexCrYNDafjIodS/szfVkYlIZO1DU2K1D8HV3rKUu31q2Z1yy7hF6/rICZIm9PrPpTczVdHN/W/Ts9zz2EQyqufTjV4cOoT6dfQiBwlrW+pMwStSWA9KUdHlzYPJmXtPbEuez/ejwQN7U0CjWiSp04H+r1MDEj/mOWpE9+jIouepjnY8bV8YTEMHdKZn7CUkdqhHdaSiaro9v4Sc/FuSi9SKnFr1pIFDXqSu3g7qZ8XJm46gjXq3bM2jlBU9WV1unLXJvV0fGjw0lILbNCQFy1VE8qY06vtsy97yXJVNn3ZVkIi5JBtXPwoKXkAH2TRpbjctIsWLm9XPCdLj1rr/b+9e4GM60z+AP3PL5CIRgiRCEpHGLSiRUnVtsKSrxLUspVVKlW1U6UWV2rKqq61auqXdpVQbpCoaVmhoULcWQVGUatWlqDZIwkx+//fMTGImF02I/Y/29/18Qrxz5j3v5bzH+8yc8x50MQsMtZ5EQZeWsew3yt96Zi46eQiMdcaiYHXm8pC1HTM62p/Tp68Qinu6qGMgoQOaVLfX31x7ABYfKyih4yGpzss/57PizNxO8BAj6ozdXLA0btna7Br2vdYW/trx6B2G1n0fx+jRw/Fw11jU8DbAr24s6mvL+lYbhE/yV4Yvc5tdwvZX4xCo9YmpKqLvT0Df3g+geU3tAdsGVOsw8/pS1WVqG+XXzZh8XyXo1WuewU3xp1590K3NXaho0MM/oJLK54+3PH+x5z/rGczt5AEx1sFYp4M5a/sMdAw22p4bVCH0HnRR7ZfQoQmqe+psSz/XHrAY+c19bd9raKuOBdF5I6x1Xzw+ejSGP9wVsdr5z68uYutrj1aohkH5B0r+M4n8+yKpyIFY3PL8Tn5OQr+q9ucf6QN64QPH6tnlKisDE5r5Oo6du9Eh4SH07/Mg2kRVsj1fyaveCKzKfwhsCeen/Oeo+fdNKjrWlLK0rzaej73ezn6e8glBdGwHTNR2olza/iriArV8TKgafT8S+vbGA81r2h48bqjWATMdA+h2ny81v26ejPvU/5naEuPBTf+ktu+GNndVhEHvj4BKqox31PL8111MeggB6jwo6nwa9fT18yksB/BKc5PtWNR5d8Qcl2XYi1uev6R+vNG5XOueLjCLAbWe/Myx3HrJy/OXZYzfuhLqU+b5VlnHQzlwnIMMgQ3RSO3XI7AxOvboje7touCvHfPq+O63wOlRMDc6ZxX7HDU1h1z7FBprD5HW+SC0eTx69X4Qre9ScyuPENQMNKg2CMWIwg+8LnWb3UTbl8O5vkznxrJsSzd0BwdqivU8ts9/Ggn3RiHIzwyj0Qy/oCi07JGItzefuf6fyE2cODRZB5Lx8qD7ER3iDy+TGRWDItE8IRH/TP/B9bkQNlnIXDQOCbG1UMnLA17+oYh5cCzezzxnf97FbwZqmix8vWwS+rey18fsWx3RnUfh3c3voEeF2xWoGVFvXDr2LB6DLtHB8PXwgG9wA3Qc9gY2/FjcznJwPG0mhsfHIDzABx5GE3yqRiC222jMyTh1Wya+F7e+jt6Ng+Btm9C3xPTDFtWlZZ14aEpf9v+XQE2TcxxpM4cjPiYcAT4eMJp8UDUiFt1Gz0HGKZcS3uZATbGexaZZQxHXIBh+HkaYvCsjrElnDJ2egsNZ32F2nDd0xkiMSrdPqG+uzbJx9NNpeDSuIUL8PWFS9a0W1Qr9J32MQ4Xn6aVuG4esr7FsUn+0igqCn9kM3+rR6DzqXWx+pwcqMFCzu8EkLud4GmYOj0dMeAB8tP73qYqI2G4YPScDrs1txdlNszA0rgGC/bR+8UblsCboPHQ6Ug5n4bvZcbbn6USOSrdvfiuBmjpH2p8RqEfggOW46Egtb9bz2zH/6QTcazt2jDCa/RAU1RI9Et/G5jOuR01x56ffCtQ0pW9f5eJWvN67MYK87UFZy+mHHS+o5jz6KaY9GoeG6v8pT5M6p1WLQqv+k/Cx0wC63efLfFlfL8Ok/q0QFeQHs9kX1aM7Y9S7m/FOjwp3bKCGcwvQvaKatOqDMHilc+vlYsvYujBqE9G2M/GtS9WKC9SUYvvxTg3UlOLqc5PzrTKNh1vlOAcZ641D+p7FGNMlGsG+HvDwDUaDjsPwxoYfXY/vMgdqGgvObJ6DJzo3tv/f5lkJES3642+pX+EtW39E4qn8hwDfTJuVte3L5VxftnNjWbalkum0P2xfrREREbm1K7JmWB3583uQwSsPyfx4Lt5ARHcQ6xF5tU19Gb+jsUzZvVUm1C/Pe2zp9+iOvUeNiIj+YC59JktTT4muVi8ZGMcgjYjcT+6GsRIT0VDaP58mhRf9zvtpk2w5YBV9xbrSgA98plJgoEZERG7skpw6flLOnNwtH457UT46ZZKmgx+T+8r50VxEROXBVC9aav78tWyc/bxMSP5GLjlW+7hyYp38ffALsuqiXsJ6/kU68LMmKgVe+khERO7L+rW8cu/dMmGH9qwVnXg1HCOpm1+Tdr72l4mI3Euu7JvTR+ITU+T7azoxV6wqAZ65cuGnXyQnzyjB978kSUtfkFaVHJsT3QADNSIicmM58sUbw+SV1efEO6qTjHhulLSvzkuGiMid5cn53cvlvfdTZeuB7+Xnqybxr1FPWsT/RR7pGSNVeQqjUmKgRkRERERE5GZ4jxoREREREZGbYaBGRERERETkZhioERERERERuZnfRaB2+dJlx29UZpcvCVvvD8RyQD56aYwkjntPdl51pP0OWQ8tlcljEmXcezsdKbdBobFjOfCRvOTY5/9L097iWLbsXyITExNl/H92icWRdiOWPQvlebX9C4v2OlKIiIioPN3ZgdrFPbIwMU6aDvtErjiSqLQuyp6FiRLXdJh8wsb747Ael3XvzpI330qRg6WZjd+hLN9/Ju/OelPeSjnoSClPxY8d6/F1Bfv83zZt+Yxly7dp8o4q/5xVB0sVaF49vEbmvjlL3l5zxJFCRERE5emODtRyt82RF95Klx9yuHBlmeVukzkvvCXpP+QIW49+b4zhneSJceNlbI9oR0o5crexw7FMRET0u8R71Ijod8cQmSDPTp0mUwbe7UghIiIiurMYJimO3+8gFtmfNFXeWr5BNmeeklyVcu3Uftl1KVRa1Kl8PfrMPSW71iyXpOQUSdu0W769YJLA8Oria3S8bmOVb1bMkDeX7BVdgxgJzTsqnyUtkqSVafLFoZ/FJ/QuCfLRcsyTXw6tl6TFH8nK9Tvk6OWKEl67qnjp7Llcz2eXWOs0kxqXv5QV7y+S5f/dKl//kCOVatWSyh6OTQsrVTktcij5VXnzw/1ijK4v2L5I5n+wVr78wSrVIsKlkiNvy4WDkrHqY1mxKlXWrMuQnQdOSo5vDQmt4lXQLpb9STL1reWyYXOmnLI3nuzfdUlCW9QRvwPaax9Kxvkgadmgqkskn3c+Q96ZPk9SDhqkQUy4+Ki6Ww4ly6tvfij7jdFSH9tl0fwPZO2XP4i1WoSE5xdK9dCpXWtkeVKypKRtkt3fXhBTYLhUd61giUq3D4tcOJghqz5eIatS18i6jJ1y4GSO+NYIlSpeTrWwfiMrZrwpS/bqVB1CBcczJHlJkqxYkyGZJ6+Jf2iYBHgWdKqTq3L6y1Xy4ZJlsmrDl3Lskp+ERgTIT/+dJf94P0OyQltIncrOraV16y5ZszxJklPSZNPub+WCKVDCq/tKsbW2nJf965MlaekKWb1hm+w7flEMVUNL3UY2pcnDekRSZi2RXdl1JGH8Q1L75Cb5eMmH8nHqRtn13RWpGB4hVYutv8iVE1tl1bKl8vGqdbJ59zH5uXB9rMfl0zdmysI1h8WjcRMJvT441G4/kX+8sUj+m3lNImMjpWJBU+XJj+tmy2v/XiMnK7WQBlmrZMabS2SvroHEhEKOZyTLkqQVsiYjU05e85fQsAApoXgurEdX2vaX9mOAtGsUZE/7ZsUt533DsXM0RWap8Z9dJ0HGP1RbTm76WJZ8+LGkbtwl311R54uIqiXkf/Pj40blKTgcLRfkYMYq+XjFKklds04ydh6Qkzm+UiO0ijgPDcs3n8gbH+6Wa/V6yjM9Q+RQ6gfy/tJUycj8Qa5VDpWwyp7iXPxrXy+XmUv3i65hHxnfo54jNd+tjXkiIiJStAde33kuY2k/f6hJg3alj+PHgJrD05Bje92KsxunoVukT6FtdPCp/SCmbjyrtsiXg9THQmAwxSBxzvNoF2xyeo8OxsAOmLHjJDZO6YAQk+56XjoTanb/F77OdWRTkE80nnzzebSuZnTJx1StBUYt/RbXHFvblaWc2Vj5SCD0pqZ45K9xqGZwlMUQjIHJP6usTmPd5HhE+OgL5SXQGSqh6chknHBkdnlpP/jrXLcx1ByONNV49tf0qPyXZLVHV5aD09DCJDA1m4L9Fnta9spHEKg3oekjf0VcNYNj3wYED0yGKhWsZzdiWrdIqKDOZX86n9p4cOpGnL1ewRL95j5Or8Pk+Aj46J36x/ajg6FSU4xMPnG9HXNS8ViIAaaYcXjvlc4INTu/R/VTYGu8+Nl5p3ZXLmdi3oD68HPOX/V/cLvn8PdHo2A01MRwrfHyWc9i47RuiPQpVB6dD2o/OBUbC1U69+ACDGrgB33hNjLXQMeXN+B8Kdqo1Hk46q8zxyHx5a4I9ypc/zaYWLj+uUewbExbhLi0lfpR9Yl4YDLWncrf+md80LsS9PoA9Fv6qyNNY8Hh6S1hUmXT+cRj3hmn3K0/4u3O6vg3NcOUfRZVvMcQYjAhZtx7eKVzKMzO9VFtHtj6RXxWigbJSRuOmmqMeHZ/35GiVf3W877R2LHnr4M5LhEvdw2HilNd828zsUj+tzo+blQelTtOr5uM+AifIseF6Ayo1HQkkvNPCop9nKlzT6dEvNA+2NZf+dvrTFUQO/IjHHU6gTmfK5yVx5gnIiIi4A4N1NTUL+cyLqwcYpsYeXX7N85duozsXPsMIOerqWhVUQUsnrXQ5dn5WL01E5nb07BwYgKivHXQ+7fB9D35EZYjwNKZ4Wn2xl3dX8L763diz7aVmN4tDEadmriE1EAV/4YY8OpybNq9CxkfTkCH6mqyq6+Khz66UCgfD5jNahLf/jl8uOMEzp7aj9X/6Is6ar867xhM3HZ9Ql+2cjoCNVUevakm4qck44udW/DJghTsV/U+ubCnbZLlERaPCQvWYlvmPuzdvg6LJvew7VsM4XhinSP0suTg8oWVGKJN2L264d/nLuFydq5tcn5zgZqqmwqkasZPQfIXO7HlkwVI2a/KnfMVpraqqMrsiVpdnsX81VuRmbkdaQsnIiHKW73HH22m70FBrFuCG+7DehILe2rt4oGw+AlYsHYbMvftxfZ1izC5Rx14q8miIfwJ5Fc9P1DRe/nAxzMMfxo3H2u27cGujR9hSkIkPFX7mho+j20FE9Lz+PTxSDVp1cO3QT/8fVkGdu/eghUzH0VTfz0MRtWGLoFaDr6a2goVVXk9a3XBs/NXY2tmJranLcTEhChVHj3820xHQbdajmBWnJ/KIxBtn35PlSUT+zO34tO5I3BPJXVsmOpi7GanILA4ZcnDUX/bxNmjJjqMmYuVW3Zh96blmNYjUgUvqv71nsGW/PJZz+HT4VHwUOnm8M4Y/+5qbNuzB1tS/olRbYJt48M3diK+uGTbGGfe7QpfFQSEPbFOtYSD9QzmP1DBHmDrq+HhFZcdLygXFqGHv9pn4wn4SrW5PdjRw8vHB55hf8K4+WvU/nZh40dTkBDpCZ0KeBo+v63QBx5FlRyo3WLeNxg79vy1oESNw5odMGbuSmzZtRublk9Dj0izLf96z2y5fryXx/i4QXmsJxeiZ6Dqf48wxE9YgLXquNi3dzvWLZqMHnVU/mJAuOqn/KFhH2f28huq3Ycn56Zi2+6dWPefZ9GxhkmV3wexk3YU9GuxgVo5jXkiIiK6gwM1Tc6aYaihJmPeCYtQMPWz/oj3HvS3faofP/dIkW+wjs/viip6Par0/gDnbGmOAEtNTsz3TEGm0xusx2aijYcKcnQV0emf38IRmygWHJzWAiYx4q6nPndMOq7n49FwLDKybIkO13DgH+3gp01qei6y77fM5XQEaqIm+iowPe38qbTlW8xsqyaaKhgbttr5mwxNNtaNCFflMqHFtIPX65CzBsNqqMmddwIWOc2bby5QExVUqkmiS6Gs+PG9B+Gv6hAQPxdHCs1+rcfno2sVPfRVeuMDewVLVPI+tKrPRFtPNbEMH4aiVV+HEeEqKDG1wLSDjgLnByoqMG82aff1YEKTlYJHtdectrccmI77tPyr98HiH1zrd+7TYYg0akHw9UDN+uN7eFAFcPqAeMwtWmnM71pF9XkV9M6v9KVFSFCBtPGup/C5y+zVgkOzEtAwpj1GfHDc6dgrRlnyKKi/p5p0F67/KgxRx4SYmmPqAfser2W+jGZqDOgr/wmzDxWqT/ZXmHKvCsB0vuj4z+O2JOsP/0QHVRZTwxewM3/zrOUYUNWACrXvUoGMEVFPby6YqF9aMUj1rRF1HQFMfrCjMzfDpN0upVPd86jtNVOLacjvzpKUHKjdet4ljZ2C/D1ji+a/aog6V6n8m0+FvWnLb3wUXx4Lvp3ZFp4qaA4fthpFh8YIhBeqb/4403k0xNiNru/I3jkJ92gfHlXtiw/P29OKBmrlWCciIiJS8/7fm1/SZGX6LyKVO8uQgbUL3Q+kl7A+/aSdH+RCeqp87rKUtVHqd+4q9ZzeoA+qLbX8dSKmGOmaECYGR7qo32qGhYiHLk+yfv1F8hypNjqztBo6WlpWcPzbxih1Bz8i9/tCLm5IlQ3aw45uupwGiW7VRqo495yhloxKOSoHdq6Wlzv6OhLzmaRGzSDbvWY52dm2a5BuB0N0K2njUqhfJG1luvqzsnQeMlBqF7o1RR/WR/q18xNcSJdU1wqWqOg+tKqPkpSjB2Tn6pelaNVrSM0gW80lO7tQzY0NpVvvaDE7/mnj3VCia6texq9y8aJVJVjlROqnsiPXIBF9npReIc771kvAnxLlkaauFfslbaXYu3WIDCxaaenTr5344YKkp35uTzMGSVBVvVi/XSITxs+TtP1nbfdcav0cNSpZMnd+JnP6OR97xbiZPIzR0rVX4frHSNO6Wv3Py5mf7PU/nrpa9lzVS3DCaHkkqlB9PJvIyNFdpJLukmxetdaWpA/qLJ1jPMRyaKNsOKHlIZK7c4Ns+dkksUMel3t8rHJsS4bYX8qVrWs3yDnVLp0eiBHnWziNDbtJ72iX0qnuiRZ791wUW/fcpNuZt8YY3VV6Fc4/pqnYm/aM2Jr2NowPVwapNSpFjh7YKatf7ihFh0ZNsQ+NbHEdGjoxtx4mo1u5vsOzyeMypI2XKv96WbWxpKe13e46ERER/bG4znp/ByxHD8nRHEjeucXSs4JOdLpCP379ZdlF9fqvJ+T4WecQSy+BavLiOrcwiEG1kM4cIFWvr35gZzSqEEhNvFAoADDUlEZ3BxZt2Ap1pE4Ng9rvMTly0nrz5dSZpGpwYJGJu9G3utS5O1JMRzbJykVvy2uTx8sTD3eX9neHS+zEbXJNbZOXd7vCNJ2YqgZLoHOhLEfl0NEcQd45WdyzQtH66fyk/7KL6vVf5cTxs4433Ugx+7Axim/1OnJ3pEmObFopi95+TSaPf0Ie7t5e7g6PlYnbbDWXIlXXB0lISOHMvMTLU/vbKlZbk1vk4IGj6l8q4GnY0CWQsDGES+PoKk59bZGjh45KDvLk3OKeUqFInXXi13+ZXFSv/3riuP0t5rby1+cfkOr6s/L5G8OkU8MQqRraTOIfeU5mLd9hXyDit9xMHvrAovXXm8XDpF2gqOpv0RrMIkeOnFCtZ1DHVhOxNU0hfo0bqwAHcvW7o/YEQ5h06dRIjNd2S3r6efVeixzasFm+19WXNl3ipUW0USx7N0vGRbXt1V2yNv2kSHCcxDd3bV19UIgU7R4vexmsVtcPR8roduat0QcWzV9v9hB706qxb2va8h4fxTD6SvU6d0uk6YhsWrlI3n5tsox/4mHp3v5uCY+dKPahkVfowxuD1IhuJIGFT2D6ylK/Xg0x5P0ix46cdiQW8r+oExER0R9IkXjiTpeXk60mymq6ERgrPQcNlsGDS/gZ2EGinGeeaiLhaZ+lF6VNMhy//iadp/g4L6WWT68makYtl2tyVU2QbrqcKlzw8ChamtwjSyWxXS0Jqddaug0cIc9MmiHzkrfJ6Qox8kDr0EIB6E3SLpV1/FqYh4eHaxvl5Ui2vYIS23NQ8XWz/QyUDq4VLFGRfdjkypGlidKuVojUa91NBo54RibNmCfJ205LhZgHpHVo8TXX6VSgrUXaJbFVFJKToz2byqD2XdzGOhXYOZcpT3Ky7dsHxvaUQcXW1/4zsEOU4z1GqTNsuezY8K68OLiTNA42y5UfvpTV//m7/LVXc6ldr5u8vj3LsW1Jyp6HTgX8qjl/AyT36lX1p31sFHuyMJvt38pZ8h/xrILaLp2krvGKbE/fJFesP8qGz78W1Ggp7erVlnat7xLDlR2S8UWOWA6nyfojeVIt7gFp5XIIqPFmNNk+CClJScfhb7udeWtU/iY1Rh3/KtFtGB9F5B6RpYntpFZIPWndbaCMeGaSzJiXLNtOV5CYB1pLCUNDPDxdvw2004vZ02Q71i0FfV3I/6JOREREfyT2KyDvTMXdo2bZPwXNTAJDrZH4zPU2kRLkLwLiie7vO91woslehUeD9ND59cFHhV66nNTXdn9G4CMrHfdyOfIxhGDo6mJ2rPIaEqzy8orHvHM3U878xUT80TepUGFytuHFJl7QqTpExD+D2UvXY8eh07hku/fEgv1TmkFNTdFows7r98KVcJ9N9rL+qKTXwf+hpOv3/Tlc2/4cGpSwmIh/30LbW/ZjSjOTillqYWTpKliiEveh5Gx7EU28dNB5RiD+mdlYun4HDp2+ZL8fK78MpkaYkH/DVP6qh57dUbi7tUUv5nbygBjrYOxm7Y6pXGQkRkGFdGj1mvM9ivl+xQe9KjotJpLf1gbUGvmZ6/1fpZaNU3vW4v0ZiUiI9lf9rYNni6kF7V06N8jjRvXHBczrYrb12ZO2Prte/2Yv7yum/mqLjEREGbV7naY6UpTcTRgTZYQhfCTWn16EHhUNCOi/FNptm/Yxq92TtgkHX2sNs74K+i29aH+fYr/Py35vWdHumYtOHgJjnbGwdc8NlHyP2q3nfeN71IrPHxfmoYtZG+9P2sd7OY6P4suTg20vNoGX1vcR8Xhm9lKs33EIp+0nhYLzj6nRhIJ7Ce3jzIDqQ1KLOXbV+Wewdv7xxp/fsy+gVOQetfKsExEREd3h96jp7d90OX8CbohoJk0CDWL9Pk1WbC16H0Te90kytnc/eeyZhZJ51ZFYnqxnZHP6Limc9ZVta+Xzn1QM0LCltPQv33Je3Z0sy/dmi77mIJmz9FUZ2et+aRYVKD62y6+yZO++Y6LdFuN66aNe+6KwyNcHOi8v8VJ/Z1/8WVzvRMmT83v2yHclfJhehCFCmjUJFIP1e0lbsVWK1DDve0ka21v6PfaMLLzpjrgqu5OXy95svdQcNEeWvjpSet3fTKICfcRe9b2y75it5kUvfSwVD2nYMkb89RbZm75eXK6U1WR9Luu3XnJqQoNENGsigQarfJ+2Qop2a558nzRWevd7TJ5ZmGlLsR5aLpOfHCyDpn/uaCNPCWrUUQaMnSnL1v5N2ptULb/ZLwe1y9RKUB55FM9DGsQ2El9V//1rU+VIkXu3cmVP6jo5ZjVIYKOmjjTFo5l0iQsROblRUhesl22XzBLbtpV4q5fMLdrLvX55cjQ9SeZ9ulOu+bWR+Psr2t93xyh+7JRJuY6PYspzdbckL98r2fqaMmjOUnl1ZC+5v1mUBNpPCmpo7FP9pn4pcumjVX7atqnoOefyZlnz+XkVydaXe+4pfMebw/9kzBMREf1x3NGBms7DLNqijNYLP8m5/Em0Z3sZ8nADMVsPy7yRT8myY0436FzeK/8aNUbeWJ4kKccNUq1crgcszCIH/zVGpqhJTX6RrKdWy/OJ78qRPH/pOGSAbVGB8iyn3qy1g5qnXTkrpy86RxM5cmRJory04oIqC+Rq7tWCMqnGE7N6E6wX5KeCxhMx1q0nEWp/17Z+KAv25ThS1ZT86FJ5dsY6uVzqyamntB/ysDQwW+XwvJHy1LJjjgUuNJdl779GyZg3lktSynEx3HRH6MVs1i49hFw5e1pcq35EliS+JCsuqERcldyrzi+WXsUuw6R/pFF+/e/f5K//OXB98mk5ISvGjpfFJ12jF8/2Q+ThBmaxHp4nI59aJq7d+i8ZNeYNWZ6UIscN1WxpOs9TsmnBQln095fkzZ3Olyda5WTGF3JYZW+MqCOF1/FwVh55lKRS/BDpHWaQnC3T5fG/ZchPBc1okZOpz8mI2fvEYmogAx9t50jXmOXeLvdLNesBWfj6Kjmtbyit2zgenu7bVtrHmsWye57M2ZwrPq3ipaO/7U13jhLGTtmU4/gorjx6sy1NnRTk7OmL18e9knNkiSS+tELsQyNXCg+Na1/PkadUX5/PT7d8LynjEuXfx/KkYtwQGVC3pPLcXJ2suVfk8uUrkmMpVBAiIqI/Osc3a3ck67HX0c5TWz7fByHRsegwMd1+yU7WdszoaH/Gk75CKO7p0gt9EjqgSXVP6LRl+GsPwOJj+RdylfOljzoDqgRWgdGjGhp16KH22x71KmvPIPJAeJ//uC5ZXaZy3uDSx2v78Fpbf+jVe7zDWqPv46MxevjD6BpbA94GP9SNrW9bMrvaoE8cZVWsx/B6O/t+fEKiEdthItK1xrOexPu9glQ9VJl8I3Bf117o0TkGNbwNqHTvn9G6mr50lz7aZGH7jI4INmrPQKuA0Hu6oFefBHRoUh2eal6pM9fGgMXHir2kztmN9nFt32to669Xx4A3wlr3xeOjR2P4w10RW8MbBr+6iK2vPQKhGgZ94qh5mS59tCXi3Nqn0Fh7eLU6zkKbx6NX7wfR+i5/1cchqBlogBhCMaLgOWpat85Ax2Cj6nM9KoTegy69+iChQxNUtx2rZtQesBgF3araKGNCM/jqtWXdg3F3hwQ81L8PHmwThUom1W5e9TBilfODz4tThjzKdOmjRtV/3XNorj2PTWdCQL326N6nN7q2ioS/QeVtDEKHGdttlzW6uJiEhwJUv6hTjDHqaafLCS048EpzmFS61mcd5/zgUrc74tLHEsZOmS59tCmf8VF8ea5h32tt1bhX+XiHoXXfxzF69HA83DXWNpb96saivvYYiWqDkD808i99DGzYSJXJA4GNO6JH7+5oF6WOdXU+MNfuhwVOJ7Bin6NW5jqdwzud1TEnJsS8vM+RRkRERJo7OlBTs0Fsfb03Ggd52yYSppbTcTh/BpBzHGkzhyM+JhwBPh4wmnxQNSIW3UbPQcYp56lPeQdqKp93duKDp+MRHVwBZq/KCG3yZ4ye8zl+LG7GVepy3iBQU6xnN2HW0Dg0CPaDh9EE78phaNJ5KKanHEbWd7MRpz1nK3IU0gsiNdV6W19H78ZB8NYmVaaWmJ7feFmZWDQuAbG1KsHLwwv+oTF4cOz7yDxnvxem9IGaJgfH02ZieHwMwgN8bGXzqRqB2G6jMSfj1G9PQpUb78OKs5tmYWhcAwT7ae3njcphTdB56HSkHM7Cd7Pj4K0zInJUun3zMgdqGgvObJ6DJzo3Roi/J0yelRDRoj/+lvoV3rJtH4mnXB9gpro1DTOHxyMmPAA+HkaYfKoiIrabOg4y4NKtGut5bJ//NBLujUKQnxlGoxl+QVFo2SMRb28+U6o2KnUeZQ7U7LIOJOPlQfcjOsQfXiYzKgZFonlCIv6Z/kPBM9FcncOC7hVV8KBH0OCVLv2Wu2Us6hq1oLItZn7rWrs7IlBTihs7ZQ/UNLc+PjTFjmXrWWyaNRRxDYLhpx2D3pUR1qQzhk5PweGs7zA7zlsF2pEY5Tgp2MeZEfXGpWPP4jHoEh0MXw8P+AY3QMdhb2BDoRNY8YGapix1YqBGRERUEp32h/27Nbo1ubJ6aG3p+u556brwvHw8QLsjh37XrEfk1Tb1ZfyOxjJl91aZUL/QmuxERERERDfpzl5MhOg2y90wVmIiGkr759PkkiMtX95Pm2TLAavoK9aVBmEM0oiIiIio/DBQI7oBU71oqfnz17Jx9vMyIfkbueRY7+DKiXXy98EvyKqLegnr+Rfp4GNPJyIiIiIqDwzUiG5AH9hP/vbKn6VG7pfyZq96UiUgSEKCK0lARCd5Ye1PUu3+SbJwWmcpYcFyIiIiIqKbwnvUyo1VvktfKCn7c6RWx6HyQJ2bWAud3FSenN+9XN57P1W2Hvhefr5qEv8a9aRF/F/kkZ4xUpVXPRIRERFROWOgRkRERERE5GZ46SMREREREZGbYaBGRERERETkZhioERERERERuRkGakRERERERG6GgRoREREREZGbYaBGRERERETkZhioERERERERuRkGakRERERERG6GgRoREREREZGbYaBGRERERETkZhioERERERERuRkGakRERERERG6GgRoREREREZGbYaBGRERERETkZhioERERERERuRkGakRERERERG6GgRoREREREZGbYaBGRERERETkZhioERERERERuRkGakRERERERG6GgRoREREREZGbYaBGRERERETkZhioERERERERuRkGakRERERERG6GgRoREREREZGbYaBGRERERETkZhioERERERERuRkGakRERERERG6GgRoREREREZGbYaBGRERERETkZhioERERERERuRkGakRERERERG6GgRoREREREZGbYaBGRERERETkZhioERERERERuRkGakRERERERG6GgRoREREREZGbYaBGRERERETkZhioERERERERuRkGakRERERERG6GgRoREREREZGbYaBGRERERETkVkT+D/djNEn+UhxiAAAAAElFTkSuQmCC"}}},{"cell_type":"code","source":"def read_record(record_id, directory):\n    \"\"\"\n    The function read_record reads and loads specified data files\n    in .npy format from a given directory into a dictionary, \n    ignoring any read errors.\n    Bands:\n        - \"band_11\" = \"Cloud-Top Phase\" Band\n        - \"band_14\" = IR Longwave Window Band\n        - \"band_15\" = \"Dirty\" Longwave Window Band\n    \"\"\"\n    record_data = {}\n    for x in [\n        \"band_11\", \n        \"band_14\", \n        \"band_15\", \n        \"human_pixel_masks\", \n        \"human_individual_masks\"\n    ]:\n        try:\n            with open(os.path.join(directory, record_id, x + \".npy\"), 'rb') as f:\n                record_data[x] = np.load(f)\n        except Exception as e:\n            pass\n    \n    return record_data\n\n\ndef normalize_range(data, bounds):\n    \"\"\"\n    The function normalizes data [0, 1].\n    \"\"\"\n    return (data - bounds[0]) / (bounds[1] - bounds[0])\n\n\ndef get_false_color(record_data):\n    \"\"\"\n    The function get_false_color generates a false color image by \n    normalizing and combining thermal bands from satellite data to\n    enhance visual interpretation of temperature differences.\n    \"\"\"\n    _T11_BOUNDS = (243, 303)\n    _CLOUD_TOP_TDIFF_BOUNDS = (-4, 5)\n    _TDIFF_BOUNDS = (-4, 2)\n    \n    N_TIMES_BEFORE = 4\n\n    r = normalize_range(record_data[\"band_15\"][..., N_TIMES_BEFORE] - record_data[\"band_14\"][..., N_TIMES_BEFORE], _TDIFF_BOUNDS)\n    g = normalize_range(record_data[\"band_14\"][..., N_TIMES_BEFORE] - record_data[\"band_11\"][..., N_TIMES_BEFORE], _CLOUD_TOP_TDIFF_BOUNDS)\n    b = normalize_range(record_data[\"band_14\"][..., N_TIMES_BEFORE], _T11_BOUNDS)\n    false_color = np.clip(np.stack([r, g, b], axis=2), 0, 1)\n    \n    return false_color","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-11-19T16:35:15.473354Z","iopub.execute_input":"2024-11-19T16:35:15.473902Z","iopub.status.idle":"2024-11-19T16:35:15.482599Z","shell.execute_reply.started":"2024-11-19T16:35:15.473877Z","shell.execute_reply":"2024-11-19T16:35:15.481831Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"def get_record_and_target(sample_record_ids, path):\n    target_array_list = []    \n    record_array_list = []\n    for record_id in sample_record_ids:\n        target_path = os.path.join(path, record_id, \"human_pixel_masks.npy\")\n        target = np.load(open(target_path, 'rb'))\n    \n        if target.sum() == 0:\n            continue\n        else:\n            record_data = read_record(record_id, path)\n            false_color = get_false_color(record_data)\n                \n            target_array_list.append(record_data[\"human_pixel_masks\"])\n            record_array_list.append(false_color)\n            \n    x = np.stack(record_array_list, axis=0)\n    y = np.stack(target_array_list, axis=0).astype(float)\n\n    return [x,y]\n\n[x_train, y_train] = get_record_and_target(get_record_ids(CFG.train_path, 5000), CFG.train_path)\n[x_val, y_val] = get_record_and_target(get_record_ids(CFG.validation_path, 1000), CFG.validation_path)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-11-19T16:35:16.751166Z","iopub.execute_input":"2024-11-19T16:35:16.751501Z","iopub.status.idle":"2024-11-19T16:39:45.440569Z","shell.execute_reply.started":"2024-11-19T16:35:16.75147Z","shell.execute_reply":"2024-11-19T16:39:45.439591Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"# checking all shapes\nprint(\"x_train shape is:\", x_train.shape)\nprint(\"y_train shape is:\", y_train.shape)\nprint(\"X_val shape is:\", x_val.shape)\nprint(\"y_val shape is:\", y_val.shape)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-11-19T16:39:45.44229Z","iopub.execute_input":"2024-11-19T16:39:45.443011Z","iopub.status.idle":"2024-11-19T16:39:45.448345Z","shell.execute_reply.started":"2024-11-19T16:39:45.44297Z","shell.execute_reply":"2024-11-19T16:39:45.447392Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"def plot_example(index):\n    image_test = x_train[index]\n    target_test = y_train[index]\n    \n    plt.figure(figsize=(18, 6))\n    ax = plt.subplot(1, 3, 1)\n    ax.imshow(image_test);\n    ax.set_title('False color image')\n    \n    ax = plt.subplot(1, 3, 2)\n    ax.imshow(target_test, interpolation='none');\n    ax.set_title('Ground truth')\n    \n    ax = plt.subplot(1, 3, 3)\n    ax.imshow(image_test)\n    ax.imshow(target_test, cmap='Reds', alpha=.4, interpolation='none')\n    ax.set_title('Contrail mask on false color image');\n    \n    print(\"Number of contrail pixel: \", target_test.sum())\n\nplot_example(15)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-11-19T16:40:04.661287Z","iopub.execute_input":"2024-11-19T16:40:04.661639Z","iopub.status.idle":"2024-11-19T16:40:05.511177Z","shell.execute_reply.started":"2024-11-19T16:40:04.661597Z","shell.execute_reply":"2024-11-19T16:40:05.510362Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"![image.png](attachment:e7c7c34a-45d1-4bdc-a674-ff5506149006.png)","metadata":{},"attachments":{"e7c7c34a-45d1-4bdc-a674-ff5506149006.png":{"image/png":"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"}}},{"cell_type":"code","source":"def proba_to_pixel(y):\n    return tf.where(y > 0.5, tf.ones_like(y), tf.zeros_like(y))\n\ndef dice_metric(y_true, y_pred):\n        y_pred = proba_to_pixel(y_pred)\n        y_true = proba_to_pixel(y_true)\n\n        y_true_sum = tf.reduce_sum(y_true)\n        y_pred_sum = tf.reduce_sum(y_pred)\n\n        intersection = tf.reduce_sum(y_true * y_pred)\n        union = y_true_sum + y_pred_sum\n\n        # define epsilon to prevent division by zero\n        smooth = 1e-5 \n    \n        dice = (2. * intersection + smooth) / (union + smooth)\n\n        return dice\n    \ndef precision(y_true, y_pred):\n    y_pred = proba_to_pixel(y_pred)\n    \n    true_positives = K.sum(K.round(K.clip(y_true * y_pred, 0, 1)))\n    predicted_positives = K.sum(K.round(K.clip(y_pred, 0, 1)))\n\n    precision = true_positives / (predicted_positives + K.epsilon())\n    \n    return precision\n\ndef recall(y_true, y_pred):\n    \n    y_pred = proba_to_pixel(y_pred)\n    \n    true_positives = K.sum(K.round(K.clip(y_true * y_pred, 0, 1)))\n    possible_positives = K.sum(K.round(K.clip(y_true, 0, 1)))\n    \n    recall = true_positives / (possible_positives + K.epsilon())\n    \n    return recall\n\ndef dice_loss(y_true, y_pred):\n    # define epsilon to prevent division by zero\n    smooth = 1e-5 \n\n    y_true_sum = tf.reduce_sum(y_true)\n    y_pred_sum = tf.reduce_sum(y_pred)\n\n    intersection = tf.reduce_sum(y_true * y_pred)\n    union = y_true_sum + y_pred_sum\n\n    dice = (2. * intersection + smooth) / (union + smooth)\n\n    return 1 - dice\n\ndef bce_dice_loss(y_true, y_pred):\n    bce = tf.keras.losses.BinaryCrossentropy()(y_true, y_pred)\n    dice = dice_loss(y_true, y_pred)\n    \n    return bce + dice","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-11-19T16:40:13.309167Z","iopub.execute_input":"2024-11-19T16:40:13.309499Z","iopub.status.idle":"2024-11-19T16:40:13.318565Z","shell.execute_reply.started":"2024-11-19T16:40:13.309469Z","shell.execute_reply":"2024-11-19T16:40:13.317675Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"\"\"\"\nŞUAN GEREK YOK ilerleyen süreçte denenecek\n\"\"\"\n\ndatagen = ImageDataGenerator(\n    rotation_range=20,\n    width_shift_range=0.1,\n    height_shift_range=0.1,\n    horizontal_flip=True,\n    vertical_flip=True,\n    zoom_range=0.2\n)\n\ndatagen.fit(x_train)","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"## Models\n### UNET","metadata":{}},{"cell_type":"code","source":"def build_model(input_layer, start_neurons):\n    # Encoder\n    conv1 = layers.Conv2D(start_neurons * 1, (3, 3), activation=\"relu\", padding=\"same\")(input_layer)\n    conv1 = layers.BatchNormalization()(conv1)\n    conv1 = layers.Conv2D(start_neurons * 1, (3, 3), activation=\"relu\", padding=\"same\")(conv1)\n    conv1 = layers.BatchNormalization()(conv1)\n    pool1 = layers.MaxPooling2D((2, 2))(conv1)\n    pool1 = layers.SpatialDropout2D(0.25)(pool1)\n\n    conv2 = layers.Conv2D(start_neurons * 2, (3, 3), activation=\"relu\", padding=\"same\")(pool1)\n    conv2 = layers.BatchNormalization()(conv2)\n    conv2 = layers.Conv2D(start_neurons * 2, (3, 3), activation=\"relu\", padding=\"same\")(conv2)\n    conv2 = layers.BatchNormalization()(conv2)\n    pool2 = layers.MaxPooling2D((2, 2))(conv2)\n    pool2 = layers.SpatialDropout2D(0.5)(pool2)\n\n    conv3 = layers.Conv2D(start_neurons * 4, (3, 3), activation=\"relu\", padding=\"same\")(pool2)\n    conv3 = layers.BatchNormalization()(conv3)\n    conv3 = layers.Conv2D(start_neurons * 4, (3, 3), activation=\"relu\", padding=\"same\")(conv3)\n    conv3 = layers.BatchNormalization()(conv3)\n    pool3 = layers.MaxPooling2D((2, 2))(conv3)\n    pool3 = layers.SpatialDropout2D(0.5)(pool3)\n\n    conv4 = layers.Conv2D(start_neurons * 8, (3, 3), activation=\"relu\", padding=\"same\")(pool3)\n    conv4 = layers.BatchNormalization()(conv4)\n    conv4 = layers.Conv2D(start_neurons * 8, (3, 3), activation=\"relu\", padding=\"same\")(conv4)\n    conv4 = layers.BatchNormalization()(conv4)\n    pool4 = layers.MaxPooling2D((2, 2))(conv4)\n    pool4 = layers.SpatialDropout2D(0.5)(pool4)\n\n    # Bottleneck\n    convm = layers.Conv2D(start_neurons * 16, (3, 3), activation=\"relu\", padding=\"same\")(pool4)\n    convm = layers.BatchNormalization()(convm)\n    convm = layers.Conv2D(start_neurons * 16, (3, 3), activation=\"relu\", padding=\"same\")(convm)\n    convm = layers.BatchNormalization()(convm)\n\n    # Decoder\n    deconv4 = layers.Conv2DTranspose(start_neurons * 8, (3, 3), strides=(2, 2), padding=\"same\")(convm)\n    uconv4 = layers.concatenate([deconv4, conv4])\n    uconv4 = layers.SpatialDropout2D(0.5)(uconv4)\n    uconv4 = layers.Conv2D(start_neurons * 8, (3, 3), activation=\"relu\", padding=\"same\")(uconv4)\n    uconv4 = layers.BatchNormalization()(uconv4)\n    uconv4 = layers.Conv2D(start_neurons * 8, (3, 3), activation=\"relu\", padding=\"same\")(uconv4)\n    uconv4 = layers.BatchNormalization()(uconv4)\n\n    deconv3 = layers.Conv2DTranspose(start_neurons * 4, (3, 3), strides=(2, 2), padding=\"same\")(uconv4)\n    uconv3 = layers.concatenate([deconv3, conv3])\n    uconv3 = layers.SpatialDropout2D(0.5)(uconv3)\n    uconv3 = layers.Conv2D(start_neurons * 4, (3, 3), activation=\"relu\", padding=\"same\")(uconv3)\n    uconv3 = layers.BatchNormalization()(uconv3)\n    uconv3 = layers.Conv2D(start_neurons * 4, (3, 3), activation=\"relu\", padding=\"same\")(uconv3)\n    uconv3 = layers.BatchNormalization()(uconv3)\n\n    deconv2 = layers.Conv2DTranspose(start_neurons * 2, (3, 3), strides=(2, 2), padding=\"same\")(uconv3)\n    uconv2 = layers.concatenate([deconv2, conv2])\n    uconv2 = layers.SpatialDropout2D(0.5)(uconv2)\n    uconv2 = layers.Conv2D(start_neurons * 2, (3, 3), activation=\"relu\", padding=\"same\")(uconv2)\n    uconv2 = layers.BatchNormalization()(uconv2)\n    uconv2 = layers.Conv2D(start_neurons * 2, (3, 3), activation=\"relu\", padding=\"same\")(uconv2)\n    uconv2 = layers.BatchNormalization()(uconv2)\n\n    deconv1 = layers.Conv2DTranspose(start_neurons * 1, (3, 3), strides=(2, 2), padding=\"same\")(uconv2)\n    uconv1 = layers.concatenate([deconv1, conv1])\n    uconv1 = layers.SpatialDropout2D(0.5)(uconv1)\n    uconv1 = layers.Conv2D(start_neurons * 1, (3, 3), activation=\"relu\", padding=\"same\")(uconv1)\n    uconv1 = layers.BatchNormalization()(uconv1)\n    uconv1 = layers.Conv2D(start_neurons * 1, (3, 3), activation=\"relu\", padding=\"same\")(uconv1)\n    uconv1 = layers.BatchNormalization()(uconv1)\n\n    output_layer = layers.Conv2D(1, (1, 1), padding=\"same\", activation=\"sigmoid\")(uconv1)\n\n    return output_layer","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-11-19T16:40:16.445643Z","iopub.execute_input":"2024-11-19T16:40:16.446124Z","iopub.status.idle":"2024-11-19T16:40:16.638814Z","shell.execute_reply.started":"2024-11-19T16:40:16.446091Z","shell.execute_reply":"2024-11-19T16:40:16.637965Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"def create_model(input_layer, start_neurons, optimizer, loss, metrics):\n    output_layer = build_model(input_layer, start_neurons)\n    model = tf.keras.Model(input_layer, output_layer)\n    \n    model.compile(optimizer=optimizer, \n                  loss=loss, \n                  metrics=metrics)\n    return model","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-11-19T16:40:17.094995Z","iopub.execute_input":"2024-11-19T16:40:17.09554Z","iopub.status.idle":"2024-11-19T16:40:17.099845Z","shell.execute_reply.started":"2024-11-19T16:40:17.095508Z","shell.execute_reply":"2024-11-19T16:40:17.098986Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"img_size_target = x_train.shape[1]\nnumber_channels_target = x_train.shape[-1]\nstart_neurons = 16\n\ninput_layer = layers.Input((img_size_target, img_size_target, number_channels_target))","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-11-19T16:40:17.600167Z","iopub.execute_input":"2024-11-19T16:40:17.600494Z","iopub.status.idle":"2024-11-19T16:40:17.607097Z","shell.execute_reply.started":"2024-11-19T16:40:17.600464Z","shell.execute_reply":"2024-11-19T16:40:17.606091Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"## LOSS = bce_dice_loss","metadata":{}},{"cell_type":"code","source":"optimizer = tf.keras.optimizers.Adam(\n    learning_rate=0.001,\n    beta_1=0.9,\n    beta_2=0.999,\n    epsilon=1e-07,\n    amsgrad=False,\n    weight_decay=None,\n    clipnorm=None,\n    clipvalue=None,\n    global_clipnorm=None,\n    use_ema=False,\n    ema_momentum=0.99,\n    ema_overwrite_frequency=None,\n    name='Adam'\n)\n\nunet_model = create_model(input_layer, start_neurons, optimizer, bce_dice_loss, [dice_metric])\nunet_model.summary()","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-11-19T16:40:19.139301Z","iopub.execute_input":"2024-11-19T16:40:19.140059Z","iopub.status.idle":"2024-11-19T16:40:20.316953Z","shell.execute_reply.started":"2024-11-19T16:40:19.140024Z","shell.execute_reply":"2024-11-19T16:40:20.31617Z"},"collapsed":true,"jupyter":{"outputs_hidden":true}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"import gc\ngc.collect()","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-11-19T18:20:20.52159Z","iopub.execute_input":"2024-11-19T18:20:20.522431Z","iopub.status.idle":"2024-11-19T18:20:20.870506Z","shell.execute_reply.started":"2024-11-19T18:20:20.522396Z","shell.execute_reply":"2024-11-19T18:20:20.869519Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"# Fitting\nes = callbacks.EarlyStopping(patience=30,\n                            restore_best_weights=True)\nlrp = callbacks.ReduceLROnPlateau(monitor='val_loss',\n                                  factor=0.2,\n                                  patience=5,\n                                  min_lr=0.0001)\ncheckpoint = callbacks.ModelCheckpoint('best_model.keras', save_best_only=True)\n\ntime_init = time.time()\nhistory_unet_model = unet_model.fit(x_train,\n                                    y_train,\n                                    batch_size=16,\n                                    epochs=100,\n                                    validation_data=(x_val,y_val),\n                                    callbacks=[es, lrp, checkpoint],\n                                    verbose=1)\ntime_finish = time.time()\nprint(\"Time:\", time_finish - time_init)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-11-19T16:40:28.624105Z","iopub.execute_input":"2024-11-19T16:40:28.624407Z","iopub.status.idle":"2024-11-19T17:18:32.309796Z","shell.execute_reply.started":"2024-11-19T16:40:28.624381Z","shell.execute_reply":"2024-11-19T17:18:32.308796Z"},"collapsed":true,"jupyter":{"outputs_hidden":true}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"def plot_history(history, title='', axs=None, exp_name=\"\"):\n    if axs is not None:\n        ax1, ax2 = axs\n    else:\n        f, (ax1, ax2) = plt.subplots(1, 2, figsize=(12, 4))\n    \n    if len(exp_name) > 0 and exp_name[0] != '_':\n        exp_name = '_' + exp_name\n    ax1.plot(history.history['loss'], label = 'train' + exp_name)\n    ax1.plot(history.history['val_loss'], label = 'val' + exp_name)\n    ax1.set_title('loss')\n    ax1.legend()\n\n    ax2.plot(history.history['dice_metric'], label='train dice metric'  + exp_name)\n    ax2.plot(history.history['val_dice_metric'], label='val dice metric'  + exp_name)\n    ax2.set_title('Dice metric')\n    ax2.legend()\n    return (ax1, ax2)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-11-19T17:18:39.094285Z","iopub.execute_input":"2024-11-19T17:18:39.094656Z","iopub.status.idle":"2024-11-19T17:18:39.101481Z","shell.execute_reply.started":"2024-11-19T17:18:39.0946Z","shell.execute_reply":"2024-11-19T17:18:39.100458Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"plot_history(history_unet_model)\nplt.show()","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-11-19T17:18:41.528494Z","iopub.execute_input":"2024-11-19T17:18:41.529163Z","iopub.status.idle":"2024-11-19T17:18:41.848266Z","shell.execute_reply.started":"2024-11-19T17:18:41.529125Z","shell.execute_reply":"2024-11-19T17:18:41.847436Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"# prediction\nindex = 35\nimage_test = np.expand_dims(x_train[index], axis=0)\npredicted_mask = unet_model.predict(image_test)\npredicted_mask = np.squeeze(predicted_mask, axis=0)\n\nimage_test = np.squeeze(image_test, axis=0)\nreal_mask = y_train[index]\n\n# Görselleştiriyoruz\nplt.figure(figsize=(10, 5))\n\n# Orijinal görüntü\nplt.subplot(1, 3, 1)\nplt.title(\"Orijinal Görüntü\")\nplt.imshow(image_test)\n\n# Gerçek maske\nplt.subplot(1, 3, 2)\nplt.title(\"Gerçek Maske\")\nplt.imshow(real_mask, cmap='gray')\n\n# Tahmin edilen maske\nplt.subplot(1, 3, 3)\nplt.title(\"Tahmin Edilen Maske\")\nplt.imshow(predicted_mask, cmap='gray')\n\nplt.show()","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-11-19T18:21:19.951591Z","iopub.execute_input":"2024-11-19T18:21:19.951967Z","iopub.status.idle":"2024-11-19T18:21:20.495976Z","shell.execute_reply.started":"2024-11-19T18:21:19.951937Z","shell.execute_reply":"2024-11-19T18:21:20.495101Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"from IPython.display import FileLink\nFileLink(\"best_model.keras\")","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-11-19T17:21:53.928777Z","iopub.execute_input":"2024-11-19T17:21:53.929113Z","iopub.status.idle":"2024-11-19T17:21:53.935097Z","shell.execute_reply.started":"2024-11-19T17:21:53.929083Z","shell.execute_reply":"2024-11-19T17:21:53.934241Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"history_unet_model.history['dice_metric'][-1]","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-11-19T17:24:19.000165Z","iopub.execute_input":"2024-11-19T17:24:19.000516Z","iopub.status.idle":"2024-11-19T17:24:19.006269Z","shell.execute_reply.started":"2024-11-19T17:24:19.000484Z","shell.execute_reply":"2024-11-19T17:24:19.005376Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"## LOSS = dice_loss","metadata":{}},{"cell_type":"code","source":"optimizer = tf.keras.optimizers.Adam(\n    learning_rate=0.001,\n    beta_1=0.9,\n    beta_2=0.999,\n    epsilon=1e-07,\n    amsgrad=False,\n    weight_decay=None,\n    clipnorm=None,\n    clipvalue=None,\n    global_clipnorm=None,\n    use_ema=False,\n    ema_momentum=0.99,\n    ema_overwrite_frequency=None,\n    name='Adam'\n)\n\nunet_model_2 = create_model(input_layer, start_neurons, optimizer, dice_loss, [dice_metric])\nunet_model_2.summary()","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-11-19T17:27:29.465024Z","iopub.execute_input":"2024-11-19T17:27:29.465772Z","iopub.status.idle":"2024-11-19T17:27:29.812432Z","shell.execute_reply.started":"2024-11-19T17:27:29.465729Z","shell.execute_reply":"2024-11-19T17:27:29.811644Z"},"collapsed":true,"jupyter":{"outputs_hidden":true}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"import gc\ngc.collect()","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-11-19T17:27:48.211176Z","iopub.execute_input":"2024-11-19T17:27:48.212241Z","iopub.status.idle":"2024-11-19T17:27:48.479965Z","shell.execute_reply.started":"2024-11-19T17:27:48.212202Z","shell.execute_reply":"2024-11-19T17:27:48.479037Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"%%time\n# Fitting\nes = callbacks.EarlyStopping(patience=30,\n                            restore_best_weights=True)\nlrp = callbacks.ReduceLROnPlateau(monitor='val_loss',\n                                  factor=0.2,\n                                  patience=5,\n                                  min_lr=0.0001)\ncheckpoint = callbacks.ModelCheckpoint('best_model.keras', save_best_only=True)\n\nhistory_unet_model = unet_model_2.fit(x_train,\n                                    y_train,\n                                    batch_size=16,\n                                    epochs=100,\n                                    validation_data=(x_val,y_val),\n                                    callbacks=[es, lrp, checkpoint],\n                                    verbose=1)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-11-19T17:29:32.119413Z","iopub.execute_input":"2024-11-19T17:29:32.120224Z","iopub.status.idle":"2024-11-19T18:07:07.461587Z","shell.execute_reply.started":"2024-11-19T17:29:32.12019Z","shell.execute_reply":"2024-11-19T18:07:07.460707Z"},"collapsed":true,"jupyter":{"outputs_hidden":true}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"plot_history(history_unet_model)\nplt.show()","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-11-19T18:11:37.235133Z","iopub.execute_input":"2024-11-19T18:11:37.235867Z","iopub.status.idle":"2024-11-19T18:11:37.642777Z","shell.execute_reply.started":"2024-11-19T18:11:37.235833Z","shell.execute_reply":"2024-11-19T18:11:37.64197Z"},"collapsed":true,"jupyter":{"outputs_hidden":true}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"# prediction\nindex = 13\nimage_test = np.expand_dims(x_train[index], axis=0)\npredicted_mask = unet_model.predict(image_test)\npredicted_mask = np.squeeze(predicted_mask, axis=0)\n\nimage_test = np.squeeze(image_test, axis=0)\nreal_mask = y_train[index]\n\n# Görselleştiriyoruz\nplt.figure(figsize=(10, 5))\n\n# Orijinal görüntü\nplt.subplot(1, 3, 1)\nplt.title(\"Orijinal Görüntü\")\nplt.imshow(image_test)\n\n# Gerçek maske\nplt.subplot(1, 3, 2)\nplt.title(\"Gerçek Maske\")\nplt.imshow(real_mask, cmap='gray')\n\n# Tahmin edilen maske\nplt.subplot(1, 3, 3)\nplt.title(\"Tahmin Edilen Maske\")\nplt.imshow(predicted_mask, cmap='gray')\n\nplt.show()","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-11-19T18:21:34.232323Z","iopub.execute_input":"2024-11-19T18:21:34.233003Z","iopub.status.idle":"2024-11-19T18:21:34.813848Z","shell.execute_reply.started":"2024-11-19T18:21:34.232967Z","shell.execute_reply":"2024-11-19T18:21:34.813046Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"history_unet_model.history['dice_metric'][-1]","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-11-19T18:12:39.076524Z","iopub.execute_input":"2024-11-19T18:12:39.077351Z","iopub.status.idle":"2024-11-19T18:12:39.082516Z","shell.execute_reply.started":"2024-11-19T18:12:39.077315Z","shell.execute_reply":"2024-11-19T18:12:39.08169Z"}},"outputs":[],"execution_count":null}]}